lacuna.sparse.coo

Classes

COO(row, col, data, shape[, dtype, check])

Coordinate (COO) sparse matrix.

class lacuna.sparse.coo.COO(row, col, data, shape, dtype=<class 'numpy.float64'>, check=True)

Bases: SparseArray

Coordinate (COO) sparse matrix.

Parameters:

• row (array_like of int64) – Row indices for nonzero entries, length nnz.

• col (array_like of int64) – Column indices for nonzero entries, length nnz.

• data (array_like of float64) – Nonzero values, length nnz.

• shape (tuple of int) – Matrix shape (nrows, ncols).

• dtype (numpy.dtype, optional) – Value dtype, defaults to np.float64.

• check (bool, optional) – If True, validate invariants in the native layer (may be slower).

row, col, data

Storage arrays for indices and values.

Type:

numpy.ndarray

shape

Matrix dimensions.

Type:

tuple[int, int]

dtype

Value dtype.

Type:

numpy.dtype

nnz

Number of stored elements (with duplicates allowed).

Type:

int

Notes

Backed by Rust kernels through lacuna._core.Coo64; operations release the GIL.

Examples

Construct a small COO and run basic ops:

>>> import numpy as np
>>> from lacuna.sparse import COO
>>> row = np.array([0, 1, 1])
>>> col = np.array([0, 0, 2])
>>> val = np.array([1.0, 2.0, 3.0])
>>> a = COO(row, col, val, shape=(2, 3))
>>> a.nnz
3
>>> (a @ np.array([1.0, 0.0, 1.0])).tolist()  # SpMV
[1.0, 3.0]
>>> a.sum()
6.0

property T

eliminate_zeros()

Remove explicit zeros. Returns a new COO.

classmethod from_arrays(row, col, data, shape, check=True)

Construct from index/value arrays.

Parameters:

• row (array_like) – Coordinate indices and values.

• col (array_like) – Coordinate indices and values.

• data (array_like) – Coordinate indices and values.

• shape (tuple[int, int]) – Matrix shape.

• check (bool, optional) – Validate invariants in the native layer.

property nnz

Number of stored values (including duplicates).

prune(eps)

Drop entries with abs(value) <= eps.

Returns a new COO.

sum(axis=None)

Sum of entries.

Parameters:

axis ({None, 0, 1}, optional) – None for global sum; 0 for column sums; 1 for row sums.

toarray()

Convert to a dense NumPy ndarray of shape (nrows, ncols).