Metadata-Version: 2.1
Name: jadapy
Version: 1.0.0
Summary: Implementations of JDQR and JDQZ with optional integration with Trilinos.
Home-page: https://github.com/BIMAU/jadapy
Author: Sven Baars
Author-email: s.baars@rug.nl
License: Apache License 2.0
Classifier: Development Status :: 5 - Production/Stable
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Topic :: Scientific/Engineering
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: scipy>=1.10
Provides-Extra: all
Requires-Dist: pytest; extra == "all"
Provides-Extra: test
Requires-Dist: pytest; extra == "test"

# JaDaPy

JaDaPy is a Python package that implements JDQR and JDQZ using SciPy and NumPy and has optional Trilinos integration.

## Eigenvalue computation

A given generalized eigenvalue problem of the form

βAv = αBv

can be solved using JDQZ using
```Python
    alpha, beta = jdqz.jdqz(A, B)
```
or
```Python
    alpha, beta, v = jdqz.jdqz(A, B, return_eigenvectors=True)
```

## Installation

JaDaPy is best installed in a [virtual environment](https://docs.python.org/3/library/venv.html).
We state the most common steps for creating and using a virtual environment here.
Refer to the documentation for more details.

To create a virtual environment run
```
python3 -m venv /path/to/new/virtual/environment
```

and to activate the virtual environment, run
```
source /path/to/new/virtual/environment/bin/activate
```

After this, we can install JaDaPy from the JaDaPy source directory.
```
pip install .
```

This will also install all of the requirements.
If one does not want to install JaDaPy, but instead just wants to run it from the source directory, one can install the requirements by running
```
pip install -r requirements.txt
```
