{"action":"created","comment":{"url":"https://api.github.com/repos/nest/nest-simulator/pulls/comments/78700535","id":78700535,"diff_hunk":"@@ -0,0 +1,347 @@\n+# -*- coding: utf-8 -*-\n+#\n+# network.py\n+#\n+# This file is part of NEST.\n+#\n+# Copyright (C) 2004 The NEST Initiative\n+#\n+# NEST is free software: you can redistribute it and/or modify\n+# it under the terms of the GNU General Public License as published by\n+# the Free Software Foundation, either version 2 of the License, or\n+# (at your option) any later version.\n+#\n+# NEST is distributed in the hope that it will be useful,\n+# but WITHOUT ANY WARRANTY; without even the implied warranty of\n+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the\n+# GNU General Public License for more details.\n+#\n+# You should have received a copy of the GNU General Public License\n+# along with NEST.  If not, see <http://www.gnu.org/licenses/>.\n+\n+'''\n+pynest microcicuit network\n+----------------------------------------------\n+\n+Main file for the microcircuit.\n+\n+Hendrik Rothe, Hannah Bos, Sacha van Albada; May 2016\n+'''\n+\n+import nest\n+import numpy as np\n+from helpers import *\n+import matplotlib.pyplot as plt\n+import os\n+\n+\n+class Network:\n+    \"\"\" Handles the setup of the network parameters and\n+    provides functions to connect the network and devices.\n+\n+    Arguments:\n+    sim_dict: dictionary containing all parameters specific to the simulation\n+              such as the directory the data is stored in and the seeds\n+              (see: stimulus_params.py)\n+    net_dict: dictionary containing all parameters specific to the neurons\n+              and the network\n+              (see: network_params.py)\n+\n+    Keyword Arguments:\n+    stim_dict: dictionary containing all parameter specific to the stimulus\n+               (see: stimulus_params.py)\n+    \"\"\"\n+    def __init__(self, sim_dict, net_dict, stim_dict=None):\n+        self.sim_dict = sim_dict\n+        self.data = sim_dict['data_path']\n+        self.net_dict = net_dict\n+        if stim_dict is not None:\n+            self.stim_dict = stim_dict\n+        print 'Data will be written to %s' % self.data\n+\n+    # hand parameters to NEST-kernel\n+    def setup(self):\n+        nest.ResetKernel()\n+        master_seed = self.sim_dict['master_seed']\n+        print 'master_seed ', master_seed\n+        nest.SetKernelStatus({\n+            'local_num_threads': self.sim_dict['local_num_threads']})\n+        N_tp = nest.GetKernelStatus(['total_num_virtual_procs'])[0]\n+        print 'number of total processes',  N_tp\n+        rng_seeds = range(master_seed + 1 + N_tp, master_seed + 1 + (2 * N_tp))\n+        grng_seed = master_seed + N_tp\n+        print 'rng_seeds', rng_seeds\n+        print 'grng_seed', grng_seed\n+        self.pyrngs = [np.random.RandomState(s) for s in range(\n+            master_seed, master_seed + N_tp)]\n+        self.sim_resolution = self.sim_dict['sim_resolution']\n+        kernel_dict = {\n+                       'resolution': self.sim_resolution,\n+                       'grng_seed': grng_seed,\n+                       'rng_seeds': rng_seeds,\n+                       'overwrite_files': self.sim_dict['overwrite_files'],\n+                       }\n+        nest.SetKernelStatus(kernel_dict)\n+\n+    # create neuronal populations\n+    def create_populations(self):\n+        self.N_ttl = self.net_dict['N_full']\n+        self.N_scl = self.net_dict['N_scaling']\n+        self.K_scl = self.net_dict['K_scaling']\n+        self.synapses = get_total_number_of_synapses()\n+        self.synapses_scaled = self.synapses * self.K_scl\n+        self.nr_neurons = self.N_ttl * self.N_scl\n+        self.K_ext = self.net_dict['K_ext'] * self.K_scl\n+        self.w_from_PSP = get_weight(self.net_dict['PSP_e'])\n+        self.weight_mat = get_weight(self.net_dict['PSP_mean_matrix'])\n+        self.weight_mat_std = self.net_dict['PSP_std_matrix']\n+        self.w_ext = self.w_from_PSP\n+        self.DC_amp_e = np.zeros(len(self.net_dict['populations']))\n+        if self.N_scl != 1:\n+            print 'The Number of neurons is scaled by a factor of:'\n+            print self.N_scl\n+\n+        # Scaling of the synapses\n+        if self.K_scl != 1:\n+            synapses_indegree = self.synapses / (\n+                self.N_ttl.reshape(len(self.N_ttl), 1) * self.N_scl)\n+            self.weight_mat, self.w_ext, self.DC_amp_e = adj_w_ext_to_K(\n+                synapses_indegree,\n+                self.K_scl,\n+                self.weight_mat, self.w_from_PSP,\n+                self.DC_amp_e)\n+            print 'The number of synapses is scalled by a factor of:'\n+            print self.K_scl\n+        else:\n+            self.w_ext = self.w_from_PSP\n+\n+        # Create cortical populations\n+        self.pops = []\n+        pop_file = open(self.data + 'population_GIDs.dat', 'w+')\n+        for i, pop in enumerate(self.net_dict['populations']):\n+            population = nest.Create(self.net_dict['neuron_model'],\n+                                     int(self.nr_neurons[i]))\n+            nest.SetStatus(population,\n+                           {'tau_syn_ex': self.net_dict['n_params']['tau_ex'],\n+                            'tau_syn_in': self.net_dict['n_params']['tau_in'],\n+                            'E_L': self.net_dict['n_params']['E_L'],\n+                            'V_th': self.net_dict['n_params']['V_th'],\n+                            'V_reset':  self.net_dict['n_params']['V_reset'],\n+                            't_ref': self.net_dict['n_params']['t_ref'],\n+                            'I_e': self.DC_amp_e[i]\n+                            })\n+            node_info = nest.GetStatus(population)\n+            local_nodes = [(ni['global_id'], ni['vp'])\n+                           for ni in node_info if ni['local']]\n+            for gid, vp in local_nodes:\n+                nest.SetStatus(\n+                    [gid],\n+                    {'V_m': self.pyrngs[vp].uniform(\n+                                self.net_dict['n_params']['V_th'],\n+                                self.net_dict['n_params']['V_reset'])})\n+            self.pops.append(population)\n+            pop_file.write('%d  %d \\n' % (population[0], population[-1]))\n+        pop_file.close()\n+\n+    # recording devices are created in this function\n+    def create_devices(self):\n+        self.spikedetector = []\n+        self.voltmeter = []\n+        for i, pop in enumerate(self.pops):\n+            if 'spike_detector' in self.net_dict['rec_dev']:\n+                recdict = {'withgid': True,\n+                           'withtime': True,\n+                           'to_memory': False,\n+                           'to_file': True,\n+                           'label': self.data + 'spike_detector'}\n+                spikedetector = nest.Create('spike_detector', params=recdict)\n+                self.spikedetector.append(spikedetector)\n+            if 'voltmeter' in self.net_dict['rec_dev']:\n+                rcdictmem = {'interval': self.sim_dict['rec_V_int'],\n+                             'withgid': True,\n+                             'withtime': True,\n+                             'to_memory': False,\n+                             'to_file': True,\n+                             'label': self.data + 'volt',\n+                             'record_from': ['V_m'],\n+                             }\n+                volt = nest.Create('voltmeter', params=rcdictmem)\n+                self.voltmeter.append(volt)\n+\n+        if 'spike_detector' in self.net_dict['rec_dev']:\n+            print 'spike_detectors created'\n+        if 'voltmeter' in self.net_dict['rec_dev']:\n+            print 'voltmeter created'\n+\n+    # thalamic neurons are created here\n+    def create_thalamic_input(self):\n+        if self.stim_dict['thalamic_input']:\n+            print 'thalamic input provided'\n+            self.thalamic_population = nest.Create(\n+                                           'parrot_neuron',\n+                                           self.stim_dict['n_thal'])\n+            self.thalamic_weight = get_weight(self.stim_dict['PSP_th'])\n+            self.stop_th = (self.stim_dict['th_start'] +\n+                            self.stim_dict['th_duration'])\n+            self.poisson_th = nest.Create('poisson_generator')\n+            nest.SetStatus(\n+                self.poisson_th, {'rate': self.stim_dict['th_rate'],\n+                                  'start': self.stim_dict['th_start'],\n+                                  