a CCCfM@sdZddlmZddlZddlmZddlmZm Z m Z m Z m Z m Z mZmZddlmZgdZGd d d eZGd d d eZGd ddeZddgddgddgddgddgddgddgddgddgdd gd!d"gd#d$gd%d&gd'd(gd)d*gd+d,gd-d.gd/d0gd1d2gd3d4gd5Zeejejejejejejejej ej!ej"ej#ej$ej%ej&ej'ej(ej)ej*gZ+d6Z,Gd7d8d8Z-Gd9d:d:Z.e-je._d;d<Z/d=d>Z0dS)?zBase class for sparse matrices)warnN)VisibleDeprecationWarning)asmatrixcheck_reshape_kwargs check_shape get_sum_dtypeisdense isscalarlikematrix validateaxis)spmatrix) isspmatrixissparsesparray SparseWarningSparseEfficiencyWarningc@s eZdZdS)rN__name__ __module__ __qualname__rrN/var/www/html/django/DPS/env/lib/python3.9/site-packages/scipy/sparse/_base.pyrsrc@s eZdZdS)SparseFormatWarningNrrrrrrsrc@s eZdZdS)rNrrrrrrsrzCompressed Sparse ColumnzCompressed Sparse RowzDictionary Of Keysz List of ListszDictionary of DictionarieszSymmetric Sparse SkylineZ COOrdinatezLinpack BAndedz#Ellpack-itpack Generalized Diagonal ZDIAgonal zBlock Sparse Row zModified compressed Sparse Row zBlock Sparse Column z!Modified compressed Sparse ColumnzSymmetric SKylinezNonsymmetric SKylinezJAgged DiagonalzUnsymmetric Sparse SkylinezVariable Block Row Undefined)ZcscZcsrZdokZlilZdodZsssZcooZlbaZegdZdiaZbsrZmsrZbscmscZsskZnskZjadZussZvbrund2c@sheZdZdZdZdZeedddZeddZ ed d Z ed d Z ed dZ eddZ eddZeddZeddZefddZddZddZddd Zed!d"Zed#d$Zd%d&Zd'd(Zd)d*Zd+d,Zdd.d/Zeedd0d1Zeedd2d3Zee dd4d5Z!ee"j#dd6d7Z$ed8d9Z%ed:d;Z&edd?Z(d@dAZ)dBdCZ*dDdEZ+e+Z,dFdGZ-ddIdJZ.dKdLZ/dMdNZ0dOdPZ1dQdRZ2ddSdTZ3dUdVZ4dWdXZ5dYdZZ6d[d\Z7d]d^Z8d_d`Z9dadbZ:ddddeZ;dfdgZdldmZ?dndoZ@dpdqZAdrdsZBdtduZCdvdwZDdxdyZEdzd{ZFd|d}ZGd~dZHddZIddZJddZKddZLddZMddZNdddZOddZPddZQddZRddZSddZTddZUddZVddZWddZXddZYddZZdddZ[dddZ\dddZ]e\je]_ddZ^ddZ_ddZ`ddZaddZbdddZcdddZddddZedddZfdddZgdddZhdddZidddÄZjdddńZkddDŽZldddɄZmddd˄Znddd̈́ZodddτZpdddфZqddӄZrddՄZsddd؄ZtddڄZudd܄ZveddބevddZwddZxddZyddZzdddZ{ddZ|ddZ}ddZ~d-S(_spbasez This class provides a base class for all sparse arrays. 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Most of the work is provided by subclasses. g333333$@r.)returncCs t|jSN)len_shapeselfrrrndimGsz _spbase.ndimcCs"|j}t|dkrd|dfS|S)Nr)r4r3)r6srrr _shape_as_2dKsz_spbase._shape_as_2dcCsddlm}|S)Nr) bsr_array)Z_bsrr;)r6r;rrr_bsr_containerPs z_spbase._bsr_containercCsddlm}|S)Nr) coo_array)Z_coor=)r6r=rrr_coo_containerUs z_spbase._coo_containercCsddlm}|S)Nr) csc_array)Z_cscr?)r6r?rrr_csc_containerZs z_spbase._csc_containercCsddlm}|S)Nr) csr_array)Z_csrrA)r6rArrr_csr_container_s z_spbase._csr_containercCsddlm}|S)Nr) dia_array)Z_diarC)r6rCrrr_dia_containerds z_spbase._dia_containercCsddlm}|S)Nr) dok_array)Z_dokrE)r6rErrr_dok_containeris z_spbase._dok_containercCsddlm}|S)Nr) lil_array)Z_lilrG)r6rGrrr_lil_containerns z_spbase._lil_containercCs$d|_|jjdkrtd||_dS)Nr0z7This class is not intended to be instantiated directly.)r4 __class__r ValueErrormaxprint)r6rKrrr__init__ss z_spbase.__init__cOsXt|t}t||j|d}t|\}}||jkr@|r<|S|S|j|dj||ddS)areshape(self, shape, order='C', copy=False) Gives a new shape to a sparse array/matrix without changing its data. Parameters ---------- shape : length-2 tuple of ints The new shape should be compatible with the original shape. order : {'C', 'F'}, optional Read the elements using this index order. 'C' means to read and write the elements using C-like index order; e.g., read entire first row, then second row, etc. 