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import numpy as np
from locData import data_in
from locInverseProblem import data_out
The goal of this tutorial is to define an inverse problem according to the recordings and the electrode geometry we have. Then we can try out source localization methods.
Let's start by loading the data:
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# Data path/filename
t_ind = 38
data_path = '../data/'
file_name = data_path + 'data_sim_low.hdf5'
data_options = {'flag_cell': True, 'flag_electode': False}
data = data_in(file_name, **data_options)
And chose the localization parameters. You can check the parameters necessary in the documentation.
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localization_options = {'p_vres':20, 'p_jlen':0, 'p_erad': 5, 't_ind': 38, 'flag_depthweighted': False}
loc = data_out(data, **localization_options)
You can see the different functions of of the inverse problem object with iPython easily:
loc. loc.cmp_fwd_matrix loc.electrode_pos loc.cmp_inv_matrix loc.evaluate_localization loc.cmp_resolution_matrix loc.load_with_pickle loc.cmp_sloreta loc.options loc.cmp_weight_matrix loc.t_ind loc.create_voxels loc.voxels loc.data loc.write_with_pickle
And chose a function.
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loc.cmp_sloreta()
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