def testCopyWithinFootprintOutside(self):
"""Copy a footprint that is larger than the image"""
target = afwImage.ImageF(100, 100)
target.set(0)
subTarget = afwImage.ImageF(
target,
afwGeom.Box2I(afwGeom.Point2I(40, 40), afwGeom.Extent2I(20, 20)))
source = afwImage.ImageF(10, 30)
source.setXY0(45, 45)
source.set(1.0)
foot = afwDetect.Footprint()
foot.addSpan(
50, 50, 60
) # Oversized on the source image, right; only some pixels overlap
foot.addSpan(
60, 0, 100
) # Oversized on the source, left and right; and on sub-target image, top
foot.addSpan(
99, 0, 1000
) # Oversized on the source image, top, left and right; aiming for segfault
afwDetect.copyWithinFootprintImage(foot, source, subTarget)
expected = np.zeros((100, 100))
expected[50, 50:55] = 1.0
self.assertTrue(np.all(target.getArray() == expected))
def testCopyWithinFootprintImage(self):
W,H = 10,10
dims = afwGeom.Extent2I(W,H)
source = afwImage.ImageF(dims)
dest = afwImage.ImageF(dims)
sa = source.getArray()
for i in range(H):
for j in range(W):
sa[i,j] = 100 * i + j
self.foot.addSpan(4, 3, 6)
self.foot.addSpan(5, 2, 4)
afwDetect.copyWithinFootprintImage(self.foot, source, dest)
da = dest.getArray()
self.assertEqual(da[4,2], 0)
self.assertEqual(da[4,3], 403)
self.assertEqual(da[4,4], 404)
self.assertEqual(da[4,5], 405)
self.assertEqual(da[4,6], 406)
self.assertEqual(da[4,7], 0)
self.assertEqual(da[5,1], 0)
self.assertEqual(da[5,2], 502)
self.assertEqual(da[5,3], 503)
self.assertEqual(da[5,4], 504)
self.assertEqual(da[5,5], 0)
self.assertTrue(numpy.all(da[:4,:] == 0))
self.assertTrue(numpy.all(da[6:,:] == 0))
def testCopyWithinFootprintImage(self):
W, H = 10, 10
dims = afwGeom.Extent2I(W, H)
source = afwImage.ImageF(dims)
dest = afwImage.ImageF(dims)
sa = source.getArray()
for i in range(H):
for j in range(W):
sa[i, j] = 100 * i + j
self.foot.addSpan(4, 3, 6)
self.foot.addSpan(5, 2, 4)
afwDetect.copyWithinFootprintImage(self.foot, source, dest)
da = dest.getArray()
self.assertEqual(da[4, 2], 0)
self.assertEqual(da[4, 3], 403)
self.assertEqual(da[4, 4], 404)
self.assertEqual(da[4, 5], 405)
self.assertEqual(da[4, 6], 406)
self.assertEqual(da[4, 7], 0)
self.assertEqual(da[5, 1], 0)
self.assertEqual(da[5, 2], 502)
self.assertEqual(da[5, 3], 503)
self.assertEqual(da[5, 4], 504)
self.assertEqual(da[5, 5], 0)
self.assertTrue(np.all(da[:4, :] == 0))
self.assertTrue(np.all(da[6:, :] == 0))
def foot_to_img(foot, img=None):
fimg = afwImage.ImageF(foot.getBBox())
fimg.getArray()[:, :] = np.nan
if foot.isHeavy():
foot.insert(fimg)
heavy = True
else:
if img is None:
return None, False
afwDet.copyWithinFootprintImage(foot, img, fimg)
# ia = img.getArray()
# fa = fimg.getArray()
# fbb = fimg.getBBox()
# fx0,fy0 = fbb.getMinX(), fbb.getMinY()
# ibb = img.getBBox()
# ix0,iy0 = ibb.getMinX(), ibb.getMinY()
# for span in foot.getSpans():
# y,x0,x1 = span.getY(), span.getX0(), span.getX1()
# # print 'Span', y, x0, x1
# # print 'img', ix0, iy0
# # print 'shape', ia[y - iy0, x0 - ix0: x1+1 - ix0].shape
# # print 'fimg', fx0, fy0,
# # print 'shape', fa[y - fy0, x0 - fx0: x1+1 - fx0].shape
# fa[y - fy0, x0 - fx0: x1+1 - fx0] = ia[y - iy0, x0 - ix0: x1+1 - ix0]
heavy = False
