freealg.submatrix

freealg.submatrix(matrix, size, block_size=None, paired=True, haar=False, seed=None)

Randomly sample a submatrix from a larger matrix.

Parameters:

matrixnumpy.ndarray

A 2D square array

sizeint

Number of rows and columns of the output submatrix.

block_sizeint, default=None

If given, sampling is performed at the block level where contiguous blocks of size block_size are selected and preserved. The output size should be an integer multiple of block_size.

pairedbool, default=True

If True, the rows and columns are sampled with the same random indices. If False, separate random indices are used for selecting rows and columns.

haarbool, default=False

If True, apply a random orthogonal conjugation to the input matrix before sampling, using a Haar-distributed orthogonal matrix. Note that this can significantly increase the runtime for large matrices.

seedint, default=None

Seed for random number generation. If None, results will not be reproducible.

Returns:

subnumpy.ndarray

A 2D array with the number of rows/columns specified by size.

See also

freealg.sample

Examples

>>> import numpy
>>> from freealg import submatrix

>>> A = numpy.random.randn(1000, 1000)
>>> B = submatrix(A, size=500, paired=True, seed=0)