def prepareBEH(self, project, part, factors, labels, project_param, to_filter):
'''
standard Behavior processing
'''
PP = PreProcessing(project = project, part = part, factor_headers = factors, factor_labels = labels)
PP.create_folder_structure()
PP.combine_single_subject_files(save = False)
PP.select_data(project_parameters = project_param, save = False)
PP.filter_data(to_filter = to_filter, filter_crit = ' and correct == 1', cnd_sel = False, save = True)
PP.exclude_outliers(criteria = dict(RT = 'RT_filter == True', correct = ''))
PP.save_data_file()
def prepareBEH(self, project, part, factors, labels, project_param): ''' standard Behavior processing ''' PP = PreProcessing(project = project, part = part, factor_headers = factors, factor_labels = labels) PP.create_folder_structure() PP.combine_single_subject_files(save = False) PP.select_data(project_parameters = project_param, save = False) #PP.filter_data(to_filter = to_filter, filter_crit = ' and correct == 1', cnd_sel = False, save = True) #PP.exclude_outliers(criteria = dict(dev_0 = '')) #PP.prep_JASP(agg_func = 'mean', voi = 'dev_0', data_filter = "", save = True) PP.save_data_file()