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dsdbcoo#

Includes the distributed block-accessible COO matrix data structure.

Classes:

  • DSDBCOO –

    A Distributed Stack of Distributed Block-accessible COO matrices.

DSDBCOO #

DSDBCOO(dtype: dtype[generic], rows: NDArray, cols: NDArray, block_sizes: NDArray, local_stack_shape: tuple | int, global_stack_shape: tuple | int, symmetry: str | None = None)

Bases: DSDBSparse

A Distributed Stack of Distributed Block-accessible COO matrices.

Note

It is the caller's responsibility to ensure that the data is distributed correctly across the ranks.

Parameters:

  • dtype (dtype[generic]) –

    The data type of the matrix.

  • rows (NDArray) –

    The local row indices of the COO matrix.

  • cols (NDArray) –

    The local column indices of the COO matrix.

  • block_sizes (NDArray) –

    The size of each block in the sparse matrix.

  • local_stack_shape (tuple or int) –

    The local shape of the stack. If this is an integer, it is interpreted as a one-dimensional stack.

  • global_stack_shape (tuple or int) –

    The global shape of the stack. If this is an integer, it is interpreted as a one-dimensional stack.

  • symmetry (str | None, default: None ) –

    The symmetry of the matrix. This can be "symmetric", "hermitian", "skew-symmetric", "skew-hermitian", or None. Default is None.

Methods:

  • block_sizes –

    Sets new block sizes for the matrix.

  • spy –

    Returns the row and column indices of the non-zero elements.

  • symmetrize –

    Symmetrizes the matrix with a given symmetry.

  • empty_like –

    Creates a new DSDBCOO matrix with the same shape and

  • from_sparray –

    Constructs a DSDBCOO matrix from a sparse matrix.

  • to_dense –

    Converts the local data to a dense array.

block_sizes #

block_sizes(block_sizes: NDArray) -> None

Sets new block sizes for the matrix.

Parameters:

  • block_sizes (NDArray) –

    The new block sizes.

spy #

spy() -> tuple[NDArray, NDArray]

Returns the row and column indices of the non-zero elements.

This is essentially the same as converting the sparsity pattern to coordinate format. The returned sparsity pattern is not sorted.

Note

In the block distributed case, this returns the local sparsity pattern.

Returns:

  • rows ( NDArray ) –

    Row indices of the non-zero elements.

  • cols ( NDArray ) –

    Column indices of the non-zero elements.

symmetrize #

symmetrize(symmetry: str) -> None

Symmetrizes the matrix with a given symmetry.

Note

This assumes that the matrix's sparsity pattern is symmetric.

Parameters:

  • symmetry (str) –

    The symmetry to enforce. This can be "symmetric", "hermitian", "skew-symmetric", or "skew-hermitian".

empty_like classmethod #

empty_like(dsdbsparse: DSDBCOO) -> DSDBCOO

Creates a new DSDBCOO matrix with the same shape and dtype.

Note

There is no data allocated in the new matrix. The sparsity pattern is the same as the original matrix.

Parameters:

  • dsdbsparse (DSDBCOO) –

    The matrix to copy the shape and dtype from.

Returns:

  • DSDBCOO –

    The new DSDBCOO matrix.

from_sparray classmethod #

from_sparray(sparray: spmatrix, block_sizes: NDArray, global_stack_shape: tuple, symmetry: str | None = None, dtype: dtype[generic] = complex128, allocate: bool = True) -> DSDBCOO

Constructs a DSDBCOO matrix from a sparse matrix.

This essentially distributed the matrix across the stack and block communicators.

Parameters:

  • sparray (spmatrix) –

    The sparse matrix from which to use the sparsity pattern.

  • block_sizes (NDArray) –

    The block sizes of the block-sparse matrix.

  • global_stack_shape (tuple) –

    The global shape of the stack.

  • symmetry (str | None, default: None ) –

    The symmetry of the matrix. This can be "symmetric", "hermitian", "skew-symmetric", "skew-hermitian", or None. Default is None.

  • dtype (dtype, default: complex128 ) –

    The data type of the matrix. Default is xp.complex128.

  • allocate (bool, default: True ) –

    Whether to allocate the data of the resulting matrix. Default is True.

Returns:

  • DSDBCOO –

    The new DSDBCOO matrix.

to_dense #

to_dense()

Converts the local data to a dense array.

This is dumb, unless used for testing and debugging.

Warning

This creates a very large dense matrix.

Returns:

  • arr ( NDArray ) –

    The dense array of shape (*local_stack_shape, *shape).