Metadata-Version: 2.1
Name: PyForecastTools
Version: 1.1.1
Summary: Model validation and forecast verification tools
Home-page: https://github.com/drsteve/PyForecastTools
Author: Steve Morley
Author-email: smorley@lanl.gov
License: BSD License
Description: # PyForecastTools
        
        [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.1256921.svg)](https://doi.org/10.5281/zenodo.1256921)
        [![Build Status](https://travis-ci.org/drsteve/PyForecastTools.svg?branch=master)](https://travis-ci.org/drsteve/PyForecastTools)
        
        A Python module to provide model validation and forecast verification tools,
        including a set of convenient plot functions. A selection of capabilites
        provided by PyForecastTools includes:
         * Accuracy and bias metrics for continuous predictands
             - Unscaled/absolute measures
             - Relative measures
             - Scaled measures
         * 2x2 and NxN contingency table classes
             - Wide range of contingency table metrics and scores
             - Multiple methods of calculating confidence intervals on scores
         * Convenient plotting for visually comparing models and data
             - Quantile-Quantile plots
             - Taylor diagrams
             - ROC curves
             - Reliability diagrams
        
        The module builds on the scientific Python stack (Python, Numpy, MatPlotLib)
        and uses the dmarray class from SpacePy's datamodel.
        
        SpacePy is available through the Python Package Index, MacPorts, and is under
        version control at [github.com/spacepy/spacepy](https://github.com/spacepy/spacepy)
        If SpacePy is not available a reduced functionality implementation of the class
        is provided with this package.
        
        PyForecastTools is available through the Python Package Index and can be installed
        simply with
        
        > pip install PyForecastTools --user
        
        To install (local user), run
        
        > python setup.py install --user
        
        After installation, the module can then be imported (within a Python script or 
        interpreter) by
        
        > import verify
        
        For help, please see the docstrings for each function and/or class.
        
        Additional documentation is under development using Github pages at [drsteve.github.io/PyForecastTools](https://drsteve.github.io/PyForecastTools), and source for this is in the [docs folder](docs/).
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: BSD License
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Astronomy
Classifier: Topic :: Scientific/Engineering :: Atmospheric Science
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Description-Content-Type: text/markdown
