Metadata-Version: 2.1
Name: pygaps
Version: 1.6.0
Summary: A framework for processing adsorption data for porous materials
Home-page: https://github.com/pauliacomi/pygaps
Author: Paul Iacomi
Author-email: iacomi.paul@gmail.com
License: MIT license
Project-URL: Documentation, https://pygaps.readthedocs.io
Project-URL: Source Code, https://github.com/pauliacomi/pygaps
Keywords: adsorption,science,porous materials
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: Unix
Classifier: Operating System :: POSIX
Classifier: Operating System :: Microsoft :: Windows
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Scientific/Engineering :: Physics
Requires-Dist: numpy (>=1.13)
Requires-Dist: scipy (>=1.0.0)
Requires-Dist: pandas (>=0.21.1)
Requires-Dist: matplotlib (>=2.1)
Requires-Dist: xlrd (>=1.1)
Requires-Dist: xlwt (>=1.3)
Requires-Dist: coolprop (>=6.0)
Requires-Dist: requests
Provides-Extra: rest
Requires-Dist: docutils (>=0.11doc8) ; extra == 'rest'
Requires-Dist: pandoc ; extra == 'rest'
Requires-Dist: restructuredtext-lint ; extra == 'rest'

========
Overview
========

pyGAPS (Python General Adsorption Processing Suite) is a framework for adsorption data analysis written in Python 3.




Features
========

    - Advanced adsorption data import and manipulation
    - Routine analysis such as BET/Langmuir surface area, t-plot, alpha-s, Dubinin plots etc.
    - Pore size distribution calculations for mesopores (BJH, Dollimore-Heal)
    - Pore size distribution calculations for micropores (Horvath-Kawazoe)
    - Pore size distribution calculations using DFT kernels
    - Isotherm model fitting (Henry, Langmuir, DS/TS Langmuir, etc..)
    - IAST calculations for binary and multicomponent adsorption
    - Isosteric enthalpy of adsorption calculations
    - Parsing to and from multiple formats such as Excel, CSV and JSON
    - An sqlite database backend for storing and retrieving data
    - Simple methods for isotherm graphing and comparison

Citing
======

A peer-reviewed paper regarding pyGAPS is currently in the process of being
published. In the meantime, consider citing the *preprint* if you use the
program in your work.

Paul Iacomi, Philip L. Llewellyn, 2019.
pyGAPS: A Python-Based Framework for Adsorption Isotherm
Processing and Material Characterisation.
https://doi.org/10.26434/chemrxiv.7970402.v1


Documentation
=============

For more info, as well as a complete manual and reference visit:

https://pygaps.readthedocs.io/

Most of the examples in the documentation are actually in the form of Jupyter Notebooks
which are turned into webpages with nbsphinx. You can find them for download in:

https://github.com/pauliacomi/pyGAPS/tree/master/docs/examples


Installation
============

The easiest way to install pyGAPS is from the command line.
Make sure that you have `numpy`, `scipy`, `pandas` and `matplotlib`, as well as
`CoolProp` already installed.

.. code-block:: bash

    pip install pygaps

`Anaconda/Conda <https://www.anaconda.com/>`__ is your best bet since it manages
environments for you. First create a new environment and use conda to
install the dependencies (or start with one that already has a full instalation).
Then use pip inside your environment.

.. code-block:: bat

    conda create -n py3 python=3 numpy scipy pandas matplotlib CoolProp
    conda activate py3
    pip install pygaps

Alternatively, to install the development branch, clone the repository from Github.
Then install the package with pip or setuptools, either in regular or developer mode.

.. code-block:: bash

    git clone https://github.com/pauliacomi/pyGAPS

    // then install

    pip install ./              # pip
    python setup.py install     # setuptools

    // or developer mode

    pip install -e ./           # pip
    python setup.py develop     # setuptools

Development
===========

If you have all the python environments needed to run the entire test suite,
use tox. To run the all tests run::

    tox

Note, to combine the coverage data from all the tox environments run:

.. list-table::
    :widths: 10 90
    :stub-columns: 1

    - - Windows
      - ::

            set PYTEST_ADDOPTS=--cov-append
            tox

    - - Other
      - ::

            PYTEST_ADDOPTS=--cov-append tox

For testing only with the environment you are currently on, run instead

.. code-block:: bash

    python setup.py test

    # or run pytest

    pytest

Alternatively, you can depend on
`TravisCI <https://travis-ci.org/pauliacomi/pyGAPS>`__ for testing,
which will be slower overall but should have all the environments required.

Questions?
==========

I'm more than happy to answer any questions. Shoot an email to
mail( at )pauliacomi.com or find me on some social media.

For any bugs found, please open an
`issue <https://github.com/pauliacomi/pyGAPS/issues/>`__ or, even better,
submit a `pull request <https://github.com/pauliacomi/pyGAPS/pulls/>`__.
It'll make my life easier.
This also applies to any features which you think might benefit the project.


