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deep_rl/agent/PPO_agent.py
pladosz/MOHQA
3
6632151
<gh_stars>1-10 ####################################################################### # Copyright (C) 2017 <NAME>(<EMAIL>) # # Permission given to modify the code as long as you keep this # # declaration at the top # ####################################################################### from ..network import * from ..component import * from .BaseAgent import * class PPOAgent_L2M_Mem(BaseAgent): def __init__(self, config): BaseAgent.__init__(self, config) self.config = config self.task = config.task_fn() self.network = config.network_fn(self.task.state_dim, self.task.action_dim) self.opt = config.optimizer_fn(self.network.parameters()) self.total_steps = 0 self.episode_rewards = np.zeros(config.num_workers) self.last_episode_rewards = np.zeros(config.num_workers) self.states = self.task.reset() self.states = config.state_normalizer(self.states) self.memory = self.task.reset() self.memory = config.state_normalizer(self.states) self.mem_update_rate = 0.1 def iteration(self): config = self.config rollout = [] states = self.states memory = self.memory for _ in range(config.rollout_length): actions, log_probs, _, values = self.network.predict(states,memory) next_states, rewards, terminals, _ = self.task.step(actions.cpu().detach().numpy()) memory = tensor((1-self.mem_update_rate)*memory+self.mem_update_rate*states) self.episode_rewards += rewards rewards = config.reward_normalizer(rewards) for i, terminal in enumerate(terminals): if terminals[i]: self.last_episode_rewards[i] = self.episode_rewards[i] self.episode_rewards[i] = 0 next_states = config.state_normalizer(next_states) memory = config.state_normalizer(memory) rollout.append([states, memory, values.detach(), actions.detach(), log_probs.detach(), rewards, 1 - terminals]) states = next_states self.states = states self.memory = memory pending_value = self.network.predict(states,memory)[-1] rollout.append([states, memory, pending_value, None, None, None, None]) processed_rollout = [None] * (len(rollout) - 1) advantages = tensor(np.zeros((config.num_workers, 1))) returns = pending_value.detach() for i in reversed(range(len(rollout) - 1)): states, memory, value, actions, log_probs, rewards, terminals = rollout[i] terminals = tensor(terminals).unsqueeze(1) rewards = tensor(rewards).unsqueeze(1) actions = tensor(actions) states = tensor(states) memory = tensor(memory) next_value = rollout[i + 1][2] returns = rewards + config.discount * terminals * returns if not config.use_gae: advantages = returns - value.detach() else: td_error = rewards + config.discount * terminals * next_value.detach() - value.detach() advantages = advantages * config.gae_tau * config.discount * terminals + td_error processed_rollout[i] = [states, memory, actions, log_probs, returns, advantages] states, memory, actions, log_probs_old, returns, advantages = map(lambda x: torch.cat(x, dim = 0), zip(*processed_rollout)) advantages = (advantages - advantages.mean()) / advantages.std() batcher = Batcher(states.size(0) // config.num_mini_batches, [np.arange(states.size(0))]) for _ in range(config.optimization_epochs): batcher.shuffle() while not batcher.end(): batch_indices = batcher.next_batch()[0] batch_indices = tensor(batch_indices).long() sampled_states = states[batch_indices] sampled_mem = memory[batch_indices] sampled_actions = actions[batch_indices] sampled_log_probs_old = log_probs_old[batch_indices] sampled_returns = returns[batch_indices] sampled_advantages = advantages[batch_indices] _, log_probs, entropy_loss, values = self.network.predict(sampled_states, sampled_mem, sampled_actions) ratio = (log_probs - sampled_log_probs_old).exp() obj = ratio * sampled_advantages obj_clipped = ratio.clamp(1.0 - self.config.ppo_ratio_clip, 1.0 + self.config.ppo_ratio_clip) * sampled_advantages policy_loss = -torch.min(obj, obj_clipped).mean(0) - config.entropy_weight * entropy_loss.mean() value_loss = 0.5 * (sampled_returns - values).pow(2).mean() self.opt.zero_grad() (policy_loss + value_loss).backward() nn.utils.clip_grad_norm_(self.network.parameters(), config.gradient_clip) self.opt.step() steps = config.rollout_length * config.num_workers self.total_steps += steps class PPOAgent(BaseAgent): def __init__(self, config): BaseAgent.__init__(self, config) self.config = config self.task = config.task_fn() self.network = config.network_fn(self.task.state_dim, self.task.action_dim) self.opt = config.optimizer_fn(self.network.parameters()) self.total_steps = 0 self.episode_rewards = np.zeros(config.num_workers) self.last_episode_rewards = np.zeros(config.num_workers) self.states = self.task.reset() self.states = config.state_normalizer(self.states) def iteration(self): config = self.config rollout = [] states = self.states for _ in range(config.rollout_length): actions, log_probs, _, values = self.network.predict(states) next_states, rewards, terminals, _ = self.task.step(actions.cpu().detach().numpy()) self.episode_rewards += rewards rewards = config.reward_normalizer(rewards) for i, terminal in enumerate(terminals): if terminals[i]: self.last_episode_rewards[i] = self.episode_rewards[i] self.episode_rewards[i] = 0 next_states = config.state_normalizer(next_states) rollout.append([states, values.detach(), actions.detach(), log_probs.detach(), rewards, 1 - terminals]) states = next_states self.states = states pending_value = self.network.predict(states)[-1] rollout.append([states, pending_value, None, None, None, None]) processed_rollout = [None] * (len(rollout) - 1) advantages = tensor(np.zeros((config.num_workers, 1))) returns = pending_value.detach() for i in reversed(range(len(rollout) - 1)): states, value, actions, log_probs, rewards, terminals = rollout[i] terminals = tensor(terminals).unsqueeze(1) rewards = tensor(rewards).unsqueeze(1) actions = tensor(actions) states = tensor(states) next_value = rollout[i + 1][1] returns = rewards + config.discount * terminals * returns if not config.use_gae: advantages = returns - value.detach() else: td_error = rewards + config.discount * terminals * next_value.detach() - value.detach() advantages = advantages * config.gae_tau * config.discount * terminals + td_error processed_rollout[i] = [states, actions, log_probs, returns, advantages] states, actions, log_probs_old, returns, advantages = map(lambda x: torch.cat(x, dim = 0), zip(*processed_rollout)) advantages = (advantages - advantages.mean()) / advantages.std() batcher = Batcher(states.size(0) // config.num_mini_batches, [np.arange(states.size(0))]) for _ in range(config.optimization_epochs): batcher.shuffle() while not batcher.end(): batch_indices = batcher.next_batch()[0] batch_indices = tensor(batch_indices).long() sampled_states = states[batch_indices] sampled_actions = actions[batch_indices] sampled_log_probs_old = log_probs_old[batch_indices] sampled_returns = returns[batch_indices] sampled_advantages = advantages[batch_indices] _, log_probs, entropy_loss, values = self.network.predict(sampled_states, sampled_actions) ratio = (log_probs - sampled_log_probs_old).exp() obj = ratio * sampled_advantages obj_clipped = ratio.clamp(1.0 - self.config.ppo_ratio_clip, 1.0 + self.config.ppo_ratio_clip) * sampled_advantages policy_loss = -torch.min(obj, obj_clipped).mean(0) - config.entropy_weight * entropy_loss.mean() value_loss = 0.5 * (sampled_returns - values).pow(2).mean() self.opt.zero_grad() (policy_loss + value_loss).backward() nn.utils.clip_grad_norm_(self.network.parameters(), config.gradient_clip) self.opt.step() steps = config.rollout_length * config.num_workers self.total_steps += steps
####################################################################### # Copyright (C) 2017 <NAME>(<EMAIL>) # # Permission given to modify the code as long as you keep this # # declaration at the top # ####################################################################### from ..network import * from ..component import * from .BaseAgent import * class PPOAgent_L2M_Mem(BaseAgent): def __init__(self, config): BaseAgent.__init__(self, config) self.config = config self.task = config.task_fn() self.network = config.network_fn(self.task.state_dim, self.task.action_dim) self.opt = config.optimizer_fn(self.network.parameters()) self.total_steps = 0 self.episode_rewards = np.zeros(config.num_workers) self.last_episode_rewards = np.zeros(config.num_workers) self.states = self.task.reset() self.states = config.state_normalizer(self.states) self.memory = self.task.reset() self.memory = config.state_normalizer(self.states) self.mem_update_rate = 0.1 def iteration(self): config = self.config rollout = [] states = self.states memory = self.memory for _ in range(config.rollout_length): actions, log_probs, _, values = self.network.predict(states,memory) next_states, rewards, terminals, _ = self.task.step(actions.cpu().detach().numpy()) memory = tensor((1-self.mem_update_rate)*memory+self.mem_update_rate*states) self.episode_rewards += rewards rewards = config.reward_normalizer(rewards) for i, terminal in enumerate(terminals): if terminals[i]: self.last_episode_rewards[i] = self.episode_rewards[i] self.episode_rewards[i] = 0 next_states = config.state_normalizer(next_states) memory = config.state_normalizer(memory) rollout.append([states, memory, values.detach(), actions.detach(), log_probs.detach(), rewards, 1 - terminals]) states = next_states self.states = states self.memory = memory pending_value = self.network.predict(states,memory)[-1] rollout.append([states, memory, pending_value, None, None, None, None]) processed_rollout = [None] * (len(rollout) - 1) advantages = tensor(np.zeros((config.num_workers, 1))) returns = pending_value.detach() for i in reversed(range(len(rollout) - 1)): states, memory, value, actions, log_probs, rewards, terminals = rollout[i] terminals = tensor(terminals).unsqueeze(1) rewards = tensor(rewards).unsqueeze(1) actions = tensor(actions) states = tensor(states) memory = tensor(memory) next_value = rollout[i + 1][2] returns = rewards + config.discount * terminals * returns if not config.use_gae: advantages = returns - value.detach() else: td_error = rewards + config.discount * terminals * next_value.detach() - value.detach() advantages = advantages * config.gae_tau * config.discount * terminals + td_error processed_rollout[i] = [states, memory, actions, log_probs, returns, advantages] states, memory, actions, log_probs_old, returns, advantages = map(lambda x: torch.cat(x, dim = 0), zip(*processed_rollout)) advantages = (advantages - advantages.mean()) / advantages.std() batcher = Batcher(states.size(0) // config.num_mini_batches, [np.arange(states.size(0))]) for _ in range(config.optimization_epochs): batcher.shuffle() while not batcher.end(): batch_indices = batcher.next_batch()[0] batch_indices = tensor(batch_indices).long() sampled_states = states[batch_indices] sampled_mem = memory[batch_indices] sampled_actions = actions[batch_indices] sampled_log_probs_old = log_probs_old[batch_indices] sampled_returns = returns[batch_indices] sampled_advantages = advantages[batch_indices] _, log_probs, entropy_loss, values = self.network.predict(sampled_states, sampled_mem, sampled_actions) ratio = (log_probs - sampled_log_probs_old).exp() obj = ratio * sampled_advantages obj_clipped = ratio.clamp(1.0 - self.config.ppo_ratio_clip, 1.0 + self.config.ppo_ratio_clip) * sampled_advantages policy_loss = -torch.min(obj, obj_clipped).mean(0) - config.entropy_weight * entropy_loss.mean() value_loss = 0.5 * (sampled_returns - values).pow(2).mean() self.opt.zero_grad() (policy_loss + value_loss).backward() nn.utils.clip_grad_norm_(self.network.parameters(), config.gradient_clip) self.opt.step() steps = config.rollout_length * config.num_workers self.total_steps += steps class PPOAgent(BaseAgent): def __init__(self, config): BaseAgent.__init__(self, config) self.config = config self.task = config.task_fn() self.network = config.network_fn(self.task.state_dim, self.task.action_dim) self.opt = config.optimizer_fn(self.network.parameters()) self.total_steps = 0 self.episode_rewards = np.zeros(config.num_workers) self.last_episode_rewards = np.zeros(config.num_workers) self.states = self.task.reset() self.states = config.state_normalizer(self.states) def iteration(self): config = self.config rollout = [] states = self.states for _ in range(config.rollout_length): actions, log_probs, _, values = self.network.predict(states) next_states, rewards, terminals, _ = self.task.step(actions.cpu().detach().numpy()) self.episode_rewards += rewards rewards = config.reward_normalizer(rewards) for i, terminal in enumerate(terminals): if terminals[i]: self.last_episode_rewards[i] = self.episode_rewards[i] self.episode_rewards[i] = 0 next_states = config.state_normalizer(next_states) rollout.append([states, values.detach(), actions.detach(), log_probs.detach(), rewards, 1 - terminals]) states = next_states self.states = states pending_value = self.network.predict(states)[-1] rollout.append([states, pending_value, None, None, None, None]) processed_rollout = [None] * (len(rollout) - 1) advantages = tensor(np.zeros((config.num_workers, 1))) returns = pending_value.detach() for i in reversed(range(len(rollout) - 1)): states, value, actions, log_probs, rewards, terminals = rollout[i] terminals = tensor(terminals).unsqueeze(1) rewards = tensor(rewards).unsqueeze(1) actions = tensor(actions) states = tensor(states) next_value = rollout[i + 1][1] returns = rewards + config.discount * terminals * returns if not config.use_gae: advantages = returns - value.detach() else: td_error = rewards + config.discount * terminals * next_value.detach() - value.detach() advantages = advantages * config.gae_tau * config.discount * terminals + td_error processed_rollout[i] = [states, actions, log_probs, returns, advantages] states, actions, log_probs_old, returns, advantages = map(lambda x: torch.cat(x, dim = 0), zip(*processed_rollout)) advantages = (advantages - advantages.mean()) / advantages.std() batcher = Batcher(states.size(0) // config.num_mini_batches, [np.arange(states.size(0))]) for _ in range(config.optimization_epochs): batcher.shuffle() while not batcher.end(): batch_indices = batcher.next_batch()[0] batch_indices = tensor(batch_indices).long() sampled_states = states[batch_indices] sampled_actions = actions[batch_indices] sampled_log_probs_old = log_probs_old[batch_indices] sampled_returns = returns[batch_indices] sampled_advantages = advantages[batch_indices] _, log_probs, entropy_loss, values = self.network.predict(sampled_states, sampled_actions) ratio = (log_probs - sampled_log_probs_old).exp() obj = ratio * sampled_advantages obj_clipped = ratio.clamp(1.0 - self.config.ppo_ratio_clip, 1.0 + self.config.ppo_ratio_clip) * sampled_advantages policy_loss = -torch.min(obj, obj_clipped).mean(0) - config.entropy_weight * entropy_loss.mean() value_loss = 0.5 * (sampled_returns - values).pow(2).mean() self.opt.zero_grad() (policy_loss + value_loss).backward() nn.utils.clip_grad_norm_(self.network.parameters(), config.gradient_clip) self.opt.step() steps = config.rollout_length * config.num_workers self.total_steps += steps
de
0.543062
####################################################################### # Copyright (C) 2017 <NAME>(<EMAIL>) # # Permission given to modify the code as long as you keep this # # declaration at the top # #######################################################################
1.975337
2
setup.py
cbrentharris/bricklayer
0
6632152
#!/usr/bin/env python from setuptools import setup, find_packages setup(name='Bricklayer', version='1.0', description='Lego Digital Designer Education Tool', author='<NAME>', author_email='<EMAIL>', url='https://bitbucket.org/pbergero/deep-impac', packages=find_packages(), entry_points = { 'console_scripts' : [ 'bricklayer = bricklayer:main' ] }, test_suite='nose.collector', tests_require=['nose'], include_package_data=True, )
#!/usr/bin/env python from setuptools import setup, find_packages setup(name='Bricklayer', version='1.0', description='Lego Digital Designer Education Tool', author='<NAME>', author_email='<EMAIL>', url='https://bitbucket.org/pbergero/deep-impac', packages=find_packages(), entry_points = { 'console_scripts' : [ 'bricklayer = bricklayer:main' ] }, test_suite='nose.collector', tests_require=['nose'], include_package_data=True, )
ru
0.26433
#!/usr/bin/env python
1.306247
1
api/files/api/app/generate_csv.py
trackit/trackit-legacy
2
6632153
import csv import StringIO def _get_cost(rgg, name, tag_name, sub_header_name, tagged): for rg in rgg: if rg[sub_header_name].lower() == name: if not tagged: return rg['cost'] else: for tagl in rg['tags']: if tagl['name'] == tag_name: return tagl['cost'] return 0 def _process(splitted_res, header_column, header_name, sub_header_name, tagged, available_tag, account): fsplitted_res = splitted_res['months'] if account else splitted_res for r in fsplitted_res: if tagged: for atag in available_tag: gen = [_get_cost(r[header_name], p, atag, sub_header_name, tagged) for p in header_column] if sum(gen): yield '{}{},{}{},{}\n'.format( '{},{},'.format(splitted_res['account_name'], splitted_res['account_id']) if account else '', r['month'], str(sum(gen)), ',{}'.format(atag) if tagged else '', ','.join(str(g) for g in gen)) else: gen = [_get_cost(r[header_name], p, None, sub_header_name, tagged) for p in header_column] yield '{}{},{},{}\n'.format( '{},{},'.format(splitted_res['account_name'], splitted_res['account_id']) if account else '', r['month'], str(sum(gen)), ','.join(str(g) for g in gen)) def generate_csv_clean(data, header_name): si = StringIO.StringIO() writer = csv.DictWriter(si, header_name) writer.writeheader() for row in data: writer.writerow(row) return si.getvalue() def generate_csv(data, header_name, sub_header_name, account=False, tagged=False): header_column = set( hc[sub_header_name].lower() for r in data for hc in r[header_name] ) if not account else set( hc[sub_header_name].lower() for p in data for r in p['months'] for hc in r[header_name] ) available_tag = set( t['name'] for p in data for r in p['months'] for hc in r[header_name] for t in hc['tags'] ) if tagged else None yield '{}month,total{},{}\n'.format('account_name,account_id,' if account else '', ',tag' if tagged else '', ','.join(header_column)) if account: for splitted_res in data: for p in _process(splitted_res, header_column, header_name, sub_header_name, tagged, available_tag, account): yield p else: for p in _process(data, header_column, header_name, sub_header_name, tagged, available_tag, account): yield p def get_csv_links(): res = [ { 'name': 'Monthly Cost By Region', 'link': 'monthlycostbyregion', }, { 'name': 'Monthly Cost By Region By Account', 'link': 'monthlycostbyregionbyaccount', }, { 'name': 'Monthly Cost By Region By Tag By Account', 'link': 'monthlycostbyregionbytagbyaccount', }, { 'name': 'Monthly Cost By Product', 'link': 'monthlycostbyproduct', }, { 'name': 'Monthly Cost By Product By Account', 'link': 'monthlycostbyproductbyaccount', }, { 'name': 'Monthly Cost By Product By Tag By Account', 'link': 'monthlycostbyproductbytagbyaccount', }, { 'name': 'Sizes of S3 buckets per name', 'link': 's3bucketsizepername', }, { 'name': 'Sizes of S3 buckets per tag', 'link': 's3bucketsizepertag' } ] return sorted(res, key=lambda x: x['name'])
import csv import StringIO def _get_cost(rgg, name, tag_name, sub_header_name, tagged): for rg in rgg: if rg[sub_header_name].lower() == name: if not tagged: return rg['cost'] else: for tagl in rg['tags']: if tagl['name'] == tag_name: return tagl['cost'] return 0 def _process(splitted_res, header_column, header_name, sub_header_name, tagged, available_tag, account): fsplitted_res = splitted_res['months'] if account else splitted_res for r in fsplitted_res: if tagged: for atag in available_tag: gen = [_get_cost(r[header_name], p, atag, sub_header_name, tagged) for p in header_column] if sum(gen): yield '{}{},{}{},{}\n'.format( '{},{},'.format(splitted_res['account_name'], splitted_res['account_id']) if account else '', r['month'], str(sum(gen)), ',{}'.format(atag) if tagged else '', ','.join(str(g) for g in gen)) else: gen = [_get_cost(r[header_name], p, None, sub_header_name, tagged) for p in header_column] yield '{}{},{},{}\n'.format( '{},{},'.format(splitted_res['account_name'], splitted_res['account_id']) if account else '', r['month'], str(sum(gen)), ','.join(str(g) for g in gen)) def generate_csv_clean(data, header_name): si = StringIO.StringIO() writer = csv.DictWriter(si, header_name) writer.writeheader() for row in data: writer.writerow(row) return si.getvalue() def generate_csv(data, header_name, sub_header_name, account=False, tagged=False): header_column = set( hc[sub_header_name].lower() for r in data for hc in r[header_name] ) if not account else set( hc[sub_header_name].lower() for p in data for r in p['months'] for hc in r[header_name] ) available_tag = set( t['name'] for p in data for r in p['months'] for hc in r[header_name] for t in hc['tags'] ) if tagged else None yield '{}month,total{},{}\n'.format('account_name,account_id,' if account else '', ',tag' if tagged else '', ','.join(header_column)) if account: for splitted_res in data: for p in _process(splitted_res, header_column, header_name, sub_header_name, tagged, available_tag, account): yield p else: for p in _process(data, header_column, header_name, sub_header_name, tagged, available_tag, account): yield p def get_csv_links(): res = [ { 'name': 'Monthly Cost By Region', 'link': 'monthlycostbyregion', }, { 'name': 'Monthly Cost By Region By Account', 'link': 'monthlycostbyregionbyaccount', }, { 'name': 'Monthly Cost By Region By Tag By Account', 'link': 'monthlycostbyregionbytagbyaccount', }, { 'name': 'Monthly Cost By Product', 'link': 'monthlycostbyproduct', }, { 'name': 'Monthly Cost By Product By Account', 'link': 'monthlycostbyproductbyaccount', }, { 'name': 'Monthly Cost By Product By Tag By Account', 'link': 'monthlycostbyproductbytagbyaccount', }, { 'name': 'Sizes of S3 buckets per name', 'link': 's3bucketsizepername', }, { 'name': 'Sizes of S3 buckets per tag', 'link': 's3bucketsizepertag' } ] return sorted(res, key=lambda x: x['name'])
none
1
2.907984
3
models/sphere_net_PFE.py
DorisWZG/Probabilistic-Face-Embeddings
1
6632154
<filename>models/sphere_net_PFE.py from __future__ import absolute_import from __future__ import division from __future__ import print_function import math import tensorflow as tf import tensorflow.contrib.slim as slim model_params = { '4': ([0, 0, 0, 0], [64, 128, 256, 512]), '10': ([0, 1, 2, 0], [64, 128, 256, 512]), '20': ([1, 2, 4, 1], [64, 128, 256, 512]), '36': ([2, 4, 8, 2], [64, 128, 256, 512]), '64': ([3, 8, 16, 3], [64, 128, 256, 512]), } batch_norm_params_last = { 'decay': 0.995, 'epsilon': 0.001, 'center': True, 'scale': False, 'updates_collections': None, 'variables_collections': [ tf.GraphKeys.TRAINABLE_VARIABLES ], } def parametric_relu(x): num_channels = x.shape[-1].value with tf.variable_scope('p_re_lu'): alpha = tf.get_variable('alpha', (1,1,num_channels), initializer=tf.constant_initializer(0.0), dtype=tf.float32) return tf.nn.relu(x) + alpha * tf.minimum(0.0, x) def se_module(input_net, ratio=16, reuse = None, scope = None): with tf.variable_scope(scope, 'SE', [input_net], reuse=reuse): h,w,c = tuple([dim.value for dim in input_net.shape[1:4]]) assert c % ratio == 0 hidden_units = int(c / ratio) squeeze = slim.avg_pool2d(input_net, [h,w], padding='VALID') excitation = slim.flatten(squeeze) excitation = slim.fully_connected(excitation, hidden_units, scope='se_fc1', weights_regularizer=None, weights_initializer=slim.xavier_initializer(), activation_fn=tf.nn.relu) excitation = slim.fully_connected(excitation, c, scope='se_fc2', weights_regularizer=None, weights_initializer=slim.xavier_initializer(), activation_fn=tf.nn.sigmoid) excitation = tf.reshape(excitation, [-1,1,1,c]) output_net = input_net * excitation return output_net def conv_module(net, num_res_layers, num_kernels, trans_kernel_size=3, trans_stride=2, use_se=False, reuse=None, scope=None): with tf.variable_scope(scope, 'conv', [net], reuse=reuse): net = slim.conv2d(net, num_kernels, kernel_size=trans_kernel_size, stride=trans_stride, padding='SAME', weights_initializer=slim.xavier_initializer()) shortcut = net for i in range(num_res_layers): net = slim.conv2d(net, num_kernels, kernel_size=3, stride=1, padding='SAME', weights_initializer=tf.truncated_normal_initializer(stddev=0.01), biases_initializer=None) net = slim.conv2d(net, num_kernels, kernel_size=3, stride=1, padding='SAME', weights_initializer=tf.truncated_normal_initializer(stddev=0.01), biases_initializer=None) print('| ---- block_%d' % i) if use_se: net = se_module(net) net = net + shortcut shortcut = net return net def inference(images, embedding_size=512, reuse=None, scope='SphereNet'): with slim.arg_scope([slim.conv2d, slim.fully_connected], weights_regularizer=slim.l2_regularizer(0.0), normalizer_fn=None, normalizer_params=None, activation_fn=parametric_relu): with tf.variable_scope('SphereNet', [images], reuse=reuse): # Fix the moving mean and std when training PFE with slim.arg_scope([slim.batch_norm, slim.dropout], is_training=False): print('SphereNet input shape:', [dim.value for dim in images.shape]) model_version = '64' num_layers, num_kernels = model_params[model_version] net = conv_module(images, num_layers[0], num_kernels[0], scope='conv1') print('module_1 shape:', [dim.value for dim in net.shape]) net = conv_module(net, num_layers[1], num_kernels[1], scope='conv2') print('module_2 shape:', [dim.value for dim in net.shape]) net = conv_module(net, num_layers[2], num_kernels[2], scope='conv3') print('module_3 shape:', [dim.value for dim in net.shape]) net = conv_module(net, num_layers[3], num_kernels[3], scope='conv4') print('module_4 shape:', [dim.value for dim in net.shape]) net_ = net net = slim.flatten(net) prelogits = slim.fully_connected(net, embedding_size, scope='Bottleneck', weights_initializer=slim.xavier_initializer(), normalizer_fn=slim.batch_norm, normalizer_params=batch_norm_params_last, activation_fn=None) # Output used for PFE mu = tf.nn.l2_normalize(prelogits, axis=1) conv_final = net return mu, conv_final
<filename>models/sphere_net_PFE.py from __future__ import absolute_import from __future__ import division from __future__ import print_function import math import tensorflow as tf import tensorflow.contrib.slim as slim model_params = { '4': ([0, 0, 0, 0], [64, 128, 256, 512]), '10': ([0, 1, 2, 0], [64, 128, 256, 512]), '20': ([1, 2, 4, 1], [64, 128, 256, 512]), '36': ([2, 4, 8, 2], [64, 128, 256, 512]), '64': ([3, 8, 16, 3], [64, 128, 256, 512]), } batch_norm_params_last = { 'decay': 0.995, 'epsilon': 0.001, 'center': True, 'scale': False, 'updates_collections': None, 'variables_collections': [ tf.GraphKeys.TRAINABLE_VARIABLES ], } def parametric_relu(x): num_channels = x.shape[-1].value with tf.variable_scope('p_re_lu'): alpha = tf.get_variable('alpha', (1,1,num_channels), initializer=tf.constant_initializer(0.0), dtype=tf.float32) return tf.nn.relu(x) + alpha * tf.minimum(0.0, x) def se_module(input_net, ratio=16, reuse = None, scope = None): with tf.variable_scope(scope, 'SE', [input_net], reuse=reuse): h,w,c = tuple([dim.value for dim in input_net.shape[1:4]]) assert c % ratio == 0 hidden_units = int(c / ratio) squeeze = slim.avg_pool2d(input_net, [h,w], padding='VALID') excitation = slim.flatten(squeeze) excitation = slim.fully_connected(excitation, hidden_units, scope='se_fc1', weights_regularizer=None, weights_initializer=slim.xavier_initializer(), activation_fn=tf.nn.relu) excitation = slim.fully_connected(excitation, c, scope='se_fc2', weights_regularizer=None, weights_initializer=slim.xavier_initializer(), activation_fn=tf.nn.sigmoid) excitation = tf.reshape(excitation, [-1,1,1,c]) output_net = input_net * excitation return output_net def conv_module(net, num_res_layers, num_kernels, trans_kernel_size=3, trans_stride=2, use_se=False, reuse=None, scope=None): with tf.variable_scope(scope, 'conv', [net], reuse=reuse): net = slim.conv2d(net, num_kernels, kernel_size=trans_kernel_size, stride=trans_stride, padding='SAME', weights_initializer=slim.xavier_initializer()) shortcut = net for i in range(num_res_layers): net = slim.conv2d(net, num_kernels, kernel_size=3, stride=1, padding='SAME', weights_initializer=tf.truncated_normal_initializer(stddev=0.01), biases_initializer=None) net = slim.conv2d(net, num_kernels, kernel_size=3, stride=1, padding='SAME', weights_initializer=tf.truncated_normal_initializer(stddev=0.01), biases_initializer=None) print('| ---- block_%d' % i) if use_se: net = se_module(net) net = net + shortcut shortcut = net return net def inference(images, embedding_size=512, reuse=None, scope='SphereNet'): with slim.arg_scope([slim.conv2d, slim.fully_connected], weights_regularizer=slim.l2_regularizer(0.0), normalizer_fn=None, normalizer_params=None, activation_fn=parametric_relu): with tf.variable_scope('SphereNet', [images], reuse=reuse): # Fix the moving mean and std when training PFE with slim.arg_scope([slim.batch_norm, slim.dropout], is_training=False): print('SphereNet input shape:', [dim.value for dim in images.shape]) model_version = '64' num_layers, num_kernels = model_params[model_version] net = conv_module(images, num_layers[0], num_kernels[0], scope='conv1') print('module_1 shape:', [dim.value for dim in net.shape]) net = conv_module(net, num_layers[1], num_kernels[1], scope='conv2') print('module_2 shape:', [dim.value for dim in net.shape]) net = conv_module(net, num_layers[2], num_kernels[2], scope='conv3') print('module_3 shape:', [dim.value for dim in net.shape]) net = conv_module(net, num_layers[3], num_kernels[3], scope='conv4') print('module_4 shape:', [dim.value for dim in net.shape]) net_ = net net = slim.flatten(net) prelogits = slim.fully_connected(net, embedding_size, scope='Bottleneck', weights_initializer=slim.xavier_initializer(), normalizer_fn=slim.batch_norm, normalizer_params=batch_norm_params_last, activation_fn=None) # Output used for PFE mu = tf.nn.l2_normalize(prelogits, axis=1) conv_final = net return mu, conv_final
en
0.884501
# Fix the moving mean and std when training PFE # Output used for PFE
1.982342
2
edtslib/opaque_types.py
dartharnold/EDTS
0
6632155
import json from .dist import Lightyears class OpaqEncoder(json.JSONEncoder): def default(self, obj): try: return obj.to_opaq() except Exception as e: return "Don't know how to serialise {}: {}".format(type(obj), e) class Opaq(object): def __repr__(self): return str(vars(self)) def to_opaq(self): return vars(self) class Fuel(Opaq): def __init__(self, **args): for attr in ['min', 'max', 'initial', 'cost', 'final']: setattr(self, attr, args.get(attr, 0.0)) class Refuel(Opaq): def __init__(self, **args): self.amount = args.get('amount', 0.0) self.percent = args.get('percent', 0) class Jumps(Opaq): def __init__(self, **args): self.min = args.get('min', 1) self.max = args.get('max', 1) class Location(Opaq): def __init__(self, **args): self.system = args.get('system') self.station = args.get('station') class WaypointTime(Opaq): def __init__(self, **args): self.accurate = args.get('accurate', True) self.cruise = args.get('cruise', 0) self.jumps = args.get('jumps', Jumps(min = 0, max = 0)) class Waypoint(Opaq): def __init__(self, **args): self.distance = args.get('distance', Lightyears(0)) self.direct = args.get('direct', self.distance) self.jumps = args.get('jumps', Jumps()) self.time = args.get('time', WaypointTime()) def to_opaq(self): return vars(self)
import json from .dist import Lightyears class OpaqEncoder(json.JSONEncoder): def default(self, obj): try: return obj.to_opaq() except Exception as e: return "Don't know how to serialise {}: {}".format(type(obj), e) class Opaq(object): def __repr__(self): return str(vars(self)) def to_opaq(self): return vars(self) class Fuel(Opaq): def __init__(self, **args): for attr in ['min', 'max', 'initial', 'cost', 'final']: setattr(self, attr, args.get(attr, 0.0)) class Refuel(Opaq): def __init__(self, **args): self.amount = args.get('amount', 0.0) self.percent = args.get('percent', 0) class Jumps(Opaq): def __init__(self, **args): self.min = args.get('min', 1) self.max = args.get('max', 1) class Location(Opaq): def __init__(self, **args): self.system = args.get('system') self.station = args.get('station') class WaypointTime(Opaq): def __init__(self, **args): self.accurate = args.get('accurate', True) self.cruise = args.get('cruise', 0) self.jumps = args.get('jumps', Jumps(min = 0, max = 0)) class Waypoint(Opaq): def __init__(self, **args): self.distance = args.get('distance', Lightyears(0)) self.direct = args.get('direct', self.distance) self.jumps = args.get('jumps', Jumps()) self.time = args.get('time', WaypointTime()) def to_opaq(self): return vars(self)
none
1
2.680574
3
lib/xslt/reader/__init__.py
zepheira/amara
6
6632156
######################################################################## # amara/xslt/reader/__init__.py """ Classes for the creation of a stylesheet object """ import cStringIO from xml.dom import Node from xml.sax import SAXParseException from xml.sax.handler import property_dom_node from amara import sax from amara.lib import IriError, inputsource from amara.lib.xmlstring import isspace from amara.namespaces import XML_NAMESPACE, XMLNS_NAMESPACE, XSL_NAMESPACE from amara.xslt import XsltError, XsltStaticError from amara.xslt import extensions, exslt from amara.xslt.tree import * __all__ = ['stylesheet_reader'] # Whitespace stripping rules for a stylesheet: # preserve all whitespace within xsl:text elements; # strip whitespace from all other elements _XSLT_WHITESPACE_STRIPPING = ((XSL_NAMESPACE, 'text', False), (None, '*', True)) # pseudo-nodes for save/restore of variable bindings class push_variables_node(xslt_node): pseudo_node = True def __init__(self, root, scope): xslt_node.__init__(self, root) self._scope = scope return def instantiate(self, context): variables = context.variables self._scope.append(variables) context.variables = variables.copy() return class pop_variables_node(xslt_node): pseudo_node = True def __init__(self, root, scope): xslt_node.__init__(self, root) self._scope = scope return def instantiate(self, context): scope = self._scope context.variables = scope[-1] del scope[-1] return ELEMENT_CLASSES = { 'apply-imports': apply_imports_element.apply_imports_element, 'apply-templates': apply_templates_element.apply_templates_element, 'attribute': attribute_element.attribute_element, 'call-template': call_template_element.call_template_element, 'choose': choose_elements.choose_element, 'otherwise': choose_elements.otherwise_element, 'when': choose_elements.when_element, 'comment': comment_element.comment_element, 'copy': copy_element.copy_element, 'copy-of': copy_of_element.copy_of_element, 'element': element_element.element_element, 'fallback': fallback_elements.fallback_element, 'for-each': for_each_element.for_each_element, 'if': if_element.if_element, 'message': message_element.message_element, 'number': number_element.number_element, 'processing-instruction': processing_instruction_element.processing_instruction_element, 'stylesheet': transform_element.transform_element, 'transform': transform_element.transform_element, 'template': template_element.template_element, 'text': text_element.text_element, 'value-of': value_of_element.value_of_element, 'variable': variable_elements.variable_element, 'param': variable_elements.param_element, 'sort': sort_element.sort_element, 'with-param': with_param_element.with_param_element, 'import': declaration_elements.import_element, 'include': declaration_elements.include_element, 'strip-space': declaration_elements.strip_space_element, 'preserve-space': declaration_elements.preserve_space_element, 'output': declaration_elements.output_element, 'key': declaration_elements.key_element, 'decimal-format': declaration_elements.decimal_format_element, 'namespace-alias': declaration_elements.namespace_alias_element, 'attribute-set': declaration_elements.attribute_set_element, } # The XSL attributes allowed on literal elements _RESULT_ELEMENT_XSL_ATTRS = { 'exclude-result-prefixes' : attribute_types.prefixes(), 'extension-element-prefixes' : attribute_types.prefixes(), 'use-attribute-sets' : attribute_types.qnames(), 'version' : attribute_types.number(), } _RESULT_ELEMENT_ATTR_INFO = attribute_types.any_avt() _root_content_model = content_model.alt( content_model.qname(XSL_NAMESPACE, 'xsl:stylesheet'), content_model.qname(XSL_NAMESPACE, 'xsl:transform'), content_model.result_elements) _XSLT_ROOT_VALIDATION = _root_content_model.compile() _LITERAL_ELEMENT_VALIDATION = content_model.template.compile() class parse_state: """ Stores the current state of the parser. Constructor arguments/instance variables: validation - validation state for the current containing node. localVariables - set of in-scope variable bindings to determine variable shadowing. forwardsCompatible - flag indicating whether or not forwards-compatible processing is enabled. currentNamespaces - set of in-scope namespaces for the current node. extensionNamespaces - set of namespaces defining extension elements outputNamespaces - set of in-scope namespaces for literal result elements """ def __init__(self, node, validation, localVariables, forwardsCompatible, currentNamespaces, extensionNamespaces, outputNamespaces): self.node = node self.validation = validation self.localVariables = localVariables self.forwardsCompatible = forwardsCompatible self.currentNamespaces = currentNamespaces self.extensionNamespaces = extensionNamespaces self.outputNamespaces = outputNamespaces return class stylesheet_reader(object): """ This class can be used to read, from a variety of sources, a stylesheet and all its included and imported stylesheets, building from them a single, compact representation of an XSLT stylesheet tree (an Ft.Xml.Xslt.Stylesheet.Stylesheet object). This is done with the most efficient parsing method available, and avoids creating a Domlette document for each document it reads. """ # runtime instance variables _input_source = None _locator = None _stylesheet = None _root = None def __init__(self): self._import_index = 0 self._global_vars = {} self._visited_stylesheet_uris = {} self._document_state_stack = [] self._element_state_stack = [] self._extelements = {} self._extelements.update(exslt.extension_elements) self._extelements.update(extensions.extension_elements) self._extelement_cache = {} return def reset(self): self._root = None self._import_index = 0 self._global_vars = {} self._visited_stylesheet_uris = {} self._document_state_stack = [] self._element_state_stack = [] return def addExtensionElementMapping(self, elementMapping): """ Add a mapping of extension element names to classes to the existing mapping of extension elements. This should only be used for standalone uses of this class. The only known standalone use for this class is for creating compiled stylesheets. The benefits of compiled stylesheets are now so minor that this use case may also disappear and then so will this function. You have been warned. """ self._extelements.update(elementMapping) for name in elementMapping: if name in self._extelement_cache: del self._extelement_cache[name] return # -- ContentHandler interface -------------------------------------- def setDocumentLocator(self, locator): """ Callback interface for SAX. """ # Save the current document state for nested parsing (inclusions) document_state = (self._locator, self._stylesheet) self._document_state_stack.append(document_state) self._locator = locator self._stylesheet = None return def startDocument(self): """ Callback interface for SAX. """ # Our root is always a document # We use a document for this because of error checking and # because we explicitly pass ownerDocument to the nodes as # they are created document_uri = self._locator.getSystemId() root = xslt_root(document_uri) if not self._root: self._root = root self._element_state_stack.append( parse_state(node=root, validation=_XSLT_ROOT_VALIDATION, localVariables={}, forwardsCompatible=False, currentNamespaces={'xml': XML_NAMESPACE, None: None}, extensionNamespaces={}, outputNamespaces={}, ) ) # for recursive include checks for xsl:include/xsl:import self._visited_stylesheet_uris[document_uri] = True # namespaces added for the next element self._new_namespaces = {} return def endDocument(self): """ Callback interface for SAX. """ stack = self._element_state_stack state = stack[-1] del stack[-1] root = state.node # ---------------------------------------------------------- # remove URI from recursive inclusion checking del self._visited_stylesheet_uris[root.baseUri] # ---------------------------------------------------------- # finalize the children for the document #root.children = tuple(state.nodes) # ---------------------------------------------------------- # finalize the stylesheet AST if stack: # An xsl:import or xsl:include # Merge the top-level elements into the "parent" stylesheet # IMPLEMENTATION NOTE: stack[-1] is the import/include element, # stack[-2] is the "parent" stylesheet stack[-2].node._merge(self._stylesheet) #parent_node = stack[-2].node #for child in self._stylesheet.children: # child.parent = parent_node else: # A top-most stylesheet stylesheet = self._root.stylesheet if stylesheet is not self._stylesheet: # An additional stylesheet (e.g., an <?xml-stylesheet ...?>); # treat it as an xsl:import into the "master" stylesheet. stylesheet.reset() # Always update the precedence from the included stylesheet # because it may have contained imports thus increasing its # import precedence. self._import_index += 1 stylesheet.import_precedence = self._import_index # Merge the top-level elements into the "master" stylesheet stylesheet._merge(self._stylesheet) #stylesheet.children += self._stylesheet.children #for child in self._stylesheet.children: # child.parent = stylesheet else: # Prepare for a possible subsequent parse. self._import_index += 1 # Prepare the "master" stylesheet stylesheet.setup() document_state = self._document_state_stack[-1] del self._document_state_stack[-1] self._locator, self._stylesheet = document_state return def startPrefixMapping(self, prefix, uri): """ Callback interface for SAX. """ self._new_namespaces[prefix] = uri return def startElementNS(self, expandedName, qualifiedName, attribs, _literal_element=literal_element.literal_element, _element_classes=ELEMENT_CLASSES, _element_cache={}, ): """ Callback interface for SAX. """ parent_state = self._element_state_stack[-1] state = parse_state(**parent_state.__dict__) self._element_state_stack.append(state) # ---------------------------------------------------------- # update in-scope namespaces if self._new_namespaces: d = state.currentNamespaces = state.currentNamespaces.copy() d.update(self._new_namespaces) d = state.outputNamespaces = state.outputNamespaces.copy() for prefix, uri in self._new_namespaces.iteritems(): if uri not in (XML_NAMESPACE, XSL_NAMESPACE): d[prefix] = uri # reset for next element self._new_namespaces = {} # ---------------------------------------------------------- # get the class defining this element namespace, local = expandedName xsl_class = ext_class = None if namespace == XSL_NAMESPACE: try: xsl_class, validation, validation_token, legal_attrs = \ _element_cache[local] except KeyError: # We need to try to import (and cache) it try: xsl_class = _element_classes[local] except KeyError: if not state.forwardsCompatible: raise XsltStaticError(XsltError.XSLT_ILLEGAL_ELEMENT, parent_state.node, element=local) xsl_class = fallback_elements.undefined_xslt_element validation_token = content_model.RESULT_ELEMENT else: validation_token = expandedName validation = xsl_class.content_model.compile() legal_attrs = xsl_class.attribute_types.items() _element_cache[local] = ( xsl_class, validation, validation_token, legal_attrs) elif namespace in state.extensionNamespaces: try: ext_class, validation, legal_attrs = \ self._extelement_cache[expandedName] except KeyError: try: ext_class = self._extelements[expandedName] except KeyError: ext_class = fallback_elements.undefined_extension_element validation = ext_class.content_model.compile() legal_attrs = ext_class.attribute_types if legal_attrs is not None: legal_attrs = legal_attrs.items() self._extelement_cache[expandedName] = ( ext_class, validation, legal_attrs) validation_token = content_model.RESULT_ELEMENT else: validation = _LITERAL_ELEMENT_VALIDATION validation_token = content_model.RESULT_ELEMENT state.validation = validation # ---------------------------------------------------------- # verify that this element can be declared here try: next = parent_state.validation[validation_token] except KeyError: #self._debug_validation(expandedName) # ignore whatever elements are defined within an undefined # element as an exception will occur when/if this element # is actually instantiated if not isinstance(parent_state.node, fallback_elements.undefined_extension_element): raise XsltStaticError(XsltError.ILLEGAL_ELEMENT_CHILD, parent_state.node, element=qualifiedName) else: # save this state for next go round parent_state.validation = next # ---------------------------------------------------------- # create the instance defining this element klass = (xsl_class or ext_class or _literal_element) state.node = instance = klass(self._root, expandedName, qualifiedName, state.currentNamespaces) instance.baseUri = self._locator.getSystemId() instance.lineNumber = self._locator.getLineNumber() instance.columnNumber = self._locator.getColumnNumber() instance.import_precedence = self._import_index if xsl_class: # -- XSLT element -------------------------------- # Handle attributes in the null-namespace standand_attributes = local in ('stylesheet', 'transform') inst_dict = instance.__dict__ for attr_name, attr_info in legal_attrs: attr_expanded = (None, attr_name) if attr_expanded in attribs: value = attribs[attr_expanded] del attribs[attr_expanded] elif attr_info.required: raise XsltStaticError(XsltError.MISSING_REQUIRED_ATTRIBUTE, instance, element=qualifiedName, attribute=attr_name) else: value = None try: value = attr_info.prepare(instance, value) except XsltError, e: #raise self._mutate_exception(e, qualifiedName) raise if standand_attributes: self._stylesheet = instance self._handle_standard_attr(state, instance, attr_name, value) else: if '-' in attr_name: attr_name = attr_name.replace('-', '_') inst_dict['_' + attr_name] = value if attribs: # Process attributes with a namespace-uri and check for # any illegal attributes in the null-namespace for expanded in attribs: attr_ns, attr_name = expanded if attr_ns is None: if not state.forwardsCompatible: raise XsltStaticError( XsltError.ILLEGAL_NULL_NAMESPACE_ATTR, instance, attribute=attr_name, element=qualifiedName) else: instance.setAttribute(attr_ns, attr_name, attribs[expanded]) # XSLT Spec 2.6 - Combining Stylesheets if local in ('import', 'include'): self._combine_stylesheet(instance, (local == 'import')) elif ext_class: # -- extension element ------------------------- validate_attributes = (legal_attrs is not None) if validate_attributes: # Handle attributes in the null-namespace inst_dict = instance.__dict__ for attr_name, attr_info in legal_attrs: attr_expanded = (None, attr_name) if attr_expanded in attribs: value = attribs[attr_expanded] del attribs[attr_expanded] elif attr_info.required: raise XsltStaticError( XsltError.MISSING_REQUIRED_ATTRIBUTE, instance, element=qualifiedName, attribute=attr_name) else: value = None try: value = attr_info.prepare(instance, value) except XsltError, e: #raise self._mutate_exception(e, qualifiedName) raise if '-' in attr_name: attr_name = attr_name.replace('-', '_') inst_dict['_' + attr_name] = value # Process attributes with a namespace-uri and check for # any illegal attributes in the null-namespace if attribs: for expanded in attribs: attr_ns, attr_name = expanded value = attribs[expanded] if validate_attributes and attr_ns is None: raise XsltStaticError( XsltError.ILLEGAL_NULL_NAMESPACE_ATTR, instance, attribute=attr_name, element=qualifiedName) elif attr_ns == XSL_NAMESPACE: self._handle_result_element_attr(state, instance, qualifiedName, attr_name, value) else: instance.setAttribute(attr_ns, attr_name, value) else: # -- literal result element ------------------------------ output_attrs = [] for expanded in attribs: attr_ns, attr_local = expanded value = attribs[expanded] if attr_ns == XSL_NAMESPACE: self._handle_result_element_attr(state, instance, qualifiedName, attr_local, value) else: # prepare attributes for literal output value = _RESULT_ELEMENT_ATTR_INFO.prepare(instance, value) attr_qname = attribs.getQNameByName(expanded) output_attrs.append((attr_qname, attr_ns, value)) # save information for literal output instance._output_namespace = namespace instance._output_nss = state.outputNamespaces instance._output_attrs = output_attrs # Check for top-level result-element in null namespace if parent_state.node is self._stylesheet and \ not namespace and not state.forwardsCompatible: raise XsltStaticError(XsltError.ILLEGAL_ELEMENT_CHILD, parent_state.node, element=qualifiedName) return def endElementNS(self, expandedName, qualifiedName, _literal_element=literal_element.literal_element, _variable_element=variable_elements.variable_element): """ Callback interface for SAX. """ stack = self._element_state_stack state = stack[-1] del stack[-1] parent_state = stack[-1] element = state.node # ---------------------------------------------------------- # verify that this element has all required content try: state.validation[content_model.END_ELEMENT] except KeyError: if expandedName == (XSL_NAMESPACE, u'choose'): raise XsltStaticError(XsltError.MISSING_REQUIRED_ELEMENT, element, element=element.nodeName, child='xsl:when') raise # ---------------------------------------------------------- # setup variable context if state.localVariables is not parent_state.localVariables: # add context save/restore nodes binding_stack = [] node = push_variables_node(self._root, binding_stack) element.insertChild(0, node) node = pop_variables_node(self._root, binding_stack) element.appendChild(node) # ---------------------------------------------------------- # finalize the children for this element #element.children = tuple(state.nodes) #for child in element.children: # if child.doesSetup: #s child.setup() del state # ---------------------------------------------------------- # update parent state parent_node = parent_state.node if self._stylesheet is None and parent_node is element.root: # a literal result element as stylesheet assert isinstance(element, _literal_element), element try: version = element._version except AttributeError: raise XsltStaticError(XsltError.LITERAL_RESULT_MISSING_VERSION, element) # Reset the root's validation as it has already seen an element. parent_state.validation = _XSLT_ROOT_VALIDATION # FIXME: use the prefix from the document for the XSL namespace stylesheet = (XSL_NAMESPACE, u'stylesheet') self.startElementNS(stylesheet, u'xsl:stylesheet', {(None, u'version') : version}) template = (XSL_NAMESPACE, u'template') self.startElementNS(template, u'xsl:template', {(None, u'match') : u'/'}) # make this element the template's content # Note, this MUST index the stack as the stack has changed # due to the startElementNS() calls. stack[-1].node.appendChild(element) self.endElementNS(template, u'xsl:template') self.endElementNS(stylesheet, u'xsl:stylesheet') return parent_node.appendChild(element) if isinstance(element, _variable_element): name = element._name if parent_node is self._stylesheet: # global variables if name in self._global_vars: existing = self._global_vars[name] if self._import_index > existing: self._global_vars[name] = self._import_index elif self._import_index == existing: raise XsltStaticError(XsltError.DUPLICATE_TOP_LEVEL_VAR, element, variable=name) else: self._global_vars[name] = self._import_index else: # local variables # it is safe to ignore import precedence here local_vars = parent_state.localVariables if name in local_vars: raise XsltStaticError(XsltError.ILLEGAL_SHADOWING, element, variable=name) # Copy on use if local_vars is stack[-2].localVariables: local_vars = local_vars.copy() parent_state.localVariables = local_vars local_vars[name] = True return def characters(self, data): """ Callback interface for SAX. """ parent_state = self._element_state_stack[-1] # verify that the current element can have text children try: next = parent_state.validation[content_model.TEXT_NODE] except KeyError: # If the parent can have element children, but not text nodes, # ignore pure whitespace nodes. This clarification is from # XSLT 2.0 [3.4] Whitespace Stripping. # e.g. xsl:stylesheet, xsl:apply-templates, xsl:choose #self._debug_validation(content_model.TEXT_NODE) #if (content_model.EMPTY in parent_state.validation or # not isspace(data)): if 1: if len(data) > 10: data = data[:10] + '...' raise XsltStaticError(XsltError.ILLEGAL_TEXT_CHILD, parent_state.node, data=data, element=parent_state.node.nodeName) #self._debug_validation(content_model.TEXT_NODE) else: # update validation parent_state.validation = next node = xslt_text(self._root, data) parent_state.node.appendChild(node) return # -- utility functions --------------------------------------------- def _combine_stylesheet(self, element, is_import): href = element._href try: new_source = self._input_source.resolve(href, self._input_source.uri) except (OSError, IriError): # FIXME: create special inputsource for 4xslt command-line #for uri in self._alt_base_uris: # try: # new_href = self._input_source.getUriResolver().normalize(href, uri) # #Do we need to figure out a way to pass the hint here? # new_source = self._input_source.factory.fromUri(new_href) # break # except (OSError, IriError): # pass #else: raise XsltStaticError(XsltError.INCLUDE_NOT_FOUND, element, uri=href, base=self._locator.getSystemId()) # XSLT Spec 2.6.1, Detect circular references in stylesheets # Note, it is NOT an error to include/import the same stylesheet # multiple times, rather that it may lead to duplicate definitions # which are handled regardless (variables, params, templates, ...) if new_source.uri in self._visited_stylesheet_uris: raise XsltStaticError(XsltError.CIRCULAR_INCLUDE, element, uri=new_source.uri) self.parse(new_source) self._import_index += is_import # Always update the precedence as the included stylesheet may have # contained imports thus increasing the import precedence. self._stylesheet.import_precedence = self._import_index return def _handle_standard_attr(self, state, instance, name, value): if name == 'extension-element-prefixes': # a whitespace separated list of prefixes ext = state.extensionNamespaces = state.extensionNamespaces.copy() out = state.outputNamespaces = state.outputNamespaces.copy() for prefix in value: # add the namespace URI to the set of extension namespaces try: uri = instance.namespaces[prefix] except KeyError: raise XsltStaticError(XsltError.UNDEFINED_PREFIX, instance, prefix=prefix or '#default') ext[uri] = True # remove all matching namespace URIs for output_prefix, output_uri in out.items(): if output_uri == uri: del out[output_prefix] elif name == 'exclude-result-prefixes': # a whitespace separated list of prefixes out = state.outputNamespaces = state.outputNamespaces.copy() for prefix in value: try: uri = instance.namespaces[prefix] except KeyError: raise XsltStaticError(XsltError.UNDEFINED_PREFIX, instance, prefix=prefix or '#default') # remove all matching namespace URIs for output_prefix, output_uri in out.items(): if output_uri == uri: del out[output_prefix] elif name == 'version': # XSLT Spec 2.5 - Forwards-Compatible Processing state.forwardsCompatible = (value != 1.0) instance._version = value else: if '-' in name: name = name.replace('-', '_') instance.__dict__['_' + name] = value return def _handle_result_element_attr(self, state, instance, elementName, attributeName, value): try: attr_info = _RESULT_ELEMENT_XSL_ATTRS[attributeName] except KeyError: raise XsltStaticError(XsltError.ILLEGAL_XSL_NAMESPACE_ATTR, instance, attribute=attributeName, element=elementName) value = attr_info.prepare(instance, value) self._handle_standard_attr(state, instance, attributeName, value) return def _mutate_exception(self, exception, elementName): assert isinstance(exception, XsltError) exception.message = MessageSource.EXPRESSION_POSITION_INFO % ( self._locator.getSystemId(), self._locator.getLineNumber(), self._locator.getColumnNumber(), elementName, exception.message) return exception # -- debugging routines -------------------------------------------- def _debug_validation(self, token=None): from pprint import pprint state = self._element_state_stack[-1] parent = state.node print '='*60 print 'parent =',parent print 'parent class =',parent.__class__ print 'parent content =', parent.content_model print 'initial validation' pprint(parent.content_model.compile()) print 'current validation' pprint(state.validation) if token: print 'token', token print '='*60 return # -- parsing routines ---------------------------------------------- def fromDocument(self, document, baseUri='', factory=None): """ Read in a stylesheet source document from a Domlette and add it to the stylesheet tree. If a document with the same URI has already been read, the cached version will be used instead (so duplicate imports, includes, or stylesheet appends do not result in multiple reads). """ if not baseUri: if hasattr(document, 'documentURI'): baseUri = document.documentURI elif hasattr(document, 'baseURI'): baseUri = document.baseURI else: raise TypeError('baseUri required') if factory is None: factory = inputsource.default_factory # check cache if self._root is not None: # We prefer to use an already-parsed doc, as it has had its # external entities and XIncludes resolved already if uri in self._root.sourceNodes: document = self._root.sourceNodes[baseUri] # It's OK to use cached string content, but we have no idea # whether we're using the same InputSource class as was used to # parse it the first time, and we don't cache external entities # or XIncludes, so there is the possibility of those things # being resolved differently this time around. Oh well. elif uri in self._root.sources: content = self._root.sources[baseUri] isrc = factory.fromString(content, baseUri) # temporarily uncache it so `parse()` will process it; # `parse()` will add it back to the cache when finished del self._root.sources[baseUri] return self.parse(isrc) isrc = factory.fromStream(None, baseUri) features = [] properties = [(property_dom_node, document)] stylesheet = self._parseSrc(isrc, features, properties) # Cache for XSLT document() function self._root.sourceNodes[baseUri] = document return stylesheet def parse(self, source): """ Read in a stylesheet source document from an InputSource and add it to the stylesheet tree. If a document with the same URI has already been read, the cached version will be used instead (so duplicate imports, includes, or stylesheet appends do not result in multiple reads). """ uri = source.uri #Check cache content = '' if self._root is not None: # We prefer to use an already-parsed doc, as it has had its # external entities and XIncludes resolved already if uri in self._root.sourceNodes: doc = self._root.sourceNodes[uri] # temporarily uncache it so fromDocument will process it; # fromDocument will add it back to the cache when finished del self._root.sourceNodes[uri] return self.fromDocument(doc, baseUri=uri) # It's OK to use cached string content, but we have no idea # whether we're using the same InputSource class as was used to # parse it the first time, and we don't cache external entities # or XIncludes, so there is the possibility of those things # being resolved differently this time around. Oh well. elif uri in self._root.sources: content = self._root.sources[uri] source = inputsource(content, uri) if not content: content = source.stream.read() source = inputsource(cStringIO.StringIO(content), source.uri) #features = [(sax.FEATURE_PROCESS_XINCLUDES, True)] features, properties = [], [] stylesheet = self._parseSrc(source, features, properties) # Cache the string content for subsequent uses # e.g., xsl:import/xsl:include and document() self._root.sources[uri] = content return stylesheet def _parseSrc(self, isrc, features, properties): parser = sax.create_parser() parser.setContentHandler(self) for featurename, value in features: parser.setFeature(featurename, value) # Always set whitespace rules property parser.setProperty(sax.PROPERTY_WHITESPACE_RULES, _XSLT_WHITESPACE_STRIPPING) for propertyname, value in properties: parser.setProperty(propertyname, value) prev_source = self._input_source try: self._input_source = isrc try: parser.parse(isrc) except SAXParseException, e: e = e.getException() or e if isinstance(e, XsltError): raise e raise XsltError(XsltError.STYLESHEET_PARSE_ERROR, uri=isrc.uri, text=str(e)) finally: self._input_source = prev_source return self._root.stylesheet
######################################################################## # amara/xslt/reader/__init__.py """ Classes for the creation of a stylesheet object """ import cStringIO from xml.dom import Node from xml.sax import SAXParseException from xml.sax.handler import property_dom_node from amara import sax from amara.lib import IriError, inputsource from amara.lib.xmlstring import isspace from amara.namespaces import XML_NAMESPACE, XMLNS_NAMESPACE, XSL_NAMESPACE from amara.xslt import XsltError, XsltStaticError from amara.xslt import extensions, exslt from amara.xslt.tree import * __all__ = ['stylesheet_reader'] # Whitespace stripping rules for a stylesheet: # preserve all whitespace within xsl:text elements; # strip whitespace from all other elements _XSLT_WHITESPACE_STRIPPING = ((XSL_NAMESPACE, 'text', False), (None, '*', True)) # pseudo-nodes for save/restore of variable bindings class push_variables_node(xslt_node): pseudo_node = True def __init__(self, root, scope): xslt_node.__init__(self, root) self._scope = scope return def instantiate(self, context): variables = context.variables self._scope.append(variables) context.variables = variables.copy() return class pop_variables_node(xslt_node): pseudo_node = True def __init__(self, root, scope): xslt_node.__init__(self, root) self._scope = scope return def instantiate(self, context): scope = self._scope context.variables = scope[-1] del scope[-1] return ELEMENT_CLASSES = { 'apply-imports': apply_imports_element.apply_imports_element, 'apply-templates': apply_templates_element.apply_templates_element, 'attribute': attribute_element.attribute_element, 'call-template': call_template_element.call_template_element, 'choose': choose_elements.choose_element, 'otherwise': choose_elements.otherwise_element, 'when': choose_elements.when_element, 'comment': comment_element.comment_element, 'copy': copy_element.copy_element, 'copy-of': copy_of_element.copy_of_element, 'element': element_element.element_element, 'fallback': fallback_elements.fallback_element, 'for-each': for_each_element.for_each_element, 'if': if_element.if_element, 'message': message_element.message_element, 'number': number_element.number_element, 'processing-instruction': processing_instruction_element.processing_instruction_element, 'stylesheet': transform_element.transform_element, 'transform': transform_element.transform_element, 'template': template_element.template_element, 'text': text_element.text_element, 'value-of': value_of_element.value_of_element, 'variable': variable_elements.variable_element, 'param': variable_elements.param_element, 'sort': sort_element.sort_element, 'with-param': with_param_element.with_param_element, 'import': declaration_elements.import_element, 'include': declaration_elements.include_element, 'strip-space': declaration_elements.strip_space_element, 'preserve-space': declaration_elements.preserve_space_element, 'output': declaration_elements.output_element, 'key': declaration_elements.key_element, 'decimal-format': declaration_elements.decimal_format_element, 'namespace-alias': declaration_elements.namespace_alias_element, 'attribute-set': declaration_elements.attribute_set_element, } # The XSL attributes allowed on literal elements _RESULT_ELEMENT_XSL_ATTRS = { 'exclude-result-prefixes' : attribute_types.prefixes(), 'extension-element-prefixes' : attribute_types.prefixes(), 'use-attribute-sets' : attribute_types.qnames(), 'version' : attribute_types.number(), } _RESULT_ELEMENT_ATTR_INFO = attribute_types.any_avt() _root_content_model = content_model.alt( content_model.qname(XSL_NAMESPACE, 'xsl:stylesheet'), content_model.qname(XSL_NAMESPACE, 'xsl:transform'), content_model.result_elements) _XSLT_ROOT_VALIDATION = _root_content_model.compile() _LITERAL_ELEMENT_VALIDATION = content_model.template.compile() class parse_state: """ Stores the current state of the parser. Constructor arguments/instance variables: validation - validation state for the current containing node. localVariables - set of in-scope variable bindings to determine variable shadowing. forwardsCompatible - flag indicating whether or not forwards-compatible processing is enabled. currentNamespaces - set of in-scope namespaces for the current node. extensionNamespaces - set of namespaces defining extension elements outputNamespaces - set of in-scope namespaces for literal result elements """ def __init__(self, node, validation, localVariables, forwardsCompatible, currentNamespaces, extensionNamespaces, outputNamespaces): self.node = node self.validation = validation self.localVariables = localVariables self.forwardsCompatible = forwardsCompatible self.currentNamespaces = currentNamespaces self.extensionNamespaces = extensionNamespaces self.outputNamespaces = outputNamespaces return class stylesheet_reader(object): """ This class can be used to read, from a variety of sources, a stylesheet and all its included and imported stylesheets, building from them a single, compact representation of an XSLT stylesheet tree (an Ft.Xml.Xslt.Stylesheet.Stylesheet object). This is done with the most efficient parsing method available, and avoids creating a Domlette document for each document it reads. """ # runtime instance variables _input_source = None _locator = None _stylesheet = None _root = None def __init__(self): self._import_index = 0 self._global_vars = {} self._visited_stylesheet_uris = {} self._document_state_stack = [] self._element_state_stack = [] self._extelements = {} self._extelements.update(exslt.extension_elements) self._extelements.update(extensions.extension_elements) self._extelement_cache = {} return def reset(self): self._root = None self._import_index = 0 self._global_vars = {} self._visited_stylesheet_uris = {} self._document_state_stack = [] self._element_state_stack = [] return def addExtensionElementMapping(self, elementMapping): """ Add a mapping of extension element names to classes to the existing mapping of extension elements. This should only be used for standalone uses of this class. The only known standalone use for this class is for creating compiled stylesheets. The benefits of compiled stylesheets are now so minor that this use case may also disappear and then so will this function. You have been warned. """ self._extelements.update(elementMapping) for name in elementMapping: if name in self._extelement_cache: del self._extelement_cache[name] return # -- ContentHandler interface -------------------------------------- def setDocumentLocator(self, locator): """ Callback interface for SAX. """ # Save the current document state for nested parsing (inclusions) document_state = (self._locator, self._stylesheet) self._document_state_stack.append(document_state) self._locator = locator self._stylesheet = None return def startDocument(self): """ Callback interface for SAX. """ # Our root is always a document # We use a document for this because of error checking and # because we explicitly pass ownerDocument to the nodes as # they are created document_uri = self._locator.getSystemId() root = xslt_root(document_uri) if not self._root: self._root = root self._element_state_stack.append( parse_state(node=root, validation=_XSLT_ROOT_VALIDATION, localVariables={}, forwardsCompatible=False, currentNamespaces={'xml': XML_NAMESPACE, None: None}, extensionNamespaces={}, outputNamespaces={}, ) ) # for recursive include checks for xsl:include/xsl:import self._visited_stylesheet_uris[document_uri] = True # namespaces added for the next element self._new_namespaces = {} return def endDocument(self): """ Callback interface for SAX. """ stack = self._element_state_stack state = stack[-1] del stack[-1] root = state.node # ---------------------------------------------------------- # remove URI from recursive inclusion checking del self._visited_stylesheet_uris[root.baseUri] # ---------------------------------------------------------- # finalize the children for the document #root.children = tuple(state.nodes) # ---------------------------------------------------------- # finalize the stylesheet AST if stack: # An xsl:import or xsl:include # Merge the top-level elements into the "parent" stylesheet # IMPLEMENTATION NOTE: stack[-1] is the import/include element, # stack[-2] is the "parent" stylesheet stack[-2].node._merge(self._stylesheet) #parent_node = stack[-2].node #for child in self._stylesheet.children: # child.parent = parent_node else: # A top-most stylesheet stylesheet = self._root.stylesheet if stylesheet is not self._stylesheet: # An additional stylesheet (e.g., an <?xml-stylesheet ...?>); # treat it as an xsl:import into the "master" stylesheet. stylesheet.reset() # Always update the precedence from the included stylesheet # because it may have contained imports thus increasing its # import precedence. self._import_index += 1 stylesheet.import_precedence = self._import_index # Merge the top-level elements into the "master" stylesheet stylesheet._merge(self._stylesheet) #stylesheet.children += self._stylesheet.children #for child in self._stylesheet.children: # child.parent = stylesheet else: # Prepare for a possible subsequent parse. self._import_index += 1 # Prepare the "master" stylesheet stylesheet.setup() document_state = self._document_state_stack[-1] del self._document_state_stack[-1] self._locator, self._stylesheet = document_state return def startPrefixMapping(self, prefix, uri): """ Callback interface for SAX. """ self._new_namespaces[prefix] = uri return def startElementNS(self, expandedName, qualifiedName, attribs, _literal_element=literal_element.literal_element, _element_classes=ELEMENT_CLASSES, _element_cache={}, ): """ Callback interface for SAX. """ parent_state = self._element_state_stack[-1] state = parse_state(**parent_state.__dict__) self._element_state_stack.append(state) # ---------------------------------------------------------- # update in-scope namespaces if self._new_namespaces: d = state.currentNamespaces = state.currentNamespaces.copy() d.update(self._new_namespaces) d = state.outputNamespaces = state.outputNamespaces.copy() for prefix, uri in self._new_namespaces.iteritems(): if uri not in (XML_NAMESPACE, XSL_NAMESPACE): d[prefix] = uri # reset for next element self._new_namespaces = {} # ---------------------------------------------------------- # get the class defining this element namespace, local = expandedName xsl_class = ext_class = None if namespace == XSL_NAMESPACE: try: xsl_class, validation, validation_token, legal_attrs = \ _element_cache[local] except KeyError: # We need to try to import (and cache) it try: xsl_class = _element_classes[local] except KeyError: if not state.forwardsCompatible: raise XsltStaticError(XsltError.XSLT_ILLEGAL_ELEMENT, parent_state.node, element=local) xsl_class = fallback_elements.undefined_xslt_element validation_token = content_model.RESULT_ELEMENT else: validation_token = expandedName validation = xsl_class.content_model.compile() legal_attrs = xsl_class.attribute_types.items() _element_cache[local] = ( xsl_class, validation, validation_token, legal_attrs) elif namespace in state.extensionNamespaces: try: ext_class, validation, legal_attrs = \ self._extelement_cache[expandedName] except KeyError: try: ext_class = self._extelements[expandedName] except KeyError: ext_class = fallback_elements.undefined_extension_element validation = ext_class.content_model.compile() legal_attrs = ext_class.attribute_types if legal_attrs is not None: legal_attrs = legal_attrs.items() self._extelement_cache[expandedName] = ( ext_class, validation, legal_attrs) validation_token = content_model.RESULT_ELEMENT else: validation = _LITERAL_ELEMENT_VALIDATION validation_token = content_model.RESULT_ELEMENT state.validation = validation # ---------------------------------------------------------- # verify that this element can be declared here try: next = parent_state.validation[validation_token] except KeyError: #self._debug_validation(expandedName) # ignore whatever elements are defined within an undefined # element as an exception will occur when/if this element # is actually instantiated if not isinstance(parent_state.node, fallback_elements.undefined_extension_element): raise XsltStaticError(XsltError.ILLEGAL_ELEMENT_CHILD, parent_state.node, element=qualifiedName) else: # save this state for next go round parent_state.validation = next # ---------------------------------------------------------- # create the instance defining this element klass = (xsl_class or ext_class or _literal_element) state.node = instance = klass(self._root, expandedName, qualifiedName, state.currentNamespaces) instance.baseUri = self._locator.getSystemId() instance.lineNumber = self._locator.getLineNumber() instance.columnNumber = self._locator.getColumnNumber() instance.import_precedence = self._import_index if xsl_class: # -- XSLT element -------------------------------- # Handle attributes in the null-namespace standand_attributes = local in ('stylesheet', 'transform') inst_dict = instance.__dict__ for attr_name, attr_info in legal_attrs: attr_expanded = (None, attr_name) if attr_expanded in attribs: value = attribs[attr_expanded] del attribs[attr_expanded] elif attr_info.required: raise XsltStaticError(XsltError.MISSING_REQUIRED_ATTRIBUTE, instance, element=qualifiedName, attribute=attr_name) else: value = None try: value = attr_info.prepare(instance, value) except XsltError, e: #raise self._mutate_exception(e, qualifiedName) raise if standand_attributes: self._stylesheet = instance self._handle_standard_attr(state, instance, attr_name, value) else: if '-' in attr_name: attr_name = attr_name.replace('-', '_') inst_dict['_' + attr_name] = value if attribs: # Process attributes with a namespace-uri and check for # any illegal attributes in the null-namespace for expanded in attribs: attr_ns, attr_name = expanded if attr_ns is None: if not state.forwardsCompatible: raise XsltStaticError( XsltError.ILLEGAL_NULL_NAMESPACE_ATTR, instance, attribute=attr_name, element=qualifiedName) else: instance.setAttribute(attr_ns, attr_name, attribs[expanded]) # XSLT Spec 2.6 - Combining Stylesheets if local in ('import', 'include'): self._combine_stylesheet(instance, (local == 'import')) elif ext_class: # -- extension element ------------------------- validate_attributes = (legal_attrs is not None) if validate_attributes: # Handle attributes in the null-namespace inst_dict = instance.__dict__ for attr_name, attr_info in legal_attrs: attr_expanded = (None, attr_name) if attr_expanded in attribs: value = attribs[attr_expanded] del attribs[attr_expanded] elif attr_info.required: raise XsltStaticError( XsltError.MISSING_REQUIRED_ATTRIBUTE, instance, element=qualifiedName, attribute=attr_name) else: value = None try: value = attr_info.prepare(instance, value) except XsltError, e: #raise self._mutate_exception(e, qualifiedName) raise if '-' in attr_name: attr_name = attr_name.replace('-', '_') inst_dict['_' + attr_name] = value # Process attributes with a namespace-uri and check for # any illegal attributes in the null-namespace if attribs: for expanded in attribs: attr_ns, attr_name = expanded value = attribs[expanded] if validate_attributes and attr_ns is None: raise XsltStaticError( XsltError.ILLEGAL_NULL_NAMESPACE_ATTR, instance, attribute=attr_name, element=qualifiedName) elif attr_ns == XSL_NAMESPACE: self._handle_result_element_attr(state, instance, qualifiedName, attr_name, value) else: instance.setAttribute(attr_ns, attr_name, value) else: # -- literal result element ------------------------------ output_attrs = [] for expanded in attribs: attr_ns, attr_local = expanded value = attribs[expanded] if attr_ns == XSL_NAMESPACE: self._handle_result_element_attr(state, instance, qualifiedName, attr_local, value) else: # prepare attributes for literal output value = _RESULT_ELEMENT_ATTR_INFO.prepare(instance, value) attr_qname = attribs.getQNameByName(expanded) output_attrs.append((attr_qname, attr_ns, value)) # save information for literal output instance._output_namespace = namespace instance._output_nss = state.outputNamespaces instance._output_attrs = output_attrs # Check for top-level result-element in null namespace if parent_state.node is self._stylesheet and \ not namespace and not state.forwardsCompatible: raise XsltStaticError(XsltError.ILLEGAL_ELEMENT_CHILD, parent_state.node, element=qualifiedName) return def endElementNS(self, expandedName, qualifiedName, _literal_element=literal_element.literal_element, _variable_element=variable_elements.variable_element): """ Callback interface for SAX. """ stack = self._element_state_stack state = stack[-1] del stack[-1] parent_state = stack[-1] element = state.node # ---------------------------------------------------------- # verify that this element has all required content try: state.validation[content_model.END_ELEMENT] except KeyError: if expandedName == (XSL_NAMESPACE, u'choose'): raise XsltStaticError(XsltError.MISSING_REQUIRED_ELEMENT, element, element=element.nodeName, child='xsl:when') raise # ---------------------------------------------------------- # setup variable context if state.localVariables is not parent_state.localVariables: # add context save/restore nodes binding_stack = [] node = push_variables_node(self._root, binding_stack) element.insertChild(0, node) node = pop_variables_node(self._root, binding_stack) element.appendChild(node) # ---------------------------------------------------------- # finalize the children for this element #element.children = tuple(state.nodes) #for child in element.children: # if child.doesSetup: #s child.setup() del state # ---------------------------------------------------------- # update parent state parent_node = parent_state.node if self._stylesheet is None and parent_node is element.root: # a literal result element as stylesheet assert isinstance(element, _literal_element), element try: version = element._version except AttributeError: raise XsltStaticError(XsltError.LITERAL_RESULT_MISSING_VERSION, element) # Reset the root's validation as it has already seen an element. parent_state.validation = _XSLT_ROOT_VALIDATION # FIXME: use the prefix from the document for the XSL namespace stylesheet = (XSL_NAMESPACE, u'stylesheet') self.startElementNS(stylesheet, u'xsl:stylesheet', {(None, u'version') : version}) template = (XSL_NAMESPACE, u'template') self.startElementNS(template, u'xsl:template', {(None, u'match') : u'/'}) # make this element the template's content # Note, this MUST index the stack as the stack has changed # due to the startElementNS() calls. stack[-1].node.appendChild(element) self.endElementNS(template, u'xsl:template') self.endElementNS(stylesheet, u'xsl:stylesheet') return parent_node.appendChild(element) if isinstance(element, _variable_element): name = element._name if parent_node is self._stylesheet: # global variables if name in self._global_vars: existing = self._global_vars[name] if self._import_index > existing: self._global_vars[name] = self._import_index elif self._import_index == existing: raise XsltStaticError(XsltError.DUPLICATE_TOP_LEVEL_VAR, element, variable=name) else: self._global_vars[name] = self._import_index else: # local variables # it is safe to ignore import precedence here local_vars = parent_state.localVariables if name in local_vars: raise XsltStaticError(XsltError.ILLEGAL_SHADOWING, element, variable=name) # Copy on use if local_vars is stack[-2].localVariables: local_vars = local_vars.copy() parent_state.localVariables = local_vars local_vars[name] = True return def characters(self, data): """ Callback interface for SAX. """ parent_state = self._element_state_stack[-1] # verify that the current element can have text children try: next = parent_state.validation[content_model.TEXT_NODE] except KeyError: # If the parent can have element children, but not text nodes, # ignore pure whitespace nodes. This clarification is from # XSLT 2.0 [3.4] Whitespace Stripping. # e.g. xsl:stylesheet, xsl:apply-templates, xsl:choose #self._debug_validation(content_model.TEXT_NODE) #if (content_model.EMPTY in parent_state.validation or # not isspace(data)): if 1: if len(data) > 10: data = data[:10] + '...' raise XsltStaticError(XsltError.ILLEGAL_TEXT_CHILD, parent_state.node, data=data, element=parent_state.node.nodeName) #self._debug_validation(content_model.TEXT_NODE) else: # update validation parent_state.validation = next node = xslt_text(self._root, data) parent_state.node.appendChild(node) return # -- utility functions --------------------------------------------- def _combine_stylesheet(self, element, is_import): href = element._href try: new_source = self._input_source.resolve(href, self._input_source.uri) except (OSError, IriError): # FIXME: create special inputsource for 4xslt command-line #for uri in self._alt_base_uris: # try: # new_href = self._input_source.getUriResolver().normalize(href, uri) # #Do we need to figure out a way to pass the hint here? # new_source = self._input_source.factory.fromUri(new_href) # break # except (OSError, IriError): # pass #else: raise XsltStaticError(XsltError.INCLUDE_NOT_FOUND, element, uri=href, base=self._locator.getSystemId()) # XSLT Spec 2.6.1, Detect circular references in stylesheets # Note, it is NOT an error to include/import the same stylesheet # multiple times, rather that it may lead to duplicate definitions # which are handled regardless (variables, params, templates, ...) if new_source.uri in self._visited_stylesheet_uris: raise XsltStaticError(XsltError.CIRCULAR_INCLUDE, element, uri=new_source.uri) self.parse(new_source) self._import_index += is_import # Always update the precedence as the included stylesheet may have # contained imports thus increasing the import precedence. self._stylesheet.import_precedence = self._import_index return def _handle_standard_attr(self, state, instance, name, value): if name == 'extension-element-prefixes': # a whitespace separated list of prefixes ext = state.extensionNamespaces = state.extensionNamespaces.copy() out = state.outputNamespaces = state.outputNamespaces.copy() for prefix in value: # add the namespace URI to the set of extension namespaces try: uri = instance.namespaces[prefix] except KeyError: raise XsltStaticError(XsltError.UNDEFINED_PREFIX, instance, prefix=prefix or '#default') ext[uri] = True # remove all matching namespace URIs for output_prefix, output_uri in out.items(): if output_uri == uri: del out[output_prefix] elif name == 'exclude-result-prefixes': # a whitespace separated list of prefixes out = state.outputNamespaces = state.outputNamespaces.copy() for prefix in value: try: uri = instance.namespaces[prefix] except KeyError: raise XsltStaticError(XsltError.UNDEFINED_PREFIX, instance, prefix=prefix or '#default') # remove all matching namespace URIs for output_prefix, output_uri in out.items(): if output_uri == uri: del out[output_prefix] elif name == 'version': # XSLT Spec 2.5 - Forwards-Compatible Processing state.forwardsCompatible = (value != 1.0) instance._version = value else: if '-' in name: name = name.replace('-', '_') instance.__dict__['_' + name] = value return def _handle_result_element_attr(self, state, instance, elementName, attributeName, value): try: attr_info = _RESULT_ELEMENT_XSL_ATTRS[attributeName] except KeyError: raise XsltStaticError(XsltError.ILLEGAL_XSL_NAMESPACE_ATTR, instance, attribute=attributeName, element=elementName) value = attr_info.prepare(instance, value) self._handle_standard_attr(state, instance, attributeName, value) return def _mutate_exception(self, exception, elementName): assert isinstance(exception, XsltError) exception.message = MessageSource.EXPRESSION_POSITION_INFO % ( self._locator.getSystemId(), self._locator.getLineNumber(), self._locator.getColumnNumber(), elementName, exception.message) return exception # -- debugging routines -------------------------------------------- def _debug_validation(self, token=None): from pprint import pprint state = self._element_state_stack[-1] parent = state.node print '='*60 print 'parent =',parent print 'parent class =',parent.__class__ print 'parent content =', parent.content_model print 'initial validation' pprint(parent.content_model.compile()) print 'current validation' pprint(state.validation) if token: print 'token', token print '='*60 return # -- parsing routines ---------------------------------------------- def fromDocument(self, document, baseUri='', factory=None): """ Read in a stylesheet source document from a Domlette and add it to the stylesheet tree. If a document with the same URI has already been read, the cached version will be used instead (so duplicate imports, includes, or stylesheet appends do not result in multiple reads). """ if not baseUri: if hasattr(document, 'documentURI'): baseUri = document.documentURI elif hasattr(document, 'baseURI'): baseUri = document.baseURI else: raise TypeError('baseUri required') if factory is None: factory = inputsource.default_factory # check cache if self._root is not None: # We prefer to use an already-parsed doc, as it has had its # external entities and XIncludes resolved already if uri in self._root.sourceNodes: document = self._root.sourceNodes[baseUri] # It's OK to use cached string content, but we have no idea # whether we're using the same InputSource class as was used to # parse it the first time, and we don't cache external entities # or XIncludes, so there is the possibility of those things # being resolved differently this time around. Oh well. elif uri in self._root.sources: content = self._root.sources[baseUri] isrc = factory.fromString(content, baseUri) # temporarily uncache it so `parse()` will process it; # `parse()` will add it back to the cache when finished del self._root.sources[baseUri] return self.parse(isrc) isrc = factory.fromStream(None, baseUri) features = [] properties = [(property_dom_node, document)] stylesheet = self._parseSrc(isrc, features, properties) # Cache for XSLT document() function self._root.sourceNodes[baseUri] = document return stylesheet def parse(self, source): """ Read in a stylesheet source document from an InputSource and add it to the stylesheet tree. If a document with the same URI has already been read, the cached version will be used instead (so duplicate imports, includes, or stylesheet appends do not result in multiple reads). """ uri = source.uri #Check cache content = '' if self._root is not None: # We prefer to use an already-parsed doc, as it has had its # external entities and XIncludes resolved already if uri in self._root.sourceNodes: doc = self._root.sourceNodes[uri] # temporarily uncache it so fromDocument will process it; # fromDocument will add it back to the cache when finished del self._root.sourceNodes[uri] return self.fromDocument(doc, baseUri=uri) # It's OK to use cached string content, but we have no idea # whether we're using the same InputSource class as was used to # parse it the first time, and we don't cache external entities # or XIncludes, so there is the possibility of those things # being resolved differently this time around. Oh well. elif uri in self._root.sources: content = self._root.sources[uri] source = inputsource(content, uri) if not content: content = source.stream.read() source = inputsource(cStringIO.StringIO(content), source.uri) #features = [(sax.FEATURE_PROCESS_XINCLUDES, True)] features, properties = [], [] stylesheet = self._parseSrc(source, features, properties) # Cache the string content for subsequent uses # e.g., xsl:import/xsl:include and document() self._root.sources[uri] = content return stylesheet def _parseSrc(self, isrc, features, properties): parser = sax.create_parser() parser.setContentHandler(self) for featurename, value in features: parser.setFeature(featurename, value) # Always set whitespace rules property parser.setProperty(sax.PROPERTY_WHITESPACE_RULES, _XSLT_WHITESPACE_STRIPPING) for propertyname, value in properties: parser.setProperty(propertyname, value) prev_source = self._input_source try: self._input_source = isrc try: parser.parse(isrc) except SAXParseException, e: e = e.getException() or e if isinstance(e, XsltError): raise e raise XsltError(XsltError.STYLESHEET_PARSE_ERROR, uri=isrc.uri, text=str(e)) finally: self._input_source = prev_source return self._root.stylesheet
en
0.655522
######################################################################## # amara/xslt/reader/__init__.py Classes for the creation of a stylesheet object # Whitespace stripping rules for a stylesheet: # preserve all whitespace within xsl:text elements; # strip whitespace from all other elements # pseudo-nodes for save/restore of variable bindings # The XSL attributes allowed on literal elements Stores the current state of the parser. Constructor arguments/instance variables: validation - validation state for the current containing node. localVariables - set of in-scope variable bindings to determine variable shadowing. forwardsCompatible - flag indicating whether or not forwards-compatible processing is enabled. currentNamespaces - set of in-scope namespaces for the current node. extensionNamespaces - set of namespaces defining extension elements outputNamespaces - set of in-scope namespaces for literal result elements This class can be used to read, from a variety of sources, a stylesheet and all its included and imported stylesheets, building from them a single, compact representation of an XSLT stylesheet tree (an Ft.Xml.Xslt.Stylesheet.Stylesheet object). This is done with the most efficient parsing method available, and avoids creating a Domlette document for each document it reads. # runtime instance variables Add a mapping of extension element names to classes to the existing mapping of extension elements. This should only be used for standalone uses of this class. The only known standalone use for this class is for creating compiled stylesheets. The benefits of compiled stylesheets are now so minor that this use case may also disappear and then so will this function. You have been warned. # -- ContentHandler interface -------------------------------------- Callback interface for SAX. # Save the current document state for nested parsing (inclusions) Callback interface for SAX. # Our root is always a document # We use a document for this because of error checking and # because we explicitly pass ownerDocument to the nodes as # they are created # for recursive include checks for xsl:include/xsl:import # namespaces added for the next element Callback interface for SAX. # ---------------------------------------------------------- # remove URI from recursive inclusion checking # ---------------------------------------------------------- # finalize the children for the document #root.children = tuple(state.nodes) # ---------------------------------------------------------- # finalize the stylesheet AST # An xsl:import or xsl:include # Merge the top-level elements into the "parent" stylesheet # IMPLEMENTATION NOTE: stack[-1] is the import/include element, # stack[-2] is the "parent" stylesheet #parent_node = stack[-2].node #for child in self._stylesheet.children: # child.parent = parent_node # A top-most stylesheet # An additional stylesheet (e.g., an <?xml-stylesheet ...?>); # treat it as an xsl:import into the "master" stylesheet. # Always update the precedence from the included stylesheet # because it may have contained imports thus increasing its # import precedence. # Merge the top-level elements into the "master" stylesheet #stylesheet.children += self._stylesheet.children #for child in self._stylesheet.children: # child.parent = stylesheet # Prepare for a possible subsequent parse. # Prepare the "master" stylesheet Callback interface for SAX. Callback interface for SAX. # ---------------------------------------------------------- # update in-scope namespaces # reset for next element # ---------------------------------------------------------- # get the class defining this element # We need to try to import (and cache) it # ---------------------------------------------------------- # verify that this element can be declared here #self._debug_validation(expandedName) # ignore whatever elements are defined within an undefined # element as an exception will occur when/if this element # is actually instantiated # save this state for next go round # ---------------------------------------------------------- # create the instance defining this element # -- XSLT element -------------------------------- # Handle attributes in the null-namespace #raise self._mutate_exception(e, qualifiedName) # Process attributes with a namespace-uri and check for # any illegal attributes in the null-namespace # XSLT Spec 2.6 - Combining Stylesheets # -- extension element ------------------------- # Handle attributes in the null-namespace #raise self._mutate_exception(e, qualifiedName) # Process attributes with a namespace-uri and check for # any illegal attributes in the null-namespace # -- literal result element ------------------------------ # prepare attributes for literal output # save information for literal output # Check for top-level result-element in null namespace Callback interface for SAX. # ---------------------------------------------------------- # verify that this element has all required content # ---------------------------------------------------------- # setup variable context # add context save/restore nodes # ---------------------------------------------------------- # finalize the children for this element #element.children = tuple(state.nodes) #for child in element.children: # if child.doesSetup: #s child.setup() # ---------------------------------------------------------- # update parent state # a literal result element as stylesheet # Reset the root's validation as it has already seen an element. # FIXME: use the prefix from the document for the XSL namespace # make this element the template's content # Note, this MUST index the stack as the stack has changed # due to the startElementNS() calls. # global variables # local variables # it is safe to ignore import precedence here # Copy on use Callback interface for SAX. # verify that the current element can have text children # If the parent can have element children, but not text nodes, # ignore pure whitespace nodes. This clarification is from # XSLT 2.0 [3.4] Whitespace Stripping. # e.g. xsl:stylesheet, xsl:apply-templates, xsl:choose #self._debug_validation(content_model.TEXT_NODE) #if (content_model.EMPTY in parent_state.validation or # not isspace(data)): #self._debug_validation(content_model.TEXT_NODE) # update validation # -- utility functions --------------------------------------------- # FIXME: create special inputsource for 4xslt command-line #for uri in self._alt_base_uris: # try: # new_href = self._input_source.getUriResolver().normalize(href, uri) # #Do we need to figure out a way to pass the hint here? # new_source = self._input_source.factory.fromUri(new_href) # break # except (OSError, IriError): # pass #else: # XSLT Spec 2.6.1, Detect circular references in stylesheets # Note, it is NOT an error to include/import the same stylesheet # multiple times, rather that it may lead to duplicate definitions # which are handled regardless (variables, params, templates, ...) # Always update the precedence as the included stylesheet may have # contained imports thus increasing the import precedence. # a whitespace separated list of prefixes # add the namespace URI to the set of extension namespaces # remove all matching namespace URIs # a whitespace separated list of prefixes # remove all matching namespace URIs # XSLT Spec 2.5 - Forwards-Compatible Processing # -- debugging routines -------------------------------------------- # -- parsing routines ---------------------------------------------- Read in a stylesheet source document from a Domlette and add it to the stylesheet tree. If a document with the same URI has already been read, the cached version will be used instead (so duplicate imports, includes, or stylesheet appends do not result in multiple reads). # check cache # We prefer to use an already-parsed doc, as it has had its # external entities and XIncludes resolved already # It's OK to use cached string content, but we have no idea # whether we're using the same InputSource class as was used to # parse it the first time, and we don't cache external entities # or XIncludes, so there is the possibility of those things # being resolved differently this time around. Oh well. # temporarily uncache it so `parse()` will process it; # `parse()` will add it back to the cache when finished # Cache for XSLT document() function Read in a stylesheet source document from an InputSource and add it to the stylesheet tree. If a document with the same URI has already been read, the cached version will be used instead (so duplicate imports, includes, or stylesheet appends do not result in multiple reads). #Check cache # We prefer to use an already-parsed doc, as it has had its # external entities and XIncludes resolved already # temporarily uncache it so fromDocument will process it; # fromDocument will add it back to the cache when finished # It's OK to use cached string content, but we have no idea # whether we're using the same InputSource class as was used to # parse it the first time, and we don't cache external entities # or XIncludes, so there is the possibility of those things # being resolved differently this time around. Oh well. #features = [(sax.FEATURE_PROCESS_XINCLUDES, True)] # Cache the string content for subsequent uses # e.g., xsl:import/xsl:include and document() # Always set whitespace rules property
2.439318
2
tests/onegov/election_day/models/test_subscriber.py
politbuero-kampagnen/onegov-cloud
0
6632157
from onegov.election_day.models import EmailSubscriber from onegov.election_day.models import SmsSubscriber from onegov.election_day.models import Subscriber def test_subscriber(session): session.add(Subscriber(address='endpoint', locale='de_CH')) session.add(EmailSubscriber(address='<EMAIL>', locale='fr_CH')) session.add(SmsSubscriber(address='+41791112233', locale='it_CH')) session.flush() assert session.query(Subscriber).count() == 3 subscriber = session.query(EmailSubscriber).one() assert subscriber.id assert subscriber.address == '<EMAIL>' assert subscriber.locale == 'fr_CH' subscriber = session.query(SmsSubscriber).one() assert subscriber.id assert subscriber.address == '+41791112233' assert subscriber.locale == 'it_CH'
from onegov.election_day.models import EmailSubscriber from onegov.election_day.models import SmsSubscriber from onegov.election_day.models import Subscriber def test_subscriber(session): session.add(Subscriber(address='endpoint', locale='de_CH')) session.add(EmailSubscriber(address='<EMAIL>', locale='fr_CH')) session.add(SmsSubscriber(address='+41791112233', locale='it_CH')) session.flush() assert session.query(Subscriber).count() == 3 subscriber = session.query(EmailSubscriber).one() assert subscriber.id assert subscriber.address == '<EMAIL>' assert subscriber.locale == 'fr_CH' subscriber = session.query(SmsSubscriber).one() assert subscriber.id assert subscriber.address == '+41791112233' assert subscriber.locale == 'it_CH'
none
1
2.394027
2
groundup/urls.py
onhan/free-site
0
6632158
<filename>groundup/urls.py """groundup URL Configuration The `urlpatterns` list routes URLs to views. For more information please see: https://docs.djangoproject.com/en/1.8/topics/http/urls/ Examples: Function views 1. Add an import: from my_app import views 2. Add a URL to urlpatterns: url(r'^$', views.home, name='home') Class-based views 1. Add an import: from other_app.views import Home 2. Add a URL to urlpatterns: url(r'^$', Home.as_view(), name='home') Including another URLconf 1. Add an import: from blog import urls as blog_urls 2. Add a URL to urlpatterns: url(r'^blog/', include(blog_urls)) """ from django.conf.urls import url from django.urls import include, path from django.contrib import admin from django.conf import settings from django.conf.urls.static import static from django.views.generic.base import TemplateView from django.views.generic.base import RedirectView from django.contrib.flatpages.sitemaps import FlatPageSitemap from django.contrib.flatpages import views from django.contrib.sitemaps import GenericSitemap from django.contrib.sitemaps.views import sitemap from newsroom.models import Article from newsroom.models import Author from gallery.models import Photograph from filebrowser.sites import site from ajax_select import urls as ajax_select_urls article_dict = { 'queryset': Article.objects.published(), 'date_field': 'published', } author_dict = { 'queryset': Author.objects.all(), 'date_field': 'modified', } photo_dict = { 'queryset': Photograph.objects.all(), 'date_field': 'modified', } app_name = 'groundup' urlpatterns = [ path('admin/filebrowser/', site.urls), path('grappelli/', include('grappelli.urls')), url(r'^ajax_select/', include(ajax_select_urls)), path('admin/login/', RedirectView.as_view(url='/accounts/login/')), path('admin/', admin.site.urls), path('imagegallery/', include('gallery.urls')), path('', include('newsroom.urls')), path('', include('payment.urls')), path('', include('letters.urls')), path('', include('agony.urls')), path('', include('security.urls')), path('', include('allauth_2fa.urls')), path('accounts/', include('allauth.urls')), url(r'^sitemap\.xml$', sitemap, {'sitemaps': {'articles': GenericSitemap(article_dict, priority=0.5), 'authors': GenericSitemap(author_dict, priority=0.5, changefreq='weekly'), 'photos': GenericSitemap(photo_dict, priority=0.5), 'flatpages': FlatPageSitemap}}, name='django.contrib.sitemaps.views.sitemap'), path('cache/', include('clearcache.urls', namespace="cache")), url(r'^robots\.txt', TemplateView.as_view(template_name='robots.txt', content_type='text/plain'), name='robots.txt'), url(r'^404testing', TemplateView.as_view(template_name='404.html'), name='test404'), url(r'^500testing', TemplateView.as_view(template_name='500.html'), name='test500'), ] + static(settings.STATIC_URL, document_root=settings.STATIC_ROOT) + \ static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT) if settings.DEBUG: import debug_toolbar urlpatterns += [ path('__debug__/', include(debug_toolbar.urls)), ] urlpatterns += [ url(r'^(?P<url>.*/)$', views.flatpage), ]
<filename>groundup/urls.py """groundup URL Configuration The `urlpatterns` list routes URLs to views. For more information please see: https://docs.djangoproject.com/en/1.8/topics/http/urls/ Examples: Function views 1. Add an import: from my_app import views 2. Add a URL to urlpatterns: url(r'^$', views.home, name='home') Class-based views 1. Add an import: from other_app.views import Home 2. Add a URL to urlpatterns: url(r'^$', Home.as_view(), name='home') Including another URLconf 1. Add an import: from blog import urls as blog_urls 2. Add a URL to urlpatterns: url(r'^blog/', include(blog_urls)) """ from django.conf.urls import url from django.urls import include, path from django.contrib import admin from django.conf import settings from django.conf.urls.static import static from django.views.generic.base import TemplateView from django.views.generic.base import RedirectView from django.contrib.flatpages.sitemaps import FlatPageSitemap from django.contrib.flatpages import views from django.contrib.sitemaps import GenericSitemap from django.contrib.sitemaps.views import sitemap from newsroom.models import Article from newsroom.models import Author from gallery.models import Photograph from filebrowser.sites import site from ajax_select import urls as ajax_select_urls article_dict = { 'queryset': Article.objects.published(), 'date_field': 'published', } author_dict = { 'queryset': Author.objects.all(), 'date_field': 'modified', } photo_dict = { 'queryset': Photograph.objects.all(), 'date_field': 'modified', } app_name = 'groundup' urlpatterns = [ path('admin/filebrowser/', site.urls), path('grappelli/', include('grappelli.urls')), url(r'^ajax_select/', include(ajax_select_urls)), path('admin/login/', RedirectView.as_view(url='/accounts/login/')), path('admin/', admin.site.urls), path('imagegallery/', include('gallery.urls')), path('', include('newsroom.urls')), path('', include('payment.urls')), path('', include('letters.urls')), path('', include('agony.urls')), path('', include('security.urls')), path('', include('allauth_2fa.urls')), path('accounts/', include('allauth.urls')), url(r'^sitemap\.xml$', sitemap, {'sitemaps': {'articles': GenericSitemap(article_dict, priority=0.5), 'authors': GenericSitemap(author_dict, priority=0.5, changefreq='weekly'), 'photos': GenericSitemap(photo_dict, priority=0.5), 'flatpages': FlatPageSitemap}}, name='django.contrib.sitemaps.views.sitemap'), path('cache/', include('clearcache.urls', namespace="cache")), url(r'^robots\.txt', TemplateView.as_view(template_name='robots.txt', content_type='text/plain'), name='robots.txt'), url(r'^404testing', TemplateView.as_view(template_name='404.html'), name='test404'), url(r'^500testing', TemplateView.as_view(template_name='500.html'), name='test500'), ] + static(settings.STATIC_URL, document_root=settings.STATIC_ROOT) + \ static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT) if settings.DEBUG: import debug_toolbar urlpatterns += [ path('__debug__/', include(debug_toolbar.urls)), ] urlpatterns += [ url(r'^(?P<url>.*/)$', views.flatpage), ]
en
0.614838
groundup URL Configuration The `urlpatterns` list routes URLs to views. For more information please see: https://docs.djangoproject.com/en/1.8/topics/http/urls/ Examples: Function views 1. Add an import: from my_app import views 2. Add a URL to urlpatterns: url(r'^$', views.home, name='home') Class-based views 1. Add an import: from other_app.views import Home 2. Add a URL to urlpatterns: url(r'^$', Home.as_view(), name='home') Including another URLconf 1. Add an import: from blog import urls as blog_urls 2. Add a URL to urlpatterns: url(r'^blog/', include(blog_urls))
2.435251
2
android/deps.bzl
Dig-Doug/rules_proto
0
6632159
load("@bazel_tools//tools/build_defs/repo:jvm.bzl", "jvm_maven_import_external") load( "//:deps.bzl", "build_bazel_rules_android", "com_google_protobuf", "com_google_protobuf_lite", "io_grpc_grpc_java", ) load( "//protobuf:deps.bzl", "protobuf", ) def com_google_guava_guava_android(**kwargs): if "com_google_guava_guava_android" not in native.existing_rules(): jvm_maven_import_external( name = "com_google_guava_guava_android", artifact = "com.google.guava:guava:27.0.1-android", server_urls = ["http://central.maven.org/maven2"], artifact_sha256 = "caf0955aed29a1e6d149f85cfb625a89161b5cf88e0e246552b7ffa358204e28", ) def android_proto_compile(**kwargs): protobuf(**kwargs) com_google_protobuf_lite(**kwargs) def android_grpc_compile(**kwargs): android_proto_compile(**kwargs) io_grpc_grpc_java(**kwargs) def android_proto_library(**kwargs): android_proto_compile(**kwargs) build_bazel_rules_android(**kwargs) com_google_guava_guava_android(**kwargs) def android_grpc_library(**kwargs): android_grpc_compile(**kwargs) android_proto_library(**kwargs)
load("@bazel_tools//tools/build_defs/repo:jvm.bzl", "jvm_maven_import_external") load( "//:deps.bzl", "build_bazel_rules_android", "com_google_protobuf", "com_google_protobuf_lite", "io_grpc_grpc_java", ) load( "//protobuf:deps.bzl", "protobuf", ) def com_google_guava_guava_android(**kwargs): if "com_google_guava_guava_android" not in native.existing_rules(): jvm_maven_import_external( name = "com_google_guava_guava_android", artifact = "com.google.guava:guava:27.0.1-android", server_urls = ["http://central.maven.org/maven2"], artifact_sha256 = "caf0955aed29a1e6d149f85cfb625a89161b5cf88e0e246552b7ffa358204e28", ) def android_proto_compile(**kwargs): protobuf(**kwargs) com_google_protobuf_lite(**kwargs) def android_grpc_compile(**kwargs): android_proto_compile(**kwargs) io_grpc_grpc_java(**kwargs) def android_proto_library(**kwargs): android_proto_compile(**kwargs) build_bazel_rules_android(**kwargs) com_google_guava_guava_android(**kwargs) def android_grpc_library(**kwargs): android_grpc_compile(**kwargs) android_proto_library(**kwargs)
none
1
1.518277
2
experiments/voe_mogaze.py
anish-pratheepkumar/anish-pratheepkumar.github.io
1
6632160
import os import sys import click project_dir = os.path.join(os.path.dirname(__file__), "..") sys.path.insert(0, project_dir) os.environ['PATH'] += os.pathsep + project_dir # ------------------------- from experiments import config @click.command() @click.option("--architecture", "-a", help='select one architecture: red OR prednet', default="prednet") @click.option("--stage_1", help='Execute Prediction Stage', default=True) @click.option("--avoid_goal", help='True for avoiding goal', default=False) def run(architecture, stage_1=True, avoid_goal=False): print("running, {} stage 1: {}, avoid_goal {}".format(architecture, stage_1, avoid_goal)) config.ARCHITECTURE = architecture config.ACTION = "p1_1" config.VIZ_VOE_CHULL = False config.AVOID_GOAL = avoid_goal from utils.evaluation.mogaze_vis import apply_mogaze_settings apply_mogaze_settings(avoid_goal=avoid_goal) from utils.evaluation import mogaze_gen_qpos_for_hulls if stage_1: mogaze_gen_qpos_for_hulls.run() config.reset_tf() from utils.data_mogaze_vis.mogaze_utils import build_env chull_viz_vol_occc_error.play(build_env, force_update=False, scenarios=[""]) from utils.evaluation import chull_viz_vol_occc_error if __name__ == '__main__': run() # =====================================================RED============================================================== # voc_avg_step_error = 52.050476178331344 # prediction_step | 80 | 160 | 320 | 400 | 600 | 720 | 880 | 1000 | # voc_error ± 0.5std (%) | 33.354 ± 8.13| 36.354 ± 8.60| 40.999 ± 9.90| 42.783 ± 10.25| 46.690 ± 11.05| 48.500 ± 11.27| 50.737 ± 11.45| 52.050 ± 11.39| # voc_error ± 0.5std (%) &$ 33.4 \pm 8.1$&$ 36.4 \pm 8.6$&$ 41.0 \pm 9.9$&$ 42.8 \pm 10.3$&$ 46.7 \pm 11.1$&$ 48.5 \pm 11.3$&$ 50.7 \pm 11.5$&$ 52.1 \pm 11.4$\\ # End time: 1624159094.5830145 # =====================================================PredNet========================================================== # prediction_step | 80 | 160 | 320 | 400 | 600 | 720 | 880 | 1000 | # voc_error ± std (%) | 14.832 ± 6.68| 17.682 ± 6.19| 23.536 ± 8.29| 26.041 ± 9.50| 31.637 ± 11.02| 34.106 ± 11.63| 37.335 ± 12.23| 39.510 ± 12.47| # voc_error ± std (%) $&$ 14.8 \pm 6.7$&$ 17.7 \pm 6.19$&$ 23.6 \pm 8.3$&$ 26.1 \pm 9.5$&$ 31.6 \pm 11.0$&$ 34.1 \pm 11.6$&$ 37.3 \pm 12.2$&$ 39.5 \pm 12.5$\\ # End time: 1624193836.6961882 # run("red") # run("red", True, False) # run("prednet", True, False) # Prednet MSM # run("prednet", False, True) #Prednet MSMwg # ==================================NEW====================================================================== # ==================Prednet MSM============= # prediction_step | 80 | 160 | 320 | 400 | 600 | 720 | 880 | 1000 | # voc_error ± std (%) | 15.71 & 18.57 & 23.97 & 26.74 & 32.06 & 34.44 & 37.70 & 39.82 \\ # ==================Prednet MSMwG============= # prediction_step | 80 | 160 | 320 | 400 | 600 | 720 | 880 | 1000 | # voc_error & 15.10 & 17.54 & 23.73 & 26.47 & 33.17 & 35.48 & 38.32 & 40.31 \\ # ==================RED======================= # prediction_step | 80 | 160 | 320 | 400 | 600 | 720 | 880 | 1000 | # voc_error & 32.94 & 35.78 & 40.53 & 42.36 & 46.36 & 48.02 & 50.21 & 51.56
import os import sys import click project_dir = os.path.join(os.path.dirname(__file__), "..") sys.path.insert(0, project_dir) os.environ['PATH'] += os.pathsep + project_dir # ------------------------- from experiments import config @click.command() @click.option("--architecture", "-a", help='select one architecture: red OR prednet', default="prednet") @click.option("--stage_1", help='Execute Prediction Stage', default=True) @click.option("--avoid_goal", help='True for avoiding goal', default=False) def run(architecture, stage_1=True, avoid_goal=False): print("running, {} stage 1: {}, avoid_goal {}".format(architecture, stage_1, avoid_goal)) config.ARCHITECTURE = architecture config.ACTION = "p1_1" config.VIZ_VOE_CHULL = False config.AVOID_GOAL = avoid_goal from utils.evaluation.mogaze_vis import apply_mogaze_settings apply_mogaze_settings(avoid_goal=avoid_goal) from utils.evaluation import mogaze_gen_qpos_for_hulls if stage_1: mogaze_gen_qpos_for_hulls.run() config.reset_tf() from utils.data_mogaze_vis.mogaze_utils import build_env chull_viz_vol_occc_error.play(build_env, force_update=False, scenarios=[""]) from utils.evaluation import chull_viz_vol_occc_error if __name__ == '__main__': run() # =====================================================RED============================================================== # voc_avg_step_error = 52.050476178331344 # prediction_step | 80 | 160 | 320 | 400 | 600 | 720 | 880 | 1000 | # voc_error ± 0.5std (%) | 33.354 ± 8.13| 36.354 ± 8.60| 40.999 ± 9.90| 42.783 ± 10.25| 46.690 ± 11.05| 48.500 ± 11.27| 50.737 ± 11.45| 52.050 ± 11.39| # voc_error ± 0.5std (%) &$ 33.4 \pm 8.1$&$ 36.4 \pm 8.6$&$ 41.0 \pm 9.9$&$ 42.8 \pm 10.3$&$ 46.7 \pm 11.1$&$ 48.5 \pm 11.3$&$ 50.7 \pm 11.5$&$ 52.1 \pm 11.4$\\ # End time: 1624159094.5830145 # =====================================================PredNet========================================================== # prediction_step | 80 | 160 | 320 | 400 | 600 | 720 | 880 | 1000 | # voc_error ± std (%) | 14.832 ± 6.68| 17.682 ± 6.19| 23.536 ± 8.29| 26.041 ± 9.50| 31.637 ± 11.02| 34.106 ± 11.63| 37.335 ± 12.23| 39.510 ± 12.47| # voc_error ± std (%) $&$ 14.8 \pm 6.7$&$ 17.7 \pm 6.19$&$ 23.6 \pm 8.3$&$ 26.1 \pm 9.5$&$ 31.6 \pm 11.0$&$ 34.1 \pm 11.6$&$ 37.3 \pm 12.2$&$ 39.5 \pm 12.5$\\ # End time: 1624193836.6961882 # run("red") # run("red", True, False) # run("prednet", True, False) # Prednet MSM # run("prednet", False, True) #Prednet MSMwg # ==================================NEW====================================================================== # ==================Prednet MSM============= # prediction_step | 80 | 160 | 320 | 400 | 600 | 720 | 880 | 1000 | # voc_error ± std (%) | 15.71 & 18.57 & 23.97 & 26.74 & 32.06 & 34.44 & 37.70 & 39.82 \\ # ==================Prednet MSMwG============= # prediction_step | 80 | 160 | 320 | 400 | 600 | 720 | 880 | 1000 | # voc_error & 15.10 & 17.54 & 23.73 & 26.47 & 33.17 & 35.48 & 38.32 & 40.31 \\ # ==================RED======================= # prediction_step | 80 | 160 | 320 | 400 | 600 | 720 | 880 | 1000 | # voc_error & 32.94 & 35.78 & 40.53 & 42.36 & 46.36 & 48.02 & 50.21 & 51.56
