o 5cn@spddlmZddlZddlmZmZmZddlm Z ddl m Z m Z dd dZ dddZdddZdddZdS)) annotationsN) ArrayLikeScalarnpt)np_percentile_argname)isnana_value_for_dtypevaluesrqsnpt.NDArray[np.float64] interpolationstrreturncCs>t|tjrt|jdd}t|}t|||||S|||S)a Compute the quantiles of the given values for each quantile in `qs`. Parameters ---------- values : np.ndarray or ExtensionArray qs : np.ndarray[float64] interpolation : str Returns ------- np.ndarray or ExtensionArray F)compat) isinstancenpndarrayrdtyperquantile_with_mask _quantile)r r r fill_valuemaskrV/var/www/html/gps/gps/lib/python3.10/site-packages/pandas/core/array_algos/quantile.pyquantile_compats  r np.ndarrayrnpt.NDArray[np.bool_]c Cs|j|jksJ|jdkr#t|}t|}t|||||}|dS|jdks*J|jddk}|rOt|gt|}t|t|t|t|}|St ||d|||d}tj|dd}|j }|S)a Compute the quantiles of the given values for each quantile in `qs`. Parameters ---------- values : np.ndarray For ExtensionArray, this is _values_for_factorize()[0] mask : np.ndarray[bool] mask = isna(values) For ExtensionArray, this is computed before calling _value_for_factorize fill_value : Scalar The value to interpret fill NA entries with For ExtensionArray, this is _values_for_factorize()[1] qs : np.ndarray[float64] interpolation : str Type of interpolation Returns ------- np.ndarray Notes ----- Assumes values is already 2D. For ExtensionArray this means np.atleast_2d has been called on _values_for_factorize()[0] Quantile is computed along axis=1. rgY@)na_valuerr Fcopy) shapendimr atleast_2drarraylenrepeatreshape_nanpercentileT) r rrr r res_valuesis_emptyflatresultrrrr*s,#     rrrScalar | np.ndarraycCs>||}t|dkrtt||Stj||fit|iS)a Wrapper for np.percentile that skips missing values, specialized to 1-dimensional case. Parameters ---------- values : array over which to find quantiles mask : ndarray[bool] locations in values that should be considered missing qs : np.ndarray[float64] of quantile indices to find na_value : scalar value to return for empty or all-null values interpolation : str Returns ------- quantiles : scalar or array r)r&rfull percentiler)r rr rr rrr_nanpercentile_1dms  r2cs|jjdvrt|dd|d}||jS|ro|j|jks'Jfddtt|t|D}|jjdkrKt j ||jddj }|St j |dd j }|j|jkrm||j|jdd k rm|j|jdd }|St j |fd d itiS) a Wrapper for np.percentile that skips missing values. Parameters ---------- values : np.ndarray[ndim=2] over which to find quantiles qs : np.ndarray[float64] of quantile indices to find na_value : scalar value to return for empty or all-null values mask : np.ndarray[bool] locations in values that should be considered missing interpolation : str Returns ------- quantiles : scalar or array )mMi8)r rrr c s"g|] \}}t||dqS))r )r2).0valr3r rr rr sz"_nanpercentile..fF)rr!r axisr)rkindr)viewastypeanyr"ziplistrr%r*allr1r)r r rrr r.rr8rr)s@     r))r rr r r r rr) r rrrr r r r rr) r rrrr r rrr r rr/)r rr r rrr r ) __future__rnumpyrpandas._typingrrrpandas.compat.numpyrpandas.core.dtypes.missingrrrrr2r)rrrrs     C,