mlos_viz ======== .. py:module:: mlos_viz .. autoapi-nested-parse:: mlos_viz is a framework to help visualizing, explain, and gain insights from results from the :py:mod:`mlos_bench` framework for benchmarking and optimization automation. It can be installed from `pypi <https://pypi.org/project/mlos-viz>`_ via ``pip install mlos-viz``. Overview ++++++++ Its main entrypoint is the :py:func:`plot` function, which can be used to automatically visualize :py:class:`~.ExperimentData` from :py:mod:`mlos_bench` using other libraries for automatic data correlation and visualization like :external:py:func:`dabl <dabl.plot>`. Submodules ---------- .. toctree:: :maxdepth: 1 /autoapi/mlos_viz/base/index /autoapi/mlos_viz/dabl/index /autoapi/mlos_viz/util/index /autoapi/mlos_viz/version/index Attributes ---------- .. autoapisummary:: mlos_viz.__version__ Classes ------- .. autoapisummary:: mlos_viz.MlosVizMethod Functions --------- .. autoapisummary:: mlos_viz.ignore_plotter_warnings mlos_viz.plot Package Contents ---------------- .. py:class:: MlosVizMethod(*args, **kwds) Bases: :py:obj:`enum.Enum` What method to use for visualizing the Experiment results. .. py:attribute:: AUTO The default automatic :py:class:`~.ExperimentData` visualization method. .. py:attribute:: DABL :value: 'dabl' Use DABL for automatic data correlation and visualization of :py:class:`~.ExperimentData`. .. py:function:: ignore_plotter_warnings(plotter_method: MlosVizMethod = MlosVizMethod.AUTO) -> None Suppress some annoying warnings from third-party data visualization packages by adding them to the warnings filter. :param plotter_method: The method to use for visualizing the Experiment results. :type plotter_method: MlosVizMethod .. py:function:: plot(exp_data: mlos_bench.storage.base_experiment_data.ExperimentData | None = None, *, results_df: pandas.DataFrame | None = None, objectives: dict[str, Literal['min', 'max']] | None = None, plotter_method: MlosVizMethod = MlosVizMethod.AUTO, filter_warnings: bool = True, **kwargs: Any) -> None Plots the results of the given :py:class:`~.ExperimentData`. Intended to be used from a Jupyter notebook. :param exp_data: The Experiment data to plot. :type exp_data: ExperimentData :param results_df: Optional `results_df` to plot. If not provided, defaults to :py:attr:`.ExperimentData.results_df` property. :type results_df: pandas.DataFrame | None :param objectives: Optional objectives to plot. If not provided, defaults to :py:attr:`.ExperimentData.objectives` property. :type objectives: Optional[dict[str, Literal["min", "max"]]] :param plotter_method: The method to use for visualizing the Experiment results. :type plotter_method: MlosVizMethod :param filter_warnings: Whether or not to filter some warnings from the plotter. :type filter_warnings: bool :param kwargs: Remaining keyword arguments are passed along to the underlying plotter(s). :type kwargs: dict .. py:data:: __version__ :value: '0.6.2'