aspen.processings.normalize

Normalize

Functions

normalize(x[, method])

Nomarlize a signal.

Classes

Normalize([normalize_method])

Nomarlize a signal.

class aspen.processings.normalize.Normalize(normalize_method='zscore')

Bases: aspen.interfaces.abs_common_interface.AbsCommonInterface, aspen.interfaces.abs_processing_interface.AbsProcessingInterface

Nomarlize a signal.

Parameters

normalize_method (str) – Type of normalization method. zscore provide the mean (centre) of the distribution = 0 and standard deviation (spread or “width”) of the distribution = 1. Defaults to “zscore”.

Todo

Implementation of other method if necessary. REF(https://www.mathworks.com/help/matlab/ref/double.normalize.html)

__call__(x)

Apply normalization

Parameters

x (ndarray) – Input signal

Return type

ndarray

Returns

Output signal

static add_arguments(parser)

add arguments

classmethod load_class_kwargs(args)

Return the kwargs dict for class __init__ from parsed arguments

Parameters

args (Namespace) – (config)argparse arguments

Return type

dict

Returns

kwargs for class __init__

aspen.processings.normalize.normalize(x, method='zscore')

Nomarlize a signal.

Parameters

• x (ndarray) – Input signal.

• method (str) – Type of normalization method. zscore provide the mean (centre) of the distribution = 0 and standard deviation (spread or “width”) of the distribution = 1. Defaults to “zscore”.

Return type

ndarray

Returns

Output signal.

aspen.processings.modulation_power_spectrum aspen.visualizations