def test_ObscAnnulus():
rng = np.random.default_rng(57)
size = 10_000
for i in range(100):
cx = rng.normal(0.0, 1.0)
cy = rng.normal(0.0, 1.0)
inner = rng.uniform(0.5, 1.5)
outer = rng.uniform(1.6, 1.9)
obsc = batoid.ObscAnnulus(inner, outer, cx, cy)
for i in range(100):
x = rng.normal(0.0, 1.0)
y = rng.normal(0.0, 1.0)
assert obsc.contains(
x, y) == (inner <= np.hypot(x - cx, y - cy) < outer)
x = rng.normal(0.0, 1.0, size=size)
y = rng.normal(0.0, 1.0, size=size)
r = np.hypot(x - cx, y - cy)
np.testing.assert_array_equal(obsc.contains(x, y),
(inner <= r) & (r < outer))
do_pickle(obsc)
rv = batoid.RayVector(x, y, 0.0, 0.0, 0.0, 0.0)
batoid.obscure(obsc, rv)
np.testing.assert_array_equal(obsc.contains(x, y), rv.vignetted)
def test_ne():
objs = [
batoid.ObscCircle(1.0),
batoid.ObscCircle(2.0),
batoid.ObscCircle(1.0, 0.1, 0.1),
batoid.ObscAnnulus(0.0, 1.0),
batoid.ObscAnnulus(0.1, 1.0),
batoid.ObscAnnulus(0.1, 1.0, 0.1, 0.1),
batoid.ObscRectangle(1.0, 2.0),
batoid.ObscRectangle(1.0, 2.0, 0.1, 0.1),
batoid.ObscRectangle(1.0, 2.0, 0.1, 0.1, 1.0),
batoid.ObscRay(1.0, 2.0),
batoid.ObscRay(1.0, 2.0, 0.1, 0.1),
batoid.ObscNegation(batoid.ObscCircle(1.0)),
batoid.ObscPolygon([0,1,1,0],[0,0,1,1]),
batoid.ObscUnion([batoid.ObscCircle(1.0)]),
batoid.ObscUnion([
batoid.ObscCircle(1.0),
batoid.ObscCircle(2.0)
]),
batoid.ObscUnion([
batoid.ObscCircle(1.0),
batoid.ObscCircle(2.2)
]),
batoid.ObscUnion([
batoid.ObscCircle(1.0),
batoid.ObscCircle(2.2),
batoid.ObscAnnulus(1.0, 2.0)
]),
batoid.ObscIntersection([batoid.ObscCircle(1.0)]),
batoid.ObscIntersection([
batoid.ObscCircle(1.0),
batoid.ObscCircle(2.0)
]),
batoid.ObscIntersection([
batoid.ObscCircle(1.0),
batoid.ObscCircle(2.2)
]),
batoid.ObscIntersection([
batoid.ObscCircle(1.0),
batoid.ObscCircle(2.2),
batoid.ObscAnnulus(1.0, 2.0)
]),
]
all_obj_diff(objs)
def test_ObscAnnulus():
import random
random.seed(57)
for i in range(100):
cx = random.gauss(0.0, 1.0)
cy = random.gauss(0.0, 1.0)
inner = random.uniform(0.5, 1.5)
outer = random.uniform(1.6, 1.9)
obsc = batoid.ObscAnnulus(inner, outer, cx, cy)
for i in range(100):
x = random.gauss(0.0, 1.0)
y = random.gauss(0.0, 1.0)
assert obsc.contains(
x, y) == (inner <= np.hypot(x - cx, y - cy) < outer)
do_pickle(obsc)
def test_zernikeGQ():
if __name__ == '__main__':
nx = 1024
rings = 10
tol = 1e-4
else:
nx = 128
rings = 5
tol = 1e-3
telescope = batoid.Optic.fromYaml("LSST_r.yaml")
telescope.clearObscuration()
telescope['LSST.M1'].obscuration = batoid.ObscNegation(
batoid.ObscCircle(4.18))
zSquare = batoid.analysis.zernike(telescope,
0.0,
0.0,
625e-9,
nx=nx,
jmax=28,
reference='chief')
zGQ = batoid.analysis.zernikeGQ(telescope,
0.0,
0.0,
625e-9,
rings=rings,
jmax=28,
reference='chief')
np.testing.assert_allclose(zSquare, zGQ, rtol=0, atol=tol)
# Repeat with annular Zernikes
telescope['LSST.M1'].obscuration = batoid.ObscNegation(
batoid.ObscAnnulus(0.61 * 4.18, 4.18))
zSquare = batoid.analysis.zernike(telescope,
0.0,
0.0,
625e-9,
nx=nx,
jmax=28,
reference='chief',
eps=0.61)
zGQ = batoid.analysis.zernikeGQ(telescope,
0.0,
0.0,
625e-9,
rings=rings,
jmax=28,
reference='chief',
eps=0.61)
np.testing.assert_allclose(zSquare, zGQ, rtol=0, atol=tol)
# Try off-axis
zSquare = batoid.analysis.zernike(telescope,
np.deg2rad(0.2),
np.deg2rad(0.1),
625e-9,
nx=nx,
jmax=28,
reference='chief',
eps=0.61)
zGQ = batoid.analysis.zernikeGQ(telescope,
np.deg2rad(0.2),
np.deg2rad(0.1),
625e-9,
