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# Authors: The MNE-Python contributors.
# License: BSD-3-Clause
# Copyright the MNE-Python contributors.
import numpy as np
import pytest
from numpy.testing import assert_almost_equal, assert_array_almost_equal
from scipy import linalg
from mne.time_frequency import istft, stft, stftfreq
from mne.time_frequency._stft import stft_norm2
@pytest.mark.parametrize("T", (127, 128, 255, 256, 1337))
@pytest.mark.parametrize("wsize", (128, 256))
@pytest.mark.parametrize("tstep", (4, 64))
@pytest.mark.parametrize("f", (7.0, 23.0)) # should be close to fftfreqs
def test_stft(T, wsize, tstep, f):
"""Test stft and istft tight frame property."""
sfreq = 1000.0 # Hz
# Test with low frequency signal
t = np.arange(T).astype(np.float64)
x = np.sin(2 * np.pi * f * t / sfreq)
x = np.array([x, x + 1.0])
X = stft(x, wsize, tstep)
xp = istft(X, tstep, Tx=T)
freqs = stftfreq(wsize, sfreq=sfreq)
max_freq = freqs[np.argmax(np.sum(np.abs(X[0]) ** 2, axis=1))]
assert X.shape[1] == len(freqs)
assert np.all(freqs >= 0.0)
assert np.abs(max_freq - f) < 1.0
assert_array_almost_equal(x, xp, decimal=6)
# norm conservation thanks to tight frame property
assert_almost_equal(
np.sqrt(stft_norm2(X)), [linalg.norm(xx) for xx in x], decimal=6
)
# Test with random signal
x = np.random.randn(2, T)
wsize = 16
tstep = 8
X = stft(x, wsize, tstep)
xp = istft(X, tstep, Tx=T)
freqs = stftfreq(wsize, sfreq=1000)
max_freq = freqs[np.argmax(np.sum(np.abs(X[0]) ** 2, axis=1))]
assert X.shape[1] == len(freqs)
assert np.all(freqs >= 0.0)
assert_array_almost_equal(x, xp, decimal=6)
# norm conservation thanks to tight frame property
assert_almost_equal(
np.sqrt(stft_norm2(X)), [linalg.norm(xx) for xx in x], decimal=6
)
# Try with empty array
x = np.zeros((0, T))
X = stft(x, wsize, tstep)
xp = istft(X, tstep, T)
assert xp.shape == x.shape
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