flasc.data_processing.dataframe_manipulations.set_pow_ref_by_n_closest_upstream_turbines#
- flasc.data_processing.dataframe_manipulations.set_pow_ref_by_n_closest_upstream_turbines(df, df_upstream, turb_no, x_turbs, y_turbs, exclude_turbs=[], N=5)[source]#
Add pow_ref column using N-nearest upstream turbines.
Add a column called 'pow_ref' to your dataframe, which is the mean of the columns pow_%03d for the N closest turbines that are upstream of the turbine of interest [turb_no].
- Parameters:
df (pd.Dataframe) -- Dataframe with measurements. This dataframe typically consists of wd_%03d, ws_%03d, ti_%03d, pow_%03d, and potentially additional measurements.
df_upstream (pd.Dataframe) -- Dataframe containing rows indicating wind direction ranges and the corresponding upstream turbines for that wind direction range. This variable can be generated with flasc.utilities.floris_tools.get_upstream_turbs_floris(...).
turb_no (int) -- Turbine number from which the radius should be calculated.
x_turbs ([list, array]) -- Array containing x locations of turbines.
y_turbs ([list, array]) -- Array containing y locations of turbines.
exclude_turbs ([list, array]) -- array-like variable containing turbine indices that should be excluded in determining the column mean quantity.
N (int) -- Number of closest turbines to consider for the calculation of the averaged column quantity. Defaults to 5.
- Returns:
- Dataframe which equals the inserted dataframe
plus the additional column called 'pow_ref'.
- Return type:
pd.Dataframe