PyForecastTools | Forecast Verification/Validation Tools in Python

by drsteve Python Version: 1.1.1 License: Non-SPDX

X-Ray Key Features Code Snippets Community Discussions Vulnerabilities Install Support

kandi X-RAY | PyForecastTools Summary

PyForecastTools is a Python library. PyForecastTools has no bugs, it has no vulnerabilities, it has build file available and it has low support. However PyForecastTools has a Non-SPDX License. You can install using 'pip install PyForecastTools' or download it from GitHub, PyPI.

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:. 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 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. 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, and source for this is in the docs folder.

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PyForecastTools has a low active ecosystem.

It has 9 star(s) with 2 fork(s). There are 2 watchers for this library.

It had no major release in the last 12 months.

There are 4 open issues and 4 have been closed. On average issues are closed in 43 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of PyForecastTools is 1.1.1

Quality

PyForecastTools has 0 bugs and 0 code smells.

Security

PyForecastTools has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

PyForecastTools code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

PyForecastTools has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

PyForecastTools releases are available to install and integrate.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

Top functions reviewed by kandi - BETA

kandi has reviewed PyForecastTools and discovered the below as its top functions. This is intended to give you an instant insight into PyForecastTools implemented functionality, and help decide if they suit your requirements.

Plot the taylor diagram
Compute the bias between predicted and observed and observed data
Mask series
Plot the reliability diagram
Plot quantiles of predicted and observed data
Set the target figure
Compute ROC curve
Compute POD
Calculate the Agresti index
Calculates the Shannon index for the binomial distribution
Summarize the connectivity matrix
Calculate the accuracy between predicted and observed values
Calculate the percased similarity between two predictions
Computes the NMRSE between predicted and observed data
Compute the accuracy
Calculate median absolute absolute absolute error
Mean squared error
Mean absolute absolute error
Computes the symmetric bias of the predicted and observed data
Compute the norm of a masked image
Compute the variance of predicted predicted variance
Root standard deviation
Calculate meanEval between predicted and observed and observed data
Print summary statistics
Compute the mean percentage of the predicted and observed data
Calculate the absolute error of the predicted and observed data

Get all kandi verified functions for this library.

PyForecastTools Key Features

No Key Features are available at this moment for PyForecastTools.

PyForecastTools Examples and Code Snippets

No Code Snippets are available at this moment for PyForecastTools.

Community Discussions

No Community Discussions are available at this moment for PyForecastTools.Refer to stack overflow page for discussions.

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install PyForecastTools

You can install using 'pip install PyForecastTools' or download it from GitHub, PyPI.
You can use PyForecastTools like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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