frflib.forecast_methods.fit_forecast.gor_fit

GOR fit Forecasters

Module Contents

Classes

GORLinearFit

GOR vs Np gor forecaster
class frflib.forecast_methods.fit_forecast.gor_fit.GORLinearFit(data, **kwargs)

Bases: frflib.forecast_methods.fit_forecast.fit_forecaster.FitForecaster

GOR vs Np gor forecaster

Fit data using model: GOR = a*Np + b

maximum value GOR as input

Parameters:

  • min_fit_points (int) – Minimum points above min. threshold required for fitting. Below that numbers, forecasting will not be computed and well will be passed to the next forecast method. (default 9)

  • max_gor (float) – Max gor (data clipped outside)

  • min_gor (float) – Min gor (data clipped outside)

  • kernel_size (int) – size of the kernel for the smoothing filter. Smoothing filter is applied before finding the bsw_fit_threshold value to avoid detecting spikes

preprocess(df=None)

realize preprocessing and returns a ready for fit data frame

Returns:

preprocessed data frame

Return type:

DF

check_validity(out)

Determine if a well_fit results is valid or not. Returns the result of the fitting by default, should be implemented in the child forecaster otherwise