if COMPUTE_COMPLETE_DATA:
data_all,op_id_good = fap.cat_data_from_matfile_root(mat_file_paths, count_op_id_min,is_from_old_matlab = IS_FROM_OLD_MATLAB,
data_all_good_op_path = data_all_good_op_path,op_id_good_path = op_id_good_path,is_return_masked = False)
# -- Create masked array from data_all
# data_all = np.ma.masked_invalid(data_all)
# ---------------------------------------------------------------------------------
# -- Calculate U_statistics for the problems
# ---------------------------------------------------------------------------------
if CALCULATE_U_STATS:
# -- skip problems with already calculated U-stats
if CALCULATE_ONLY_NEW_U_STATS:
task_names = tstat.filter_calculated(mat_file_root,HCTSA_name_search_pattern = 'HCTSA_(.*)_N_70_100_reduced.mat')
file_paths = [mat_file_root+"HCTSA_{0:s}_N_70_100_reduced.mat".format(s) for s in task_names]
# -- calculate U-stats for all problems
else:
file_paths = mat_file_paths
_,task_names = tstat.get_calculated_names(mat_file_root,HCTSA_name_search_pattern = 'HCTSA_(.*)_N_70_100_reduced.mat')
u_stat_file_paths = tstat.calculate_ustat_mult_tasks(mat_file_paths,task_names,ustat_data_out_folder,is_from_old_matlab = IS_FROM_OLD_MATLAB)
if CALCULATE_U_STATS_ALL_CLASSES_AVG:
all_classes_avg = tstat.calculate_ustat_avg_mult_task(mat_file_paths,u_stat_file_paths,all_classes_avg_out_path ,is_from_old_matlab = IS_FROM_OLD_MATLAB)
# ---------------------------------------------------------------------------------
data_all_good_op_path=data_all_good_op_path,
op_id_good_path=op_id_good_path,
is_return_masked=False)
# -- Create masked array from data_all
# data_all = np.ma.masked_invalid(data_all)
# ---------------------------------------------------------------------------------
# -- Calculate U_statistics for the problems
# ---------------------------------------------------------------------------------
if CALCULATE_U_STATS:
# -- skip problems with already calculated U-stats
if CALCULATE_ONLY_NEW_U_STATS:
task_names = tstat.filter_calculated(
mat_file_root,
HCTSA_name_search_pattern='HCTSA_(.*)_N_70_100_reduced.mat')
file_paths = [
mat_file_root + "HCTSA_{0:s}_N_70_100_reduced.mat".format(s)
for s in task_names
]
# -- calculate U-stats for all problems
else:
file_paths = mat_file_paths
_, task_names = tstat.get_calculated_names(
mat_file_root,
HCTSA_name_search_pattern='HCTSA_(.*)_N_70_100_reduced.mat')
u_stat_file_paths = tstat.calculate_ustat_mult_tasks(
mat_file_paths,
