U -e@srdZddlmZddlZddlmZmZmZm Z m Z m Z m Z m Z mZdddd d gZGd d d eZGd d d eZGdd d eZddgddgddgddgddgddgddgddgddgdd gd!d"gd#d$gd%d&gd'd(gd)d*gd+d,gd-d.gd/d0gd1d2gd3d4gd5Zeejejejejejejejejejejej ej!ej"ej#ej$ej%ej&ej'gZ(d6Z)Gd7ddZ*d8dZ+e+Z,dS)9zBase class for sparse matrices)warnN) asmatrixcheck_reshape_kwargs check_shape get_sum_dtypeisdense isintlike isscalarlikematrix validateaxisspmatrix isspmatrixissparse SparseWarningSparseEfficiencyWarningc@s eZdZdS)rN__name__ __module__ __qualname__rrS/var/www/html/Darija-Ai-Train/env/lib/python3.8/site-packages/scipy/sparse/_base.pyrsc@s eZdZdS)SparseFormatWarningNrrrrrrsrc@s eZdZdS)rNrrrrrrszCompressed 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@seZdZdZdZdZeddZeddZedd Z ed d Z ed d Z eddZ eddZ dZefddZddZddZeeedZddZddZdd d!Zed"d#Zed$d%Zd&d'Zd(d)Zd*d+Zd,d-Zdd/d0Zed1d2Zd3d4Z d5d6Z!d7d8Z"d9d:Z#e#Z$d;d<Z%dd=d>Z&d?d@Z'dAdBZ(dCdDZ)dEdFZ*ddGdHZ+dIdJZ,dKdLZ-dMdNZ.dOdPZ/dQdRZ0dSdTZ1dUdVZ2ddXdYZ3dZd[Z4d\d]Z5d^d_Z6d`daZ7dbdcZ8dddeZ9dfdgZ:dhdiZ;djdkZdpdqZ?drdsZ@dtduZAdvdwZBdxdyZCdzd{ZDd|d}ZEd~dZFdddZGddZHddZIddZJddZKddZLddZMddZNddZOddZPddZQddZRddZSdddZTdddZUdddZVeUjeV_ddZWddZXddZYddZZddZ[ddZ\dddZ]dddZ^dddZ_dddZ`dddZadddZbdddZcdddZddddZeddZfdddZgdddÄZhdddńZidddDŽZjdddɄZkdd˄Zldd̈́Zmd.S)r z This class provides a base class for all sparse matrices. It cannot be instantiated. Most of the work is provided by subclasses. g333333$@rcCsddlm}|S)Nr) bsr_matrix)Z_bsrr/)selfr/rrr_bsr_containerDs zspmatrix._bsr_containercCsddlm}|S)Nr) coo_matrix)Z_coor2)r0r2rrr_coo_containerIs zspmatrix._coo_containercCsddlm}|S)Nr) csc_matrix)Z_cscr4)r0r4rrr_csc_containerNs zspmatrix._csc_containercCsddlm}|S)Nr) csr_matrix)Z_csrr6)r0r6rrr_csr_containerSs zspmatrix._csr_containercCsddlm}|S)Nr) dia_matrix)Z_diar8)r0r8rrr_dia_containerXs zspmatrix._dia_containercCsddlm}|S)Nr) dok_matrix)Z_dokr:)r0r:rrr_dok_container]s zspmatrix._dok_containercCsddlm}|S)Nr) lil_matrix)Z_lilr<)r0r<rrr_lil_containerbs zspmatrix._lil_containerFcCs$d|_|jjdkrtd||_dS)Nr z7This class is not intended to be instantiated directly.)_shape __class__r ValueErrormaxprint)r0rArrr__init__is zspmatrix.__init__cCs"|j|dd|j}|j|_dS)zSee `reshape`.FcopyN)reshapeasformatformat__dict__)r0shapeZ new_matrixrrr set_shapepszspmatrix.set_shapecCs|jS)zGet shape of a matrix.)r>r0rrr get_shapewszspmatrix.get_shape)fgetfsetcOsJt||j}t|\}}||jkr2|r.|S|S|j|dj||ddS)areshape(self, shape, order='C', copy=False) Gives a new shape to a sparse 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 matrix being used. Returns ------- reshaped_matrix : sparse matrix A sparse matrix with the given `shape`, not necessarily of the same format as the current object. See Also -------- numpy.matrix.reshape : NumPy's implementation of 'reshape' for matrices rCF)orderrD)rrIrrDtocoorE)r0argskwargsrIrOrDrrrrE}s!   