mne-testing-icalabel-data
Data for mne-icalabel testing.
Acquire this data in MNE
Use mne.datasets.icalabel.data_path(verbose=True)
.
Update to the latest version in MNE
Use mne.datasets.icalabel.data_path(force_update=True, verbose=True)
.
Add or change files in the repo for use with MNE
-
Ensure your only option is to add files here. Alternatives would be e.g.:
- See if you can make use of existing files
- Synthesize the necessary testing files using e.g. RawArray and NumPy directly
-
If new files are needed, make a PR to this repo to add your files.
.. warning:: Make files as small as possible while ensuring proper testing! This often means e.g. cropping to a very short segment of data or using a small subset of channels.
-
Update the
version.txt
of the repo in your PR to the next increment. -
Once your PR is merged, ask a maintainer to cut a new release of the testing data, e.g. 0.53.
-
In MNE, update
mne/datasets/utils.py
to:-
Change the
'testing'
value in thereleases
dict inmne/datasets/utils.py
to the new version. -
Set the new hash. This can be easily done by either:
-
Downloading and running
md5sum
on this (with the proper version number):https://codeload.github.com/mne-tools/mne-testing-icalabel-data/tar.gz/0.01
or
-
Force-updating the repo and looking at the error message (as it gives the new true hash), e.g.:
$ python -c "import mne; mne.datasets.testing.data_path(force_update=True)"
-
-