'F' means to read and write the elements using Fortran-like index order; e.g., read entire first column, then second column, etc. copy : bool, optional Indicates whether or not attributes of self should be copied whenever possible. The degree to which attributes are copied varies depending on the type of sparse array being used. Returns ------- reshaped : sparse array/matrix A sparse array/matrix with the given `shape`, not necessarily of the same format as the current object. See Also -------- numpy.reshape : NumPy's implementation of 'reshape' for ndarrays )Zallow_1dcopyF)orderrN) isinstancerrshaperrNtocooreshape)r6argskwargsZis_arrayrQrOrNrrrrSs   z_spbase.reshapecCstt|jddS)aResize the array/matrix in-place to dimensions given by ``shape`` Any elements that lie within the new shape will remain at the same indices, while non-zero elements lying outside the new shape are removed. Parameters ---------- shape : (int, int) number of rows and columns in the new array/matrix Notes ----- The semantics are not identical to `numpy.ndarray.resize` or `numpy.resize`. Here, the same data will be maintained at each index before and after reshape, if that index is within the new bounds. In numpy, resizing maintains contiguity of the array, moving elements around in the logical array but not within a flattened representation. We give no guarantees about whether the underlying data attributes (arrays, etc.) will be modified in place or replaced with new objects. z.resize is not implementedN)NotImplementedErrortyper)r6rQrrrresizesz_spbase.resizeunsafeTcCsDt|}|j|kr0|j|||d|jS|r<|S|SdS)aCast the array/matrix elements to a specified type. Parameters ---------- dtype : string or numpy dtype Typecode or data-type to which to cast the data. casting : {'no', 'equiv', 'safe', 'same_kind', 'unsafe'}, optional Controls what kind of data casting may occur. Defaults to 'unsafe' for backwards compatibility. 'no' means the data types should not be cast at all. 'equiv' means only byte-order changes are allowed. 'safe' means only casts which can preserve values are allowed. 'same_kind' means only safe casts or casts within a kind, like float64 to float32, are allowed. 'unsafe' means any data conversions may be done. copy : bool, optional If `copy` is `False`, the result might share some memory with this array/matrix. If `copy` is `True`, it is guaranteed that the result and this array/matrix do not share any memory. )castingrNN)npdtypetocsrastypeasformatformatrN)r6r\rZrNrrrr^s  z_spbase.astypecKs0t|trtj|fi|St|fi|SdSr2) issubclassrr[asarrayrclsXrUrrr _ascontainers z_spbase._ascontainercKs0t|trtj|fi|St|fi|SdSr2)rarr[arrayr rcrrr _containers z_spbase._containercCsTgd}|jj|vr|S|D]"}|jt|kr||Sqtd|jjdS)z6Upcast array to a floating point format (if necessary))fdFDz-cannot upcast [%s] to a floating point formatN)r\charr[r^ TypeErrorname)r6Zfp_typesZfp_typerrr _asfptypes z_spbase._asfptypeccs"t|jdD]}||VqdS)Nr)rangerQ)r6rrrr__iter__sz_spbase.__iter__cCs|jS)z3Maximum number of elements to display when printed.)rKr5rrr _getmaxprintsz_spbase._getmaxprintcCstd|jjdS)aNumber of non-zero entries, equivalent to np.count_nonzero(a.toarray()) Unlike the nnz property, which return the number of stored entries (the length of the data attribute), this method counts the actual number of non-zero entries in data. z%count_nonzero not implemented for %s.NrVrIrr5rrr count_nonzero s z_spbase.count_nonzeroNcCstd|jjdS)aINumber of stored values, including explicit zeros. Parameters ---------- axis : None, 0, or 1 Select between the number of values across the whole array, in each column, or in each row. See also -------- count_nonzero : Number of non-zero entries zgetnnz not implemented for %s.Nrur6axisrrr_getnnzs z_spbase._getnnzcCs|S)zNumber of stored values, including explicit zeros. See also -------- count_nonzero : Number of non-zero entries ryr5rrrnnz&sz _spbase.nnzcCs|S)zwNumber of stored values. See also -------- count_nonzero : Number of non-zero values. rzr5rrrsize0sz _spbase.sizecCs|jS)zFormat string for matrix.)