adelie.adelie_core.matrix.MatrixCovSparse32F#

class adelie.adelie_core.matrix.MatrixCovSparse32F#

Core matrix class for covariance sparse matrix.

Methods

`__init__`(self, rows, cols, nnz, outer, ...)
`bmul`(self, arg0, arg1, arg2, arg3)	Computes a block matrix-sparse vector multiplication.
`cols`(self)	Returns the number of columns.
`mul`(self, arg0, arg1, arg2)	Computes a matrix-sparse vector multiplication.
`rows`(self)	Returns the number of rows.
`to_dense`(self, arg0, arg1, arg2)	Converts a block to a dense matrix.

Attributes

`ndim`	Number of dimensions.
`shape`	Shape of the matrix.

__init__(self: adelie.adelie_core.matrix.MatrixCovSparse32F, rows: int, cols: int, nnz: int, outer: numpy.ndarray[numpy.int32[1, n]], inner: numpy.ndarray[numpy.int32[1, n]], value: numpy.ndarray[numpy.float32[1, n]], n_threads: int) → None#

bmul(self: adelie.adelie_core.matrix.MatrixCovBase32, arg0: numpy.ndarray[numpy.int64[1, n]], arg1: numpy.ndarray[numpy.int64[1, n]], arg2: numpy.ndarray[numpy.float32[1, n]], arg3: numpy.ndarray[numpy.float32[1, n], flags.writeable]) → None#

Computes a block matrix-sparse vector multiplication.

Computes the matrix-sparse vector multiplication v.T @ A[:, subset] where v is represented by the sparse-format indices and values.

Parameters:

subset(s,) ndarray: Vector of column indices of A to subset in increasing order.
indices(nnz,) ndarray: Vector of indices in increasing order.
values(nnz,) ndarray: Vector of values associated with indices.
out(s,) ndarray: Vector to store the result.

cols(self: adelie.adelie_core.matrix.MatrixCovBase32) → int#: Returns the number of columns.

mul(self: adelie.adelie_core.matrix.MatrixCovBase32, arg0: numpy.ndarray[numpy.int64[1, n]], arg1: numpy.ndarray[numpy.float32[1, n]], arg2: numpy.ndarray[numpy.float32[1, n], flags.writeable]) → None#

Computes a matrix-sparse vector multiplication.

Computes the matrix-sparse vector multiplication v.T @ A where v is represented by the sparse-format indices and values.

Parameters:

indices(nnz,) ndarray: Vector of indices in increasing order.
values(nnz,) ndarray: Vector of values associated with indices.
out(n,) ndarray: Vector to store in-place the result.

rows(self: adelie.adelie_core.matrix.MatrixCovBase32) → int#: Returns the number of rows.

to_dense(self: adelie.adelie_core.matrix.MatrixCovBase32, arg0: int, arg1: int, arg2: numpy.ndarray[numpy.float32[m, n], flags.writeable, flags.f_contiguous]) → None#

Converts a block to a dense matrix.

Converts the block A[i:i+p, i:i+p] into a dense matrix.

Parameters:

iint: Row index.
pint: Number of rows.
out(p, p) ndarray: Matrix to store the dense result.

ndim#: Number of dimensions. It is always 2.

shape#: Shape of the matrix.