Commit 79d95fdf authored by Andrei-Claudiu Roibu's avatar Andrei-Claudiu Roibu
Browse files

branch 'CrossDomain_autoencoder' of git.fmrib.ox.ac.uk:aroibu/functionmapper...

branch 'CrossDomain_autoencoder' of git.fmrib.ox.ac.uk:aroibu/functionmapper into CrossDomain_autoencoder
parents 0da347fc 574e0817
......@@ -787,14 +787,14 @@ def _generate_target_volume(file_path,
volume = data_utils.load_and_preprocess_targets(file_path, cross_domain_x2x_flag, crop_flag=False)
if mean_regression_flag == True:
volume = _regress_target(volume, subject, dmri_mean_mask_path, rsfmri_mean_mask_path, regression_factors, crop_flag, cross_domain_x2x_flag, mean_regression_all_flag)
volume = _regress_target(volume, subject, dmri_mean_mask_path, rsfmri_mean_mask_path, regression_factors, cross_domain_x2x_flag, mean_regression_all_flag, crop_flag=False)
elif mean_subtraction_flag == True:
volume = _subtract_target(volume, subject, dmri_mean_mask_path, rsfmri_mean_mask_path, crop_flag, cross_domain_x2x_flag)
volume = _subtract_target(volume, subject, dmri_mean_mask_path, rsfmri_mean_mask_path, cross_domain_x2x_flag, crop_flag=False)
return volume
def _regress_target(volume, subject, dmri_mean_mask_path, rsfmri_mean_mask_path, regression_factors, crop_flag, cross_domain_x2x_flag, mean_regression_all_flag):
def _regress_target(volume, subject, dmri_mean_mask_path, rsfmri_mean_mask_path, regression_factors, cross_domain_x2x_flag, mean_regression_all_flag, crop_flag=False):
""" Target Regression
This function regresse the group mean from the target volume using the saved regression weights.
......@@ -839,7 +839,7 @@ def _regress_target(volume, subject, dmri_mean_mask_path, rsfmri_mean_mask_path,
return regressed_volume
def _subtract_target(volume, subject, dmri_mean_mask_path, rsfmri_mean_mask_path, crop_flag, cross_domain_x2x_flag):
def _subtract_target(volume, subject, dmri_mean_mask_path, rsfmri_mean_mask_path, cross_domain_x2x_flag, crop_flag=False):
""" Target Subtraction
This function subtracts the group mean from the target volume using the saved regression weights.
......
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