Metadata-Version: 2.1
Name: pysat
Version: 3.0.0
Summary: 'Supports science analysis across disparate data platforms'
Home-page: https://github.com/pysat/pysat
Author: Russell Stoneback, et al.
Author-email: pysat.developers@gmail.com
License: UNKNOWN
Description: <div align="center">
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                <img width="20%" src="/logo.png" alt="pysat" title="pysat"</img>
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        # pysat: Python Satellite Data Analysis Toolkit
        [![Build Status](https://travis-ci.com/pysat/pysat.svg?branch=main)](https://travis-ci.com/pysat/pysat)
        [![Documentation Status](https://readthedocs.org/projects/pysat/badge/?version=latest)](http://pysat.readthedocs.io/en/latest/?badge=latest)
        [![Coverage Status](https://coveralls.io/repos/github/pysat/pysat/badge.svg?branch=main)](https://coveralls.io/github/pysat/pysat?branch=main)
        [![DOI](https://zenodo.org/badge/33449914.svg)](https://zenodo.org/badge/latestdoi/33449914)
        
        The Python Satellite Data Analysis Toolkit (pysat) is a package providing a
        simple and flexible interface for downloading, loading, cleaning, managing,
        processing, and analyzing scientific measurements. Although pysat was initially
        designed for in situ satellite observations, it now supports many different
        types of ground- and space-based measurements.
        
        Full [Documentation](http://pysat.readthedocs.io/en/latest/index.html)
        
        JGR-Space Physics [Publication](https://doi.org/10.1029/2018JA025297)
        
        [Citation Info](https://pysat.readthedocs.io/en/latest/citing.html)
        
        # Main Features
        * Instrument independent analysis routines.
        * Instrument object providing an interface for downloading and analyzing a wide
          variety of science data sets.
          * Uses pandas or xarray for the underlying data structure;
            capable of handling the many forms scientific measurements take in a
            consistent manner.
          * Standard scientific data handling tasks (e.g., identifying, downloading,
            and loading files and cleaning and modifying data) are built into the
            Instrument object.
          * Supports metadata consistent with the netCDF CF-1.6 standard. Each variable
            has a name, long name, and units. Note units are informational only.
        * Simplifies data management
          * Iterator support for loading data by day/file/orbit, independent of data
            storage details.
          * Orbits are calculated on the fly from loaded data and span day breaks.
          * Iterate over custom seasons
        * Supports rigorous time-series calculations that require spin up/down time
          across day, orbit, and file breaks.
        * Includes helper functions to reduce the barrier in adding new science
          instruments to pysat
        
        # Installation
        ## Starting from scratch
        * Python and associated packages for science are freely available. Convenient
          science python package setups are available from https://www.python.org/,
          [Anaconda](https://www.anaconda.com/distribution/), and other locations
          (some platform specific). Anaconda also includes a developer environment that
          works well with pysat. Core science packages such as numpy, scipy, matplotlib,
          pandas and many others may also be installed directly via pip or your
          favorite package manager.
        
        * Installation through pip
        ```
        pip install pysat
        ```
        * Installation through github
        ```
        git clone https://github.com/pysat/pysat.git
        cd pysat
        python setup.py install
        ```
        An advantage to installing through github is access to the development branches.
        The latest bugfixes can be found in the `develop` branch.  However, this branch
        is not stable (as the name implies).  We recommend using this branch in a
        virtual environment or using `python setup.py develop`.
        ```
        git clone https://github.com/pysat/pysat.git
        cd pysat
        git checkout develop
        python setup.py develop
        ```
        * Note that pysat requires a number of packages for the install.  
          * dask
          * netCDF4
          * numpy
          * pandas
          * portalocker
          * scipy
          * toolz
          * xarray
        * The first time the package is run, you will need to specify a directory to
          store data. In python, run:
        ```
        pysat.params['data_dirs'] = 'path/to/directory/that/exists'
        ```
          * Nominal organization of data is top_dir/platform/name/tag/inst_id/files
        
Keywords: pysat,ionosphere,atmosphere,thermosphere,magnetosphere,heliosphere,observations,models,space,satellites,analysis
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Astronomy
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Topic :: Scientific/Engineering :: Atmospheric Science
Classifier: License :: OSI Approved :: BSD License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: POSIX :: Linux
Requires-Python: >=3.5
Description-Content-Type: text/markdown
