flasc.data_processing.dataframe_manipulations.set_ti_by_upstream_turbines#
- flasc.data_processing.dataframe_manipulations.set_ti_by_upstream_turbines(df, df_upstream, exclude_turbs=[])[source]#
Add TI column using upstream turbines.
Add a column called 'ti' in your dataframe with value equal to the averaged turbulence intensity measurements of all the turbines upstream, excluding the turbines listed in exclude_turbs.
- 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(...). exclude_turbs ([list, array]): array-like variable containing turbine indices that should be excluded in determining the column mean quantity.
exclude_turbs ([list, array]) -- array-like variable containing turbine indices that should be excluded in determining the column mean quantity.
- Returns:
- Dataframe which equals the inserted dataframe
plus the additional column called 'ti'.
- Return type:
pd.Dataframe