def finalize(self, idFactory):
"""Finalize construction of the catalog.
Create a SourceCatalog from the MultiMatch object and compute the corresponding
merged footprint.
@param[in] idFactory Used to generate ids.
@return SourceCatalog of DIAObjects
"""
if self.multi_matches is None:
return None
schema = afwTable.SourceTable.makeMinimalSchema()
nobsKey = schema.addField("nobs",
type=np.int32,
doc='Number of times observed')
fluxKey = schema.addField("flux", type=float, doc='Average flux')
raKey = schema['coord_ra'].asKey()
decKey = schema['coord_dec'].asKey()
table = afwTable.SourceTable.make(schema, idFactory)
cat = afwTable.SourceCatalog(table)
results = self.multi_matches.finish(removeAmbiguous=False)
allMatches = afwTable.GroupView.build(results)
psfMagKey = allMatches.schema.find(self.config.fluxType).key
raKey = allMatches.schema.find("coord_ra").key
decKey = allMatches.schema.find("coord_dec").key
ave_ra = allMatches.aggregate(np.mean, field=raKey)
ave_dec = allMatches.aggregate(np.mean, field=decKey)
ave_flux = allMatches.aggregate(np.mean, field=psfMagKey)
# Merge the footprints from the same object together
object_ids = np.unique(results['object'])
footprints = []
for id in object_ids:
mask = results['object'] == id
footprint = None
for rec in results[mask]:
if footprint is None:
footprint = rec.getFootprint()
else:
footprint = afwDet.mergeFootprints(footprint,
rec.getFootprint())
footprints.append(footprint)
for i in range(len(ave_ra)):
rec = cat.addNew()
rec.setFootprint(footprints[i])
rec.set(raKey, ave_ra[i] * geom.radians)
rec.set(decKey, ave_dec[i] * geom.radians)
rec.set(fluxKey, ave_flux[i])
return cat
def testMergeFootprints(self):
f1 = self.foot
f2 = afwDetect.Footprint()
spanList1 = [(10, 10, 20), (10, 30, 40), (10, 50, 60), (11, 30, 50),
(12, 30, 50), (13, 10, 20), (13, 30, 40), (13, 50, 60),
(15, 10, 20), (15, 31, 40), (15, 51, 60)]
spanSet1 = afwGeom.SpanSet([afwGeom.Span(*span) for span in spanList1])
f1.spans = spanSet1
spanList2 = [(8, 10, 20), (9, 20, 30), (10, 0, 9), (10, 35, 65),
(10, 70, 80), (13, 49, 54), (14, 10, 30), (15, 21, 30),
(15, 41, 50), (15, 61, 70)]
spanSet2 = afwGeom.SpanSet([afwGeom.Span(*span) for span in spanList2])
f2.spans = spanSet2
fA = afwDetect.mergeFootprints(f1, f2)
fB = afwDetect.mergeFootprints(f2, f1)
ims = []
for i, f in enumerate([f1, f2, fA, fB]):
im1 = afwImage.ImageU(100, 100)
im1.set(0)
imbb = im1.getBBox()
f.setRegion(imbb)
f.spans.setImage(im1, 1)
ims.append(im1)
for i, merged in enumerate([ims[2], ims[3]]):
m = merged.getArray()
a1 = ims[0].getArray()
a2 = ims[1].getArray()
# Slightly looser tests to start...
# Every pixel in f1 is in f[AB]
self.assertTrue(np.all(m.flat[np.flatnonzero(a1)] == 1))
# Every pixel in f2 is in f[AB]
self.assertTrue(np.all(m.flat[np.flatnonzero(a2)] == 1))
# merged == a1 | a2.
self.assertTrue(np.all(m == np.maximum(a1, a2)))
def _fig8Test(self, x1, y1, x2, y2):
