def test_center_kernel():
x_grid, y_gird = Util.make_grid(31, 1)
sigma = 2
flux = gaussian.function(x_grid, y_gird, amp=1, sigma=sigma)
kernel = Util.array2image(flux)
kernel = kernel_util.kernel_norm(kernel)
# kernel being centered
kernel_new = kernel_util.center_kernel(kernel, iterations=20)
kernel_new = kernel_util.kernel_norm(kernel_new)
npt.assert_almost_equal(kernel_new/kernel, 1, decimal=8)
# kernel shifted in x
kernel_shifted = interp.shift(kernel, [-.1, 0], order=1)
kernel_new = kernel_util.center_kernel(kernel_shifted, iterations=5)
kernel_new = kernel_util.kernel_norm(kernel_new)
npt.assert_almost_equal((kernel_new + 0.00001) / (kernel + 0.00001), 1, decimal=4)
# kernel shifted in y
kernel_shifted = interp.shift(kernel, [0, -0.4], order=1)
kernel_new = kernel_util.center_kernel(kernel_shifted, iterations=5)
kernel_new = kernel_util.kernel_norm(kernel_new)
npt.assert_almost_equal((kernel_new + 0.01) / (kernel + 0.01), 1, decimal=3)
# kernel shifted in x and y
kernel_shifted = interp.shift(kernel, [0.2, -0.3], order=1)
kernel_new = kernel_util.center_kernel(kernel_shifted, iterations=5)
kernel_new = kernel_util.kernel_norm(kernel_new)
npt.assert_almost_equal((kernel_new + 0.01) / (kernel + 0.01), 1, decimal=3)
def test_raise(self):
with self.assertRaises(ValueError):
kernel = np.zeros((2, 2))
kernel_util.center_kernel(kernel, iterations=1)
with self.assertRaises(ValueError):
kernel_super = np.ones((9, 9))
kernel_util.split_kernel(kernel_super, supersampling_kernel_size=2, supersampling_factor=3)
with self.assertRaises(ValueError):
kernel_util.split_kernel(kernel_super, supersampling_kernel_size=3, supersampling_factor=0)
with self.assertRaises(ValueError):
image = np.ones((10, 10))
kernel_util.cutout_source(x_pos=3, y_pos=2, image=image, kernelsize=2)
with self.assertRaises(ValueError):
kernel_util.fwhm_kernel(kernel=np.ones((4, 4)))
with self.assertRaises(ValueError):
kernel_util.fwhm_kernel(kernel=np.ones((5, 5)))