Metadata-Version: 2.1
Name: pybaselines
Version: 0.1.0
Summary: A collection of algorithms for fitting the baseline of experimental data.
Home-page: https://github.com/derb12/pybaselines
Author: Donald Erb
Author-email: donnie.erb@gmail.com
License: BSD 3-Clause
Description: ===========
        pybaselines
        ===========
        
        .. image:: https://github.com/derb12/baselines/raw/main/docs/images/logo.png
            :alt: pybaselines Logo
            :align: center
        
        .. image:: https://img.shields.io/pypi/v/pybaselines.svg
            :target: https://pypi.python.org/pypi/pybaselines
            :alt: Most Recent Version
        
        .. image:: https://readthedocs.org/projects/pybaselines/badge/?version=latest
            :target: https://pybaselines.readthedocs.io
            :alt: Documentation Status
        
        .. image:: https://img.shields.io/pypi/pyversions/pybaselines.svg
            :target: https://pypi.python.org/pypi/pybaselines
            :alt: Supported Python versions
        
        .. image:: https://img.shields.io/badge/license-BSD%203--Clause-blue.svg
            :target: https://github.com/derb12/pybaselines/tree/main/LICENSE.txt
            :alt: BSD 3-clause license
        
        
        pybaselines is a collection of baseline algorithms for fitting experimental data.
        
        * For Python 3.6+
        * Open Source: BSD 3-Clause License
        * Source Code: https://github.com/derb12/pybaselines
        * Documentation: https://pybaselines.readthedocs.io.
        
        
        .. contents:: **Contents**
            :depth: 1
        
        
        Introduction
        ------------
        
        pybaselines provides different techniques for fitting baselines to experimental data.
        
        Baseline fitting techniques are grouped accordingly (note: when a method
        is labelled as 'improved', that is the method's name, not editorialization):
        
        a) Penalized least squares (pybaselines.penalized_least_squares)
        
            1) asls (Asymmetric Least Squares)
            2) iasls (Improved Asymmetric Least Squares)
            3) airpls (Adaptive iteratively reweighted penalized least squares)
            4) arpls (Asymmetrically reweighted penalized least squares)
            5) drpls (Doubly reweighted penalized least squares)
            6) iarpls (Improved Asymmetrically reweighted penalized least squares)
            7) aspls (Adaptive smoothness penalized least squares)
        
        b) Morphological (pybaselines.morphological)
        
            1) mpls (Morphological Penalized Least Squares)
            2) mor (Morphological)
            3) imor (Improved Morphological)
            4) iamor (Iterative averaging morphological)
        
        c) Polynomial (pybaselines.polynomial)
        
            1) poly (regular polynomial)
            2) modpoly (Modified Polynomial)
            3) imodpoly (Improved Modified Polynomial)
        
        d) Window-based (pybaselines.window)
        
            1) noise_median (Noise Median method)
            2) snip (Statistics-sensitive Non-linear Iterative Peak-clipping)
        
        
        Installation
        ------------
        
        Dependencies
        ~~~~~~~~~~~~
        
        pybaselines requires `Python <https://python.org>`_ version 3.6 or later and the following libraries:
        
        * `NumPy <https://numpy.org>`_ (>= 1.9)
        * `SciPy <https://www.scipy.org/scipylib/index.html>`_
        
        
        All of the required libraries should be automatically installed when installing pybaselines
        using either of the two installation methods below.
        
        
        Stable Release
        ~~~~~~~~~~~~~~
        
        pybaselines is easily installed using `pip <https://pip.pypa.io>`_, simply by running
        the following command in your terminal:
        
        .. code-block:: console
        
            pip install --upgrade pybaselines
        
        This is the preferred method to install pybaselines, as it will always install the
        most recent stable release.
        
        
        Development Version
        ~~~~~~~~~~~~~~~~~~~
        
        The sources for pybaselines can be downloaded from the `Github repo`_.
        
        The public repository can be cloned using:
        
        .. code-block:: console
        
            git clone https://github.com/derb12/pybaselines.git
        
        
        Once the repository is downloaded, it can be installed with:
        
        .. code-block:: console
        
            cd pybaselines
            python setup.py install
        
        
        .. _Github repo: https://github.com/derb12/pybaselines
        
        
        Usage
        -----------
        
        To be added...
        
        
        Contributing
        ------------
        
        Contributions are welcomed and greatly appreciated. For information on submitting bug reports,
        pull requests, or general feedback, please refer to the `contributing guide`_.
        
        .. _contributing guide: https://github.com/derb12/pybaselines/tree/main/docs/contributing.rst
        
        
        Changelog
        ---------
        
        Refer to the changelog_ for information on pybaselines's changes.
        
        .. _changelog: https://github.com/derb12/pybaselines/tree/main/CHANGELOG.rst
        
        
        License
        -------
        
        pybaselines is open source and freely available under the BSD 3-clause license.
        For more information, refer to the license_.
        
        .. _license: https://github.com/derb12/pybaselines/tree/main/LICENSE.txt
        
        
        Author
        ------
        
        * Donald Erb <donnie.erb@gmail.com>
        
Keywords: materials characterization,baseline,background,baseline subtraction,background subtraction
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
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: Topic :: Scientific/Engineering :: Chemistry
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Scientific/Engineering :: Physics
Requires-Python: >=3.6
Description-Content-Type: text/x-rst
