def test_zeros(self):
sample_rate = 2000
times = np.linspace(-0.5, 0.5, sample_rate)
freqs = 0.0 * times
expected = np.array([
0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0
])
actual = utils.get_contour_shape_features(times, freqs, sample_rate)
self.assertTrue(array_equal(expected, actual))
def test_line_with_vib(self):
sample_rate = 2000
times = np.linspace(-0.5, 0.5, sample_rate)
freqs = (
(1.2 * times + 440.0) + 7.3 * np.cos(2.0 * np.pi * 12.0 * times)
)
expected = np.array([
12.0, 7.296015, 1.0, 1.0, 1.0, 1.0,
440.139861, 1.2, -6.77396486e+00, 3.49420344e-12,
3.42394991e+01, -1.48802985e-11,
1.15390225e-01, 3.77435044e-03
])
actual = utils.get_contour_shape_features(times, freqs, sample_rate)
print(expected)
print(actual)
self.assertTrue(array_equal(expected, actual))
def get_feature_vector(self, times, freqs_hz, salience, sample_rate):
"""Get feature vector for a contour.
Parameters
----------
times : np.array
Contour times
freqs_hz : np.array
Contour frequencies (Hz)
salience : np.array
Contour salience
sample_rate : float
Contour sample rate.
Returns
-------
feature_vector : np.array
Feature vector.
"""
freqs_cents = utils.hz_to_cents(freqs_hz, ref_hz=self.ref_hz)
features = [
utils.get_contour_shape_features(
times,
freqs_cents,
sample_rate,
poly_degree=self.poly_degree,
min_freq=self.min_freq,
max_freq=self.max_freq,
freq_step=self.freq_step,
vibrato_threshold=self.vibrato_threshold),
utils.get_polynomial_fit_features(times - np.mean(times),
salience,
n_deg=self.poly_degree,
norm=False),
utils.get_contour_duration(times),
utils.get_std(freqs_cents),
utils.get_range(freqs_cents),
utils.get_total_variation(freqs_cents) / len(freqs_cents),
utils.get_std(salience),
utils.get_range(salience),
utils.get_total_variation(salience) / len(freqs_cents)
]
return np.concatenate(features)