return fimg, heavy
def makeImage(footprint):
"""Make an ImageF with 1 in the footprint, and 0 elsewhere"""
ones = afwImage.ImageI(bbox)
ones.set(1)
image = afwImage.ImageI(bbox)
image.set(0)
afwDetect.copyWithinFootprintImage(footprint, ones, image)
return image
def makeImage(footprint):
"""Make an ImageF with 1 in the footprint, and 0 elsewhere"""
ones = afwImage.ImageI(bbox)
ones.set(1)
image = afwImage.ImageI(bbox)
image.set(0)
afwDetect.copyWithinFootprintImage(footprint, ones, image)
return image
def testCopyWithinFootprintOutside(self):
"""Copy a footprint that is larger than the image"""
target = afwImage.ImageF(100, 100)
target.set(0)
subTarget = afwImage.ImageF(target, afwGeom.Box2I(afwGeom.Point2I(40, 40), afwGeom.Extent2I(20, 20)))
source = afwImage.ImageF(10, 30)
source.setXY0(45, 45)
source.set(1.0)
foot = afwDetect.Footprint()
foot.addSpan(50, 50, 60) # Oversized on the source image, right; only some pixels overlap
foot.addSpan(60, 0, 100) # Oversized on the source, left and right; and on sub-target image, top
foot.addSpan(99, 0, 1000) # Oversized on the source image, top, left and right; aiming for segfault
afwDetect.copyWithinFootprintImage(foot, source, subTarget)
expected = numpy.zeros((100, 100))
expected[50,50:55] = 1.0
self.assertTrue(numpy.all(target.getArray() == expected))
def test1(self):
'''
In this test, we create a test image containing two blobs, one
of which is truncated by the edge of the image.
We run the detection code to get realistic peaks and
footprints.
We then test out the different edge treatments and assert that
they do what they claim. We also make plots, tests/edge*.png
'''
# Create fake image...
H,W = 100,100
fpbb = afwGeom.Box2I(afwGeom.Point2I(0,0),
afwGeom.Point2I(W-1,H-1))
afwimg = afwImage.MaskedImageF(fpbb)
imgbb = afwimg.getBBox()
img = afwimg.getImage().getArray()
var = afwimg.getVariance().getArray()
var[:,:] = 1.
blob_fwhm = 15.
blob_psf = doubleGaussianPsf(201, 201, blob_fwhm, 3.*blob_fwhm, 0.03)
fakepsf_fwhm = 5.
S = int(np.ceil(fakepsf_fwhm * 2.)) * 2 + 1
print 'S', S
fakepsf = gaussianPsf(S, S, fakepsf_fwhm)
# Create and save blob images, and add to image to deblend.
blobimgs = []
XY = [(50.,50.), (90.,50.)]
flux = 1e6
for x,y in XY:
bim = blob_psf.computeImage(afwGeom.Point2D(x, y))
bbb = bim.getBBox()
bbb.clip(imgbb)
bim = bim.Factory(bim, bbb)
bim2 = bim.getArray()
blobimg = np.zeros_like(img)
blobimg[bbb.getMinY():bbb.getMaxY()+1,
bbb.getMinX():bbb.getMaxX()+1] += flux * bim2
blobimgs.append(blobimg)
img[bbb.getMinY():bbb.getMaxY()+1,
bbb.getMinX():bbb.getMaxX()+1] += flux * bim2
# Run the detection code to get a ~ realistic footprint
thresh = afwDet.createThreshold(10., 'value', True)
fpSet = afwDet.FootprintSet(afwimg, thresh, 'DETECTED', 1)
fps = fpSet.getFootprints()
print 'found', len(fps), 'footprints'
