Results

Submodules

Classes

Results

Subclass to intuitively group the results.

Functions

combine_df_beta_per_limit_state(calc_results)

combine_df_beta_per_scenario_rp(calc_results)

combine_df_beta_per_scenario_cp(calc_results)

combine_df_beta_per_scenario_final(calc_results)

calculate_df_beta_per_uittredepunt(geoprob_pipe, results)

Generates the DataFrame of the final result for the exit points.

construct_df_beta_per_vak(results)

Constructs the DataFrame of the final result for the vakken.

construct_df(geoprob_pipe)

Package Contents

combine_df_beta_per_limit_state(calc_results)
Parameters:

calc_results (List[Calcresult])

Return type:

pandas.DataFrame

combine_df_beta_per_scenario_rp(calc_results)
Parameters:

calc_results (List[Calcresult])

Return type:

pandas.DataFrame

combine_df_beta_per_scenario_cp(calc_results)
Parameters:

calc_results (List[Calcresult])

Return type:

pandas.DataFrame

combine_df_beta_per_scenario_final(calc_results)
Parameters:

calc_results (List[Calcresult])

Return type:

pandas.DataFrame

calculate_df_beta_per_uittredepunt(geoprob_pipe, results)

Generates the DataFrame of the final result for the exit points.

Because there is an automated decision-making in the scenario calculations (see flow chart over there), for the exit points the flow chart is extended below.

Flow chart final result exit point calculations
Parameters:
Returns:

Return type:

pandas.DataFrame

construct_df_beta_per_vak(results)

Constructs the DataFrame of the final result for the vakken.

Because there is an automated decision-making in the scenario and exit point calculations (see flow charts over there), for the vakken the flow chart is extended below.

Flow chart final result vak calculations
Parameters:

results (Results)

Returns:

Return type:

pandas.DataFrame

construct_df(geoprob_pipe)
Parameters:

geoprob_pipe (Geoprobpipe)

class Results(geoprob_pipe)

Subclass to intuitively group the results.

Parameters:

geoprob_pipe (Geoprobpipe)

geoprob_pipe
df_beta_limit_states
df_beta_scenarios_rp
df_beta_scenarios_cp
df_beta_scenarios_final
_df_alphas_influence_factors_and_physical_values: pandas.DataFrame | None = None
df_beta_uittredepunten
df_beta_vakken
df_alphas_influence_factors_and_physical_values(filter_deterministic=True, filter_derived=False)
Parameters:

  • filter_deterministic (bool)

  • filter_derived (bool)

Return type:

pandas.DataFrame

property export_dir: str
Return type:

str

export_results(bool_beta_limit_states=True, bool_beta_scenarios_rp=True, bool_beta_scenarios_cp=True, bool_beta_scenarios_final=True, bool_alphas_influence_factors_and_physical_values=True, bool_beta_uittredepunten=True, bool_beta_vakken=True)
Parameters:

  • bool_beta_limit_states (bool)

  • bool_beta_scenarios_rp (bool)

  • bool_beta_scenarios_cp (bool)

  • bool_beta_scenarios_final (bool)

  • bool_alphas_influence_factors_and_physical_values (bool)

  • bool_beta_uittredepunten (bool)

  • bool_beta_vakken (bool)