03_file_management_extra.md

Re-name subject files

Write a function which, given a subject directory, renames all of the image files for this subject so that they are prefixed with [group]_subj_[id], where [group] is either CON or PAT, and [id] is the (zero-padded) subject ID.

This function should accept the following parameters:

• The subject directory
• The subject group

Bonus 1 Make your function work with both .nii and .nii.gz files.

Bonus 2 If you completed the previous exercise, write a second function which accepts the data set directory as a sole parameter, and then calls the first function for every subject.

Compress all uncompressed images

Write a function which recursively scans a directory, and replaces all .nii files with .nii.gz files, using the built-in gzip library to perform the compression.

Write your own os.path.splitext

Write an implementation of os.path.splitext which works with compressed or uncompressed NIFTI images.

Hint: you know what suffixes to expect!

Write a function to return a specific image file

Assuming that you have completed the previous exercises, and re-organised raw_mri_data so that it has the structure:

raw_mri_data/[group]/subj_[id]/[group]_subj_[id]_[modality].nii.gz

write a function which is given:

• the data set directory
• a group label
• integer ubject ID
• modality ('t1', 't2', 'task', 'rest')

and which returns the fully resolved path to the relevant image file.

Hint: Python has regular expressions - you might want to use one to cope with zero-padding.

Bonus Modify the function so the group label does not need to be passed in.