semvec/pypi-packages huggingface dataset:
diagonal 0.0.2
A small collection of functions to get various diagonals of a 2d matrix

# A small module for getting diagonals in a 2D Array

```python
import diagonal
arr = [] #your array
```

### Definition

#### get(arr, start = "0", direction = "up", type="all")

**start** (single character)

0 - start from the first row

m - start from m'th row

**direction** (string)

up - uses upward direction for traversal

down - downward direction for traversal

**type **(string)

all - default value which indicates that all diagonals are considered

main - gives the main diagonal of square matrix

anti - gives anti diagonal of square matrix

zigzag - gives zigzag traversal of the matrix



---



### Usages

1. Square matrix

   * Main diagonal  `diagonal.get(arr, type = "main")`

   * Anti diagonal `diagonal.get(arr, type = "anti")`

   * Also zigzags upwards and downwards

     ` diagonal.get(arr, type = "zigzag" ,direction ="up")`

2. Other matrices

   All traversals except main and anti diagonals

   Ex: `diagonal.get(arr, start = "0", direction = "up")` gives all diagonals starting from the first elements traversed in upward direction.

### Return values

* Any errors return a string

* Main and Anti diagonal traversals returns a list

* ZigZag traversals return a list

* Others return a list of list having individual diagonals
html-to-draftjs 1.0.1
Convert basic HTML into DraftJS JSON format.

<div align='center'>
  <h1>HTML to DraftJS</h1>
  <p>Convert HTML into DraftJS JSON format.</p>
  <p>
    <a href='https://travis-ci.org/NyanKiyoshi/html-to-draftjs/'>
      <img src='https://travis-ci.org/NyanKiyoshi/html-to-draftjs.svg?branch=master' alt='Requirement Status' />
    </a>
    <a href='https://codecov.io/gh/NyanKiyoshi/html-to-draftjs'>
      <img src='https://codecov.io/gh/NyanKiyoshi/html-to-draftjs/branch/master/graph/badge.svg' alt='Coverage Status' />
    </a>
    <a href='https://pypi.python.org/pypi/html-to-draftjs'>
      <img src='https://img.shields.io/pypi/v/html-to-draftjs.svg' alt='Version' />
    </a>
  </p>
  <p>
    <a href='https://github.com/NyanKiyoshi/html-to-draftjs/compare/v1.0.1...master'>
      <img src='https://img.shields.io/github/commits-since/NyanKiyoshi/html-to-draftjs/v1.0.1.svg' alt='Commits since latest release' />
    </a>
    <a href='https://pypi.python.org/pypi/html-to-draftjs'>
      <img src='https://img.shields.io/pypi/pyversions/html-to-draftjs.svg' alt='Supported versions' />
    </a>
    <a href='https://pypi.python.org/pypi/html-to-draftjs'>
      <img src='https://img.shields.io/pypi/implementation/html-to-draftjs.svg' alt='Supported implementations' />
    </a>
  </p>
</div>

## Installation
```
pip install html-to-draftjs
```

## Usage

```python
from html_to_draftjs import html_to_draftjs


json = html_to_draftjs("""
    <h1>My Page</h1>

    <h2>Introduction</h2>

    <p>Some <em>content</em> that is pretty <strong>interesting</strong></p>
    <p>Don't forget to <a href="https://example.com">follow me!</a></p>

    <h2>Illustration</h2>
    <p><img src="https://example.com/image.png" alt="image" /></p>
""")
```

## API
### `html_to_draftjs(raw_html_content: str[, features="lxml", strict=False]) -> dict`
Converts a given HTML input into JSON.

- `features` the features for the HTML tree-builder. By default it is set to `lxml` which is fast and powerful.
- `strict` (boolean), if false, it will only warn on invalid operations. If true, it will raise errors.

### `soup_to_draftjs(bs_object: BeautifulSoup[, strict=False]) -> dict`
Converts a given beautiful soup into JSON. Useful if you have to select a given part of the HTML content to convert it (e.g. `#content`).

- `strict` (boolean), if false, it will only warn on invalid operations. If true, it will raise errors.

## Supported Tags and Attributes

### Blocks
- `<div>`, `<p>`
- `<h1>` ... `<h6>`
- `<blockquote>`
- `<li>` and `<ol>` (doesn't support `<ul>` grouping)
- Doesn't support the `align` attribute.

### Inline Styling
- `<strong>`, `<b>`
- `<em>`, `<i>`

### Entities
- `<img src="url" [alt="alt"] [height="123"] [width="123"]>`
- `<a href="url">`
- `<br/>`
- Doesn't support the `title` and `align` attributes.

## Development
```
./setup.py develop
pip install -r requirements_dev.txt
```
sdanalysis 0.9.3
Statistical dynamics analysis of molecular dynamics trajectories.
Requires Python: >=3.6

Statdyn Analysis
================

[![Build Status](https://travis-ci.org/malramsay64/statdyn-analysis.svg?branch=master)](https://travis-ci.org/malramsay64/statdyn-analysis)
[![Documentation Status](https://readthedocs.org/projects/statdyn-analysis/badge/?version=latest)](https://statdyn-analysis.readthedocs.io/en/latest/?badge=latest)
[![codecov](https://codecov.io/gh/malramsay64/statdyn-analysis/branch/master/graph/badge.svg)](https://codecov.io/gh/malramsay64/statdyn-analysis)
[![Anaconda-Server Badge](https://anaconda.org/malramsay/sdanalysis/badges/installer/conda.svg)](https://conda.anaconda.org/malramsay)
[![Anaconda-Server Badge](https://anaconda.org/malramsay/sdanalysis/badges/version.svg)](https://anaconda.org/malramsay/sdanalysis)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/python/black)

This is a set of scripts that use
[Hoomd](https://bitbucket.org/glotzer/hoomd-blue) to perform the Molecular
dynamics simulations of a glass forming molecular liquid. There is a particular
focus on understanding the dynamic properties of these molecules.

Note that this is still very early alpha software and there are likely to be
large breaking changes that occur.

Installation
------------

The simplest method of installation is using `conda`. To install

    conda install -c malramsay statdyn-analysis

It is also possible to set the repository up as a development environment,
in which case cloning the repository and installing is possible by running

    git clone https://github.com/malramsay64/statdyn-analysis.git
    cd statdyn-analysis
    conda env create
    source activate sdanalysis-dev
    python setup.py develop

Once the environment is setup the tests can be run with

    pytest

Running Analysis
-------------------

Dynamics of a trajectory can be computed using the command

    sdanalysis comp-dynamics trajectory-Trimer-13.50-1.20.gsd

which will generate an hdf5 file of the same name containing a single table,
`dynamics` which has all the dynamic quantities tabulated. This also includes
a start index, over which statistics can be computed.

Finally the command

    sdanalysis figure

will open up a bokeh server which will allow for the interactive visualisation
of all `dump-*.gsd` files in the current directory.