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scipy.sparse.construct

Functions to construct sparse matrices

Functions

bmat(blocks[, format, dtype])	Build a sparse matrix from sparse sub-blocks
eye(m, n[, k, dtype, format])	eye(m, n) returns a sparse (m x n) matrix where the k-th diagonal
hstack(blocks[, format, dtype])	Stack sparse matrices horizontally (column wise)
identity(n[, dtype, format])	Identity matrix in sparse format
kron(A, B[, format])	kronecker product of sparse matrices A and B
kronsum(A, B[, format])	kronecker sum of sparse matrices A and B
rand(m, n[, density, format, dtype])	Generate a sparse matrix of the given shape and density with uniformely distributed values.
spdiags(data, diags, m, n[, format])	Return a sparse matrix from diagonals.
upcast(*args)	Returns the nearest supported sparse dtype for the combination of one or more types.
vstack(blocks[, format, dtype])	Stack sparse matrices vertically (row wise)
warn(message[, category, stacklevel])	Issue a warning, or maybe ignore it or raise an exception.

Classes

bsr_matrix(arg1[, shape, dtype, copy, blocksize])	Block Sparse Row matrix
coo_matrix(arg1[, shape, dtype, copy])	A sparse matrix in COOrdinate format.
csc_matrix(arg1[, shape, dtype, copy])	Compressed Sparse Column matrix
csr_matrix(arg1[, shape, dtype, copy])	Compressed Sparse Row matrix
dia_matrix(arg1[, shape, dtype, copy])	Sparse matrix with DIAgonal storage
lil_matrix(arg1[, shape, dtype, copy])	Row-based linked list sparse matrix