# set EDGE bit on edge pixels.
margin = 5
lo = imgbb.getMin()
lo.shift(afwGeom.Extent2I(margin, margin))
hi = imgbb.getMax()
hi.shift(afwGeom.Extent2I(-margin, -margin))
goodbbox = afwGeom.Box2I(lo, hi)
print 'Good bbox for setting EDGE pixels:', goodbbox
print 'image bbox:', imgbb
edgebit = afwimg.getMask().getPlaneBitMask("EDGE")
print 'edgebit:', edgebit
measAlg.SourceDetectionTask.setEdgeBits(afwimg, goodbbox, edgebit)
if False:
plt.clf()
plt.imshow(afwimg.getMask().getArray(),
interpolation='nearest', origin='lower')
plt.colorbar()
plt.title('Mask')
plt.savefig('mask.png')
M = afwimg.getMask().getArray()
for bit in range(32):
mbit = (1 << bit)
if not np.any(M & mbit):
continue
plt.clf()
plt.imshow(M & mbit,
interpolation='nearest', origin='lower')
plt.colorbar()
plt.title('Mask bit %i (0x%x)' % (bit, mbit))
plt.savefig('mask-%02i.png' % bit)
for fp in fps:
print 'peaks:', len(fp.getPeaks())
for pk in fp.getPeaks():
print ' ', pk.getIx(), pk.getIy()
assert(len(fps) == 1)
fp = fps[0]
assert(len(fp.getPeaks()) == 2)
ima = dict(interpolation='nearest', origin='lower', #cmap='gray',
cmap='jet',
vmin=0, vmax=400)
for j,(tt,kwa) in enumerate([
('No edge treatment', dict()),
('Ramp by PSF', dict(rampFluxAtEdge=True)),
('No clip at edge', dict(patchEdges=True)),
]):
#print 'Deblending...'
deb = deblend(fp, afwimg, fakepsf, fakepsf_fwhm, verbose=True,
**kwa)
#print 'Result:', deb
#print len(deb.peaks), 'deblended peaks'
parent_img = afwImage.ImageF(fpbb)
afwDet.copyWithinFootprintImage(fp, afwimg.getImage(), parent_img)
X = [x for x,y in XY]
Y = [y for x,y in XY]
PX = [pk.getIx() for pk in fp.getPeaks()]
PY = [pk.getIy() for pk in fp.getPeaks()]
# Grab 1-d slices to make assertion about.
symms = []
monos = []
symm1ds = []
mono1ds = []
yslice = H/2
parent1d = img[yslice, :]
for i,dpk in enumerate(deb.peaks):
symm = dpk.origTemplate
symms.append(symm)
bbox = symm.getBBox()
x0,y0 = bbox.getMinX(), bbox.getMinY()
im = symm.getArray()
h,w = im.shape
oned = np.zeros(W)
oned[x0: x0+w] = im[yslice-y0, :]
symm1ds.append(oned)
mono = afwImage.ImageF(fpbb)
afwDet.copyWithinFootprintImage(dpk.templateFootprint,
dpk.templateImage, mono)
monos.append(mono)
im = mono.getArray()
bbox = mono.getBBox()
x0,y0 = bbox.getMinX(), bbox.getMinY()
h,w = im.shape
oned = np.zeros(W)
oned[x0: x0+w] = im[yslice-y0, :]
mono1ds.append(oned)
for i,(symm,mono) in enumerate(zip(symm1ds, mono1ds)):
# for the first two cases, the basic symmetric
# template for the second source drops to zero at <
# ~75 where the symmetric part is outside the
# footprint.
if i == 1 and j in [0,1]:
self.assertTrue(np.all(symm[:74] == 0))
if i == 1 and j == 2:
# For the third case, the 'symm' template gets
# "patched" with the parent's value
self.assertTrue(np.all((symm == parent1d)[:74]))
if i == 1 and j == 0:
# No edge handling: mono template == 0
self.assertTrue(np.all(mono[:74] == 0))
if i == 1 and j == 1:
# ramp by psf: zero up to ~65, ramps up
self.assertTrue(np.all(mono[:64] == 0))
self.assertTrue(np.any(mono[65:74] > 0))
self.assertTrue(np.all(np.diff(mono)[60:80] >= 0.))
if i == 1 and j == 2:
# no edge clipping: profile is monotonic and positive.
self.assertTrue(np.all(np.diff(mono)[:85] >= 0.))
self.assertTrue(np.all(mono[:85] > 0.))
