Anwar Nunez-Elizalde
Anwar Nunez-Elizalde
Anatomical data can be viewed using the built-in `identity` transform in pycortex: ``` import cortex nifti = cortex.db.get_anat('S1') arr = nifti.get_data().T vol = cortex.Volume(arr, 'S1', 'identity') cortex.webgl.show(vol) ```
Currently, `cortex.fmriprep` imports the subject from an fmriprep dataset as the subject ID within that dataset. The same subject ID (e.g. 001), exists across multiple datasets (e.g. ds000014/sub001/ and ds000032/sub001/)...
The options are fixing travis setup or switching to github workflows
abstract away numpy/torch to allow for cpu/gpu agnostic code.
requires minor modifications from old API
needs to be double checked
a complex pyramid class that constructs two static pyramids with 0 and 90 degree spatial phase offsets
It should be feasible to have a running buffer of image luminance values and compute the motion-energy features using that buffer only. advantages: removes memory errors due to loading a...
* force break when detecting PY2 * make new release on pip
* Roundtrip test for non-continguous F and C order arrays that trigger at 2GB -- as per defaults * Roundtrip test for all dtype/order conditions that use large array compression...