zspmatrix.reshapecCstdt|jdS)aResize the 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 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 matrix 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)NotImplementedErrorrGtyper)r0rIrrrresizeszspmatrix.resizeunsafeTcCsDt|}|j|kr0|j|||d|jS|r<|S|SdS)aCast the 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 matrix. If `copy` is `True`, it is guaranteed that the result and this matrix do not share any memory. )castingrDN)npdtypetocsrastyperFrGrD)r0rYrWrDrrrr[s  zspmatrix.astypecKs$|jrtj|f|St|f|SdSN) _is_arrayrXasarrayrclsXrRrrr _ascontainerszspmatrix._ascontainercKs$|jrtj|f|St|f|SdSr\)r]rXarrayr r_rrr _containerszspmatrix._containercCsXddddg}|jj|kr|S|D]"}|jt|kr ||Sq td|jjdS)z7Upcast matrix to a floating point format (if necessary)fdFDz-cannot upcast [%s] to a floating point formatN)rYcharrXr[ TypeErrorname)r0Zfp_typesZfp_typerrrasfptypes  zspmatrix.asfptypeccs*t|jdD]}||ddfVqdSNr)rangerI)r0rrrr__iter__szspmatrix.__iter__cCs|jS)z3Maximum number of elements to display when printed.)rArKrrr getmaxprintszspmatrix.getmaxprintcCstd|jjdS)a(Number of non-zero entries, equivalent to np.count_nonzero(a.toarray()) Unlike getnnz() and 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.NrSr?rrKrrr count_nonzeros zspmatrix.count_nonzeroNcCstd|jjdS)aJNumber of stored values, including explicit zeros. Parameters ---------- axis : None, 0, or 1 Select between the number of values across the whole matrix, in each column, or in each row. See also -------- count_nonzero : Number of non-zero entries zgetnnz not implemented for %s.Nrr)r0axisrrrgetnnzs zspmatrix.getnnzcCs|S)zNumber of stored values, including explicit zeros. See also -------- count_nonzero : Number of non-zero entries )rurKrrrnnz#sz spmatrix.nnzcCs t|ddS)z.Format of a matrix representation as a string.rGr-)getattrrKrrr getformat-szspmatrix.getformatcCs@t|\}}|jrdnd}d|d|j|jj|j|fS)Nrcr z<%dx%d sparse z4 of type '%s' with %d stored elements in %s format>)_formatsrxr]rIrYrTrv)r0_ format_nameZ sparse_clsrrr__repr__1s  zspmatrix.__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|] }d|qS)z %s %sr).0trrr @sz3spmatrix.__str__..tostr..)ziplistjoin)rowcoldataZtriplesrrrtostr>szspmatrix.__str__..tostrrz : : )rqrPrvrrr)r0rAArZhalfoutrrr__str__8s * 6zspmatrix.__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().)rIrvr@rKrrr__bool__Ms  zspmatrix.__bool__cCs tddS)Nz;sparse matrix length is ambiguous; use getnnz() or shape[0])rjrKrrr__len__Xszspmatrix.