def testBin(self):
"""Test that we can bin images anisotropically"""
inImage = afwImage.ImageF(203, 131)
val = 1
inImage.set(val)
binX, binY = 2, 4
outImage = afwMath.binImage(inImage, binX, binY)
self.assertEqual(outImage.getWidth(), inImage.getWidth()//binX)
self.assertEqual(outImage.getHeight(), inImage.getHeight()//binY)
stats = afwMath.makeStatistics(outImage, afwMath.MAX | afwMath.MIN)
self.assertEqual(stats.getValue(afwMath.MIN), val)
self.assertEqual(stats.getValue(afwMath.MAX), val)
inImage.set(0)
subImg = inImage.Factory(inImage, afwGeom.BoxI(afwGeom.PointI(4, 4), afwGeom.ExtentI(4, 8)),
afwImage.LOCAL)
subImg.set(100)
del subImg
outImage = afwMath.binImage(inImage, binX, binY)
if display:
ds9.mtv(inImage, frame=2, title="unbinned")
ds9.mtv(outImage, frame=3, title="binned %dx%d" % (binX, binY))
def testImageSlices(self):
"""Test image slicing, which generate sub-images using Box2I under the covers"""
im = afwImage.ImageF(10, 20)
im[-1, :] = -5
im[..., 18] = -5 # equivalent to im[:, 18]
im[4, 10] = 10
im[-3:, -2:] = 100
im[-2, -2] = -10
sim = im[1:4, 6:10]
sim[:] = -1
im[0:4, 0:4] = im[2:6, 8:12]
if display:
ds9.mtv(im)
self.assertEqual(im.get(0, 6), 0)
self.assertEqual(im.get(9, 15), -5)
self.assertEqual(im.get(5, 18), -5)
self.assertEqual(im.get(6, 17), 0)
self.assertEqual(im.get(7, 18),100)
self.assertEqual(im.get(9, 19),100)
self.assertEqual(im.get(8, 18),-10)
self.assertEqual(im.get(1, 6), -1)
self.assertEqual(im.get(3, 9), -1)
self.assertEqual(im.get(4, 10), 10)
self.assertEqual(im.get(4, 9), 0)
self.assertEqual(im.get(2, 2), 10)
self.assertEqual(im.get(0, 0), -1)
def checkCandidateMasking(self, badPixels, extraPixels=[], size=25, threshold=0.1, pixelThreshold=0.0):
"""Check that candidates are masked properly
We add various pixels to the image and investigate the masking.
@param badPixels: (x,y,flux) triplet of pixels that should be masked
@param extraPixels: (x,y,flux) triplet of additional pixels to add to image
@param size: Size of candidate
@param threshold: Threshold for creating footprints on image
@param pixelThreshold: Threshold for masking pixels on candidate
"""
image = self.exp.getMaskedImage().getImage()
for x,y,f in badPixels + extraPixels:
image[x,y] = f
cand = self.createCandidate(threshold=threshold)
oldPixelThreshold = cand.getPixelThreshold()
try:
cand.setPixelThreshold(pixelThreshold)
candImage = cand.getMaskedImage(size, size)
mask = candImage.getMask()
if display:
ds9.mtv(candImage, frame=2)
ds9.mtv(candImage.getMask().convertU(), frame=3)
detected = mask.getMaskPlane("DETECTED")
intrp = mask.getMaskPlane("INTRP")
for x,y,f in badPixels:
x -= self.x - size//2
y -= self.y - size//2
self.assertTrue(mask.get(x, y, intrp))
self.assertFalse(mask.get(x, y, detected))
finally:
# Ensure this static variable is reset
cand.setPixelThreshold(oldPixelThreshold)
def testSingleExposure(self):
policyFile = pexPolicy.DefaultPolicyFile("ip_pipeline",
"DiffImStageDictionary.paf", "policy")
policy = pexPolicy.Policy.createPolicy(policyFile, policyFile.getRepositoryPath(), True)
self.subBackground(policy.get("diffImPolicy").get("backgroundPolicy"))
stage = ipPipe.DiffImStage(policy)
tester = SimpleStageTester(stage)
#print policy
clipboard = pexClipboard.Clipboard()
clipboard.put(policy.get("inputKeys.templateExposureKey"), self.templateExposure)
clipboard.put(policy.get("inputKeys.scienceExposureKey"), self.scienceExposure)
outWorker = tester.runWorker(clipboard)
outPolicy = policy.get("outputKeys")
#print outPolicy
self.assertTrue(outWorker.contains(outPolicy.get("differenceExposureKey")))
self.assertTrue(outWorker.contains(outPolicy.get("psfMatchingKernelKey")))
self.assertTrue(outWorker.contains(outPolicy.get("backgroundFunctionKey")))
# also check types
diffExposure = outWorker.get(outPolicy.get("differenceExposureKey"))
matchingKernel = outWorker.get(outPolicy.get("psfMatchingKernelKey"))
background = outWorker.get(outPolicy.get("backgroundFunctionKey"))
self.assertTrue(isinstance(diffExposure, afwImage.ExposureF))
