def test_shapelet_fit():
"""Test fitting a Shapelet decomposition of an image
"""
import time
t1 = time.time()
for method, norm in [('no_pixel','f'), ('sb','sb')]:
# We fit a shapelet approximation of a distorted Moffat profile:
flux = 20
psf = galsim.Moffat(beta=3.4, half_light_radius=1.2, flux=flux)
psf = psf.shear(g1=0.11,g2=0.07).shift(0.03,0.04)
scale = 0.2
pixel = galsim.Pixel(scale)
conv = galsim.Convolve([psf,pixel])
im1 = conv.drawImage(scale=scale, method=method)
sigma = 1.2 # Match half-light-radius as a decent first approximation.
shapelet = galsim.FitShapelet(sigma, 10, im1, normalization=norm)
print 'fitted shapelet coefficients = ',shapelet.bvec
# Check flux
print 'flux = ',shapelet.getFlux(),' cf. ',flux
np.testing.assert_almost_equal(shapelet.getFlux() / flux, 1., 1,
err_msg="Fitted shapelet has the wrong flux")
# Test centroid
print 'centroid = ',shapelet.centroid(),' cf. ',conv.centroid()
np.testing.assert_almost_equal(shapelet.centroid().x, conv.centroid().x, 2,
err_msg="Fitted shapelet has the wrong centroid (x)")
np.testing.assert_almost_equal(shapelet.centroid().y, conv.centroid().y, 2,
err_msg="Fitted shapelet has the wrong centroid (y)")
# Test drawing image from shapelet
im2 = im1.copy()
shapelet.drawImage(im2, method=method)
# Check that images are close to the same:
print 'norm(diff) = ',np.sum((im1.array-im2.array)**2)
print 'norm(im) = ',np.sum(im1.array**2)
assert np.sum((im1.array-im2.array)**2) < 1.e-3 * np.sum(im1.array**2)
# Remeasure -- should now be very close to the same.
shapelet2 = galsim.FitShapelet(sigma, 10, im2, normalization=norm)
np.testing.assert_equal(shapelet.sigma, shapelet2.sigma,
err_msg="Second fitted shapelet has the wrong sigma")
np.testing.assert_equal(shapelet.order, shapelet2.order,
err_msg="Second fitted shapelet has the wrong order")
np.testing.assert_almost_equal(shapelet.bvec, shapelet2.bvec, 6,
err_msg="Second fitted shapelet coefficients do not match original")
t2 = time.time()
print 'time for %s = %.2f'%(funcname(),t2-t1)
def fitImage(self, image, center=None, normalization='flux'):
"""An obsolete method that is roughly equivalent to
self = galsim.FitShapelet(self.sigma, self.order, image)
"""
new_obj = galsim.FitShapelet(self.sigma, self.order, image, center, normalization)
bvec = new_obj.SBProfile.getBVec()
GSObject.__init__(self, galsim._galsim.SBShapelet(self.sigma, bvec))
def Shapelet_fitImage(self, image, center=None, normalization='flux'):
"""A deprecated method that is roughly equivalent to
self = galsim.FitShapelet(self.sigma, self.order, image)
"""
depr('fitImage', 1.1, 'galsim.FitShapelet')
new_obj = galsim.FitShapelet(self.sigma, self.order, image, center, normalization)
bvec = new_obj.SBProfile.getBVec()
galsim.GSObject.__init__(self, galsim._galsim.SBShapelet(self.sigma, bvec))
def test_dep_shapelet():
