scipy.sparse.

spmatrix

class scipy.sparse.spmatrix(*args, **kwargs)

This class provides a base class for all sparse matrix classes.

Warning

SciPy sparse is shifting from a sparse matrix interface to a sparse array interface. In the next few releases we expect to deprecate the sparse matrix interface. For documentation of the matrix interface, see the spmatrix interface docs. For guidance on converting existing code to sparse arrays, see Migration from spmatrix to sparray.

This class also serves as the namespace for SciPy sparse matrix types. It cannot be instantiated. Most of the work is provided by subclasses. Use a subclass that overrides at least one of tocoo or tocsr.

Attributes:

T

Transpose.

format

Format string for matrix.

imag

mT

Matrix transpose.

ndim

nnz

Number of stored values, including explicit zeros.

real

shape

Shape of the matrix

size

Number of stored values.

Methods

__len__()
__mul__(other)
__pow__(power)
asformat(format[, copy])	Return this array/matrix in the passed format.
asfptype()	Upcast matrix to a floating point format (if necessary)
astype(dtype[, casting, copy])	Cast the array/matrix elements to a specified type.
conj([copy])	Element-wise complex conjugation.
conjugate([copy])	Element-wise complex conjugation.
copy()	Returns a copy of this array/matrix.
count_nonzero([axis])	Number of non-zero entries.
diagonal([k])	Returns the kth diagonal of the array/matrix.
dot(other)	Ordinary dot product.
getH()	Return the Hermitian transpose of this matrix.
get_shape()	Get the shape of the matrix
getcol(j)	Returns a copy of column j of the matrix, as an (m x 1) sparse matrix (column vector).
getformat()	Matrix storage format
getmaxprint()	Maximum number of elements to display when printed.
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)	Element-wise maximum between this and another array/matrix.
mean([axis, dtype, out])	Compute the arithmetic mean along the specified axis.
minimum(other)	Element-wise minimum between this and another array/matrix.
multiply(other)	Element-wise multiplication by another array/matrix.
nonzero()	Nonzero indices of the array/matrix.
power(n[, dtype])	Element-wise power.
reshape(self, shape[, order, copy])	Gives a new shape to a sparse array/matrix without changing its data.
resize(*shape)	Resize the array/matrix in-place to dimensions given by shape.
set_shape(shape)	Set the shape of the matrix in-place
setdiag(values[, k])	Set diagonal or off-diagonal elements of the array/matrix.
sum([axis, dtype, out])	Sum the array/matrix elements over a given axis.
toarray([order, out])	Return a dense ndarray representation of this sparse array/matrix.
tobsr([blocksize, copy])	Convert this array/matrix to Block Sparse Row format.
tocoo([copy])	Convert this array/matrix to COOrdinate format.
tocsc([copy])	Convert this array/matrix to Compressed Sparse Column format.
tocsr([copy])	Convert this array/matrix to Compressed Sparse Row format.
todense([order, out])	Return a dense representation of this sparse matrix.
todia([copy])	Convert this array/matrix to sparse DIAgonal format.
todok([copy])	Convert this array/matrix to Dictionary Of Keys format.
tolil([copy])	Convert this array/matrix to List of Lists format.
trace([offset])	Returns the sum along diagonals of the sparse array/matrix.
transpose([axes, copy])	Reverses the dimensions of the sparse array/matrix.

__add__
__matmul__
__rmatmul__
__rmul__
__truediv__