if not doPlot:
continue
plt.clf()
p1 = plt.plot(parent1d, 'b-', lw=3, alpha=0.5)
for i,(symm,mono) in enumerate(zip(symm1ds, mono1ds)):
p2 = plt.plot(symm, 'r-', lw=2, alpha=0.7)
p3 = plt.plot(mono, 'g-')
plt.legend((p1[0],p2[0],p3[0]), ('Parent','Symm template', 'Mono template'),
loc='upper left')
plt.title('1-d slice: %s' % tt)
fn = plotpat % (2*j+0)
plt.savefig(fn)
print 'Wrote', fn
def myimshow(*args, **kwargs):
x0,x1,y0,y1 = imExt(afwimg)
plt.fill([x0,x0,x1,x1,x0],[y0,y1,y1,y0,y0], color=(1,1,0.8),
zorder=20)
plt.imshow(*args, zorder=25, **kwargs)
plt.xticks([]); plt.yticks([])
plt.axis(imExt(afwimg))
plt.clf()
pa = dict(color='m', marker='.', linestyle='None', zorder=30)
R,C = 3,6
plt.subplot(R, C, (2*C) + 1)
myimshow(img, **ima)
ax = plt.axis()
plt.plot(X, Y, **pa)
plt.axis(ax)
plt.title('Image')
plt.subplot(R, C, (2*C) + 2)
myimshow(parent_img.getArray(), **ima)
ax = plt.axis()
plt.plot(PX, PY, **pa)
plt.axis(ax)
plt.title('Footprint')
sumimg = None
for i,dpk in enumerate(deb.peaks):
plt.subplot(R, C, i*C + 1)
myimshow(blobimgs[i], **ima)
ax = plt.axis()
plt.plot(PX[i], PY[i], **pa)
plt.axis(ax)
plt.title('true')
plt.subplot(R, C, i*C + 2)
t = dpk.origTemplate
myimshow(t.getArray(), extent=imExt(t), **ima)
ax = plt.axis()
plt.plot(PX[i], PY[i], **pa)
plt.axis(ax)
plt.title('symm')
# monotonic template
mimg = afwImage.ImageF(fpbb)
afwDet.copyWithinFootprintImage(dpk.templateFootprint,
dpk.templateImage, mimg)
plt.subplot(R, C, i*C + 3)
myimshow(mimg.getArray(), extent=imExt(mimg), **ima)
ax = plt.axis()
plt.plot(PX[i], PY[i], **pa)
plt.axis(ax)
plt.title('monotonic')
plt.subplot(R, C, i*C + 4)
port = dpk.fluxPortion.getImage()
myimshow(port.getArray(), extent=imExt(port), **ima)
plt.title('portion')
ax = plt.axis()
plt.plot(PX[i], PY[i], **pa)
plt.axis(ax)
if dpk.strayFlux is not None:
simg = afwImage.ImageF(fpbb)
dpk.strayFlux.insert(simg)
plt.subplot(R, C, i*C + 5)
myimshow(simg.getArray(), **ima)
plt.title('stray')
ax = plt.axis()
plt.plot(PX, PY, **pa)
plt.axis(ax)
himg2 = afwImage.ImageF(fpbb)
portion = dpk.getFluxPortion()
portion.insert(himg2)
if sumimg is None:
sumimg = himg2.getArray().copy()
else:
sumimg += himg2.getArray()
plt.subplot(R, C, i*C + 6)
myimshow(himg2.getArray(), **ima)
plt.title('portion+stray')
ax = plt.axis()
plt.plot(PX, PY, **pa)
plt.axis(ax)
plt.subplot(R, C, (2*C) + C)
myimshow(sumimg, **ima)
ax = plt.axis()
plt.plot(X, Y, **pa)
plt.axis(ax)
plt.title('Sum of deblends')
plt.suptitle(tt)
fn = plotpat % (2*j + 1)
plt.savefig(fn)
print 'Wrote', fn
def test1(self):
'''
In this test, we create a test image containing two blobs, one
of which is truncated by the edge of the image.
We run the detection code to get realistic peaks and
footprints.
We then test out the different edge treatments and assert that
they do what they claim. We also make plots, tests/edge*.png
'''
# Create fake image...
H, W = 100, 100
fpbb = geom.Box2I(geom.Point2I(0, 0),
geom.Point2I(W-1, H-1))
afwimg = afwImage.MaskedImageF(fpbb)
imgbb = afwimg.getBBox()
img = afwimg.getImage().getArray()
var = afwimg.getVariance().getArray()
var[:, :] = 1.
blob_fwhm = 15.
blob_psf = doubleGaussianPsf(201, 201, blob_fwhm, 3.*blob_fwhm, 0.03)
fakepsf_fwhm = 5.