"""Test the deprecated methods in galsim/deprecated/shapelet.py
"""
np.testing.assert_almost_equal(check_dep(galsim.LVectorSize, 12),
galsim.ShapeletSize(12))
# The next bit is from the old test_shapelet_adjustments() test
ftypes = [np.float32, np.float64]
nx = 128
ny = 128
scale = 0.2
im = galsim.ImageF(nx, ny, scale=scale)
sigma = 1.8
order = 6
bvec = [
1.3, # n = 0
0.02,
0.03, # n = 1
0.23,
-0.19,
0.08, # n = 2
0.01,
0.02,
0.04,
-0.03, # n = 3
-0.09,
0.07,
-0.11,
-0.08,
0.11, # n = 4
-0.03,
-0.02,
-0.08,
0.01,
-0.06,
-0.03, # n = 5
0.06,
-0.02,
0.00,
-0.05,
-0.04,
0.01,
0.09
] # n = 6
ref_shapelet = galsim.Shapelet(sigma=sigma, order=order, bvec=bvec)
ref_im = galsim.ImageF(nx, ny)
ref_shapelet.drawImage(ref_im, scale=scale, method='no_pixel')
# test setsigma
shapelet = galsim.Shapelet(sigma=1., order=order, bvec=bvec)
check_dep(shapelet.setSigma, sigma)
shapelet.drawImage(im, method='no_pixel')
np.testing.assert_array_almost_equal(
im.array,
ref_im.array,
6,
err_msg="Shapelet set with setSigma disagrees with reference Shapelet")
# Test setBVec
shapelet = galsim.Shapelet(sigma=sigma, order=order)
check_dep(shapelet.setBVec, bvec)
shapelet.drawImage(im, method='no_pixel')
np.testing.assert_array_almost_equal(
im.array,
ref_im.array,
6,
err_msg="Shapelet set with setBVec disagrees with reference Shapelet")
# Test setOrder
shapelet = galsim.Shapelet(sigma=sigma, order=2)
check_dep(shapelet.setOrder, order)
check_dep(shapelet.setBVec, bvec)
shapelet.drawImage(im, method='no_pixel')
np.testing.assert_array_almost_equal(
im.array,
ref_im.array,
6,
err_msg="Shapelet set with setOrder disagrees with reference Shapelet")
# Test that changing the order preserves the values to the extent possible.
shapelet = galsim.Shapelet(sigma=sigma, order=order, bvec=bvec)
check_dep(shapelet.setOrder, 10)
np.testing.assert_array_equal(
shapelet.getBVec()[0:28],
bvec,
err_msg="Shapelet setOrder to larger doesn't preserve existing values."
)
np.testing.assert_array_equal(
shapelet.getBVec()[28:66],
np.zeros(66 - 28),
err_msg="Shapelet setOrder to larger doesn't fill with zeros.")
check_dep(shapelet.setOrder, 6)
np.testing.assert_array_equal(
shapelet.getBVec(),
bvec,
err_msg=
"Shapelet setOrder back to original from larger doesn't preserve existing values."
)
check_dep(shapelet.setOrder, 3)
np.testing.assert_array_equal(
shapelet.getBVec()[0:10],
bvec[0:10],
err_msg="Shapelet setOrder to smaller doesn't preserve existing values."
)
check_dep(shapelet.setOrder, 6)
np.testing.assert_array_equal(
shapelet.getBVec()[0:10],
bvec[0:10],
err_msg=
"Shapelet setOrder back to original from smaller doesn't preserve existing values."
)
check_dep(shapelet.setOrder, 6)
np.testing.assert_array_equal(
shapelet.getBVec()[10:28],
np.zeros(28 - 10),
err_msg=
"Shapelet setOrder back to original from smaller doesn't fill with zeros."