_formatr5rrrr`:sz_spbase.formatcCs&t|trd}tt|dd|S)zDEPRECATED: Return a dense array. .. deprecated:: 1.11.0 `.A` is deprecated and will be removed in v1.14.0. Use `.toarray()` instead. zL`.A` is deprecated and will be removed in v1.14.0. Use `.toarray()` instead.r stacklevel)rPrrrtoarrayr6messagerrrA?s z _spbase.AcCs|S)z Transpose.) transposer5rrrTNsz _spbase.TcCs(t|trd}tt|dd|jS)zDEPRECATED: Returns the (complex) conjugate transpose. .. deprecated:: 1.11.0 `.H` is deprecated and will be removed in v1.14.0. Please use `.T.conjugate()` instead. zW`.H` is deprecated and will be removed in v1.14.0. Please use `.T.conjugate()` instead.rr~)rPrrrr conjugaterrrrHSs z _spbase.HcCs|Sr2)_realr5rrrrealbsz _spbase.realcCs|Sr2)_imagr5rrrimagfsz _spbase.imagc Cs`t|j\}}t|trdnd}ddd|jD}d|d|d|jjd |jd |d S) Nrgr xcss|]}t|VqdSr2)str).0rrrr mz#_spbase.__repr__..) _formatsr`rPrjoinrQr\rWr{)r6_ format_nameZ sparse_clsZ shape_strrrr__repr__jsz_spbase.__repr__cCs|}|}dd}|j|kr|d}||jd||jd||jd|}|d7}||d}|||j| d|j| d|j| d7}n||j|j|j}|S)NcSs(ttt|||}ddd|DS)N cSsg|]}dj|qS)z {} {})r`)rtrrr {rz2_spbase.__str__..tostr..)ziplistr)rowcoldataZtriplesrrrtostrysz_spbase.__str__..tostrrz : : )rtrRr{rrr)r6rKrrZhalfoutrrr__str__ss * 6z_spbase.__str__cCs |jdkr|jdkStddS)N)rrrz\The truth value of an array with more than one element is ambiguous. Use a.any() or a.all().)rQr{rJr5rrr__bool__s  z_spbase.__bool__cCs tddS)Nz:sparse array length is ambiguous; use getnnz() or shape[0])rnr5rrr__len__sz_spbase.__len__Fc Cs|dus||jkr$|r|S|Snpzt|d|}Wn6tyl}ztd|d|WYd}~n d}~00z ||dWSty|YS0dS)aReturn this array/matrix in the passed format. Parameters ---------- format : {str, None} The desired sparse format ("csr", "csc", "lil", "dok", "array", ...) or None for no conversion. copy : bool, optional If True, the result is guaranteed to not share data with self. Returns ------- A : This array/matrix in the passed format. NtozFormat z is unknown.rM)r`rNgetattrAttributeErrorrJrn)r6r`rNZconvert_methoderrrr_s(  z_spbase.asformatcCs||S)z2Point-wise multiplication by another array/matrix.)r]multiplyr6otherrrrrsz_spbase.multiplycCs||S)z;Element-wise maximum between this and another array/matrix.)r]maximumrrrrrsz_spbase.maximumcCs||S)z;Element-wise minimum between this and another array/matrix.)r]minimumrrrrrsz_spbase.minimumcCst|r||S||SdS)a/Ordinary dot product Examples -------- >>> import numpy as np >>> from scipy.sparse import csr_array >>> A = csr_array([[1, 2, 0], [0, 0, 3], [4, 0, 5]]) >>> v = np.array([1, 0, -1]) >>> A.dot(v) array([ 1, -3, -1], dtype=int64) N)r[Zisscalarrrrrdots z _spbase.dotcCs|j||dS)zElement-wise power.r\)r]power)r6nr\rrrrsz _spbase.powercCs||Sr2)r]__eq__rrrrrsz_spbase.__eq__cCs||Sr2)r]__ne__rrrrrsz_spbase.__ne__cCs||Sr2)r]__lt__rrrrrsz_spbase.__lt__cCs||Sr2)r]__gt__rrrrrsz_spbase.__gt__cCs||Sr2)r]__le__rrrrrsz_spbase.__le__cCs||Sr2)r]__ge__rrrrrsz_spbase.__ge__cCs t|Sr2)absr]r5rrr__abs__sz_spbase.__abs__rcCst||dS)N)ndigits)roundr])r6rrrr __round__sz_spbase.__round__cCs||Sr2)r] _add_sparserrrrrsz_spbase._add_sparsecCs||Sr2)rR _add_denserrrrrsz_spbase._add_densecCs||Sr2)r] _sub_sparserrrrrsz_spbase._sub_sparsecCs ||Sr2todenserrrr _sub_densesz_spbase._sub_densecCs ||Sr2rrrrr _rsub_densesz_spbase._rsub_densecCspt|r"|dkr|StdnJt|rH|j|jkr>td||St|rht ||j}| |St SdS)Nrz:adding a nonzero scalar to a sparse array is not supportedinconsistent shapes) r rNrVrrQrJrr r[ broadcast_torNotImplementedrrrr__add__s    z_spbase.__add__cCs ||Sr2)rrrrr__radd__sz_spbase.__radd__cCspt|r"|dkr|StdnJt|rH|j|jkr>td||St|rht ||j}| |St SdS)NrzAsubtracting a nonzero scalar from a sparse array is not supportedr) r rNrVrrQrJrr r[rrrrrrr__sub__s    z_spbase.