eigs


Nameeigs JSON
Version 0.0.3 PyPI version JSON
download
home_pagehttps://github.com/flaport/eigs
SummaryAn efficient complex eigensolver written in Rust.
upload_time2023-09-06 18:04:04
maintainer
docs_urlNone
authorFloris Laporte <floris.laporte@gmail.com>
requires_python>=3.9
licenseLGPL-2.1-only
keywords eigenvalues eigenvectors eigenmodes eigs
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            # eigs (The Python Package)

Find Eigenvalues and Eigenvectors efficiently in Python using UMFPACK + ARPACK (powered
by Rust).

## Example

```python
import numpy as np
from scipy.sparse import csc_matrix
from eigs import eigs

data = np.array([ 0.+4.j,  2.+3.j,  4.+0.j,  0.-2.j, -3.+3.j,  0.-1.j,
                 -3.-3.j,  4.-4.j, -4.+0.j,  4.+1.j, -4.-1.j,  4.+2.j,
                  3.+2.j,  0.+2.j, -4.+0.j, -4.+1.j, -4.+2.j, -2.+2.j,
                 -1.-2.j,  0.+3.j, -3.+0.j,  4.+0.j, -1.+3.j])  # fmt: skip
indices = np.array([6, 1, 4, 5, 7, 2, 3, 4, 5, 6, 7, 1,
                    1, 3, 3, 4, 0, 2, 5, 6, 3, 6, 7])  # fmt: skip
indptr = np.array([0, 1, 5, 11, 12, 14, 16, 20, 23])
A = csc_matrix((data, indices, indptr))
vals, vecs = eigs(A=A, num_eigs=4, sigma=-2.0 + 7.0j)

for i, val in enumerate(vals):
    print(f"{i}: {val.real} + {val.imag}j")
```
```
0: -2.3310185657008846 + 7.624960781252993j
1: -4.525347075933688 + 1.8131068538310453j
2: 5.301183172745191 + 4.2055904210543575j
3: 0.1713950830265607 + 0.46316839127801934j
```

Find more examples in the [examples](./examples) folder.

## Installation

> Eigs is currently **linux-only** (x86_64) and **python 3.9+**.
> More platforms might be supported at a later point in time.

```bash
pip install eigs
```

## License & Credits

© Floris Laporte 2023, LGPL-2.1


            

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