scipy.sparse.spmatrix¶

class scipy.sparse.spmatrix(maxprint=50)[source]

This class provides a base class for all sparse matrices. It cannot be instantiated. Most of the work is provided by subclasses.

Attributes

 nnz Number of stored values, including explicit zeros. shape

Methods

 asformat(format) Return this matrix in a given sparse format asfptype() Upcast matrix to a floating point format (if necessary) astype(t) conj() conjugate() copy() Returns a copy of this matrix. count_nonzero() Number of non-zero entries, equivalent to diagonal() Returns the main diagonal of the matrix dot(other) Ordinary dot product getH() get_shape() getcol(j) Returns a copy of column j of the matrix, as an (m x 1) sparse matrix (column vector). getformat() getmaxprint() getnnz([axis]) Number of stored values, including explicit zeros. getrow(i) Returns a copy of row i of the matrix, as a (1 x n) sparse matrix (row vector). maximum(other) mean([axis, dtype, out]) Compute the arithmetic mean along the specified axis. minimum(other) multiply(other) Point-wise multiplication by another matrix nonzero() nonzero indices power(n[, dtype]) reshape(shape[, order]) Gives a new shape to a sparse matrix without changing its data. set_shape(shape) setdiag(values[, k]) Set diagonal or off-diagonal elements of the array. sum([axis, dtype, out]) Sum the matrix elements over a given axis. toarray([order, out]) Return a dense ndarray representation of this matrix. tobsr([blocksize, copy]) Convert this matrix to Block Sparse Row format. tocoo([copy]) Convert this matrix to COOrdinate format. tocsc([copy]) Convert this matrix to Compressed Sparse Column format. tocsr([copy]) Convert this matrix to Compressed Sparse Row format. todense([order, out]) Return a dense matrix representation of this matrix. todia([copy]) Convert this matrix to sparse DIAgonal format. todok([copy]) Convert this matrix to Dictionary Of Keys format. tolil([copy]) Convert this matrix to LInked List format. transpose([axes, copy]) Reverses the dimensions of the sparse matrix.

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