First, change directory into your fmri-methods-2013 directory.
Fetch the upstream changes with the homework with:
git fetch origin
Make a new feature branch to work on with:
git branch day3-homework origin/master
Connect this branch with your own fork with:
git checkout day3-homework git push your-github-username day3-homework --set-upstream
Go to your fmri-methods-2015 repository and change directory (in the
terminal) to the day3 folder.
You'll find some IPython notebooks in that folder.
Make sure you have the IPythono notebook installed. Check by running
ipython notebook from the command line. If you installed using Anaconda,
this should work. If you installed using more standard methods (Python.org
installer on Mac, Linux package manager) then try:
pip install ipython[notebook]
from the command line. Please let us know if that does not work for you, we will try and fix it.
Review the page on slice time correction that we looked at on Monday.
Work through the exercises in the notebook slice_timing.ipynb. The
solutions are in slice_timing_solutions.ipynb.
Now you know all about slice timing your job is to write a Python script to run slice timing on a 4D image.
Edit slice_time_image.py to implement linear slice timing on an image file.
Check the script runs with python slice_time_image.py
ds107_sub012_t1r2.nii. You can run the script interactively in the IPython
console with run slice_time_image.py ds107_sub012_t1r2.nii.
When you have finished, git add your edits to slice_time_image.py,
commit, push up to your github fork, and them make a pull request to the main
repository. I will review these as they come in.
Feel free to put up questions or point out problems using the Github issues for our repository.
Read:
- Optimizing in space.
There is a copy of this notebook in your
day3repository if you want to try running it interactively; - About the image affine and Coordinate transformations.