def test_non_ndarray_with_dtype(self):
x = np.array([1., 2., 3., 4., 5.])
xs = _TestRFFTBase.MockSeries(x)
expected = [1, 2, 3, 4, 5]
rfft(xs)
# Data should not have been overwritten
assert_equal(x, expected)
assert_equal(xs.data, expected)
def test_size_accuracy(self):
# Sanity check for the accuracy for prime and non-prime sized inputs
if self.rdt == np.float32:
rtol = 1e-5
elif self.rdt == np.float64:
rtol = 1e-10
for size in LARGE_COMPOSITE_SIZES + LARGE_PRIME_SIZES:
np.random.seed(1234)
x = np.random.rand(size).astype(self.rdt)
y = irfft(rfft(x), len(x))
_assert_close_in_norm(x, y, rtol, size, self.rdt)
y = rfft(irfft(x, 2 * len(x) - 1))
_assert_close_in_norm(x, y, rtol, size, self.rdt)
def test_random_real(self):
for size in [1, 51, 111, 100, 200, 64, 128, 256, 1024]:
x = random([size]).astype(self.rdt)
y1 = irfft(rfft(x), n=size)
y2 = rfft(irfft(x, n=(size * 2 - 1)))
assert_equal(y1.dtype, self.rdt)
assert_equal(y2.dtype, self.cdt)
assert_array_almost_equal(y1,
x,
decimal=self.ndec,
err_msg="size=%d" % size)
assert_array_almost_equal(y2,
x,
decimal=self.ndec,
err_msg="size=%d" % size)
def test_djbfft(self):
for i in range(2, 14):
n = 2**i
x = np.arange(n)
y1 = np.fft.rfft(x)
y = rfft(x)
assert_array_almost_equal(y, y1)
def test_definition(self):
for t in [[1, 2, 3, 4, 1, 2, 3, 4], [1, 2, 3, 4, 1, 2, 3, 4, 5]]:
x = np.array(t, dtype=self.rdt)
y = rfft(x)
y1 = direct_rdft(x)
assert_array_almost_equal(y, y1)
assert_equal(y.dtype, self.cdt)
def test_complex_input(self):
x = np.zeros(10, dtype=self.cdt)
with assert_raises(TypeError, match="x must be a real sequence"):
rfft(x)
def direct_rdftn(x):
return fftn(rfft(x), axes=range(x.ndim - 1))
