replaced mean subtraction with mean regression, fixed data file reader

run.py

@@ -41,7 +41,7 @@ import numpy as np
 
 from solver import Solver
 from BrainMapperAE import BrainMapperAE3D
-from utils.data_utils import get_datasets, data_test_train_validation_split, update_shuffling_flag, create_folder
+from utils.data_utils import get_datasets, data_preparation, update_shuffling_flag, create_folder
 import utils.data_evaluation_utils as evaluations
 from utils.data_logging_utils import LogWriter
 
@@ -360,29 +360,29 @@ if __name__ == '__main__':
     # Here we shuffle the data!
 
     if data_parameters['data_split_flag'] == True:
-
         print('Data is shuffling... This could take a few minutes!')
 
-    if data_parameters['data_split_flag'] == True:
         if data_parameters['use_data_file'] == True:
-            data_test_train_validation_split(data_parameters['data_folder_name'],
+            data_preparation(data_parameters['data_folder_name'],
                                              data_parameters['test_percentage'],
                                              data_parameters['subject_number'],
                                              data_directory=data_parameters['data_directory'],
                                              train_inputs=data_parameters['train_data_file'],
                                              train_targets=data_parameters['train_output_targets'],
-                                             mean_mask_path=data_parameters['mean_mask_path'],
+                                             rsfMRI_mean_mask_path=data_parameters['rsfmri_mean_mask_path'],
+                                             dMRI_mean_mask_path=data_parameters['dmri_mean_mask_path'],
                                              data_file=data_parameters['data_file'],
                                              K_fold=data_parameters['k_fold']
                                              )
         else:
-            data_test_train_validation_split(data_parameters['data_folder_name'],
+            data_preparation(data_parameters['data_folder_name'],
                                              data_parameters['test_percentage'],
                                              data_parameters['subject_number'],
                                              data_directory=data_parameters['data_directory'],
                                              train_inputs=data_parameters['train_data_file'],
                                              train_targets=data_parameters['train_output_targets'],
-                                             mean_mask_path=data_parameters['mean_mask_path'],
+                                             rsfMRI_mean_mask_path=data_parameters['rsfmri_mean_mask_path'],
+                                             dMRI_mean_mask_path=data_parameters['dmri_mean_mask_path'],
                                              K_fold=data_parameters['k_fold']
                                              )
         update_shuffling_flag('settings.ini')
@@ -394,7 +394,6 @@ if __name__ == '__main__':
               network_parameters, misc_parameters)
 
     # NOTE: THE EVAL FUNCTIONS HAVE NOT YET BEEN DEBUGGED (16/04/20)
-    # NOTE: THE EVAL-MAPPING FUNCTION HAS BEEN DEBUGGED (28/04/20)
 
     elif arguments.mode == 'evaluate-score':
         evaluate_score(training_parameters,

settings.ini

 [DATA]
 data_folder_name = "datasets"
-use_data_file = True
+use_data_file = False
 data_directory = "/well/win-biobank/projects/imaging/data/data3/subjectsAll/"
 data_file = "/well/win-biobank/projects/imaging/data/data3/subjectsAll/subj_22k.txt"
 k_fold = None
@@ -11,12 +11,14 @@ train_list = "datasets/train.txt"
 validation_list = "datasets/validation.txt"
 test_list = "datasets/test.txt"
 scaling_factors = "datasets/scaling_factors.pkl"
+regression_weights = "datasets/regression_weights.pkl"
 train_data_file = "dMRI/autoptx_preproc/tractsNormSummed.nii.gz"
 train_output_targets = "fMRI/rfMRI_25.dr/dr_stage2.nii.gz"
 validation_data_file = "dMRI/autoptx_preproc/tractsNormSummed.nii.gz"
 validation_target_file = "fMRI/rfMRI_25.dr/dr_stage2.nii.gz"
 brain_mask_path = "utils/MNI152_T1_2mm_brain_mask.nii.gz"
-mean_mask_path = "utils/mean_dr_stage2.nii.gz"
+rsfmri_mean_mask_path = "utils/mean_dr_stage2.nii.gz"
+dmri_mean_mask_path = "utils/mean_tractsNormSummed_downsampled.nii.gz"
 mean_reduction = True
 
 [TRAINING]