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Aluode/PerceptionLabPortable

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a3Compute the weighted percentile with method 'inverted_cdf'.8 9    When the percentile lies between two data points of `array`, the function returns10    the lower value.11 12    If `array` is a 2D array, the `values` are selected along axis 0.13 14    `NaN` values are ignored by setting their weights to 0. If `array` is 2D, this15    is done in a column-isolated manner: a `NaN` in the second column, does not impact16    the percentile computed for the first column even if `sample_weight` is 1D.17 18        .. versionchanged:: 0.2419            Accepts 2D `array`.20 21        .. versionchanged:: 1.722            Supports handling of `NaN` values.23 24    Parameters25    ----------26    array : 1D or 2D array27        Values to take the weighted percentile of.28 29    sample_weight: 1D or 2D array30        Weights for each value in `array`. Must be same shape as `array` or of shape31        `(array.shape[0],)`.32 33    percentile_rank: int or float, default=5034        The probability level of the percentile to compute, in percent. Must be between35        0 and 100.36 37    xp : array_namespace, default=None38        The standard-compatible namespace for `array`. Default: infer.39 40    Returns41    -------42    percentile : scalar or 0D array if `array` 1D (or 0D), array if `array` 2D43        Weighted percentile at the requested probability level.44    ��xp)Zdtype�device��)�����r	)Zaxis)r45.)r�d).r46cs$g|]}���|df�|��qS).)Zsearchsorted)�.0Zfeature_idx�Zadjusted_percentile_rankZ47weight_cdfr��}E:\DocsHouse\542 percep lab latest\PerceptionLab\PerceptionLab_Portable\python_embed\Lib\site-packages\sklearn/utils/stats.py�48<listcomp>as���z(_weighted_percentile.<locals>.<listcomp>)rrZasarray�ndimZreshape�shapeZtile�TZargsortZtake_along_axisZarange�any�isnanZcumulative_sum�	nextafter�stack�rangeZclip)�array�
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