added function to stop shuffling data once done

run.py

@@ -39,7 +39,7 @@ import torch.utils.data as data
 
 from solver import Solver
 from BrainMapperUNet import BrainMapperUNet
-from utils.data_utils import get_datasets, data_test_train_validation_split
+from utils.data_utils import get_datasets, data_test_train_validation_split, update_shuffling_flag
 import utils.data_evaluation_utils as evaluations
 from utils.data_logging_utils import LogWriter
 
@@ -133,7 +133,7 @@ def train(data_parameters, training_parameters, network_parameters, misc_paramet
     )
 
     if training_parameters['use_pre_trained']:
-        BrainMapperModel = torch.load(training_parameters['pre_trained_path'])
+        BrainMapperModel = torch.load(traikning_parameters['pre_trained_path'])
     else:
         BrainMapperModel = BrainMapperUNet(network_parameters)
 
@@ -355,7 +355,7 @@ if __name__ == '__main__':
     if data_shuffling_flag == True:
         # Here we shuffle the data!
         data_test_train_validation_split(data_parameters['data_directory'], data_parameters['train_percentage'], data_parameters['validation_percentage'])
-
+        update_shuffling_flag('settings.ini')
         # TODO: This might also be a very good point to add cross-validation later
     else:
 

utils/data_utils.py

@@ -21,6 +21,7 @@ import torch
 import torch.utils.data as data
 import nibabel as nb
 import random
+import configparser
 
 def directory_reader(folder_location, write_txt=False):
     """Produces a list of of data-tags which are accessible
@@ -75,7 +76,19 @@ def data_test_train_validation_split(folder_location, train_percentage, validati
     np.savetxt('validation.txt', validation)
 
 def update_shuffling_flag(file_name):
-    pass
+    """ Update shuffling flag
+
+    Changes shuffling flag in settings to False once data has been shuffled
+
+    Args:
+        file_name (str): The settings file name
+    """
+
+    config = configparser.ConfigParser()
+    config.read(file_name)
+    config.set('DATA', 'data_split_flag', 'False')
+    with open(file_name, 'w') as configfile:
+        config.write(configfile)
 
 def tract_sum_generator(folder_path):
     """Sums the tracts of different dMRI files