def dst_2d_ref(x, **kwargs):
"""Calculate reference values for testing dst2."""
x = np.array(x, copy=True)
for row in range(x.shape[0]):
x[row, :] = dst(x[row, :], **kwargs)
for col in range(x.shape[1]):
x[:, col] = dst(x[:, col], **kwargs)
return x
def dst_2d_ref(x, **kwargs):
""" used as a reference in testing dst2. """
x = np.array(x, copy=True)
for row in range(x.shape[0]):
x[row, :] = dst(x[row, :], **kwargs)
for col in range(x.shape[1]):
x[:, col] = dst(x[:, col], **kwargs)
return x
def dst_2d_ref(x, **kwargs):
"""Calculate reference values for testing dst2."""
x = np.array(x, copy=True)
for row in range(x.shape[0]):
x[row, :] = dst(x[row, :], **kwargs)
for col in range(x.shape[1]):
x[:, col] = dst(x[:, col], **kwargs)
return x
def dst_2d_ref(x, **kwargs):
""" used as a reference in testing dst2. """
x = np.array(x, copy=True)
for row in range(x.shape[0]):
x[row, :] = dst(x[row, :], **kwargs)
for col in range(x.shape[1]):
x[:, col] = dst(x[:, col], **kwargs)
return x
def test_definition_ortho(self):
# Test orthornomal mode.
for i in range(len(X)):
x = np.array(X[i], dtype=self.rdt)
dt = np.result_type(np.float32, self.rdt)
y = dst(x, norm='ortho', type=4)
y2 = naive_dst4(x, norm='ortho')
assert_equal(y.dtype, dt)
assert_array_almost_equal(y, y2, decimal=self.dec)
def test_definition_ortho(self):
# Test orthornomal mode.
for i in range(len(X)):
x = np.array(X[i], dtype=self.rdt)
dt = np.result_type(np.float32, self.rdt)
y = dst(x, norm='ortho', type=4)
y2 = naive_dst4(x, norm='ortho')
assert_equal(y.dtype, dt)
assert_array_almost_equal(y, y2, decimal=self.dec)
def test_definition_ortho(self):
# Test orthornomal mode.
dt = np.result_type(np.float32, self.rdt)
for xr in X:
x = np.array(xr, dtype=self.rdt)
y = dst(x, norm='ortho', type=1)
y2 = naive_dst1(x, norm='ortho')
assert_equal(y.dtype, dt)
assert_array_almost_equal(y / np.max(y), y2 / np.max(y), decimal=self.dec)
def test_definition(self):
for i in FFTWDATA_SIZES:
xr, yr, dt = fftw_dst_ref(self.type, i, self.rdt)
y = dst(xr, type=self.type)
assert_equal(y.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(y / np.max(y), yr / np.max(y), decimal=self.dec, err_msg="Size %d failed" % i)
def test_definition(self):
for i in FFTWDATA_SIZES:
xr, yr, dt = fftw_dst_ref(self.type, i, self.rdt)
y = dst(xr, type=self.type)
assert_equal(y.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(y / np.max(y), yr / np.max(y), decimal=self.dec,
err_msg="Size %d failed" % i)
def test_dst_complex(self):
y = dst(np.arange(5) * 1j)
x = 1j * dst(np.arange(5))
assert_array_almost_equal(x, y)
def test_dst_complex64(self):
y = dst(np.arange(5, dtype=np.complex64) * 1j)
x = 1j * dst(np.arange(5))
assert_array_almost_equal(x, y)
def test_dst_complex(self):
y = dst(np.arange(5) * 1j)
x = 1j * dst(np.arange(5))
assert_array_almost_equal(x, y)
def test_dst_complex64(self):
y = dst(np.arange(5, dtype=np.complex64) * 1j)
x = 1j * dst(np.arange(5))
assert_array_almost_equal(x, y)