<s> """<STR_LIT>""" <EOL> import os <EOL> import sys <EOL> import math <EOL> import random as rd <EOL> import numpy as np <EOL> import warnings <EOL> import scipy . linalg as la <EOL> from pprint import pprint <EOL> import io_mp <EOL> import sampler <EOL> def get_new_position ( data , eigv , U , k , Cholesky , Rotation ) : <EOL> """<STR_LIT>""" <EOL> parameter_names = data . get_mcmc_parameters ( [ '<STR_LIT>' ] ) <EOL> vector_new = np . zeros ( len ( parameter_names ) , '<STR_LIT>' ) <EOL> sigmas = np . zeros ( len ( parameter_names ) , '<STR_LIT>' ) <EOL> vector = np . zeros ( len ( parameter_names ) , '<STR_LIT>' ) <EOL> try : <EOL> for elem in parameter_names : <EOL> vector [ parameter_names . index ( elem ) ] = data . mcmc_parameters [ elem ] [ '<STR_LIT>' ] <EOL> except KeyError : <EOL> for elem in parameter_names : <EOL> vector [ parameter_names . index ( elem ) ] = data . mcmc_parameters [ elem ] [ '<STR_LIT>' ] [ <NUM_LIT:0> ] <EOL> rd . seed ( ) <EOL> if data . jumping == '<STR_LIT>' : <EOL> for i in range ( len ( vector ) ) : <EOL> sigmas [ i ] = ( math . sqrt ( <NUM_LIT:1> / eigv [ i ] / len ( vector ) ) ) * rd . gauss ( <NUM_LIT:0> , <NUM_LIT:1> ) * data . jumping_factor <EOL> elif data . jumping == '<STR_LIT>' : <EOL> i = k % len ( vector ) <EOL> sigmas [ i ] = ( math . sqrt ( <NUM_LIT:1> / eigv [ i ] ) ) * rd . gauss ( <NUM_LIT:0> , <NUM_LIT:1> ) * data . jumping_factor <EOL> elif data . jumping == '<STR_LIT>' : <EOL> j = k % len ( data . over_sampling_indices ) <EOL> i = data . over_sampling_indices [ j ] <EOL> for index , elem in enumerate ( data . block_parameters ) : <EOL> if i < elem : <EOL> if index == <NUM_LIT:0> : <EOL> Range = elem <EOL> Previous = <NUM_LIT:0> <EOL> else : <EOL> Range = elem - data . block_parameters [ index - <NUM_LIT:1> ] <EOL> Previous = data . block_parameters [ index - <NUM_LIT:1> ] <EOL> for j in range ( Range ) : <EOL> sigmas [ j + Previous ] = ( math . sqrt ( <NUM_LIT:1.> / Range ) ) * rd . gauss ( <NUM_LIT:0> , <NUM_LIT:1> ) * data . jumping_factor <EOL> break <EOL> else : <EOL> continue <EOL> else : <EOL> print ( '<STR_LIT>' ) <EOL> print ( '<STR_LIT>' ) <EOL> if data . jumping in [ '<STR_LIT>' , '<STR_LIT>' ] : <EOL> vector_new = vector + np . dot ( U , sigmas ) <EOL> else : <EOL> vector_new = vector + np . dot ( Cholesky , sigmas ) <EOL> flag = <NUM_LIT:0> <EOL> for i , elem in enumerate ( parameter_names ) : <EOL> value = data . mcmc_parameters [ elem ] [ '<STR_LIT>' ] <EOL> if ( ( str ( value [ <NUM_LIT:1> ] ) != str ( - <NUM_LIT:1> ) and value [ <NUM_LIT:1> ] is not None ) and <EOL> ( vector_new [ i ] < value [ <NUM_LIT:1> ] ) ) : <EOL> flag += <NUM_LIT:1> <EOL> elif ( ( str ( value [ <NUM_LIT:2> ] ) != str ( - <NUM_LIT:1> ) and value [ <NUM_LIT:2> ] is not None ) and <EOL> vector_new [ i ] > value [ <NUM_LIT:2> ] ) : <EOL> flag += <NUM_LIT:1> <EOL> if flag != <NUM_LIT:0> : <EOL> return False <EOL> try : <EOL> data . check_for_slow_step ( vector_new ) <EOL> except KeyError : <EOL> pass <EOL> for index , elem in enumerate ( parameter_names ) : <EOL> data . mcmc_parameters [ elem ] [ '<STR_LIT>' ] = vector_new [ index ] <EOL> data . update_cosmo_arguments ( ) <EOL> return True <EOL> def chain ( cosmo , data , command_line ) : <EOL> """<STR_LIT>""" <EOL> loglike = <NUM_LIT:0> <EOL> outputs = [ data . out ] <EOL> if not command_line . silent : <EOL> outputs . append ( sys . stdout ) <EOL> try : <EOL> from mpi4py import MPI <EOL> comm = MPI . COMM_WORLD <EOL> rank = comm . Get_rank ( ) <EOL> if rank : <EOL> command_line . quiet = True <EOL> except ImportError : <EOL> rank = <NUM_LIT:0> <EOL> if ( data . get_mcmc_parameters ( [ '<STR_LIT>' ] ) != [ ] ) : <EOL> sigma_eig , U , C = sampler . get_covariance_matrix ( cosmo , data , command_line ) <EOL> if data . jumping_factor == <NUM_LIT:0> : <EOL> warnings . warn ( <EOL> "<STR_LIT>" + <EOL> "<STR_LIT>" ) <EOL> else : <EOL> warnings . warn ( <EOL> "<STR_LIT>" + <EOL> "<STR_LIT>" ) <EOL> data . update_cosmo_arguments ( ) <EOL> loglike = sampler . compute_lkl ( cosmo , data ) <EOL> io_mp . print_vector ( outputs , <NUM_LIT:1> , loglike , data ) <EOL> return <NUM_LIT:1> , loglike <EOL> Cholesky = None <EOL> Rotation = None <EOL> if command_line . jumping == '<STR_LIT>' : <EOL> Cholesky = la . cholesky ( C ) . T <EOL> Rotation = np . identity ( len ( sigma_eig ) ) <EOL> if command_line . update : <EOL> previous = ( sigma_eig , U , C , Cholesky ) <EOL> if command_line . restart is not None : <EOL> sampler . read_args_from_chain ( data , command_line . restart ) <EOL> if command_line . bf is not None : <EOL> sampler . read_args_from_bestfit ( data , command_line . bf ) <EOL> for i in range ( <NUM_LIT:100> ) : <EOL> if get_new_position ( data , sigma_eig , U , i , <EOL> Cholesky , Rotation ) is True : <EOL> break <EOL> if i == <NUM_LIT> : <EOL> raise io_mp . ConfigurationError ( <EOL> "<STR_LIT>" + <EOL> "<STR_LIT>" ) <EOL> loglike = sampler . compute_lkl ( cosmo , data ) <EOL> sampler . accept_step ( data ) <EOL> max_loglike = loglike <EOL> if data . jumping_factor == <NUM_LIT:0> : <EOL> io_mp . print_vector ( outputs , <NUM_LIT:1> , loglike , data ) <EOL> return <NUM_LIT:1> , loglike <EOL> acc , rej = <NUM_LIT:0.0> , <NUM_LIT:0.0> <EOL> N = <NUM_LIT:1> <EOL> input_covmat = command_line . cov <EOL> base = os . path . basename ( command_line . folder ) <EOL> if base == '<STR_LIT>' : <EOL> base = os . path . basename ( command_line . folder [ : - <NUM_LIT:1> ] ) <EOL> command_line . cov = os . path . join ( <EOL> command_line . folder , base + '<STR_LIT>' ) <EOL> if not command_line . silent and not command_line . quiet : <EOL> io_mp . print_parameters ( sys . stdout , data ) <EOL> command_line . quiet = True <EOL> k = <NUM_LIT:1> <EOL> while k <= command_line . N : <EOL> if command_line . update : <EOL> if not rank : <EOL> from parser_mp import parse <EOL> info_command_line = parse ( <EOL> '<STR_LIT>' % command_line . folder ) <EOL> info_command_line . update = command_line . update <EOL> if not ( k + <NUM_LIT:10> ) % command_line . update and k > <NUM_LIT:10> : <EOL> try : <EOL> from analyze import analyze <EOL> R_minus_one = analyze ( info_command_line ) <EOL> except : <EOL> if not command_line . silent : <EOL> print '<STR_LIT>' , k , '<STR_LIT>' , rank , '<STR_LIT>' <EOL> pass <EOL> if not ( k - <NUM_LIT:1> ) % command_line . update : <EOL> try : <EOL> sigma_eig , U , C = sampler . get_covariance_matrix ( <EOL> cosmo , data , command_line ) <EOL> if command_line . jumping == '<STR_LIT>' : <EOL> Cholesky = la . cholesky ( C ) . T <EOL> if not C [ <NUM_LIT:0> , <NUM_LIT:0> ] == previous [ <NUM_LIT:2> ] [ <NUM_LIT:0> , <NUM_LIT:0> ] : <EOL> previous = ( sigma_eig , U , C , Cholesky ) <EOL> if k == <NUM_LIT:1> : <EOL> if not command_line . silent : <EOL> if not input_covmat == None : <EOL> warnings . warn ( <EOL> '<STR_LIT>' <EOL> '<STR_LIT>' <EOL> % ( command_line . cov , input_covmat ) ) <EOL> else : <EOL> warnings . warn ( <EOL> '<STR_LIT>' <EOL> '<STR_LIT>' <EOL> % command_line . cov ) <EOL> else : <EOL> data . out . write ( '<STR_LIT>' % ( int ( acc ) , max ( R_minus_one ) ) ) <EOL> if not command_line . silent : <EOL> print '<STR_LIT>' % ( int ( acc ) , max ( R_minus_one ) ) <EOL> try : <EOL> if stop - after - update : <EOL> k = command_line . N <EOL> print '<STR_LIT>' <EOL> except : <EOL> pass <EOL> except : <EOL> pass <EOL> command_line . quiet = True <EOL> else : <EOL> if not ( k - <NUM_LIT:1> ) % command_line . update : <EOL> try : <EOL> sigma_eig , U , C = sampler . get_covariance_matrix ( <EOL> cosmo , data , command_line ) <EOL> if command_line . jumping == '<STR_LIT>' : <EOL> Cholesky = la . cholesky ( C ) . T <EOL> if not C [ <NUM_LIT:0> , <NUM_LIT:0> ] == previous [ <NUM_LIT:2> ] [ <NUM_LIT:0> , <NUM_LIT:0> ] and not k == <NUM_LIT:1> : <EOL> data . out . write ( '<STR_LIT>' % int ( acc ) ) <EOL> if not command_line . silent : <EOL> print '<STR_LIT>' % int ( acc ) <EOL> try : <EOL> if stop_after_update : <EOL> k = command_line . N <EOL> print '<STR_LIT>' <EOL> except : <EOL> pass <EOL> previous = ( sigma_eig , U , C , Cholesky ) <EOL> except IOError : <EOL> pass <EOL> if get_new_position ( <EOL> data , sigma_eig , U , k , Cholesky , Rotation ) is True : <EOL> newloglike = sampler . compute_lkl ( cosmo , data ) <EOL> else : <EOL> rej += <NUM_LIT:1> <EOL> N += <NUM_LIT:1> <EOL> k += <NUM_LIT:1> <EOL> continue <EOL> if ( newloglike != data . boundary_loglike ) : <EOL> if ( newloglike >= loglike ) : <EOL> alpha = <NUM_LIT:1.> <EOL> else : <EOL> alpha = np . exp ( newloglike - loglike ) <EOL> else : <EOL> alpha = - <NUM_LIT:1> <EOL> if ( ( alpha == <NUM_LIT:1.> ) or ( rd . uniform ( <NUM_LIT:0> , <NUM_LIT:1> ) < alpha ) ) : <EOL> io_mp . print_vector ( outputs , N , loglike , data ) <EOL> sampler . accept_step ( data ) <EOL> loglike = newloglike <EOL> if loglike > max_loglike : <EOL> max_loglike = loglike <EOL> acc += <NUM_LIT:1.0> <EOL> N = <NUM_LIT:1> <EOL> else : <EOL> rej += <NUM_LIT:1.0> <EOL> N += <NUM_LIT:1> <EOL> if acc % data . write_step == <NUM_LIT:0> : <EOL> io_mp . refresh_file ( data ) <EOL> outputs [ <NUM_LIT:0> ] = data . out <EOL> k += <NUM_LIT:1> <EOL> if N > <NUM_LIT:1> : <EOL> io_mp . print_vector ( outputs , N - <NUM_LIT:1> , loglike , data ) <EOL> rate = acc / ( acc + rej ) <EOL> sys . stdout . write ( '<STR_LIT>' . <EOL> format ( command_line . N , rate ) ) <EOL> if rate < <NUM_LIT> : <EOL> warnings . warn ( "<STR_LIT>" <EOL> "<STR_LIT>" <EOL> "<STR_LIT>" ) <EOL> elif rate > <NUM_LIT> : <EOL> warnings . warn ( "<STR_LIT>" <EOL> "<STR_LIT>" <EOL> "<STR_LIT>" <EOL> "<STR_LIT>" <EOL> "<STR_LIT>" ) <EOL> if command_line . restart is not None : <EOL> os . remove ( command_line . restart ) <EOL> sys . stdout . write ( '<STR_LIT>' . <EOL> format ( command_line . restart ) ) <EOL> return </s>
