o }oi @sddlmZddlmZddlmZddlmZddlmZddl m Z ddl m Z ddl m Z dd lmZerLdd lmZdd lmZdd lmZed ddddddd(ddZd)d"d#Zd)d$d%Zd)d&d'ZdS)*) annotations)Callable)Sequence)experimental_func)Study) FrozenTrial)_get_pareto_front_info)_ParetoFrontInfo)_imports)Axes)Axes3D)pltz2.8.0NT) target_namesinclude_dominated_trials axis_orderconstraints_functargetsstudyrrlist[str] | Nonerboolrlist[int] | Noner/Callable[[FrozenTrial], Sequence[float]] | Nonerreturn'Axes'cCs"tt||||||}t|S)a Plot the Pareto front of a study. .. seealso:: Please refer to :func:`optuna.visualization.plot_pareto_front` for an example. Args: study: A :class:`~optuna.study.Study` object whose trials are plotted for their objective values. ``study.n_objectives`` must be either 2 or 3 when ``targets`` is :obj:`None`. target_names: Objective name list used as the axis titles. If :obj:`None` is specified, "Objective {objective_index}" is used instead. If ``targets`` is specified for a study that does not contain any completed trial, ``target_name`` must be specified. include_dominated_trials: A flag to include all dominated trial's objective values. axis_order: A list of indices indicating the axis order. If :obj:`None` is specified, default order is used. ``axis_order`` and ``targets`` cannot be used at the same time. .. warning:: Deprecated in v3.0.0. This feature will be removed in the future. The removal of this feature is currently scheduled for v5.0.0, but this schedule is subject to change. See https://github.com/optuna/optuna/releases/tag/v3.0.0. constraints_func: An optional function that computes the objective constraints. It must take a :class:`~optuna.trial.FrozenTrial` and return the constraints. The return value must be a sequence of :obj:`float` s. A value strictly larger than 0 means that a constraint is violated. A value equal to or smaller than 0 is considered feasible. This specification is the same as in, for example, :class:`~optuna.samplers.NSGAIISampler`. If given, trials are classified into three categories: feasible and best, feasible but non-best, and infeasible. Categories are shown in different colors. Here, whether a trial is best (on Pareto front) or not is determined ignoring all infeasible trials. .. warning:: Deprecated in v4.0.0. This feature will be removed in the future. The removal of this feature is currently scheduled for v6.0.0, but this schedule is subject to change. See https://github.com/optuna/optuna/releases/tag/v4.0.0. targets: A function that returns a tuple of target values to display. The argument to this function is :class:`~optuna.trial.FrozenTrial`. ``targets`` must be :obj:`None` or return 2 or 3 values. ``axis_order`` and ``targets`` cannot be used at the same time. If the number of objectives is neither 2 nor 3, ``targets`` must be specified. .. note:: Added in v3.0.0 as an experimental feature. The interface may change in newer versions without prior notice. See https://github.com/optuna/optuna/releases/tag/v3.0.0. Returns: A :class:`matplotlib.axes.Axes` object. )r checkr_get_pareto_front_plot)rrrrrrinfora/home/ubuntu/.local/lib/python3.10/site-packages/optuna/visualization/matplotlib/_pareto_front.pyplot_pareto_fronts B rrr cCs,|jdkr t|S|jdkrt|SJd)NFzMust not reach here) n_targets_get_pareto_front_2d_get_pareto_front_3drrrrr^s  rcsFtjdt\}}|dtd}|jjd| jjdd}t j dkrP|j fddj Dfd dj Dd d d d }t j dkrr|j fddj Dfddj D|d|d t jdkr|j fddjDfddjD|ddd j dur|r||S)NggplotPareto-front Plottab10rTrialcg|] \}}|jdqSrr.0_valuesr%rr tz(_get_pareto_front_2d..cr+r)r-r.r%rrr2ur3#ccccccInfeasible Trial)xycolorlabelFeasible Trialcr+r,r-r.r%rrr2|r3cr+r4r-r.r%rrr2}r3cr+r,r-r.r%rrr2r3cr+r4r-r.r%rrr2r3r! Best Trial)r styleusesubplots set_titleget_cmap set_xlabelrr set_ylabelleninfeasible_trials_with_valuesscatternon_best_trials_with_valuesbest_trials_with_valueshas_datalegend)rr0axcmap trial_labelrr%rr#gs@    r#cstjdt}|jdd}|dtd}|jj d| jj d| jj dd }j durmt j dkrm|jfd d j Dfd d j Dfd d j Ddddd}jdurt jdkr|jfdd jDfdd jDfdd jD|d|djdurt jr|jfdd jDfdd jDfdd jD|dddjdur|r||S)Nr&3d) projectionr'r(rr)r r*cr+r,r-r.r%rrr2r3z(_get_pareto_front_3d..cr+r4r-r.r%rrr2r3cr+r r-r.r%rrr2r3r5r6)xsyszsr9r:r;cr+r,r-r.r%rrr2r3cr+r4r-r.r%rrr2r3cr+rPr-r.r%rrr2r3cr+r,r-r.r%rrr2r3cr+r4r-r.r%rrr2r3cr+rPr-r.r%rrr2r3r!r<)r r=r>figure add_subplotr@rArBrrrC set_zlabelrErDrFrGrHrIrJ)rfigrKrLrMrr%rr$sL     r$)rrrrrrrrrrrrrr)rr rr) __future__rcollections.abcrroptuna._experimentalr optuna.studyr optuna.trialr"optuna.visualization._pareto_frontrr 3optuna.visualization.matplotlib._matplotlib_importsr is_successfulr r r rrr#r$rrrrs.            I (