python_api_usage#

Attributes#

`OUTPUT_FILES_PATH`
`impact_model`
`new_nodes_uncertainty_result`
`new_nodes_uncertainty_table`
`nodes_scores`
`sankey_result`
`sankey_table`
`scores`
`sobol_result`
`sobol_table`
`tree_map_result`
`tree_map_table`
`uncertainty_nodes_result`
`uncertainty_nodes_table`

`NewNodesUncertaintyResult`	Generate uncertainty for each node using Monte Carlo. Result figure as a boxplot.
`UncertaintyResult`	An impact model result is one, or a collection of tables and/or figures generated

class python_api_usage.NewNodesUncertaintyResult#

Generate uncertainty for each node using Monte Carlo. Result figure as a boxplot.

get_figure(table: pandas.DataFrame)#: Display uncertainty result of each node with boxplots, one figure per impact. :param table: results of each draw for each node as a long format table :return: all figures generated

class python_api_usage.UncertaintyResult#

Bases: apparun.results.ImpactModelResult

An impact model result is one, or a collection of tables and/or figures generated by executing an impact model.

get_figure(table: pandas.DataFrame)#: Abstract method. Generate the output as a figures, or a collection of figures, using the output of the get_table method. :param table: tabular result data. :return: figure, or collection of figure generated.

get_table() → pandas.DataFrame#: Abstract method. Generate the output as a table, or a collection of tables. :return: tabular results as a pandas DataFrame.

n: int#: Generate uncertainty for each node using Monte Carlo. Result figure as a boxplot.