HydroErr

Name	HydroErr JSON
Version	1.24 JSON
	download
home_page	https://github.com/BYU-Hydroinformatics/HydroErr
Summary	Goodness of fit metrics for use in comparison studies, specifically for use in the field of hydrology
upload_time	2019-04-23 15:02:49
maintainer
docs_url	None
author	Wade Roberts
requires_python
license
keywords	hydrology error metrics comparison statistics forecast observed
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI
coveralls test coverage

            [![Build Status](https://travis-ci.org/BYU-Hydroinformatics/HydroErr.svg?branch=master)](https://travis-ci.org/BYU-Hydroinformatics/HydroErr)
[![codecov](https://codecov.io/gh/BYU-Hydroinformatics/HydroErr/branch/master/graph/badge.svg)](https://codecov.io/gh/BYU-Hydroinformatics/HydroErr)

Goodness of fit metrics for use in comparison studies, specifically for use in the field of hydrology

- **Documentation:** https://hydroerr.readthedocs.io/en/stable/
- **Source:** https://github.com/BYU-Hydroinformatics/HydroErr
- **Bug reports:** https://github.com/BYU-Hydroinformatics/HydroErr/issues

HydroErr provides:

- A library of over 70 error metrics to measure hydrologic skill
- Treatment of NaN, Inf, negative, and zero values.
- Scholarly journal sources and code examples for metric methods in the documentation.

Publications:
- Roberts, W., Williams, G., Jackson, E., Nelson, E., Ames, D., 2018. Hydrostats: A Python Package for Characterizing Errors between Observed and Predicted Time Series. Hydrology 5(4) 66, doi:10.3390/hydrology5040066

We would request that if you use this package that you please cite the above paper. The journal paper is open access and can be found at https://doi.org/10.3390/hydrology5040066. BibTeX, EndNote, and RIS files can be downloaded at the journal site.

[![Powered by BYU Hydroinformatics](https://img.shields.io/badge/powered%20by-BYU%20HydroInformatics-blue.svg)](http://worldwater.byu.edu/)
            

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