o i@s~zddlZdZWn eydZYnwddlZddlmZddlmZddlmZddlm Z Gdd d ej Z d d Z dS) NTF)_core)_csc)_data)_utilc@sleZdZdZdZdddZddd Zdd d Zd d ZdddZ dddZ dddZ dddZ dddZ dS) dia_matrixaSparse matrix with DIAgonal storage. Now it has only one initializer format below: ``dia_matrix((data, offsets))`` Args: arg1: Arguments for the initializer. shape (tuple): Shape of a matrix. Its length must be two. dtype: Data type. It must be an argument of :class:`numpy.dtype`. copy (bool): If ``True``, copies of given arrays are always used. .. seealso:: :class:`scipy.sparse.dia_matrix` diaNFc CsPtrtj|r|}|j}|j}|j}|j}d}nt |t r-|\}}|dur,t dnt dt j |||d}t |}t j |d|d}t |}|jdkrTt d|jdkr]t d |jd t|krst d |jd t|ft |}|dd |ddkrt d ||_||_t|st dt|d t|df|_dS)NFzexpected a shape argumentz,unrecognized form for dia_matrix constructor)dtypecopyizoffsets array must have rank 1zdata array must have rank 2rzBnumber of diagonals (%d) does not match the number of offsets (%d)z&offset array contains duplicate valuesz(invalid shape (must be a 2-tuple of int))_scipy_availablescipysparseissparsetodiadataoffsetsshaper isinstancetuple ValueErrorcupyarray atleast_2d atleast_1dndimlensortanyrisshapeint_shape) selfarg1rrr xrrsorted_offsetsr(T/home/ubuntu/veenaModal/venv/lib/python3.10/site-packages/cupyx/scipy/sparse/_dia.py__init__%sJ       zdia_matrix.__init__TcCs0|rt||jf|jdSt||jf|jdS)zReturns a matrix with the same sparsity structure as self, but with different data. By default the structure arrays are copied. r)rrr r)r$rr r(r(r) _with_dataQszdia_matrix._with_datacCs:tstd|j|}|j|}tjj||f|jdS)a:Returns a copy of the array on host memory. Args: stream (cupy.cuda.Stream): CUDA stream object. If it is given, the copy runs asynchronously. Otherwise, the copy is synchronous. Returns: scipy.sparse.dia_matrix: Copy of the array on host memory. zscipy is not availabler+) r RuntimeErrorrgetrrrrr#)r$streamrrr(r(r)r.Zs    zdia_matrix.getcCs|jS)zcReturns the shape of the matrix. Returns: tuple: Shape of the matrix. )r#)r$r(r(r) get_shapekszdia_matrix.get_shapec CsB|durtd|j\}}tddddddd |j||}t|S) zReturns the number of stored values, including explicit zeros. Args: axis: Not supported yet. Returns: int: The number of stored values. Nz5getnnz over an axis is not implemented for DIA formatzint32 offsets, int32 m, int32 nz int32 nnzz7offsets > 0 ? min(m, n - offsets) : min(m + offsets, n)za + bznnz = a0dia_nnz)NotImplementedErrorrrReductionKernelrr")r$axismnnnzr(r(r)getnnzss  zdia_matrix.getnnzcCs|j||dS)z3Returns a dense matrix representing the same value.)orderout)tocsctoarray)r$r:r;r(r(r)r=szdia_matrix.toarrayc Cs|jjdkrtj|j|jdS|j\}}|jj\}}tdddd||jdddf|||j\}}t j |dd d}t |j dd |d|d<||||dd<|j |j jd d d } |jj |j } tj| | |f|j|jd S)a{Converts the matrix to Compressed Sparse Column format. Args: copy (bool): If ``False``, it shares data arrays as much as possible. Actually this option is ignored because all arrays in a matrix cannot be shared in dia to csc conversion. Returns: cupyx.scipy.sparse.csc_matrix: Converted matrix. rrzGint32 offset_len, int32 offsets, int32 num_rows, int32 num_cols, T datazint32 row, bool maskz int offset_inds = i % offset_len; row = offset_inds - offsets; mask = (row >= 0 && row < num_rows && offset_inds < num_cols && data != T(0)); cupyx_scipy_sparse_dia_tocscNr r )r5F)r )rr)rsizer csc_matrixrrrElementwiseKernelrrzeroscumsumsumTastype) r$r num_rowsnum_cols num_offsets offset_lenrowmaskindptrindicesrr(r(r)r<s*     zdia_matrix.tocsccCs |S)axConverts the matrix to Compressed Sparse Row format. Args: copy (bool): If ``False``, it shares data arrays as much as possible. Actually this option is ignored because all arrays in a matrix cannot be shared in dia to csr conversion. Returns: cupyx.scipy.sparse.csc_matrix: Converted matrix. )r<tocsr)r$r r(r(r)rPs zdia_matrix.tocsrrcCs|j\}}|| ks||krtjd|jjdSt|j|k\}td|t|||}}|j dkr=tj |||jjdS|j|d||fS)aReturns the k-th diagonal of the matrix. Args: k (int, optional): Which diagonal to get, corresponding to elements a[i, i+k]. Default: 0 (the main diagonal). Returns: cupy.ndarray : The k-th diagonal. rr>) rremptyrrnonzerormaxminr@rC)r$krowscolsidx first_collast_colr(r(r)diagonals  zdia_matrix.diagonal)NNF)T)N)NN)F)r)__name__ __module__ __qualname____doc__formatr*r,r.r0r9r=r<rPr[r(r(r(r)rs  ,     &rcCs t|tS)zChecks if a given matrix is of DIA format. Returns: bool: Returns if ``x`` is :class:`cupyx.scipy.sparse.dia_matrix`. )rr)r&r(r(r)isspmatrix_dias ra) scipy.sparserr ImportErrorrrcupyx.scipy.sparserrr _data_matrixrrar(r(r(r)s      E