# Construct a "figure of 8" consisting of two circles touching at the
# centre of an image, then demonstrate that it shrinks correctly.
# (Helper method for tests below.)
radius = 3
imwidth, imheight = 100, 100
nshrink = 1
# These are the correct values for footprint sizes given the paramters
# above.
circle_npix = 29
initial_npix = circle_npix * 2 - 1 # touch at one pixel
shrunk_npix = 26
box = lsst.geom.Box2I(lsst.geom.Point2I(0, 0),
lsst.geom.Extent2I(imwidth, imheight))
e1 = afwGeom.Ellipse(afwGeomEllipses.Axes(radius, radius, 0),
lsst.geom.Point2D(x1, y1))
spanSet1 = afwGeom.SpanSet.fromShape(e1)
f1 = afwDetect.Footprint(spanSet1, box)
self.assertEqual(f1.getArea(), circle_npix)
e2 = afwGeom.Ellipse(afwGeomEllipses.Axes(radius, radius, 0),
lsst.geom.Point2D(x2, y2))
spanSet2 = afwGeom.SpanSet.fromShape(e2)
f2 = afwDetect.Footprint(spanSet2, box)
self.assertEqual(f2.getArea(), circle_npix)
initial = afwDetect.mergeFootprints(f1, f2)
initial.setRegion(
f2.getRegion()) # merge does not propagate the region
self.assertEqual(initial_npix, initial.getArea())
shrunk = afwDetect.Footprint().assign(initial)
shrunk.erode(nshrink)
self.assertEqual(shrunk_npix, shrunk.getArea())
if display:
idImage = afwImage.ImageU(imwidth, imheight)
for i, foot in enumerate([initial, shrunk]):
print(foot.getArea())
foot.spans.setImage(idImage, i + 1)
afwDisplay.Display(frame=1).mtv(idImage,
title=self._testMethodName +
" image")
def _fig8Test(self, x1, y1, x2, y2):
# Construct a "figure of 8" consisting of two circles touching at the
# centre of an image, then demonstrate that it shrinks correctly.
# (Helper method for tests below.)
radius = 3
imwidth, imheight = 100, 100
nshrink = 1
# These are the correct values for footprint sizes given the paramters
# above.
circle_npix = 29
initial_npix = circle_npix * 2 - 1 # touch at one pixel
shrunk_npix = 26
box = afwGeom.Box2I(afwGeom.Point2I(0, 0),
afwGeom.Extent2I(imwidth, imheight))
e1 = afwGeomEllipses.Ellipse(afwGeomEllipses.Axes(radius, radius, 0),
afwGeom.Point2D(x1, y1))
f1 = afwDetect.Footprint(e1, box)
self.assertEqual(f1.getNpix(), circle_npix)
e2 = afwGeomEllipses.Ellipse(afwGeomEllipses.Axes(radius, radius, 0),
afwGeom.Point2D(x2, y2))
f2 = afwDetect.Footprint(e2, box)
self.assertEqual(f2.getNpix(), circle_npix)
initial = afwDetect.mergeFootprints(f1, f2)
initial.setRegion(
f2.getRegion()) # merge does not propagate the region
self.assertEqual(initial_npix, initial.getNpix())
shrunk = afwDetect.shrinkFootprint(initial, nshrink, True)
self.assertEqual(shrunk_npix, shrunk.getNpix())
if display:
idImage = afwImage.ImageU(imwidth, imheight)
for i, foot in enumerate([initial, shrunk]):
print(foot.getNpix())
foot.insertIntoImage(idImage, i + 1)
ds9.mtv(idImage)
def _fig8Test(self, x1, y1, x2, y2):
# Construct a "figure of 8" consisting of two circles touching at the
# centre of an image, then demonstrate that it shrinks correctly.
# (Helper method for tests below.)
radius = 3
imwidth, imheight = 100, 100
nshrink = 1
# These are the correct values for footprint sizes given the paramters
# above.
circle_npix = 29
initial_npix = circle_npix * 2 - 1 # touch at one pixel
shrunk_npix = 26
box = afwGeom.Box2I(afwGeom.Point2I(0, 0), afwGeom.Extent2I(imwidth, imheight))
e1 = afwGeomEllipses.Ellipse(afwGeomEllipses.Axes(radius, radius, 0),
afwGeom.Point2D(x1, y1))
f1 = afwDetect.Footprint(e1,box)
self.assertEqual(f1.getNpix(), circle_npix)
e2 = afwGeomEllipses.Ellipse(afwGeomEllipses.Axes(radius, radius, 0),
afwGeom.Point2D(x2, y2))
