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# -*- 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 dgtreal calculation
Ported from ltfat_2.1.0/gabor/dgtreal.m
.. moduleauthor:: Denis Arrivault
"""
from __future__ import print_function, division
import numpy as np
from ltfatpy.comp.gabpars_from_windowsignal import gabpars_from_windowsignal
from ltfatpy.comp.comp_sepdgtreal import comp_sepdgtreal
def dgtreal(f, g, a, M, L=None, pt='freqinv'):
"""Discrete Gabor transform for real signals
- Usage:
| ``(c, Ls, g) = dgtreal(f, g, a, M)``
| ``(c, Ls, g) = dgtreal(f, g, a, M, L)``
| ``(c, Ls, g) = dgtreal(f, g, a, M, L, pt)``
- Input parameters:
:param numpy.ndarray f: Input data. **f** dtype should be float64
:param g: Window function.
:param int a: Length of time shift.
:param int M: Number of modulations.
:param int L: Length of transform to do. Default is None.
:param str pt: 'freqinv' or 'timeinv'. Default is 'freqinv'.
:type g: str, dict or numpy.ndarray of float64
- Output parameters:
:returns: ``(c, Ls, g)``
:rtype: tuple
:var numpy.ndarray c: :math:`M*N` array of complex128 coefficients.
:var int Ls: length of input signal
:var numpy.ndarray g: updated window function. dtype is float64.
``dgtreal(f, g, a, M)`` computes the Gabor coefficients (also known as a
windowed Fourier transform) of the real-valued input signal **f** with
respect to the real-valued window **g** and parameters **a** and **M**.
The output is a vector/matrix in a rectangular layout.
As opposed to :func:`~ltfatpy.gabor.dgt.dgt` only the coefficients of the
positive frequencies of the output are returned. ``dgtreal`` will refuse
to work for complex valued input signals.
The length of the transform will be the smallest multiple of **a** and
**M** that is larger than the signal. **f** will be zero-extended to the
length of the transform. If **f** is a matrix, the transformation is
applied to each column. The length of the transform done can be obtained
by ``L = c.shape[1] * a``.
The window **g** may be a vector of numerical values, a text string or a
dictionary. See the help of :py:meth:`~ltfatpy.gabor.gabwin` for more
details.
``dgtreal(f, g, a, M, L)`` computes the Gabor coefficients as above, but
does a transform of length **L**. **f** will be cut or zero-extended to
length **L** before the transform is done.
The ``dgtreal`` function returns the length of the input signal **f**.
This is handy for reconstruction:
>>> (c, Ls, g) = dgtreal(f, g, a, M) # doctest: +SKIP
>>> fr = idgtreal(c, gd, a, M, Ls) # doctest: +SKIP
will reconstruct the signal **f** no matter what the length of **f** is,
provided that **gd** is a dual window of **g**.
It also outputs the window used in the transform. This is useful if the
window was generated from a description in a string or dictionary.
See the help on :func:`~ltfatpy.gabor.dgt.dgt` for the definition of the
discrete Gabor transform. This routine will return the coefficients for
channel frequencies from 0 to ``floor(M/2)``.
``dgtreal`` optionnaly takes a **pt** argument:
'freqinv'
Compute a ``dgtreal`` using a frequency-invariant phase. This
is the default convention described in the help for
:func:`~ltfatpy.gabor.dgt.dgt`.
'timeinv'
Compute a ``dgtreal`` using a time-invariant phase. This
convention is typically used in filter bank algorithms.
``dgtreal`` can be used to manually compute a spectrogram, if you
want full control over the parameters and want to capture the output.
- Example:
>>> import matplotlib.pyplot as plt
>>> from ltfatpy import greasy
>>> (f,fs) = greasy() # Input test signal
>>> a = 10 # Downsampling factor in time
>>> M = 200 # Total number of channels, only 101 will be computed
>>> # Compute the coefficients using a 20 ms long Hann window
>>> c = dgtreal(f, {'name' : 'hann', 'M' : 0.02*fs}, a, M)[0]
>>> # Visualize the coefficients as a spectrogram
>>> dynrange = 90 # 90 dB dynamical range for the plotting
>>> from ltfatpy import plotdgtreal
>>> coef = plotdgtreal(c, a, M, fs=fs, dynrange=dynrange)
>>> plt.show()
.. image:: images/dgtreal.png
:width: 700px
:alt: spectrogram image
:align: center
.. seealso:: :func:`~ltfatpy.gabor.dgt.dgt`,
:func:`~ltfatpy.gabor.idgtreal.idgtreal`,
:func:`~ltfatpy.gabor.gabwin.gabwin`, :func:`dwilt`,
:func:`~ltfatpy.gabor.gabtight.gabtight`,
:func:`~ltfatpy.gabor.plotdgtreal.plotdgtreal`
- References:
:cite:`fest98,gr01`
"""
(f, gnum, _, Ls) = gabpars_from_windowsignal(f, g, a, M, L)[0:4]
if not np.issubdtype(gnum.dtype, np.floating):
raise ValueError('The window must be real-valued.')
# verify pt
if pt == 'timeinv':
pt = 1
elif pt == 'freqinv':
pt = 0
else:
raise ValueError("pt argument should be 'timeinv' or 'freqinv'.")
c = comp_sepdgtreal(f, gnum, a, M, pt)
return (c, Ls, gnum)
if __name__ == '__main__': # pragma: no cover
import doctest
doctest.testmod()
|