S = int(np.ceil(fakepsf_fwhm * 2.)) * 2 + 1
print('S', S)
fakepsf = gaussianPsf(S, S, fakepsf_fwhm)
# Create and save blob images, and add to image to deblend.
blobimgs = []
XY = [(50., 50.), (90., 50.)]
flux = 1e6
for x, y in XY:
bim = blob_psf.computeImage(geom.Point2D(x, y))
bbb = bim.getBBox()
bbb.clip(imgbb)
bim = bim.Factory(bim, bbb)
bim2 = bim.getArray()
blobimg = np.zeros_like(img)
blobimg[bbb.getMinY():bbb.getMaxY()+1,
bbb.getMinX():bbb.getMaxX()+1] += flux * bim2
blobimgs.append(blobimg)
img[bbb.getMinY():bbb.getMaxY()+1,
bbb.getMinX():bbb.getMaxX()+1] += flux * bim2
# Run the detection code to get a ~ realistic footprint
thresh = afwDet.createThreshold(10., 'value', True)
fpSet = afwDet.FootprintSet(afwimg, thresh, 'DETECTED', 1)
fps = fpSet.getFootprints()
print('found', len(fps), 'footprints')
# set EDGE bit on edge pixels.
margin = 5
lo = imgbb.getMin()
lo.shift(geom.Extent2I(margin, margin))
hi = imgbb.getMax()
hi.shift(geom.Extent2I(-margin, -margin))
goodbbox = geom.Box2I(lo, hi)
print('Good bbox for setting EDGE pixels:', goodbbox)
print('image bbox:', imgbb)
edgebit = afwimg.getMask().getPlaneBitMask("EDGE")
print('edgebit:', edgebit)
measAlg.SourceDetectionTask.setEdgeBits(afwimg, goodbbox, edgebit)
if False:
plt.clf()
plt.imshow(afwimg.getMask().getArray(),
interpolation='nearest', origin='lower')
plt.colorbar()
plt.title('Mask')
plt.savefig('mask.png')
M = afwimg.getMask().getArray()
for bit in range(32):
mbit = (1 << bit)
if not np.any(M & mbit):
continue
plt.clf()
plt.imshow(M & mbit,
interpolation='nearest', origin='lower')
plt.colorbar()
plt.title('Mask bit %i (0x%x)' % (bit, mbit))
plt.savefig('mask-%02i.png' % bit)
for fp in fps:
print('peaks:', len(fp.getPeaks()))
for pk in fp.getPeaks():
print(' ', pk.getIx(), pk.getIy())
assert(len(fps) == 1)
fp = fps[0]
assert(len(fp.getPeaks()) == 2)
ima = dict(interpolation='nearest', origin='lower', # cmap='gray',
cmap='jet',
vmin=0, vmax=400)
for j, (tt, kwa) in enumerate([
('No edge treatment', dict()),
('Ramp by PSF', dict(rampFluxAtEdge=True)),
('No clip at edge', dict(patchEdges=True)),
]):
# print 'Deblending...'
# Change verbose to False to quiet down the meas_deblender.baseline logger
deb = deblend(fp, afwimg, fakepsf, fakepsf_fwhm, verbose=True,
**kwa)
# print 'Result:', deb
# print len(deb.peaks), 'deblended peaks'
parent_img = afwImage.ImageF(fpbb)
fp.spans.copyImage(afwimg.getImage(), parent_img)
X = [x for x, y in XY]
Y = [y for x, y in XY]
PX = [pk.getIx() for pk in fp.getPeaks()]
PY = [pk.getIy() for pk in fp.getPeaks()]
