def test_hfft(self):
x = random(14) + 1j*random(14)
x_herm = np.concatenate((random(1), x, random(1)))
x = np.concatenate((x_herm, x[::-1].conj()))
assert_array_almost_equal(fft.fft(x), fft.hfft(x_herm))
assert_array_almost_equal(fft.hfft(x_herm) / np.sqrt(30),
fft.hfft(x_herm, norm="ortho"))
def test_ihfft(self):
x = random(14) + 1j * random(14)
x_herm = np.concatenate((random(1), x, random(1)))
x = np.concatenate((x_herm, x[::-1].conj()))
assert_array_almost_equal(x_herm, fft.ihfft(fft.hfft(x_herm)))
for norm in ["backward", "ortho", "forward"]:
assert_array_almost_equal(
x_herm, fft.ihfft(fft.hfft(x_herm, norm=norm), norm=norm))
def test_hfft(self):
x = random(14) + 1j * random(14)
x_herm = np.concatenate((random(1), x, random(1)))
x = np.concatenate((x_herm, x[::-1].conj()))
expect = fft.fft(x)
assert_array_almost_equal(expect, fft.hfft(x_herm))
assert_array_almost_equal(expect, fft.hfft(x_herm, norm="backward"))
assert_array_almost_equal(expect / np.sqrt(30),
fft.hfft(x_herm, norm="ortho"))
assert_array_almost_equal(expect / 30, fft.hfft(x_herm,
norm="forward"))
def test_dtypes(self, dtype):
# make sure that all input precisions are accepted
x = random(30).astype(dtype)
assert_array_almost_equal(fft.ifft(fft.fft(x)), x)
assert_array_almost_equal(fft.irfft(fft.rfft(x)), x)
assert_array_almost_equal(fft.hfft(fft.ihfft(x), len(x)), x)