__sub__cCsLt|r$|dkr| Stdn$t|rDt||j}||StSdS)NrzAsubtracting a sparse array from a nonzero scalar is not supported) r rNrVr r[rrQrrrrrr__rsub__,s   z_spbase.__rsub__cCs|j\}}|jtjur|j|fkr,||S|j|dfkrb||}|jdkrV|S||dS|jdkr|jd|kr| |St |r| |St |r|jd|jdkrt d|jdkrt d||St|}|jdkr|jtjkrtSz |jWnty|}Yn0|jdksF|jdkr|jddkr|j|fkrl|j|dfkrlt d|t|}t|tjr||}|jdkr|jddkr|dd}|S|jdkr|jd|krt d| t|}t|tjr ||}|St ddS) anp.array-like matmul & `np.matrix`-like mul, i.e. `dot` or `NotImplemented` interpret other and call one of the following self._mul_scalar() self._matmul_vector() self._matmul_multivector() self._matmul_sparse() rrrr8zdimension mismatchz%Cannot yet multiply a 1d sparse arrayzcould not interpret dimensionsN)r:rIr[ndarrayrQ_matmul_vectorZravelr7rS_matmul_multivectorr _mul_scalarrrJ_matmul_sparseZ asanyarrayr\Zobject_rrrPr rfrb)r6rMNresultZother_arrr_matmul_dispatch8sV             (    z_spbase._matmul_dispatchcOs|j|i|Sr2rr6rTrUrrr__mul__sz_spbase.__mul__cOs|j|i|Sr2rrrrr__rmul__sz_spbase.__rmul__cCs||Sr2)r]rrrrrrsz_spbase._mul_scalarcCs||Sr2)r]rrrrrrsz_spbase._matmul_vectorcCs||Sr2)r]rrrrrrsz_spbase._matmul_multivectorcCs||Sr2)r]rrrrrrsz_spbase._matmul_sparsecCsft|r||Sz |}Wn ty>t|}Yn0||}|turZtS|SdSr2)r rrrr[rbrr)r6rtrretrrr_rmatmul_dispatchs   z_spbase._rmatmul_dispatchcCst|rtd||SNz0Scalar operands are not allowed, use '*' instead)r rJrrrrr __matmul__sz_spbase.__matmul__cCst|rtd||Sr)r rJrrrrr __rmatmul__sz_spbase.__rmatmul__cCsft|r|r0|r t||St||S|rZt|jtjrZ|tj d|S| d|}t |j}t |jtj rt |tj r||jS|Snt |r|s|rtd|}n td|}||S|rt||St||Snbt|r^|r |j||ddS|}|rRt|jtjrR|tj|S||SntSdS)N?F)rdivide)r r[ true_dividerdivideZcan_castr\float64r^rrb issubdtypeintegerr rr_divider]Z_divide_sparser)r6rrrrrZ scalar_dtypeZrecipZself_csrrrrrs>        z_spbase._dividecCs|j|ddSNT)rrrrrr __truediv__sz_spbase.__truediv__cCs|j|ddSrrrrrr__div__sz_spbase.__div__cCstSr2rrrrr __rtruediv__sz_spbase.__rtruediv__cCstSr2rrrrr__rdiv__sz_spbase.__rdiv__cCs | Sr2)r]r5rrr__neg__sz_spbase.__neg__cCstSr2rrrrr__iadd__sz_spbase.__iadd__cCstSr2rrrrr__isub__sz_spbase.__isub__cCstSr2rrrrr__imul__sz_spbase.__imul__cCs ||Sr2) __itruediv__rrrr__idiv__ sz_spbase.__idiv__cCstSr2rrrrrr sz_spbase.__itruediv__cOs|j|i|Sr2)rrrrr__pow__sz_spbase.__pow__cCs|j|dj|ddS)a Reverses the dimensions of the sparse array/matrix. Parameters ---------- axes : None, optional This argument is in the signature *solely* for NumPy compatibility reasons. Do not pass in anything except for the default value. copy : bool, optional Indicates whether or not attributes of `self` should be copied whenever possible. The degree to which attributes are copied varies depending on the type of sparse array/matrix being used. Returns ------- p : `self` with the dimensions reversed. Notes ----- If `self` is a `csr_array` or a `csc_array`, then this will return a `csc_array` or a `csr_array`, respectively. See Also -------- numpy.transpose : NumPy's implementation of 'transpose' for ndarrays rMF)axesrN)r]r)r6rrNrrrrsz_spbase.transposecCs8t|jtjr$|j|djddS|r0|S|SdS)aElement-wise complex conjugation. If the array/matrix is of non-complex data type and `copy` is False, this method does nothing and the data is not copied. Parameters ---------- copy : bool, optional If True, the result is guaranteed to not share data with self. Returns ------- A : The element-wise complex conjugate. rMFN)r[rr\Zcomplexfloatingr]rrNr6rNrrrr2s z_spbase.conjugatecCs |j|dS)NrM)rrrrrconjIsz _spbase.conjcCs |Sr2)r]rr5rrrrNsz _spbase._realcCs |Sr2)r]rr5rrrrQsz _spbase._imagcCs&|}|jdk}|j||j|fS)ayNonzero indices of the array/matrix. Returns