# Grab 1-d slices to make assertion about.
symms = []
monos = []
symm1ds = []
mono1ds = []
yslice = H//2
parent1d = img[yslice, :]
for i, dpk in enumerate(deb.deblendedParents[0].peaks):
symm = dpk.origTemplate
symms.append(symm)
bbox = symm.getBBox()
x0, y0 = bbox.getMinX(), bbox.getMinY()
im = symm.getArray()
h, w = im.shape
oned = np.zeros(W)
oned[x0: x0+w] = im[yslice-y0, :]
symm1ds.append(oned)
mono = afwImage.ImageF(fpbb)
dpk.templateFootprint.spans.copyImage(dpk.templateImage, mono)
monos.append(mono)
im = mono.getArray()
bbox = mono.getBBox()
x0, y0 = bbox.getMinX(), bbox.getMinY()
h, w = im.shape
oned = np.zeros(W)
oned[x0: x0+w] = im[yslice-y0, :]
mono1ds.append(oned)
for i, (symm, mono) in enumerate(zip(symm1ds, mono1ds)):
# for the first two cases, the basic symmetric
# template for the second source drops to zero at <
# ~75 where the symmetric part is outside the
# footprint.
if i == 1 and j in [0, 1]:
self.assertFloatsEqual(symm[:74], 0.0)
if i == 1 and j == 2:
# For the third case, the 'symm' template gets
# "patched" with the parent's value
self.assertFloatsEqual(symm[:74], parent1d[:74])
if i == 1 and j == 0:
# No edge handling: mono template == 0
self.assertFloatsEqual(mono[:74], 0.0)
if i == 1 and j == 1:
# ramp by psf: zero up to ~65, ramps up
self.assertFloatsEqual(mono[:64], 0.0)
self.assertTrue(np.any(mono[65:74] > 0))
self.assertTrue(np.all(np.diff(mono)[60:80] >= 0.))
if i == 1 and j == 2:
# no edge clipping: profile is monotonic and positive.
self.assertTrue(np.all(np.diff(mono)[:85] >= 0.))
self.assertTrue(np.all(mono[:85] > 0.))
if not doPlot:
continue
plt.clf()
p1 = plt.plot(parent1d, 'b-', lw=3, alpha=0.5)
for i, (symm, mono) in enumerate(zip(symm1ds, mono1ds)):
p2 = plt.plot(symm, 'r-', lw=2, alpha=0.7)
p3 = plt.plot(mono, 'g-')
plt.legend((p1[0], p2[0], p3[0]), ('Parent', 'Symm template', 'Mono template'),
loc='upper left')
plt.title('1-d slice: %s' % tt)
fn = plotpat % (2*j+0)
plt.savefig(fn)
print('Wrote', fn)
def myimshow(*args, **kwargs):
x0, x1, y0, y1 = imExt(afwimg)
plt.fill([x0, x0, x1, x1, x0], [y0, y1, y1, y0, y0], color=(1, 1, 0.8),
zorder=20)
plt.imshow(*args, zorder=25, **kwargs)
plt.xticks([])
plt.yticks([])
plt.axis(imExt(afwimg))
plt.clf()
pa = dict(color='m', marker='.', linestyle='None', zorder=30)
R, C = 3, 6
plt.subplot(R, C, (2*C) + 1)
myimshow(img, **ima)
ax = plt.axis()
plt.plot(X, Y, **pa)
plt.axis(ax)
plt.title('Image')
plt.subplot(R, C, (2*C) + 2)
myimshow(parent_img.getArray(), **ima)
ax = plt.axis()
plt.plot(PX, PY, **pa)
plt.axis(ax)
plt.title('Footprint')
sumimg = None
for i, dpk in enumerate(deb.deblendedParents[0].peaks):
plt.subplot(R, C, i*C + 1)
myimshow(blobimgs[i], **ima)
ax = plt.axis()
plt.plot(PX[i], PY[i], **pa)
plt.axis(ax)
plt.title('true')
plt.subplot(R, C, i*C + 2)
t = dpk.origTemplate
myimshow(t.getArray(), extent=imExt(t), **ima)
ax = plt.axis()
plt.plot(PX[i], PY[i], **pa)
plt.axis(ax)
plt.title('symm')
# monotonic template
mimg = afwImage.ImageF(fpbb)
afwDet.copyWithinFootprintImage(dpk.templateFootprint,
dpk.templateImage, mimg)
plt.subplot(R, C, i*C + 3)