self.assertTrue(isinstance(matchingKernel, afwMath.LinearCombinationKernel))
self.assertTrue(isinstance(background, afwMath.Function2D))
if display:
ds9.mtv(outWorker.get(outPolicy.get("differenceExposureKey")), frame=5)
def readSExtractor(filename):
with pyfits.open(filename) as pf:
for hdu in pf:
if hdu.name == "PRIMARY":
pass
elif hdu.name == "LDAC_IMHEAD":
hdr = hdu.data[0][0] # the fits header from the original fits image
print hdr[3]
elif hdu.name == "LDAC_OBJECTS":
print "%d objects" % (len(hdu.data))
# Find the VIGNET column
ttype = [k for k, v in hdu.header.items() if v == "VIGNET"]
if not ttype:
raise RuntimeError("Unable to find a VIGNET column")
vignetCol = int(re.search(r"^TTYPE(\d+)$", ttype[0]).group(1)) - 1
for row in range(len(hdu.data)):
pixelData = hdu.data[row][vignetCol]
bad = np.where(pixelData < -1e29)
sat = np.where(pixelData > 99e3)
pixelData[bad] = 0.0
mi = afwImage.MaskedImageF(*hdu.data[row][vignetCol].shape)
im = mi.getImage()
im.getArray()[:] = pixelData
msk = mi.getMask().getArray()
msk[bad] = afwImage.MaskU.getPlaneBitMask("BAD")
msk[sat] = afwImage.MaskU.getPlaneBitMask("SAT")
ds9.mtv(mi, title=row)
raw_input("Next ")
def testKernelPsf(self):
"""Test creating a Psf from a Kernel"""
x,y = 10.4999, 10.4999
ksize = 15
sigma1 = 1
#
# Make a PSF from that kernel
#
kPsf = measAlg.KernelPsf(afwMath.AnalyticKernel(ksize, ksize,
afwMath.GaussianFunction2D(sigma1, sigma1)))
kIm = kPsf.computeImage(afwGeom.Point2D(x, y))
#
# And now via the dgPsf model
#
dgPsf = measAlg.DoubleGaussianPsf(ksize, ksize, sigma1)
dgIm = dgPsf.computeImage(afwGeom.Point2D(x, y))
#
# Check that they're the same
#
diff = type(kIm)(kIm, True); diff -= dgIm
stats = afwMath.makeStatistics(diff, afwMath.MAX | afwMath.MIN)
self.assertAlmostEqual(stats.getValue(afwMath.MAX), 0.0, places=16)
self.assertAlmostEqual(stats.getValue(afwMath.MIN), 0.0, places=16)
if display:
mos = displayUtils.Mosaic()
mos.setBackground(-0.1)
ds9.mtv(mos.makeMosaic([kIm, dgIm, diff], mode="x"), frame=1)
def testCFHT_oldAPI(self):
"""Test background subtraction on some real CFHT data"""
afwdataDir = eups.productDir("afwdata")
if not afwdataDir:
print >> sys.stderr, "Skipping testCFHT as afwdata is not setup"
return
mi = afwImage.MaskedImageF(os.path.join(afwdataDir,
"CFHT", "D4", "cal-53535-i-797722_1"))
mi = mi.Factory(mi, afwGeom.Box2I(afwGeom.Point2I(32, 2), afwGeom.Point2I(2079, 4609)), afwImage.LOCAL)
bctrl = afwMath.BackgroundControl(afwMath.Interpolate.AKIMA_SPLINE)
bctrl.setNxSample(16)
bctrl.setNySample(16)
bctrl.getStatisticsControl().setNumSigmaClip(3.0)
bctrl.getStatisticsControl().setNumIter(2)
backobj = afwMath.makeBackground(mi.getImage(), bctrl)
if display:
ds9.mtv(mi, frame = 0)
im = mi.getImage()
im -= backobj.getImageF()
if display:
ds9.mtv(mi, frame = 1)
def saveSpatialCellSet(psfCellSet, fileName="foo.fits", frame=None):
"""Write the contents of a SpatialCellSet to a many-MEF fits file"""
mode = "w"
for cell in psfCellSet.getCellList():
for cand in cell.begin(False): # include bad candidates
cand = algorithmsLib.cast_PsfCandidateF(cand)
dx = afwImage.positionToIndex(cand.getXCenter(), True)[1]
dy = afwImage.positionToIndex(cand.getYCenter(), True)[1]
im = afwMath.offsetImage(cand.getMaskedImage(), -dx, -dy, "lanczos5")
md = dafBase.PropertySet()
md.set("CELL", cell.getLabel())
md.set("ID", cand.getId())
md.set("XCENTER", cand.getXCenter())
md.set("YCENTER", cand.getYCenter())
md.set("BAD", cand.isBad())
md.set("AMPL", cand.getAmplitude())
md.set("FLUX", cand.getSource().getPsfFlux())
md.set("CHI2", cand.getSource().getChi2())
im.writeFits(fileName, md, mode)
mode = "a"
if frame is not None:
ds9.mtv(im, frame=frame)
def showAmp(amp, imageSource=FakeImageDataSource(isTrimmed=False), frame=None, overlay=True, imageFactory=afwImage.ImageU):
"""!Show an amp in a ds9 frame
@param[in] amp amp record to use in display
@param[in] imageSource Source for getting the amp image. Must have a getAmpImage method.
