Function compression_level

dask/array/linalg.py:624–654

Compression level to use in svd_compressed Given the size ``n`` of a space, compress that that to one of size ``q`` plus n_oversamples. The oversampling allows for greater flexibility in finding an appropriate subspace, a low value is often enough (10 is already a very conserva

(n, q, n_oversamples=10, min_subspace_size=20)

def compression_level(n, q, n_oversamples=10, min_subspace_size=20):
    """Compression level to use in svd_compressed

    Given the size ``n`` of a space, compress that that to one of size
    ``q`` plus n_oversamples.

    The oversampling allows for greater flexibility in finding an
    appropriate subspace, a low value is often enough (10 is already a
    very conservative choice, it can be further reduced).
    ``q + oversampling`` should not be larger than ``n``.  In this
    specific implementation, ``q + n_oversamples`` is at least
    ``min_subspace_size``.

    Parameters
    ----------
    n: int
        Column/row dimension of original matrix
    q: int
        Size of the desired subspace (the actual size will be bigger,
        because of oversampling, see ``da.linalg.compression_level``)
    n_oversamples: int, default=10
        Number of oversamples used for generating the sampling matrix.
    min_subspace_size : int, default=20
        Minimum subspace size.

     Examples
    --------
    >>> compression_level(100, 10)
    20
    """
    return min(max(min_subspace_size, q + n_oversamples), n)


def compression_matrix(