en
0.227106
# ------------------------- # =====================================================RED============================================================== # voc_avg_step_error = 52.050476178331344 # prediction_step | 80 | 160 | 320 | 400 | 600 | 720 | 880 | 1000 | # voc_error ± 0.5std (%) | 33.354 ± 8.13| 36.354 ± 8.60| 40.999 ± 9.90| 42.783 ± 10.25| 46.690 ± 11.05| 48.500 ± 11.27| 50.737 ± 11.45| 52.050 ± 11.39| # voc_error ± 0.5std (%) &$ 33.4 \pm 8.1$&$ 36.4 \pm 8.6$&$ 41.0 \pm 9.9$&$ 42.8 \pm 10.3$&$ 46.7 \pm 11.1$&$ 48.5 \pm 11.3$&$ 50.7 \pm 11.5$&$ 52.1 \pm 11.4$\\ # End time: 1624159094.5830145 # =====================================================PredNet========================================================== # prediction_step | 80 | 160 | 320 | 400 | 600 | 720 | 880 | 1000 | # voc_error ± std (%) | 14.832 ± 6.68| 17.682 ± 6.19| 23.536 ± 8.29| 26.041 ± 9.50| 31.637 ± 11.02| 34.106 ± 11.63| 37.335 ± 12.23| 39.510 ± 12.47| # voc_error ± std (%) $&$ 14.8 \pm 6.7$&$ 17.7 \pm 6.19$&$ 23.6 \pm 8.3$&$ 26.1 \pm 9.5$&$ 31.6 \pm 11.0$&$ 34.1 \pm 11.6$&$ 37.3 \pm 12.2$&$ 39.5 \pm 12.5$\\ # End time: 1624193836.6961882 # run("red") # run("red", True, False) # run("prednet", True, False) # Prednet MSM # run("prednet", False, True) #Prednet MSMwg # ==================================NEW====================================================================== # ==================Prednet MSM============= # prediction_step | 80 | 160 | 320 | 400 | 600 | 720 | 880 | 1000 | # voc_error ± std (%) | 15.71 & 18.57 & 23.97 & 26.74 & 32.06 & 34.44 & 37.70 & 39.82 \\ # ==================Prednet MSMwG============= # prediction_step | 80 | 160 | 320 | 400 | 600 | 720 | 880 | 1000 | # voc_error & 15.10 & 17.54 & 23.73 & 26.47 & 33.17 & 35.48 & 38.32 & 40.31 \\ # ==================RED======================= # prediction_step | 80 | 160 | 320 | 400 | 600 | 720 | 880 | 1000 | # voc_error & 32.94 & 35.78 & 40.53 & 42.36 & 46.36 & 48.02 & 50.21 & 51.56
2.010335
2
Exam6-practice/specialNumbers.py
nikolayvutov/Python
0
6632161
<reponame>nikolayvutov/Python n = int(input()) for i in range(1, 10): for j in range(1, 10): for k in range(1, 10): for l in range(1, 10): if n % i == 0 and n % j == 0 and n % k == 0 and n % l == 0: print('{0}{1}{2}{3}'.format(i, j, k ,l), end=' ')
n = int(input()) for i in range(1, 10): for j in range(1, 10): for k in range(1, 10): for l in range(1, 10): if n % i == 0 and n % j == 0 and n % k == 0 and n % l == 0: print('{0}{1}{2}{3}'.format(i, j, k ,l), end=' ')
none
1
3.445095
3
vision/camcalib/fusion.py
Photon26/wrs-main-210414
0
6632162
import cv2 import math import yaml import numpy as np from cv2 import aruco from sklearn import cluster import utiltools.robotmath as rm from pandaplotutils import pandactrl def trackobject_multicamfusion(camcaps, cammtxs, camdists, camrelhomos, aruco_dict, arucomarkersize = 100, nframe = 5, denoise = True, bandwidth=10): """ :param camcaps: a list of cv2.VideoCaptures :param cammtxs: a list of mtx for each of the camcaps :param camdists: as list of dist for each of the camcaps :param camrelhomos: a list of relative homogeneous matrices :param aruco_dict: NOTE this is not things like aruco.DICT_6x6_250, instead, it is the return value of aruco.Dictionary_get :param nframe: number of frames used for fusion :param denoise: :param bandwidth: the bandwidth for meanshift, a large bandwidth leads to tracking instead of clustering, a small bandwith will be very costly :return: author: weiwei date: 20190422 """ parameters = aruco.DetectorParameters_create() framelist = {} for i in range(nframe): for capid, cap in enumerate(camcaps): ret, frame = cap.read() corners, ids, rejectedImgPoints = aruco.detectMarkers(frame, aruco_dict, parameters=parameters, ids=np.array([[1,2,3,4]])) ids = ids.get() if ids is not None: rvecs, tvecs, _objPoints = aruco.estimatePoseSingleMarkers(corners, arucomarkersize, cammtxs[capid], camdists[capid]) for i in range(ids.size): rot = cv2.Rodrigues(rvecs[i])[0] pos = tvecs[i][0].ravel() if capid > 0: matinb = np.dot(rm.homoinverse(camrelhomos[capid-1]), rm.homobuild(pos, rot)) rot = matinb[:3, :3] pos = matinb[:3, 3] idslist = ids.ravel().tolist() if idslist[i] in framelist: framelist[idslist[i]].append([pos, rot]) else: framelist[idslist[i]] = [[pos, rot]] import time frameavglist = {} for id in framelist: posveclist = [frame[0] for frame in framelist[id]] rotmatlist = [frame[1] for frame in framelist[id]] if len(posveclist) >= nframe: posvecavg = rm.posvec_average(posveclist, bandwidth, denoise) rotmatavg = rm.rotmat_average(rotmatlist, bandwidth, denoise) frameavglist[id] = [posvecavg, rotmatavg] return frameavglist if __name__=='__main__': # squaremarkersize = 40 # # calibcharucoboard(7,5, squaremarkersize=squaremarkersize, imgspath='./camimgs0/', savename='cam0_calib.yaml') # calibcharucoboard(7,5, squaremarkersize=squaremarkersize, imgspath='./camimgs2/', savename='cam2_calib.yaml') # calibcharucoboard(7,5, squaremarkersize=squaremarkersize, imgspath='./camimgs4/', savename='cam4_calib.yaml') # find_rhomo(basecamyamlpath = 'cam0_calib.yaml', relcamyamlpath = 'cam2_calib.yaml', savename = 'homo_rb20.yaml') # find_rhomo(basecamyamlpath = 'cam0_calib.yaml', relcamyamlpath = 'cam4_calib.yaml', savename = 'homo_rb40.yaml') base = pandactrl.World(camp=[2700, 300, 2700], lookatpos=[0, 0, 0]) # framenp = base.pggen.genAxis() # framenp.reparentTo(base.render) # base.run() base.pggen.plotAxis(base.render) homo_rb20 = yaml.load(open('homo_rb20.yaml', 'r'), Loader=yaml.UnsafeLoader) homo_rb40 = yaml.load(open('homo_rb40.yaml', 'r'), Loader=yaml.UnsafeLoader) # draw in 3d to validate pandamat4homo_r2 = base.pg.np4ToMat4(rm.homoinverse(homo_rb20)) base.pggen.plotAxis(base.render, spos = pandamat4homo_r2.getRow3(3), pandamat3 = pandamat4homo_r2.getUpper3()) pandamat4homo_r4 = base.pg.np4ToMat4(rm.homoinverse(homo_rb40)) base.pggen.plotAxis(base.render, spos = pandamat4homo_r4.getRow3(3), pandamat3 = pandamat4homo_r4.getUpper3()) # show in videos mtx0, dist0, rvecs0, tvecs0, candfiles0 = yaml.load(open('cam0_calib.yaml', 'r'), Loader=yaml.UnsafeLoader) mtx2, dist2, rvecs2, tvecs2, candfiles2 = yaml.load(open('cam2_calib.yaml', 'r'), Loader=yaml.UnsafeLoader) mtx4, dist4, rvecs4, tvecs4, candfiles4 = yaml.load(open('cam4_calib.yaml', 'r'), Loader=yaml.UnsafeLoader) import time # arucomarkersize = int(40*.57) # aruco_dict = aruco.Dictionary_get(aruco.DICT_6X6_250) cap0 = cv2.VideoCapture(0) cap2 = cv2.VideoCapture(2) cap4 = cv2.VideoCapture(4) camcaps = [cap0, cap2, cap4] cammtxs = [mtx0, mtx2, mtx4] camdists = [dist0, dist2, dist4] camrelhomos = [homo_rb20, homo_rb40] aruco_dict = aruco.Dictionary_get(aruco.DICT_4X4_250) arucomarkersize = 100 nframe = 2 denoise = True framenplist = [[]] def updateview(framenplist, task): if len(framenplist[0]) > 0: for axisnp in framenplist[0]: axisnp.removeNode() framenplist[0] = [] tic = time.time() frameavglist = trackobject_multicamfusion(camcaps, cammtxs, camdists, camrelhomos, aruco_dict, arucomarkersize, nframe, denoise, bandwidth=arucomarkersize*.05) print(time.time()-tic) for id in frameavglist: posvecavg = frameavglist[id][0] rotmatavg = frameavglist[id][1] framenp = base.pggen.genAxis(spos=base.pg.npToV3(posvecavg), pandamat3=base.pg.npToMat3(rotmatavg)) framenp.reparentTo(base.render) framenplist[0].append(framenp) return task.again taskMgr.doMethodLater(0.01, updateview, "updateview", extraArgs=[framenplist], appendTask=True) base.run()
import cv2 import math import yaml import numpy as np from cv2 import aruco from sklearn import cluster import utiltools.robotmath as rm from pandaplotutils import pandactrl def trackobject_multicamfusion(camcaps, cammtxs, camdists, camrelhomos, aruco_dict, arucomarkersize = 100, nframe = 5, denoise = True, bandwidth=10): """ :param camcaps: a list of cv2.VideoCaptures :param cammtxs: a list of mtx for each of the camcaps :param camdists: as list of dist for each of the camcaps :param camrelhomos: a list of relative homogeneous matrices :param aruco_dict: NOTE this is not things like aruco.DICT_6x6_250, instead, it is the return value of aruco.Dictionary_get :param nframe: number of frames used for fusion :param denoise: :param bandwidth: the bandwidth for meanshift, a large bandwidth leads to tracking instead of clustering, a small bandwith will be very costly :return: author: weiwei date: 20190422 """ parameters = aruco.DetectorParameters_create() framelist = {} for i in range(nframe): for capid, cap in enumerate(camcaps): ret, frame = cap.read() corners, ids, rejectedImgPoints = aruco.detectMarkers(frame, aruco_dict, parameters=parameters, ids=np.array([[1,2,3,4]])) ids = ids.get() if ids is not None: rvecs, tvecs, _objPoints = aruco.estimatePoseSingleMarkers(corners, arucomarkersize, cammtxs[capid], camdists[capid]) for i in range(ids.size): rot = cv2.Rodrigues(rvecs[i])[0] pos = tvecs[i][0].ravel() if capid > 0: matinb = np.dot(rm.homoinverse(camrelhomos[capid-1]), rm.homobuild(pos, rot)) rot = matinb[:3, :3] pos = matinb[:3, 3] idslist = ids.ravel().tolist() if idslist[i] in framelist: framelist[idslist[i]].append([pos, rot]) else: framelist[idslist[i]] = [[pos, rot]] import time frameavglist = {} for id in framelist: posveclist = [frame[0] for frame in framelist[id]] rotmatlist = [frame[1] for frame in framelist[id]] if len(posveclist) >= nframe: posvecavg = rm.posvec_average(posveclist, bandwidth, denoise) rotmatavg = rm.rotmat_average(rotmatlist, bandwidth, denoise) frameavglist[id] = [posvecavg, rotmatavg] return frameavglist if __name__=='__main__': # squaremarkersize = 40 # # calibcharucoboard(7,5, squaremarkersize=squaremarkersize, imgspath='./camimgs0/', savename='cam0_calib.yaml') # calibcharucoboard(7,5, squaremarkersize=squaremarkersize, imgspath='./camimgs2/', savename='cam2_calib.yaml') # calibcharucoboard(7,5, squaremarkersize=squaremarkersize, imgspath='./camimgs4/', savename='cam4_calib.yaml') # find_rhomo(basecamyamlpath = 'cam0_calib.yaml', relcamyamlpath = 'cam2_calib.yaml', savename = 'homo_rb20.yaml') # find_rhomo(basecamyamlpath = 'cam0_calib.yaml', relcamyamlpath = 'cam4_calib.yaml', savename = 'homo_rb40.yaml') base = pandactrl.World(camp=[2700, 300, 2700], lookatpos=[0, 0, 0]) # framenp = base.pggen.genAxis() # framenp.reparentTo(base.render) # base.run() base.pggen.plotAxis(base.render) homo_rb20 = yaml.load(open('homo_rb20.yaml', 'r'), Loader=yaml.UnsafeLoader) homo_rb40 = yaml.load(open('homo_rb40.yaml', 'r'), Loader=yaml.UnsafeLoader) # draw in 3d to validate pandamat4homo_r2 = base.pg.np4ToMat4(rm.homoinverse(homo_rb20)) base.pggen.plotAxis(base.render, spos = pandamat4homo_r2.getRow3(3), pandamat3 = pandamat4homo_r2.getUpper3()) pandamat4homo_r4 = base.pg.np4ToMat4(rm.homoinverse(homo_rb40)) base.pggen.plotAxis(base.render, spos = pandamat4homo_r4.getRow3(3), pandamat3 = pandamat4homo_r4.getUpper3()) # show in videos mtx0, dist0, rvecs0, tvecs0, candfiles0 = yaml.load(open('cam0_calib.yaml', 'r'), Loader=yaml.UnsafeLoader) mtx2, dist2, rvecs2, tvecs2, candfiles2 = yaml.load(open('cam2_calib.yaml', 'r'), Loader=yaml.UnsafeLoader) mtx4, dist4, rvecs4, tvecs4, candfiles4 = yaml.load(open('cam4_calib.yaml', 'r'), Loader=yaml.UnsafeLoader) import time # arucomarkersize = int(40*.57) # aruco_dict = aruco.Dictionary_get(aruco.DICT_6X6_250) cap0 = cv2.VideoCapture(0) cap2 = cv2.VideoCapture(2) cap4 = cv2.VideoCapture(4) camcaps = [cap0, cap2, cap4] cammtxs = [mtx0, mtx2, mtx4] camdists = [dist0, dist2, dist4] camrelhomos = [homo_rb20, homo_rb40] aruco_dict = aruco.Dictionary_get(aruco.DICT_4X4_250) arucomarkersize = 100 nframe = 2 denoise = True framenplist = [[]] def updateview(framenplist, task): if len(framenplist[0]) > 0: for axisnp in framenplist[0]: axisnp.removeNode() framenplist[0] = [] tic = time.time() frameavglist = trackobject_multicamfusion(camcaps, cammtxs, camdists, camrelhomos, aruco_dict, arucomarkersize, nframe, denoise, bandwidth=arucomarkersize*.05) print(time.time()-tic) for id in frameavglist: posvecavg = frameavglist[id][0] rotmatavg = frameavglist[id][1] framenp = base.pggen.genAxis(spos=base.pg.npToV3(posvecavg), pandamat3=base.pg.npToMat3(rotmatavg)) framenp.reparentTo(base.render) framenplist[0].append(framenp) return task.again taskMgr.doMethodLater(0.01, updateview, "updateview", extraArgs=[framenplist], appendTask=True) base.run()
en
0.572291
:param camcaps: a list of cv2.VideoCaptures :param cammtxs: a list of mtx for each of the camcaps :param camdists: as list of dist for each of the camcaps :param camrelhomos: a list of relative homogeneous matrices :param aruco_dict: NOTE this is not things like aruco.DICT_6x6_250, instead, it is the return value of aruco.Dictionary_get :param nframe: number of frames used for fusion :param denoise: :param bandwidth: the bandwidth for meanshift, a large bandwidth leads to tracking instead of clustering, a small bandwith will be very costly :return: author: weiwei date: 20190422 # squaremarkersize = 40 # # calibcharucoboard(7,5, squaremarkersize=squaremarkersize, imgspath='./camimgs0/', savename='cam0_calib.yaml') # calibcharucoboard(7,5, squaremarkersize=squaremarkersize, imgspath='./camimgs2/', savename='cam2_calib.yaml') # calibcharucoboard(7,5, squaremarkersize=squaremarkersize, imgspath='./camimgs4/', savename='cam4_calib.yaml') # find_rhomo(basecamyamlpath = 'cam0_calib.yaml', relcamyamlpath = 'cam2_calib.yaml', savename = 'homo_rb20.yaml') # find_rhomo(basecamyamlpath = 'cam0_calib.yaml', relcamyamlpath = 'cam4_calib.yaml', savename = 'homo_rb40.yaml') # framenp = base.pggen.genAxis() # framenp.reparentTo(base.render) # base.run() # draw in 3d to validate # show in videos # arucomarkersize = int(40*.57) # aruco_dict = aruco.Dictionary_get(aruco.DICT_6X6_250)
2.262472
2
HydrothermalCoordination_Metaheuristics/EvolutionaryParticleSwarmOptimization/Functions/mutate.py
anaSilva2018/TryingPy
0
6632163
# -*- coding: utf-8 -*- """ @author: <NAME> """ import numpy as np def _popmut(cpar, nper, mdupl, indxa, indxb): mmut = np.zeros([indxa, 2*cpar.pop]) munif = np.zeros([indxb, 2*cpar.pop]) mgauss = np.zeros([indxb, 2*cpar.pop]) for i in range(indxb): for j in range(cpar.pop): mmut[i, j] = mdupl[i, j] for j in range(cpar.pop, 2*cpar.pop, 1): munif[nper, j] = np.random.uniform(0, 1, 1) mgauss[nper, j] = (np.power((-2*np.log(munif[nper, j])), 0.5))*np.cos(2*np.pi* munif[nper, j]) mmut[nper, j] = mdupl[nper, j] + cpar.tau*mgauss[nper, j] for i in range(nper): munif[i, j] = np.random.uniform(0, 1, 1) mgauss[i, j] = (np.power((-2*np.log(munif[i, j])), 0.5))*np.cos(2*np.pi* munif[i, j]) mmut[i, j] = mdupl[i, j] + mmut[nper, j]*mgauss[i, j] if mmut[i, j] > 1: mmut[i, j] = 1 elif mmut[i, j] < 0: mmut[i, j] = 0 return mmut
# -*- coding: utf-8 -*- """ @author: <NAME> """ import numpy as np def _popmut(cpar, nper, mdupl, indxa, indxb): mmut = np.zeros([indxa, 2*cpar.pop]) munif = np.zeros([indxb, 2*cpar.pop]) mgauss = np.zeros([indxb, 2*cpar.pop]) for i in range(indxb): for j in range(cpar.pop): mmut[i, j] = mdupl[i, j] for j in range(cpar.pop, 2*cpar.pop, 1): munif[nper, j] = np.random.uniform(0, 1, 1) mgauss[nper, j] = (np.power((-2*np.log(munif[nper, j])), 0.5))*np.cos(2*np.pi* munif[nper, j]) mmut[nper, j] = mdupl[nper, j] + cpar.tau*mgauss[nper, j] for i in range(nper): munif[i, j] = np.random.uniform(0, 1, 1) mgauss[i, j] = (np.power((-2*np.log(munif[i, j])), 0.5))*np.cos(2*np.pi* munif[i, j]) mmut[i, j] = mdupl[i, j] + mmut[nper, j]*mgauss[i, j] if mmut[i, j] > 1: mmut[i, j] = 1 elif mmut[i, j] < 0: mmut[i, j] = 0 return mmut
en
0.609409
# -*- coding: utf-8 -*- @author: <NAME>
2.051955
2
crawling_yes24.py
sourcery-ai-bot/github-action-with-python
0
6632164
<gh_stars>0 import requests from bs4 import BeautifulSoup def parsing_beautifulsoup(url): """ 뷰티풀 수프로 파싱하는 함수 :param url: paring할 URL. 여기선 YES24 Link :return: BeautifulSoup soup Object """ data = requests.get(url) html = data.text return BeautifulSoup(html, 'html.parser') def extract_book_data(soup): """ BeautifulSoup Object에서 book data를 추출하는 함수 :param soup: BeautifulSoup soup Object :return: contents(str) """ upload_contents = '' new_books = soup.select(".goodsTxtInfo") url_prefix = "http://www.yes24.com" for new_book in new_books: book_name = new_book.select("a")[0].text url_suffix = new_book.select("a")[1].attrs['href'] url = url_prefix + url_suffix price = new_book.select(".priceB")[0].text content = f"<a href={url}>" + book_name + "</a>" + ", " + price + "<br/>\n" upload_contents += content return upload_contents
import requests from bs4 import BeautifulSoup def parsing_beautifulsoup(url): """ 뷰티풀 수프로 파싱하는 함수 :param url: paring할 URL. 여기선 YES24 Link :return: BeautifulSoup soup Object """ data = requests.get(url) html = data.text return BeautifulSoup(html, 'html.parser') def extract_book_data(soup): """ BeautifulSoup Object에서 book data를 추출하는 함수 :param soup: BeautifulSoup soup Object :return: contents(str) """ upload_contents = '' new_books = soup.select(".goodsTxtInfo") url_prefix = "http://www.yes24.com" for new_book in new_books: book_name = new_book.select("a")[0].text url_suffix = new_book.select("a")[1].attrs['href'] url = url_prefix + url_suffix price = new_book.select(".priceB")[0].text content = f"<a href={url}>" + book_name + "</a>" + ", " + price + "<br/>\n" upload_contents += content return upload_contents
ko
0.697257
뷰티풀 수프로 파싱하는 함수 :param url: paring할 URL. 여기선 YES24 Link :return: BeautifulSoup soup Object BeautifulSoup Object에서 book data를 추출하는 함수 :param soup: BeautifulSoup soup Object :return: contents(str)
3.505109
4
test/alignat_tst.py
ikucan/MathsMonkey
0
6632165
import numpy as np from pylatex import Document, Section, Subsection, Tabular, Math, TikZ, Axis, \ Plot, Figure, Matrix, Alignat from pylatex.utils import italic import os if __name__ == '__main__': image_filename = os.path.join(os.path.dirname(__file__), 'kitten.jpg') geometry_options = {"tmargin": "1cm", "lmargin": "10cm"} doc = Document(geometry_options=geometry_options) with doc.create(Section('The simple stuff')): doc.append('Some regular text and some') doc.append(italic('italic text. ')) doc.append('\nAlso some crazy characters: $&#{}') with doc.create(Subsection('Math that is incorrect')): doc.append(Math(data=['2*3', '=', 9])) with doc.create(Subsection('Table of something')): with doc.create(Tabular('rc|cl')) as table: table.add_hline() table.add_row((1, 2, 3, 4)) table.add_hline(1, 2) table.add_empty_row() table.add_row((4, 5, 6, 7)) a = np.array([[100, 10, 20]]).T M = np.matrix([[2, 3, 4], [0, 0, 1], [0, 0, 2]]) with doc.create(Section('The fancy stuff')): with doc.create(Subsection('Correct matrix equations')): doc.append(Math(data=[Matrix(M), Matrix(a), '=', Matrix(M * a)])) with doc.create(Subsection('Alignat math environment')): with doc.create(Alignat(numbering=False, escape=False)) as agn: agn.append(r'\frac{a}{b} &= 0 \\') agn.append(r'\frac{a}{b} &= 0 \\') agn.extend([Matrix(M), Matrix(a), '&=', Matrix(M * a)]) with doc.create(Subsection('Beautiful graphs')): with doc.create(TikZ()): plot_options = 'height=4cm, width=6cm, grid=major' with doc.create(Axis(options=plot_options)) as plot: plot.append(Plot(name='model', func='-x^5 - 242')) coordinates = [ (-4.77778, 2027.60977), (-3.55556, 347.84069), (-2.33333, 22.58953), (-1.11111, -493.50066), (0.11111, 46.66082), (1.33333, -205.56286), (2.55556, -341.40638), (3.77778, -1169.24780), (5.00000, -3269.56775), ] plot.append(Plot(name='estimate', coordinates=coordinates)) with doc.create(Subsection('Cute kitten pictures')): with doc.create(Figure(position='h!')) as kitten_pic: kitten_pic.add_image(image_filename, width='120px') kitten_pic.add_caption('Look it\'s on its back') doc.generate_pdf('full', clean_tex=False)
import numpy as np from pylatex import Document, Section, Subsection, Tabular, Math, TikZ, Axis, \ Plot, Figure, Matrix, Alignat from pylatex.utils import italic import os if __name__ == '__main__': image_filename = os.path.join(os.path.dirname(__file__), 'kitten.jpg') geometry_options = {"tmargin": "1cm", "lmargin": "10cm"} doc = Document(geometry_options=geometry_options) with doc.create(Section('The simple stuff')): doc.append('Some regular text and some') doc.append(italic('italic text. ')) doc.append('\nAlso some crazy characters: $&#{}') with doc.create(Subsection('Math that is incorrect')): doc.append(Math(data=['2*3', '=', 9])) with doc.create(Subsection('Table of something')): with doc.create(Tabular('rc|cl')) as table: table.add_hline() table.add_row((1, 2, 3, 4)) table.add_hline(1, 2) table.add_empty_row() table.add_row((4, 5, 6, 7)) a = np.array([[100, 10, 20]]).T M = np.matrix([[2, 3, 4], [0, 0, 1], [0, 0, 2]]) with doc.create(Section('The fancy stuff')): with doc.create(Subsection('Correct matrix equations')): doc.append(Math(data=[Matrix(M), Matrix(a), '=', Matrix(M * a)])) with doc.create(Subsection('Alignat math environment')): with doc.create(Alignat(numbering=False, escape=False)) as agn: agn.append(r'\frac{a}{b} &= 0 \\') agn.append(r'\frac{a}{b} &= 0 \\') agn.extend([Matrix(M), Matrix(a), '&=', Matrix(M * a)]) with doc.create(Subsection('Beautiful graphs')): with doc.create(TikZ()): plot_options = 'height=4cm, width=6cm, grid=major' with doc.create(Axis(options=plot_options)) as plot: plot.append(Plot(name='model', func='-x^5 - 242')) coordinates = [ (-4.77778, 2027.60977), (-3.55556, 347.84069), (-2.33333, 22.58953), (-1.11111, -493.50066), (0.11111, 46.66082), (1.33333, -205.56286), (2.55556, -341.40638), (3.77778, -1169.24780), (5.00000, -3269.56775), ] plot.append(Plot(name='estimate', coordinates=coordinates)) with doc.create(Subsection('Cute kitten pictures')): with doc.create(Figure(position='h!')) as kitten_pic: kitten_pic.add_image(image_filename, width='120px') kitten_pic.add_caption('Look it\'s on its back') doc.generate_pdf('full', clean_tex=False)
none
1
2.750823
3
app/main/models/movies.py
NiHighlism/Minerva
4
6632166
<reponame>NiHighlism/Minerva """ DB Model for Movies table and relevant junction tables """ import datetime import json from sqlalchemy.sql import and_, select from app.main import db, login_manager from app.main.models.movieSearches import SearchableMixin class Movie(SearchableMixin, db.Model): """ Description of User model. Columns ----------- :id: int [pk] :user_id: int [Foreign Key -> User.id] :imdb_ID: varchar(128) [not NULL] :title: Text [not NULL] :year: int :release_date: DateTime :runtime: int :genre: JSON :director: JSON :writer: JSON :actors: JSON :plot: Text :language: JSON :country: JSON :awards: Text :ratings: JSON :imdb_rating: Float :rotten_tomatoes: int :metascore: int :poster_URL: varchar(255) :box_office: varchar(255) :added_to_db: DateTime """ # Columns id = db.Column(db.Integer, primary_key=True) parent_user_id = db.Column(db.Integer, db.ForeignKey('user.id')) imdb_ID = db.Column(db.String(128), unique=True, nullable=False) title = db.Column(db.Text, nullable=False) year = db.Column(db.Integer) release_date = db.Column(db.String(128)) runtime = db.Column(db.String(128)) plot = db.Column(db.Text) genre = db.Column(db.JSON) director = db.Column(db.JSON) writer = db.Column(db.JSON) actors = db.Column(db.JSON) language = db.Column(db.JSON) country = db.Column(db.JSON) awards = db.Column(db.Text) imdb_rating = db.Column(db.String(128)) rotten_tomatoes = db.Column(db.String(128)) metascore = db.Column(db.String(128)) poster_url = db.Column(db.String(255)) box_office = db.Column(db.String(128)) added_time = db.Column(db.DateTime) __searchable__ = ['title', 'year', 'genre', 'director', 'actors', 'language', 'country'] def __init__(self, imdb_ID, title, year, release_date, runtime, genre, director, writer, actors, plot, language, country, awards, imdb_rating, rotten_tomatoes, metascore, poster_url, box_office): self.imdb_ID = imdb_ID self.title = title self.year = year self.release_date = release_date self.runtime = runtime self.genre = genre self.director = director self.writer = writer self.actors = actors self.plot = plot self.language = language self.country = country self.awards = awards self.imdb_rating = imdb_rating self.rotten_tomatoes = rotten_tomatoes self.metascore = metascore self.poster_url = poster_url self.box_office = box_office self.added_time = datetime.datetime.now() db.session.add(self) db.session.commit() def update_col(self, key, value): setattr(self, key, value) db.session.commit()
""" DB Model for Movies table and relevant junction tables """ import datetime import json from sqlalchemy.sql import and_, select from app.main import db, login_manager from app.main.models.movieSearches import SearchableMixin class Movie(SearchableMixin, db.Model): """ Description of User model. Columns ----------- :id: int [pk] :user_id: int [Foreign Key -> User.id] :imdb_ID: varchar(128) [not NULL] :title: Text [not NULL] :year: int :release_date: DateTime :runtime: int :genre: JSON :director: JSON :writer: JSON :actors: JSON :plot: Text :language: JSON :country: JSON :awards: Text :ratings: JSON :imdb_rating: Float :rotten_tomatoes: int :metascore: int :poster_URL: varchar(255) :box_office: varchar(255) :added_to_db: DateTime """ # Columns id = db.Column(db.Integer, primary_key=True) parent_user_id = db.Column(db.Integer, db.ForeignKey('user.id')) imdb_ID = db.Column(db.String(128), unique=True, nullable=False) title = db.Column(db.Text, nullable=False) year = db.Column(db.Integer) release_date = db.Column(db.String(128)) runtime = db.Column(db.String(128)) plot = db.Column(db.Text) genre = db.Column(db.JSON) director = db.Column(db.JSON) writer = db.Column(db.JSON) actors = db.Column(db.JSON) language = db.Column(db.JSON) country = db.Column(db.JSON) awards = db.Column(db.Text) imdb_rating = db.Column(db.String(128)) rotten_tomatoes = db.Column(db.String(128)) metascore = db.Column(db.String(128)) poster_url = db.Column(db.String(255)) box_office = db.Column(db.String(128)) added_time = db.Column(db.DateTime) __searchable__ = ['title', 'year', 'genre', 'director', 'actors', 'language', 'country'] def __init__(self, imdb_ID, title, year, release_date, runtime, genre, director, writer, actors, plot, language, country, awards, imdb_rating, rotten_tomatoes, metascore, poster_url, box_office): self.imdb_ID = imdb_ID self.title = title self.year = year self.release_date = release_date self.runtime = runtime self.genre = genre self.director = director self.writer = writer self.actors = actors self.plot = plot self.language = language self.country = country self.awards = awards self.imdb_rating = imdb_rating self.rotten_tomatoes = rotten_tomatoes self.metascore = metascore self.poster_url = poster_url self.box_office = box_office self.added_time = datetime.datetime.now() db.session.add(self) db.session.commit() def update_col(self, key, value): setattr(self, key, value) db.session.commit()
en
0.481977
DB Model for Movies table and relevant junction tables Description of User model. Columns ----------- :id: int [pk] :user_id: int [Foreign Key -> User.id] :imdb_ID: varchar(128) [not NULL] :title: Text [not NULL] :year: int :release_date: DateTime :runtime: int :genre: JSON :director: JSON :writer: JSON :actors: JSON :plot: Text :language: JSON :country: JSON :awards: Text :ratings: JSON :imdb_rating: Float :rotten_tomatoes: int :metascore: int :poster_URL: varchar(255) :box_office: varchar(255) :added_to_db: DateTime # Columns
2.994666
3
usr/share/pyshared/ajenti/plugins/network/api.py
lupyuen/RaspberryPiImage
7
6632167
import psutil from ajenti.api import * from ajenti.ui import * @plugin class NetworkManager (BasePlugin): def get_devices(self): return psutil.net_io_counters(pernic=True).keys() @interface class INetworkConfig (object): interfaces = {} @property def interface_list(self): return self.interfaces.values() def rescan(self): pass def save(self): pass @interface class INetworkConfigBit (object): def apply(self): pass @plugin class NetworkConfigBit (UIElement, INetworkConfigBit): cls = 'unknown' iface = None title = 'Unknown' typeid = 'box' class NetworkInterface(object): def __init__(self): self.up = False self.auto = False self.name = '' self.devclass = '' self.addressing = 'static' self.bits = [] self.params = {'address': '0.0.0.0'} self.type = '' self.editable = True def __getitem__(self, idx): if idx in self.params: return self.params[idx] else: return '' def __setitem__(self, idx, val): self.params[idx] = val def add_bits(self, ui): for cls in INetworkConfigBit.get_classes(): if cls.cls in self.bit_classes: b = cls.new(ui) b.iface = self b.refresh() self.bits.append(b)
import psutil from ajenti.api import * from ajenti.ui import * @plugin class NetworkManager (BasePlugin): def get_devices(self): return psutil.net_io_counters(pernic=True).keys() @interface class INetworkConfig (object): interfaces = {} @property def interface_list(self): return self.interfaces.values() def rescan(self): pass def save(self): pass @interface class INetworkConfigBit (object): def apply(self): pass @plugin class NetworkConfigBit (UIElement, INetworkConfigBit): cls = 'unknown' iface = None title = 'Unknown' typeid = 'box' class NetworkInterface(object): def __init__(self): self.up = False self.auto = False self.name = '' self.devclass = '' self.addressing = 'static' self.bits = [] self.params = {'address': '0.0.0.0'} self.type = '' self.editable = True def __getitem__(self, idx): if idx in self.params: return self.params[idx] else: return '' def __setitem__(self, idx, val): self.params[idx] = val def add_bits(self, ui): for cls in INetworkConfigBit.get_classes(): if cls.cls in self.bit_classes: b = cls.new(ui) b.iface = self b.refresh() self.bits.append(b)
none
1
1.979867
2
qdmr_parsing/model/rule_based/rule_based_model.py
justeuer/Break
38
6632168
<filename>qdmr_parsing/model/rule_based/rule_based_model.py import re from model.rule_based.decompose_rules import * from model.model_base import ModelBase class RuleBasedModel(ModelBase): def __init__(self): super(RuleBasedModel, self).__init__() self.prefixes_to_remove = ["what is", "what are", "who is", "who are", "who was", "who were", "in what", "in which", "show me", "return me", "give me", "can you list", "i'd like to see", "i would like", "do you have", "what", "which", "list", "show", "return", "find"] # TODO: consider keeping question marks, which improve tagger accuracy # (e.g. "Where did the illustrator of \"De Divina Proportione\" die?"). self.suffixes_to_remove = ["?", "?\"", ".", "please"] self.infixes_to_substitute = [ ("are there", "(.*are) there(.*)", lambda x: x.group(1) + x.group(2)), ("were there", "(.*were) there(.*)", lambda x: x.group(1) + x.group(2)) ] self.rules = {"single_prep": DecomposeRuleSinglePrep(), "superlative": DecomposeRuleSuperlative(), "conjunction": DecomposeRuleConjunction(), "subj_do_have": DecomposeRuleSubjDoHave(), "do_subj": DecomposeRuleDoSubj(), "relcl": DecomposeRuleRelcl(), "how_many": DecomposeRuleHowMany(), "be_auxpass": DecomposeRuleBeAuxpass(), "be_root": DecomposeRuleBeRoot(), "multi_prep": DecomposeRuleMultiPrep(), "acl_verb": DecomposeRuleAclVerb()} def _clean(self, question): """Simplify the question by removing extra unnecessary parts of it, if exist.""" for prefix in self.prefixes_to_remove: if question.lower().startswith(prefix): question = question[len(prefix):].strip() break for suffix in self.suffixes_to_remove: if question.lower().endswith(suffix): question = question[:-len(suffix)].strip() break for infix in self.infixes_to_substitute: if infix[0] in question.lower(): question = re.sub(infix[1], infix[2], question).strip() break return question def _get_num_sentences(self, question): parsed = self.parser(question) return len([sent for sent in parsed.sents]) def _get_multi_sent_decomposition(self, question): parsed = self.parser(question) sents = [sent.text for sent in parsed.sents] # extract mention-reference sentence pairs replace_pairs = [] if parsed._.coref_clusters is not None: for cluster in parsed._.coref_clusters: main_sent = cluster.main.sent.text main_sent_index = sents.index(main_sent) for mention in cluster.mentions: if mention != cluster.main: mention_sent = mention.sent.text mention_sent_index = sents.index(mention_sent) if main_sent_index != mention_sent_index: replace_pairs.append((mention, main_sent_index)) # in case there is no coref, treat the text as a single sentence if not replace_pairs: return [] # replace any mention with the corresponding reference sentence index tokens = [token.text for token in parsed] for (mention, ref_sent_index) in replace_pairs: remove_indices = [x for x in range(mention.start, mention.end)][::-1] for index in remove_indices: tokens.pop(index) tokens.insert(mention.start, "@@{}@@".format(ref_sent_index+1)) # parse each sentence separately question_coref = self.parser(' '.join(tokens)) sents_coref = [sent.text for sent in question_coref.sents] return [self._parse(self._clean(sent)) for sent in sents_coref] def _update_decomposition(self, decomposition, i, decomposed): # remove non-decomposed part decomposition_previous_len = len(decomposition) decomposition.remove(decomposition[i]) # fix references in text following the decomposed part, by increasing it by len(decomposed) - 1. # this way, if the reference was to the i'th position (which is now decomposed), it will be updated # to the last part of the decomposition. for j in range(i+1, decomposition_previous_len): # -1 because we removed one element updated_part = re.sub("@@(\d\d)?@@", lambda x: "@@" + str(int(x.group(1)) + len(decomposed) - 1) + "@@", decomposition[j-1].text) decomposition[j-1] = self._parse(updated_part) # insert decomposed parts one by one for part in decomposed[::-1]: decomposition.insert(i, self._parse(part)) return decomposition def _decompose(self, question, verbose): trace = [] num_sentences = self._get_num_sentences(question) if num_sentences > 1: decomposition = self._get_multi_sent_decomposition(question) if not decomposition: decomposition = [self._parse(self._clean(question))] else: trace.append("multi_sent_coref") else: decomposition = [self._parse(self._clean(question))] if verbose: print(decomposition) while True: is_decomposed = False for i, part in enumerate(decomposition): decomposed = None if self.rules["be_root"].check(part, i + 1): decomposed = self.rules["be_root"].decompose() trace.append("be_root") elif self.rules["be_auxpass"].check(part, i + 1): decomposed = self.rules["be_auxpass"].decompose() trace.append("be_auxpass") elif self.rules["do_subj"].check(part, i + 1): decomposed = self.rules["do_subj"].decompose() trace.append("do_subj") elif self.rules["subj_do_have"].check(part, i+1): decomposed = self.rules["subj_do_have"].decompose() trace.append("subj_do_have") elif self.rules["conjunction"].check(part, i+1): decomposed = self.rules["conjunction"].decompose() trace.append("conjunction") elif self.rules["how_many"].check(part, i+1): decomposed = self.rules["how_many"].decompose() trace.append("how_many") elif self.rules["multi_prep"].check(part, i+1): decomposed = self.rules["multi_prep"].decompose() trace.append("multi_prep") elif self.rules["single_prep"].check(part, i+1): # check that "relcl" should not be applied single_prep_index = self.rules["single_prep"].prep_index if self.rules["relcl"].check(part, i + 1) and \ self.rules["relcl"].check_relcl_contains_index(single_prep_index): decomposed = self.rules["relcl"].decompose() trace.append("relcl") else: decomposed = self.rules["single_prep"].decompose() trace.append("single_prep") elif self.rules["relcl"].check(part, i+1): decomposed = self.rules["relcl"].decompose() trace.append("relcl") elif self.rules["superlative"].check(part, i+1): decomposed = self.rules["superlative"].decompose() trace.append("superlative") elif self.rules["acl_verb"].check(part, i+1): decomposed = self.rules["acl_verb"].decompose() trace.append("acl_verb") if decomposed: decomposition = self._update_decomposition(decomposition, i, decomposed) is_decomposed = True if verbose: print(decomposition) if not is_decomposed: break return decomposition, trace
<filename>qdmr_parsing/model/rule_based/rule_based_model.py import re from model.rule_based.decompose_rules import * from model.model_base import ModelBase class RuleBasedModel(ModelBase): def __init__(self): super(RuleBasedModel, self).__init__() self.prefixes_to_remove = ["what is", "what are", "who is", "who are", "who was", "who were", "in what", "in which", "show me", "return me", "give me", "can you list", "i'd like to see", "i would like", "do you have", "what", "which", "list", "show", "return", "find"] # TODO: consider keeping question marks, which improve tagger accuracy # (e.g. "Where did the illustrator of \"De Divina Proportione\" die?"). self.suffixes_to_remove = ["?", "?\"", ".", "please"] self.infixes_to_substitute = [ ("are there", "(.*are) there(.*)", lambda x: x.group(1) + x.group(2)), ("were there", "(.*were) there(.*)", lambda x: x.group(1) + x.group(2)) ] self.rules = {"single_prep": DecomposeRuleSinglePrep(), "superlative": DecomposeRuleSuperlative(), "conjunction": DecomposeRuleConjunction(), "subj_do_have": DecomposeRuleSubjDoHave(), "do_subj": DecomposeRuleDoSubj(), "relcl": DecomposeRuleRelcl(), "how_many": DecomposeRuleHowMany(), "be_auxpass": DecomposeRuleBeAuxpass(), "be_root": DecomposeRuleBeRoot(), "multi_prep": DecomposeRuleMultiPrep(), "acl_verb": DecomposeRuleAclVerb()} def _clean(self, question): """Simplify the question by removing extra unnecessary parts of it, if exist.""" for prefix in self.prefixes_to_remove: if question.lower().startswith(prefix): question = question[len(prefix):].strip() break for suffix in self.suffixes_to_remove: if question.lower().endswith(suffix): question = question[:-len(suffix)].strip() break for infix in self.infixes_to_substitute: if infix[0] in question.lower(): question = re.sub(infix[1], infix[2], question).strip() break return question def _get_num_sentences(self, question): parsed = self.parser(question) return len([sent for sent in parsed.sents]) def _get_multi_sent_decomposition(self, question): parsed = self.parser(question) sents = [sent.text for sent in parsed.sents] # extract mention-reference sentence pairs replace_pairs = [] if parsed._.coref_clusters is not None: for cluster in parsed._.coref_clusters: main_sent = cluster.main.sent.text main_sent_index = sents.index(main_sent) for mention in cluster.mentions: if mention != cluster.main: mention_sent = mention.sent.text mention_sent_index = sents.index(mention_sent) if main_sent_index != mention_sent_index: replace_pairs.append((mention, main_sent_index)) # in case there is no coref, treat the text as a single sentence if not replace_pairs: return [] # replace any mention with the corresponding reference sentence index tokens = [token.text for token in parsed] for (mention, ref_sent_index) in replace_pairs: remove_indices = [x for x in range(mention.start, mention.end)][::-1] for index in remove_indices: tokens.pop(index) tokens.insert(mention.start, "@@{}@@".format(ref_sent_index+1)) # parse each sentence separately question_coref = self.parser(' '.join(tokens)) sents_coref = [sent.text for sent in question_coref.sents] return [self._parse(self._clean(sent)) for sent in sents_coref] def _update_decomposition(self, decomposition, i, decomposed): # remove non-decomposed part decomposition_previous_len = len(decomposition) decomposition.remove(decomposition[i]) # fix references in text following the decomposed part, by increasing it by len(decomposed) - 1. # this way, if the reference was to the i'th position (which is now decomposed), it will be updated # to the last part of the decomposition. for j in range(i+1, decomposition_previous_len): # -1 because we removed one element updated_part = re.sub("@@(\d\d)?@@", lambda x: "@@" + str(int(x.group(1)) + len(decomposed) - 1) + "@@", decomposition[j-1].text) decomposition[j-1] = self._parse(updated_part) # insert decomposed parts one by one for part in decomposed[::-1]: decomposition.insert(i, self._parse(part)) return decomposition def _decompose(self, question, verbose): trace = [] num_sentences = self._get_num_sentences(question) if num_sentences > 1: decomposition = self._get_multi_sent_decomposition(question) if not decomposition: decomposition = [self._parse(self._clean(question))] else: trace.append("multi_sent_coref") else: decomposition = [self._parse(self._clean(question))] if verbose: print(decomposition) while True: is_decomposed = False for i, part in enumerate(decomposition): decomposed = None if self.rules["be_root"].check(part, i + 1): decomposed = self.rules["be_root"].decompose() trace.append("be_root") elif self.rules["be_auxpass"].check(part, i + 1): decomposed = self.rules["be_auxpass"].decompose() trace.append("be_auxpass") elif self.rules["do_subj"].check(part, i + 1): decomposed = self.rules["do_subj"].decompose() trace.append("do_subj") elif self.rules["subj_do_have"].check(part, i+1): decomposed = self.rules["subj_do_have"].decompose() trace.append("subj_do_have") elif self.rules["conjunction"].check(part, i+1): decomposed = self.rules["conjunction"].decompose() trace.append("conjunction") elif self.rules["how_many"].check(part, i+1): decomposed = self.rules["how_many"].decompose() trace.append("how_many") elif self.rules["multi_prep"].check(part, i+1): decomposed = self.rules["multi_prep"].decompose() trace.append("multi_prep") elif self.rules["single_prep"].check(part, i+1): # check that "relcl" should not be applied single_prep_index = self.rules["single_prep"].prep_index if self.rules["relcl"].check(part, i + 1) and \ self.rules["relcl"].check_relcl_contains_index(single_prep_index): decomposed = self.rules["relcl"].decompose() trace.append("relcl") else: decomposed = self.rules["single_prep"].decompose() trace.append("single_prep") elif self.rules["relcl"].check(part, i+1): decomposed = self.rules["relcl"].decompose() trace.append("relcl") elif self.rules["superlative"].check(part, i+1): decomposed = self.rules["superlative"].decompose() trace.append("superlative") elif self.rules["acl_verb"].check(part, i+1): decomposed = self.rules["acl_verb"].decompose() trace.append("acl_verb") if decomposed: decomposition = self._update_decomposition(decomposition, i, decomposed) is_decomposed = True if verbose: print(decomposition) if not is_decomposed: break return decomposition, trace
en
0.911877
# TODO: consider keeping question marks, which improve tagger accuracy # (e.g. "Where did the illustrator of \"De Divina Proportione\" die?"). Simplify the question by removing extra unnecessary parts of it, if exist. # extract mention-reference sentence pairs # in case there is no coref, treat the text as a single sentence # replace any mention with the corresponding reference sentence index # parse each sentence separately # remove non-decomposed part # fix references in text following the decomposed part, by increasing it by len(decomposed) - 1. # this way, if the reference was to the i'th position (which is now decomposed), it will be updated # to the last part of the decomposition. # -1 because we removed one element # insert decomposed parts one by one # check that "relcl" should not be applied
2.713692
3
venv/Lib/site-packages/pygame/tests/image__save_gl_surface_test.py
ZenithEmber/COMP120-Assignment-1-contract
46
6632169
import os import unittest from pygame.tests import test_utils import pygame from pygame.locals import * @unittest.skipIf(os.environ.get('SDL_VIDEODRIVER') == 'dummy', 'OpenGL requires a non-"dummy" SDL_VIDEODRIVER') class GL_ImageSave(unittest.TestCase): def test_image_save_works_with_opengl_surfaces(self): """ |tags:display,slow,opengl| """ pygame.display.init() screen = pygame.display.set_mode((640,480), OPENGL|DOUBLEBUF) pygame.display.flip() tmp_dir = test_utils.get_tmp_dir() # Try the imageext module. tmp_file = os.path.join(tmp_dir, "opengl_save_surface_test.png") pygame.image.save(screen, tmp_file) self.assertTrue(os.path.exists(tmp_file)) os.remove(tmp_file) # Only test the image module. tmp_file = os.path.join(tmp_dir, "opengl_save_surface_test.bmp") pygame.image.save(screen, tmp_file) self.assertTrue(os.path.exists(tmp_file)) os.remove(tmp_file) # stops tonnes of tmp dirs building up in trunk dir os.rmdir(tmp_dir) pygame.display.quit() if __name__ == '__main__': unittest.main()
import os import unittest from pygame.tests import test_utils import pygame from pygame.locals import * @unittest.skipIf(os.environ.get('SDL_VIDEODRIVER') == 'dummy', 'OpenGL requires a non-"dummy" SDL_VIDEODRIVER') class GL_ImageSave(unittest.TestCase): def test_image_save_works_with_opengl_surfaces(self): """ |tags:display,slow,opengl| """ pygame.display.init() screen = pygame.display.set_mode((640,480), OPENGL|DOUBLEBUF) pygame.display.flip() tmp_dir = test_utils.get_tmp_dir() # Try the imageext module. tmp_file = os.path.join(tmp_dir, "opengl_save_surface_test.png") pygame.image.save(screen, tmp_file) self.assertTrue(os.path.exists(tmp_file)) os.remove(tmp_file) # Only test the image module. tmp_file = os.path.join(tmp_dir, "opengl_save_surface_test.bmp") pygame.image.save(screen, tmp_file) self.assertTrue(os.path.exists(tmp_file)) os.remove(tmp_file) # stops tonnes of tmp dirs building up in trunk dir os.rmdir(tmp_dir) pygame.display.quit() if __name__ == '__main__': unittest.main()
en
0.341557
|tags:display,slow,opengl| # Try the imageext module. # Only test the image module. # stops tonnes of tmp dirs building up in trunk dir
2.451428
2
plugin/references.py
kaste/LSP
0
6632170
import os import sublime import linecache from .core.panels import ensure_panel from .core.protocol import Request, Point from .core.registry import get_position from .core.registry import LspTextCommand from .core.registry import windows from .core.settings import PLUGIN_NAME from .core.settings import userprefs from .core.typing import List, Dict, Optional, Tuple, TypedDict from .core.url import uri_to_filename from .core.views import get_line, text_document_position_params from .documents import is_at_word ReferenceDict = TypedDict('ReferenceDict', {'uri': str, 'range': dict}) def ensure_references_panel(window: sublime.Window) -> 'Optional[sublime.View]': return ensure_panel(window, "references", r"^\s*\S\s+(\S.*):$", r"^\s+([0-9]+):?([0-9]+).*$", "Packages/" + PLUGIN_NAME + "/Syntaxes/References.sublime-syntax") class LspSymbolReferencesCommand(LspTextCommand): capability = 'referencesProvider' def __init__(self, view: sublime.View) -> None: super().__init__(view) self.reflist = [] # type: List[List[str]] self.word_region = None # type: Optional[sublime.Region] self.word = "" self.base_dir = None # type: Optional[str] def is_enabled(self, event: Optional[dict] = None) -> bool: return super().is_enabled(event) and is_at_word(self.view, event) def run(self, edit: sublime.Edit, event: Optional[dict] = None) -> None: session = self.best_session(self.capability) file_path = self.view.file_name() if session and file_path: pos = get_position(self.view, event) window = self.view.window() if not window: return self.word_region = self.view.word(pos) self.word = self.view.substr(self.word_region) # use relative paths if file on the same root. base_dir = windows.lookup(window).get_project_path(file_path) if base_dir: if os.path.commonprefix([base_dir, file_path]): self.base_dir = base_dir document_position = text_document_position_params(self.view, pos) document_position['context'] = {"includeDeclaration": False} request = Request.references(document_position) session.send_request(request, lambda response: self.handle_response(response, pos)) def handle_response(self, response: Optional[List[ReferenceDict]], pos: int) -> None: window = self.view.window() if response is None: response = [] if window: references_count = len(response) # return if there are no references if references_count < 1: window.run_command("hide_panel", {"panel": "output.references"}) window.status_message("No references found") return references_by_file = self._group_references_by_file(response) if userprefs().show_references_in_quick_panel: self.show_quick_panel(references_by_file) else: self.show_references_panel(references_by_file) def show_quick_panel(self, references_by_file: Dict[str, List[Tuple[Point, str]]]) -> None: selected_index = -1 current_file_path = self.view.file_name() self.reflist.clear() for file_path, references in references_by_file.items(): for reference in references: point, line = reference item = ['{}:{}:{}'.format(self.get_relative_path(file_path), point.row + 1, point.col + 1), line] self.reflist.append(item) # pre-select a reference in the current file. if current_file_path == file_path and selected_index == -1: selected_index = len(self.reflist) - 1 flags = sublime.KEEP_OPEN_ON_FOCUS_LOST window = self.view.window() if window: window.show_quick_panel( self.reflist, self.on_ref_choice, flags, selected_index, self.on_ref_highlight ) def on_ref_choice(self, index: int) -> None: self.open_ref_index(index) def on_ref_highlight(self, index: int) -> None: self.open_ref_index(index, transient=True) def open_ref_index(self, index: int, transient: bool = False) -> None: if index != -1: flags = sublime.ENCODED_POSITION | sublime.TRANSIENT if transient else sublime.ENCODED_POSITION window = self.view.window() if window: window.open_file(self.get_selected_file_path(index), flags) def show_references_panel(self, references_by_file: Dict[str, List[Tuple[Point, str]]]) -> None: window = self.view.window() if window: panel = ensure_references_panel(window) if not panel: return text = '' references_count = 0 for file, references in references_by_file.items(): text += '◌ {}:\n'.format(self.get_relative_path(file)) for reference in references: references_count += 1 point, line = reference text += '\t{:>8}:{:<4} {}\n'.format(point.row + 1, point.col + 1, line) # append a new line after each file name text += '\n' base_dir = windows.lookup(window).get_project_path(self.view.file_name() or "") panel.settings().set("result_base_dir", base_dir) panel.run_command("lsp_clear_panel") window.run_command("show_panel", {"panel": "output.references"}) panel.run_command('append', { 'characters': "{} references for '{}'\n\n{}".format(references_count, self.word, text), 'force': True, 'scroll_to_end': False }) # highlight all word occurrences regions = panel.find_all(r"\b{}\b".format(self.word)) panel.add_regions('ReferenceHighlight', regions, 'comment', flags=sublime.DRAW_OUTLINED) def get_selected_file_path(self, index: int) -> str: return self.get_full_path(self.reflist[index][0]) def get_relative_path(self, file_path: str) -> str: if self.base_dir: return os.path.relpath(file_path, self.base_dir) else: return file_path def get_full_path(self, file_path: str) -> str: if self.base_dir: return os.path.join(self.base_dir, file_path) return file_path def _group_references_by_file(self, references: List[ReferenceDict] ) -> Dict[str, List[Tuple[Point, str]]]: """ Return a dictionary that groups references by the file it belongs. """ grouped_references = {} # type: Dict[str, List[Tuple[Point, str]]] for reference in references: file_path = uri_to_filename(reference["uri"]) point = Point.from_lsp(reference['range']['start']) # get line of the reference, to showcase its use reference_line = get_line(self.view.window(), file_path, point.row) if grouped_references.get(file_path) is None: grouped_references[file_path] = [] grouped_references[file_path].append((point, reference_line)) # we don't want to cache the line, we always want to get fresh data linecache.clearcache() return grouped_references
import os import sublime import linecache from .core.panels import ensure_panel from .core.protocol import Request, Point from .core.registry import get_position from .core.registry import LspTextCommand from .core.registry import windows from .core.settings import PLUGIN_NAME from .core.settings import userprefs from .core.typing import List, Dict, Optional, Tuple, TypedDict from .core.url import uri_to_filename from .core.views import get_line, text_document_position_params from .documents import is_at_word ReferenceDict = TypedDict('ReferenceDict', {'uri': str, 'range': dict}) def ensure_references_panel(window: sublime.Window) -> 'Optional[sublime.View]': return ensure_panel(window, "references", r"^\s*\S\s+(\S.*):$", r"^\s+([0-9]+):?([0-9]+).*$", "Packages/" + PLUGIN_NAME + "/Syntaxes/References.sublime-syntax") class LspSymbolReferencesCommand(LspTextCommand): capability = 'referencesProvider' def __init__(self, view: sublime.View) -> None: super().__init__(view) self.reflist = [] # type: List[List[str]] self.word_region = None # type: Optional[sublime.Region] self.word = "" self.base_dir = None # type: Optional[str] def is_enabled(self, event: Optional[dict] = None) -> bool: return super().is_enabled(event) and is_at_word(self.view, event) def run(self, edit: sublime.Edit, event: Optional[dict] = None) -> None: session = self.best_session(self.capability) file_path = self.view.file_name() if session and file_path: pos = get_position(self.view, event) window = self.view.window() if not window: return self.word_region = self.view.word(pos) self.word = self.view.substr(self.word_region) # use relative paths if file on the same root. base_dir = windows.lookup(window).get_project_path(file_path) if base_dir: if os.path.commonprefix([base_dir, file_path]): self.base_dir = base_dir document_position = text_document_position_params(self.view, pos) document_position['context'] = {"includeDeclaration": False} request = Request.references(document_position) session.send_request(request, lambda response: self.handle_response(response, pos)) def handle_response(self, response: Optional[List[ReferenceDict]], pos: int) -> None: window = self.view.window() if response is None: response = [] if window: references_count = len(response) # return if there are no references if references_count < 1: window.run_command("hide_panel", {"panel": "output.references"}) window.status_message("No references found") return references_by_file = self._group_references_by_file(response) if userprefs().show_references_in_quick_panel: self.show_quick_panel(references_by_file) else: self.show_references_panel(references_by_file) def show_quick_panel(self, references_by_file: Dict[str, List[Tuple[Point, str]]]) -> None: selected_index = -1 current_file_path = self.view.file_name() self.reflist.clear() for file_path, references in references_by_file.items(): for reference in references: point, line = reference item = ['{}:{}:{}'.format(self.get_relative_path(file_path), point.row + 1, point.col + 1), line] self.reflist.append(item) # pre-select a reference in the current file. if current_file_path == file_path and selected_index == -1: selected_index = len(self.reflist) - 1 flags = sublime.KEEP_OPEN_ON_FOCUS_LOST window = self.view.window() if window: window.show_quick_panel( self.reflist, self.on_ref_choice, flags, selected_index, self.on_ref_highlight ) def on_ref_choice(self, index: int) -> None: self.open_ref_index(index) def on_ref_highlight(self, index: int) -> None: self.open_ref_index(index, transient=True) def open_ref_index(self, index: int, transient: bool = False) -> None: if index != -1: flags = sublime.ENCODED_POSITION | sublime.TRANSIENT if transient else sublime.ENCODED_POSITION window = self.view.window() if window: window.open_file(self.get_selected_file_path(index), flags) def show_references_panel(self, references_by_file: Dict[str, List[Tuple[Point, str]]]) -> None: window = self.view.window() if window: panel = ensure_references_panel(window) if not panel: return text = '' references_count = 0 for file, references in references_by_file.items(): text += '◌ {}:\n'.format(self.get_relative_path(file)) for reference in references: references_count += 1 point, line = reference text += '\t{:>8}:{:<4} {}\n'.format(point.row + 1, point.col + 1, line) # append a new line after each file name text += '\n' base_dir = windows.lookup(window).get_project_path(self.view.file_name() or "") panel.settings().set("result_base_dir", base_dir) panel.run_command("lsp_clear_panel") window.run_command("show_panel", {"panel": "output.references"}) panel.run_command('append', { 'characters': "{} references for '{}'\n\n{}".format(references_count, self.word, text), 'force': True, 'scroll_to_end': False }) # highlight all word occurrences regions = panel.find_all(r"\b{}\b".format(self.word)) panel.add_regions('ReferenceHighlight', regions, 'comment', flags=sublime.DRAW_OUTLINED) def get_selected_file_path(self, index: int) -> str: return self.get_full_path(self.reflist[index][0]) def get_relative_path(self, file_path: str) -> str: if self.base_dir: return os.path.relpath(file_path, self.base_dir) else: return file_path def get_full_path(self, file_path: str) -> str: if self.base_dir: return os.path.join(self.base_dir, file_path) return file_path def _group_references_by_file(self, references: List[ReferenceDict] ) -> Dict[str, List[Tuple[Point, str]]]: """ Return a dictionary that groups references by the file it belongs. """ grouped_references = {} # type: Dict[str, List[Tuple[Point, str]]] for reference in references: file_path = uri_to_filename(reference["uri"]) point = Point.from_lsp(reference['range']['start']) # get line of the reference, to showcase its use reference_line = get_line(self.view.window(), file_path, point.row) if grouped_references.get(file_path) is None: grouped_references[file_path] = [] grouped_references[file_path].append((point, reference_line)) # we don't want to cache the line, we always want to get fresh data linecache.clearcache() return grouped_references
en
0.800215
# type: List[List[str]] # type: Optional[sublime.Region] # type: Optional[str] # use relative paths if file on the same root. # return if there are no references # pre-select a reference in the current file. # append a new line after each file name # highlight all word occurrences Return a dictionary that groups references by the file it belongs. # type: Dict[str, List[Tuple[Point, str]]] # get line of the reference, to showcase its use # we don't want to cache the line, we always want to get fresh data
1.95289
2
tensorimage/util/system/mkdir.py
Nesac128/tensorimage
19
6632171
<gh_stars>10-100 import os def mkdir(dir_path): if not os.path.exists(dir_path): os.mkdir(dir_path)
import os def mkdir(dir_path): if not os.path.exists(dir_path): os.mkdir(dir_path)
none
1
2.580427
3
VolumeToMesh/VolumeToMesh.py
lassoan/SlicerMorph
0
6632172
<reponame>lassoan/SlicerMorph import os import unittest import vtk, qt, ctk, slicer from slicer.ScriptedLoadableModule import * import logging import fnmatch import numpy as np import random import math # # VolumeToMesh # class VolumeToMesh(ScriptedLoadableModule): """Uses ScriptedLoadableModule base class, available at: https://github.com/Slicer/Slicer/blob/master/Base/Python/slicer/ScriptedLoadableModule.py """ def __init__(self, parent): ScriptedLoadableModule.__init__(self, parent) self.parent.title = "VolumeToMesh" # TODO make this more human readable by adding spaces self.parent.categories = ["SlicerMorph.SlicerMorph Labs"] self.parent.dependencies = [] self.parent.contributors = ["<NAME> (UW), <NAME> (UW)"] # replace with "Firstname Lastname (Organization)" self.parent.helpText = """ This module takes a directory of volumes and segments them using a user-supplied threshold value. The output segments are converted to models and saved in the output directory. """ self.parent.helpText += self.getDefaultModuleDocumentationLink() self.parent.acknowledgementText = """ This module was developed by <NAME> and <NAME>, through a NSF ABI Development grant, "An Integrated Platform for Retrieval, Visualization and Analysis of 3D Morphology From Digital Biological Collections" (Award Numbers: 1759883 (Murat Maga), 1759637 (<NAME>), 1759839 (Douglas Boyer)). https://nsf.gov/awardsearch/showAward?AWD_ID=1759883&HistoricalAwards=false """ # replace with organization, grant and thanks. # # VolumeToMeshWidget # class VolumeToMeshWidget(ScriptedLoadableModuleWidget): """Uses ScriptedLoadableModuleWidget base class, available at: https://github.com/Slicer/Slicer/blob/master/Base/Python/slicer/ScriptedLoadableModule.py """ def onSelectInput(self): self.applyButton.enabled = bool (self.inputDirectory.currentPath and self.outputDirectory.currentPath) def onSelectOutput(self): self.applyButton.enabled = bool (self.inputDirectory.currentPath and self.outputDirectory.currentPath) def setup(self): ScriptedLoadableModuleWidget.setup(self) # Instantiate and connect widgets ... # # Parameters Area # parametersCollapsibleButton = ctk.ctkCollapsibleButton() parametersCollapsibleButton.text = "Parameters" self.layout.addWidget(parametersCollapsibleButton) # Layout within the dummy collapsible button parametersFormLayout = qt.QFormLayout(parametersCollapsibleButton) self.inputDirectory=ctk.ctkPathLineEdit() self.inputDirectory.filters = ctk.ctkPathLineEdit.Dirs self.inputDirectory.setToolTip( "Select directory containing volumes" ) parametersFormLayout.addRow("Input directory: ", self.inputDirectory) # Select output directory self.outputDirectory=ctk.ctkPathLineEdit() self.outputDirectory.filters = ctk.ctkPathLineEdit.Dirs self.outputDirectory.setToolTip( "Select directory for output models: " ) parametersFormLayout.addRow("Output directory: ", self.outputDirectory) # # Select the extension type # self.extensionOptionGZ = qt.QRadioButton(".nii.gz") self.extensionOptionGZ.setChecked(True) parametersFormLayout.addRow("Select extension type: ", self.extensionOptionGZ) # # set threshold value # self.threshold = ctk.ctkDoubleSpinBox() self.threshold.singleStep = 1 self.threshold.minimum = 0 self.threshold.maximum = 100000 self.threshold.setDecimals(0) self.threshold.value = 500 self.threshold.setToolTip("Select threshold for segmentation of volume") parametersFormLayout.addRow("Threshold for segmentation:", self.threshold) # # Apply Button # self.applyButton = qt.QPushButton("Apply") self.applyButton.toolTip = "Generate VolumeToMeshs." self.applyButton.enabled = False parametersFormLayout.addRow(self.applyButton) # # check box to trigger taking screen shots for later use in tutorials # self.enableScreenshotsFlagCheckBox = qt.QCheckBox() self.enableScreenshotsFlagCheckBox.checked = 0 self.enableScreenshotsFlagCheckBox.setToolTip("If checked, take screen shots for tutorials. Use Save Data to write them to disk.") parametersFormLayout.addRow("Enable Screenshots", self.enableScreenshotsFlagCheckBox) # connections self.inputDirectory.connect('validInputChanged(bool)', self.onSelectInput) self.outputDirectory.connect('validInputChanged(bool)', self.onSelectOutput) self.applyButton.connect('clicked(bool)', self.onApplyButton) # Add vertical spacer self.layout.addStretch(1) def cleanup(self): pass def onApplyButton(self): logic = VolumeToMeshLogic() enableScreenshotsFlag = self.enableScreenshotsFlagCheckBox.checked extension ="" if self.extensionOptionGZ.checked: extension = ".nii.gz" logic.run(self.inputDirectory.currentPath, self.outputDirectory.currentPath, extension, int(self.threshold.value)) # # VolumeToMeshLogic # class VolumeToMeshLogic(ScriptedLoadableModuleLogic): """This class should implement all the actual computation done by your module. The interface should be such that other python code can import this class and make use of the functionality without requiring an instance of the Widget. Uses ScriptedLoadableModuleLogic base class, available at: https://github.com/Slicer/Slicer/blob/master/Base/Python/slicer/ScriptedLoadableModule.py """ def run(self, inputDirectory, outputDirectory, extension, stepThreshold): renderLogic = slicer.modules.volumerendering.logic() for file in os.listdir(inputDirectory): if file.endswith(extension): inputFile = os.path.join(inputDirectory, file) volumeNode =slicer.util.loadVolume(inputFile) labelVolumeNode = slicer.mrmlScene.AddNewNodeByClass("vtkMRMLLabelMapVolumeNode") slicer.vtkSlicerVolumesLogic().CreateLabelVolumeFromVolume(slicer.mrmlScene, labelVolumeNode, volumeNode) voxelArray = slicer.util.arrayFromVolume(volumeNode) labelVoxelArray = slicer.util.arrayFromVolume(labelVolumeNode) labelVoxelArray[voxelArray >= stepThreshold] = 100 labelVoxelArray[voxelArray < stepThreshold] = 0 slicer.util.arrayFromVolumeModified(labelVolumeNode) imageName = volumeNode.GetName() segmentationNode = slicer.mrmlScene.AddNewNodeByClass('vtkMRMLSegmentationNode', imageName) slicer.modules.segmentations.logic().ImportLabelmapToSegmentationNode(labelVolumeNode, segmentationNode) segmentID = segmentationNode.GetSegmentation().GetNthSegmentID(0) polydata=vtk.vtkPolyData() slicer.modules.segmentations.logic().GetSegmentClosedSurfaceRepresentation(segmentationNode, segmentID, polydata,1) normalFilter = vtk.vtkPolyDataNormals() normalFilter.SetInputData(polydata) normalFilter.SetFlipNormals(1) normalFilter.Update() polydataFlip = normalFilter.GetOutput() modelNode = slicer.mrmlScene.AddNewNodeByClass('vtkMRMLModelNode',imageName) modelNode.CreateDefaultDisplayNodes() modelNode.SetAndObservePolyData(polydataFlip) outputFilename = os.path.join(outputDirectory, imageName + '.ply') slicer.util.saveNode(modelNode, outputFilename) slicer.mrmlScene.RemoveNode(labelVolumeNode) slicer.mrmlScene.RemoveNode(volumeNode) slicer.mrmlScene.RemoveNode(segmentationNode) slicer.mrmlScene.RemoveNode(modelNode) def takeScreenshot(self,name,description,type=-1): # show the message even if not taking a screen shot slicer.util.delayDisplay('Take screenshot: '+description+'.\nResult is available in the Annotations module.', 3000) lm = slicer.app.layoutManager() # switch on the type to get the requested window widget = 0 if type == slicer.qMRMLScreenShotDialog.FullLayout: # full layout widget = lm.viewport() elif type == slicer.qMRMLScreenShotDialog.ThreeD: # just the 3D window widget = lm.threeDWidget(0).threeDView() elif type == slicer.qMRMLScreenShotDialog.Red: # red slice window widget = lm.sliceWidget("Red") elif type == slicer.qMRMLScreenShotDialog.Yellow: # yellow slice window widget = lm.sliceWidget("Yellow") elif type == slicer.qMRMLScreenShotDialog.Green: # green slice window widget = lm.sliceWidget("Green") else: # default to using the full window widget = slicer.util.mainWindow() # reset the type so that the node is set correctly type = slicer.qMRMLScreenShotDialog.FullLayout # grab and convert to vtk image data qimage = ctk.ctkWidgetsUtils.grabWidget(widget) imageData = vtk.vtkImageData() slicer.qMRMLUtils().qImageToVtkImageData(qimage,imageData) annotationLogic = slicer.modules.annotations.logic() annotationLogic.CreateSnapShot(name, description, type, 1, imageData) class VolumeToMeshTest(ScriptedLoadableModuleTest): """ This is the test case for your scripted module. Uses ScriptedLoadableModuleTest base class, available at: https://github.com/Slicer/Slicer/blob/master/Base/Python/slicer/ScriptedLoadableModule.py """ def setUp(self): """ Do whatever is needed to reset the state - typically a scene clear will be enough. """ slicer.mrmlScene.Clear(0) def runTest(self): """Run as few or as many tests as needed here. """ self.setUp() self.test_VolumeToMesh1() def test_VolumeToMesh1(self): """ Ideally you should have several levels of tests. At the lowest level tests should exercise the functionality of the logic with different inputs (both valid and invalid). At higher levels your tests should emulate the way the user would interact with your code and confirm that it still works the way you intended. One of the most important features of the tests is that it should alert other developers when their changes will have an impact on the behavior of your module. For example, if a developer removes a feature that you depend on, your test should break so they know that the feature is needed. """ self.delayDisplay("Starting the test") # # first, get some data # import SampleData SampleData.downloadFromURL( nodeNames='FA', fileNames='FA.nrrd', uris='http://slicer.kitware.com/midas3/download?items=5767', checksums='SHA256:12d17fba4f2e1f1a843f0757366f28c3f3e1a8bb38836f0de2a32bb1cd476560') self.delayDisplay('Finished with download and loading') volumeNode = slicer.util.getNode(pattern="FA") logic = VolumeToMeshLogic() self.assertIsNotNone( logic.hasImageData(volumeNode) ) self.delayDisplay('Test passed!')
import os import unittest import vtk, qt, ctk, slicer from slicer.ScriptedLoadableModule import * import logging import fnmatch import numpy as np import random import math # # VolumeToMesh # class VolumeToMesh(ScriptedLoadableModule): """Uses ScriptedLoadableModule base class, available at: https://github.com/Slicer/Slicer/blob/master/Base/Python/slicer/ScriptedLoadableModule.py """ def __init__(self, parent): ScriptedLoadableModule.__init__(self, parent) self.parent.title = "VolumeToMesh" # TODO make this more human readable by adding spaces self.parent.categories = ["SlicerMorph.SlicerMorph Labs"] self.parent.dependencies = [] self.parent.contributors = ["<NAME> (UW), <NAME> (UW)"] # replace with "Firstname Lastname (Organization)" self.parent.helpText = """ This module takes a directory of volumes and segments them using a user-supplied threshold value. The output segments are converted to models and saved in the output directory. """ self.parent.helpText += self.getDefaultModuleDocumentationLink() self.parent.acknowledgementText = """ This module was developed by <NAME> and <NAME>, through a NSF ABI Development grant, "An Integrated Platform for Retrieval, Visualization and Analysis of 3D Morphology From Digital Biological Collections" (Award Numbers: 1759883 (Murat Maga), 1759637 (<NAME>), 1759839 (Douglas Boyer)). https://nsf.gov/awardsearch/showAward?AWD_ID=1759883&HistoricalAwards=false """ # replace with organization, grant and thanks. # # VolumeToMeshWidget # class VolumeToMeshWidget(ScriptedLoadableModuleWidget): """Uses ScriptedLoadableModuleWidget base class, available at: https://github.com/Slicer/Slicer/blob/master/Base/Python/slicer/ScriptedLoadableModule.py """ def onSelectInput(self): self.applyButton.enabled = bool (self.inputDirectory.currentPath and self.outputDirectory.currentPath) def onSelectOutput(self): self.applyButton.enabled = bool (self.inputDirectory.currentPath and self.outputDirectory.currentPath) def setup(self): ScriptedLoadableModuleWidget.setup(self) # Instantiate and connect widgets ... # # Parameters Area # parametersCollapsibleButton = ctk.ctkCollapsibleButton() parametersCollapsibleButton.text = "Parameters" self.layout.addWidget(parametersCollapsibleButton) # Layout within the dummy collapsible button parametersFormLayout = qt.QFormLayout(parametersCollapsibleButton) self.inputDirectory=ctk.ctkPathLineEdit() self.inputDirectory.filters = ctk.ctkPathLineEdit.Dirs self.inputDirectory.setToolTip( "Select directory containing volumes" ) parametersFormLayout.addRow("Input directory: ", self.inputDirectory) # Select output directory self.outputDirectory=ctk.ctkPathLineEdit() self.outputDirectory.filters = ctk.ctkPathLineEdit.Dirs self.outputDirectory.setToolTip( "Select directory for output models: " ) parametersFormLayout.addRow("Output directory: ", self.outputDirectory) # # Select the extension type # self.extensionOptionGZ = qt.QRadioButton(".nii.gz") self.extensionOptionGZ.setChecked(True) parametersFormLayout.addRow("Select extension type: ", self.extensionOptionGZ) # # set threshold value # self.threshold = ctk.ctkDoubleSpinBox() self.threshold.singleStep = 1 self.threshold.minimum = 0 self.threshold.maximum = 100000 self.threshold.setDecimals(0) self.threshold.value = 500 self.threshold.setToolTip("Select threshold for segmentation of volume") parametersFormLayout.addRow("Threshold for segmentation:", self.threshold) # # Apply Button # self.applyButton = qt.QPushButton("Apply") self.applyButton.toolTip = "Generate VolumeToMeshs." self.applyButton.enabled = False parametersFormLayout.addRow(self.applyButton) # # check box to trigger taking screen shots for later use in tutorials # self.enableScreenshotsFlagCheckBox = qt.QCheckBox() self.enableScreenshotsFlagCheckBox.checked = 0 self.enableScreenshotsFlagCheckBox.setToolTip("If checked, take screen shots for tutorials. Use Save Data to write them to disk.") parametersFormLayout.addRow("Enable Screenshots", self.enableScreenshotsFlagCheckBox) # connections self.inputDirectory.connect('validInputChanged(bool)', self.onSelectInput) self.outputDirectory.connect('validInputChanged(bool)', self.onSelectOutput) self.applyButton.connect('clicked(bool)', self.onApplyButton) # Add vertical spacer self.layout.addStretch(1) def cleanup(self): pass def onApplyButton(self): logic = VolumeToMeshLogic() enableScreenshotsFlag = self.enableScreenshotsFlagCheckBox.checked extension ="" if self.extensionOptionGZ.checked: extension = ".nii.gz" logic.run(self.inputDirectory.currentPath, self.outputDirectory.currentPath, extension, int(self.threshold.value)) # # VolumeToMeshLogic # class VolumeToMeshLogic(ScriptedLoadableModuleLogic): """This class should implement all the actual computation done by your module. The interface should be such that other python code can import this class and make use of the functionality without requiring an instance of the Widget. Uses ScriptedLoadableModuleLogic base class, available at: https://github.com/Slicer/Slicer/blob/master/Base/Python/slicer/ScriptedLoadableModule.py """ def run(self, inputDirectory, outputDirectory, extension, stepThreshold): renderLogic = slicer.modules.volumerendering.logic() for file in os.listdir(inputDirectory): if file.endswith(extension): inputFile = os.path.join(inputDirectory, file) volumeNode =slicer.util.loadVolume(inputFile) labelVolumeNode = slicer.mrmlScene.AddNewNodeByClass("vtkMRMLLabelMapVolumeNode") slicer.vtkSlicerVolumesLogic().CreateLabelVolumeFromVolume(slicer.mrmlScene, labelVolumeNode, volumeNode) voxelArray = slicer.util.arrayFromVolume(volumeNode) labelVoxelArray = slicer.util.arrayFromVolume(labelVolumeNode) labelVoxelArray[voxelArray >= stepThreshold] = 100 labelVoxelArray[voxelArray < stepThreshold] = 0 slicer.util.arrayFromVolumeModified(labelVolumeNode) imageName = volumeNode.GetName() segmentationNode = slicer.mrmlScene.AddNewNodeByClass('vtkMRMLSegmentationNode', imageName) slicer.modules.segmentations.logic().ImportLabelmapToSegmentationNode(labelVolumeNode, segmentationNode) segmentID = segmentationNode.GetSegmentation().GetNthSegmentID(0) polydata=vtk.vtkPolyData() slicer.modules.segmentations.logic().GetSegmentClosedSurfaceRepresentation(segmentationNode, segmentID, polydata,1) normalFilter = vtk.vtkPolyDataNormals() normalFilter.SetInputData(polydata) normalFilter.SetFlipNormals(1) normalFilter.Update() polydataFlip = normalFilter.GetOutput() modelNode = slicer.mrmlScene.AddNewNodeByClass('vtkMRMLModelNode',imageName) modelNode.CreateDefaultDisplayNodes() modelNode.SetAndObservePolyData(polydataFlip) outputFilename = os.path.join(outputDirectory, imageName + '.ply') slicer.util.saveNode(modelNode, outputFilename) slicer.mrmlScene.RemoveNode(labelVolumeNode) slicer.mrmlScene.RemoveNode(volumeNode) slicer.mrmlScene.RemoveNode(segmentationNode) slicer.mrmlScene.RemoveNode(modelNode) def takeScreenshot(self,name,description,type=-1): # show the message even if not taking a screen shot slicer.util.delayDisplay('Take screenshot: '+description+'.\nResult is available in the Annotations module.', 3000) lm = slicer.app.layoutManager() # switch on the type to get the requested window widget = 0 if type == slicer.qMRMLScreenShotDialog.FullLayout: # full layout widget = lm.viewport() elif type == slicer.qMRMLScreenShotDialog.ThreeD: # just the 3D window widget = lm.threeDWidget(0).threeDView() elif type == slicer.qMRMLScreenShotDialog.Red: # red slice window widget = lm.sliceWidget("Red") elif type == slicer.qMRMLScreenShotDialog.Yellow: # yellow slice window widget = lm.sliceWidget("Yellow") elif type == slicer.qMRMLScreenShotDialog.Green: # green slice window widget = lm.sliceWidget("Green") else: # default to using the full window widget = slicer.util.mainWindow() # reset the type so that the node is set correctly type = slicer.qMRMLScreenShotDialog.FullLayout # grab and convert to vtk image data qimage = ctk.ctkWidgetsUtils.grabWidget(widget) imageData = vtk.vtkImageData() slicer.qMRMLUtils().qImageToVtkImageData(qimage,imageData) annotationLogic = slicer.modules.annotations.logic() annotationLogic.CreateSnapShot(name, description, type, 1, imageData) class VolumeToMeshTest(ScriptedLoadableModuleTest): """ This is the test case for your scripted module. Uses ScriptedLoadableModuleTest base class, available at: https://github.com/Slicer/Slicer/blob/master/Base/Python/slicer/ScriptedLoadableModule.py """ def setUp(self): """ Do whatever is needed to reset the state - typically a scene clear will be enough. """ slicer.mrmlScene.Clear(0) def runTest(self): """Run as few or as many tests as needed here. """ self.setUp() self.test_VolumeToMesh1() def test_VolumeToMesh1(self): """ Ideally you should have several levels of tests. At the lowest level tests should exercise the functionality of the logic with different inputs (both valid and invalid). At higher levels your tests should emulate the way the user would interact with your code and confirm that it still works the way you intended. One of the most important features of the tests is that it should alert other developers when their changes will have an impact on the behavior of your module. For example, if a developer removes a feature that you depend on, your test should break so they know that the feature is needed. """ self.delayDisplay("Starting the test") # # first, get some data # import SampleData SampleData.downloadFromURL( nodeNames='FA', fileNames='FA.nrrd', uris='http://slicer.kitware.com/midas3/download?items=5767', checksums='SHA256:12d17fba4f2e1f1a843f0757366f28c3f3e1a8bb38836f0de2a32bb1cd476560') self.delayDisplay('Finished with download and loading') volumeNode = slicer.util.getNode(pattern="FA") logic = VolumeToMeshLogic() self.assertIsNotNone( logic.hasImageData(volumeNode) ) self.delayDisplay('Test passed!')
en
0.780295
# # VolumeToMesh # Uses ScriptedLoadableModule base class, available at: https://github.com/Slicer/Slicer/blob/master/Base/Python/slicer/ScriptedLoadableModule.py # TODO make this more human readable by adding spaces # replace with "Firstname Lastname (Organization)" This module takes a directory of volumes and segments them using a user-supplied threshold value. The output segments are converted to models and saved in the output directory. This module was developed by <NAME> and <NAME>, through a NSF ABI Development grant, "An Integrated Platform for Retrieval, Visualization and Analysis of 3D Morphology From Digital Biological Collections" (Award Numbers: 1759883 (Murat Maga), 1759637 (<NAME>), 1759839 (Douglas Boyer)). https://nsf.gov/awardsearch/showAward?AWD_ID=1759883&HistoricalAwards=false # replace with organization, grant and thanks. # # VolumeToMeshWidget # Uses ScriptedLoadableModuleWidget base class, available at: https://github.com/Slicer/Slicer/blob/master/Base/Python/slicer/ScriptedLoadableModule.py # Instantiate and connect widgets ... # # Parameters Area # # Layout within the dummy collapsible button # Select output directory # # Select the extension type # # # set threshold value # # # Apply Button # # # check box to trigger taking screen shots for later use in tutorials # # connections # Add vertical spacer # # VolumeToMeshLogic # This class should implement all the actual computation done by your module. The interface should be such that other python code can import this class and make use of the functionality without requiring an instance of the Widget. Uses ScriptedLoadableModuleLogic base class, available at: https://github.com/Slicer/Slicer/blob/master/Base/Python/slicer/ScriptedLoadableModule.py # show the message even if not taking a screen shot # switch on the type to get the requested window # full layout # just the 3D window # red slice window # yellow slice window # green slice window # default to using the full window # reset the type so that the node is set correctly # grab and convert to vtk image data This is the test case for your scripted module. Uses ScriptedLoadableModuleTest base class, available at: https://github.com/Slicer/Slicer/blob/master/Base/Python/slicer/ScriptedLoadableModule.py Do whatever is needed to reset the state - typically a scene clear will be enough. Run as few or as many tests as needed here. Ideally you should have several levels of tests. At the lowest level tests should exercise the functionality of the logic with different inputs (both valid and invalid). At higher levels your tests should emulate the way the user would interact with your code and confirm that it still works the way you intended. One of the most important features of the tests is that it should alert other developers when their changes will have an impact on the behavior of your module. For example, if a developer removes a feature that you depend on, your test should break so they know that the feature is needed. # # first, get some data #
2.240111
2
week6-Evasion/bot/random_player.py
chirag1992m/heuristicProblemSolvingFall17
0
6632173
import argparse from .base_bot import BaseBot import random class RandomBot(BaseBot): def __init__(self, host, port, name, visualize=False, seed=42): super().__init__(host=host, port=port, name=name, visualize=visualize) random.seed(seed) def move_hunter(self): wall = random.randint(0, 4) to_delete = [] for wall_idx in range(len(self.game.walls)): if random.random() < .1: to_delete.append(wall_idx) return wall, to_delete def move_prey(self): x = random.randint(-1, 1) y = random.randint(-1, 1) return x, y if __name__ == "__main__": parser = argparse.ArgumentParser() parser.add_argument('--ip', default='127.0.0.1', type=str) parser.add_argument('--port', default=9001, type=int) parser.add_argument('--name', default='chirag-ojas', type=str) parser.add_argument('--viz', default=False, action='store_true') parser.add_argument('--seed', default=42, type=int) args = parser.parse_args() client = RandomBot(args.ip, args.port, args.name, visualize=args.viz, seed=args.seed) client.start() client.done()
import argparse from .base_bot import BaseBot import random class RandomBot(BaseBot): def __init__(self, host, port, name, visualize=False, seed=42): super().__init__(host=host, port=port, name=name, visualize=visualize) random.seed(seed) def move_hunter(self): wall = random.randint(0, 4) to_delete = [] for wall_idx in range(len(self.game.walls)): if random.random() < .1: to_delete.append(wall_idx) return wall, to_delete def move_prey(self): x = random.randint(-1, 1) y = random.randint(-1, 1) return x, y if __name__ == "__main__": parser = argparse.ArgumentParser() parser.add_argument('--ip', default='127.0.0.1', type=str) parser.add_argument('--port', default=9001, type=int) parser.add_argument('--name', default='chirag-ojas', type=str) parser.add_argument('--viz', default=False, action='store_true') parser.add_argument('--seed', default=42, type=int) args = parser.parse_args() client = RandomBot(args.ip, args.port, args.name, visualize=args.viz, seed=args.seed) client.start() client.done()
none
1
2.863017
3
aumento de salario .py
Danielporcela/Meus-exercicios-phyton
2
6632174
<filename>aumento de salario .py<gh_stars>1-10 salario = float(input('Qual é o salario do funcionario ? R$ ')) aumento = salario + (salario *15 / 100) print(' Um funcionario que ganhava R$ {:.2f}, com aumento de 15 % passa a receber R$ {:.2f} '.format(salario,aumento ))
<filename>aumento de salario .py<gh_stars>1-10 salario = float(input('Qual é o salario do funcionario ? R$ ')) aumento = salario + (salario *15 / 100) print(' Um funcionario que ganhava R$ {:.2f}, com aumento de 15 % passa a receber R$ {:.2f} '.format(salario,aumento ))
none
1
3.587743
4
examples/misc/h2o2_ilt.py
amatsugi/me2d
0
6632175
#! /usr/bin/env python3 """ ILT (inverse laplace transform) calculation of k(E) for H2O2 => OH + OH output file: h2o2_iltE_dE10.dat """ from me2d import RoVib from me2d import ilt nsym = 2 rotA = 10.3560 rotB2D = 0.84680 freq = [877, 1266, 1402, 3599, 3608] # HO-OH rotational energy levels levels = [0.0, 13.28417, 251.96034, 375.2889, 576.38451, 786.65549, 1014.27698, 1251.27288, 1492.82778, 1738.07658, 1965.91838, 2224.64158, 2354.85548, 2728.62328, 2750.95608, 3300.27678, 3301.84558, 3960.96818, 3961.04278, 4709.42418, 4709.42688, 5542.65208, 5542.65218, 6458.95218, 6458.95218, 7457.38088, 7457.38088, 8537.37598, 8537.37598, 9698.58218, 9698.58218, 10940.76388, 10940.76388, 12263.76088, 12263.76088, 13667.45788, 13667.45788, 15151.77188, 15151.77188, 16716.64188, 16716.64188, 18362.02188, 18362.02188, 20087.87688, 20087.87688, 21894.17788, 21894.17788, 23780.90488, 23780.90488, 25748.03888, 25748.03888, 27795.56688, 27795.56688, 29923.47788, 29923.47788, 32131.76188, 32131.76188, 34420.41188, 34420.41188, 36789.42088, 36789.42088, 39238.78388, 39238.78388, 41768.49588, 41768.49588, 44378.55388, 44378.55388, 47068.95488, 47068.95488, 49839.69488, 49839.69488, 52690.77188, 52690.77188, 55622.18388, 55622.18388, 58633.92988, 58633.92988, 61726.00688, 61726.00688, 64898.41488, 64898.41488] states = [(1, x) for x in levels] rovib = RoVib(nsym, rotA, rotB2D, freq, states=states) # ILT [k(T) = A*exp(-E/RT)] ilt_A = 6.7e14 # s^-1 ilt_E = 17236.884 # cm^-1 maxE = 65000 dE = 10 ilt(maxE, dE, rovib, ilt_A, ilt_E, outf="h2o2_iltE_dE%d.dat" % (dE))
#! /usr/bin/env python3 """ ILT (inverse laplace transform) calculation of k(E) for H2O2 => OH + OH output file: h2o2_iltE_dE10.dat """ from me2d import RoVib from me2d import ilt nsym = 2 rotA = 10.3560 rotB2D = 0.84680 freq = [877, 1266, 1402, 3599, 3608] # HO-OH rotational energy levels levels = [0.0, 13.28417, 251.96034, 375.2889, 576.38451, 786.65549, 1014.27698, 1251.27288, 1492.82778, 1738.07658, 1965.91838, 2224.64158, 2354.85548, 2728.62328, 2750.95608, 3300.27678, 3301.84558, 3960.96818, 3961.04278, 4709.42418, 4709.42688, 5542.65208, 5542.65218, 6458.95218, 6458.95218, 7457.38088, 7457.38088, 8537.37598, 8537.37598, 9698.58218, 9698.58218, 10940.76388, 10940.76388, 12263.76088, 12263.76088, 13667.45788, 13667.45788, 15151.77188, 15151.77188, 16716.64188, 16716.64188, 18362.02188, 18362.02188, 20087.87688, 20087.87688, 21894.17788, 21894.17788, 23780.90488, 23780.90488, 25748.03888, 25748.03888, 27795.56688, 27795.56688, 29923.47788, 29923.47788, 32131.76188, 32131.76188, 34420.41188, 34420.41188, 36789.42088, 36789.42088, 39238.78388, 39238.78388, 41768.49588, 41768.49588, 44378.55388, 44378.55388, 47068.95488, 47068.95488, 49839.69488, 49839.69488, 52690.77188, 52690.77188, 55622.18388, 55622.18388, 58633.92988, 58633.92988, 61726.00688, 61726.00688, 64898.41488, 64898.41488] states = [(1, x) for x in levels] rovib = RoVib(nsym, rotA, rotB2D, freq, states=states) # ILT [k(T) = A*exp(-E/RT)] ilt_A = 6.7e14 # s^-1 ilt_E = 17236.884 # cm^-1 maxE = 65000 dE = 10 ilt(maxE, dE, rovib, ilt_A, ilt_E, outf="h2o2_iltE_dE%d.dat" % (dE))
en
0.506519
#! /usr/bin/env python3 ILT (inverse laplace transform) calculation of k(E) for H2O2 => OH + OH output file: h2o2_iltE_dE10.dat # HO-OH rotational energy levels # ILT [k(T) = A*exp(-E/RT)] # s^-1 # cm^-1
2.407072
2
src/selena/stats/migrations/0002_auto__add_field_incident_incident_type.py
deejay1/selena
23
6632176
# -*- coding: utf-8 -*- import datetime from south.db import db from south.v2 import SchemaMigration from django.db import models class Migration(SchemaMigration): def forwards(self, orm): # Adding field 'Incident.incident_type' db.add_column(u'stats_incident', 'incident_type', self.gf('django.db.models.fields.CharField')(default=u'failure', max_length=15), keep_default=False) def backwards(self, orm): # Deleting field 'Incident.incident_type' db.delete_column(u'stats_incident', 'incident_type') models = { u'services.agent': { 'Meta': {'object_name': 'Agent'}, u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'is_active': ('django.db.models.fields.BooleanField', [], {'default': 'True', 'db_index': 'True'}), 'is_main': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_index': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '75', 'db_index': 'True'}), 'queue': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['services.Queue']", 'null': 'True', 'on_delete': 'models.PROTECT', 'blank': 'True'}), 'salt': ('django.db.models.fields.CharField', [], {'max_length': '16'}) }, u'services.queue': { 'Meta': {'object_name': 'Queue'}, u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '75', 'db_index': 'True'}) }, u'services.service': { 'Meta': {'ordering': "[u'name']", 'object_name': 'Service'}, 'additional_agents': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'to': u"orm['services.Agent']", 'null': 'True', 'blank': 'True'}), 'auth_method': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '1', 'db_index': 'True'}), 'auth_pass': ('django.db.models.fields.CharField', [], {'max_length': '250', 'null': 'True', 'blank': 'True'}), 'auth_user': ('django.db.models.fields.CharField', [], {'max_length': '250', 'null': 'True', 'blank': 'True'}), 'base_referer': ('django.db.models.fields.URLField', [], {'default': "u''", 'max_length': '200', 'null': 'True', 'blank': 'True'}), 'base_useragent': ('django.db.models.fields.CharField', [], {'default': "u'Mozilla/5.0 (X11; U; Linux x86_64; pl-PL; rv:1.9.2.3) Gecko/20100423 Ubuntu/10.04 (lucid) Firefox/3.6.3'", 'max_length': '250'}), 'comments': ('django.db.models.fields.TextField', [], {'null': 'True', 'blank': 'True'}), 'connection_timeout': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '30'}), 'created': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'blank': 'True'}), 'hosting': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'is_active': ('django.db.models.fields.BooleanField', [], {'default': 'True', 'db_index': 'True'}), 'is_core_service': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_index': 'True'}), 'is_technical_break': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_index': 'True'}), 'modified': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'auto_now_add': 'True', 'blank': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '200', 'db_index': 'True'}), 'order': ('django.db.models.fields.PositiveIntegerField', [], {'default': '100'}), 'performance_issues_min_probes_count': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '8'}), 'performance_issues_time': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '15'}), 'response_code': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '200'}), 'sensitivity': ('django.db.models.fields.DecimalField', [], {'default': "'0.5'", 'max_digits': '3', 'decimal_places': '2'}), 'service_not_working_min_probes_count': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '8'}), 'service_working_min_probes_count': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '5'}), 'time_delta': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '10'}), 'url': ('django.db.models.fields.URLField', [], {'max_length': '200'}) }, u'stats.incident': { 'Meta': {'object_name': 'Incident'}, 'end_date': ('django.db.models.fields.DateTimeField', [], {}), u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'incident_type': ('django.db.models.fields.CharField', [], {'default': "u'failure'", 'max_length': '15'}), 'is_closed': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_index': 'True'}), 'service': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['services.Service']"}), 'start_date': ('django.db.models.fields.DateTimeField', [], {}) } } complete_apps = ['stats']
# -*- coding: utf-8 -*- import datetime from south.db import db from south.v2 import SchemaMigration from django.db import models class Migration(SchemaMigration): def forwards(self, orm): # Adding field 'Incident.incident_type' db.add_column(u'stats_incident', 'incident_type', self.gf('django.db.models.fields.CharField')(default=u'failure', max_length=15), keep_default=False) def backwards(self, orm): # Deleting field 'Incident.incident_type' db.delete_column(u'stats_incident', 'incident_type') models = { u'services.agent': { 'Meta': {'object_name': 'Agent'}, u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'is_active': ('django.db.models.fields.BooleanField', [], {'default': 'True', 'db_index': 'True'}), 'is_main': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_index': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '75', 'db_index': 'True'}), 'queue': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['services.Queue']", 'null': 'True', 'on_delete': 'models.PROTECT', 'blank': 'True'}), 'salt': ('django.db.models.fields.CharField', [], {'max_length': '16'}) }, u'services.queue': { 'Meta': {'object_name': 'Queue'}, u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '75', 'db_index': 'True'}) }, u'services.service': { 'Meta': {'ordering': "[u'name']", 'object_name': 'Service'}, 'additional_agents': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'to': u"orm['services.Agent']", 'null': 'True', 'blank': 'True'}), 'auth_method': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '1', 'db_index': 'True'}), 'auth_pass': ('django.db.models.fields.CharField', [], {'max_length': '250', 'null': 'True', 'blank': 'True'}), 'auth_user': ('django.db.models.fields.CharField', [], {'max_length': '250', 'null': 'True', 'blank': 'True'}), 'base_referer': ('django.db.models.fields.URLField', [], {'default': "u''", 'max_length': '200', 'null': 'True', 'blank': 'True'}), 'base_useragent': ('django.db.models.fields.CharField', [], {'default': "u'Mozilla/5.0 (X11; U; Linux x86_64; pl-PL; rv:1.9.2.3) Gecko/20100423 Ubuntu/10.04 (lucid) Firefox/3.6.3'", 'max_length': '250'}), 'comments': ('django.db.models.fields.TextField', [], {'null': 'True', 'blank': 'True'}), 'connection_timeout': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '30'}), 'created': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'blank': 'True'}), 'hosting': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'is_active': ('django.db.models.fields.BooleanField', [], {'default': 'True', 'db_index': 'True'}), 'is_core_service': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_index': 'True'}), 'is_technical_break': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_index': 'True'}), 'modified': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'auto_now_add': 'True', 'blank': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '200', 'db_index': 'True'}), 'order': ('django.db.models.fields.PositiveIntegerField', [], {'default': '100'}), 'performance_issues_min_probes_count': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '8'}), 'performance_issues_time': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '15'}), 'response_code': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '200'}), 'sensitivity': ('django.db.models.fields.DecimalField', [], {'default': "'0.5'", 'max_digits': '3', 'decimal_places': '2'}), 'service_not_working_min_probes_count': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '8'}), 'service_working_min_probes_count': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '5'}), 'time_delta': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '10'}), 'url': ('django.db.models.fields.URLField', [], {'max_length': '200'}) }, u'stats.incident': { 'Meta': {'object_name': 'Incident'}, 'end_date': ('django.db.models.fields.DateTimeField', [], {}), u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'incident_type': ('django.db.models.fields.CharField', [], {'default': "u'failure'", 'max_length': '15'}), 'is_closed': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_index': 'True'}), 'service': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['services.Service']"}), 'start_date': ('django.db.models.fields.DateTimeField', [], {}) } } complete_apps = ['stats']
en
0.530649
# -*- coding: utf-8 -*- # Adding field 'Incident.incident_type' # Deleting field 'Incident.incident_type'
2.176739
2
Club_Performance_BenjaminMeco_Final.py
jesperiksson/SoccermaticsForPython
0
6632177
<reponame>jesperiksson/SoccermaticsForPython<gh_stars>0 #!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Sun Oct 25 10:35:12 2020 @author: BenjaminMeco """ import matplotlib.pyplot as plt import numpy as np import json import pandas as pd from pandas import json_normalize from FCPython import createPitch import statsmodels.formula.api as smf def factorial(n): if(n == 0): return 1 else: return n*factorial(n-1) def pois(l,k): return (l**k)*np.exp(-l)/factorial(k) # this is just a help for getting the data def indexOf(team_name,team_list): index = -1 for element in team_list: index = index + 1 if(element[0] == team_name): return index return -1 # for getting the distributions: def getWeights(arr,size): weights = np.zeros(size) W = 0 for k in range(0,size): W = W + arr[k] for k in range(0,size): weights[k] = arr[k]/W return weights def outcomeWeights(r,probabilities): s = probabilities[0] count = 0 for p in probabilities: if(s > r): return count else: count = count + 1 s = s + p return count # this makes a simulation using weights as the probability distribution def simulate(team_list): points = np.zeros(len(team_list)) for i in range(0,len(team_list)): for j in range(1,len(team_list)): t_1 = team_list[i] t_2 = team_list[(i+j)%len(team_list)] lambda_1 = (t_1[1] + t_2[2])/2 lambda_2 = (t_1[2] + t_2[1])/2 g_1 = int(np.random.poisson(lambda_1)) g_2 = int(np.random.poisson(lambda_2)) if(g_1 > g_2): points[i] = points[i] + 3 elif(g_1 < g_2): points[(i+j)%len(team_list)] = points[(i+j)%len(team_list)] + 3 else: points[i] = points[i] + 1 points[(i+j)%len(team_list)] = points[(i+j)%len(team_list)] + 1 result = [] for i in range(0,len(team_list)): result = result + [[points[i],team_list[i][0]]] return result def simulMany(team_list,N): team_placements = [] for t in team_list: team_placements = team_placements + [[t[0],np.zeros(21)]] for n in range(N): # do a simulation: s = sorted(simulate(team_list)) # get the placements: for i in range(0,len(s)): e = s[i] index = indexOf(e[1],team_list) team_placements[index][1][20-i] = team_placements[index][1][20-i] + 1 for t in team_placements: t[1] = getWeights(t[1],21)[1:] return team_placements #Load the data with open('Wyscout/matches/matches_England.json') as data_file: data = json.load(data_file) df = json_normalize(data, sep = "_") # first we extract the relevant bits of the matches: matches = [] for i,game in df.iterrows(): label = game['label'] dash = label.find(" -") comma = label.find(",") team_1 = label[0:dash] team_2 = label[dash+3:comma] score_1 = label[comma+2:comma+3] score_2 = label[comma+6:] matches = matches + [[team_1,score_1,team_2,score_2]] # now we make the distributions for each team: teamList = [] for m in matches: index_1 = indexOf(m[0],teamList) index_2 = indexOf(m[2],teamList) # update the data for the first team if(index_1 == -1): new_team = [m[0],0,0] new_team[1] = int(m[1]) new_team[2] = int(m[3]) teamList = teamList + [new_team] else: teamList[index_1][1] = teamList[index_1][1] + int(m[1]) teamList[index_1][2] = teamList[index_1][2] + int(m[3]) # update the data for the second team if(index_2 == -1): new_team = [m[2],0,0] new_team[1] = int(m[3]) new_team[2] = int(m[1]) teamList = teamList + [new_team] else: teamList[index_2][1] = teamList[index_2][1] + int(m[3]) teamList[index_2][2] = teamList[index_2][2] + int(m[1]) teamList.sort() # now we get the desired data for the weights and the poisson distributions: teamPoisson = [] for t in teamList: teamPoisson = teamPoisson + [[t[0],t[1]/38,t[2]/38]] # finally some simulations, first with the Poisson distributions: N = 10000 alph = 0.8 W = 0.25 team_placements = simulMany(teamPoisson,N) col = (1,0,0) c = -1 plt.figure(dpi = 160) for t in team_placements: if(t[0] == "Liverpool" or t[0] == "Manchester City" or t[0] == "Manchester United"): plt.bar([k+c*(W + 0.03) for k in range(1,21)],t[1], color = col, label = t[0],alpha = 0.9,width = W) c = c+1 if(col == (1,0,0)): col = (0,1,0) else: col = (0,0,1) plt.xlabel("Placement") plt.ylabel("Probability of placement") plt.xticks(range(1,21)) plt.xlim(0,8) plt.legend() plt.show() # next we look at how the performance of liverpool changes when they # improve the offence/defence or both. We do this by changing their parameters in the # poisson distribution. lambda_off = teamPoisson[indexOf("Liverpool",teamPoisson)][1] lambda_def = teamPoisson[indexOf("Liverpool",teamPoisson)][2] # first we look at improving offence: plt.figure(dpi = 160) c = -1 for d in np.linspace(20,10,2): print(str(d)) # make the modifications: teamPoisson[indexOf("Liverpool",teamPoisson)][1] = lambda_off + d/38 # simulate and plot the distributions of Liverpool: T = simulMany(teamPoisson,N) t = T[indexOf("Liverpool",T)] plt.bar([k+c*(W + 0.03) for k in range(1,21)],t[1], color = (0.5-c*0.5,0,0),width = W, label = "Scoring " +str(d) + " more goals", alpha = alph) c = c+1 plt.bar([k+c*(W + 0.03) for k in range(1,21)],team_placements[indexOf("Liverpool",team_placements)][1],color = "black", width = W, label = "Baseline") plt.xlabel("Placement") plt.ylabel("Probability of placement for Liverpool\n with improved offence") plt.xticks(range(1,21)) plt.xlim(0,10) plt.legend() plt.show() plt.figure(dpi = 160) # secondly we look at improving defence: c = -1 for d in np.linspace(20,10,2): print(str(d)) # make the modifications: teamPoisson[indexOf("Liverpool",teamPoisson)][2] = lambda_def-d/38 # simulate and plot the distributions of Liverpool: T = simulMany(teamPoisson,N) t = T[indexOf("Liverpool",T)] plt.bar([k+c*(W + 0.03) for k in range(1,21)],t[1], color = (0,0,0.5-c*0.5),width = W, label = "Conceding " +str(d) + " fewer goals",alpha = alph) c = c+1 plt.bar([k+c*(W + 0.03) for k in range(1,21)],team_placements[indexOf("Liverpool",team_placements)][1],color = "black",width = W, label = "Baseline") plt.xlabel("Placement") plt.ylabel("Probability of placement for Liverpool\n with defence") plt.xticks(range(1,21)) plt.xlim(0,10) plt.legend() plt.show() c = -1 col = (1,0,0) plt.figure(dpi = 160) for t in T: if(t[0] == "Liverpool" or t[0] == "Manchester City" or t[0] == "Manchester United"): plt.bar([k+c*(W + 0.03) for k in range(1,21)],t[1], color = col, label = t[0],alpha = 0.9,width = W) c = c+1 if(col == (1,0,0)): col = (0,1,0) else: col = (0,0,1) plt.xlabel("Placement") plt.ylabel("Probability of placement") plt.xticks(range(1,21)) plt.xlim(0,8) plt.legend() plt.show()
#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Sun Oct 25 10:35:12 2020 @author: BenjaminMeco """ import matplotlib.pyplot as plt import numpy as np import json import pandas as pd from pandas import json_normalize from FCPython import createPitch import statsmodels.formula.api as smf def factorial(n): if(n == 0): return 1 else: return n*factorial(n-1) def pois(l,k): return (l**k)*np.exp(-l)/factorial(k) # this is just a help for getting the data def indexOf(team_name,team_list): index = -1 for element in team_list: index = index + 1 if(element[0] == team_name): return index return -1 # for getting the distributions: def getWeights(arr,size): weights = np.zeros(size) W = 0 for k in range(0,size): W = W + arr[k] for k in range(0,size): weights[k] = arr[k]/W return weights def outcomeWeights(r,probabilities): s = probabilities[0] count = 0 for p in probabilities: if(s > r): return count else: count = count + 1 s = s + p return count # this makes a simulation using weights as the probability distribution def simulate(team_list): points = np.zeros(len(team_list)) for i in range(0,len(team_list)): for j in range(1,len(team_list)): t_1 = team_list[i] t_2 = team_list[(i+j)%len(team_list)] lambda_1 = (t_1[1] + t_2[2])/2 lambda_2 = (t_1[2] + t_2[1])/2 g_1 = int(np.random.poisson(lambda_1)) g_2 = int(np.random.poisson(lambda_2)) if(g_1 > g_2): points[i] = points[i] + 3 elif(g_1 < g_2): points[(i+j)%len(team_list)] = points[(i+j)%len(team_list)] + 3 else: points[i] = points[i] + 1 points[(i+j)%len(team_list)] = points[(i+j)%len(team_list)] + 1 result = [] for i in range(0,len(team_list)): result = result + [[points[i],team_list[i][0]]] return result def simulMany(team_list,N): team_placements = [] for t in team_list: team_placements = team_placements + [[t[0],np.zeros(21)]] for n in range(N): # do a simulation: s = sorted(simulate(team_list)) # get the placements: for i in range(0,len(s)): e = s[i] index = indexOf(e[1],team_list) team_placements[index][1][20-i] = team_placements[index][1][20-i] + 1 for t in team_placements: t[1] = getWeights(t[1],21)[1:] return team_placements #Load the data with open('Wyscout/matches/matches_England.json') as data_file: data = json.load(data_file) df = json_normalize(data, sep = "_") # first we extract the relevant bits of the matches: matches = [] for i,game in df.iterrows(): label = game['label'] dash = label.find(" -") comma = label.find(",") team_1 = label[0:dash] team_2 = label[dash+3:comma] score_1 = label[comma+2:comma+3] score_2 = label[comma+6:] matches = matches + [[team_1,score_1,team_2,score_2]] # now we make the distributions for each team: teamList = [] for m in matches: index_1 = indexOf(m[0],teamList) index_2 = indexOf(m[2],teamList) # update the data for the first team if(index_1 == -1): new_team = [m[0],0,0] new_team[1] = int(m[1]) new_team[2] = int(m[3]) teamList = teamList + [new_team] else: teamList[index_1][1] = teamList[index_1][1] + int(m[1]) teamList[index_1][2] = teamList[index_1][2] + int(m[3]) # update the data for the second team if(index_2 == -1): new_team = [m[2],0,0] new_team[1] = int(m[3]) new_team[2] = int(m[1]) teamList = teamList + [new_team] else: teamList[index_2][1] = teamList[index_2][1] + int(m[3]) teamList[index_2][2] = teamList[index_2][2] + int(m[1]) teamList.sort() # now we get the desired data for the weights and the poisson distributions: teamPoisson = [] for t in teamList: teamPoisson = teamPoisson + [[t[0],t[1]/38,t[2]/38]] # finally some simulations, first with the Poisson distributions: N = 10000 alph = 0.8 W = 0.25 team_placements = simulMany(teamPoisson,N) col = (1,0,0) c = -1 plt.figure(dpi = 160) for t in team_placements: if(t[0] == "Liverpool" or t[0] == "Manchester City" or t[0] == "Manchester United"): plt.bar([k+c*(W + 0.03) for k in range(1,21)],t[1], color = col, label = t[0],alpha = 0.9,width = W) c = c+1 if(col == (1,0,0)): col = (0,1,0) else: col = (0,0,1) plt.xlabel("Placement") plt.ylabel("Probability of placement") plt.xticks(range(1,21)) plt.xlim(0,8) plt.legend() plt.show() # next we look at how the performance of liverpool changes when they # improve the offence/defence or both. We do this by changing their parameters in the # poisson distribution. lambda_off = teamPoisson[indexOf("Liverpool",teamPoisson)][1] lambda_def = teamPoisson[indexOf("Liverpool",teamPoisson)][2] # first we look at improving offence: plt.figure(dpi = 160) c = -1 for d in np.linspace(20,10,2): print(str(d)) # make the modifications: teamPoisson[indexOf("Liverpool",teamPoisson)][1] = lambda_off + d/38 # simulate and plot the distributions of Liverpool: T = simulMany(teamPoisson,N) t = T[indexOf("Liverpool",T)] plt.bar([k+c*(W + 0.03) for k in range(1,21)],t[1], color = (0.5-c*0.5,0,0),width = W, label = "Scoring " +str(d) + " more goals", alpha = alph) c = c+1 plt.bar([k+c*(W + 0.03) for k in range(1,21)],team_placements[indexOf("Liverpool",team_placements)][1],color = "black", width = W, label = "Baseline") plt.xlabel("Placement") plt.ylabel("Probability of placement for Liverpool\n with improved offence") plt.xticks(range(1,21)) plt.xlim(0,10) plt.legend() plt.show() plt.figure(dpi = 160) # secondly we look at improving defence: c = -1 for d in np.linspace(20,10,2): print(str(d)) # make the modifications: teamPoisson[indexOf("Liverpool",teamPoisson)][2] = lambda_def-d/38 # simulate and plot the distributions of Liverpool: T = simulMany(teamPoisson,N) t = T[indexOf("Liverpool",T)] plt.bar([k+c*(W + 0.03) for k in range(1,21)],t[1], color = (0,0,0.5-c*0.5),width = W, label = "Conceding " +str(d) + " fewer goals",alpha = alph) c = c+1 plt.bar([k+c*(W + 0.03) for k in range(1,21)],team_placements[indexOf("Liverpool",team_placements)][1],color = "black",width = W, label = "Baseline") plt.xlabel("Placement") plt.ylabel("Probability of placement for Liverpool\n with defence") plt.xticks(range(1,21)) plt.xlim(0,10) plt.legend() plt.show() c = -1 col = (1,0,0) plt.figure(dpi = 160) for t in T: if(t[0] == "Liverpool" or t[0] == "Manchester City" or t[0] == "Manchester United"): plt.bar([k+c*(W + 0.03) for k in range(1,21)],t[1], color = col, label = t[0],alpha = 0.9,width = W) c = c+1 if(col == (1,0,0)): col = (0,1,0) else: col = (0,0,1) plt.xlabel("Placement") plt.ylabel("Probability of placement") plt.xticks(range(1,21)) plt.xlim(0,8) plt.legend() plt.show()
en
0.863498
#!/usr/bin/env python3 # -*- coding: utf-8 -*- Created on Sun Oct 25 10:35:12 2020 @author: BenjaminMeco # this is just a help for getting the data # for getting the distributions: # this makes a simulation using weights as the probability distribution # do a simulation: # get the placements: #Load the data # first we extract the relevant bits of the matches: # now we make the distributions for each team: # update the data for the first team # update the data for the second team # now we get the desired data for the weights and the poisson distributions: # finally some simulations, first with the Poisson distributions: # next we look at how the performance of liverpool changes when they # improve the offence/defence or both. We do this by changing their parameters in the # poisson distribution. # first we look at improving offence: # make the modifications: # simulate and plot the distributions of Liverpool: # secondly we look at improving defence: # make the modifications: # simulate and plot the distributions of Liverpool:
3.273476
3
Py57/main.py
xhexe/Py8R
0
6632178
<gh_stars>0 def longest_word(file): with open(file, "r") as f: words = f.read().split() longest_word = len(max(words, key=len)) return [word for word in words if len(word) == longest_word] print(longest_word("/home/xhexe/Py/Py8R/files/text.txt"))
def longest_word(file): with open(file, "r") as f: words = f.read().split() longest_word = len(max(words, key=len)) return [word for word in words if len(word) == longest_word] print(longest_word("/home/xhexe/Py/Py8R/files/text.txt"))
none
1
4.161389
4
turb2d/cip.py
narusehajime/turb2d
0
6632179
