bencher.results.optimize_result
===============================

.. py:module:: bencher.results.optimize_result

.. autoapi-nested-parse::

   OptimizeResult — first-class container for optimization results.



Classes
-------

.. autoapisummary::

   bencher.results.optimize_result.OptimizeResult


Module Contents
---------------

.. py:class:: OptimizeResult

   Wraps an ``optuna.Study`` with bencher-friendly accessors.

   .. attribute:: study

      The underlying optuna study.

   .. attribute:: n_warm_start_trials

      Number of trials seeded from cache / prior results.

   .. attribute:: n_new_trials

      Number of new trials evaluated during optimization.

   .. attribute:: target_names

      Names of the optimization target variables.

   .. attribute:: bench_cfg

      Optional BenchCfg for rich report generation.


   .. py:attribute:: study
      :type:  optuna.Study


   .. py:attribute:: n_warm_start_trials
      :type:  int
      :value: 0



   .. py:attribute:: n_new_trials
      :type:  int
      :value: 0



   .. py:attribute:: target_names
      :type:  list[str]
      :value: []



   .. py:attribute:: bench_cfg
      :type:  bencher.bench_cfg.BenchCfg | None
      :value: None



   .. py:method:: _ensure_single_objective() -> None

      Raise if study is multi-objective.



   .. py:property:: best_params
      :type: dict[str, Any]


      Best parameters found (single-objective only).


   .. py:property:: best_value
      :type: float


      Best objective value (single-objective only).


   .. py:property:: best_trials
      :type: list[optuna.trial.FrozenTrial]


      Pareto-optimal trials (multi-objective).


   .. py:method:: summary() -> str

      Return a human-readable summary of the optimization.