semvec/pypi-packages huggingface dataset:
coindata 1.4
Historical data manager for cryptos.

Coindata
========
|PyPI|
|Python|
|Build Status|
|License|

Read, `Markdown Documentation.`_

.. _`Markdown Documentation.`: https://github.com/Anaxilaus/coindata/tree/master/README.md/
.. |PyPI| image:: https://badge.fury.io/py/coindata.svg
    :target: https://badge.fury.io/py/coindata
.. |Build Status| image:: https://travis-ci.org/Anaxilaus/coindata.svg?branch=master
    :target: https://travis-ci.org/Anaxilaus/coindata
.. |License| image:: https://img.shields.io/badge/license-MIT-green.svg
    :target: https://github.com/Anaxilaus/coindata/blob/master/LICENSE
.. |Python| image:: https://img.shields.io/badge/Python-3.5|3.6|3.7-blue.svg
    :target: https://github.com/Anaxilaus/coindata/blob/master/.travis.yml


History
=======

1.4 (2019-03-31)
----------------
- Update documentation
- Dump as JSON
- Refactor cache.py to cacher.py

1.3 (2019-03-22)
----------------

- Refactor snapshot.py to cache.py
- Migrate from snapshot logic to single caching
- Update documentation
- Update parsing for coinmarketcap's html template change
- Add test case

1.2 (2019-01-28)
----------------

- Update snapshot.py
    - Align with documentation by refactoring take_snapshot to take
    - Add docstrings to take
- Handle first snapshot by giving warnings


1.1 (2019-01-27)
----------------

- Major update to data manager
    - Refactor main.py to request.py
    - Add snapshot.py and parser.py
    - Update documentation


1.0 (????-??-??)
----------------

- First release
tomograph 0.1
Parametrized computer tomography simulator

# tomograph - paramterized computer tomography simulator

[![Build Status](https://travis-ci.com/fkokosinski/tomograph.svg?token=KqDQHrZxZ4q79UZ1qZJw&branch=master)](https://travis-ci.com/fkokosinski/tomograph) [![codecov](https://codecov.io/gh/fkokosinski/tomograph/branch/master/graph/badge.svg?token=SogoLYXs8u)](https://codecov.io/gh/fkokosinski/tomograph)

`tomograph` is a parametrized computer tomography simulator, which can be run as
a standalone script or included as a module in your Python programs. It
implements both Radon and reverse Radon transforms. It currently models two
types of beam projections: cone and parallel.

## Dependencies
Currently `tomograph` requires:
- Click (`click`)
- tqdm (`tqdm`)
- NumPy (`numpy`)
- Image Processing SciKit (`scikit-image`)

Their respective required versions can be seen in `requirements.txt` file.

## Installation
Simply run:

    pip install tomograph

Tomograph supports Python 3.5, Python 3.6 and Python 3.7.

## Usage
`tomograph` can be used directly through command-line interface or as a Python
module:

### Commandline
Using command-line interface:

    tomograph --model cone --detectors 256 --angle 150 --rotations 512 image.jpg

All command-line arguments can be seen by running:

    tomograph --help

### Module
Example script that does Radon transform using cone beam model:

    from skimage.io import imsave
    from tomograph.model import ConeTomograph

    # variables
    path = 'image.jpg'
    detectors = 256
    angle = 180
    rotations = 512

    # one scan per rotation
    step = 360 / rotations

    # perform Radon transform
    tomograph = ConeTomograph(path, detectors, angle)
    sinogram = []
    for i in range(rotations):
        tomograph.rotate(step)  # rotate tomograph
        scan = tomograph.scan() # do the scan
        sinogram.append(scan)

    imsave('radon.bmp', np.array(sinogram).T)

## Live demonstration
| Beam lines                  | Radon transform                   | reverse Radon transform                     |
|-----------------------------|-----------------------------------|---------------------------------------------|
| ![beam lines](res/scan.gif) | ![radon transform](res/radon.gif) | ![reverse radon transform](res/reverse.gif) |