windkit.ltc.VarRatMCP#

class windkit.ltc.VarRatMCP(fit_intercept=True, ws_cutoff=0.0, **kwargs)[source]#

Sectorwise MCP using variance ratio linear regression.

Parameters:

  • n_sectors (int) – Number of sectors to fit independant regression models to. Default is 12 sectors.

  • quantiles (bool) – Use equal probability sectors instead of constant widths. The sector edges are the quantiles of the reference wind directions passed to fit, pooled over all points, and are reused at predict. Sector 0 starts at north rather than being centred on it. Default is False.

  • ws_cutoff (float)

  • model_kws (dict) – kwargs to input when the model is instanciated.

model#
Type:

what model to use in each sector

models#

one instanciated model per sector

Type:

list, shape (n_sectors,)

Methods

__init__([fit_intercept, ws_cutoff])

fit(ds_ref, ds_target, **kwargs)

Fit the reference data to the target data by looping through the sectors and fitting the model to the data for that sector.

predict(ds_ref[, return_std])

Predict wind speed from the reference data.

wd_to_sector(wd[, recalc_sectors])

Convert wind direction to sector indices using the object's n_sectors and quantiles settings.