import numpy as np def cip_2d_M_advection( f, dfdx, dfdy, u, v, core, h_up, v_up, dx, dt, out_f=None, out_dfdx=None, out_dfdy=None, ): """Calculate one time step using M-type 2D cip method """ # First, the variables out and temp are allocated to # store the calculation results if out_f is None: out_f = np.empty(f.shape) if out_dfdx is None: out_dfdx = np.empty(dfdx.shape) if out_dfdy is None: out_dfdy = np.empty(dfdy.shape) # 1st step for horizontal advection D_x = -np.where(u > 0.0, 1.0, -1.0) * dx xi_x = -u * dt cip_1d_advection(f, dfdx, u, core, h_up, dx, dt, out_f=out_f, out_dfdx=out_dfdx) out_dfdy[core] = dfdy[core] - xi_x[core] / D_x[core] * ( dfdy[core] - dfdy[h_up[core]] ) # 2nd step for vertical advection D_y = -np.where(v > 0.0, 1.0, -1.0) * dx xi_y = -v * dt cip_1d_advection(out_f, dfdy, v, core, v_up, dx, dt, out_f=out_f, out_dfdx=out_dfdy) out_dfdx[core] = out_dfdx[core] - xi_y[core] / D_y[core] * ( out_dfdx[core] - out_dfdx[v_up[core]] ) return out_f, out_dfdx, out_dfdy def cip_1d_advection( f, dfdx, u, core, up_id, dx, dt, out_f=None, out_dfdx=None, ): """Calculate one time step using M-type 2D cip method """ # First, the variables out and temp are allocated to # store the calculation results if out_f is None: out_f = np.empty(f.shape) if out_dfdx is None: out_dfdx = np.empty(dfdx.shape) up = up_id[core] # 1st step for horizontal advection D_x = -np.where(u > 0.0, 1.0, -1.0) * dx xi_x = -u * dt a = (dfdx[core] + dfdx[up]) / (D_x[core] ** 2) + 2.0 * (f[core] - f[up]) / ( D_x[core] ** 3 ) b = ( 3.0 * (f[up] - f[core]) / (D_x[core] ** 2) - (2.0 * dfdx[core] + dfdx[up]) / D_x[core] ) out_f[core] = ( a * (xi_x[core] ** 3) + b * (xi_x[core] ** 2) + dfdx[core] * xi_x[core] + f[core] ) out_dfdx[core] = 3.0 * a * (xi_x[core] ** 2) + \ 2.0 * b * xi_x[core] + dfdx[core] return out_f, out_dfdx def cip_2d_nonadvection( f, dfdx, dfdy, G, u, v, core, h_up, h_down, v_up, v_down, dx, dt, out_f=None, out_dfdx=None, out_dfdy=None, ): if out_f is None: out_f = np.zeros(f.shape) if out_dfdx is None: out_dfdx = np.zeros(dfdx.shape) if out_dfdy is None: out_dfdy = np.zeros(dfdy.shape) D_x = -np.where(u > 0.0, 1.0, -1.0) * dx xi_x = -u * dt D_y = -np.where(v > 0.0, 1.0, -1.0) * dx xi_y = -v * dt # non-advection term out_f[core] = f[core] + G[core] * dt out_dfdx[core] = ( dfdx[core] + ((out_f[h_down] - f[h_down]) - (out_f[h_up] - f[h_up])) / (-2 * D_x[core]) - dfdx[core] * (xi_x[h_down] - xi_x[h_up]) / (2 * D_x[core]) ) out_dfdy[core] = dfdy[core] +((out_f[v_down] - f[v_down]) - (out_f[v_up] - f[v_up])) / (-2 * D_y[core]) - dfdy[ core ] * (xi_y[v_down] - xi_y[v_up]) / (2 * D_y[core]) return out_f, out_dfdx, out_dfdy def cip_2d_diffusion( u, v, nu_t, h_active, v_active, north, south, east, west, dx, dt, out_u=None, out_v=None, ): """Caclulate horizontal and vertical diffusion of velocities u and v """ if out_u is None: out_u = np.zeros(u.shape) if out_v is None: out_v = np.zeros(v.shape) out_u[h_active] = ( u[h_active] + nu_t[h_active] * dt * ( (u[east][h_active] - 2 * u[h_active] + u[west][h_active]) + (u[north][h_active] - 2 * u[h_active] + u[south][h_active]) ) / dx ** 2 ) out_v[v_active] = ( v[v_active] + nu_t[v_active] * dt * ( (v[east][v_active] - 2 * v[v_active] + v[west][v_active]) + (v[north][v_active] - 2 * v[v_active] + v[south][v_active]) ) / dx ** 2 ) return out_u, out_v def rcip_1d_advection(f, dfdx, u, core, up_id, dx, dt, out_f=None, out_dfdx=None): """ calculate 1 step of advection phase by rational function CIP method. Parameters ---------------- f : ndarray variable to be calculated dfdx : ndarray spatial gradient of the parameter f u : ndarray advection velocity of f core : ndarray indeces of core grids up : ndarray indeces of grids that locate upstream down : ndarray indeces of grids that locate downstream dx : float spatial grid spacing dt : float time step length out_f : ndarray resultant value of f out_dfdx : ndarray resultant value of dfdx Returns -------------------- out_f : ndarray output value of f out_dfdx : ndarray output value of dfdx """ if out_f is None: out_f = np.zeros(f.shape) if out_dfdx is None: out_dfdx = np.zeros(f.shape) up = up_id[core] # advection phase D = -np.where(u[core] > 0.0, 1.0, -1.0) * dx xi = -u * dt BB = np.zeros(D.shape) S = (f[up] - f[core]) / D dz_index = (S - dfdx[core]) * (dfdx[up] - S) > 0.0 BB[dz_index] = ( np.abs( (S[dz_index] - dfdx[core][dz_index]) / (dfdx[up][dz_index] - S[dz_index]) ) - 1.0 ) / D[dz_index] a = (dfdx[core] - S + (dfdx[up] - S) * (1.0 + BB * D)) / (D * D) b = S * BB + (S - dfdx[core]) / D - a * D c = dfdx[core] + f[core] * BB out_f[core] = (((a * xi[core] + b) * xi[core] + c) * xi[core] + f[core]) / ( 1.0 + BB * xi[core] ) out_dfdx[core] = ((3.0 * a * xi[core] + 2.0 * b) * xi[core] + c) / ( 1.0 + BB * xi[core] ) - out_f[core] * BB / (1.0 + BB * xi[core]) return out_f, out_dfdx def rcip_2d_M_advection( f, dfdx, dfdy, u, v, core, h_up, v_up, dx, dt, out_f=None, out_dfdx=None, out_dfdy=None, ): """Calculate one time step using M-type 2D cip method """ # First, the variables out and temp are allocated to # store the calculation results if out_f is None: out_f = np.empty(f.shape) if out_dfdx is None: out_dfdx = np.empty(dfdx.shape) if out_dfdy is None: out_dfdy = np.empty(dfdy.shape) # 1st step for horizontal advection rcip_1d_advection(f, dfdx, u, core, h_up, dx, dt, out_f=out_f, out_dfdx=out_dfdx) D_x = -np.where(u > 0.0, 1.0, -1.0) * dx xi_x = -u * dt out_dfdy[core] = dfdy[core] - xi_x[core] / D_x[core] * ( dfdy[core] - dfdy[h_up[core]] ) # 2nd step for vertical advection rcip_1d_advection( out_f, dfdy, v, core, v_up, dx, dt, out_f=out_f, out_dfdx=out_dfdy ) D_y = -np.where(v > 0.0, 1.0, -1.0) * dx xi_y = -v * dt out_dfdx[core] = out_dfdx[core] - xi_y[core] / D_y[core] * ( out_dfdx[core] - out_dfdx[v_up[core]] ) return out_f, out_dfdx, out_dfdy def shock_dissipation( f, p, core, north_id, south_id, east_id, west_id, dt, kappa2, kappa4, out=None, ): """ adding artificial viscosity for numerical stability Parameters ------------------ f : ndarray, float parameter for which the artificial viscosity is applied h : ndarray, float flow height core : ndarray, int indeces of core nodes or links north_id : ndarray, int indeces of nodes or links that locate north of core south_id : ndarray, int indeces of nodes or links that locate south of core east_id : ndarray, int indeces of nodes or links that locate east of core west_id : ndarray, int indeces of nodes or links that locate west of core """ n = f.shape[0] if out is None: out = np.zeros(n) nu_i = np.zeros(n, dtype=np.float) nu_j = np.zeros(n, dtype=np.float) eps_i_half2 = np.zeros(n, dtype=np.float) # eps_i_half4 = np.zeros(n, dtype=np.float) eps_j_half2 = np.zeros(n, dtype=np.float) # eps_j_half4 = np.zeros(n, dtype=np.float) d_i_half = np.zeros(n, dtype=np.float) d_j_half = np.zeros(n, dtype=np.float) north = north_id[core] south = south_id[core] east = east_id[core] west = west_id[core] # easteast = east_id[east] # northnorth = north_id[north] # First, artificial diffusion is applied to east-west direction nu_i[core] = np.abs(p[east] - 2 * p[core] + p[west]) / ( np.abs(p[east]) + 2 * np.abs(p[core]) + np.abs(p[west]) + 10 ** -20 ) eps_i_half2[core] = kappa2 * np.max([nu_i[east], nu_i[core]], axis=0) # eps_i_half4[core] = np.max( # [np.zeros_like(core), kappa4 - eps_i_half2[core]], axis=0) # d_i_half[core] = eps_i_half2[core] * ( # f[east] - f[core]) - eps_i_half4[core] * (f[easteast] - 3.0 * f[east] + # 3.0 * f[core] - f[west]) d_i_half[core] = eps_i_half2[core] * (f[east] - f[core]) # Next, artificial diffusion is applied to north-south direction nu_j[core] = np.abs(p[north] - 2 * p[core] + p[south]) / ( np.abs(p[north]) + 2 * np.abs(p[core]) + np.abs(p[south]) + 10 ** -20 ) eps_j_half2[core] = kappa2 * np.max([nu_j[north], nu_j[core]], axis=0) # eps_j_half4[core] = np.max( # [np.zeros_like(core), kappa4 - eps_j_half2[core]], axis=0) # d_j_half[core] = eps_j_half2[core] * (f[north] - f[core]) - eps_j_half4[ # core] * (f[northnorth] - 3.0 * f[north] + 3.0 * f[core] - f[south]) d_j_half[core] = eps_j_half2[core] * (f[north] - f[core]) # apply artificial diffusion out[core] = ( f[core] + d_i_half[core] - d_i_half[west] + d_j_half[core] - d_j_half[south] ) return out def update_gradient( f, f_new, dfdx, dfdy, core, north, south, east, west, dx, dt, out_dfdx=None, out_dfdy=None, ): """Update gradients when main variables are updated """ if out_dfdx is None: out_dfdx = np.zeros(dfdx.shape[0], dtype=np.float) if out_dfdy is None: out_dfdx = np.zeros(dfdy.shape[0], dtype=np.float) # non-advection term out_dfdx[core] = dfdx[core] + ( (f_new[east] - f[east]) - (f_new[west] - f[west]) ) / (2 * dx) out_dfdy[core] = dfdy[core] + ( (f_new[north] - f[north]) - (f_new[south] - f[south]) ) / (2 * dx) def update_gradient2( f, dfdx, dfdy, u, v, core, north, south, east, west, dx, dt, out_dfdx=None, out_dfdy=None, ): """Update gradients when main variables are updated """ if out_dfdx is None: out_dfdx = np.zeros(dfdx.shape[0], dtype=np.float) if out_dfdy is None: out_dfdx = np.zeros(dfdy.shape[0], dtype=np.float) # non-advection term out_dfdx[core] = ( dfdx[core] - ( (f[east] - f[west]) * (u[east] - u[west]) / (2 * dx) ** 2 + (f[north] - f[south]) * (v[east] - v[west]) / (2 * dx) ** 2 ) * dt ) out_dfdy[core] = ( dfdy[core] - ( (f[east] - f[west]) * (u[north] - u[south]) / (2 * dx) ** 2 + (f[north] - f[south]) * (v[north] - v[south]) / (2 * dx) ** 2 ) * dt ) class CIP2D: """ CIP Direct 2D scheme parameters --------------------- max_number_of_grids : int maximum number of grids that may be used in this solver """ def __init__(self, max_number_of_grids): self.XX = np.empty(max_number_of_grids, dtype=float) self.YY = np.empty(max_number_of_grids, dtype=float) self.Ddx = np.empty(max_number_of_grids, dtype=float) self.Ddy = np.empty(max_number_of_grids, dtype=float) self.xup = np.empty(max_number_of_grids, dtype=int) self.yup = np.empty(max_number_of_grids, dtype=int) self.xyup = np.empty(max_number_of_grids, dtype=int) self.C30 = np.empty(max_number_of_grids, dtype=float) self.C20 = np.empty(max_number_of_grids, dtype=float) self.C03 = np.empty(max_number_of_grids, dtype=float) self.C02 = np.empty(max_number_of_grids, dtype=float) self.tmp = np.empty(max_number_of_grids, dtype=float) self.tmq = np.empty(max_number_of_grids, dtype=float) self.C12 = np.empty(max_number_of_grids, dtype=float) self.C21 = np.empty(max_number_of_grids, dtype=float) self.C11 = np.empty(max_number_of_grids, dtype=float) def run( self, f, dfdx, dfdy, u, v, core, h_up, v_up, dx, dt, out_f=None, out_dfdx=None, out_dfdy=None, ): """run this solver to calculate advection transport of a variable f parameters ---------------------- f : ndarray, float A variable to calculate """ if out_f is None: out_f = np.zeros_like(f) if out_dfdx is None: out_dfdx = np.zeros_like(f) if out_dfdy is None: out_dfdy = np.zeros_like(f) XX = self.XX YY = self.YY Ddx = self.Ddx Ddy = self.Ddy xup = self.xup yup = self.yup xyup = self.xyup XX[core] = -u[core] * dt YY[core] = -v[core] * dt Ddx[core] = np.where(u[core] > 0.0, 1.0, -1.0) * dx Ddy[core] = np.where(v[core] > 0.0, 1.0, -1.0) * dx xup[core] = h_up[core] yup[core] = v_up[core] xyup[core] = v_up[h_up[core]] tmp = self.tmp tmq = self.tmq self.C30[core] = ( (dfdx[xup[core]] + dfdx[core]) * Ddx[core] - 2.0 * (f[core] - f[xup[core]]) ) / (Ddx[core] * Ddx[core] * Ddx[core]) self.C20[core] = ( 3.0 * (f[xup[core]] - f[core]) + (dfdx[xup[core]] + 2.0 * dfdx[core]) * Ddx[core] ) / (Ddx[core] * Ddx[core]) self.C03[core] = ( (dfdy[yup[core]] + dfdy[core]) * Ddy[core] - 2.0 * (f[core] - f[yup[core]]) ) / (Ddy[core] * Ddy[core] * Ddy[core]) self.C02[core] = ( 3.0 * (f[yup[core]] - f[core]) + (dfdy[yup[core]] + 2.0 * dfdy[core]) * Ddy[core] ) / (Ddy[core] * Ddy[core]) self.tmp[core] = f[core] - f[yup[core]] - f[xup[core]] + f[xyup[core]] self.tmq[core] = dfdy[xup[core]] - dfdy[core] self.C12[core] = (-tmp[core] - tmq[core] * Ddy[core]) / ( Ddx[core] * Ddy[core] * Ddy[core] ) self.C21[core] = (-tmp[core] - (dfdx[yup[core]] - dfdx[core]) * Ddx[core]) / ( Ddx[core] * Ddx[core] * Ddy[core] ) self.C11[core] = (-tmq[core] + self.C21[core] * Ddx[core] * Ddx[core]) / ( Ddx[core] ) out_f[core] = ( ( (self.C30[core] * XX[core] + self.C21[core] * YY[core] + self.C20[core]) * XX[core] + self.C11[core] * YY[core] + dfdx[core] ) * XX[core] + ( (self.C03[core] * YY[core] + self.C12[core] * XX[core] + self.C02[core]) * YY[core] + dfdy[core] ) * YY[core] + f[core] ) out_dfdx[core] = ( ( 3.0 * self.C30[core] * XX[core] + 2.0 * (self.C21[core] * YY[core] + self.C20[core]) ) * XX[core] + (self.C12[core] * YY[core] + self.C11[core]) * YY[core] + dfdx[core] ) out_dfdy[core] = ( ( 3.0 * self.C03[core] * YY[core] + 2.0 * (self.C12[core] * XX[core] + self.C02[core]) ) * YY[core] + (self.C21[core] * XX[core] + self.C11[core]) * XX[core] + dfdy[core] ) return out_f, out_dfdx, out_dfdy def rcip_2d_advection( f, dfdx, dfdy, u, v, core, h_up, v_up, dx, dt, out_f=None, out_dfdx=None, out_dfdy=None, ): """Direct 2D calculation of advection by R-CIP method """ if out_f is None: out_f = np.zeros(f.shape[0]) if out_dfdx is None: out_dfdx = np.zeros(f.shape[0]) if out_dfdy is None: out_dfdy = np.zeros(f.shape[0]) XX = -u[core] * dt YY = -v[core] * dt Ddx = np.where(u[core] > 0.0, -1.0, 1.0) * dx Ddy = np.where(v[core] > 0.0, -1.0, 1.0) * dx xup = h_up[core] yup = v_up[core] xyup = (v_up[h_up])[core] a01 = np.zeros(core.shape[0]) a10 = np.zeros(core.shape[0]) b01 = np.zeros(core.shape[0]) b10 = np.zeros(core.shape[0]) Sx = (f[xup] - f[core]) / Ddx Sy = (f[yup] - f[core]) / Ddy a10 = np.where(dfdx[core] * dfdx[xup] < 0, 1.0, 0.0) a01 = np.where(dfdy[core] * dfdy[yup] < 0, 1.0, 0.0) b10 = (np.abs((Sx - dfdx[core]) / (dfdx[xup] - Sx + 1.0 * 10 ** -10)) - 1) / Ddx b01 = (np.abs((Sy - dfdy[core]) / (dfdy[yup] - Sy + 1.0 * 10 ** -10)) - 1) / Ddy C00 = f[core] C10 = dfdx[core] + a10 * b10 * C00 C01 = dfdy[core] + a01 * b01 * C00 # C30 = ((dfdx[xup] + dfdx[core]) * Ddx - 2.0 * # (f[core] - f[xup])) / (Ddx * Ddx * Ddx) C30 = ((1 + a10 * b10 * Ddx) * (dfdx[xup] - Sx) + dfdx[core] - Sx) / (Ddx * Ddx) # C20 = (3.0 * (f[xup] - f[core]) + # (dfdx[xup] + 2.0 * dfdx[core]) * Ddx) / (Ddx * Ddx) C20 = ((1 + a10 * b10 * Ddx) * f[xup] - C00 - C10 * Ddx) / (Ddx * Ddx) - C30 * Ddx # C03 = ((dfdy[yup] + dfdy[core]) * Ddy - 2.0 * # (f[core] - f[yup])) / (Ddy * Ddy * Ddy) C03 = ((1 + a01 * b01 * Ddy) * (dfdy[yup] - Sy) + dfdy[core] - Sy) / (Ddy * Ddy) # C02 = (3.0 * (f[yup] - f[core]) + # (dfdy[yup] + 2.0 * dfdy[core]) * Ddy) / (Ddy * Ddy) C02 = ((1 + a01 * b01 * Ddy) * f[yup] - C00 - C01 * Ddy) / (Ddy * Ddy) - C03 * Ddy # tmp = f[core] - f[yup] - f[xup] + f[xyup] # tmq = dfdy[xup] - dfdy[core] C11 = ( (a01 * b01 * f[xup] + (1.0 + a10 * b10 * Ddx) * dfdy[xup]) / Ddx + (a10 * b10 * f[yup] + (1.0 + a01 * b01 * Ddy) * dfdx[yup]) / Ddy + (C00 - (1.0 + a10 * b10 * Ddx + a01 * b01 * Ddy) * f[xyup]) / Ddx / Ddy + C30 * Ddx * Ddx / Ddy + C03 * Ddy * Ddy / Ddx + C20 * Ddx / Ddy + C02 * Ddy / Ddx ) # C12 = (-tmp - tmq * Ddy) / (Ddx * Ddy * Ddy) C12 = (a10 * b10 * f[yup] + (1 + a01 * b01 * Ddy) * dfdx[yup] - C10) / ( Ddy * Ddy ) - C11 / Ddy # C21 = (-tmp - (dfdx[yup] - dfdx[core]) * Ddx) / (Ddx * Ddx * Ddy) C21 = (a01 * b01 * f[xup] + (1 + a10 * b10 * Ddx) * dfdy[xup] - C01) / ( Ddx * Ddx ) - C11 / Ddx # C11 = (-tmq + C21 * Ddx * Ddx) / (Ddx) out_f[core] = ( ((C30 * XX + C21 * YY + C20) * XX + C11 * YY + C10) * XX + ((C03 * YY + C12 * XX + C02) * YY + C01) * YY + C00 ) / (1 + a10 * b10 * XX + a01 * b01 * YY) out_dfdx[core] = ( (3.0 * C30 * XX + 2.0 * (C21 * YY + C20)) * XX + (C12 * YY + C11) * YY + C10 - a10 * b10 * out_f[core] ) / (1 + a10 * b10 * XX + a01 * b01 * YY) out_dfdy[core] = ( (3.0 * C03 * YY + 2.0 * (C12 * XX + C02)) * YY + (C21 * XX + C11) * XX + C01 - a01 * b01 * out_f[core] ) / (1 + a10 * b10 * XX + a01 * b01 * YY) return out_f, out_dfdx, out_dfdy def cubic_interp_1d(f, dfdx, core, iplus, iminus, dx, out=None): """interpolate values to links or nodes by cubic function Interplated values at the grid between "iplus" and "iminus" is returned. Parameters -------------------------- f : ndarray, float values to be interpolated dfdx : ndarray, float spatial gradient of f iplus : ndarray, int grid id of (i + dx / 2) iminus : ndarray, int grid id of (i - dx / 2) dx : ndarray, float grid spacing out : ndarray, float interpolated values between grids of iplus and iminus """ if out is None: out = np.empty(iplus.shape) # interplation by cubic function D_x = -dx xi_x = -dx / 2.0 a = (dfdx[iplus] + dfdx[iminus]) / (D_x ** 2) + 2.0 * (f[iplus] - f[iminus]) / ( D_x ** 3 ) b = ( 3.0 * (f[iminus] - f[iplus]) / (D_x ** 2) - (2.0 * dfdx[iplus] + dfdx[iminus]) / D_x ) out[core] = a * (xi_x ** 3) + b * (xi_x ** 2) + \ dfdx[iplus] * xi_x + f[iplus] return out def rcubic_interp_1d(f, dfdx, core, iplus, iminus, dx, out=None): """interpolate values to links or nodes by cubic function Interplated values at the grid between "iplus" and "iminus" is returned. Parameters -------------------------- f : ndarray, float values to be interpolated dfdx : ndarray, float spatial gradient of f iplus : ndarray, int grid id of (i + dx / 2) iminus : ndarray, int grid id of (i - dx / 2) dx : ndarray, float grid spacing out : ndarray, float interpolated values between grids of iplus and iminus """ if out is None: out = np.zeros(f.shape) # advection phase D = -dx xi = -dx / 2.0 BB = np.zeros(core.shape, dtype=float) S = (f[iminus] - f[iplus]) / D dz_index = (S - dfdx[iplus]) * (dfdx[iminus] - S) > 0.0 BB[dz_index] = ( np.abs( (S[dz_index] - dfdx[iplus][dz_index]) / (dfdx[iminus][dz_index] - S[dz_index]) ) - 1.0 ) / D a = (dfdx[iplus] - S + (dfdx[iminus] - S) * (1.0 + BB * D)) / (D ** 2) b = S * BB + (S - dfdx[iplus]) / D - a * D c = dfdx[iplus] + f[iplus] * BB out[core] = (((a * xi + b) * xi + c) * xi + f[iplus]) / (1.0 + BB * xi) # adjust negative values negative_value = out[core] < 0 out[core][negative_value] = ( f[iplus][negative_value] + f[iminus][negative_value] ) / 2.0 return out def forester_filter( f, core, east_id, west_id, north_id, south_id, nu_f=0.1, out_f=None, ): """ Forester filter for removing negative values from Concentration and Flow depth """ if out_f is None: out_f = np.zeros_like(f) out_f[:] = f[:] east = east_id[core] west = west_id[core] north = north_id[core] south = south_id[core] out_f[core] += ( nu_f * (f[east] + f[west] + f[north] + f[south] - 4.0 * f[core]) / 4.0 ) out_f[east] -= nu_f * (f[east] - f[core]) / 4.0 out_f[west] -= nu_f * (f[west] - f[core]) / 4.0 out_f[north] -= nu_f * (f[north] - f[core]) / 4.0 out_f[south] -= nu_f * (f[south] - f[core]) / 4.0 return out_f class Jameson: """ Jameson filter for smoothing the variables Parameters ------------------- tc: TurbudityCurrent2D Instance of TurbidityCurrent2D to obtain necessary parameters """ def __init__(self, tc): self.number_of_nodes = tc.grid.number_of_nodes self.number_of_links = tc.grid.number_of_links self.node_east = tc.node_east self.node_west = tc.node_west self.node_north = tc.node_north self.node_south = tc.node_south self.link_east = tc.link_east self.link_west = tc.link_west self.link_north = tc.link_north self.link_south = tc.link_south self.link_horiz = tc.grid.horizontal_links self.link_vert = tc.grid.vertical_links self.east_node_at_horizontal_link = tc.east_node_at_horizontal_link self.west_node_at_horizontal_link = tc.west_node_at_horizontal_link self.north_node_at_vertical_link = tc.north_node_at_vertical_link self.south_node_at_vertical_link = tc.south_node_at_vertical_link self.east_link_at_node = tc.east_link_at_node self.west_link_at_node = tc.west_link_at_node self.north_link_at_node = tc.north_link_at_node self.south_link_at_node = tc.south_link_at_node self.kappa = tc.kappa self.kappa = tc.kappa self.nu_x = np.zeros(self.number_of_nodes) self.nu_y = np.zeros(self.number_of_nodes) self.nu_x_link = np.zeros(self.number_of_links) self.nu_y_link = np.zeros(self.number_of_links) self.eps_link = np.zeros(self.number_of_links) self.eps_node_horiz = np.zeros(self.number_of_nodes) self.eps_node_vert = np.zeros(self.number_of_nodes) def update_artificial_viscosity(self, p, p_link): """ update artificial viscosity at nodes (nu) and links (eps) paramters ------------------- p : ndarray, float pressure at nodes p_link : ndarray, float pressure at links """ # artificial viscosity coefficient at links self.nu_x_link[self.link_horiz] = np.abs( p_link[self.link_east[self.link_horiz]] - 2 * p_link[self.link_horiz] + p_link[self.link_west[self.link_horiz]] ) / ( p_link[self.link_east[self.link_horiz]] + 2 * p_link[self.link_horiz] + p_link[self.link_west[self.link_horiz]] + 10 ** -20 ) self.nu_y_link[self.link_vert] = np.abs( p_link[self.link_north[self.link_vert]] - 2 * p_link[self.link_vert] + p_link[self.link_south[self.link_vert]] ) / ( p_link[self.link_north[self.link_vert]] + 2 * p_link[self.link_vert] + p_link[self.link_south[self.link_vert]] + 10 ** -20 ) # artificial viscosity coefficient at nodes self.nu_x[:] = np.abs( p[self.node_east] + p[self.node_north] + p[self.node_south] + p[self.node_west] - 4 * p ) / ( p[self.node_east] + p[self.node_west] + p[self.node_north] + p[self.node_south] + 4 * p + 10 ** -20 ) self.nu_y[:] = self.nu_x[:] # maximum artificial viscosity coefficient at links self.eps_link[self.link_horiz] = self.kappa * np.max( [ self.nu_x[self.east_node_at_horizontal_link[self.link_horiz]], self.nu_x[self.west_node_at_horizontal_link[self.link_horiz]], ], axis=0, ) self.eps_link[self.link_vert] = self.kappa * np.max( [ self.nu_y[self.north_node_at_vertical_link[self.link_vert]], self.nu_y[self.south_node_at_vertical_link[self.link_vert]], ], axis=0, ) # maximum artificial viscosity coefficient at nodes self.eps_node_horiz[:] = ( 0.01 * self.kappa * np.max( [ self.nu_x_link[self.east_link_at_node], self.nu_x_link[self.west_link_at_node], ], axis=0, ) ) self.eps_node_vert[:] = ( 0.01 * self.kappa * np.max( [ self.nu_y_link[self.north_link_at_node], self.nu_y_link[self.south_link_at_node], ], axis=0, ) ) def run(self, f, core, at="node", out=None): """ run one step of the Jameson filter paramters -------------------- f : ndarray, float variables to be filtered core : ndarray, int grid ids to apply the filter at : String, optional 'node', 'hlink', or 'vlink' for values on nodes, horizontal links or vertical links out : ndarray, float output returns -------------------- out : ndarray, float filtered variables """ if out is None: out = np.zeros_like(f) if at == "node": out[core] = ( f[core] + self.eps_link[self.east_link_at_node[core]] * (f[self.node_east[core]] - f[core]) - self.eps_link[self.west_link_at_node[core]] * (f[core] - f[self.node_west[core]]) + self.eps_link[self.north_link_at_node[core]] * (f[self.node_north[core]] - f[core]) - self.eps_link[self.south_link_at_node[core]] * (f[core] - f[self.node_south[core]]) ) if at == "hlink": out[core] = ( f[core] + self.eps_node_horiz[self.east_node_at_horizontal_link[core]] * (f[self.link_east[core]] - f[core]) - self.eps_node_horiz[self.west_node_at_horizontal_link[core]] * (f[core] - f[self.west_node_at_horizontal_link[core]]) ) if at == "vlink": out[core] = ( f[core] + self.eps_node_vert[self.north_node_at_vertical_link[core]] * (f[self.link_north[core]] - f[core]) - self.eps_node_vert[self.south_node_at_vertical_link[core]] * (f[core] - f[self.south_node_at_vertical_link[core]]) ) return out class SOR: """SOR method to solve inverse matrix """ def __init__( self, number_of_nodes, node_east, node_west, node_north, node_south, implicit_threshold, max_loop, alpha, update_boundary_conditions, ): self.implicit_threshold = implicit_threshold self.max_loop = max_loop self.alpha = alpha self.update_boundary_conditions = update_boundary_conditions self.node_east = node_east self.node_west = node_west self.node_north = node_north self.node_south = node_south self.a = np.empty(number_of_nodes) self.b = np.empty(number_of_nodes) self.c = np.empty(number_of_nodes) self.d = np.empty(number_of_nodes) self.e = np.empty(number_of_nodes) self.g = np.empty(number_of_nodes) self.w = np.empty(number_of_nodes) def run(self, p, core, out=None): if out is None: out = np.zeros_like(p) out[:] = p[:] err = 100.0 count = 0 core_size = core.shape[0] while err > self.implicit_threshold: self.w[core] = ( self.g[core] - self.b[core] * out[self.node_east[core]] - self.c[core] * out[self.node_west[core]] - self.d[core] * out[self.node_north[core]] - self.e[core] * out[self.node_south[core]] ) / self.a[core] err = np.linalg.norm(self.w[core] - out[core]) / ( core_size + 1.0 * 10 ** -20 ) out[core] = out[core] * (1 - self.alpha) + \ self.alpha * self.w[core] self.update_boundary_conditions(p=out) count += 1 if count == self.max_loop: print("Implicit calculation did not converge") return out return out
import numpy as np def cip_2d_M_advection( f, dfdx, dfdy, u, v, core, h_up, v_up, dx, dt, out_f=None, out_dfdx=None, out_dfdy=None, ): """Calculate one time step using M-type 2D cip method """ # First, the variables out and temp are allocated to # store the calculation results if out_f is None: out_f = np.empty(f.shape) if out_dfdx is None: out_dfdx = np.empty(dfdx.shape) if out_dfdy is None: out_dfdy = np.empty(dfdy.shape) # 1st step for horizontal advection D_x = -np.where(u > 0.0, 1.0, -1.0) * dx xi_x = -u * dt cip_1d_advection(f, dfdx, u, core, h_up, dx, dt, out_f=out_f, out_dfdx=out_dfdx) out_dfdy[core] = dfdy[core] - xi_x[core] / D_x[core] * ( dfdy[core] - dfdy[h_up[core]] ) # 2nd step for vertical advection D_y = -np.where(v > 0.0, 1.0, -1.0) * dx xi_y = -v * dt cip_1d_advection(out_f, dfdy, v, core, v_up, dx, dt, out_f=out_f, out_dfdx=out_dfdy) out_dfdx[core] = out_dfdx[core] - xi_y[core] / D_y[core] * ( out_dfdx[core] - out_dfdx[v_up[core]] ) return out_f, out_dfdx, out_dfdy def cip_1d_advection( f, dfdx, u, core, up_id, dx, dt, out_f=None, out_dfdx=None, ): """Calculate one time step using M-type 2D cip method """ # First, the variables out and temp are allocated to # store the calculation results if out_f is None: out_f = np.empty(f.shape) if out_dfdx is None: out_dfdx = np.empty(dfdx.shape) up = up_id[core] # 1st step for horizontal advection D_x = -np.where(u > 0.0, 1.0, -1.0) * dx xi_x = -u * dt a = (dfdx[core] + dfdx[up]) / (D_x[core] ** 2) + 2.0 * (f[core] - f[up]) / ( D_x[core] ** 3 ) b = ( 3.0 * (f[up] - f[core]) / (D_x[core] ** 2) - (2.0 * dfdx[core] + dfdx[up]) / D_x[core] ) out_f[core] = ( a * (xi_x[core] ** 3) + b * (xi_x[core] ** 2) + dfdx[core] * xi_x[core] + f[core] ) out_dfdx[core] = 3.0 * a * (xi_x[core] ** 2) + \ 2.0 * b * xi_x[core] + dfdx[core] return out_f, out_dfdx def cip_2d_nonadvection( f, dfdx, dfdy, G, u, v, core, h_up, h_down, v_up, v_down, dx, dt, out_f=None, out_dfdx=None, out_dfdy=None, ): if out_f is None: out_f = np.zeros(f.shape) if out_dfdx is None: out_dfdx = np.zeros(dfdx.shape) if out_dfdy is None: out_dfdy = np.zeros(dfdy.shape) D_x = -np.where(u > 0.0, 1.0, -1.0) * dx xi_x = -u * dt D_y = -np.where(v > 0.0, 1.0, -1.0) * dx xi_y = -v * dt # non-advection term out_f[core] = f[core] + G[core] * dt out_dfdx[core] = ( dfdx[core] + ((out_f[h_down] - f[h_down]) - (out_f[h_up] - f[h_up])) / (-2 * D_x[core]) - dfdx[core] * (xi_x[h_down] - xi_x[h_up]) / (2 * D_x[core]) ) out_dfdy[core] = dfdy[core] +((out_f[v_down] - f[v_down]) - (out_f[v_up] - f[v_up])) / (-2 * D_y[core]) - dfdy[ core ] * (xi_y[v_down] - xi_y[v_up]) / (2 * D_y[core]) return out_f, out_dfdx, out_dfdy def cip_2d_diffusion( u, v, nu_t, h_active, v_active, north, south, east, west, dx, dt, out_u=None, out_v=None, ): """Caclulate horizontal and vertical diffusion of velocities u and v """ if out_u is None: out_u = np.zeros(u.shape) if out_v is None: out_v = np.zeros(v.shape) out_u[h_active] = ( u[h_active] + nu_t[h_active] * dt * ( (u[east][h_active] - 2 * u[h_active] + u[west][h_active]) + (u[north][h_active] - 2 * u[h_active] + u[south][h_active]) ) / dx ** 2 ) out_v[v_active] = ( v[v_active] + nu_t[v_active] * dt * ( (v[east][v_active] - 2 * v[v_active] + v[west][v_active]) + (v[north][v_active] - 2 * v[v_active] + v[south][v_active]) ) / dx ** 2 ) return out_u, out_v def rcip_1d_advection(f, dfdx, u, core, up_id, dx, dt, out_f=None, out_dfdx=None): """ calculate 1 step of advection phase by rational function CIP method. Parameters ---------------- f : ndarray variable to be calculated dfdx : ndarray spatial gradient of the parameter f u : ndarray advection velocity of f core : ndarray indeces of core grids up : ndarray indeces of grids that locate upstream down : ndarray indeces of grids that locate downstream dx : float spatial grid spacing dt : float time step length out_f : ndarray resultant value of f out_dfdx : ndarray resultant value of dfdx Returns -------------------- out_f : ndarray output value of f out_dfdx : ndarray output value of dfdx """ if out_f is None: out_f = np.zeros(f.shape) if out_dfdx is None: out_dfdx = np.zeros(f.shape) up = up_id[core] # advection phase D = -np.where(u[core] > 0.0, 1.0, -1.0) * dx xi = -u * dt BB = np.zeros(D.shape) S = (f[up] - f[core]) / D dz_index = (S - dfdx[core]) * (dfdx[up] - S) > 0.0 BB[dz_index] = ( np.abs( (S[dz_index] - dfdx[core][dz_index]) / (dfdx[up][dz_index] - S[dz_index]) ) - 1.0 ) / D[dz_index] a = (dfdx[core] - S + (dfdx[up] - S) * (1.0 + BB * D)) / (D * D) b = S * BB + (S - dfdx[core]) / D - a * D c = dfdx[core] + f[core] * BB out_f[core] = (((a * xi[core] + b) * xi[core] + c) * xi[core] + f[core]) / ( 1.0 + BB * xi[core] ) out_dfdx[core] = ((3.0 * a * xi[core] + 2.0 * b) * xi[core] + c) / ( 1.0 + BB * xi[core] ) - out_f[core] * BB / (1.0 + BB * xi[core]) return out_f, out_dfdx def rcip_2d_M_advection( f, dfdx, dfdy, u, v, core, h_up, v_up, dx, dt, out_f=None, out_dfdx=None, out_dfdy=None, ): """Calculate one time step using M-type 2D cip method """ # First, the variables out and temp are allocated to # store the calculation results if out_f is None: out_f = np.empty(f.shape) if out_dfdx is None: out_dfdx = np.empty(dfdx.shape) if out_dfdy is None: out_dfdy = np.empty(dfdy.shape) # 1st step for horizontal advection rcip_1d_advection(f, dfdx, u, core, h_up, dx, dt, out_f=out_f, out_dfdx=out_dfdx) D_x = -np.where(u > 0.0, 1.0, -1.0) * dx xi_x = -u * dt out_dfdy[core] = dfdy[core] - xi_x[core] / D_x[core] * ( dfdy[core] - dfdy[h_up[core]] ) # 2nd step for vertical advection rcip_1d_advection( out_f, dfdy, v, core, v_up, dx, dt, out_f=out_f, out_dfdx=out_dfdy ) D_y = -np.where(v > 0.0, 1.0, -1.0) * dx xi_y = -v * dt out_dfdx[core] = out_dfdx[core] - xi_y[core] / D_y[core] * ( out_dfdx[core] - out_dfdx[v_up[core]] ) return out_f, out_dfdx, out_dfdy def shock_dissipation( f, p, core, north_id, south_id, east_id, west_id, dt, kappa2, kappa4, out=None, ): """ adding artificial viscosity for numerical stability Parameters ------------------ f : ndarray, float parameter for which the artificial viscosity is applied h : ndarray, float flow height core : ndarray, int indeces of core nodes or links north_id : ndarray, int indeces of nodes or links that locate north of core south_id : ndarray, int indeces of nodes or links that locate south of core east_id : ndarray, int indeces of nodes or links that locate east of core west_id : ndarray, int indeces of nodes or links that locate west of core """ n = f.shape[0] if out is None: out = np.zeros(n) nu_i = np.zeros(n, dtype=np.float) nu_j = np.zeros(n, dtype=np.float) eps_i_half2 = np.zeros(n, dtype=np.float) # eps_i_half4 = np.zeros(n, dtype=np.float) eps_j_half2 = np.zeros(n, dtype=np.float) # eps_j_half4 = np.zeros(n, dtype=np.float) d_i_half = np.zeros(n, dtype=np.float) d_j_half = np.zeros(n, dtype=np.float) north = north_id[core] south = south_id[core] east = east_id[core] west = west_id[core] # easteast = east_id[east] # northnorth = north_id[north] # First, artificial diffusion is applied to east-west direction nu_i[core] = np.abs(p[east] - 2 * p[core] + p[west]) / ( np.abs(p[east]) + 2 * np.abs(p[core]) + np.abs(p[west]) + 10 ** -20 ) eps_i_half2[core] = kappa2 * np.max([nu_i[east], nu_i[core]], axis=0) # eps_i_half4[core] = np.max( # [np.zeros_like(core), kappa4 - eps_i_half2[core]], axis=0) # d_i_half[core] = eps_i_half2[core] * ( # f[east] - f[core]) - eps_i_half4[core] * (f[easteast] - 3.0 * f[east] + # 3.0 * f[core] - f[west]) d_i_half[core] = eps_i_half2[core] * (f[east] - f[core]) # Next, artificial diffusion is applied to north-south direction nu_j[core] = np.abs(p[north] - 2 * p[core] + p[south]) / ( np.abs(p[north]) + 2 * np.abs(p[core]) + np.abs(p[south]) + 10 ** -20 ) eps_j_half2[core] = kappa2 * np.max([nu_j[north], nu_j[core]], axis=0) # eps_j_half4[core] = np.max( # [np.zeros_like(core), kappa4 - eps_j_half2[core]], axis=0) # d_j_half[core] = eps_j_half2[core] * (f[north] - f[core]) - eps_j_half4[ # core] * (f[northnorth] - 3.0 * f[north] + 3.0 * f[core] - f[south]) d_j_half[core] = eps_j_half2[core] * (f[north] - f[core]) # apply artificial diffusion out[core] = ( f[core] + d_i_half[core] - d_i_half[west] + d_j_half[core] - d_j_half[south] ) return out def update_gradient( f, f_new, dfdx, dfdy, core, north, south, east, west, dx, dt, out_dfdx=None, out_dfdy=None, ): """Update gradients when main variables are updated """ if out_dfdx is None: out_dfdx = np.zeros(dfdx.shape[0], dtype=np.float) if out_dfdy is None: out_dfdx = np.zeros(dfdy.shape[0], dtype=np.float) # non-advection term out_dfdx[core] = dfdx[core] + ( (f_new[east] - f[east]) - (f_new[west] - f[west]) ) / (2 * dx) out_dfdy[core] = dfdy[core] + ( (f_new[north] - f[north]) - (f_new[south] - f[south]) ) / (2 * dx) def update_gradient2( f, dfdx, dfdy, u, v, core, north, south, east, west, dx, dt, out_dfdx=None, out_dfdy=None, ): """Update gradients when main variables are updated """ if out_dfdx is None: out_dfdx = np.zeros(dfdx.shape[0], dtype=np.float) if out_dfdy is None: out_dfdx = np.zeros(dfdy.shape[0], dtype=np.float) # non-advection term out_dfdx[core] = ( dfdx[core] - ( (f[east] - f[west]) * (u[east] - u[west]) / (2 * dx) ** 2 + (f[north] - f[south]) * (v[east] - v[west]) / (2 * dx) ** 2 ) * dt ) out_dfdy[core] = ( dfdy[core] - ( (f[east] - f[west]) * (u[north] - u[south]) / (2 * dx) ** 2 + (f[north] - f[south]) * (v[north] - v[south]) / (2 * dx) ** 2 ) * dt ) class CIP2D: """ CIP Direct 2D scheme parameters --------------------- max_number_of_grids : int maximum number of grids that may be used in this solver """ def __init__(self, max_number_of_grids): self.XX = np.empty(max_number_of_grids, dtype=float) self.YY = np.empty(max_number_of_grids, dtype=float) self.Ddx = np.empty(max_number_of_grids, dtype=float) self.Ddy = np.empty(max_number_of_grids, dtype=float) self.xup = np.empty(max_number_of_grids, dtype=int) self.yup = np.empty(max_number_of_grids, dtype=int) self.xyup = np.empty(max_number_of_grids, dtype=int) self.C30 = np.empty(max_number_of_grids, dtype=float) self.C20 = np.empty(max_number_of_grids, dtype=float) self.C03 = np.empty(max_number_of_grids, dtype=float) self.C02 = np.empty(max_number_of_grids, dtype=float) self.tmp = np.empty(max_number_of_grids, dtype=float) self.tmq = np.empty(max_number_of_grids, dtype=float) self.C12 = np.empty(max_number_of_grids, dtype=float) self.C21 = np.empty(max_number_of_grids, dtype=float) self.C11 = np.empty(max_number_of_grids, dtype=float) def run( self, f, dfdx, dfdy, u, v, core, h_up, v_up, dx, dt, out_f=None, out_dfdx=None, out_dfdy=None, ): """run this solver to calculate advection transport of a variable f parameters ---------------------- f : ndarray, float A variable to calculate """ if out_f is None: out_f = np.zeros_like(f) if out_dfdx is None: out_dfdx = np.zeros_like(f) if out_dfdy is None: out_dfdy = np.zeros_like(f) XX = self.XX YY = self.YY Ddx = self.Ddx Ddy = self.Ddy xup = self.xup yup = self.yup xyup = self.xyup XX[core] = -u[core] * dt YY[core] = -v[core] * dt Ddx[core] = np.where(u[core] > 0.0, 1.0, -1.0) * dx Ddy[core] = np.where(v[core] > 0.0, 1.0, -1.0) * dx xup[core] = h_up[core] yup[core] = v_up[core] xyup[core] = v_up[h_up[core]] tmp = self.tmp tmq = self.tmq self.C30[core] = ( (dfdx[xup[core]] + dfdx[core]) * Ddx[core] - 2.0 * (f[core] - f[xup[core]]) ) / (Ddx[core] * Ddx[core] * Ddx[core]) self.C20[core] = ( 3.0 * (f[xup[core]] - f[core]) + (dfdx[xup[core]] + 2.0 * dfdx[core]) * Ddx[core] ) / (Ddx[core] * Ddx[core]) self.C03[core] = ( (dfdy[yup[core]] + dfdy[core]) * Ddy[core] - 2.0 * (f[core] - f[yup[core]]) ) / (Ddy[core] * Ddy[core] * Ddy[core]) self.C02[core] = ( 3.0 * (f[yup[core]] - f[core]) + (dfdy[yup[core]] + 2.0 * dfdy[core]) * Ddy[core] ) / (Ddy[core] * Ddy[core]) self.tmp[core] = f[core] - f[yup[core]] - f[xup[core]] + f[xyup[core]] self.tmq[core] = dfdy[xup[core]] - dfdy[core] self.C12[core] = (-tmp[core] - tmq[core] * Ddy[core]) / ( Ddx[core] * Ddy[core] * Ddy[core] ) self.C21[core] = (-tmp[core] - (dfdx[yup[core]] - dfdx[core]) * Ddx[core]) / ( Ddx[core] * Ddx[core] * Ddy[core] ) self.C11[core] = (-tmq[core] + self.C21[core] * Ddx[core] * Ddx[core]) / ( Ddx[core] ) out_f[core] = ( ( (self.C30[core] * XX[core] + self.C21[core] * YY[core] + self.C20[core]) * XX[core] + self.C11[core] * YY[core] + dfdx[core] ) * XX[core] + ( (self.C03[core] * YY[core] + self.C12[core] * XX[core] + self.C02[core]) * YY[core] + dfdy[core] ) * YY[core] + f[core] ) out_dfdx[core] = ( ( 3.0 * self.C30[core] * XX[core] + 2.0 * (self.C21[core] * YY[core] + self.C20[core]) ) * XX[core] + (self.C12[core] * YY[core] + self.C11[core]) * YY[core] + dfdx[core] ) out_dfdy[core] = ( ( 3.0 * self.C03[core] * YY[core] + 2.0 * (self.C12[core] * XX[core] + self.C02[core]) ) * YY[core] + (self.C21[core] * XX[core] + self.C11[core]) * XX[core] + dfdy[core] ) return out_f, out_dfdx, out_dfdy def rcip_2d_advection( f, dfdx, dfdy, u, v, core, h_up, v_up, dx, dt, out_f=None, out_dfdx=None, out_dfdy=None, ): """Direct 2D calculation of advection by R-CIP method """ if out_f is None: out_f = np.zeros(f.shape[0]) if out_dfdx is None: out_dfdx = np.zeros(f.shape[0]) if out_dfdy is None: out_dfdy = np.zeros(f.shape[0]) XX = -u[core] * dt YY = -v[core] * dt Ddx = np.where(u[core] > 0.0, -1.0, 1.0) * dx Ddy = np.where(v[core] > 0.0, -1.0, 1.0) * dx xup = h_up[core] yup = v_up[core] xyup = (v_up[h_up])[core] a01 = np.zeros(core.shape[0]) a10 = np.zeros(core.shape[0]) b01 = np.zeros(core.shape[0]) b10 = np.zeros(core.shape[0]) Sx = (f[xup] - f[core]) / Ddx Sy = (f[yup] - f[core]) / Ddy a10 = np.where(dfdx[core] * dfdx[xup] < 0, 1.0, 0.0) a01 = np.where(dfdy[core] * dfdy[yup] < 0, 1.0, 0.0) b10 = (np.abs((Sx - dfdx[core]) / (dfdx[xup] - Sx + 1.0 * 10 ** -10)) - 1) / Ddx b01 = (np.abs((Sy - dfdy[core]) / (dfdy[yup] - Sy + 1.0 * 10 ** -10)) - 1) / Ddy C00 = f[core] C10 = dfdx[core] + a10 * b10 * C00 C01 = dfdy[core] + a01 * b01 * C00 # C30 = ((dfdx[xup] + dfdx[core]) * Ddx - 2.0 * # (f[core] - f[xup])) / (Ddx * Ddx * Ddx) C30 = ((1 + a10 * b10 * Ddx) * (dfdx[xup] - Sx) + dfdx[core] - Sx) / (Ddx * Ddx) # C20 = (3.0 * (f[xup] - f[core]) + # (dfdx[xup] + 2.0 * dfdx[core]) * Ddx) / (Ddx * Ddx) C20 = ((1 + a10 * b10 * Ddx) * f[xup] - C00 - C10 * Ddx) / (Ddx * Ddx) - C30 * Ddx # C03 = ((dfdy[yup] + dfdy[core]) * Ddy - 2.0 * # (f[core] - f[yup])) / (Ddy * Ddy * Ddy) C03 = ((1 + a01 * b01 * Ddy) * (dfdy[yup] - Sy) + dfdy[core] - Sy) / (Ddy * Ddy) # C02 = (3.0 * (f[yup] - f[core]) + # (dfdy[yup] + 2.0 * dfdy[core]) * Ddy) / (Ddy * Ddy) C02 = ((1 + a01 * b01 * Ddy) * f[yup] - C00 - C01 * Ddy) / (Ddy * Ddy) - C03 * Ddy # tmp = f[core] - f[yup] - f[xup] + f[xyup] # tmq = dfdy[xup] - dfdy[core] C11 = ( (a01 * b01 * f[xup] + (1.0 + a10 * b10 * Ddx) * dfdy[xup]) / Ddx + (a10 * b10 * f[yup] + (1.0 + a01 * b01 * Ddy) * dfdx[yup]) / Ddy + (C00 - (1.0 + a10 * b10 * Ddx + a01 * b01 * Ddy) * f[xyup]) / Ddx / Ddy + C30 * Ddx * Ddx / Ddy + C03 * Ddy * Ddy / Ddx + C20 * Ddx / Ddy + C02 * Ddy / Ddx ) # C12 = (-tmp - tmq * Ddy) / (Ddx * Ddy * Ddy) C12 = (a10 * b10 * f[yup] + (1 + a01 * b01 * Ddy) * dfdx[yup] - C10) / ( Ddy * Ddy ) - C11 / Ddy # C21 = (-tmp - (dfdx[yup] - dfdx[core]) * Ddx) / (Ddx * Ddx * Ddy) C21 = (a01 * b01 * f[xup] + (1 + a10 * b10 * Ddx) * dfdy[xup] - C01) / ( Ddx * Ddx ) - C11 / Ddx # C11 = (-tmq + C21 * Ddx * Ddx) / (Ddx) out_f[core] = ( ((C30 * XX + C21 * YY + C20) * XX + C11 * YY + C10) * XX + ((C03 * YY + C12 * XX + C02) * YY + C01) * YY + C00 ) / (1 + a10 * b10 * XX + a01 * b01 * YY) out_dfdx[core] = ( (3.0 * C30 * XX + 2.0 * (C21 * YY + C20)) * XX + (C12 * YY + C11) * YY + C10 - a10 * b10 * out_f[core] ) / (1 + a10 * b10 * XX + a01 * b01 * YY) out_dfdy[core] = ( (3.0 * C03 * YY + 2.0 * (C12 * XX + C02)) * YY + (C21 * XX + C11) * XX + C01 - a01 * b01 * out_f[core] ) / (1 + a10 * b10 * XX + a01 * b01 * YY) return out_f, out_dfdx, out_dfdy def cubic_interp_1d(f, dfdx, core, iplus, iminus, dx, out=None): """interpolate values to links or nodes by cubic function Interplated values at the grid between "iplus" and "iminus" is returned. Parameters -------------------------- f : ndarray, float values to be interpolated dfdx : ndarray, float spatial gradient of f iplus : ndarray, int grid id of (i + dx / 2) iminus : ndarray, int grid id of (i - dx / 2) dx : ndarray, float grid spacing out : ndarray, float interpolated values between grids of iplus and iminus """ if out is None: out = np.empty(iplus.shape) # interplation by cubic function D_x = -dx xi_x = -dx / 2.0 a = (dfdx[iplus] + dfdx[iminus]) / (D_x ** 2) + 2.0 * (f[iplus] - f[iminus]) / ( D_x ** 3 ) b = ( 3.0 * (f[iminus] - f[iplus]) / (D_x ** 2) - (2.0 * dfdx[iplus] + dfdx[iminus]) / D_x ) out[core] = a * (xi_x ** 3) + b * (xi_x ** 2) + \ dfdx[iplus] * xi_x + f[iplus] return out def rcubic_interp_1d(f, dfdx, core, iplus, iminus, dx, out=None): """interpolate values to links or nodes by cubic function Interplated values at the grid between "iplus" and "iminus" is returned. Parameters -------------------------- f : ndarray, float values to be interpolated dfdx : ndarray, float spatial gradient of f iplus : ndarray, int grid id of (i + dx / 2) iminus : ndarray, int grid id of (i - dx / 2) dx : ndarray, float grid spacing out : ndarray, float interpolated values between grids of iplus and iminus """ if out is None: out = np.zeros(f.shape) # advection phase D = -dx xi = -dx / 2.0 BB = np.zeros(core.shape, dtype=float) S = (f[iminus] - f[iplus]) / D dz_index = (S - dfdx[iplus]) * (dfdx[iminus] - S) > 0.0 BB[dz_index] = ( np.abs( (S[dz_index] - dfdx[iplus][dz_index]) / (dfdx[iminus][dz_index] - S[dz_index]) ) - 1.0 ) / D a = (dfdx[iplus] - S + (dfdx[iminus] - S) * (1.0 + BB * D)) / (D ** 2) b = S * BB + (S - dfdx[iplus]) / D - a * D c = dfdx[iplus] + f[iplus] * BB out[core] = (((a * xi + b) * xi + c) * xi + f[iplus]) / (1.0 + BB * xi) # adjust negative values negative_value = out[core] < 0 out[core][negative_value] = ( f[iplus][negative_value] + f[iminus][negative_value] ) / 2.0 return out def forester_filter( f, core, east_id, west_id, north_id, south_id, nu_f=0.1, out_f=None, ): """ Forester filter for removing negative values from Concentration and Flow depth """ if out_f is None: out_f = np.zeros_like(f) out_f[:] = f[:] east = east_id[core] west = west_id[core] north = north_id[core] south = south_id[core] out_f[core] += ( nu_f * (f[east] + f[west] + f[north] + f[south] - 4.0 * f[core]) / 4.0 ) out_f[east] -= nu_f * (f[east] - f[core]) / 4.0 out_f[west] -= nu_f * (f[west] - f[core]) / 4.0 out_f[north] -= nu_f * (f[north] - f[core]) / 4.0 out_f[south] -= nu_f * (f[south] - f[core]) / 4.0 return out_f class Jameson: """ Jameson filter for smoothing the variables Parameters ------------------- tc: TurbudityCurrent2D Instance of TurbidityCurrent2D to obtain necessary parameters """ def __init__(self, tc): self.number_of_nodes = tc.grid.number_of_nodes self.number_of_links = tc.grid.number_of_links self.node_east = tc.node_east self.node_west = tc.node_west self.node_north = tc.node_north self.node_south = tc.node_south self.link_east = tc.link_east self.link_west = tc.link_west self.link_north = tc.link_north self.link_south = tc.link_south self.link_horiz = tc.grid.horizontal_links self.link_vert = tc.grid.vertical_links self.east_node_at_horizontal_link = tc.east_node_at_horizontal_link self.west_node_at_horizontal_link = tc.west_node_at_horizontal_link self.north_node_at_vertical_link = tc.north_node_at_vertical_link self.south_node_at_vertical_link = tc.south_node_at_vertical_link self.east_link_at_node = tc.east_link_at_node self.west_link_at_node = tc.west_link_at_node self.north_link_at_node = tc.north_link_at_node self.south_link_at_node = tc.south_link_at_node self.kappa = tc.kappa self.kappa = tc.kappa self.nu_x = np.zeros(self.number_of_nodes) self.nu_y = np.zeros(self.number_of_nodes) self.nu_x_link = np.zeros(self.number_of_links) self.nu_y_link = np.zeros(self.number_of_links) self.eps_link = np.zeros(self.number_of_links) self.eps_node_horiz = np.zeros(self.number_of_nodes) self.eps_node_vert = np.zeros(self.number_of_nodes) def update_artificial_viscosity(self, p, p_link): """ update artificial viscosity at nodes (nu) and links (eps) paramters ------------------- p : ndarray, float pressure at nodes p_link : ndarray, float pressure at links """ # artificial viscosity coefficient at links self.nu_x_link[self.link_horiz] = np.abs( p_link[self.link_east[self.link_horiz]] - 2 * p_link[self.link_horiz] + p_link[self.link_west[self.link_horiz]] ) / ( p_link[self.link_east[self.link_horiz]] + 2 * p_link[self.link_horiz] + p_link[self.link_west[self.link_horiz]] + 10 ** -20 ) self.nu_y_link[self.link_vert] = np.abs( p_link[self.link_north[self.link_vert]] - 2 * p_link[self.link_vert] + p_link[self.link_south[self.link_vert]] ) / ( p_link[self.link_north[self.link_vert]] + 2 * p_link[self.link_vert] + p_link[self.link_south[self.link_vert]] + 10 ** -20 ) # artificial viscosity coefficient at nodes self.nu_x[:] = np.abs( p[self.node_east] + p[self.node_north] + p[self.node_south] + p[self.node_west] - 4 * p ) / ( p[self.node_east] + p[self.node_west] + p[self.node_north] + p[self.node_south] + 4 * p + 10 ** -20 ) self.nu_y[:] = self.nu_x[:] # maximum artificial viscosity coefficient at links self.eps_link[self.link_horiz] = self.kappa * np.max( [ self.nu_x[self.east_node_at_horizontal_link[self.link_horiz]], self.nu_x[self.west_node_at_horizontal_link[self.link_horiz]], ], axis=0, ) self.eps_link[self.link_vert] = self.kappa * np.max( [ self.nu_y[self.north_node_at_vertical_link[self.link_vert]], self.nu_y[self.south_node_at_vertical_link[self.link_vert]], ], axis=0, ) # maximum artificial viscosity coefficient at nodes self.eps_node_horiz[:] = ( 0.01 * self.kappa * np.max( [ self.nu_x_link[self.east_link_at_node], self.nu_x_link[self.west_link_at_node], ], axis=0, ) ) self.eps_node_vert[:] = ( 0.01 * self.kappa * np.max( [ self.nu_y_link[self.north_link_at_node], self.nu_y_link[self.south_link_at_node], ], axis=0, ) ) def run(self, f, core, at="node", out=None): """ run one step of the Jameson filter paramters -------------------- f : ndarray, float variables to be filtered core : ndarray, int grid ids to apply the filter at : String, optional 'node', 'hlink', or 'vlink' for values on nodes, horizontal links or vertical links out : ndarray, float output returns -------------------- out : ndarray, float filtered variables """ if out is None: out = np.zeros_like(f) if at == "node": out[core] = ( f[core] + self.eps_link[self.east_link_at_node[core]] * (f[self.node_east[core]] - f[core]) - self.eps_link[self.west_link_at_node[core]] * (f[core] - f[self.node_west[core]]) + self.eps_link[self.north_link_at_node[core]] * (f[self.node_north[core]] - f[core]) - self.eps_link[self.south_link_at_node[core]] * (f[core] - f[self.node_south[core]]) ) if at == "hlink": out[core] = ( f[core] + self.eps_node_horiz[self.east_node_at_horizontal_link[core]] * (f[self.link_east[core]] - f[core]) - self.eps_node_horiz[self.west_node_at_horizontal_link[core]] * (f[core] - f[self.west_node_at_horizontal_link[core]]) ) if at == "vlink": out[core] = ( f[core] + self.eps_node_vert[self.north_node_at_vertical_link[core]] * (f[self.link_north[core]] - f[core]) - self.eps_node_vert[self.south_node_at_vertical_link[core]] * (f[core] - f[self.south_node_at_vertical_link[core]]) ) return out class SOR: """SOR method to solve inverse matrix """ def __init__( self, number_of_nodes, node_east, node_west, node_north, node_south, implicit_threshold, max_loop, alpha, update_boundary_conditions, ): self.implicit_threshold = implicit_threshold self.max_loop = max_loop self.alpha = alpha self.update_boundary_conditions = update_boundary_conditions self.node_east = node_east self.node_west = node_west self.node_north = node_north self.node_south = node_south self.a = np.empty(number_of_nodes) self.b = np.empty(number_of_nodes) self.c = np.empty(number_of_nodes) self.d = np.empty(number_of_nodes) self.e = np.empty(number_of_nodes) self.g = np.empty(number_of_nodes) self.w = np.empty(number_of_nodes) def run(self, p, core, out=None): if out is None: out = np.zeros_like(p) out[:] = p[:] err = 100.0 count = 0 core_size = core.shape[0] while err > self.implicit_threshold: self.w[core] = ( self.g[core] - self.b[core] * out[self.node_east[core]] - self.c[core] * out[self.node_west[core]] - self.d[core] * out[self.node_north[core]] - self.e[core] * out[self.node_south[core]] ) / self.a[core] err = np.linalg.norm(self.w[core] - out[core]) / ( core_size + 1.0 * 10 ** -20 ) out[core] = out[core] * (1 - self.alpha) + \ self.alpha * self.w[core] self.update_boundary_conditions(p=out) count += 1 if count == self.max_loop: print("Implicit calculation did not converge") return out return out
en
0.59521
Calculate one time step using M-type 2D cip method # First, the variables out and temp are allocated to # store the calculation results # 1st step for horizontal advection # 2nd step for vertical advection Calculate one time step using M-type 2D cip method # First, the variables out and temp are allocated to # store the calculation results # 1st step for horizontal advection # non-advection term Caclulate horizontal and vertical diffusion of velocities u and v calculate 1 step of advection phase by rational function CIP method. Parameters ---------------- f : ndarray variable to be calculated dfdx : ndarray spatial gradient of the parameter f u : ndarray advection velocity of f core : ndarray indeces of core grids up : ndarray indeces of grids that locate upstream down : ndarray indeces of grids that locate downstream dx : float spatial grid spacing dt : float time step length out_f : ndarray resultant value of f out_dfdx : ndarray resultant value of dfdx Returns -------------------- out_f : ndarray output value of f out_dfdx : ndarray output value of dfdx # advection phase Calculate one time step using M-type 2D cip method # First, the variables out and temp are allocated to # store the calculation results # 1st step for horizontal advection # 2nd step for vertical advection adding artificial viscosity for numerical stability Parameters ------------------ f : ndarray, float parameter for which the artificial viscosity is applied h : ndarray, float flow height core : ndarray, int indeces of core nodes or links north_id : ndarray, int indeces of nodes or links that locate north of core south_id : ndarray, int indeces of nodes or links that locate south of core east_id : ndarray, int indeces of nodes or links that locate east of core west_id : ndarray, int indeces of nodes or links that locate west of core # eps_i_half4 = np.zeros(n, dtype=np.float) # eps_j_half4 = np.zeros(n, dtype=np.float) # easteast = east_id[east] # northnorth = north_id[north] # First, artificial diffusion is applied to east-west direction # eps_i_half4[core] = np.max( # [np.zeros_like(core), kappa4 - eps_i_half2[core]], axis=0) # d_i_half[core] = eps_i_half2[core] * ( # f[east] - f[core]) - eps_i_half4[core] * (f[easteast] - 3.0 * f[east] + # 3.0 * f[core] - f[west]) # Next, artificial diffusion is applied to north-south direction # eps_j_half4[core] = np.max( # [np.zeros_like(core), kappa4 - eps_j_half2[core]], axis=0) # d_j_half[core] = eps_j_half2[core] * (f[north] - f[core]) - eps_j_half4[ # core] * (f[northnorth] - 3.0 * f[north] + 3.0 * f[core] - f[south]) # apply artificial diffusion Update gradients when main variables are updated # non-advection term Update gradients when main variables are updated # non-advection term CIP Direct 2D scheme parameters --------------------- max_number_of_grids : int maximum number of grids that may be used in this solver run this solver to calculate advection transport of a variable f parameters ---------------------- f : ndarray, float A variable to calculate Direct 2D calculation of advection by R-CIP method # C30 = ((dfdx[xup] + dfdx[core]) * Ddx - 2.0 * # (f[core] - f[xup])) / (Ddx * Ddx * Ddx) # C20 = (3.0 * (f[xup] - f[core]) + # (dfdx[xup] + 2.0 * dfdx[core]) * Ddx) / (Ddx * Ddx) # C03 = ((dfdy[yup] + dfdy[core]) * Ddy - 2.0 * # (f[core] - f[yup])) / (Ddy * Ddy * Ddy) # C02 = (3.0 * (f[yup] - f[core]) + # (dfdy[yup] + 2.0 * dfdy[core]) * Ddy) / (Ddy * Ddy) # tmp = f[core] - f[yup] - f[xup] + f[xyup] # tmq = dfdy[xup] - dfdy[core] # C12 = (-tmp - tmq * Ddy) / (Ddx * Ddy * Ddy) # C21 = (-tmp - (dfdx[yup] - dfdx[core]) * Ddx) / (Ddx * Ddx * Ddy) # C11 = (-tmq + C21 * Ddx * Ddx) / (Ddx) interpolate values to links or nodes by cubic function Interplated values at the grid between "iplus" and "iminus" is returned. Parameters -------------------------- f : ndarray, float values to be interpolated dfdx : ndarray, float spatial gradient of f iplus : ndarray, int grid id of (i + dx / 2) iminus : ndarray, int grid id of (i - dx / 2) dx : ndarray, float grid spacing out : ndarray, float interpolated values between grids of iplus and iminus # interplation by cubic function interpolate values to links or nodes by cubic function Interplated values at the grid between "iplus" and "iminus" is returned. Parameters -------------------------- f : ndarray, float values to be interpolated dfdx : ndarray, float spatial gradient of f iplus : ndarray, int grid id of (i + dx / 2) iminus : ndarray, int grid id of (i - dx / 2) dx : ndarray, float grid spacing out : ndarray, float interpolated values between grids of iplus and iminus # advection phase # adjust negative values Forester filter for removing negative values from Concentration and Flow depth Jameson filter for smoothing the variables Parameters ------------------- tc: TurbudityCurrent2D Instance of TurbidityCurrent2D to obtain necessary parameters update artificial viscosity at nodes (nu) and links (eps) paramters ------------------- p : ndarray, float pressure at nodes p_link : ndarray, float pressure at links # artificial viscosity coefficient at links # artificial viscosity coefficient at nodes # maximum artificial viscosity coefficient at links # maximum artificial viscosity coefficient at nodes run one step of the Jameson filter paramters -------------------- f : ndarray, float variables to be filtered core : ndarray, int grid ids to apply the filter at : String, optional 'node', 'hlink', or 'vlink' for values on nodes, horizontal links or vertical links out : ndarray, float output returns -------------------- out : ndarray, float filtered variables SOR method to solve inverse matrix
3.052096
3
cortex/secondary/entropy.py
dcurrey88/LAMP-cortex
0
6632180
<gh_stars>0 from ..feature_types import secondary_feature, log from ..primary.significant_locations import significant_locations MS_IN_A_DAY = 86400000 @secondary_feature( name='cortex.feature.entropy', dependencies=[significant_locations] ) def entropy(resolution=MS_IN_A_DAY, **kwargs): """ Calculate entropy """ #log.info(f'Loading significant locations data...') _significant_locations = significant_locations(id=kwargs['id'], start=kwargs['start'], end=kwargs['end']) if len(_significant_locations['data']) == 0: _entropy = None #log.info(f'Computing entropy...') _entropy = sum([loc['proportion'] * math.log(loc['proportion']) for loc in _significant_locations['data']]) if _entropy == 0: #no sig locs _entropy = None return {'timetamp':kwargs['start'], 'entropy': _entropy}
from ..feature_types import secondary_feature, log from ..primary.significant_locations import significant_locations MS_IN_A_DAY = 86400000 @secondary_feature( name='cortex.feature.entropy', dependencies=[significant_locations] ) def entropy(resolution=MS_IN_A_DAY, **kwargs): """ Calculate entropy """ #log.info(f'Loading significant locations data...') _significant_locations = significant_locations(id=kwargs['id'], start=kwargs['start'], end=kwargs['end']) if len(_significant_locations['data']) == 0: _entropy = None #log.info(f'Computing entropy...') _entropy = sum([loc['proportion'] * math.log(loc['proportion']) for loc in _significant_locations['data']]) if _entropy == 0: #no sig locs _entropy = None return {'timetamp':kwargs['start'], 'entropy': _entropy}
en
0.340194
Calculate entropy #log.info(f'Loading significant locations data...') #log.info(f'Computing entropy...') #no sig locs
2.570448
3
mne/io/artemis123/tests/test_artemis123.py
slew/mne-python
0
6632181
# Author: <NAME> <<EMAIL>> # # License: BSD (3-clause) import os.path as op import numpy as np from numpy.testing import assert_allclose, assert_equal import pytest from mne.io import read_raw_artemis123 from mne.io.tests.test_raw import _test_raw_reader from mne.datasets import testing from mne.io.artemis123.utils import _generate_mne_locs_file, _load_mne_locs from mne import pick_types from mne.transforms import rot_to_quat, _angle_between_quats from mne.io.constants import FIFF artemis123_dir = op.join(testing.data_path(download=False), 'ARTEMIS123') short_HPI_dip_fname = op.join(artemis123_dir, 'Artemis_Data_2017-04-04-15h-44m-' + '22s_Motion_Translation-z.bin') dig_fname = op.join(artemis123_dir, 'Phantom_040417_dig.pos') short_hpi_1kz_fname = op.join(artemis123_dir, 'Artemis_Data_2017-04-14-10h' + '-38m-59s_Phantom_1k_HPI_1s.bin') # XXX this tol is way too high, but it's not clear which is correct # (old or new) def _assert_trans(actual, desired, dist_tol=0.017, angle_tol=5.): __tracebackhide__ = True trans_est = actual[0:3, 3] quat_est = rot_to_quat(actual[0:3, 0:3]) trans = desired[0:3, 3] quat = rot_to_quat(desired[0:3, 0:3]) angle = np.rad2deg(_angle_between_quats(quat_est, quat)) dist = np.linalg.norm(trans - trans_est) assert dist <= dist_tol, \ '%0.3f > %0.3f mm translation' % (1000 * dist, 1000 * dist_tol) assert angle <= angle_tol, \ '%0.3f > %0.3f° rotation' % (angle, angle_tol) @pytest.mark.timeout(60) # ~25 sec on Travis Linux OpenBLAS @testing.requires_testing_data def test_artemis_reader(): """Test reading raw Artemis123 files.""" _test_raw_reader(read_raw_artemis123, input_fname=short_hpi_1kz_fname, pos_fname=dig_fname, verbose='error') @pytest.mark.timeout(60) def test_dev_head_t(): """Test dev_head_t computation for Artemis123.""" # test a random selected point raw = read_raw_artemis123(short_hpi_1kz_fname, preload=True, add_head_trans=False) meg_picks = pick_types(raw.info, meg=True, eeg=False) # checked against matlab reader. assert_allclose(raw[meg_picks[12]][0][0][123], 1.08239606023e-11) dev_head_t_1 = np.array([[9.713e-01, 2.340e-01, -4.164e-02, 1.302e-04], [-2.371e-01, 9.664e-01, -9.890e-02, 1.977e-03], [1.710e-02, 1.059e-01, 9.942e-01, -8.159e-03], [0.0, 0.0, 0.0, 1.0]]) dev_head_t_2 = np.array([[9.890e-01, 1.475e-01, -8.090e-03, 4.997e-04], [-1.476e-01, 9.846e-01, -9.389e-02, 1.962e-03], [-5.888e-03, 9.406e-02, 9.955e-01, -1.610e-02], [0.0, 0.0, 0.0, 1.0]]) expected_dev_hpi_rr = np.array([[-0.01579644, 0.06527367, 0.00152648], [0.06666813, 0.0148956, 0.00545488], [-0.06699212, -0.01732376, 0.0112027]]) # test with head loc no digitization raw = read_raw_artemis123(short_HPI_dip_fname, add_head_trans=True) _assert_trans(raw.info['dev_head_t']['trans'], dev_head_t_1) assert_equal(raw.info['sfreq'], 5000.0) # test with head loc and digitization with pytest.warns(RuntimeWarning, match='Large difference'): raw = read_raw_artemis123(short_HPI_dip_fname, add_head_trans=True, pos_fname=dig_fname) _assert_trans(raw.info['dev_head_t']['trans'], dev_head_t_1) # test cHPI localization.. dev_hpi_rr = np.array([p['r'] for p in raw.info['dig'] if p['coord_frame'] == FIFF.FIFFV_COORD_DEVICE]) # points should be within 0.1 mm (1e-4m) and within 1% assert_allclose(dev_hpi_rr, expected_dev_hpi_rr, atol=1e-4, rtol=0.01) # test 1kz hpi head loc (different freq) raw = read_raw_artemis123(short_hpi_1kz_fname, add_head_trans=True) _assert_trans(raw.info['dev_head_t']['trans'], dev_head_t_2) assert_equal(raw.info['sfreq'], 1000.0) def test_utils(tmpdir): """Test artemis123 utils.""" # make a tempfile tmp_dir = str(tmpdir) tmp_fname = op.join(tmp_dir, 'test_gen_mne_locs.csv') _generate_mne_locs_file(tmp_fname) installed_locs = _load_mne_locs() generated_locs = _load_mne_locs(tmp_fname) assert_equal(set(installed_locs.keys()), set(generated_locs.keys())) for key in installed_locs.keys(): assert_allclose(installed_locs[key], generated_locs[key], atol=1e-7)
# Author: <NAME> <<EMAIL>> # # License: BSD (3-clause) import os.path as op import numpy as np from numpy.testing import assert_allclose, assert_equal import pytest from mne.io import read_raw_artemis123 from mne.io.tests.test_raw import _test_raw_reader from mne.datasets import testing from mne.io.artemis123.utils import _generate_mne_locs_file, _load_mne_locs from mne import pick_types from mne.transforms import rot_to_quat, _angle_between_quats from mne.io.constants import FIFF artemis123_dir = op.join(testing.data_path(download=False), 'ARTEMIS123') short_HPI_dip_fname = op.join(artemis123_dir, 'Artemis_Data_2017-04-04-15h-44m-' + '22s_Motion_Translation-z.bin') dig_fname = op.join(artemis123_dir, 'Phantom_040417_dig.pos') short_hpi_1kz_fname = op.join(artemis123_dir, 'Artemis_Data_2017-04-14-10h' + '-38m-59s_Phantom_1k_HPI_1s.bin') # XXX this tol is way too high, but it's not clear which is correct # (old or new) def _assert_trans(actual, desired, dist_tol=0.017, angle_tol=5.): __tracebackhide__ = True trans_est = actual[0:3, 3] quat_est = rot_to_quat(actual[0:3, 0:3]) trans = desired[0:3, 3] quat = rot_to_quat(desired[0:3, 0:3]) angle = np.rad2deg(_angle_between_quats(quat_est, quat)) dist = np.linalg.norm(trans - trans_est) assert dist <= dist_tol, \ '%0.3f > %0.3f mm translation' % (1000 * dist, 1000 * dist_tol) assert angle <= angle_tol, \ '%0.3f > %0.3f° rotation' % (angle, angle_tol) @pytest.mark.timeout(60) # ~25 sec on Travis Linux OpenBLAS @testing.requires_testing_data def test_artemis_reader(): """Test reading raw Artemis123 files.""" _test_raw_reader(read_raw_artemis123, input_fname=short_hpi_1kz_fname, pos_fname=dig_fname, verbose='error') @pytest.mark.timeout(60) def test_dev_head_t(): """Test dev_head_t computation for Artemis123.""" # test a random selected point raw = read_raw_artemis123(short_hpi_1kz_fname, preload=True, add_head_trans=False) meg_picks = pick_types(raw.info, meg=True, eeg=False) # checked against matlab reader. assert_allclose(raw[meg_picks[12]][0][0][123], 1.08239606023e-11) dev_head_t_1 = np.array([[9.713e-01, 2.340e-01, -4.164e-02, 1.302e-04], [-2.371e-01, 9.664e-01, -9.890e-02, 1.977e-03], [1.710e-02, 1.059e-01, 9.942e-01, -8.159e-03], [0.0, 0.0, 0.0, 1.0]]) dev_head_t_2 = np.array([[9.890e-01, 1.475e-01, -8.090e-03, 4.997e-04], [-1.476e-01, 9.846e-01, -9.389e-02, 1.962e-03], [-5.888e-03, 9.406e-02, 9.955e-01, -1.610e-02], [0.0, 0.0, 0.0, 1.0]]) expected_dev_hpi_rr = np.array([[-0.01579644, 0.06527367, 0.00152648], [0.06666813, 0.0148956, 0.00545488], [-0.06699212, -0.01732376, 0.0112027]]) # test with head loc no digitization raw = read_raw_artemis123(short_HPI_dip_fname, add_head_trans=True) _assert_trans(raw.info['dev_head_t']['trans'], dev_head_t_1) assert_equal(raw.info['sfreq'], 5000.0) # test with head loc and digitization with pytest.warns(RuntimeWarning, match='Large difference'): raw = read_raw_artemis123(short_HPI_dip_fname, add_head_trans=True, pos_fname=dig_fname) _assert_trans(raw.info['dev_head_t']['trans'], dev_head_t_1) # test cHPI localization.. dev_hpi_rr = np.array([p['r'] for p in raw.info['dig'] if p['coord_frame'] == FIFF.FIFFV_COORD_DEVICE]) # points should be within 0.1 mm (1e-4m) and within 1% assert_allclose(dev_hpi_rr, expected_dev_hpi_rr, atol=1e-4, rtol=0.01) # test 1kz hpi head loc (different freq) raw = read_raw_artemis123(short_hpi_1kz_fname, add_head_trans=True) _assert_trans(raw.info['dev_head_t']['trans'], dev_head_t_2) assert_equal(raw.info['sfreq'], 1000.0) def test_utils(tmpdir): """Test artemis123 utils.""" # make a tempfile tmp_dir = str(tmpdir) tmp_fname = op.join(tmp_dir, 'test_gen_mne_locs.csv') _generate_mne_locs_file(tmp_fname) installed_locs = _load_mne_locs() generated_locs = _load_mne_locs(tmp_fname) assert_equal(set(installed_locs.keys()), set(generated_locs.keys())) for key in installed_locs.keys(): assert_allclose(installed_locs[key], generated_locs[key], atol=1e-7)
en
0.813608
# Author: <NAME> <<EMAIL>> # # License: BSD (3-clause) # XXX this tol is way too high, but it's not clear which is correct # (old or new) # ~25 sec on Travis Linux OpenBLAS Test reading raw Artemis123 files. Test dev_head_t computation for Artemis123. # test a random selected point # checked against matlab reader. # test with head loc no digitization # test with head loc and digitization # test cHPI localization.. # points should be within 0.1 mm (1e-4m) and within 1% # test 1kz hpi head loc (different freq) Test artemis123 utils. # make a tempfile
1.766914
2
server/athenian/api/controllers/datetime_utils.py
athenianco/athenian-api
9
6632182
from datetime import date, datetime, timedelta, timezone from typing import List, Optional, Tuple, Union from athenian.api.models.web import Granularity, InvalidRequestError from athenian.api.response import ResponseError def coarsen_time_interval(time_from: datetime, time_to: datetime) -> Tuple[date, date]: """Extend the time interval to align at the date boarders.""" assert time_to > time_from zerotd = timedelta(0) assert isinstance(time_from, datetime) and time_from.tzinfo.utcoffset(time_from) == zerotd assert isinstance(time_to, datetime) and time_to.tzinfo.utcoffset(time_to) == zerotd date_from = time_from.date() date_to = time_to.date() if time_to.time() != datetime.min.time(): date_to += timedelta(days=1) return date_from, date_to def split_to_time_intervals(date_from: date, date_to: date, granularities: Union[str, List[str]], tzoffset: Optional[int], ) -> Tuple[Union[List[datetime], List[List[datetime]]], timedelta]: """Produce time interval boundaries from the min and the max dates and the interval lengths \ (granularities). :param tzoffset: Time zone offset in minutes. We ignore DST for now. :return: tuple with the time intervals and the timezone offset converted to timedelta. \ If `granularities` is a scalar, then return a list of boundaries, otherwise, return \ a list of lists. """ if date_to < date_from: raise ResponseError(InvalidRequestError( detail="date_from may not be greater than date_to", pointer=".date_from", )) tzoffset = timedelta(minutes=-tzoffset) if tzoffset is not None else timedelta(0) def split(granularity: str, ptr: str) -> List[datetime]: try: intervals = Granularity.split(granularity, date_from, date_to) except ValueError: raise ResponseError(InvalidRequestError( detail='granularity "%s" does not match /%s/' % ( granularity, Granularity.format.pattern), pointer=ptr, )) return [datetime.combine(i, datetime.min.time(), tzinfo=timezone.utc) + tzoffset for i in intervals] if isinstance(granularities, str): return split(granularities, ".granularity"), tzoffset return [split(g, ".granularities[%d]" % i) for i, g in enumerate(granularities)], tzoffset
from datetime import date, datetime, timedelta, timezone from typing import List, Optional, Tuple, Union from athenian.api.models.web import Granularity, InvalidRequestError from athenian.api.response import ResponseError def coarsen_time_interval(time_from: datetime, time_to: datetime) -> Tuple[date, date]: """Extend the time interval to align at the date boarders.""" assert time_to > time_from zerotd = timedelta(0) assert isinstance(time_from, datetime) and time_from.tzinfo.utcoffset(time_from) == zerotd assert isinstance(time_to, datetime) and time_to.tzinfo.utcoffset(time_to) == zerotd date_from = time_from.date() date_to = time_to.date() if time_to.time() != datetime.min.time(): date_to += timedelta(days=1) return date_from, date_to def split_to_time_intervals(date_from: date, date_to: date, granularities: Union[str, List[str]], tzoffset: Optional[int], ) -> Tuple[Union[List[datetime], List[List[datetime]]], timedelta]: """Produce time interval boundaries from the min and the max dates and the interval lengths \ (granularities). :param tzoffset: Time zone offset in minutes. We ignore DST for now. :return: tuple with the time intervals and the timezone offset converted to timedelta. \ If `granularities` is a scalar, then return a list of boundaries, otherwise, return \ a list of lists. """ if date_to < date_from: raise ResponseError(InvalidRequestError( detail="date_from may not be greater than date_to", pointer=".date_from", )) tzoffset = timedelta(minutes=-tzoffset) if tzoffset is not None else timedelta(0) def split(granularity: str, ptr: str) -> List[datetime]: try: intervals = Granularity.split(granularity, date_from, date_to) except ValueError: raise ResponseError(InvalidRequestError( detail='granularity "%s" does not match /%s/' % ( granularity, Granularity.format.pattern), pointer=ptr, )) return [datetime.combine(i, datetime.min.time(), tzinfo=timezone.utc) + tzoffset for i in intervals] if isinstance(granularities, str): return split(granularities, ".granularity"), tzoffset return [split(g, ".granularities[%d]" % i) for i, g in enumerate(granularities)], tzoffset
en
0.718588
Extend the time interval to align at the date boarders. Produce time interval boundaries from the min and the max dates and the interval lengths \ (granularities). :param tzoffset: Time zone offset in minutes. We ignore DST for now. :return: tuple with the time intervals and the timezone offset converted to timedelta. \ If `granularities` is a scalar, then return a list of boundaries, otherwise, return \ a list of lists.
2.696744
3
binreconfiguration/strategy/gauge/count.py
vialette/binreconfiguration
0
6632183
"""Count gauge""" from .gauge import Gauge class Count(Gauge): def __call__(self, t): """Return the number of items in a bin (including the requested one).""" (_, bin) = t return bin.count() + 1
"""Count gauge""" from .gauge import Gauge class Count(Gauge): def __call__(self, t): """Return the number of items in a bin (including the requested one).""" (_, bin) = t return bin.count() + 1
en
0.893536
Count gauge Return the number of items in a bin (including the requested one).
3.035648
3
dakara_server/library/tests/test_song_tag.py
DakaraProject/dakara-server
4
6632184
from django.urls import reverse from rest_framework import status from internal.tests.base_test import UserModel from library.models import SongTag from library.tests.base_test import LibraryAPITestCase class SongTagListViewTestCase(LibraryAPITestCase): url = reverse("library-songtag-list") def setUp(self): # create a manager self.manager = self.create_user( "TestUserManager", library_level=UserModel.MANAGER ) # create a user without any rights self.user = self.create_user("TestUser") # create test data self.create_test_data() def test_get_tag_list(self): """Test to verify tag list.""" # Login as simple user self.authenticate(self.user) # Get tags list response = self.client.get(self.url) self.assertEqual(response.status_code, status.HTTP_200_OK) self.assertEqual(response.data["count"], 2) self.assertEqual(len(response.data["results"]), 2) # Tags are sorted by name self.check_tag_json(response.data["results"][0], self.tag1) self.check_tag_json(response.data["results"][1], self.tag2) def test_get_tag_list_forbidden(self): """Test to verify unauthenticated user can't get tag list.""" # Attempt to get work type list response = self.client.get(self.url) self.assertEqual(response.status_code, status.HTTP_401_UNAUTHORIZED) def test_post_tag_already_exists(self): """Test to create a tag when it already exists.""" # Login as simple user self.authenticate(self.manager) # create an existing tag response = self.client.post(self.url, {"name": "TAG1"}) self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST) class SongTagViewTestCase(LibraryAPITestCase): def setUp(self): # create a manager self.manager = self.create_user( "TestUserManager", library_level=UserModel.MANAGER ) self.user = self.create_user("TestUser") # create test data self.create_test_data() # create urls self.url_sg1 = reverse("library-songtag", kwargs={"pk": self.tag1.id}) self.url_sg2 = reverse("library-songtag", kwargs={"pk": self.tag2.id}) def test_update_song_tag_manager(self): """Test manager can update tag.""" # login as manager self.authenticate(self.manager) # pre-assertion: the tag is enabled tag = SongTag.objects.get(id=self.tag1.id) self.assertFalse(tag.disabled) # alter one tag response = self.client.patch(self.url_sg1, {"disabled": True}) self.assertEqual(response.status_code, status.HTTP_200_OK) # the tag should be disabled now tag = SongTag.objects.get(id=self.tag1.id) self.assertTrue(tag.disabled) def test_update_song_tag_user(self): """Test simple user can not update tags.""" # login as user self.authenticate(self.user) # attempt to alter one tag response = self.client.patch(self.url_sg1, {"disabled": True}) # user can't update tag self.assertEqual(response.status_code, status.HTTP_403_FORBIDDEN)
from django.urls import reverse from rest_framework import status from internal.tests.base_test import UserModel from library.models import SongTag from library.tests.base_test import LibraryAPITestCase class SongTagListViewTestCase(LibraryAPITestCase): url = reverse("library-songtag-list") def setUp(self): # create a manager self.manager = self.create_user( "TestUserManager", library_level=UserModel.MANAGER ) # create a user without any rights self.user = self.create_user("TestUser") # create test data self.create_test_data() def test_get_tag_list(self): """Test to verify tag list.""" # Login as simple user self.authenticate(self.user) # Get tags list response = self.client.get(self.url) self.assertEqual(response.status_code, status.HTTP_200_OK) self.assertEqual(response.data["count"], 2) self.assertEqual(len(response.data["results"]), 2) # Tags are sorted by name self.check_tag_json(response.data["results"][0], self.tag1) self.check_tag_json(response.data["results"][1], self.tag2) def test_get_tag_list_forbidden(self): """Test to verify unauthenticated user can't get tag list.""" # Attempt to get work type list response = self.client.get(self.url) self.assertEqual(response.status_code, status.HTTP_401_UNAUTHORIZED) def test_post_tag_already_exists(self): """Test to create a tag when it already exists.""" # Login as simple user self.authenticate(self.manager) # create an existing tag response = self.client.post(self.url, {"name": "TAG1"}) self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST) class SongTagViewTestCase(LibraryAPITestCase): def setUp(self): # create a manager self.manager = self.create_user( "TestUserManager", library_level=UserModel.MANAGER ) self.user = self.create_user("TestUser") # create test data self.create_test_data() # create urls self.url_sg1 = reverse("library-songtag", kwargs={"pk": self.tag1.id}) self.url_sg2 = reverse("library-songtag", kwargs={"pk": self.tag2.id}) def test_update_song_tag_manager(self): """Test manager can update tag.""" # login as manager self.authenticate(self.manager) # pre-assertion: the tag is enabled tag = SongTag.objects.get(id=self.tag1.id) self.assertFalse(tag.disabled) # alter one tag response = self.client.patch(self.url_sg1, {"disabled": True}) self.assertEqual(response.status_code, status.HTTP_200_OK) # the tag should be disabled now tag = SongTag.objects.get(id=self.tag1.id) self.assertTrue(tag.disabled) def test_update_song_tag_user(self): """Test simple user can not update tags.""" # login as user self.authenticate(self.user) # attempt to alter one tag response = self.client.patch(self.url_sg1, {"disabled": True}) # user can't update tag self.assertEqual(response.status_code, status.HTTP_403_FORBIDDEN)
en
0.788675
# create a manager # create a user without any rights # create test data Test to verify tag list. # Login as simple user # Get tags list # Tags are sorted by name Test to verify unauthenticated user can't get tag list. # Attempt to get work type list Test to create a tag when it already exists. # Login as simple user # create an existing tag # create a manager # create test data # create urls Test manager can update tag. # login as manager # pre-assertion: the tag is enabled # alter one tag # the tag should be disabled now Test simple user can not update tags. # login as user # attempt to alter one tag # user can't update tag
2.554426
3
trace_event/etw_manifest/BUILD/message_compiler.py
chinmaygarde/flutter_base
20
6632185
<filename>trace_event/etw_manifest/BUILD/message_compiler.py # Copyright 2015 The Chromium Authors. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. # Runs the Microsoft Message Compiler (mc.exe). This Python adapter is for the # GN build, which can only run Python and not native binaries. import subprocess import sys # mc writes to stderr, so this explicily redirects to stdout and eats it. try: subprocess.check_output(["mc.exe"] + sys.argv[1:], stderr=subprocess.STDOUT) except subprocess.CalledProcessError as e: print e.output sys.exit(e.returncode)
<filename>trace_event/etw_manifest/BUILD/message_compiler.py # Copyright 2015 The Chromium Authors. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. # Runs the Microsoft Message Compiler (mc.exe). This Python adapter is for the # GN build, which can only run Python and not native binaries. import subprocess import sys # mc writes to stderr, so this explicily redirects to stdout and eats it. try: subprocess.check_output(["mc.exe"] + sys.argv[1:], stderr=subprocess.STDOUT) except subprocess.CalledProcessError as e: print e.output sys.exit(e.returncode)
en
0.888763
# Copyright 2015 The Chromium Authors. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. # Runs the Microsoft Message Compiler (mc.exe). This Python adapter is for the # GN build, which can only run Python and not native binaries. # mc writes to stderr, so this explicily redirects to stdout and eats it.
1.890278
2
spotui/src/SearchInput.py
ssiyad/spotui
410
6632186
import curses from spotui.src.util import truncate from spotui.src.input import Input from spotui.src.component import Component class SearchInput(Component): def __init__(self, stdscr, api, handle_search): self.stdscr = stdscr self.api = api self.handle_search = handle_search self.active = True self.popup = True self.title = "Search" self.interactive = False self.restart() def restart(self): scry, scrx = self.stdscr.getmaxyx() box_height = 4 box_width = round(scrx / 3) self.startx = round((scrx / 2) - (box_width / 2)) self.endx = self.startx + box_width self.starty = round((scry / 2) - (box_height / 2)) self.endy = self.starty + box_height self.component = Input( self.stdscr, self.starty, self.startx, self.endy, self.endx, self.handle_search, ) def activate(self): self.component.active = True def deactivate(self): self.component.active = False
import curses from spotui.src.util import truncate from spotui.src.input import Input from spotui.src.component import Component class SearchInput(Component): def __init__(self, stdscr, api, handle_search): self.stdscr = stdscr self.api = api self.handle_search = handle_search self.active = True self.popup = True self.title = "Search" self.interactive = False self.restart() def restart(self): scry, scrx = self.stdscr.getmaxyx() box_height = 4 box_width = round(scrx / 3) self.startx = round((scrx / 2) - (box_width / 2)) self.endx = self.startx + box_width self.starty = round((scry / 2) - (box_height / 2)) self.endy = self.starty + box_height self.component = Input( self.stdscr, self.starty, self.startx, self.endy, self.endx, self.handle_search, ) def activate(self): self.component.active = True def deactivate(self): self.component.active = False
none
1
2.488842
2
vollseg/spatial_image.py
Kapoorlabs-CAPED/CAPED-VollSeg
7
6632187
# -*- python -*- # # spatial_image: spatial nd images # # Copyright 2006 INRIA - CIRAD - INRA # # File author(s): <NAME> <<EMAIL>> # # Distributed under the Cecill-C License. # See accompanying file LICENSE.txt or copy at # http://www.cecill.info/licences/Licence_CeCILL-C_V1-en.html # # OpenAlea WebSite : http://openalea.gforge.inria.fr # """ This module create the main |SpatialImage| object """ __license__= "Cecill-C" __revision__=" $Id: $ " import numpy as np from scipy import ndimage import copy as cp # -- deprecation messages -- # import warnings, exceptions # msg = "SpatialImage.resolution is deprecated, use SpatialImage.voxelsize" # rezexc = exceptions.PendingDeprecationWarning(msg) class SpatialImage(np.ndarray) : """ Associate meta data to np.ndarray """ def __new__ (cls, input_array, voxelsize = None, vdim = None, info = None, dtype = None, **kwargs) : """Instantiate a new |SpatialImage| if voxelsize is None, vdim will be used to infer space size and affect a voxelsize of 1 in each direction of space .. warning :: `resolution` keyword is deprecated. Use `voxelsize` instead. :Parameters: - `cls` - internal python - `input_array` (array) - data to put in the image - `voxelsize` (tuple of float) - spatial extension in each direction of space - `vdim` (int) - size of data if vector data are used - `info` (dict of str|any) - metainfo """ #if the input_array is 2D we can reshape it to 3D. #~ if input_array.ndim == 2: # Jonathan #~ input_array = input_array.reshape( input_array.shape+(1,) ) # Jonathan #initialize datas. For some obscure reason, we want the data #to be F-Contiguous in the NUMPY sense. I mean, if this is not #respected, we will have problems when communicating with #C-Code... yeah, that makes so much sense (fortran-contiguous #to be c-readable...). dtype = dtype if dtype is not None else input_array.dtype if input_array.flags.f_contiguous : obj = np.asarray(input_array, dtype=dtype).view(cls) else : obj = np.asarray(input_array, dtype=dtype, order='F').view(cls) voxelsize = kwargs.get("resolution", voxelsize) #to manage transition if voxelsize is None : #~ voxelsize = (1.,) * 3 voxelsize = (1.,) * input_array.ndim # Jonathan else : #~ if len(voxelsize) != 3 : if (input_array.ndim != 4) and (len(voxelsize) != input_array.ndim) : # Jonathan _ Compatibility with "champs_*.inr.gz" generated by Baloo & SuperBaloo raise ValueError("data dimension and voxelsize mismatch") obj.voxelsize = tuple(voxelsize) obj.vdim = vdim if vdim else 1 #set metadata if info is None : obj.info = {} else : obj.info = dict(info) #return return obj def _get_resolution(self): # warnings.warn(rezexc) return self.voxelsize def _set_resolution(self, val): # warnings.warn(rezexc) self.voxelsize = val resolution = property(_get_resolution, _set_resolution) @property def real_shape(self): #~ return np.multiply(self.shape[:3], self.voxelsize) return np.multiply(self.shape, self.voxelsize) # Jonathan def invert_z_axis( self ): """ invert allong 'Z' axis """ self = self[:,:,::-1] def __array_finalize__ (self, obj) : if obj is None : return #assert resolution res = getattr(obj, 'voxelsize', None) if res is None :#assert vdim == 1 res = (1.,) * len(obj.shape) self.voxelsize = tuple(res) #metadata self.info = dict(getattr(obj, 'info', {}) ) def clone (self, data) : """Clone the current image metadata on the given data. .. warning:: vdim is defined according to self.voxelsize and data.shape :Parameters: - `data` - (array) :Returns Type: |SpatialImage| """ if len(data.shape) == len(self.voxelsize) : vdim = 1 elif len(data.shape) - len(self.voxelsize) == 1 : vdim =data.shape[-1] else : raise UserWarning("unable to handle such data dimension") return SpatialImage(data,self.voxelsize,vdim,self.info) @classmethod def valid_array(cls, array_like): return isinstance(array_like, (np.ndarray, cls)) and \ array_like.flags.f_contiguous def empty_image_like(spatial_image): array = np.zeros( spatial_image.shape, dtype=spatial_image.dtype ) return SpatialImage(array, spatial_image.voxelsize, vdim=1) def null_vector_field_like(spatial_image): array = np.zeros( list(spatial_image.shape)+[3], dtype=np.float32 ) return SpatialImage(array, spatial_image.voxelsize, vdim=3) def random_vector_field_like(spatial_image, smooth=0, max_=1): #~ if spatial_image.vdim == 1: #~ shape = spatial_image.shape+(3,) #~ else: #~ shape = spatial_image.shape shape = spatial_image.shape # Jonathan array = np.random.uniform(-max_, max_, shape) if smooth: array = ndimage.gaussian_filter(array, smooth) return SpatialImage(array, spatial_image.voxelsize, dtype=np.float32) def checkerboard(nx=9, ny=8, nz=5, size=10, vs=(1.,1.,1.), dtype=np.uint8): """Creates a 3D checkerboard image with `nx` squares in width, `ny` squares in height and `nz` squares in depth. The length of the edge in real units of each square is `size`.""" sxv, syv, szv = np.array([size]*3) / np.array(vs) array = np.zeros( (sxv*nx, syv*ny, szv*nz), dtype=dtype, order="F") typeinfo = np.iinfo(dtype) # -- wooo surely not the most beautiful implementation out here -- for k in range(nz): kval = typeinfo.max if (k%2==0) else typeinfo.min jval = kval for j in range(ny): ival = jval for i in range(nx): array[i*sxv:i*sxv+sxv, j*syv:j*syv+syv, k*szv:k*szv+szv] = ival ival = typeinfo.max if (ival==typeinfo.min) else typeinfo.min jval = typeinfo.max if (jval==typeinfo.min) else typeinfo.min kval = typeinfo.max if (kval==typeinfo.min) else typeinfo.min return SpatialImage(array, vs, dtype=dtype) def is2D(image): """ Test if the `image` (array) is in 2D or 3D. Return True if 2D, False if not. """ if len(image.shape) == 2 or image.shape[2] == 1: return True else: return False
# -*- python -*- # # spatial_image: spatial nd images # # Copyright 2006 INRIA - CIRAD - INRA # # File author(s): <NAME> <<EMAIL>> # # Distributed under the Cecill-C License. # See accompanying file LICENSE.txt or copy at # http://www.cecill.info/licences/Licence_CeCILL-C_V1-en.html # # OpenAlea WebSite : http://openalea.gforge.inria.fr # """ This module create the main |SpatialImage| object """ __license__= "Cecill-C" __revision__=" $Id: $ " import numpy as np from scipy import ndimage import copy as cp # -- deprecation messages -- # import warnings, exceptions # msg = "SpatialImage.resolution is deprecated, use SpatialImage.voxelsize" # rezexc = exceptions.PendingDeprecationWarning(msg) class SpatialImage(np.ndarray) : """ Associate meta data to np.ndarray """ def __new__ (cls, input_array, voxelsize = None, vdim = None, info = None, dtype = None, **kwargs) : """Instantiate a new |SpatialImage| if voxelsize is None, vdim will be used to infer space size and affect a voxelsize of 1 in each direction of space .. warning :: `resolution` keyword is deprecated. Use `voxelsize` instead. :Parameters: - `cls` - internal python - `input_array` (array) - data to put in the image - `voxelsize` (tuple of float) - spatial extension in each direction of space - `vdim` (int) - size of data if vector data are used - `info` (dict of str|any) - metainfo """ #if the input_array is 2D we can reshape it to 3D. #~ if input_array.ndim == 2: # Jonathan #~ input_array = input_array.reshape( input_array.shape+(1,) ) # Jonathan #initialize datas. For some obscure reason, we want the data #to be F-Contiguous in the NUMPY sense. I mean, if this is not #respected, we will have problems when communicating with #C-Code... yeah, that makes so much sense (fortran-contiguous #to be c-readable...). dtype = dtype if dtype is not None else input_array.dtype if input_array.flags.f_contiguous : obj = np.asarray(input_array, dtype=dtype).view(cls) else : obj = np.asarray(input_array, dtype=dtype, order='F').view(cls) voxelsize = kwargs.get("resolution", voxelsize) #to manage transition if voxelsize is None : #~ voxelsize = (1.,) * 3 voxelsize = (1.,) * input_array.ndim # Jonathan else : #~ if len(voxelsize) != 3 : if (input_array.ndim != 4) and (len(voxelsize) != input_array.ndim) : # Jonathan _ Compatibility with "champs_*.inr.gz" generated by Baloo & SuperBaloo raise ValueError("data dimension and voxelsize mismatch") obj.voxelsize = tuple(voxelsize) obj.vdim = vdim if vdim else 1 #set metadata if info is None : obj.info = {} else : obj.info = dict(info) #return return obj def _get_resolution(self): # warnings.warn(rezexc) return self.voxelsize def _set_resolution(self, val): # warnings.warn(rezexc) self.voxelsize = val resolution = property(_get_resolution, _set_resolution) @property def real_shape(self): #~ return np.multiply(self.shape[:3], self.voxelsize) return np.multiply(self.shape, self.voxelsize) # Jonathan def invert_z_axis( self ): """ invert allong 'Z' axis """ self = self[:,:,::-1] def __array_finalize__ (self, obj) : if obj is None : return #assert resolution res = getattr(obj, 'voxelsize', None) if res is None :#assert vdim == 1 res = (1.,) * len(obj.shape) self.voxelsize = tuple(res) #metadata self.info = dict(getattr(obj, 'info', {}) ) def clone (self, data) : """Clone the current image metadata on the given data. .. warning:: vdim is defined according to self.voxelsize and data.shape :Parameters: - `data` - (array) :Returns Type: |SpatialImage| """ if len(data.shape) == len(self.voxelsize) : vdim = 1 elif len(data.shape) - len(self.voxelsize) == 1 : vdim =data.shape[-1] else : raise UserWarning("unable to handle such data dimension") return SpatialImage(data,self.voxelsize,vdim,self.info) @classmethod def valid_array(cls, array_like): return isinstance(array_like, (np.ndarray, cls)) and \ array_like.flags.f_contiguous def empty_image_like(spatial_image): array = np.zeros( spatial_image.shape, dtype=spatial_image.dtype ) return SpatialImage(array, spatial_image.voxelsize, vdim=1) def null_vector_field_like(spatial_image): array = np.zeros( list(spatial_image.shape)+[3], dtype=np.float32 ) return SpatialImage(array, spatial_image.voxelsize, vdim=3) def random_vector_field_like(spatial_image, smooth=0, max_=1): #~ if spatial_image.vdim == 1: #~ shape = spatial_image.shape+(3,) #~ else: #~ shape = spatial_image.shape shape = spatial_image.shape # Jonathan array = np.random.uniform(-max_, max_, shape) if smooth: array = ndimage.gaussian_filter(array, smooth) return SpatialImage(array, spatial_image.voxelsize, dtype=np.float32) def checkerboard(nx=9, ny=8, nz=5, size=10, vs=(1.,1.,1.), dtype=np.uint8): """Creates a 3D checkerboard image with `nx` squares in width, `ny` squares in height and `nz` squares in depth. The length of the edge in real units of each square is `size`.""" sxv, syv, szv = np.array([size]*3) / np.array(vs) array = np.zeros( (sxv*nx, syv*ny, szv*nz), dtype=dtype, order="F") typeinfo = np.iinfo(dtype) # -- wooo surely not the most beautiful implementation out here -- for k in range(nz): kval = typeinfo.max if (k%2==0) else typeinfo.min jval = kval for j in range(ny): ival = jval for i in range(nx): array[i*sxv:i*sxv+sxv, j*syv:j*syv+syv, k*szv:k*szv+szv] = ival ival = typeinfo.max if (ival==typeinfo.min) else typeinfo.min jval = typeinfo.max if (jval==typeinfo.min) else typeinfo.min kval = typeinfo.max if (kval==typeinfo.min) else typeinfo.min return SpatialImage(array, vs, dtype=dtype) def is2D(image): """ Test if the `image` (array) is in 2D or 3D. Return True if 2D, False if not. """ if len(image.shape) == 2 or image.shape[2] == 1: return True else: return False
en
0.577009
# -*- python -*- # # spatial_image: spatial nd images # # Copyright 2006 INRIA - CIRAD - INRA # # File author(s): <NAME> <<EMAIL>> # # Distributed under the Cecill-C License. # See accompanying file LICENSE.txt or copy at # http://www.cecill.info/licences/Licence_CeCILL-C_V1-en.html # # OpenAlea WebSite : http://openalea.gforge.inria.fr # This module create the main |SpatialImage| object # -- deprecation messages -- # import warnings, exceptions # msg = "SpatialImage.resolution is deprecated, use SpatialImage.voxelsize" # rezexc = exceptions.PendingDeprecationWarning(msg) Associate meta data to np.ndarray Instantiate a new |SpatialImage| if voxelsize is None, vdim will be used to infer space size and affect a voxelsize of 1 in each direction of space .. warning :: `resolution` keyword is deprecated. Use `voxelsize` instead. :Parameters: - `cls` - internal python - `input_array` (array) - data to put in the image - `voxelsize` (tuple of float) - spatial extension in each direction of space - `vdim` (int) - size of data if vector data are used - `info` (dict of str|any) - metainfo #if the input_array is 2D we can reshape it to 3D. #~ if input_array.ndim == 2: # Jonathan #~ input_array = input_array.reshape( input_array.shape+(1,) ) # Jonathan #initialize datas. For some obscure reason, we want the data #to be F-Contiguous in the NUMPY sense. I mean, if this is not #respected, we will have problems when communicating with #C-Code... yeah, that makes so much sense (fortran-contiguous #to be c-readable...). #to manage transition #~ voxelsize = (1.,) * 3 # Jonathan #~ if len(voxelsize) != 3 : # Jonathan _ Compatibility with "champs_*.inr.gz" generated by Baloo & SuperBaloo #set metadata #return # warnings.warn(rezexc) # warnings.warn(rezexc) #~ return np.multiply(self.shape[:3], self.voxelsize) # Jonathan invert allong 'Z' axis #assert resolution #assert vdim == 1 #metadata Clone the current image metadata on the given data. .. warning:: vdim is defined according to self.voxelsize and data.shape :Parameters: - `data` - (array) :Returns Type: |SpatialImage| #~ if spatial_image.vdim == 1: #~ shape = spatial_image.shape+(3,) #~ else: #~ shape = spatial_image.shape # Jonathan Creates a 3D checkerboard image with `nx` squares in width, `ny` squares in height and `nz` squares in depth. The length of the edge in real units of each square is `size`. # -- wooo surely not the most beautiful implementation out here -- Test if the `image` (array) is in 2D or 3D. Return True if 2D, False if not.
2.668311
3
snippets/math/digit.py
KATO-Hiro/Somen-Soupy
1
6632188
# -*- coding: utf-8 -*- def count_digit(max_number: int) -> int: ''' Args: max_number: Int of number (greater than 1). Returns: the number of digit. Landau notation: O(log n) ''' if max_number == 0: return 1 digit = 0 while max_number: digit += 1 max_number //= 10 return digit
# -*- coding: utf-8 -*- def count_digit(max_number: int) -> int: ''' Args: max_number: Int of number (greater than 1). Returns: the number of digit. Landau notation: O(log n) ''' if max_number == 0: return 1 digit = 0 while max_number: digit += 1 max_number //= 10 return digit
en
0.659243
# -*- coding: utf-8 -*- Args: max_number: Int of number (greater than 1). Returns: the number of digit. Landau notation: O(log n)
3.993526
4
learning-flask/application.py
eduardoc7/edx_python_javascript
1
6632189
from flask import Flask, render_template, request, session from flask_session import Session app = Flask(__name__) notes = list() # Aplicação para receber um formulário e adicionar a uma lista de notas, # que será exibida na tela # Main Program app.config["SESSION_PERMANENT"] = False app.config["SESSION_TYPE"] = 'filesystem' Session(app) @app.route('/', methods=['GET', 'POST']) def index(): if session.get('notes') is None: session['notes'] = list() if request.method == 'POST': note = request.form.get('note') session['notes'].append(note) return render_template('index4.html', notes=session['notes'])
from flask import Flask, render_template, request, session from flask_session import Session app = Flask(__name__) notes = list() # Aplicação para receber um formulário e adicionar a uma lista de notas, # que será exibida na tela # Main Program app.config["SESSION_PERMANENT"] = False app.config["SESSION_TYPE"] = 'filesystem' Session(app) @app.route('/', methods=['GET', 'POST']) def index(): if session.get('notes') is None: session['notes'] = list() if request.method == 'POST': note = request.form.get('note') session['notes'].append(note) return render_template('index4.html', notes=session['notes'])
pt
0.994828
# Aplicação para receber um formulário e adicionar a uma lista de notas, # que será exibida na tela # Main Program
3.311467
3
python/perspective/perspective/tests/table/test_remove.py
willium/perspective
0
6632190
# ***************************************************************************** # # Copyright (c) 2019, the Perspective Authors. # # This file is part of the Perspective library, distributed under the terms of # the Apache License 2.0. The full license can be found in the LICENSE file. # from perspective.table import Table class TestRemove(object): def test_remove_all(self): tbl = Table([{"a": "abc", "b": 123}], {"index": "a"}) tbl.remove(["abc"]) assert tbl.view().to_records() == [] def test_remove_nonsequential(self): tbl = Table([{"a": "abc", "b": 123}, {"a": "def", "b": 456}, {"a": "efg", "b": 789}], {"index": "a"}) tbl.remove(["abc", "efg"]) assert tbl.view().to_records() == [{"a": "def", "b": 456}] def test_remove_multiple_single(self): tbl = Table({"a": int, "b": str}, {"index": "a"}) for i in range(0, 10): tbl.update([{"a": i, "b": str(i)}]) for i in range(1, 10): tbl.remove([i]) assert tbl.view().to_records() == [{"a": 0, "b": "0"}]
# ***************************************************************************** # # Copyright (c) 2019, the Perspective Authors. # # This file is part of the Perspective library, distributed under the terms of # the Apache License 2.0. The full license can be found in the LICENSE file. # from perspective.table import Table class TestRemove(object): def test_remove_all(self): tbl = Table([{"a": "abc", "b": 123}], {"index": "a"}) tbl.remove(["abc"]) assert tbl.view().to_records() == [] def test_remove_nonsequential(self): tbl = Table([{"a": "abc", "b": 123}, {"a": "def", "b": 456}, {"a": "efg", "b": 789}], {"index": "a"}) tbl.remove(["abc", "efg"]) assert tbl.view().to_records() == [{"a": "def", "b": 456}] def test_remove_multiple_single(self): tbl = Table({"a": int, "b": str}, {"index": "a"}) for i in range(0, 10): tbl.update([{"a": i, "b": str(i)}]) for i in range(1, 10): tbl.remove([i]) assert tbl.view().to_records() == [{"a": 0, "b": "0"}]
en
0.76268
# ***************************************************************************** # # Copyright (c) 2019, the Perspective Authors. # # This file is part of the Perspective library, distributed under the terms of # the Apache License 2.0. The full license can be found in the LICENSE file. #
2.415083
2
main/urls.py
dera1992/blog_tutorial
0
6632191
app_name = "main" urlpatterns = [ ]
app_name = "main" urlpatterns = [ ]
none
1
1.023896
1
kstore/migrations/0013_auto_20160215_1028.py
KeoH/django-keoh-kstore
0
6632192
# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import models, migrations import datetime from django.utils.timezone import utc class Migration(migrations.Migration): dependencies = [ ('kstore', '0012_basicconfiguration_theme'), ] operations = [ migrations.AddField( model_name='mailmessage', name='created_at', field=models.DateTimeField(default=datetime.datetime(2016, 2, 15, 9, 28, 18, 635423, tzinfo=utc), auto_now_add=True), preserve_default=False, ), migrations.AlterField( model_name='mailmessage', name='sended_at', field=models.DateTimeField(blank=True), ), ]
# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import models, migrations import datetime from django.utils.timezone import utc class Migration(migrations.Migration): dependencies = [ ('kstore', '0012_basicconfiguration_theme'), ] operations = [ migrations.AddField( model_name='mailmessage', name='created_at', field=models.DateTimeField(default=datetime.datetime(2016, 2, 15, 9, 28, 18, 635423, tzinfo=utc), auto_now_add=True), preserve_default=False, ), migrations.AlterField( model_name='mailmessage', name='sended_at', field=models.DateTimeField(blank=True), ), ]
en
0.769321
# -*- coding: utf-8 -*-
1.667571
2
client/commands/tests/start_test.py
aspin/pyre-check
0
6632193
<filename>client/commands/tests/start_test.py # Copyright (c) 2016-present, Facebook, Inc. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. import errno import fcntl import unittest from unittest.mock import MagicMock, call, mock_open, patch from ... import commands, monitor, project_files_monitor # noqa from ...filesystem import AnalysisDirectory, acquire_lock # noqa from .command_test import mock_arguments, mock_configuration class StartTest(unittest.TestCase): @patch("{}.ProjectFilesMonitor".format(project_files_monitor.__name__)) @patch("fcntl.lockf") @patch.object(commands.Reporting, "_get_directories_to_analyze", return_value=set()) @patch.object(monitor.Monitor, "daemonize") def test_start( self, _daemonize, get_directories_to_analyze, lock_file, _daemonize_files_monitor, ) -> None: arguments = mock_arguments() arguments.terminal = False configuration = mock_configuration() configuration.version_hash = "hash" configuration.number_of_workers = 5 analysis_directory = AnalysisDirectory(".") # Check start without watchman. with patch("builtins.open", mock_open()), patch.object( commands.Command, "_call_client" ) as call_client: arguments.no_watchman = True command = commands.Start(arguments, configuration, analysis_directory) self.assertEqual( command._flags(), [ "-logging-sections", "parser", "-project-root", ".", "-workers", "5", "-typeshed", "stub", "-expected-binary-version", "hash", "-search-path", "path1,path2", ], ) command.run() call_client.assert_called_once_with(command=commands.Start.NAME) analysis_directory = AnalysisDirectory(".") # This magic is necessary to test, because the inner call to ping a server is # always non-blocking. def pass_when_blocking(file_descriptor, command): if not pass_when_blocking.failed and (command & fcntl.LOCK_NB): pass_when_blocking.failed = True raise OSError(errno.EAGAIN, "Only accepting blocking calls.") pass_when_blocking.failed = False lock_file.side_effect = pass_when_blocking # EAGAINs get caught. with patch("builtins.open", mock_open()), patch.object( commands.Command, "_call_client" ) as call_client: arguments.no_watchman = True command = commands.Start(arguments, configuration, analysis_directory) self.assertEqual( command._flags(), [ "-logging-sections", "parser", "-project-root", ".", "-workers", "5", "-typeshed", "stub", "-expected-binary-version", "hash", "-search-path", "path1,path2", ], ) command.run() call_client.assert_called_once_with(command=commands.Start.NAME) lock_file.side_effect = None def raise_mount_error(fileno, command): raise OSError(errno.ENOTCONN) lock_file.side_effect = raise_mount_error # Check that the command errors on OS errors other than EAGAIN. with patch("builtins.open", mock_open()), patch.object( commands.Command, "_call_client" ) as call_client: arguments.no_watchman = True command = commands.Start(arguments, configuration, analysis_directory) self.assertEqual( command._flags(), [ "-logging-sections", "parser", "-project-root", ".", "-workers", "5", "-typeshed", "stub", "-expected-binary-version", "hash", "-search-path", "path1,path2", ], ) with self.assertRaises(OSError): command.run() call_client.assert_not_called() lock_file.side_effect = None # Shared analysis directories are prepared when starting. shared_analysis_directory = MagicMock() shared_analysis_directory.get_root = lambda: "." with patch.object( commands.Command, "_call_client" ) as call_client, patch.object(shared_analysis_directory, "prepare") as prepare: arguments = mock_arguments(no_watchman=True) configuration = mock_configuration(version_hash="hash") command = commands.Start( arguments, configuration, shared_analysis_directory ) self.assertEqual( command._flags(), [ "-logging-sections", "parser", "-project-root", ".", "-workers", "5", "-typeshed", "stub", "-expected-binary-version", "hash", "-search-path", "path1,path2", ], ) command.run() call_client.assert_called_once_with(command=commands.Start.NAME) prepare.assert_called_once_with() @patch.object(commands.Reporting, "_get_directories_to_analyze", return_value=set()) def test_start_flags(self, get_directories_to_analyze): # Check start with watchman. arguments = mock_arguments() configuration = mock_configuration(version_hash="hash") command = commands.Start(arguments, configuration, AnalysisDirectory(".")) self.assertEqual( command._flags(), [ "-logging-sections", "parser", "-project-root", ".", "-workers", "5", "-typeshed", "stub", "-expected-binary-version", "hash", "-search-path", "path1,path2", ], ) arguments = mock_arguments(no_watchman=True, terminal=True) configuration = mock_configuration(version_hash="hash") command = commands.Start(arguments, configuration, AnalysisDirectory(".")) self.assertEqual( command._flags(), [ "-logging-sections", "parser", "-project-root", ".", "-terminal", "-workers", "5", "-typeshed", "stub", "-expected-binary-version", "hash", "-search-path", "path1,path2", ], ) # Check filter directories. arguments = mock_arguments(no_watchman=True) configuration = mock_configuration(version_hash="hash") command = commands.Start(arguments, configuration, AnalysisDirectory(".")) with patch.object(command, "_get_directories_to_analyze") as get_directories: get_directories.return_value = {"a", "b"} self.assertEqual( command._flags(), [ "-logging-sections", "parser", "-project-root", ".", "-filter-directories", "a;b", "-workers", "5", "-typeshed", "stub", "-expected-binary-version", "hash", "-search-path", "path1,path2", ], ) # Check configuration-file-hash. arguments = mock_arguments(no_watchman=True) configuration = mock_configuration(version_hash="hash", file_hash="ABCD") command = commands.Start(arguments, configuration, AnalysisDirectory(".")) with patch.object(command, "_get_directories_to_analyze") as get_directories: get_directories.return_value = {"a", "b"} self.assertEqual( command._flags(), [ "-logging-sections", "parser", "-project-root", ".", "-filter-directories", "a;b", "-configuration-file-hash", "ABCD", "-workers", "5", "-typeshed", "stub", "-expected-binary-version", "hash", "-search-path", "path1,path2", ], ) # Check save-initial-state-to. arguments = mock_arguments(save_initial_state_to="/tmp") configuration = mock_configuration(version_hash="hash") command = commands.Start(arguments, configuration, AnalysisDirectory(".")) self.assertEqual( command._flags(), [ "-logging-sections", "parser", "-project-root", ".", "-save-initial-state-to", "/tmp", "-workers", "5", "-typeshed", "stub", "-expected-binary-version", "hash", "-search-path", "path1,path2", ], ) # Check load-initial-state-from. arguments = mock_arguments( load_initial_state_from="/tmp/pyre_shared_memory", changed_files_path="/tmp/changed_files", ) command = commands.Start(arguments, configuration, AnalysisDirectory(".")) self.assertEqual( command._flags(), [ "-logging-sections", "parser", "-project-root", ".", "-load-state-from", "/tmp/pyre_shared_memory", "-changed-files-path", "/tmp/changed_files", "-workers", "5", "-typeshed", "stub", "-expected-binary-version", "hash", "-search-path", "path1,path2", ], ) # Both changed-files-path and load-initial-state-from must be not-None. arguments = mock_arguments(changed_files_path="/tmp/changed_files") command = commands.Start(arguments, configuration, AnalysisDirectory(".")) self.assertEqual( command._flags(), [ "-logging-sections", "parser", "-project-root", ".", "-workers", "5", "-typeshed", "stub", "-expected-binary-version", "hash", "-search-path", "path1,path2", ], ) # Check load-initial-state-from. arguments = mock_arguments(changed_files_path="/tmp/changed_files") command = commands.Start(arguments, configuration, AnalysisDirectory(".")) self.assertEqual( command._flags(), [ "-logging-sections", "parser", "-project-root", ".", "-workers", "5", "-typeshed", "stub", "-expected-binary-version", "hash", "-search-path", "path1,path2", ], ) # Check --saved-state-project. arguments = mock_arguments(saved_state_project="pyre/saved_state") command = commands.Start(arguments, configuration, AnalysisDirectory(".")) self.assertEqual( command._flags(), [ "-logging-sections", "parser", "-project-root", ".", "-saved-state-project", "pyre/saved_state", "-workers", "5", "-typeshed", "stub", "-expected-binary-version", "hash", "-search-path", "path1,path2", ], ) # Check --no-saved-state. arguments = mock_arguments( saved_state_project="pyre/saved_state", no_saved_state=True ) command = commands.Start(arguments, configuration, AnalysisDirectory(".")) self.assertEqual( command._flags(), [ "-logging-sections", "parser", "-project-root", ".", "-workers", "5", "-typeshed", "stub", "-expected-binary-version", "hash", "-search-path", "path1,path2", ], ) arguments = mock_arguments(no_saved_state=True) arguments.load_initial_state_from = "/do/not/load" arguments.save_initial_state_to = "/do/not/save" arguments.changed_files_path = "/do/not/change" command = commands.Start(arguments, configuration, AnalysisDirectory(".")) self.assertEqual( command._flags(), [ "-logging-sections", "parser", "-project-root", ".", "-workers", "5", "-typeshed", "stub", "-expected-binary-version", "hash", "-search-path", "path1,path2", ], ) arguments = mock_arguments(store_type_check_resolution=True) command = commands.Start(arguments, configuration, AnalysisDirectory(".")) self.assertEqual( command._flags(), [ "-logging-sections", "parser", "-project-root", ".", "-store-type-check-resolution", "-workers", "5", "-typeshed", "stub", "-expected-binary-version", "hash", "-search-path", "path1,path2", ], )
<filename>client/commands/tests/start_test.py # Copyright (c) 2016-present, Facebook, Inc. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. import errno import fcntl import unittest from unittest.mock import MagicMock, call, mock_open, patch from ... import commands, monitor, project_files_monitor # noqa from ...filesystem import AnalysisDirectory, acquire_lock # noqa from .command_test import mock_arguments, mock_configuration class StartTest(unittest.TestCase): @patch("{}.ProjectFilesMonitor".format(project_files_monitor.__name__)) @patch("fcntl.lockf") @patch.object(commands.Reporting, "_get_directories_to_analyze", return_value=set()) @patch.object(monitor.Monitor, "daemonize") def test_start( self, _daemonize, get_directories_to_analyze, lock_file, _daemonize_files_monitor, ) -> None: arguments = mock_arguments() arguments.terminal = False configuration = mock_configuration() configuration.version_hash = "hash" configuration.number_of_workers = 5 analysis_directory = AnalysisDirectory(".") # Check start without watchman. with patch("builtins.open", mock_open()), patch.object( commands.Command, "_call_client" ) as call_client: arguments.no_watchman = True command = commands.Start(arguments, configuration, analysis_directory) self.assertEqual( command._flags(), [ "-logging-sections", "parser", "-project-root", ".", "-workers", "5", "-typeshed", "stub", "-expected-binary-version", "hash", "-search-path", "path1,path2", ], ) command.run() call_client.assert_called_once_with(command=commands.Start.NAME) analysis_directory = AnalysisDirectory(".") # This magic is necessary to test, because the inner call to ping a server is # always non-blocking. def pass_when_blocking(file_descriptor, command): if not pass_when_blocking.failed and (command & fcntl.LOCK_NB): pass_when_blocking.failed = True raise OSError(errno.EAGAIN, "Only accepting blocking calls.") pass_when_blocking.failed = False lock_file.side_effect = pass_when_blocking # EAGAINs get caught. with patch("builtins.open", mock_open()), patch.object( commands.Command, "_call_client" ) as call_client: arguments.no_watchman = True command = commands.Start(arguments, configuration, analysis_directory) self.assertEqual( command._flags(), [ "-logging-sections", "parser", "-project-root", ".", "-workers", "5", "-typeshed", "stub", "-expected-binary-version", "hash", "-search-path", "path1,path2", ], ) command.run() call_client.assert_called_once_with(command=commands.Start.NAME) lock_file.side_effect = None def raise_mount_error(fileno, command): raise OSError(errno.ENOTCONN) lock_file.side_effect = raise_mount_error # Check that the command errors on OS errors other than EAGAIN. with patch("builtins.open", mock_open()), patch.object( commands.Command, "_call_client" ) as call_client: arguments.no_watchman = True command = commands.Start(arguments, configuration, analysis_directory) self.assertEqual( command._flags(), [ "-logging-sections", "parser", "-project-root", ".", "-workers", "5", "-typeshed", "stub", "-expected-binary-version", "hash", "-search-path", "path1,path2", ], ) with self.assertRaises(OSError): command.run() call_client.assert_not_called() lock_file.side_effect = None # Shared analysis directories are prepared when starting. shared_analysis_directory = MagicMock() shared_analysis_directory.get_root = lambda: "." with patch.object( commands.Command, "_call_client" ) as call_client, patch.object(shared_analysis_directory, "prepare") as prepare: arguments = mock_arguments(no_watchman=True) configuration = mock_configuration(version_hash="hash") command = commands.Start( arguments, configuration, shared_analysis_directory ) self.assertEqual( command._flags(), [ "-logging-sections", "parser", "-project-root", ".", "-workers", "5", "-typeshed", "stub", "-expected-binary-version", "hash", "-search-path", "path1,path2", ], ) command.run() call_client.assert_called_once_with(command=commands.Start.NAME) prepare.assert_called_once_with() @patch.object(commands.Reporting, "_get_directories_to_analyze", return_value=set()) def test_start_flags(self, get_directories_to_analyze): # Check start with watchman. arguments = mock_arguments() configuration = mock_configuration(version_hash="hash") command = commands.Start(arguments, configuration, AnalysisDirectory(".")) self.assertEqual( command._flags(), [ "-logging-sections", "parser", "-project-root", ".", "-workers", "5", "-typeshed", "stub", "-expected-binary-version", "hash", "-search-path", "path1,path2", ], ) arguments = mock_arguments(no_watchman=True, terminal=True) configuration = mock_configuration(version_hash="hash") command = commands.Start(arguments, configuration, AnalysisDirectory(".")) self.assertEqual( command._flags(), [ "-logging-sections", "parser", "-project-root", ".", "-terminal", "-workers", "5", "-typeshed", "stub", "-expected-binary-version", "hash", "-search-path", "path1,path2", ], ) # Check filter directories. arguments = mock_arguments(no_watchman=True) configuration = mock_configuration(version_hash="hash") command = commands.Start(arguments, configuration, AnalysisDirectory(".")) with patch.object(command, "_get_directories_to_analyze") as get_directories: get_directories.return_value = {"a", "b"} self.assertEqual( command._flags(), [ "-logging-sections", "parser", "-project-root", ".", "-filter-directories", "a;b", "-workers", "5", "-typeshed", "stub", "-expected-binary-version", "hash", "-search-path", "path1,path2", ], ) # Check configuration-file-hash. arguments = mock_arguments(no_watchman=True) configuration = mock_configuration(version_hash="hash", file_hash="ABCD") command = commands.Start(arguments, configuration, AnalysisDirectory(".")) with patch.object(command, "_get_directories_to_analyze") as get_directories: get_directories.return_value = {"a", "b"} self.assertEqual( command._flags(), [ "-logging-sections", "parser", "-project-root", ".", "-filter-directories", "a;b", "-configuration-file-hash", "ABCD", "-workers", "5", "-typeshed", "stub", "-expected-binary-version", "hash", "-search-path", "path1,path2", ], ) # Check save-initial-state-to. arguments = mock_arguments(save_initial_state_to="/tmp") configuration = mock_configuration(version_hash="hash") command = commands.Start(arguments, configuration, AnalysisDirectory(".")) self.assertEqual( command._flags(), [ "-logging-sections", "parser", "-project-root", ".", "-save-initial-state-to", "/tmp", "-workers", "5", "-typeshed", "stub", "-expected-binary-version", "hash", "-search-path", "path1,path2", ], ) # Check load-initial-state-from. arguments = mock_arguments( load_initial_state_from="/tmp/pyre_shared_memory", changed_files_path="/tmp/changed_files", ) command = commands.Start(arguments, configuration, AnalysisDirectory(".")) self.assertEqual( command._flags(), [ "-logging-sections", "parser", "-project-root", ".", "-load-state-from", "/tmp/pyre_shared_memory", "-changed-files-path", "/tmp/changed_files", "-workers", "5", "-typeshed", "stub", "-expected-binary-version", "hash", "-search-path", "path1,path2", ], ) # Both changed-files-path and load-initial-state-from must be not-None. arguments = mock_arguments(changed_files_path="/tmp/changed_files") command = commands.Start(arguments, configuration, AnalysisDirectory(".")) self.assertEqual( command._flags(), [ "-logging-sections", "parser", "-project-root", ".", "-workers", "5", "-typeshed", "stub", "-expected-binary-version", "hash", "-search-path", "path1,path2", ], ) # Check load-initial-state-from. arguments = mock_arguments(changed_files_path="/tmp/changed_files") command = commands.Start(arguments, configuration, AnalysisDirectory(".")) self.assertEqual( command._flags(), [ "-logging-sections", "parser", "-project-root", ".", "-workers", "5", "-typeshed", "stub", "-expected-binary-version", "hash", "-search-path", "path1,path2", ], ) # Check --saved-state-project. arguments = mock_arguments(saved_state_project="pyre/saved_state") command = commands.Start(arguments, configuration, AnalysisDirectory(".")) self.assertEqual( command._flags(), [ "-logging-sections", "parser", "-project-root", ".", "-saved-state-project", "pyre/saved_state", "-workers", "5", "-typeshed", "stub", "-expected-binary-version", "hash", "-search-path", "path1,path2", ], ) # Check --no-saved-state. arguments = mock_arguments( saved_state_project="pyre/saved_state", no_saved_state=True ) command = commands.Start(arguments, configuration, AnalysisDirectory(".")) self.assertEqual( command._flags(), [ "-logging-sections", "parser", "-project-root", ".", "-workers", "5", "-typeshed", "stub", "-expected-binary-version", "hash", "-search-path", "path1,path2", ], ) arguments = mock_arguments(no_saved_state=True) arguments.load_initial_state_from = "/do/not/load" arguments.save_initial_state_to = "/do/not/save" arguments.changed_files_path = "/do/not/change" command = commands.Start(arguments, configuration, AnalysisDirectory(".")) self.assertEqual( command._flags(), [ "-logging-sections", "parser", "-project-root", ".", "-workers", "5", "-typeshed", "stub", "-expected-binary-version", "hash", "-search-path", "path1,path2", ], ) arguments = mock_arguments(store_type_check_resolution=True) command = commands.Start(arguments, configuration, AnalysisDirectory(".")) self.assertEqual( command._flags(), [ "-logging-sections", "parser", "-project-root", ".", "-store-type-check-resolution", "-workers", "5", "-typeshed", "stub", "-expected-binary-version", "hash", "-search-path", "path1,path2", ], )
en
0.819658
# Copyright (c) 2016-present, Facebook, Inc. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. # noqa # noqa # Check start without watchman. # This magic is necessary to test, because the inner call to ping a server is # always non-blocking. # EAGAINs get caught. # Check that the command errors on OS errors other than EAGAIN. # Shared analysis directories are prepared when starting. # Check start with watchman. # Check filter directories. # Check configuration-file-hash. # Check save-initial-state-to. # Check load-initial-state-from. # Both changed-files-path and load-initial-state-from must be not-None. # Check load-initial-state-from. # Check --saved-state-project. # Check --no-saved-state.
