Note

This page is a reference documentation. It only explains the function signature, and not how to use it. Please refer to the user guide for the big picture.

meierlab.outliers.compute_outlier_values#

meierlab.outliers.compute_outlier_values(nii_images, out_folder, save_m_sd=False, save_prefix=None, save_nii=False, mask=None)[source]#

Compute outlier values for a set of nifti images.

Parameters:

nii_imageslist: Nifti images or file paths to compute outliers for.
out_folderstr or path: Destination folder.
save_m_sdbool, optional: Option to save the mean and standard deviation images, by default False.
save_prefixstr, optional: String prefix to use when (if) saving files, by default None.
save_niibool, optional: Option to save individual outlier nifti files, by default False.
maskimage (Nifti1Image or file name), optional: Data mask to compute outliers within, by default None. If none given, a binary mask of the average computed from the dataset will be used.

Returns:

DataFrame: A dataframe containing: subject, total voxels, positive outlier counts and percentages, negative outlier counts and percentages.

Examples

>>> from meierlab import outliers
>>> nii_images = ['sub-001.nii.gz','sub-002.nii.gz','sub-003.nii.gz']
>>> out_folder = './outliers'
>>> outlier_df = compute_outlier_values(nii_images, out_folder, save_m_sd=True)
>>> outlier_df.to_csv(f'{out_folder}/outliers.csv',index=False)