cave.analyzer.parallel_coordinates module

class cave.analyzer.parallel_coordinates.ParallelCoordinates(original_rh: smac.runhistory.runhistory.RunHistory, validated_rh: smac.runhistory.runhistory.RunHistory, validator: smac.utils.validate.Validator, scenario: smac.scenario.scenario.Scenario, default: ConfigSpace.configuration_space.Configuration, incumbent: ConfigSpace.configuration_space.Configuration, param_imp: Union[None, Dict[str, float]], params: Union[int, List[str]], n_configs: int, pc_sort_by: str, output_dir: str, cs: ConfigSpace.configuration_space.ConfigurationSpace, runtime: bool = False, max_runs_epm: int = 3000000)[source]

Bases: cave.analyzer.base_analyzer.BaseAnalyzer

This function prepares the data from a SMAC-related format (using runhistories and parameters) to a more general format (using a dataframe). The resulting dataframe is passed to the parallel_coordinates-routine

Parameters
  • original_rh (RunHistory) – runhistory that should contain only runs that were executed during search

  • validated_rh (RunHistory) – runhistory that may contain as many runs as possible, also external runs. this runhistory will be used to build the EPM

  • validator (Validator) – validator to be used to estimate costs for configurations

  • scenario (Scenario) – scenario object to take instances from

  • incumbent (default,) – default and incumbent, they will surely be displayed

  • param_imp (Union[None, Dict[str->float]) – if given, maps parameter-names to importance

  • params (Union[int, List[str]]) – either directly the parameters to displayed or the number of parameters (will try to define the most important ones

  • n_configs (int) – number of configs to be plotted

  • pc_sort_by (str) – defines the pimp-method by which to choose the plotted parameters

  • max_runs_epm (int) – maximum number of runs to train the epm with. this should prevent MemoryErrors

  • output_dir (str) – output directory for plots

  • cs (ConfigurationSpace) – parameter configuration space to be visualized

  • runtime (boolean) – runtime will be on logscale

get_html(d=None, tooltip=None)[source]
Parameters
  • n_configs (int) – number of configurations to plot (if this is less than available, worst configurations will be removed)

  • params (List[str]) – what parameters to plot

get_jupyter()[source]
Parameters
  • n_configs (int) – number of configurations to plot (if this is less than available, worst configurations will be removed)

  • params (List[str]) – what parameters to plot

get_params(params)[source]
get_plots()[source]
Parameters
  • n_configs (int) – number of configurations to plot (if this is less than available, worst configurations will be removed)

  • params (List[str]) – what parameters to plot

get_static_plots() → List[str]

Returns plot-paths, if any are available

Returns

plot_paths – returns list of strings

Return type

List[str]

get_table()

Get table, if available