`src.plotting.task_plot_decomposition`¶

This module holds the code to compute marginal contributions and shapley values.

Module Contents¶

`task_plot_decomposition_of_infection_channels_in_spring`(depends_on, produces)
`task_plot_decomposition_of_rapid_tests_in_spring`(depends_on, produces)
`_create_bar_plot`(df, scenario_to_members, no_effects_scenario, ordering, color)
`_create_area_plot`(df, scenario_to_members, no_effects_scenario, ordering, color)
`_compute_ratios_based_on_shapley_values`(s, scenario_to_members: Dict[str, frozenset], no_effects_scenario: str)
`_compute_shapley_values`(coalitions)	Compute Shapley values.
`_compute_marginal_effects`(coalitions)
`_compute_shapley_values_from_marginal_effects`(coalitions)

_ORDERED_CHANNELS = ['Rapid Tests', 'Seasonality', 'Vaccinations'][source]¶

task_plot_decomposition_of_infection_channels_in_spring(depends_on, produces)[source]¶

task_plot_decomposition_of_rapid_tests_in_spring(depends_on, produces)[source]¶

_create_bar_plot(df, scenario_to_members, no_effects_scenario, ordering, color)[source]¶

_create_area_plot(df, scenario_to_members, no_effects_scenario, ordering, color)[source]¶

_compute_ratios_based_on_shapley_values(s, scenario_to_members: Dict[str, frozenset], no_effects_scenario: str)[source]¶

_compute_shapley_values(coalitions)[source]¶

Compute Shapley values.

Parameters

coalitions (pandas.DataFrame) –

A DataFrame where each row contains one coalition and an associated payoff.

"members" contains an iterable with all the members participating in the specific coalition.
"payoff" contains the value associated with the coalition.

Returns

shapley_values – The Shapley values associated with each of the members found in all coalitions.

Return type

pandas.Series