def METHOD_NAME(self):
    x = np.array([1, 2, 3])
    h = np.array([0, 1, 0.5])
    expected_result = np.array([1., 2.5, 4.])
    result_np = np.convolve(x, h, 'same')
    self.assertTrue(np.array_equal(result_np, expected_result))
    result_fft = Filter.fft_convolve_1d(x, h)
    self.assertEqual(len(expected_result), len(result_fft))
    for i in range(len(expected_result)):
        self.assertAlmostEqual(expected_result[i], result_fft[i], places=8, msg=str(i))
    x = np.linspace(0, 1, num=10 ** 3).astype(np.complex64)
    h = Filter.design_windowed_sinc_bandpass(0.1, 0.4, 0.01)
    # fft convolve is faster if IR is round about 400 samples or windowed sinc has bandwidth of 0.01
    result_np = np.convolve(x, h, mode="same")
    result_fft = Filter.fft_convolve_1d(x, h)
    np.testing.assert_array_almost_equal(result_np, result_fft)