L i TddlmZddlmZddlmZddlmZ d dede de defd Z y ) )Study)FloatDistribution) create_study) create_trial n_objectives directionvalue_for_first_trialreturnc t|g|z}|jt|g|zdddddtddtddtddtddd |jtdg|zddd tddtddd  |jtdg|zd dd ddtddtddtddtddd |S) aUReturn a dummy study object for tests. This function is added to reduce the code to set up dummy study object in each test case. However, you can only use this function for unit tests that are loosely coupled with the dummy study object. Unit tests that are tightly coupled with the study become difficult to read because of `Mystery Guest `__ and/or `Eager Test `__ anti-patterns. Args: n_objectives: Number of objective values. direction: Study's optimization direction. value_for_first_trial: Objective value in first trial. This value will be broadcasted to all objectives in multi-objective optimization. Returns: :class:`~optuna.study.Study` ) directionsg?g@g@g@)param_aparam_bparam_cparam_dg@)valuesparams distributions)rrg@g@)r add_trialrr)rrr studys b/mnt/ssd/data/python-lab/Trading/venv/lib/python3.12/site-packages/optuna/testing/visualization.pyprepare_study_with_trialsrs2 YK,$> ?E OO)*\9"sssS,S#6,S#6,S#6,S#6    OO5<'"s3,S#6,S#6   OO5<'"sssS,S#6,S#6,S#6,S#6    LN)minimizer) optunaroptuna.distributionsr optuna.studyr optuna.trialrintstrfloatrrrr$sE2%%#&<<<!< <r