'stop': self.stop_th})\n+            nest.Connect(self.poisson_th, self.thalamic_population)\n+            self.nr_synapses_th = synapses_th_matrix()\n+            if self.K_scl != 1:\n+                self.thalamic_weight = self.thalamic_weight/(self.K_scl**0.5)\n+                self.nr_synapses_th = (self.nr_synapses_th * self.K_scl)\n+        else:\n+            print 'thalamic input not provided'\n+\n+    # poisson generators are created in this function\n+    def create_poisson(self):\n+        if self.net_dict['poisson_input']:\n+            rate_ext = self.net_dict['bg_rate'] * self.K_ext\n+            self.poisson = []\n+            for i, target_pop in enumerate(self.pops):\n+                    poisson = nest.Create('poisson_generator')\n+                    nest.SetStatus(poisson, {'rate': rate_ext[i]})\n+                    self.poisson.append(poisson)\n+            print 'Poisson background input created'\n+\n+    # dc generators are created in this functions\n+    def create_dc_generator(self):\n+        if self.stim_dict['dc_input']:\n+            dc_amp_stim = self.net_dict['K_ext'] * self.stim_dict['dc_amp']\n+            self.dc = []\n+            print 'DC_amp_stim', dc_amp_stim\n+            for i, target_pop in enumerate(self.pops):\n+                dc = nest.Create('dc_generator',\n+                                 params={'amplitude': dc_amp_stim[i],\n+                                         'start': self.stim_dict['dc_start'],\n+                                         'stop': self.stim_dict['dc_start'] +\n+                                         self.stim_dict['dc_dur']})\n+                self.dc.append(dc)\n+            print 'DC generator created'\n+\n+    # connections between neuronal populations are created in this function\n+    def create_connections(self):\n+        mean_delays = self.net_dict['mean_delay_matrix']\n+        std_delays = self.net_dict['std_delay_matrix']\n+        norm_clp = 'normal_clipped'\n+        for i, target_pop in enumerate(self.pops):\n+            for j, source_pop in enumerate(self.pops):\n+                synapse_nr = int(self.synapses_scaled[i][j])\n+                if synapse_nr >= 0.:\n+                    weight = self.weight_mat[i][j]\n+                    w_sd = abs(weight * self.weight_mat_std[i][j])\n+                    conn_dict_poisson = {'rule': 'all_to_all'}\n+                    syn_dict_poisson = {'model': 'static_synapse',\n+                                        'weight': self.w_ext,\n+                                        'delay': {'distribution': norm_clp,\n+                                                  'mu': 1.5,\n+                                                  'sigma': 0.75,\n+                                                  'low': self.sim_resolution}}\n+                    conn_dict_rec = {'rule': 'fixed_total_number',\n+                                     'N': synapse_nr}\n+                    syn_dict_rec_ex = {'model': 'static_synapse',\n+                                       'weight': {'distribution': norm_clp,\n+                                                  'mu': weight,\n+                                                  'sigma': w_sd,\n+                                                  'low': 0.0},\n+                                       'delay': {'distribution': norm_clp,\n+                                                 'mu': mean_delays[i][j],\n+                                                 'sigma': std_delays[i][j],\n+                                                 'low': self.sim_resolution}}\n+                    syn_dict_rec_in = {'model': 'static_synapse',\n+                                       'weight': {'distribution': norm_clp,\n+                                                  'mu': weight,\n+                                                  'sigma': w_sd,\n+                                                  'high': 0.0},\n+                                       'delay': {'distribution': norm_clp,\n+                                                 'mu': mean_delays[i][j],\n+                                                 'sigma': std_delays[i][j],\n+                                                 'low': self.sim_resolution}}\n+                    if j % 2:\n+                        syn_dict_rec = syn_dict_rec_in\n+                    