flownet.utils.plot_results module

flownet.utils.plot_results.build_ensemble_df_list(ensemble_paths: Optional[List[str]], vectors: List[str]) → List[pandas.core.frame.DataFrame]

Helper function to read and prepare ensemble data.

Parameters

• ensemble_paths – The ensemble paths to retrieve data from

• vectors – List of vector to extract

Returns

List of ensemble dataframe with required data to create plots.

flownet.utils.plot_results.check_args(args)

Helper function to verify input arguments.

Returns

Nothing

Raises

ValueError in case the input arguments are inconsistent. –

flownet.utils.plot_results.main()

Main function for the plotting of simulations results from FlowNet.

Returns

Nothing

flownet.utils.plot_results.plot(vector: str, prior_data: list, posterior_data: list, reference_simulation: Optional[ecl.summary.ecl_sum.EclSum], plot_settings: dict)

Main plotting function that generates a single plot from potentially multiple ensembles and other data.

Parameters

• vector – Name of the vector to plot.

• prior_data – List of prior ensemble data DataFrames.

• posterior_data – List of posterior ensemble data DataFrames.

• reference_simulation – EclSum object for the reference simulation.

• plot_settings – Settings dictionary for the plots.

flownet.utils.plot_results.plot_ensembles(ensemble_type: str, vector: str, ensembles_data: List[pandas.core.frame.DataFrame], plot_settings: dict)

Function to plot a list of ensembles.

Parameters

• ensemble_type – prior or posterior

• vector – Name of the vector to plot

• ensembles_data – List of dataframes with ensemble data

• plot_settings – Settings dictionary for the plots.

Returns

Nothing

Raises

Value error if incorrect plot type. –

flownet.utils.plot_results.remove_duplicates(df: pandas.core.frame.DataFrame) → pandas.core.frame.DataFrame

Remove duplicates for the combination or DATE and REAL.

Parameters

df – Input pandas DataFrame with columns: [DATE, REAL, VECTOR1, VECTOR2, …, VECTOR_N]

Returns

A cleaned dataframe