__len__c Cs|dks||jkr$|r|S|Snnzt|d|}Wn2tk rh}ztd||W5d}~XYnXz ||dWStk r|YSXdS)aReturn this matrix in the passed format. Parameters ---------- format : {str, None} The desired matrix 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 matrix in the passed format. NtozFormat {} is unknown.rC)rGrDrwAttributeErrorr@rj)r0rGrDZconvert_methoderrrrF\s" zspmatrix.asformatcCs||S)z4Point-wise multiplication by another matrix )rZmultiplyr0otherrrrrszspmatrix.multiplycCs||S)z5Element-wise maximum between this and another matrix.)rZmaximumrrrrrszspmatrix.maximumcCs||S)z5Element-wise minimum between this and another matrix.)rZminimumrrrrrszspmatrix.minimumcCst|r||S||SdS)a1Ordinary dot product Examples -------- >>> import numpy as np >>> from scipy.sparse import csr_matrix >>> A = csr_matrix([[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)rXZisscalarrrrrdots z spmatrix.dotcCs|j||dS)zElement-wise power.rY)rZpower)r0nrYrrrrszspmatrix.powercCs||Sr\)rZ__eq__rrrrrszspmatrix.__eq__cCs||Sr\)rZ__ne__rrrrrszspmatrix.__ne__cCs||Sr\)rZ__lt__rrrrrszspmatrix.__lt__cCs||Sr\)rZ__gt__rrrrrszspmatrix.__gt__cCs||Sr\)rZ__le__rrrrrszspmatrix.__le__cCs||Sr\)rZ__ge__rrrrrszspmatrix.__ge__cCs t|Sr\)absrZrKrrr__abs__szspmatrix.__abs__rcCst||dS)N)ndigits)roundrZ)r0rrrr __round__szspmatrix.__round__cCs||Sr\)rZ _add_sparserrrrrszspmatrix._add_sparsecCs||Sr\)rP _add_denserrrrrszspmatrix._add_densecCs||Sr\)rZ _sub_sparserrrrrszspmatrix._sub_sparsecCs ||Sr\todenserrrr _sub_denseszspmatrix._sub_densecCs ||Sr\rrrrr _rsub_denseszspmatrix._rsub_densecCspt|r"|dkr|StdnJt|rH|j|jkr>td||St|rht ||j}| |St SdS)Nrz;adding a nonzero scalar to a sparse matrix is not supportedinconsistent shapes) r rDrSrrIr@rrrX broadcast_torNotImplementedrrrr__add__s    zspmatrix.__add__cCs ||Sr\)rrrrr__radd__szspmatrix.__radd__cCspt|r"|dkr|StdnJt|rH|j|jkr>td||St|rht ||j}| |St SdS)NrzBsubtracting a nonzero scalar from a sparse matrix is not supportedr) r rDrSrrIr@rrrXrrrrrrr__sub__s    zspmatrix.__sub__cCsLt|r$|dkr| Stdn$t|rDt||j}||StSdS)NrzBsubtracting a sparse matrix from a nonzero scalar is not supported) r rDrSrrXrrIrrrrrr__rsub__s   zspmatrix.__rsub__cCs|j\}}|jtjkrr|j|fkr,||S|j|dfkrP|||dS|jdkrr|jd|krr||St |r| |St |r|jd|jdkrt d| |St|}|jdkr|jtjkrtSz |jWntk r|}YnX|jdks"|jdkr|jddkr|j|fkrH|j|dfkrHt d|t|}t|tjrp||}|jdkr|jddkr|dd}|S|jdkr|jd|jdkrt d|t|}t|tjr||}|St ddS)z`np.matrix`-compatible mul, i.e. `dot` or `NotImplemented` interpret other and call one of the following self._mul_scalar() self._mul_vector() self._mul_multivector() self._mul_sparse_matrix() rrrzdimension mismatchzcould not interpret dimensionsN)rIr?rXZndarray _mul_vectorZravelrEndim_mul_multivectorr _mul_scalarrr@_mul_sparse_matrixZ asanyarrayrYZobject_rr isinstancer rbr^)r0rMNZother_aresultrrr _mul_dispatchsL          (    zspmatrix._mul_dispatchcCs ||Sr\)rrrrr__mul__Mszspmatrix.__mul__cCs||Sr\)rZrrrrrrQszspmatrix._mul_scalarcCs||Sr\)rZrrrrrrTszspmatrix._mul_vectorcCs||Sr\)rZrrrrrrWszspmatrix._mul_multivectorcCs||Sr\)rZrrrrrrZszspmatrix._mul_sparse_matrixcCsht|r||Sz |}Wn"tk r@t|}YnX||}|tkr\tS|SdSr\)r r transposerrXr^rr)r0rtrretrrr_rmul_dispatch]s  zspmatrix._rmul_dispatchcCs ||Sr\)rrrrr__rmul__kszspmatrix.