bug fixes - fixed split function txt file writer: added string format

utils/data_utils.py

@@ -19,7 +19,6 @@ import numpy as np
 import nibabel as nib
 import torch
 import torch.utils.data as data
-import nibabel as nb
 import random
 import configparser
 
@@ -71,9 +70,9 @@ def data_test_train_validation_split(folder_location, train_percentage, validati
 
     train, validation, test = np.split(subDirectoryList, [int(train_percentage/100 * len(subDirectoryList)), int((train_percentage+validation_percentage)/100 * len(subDirectoryList))])
 
-    np.savetxt('train.txt', train)
-    np.savetxt('test.txt', test)
-    np.savetxt('validation.txt', validation)
+    np.savetxt('train.txt', train, fmt='%s')
+    np.savetxt('test.txt', test, fmt='%s')
+    np.savetxt('validation.txt', validation, fmt='%s')
 
 def update_shuffling_flag(file_name):
     """ Update shuffling flag
@@ -298,7 +297,7 @@ def load(file_path, orientation):
         header (class): 'nibabel.nifti1.Nifti1Header' class object, containing image metadata
     """
 
-    nifty_volume, label_map = nb.load(file_path[0]), nb.load(file_path[1])
+    nifty_volume, label_map = nib.load(file_path[0]), nib.load(file_path[1])
     volume, label_map = nifty_volume.get_fdata(), label_map.ged_fdata()
 
     # Do we need min-max normalization here? Will need to check when debuggint and testing
@@ -372,7 +371,7 @@ def load_and_preprocess_evaluation(file_path, orientation, min_max=True):
         ValueError: "Orientation value is invalid. It must be either >>coronal<<, >>axial<< or >>sagital<< "
     """
 
-    nifty_volume = nb.load(file_path[0])
+    nifty_volume = nib.load(file_path[0])
 
     volume = nifty_volume.get_fdata()
     header = nifty_volume.header
@@ -397,5 +396,5 @@ def load_and_preprocess_evaluation(file_path, orientation, min_max=True):
 
 if __name__ == "__main__":
 
-    folder_location = '/well/win-biobank/projects/imaging/data/data3/subjectsAll/'
-    tract_sum_generator(folder_location)
+    folder_location = "../well/win-biobank/projects/imaging/data/data3/subjectsAll/"
+    data_test_train_validation_split(folder_location, 90, 5)