Stats, linear algebra and einops for xarray
To install, run
(.venv) $ pip install xarray-einstats
See the docs for more extensive install instructions.
As stated in their website:
xarray makes working with multi-dimensional labeled arrays simple, efficient and fun!
The code is often more verbose, but it is generally because it is clearer and thus less error prone and more intuitive. Here are some examples of such trade-off where we believe the increased clarity is worth the extra characters:
| numpy | xarray |
|---|---|
a[2, 5] |
da.sel(drug="paracetamol", subject=5) |
a.mean(axis=(0, 1)) |
da.mean(dim=("chain", "draw")) |
a.reshape((-1, 10)) |
da.stack(sample=("chain", "draw")) |
a.transpose(2, 0, 1) |
da.transpose("drug", "chain", "draw") |
In some other cases however, using xarray can result in overly verbose code
that often also becomes less clear. xarray_einstats provides wrappers
around some numpy and scipy functions (mostly numpy.linalg and scipy.stats)
and around einops with an api and features adapted to xarray.
Continue at the getting started page.
xarray-einstats is in active development and all types of contributions are welcome! See the contributing guide for details on how to contribute.
- Documentation: https://einstats.python.arviz.org/en/latest/
- Contributing guide: https://einstats.python.arviz.org/en/latest/contributing/overview.html
- ArviZ project website: https://www.arviz.org
Here we list some similar projects we know of. Note that all of them are complementary and don't overlap:
If you use this software, please cite it using the following template and the version
specific DOI provided by Zenodo. Click on the badge to go to the Zenodo page
and select the DOI corresponding to the version you used
- Oriol Abril-Pla. (2022). arviz-devs/xarray-einstats
<version>. Zenodo.<version_doi>
or in bibtex format:
@software{xarray_einstats2022,
author = {Abril-Pla, Oriol},
title = {{xarray-einstats}},
year = 2022,
url = {https://github.com/arviz-devs/xarray-einstats}
publisher = {Zenodo},
version = {<version>},
doi = {<version_doi>},
}