Metadata-Version: 2.1
Name: blockmatrix
Version: 0.2.1
Summary: Utilities to handle blockmatrices, especially covariance matrices.
Home-page: https://github.com/jsosulski/blockmatrix
License: BSD-3-Clause
Keywords: block matrix,numpy,spatio-temporal data
Author: Jan Sosulski
Author-email: mail@jan-sosulski.de
Requires-Python: >=3.8,<4.0
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Provides-Extra: channels
Provides-Extra: solver
Requires-Dist: matplotlib (>=3.5.1,<4.0.0)
Requires-Dist: mne (>=0.24.1,<0.25.0); extra == "channels"
Requires-Dist: seaborn (>=0.11.2,<0.12.0)
Requires-Dist: toeplitz (>=0.3.2,<0.4.0); extra == "solver"
Requires-Dist: vg (>=2.0.0,<3.0.0)
Project-URL: Repository, https://github.com/jsosulski/blockmatrix
Description-Content-Type: text/markdown

# blockmatrix

A python package to provide easier working with block-structured matrices. Currently, this
code mostly serves my purposes, i.e., manipulating block-structured covariance matrices
and applying high-dimensional estimation techniques to them.

This package is also available on PyPi.

## Usage

As of now unfortunately only the code and the docstrings are available as documentation.

Running the `examples/main_spatiotemporal_manipulations.py` showcases some of the
functionality and visualizations.

## Todos

- [ ] Documentation
- [ ] Testing
- [x] Implementation of sklearn style covariance estimators
  - Moved to ToeplitzLDA package
- [x] Abstract mne channels away
  - Using optional mne dependency
- [x] Reduce unnecessary dependencies
  - `toeplitz` is now optional

