# -*- coding: utf-8 -*-
# ######### COPYRIGHT #########
# Credits
# #######
#
# Copyright(c) 2015-2018
# ----------------------
#
# * `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) 2005-2018 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 = 1.0.16
# * 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 symmetrical zero-extension or cut of data
Ported from ltfat_2.1.0/fourier/middlepad.m
.. moduleauthor:: Florent Jaillet
"""
from __future__ import print_function, division
import six
import numpy as np
from ltfatpy.comp.assert_sigreshape_pre import assert_sigreshape_pre
from ltfatpy.comp.assert_sigreshape_post import assert_sigreshape_post
[docs]def middlepad(f, L, dim=None, centering='wp'):
"""Symmetrically zero-extends or cuts a function
- Usage:
| ``h = middlepad(f, L)``
| ``h = middlepad(f, L, dim)``
| ``h = middlepad(f, L, ...)``
- Input parameters:
:param numpy.ndarray f: Input array
:param int L: Length of the output array
:param int dim: Axis over which to zero-extend or cut **f**
:param str centering: Flag specifying if **f** is whole point even when
``centering='wp'`` or half point even when ``centering='hp'``
- Output parameters:
:returns: Zero-extended or cut array
:rtype: numpy.ndarray
``middlepad(f, L)`` zero-extends or cuts **f** to length **L** by
inserting zeros in the middle of the vector, or by cutting in the middle
of the vector.
If **f** is whole-point even, ``middlepad(f, L)`` will also be
whole-point even.
``middlepad(f, L, dim)`` does the same along dimension **dim**.
If **f** has even length, then **f** will not be purely zero-extended,
but the last element will be repeated once and multiplied by ``1/2``.
That is, the support of **f** will increase by one!
Adding the flag ``centering='wp'`` will cut or extend whole point even
functions (the default). Adding ``centering='hp'`` will do the same for
half point even functions.
.. seealso:: :func:`~ltfatpy.fourier.isevenfunction.isevenfunction`,
:func:`~ltfatpy.sigproc.fir2long.fir2long`,
:func:`~ltfatpy.fourier.fftresample.fftresample`
"""
# Note: For a future improvement, it might be possible to replace the use
# of numpy.concatenate with numpy.r_ in this function to simplify the code.
if not isinstance(L, six.integer_types):
raise TypeError('L must be an integer.')
if L < 1:
raise ValueError('L must be larger than 0.')
f, L, Ls, W, dim, permutedsize, order = assert_sigreshape_pre(f, L, dim)
Lorig = Ls
# Skip the main section if there is nothing to do. This is necessary
# because some of the code below cannot handle the case of 'nothing to do'
if L != Ls:
if centering == 'wp':
# --------------- WPE case --------------------------------------
if Lorig == 1:
# Rather trivial case
h = np.concatenate((f[np.newaxis, 0, :],
np.zeros((L-1, W), dtype=f.dtype)))
else:
if Lorig > L:
# Cut
if L % 2 == 0:
# L even. Use average of endpoints.
h = np.concatenate((f[:L//2, :],
(f[np.newaxis, L//2, :] +
f[np.newaxis, Lorig-L//2, :]) / 2,
f[Lorig-L//2+1:Lorig, :]))
else:
# No problem, just cut.
h = np.concatenate((f[:(L+1)//2, :],
f[Lorig-(L-1)//2:Lorig, :]))
else:
d = L - Lorig
# Extend
if Lorig % 2 == 0:
# Lorig even. We must split a value.
h = np.concatenate((f[:Lorig//2, :],
f[np.newaxis, Lorig//2, :]/2,
np.zeros((d-1, W), dtype=f.dtype),
f[np.newaxis, Lorig//2, :]/2,
f[Lorig//2+1:Lorig, :]))
else:
# Lorig is odd, we can just insert zeros.
h = np.concatenate((f[:(Lorig+1)//2, :],
np.zeros((d, W), dtype=f.dtype),
f[(Lorig+1)//2:Lorig, :]))
elif centering == 'hp':
# ------------------ HPE case ------------------------------------
# NOTE: There is a bug here in LTFAT 2.1.0 for Octave, see:
# https://sourceforge.net/p/ltfat/bugs/123
# This bug arise because the case "if Lorig==1" hasn't been
# implemented in the Octave code when centering = 'hp'.
# To solve this bug, we simply remove the test "if Lorig==1", which
# seems to lead to satisfactory results.
if Lorig > L:
d = Lorig-L
# Cut
if L % 2 == 0:
# L even
# No problem, just cut.
h = np.concatenate((f[:L//2, :], f[Lorig-L//2:Lorig, :]))
else:
# Average of endpoints.
h = np.concatenate((f[:(L-1)//2, :],
(f[np.newaxis, (L-1)//2, :] +
f[np.newaxis, Lorig-(L+1)//2, :]) / 2,
f[Lorig-(L-1)//2:Lorig, :]))
else:
d = L-Lorig
# Extend
if Lorig % 2 == 0:
# Lorig even. We can just insert zeros in the middle.
h = np.concatenate((f[:Lorig//2, :],
np.zeros((d, W), dtype=f.dtype),
f[Lorig//2:Lorig, :]))
else:
# Lorig odd. We need to split a value in two
h = np.concatenate((f[:(Lorig-1)//2, :],
f[np.newaxis, (Lorig-1)//2, :]/2,
np.zeros((d-1, W), f.dtype),
f[np.newaxis, (Lorig-1)//2, :]/2,
f[(Lorig+1)//2:Lorig, :]))
else:
# we don't want this function to return a reference or a view to the
# input, so we make a copy
h = f.copy()
h = assert_sigreshape_post(h, dim, permutedsize, order)
return h