pyextremes
Extreme Value Analysis (EVA) in Python
Documentation: https://georgebv.github.io/pyextremes/
License: MIT
E-Mail: [email protected]
pyextremes is a Python library aimed at performing univariate Extreme Value Analysis (EVA). It provides tools necessary to perform a wide range of tasks required to perform EVA, such as:
- extraction of extreme events from time series using methods such as Block Maxima (BM) or Peaks Over Threshold (POT)
- fitting continuous distributions, such as GEVD, GPD, or user-specified continous distributions to the extracted extreme events
- visualization of model inputs, results, and goodness-of-fit statistics
- estimation of extreme events of given probability or return period (e.g. 100-year event) and of corresponding confidence intervals
- tools assisting with model selection and tuning, such as selection of block size in BM and threshold in POT
Get latest version from PyPI:
pip install pyextremesGet latest experimental build from GitHub:
pip install "git+https://github.com/georgebv/pyextremes.git#egg=pyextremes"Get pyextremes for the Anaconda Python distribution:
conda install -c conda-forge pyextremesThis section will be removed in the future in favor of the official documentation which can be found at https://georgebv.github.io/pyextremes/.
Model diagnostic
Extreme value extraction
Trace plot
Corner plot
