0Ph|ddlZddlmZddlmZddlmZddlm Z ddl m Z Gdd Z d Z d Zd Zd ZdS)N)check_consistent_length)check_matplotlib_support)_get_response_values_binary)type_of_target)_check_pos_label_consistencyc`eZdZdZddddZedddddZeddddd ZdS) "_BinaryClassifierCurveDisplayMixinzMixin class to be used in Displays requiring a binary classifier. The aim of this class is to centralize some validations regarding the estimator and the target and gather the response of the estimator. N)axnamect|jjdddlm}||\}}||jn|}||j|fS)Nz.plotr)r __class____name__matplotlib.pyplotpyplotsubplotsestimator_namefigure)selfr r plt_s W/var/www/html/test/jupyter/venv/lib/python3.11/site-packages/sklearn/utils/_plotting.py_validate_plot_paramsz8_BinaryClassifierCurveDisplayMixin._validate_plot_paramssf DN$;!B!B!BCCC'''''' :LLNNEAr&*lt""29d""auto)response_method pos_labelr ct|jd| |jjn|}t||||\}}|||fS)Nz.from_estimator)rr)rrrr)cls estimatorXyrrr y_preds r!_validate_and_get_response_valueszD_BinaryClassifierCurveDisplayMixin._validate_and_get_response_valuesse !CL!A!A!ABBB/3|y"++7  +     y$&&r) sample_weightrr ct|jdt|dkr tdt|dt |||t ||}||nd}||fS)Nz.from_predictionsbinaryz The target y is not binary. Got z type of target. Classifier)rrr ValueErrorrr)ry_truer#r%rr s r!_validate_from_predictions_paramszD_BinaryClassifierCurveDisplayMixin._validate_from_predictions_params/s !CL!C!C!CDDD & ! !X - ->&3I3I   >>>0FCC 'tt\$r)r __module__ __qualname____doc__r classmethodr$r+rrr r s +/T#####174d''''[' .2d[rr c2||S||rdndSt|r|jn|}|r&|dr |dd}n(d|}n"|dr d|dd}|dd}|S) aValidate the `score_name` parameter. If `score_name` is provided, we just return it as-is. If `score_name` is `None`, we use `Score` if `negate_score` is `False` and `Negative score` otherwise. If `score_name` is a string or a callable, we infer the name. We replace `_` by spaces and capitalize the first letter. We remove `neg_` and replace it by `"Negative"` if `negate_score` is `False` or just remove it otherwise. NzNegative scoreScoreneg_z Negative r )callabler startswithreplace capitalize) score_namescoring negate_scores r_validate_score_namer=Cs #/<W<)1'):):GW%%  6$$V,, 6'^ 555  " "6 * * 65Z^55J''S11 $$&&&rctjtj|}||z S)aCompute the ratio between the largest and smallest inter-point distances. A value larger than 5 typically indicates that the parameter range would better be displayed with a log scale while a linear scale would be more suitable otherwise. )npdiffsortmaxmin)datar@s r_interval_max_min_ratiorE^s6 7274== ! !D 88:: ""rciddddddddd d d d d ddddddddddddddddddd d!d"d#d$d%d&d'd(d)}|D]#\}}||vr||vrtd*|d+|d,$|}|D]#}||vr|||||<||||<$|S)-aCreate valid style kwargs by avoiding Matplotlib alias errors. Matplotlib raises an error when, for example, 'color' and 'c', or 'linestyle' and 'ls', are specified together. To avoid this, we automatically keep only the one specified by the user and raise an error if the user specifies both. Parameters ---------- default_style_kwargs : dict The Matplotlib style kwargs used by default in the scikit-learn display. user_style_kwargs : dict The user-defined Matplotlib style kwargs. Returns ------- valid_style_kwargs : dict The validated style kwargs taking into account both default and user-defined Matplotlib style kwargs. ls linestyleccolorec edgecolorfc facecolorlw linewidthmecmarkeredgecolormfcaltmarkerfacecoloraltms markersizemewmarkeredgewidthmfcmarkerfacecoloraa antialiasedds drawstylefontfontpropertiesfamily fontfamilyr fontnamesizefontsizestretch fontstretch fontstyle fontvariant fontweighthorizontalalignmentverticalalignmentmultialignment)stylevariantweighthavamaz Got both z and z", which are aliases of one another)items TypeErrorcopykeys)default_style_kwargsuser_style_kwargsinvalid_to_valid_kw invalid_key valid_keyvalid_style_kwargskeys r_validate_style_kwargsris* k W k k  k    & l     m k   ,    !" =#$ #!/2#6";";"="= Y + + + =N0N0NKi .2244 %%''== % % %;LS;Q 237 8 8&7&< s # # rcdD]"}|j|d#dD]#}|j|dd$dS)zRemove the top and right spines of the plot. Parameters ---------- ax : matplotlib.axes.Axes The axes of the plot to despine. )toprightF)bottomleftrrN)spines set_visible set_bounds)r ss r_despinersh(( !   '''' && ! 1%%%%&&r)numpyr?r_optional_dependenciesr _responser multiclassr validationrr r=rErrr0rrrs%%%%%%<<<<<<222222&&&&&&44444433333333l'''6###<<<~ & & & & &r