a tuple of arrays (row,col) containing the indices of the non-zero elements of the array. Examples -------- >>> from scipy.sparse import csr_array >>> A = csr_array([[1,2,0],[0,0,3],[4,0,5]]) >>> A.nonzero() (array([0, 0, 1, 2, 2]), array([0, 1, 2, 0, 2])) r)rRrrr)r6rZnz_maskrrrnonzeroTs z_spbase.nonzerocCst|jdkrtd|jd}|dkr,||7}|dks<||krDtd|jdg|gdggf|df|jd}||}|S)zeReturns a copy of column j of the array, as an (m x 1) sparse array (column vector). rz4getcol not provided for 1d arrays. Use indexing A[j]r8rindex out of boundsrQr\)r7rJrQ IndexErrorr@r\)r6jrZ col_selectorrrrr_getcolhs   z_spbase._getcolcCsp|jdkrtd|jd}|dkr,||7}|dks<||krDtd|jdgdg|ggfd|f|jd}||S)z^Returns a copy of row i of the array, as a (1 x n) sparse array (row vector). rz$getrow not meaningful for a 1d arrayrrr)r7rJrQrrBr\)r6irZ row_selectorrrr_getrow{s   z_spbase._getrowcCs||j||dS)a Return a dense representation of this sparse array/matrix. Parameters ---------- order : {'C', 'F'}, optional Whether to store multi-dimensional data in C (row-major) or Fortran (column-major) order in memory. The default is 'None', which provides no ordering guarantees. Cannot be specified in conjunction with the `out` argument. out : ndarray, 2-D, optional If specified, uses this array (or `numpy.matrix`) as the output buffer instead of allocating a new array to return. The provided array must have the same shape and dtype as the sparse array/matrix on which you are calling the method. Returns ------- arr : numpy.matrix, 2-D A NumPy matrix object with the same shape and containing the same data represented by the sparse array/matrix, with the requested memory order. If `out` was passed and was an array (rather than a `numpy.matrix`), it will be filled with the appropriate values and returned wrapped in a `numpy.matrix` object that shares the same memory. rOr)rfrr6rOrrrrrsz_spbase.todensecCs|jddj||dS)a Return a dense ndarray representation of this sparse array/matrix. Parameters ---------- order : {'C', 'F'}, optional Whether to store multidimensional data in C (row-major) or Fortran (column-major) order in memory. The default is 'None', which provides no ordering guarantees. Cannot be specified in conjunction with the `out` argument. out : ndarray, 2-D, optional If specified, uses this array as the output buffer instead of allocating a new array to return. The provided array must have the same shape and dtype as the sparse array/matrix on which you are calling the method. For most sparse types, `out` is required to be memory contiguous (either C or Fortran ordered). Returns ------- arr : ndarray, 2-D An array with the same shape and containing the same data represented by the sparse array/matrix, with the requested memory order. If `out` was passed, the same object is returned after being modified in-place to contain the appropriate values. FrMr)rRrrrrrrsz_spbase.toarraycCs|j|djddS)zConvert this array/matrix to Compressed Sparse Row format. With copy=False, the data/indices may be shared between this array/matrix and the resultant csr_array/matrix. rMF)rRr]rrrrr]sz _spbase.tocsrcCs|j|djddS)zConvert this array/matrix to Dictionary Of Keys format. With copy=False, the data/indices may be shared between this array/matrix and the resultant dok_array/matrix. rMF)rRtodokrrrrrsz _spbase.todokcCs|jddj|dS)zConvert this array/matrix to COOrdinate format. With copy=False, the data/indices may be shared between this array/matrix and the resultant coo_array/matrix. FrM)r]rRrrrrrRsz _spbase.tocoocCs|jddj|dS)zConvert this array/matrix to List of Lists format. With copy=False, the data/indices may be shared between this