def test_convolve_compare_with_numpy(self):
signal = [0, -1, -1.2, 2, 1.4, 1.4, 0.8, 0, -0.8]
impulse_response = [1, 0.5, 0.2, 0]
res = convolve(signal, impulse_response)
expected_res = [0.0, -1.0, -1.7, 1.2, 2.16, 2.5, 1.78, 0.68, -0.64, -0.4, -0.16, 0.0]
numpy_res = np.convolve(signal, impulse_response)
npt.assert_array_equal(res, numpy_res)
npt.assert_array_almost_equal(res, expected_res)
def test_distributivity(self):
npt.assert_array_equal(
np.add(convolve(self.signal_1, self.signal_2),
convolve(self.signal_1, self.signal_3)),
convolve(self.signal_1, np.add(self.signal_2, self.signal_3)))
def test_associativity(self):
npt.assert_array_equal(
convolve(self.signal_1, convolve(self.signal_2, self.signal_3)),
convolve(convolve(self.signal_1, self.signal_2), self.signal_3))
def test_commutativity(self):
npt.assert_array_equal(convolve(self.signal_1, self.signal_2),
convolve(self.signal_1, self.signal_2))
def test_convolve_with_echo_function(self):
signal = [1.0, 2.0, 3.0, 4.0, 5.0]
impulse_response = [1, 0, 0, 0.5]
res = [1.0, 2.0, 3.0, 4.5, 6.0, 1.5, 2.0, 2.5]
npt.assert_array_equal(res, convolve(signal, impulse_response))
def test_convolve_with_shift_and_amply_function(self):
signal = [1.0, 2.0, 3.0, 4.0, 5.0]
impulse_response = [0, 0, 3]
res = [0, 0, 3.0, 6.0, 9.0, 12.0, 15.0]
npt.assert_array_equal(res, convolve(signal, impulse_response))
def test_convolve_with_amplifier_function(self):
signal = [1.0, 2.0, 3.0, 4.0, 5.0]
impulse_response = [2, 0, 0]
res = [2.0, 4.0, 6.0, 8.0, 10.0]
npt.assert_array_equal(res,
np.trim_zeros(convolve(signal, impulse_response), trim="b"))
def test_convolve_with_delta_function(self):
signal = [1.0, 2.0, 3.0, 4.0, 5.0]
impulse_response = [1, 0, 0]
npt.assert_array_equal(signal,
np.trim_zeros(convolve(signal, impulse_response), trim="b"))