__rmul__cCst|rtd||SNz0Scalar operands are not allowed, use '*' instead)r r@rrrrr __matmul__rszspmatrix.__matmul__cCst|rtd||Sr)r r@rrrrr __rmatmul__xszspmatrix.__rmatmul__cCsdt|r|r0|r t||St||S|rZt|jtjrZ|tj d|S| d|}t |j}t |jtj rt |tj r||jS|Snt |r|s|rt||St||Sn$|rt||St||Snbt|r\|r|j||ddS|}|rPt|jtjrP|tj|S||SntSdS)N?F)rdivide)r rX true_dividerdivideZcan_castrYZfloat_r[rr^ issubdtypeintegerrr_dividerZZ_divide_sparser)r0rrrroZ scalar_dtypeZself_csrrrrrs<      zspmatrix._dividecCs|j|ddSNT)rrrrrr __truediv__szspmatrix.__truediv__cCs|j|ddSrrrrrr__div__szspmatrix.__div__cCstSr\rrrrr __rtruediv__szspmatrix.__rtruediv__cCstSr\rrrrr__rdiv__szspmatrix.__rdiv__cCs | Sr\)rZrKrrr__neg__szspmatrix.__neg__cCstSr\rrrrr__iadd__szspmatrix.__iadd__cCstSr\rrrrr__isub__szspmatrix.__isub__cCstSr\rrrrr__imul__szspmatrix.__imul__cCs ||Sr\) __itruediv__rrrr__idiv__szspmatrix.__idiv__cCstSr\rrrrrrszspmatrix.__itruediv__cCs|jd|jd}}||kr&tdt|rt|}|dkrFtd|dkrddlm}|||jd}|jrddl m }||}|S|dkr| S| |d}|dr|||S||Snt |rtd ntSdS) Nrrzmatrix is not squarezexponent must be >= 0)eyer) dia_arrayrzexponent must be an integer)rIrjr intr@Z _constructrrYr]Z_arraysrrD__pow__r r)r0rrrrErtmprrrrs.     zspmatrix.__pow__cCs|dkr$|jrttd|S|dkr4|S|dkrX|jrPttd|S|dkrh|S|dkrx|S|dkr| St |d dS) NrzPlease use `.todense()` insteadTHzPlease use `.conj().T` insteadrealimagsizez not found) r]rrXZVisibleDeprecationWarningtoarrayrgetH_real_imagrur)r0attrrrr __getattr__s*zspmatrix.__getattr__cCs|j|dj|ddS)a Reverses the dimensions of the sparse matrix. Parameters ---------- axes : None, optional This argument is in the signature *solely* for NumPy compatibility reasons. Do not pass in anything except for the default value. copy : bool, optional Indicates whether or not attributes of `self` should be copied whenever possible. The degree to which attributes are copied varies depending on the type of sparse matrix being used. Returns ------- p : `self` with the dimensions reversed. See Also -------- numpy.matrix.transpose : NumPy's implementation of 'transpose' for matrices rCF)axesrD)rZr)r0rrDrrrrszspmatrix.transposecCs8t|jtjr$|j|djddS|r0|S|SdS)aElement-wise complex conjugation. If the 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. rCFN)rXrrYZcomplexfloatingrZconjrDr0rDrrrr s z spmatrix.conjcCs |j|dS)NrC)rrrrr conjugate7szspmatrix.conjugatecCs |S)zReturn the Hermitian transpose of this matrix. See Also -------- numpy.matrix.getH : NumPy's implementation of `getH` for matrices )rrrKrrrr=sz spmatrix.getHcCs |Sr\)rZrrKrrrrFszspmatrix._realcCs |Sr\)rZrrKrrrrIszspmatrix._imagcCs&|}|jdk}|j||j|fS)agnonzero indices Returns a tuple of arrays (row,col) containing the indices of the non-zero elements of the matrix. Examples -------- >>> from scipy.sparse import csr_matrix >>> A = csr_matrix([[1,2,0],[0,0,3],[4,0,5]]) >>> A.nonzero() (array([0, 0, 1, 2, 2]), array([0, 1, 2, 0, 2])) r)rPrrr)r0rZnz_maskrrrnonzeroLs zspmatrix.nonzerocCs^|jd}|dkr||7}|dks*||kr2td|jdg|gdggf|df|jd}||S)zgReturns a copy of column j of the matrix, as an (m x 1) sparse matrix (column vector). rrindex out of boundsrIrY)rI IndexErrorr5rY)r0jrZ col_selectorrrrgetcol`s zspmatrix.getcolcCs^|jd}|dkr||7}|dks*||kr2td|jdgdg|ggfd|f|jd}||S)z`Returns a copy of row i of the matrix, as a (1 x n) sparse matrix (row vector). rrrr)rIrr7rY)r0imZ row_selectorrrrgetrowps zspmatrix.getrowcCs||j||dS)a Return a dense matrix representation of this 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 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 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)rbrr0rOrrrrrszspmatrix.todensecCs|jddj||dS)a Return a dense ndarray representation of this 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 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 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. FrCr)rPrrrrrrszspmatrix.toarraycCs|j|djddS)zConvert this matrix to Compressed Sparse Row format. With copy=False, the data/indices may be shared between this matrix and the resultant csr_matrix. rCF)rPrZrrrrrZszspmatrix.tocsrcCs|j|djddS)zConvert this matrix to Dictionary Of Keys format. With copy=False, the data/indices may be shared between this matrix and the resultant dok_matrix. rCF)rPtodokrrrrrszspmatrix.todokcCs|jddj|dS)zConvert this matrix to COOrdinate format. With copy=False, the data/indices may be shared between this matrix and the resultant coo_matrix. FrC)rZrPrrrrrPszspmatrix.tocoocCs|jddj|dS)zConvert this matrix to List of Lists format. With copy=False, the data/indices may be shared between this matrix and the resultant lil_matrix. FrC)rZtolilrrrrrszspmatrix.tolilcCs|j|djddS)zConvert this matrix to sparse DIAgonal format. With copy=False, the data/indices may be shared between this matrix and the resultant dia_matrix. rCF)rPtodiarrrrrszspmatrix.todiacCs|jddj||dS)aConvert this matrix to Block Sparse Row format. With copy=False, the data/indices may be shared between this matrix and the resultant bsr_matrix. When blocksize=(R, C) is provided, it will be used for construction of the bsr_matrix. FrC) blocksizerD)rZtobsr)r0rrDrrrrs zspmatrix.tobsrcCs|j|djddS)zConvert this matrix to Compressed Sparse Column format. With copy=False, the data/indices may be shared between this matrix and the resultant csc_matrix. rCF)rZtocscrrrrr szspmatrix.tocsccCs|j|ddS)zReturns a copy of this matrix. No data/indices will be shared between the returned value and current matrix. TrC)r?rKrrrrDsz spmatrix.copycCst||j\}}t|j}|dkrJ||tj|df|dj||dS|dkrZ|d7}|dkr|tjd|f|d|}n||tj|df|d}|dk r|j|jkrtd|j|||dS) aw Sum the 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 matrix elements, returning a scalar (i.e., `axis` = `None`). dtype : dtype, optional The type of the returned 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 NrrrYrrrzdimensions do not matchrtrYr) r rIrrYrbrXZonessumr@)r0rtrYrrr res_dtyperrrrrs.