o ְi@s^ddlZddlZddlZddlZddlmZd ddddZddd Z  dddd d ZdS)N)_coreTdtypec Cs|dus|durtdtt||||d}zt|}Wn ty*||YSwt|j}||dddf}||dddf}tj |jdd|jdt |r`tj |j dd|j d|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) ayrowvarbiasddofrrdstddevrP/home/ubuntu/.local/lib/python3.10/site-packages/cupy/_statistics/correlation.pycorrcoef s"    rvalidcCs|jdks |jdkrtd|jdks|jdkrtdtjj|||}|dkr;tjj||ddd|}|S|dkrQtjj ||ddd|}|Std ) 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)rvmodemethodrrrr correlate5s  r,FcCs|dur|t|krtd|jdkrtd|dur>|dur(t|jtj}n|jdkr1tdttj|j|jtjf}t j |d|d}|sR|j ddkrR|j }|j ddkrbt g ddS|durt j |d d|d }|s{|j ddkr{|j }tj||fdd }|dur|rdnd}d} |durt|t jstd |jjd vrtd|jtd}|jdkrtd|j d|j dkrtd|} |durt|t jstd|jtd}|jdkrtd|j d|j dkrtd| dur|} n| |9} t j|d| dd\} } | d} | dur|j d|} n|dkr!| } n|dur+| |} n | |t| || } | dkrFtjdtddd} ||jdd dddf8}| dur]|j } n|| j } || dt | }|S)apReturns the covariance matrix of an array. This function currently does not support ``fweights`` and ``aweights`` options. Args: a (cupy.ndarray): Array to compute covariance matrix. 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 (bool): If ``False``, normalization is by ``(N - 1)``, where N is the number of observations given (unbiased estimate). If ``True``, then normalization is by ``N``. ddof (int): If not ``None`` the default value implied by bias is overridden. Note that ``ddof=1`` will return the unbiased estimate and ``ddof=0`` will return the simple average. fweights (cupy.ndarray, int): 1-D array of integer frequency weights. the number of times each observation vector should be repeated. It is required that fweights >= 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)copyr.r)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)r0weightsreturnedz!Degrees of freedom <= 0 for slice) stacklevelg) intrr"numpy promote_typesrfloat64 functoolsreducer arrayshapeTreshaperconcatenate_method isinstancendarray TypeErrorcharastypefloat RuntimeErroraveragesumrr RuntimeWarningmeandotr'squeeze)rrrrrfweightsaweightsrXwavgw_sumfactX_Trrrrr Ss(                 r )NTNN)r)NTFNNN)r9rr6r rrr,r rrrrs  +