semvec/pypi-packages huggingface dataset:
GaloisField 0.1.1
Galois Finite Field Implementation in Python 3
Requires Python: >=3.5

Galois Field (GF) is a field contains a finite number of elements. There are 2 types of Galois Field:
1. Prime Field (m = 1)
2. Extension Field (m != 1)

In prime field, elements are integer within [0, p-1] range. Prime field have a prime `p` that limits our value so it will always be within the field.

In extension field, elements can be polynomials with maximum degree of (m-1). Extension field have a prime `p` and prime polynomial (irreducible) that limits our polynomial and its values so it will always be within the field.
comment-object 0.0.0
An explicit object for comments
Requires Python: >=2.7
Keywords: comment

# comment

The `comment` Python library provides an explicit object for comments.

## Install

```
pip install comment-object
```

## Usage

You can use `Comment` as a context. It does nothing but expell all comments
from your source code!

```
from comment import Comment

with Comment("seconds") as c:
    DAY = 60 * 60 * 24
```

## Philosophy

A comment should have its scope inside some other code scope.

For example,

```
DAY = 60 * 60 * 24 # seconds
```

The comment "# seconds" explains `DAY` constant that it has the unit second.
The scope of this comment is this one line, inside module scope maybe.

A comment can be replaced with an object which does not have any effects on
the code around.

If a comment breaks the principle, then it is not a comment.
The coding comment, for example, can be such a type; it should be called a pragma.

## License

See LICENSE.txt.
picturedrocks 1.0.2
Single Cell RNA Sequencing Marker Selection Package
Requires Python: ~=3.6

# PicturedRocks Single Cell Analysis Tool

[![Build Status](https://travis-ci.com/umangv/picturedrocks.svg?branch=master)](https://travis-ci.com/umangv/picturedrocks)
[![Documentation Status](https://readthedocs.org/projects/picturedrocks/badge/?version=latest)](https://picturedrocks.readthedocs.io/en/latest/?badge=latest)

PicturedRocks is a python package that implements information-theoretic feature selection algorithms. 

## Usage

To install the latest GitHub version of PicturedRocks, do an "editable" installation of PicturedRocks:
```
git clone git@github.com:umangv/picturedrocks.git
cd picturedrocks
pip install -e .
```

PicturedRocks in compatible with `scanpy` and uses its `AnnData` objects. Most methods require cluster labels to be loaded. 

```python
from picturedrocks.read import read_clusts, process_clusts
adata = read_clusts(adata, "clust_labels.csv")
adata = process_clusts(adata)
```

More detailed information can be found on the [online documentation](https://picturedrocks.rtfd.io/).

## Code Style

Pull requests are welcome. Please use [numpy-style docstrings](https://sphinxcontrib-napoleon.rtfd.io/) and format your code with [black](https://black.rtfd.io).

## Copyright

Copyright © 2017-2019 Umang Varma, Anna Gilbert

PicturedRocks is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.

PicturedRocks is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.

You should have received a copy of the GNU General Public License
along with PicturedRocks.  If not, see <http://www.gnu.org/licenses/>.