o iN@sdZddlZdddZdS)z A collection of basic statistical functions for Python. References ---------- .. [CRCProbStat2000] Zwillinger, D. and Kokoska, S. (2000). CRC Standard Probability and Statistics Tables and Formulae. Chapman & Hall: New York. 2000. NcCs|jdkrtjS|dur|}d}|j|}t||}||}||kr)tdt|||df|}tdg|j }t||||<tj |t ||dS)a=Return mean of array after trimming distribution from both tails. If `proportiontocut` = 0.1, slices off 'leftmost' and 'rightmost' 10% of scores. The input is sorted before slicing. Slices off less if proportion results in a non-integer slice index (i.e., conservatively slices off `proportiontocut` ). Parameters ---------- a : cupy.ndarray Input array. proportiontocut : float Fraction to cut off of both tails of the distribution. axis : int or None, optional Axis along which the trimmed means are computed. Default is 0. If None, compute over the whole array `a`. Returns ------- trim_mean : ndarray Mean of trimmed array. See Also -------- trimboth tmean : Compute the trimmed mean ignoring values outside given `limits`. Examples -------- >>> import cupy as cp >>> from cupyx.scipy import stats >>> x = cp.arange(20) >>> stats.trim_mean(x, 0.1) array(9.5) >>> x2 = x.reshape(5, 4) >>> x2 array([[ 0, 1, 2, 3], [ 4, 5, 6, 7], [ 8, 9, 10, 11], [12, 13, 14, 15], [16, 17, 18, 19]]) >>> stats.trim_mean(x2, 0.25) array([ 8., 9., 10., 11.]) >>> stats.trim_mean(x2, 0.25, axis=1) array([ 1.5, 5.5, 9.5, 13.5, 17.5]) rNzProportion too big.)axis) sizecpnanravelshapeint ValueError partitionslicendimmeantuple)aproportiontocutrnobslowercutuppercutatmpslrU/home/ubuntu/veenaModal/venv/lib/python3.10/site-packages/cupyx/scipy/stats/_stats.py trim_mean s /  r)r)__doc__cupyrrrrrrs