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
