semvec/pypi-packages huggingface dataset:
SpatialKappa 2.1.5
Implementation of syntactic extension of Kappa to allow expression of location and transport in models
Requires Python: <3

SpatialKappa
============

14 September 2012

Copyright © 2012 DemonSoft.org [http://www.demonsoft.org/](http://www.demonsoft.org)

Copyright © 2014 David C Sterratt <david.c.sterratt@ed.ac.uk>

INTRODUCTION
------------

This project contains an implementation of a syntactic extension of Kappa to allow expression of location and transport in models. A user manual is available [here][manual-link].

Feel free to add bug reports or feature requests [here][bug-link].

ACKNOWLEDGEMENTS
----------------

The development of Spatial Kappa was funded in part by <a href="http://www.csbe.ed.ac.uk/">SynthSys</a>. SynthSys is a Centre for Integrative Systems Biology (CISB) funded by BBSRC and EPSRC, reference BB/D019621/1.

DISCLAIMER
----------	

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

[bug-link]: https://github.com/lptolik/SpatialKappa/issues
[manual-link]: https://github.com/lptolik/SpatialKappa/raw/master/docs/manual/SpatialKappaManual-v2.1.0.pdf
[1]: python/INSTALL.md
rawimage 0.0.2
Read and write RAW images (or data arrays) without a headache.
Keywords: ndarray data development reader writer raw-image image raw

RawImage    
-----------

.. image:: https://travis-ci.org/ashkarin/rawimage.svg?branch=master 
    :target: https://travis-ci.org/ashkarin/rawimage


**RawImage** is the package for reading and writing images (data arrays) in RAW format so that they can be easily read by the ImageJ.

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

The easiest way to install the latest version is by using pip::

    $ pip install rawimage

You may also use Git to clone the repository and install it manually::

    $ git clone https://github.com/ashkarin/rawimage.git
    $ cd rawimage
    $ python setup.py install
ndpatch 0.0.2
Extract arbitrary n-dimensional regions from ndarrays.
Keywords: ndarray patch region data development

.. image:: static/ndpatch.svg
    :height: 120
    :align: center

-----------

.. image:: https://travis-ci.org/ashkarin/ndpatch.svg?branch=master 
    :target: https://travis-ci.org/ashkarin/ndpatch


**NDPatch** is the package for extracting arbitrary regions from an N-dimensional numpy array assuming it mirrored infinitely.

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

The easiest way to install the latest version is by using pip::

    $ pip install ndpatch

You may also use Git to clone the repository and install it manually::

    $ git clone https://github.com/ashkarin/ndpatch.git
    $ cd ndpatch
    $ python setup.py install

Usage
-----
To take a patch from the array:

.. code-block:: python

  import numpy as np
  import ndpatch
  array = np.arange(25).reshape((5,5))
  index = (1, 2)
  shape = (3, 3)
  patch = ndpatch.get_ndpatch(array, shape, index)
  # patch =
  # [[ 7,  8,  9],
  #  [12, 13, 14],
  #  [17, 18, 19]]

To take get a random patch index:

.. code-block:: python

  import numpy as np
  import ndpatch
  array_shape = (5, 5)
  index = ndpatch.get_random_patch_index(array_shape)

To extract random patches from the array:

.. code-block:: python

  import numpy as np
  import ndpatch
  npatches = 10
  patch_shape = (3, 3)
  array = np.arange(100).reshape((10,10))
  patches = [ndpatch.get_random_ndpatch(array, patch_shape) for _ in range(npatches)]

To split the 3D array on set of overlapping 3D patches and rebuild it back:

.. code-block:: python

  import numpy as np
  import ndpatch
  array = np.arange(0, 125).reshape((5,5,5))
  patch_shape = (4, 3, 3)
  overlap = 2
  indices = ndpatch.get_patches_indices(array.shape, patch_shape, overlap)
  patches = [ndpatch.get_ndpatch(array, patch_shape, index) for index in indices]
  reconstructed = ndpatch.reconstruct_from_patches(patches, indices, array.shape, default_value=0)
  # Validate
  equal = (reconstructed == array)
  assert (np.all(equal))
colorcode 1.0.2
Using Python to make multi-colored 2D codes!


ColorCode
=========

A library that creates multi-colored Aztec codes.
They are actually multiple Aztec codes, merged into a single image.
Usually they are each on a separate color channel.

Command line tool
-----------------

This package comes with the `colorcode` command, that creates a color code.

For instance:

.. code-block:: bash

    colorcode "Hello World" "Python 3 RuleZ" "Let's go Aztec"

Will create a code with data ``Hello World``, ``Python 3 RuleZ`` and ``Let's go Aztec``.
Each data string must be surrounded by quotes if you run the command from a shell,
because each parameter to the command becomes a separate data set.

You can override default settings with various parameters:

.. code-block:: bash

    colorcode -o mycode.png -m 4 -i redcyan "Hello World" "Python 3 RuleZ"

- ``-o mycode.png`` means "Save the image to the file ``mycode.png``"
- ``-m 4`` means "Each square block (aka module) will have a size of 4x4 pixels"
- ``-i redcyan`` means "Use the Red/Cyan method to combine the codes instead of the default"

By default the combination method is chosen automatically depending on the number of data entries.

There are more parameters, you can find them out with ``--help`` as usual.

You can also run the command as a Python module: ``python3 -m colorcode``.

About the project
-----------------

Don't expect the project to be improved or maintained in the future.
This was mostly a learning project for me, to learn about Cython, Sphinx docs,
Python packagaing and Aztec codes.

It works, and it's fun, so I share it. But it's currently mostly useless.
There is no app to decode the codes and I don't plan to make one.

Anyway, I hope you will find this project interesting and inspiring.