binned_spiking_activity_human_epilepsy/python_code/analysis_PlosCB/run_analysis_timeresolved.py

import os
import mr_epilepsy_timeresolved


def run_2parts_regions():
    # -----------------------------------------------------------------------#
    # preictal data 4ms
    # -----------------------------------------------------------------------#
    data_path = '../Data/preictal/'
    result_path = '../Results/preictal/singleunits_regions/'

    # -----------------------------------------------------------------------#
    # create result directories
    # -----------------------------------------------------------------------#
    recordings = [dI for dI in os.listdir(data_path) if os.path.isdir(
        os.path.join(data_path, dI))]

    if not os.path.exists(result_path):
        os.makedirs(result_path)
    for rec in recordings:
        if not os.path.exists(result_path + rec):
            os.makedirs(result_path + rec)

    # -----------------------------------------------------------------------#
    # run mr analysis
    # -----------------------------------------------------------------------#
    outputfilename = 'pkl/activity_brainregions_SU_4ms.pkl'
    x = 2
    mr_epilepsy_timeresolved.mt_x_parts(x, outputfilename, data_path,
       result_path, recordings=recordings, binnings='all', ksteps=(1, 400),
       fit_method="offset")


def run_2parts_hemispheres():
    # -----------------------------------------------------------------------#
    # preictal data 4ms
    # -----------------------------------------------------------------------#
    data_path = '../Data/preictal/'
    result_path = '../Results/preictal/singleunits/'

    # -----------------------------------------------------------------------#
    # create result directories
    # -----------------------------------------------------------------------#
    recordings = [dI for dI in os.listdir(data_path) if os.path.isdir(
        os.path.join(data_path, dI))]

    if not os.path.exists(result_path):
        os.makedirs(result_path)
    for rec in recordings:
        if not os.path.exists(result_path + rec):
            os.makedirs(result_path + rec)

    # -----------------------------------------------------------------------#
    # run timeresolved mr analysis
    # -----------------------------------------------------------------------#
    x = 2
    outputfilename = "pkl/activity_SU_4ms.pkl"
    mr_epilepsy_timeresolved.mt_x_parts(x, outputfilename, data_path,
       result_path, recordings=recordings, binnings=['left', 'right'],
       ksteps=(1, 400), fit_method="offset")


def run_timeresolved_hemispheres():
    # -----------------------------------------------------------------------#
    # preictal data 4ms
    # -----------------------------------------------------------------------#
    data_path = '../Data/preictal/'
    result_path = '../Results/preictal/singleunits/'

    # -----------------------------------------------------------------------#
    # create result directories
    # -----------------------------------------------------------------------#
    recordings = [dI for dI in os.listdir(data_path) if os.path.isdir(
        os.path.join(data_path, dI))]

    if not os.path.exists(result_path):
        os.makedirs(result_path)
    for rec in recordings:
        if not os.path.exists(result_path + rec):
            os.makedirs(result_path + rec)

    # -----------------------------------------------------------------------#
    # run timeresolved mr analysis
    # -----------------------------------------------------------------------#
    ksteps = (1, 400)
    for binning in ['left', 'right']:

        for rec in recordings[60:]:
            windowsize = 20000
            windowstep = 500
            binning = binning
            fit_method = 'offset'
            dt = 4
            mt_file = '{}{}/mt_results_{}_{}_kmin{}_kmax{}_winsize{}_winstep{}_dt{}.pkl'.format(
                result_path, rec, binning, fit_method, ksteps[0], ksteps[1],
                windowsize, windowstep, dt)

            if not os.path.isfile(mt_file):
                mr_epilepsy_timeresolved.analyse_timeresolved_mr(data_path,
                    result_path, recordings=[rec], binnings=[binning],
                    ksteps=ksteps, windowsize=20000, windowstep=500,
                    fit_method='offset')


def main():
    run_2parts_hemispheres()
    run_2parts_regions()
    run_timeresolved_hemispheres()  # warning: timeresolved analysis is computationally costly


if __name__ == '__main__':
    main()