Metadata-Version: 2.1
Name: pygaps
Version: 3.0.0
Summary: A framework for processing adsorption data for porous materials.
Home-page: https://github.com/pauliacomi/pygaps
Author: Paul Iacomi
Author-email: mail@pauliacomi.com
License: MIT license
Project-URL: Documentation, https://pygaps.readthedocs.io
Project-URL: Source Code, https://github.com/pauliacomi/pygaps
Description: ========
        Overview
        ========
        
        pyGAPS (Python General Adsorption Processing Suite) is a framework for
        adsorption data analysis and fitting, 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..)
            - Isosteric enthalpy of adsorption calculation.
            - IAST calculations for binary and multicomponent adsorption.
            - 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.
        
        Documentation
        =============
        
        pyGAPS is built with three key mantras in mind:
        
            - **opinionated**: There are many places where the code will suggest or
              default to what the it considers a good practice. As examples: the
              standard units, pore size distribution methods and BET calculation limits.
            - **flexible**: While the defaults are there for a reason, you can override
              pretty much any parameter. Want to pass a custom adsorbate thickness
              function or use volumetric bases? Can do!
            - **transparency**: All code is well documented and open source. There are
              no black boxes.
        
        In-depth explanations, examples and theory can be found in the
        `online documentation <https://pygaps.readthedocs.io/>`__. If you are familiar
        with Python and adsorption theory and want to jump right in, look at the
        `quickstart section
        <https://pygaps.readthedocs.io/en/latest/examples/quickstart.html>`__. Examples
        on each of the capabilities specified above can be found in the
        `examples <https://pygaps.readthedocs.io/en/latest/examples/index.html>`__. Most
        of the pages in the documentation are actually Jupyter Notebooks. You can
        download them and run them yourself from the
        `/docs/examples <https://github.com/pauliacomi/pyGAPS/tree/master/docs/examples>`__
        folder.
        
        To become well familiarised with the concepts introduced by pyGAPS, such as what
        is an Isotherm, how units work, what data is required and can be stored etc., a
        deep dive is available in the
        `manual <https://pygaps.readthedocs.io/en/latest/manual/index.html>`__.
        
        Finally, having a strong grasp of the science of adsorption is recommended, to
        understand the strengths and shortcomings of various methods. We have done our
        best to explain the theory and application range of each capability and model.
        To learn more, look at the
        `reference <https://pygaps.readthedocs.io/en/latest/reference/index.html>`__ or
        simply call ``help()`` from a python interpreter (for example
        ``help(pygaps.area_BET)``.
        
        Citing
        ======
        
        Please consider citing the related paper we published if you use
        the program in your research.
        
            Paul Iacomi, Philip L. Llewellyn, *Adsorption* (2019).
            pyGAPS: A Python-Based Framework for Adsorption Isotherm
            Processing and Material Characterisation.
            DOI: https://doi.org/10.1007/s10450-019-00168-5
        
        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:: bash
        
            conda create -n myenv python=3 numpy scipy pandas matplotlib
            conda activate myenv
            pip install pygaps
        
        To install the development branch, clone the repository from GitHub.
        Then install the package with pip either in regular or developer mode.
        
        .. code-block:: bash
        
            git clone https://github.com/pauliacomi/pyGAPS
        
            # then install
            pip install pyGAPS/
        
            # or developer mode
            pip install -e pyGAPS/
        
        Development
        ===========
        
        If you want to contribute to pyGAPS or develop your own code from the package,
        check out the detailed information in CONTRIBUTING.rst.
        
        Bugs or questions?
        ==================
        
        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. I'm also more than happy to answer any questions. Shoot an email to
        mail( at )pauliacomi.com or find me at https://pauliacomi.com or on
        `Twitter <https://twitter.com/iacomip>`__.
        
Keywords: adsorption,characterization,porous materials
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Operating System :: Unix
Classifier: Operating System :: POSIX
Classifier: Operating System :: Microsoft :: Windows
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Topic :: Scientific/Engineering :: Chemistry
Requires-Python: >=3.6
Description-Content-Type: text/x-rst
Provides-Extra: dev
Provides-Extra: docs
