`iZddlZddlZddlZddlZddlmZd dddZd dZ d ddd ZdS) N)_coreTdtypec||tjdtt||||} t j|}n#t $r||z cYSwxYwt j|j}||dddfz}||dddfz}t j |jdd|jt j |r"t j |j dd|j |S)a:Returns the Pearson product-moment correlation coefficients of an array. Args: a (cupy.ndarray): Array to compute the Pearson product-moment correlation coefficients. y (cupy.ndarray): An additional set of variables and observations. rowvar (bool): If ``True``, then each row represents a variable, with observations in the columns. Otherwise, the relationship is transposed. bias (None): Has no effect, do not use. ddof (None): Has no effect, do not use. dtype: Data type specifier. By default, the return data-type will have at least `numpy.float64` precision. Returns: cupy.ndarray: The Pearson product-moment correlation coefficients of the input array. .. seealso:: :func:`numpy.corrcoef` Nz/bias and ddof have no effect and are deprecatedr)out) warningswarnDeprecationWarningcovcupydiag ValueErrorsqrtrealclip iscomplexobjimag) ayrowvarbiasddofrr dstddevs p/home/jaya/work/projects/VOICE-AGENT/VIET/agent-env/lib/python3.11/site-packages/cupy/_statistics/correlation.pycorrcoefr s, 4+ G( * * * aF% ( ( (C IcNN SyYqv  F6!!!T'?C6$'?CIchA38,,,, 1 #(Bsx0000 JsAAAvalidc$|jdks |jdkrtd|jdks |jdkrtdtjj|||}|dkrBtjj||ddd|}nW|dkrBtjj ||ddd|}ntd |S) adReturns the cross-correlation of two 1-dimensional sequences. Args: a (cupy.ndarray): first 1-dimensional input. v (cupy.ndarray): second 1-dimensional input. mode (str, optional): `valid`, `same`, `full` Returns: cupy.ndarray: Discrete cross-correlation of a and v. .. seealso:: :func:`numpy.correlate` rzArray arguments cannot be emptyrz!object too deep for desired arraydirectNrfftzUnsupported method) sizerndimr_mathmisc_choose_conv_method _dot_convolveconj _fft_convolve)rvmodemethodr s r correlater.5s v{{afkk:;;;v{{afkk<===Z_ 0 0At < = 0. However, the function will not error when fweights < 0 for performance reasons. aweights (cupy.ndarray): 1-D array of observation vector weights. These relative weights are typically large for observations considered "important" and smaller for observations considered less "important". If ``ddof=0`` the array of weights can be used to assign probabilities to observation vectors. It is required that aweights >= 0. However, the function will not error when aweights < 0 for performance reasons. dtype: Data type specifier. By default, the return data-type will have at least `numpy.float64` precision. Returns: cupy.ndarray: The covariance matrix of the input array. .. seealso:: :func:`numpy.cov` Nzddof must be integerzInput must be <= 2-dzy must be <= 2-d)ndminrrrF)copyr2r)axiszfweights must be a cupy.ndarray bBhHiIlLqQzfweights must be integerrz'cannot handle multidimensional fweightsz,incompatible numbers of samples and fweightszaweights must be a cupy.ndarrayz'cannot handle multidimensional aweightsz,incompatible numbers of samples and aweightsT)r4weightsreturnedz!Degrees of freedom <= 0 for slice) stacklevelg) intrr$numpy promote_typesrfloat64 functoolsreducerarrayshapeTreshaperconcatenate_method isinstancendarray TypeErrorcharastypefloat RuntimeErroraveragesumr r RuntimeWarningmeandotr)squeeze)rrrrrfweightsaweightsrXwavgw_sumfactX_Tr s rr r SsP DCII--/000vzz/000 } 9'??EEvzz !3444$#!'5=1E 1AU+++A agajAoo CwqzQz"~~%%a+++} JquAU ; ; ; !'!*//A  $aV! 4 4 4 |qqa A(DL11 3133 3 > l 2 2*,, ,???// =1  9;; ; >!  * *>@@ @ (DL11 3133 3???// =1  9;; ; >!  * *>@@ @ 9AA MAaaTBBBJC !HE ywqzD    t|tc!H*oo-55 qyy 9$ 4 4 4 4Q4  Ayc1ui %%  q4<#5#55 6C ;;==r/)NTNN)r)NTFNNN)r=r r:rrrr.r r/rrZs (D(((((V<26 $A/3AAAAAAAr/