@param[in] frame ds9 frame to display on; defaults to frame zero
@param[in] overlay Overlay bounding boxes?
@param[in] imageFactory Type of image to display (only used if ampImage is None)
"""
ampImage = imageSource.getAmpImage(amp, imageFactory=imageFactory)
ampImSize = ampImage.getDimensions()
title = amp.getName()
ds9.mtv(ampImage, frame=frame, title=title)
if overlay:
with ds9.Buffering():
if amp.getHasRawInfo() and ampImSize == amp.getRawBBox().getDimensions():
bboxes = [(amp.getRawBBox(), 0.49, ds9.GREEN),]
xy0 = bboxes[0][0].getMin()
bboxes.append((amp.getRawHorizontalOverscanBBox(), 0.49, ds9.RED))
bboxes.append((amp.getRawDataBBox(), 0.49, ds9.BLUE))
bboxes.append((amp.getRawPrescanBBox(), 0.49, ds9.YELLOW))
bboxes.append((amp.getRawVerticalOverscanBBox(), 0.49, ds9.MAGENTA))
else:
bboxes = [(amp.getBBox(), 0.49, None),]
xy0 = bboxes[0][0].getMin()
for bbox, borderWidth, ctype in bboxes:
if bbox.isEmpty():
continue
bbox = afwGeom.Box2I(bbox)
bbox.shift(-afwGeom.ExtentI(xy0))
displayUtils.drawBBox(bbox, borderWidth=borderWidth, ctype=ctype, frame=frame)
def main(rootDir, visit, ccd, frame=1, title="", scale="zscale", zoom="to fit", trans=60, useEllipse=False):
# make a butler and specify your dataId
butler = dafPersist.Butler(rootDir)
dataId = {'visit': visit, 'ccd':ccd}
# get the exposure from the butler
exposure = butler.get('calexp', dataId)
# put the settings in a dict object and call ds9.mtv()
settings = {'scale':scale, 'zoom': zoom, 'mask' : 'transparency %d' %(trans)}
ds9.mtv(exposure, frame=frame, title=title, settings=settings)
# now get the source catalog and overplot the points
sources = butler.get('src', dataId)
with ds9.Buffering():
for i,source in enumerate(sources):
color = ds9.RED
size = 5.0
if useEllipse:
# show an ellipse symbol
symbol = "@:{ixx},{ixy},{iyy}".format(ixx=source.getIxx(),
ixy=source.getIxy(),
iyy=source.getIyy())
else:
# just a simple point (symbols +, x, *, o are all accepted)
symbol = "o"
ds9.dot(symbol, source.getX(), source.getY(), ctype=color,
size=size, frame=frame, silent=True)
def testGetImage(self):
"""Test returning a realisation of the dgPsf"""
xcen = self.psf.getKernel().getWidth()//2
ycen = self.psf.getKernel().getHeight()//2
stamps = []
trueCenters = []
for x, y in ([10, 10], [9.4999, 10.4999], [10.5001, 10.5001]):
fx, fy = x - int(x), y - int(y)
if fx >= 0.5:
fx -= 1.0
if fy >= 0.5:
fy -= 1.0
im = self.psf.computeImage(afwGeom.Point2D(x, y)).convertF()
stamps.append(im.Factory(im, True))
trueCenters.append([xcen + fx, ycen + fy])
if display:
mos = displayUtils.Mosaic() # control mosaics
ds9.mtv(mos.makeMosaic(stamps))
for i in range(len(trueCenters)):
bbox = mos.getBBox(i)
ds9.dot("+",
bbox.getMinX() + xcen, bbox.getMinY() + ycen, ctype = ds9.RED, size = 1)
ds9.dot("+",
bbox.getMinX() + trueCenters[i][0], bbox.getMinY() + trueCenters[i][1])
ds9.dot("%.2f, %.2f" % (trueCenters[i][0], trueCenters[i][1]),
bbox.getMinX() + xcen, bbox.getMinY() + 2)
def showCcd(ccd, imageSource=FakeImageDataSource(), frame=None, overlay=True, imageFactory=afwImage.ImageU, binSize=1, inCameraCoords=False):
"""!Show a CCD on ds9
@param[in] ccd Detector to use in display
@param[in] imageSource Source for producing images to display. Must have a getCcdImage method.