2.083856
2
evaluation_cyclegan/test.py
samxuxiang/mcmi
3
6632194
import torch from options.test_options import TestOptions from dataset import dataset_single from saver import save_imgs import os import inception_utils from inception import InceptionV3 import numpy as np import glob from models import create_model import modelss import torchvision def compute_lpips(imgs, model_alexnet): num_samples = len(imgs) dists = [] for idx1 in range(0,num_samples): idx2 = idx1+1 while idx2 < num_samples: img0 = imgs[idx1] img1 = imgs[idx2] lpips_dist = model_alexnet.forward(img0,img1).item() dists.append(lpips_dist) idx2 += 1 lpips_score = sum(dists) / len(dists) return lpips_score def main(): # parse options opt = TestOptions().parse() opt.num_threads = 0 # test code only supports num_threads = 1 opt.batch_size = 1 # test code only supports batch_size = 1 opt.serial_batches = True # disable data shuffling; comment this line if results on randomly chosen images are needed. opt.no_flip = True # no flip; comment this line if results on flipped images are needed. opt.display_id = -1 # no visdom display; the test code saves the results to a HTML file. # data loader print('\n--- load dataset ---') #if opt.a2b: dataset = dataset_single(opt, 'A') #else: #dataset = dataset_single(opt, 'B') loader = torch.utils.data.DataLoader(dataset, batch_size=1, num_workers=8) file_name = opt.fid data_mu = np.load(file_name)['mu'] data_sigma = np.load(file_name)['sigma'] # Load inception net print('\n--- load inception net ---') block_idx = InceptionV3.BLOCK_INDEX_BY_DIM[2048] model_inception = InceptionV3([block_idx]).cuda() model_inception.eval() # set to eval mode ## Initializing the AlexNet model model_alexnet = modelss.PerceptualLoss(model='net-lin',net='alex',use_gpu=True) transform = torchvision.transforms.Compose([ torchvision.transforms.ToPILImage(), torchvision.transforms.Resize(64), torchvision.transforms.ToTensor()]) # Load pre-trained model print('\n--- load model ---') model = create_model(opt) all_files = np.arange(200, 210, 10).tolist() torch.manual_seed(8) torch.backends.cudnn.deterministic = True torch.backends.cudnn.benchmark = False np.random.seed(8) test_sample = 1 for epoch in all_files: model.load_networks(epoch) model.eval() # generate images & accumulate inception activation pool1 = [] pool2 = [] dists = [] for idx1, img1 in enumerate(loader): img = img1.cuda() imgs = [img] names = ['input'] with torch.no_grad(): img = model.test_forward(img, a2b=True) imgs = [img] imgss = [] # accumulate inception activation for FID1 assert (torch.max(img)<=1.0 and torch.min(img)>=-1.0) pool_val = model_inception(img)[0] # bs x 2048 x 1 x 1 assert(pool_val.size(1)==2048 and pool_val.size(2) == 1 and pool_val.size(3)==1) pool_val = pool_val.squeeze() pool1 += [np.asarray(pool_val.cpu())] for i in range(1): img = model.test_forward(img, a2b=False) img = model.test_forward(img, a2b=True) imgs += [img] # accumulate inception activation for FID2 assert (torch.max(img)<=1.0 and torch.min(img)>=-1.0) pool_val = model_inception(img)[0] # bs x 2048 x 1 x 1 assert(pool_val.size(1)==2048 and pool_val.size(2) == 1 and pool_val.size(3)==1) pool_val = pool_val.squeeze() pool2 += [np.asarray(pool_val.cpu())] # test lpips on 4 (1+1+2) generated images for i in range(2): img = model.test_forward(img, a2b=False) img = model.test_forward(img, a2b=True) imgs += [img] for i in imgs: imgss.append(transform(i[0].cpu()).cuda()) dist = compute_lpips(imgss, model_alexnet) dists.append(dist) # compute fid score lpips_score = sum(dists) / len(dists) print('LPIPS score for epoch %d is %f ' %(epoch, lpips_score)) pool1 = np.vstack(pool1) mu, sigma = np.mean(pool1, axis=0), np.cov(pool1, rowvar=False) FID1 = inception_utils.numpy_calculate_frechet_distance(mu, sigma, data_mu, data_sigma) print('FID1 score for epoch %d is %f ' %(epoch, FID1)) pool2 = np.vstack(pool2) mu, sigma = np.mean(pool2, axis=0), np.cov(pool2, rowvar=False) FID2 = inception_utils.numpy_calculate_frechet_distance(mu, sigma, data_mu, data_sigma) print('FID2 score for epoch %d is %f ' %(epoch, FID2)) if __name__ == '__main__': main()
import torch from options.test_options import TestOptions from dataset import dataset_single from saver import save_imgs import os import inception_utils from inception import InceptionV3 import numpy as np import glob from models import create_model import modelss import torchvision def compute_lpips(imgs, model_alexnet): num_samples = len(imgs) dists = [] for idx1 in range(0,num_samples): idx2 = idx1+1 while idx2 < num_samples: img0 = imgs[idx1] img1 = imgs[idx2] lpips_dist = model_alexnet.forward(img0,img1).item() dists.append(lpips_dist) idx2 += 1 lpips_score = sum(dists) / len(dists) return lpips_score def main(): # parse options opt = TestOptions().parse() opt.num_threads = 0 # test code only supports num_threads = 1 opt.batch_size = 1 # test code only supports batch_size = 1 opt.serial_batches = True # disable data shuffling; comment this line if results on randomly chosen images are needed. opt.no_flip = True # no flip; comment this line if results on flipped images are needed. opt.display_id = -1 # no visdom display; the test code saves the results to a HTML file. # data loader print('\n--- load dataset ---') #if opt.a2b: dataset = dataset_single(opt, 'A') #else: #dataset = dataset_single(opt, 'B') loader = torch.utils.data.DataLoader(dataset, batch_size=1, num_workers=8) file_name = opt.fid data_mu = np.load(file_name)['mu'] data_sigma = np.load(file_name)['sigma'] # Load inception net print('\n--- load inception net ---') block_idx = InceptionV3.BLOCK_INDEX_BY_DIM[2048] model_inception = InceptionV3([block_idx]).cuda() model_inception.eval() # set to eval mode ## Initializing the AlexNet model model_alexnet = modelss.PerceptualLoss(model='net-lin',net='alex',use_gpu=True) transform = torchvision.transforms.Compose([ torchvision.transforms.ToPILImage(), torchvision.transforms.Resize(64), torchvision.transforms.ToTensor()]) # Load pre-trained model print('\n--- load model ---') model = create_model(opt) all_files = np.arange(200, 210, 10).tolist() torch.manual_seed(8) torch.backends.cudnn.deterministic = True torch.backends.cudnn.benchmark = False np.random.seed(8) test_sample = 1 for epoch in all_files: model.load_networks(epoch) model.eval() # generate images & accumulate inception activation pool1 = [] pool2 = [] dists = [] for idx1, img1 in enumerate(loader): img = img1.cuda() imgs = [img] names = ['input'] with torch.no_grad(): img = model.test_forward(img, a2b=True) imgs = [img] imgss = [] # accumulate inception activation for FID1 assert (torch.max(img)<=1.0 and torch.min(img)>=-1.0) pool_val = model_inception(img)[0] # bs x 2048 x 1 x 1 assert(pool_val.size(1)==2048 and pool_val.size(2) == 1 and pool_val.size(3)==1) pool_val = pool_val.squeeze() pool1 += [np.asarray(pool_val.cpu())] for i in range(1): img = model.test_forward(img, a2b=False) img = model.test_forward(img, a2b=True) imgs += [img] # accumulate inception activation for FID2 assert (torch.max(img)<=1.0 and torch.min(img)>=-1.0) pool_val = model_inception(img)[0] # bs x 2048 x 1 x 1 assert(pool_val.size(1)==2048 and pool_val.size(2) == 1 and pool_val.size(3)==1) pool_val = pool_val.squeeze() pool2 += [np.asarray(pool_val.cpu())] # test lpips on 4 (1+1+2) generated images for i in range(2): img = model.test_forward(img, a2b=False) img = model.test_forward(img, a2b=True) imgs += [img] for i in imgs: imgss.append(transform(i[0].cpu()).cuda()) dist = compute_lpips(imgss, model_alexnet) dists.append(dist) # compute fid score lpips_score = sum(dists) / len(dists) print('LPIPS score for epoch %d is %f ' %(epoch, lpips_score)) pool1 = np.vstack(pool1) mu, sigma = np.mean(pool1, axis=0), np.cov(pool1, rowvar=False) FID1 = inception_utils.numpy_calculate_frechet_distance(mu, sigma, data_mu, data_sigma) print('FID1 score for epoch %d is %f ' %(epoch, FID1)) pool2 = np.vstack(pool2) mu, sigma = np.mean(pool2, axis=0), np.cov(pool2, rowvar=False) FID2 = inception_utils.numpy_calculate_frechet_distance(mu, sigma, data_mu, data_sigma) print('FID2 score for epoch %d is %f ' %(epoch, FID2)) if __name__ == '__main__': main()
en
0.619141
# parse options # test code only supports num_threads = 1 # test code only supports batch_size = 1 # disable data shuffling; comment this line if results on randomly chosen images are needed. # no flip; comment this line if results on flipped images are needed. # no visdom display; the test code saves the results to a HTML file. # data loader #if opt.a2b: #else: #dataset = dataset_single(opt, 'B') # Load inception net # set to eval mode ## Initializing the AlexNet model # Load pre-trained model # generate images & accumulate inception activation # accumulate inception activation for FID1 # bs x 2048 x 1 x 1 # accumulate inception activation for FID2 # bs x 2048 x 1 x 1 # test lpips on 4 (1+1+2) generated images # compute fid score
2.158939
2
api/v1/app.py
Theemiss/Quick_Report
4
6632195
<gh_stars>1-10 from flask import Flask, make_response, jsonify from datetime import timedelta from flask_restful import Api from flask_sqlalchemy import SQLAlchemy from flask_jwt_extended import JWTManager from flask_cors import CORS from flask_migrate import Migrate from flask_restful_swagger import swagger from dotenv import dotenv_values from flask_wkhtmltopdf import Wkhtmltopdf """ Global File Config And Route api instance """ config = dotenv_values('.env') app = Flask(__name__) wkhtmltopdf = Wkhtmltopdf(app) api = swagger.docs(Api(app), apiVersion='2.8') # swagger Init jwt = JWTManager(app) WKHTMLTOPDF_BIN_PATH = "" #path to your wkhtmltopdf installation. db = SQLAlchemy(app) migrate = Migrate(app, db) #app.config['JSONIFY_PRETTYPRINT_REGULAR'] = True app.config['SQLALCHEMY_DATABASE_URI'] = 'postgresql://postgres:55664730@localhost:5432/quick_report' app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False app.config['SECRET_KEY'] = 'holbieQuickreport' app.config['JWT_SECRET_KEY'] = 'Qucikreportadmin' ACCESS_EXPIRES = timedelta(hours=24) app.config["JWT_ACCESS_TOKEN_EXPIRES"] = ACCESS_EXPIRES #Token Time Auto Revoke app.config['JWT_BLACKLIST_ENABLED'] = True # Enable Token Blocklist app.config['JWT_BLACKLIST_TOKEN_CHECKS'] = ['access', 'refresh'] #Type of Token db = SQLAlchemy(app) migrate = Migrate(app, db) class TokenBlocklist(db.Model): """ db table for the jwt token Blocklist """ id = db.Column(db.Integer, primary_key=True) jti = db.Column(db.String(36), nullable=False) created_at = db.Column(db.DateTime, nullable=False) # Callback function to check if a JWT exists in the database blocklist @jwt.token_in_blocklist_loader def check_if_token_revoked(jwt_header,jwt_payload): """ Check if Token in Database Bloclist or Revoked jwt_header: Header of the Request to check jwt_payload: Body of the Request to Check """ jti = jwt_payload["jti"] token = db.session.query(TokenBlocklist.id).filter_by(jti=jti).scalar() return token is not None @app.before_first_request def create_tables(): """ First thing to excute in first request to the server """ db.create_all() cors = CORS(app, resources={"/*": {"origins": "*"}}) @app.errorhandler(404) def not_found(error): """ 404 Error --- responses: 404: description: a resource was not found """ return make_response(jsonify({'error': "Not found"}), 404) @app.errorhandler(500) def special_exception_handler(error): return make_response(jsonify({'error': "'Database connection failed'"}), 500) from api.v1.views import company_route_all # Public Route for now getting comapny and creating new one api.add_resource(company_route_all, "/api/hidden") from api.v1.views import Login, sign_up, Logout, TokenRefresh, ClientUserForm, CompanyAllClient, AdminUserID, CompanyAllRepport,CompanySingleRapport # Authentication api.add_resource(sign_up, "/api/signup") # signup api.add_resource(Login, "/api/login") # Login api.add_resource(Logout, "/api/logout") # Logout api.add_resource(TokenRefresh, "/api/refresh") # Token refrecher # Get Current Logged Client or update user information api.add_resource(ClientUserForm, "/api/client") # Company Action Web # Get All Client that Belong to this Comapny api.add_resource(CompanyAllClient, "/api/company/clients") # Get Client that belong to this comapny by id api.add_resource(AdminUserID, "/api/company/clients/<id>") # Get All Report that bellong to current Company api.add_resource(CompanyAllRepport, '/api/company/reports') api.add_resource(CompanySingleRapport,'/api/report/<id>') from api.v1.views import NewCar, GetUserCar, NewInsurance, GetClientCarId # Cars and insurance Endpoint api.add_resource(NewInsurance, '/api/insurance/new') # Create new insurance api.add_resource(NewCar, '/api/car/new') # Create new car # All Car that belong to the current client api.add_resource(GetUserCar, '/api/client/cars') # Car by id that belong current Client api.add_resource(GetClientCarId, '/api/client/cars/<id>') from api.v1.views import ReportNew, Reportid, ReportPdf, Media, AllMedia,MatcherA,MatcherB # Rapport Creation and Handling # Create new Repport or Get All current Client Repport api.add_resource(ReportNew, '/api/client/report') # Get repport bellong to current client api.add_resource(Reportid, '/api/client/report/<id>') # Create a pdf file from reports api.add_resource(ReportPdf, '/api/client/report/pdf/<a>') # Get File image api.add_resource(Media, "/api/client/report/media/<path:path>") api.add_resource(AllMedia, "/api/client/report/media") # List all file media api.add_resource(MatcherA,'/api/reportA') api.add_resource(MatcherB,'/api/reportB') from api.v1.views import FetchCar,Dashboard,GetBReport,AllClientCar api.add_resource(Dashboard,"/api/company/data") api.add_resource(GetBReport,"/api/company/<id>") api.add_resource(FetchCar,'/api/company/Car') api.add_resource(AllClientCar,"/api/company/client/car")
from flask import Flask, make_response, jsonify from datetime import timedelta from flask_restful import Api from flask_sqlalchemy import SQLAlchemy from flask_jwt_extended import JWTManager from flask_cors import CORS from flask_migrate import Migrate from flask_restful_swagger import swagger from dotenv import dotenv_values from flask_wkhtmltopdf import Wkhtmltopdf """ Global File Config And Route api instance """ config = dotenv_values('.env') app = Flask(__name__) wkhtmltopdf = Wkhtmltopdf(app) api = swagger.docs(Api(app), apiVersion='2.8') # swagger Init jwt = JWTManager(app) WKHTMLTOPDF_BIN_PATH = "" #path to your wkhtmltopdf installation. db = SQLAlchemy(app) migrate = Migrate(app, db) #app.config['JSONIFY_PRETTYPRINT_REGULAR'] = True app.config['SQLALCHEMY_DATABASE_URI'] = 'postgresql://postgres:55664730@localhost:5432/quick_report' app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False app.config['SECRET_KEY'] = 'holbieQuickreport' app.config['JWT_SECRET_KEY'] = 'Qucikreportadmin' ACCESS_EXPIRES = timedelta(hours=24) app.config["JWT_ACCESS_TOKEN_EXPIRES"] = ACCESS_EXPIRES #Token Time Auto Revoke app.config['JWT_BLACKLIST_ENABLED'] = True # Enable Token Blocklist app.config['JWT_BLACKLIST_TOKEN_CHECKS'] = ['access', 'refresh'] #Type of Token db = SQLAlchemy(app) migrate = Migrate(app, db) class TokenBlocklist(db.Model): """ db table for the jwt token Blocklist """ id = db.Column(db.Integer, primary_key=True) jti = db.Column(db.String(36), nullable=False) created_at = db.Column(db.DateTime, nullable=False) # Callback function to check if a JWT exists in the database blocklist @jwt.token_in_blocklist_loader def check_if_token_revoked(jwt_header,jwt_payload): """ Check if Token in Database Bloclist or Revoked jwt_header: Header of the Request to check jwt_payload: Body of the Request to Check """ jti = jwt_payload["jti"] token = db.session.query(TokenBlocklist.id).filter_by(jti=jti).scalar() return token is not None @app.before_first_request def create_tables(): """ First thing to excute in first request to the server """ db.create_all() cors = CORS(app, resources={"/*": {"origins": "*"}}) @app.errorhandler(404) def not_found(error): """ 404 Error --- responses: 404: description: a resource was not found """ return make_response(jsonify({'error': "Not found"}), 404) @app.errorhandler(500) def special_exception_handler(error): return make_response(jsonify({'error': "'Database connection failed'"}), 500) from api.v1.views import company_route_all # Public Route for now getting comapny and creating new one api.add_resource(company_route_all, "/api/hidden") from api.v1.views import Login, sign_up, Logout, TokenRefresh, ClientUserForm, CompanyAllClient, AdminUserID, CompanyAllRepport,CompanySingleRapport # Authentication api.add_resource(sign_up, "/api/signup") # signup api.add_resource(Login, "/api/login") # Login api.add_resource(Logout, "/api/logout") # Logout api.add_resource(TokenRefresh, "/api/refresh") # Token refrecher # Get Current Logged Client or update user information api.add_resource(ClientUserForm, "/api/client") # Company Action Web # Get All Client that Belong to this Comapny api.add_resource(CompanyAllClient, "/api/company/clients") # Get Client that belong to this comapny by id api.add_resource(AdminUserID, "/api/company/clients/<id>") # Get All Report that bellong to current Company api.add_resource(CompanyAllRepport, '/api/company/reports') api.add_resource(CompanySingleRapport,'/api/report/<id>') from api.v1.views import NewCar, GetUserCar, NewInsurance, GetClientCarId # Cars and insurance Endpoint api.add_resource(NewInsurance, '/api/insurance/new') # Create new insurance api.add_resource(NewCar, '/api/car/new') # Create new car # All Car that belong to the current client api.add_resource(GetUserCar, '/api/client/cars') # Car by id that belong current Client api.add_resource(GetClientCarId, '/api/client/cars/<id>') from api.v1.views import ReportNew, Reportid, ReportPdf, Media, AllMedia,MatcherA,MatcherB # Rapport Creation and Handling # Create new Repport or Get All current Client Repport api.add_resource(ReportNew, '/api/client/report') # Get repport bellong to current client api.add_resource(Reportid, '/api/client/report/<id>') # Create a pdf file from reports api.add_resource(ReportPdf, '/api/client/report/pdf/<a>') # Get File image api.add_resource(Media, "/api/client/report/media/<path:path>") api.add_resource(AllMedia, "/api/client/report/media") # List all file media api.add_resource(MatcherA,'/api/reportA') api.add_resource(MatcherB,'/api/reportB') from api.v1.views import FetchCar,Dashboard,GetBReport,AllClientCar api.add_resource(Dashboard,"/api/company/data") api.add_resource(GetBReport,"/api/company/<id>") api.add_resource(FetchCar,'/api/company/Car') api.add_resource(AllClientCar,"/api/company/client/car")
en
0.733972
Global File Config And Route api instance # swagger Init #path to your wkhtmltopdf installation. #app.config['JSONIFY_PRETTYPRINT_REGULAR'] = True #Token Time Auto Revoke # Enable Token Blocklist #Type of Token db table for the jwt token Blocklist # Callback function to check if a JWT exists in the database blocklist Check if Token in Database Bloclist or Revoked jwt_header: Header of the Request to check jwt_payload: Body of the Request to Check First thing to excute in first request to the server 404 Error --- responses: 404: description: a resource was not found # Public Route for now getting comapny and creating new one # Authentication # signup # Login # Logout # Token refrecher # Get Current Logged Client or update user information # Company Action Web # Get All Client that Belong to this Comapny # Get Client that belong to this comapny by id # Get All Report that bellong to current Company # Cars and insurance Endpoint # Create new insurance # Create new car # All Car that belong to the current client # Car by id that belong current Client # Rapport Creation and Handling # Create new Repport or Get All current Client Repport # Get repport bellong to current client # Create a pdf file from reports # Get File image # List all file media
2.015714
2
validations/argsparser.py
binary-hideout/p-dispersion-problem
1
6632196
''' Validations for inputs from the command-line argument parsers. ''' from argparse import ArgumentTypeError from typing import Tuple from .numerical import is_float, is_int def is_valid_n(string: str) -> int: ''' If the string parameter represents a valid value for 'n' returns its value, otherwise raises ArgumentTypeError exception. ''' if is_int(string): number = int(string) if number > 2: return number msg = f'must be greater than 2' else: msg = f'invalid int value: {repr(string)}' raise ArgumentTypeError(msg) def is_percentage(string: str) -> float: ''' If the string parameter represents a valid decimal percentage returns its value, otherwise raises ArgumentTypeError exception. ''' if is_float(string): number = float(string) if 0 <= number <= 1: return number msg = f'invalid decimal percentage: {number}' else: msg = f'invalid float value: {repr(string)}' raise ArgumentTypeError(msg) def is_positive_int(string: str) -> int: ''' If the string parameter represents a positive integer (> 0) returns its value, otherwise raises ArgumentTypeError exception. ''' if is_int(string): number = int(string) if number > 0: return number msg = f'invalid positive int value (> 0): {number}' else: msg = f'invalid int value: {repr(string)}' raise ArgumentTypeError(msg) def is_time(string: str) -> float: if is_float(string): number = float(string) if number >= 0: return number msg = f'invalid positive float value: {number}' else: msg = f'invalid float value: {repr(string)}' raise ArgumentTypeError(msg) def are_valid_dimensions(n: int, dimensions: Tuple[int, int]) -> bool: ''' x*y must be greater or equal to n. ''' x, y = dimensions # if there is enough space in dimensions for all n points if n <= x * y: return True return False def is_valid_p(p: int) -> bool: if p >= 2: return True return False
''' Validations for inputs from the command-line argument parsers. ''' from argparse import ArgumentTypeError from typing import Tuple from .numerical import is_float, is_int def is_valid_n(string: str) -> int: ''' If the string parameter represents a valid value for 'n' returns its value, otherwise raises ArgumentTypeError exception. ''' if is_int(string): number = int(string) if number > 2: return number msg = f'must be greater than 2' else: msg = f'invalid int value: {repr(string)}' raise ArgumentTypeError(msg) def is_percentage(string: str) -> float: ''' If the string parameter represents a valid decimal percentage returns its value, otherwise raises ArgumentTypeError exception. ''' if is_float(string): number = float(string) if 0 <= number <= 1: return number msg = f'invalid decimal percentage: {number}' else: msg = f'invalid float value: {repr(string)}' raise ArgumentTypeError(msg) def is_positive_int(string: str) -> int: ''' If the string parameter represents a positive integer (> 0) returns its value, otherwise raises ArgumentTypeError exception. ''' if is_int(string): number = int(string) if number > 0: return number msg = f'invalid positive int value (> 0): {number}' else: msg = f'invalid int value: {repr(string)}' raise ArgumentTypeError(msg) def is_time(string: str) -> float: if is_float(string): number = float(string) if number >= 0: return number msg = f'invalid positive float value: {number}' else: msg = f'invalid float value: {repr(string)}' raise ArgumentTypeError(msg) def are_valid_dimensions(n: int, dimensions: Tuple[int, int]) -> bool: ''' x*y must be greater or equal to n. ''' x, y = dimensions # if there is enough space in dimensions for all n points if n <= x * y: return True return False def is_valid_p(p: int) -> bool: if p >= 2: return True return False
en
0.269757
Validations for inputs from the command-line argument parsers. If the string parameter represents a valid value for 'n' returns its value, otherwise raises ArgumentTypeError exception. If the string parameter represents a valid decimal percentage returns its value, otherwise raises ArgumentTypeError exception. If the string parameter represents a positive integer (> 0) returns its value, otherwise raises ArgumentTypeError exception. x*y must be greater or equal to n. # if there is enough space in dimensions for all n points
4.097856
4
client/over-the-rainbow/over-the-rainbow-client.py
GamesCreatorsClub/GCC-Rover
3
6632197
<filename>client/over-the-rainbow/over-the-rainbow-client.py # # Copyright 2016-2017 Games Creators Club # # MIT License # import sys import time import pygame import pyros import pyros.gcc import pyros.gccui import pyros.agent import pyros.pygamehelper from PIL import Image MAX_PING_TIMEOUT = 1 MAX_PICTURES = 400 pingLastTime = 0 screen_size = (1024, 800) screen = pyros.gccui.initAll(screen_size, True) cameraImage = Image.new("L", [80, 64]) rawImage = pygame.Surface((80, 64), 24) rawImageBig = pygame.Surface((320, 256), 24) arrow_image = pygame.image.load("arrow.png") arrow_image = pygame.transform.scale(arrow_image, (50, 50)) completeRawImage = None lastImage = None processedImages = [] processedBigImages = [] forwardSpeed = 5 running = False lights = False resubscribe = time.time() lastReceivedTime = time.time() frameTime = "" receivedFrameTime = "" feedback = { "angle": "", "turnDistance": "", "action": "", "left": "", "right": "" } imgNo = 0 ptr = -1 size = (320, 256) record = False sequence = False continuous = False localFPS = 0 lastProcessed = time.time() renewContinuous = time.time() distanceDeg1 = -1 distanceDeg2 = -1 distance1 = -1 distance2 = -1 avgDistance1 = -1 avgDistance2 = -1 gyroAngle = 0 def connected(): print("Starting agent... ", end="") pyros.agent.init(pyros.client, "over-the-rainbow-agent.py") print("Done.") pyros.publish("camera/processed/fetch", "") pyros.publish("camera/format", "RGB " + str(size[0]) + "," + str(size[1]) + " False") def toPILImage(imageBytes): pilImage = Image.frombytes("RGB", size, imageBytes) return pilImage def toPyImage(pilImage): pyImage = pygame.image.fromstring(pilImage.tobytes("raw"), size, "RGB") return pyImage def handleDistances(topic, message, groups): global distanceDeg1, distanceDeg2, distance1, distance2, avgDistance1, avgDistance2 c = 0 split1 = message.split(",") for s1 in split1: split2 = s1.split(":") if len(split2) == 2: deg = int(split2[0]) split3 = split2[1].split(";") if len(split3) == 2: dis = float(split3[0]) avg = float(split3[1]) if c == 0: distanceDeg1 = deg distance1 = dis avgDistance1 = avg elif c == 1: distanceDeg2 = deg distance2 = dis avgDistance2 = avg c += 1 def handleGyro(topic, message, groups): global gyroAngle gyroAngle = float(message) def handleImageDetails(topic, message, groups): global rawImage, rawImageBig, completeRawImage results = [] for line in message.split("\n"): split = line.split(",") if len(split) == 3: result = int(split[0]), int(split[1]), split[2].lower(), 10 results.append(result) elif len(split) >= 4: result = int(split[0]), int(split[1]), split[2].lower(), int(split[3]) results.append(result) print("Got details " + str(results) + " from: \n" + message) for result in results: if "red" == result[2]: drawTarget(completeRawImage, result, pyros.gccui.RED, "red", result[3]) if "green" == result[2]: drawTarget(completeRawImage, result, pyros.gccui.GREEN, "green", result[3]) if "yellow" == result[2]: drawTarget(completeRawImage, result, pyros.gccui.YELLOW, "yellow", result[3]) if "blue" == result[2]: drawTarget(completeRawImage, result, pyros.gccui.BLUE, "blue", result[3]) if completeRawImage is not None: rawImage = pygame.transform.scale(completeRawImage, (80, 64)) rawImageBig = pygame.transform.scale(completeRawImage, (320, 256)) if record: processedImages.append(rawImage) processedBigImages.append(rawImageBig) def handleCameraRaw(topic, message, groups): global rawImage, rawImageBig, lastProcessed, localFPS, completeRawImage handleCameraProcessed(topic, message, groups) completeRawImage = lastImage def handleCameraProcessed(topic, message, groups): global rawImage, rawImageBig, lastProcessed, localFPS, lastImage n = time.time() delta = n - lastProcessed lastProcessed = n if delta < 5: localFPS = "%.2f" % round(1 / delta, 2) else: localFPS = "-" pilImage = toPILImage(message) processedPilImage = processImage(pilImage) image = toPyImage(processedPilImage) lastImage = image # if "red" in result: # drawTarget(image, result["red"], pyros.gccui.RED, "red") # if "green" in result: # drawTarget(image, result["green"], pyros.gccui.GREEN, "green") # if "yellow" in result: # drawTarget(image, result["yellow"], pyros.gccui.YELLOW, "yellow") # if "blue" in result: # drawTarget(image, result["blue"], pyros.gccui.BLUE, "blue") # rawImage = pygame.transform.scale(lastImage, (80, 64)) rawImageBig = pygame.transform.scale(lastImage, (320, 256)) if record: processedImages.append(rawImage) processedBigImages.append(rawImageBig) # # if sequence and not continuous: # pyros.publish("camera/raw/fetch", "") def processImage(image): red_pixels = [] green_pixels = [] blue_pixels = [] yellow_pixels = [] for y in range(0, 256): for x in range(0, 320): p = image.getpixel((x, y)) if isRed(p): red_pixels.append((x, y)) if isGreen(p): green_pixels.append((x, y)) if isBlue(p): blue_pixels.append((x, y)) if isYellow(p): yellow_pixels.append((x, y)) result = {} if len(red_pixels) > 20: centre = calculateCentre(red_pixels) result["red"] = centre drawSpot(image, centre[0], centre[1], (255, 64, 64), "red") if len(green_pixels) > 20: centre = calculateCentre(green_pixels) result["green"] = centre drawSpot(image, centre[0], centre[1], (64, 255, 64), "green") if len(blue_pixels) > 20: centre = calculateCentre(blue_pixels) result["blue"] = centre drawSpot(image, centre[0], centre[1], (64, 64, 255), "blue") if len(yellow_pixels) > 20: centre = calculateCentre(yellow_pixels) result["yellow"] = centre drawSpot(image, centre[0], centre[1], (255, 255, 64), "yellow") processedImage = image return processedImage def isRed(p): return p[0] > 64 and distance(p[0], p[1]) > 1.2 and distance(p[0], p[1]) > 1.2 and 0.8 < distance(p[1], p[2]) < 1.2 def isGreen(p): return p[1] > 64 and distance(p[1], p[0]) > 1.2 and distance(p[1], p[2]) > 1.2 and 0.8 < distance(p[0], p[2]) < 1.2 def isBlue(p): return p[2] > 64 and distance(p[2], p[0]) > 1.2 and distance(p[2], p[1]) > 1.2 and 0.8 < distance(p[0], p[1]) < 1.2 def isYellow(p): return p[0] > 64 and p[1] > 128 and 0.8 < distance(p[0], p[1]) < 1.2 and distance(p[0], p[2]) > 1.2 and distance(p[1], p[2]) > 1.2 def distance(x, y): if y != 0: return x / y else: return x / 256 def calculateCentre(pixels): cx = 0 cy = 0 for p in pixels: cx = cx + p[0] cy = cy + p[1] cx = int(cx / len(pixels)) cy = int(cy / len(pixels)) return cx, cy def drawTarget(image, centre, colour, text, radius=20): if radius < 16: radius = 16 x = centre[0] - radius / 4 if x < 0: x = 0 y = centre[1] - radius / 4 if y < 0: y = 0 w = radius - 1 h = radius - 1 tl = 13 tl1 = 12 # pygame.draw.rect(image, pyros.gccui.WHITE, pygame.Rect(x + 2, y + 2, w - 2, h - 2), 1) pygame.draw.line(image, pyros.gccui.WHITE, (x, y), (x + tl, y)) pygame.draw.line(image, pyros.gccui.WHITE, (x, y), (x, y + tl)) pygame.draw.line(image, colour, (x + 1, y + 1), (x + 1, y + tl1)) pygame.draw.line(image, colour, (x + 1, y + 1), (x + tl1, y + 1)) pygame.draw.line(image, pyros.gccui.WHITE, (x, y + h), (x + tl, y + h)) pygame.draw.line(image, pyros.gccui.WHITE, (x, y + h), (x, y + h - tl)) pygame.draw.line(image, colour, (x + 1, y + h - 1), (x + 1, y + h - tl1)) pygame.draw.line(image, colour, (x + 1, y + h - 1), (x + tl1, y + h - 1)) pygame.draw.line(image, pyros.gccui.WHITE, (x + w, y), (x + w - tl, y)) pygame.draw.line(image, pyros.gccui.WHITE, (x + w, y), (x + w, y + tl)) pygame.draw.line(image, colour, (x + w - 1, y + 1), (x + w - 1, y + tl1)) pygame.draw.line(image, colour, (x + w - 1, y + 1), (x + w - tl1, y + 1)) pygame.draw.line(image, pyros.gccui.WHITE, (x + w, y + h), (x + w - tl, y + h)) pygame.draw.line(image, pyros.gccui.WHITE, (x + w, y + h), (x + w, y + h - tl)) pygame.draw.line(image, colour, (x + w - 1, y + h - 1), (x + w - 1, y + h - tl1)) pygame.draw.line(image, colour, (x + w - 1, y + h - 1), (x + w - tl1, y + h - 1)) tdist = 30 left = False if x > tdist: tx = x - tdist lx = x - 2 left = True elif x + w < image.get_width() - tdist: tx = x + w + tdist lx = x + w + 2 else: tx = centre[0] lx = centre[0] if y > tdist: ty = y - tdist ly = y - 2 elif y + h < image.get_height() - tdist: ty = y + h + tdist ly = y + h + 2 else: ty = centre[0] ly = centre[0] pyros.gccui.font.set_bold(True) tw = pyros.gccui.font.size(text)[1] pygame.draw.line(image, pyros.gccui.WHITE, (lx, ly), (tx, ty)) if left: pygame.draw.line(image, pyros.gccui.WHITE, (tx - tw - 5, ty), (tx, ty)) image.blit(pyros.gccui.font.render(text, 1, colour), (tx - tw, ty - 25)) else: pygame.draw.line(image, pyros.gccui.WHITE, (tx + tw + 5, ty), (tx, ty)) image.blit(pyros.gccui.font.render(text, 1, colour), (tx, ty - 25)) pyros.gccui.font.set_bold(False) def drawSpot(image, cx, cy, colour, text): if False: for x in range(cx - 30, cx + 30): if x >= 0 and x < 320: if cy > 0: image.putpixel((x, cy - 1), (255, 255, 255)) image.putpixel((x, cy), colour) if cy < 256 - 1: image.putpixel((x, cy + 1), (255, 255, 255)) for y in range(cy - 30, cy + 30): if y >= 0 and y < 256: if cx > 0: image.putpixel((cx - 1, y), (255, 255, 255)) image.putpixel((cx, y), colour) if cx < 320 - 1: image.putpixel((cx + 1, y), (255, 255, 255)) def toggleStart(): global imgNo, processedImages, processedBigImages, running pass def stop(): global running pyros.publish("camera/lift", "stop") pyros.publish("move/stop", "") pyros.publish("overtherainbow/command", "stop") running = False def clear(): global imgNo, processedImages, processedBigImages imgNo = 0 del processedImages[:] del processedBigImages[:] def onKeyDown(key): global lights, forwardSpeed, running, ptr, imgNo global sequence, record, continuous global processedImages, processedBigImages global gyroAngle if pyros.gcc.handleConnectKeyDown(key): pass elif key == pygame.K_f: print(" fetching picture...") pyros.publish("camera/raw/fetch", "") elif key == pygame.K_s: sequence = not sequence elif key == pygame.K_r: record = not record elif key == pygame.K_c: continuous = not continuous if continuous: print(" fetching continuous pictures...") pyros.publish("camera/continuous", "") else: print(" stopping continuous pictures...") pyros.publish("camera/continuous", "stop") elif key == pygame.K_x: clear() elif key == pygame.K_RETURN: toggleStart() elif key == pygame.K_SPACE: stop() elif key == pygame.K_1: pyros.publish("overtherainbow/command", "alg1") elif key == pygame.K_2: pyros.publish("overtherainbow/command", "alg2") elif key == pygame.K_3: pyros.publish("overtherainbow/command", "alg3") elif key == pygame.K_4: pyros.publish("overtherainbow/command", "alg4") elif key == pygame.K_5: pyros.publish("overtherainbow/command", "alg5") elif key == pygame.K_6: pyros.publish("overtherainbow/command", "alg6") elif key == pygame.K_7: pyros.publish("overtherainbow/command", "alg7") elif key == pygame.K_8: pyros.publish("overtherainbow/command", "alg8") elif key == pygame.K_9: pyros.publish("overtherainbow/command", "alg9") elif key == pygame.K_0: pyros.publish("overtherainbow/command", "alg10") elif key == pygame.K_g: pyros.publish("sensor/gyro/continuous", "calibrate,50") gyroAngle = 0 elif key == pygame.K_u: pyros.publish("camera/lift", "up") elif key == pygame.K_d: pyros.publish("camera/lift", "down") elif key == pygame.K_SLASH: pyros.publish("camera/lift", "reset") elif key == pygame.K_LEFT: if ptr == -1: ptr = len(processedImages) - 2 else: ptr -= 1 elif key == pygame.K_RIGHT: ptr += 1 if ptr >= len(processedImages) - 1: ptr = -1 def onKeyUp(key): pyros.gcc.handleConnectKeyUp(key) return def swap(array): v = array[0] array[0] = array[1] array[1] = v pyros.subscribeBinary("camera/raw", handleCameraRaw) pyros.subscribe("overtherainbow/distances", handleDistances) pyros.subscribe("overtherainbow/gyro", handleGyro) pyros.subscribe("overtherainbow/imagedetails", handleImageDetails) pyros.subscribeBinary("overtherainbow/processed", handleCameraProcessed) pyros.init("over-the-rainbow-#", unique=True, onConnected=connected, host=pyros.gcc.getHost(), port=pyros.gcc.getPort(), waitToConnect=False) while True: for event in pygame.event.get(): if event.type == pygame.QUIT: pygame.quit() sys.exit() if event.type == pygame.VIDEORESIZE: pyros.gccui.screenResized(event.size) pyros.pygamehelper.processKeys(onKeyDown, onKeyUp) pyros.loop(0.03) pyros.agent.keepAgents() pyros.gccui.background(True) avgDistance1String = str(format(avgDistance1, '.2f')) avgDistance2String = str(format(avgDistance2, '.2f')) # noinspection PyRedeclaration hpos = 40 hpos = pyros.gccui.drawKeyValue("Local FPS", str(localFPS), 8, hpos) hpos = pyros.gccui.drawKeyValue("Recording", str(record), 8, hpos) hpos = pyros.gccui.drawKeyValue("Sequence", str(sequence), 8, hpos) hpos = pyros.gccui.drawKeyValue("Continuous", str(continuous), 8, hpos) hpos = pyros.gccui.drawKeyValue("Selected", str(ptr) + " of " + str(len(processedImages)), 8, hpos) hpos = pyros.gccui.drawKeyValue("Running", str(running), 8, hpos) hpos = pyros.gccui.drawKeyValue("Turn dist", str(feedback["turnDistance"]), 8, hpos) hpos = pyros.gccui.drawKeyValue("Dist @ " + str(distanceDeg1), str(distance1) + ", avg: " + avgDistance1String, 8, hpos) hpos = pyros.gccui.drawKeyValue("Dist @ " + str(distanceDeg2), str(distance2) + ", avg: " + avgDistance2String, 8, hpos) hpos = pyros.gccui.drawKeyValue("Gyro", str(round(gyroAngle, 2)), 8, hpos) # if len(historyDistances[0]): # mn = min(historyDistances[0]) # mx = max(historyDistances[0]) # pyros.gccui.drawGraph((200, 50), (81, 65), historyDistances[0], mn, mx, 80, stick = 10) # # if len(historyDistances[1]): # mn = min(historyDistances[1]) # mx = max(historyDistances[1]) # pyros.gccui.drawGraph((320, 50), (81, 65), historyDistances[1], mn, mx, 80, stick = 10) loc = arrow_image.get_rect().center rot_arrow_image = pygame.transform.rotate(arrow_image, -gyroAngle) rot_arrow_image.get_rect().center = loc screen.blit(rot_arrow_image, (530, 200)) # if len(rotSpeeds) > 0: # gyroDegPersSecText = str(round(sum(rotSpeeds) / len(rotSpeeds), 2)) # pyros.gccui.drawBigText(gyroDegPersSecText, (440, 10)) # # pyros.gccui.drawText("º/s", (445 + pyros.gccui.bigFont.size(gyroDegPersSecText)[0], 15)) # # pyros.gccui.drawBigText(str(int(thisGyroAngle)), (440, 40)) pyros.gccui.drawSmallText("r-toggle record, f - fetch, s-sequence, LEFT/RIGHT-scroll, SPACE-stop, RETURN-start, l-lights, d-distances, x- clear, camera: u-up, d-down, /-reset", (8, screen.get_height() - pyros.gccui.smallFont.get_height())) pyros.gccui.drawImage(rawImage, (500, 50), 10) pyros.gccui.drawImage(rawImageBig, (688, 50), 10) if ptr >= 0: if ptr > len(processedImages) - 1: ptr = len(processedImages) - 1 i = ptr else: i = len(processedImages) - 1 imgX = 1024 - 320 - 16 while i >= 0 and imgX >= 0: pyros.gccui.drawImage(processedBigImages[i], (imgX, 420)) imgX -= 336 i -= 1 pyros.gcc.drawConnection() pyros.gccui.frameEnd() now = time.time()
<filename>client/over-the-rainbow/over-the-rainbow-client.py # # Copyright 2016-2017 Games Creators Club # # MIT License # import sys import time import pygame import pyros import pyros.gcc import pyros.gccui import pyros.agent import pyros.pygamehelper from PIL import Image MAX_PING_TIMEOUT = 1 MAX_PICTURES = 400 pingLastTime = 0 screen_size = (1024, 800) screen = pyros.gccui.initAll(screen_size, True) cameraImage = Image.new("L", [80, 64]) rawImage = pygame.Surface((80, 64), 24) rawImageBig = pygame.Surface((320, 256), 24) arrow_image = pygame.image.load("arrow.png") arrow_image = pygame.transform.scale(arrow_image, (50, 50)) completeRawImage = None lastImage = None processedImages = [] processedBigImages = [] forwardSpeed = 5 running = False lights = False resubscribe = time.time() lastReceivedTime = time.time() frameTime = "" receivedFrameTime = "" feedback = { "angle": "", "turnDistance": "", "action": "", "left": "", "right": "" } imgNo = 0 ptr = -1 size = (320, 256) record = False sequence = False continuous = False localFPS = 0 lastProcessed = time.time() renewContinuous = time.time() distanceDeg1 = -1 distanceDeg2 = -1 distance1 = -1 distance2 = -1 avgDistance1 = -1 avgDistance2 = -1 gyroAngle = 0 def connected(): print("Starting agent... ", end="") pyros.agent.init(pyros.client, "over-the-rainbow-agent.py") print("Done.") pyros.publish("camera/processed/fetch", "") pyros.publish("camera/format", "RGB " + str(size[0]) + "," + str(size[1]) + " False") def toPILImage(imageBytes): pilImage = Image.frombytes("RGB", size, imageBytes) return pilImage def toPyImage(pilImage): pyImage = pygame.image.fromstring(pilImage.tobytes("raw"), size, "RGB") return pyImage def handleDistances(topic, message, groups): global distanceDeg1, distanceDeg2, distance1, distance2, avgDistance1, avgDistance2 c = 0 split1 = message.split(",") for s1 in split1: split2 = s1.split(":") if len(split2) == 2: deg = int(split2[0]) split3 = split2[1].split(";") if len(split3) == 2: dis = float(split3[0]) avg = float(split3[1]) if c == 0: distanceDeg1 = deg distance1 = dis avgDistance1 = avg elif c == 1: distanceDeg2 = deg distance2 = dis avgDistance2 = avg c += 1 def handleGyro(topic, message, groups): global gyroAngle gyroAngle = float(message) def handleImageDetails(topic, message, groups): global rawImage, rawImageBig, completeRawImage results = [] for line in message.split("\n"): split = line.split(",") if len(split) == 3: result = int(split[0]), int(split[1]), split[2].lower(), 10 results.append(result) elif len(split) >= 4: result = int(split[0]), int(split[1]), split[2].lower(), int(split[3]) results.append(result) print("Got details " + str(results) + " from: \n" + message) for result in results: if "red" == result[2]: drawTarget(completeRawImage, result, pyros.gccui.RED, "red", result[3]) if "green" == result[2]: drawTarget(completeRawImage, result, pyros.gccui.GREEN, "green", result[3]) if "yellow" == result[2]: drawTarget(completeRawImage, result, pyros.gccui.YELLOW, "yellow", result[3]) if "blue" == result[2]: drawTarget(completeRawImage, result, pyros.gccui.BLUE, "blue", result[3]) if completeRawImage is not None: rawImage = pygame.transform.scale(completeRawImage, (80, 64)) rawImageBig = pygame.transform.scale(completeRawImage, (320, 256)) if record: processedImages.append(rawImage) processedBigImages.append(rawImageBig) def handleCameraRaw(topic, message, groups): global rawImage, rawImageBig, lastProcessed, localFPS, completeRawImage handleCameraProcessed(topic, message, groups) completeRawImage = lastImage def handleCameraProcessed(topic, message, groups): global rawImage, rawImageBig, lastProcessed, localFPS, lastImage n = time.time() delta = n - lastProcessed lastProcessed = n if delta < 5: localFPS = "%.2f" % round(1 / delta, 2) else: localFPS = "-" pilImage = toPILImage(message) processedPilImage = processImage(pilImage) image = toPyImage(processedPilImage) lastImage = image # if "red" in result: # drawTarget(image, result["red"], pyros.gccui.RED, "red") # if "green" in result: # drawTarget(image, result["green"], pyros.gccui.GREEN, "green") # if "yellow" in result: # drawTarget(image, result["yellow"], pyros.gccui.YELLOW, "yellow") # if "blue" in result: # drawTarget(image, result["blue"], pyros.gccui.BLUE, "blue") # rawImage = pygame.transform.scale(lastImage, (80, 64)) rawImageBig = pygame.transform.scale(lastImage, (320, 256)) if record: processedImages.append(rawImage) processedBigImages.append(rawImageBig) # # if sequence and not continuous: # pyros.publish("camera/raw/fetch", "") def processImage(image): red_pixels = [] green_pixels = [] blue_pixels = [] yellow_pixels = [] for y in range(0, 256): for x in range(0, 320): p = image.getpixel((x, y)) if isRed(p): red_pixels.append((x, y)) if isGreen(p): green_pixels.append((x, y)) if isBlue(p): blue_pixels.append((x, y)) if isYellow(p): yellow_pixels.append((x, y)) result = {} if len(red_pixels) > 20: centre = calculateCentre(red_pixels) result["red"] = centre drawSpot(image, centre[0], centre[1], (255, 64, 64), "red") if len(green_pixels) > 20: centre = calculateCentre(green_pixels) result["green"] = centre drawSpot(image, centre[0], centre[1], (64, 255, 64), "green") if len(blue_pixels) > 20: centre = calculateCentre(blue_pixels) result["blue"] = centre drawSpot(image, centre[0], centre[1], (64, 64, 255), "blue") if len(yellow_pixels) > 20: centre = calculateCentre(yellow_pixels) result["yellow"] = centre drawSpot(image, centre[0], centre[1], (255, 255, 64), "yellow") processedImage = image return processedImage def isRed(p): return p[0] > 64 and distance(p[0], p[1]) > 1.2 and distance(p[0], p[1]) > 1.2 and 0.8 < distance(p[1], p[2]) < 1.2 def isGreen(p): return p[1] > 64 and distance(p[1], p[0]) > 1.2 and distance(p[1], p[2]) > 1.2 and 0.8 < distance(p[0], p[2]) < 1.2 def isBlue(p): return p[2] > 64 and distance(p[2], p[0]) > 1.2 and distance(p[2], p[1]) > 1.2 and 0.8 < distance(p[0], p[1]) < 1.2 def isYellow(p): return p[0] > 64 and p[1] > 128 and 0.8 < distance(p[0], p[1]) < 1.2 and distance(p[0], p[2]) > 1.2 and distance(p[1], p[2]) > 1.2 def distance(x, y): if y != 0: return x / y else: return x / 256 def calculateCentre(pixels): cx = 0 cy = 0 for p in pixels: cx = cx + p[0] cy = cy + p[1] cx = int(cx / len(pixels)) cy = int(cy / len(pixels)) return cx, cy def drawTarget(image, centre, colour, text, radius=20): if radius < 16: radius = 16 x = centre[0] - radius / 4 if x < 0: x = 0 y = centre[1] - radius / 4 if y < 0: y = 0 w = radius - 1 h = radius - 1 tl = 13 tl1 = 12 # pygame.draw.rect(image, pyros.gccui.WHITE, pygame.Rect(x + 2, y + 2, w - 2, h - 2), 1) pygame.draw.line(image, pyros.gccui.WHITE, (x, y), (x + tl, y)) pygame.draw.line(image, pyros.gccui.WHITE, (x, y), (x, y + tl)) pygame.draw.line(image, colour, (x + 1, y + 1), (x + 1, y + tl1)) pygame.draw.line(image, colour, (x + 1, y + 1), (x + tl1, y + 1)) pygame.draw.line(image, pyros.gccui.WHITE, (x, y + h), (x + tl, y + h)) pygame.draw.line(image, pyros.gccui.WHITE, (x, y + h), (x, y + h - tl)) pygame.draw.line(image, colour, (x + 1, y + h - 1), (x + 1, y + h - tl1)) pygame.draw.line(image, colour, (x + 1, y + h - 1), (x + tl1, y + h - 1)) pygame.draw.line(image, pyros.gccui.WHITE, (x + w, y), (x + w - tl, y)) pygame.draw.line(image, pyros.gccui.WHITE, (x + w, y), (x + w, y + tl)) pygame.draw.line(image, colour, (x + w - 1, y + 1), (x + w - 1, y + tl1)) pygame.draw.line(image, colour, (x + w - 1, y + 1), (x + w - tl1, y + 1)) pygame.draw.line(image, pyros.gccui.WHITE, (x + w, y + h), (x + w - tl, y + h)) pygame.draw.line(image, pyros.gccui.WHITE, (x + w, y + h), (x + w, y + h - tl)) pygame.draw.line(image, colour, (x + w - 1, y + h - 1), (x + w - 1, y + h - tl1)) pygame.draw.line(image, colour, (x + w - 1, y + h - 1), (x + w - tl1, y + h - 1)) tdist = 30 left = False if x > tdist: tx = x - tdist lx = x - 2 left = True elif x + w < image.get_width() - tdist: tx = x + w + tdist lx = x + w + 2 else: tx = centre[0] lx = centre[0] if y > tdist: ty = y - tdist ly = y - 2 elif y + h < image.get_height() - tdist: ty = y + h + tdist ly = y + h + 2 else: ty = centre[0] ly = centre[0] pyros.gccui.font.set_bold(True) tw = pyros.gccui.font.size(text)[1] pygame.draw.line(image, pyros.gccui.WHITE, (lx, ly), (tx, ty)) if left: pygame.draw.line(image, pyros.gccui.WHITE, (tx - tw - 5, ty), (tx, ty)) image.blit(pyros.gccui.font.render(text, 1, colour), (tx - tw, ty - 25)) else: pygame.draw.line(image, pyros.gccui.WHITE, (tx + tw + 5, ty), (tx, ty)) image.blit(pyros.gccui.font.render(text, 1, colour), (tx, ty - 25)) pyros.gccui.font.set_bold(False) def drawSpot(image, cx, cy, colour, text): if False: for x in range(cx - 30, cx + 30): if x >= 0 and x < 320: if cy > 0: image.putpixel((x, cy - 1), (255, 255, 255)) image.putpixel((x, cy), colour) if cy < 256 - 1: image.putpixel((x, cy + 1), (255, 255, 255)) for y in range(cy - 30, cy + 30): if y >= 0 and y < 256: if cx > 0: image.putpixel((cx - 1, y), (255, 255, 255)) image.putpixel((cx, y), colour) if cx < 320 - 1: image.putpixel((cx + 1, y), (255, 255, 255)) def toggleStart(): global imgNo, processedImages, processedBigImages, running pass def stop(): global running pyros.publish("camera/lift", "stop") pyros.publish("move/stop", "") pyros.publish("overtherainbow/command", "stop") running = False def clear(): global imgNo, processedImages, processedBigImages imgNo = 0 del processedImages[:] del processedBigImages[:] def onKeyDown(key): global lights, forwardSpeed, running, ptr, imgNo global sequence, record, continuous global processedImages, processedBigImages global gyroAngle if pyros.gcc.handleConnectKeyDown(key): pass elif key == pygame.K_f: print(" fetching picture...") pyros.publish("camera/raw/fetch", "") elif key == pygame.K_s: sequence = not sequence elif key == pygame.K_r: record = not record elif key == pygame.K_c: continuous = not continuous if continuous: print(" fetching continuous pictures...") pyros.publish("camera/continuous", "") else: print(" stopping continuous pictures...") pyros.publish("camera/continuous", "stop") elif key == pygame.K_x: clear() elif key == pygame.K_RETURN: toggleStart() elif key == pygame.K_SPACE: stop() elif key == pygame.K_1: pyros.publish("overtherainbow/command", "alg1") elif key == pygame.K_2: pyros.publish("overtherainbow/command", "alg2") elif key == pygame.K_3: pyros.publish("overtherainbow/command", "alg3") elif key == pygame.K_4: pyros.publish("overtherainbow/command", "alg4") elif key == pygame.K_5: pyros.publish("overtherainbow/command", "alg5") elif key == pygame.K_6: pyros.publish("overtherainbow/command", "alg6") elif key == pygame.K_7: pyros.publish("overtherainbow/command", "alg7") elif key == pygame.K_8: pyros.publish("overtherainbow/command", "alg8") elif key == pygame.K_9: pyros.publish("overtherainbow/command", "alg9") elif key == pygame.K_0: pyros.publish("overtherainbow/command", "alg10") elif key == pygame.K_g: pyros.publish("sensor/gyro/continuous", "calibrate,50") gyroAngle = 0 elif key == pygame.K_u: pyros.publish("camera/lift", "up") elif key == pygame.K_d: pyros.publish("camera/lift", "down") elif key == pygame.K_SLASH: pyros.publish("camera/lift", "reset") elif key == pygame.K_LEFT: if ptr == -1: ptr = len(processedImages) - 2 else: ptr -= 1 elif key == pygame.K_RIGHT: ptr += 1 if ptr >= len(processedImages) - 1: ptr = -1 def onKeyUp(key): pyros.gcc.handleConnectKeyUp(key) return def swap(array): v = array[0] array[0] = array[1] array[1] = v pyros.subscribeBinary("camera/raw", handleCameraRaw) pyros.subscribe("overtherainbow/distances", handleDistances) pyros.subscribe("overtherainbow/gyro", handleGyro) pyros.subscribe("overtherainbow/imagedetails", handleImageDetails) pyros.subscribeBinary("overtherainbow/processed", handleCameraProcessed) pyros.init("over-the-rainbow-#", unique=True, onConnected=connected, host=pyros.gcc.getHost(), port=pyros.gcc.getPort(), waitToConnect=False) while True: for event in pygame.event.get(): if event.type == pygame.QUIT: pygame.quit() sys.exit() if event.type == pygame.VIDEORESIZE: pyros.gccui.screenResized(event.size) pyros.pygamehelper.processKeys(onKeyDown, onKeyUp) pyros.loop(0.03) pyros.agent.keepAgents() pyros.gccui.background(True) avgDistance1String = str(format(avgDistance1, '.2f')) avgDistance2String = str(format(avgDistance2, '.2f')) # noinspection PyRedeclaration hpos = 40 hpos = pyros.gccui.drawKeyValue("Local FPS", str(localFPS), 8, hpos) hpos = pyros.gccui.drawKeyValue("Recording", str(record), 8, hpos) hpos = pyros.gccui.drawKeyValue("Sequence", str(sequence), 8, hpos) hpos = pyros.gccui.drawKeyValue("Continuous", str(continuous), 8, hpos) hpos = pyros.gccui.drawKeyValue("Selected", str(ptr) + " of " + str(len(processedImages)), 8, hpos) hpos = pyros.gccui.drawKeyValue("Running", str(running), 8, hpos) hpos = pyros.gccui.drawKeyValue("Turn dist", str(feedback["turnDistance"]), 8, hpos) hpos = pyros.gccui.drawKeyValue("Dist @ " + str(distanceDeg1), str(distance1) + ", avg: " + avgDistance1String, 8, hpos) hpos = pyros.gccui.drawKeyValue("Dist @ " + str(distanceDeg2), str(distance2) + ", avg: " + avgDistance2String, 8, hpos) hpos = pyros.gccui.drawKeyValue("Gyro", str(round(gyroAngle, 2)), 8, hpos) # if len(historyDistances[0]): # mn = min(historyDistances[0]) # mx = max(historyDistances[0]) # pyros.gccui.drawGraph((200, 50), (81, 65), historyDistances[0], mn, mx, 80, stick = 10) # # if len(historyDistances[1]): # mn = min(historyDistances[1]) # mx = max(historyDistances[1]) # pyros.gccui.drawGraph((320, 50), (81, 65), historyDistances[1], mn, mx, 80, stick = 10) loc = arrow_image.get_rect().center rot_arrow_image = pygame.transform.rotate(arrow_image, -gyroAngle) rot_arrow_image.get_rect().center = loc screen.blit(rot_arrow_image, (530, 200)) # if len(rotSpeeds) > 0: # gyroDegPersSecText = str(round(sum(rotSpeeds) / len(rotSpeeds), 2)) # pyros.gccui.drawBigText(gyroDegPersSecText, (440, 10)) # # pyros.gccui.drawText("º/s", (445 + pyros.gccui.bigFont.size(gyroDegPersSecText)[0], 15)) # # pyros.gccui.drawBigText(str(int(thisGyroAngle)), (440, 40)) pyros.gccui.drawSmallText("r-toggle record, f - fetch, s-sequence, LEFT/RIGHT-scroll, SPACE-stop, RETURN-start, l-lights, d-distances, x- clear, camera: u-up, d-down, /-reset", (8, screen.get_height() - pyros.gccui.smallFont.get_height())) pyros.gccui.drawImage(rawImage, (500, 50), 10) pyros.gccui.drawImage(rawImageBig, (688, 50), 10) if ptr >= 0: if ptr > len(processedImages) - 1: ptr = len(processedImages) - 1 i = ptr else: i = len(processedImages) - 1 imgX = 1024 - 320 - 16 while i >= 0 and imgX >= 0: pyros.gccui.drawImage(processedBigImages[i], (imgX, 420)) imgX -= 336 i -= 1 pyros.gcc.drawConnection() pyros.gccui.frameEnd() now = time.time()
en
0.484584
# # Copyright 2016-2017 Games Creators Club # # MIT License # # if "red" in result: # drawTarget(image, result["red"], pyros.gccui.RED, "red") # if "green" in result: # drawTarget(image, result["green"], pyros.gccui.GREEN, "green") # if "yellow" in result: # drawTarget(image, result["yellow"], pyros.gccui.YELLOW, "yellow") # if "blue" in result: # drawTarget(image, result["blue"], pyros.gccui.BLUE, "blue") # # # if sequence and not continuous: # pyros.publish("camera/raw/fetch", "") # pygame.draw.rect(image, pyros.gccui.WHITE, pygame.Rect(x + 2, y + 2, w - 2, h - 2), 1) #", unique=True, onConnected=connected, host=pyros.gcc.getHost(), port=pyros.gcc.getPort(), waitToConnect=False) # noinspection PyRedeclaration # if len(historyDistances[0]): # mn = min(historyDistances[0]) # mx = max(historyDistances[0]) # pyros.gccui.drawGraph((200, 50), (81, 65), historyDistances[0], mn, mx, 80, stick = 10) # # if len(historyDistances[1]): # mn = min(historyDistances[1]) # mx = max(historyDistances[1]) # pyros.gccui.drawGraph((320, 50), (81, 65), historyDistances[1], mn, mx, 80, stick = 10) # if len(rotSpeeds) > 0: # gyroDegPersSecText = str(round(sum(rotSpeeds) / len(rotSpeeds), 2)) # pyros.gccui.drawBigText(gyroDegPersSecText, (440, 10)) # # pyros.gccui.drawText("º/s", (445 + pyros.gccui.bigFont.size(gyroDegPersSecText)[0], 15)) # # pyros.gccui.drawBigText(str(int(thisGyroAngle)), (440, 40))
2.421881
2
cpppm/conans.py
Garcia6l20/cpppm
3
6632198
import asyncio from pathlib import Path from conans import ConanFile as ConanConanFile from conans import tools from cpppm import Project, Library, root_project import nest_asyncio nest_asyncio.apply() class PackageInfos: def __init__(self, data): self.include_dirs = set() self.lib_dirs = set() self.libs = set() self.res_dirs = set() self.bin_dirs = set() self.build_dirs = set() self.defines = dict() self.name = data['name'] self.version = data['version'] self.root = Path(data['rootpath']) self.description = data['description'] if 'description' in data else None self.load(data) self.header_only = self.name not in data['libs'] def load(self, comp): if 'include_paths' in comp: self.include_dirs.update(comp['include_paths']) if 'lib_paths' in comp: self.lib_dirs.update(comp['lib_paths']) if 'libs' in comp: self.libs.update([lib for lib in comp['libs'] if lib != self.name]) if 'system_libs' in comp: self.libs.update(comp['system_libs']) if 'res_paths' in comp: self.res_dirs.update(comp['res_paths']) if 'bin_paths' in comp: self.bin_dirs.update(comp['bin_paths']) if 'build_paths' in comp: self.build_dirs.update(comp['build_paths']) if 'defines' in comp: for definition in comp['defines']: tmp = definition.split('=') self.defines[tmp[0]] = tmp[1] if len(tmp) > 1 else None @property def conan_ref(self): return f'{self.name}/{self.version}@' class PackageLibrary(Library): def __init__(self, infos, **kwargs): self._infos = PackageInfos(infos) super().__init__(self._infos.name, self._infos.root, self._infos.root, **kwargs) self.include_dirs = self._infos.include_dirs self.link_libraries = self._infos.libs self.compile_definitions = self._infos.defines self.library_dirs = {self._infos.root / p for p in self._infos.lib_dirs} def resolve_deps(self): # for dep in self._infos.deps: # self.link_libraries = Project._pkg_libraries[dep] pass @property def conan_ref(self): return self._infos.conan_ref @property def is_header_only(self): return self._infos.header_only async def build(self): return False class ConanFile(ConanConanFile): project: Project = root_project() name = project.package_name # url = project.url version = project.version license = project.license settings = {"os", "compiler", "build_type", "arch"} options = project.options requires = tuple(project.requires) build_requires = tuple(project.build_requires) default_options = project.default_options no_copy_source = False exports_sources = '*' def deploy(self): self.copy("*", dst="bin", src="bin") def configure(self): if self.settings.os == "Windows": del self.options.fPIC def build(self): print(self.source_folder) loop = asyncio.get_event_loop() ConanFile.project.install_requirements() loop.run_until_complete(ConanFile.project.build()) def package(self): loop = asyncio.get_event_loop() loop.run_until_complete(ConanFile.project.install(self.package_folder)) def package_info(self): self.cpp_info.libs = tools.collect_libs(self) self.cpp_info.bindirs = ['bin'] def test(self): loop = asyncio.get_event_loop() loop.run_until_complete(ConanFile.project.test())
import asyncio from pathlib import Path from conans import ConanFile as ConanConanFile from conans import tools from cpppm import Project, Library, root_project import nest_asyncio nest_asyncio.apply() class PackageInfos: def __init__(self, data): self.include_dirs = set() self.lib_dirs = set() self.libs = set() self.res_dirs = set() self.bin_dirs = set() self.build_dirs = set() self.defines = dict() self.name = data['name'] self.version = data['version'] self.root = Path(data['rootpath']) self.description = data['description'] if 'description' in data else None self.load(data) self.header_only = self.name not in data['libs'] def load(self, comp): if 'include_paths' in comp: self.include_dirs.update(comp['include_paths']) if 'lib_paths' in comp: self.lib_dirs.update(comp['lib_paths']) if 'libs' in comp: self.libs.update([lib for lib in comp['libs'] if lib != self.name]) if 'system_libs' in comp: self.libs.update(comp['system_libs']) if 'res_paths' in comp: self.res_dirs.update(comp['res_paths']) if 'bin_paths' in comp: self.bin_dirs.update(comp['bin_paths']) if 'build_paths' in comp: self.build_dirs.update(comp['build_paths']) if 'defines' in comp: for definition in comp['defines']: tmp = definition.split('=') self.defines[tmp[0]] = tmp[1] if len(tmp) > 1 else None @property def conan_ref(self): return f'{self.name}/{self.version}@' class PackageLibrary(Library): def __init__(self, infos, **kwargs): self._infos = PackageInfos(infos) super().__init__(self._infos.name, self._infos.root, self._infos.root, **kwargs) self.include_dirs = self._infos.include_dirs self.link_libraries = self._infos.libs self.compile_definitions = self._infos.defines self.library_dirs = {self._infos.root / p for p in self._infos.lib_dirs} def resolve_deps(self): # for dep in self._infos.deps: # self.link_libraries = Project._pkg_libraries[dep] pass @property def conan_ref(self): return self._infos.conan_ref @property def is_header_only(self): return self._infos.header_only async def build(self): return False class ConanFile(ConanConanFile): project: Project = root_project() name = project.package_name # url = project.url version = project.version license = project.license settings = {"os", "compiler", "build_type", "arch"} options = project.options requires = tuple(project.requires) build_requires = tuple(project.build_requires) default_options = project.default_options no_copy_source = False exports_sources = '*' def deploy(self): self.copy("*", dst="bin", src="bin") def configure(self): if self.settings.os == "Windows": del self.options.fPIC def build(self): print(self.source_folder) loop = asyncio.get_event_loop() ConanFile.project.install_requirements() loop.run_until_complete(ConanFile.project.build()) def package(self): loop = asyncio.get_event_loop() loop.run_until_complete(ConanFile.project.install(self.package_folder)) def package_info(self): self.cpp_info.libs = tools.collect_libs(self) self.cpp_info.bindirs = ['bin'] def test(self): loop = asyncio.get_event_loop() loop.run_until_complete(ConanFile.project.test())
en
0.547831
# for dep in self._infos.deps: # self.link_libraries = Project._pkg_libraries[dep] # url = project.url
2.184102
2
engfrosh_site/frosh/migrations/0013_alter_userdetails_invite_email_sent.py
engfrosh/engfrosh
1
6632199
# Generated by Django 3.2.5 on 2021-09-03 01:17 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('frosh', '0012_userdetails_invite_email_sent'), ] operations = [ migrations.AlterField( model_name='userdetails', name='invite_email_sent', field=models.BooleanField(default=False, verbose_name='Invite Email Sent'), ), ]
# Generated by Django 3.2.5 on 2021-09-03 01:17 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('frosh', '0012_userdetails_invite_email_sent'), ] operations = [ migrations.AlterField( model_name='userdetails', name='invite_email_sent', field=models.BooleanField(default=False, verbose_name='Invite Email Sent'), ), ]
en
0.864762
# Generated by Django 3.2.5 on 2021-09-03 01:17
1.429134
1
cardclass.py
sackidude/2048-solitaire
1
6632200
<reponame>sackidude/2048-solitaire<filename>cardclass.py """This is all the classes. card, piles and hand""" from random import randrange import funcs INVALID_INPUT = 2 class NonRenderGame: """This is the whole game class without any rendering.""" def __init__(self, max_cards): self.hand = NonRenderHand() self.piles = NonRenderPiles() self.score = 0 self.multiplier = 1 self.trashes = 2 self.mix = True self.max_cards = max_cards def init_hand(self): """Initiate the hand with two cards""" for i in range(2): self.hand.add_card(NonRenderCard(randrange(6) + 1)) def place_card(self, _place): """ This function takes a number between 0-3 and places a card there if it can. It return true if it placed a card. This is only used in the msachine learning part of the program. """ if len(self.piles.piles[_place]) < self.max_cards: self.piles.add_card(self.hand.cards[0], _place) self.hand.cards.pop(0) self.hand.add_card(NonRenderCard((randrange(6) + 1))) answer = self.piles.update(_place) self.score += answer[0] if answer[1]: self.piles.piles[_place] = [] self.multiplier += 1 self.mix = True self.trashes = 2 return True elif self.piles.piles[_place][self.max_cards-1].value == self.hand.cards[0].value: self.piles.piles[_place][self.max_cards-1].value += 1 self.piles.update(_place) self.hand.cards.pop(0) self.hand.add_card(NonRenderCard((randrange(6) + 1))) return True else: return False def check_game_over(self): """Function used for checking if game is over.""" total_length = 0 for current_pile in self.piles.piles: total_length += len(current_pile) return bool(total_length >= 24) def trash(self): """Throw away a card from the hand.""" self.trashes -= 1 self.hand.trash() def mix_hand(self): """Mixes the cards in the hand.""" self.mix = False self.hand.mix() class MLGame(NonRenderGame): """ This is the normal game with machine learning related functions. """ def get_network_inputs(self): """ This function is for the machine learning. It gives back an array of length 24 with the values(1-x not to 2048)of all of the cards. """ return_array = [] # Add the pile values to the array for i in range(4): for j in range(6): try: self.piles.piles[i][j] except IndexError: return_array.append(0) else: return_array.append(self.piles.piles[i][j].value/11) # Add the hand to the array for card in self.hand.cards: return_array.append(card.value) # Add the amount of trashes and if there is a mix return_array.append(self.trashes) if self.mix: return_array.append(1) else: return_array.append(0) return return_array def get_action_random(self): pass def get_action_highest(self): pass class GameWithRender(NonRenderGame): """Game With render function.""" def __init__(self, _max_card, _height, _width): super().__init__(_max_card) self.hand = Hand() self.piles = Piles() self.height = _height self.width = _width def init_hand(self): """Initiate the hand with two cards""" for i in range(2): self.hand.add_card(Card((randrange(6) + 1), 70, 100)) def place_card(self, _place): """This function takes a number between 0-3 and places a card there if it can.""" if len(self.piles.piles[_place]) < self.max_cards: self.piles.add_card(self.hand.cards[0], _place) self.hand.cards.pop(0) self.hand.add_card(Card((randrange(6) + 1), 70, 100)) answer = self.piles.update(_place) self.score += answer[0] if answer[1]: self.piles.piles[_place] = [] self.multiplier += 1 self.mix = True self.trashes = 2 elif self.piles.piles[_place][self.max_cards-1].value == self.hand.cards[0].value: self.piles.piles[_place][self.max_cards-1].value += 1 self.piles.update(_place) self.hand.cards.pop(0) self.hand.add_card(Card((randrange(6) + 1), 70, 100)) def render(self, font, screen, pygame): """Renders hand and piles.""" self.piles.render(font, screen, pygame, self.width, self.height) self.hand.render(font, screen, pygame, self.height) def trash(self): """Throw away a card from the hand.""" if self.trashes == 0: return INVALID_INPUT self.trashes -= 1 self.hand.trash() return None class NonRenderCard(): """Just information about card without any rendering capabilities""" def __init__(self, _value): self.value = _value def get_value(self): """This gets the not power two value of the card""" return 2 ** self.value class Card(NonRenderCard): """This is the class for a single card with rendering capabilities.""" def __init__(self, _value, _width=70, _height=100, _canMove=False): super().__init__(_value) self.width = _width self.height = _height def get_color(self): """Gets the color of the card. Will maybe be based on a color theme in the future""" translated = funcs.translate(self.value, 1, 12, 0, 255) return ( translated, 255 - translated, 255 - translated ) def render(self, _font, _screen, x_cord, y_cord, border, _pygame): """Render the card""" # Render the outline. Large them the card by 5 pixels. if border > 0: _pygame.draw.rect(_screen, (255, 255, 255), _pygame.Rect( (x_cord - border, y_cord - border), (self.width + 2*border, self.height + 2*border) )) # Render the actual card _pygame.draw.rect( _screen, self.get_color(), _pygame.Rect( (x_cord, y_cord), (self.width, self.height) ) ) current_text = _font.render( str(self.get_value()), True, (0, 0, 0) ) _screen.blit(current_text, (x_cord, y_cord)) # render the text class NonRenderPiles(): """Nonrender pile class. Parent to piles""" def __init__(self): self.piles = [[], [], [], []] def update(self, update_pile_index): """This combines all the cards that can be combined in the specific pile""" answer = [0, False] for i in range(len(self.piles[update_pile_index]), 0, -1): current_card_i = i - 1 if current_card_i > 0: current_pile = self.piles[update_pile_index] if current_pile[current_card_i].value == current_pile[current_card_i - 1].value: del self.piles[update_pile_index][-1] current_pile[len( self.piles[update_pile_index]) - 1].value += 1 new_value = current_pile[len( self.piles[update_pile_index]) - 1].get_value() answer[0] += new_value if new_value == 2048: answer[1] = True else: i = 1 break return answer def add_card(self, _card, _pile): """Adds a card object to one of the piles""" self.piles[_pile].append(_card) class Piles(NonRenderPiles): """The class for the four piles in this game""" def render(self, _font, _screen, _pygame, _width, _height): """Render all the cards in the piles""" for i, current_pile in enumerate(self.piles): x_cord = funcs.translate(i, 0, 4, 30, _width) for j, current_card in enumerate(current_pile): y_cord = funcs.translate(j, 0, 8, 30, _height - 100) current_card.render(_font, _screen, x_cord, y_cord, 2, _pygame) class NonRenderHand(): """NonRender hand parent to hand. Which has rendering functoin""" def __init__(self): self.cards = [] def add_card(self, _card): """Adds a card to the end of the hand""" self.cards.append(_card) def trash(self): """Removes the card at the front and adds one to the end""" self.cards.pop(0) self.add_card(NonRenderCard(randrange(6)+1)) def mix(self): """Switches the values of all the cards in the hand""" for i in range(0, len(self.cards)): self.cards[i].value = randrange(6)+1 class Hand(NonRenderHand): """This is the class for the two cards in the corner""" def render(self, _font, screen, pygame, height): """Renders the hand""" idx = 0 for val in reversed(self.cards): val.render(_font, screen, 50 + 35 * idx, height - 130, 2, pygame) idx += 1 def trash(self): """Removes the card at the front and adds one to the end""" self.cards.pop(0) self.add_card(Card(randrange(6)+1, 70, 100))
"""This is all the classes. card, piles and hand""" from random import randrange import funcs INVALID_INPUT = 2 class NonRenderGame: """This is the whole game class without any rendering.""" def __init__(self, max_cards): self.hand = NonRenderHand() self.piles = NonRenderPiles() self.score = 0 self.multiplier = 1 self.trashes = 2 self.mix = True self.max_cards = max_cards def init_hand(self): """Initiate the hand with two cards""" for i in range(2): self.hand.add_card(NonRenderCard(randrange(6) + 1)) def place_card(self, _place): """ This function takes a number between 0-3 and places a card there if it can. It return true if it placed a card. This is only used in the msachine learning part of the program. """ if len(self.piles.piles[_place]) < self.max_cards: self.piles.add_card(self.hand.cards[0], _place) self.hand.cards.pop(0) self.hand.add_card(NonRenderCard((randrange(6) + 1))) answer = self.piles.update(_place) self.score += answer[0] if answer[1]: self.piles.piles[_place] = [] self.multiplier += 1 self.mix = True self.trashes = 2 return True elif self.piles.piles[_place][self.max_cards-1].value == self.hand.cards[0].value: self.piles.piles[_place][self.max_cards-1].value += 1 self.piles.update(_place) self.hand.cards.pop(0) self.hand.add_card(NonRenderCard((randrange(6) + 1))) return True else: return False def check_game_over(self): """Function used for checking if game is over.""" total_length = 0 for current_pile in self.piles.piles: total_length += len(current_pile) return bool(total_length >= 24) def trash(self): """Throw away a card from the hand.""" self.trashes -= 1 self.hand.trash() def mix_hand(self): """Mixes the cards in the hand.""" self.mix = False self.hand.mix() class MLGame(NonRenderGame): """ This is the normal game with machine learning related functions. """ def get_network_inputs(self): """ This function is for the machine learning. It gives back an array of length 24 with the values(1-x not to 2048)of all of the cards. """ return_array = [] # Add the pile values to the array for i in range(4): for j in range(6): try: self.piles.piles[i][j] except IndexError: return_array.append(0) else: return_array.append(self.piles.piles[i][j].value/11) # Add the hand to the array for card in self.hand.cards: return_array.append(card.value) # Add the amount of trashes and if there is a mix return_array.append(self.trashes) if self.mix: return_array.append(1) else: return_array.append(0) return return_array def get_action_random(self): pass def get_action_highest(self): pass class GameWithRender(NonRenderGame): """Game With render function.""" def __init__(self, _max_card, _height, _width): super().__init__(_max_card) self.hand = Hand() self.piles = Piles() self.height = _height self.width = _width def init_hand(self): """Initiate the hand with two cards""" for i in range(2): self.hand.add_card(Card((randrange(6) + 1), 70, 100)) def place_card(self, _place): """This function takes a number between 0-3 and places a card there if it can.""" if len(self.piles.piles[_place]) < self.max_cards: self.piles.add_card(self.hand.cards[0], _place) self.hand.cards.pop(0) self.hand.add_card(Card((randrange(6) + 1), 70, 100)) answer = self.piles.update(_place) self.score += answer[0] if answer[1]: self.piles.piles[_place] = [] self.multiplier += 1 self.mix = True self.trashes = 2 elif self.piles.piles[_place][self.max_cards-1].value == self.hand.cards[0].value: self.piles.piles[_place][self.max_cards-1].value += 1 self.piles.update(_place) self.hand.cards.pop(0) self.hand.add_card(Card((randrange(6) + 1), 70, 100)) def render(self, font, screen, pygame): """Renders hand and piles.""" self.piles.render(font, screen, pygame, self.width, self.height) self.hand.render(font, screen, pygame, self.height) def trash(self): """Throw away a card from the hand.""" if self.trashes == 0: return INVALID_INPUT self.trashes -= 1 self.hand.trash() return None class NonRenderCard(): """Just information about card without any rendering capabilities""" def __init__(self, _value): self.value = _value def get_value(self): """This gets the not power two value of the card""" return 2 ** self.value class Card(NonRenderCard): """This is the class for a single card with rendering capabilities.""" def __init__(self, _value, _width=70, _height=100, _canMove=False): super().__init__(_value) self.width = _width self.height = _height def get_color(self): """Gets the color of the card. Will maybe be based on a color theme in the future""" translated = funcs.translate(self.value, 1, 12, 0, 255) return ( translated, 255 - translated, 255 - translated ) def render(self, _font, _screen, x_cord, y_cord, border, _pygame): """Render the card""" # Render the outline. Large them the card by 5 pixels. if border > 0: _pygame.draw.rect(_screen, (255, 255, 255), _pygame.Rect( (x_cord - border, y_cord - border), (self.width + 2*border, self.height + 2*border) )) # Render the actual card _pygame.draw.rect( _screen, self.get_color(), _pygame.Rect( (x_cord, y_cord), (self.width, self.height) ) ) current_text = _font.render( str(self.get_value()), True, (0, 0, 0) ) _screen.blit(current_text, (x_cord, y_cord)) # render the text class NonRenderPiles(): """Nonrender pile class. Parent to piles""" def __init__(self): self.piles = [[], [], [], []] def update(self, update_pile_index): """This combines all the cards that can be combined in the specific pile""" answer = [0, False] for i in range(len(self.piles[update_pile_index]), 0, -1): current_card_i = i - 1 if current_card_i > 0: current_pile = self.piles[update_pile_index] if current_pile[current_card_i].value == current_pile[current_card_i - 1].value: del self.piles[update_pile_index][-1] current_pile[len( self.piles[update_pile_index]) - 1].value += 1 new_value = current_pile[len( self.piles[update_pile_index]) - 1].get_value() answer[0] += new_value if new_value == 2048: answer[1] = True else: i = 1 break return answer def add_card(self, _card, _pile): """Adds a card object to one of the piles""" self.piles[_pile].append(_card) class Piles(NonRenderPiles): """The class for the four piles in this game""" def render(self, _font, _screen, _pygame, _width, _height): """Render all the cards in the piles""" for i, current_pile in enumerate(self.piles): x_cord = funcs.translate(i, 0, 4, 30, _width) for j, current_card in enumerate(current_pile): y_cord = funcs.translate(j, 0, 8, 30, _height - 100) current_card.render(_font, _screen, x_cord, y_cord, 2, _pygame) class NonRenderHand(): """NonRender hand parent to hand. Which has rendering functoin""" def __init__(self): self.cards = [] def add_card(self, _card): """Adds a card to the end of the hand""" self.cards.append(_card) def trash(self): """Removes the card at the front and adds one to the end""" self.cards.pop(0) self.add_card(NonRenderCard(randrange(6)+1)) def mix(self): """Switches the values of all the cards in the hand""" for i in range(0, len(self.cards)): self.cards[i].value = randrange(6)+1 class Hand(NonRenderHand): """This is the class for the two cards in the corner""" def render(self, _font, screen, pygame, height): """Renders the hand""" idx = 0 for val in reversed(self.cards): val.render(_font, screen, 50 + 35 * idx, height - 130, 2, pygame) idx += 1 def trash(self): """Removes the card at the front and adds one to the end""" self.cards.pop(0) self.add_card(Card(randrange(6)+1, 70, 100))
en
0.884638
This is all the classes. card, piles and hand This is the whole game class without any rendering. Initiate the hand with two cards This function takes a number between 0-3 and places a card there if it can. It return true if it placed a card. This is only used in the msachine learning part of the program. Function used for checking if game is over. Throw away a card from the hand. Mixes the cards in the hand. This is the normal game with machine learning related functions. This function is for the machine learning. It gives back an array of length 24 with the values(1-x not to 2048)of all of the cards. # Add the pile values to the array # Add the hand to the array # Add the amount of trashes and if there is a mix Game With render function. Initiate the hand with two cards This function takes a number between 0-3 and places a card there if it can. Renders hand and piles. Throw away a card from the hand. Just information about card without any rendering capabilities This gets the not power two value of the card This is the class for a single card with rendering capabilities. Gets the color of the card. Will maybe be based on a color theme in the future Render the card # Render the outline. Large them the card by 5 pixels. # Render the actual card # render the text Nonrender pile class. Parent to piles This combines all the cards that can be combined in the specific pile Adds a card object to one of the piles The class for the four piles in this game Render all the cards in the piles NonRender hand parent to hand. Which has rendering functoin Adds a card to the end of the hand Removes the card at the front and adds one to the end Switches the values of all the cards in the hand This is the class for the two cards in the corner Renders the hand Removes the card at the front and adds one to the end
3.882328
4
LeetCode/0076_minimum_window_substring.py
KanegaeGabriel/ye-olde-interview-prep-grind
1
6632201
<gh_stars>1-10 def countChars(s): count = [0 for _ in range(256)] for c in s: count[ord(c)] += 1 return count def minWindow(s, t): tCount = countChars(t) i, j = 0, 0 sCount = [0 for _ in range(256)] best = [None, i, j] while i <= j and j < len(s): sCount[ord(s[j])] += 1 while i <= j and all(si>=ti for si, ti in zip(sCount, tCount)): if not best[0] or j-i < best[0]: best = [j-i, i, j] sCount[ord(s[i])] -= 1 i += 1 j += 1 if best[0] == None: return "" return s[best[1]:best[2]+1] print(minWindow("ADOBECODEBANC", "ABC")) # "BANC" print(minWindow("a", "aa")) # ""
def countChars(s): count = [0 for _ in range(256)] for c in s: count[ord(c)] += 1 return count def minWindow(s, t): tCount = countChars(t) i, j = 0, 0 sCount = [0 for _ in range(256)] best = [None, i, j] while i <= j and j < len(s): sCount[ord(s[j])] += 1 while i <= j and all(si>=ti for si, ti in zip(sCount, tCount)): if not best[0] or j-i < best[0]: best = [j-i, i, j] sCount[ord(s[i])] -= 1 i += 1 j += 1 if best[0] == None: return "" return s[best[1]:best[2]+1] print(minWindow("ADOBECODEBANC", "ABC")) # "BANC" print(minWindow("a", "aa")) # ""
en
0.486913
# "BANC" # ""
3.240774
3
database_files/hr_naselja_gradovi/izvezi_hr_naselja_u_csv.py
mvrban123/PHP-Laravel-Project---Website
0
6632202
<filename>database_files/hr_naselja_gradovi/izvezi_hr_naselja_u_csv.py<gh_stars>0 #!/usr/bin/env python # coding: utf-8 # **Dataset from: https://www.posta.hr/preuzimanje-podataka-o-postanskim-uredima-6543/6543** import pandas as pd target_cols = [ "BrojPu", "Naselje" ] df_mjesta = pd.read_excel("./mjestaRh.xlsx", usecols=target_cols) # df_mjesta df_mjesta.to_csv("hr_naselja_air_2020.csv", index=False)
<filename>database_files/hr_naselja_gradovi/izvezi_hr_naselja_u_csv.py<gh_stars>0 #!/usr/bin/env python # coding: utf-8 # **Dataset from: https://www.posta.hr/preuzimanje-podataka-o-postanskim-uredima-6543/6543** import pandas as pd target_cols = [ "BrojPu", "Naselje" ] df_mjesta = pd.read_excel("./mjestaRh.xlsx", usecols=target_cols) # df_mjesta df_mjesta.to_csv("hr_naselja_air_2020.csv", index=False)
en
0.322035
#!/usr/bin/env python # coding: utf-8 # **Dataset from: https://www.posta.hr/preuzimanje-podataka-o-postanskim-uredima-6543/6543** # df_mjesta
2.417385
2
test/func_test/test_ctrt/test_pay_chan_ctrt.py
josephzxy/py-vsys
1
6632203
<filename>test/func_test/test_ctrt/test_pay_chan_ctrt.py import asyncio import time from typing import Tuple import pytest import py_vsys as pv from test.func_test import conftest as cft class TestPayChanCtrt: """ TestPayChanCtrt is the collection of functional tests of Payment Channel Contract. """ TOK_MAX = 100 TOK_UNIT = 1 INIT_LOAD = TOK_MAX // 2 @pytest.fixture async def new_tok_ctrt(self, acnt0: pv.Account) -> pv.TokCtrtWithoutSplit: """ new_tok_ctrt is the fixture that registers a new token contract without split instance. Args: acnt0 (pv.Account): The account of nonce 0. Returns: pv.TokCtrtWithoutSplit: The token contract instance. """ tc = await pv.TokCtrtWithoutSplit.register(acnt0, self.TOK_MAX, self.TOK_UNIT) await cft.wait_for_block() await tc.issue(acnt0, self.TOK_MAX) await cft.wait_for_block() return tc @pytest.fixture async def new_ctrt( self, acnt0: pv.Account, new_tok_ctrt: pv.TokCtrtWithoutSplit ) -> pv.PayChanCtrt: """ new_ctrt is the fixture that registers a new Payment Channel contract. Args: acnt0 (pv.Account): The account of nonce 0. new_tok_ctrt (pv.TokCtrtWithoutSplit): The fixture that registers a new Token contract. Returns: pv.PayChanCtrt: The PayChanCtrt instance. """ tc = new_tok_ctrt api = acnt0.api pc = await pv.PayChanCtrt.register(acnt0, tc.tok_id.data) await cft.wait_for_block() resp = await tc.deposit(acnt0, pc.ctrt_id.data, self.TOK_MAX) await cft.wait_for_block() await cft.assert_tx_success(api, resp["id"]) return pc @pytest.fixture async def new_ctrt_with_chan( self, acnt0: pv.Account, acnt1: pv.Account, new_ctrt: pv.PayChanCtrt, ) -> Tuple[pv.PayChanCtrt, str]: """ new_ctrt_with_chan is the fixture that registers a new Payment Channel contract and creates a channel. Args: acnt0 (pv.Account): The account of nonce 0. acnt1 (pv.Account): The account of nonce 1. new_ctrt (pv.PayChanCtrt): The fixture that registers a new Payment Channel contract. Returns: Tuple[pv.PayChanCtrt, str]: The PayChanCtrt instance & channel id """ pc = new_ctrt load_amount = self.INIT_LOAD later = int(time.time()) + 60 * 10 resp = await pc.create_and_load( by=acnt0, recipient=acnt1.addr.data, amount=load_amount, expire_at=later, ) await cft.wait_for_block() chan_id = resp["id"] return pc, chan_id async def test_register( self, acnt0: pv.Account, new_tok_ctrt: pv.TokCtrtWithoutSplit, new_ctrt: pv.PayChanCtrt, ) -> pv.PayChanCtrt: """ test_register tests the method register. Args: acnt0 (pv.Account): The account of nonce 0. new_tok_ctrt (pv.TokCtrtWithoutSplit): The fixture that registers a new Token contract. new_ctrt (pv.PayChanCtrt): The fixture that registers a new Payment Channel contract. Returns: pv.PayChanCtrt: The PayChanCtrt instance. """ tc = new_tok_ctrt pc = new_ctrt assert (await pc.maker) == acnt0.addr assert (await pc.tok_id) == tc.tok_id ctrt_bal = await pc.get_ctrt_bal(acnt0.addr.data) assert ctrt_bal.amount == self.TOK_MAX return pc async def test_create_and_load( self, acnt0: pv.Account, acnt1: pv.Account, new_ctrt: pv.PayChanCtrt, ) -> str: """ test_create_and_load tests the method create_and_load. Args: acnt0 (pv.Account): The account of nonce 0. acnt1 (pv.Account): The account of nonce 1. new_ctrt (pv.PayChanCtrt): The fixture that registers a new Payment Channel contract. Returns: str: The channel ID. """ pc = new_ctrt api = acnt0.api load_amount = self.INIT_LOAD later = int(time.time()) + 60 * 10 resp = await pc.create_and_load( by=acnt0, recipient=acnt1.addr.data, amount=load_amount, expire_at=later, ) await cft.wait_for_block() await cft.assert_tx_success(api, resp["id"]) chan_id = resp["id"] chan_creator = await pc.get_chan_creator(chan_id) assert chan_creator == acnt0.addr chan_creator_pub_key = await pc.get_chan_creator_pub_key(chan_id) assert chan_creator_pub_key == acnt0.key_pair.pub chan_accum_load = await pc.get_chan_accum_load(chan_id) assert chan_accum_load.amount == load_amount chan_accum_pay = await pc.get_chan_accum_pay(chan_id) assert chan_accum_pay.amount == 0 chan_exp_time = await pc.get_chan_exp_time(chan_id) assert chan_exp_time.unix_ts == later chan_status = await pc.get_chan_status(chan_id) assert chan_status is True return chan_id async def test_extend_exp_time( self, acnt0: pv.Account, new_ctrt_with_chan: Tuple[pv.PayChanCtrt, str], ) -> None: """ test_extend_exp_time tests the method extend_exp_time. Args: acnt0 (pv.Account): The account of nonce 0. new_ctrt_with_chan (Tuple[pv.PayChanCtrt, str]): The fixture that registers a new Payment Channel contract and creates a new channel. """ pc, chan_id = new_ctrt_with_chan api = acnt0.api chan_exp_time_old = await pc.get_chan_exp_time(chan_id) new_later = chan_exp_time_old.unix_ts + 300 resp = await pc.extend_exp_time( by=acnt0, chan_id=chan_id, expire_at=new_later, ) await cft.wait_for_block() await cft.assert_tx_success(api, resp["id"]) chan_exp_time = await pc.get_chan_exp_time(chan_id) assert chan_exp_time.unix_ts == new_later async def test_load( self, acnt0: pv.Account, new_ctrt_with_chan: Tuple[pv.PayChanCtrt, str], ) -> None: """ test_load tests the method load. Args: acnt0 (pv.Account): The account of nonce 0. new_ctrt_with_chan (Tuple[pv.PayChanCtrt, str]): The fixture that registers a new Payment Channel contract and creates a new channel. """ pc, chan_id = new_ctrt_with_chan api = acnt0.api chan_load_old = await pc.get_chan_accum_load(chan_id) assert chan_load_old.amount == self.INIT_LOAD more_load = self.INIT_LOAD // 2 resp = await pc.load(acnt0, chan_id, more_load) await cft.wait_for_block() await cft.assert_tx_success(api, resp["id"]) chan_load = await pc.get_chan_accum_load(chan_id) assert chan_load.amount == self.INIT_LOAD + more_load async def test_abort( self, acnt0: pv.Account, new_ctrt_with_chan: Tuple[pv.PayChanCtrt, str], ) -> None: """ test_abort tests the method abort. Args: acnt0 (pv.Account): The account of nonce 0. new_ctrt_with_chan (Tuple[pv.PayChanCtrt, str]): The fixture that registers a new Payment Channel contract and creates a new channel. """ pc, chan_id = new_ctrt_with_chan api = acnt0.api chan_status = await pc.get_chan_status(chan_id) assert chan_status is True resp = await pc.abort(acnt0, chan_id) await cft.wait_for_block() await cft.assert_tx_success(api, resp["id"]) chan_status = await pc.get_chan_status(chan_id) assert chan_status is False async def test_unload( self, acnt0: pv.Account, acnt1: pv.Account, new_ctrt: pv.PayChanCtrt, ) -> None: """ test_unload tests the method unload. Args: acnt0 (pv.Account): The account of nonce 0. acnt1 (pv.Account): The account of nonce 1. new_ctrt (pv.PayChanCtrt): The fixture that registers a new Payment Channel contract. """ pc = new_ctrt api = acnt0.api load_amount = self.TOK_MAX // 10 later = int(time.time()) + cft.AVG_BLOCK_DELAY * 2 # create a channel resp = await pc.create_and_load( by=acnt0, recipient=acnt1.addr.data, amount=load_amount, expire_at=later, ) await cft.wait_for_block() await cft.assert_tx_success(api, resp["id"]) chan_id = resp["id"] bal_old = await pc.get_ctrt_bal(acnt0.addr.data) # wait until the channel expires await asyncio.sleep(cft.AVG_BLOCK_DELAY * 2) resp = await pc.unload(acnt0, chan_id) await cft.wait_for_block() await cft.assert_tx_success(api, resp["id"]) bal = await pc.get_ctrt_bal(acnt0.addr.data) assert bal.amount == bal_old.amount + load_amount async def test_offchain_pay_and_collect_payment( self, acnt0: pv.Account, acnt1: pv.Account, new_ctrt_with_chan: Tuple[pv.PayChanCtrt, str], ) -> None: """ test_offchain_pay_and_collect_payment tests the method - offchain_pay - collect_payment. Args: acnt0 (pv.Account): The account of nonce 0. acnt1 (pv.Account): The account of nonce 1. new_ctrt_with_chan (Tuple[pv.PayChanCtrt, str]): The fixture that registers a new Payment Channel contract and creates a new channel. """ pc, chan_id = new_ctrt_with_chan api = acnt0.api sig = await pc.offchain_pay( key_pair=acnt0.key_pair, chan_id=chan_id, amount=self.INIT_LOAD, ) resp = await pc.collect_payment( by=acnt1, chan_id=chan_id, amount=self.INIT_LOAD, signature=sig, ) await cft.wait_for_block() await cft.assert_tx_success(api, resp["id"]) accum_pay = await pc.get_chan_accum_pay(chan_id) assert accum_pay.amount == self.INIT_LOAD acnt1_bal = await pc.get_ctrt_bal(acnt1.addr.data) assert acnt1_bal.amount == self.INIT_LOAD @pytest.mark.whole async def test_as_whole( self, acnt0: pv.Account, acnt1: pv.Account, new_tok_ctrt: pv.TokCtrtWithoutSplit, new_ctrt: pv.PayChanCtrt, ) -> None: """ test_as_whole tests methods of PayChanCtrt as a whole so as to reduce resource consumption. Args: acnt0 (pv.Account): The account of nonce 0. acnt1 (pv.Account): The account of nonce 1. new_tok_ctrt (pv.TokCtrtWithoutSplit): The token contract instance. new_ctrt (pv.PayChanCtrt): The fixture that registers a new Payment Channel contract. """ tc = new_tok_ctrt pc = new_ctrt await self.test_register(acnt0, tc, pc) chan_id = await self.test_create_and_load(acnt0, acnt1, pc) pc_with_chan = (pc, chan_id) await self.test_extend_exp_time(acnt0, pc_with_chan) await self.test_load(acnt0, pc_with_chan) await self.test_offchain_pay_and_collect_payment(acnt0, acnt1, pc_with_chan) await self.test_abort(acnt0, pc_with_chan) await self.test_unload(acnt0, acnt1, pc)
<filename>test/func_test/test_ctrt/test_pay_chan_ctrt.py import asyncio import time from typing import Tuple import pytest import py_vsys as pv from test.func_test import conftest as cft class TestPayChanCtrt: """ TestPayChanCtrt is the collection of functional tests of Payment Channel Contract. """ TOK_MAX = 100 TOK_UNIT = 1 INIT_LOAD = TOK_MAX // 2 @pytest.fixture async def new_tok_ctrt(self, acnt0: pv.Account) -> pv.TokCtrtWithoutSplit: """ new_tok_ctrt is the fixture that registers a new token contract without split instance. Args: acnt0 (pv.Account): The account of nonce 0. Returns: pv.TokCtrtWithoutSplit: The token contract instance. """ tc = await pv.TokCtrtWithoutSplit.register(acnt0, self.TOK_MAX, self.TOK_UNIT) await cft.wait_for_block() await tc.issue(acnt0, self.TOK_MAX) await cft.wait_for_block() return tc @pytest.fixture async def new_ctrt( self, acnt0: pv.Account, new_tok_ctrt: pv.TokCtrtWithoutSplit ) -> pv.PayChanCtrt: """ new_ctrt is the fixture that registers a new Payment Channel contract. Args: acnt0 (pv.Account): The account of nonce 0. new_tok_ctrt (pv.TokCtrtWithoutSplit): The fixture that registers a new Token contract. Returns: pv.PayChanCtrt: The PayChanCtrt instance. """ tc = new_tok_ctrt api = acnt0.api pc = await pv.PayChanCtrt.register(acnt0, tc.tok_id.data) await cft.wait_for_block() resp = await tc.deposit(acnt0, pc.ctrt_id.data, self.TOK_MAX) await cft.wait_for_block() await cft.assert_tx_success(api, resp["id"]) return pc @pytest.fixture async def new_ctrt_with_chan( self, acnt0: pv.Account, acnt1: pv.Account, new_ctrt: pv.PayChanCtrt, ) -> Tuple[pv.PayChanCtrt, str]: """ new_ctrt_with_chan is the fixture that registers a new Payment Channel contract and creates a channel. Args: acnt0 (pv.Account): The account of nonce 0. acnt1 (pv.Account): The account of nonce 1. new_ctrt (pv.PayChanCtrt): The fixture that registers a new Payment Channel contract. Returns: Tuple[pv.PayChanCtrt, str]: The PayChanCtrt instance & channel id """ pc = new_ctrt load_amount = self.INIT_LOAD later = int(time.time()) + 60 * 10 resp = await pc.create_and_load( by=acnt0, recipient=acnt1.addr.data, amount=load_amount, expire_at=later, ) await cft.wait_for_block() chan_id = resp["id"] return pc, chan_id async def test_register( self, acnt0: pv.Account, new_tok_ctrt: pv.TokCtrtWithoutSplit, new_ctrt: pv.PayChanCtrt, ) -> pv.PayChanCtrt: """ test_register tests the method register. Args: acnt0 (pv.Account): The account of nonce 0. new_tok_ctrt (pv.TokCtrtWithoutSplit): The fixture that registers a new Token contract. new_ctrt (pv.PayChanCtrt): The fixture that registers a new Payment Channel contract. Returns: pv.PayChanCtrt: The PayChanCtrt instance. """ tc = new_tok_ctrt pc = new_ctrt assert (await pc.maker) == acnt0.addr assert (await pc.tok_id) == tc.tok_id ctrt_bal = await pc.get_ctrt_bal(acnt0.addr.data) assert ctrt_bal.amount == self.TOK_MAX return pc async def test_create_and_load( self, acnt0: pv.Account, acnt1: pv.Account, new_ctrt: pv.PayChanCtrt, ) -> str: """ test_create_and_load tests the method create_and_load. Args: acnt0 (pv.Account): The account of nonce 0. acnt1 (pv.Account): The account of nonce 1. new_ctrt (pv.PayChanCtrt): The fixture that registers a new Payment Channel contract. Returns: str: The channel ID. """ pc = new_ctrt api = acnt0.api load_amount = self.INIT_LOAD later = int(time.time()) + 60 * 10 resp = await pc.create_and_load( by=acnt0, recipient=acnt1.addr.data, amount=load_amount, expire_at=later, ) await cft.wait_for_block() await cft.assert_tx_success(api, resp["id"]) chan_id = resp["id"] chan_creator = await pc.get_chan_creator(chan_id) assert chan_creator == acnt0.addr chan_creator_pub_key = await pc.get_chan_creator_pub_key(chan_id) assert chan_creator_pub_key == acnt0.key_pair.pub chan_accum_load = await pc.get_chan_accum_load(chan_id) assert chan_accum_load.amount == load_amount chan_accum_pay = await pc.get_chan_accum_pay(chan_id) assert chan_accum_pay.amount == 0 chan_exp_time = await pc.get_chan_exp_time(chan_id) assert chan_exp_time.unix_ts == later chan_status = await pc.get_chan_status(chan_id) assert chan_status is True return chan_id async def test_extend_exp_time( self, acnt0: pv.Account, new_ctrt_with_chan: Tuple[pv.PayChanCtrt, str], ) -> None: """ test_extend_exp_time tests the method extend_exp_time. Args: acnt0 (pv.Account): The account of nonce 0. new_ctrt_with_chan (Tuple[pv.PayChanCtrt, str]): The fixture that registers a new Payment Channel contract and creates a new channel. """ pc, chan_id = new_ctrt_with_chan api = acnt0.api chan_exp_time_old = await pc.get_chan_exp_time(chan_id) new_later = chan_exp_time_old.unix_ts + 300 resp = await pc.extend_exp_time( by=acnt0, chan_id=chan_id, expire_at=new_later, ) await cft.wait_for_block() await cft.assert_tx_success(api, resp["id"]) chan_exp_time = await pc.get_chan_exp_time(chan_id) assert chan_exp_time.unix_ts == new_later async def test_load( self, acnt0: pv.Account, new_ctrt_with_chan: Tuple[pv.PayChanCtrt, str], ) -> None: """ test_load tests the method load. Args: acnt0 (pv.Account): The account of nonce 0. new_ctrt_with_chan (Tuple[pv.PayChanCtrt, str]): The fixture that registers a new Payment Channel contract and creates a new channel. """ pc, chan_id = new_ctrt_with_chan api = acnt0.api chan_load_old = await pc.get_chan_accum_load(chan_id) assert chan_load_old.amount == self.INIT_LOAD more_load = self.INIT_LOAD // 2 resp = await pc.load(acnt0, chan_id, more_load) await cft.wait_for_block() await cft.assert_tx_success(api, resp["id"]) chan_load = await pc.get_chan_accum_load(chan_id) assert chan_load.amount == self.INIT_LOAD + more_load async def test_abort( self, acnt0: pv.Account, new_ctrt_with_chan: Tuple[pv.PayChanCtrt, str], ) -> None: """ test_abort tests the method abort. Args: acnt0 (pv.Account): The account of nonce 0. new_ctrt_with_chan (Tuple[pv.PayChanCtrt, str]): The fixture that registers a new Payment Channel contract and creates a new channel. """ pc, chan_id = new_ctrt_with_chan api = acnt0.api chan_status = await pc.get_chan_status(chan_id) assert chan_status is True resp = await pc.abort(acnt0, chan_id) await cft.wait_for_block() await cft.assert_tx_success(api, resp["id"]) chan_status = await pc.get_chan_status(chan_id) assert chan_status is False async def test_unload( self, acnt0: pv.Account, acnt1: pv.Account, new_ctrt: pv.PayChanCtrt, ) -> None: """ test_unload tests the method unload. Args: acnt0 (pv.Account): The account of nonce 0. acnt1 (pv.Account): The account of nonce 1. new_ctrt (pv.PayChanCtrt): The fixture that registers a new Payment Channel contract. """ pc = new_ctrt api = acnt0.api load_amount = self.TOK_MAX // 10 later = int(time.time()) + cft.AVG_BLOCK_DELAY * 2 # create a channel resp = await pc.create_and_load( by=acnt0, recipient=acnt1.addr.data, amount=load_amount, expire_at=later, ) await cft.wait_for_block() await cft.assert_tx_success(api, resp["id"]) chan_id = resp["id"] bal_old = await pc.get_ctrt_bal(acnt0.addr.data) # wait until the channel expires await asyncio.sleep(cft.AVG_BLOCK_DELAY * 2) resp = await pc.unload(acnt0, chan_id) await cft.wait_for_block() await cft.assert_tx_success(api, resp["id"]) bal = await pc.get_ctrt_bal(acnt0.addr.data) assert bal.amount == bal_old.amount + load_amount async def test_offchain_pay_and_collect_payment( self, acnt0: pv.Account, acnt1: pv.Account, new_ctrt_with_chan: Tuple[pv.PayChanCtrt, str], ) -> None: """ test_offchain_pay_and_collect_payment tests the method - offchain_pay - collect_payment. Args: acnt0 (pv.Account): The account of nonce 0. acnt1 (pv.Account): The account of nonce 1. new_ctrt_with_chan (Tuple[pv.PayChanCtrt, str]): The fixture that registers a new Payment Channel contract and creates a new channel. """ pc, chan_id = new_ctrt_with_chan api = acnt0.api sig = await pc.offchain_pay( key_pair=acnt0.key_pair, chan_id=chan_id, amount=self.INIT_LOAD, ) resp = await pc.collect_payment( by=acnt1, chan_id=chan_id, amount=self.INIT_LOAD, signature=sig, ) await cft.wait_for_block() await cft.assert_tx_success(api, resp["id"]) accum_pay = await pc.get_chan_accum_pay(chan_id) assert accum_pay.amount == self.INIT_LOAD acnt1_bal = await pc.get_ctrt_bal(acnt1.addr.data) assert acnt1_bal.amount == self.INIT_LOAD @pytest.mark.whole async def test_as_whole( self, acnt0: pv.Account, acnt1: pv.Account, new_tok_ctrt: pv.TokCtrtWithoutSplit, new_ctrt: pv.PayChanCtrt, ) -> None: """ test_as_whole tests methods of PayChanCtrt as a whole so as to reduce resource consumption. Args: acnt0 (pv.Account): The account of nonce 0. acnt1 (pv.Account): The account of nonce 1. new_tok_ctrt (pv.TokCtrtWithoutSplit): The token contract instance. new_ctrt (pv.PayChanCtrt): The fixture that registers a new Payment Channel contract. """ tc = new_tok_ctrt pc = new_ctrt await self.test_register(acnt0, tc, pc) chan_id = await self.test_create_and_load(acnt0, acnt1, pc) pc_with_chan = (pc, chan_id) await self.test_extend_exp_time(acnt0, pc_with_chan) await self.test_load(acnt0, pc_with_chan) await self.test_offchain_pay_and_collect_payment(acnt0, acnt1, pc_with_chan) await self.test_abort(acnt0, pc_with_chan) await self.test_unload(acnt0, acnt1, pc)
en
0.61532
TestPayChanCtrt is the collection of functional tests of Payment Channel Contract. new_tok_ctrt is the fixture that registers a new token contract without split instance. Args: acnt0 (pv.Account): The account of nonce 0. Returns: pv.TokCtrtWithoutSplit: The token contract instance. new_ctrt is the fixture that registers a new Payment Channel contract. Args: acnt0 (pv.Account): The account of nonce 0. new_tok_ctrt (pv.TokCtrtWithoutSplit): The fixture that registers a new Token contract. Returns: pv.PayChanCtrt: The PayChanCtrt instance. new_ctrt_with_chan is the fixture that registers a new Payment Channel contract and creates a channel. Args: acnt0 (pv.Account): The account of nonce 0. acnt1 (pv.Account): The account of nonce 1. new_ctrt (pv.PayChanCtrt): The fixture that registers a new Payment Channel contract. Returns: Tuple[pv.PayChanCtrt, str]: The PayChanCtrt instance & channel id test_register tests the method register. Args: acnt0 (pv.Account): The account of nonce 0. new_tok_ctrt (pv.TokCtrtWithoutSplit): The fixture that registers a new Token contract. new_ctrt (pv.PayChanCtrt): The fixture that registers a new Payment Channel contract. Returns: pv.PayChanCtrt: The PayChanCtrt instance. test_create_and_load tests the method create_and_load. Args: acnt0 (pv.Account): The account of nonce 0. acnt1 (pv.Account): The account of nonce 1. new_ctrt (pv.PayChanCtrt): The fixture that registers a new Payment Channel contract. Returns: str: The channel ID. test_extend_exp_time tests the method extend_exp_time. Args: acnt0 (pv.Account): The account of nonce 0. new_ctrt_with_chan (Tuple[pv.PayChanCtrt, str]): The fixture that registers a new Payment Channel contract and creates a new channel. test_load tests the method load. Args: acnt0 (pv.Account): The account of nonce 0. new_ctrt_with_chan (Tuple[pv.PayChanCtrt, str]): The fixture that registers a new Payment Channel contract and creates a new channel. test_abort tests the method abort. Args: acnt0 (pv.Account): The account of nonce 0. new_ctrt_with_chan (Tuple[pv.PayChanCtrt, str]): The fixture that registers a new Payment Channel contract and creates a new channel. test_unload tests the method unload. Args: acnt0 (pv.Account): The account of nonce 0. acnt1 (pv.Account): The account of nonce 1. new_ctrt (pv.PayChanCtrt): The fixture that registers a new Payment Channel contract. # create a channel # wait until the channel expires test_offchain_pay_and_collect_payment tests the method - offchain_pay - collect_payment. Args: acnt0 (pv.Account): The account of nonce 0. acnt1 (pv.Account): The account of nonce 1. new_ctrt_with_chan (Tuple[pv.PayChanCtrt, str]): The fixture that registers a new Payment Channel contract and creates a new channel. test_as_whole tests methods of PayChanCtrt as a whole so as to reduce resource consumption. Args: acnt0 (pv.Account): The account of nonce 0. acnt1 (pv.Account): The account of nonce 1. new_tok_ctrt (pv.TokCtrtWithoutSplit): The token contract instance. new_ctrt (pv.PayChanCtrt): The fixture that registers a new Payment Channel contract.