)
# Test that setting a Shapelet with setNM gives the right profile
shapelet = galsim.Shapelet(sigma=sigma, order=order)
i = 0
for n in range(order + 1):
for m in range(n, -1, -2):
if m == 0:
check_dep(shapelet.setNM, n, m, bvec[i])
i = i + 1
else:
check_dep(shapelet.setNM, n, m, bvec[i], bvec[i + 1])
i = i + 2
shapelet.drawImage(im, method='no_pixel')
np.testing.assert_array_almost_equal(
im.array,
ref_im.array,
6,
err_msg="Shapelet set with setNM disagrees with reference Shapelet")
# Test that setting a Shapelet with setPQ gives the right profile
shapelet = galsim.Shapelet(sigma=sigma, order=order)
i = 0
for n in range(order + 1):
for m in range(n, -1, -2):
p = (n + m) // 2
q = (n - m) // 2
if m == 0:
check_dep(shapelet.setPQ, p, q, bvec[i])
i = i + 1
else:
check_dep(shapelet.setPQ, p, q, bvec[i], bvec[i + 1])
i = i + 2
shapelet.drawImage(im, method='no_pixel')
np.testing.assert_array_almost_equal(
im.array,
ref_im.array,
6,
err_msg="Shapelet set with setPQ disagrees with reference Shapelet")
# Check fitImage
s1 = galsim.Shapelet(sigma=sigma, order=10)
check_dep(s1.fitImage, image=im)
s2 = galsim.FitShapelet(sigma=sigma, order=10, image=im)
np.testing.assert_array_almost_equal(s1.getBVec(), s2.getBVec())
def test_shapelet_fit():
"""Test fitting a Shapelet decomposition of an image
"""
for method, norm in [('no_pixel', 'f'), ('sb', 'sb')]:
# We fit a shapelet approximation of a distorted Moffat profile:
flux = 20
psf = galsim.Moffat(beta=3.4, half_light_radius=1.2, flux=flux)
psf = psf.shear(g1=0.11, g2=0.07).shift(0.03, 0.04)
scale = 0.2
pixel = galsim.Pixel(scale)
conv = galsim.Convolve([psf, pixel])
im1 = conv.drawImage(scale=scale, method=method)
sigma = 1.2 # Match half-light-radius as a decent first approximation.
shapelet = galsim.FitShapelet(sigma, 10, im1, normalization=norm)
#print('fitted shapelet coefficients = ',shapelet.bvec)
# Check flux
print('flux = ', shapelet.getFlux(), ' cf. ', flux)
np.testing.assert_almost_equal(
shapelet.getFlux() / flux,
1.,
1,
err_msg="Fitted shapelet has the wrong flux")
# Test centroid
print('centroid = ', shapelet.centroid(), ' cf. ', conv.centroid())
np.testing.assert_almost_equal(
shapelet.centroid().x,
conv.centroid().x,
2,
err_msg="Fitted shapelet has the wrong centroid (x)")
np.testing.assert_almost_equal(
shapelet.centroid().y,
conv.centroid().y,
2,
err_msg="Fitted shapelet has the wrong centroid (y)")
# Test drawing image from shapelet
im2 = im1.copy()
shapelet.drawImage(im2, method=method)
# Check that images are close to the same:
print('norm(diff) = ', np.sum((im1.array - im2.array)**2))
print('norm(im) = ', np.sum(im1.array**2))
print('max(diff) = ', np.max(np.abs(im1.array - im2.array)))
print('max(im) = ', np.max(np.abs(im1.array)))
peak_scale = np.max(np.abs(
im1.array)) * 3 # Check agreement to within 3% of peak value.
np.testing.assert_almost_equal(
im2.array / peak_scale,
im1.array / peak_scale,
decimal=2,
err_msg="Shapelet version not a good match to original")
# Remeasure -- should now be very close to the same.
shapelet2 = galsim.FitShapelet(sigma, 10, im2, normalization=norm)
np.testing.assert_equal(
shapelet.sigma,
shapelet2.sigma,
err_msg="Second fitted shapelet has the wrong sigma")
np.testing.assert_equal(
shapelet.order,
shapelet2.order,
err_msg="Second fitted shapelet has the wrong order")
np.testing.assert_almost_equal(
shapelet.bvec,
shapelet2.bvec,
6,
err_msg="Second fitted shapelet coefficients do not match original"
)
# Test drawing off center
im2 = im1.copy()
offset = galsim.PositionD(0.3, 1.4)
shapelet.drawImage(im2, method=method, offset=offset)
shapelet2 = galsim.FitShapelet(sigma,
10,
im2,
normalization=norm,
center=im2.trueCenter() + offset)
np.testing.assert_equal(
shapelet.sigma,
shapelet2.sigma,
err_msg="Second fitted shapelet has the wrong sigma")
np.testing.assert_equal(
shapelet.order,
shapelet2.order,
err_msg="Second fitted shapelet has the wrong order")
np.testing.assert_almost_equal(
shapelet.bvec,
shapelet2.bvec,
6,
err_msg="Second fitted shapelet coefficients do not match original"
)
