def test_L2_Abs_angle():
'''Test that that shadow area increases with angle.
The comparison number was calculated by H. M. Guenther in response
to Arcus DQ36.'''
l2_dims = {'period': 0.966 * u.mm, 'bardepth': 0.5 * u.mm,
'barwidth': 0.1 * u.mm}
l2 = L2Abs(l2_dims=l2_dims)
p1 = l2(generate_test_photons(1))
l2 = L2Abs(l2_dims=l2_dims, orientation=euler2mat(np.deg2rad(1.8), 0, 0, 'szxy'))
p2 = l2(generate_test_photons(1))
assert np.isclose(p2['probability'][0] / p1['probability'][0], 0.979, rtol=1e-3)
def test_FlatStack():
'''Run a stack of two elements and check that both are applied to the photons.'''
fs = marxs.optics.FlatStack(
position=[0, 5, 0],
zoom=2,
elements=[marxs.optics.EnergyFilter, marxs.optics.FlatDetector],
keywords=[{
'filterfunc': lambda x: 0.5
}, {}])
# Check all layers are at the same position
assert np.allclose(fs.geometry['center'], np.array([0, 5, 0, 1]))
assert np.allclose(fs.elements[0].geometry['center'],
np.array([0, 5, 0, 1]))
assert np.allclose(fs.elements[1].geometry['center'],
np.array([0, 5, 0, 1]))
assert np.allclose(fs.pos4d, fs.elements[1].pos4d)
p = generate_test_photons(5)
# Photons 0, 1 miss the stack
p['pos'][:, 1] = [0, 1, 3.1, 4, 5]
fs.loc_coos_name = ['a', 'b']
p = fs(p)
assert np.allclose(p['probability'], [1, 1, .5, .5, .5])
assert np.all(np.isnan(p['a'][:2]))
assert np.allclose(p['a'][2:], [-1.9, -1., 0])
def test_efficiency_table_in_use():
'''Use table in a optical element'''
efftab = InterpolateEfficiencyTable(get_pkg_data_filename('grating_efficiency.csv'), k=2)
cat = CATGrating(order_selector=efftab, d=0.001)
photons = generate_test_photons(500)
photons = cat(photons)
assert np.isclose((photons['order']==0).sum(), len(photons) / 2, rtol=.05)
def test_L2_Abs_angle():
'''Test that that shadow area increases with angle.
The comparison number was calculated by H. M. Guenther in response
to Arcus DQ36.'''
l2_dims = {'period': 0.966 * u.mm, 'bardepth': 0.5 * u.mm,
'barwidth': 0.1 * u.mm}
l2 = catgrating.L2Abs(l2_dims=l2_dims)
p1 = l2(generate_test_photons(1))
l2 = catgrating.L2Abs(l2_dims=l2_dims,
orientation=euler2mat(np.deg2rad(1.8), 0, 0, 'szxy'))
p2 = l2(generate_test_photons(1))
assert np.isclose(p2['probability'][0] / p1['probability'][0], 0.979,
rtol=1e-3)
def test_L2_Abs():
'''Check L2 absorption against numbers calculated by Ralf Heilmann.'''
photons = generate_test_photons(1)
l2 = L2Abs(l2_dims={'period': 0.966 * u.mm, 'bardepth': 0.5 * u.mm,
'barwidth': 0.1 * u.mm})
photons = l2(photons)
assert np.isclose(photons['probability'], 0.81, rtol=0.02)
def test_scalingSitransparancy():
'''The module has data for 1 mu Si and scales that to the depth of the
grating. Test against known-good coefficient from CXRO.'''
photons = generate_test_photons(1)
cat = L1(order_selector=OrderSelector([-5]), relativearea=0.,
depth=4*u.mu, d=0.00001)
photons = cat(photons)
assert np.isclose(photons['probability'][0], 0.22458, rtol=1e-4)
def test_L2_Abs():
'''Check L2 absorption against numbers calculated by Ralf Heilmann.'''
photons = generate_test_photons(1)
l2 = catgrating.L2Abs(l2_dims={'period': 0.966 * u.mm,
'bardepth': 0.5 * u.mm,
'barwidth': 0.1 * u.mm})
photons = l2(photons)
assert np.isclose(photons['probability'], 0.81, rtol=0.02)
def test_efficiency_table_in_use():
'''Use table in a optical element'''
efftab = catgrating.InterpolateEfficiencyTable(get_pkg_data_filename('grating_efficiency.csv'), k=2)
cat = CATGrating(order_selector=efftab, d=0.001)
photons = generate_test_photons(5000)
photons = cat(photons)
assert np.isclose((photons['order'] == 0).sum(), len(photons) / 2,
rtol=.05)
def test_catsupportbars():
photons = generate_test_photons(5)
p = catgrating.catsupportbars(photons.copy())
assert np.all(p['probability'] == 0)
photons['facet'] = np.arange(-1, 4)
p = catgrating.catsupportbars(photons)
assert np.all(p['probability'][1:] == 1)
assert p['probability'][0] == 0
def test_scalingSitransparancy():
'''The module has data for 1 mu Si and scales that to the depth of the
grating. Test against known-good coefficient from CXRO.'''