2.444988
2
cfgov/data_research/tests/test_views.py
thephillipsequation/cfgov-refresh
0
6632204
import datetime import json import unittest import django from django.core.urlresolvers import NoReverseMatch, reverse from model_bakery import baker from data_research.models import ( County, CountyMortgageData, MetroArea, MSAMortgageData, NationalMortgageData, NonMSAMortgageData, State, StateMortgageData ) from data_research.views import validate_year_month class YearMonthValidatorTests(unittest.TestCase): """check the year_month validator""" good_pair = '2016-09' future_year = '2040-08' too_old_year = '1957-08' bad_month = '2015-13' non_integer = '201A-12' bad_format = '201609' def test_validate_year_month_good(self): self.assertTrue(validate_year_month(self.good_pair)) def test_validate_year_month_future_year(self): self.assertFalse(validate_year_month(self.future_year)) def test_validate_year_month_too_old(self): self.assertFalse(validate_year_month(self.too_old_year)) def test_validate_year_month_bad_month(self): self.assertFalse(validate_year_month(self.bad_month)) def test_validate_year_month_non_integer(self): self.assertFalse(validate_year_month(self.non_integer)) def test_validate_year_month_bad_format(self): self.assertFalse(validate_year_month(self.bad_format)) class TimeseriesViewTests(django.test.TestCase): fixtures = ['mortgage_constants.json', 'mortgage_metadata.json'] def setUp(self): baker.make( State, fips='12', abbr='FL', ap_abbr='Fla.', counties=["12081"], msas=["52081"], name='Florida', non_msa_counties=["12001"], non_msa_valid=True) baker.make( County, fips='12081', name='<NAME>', state=State.objects.get(fips='12'), valid=True) baker.make( MetroArea, fips='35840', name='North Port-Sarasota-Bradenton, FL', states=["12"], counties=["12081", "12115"], valid=True) baker.make( MetroArea, fips='16220', name='<NAME>', states=["56"], counties=["12081", "12115"], valid=True) baker.make( NationalMortgageData, current=2500819, date=datetime.date(2008, 1, 1), fips='-----', id=1, ninety=40692, other=36196, sixty=27586, thirty=67668, total=2674899) baker.make( StateMortgageData, current=250081, date=datetime.date(2008, 1, 1), fips='12', id=1, state=State.objects.get(fips='12'), ninety=4069, other=3619, sixty=2758, thirty=6766, total=26748) baker.make( MSAMortgageData, current=5250, date=datetime.date(2008, 1, 1), msa=MetroArea.objects.get(fips='35840'), fips='35840', id=1, ninety=1406, other=361, sixty=1275, thirty=3676, total=22674) baker.make( NonMSAMortgageData, current=5250, date=datetime.date(2008, 1, 1), state=State.objects.get(fips='12'), fips='12-non', id=1, ninety=1406, other=361, sixty=1275, thirty=3676, total=22674) baker.make( CountyMortgageData, current=250, date=datetime.date(2008, 1, 1), county=County.objects.get(fips='12081'), fips='12081', id=1, ninety=406, other=361, sixty=275, thirty=676, total=2674) def test_metadata_request(self): response = self.client.get( reverse( 'data_research_api_metadata', kwargs={'meta_name': 'sampling_dates'})) self.assertEqual(response.status_code, 200) self.assertIn( '2008-01-01', json.loads(response.content) ) def test_metadata_request_bad_meta_name(self): response = self.client.get( reverse( 'data_research_api_metadata', kwargs={'meta_name': 'xxx'})) self.assertEqual(response.status_code, 200) self.assertContains(response, 'No metadata object found.') def test_national_timeseries_30_89(self): response = self.client.get( reverse( 'data_research_api_mortgage_timeseries_national', kwargs={'days_late': '30-89'})) self.assertEqual(response.status_code, 200) def test_national_timeseries_90(self): response = self.client.get( reverse( 'data_research_api_mortgage_timeseries_national', kwargs={'days_late': '90'})) self.assertEqual(response.status_code, 200) def test_state_timeseries_30_89(self): response = self.client.get( reverse( 'data_research_api_mortgage_timeseries', kwargs={'fips': '12', 'days_late': '30-89'})) self.assertEqual(response.status_code, 200) def test_state_timeseries_90(self): response = self.client.get( reverse( 'data_research_api_mortgage_timeseries', kwargs={'fips': '12', 'days_late': '90'})) self.assertEqual(response.status_code, 200) def test_msa_timeseries_30_89(self): response = self.client.get( reverse( 'data_research_api_mortgage_timeseries', kwargs={'fips': '35840', 'days_late': '30-89'})) self.assertEqual(response.status_code, 200) def test_msa_timeseries_90(self): response = self.client.get( reverse( 'data_research_api_mortgage_timeseries', kwargs={'fips': '35840', 'days_late': '90'})) self.assertEqual(response.status_code, 200) def test_msa_timeseries_90_below_threshold(self): response = self.client.get( reverse( 'data_research_api_mortgage_timeseries', kwargs={'fips': '16220', 'days_late': '90'})) self.assertEqual(response.status_code, 200) self.assertContains(response, 'not valid') def test_non_msa_timeseries_30_89(self): response = self.client.get( reverse( 'data_research_api_mortgage_timeseries', kwargs={'fips': '12-non', 'days_late': '30-89'})) self.assertEqual(response.status_code, 200) def test_non_msa_timeseries_90(self): response = self.client.get( reverse( 'data_research_api_mortgage_timeseries', kwargs={'fips': '12-non', 'days_late': '90'})) self.assertEqual(response.status_code, 200) def test_county_timeseries_30_89(self): response = self.client.get( reverse( 'data_research_api_mortgage_timeseries', kwargs={'fips': '12081', 'days_late': '30-89'})) self.assertEqual(response.status_code, 200) def test_county_timeseries_90(self): response = self.client.get( reverse( 'data_research_api_mortgage_timeseries', kwargs={'fips': '12081', 'days_late': '90'})) self.assertEqual(response.status_code, 200) def test_timeseries_bad_fips(self): response = self.client.get( reverse( 'data_research_api_mortgage_timeseries', kwargs={'fips': '99999', 'days_late': '90'})) self.assertEqual(response.status_code, 200) self.assertContains(response, 'FIPS code not found') def test_map_data_bad_date(self): response = self.client.get( reverse( 'data_research_api_mortgage_mapdata', kwargs={'geo': 'counties', 'days_late': '90', 'year_month': '0000-01'})) self.assertEqual(response.status_code, 200) self.assertContains(response, 'Invalid year-month pair') def test_map_data_disallowed_delinquency_digit(self): with self.assertRaises(NoReverseMatch): self.client.get(reverse( 'data_research_api_mortgage_mapdata', kwargs={'geo': 'counties', 'days_late': '100', 'year_month': '2008-01'})) def test_map_data_disallowed_delinquency_range(self): response = self.client.get(reverse( 'data_research_api_mortgage_mapdata', kwargs={'geo': 'counties', 'days_late': '38-89', 'year_month': '2008-01'})) self.assertEqual(response.status_code, 200) self.assertContains(response, 'Unknown delinquency range') def test_timeseries_disallowed_delinquency_range(self): response = self.client.get(reverse( 'data_research_api_mortgage_timeseries', kwargs={'fips': '12081', 'days_late': '38-89'})) self.assertEqual(response.status_code, 200) self.assertContains(response, 'Unknown delinquency range') def test_national_timeseries_disallowed_delinquency_range(self): response = self.client.get(reverse( 'data_research_api_mortgage_timeseries_national', kwargs={'days_late': '38-89'})) self.assertEqual(response.status_code, 200) self.assertContains(response, 'Unknown delinquency range') def test_map_data_unknown_geo(self): response = self.client.get( reverse( 'data_research_api_mortgage_mapdata', kwargs={'geo': 'parish', 'days_late': '90', 'year_month': '2008-01'})) self.assertEqual(response.status_code, 200) self.assertContains(response, 'Unkown geographic unit') def test_county_map_data_30_89(self): response = self.client.get( reverse( 'data_research_api_mortgage_mapdata', kwargs={'geo': 'counties', 'days_late': '30-89', 'year_month': '2008-01'})) self.assertEqual(response.status_code, 200) response_data = json.loads(response.content) self.assertEqual( sorted(response_data.get('data').get('12081').keys()), ['name', 'value']) def test_county_map_data_90(self): response = self.client.get( reverse( 'data_research_api_mortgage_mapdata', kwargs={'geo': 'counties', 'days_late': '90', 'year_month': '2008-01'})) self.assertEqual(response.status_code, 200) response_data = json.loads(response.content) self.assertEqual( sorted(response_data.get('data').get('12081').keys()), ['name', 'value']) def test_msa_map_data_30_89(self): response = self.client.get( reverse( 'data_research_api_mortgage_mapdata', kwargs={'geo': 'metros', 'days_late': '30-89', 'year_month': '2008-01'})) self.assertEqual(response.status_code, 200) def test_msa_map_data_90(self): response = self.client.get( reverse( 'data_research_api_mortgage_mapdata', kwargs={'geo': 'metros', 'days_late': '90', 'year_month': '2008-01'})) self.assertEqual(response.status_code, 200) def test_map_view_msa_below_threshold(self): """The view should deliver a below-threshold MSA with value of None""" msa = MSAMortgageData.objects.get(fips='35840') geo = msa.msa geo.valid = False geo.save() response = self.client.get( reverse( 'data_research_api_mortgage_mapdata', kwargs={'geo': 'metros', 'days_late': '90', 'year_month': '2008-01'})) self.assertEqual(response.status_code, 200) msa_value = json.loads(response.content)['data'][msa.fips]['value'] self.assertIs(msa_value, None) def test_map_view_non_msa_below_threshold(self): """Should deliver a below-threshold non-MSA with value of None""" non_msa = NonMSAMortgageData.objects.get(fips='12-non') geo = non_msa.state geo.non_msa_valid = False geo.save() response = self.client.get( reverse( 'data_research_api_mortgage_mapdata', kwargs={'geo': 'metros', 'days_late': '90', 'year_month': '2008-01'})) self.assertEqual(response.status_code, 200) msa_value = json.loads(response.content)['data'][non_msa.fips]['value'] self.assertIs(msa_value, None) def test_national_map_data_30_89(self): response = self.client.get( reverse( 'data_research_api_mortgage_mapdata', kwargs={'geo': 'national', 'days_late': '30-89', 'year_month': '2008-01'})) self.assertEqual(response.status_code, 200) def test_national_map_data_90(self): response = self.client.get( reverse( 'data_research_api_mortgage_mapdata', kwargs={'geo': 'national', 'days_late': '90', 'year_month': '2008-01'})) self.assertEqual(response.status_code, 200) def test_county_timeseries_data_invalid(self): county = County.objects.get(fips='12081') county.valid = False county.save() response = self.client.get( reverse( 'data_research_api_mortgage_timeseries', kwargs={'fips': '12081', 'days_late': '90'})) self.assertEqual(response.status_code, 200) self.assertContains(response, 'County is below display threshold')
import datetime import json import unittest import django from django.core.urlresolvers import NoReverseMatch, reverse from model_bakery import baker from data_research.models import ( County, CountyMortgageData, MetroArea, MSAMortgageData, NationalMortgageData, NonMSAMortgageData, State, StateMortgageData ) from data_research.views import validate_year_month class YearMonthValidatorTests(unittest.TestCase): """check the year_month validator""" good_pair = '2016-09' future_year = '2040-08' too_old_year = '1957-08' bad_month = '2015-13' non_integer = '201A-12' bad_format = '201609' def test_validate_year_month_good(self): self.assertTrue(validate_year_month(self.good_pair)) def test_validate_year_month_future_year(self): self.assertFalse(validate_year_month(self.future_year)) def test_validate_year_month_too_old(self): self.assertFalse(validate_year_month(self.too_old_year)) def test_validate_year_month_bad_month(self): self.assertFalse(validate_year_month(self.bad_month)) def test_validate_year_month_non_integer(self): self.assertFalse(validate_year_month(self.non_integer)) def test_validate_year_month_bad_format(self): self.assertFalse(validate_year_month(self.bad_format)) class TimeseriesViewTests(django.test.TestCase): fixtures = ['mortgage_constants.json', 'mortgage_metadata.json'] def setUp(self): baker.make( State, fips='12', abbr='FL', ap_abbr='Fla.', counties=["12081"], msas=["52081"], name='Florida', non_msa_counties=["12001"], non_msa_valid=True) baker.make( County, fips='12081', name='<NAME>', state=State.objects.get(fips='12'), valid=True) baker.make( MetroArea, fips='35840', name='North Port-Sarasota-Bradenton, FL', states=["12"], counties=["12081", "12115"], valid=True) baker.make( MetroArea, fips='16220', name='<NAME>', states=["56"], counties=["12081", "12115"], valid=True) baker.make( NationalMortgageData, current=2500819, date=datetime.date(2008, 1, 1), fips='-----', id=1, ninety=40692, other=36196, sixty=27586, thirty=67668, total=2674899) baker.make( StateMortgageData, current=250081, date=datetime.date(2008, 1, 1), fips='12', id=1, state=State.objects.get(fips='12'), ninety=4069, other=3619, sixty=2758, thirty=6766, total=26748) baker.make( MSAMortgageData, current=5250, date=datetime.date(2008, 1, 1), msa=MetroArea.objects.get(fips='35840'), fips='35840', id=1, ninety=1406, other=361, sixty=1275, thirty=3676, total=22674) baker.make( NonMSAMortgageData, current=5250, date=datetime.date(2008, 1, 1), state=State.objects.get(fips='12'), fips='12-non', id=1, ninety=1406, other=361, sixty=1275, thirty=3676, total=22674) baker.make( CountyMortgageData, current=250, date=datetime.date(2008, 1, 1), county=County.objects.get(fips='12081'), fips='12081', id=1, ninety=406, other=361, sixty=275, thirty=676, total=2674) def test_metadata_request(self): response = self.client.get( reverse( 'data_research_api_metadata', kwargs={'meta_name': 'sampling_dates'})) self.assertEqual(response.status_code, 200) self.assertIn( '2008-01-01', json.loads(response.content) ) def test_metadata_request_bad_meta_name(self): response = self.client.get( reverse( 'data_research_api_metadata', kwargs={'meta_name': 'xxx'})) self.assertEqual(response.status_code, 200) self.assertContains(response, 'No metadata object found.') def test_national_timeseries_30_89(self): response = self.client.get( reverse( 'data_research_api_mortgage_timeseries_national', kwargs={'days_late': '30-89'})) self.assertEqual(response.status_code, 200) def test_national_timeseries_90(self): response = self.client.get( reverse( 'data_research_api_mortgage_timeseries_national', kwargs={'days_late': '90'})) self.assertEqual(response.status_code, 200) def test_state_timeseries_30_89(self): response = self.client.get( reverse( 'data_research_api_mortgage_timeseries', kwargs={'fips': '12', 'days_late': '30-89'})) self.assertEqual(response.status_code, 200) def test_state_timeseries_90(self): response = self.client.get( reverse( 'data_research_api_mortgage_timeseries', kwargs={'fips': '12', 'days_late': '90'})) self.assertEqual(response.status_code, 200) def test_msa_timeseries_30_89(self): response = self.client.get( reverse( 'data_research_api_mortgage_timeseries', kwargs={'fips': '35840', 'days_late': '30-89'})) self.assertEqual(response.status_code, 200) def test_msa_timeseries_90(self): response = self.client.get( reverse( 'data_research_api_mortgage_timeseries', kwargs={'fips': '35840', 'days_late': '90'})) self.assertEqual(response.status_code, 200) def test_msa_timeseries_90_below_threshold(self): response = self.client.get( reverse( 'data_research_api_mortgage_timeseries', kwargs={'fips': '16220', 'days_late': '90'})) self.assertEqual(response.status_code, 200) self.assertContains(response, 'not valid') def test_non_msa_timeseries_30_89(self): response = self.client.get( reverse( 'data_research_api_mortgage_timeseries', kwargs={'fips': '12-non', 'days_late': '30-89'})) self.assertEqual(response.status_code, 200) def test_non_msa_timeseries_90(self): response = self.client.get( reverse( 'data_research_api_mortgage_timeseries', kwargs={'fips': '12-non', 'days_late': '90'})) self.assertEqual(response.status_code, 200) def test_county_timeseries_30_89(self): response = self.client.get( reverse( 'data_research_api_mortgage_timeseries', kwargs={'fips': '12081', 'days_late': '30-89'})) self.assertEqual(response.status_code, 200) def test_county_timeseries_90(self): response = self.client.get( reverse( 'data_research_api_mortgage_timeseries', kwargs={'fips': '12081', 'days_late': '90'})) self.assertEqual(response.status_code, 200) def test_timeseries_bad_fips(self): response = self.client.get( reverse( 'data_research_api_mortgage_timeseries', kwargs={'fips': '99999', 'days_late': '90'})) self.assertEqual(response.status_code, 200) self.assertContains(response, 'FIPS code not found') def test_map_data_bad_date(self): response = self.client.get( reverse( 'data_research_api_mortgage_mapdata', kwargs={'geo': 'counties', 'days_late': '90', 'year_month': '0000-01'})) self.assertEqual(response.status_code, 200) self.assertContains(response, 'Invalid year-month pair') def test_map_data_disallowed_delinquency_digit(self): with self.assertRaises(NoReverseMatch): self.client.get(reverse( 'data_research_api_mortgage_mapdata', kwargs={'geo': 'counties', 'days_late': '100', 'year_month': '2008-01'})) def test_map_data_disallowed_delinquency_range(self): response = self.client.get(reverse( 'data_research_api_mortgage_mapdata', kwargs={'geo': 'counties', 'days_late': '38-89', 'year_month': '2008-01'})) self.assertEqual(response.status_code, 200) self.assertContains(response, 'Unknown delinquency range') def test_timeseries_disallowed_delinquency_range(self): response = self.client.get(reverse( 'data_research_api_mortgage_timeseries', kwargs={'fips': '12081', 'days_late': '38-89'})) self.assertEqual(response.status_code, 200) self.assertContains(response, 'Unknown delinquency range') def test_national_timeseries_disallowed_delinquency_range(self): response = self.client.get(reverse( 'data_research_api_mortgage_timeseries_national', kwargs={'days_late': '38-89'})) self.assertEqual(response.status_code, 200) self.assertContains(response, 'Unknown delinquency range') def test_map_data_unknown_geo(self): response = self.client.get( reverse( 'data_research_api_mortgage_mapdata', kwargs={'geo': 'parish', 'days_late': '90', 'year_month': '2008-01'})) self.assertEqual(response.status_code, 200) self.assertContains(response, 'Unkown geographic unit') def test_county_map_data_30_89(self): response = self.client.get( reverse( 'data_research_api_mortgage_mapdata', kwargs={'geo': 'counties', 'days_late': '30-89', 'year_month': '2008-01'})) self.assertEqual(response.status_code, 200) response_data = json.loads(response.content) self.assertEqual( sorted(response_data.get('data').get('12081').keys()), ['name', 'value']) def test_county_map_data_90(self): response = self.client.get( reverse( 'data_research_api_mortgage_mapdata', kwargs={'geo': 'counties', 'days_late': '90', 'year_month': '2008-01'})) self.assertEqual(response.status_code, 200) response_data = json.loads(response.content) self.assertEqual( sorted(response_data.get('data').get('12081').keys()), ['name', 'value']) def test_msa_map_data_30_89(self): response = self.client.get( reverse( 'data_research_api_mortgage_mapdata', kwargs={'geo': 'metros', 'days_late': '30-89', 'year_month': '2008-01'})) self.assertEqual(response.status_code, 200) def test_msa_map_data_90(self): response = self.client.get( reverse( 'data_research_api_mortgage_mapdata', kwargs={'geo': 'metros', 'days_late': '90', 'year_month': '2008-01'})) self.assertEqual(response.status_code, 200) def test_map_view_msa_below_threshold(self): """The view should deliver a below-threshold MSA with value of None""" msa = MSAMortgageData.objects.get(fips='35840') geo = msa.msa geo.valid = False geo.save() response = self.client.get( reverse( 'data_research_api_mortgage_mapdata', kwargs={'geo': 'metros', 'days_late': '90', 'year_month': '2008-01'})) self.assertEqual(response.status_code, 200) msa_value = json.loads(response.content)['data'][msa.fips]['value'] self.assertIs(msa_value, None) def test_map_view_non_msa_below_threshold(self): """Should deliver a below-threshold non-MSA with value of None""" non_msa = NonMSAMortgageData.objects.get(fips='12-non') geo = non_msa.state geo.non_msa_valid = False geo.save() response = self.client.get( reverse( 'data_research_api_mortgage_mapdata', kwargs={'geo': 'metros', 'days_late': '90', 'year_month': '2008-01'})) self.assertEqual(response.status_code, 200) msa_value = json.loads(response.content)['data'][non_msa.fips]['value'] self.assertIs(msa_value, None) def test_national_map_data_30_89(self): response = self.client.get( reverse( 'data_research_api_mortgage_mapdata', kwargs={'geo': 'national', 'days_late': '30-89', 'year_month': '2008-01'})) self.assertEqual(response.status_code, 200) def test_national_map_data_90(self): response = self.client.get( reverse( 'data_research_api_mortgage_mapdata', kwargs={'geo': 'national', 'days_late': '90', 'year_month': '2008-01'})) self.assertEqual(response.status_code, 200) def test_county_timeseries_data_invalid(self): county = County.objects.get(fips='12081') county.valid = False county.save() response = self.client.get( reverse( 'data_research_api_mortgage_timeseries', kwargs={'fips': '12081', 'days_late': '90'})) self.assertEqual(response.status_code, 200) self.assertContains(response, 'County is below display threshold')
en
0.811758
check the year_month validator The view should deliver a below-threshold MSA with value of None Should deliver a below-threshold non-MSA with value of None
2.475304
2
gdutils/datamine.py
InnovativeInventor/gdutils
0
6632205
""" gdutils.datamine ================ Provides - A ``python`` module for mining and listing data sources. Metadata -------- :Module: ``gdutils.datamine`` :Filename: `datamine.py <https://github.com/mggg/gdutils/>`_ :Author: `@KeiferC <https://github.com/keiferc>`_ :Date: 27 July 2020 :Version: 1.1.0 :Description: Module for data mining :Contributors: `@InnovativeInventor <https://github.com/InnovativeInventor>`_ Documentation ------------- Documentation for the ``datamine`` module can be found as docstrings. Run ``import gdutils.datamine; help(gdutils.datamine)`` to view documentation. :: $ python >>> import gdutils.datamine; help(gdutils.datamine) Additionally, documentation can be found on `Read the Docs <https://gdutils.readthedocs.io>`_. """ import json import os import pathlib import requests import subprocess import sys import urllib.parse from typing import (Dict, Hashable, Iterable, List, NoReturn, Optional, Tuple, Union) ######################################### # # # Function Definitions # # # ######################################### def list_gh_repos(account: str, account_type: str) -> List[Tuple[str, str]]: """ Returns a list of tuples of public GitHub repositories and their URLs associated with the given account and account type. Parameters ---------- account : str Github account whose public repos are to be cloned. account_type: str Type of github account whose public repos are to be cloned. Valid options: ``'users'``, ``'orgs'``. Returns ------- List[Tuple[str, str]] A list of tuples of public Github repositories and their URLs. E.g. :: [('boysenberry-repo-1', 'https://github.com/octocat/boysenberry-repo-1.git'), ('git-consortium', 'https://github.com/octocat/git-consortium.git'), ... ('test-repo1', https://github.com/octocat/test-repo1.git)] Raises ------ ValueError Raised if the given account_type is neither ``'users'`` nor ``'orgs'``. RuntimeError Raised if unable to query GitHub for repo information. Examples -------- >>> repos = datamine.list_gh_repos('octocat', 'users') # gets a list of all repos and their GitHub URLs for account 'octocat' >>> for repo, url in repos: ... print('{} : {}'.format(repo, url)) boysenberry-repo-1 : https://github.com/octocat/boysenberry-repo-1.git git-consortium : https://github.com/octocat/git-consortium.git hello-worId : https://github.com/octocat/hello-worId.git Hello-World : https://github.com/octocat/Hello-World.git linguist : https://github.com/octocat/linguist.git octocat.github.io : https://github.com/octocat/octocat.github.io.git Spoon-Knife : https://github.com/octocat/Spoon-Knife.git test-repo1 : https://github.com/octocat/test-repo1.git """ valid_acc_types = ['users', 'orgs'] gh_api = 'https://api.github.com' gh_endpt = 'repos' if account_type not in valid_acc_types: raise ValueError( "Invalid account type. Valid options: {}.".format(valid_acc_types)) gh_api_url = gh_api + '/' + account_type + '/' + account + '/' + gh_endpt raw_response = requests.get(gh_api_url) response = json.loads(raw_response.text) try: return [(__get_repo_name(repo['clone_url']), repo['clone_url']) for repo in response] except Exception: msg = "Unable to list repos for account {}.".format(account) try: raise RuntimeError(msg + response['message']) except: raise RuntimeError(msg + e) def clone_gh_repos(account: str, account_type: str, repos: Optional[List[str]] = None, outpath: Optional[Union[str, pathlib.Path]] = None, shallow: bool = True, silent: bool = False ) -> NoReturn: """ Clones public GitHub repositories into the given directory. If directory path is not provided, clones repos into the current working directory. Parameters ---------- account : str GitHub account whose public repos are to be cloned. account_type : str Type of GitHub account whose public repos are to be cloned. Valid options: ``'users'``, ``'orgs'``. repos : List[str], optional, default = ``None`` List of specific repositories to clone. outpath : str | pathlib.Path, optional, default = ``None`` Path to which repos are to be cloned. If not specified, clones repos into current working directory. shallow : bool | optional, default = ``True`` Determines whether the clone will be shallow or not. If not specified, defaults to a shallow git clone. silent : bool | optional, default = ``False`` Determines whether the clone will be silent or not. If not specified, defaults to a loud git clone. Raises ------ ValueError Raised if provided an account type other than ``'users'`` or ``'orgs'``. Examples -------- >>> datamine.clone_repos('mggg-states', 'orgs') # clones all repositories of 'mggg-states' into the current directory >>> datamine.clone_repos('mggg-states', 'orgs', ['AZ-shapefiles']) # clones repo 'AZ-shapefiles' from 'mggg-states' into current directory >>> datamine.clone_repos('mggg-states', 'orgs', ... ['AZ-shapefiles', 'HI-shapefiles']) # clones repos 'AZ-shapefiles' & 'HI-shapefiles' into current directory >>> datamine.clone_repos('mggg-states', 'orgs', ['HI-shapefiles'], 'shps/') # clones repo 'HI-shapefiles' into directory 'shps/' >>> datamine.clone_repos('octocat', 'users', outpath='cloned-repos/') # clones all repos of 'octocat' into directory 'cloned-repos/' >>> datamine.clone_repos('octocat', 'users', outpath='cloned-repos/', ... shallow=False) # deep clones all repos of 'octocat' into directory 'cloned-repos/' >>> datamine.clone_repos('octocat', 'users', outpath='cloned-repos/', ... silent=True) # silently deep clones all repos of 'octocat' into directory 'cloned-repos/' """ try: if repos is None: queried_repos = [repo for _, repo in list_gh_repos(account, account_type)] cmds = __generate_clone_cmds(queried_repos, outpath, shallow=shallow) else: repo_urls = [__create_gh_repo_url(account, rname) for rname in repos] cmds = __generate_clone_cmds(repo_urls, outpath, shallow=shallow) if silent: responses = list(map(lambda cmd : subprocess.run(cmd, stderr=open(os.devnull, 'wb'), stdout=open(os.devnull, 'wb')), cmds)) else: responses = list(map(lambda cmd : subprocess.run(cmd), cmds)) for res in responses: if res.returncode != 0: sys.stderr.write("Failed to clone {}.\n".format(res.args[2])) except Exception as e: raise RuntimeError("Unable to clone repos. {}".format(e)) def remove_repos(dirpath: Union[str, pathlib.Path]) -> NoReturn: """ Given a name/path of a directory, recursively removes all git repositories starting from the given directory. This action cannot be undone. *Warning:* this function will remove the given directory if the given directory itself is a git repo. Parameters ---------- dirpath: str | pathlib.Path Name/path of directory from which recursive removal of repos begins. Raises ------ FileNotFoundError Raised if unable to find the given directory. Examples -------- >>> datamine.remove_repos('repos_to_remove/') # removes all repos in directory 'repos_to_remove/' >>> datamine.remove_repos('repos_to_remove/repo1') # removes repo 'repo1' in directory 'repos_to_remove/' """ try: repos = __list_repos(dirpath) cmds = [['rm', '-rf', repo] for repo in repos] responses = list(map(lambda cmd : subprocess.run(cmd), cmds)) for res in responses: if res.returncode != 0: sys.stderr.write("Failed to remove repo {}.\n".format(res.args[2])) except Exception as e: raise RuntimeError("Unable to remove repo. {}".format(e)) def list_files_of_type(filetype: Union[str, List[str]], dirpath: Optional[Union[str, pathlib.Path]] = '.', exclude_hidden: Optional[bool] = True ) -> List[str]: """ Given a file extension and an optional directory path, returns a list of file paths of files containing the extension. If the directory path is not specified, function defaults to listing files from the current working directory. Parameters ---------- filetype: str | List[str] File extension of files to list (e.g. ``'.zip'``). Can be a list of extensions (e.g. ``['.zip', '.shp', '.csv']``). dirpath: str | pathlib.Path, optional, default = ``'.'``. Path to directory from which file listing begins. Defaults to current working directory if not specified. exclude_hidden: bool, option, default = ``True`` If false, function includes hidden files in the search. Returns ------- List[str] List of file paths of files containing the given extension. Raises ------ FileNotFoundError Raised if unable to find given directory. Examples -------- >>> list_of_zips = datamine.list_files_of_type('.zip') # recursively gets a list of '.zip' files from the current directory >>> print(list_of_zips) ['./zipfile1.zip', './zipfile2.zip', './shapefiles/shape1.zip', './shapefiles/shape2.zip'] >>> list_of_shps = datamine.list_files_of_type('.shp', 'shapefiles/') # recursively gets a list of '.shp' files from the 'shapefiles/' directory >>> print(list_of_shps) ['./shapefiles/shape1/shape1.shp', './shapefiles/shape2/shape2.shp'] >>> list_of_csvs = datamine.list_files_of_type('.csv', ... exclude_hidden = False) # recursively gets a list of '.csv' files, including hidden files >>> print(list_of_csvs) ['./csv1.csv', './.csv_hidden.csv'] >>> list_of_mix = datamine.list_files_of_type(['.shp', '.zip']) # recursively gets a list of '.shp' and '.zip' files >>> print(list_of_mix) ['./shapefiles/shape1/shape1.shp', './shapefiles/shape2/shape2.shp', './zipfile1.zip', './zipfile2.zip', './shapefiles/shape1.zip', './shapefiles/shape2.zip'] """ root_path = __get_validated_path(dirpath) if isinstance(filetype, str): filetype = [filetype] all_files = [] for path, _, files in os.walk(root_path): [all_files.append(os.path.join(path, file)) for file in files if not (exclude_hidden and file[0] == '.')] return [file for file in all_files if any([file.endswith(ftype) for ftype in filetype])] def get_keys_by_category(dictionary: Dict[Hashable, List[Iterable]], category: Union[Hashable, List[Hashable]] ) -> List[Hashable]: """ Given a dictionary with categories, returns a list of keys in the given category. Examples of accepted forms of dictionary input: :: {category1 : [{key1 : value1}, {key2 : value2}] category2 : [{key3 : value3},]} :: {category1 : [[key1, key2, key3]]} :: {category1 : [[key1]], category2 : [[key2], {key3: value3}]} Parameters ---------- dictionary : Dict[Hashable, List[Iterable]] Dictionary containing categories in which keys are stored. category : Hashable | List[Hashable] Category containing keys. Returns ------- List[Hashable] List of keys of every key-value pair in the given category of the given dictionary. Examples -------- >>> sample_dict = {'category1' : [{'key1': 1}], ... 'category2' : [{'key2' : 2}, {'key3' : 3}]} >>> keys = datamine.get_keys_by_category(sample_dict, 'category2') # gets a list of keys under 'category2' from the dictionary 'sample_dict' >>> print(keys) ['key2', 'key3'] >>> sample_dict = {'category1' : [['key1', 'key4']], ... 'category2' : [['key2'], {'key3': 'value3'}]} >>> keys = datamine.get_keys_by_category(sample_dict, 'category2') # note: keys can be stored in both list and dictionary form >>> print(keys) ['key2', 'key3'] >>> keys = datamine.get_keys_by_category(sample_dict, ... ['category1', 'category2']) # gets a list of keys under categories 'category1' and 'category2' >>> print(keys) ['key1', 'key2', 'key3'] """ flatten = lambda xs : [x for sublist in xs for x in sublist] try: return flatten([list(key) for key in dictionary[category]]) except: # category is a list return flatten([list(key) for item in category for key in dictionary[item]]) ######################################### # # # Helper Definitions # # # ######################################### def __generate_clone_cmds( repos: Optional[Union[Dict[str, str], List[str]]] = None, dirpath: Optional[Union[str, pathlib.Path]] = None, shallow: bool = True ) -> List[str]: """ Given a list of repos, returns a list of subprocess-valid git clone commands. """ try: # if repos is a Dict - EAFP cmds = [['git', 'clone', repo['clone_url']] for repo in repos] except Exception: pass try: # if repos is a List - EAFP cmds = [['git', 'clone', repo] for repo in repos] except Exception as e: raise RuntimeError( 'Unable to generate clone commands. {}'.format(e)) if dirpath is not None: [cmd.append(os.path.join(dirpath, __get_repo_name(cmd[2]))) for cmd in cmds] if shallow: [cmd.extend(['--depth', '1']) for cmd in cmds] return cmds def __get_repo_name(url: str) -> str: """ Returns the name of the repository from its given URL. """ parsed = urllib.parse.urlparse(url) name = os.path.basename(parsed.path) if name.endswith('.git'): name = name[:-4] return name def __create_gh_repo_url(account: str, repo: str) -> str: """ Given an account name and a repo name, returns a cloneable gh repo url. """ return 'https://github.com/' + account + '/' + repo + '.git' def __list_repos(dirpath: Optional[Union[str, pathlib.Path]] = '.' ) -> List[str]: """ Given a starting search directory, returns a list of paths to git repos on the local machine. """ root_path = __get_validated_path(dirpath) subdirs = [] for path, dirs, _ in os.walk(root_path): [subdirs.append(os.path.join(path, directory)) for directory in dirs] return [str(pathlib.Path(subdir).parent) for subdir in subdirs if pathlib.Path(subdir).name == '.git'] def __get_validated_path(dirpath: Union[str, pathlib.Path]) -> pathlib.Path: try: root_path = pathlib.Path(dirpath) if not os.path.isdir(root_path): raise FileNotFoundError("'{}.'".format(dirpath)) return root_path except FileNotFoundError as e: raise FileNotFoundError("Unable to find directory", e) except Exception as e: raise Exception("Failed to traverse path.".format(e))
""" gdutils.datamine ================ Provides - A ``python`` module for mining and listing data sources. Metadata -------- :Module: ``gdutils.datamine`` :Filename: `datamine.py <https://github.com/mggg/gdutils/>`_ :Author: `@KeiferC <https://github.com/keiferc>`_ :Date: 27 July 2020 :Version: 1.1.0 :Description: Module for data mining :Contributors: `@InnovativeInventor <https://github.com/InnovativeInventor>`_ Documentation ------------- Documentation for the ``datamine`` module can be found as docstrings. Run ``import gdutils.datamine; help(gdutils.datamine)`` to view documentation. :: $ python >>> import gdutils.datamine; help(gdutils.datamine) Additionally, documentation can be found on `Read the Docs <https://gdutils.readthedocs.io>`_. """ import json import os import pathlib import requests import subprocess import sys import urllib.parse from typing import (Dict, Hashable, Iterable, List, NoReturn, Optional, Tuple, Union) ######################################### # # # Function Definitions # # # ######################################### def list_gh_repos(account: str, account_type: str) -> List[Tuple[str, str]]: """ Returns a list of tuples of public GitHub repositories and their URLs associated with the given account and account type. Parameters ---------- account : str Github account whose public repos are to be cloned. account_type: str Type of github account whose public repos are to be cloned. Valid options: ``'users'``, ``'orgs'``. Returns ------- List[Tuple[str, str]] A list of tuples of public Github repositories and their URLs. E.g. :: [('boysenberry-repo-1', 'https://github.com/octocat/boysenberry-repo-1.git'), ('git-consortium', 'https://github.com/octocat/git-consortium.git'), ... ('test-repo1', https://github.com/octocat/test-repo1.git)] Raises ------ ValueError Raised if the given account_type is neither ``'users'`` nor ``'orgs'``. RuntimeError Raised if unable to query GitHub for repo information. Examples -------- >>> repos = datamine.list_gh_repos('octocat', 'users') # gets a list of all repos and their GitHub URLs for account 'octocat' >>> for repo, url in repos: ... print('{} : {}'.format(repo, url)) boysenberry-repo-1 : https://github.com/octocat/boysenberry-repo-1.git git-consortium : https://github.com/octocat/git-consortium.git hello-worId : https://github.com/octocat/hello-worId.git Hello-World : https://github.com/octocat/Hello-World.git linguist : https://github.com/octocat/linguist.git octocat.github.io : https://github.com/octocat/octocat.github.io.git Spoon-Knife : https://github.com/octocat/Spoon-Knife.git test-repo1 : https://github.com/octocat/test-repo1.git """ valid_acc_types = ['users', 'orgs'] gh_api = 'https://api.github.com' gh_endpt = 'repos' if account_type not in valid_acc_types: raise ValueError( "Invalid account type. Valid options: {}.".format(valid_acc_types)) gh_api_url = gh_api + '/' + account_type + '/' + account + '/' + gh_endpt raw_response = requests.get(gh_api_url) response = json.loads(raw_response.text) try: return [(__get_repo_name(repo['clone_url']), repo['clone_url']) for repo in response] except Exception: msg = "Unable to list repos for account {}.".format(account) try: raise RuntimeError(msg + response['message']) except: raise RuntimeError(msg + e) def clone_gh_repos(account: str, account_type: str, repos: Optional[List[str]] = None, outpath: Optional[Union[str, pathlib.Path]] = None, shallow: bool = True, silent: bool = False ) -> NoReturn: """ Clones public GitHub repositories into the given directory. If directory path is not provided, clones repos into the current working directory. Parameters ---------- account : str GitHub account whose public repos are to be cloned. account_type : str Type of GitHub account whose public repos are to be cloned. Valid options: ``'users'``, ``'orgs'``. repos : List[str], optional, default = ``None`` List of specific repositories to clone. outpath : str | pathlib.Path, optional, default = ``None`` Path to which repos are to be cloned. If not specified, clones repos into current working directory. shallow : bool | optional, default = ``True`` Determines whether the clone will be shallow or not. If not specified, defaults to a shallow git clone. silent : bool | optional, default = ``False`` Determines whether the clone will be silent or not. If not specified, defaults to a loud git clone. Raises ------ ValueError Raised if provided an account type other than ``'users'`` or ``'orgs'``. Examples -------- >>> datamine.clone_repos('mggg-states', 'orgs') # clones all repositories of 'mggg-states' into the current directory >>> datamine.clone_repos('mggg-states', 'orgs', ['AZ-shapefiles']) # clones repo 'AZ-shapefiles' from 'mggg-states' into current directory >>> datamine.clone_repos('mggg-states', 'orgs', ... ['AZ-shapefiles', 'HI-shapefiles']) # clones repos 'AZ-shapefiles' & 'HI-shapefiles' into current directory >>> datamine.clone_repos('mggg-states', 'orgs', ['HI-shapefiles'], 'shps/') # clones repo 'HI-shapefiles' into directory 'shps/' >>> datamine.clone_repos('octocat', 'users', outpath='cloned-repos/') # clones all repos of 'octocat' into directory 'cloned-repos/' >>> datamine.clone_repos('octocat', 'users', outpath='cloned-repos/', ... shallow=False) # deep clones all repos of 'octocat' into directory 'cloned-repos/' >>> datamine.clone_repos('octocat', 'users', outpath='cloned-repos/', ... silent=True) # silently deep clones all repos of 'octocat' into directory 'cloned-repos/' """ try: if repos is None: queried_repos = [repo for _, repo in list_gh_repos(account, account_type)] cmds = __generate_clone_cmds(queried_repos, outpath, shallow=shallow) else: repo_urls = [__create_gh_repo_url(account, rname) for rname in repos] cmds = __generate_clone_cmds(repo_urls, outpath, shallow=shallow) if silent: responses = list(map(lambda cmd : subprocess.run(cmd, stderr=open(os.devnull, 'wb'), stdout=open(os.devnull, 'wb')), cmds)) else: responses = list(map(lambda cmd : subprocess.run(cmd), cmds)) for res in responses: if res.returncode != 0: sys.stderr.write("Failed to clone {}.\n".format(res.args[2])) except Exception as e: raise RuntimeError("Unable to clone repos. {}".format(e)) def remove_repos(dirpath: Union[str, pathlib.Path]) -> NoReturn: """ Given a name/path of a directory, recursively removes all git repositories starting from the given directory. This action cannot be undone. *Warning:* this function will remove the given directory if the given directory itself is a git repo. Parameters ---------- dirpath: str | pathlib.Path Name/path of directory from which recursive removal of repos begins. Raises ------ FileNotFoundError Raised if unable to find the given directory. Examples -------- >>> datamine.remove_repos('repos_to_remove/') # removes all repos in directory 'repos_to_remove/' >>> datamine.remove_repos('repos_to_remove/repo1') # removes repo 'repo1' in directory 'repos_to_remove/' """ try: repos = __list_repos(dirpath) cmds = [['rm', '-rf', repo] for repo in repos] responses = list(map(lambda cmd : subprocess.run(cmd), cmds)) for res in responses: if res.returncode != 0: sys.stderr.write("Failed to remove repo {}.\n".format(res.args[2])) except Exception as e: raise RuntimeError("Unable to remove repo. {}".format(e)) def list_files_of_type(filetype: Union[str, List[str]], dirpath: Optional[Union[str, pathlib.Path]] = '.', exclude_hidden: Optional[bool] = True ) -> List[str]: """ Given a file extension and an optional directory path, returns a list of file paths of files containing the extension. If the directory path is not specified, function defaults to listing files from the current working directory. Parameters ---------- filetype: str | List[str] File extension of files to list (e.g. ``'.zip'``). Can be a list of extensions (e.g. ``['.zip', '.shp', '.csv']``). dirpath: str | pathlib.Path, optional, default = ``'.'``. Path to directory from which file listing begins. Defaults to current working directory if not specified. exclude_hidden: bool, option, default = ``True`` If false, function includes hidden files in the search. Returns ------- List[str] List of file paths of files containing the given extension. Raises ------ FileNotFoundError Raised if unable to find given directory. Examples -------- >>> list_of_zips = datamine.list_files_of_type('.zip') # recursively gets a list of '.zip' files from the current directory >>> print(list_of_zips) ['./zipfile1.zip', './zipfile2.zip', './shapefiles/shape1.zip', './shapefiles/shape2.zip'] >>> list_of_shps = datamine.list_files_of_type('.shp', 'shapefiles/') # recursively gets a list of '.shp' files from the 'shapefiles/' directory >>> print(list_of_shps) ['./shapefiles/shape1/shape1.shp', './shapefiles/shape2/shape2.shp'] >>> list_of_csvs = datamine.list_files_of_type('.csv', ... exclude_hidden = False) # recursively gets a list of '.csv' files, including hidden files >>> print(list_of_csvs) ['./csv1.csv', './.csv_hidden.csv'] >>> list_of_mix = datamine.list_files_of_type(['.shp', '.zip']) # recursively gets a list of '.shp' and '.zip' files >>> print(list_of_mix) ['./shapefiles/shape1/shape1.shp', './shapefiles/shape2/shape2.shp', './zipfile1.zip', './zipfile2.zip', './shapefiles/shape1.zip', './shapefiles/shape2.zip'] """ root_path = __get_validated_path(dirpath) if isinstance(filetype, str): filetype = [filetype] all_files = [] for path, _, files in os.walk(root_path): [all_files.append(os.path.join(path, file)) for file in files if not (exclude_hidden and file[0] == '.')] return [file for file in all_files if any([file.endswith(ftype) for ftype in filetype])] def get_keys_by_category(dictionary: Dict[Hashable, List[Iterable]], category: Union[Hashable, List[Hashable]] ) -> List[Hashable]: """ Given a dictionary with categories, returns a list of keys in the given category. Examples of accepted forms of dictionary input: :: {category1 : [{key1 : value1}, {key2 : value2}] category2 : [{key3 : value3},]} :: {category1 : [[key1, key2, key3]]} :: {category1 : [[key1]], category2 : [[key2], {key3: value3}]} Parameters ---------- dictionary : Dict[Hashable, List[Iterable]] Dictionary containing categories in which keys are stored. category : Hashable | List[Hashable] Category containing keys. Returns ------- List[Hashable] List of keys of every key-value pair in the given category of the given dictionary. Examples -------- >>> sample_dict = {'category1' : [{'key1': 1}], ... 'category2' : [{'key2' : 2}, {'key3' : 3}]} >>> keys = datamine.get_keys_by_category(sample_dict, 'category2') # gets a list of keys under 'category2' from the dictionary 'sample_dict' >>> print(keys) ['key2', 'key3'] >>> sample_dict = {'category1' : [['key1', 'key4']], ... 'category2' : [['key2'], {'key3': 'value3'}]} >>> keys = datamine.get_keys_by_category(sample_dict, 'category2') # note: keys can be stored in both list and dictionary form >>> print(keys) ['key2', 'key3'] >>> keys = datamine.get_keys_by_category(sample_dict, ... ['category1', 'category2']) # gets a list of keys under categories 'category1' and 'category2' >>> print(keys) ['key1', 'key2', 'key3'] """ flatten = lambda xs : [x for sublist in xs for x in sublist] try: return flatten([list(key) for key in dictionary[category]]) except: # category is a list return flatten([list(key) for item in category for key in dictionary[item]]) ######################################### # # # Helper Definitions # # # ######################################### def __generate_clone_cmds( repos: Optional[Union[Dict[str, str], List[str]]] = None, dirpath: Optional[Union[str, pathlib.Path]] = None, shallow: bool = True ) -> List[str]: """ Given a list of repos, returns a list of subprocess-valid git clone commands. """ try: # if repos is a Dict - EAFP cmds = [['git', 'clone', repo['clone_url']] for repo in repos] except Exception: pass try: # if repos is a List - EAFP cmds = [['git', 'clone', repo] for repo in repos] except Exception as e: raise RuntimeError( 'Unable to generate clone commands. {}'.format(e)) if dirpath is not None: [cmd.append(os.path.join(dirpath, __get_repo_name(cmd[2]))) for cmd in cmds] if shallow: [cmd.extend(['--depth', '1']) for cmd in cmds] return cmds def __get_repo_name(url: str) -> str: """ Returns the name of the repository from its given URL. """ parsed = urllib.parse.urlparse(url) name = os.path.basename(parsed.path) if name.endswith('.git'): name = name[:-4] return name def __create_gh_repo_url(account: str, repo: str) -> str: """ Given an account name and a repo name, returns a cloneable gh repo url. """ return 'https://github.com/' + account + '/' + repo + '.git' def __list_repos(dirpath: Optional[Union[str, pathlib.Path]] = '.' ) -> List[str]: """ Given a starting search directory, returns a list of paths to git repos on the local machine. """ root_path = __get_validated_path(dirpath) subdirs = [] for path, dirs, _ in os.walk(root_path): [subdirs.append(os.path.join(path, directory)) for directory in dirs] return [str(pathlib.Path(subdir).parent) for subdir in subdirs if pathlib.Path(subdir).name == '.git'] def __get_validated_path(dirpath: Union[str, pathlib.Path]) -> pathlib.Path: try: root_path = pathlib.Path(dirpath) if not os.path.isdir(root_path): raise FileNotFoundError("'{}.'".format(dirpath)) return root_path except FileNotFoundError as e: raise FileNotFoundError("Unable to find directory", e) except Exception as e: raise Exception("Failed to traverse path.".format(e))
en
0.594174
gdutils.datamine ================ Provides - A ``python`` module for mining and listing data sources. Metadata -------- :Module: ``gdutils.datamine`` :Filename: `datamine.py <https://github.com/mggg/gdutils/>`_ :Author: `@KeiferC <https://github.com/keiferc>`_ :Date: 27 July 2020 :Version: 1.1.0 :Description: Module for data mining :Contributors: `@InnovativeInventor <https://github.com/InnovativeInventor>`_ Documentation ------------- Documentation for the ``datamine`` module can be found as docstrings. Run ``import gdutils.datamine; help(gdutils.datamine)`` to view documentation. :: $ python >>> import gdutils.datamine; help(gdutils.datamine) Additionally, documentation can be found on `Read the Docs <https://gdutils.readthedocs.io>`_. ######################################### # # # Function Definitions # # # ######################################### Returns a list of tuples of public GitHub repositories and their URLs associated with the given account and account type. Parameters ---------- account : str Github account whose public repos are to be cloned. account_type: str Type of github account whose public repos are to be cloned. Valid options: ``'users'``, ``'orgs'``. Returns ------- List[Tuple[str, str]] A list of tuples of public Github repositories and their URLs. E.g. :: [('boysenberry-repo-1', 'https://github.com/octocat/boysenberry-repo-1.git'), ('git-consortium', 'https://github.com/octocat/git-consortium.git'), ... ('test-repo1', https://github.com/octocat/test-repo1.git)] Raises ------ ValueError Raised if the given account_type is neither ``'users'`` nor ``'orgs'``. RuntimeError Raised if unable to query GitHub for repo information. Examples -------- >>> repos = datamine.list_gh_repos('octocat', 'users') # gets a list of all repos and their GitHub URLs for account 'octocat' >>> for repo, url in repos: ... print('{} : {}'.format(repo, url)) boysenberry-repo-1 : https://github.com/octocat/boysenberry-repo-1.git git-consortium : https://github.com/octocat/git-consortium.git hello-worId : https://github.com/octocat/hello-worId.git Hello-World : https://github.com/octocat/Hello-World.git linguist : https://github.com/octocat/linguist.git octocat.github.io : https://github.com/octocat/octocat.github.io.git Spoon-Knife : https://github.com/octocat/Spoon-Knife.git test-repo1 : https://github.com/octocat/test-repo1.git Clones public GitHub repositories into the given directory. If directory path is not provided, clones repos into the current working directory. Parameters ---------- account : str GitHub account whose public repos are to be cloned. account_type : str Type of GitHub account whose public repos are to be cloned. Valid options: ``'users'``, ``'orgs'``. repos : List[str], optional, default = ``None`` List of specific repositories to clone. outpath : str | pathlib.Path, optional, default = ``None`` Path to which repos are to be cloned. If not specified, clones repos into current working directory. shallow : bool | optional, default = ``True`` Determines whether the clone will be shallow or not. If not specified, defaults to a shallow git clone. silent : bool | optional, default = ``False`` Determines whether the clone will be silent or not. If not specified, defaults to a loud git clone. Raises ------ ValueError Raised if provided an account type other than ``'users'`` or ``'orgs'``. Examples -------- >>> datamine.clone_repos('mggg-states', 'orgs') # clones all repositories of 'mggg-states' into the current directory >>> datamine.clone_repos('mggg-states', 'orgs', ['AZ-shapefiles']) # clones repo 'AZ-shapefiles' from 'mggg-states' into current directory >>> datamine.clone_repos('mggg-states', 'orgs', ... ['AZ-shapefiles', 'HI-shapefiles']) # clones repos 'AZ-shapefiles' & 'HI-shapefiles' into current directory >>> datamine.clone_repos('mggg-states', 'orgs', ['HI-shapefiles'], 'shps/') # clones repo 'HI-shapefiles' into directory 'shps/' >>> datamine.clone_repos('octocat', 'users', outpath='cloned-repos/') # clones all repos of 'octocat' into directory 'cloned-repos/' >>> datamine.clone_repos('octocat', 'users', outpath='cloned-repos/', ... shallow=False) # deep clones all repos of 'octocat' into directory 'cloned-repos/' >>> datamine.clone_repos('octocat', 'users', outpath='cloned-repos/', ... silent=True) # silently deep clones all repos of 'octocat' into directory 'cloned-repos/' Given a name/path of a directory, recursively removes all git repositories starting from the given directory. This action cannot be undone. *Warning:* this function will remove the given directory if the given directory itself is a git repo. Parameters ---------- dirpath: str | pathlib.Path Name/path of directory from which recursive removal of repos begins. Raises ------ FileNotFoundError Raised if unable to find the given directory. Examples -------- >>> datamine.remove_repos('repos_to_remove/') # removes all repos in directory 'repos_to_remove/' >>> datamine.remove_repos('repos_to_remove/repo1') # removes repo 'repo1' in directory 'repos_to_remove/' Given a file extension and an optional directory path, returns a list of file paths of files containing the extension. If the directory path is not specified, function defaults to listing files from the current working directory. Parameters ---------- filetype: str | List[str] File extension of files to list (e.g. ``'.zip'``). Can be a list of extensions (e.g. ``['.zip', '.shp', '.csv']``). dirpath: str | pathlib.Path, optional, default = ``'.'``. Path to directory from which file listing begins. Defaults to current working directory if not specified. exclude_hidden: bool, option, default = ``True`` If false, function includes hidden files in the search. Returns ------- List[str] List of file paths of files containing the given extension. Raises ------ FileNotFoundError Raised if unable to find given directory. Examples -------- >>> list_of_zips = datamine.list_files_of_type('.zip') # recursively gets a list of '.zip' files from the current directory >>> print(list_of_zips) ['./zipfile1.zip', './zipfile2.zip', './shapefiles/shape1.zip', './shapefiles/shape2.zip'] >>> list_of_shps = datamine.list_files_of_type('.shp', 'shapefiles/') # recursively gets a list of '.shp' files from the 'shapefiles/' directory >>> print(list_of_shps) ['./shapefiles/shape1/shape1.shp', './shapefiles/shape2/shape2.shp'] >>> list_of_csvs = datamine.list_files_of_type('.csv', ... exclude_hidden = False) # recursively gets a list of '.csv' files, including hidden files >>> print(list_of_csvs) ['./csv1.csv', './.csv_hidden.csv'] >>> list_of_mix = datamine.list_files_of_type(['.shp', '.zip']) # recursively gets a list of '.shp' and '.zip' files >>> print(list_of_mix) ['./shapefiles/shape1/shape1.shp', './shapefiles/shape2/shape2.shp', './zipfile1.zip', './zipfile2.zip', './shapefiles/shape1.zip', './shapefiles/shape2.zip'] Given a dictionary with categories, returns a list of keys in the given category. Examples of accepted forms of dictionary input: :: {category1 : [{key1 : value1}, {key2 : value2}] category2 : [{key3 : value3},]} :: {category1 : [[key1, key2, key3]]} :: {category1 : [[key1]], category2 : [[key2], {key3: value3}]} Parameters ---------- dictionary : Dict[Hashable, List[Iterable]] Dictionary containing categories in which keys are stored. category : Hashable | List[Hashable] Category containing keys. Returns ------- List[Hashable] List of keys of every key-value pair in the given category of the given dictionary. Examples -------- >>> sample_dict = {'category1' : [{'key1': 1}], ... 'category2' : [{'key2' : 2}, {'key3' : 3}]} >>> keys = datamine.get_keys_by_category(sample_dict, 'category2') # gets a list of keys under 'category2' from the dictionary 'sample_dict' >>> print(keys) ['key2', 'key3'] >>> sample_dict = {'category1' : [['key1', 'key4']], ... 'category2' : [['key2'], {'key3': 'value3'}]} >>> keys = datamine.get_keys_by_category(sample_dict, 'category2') # note: keys can be stored in both list and dictionary form >>> print(keys) ['key2', 'key3'] >>> keys = datamine.get_keys_by_category(sample_dict, ... ['category1', 'category2']) # gets a list of keys under categories 'category1' and 'category2' >>> print(keys) ['key1', 'key2', 'key3'] # category is a list ######################################### # # # Helper Definitions # # # ######################################### Given a list of repos, returns a list of subprocess-valid git clone commands. # if repos is a Dict - EAFP # if repos is a List - EAFP Returns the name of the repository from its given URL. Given an account name and a repo name, returns a cloneable gh repo url. Given a starting search directory, returns a list of paths to git repos on the local machine.
2.506256
3
examples/example_ocr.py
Ichunjo/vardefunc
18
6632206
<reponame>Ichunjo/vardefunc<filename>examples/example_ocr.py import vapoursynth as vs from vardefunc.ocr import OCR from vsutil import get_y core = vs.core # Import your clip SOURCE = core.std.BlankClip(format=vs.YUV410P8) def ocring() -> None: clip = SOURCE ocr = OCR(get_y(clip), (1900, 125, 70), coord_alt=(1500, 125, 70)) ocr.preview_cropped.set_output(0) ocr.preview_cleaned.set_output(1) ocr.launch(datapath=r'C:\Users\Varde\AppData\Roaming\VapourSynth\plugins64\tessdata', language='fra+eng') ocr.write_ass( 'output.ass', [('_', '-'), ('…', '...'), ('‘', "'"), ('’', "'"), (" '", "'"), ('—', '-'), ('- ', '– '), ('0u', 'Ou'), ('Gomme', 'Comme'), ('A ', 'À '), ('II', 'Il'), ('ees', 'ces'), ('@', 'O'), ('oe', 'œ'), ('téte', 'tête')] ) if __name__ == '__main__': ocring() else: ocring()
import vapoursynth as vs from vardefunc.ocr import OCR from vsutil import get_y core = vs.core # Import your clip SOURCE = core.std.BlankClip(format=vs.YUV410P8) def ocring() -> None: clip = SOURCE ocr = OCR(get_y(clip), (1900, 125, 70), coord_alt=(1500, 125, 70)) ocr.preview_cropped.set_output(0) ocr.preview_cleaned.set_output(1) ocr.launch(datapath=r'C:\Users\Varde\AppData\Roaming\VapourSynth\plugins64\tessdata', language='fra+eng') ocr.write_ass( 'output.ass', [('_', '-'), ('…', '...'), ('‘', "'"), ('’', "'"), (" '", "'"), ('—', '-'), ('- ', '– '), ('0u', 'Ou'), ('Gomme', 'Comme'), ('A ', 'À '), ('II', 'Il'), ('ees', 'ces'), ('@', 'O'), ('oe', 'œ'), ('téte', 'tête')] ) if __name__ == '__main__': ocring() else: ocring()
en
0.516469
# Import your clip
2.132953
2
dags/tableau/.ipynb_checkpoints/config-checkpoint.py
divinorum-webb/docker-airflow
1
6632207
<reponame>divinorum-webb/docker-airflow<gh_stars>1-10 """ Reference Notes tableau_server_config details configuration for TableauServer class 'password' -> Note that this is NOT your AD password. If you use your AD password, authentication will fail. You will need to obtain your actual Tableau Server password for this. For example, your AD password could be '<PASSWORD>', but your Tableau Server password is '<PASSWORD>'. You probably need a Tableau Server Admin to help you set / discover your Tableau Server password. 'api_version' -> Change this value to match the API version which corresponds to the current Tableau Server version. Look here to look up the appropriate api_version, given the current Tableau Server version: https://onlinehelp.tableau.com/current/api/rest_api/en-us/REST/rest_api_concepts_versions.htm 'cache_buster' -> This value references a dummy parameter within a Tableau Workbook file. We use this value when downloading images from Tableau Server so that the image returned is not a cached ancient relic of days past. Your workbook needs a parameter whose name matches that of your 'cache_buster' name for this to work. The subscription_email_config dict details configuration for the EmailSubscription class """ tableau_server_config = { 'tableau_prod': { 'server': 'https://tableaupoc.interworks.com', 'api_version': '3.2', 'username': 'estam', 'password': '<PASSWORD>!', 'site': 'estam', 'cache_buster': 'Donut', 'temp_dir': '/dags/tableau_subscriptions/temp/' } } subscription_email_config = { 'default': { 'smtp': { 'username': '<EMAIL>', 'password': '<PASSWORD>!', 'server': 'smtp.office365.com:587' }, 'assets': { 'html_file': '/dags/tableau_subscriptions/assets/html_test.html' } } }
""" Reference Notes tableau_server_config details configuration for TableauServer class 'password' -> Note that this is NOT your AD password. If you use your AD password, authentication will fail. You will need to obtain your actual Tableau Server password for this. For example, your AD password could be '<PASSWORD>', but your Tableau Server password is '<PASSWORD>'. You probably need a Tableau Server Admin to help you set / discover your Tableau Server password. 'api_version' -> Change this value to match the API version which corresponds to the current Tableau Server version. Look here to look up the appropriate api_version, given the current Tableau Server version: https://onlinehelp.tableau.com/current/api/rest_api/en-us/REST/rest_api_concepts_versions.htm 'cache_buster' -> This value references a dummy parameter within a Tableau Workbook file. We use this value when downloading images from Tableau Server so that the image returned is not a cached ancient relic of days past. Your workbook needs a parameter whose name matches that of your 'cache_buster' name for this to work. The subscription_email_config dict details configuration for the EmailSubscription class """ tableau_server_config = { 'tableau_prod': { 'server': 'https://tableaupoc.interworks.com', 'api_version': '3.2', 'username': 'estam', 'password': '<PASSWORD>!', 'site': 'estam', 'cache_buster': 'Donut', 'temp_dir': '/dags/tableau_subscriptions/temp/' } } subscription_email_config = { 'default': { 'smtp': { 'username': '<EMAIL>', 'password': '<PASSWORD>!', 'server': 'smtp.office365.com:587' }, 'assets': { 'html_file': '/dags/tableau_subscriptions/assets/html_test.html' } } }
en
0.68281
Reference Notes tableau_server_config details configuration for TableauServer class 'password' -> Note that this is NOT your AD password. If you use your AD password, authentication will fail. You will need to obtain your actual Tableau Server password for this. For example, your AD password could be '<PASSWORD>', but your Tableau Server password is '<PASSWORD>'. You probably need a Tableau Server Admin to help you set / discover your Tableau Server password. 'api_version' -> Change this value to match the API version which corresponds to the current Tableau Server version. Look here to look up the appropriate api_version, given the current Tableau Server version: https://onlinehelp.tableau.com/current/api/rest_api/en-us/REST/rest_api_concepts_versions.htm 'cache_buster' -> This value references a dummy parameter within a Tableau Workbook file. We use this value when downloading images from Tableau Server so that the image returned is not a cached ancient relic of days past. Your workbook needs a parameter whose name matches that of your 'cache_buster' name for this to work. The subscription_email_config dict details configuration for the EmailSubscription class
1.482136
1
spacenav_remote/src/spacenav_remote/server.py
carlosvquezada/lg_ros_nodes
0
6632208
#!/usr/bin/env python import SocketServer import thread import socket def print_handler(data): print data class MyTCPHandler(SocketServer.StreamRequestHandler): def __init__(self, callback, *args, **keys): self.callback = callback SocketServer.StreamRequestHandler.__init__(self, *args, **keys) def handle(self): data = self.rfile.readline().strip() while data: self.callback(data) data = self.rfile.readline().strip() def handler_factory(callback): def createHandler(*args, **keys): return MyTCPHandler(callback, *args, **keys) return createHandler class SpacenavRemote(object): def __init__(self, handler=print_handler, port=6465): HOST, PORT = '', port # Create the server, binding to localhost on port 6564 SocketServer.TCPServer.allow_reuse_address = True self.server = SocketServer.TCPServer((HOST, PORT), handler_factory(handler)) self.server.socket.setsockopt(socket.IPPROTO_TCP, socket.TCP_NODELAY, 1) def fork_and_run(self): """ Activate the server in separate thread """ thread.start_new_thread(self.serve_forever, ()) def serve_forever(self): try: self.server.serve_forever() except KeyboardInterrupt: self.shutdown() def shutdown(self): self.server.shutdown() self.server.socket.close() if __name__ == "__main__": print "Start spacenav remote server" server = SpacenavRemote() server.serve_forever()
#!/usr/bin/env python import SocketServer import thread import socket def print_handler(data): print data class MyTCPHandler(SocketServer.StreamRequestHandler): def __init__(self, callback, *args, **keys): self.callback = callback SocketServer.StreamRequestHandler.__init__(self, *args, **keys) def handle(self): data = self.rfile.readline().strip() while data: self.callback(data) data = self.rfile.readline().strip() def handler_factory(callback): def createHandler(*args, **keys): return MyTCPHandler(callback, *args, **keys) return createHandler class SpacenavRemote(object): def __init__(self, handler=print_handler, port=6465): HOST, PORT = '', port # Create the server, binding to localhost on port 6564 SocketServer.TCPServer.allow_reuse_address = True self.server = SocketServer.TCPServer((HOST, PORT), handler_factory(handler)) self.server.socket.setsockopt(socket.IPPROTO_TCP, socket.TCP_NODELAY, 1) def fork_and_run(self): """ Activate the server in separate thread """ thread.start_new_thread(self.serve_forever, ()) def serve_forever(self): try: self.server.serve_forever() except KeyboardInterrupt: self.shutdown() def shutdown(self): self.server.shutdown() self.server.socket.close() if __name__ == "__main__": print "Start spacenav remote server" server = SpacenavRemote() server.serve_forever()
en
0.639124
#!/usr/bin/env python # Create the server, binding to localhost on port 6564 Activate the server in separate thread
2.911752
3
examples/splunk_to_argus.py
salesforce/python-argusclient
16
6632209
<gh_stars>10-100 # # Copyright (c) 2016, salesforce.com, inc. # All rights reserved. # Licensed under the BSD 3-Clause license. # For full license text, see LICENSE.txt file in the repo root or https://opensource.org/licenses/BSD-3-Clause # import requests, sys, json, os, time, calendar, csv, getpass, logging from optparse import OptionParser, Option, OptionValueError from six import itervalues from six.moves import urllib import splunklib.client as splunkclient from argusclient import ArgusServiceClient, Metric class MyOptionParser(OptionParser,object): def check_values(self, values, args): opt, args = super(MyOptionParser, self).check_values(values, args) if not opt.password: opt.password = <PASSWORD>("Password: ") return opt, args parser = MyOptionParser() parser.add_option("-q", "--quite", dest="quite", action="store_true", help="Quite mode, output only errors", default=False) parser.add_option("-v", "--verbose", dest="verbose", action="store_true", help="Verbose mode", default=False) parser.add_option("-d", "--debug", dest="debug", action="store_true", help="Debug mode", default=False) parser.add_option("-u", "--user", dest="user", default=getpass.getuser(), help="Specify username for Argus/Splunk connection") parser.add_option("-p", "--pass", dest="password", default=None, help="Specify password for Argus/Splunk connection (not specifying this option will result in getting prompted") parser.add_option("--argusws", dest="argusws", help="Specify Argus webservice endpoint") parser.add_option("--splunkapi", dest="splunkapi", help="Specify Splunk API endpoint") parser.add_option("--alert", dest="alert", action="store_true", help="Create/update alert", default=False) parser.add_option("--dashboard", dest="dashboard", action="store_true", help="Create/update dashboard", default=False) parser.add_option("-I", "--index", dest="index", default="na44", help="Specify the Splunk index to search against") parser.add_option("-S", "--earliest", dest="earliest", default="-1d@d", help="Specify splunk time expression for the start of the time range") parser.add_option("-E", "--latest", dest="latest", default="-0d@d", help="Specify splunk time expression for the end of the time range") parser.add_option("-P", "--pattern", dest="pattern", default=None, help="Specify a Splunk pattern to search for") parser.add_option("-T", "--span", dest="span", default="15m", help="Specify an alternative span for bucketing option") parser.add_option("--scope", dest="scope", default="patternStats", help="The Argus scope name for posting metrics") parser.add_option("--namespace", dest="namespace", default="testNamespace", help="The Argus namespace name for posting metrics") (opts, args) = parser.parse_args() if not opts.pattern: parser.error("Please specify a Splunk pattern to search for") if not opts.argusws: parser.error("Need the URL to the Argus endpoint") if not opts.splunkapi: parser.error("Need the URL to the Splunk endpoint") logging.basicConfig() if not opts.quite: logging.root.setLevel(opts.quite and logging.WARN or (opts.debug and logging.DEBUG or logging.INFO)) def to_gmt_epoch(tsstr): # tsstr is expected to be in the default Splunk format: "2015-11-01T00:00:00.000+00:00" return calendar.timegm(time.strptime(tsstr[:19], "%Y-%m-%dT%H:%M:%S")) def get_splunk_metrics(opts): splunkendpoint = urllib.parse.urlsplit(opts.splunkapi) splunk_opts = { "scheme": splunkendpoint.scheme, "host": splunkendpoint.hostname, "port": splunkendpoint.port, "username": opts.user, "password": opts.password, } try: if not opts.quite: logging.info("Logging into Splunk service") service = splunkclient.connect(**splunk_opts) if not opts.quite: logging.info("Splunk login successful") except: logging.exception("Splunk login failed") return None splunkquery = """ search index={index} earliest={earliest} latest={latest} "{pattern}" | bucket _time span={span} | stats count by _time, host | appendpipe [stats avg(count) as avgCount, sum(count) as sumCount, min(count) as minCount, max(count) as maxCount, stdev(count) as stdevCount by host] """ if not opts.quite: logging.info("Submitting job to Splunk..") job = service.jobs.create(splunkquery.format(index=opts.index, pattern=opts.pattern, earliest=opts.earliest, latest=opts.latest, span=opts.span)) if not opts.quite: logging.info("Waiting for job to be ready..") while not job.is_ready(): if opts.verbose: logging.info("Still waiting for job to be ready..") time.sleep(1) else: if not opts.quite: logging.info("Job is ready, waiting for completion..") while not job.is_done(): if opts.verbose: logging.info("Still waiting for job to be completed..") time.sleep(2) else: if not opts.quite: logging.info("Job is done, collecting results..") results = job.results(output_mode="csv", count=0) csvr = csv.reader(results) cols = None data = [] for row in csvr: logging.debug("Got row: %s", row) if not cols: cols = row continue data.append(dict(zip(cols, row))) if not opts.quite: logging.info("Total result count: %s", len(data)) runts = int(time.time()) m_dict = {} patternTagVal = opts.pattern.replace(" ", "__") # We can't have spaces in tag values. for row in data: host = row["host"] if not host: logging.warn("Skipping row with no host: %s", row) continue for col in row: if col in ("_time", "host") or not row[col]: continue m_key = (host, col) if not m_key in m_dict: m_dict[m_key] = Metric(opts.scope, patternTagVal+"."+col, tags=dict(host=host, patternStr=patternTagVal), namespace=opts.namespace) m = m_dict[m_key] ts = row["_time"] and to_gmt_epoch(row["_time"]) or runts val = row[col] if "." in val: val = float(val) else: val = int(val) if logging.root.isEnabledFor(logging.DEBUG): logging.debug("Adding %s at timestamp: %s for metric: %s", val, ts, m.desc()) m.datapoints[ts] = val if not opts.quite: logging.info("Total metric count: %s", len(m_dict)) job.cancel() return list(itervalues(m_dict)) metrics = get_splunk_metrics(opts) if metrics: argus = ArgusServiceClient(opts.user, opts.password, endpoint=opts.argusws) if not opts.quite: logging.info("Logging into Argus service") try: argus.login() if opts.verbose: logging.info("Argus login successful") if not opts.quite: logging.info("Posting metrics to Argus..") argus.metrics.add(metrics); if not opts.quite: logging.info("Done.") except: logging.exception("Argus failure")
# # Copyright (c) 2016, salesforce.com, inc. # All rights reserved. # Licensed under the BSD 3-Clause license. # For full license text, see LICENSE.txt file in the repo root or https://opensource.org/licenses/BSD-3-Clause # import requests, sys, json, os, time, calendar, csv, getpass, logging from optparse import OptionParser, Option, OptionValueError from six import itervalues from six.moves import urllib import splunklib.client as splunkclient from argusclient import ArgusServiceClient, Metric class MyOptionParser(OptionParser,object): def check_values(self, values, args): opt, args = super(MyOptionParser, self).check_values(values, args) if not opt.password: opt.password = <PASSWORD>("Password: ") return opt, args parser = MyOptionParser() parser.add_option("-q", "--quite", dest="quite", action="store_true", help="Quite mode, output only errors", default=False) parser.add_option("-v", "--verbose", dest="verbose", action="store_true", help="Verbose mode", default=False) parser.add_option("-d", "--debug", dest="debug", action="store_true", help="Debug mode", default=False) parser.add_option("-u", "--user", dest="user", default=getpass.getuser(), help="Specify username for Argus/Splunk connection") parser.add_option("-p", "--pass", dest="password", default=None, help="Specify password for Argus/Splunk connection (not specifying this option will result in getting prompted") parser.add_option("--argusws", dest="argusws", help="Specify Argus webservice endpoint") parser.add_option("--splunkapi", dest="splunkapi", help="Specify Splunk API endpoint") parser.add_option("--alert", dest="alert", action="store_true", help="Create/update alert", default=False) parser.add_option("--dashboard", dest="dashboard", action="store_true", help="Create/update dashboard", default=False) parser.add_option("-I", "--index", dest="index", default="na44", help="Specify the Splunk index to search against") parser.add_option("-S", "--earliest", dest="earliest", default="-1d@d", help="Specify splunk time expression for the start of the time range") parser.add_option("-E", "--latest", dest="latest", default="-0d@d", help="Specify splunk time expression for the end of the time range") parser.add_option("-P", "--pattern", dest="pattern", default=None, help="Specify a Splunk pattern to search for") parser.add_option("-T", "--span", dest="span", default="15m", help="Specify an alternative span for bucketing option") parser.add_option("--scope", dest="scope", default="patternStats", help="The Argus scope name for posting metrics") parser.add_option("--namespace", dest="namespace", default="testNamespace", help="The Argus namespace name for posting metrics") (opts, args) = parser.parse_args() if not opts.pattern: parser.error("Please specify a Splunk pattern to search for") if not opts.argusws: parser.error("Need the URL to the Argus endpoint") if not opts.splunkapi: parser.error("Need the URL to the Splunk endpoint") logging.basicConfig() if not opts.quite: logging.root.setLevel(opts.quite and logging.WARN or (opts.debug and logging.DEBUG or logging.INFO)) def to_gmt_epoch(tsstr): # tsstr is expected to be in the default Splunk format: "2015-11-01T00:00:00.000+00:00" return calendar.timegm(time.strptime(tsstr[:19], "%Y-%m-%dT%H:%M:%S")) def get_splunk_metrics(opts): splunkendpoint = urllib.parse.urlsplit(opts.splunkapi) splunk_opts = { "scheme": splunkendpoint.scheme, "host": splunkendpoint.hostname, "port": splunkendpoint.port, "username": opts.user, "password": opts.password, } try: if not opts.quite: logging.info("Logging into Splunk service") service = splunkclient.connect(**splunk_opts) if not opts.quite: logging.info("Splunk login successful") except: logging.exception("Splunk login failed") return None splunkquery = """ search index={index} earliest={earliest} latest={latest} "{pattern}" | bucket _time span={span} | stats count by _time, host | appendpipe [stats avg(count) as avgCount, sum(count) as sumCount, min(count) as minCount, max(count) as maxCount, stdev(count) as stdevCount by host] """ if not opts.quite: logging.info("Submitting job to Splunk..") job = service.jobs.create(splunkquery.format(index=opts.index, pattern=opts.pattern, earliest=opts.earliest, latest=opts.latest, span=opts.span)) if not opts.quite: logging.info("Waiting for job to be ready..") while not job.is_ready(): if opts.verbose: logging.info("Still waiting for job to be ready..") time.sleep(1) else: if not opts.quite: logging.info("Job is ready, waiting for completion..") while not job.is_done(): if opts.verbose: logging.info("Still waiting for job to be completed..") time.sleep(2) else: if not opts.quite: logging.info("Job is done, collecting results..") results = job.results(output_mode="csv", count=0) csvr = csv.reader(results) cols = None data = [] for row in csvr: logging.debug("Got row: %s", row) if not cols: cols = row continue data.append(dict(zip(cols, row))) if not opts.quite: logging.info("Total result count: %s", len(data)) runts = int(time.time()) m_dict = {} patternTagVal = opts.pattern.replace(" ", "__") # We can't have spaces in tag values. for row in data: host = row["host"] if not host: logging.warn("Skipping row with no host: %s", row) continue for col in row: if col in ("_time", "host") or not row[col]: continue m_key = (host, col) if not m_key in m_dict: m_dict[m_key] = Metric(opts.scope, patternTagVal+"."+col, tags=dict(host=host, patternStr=patternTagVal), namespace=opts.namespace) m = m_dict[m_key] ts = row["_time"] and to_gmt_epoch(row["_time"]) or runts val = row[col] if "." in val: val = float(val) else: val = int(val) if logging.root.isEnabledFor(logging.DEBUG): logging.debug("Adding %s at timestamp: %s for metric: %s", val, ts, m.desc()) m.datapoints[ts] = val if not opts.quite: logging.info("Total metric count: %s", len(m_dict)) job.cancel() return list(itervalues(m_dict)) metrics = get_splunk_metrics(opts) if metrics: argus = ArgusServiceClient(opts.user, opts.password, endpoint=opts.argusws) if not opts.quite: logging.info("Logging into Argus service") try: argus.login() if opts.verbose: logging.info("Argus login successful") if not opts.quite: logging.info("Posting metrics to Argus..") argus.metrics.add(metrics); if not opts.quite: logging.info("Done.") except: logging.exception("Argus failure")
en
0.834089
# # Copyright (c) 2016, salesforce.com, inc. # All rights reserved. # Licensed under the BSD 3-Clause license. # For full license text, see LICENSE.txt file in the repo root or https://opensource.org/licenses/BSD-3-Clause # # tsstr is expected to be in the default Splunk format: "2015-11-01T00:00:00.000+00:00" search index={index} earliest={earliest} latest={latest} "{pattern}" | bucket _time span={span} | stats count by _time, host | appendpipe [stats avg(count) as avgCount, sum(count) as sumCount, min(count) as minCount, max(count) as maxCount, stdev(count) as stdevCount by host] # We can't have spaces in tag values.
2.03605
2
heat/engine/resources/openstack/mistral/workflow.py
maestro-hybrid-cloud/heat
0
6632210
# # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. from oslo_serialization import jsonutils import six import yaml from heat.common import exception from heat.common.i18n import _ from heat.engine import attributes from heat.engine import constraints from heat.engine import properties from heat.engine import resource from heat.engine.resources import signal_responder from heat.engine import support class Workflow(signal_responder.SignalResponder, resource.Resource): support_status = support.SupportStatus(version='2015.1') default_client_name = 'mistral' entity = 'workflows' PROPERTIES = ( NAME, TYPE, DESCRIPTION, INPUT, OUTPUT, TASKS, PARAMS, TASK_DEFAULTS ) = ( 'name', 'type', 'description', 'input', 'output', 'tasks', 'params', 'task_defaults' ) _TASKS_KEYS = ( TASK_NAME, TASK_DESCRIPTION, ON_ERROR, ON_COMPLETE, ON_SUCCESS, POLICIES, ACTION, WORKFLOW, PUBLISH, TASK_INPUT, REQUIRES, RETRY, WAIT_BEFORE, WAIT_AFTER, PAUSE_BEFORE, TIMEOUT, WITH_ITEMS, KEEP_RESULT, TARGET ) = ( 'name', 'description', 'on_error', 'on_complete', 'on_success', 'policies', 'action', 'workflow', 'publish', 'input', 'requires', 'retry', 'wait_before', 'wait_after', 'pause_before', 'timeout', 'with_items', 'keep_result', 'target' ) _TASKS_TASK_DEFAULTS = [ ON_ERROR, ON_COMPLETE, ON_SUCCESS, REQUIRES, RETRY, WAIT_BEFORE, WAIT_AFTER, PAUSE_BEFORE, TIMEOUT ] _SIGNAL_DATA_KEYS = ( SIGNAL_DATA_INPUT, SIGNAL_DATA_PARAMS ) = ( 'input', 'params' ) ATTRIBUTES = ( WORKFLOW_DATA, ALARM_URL, EXECUTIONS ) = ( 'data', 'alarm_url', 'executions' ) properties_schema = { NAME: properties.Schema( properties.Schema.STRING, _('Workflow name.') ), TYPE: properties.Schema( properties.Schema.STRING, _('Workflow type.'), constraints=[ constraints.AllowedValues(['direct', 'reverse']) ], required=True, update_allowed=True ), DESCRIPTION: properties.Schema( properties.Schema.STRING, _('Workflow description.'), update_allowed=True ), INPUT: properties.Schema( properties.Schema.MAP, _('Dictionary which contains input for workflow.'), update_allowed=True ), OUTPUT: properties.Schema( properties.Schema.MAP, _('Any data structure arbitrarily containing YAQL ' 'expressions that defines workflow output. May be ' 'nested.'), update_allowed=True ), PARAMS: properties.Schema( properties.Schema.MAP, _("Workflow additional parameters. If Workflow is reverse typed, " "params requires 'task_name', which defines initial task."), update_allowed=True ), TASK_DEFAULTS: properties.Schema( properties.Schema.MAP, _("Default settings for some of task " "attributes defined " "at workflow level."), support_status=support.SupportStatus(version='5.0.0'), schema={ ON_SUCCESS: properties.Schema( properties.Schema.LIST, _('List of tasks which will run after ' 'the task has completed successfully.') ), ON_ERROR: properties.Schema( properties.Schema.LIST, _('List of tasks which will run after ' 'the task has completed with an error.') ), ON_COMPLETE: properties.Schema( properties.Schema.LIST, _('List of tasks which will run after ' 'the task has completed regardless of whether ' 'it is successful or not.') ), REQUIRES: properties.Schema( properties.Schema.LIST, _('List of tasks which should be executed before ' 'this task. Used only in reverse workflows.') ), RETRY: properties.Schema( properties.Schema.MAP, _('Defines a pattern how task should be repeated in ' 'case of an error.') ), WAIT_BEFORE: properties.Schema( properties.Schema.INTEGER, _('Defines a delay in seconds that Mistral Engine' ' should wait before starting a task.') ), WAIT_AFTER: properties.Schema( properties.Schema.INTEGER, _('Defines a delay in seconds that Mistral Engine' ' should wait after a task has completed before' ' starting next tasks defined in ' 'on-success, on-error or on-complete.') ), PAUSE_BEFORE: properties.Schema( properties.Schema.BOOLEAN, _('Defines whether Mistral Engine should put the ' 'workflow on hold or not before starting a task') ), TIMEOUT: properties.Schema( properties.Schema.INTEGER, _('Defines a period of time in seconds after which ' 'a task will be failed automatically ' 'by engine if hasn\'t completed.') ), }, update_allowed=True ), TASKS: properties.Schema( properties.Schema.LIST, _('Dictionary containing workflow tasks.'), schema=properties.Schema( properties.Schema.MAP, schema={ TASK_NAME: properties.Schema( properties.Schema.STRING, _('Task name.'), required=True ), TASK_DESCRIPTION: properties.Schema( properties.Schema.STRING, _('Task description.') ), TASK_INPUT: properties.Schema( properties.Schema.MAP, _('Actual input parameter values of the task.') ), ACTION: properties.Schema( properties.Schema.STRING, _('Name of the action associated with the task. ' 'Either action or workflow may be defined in the ' 'task.') ), WORKFLOW: properties.Schema( properties.Schema.STRING, _('Name of the workflow associated with the task. ' 'Can be defined by intrinsic function get_resource ' 'or by name of the referenced workflow, i.e. ' '{ workflow: wf_name } or ' '{ workflow: { get_resource: wf_name }}. Either ' 'action or workflow may be defined in the task.') ), PUBLISH: properties.Schema( properties.Schema.MAP, _('Dictionary of variables to publish to ' 'the workflow context.') ), ON_SUCCESS: properties.Schema( properties.Schema.LIST, _('List of tasks which will run after ' 'the task has completed successfully.') ), ON_ERROR: properties.Schema( properties.Schema.LIST, _('List of tasks which will run after ' 'the task has completed with an error.') ), ON_COMPLETE: properties.Schema( properties.Schema.LIST, _('List of tasks which will run after ' 'the task has completed regardless of whether ' 'it is successful or not.') ), POLICIES: properties.Schema( properties.Schema.MAP, _('Dictionary-like section defining task policies ' 'that influence how Mistral Engine runs tasks. Must ' 'satisfy Mistral DSL v2.'), support_status=support.SupportStatus( status=support.DEPRECATED, version='5.0.0', message=_('Add needed policies directly to ' 'the task, Policy keyword is not ' 'needed'), previous_status=support.SupportStatus( version='2015.1')) ), REQUIRES: properties.Schema( properties.Schema.LIST, _('List of tasks which should be executed before ' 'this task. Used only in reverse workflows.') ), RETRY: properties.Schema( properties.Schema.MAP, _('Defines a pattern how task should be repeated in ' 'case of an error.'), support_status=support.SupportStatus(version='5.0.0') ), WAIT_BEFORE: properties.Schema( properties.Schema.INTEGER, _('Defines a delay in seconds that Mistral Engine ' 'should wait before starting a task.'), support_status=support.SupportStatus(version='5.0.0') ), WAIT_AFTER: properties.Schema( properties.Schema.INTEGER, _('Defines a delay in seconds that Mistral ' 'Engine should wait after ' 'a task has completed before starting next tasks ' 'defined in on-success, on-error or on-complete.'), support_status=support.SupportStatus(version='5.0.0') ), PAUSE_BEFORE: properties.Schema( properties.Schema.BOOLEAN, _('Defines whether Mistral Engine should ' 'put the workflow on hold ' 'or not before starting a task.'), support_status=support.SupportStatus(version='5.0.0') ), TIMEOUT: properties.Schema( properties.Schema.INTEGER, _('Defines a period of time in seconds after which a ' 'task will be failed automatically by engine ' 'if hasn\'t completed.'), support_status=support.SupportStatus(version='5.0.0') ), WITH_ITEMS: properties.Schema( properties.Schema.STRING, _('If configured, it allows to run action or workflow ' 'associated with a task multiple times ' 'on a provided list of items.'), support_status=support.SupportStatus(version='5.0.0') ), KEEP_RESULT: properties.Schema( properties.Schema.BOOLEAN, _('Allowing not to store action results ' 'after task completion.'), support_status=support.SupportStatus(version='5.0.0') ), TARGET: properties.Schema( properties.Schema.STRING, _('It defines an executor to which task action ' 'should be sent to.'), support_status=support.SupportStatus(version='5.0.0') ), }, ), required=True, update_allowed=True ) } attributes_schema = { WORKFLOW_DATA: attributes.Schema( _('A dictionary which contains name and input of the workflow.'), type=attributes.Schema.MAP ), ALARM_URL: attributes.Schema( _("A signed url to create executions for workflows specified in " "Workflow resource."), type=attributes.Schema.STRING ), EXECUTIONS: attributes.Schema( _("List of workflows' executions, each of them is a dictionary " "with information about execution. Each dictionary returns " "values for next keys: id, workflow_name, created_at, " "updated_at, state for current execution state, input, output."), type=attributes.Schema.LIST ) } def get_reference_id(self): return self._workflow_name() def _validate_signal_data(self, data): if data is not None: input_value = data.get(self.SIGNAL_DATA_INPUT) params_value = data.get(self.SIGNAL_DATA_PARAMS) if input_value is not None: if not isinstance(input_value, dict): message = (_('Input in signal data must be a map, ' 'find a %s') % type(input_value)) raise exception.StackValidationFailed( error=_('Signal data error'), message=message) for key in six.iterkeys(input_value): if (self.properties.get(self.INPUT) is None or key not in self.properties.get(self.INPUT)): message = _('Unknown input %s') % key raise exception.StackValidationFailed( error=_('Signal data error'), message=message) if params_value is not None and not isinstance(params_value, dict): message = (_('Params must be a map, find a ' '%s') % type(params_value)) raise exception.StackValidationFailed( error=_('Signal data error'), message=message) def validate(self): super(Workflow, self).validate() if self.properties.get(self.TYPE) == 'reverse': params = self.properties.get(self.PARAMS) if params is None or not params.get('task_name'): raise exception.StackValidationFailed( error=_('Mistral resource validation error'), path=[self.name, ('properties' if self.stack.t.VERSION == 'heat_template_version' else 'Properties'), self.PARAMS], message=_("'task_name' is not assigned in 'params' " "in case of reverse type workflow.") ) for task in self.properties.get(self.TASKS): wf_value = task.get(self.WORKFLOW) action_value = task.get(self.ACTION) if wf_value and action_value: raise exception.ResourcePropertyConflict(self.WORKFLOW, self.ACTION) if not wf_value and not action_value: raise exception.PropertyUnspecifiedError(self.WORKFLOW, self.ACTION) if (task.get(self.REQUIRES) is not None and self.properties.get(self.TYPE)) == 'direct': msg = _("task %(task)s contains property 'requires' " "in case of direct workflow. Only reverse workflows " "can contain property 'requires'.") % { 'name': self.name, 'task': task.get(self.TASK_NAME) } raise exception.StackValidationFailed( error=_('Mistral resource validation error'), path=[self.name, ('properties' if self.stack.t.VERSION == 'heat_template_version' else 'Properties'), self.TASKS, task.get(self.TASK_NAME), self.REQUIRES], message=msg) if task.get(self.POLICIES) is not None: for task_item in task.get(self.POLICIES): if task.get(task_item) is not None: msg = _('Property %(policies)s and %(item)s cannot be ' 'used both at one time.') % { 'policies': self.POLICIES, 'item': task_item } raise exception.StackValidationFailed(message=msg) def _workflow_name(self): return self.properties.get(self.NAME) or self.physical_resource_name() def build_tasks(self, props): for task in props[self.TASKS]: current_task = {} wf_value = task.get(self.WORKFLOW) if wf_value is not None: if wf_value in [res.resource_id for res in six.itervalues(self.stack)]: current_task.update({self.WORKFLOW: wf_value}) else: msg = _("No such workflow %s") % wf_value raise ValueError(msg) # backward support for kilo. if task.get(self.POLICIES) is not None: task.update(task.get(self.POLICIES)) task_keys = [key for key in self._TASKS_KEYS if key not in [ self.WORKFLOW, self.TASK_NAME, self.POLICIES ]] for task_prop in task_keys: if task.get(task_prop) is not None: current_task.update( {task_prop.replace('_', '-'): task[task_prop]}) yield {task[self.TASK_NAME]: current_task} def prepare_properties(self, props): """Prepare correct YAML-formatted definition for Mistral.""" defn_name = self._workflow_name() definition = {'version': '2.0', defn_name: {self.TYPE: props.get(self.TYPE), self.DESCRIPTION: props.get( self.DESCRIPTION), self.OUTPUT: props.get(self.OUTPUT)}} for key in list(definition[defn_name].keys()): if definition[defn_name][key] is None: del definition[defn_name][key] if props.get(self.INPUT) is not None: definition[defn_name][self.INPUT] = list(props.get( self.INPUT).keys()) definition[defn_name][self.TASKS] = {} for task in self.build_tasks(props): definition.get(defn_name).get(self.TASKS).update(task) if props.get(self.TASK_DEFAULTS) is not None: definition[defn_name][self.TASK_DEFAULTS.replace('_', '-')] = { k.replace('_', '-'): v for k, v in six.iteritems(props.get(self.TASK_DEFAULTS)) if v} return yaml.dump(definition, Dumper=yaml.CSafeDumper if hasattr(yaml, 'CSafeDumper') else yaml.SafeDumper) def handle_create(self): super(Workflow, self).handle_create() props = self.prepare_properties(self.properties) try: workflow = self.client().workflows.create(props) except Exception as ex: raise exception.ResourceFailure(ex, self) # NOTE(prazumovsky): Mistral uses unique names for resource # identification. self.resource_id_set(workflow[0].name) def handle_signal(self, details=None): self._validate_signal_data(details) result_input = {} result_params = {} if details is not None: if details.get(self.INPUT) is not None: # NOTE(prazumovsky): Signal can contains some data, interesting # for workflow, e.g. inputs. So, if signal data contains input # we update override inputs, other leaved defined in template. for key, value in six.iteritems( self.properties.get(self.INPUT)): result_input.update( {key: details.get( self.SIGNAL_DATA_INPUT).get(key) or value}) if details.get(self.SIGNAL_DATA_PARAMS) is not None: if self.properties.get(self.PARAMS) is not None: result_params.update(self.properties.get(self.PARAMS)) result_params.update(details.get(self.SIGNAL_DATA_PARAMS)) if not result_input and self.properties.get(self.INPUT): result_input.update(self.properties.get(self.INPUT)) if not result_params and self.properties.get(self.PARAMS): result_params.update(self.properties.get(self.PARAMS)) try: execution = self.client().executions.create( self._workflow_name(), jsonutils.dumps(result_input), **result_params) except Exception as ex: raise exception.ResourceFailure(ex, self) executions = [execution.id] if self.EXECUTIONS in self.data(): executions.extend(self.data().get(self.EXECUTIONS).split(',')) self.data_set(self.EXECUTIONS, ','.join(executions)) def handle_update(self, json_snippet, tmpl_diff, prop_diff): update_allowed = [self.INPUT, self.PARAMS, self.DESCRIPTION] for prop in update_allowed: if prop in prop_diff: del prop_diff[prop] if len(prop_diff) > 0: new_props = self.prepare_properties(tmpl_diff['Properties']) try: workflow = self.client().workflows.update(new_props) except Exception as ex: raise exception.ResourceFailure(ex, self) self.data_set(self.NAME, workflow[0].name) self.resource_id_set(workflow[0].name) def _delete_executions(self): if self.data().get(self.EXECUTIONS): for id in self.data().get(self.EXECUTIONS).split(','): try: self.client().executions.delete(id) except Exception as ex: self.client_plugin().ignore_not_found(ex) self.data_delete('executions') def handle_delete(self): self._delete_executions() return super(Workflow, self).handle_delete() def _resolve_attribute(self, name): if name == self.EXECUTIONS: if self.EXECUTIONS not in self.data(): return [] def parse_execution_response(execution): return { 'id': execution.id, 'workflow_name': execution.workflow_name, 'created_at': execution.created_at, 'updated_at': execution.updated_at, 'state': execution.state, 'input': jsonutils.loads(six.text_type(execution.input)), 'output': jsonutils.loads(six.text_type(execution.output)) } return [parse_execution_response( self.client().executions.get(exec_id)) for exec_id in self.data().get(self.EXECUTIONS).split(',')] elif name == self.WORKFLOW_DATA: return {self.NAME: self.resource_id, self.INPUT: self.properties.get(self.INPUT)} elif name == self.ALARM_URL: return six.text_type(self._get_ec2_signed_url()) # TODO(tlashchova): remove this method when mistralclient>1.0.0 is used. def _show_resource(self): workflow = self.client().workflows.get(self.resource_id) if hasattr(workflow, 'to_dict'): super(Workflow, self)._show_resource() return workflow._data def resource_mapping(): return { 'OS::Mistral::Workflow': Workflow }
# # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. from oslo_serialization import jsonutils import six import yaml from heat.common import exception from heat.common.i18n import _ from heat.engine import attributes from heat.engine import constraints from heat.engine import properties from heat.engine import resource from heat.engine.resources import signal_responder from heat.engine import support class Workflow(signal_responder.SignalResponder, resource.Resource): support_status = support.SupportStatus(version='2015.1') default_client_name = 'mistral' entity = 'workflows' PROPERTIES = ( NAME, TYPE, DESCRIPTION, INPUT, OUTPUT, TASKS, PARAMS, TASK_DEFAULTS ) = ( 'name', 'type', 'description', 'input', 'output', 'tasks', 'params', 'task_defaults' ) _TASKS_KEYS = ( TASK_NAME, TASK_DESCRIPTION, ON_ERROR, ON_COMPLETE, ON_SUCCESS, POLICIES, ACTION, WORKFLOW, PUBLISH, TASK_INPUT, REQUIRES, RETRY, WAIT_BEFORE, WAIT_AFTER, PAUSE_BEFORE, TIMEOUT, WITH_ITEMS, KEEP_RESULT, TARGET ) = ( 'name', 'description', 'on_error', 'on_complete', 'on_success', 'policies', 'action', 'workflow', 'publish', 'input', 'requires', 'retry', 'wait_before', 'wait_after', 'pause_before', 'timeout', 'with_items', 'keep_result', 'target' ) _TASKS_TASK_DEFAULTS = [ ON_ERROR, ON_COMPLETE, ON_SUCCESS, REQUIRES, RETRY, WAIT_BEFORE, WAIT_AFTER, PAUSE_BEFORE, TIMEOUT ] _SIGNAL_DATA_KEYS = ( SIGNAL_DATA_INPUT, SIGNAL_DATA_PARAMS ) = ( 'input', 'params' ) ATTRIBUTES = ( WORKFLOW_DATA, ALARM_URL, EXECUTIONS ) = ( 'data', 'alarm_url', 'executions' ) properties_schema = { NAME: properties.Schema( properties.Schema.STRING, _('Workflow name.') ), TYPE: properties.Schema( properties.Schema.STRING, _('Workflow type.'), constraints=[ constraints.AllowedValues(['direct', 'reverse']) ], required=True, update_allowed=True ), DESCRIPTION: properties.Schema( properties.Schema.STRING, _('Workflow description.'), update_allowed=True ), INPUT: properties.Schema( properties.Schema.MAP, _('Dictionary which contains input for workflow.'), update_allowed=True ), OUTPUT: properties.Schema( properties.Schema.MAP, _('Any data structure arbitrarily containing YAQL ' 'expressions that defines workflow output. May be ' 'nested.'), update_allowed=True ), PARAMS: properties.Schema( properties.Schema.MAP, _("Workflow additional parameters. If Workflow is reverse typed, " "params requires 'task_name', which defines initial task."), update_allowed=True ), TASK_DEFAULTS: properties.Schema( properties.Schema.MAP, _("Default settings for some of task " "attributes defined " "at workflow level."), support_status=support.SupportStatus(version='5.0.0'), schema={ ON_SUCCESS: properties.Schema( properties.Schema.LIST, _('List of tasks which will run after ' 'the task has completed successfully.') ), ON_ERROR: properties.Schema( properties.Schema.LIST, _('List of tasks which will run after ' 'the task has completed with an error.') ), ON_COMPLETE: properties.Schema( properties.Schema.LIST, _('List of tasks which will run after ' 'the task has completed regardless of whether ' 'it is successful or not.') ), REQUIRES: properties.Schema( properties.Schema.LIST, _('List of tasks which should be executed before ' 'this task. Used only in reverse workflows.') ), RETRY: properties.Schema( properties.Schema.MAP, _('Defines a pattern how task should be repeated in ' 'case of an error.') ), WAIT_BEFORE: properties.Schema( properties.Schema.INTEGER, _('Defines a delay in seconds that Mistral Engine' ' should wait before starting a task.') ), WAIT_AFTER: properties.Schema( properties.Schema.INTEGER, _('Defines a delay in seconds that Mistral Engine' ' should wait after a task has completed before' ' starting next tasks defined in ' 'on-success, on-error or on-complete.') ), PAUSE_BEFORE: properties.Schema( properties.Schema.BOOLEAN, _('Defines whether Mistral Engine should put the ' 'workflow on hold or not before starting a task') ), TIMEOUT: properties.Schema( properties.Schema.INTEGER, _('Defines a period of time in seconds after which ' 'a task will be failed automatically ' 'by engine if hasn\'t completed.') ), }, update_allowed=True ), TASKS: properties.Schema( properties.Schema.LIST, _('Dictionary containing workflow tasks.'), schema=properties.Schema( properties.Schema.MAP, schema={ TASK_NAME: properties.Schema( properties.Schema.STRING, _('Task name.'), required=True ), TASK_DESCRIPTION: properties.Schema( properties.Schema.STRING, _('Task description.') ), TASK_INPUT: properties.Schema( properties.Schema.MAP, _('Actual input parameter values of the task.') ), ACTION: properties.Schema( properties.Schema.STRING, _('Name of the action associated with the task. ' 'Either action or workflow may be defined in the ' 'task.') ), WORKFLOW: properties.Schema( properties.Schema.STRING, _('Name of the workflow associated with the task. ' 'Can be defined by intrinsic function get_resource ' 'or by name of the referenced workflow, i.e. ' '{ workflow: wf_name } or ' '{ workflow: { get_resource: wf_name }}. Either ' 'action or workflow may be defined in the task.') ), PUBLISH: properties.Schema( properties.Schema.MAP, _('Dictionary of variables to publish to ' 'the workflow context.') ), ON_SUCCESS: properties.Schema( properties.Schema.LIST, _('List of tasks which will run after ' 'the task has completed successfully.') ), ON_ERROR: properties.Schema( properties.Schema.LIST, _('List of tasks which will run after ' 'the task has completed with an error.') ), ON_COMPLETE: properties.Schema( properties.Schema.LIST, _('List of tasks which will run after ' 'the task has completed regardless of whether ' 'it is successful or not.') ), POLICIES: properties.Schema( properties.Schema.MAP, _('Dictionary-like section defining task policies ' 'that influence how Mistral Engine runs tasks. Must ' 'satisfy Mistral DSL v2.'), support_status=support.SupportStatus( status=support.DEPRECATED, version='5.0.0', message=_('Add needed policies directly to ' 'the task, Policy keyword is not ' 'needed'), previous_status=support.SupportStatus( version='2015.1')) ), REQUIRES: properties.Schema( properties.Schema.LIST, _('List of tasks which should be executed before ' 'this task. Used only in reverse workflows.') ), RETRY: properties.Schema( properties.Schema.MAP, _('Defines a pattern how task should be repeated in ' 'case of an error.'), support_status=support.SupportStatus(version='5.0.0') ), WAIT_BEFORE: properties.Schema( properties.Schema.INTEGER, _('Defines a delay in seconds that Mistral Engine ' 'should wait before starting a task.'), support_status=support.SupportStatus(version='5.0.0') ), WAIT_AFTER: properties.Schema( properties.Schema.INTEGER, _('Defines a delay in seconds that Mistral ' 'Engine should wait after ' 'a task has completed before starting next tasks ' 'defined in on-success, on-error or on-complete.'), support_status=support.SupportStatus(version='5.0.0') ), PAUSE_BEFORE: properties.Schema( properties.Schema.BOOLEAN, _('Defines whether Mistral Engine should ' 'put the workflow on hold ' 'or not before starting a task.'), support_status=support.SupportStatus(version='5.0.0') ), TIMEOUT: properties.Schema( properties.Schema.INTEGER, _('Defines a period of time in seconds after which a ' 'task will be failed automatically by engine ' 'if hasn\'t completed.'), support_status=support.SupportStatus(version='5.0.0') ), WITH_ITEMS: properties.Schema( properties.Schema.STRING, _('If configured, it allows to run action or workflow ' 'associated with a task multiple times ' 'on a provided list of items.'), support_status=support.SupportStatus(version='5.0.0') ), KEEP_RESULT: properties.Schema( properties.Schema.BOOLEAN, _('Allowing not to store action results ' 'after task completion.'), support_status=support.SupportStatus(version='5.0.0') ), TARGET: properties.Schema( properties.Schema.STRING, _('It defines an executor to which task action ' 'should be sent to.'), support_status=support.SupportStatus(version='5.0.0') ), }, ), required=True, update_allowed=True ) } attributes_schema = { WORKFLOW_DATA: attributes.Schema( _('A dictionary which contains name and input of the workflow.'), type=attributes.Schema.MAP ), ALARM_URL: attributes.Schema( _("A signed url to create executions for workflows specified in " "Workflow resource."), type=attributes.Schema.STRING ), EXECUTIONS: attributes.Schema( _("List of workflows' executions, each of them is a dictionary " "with information about execution. Each dictionary returns " "values for next keys: id, workflow_name, created_at, " "updated_at, state for current execution state, input, output."), type=attributes.Schema.LIST ) } def get_reference_id(self): return self._workflow_name() def _validate_signal_data(self, data): if data is not None: input_value = data.get(self.SIGNAL_DATA_INPUT) params_value = data.get(self.SIGNAL_DATA_PARAMS) if input_value is not None: if not isinstance(input_value, dict): message = (_('Input in signal data must be a map, ' 'find a %s') % type(input_value)) raise exception.StackValidationFailed( error=_('Signal data error'), message=message) for key in six.iterkeys(input_value): if (self.properties.get(self.INPUT) is None or key not in self.properties.get(self.INPUT)): message = _('Unknown input %s') % key raise exception.StackValidationFailed( error=_('Signal data error'), message=message) if params_value is not None and not isinstance(params_value, dict): message = (_('Params must be a map, find a ' '%s') % type(params_value)) raise exception.StackValidationFailed( error=_('Signal data error'), message=message) def validate(self): super(Workflow, self).validate() if self.properties.get(self.TYPE) == 'reverse': params = self.properties.get(self.PARAMS) if params is None or not params.get('task_name'): raise exception.StackValidationFailed( error=_('Mistral resource validation error'), path=[self.name, ('properties' if self.stack.t.VERSION == 'heat_template_version' else 'Properties'), self.PARAMS], message=_("'task_name' is not assigned in 'params' " "in case of reverse type workflow.") ) for task in self.properties.get(self.TASKS): wf_value = task.get(self.WORKFLOW) action_value = task.get(self.ACTION) if wf_value and action_value: raise exception.ResourcePropertyConflict(self.WORKFLOW, self.ACTION) if not wf_value and not action_value: raise exception.PropertyUnspecifiedError(self.WORKFLOW, self.ACTION) if (task.get(self.REQUIRES) is not None and self.properties.get(self.TYPE)) == 'direct': msg = _("task %(task)s contains property 'requires' " "in case of direct workflow. Only reverse workflows " "can contain property 'requires'.") % { 'name': self.name, 'task': task.get(self.TASK_NAME) } raise exception.StackValidationFailed( error=_('Mistral resource validation error'), path=[self.name, ('properties' if self.stack.t.VERSION == 'heat_template_version' else 'Properties'), self.TASKS, task.get(self.TASK_NAME), self.REQUIRES], message=msg) if task.get(self.POLICIES) is not None: for task_item in task.get(self.POLICIES): if task.get(task_item) is not None: msg = _('Property %(policies)s and %(item)s cannot be ' 'used both at one time.') % { 'policies': self.POLICIES, 'item': task_item } raise exception.StackValidationFailed(message=msg) def _workflow_name(self): return self.properties.get(self.NAME) or self.physical_resource_name() def build_tasks(self, props): for task in props[self.TASKS]: current_task = {} wf_value = task.get(self.WORKFLOW) if wf_value is not None: if wf_value in [res.resource_id for res in six.itervalues(self.stack)]: current_task.update({self.WORKFLOW: wf_value}) else: msg = _("No such workflow %s") % wf_value raise ValueError(msg) # backward support for kilo. if task.get(self.POLICIES) is not None: task.update(task.get(self.POLICIES)) task_keys = [key for key in self._TASKS_KEYS if key not in [ self.WORKFLOW, self.TASK_NAME, self.POLICIES ]] for task_prop in task_keys: if task.get(task_prop) is not None: current_task.update( {task_prop.replace('_', '-'): task[task_prop]}) yield {task[self.TASK_NAME]: current_task} def prepare_properties(self, props): """Prepare correct YAML-formatted definition for Mistral.""" defn_name = self._workflow_name() definition = {'version': '2.0', defn_name: {self.TYPE: props.get(self.TYPE), self.DESCRIPTION: props.get( self.DESCRIPTION), self.OUTPUT: props.get(self.OUTPUT)}} for key in list(definition[defn_name].keys()): if definition[defn_name][key] is None: del definition[defn_name][key] if props.get(self.INPUT) is not None: definition[defn_name][self.INPUT] = list(props.get( self.INPUT).keys()) definition[defn_name][self.TASKS] = {} for task in self.build_tasks(props): definition.get(defn_name).get(self.TASKS).update(task) if props.get(self.TASK_DEFAULTS) is not None: definition[defn_name][self.TASK_DEFAULTS.replace('_', '-')] = { k.replace('_', '-'): v for k, v in six.iteritems(props.get(self.TASK_DEFAULTS)) if v} return yaml.dump(definition, Dumper=yaml.CSafeDumper if hasattr(yaml, 'CSafeDumper') else yaml.SafeDumper) def handle_create(self): super(Workflow, self).handle_create() props = self.prepare_properties(self.properties) try: workflow = self.client().workflows.create(props) except Exception as ex: raise exception.ResourceFailure(ex, self) # NOTE(prazumovsky): Mistral uses unique names for resource # identification. self.resource_id_set(workflow[0].name) def handle_signal(self, details=None): self._validate_signal_data(details) result_input = {} result_params = {} if details is not None: if details.get(self.INPUT) is not None: # NOTE(prazumovsky): Signal can contains some data, interesting # for workflow, e.g. inputs. So, if signal data contains input # we update override inputs, other leaved defined in template. for key, value in six.iteritems( self.properties.get(self.INPUT)): result_input.update( {key: details.get( self.SIGNAL_DATA_INPUT).get(key) or value}) if details.get(self.SIGNAL_DATA_PARAMS) is not None: if self.properties.get(self.PARAMS) is not None: result_params.update(self.properties.get(self.PARAMS)) result_params.update(details.get(self.SIGNAL_DATA_PARAMS)) if not result_input and self.properties.get(self.INPUT): result_input.update(self.properties.get(self.INPUT)) if not result_params and self.properties.get(self.PARAMS): result_params.update(self.properties.get(self.PARAMS)) try: execution = self.client().executions.create( self._workflow_name(), jsonutils.dumps(result_input), **result_params) except Exception as ex: raise exception.ResourceFailure(ex, self) executions = [execution.id] if self.EXECUTIONS in self.data(): executions.extend(self.data().get(self.EXECUTIONS).split(',')) self.data_set(self.EXECUTIONS, ','.join(executions)) def handle_update(self, json_snippet, tmpl_diff, prop_diff): update_allowed = [self.INPUT, self.PARAMS, self.DESCRIPTION] for prop in update_allowed: if prop in prop_diff: del prop_diff[prop] if len(prop_diff) > 0: new_props = self.prepare_properties(tmpl_diff['Properties']) try: workflow = self.client().workflows.update(new_props) except Exception as ex: raise exception.ResourceFailure(ex, self) self.data_set(self.NAME, workflow[0].name) self.resource_id_set(workflow[0].name) def _delete_executions(self): if self.data().get(self.EXECUTIONS): for id in self.data().get(self.EXECUTIONS).split(','): try: self.client().executions.delete(id) except Exception as ex: self.client_plugin().ignore_not_found(ex) self.data_delete('executions') def handle_delete(self): self._delete_executions() return super(Workflow, self).handle_delete() def _resolve_attribute(self, name): if name == self.EXECUTIONS: if self.EXECUTIONS not in self.data(): return [] def parse_execution_response(execution): return { 'id': execution.id, 'workflow_name': execution.workflow_name, 'created_at': execution.created_at, 'updated_at': execution.updated_at, 'state': execution.state, 'input': jsonutils.loads(six.text_type(execution.input)), 'output': jsonutils.loads(six.text_type(execution.output)) } return [parse_execution_response( self.client().executions.get(exec_id)) for exec_id in self.data().get(self.EXECUTIONS).split(',')] elif name == self.WORKFLOW_DATA: return {self.NAME: self.resource_id, self.INPUT: self.properties.get(self.INPUT)} elif name == self.ALARM_URL: return six.text_type(self._get_ec2_signed_url()) # TODO(tlashchova): remove this method when mistralclient>1.0.0 is used. def _show_resource(self): workflow = self.client().workflows.get(self.resource_id) if hasattr(workflow, 'to_dict'): super(Workflow, self)._show_resource() return workflow._data def resource_mapping(): return { 'OS::Mistral::Workflow': Workflow }
en
0.756955
# # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. # backward support for kilo. Prepare correct YAML-formatted definition for Mistral. # NOTE(prazumovsky): Mistral uses unique names for resource # identification. # NOTE(prazumovsky): Signal can contains some data, interesting # for workflow, e.g. inputs. So, if signal data contains input # we update override inputs, other leaved defined in template. # TODO(tlashchova): remove this method when mistralclient>1.0.0 is used.
1.63323
2
keyvaultlib/key_vault.py
Tom-Ganor/keyvaultlib
0
6632211
import logging from logging import Logger # noinspection PyPackageRequirements from azure.keyvault import KeyVaultClient from msrestazure.azure_active_directory import MSIAuthentication as MSICredentials, ServicePrincipalCredentials class KeyVaultOAuthClient(KeyVaultClient): """ KeyVaultOAuthClient is a KeyVault client wrapper that supports both MSI and ADAL authentication mechanisms. It's helpful for scenarios where one is transitioning from ADAL authentication to MSI, and exists to save the small code duplication of using either MSIAuthentication or ServicePrincipalCredentials. """ KEY_VAULT_RESOURCE_URL = 'https://vault.azure.net' KEY_VAULT_URL_TEMPLATE = 'https://{key_vault_name}.vault.azure.net/' LATEST_SECRET_VERSION = '' def __init__(self, client_id=None, client_secret=None, tenant_id=None, use_msi=False, logger=None, *args, **kwargs): # type: (str, str, str, bool, Logger|logging) -> None """ Initiates a new key vault client with either MSI or ADAL token providers underneath. :param client_id: An optional (When using MSI) client ID - Of a user or an application that is authorized with your KeyVault resources :param client_secret: An optional (When using MSI) client secret - Of a user or an application that is authorized with your KeyVault resources :param tenant_id: An optional (When using MSI) tenant ID of your KeyVault resources :param use_msi: A flag indicated if the client should use MSI (Managed-Service-Identity) to get an OAuth token for your KeyVault resources :param logger: An optional logger to use in case of initialization errors """ self._logger = logger or logging.getLogger(KeyVaultOAuthClient.__class__.__name__) if not use_msi and (not client_id or not client_secret or not tenant_id): err = 'You should either use MSI, or pass a valid client ID, secret and tenant ID' self._logger.error(err) raise ValueError(err) self._using_msi = use_msi if use_msi: msi_creds = MSICredentials(resource=self.KEY_VAULT_RESOURCE_URL) super(KeyVaultOAuthClient, self).__init__(msi_creds, *args, **kwargs) else: adal_creds = ServicePrincipalCredentials(client_id, client_secret, tenant=tenant_id, resource=self.KEY_VAULT_RESOURCE_URL) super(KeyVaultOAuthClient, self).__init__(adal_creds, *args, **kwargs) def get_secret_with_key_vault_name(self, key_vault_name, secret_name, secret_version=LATEST_SECRET_VERSION): # type: (str, str, str) -> basestring """ Use this wrapper to get a KeyVault secret by KeyVault name (i.e. not by a full URL). If successful, the secret's value will be returned, otherwise an error will be logged and an exception thrown. :param key_vault_name: Name of KeyVault resource (e.g. For 'https://mykv.vault.azure.net/' the name is 'mykv') :param secret_name: The secret's name inside the KeyVault resource :param secret_version: An optional version of the secret to fetch (latest being the default) :return: The secret's value as a string """ key_vault_url = self.KEY_VAULT_URL_TEMPLATE.format(key_vault_name=key_vault_name) try: return self.get_secret(key_vault_url, secret_name, secret_version).value except Exception as e: self._logger.error('Failed retrieving secret vault={} secret={} version={} using_msi={}'.format( key_vault_url, secret_name, secret_version, self._using_msi )) raise e
import logging from logging import Logger # noinspection PyPackageRequirements from azure.keyvault import KeyVaultClient from msrestazure.azure_active_directory import MSIAuthentication as MSICredentials, ServicePrincipalCredentials class KeyVaultOAuthClient(KeyVaultClient): """ KeyVaultOAuthClient is a KeyVault client wrapper that supports both MSI and ADAL authentication mechanisms. It's helpful for scenarios where one is transitioning from ADAL authentication to MSI, and exists to save the small code duplication of using either MSIAuthentication or ServicePrincipalCredentials. """ KEY_VAULT_RESOURCE_URL = 'https://vault.azure.net' KEY_VAULT_URL_TEMPLATE = 'https://{key_vault_name}.vault.azure.net/' LATEST_SECRET_VERSION = '' def __init__(self, client_id=None, client_secret=None, tenant_id=None, use_msi=False, logger=None, *args, **kwargs): # type: (str, str, str, bool, Logger|logging) -> None """ Initiates a new key vault client with either MSI or ADAL token providers underneath. :param client_id: An optional (When using MSI) client ID - Of a user or an application that is authorized with your KeyVault resources :param client_secret: An optional (When using MSI) client secret - Of a user or an application that is authorized with your KeyVault resources :param tenant_id: An optional (When using MSI) tenant ID of your KeyVault resources :param use_msi: A flag indicated if the client should use MSI (Managed-Service-Identity) to get an OAuth token for your KeyVault resources :param logger: An optional logger to use in case of initialization errors """ self._logger = logger or logging.getLogger(KeyVaultOAuthClient.__class__.__name__) if not use_msi and (not client_id or not client_secret or not tenant_id): err = 'You should either use MSI, or pass a valid client ID, secret and tenant ID' self._logger.error(err) raise ValueError(err) self._using_msi = use_msi if use_msi: msi_creds = MSICredentials(resource=self.KEY_VAULT_RESOURCE_URL) super(KeyVaultOAuthClient, self).__init__(msi_creds, *args, **kwargs) else: adal_creds = ServicePrincipalCredentials(client_id, client_secret, tenant=tenant_id, resource=self.KEY_VAULT_RESOURCE_URL) super(KeyVaultOAuthClient, self).__init__(adal_creds, *args, **kwargs) def get_secret_with_key_vault_name(self, key_vault_name, secret_name, secret_version=LATEST_SECRET_VERSION): # type: (str, str, str) -> basestring """ Use this wrapper to get a KeyVault secret by KeyVault name (i.e. not by a full URL). If successful, the secret's value will be returned, otherwise an error will be logged and an exception thrown. :param key_vault_name: Name of KeyVault resource (e.g. For 'https://mykv.vault.azure.net/' the name is 'mykv') :param secret_name: The secret's name inside the KeyVault resource :param secret_version: An optional version of the secret to fetch (latest being the default) :return: The secret's value as a string """ key_vault_url = self.KEY_VAULT_URL_TEMPLATE.format(key_vault_name=key_vault_name) try: return self.get_secret(key_vault_url, secret_name, secret_version).value except Exception as e: self._logger.error('Failed retrieving secret vault={} secret={} version={} using_msi={}'.format( key_vault_url, secret_name, secret_version, self._using_msi )) raise e
en
0.704915
# noinspection PyPackageRequirements KeyVaultOAuthClient is a KeyVault client wrapper that supports both MSI and ADAL authentication mechanisms. It's helpful for scenarios where one is transitioning from ADAL authentication to MSI, and exists to save the small code duplication of using either MSIAuthentication or ServicePrincipalCredentials. # type: (str, str, str, bool, Logger|logging) -> None Initiates a new key vault client with either MSI or ADAL token providers underneath. :param client_id: An optional (When using MSI) client ID - Of a user or an application that is authorized with your KeyVault resources :param client_secret: An optional (When using MSI) client secret - Of a user or an application that is authorized with your KeyVault resources :param tenant_id: An optional (When using MSI) tenant ID of your KeyVault resources :param use_msi: A flag indicated if the client should use MSI (Managed-Service-Identity) to get an OAuth token for your KeyVault resources :param logger: An optional logger to use in case of initialization errors # type: (str, str, str) -> basestring Use this wrapper to get a KeyVault secret by KeyVault name (i.e. not by a full URL). If successful, the secret's value will be returned, otherwise an error will be logged and an exception thrown. :param key_vault_name: Name of KeyVault resource (e.g. For 'https://mykv.vault.azure.net/' the name is 'mykv') :param secret_name: The secret's name inside the KeyVault resource :param secret_version: An optional version of the secret to fetch (latest being the default) :return: The secret's value as a string
2.373065
2
blog/models.py
asemarian/weCode
1
6632212
<reponame>asemarian/weCode<filename>blog/models.py from django.db import models from django.contrib.auth.models import User from django.urls import reverse from datetime import datetime, date from ckeditor.fields import RichTextField from django.db.models.signals import pre_save from hitcount.models import HitCountMixin, HitCount from django.contrib.contenttypes.fields import GenericRelation from taggit.managers import TaggableManager # from django.utils.text import slugify class Category(models.Model): name = models.CharField(max_length=255) slug = models.SlugField(unique=True, allow_unicode=True) class Meta: ordering = ('name',) def __str__(self): return self.name def get_absolute_url(self): return f'/{self.slug}/' class Post(models.Model, HitCountMixin): title = models.CharField(max_length=255) slug = models.SlugField(unique=True, allow_unicode=True) summary = models.CharField(max_length=500) header_image = models.ImageField(null=True, blank=True, upload_to="images/") tags = TaggableManager() author = models.ForeignKey(User, on_delete=models.CASCADE) body = RichTextField(blank=True, null=True) post_date = models.DateField(auto_now_add=True) update_date = models.DateField(auto_now=True) category = models.ForeignKey(Category, related_name='posts', on_delete=models.CASCADE) featured = models.BooleanField(default=False) views = GenericRelation(HitCount, object_id_field='object_pk',related_query_name='hit_count_generic_relation') class Meta: ordering = ('-post_date',) def __str__(self): return self.title + ' | ' + str(self.author) + ' | ' + str(self.post_date) def get_absolute_url(self): return reverse('post-detail', kwargs={"slug":self.slug}) def create_slug(instance, new_slug=None): slug = arabic_slugify(instance.title) if new_slug is not None: slug = new_slug qs = Post.objects.filter(slug=slug).order_by("-id") exists = qs.exists() if exists: new_slug = "%s-%s" %(slug, qs.first().id) return create_slug(instance, new_slug=new_slug) return slug def arabic_slugify(str): str = str.replace(" ", "-") str = str.replace(",", "-") str = str.replace("(", "-") str = str.replace(")", "") str = str.replace("؟", "") return str def pre_save_post_reciever(sender, instance, *args, **kwargs): if not instance.slug: instance.slug = create_slug(instance) pre_save.connect(pre_save_post_reciever, sender=Post) class Comment(models.Model): post = models.ForeignKey(Post, related_name="comments", on_delete=models.CASCADE) user = models.ForeignKey(User, on_delete=models.CASCADE) body = models.TextField() post_date = models.DateField(auto_now_add=True) update_date = models.DateField(auto_now=True) def __str__(self): return '%s - %s' % (self.post.title, self.user)
from django.db import models from django.contrib.auth.models import User from django.urls import reverse from datetime import datetime, date from ckeditor.fields import RichTextField from django.db.models.signals import pre_save from hitcount.models import HitCountMixin, HitCount from django.contrib.contenttypes.fields import GenericRelation from taggit.managers import TaggableManager # from django.utils.text import slugify class Category(models.Model): name = models.CharField(max_length=255) slug = models.SlugField(unique=True, allow_unicode=True) class Meta: ordering = ('name',) def __str__(self): return self.name def get_absolute_url(self): return f'/{self.slug}/' class Post(models.Model, HitCountMixin): title = models.CharField(max_length=255) slug = models.SlugField(unique=True, allow_unicode=True) summary = models.CharField(max_length=500) header_image = models.ImageField(null=True, blank=True, upload_to="images/") tags = TaggableManager() author = models.ForeignKey(User, on_delete=models.CASCADE) body = RichTextField(blank=True, null=True) post_date = models.DateField(auto_now_add=True) update_date = models.DateField(auto_now=True) category = models.ForeignKey(Category, related_name='posts', on_delete=models.CASCADE) featured = models.BooleanField(default=False) views = GenericRelation(HitCount, object_id_field='object_pk',related_query_name='hit_count_generic_relation') class Meta: ordering = ('-post_date',) def __str__(self): return self.title + ' | ' + str(self.author) + ' | ' + str(self.post_date) def get_absolute_url(self): return reverse('post-detail', kwargs={"slug":self.slug}) def create_slug(instance, new_slug=None): slug = arabic_slugify(instance.title) if new_slug is not None: slug = new_slug qs = Post.objects.filter(slug=slug).order_by("-id") exists = qs.exists() if exists: new_slug = "%s-%s" %(slug, qs.first().id) return create_slug(instance, new_slug=new_slug) return slug def arabic_slugify(str): str = str.replace(" ", "-") str = str.replace(",", "-") str = str.replace("(", "-") str = str.replace(")", "") str = str.replace("؟", "") return str def pre_save_post_reciever(sender, instance, *args, **kwargs): if not instance.slug: instance.slug = create_slug(instance) pre_save.connect(pre_save_post_reciever, sender=Post) class Comment(models.Model): post = models.ForeignKey(Post, related_name="comments", on_delete=models.CASCADE) user = models.ForeignKey(User, on_delete=models.CASCADE) body = models.TextField() post_date = models.DateField(auto_now_add=True) update_date = models.DateField(auto_now=True) def __str__(self): return '%s - %s' % (self.post.title, self.user)
en
0.23675
# from django.utils.text import slugify
1.991292
2
examples/__init__.py
HANhuiyu/SpikingStereoMatching
1
6632213
from examples.nst_letters import run_experiment_nst from examples.two_fans import run_experiment_fans from examples.pendulum import run_experiment_pendulum
from examples.nst_letters import run_experiment_nst from examples.two_fans import run_experiment_fans from examples.pendulum import run_experiment_pendulum
none
1
1.040603
1
python_code/vnev/Lib/site-packages/jdcloud_sdk/services/cdn/models/WafBlackRuleModel.py
Ureimu/weather-robot
14
6632214
<gh_stars>10-100 # coding=utf8 # Copyright 2018 JDCLOUD.COM # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # # NOTE: This class is auto generated by the jdcloud code generator program. class WafBlackRuleModel(object): def __init__(self, id=None, matchOp=None, val=None, valZh=None, enable=None, action=None, updateTime=None): """ :param id: (Optional) 黑名单规则id :param matchOp: (Optional) 匹配模式,uri类型有效,0=完全匹配 1=前缀匹配 2=包含 3=正则 4=大于 5=后缀 :param val: (Optional) 匹配值 :param valZh: (Optional) 匹配值的中文名 :param enable: (Optional) 是否启用, true为启用,false为未启用 :param action: (Optional) null :param updateTime: (Optional) 黑名单的修改时间,UTC时间 """ self.id = id self.matchOp = matchOp self.val = val self.valZh = valZh self.enable = enable self.action = action self.updateTime = updateTime
# coding=utf8 # Copyright 2018 JDCLOUD.COM # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # # NOTE: This class is auto generated by the jdcloud code generator program. class WafBlackRuleModel(object): def __init__(self, id=None, matchOp=None, val=None, valZh=None, enable=None, action=None, updateTime=None): """ :param id: (Optional) 黑名单规则id :param matchOp: (Optional) 匹配模式,uri类型有效,0=完全匹配 1=前缀匹配 2=包含 3=正则 4=大于 5=后缀 :param val: (Optional) 匹配值 :param valZh: (Optional) 匹配值的中文名 :param enable: (Optional) 是否启用, true为启用,false为未启用 :param action: (Optional) null :param updateTime: (Optional) 黑名单的修改时间,UTC时间 """ self.id = id self.matchOp = matchOp self.val = val self.valZh = valZh self.enable = enable self.action = action self.updateTime = updateTime
en
0.623542
# coding=utf8 # Copyright 2018 JDCLOUD.COM # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # # NOTE: This class is auto generated by the jdcloud code generator program. :param id: (Optional) 黑名单规则id :param matchOp: (Optional) 匹配模式,uri类型有效,0=完全匹配 1=前缀匹配 2=包含 3=正则 4=大于 5=后缀 :param val: (Optional) 匹配值 :param valZh: (Optional) 匹配值的中文名 :param enable: (Optional) 是否启用, true为启用,false为未启用 :param action: (Optional) null :param updateTime: (Optional) 黑名单的修改时间,UTC时间
1.699171
2
src/pudl/workspace/setup.py
kevinsung/pudl
285
6632215
<filename>src/pudl/workspace/setup.py """Tools for setting up and managing PUDL workspaces.""" import importlib import logging import pathlib import shutil import yaml from pudl import constants as pc logger = logging.getLogger(__name__) def set_defaults(pudl_in, pudl_out, clobber=False): """ Set default user input and output locations in ``$HOME/.pudl.yml``. Create a user settings file for future reference, that defines the default PUDL input and output directories. If this file already exists, behavior depends on the clobber parameter, which is False by default. If it's True, the existing file is replaced. If False, the existing file is not changed. Args: pudl_in (os.PathLike): Path to be used as the default input directory for PUDL -- this is where :mod:`pudl.workspace.datastore` will look to find the ``data`` directory, full of data from public agencies. pudl_out (os.PathLike): Path to the default output directory for PUDL, where results of data processing will be organized. clobber (bool): If True and a user settings file exists, overwrite it. If False, do not alter the existing file. Defaults to False. Returns: None """ settings_file = pathlib.Path.home() / '.pudl.yml' if settings_file.exists(): if clobber: logger.info(f"{settings_file} exists: clobbering.") else: logger.info(f"{settings_file} exists: not clobbering.") return with settings_file.open(mode='w') as f: f.write(f"pudl_in: {pudl_in.expanduser().resolve()}\n") f.write(f"pudl_out: {pudl_out.expanduser().resolve()}\n") def get_defaults(): """ Read paths to default PUDL input/output dirs from user's $HOME/.pudl.yml. Args: None Returns: dict: The contents of the user's PUDL settings file, with keys ``pudl_in`` and ``pudl_out`` defining their default PUDL workspace. If the ``$HOME/.pudl.yml`` file does not exist, set these paths to None. """ settings_file = pathlib.Path.home() / '.pudl.yml' try: with pathlib.Path(settings_file).open() as f: default_workspace = yaml.safe_load(f) except FileNotFoundError: logger.info("PUDL user settings file .pudl.yml not found.") default_workspace = {"pudl_in": None, "pudl_out": None} return default_workspace # Ensure that no matter what the user has put in this file, we get fully # specified absolute paths out when we read it: pudl_in = ( pathlib.Path(default_workspace["pudl_in"]). expanduser(). resolve() ) pudl_out = ( pathlib.Path(default_workspace["pudl_out"]). expanduser(). resolve() ) return derive_paths(pudl_in, pudl_out) def derive_paths(pudl_in, pudl_out): """ Derive PUDL paths based on given input and output paths. If no configuration file path is provided, attempt to read in the user configuration from a file called .pudl.yml in the user's HOME directory. Presently the only values we expect are pudl_in and pudl_out, directories that store files that PUDL either depends on that rely on PUDL. Args: pudl_in (os.PathLike): Path to the directory containing the PUDL input files, most notably the ``data`` directory which houses the raw data downloaded from public agencies by the :mod:`pudl.workspace.datastore` tools. ``pudl_in`` may be the same directory as ``pudl_out``. pudl_out (os.PathLike): Path to the directory where PUDL should write the outputs it generates. These will be organized into directories according to the output format (sqlite, datapackage, etc.). Returns: dict: A dictionary containing common PUDL settings, derived from those read out of the YAML file. Mostly paths for inputs & outputs. """ # ps is short for pudl settings -- a dictionary of paths, etc. ps = {} # The only "inputs" are the datastore and example settings files: # Convert from input string to Path and make it absolute w/ resolve() pudl_in = pathlib.Path(pudl_in).expanduser().resolve() data_dir = pudl_in / "data" settings_dir = pudl_in / "settings" # Store these as strings... since we aren't using Paths everywhere yet: ps["pudl_in"] = str(pudl_in) ps["data_dir"] = str(data_dir) ps["settings_dir"] = str(settings_dir) # Everything else goes into outputs, generally organized by type of file: pudl_out = pathlib.Path(pudl_out).expanduser().resolve() ps["pudl_out"] = str(pudl_out) # One directory per output format, datapackage, sqlite, etc.: for fmt in pc.output_formats: ps[f"{fmt}_dir"] = str(pudl_out / fmt) ferc1_db_file = pathlib.Path(ps['sqlite_dir'], 'ferc1.sqlite') ps['ferc1_db'] = "sqlite:///" + str(ferc1_db_file.resolve()) ps['pudl_db'] = "sqlite:///" + str(pathlib.Path( ps['sqlite_dir'], 'pudl.sqlite')) ps['censusdp1tract_db'] = "sqlite:///" + str(pathlib.Path( ps['sqlite_dir'], 'censusdp1tract.sqlite')) return ps def init(pudl_in, pudl_out, clobber=False): """ Set up a new PUDL working environment based on the user settings. Args: pudl_in (os.PathLike): Path to the directory containing the PUDL input files, most notably the ``data`` directory which houses the raw data downloaded from public agencies by the :mod:`pudl.workspace.datastore` tools. ``pudl_in`` may be the same directory as ``pudl_out``. pudl_out (os.PathLike): Path to the directory where PUDL should write the outputs it generates. These will be organized into directories according to the output format (sqlite, datapackage, etc.). clobber (bool): if True, replace existing files. If False (the default) do not replace existing files. Returns: None """ # Generate paths for the workspace: ps = derive_paths(pudl_in, pudl_out) # Create tmp directory tmp_dir = pathlib.Path(ps["data_dir"], "tmp") tmp_dir.mkdir(parents=True, exist_ok=True) # These are files that may exist in the package_data directory, but that # we do not want to deploy into a user workspace: ignore_files = ['__init__.py', '.gitignore'] # Make a settings directory in the workspace, and deploy settings files: settings_dir = pathlib.Path(ps['settings_dir']) settings_dir.mkdir(parents=True, exist_ok=True) settings_pkg = "pudl.package_data.settings" deploy(settings_pkg, settings_dir, ignore_files, clobber=clobber) # Make several output directories: for fmt in pc.output_formats: format_dir = pathlib.Path(ps["pudl_out"], fmt) format_dir.mkdir(parents=True, exist_ok=True) def deploy(pkg_path, deploy_dir, ignore_files, clobber=False): """ Deploy all files from a package_data directory into a workspace. Args: pkg_path (str): Dotted module path to the subpackage inside of package_data containing the resources to be deployed. deploy_dir (os.PathLike): Directory on the filesystem to which the files within pkg_path should be deployed. ignore_files (iterable): List of filenames (strings) that may be present in the pkg_path subpackage, but that should be ignored. clobber (bool): if True, replace existing copies of the files that are being deployed from pkg_path to deploy_dir. If False, do not replace existing files. Returns: None """ files = [ file for file in importlib.resources.contents(pkg_path) if importlib.resources.is_resource(pkg_path, file) and file not in ignore_files ] for file in files: with importlib.resources.path(pkg_path, file) as f: dest_file = pathlib.Path(deploy_dir, file) if pathlib.Path.exists(dest_file): if clobber: logger.info(f"CLOBBERING existing file at {dest_file}.") else: logger.info(f"Skipping existing file at {dest_file}") continue shutil.copy(f, dest_file)