rings=rings,
jmax=28,
reference='chief',
eps=0.61)
np.testing.assert_allclose(zSquare, zGQ, rtol=0, atol=tol)
def test_huygens_paraboloid(plot=False):
if __name__ == '__main__':
obscurations = [0.0, 0.25, 0.5, 0.75]
else:
obscurations = [0.25]
print("Testing HuygensPSF")
# Just do a single parabolic mirror test
focalLength = 1.5
diam = 0.3
R = 2*focalLength
for obscuration in obscurations:
telescope = batoid.CompoundOptic(
items = [
batoid.Mirror(
batoid.Paraboloid(R),
name="Mirror",
obscuration=batoid.ObscNegation(
batoid.ObscAnnulus(0.5*obscuration*diam, 0.5*diam)
)
),
batoid.Detector(
batoid.Plane(),
name="detector",
coordSys=batoid.CoordSys(origin=[0, 0, focalLength])
)
],
pupilSize=diam,
backDist=10.0,
inMedium=batoid.ConstMedium(1.0)
)
airy_size = 1.22*500e-9/diam * 206265
print()
print("Airy radius: {:4.2f} arcsec".format(airy_size))
# Start with the HuygensPSF
npix = 96
size = 3.0 # arcsec
dsize = size/npix
dsize_X = dsize*focalLength/206265 # meters
psf = batoid.huygensPSF(
telescope, 0.0, 0.0, 500e-9,
nx=npix, dx=dsize_X, dy=dsize_X
)
psf.array /= np.max(psf.array)
scale = np.sqrt(np.abs(np.linalg.det(psf.primitiveVectors))) # meters
scale *= 206265/focalLength # arcsec
obj = galsim.Airy(lam=500, diam=diam, obscuration=obscuration)
# Need to shift by half a pixel.
obj = obj.shift(scale/2, scale/2)
im = obj.drawImage(nx=npix, ny=npix, scale=scale, method='no_pixel')
arr = im.array/np.max(im.array)
gs_mom = galsim.hsm.FindAdaptiveMom(im)
psfim = galsim.Image(psf.array)
jt_mom = galsim.hsm.FindAdaptiveMom(psfim)
print("GalSim shape: ", gs_mom.observed_shape)
print("batoid shape: ", jt_mom.observed_shape)
print("GalSim centroid: ", gs_mom.moments_centroid)
print("batoid centroid: ", jt_mom.moments_centroid)
print("GalSim size: ", gs_mom.moments_sigma)
print("batoid size: ", jt_mom.moments_sigma)
print("GalSim rho4: ", gs_mom.moments_rho4)
print("batoid rho4: ", jt_mom.moments_rho4)
np.testing.assert_allclose(
gs_mom.observed_shape.g1,
jt_mom.observed_shape.g1,
rtol=0.0, atol=3e-3
)
np.testing.assert_allclose(
gs_mom.observed_shape.g2,
jt_mom.observed_shape.g2,
rtol=0.0, atol=3e-3
)
np.testing.assert_allclose(
gs_mom.moments_centroid.x,
jt_mom.moments_centroid.x,
rtol=0.0, atol=1e-9
)
np.testing.assert_allclose(
gs_mom.moments_centroid.y,
jt_mom.moments_centroid.y,
rtol=0.0, atol=1e-9
)
np.testing.assert_allclose(
gs_mom.moments_sigma,
jt_mom.moments_sigma,
rtol=1e-2 # why not better?!
)
np.testing.assert_allclose(
gs_mom.moments_rho4,
jt_mom.moments_rho4,
rtol=2e-2
)
if plot:
size = scale*npix
import matplotlib.pyplot as plt
fig = plt.figure(figsize=(15, 4))
ax1 = fig.add_subplot(131)
im1 = ax1.imshow(
np.log10(arr),
extent=np.r_[-1,1,-1,1]*size/2,
vmin=-7, vmax=0
)
plt.colorbar(im1, ax=ax1, label=r'$\log_{10}$ flux')
ax1.set_title('GalSim')
ax1.set_xlabel("arcsec")
ax1.set_ylabel("arcsec")
sizeX = dsize_X * npix * 1e6 # microns
ax2 = fig.add_subplot(132)
im2 = ax2.imshow(
np.log10(psf.array),
extent=np.r_[-1,1,-1,1]*sizeX/2,
vmin=-7, vmax=0
)
plt.colorbar(im2, ax=ax2, label=r'$\log_{10}$ flux')
ax2.set_title('batoid')
ax2.set_xlabel(r"$\mu m$")
ax2.set_ylabel(r"$\mu m$")
ax3 = fig.add_subplot(133)
im3 = ax3.imshow(
(psf.array-arr)/np.max(arr),
vmin=-0.01, vmax=0.01,
cmap='seismic'
)
plt.colorbar(im3, ax=ax3, label="(batoid-GalSim)/max(GalSim)")
ax3.set_title('resid')
ax3.set_xlabel(r"$\mu m$")
ax3.set_ylabel(r"$\mu m$")
fig.tight_layout()
plt.show()