photons = generate_test_photons(100)
cat = catgrating.L1(order_selector=OrderSelector([-5]),
l1_dims={'bardepth': 0.004 * u.mm,
'period': 0.0001 * u.mm,
'barwidth': 0.00009 * u.mm})
photons = cat(photons)
assert np.isclose(np.median(photons['probability']), 0.22458, rtol=1e-4)
def test_nonparallelCATGrating_simplifies_to_CATGrating():
'''With all randomness parameters set to 0, the results
should match a CAT grating exactly.'''
photons = generate_test_photons(50)
# Mix the photons up a little
scat = RandomGaussianScatter(scatter=0.01)
photons = scat(photons)
order_selector = OrderSelector([2])
cat = CATGrating(order_selector=order_selector, d=0.001)
npcat = NonParallelCATGrating(order_selector=order_selector, d=0.001)
p1 = cat(photons.copy())
p2 = npcat(photons)
assert np.all(p1['dir'] == p2['dir'])
def test_nonparallelCATGrating_simplifies_to_CATGrating():
'''With all randomness parameters set to 0, the results
should match a CAT grating exactly.'''
photons = generate_test_photons(50)
# Mix the photons up a little
scat = RandomGaussianScatter(scatter=0.01 * u.rad)
photons = scat(photons)
order_selector = OrderSelector([2])
cat = CATGrating(order_selector=order_selector, d=0.001)
npcat = catgrating.NonParallelCATGrating(order_selector=order_selector,
d=0.001)
p1 = cat(photons.copy())
p2 = npcat(photons)
assert np.all(p1['dir'] == p2['dir'])
def test_L2_broadening():
'''Compare calculated L2 broadening with the values calculated
by Ralf Heilmann. Both calculation make simplications (e.g. assuming
a circular hole), but should give the right order of magnitude for
diffraction.'''
photons = generate_test_photons(1000)
photons['energy'] = 0.25 # 50 Ang
l2 = L2Diffraction(l2_dims={'period': 0.966 * u.mm,
'barwidth': 0.1 * u.mm})
photons = l2(photons)
det = FlatDetector(position=[-1, 0, 0])
photons = det(photons)
sigma = np.std(photons['det_x'])
# for small angles tan(alpha) = alpha
# 1 arcsec = 4.8...e-6 rad
# 0.5 is sigma calculated by Ralf Heilmann for a rectangular
# aperture
assert np.isclose(sigma, .5 * 4.8e-6, rtol=.5)
def test_L2_broadening():
'''Compare calculated L2 broadening with the values calculated
by Ralf Heilmann. Both calculation make simplications (e.g. assuming
a circular hole), but should give the right order of magnitude for
diffraction.'''
photons = generate_test_photons(1000)
photons['energy'] = 0.25 # 50 Ang
l2 = catgrating.L2Diffraction(l2_dims={'period': 0.966 * u.mm,
'barwidth': 0.1 * u.mm})
photons = l2(photons)
det = FlatDetector(position=[-1, 0, 0])
photons = det(photons)
sigma = np.std(photons['det_x'])
# for small angles tan(alpha) = alpha
# 1 arcsec = 4.8...e-6 rad
# 0.5 is sigma calculated by Ralf Heilmann for a rectangular
# aperture
assert np.isclose(sigma, .5 * 4.8e-6, rtol=.5)
def test_FlatStack():
'''Run a stack of two elements and check that both are applied to the photons.'''
fs = marxs.optics.FlatStack(position=[0, 5, 0], zoom=2,
sequence=[marxs.optics.EnergyFilter, marxs.optics.FlatDetector],
keywords=[{'filterfunc': lambda x: 0.5},{}])
# Check all layers are at the same position
assert np.allclose(fs.geometry['center'], np.array([0, 5, 0, 1]))
assert np.allclose(fs.sequence[0].geometry['center'], np.array([0, 5, 0, 1]))
assert np.allclose(fs.sequence[1].geometry['center'], np.array([0, 5, 0, 1]))
assert np.allclose(fs.pos4d, fs.sequence[1].pos4d)
p = generate_test_photons(5)
# Photons 0, 1 miss the stack
p['pos'][:, 1] = [0, 1, 3.1, 4, 5]
fs.loc_coos_name = ['a', 'b']
p = fs(p)
assert np.allclose(p['probability'], [1, 1, .5, .5, .5])
assert np.all(np.isnan(p['a'][:2]))
assert np.allclose(p['a'][2:], [-1.9, -1., 0])