pywasp.wasp.bwc_from_timeseries(ds, hist=None, normalize=True, revert_to_original=True, ws_bin_width=1, nwsbins=30, nsecs=12)[source]

Add timeseries to histogram

Converts a time series with wind speed & direction to derive summed histogram of the wind vector.


This function is experimental and its signature may change.

  • ds (Dataset) – PyWAsP Timeseries dataset. Can have any of the pywasp spatial data structures

  • hist (Dataset, optional) – Histogram with dimensions point, wsbin, sector containg a count Default is None, creating a histogram using ws_bin_width, nwsbins, and nsecs

  • normalize (bool) – Normalize histogram for each sector, storing the frequency per sector in “wdfreq” variable, Default True

  • revert_to_original (bool) – Return the histogram input in the same spatial struction as ds? If false, keeps the data is kept in stacked point, which is more efficient when doing large calculations for numerical wind atlases.

  • ws_bin_width (float) – width of wind speed bins

  • nwsbins (int) – Number of wind speed bins

  • nsecs (int) – Number of sectors (wind direction bins)


hist (Dataset) – Histogram with dimensions point, wsbin, sector with the values from ds-timeseries added.