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- 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()
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