Metadata-Version: 2.1
Name: sherpa
Version: 4.12.2
Summary: Modeling and fitting package for scientific data analysis
Home-page: http://cxc.harvard.edu/sherpa/
Author: Smithsonian Astrophysical Observatory / Chandra X-Ray Center
Author-email: cxchelp@head.cfa.harvard.edu
License: GNU GPL v3
Description: [![Build Status](https://travis-ci.org/sherpa/sherpa.svg?branch=master)](https://travis-ci.org/sherpa/sherpa)
        [![Documentation Status](https://readthedocs.org/projects/sherpa/badge/)](https://sherpa.readthedocs.io/)
        [![DOI](https://zenodo.org/badge/683/sherpa/sherpa.svg)](https://zenodo.org/badge/latestdoi/683/sherpa/sherpa)
        [![GPLv3+ License](https://img.shields.io/badge/license-GPLv3+-blue.svg)](https://www.gnu.org/copyleft/gpl.html)
        ![Python version](https://img.shields.io/badge/Python-3.5,3.6,3.7-green.svg?style=flat)
        
        <!-- TOC *generated with [DocToc](https://github.com/thlorenz/doctoc)* -->
        **Table of Contents**
        
        - [Sherpa](#sherpa)
        - [License](#license)
        - [How To Install Sherpa](#how-to-install-sherpa)
          - [Using Anaconda](#using-anaconda)
          - [Using pip](#using-pip)
          - [Building from source](#building-from-source)
        - [History](#history)
          - [Release History](#release-history)
          
        <!-- END doctoc generated TOC please keep comment here to allow auto update -->
        
        
        Sherpa
        ======
        
        Sherpa is a modeling and fitting application for Python. It contains a
        powerful language for combining simple models into complex expressions
        that can be fit to the data using a variety of statistics and
        optimization methods.  It is easily extensible to include user models,
        statistics, and optimization methods.  It provides a high-level User
        Interface for interactive data-analysis work, such as within a
        Jupyter notebook, and it can also be used as a library component,
        providing fitting and modeling capabilities to an application.
        
        What can you do with Sherpa?
        
        - fit 1D (multiple) data including: spectra, surface brightness profiles, light curves, general ASCII arrays
        - fit 2D images/surfaces in Poisson/Gaussian regime
        - build complex model expressions
        - import and use your own models
        - use appropriate statistics for modeling Poisson or Gaussian data
        - import new statistics, with priors if required by analysis
        - visualize the parameter space with simulations or using 1D/2D cuts of the parameter space
        - calculate confidence levels on the best fit model parameters
        - choose a robust optimization method for the fit: Levenberg-Marquardt, Nelder-Mead Simplex or Monte Carlo/Differential Evolution.
        
        Documentation for Sherpa is available at
        [Read The Docs](https://sherpa.readthedocs.io/)
        and also for [Sherpa in CIAO](http://cxc.harvard.edu/sherpa/).
        
        A [Quick Start Tutorial](http://nbviewer.ipython.org/github/sherpa/sherpa/tree/master/notebooks/SherpaQuickStart.ipynb)
        is included in the `notebooks` folder and can be opened with an `ipython notebook`.
        
        License
        =======
        
        This program is free software: you can redistribute it and/or modify it under
        the terms of the GNU General Public License as published by the Free Software
        Foundation, either version 3 of the License, or (at your option) any later
        version. A copy of the GNU General Public License can be found in the
        `LICENSE` file provided with the source code, or from the
        [Free Software Foundation](http://www.gnu.org/licenses/).
        
        How To Install Sherpa
        =====================
        
        [Full installation instructions](https://sherpa.readthedocs.io/en/latest/install.html)
        are part of the [Read The Docs](https://sherpa.readthedocs.io/)
        documentation, and should be read if the following is not sufficient.
        
        It is strongly recommended that some form of *virtual environment* is
        used with Sherpa.
        
        Sherpa is tested against Python versions 3.5, 3.6, and 3.7. It is
        expected that it will work with Python 3.8 but testing has been
        limited.
        
        The last version of Sherpa which supported Python 2.7 is
        [Sherpa 4.11.1](https://doi.org/10.5281/zenodo.3358134).
        
        Using Anaconda
        --------------
        
        Sherpa is provided for both Linux and macOS operating systems running
        Python 3.5, 3.6, and 3.7. It can be installed with the `conda`
        package manager by saying
        
            $ conda install -c sherpa sherpa
        
        Using pip
        ---------
        
        Sherpa is also available
        [on PyPI](https://pypi.python.org/pypi/sherpa) and so can be installed
        with the following command (which requires that the NumPy package is
        already installed).
        
            % pip install sherpa
        
        Building from source
        --------------------
        
        Source installation is available for platforms incompatible with the
        binary builds, or for when the default build options are not sufficient
        (such as including support for the
        [`XSPEC` model library](https://heasarc.gsfc.nasa.gov/xanadu/xspec/)).
        The steps are described in the
        [building from source](https://sherpa.readthedocs.io/en/latest/install.html#building-from-source)
        documentation.
        
        History
        =======
        
        Sherpa is developed by the [Chandra X-ray
        Observatory](http://chandra.harvard.edu/) to provide fitting and modelling
        capabilities to the [CIAO](http://cxc.harvard.edu/ciao/) analysis package. It
        has been released onto [GitHub](https://github.com/sherpa/sherpa) for users to
        extend (whether to other areas of Astronomy or in other domains).
        
        Release History
        ---------------
        
        4.12.1: 14 July 2020 [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3944985.svg)](https://doi.org/10.5281/zenodo.3944985) 
        
        4.12.0: 30 January 2020 [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3631574.svg)](https://doi.org/10.5281/zenodo.3631574)
        
        4.11.1: 1 August 2019 [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3358134.svg)](https://doi.org/10.5281/zenodo.3358134)
        
        4.11.0: 20 February 2019 [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.2573885.svg)](https://doi.org/10.5281/zenodo.2573885)
        
        4.10.2: 14 December 2018 [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.2275738.svg)](https://doi.org/10.5281/zenodo.2275738)
        
        4.10.1: 16 October 2018 [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.1463962.svg)](https://doi.org/10.5281/zenodo.1463962)
        
        4.10.0: 11 May 2018 [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.1245678.svg)](https://doi.org/10.5281/zenodo.1245678)
        
        4.9.1: 01 August 2017 [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.838686.svg)](https://doi.org/10.5281/zenodo.838686)
        
        4.9.0: 27 January 2017 [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.260416.svg)](https://doi.org/10.5281/zenodo.260416)
        
        4.8.2: 23 September 2016 [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.154744.svg)](https://doi.org/10.5281/zenodo.154744)
        
        4.8.1: 15 April 2016 [![DOI](https://zenodo.org/badge/doi/10.5281/zenodo.49832.svg)](https://doi.org/10.5281/zenodo.49832)
        
        4.8.0: 27 January 2016 [![DOI](https://zenodo.org/badge/doi/10.5281/zenodo.45243.svg)](https://doi.org/10.5281/zenodo.45243)
        
        
Platform: Linux
Platform: Mac OS X
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)
Classifier: Programming Language :: C
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Topic :: Scientific/Engineering :: Astronomy
Classifier: Topic :: Scientific/Engineering :: Physics
Requires-Python: ~=3.5
Description-Content-Type: text/markdown