else:\n+                        syn_dict_rec = syn_dict_rec_ex\n+                    nest.Connect(source_pop, target_pop,\n+                                 conn_spec=conn_dict_rec,\n+                                 syn_spec=syn_dict_rec)\n+        print 'Recurrent connections established'\n+\n+    # poisson generators connected to the different populations\n+    def connect_poisson(self):\n+        for i, target_pop in enumerate(self.pops):\n+                conn_dict_poisson = {'rule': 'all_to_all'}","path":"pynest/examples/pynest-microcircuit/network.py","position":275,"original_position":275,"commit_id":"f4b8a2eac3aade3d1beab9e0d18a46891fd799c5","original_commit_id":"f4b8a2eac3aade3d1beab9e0d18a46891fd799c5","user":{"login":"jhnnsnk","id":11767751,"avatar_url":"https://avatars.githubusercontent.com/u/11767751?v=3","gravatar_id":"","url":"https://api.github.com/users/jhnnsnk","html_url":"https://github.com/jhnnsnk","followers_url":"https://api.github.com/users/jhnnsnk/followers","following_url":"https://api.github.com/users/jhnnsnk/following{/other_user}","gists_url":"https://api.github.com/users/jhnnsnk/gists{/gist_id}","starred_url":"https://api.github.com/users/jhnnsnk/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/jhnnsnk/subscriptions","organizations_url":"https://api.github.com/users/jhnnsnk/orgs","repos_url":"https://api.github.com/users/jhnnsnk/repos","events_url":"https://api.github.com/users/jhnnsnk/events{/privacy}","received_events_url":"https://api.github.com/users/jhnnsnk/received_events","type":"User","site_admin":false},"body":"4 spaces, see also the following for-loops","created_at":"2016-09-14T07:49:35Z","updated_at":"2016-09-14T07:49:35Z","html_url":"https://github.com/nest/nest-simulator/pull/451#discussion_r78700535","pull_request_url":"https://api.github.com/repos/nest/nest-simulator/pulls/451","_links":{"self":{"href":"https://api.github.com/repos/nest/nest-simulator/pulls/comments/78700535"},"html":{"href":"https://github.com/nest/nest-simulator/pull/451#discussion_r78700535"},"pull_request":{"href":"https://api.github.com/repos/nest/nest-simulator/pulls/451"}}},"pull_request":{"url":"https://api.github.com/repos/nest/nest-simulator/pulls/451","id":80240512,"html_url":"https://github.com/nest/nest-simulator/pull/451","diff_url":"https://github.com/nest/nest-simulator/pull/451.diff","patch_url":"https://github.com/nest/nest-simulator/pull/451.patch","issue_url":"https://api.github.com/repos/nest/nest-simulator/issues/451","number":451,"state":"open","locked":false,"title":"Pynest microcircuit","user":{"login":"hendrikrth","id":15939240,"avatar_url":"https://avatars.githubusercontent.com/u/15939240?v=3","gravatar_id":"","url":"https://api.github.com/users/hendrikrth","html_url":"https://github.com/hendrikrth","followers_url":"https://api.github.com/users/hendrikrth/followers","following_url":"https://api.github.com/users/hendrikrth/following{/other_user}","gists_url":"https://api.github.com/users/hendrikrth/gists{/gist_id}","starred_url":"https://api.github.com/users/hendrikrth/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/hendrikrth/subscriptions","organizations_url":"https://api.github.com/users/hendrikrth/orgs","repos_url":"https://api.github.com/users/hendrikrth/repos","events_url":"https://api.github.com/users/hendrikrth/events{/privacy}","received_events_url":"https://api.github.com/users/hendrikrth/received_events","type":"User","site_admin":false},"body":"The example files of NEST are lacking a PyNEST version of the microcircuit #450. To compensate this I would like you to include my branch. As reviewers I suggest @jhnnsnk and @mschmidt87. ","created_at":"2016-08-05T13:09:33Z","updated_at":"2016-09-14T07:49:35Z","closed_at":null,"merged_at":null,"merge_commit_sha":"19dca1950b29923edfcba896c23d158b1e820915","assignee":{"login":"mschmidt87","id":6512628,"avatar_url":"https://avatars.githubusercontent.com/u/6512628?v=3","gravatar_id":"","url":"https://api.github.com/users/mschmidt87","html_url":"https://github.com/mschmidt87","followers_url":"https://api.github.com/users/mschmidt87/followers","following_url":"https://api.github.com/users/mschmidt87/following{/other_user}","gists_url":"https://api.github.com/users/mschmidt87/gists{/gist_id}","starred_url":"https://api.github.com/users