myimshow(mimg.getArray(), extent=imExt(mimg), **ima)
ax = plt.axis()
plt.plot(PX[i], PY[i], **pa)
plt.axis(ax)
plt.title('monotonic')
plt.subplot(R, C, i*C + 4)
port = dpk.fluxPortion.getImage()
myimshow(port.getArray(), extent=imExt(port), **ima)
plt.title('portion')
ax = plt.axis()
plt.plot(PX[i], PY[i], **pa)
plt.axis(ax)
if dpk.strayFlux is not None:
simg = afwImage.ImageF(fpbb)
dpk.strayFlux.insert(simg)
plt.subplot(R, C, i*C + 5)
myimshow(simg.getArray(), **ima)
plt.title('stray')
ax = plt.axis()
plt.plot(PX, PY, **pa)
plt.axis(ax)
himg2 = afwImage.ImageF(fpbb)
portion = dpk.getFluxPortion()
portion.insert(himg2)
if sumimg is None:
sumimg = himg2.getArray().copy()
else:
sumimg += himg2.getArray()
plt.subplot(R, C, i*C + 6)
myimshow(himg2.getArray(), **ima)
plt.title('portion+stray')
ax = plt.axis()
plt.plot(PX, PY, **pa)
plt.axis(ax)
plt.subplot(R, C, (2*C) + C)
myimshow(sumimg, **ima)
ax = plt.axis()
plt.plot(X, Y, **pa)
plt.axis(ax)
plt.title('Sum of deblends')
plt.suptitle(tt)
fn = plotpat % (2*j + 1)
plt.savefig(fn)
print('Wrote', fn)
def test1(self):
'''
A simple example: three overlapping blobs (detected as 1
footprint with three peaks). We artificially omit one of the
peaks, meaning that its flux is "stray". Assert that the
stray flux assigned to the other two peaks accounts for all
the flux in the parent.
'''
H,W = 100,100
fpbb = afwGeom.Box2I(afwGeom.Point2I(0,0),
afwGeom.Point2I(W-1,H-1))
afwimg = afwImage.MaskedImageF(fpbb)
imgbb = afwimg.getBBox(afwImage.PARENT)
img = afwimg.getImage().getArray()
var = afwimg.getVariance().getArray()
var[:,:] = 1.
blob_fwhm = 10.
blob_psf = doubleGaussianPsf(99, 99, blob_fwhm, 3.*blob_fwhm, 0.03)
fakepsf_fwhm = 3.
fakepsf = gaussianPsf(11, 11, fakepsf_fwhm)
blobimgs = []
x = 75.
XY = [(x,35.), (x,65.), (50.,50.)]
flux = 1e6
for x,y in XY:
bim = blob_psf.computeImage(afwGeom.Point2D(x, y))
bbb = bim.getBBox(afwImage.PARENT)
bbb.clip(imgbb)
bim = bim.Factory(bim, bbb, afwImage.PARENT)
bim2 = bim.getArray()
blobimg = np.zeros_like(img)
blobimg[bbb.getMinY():bbb.getMaxY()+1,
bbb.getMinX():bbb.getMaxX()+1] += flux * bim2
blobimgs.append(blobimg)
img[bbb.getMinY():bbb.getMaxY()+1,
bbb.getMinX():bbb.getMaxX()+1] += flux * bim2
# Run the detection code to get a ~ realistic footprint
thresh = afwDet.createThreshold(5., 'value', True)
fpSet = afwDet.FootprintSet(afwimg, thresh, 'DETECTED', 1)
fps = fpSet.getFootprints()
print 'found', len(fps), 'footprints'
pks2 = []
for fp in fps:
print 'peaks:', len(fp.getPeaks())
for pk in fp.getPeaks():
print ' ', pk.getIx(), pk.getIy()
pks2.append((pk.getIx(), pk.getIy()))
# The first peak in this list is the one we want to omit.
fp0 = fps[0]
fakefp = afwDet.Footprint(fp0.getSpans(), fp0.getBBox())
for pk in fp0.getPeaks()[1:]:
fakefp.getPeaks().append(pk)
ima = dict(interpolation='nearest', origin='lower', cmap='gray',
vmin=0, vmax=1e3)
if doPlot:
plt.figure(figsize=(12,6))
plt.clf()
plt.suptitle('strayFlux.py: test1 input')
plt.subplot(2,2,1)
plt.title('Image')
plt.imshow(img, **ima)
ax = plt.axis()
plt.plot([x for x,y in XY], [y for x,y in XY], 'r.')
