# 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