array/matrix and the resultant lil_array/matrix. FrM)r]tolilrrrrrsz _spbase.tolilcCs|j|djddS)zConvert this array/matrix to sparse DIAgonal format. With copy=False, the data/indices may be shared between this array/matrix and the resultant dia_array/matrix. rMF)rRtodiarrrrrsz _spbase.todiacCs|jddj||dS)a+Convert this array/matrix to Block Sparse Row format. With copy=False, the data/indices may be shared between this array/matrix and the resultant bsr_array/matrix. When blocksize=(R, C) is provided, it will be used for construction of the bsr_array/matrix. FrM) blocksizerN)r]tobsr)r6rrNrrrr s z _spbase.tobsrcCs|j|djddS)zConvert this array/matrix to Compressed Sparse Column format. With copy=False, the data/indices may be shared between this array/matrix and the resultant csc_array/matrix. rMF)r]tocscrrrrrsz _spbase.tocsccCs|j|ddS)zReturns a copy of this array/matrix. No data/indices will be shared between the returned value and current array/matrix. TrM)rIr5rrrrNsz _spbase.copycCs0t|t|j}|jdkrv|dvr,td|tj|j|d|}|durrt dd|jDrjtd||d <|S|j\}}|dur|| tj|df|dj ||d S|d kr|d 7}|d kr| tjd|f|d|}n|| tj|df|d}|dur |j|jkr td|j |||d S)a Sum the array/matrix elements over a given axis. Parameters ---------- axis : {-2, -1, 0, 1, None} optional Axis along which the sum is computed. The default is to compute the sum of all the array/matrix elements, returning a scalar (i.e., `axis` = `None`). dtype : dtype, optional The type of the returned array/matrix and of the accumulator in which the elements are summed. The dtype of `a` is used by default unless `a` has an integer dtype of less precision than the default platform integer. In that case, if `a` is signed then the platform integer is used while if `a` is unsigned then an unsigned integer of the same precision as the platform integer is used. .. versionadded:: 0.18.0 out : np.matrix, optional Alternative output matrix in which to place the result. It must have the same shape as the expected output, but the type of the output values will be cast if necessary. .. versionadded:: 0.18.0 Returns ------- sum_along_axis : np.matrix A matrix with the same shape as `self`, with the specified axis removed. See Also -------- numpy.matrix.sum : NumPy's implementation of 'sum' for matrices rNr8raxis must be None, -1 or 0rNcss|]}|dkVqdS)rNr)rdimrrrrXrz_spbase.sum..zdimensions do not match.r\rrrrxr\r) r rr\r7rJr[ZonesrQr^anyrfsum)r6rxr\r res_dtyperrrrrrr 's>&   z _spbase.sumc Cs"t||jj}t|jtjp.t|jtj}|durD|rPtj}n t|j}|rZtjn|}||}|j dkr|dvrt d||j d}|j ||dS|dur||j d|j dj ||dS|dkr|d7}|dkr|d |j dj d||d S|d |j dj d||d SdS) a Compute the arithmetic mean along the specified axis. Returns the average of the array/matrix elements. The average is taken over all elements in the array/matrix by default, otherwise over the specified axis. `float64` intermediate and return values are used for integer inputs. Parameters ---------- axis : {-2, -1, 0, 1, None} optional Axis along which the mean is computed. The default is to compute the mean of all elements in the array/matrix (i.e., `axis` = `None`). dtype : data-type, optional Type to use in computing the mean. For integer inputs, the default is `float64`; for floating point inputs, it is the same as the input dtype. .. versionadded:: 0.18.0 out : np.matrix, optional Alternative output matrix in which to place the result. It must have the same shape as the expected output, but the type of the output values will be cast if necessary. .. versionadded:: 0.18.0 Returns ------- m : np.matrix See Also -------- numpy.matrix.mean : NumPy's implementation of 'mean' for matrices Nrrrr8r rrrr ) r r\rWr[rrZbool_rr^r7rJrQr ) r6rxr\rr ZintegralZ inter_dtypeZ inter_selfresrrrmean|s:%    z _spbase.meancCs|j|dS)aXReturns the kth diagonal of the array/matrix. Parameters ---------- k : int, optional Which diagonal to get, corresponding to elements a[i, i+k]. Default: 0 (the main diagonal). .. versionadded:: 1.0 See also -------- numpy.diagonal : Equivalent numpy function. Examples -------- >>> from scipy.sparse import csr_array >>> A = csr_array([[1, 2, 0], [0, 0, 3], [4, 0, 5]]) >>> A.diagonal() array([1, 0, 5]) >>> A.diagonal(k=1) array([2, 3]) k)r]diagonal)r6rrrrrsz_spbase.diagonalcCs|j|dS)aReturns the sum along diagonals of the sparse array/matrix. Parameters ---------- offset : int, optional Which diagonal to get, corresponding to elements a[i, i+offset]. Default: 0 (the main diagonal). r)rr )r6offsetrrrtraces z _spbase.tracecCsJ|j\}}|dkr||ks,|dkr4| |kr4td|t||dS)a Set diagonal or off-diagonal elements of the array/matrix. Parameters ---------- values : array_like New values of the diagonal elements. Values may have any length. If the diagonal is longer than values, then the remaining diagonal entries will not be set. If values are longer than the diagonal, then the remaining values are ignored. If a scalar value is given, all of the diagonal is set to it. k : int, optional Which off-diagonal to set, corresponding to elements a[i,i+k]. Default: 0 (the main diagonal). rzk exceeds array dimensionsN)rQrJ_setdiagr[rb)r6valuesrrrrrrsetdiags "z_spbase.setdiagcCs|j\}}|dkr|jdkrJt|||}t|D]}|||||f<q2nJt|||t|}|dkrjdSt|d|D]\}}|||||f<qzn|jdkrt|||}t|D]}|||||f<qnJt|||t|}|dkrdSt|d|D]\}}|||||f<qdS)zZThis part of the implementation gets overridden by the different formats. rN)rQr7minrqr3 enumerate)r6rrrrZ max_indexrvrrrrs(     z_spbase._setdiagcCs\|durD|durtd|j|jks0|j|jkr8tdd|d<|Stj|j|j|dSdS)Nz,order cannot be specified if out is not Nonez6out array must be same dtype and shape as sparse arrayg.)r\rO)rJrQr\r[Zzerosrrrr_process_toarray_args$sz_spbase._process_toarray_argsrcCs$ddlm}||||o t|t S)a Determine index dtype for array. This wraps _sputils.get_index_dtype, providing compatibility for both array and matrix API sparse matrices. Matrix API sparse matrices would attempt to downcast the indices - which can be computationally expensive and undesirable for users. The array API changes this behaviour. See discussion: https://github.com/scipy/scipy/issues/16774 The get_index_dtype import is due to implementation details of the test suite. It allows the decorator ``with_64bit_maxval_limit`` to mock a lower int32 max value for checks on the matrix API's downcasting behaviour. r)get_index_dtype)_sputilsrrPr)r6ZarraysmaxvalZcheck_contentsrrrr_get_index_dtype1s  z_spbase._get_index_dtypecCsd}t|tdd|jS)zGet shape of a sparse array/matrix. .. deprecated:: 1.11.0 This method will be removed in SciPy 1.14.0. Use `X.shape` instead. zP`get_shape` is deprecated and will be removed in v1.14.0; use `X.shape` instead.rr~)rDeprecationWarningr4r6msgrrr get_shapeOsz_spbase.get_shapecCs4d}t|tdd|j|dd|j}|j|_dS)zSee `reshape`. .. deprecated:: 1.11.0 This method will be removed in SciPy 1.14.0. Use `X.reshape` instead. zUShape assignment is deprecated and will be removed in v1.14.0; use `reshape` instead.rr~FrMN)rr rSr_r`__dict__)r6rQr"Znew_selfrrr set_shape^s z_spbase.set_shapecCs|jSr2)r4r5rrrqrz_spbase.zThe shape of the array. Note that, starting in SciPy 1.14.0, this property will no longer be settable. To change the array shape, use `X.reshape` instead. )fgetfsetdoccCsd}t|tdd|S)zUpcast array/matrix to a floating point format (if necessary) .. deprecated:: 1.11.0 This method is for internal use only, and will be removed