<filename>src/pudl/workspace/setup.py """Tools for setting up and managing PUDL workspaces.""" import importlib import logging import pathlib import shutil import yaml from pudl import constants as pc logger = logging.getLogger(__name__) def set_defaults(pudl_in, pudl_out, clobber=False): """ Set default user input and output locations in ``$HOME/.pudl.yml``. Create a user settings file for future reference, that defines the default PUDL input and output directories. If this file already exists, behavior depends on the clobber parameter, which is False by default. If it's True, the existing file is replaced. If False, the existing file is not changed. Args: pudl_in (os.PathLike): Path to be used as the default input directory for PUDL -- this is where :mod:`pudl.workspace.datastore` will look to find the ``data`` directory, full of data from public agencies. pudl_out (os.PathLike): Path to the default output directory for PUDL, where results of data processing will be organized. clobber (bool): If True and a user settings file exists, overwrite it. If False, do not alter the existing file. Defaults to False. Returns: None """ settings_file = pathlib.Path.home() / '.pudl.yml' if settings_file.exists(): if clobber: logger.info(f"{settings_file} exists: clobbering.") else: logger.info(f"{settings_file} exists: not clobbering.") return with settings_file.open(mode='w') as f: f.write(f"pudl_in: {pudl_in.expanduser().resolve()}\n") f.write(f"pudl_out: {pudl_out.expanduser().resolve()}\n") def get_defaults(): """ Read paths to default PUDL input/output dirs from user's $HOME/.pudl.yml. Args: None Returns: dict: The contents of the user's PUDL settings file, with keys ``pudl_in`` and ``pudl_out`` defining their default PUDL workspace. If the ``$HOME/.pudl.yml`` file does not exist, set these paths to None. """ settings_file = pathlib.Path.home() / '.pudl.yml' try: with pathlib.Path(settings_file).open() as f: default_workspace = yaml.safe_load(f) except FileNotFoundError: logger.info("PUDL user settings file .pudl.yml not found.") default_workspace = {"pudl_in": None, "pudl_out": None} return default_workspace # Ensure that no matter what the user has put in this file, we get fully # specified absolute paths out when we read it: pudl_in = ( pathlib.Path(default_workspace["pudl_in"]). expanduser(). resolve() ) pudl_out = ( pathlib.Path(default_workspace["pudl_out"]). expanduser(). resolve() ) return derive_paths(pudl_in, pudl_out) def derive_paths(pudl_in, pudl_out): """ Derive PUDL paths based on given input and output paths. If no configuration file path is provided, attempt to read in the user configuration from a file called .pudl.yml in the user's HOME directory. Presently the only values we expect are pudl_in and pudl_out, directories that store files that PUDL either depends on that rely on PUDL. Args: pudl_in (os.PathLike): Path to the directory containing the PUDL input files, most notably the ``data`` directory which houses the raw data downloaded from public agencies by the :mod:`pudl.workspace.datastore` tools. ``pudl_in`` may be the same directory as ``pudl_out``. pudl_out (os.PathLike): Path to the directory where PUDL should write the outputs it generates. These will be organized into directories according to the output format (sqlite, datapackage, etc.). Returns: dict: A dictionary containing common PUDL settings, derived from those read out of the YAML file. Mostly paths for inputs & outputs. """ # ps is short for pudl settings -- a dictionary of paths, etc. ps = {} # The only "inputs" are the datastore and example settings files: # Convert from input string to Path and make it absolute w/ resolve() pudl_in = pathlib.Path(pudl_in).expanduser().resolve() data_dir = pudl_in / "data" settings_dir = pudl_in / "settings" # Store these as strings... since we aren't using Paths everywhere yet: ps["pudl_in"] = str(pudl_in) ps["data_dir"] = str(data_dir) ps["settings_dir"] = str(settings_dir) # Everything else goes into outputs, generally organized by type of file: pudl_out = pathlib.Path(pudl_out).expanduser().resolve() ps["pudl_out"] = str(pudl_out) # One directory per output format, datapackage, sqlite, etc.: for fmt in pc.output_formats: ps[f"{fmt}_dir"] = str(pudl_out / fmt) ferc1_db_file = pathlib.Path(ps['sqlite_dir'], 'ferc1.sqlite') ps['ferc1_db'] = "sqlite:///" + str(ferc1_db_file.resolve()) ps['pudl_db'] = "sqlite:///" + str(pathlib.Path( ps['sqlite_dir'], 'pudl.sqlite')) ps['censusdp1tract_db'] = "sqlite:///" + str(pathlib.Path( ps['sqlite_dir'], 'censusdp1tract.sqlite')) return ps def init(pudl_in, pudl_out, clobber=False): """ Set up a new PUDL working environment based on the user settings. Args: pudl_in (os.PathLike): Path to the directory containing the PUDL input files, most notably the ``data`` directory which houses the raw data downloaded from public agencies by the :mod:`pudl.workspace.datastore` tools. ``pudl_in`` may be the same directory as ``pudl_out``. pudl_out (os.PathLike): Path to the directory where PUDL should write the outputs it generates. These will be organized into directories according to the output format (sqlite, datapackage, etc.). clobber (bool): if True, replace existing files. If False (the default) do not replace existing files. Returns: None """ # Generate paths for the workspace: ps = derive_paths(pudl_in, pudl_out) # Create tmp directory tmp_dir = pathlib.Path(ps["data_dir"], "tmp") tmp_dir.mkdir(parents=True, exist_ok=True) # These are files that may exist in the package_data directory, but that # we do not want to deploy into a user workspace: ignore_files = ['__init__.py', '.gitignore'] # Make a settings directory in the workspace, and deploy settings files: settings_dir = pathlib.Path(ps['settings_dir']) settings_dir.mkdir(parents=True, exist_ok=True) settings_pkg = "pudl.package_data.settings" deploy(settings_pkg, settings_dir, ignore_files, clobber=clobber) # Make several output directories: for fmt in pc.output_formats: format_dir = pathlib.Path(ps["pudl_out"], fmt) format_dir.mkdir(parents=True, exist_ok=True) def deploy(pkg_path, deploy_dir, ignore_files, clobber=False): """ Deploy all files from a package_data directory into a workspace. Args: pkg_path (str): Dotted module path to the subpackage inside of package_data containing the resources to be deployed. deploy_dir (os.PathLike): Directory on the filesystem to which the files within pkg_path should be deployed. ignore_files (iterable): List of filenames (strings) that may be present in the pkg_path subpackage, but that should be ignored. clobber (bool): if True, replace existing copies of the files that are being deployed from pkg_path to deploy_dir. If False, do not replace existing files. Returns: None """ files = [ file for file in importlib.resources.contents(pkg_path) if importlib.resources.is_resource(pkg_path, file) and file not in ignore_files ] for file in files: with importlib.resources.path(pkg_path, file) as f: dest_file = pathlib.Path(deploy_dir, file) if pathlib.Path.exists(dest_file): if clobber: logger.info(f"CLOBBERING existing file at {dest_file}.") else: logger.info(f"Skipping existing file at {dest_file}") continue shutil.copy(f, dest_file)
en
0.83142
Tools for setting up and managing PUDL workspaces. Set default user input and output locations in ``$HOME/.pudl.yml``. Create a user settings file for future reference, that defines the default PUDL input and output directories. If this file already exists, behavior depends on the clobber parameter, which is False by default. If it's True, the existing file is replaced. If False, the existing file is not changed. Args: pudl_in (os.PathLike): Path to be used as the default input directory for PUDL -- this is where :mod:`pudl.workspace.datastore` will look to find the ``data`` directory, full of data from public agencies. pudl_out (os.PathLike): Path to the default output directory for PUDL, where results of data processing will be organized. clobber (bool): If True and a user settings file exists, overwrite it. If False, do not alter the existing file. Defaults to False. Returns: None Read paths to default PUDL input/output dirs from user's $HOME/.pudl.yml. Args: None Returns: dict: The contents of the user's PUDL settings file, with keys ``pudl_in`` and ``pudl_out`` defining their default PUDL workspace. If the ``$HOME/.pudl.yml`` file does not exist, set these paths to None. # Ensure that no matter what the user has put in this file, we get fully # specified absolute paths out when we read it: Derive PUDL paths based on given input and output paths. If no configuration file path is provided, attempt to read in the user configuration from a file called .pudl.yml in the user's HOME directory. Presently the only values we expect are pudl_in and pudl_out, directories that store files that PUDL either depends on that rely on PUDL. Args: pudl_in (os.PathLike): Path to the directory containing the PUDL input files, most notably the ``data`` directory which houses the raw data downloaded from public agencies by the :mod:`pudl.workspace.datastore` tools. ``pudl_in`` may be the same directory as ``pudl_out``. pudl_out (os.PathLike): Path to the directory where PUDL should write the outputs it generates. These will be organized into directories according to the output format (sqlite, datapackage, etc.). Returns: dict: A dictionary containing common PUDL settings, derived from those read out of the YAML file. Mostly paths for inputs & outputs. # ps is short for pudl settings -- a dictionary of paths, etc. # The only "inputs" are the datastore and example settings files: # Convert from input string to Path and make it absolute w/ resolve() # Store these as strings... since we aren't using Paths everywhere yet: # Everything else goes into outputs, generally organized by type of file: # One directory per output format, datapackage, sqlite, etc.: Set up a new PUDL working environment based on the user settings. Args: pudl_in (os.PathLike): Path to the directory containing the PUDL input files, most notably the ``data`` directory which houses the raw data downloaded from public agencies by the :mod:`pudl.workspace.datastore` tools. ``pudl_in`` may be the same directory as ``pudl_out``. pudl_out (os.PathLike): Path to the directory where PUDL should write the outputs it generates. These will be organized into directories according to the output format (sqlite, datapackage, etc.). clobber (bool): if True, replace existing files. If False (the default) do not replace existing files. Returns: None # Generate paths for the workspace: # Create tmp directory # These are files that may exist in the package_data directory, but that # we do not want to deploy into a user workspace: # Make a settings directory in the workspace, and deploy settings files: # Make several output directories: Deploy all files from a package_data directory into a workspace. Args: pkg_path (str): Dotted module path to the subpackage inside of package_data containing the resources to be deployed. deploy_dir (os.PathLike): Directory on the filesystem to which the files within pkg_path should be deployed. ignore_files (iterable): List of filenames (strings) that may be present in the pkg_path subpackage, but that should be ignored. clobber (bool): if True, replace existing copies of the files that are being deployed from pkg_path to deploy_dir. If False, do not replace existing files. Returns: None
2.645661
3
ts/torch_handler/unit_tests/test_image_classifier.py
akarazniewicz/serve
1
6632216
# pylint: disable=W0621 # Using the same name as global function is part of pytest """ Basic unit test for ImageClassifier class. Ensures it can load and execute an example model """ import sys import pytest from ts.torch_handler.image_classifier import ImageClassifier from .test_utils.mock_context import MockContext sys.path.append('ts/torch_handler/unit_tests/models/tmp') @pytest.fixture() def model_setup(): context = MockContext() with open('ts/torch_handler/unit_tests/models/tmp/images/kitten.jpg', 'rb') as fin: image_bytes = fin.read() return (context, image_bytes) def test_initialize(model_setup): model_context, _ = model_setup handler = ImageClassifier() handler.initialize(model_context) assert(True) return handler def test_handle(model_setup): _, image_bytes = model_setup handler = test_initialize(model_setup) test_data = [{'data': image_bytes}] * 2 results = handler.handle(test_data, image_bytes) assert(len(results) == 2) assert('tiger_cat' in results[0])
# pylint: disable=W0621 # Using the same name as global function is part of pytest """ Basic unit test for ImageClassifier class. Ensures it can load and execute an example model """ import sys import pytest from ts.torch_handler.image_classifier import ImageClassifier from .test_utils.mock_context import MockContext sys.path.append('ts/torch_handler/unit_tests/models/tmp') @pytest.fixture() def model_setup(): context = MockContext() with open('ts/torch_handler/unit_tests/models/tmp/images/kitten.jpg', 'rb') as fin: image_bytes = fin.read() return (context, image_bytes) def test_initialize(model_setup): model_context, _ = model_setup handler = ImageClassifier() handler.initialize(model_context) assert(True) return handler def test_handle(model_setup): _, image_bytes = model_setup handler = test_initialize(model_setup) test_data = [{'data': image_bytes}] * 2 results = handler.handle(test_data, image_bytes) assert(len(results) == 2) assert('tiger_cat' in results[0])
en
0.729742
# pylint: disable=W0621 # Using the same name as global function is part of pytest Basic unit test for ImageClassifier class. Ensures it can load and execute an example model
2.631016
3
venv/Lib/site-packages/pandas/tests/series/indexing/test_delitem.py
OliviaNabbosa89/Disaster_Responses
0
6632217
import pytest from pandas import Index, Series import pandas._testing as tm class TestSeriesDelItem: def test_delitem(self): # GH#5542 # should delete the item inplace s = Series(range(5)) del s[0] expected = Series(range(1, 5), index=range(1, 5)) tm.assert_series_equal(s, expected) del s[1] expected = Series(range(2, 5), index=range(2, 5)) tm.assert_series_equal(s, expected) # only 1 left, del, add, del s = Series(1) del s[0] tm.assert_series_equal(s, Series(dtype="int64", index=Index([], dtype="int64"))) s[0] = 1 tm.assert_series_equal(s, Series(1)) del s[0] tm.assert_series_equal(s, Series(dtype="int64", index=Index([], dtype="int64"))) def test_delitem_object_index(self): # Index(dtype=object) s = Series(1, index=["a"]) del s["a"] tm.assert_series_equal( s, Series(dtype="int64", index=Index([], dtype="object")) ) s["a"] = 1 tm.assert_series_equal(s, Series(1, index=["a"])) del s["a"] tm.assert_series_equal( s, Series(dtype="int64", index=Index([], dtype="object")) ) def test_delitem_missing_key(self): # empty s = Series(dtype=object) with pytest.raises(KeyError, match=r"^0$"): del s[0]
import pytest from pandas import Index, Series import pandas._testing as tm class TestSeriesDelItem: def test_delitem(self): # GH#5542 # should delete the item inplace s = Series(range(5)) del s[0] expected = Series(range(1, 5), index=range(1, 5)) tm.assert_series_equal(s, expected) del s[1] expected = Series(range(2, 5), index=range(2, 5)) tm.assert_series_equal(s, expected) # only 1 left, del, add, del s = Series(1) del s[0] tm.assert_series_equal(s, Series(dtype="int64", index=Index([], dtype="int64"))) s[0] = 1 tm.assert_series_equal(s, Series(1)) del s[0] tm.assert_series_equal(s, Series(dtype="int64", index=Index([], dtype="int64"))) def test_delitem_object_index(self): # Index(dtype=object) s = Series(1, index=["a"]) del s["a"] tm.assert_series_equal( s, Series(dtype="int64", index=Index([], dtype="object")) ) s["a"] = 1 tm.assert_series_equal(s, Series(1, index=["a"])) del s["a"] tm.assert_series_equal( s, Series(dtype="int64", index=Index([], dtype="object")) ) def test_delitem_missing_key(self): # empty s = Series(dtype=object) with pytest.raises(KeyError, match=r"^0$"): del s[0]
en
0.644094
# GH#5542 # should delete the item inplace # only 1 left, del, add, del # Index(dtype=object) # empty
2.68467
3
azext_iot/sdk/iothub/service/models/registry_statistics_py3.py
YingXue/azure-iot-cli-extension
0
6632218
<gh_stars>0 # coding=utf-8 # -------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for # license information. # # Code generated by Microsoft (R) AutoRest Code Generator. # Changes may cause incorrect behavior and will be lost if the code is # regenerated. # -------------------------------------------------------------------------- from msrest.serialization import Model class RegistryStatistics(Model): """RegistryStatistics. :param total_device_count: :type total_device_count: long :param enabled_device_count: :type enabled_device_count: long :param disabled_device_count: :type disabled_device_count: long """ _attribute_map = { 'total_device_count': {'key': 'totalDeviceCount', 'type': 'long'}, 'enabled_device_count': {'key': 'enabledDeviceCount', 'type': 'long'}, 'disabled_device_count': {'key': 'disabledDeviceCount', 'type': 'long'}, } def __init__(self, *, total_device_count: int=None, enabled_device_count: int=None, disabled_device_count: int=None, **kwargs) -> None: super(RegistryStatistics, self).__init__(**kwargs) self.total_device_count = total_device_count self.enabled_device_count = enabled_device_count self.disabled_device_count = disabled_device_count
# coding=utf-8 # -------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for # license information. # # Code generated by Microsoft (R) AutoRest Code Generator. # Changes may cause incorrect behavior and will be lost if the code is # regenerated. # -------------------------------------------------------------------------- from msrest.serialization import Model class RegistryStatistics(Model): """RegistryStatistics. :param total_device_count: :type total_device_count: long :param enabled_device_count: :type enabled_device_count: long :param disabled_device_count: :type disabled_device_count: long """ _attribute_map = { 'total_device_count': {'key': 'totalDeviceCount', 'type': 'long'}, 'enabled_device_count': {'key': 'enabledDeviceCount', 'type': 'long'}, 'disabled_device_count': {'key': 'disabledDeviceCount', 'type': 'long'}, } def __init__(self, *, total_device_count: int=None, enabled_device_count: int=None, disabled_device_count: int=None, **kwargs) -> None: super(RegistryStatistics, self).__init__(**kwargs) self.total_device_count = total_device_count self.enabled_device_count = enabled_device_count self.disabled_device_count = disabled_device_count
en
0.564893
# coding=utf-8 # -------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for # license information. # # Code generated by Microsoft (R) AutoRest Code Generator. # Changes may cause incorrect behavior and will be lost if the code is # regenerated. # -------------------------------------------------------------------------- RegistryStatistics. :param total_device_count: :type total_device_count: long :param enabled_device_count: :type enabled_device_count: long :param disabled_device_count: :type disabled_device_count: long
1.842679
2
Apps/rsp/eqcheck.py
zhanghongce/ila-mcm-fmcad18
0
6632219
from traceStep import * import axiom # --------------------------- # Configurations # --------------------------- FORCE_ALL_INST_DECODE_TRUE = True DEBUG = False # --------------------------- # Prerequisites # --------------------------- def LAnd(l): if len(l) == 0: return z3.BoolVal(True) elif len(l) == 1: return l[0] else: return z3.And(l) def LOr(l): if len(l) == 0: return z3.BoolVal(True) elif len(l) == 1: return l[0] else: return z3.Or(l) # --------------------------- # clInstruction = openclrsp.CL_load_DV_N # gpuInstruction = [ gpuModel.ev_FETCH_L1 , gpuModel.inst_LD , gpuModel.inst_INV_L1_WG ] wvopListTp = namedtuple('wvopListTp','WG DV addr value') rvopListTp = namedtuple('rvopListTp','WG DV addr value') prevEVsequence = { gpuModel.inst_LD: [gpuModel.ev_FETCH_L1] , gpuModel.inst_INC_L1 : [gpuModel.ev_FETCH_L1] } postEVsequence = { gpuModel.inst_ST: [ gpuModel.ev_FLUSH_L1, gpuModel.ev_DEQLOC_L1 ], # fetch will also need this gpuModel.inst_INC_L1 : [ gpuModel.ev_FLUSH_L1 , gpuModel.ev_DEQLOC_L1 ] } blockSequence = { gpuModel.inst_FLU_L1_DV : gpuModel.ev_DEQMARKER_L1, # will wait for many of it gpuModel.inst_FLU_L1_WG : gpuModel.ev_DEQMARKER_L1 } # pre is already modeled in the sequence rfMapInst = { openclrsp.CL_load_na_or_WG: [ gpuModel.inst_LD ], openclrsp.CL_load_DV_N: [ gpuModel.inst_LD , gpuModel.inst_INV_L1_WG ], #Corret : [ gpuModel.inst_LD , gpuModel.inst_INV_L1_WG ], # wrong implementation: [ gpuModel.inst_INV_L1_WG , gpuModel.inst_LD ], openclrsp.CL_load_DV_R: [ gpuModel.inst_LD , gpuModel.inst_FLU_L1_DV , gpuModel.inst_INV_L1_WG ], #[ gpuModel.inst_LK_L2, gpuModel.inst_FLU_L1_DV, gpuModel.inst_INV_L1_WG, gpuModel.inst_LD, gpuModel.inst_UL_L2 ], # new: [ gpuModel.inst_LD , gpuModel.inst_FLU_L1_DV , gpuModel.inst_INV_L1_WG ] original : [ gpuModel.inst_LK_L2, gpuModel.inst_FLU_L1_DV, gpuModel.inst_INV_L1_WG, gpuModel.inst_LD, gpuModel.inst_UL_L2 ] openclrsp.CL_store_na_or_WG:[ gpuModel.inst_ST ], openclrsp.CL_store_DV_N: [ gpuModel.inst_FLU_L1_WG, gpuModel.inst_ST ], openclrsp.CL_store_DV_R: [ gpuModel.inst_LK_rmw_DV, gpuModel.inst_FLU_L1_DV, gpuModel.inst_INV_L1_DV, gpuModel.inst_ST, gpuModel.inst_FLU_L1_WG, gpuModel.inst_INV_L1_DV, gpuModel.inst_UL_rmw_DV ], # Wrong : [ gpuModel.inst_LK_L2, gpuModel.inst_FLU_L1_WG, gpuModel.inst_ST, gpuModel.inst_INV_L1_DV, gpuModel.inst_UL_L2 ], # this was the wrong thing openclrsp.CL_fetch_inc_WG: [ gpuModel.inst_INC_L1 ] } def HB(a,b): return a.timestamp < b.timestamp def HBd(a,b): return z3.Implies( z3.And( a.inst.decodeFunc, b.inst.decodeFunc), a.timestamp < b.timestamp ) # ============================================= # EQ CHECKER # ============================================= class eqchecker(object): def __init__(self, num_dev, num_wg, num_t): self.PiVarList = {} # pi_var_name (ts + statename) -> [ (sname, pivar, ts, addr ) ] self.PiVarListOld = {} self.TsThatWritesVar = {} self.TsThatWritesVarOld = {} self.TsNameToObj = {} self.ConstraintList = [] self.runProp = [] self.num_of_parent_inst_in_scene = 0 self.tsList = [] # Note this is not a list of PO self.PrevDecode = None # Note that the prev decode may be in self.num_dev, self.num_wg, self.num_t = num_dev, num_wg, num_t self.ConstrainedPiVarNames = set([]) # set of String : name of the PiVar self.L1fr_read_from = {} # ld --> fetch (if fetch.decode then must read from fetch else must others) # ====================================== # below is the content of the collector # ====================================== self.load_na_or_WG_list = [] self.load_DV_N_list = [] self.load_DV_R_list = [] self.store_na_or_WG_list = [] self.store_DV_N_list = [] self.store_DV_R_list = [] self.LOAD_list = [] self.STORE_list = [] self.rmw_list = [] self.name_to_list_mapping = {'load_na_or_WG':[self.load_na_or_WG_list, self.LOAD_list], 'load_DV_N':[self.load_DV_N_list ,self.LOAD_list], 'load_DV_R':[self.load_DV_R_list ,self.LOAD_list], 'store_na_or_WG':[self.store_na_or_WG_list ,self.STORE_list], 'store_DV_N':[self.store_DV_N_list ,self.STORE_list], 'store_DV_R':[self.store_DV_R_list ,self.STORE_list], 'fetch_inc_WG':[self.rmw_list, self.LOAD_list,self.STORE_list], } def addToList(self,inst): for lref in self.name_to_list_mapping[inst.name]: lref.append(inst) def addParentInst(self, addr, reg, e1, inst_func): def dummyRead(sname,addr = 0, entity = 0): return 0 #state = lambda stateName, addr = None , overWriteVA = None: ts1.stateReadFunc(stateName,addr,overWriteVA) paramDict = {'x': addr, 'r' :reg, 'Eid': e1 , 'state':dummyRead } inst = inst_func( **paramDict ) self.addToList(inst) return inst def addInstToScene(self, addr, reg, e1, inst_func, decodeWaitList, slot = None): # need to plug-in additional decode in the beginning, if it is not None, will add # unless specify slot, will not provide # addr = z3.Int('addr'+str(self.num_of_inst_in_scene) ) # the order here matters # reg = z3.Int('reg' +str(self.num_of_inst_in_scene) ) # the order here matters # and you need to check if you need an entity or not # e1 = self._genEntity() # entity for the instruction ts1 = TraceStep(entity = e1, TsThatWritesVar = self.TsThatWritesVar , TsNameToObj = self.TsNameToObj, ConstraintList = self.ConstraintList, PiVarList = self.PiVarList ) self.tsList.append(ts1) # tsList is gathering all these # concretize the instruction state = lambda stateName, addr = None , entity = None: ts1.stateReadFunc(stateName,addr,entity) paramDict = {'x': addr, 'r' :reg, 'Eid': e1 , 'state':state, 'num_dev':self.num_dev, 'num_wg': self.num_wg , 'num_t': self.num_t } if slot is not None: paramDict['slot'] = slot inst = inst_func( **paramDict ) # get the instruction # here is the logic for the pause after flush if decodeWaitList is not None: # then it should be a list if len( decodeWaitList ) == 1: extraDecodeExpr = ts1.stateReadFunc( 'L1fifotail' ) == decodeWaitList[0] # Previous is FLU_WG else: assert len( decodeWaitList ) == self.num_wg extraDecodeExpr = z3.And( [ \ ts1.stateReadFunc('L1fifotail' , entity = gpuModel.entity(e1.d, wgId ) ) == decodeWaitList[wgId] \ for wgId in range(self.num_wg) ] ) inst.decodeFunc = z3.And( inst.decodeFunc, extraDecodeExpr ) # change the decode function when necessary ts1.assignInst(inst) # r return inst,ts1 # PO relations are added by axioms # w/r vop relations are added by axioms # prev decode may be in effect for another instruction, but not in our case # but still it would be best to add parent instruction according their program order ?? def addAChain(self, Eid, parentInstruction, childInstructions, prevTimeStamp): # for one parent-instruction -> should return one child instruction # entity # gen addrs addr = z3.Int('addr'+str(self.num_of_parent_inst_in_scene) ) # the order here matters reg = z3.Int('reg' +str(self.num_of_parent_inst_in_scene) ) # the order here matters # and you need to check if you need an entity or not # e1 = self._genEntity() # entity for the instruction self.num_of_parent_inst_in_scene += 1 pInst_ref = self.addParentInst(addr = addr, reg = reg, e1 = Eid, inst_func = parentInstruction) #addr, reg, e1, inst_func prevTs = None blockSeqSlotList = [] instructions_in_the_chain = [] for uinst in childInstructions: _ , tsRef = self.addInstToScene(addr = addr, reg = reg, e1 = Eid, inst_func = uinst, decodeWaitList = self.PrevDecode ) instructions_in_the_chain.append(tsRef) self.ConstraintList.append( tsRef.timestamp > prevTimeStamp ) # every child instruction step is later than init or the previous barrier (not including evs) if prevTs is not None: self.ConstraintList.append( HB(prevTs, tsRef) ) # tsRef.timestamp > prevTs.timestamp ) # constraint 2: child instruction po else: # prevTs is None assert self.PrevDecode is None # check that flush is not the last child instruction !!! self.PrevDecode = None # reset it # constraint #3: child instructions must be executed self.ConstraintList.append( tsRef.inst.decodeFunc ) # Constriant DECODE # here, start to # check the need to add additional environmental transition if uinst in prevEVsequence: # FETCH -> LD seq = prevEVsequence[uinst] assert len(seq) == 1 # we only handle the case with one fetch (RVOP) fetch_ev = seq[0] inst_sub, tsRef_sub = self.addInstToScene(addr = addr , reg = reg, e1 = Eid, inst_func = fetch_ev, decodeWaitList = None, slot = None) # we don't require its decode to be true valueToBeWritten = tsRef.inst.updateDict[gpuModel.setSname('r',Eid)][0] # get from updateDict pInst_ref.rvop = rvopListTp( WG = tsRef, DV = tsRef_sub, addr = addr, value = valueToBeWritten ) pInst_ref.timestamp = tsRef.timestamp self.ConstraintList.append( HBd(tsRef_sub, tsRef) ) # only guarantee if both decodes are true self.ConstraintList.append( tsRef_sub.timestamp > 0 ) self.L1fr_read_from[tsRef] = tsRef_sub if uinst in postEVsequence: # ST -> will seq = postEVsequence[uinst] parent_or_prev_ts = tsRef # the one that will happenBefore it tmpTsList = [] # get the slot storeFIFOSlot = tsRef.stateReadFunc('L1fifotail') for post_inst in seq: inst_sub, tsRef_sub = self.addInstToScene(addr = addr , reg = reg, e1 = Eid, inst_func = post_inst, decodeWaitList = None, slot = storeFIFOSlot) self.ConstraintList.append( HB(parent_or_prev_ts, tsRef_sub) ) # parent_or_prev_ts.timestamp < tsRef_sub.timestamp ) self.ConstraintList.append( tsRef_sub.timestamp > 0 ) # parent_or_prev_ts = tsRef_sub tmpTsList.append(tsRef_sub) valueToBeRead = tsRef.stateReadFunc('r', addr = reg) # get from read its local register value pInst_ref.wvop = wvopListTp( WG = tsRef, DV = tmpTsList[0], addr = addr, value = valueToBeRead ) pInst_ref.timestamp = tsRef.timestamp if uinst in blockSequence: # FLUSH: either the device or workgroup blockSeqSlotList = [] flush_ev = blockSequence[uinst] # it will only be one instruction # but still you won't need to change decode ? if uinst is gpuModel.inst_FLU_L1_DV: # in this case we will need to create #WG flush MARKER and for wgId in range(self.num_wg): # read the slot from tsRef DEQ_MARKER_ENTITY = gpuModel.entity(Eid.d, wgId ) slot = tsRef.stateReadFunc( 'L1fifohead' , entity = DEQ_MARKER_ENTITY) # dep marker will need this blockSeqSlotList.append(slot + 1) # create a ts after it inst_sub, tsRef_sub = self.addInstToScene(addr = addr , reg = reg, e1 = DEQ_MARKER_ENTITY, inst_func = flush_ev, decodeWaitList = None, slot = slot) self.ConstraintList.append( HB(tsRef, tsRef_sub) ) # tsRef_sub.timestamp > tsRef.timestamp ) self.ConstraintList.append( tsRef_sub.timestamp > 0 ) # concat decode for all Wg # may be we can directly instantiate the function (to z3expr) here without calling it self.PrevDecode = blockSeqSlotList elif uinst is gpuModel.inst_FLU_L1_WG: slot = tsRef.stateReadFunc('L1fifohead') # dep marker will need this flush_ev = blockSequence[uinst] # it will only be one instruction self.PrevDecode = [ slot +1 ] inst_sub, tsRef_sub = self.addInstToScene(addr = addr , reg = reg, e1 = Eid, inst_func = flush_ev, decodeWaitList = None, slot = slot) self.ConstraintList.append( HB(tsRef, tsRef_sub) ) # tsRef_sub.timestamp > tsRef.timestamp ) else: assert False # we won't support other cases # depends on which one WG or DV # we need to add decode expr once or all # add happen before before instructions prevTs = tsRef # set the end and start pInst_ref.begin = instructions_in_the_chain[0] pInst_ref.end = instructions_in_the_chain[-1] return instructions_in_the_chain # Let's add pi function def setPiFunAW(self, PiVarList , TsThatWritesVar, AllWriteTsList ): # by default should be self.PiVarList for sname, piVar, tsRef, VAddr in PiVarList.values(): # check its name, so repetition piVarName = str(piVar) if piVarName in self.ConstrainedPiVarNames: continue # else: self.ConstrainedPiVarNames.add(piVarName) timestamp = tsRef.timestamp writerTraceSteps = TsThatWritesVar.get(sname,[]) fetch_ts = None if gpuModel.removeEntity(sname) == 'L1fr' and tsRef in self.L1fr_read_from: fetch_ts = self.L1fr_read_from[tsRef] # fetch_ts.inst.decodeFunc => rf constraint = mm.build_rf_constraint(sname, piVar, VAddr, TsThatWritesVar, read = tsRef, write = fetch_ts, AllWriteTsList = []) # 3 update check constraint = z3.Implies( fetch_ts.inst.decodeFunc , z3.Implies( tsRef.inst.decodeFunc , constraint )) self.ConstraintList.append( constraint ) OrClauses = [] for traceStep in list(writerTraceSteps) + AllWriteTsList: if traceStep is tsRef: continue if traceStep is fetch_ts: continue # this will disallow read from the fetch constraint = mm.build_rf_constraint(sname, piVar, VAddr, TsThatWritesVar, read = tsRef, write = traceStep, AllWriteTsList = AllWriteTsList) # 3 update check constraint = z3.Implies( tsRef.inst.decodeFunc , constraint ) # check decode OrClauses.append(constraint) # but we will add all the inst to be true??? if fetch_ts is not None: self.ConstraintList.append( z3.Implies( z3.Not(fetch_ts.inst.decodeFunc), z3.Or(OrClauses) ) ) else: self.ConstraintList.append( z3.Or(OrClauses) ) def POAhead2Store(self, parent_instruction_1, e1, parent_instruction_2, e2): def constrainIntervals(ts1,ts2): # ts1 is the init , and ts2 is the interval assert len(ts1.L1FifoTails) == len(ts2.L1FifoTailDeltas) assert len(ts1.L1FifoHeads) == len(ts2.L1FifoHeadDeltas) assert len(ts1.L1FifoTails) == len(ts2.L1FifoHeads) for sname in ts1.L1FifoHeads.keys(): # this is actually for all dw head_name = sname tail_name = sname.replace('head','tail') self.ConstraintList.append( ts1.L1FifoHeads[head_name] >= 0 ) self.ConstraintList.append( ts1.L1FifoTails[tail_name] >= 0 ) self.ConstraintList.append( ts1.L1FifoHeads[head_name] >= ts1.L1FifoTails[tail_name] ) self.ConstraintList.append( ts2.L1FifoHeadDeltas[head_name] >= 0 ) self.ConstraintList.append( ts2.L1FifoTailDeltas[tail_name] >= 0 ) self.ConstraintList.append( ts2.L1FifoHeadDeltas[head_name] == ts2.L1FifoTailDeltas[tail_name] ) # these are the environmental constraint #first get the micro instructions tsInit = InitStep_fifo( num_dev = self.num_dev, num_wg = self.num_wg, num_t = self.num_t, TsNameToObj = self.TsNameToObj , overwriteTimeStamp = 0 ) self.tsList.append( tsInit ) tsBList = self.addAChain( parentInstruction = parent_instruction_1, Eid = e1, childInstructions = rfMapInst[ parent_instruction_1 ], prevTimeStamp = tsInit.timestamp ) tsInterval = IntervalStep_fifo( num_dev = self.num_dev, num_wg = self.num_wg, num_t = self.num_t, TsNameToObj = self.TsNameToObj, TsThatWritesVar = self.TsThatWritesVar , ConstraintList = self.ConstraintList , PiVarList = self.PiVarList ) self.tsList.append( tsInterval ) tsU = self.addAChain( parentInstruction = parent_instruction_2, Eid = e2, childInstructions = rfMapInst[ parent_instruction_2 ], prevTimeStamp = tsInterval.timestamp ) self.ConstraintList.append( HB(tsInit,tsBList[0]) ) # do we really need this? self.ConstraintList.append( HB(tsBList[-1],tsInterval) ) # tsInterval --HB--> tsU is guaranteed by addAChain self.setPiFunAW( PiVarList = self.PiVarList, TsThatWritesVar = self.TsThatWritesVar, AllWriteTsList = [tsInit, tsInterval] ) ## TODO: add the invariants constrainIntervals(tsInit,tsInterval) def POAfter2Load(self, parent_instruction_1, e1, parent_instruction_2, e2): #first get the micro instructions # add init frame # add instr @ check frame # add instr that separate # add inst @ after frame tsInit = InitStep_any( num_dev = self.num_dev, num_wg = self.num_wg, num_t = self.num_t, TsNameToObj = self.TsNameToObj , overwriteTimeStamp = 0 ) self.tsList.append(tsInit) tsUnderCheck = self.addAChain( parentInstruction = parent_instruction_1, Eid = e1, childInstructions = rfMapInst[parent_instruction_1], prevTimeStamp = tsInit.timestamp ) tsInterval = IntervalStep_frKeep( num_dev = self.num_dev, num_wg = self.num_wg, num_t = self.num_t, TsNameToObj = self.TsNameToObj, ConstraintList = self.ConstraintList , PiVarList = self.PiVarList ) self.tsList.append(tsInterval) # here let's backup the whole thing """ push pi var to a stack """ #self.setPiFun(init = tsInit, PiVarList = self.PiVarList, TsThatWritesVar = self.TsThatWritesVar) #self.PiVarListOld = self.PiVarList #.update(self.PiVarList) #self.PiVarList = {} """ push TsThatWritesVar """ #self.TsThatWritesVarOld = self.TsThatWritesVar #.update(self.TsThatWritesVar) #self.TsThatWritesVar = {} tsAfterCheck = self.addAChain( parentInstruction = parent_instruction_2, Eid = e2, childInstructions = rfMapInst[parent_instruction_2], prevTimeStamp = tsInterval.timestamp ) # instructions are PO after tsInterval # this will update the PiVarList associated with IntervalStep_frKeep # #self.setPiFun(init = tsInterval, PiVarList = self.PiVarList, TsThatWritesVar = self.TsThatWritesVar) self.setPiFunAW( PiVarList = self.PiVarList, TsThatWritesVar = self.TsThatWritesVar, AllWriteTsList = [tsInit, tsInterval] ) # redo this, but the constrained ones should be okay, because no repetition is there self.setPiFunAW( PiVarList = self.PiVarList, TsThatWritesVar = self.TsThatWritesVar, AllWriteTsList = [tsInit, tsInterval] ) # do it twice because in the first case, there are pi var generated (on demand) #assert ('pi_intervalts5_L1fr@0,0addr0' in self.PiVarList) #assert ('pi_intervalts5_L1fr@0,0addr1' in self.PiVarList) self.ConstraintList.append( HB(tsInit,tsUnderCheck[0]) ) # do we really need this? self.ConstraintList.append( HB(tsUnderCheck[-1],tsInterval) ) # self.ConstraintList.append( HB(tsInterval,tsAfterCheck[0]) ) # we don't need this, it is already enforced ## TODO: add the invariants # you will need rf relation as a function def PO3SLL(self, parent_instruction_1, e1, parent_instruction_2, e2, parent_instruction_3, e3): # for store_DV_Rs : axiom 3 def constrainIntervals(ts1): #,ts2): # ts1 is the init , and ts2 is the interval #assert len(ts1.L1FifoTails) == len(ts2.L1FifoTailDeltas) #assert len(ts1.L1FifoHeads) == len(ts2.L1FifoHeadDeltas) #assert len(ts1.L1FifoTails) == len(ts2.L1FifoHeads) for sname in ts1.L1FifoHeads.keys(): # this is actually for all dw head_name = sname tail_name = sname.replace('head','tail') self.ConstraintList.append( ts1.L1FifoHeads[head_name] >= 0 ) self.ConstraintList.append( ts1.L1FifoTails[tail_name] >= 0 ) self.ConstraintList.append( ts1.L1FifoHeads[head_name] >= ts1.L1FifoTails[tail_name] ) #self.ConstraintList.append( ts2.L1FifoHeadDeltas[head_name] >= 0 ) #self.ConstraintList.append( ts2.L1FifoTailDeltas[tail_name] >= 0 ) #self.ConstraintList.append( ts2.L1FifoHeadDeltas[head_name] == ts2.L1FifoTailDeltas[tail_name] ) #first get the micro instructions tsInit = InitStep_fifo( num_dev = self.num_dev, num_wg = self.num_wg, num_t = self.num_t, TsNameToObj = self.TsNameToObj , overwriteTimeStamp = 0 ) #InitStep_any( num_dev = self.num_dev, num_wg = self.num_wg, num_t = self.num_t, TsNameToObj = self.TsNameToObj , overwriteTimeStamp = 0 ) self.tsList.append( tsInit ) tsBListS1 = self.addAChain( parentInstruction = parent_instruction_1, Eid = e1, childInstructions = rfMapInst[ parent_instruction_1 ], prevTimeStamp = tsInit.timestamp ) tsIntervalSL = IntervalStep_frKeep( num_dev = self.num_dev, num_wg = self.num_wg, num_t = self.num_t, TsNameToObj = self.TsNameToObj, ConstraintList = self.ConstraintList , PiVarList = self.PiVarList ) self.tsList.append( tsIntervalSL ) tsBListS2 = self.addAChain( parentInstruction = parent_instruction_2, Eid = e2, childInstructions = rfMapInst[ parent_instruction_2 ], prevTimeStamp = tsIntervalSL.timestamp ) tsIntervalLL = IntervalStep_frKeep( num_dev = self.num_dev, num_wg = self.num_wg, num_t = self.num_t, TsNameToObj = self.TsNameToObj, ConstraintList = self.ConstraintList , PiVarList = self.PiVarList ) self.tsList.append( tsIntervalLL ) tsUListR = self.addAChain( parentInstruction = parent_instruction_3, Eid = e3, childInstructions = rfMapInst[ parent_instruction_3 ], prevTimeStamp = tsIntervalLL.timestamp ) #self.ConstraintList.append( HB(tsInit,tsBListS1[0]) ) self.ConstraintList.append( HB(tsBListS1[-1], tsIntervalSL) ) self.ConstraintList.append( HB(tsBListS2[-1], tsIntervalLL) ) # tsIntervalSL --HB--> tsU is guaranteed by addAChain self.setPiFunAW( PiVarList = self.PiVarList, TsThatWritesVar = self.TsThatWritesVar, AllWriteTsList = [tsInit, tsIntervalSL, tsIntervalLL] ) self.setPiFunAW( PiVarList = self.PiVarList, TsThatWritesVar = self.TsThatWritesVar, AllWriteTsList = [tsInit, tsIntervalSL, tsIntervalLL] ) constrainIntervals(tsInit) def PO3SSL(self, parent_instruction_1, e1, parent_instruction_2, e2, parent_instruction_3, e3): # for load_DV_Rs : axiom 3 def constrainIntervals(ts1,ts2, ts3): # ts1 is the init , and ts2 is the interval assert len(ts1.L1FifoTails) == len(ts2.L1FifoTailDeltas) assert len(ts1.L1FifoHeads) == len(ts2.L1FifoHeadDeltas) assert len(ts1.L1FifoTails) == len(ts2.L1FifoHeads) assert len(ts1.L1FifoTails) == len(ts3.L1FifoTailDeltas) assert len(ts1.L1FifoHeads) == len(ts3.L1FifoHeadDeltas) assert len(ts1.L1FifoTails) == len(ts3.L1FifoHeads) for sname in ts1.L1FifoHeads.keys(): # this is actually for all dw head_name = sname tail_name = sname.replace('head','tail') self.ConstraintList.append( ts1.L1FifoHeads[head_name] >= 0 ) self.ConstraintList.append( ts1.L1FifoTails[tail_name] >= 0 ) self.ConstraintList.append( ts1.L1FifoHeads[head_name] >= ts1.L1FifoTails[tail_name] ) self.ConstraintList.append( ts2.L1FifoHeadDeltas[head_name] >= 0 ) self.ConstraintList.append( ts2.L1FifoTailDeltas[tail_name] >= 0 ) self.ConstraintList.append( ts2.L1FifoHeads[head_name] >= ts2.L1FifoTails[tail_name] ) self.ConstraintList.append( ts3.L1FifoHeadDeltas[head_name] >= 0 ) self.ConstraintList.append( ts3.L1FifoTailDeltas[tail_name] >= 0 ) self.ConstraintList.append( ts3.L1FifoHeads[head_name] >= ts3.L1FifoTails[tail_name] ) self.ConstraintList.append( ts2.L1FifoHeadDeltas[head_name] + ts3.L1FifoHeadDeltas[head_name] >= ts2.L1FifoTailDeltas[tail_name] + ts3.L1FifoTailDeltas[tail_name] ) # these are the environmental constraint #first get the micro instructions tsInit = InitStep_fifo( num_dev = self.num_dev, num_wg = self.num_wg, num_t = self.num_t, TsNameToObj = self.TsNameToObj , overwriteTimeStamp = 0 ) self.tsList.append( tsInit ) tsBListS1 = self.addAChain( parentInstruction = parent_instruction_1, Eid = e1, childInstructions = rfMapInst[ parent_instruction_1 ], prevTimeStamp = tsInit.timestamp ) tsIntervalSS = IntervalStep_fifo( num_dev = self.num_dev, num_wg = self.num_wg, num_t = self.num_t, TsNameToObj = self.TsNameToObj, TsThatWritesVar = self.TsThatWritesVar , ConstraintList = self.ConstraintList , PiVarList = self.PiVarList ) self.tsList.append( tsIntervalSS ) tsBListS2 = self.addAChain( parentInstruction = parent_instruction_2, Eid = e2, childInstructions = rfMapInst[ parent_instruction_2 ], prevTimeStamp = tsIntervalSS.timestamp ) tsIntervalSL = IntervalStep_fifo( num_dev = self.num_dev, num_wg = self.num_wg, num_t = self.num_t, TsNameToObj = self.TsNameToObj, TsThatWritesVar = self.TsThatWritesVar , ConstraintList = self.ConstraintList , PiVarList = self.PiVarList ) self.tsList.append( tsIntervalSL ) tsUListR = self.addAChain( parentInstruction = parent_instruction_3, Eid = e3, childInstructions = rfMapInst[ parent_instruction_3 ], prevTimeStamp = tsIntervalSL.timestamp ) #self.ConstraintList.append( HB(tsInit,tsBListS1[0]) ) self.ConstraintList.append( HB(tsBListS1[-1], tsIntervalSS) ) self.ConstraintList.append( HB(tsBListS2[-1], tsIntervalSL) ) # tsIntervalSS --HB--> tsU is guaranteed by addAChain self.setPiFunAW( PiVarList = self.PiVarList, TsThatWritesVar = self.TsThatWritesVar, AllWriteTsList = [tsInit, tsIntervalSS, tsIntervalSL] ) ## TODO: add the invariants constrainIntervals(tsInit,tsIntervalSS,tsIntervalSL) def add_check_axiom(self): #axiom.store_dv_r_3(self) #axiom.load_dv_r_3(self) axiom.PO2Axioms(self) def pushInstConstraintAndCheck(self): self.solver = z3.Solver() s = self.solver s.set(unsat_core=True if DEBUG else False) idx = 0 for c in self.ConstraintList: if DEBUG: print >>self.logcat, idx,':', c #raw_input() if c is False: print '<W>: False cannot be satisfied' elif c is True: pass else: s.assert_and_track(c,'n'+str(idx)) idx += 1 else: s.add(c) result = s.check() print 'w.o. run Property:', result self.modelCheckResult = result if result == z3.sat: self.model = s.model() else: # unsat if DEBUG: print >>self.logcat, s.unsat_core() print '<W>: Not all the reads can be executed! Trace debug info dumped.' return result def solve(self): if self.modelCheckResult == z3.unsat: print '<W>: inconsistent model. Won\'t continue to check the properties.' return s = self.solver if len(self.runProp) == 0: print '<W>: no property specified.' return else: runProp = z3.Not( LAnd(self.runProp) ) if DEBUG: print >> self.logcat, 'rp : ', runProp s.assert_and_track(runProp,'rp') else: s.add(runProp) # extract module result = s.check() print result if result == z3.unsat: # this may use the old one if DEBUG: print >>self.logcat, s.unsat_core() elif result == z3.sat: self.model = s.model() print 'negation is witnessed' #self.printModel() else: print 'status Unknown' return result def printModel(self): print >> self.logcat, '====================== MODEL =====================' for ts in self.tsList: print >>self.logcat, ts.name, ' entity:', ts.entity.toName() if 'entity' in ts.__dict__ else 'GLOBAL' t,d,val,readCol = ts.getConcreteModel(self.model) instName = ts.inst.name if 'inst' in ts.__dict__ else 'INIT' print >>self.logcat, '@%s, %s:%s'%(str(t), instName, d) for n,v in readCol.items(): if isinstance(v, tuple): value = str(v[0]) + '\taddr: ' + str('ANY' if v[1].anyAddr else ( 'z3:' + str(v[1].eval(self.model) ) + ', id:' + v[1].vaid ) ) print >> self.logcat, '\t (Read %s = %s)' % (n, value ) else: print >>self.logcat, '\t (Read %s = %s)' % (n, str(v) ) for n,v in val.items(): if isinstance(v, tuple): value = str(v[0]) + '\taddr: ' + str('ANY' if v[1].anyAddr else ( 'z3:' + str(v[1].eval(self.model) ) + ', id:' + v[1].vaid ) ) print >>self.logcat, '\t %s:%s' % (n,value) else: print >>self.logcat, '\t %s:%s' % (n,str(v)) self.logcat.flush() def check2store(num_dev,num_wg,num_t): #for devIdx1 in range(num_dev): # for wgId1 in range(num_wg): # for tIdx1 in range(num_t): devIdx1 = 0; wgId1 = 0; tIdx1 = 0 for devIdx2 in range(num_dev): for wgId2 in range(num_wg): for tIdx2 in range(num_t): eqc = eqchecker(num_dev,num_wg,num_t) eqc.logcat = open('eqcheck.log', 'wt') eid1 = gpuModel.entity(devIdx1,wgId1,tIdx1) eid2 = gpuModel.entity(devIdx2,wgId2,tIdx2) eqc.POAhead2Store(parent_instruction_1 = openclrsp.CL_store_DV_R, e1 = eid1, parent_instruction_2 = openclrsp.CL_store_na_or_WG, e2 = eid2 ) eqc.add_check_axiom() if eqc.pushInstConstraintAndCheck() != z3.sat: print 'unrealistic scenario!' assert False if eqc.solve() == z3.sat: print 'Ordering is not guaranteed.' eqc.printModel() assert False eqc.logcat.close() def checkSSL(num_dev,num_wg,num_t): devIdx1 = 0; wgId1 = 0; tIdx1 = 0 #for devIdx1 in range(num_dev): # for wgId1 in range(num_wg): # for tIdx1 in range(num_t): for devIdx2 in range(num_dev): for wgId2 in range(num_wg): for tIdx2 in range(num_t): for devIdx3 in range(num_dev): for wgId3 in range(num_wg): for tIdx3 in range(num_t): eqc = eqchecker(num_dev,num_wg,num_t) eqc.logcat = open('eqcheck.log', 'wt') eid1 = gpuModel.entity(devIdx1,wgId1,tIdx1) eid2 = gpuModel.entity(devIdx2,wgId2,tIdx2) eid3 = gpuModel.entity(devIdx3,wgId3,tIdx3) eqc.PO3SSL( parent_instruction_1 = openclrsp.CL_store_DV_N, e1 = eid1, parent_instruction_2 = openclrsp.CL_store_DV_N, e2 = eid2, parent_instruction_3 = openclrsp.CL_load_DV_R, e3 = eid3 ) eqc.add_check_axiom() if eqc.pushInstConstraintAndCheck() != z3.sat: print 'unrealistic scenario!' assert False #eqc.printModel() #eqc.logcat.close() #exit(1) if eqc.solve() == z3.sat: print 'Ordering is not guaranteed.' eqc.printModel() assert False eqc.logcat.close() #eqc.printModel() #eqc.logcat.close() #exit(1) def checkSLL(num_dev,num_wg,num_t): devIdx1 = 0; wgId1 = 0; tIdx1 = 0 #devIdx2 = 0; wgId2 = 1; tIdx2 = 0 #devIdx3 = 0; wgId3 = 0; tIdx3 = 0 #for devIdx1 in range(num_dev): # for wgId1 in range(num_wg): # for tIdx1 in range(num_t): for devIdx2 in range(num_dev): for wgId2 in range(num_wg): for tIdx2 in range(num_t): for devIdx3 in range(num_dev): for wgId3 in range(num_wg): for tIdx3 in range(num_t): eqc = eqchecker(num_dev,num_wg,num_t) eqc.logcat = open('eqcheck.log', 'wt') eid1 = gpuModel.entity(devIdx1,wgId1,tIdx1) eid2 = gpuModel.entity(devIdx2,wgId2,tIdx2) eid3 = gpuModel.entity(devIdx3,wgId3,tIdx3) eqc.PO3SLL( parent_instruction_1 = openclrsp.CL_store_DV_R, e1 = eid1, parent_instruction_2 = openclrsp.CL_load_na_or_WG, e2 = eid2, parent_instruction_3 = openclrsp.CL_load_na_or_WG, e3 = eid3 ) eqc.add_check_axiom() if eqc.pushInstConstraintAndCheck() != z3.sat: print 'unrealistic scenario!' assert False if eqc.solve() == z3.sat: print 'Ordering is not guaranteed.' eqc.printModel() assert False eqc.logcat.close() def check2load(num_dev,num_wg,num_t): devIdx1 = 0; wgId1 = 0; tIdx1 = 0 #for devIdx1 in range(num_dev): # for wgId1 in range(num_wg): # for tIdx1 in range(num_t): for devIdx2 in range(num_dev): for wgId2 in range(num_wg): for tIdx2 in range(num_t): eqc = eqchecker(num_dev,num_wg,num_t) eqc.logcat = open('eqcheck.log', 'wt') eid1 = gpuModel.entity(devIdx1,wgId1,tIdx1) eid2 = gpuModel.entity(devIdx2,wgId2,tIdx2) eqc.POAfter2Load(parent_instruction_1 = openclrsp.CL_load_DV_N, e1 = eid1, parent_instruction_2 = openclrsp.CL_load_DV_N, e2 = eid2 ) eqc.add_check_axiom() if eqc.pushInstConstraintAndCheck() != z3.sat: print 'unrealistic scenario!' assert False #eqc.printModel() #eqc.logcat.close() #exit(1) if eqc.solve() == z3.sat: print 'Ordering is not guaranteed.' eqc.printModel() assert False eqc.logcat.close() if __name__ == '__main__': #check2store(2,2,2) # should also check for store_DV_R to previous stores AXIOM 1 2 check2load(2,2,2) #checkSSL(2,2,2) #checkSLL(2,2,2)
from traceStep import * import axiom # --------------------------- # Configurations # --------------------------- FORCE_ALL_INST_DECODE_TRUE = True DEBUG = False # --------------------------- # Prerequisites # --------------------------- def LAnd(l): if len(l) == 0: return z3.BoolVal(True) elif len(l) == 1: return l[0] else: return z3.And(l) def LOr(l): if len(l) == 0: return z3.BoolVal(True) elif len(l) == 1: return l[0] else: return z3.Or(l) # --------------------------- # clInstruction = openclrsp.CL_load_DV_N # gpuInstruction = [ gpuModel.ev_FETCH_L1 , gpuModel.inst_LD , gpuModel.inst_INV_L1_WG ] wvopListTp = namedtuple('wvopListTp','WG DV addr value') rvopListTp = namedtuple('rvopListTp','WG DV addr value') prevEVsequence = { gpuModel.inst_LD: [gpuModel.ev_FETCH_L1] , gpuModel.inst_INC_L1 : [gpuModel.ev_FETCH_L1] } postEVsequence = { gpuModel.inst_ST: [ gpuModel.ev_FLUSH_L1, gpuModel.ev_DEQLOC_L1 ], # fetch will also need this gpuModel.inst_INC_L1 : [ gpuModel.ev_FLUSH_L1 , gpuModel.ev_DEQLOC_L1 ] } blockSequence = { gpuModel.inst_FLU_L1_DV : gpuModel.ev_DEQMARKER_L1, # will wait for many of it gpuModel.inst_FLU_L1_WG : gpuModel.ev_DEQMARKER_L1 } # pre is already modeled in the sequence rfMapInst = { openclrsp.CL_load_na_or_WG: [ gpuModel.inst_LD ], openclrsp.CL_load_DV_N: [ gpuModel.inst_LD , gpuModel.inst_INV_L1_WG ], #Corret : [ gpuModel.inst_LD , gpuModel.inst_INV_L1_WG ], # wrong implementation: [ gpuModel.inst_INV_L1_WG , gpuModel.inst_LD ], openclrsp.CL_load_DV_R: [ gpuModel.inst_LD , gpuModel.inst_FLU_L1_DV , gpuModel.inst_INV_L1_WG ], #[ gpuModel.inst_LK_L2, gpuModel.inst_FLU_L1_DV, gpuModel.inst_INV_L1_WG, gpuModel.inst_LD, gpuModel.inst_UL_L2 ], # new: [ gpuModel.inst_LD , gpuModel.inst_FLU_L1_DV , gpuModel.inst_INV_L1_WG ] original : [ gpuModel.inst_LK_L2, gpuModel.inst_FLU_L1_DV, gpuModel.inst_INV_L1_WG, gpuModel.inst_LD, gpuModel.inst_UL_L2 ] openclrsp.CL_store_na_or_WG:[ gpuModel.inst_ST ], openclrsp.CL_store_DV_N: [ gpuModel.inst_FLU_L1_WG, gpuModel.inst_ST ], openclrsp.CL_store_DV_R: [ gpuModel.inst_LK_rmw_DV, gpuModel.inst_FLU_L1_DV, gpuModel.inst_INV_L1_DV, gpuModel.inst_ST, gpuModel.inst_FLU_L1_WG, gpuModel.inst_INV_L1_DV, gpuModel.inst_UL_rmw_DV ], # Wrong : [ gpuModel.inst_LK_L2, gpuModel.inst_FLU_L1_WG, gpuModel.inst_ST, gpuModel.inst_INV_L1_DV, gpuModel.inst_UL_L2 ], # this was the wrong thing openclrsp.CL_fetch_inc_WG: [ gpuModel.inst_INC_L1 ] } def HB(a,b): return a.timestamp < b.timestamp def HBd(a,b): return z3.Implies( z3.And( a.inst.decodeFunc, b.inst.decodeFunc), a.timestamp < b.timestamp ) # ============================================= # EQ CHECKER # ============================================= class eqchecker(object): def __init__(self, num_dev, num_wg, num_t): self.PiVarList = {} # pi_var_name (ts + statename) -> [ (sname, pivar, ts, addr ) ] self.PiVarListOld = {} self.TsThatWritesVar = {} self.TsThatWritesVarOld = {} self.TsNameToObj = {} self.ConstraintList = [] self.runProp = [] self.num_of_parent_inst_in_scene = 0 self.tsList = [] # Note this is not a list of PO self.PrevDecode = None # Note that the prev decode may be in self.num_dev, self.num_wg, self.num_t = num_dev, num_wg, num_t self.ConstrainedPiVarNames = set([]) # set of String : name of the PiVar self.L1fr_read_from = {} # ld --> fetch (if fetch.decode then must read from fetch else must others) # ====================================== # below is the content of the collector # ====================================== self.load_na_or_WG_list = [] self.load_DV_N_list = [] self.load_DV_R_list = [] self.store_na_or_WG_list = [] self.store_DV_N_list = [] self.store_DV_R_list = [] self.LOAD_list = [] self.STORE_list = [] self.rmw_list = [] self.name_to_list_mapping = {'load_na_or_WG':[self.load_na_or_WG_list, self.LOAD_list], 'load_DV_N':[self.load_DV_N_list ,self.LOAD_list], 'load_DV_R':[self.load_DV_R_list ,self.LOAD_list], 'store_na_or_WG':[self.store_na_or_WG_list ,self.STORE_list], 'store_DV_N':[self.store_DV_N_list ,self.STORE_list], 'store_DV_R':[self.store_DV_R_list ,self.STORE_list], 'fetch_inc_WG':[self.rmw_list, self.LOAD_list,self.STORE_list], } def addToList(self,inst): for lref in self.name_to_list_mapping[inst.name]: lref.append(inst) def addParentInst(self, addr, reg, e1, inst_func): def dummyRead(sname,addr = 0, entity = 0): return 0 #state = lambda stateName, addr = None , overWriteVA = None: ts1.stateReadFunc(stateName,addr,overWriteVA) paramDict = {'x': addr, 'r' :reg, 'Eid': e1 , 'state':dummyRead } inst = inst_func( **paramDict ) self.addToList(inst) return inst def addInstToScene(self, addr, reg, e1, inst_func, decodeWaitList, slot = None): # need to plug-in additional decode in the beginning, if it is not None, will add # unless specify slot, will not provide # addr = z3.Int('addr'+str(self.num_of_inst_in_scene) ) # the order here matters # reg = z3.Int('reg' +str(self.num_of_inst_in_scene) ) # the order here matters # and you need to check if you need an entity or not # e1 = self._genEntity() # entity for the instruction ts1 = TraceStep(entity = e1, TsThatWritesVar = self.TsThatWritesVar , TsNameToObj = self.TsNameToObj, ConstraintList = self.ConstraintList, PiVarList = self.PiVarList ) self.tsList.append(ts1) # tsList is gathering all these # concretize the instruction state = lambda stateName, addr = None , entity = None: ts1.stateReadFunc(stateName,addr,entity) paramDict = {'x': addr, 'r' :reg, 'Eid': e1 , 'state':state, 'num_dev':self.num_dev, 'num_wg': self.num_wg , 'num_t': self.num_t } if slot is not None: paramDict['slot'] = slot inst = inst_func( **paramDict ) # get the instruction # here is the logic for the pause after flush if decodeWaitList is not None: # then it should be a list if len( decodeWaitList ) == 1: extraDecodeExpr = ts1.stateReadFunc( 'L1fifotail' ) == decodeWaitList[0] # Previous is FLU_WG else: assert len( decodeWaitList ) == self.num_wg extraDecodeExpr = z3.And( [ \ ts1.stateReadFunc('L1fifotail' , entity = gpuModel.entity(e1.d, wgId ) ) == decodeWaitList[wgId] \ for wgId in range(self.num_wg) ] ) inst.decodeFunc = z3.And( inst.decodeFunc, extraDecodeExpr ) # change the decode function when necessary ts1.assignInst(inst) # r return inst,ts1 # PO relations are added by axioms # w/r vop relations are added by axioms # prev decode may be in effect for another instruction, but not in our case # but still it would be best to add parent instruction according their program order ?? def addAChain(self, Eid, parentInstruction, childInstructions, prevTimeStamp): # for one parent-instruction -> should return one child instruction # entity # gen addrs addr = z3.Int('addr'+str(self.num_of_parent_inst_in_scene) ) # the order here matters reg = z3.Int('reg' +str(self.num_of_parent_inst_in_scene) ) # the order here matters # and you need to check if you need an entity or not # e1 = self._genEntity() # entity for the instruction self.num_of_parent_inst_in_scene += 1 pInst_ref = self.addParentInst(addr = addr, reg = reg, e1 = Eid, inst_func = parentInstruction) #addr, reg, e1, inst_func prevTs = None blockSeqSlotList = [] instructions_in_the_chain = [] for uinst in childInstructions: _ , tsRef = self.addInstToScene(addr = addr, reg = reg, e1 = Eid, inst_func = uinst, decodeWaitList = self.PrevDecode ) instructions_in_the_chain.append(tsRef) self.ConstraintList.append( tsRef.timestamp > prevTimeStamp ) # every child instruction step is later than init or the previous barrier (not including evs) if prevTs is not None: self.ConstraintList.append( HB(prevTs, tsRef) ) # tsRef.timestamp > prevTs.timestamp ) # constraint 2: child instruction po else: # prevTs is None assert self.PrevDecode is None # check that flush is not the last child instruction !!! self.PrevDecode = None # reset it # constraint #3: child instructions must be executed self.ConstraintList.append( tsRef.inst.decodeFunc ) # Constriant DECODE # here, start to # check the need to add additional environmental transition if uinst in prevEVsequence: # FETCH -> LD seq = prevEVsequence[uinst] assert len(seq) == 1 # we only handle the case with one fetch (RVOP) fetch_ev = seq[0] inst_sub, tsRef_sub = self.addInstToScene(addr = addr , reg = reg, e1 = Eid, inst_func = fetch_ev, decodeWaitList = None, slot = None) # we don't require its decode to be true valueToBeWritten = tsRef.inst.updateDict[gpuModel.setSname('r',Eid)][0] # get from updateDict pInst_ref.rvop = rvopListTp( WG = tsRef, DV = tsRef_sub, addr = addr, value = valueToBeWritten ) pInst_ref.timestamp = tsRef.timestamp self.ConstraintList.append( HBd(tsRef_sub, tsRef) ) # only guarantee if both decodes are true self.ConstraintList.append( tsRef_sub.timestamp > 0 ) self.L1fr_read_from[tsRef] = tsRef_sub if uinst in postEVsequence: # ST -> will seq = postEVsequence[uinst] parent_or_prev_ts = tsRef # the one that will happenBefore it tmpTsList = [] # get the slot storeFIFOSlot = tsRef.stateReadFunc('L1fifotail') for post_inst in seq: inst_sub, tsRef_sub = self.addInstToScene(addr = addr , reg = reg, e1 = Eid, inst_func = post_inst, decodeWaitList = None, slot = storeFIFOSlot) self.ConstraintList.append( HB(parent_or_prev_ts, tsRef_sub) ) # parent_or_prev_ts.timestamp < tsRef_sub.timestamp ) self.ConstraintList.append( tsRef_sub.timestamp > 0 ) # parent_or_prev_ts = tsRef_sub tmpTsList.append(tsRef_sub) valueToBeRead = tsRef.stateReadFunc('r', addr = reg) # get from read its local register value pInst_ref.wvop = wvopListTp( WG = tsRef, DV = tmpTsList[0], addr = addr, value = valueToBeRead ) pInst_ref.timestamp = tsRef.timestamp if uinst in blockSequence: # FLUSH: either the device or workgroup blockSeqSlotList = [] flush_ev = blockSequence[uinst] # it will only be one instruction # but still you won't need to change decode ? if uinst is gpuModel.inst_FLU_L1_DV: # in this case we will need to create #WG flush MARKER and for wgId in range(self.num_wg): # read the slot from tsRef DEQ_MARKER_ENTITY = gpuModel.entity(Eid.d, wgId ) slot = tsRef.stateReadFunc( 'L1fifohead' , entity = DEQ_MARKER_ENTITY) # dep marker will need this blockSeqSlotList.append(slot + 1) # create a ts after it inst_sub, tsRef_sub = self.addInstToScene(addr = addr , reg = reg, e1 = DEQ_MARKER_ENTITY, inst_func = flush_ev, decodeWaitList = None, slot = slot) self.ConstraintList.append( HB(tsRef, tsRef_sub) ) # tsRef_sub.timestamp > tsRef.timestamp ) self.ConstraintList.append( tsRef_sub.timestamp > 0 ) # concat decode for all Wg # may be we can directly instantiate the function (to z3expr) here without calling it self.PrevDecode = blockSeqSlotList elif uinst is gpuModel.inst_FLU_L1_WG: slot = tsRef.stateReadFunc('L1fifohead') # dep marker will need this flush_ev = blockSequence[uinst] # it will only be one instruction self.PrevDecode = [ slot +1 ] inst_sub, tsRef_sub = self.addInstToScene(addr = addr , reg = reg, e1 = Eid, inst_func = flush_ev, decodeWaitList = None, slot = slot) self.ConstraintList.append( HB(tsRef, tsRef_sub) ) # tsRef_sub.timestamp > tsRef.timestamp ) else: assert False # we won't support other cases # depends on which one WG or DV # we need to add decode expr once or all # add happen before before instructions prevTs = tsRef # set the end and start pInst_ref.begin = instructions_in_the_chain[0] pInst_ref.end = instructions_in_the_chain[-1] return instructions_in_the_chain # Let's add pi function def setPiFunAW(self, PiVarList , TsThatWritesVar, AllWriteTsList ): # by default should be self.PiVarList for sname, piVar, tsRef, VAddr in PiVarList.values(): # check its name, so repetition piVarName = str(piVar) if piVarName in self.ConstrainedPiVarNames: continue # else: self.ConstrainedPiVarNames.add(piVarName) timestamp = tsRef.timestamp writerTraceSteps = TsThatWritesVar.get(sname,[]) fetch_ts = None if gpuModel.removeEntity(sname) == 'L1fr' and tsRef in self.L1fr_read_from: fetch_ts = self.L1fr_read_from[tsRef] # fetch_ts.inst.decodeFunc => rf constraint = mm.build_rf_constraint(sname, piVar, VAddr, TsThatWritesVar, read = tsRef, write = fetch_ts, AllWriteTsList = []) # 3 update check constraint = z3.Implies( fetch_ts.inst.decodeFunc , z3.Implies( tsRef.inst.decodeFunc , constraint )) self.ConstraintList.append( constraint ) OrClauses = [] for traceStep in list(writerTraceSteps) + AllWriteTsList: if traceStep is tsRef: continue if traceStep is fetch_ts: continue # this will disallow read from the fetch constraint = mm.build_rf_constraint(sname, piVar, VAddr, TsThatWritesVar, read = tsRef, write = traceStep, AllWriteTsList = AllWriteTsList) # 3 update check constraint = z3.Implies( tsRef.inst.decodeFunc , constraint ) # check decode OrClauses.append(constraint) # but we will add all the inst to be true??? if fetch_ts is not None: self.ConstraintList.append( z3.Implies( z3.Not(fetch_ts.inst.decodeFunc), z3.Or(OrClauses) ) ) else: self.ConstraintList.append( z3.Or(OrClauses) ) def POAhead2Store(self, parent_instruction_1, e1, parent_instruction_2, e2): def constrainIntervals(ts1,ts2): # ts1 is the init , and ts2 is the interval assert len(ts1.L1FifoTails) == len(ts2.L1FifoTailDeltas) assert len(ts1.L1FifoHeads) == len(ts2.L1FifoHeadDeltas) assert len(ts1.L1FifoTails) == len(ts2.L1FifoHeads) for sname in ts1.L1FifoHeads.keys(): # this is actually for all dw head_name = sname tail_name = sname.replace('head','tail') self.ConstraintList.append( ts1.L1FifoHeads[head_name] >= 0 ) self.ConstraintList.append( ts1.L1FifoTails[tail_name] >= 0 ) self.ConstraintList.append( ts1.L1FifoHeads[head_name] >= ts1.L1FifoTails[tail_name] ) self.ConstraintList.append( ts2.L1FifoHeadDeltas[head_name] >= 0 ) self.ConstraintList.append( ts2.L1FifoTailDeltas[tail_name] >= 0 ) self.ConstraintList.append( ts2.L1FifoHeadDeltas[head_name] == ts2.L1FifoTailDeltas[tail_name] ) # these are the environmental constraint #first get the micro instructions tsInit = InitStep_fifo( num_dev = self.num_dev, num_wg = self.num_wg, num_t = self.num_t, TsNameToObj = self.TsNameToObj , overwriteTimeStamp = 0 ) self.tsList.append( tsInit ) tsBList = self.addAChain( parentInstruction = parent_instruction_1, Eid = e1, childInstructions = rfMapInst[ parent_instruction_1 ], prevTimeStamp = tsInit.timestamp ) tsInterval = IntervalStep_fifo( num_dev = self.num_dev, num_wg = self.num_wg, num_t = self.num_t, TsNameToObj = self.TsNameToObj, TsThatWritesVar = self.TsThatWritesVar , ConstraintList = self.ConstraintList , PiVarList = self.PiVarList ) self.tsList.append( tsInterval ) tsU = self.addAChain( parentInstruction = parent_instruction_2, Eid = e2, childInstructions = rfMapInst[ parent_instruction_2 ], prevTimeStamp = tsInterval.timestamp ) self.ConstraintList.append( HB(tsInit,tsBList[0]) ) # do we really need this? self.ConstraintList.append( HB(tsBList[-1],tsInterval) ) # tsInterval --HB--> tsU is guaranteed by addAChain self.setPiFunAW( PiVarList = self.PiVarList, TsThatWritesVar = self.TsThatWritesVar, AllWriteTsList = [tsInit, tsInterval] ) ## TODO: add the invariants constrainIntervals(tsInit,tsInterval) def POAfter2Load(self, parent_instruction_1, e1, parent_instruction_2, e2): #first get the micro instructions # add init frame # add instr @ check frame # add instr that separate # add inst @ after frame tsInit = InitStep_any( num_dev = self.num_dev, num_wg = self.num_wg, num_t = self.num_t, TsNameToObj = self.TsNameToObj , overwriteTimeStamp = 0 ) self.tsList.append(tsInit) tsUnderCheck = self.addAChain( parentInstruction = parent_instruction_1, Eid = e1, childInstructions = rfMapInst[parent_instruction_1], prevTimeStamp = tsInit.timestamp ) tsInterval = IntervalStep_frKeep( num_dev = self.num_dev, num_wg = self.num_wg, num_t = self.num_t, TsNameToObj = self.TsNameToObj, ConstraintList = self.ConstraintList , PiVarList = self.PiVarList ) self.tsList.append(tsInterval) # here let's backup the whole thing """ push pi var to a stack """ #self.setPiFun(init = tsInit, PiVarList = self.PiVarList, TsThatWritesVar = self.TsThatWritesVar) #self.PiVarListOld = self.PiVarList #.update(self.PiVarList) #self.PiVarList = {} """ push TsThatWritesVar """ #self.TsThatWritesVarOld = self.TsThatWritesVar #.update(self.TsThatWritesVar) #self.TsThatWritesVar = {} tsAfterCheck = self.addAChain( parentInstruction = parent_instruction_2, Eid = e2, childInstructions = rfMapInst[parent_instruction_2], prevTimeStamp = tsInterval.timestamp ) # instructions are PO after tsInterval # this will update the PiVarList associated with IntervalStep_frKeep # #self.setPiFun(init = tsInterval, PiVarList = self.PiVarList, TsThatWritesVar = self.TsThatWritesVar) self.setPiFunAW( PiVarList = self.PiVarList, TsThatWritesVar = self.TsThatWritesVar, AllWriteTsList = [tsInit, tsInterval] ) # redo this, but the constrained ones should be okay, because no repetition is there self.setPiFunAW( PiVarList = self.PiVarList, TsThatWritesVar = self.TsThatWritesVar, AllWriteTsList = [tsInit, tsInterval] ) # do it twice because in the first case, there are pi var generated (on demand) #assert ('pi_intervalts5_L1fr@0,0addr0' in self.PiVarList) #assert ('pi_intervalts5_L1fr@0,0addr1' in self.PiVarList) self.ConstraintList.append( HB(tsInit,tsUnderCheck[0]) ) # do we really need this? self.ConstraintList.append( HB(tsUnderCheck[-1],tsInterval) ) # self.ConstraintList.append( HB(tsInterval,tsAfterCheck[0]) ) # we don't need this, it is already enforced ## TODO: add the invariants # you will need rf relation as a function def PO3SLL(self, parent_instruction_1, e1, parent_instruction_2, e2, parent_instruction_3, e3): # for store_DV_Rs : axiom 3 def constrainIntervals(ts1): #,ts2): # ts1 is the init , and ts2 is the interval #assert len(ts1.L1FifoTails) == len(ts2.L1FifoTailDeltas) #assert len(ts1.L1FifoHeads) == len(ts2.L1FifoHeadDeltas) #assert len(ts1.L1FifoTails) == len(ts2.L1FifoHeads) for sname in ts1.L1FifoHeads.keys(): # this is actually for all dw head_name = sname tail_name = sname.replace('head','tail') self.ConstraintList.append( ts1.L1FifoHeads[head_name] >= 0 ) self.ConstraintList.append( ts1.L1FifoTails[tail_name] >= 0 ) self.ConstraintList.append( ts1.L1FifoHeads[head_name] >= ts1.L1FifoTails[tail_name] ) #self.ConstraintList.append( ts2.L1FifoHeadDeltas[head_name] >= 0 ) #self.ConstraintList.append( ts2.L1FifoTailDeltas[tail_name] >= 0 ) #self.ConstraintList.append( ts2.L1FifoHeadDeltas[head_name] == ts2.L1FifoTailDeltas[tail_name] ) #first get the micro instructions tsInit = InitStep_fifo( num_dev = self.num_dev, num_wg = self.num_wg, num_t = self.num_t, TsNameToObj = self.TsNameToObj , overwriteTimeStamp = 0 ) #InitStep_any( num_dev = self.num_dev, num_wg = self.num_wg, num_t = self.num_t, TsNameToObj = self.TsNameToObj , overwriteTimeStamp = 0 ) self.tsList.append( tsInit ) tsBListS1 = self.addAChain( parentInstruction = parent_instruction_1, Eid = e1, childInstructions = rfMapInst[ parent_instruction_1 ], prevTimeStamp = tsInit.timestamp ) tsIntervalSL = IntervalStep_frKeep( num_dev = self.num_dev, num_wg = self.num_wg, num_t = self.num_t, TsNameToObj = self.TsNameToObj, ConstraintList = self.ConstraintList , PiVarList = self.PiVarList ) self.tsList.append( tsIntervalSL ) tsBListS2 = self.addAChain( parentInstruction = parent_instruction_2, Eid = e2, childInstructions = rfMapInst[ parent_instruction_2 ], prevTimeStamp = tsIntervalSL.timestamp ) tsIntervalLL = IntervalStep_frKeep( num_dev = self.num_dev, num_wg = self.num_wg, num_t = self.num_t, TsNameToObj = self.TsNameToObj, ConstraintList = self.ConstraintList , PiVarList = self.PiVarList ) self.tsList.append( tsIntervalLL ) tsUListR = self.addAChain( parentInstruction = parent_instruction_3, Eid = e3, childInstructions = rfMapInst[ parent_instruction_3 ], prevTimeStamp = tsIntervalLL.timestamp ) #self.ConstraintList.append( HB(tsInit,tsBListS1[0]) ) self.ConstraintList.append( HB(tsBListS1[-1], tsIntervalSL) ) self.ConstraintList.append( HB(tsBListS2[-1], tsIntervalLL) ) # tsIntervalSL --HB--> tsU is guaranteed by addAChain self.setPiFunAW( PiVarList = self.PiVarList, TsThatWritesVar = self.TsThatWritesVar, AllWriteTsList = [tsInit, tsIntervalSL, tsIntervalLL] ) self.setPiFunAW( PiVarList = self.PiVarList, TsThatWritesVar = self.TsThatWritesVar, AllWriteTsList = [tsInit, tsIntervalSL, tsIntervalLL] ) constrainIntervals(tsInit) def PO3SSL(self, parent_instruction_1, e1, parent_instruction_2, e2, parent_instruction_3, e3): # for load_DV_Rs : axiom 3 def constrainIntervals(ts1,ts2, ts3): # ts1 is the init , and ts2 is the interval assert len(ts1.L1FifoTails) == len(ts2.L1FifoTailDeltas) assert len(ts1.L1FifoHeads) == len(ts2.L1FifoHeadDeltas) assert len(ts1.L1FifoTails) == len(ts2.L1FifoHeads) assert len(ts1.L1FifoTails) == len(ts3.L1FifoTailDeltas) assert len(ts1.L1FifoHeads) == len(ts3.L1FifoHeadDeltas) assert len(ts1.L1FifoTails) == len(ts3.L1FifoHeads) for sname in ts1.L1FifoHeads.keys(): # this is actually for all dw head_name = sname tail_name = sname.replace('head','tail') self.ConstraintList.append( ts1.L1FifoHeads[head_name] >= 0 ) self.ConstraintList.append( ts1.L1FifoTails[tail_name] >= 0 ) self.ConstraintList.append( ts1.L1FifoHeads[head_name] >= ts1.L1FifoTails[tail_name] ) self.ConstraintList.append( ts2.L1FifoHeadDeltas[head_name] >= 0 ) self.ConstraintList.append( ts2.L1FifoTailDeltas[tail_name] >= 0 ) self.ConstraintList.append( ts2.L1FifoHeads[head_name] >= ts2.L1FifoTails[tail_name] ) self.ConstraintList.append( ts3.L1FifoHeadDeltas[head_name] >= 0 ) self.ConstraintList.append( ts3.L1FifoTailDeltas[tail_name] >= 0 ) self.ConstraintList.append( ts3.L1FifoHeads[head_name] >= ts3.L1FifoTails[tail_name] ) self.ConstraintList.append( ts2.L1FifoHeadDeltas[head_name] + ts3.L1FifoHeadDeltas[head_name] >= ts2.L1FifoTailDeltas[tail_name] + ts3.L1FifoTailDeltas[tail_name] ) # these are the environmental constraint #first get the micro instructions tsInit = InitStep_fifo( num_dev = self.num_dev, num_wg = self.num_wg, num_t = self.num_t, TsNameToObj = self.TsNameToObj , overwriteTimeStamp = 0 ) self.tsList.append( tsInit ) tsBListS1 = self.addAChain( parentInstruction = parent_instruction_1, Eid = e1, childInstructions = rfMapInst[ parent_instruction_1 ], prevTimeStamp = tsInit.timestamp ) tsIntervalSS = IntervalStep_fifo( num_dev = self.num_dev, num_wg = self.num_wg, num_t = self.num_t, TsNameToObj = self.TsNameToObj, TsThatWritesVar = self.TsThatWritesVar , ConstraintList = self.ConstraintList , PiVarList = self.PiVarList ) self.tsList.append( tsIntervalSS ) tsBListS2 = self.addAChain( parentInstruction = parent_instruction_2, Eid = e2, childInstructions = rfMapInst[ parent_instruction_2 ], prevTimeStamp = tsIntervalSS.timestamp ) tsIntervalSL = IntervalStep_fifo( num_dev = self.num_dev, num_wg = self.num_wg, num_t = self.num_t, TsNameToObj = self.TsNameToObj, TsThatWritesVar = self.TsThatWritesVar , ConstraintList = self.ConstraintList , PiVarList = self.PiVarList ) self.tsList.append( tsIntervalSL ) tsUListR = self.addAChain( parentInstruction = parent_instruction_3, Eid = e3, childInstructions = rfMapInst[ parent_instruction_3 ], prevTimeStamp = tsIntervalSL.timestamp ) #self.ConstraintList.append( HB(tsInit,tsBListS1[0]) ) self.ConstraintList.append( HB(tsBListS1[-1], tsIntervalSS) ) self.ConstraintList.append( HB(tsBListS2[-1], tsIntervalSL) ) # tsIntervalSS --HB--> tsU is guaranteed by addAChain self.setPiFunAW( PiVarList = self.PiVarList, TsThatWritesVar = self.TsThatWritesVar, AllWriteTsList = [tsInit, tsIntervalSS, tsIntervalSL] ) ## TODO: add the invariants constrainIntervals(tsInit,tsIntervalSS,tsIntervalSL) def add_check_axiom(self): #axiom.store_dv_r_3(self) #axiom.load_dv_r_3(self) axiom.PO2Axioms(self) def pushInstConstraintAndCheck(self): self.solver = z3.Solver() s = self.solver s.set(unsat_core=True if DEBUG else False) idx = 0 for c in self.ConstraintList: if DEBUG: print >>self.logcat, idx,':', c #raw_input() if c is False: print '<W>: False cannot be satisfied' elif c is True: pass else: s.assert_and_track(c,'n'+str(idx)) idx += 1 else: s.add(c) result = s.check() print 'w.o. run Property:', result self.modelCheckResult = result if result == z3.sat: self.model = s.model() else: # unsat if DEBUG: print >>self.logcat, s.unsat_core() print '<W>: Not all the reads can be executed! Trace debug info dumped.' return result def solve(self): if self.modelCheckResult == z3.unsat: print '<W>: inconsistent model. Won\'t continue to check the properties.' return s = self.solver if len(self.runProp) == 0: print '<W>: no property specified.' return else: runProp = z3.Not( LAnd(self.runProp) ) if DEBUG: print >> self.logcat, 'rp : ', runProp s.assert_and_track(runProp,'rp') else: s.add(runProp) # extract module result = s.check() print result if result == z3.unsat: # this may use the old one if DEBUG: print >>self.logcat, s.unsat_core() elif result == z3.sat: self.model = s.model() print 'negation is witnessed' #self.printModel() else: print 'status Unknown' return result def printModel(self): print >> self.logcat, '====================== MODEL =====================' for ts in self.tsList: print >>self.logcat, ts.name, ' entity:', ts.entity.toName() if 'entity' in ts.__dict__ else 'GLOBAL' t,d,val,readCol = ts.getConcreteModel(self.model) instName = ts.inst.name if 'inst' in ts.__dict__ else 'INIT' print >>self.logcat, '@%s, %s:%s'%(str(t), instName, d) for n,v in readCol.items(): if isinstance(v, tuple): value = str(v[0]) + '\taddr: ' + str('ANY' if v[1].anyAddr else ( 'z3:' + str(v[1].eval(self.model) ) + ', id:' + v[1].vaid ) ) print >> self.logcat, '\t (Read %s = %s)' % (n, value ) else: print >>self.logcat, '\t (Read %s = %s)' % (n, str(v) ) for n,v in val.items(): if isinstance(v, tuple): value = str(v[0]) + '\taddr: ' + str('ANY' if v[1].anyAddr else ( 'z3:' + str(v[1].eval(self.model) ) + ', id:' + v[1].vaid ) ) print >>self.logcat, '\t %s:%s' % (n,value) else: print >>self.logcat, '\t %s:%s' % (n,str(v)) self.logcat.flush() def check2store(num_dev,num_wg,num_t): #for devIdx1 in range(num_dev): # for wgId1 in range(num_wg): # for tIdx1 in range(num_t): devIdx1 = 0; wgId1 = 0; tIdx1 = 0 for devIdx2 in range(num_dev): for wgId2 in range(num_wg): for tIdx2 in range(num_t): eqc = eqchecker(num_dev,num_wg,num_t) eqc.logcat = open('eqcheck.log', 'wt') eid1 = gpuModel.entity(devIdx1,wgId1,tIdx1) eid2 = gpuModel.entity(devIdx2,wgId2,tIdx2) eqc.POAhead2Store(parent_instruction_1 = openclrsp.CL_store_DV_R, e1 = eid1, parent_instruction_2 = openclrsp.CL_store_na_or_WG, e2 = eid2 ) eqc.add_check_axiom() if eqc.pushInstConstraintAndCheck() != z3.sat: print 'unrealistic scenario!' assert False if eqc.solve() == z3.sat: print 'Ordering is not guaranteed.' eqc.printModel() assert False eqc.logcat.close() def checkSSL(num_dev,num_wg,num_t): devIdx1 = 0; wgId1 = 0; tIdx1 = 0 #for devIdx1 in range(num_dev): # for wgId1 in range(num_wg): # for tIdx1 in range(num_t): for devIdx2 in range(num_dev): for wgId2 in range(num_wg): for tIdx2 in range(num_t): for devIdx3 in range(num_dev): for wgId3 in range(num_wg): for tIdx3 in range(num_t): eqc = eqchecker(num_dev,num_wg,num_t) eqc.logcat = open('eqcheck.log', 'wt') eid1 = gpuModel.entity(devIdx1,wgId1,tIdx1) eid2 = gpuModel.entity(devIdx2,wgId2,tIdx2) eid3 = gpuModel.entity(devIdx3,wgId3,tIdx3) eqc.PO3SSL( parent_instruction_1 = openclrsp.CL_store_DV_N, e1 = eid1, parent_instruction_2 = openclrsp.CL_store_DV_N, e2 = eid2, parent_instruction_3 = openclrsp.CL_load_DV_R, e3 = eid3 ) eqc.add_check_axiom() if eqc.pushInstConstraintAndCheck() != z3.sat: print 'unrealistic scenario!' assert False #eqc.printModel() #eqc.logcat.close() #exit(1) if eqc.solve() == z3.sat: print 'Ordering is not guaranteed.' eqc.printModel() assert False eqc.logcat.close() #eqc.printModel() #eqc.logcat.close() #exit(1) def checkSLL(num_dev,num_wg,num_t): devIdx1 = 0; wgId1 = 0; tIdx1 = 0 #devIdx2 = 0; wgId2 = 1; tIdx2 = 0 #devIdx3 = 0; wgId3 = 0; tIdx3 = 0 #for devIdx1 in range(num_dev): # for wgId1 in range(num_wg): # for tIdx1 in range(num_t): for devIdx2 in range(num_dev): for wgId2 in range(num_wg): for tIdx2 in range(num_t): for devIdx3 in range(num_dev): for wgId3 in range(num_wg): for tIdx3 in range(num_t): eqc = eqchecker(num_dev,num_wg,num_t) eqc.logcat = open('eqcheck.log', 'wt') eid1 = gpuModel.entity(devIdx1,wgId1,tIdx1) eid2 = gpuModel.entity(devIdx2,wgId2,tIdx2) eid3 = gpuModel.entity(devIdx3,wgId3,tIdx3) eqc.PO3SLL( parent_instruction_1 = openclrsp.CL_store_DV_R, e1 = eid1, parent_instruction_2 = openclrsp.CL_load_na_or_WG, e2 = eid2, parent_instruction_3 = openclrsp.CL_load_na_or_WG, e3 = eid3 ) eqc.add_check_axiom() if eqc.pushInstConstraintAndCheck() != z3.sat: print 'unrealistic scenario!' assert False if eqc.solve() == z3.sat: print 'Ordering is not guaranteed.' eqc.printModel() assert False eqc.logcat.close() def check2load(num_dev,num_wg,num_t): devIdx1 = 0; wgId1 = 0; tIdx1 = 0 #for devIdx1 in range(num_dev): # for wgId1 in range(num_wg): # for tIdx1 in range(num_t): for devIdx2 in range(num_dev): for wgId2 in range(num_wg): for tIdx2 in range(num_t): eqc = eqchecker(num_dev,num_wg,num_t) eqc.logcat = open('eqcheck.log', 'wt') eid1 = gpuModel.entity(devIdx1,wgId1,tIdx1) eid2 = gpuModel.entity(devIdx2,wgId2,tIdx2) eqc.POAfter2Load(parent_instruction_1 = openclrsp.CL_load_DV_N, e1 = eid1, parent_instruction_2 = openclrsp.CL_load_DV_N, e2 = eid2 ) eqc.add_check_axiom() if eqc.pushInstConstraintAndCheck() != z3.sat: print 'unrealistic scenario!' assert False #eqc.printModel() #eqc.logcat.close() #exit(1) if eqc.solve() == z3.sat: print 'Ordering is not guaranteed.' eqc.printModel() assert False eqc.logcat.close() if __name__ == '__main__': #check2store(2,2,2) # should also check for store_DV_R to previous stores AXIOM 1 2 check2load(2,2,2) #checkSSL(2,2,2) #checkSLL(2,2,2)
en
0.667276
# --------------------------- # Configurations # --------------------------- # --------------------------- # Prerequisites # --------------------------- # --------------------------- # clInstruction = openclrsp.CL_load_DV_N # gpuInstruction = [ gpuModel.ev_FETCH_L1 , gpuModel.inst_LD , gpuModel.inst_INV_L1_WG ] # fetch will also need this # will wait for many of it # pre is already modeled in the sequence #Corret : [ gpuModel.inst_LD , gpuModel.inst_INV_L1_WG ], # wrong implementation: [ gpuModel.inst_INV_L1_WG , gpuModel.inst_LD ], #[ gpuModel.inst_LK_L2, gpuModel.inst_FLU_L1_DV, gpuModel.inst_INV_L1_WG, gpuModel.inst_LD, gpuModel.inst_UL_L2 ], # new: [ gpuModel.inst_LD , gpuModel.inst_FLU_L1_DV , gpuModel.inst_INV_L1_WG ] original : [ gpuModel.inst_LK_L2, gpuModel.inst_FLU_L1_DV, gpuModel.inst_INV_L1_WG, gpuModel.inst_LD, gpuModel.inst_UL_L2 ] # Wrong : [ gpuModel.inst_LK_L2, gpuModel.inst_FLU_L1_WG, gpuModel.inst_ST, gpuModel.inst_INV_L1_DV, gpuModel.inst_UL_L2 ], # this was the wrong thing # ============================================= # EQ CHECKER # ============================================= # pi_var_name (ts + statename) -> [ (sname, pivar, ts, addr ) ] # Note this is not a list of PO # Note that the prev decode may be in # set of String : name of the PiVar # ld --> fetch (if fetch.decode then must read from fetch else must others) # ====================================== # below is the content of the collector # ====================================== #state = lambda stateName, addr = None , overWriteVA = None: ts1.stateReadFunc(stateName,addr,overWriteVA) # need to plug-in additional decode in the beginning, if it is not None, will add # unless specify slot, will not provide # addr = z3.Int('addr'+str(self.num_of_inst_in_scene) ) # the order here matters # reg = z3.Int('reg' +str(self.num_of_inst_in_scene) ) # the order here matters # and you need to check if you need an entity or not # e1 = self._genEntity() # entity for the instruction # tsList is gathering all these # concretize the instruction # get the instruction # here is the logic for the pause after flush # then it should be a list # Previous is FLU_WG # change the decode function when necessary # r # PO relations are added by axioms # w/r vop relations are added by axioms # prev decode may be in effect for another instruction, but not in our case # but still it would be best to add parent instruction according their program order ?? # for one parent-instruction -> should return one child instruction # entity # gen addrs # the order here matters # the order here matters # and you need to check if you need an entity or not # e1 = self._genEntity() # entity for the instruction #addr, reg, e1, inst_func # every child instruction step is later than init or the previous barrier (not including evs) # tsRef.timestamp > prevTs.timestamp ) # constraint 2: child instruction po # prevTs is None # check that flush is not the last child instruction !!! # reset it # constraint #3: child instructions must be executed # Constriant DECODE # here, start to # check the need to add additional environmental transition # FETCH -> LD # we only handle the case with one fetch (RVOP) # we don't require its decode to be true # get from updateDict # only guarantee if both decodes are true # ST -> will # the one that will happenBefore it # get the slot # parent_or_prev_ts.timestamp < tsRef_sub.timestamp ) # # get from read its local register value # FLUSH: either the device or workgroup # it will only be one instruction # but still you won't need to change decode ? # in this case we will need to create #WG flush MARKER and # read the slot from tsRef # dep marker will need this # create a ts after it # tsRef_sub.timestamp > tsRef.timestamp ) # concat decode for all Wg # may be we can directly instantiate the function (to z3expr) here without calling it # dep marker will need this # it will only be one instruction # tsRef_sub.timestamp > tsRef.timestamp ) # we won't support other cases # depends on which one WG or DV # we need to add decode expr once or all # add happen before before instructions # set the end and start # Let's add pi function # by default should be self.PiVarList # check its name, so repetition # else: # fetch_ts.inst.decodeFunc => rf # 3 update check # this will disallow read from the fetch # 3 update check # check decode # but we will add all the inst to be true??? # ts1 is the init , and ts2 is the interval # this is actually for all dw # these are the environmental constraint #first get the micro instructions # do we really need this? # tsInterval --HB--> tsU is guaranteed by addAChain ## TODO: add the invariants #first get the micro instructions # add init frame # add instr @ check frame # add instr that separate # add inst @ after frame # here let's backup the whole thing push pi var to a stack #self.setPiFun(init = tsInit, PiVarList = self.PiVarList, TsThatWritesVar = self.TsThatWritesVar) #self.PiVarListOld = self.PiVarList #.update(self.PiVarList) #self.PiVarList = {} push TsThatWritesVar #self.TsThatWritesVarOld = self.TsThatWritesVar #.update(self.TsThatWritesVar) #self.TsThatWritesVar = {} # instructions are PO after tsInterval # this will update the PiVarList associated with IntervalStep_frKeep # #self.setPiFun(init = tsInterval, PiVarList = self.PiVarList, TsThatWritesVar = self.TsThatWritesVar) # redo this, but the constrained ones should be okay, because no repetition is there # do it twice because in the first case, there are pi var generated (on demand) #assert ('pi_intervalts5_L1fr@0,0addr0' in self.PiVarList) #assert ('pi_intervalts5_L1fr@0,0addr1' in self.PiVarList) # do we really need this? # self.ConstraintList.append( HB(tsInterval,tsAfterCheck[0]) ) # we don't need this, it is already enforced ## TODO: add the invariants # you will need rf relation as a function # for store_DV_Rs : axiom 3 #,ts2): # ts1 is the init , and ts2 is the interval #assert len(ts1.L1FifoTails) == len(ts2.L1FifoTailDeltas) #assert len(ts1.L1FifoHeads) == len(ts2.L1FifoHeadDeltas) #assert len(ts1.L1FifoTails) == len(ts2.L1FifoHeads) # this is actually for all dw #self.ConstraintList.append( ts2.L1FifoHeadDeltas[head_name] >= 0 ) #self.ConstraintList.append( ts2.L1FifoTailDeltas[tail_name] >= 0 ) #self.ConstraintList.append( ts2.L1FifoHeadDeltas[head_name] == ts2.L1FifoTailDeltas[tail_name] ) #first get the micro instructions #InitStep_any( num_dev = self.num_dev, num_wg = self.num_wg, num_t = self.num_t, TsNameToObj = self.TsNameToObj , overwriteTimeStamp = 0 ) #self.ConstraintList.append( HB(tsInit,tsBListS1[0]) ) # tsIntervalSL --HB--> tsU is guaranteed by addAChain # for load_DV_Rs : axiom 3 # ts1 is the init , and ts2 is the interval # this is actually for all dw # these are the environmental constraint #first get the micro instructions #self.ConstraintList.append( HB(tsInit,tsBListS1[0]) ) # tsIntervalSS --HB--> tsU is guaranteed by addAChain ## TODO: add the invariants #axiom.store_dv_r_3(self) #axiom.load_dv_r_3(self) #raw_input() # unsat # extract module # this may use the old one #self.printModel() #for devIdx1 in range(num_dev): # for wgId1 in range(num_wg): # for tIdx1 in range(num_t): #for devIdx1 in range(num_dev): # for wgId1 in range(num_wg): # for tIdx1 in range(num_t): #eqc.printModel() #eqc.logcat.close() #exit(1) #eqc.printModel() #eqc.logcat.close() #exit(1) #devIdx2 = 0; wgId2 = 1; tIdx2 = 0 #devIdx3 = 0; wgId3 = 0; tIdx3 = 0 #for devIdx1 in range(num_dev): # for wgId1 in range(num_wg): # for tIdx1 in range(num_t): #for devIdx1 in range(num_dev): # for wgId1 in range(num_wg): # for tIdx1 in range(num_t): #eqc.printModel() #eqc.logcat.close() #exit(1) #check2store(2,2,2) # should also check for store_DV_R to previous stores AXIOM 1 2 #checkSSL(2,2,2) #checkSLL(2,2,2)
1.903766
2
src/python/pants/backend/python/target_types_rules.py
rcuza/pants
0
6632220
<reponame>rcuza/pants # Copyright 2020 Pants project contributors (see CONTRIBUTORS.md). # Licensed under the Apache License, Version 2.0 (see LICENSE). """Rules for the core Python target types. This is a separate module to avoid circular dependencies. Note that all types used by call sites are defined in `target_types.py`. """ import dataclasses import os.path from pants.backend.python.dependency_inference.module_mapper import PythonModule, PythonModuleOwners from pants.backend.python.dependency_inference.rules import PythonInferSubsystem, import_rules from pants.backend.python.target_types import ( PexBinaryDependencies, PexEntryPointField, PythonDistributionDependencies, PythonProvidesField, ResolvedPexEntryPoint, ResolvePexEntryPointRequest, ) from pants.engine.addresses import Address, Addresses, UnparsedAddressInputs from pants.engine.fs import GlobMatchErrorBehavior, PathGlobs, Paths from pants.engine.rules import Get, MultiGet, collect_rules, rule from pants.engine.target import ( Dependencies, DependenciesRequest, ExplicitlyProvidedDependencies, InjectDependenciesRequest, InjectedDependencies, InvalidFieldException, WrappedTarget, ) from pants.engine.unions import UnionRule from pants.source.source_root import SourceRoot, SourceRootRequest # ----------------------------------------------------------------------------------------------- # `pex_binary` rules # ----------------------------------------------------------------------------------------------- @rule(desc="Determining the entry point for a `pex_binary` target") async def resolve_pex_entry_point(request: ResolvePexEntryPointRequest) -> ResolvedPexEntryPoint: ep_val = request.entry_point_field.value address = request.entry_point_field.address # We support several different schemes: # 1) `<none>` or `<None>` => set to `None`. # 2) `path.to.module` => preserve exactly. # 3) `path.to.module:func` => preserve exactly. # 4) `app.py` => convert into `path.to.app`. # 5) `app.py:func` => convert into `path.to.app:func`. # Case #1. if ep_val.module in ("<none>", "<None>"): return ResolvedPexEntryPoint(None) # If it's already a module (cases #2 and #3), simply use that. Otherwise, convert the file name # into a module path (cases #4 and #5). if not ep_val.module.endswith(".py"): return ResolvedPexEntryPoint(ep_val) # Use the engine to validate that the file exists and that it resolves to only one file. full_glob = os.path.join(address.spec_path, ep_val.module) entry_point_paths = await Get( Paths, PathGlobs( [full_glob], glob_match_error_behavior=GlobMatchErrorBehavior.error, description_of_origin=f"{address}'s `{request.entry_point_field.alias}` field", ), ) # We will have already raised if the glob did not match, i.e. if there were no files. But # we need to check if they used a file glob (`*` or `**`) that resolved to >1 file. if len(entry_point_paths.files) != 1: raise InvalidFieldException( f"Multiple files matched for the `{request.entry_point_field.alias}` " f"{ep_val.spec!r} for the target {address}, but only one file expected. Are you using " f"a glob, rather than a file name?\n\n" f"All matching files: {list(entry_point_paths.files)}." ) entry_point_path = entry_point_paths.files[0] source_root = await Get( SourceRoot, SourceRootRequest, SourceRootRequest.for_file(entry_point_path), ) stripped_source_path = os.path.relpath(entry_point_path, source_root.path) module_base, _ = os.path.splitext(stripped_source_path) normalized_path = module_base.replace(os.path.sep, ".") return ResolvedPexEntryPoint(dataclasses.replace(ep_val, module=normalized_path)) class InjectPexBinaryEntryPointDependency(InjectDependenciesRequest): inject_for = PexBinaryDependencies @rule(desc="Inferring dependency from the pex_binary `entry_point` field") async def inject_pex_binary_entry_point_dependency( request: InjectPexBinaryEntryPointDependency, python_infer_subsystem: PythonInferSubsystem ) -> InjectedDependencies: if not python_infer_subsystem.entry_points: return InjectedDependencies() original_tgt = await Get(WrappedTarget, Address, request.dependencies_field.address) explicitly_provided_deps, entry_point = await MultiGet( Get(ExplicitlyProvidedDependencies, DependenciesRequest(original_tgt.target[Dependencies])), Get( ResolvedPexEntryPoint, ResolvePexEntryPointRequest(original_tgt.target[PexEntryPointField]), ), ) if entry_point.val is None: return InjectedDependencies() owners = await Get(PythonModuleOwners, PythonModule(entry_point.val.module)) address = original_tgt.target.address explicitly_provided_deps.maybe_warn_of_ambiguous_dependency_inference( owners.ambiguous, address, import_reference="module", context=( f"The pex_binary target {address} has the field " f"`entry_point={repr(original_tgt.target[PexEntryPointField].value.spec)}`, which " f"maps to the Python module `{entry_point.val.module}`" ), ) maybe_disambiguated = explicitly_provided_deps.disambiguated_via_ignores(owners.ambiguous) unambiguous_owners = owners.unambiguous or ( (maybe_disambiguated,) if maybe_disambiguated else () ) return InjectedDependencies(unambiguous_owners) # ----------------------------------------------------------------------------------------------- # `python_distribution` rules # ----------------------------------------------------------------------------------------------- class InjectPythonDistributionDependencies(InjectDependenciesRequest): inject_for = PythonDistributionDependencies @rule async def inject_python_distribution_dependencies( request: InjectPythonDistributionDependencies, ) -> InjectedDependencies: """Inject any `.with_binaries()` values, as it would be redundant to have to include in the `dependencies` field.""" original_tgt = await Get(WrappedTarget, Address, request.dependencies_field.address) with_binaries = original_tgt.target[PythonProvidesField].value.binaries if not with_binaries: return InjectedDependencies() # Note that we don't validate that these are all `pex_binary` targets; we don't care about # that here. `setup_py.py` will do that validation. addresses = await Get( Addresses, UnparsedAddressInputs( with_binaries.values(), owning_address=request.dependencies_field.address ), ) return InjectedDependencies(addresses) def rules(): return ( *collect_rules(), *import_rules(), UnionRule(InjectDependenciesRequest, InjectPexBinaryEntryPointDependency), UnionRule(InjectDependenciesRequest, InjectPythonDistributionDependencies), )
# Copyright 2020 Pants project contributors (see CONTRIBUTORS.md). # Licensed under the Apache License, Version 2.0 (see LICENSE). """Rules for the core Python target types. This is a separate module to avoid circular dependencies. Note that all types used by call sites are defined in `target_types.py`. """ import dataclasses import os.path from pants.backend.python.dependency_inference.module_mapper import PythonModule, PythonModuleOwners from pants.backend.python.dependency_inference.rules import PythonInferSubsystem, import_rules from pants.backend.python.target_types import ( PexBinaryDependencies, PexEntryPointField, PythonDistributionDependencies, PythonProvidesField, ResolvedPexEntryPoint, ResolvePexEntryPointRequest, ) from pants.engine.addresses import Address, Addresses, UnparsedAddressInputs from pants.engine.fs import GlobMatchErrorBehavior, PathGlobs, Paths from pants.engine.rules import Get, MultiGet, collect_rules, rule from pants.engine.target import ( Dependencies, DependenciesRequest, ExplicitlyProvidedDependencies, InjectDependenciesRequest, InjectedDependencies, InvalidFieldException, WrappedTarget, ) from pants.engine.unions import UnionRule from pants.source.source_root import SourceRoot, SourceRootRequest # ----------------------------------------------------------------------------------------------- # `pex_binary` rules # ----------------------------------------------------------------------------------------------- @rule(desc="Determining the entry point for a `pex_binary` target") async def resolve_pex_entry_point(request: ResolvePexEntryPointRequest) -> ResolvedPexEntryPoint: ep_val = request.entry_point_field.value address = request.entry_point_field.address # We support several different schemes: # 1) `<none>` or `<None>` => set to `None`. # 2) `path.to.module` => preserve exactly. # 3) `path.to.module:func` => preserve exactly. # 4) `app.py` => convert into `path.to.app`. # 5) `app.py:func` => convert into `path.to.app:func`. # Case #1. if ep_val.module in ("<none>", "<None>"): return ResolvedPexEntryPoint(None) # If it's already a module (cases #2 and #3), simply use that. Otherwise, convert the file name # into a module path (cases #4 and #5). if not ep_val.module.endswith(".py"): return ResolvedPexEntryPoint(ep_val) # Use the engine to validate that the file exists and that it resolves to only one file. full_glob = os.path.join(address.spec_path, ep_val.module) entry_point_paths = await Get( Paths, PathGlobs( [full_glob], glob_match_error_behavior=GlobMatchErrorBehavior.error, description_of_origin=f"{address}'s `{request.entry_point_field.alias}` field", ), ) # We will have already raised if the glob did not match, i.e. if there were no files. But # we need to check if they used a file glob (`*` or `**`) that resolved to >1 file. if len(entry_point_paths.files) != 1: raise InvalidFieldException( f"Multiple files matched for the `{request.entry_point_field.alias}` " f"{ep_val.spec!r} for the target {address}, but only one file expected. Are you using " f"a glob, rather than a file name?\n\n" f"All matching files: {list(entry_point_paths.files)}." ) entry_point_path = entry_point_paths.files[0] source_root = await Get( SourceRoot, SourceRootRequest, SourceRootRequest.for_file(entry_point_path), ) stripped_source_path = os.path.relpath(entry_point_path, source_root.path) module_base, _ = os.path.splitext(stripped_source_path) normalized_path = module_base.replace(os.path.sep, ".") return ResolvedPexEntryPoint(dataclasses.replace(ep_val, module=normalized_path)) class InjectPexBinaryEntryPointDependency(InjectDependenciesRequest): inject_for = PexBinaryDependencies @rule(desc="Inferring dependency from the pex_binary `entry_point` field") async def inject_pex_binary_entry_point_dependency( request: InjectPexBinaryEntryPointDependency, python_infer_subsystem: PythonInferSubsystem ) -> InjectedDependencies: if not python_infer_subsystem.entry_points: return InjectedDependencies() original_tgt = await Get(WrappedTarget, Address, request.dependencies_field.address) explicitly_provided_deps, entry_point = await MultiGet( Get(ExplicitlyProvidedDependencies, DependenciesRequest(original_tgt.target[Dependencies])), Get( ResolvedPexEntryPoint, ResolvePexEntryPointRequest(original_tgt.target[PexEntryPointField]), ), ) if entry_point.val is None: return InjectedDependencies() owners = await Get(PythonModuleOwners, PythonModule(entry_point.val.module)) address = original_tgt.target.address explicitly_provided_deps.maybe_warn_of_ambiguous_dependency_inference( owners.ambiguous, address, import_reference="module", context=( f"The pex_binary target {address} has the field " f"`entry_point={repr(original_tgt.target[PexEntryPointField].value.spec)}`, which " f"maps to the Python module `{entry_point.val.module}`" ), ) maybe_disambiguated = explicitly_provided_deps.disambiguated_via_ignores(owners.ambiguous) unambiguous_owners = owners.unambiguous or ( (maybe_disambiguated,) if maybe_disambiguated else () ) return InjectedDependencies(unambiguous_owners) # ----------------------------------------------------------------------------------------------- # `python_distribution` rules # ----------------------------------------------------------------------------------------------- class InjectPythonDistributionDependencies(InjectDependenciesRequest): inject_for = PythonDistributionDependencies @rule async def inject_python_distribution_dependencies( request: InjectPythonDistributionDependencies, ) -> InjectedDependencies: """Inject any `.with_binaries()` values, as it would be redundant to have to include in the `dependencies` field.""" original_tgt = await Get(WrappedTarget, Address, request.dependencies_field.address) with_binaries = original_tgt.target[PythonProvidesField].value.binaries if not with_binaries: return InjectedDependencies() # Note that we don't validate that these are all `pex_binary` targets; we don't care about # that here. `setup_py.py` will do that validation. addresses = await Get( Addresses, UnparsedAddressInputs( with_binaries.values(), owning_address=request.dependencies_field.address ), ) return InjectedDependencies(addresses) def rules(): return ( *collect_rules(), *import_rules(), UnionRule(InjectDependenciesRequest, InjectPexBinaryEntryPointDependency), UnionRule(InjectDependenciesRequest, InjectPythonDistributionDependencies), )
en
0.707392
# Copyright 2020 Pants project contributors (see CONTRIBUTORS.md). # Licensed under the Apache License, Version 2.0 (see LICENSE). Rules for the core Python target types. This is a separate module to avoid circular dependencies. Note that all types used by call sites are defined in `target_types.py`. # ----------------------------------------------------------------------------------------------- # `pex_binary` rules # ----------------------------------------------------------------------------------------------- # We support several different schemes: # 1) `<none>` or `<None>` => set to `None`. # 2) `path.to.module` => preserve exactly. # 3) `path.to.module:func` => preserve exactly. # 4) `app.py` => convert into `path.to.app`. # 5) `app.py:func` => convert into `path.to.app:func`. # Case #1. # If it's already a module (cases #2 and #3), simply use that. Otherwise, convert the file name # into a module path (cases #4 and #5). # Use the engine to validate that the file exists and that it resolves to only one file. # We will have already raised if the glob did not match, i.e. if there were no files. But # we need to check if they used a file glob (`*` or `**`) that resolved to >1 file. # ----------------------------------------------------------------------------------------------- # `python_distribution` rules # ----------------------------------------------------------------------------------------------- Inject any `.with_binaries()` values, as it would be redundant to have to include in the `dependencies` field. # Note that we don't validate that these are all `pex_binary` targets; we don't care about # that here. `setup_py.py` will do that validation.
1.916352
2
reskit/test/test_CosmoSource.py
r-beer/RESKit
0
6632221
def test___init__(): # (s, source, bounds=None, indexPad=0, **kwargs): print( "__init__ not tested...") def test_loc2Index(): # (s, loc, outsideOkay=False, asInt=True): print( "loc2Index not tested...") def test_loadRadiation(): # (s): print( "loadRadiation not tested...") def test_loadWindSpeedLevels(): # (s): print( "loadWindSpeedLevels not tested...") def test_loadWindSpeedAtHeight(): # (s, height=100): print( "loadWindSpeedAtHeight not tested...") def test_loadTemperature(): # (s, processor=lambda x: x-273.15): print( "loadTemperature not tested...") def test_loadPressure(): # (s): print( "loadPressure not tested...") def test_loadSet_PV(): # (s): print( "loadSet_PV not tested...") def test_getWindSpeedAtHeights(): # (s, locations, heights, spatialInterpolation='near', forceDataFrame=False, outsideOkay=False, _indicies=None): print( "getWindSpeedAtHeights not tested...") if __name__ == "__main__": test___init__() test_loc2Index() test_loadRadiation() test_loadWindSpeedLevels() test_loadWindSpeedAtHeight() test_loadTemperature() test_loadPressure() test_loadSet_PV() test_getWindSpeedAtHeights()
def test___init__(): # (s, source, bounds=None, indexPad=0, **kwargs): print( "__init__ not tested...") def test_loc2Index(): # (s, loc, outsideOkay=False, asInt=True): print( "loc2Index not tested...") def test_loadRadiation(): # (s): print( "loadRadiation not tested...") def test_loadWindSpeedLevels(): # (s): print( "loadWindSpeedLevels not tested...") def test_loadWindSpeedAtHeight(): # (s, height=100): print( "loadWindSpeedAtHeight not tested...") def test_loadTemperature(): # (s, processor=lambda x: x-273.15): print( "loadTemperature not tested...") def test_loadPressure(): # (s): print( "loadPressure not tested...") def test_loadSet_PV(): # (s): print( "loadSet_PV not tested...") def test_getWindSpeedAtHeights(): # (s, locations, heights, spatialInterpolation='near', forceDataFrame=False, outsideOkay=False, _indicies=None): print( "getWindSpeedAtHeights not tested...") if __name__ == "__main__": test___init__() test_loc2Index() test_loadRadiation() test_loadWindSpeedLevels() test_loadWindSpeedAtHeight() test_loadTemperature() test_loadPressure() test_loadSet_PV() test_getWindSpeedAtHeights()
en
0.74998
# (s, source, bounds=None, indexPad=0, **kwargs): # (s, loc, outsideOkay=False, asInt=True): # (s): # (s): # (s, height=100): # (s, processor=lambda x: x-273.15): # (s): # (s): # (s, locations, heights, spatialInterpolation='near', forceDataFrame=False, outsideOkay=False, _indicies=None):
2.254461
2
hdf2mic/writer_dri.py
ralph0101/hdf2mic-converter
1
6632222
# -*- coding: utf-8 -*- r""" This module contains the MICRESS input driving file writer for the script hdf2mic.py. """ import os import re from hdf2mic.data import * from hdf2mic.writer import * from hdf2mic.arg_mapping import ArgMap_settingsOutputDri class DriWriter(Writer): """ Reads a tagged MICRESS driving template file, replaces tags and writes result. Tags in the template are of the form <mytagname>. Notes ----- Use with a context manager (see example). Examples -------- Write to file. >>> #... >>> data = reader.data >>> writer = DriWriter(ouputfile_txt) >>> with writer as f: ... writer.write(data) """ def __init__(self, filepath): Writer.__init__(self, filepath) self.template = None self._msg_warn_tag = "Warning: dri template is missing tag: {}." self._msg_err_outfile = "Error: driving template file requires output file {}, but was not found. Abort." self._inputfile_template = None def _replace(self, tag, replacement): match = re.match('(<.*>)', tag) if not match or len(match.groups()) != 1: if not tag: print("Warning: tag not specified for:\n\treplacement = {}\n\tin template = {}." .format(replacement, self._inputfile_template)) else: print("Warning: tag '{}' does not comply with recommended format '<mytagname>' for " "\n\treplacement = {}".format(tag, replacement)) if tag in self.template: self.template = self.template.replace(tag, str(replacement)) else: print(self._msg_warn_tag.format(tag)) def write(self, data, settings, verbose, inputfile_template, f_vtk='', f_txt=''): """ Parameters ---------- data : Data hdf2mic Data object settings : ArgMap_settingsOutputDri verbose : bool inputfile_template : str the hdf2mic input MICRESS driving template file f_vtk : str the optional hdf2mic output vtk file f_txt : str the optional hdf2mic output txt file (grain properties) Raises ------ AttributeError If not called inside a context manager. """ super(DriWriter, self).write(data, settings, verbose) self._inputfile_template = inputfile_template # check output files existence # os.path.isfile(filename_txt) # os.path.isfile(filename_vtk) # read driving template file template = "" try: with open(inputfile_template, 'r') as f_t: template = f_t.read() if not template: raise Hdf2Mic_DrivingFileTaggingError( "Dri_writer: processing driving template file was implied, " "but template file {} was empty." .format(inputfile_template) ) else: self.template = template # replace implicit tags: # regarding TAG_CELLS: DRI requires #cells, not #nodes, # so decrement by one. for i in range(data.dim): self._replace(Data.DRI_TAG_CELLS[i], str(data.dimensions[i] - 1)) self._replace(Data.DRI_TAG_SPACING, data.spacing[0]) # DEVNOTE: tag distinct-phases deactivated in v0.5 # as per request by RA # self._replace(Data.INPUT_DRI_TAG_PHASES, # len(np.unique(data.phases))) if f_txt: if (os.path.isfile(f_txt)): if self.settings.makePathsAbsolute: f_txt = os.path.abspath(f_txt) self._replace(Data.DRI_TAG_GRAIN_PROPERTIES, f_txt) else: raise Hdf2Mic_DrivingFileTaggingError( self._msg_err_outfile.format(f_txt)) # replace user-defined tags if f_vtk: if (os.path.isfile(f_vtk)): for tupl in data.celldata: # from Data.celldata: # tuples have either length 5 or 7 dataName = tupl[1] tag = tupl[-1] # replacement: fieldArrayName = "" if (len(tupl) == 7): fieldArrayName = tupl[-2] if self.settings.makePathsAbsolute: f_vtk = os.path.abspath(f_vtk) replacement = f_vtk + " " + dataName if fieldArrayName: replacement += " " + fieldArrayName self._replace(tag, replacement) else: raise Hdf2Mic_DrivingFileTaggingError( self._msg_err_outfile.format(f_vtk)) # save formatted driving template file self._f.write(self.template) except IOError as e: print("ERROR: could not find or open input file \'{}\'.".format(inputfile_template))
# -*- coding: utf-8 -*- r""" This module contains the MICRESS input driving file writer for the script hdf2mic.py. """ import os import re from hdf2mic.data import * from hdf2mic.writer import * from hdf2mic.arg_mapping import ArgMap_settingsOutputDri class DriWriter(Writer): """ Reads a tagged MICRESS driving template file, replaces tags and writes result. Tags in the template are of the form <mytagname>. Notes ----- Use with a context manager (see example). Examples -------- Write to file. >>> #... >>> data = reader.data >>> writer = DriWriter(ouputfile_txt) >>> with writer as f: ... writer.write(data) """ def __init__(self, filepath): Writer.__init__(self, filepath) self.template = None self._msg_warn_tag = "Warning: dri template is missing tag: {}." self._msg_err_outfile = "Error: driving template file requires output file {}, but was not found. Abort." self._inputfile_template = None def _replace(self, tag, replacement): match = re.match('(<.*>)', tag) if not match or len(match.groups()) != 1: if not tag: print("Warning: tag not specified for:\n\treplacement = {}\n\tin template = {}." .format(replacement, self._inputfile_template)) else: print("Warning: tag '{}' does not comply with recommended format '<mytagname>' for " "\n\treplacement = {}".format(tag, replacement)) if tag in self.template: self.template = self.template.replace(tag, str(replacement)) else: print(self._msg_warn_tag.format(tag)) def write(self, data, settings, verbose, inputfile_template, f_vtk='', f_txt=''): """ Parameters ---------- data : Data hdf2mic Data object settings : ArgMap_settingsOutputDri verbose : bool inputfile_template : str the hdf2mic input MICRESS driving template file f_vtk : str the optional hdf2mic output vtk file f_txt : str the optional hdf2mic output txt file (grain properties) Raises ------ AttributeError If not called inside a context manager. """ super(DriWriter, self).write(data, settings, verbose) self._inputfile_template = inputfile_template # check output files existence # os.path.isfile(filename_txt) # os.path.isfile(filename_vtk) # read driving template file template = "" try: with open(inputfile_template, 'r') as f_t: template = f_t.read() if not template: raise Hdf2Mic_DrivingFileTaggingError( "Dri_writer: processing driving template file was implied, " "but template file {} was empty." .format(inputfile_template) ) else: self.template = template # replace implicit tags: # regarding TAG_CELLS: DRI requires #cells, not #nodes, # so decrement by one. for i in range(data.dim): self._replace(Data.DRI_TAG_CELLS[i], str(data.dimensions[i] - 1)) self._replace(Data.DRI_TAG_SPACING, data.spacing[0]) # DEVNOTE: tag distinct-phases deactivated in v0.5 # as per request by RA # self._replace(Data.INPUT_DRI_TAG_PHASES, # len(np.unique(data.phases))) if f_txt: if (os.path.isfile(f_txt)): if self.settings.makePathsAbsolute: f_txt = os.path.abspath(f_txt) self._replace(Data.DRI_TAG_GRAIN_PROPERTIES, f_txt) else: raise Hdf2Mic_DrivingFileTaggingError( self._msg_err_outfile.format(f_txt)) # replace user-defined tags if f_vtk: if (os.path.isfile(f_vtk)): for tupl in data.celldata: # from Data.celldata: # tuples have either length 5 or 7 dataName = tupl[1] tag = tupl[-1] # replacement: fieldArrayName = "" if (len(tupl) == 7): fieldArrayName = tupl[-2] if self.settings.makePathsAbsolute: f_vtk = os.path.abspath(f_vtk) replacement = f_vtk + " " + dataName if fieldArrayName: replacement += " " + fieldArrayName self._replace(tag, replacement) else: raise Hdf2Mic_DrivingFileTaggingError( self._msg_err_outfile.format(f_vtk)) # save formatted driving template file self._f.write(self.template) except IOError as e: print("ERROR: could not find or open input file \'{}\'.".format(inputfile_template))
en
0.591926
# -*- coding: utf-8 -*- This module contains the MICRESS input driving file writer for the script hdf2mic.py. Reads a tagged MICRESS driving template file, replaces tags and writes result. Tags in the template are of the form <mytagname>. Notes ----- Use with a context manager (see example). Examples -------- Write to file. >>> #... >>> data = reader.data >>> writer = DriWriter(ouputfile_txt) >>> with writer as f: ... writer.write(data) Parameters ---------- data : Data hdf2mic Data object settings : ArgMap_settingsOutputDri verbose : bool inputfile_template : str the hdf2mic input MICRESS driving template file f_vtk : str the optional hdf2mic output vtk file f_txt : str the optional hdf2mic output txt file (grain properties) Raises ------ AttributeError If not called inside a context manager. # check output files existence # os.path.isfile(filename_txt) # os.path.isfile(filename_vtk) # read driving template file # replace implicit tags: # regarding TAG_CELLS: DRI requires #cells, not #nodes, # so decrement by one. # DEVNOTE: tag distinct-phases deactivated in v0.5 # as per request by RA # self._replace(Data.INPUT_DRI_TAG_PHASES, # len(np.unique(data.phases))) # replace user-defined tags # from Data.celldata: # tuples have either length 5 or 7 # replacement: # save formatted driving template file
2.842708
3
camera-test.py
AluminatiFRC/Vision2016
4
6632223
<gh_stars>1-10 import cv2 cap = cv2.VideoCapture(0) print "OpenCV version: " + cv2.__version__ while(True): ret, frame = cap.read() if ret: cv2.imshow('source', frame) if cv2.waitKey(1) & 0xFF == ord('q'): break cap.release() cv2.destroyAllWindows()
import cv2 cap = cv2.VideoCapture(0) print "OpenCV version: " + cv2.__version__ while(True): ret, frame = cap.read() if ret: cv2.imshow('source', frame) if cv2.waitKey(1) & 0xFF == ord('q'): break cap.release() cv2.destroyAllWindows()
none
1
2.889409
3
hwt/synthesizer/rtlLevel/signalUtils/ops.py
mgielda/hwt
0
6632224
<reponame>mgielda/hwt from hwt.doc_markers import internal from hwt.hdl.assignment import Assignment from hwt.hdl.operatorDefs import AllOps from hwt.hdl.types.defs import BOOL from hwt.hdl.types.sliceUtils import slice_to_SLICE from hwt.hdl.types.typeCast import toHVal from hwt.synthesizer.exceptions import TypeConversionErr from hwt.synthesizer.interfaceLevel.mainBases import InterfaceBase from hwt.synthesizer.rtlLevel.mainBases import RtlSignalBase from hwt.synthesizer.rtlLevel.signalUtils.exceptions import MultipleDriversErr,\ NoDriverErr def tv(signal): """ Value class for type of signal """ return signal._dtype.getValueCls() class RtlSignalOps(): """ Definitions of operators and other operator functions for RtlSignal :ivar _usedOps: cache for expressions with this signal """ def _auto_cast(self, toT): return self._dtype.auto_cast(self, toT) def _reinterpret_cast(self, toT): return self._dtype.reinterpret_cast(self, toT) @internal def naryOp(self, operator, opCreateDelegate, *otherOps) -> RtlSignalBase: """ Try lookup operator with this parameters in _usedOps if not found create new one and soter it in _usedOps :param operator: instance of OpDefinition :param opCreateDelegate: function (*ops) to create operator :param otherOps: other operands (ops = self + otherOps) :return: RtlSignal which is result of newly created operator """ k = (operator, *otherOps) used = self._usedOps try: return used[k] except KeyError: pass o = opCreateDelegate(self, *otherOps) # input operads may be type converted, # search if this happend, and return always same result signal try: op_instanciated = (o.origin.operator == operator and o.origin.operands[0] is self) except AttributeError: op_instanciated = False if op_instanciated: k_real = (operator, *o.origin.operands[1:]) real_o = used.get(k_real, None) if real_o is not None: # destroy newly created operator and result, because it is same # as ctx = self.ctx if ctx is not None: ctx.signals.remove(o) op = o.origin o.origin = None o.drivers.clear() for inp in op.operands: if isinstance(inp, RtlSignalBase): inp.endpoints.remove(op) o = real_o else: used[k_real] = o used[k] = o return o def __invert__(self): return self.naryOp(AllOps.NOT, tv(self).__invert__) def _onRisingEdge(self, now=None): return self.naryOp(AllOps.RISING_EDGE, tv(self)._onRisingEdge, now) def _onFallingEdge(self, now=None): return self.naryOp(AllOps.FALLING_EDGE, tv(self)._onFallingEdge, now) def _isOn(self): return self._auto_cast(BOOL) # conversions def _convSign(self, signed): return tv(self)._convSign(self, signed) def _signed(self): return tv(self)._signed(self) def _unsigned(self): return tv(self)._unsigned(self) def _vec(self): return tv(self)._vec(self) # logic def __and__(self, other): return self.naryOp(AllOps.AND, tv(self).__and__, other) def __xor__(self, other): return self.naryOp(AllOps.XOR, tv(self).__xor__, other) def __or__(self, other): return self.naryOp(AllOps.OR, tv(self).__or__, other) # cmp def _eq(self, other): """ __eq__ is not overloaded because it will destroy hashability of object """ return self.naryOp(AllOps.EQ, tv(self)._eq, other) def __ne__(self, other): return self.naryOp(AllOps.NEQ, tv(self).__ne__, other) def __ge__(self, other): return self.naryOp(AllOps.GE, tv(self).__ge__, other) def __gt__(self, other): return self.naryOp(AllOps.GT, tv(self).__gt__, other) def __lt__(self, other): return self.naryOp(AllOps.LT, tv(self).__lt__, other) def __le__(self, other): return self.naryOp(AllOps.LE, tv(self).__le__, other) # arithmetic def __add__(self, other): return self.naryOp(AllOps.ADD, tv(self).__add__, other) def __sub__(self, other): return self.naryOp(AllOps.SUB, tv(self).__sub__, other) def __mul__(self, other): return self.naryOp(AllOps.MUL, tv(self).__mul__, other) def __floordiv__(self, divider): return self.naryOp(AllOps.DIV, tv(self).__floordiv__, divider) # selections def _downto(self, to): return self.naryOp(AllOps.DOWNTO, tv(self)._downto, to) def __getitem__(self, key): if isinstance(key, slice): key = slice_to_SLICE(key, self._dtype.bit_length()) return self.naryOp(AllOps.INDEX, tv(self).__getitem__, key) def _concat(self, *operands): return self.naryOp(AllOps.CONCAT, tv(self)._concat, *operands) def _ternary(self, ifTrue, ifFalse): return self.naryOp(AllOps.TERNARY, tv(self)._ternary, ifTrue, ifFalse) @internal def _getIndexCascade(self): """ Find out if this signal is something indexed """ try: # now I am result of the index xxx[xx] <= source # get index op d = self.singleDriver() try: op = d.operator except AttributeError: return if op == AllOps.INDEX: # get signal on which is index applied indexedOn = d.operands[0] if isinstance(indexedOn, RtlSignalBase): # [TODO] multidimensional indexing return indexedOn, [d.operands[1]] else: raise Exception( "can not drive static value %r" % indexedOn) except (MultipleDriversErr, NoDriverErr): pass def __call__(self, source) -> Assignment: """ Create assignment to this signal :attention: it is not call of function it is operator of assignment :return: list of assignments """ if isinstance(source, InterfaceBase): assert source._isAccessible source = source._sig if source is None: source = self._dtype.fromPy(None) else: source = toHVal(source, suggestedType=self._dtype) err = False try: source = source._auto_cast(self._dtype) except TypeConversionErr: err = True if err: raise TypeConversionErr( ("Can not connect %r (of type %r) to %r " "(of type %r) due type incompatibility") % (source, source._dtype, self, self._dtype)) tmp = self._getIndexCascade() if tmp: mainSig, indexCascade = tmp self = mainSig else: indexCascade = None # self = self._tryMyIndexToEndpoint() return Assignment(source, self, indexCascade) def __int__(self): if not self._const: raise TypeError("Int value of signal can be evaluated" " because it is not constant expression:", self) else: return int(self._val) def __bool__(self): if not self._const: raise TypeError("Bool value of signal can be evaluated" " because it is not constant expression:", self) else: return bool(self._val) def _isFullVld(self): return self._const and self._val._isFullVld()
from hwt.doc_markers import internal from hwt.hdl.assignment import Assignment from hwt.hdl.operatorDefs import AllOps from hwt.hdl.types.defs import BOOL from hwt.hdl.types.sliceUtils import slice_to_SLICE from hwt.hdl.types.typeCast import toHVal from hwt.synthesizer.exceptions import TypeConversionErr from hwt.synthesizer.interfaceLevel.mainBases import InterfaceBase from hwt.synthesizer.rtlLevel.mainBases import RtlSignalBase from hwt.synthesizer.rtlLevel.signalUtils.exceptions import MultipleDriversErr,\ NoDriverErr def tv(signal): """ Value class for type of signal """ return signal._dtype.getValueCls() class RtlSignalOps(): """ Definitions of operators and other operator functions for RtlSignal :ivar _usedOps: cache for expressions with this signal """ def _auto_cast(self, toT): return self._dtype.auto_cast(self, toT) def _reinterpret_cast(self, toT): return self._dtype.reinterpret_cast(self, toT) @internal def naryOp(self, operator, opCreateDelegate, *otherOps) -> RtlSignalBase: """ Try lookup operator with this parameters in _usedOps if not found create new one and soter it in _usedOps :param operator: instance of OpDefinition :param opCreateDelegate: function (*ops) to create operator :param otherOps: other operands (ops = self + otherOps) :return: RtlSignal which is result of newly created operator """ k = (operator, *otherOps) used = self._usedOps try: return used[k] except KeyError: pass o = opCreateDelegate(self, *otherOps) # input operads may be type converted, # search if this happend, and return always same result signal try: op_instanciated = (o.origin.operator == operator and o.origin.operands[0] is self) except AttributeError: op_instanciated = False if op_instanciated: k_real = (operator, *o.origin.operands[1:]) real_o = used.get(k_real, None) if real_o is not None: # destroy newly created operator and result, because it is same # as ctx = self.ctx if ctx is not None: ctx.signals.remove(o) op = o.origin o.origin = None o.drivers.clear() for inp in op.operands: if isinstance(inp, RtlSignalBase): inp.endpoints.remove(op) o = real_o else: used[k_real] = o used[k] = o return o def __invert__(self): return self.naryOp(AllOps.NOT, tv(self).__invert__) def _onRisingEdge(self, now=None): return self.naryOp(AllOps.RISING_EDGE, tv(self)._onRisingEdge, now) def _onFallingEdge(self, now=None): return self.naryOp(AllOps.FALLING_EDGE, tv(self)._onFallingEdge, now) def _isOn(self): return self._auto_cast(BOOL) # conversions def _convSign(self, signed): return tv(self)._convSign(self, signed) def _signed(self): return tv(self)._signed(self) def _unsigned(self): return tv(self)._unsigned(self) def _vec(self): return tv(self)._vec(self) # logic def __and__(self, other): return self.naryOp(AllOps.AND, tv(self).__and__, other) def __xor__(self, other): return self.naryOp(AllOps.XOR, tv(self).__xor__, other) def __or__(self, other): return self.naryOp(AllOps.OR, tv(self).__or__, other) # cmp def _eq(self, other): """ __eq__ is not overloaded because it will destroy hashability of object """ return self.naryOp(AllOps.EQ, tv(self)._eq, other) def __ne__(self, other): return self.naryOp(AllOps.NEQ, tv(self).__ne__, other) def __ge__(self, other): return self.naryOp(AllOps.GE, tv(self).__ge__, other) def __gt__(self, other): return self.naryOp(AllOps.GT, tv(self).__gt__, other) def __lt__(self, other): return self.naryOp(AllOps.LT, tv(self).__lt__, other) def __le__(self, other): return self.naryOp(AllOps.LE, tv(self).__le__, other) # arithmetic def __add__(self, other): return self.naryOp(AllOps.ADD, tv(self).__add__, other) def __sub__(self, other): return self.naryOp(AllOps.SUB, tv(self).__sub__, other) def __mul__(self, other): return self.naryOp(AllOps.MUL, tv(self).__mul__, other) def __floordiv__(self, divider): return self.naryOp(AllOps.DIV, tv(self).__floordiv__, divider) # selections def _downto(self, to): return self.naryOp(AllOps.DOWNTO, tv(self)._downto, to) def __getitem__(self, key): if isinstance(key, slice): key = slice_to_SLICE(key, self._dtype.bit_length()) return self.naryOp(AllOps.INDEX, tv(self).__getitem__, key) def _concat(self, *operands): return self.naryOp(AllOps.CONCAT, tv(self)._concat, *operands) def _ternary(self, ifTrue, ifFalse): return self.naryOp(AllOps.TERNARY, tv(self)._ternary, ifTrue, ifFalse) @internal def _getIndexCascade(self): """ Find out if this signal is something indexed """ try: # now I am result of the index xxx[xx] <= source # get index op d = self.singleDriver() try: op = d.operator except AttributeError: return if op == AllOps.INDEX: # get signal on which is index applied indexedOn = d.operands[0] if isinstance(indexedOn, RtlSignalBase): # [TODO] multidimensional indexing return indexedOn, [d.operands[1]] else: raise Exception( "can not drive static value %r" % indexedOn) except (MultipleDriversErr, NoDriverErr): pass def __call__(self, source) -> Assignment: """ Create assignment to this signal :attention: it is not call of function it is operator of assignment :return: list of assignments """ if isinstance(source, InterfaceBase): assert source._isAccessible source = source._sig if source is None: source = self._dtype.fromPy(None) else: source = toHVal(source, suggestedType=self._dtype) err = False try: source = source._auto_cast(self._dtype) except TypeConversionErr: err = True if err: raise TypeConversionErr( ("Can not connect %r (of type %r) to %r " "(of type %r) due type incompatibility") % (source, source._dtype, self, self._dtype)) tmp = self._getIndexCascade() if tmp: mainSig, indexCascade = tmp self = mainSig else: indexCascade = None # self = self._tryMyIndexToEndpoint() return Assignment(source, self, indexCascade) def __int__(self): if not self._const: raise TypeError("Int value of signal can be evaluated" " because it is not constant expression:", self) else: return int(self._val) def __bool__(self): if not self._const: raise TypeError("Bool value of signal can be evaluated" " because it is not constant expression:", self) else: return bool(self._val) def _isFullVld(self): return self._const and self._val._isFullVld()
en
0.819578
Value class for type of signal Definitions of operators and other operator functions for RtlSignal :ivar _usedOps: cache for expressions with this signal Try lookup operator with this parameters in _usedOps if not found create new one and soter it in _usedOps :param operator: instance of OpDefinition :param opCreateDelegate: function (*ops) to create operator :param otherOps: other operands (ops = self + otherOps) :return: RtlSignal which is result of newly created operator # input operads may be type converted, # search if this happend, and return always same result signal # destroy newly created operator and result, because it is same # as # conversions # logic # cmp __eq__ is not overloaded because it will destroy hashability of object # arithmetic # selections Find out if this signal is something indexed # now I am result of the index xxx[xx] <= source # get index op # get signal on which is index applied # [TODO] multidimensional indexing Create assignment to this signal :attention: it is not call of function it is operator of assignment :return: list of assignments # self = self._tryMyIndexToEndpoint()
1.802101
2
neo_utils/core.py
Pierre-Thibault/neo-utils
0
6632225
<filename>neo_utils/core.py # -*- coding: utf-8 -*- ''' Fundamental functions and class helpers to support everyday programming. @author: <NAME> (<EMAIL>re.thibault1 -at- gmail.com) @license: MIT @since: 2010-11-10 ''' __docformat__ = "epytext en" import functools class Prototype: """ An empty class to create objects as prototypes. Client are free to add properties to instances of this type. I created this class because we cannot do the same with object type. """ def count(predicate, iterable): """ Iterate over iterable, pass the value to the predicate predicate and return the number of times the predicate returns value considered True. @param predicate: Predicate function. @param iterable: Iterable containing the elements to count. @return: The number of true element. """ result = 0L for i in iterable: if predicate(i): result += 1 return result def every(predicate, iterable): """ Iterate over iterable, pass the value to the predicate predicate and return True if all the predicate returns True for all the values. @param predicate: Predicate function. @param iterable: Iterable containing the elements to test. @return: Return True if all the elements are True based on the predicate. If iterable is empty, it returns True. """ for i in iterable: if not predicate(i): return False return True def inverse_linked_list(list_to_inverse, next_node_property_name="next"): """ A linked list inversor. No new nodes are created. @param list_to_inverse: The linked list to inverse. @param next_node_property_name: The name of property pointing to the next node. @return: The head of the inversed list. """ source_current_node = list_to_inverse dest_head = None while source_current_node: old_source_head_next = getattr(source_current_node, next_node_property_name) setattr(source_current_node, next_node_property_name, dest_head) dest_head = source_current_node source_current_node = old_source_head_next return dest_head def negate(function): """ Return the opposite function of function. @param function: The function to negate. @return: The negated function. """ @functools.wraps(function) def result(*args, **keywords): return not function(*args, **keywords) return result def some(predicate, iterable): """ Iterate over iterable, pass the value to the predicate predicate and return True if the predicate returns True at least one time. @param predicate: Predicate function. @param iterable: Iterable containing the elements to test. @return: Return True if any element is True based on the predicate. If iterable is empty, it returns False. """ for i in iterable: if predicate(i): return True return False def transform(func, sequence): """ Process all the elements in sequence with func and store the result again in sequence at the same place. Sequence must be mutable. @param func: Transformation function. @param sequence: The sequence to process. """ for index, value in enumerate(sequence): sequence[index] = func(value)
<filename>neo_utils/core.py # -*- coding: utf-8 -*- ''' Fundamental functions and class helpers to support everyday programming. @author: <NAME> (<EMAIL>re.thibault1 -at- gmail.com) @license: MIT @since: 2010-11-10 ''' __docformat__ = "epytext en" import functools class Prototype: """ An empty class to create objects as prototypes. Client are free to add properties to instances of this type. I created this class because we cannot do the same with object type. """ def count(predicate, iterable): """ Iterate over iterable, pass the value to the predicate predicate and return the number of times the predicate returns value considered True. @param predicate: Predicate function. @param iterable: Iterable containing the elements to count. @return: The number of true element. """ result = 0L for i in iterable: if predicate(i): result += 1 return result def every(predicate, iterable): """ Iterate over iterable, pass the value to the predicate predicate and return True if all the predicate returns True for all the values. @param predicate: Predicate function. @param iterable: Iterable containing the elements to test. @return: Return True if all the elements are True based on the predicate. If iterable is empty, it returns True. """ for i in iterable: if not predicate(i): return False return True def inverse_linked_list(list_to_inverse, next_node_property_name="next"): """ A linked list inversor. No new nodes are created. @param list_to_inverse: The linked list to inverse. @param next_node_property_name: The name of property pointing to the next node. @return: The head of the inversed list. """ source_current_node = list_to_inverse dest_head = None while source_current_node: old_source_head_next = getattr(source_current_node, next_node_property_name) setattr(source_current_node, next_node_property_name, dest_head) dest_head = source_current_node source_current_node = old_source_head_next return dest_head def negate(function): """ Return the opposite function of function. @param function: The function to negate. @return: The negated function. """ @functools.wraps(function) def result(*args, **keywords): return not function(*args, **keywords) return result def some(predicate, iterable): """ Iterate over iterable, pass the value to the predicate predicate and return True if the predicate returns True at least one time. @param predicate: Predicate function. @param iterable: Iterable containing the elements to test. @return: Return True if any element is True based on the predicate. If iterable is empty, it returns False. """ for i in iterable: if predicate(i): return True return False def transform(func, sequence): """ Process all the elements in sequence with func and store the result again in sequence at the same place. Sequence must be mutable. @param func: Transformation function. @param sequence: The sequence to process. """ for index, value in enumerate(sequence): sequence[index] = func(value)
en
0.685306
# -*- coding: utf-8 -*- Fundamental functions and class helpers to support everyday programming. @author: <NAME> (<EMAIL>re.thibault1 -at- gmail.com) @license: MIT @since: 2010-11-10 An empty class to create objects as prototypes. Client are free to add properties to instances of this type. I created this class because we cannot do the same with object type. Iterate over iterable, pass the value to the predicate predicate and return the number of times the predicate returns value considered True. @param predicate: Predicate function. @param iterable: Iterable containing the elements to count. @return: The number of true element. Iterate over iterable, pass the value to the predicate predicate and return True if all the predicate returns True for all the values. @param predicate: Predicate function. @param iterable: Iterable containing the elements to test. @return: Return True if all the elements are True based on the predicate. If iterable is empty, it returns True. A linked list inversor. No new nodes are created. @param list_to_inverse: The linked list to inverse. @param next_node_property_name: The name of property pointing to the next node. @return: The head of the inversed list. Return the opposite function of function. @param function: The function to negate. @return: The negated function. Iterate over iterable, pass the value to the predicate predicate and return True if the predicate returns True at least one time. @param predicate: Predicate function. @param iterable: Iterable containing the elements to test. @return: Return True if any element is True based on the predicate. If iterable is empty, it returns False. Process all the elements in sequence with func and store the result again in sequence at the same place. Sequence must be mutable. @param func: Transformation function. @param sequence: The sequence to process.
