Heatmaps of empirical and exceedance probability of many (time-)series.

Aggregate empirical and exceedance frequency/probability of many and long time-series, for example summarizing meteorological and hydrological time-series. Create cycle plots to illustrate for example annual cycles for longer time-series, see some examples of this usage below.

Also see the kdlines package for similar functionality using kernel density estimation.

This package was inspired by DenseLines by Moritz & Fisher.

Please note that this package is at alpha stage and experimental.

numpy
matplotlib

pip install eplines

See \examples folder for example applications of eplines

Temperature time-series ECDF \examples\example_temperature_timeseries.py

Discharge time-series exceedance probability (aka flow-duration curve for each individual day) \examples\example_usgs_discharge.py