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qttools.datastructures.dsdbcoo#

source module qttools.datastructures.dsdbcoo

Classes

  • DSDBCOO — A Distributed Stack of Distributed Block-accessible COO matrices.

source class DSDBCOO(data: NDArray, rows: NDArray, cols: NDArray, block_sizes: NDArray, global_stack_shape: tuple, return_dense: bool = True, symmetry: bool | None = False, symmetry_op: Callable = xp.conj)

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.

Initializes a DSDBCOO matrix.

Parameters

  • data : NDArray — The local slice of the data. This should be an array of shape (*local_stack_shape, local_nnz).

  • 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.

  • 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.

  • return_dense : bool, optional — Whether to return dense arrays when accessing the blocks. Default is True.

  • symmetry : bool, optional — Whether the matrix is symmetric. Default is False.

  • symmetry_op : callable, optional — The operation to use for the symmetry. Default is xp.conj.

Attributes

  • block_offsets : ArrayLike — Returns the block sizes.

  • blocks : _DSDBlockIndexer — Returns a block indexer.

  • sparse_blocks : _DSDBlockIndexer — Returns a block indexer.

  • stack : _DStackIndexer — Returns a stack indexer.

  • data : NDArray — Returns the local slice of the data, masking the padding.

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 operation.

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

  • from_sparray — Constructs a DSDBCOO matrix from a COO matrix.

  • to_dense — Converts the local data to a dense array.

source method DSDBCOO.block_sizes(block_sizes: NDArray) → None

Sets new block sizes for the matrix.

Parameters

  • block_sizes : NDArray — The new block sizes.

Raises

  • NotImplementedError

  • ValueError

source method DSDBCOO.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.

Returns

  • rows : NDArray — Row indices of the non-zero elements.

  • cols : NDArray — Column indices of the non-zero elements.

source method DSDBCOO.symmetrize(op: Callable[[NDArray, NDArray], NDArray] = xp.add) → None

Symmetrizes the matrix with a given operation.

This is done by setting the data to the result of the operation applied to the data and its conjugate transpose.

Note

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

Parameters

  • op : callable, optional — The operation to apply to the data and its conjugate transpose. Default is xp.add, so that the matrix is Hermitian after calling.

Raises

  • NotImplementedError

source classmethod DSDBCOO.zeros_like(dsdbsparse: DSDBCOO) → DSDBCOO

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

All non-zero elements are set to zero, but the sparsity pattern is preserved.

Parameters

  • dsdbcoo : DSDBCOO — The matrix to copy the shape and dtype from.

Returns

  • dsdbcoo — The new DSDBCOO matrix.

Raises

  • ValueError

source classmethod DSDBCOO.from_sparray(sparray: sparse.spmatrix, block_sizes: NDArray, global_stack_shape: tuple, symmetry: bool | None = False, symmetry_op: Callable = xp.conj) → DSDBCOO

Constructs a DSDBCOO matrix from a COO matrix.

This essentially distributes the COO matrix across the participating ranks.

Parameters

  • sparray : sparse.coo_matrix — The COO matrix to distribute.

  • block_sizes : NDArray — The block sizes of the block-sparse matrix.

  • global_stack_shape : tuple — The global shape of the stack.

  • symmetry : bool, optional — Whether to enforce symmetry in the matrix. Default is False.

  • symmetry_op : callable, optional — The operation to use for the symmetry. Default is xp.conj.

Returns

  • DSDBCOO — The new DSDBCOO matrix.

Raises

  • ValueError

source method DSDBCOO.to_dense()

Converts the local data to a dense array.

This is dumb, unless used for testing and debugging.

Returns

  • arr : NDArray — The dense array of shape (*local_stack_shape, *shape).

Raises

  • ValueError