mne-testing-data

Data for mne-python testing.

Acquire this data in MNE

Use mne.datasets.testing.data_path(verbose=True).

Update to the latest version in MNE

Use mne.datasets.testing.data_path(force_update=True, verbose=True).

Add or change files in the repo for use with MNE

1. 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

2. 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.

   Please add licensing information for your files under license.txt in the directory that contains the files. CC0 licensing is preferred.

3. Update the version.txt of the repo in your PR to the next increment.

4. Once your PR is merged, ask a maintainer to cut a new release of the testing data, e.g. 0.53.

5. In MNE, update mne/datasets/config.py to:

   1. Change the 'testing' value in the RELEASES dict in mne/datasets/config.py to the new version.

   2. Set the new hash. This can be easily done by either:

      1. Downloading and running md5sum on this (with the proper version number):

         https://codeload.github.com/mne-tools/mne-testing-data/tar.gz/0.53

         or

      2. 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)"