def test_compute_intensity(self):
shape = (32, 32)
u = (np.ones(shape) + 1j * np.ones(shape) * 3).astype(
cfg.PRECISION.np_cplx)
np.testing.assert_almost_equal(
np.abs(u)**2,
ip.compute_intensity(u).get())
def compare_sampling(gauss, factor):
shape = (int(factor * self.n), ) * 2
im = ip.compute_intensity(
source.transfer(shape,
self.ps / factor,
self.energies[0],
check=False)).get()
self.assertAlmostEqual(im.sum(), gauss.sum(), places=3)
hd = ip.rescale(gauss, shape).get() / factor**2
np.testing.assert_almost_equal(im, hd, decimal=5)
def run_fixed():
syris.init()
n = 512
ps = 1 * q.um
energies = np.arange(5, 30) * q.keV
y, x = np.mgrid[-n // 2:n // 2, -n // 2:n // 2]
flux = np.exp(-(x**2 + y**2) / (100**2)) / q.s
weights = np.arange(1, len(energies) + 1)[:, np.newaxis, np.newaxis]
flux = weights * flux
traj = Trajectory([(n / 2, n / 2, 0)] * ps)
source = FixedSpectrumSource(energies,
flux,
30 * q.m, (100, 500) * q.um,
traj,
pixel_size=ps)
im = ip.compute_intensity(source.transfer((n, n), ps, 5 * q.keV)).get()
show(im, title="Original sampling")
im = ip.compute_intensity(source.transfer((2 * n, ) * 2, ps / 2,
5 * q.keV)).get()
show(im, title="2x supersampled")
plt.show()
def test_compute_intensity(self):
shape = (32, 32)
u = (np.ones(shape) + 1j * np.ones(shape) * 3).astype(cfg.PRECISION.np_cplx)
np.testing.assert_almost_equal(np.abs(u) ** 2, ip.compute_intensity(u).get())