<s> import sct_utils as sct <EOL> import commands <EOL> import sct_propseg <EOL> from msct_parser import Parser <EOL> from pandas import DataFrame <EOL> import os . path <EOL> import time , random <EOL> from copy import deepcopy <EOL> def test ( path_data = '<STR_LIT>' , parameters = '<STR_LIT>' ) : <EOL> verbose = <NUM_LIT:0> <EOL> if not parameters : <EOL> parameters = '<STR_LIT>' <EOL> dice_threshold = <NUM_LIT> <EOL> parser = sct_propseg . get_parser ( ) <EOL> dict_param = parser . parse ( parameters . split ( ) , check_file_exist = False ) <EOL> dict_param_with_path = parser . add_path_to_file ( deepcopy ( dict_param ) , path_data , input_file = True ) <EOL> param_with_path = parser . dictionary_to_string ( dict_param_with_path ) <EOL> if not ( os . path . isfile ( dict_param_with_path [ '<STR_LIT>' ] ) ) : <EOL> status = <NUM_LIT:200> <EOL> output = '<STR_LIT>' + path_data <EOL> return status , output , DataFrame ( <EOL> data = { '<STR_LIT:status>' : status , '<STR_LIT>' : output , '<STR_LIT>' : float ( '<STR_LIT>' ) } , index = [ path_data ] ) <EOL> contrast_folder = '<STR_LIT>' <EOL> input_filename = '<STR_LIT>' <EOL> if dict_param [ '<STR_LIT>' ] [ <NUM_LIT:0> ] == '<STR_LIT:/>' : <EOL> dict_param [ '<STR_LIT>' ] = dict_param [ '<STR_LIT>' ] [ <NUM_LIT:1> : ] <EOL> input_split = dict_param [ '<STR_LIT>' ] . split ( '<STR_LIT:/>' ) <EOL> if len ( input_split ) == <NUM_LIT:2> : <EOL> contrast_folder = input_split [ <NUM_LIT:0> ] + '<STR_LIT:/>' <EOL> input_filename = input_split [ <NUM_LIT:1> ] <EOL> else : <EOL> input_filename = input_split [ <NUM_LIT:0> ] <EOL> if not contrast_folder : <EOL> status = <NUM_LIT> <EOL> output = '<STR_LIT>' + dict_param [ <EOL> '<STR_LIT>' ] + '<STR_LIT>' + path_data <EOL> return status , output , DataFrame ( <EOL> data = { '<STR_LIT:status>' : status , '<STR_LIT>' : output , '<STR_LIT>' : float ( '<STR_LIT>' ) } , index = [ path_data ] ) <EOL> import time , random <EOL> subject_folder = path_data . split ( '<STR_LIT:/>' ) <EOL> if subject_folder [ - <NUM_LIT:1> ] == '<STR_LIT>' and len ( subject_folder ) > <NUM_LIT:1> : <EOL> subject_folder = subject_folder [ - <NUM_LIT:2> ] <EOL> else : <EOL> subject_folder = subject_folder [ - <NUM_LIT:1> ] <EOL> path_output = sct . slash_at_the_end ( '<STR_LIT>' + subject_folder + '<STR_LIT:_>' + time . strftime ( "<STR_LIT>" ) + '<STR_LIT:_>' + str ( random . randint ( <NUM_LIT:1> , <NUM_LIT> ) ) , slash = <NUM_LIT:1> ) <EOL> param_with_path += '<STR_LIT>' + path_output <EOL> cmd = '<STR_LIT>' + param_with_path <EOL> output = '<STR_LIT>' + cmd + '<STR_LIT>' <EOL> time_start = time . time ( ) <EOL> status , o = sct . run ( cmd , verbose ) <EOL> output += o <EOL> duration = time . time ( ) - time_start <EOL> segmentation_filename = path_output + sct . add_suffix ( input_filename , '<STR_LIT>' ) <EOL> manual_segmentation_filename = path_data + contrast_folder + sct . add_suffix ( input_filename , '<STR_LIT>' ) <EOL> dice_segmentation = float ( '<STR_LIT>' ) <EOL> if status == <NUM_LIT:0> : <EOL> cmd = '<STR_LIT>' + segmentation_filename + '<STR_LIT>' + manual_segmentation_filename <EOL> status , output = sct . run ( cmd , verbose ) <EOL> dice_segmentation = float ( output . split ( '<STR_LIT>' ) [ <NUM_LIT:1> ] . split ( '<STR_LIT:\n>' ) [ <NUM_LIT:0> ] ) <EOL> if dice_segmentation < dice_threshold : <EOL> status = <NUM_LIT> <EOL> results = DataFrame ( data = { '<STR_LIT:status>' : status , '<STR_LIT>' : output , '<STR_LIT>' : dice_segmentation , '<STR_LIT>' : duration } , index = [ path_data ] ) <EOL> return status , output , results <EOL> if __name__ == "<STR_LIT:__main__>" : <EOL> test ( ) </s>