f2 = afwDetect.Footprint(e2,box)
self.assertEqual(f2.getNpix(), circle_npix)
initial = afwDetect.mergeFootprints(f1, f2)
initial.setRegion(f2.getRegion()) # merge does not propagate the region
self.assertEqual(initial_npix, initial.getNpix())
shrunk = afwDetect.shrinkFootprint(initial, nshrink, True)
self.assertEqual(shrunk_npix, shrunk.getNpix())
if display:
idImage = afwImage.ImageU(imwidth, imheight)
for i, foot in enumerate([initial, shrunk]):
print foot.getNpix()
foot.insertIntoImage(idImage, i+1);
ds9.mtv(idImage)
def testMergeFootprints(self):
f1 = self.foot
f2 = afwDetect.Footprint()
f1.addSpan(10, 10, 20)
f1.addSpan(10, 30, 40)
f1.addSpan(10, 50, 60)
f1.addSpan(11, 30, 50)
f1.addSpan(12, 30, 50)
f1.addSpan(13, 10, 20)
f1.addSpan(13, 30, 40)
f1.addSpan(13, 50, 60)
f1.addSpan(15, 10, 20)
f1.addSpan(15, 31, 40)
f1.addSpan(15, 51, 60)
f2.addSpan(8, 10, 20)
f2.addSpan(9, 20, 30)
f2.addSpan(10, 0, 9)
f2.addSpan(10, 35, 65)
f2.addSpan(10, 70, 80)
f2.addSpan(13, 49, 54)
f2.addSpan(14, 10, 30)
f2.addSpan(15, 21, 30)
f2.addSpan(15, 41, 50)
f2.addSpan(15, 61, 70)
f1.normalize()
f2.normalize()
fA = afwDetect.mergeFootprints(f1, f2)
fB = afwDetect.mergeFootprints(f2, f1)
ims = []
for i, f in enumerate([f1, f2, fA, fB]):
im1 = afwImage.ImageU(100, 100)
im1.set(0)
imbb = im1.getBBox()
f.setRegion(imbb)
f.insertIntoImage(im1, 1)
ims.append(im1)
for i, merged in enumerate([ims[2], ims[3]]):
m = merged.getArray()
a1 = ims[0].getArray()
a2 = ims[1].getArray()
# Slightly looser tests to start...
# Every pixel in f1 is in f[AB]
self.assertTrue(np.all(m.flat[np.flatnonzero(a1)] == 1))
# Every pixel in f2 is in f[AB]
self.assertTrue(np.all(m.flat[np.flatnonzero(a2)] == 1))
# merged == a1 | a2.
self.assertTrue(np.all(m == np.maximum(a1, a2)))
if False:
import matplotlib
matplotlib.use('Agg')
import pylab as plt
plt.clf()
for i, im1 in enumerate(ims):
plt.subplot(4, 1, i + 1)
plt.imshow(im1.getArray(),
interpolation='nearest',
origin='lower')
plt.axis([0, 100, 0, 20])
plt.savefig('merge2.png')
def finalize(self, idFactory):
"""Finalize construction of the catalog.
Create a SourceCatalog from the MultiMatch object and compute the corresponding
merged footprint.
@param[in] idFactory Used to generate ids.
@return SourceCatalog of DIAObjects
"""
if self.multi_matches is None:
return None
schema = afwTable.SourceTable.makeMinimalSchema()
nobsKey = schema.addField("nobs",
type=np.int32,
doc='Number of times observed')
keys = {}
for filter in self.config.filters:
flux = self.config.fluxType
keys[f'{flux}_Mean_{filter}'] = schema.addField(
f"{flux}_Mean_{filter}",
type=float,
doc=f'Mean {flux} in filter {filter}')
keys[f'{flux}_MeanErr_{filter}'] = schema.addField(
f"{flux}_MeanErr_{filter}",
type=float,
doc=f'MeanErr {flux} in filter {filter}')
keys[f'{flux}_Sigma_{filter}'] = schema.addField(
f"{flux}_Sigma_{filter}",
type=float,
doc=f'Sigma {flux} in filter {filter}')
keys[f'{flux}_Ndata_{filter}'] = schema.addField(
f"{flux}_NData_{filter}",
type=np.int32,
doc=f'Number of observations in filter {filter}')
keys[f'{flux}_Chi2_{filter}'] = schema.addField(
f"{flux}_Chi2_{filter}",
type=float,
doc=f'Chi2 of {flux} for {filter}')
raKey = schema['coord_ra'].asKey()
decKey = schema['coord_dec'].asKey()
table = afwTable.SourceTable.make(schema, idFactory)
cat = afwTable.SourceCatalog(table)
results = self.multi_matches.finish(removeAmbiguous=False)
allMatches = afwTable.GroupView.build(results)
raKey = allMatches.schema.find("coord_ra").key
decKey = allMatches.schema.find("coord_dec").key