/mschmidt87/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/mschmidt87/subscriptions","organizations_url":"https://api.github.com/users/mschmidt87/orgs","repos_url":"https://api.github.com/users/mschmidt87/repos","events_url":"https://api.github.com/users/mschmidt87/events{/privacy}","received_events_url":"https://api.github.com/users/mschmidt87/received_events","type":"User","site_admin":false},"assignees":[{"login":"mschmidt87","id":6512628,"avatar_url":"https://avatars.githubusercontent.com/u/6512628?v=3","gravatar_id":"","url":"https://api.github.com/users/mschmidt87","html_url":"https://github.com/mschmidt87","followers_url":"https://api.github.com/users/mschmidt87/followers","following_url":"https://api.github.com/users/mschmidt87/following{/other_user}","gists_url":"https://api.github.com/users/mschmidt87/gists{/gist_id}","starred_url":"https://api.github.com/users/mschmidt87/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/mschmidt87/subscriptions","organizations_url":"https://api.github.com/users/mschmidt87/orgs","repos_url":"https://api.github.com/users/mschmidt87/repos","events_url":"https://api.github.com/users/mschmidt87/events{/privacy}","received_events_url":"https://api.github.com/users/mschmidt87/received_events","type":"User","site_admin":false},{"login":"jhnnsnk","id":11767751,"avatar_url":"https://avatars.githubusercontent.com/u/11767751?v=3","gravatar_id":"","url":"https://api.github.com/users/jhnnsnk","html_url":"https://github.com/jhnnsnk","followers_url":"https://api.github.com/users/jhnnsnk/followers","following_url":"https://api.github.com/users/jhnnsnk/following{/other_user}","gists_url":"https://api.github.com/users/jhnnsnk/gists{/gist_id}","starred_url":"https://api.github.com/users/jhnnsnk/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/jhnnsnk/subscriptions","organizations_url":"https://api.github.com/users/jhnnsnk/orgs","repos_url":"https://api.github.com/users/jhnnsnk/repos","events_url":"https://api.github.com/users/jhnnsnk/events{/privacy}","received_events_url":"https://api.github.com/users/jhnnsnk/received_events","type":"User","site_admin":false}],"milestone":null,"commits_url":"https://api.github.com/repos/nest/nest-simulator/pulls/451/commits","review_comments_url":"https://api.github.com/repos/nest/nest-simulator/pulls/451/comments","review_comment_url":"https://api.github.com/repos/nest/nest-simulator/pulls/comments{/number}","comments_url":"https://api.github.com/repos/nest/nest-simulator/issues/451/comments","statuses_url":"https://api.github.com/repos/nest/nest-simulator/statuses/f4b8a2eac3aade3d1beab9e0d18a46891fd799c5","head":{"label":"hendrikrth:pynest-microcircuit","ref":"pynest-microcircuit","sha":"f4b8a2eac3aade3d1beab9e0d18a46891fd799c5","user":{"login":"hendrikrth","id":15939240,"avatar_url":"https://avatars.githubusercontent.com/u/15939240?v=3","gravatar_id":"","url":"https://api.github.com/users/hendrikrth","html_url":"https://github.com/hendrikrth","followers_url":"https://api.github.com/users/hendrikrth/followers","following_url":"https://api.github.com/users/hendrikrth/following{/other_user}","gists_url":"https://api.github.com/users/hendrikrth/gists{/gist_id}","starred_url":"https://api.github.com/users/hendrikrth/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/hendrikrth/subscriptions","organizations_url":"https://api.github.com/users/hendrikrth/orgs","repos_url":"https://api.github.com/users/hendrikrth/repos","events_url":"https://api.github.com/users/hendrikrth/events{/privacy}","received_events_url":"https://api.github.com/users/hendrikrth/received_events","type":"User","site_admin":false},"repo":{"id":64954071,"name":"nest-simulator","full_name":"hendrikrth/nest-simulator","owner":{"login":"hendrikrth","id":15939240,"avatar_url":"https://avatars.githubusercontent.com/u/15939240?v=3","gravatar_id":"","url":"https://api.github.com/users/hendrikrth","html_url":"https://github.com/hendrikrth","followers_url":"https://api.github.com/users/hendrikrth/followers","following_url":"https://api.github.com/users/hendrikrth/following{/other_user}","gists_url":"https://api.github.com/users/hendrikrth/gists{/gist_id}","starred_url":"https://api.github.com/users/hendrikrth/starred{/owner}{/repo}","subscriptions_url":"h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