Microcircuit.
PLOS Computational Biology 12, 1-34 (2016).
"""
import plot_helpers
import meanfield.circuit as circuit
import numpy as np
import h5py_wrapper.wrapper as h5
fix_path = 'integration/data/'
if __name__ == '__main__':
filename = fix_path + 'Bos2016_data.h5'
# Original parameters extracted from the data + modification
circ_params_with_modifications = plot_helpers.get_parameter_microcircuit()
circ = circuit.Circuit('microcircuit',
circ_params_with_modifications,
analysis_type='dynamical',
fmax=500.0,
from_file=False)
power_spectra_freqs, power_spectra = circ.create_power_spectra()
exemplary_frequency_idx = 20
omega = circ.omegas[exemplary_frequency_idx]
print(omega)
H = circ.ana.create_H(omega)
MH = circ.ana.create_MH(omega)
delay_dist = circ.ana.create_delay_dist_matrix(omega)
import numpy as np
import matplotlib.pyplot as plt
import read_sim as rs
import plot_helpers as ph
import h5py_wrapper.wrapper as h5
import meanfield.circuit as circuit
ph.set_fig_defaults()
circuit_params = ph.get_parameter_microcircuit()
def get_sensitivity_measure(calcAna, calcAnaAll, mode='gamma', eig_index=None):
print 'Calculate sensitivity measure.'
if calcAna or calcAnaAll:
if mode == 'gamma' or mode == 'low':
fmax = 100.0
elif mode == 'high_gamma':
fmax = 400.0
circ = circuit.Circuit('microcircuit',
circuit_params,
fmax=fmax,
from_file=not calcAnaAll)
freqs, eigs = circ.create_eigenvalue_spectra('MH')
if mode == 'gamma':
fmax = freqs[np.argmin(abs(eigs[eig_index] - 1))]
Z = circ.get_sensitivity_measure(fmax)
eigc = eigs[eig_index][np.argmin(abs(eigs[eig_index] - 1))]
elif mode == 'high_gamma':
eigs = eigs[eig_index][np.where(freqs > 150.)]
freqs = freqs[np.where(freqs > 150.)]
fmax = freqs[np.argmin(abs(eigs - 1.0))]
Options:
-h --help Show this screen.
--version Show version.
"""
import plot_helpers
import meanfield.circuit as circuit
from docopt import docopt
import sys
if __name__ == '__main__':
arguments = docopt(__doc__, version='0.1')
filename = arguments['<filename>']
# New parameters used for Fig. 1
circ_params_new = plot_helpers.get_parameter_microcircuit()
# Original parameters extracted from the data
circ = circuit.Circuit('microcircuit', analysis_type=None)
circ_params_old = circ.params
file = open(filename, 'w')
sys.stdout = file
for attribute in circ_params_new.keys():
print(attribute)
print('old/original:')
print(circ_params_old[attribute])
print('new:')
print(circ_params_new[attribute])
print('\n')