Version 1.1.1

PyForecastTools v1.1.1

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

Release history

Changes in Version 1.1.1 (2020-04-23)

• Updated version number in package metadata

Changes in Version 1.1.0 (2020-04-23)

• Restructure package with modules
• Code tidying for PEP8
• Updated license and copyright
• Documentation at drsteve.github.io/PyForecastTools
  categorical
• Added bootstrapped CI for Matthews correlation
  metrics
• Updated docstrings
• Compatibility with xarray input
  plot
• Added plot module
  • QQ plots
  • Taylor diagrams
  • ROC curves
  • Reliability diagrams

Changes in Version 1.0.1 (2018-06-27)

• Repackaged for pip install
• Expanded test coverage

Changes in Version 1.0.0 (2018-05-31)

• Initial release

Version 1.1.0

PyForecastTools

Forecast Verification/Validation Tools in Python

Changes in Version 1.1.0 (2020-04-23)

• Restructure package with modules
• Code tidying for PEP8
• Updated license and copyright
• Documentation at drsteve.github.io/PyForecastTools
  categorical
• Added bootstrapped CI for Matthews correlation
  metrics
• Updated docstrings
• Compatibility with xarray input
  plot
• Added plot module
  • QQ plots
  • Taylor diagrams
  • ROC curves
  • Reliability diagrams

PyForecastTools: Version 1.0.1

PyForecastTools: Module for forecast verification and model validation. Provides numerous metrics, including accuracy and bias, and fully featured classes for NxN contingency table analysis. Contingency2x2 class provides 3 methods for estimating confidence intervals on metrics (Wald intervals, Agresti-Coull intervals, and bootstrapped intervals).

v1.0.1 -- Repackaged for pip install, expanded test coverage

PyForecastTools: Version 1.0

PyForecastTools: Module for forecast verification and model validation. Provides numerous metrics, including accuracy and bias, and fully featured classes for NxN contingency table analysis. Contingency2x2 class provides 3 methods for estimating confidence intervals on metrics (Wald intervals, Agresti-Coull intervals, and bootstrapped intervals).