3.338797
3
core/models.py
ResearchKernel/search
2
6632226
<reponame>ResearchKernel/search from uuid import uuid4 from django.db import models class BaseModelMixin(models.Model): created = models.DateTimeField(auto_now_add=True, null=True) modified = models.DateTimeField(auto_now=True) id = models.UUIDField( primary_key=True, default=uuid4, editable=False, max_length=36, unique=True ) class Meta: abstract = True
from uuid import uuid4 from django.db import models class BaseModelMixin(models.Model): created = models.DateTimeField(auto_now_add=True, null=True) modified = models.DateTimeField(auto_now=True) id = models.UUIDField( primary_key=True, default=uuid4, editable=False, max_length=36, unique=True ) class Meta: abstract = True
none
1
2.237287
2
predict.py
TerenceChen95/Retina-Unet-Pytorch
5
6632227
import torch from PIL import Image from torch.autograd import Variable import numpy as np from matplotlib import pyplot as plt from models.net2 import UNET from torchvision import transforms as transforms import torch.nn.functional as F from config import config from posprocess import rgb2gray, pad_border, recover_overlap, get_data_testing_overlap, clahe_equal, adjust_gamma from torch.utils.data import DataLoader import cv2 def prepro(img): img = cv2.imread(img) img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) img = img[9:574,:] img = clahe_equal(img) img = adjust_gamma(img) img = np.expand_dims(img, 0) img = np.expand_dims(img, 0) return img img = '/home/tianshu/unet/data/training/images/22_training.tif' state = torch.load('./saved/BEST_checkpoint.pth.tar', map_location={'cuda:1':'cuda:0'})['model'] net = UNET(1, 1) net.load_state_dict(state) device = torch.device('cuda:0') #normalize input img = prepro(img) stride_h = config['stride_h'] stride_w = config['stride_w'] patch_h = config['patch_height'] patch_w = config['patch_width'] patches_img_test, new_h, new_w = get_data_testing_overlap(img, patch_h, patch_w, stride_h, stride_w) batch_size = config['batch_size'] #batch_size = 32 test_loader = DataLoader(patches_img_test, batch_size=batch_size, shuffle=False) net = net.to(device) net.eval() outsize = patches_img_test.shape msks = np.empty((outsize)) activate = torch.nn.Sigmoid() #patches too large to be put into model all at once for i, data in enumerate(test_loader): with torch.no_grad(): data = data.to(device, dtype=torch.float32) msk = net(data) msk = activate(msk) try: msks[i*batch_size:(i+1)*batch_size] = msk.detach().data.cpu().numpy() except Exception as e: print(e) msks[i*batch_size:] = msk.detach().data.cpu().numpy() pred_img = recover_overlap(msks, new_h, new_w, stride_h, stride_w) print(pred_img.shape) pred_img = pred_img[0][0] print(np.max(pred_img), np.min(pred_img)) threshold = np.zeros((pred_img.shape)) for j in range(pred_img.shape[1]): for i in range(pred_img.shape[0]): if pred_img[i,j] > 0.5: threshold[i,j] = 1 else: threshold[i,j] = 0 out_img = Image.fromarray((threshold*255)) plt.figure() plt.imshow(out_img) plt.savefig('out.jpg')
import torch from PIL import Image from torch.autograd import Variable import numpy as np from matplotlib import pyplot as plt from models.net2 import UNET from torchvision import transforms as transforms import torch.nn.functional as F from config import config from posprocess import rgb2gray, pad_border, recover_overlap, get_data_testing_overlap, clahe_equal, adjust_gamma from torch.utils.data import DataLoader import cv2 def prepro(img): img = cv2.imread(img) img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) img = img[9:574,:] img = clahe_equal(img) img = adjust_gamma(img) img = np.expand_dims(img, 0) img = np.expand_dims(img, 0) return img img = '/home/tianshu/unet/data/training/images/22_training.tif' state = torch.load('./saved/BEST_checkpoint.pth.tar', map_location={'cuda:1':'cuda:0'})['model'] net = UNET(1, 1) net.load_state_dict(state) device = torch.device('cuda:0') #normalize input img = prepro(img) stride_h = config['stride_h'] stride_w = config['stride_w'] patch_h = config['patch_height'] patch_w = config['patch_width'] patches_img_test, new_h, new_w = get_data_testing_overlap(img, patch_h, patch_w, stride_h, stride_w) batch_size = config['batch_size'] #batch_size = 32 test_loader = DataLoader(patches_img_test, batch_size=batch_size, shuffle=False) net = net.to(device) net.eval() outsize = patches_img_test.shape msks = np.empty((outsize)) activate = torch.nn.Sigmoid() #patches too large to be put into model all at once for i, data in enumerate(test_loader): with torch.no_grad(): data = data.to(device, dtype=torch.float32) msk = net(data) msk = activate(msk) try: msks[i*batch_size:(i+1)*batch_size] = msk.detach().data.cpu().numpy() except Exception as e: print(e) msks[i*batch_size:] = msk.detach().data.cpu().numpy() pred_img = recover_overlap(msks, new_h, new_w, stride_h, stride_w) print(pred_img.shape) pred_img = pred_img[0][0] print(np.max(pred_img), np.min(pred_img)) threshold = np.zeros((pred_img.shape)) for j in range(pred_img.shape[1]): for i in range(pred_img.shape[0]): if pred_img[i,j] > 0.5: threshold[i,j] = 1 else: threshold[i,j] = 0 out_img = Image.fromarray((threshold*255)) plt.figure() plt.imshow(out_img) plt.savefig('out.jpg')
en
0.92714
#normalize input #batch_size = 32 #patches too large to be put into model all at once
2.189336
2
demo/examples/sum.summa/usage.py
YourNorth/rezak-summarizator
3
6632228
""" NOTE: Здесь описываем базовое использование модуля (без прочих настроек) """ from summa.summarizer import summarize example = """ Automatic summarization is the process of reducing a text document with a \ computer program in order to create a summary that retains the most important points \ of the original document. As the problem of information overload has grown, and as \ the quantity of data has increased, so has interest in automatic summarization. \ Technologies that can make a coherent summary take into account variables such as \ length, writing style and syntax. An example of the use of summarization technology \ is search engines such as Google. Document summarization is another. """ summarize(example) """ Automatic summarization is the process of reducing a text document with a computer program in order to create a summary that retains the most important points of the original document. """
""" NOTE: Здесь описываем базовое использование модуля (без прочих настроек) """ from summa.summarizer import summarize example = """ Automatic summarization is the process of reducing a text document with a \ computer program in order to create a summary that retains the most important points \ of the original document. As the problem of information overload has grown, and as \ the quantity of data has increased, so has interest in automatic summarization. \ Technologies that can make a coherent summary take into account variables such as \ length, writing style and syntax. An example of the use of summarization technology \ is search engines such as Google. Document summarization is another. """ summarize(example) """ Automatic summarization is the process of reducing a text document with a computer program in order to create a summary that retains the most important points of the original document. """
en
0.844707
NOTE: Здесь описываем базовое использование модуля (без прочих настроек) Automatic summarization is the process of reducing a text document with a \ computer program in order to create a summary that retains the most important points \ of the original document. As the problem of information overload has grown, and as \ the quantity of data has increased, so has interest in automatic summarization. \ Technologies that can make a coherent summary take into account variables such as \ length, writing style and syntax. An example of the use of summarization technology \ is search engines such as Google. Document summarization is another. Automatic summarization is the process of reducing a text document with a computer program in order to create a summary that retains the most important points of the original document.
3.959
4
01-presentation-example/01_simple_open.py
ryansmccoy/201911-spreadsheets-to-dataframes
28
6632229
filename = r'data\WMT_US.csv' f = open(filename, 'r') print(f) data = f.read() print(data) f.close() f = open(filename, 'r') # open file for line in f: print(line) f.close() # close file
filename = r'data\WMT_US.csv' f = open(filename, 'r') print(f) data = f.read() print(data) f.close() f = open(filename, 'r') # open file for line in f: print(line) f.close() # close file
en
0.848327
# open file # close file
3.352008
3
source/CRRMonitor/CRRMonitor.py
AugusYin/aws-crr-monitor-master-GCR
41
6632230
#!/usr/bin/python # -*- coding: utf-8 -*- ###################################################################################################################### # Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved. # # # # Licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance # # with the License. A copy of the License is located at # # # # http://www.apache.org/licenses/LICENSE-2.0 # # # # or in the 'license' file accompanying this file. This file is distributed on an 'AS IS' BASIS, WITHOUT WARRANTIES # # OR CONDITIONS OF ANY KIND, express or implied. See the License for the specific language governing permissions # # and limitations under the License. # ###################################################################################################################### from __future__ import print_function import json import boto3 from botocore.exceptions import ClientError import os from datetime import datetime, timedelta import urllib.request def getparm(parmname, defaultval): try: myval = os.environ[parmname] print('Environmental variable \'' + parmname + '\' = ' + str(myval)) if isinstance(defaultval, int): return int(myval) else: return myval except: print('Environmental variable \'' + parmname + '\' not found. Using default [' + \ str(defaultval) + ']') return defaultval # ===================================================================== # Configuration # # appname: the names of AWS resources are derived from this. It is not # recommended that you change this from the default 'CRRMonitor' appname = getparm('appname', 'CRRMonitor') # maxtask: Tune this parameter to get the most effective use of a single # instance of your lambda. It should be roughly 300,000 divided by the average # time required to process a single SQS record (160ms). Example: if it takes an # average of 500ms to process a single SQS record you would set this to # 300 / 0.5 = 600. This parameter tells the lambda when to ask for help: # If the queue depth is > maxtask it will spawn a copy of itself. maxtask = getparm('maxtask', 1800) # maxspawn: This parameter limits how many copies of itself the lambda # can spawn. This should not allow you to exceed your maximum concurrent # lambda execution limit (default 100). By default the lambda is set # to execute every minute and time out after 5. With a default maxspawn # of 25 this will allow 100 concurrent lambdas to execute. This should # allow capacity of 200 events per second at an average processing time # of 500ms per event, or 100 CRR replications per second. Scale and # request limits accordingly. maxspawn = getparm('maxspawn', 20) # How long to keep records for completed transfers purge_thresh = getparm('purge_thresh', 24) # DEBUG DEBUG = getparm('debug', 0) # VERSION_ID: The version of this solution VERSION_ID = getparm('SolutionVersion', "").strip() # ANONYMOUS_SOLUTION_ID: An anonymous identifier for this instance of the solution ANONYMOUS_SOLUTION_ID = getparm('UUID', "").strip() # SEND_ANONYMOUS_USAGE_METRIC: A flag indicating whether the solution should # report anonymous usage metrics to AWS SEND_ANONYMOUS_USAGE_METRIC = (getparm('AnonymousUsage', 'No') == 'Yes') # Make sure the VERSION_ID and ANONYMOUS_SOLUTION_ID are valid if VERSION_ID is None or VERSION_ID == "": SEND_ANONYMOUS_USAGE_METRIC = False if ANONYMOUS_SOLUTION_ID is None or ANONYMOUS_SOLUTION_ID == "": SEND_ANONYMOUS_USAGE_METRIC = False # # ddbtable and stattable: name of the DynamoDB tables. The tables are # created in the CloudFormation stack and defaults to the value of appname. # Do not change this without changing the template. ddbtable = appname stattable = ddbtable + 'Statistics' # queue: name of the SQS queue. Derived from the appname. The SQS queue # is created in the CloudFormation template. Do not change this without # changing the template queue = appname + 'Queue' # timefmt: used to format timestamps. Do not change. timefmt = '%Y-%m-%dT%H:%M:%SZ' # client: defines the api client connections to create client={ 'ddb': {'service': 'dynamodb'}, 'sqs': {'service': 'sqs'}, 'lbd': {'service': 'lambda'} } s3client = {} # will hold client handle for s3 per region initfail = {} # hash of source buckets to handle FAILED counter initialization # ===================================================================== # connect_clients # --------------- # Connect to all the clients. We will do this once per instantiation of # the Lambda function (not per execution) # ===================================================================== def connect_clients(clients_to_connect): for c in clients_to_connect: try: if 'region' in clients_to_connect[c]: clients_to_connect[c]['handle'] = boto3.client(clients_to_connect[c]['service'], region_name=clients_to_connect[c]['region']) else: clients_to_connect[c]['handle'] = boto3.client(clients_to_connect[c]['service']) except Exception as e: print(e) print('Error connecting to ' + clients_to_connect[c]['service']) raise e return clients_to_connect def message_handler(event): def log_statistics(Src, Dst, Tstamp, Size, ET, roundTo): # ------------------------------------------------------------- # Derive the statistic bucket from source/dest and time bucket # (5 minute rolling window) # statbucket = Src + ':' + Dst ts = datetime.strptime(Tstamp, timefmt) secs = (ts.replace(tzinfo=None) - ts.min).seconds rounding = (secs+roundTo/2) // roundTo * roundTo ts = ts + timedelta(0, rounding-secs, -ts.microsecond) timebucket = datetime.strftime(ts, timefmt) statbucket += ':' + timebucket # ------------------------------------------------------------- # Init a dict to use to hold our attrs for DDB stat_exp_attrs = {} # ------------------------------------------------------------- # Build the DDB UpdateExpression stat_update_exp = 'SET timebucket = :t, source_bucket = :o, dest_bucket = :r ADD objects :a, size :c, elapsed :d' # ------------------------------------------------------------- # push the first attr: s3Object stat_exp_attrs[':a'] = {'N': '1'} stat_exp_attrs[':c'] = {'N': Size} stat_exp_attrs[':d'] = {'N': ET} stat_exp_attrs[':t'] = {'S': timebucket} stat_exp_attrs[':o'] = {'S': Src} stat_exp_attrs[':r'] = {'S': Dst} # Update the DDB table try: response = client['ddb']['handle'].update_item( TableName=stattable, Key={'OriginReplicaBucket': {'S': statbucket}}, UpdateExpression=stat_update_exp, ExpressionAttributeValues=stat_exp_attrs) except Exception as e: print(e) print('Table ' + stattable + ' update failed') raise e # Initialize a counter for failed replications for the source bucket if not Src in initfail: initfail[Src] = 'foo' if Dst != 'FAILED' and initfail[Src] != timebucket: print('Initializing FAILED bucket for ' + Src + ':' + timebucket) statbucket = Src + ':FAILED:' + timebucket stat_exp_attrs = {} # ------------------------------------------------------------- # Build the DDB UpdateExpression stat_update_exp = 'SET timebucket = :t, source_bucket = :o, dest_bucket = :r ADD objects :a, size :c, elapsed :d' # ------------------------------------------------------------- # push the first attr: s3Object stat_exp_attrs[':a'] = {'N': '0'} stat_exp_attrs[':c'] = {'N': '1'} stat_exp_attrs[':d'] = {'N': '1'} stat_exp_attrs[':t'] = {'S': timebucket} stat_exp_attrs[':o'] = {'S': Src} stat_exp_attrs[':r'] = {'S': 'FAILED'} try: response = client['ddb']['handle'].update_item( TableName=stattable, Key={'OriginReplicaBucket': {'S': statbucket }}, UpdateExpression=stat_update_exp, ExpressionAttributeValues=stat_exp_attrs) initfail[Src] = timebucket except Exception as e: print(e) print('Table ' + stattable + ' update failed') raise e #print('Stats written to ' + statbucket) # So this will work with CloudWatch Events directly or via SNS, let's look # at the structure of the incoming JSON. Note that this has not been # tested with CloudWatch events directly, but should be a simple matter. # I kept the code here as it adds no overhead but is a solid flexible # example. # # A Cloudwatch Event looks like event[event json] # An SNS notification looks like event['Records'][0][event json] # print("Received raw event: " + json.dumps(event, indent=2)) # Create a reference in evdata that points to the correct element in the # event dictionary if 'detail-type' in event: evdata = event elif 'Records' in event: # An SNS notification will have another layer in the dict. Look for # EventSource = aws:sns. Otherwise generate an exception and get out. if event['Records'][0]['EventSource'] == 'aws:sns': #print('Message is ' + event['Records'][0]['Sns']['Message']) evdata = json.loads(event['Records'][0]['Sns']['Message']) #print("Message event: " + json.dumps(evdata, indent=2)) else: # Unrecognized event format: uncomment print statements to # identify the format and enhance this logic. At the end of # the day, evdata must contain the dict for the event record # of the Cloudwatch log event for the S3 update notification print('Error: unrecognized event format received') raise Exception('Unrecognized event format') elif 'MessageId' in event: evdata = json.loads(event['Message']) else: evdata = event if DEBUG > 1: print(json.dumps(evdata)) #----------------------------------------------------------------- # Quietly ignore all but PutObject # if evdata['detail']['eventName'] != 'PutObject': if DEBUG > 0: print('Ignoring ' + evdata['detail']['eventName'] + ' event') return #----------------------------------------------------------------- # # Collect the data we want for the DynamoDB table # region = evdata['region'] bucket = evdata['detail']['requestParameters']['bucketName'] key = evdata['detail']['requestParameters']['key'] # This timestamp is from the CW Event record and is most accurate now = evdata['detail']['eventTime'] # Init a dict to use to hold our attrs for DDB ddb_exp_attrs = {} # Build th e DDB UpdateExpression ddb_update_exp = 'set s3Object = :a' # push the first attr: s3Object ddb_exp_attrs[':a'] = {'S': key} # establish s3 client per region, but only once. if not region in s3client: s3client[region] = boto3.client('s3', region) # ----------------------------------------------------------------- # Do a head_object. If the object no longer exists just return. # try: response = s3client[region].head_object( Bucket=bucket, Key=key ) except ClientError as e: # { "Error": { # "Code": "403", # "Message": "Forbidden" # }, # "ResponseMetadata": { # "RequestId": "B7C8873E3C067128", # "HostId": "kYARs5PKMuah57ewyzYq6l5laO4xu9fcWFYVnEPLMHeqNSF4yLhrYIhbbUT0Tw7hp3f2PgCQO9E=", # "HTTPStatusCode": 403, # "HTTPHeaders": { # "x-amz-request-id": "B7C8873E3C067128", # "x-amz-id-2": "<KEY> # "content-type": "application/xml", # "transfer-encoding": "chunked", # "date": "Tue, 25 Sep 2018 11:58:48 GMT", # "server": "AmazonS3" # }, # "RetryAttempts": 0 # } # } if e.response['Error']['Code'] == '403': print('IGNORING: CRRMonitor does not have access to Object - ' + \ evdata['detail']['requestParameters']['bucketName'] + '/' + \ evdata['detail']['requestParameters']['key']) elif e.response['Error']['Code'] == '404': print('IGNORING: Object no longer exists - ' + \ evdata['detail']['requestParameters']['bucketName'] + '/' + \ evdata['detail']['requestParameters']['key']) else: # Need to improve this to recognize specifically a 404 print('Unhandled ClientError ' + str(e)) print(json.dumps(e.response)) #print('Removing from queue / ignoring') return except Exception as e: # Need to improve this to recognize specifically a 404 print('Unandled Exception ' + str(e)) print('Removing from queue / ignoring') return # 2) check that the x-amz-replication-status header is present # response['ResponseMetadata']['HTTPHeaders']['x-amz-replication-status'] # # Note that this function is only called when an object is written. Assume that # the object was written and the x-amz-replication-status is a final status for # this object in this bucket. So, if it is the source it can be COMPLETED, PENDING, # or FAILED. If it is the replica it can only be REPLICA. # # That in mind, the update date/time for the REPLICA will always be definitive for # the end_datetime column # # Conversely, the source object is always definitive for the start_datetime. # # Code must not assume that the events (source and dest) are processed in the correct # order. Any process consuming the DynamoDB table should do their own Elapsed Time # calculation. # # Reference the dict we want for clarity in the code headers = response['ResponseMetadata']['HTTPHeaders'] # If this object has no x-amz-replication-status header then we can leave if 'x-amz-replication-status' not in headers: # This is not a replicated object - get out if DEBUG > 0: print('Not a replicated object') return() # repstatus is a pointer to the headers (for code clarity) repstatus = headers['x-amz-replication-status'] # ----------------------------------------------------------------- # Verify that the DynamoDB table exists. Note: we could create it # but that takes so long that the lambda function may time out. # Better to create it in the CFn template and handle this as a # failure condition # try: response = client['ddb']['handle'].describe_table( TableName=ddbtable ) except Exception as e: print(e) print('Table ' + ddbtable + ' does not exist - need to create it') raise e # Update object size objsize = headers['content-length'] ddb_update_exp += ', ObjectSize = :s' ddb_exp_attrs[':s'] = {'N': objsize} ETag = {'S': headers['etag'][1:-1] + ':' + headers['x-amz-version-id'][1:-1]} # ----------------------------------------------------------------- # If the object already has a DDB record get it # ddbdata = client['ddb']['handle'].get_item( TableName=ddbtable, Key={'ETag': ETag}, ConsistentRead=True ) ddbitem = {} # reset the dict if 'Item' in ddbdata: ddbitem = ddbdata['Item'] if DEBUG > 4: print("DDB record: " + json.dumps(ddbitem, indent=2)) # # Is this a REPLICA? Use timestamp as completion time # # Note: replica only updates s3Replica, replication_status, and end_datetime. # # We do this so we don't have to handle conditional update of fields that might get # stepped on of the events are processed out of order. # if repstatus == 'REPLICA': # print('Processing a REPLICA object: ' + ETag['S']) ddb_update_exp += ', s3Replica = :d' ddb_exp_attrs[':d'] = {'S': bucket} #print('s3Replica: ' + bucket) ddb_update_exp += ', end_datetime = :e' ddb_exp_attrs[':e'] = {'S': now} # 'now' is from the event data #print('end_datetime: ' + now) # Set the ttl purge = datetime.strptime(now, timefmt) - timedelta(hours=purge_thresh) # datetime object ttl = purge.strftime('%s') ddb_update_exp += ', itemttl = :p' ddb_exp_attrs[':p'] = {'N': ttl} # If this is a replica then status is COMPLETE ddb_update_exp += ', replication_status = :b' ddb_exp_attrs[':b'] = {'S': 'COMPLETED'} #print('replication_status: COMPLETED (implied)') if 'start_datetime' in ddbitem and 'crr_rate' not in ddbitem: etime = datetime.strptime(now, timefmt) - datetime.strptime(ddbitem['start_datetime']['S'], timefmt) etimesecs = (etime.days * 24 * 60 * 60) + etime.seconds #print("Calculate elapsed time in seconds") crr_rate = int(objsize) * 8 / (etimesecs + 1) # Add 1 to prevent /0 errors ddb_update_exp += ', crr_rate = :r' ddb_exp_attrs[':r'] = {'N': str(crr_rate)} #print('crr_rate: ', crr_rate) ddb_update_exp += ', elapsed = :t' ddb_exp_attrs[':t'] = {'N': str(etimesecs)} #print('elapsed: ', etimesecs) log_statistics( ddbitem['s3Origin']['S'], bucket, ddbitem['start_datetime']['S'], objsize, str(etimesecs), 300) # ----------------------------------------------------------------- # Or is this a SOURCE? Use timestamp as replication start time # else: ddb_update_exp += ', s3Origin = :f' ddb_exp_attrs[':f'] = {'S': bucket} # If this is not a replica then do not report status. It's not important and # makes the DynamoDB update much more complicated. Just get the start time # # We also do not care what the status is. If it has a FAILED status we could # write code to send a notification, but that's outside our scope. if repstatus == 'COMPLETED' or repstatus == 'FAILED' or repstatus == 'PENDING': # print('Processing a ORIGINAL object: ' + ETag['S'] + ' status: ' + repstatus) ddb_update_exp += ', start_datetime = :g' ddb_exp_attrs[':g'] = {'S': now} # --------------------------------------------------------- # If we already got the replica event... # if 'end_datetime' in ddbitem and 'crr_rate' not in ddbitem: etime = datetime.strptime(ddbitem['end_datetime']['S'], timefmt) - datetime.strptime(now, timefmt) etimesecs = (etime.days * 24 * 60 * 60) + etime.seconds #print("Calculate elapsed time in seconds") crr_rate = int(objsize) * 8 / (etimesecs + 1) # Add 1 to prevent /0 errors ddb_update_exp += ', crr_rate = :r' ddb_exp_attrs[':r'] = {'N': str(crr_rate)} # Set the ttl purge = datetime.strptime(ddbitem['end_datetime']['S'], timefmt) - timedelta(hours=purge_thresh) # datetime object ttl = purge.strftime('%s') ddb_update_exp += ', itemttl = :p' ddb_exp_attrs[':p'] = {'N': ttl} ddb_update_exp += ', elapsed = :t' ddb_exp_attrs[':t'] = {'N': str(etimesecs)} log_statistics( bucket,ddbitem['s3Replica']['S'], ddbitem['end_datetime']['S'], objsize, str(etimesecs),300) # --------------------------------------------------------- # We did not yet get the replica event # else: if repstatus == 'FAILED': # If replication failed this is the only time we will see this object. # Update the status to FAILED ddb_update_exp += ', replication_status = :b' ddb_exp_attrs[':b'] = {'S': 'FAILED'} log_statistics( bucket, 'FAILED', now, '0', '1', 300) else: print('Unknown Replication Status: ' + repstatus) raise Exception('Unknown Replication Status') # Create a record in the DDB table try: response = client['ddb']['handle'].update_item( TableName=ddbtable, Key={'ETag': ETag}, UpdateExpression=ddb_update_exp, ExpressionAttributeValues=ddb_exp_attrs) except Exception as e: print(e) print('Table ' + ddbtable + ' update failed') raise e # ===================================================================== # queue_handler # ------------- # Main entry point # Count the SQS queue and manage scale. # Here's what my event looks like: # { # "account": "SAMPLE12345", # "region": "us-east-2", # "detail": {}, # "detail-type": "Scheduled Event", # "source": "aws.events", # "version": "0", # "time": "2017-02-09T13:56:03Z", # "id": "a8b4f046-06c5-4b3c-b543-90c3fdaaac14", # "resources": [ # "arn:aws:events:us-east-2:SAMPLE12345:rule/CRRMonitor-2" # ] # } # # When I spawn a child process I will change "detail-type" to "Spawned Event" # and add "child-number", where 0 is the top-level # ===================================================================== def queue_handler(event, context): cnum = 0 if 'child-number' in event: cnum = int(event['child-number']) message_floor = cnum * maxtask # { # "Attributes": {"ApproximateNumberOfMessages": "1040"}, # "ResponseMetadata": { # "RetryAttempts": 0, # "HTTPStatusCode": 200, # "RequestId": "51c43b7e-9b05-59c8-b68e-6a68f3f3b999", # "HTTPHeaders": { # "x-amzn-requestid": "51c43b7e-9b05-59c8-b68e-6a68f3f3b999", # "content-length": "360", # "server": "Server", # "connection": "keep-alive", # "date": "Thu, 09 Feb 2017 12:55:18 GMT", # "content-type": "text/xml" # } # } # } response = client['sqs']['handle'].get_queue_attributes( QueueUrl=queue_endpoint, AttributeNames=['ApproximateNumberOfMessages'] ) if response['ResponseMetadata']['HTTPStatusCode'] != 200: print('Bad status from ' + queue + ': ' + response['ResponseMetadata']['HTTPStatusCode']) return queue_sz = int(response['Attributes']['ApproximateNumberOfMessages']) queue_backlog = queue_sz - message_floor print('INFO [CNUM-' + str(cnum) + '] Queue is ' + str(queue_sz) + \ ' deep. Backlog is ' + str(queue_backlog)) # We subtracted the number of messages for which processes are already # running. If the backlog is still too deep them first spawn another child, # updating child-number + 1 if queue_backlog > maxtask: # increment child-number (or initialize to 1) in the event dict # spawn another lambda, passing the event and context dicts if cnum < maxspawn: event['child-number'] = cnum + 1 try: client['lbd']['handle'].invoke( FunctionName=context.function_name, InvocationType='Event', Payload=json.dumps(event) ) print('Spawning a child because there are ' + str(queue_sz) + ' messages in the queue. I am child ' + str(cnum) + ' with a max capacity of ' + str(maxtask) + '. Message floor is ' + str(message_floor)) print('Reproduction successful - child ' + str(cnum+1) + ' spawned') except Exception as e: print(e) print('ERROR[CNUM-' + str(cnum) + '] Failed to reproduce') raise e else: print('WARNING: maxspawn(' + str(maxspawn) + ') exceeded. Not spawning a helper.') # ----------------------------------------------------------------- # Now we get to work. Process messages from the queue until empty # or we time out. This is the secret sauce to our horizontal scale print('INFO [CNUM-' + str(cnum) + '] Priming read from SQS...') msg_ctr = 0 # keep a count of messages processed sqs_msgs = client['sqs']['handle'].receive_message( QueueUrl=queue_endpoint, AttributeNames=['All'], MaxNumberOfMessages=10, VisibilityTimeout=60 ) sqs_delete = [] while 'Messages' in sqs_msgs: print('INFO [CNUM-' + str(cnum) + '] Processing ' + str(len(sqs_msgs['Messages'])) + ' messages') for message in sqs_msgs['Messages']: rc = message_handler(json.loads(message['Body'])) # If we did not get a 0 return code let the record time out back # back into the queue if not rc: sqs_delete.append({'Id': message['MessageId'], 'ReceiptHandle': message['ReceiptHandle']}) msg_ctr += 1 # keep a count of messages processed if len(sqs_delete) > 0: # Delete the messages we just processed response = client['sqs']['handle'].delete_message_batch( QueueUrl=queue_endpoint, Entries=sqs_delete ) if len(response['Successful']) < len(sqs_delete): print('ERROR[CNUM-' + str(cnum) + ']: processed ' + str(len(sqs_msgs)) + ' messages but only deleted ' + str(len(response['Successful'])) + ' messages') sqs_delete = [] # reset the list print('INFO [CNUM-' + str(cnum) + '] Reading from SQS...') sqs_msgs = client['sqs']['handle'].receive_message( QueueUrl=queue_endpoint, AttributeNames=['All'], MaxNumberOfMessages=10, VisibilityTimeout=60 ) print('INFO [CNUM-' + str(cnum) + '] Completed - ' + str(msg_ctr) + ' messages processed') if SEND_ANONYMOUS_USAGE_METRIC and msg_ctr > 0: send_anonymous_usage_metric({ "Action": f"Num messages processed by CRRMonitor: {msg_ctr}" }) def send_anonymous_usage_metric(metric_data={}): try: if type(metric_data) is not dict or not dict: raise Exception('Invalid metric_data passed to send_anonymous_usage_metric') metric_endpoint = 'https://metrics.awssolutionsbuilder.com/generic' metric_payload = { "Solution": "SO0022", "UUID": ANONYMOUS_SOLUTION_ID, "Version": VERSION_ID, "Timestamp": str(datetime.utcnow()), "Data": metric_data } data = bytes(json.dumps(metric_payload), 'utf-8') headers = { "Content-Type": "application/json" } print(f"Sending anonymous usage metric: {str(metric_payload)}") req = urllib.request.Request(url=metric_endpoint, data=data, method='POST', headers=headers) with urllib.request.urlopen(req) as f: print(f"Anonymous usage metric send status: {f.status}") except Exception as e: # Log the exception but do not raise it again print(f'Exception while sending anonymous usage metric: {e}') ###### M A I N ###### client = connect_clients(client) try: queue_endpoint = client['sqs']['handle'].get_queue_url( QueueName=queue )['QueueUrl'] except Exception as e: print(e) print('Could not get the url for ' + queue) raise e
#!/usr/bin/python # -*- coding: utf-8 -*- ###################################################################################################################### # Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved. # # # # Licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance # # with the License. A copy of the License is located at # # # # http://www.apache.org/licenses/LICENSE-2.0 # # # # or in the 'license' file accompanying this file. This file is distributed on an 'AS IS' BASIS, WITHOUT WARRANTIES # # OR CONDITIONS OF ANY KIND, express or implied. See the License for the specific language governing permissions # # and limitations under the License. # ###################################################################################################################### from __future__ import print_function import json import boto3 from botocore.exceptions import ClientError import os from datetime import datetime, timedelta import urllib.request def getparm(parmname, defaultval): try: myval = os.environ[parmname] print('Environmental variable \'' + parmname + '\' = ' + str(myval)) if isinstance(defaultval, int): return int(myval) else: return myval except: print('Environmental variable \'' + parmname + '\' not found. Using default [' + \ str(defaultval) + ']') return defaultval # ===================================================================== # Configuration # # appname: the names of AWS resources are derived from this. It is not # recommended that you change this from the default 'CRRMonitor' appname = getparm('appname', 'CRRMonitor') # maxtask: Tune this parameter to get the most effective use of a single # instance of your lambda. It should be roughly 300,000 divided by the average # time required to process a single SQS record (160ms). Example: if it takes an # average of 500ms to process a single SQS record you would set this to # 300 / 0.5 = 600. This parameter tells the lambda when to ask for help: # If the queue depth is > maxtask it will spawn a copy of itself. maxtask = getparm('maxtask', 1800) # maxspawn: This parameter limits how many copies of itself the lambda # can spawn. This should not allow you to exceed your maximum concurrent # lambda execution limit (default 100). By default the lambda is set # to execute every minute and time out after 5. With a default maxspawn # of 25 this will allow 100 concurrent lambdas to execute. This should # allow capacity of 200 events per second at an average processing time # of 500ms per event, or 100 CRR replications per second. Scale and # request limits accordingly. maxspawn = getparm('maxspawn', 20) # How long to keep records for completed transfers purge_thresh = getparm('purge_thresh', 24) # DEBUG DEBUG = getparm('debug', 0) # VERSION_ID: The version of this solution VERSION_ID = getparm('SolutionVersion', "").strip() # ANONYMOUS_SOLUTION_ID: An anonymous identifier for this instance of the solution ANONYMOUS_SOLUTION_ID = getparm('UUID', "").strip() # SEND_ANONYMOUS_USAGE_METRIC: A flag indicating whether the solution should # report anonymous usage metrics to AWS SEND_ANONYMOUS_USAGE_METRIC = (getparm('AnonymousUsage', 'No') == 'Yes') # Make sure the VERSION_ID and ANONYMOUS_SOLUTION_ID are valid if VERSION_ID is None or VERSION_ID == "": SEND_ANONYMOUS_USAGE_METRIC = False if ANONYMOUS_SOLUTION_ID is None or ANONYMOUS_SOLUTION_ID == "": SEND_ANONYMOUS_USAGE_METRIC = False # # ddbtable and stattable: name of the DynamoDB tables. The tables are # created in the CloudFormation stack and defaults to the value of appname. # Do not change this without changing the template. ddbtable = appname stattable = ddbtable + 'Statistics' # queue: name of the SQS queue. Derived from the appname. The SQS queue # is created in the CloudFormation template. Do not change this without # changing the template queue = appname + 'Queue' # timefmt: used to format timestamps. Do not change. timefmt = '%Y-%m-%dT%H:%M:%SZ' # client: defines the api client connections to create client={ 'ddb': {'service': 'dynamodb'}, 'sqs': {'service': 'sqs'}, 'lbd': {'service': 'lambda'} } s3client = {} # will hold client handle for s3 per region initfail = {} # hash of source buckets to handle FAILED counter initialization # ===================================================================== # connect_clients # --------------- # Connect to all the clients. We will do this once per instantiation of # the Lambda function (not per execution) # ===================================================================== def connect_clients(clients_to_connect): for c in clients_to_connect: try: if 'region' in clients_to_connect[c]: clients_to_connect[c]['handle'] = boto3.client(clients_to_connect[c]['service'], region_name=clients_to_connect[c]['region']) else: clients_to_connect[c]['handle'] = boto3.client(clients_to_connect[c]['service']) except Exception as e: print(e) print('Error connecting to ' + clients_to_connect[c]['service']) raise e return clients_to_connect def message_handler(event): def log_statistics(Src, Dst, Tstamp, Size, ET, roundTo): # ------------------------------------------------------------- # Derive the statistic bucket from source/dest and time bucket # (5 minute rolling window) # statbucket = Src + ':' + Dst ts = datetime.strptime(Tstamp, timefmt) secs = (ts.replace(tzinfo=None) - ts.min).seconds rounding = (secs+roundTo/2) // roundTo * roundTo ts = ts + timedelta(0, rounding-secs, -ts.microsecond) timebucket = datetime.strftime(ts, timefmt) statbucket += ':' + timebucket # ------------------------------------------------------------- # Init a dict to use to hold our attrs for DDB stat_exp_attrs = {} # ------------------------------------------------------------- # Build the DDB UpdateExpression stat_update_exp = 'SET timebucket = :t, source_bucket = :o, dest_bucket = :r ADD objects :a, size :c, elapsed :d' # ------------------------------------------------------------- # push the first attr: s3Object stat_exp_attrs[':a'] = {'N': '1'} stat_exp_attrs[':c'] = {'N': Size} stat_exp_attrs[':d'] = {'N': ET} stat_exp_attrs[':t'] = {'S': timebucket} stat_exp_attrs[':o'] = {'S': Src} stat_exp_attrs[':r'] = {'S': Dst} # Update the DDB table try: response = client['ddb']['handle'].update_item( TableName=stattable, Key={'OriginReplicaBucket': {'S': statbucket}}, UpdateExpression=stat_update_exp, ExpressionAttributeValues=stat_exp_attrs) except Exception as e: print(e) print('Table ' + stattable + ' update failed') raise e # Initialize a counter for failed replications for the source bucket if not Src in initfail: initfail[Src] = 'foo' if Dst != 'FAILED' and initfail[Src] != timebucket: print('Initializing FAILED bucket for ' + Src + ':' + timebucket) statbucket = Src + ':FAILED:' + timebucket stat_exp_attrs = {} # ------------------------------------------------------------- # Build the DDB UpdateExpression stat_update_exp = 'SET timebucket = :t, source_bucket = :o, dest_bucket = :r ADD objects :a, size :c, elapsed :d' # ------------------------------------------------------------- # push the first attr: s3Object stat_exp_attrs[':a'] = {'N': '0'} stat_exp_attrs[':c'] = {'N': '1'} stat_exp_attrs[':d'] = {'N': '1'} stat_exp_attrs[':t'] = {'S': timebucket} stat_exp_attrs[':o'] = {'S': Src} stat_exp_attrs[':r'] = {'S': 'FAILED'} try: response = client['ddb']['handle'].update_item( TableName=stattable, Key={'OriginReplicaBucket': {'S': statbucket }}, UpdateExpression=stat_update_exp, ExpressionAttributeValues=stat_exp_attrs) initfail[Src] = timebucket except Exception as e: print(e) print('Table ' + stattable + ' update failed') raise e #print('Stats written to ' + statbucket) # So this will work with CloudWatch Events directly or via SNS, let's look # at the structure of the incoming JSON. Note that this has not been # tested with CloudWatch events directly, but should be a simple matter. # I kept the code here as it adds no overhead but is a solid flexible # example. # # A Cloudwatch Event looks like event[event json] # An SNS notification looks like event['Records'][0][event json] # print("Received raw event: " + json.dumps(event, indent=2)) # Create a reference in evdata that points to the correct element in the # event dictionary if 'detail-type' in event: evdata = event elif 'Records' in event: # An SNS notification will have another layer in the dict. Look for # EventSource = aws:sns. Otherwise generate an exception and get out. if event['Records'][0]['EventSource'] == 'aws:sns': #print('Message is ' + event['Records'][0]['Sns']['Message']) evdata = json.loads(event['Records'][0]['Sns']['Message']) #print("Message event: " + json.dumps(evdata, indent=2)) else: # Unrecognized event format: uncomment print statements to # identify the format and enhance this logic. At the end of # the day, evdata must contain the dict for the event record # of the Cloudwatch log event for the S3 update notification print('Error: unrecognized event format received') raise Exception('Unrecognized event format') elif 'MessageId' in event: evdata = json.loads(event['Message']) else: evdata = event if DEBUG > 1: print(json.dumps(evdata)) #----------------------------------------------------------------- # Quietly ignore all but PutObject # if evdata['detail']['eventName'] != 'PutObject': if DEBUG > 0: print('Ignoring ' + evdata['detail']['eventName'] + ' event') return #----------------------------------------------------------------- # # Collect the data we want for the DynamoDB table # region = evdata['region'] bucket = evdata['detail']['requestParameters']['bucketName'] key = evdata['detail']['requestParameters']['key'] # This timestamp is from the CW Event record and is most accurate now = evdata['detail']['eventTime'] # Init a dict to use to hold our attrs for DDB ddb_exp_attrs = {} # Build th e DDB UpdateExpression ddb_update_exp = 'set s3Object = :a' # push the first attr: s3Object ddb_exp_attrs[':a'] = {'S': key} # establish s3 client per region, but only once. if not region in s3client: s3client[region] = boto3.client('s3', region) # ----------------------------------------------------------------- # Do a head_object. If the object no longer exists just return. # try: response = s3client[region].head_object( Bucket=bucket, Key=key ) except ClientError as e: # { "Error": { # "Code": "403", # "Message": "Forbidden" # }, # "ResponseMetadata": { # "RequestId": "B7C8873E3C067128", # "HostId": "kYARs5PKMuah57ewyzYq6l5laO4xu9fcWFYVnEPLMHeqNSF4yLhrYIhbbUT0Tw7hp3f2PgCQO9E=", # "HTTPStatusCode": 403, # "HTTPHeaders": { # "x-amz-request-id": "B7C8873E3C067128", # "x-amz-id-2": "<KEY> # "content-type": "application/xml", # "transfer-encoding": "chunked", # "date": "Tue, 25 Sep 2018 11:58:48 GMT", # "server": "AmazonS3" # }, # "RetryAttempts": 0 # } # } if e.response['Error']['Code'] == '403': print('IGNORING: CRRMonitor does not have access to Object - ' + \ evdata['detail']['requestParameters']['bucketName'] + '/' + \ evdata['detail']['requestParameters']['key']) elif e.response['Error']['Code'] == '404': print('IGNORING: Object no longer exists - ' + \ evdata['detail']['requestParameters']['bucketName'] + '/' + \ evdata['detail']['requestParameters']['key']) else: # Need to improve this to recognize specifically a 404 print('Unhandled ClientError ' + str(e)) print(json.dumps(e.response)) #print('Removing from queue / ignoring') return except Exception as e: # Need to improve this to recognize specifically a 404 print('Unandled Exception ' + str(e)) print('Removing from queue / ignoring') return # 2) check that the x-amz-replication-status header is present # response['ResponseMetadata']['HTTPHeaders']['x-amz-replication-status'] # # Note that this function is only called when an object is written. Assume that # the object was written and the x-amz-replication-status is a final status for # this object in this bucket. So, if it is the source it can be COMPLETED, PENDING, # or FAILED. If it is the replica it can only be REPLICA. # # That in mind, the update date/time for the REPLICA will always be definitive for # the end_datetime column # # Conversely, the source object is always definitive for the start_datetime. # # Code must not assume that the events (source and dest) are processed in the correct # order. Any process consuming the DynamoDB table should do their own Elapsed Time # calculation. # # Reference the dict we want for clarity in the code headers = response['ResponseMetadata']['HTTPHeaders'] # If this object has no x-amz-replication-status header then we can leave if 'x-amz-replication-status' not in headers: # This is not a replicated object - get out if DEBUG > 0: print('Not a replicated object') return() # repstatus is a pointer to the headers (for code clarity) repstatus = headers['x-amz-replication-status'] # ----------------------------------------------------------------- # Verify that the DynamoDB table exists. Note: we could create it # but that takes so long that the lambda function may time out. # Better to create it in the CFn template and handle this as a # failure condition # try: response = client['ddb']['handle'].describe_table( TableName=ddbtable ) except Exception as e: print(e) print('Table ' + ddbtable + ' does not exist - need to create it') raise e # Update object size objsize = headers['content-length'] ddb_update_exp += ', ObjectSize = :s' ddb_exp_attrs[':s'] = {'N': objsize} ETag = {'S': headers['etag'][1:-1] + ':' + headers['x-amz-version-id'][1:-1]} # ----------------------------------------------------------------- # If the object already has a DDB record get it # ddbdata = client['ddb']['handle'].get_item( TableName=ddbtable, Key={'ETag': ETag}, ConsistentRead=True ) ddbitem = {} # reset the dict if 'Item' in ddbdata: ddbitem = ddbdata['Item'] if DEBUG > 4: print("DDB record: " + json.dumps(ddbitem, indent=2)) # # Is this a REPLICA? Use timestamp as completion time # # Note: replica only updates s3Replica, replication_status, and end_datetime. # # We do this so we don't have to handle conditional update of fields that might get # stepped on of the events are processed out of order. # if repstatus == 'REPLICA': # print('Processing a REPLICA object: ' + ETag['S']) ddb_update_exp += ', s3Replica = :d' ddb_exp_attrs[':d'] = {'S': bucket} #print('s3Replica: ' + bucket) ddb_update_exp += ', end_datetime = :e' ddb_exp_attrs[':e'] = {'S': now} # 'now' is from the event data #print('end_datetime: ' + now) # Set the ttl purge = datetime.strptime(now, timefmt) - timedelta(hours=purge_thresh) # datetime object ttl = purge.strftime('%s') ddb_update_exp += ', itemttl = :p' ddb_exp_attrs[':p'] = {'N': ttl} # If this is a replica then status is COMPLETE ddb_update_exp += ', replication_status = :b' ddb_exp_attrs[':b'] = {'S': 'COMPLETED'} #print('replication_status: COMPLETED (implied)') if 'start_datetime' in ddbitem and 'crr_rate' not in ddbitem: etime = datetime.strptime(now, timefmt) - datetime.strptime(ddbitem['start_datetime']['S'], timefmt) etimesecs = (etime.days * 24 * 60 * 60) + etime.seconds #print("Calculate elapsed time in seconds") crr_rate = int(objsize) * 8 / (etimesecs + 1) # Add 1 to prevent /0 errors ddb_update_exp += ', crr_rate = :r' ddb_exp_attrs[':r'] = {'N': str(crr_rate)} #print('crr_rate: ', crr_rate) ddb_update_exp += ', elapsed = :t' ddb_exp_attrs[':t'] = {'N': str(etimesecs)} #print('elapsed: ', etimesecs) log_statistics( ddbitem['s3Origin']['S'], bucket, ddbitem['start_datetime']['S'], objsize, str(etimesecs), 300) # ----------------------------------------------------------------- # Or is this a SOURCE? Use timestamp as replication start time # else: ddb_update_exp += ', s3Origin = :f' ddb_exp_attrs[':f'] = {'S': bucket} # If this is not a replica then do not report status. It's not important and # makes the DynamoDB update much more complicated. Just get the start time # # We also do not care what the status is. If it has a FAILED status we could # write code to send a notification, but that's outside our scope. if repstatus == 'COMPLETED' or repstatus == 'FAILED' or repstatus == 'PENDING': # print('Processing a ORIGINAL object: ' + ETag['S'] + ' status: ' + repstatus) ddb_update_exp += ', start_datetime = :g' ddb_exp_attrs[':g'] = {'S': now} # --------------------------------------------------------- # If we already got the replica event... # if 'end_datetime' in ddbitem and 'crr_rate' not in ddbitem: etime = datetime.strptime(ddbitem['end_datetime']['S'], timefmt) - datetime.strptime(now, timefmt) etimesecs = (etime.days * 24 * 60 * 60) + etime.seconds #print("Calculate elapsed time in seconds") crr_rate = int(objsize) * 8 / (etimesecs + 1) # Add 1 to prevent /0 errors ddb_update_exp += ', crr_rate = :r' ddb_exp_attrs[':r'] = {'N': str(crr_rate)} # Set the ttl purge = datetime.strptime(ddbitem['end_datetime']['S'], timefmt) - timedelta(hours=purge_thresh) # datetime object ttl = purge.strftime('%s') ddb_update_exp += ', itemttl = :p' ddb_exp_attrs[':p'] = {'N': ttl} ddb_update_exp += ', elapsed = :t' ddb_exp_attrs[':t'] = {'N': str(etimesecs)} log_statistics( bucket,ddbitem['s3Replica']['S'], ddbitem['end_datetime']['S'], objsize, str(etimesecs),300) # --------------------------------------------------------- # We did not yet get the replica event # else: if repstatus == 'FAILED': # If replication failed this is the only time we will see this object. # Update the status to FAILED ddb_update_exp += ', replication_status = :b' ddb_exp_attrs[':b'] = {'S': 'FAILED'} log_statistics( bucket, 'FAILED', now, '0', '1', 300) else: print('Unknown Replication Status: ' + repstatus) raise Exception('Unknown Replication Status') # Create a record in the DDB table try: response = client['ddb']['handle'].update_item( TableName=ddbtable, Key={'ETag': ETag}, UpdateExpression=ddb_update_exp, ExpressionAttributeValues=ddb_exp_attrs) except Exception as e: print(e) print('Table ' + ddbtable + ' update failed') raise e # ===================================================================== # queue_handler # ------------- # Main entry point # Count the SQS queue and manage scale. # Here's what my event looks like: # { # "account": "SAMPLE12345", # "region": "us-east-2", # "detail": {}, # "detail-type": "Scheduled Event", # "source": "aws.events", # "version": "0", # "time": "2017-02-09T13:56:03Z", # "id": "a8b4f046-06c5-4b3c-b543-90c3fdaaac14", # "resources": [ # "arn:aws:events:us-east-2:SAMPLE12345:rule/CRRMonitor-2" # ] # } # # When I spawn a child process I will change "detail-type" to "Spawned Event" # and add "child-number", where 0 is the top-level # ===================================================================== def queue_handler(event, context): cnum = 0 if 'child-number' in event: cnum = int(event['child-number']) message_floor = cnum * maxtask # { # "Attributes": {"ApproximateNumberOfMessages": "1040"}, # "ResponseMetadata": { # "RetryAttempts": 0, # "HTTPStatusCode": 200, # "RequestId": "51c43b7e-9b05-59c8-b68e-6a68f3f3b999", # "HTTPHeaders": { # "x-amzn-requestid": "51c43b7e-9b05-59c8-b68e-6a68f3f3b999", # "content-length": "360", # "server": "Server", # "connection": "keep-alive", # "date": "Thu, 09 Feb 2017 12:55:18 GMT", # "content-type": "text/xml" # } # } # } response = client['sqs']['handle'].get_queue_attributes( QueueUrl=queue_endpoint, AttributeNames=['ApproximateNumberOfMessages'] ) if response['ResponseMetadata']['HTTPStatusCode'] != 200: print('Bad status from ' + queue + ': ' + response['ResponseMetadata']['HTTPStatusCode']) return queue_sz = int(response['Attributes']['ApproximateNumberOfMessages']) queue_backlog = queue_sz - message_floor print('INFO [CNUM-' + str(cnum) + '] Queue is ' + str(queue_sz) + \ ' deep. Backlog is ' + str(queue_backlog)) # We subtracted the number of messages for which processes are already # running. If the backlog is still too deep them first spawn another child, # updating child-number + 1 if queue_backlog > maxtask: # increment child-number (or initialize to 1) in the event dict # spawn another lambda, passing the event and context dicts if cnum < maxspawn: event['child-number'] = cnum + 1 try: client['lbd']['handle'].invoke( FunctionName=context.function_name, InvocationType='Event', Payload=json.dumps(event) ) print('Spawning a child because there are ' + str(queue_sz) + ' messages in the queue. I am child ' + str(cnum) + ' with a max capacity of ' + str(maxtask) + '. Message floor is ' + str(message_floor)) print('Reproduction successful - child ' + str(cnum+1) + ' spawned') except Exception as e: print(e) print('ERROR[CNUM-' + str(cnum) + '] Failed to reproduce') raise e else: print('WARNING: maxspawn(' + str(maxspawn) + ') exceeded. Not spawning a helper.') # ----------------------------------------------------------------- # Now we get to work. Process messages from the queue until empty # or we time out. This is the secret sauce to our horizontal scale print('INFO [CNUM-' + str(cnum) + '] Priming read from SQS...') msg_ctr = 0 # keep a count of messages processed sqs_msgs = client['sqs']['handle'].receive_message( QueueUrl=queue_endpoint, AttributeNames=['All'], MaxNumberOfMessages=10, VisibilityTimeout=60 ) sqs_delete = [] while 'Messages' in sqs_msgs: print('INFO [CNUM-' + str(cnum) + '] Processing ' + str(len(sqs_msgs['Messages'])) + ' messages') for message in sqs_msgs['Messages']: rc = message_handler(json.loads(message['Body'])) # If we did not get a 0 return code let the record time out back # back into the queue if not rc: sqs_delete.append({'Id': message['MessageId'], 'ReceiptHandle': message['ReceiptHandle']}) msg_ctr += 1 # keep a count of messages processed if len(sqs_delete) > 0: # Delete the messages we just processed response = client['sqs']['handle'].delete_message_batch( QueueUrl=queue_endpoint, Entries=sqs_delete ) if len(response['Successful']) < len(sqs_delete): print('ERROR[CNUM-' + str(cnum) + ']: processed ' + str(len(sqs_msgs)) + ' messages but only deleted ' + str(len(response['Successful'])) + ' messages') sqs_delete = [] # reset the list print('INFO [CNUM-' + str(cnum) + '] Reading from SQS...') sqs_msgs = client['sqs']['handle'].receive_message( QueueUrl=queue_endpoint, AttributeNames=['All'], MaxNumberOfMessages=10, VisibilityTimeout=60 ) print('INFO [CNUM-' + str(cnum) + '] Completed - ' + str(msg_ctr) + ' messages processed') if SEND_ANONYMOUS_USAGE_METRIC and msg_ctr > 0: send_anonymous_usage_metric({ "Action": f"Num messages processed by CRRMonitor: {msg_ctr}" }) def send_anonymous_usage_metric(metric_data={}): try: if type(metric_data) is not dict or not dict: raise Exception('Invalid metric_data passed to send_anonymous_usage_metric') metric_endpoint = 'https://metrics.awssolutionsbuilder.com/generic' metric_payload = { "Solution": "SO0022", "UUID": ANONYMOUS_SOLUTION_ID, "Version": VERSION_ID, "Timestamp": str(datetime.utcnow()), "Data": metric_data } data = bytes(json.dumps(metric_payload), 'utf-8') headers = { "Content-Type": "application/json" } print(f"Sending anonymous usage metric: {str(metric_payload)}") req = urllib.request.Request(url=metric_endpoint, data=data, method='POST', headers=headers) with urllib.request.urlopen(req) as f: print(f"Anonymous usage metric send status: {f.status}") except Exception as e: # Log the exception but do not raise it again print(f'Exception while sending anonymous usage metric: {e}') ###### M A I N ###### client = connect_clients(client) try: queue_endpoint = client['sqs']['handle'].get_queue_url( QueueName=queue )['QueueUrl'] except Exception as e: print(e) print('Could not get the url for ' + queue) raise e
en
0.729153
#!/usr/bin/python # -*- coding: utf-8 -*- ###################################################################################################################### # Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved. # # # # Licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance # # with the License. A copy of the License is located at # # # # http://www.apache.org/licenses/LICENSE-2.0 # # # # or in the 'license' file accompanying this file. This file is distributed on an 'AS IS' BASIS, WITHOUT WARRANTIES # # OR CONDITIONS OF ANY KIND, express or implied. See the License for the specific language governing permissions # # and limitations under the License. # ###################################################################################################################### # ===================================================================== # Configuration # # appname: the names of AWS resources are derived from this. It is not # recommended that you change this from the default 'CRRMonitor' # maxtask: Tune this parameter to get the most effective use of a single # instance of your lambda. It should be roughly 300,000 divided by the average # time required to process a single SQS record (160ms). Example: if it takes an # average of 500ms to process a single SQS record you would set this to # 300 / 0.5 = 600. This parameter tells the lambda when to ask for help: # If the queue depth is > maxtask it will spawn a copy of itself. # maxspawn: This parameter limits how many copies of itself the lambda # can spawn. This should not allow you to exceed your maximum concurrent # lambda execution limit (default 100). By default the lambda is set # to execute every minute and time out after 5. With a default maxspawn # of 25 this will allow 100 concurrent lambdas to execute. This should # allow capacity of 200 events per second at an average processing time # of 500ms per event, or 100 CRR replications per second. Scale and # request limits accordingly. # How long to keep records for completed transfers # DEBUG # VERSION_ID: The version of this solution # ANONYMOUS_SOLUTION_ID: An anonymous identifier for this instance of the solution # SEND_ANONYMOUS_USAGE_METRIC: A flag indicating whether the solution should # report anonymous usage metrics to AWS # Make sure the VERSION_ID and ANONYMOUS_SOLUTION_ID are valid # # ddbtable and stattable: name of the DynamoDB tables. The tables are # created in the CloudFormation stack and defaults to the value of appname. # Do not change this without changing the template. # queue: name of the SQS queue. Derived from the appname. The SQS queue # is created in the CloudFormation template. Do not change this without # changing the template # timefmt: used to format timestamps. Do not change. # client: defines the api client connections to create # will hold client handle for s3 per region # hash of source buckets to handle FAILED counter initialization # ===================================================================== # connect_clients # --------------- # Connect to all the clients. We will do this once per instantiation of # the Lambda function (not per execution) # ===================================================================== # ------------------------------------------------------------- # Derive the statistic bucket from source/dest and time bucket # (5 minute rolling window) # # ------------------------------------------------------------- # Init a dict to use to hold our attrs for DDB # ------------------------------------------------------------- # Build the DDB UpdateExpression # ------------------------------------------------------------- # push the first attr: s3Object # Update the DDB table # Initialize a counter for failed replications for the source bucket # ------------------------------------------------------------- # Build the DDB UpdateExpression # ------------------------------------------------------------- # push the first attr: s3Object #print('Stats written to ' + statbucket) # So this will work with CloudWatch Events directly or via SNS, let's look # at the structure of the incoming JSON. Note that this has not been # tested with CloudWatch events directly, but should be a simple matter. # I kept the code here as it adds no overhead but is a solid flexible # example. # # A Cloudwatch Event looks like event[event json] # An SNS notification looks like event['Records'][0][event json] # print("Received raw event: " + json.dumps(event, indent=2)) # Create a reference in evdata that points to the correct element in the # event dictionary # An SNS notification will have another layer in the dict. Look for # EventSource = aws:sns. Otherwise generate an exception and get out. #print('Message is ' + event['Records'][0]['Sns']['Message']) #print("Message event: " + json.dumps(evdata, indent=2)) # Unrecognized event format: uncomment print statements to # identify the format and enhance this logic. At the end of # the day, evdata must contain the dict for the event record # of the Cloudwatch log event for the S3 update notification #----------------------------------------------------------------- # Quietly ignore all but PutObject # #----------------------------------------------------------------- # # Collect the data we want for the DynamoDB table # # This timestamp is from the CW Event record and is most accurate # Init a dict to use to hold our attrs for DDB # Build th e DDB UpdateExpression # push the first attr: s3Object # establish s3 client per region, but only once. # ----------------------------------------------------------------- # Do a head_object. If the object no longer exists just return. # # { "Error": { # "Code": "403", # "Message": "Forbidden" # }, # "ResponseMetadata": { # "RequestId": "B7C8873E3C067128", # "HostId": "kYARs5PKMuah57ewyzYq6l5laO4xu9fcWFYVnEPLMHeqNSF4yLhrYIhbbUT0Tw7hp3f2PgCQO9E=", # "HTTPStatusCode": 403, # "HTTPHeaders": { # "x-amz-request-id": "B7C8873E3C067128", # "x-amz-id-2": "<KEY> # "content-type": "application/xml", # "transfer-encoding": "chunked", # "date": "Tue, 25 Sep 2018 11:58:48 GMT", # "server": "AmazonS3" # }, # "RetryAttempts": 0 # } # } # Need to improve this to recognize specifically a 404 #print('Removing from queue / ignoring') # Need to improve this to recognize specifically a 404 # 2) check that the x-amz-replication-status header is present # response['ResponseMetadata']['HTTPHeaders']['x-amz-replication-status'] # # Note that this function is only called when an object is written. Assume that # the object was written and the x-amz-replication-status is a final status for # this object in this bucket. So, if it is the source it can be COMPLETED, PENDING, # or FAILED. If it is the replica it can only be REPLICA. # # That in mind, the update date/time for the REPLICA will always be definitive for # the end_datetime column # # Conversely, the source object is always definitive for the start_datetime. # # Code must not assume that the events (source and dest) are processed in the correct # order. Any process consuming the DynamoDB table should do their own Elapsed Time # calculation. # # Reference the dict we want for clarity in the code # If this object has no x-amz-replication-status header then we can leave # This is not a replicated object - get out # repstatus is a pointer to the headers (for code clarity) # ----------------------------------------------------------------- # Verify that the DynamoDB table exists. Note: we could create it # but that takes so long that the lambda function may time out. # Better to create it in the CFn template and handle this as a # failure condition # # Update object size # ----------------------------------------------------------------- # If the object already has a DDB record get it # # reset the dict # # Is this a REPLICA? Use timestamp as completion time # # Note: replica only updates s3Replica, replication_status, and end_datetime. # # We do this so we don't have to handle conditional update of fields that might get # stepped on of the events are processed out of order. # # print('Processing a REPLICA object: ' + ETag['S']) #print('s3Replica: ' + bucket) # 'now' is from the event data #print('end_datetime: ' + now) # Set the ttl # datetime object # If this is a replica then status is COMPLETE #print('replication_status: COMPLETED (implied)') #print("Calculate elapsed time in seconds") # Add 1 to prevent /0 errors #print('crr_rate: ', crr_rate) #print('elapsed: ', etimesecs) # ----------------------------------------------------------------- # Or is this a SOURCE? Use timestamp as replication start time # # If this is not a replica then do not report status. It's not important and # makes the DynamoDB update much more complicated. Just get the start time # # We also do not care what the status is. If it has a FAILED status we could # write code to send a notification, but that's outside our scope. # print('Processing a ORIGINAL object: ' + ETag['S'] + ' status: ' + repstatus) # --------------------------------------------------------- # If we already got the replica event... # #print("Calculate elapsed time in seconds") # Add 1 to prevent /0 errors # Set the ttl # datetime object # --------------------------------------------------------- # We did not yet get the replica event # # If replication failed this is the only time we will see this object. # Update the status to FAILED # Create a record in the DDB table # ===================================================================== # queue_handler # ------------- # Main entry point # Count the SQS queue and manage scale. # Here's what my event looks like: # { # "account": "SAMPLE12345", # "region": "us-east-2", # "detail": {}, # "detail-type": "Scheduled Event", # "source": "aws.events", # "version": "0", # "time": "2017-02-09T13:56:03Z", # "id": "a8b4f046-06c5-4b3c-b543-90c3fdaaac14", # "resources": [ # "arn:aws:events:us-east-2:SAMPLE12345:rule/CRRMonitor-2" # ] # } # # When I spawn a child process I will change "detail-type" to "Spawned Event" # and add "child-number", where 0 is the top-level # ===================================================================== # { # "Attributes": {"ApproximateNumberOfMessages": "1040"}, # "ResponseMetadata": { # "RetryAttempts": 0, # "HTTPStatusCode": 200, # "RequestId": "51c43b7e-9b05-59c8-b68e-6a68f3f3b999", # "HTTPHeaders": { # "x-amzn-requestid": "51c43b7e-9b05-59c8-b68e-6a68f3f3b999", # "content-length": "360", # "server": "Server", # "connection": "keep-alive", # "date": "Thu, 09 Feb 2017 12:55:18 GMT", # "content-type": "text/xml" # } # } # } # We subtracted the number of messages for which processes are already # running. If the backlog is still too deep them first spawn another child, # updating child-number + 1 # increment child-number (or initialize to 1) in the event dict # spawn another lambda, passing the event and context dicts # ----------------------------------------------------------------- # Now we get to work. Process messages from the queue until empty # or we time out. This is the secret sauce to our horizontal scale # keep a count of messages processed # If we did not get a 0 return code let the record time out back # back into the queue # keep a count of messages processed # Delete the messages we just processed # reset the list # Log the exception but do not raise it again ###### M A I N ######
2.085945
2
app/controllers/authControllers.py
nicolunardi/travela-server
0
6632231
<reponame>nicolunardi/travela-server from fastapi import HTTPException, status, Depends from email_validator import EmailNotValidError from sqlalchemy.orm import Session from app.schemas.tokens import Token from app.models.users import User as UserModel from app.schemas.users import UserCreate, UserLogin from app.dependencies.authentication import ( get_password_hash, check_valid_email, get_user_by_email, verify_password, ) from app.dependencies.JWTtokens import create_access_token from app.config.database import get_db def create_user(db: Session, user: UserCreate): # check the email address isn't already in use db_user = get_user_by_email(db, user.email) if db_user: raise HTTPException( status_code=status.HTTP_400_BAD_REQUEST, detail="Email already registered.", ) # ensure the email address is valid try: email = check_valid_email(user.email) except EmailNotValidError as e: raise HTTPException( status_code=status.HTTP_400_BAD_REQUEST, detail=str(e), ) hashed_password = get_password_hash(user.password) # create the user new_user = UserModel( email=user.email, name=user.name, hashed_password=hashed_password ) # add the user to the db db.add(new_user) db.commit() db.refresh(new_user) return new_user def register_user(db: Session, user: UserCreate): new_user = create_user(db, user) # if the user was created without problems, generate the jwt token if new_user: token = create_access_token( data={ "email": new_user.email, "name": new_user.name, "id": new_user.id, } ) return Token(access_token=token, token_type="bearer") else: raise HTTPException( status.HTTP_500_INTERNAL_SERVER_ERROR, detail="Something went wrong.", ) def login_user(form_data: UserLogin, db): # check if the user exists in the db curr_user = get_user_by_email(db, form_data.username) if not curr_user: raise HTTPException( status_code=status.HTTP_404_NOT_FOUND, detail="No user exists with that email address.", ) # check if the passwords match if not verify_password(form_data.password, curr_user.hashed_password): raise HTTPException( status_code=status.HTTP_403_FORBIDDEN, detail="Incorrect password.", ) token = create_access_token( data={ "email": curr_user.email, "name": curr_user.name, "id": curr_user.id, } ) return Token(access_token=token, token_type="bearer")
from fastapi import HTTPException, status, Depends from email_validator import EmailNotValidError from sqlalchemy.orm import Session from app.schemas.tokens import Token from app.models.users import User as UserModel from app.schemas.users import UserCreate, UserLogin from app.dependencies.authentication import ( get_password_hash, check_valid_email, get_user_by_email, verify_password, ) from app.dependencies.JWTtokens import create_access_token from app.config.database import get_db def create_user(db: Session, user: UserCreate): # check the email address isn't already in use db_user = get_user_by_email(db, user.email) if db_user: raise HTTPException( status_code=status.HTTP_400_BAD_REQUEST, detail="Email already registered.", ) # ensure the email address is valid try: email = check_valid_email(user.email) except EmailNotValidError as e: raise HTTPException( status_code=status.HTTP_400_BAD_REQUEST, detail=str(e), ) hashed_password = get_password_hash(user.password) # create the user new_user = UserModel( email=user.email, name=user.name, hashed_password=hashed_password ) # add the user to the db db.add(new_user) db.commit() db.refresh(new_user) return new_user def register_user(db: Session, user: UserCreate): new_user = create_user(db, user) # if the user was created without problems, generate the jwt token if new_user: token = create_access_token( data={ "email": new_user.email, "name": new_user.name, "id": new_user.id, } ) return Token(access_token=token, token_type="bearer") else: raise HTTPException( status.HTTP_500_INTERNAL_SERVER_ERROR, detail="Something went wrong.", ) def login_user(form_data: UserLogin, db): # check if the user exists in the db curr_user = get_user_by_email(db, form_data.username) if not curr_user: raise HTTPException( status_code=status.HTTP_404_NOT_FOUND, detail="No user exists with that email address.", ) # check if the passwords match if not verify_password(form_data.password, curr_user.hashed_password): raise HTTPException( status_code=status.HTTP_403_FORBIDDEN, detail="Incorrect password.", ) token = create_access_token( data={ "email": curr_user.email, "name": curr_user.name, "id": curr_user.id, } ) return Token(access_token=token, token_type="bearer")
en
0.883382
# check the email address isn't already in use # ensure the email address is valid # create the user # add the user to the db # if the user was created without problems, generate the jwt token # check if the user exists in the db # check if the passwords match
2.785975
3
tests/parsers/bsm.py
ir4n6/plaso
0
6632232
<filename>tests/parsers/bsm.py #!/usr/bin/python # -*- coding: utf-8 -*- """Tests for Basic Security Module (BSM) file parser.""" from __future__ import unicode_literals import unittest from plaso.formatters import bsm as _ # pylint: disable=unused-import from plaso.lib import definitions from plaso.parsers import bsm from tests import test_lib as shared_test_lib from tests.parsers import test_lib class MacOSBSMParserTest(test_lib.ParserTestCase): """Tests for Basic Security Module (BSM) file parser.""" @shared_test_lib.skipUnlessHasTestFile(['apple.bsm']) def testParse(self): """Tests the Parse function on a MacOS BSM file.""" parser = bsm.BSMParser() knowledge_base_values = { 'operating_system': definitions.OPERATING_SYSTEM_MACOS} storage_writer = self._ParseFile( ['apple.bsm'], parser, knowledge_base_values=knowledge_base_values) self.assertEqual(storage_writer.number_of_events, 54) events = list(storage_writer.GetEvents()) event = events[0] self.assertEqual(event.data_type, 'bsm:event') self.CheckTimestamp(event.timestamp, '2013-11-04 18:36:20.000381') self.assertEqual(event.event_type, 'audit crash recovery (45029)') expected_extra_tokens = { 'BSM_TOKEN_PATH': '/var/audit/20131104171720.crash_recovery', 'BSM_TOKEN_RETURN32': { 'call_status': 0, 'error': 'Success', 'token_status': 0}, 'BSM_TOKEN_TEXT': 'launchctl::Audit recovery', 'BSM_TOKEN_TRAILER': 104 } self.assertEqual(event.extra_tokens, expected_extra_tokens) expected_return_value = { 'call_status': 0, 'error': 'Success', 'token_status': 0 } self.assertEqual(event.return_value, expected_return_value) event = events[15] self.CheckTimestamp(event.timestamp, '2013-11-04 18:36:26.000171') self.assertEqual(event.event_type, 'user authentication (45023)') expected_extra_tokens = { 'BSM_TOKEN_RETURN32': { 'call_status': 5000, 'error': 'Unknown', 'token_status': 255}, 'BSM_TOKEN_SUBJECT32': { 'aid': 4294967295, 'egid': 92, 'euid': 92, 'gid': 92, 'pid': 143, 'session_id': 100004, 'terminal_ip': '0.0.0.0', 'terminal_port': 143, 'uid': 92}, 'BSM_TOKEN_TEXT': ( 'Verify password for record type Users \'moxilo\' node ' '\'/Local/Default\''), 'BSM_TOKEN_TRAILER': 140 } self.assertEqual(event.extra_tokens, expected_extra_tokens) expected_return_value = { 'call_status': 5000, 'error': 'Unknown', 'token_status': 255 } self.assertEqual(event.return_value, expected_return_value) event = events[31] self.CheckTimestamp(event.timestamp, '2013-11-04 18:36:26.000530') self.assertEqual(event.event_type, 'SecSrvr AuthEngine (45025)') expected_extra_tokens = { 'BSM_TOKEN_RETURN32': { 'call_status': 0, 'error': 'Success', 'token_status': 0}, 'BSM_TOKEN_SUBJECT32': { 'aid': 4294967295, 'egid': 0, 'euid': 0, 'gid': 0, 'pid': 67, 'session_id': 100004, 'terminal_ip': '0.0.0.0', 'terminal_port': 67, 'uid': 0}, 'BSM_TOKEN_TEXT': 'system.<PASSWORD>', 'BSM_TOKEN_TRAILER': 110 } self.assertEqual(event.extra_tokens, expected_extra_tokens) expected_return_value = { 'call_status': 0, 'error': 'Success', 'token_status': 0 } self.assertEqual(event.return_value, expected_return_value) event = events[50] self.CheckTimestamp(event.timestamp, '2013-11-04 18:37:36.000399') self.assertEqual(event.event_type, 'session end (44903)') expected_extra_tokens = { 'BSM_TOKEN_ARGUMENT32': { 'is': 12288, 'num_arg': 3, 'string': 'am_failure'}, 'BSM_TOKEN_ARGUMENT64': { 'is': 0, 'num_arg': 1, 'string': 'sflags'}, 'BSM_TOKEN_RETURN32': { 'call_status': 0, 'error': 'Success', 'token_status': 0}, 'BSM_TOKEN_SUBJECT32': { 'aid': 4294967295, 'egid': 0, 'euid': 0, 'gid': 0, 'pid': 0, 'session_id': 100015, 'terminal_ip': '0.0.0.0', 'terminal_port': 0, 'uid': 0}, 'BSM_TOKEN_TRAILER': 125 } self.assertEqual(event.extra_tokens, expected_extra_tokens) expected_return_value = { 'call_status': 0, 'error': 'Success', 'token_status': 0 } self.assertEqual(event.return_value, expected_return_value) class OpenBSMParserTest(test_lib.ParserTestCase): """Tests for Basic Security Module (BSM) file parser.""" @shared_test_lib.skipUnlessHasTestFile(['openbsm.bsm']) def testParse(self): """Tests the Parse function on a "generic" BSM file.""" parser = bsm.BSMParser() knowledge_base_values = { 'operating_system': definitions.OPERATING_SYSTEM_LINUX} storage_writer = self._ParseFile( ['openbsm.bsm'], parser, knowledge_base_values=knowledge_base_values) self.assertEqual(storage_writer.number_of_events, 50) events = list(storage_writer.GetEvents()) expected_extra_tokens = [ {'BSM_TOKEN_ARGUMENT32': { 'is': 2882400000, 'num_arg': 3, 'string': 'test_arg32_token'}, 'BSM_TOKEN_TRAILER': 50}, {'BSM_TOKEN_DATA':{ 'data': 'SomeData', 'format': 'String'}, 'BSM_TOKEN_TRAILER': 39}, {'BSM_TOKEN_FILE': { 'string': 'test', 'timestamp': '1970-01-01 20:42:45.000424'}, 'BSM_TOKEN_TRAILER': 41}, {'BSM_TOKEN_ADDR': '192.168.100.15', 'BSM_TOKEN_TRAILER': 30}, {'BSM_TOKEN_TRAILER': 46, 'IPv4_Header': '0x400000145478000040010000c0a8649bc0a86e30]'}, {'BSM_TOKEN_IPC': { 'object_id': 305419896, 'object_type': 1}, 'BSM_TOKEN_TRAILER': 31}, {'BSM_TOKEN_PORT': 20480, 'BSM_TOKEN_TRAILER': 28}, {'BSM_TOKEN_OPAQUE': 'aabb<PASSWORD>', 'BSM_TOKEN_TRAILER': 32}, {'BSM_TOKEN_PATH': '/test/this/is/a/test', 'BSM_TOKEN_TRAILER': 49}, {'BSM_TOKEN_PROCESS32': { 'aid': 305419896, 'egid': 591751049, 'euid': 19088743, 'gid': 159868227, 'pid': 321140038, 'session_id': 2542171492, 'terminal_ip': '127.0.0.1', 'terminal_port': 374945606, 'uid': 2557891634}, 'BSM_TOKEN_TRAILER': 62}, {'BSM_TOKEN_PROCESS64': { 'aid': 305419896, 'egid': 591751049, 'euid': 19088743, 'gid': 159868227, 'pid': 321140038, 'session_id': 2542171492, 'terminal_ip': '127.0.0.1', 'terminal_port': 374945606, 'uid': 2557891634}, 'BSM_TOKEN_TRAILER': 66}, {'BSM_TOKEN_RETURN32': { 'call_status': 305419896, 'error': 'Invalid argument', 'token_status': 22}, 'BSM_TOKEN_TRAILER': 31}, {'BSM_TOKEN_SEQUENCE': 305419896, 'BSM_TOKEN_TRAILER': 30}, {'BSM_TOKEN_AUT_SOCKINET32_EX':{ 'from': '127.0.0.1', 'from_port': 0, 'to': '127.0.0.1', 'to_port': 0}, 'BSM_TOKEN_TRAILER': 44}, {'BSM_TOKEN_SUBJECT32': { 'aid': 305419896, 'egid': 591751049, 'euid': 19088743, 'gid': 159868227, 'pid': 321140038, 'session_id': 2542171492, 'terminal_ip': '127.0.0.1', 'terminal_port': 374945606, 'uid': 2557891634}, 'BSM_TOKEN_TRAILER': 62}, {'BSM_TOKEN_SUBJECT32_EX': { 'aid': 305419896, 'egid': 591751049, 'euid': 19088743, 'gid': 159868227, 'pid': 321140038, 'session_id': 2542171492, 'terminal_ip': 'fe80::1', 'terminal_port': 374945606, 'uid': 2557891634}, 'BSM_TOKEN_TRAILER': 78}, {'BSM_TOKEN_TEXT': 'This is a test.', 'BSM_TOKEN_TRAILER': 44}, {'BSM_TOKEN_TRAILER': 37, 'BSM_TOKEN_ZONENAME': '<PASSWORD>'}, {'BSM_TOKEN_RETURN32': { 'call_status': 4294967295, 'error': 'Argument list too long', 'token_status': 7}, 'BSM_TOKEN_TRAILER': 31} ] for event_index in range(0, 19): event = events[event_index] expected_extra_tokens_dict = expected_extra_tokens[event_index] extra_tokens_dict = getattr(event, 'extra_tokens', {}) self.CheckDictContents(extra_tokens_dict, expected_extra_tokens_dict) if __name__ == '__main__': unittest.main()
<filename>tests/parsers/bsm.py #!/usr/bin/python # -*- coding: utf-8 -*- """Tests for Basic Security Module (BSM) file parser.""" from __future__ import unicode_literals import unittest from plaso.formatters import bsm as _ # pylint: disable=unused-import from plaso.lib import definitions from plaso.parsers import bsm from tests import test_lib as shared_test_lib from tests.parsers import test_lib class MacOSBSMParserTest(test_lib.ParserTestCase): """Tests for Basic Security Module (BSM) file parser.""" @shared_test_lib.skipUnlessHasTestFile(['apple.bsm']) def testParse(self): """Tests the Parse function on a MacOS BSM file.""" parser = bsm.BSMParser() knowledge_base_values = { 'operating_system': definitions.OPERATING_SYSTEM_MACOS} storage_writer = self._ParseFile( ['apple.bsm'], parser, knowledge_base_values=knowledge_base_values) self.assertEqual(storage_writer.number_of_events, 54) events = list(storage_writer.GetEvents()) event = events[0] self.assertEqual(event.data_type, 'bsm:event') self.CheckTimestamp(event.timestamp, '2013-11-04 18:36:20.000381') self.assertEqual(event.event_type, 'audit crash recovery (45029)') expected_extra_tokens = { 'BSM_TOKEN_PATH': '/var/audit/20131104171720.crash_recovery', 'BSM_TOKEN_RETURN32': { 'call_status': 0, 'error': 'Success', 'token_status': 0}, 'BSM_TOKEN_TEXT': 'launchctl::Audit recovery', 'BSM_TOKEN_TRAILER': 104 } self.assertEqual(event.extra_tokens, expected_extra_tokens) expected_return_value = { 'call_status': 0, 'error': 'Success', 'token_status': 0 } self.assertEqual(event.return_value, expected_return_value) event = events[15] self.CheckTimestamp(event.timestamp, '2013-11-04 18:36:26.000171') self.assertEqual(event.event_type, 'user authentication (45023)') expected_extra_tokens = { 'BSM_TOKEN_RETURN32': { 'call_status': 5000, 'error': 'Unknown', 'token_status': 255}, 'BSM_TOKEN_SUBJECT32': { 'aid': 4294967295, 'egid': 92, 'euid': 92, 'gid': 92, 'pid': 143, 'session_id': 100004, 'terminal_ip': '0.0.0.0', 'terminal_port': 143, 'uid': 92}, 'BSM_TOKEN_TEXT': ( 'Verify password for record type Users \'moxilo\' node ' '\'/Local/Default\''), 'BSM_TOKEN_TRAILER': 140 } self.assertEqual(event.extra_tokens, expected_extra_tokens) expected_return_value = { 'call_status': 5000, 'error': 'Unknown', 'token_status': 255 } self.assertEqual(event.return_value, expected_return_value) event = events[31] self.CheckTimestamp(event.timestamp, '2013-11-04 18:36:26.000530') self.assertEqual(event.event_type, 'SecSrvr AuthEngine (45025)') expected_extra_tokens = { 'BSM_TOKEN_RETURN32': { 'call_status': 0, 'error': 'Success', 'token_status': 0}, 'BSM_TOKEN_SUBJECT32': { 'aid': 4294967295, 'egid': 0, 'euid': 0, 'gid': 0, 'pid': 67, 'session_id': 100004, 'terminal_ip': '0.0.0.0', 'terminal_port': 67, 'uid': 0}, 'BSM_TOKEN_TEXT': 'system.<PASSWORD>', 'BSM_TOKEN_TRAILER': 110 } self.assertEqual(event.extra_tokens, expected_extra_tokens) expected_return_value = { 'call_status': 0, 'error': 'Success', 'token_status': 0 } self.assertEqual(event.return_value, expected_return_value) event = events[50] self.CheckTimestamp(event.timestamp, '2013-11-04 18:37:36.000399') self.assertEqual(event.event_type, 'session end (44903)') expected_extra_tokens = { 'BSM_TOKEN_ARGUMENT32': { 'is': 12288, 'num_arg': 3, 'string': 'am_failure'}, 'BSM_TOKEN_ARGUMENT64': { 'is': 0, 'num_arg': 1, 'string': 'sflags'}, 'BSM_TOKEN_RETURN32': { 'call_status': 0, 'error': 'Success', 'token_status': 0}, 'BSM_TOKEN_SUBJECT32': { 'aid': 4294967295, 'egid': 0, 'euid': 0, 'gid': 0, 'pid': 0, 'session_id': 100015, 'terminal_ip': '0.0.0.0', 'terminal_port': 0, 'uid': 0}, 'BSM_TOKEN_TRAILER': 125 } self.assertEqual(event.extra_tokens, expected_extra_tokens) expected_return_value = { 'call_status': 0, 'error': 'Success', 'token_status': 0 } self.assertEqual(event.return_value, expected_return_value) class OpenBSMParserTest(test_lib.ParserTestCase): """Tests for Basic Security Module (BSM) file parser.""" @shared_test_lib.skipUnlessHasTestFile(['openbsm.bsm']) def testParse(self): """Tests the Parse function on a "generic" BSM file.""" parser = bsm.BSMParser() knowledge_base_values = { 'operating_system': definitions.OPERATING_SYSTEM_LINUX} storage_writer = self._ParseFile( ['openbsm.bsm'], parser, knowledge_base_values=knowledge_base_values) self.assertEqual(storage_writer.number_of_events, 50) events = list(storage_writer.GetEvents()) expected_extra_tokens = [ {'BSM_TOKEN_ARGUMENT32': { 'is': 2882400000, 'num_arg': 3, 'string': 'test_arg32_token'}, 'BSM_TOKEN_TRAILER': 50}, {'BSM_TOKEN_DATA':{ 'data': 'SomeData', 'format': 'String'}, 'BSM_TOKEN_TRAILER': 39}, {'BSM_TOKEN_FILE': { 'string': 'test', 'timestamp': '1970-01-01 20:42:45.000424'}, 'BSM_TOKEN_TRAILER': 41}, {'BSM_TOKEN_ADDR': '192.168.100.15', 'BSM_TOKEN_TRAILER': 30}, {'BSM_TOKEN_TRAILER': 46, 'IPv4_Header': '0x400000145478000040010000c0a8649bc0a86e30]'}, {'BSM_TOKEN_IPC': { 'object_id': 305419896, 'object_type': 1}, 'BSM_TOKEN_TRAILER': 31}, {'BSM_TOKEN_PORT': 20480, 'BSM_TOKEN_TRAILER': 28}, {'BSM_TOKEN_OPAQUE': 'aabb<PASSWORD>', 'BSM_TOKEN_TRAILER': 32}, {'BSM_TOKEN_PATH': '/test/this/is/a/test', 'BSM_TOKEN_TRAILER': 49}, {'BSM_TOKEN_PROCESS32': { 'aid': 305419896, 'egid': 591751049, 'euid': 19088743, 'gid': 159868227, 'pid': 321140038, 'session_id': 2542171492, 'terminal_ip': '127.0.0.1', 'terminal_port': 374945606, 'uid': 2557891634}, 'BSM_TOKEN_TRAILER': 62}, {'BSM_TOKEN_PROCESS64': { 'aid': 305419896, 'egid': 591751049, 'euid': 19088743, 'gid': 159868227, 'pid': 321140038, 'session_id': 2542171492, 'terminal_ip': '127.0.0.1', 'terminal_port': 374945606, 'uid': 2557891634}, 'BSM_TOKEN_TRAILER': 66}, {'BSM_TOKEN_RETURN32': { 'call_status': 305419896, 'error': 'Invalid argument', 'token_status': 22}, 'BSM_TOKEN_TRAILER': 31}, {'BSM_TOKEN_SEQUENCE': 305419896, 'BSM_TOKEN_TRAILER': 30}, {'BSM_TOKEN_AUT_SOCKINET32_EX':{ 'from': '127.0.0.1', 'from_port': 0, 'to': '127.0.0.1', 'to_port': 0}, 'BSM_TOKEN_TRAILER': 44}, {'BSM_TOKEN_SUBJECT32': { 'aid': 305419896, 'egid': 591751049, 'euid': 19088743, 'gid': 159868227, 'pid': 321140038, 'session_id': 2542171492, 'terminal_ip': '127.0.0.1', 'terminal_port': 374945606, 'uid': 2557891634}, 'BSM_TOKEN_TRAILER': 62}, {'BSM_TOKEN_SUBJECT32_EX': { 'aid': 305419896, 'egid': 591751049, 'euid': 19088743, 'gid': 159868227, 'pid': 321140038, 'session_id': 2542171492, 'terminal_ip': 'fe80::1', 'terminal_port': 374945606, 'uid': 2557891634}, 'BSM_TOKEN_TRAILER': 78}, {'BSM_TOKEN_TEXT': 'This is a test.', 'BSM_TOKEN_TRAILER': 44}, {'BSM_TOKEN_TRAILER': 37, 'BSM_TOKEN_ZONENAME': '<PASSWORD>'}, {'BSM_TOKEN_RETURN32': { 'call_status': 4294967295, 'error': 'Argument list too long', 'token_status': 7}, 'BSM_TOKEN_TRAILER': 31} ] for event_index in range(0, 19): event = events[event_index] expected_extra_tokens_dict = expected_extra_tokens[event_index] extra_tokens_dict = getattr(event, 'extra_tokens', {}) self.CheckDictContents(extra_tokens_dict, expected_extra_tokens_dict) if __name__ == '__main__': unittest.main()
en
0.523967
#!/usr/bin/python # -*- coding: utf-8 -*- Tests for Basic Security Module (BSM) file parser. # pylint: disable=unused-import Tests for Basic Security Module (BSM) file parser. Tests the Parse function on a MacOS BSM file. Tests for Basic Security Module (BSM) file parser. Tests the Parse function on a "generic" BSM file.