ave_ra = allMatches.aggregate(np.mean, field=raKey)
ave_dec = allMatches.aggregate(np.mean, field=decKey)
# Merge the footprints from the same object together and accumulate
# information
object_ids = np.unique(results['object'])
footprints = []
all_fluxes = []
all_flux_errs = []
num_nobs = []
self.diaSrcIds = []
self.diaObjectIds = []
for id in object_ids:
mask = results['object'] == id
num_nobs.append(np.sum(mask))
footprint = None
src_ids = []
fluxes = defaultdict(list)
flux_errs = defaultdict(list)
for rec in results[mask]:
if footprint is None:
footprint = rec.getFootprint()
else:
footprint = afwDet.mergeFootprints(footprint,
rec.getFootprint())
src_ids.append(rec.get('id'))
flux = rec.get(self.config.fluxType)
if np.isfinite(flux) is False:
continue
filter = self.config.filters[rec.get('filter')]
calib = self.calibDict[rec.get('visit')][rec.get('ccd')]
flux_err = rec.get(self.config.fluxType + "Err")
new_val, new_val_err = scaleFlux(flux, flux_err, calib,
self.calib)
fluxes[filter].append(new_val)
flux_errs[filter].append(new_val_err)
self.diaSrcIds.append(src_ids)
footprints.append(footprint)
all_fluxes.append(fluxes)
all_flux_errs.append(flux_errs)
for i in range(len(ave_ra)):
rec = cat.addNew()
self.diaObjectIds.append(rec.get('id'))
rec.setFootprint(footprints[i])
rec.set(raKey, ave_ra[i] * geom.radians)
rec.set(decKey, ave_dec[i] * geom.radians)
rec.set(nobsKey, num_nobs[i])
for filter in self.config.filters:
fluxes = np.array(all_fluxes[i][filter])
if len(fluxes) == 0:
continue
flux_errs = np.array(all_flux_errs[i][filter])
flux = self.config.fluxType
rec.set(keys[f'{flux}_Mean_{filter}'], np.mean(fluxes))
rec.set(keys[f'{flux}_Sigma_{filter}'], np.std(fluxes, ddof=1))
rec.set(keys[f'{flux}_Ndata_{filter}'], len(fluxes))
rec.set(
keys[f'{flux}_MeanErr_{filter}'],
rec.get(f'{flux}_Sigma_{filter}') / np.sqrt(len(fluxes)))
residuals = fluxes - rec.get(keys[f'{flux}_Mean_{filter}'])
rec.set(keys[f'{flux}_Chi2_{filter}'],
np.sum((residuals / flux_errs)**2))
return cat
def testMergeFootprints(self):
f1 = self.foot
f2 = afwDetect.Footprint()
f1.addSpan(10, 10, 20)
f1.addSpan(10, 30, 40)
f1.addSpan(10, 50, 60)
f1.addSpan(11, 30, 50)
f1.addSpan(12, 30, 50)
f1.addSpan(13, 10, 20)
f1.addSpan(13, 30, 40)
f1.addSpan(13, 50, 60)
f1.addSpan(15, 10,20)
f1.addSpan(15, 31,40)
f1.addSpan(15, 51,60)
f2.addSpan(8, 10, 20)
f2.addSpan(9, 20, 30)
f2.addSpan(10, 0, 9)
f2.addSpan(10, 35, 65)
f2.addSpan(10, 70, 80)
f2.addSpan(13, 49, 54)
f2.addSpan(14, 10, 30)
f2.addSpan(15, 21,30)
f2.addSpan(15, 41,50)
f2.addSpan(15, 61,70)
f1.normalize()
f2.normalize()
fA = afwDetect.mergeFootprints(f1, f2)
fB = afwDetect.mergeFootprints(f2, f1)
ims = []
for i,f in enumerate([f1,f2,fA,fB]):
im1 = afwImage.ImageU(100, 100)
im1.set(0)
imbb = im1.getBBox()
f.setRegion(imbb)
f.insertIntoImage(im1, 1)
ims.append(im1)
for i,merged in enumerate([ims[2],ims[3]]):
m = merged.getArray()
a1 = ims[0].getArray()
a2 = ims[1].getArray()
# Slightly looser tests to start...
# Every pixel in f1 is in f[AB]
self.assertTrue(numpy.all(m.flat[numpy.flatnonzero(a1)] == 1))
# Every pixel in f2 is in f[AB]
self.assertTrue(numpy.all(m.flat[numpy.flatnonzero(a2)] == 1))
# merged == a1 | a2.
self.assertTrue(numpy.all(m == numpy.maximum(a1, a2)))
if False:
import matplotlib
matplotlib.use('Agg')
import pylab as plt
plt.clf()
for i,im1 in enumerate(ims):
plt.subplot(4,1, i+1)
plt.imshow(im1.getArray(), interpolation='nearest', origin='lower')
plt.axis([0, 100, 0, 20])
plt.savefig('merge2.png')