1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
|
# -*- coding: utf-8 -*-
# ######### COPYRIGHT #########
# Credits
# #######
#
# Copyright(c) 2015-2025
# ----------------------
#
# * `LabEx Archimède <http://labex-archimede.univ-amu.fr/>`_
# * `Laboratoire d'Informatique Fondamentale <http://www.lif.univ-mrs.fr/>`_
# (now `Laboratoire d'Informatique et Systèmes <http://www.lis-lab.fr/>`_)
# * `Institut de Mathématiques de Marseille <http://www.i2m.univ-amu.fr/>`_
# * `Université d'Aix-Marseille <http://www.univ-amu.fr/>`_
#
# This software is a port from LTFAT 2.1.0 :
# Copyright (C) 2005-2025 Peter L. Soendergaard <peter@sonderport.dk>.
#
# Contributors
# ------------
#
# * Denis Arrivault <contact.dev_AT_lis-lab.fr>
# * Florent Jaillet <contact.dev_AT_lis-lab.fr>
#
# Description
# -----------
#
# ltfatpy is a partial Python port of the
# `Large Time/Frequency Analysis Toolbox <http://ltfat.sourceforge.net/>`_,
# a MATLAB®/Octave toolbox for working with time-frequency analysis and
# synthesis.
#
# Version
# -------
#
# * ltfatpy version = 1.1.2
# * LTFAT version = 2.1.0
#
# Licence
# -------
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
#
# ######### COPYRIGHT #########
""" Module of signal normalization
Ported from ltfat_2.1.0/sigproc/normalize.m
.. moduleauthor:: Denis Arrivault
"""
from __future__ import print_function, division
import numpy as np
from numpy import linalg as LA
from ltfatpy.comp.assert_sigreshape_pre import assert_sigreshape_pre
from ltfatpy.comp.assert_sigreshape_post import assert_sigreshape_post
from ltfatpy.sigproc.rms import rms
from ltfatpy.gabor.s0norm import s0norm
def normalize(f, norm='2', dim=None):
r"""Normalize input signal by specified norm
- Usage:
| ``(f, fnorm) = normalize(f)``
| ``(f, fnorm) = normalize(f, 'area')``
| ``(f, fnorm) = normalize(f, dim=2)``
| ...
:param numpy.ndarray f: Input signal
:param str norm: Name of the norm to apply
:param int dim: Dimension along which norm is applied (first non-singleton
dimension as default)
- Output parameters:
:return: ``(f, fnorm)``
:rtype: tuple
:var numpy.ndarray f: normalized signal
:var numpy.ndarray fnorm: norm of the signal
``normalize(f,...)`` will normalize the signal **f** by the specified norm.
The norm is specified as a string and may be one of:
============ ==========================================================
``'1'`` Normalize the :math:`l^1` norm to be *1*.
``'area'`` Normalize the area of the signal to be *1*. This is
exactly the same as ``'1'``.
``'2'`` Normalize the :math:`l^2` norm to be *1*. This is the
default
``'energy'`` Normalize the energy of the signal to be *1*. This is
exactly the same as ``'2'``.
``'inf'`` Normalize the :math:`l^{\\inf}` norm to be *1*.
``'peak'`` Normalize the peak value of the signal to be *1*.
This is exactly the same as ``'inf'``.
``'rms'`` Normalize the Root Mean Square (RMS) norm of the signal to
be *1*.
``'s0'`` Normalize the S0-norm to be *1*.
``'wav'`` Normalize to the :math:`l^{inf}` norm to be *0.99* to
avoid possible clipping introduced by the quantization
procedure when saving as a wav file. This only works with
floating point data types.
``'null'`` Do NOT normalize, output is identical to input.
============ ==========================================================
.. seealso::
:func:`~ltfatpy.sigproc.rms.rms`,
:func:`~ltfatpy.gabor.s0norm.s0norm`
"""
if not isinstance(norm, str):
raise TypeError('norm should be string.')
norm = norm.lower()
f = f.copy()
(f, _unused, _unused, W, dim, permutedshape, order) = \
assert_sigreshape_pre(f, dim=dim)
if np.issubdtype(f.dtype, np.integer) and norm == 'wav':
raise TypeError('Integer data types are unsupported for wav norm.')
fnorm = np.zeros((W, ))
for ii in range(W):
if norm == '1' or norm == 'area':
fnorm[ii] = LA.norm(f[:, ii], 1)
f[:, ii] = f[:, ii] / fnorm[ii]
elif norm == '2' or norm == 'energy':
fnorm[ii] = LA.norm(f[:, ii], 2)
f[:, ii] = f[:, ii] / fnorm[ii]
elif norm == 'inf' or norm == 'peak':
fnorm[ii] = LA.norm(f[:, ii], np.inf)
f[:, ii] = f[:, ii] / fnorm[ii]
elif norm == 'rms':
fnorm[ii] = rms(f[:, ii]).item()
f[:, ii] = f[:, ii] / fnorm[ii]
elif norm == 's0':
fnorm[ii] = s0norm(f[:, ii]).item()
f[:, ii] = f[:, ii] / fnorm[ii]
elif norm == 'wav':
if np.issubdtype(f.dtype, np.floating):
fnorm[ii] = LA.norm(f[:, ii], np.inf)
f[:, ii] = 0.99 * f[:, ii] / fnorm[ii]
else:
raise TypeError("TO DO: Normalizing integer data types not"
"supported yet.")
f = assert_sigreshape_post(f, dim, permutedshape, order)
return (f, fnorm)
|