2.497015
2
strategy/deribit_cross_remote_future.py
Hudie/crypto_algo_trading
20
6632233
# -*- coding: utf-8 -*- import zmq.asyncio import asyncio import json from crypto_trading.service.base import ServiceState, ServiceBase, start_service # from crypto_trading.config import * DERIBIT_ACCOUNT_ID = 'maxlu' SYMBOL = 'BTC' MINIMUM_TICK_SIZE = 0.5 NEAR_FUTURE = 'BTC-25SEP20' FAR_FUTURE = 'BTC-25DEC20' LONG_GAP = [180, 225, 270, 315, 360] LONG_POSITION_SIZE_THRESHOLD = [300000 * i for i in [1, 2, 3, 4, 5]] SHORT_GAP = [-135, -180, -225, -270, -315] SHORT_POSITION_SIZE_THRESHOLD = [250000 * i for i in [1, 2, 3, 4, 5]] SIZE_PER_TRADE = 1000 # margin: [equity, initial_margin, maintenance_margin] margin = [0, 0, 0] future = None future_size = 0 perpetual = None perpetual_size = 0 class OrderState(): def __init__(self, if_placed=False, if_changing=False, if_cancelling=False, label='', order={}): self.if_placed = if_placed self.if_changing = if_changing self.if_cancelling = if_cancelling self.label = label self.order = order def reset(self): self.if_placed = False self.if_changing = False self.if_cancelling = False self.label = '' self.order = {} f_limit_order = OrderState() p_limit_order = OrderState() class Quote(): def __init__(self, bid, bidsize, ask, asksize, index_price): self.bid = bid self.bidsize = bidsize self.ask = ask self.asksize = asksize self.index_price = index_price class FutureArbitrage(ServiceBase): def __init__(self, logger_name): ServiceBase.__init__(self, logger_name) # subscribe market data self.deribitmd = self.ctx.socket(zmq.SUB) self.deribitmd.connect('tcp://localhost:9050') self.deribitmd.setsockopt_string(zmq.SUBSCRIBE, '') # request client for transaction self.deribittdreq = self.ctx.socket(zmq.REQ) self.deribittdreq.connect('tcp://localhost:9020') # subscribe transaction data self.deribittd = self.ctx.socket(zmq.SUB) self.deribittd.connect('tcp://localhost:9010') self.deribittd.setsockopt_string(zmq.SUBSCRIBE, '') # async queue to sequentially combine market data and tx data self.msg = asyncio.Queue() # find gap between perpetual and current season future, and make transaction when conditions are satisfied async def find_quotes_gap(self): try: global future, future_size, f_limit_order, perpetual, perpetual_size, p_limit_order, margin if min(future.bid - perpetual.bid, future.ask - perpetual.ask) >= LONG_GAP[0]: pos_idx = sum([1 if perpetual_size >= i else 0 for i in LONG_POSITION_SIZE_THRESHOLD]) pos_idx = min(pos_idx, len(LONG_POSITION_SIZE_THRESHOLD) - 1) if all((min(future.bid - perpetual.bid, future.ask - perpetual.ask) >= LONG_GAP[pos_idx], perpetual_size < LONG_POSITION_SIZE_THRESHOLD[pos_idx])): if not f_limit_order.if_placed: await self.deribittdreq.send_string(json.dumps({ 'accountid': DERIBIT_ACCOUNT_ID, 'method': 'sell', 'params': {'instrument_name': FAR_FUTURE, 'amount': min(SIZE_PER_TRADE, perpetual.asksize, abs(future_size) if abs(future_size) > 0 else SIZE_PER_TRADE), 'type': 'limit', 'price': future.ask - MINIMUM_TICK_SIZE, 'post_only': True, } })) f_limit_order.label = json.loads(await self.deribittdreq.recv_string())['internalid'] f_limit_order.if_placed = True else: if f_limit_order.order: if not f_limit_order.order['order_state'] in ('filled', 'cancelled'): if future.ask < f_limit_order.order['price'] and not f_limit_order.if_changing: self.logger.info('**** change price to: {}, future sell limit order ****'.format(future.ask - MINIMUM_TICK_SIZE)) await self.deribittdreq.send_string(json.dumps({ 'accountid': DERIBIT_ACCOUNT_ID, 'method': 'edit', 'params': {'order_id': f_limit_order.order['order_id'], 'amount': min(SIZE_PER_TRADE, perpetual.asksize, abs(future_size) if abs(future_size) > 0 else SIZE_PER_TRADE), 'price': future.ask - MINIMUM_TICK_SIZE, 'post_only': True, } })) await self.deribittdreq.recv_string() f_limit_order.if_changing = True else: f_limit_order.reset() if not p_limit_order.if_placed: await self.deribittdreq.send_string(json.dumps({ 'accountid': DERIBIT_ACCOUNT_ID, 'method': 'buy', 'params': {'instrument_name': NEAR_FUTURE, 'amount': min(SIZE_PER_TRADE, future.bidsize, abs(perpetual_size) if abs(perpetual_size) > 0 else SIZE_PER_TRADE), 'type': 'limit', 'price': perpetual.bid + MINIMUM_TICK_SIZE, 'post_only': True, } })) p_limit_order.label = json.loads(await self.deribittdreq.recv_string())['internalid'] p_limit_order.if_placed = True else: if p_limit_order.order: if not p_limit_order.order['order_state'] in ('filled', 'cancelled'): if perpetual.bid > p_limit_order.order['price'] and not p_limit_order.if_changing: self.logger.info('**** change price to: {}, perpetual buy limit order ****'.format(perpetual.bid + MINIMUM_TICK_SIZE)) await self.deribittdreq.send_string(json.dumps({ 'accountid': DERIBIT_ACCOUNT_ID, 'method': 'edit', 'params': {'order_id': p_limit_order.order['order_id'], 'amount': min(SIZE_PER_TRADE, future.bidsize, abs(perpetual_size) if abs(perpetual_size) > 0 else SIZE_PER_TRADE), 'price': perpetual.bid + MINIMUM_TICK_SIZE, 'post_only': True, } })) await self.deribittdreq.recv_string() p_limit_order.if_changing = True else: p_limit_order.reset() # perpetual > future situation elif max(future.bid - perpetual.bid, future.ask - perpetual.ask) <= SHORT_GAP[0]: pos_idx = sum([1 if future_size >= i else 0 for i in SHORT_POSITION_SIZE_THRESHOLD]) pos_idx = min(pos_idx, len(SHORT_POSITION_SIZE_THRESHOLD) - 1) if all((max(future.bid - perpetual.bid, future.ask - perpetual.ask) <= SHORT_GAP[pos_idx], future_size < SHORT_POSITION_SIZE_THRESHOLD[pos_idx])): if not f_limit_order.if_placed: await self.deribittdreq.send_string(json.dumps({ 'accountid': DERIBIT_ACCOUNT_ID, 'method': 'buy', 'params': {'instrument_name': FAR_FUTURE, 'amount': min(SIZE_PER_TRADE, perpetual.bidsize, abs(future_size) if abs(future_size) > 0 else SIZE_PER_TRADE), 'type': 'limit', 'price': future.bid + MINIMUM_TICK_SIZE, 'post_only': True, } })) f_limit_order.label = json.loads(await self.deribittdreq.recv_string())['internalid'] f_limit_order.if_placed = True else: if f_limit_order.order: if not f_limit_order.order['order_state'] in ('filled', 'cancelled'): if future.bid > f_limit_order.order['price'] and not f_limit_order.if_changing: self.logger.info('**** change price to: {}, future buy limit order ****'.format(future.bid + MINIMUM_TICK_SIZE)) await self.deribittdreq.send_string(json.dumps({ 'accountid': DERIBIT_ACCOUNT_ID, 'method': 'edit', 'params': {'order_id': f_limit_order.order['order_id'], 'amount': min(SIZE_PER_TRADE, perpetual.bidsize, abs(future_size) if abs(future_size) > 0 else SIZE_PER_TRADE), 'price': future.bid + MINIMUM_TICK_SIZE, 'post_only': True, } })) await self.deribittdreq.recv_string() f_limit_order.if_changing = True else: f_limit_order.reset() if not p_limit_order.if_placed: await self.deribittdreq.send_string(json.dumps({ 'accountid': DERIBIT_ACCOUNT_ID, 'method': 'sell', 'params': {'instrument_name': NEAR_FUTURE, 'amount': min(SIZE_PER_TRADE, future.asksize, abs(perpetual_size) if abs(perpetual_size) > 0 else SIZE_PER_TRADE), 'type': 'limit', 'price': perpetual.ask - MINIMUM_TICK_SIZE, 'post_only': True, } })) p_limit_order.label = json.loads(await self.deribittdreq.recv_string())['internalid'] p_limit_order.if_placed = True else: if p_limit_order.order: if not p_limit_order.order['order_state'] in ('filled', 'cancelled'): if perpetual.ask < p_limit_order.order['price'] and not p_limit_order.if_changing: self.logger.info('**** change price to: {}, perpetual sell limit order ****'.format(perpetual.ask - MINIMUM_TICK_SIZE)) await self.deribittdreq.send_string(json.dumps({ 'accountid': DERIBIT_ACCOUNT_ID, 'method': 'edit', 'params': {'order_id': p_limit_order.order['order_id'], 'amount': min(SIZE_PER_TRADE, future.asksize, abs(perpetual_size) if abs(perpetual_size) > 0 else SIZE_PER_TRADE), 'price': perpetual.ask - MINIMUM_TICK_SIZE, 'post_only': True, } })) await self.deribittdreq.recv_string() p_limit_order.if_changing = True else: p_limit_order.reset() else: if f_limit_order.if_placed or p_limit_order.if_placed: if not f_limit_order.if_cancelling or not p_limit_order.if_cancelling: self.logger.info('**** gap disppear, cancel_all ****') await self.deribittdreq.send_string(json.dumps({ 'accountid': DERIBIT_ACCOUNT_ID, 'method': 'cancel_all', 'params': {} })) await self.deribittdreq.recv_string() f_limit_order.if_cancelling = True p_limit_order.if_cancelling = True except AttributeError: pass except Exception as e: self.logger.exception(e) async def process_msg(self): try: global future, future_size, perpetual, perpetual_size, margin, f_limit_order, p_limit_order while self.state == ServiceState.started: msg = await self.msg.get() if msg['type'] not in ('quote', 'user.portfolio', 'buy', 'sell', 'edit'): self.logger.info('---- td res: {}, {}'.format(msg['type'], msg['data'])) if msg.get('error', ''): await self.deribittdreq.send_string(json.dumps({ 'accountid': DERIBIT_ACCOUNT_ID, 'method': 'cancel_all', 'params': {} })) await self.deribittdreq.recv_string() continue if msg['type'] == 'quote': d = msg['data'] if d['instrument_name'] == NEAR_FUTURE: perpetual = Quote(d['best_bid_price'], d['best_bid_amount'], d['best_ask_price'], d['best_ask_amount'], d['index_price']) elif d['instrument_name'] == FAR_FUTURE: future = Quote(d['best_bid_price'], d['best_bid_amount'], d['best_ask_price'], d['best_ask_amount'], d['index_price']) await self.find_quotes_gap() elif msg['type'] == 'user.changes.future': changes = msg['data'] if changes['instrument_name'] == FAR_FUTURE: if changes['trades']: filled = sum([tx['amount'] if tx['order_type'] == 'limit' else 0 for tx in changes['trades']]) if filled > 0: await self.deribittdreq.send_string(json.dumps({ 'accountid': DERIBIT_ACCOUNT_ID, 'method': 'buy' if changes['trades'][0]['direction'] == 'sell' else 'sell', 'params': {'instrument_name': NEAR_FUTURE, 'amount': filled, 'type': 'market', } })) await self.deribittdreq.recv_string() if changes['positions']: future_size = changes['positions'][0]['size'] if changes['orders']: for order in changes['orders']: if order['order_type'] == 'limit' and f_limit_order.if_placed == True and f_limit_order.label == order['label']: f_limit_order.order = order f_limit_order.if_changing = False break elif changes['instrument_name'] == NEAR_FUTURE: if changes['trades']: filled = sum([tx['amount'] if tx['order_type'] == 'limit' else 0 for tx in changes['trades']]) if filled > 0: await self.deribittdreq.send_string(json.dumps({ 'accountid': DERIBIT_ACCOUNT_ID, 'method': 'buy' if changes['trades'][0]['direction'] == 'sell' else 'sell', 'params': {'instrument_name': FAR_FUTURE, 'amount': filled, 'type': 'market', } })) await self.deribittdreq.recv_string() if changes['positions']: perpetual_size = changes['positions'][0]['size'] if changes['orders']: for order in changes['orders']: if order['order_type'] == 'limit' and p_limit_order.if_placed == True and p_limit_order.label == order['label']: p_limit_order.order = order p_limit_order.if_changing = False break elif msg['type'] == 'user.portfolio': portfolio = msg['data'] margin = [portfolio['equity'], portfolio['initial_margin'], portfolio['maintenance_margin']] elif msg['type'] == 'cancel_all': f_limit_order.reset() p_limit_order.reset() elif msg['type'] == 'positions': for d in msg['data']: if d['instrument_name'] == FAR_FUTURE: future_size = d['size'] elif d['instrument_name'] == NEAR_FUTURE: perpetual_size = d['size'] elif msg['type'] == 'account_summary': d = msg['data'] margin = [d['equity'], d['initial_margin'], d['maintenance_margin']] elif msg['type'] in ('buy', 'sell', 'edit'): pass self.msg.task_done() except Exception as e: self.logger.exception(e) await self.process_msg() async def sub_msg_md(self): try: await asyncio.sleep(1) while self.state == ServiceState.started: task = asyncio.ensure_future(self.deribitmd.recv_string()) done, pending = await asyncio.wait({task}, timeout=5) for t in pending: t.cancel() msg = json.loads(done.pop().result()) if done else {} if msg: if msg['type'] == 'quote': await self.msg.put(msg) else: self.logger.info('cant receive msg from future md') await self.deribittdreq.send_string(json.dumps({ 'accountid': DERIBIT_ACCOUNT_ID, 'method': 'cancel_all', 'params': {} })) await self.deribittdreq.recv_string() except Exception as e: self.logger.exception(e) await self.sub_msg_md() async def sub_msg_td(self): try: await self.deribittdreq.send_string(json.dumps({ 'accountid': DERIBIT_ACCOUNT_ID, 'method': 'get_positions', 'params': {'currency': SYMBOL, 'kind': 'future'} })) await self.deribittdreq.recv_string() await self.deribittdreq.send_string(json.dumps({ 'accountid': DERIBIT_ACCOUNT_ID, 'method': 'get_account_summary', 'params': {'currency': SYMBOL, } })) await self.deribittdreq.recv_string() while self.state == ServiceState.started: msg = json.loads(await self.deribittd.recv_string()) if msg['accountid'] == DERIBIT_ACCOUNT_ID: await self.msg.put(msg) except Exception as e: self.logger.exception(e) await self.sub_msg_td() async def balance_positions(self): try: global f_limit_order, p_limit_order while self.state == ServiceState.started: await asyncio.sleep(60) if not (f_limit_order.if_placed or p_limit_order.if_placed): unbalanced = future_size + perpetual_size if unbalanced != 0: await self.deribittdreq.send_string(json.dumps({ 'accountid': DERIBIT_ACCOUNT_ID, 'method': 'sell' if unbalanced > 0 else 'buy', 'params': {'instrument_name': FAR_FUTURE if abs(future_size) > abs(perpetual_size) else NEAR_FUTURE, 'amount': abs(unbalanced), 'type': 'market', } })) await self.deribittdreq.recv_string() except Exception as e: self.logger.exception(e) await self.balance_positions() async def run(self): if self.state == ServiceState.started: self.logger.error('tried to run service, but state is %s' % self.state) else: self.state = ServiceState.started asyncio.ensure_future(self.process_msg()) asyncio.ensure_future(self.sub_msg_md()) asyncio.ensure_future(self.sub_msg_td()) asyncio.ensure_future(self.balance_positions()) if __name__ == '__main__': service = FutureArbitrage('cross-remote-future') start_service(service, {})
# -*- coding: utf-8 -*- import zmq.asyncio import asyncio import json from crypto_trading.service.base import ServiceState, ServiceBase, start_service # from crypto_trading.config import * DERIBIT_ACCOUNT_ID = 'maxlu' SYMBOL = 'BTC' MINIMUM_TICK_SIZE = 0.5 NEAR_FUTURE = 'BTC-25SEP20' FAR_FUTURE = 'BTC-25DEC20' LONG_GAP = [180, 225, 270, 315, 360] LONG_POSITION_SIZE_THRESHOLD = [300000 * i for i in [1, 2, 3, 4, 5]] SHORT_GAP = [-135, -180, -225, -270, -315] SHORT_POSITION_SIZE_THRESHOLD = [250000 * i for i in [1, 2, 3, 4, 5]] SIZE_PER_TRADE = 1000 # margin: [equity, initial_margin, maintenance_margin] margin = [0, 0, 0] future = None future_size = 0 perpetual = None perpetual_size = 0 class OrderState(): def __init__(self, if_placed=False, if_changing=False, if_cancelling=False, label='', order={}): self.if_placed = if_placed self.if_changing = if_changing self.if_cancelling = if_cancelling self.label = label self.order = order def reset(self): self.if_placed = False self.if_changing = False self.if_cancelling = False self.label = '' self.order = {} f_limit_order = OrderState() p_limit_order = OrderState() class Quote(): def __init__(self, bid, bidsize, ask, asksize, index_price): self.bid = bid self.bidsize = bidsize self.ask = ask self.asksize = asksize self.index_price = index_price class FutureArbitrage(ServiceBase): def __init__(self, logger_name): ServiceBase.__init__(self, logger_name) # subscribe market data self.deribitmd = self.ctx.socket(zmq.SUB) self.deribitmd.connect('tcp://localhost:9050') self.deribitmd.setsockopt_string(zmq.SUBSCRIBE, '') # request client for transaction self.deribittdreq = self.ctx.socket(zmq.REQ) self.deribittdreq.connect('tcp://localhost:9020') # subscribe transaction data self.deribittd = self.ctx.socket(zmq.SUB) self.deribittd.connect('tcp://localhost:9010') self.deribittd.setsockopt_string(zmq.SUBSCRIBE, '') # async queue to sequentially combine market data and tx data self.msg = asyncio.Queue() # find gap between perpetual and current season future, and make transaction when conditions are satisfied async def find_quotes_gap(self): try: global future, future_size, f_limit_order, perpetual, perpetual_size, p_limit_order, margin if min(future.bid - perpetual.bid, future.ask - perpetual.ask) >= LONG_GAP[0]: pos_idx = sum([1 if perpetual_size >= i else 0 for i in LONG_POSITION_SIZE_THRESHOLD]) pos_idx = min(pos_idx, len(LONG_POSITION_SIZE_THRESHOLD) - 1) if all((min(future.bid - perpetual.bid, future.ask - perpetual.ask) >= LONG_GAP[pos_idx], perpetual_size < LONG_POSITION_SIZE_THRESHOLD[pos_idx])): if not f_limit_order.if_placed: await self.deribittdreq.send_string(json.dumps({ 'accountid': DERIBIT_ACCOUNT_ID, 'method': 'sell', 'params': {'instrument_name': FAR_FUTURE, 'amount': min(SIZE_PER_TRADE, perpetual.asksize, abs(future_size) if abs(future_size) > 0 else SIZE_PER_TRADE), 'type': 'limit', 'price': future.ask - MINIMUM_TICK_SIZE, 'post_only': True, } })) f_limit_order.label = json.loads(await self.deribittdreq.recv_string())['internalid'] f_limit_order.if_placed = True else: if f_limit_order.order: if not f_limit_order.order['order_state'] in ('filled', 'cancelled'): if future.ask < f_limit_order.order['price'] and not f_limit_order.if_changing: self.logger.info('**** change price to: {}, future sell limit order ****'.format(future.ask - MINIMUM_TICK_SIZE)) await self.deribittdreq.send_string(json.dumps({ 'accountid': DERIBIT_ACCOUNT_ID, 'method': 'edit', 'params': {'order_id': f_limit_order.order['order_id'], 'amount': min(SIZE_PER_TRADE, perpetual.asksize, abs(future_size) if abs(future_size) > 0 else SIZE_PER_TRADE), 'price': future.ask - MINIMUM_TICK_SIZE, 'post_only': True, } })) await self.deribittdreq.recv_string() f_limit_order.if_changing = True else: f_limit_order.reset() if not p_limit_order.if_placed: await self.deribittdreq.send_string(json.dumps({ 'accountid': DERIBIT_ACCOUNT_ID, 'method': 'buy', 'params': {'instrument_name': NEAR_FUTURE, 'amount': min(SIZE_PER_TRADE, future.bidsize, abs(perpetual_size) if abs(perpetual_size) > 0 else SIZE_PER_TRADE), 'type': 'limit', 'price': perpetual.bid + MINIMUM_TICK_SIZE, 'post_only': True, } })) p_limit_order.label = json.loads(await self.deribittdreq.recv_string())['internalid'] p_limit_order.if_placed = True else: if p_limit_order.order: if not p_limit_order.order['order_state'] in ('filled', 'cancelled'): if perpetual.bid > p_limit_order.order['price'] and not p_limit_order.if_changing: self.logger.info('**** change price to: {}, perpetual buy limit order ****'.format(perpetual.bid + MINIMUM_TICK_SIZE)) await self.deribittdreq.send_string(json.dumps({ 'accountid': DERIBIT_ACCOUNT_ID, 'method': 'edit', 'params': {'order_id': p_limit_order.order['order_id'], 'amount': min(SIZE_PER_TRADE, future.bidsize, abs(perpetual_size) if abs(perpetual_size) > 0 else SIZE_PER_TRADE), 'price': perpetual.bid + MINIMUM_TICK_SIZE, 'post_only': True, } })) await self.deribittdreq.recv_string() p_limit_order.if_changing = True else: p_limit_order.reset() # perpetual > future situation elif max(future.bid - perpetual.bid, future.ask - perpetual.ask) <= SHORT_GAP[0]: pos_idx = sum([1 if future_size >= i else 0 for i in SHORT_POSITION_SIZE_THRESHOLD]) pos_idx = min(pos_idx, len(SHORT_POSITION_SIZE_THRESHOLD) - 1) if all((max(future.bid - perpetual.bid, future.ask - perpetual.ask) <= SHORT_GAP[pos_idx], future_size < SHORT_POSITION_SIZE_THRESHOLD[pos_idx])): if not f_limit_order.if_placed: await self.deribittdreq.send_string(json.dumps({ 'accountid': DERIBIT_ACCOUNT_ID, 'method': 'buy', 'params': {'instrument_name': FAR_FUTURE, 'amount': min(SIZE_PER_TRADE, perpetual.bidsize, abs(future_size) if abs(future_size) > 0 else SIZE_PER_TRADE), 'type': 'limit', 'price': future.bid + MINIMUM_TICK_SIZE, 'post_only': True, } })) f_limit_order.label = json.loads(await self.deribittdreq.recv_string())['internalid'] f_limit_order.if_placed = True else: if f_limit_order.order: if not f_limit_order.order['order_state'] in ('filled', 'cancelled'): if future.bid > f_limit_order.order['price'] and not f_limit_order.if_changing: self.logger.info('**** change price to: {}, future buy limit order ****'.format(future.bid + MINIMUM_TICK_SIZE)) await self.deribittdreq.send_string(json.dumps({ 'accountid': DERIBIT_ACCOUNT_ID, 'method': 'edit', 'params': {'order_id': f_limit_order.order['order_id'], 'amount': min(SIZE_PER_TRADE, perpetual.bidsize, abs(future_size) if abs(future_size) > 0 else SIZE_PER_TRADE), 'price': future.bid + MINIMUM_TICK_SIZE, 'post_only': True, } })) await self.deribittdreq.recv_string() f_limit_order.if_changing = True else: f_limit_order.reset() if not p_limit_order.if_placed: await self.deribittdreq.send_string(json.dumps({ 'accountid': DERIBIT_ACCOUNT_ID, 'method': 'sell', 'params': {'instrument_name': NEAR_FUTURE, 'amount': min(SIZE_PER_TRADE, future.asksize, abs(perpetual_size) if abs(perpetual_size) > 0 else SIZE_PER_TRADE), 'type': 'limit', 'price': perpetual.ask - MINIMUM_TICK_SIZE, 'post_only': True, } })) p_limit_order.label = json.loads(await self.deribittdreq.recv_string())['internalid'] p_limit_order.if_placed = True else: if p_limit_order.order: if not p_limit_order.order['order_state'] in ('filled', 'cancelled'): if perpetual.ask < p_limit_order.order['price'] and not p_limit_order.if_changing: self.logger.info('**** change price to: {}, perpetual sell limit order ****'.format(perpetual.ask - MINIMUM_TICK_SIZE)) await self.deribittdreq.send_string(json.dumps({ 'accountid': DERIBIT_ACCOUNT_ID, 'method': 'edit', 'params': {'order_id': p_limit_order.order['order_id'], 'amount': min(SIZE_PER_TRADE, future.asksize, abs(perpetual_size) if abs(perpetual_size) > 0 else SIZE_PER_TRADE), 'price': perpetual.ask - MINIMUM_TICK_SIZE, 'post_only': True, } })) await self.deribittdreq.recv_string() p_limit_order.if_changing = True else: p_limit_order.reset() else: if f_limit_order.if_placed or p_limit_order.if_placed: if not f_limit_order.if_cancelling or not p_limit_order.if_cancelling: self.logger.info('**** gap disppear, cancel_all ****') await self.deribittdreq.send_string(json.dumps({ 'accountid': DERIBIT_ACCOUNT_ID, 'method': 'cancel_all', 'params': {} })) await self.deribittdreq.recv_string() f_limit_order.if_cancelling = True p_limit_order.if_cancelling = True except AttributeError: pass except Exception as e: self.logger.exception(e) async def process_msg(self): try: global future, future_size, perpetual, perpetual_size, margin, f_limit_order, p_limit_order while self.state == ServiceState.started: msg = await self.msg.get() if msg['type'] not in ('quote', 'user.portfolio', 'buy', 'sell', 'edit'): self.logger.info('---- td res: {}, {}'.format(msg['type'], msg['data'])) if msg.get('error', ''): await self.deribittdreq.send_string(json.dumps({ 'accountid': DERIBIT_ACCOUNT_ID, 'method': 'cancel_all', 'params': {} })) await self.deribittdreq.recv_string() continue if msg['type'] == 'quote': d = msg['data'] if d['instrument_name'] == NEAR_FUTURE: perpetual = Quote(d['best_bid_price'], d['best_bid_amount'], d['best_ask_price'], d['best_ask_amount'], d['index_price']) elif d['instrument_name'] == FAR_FUTURE: future = Quote(d['best_bid_price'], d['best_bid_amount'], d['best_ask_price'], d['best_ask_amount'], d['index_price']) await self.find_quotes_gap() elif msg['type'] == 'user.changes.future': changes = msg['data'] if changes['instrument_name'] == FAR_FUTURE: if changes['trades']: filled = sum([tx['amount'] if tx['order_type'] == 'limit' else 0 for tx in changes['trades']]) if filled > 0: await self.deribittdreq.send_string(json.dumps({ 'accountid': DERIBIT_ACCOUNT_ID, 'method': 'buy' if changes['trades'][0]['direction'] == 'sell' else 'sell', 'params': {'instrument_name': NEAR_FUTURE, 'amount': filled, 'type': 'market', } })) await self.deribittdreq.recv_string() if changes['positions']: future_size = changes['positions'][0]['size'] if changes['orders']: for order in changes['orders']: if order['order_type'] == 'limit' and f_limit_order.if_placed == True and f_limit_order.label == order['label']: f_limit_order.order = order f_limit_order.if_changing = False break elif changes['instrument_name'] == NEAR_FUTURE: if changes['trades']: filled = sum([tx['amount'] if tx['order_type'] == 'limit' else 0 for tx in changes['trades']]) if filled > 0: await self.deribittdreq.send_string(json.dumps({ 'accountid': DERIBIT_ACCOUNT_ID, 'method': 'buy' if changes['trades'][0]['direction'] == 'sell' else 'sell', 'params': {'instrument_name': FAR_FUTURE, 'amount': filled, 'type': 'market', } })) await self.deribittdreq.recv_string() if changes['positions']: perpetual_size = changes['positions'][0]['size'] if changes['orders']: for order in changes['orders']: if order['order_type'] == 'limit' and p_limit_order.if_placed == True and p_limit_order.label == order['label']: p_limit_order.order = order p_limit_order.if_changing = False break elif msg['type'] == 'user.portfolio': portfolio = msg['data'] margin = [portfolio['equity'], portfolio['initial_margin'], portfolio['maintenance_margin']] elif msg['type'] == 'cancel_all': f_limit_order.reset() p_limit_order.reset() elif msg['type'] == 'positions': for d in msg['data']: if d['instrument_name'] == FAR_FUTURE: future_size = d['size'] elif d['instrument_name'] == NEAR_FUTURE: perpetual_size = d['size'] elif msg['type'] == 'account_summary': d = msg['data'] margin = [d['equity'], d['initial_margin'], d['maintenance_margin']] elif msg['type'] in ('buy', 'sell', 'edit'): pass self.msg.task_done() except Exception as e: self.logger.exception(e) await self.process_msg() async def sub_msg_md(self): try: await asyncio.sleep(1) while self.state == ServiceState.started: task = asyncio.ensure_future(self.deribitmd.recv_string()) done, pending = await asyncio.wait({task}, timeout=5) for t in pending: t.cancel() msg = json.loads(done.pop().result()) if done else {} if msg: if msg['type'] == 'quote': await self.msg.put(msg) else: self.logger.info('cant receive msg from future md') await self.deribittdreq.send_string(json.dumps({ 'accountid': DERIBIT_ACCOUNT_ID, 'method': 'cancel_all', 'params': {} })) await self.deribittdreq.recv_string() except Exception as e: self.logger.exception(e) await self.sub_msg_md() async def sub_msg_td(self): try: await self.deribittdreq.send_string(json.dumps({ 'accountid': DERIBIT_ACCOUNT_ID, 'method': 'get_positions', 'params': {'currency': SYMBOL, 'kind': 'future'} })) await self.deribittdreq.recv_string() await self.deribittdreq.send_string(json.dumps({ 'accountid': DERIBIT_ACCOUNT_ID, 'method': 'get_account_summary', 'params': {'currency': SYMBOL, } })) await self.deribittdreq.recv_string() while self.state == ServiceState.started: msg = json.loads(await self.deribittd.recv_string()) if msg['accountid'] == DERIBIT_ACCOUNT_ID: await self.msg.put(msg) except Exception as e: self.logger.exception(e) await self.sub_msg_td() async def balance_positions(self): try: global f_limit_order, p_limit_order while self.state == ServiceState.started: await asyncio.sleep(60) if not (f_limit_order.if_placed or p_limit_order.if_placed): unbalanced = future_size + perpetual_size if unbalanced != 0: await self.deribittdreq.send_string(json.dumps({ 'accountid': DERIBIT_ACCOUNT_ID, 'method': 'sell' if unbalanced > 0 else 'buy', 'params': {'instrument_name': FAR_FUTURE if abs(future_size) > abs(perpetual_size) else NEAR_FUTURE, 'amount': abs(unbalanced), 'type': 'market', } })) await self.deribittdreq.recv_string() except Exception as e: self.logger.exception(e) await self.balance_positions() async def run(self): if self.state == ServiceState.started: self.logger.error('tried to run service, but state is %s' % self.state) else: self.state = ServiceState.started asyncio.ensure_future(self.process_msg()) asyncio.ensure_future(self.sub_msg_md()) asyncio.ensure_future(self.sub_msg_td()) asyncio.ensure_future(self.balance_positions()) if __name__ == '__main__': service = FutureArbitrage('cross-remote-future') start_service(service, {})
en
0.816902
# -*- coding: utf-8 -*- # from crypto_trading.config import * # margin: [equity, initial_margin, maintenance_margin] # subscribe market data # request client for transaction # subscribe transaction data # async queue to sequentially combine market data and tx data # find gap between perpetual and current season future, and make transaction when conditions are satisfied # perpetual > future situation
2.196787
2
tool/comparispawn.bzl
grencez/lace
1
6632234
<reponame>grencez/lace load("@fildesh//tool:spawn.bzl", "spawn_test") def fildesh_expect_test(name, srcs, expect, data=[], args=[], size="small", **kwargs): spawn_test( name = name, data = [ expect, "@fildesh//tool:comparispawn", "@fildesh//:fildesh", ] + srcs + data, args = [ "$(location @fildesh//tool:comparispawn)", "$(location " + expect + ")", "$(location @fildesh//:fildesh)", "-x", "$(location " + srcs[0] + ")", ] + args, size = size, **kwargs, )
load("@fildesh//tool:spawn.bzl", "spawn_test") def fildesh_expect_test(name, srcs, expect, data=[], args=[], size="small", **kwargs): spawn_test( name = name, data = [ expect, "@fildesh//tool:comparispawn", "@fildesh//:fildesh", ] + srcs + data, args = [ "$(location @fildesh//tool:comparispawn)", "$(location " + expect + ")", "$(location @fildesh//:fildesh)", "-x", "$(location " + srcs[0] + ")", ] + args, size = size, **kwargs, )
none
1
1.863409
2
tests/utils/thread.py
gururajo/Self-Driving-Car
0
6632235
import threading import time numli=[1,2,3,4,5] def add(): global num,s1,s2 for numbur in numli: print(threading.currentThread(),"waiting for s1") s1.acquire() num=numbur print(threading.currentThread(),"got s1") #num= int(input()) num+=3 print(threading.currentThread()," num= ",num) s2.release() # time.sleep(10) def mul(bt): print("inside mul") global num,s1,s2,s3,num2 while True: # bt.join() print(threading.currentThread(),"waiting for s2") s2.acquire() print(threading.currentThread(),"got s2") print(threading.currentThread(),"waiting for s3") s3.acquire() print(threading.currentThread(),"got s3") temp=num s1.release() print(threading.currentThread(),"read num as",num) temp*=10 time.sleep(1.8) print(threading.currentThread()," num= ",temp) num2=temp s4.release() # time.sleep(10) def sub(bt): print("inside sub") global num,s3,s4,num2 # bt.join() while True: print(threading.currentThread(),"waiting for s4") s4.acquire() print(threading.currentThread(),"got s4") temp=num2 s3.release() temp/=10 print(threading.currentThread()," num= ",temp) # time.sleep(10) start_t=time.time() num2=num=0 s1=threading.Semaphore(value=1) s2=threading.Semaphore(value=0) s3=threading.Semaphore(value=1) s4=threading.Semaphore(value=0) t1=threading.Thread(target=add) t2=threading.Thread(target=mul,args=[t1]) t3=threading.Thread(target=sub,args=[t2]) t1.start() t2.start() t3.start() t1.join() t2.join() t3.join() # threading.excepthook(args=[]) end_t=time.time() print(end_t-start_t)
import threading import time numli=[1,2,3,4,5] def add(): global num,s1,s2 for numbur in numli: print(threading.currentThread(),"waiting for s1") s1.acquire() num=numbur print(threading.currentThread(),"got s1") #num= int(input()) num+=3 print(threading.currentThread()," num= ",num) s2.release() # time.sleep(10) def mul(bt): print("inside mul") global num,s1,s2,s3,num2 while True: # bt.join() print(threading.currentThread(),"waiting for s2") s2.acquire() print(threading.currentThread(),"got s2") print(threading.currentThread(),"waiting for s3") s3.acquire() print(threading.currentThread(),"got s3") temp=num s1.release() print(threading.currentThread(),"read num as",num) temp*=10 time.sleep(1.8) print(threading.currentThread()," num= ",temp) num2=temp s4.release() # time.sleep(10) def sub(bt): print("inside sub") global num,s3,s4,num2 # bt.join() while True: print(threading.currentThread(),"waiting for s4") s4.acquire() print(threading.currentThread(),"got s4") temp=num2 s3.release() temp/=10 print(threading.currentThread()," num= ",temp) # time.sleep(10) start_t=time.time() num2=num=0 s1=threading.Semaphore(value=1) s2=threading.Semaphore(value=0) s3=threading.Semaphore(value=1) s4=threading.Semaphore(value=0) t1=threading.Thread(target=add) t2=threading.Thread(target=mul,args=[t1]) t3=threading.Thread(target=sub,args=[t2]) t1.start() t2.start() t3.start() t1.join() t2.join() t3.join() # threading.excepthook(args=[]) end_t=time.time() print(end_t-start_t)
en
0.265228
#num= int(input()) # time.sleep(10) # bt.join() # time.sleep(10) # bt.join() # time.sleep(10) # threading.excepthook(args=[])
3.997319
4
199_NSFW/demo/demo_nsfw_onnx.py
IgiArdiyanto/PINTO_model_zoo
2
6632236
<filename>199_NSFW/demo/demo_nsfw_onnx.py #!/usr/bin/env python # -*- coding: utf-8 -*- import time import argparse import cv2 as cv import numpy as np import onnxruntime def get_args(): parser = argparse.ArgumentParser() parser.add_argument( "--image", type=str, default='image/sample.jpg', ) parser.add_argument( "--model", type=str, default='saved_model_nsfw/model_float32.onnx', ) parser.add_argument( "--input_size", type=str, default='224,224', ) args = parser.parse_args() return args def run_inference( onnx_session, input_size, image, ): # Pre process:Resize, RGB->BGR, Transpose, float32 cast input_image = cv.resize(image, dsize=(input_size[1], input_size[0])) input_image = cv.cvtColor(input_image, cv.COLOR_BGR2RGB) vgg_mean = [104, 117, 123] input_image = input_image - vgg_mean input_image = input_image.transpose(2, 0, 1) input_image = np.expand_dims(input_image, axis=0) input_image = input_image.astype('float32') # Inference input_name = onnx_session.get_inputs()[0].name output_name = onnx_session.get_outputs()[0].name onnx_result = onnx_session.run( [output_name], {input_name: input_image}, ) # Post process onnx_result = np.squeeze(onnx_result).astype(np.float32) return onnx_result def main(): args = get_args() model_path = args.model input_size = [int(i) for i in args.input_size.split(',')] # Load model onnx_session = onnxruntime.InferenceSession(model_path) # read image image_path = args.image image = cv.imread(image_path) # Inference execution start_time = time.time() result = run_inference( onnx_session, input_size, image, ) elapsed_time = time.time() - start_time print('Elapsed Time :', '{:.1f}'.format(elapsed_time * 1000) + "ms") print('sfw :', '{:.3f}'.format(result[0])) print('nsfw:', '{:.3f}'.format(result[1])) if __name__ == '__main__': main()
<filename>199_NSFW/demo/demo_nsfw_onnx.py #!/usr/bin/env python # -*- coding: utf-8 -*- import time import argparse import cv2 as cv import numpy as np import onnxruntime def get_args(): parser = argparse.ArgumentParser() parser.add_argument( "--image", type=str, default='image/sample.jpg', ) parser.add_argument( "--model", type=str, default='saved_model_nsfw/model_float32.onnx', ) parser.add_argument( "--input_size", type=str, default='224,224', ) args = parser.parse_args() return args def run_inference( onnx_session, input_size, image, ): # Pre process:Resize, RGB->BGR, Transpose, float32 cast input_image = cv.resize(image, dsize=(input_size[1], input_size[0])) input_image = cv.cvtColor(input_image, cv.COLOR_BGR2RGB) vgg_mean = [104, 117, 123] input_image = input_image - vgg_mean input_image = input_image.transpose(2, 0, 1) input_image = np.expand_dims(input_image, axis=0) input_image = input_image.astype('float32') # Inference input_name = onnx_session.get_inputs()[0].name output_name = onnx_session.get_outputs()[0].name onnx_result = onnx_session.run( [output_name], {input_name: input_image}, ) # Post process onnx_result = np.squeeze(onnx_result).astype(np.float32) return onnx_result def main(): args = get_args() model_path = args.model input_size = [int(i) for i in args.input_size.split(',')] # Load model onnx_session = onnxruntime.InferenceSession(model_path) # read image image_path = args.image image = cv.imread(image_path) # Inference execution start_time = time.time() result = run_inference( onnx_session, input_size, image, ) elapsed_time = time.time() - start_time print('Elapsed Time :', '{:.1f}'.format(elapsed_time * 1000) + "ms") print('sfw :', '{:.3f}'.format(result[0])) print('nsfw:', '{:.3f}'.format(result[1])) if __name__ == '__main__': main()
en
0.671448
#!/usr/bin/env python # -*- coding: utf-8 -*- # Pre process:Resize, RGB->BGR, Transpose, float32 cast # Inference # Post process # Load model # read image # Inference execution
2.456852
2
apps/zop/zop.py
herimonster/zoid
0
6632237
<reponame>herimonster/zoid<filename>apps/zop/zop.py<gh_stars>0 import zapp import zframe import zborderframe import zlabel import zkeylabel import zlineedit import ztextedit import ztable import zutils import os import re import pwd class zop(zapp.zapp): PROC_DIR = "/proc" def get_user(self, id): try: return str(pwd.getpwuid( id ).pw_name) except: return str(id) def rebuild(self): pattern = re.compile("^[0-9]+$") listing = os.listdir(self.PROC_DIR) res = [] for infile in listing: if not pattern.match(infile): continue if not os.path.isdir(self.PROC_DIR + "/" + infile): continue #print(infile) data = "" with open(self.PROC_DIR+"/"+infile+"/status", 'r') as f: data = f.read() with open(self.PROC_DIR+"/"+infile+"/cmdline", 'r') as f: data += "CmdLine: " + f.read() #d = [item.split(":") for item in data.split("\n")] d = [] for pair in [item.split(":", 1) for item in data.split("\n")]: if len(pair) < 2: continue pair[0] = pair[0].strip() pair[1] = pair[1].strip() d.append(pair) data = dict(d) res.append(data) return res def reinsert(self, tab): procs = self.rebuild() tab.rows.clear(); for i in range(len(procs)): #tab.add_row([str(i), "Test", "root", "1024", "43", "1", "/bin/Test"]) self.HUI = i self.HUI2 = procs[i] pid = int(procs[i]["Pid"]) name = procs[i]["Name"] owner = self.get_user(int(procs[i]["Uid"].split("\t")[0])) mem = procs[i]["VmRSS"] if "VmRSS" in procs[i] else "" if mem != "": #mem = str(int(float(mem.split(" ")[0]) / 1000.0)) mem = int(mem.split(" ")[0]) else: mem = 0; cpu = "43" parent = int(procs[i]["PPid"]) #tab.rows.append([str(i), procs[i]["Name"], self.get_user(int(procs[i]["Pid"])), procs[i]["VmSize"] if "VmSize" in procs[i] else "", "43", procs[i]["PPid"], procs[i]["CmdLine"]]) tab.rows.append([pid, name, owner, mem, cpu, parent, ""]) tab.resort() def do_run(self): r = self._root_frame tab = ztable.ztable(r, (0,0), r._size, 7) r.add_child(tab) tab.head[0]["caption"] = "PID" tab.head[0]["width"] = 6 tab.head[0]["align"] = ztable.ztable.AL_RIGHT tab.head[1]["caption"] = "Name" tab.head[1]["width"] = 16 tab.head[2]["caption"] = "Owner" tab.head[2]["width"] = 10 tab.head[3]["caption"] = "Mem" tab.head[3]["width"] = 9 tab.head[3]["align"] = ztable.ztable.AL_RIGHT tab.head[4]["caption"] = "CPU" tab.head[4]["width"] = 4 tab.head[4]["align"] = ztable.ztable.AL_RIGHT tab.head[5]["caption"] = "Parent" tab.head[5]["width"] = 6 tab.head[5]["align"] = ztable.ztable.AL_RIGHT w = 0 for i in range(6): w += tab.head[i]["width"] w = tab._size[0] - w tab.head[6]["caption"] = "Command Line" tab.head[6]["width"] = w #wupp = ztextedit.ztextedit(r, (10,5), (20, 8), "") #r.add_child(wupp) r.next_focus() #bf = zborderframe.zborderframe(self._root_frame, (2,2), (70,20), "Hallo") #bf2 = zborderframe.zborderframe(self._root_frame, (75,2), (20,10), "Hallo2") #lbl = zkeylabel.zkeylabel(bf2, (1,1), (18,1), "HUHU") #ed = zlineedit.zlineedit(bf, (1,1), (18,1), "Test text" ) #tab = ztable.ztable(bf, (1,2), (68,17), 4) #bf2.add_child(lbl) #bf.add_child(ed) #bf.add_child(tab) #tab.add_row(["Test " + str(i), "i*i = " + str(i*i), "i^i = " + str(i**i), "Ende", ]) #bf = zborderframe.zborderframe(None, (2,2), (20,20), "Hallo") #self._root_frame.add_child(bf) #self._root_frame.add_child(bf2) #ed.on_enter = lambda sender: tab.add_row([ed.get_text(), "2", "3", "4"]) or ed.set_text("") #ed.on_change = lambda sender: lbl2.set_caption(sender.get_text()) or lbl2.set_fcolor(-1) self.reinsert(tab) while True: self.render() c, buf = self._get_char() if(buf == "r"): self.reinsert(tab) elif(buf == "d"): tab.set_desc(not tab.get_desc()) elif(buf == ">"): tab.set_order_by(tab.get_order_by()+1) elif(buf == "<"): tab.set_order_by(tab.get_order_by()-1) self._root_frame.on_key(c, buf) app = zop() app.run()
import zapp import zframe import zborderframe import zlabel import zkeylabel import zlineedit import ztextedit import ztable import zutils import os import re import pwd class zop(zapp.zapp): PROC_DIR = "/proc" def get_user(self, id): try: return str(pwd.getpwuid( id ).pw_name) except: return str(id) def rebuild(self): pattern = re.compile("^[0-9]+$") listing = os.listdir(self.PROC_DIR) res = [] for infile in listing: if not pattern.match(infile): continue if not os.path.isdir(self.PROC_DIR + "/" + infile): continue #print(infile) data = "" with open(self.PROC_DIR+"/"+infile+"/status", 'r') as f: data = f.read() with open(self.PROC_DIR+"/"+infile+"/cmdline", 'r') as f: data += "CmdLine: " + f.read() #d = [item.split(":") for item in data.split("\n")] d = [] for pair in [item.split(":", 1) for item in data.split("\n")]: if len(pair) < 2: continue pair[0] = pair[0].strip() pair[1] = pair[1].strip() d.append(pair) data = dict(d) res.append(data) return res def reinsert(self, tab): procs = self.rebuild() tab.rows.clear(); for i in range(len(procs)): #tab.add_row([str(i), "Test", "root", "1024", "43", "1", "/bin/Test"]) self.HUI = i self.HUI2 = procs[i] pid = int(procs[i]["Pid"]) name = procs[i]["Name"] owner = self.get_user(int(procs[i]["Uid"].split("\t")[0])) mem = procs[i]["VmRSS"] if "VmRSS" in procs[i] else "" if mem != "": #mem = str(int(float(mem.split(" ")[0]) / 1000.0)) mem = int(mem.split(" ")[0]) else: mem = 0; cpu = "43" parent = int(procs[i]["PPid"]) #tab.rows.append([str(i), procs[i]["Name"], self.get_user(int(procs[i]["Pid"])), procs[i]["VmSize"] if "VmSize" in procs[i] else "", "43", procs[i]["PPid"], procs[i]["CmdLine"]]) tab.rows.append([pid, name, owner, mem, cpu, parent, ""]) tab.resort() def do_run(self): r = self._root_frame tab = ztable.ztable(r, (0,0), r._size, 7) r.add_child(tab) tab.head[0]["caption"] = "PID" tab.head[0]["width"] = 6 tab.head[0]["align"] = ztable.ztable.AL_RIGHT tab.head[1]["caption"] = "Name" tab.head[1]["width"] = 16 tab.head[2]["caption"] = "Owner" tab.head[2]["width"] = 10 tab.head[3]["caption"] = "Mem" tab.head[3]["width"] = 9 tab.head[3]["align"] = ztable.ztable.AL_RIGHT tab.head[4]["caption"] = "CPU" tab.head[4]["width"] = 4 tab.head[4]["align"] = ztable.ztable.AL_RIGHT tab.head[5]["caption"] = "Parent" tab.head[5]["width"] = 6 tab.head[5]["align"] = ztable.ztable.AL_RIGHT w = 0 for i in range(6): w += tab.head[i]["width"] w = tab._size[0] - w tab.head[6]["caption"] = "Command Line" tab.head[6]["width"] = w #wupp = ztextedit.ztextedit(r, (10,5), (20, 8), "") #r.add_child(wupp) r.next_focus() #bf = zborderframe.zborderframe(self._root_frame, (2,2), (70,20), "Hallo") #bf2 = zborderframe.zborderframe(self._root_frame, (75,2), (20,10), "Hallo2") #lbl = zkeylabel.zkeylabel(bf2, (1,1), (18,1), "HUHU") #ed = zlineedit.zlineedit(bf, (1,1), (18,1), "Test text" ) #tab = ztable.ztable(bf, (1,2), (68,17), 4) #bf2.add_child(lbl) #bf.add_child(ed) #bf.add_child(tab) #tab.add_row(["Test " + str(i), "i*i = " + str(i*i), "i^i = " + str(i**i), "Ende", ]) #bf = zborderframe.zborderframe(None, (2,2), (20,20), "Hallo") #self._root_frame.add_child(bf) #self._root_frame.add_child(bf2) #ed.on_enter = lambda sender: tab.add_row([ed.get_text(), "2", "3", "4"]) or ed.set_text("") #ed.on_change = lambda sender: lbl2.set_caption(sender.get_text()) or lbl2.set_fcolor(-1) self.reinsert(tab) while True: self.render() c, buf = self._get_char() if(buf == "r"): self.reinsert(tab) elif(buf == "d"): tab.set_desc(not tab.get_desc()) elif(buf == ">"): tab.set_order_by(tab.get_order_by()+1) elif(buf == "<"): tab.set_order_by(tab.get_order_by()-1) self._root_frame.on_key(c, buf) app = zop() app.run()
en
0.200178
#print(infile) #d = [item.split(":") for item in data.split("\n")] #tab.add_row([str(i), "Test", "root", "1024", "43", "1", "/bin/Test"]) #mem = str(int(float(mem.split(" ")[0]) / 1000.0)) #tab.rows.append([str(i), procs[i]["Name"], self.get_user(int(procs[i]["Pid"])), procs[i]["VmSize"] if "VmSize" in procs[i] else "", "43", procs[i]["PPid"], procs[i]["CmdLine"]]) #wupp = ztextedit.ztextedit(r, (10,5), (20, 8), "") #r.add_child(wupp) #bf = zborderframe.zborderframe(self._root_frame, (2,2), (70,20), "Hallo") #bf2 = zborderframe.zborderframe(self._root_frame, (75,2), (20,10), "Hallo2") #lbl = zkeylabel.zkeylabel(bf2, (1,1), (18,1), "HUHU") #ed = zlineedit.zlineedit(bf, (1,1), (18,1), "Test text" ) #tab = ztable.ztable(bf, (1,2), (68,17), 4) #bf2.add_child(lbl) #bf.add_child(ed) #bf.add_child(tab) #tab.add_row(["Test " + str(i), "i*i = " + str(i*i), "i^i = " + str(i**i), "Ende", ]) #bf = zborderframe.zborderframe(None, (2,2), (20,20), "Hallo") #self._root_frame.add_child(bf) #self._root_frame.add_child(bf2) #ed.on_enter = lambda sender: tab.add_row([ed.get_text(), "2", "3", "4"]) or ed.set_text("") #ed.on_change = lambda sender: lbl2.set_caption(sender.get_text()) or lbl2.set_fcolor(-1)
2.193503
2
tests/gridworld_test.py
Duckie-town-isu/tulip-control
91
6632238
<filename>tests/gridworld_test.py """Tests for the tulip.gridworld.""" from __future__ import division from __future__ import print_function try: from dd import cudd as dd_cudd except ImportError: dd_cudd = None import numpy as np import pytest import tulip.gridworld as gw import unittest from tulip.synth import is_realizable REFERENCE_GWFILE = """ # A very small example, realizable by itself. 6 10 * G* *** *** * I * * * ****** * * """ UNREACHABLE_GOAL_GWFILE = """ 4 4 **G ** I* * """ TRIVIAL_GWFILE = """ 2 2 * """ # Module-level fixture setup def setup_module(): np.random.seed(0) # Make pseudorandom number sequence repeatable class GridWorld_test(object): def setup_method(self): self.prefix = "testworld" self.X = gw.GridWorld(REFERENCE_GWFILE, prefix=self.prefix) self.Y_testpaths = gw.GridWorld(UNREACHABLE_GOAL_GWFILE, prefix=self.prefix) def teardown_method(self): self.X = None self.Y_testpaths = None def test_reachability(self): # Reachability is assumed to be bidirectional assert not self.Y_testpaths.is_reachable((3,0), (0,2)) assert not self.Y_testpaths.is_reachable((0,2), (3,0)) assert self.Y_testpaths.is_reachable((1,1), (2,3)) assert self.Y_testpaths.is_reachable((2,3), (1,1)) def test_size(self): assert self.X.size() == (6, 10) def test_copy(self): Z = self.X.copy() assert Z is not self.X assert Z.W is not self.X.W assert Z == self.X def test_getitem(self): assert self.X.__getitem__( (0,0), nonbool=False) == self.prefix+"_"+str(0)+"_"+str(0) assert self.X.__getitem__( (-1,0), nonbool=False) == self.prefix+"_"+str(5)+"_"+str(0) assert self.X.__getitem__( (-1,-2), nonbool=False) == self.prefix+"_"+str(5)+"_"+str(8) def test_state(self): assert self.X.state((2,3), nonbool=False) == { 'testworld_3_9': 0, 'testworld_1_8': 0, 'testworld_1_9': 0, 'testworld_1_4': 0, 'testworld_1_5': 0, 'testworld_1_6': 0, 'testworld_1_7': 0, 'testworld_1_0': 0, 'testworld_1_1': 0, 'testworld_1_2': 0, 'testworld_1_3': 0, 'testworld_0_5': 0, 'testworld_0_4': 0, 'testworld_0_7': 0, 'testworld_0_6': 0, 'testworld_0_1': 0, 'testworld_0_0': 0, 'testworld_0_3': 0, 'testworld_0_2': 0, 'testworld_5_7': 0, 'testworld_0_9': 0, 'testworld_0_8': 0, 'testworld_3_2': 0, 'testworld_3_3': 0, 'testworld_2_9': 0, 'testworld_2_8': 0, 'testworld_3_6': 0, 'testworld_3_7': 0, 'testworld_3_4': 0, 'testworld_3_5': 0, 'testworld_2_3': 1, 'testworld_2_2': 0, 'testworld_2_1': 0, 'testworld_2_0': 0, 'testworld_2_7': 0, 'testworld_2_6': 0, 'testworld_2_5': 0, 'testworld_2_4': 0, 'testworld_4_1': 0, 'testworld_4_0': 0, 'testworld_4_3': 0, 'testworld_4_2': 0, 'testworld_4_5': 0, 'testworld_4_4': 0, 'testworld_4_7': 0, 'testworld_4_6': 0, 'testworld_4_9': 0, 'testworld_4_8': 0, 'testworld_5_8': 0, 'testworld_5_2': 0, 'testworld_5_9': 0, 'testworld_3_0': 0, 'testworld_3_1': 0, 'testworld_5_3': 0, 'testworld_5_5': 0, 'testworld_5_0': 0, 'testworld_5_4': 0, 'testworld_5_1': 0, 'testworld_5_6': 0, 'testworld_3_8': 0} assert self.X.state((-1,0), nonbool=False) == { 'testworld_3_9': 0, 'testworld_1_8': 0, 'testworld_1_9': 0, 'testworld_1_4': 0, 'testworld_1_5': 0, 'testworld_1_6': 0, 'testworld_1_7': 0, 'testworld_1_0': 0, 'testworld_1_1': 0, 'testworld_1_2': 0, 'testworld_1_3': 0, 'testworld_0_5': 0, 'testworld_0_4': 0, 'testworld_0_7': 0, 'testworld_0_6': 0, 'testworld_0_1': 0, 'testworld_0_0': 0, 'testworld_0_3': 0, 'testworld_0_2': 0, 'testworld_5_7': 0, 'testworld_0_9': 0, 'testworld_0_8': 0, 'testworld_3_2': 0, 'testworld_3_3': 0, 'testworld_2_9': 0, 'testworld_2_8': 0, 'testworld_3_6': 0, 'testworld_3_7': 0, 'testworld_3_4': 0, 'testworld_3_5': 0, 'testworld_2_3': 0, 'testworld_2_2': 0, 'testworld_2_1': 0, 'testworld_2_0': 0, 'testworld_2_7': 0, 'testworld_2_6': 0, 'testworld_2_5': 0, 'testworld_2_4': 0, 'testworld_4_1': 0, 'testworld_4_0': 0, 'testworld_4_3': 0, 'testworld_4_2': 0, 'testworld_4_5': 0, 'testworld_4_4': 0, 'testworld_4_7': 0, 'testworld_4_6': 0, 'testworld_4_9': 0, 'testworld_4_8': 0, 'testworld_5_8': 0, 'testworld_5_2': 0, 'testworld_5_9': 0, 'testworld_3_0': 0, 'testworld_3_1': 0, 'testworld_5_3': 0, 'testworld_5_5': 0, 'testworld_5_0': 1, 'testworld_5_4': 0, 'testworld_5_1': 0, 'testworld_5_6': 0, 'testworld_3_8': 0} assert self.X.state((-1,-1), nonbool=False) == { 'testworld_3_9': 0, 'testworld_1_8': 0, 'testworld_1_9': 0, 'testworld_1_4': 0, 'testworld_1_5': 0, 'testworld_1_6': 0, 'testworld_1_7': 0, 'testworld_1_0': 0, 'testworld_1_1': 0, 'testworld_1_2': 0, 'testworld_1_3': 0, 'testworld_0_5': 0, 'testworld_0_4': 0, 'testworld_0_7': 0, 'testworld_0_6': 0, 'testworld_0_1': 0, 'testworld_0_0': 0, 'testworld_0_3': 0, 'testworld_0_2': 0, 'testworld_5_7': 0, 'testworld_0_9': 0, 'testworld_0_8': 0, 'testworld_3_2': 0, 'testworld_3_3': 0, 'testworld_2_9': 0, 'testworld_2_8': 0, 'testworld_3_6': 0, 'testworld_3_7': 0, 'testworld_3_4': 0, 'testworld_3_5': 0, 'testworld_2_3': 0, 'testworld_2_2': 0, 'testworld_2_1': 0, 'testworld_2_0': 0, 'testworld_2_7': 0, 'testworld_2_6': 0, 'testworld_2_5': 0, 'testworld_2_4': 0, 'testworld_4_1': 0, 'testworld_4_0': 0, 'testworld_4_3': 0, 'testworld_4_2': 0, 'testworld_4_5': 0, 'testworld_4_4': 0, 'testworld_4_7': 0, 'testworld_4_6': 0, 'testworld_4_9': 0, 'testworld_4_8': 0, 'testworld_5_8': 0, 'testworld_5_2': 0, 'testworld_5_9': 1, 'testworld_3_0': 0, 'testworld_3_1': 0, 'testworld_5_3': 0, 'testworld_5_5': 0, 'testworld_5_0': 0, 'testworld_5_4': 0, 'testworld_5_1': 0, 'testworld_5_6': 0, 'testworld_3_8': 0} def test_equality(self): assert self.X == gw.GridWorld(REFERENCE_GWFILE) Y = gw.GridWorld() assert self.X != Y Y = gw.GridWorld(TRIVIAL_GWFILE) assert self.X != Y def test_dumploadloop(self): assert self.X == gw.GridWorld(self.X.dumps()) @unittest.skipIf(dd_cudd is None, '`dd.cudd` not installed') def test_spec_realizable_bool(self): spec = self.X.spec(nonbool=False) spec.moore = False spec.plus_one = False spec.qinit = r'\A \E' assert is_realizable(spec) def test_spec_realizable(self): spec = self.X.spec() spec.moore = False spec.plus_one = False spec.qinit = r'\A \E' assert is_realizable(spec) @pytest.mark.parametrize('coord,expected', [((0, 0), False), ((0, 1), True), ((-1, 0), False), ((0, -1), True)]) def test_is_empty(self, coord, expected): assert self.X.is_empty(coord) == expected @pytest.mark.parametrize('coord,expected', [((0, 0), False), ((0, 1), True), ((-1, 0), False), ((0, -1), False)]) def test_is_empty_extend(self, coord, expected): assert self.X.is_empty(coord, extend=True) == expected def test_dump_subworld(self): # No offset X_local = self.X.dump_subworld((2,4), prefix="X") assert X_local.size() == (2, 4) assert X_local.__getitem__((0,0), nonbool=False) == "X_0_0" assert not X_local.is_empty((0,0)) assert X_local.is_empty((0,1)) # Offset X_local = self.X.dump_subworld((2,4), offset=(1,0), prefix="Xoff") assert X_local.size() == (2, 4) assert X_local.__getitem__((0,0), nonbool=False) == "Xoff_0_0" assert X_local.is_empty((0,0)) assert X_local.is_empty((0,1)) assert not X_local.is_empty((0,3)) def test_dump_subworld_extend(self): # No offset Xsize = self.X.size() X_local = self.X.dump_subworld((Xsize[0]+1, Xsize[1]), prefix="X", extend=True) X_local.goal_list = self.X.goal_list[:] X_local.init_list = self.X.init_list[:] assert X_local.size() == (7, 10) assert X_local.__getitem__((0,0), nonbool=False) == "X_0_0" assert not X_local.is_empty((0,0)) assert X_local.is_empty((0,1)) # Equal except for the last row, which should be all occupied in X_local X_local_s = X_local.dumps().splitlines() assert np.all(X_local_s[1:-1] == self.X.dumps().splitlines()[1:]) assert not X_local.is_empty((6,1)) assert X_local_s[-1] == "*"*10 # Offset X_local = self.X.dump_subworld((3,4), offset=(-1,0), prefix="Xoff", extend=True) assert X_local.size() == (3, 4) assert X_local.__getitem__((0,0), nonbool=False) == "Xoff_0_0" assert not X_local.is_empty((0,0)) assert not X_local.is_empty((0,1)) assert not X_local.is_empty((0,3)) assert X_local.is_empty((1,1)) @pytest.mark.slow class RandomWorld_test(object): def setup_method(self): self.wall_densities = [.2, .4, .6] self.sizes = [(4,5), (4,5), (10,20)] self.rworlds = [ gw.random_world( self.sizes[r], wall_density=self.wall_densities[r], prefix="Y") for r in range(len(self.sizes))] self.rworlds_ensuredfeasible = [ gw.random_world( self.sizes[r], self.wall_densities[r], num_init=2, num_goals=2, ensure_feasible=True) for r in range(len(self.sizes))] def teardown_method(self): self.rworlds = [] def test_feasibility(self): for r in range(len(self.rworlds_ensuredfeasible)): print('test "ensured feasible" world index', r) print(self.rworlds_ensuredfeasible[r]) assert self.rworlds_ensuredfeasible[r].is_reachable( self.rworlds_ensuredfeasible[r].init_list[0], self.rworlds_ensuredfeasible[r].init_list[1]) assert self.rworlds_ensuredfeasible[r].is_reachable( self.rworlds_ensuredfeasible[r].init_list[1], self.rworlds_ensuredfeasible[r].goal_list[0]) assert self.rworlds_ensuredfeasible[r].is_reachable( self.rworlds_ensuredfeasible[r].goal_list[0], self.rworlds_ensuredfeasible[r].goal_list[1]) assert self.rworlds_ensuredfeasible[r].is_reachable( self.rworlds_ensuredfeasible[r].goal_list[1], self.rworlds_ensuredfeasible[r].init_list[0]) def test_size(self): for r in range(len(self.rworlds)): print("test world index", r) print(self.rworlds[r]) assert self.sizes[r] == self.rworlds[r].size() def test_density(self): for r in range(len(self.rworlds)): print("test world index", r) print(self.rworlds[r]) (num_rows, num_cols) = self.rworlds[r].size() num_occupied = 0 for i in range(num_rows): for j in range(num_cols): if not self.rworlds[r].is_empty((i,j)): num_occupied += 1 assert ( float(num_occupied) / (num_rows*num_cols) == self.wall_densities[r]) @pytest.mark.parametrize('label,expected_coord', [('test_3_0', ('test', 3, 0)), ('obstacle_5_4_11', ('obstacle_5', 4, 11)), ('test3_0', None)]) def extract_coord_test(label, expected_coord): assert gw.extract_coord(label) == expected_coord def eq_gridworld_param(): empty = gw.GridWorld() trivial_nonempty = gw.GridWorld(TRIVIAL_GWFILE) trivial_diff = gw.GridWorld(TRIVIAL_GWFILE) if trivial_diff.is_empty((0, 0)): trivial_diff.mark_occupied((0, 0)) else: trivial_diff.mark_empty((0, 0)) trivial_nonempty_2goals = gw.GridWorld(TRIVIAL_GWFILE) trivial_nonempty_2goals.goal_list = [(0, 0), (1, 1)] trivial_nonempty_2init = gw.GridWorld(TRIVIAL_GWFILE) trivial_nonempty_2init.init_list = [(0, 0), (1, 1)] for (G, H, is_equal) in [ (gw.GridWorld(), gw.GridWorld(), True), (empty, trivial_nonempty, False), (trivial_nonempty_2goals, trivial_nonempty, False), (trivial_nonempty_2init, trivial_nonempty, False), (trivial_nonempty, trivial_diff, False), (gw.unoccupied((3, 5)), gw.unoccupied((1, 1)), False)]: yield (G, H, is_equal) @pytest.mark.parametrize('G,H,eq', eq_gridworld_param()) def eq_gridworld_test(G, H, eq): if eq: G == H else: not (G == H) def narrow_passage_test(): G = gw.narrow_passage((5, 10), num_init=1, num_goals=1) assert G.is_reachable(G.init_list[0], G.goal_list[0]) def scale_gridworld_test(): G = gw.unoccupied((1, 2)) assert G.size() == (1, 2) assert G.scale().size() == G.size() assert G.scale(xf=1, yf=1).size() == G.size() assert G.scale(xf=2).size() == (1, 4) assert G.scale(yf=2).size() == (2, 2) assert G.scale(xf=3, yf=4).size() == (4, 6) def add_trolls_test(): G = gw.unoccupied((3, 5)) G.init_list = [(0, 0)] G.goal_list = [(0, 4)] spc = gw.add_trolls(G, [((2, 2), 1)], get_moves_lists=False) spc.moore = False spc.plus_one = False spc.qinit = r'\A \E' assert is_realizable(spc)
<filename>tests/gridworld_test.py """Tests for the tulip.gridworld.""" from __future__ import division from __future__ import print_function try: from dd import cudd as dd_cudd except ImportError: dd_cudd = None import numpy as np import pytest import tulip.gridworld as gw import unittest from tulip.synth import is_realizable REFERENCE_GWFILE = """ # A very small example, realizable by itself. 6 10 * G* *** *** * I * * * ****** * * """ UNREACHABLE_GOAL_GWFILE = """ 4 4 **G ** I* * """ TRIVIAL_GWFILE = """ 2 2 * """ # Module-level fixture setup def setup_module(): np.random.seed(0) # Make pseudorandom number sequence repeatable class GridWorld_test(object): def setup_method(self): self.prefix = "testworld" self.X = gw.GridWorld(REFERENCE_GWFILE, prefix=self.prefix) self.Y_testpaths = gw.GridWorld(UNREACHABLE_GOAL_GWFILE, prefix=self.prefix) def teardown_method(self): self.X = None self.Y_testpaths = None def test_reachability(self): # Reachability is assumed to be bidirectional assert not self.Y_testpaths.is_reachable((3,0), (0,2)) assert not self.Y_testpaths.is_reachable((0,2), (3,0)) assert self.Y_testpaths.is_reachable((1,1), (2,3)) assert self.Y_testpaths.is_reachable((2,3), (1,1)) def test_size(self): assert self.X.size() == (6, 10) def test_copy(self): Z = self.X.copy() assert Z is not self.X assert Z.W is not self.X.W assert Z == self.X def test_getitem(self): assert self.X.__getitem__( (0,0), nonbool=False) == self.prefix+"_"+str(0)+"_"+str(0) assert self.X.__getitem__( (-1,0), nonbool=False) == self.prefix+"_"+str(5)+"_"+str(0) assert self.X.__getitem__( (-1,-2), nonbool=False) == self.prefix+"_"+str(5)+"_"+str(8) def test_state(self): assert self.X.state((2,3), nonbool=False) == { 'testworld_3_9': 0, 'testworld_1_8': 0, 'testworld_1_9': 0, 'testworld_1_4': 0, 'testworld_1_5': 0, 'testworld_1_6': 0, 'testworld_1_7': 0, 'testworld_1_0': 0, 'testworld_1_1': 0, 'testworld_1_2': 0, 'testworld_1_3': 0, 'testworld_0_5': 0, 'testworld_0_4': 0, 'testworld_0_7': 0, 'testworld_0_6': 0, 'testworld_0_1': 0, 'testworld_0_0': 0, 'testworld_0_3': 0, 'testworld_0_2': 0, 'testworld_5_7': 0, 'testworld_0_9': 0, 'testworld_0_8': 0, 'testworld_3_2': 0, 'testworld_3_3': 0, 'testworld_2_9': 0, 'testworld_2_8': 0, 'testworld_3_6': 0, 'testworld_3_7': 0, 'testworld_3_4': 0, 'testworld_3_5': 0, 'testworld_2_3': 1, 'testworld_2_2': 0, 'testworld_2_1': 0, 'testworld_2_0': 0, 'testworld_2_7': 0, 'testworld_2_6': 0, 'testworld_2_5': 0, 'testworld_2_4': 0, 'testworld_4_1': 0, 'testworld_4_0': 0, 'testworld_4_3': 0, 'testworld_4_2': 0, 'testworld_4_5': 0, 'testworld_4_4': 0, 'testworld_4_7': 0, 'testworld_4_6': 0, 'testworld_4_9': 0, 'testworld_4_8': 0, 'testworld_5_8': 0, 'testworld_5_2': 0, 'testworld_5_9': 0, 'testworld_3_0': 0, 'testworld_3_1': 0, 'testworld_5_3': 0, 'testworld_5_5': 0, 'testworld_5_0': 0, 'testworld_5_4': 0, 'testworld_5_1': 0, 'testworld_5_6': 0, 'testworld_3_8': 0} assert self.X.state((-1,0), nonbool=False) == { 'testworld_3_9': 0, 'testworld_1_8': 0, 'testworld_1_9': 0, 'testworld_1_4': 0, 'testworld_1_5': 0, 'testworld_1_6': 0, 'testworld_1_7': 0, 'testworld_1_0': 0, 'testworld_1_1': 0, 'testworld_1_2': 0, 'testworld_1_3': 0, 'testworld_0_5': 0, 'testworld_0_4': 0, 'testworld_0_7': 0, 'testworld_0_6': 0, 'testworld_0_1': 0, 'testworld_0_0': 0, 'testworld_0_3': 0, 'testworld_0_2': 0, 'testworld_5_7': 0, 'testworld_0_9': 0, 'testworld_0_8': 0, 'testworld_3_2': 0, 'testworld_3_3': 0, 'testworld_2_9': 0, 'testworld_2_8': 0, 'testworld_3_6': 0, 'testworld_3_7': 0, 'testworld_3_4': 0, 'testworld_3_5': 0, 'testworld_2_3': 0, 'testworld_2_2': 0, 'testworld_2_1': 0, 'testworld_2_0': 0, 'testworld_2_7': 0, 'testworld_2_6': 0, 'testworld_2_5': 0, 'testworld_2_4': 0, 'testworld_4_1': 0, 'testworld_4_0': 0, 'testworld_4_3': 0, 'testworld_4_2': 0, 'testworld_4_5': 0, 'testworld_4_4': 0, 'testworld_4_7': 0, 'testworld_4_6': 0, 'testworld_4_9': 0, 'testworld_4_8': 0, 'testworld_5_8': 0, 'testworld_5_2': 0, 'testworld_5_9': 0, 'testworld_3_0': 0, 'testworld_3_1': 0, 'testworld_5_3': 0, 'testworld_5_5': 0, 'testworld_5_0': 1, 'testworld_5_4': 0, 'testworld_5_1': 0, 'testworld_5_6': 0, 'testworld_3_8': 0} assert self.X.state((-1,-1), nonbool=False) == { 'testworld_3_9': 0, 'testworld_1_8': 0, 'testworld_1_9': 0, 'testworld_1_4': 0, 'testworld_1_5': 0, 'testworld_1_6': 0, 'testworld_1_7': 0, 'testworld_1_0': 0, 'testworld_1_1': 0, 'testworld_1_2': 0, 'testworld_1_3': 0, 'testworld_0_5': 0, 'testworld_0_4': 0, 'testworld_0_7': 0, 'testworld_0_6': 0, 'testworld_0_1': 0, 'testworld_0_0': 0, 'testworld_0_3': 0, 'testworld_0_2': 0, 'testworld_5_7': 0, 'testworld_0_9': 0, 'testworld_0_8': 0, 'testworld_3_2': 0, 'testworld_3_3': 0, 'testworld_2_9': 0, 'testworld_2_8': 0, 'testworld_3_6': 0, 'testworld_3_7': 0, 'testworld_3_4': 0, 'testworld_3_5': 0, 'testworld_2_3': 0, 'testworld_2_2': 0, 'testworld_2_1': 0, 'testworld_2_0': 0, 'testworld_2_7': 0, 'testworld_2_6': 0, 'testworld_2_5': 0, 'testworld_2_4': 0, 'testworld_4_1': 0, 'testworld_4_0': 0, 'testworld_4_3': 0, 'testworld_4_2': 0, 'testworld_4_5': 0, 'testworld_4_4': 0, 'testworld_4_7': 0, 'testworld_4_6': 0, 'testworld_4_9': 0, 'testworld_4_8': 0, 'testworld_5_8': 0, 'testworld_5_2': 0, 'testworld_5_9': 1, 'testworld_3_0': 0, 'testworld_3_1': 0, 'testworld_5_3': 0, 'testworld_5_5': 0, 'testworld_5_0': 0, 'testworld_5_4': 0, 'testworld_5_1': 0, 'testworld_5_6': 0, 'testworld_3_8': 0} def test_equality(self): assert self.X == gw.GridWorld(REFERENCE_GWFILE) Y = gw.GridWorld() assert self.X != Y Y = gw.GridWorld(TRIVIAL_GWFILE) assert self.X != Y def test_dumploadloop(self): assert self.X == gw.GridWorld(self.X.dumps()) @unittest.skipIf(dd_cudd is None, '`dd.cudd` not installed') def test_spec_realizable_bool(self): spec = self.X.spec(nonbool=False) spec.moore = False spec.plus_one = False spec.qinit = r'\A \E' assert is_realizable(spec) def test_spec_realizable(self): spec = self.X.spec() spec.moore = False spec.plus_one = False spec.qinit = r'\A \E' assert is_realizable(spec) @pytest.mark.parametrize('coord,expected', [((0, 0), False), ((0, 1), True), ((-1, 0), False), ((0, -1), True)]) def test_is_empty(self, coord, expected): assert self.X.is_empty(coord) == expected @pytest.mark.parametrize('coord,expected', [((0, 0), False), ((0, 1), True), ((-1, 0), False), ((0, -1), False)]) def test_is_empty_extend(self, coord, expected): assert self.X.is_empty(coord, extend=True) == expected def test_dump_subworld(self): # No offset X_local = self.X.dump_subworld((2,4), prefix="X") assert X_local.size() == (2, 4) assert X_local.__getitem__((0,0), nonbool=False) == "X_0_0" assert not X_local.is_empty((0,0)) assert X_local.is_empty((0,1)) # Offset X_local = self.X.dump_subworld((2,4), offset=(1,0), prefix="Xoff") assert X_local.size() == (2, 4) assert X_local.__getitem__((0,0), nonbool=False) == "Xoff_0_0" assert X_local.is_empty((0,0)) assert X_local.is_empty((0,1)) assert not X_local.is_empty((0,3)) def test_dump_subworld_extend(self): # No offset Xsize = self.X.size() X_local = self.X.dump_subworld((Xsize[0]+1, Xsize[1]), prefix="X", extend=True) X_local.goal_list = self.X.goal_list[:] X_local.init_list = self.X.init_list[:] assert X_local.size() == (7, 10) assert X_local.__getitem__((0,0), nonbool=False) == "X_0_0" assert not X_local.is_empty((0,0)) assert X_local.is_empty((0,1)) # Equal except for the last row, which should be all occupied in X_local X_local_s = X_local.dumps().splitlines() assert np.all(X_local_s[1:-1] == self.X.dumps().splitlines()[1:]) assert not X_local.is_empty((6,1)) assert X_local_s[-1] == "*"*10 # Offset X_local = self.X.dump_subworld((3,4), offset=(-1,0), prefix="Xoff", extend=True) assert X_local.size() == (3, 4) assert X_local.__getitem__((0,0), nonbool=False) == "Xoff_0_0" assert not X_local.is_empty((0,0)) assert not X_local.is_empty((0,1)) assert not X_local.is_empty((0,3)) assert X_local.is_empty((1,1)) @pytest.mark.slow class RandomWorld_test(object): def setup_method(self): self.wall_densities = [.2, .4, .6] self.sizes = [(4,5), (4,5), (10,20)] self.rworlds = [ gw.random_world( self.sizes[r], wall_density=self.wall_densities[r], prefix="Y") for r in range(len(self.sizes))] self.rworlds_ensuredfeasible = [ gw.random_world( self.sizes[r], self.wall_densities[r], num_init=2, num_goals=2, ensure_feasible=True) for r in range(len(self.sizes))] def teardown_method(self): self.rworlds = [] def test_feasibility(self): for r in range(len(self.rworlds_ensuredfeasible)): print('test "ensured feasible" world index', r) print(self.rworlds_ensuredfeasible[r]) assert self.rworlds_ensuredfeasible[r].is_reachable( self.rworlds_ensuredfeasible[r].init_list[0], self.rworlds_ensuredfeasible[r].init_list[1]) assert self.rworlds_ensuredfeasible[r].is_reachable( self.rworlds_ensuredfeasible[r].init_list[1], self.rworlds_ensuredfeasible[r].goal_list[0]) assert self.rworlds_ensuredfeasible[r].is_reachable( self.rworlds_ensuredfeasible[r].goal_list[0], self.rworlds_ensuredfeasible[r].goal_list[1]) assert self.rworlds_ensuredfeasible[r].is_reachable( self.rworlds_ensuredfeasible[r].goal_list[1], self.rworlds_ensuredfeasible[r].init_list[0]) def test_size(self): for r in range(len(self.rworlds)): print("test world index", r) print(self.rworlds[r]) assert self.sizes[r] == self.rworlds[r].size() def test_density(self): for r in range(len(self.rworlds)): print("test world index", r) print(self.rworlds[r]) (num_rows, num_cols) = self.rworlds[r].size() num_occupied = 0 for i in range(num_rows): for j in range(num_cols): if not self.rworlds[r].is_empty((i,j)): num_occupied += 1 assert ( float(num_occupied) / (num_rows*num_cols) == self.wall_densities[r]) @pytest.mark.parametrize('label,expected_coord', [('test_3_0', ('test', 3, 0)), ('obstacle_5_4_11', ('obstacle_5', 4, 11)), ('test3_0', None)]) def extract_coord_test(label, expected_coord): assert gw.extract_coord(label) == expected_coord def eq_gridworld_param(): empty = gw.GridWorld() trivial_nonempty = gw.GridWorld(TRIVIAL_GWFILE) trivial_diff = gw.GridWorld(TRIVIAL_GWFILE) if trivial_diff.is_empty((0, 0)): trivial_diff.mark_occupied((0, 0)) else: trivial_diff.mark_empty((0, 0)) trivial_nonempty_2goals = gw.GridWorld(TRIVIAL_GWFILE) trivial_nonempty_2goals.goal_list = [(0, 0), (1, 1)] trivial_nonempty_2init = gw.GridWorld(TRIVIAL_GWFILE) trivial_nonempty_2init.init_list = [(0, 0), (1, 1)] for (G, H, is_equal) in [ (gw.GridWorld(), gw.GridWorld(), True), (empty, trivial_nonempty, False), (trivial_nonempty_2goals, trivial_nonempty, False), (trivial_nonempty_2init, trivial_nonempty, False), (trivial_nonempty, trivial_diff, False), (gw.unoccupied((3, 5)), gw.unoccupied((1, 1)), False)]: yield (G, H, is_equal) @pytest.mark.parametrize('G,H,eq', eq_gridworld_param()) def eq_gridworld_test(G, H, eq): if eq: G == H else: not (G == H) def narrow_passage_test(): G = gw.narrow_passage((5, 10), num_init=1, num_goals=1) assert G.is_reachable(G.init_list[0], G.goal_list[0]) def scale_gridworld_test(): G = gw.unoccupied((1, 2)) assert G.size() == (1, 2) assert G.scale().size() == G.size() assert G.scale(xf=1, yf=1).size() == G.size() assert G.scale(xf=2).size() == (1, 4) assert G.scale(yf=2).size() == (2, 2) assert G.scale(xf=3, yf=4).size() == (4, 6) def add_trolls_test(): G = gw.unoccupied((3, 5)) G.init_list = [(0, 0)] G.goal_list = [(0, 4)] spc = gw.add_trolls(G, [((2, 2), 1)], get_moves_lists=False) spc.moore = False spc.plus_one = False spc.qinit = r'\A \E' assert is_realizable(spc)
en
0.78507
Tests for the tulip.gridworld. # A very small example, realizable by itself. 6 10 * G* *** *** * I * * * ****** * * 4 4 **G ** I* * 2 2 * # Module-level fixture setup # Make pseudorandom number sequence repeatable # Reachability is assumed to be bidirectional # No offset # Offset # No offset # Equal except for the last row, which should be all occupied in X_local # Offset
2.585206
3
jackselect/devmonitor.py
SpotlightKid/jack-select
12
6632239
# -*- coding: utf-8 -*- """Set up an udev monitor to be notified about changes in attached sound devices.""" import logging from pyudev import Context, Monitor from .pyudev_gobject import MonitorObserver log = logging.getLogger(__name__) class AlsaDevMonitor: def __init__(self, callback): # set up udev device monitor context = Context() self._monitor = Monitor.from_netlink(context) self._monitor.filter_by(subsystem='sound') self._observer = MonitorObserver(self._monitor) self._observer.connect('device-event', callback) def start(self): log.debug("Starting AlsaDevMonitor...") self._monitor.start()
# -*- coding: utf-8 -*- """Set up an udev monitor to be notified about changes in attached sound devices.""" import logging from pyudev import Context, Monitor from .pyudev_gobject import MonitorObserver log = logging.getLogger(__name__) class AlsaDevMonitor: def __init__(self, callback): # set up udev device monitor context = Context() self._monitor = Monitor.from_netlink(context) self._monitor.filter_by(subsystem='sound') self._observer = MonitorObserver(self._monitor) self._observer.connect('device-event', callback) def start(self): log.debug("Starting AlsaDevMonitor...") self._monitor.start()
en
0.806524
# -*- coding: utf-8 -*- Set up an udev monitor to be notified about changes in attached sound devices. # set up udev device monitor
2.611645
3
objectModel/Python/cdm/objectmodel/cdm_folder_collection.py
Venkata1920/CDM
1
6632240
<reponame>Venkata1920/CDM # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. from typing import Union, List from cdm.enums import CdmObjectType from .cdm_collection import CdmCollection class CdmFolderCollection(CdmCollection): def __init__(self, ctx: 'CdmCorpusContext', owner: 'CdmObject'): super().__init__(ctx, owner, CdmObjectType.FOLDER_DEF) def append(self, obj: Union[str, 'CdmFolderDefinition']) -> 'CdmFolderDefinition': if isinstance(obj, str): return self.append(self.ctx.corpus.make_object(self.default_type, obj)) self._add_item_modifications(obj) return super().append(obj) def insert(self, index: int, obj: 'CdmFolderDefinition') -> None: self._add_item_modifications(obj) super().insert(index, obj) def extend(self, folder_list: List['CdmFolderDefinition']) -> None: for folder in folder_list: self.append(folder) def _add_item_modifications(self, obj: 'CdmFolderDefinition') -> None: obj._corpus = self.owner._corpus obj.namespace = self.owner.namespace obj.folder_path = '{}{}/'.format(self.owner.folder_path, obj.name) # TODO: At this point we should also propagate the root adapter into the child folder # and all its sub-folders and contained documents. For now, don't add things to the # folder unless it's tied to an adapter root. @property def _owner(self) -> 'CdmFolderDefinition': return super().owner
# Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. from typing import Union, List from cdm.enums import CdmObjectType from .cdm_collection import CdmCollection class CdmFolderCollection(CdmCollection): def __init__(self, ctx: 'CdmCorpusContext', owner: 'CdmObject'): super().__init__(ctx, owner, CdmObjectType.FOLDER_DEF) def append(self, obj: Union[str, 'CdmFolderDefinition']) -> 'CdmFolderDefinition': if isinstance(obj, str): return self.append(self.ctx.corpus.make_object(self.default_type, obj)) self._add_item_modifications(obj) return super().append(obj) def insert(self, index: int, obj: 'CdmFolderDefinition') -> None: self._add_item_modifications(obj) super().insert(index, obj) def extend(self, folder_list: List['CdmFolderDefinition']) -> None: for folder in folder_list: self.append(folder) def _add_item_modifications(self, obj: 'CdmFolderDefinition') -> None: obj._corpus = self.owner._corpus obj.namespace = self.owner.namespace obj.folder_path = '{}{}/'.format(self.owner.folder_path, obj.name) # TODO: At this point we should also propagate the root adapter into the child folder # and all its sub-folders and contained documents. For now, don't add things to the # folder unless it's tied to an adapter root. @property def _owner(self) -> 'CdmFolderDefinition': return super().owner
en
0.904216
# Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # TODO: At this point we should also propagate the root adapter into the child folder # and all its sub-folders and contained documents. For now, don't add things to the # folder unless it's tied to an adapter root.
2.031296
2
python/day10.py
JohanWranker/advent-of-code-2020
0
6632241
<filename>python/day10.py<gh_stars>0 import os import re from datetime import datetime import time print("day10") path = "input" if not os.path.exists(path): print(" File not exist ", os.path.abspath(path)) exit(1) rawtext = open(path).readlines() # Get all joltage all inital 0 and sort it data = sorted([0] + [int(x) for x in rawtext]) # List with "next" joltage - include output which is last +3 next =data[1:] + [data[-1]+3] # Make a difflist diff = [y-x for x,y in zip(data, next)] print(f"first mission {diff.count(1)*diff.count(3)}") assert 2210 == diff.count(1)*diff.count(3) #dict over the paths to the device, add the last jolt which has 1 exit path paths = {data[-1] : 1} for val in reversed(data[0:-1]): # handle the jolts starting at the last-but-one paths[val] = 0 # Test each jolt with offset 1-3 for step in [1,2,3]: if val+step in paths: # New path found, add based on the number of way "next step" has paths[val] += paths[val+step] print(f"ways {paths[0]} ") assert 7086739046912 == paths[0]
<filename>python/day10.py<gh_stars>0 import os import re from datetime import datetime import time print("day10") path = "input" if not os.path.exists(path): print(" File not exist ", os.path.abspath(path)) exit(1) rawtext = open(path).readlines() # Get all joltage all inital 0 and sort it data = sorted([0] + [int(x) for x in rawtext]) # List with "next" joltage - include output which is last +3 next =data[1:] + [data[-1]+3] # Make a difflist diff = [y-x for x,y in zip(data, next)] print(f"first mission {diff.count(1)*diff.count(3)}") assert 2210 == diff.count(1)*diff.count(3) #dict over the paths to the device, add the last jolt which has 1 exit path paths = {data[-1] : 1} for val in reversed(data[0:-1]): # handle the jolts starting at the last-but-one paths[val] = 0 # Test each jolt with offset 1-3 for step in [1,2,3]: if val+step in paths: # New path found, add based on the number of way "next step" has paths[val] += paths[val+step] print(f"ways {paths[0]} ") assert 7086739046912 == paths[0]
en
0.918999
# Get all joltage all inital 0 and sort it # List with "next" joltage - include output which is last +3 # Make a difflist #dict over the paths to the device, add the last jolt which has 1 exit path # handle the jolts starting at the last-but-one # Test each jolt with offset 1-3 # New path found, add based on the number of way "next step" has
3.072922
3
Test/test_DirtyWordOfFilter.py
Rainstyd/rainsty
1
6632242
<filename>Test/test_DirtyWordOfFilter.py # test_DirtyWordOfFilter.py from Algorithm.DirtyWordOfFilter import DFAFilter import time def main(): time1 = time.time() gfw = DFAFilter() text = "你真是个大傻逼,大傻子,傻大个,大坏蛋,坏人。乱交, 乱小" result = gfw.filter(text) print(text) print(result) time2 = time.time() print('总共耗时:' + str(time2 - time1) + 's') if __name__ == '__main__': main()
<filename>Test/test_DirtyWordOfFilter.py # test_DirtyWordOfFilter.py from Algorithm.DirtyWordOfFilter import DFAFilter import time def main(): time1 = time.time() gfw = DFAFilter() text = "你真是个大傻逼,大傻子,傻大个,大坏蛋,坏人。乱交, 乱小" result = gfw.filter(text) print(text) print(result) time2 = time.time() print('总共耗时:' + str(time2 - time1) + 's') if __name__ == '__main__': main()
en
0.170308
# test_DirtyWordOfFilter.py
2.89309
3
models/shum/ashum.py
INTENS-FI/intens
0
6632243
"""Attempt to use asyncio. Failed because asyncio subprocess support requires setup in the main thread, which we do not control in the Dask worker. """ from concurrent.futures import CancelledError import asyncio, os, traceback as tb import dask async def run_it(spec): #TODO script = os.path.join(os.path.dirname(__file__), "sum.sh") proc = await asyncio.create_subprocess_exec( script, *(str(spec.inputs[n]) for n in ['x', 'y']), cwd=spec.workdir) out, err = await proc.communicate() if err: raise RuntimeError(err) else: return {'sum': int(out)} async def poll_cancel(run, cancel): while not cancel.get(): await asyncio.sleep(5) run.cancel() async def main(spec, cancel): run = asyncio.ensure_future(run_it(spec)) watch = asyncio.ensure_future(poll_cancel(run, cancel)) try: return await run finally: watch.cancel() @dask.delayed def task(spec, cancel): try: loop = asyncio.get_event_loop() return loop.run_until_complete(main(spec, cancel)) except: tb.print_exc() raise
"""Attempt to use asyncio. Failed because asyncio subprocess support requires setup in the main thread, which we do not control in the Dask worker. """ from concurrent.futures import CancelledError import asyncio, os, traceback as tb import dask async def run_it(spec): #TODO script = os.path.join(os.path.dirname(__file__), "sum.sh") proc = await asyncio.create_subprocess_exec( script, *(str(spec.inputs[n]) for n in ['x', 'y']), cwd=spec.workdir) out, err = await proc.communicate() if err: raise RuntimeError(err) else: return {'sum': int(out)} async def poll_cancel(run, cancel): while not cancel.get(): await asyncio.sleep(5) run.cancel() async def main(spec, cancel): run = asyncio.ensure_future(run_it(spec)) watch = asyncio.ensure_future(poll_cancel(run, cancel)) try: return await run finally: watch.cancel() @dask.delayed def task(spec, cancel): try: loop = asyncio.get_event_loop() return loop.run_until_complete(main(spec, cancel)) except: tb.print_exc() raise
en
0.871562
Attempt to use asyncio. Failed because asyncio subprocess support requires setup in the main thread, which we do not control in the Dask worker. #TODO
2.497871
2
gdc_rnaseq_tools/merge_junctions.py
NCI-GDC/gdc-rnaseq-tool
0
6632244
"""A gdc-rnaseq-tools subcommand to format and merge STAR junction counts files from the same sample. @author: <NAME> <<EMAIL>> """ from operator import itemgetter from gdc_rnaseq_tools.utils import get_logger, get_open_function COLUMN_NAMES = [ "chromosome", "intron_start", "intron_end", "strand", "intron_motif", "annotation", "n_unique_map", "n_multi_map", "max_splice_overhang", ] class StarJunctionRecord: """Represents a row in the SJ file""" def __init__( self, chromosome, intron_first, intron_last, strand, motif, annotation, n_unique_mapped, n_multi_mapped, max_splice_overhang, ): self.chromosome = chromosome self.intron_first = int(intron_first) self.intron_last = int(intron_last) self.strand = int(strand) self.motif = int(motif) self.annotation = int(annotation) self.n_unique_mapped = int(n_unique_mapped) self.n_multi_mapped = int(n_multi_mapped) self.max_splice_overhang = int(max_splice_overhang) @property def key(self): """ The first six columns are the identifiers and are used to match between input files. """ return ( self.chromosome, self.intron_first, self.intron_last, self.strand, self.motif, self.annotation, ) @classmethod def from_line(cls, line): """ Initialize record from a line. """ return cls(*line.rstrip("\r\n").split("\t")) def __iadd__(self, other): """ Used to merge overlapping records by adding the appropriate columns and getting the max of the splice overhang column. """ assert self.key == other.key self.n_unique_mapped += other.n_unique_mapped self.n_multi_mapped += other.n_multi_mapped self.max_splice_overhang = max( self.max_splice_overhang, other.max_splice_overhang ) return self def __str__(self): return "\t".join( map( str, [ self.chromosome, self.intron_first, self.intron_last, self.strand, self.motif, self.annotation, self.n_unique_mapped, self.n_multi_mapped, self.max_splice_overhang, ], ) ) def process_files(args, logger): """ All the logic for formatting/merging STAR junction counts. :param args: argparser :param logger: `logging.Logger` instance """ writer = get_open_function(args.output) logger.info("Writing outputs to {0}".format(args.output)) with writer(args.output, "wt") as o: # Write header row as comment o.write("#" + "\t".join(COLUMN_NAMES) + "\n") if len(args.input) > 1: logger.info("Merging {0} STAR gene counts files.".format(len(args.input))) # Load dic = dict() for fil in args.input: dic = load_junction_file(fil, dic) logger.info( "Writing merged STAR junction counts to {0}.".format(args.output) ) # Merge and write for key in sorted(dic, key=itemgetter(0, 1, 2)): o.write(str(dic[key]) + "\n") else: logger.info( "Only 1 STAR junction counts file provided. " + "A new STAR junction counts file will be produced " + "with a header line." ) logger.info( "Writing formatted STAR junction " + "counts to {0}.".format(args.output) ) fil = args.input[0] reader = get_open_function(fil) with reader(fil, "rt") as fh: for line in fh: o.write(line) def load_junction_file(fil, dic): """ Load star junction file into a dictionary. :param fil: path to STAR counts file to load :param dic: dict to load file to :returns: updated dictionary """ reader = get_open_function(fil) with reader(fil, "rt") as fh: for line in fh: rec = StarJunctionRecord.from_line(line) if rec.key not in dic: dic[rec.key] = rec else: dic[rec.key] += rec return dic def main(args): """ Main entrypoint for merge_star_gene_counts. """ logger = get_logger("merge_star_junction_counts") logger.info( "Merging/Formatting {0} STAR junction counts files.".format(len(args.input)) ) process_files(args, logger)
"""A gdc-rnaseq-tools subcommand to format and merge STAR junction counts files from the same sample. @author: <NAME> <<EMAIL>> """ from operator import itemgetter from gdc_rnaseq_tools.utils import get_logger, get_open_function COLUMN_NAMES = [ "chromosome", "intron_start", "intron_end", "strand", "intron_motif", "annotation", "n_unique_map", "n_multi_map", "max_splice_overhang", ] class StarJunctionRecord: """Represents a row in the SJ file""" def __init__( self, chromosome, intron_first, intron_last, strand, motif, annotation, n_unique_mapped, n_multi_mapped, max_splice_overhang, ): self.chromosome = chromosome self.intron_first = int(intron_first) self.intron_last = int(intron_last) self.strand = int(strand) self.motif = int(motif) self.annotation = int(annotation) self.n_unique_mapped = int(n_unique_mapped) self.n_multi_mapped = int(n_multi_mapped) self.max_splice_overhang = int(max_splice_overhang) @property def key(self): """ The first six columns are the identifiers and are used to match between input files. """ return ( self.chromosome, self.intron_first, self.intron_last, self.strand, self.motif, self.annotation, ) @classmethod def from_line(cls, line): """ Initialize record from a line. """ return cls(*line.rstrip("\r\n").split("\t")) def __iadd__(self, other): """ Used to merge overlapping records by adding the appropriate columns and getting the max of the splice overhang column. """ assert self.key == other.key self.n_unique_mapped += other.n_unique_mapped self.n_multi_mapped += other.n_multi_mapped self.max_splice_overhang = max( self.max_splice_overhang, other.max_splice_overhang ) return self def __str__(self): return "\t".join( map( str, [ self.chromosome, self.intron_first, self.intron_last, self.strand, self.motif, self.annotation, self.n_unique_mapped, self.n_multi_mapped, self.max_splice_overhang, ], ) ) def process_files(args, logger): """ All the logic for formatting/merging STAR junction counts. :param args: argparser :param logger: `logging.Logger` instance """ writer = get_open_function(args.output) logger.info("Writing outputs to {0}".format(args.output)) with writer(args.output, "wt") as o: # Write header row as comment o.write("#" + "\t".join(COLUMN_NAMES) + "\n") if len(args.input) > 1: logger.info("Merging {0} STAR gene counts files.".format(len(args.input))) # Load dic = dict() for fil in args.input: dic = load_junction_file(fil, dic) logger.info( "Writing merged STAR junction counts to {0}.".format(args.output) ) # Merge and write for key in sorted(dic, key=itemgetter(0, 1, 2)): o.write(str(dic[key]) + "\n") else: logger.info( "Only 1 STAR junction counts file provided. " + "A new STAR junction counts file will be produced " + "with a header line." ) logger.info( "Writing formatted STAR junction " + "counts to {0}.".format(args.output) ) fil = args.input[0] reader = get_open_function(fil) with reader(fil, "rt") as fh: for line in fh: o.write(line) def load_junction_file(fil, dic): """ Load star junction file into a dictionary. :param fil: path to STAR counts file to load :param dic: dict to load file to :returns: updated dictionary """ reader = get_open_function(fil) with reader(fil, "rt") as fh: for line in fh: rec = StarJunctionRecord.from_line(line) if rec.key not in dic: dic[rec.key] = rec else: dic[rec.key] += rec return dic def main(args): """ Main entrypoint for merge_star_gene_counts. """ logger = get_logger("merge_star_junction_counts") logger.info( "Merging/Formatting {0} STAR junction counts files.".format(len(args.input)) ) process_files(args, logger)
en
0.83875
A gdc-rnaseq-tools subcommand to format and merge STAR junction counts files from the same sample. @author: <NAME> <<EMAIL>> Represents a row in the SJ file The first six columns are the identifiers and are used to match between input files. Initialize record from a line. Used to merge overlapping records by adding the appropriate columns and getting the max of the splice overhang column. All the logic for formatting/merging STAR junction counts. :param args: argparser :param logger: `logging.Logger` instance # Write header row as comment # Load # Merge and write Load star junction file into a dictionary. :param fil: path to STAR counts file to load :param dic: dict to load file to :returns: updated dictionary Main entrypoint for merge_star_gene_counts.
2.902023
3
django_messages/forms.py
mirumee/django-messages
16
6632245
<reponame>mirumee/django-messages<filename>django_messages/forms.py import datetime from django import forms from django.conf import settings from django.utils.translation import ugettext_lazy as _ from django.utils.translation import ugettext_noop from django.contrib.auth.models import User import uuid if "notification" in settings.INSTALLED_APPS: from notification import models as notification else: notification = None from django_messages.models import Message from django_messages.fields import CommaSeparatedUserField from django_messages.utils import format_quote class MessageForm(forms.ModelForm): """ base message form """ recipients = CommaSeparatedUserField(label=_(u"Recipient")) subject = forms.CharField(label=_(u"Subject")) body = forms.CharField(label=_(u"Body"), widget=forms.Textarea(attrs={'rows': '12', 'cols':'55'})) class Meta: model = Message fields = ('recipients', 'subject', 'body',) def __init__(self, sender, *args, **kw): recipient_filter = kw.pop('recipient_filter', None) self.sender = sender super(MessageForm, self).__init__(*args, **kw) if recipient_filter is not None: self.fields['recipients']._recipient_filter = recipient_filter def create_recipient_message(self, recipient, message): return Message( owner = recipient, sender = self.sender, to = recipient.username, recipient = recipient, subject = message.subject, body = message.body, thread = message.thread, sent_at = message.sent_at, ) def get_thread(self, message): return message.thread or uuid.uuid4().hex def save(self, commit=True): recipients = self.cleaned_data['recipients'] instance = super(MessageForm, self).save(commit=False) instance.sender = self.sender instance.owner = self.sender instance.recipient = recipients[0] instance.thread = self.get_thread(instance) instance.unread = False instance.sent_at = datetime.datetime.now() message_list = [] # clone messages in recipients inboxes for r in recipients: if r == self.sender: # skip duplicates continue msg = self.create_recipient_message(r, instance) message_list.append(msg) instance.to = ','.join([r.username for r in recipients]) if commit: instance.save() for msg in message_list: msg.save() if notification: notification.send([msg.recipient], "messages_received", {'message': msg,}) return instance, message_list class ComposeForm(MessageForm): """ A simple default form for private messages. """ class Meta: model = Message fields = ('recipients', 'subject', 'body',) class ReplyForm(MessageForm): """ reply to form """ class Meta: model = Message fields = ('recipients', 'subject', 'body',) def __init__(self, sender, message, *args, **kw): self.parent_message = message initial = kw.pop('initial', {}) initial['recipients'] = message.sender.username initial['body'] = self.quote_message(message) initial['subject'] = self.quote_subject(message.subject) kw['initial'] = initial super(ReplyForm, self).__init__(sender, *args, **kw) def quote_message(self, original_message): return format_quote(original_message.sender, original_message.body) def quote_subject(self, subject): return u'Re: %s' % subject def create_recipient_message(self, recipient, message): msg = super(ReplyForm, self).create_recipient_message(recipient, message) msg.replied_at = datetime.datetime.now() # find parent in recipient messages try: msg.parent_msg = Message.objects.get( owner=recipient, sender=message.recipient, recipient=message.sender, thread=message.thread) except (Message.DoesNotExist, Message.MultipleObjectsReturned): # message may be deleted pass return msg def get_thread(self, message): return self.parent_message.thread def save(self, commit=True): instance, message_list = super(ReplyForm, self).save(commit=False) instance.replied_at = datetime.datetime.now() instance.parent_msg = self.parent_message if commit: instance.save() for msg in message_list: msg.save() if notification: notification.send([msg.recipient], "messages_reply_received", { 'message': msg, 'parent_msg': self.parent_message, }) return instance, message_list
import datetime from django import forms from django.conf import settings from django.utils.translation import ugettext_lazy as _ from django.utils.translation import ugettext_noop from django.contrib.auth.models import User import uuid if "notification" in settings.INSTALLED_APPS: from notification import models as notification else: notification = None from django_messages.models import Message from django_messages.fields import CommaSeparatedUserField from django_messages.utils import format_quote class MessageForm(forms.ModelForm): """ base message form """ recipients = CommaSeparatedUserField(label=_(u"Recipient")) subject = forms.CharField(label=_(u"Subject")) body = forms.CharField(label=_(u"Body"), widget=forms.Textarea(attrs={'rows': '12', 'cols':'55'})) class Meta: model = Message fields = ('recipients', 'subject', 'body',) def __init__(self, sender, *args, **kw): recipient_filter = kw.pop('recipient_filter', None) self.sender = sender super(MessageForm, self).__init__(*args, **kw) if recipient_filter is not None: self.fields['recipients']._recipient_filter = recipient_filter def create_recipient_message(self, recipient, message): return Message( owner = recipient, sender = self.sender, to = recipient.username, recipient = recipient, subject = message.subject, body = message.body, thread = message.thread, sent_at = message.sent_at, ) def get_thread(self, message): return message.thread or uuid.uuid4().hex def save(self, commit=True): recipients = self.cleaned_data['recipients'] instance = super(MessageForm, self).save(commit=False) instance.sender = self.sender instance.owner = self.sender instance.recipient = recipients[0] instance.thread = self.get_thread(instance) instance.unread = False instance.sent_at = datetime.datetime.now() message_list = [] # clone messages in recipients inboxes for r in recipients: if r == self.sender: # skip duplicates continue msg = self.create_recipient_message(r, instance) message_list.append(msg) instance.to = ','.join([r.username for r in recipients]) if commit: instance.save() for msg in message_list: msg.save() if notification: notification.send([msg.recipient], "messages_received", {'message': msg,}) return instance, message_list class ComposeForm(MessageForm): """ A simple default form for private messages. """ class Meta: model = Message fields = ('recipients', 'subject', 'body',) class ReplyForm(MessageForm): """ reply to form """ class Meta: model = Message fields = ('recipients', 'subject', 'body',) def __init__(self, sender, message, *args, **kw): self.parent_message = message initial = kw.pop('initial', {}) initial['recipients'] = message.sender.username initial['body'] = self.quote_message(message) initial['subject'] = self.quote_subject(message.subject) kw['initial'] = initial super(ReplyForm, self).__init__(sender, *args, **kw) def quote_message(self, original_message): return format_quote(original_message.sender, original_message.body) def quote_subject(self, subject): return u'Re: %s' % subject def create_recipient_message(self, recipient, message): msg = super(ReplyForm, self).create_recipient_message(recipient, message) msg.replied_at = datetime.datetime.now() # find parent in recipient messages try: msg.parent_msg = Message.objects.get( owner=recipient, sender=message.recipient, recipient=message.sender, thread=message.thread) except (Message.DoesNotExist, Message.MultipleObjectsReturned): # message may be deleted pass return msg def get_thread(self, message): return self.parent_message.thread def save(self, commit=True): instance, message_list = super(ReplyForm, self).save(commit=False) instance.replied_at = datetime.datetime.now() instance.parent_msg = self.parent_message if commit: instance.save() for msg in message_list: msg.save() if notification: notification.send([msg.recipient], "messages_reply_received", { 'message': msg, 'parent_msg': self.parent_message, }) return instance, message_list
en
0.729635
base message form # clone messages in recipients inboxes # skip duplicates A simple default form for private messages. reply to form # find parent in recipient messages # message may be deleted
2.09474
2
Examples/Physics_applications/laser_acceleration/PICMI_inputs_3d.py
Alpine-DAV/WarpX
0
6632246
<gh_stars>0 #!/usr/bin/env python3 from pywarpx import picmi # Physical constants c = picmi.constants.c q_e = picmi.constants.q_e # Number of time steps max_steps = 100 # Number of cells nx = 32 ny = 32 nz = 256 # Physical domain xmin = -30e-06 xmax = 30e-06 ymin = -30e-06 ymax = 30e-06 zmin = -56e-06 zmax = 12e-06 # Domain decomposition max_grid_size = 64 blocking_factor = 32 # Create grid grid = picmi.Cartesian3DGrid( number_of_cells = [nx, ny, nz], lower_bound = [xmin, ymin, zmin], upper_bound = [xmax, ymax, zmax], lower_boundary_conditions = ['periodic', 'periodic', 'dirichlet'], upper_boundary_conditions = ['periodic', 'periodic', 'dirichlet'], lower_boundary_conditions_particles = ['periodic', 'periodic', 'absorbing'], upper_boundary_conditions_particles = ['periodic', 'periodic', 'absorbing'], moving_window_velocity = [0., 0., c], warpx_max_grid_size = max_grid_size, warpx_blocking_factor = blocking_factor) # Particles: plasma electrons plasma_density = 2e23 plasma_xmin = -20e-06 plasma_ymin = -20e-06 plasma_zmin = 0 plasma_xmax = 20e-06 plasma_ymax = 20e-06 plasma_zmax = None uniform_distribution = picmi.UniformDistribution( density = plasma_density, lower_bound = [plasma_xmin, plasma_ymin, plasma_zmin], upper_bound = [plasma_xmax, plasma_ymax, plasma_zmax], fill_in = True) electrons = picmi.Species( particle_type = 'electron', name = 'electrons', initial_distribution = uniform_distribution) # Particles: beam electrons q_tot = 1e-12 x_m = 0. y_m = 0. z_m = -28e-06 x_rms = 0.5e-06 y_rms = 0.5e-06 z_rms = 0.5e-06 ux_m = 0. uy_m = 0. uz_m = 500. ux_th = 2. uy_th = 2. uz_th = 50. gaussian_bunch_distribution = picmi.GaussianBunchDistribution( n_physical_particles = q_tot / q_e, rms_bunch_size = [x_rms, y_rms, z_rms], rms_velocity = [c*ux_th, c*uy_th, c*uz_th], centroid_position = [x_m, y_m, z_m], centroid_velocity = [c*ux_m, c*uy_m, c*uz_m]) beam = picmi.Species( particle_type = 'electron', name = 'beam', initial_distribution = gaussian_bunch_distribution) # Laser e_max = 16e12 position_z = 9e-06 profile_t_peak = 30.e-15 profile_focal_distance = 100e-06 laser = picmi.GaussianLaser( wavelength = 0.8e-06, waist = 5e-06, duration = 15e-15, focal_position = [0, 0, profile_focal_distance + position_z], centroid_position = [0, 0, position_z - c*profile_t_peak], propagation_direction = [0, 0, 1], polarization_direction = [0, 1, 0], E0 = e_max, fill_in = False) laser_antenna = picmi.LaserAntenna( position = [0., 0., position_z], normal_vector = [0, 0, 1]) # Electromagnetic solver solver = picmi.ElectromagneticSolver( grid = grid, method = 'Yee', cfl = 1., divE_cleaning = 0) # Diagnostics diag_field_list = ['B', 'E', 'J', 'rho'] field_diag = picmi.FieldDiagnostic( name = 'diag1', grid = grid, period = 100, data_list = diag_field_list, write_dir = '.', warpx_file_prefix = 'Python_LaserAcceleration_plt') # Set up simulation sim = picmi.Simulation( solver = solver, max_steps = max_steps, verbose = 1, particle_shape = 'cubic', warpx_use_filter = 1, warpx_serialize_ics = 1, warpx_do_dynamic_scheduling = 0) # Add plasma electrons sim.add_species( electrons, layout = picmi.GriddedLayout(grid = grid, n_macroparticle_per_cell = [1, 1, 1])) # Add beam electrons sim.add_species( beam, layout = picmi.PseudoRandomLayout(grid = grid, n_macroparticles = 100)) # Add laser sim.add_laser( laser, injection_method = laser_antenna) # Add diagnostics sim.add_diagnostic(field_diag) # Write input file that can be used to run with the compiled version sim.write_input_file(file_name = 'inputs_3d_picmi') # Initialize inputs and WarpX instance sim.initialize_inputs() sim.initialize_warpx() # Advance simulation until last time step sim.step(max_steps)
#!/usr/bin/env python3 from pywarpx import picmi # Physical constants c = picmi.constants.c q_e = picmi.constants.q_e # Number of time steps max_steps = 100 # Number of cells nx = 32 ny = 32 nz = 256 # Physical domain xmin = -30e-06 xmax = 30e-06 ymin = -30e-06 ymax = 30e-06 zmin = -56e-06 zmax = 12e-06 # Domain decomposition max_grid_size = 64 blocking_factor = 32 # Create grid grid = picmi.Cartesian3DGrid( number_of_cells = [nx, ny, nz], lower_bound = [xmin, ymin, zmin], upper_bound = [xmax, ymax, zmax], lower_boundary_conditions = ['periodic', 'periodic', 'dirichlet'], upper_boundary_conditions = ['periodic', 'periodic', 'dirichlet'], lower_boundary_conditions_particles = ['periodic', 'periodic', 'absorbing'], upper_boundary_conditions_particles = ['periodic', 'periodic', 'absorbing'], moving_window_velocity = [0., 0., c], warpx_max_grid_size = max_grid_size, warpx_blocking_factor = blocking_factor) # Particles: plasma electrons plasma_density = 2e23 plasma_xmin = -20e-06 plasma_ymin = -20e-06 plasma_zmin = 0 plasma_xmax = 20e-06 plasma_ymax = 20e-06 plasma_zmax = None uniform_distribution = picmi.UniformDistribution( density = plasma_density, lower_bound = [plasma_xmin, plasma_ymin, plasma_zmin], upper_bound = [plasma_xmax, plasma_ymax, plasma_zmax], fill_in = True) electrons = picmi.Species( particle_type = 'electron', name = 'electrons', initial_distribution = uniform_distribution) # Particles: beam electrons q_tot = 1e-12 x_m = 0. y_m = 0. z_m = -28e-06 x_rms = 0.5e-06 y_rms = 0.5e-06 z_rms = 0.5e-06 ux_m = 0. uy_m = 0. uz_m = 500. ux_th = 2. uy_th = 2. uz_th = 50. gaussian_bunch_distribution = picmi.GaussianBunchDistribution( n_physical_particles = q_tot / q_e, rms_bunch_size = [x_rms, y_rms, z_rms], rms_velocity = [c*ux_th, c*uy_th, c*uz_th], centroid_position = [x_m, y_m, z_m], centroid_velocity = [c*ux_m, c*uy_m, c*uz_m]) beam = picmi.Species( particle_type = 'electron', name = 'beam', initial_distribution = gaussian_bunch_distribution) # Laser e_max = 16e12 position_z = 9e-06 profile_t_peak = 30.e-15 profile_focal_distance = 100e-06 laser = picmi.GaussianLaser( wavelength = 0.8e-06, waist = 5e-06, duration = 15e-15, focal_position = [0, 0, profile_focal_distance + position_z], centroid_position = [0, 0, position_z - c*profile_t_peak], propagation_direction = [0, 0, 1], polarization_direction = [0, 1, 0], E0 = e_max, fill_in = False) laser_antenna = picmi.LaserAntenna( position = [0., 0., position_z], normal_vector = [0, 0, 1]) # Electromagnetic solver solver = picmi.ElectromagneticSolver( grid = grid, method = 'Yee', cfl = 1., divE_cleaning = 0) # Diagnostics diag_field_list = ['B', 'E', 'J', 'rho'] field_diag = picmi.FieldDiagnostic( name = 'diag1', grid = grid, period = 100, data_list = diag_field_list, write_dir = '.', warpx_file_prefix = 'Python_LaserAcceleration_plt') # Set up simulation sim = picmi.Simulation( solver = solver, max_steps = max_steps, verbose = 1, particle_shape = 'cubic', warpx_use_filter = 1, warpx_serialize_ics = 1, warpx_do_dynamic_scheduling = 0) # Add plasma electrons sim.add_species( electrons, layout = picmi.GriddedLayout(grid = grid, n_macroparticle_per_cell = [1, 1, 1])) # Add beam electrons sim.add_species( beam, layout = picmi.PseudoRandomLayout(grid = grid, n_macroparticles = 100)) # Add laser sim.add_laser( laser, injection_method = laser_antenna) # Add diagnostics sim.add_diagnostic(field_diag) # Write input file that can be used to run with the compiled version sim.write_input_file(file_name = 'inputs_3d_picmi') # Initialize inputs and WarpX instance sim.initialize_inputs() sim.initialize_warpx() # Advance simulation until last time step sim.step(max_steps)
en
0.637696
#!/usr/bin/env python3 # Physical constants # Number of time steps # Number of cells # Physical domain # Domain decomposition # Create grid # Particles: plasma electrons # Particles: beam electrons # Laser # Electromagnetic solver # Diagnostics # Set up simulation # Add plasma electrons # Add beam electrons # Add laser # Add diagnostics # Write input file that can be used to run with the compiled version # Initialize inputs and WarpX instance # Advance simulation until last time step
1.855406
2
Examples/input_text_example.py
mmorandi/DearPyGui
0
6632247
<filename>Examples/input_text_example.py from dearpygui.core import * from dearpygui.simple import * set_main_window_size(500, 500) # callback def retrieve_callback(sender, callback): show_logger() log_info(get_value("Regular##inputtext")) log_info(get_value("With hint##inputtext")) log_info(get_value("No spaces##inputtext")) log_info(get_value("Uppercase##inputtext")) log_info(get_value("Decimal##inputtext")) log_info(get_value("Hexadecimal##inputtext")) log_info(get_value("Read Only##inputtext")) log_info(get_value("Password##inputtext")) log_info(get_value("Multiline##inputtext")) add_text("This example demonstrates the input text widget.", bullet=True) add_text("Press the 'Retrieve' button to display the inputed values in the logger", wrap = 500, bullet=True) add_input_text("Regular##inputtext") add_input_text("With hint##inputtext", hint="A hint") add_input_text("No spaces##inputtext", no_spaces=True) add_input_text("Uppercase##inputtext", uppercase=True) add_input_text("Decimal##inputtext", decimal=True) add_input_text("Hexadecimal##inputtext", hexadecimal=True) add_input_text("Read Only##inputtext", readonly=True, default_value="read only") add_input_text("Password##inputtext", password=True) add_input_text("Multiline##inputtext", multiline=True) add_button("Retrieve", callback=retrieve_callback) start_dearpygui()
<filename>Examples/input_text_example.py from dearpygui.core import * from dearpygui.simple import * set_main_window_size(500, 500) # callback def retrieve_callback(sender, callback): show_logger() log_info(get_value("Regular##inputtext")) log_info(get_value("With hint##inputtext")) log_info(get_value("No spaces##inputtext")) log_info(get_value("Uppercase##inputtext")) log_info(get_value("Decimal##inputtext")) log_info(get_value("Hexadecimal##inputtext")) log_info(get_value("Read Only##inputtext")) log_info(get_value("Password##inputtext")) log_info(get_value("Multiline##inputtext")) add_text("This example demonstrates the input text widget.", bullet=True) add_text("Press the 'Retrieve' button to display the inputed values in the logger", wrap = 500, bullet=True) add_input_text("Regular##inputtext") add_input_text("With hint##inputtext", hint="A hint") add_input_text("No spaces##inputtext", no_spaces=True) add_input_text("Uppercase##inputtext", uppercase=True) add_input_text("Decimal##inputtext", decimal=True) add_input_text("Hexadecimal##inputtext", hexadecimal=True) add_input_text("Read Only##inputtext", readonly=True, default_value="read only") add_input_text("Password##inputtext", password=True) add_input_text("Multiline##inputtext", multiline=True) add_button("Retrieve", callback=retrieve_callback) start_dearpygui()
ja
0.37475
# callback ##inputtext")) ##inputtext")) ##inputtext")) ##inputtext")) ##inputtext")) ##inputtext")) ##inputtext")) ##inputtext")) ##inputtext")) ##inputtext") ##inputtext", hint="A hint") ##inputtext", no_spaces=True) ##inputtext", uppercase=True) ##inputtext", decimal=True) ##inputtext", hexadecimal=True) ##inputtext", readonly=True, default_value="read only") ##inputtext", password=True) ##inputtext", multiline=True)
3.228554
3
commands/setcannon.py
1757WestwoodRobotics/mentorbot
2
6632248
<reponame>1757WestwoodRobotics/mentorbot<gh_stars>1-10 from enum import Enum, auto from subsystems.cannonsubsystem import CannonSubsystem from commands2 import CommandBase class SetCannon(CommandBase): class Mode(Enum): Off = auto() Fill = auto() Launch = auto() def __init__(self, cannon: CannonSubsystem, mode: Mode) -> None: CommandBase.__init__(self) self.setName(__class__.__name__) self.cannon = cannon self.mode = mode self.addRequirements([self.cannon]) self.funcs = { SetCannon.Mode.Off: self.cannon.close, SetCannon.Mode.Fill: self.cannon.fill, SetCannon.Mode.Launch: self.cannon.launch } self.isFinished = lambda: True def execute(self) -> None: self.funcs[self.mode]()
from enum import Enum, auto from subsystems.cannonsubsystem import CannonSubsystem from commands2 import CommandBase class SetCannon(CommandBase): class Mode(Enum): Off = auto() Fill = auto() Launch = auto() def __init__(self, cannon: CannonSubsystem, mode: Mode) -> None: CommandBase.__init__(self) self.setName(__class__.__name__) self.cannon = cannon self.mode = mode self.addRequirements([self.cannon]) self.funcs = { SetCannon.Mode.Off: self.cannon.close, SetCannon.Mode.Fill: self.cannon.fill, SetCannon.Mode.Launch: self.cannon.launch } self.isFinished = lambda: True def execute(self) -> None: self.funcs[self.mode]()
none
1
2.769027
3
python-lib/org_manager_bot.py
abrazite/sc-org
0
6632249
import discord from discord.ext import commands, tasks import org_manager_api import theimc import secrets import string import os os.environ['REQUESTS_CA_BUNDLE'] = os.path.join( '/etc/ssl/certs/', 'ca-certificates.crt') # API Server API_SERVER = 'https://api.org-manager.space/1.0.0' api = org_manager_api.OrgManagerAPI(API_SERVER, secrets.ORGANIZATION_ID) # Prefix for calling bot in discord client = commands.Bot(command_prefix='.') # Runs on start to show bot is online @client.event async def on_ready(): await client.change_presence(status=discord.Status.online, activity=discord.Game('.help')) print("Bot is ready") app_info = await client.application_info() print(f'https://discord.com/oauth2/authorize?client_id={app_info.id}&bot') @client.command(brief='superadmin') async def create_theimc_from_discord(ctx): if ctx.author.name == 'abrazite': theimc.create_org(api, create_api_context(ctx)) @client.command(brief='superadmin') async def sync_theimc_from_discord(ctx): if ctx.author.name == 'abrazite': theimc.create_org(api, create_api_context(ctx)) theimc.sync_org(api, create_api_context(ctx), ctx.message.channel.guild.members) # Clear messages in chat @client.command(brief='superadmin') async def clear(ctx, amount=5): if ctx.author.name == 'abrazite': await ctx.channel.purge(limit=amount + 1) await ctx.send(f'{amount} Posts have been cleared') @client.command(brief='Reports when user joined the org') async def is_member(ctx, personnel_str): membership = api.membership(create_api_context(ctx), personnel_str) if membership: # todo(James): format date :) await ctx.send(f'joined {membership["joinedDate"]}') else: await ctx.send('no membership found') @client.command(brief='Shows basic personnel info') async def whois(ctx, *, personnel_str=None): if personnel_str: personnel = api.personnel_summary(create_api_context(ctx), personnel_str) else: personnel = api.personnel_summary(create_api_context(ctx), f'{ctx.author.name}#{ctx.author.discriminator}') if personnel: message_str = f'{full_formatted_nick(personnel)}\r' if personnel['username']: message_str += f'\rdiscord:\t {personnel["username"]}#{personnel["discriminator"]}' if personnel['citizenRecord']: message_str += f'\rcitizenRecord:\t {personnel["citizenRecord"]}' if personnel['citizenName']: message_str += f'\rcitizenName:\t {personnel["citizenName"]}' if personnel['handleName']: message_str += f'\rhandleName:\t {personnel["handleName"]}' message_str += '\r' if personnel['rankDate']: message_str += f'\rrankDate:\t {personnel["rankDate"]}' await ctx.send(message_str) else: await ctx.send('error: record not found') @client.command(brief='Lists all org branches') async def list_branches(ctx, page=0): LIMIT = 10 branches = api.branches(create_api_context(ctx), limit=LIMIT, page=page) branches_strs = '' if len(branches) == LIMIT or page > 0: branches_strs += f'(page {page})\r\r' for branch in branches: branch_str = branch["abbreviation"] if branch["branch"]: branch_str += '\t' + branch["branch"] + '\r' branches_strs += branch_str await ctx.send(branches_strs) @client.command(brief='Lists all org grades') async def list_grades(ctx, page=0): LIMIT = 10 grades = api.grades(create_api_context(ctx), limit=LIMIT, page=page) grades_strs = '' if len(grades) == LIMIT or page > 0: grades_strs += f'(page {page})\r\r' for grade in grades: grade_str = grade["abbreviation"] if grade["grade"]: grade_str += '\t' + grade["grade"] grades_strs += grade_str + '\r' await ctx.send(grades_strs) @client.command(brief='Lists all org ranks') async def list_ranks(ctx, page=0): LIMIT = 10 ranks = api.ranks(create_api_context(ctx), limit=LIMIT, page=page) ranks_strs = '' if len(ranks) == LIMIT or page > 0: ranks_strs += f'(page {page})\r\r' for rank in ranks: ranks_str = '' if rank["branchAbbreviation"]: ranks_str += rank["branchAbbreviation"] + '-' if rank["gradeAbbreviation"]: ranks_str += rank["gradeAbbreviation"] + '-' if rank["rankAbbreviation"]: ranks_str += rank["rankAbbreviation"] if rank["rankName"]: ranks_str += '\t' + rank["rankName"] ranks_strs += ranks_str + '\r' await ctx.send(ranks_strs) @client.command(brief='Lists all org certifications') async def list_certifications(ctx, page: int = 0): LIMIT = 10 certifications = api.certifications(create_api_context(ctx), limit=LIMIT, page=page) certifications_strs = '' if len(certifications) == LIMIT or page > 0: certifications_strs += f'(page {page})\r\r' for certification in certifications: certification_str = certification["abbreviation"] if certification["name"]: certification_str += '\t' + certification["name"] certifications_strs += certification_str + '\r' await ctx.send(certifications_strs) @client.command(brief='Lists all rank change records') async def list_rank_records(ctx, personnel_str: str = None, page: int = 0): LIMIT = 10 if personnel_str: personnel = api.personnel(create_api_context(ctx), personnel_str) else: personnel = api.personnel(create_api_context(ctx), f'{ctx.author.name}#{ctx.author.discriminator}') if personnel is None or 'rankChangeRecords' not in personnel: await ctx.send('error: no records found') return records = personnel['rankChangeRecords'] record_str = '' if len(records) == LIMIT or page > 0: record_str += f'(page {page})\r\r' for i, record in enumerate(records): if page * LIMIT <= i < (page + 1) * LIMIT: record_str += record['date'] if record['abbreviation']: record_str += '\t' + record['abbreviation'] record_str += '\r' await ctx.send(record_str) @client.command(brief='Lists all certification records') async def list_cert_records(ctx, personnel_str: str = None, page: int = 0): LIMIT = 10 if personnel_str: personnel = api.personnel(create_api_context(ctx), personnel_str) else: personnel = api.personnel(create_api_context(ctx), f'{ctx.author.name}#{ctx.author.discriminator}') if personnel is None or 'certificationRecords' not in personnel: await ctx.send('error: no records found') return records = personnel['certificationRecords'] record_str = '' if len(records) == LIMIT or page > 0: record_str += f'(page {page})\r\r' for i, record in enumerate(records): if page * LIMIT <= i < (page + 1) * LIMIT: record_str += record['date'] if record['abbreviation']: record_str += '\t' + record['abbreviation'] record_str += '\r' await ctx.send(record_str) @client.command(brief='Lists all ops attended by personnel') async def list_op_records(ctx, personnel_str: str = None, page: int = 0): LIMIT = 10 if personnel_str: personnel = api.personnel(create_api_context(ctx), personnel_str) else: personnel = api.personnel(create_api_context(ctx), f'{ctx.author.name}#{ctx.author.discriminator}') if personnel is None or 'operationAttendenceRecords' not in personnel: await ctx.send('error: no records found') return records = personnel['operationAttendenceRecords'] record_str = '' if len(records) == LIMIT or page > 0: record_str += f'(page {page})\r\r' for i, record in enumerate(records): if page * LIMIT <= i < (page + 1) * LIMIT: record_str += record['date'] if record['name']: record_str += '\t' + record['name'] record_str += '\r' await ctx.send(record_str) @client.command(brief='Lists all notes for personnel') async def list_note_records(ctx, personnel_str: str = None, page: int = 0): LIMIT = 10 if personnel_str: personnel = api.personnel(create_api_context(ctx), personnel_str) else: personnel = api.personnel(create_api_context(ctx), f'{ctx.author.name}#{ctx.author.discriminator}') if personnel is None or 'noteRecords' not in personnel: await ctx.send('error: no records found') return records = personnel['noteRecords'] record_str = '' if len(records) == LIMIT or page > 0: record_str += f'(page {page})\r\r' for i, record in enumerate(records): if page * LIMIT <= i < (page + 1) * LIMIT: record_str += record['date'] if record['note']: record_str += '\t' + record['note'] record_str += '\r' await ctx.send(record_str) @client.command(brief='Lists all personnel with filtering') async def search_personnel(ctx, filter_str=None, page=0): LIMIT = 10 summary = api.personnel_summary_all(create_api_context(ctx)) list_str = '' summary = sorted(summary, key=lambda e: formatted_nick(e)) count = 0 total_count = 0 for personnel in summary: include = filter_str is None include = include or (filter_str == personnel["gradeAbbreviation"]) include = include or (filter_str == personnel["branchAbbreviation"]) include = include or (filter_str == personnel["rankAbbreviation"]) include = include or (filter_str == f'{personnel["branchAbbreviation"]}-{personnel["gradeAbbreviation"]}-{personnel["rankAbbreviation"]}') include = include or (filter_str == f'{personnel["branchAbbreviation"]}-{personnel["rankAbbreviation"]}') include = include or (filter_str == f'{personnel["citizenRecord"]}') include = include or (filter_str == f'{personnel["citizenName"]}') include = include or (filter_str == f'{personnel["handleName"]}') include = include or (filter_str == f'{personnel["username"]}#{personnel["discriminator"]}') if include: total_count += 1 if include and count < LIMIT: list_str += f'{formatted_nick(personnel)}\r' count += 1 if total_count > LIMIT: total_pages = int(total_count / LIMIT) list_str = f'(page {page} of {total_pages})\r\r' + list_str list_str += '\r' await ctx.send(list_str) @client.command(brief='Create a new org branch') async def create_branch(ctx, abbreviation: str, branch: str = None): record_id = api.create_branch(create_api_context(ctx), abbreviation, branch) if record_id: await ctx.send(f'created branch {abbreviation}') else: await ctx.send('error: no branch created') @client.command(brief='Create a new org grade') async def create_grade(ctx, abbreviation: str, grade: str = None): record_id = api.create_grade(create_api_context(ctx), abbreviation, grade) if record_id: await ctx.send(f'created grade {abbreviation}') else: await ctx.send('error: no grade created') @client.command(brief='Create a new org grade') async def create_rank(ctx, abbreviation: str, rank: str = None, branch_str: str = None, grade_str: str = None): record_id = api.create_rank(create_api_context(ctx), abbreviation, rank, branch_str, grade_str) if record_id: await ctx.send(f'created rank {abbreviation}') else: await ctx.send('error: no rank created') @client.command(brief='Create a new certification') async def create_certification(ctx, branch_str: str, abbreviation: str, name: str): record_id = api.create_certification(create_api_context(ctx), branch_str, abbreviation, name) if record_id: await ctx.send(f'created certification {abbreviation}') else: await ctx.send('error: no certification created') @client.command(brief='Records certification') async def record_cert(ctx, personnel_or_channel_str: str, certification_str: str): members = None for channel in ctx.message.channel.guild.voice_channels: if channel.name == personnel_or_channel_str: members = [] for member in channel.members: personnel_str = f'{member.name}#{member.discriminator}' personnel = api.personnel_summary(create_api_context(ctx), personnel_str) if personnel: members.append(personnel) if members is None: personnel = api.personnel_summary(create_api_context(ctx), personnel_or_channel_str) members = [personnel] records_str = '' for member in members: personnel_str = f'{member["username"]}#{member["discriminator"]}' record_id = api.record_cert(create_api_context(ctx), personnel_str, certification_str) if record_id: name = member["handleName"] if member["handleName"] else member["username"] records_str += f'updated {name}\r' if records_str != '': await ctx.send(records_str) else: await ctx.send('warning: no records updated') @client.command(brief='Records operation attendance') async def record_op(ctx, personnel_or_channel_str: str, op_name: str = None): members = None for channel in ctx.message.channel.guild.voice_channels: if channel.name == personnel_or_channel_str: members = [] for member in channel.members: personnel_str = f'{member.name}#{member.discriminator}' personnel = api.personnel_summary(create_api_context(ctx), personnel_str) if personnel: members.append(personnel) if members is None: personnel = api.personnel_summary(create_api_context(ctx), personnel_or_channel_str) members = [personnel] records_str = '' for member in members: personnel_str = f'{member["username"]}#{member["discriminator"]}' record_id = api.record_op(create_api_context(ctx), personnel_str, op_name) if record_id: name = member["handleName"] if member["handleName"] else member["username"] records_str += f'updated {name}\r' if records_str != '': await ctx.send(records_str) else: await ctx.send('warning: no records updated') @client.command(brief='Records note') async def record_note(ctx, personnel_or_channel_str: str, *, note: str): members = None for channel in ctx.message.channel.guild.voice_channels: if channel.name == personnel_or_channel_str: members = [] for member in channel.members: personnel_str = f'{member.name}#{member.discriminator}' personnel = api.personnel_summary(create_api_context(ctx), personnel_str) if personnel: members.append(personnel) if members is None: personnel = api.personnel_summary(create_api_context(ctx), personnel_or_channel_str) members = [personnel] records_str = '' for member in members: personnel_str = f'{member["username"]}#{member["discriminator"]}' record_id = api.record_note(create_api_context(ctx), f'{ctx.author.name}#{ctx.author.discriminator}', personnel_str, note) if record_id: name = member["handleName"] if member["handleName"] else member["username"] records_str += f'updated {name}\r' if records_str != '': await ctx.send(records_str) else: await ctx.send('warning: no records updated') @client.command(brief='Creates all records for a new member') async def add_member(ctx, discord_handle, sc_handle_name, rank_str, recruited_by_str=None): joined_date = ctx.message.channel.guild.get_member(discord_handle) record_id = api.add_member(create_api_context(ctx), discord_handle, sc_handle_name, rank_str, recruited_by_str, joined_date) if record_id: await ctx.send('member added') else: await ctx.send('error: could not add member') @client.command(brief='Records personnel joining org - do not use with add_member') async def record_joined_org(ctx, personnel_str, recruited_by_str=None): record_id = api.record_joined_org(create_api_context(ctx), personnel_str, recruited_by_str) if record_id: await ctx.send('joined org') else: await ctx.send('error: could not join org') @client.command(brief='Records personnel leaving org') async def record_left_org(ctx, personnel_str): record_id = api.record_left_org(create_api_context(ctx), personnel_str) if record_id: await ctx.send('left org') else: await ctx.send('error: could not leave org') @client.command(brief='Changes users rank, grade, and branch') async def change_rank(ctx, personnel_str, rank_str): record_id = api.change_rank(create_api_context(ctx), personnel_str, rank_str) personnel = api.personnel_summary(create_api_context(ctx), personnel_str) member = ctx.message.channel.guild.get_member_named(f'{personnel["username"]}#{personnel["discriminator"]}') if member is None: await ctx.send('error: could not change rank, no discord member found in guild') return if record_id: try: await member.edit(nick=formatted_nick(personnel)) await ctx.send('rank changed') except: await ctx.send('rank changed, could not update nickname') else: await ctx.send('error: could not change rank') @client.command(brief='Changes user nickname - testing') async def change_nick(ctx, personnel_str, nick): member = ctx.message.channel.guild.get_member_named(personnel_str) if member is None: await ctx.send('error: could not change nickname, no discord member found in guild') return await member.edit(nick=nick) @client.command(brief='Checks discord tags against database') async def check_tags(ctx, correct_tags: bool = False): report_users = '' all_personnel = api.personnel_summary_all(create_api_context(ctx)) if all_personnel is None: await ctx.send('error: could not lookup personnel') return for personnel in all_personnel: personnel_str = f'{personnel["username"]}#{personnel["discriminator"]}' member = ctx.message.channel.guild.get_member_named(personnel_str) if member: member_nick = member.nick if member.nick else member.display_name nick = formatted_nick(personnel) if member_nick != nick: report_users += f'{member_nick}\t -> \t {nick}' if correct_tags: try: await member.edit(nick=nick) except: report_users += '\tE' report_users += '\r' if len(report_users) > 0: await ctx.send(report_users) else: await ctx.send('all member tags are correct') @client.command(brief='Validates user credentials') async def validate(ctx): response = api.validate(create_api_context(ctx)) await ctx.send(response) def create_api_context(ctx) -> org_manager_api.APIContext: printable = set(string.printable) return org_manager_api.APIContext( ctx.author.id, ''.join(filter(lambda x: x in printable, ctx.author.name)), ctx.author.discriminator ) def formatted_nick(personnel) -> str: tag = personnel["rankAbbreviation"] name = personnel["handleName"] if personnel["handleName"] else personnel["username"] return f'[{tag}] {name}' def full_formatted_nick(personnel) -> str: tag = '' if personnel["branchAbbreviation"]: tag += personnel["branchAbbreviation"] + '-' if personnel["gradeAbbreviation"]: tag += personnel["gradeAbbreviation"] + '-' if personnel["rankAbbreviation"]: tag += personnel["rankAbbreviation"] name = personnel["handleName"] if personnel["handleName"] else personnel["username"] return f'[{tag}] {name}' client.run(secrets.CLIENT_KEY)
import discord from discord.ext import commands, tasks import org_manager_api import theimc import secrets import string import os os.environ['REQUESTS_CA_BUNDLE'] = os.path.join( '/etc/ssl/certs/', 'ca-certificates.crt') # API Server API_SERVER = 'https://api.org-manager.space/1.0.0' api = org_manager_api.OrgManagerAPI(API_SERVER, secrets.ORGANIZATION_ID) # Prefix for calling bot in discord client = commands.Bot(command_prefix='.') # Runs on start to show bot is online @client.event async def on_ready(): await client.change_presence(status=discord.Status.online, activity=discord.Game('.help')) print("Bot is ready") app_info = await client.application_info() print(f'https://discord.com/oauth2/authorize?client_id={app_info.id}&bot') @client.command(brief='superadmin') async def create_theimc_from_discord(ctx): if ctx.author.name == 'abrazite': theimc.create_org(api, create_api_context(ctx)) @client.command(brief='superadmin') async def sync_theimc_from_discord(ctx): if ctx.author.name == 'abrazite': theimc.create_org(api, create_api_context(ctx)) theimc.sync_org(api, create_api_context(ctx), ctx.message.channel.guild.members) # Clear messages in chat @client.command(brief='superadmin') async def clear(ctx, amount=5): if ctx.author.name == 'abrazite': await ctx.channel.purge(limit=amount + 1) await ctx.send(f'{amount} Posts have been cleared') @client.command(brief='Reports when user joined the org') async def is_member(ctx, personnel_str): membership = api.membership(create_api_context(ctx), personnel_str) if membership: # todo(James): format date :) await ctx.send(f'joined {membership["joinedDate"]}') else: await ctx.send('no membership found') @client.command(brief='Shows basic personnel info') async def whois(ctx, *, personnel_str=None): if personnel_str: personnel = api.personnel_summary(create_api_context(ctx), personnel_str) else: personnel = api.personnel_summary(create_api_context(ctx), f'{ctx.author.name}#{ctx.author.discriminator}') if personnel: message_str = f'{full_formatted_nick(personnel)}\r' if personnel['username']: message_str += f'\rdiscord:\t {personnel["username"]}#{personnel["discriminator"]}' if personnel['citizenRecord']: message_str += f'\rcitizenRecord:\t {personnel["citizenRecord"]}' if personnel['citizenName']: message_str += f'\rcitizenName:\t {personnel["citizenName"]}' if personnel['handleName']: message_str += f'\rhandleName:\t {personnel["handleName"]}' message_str += '\r' if personnel['rankDate']: message_str += f'\rrankDate:\t {personnel["rankDate"]}' await ctx.send(message_str) else: await ctx.send('error: record not found') @client.command(brief='Lists all org branches') async def list_branches(ctx, page=0): LIMIT = 10 branches = api.branches(create_api_context(ctx), limit=LIMIT, page=page) branches_strs = '' if len(branches) == LIMIT or page > 0: branches_strs += f'(page {page})\r\r' for branch in branches: branch_str = branch["abbreviation"] if branch["branch"]: branch_str += '\t' + branch["branch"] + '\r' branches_strs += branch_str await ctx.send(branches_strs) @client.command(brief='Lists all org grades') async def list_grades(ctx, page=0): LIMIT = 10 grades = api.grades(create_api_context(ctx), limit=LIMIT, page=page) grades_strs = '' if len(grades) == LIMIT or page > 0: grades_strs += f'(page {page})\r\r' for grade in grades: grade_str = grade["abbreviation"] if grade["grade"]: grade_str += '\t' + grade["grade"] grades_strs += grade_str + '\r' await ctx.send(grades_strs) @client.command(brief='Lists all org ranks') async def list_ranks(ctx, page=0): LIMIT = 10 ranks = api.ranks(create_api_context(ctx), limit=LIMIT, page=page) ranks_strs = '' if len(ranks) == LIMIT or page > 0: ranks_strs += f'(page {page})\r\r' for rank in ranks: ranks_str = '' if rank["branchAbbreviation"]: ranks_str += rank["branchAbbreviation"] + '-' if rank["gradeAbbreviation"]: ranks_str += rank["gradeAbbreviation"] + '-' if rank["rankAbbreviation"]: ranks_str += rank["rankAbbreviation"] if rank["rankName"]: ranks_str += '\t' + rank["rankName"] ranks_strs += ranks_str + '\r' await ctx.send(ranks_strs) @client.command(brief='Lists all org certifications') async def list_certifications(ctx, page: int = 0): LIMIT = 10 certifications = api.certifications(create_api_context(ctx), limit=LIMIT, page=page) certifications_strs = '' if len(certifications) == LIMIT or page > 0: certifications_strs += f'(page {page})\r\r' for certification in certifications: certification_str = certification["abbreviation"] if certification["name"]: certification_str += '\t' + certification["name"] certifications_strs += certification_str + '\r' await ctx.send(certifications_strs) @client.command(brief='Lists all rank change records') async def list_rank_records(ctx, personnel_str: str = None, page: int = 0): LIMIT = 10 if personnel_str: personnel = api.personnel(create_api_context(ctx), personnel_str) else: personnel = api.personnel(create_api_context(ctx), f'{ctx.author.name}#{ctx.author.discriminator}') if personnel is None or 'rankChangeRecords' not in personnel: await ctx.send('error: no records found') return records = personnel['rankChangeRecords'] record_str = '' if len(records) == LIMIT or page > 0: record_str += f'(page {page})\r\r' for i, record in enumerate(records): if page * LIMIT <= i < (page + 1) * LIMIT: record_str += record['date'] if record['abbreviation']: record_str += '\t' + record['abbreviation'] record_str += '\r' await ctx.send(record_str) @client.command(brief='Lists all certification records') async def list_cert_records(ctx, personnel_str: str = None, page: int = 0): LIMIT = 10 if personnel_str: personnel = api.personnel(create_api_context(ctx), personnel_str) else: personnel = api.personnel(create_api_context(ctx), f'{ctx.author.name}#{ctx.author.discriminator}') if personnel is None or 'certificationRecords' not in personnel: await ctx.send('error: no records found') return records = personnel['certificationRecords'] record_str = '' if len(records) == LIMIT or page > 0: record_str += f'(page {page})\r\r' for i, record in enumerate(records): if page * LIMIT <= i < (page + 1) * LIMIT: record_str += record['date'] if record['abbreviation']: record_str += '\t' + record['abbreviation'] record_str += '\r' await ctx.send(record_str) @client.command(brief='Lists all ops attended by personnel') async def list_op_records(ctx, personnel_str: str = None, page: int = 0): LIMIT = 10 if personnel_str: personnel = api.personnel(create_api_context(ctx), personnel_str) else: personnel = api.personnel(create_api_context(ctx), f'{ctx.author.name}#{ctx.author.discriminator}') if personnel is None or 'operationAttendenceRecords' not in personnel: await ctx.send('error: no records found') return records = personnel['operationAttendenceRecords'] record_str = '' if len(records) == LIMIT or page > 0: record_str += f'(page {page})\r\r' for i, record in enumerate(records): if page * LIMIT <= i < (page + 1) * LIMIT: record_str += record['date'] if record['name']: record_str += '\t' + record['name'] record_str += '\r' await ctx.send(record_str) @client.command(brief='Lists all notes for personnel') async def list_note_records(ctx, personnel_str: str = None, page: int = 0): LIMIT = 10 if personnel_str: personnel = api.personnel(create_api_context(ctx), personnel_str) else: personnel = api.personnel(create_api_context(ctx), f'{ctx.author.name}#{ctx.author.discriminator}') if personnel is None or 'noteRecords' not in personnel: await ctx.send('error: no records found') return records = personnel['noteRecords'] record_str = '' if len(records) == LIMIT or page > 0: record_str += f'(page {page})\r\r' for i, record in enumerate(records): if page * LIMIT <= i < (page + 1) * LIMIT: record_str += record['date'] if record['note']: record_str += '\t' + record['note'] record_str += '\r' await ctx.send(record_str) @client.command(brief='Lists all personnel with filtering') async def search_personnel(ctx, filter_str=None, page=0): LIMIT = 10 summary = api.personnel_summary_all(create_api_context(ctx)) list_str = '' summary = sorted(summary, key=lambda e: formatted_nick(e)) count = 0 total_count = 0 for personnel in summary: include = filter_str is None include = include or (filter_str == personnel["gradeAbbreviation"]) include = include or (filter_str == personnel["branchAbbreviation"]) include = include or (filter_str == personnel["rankAbbreviation"]) include = include or (filter_str == f'{personnel["branchAbbreviation"]}-{personnel["gradeAbbreviation"]}-{personnel["rankAbbreviation"]}') include = include or (filter_str == f'{personnel["branchAbbreviation"]}-{personnel["rankAbbreviation"]}') include = include or (filter_str == f'{personnel["citizenRecord"]}') include = include or (filter_str == f'{personnel["citizenName"]}') include = include or (filter_str == f'{personnel["handleName"]}') include = include or (filter_str == f'{personnel["username"]}#{personnel["discriminator"]}') if include: total_count += 1 if include and count < LIMIT: list_str += f'{formatted_nick(personnel)}\r' count += 1 if total_count > LIMIT: total_pages = int(total_count / LIMIT) list_str = f'(page {page} of {total_pages})\r\r' + list_str list_str += '\r' await ctx.send(list_str) @client.command(brief='Create a new org branch') async def create_branch(ctx, abbreviation: str, branch: str = None): record_id = api.create_branch(create_api_context(ctx), abbreviation, branch) if record_id: await ctx.send(f'created branch {abbreviation}') else: await ctx.send('error: no branch created') @client.command(brief='Create a new org grade') async def create_grade(ctx, abbreviation: str, grade: str = None): record_id = api.create_grade(create_api_context(ctx), abbreviation, grade) if record_id: await ctx.send(f'created grade {abbreviation}') else: await ctx.send('error: no grade created') @client.command(brief='Create a new org grade') async def create_rank(ctx, abbreviation: str, rank: str = None, branch_str: str = None, grade_str: str = None): record_id = api.create_rank(create_api_context(ctx), abbreviation, rank, branch_str, grade_str) if record_id: await ctx.send(f'created rank {abbreviation}') else: await ctx.send('error: no rank created') @client.command(brief='Create a new certification') async def create_certification(ctx, branch_str: str, abbreviation: str, name: str): record_id = api.create_certification(create_api_context(ctx), branch_str, abbreviation, name) if record_id: await ctx.send(f'created certification {abbreviation}') else: await ctx.send('error: no certification created') @client.command(brief='Records certification') async def record_cert(ctx, personnel_or_channel_str: str, certification_str: str): members = None for channel in ctx.message.channel.guild.voice_channels: if channel.name == personnel_or_channel_str: members = [] for member in channel.members: personnel_str = f'{member.name}#{member.discriminator}' personnel = api.personnel_summary(create_api_context(ctx), personnel_str) if personnel: members.append(personnel) if members is None: personnel = api.personnel_summary(create_api_context(ctx), personnel_or_channel_str) members = [personnel] records_str = '' for member in members: personnel_str = f'{member["username"]}#{member["discriminator"]}' record_id = api.record_cert(create_api_context(ctx), personnel_str, certification_str) if record_id: name = member["handleName"] if member["handleName"] else member["username"] records_str += f'updated {name}\r' if records_str != '': await ctx.send(records_str) else: await ctx.send('warning: no records updated') @client.command(brief='Records operation attendance') async def record_op(ctx, personnel_or_channel_str: str, op_name: str = None): members = None for channel in ctx.message.channel.guild.voice_channels: if channel.name == personnel_or_channel_str: members = [] for member in channel.members: personnel_str = f'{member.name}#{member.discriminator}' personnel = api.personnel_summary(create_api_context(ctx), personnel_str) if personnel: members.append(personnel) if members is None: personnel = api.personnel_summary(create_api_context(ctx), personnel_or_channel_str) members = [personnel] records_str = '' for member in members: personnel_str = f'{member["username"]}#{member["discriminator"]}' record_id = api.record_op(create_api_context(ctx), personnel_str, op_name) if record_id: name = member["handleName"] if member["handleName"] else member["username"] records_str += f'updated {name}\r' if records_str != '': await ctx.send(records_str) else: await ctx.send('warning: no records updated') @client.command(brief='Records note') async def record_note(ctx, personnel_or_channel_str: str, *, note: str): members = None for channel in ctx.message.channel.guild.voice_channels: if channel.name == personnel_or_channel_str: members = [] for member in channel.members: personnel_str = f'{member.name}#{member.discriminator}' personnel = api.personnel_summary(create_api_context(ctx), personnel_str) if personnel: members.append(personnel) if members is None: personnel = api.personnel_summary(create_api_context(ctx), personnel_or_channel_str) members = [personnel] records_str = '' for member in members: personnel_str = f'{member["username"]}#{member["discriminator"]}' record_id = api.record_note(create_api_context(ctx), f'{ctx.author.name}#{ctx.author.discriminator}', personnel_str, note) if record_id: name = member["handleName"] if member["handleName"] else member["username"] records_str += f'updated {name}\r' if records_str != '': await ctx.send(records_str) else: await ctx.send('warning: no records updated') @client.command(brief='Creates all records for a new member') async def add_member(ctx, discord_handle, sc_handle_name, rank_str, recruited_by_str=None): joined_date = ctx.message.channel.guild.get_member(discord_handle) record_id = api.add_member(create_api_context(ctx), discord_handle, sc_handle_name, rank_str, recruited_by_str, joined_date) if record_id: await ctx.send('member added') else: await ctx.send('error: could not add member') @client.command(brief='Records personnel joining org - do not use with add_member') async def record_joined_org(ctx, personnel_str, recruited_by_str=None): record_id = api.record_joined_org(create_api_context(ctx), personnel_str, recruited_by_str) if record_id: await ctx.send('joined org') else: await ctx.send('error: could not join org') @client.command(brief='Records personnel leaving org') async def record_left_org(ctx, personnel_str): record_id = api.record_left_org(create_api_context(ctx), personnel_str) if record_id: await ctx.send('left org') else: await ctx.send('error: could not leave org') @client.command(brief='Changes users rank, grade, and branch') async def change_rank(ctx, personnel_str, rank_str): record_id = api.change_rank(create_api_context(ctx), personnel_str, rank_str) personnel = api.personnel_summary(create_api_context(ctx), personnel_str) member = ctx.message.channel.guild.get_member_named(f'{personnel["username"]}#{personnel["discriminator"]}') if member is None: await ctx.send('error: could not change rank, no discord member found in guild') return if record_id: try: await member.edit(nick=formatted_nick(personnel)) await ctx.send('rank changed') except: await ctx.send('rank changed, could not update nickname') else: await ctx.send('error: could not change rank') @client.command(brief='Changes user nickname - testing') async def change_nick(ctx, personnel_str, nick): member = ctx.message.channel.guild.get_member_named(personnel_str) if member is None: await ctx.send('error: could not change nickname, no discord member found in guild') return await member.edit(nick=nick) @client.command(brief='Checks discord tags against database') async def check_tags(ctx, correct_tags: bool = False): report_users = '' all_personnel = api.personnel_summary_all(create_api_context(ctx)) if all_personnel is None: await ctx.send('error: could not lookup personnel') return for personnel in all_personnel: personnel_str = f'{personnel["username"]}#{personnel["discriminator"]}' member = ctx.message.channel.guild.get_member_named(personnel_str) if member: member_nick = member.nick if member.nick else member.display_name nick = formatted_nick(personnel) if member_nick != nick: report_users += f'{member_nick}\t -> \t {nick}' if correct_tags: try: await member.edit(nick=nick) except: report_users += '\tE' report_users += '\r' if len(report_users) > 0: await ctx.send(report_users) else: await ctx.send('all member tags are correct') @client.command(brief='Validates user credentials') async def validate(ctx): response = api.validate(create_api_context(ctx)) await ctx.send(response) def create_api_context(ctx) -> org_manager_api.APIContext: printable = set(string.printable) return org_manager_api.APIContext( ctx.author.id, ''.join(filter(lambda x: x in printable, ctx.author.name)), ctx.author.discriminator ) def formatted_nick(personnel) -> str: tag = personnel["rankAbbreviation"] name = personnel["handleName"] if personnel["handleName"] else personnel["username"] return f'[{tag}] {name}' def full_formatted_nick(personnel) -> str: tag = '' if personnel["branchAbbreviation"]: tag += personnel["branchAbbreviation"] + '-' if personnel["gradeAbbreviation"]: tag += personnel["gradeAbbreviation"] + '-' if personnel["rankAbbreviation"]: tag += personnel["rankAbbreviation"] name = personnel["handleName"] if personnel["handleName"] else personnel["username"] return f'[{tag}] {name}' client.run(secrets.CLIENT_KEY)
en
0.39764
# API Server # Prefix for calling bot in discord # Runs on start to show bot is online # Clear messages in chat # todo(James): format date :) #{ctx.author.discriminator}') #{personnel["discriminator"]}' #{ctx.author.discriminator}') #{ctx.author.discriminator}') #{ctx.author.discriminator}') #{ctx.author.discriminator}') #{personnel["discriminator"]}') #{member.discriminator}' #{member["discriminator"]}' #{member.discriminator}' #{member["discriminator"]}' #{member.discriminator}' #{member["discriminator"]}' #{ctx.author.discriminator}', personnel_str, note) #{personnel["discriminator"]}') #{personnel["discriminator"]}'
2.419804
2
vk/types/responses/docs.py
Inzilkin/vk.py
24
6632250
<reponame>Inzilkin/vk.py from .others import SimpleResponse from ..base import BaseModel from ..attachments import Document import typing class Add(SimpleResponse): pass class Delete(SimpleResponse): pass class Edit(SimpleResponse): pass class GetResponse(BaseModel): count: int = None items: typing.List[Document] = None class Get(BaseModel): response: GetResponse = None class GetById(BaseModel): response: typing.List[Document] = None class GetMessagesUploadServerResponse(BaseModel): upload_url: str = None class GetMessagesUploadServer(BaseModel): response: GetMessagesUploadServerResponse = None class GetTypesItems(BaseModel): id: int = None name: str = None count: int = None class GetTypesResponse(BaseModel): count: int = None items: typing.List[GetTypesItems] = None class GetTypes(BaseModel): response: GetTypesResponse = None class GetUploadServer(BaseModel): response: GetMessagesUploadServerResponse = None class GetWallUploadServer(BaseModel): response: GetMessagesUploadServerResponse = None class Save(BaseModel): response: typing.List[Document] = None class SearchResponse(BaseModel): count: int = None items: typing.List[Document] = None class Search(BaseModel): response: SearchResponse = None
from .others import SimpleResponse from ..base import BaseModel from ..attachments import Document import typing class Add(SimpleResponse): pass class Delete(SimpleResponse): pass class Edit(SimpleResponse): pass class GetResponse(BaseModel): count: int = None items: typing.List[Document] = None class Get(BaseModel): response: GetResponse = None class GetById(BaseModel): response: typing.List[Document] = None class GetMessagesUploadServerResponse(BaseModel): upload_url: str = None class GetMessagesUploadServer(BaseModel): response: GetMessagesUploadServerResponse = None class GetTypesItems(BaseModel): id: int = None name: str = None count: int = None class GetTypesResponse(BaseModel): count: int = None items: typing.List[GetTypesItems] = None class GetTypes(BaseModel): response: GetTypesResponse = None class GetUploadServer(BaseModel): response: GetMessagesUploadServerResponse = None class GetWallUploadServer(BaseModel): response: GetMessagesUploadServerResponse = None class Save(BaseModel): response: typing.List[Document] = None class SearchResponse(BaseModel): count: int = None items: typing.List[Document] = None class Search(BaseModel): response: SearchResponse = None
none
1
2.10805
2