&  z spmatrix.sumc Csdd}t||jj}||j}|dkr6|rBtj}n t|j}|rLtjn|}||}|dkr|t|jd|jdj||dS|dkr|d7}|dkr|d|jdjd||d S|d|jdjd||d SdS) a Compute the arithmetic mean along the specified axis. Returns the average of the matrix elements. The average is taken over all elements in the 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 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 cSst|tjpt|tjSr\)rXrrZbool_rrrr _is_integrals z#spmatrix.mean.._is_integralNrrrrrr) r rYrTrXZfloat64r[rcrIr) r0rtrYrrrZintegralZ inter_dtypeZ inter_selfrrrmeands<%   z spmatrix.meancCs|j|dS)aTReturns the kth diagonal of the 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_matrix >>> A = csr_matrix([[1, 2, 0], [0, 0, 3], [4, 0, 5]]) >>> A.diagonal() array([1, 0, 5]) >>> A.diagonal(k=1) array([2, 3]) k)rZdiagonal)r0rrrrrszspmatrix.diagonalcCs|j|dS)zReturns the sum along diagonals of the sparse matrix. Parameters ---------- offset : int, optional Which diagonal to get, corresponding to elements a[i, i+offset]. Default: 0 (the main diagonal). r)rr)r0offsetrrrtraces zspmatrix.tracecCsJ|j\}}|dkr||ks,|dkr4| |kr4td|t||dS)a Set diagonal or off-diagonal elements of the array. 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 matrix dimensionsN)rIr@_setdiagrXr^)r0valuesrrrrrrsetdiags "zspmatrix.setdiagcCs|j\}}|dkr|jdkrJt|||}t|D]}|||||f<q2nJt|||t|}|dkrjdSt|d|D]\}}|||||f<qzn|jdkrt|||}t|D]}|||||f<qnJt|||t|}|dkrdSt|d|D]\}}|||||f<qdSrm)rIrminrnlen enumerate)r0r rrrZ max_indexrvrrrr s(     zspmatrix._setdiagcCs\|dk rD|dk rtd|j|jks0|j|jkr8tdd|d<|Stj|j|j|dSdS)Nz,order cannot be specified if out is not Nonez7out array must be same dtype and shape as sparse matrixg.)rYrO)r@rIrYrXZzerosrrrr_process_toarray_argsszspmatrix._process_toarray_args)rVT)N)F)N)r)FF)NF)T)T)NN)NN)F)F)F)F)F)NF)F)NNN)NNN)r)r)r)nrrr__doc__Z__array_priority__rpropertyr1r3r5r7r9r;r=r]MAXPRINTrBrJrLrIrErUr[ classmethodrbrdrlrprqrsrurvrxr|rr __nonzero__rrFrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrZrrPrrrrrDrrrr r r rrrrrr <s         +      '   O +    $ #       J I  cCs 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 Notes ----- issparse and isspmatrix are aliases for the same function. Examples -------- >>> from scipy.sparse import csr_matrix, isspmatrix >>> isspmatrix(csr_matrix([[5]])) True >>> from scipy.sparse import isspmatrix >>> isspmatrix(5) False )rr )xrrrrs)-rwarningsrnumpyrXZ_sputilsrrrrrr r r r __all__Warningrrrry frozensetsintanZarcsinZarctansinhtanhZarcsinhZarctanhZrintsignexpm1log1pZdeg2radZrad2degfloorceiltruncsqrtZ _ufuncs_with_fixed_point_at_zerorr rrrrrrs ,b