Utilities

micarray.util.norm_of_columns(A, p=2)

Vector p-norm of each column of a matrix.

Parameters:

• A (array_like) – Input matrix.
• p (int, optional) – p-th norm.

Returns:

array_like – p-norm of each column of A.

micarray.util.coherence_of_columns(A)

Mutual coherence of columns of A.

Parameters:

• A (array_like) – Input matrix.
• p (int, optional) – p-th norm.

Returns:

array_like – Mutual coherence of columns of A.

micarray.util.asarray_1d(a, **kwargs)

Squeeze the input and check if the result is one-dimensional.

Returns a converted to a numpy.ndarray and stripped of all singleton dimensions. Scalars are “upgraded” to 1D arrays. The result must have exactly one dimension. If not, an error is raised.