def test_sti_value_error_gender():
sig = Signal(np.zeros((1, 31072)), 44100)
sig.time[0] = 1
with pytest.raises(ValueError,
match="Gender is 'generic' but must be "
"'male' or 'female'."):
sti.sti(sig, gender="generic")
def test_sti_warn_data_type_unknown():
sig = Signal(np.zeros((1, 31072)), 44100)
sig.time[0] = 1
with pytest.raises(ValueError,
match="Data_type is 'generic' but must "
"be 'electrical' or 'acoustical'."):
sti.sti(sig, data_type="generic")
def test_sti_warn_data_type_not_given():
sig = Signal(np.zeros((1, 31072)), 44100)
sig.time[0] = 1
with pytest.warns(UserWarning,
match="Data type is considered as "
"acoustical. Consideration of masking effects not valid "
"for electrically obtained signals."):
sti.sti(sig)
def test_sti_value_error_level():
sig = Signal(np.zeros((1, 31072)), 44100)
sig.time[0] = 1
lvl = np.array([30, 30, 30, 30, 30, 30])
with pytest.raises(ValueError,
match="Level consists of wrong number of "
"components."):
sti.sti(sig, level=lvl)
def test_sti_value_error_snr():
sig = Signal(np.zeros((1, 31072)), 44100)
sig.time[0] = 1
sn = np.array([30, 30, 30, 30, 30, 30])
with pytest.raises(ValueError,
match="SNR consists of wrong number of "
"components."):
sti.sti(sig, snr=sn)
def test_sti_warn_snr_low():
sig = Signal(np.zeros((1, 31072)), 44100)
sig.time[0] = 1
lvl = np.array([70, 70, 70, 70, 70, 70, 70])
sn = np.array([10, 30, 30, 30, 30, 30, 30])
with pytest.warns(UserWarning,
match="SNR should be at least 20 dB for "
"every octave band."):
sti.sti(sig, level=lvl, snr=sn)
def test_sti_female():
expected = np.array([0.6116])
sig = Signal(np.zeros((1, 131072)), 44100)
sig.time[0, 0] = 1
sig.time[0, 1000] = 1
sig.time[0, 10000] = 1
array = sti.sti(sig, gender="female")
np.testing.assert_allclose(array, expected, rtol=1e-3, atol=0)
def test_sti_lvl_snr_1D():
expected = np.array([0.8933])
sig = Signal(np.zeros((1, 131072)), 44100)
sig.time[0, 0] = 1
sig.time[0, 1000] = 1
lvl = np.array([70, 70, 70, 70, 70, 70, 70])
sn = np.array([30, 30, 30, 30, 30, 30, 30])
array = sti.sti(sig, level=lvl, snr=sn)
np.testing.assert_allclose(array, expected, rtol=1e-3, atol=0)
def test_sti_2D():
expected = np.ones((2, 2))
sig = Signal(np.zeros((2, 2, 131072)), 44100)
sig.time[0, 0, 0] = 1
sig.time[1, 0, 0] = 1
sig.time[0, 1, 0] = 1
sig.time[1, 1, 0] = 1
array = sti.sti(sig)
np.testing.assert_allclose(array, expected, rtol=1e-2, atol=0)
def test_sti_amb_false():
expected = np.array([0.8864])
sig = Signal(np.zeros((1, 131072)), 44100)
sig.time[0, 0] = 1
sig.time[0, 1000] = 1
lvl = np.array([70, 70, 70, 70, 70, 70, 70])
sn = np.array([20, 20, 20, 20, 20, 20, 20])
array = sti.sti(sig, level=lvl, snr=sn, amb=False)
np.testing.assert_allclose(array, expected, rtol=1e-3, atol=0)
def test_sti_lvl_snr_2D():
expected = np.array([0.8934, 0.8888])
sig = Signal(np.zeros((2, 131072)), 44100)
sig.time[:, 0] = 1
sig.time[:, 1000] = 1
lvl = np.array([[70, 70, 70, 70, 70, 70, 70], [80, 70, 60, 50, 40, 50,
60]])
sn = np.array([[30, 30, 30, 30, 30, 30, 30], [10, 20, 30, 40, 50, 60, 70]])
array = sti.sti(sig, level=lvl, snr=sn)
np.testing.assert_allclose(array, expected, rtol=1e-3, atol=0)
def test_sti_warn_length():
sig = Signal(np.zeros((1, 31072)), 44100)
sig.time[0] = 1
with pytest.warns(UserWarning, match="Signal length below 1.6 seconds."):
sti.sti(sig)