from the public API in SciPy 1.14.0. zo`asfptype` is an internal function, and is deprecated as part of the public API. It will be removed in v1.14.0.rr~)rr rpr!rrrasfptypezsz_spbase.asfptypecCsd}t|tdd|S)zMaximum number of elements to display when printed. .. deprecated:: 1.11.0 This method is for internal use only, and will be removed from the public API in SciPy 1.14.0. zr`getmaxprint` is an internal function, and is deprecated as part of the public API. It will be removed in v1.14.0.rr~)rr rtr!rrr getmaxprintsz_spbase.getmaxprintcCsd}t|tdd|jS)zSparse array/matrix storage format. .. deprecated:: 1.11.0 This method will be removed in SciPy 1.14.0. Use `X.format` instead. zQ`getformat` is deprecated and will be removed in v1.14.0; use `X.format` instead.rr~)rr r`r!rrr getformatsz_spbase.getformatcCs |j|dS)aPNumber of stored values, including explicit zeros. Parameters ---------- axis : None, 0, or 1 Select between the number of values across the whole array/matrix, in each column, or in each row. See also -------- count_nonzero : Number of non-zero entries )rxrzrwrrrgetnnzs z_spbase.getnnzcCsd}t|tdd|S)zReturn the Hermitian transpose of this array/matrix. .. deprecated:: 1.11.0 This method will be removed in SciPy 1.14.0. Use `X.conj().T` instead. zN`getH` is deprecated and will be removed in v1.14.0; use `X.conj().T` instead.rr~)rr rrr!rrrgetHsz _spbase.getHcCs$d|d}t|tdd||S)zReturns a copy of column j of the array/matrix, as an (m x 1) sparse array/matrix (column vector). .. deprecated:: 1.11.0 This method will be removed in SciPy 1.14.0. Use array/matrix indexing instead. zB`getcol` is deprecated and will be removed in v1.14.0; use `X[:, [ ]]` instead.rr~)rr r)r6rr"rrrgetcols z_spbase.getcolcCs$d|d}t|tdd||S)zReturns a copy of row i of the array/matrix, as a (1 x n) sparse array/matrix (row vector). .. deprecated:: 1.11.0 This method will be removed in SciPy 1.14.0. Use array/matrix indexing instead. z?`getrow` is deprecated and will be removed in v1.14.0; use `X[[r/rr~)rr r)r6rr"rrrgetrows z_spbase.getrow)rYT)N)F)N)r)FF)NF)T)T)NN)NN)F)F)F)F)F)NF)F)NNN)NNN)r)r)r)rNF)N)rrr__doc__Z__array_priority__r}propertyintr7r:r<r>r@rBrDrFrHMAXPRINTrLrSrXr^ classmethodrfrhrprsrtrvryr{r|rr`r[rrrrrrrrr __nonzero__rr_rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr]rrRrrrrrNr rrrrrrrr#r%rQr*r+r,r-r.r0r1rrrrr0?s         +            '   V ,   & #       U K     r0c@seZdZdZdS)rz3A namespace class to separate sparray from spmatrixN)rrrr2rrrrrsrcCs t|tS)a!Is `x` of a sparse array or sparse matrix type? Parameters ---------- x object to check for being a sparse array or sparse matrix Returns ------- bool True if `x` is a sparse array or a sparse matrix, False otherwise Examples -------- >>> import numpy as np >>> from scipy.sparse import csr_array, csr_matrix, issparse >>> issparse(csr_matrix([[5]])) True >>> issparse(csr_array([[5]])) True >>> issparse(np.array([[5]])) False >>> issparse(5) False )rPr0rrrrrsrcCs t|tS)aIs `x` of a sparse matrix type? Parameters ---------- x object to check for being a sparse matrix Returns ------- bool True if `x` is a sparse matrix, False otherwise Examples -------- >>> import numpy as np >>> from scipy.sparse import csr_array, csr_matrix, isspmatrix >>> isspmatrix(csr_matrix([[5]])) True >>> isspmatrix(csr_array([[5]])) False >>> isspmatrix(np.array([[5]])) False >>> isspmatrix(5) False )rPr r8rrrrsr)1r2warningsrnumpyr[Zscipy._lib._utilrrrrrrr r r r Z_matrixr __all__Warningrrrr frozensetsintanZarcsinZarctansinhtanhZarcsinhZarctanhZrintsignexpm1log1pZdeg2radZrad2degfloorceiltruncsqrtZ _ufuncs_with_fixed_point_at_zeror5r0rrrrrrrsh  ( .