plt.axis(ax)
for i,(b,(x,y)) in enumerate(zip(blobimgs, XY)):
plt.subplot(2,2, 2+i)
plt.title('Blob %i' % i)
plt.imshow(b, **ima)
ax = plt.axis()
plt.plot(x, y, 'r.')
plt.axis(ax)
plt.savefig(plotpat % 1)
deb = deblend(fakefp, afwimg, fakepsf, fakepsf_fwhm, verbose=True)
parent_img = afwImage.ImageF(fpbb)
afwDet.copyWithinFootprintImage(fakefp, afwimg.getImage(), parent_img)
if doPlot:
def myimshow(*args, **kwargs):
plt.imshow(*args, **kwargs)
plt.xticks([]); plt.yticks([])
plt.axis(imExt(afwimg))
plt.clf()
plt.suptitle('strayFlux.py: test1 results')
#R,C = 3,5
R,C = 3,4
plt.subplot(R, C, (2*C) + 1)
plt.title('Image')
myimshow(img, **ima)
ax = plt.axis()
plt.plot([x for x,y in XY], [y for x,y in XY], 'r.')
plt.axis(ax)
plt.subplot(R, C, (2*C) + 2)
plt.title('Parent footprint')
myimshow(parent_img.getArray(), **ima)
ax = plt.axis()
plt.plot([pk.getIx() for pk in fakefp.getPeaks()],
[pk.getIy() for pk in fakefp.getPeaks()], 'r.')
plt.axis(ax)
sumimg = None
for i,dpk in enumerate(deb.peaks):
plt.subplot(R, C, i*C + 1)
plt.title('ch%i symm' % i)
symm = dpk.templateImage
myimshow(symm.getArray(), extent=imExt(symm), **ima)
plt.subplot(R, C, i*C + 2)
plt.title('ch%i portion' % i)
port = dpk.fluxPortion.getImage()
myimshow(port.getArray(), extent=imExt(port), **ima)
himg = afwImage.ImageF(fpbb)
heavy = dpk.getFluxPortion(strayFlux=False)
heavy.insert(himg)
# plt.subplot(R, C, i*C + 3)
# plt.title('ch%i heavy' % i)
# myimshow(himg.getArray(), **ima)
# ax = plt.axis()
# plt.plot([x for x,y in XY], [y for x,y in XY], 'r.')
# plt.axis(ax)
simg = afwImage.ImageF(fpbb)
dpk.strayFlux.insert(simg)
plt.subplot(R, C, i*C + 3)
plt.title('ch%i stray' % i)
myimshow(simg.getArray(), **ima)
ax = plt.axis()
plt.plot([x for x,y in XY], [y for x,y in XY], 'r.')
plt.axis(ax)
himg2 = afwImage.ImageF(fpbb)
heavy = dpk.getFluxPortion(strayFlux=True)
heavy.insert(himg2)
if sumimg is None:
sumimg = himg2.getArray().copy()
else:
sumimg += himg2.getArray()
plt.subplot(R, C, i*C + 4)
myimshow(himg2.getArray(), **ima)
plt.title('ch%i total' % i)
ax = plt.axis()
plt.plot([x for x,y in XY], [y for x,y in XY], 'r.')
plt.axis(ax)
plt.subplot(R, C, (2*C) + C)
myimshow(sumimg, **ima)
ax = plt.axis()
plt.plot([x for x,y in XY], [y for x,y in XY], 'r.')
plt.axis(ax)
plt.title('Sum of deblends')
plt.savefig(plotpat % 2)
# Compute the sum-of-children image
sumimg = None
for i,dpk in enumerate(deb.peaks):
himg2 = afwImage.ImageF(fpbb)
dpk.getFluxPortion().insert(himg2)
if sumimg is None:
sumimg = himg2.getArray().copy()
else:
sumimg += himg2.getArray()
# Sum of children ~= Original image inside footprint (parent_img)
absdiff = np.max(np.abs(sumimg - parent_img.getArray()))
print 'Max abs diff:', absdiff
imgmax = parent_img.getArray().max()
print 'Img max:', imgmax
self.assertTrue(absdiff < imgmax * 1e-6)