9jnSSKJr SSKrSSKrSSKrSSKrSSKJr SSS.SjjrS SjrS SS.Sjjr g) ) annotationsN)_coredtypecUcUb"S[5 [XX%S9n[R "U5n[R"UR5nXhSS2S4-nXhSSS24-n[R"URSSURS9 [R"U5(a+[R"URSSURS9 U$![ a Xf- s$f=f)aReturns 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 V/home/wildlama/miniconda3/lib/python3.13/site-packages/cupy/_statistics/correlation.pycorrcoefr s, 4+ G( * aF (C IIcNYYqvv F!T'?C$'?CIIchhA388,  #((Bsxx0 J ysC,,C=<C=c0URS:XdURS:Xa [S5eURS:wdURS:wa [S5e[RR R XU5nUS:Xa@[RR RXR5SSS2U5nU$US:Xa@[RR RXR5SSS2U5nU$[S 5e) aDReturns the cross-correlation of two 1-dimensional sequences. Args: a (cupy.ndarray): first 1-dimensional input. v (cupy.ndarray): second 1-dimensional input. mode (str, optional): `valid`, `same`, `full` Returns: cupy.ndarray: Discrete cross-correlation of a and v. .. seealso:: :func:`numpy.correlate` rzArray arguments cannot be emptyr z!object too deep for desired arraydirectNrfftzUnsupported method) sizerndimr_mathmisc_choose_conv_method _dot_convolveconj _fft_convolve)rvmodemethodr s r correlater.7s vv{affk:;;vv{affk<==ZZ__ 0 0t = 0. However, the function will not error when fweights < 0 for performance reasons. aweights (cupy.ndarray): 1-D array of observation vector weights. These relative weights are typically large for observations considered "important" and smaller for observations considered less "important". If ``ddof=0`` the array of weights can be used to assign probabilities to observation vectors. It is required that aweights >= 0. However, the function will not error when aweights < 0 for performance reasons. dtype: Data type specifier. By default, the return data-type will have at least `numpy.float64` precision. Returns: cupy.ndarray: The covariance matrix of the input array. .. seealso:: :func:`numpy.cov` Nzddof must be integerzInput must be <= 2-dzy must be <= 2-d)ndminrr r)copyr2r)axiszfweights must be a cupy.ndarray bBhHiIlLqQzfweights must be integerrz'cannot handle multidimensional fweightsz,incompatible numbers of samples and fweightszaweights must be a cupy.ndarrayz'cannot handle multidimensional aweightsz,incompatible numbers of samples and aweightsT)r4weightsreturnedz!Degrees of freedom <= 0 for slice) stacklevelg) intrr$numpy promote_typesrfloat64 functoolsreducerarrayTshapereshaperconcatenate_method isinstancendarray TypeErrorcharastypefloat RuntimeErroraveragesumr r RuntimeWarningmeandotr)squeeze)rrrrrfweightsaweightsrXwavgw_sumfactX_Tr s rrrUsgP DCI-/00vvz/00 } 9''?Evvz !344$$##!''5==1E 1AU+A affk CCwwqzQzz"~%%a++} JJqt1E :!''!*/A  $ $aV! 4 |qa A(DLL1113 3 >>  l 2*, ,???/ ==1 9; ; >>!  *>@ @ (DLL1113 3???/ ==1 9; ; >>!  *>@ @ 9A MAaaTBJC !HE ywwqzD    |c!*o-55 qy 9$ 4Q4  Ayccuii %% d "C ;;=r/)NTNN)valid)NTFNNN) __future__rr=r r:rrrr.rr/rr\s@" (D(V<26 $A/3Ar/