def idct_2d_ref(x, **kwargs):
"""Calculate reference values for testing idct2."""
x = np.array(x, copy=True)
for row in range(x.shape[0]):
x[row, :] = idct(x[row, :], **kwargs)
for col in range(x.shape[1]):
x[:, col] = idct(x[:, col], **kwargs)
return x
def test_definition(self):
for i in FFTWDATA_SIZES:
xr, yr, dt = fftw_dct_ref(self.type, i, self.rdt)
x = idct(yr, type=self.type)
assert_equal(x.dtype, dt)
# XXX: we divide by np.max(y) because the tests fail otherwise. We
# should really use something like assert_array_approx_equal. The
# difference is due to fftw using a better algorithm w.r.t error
# propagation compared to the ones from fftpack.
assert_array_almost_equal(x / np.max(x), xr / np.max(x), decimal=self.dec,
err_msg="Size %d failed" % i)
def test_idct_definition(fftwdata_size, rdt, type):
xr, yr, dt = fftw_dct_ref(type, fftwdata_size, rdt)
x = idct(yr, type=type)
dec = dec_map[(idct, rdt, type)]
assert_equal(x.dtype, dt)
assert_allclose(x, xr, rtol=0., atol=np.max(xr)*10**(-dec))
def test_idct_complex(self):
y = idct(np.arange(5)*1j)
x = 1j*idct(np.arange(5))
assert_array_almost_equal(x, y)