brightwind.analyse.correlation.OrthogonalLeastSquares

class brightwind.analyse.correlation.OrthogonalLeastSquares(ref_spd, target_spd, averaging_prd, coverage_threshold=0.9, preprocess=True)

Accepts two series with timestamps as indexes and averaging period.

Parameters

• ref_spd – Series containing reference speed as a column, timestamp as the index

• target_spd – Series containing target speed as a column, timestamp as the index

• averaging_prd –

  Groups data by the period specified by period.

  • 2T, 2 min for minutely average

  • Set period to 1D for a daily average, 3D for three hourly average, similarly 5D, 7D, 15D etc.

  • Set period to 1H for hourly average, 3H for three hourly average and so on for 5H, 6H etc.

  • Set period to 1MS for monthly average

  • Set period to 1AS fo annual average

• coverage_threshold – Minimum coverage to include for correlation

• preprocess – To average and check for coverage before correlating

Returns

Returns an object representing the model

__init__(ref_spd, target_spd, averaging_prd, coverage_threshold=0.9, preprocess=True)

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__(ref_spd, target_spd, averaging_prd)	Initialize self.
get_error_metrics()
get_r2()	Returns the r2 score of the model
linear_func(x)
plot([title])	For plotting
run([show_params])
show_params()	Show the dictionary of parameters
synthesize([ext_input])