Utilities

Utilities contains a number of frequently used functions.

padvinder.util.normalize(array)

Returns a normalized version of the provided array.

Parameters:

array (numpy.ndarray_like) – The array to be normalized. Afterwards np.linalg.norm(normalize(array)) is approximately equal to 1.

Returns:

normalized array – the array normalized to unit length: np.linalg.norm(normalize(array)) ~= 1.

Return type:

numpy.ndarray_like

Raises:

• ValueError – if the input array contains Inf’s or Nan’s
• ZeroDivisionError – if the length of the provided array has length ofzero the division will cause a ZeroDivisionError to be raised

Examples

>>> normalize([1, 0, 0])
[1.0, 0.0, 0.0]
>>> normalize([2, 4, 4])
[0.33333333, 0.66666667, 0.66666667]
>>> normalize(np.array((3,4,5)))
[0.42426407, 0.56568542, 0.70710678]
### np.linalg.norm(normalize((x, y, z))) ~= 1

padvinder.util.check_finite(*args)

Validate the input parameters and raise ValueErrors if any contains incompatible values (Infs or NaNs) are present.

Parameters:args (numpy.ndarray_like) – a list of lists or arrays Raises:ValueError – if any passed in element is Inf or NaN.