Utilities¶
-
micarray.util.
norm_of_columns
(A, p=2)[source]¶ 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)[source]¶ 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)[source]¶ 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.