@param[in] frame ds9 frame to use, defaults to frame zero
@param[in] overlay Show amp bounding boxes on the displayed image?
@param[in] imageFactory The image factory to use in generating the images.
@param[in] binSize Binning factor
@param[in] inCameraCoords Show the Detector in camera coordinates?
"""
ccdOrigin = afwGeom.Point2I(0,0)
nQuarter = 0
ccdImage = imageSource.getCcdImage(ccd, imageFactory=imageFactory, binSize=binSize)
ccdBbox = ccdImage.getBBox()
if ccdBbox.getDimensions() == ccd.getBBox().getDimensions():
isTrimmed = True
else:
isTrimmed = False
if inCameraCoords:
nQuarter = ccd.getOrientation().getNQuarter()
ccdImage = afwMath.rotateImageBy90(ccdImage, nQuarter)
title = ccd.getName()
if isTrimmed:
title += "(trimmed)"
ds9.mtv(ccdImage, frame=frame, title=title)
if overlay:
overlayCcdBoxes(ccd, ccdBbox, nQuarter, isTrimmed, ccdOrigin, frame, binSize)
def testSingleExposure(self):
file = pexPolicy.DefaultPolicyFile("meas_pipeline",
"backgroundEstimation_policy.paf", "tests")
policy = pexPolicy.Policy.createPolicy(file)
stage = measPipe.BackgroundEstimationStage(policy)
tester = SimpleStageTester(stage)
clipboard = pexClipboard.Clipboard()
clipboard.put(policy.get("inputKeys.exposure"), self.exposure)
if display:
ds9.mtv(self.exposure, frame=0, title="Input")
#
# Do the work
#
outWorker = tester.runWorker(clipboard)
outPolicy = policy.get("outputKeys")
assert(outWorker.contains(outPolicy.get("backgroundSubtractedExposure")))
assert(outWorker.contains(outPolicy.get("background")))
if display:
ds9.mtv(outWorker.get(outPolicy.get("backgroundSubtractedExposure")),
frame=1, title="Subtracted")
def getMosaic(sources, exposure, idname):
"""
make a ds9 mosaic for the given source list from the given exposure
stolen from psfMosaic.py on the sphinx documentation
"""
img = exposure.getMaskedImage().getImage()
subImages=[]
labels = []
for src in sources:
footBBox = src.getFootprint().getBBox()
subimg = lsst.afw.image.ImageF(img, footBBox,
lsst.afw.image.PARENT, True)
footMask = lsst.afw.image.ImageU(footBBox)
src.getFootprint().insertIntoImage(footMask, 1, footBBox)
subimg *= footMask.convertF()
subImages.append(subimg)
labels.append('ID=%s'%str(src.get(idname)))
m = lsst.afw.display.utils.Mosaic()
m.setGutter(2)
m.setBackground(0)
m.setMode("square")
# create the mosaic
for img in subImages:
m.append(img)
mosaic = m.makeMosaic()
# display it with labels in ds9
ds9.mtv(mosaic)
m.drawLabels(labels)
def testComputeImage(self):
"""Test the computation of the PSF's image at a point"""
ccdXY = afwGeom.Point2D(0, 0)
kIm = self.psf.computeImage(ccdXY)
if False:
ds9.mtv(kIm)
self.assertTrue(kIm.getWidth() == self.ksize)
#
# Check that the image is as expected.
#
xcen, ycen = self.ksize/2, self.ksize/2
I0 = kIm.get(xcen, ycen)
self.assertAlmostEqual(kIm.get(xcen + 1, ycen + 1),
I0*self.psf.computeImage().get(xcen + 1, ycen + 1))
#
# Is image normalised to a peak value of unity?
#
self.assertAlmostEqual(afwMath.makeStatistics(kIm, afwMath.MAX).getValue(), 1.0)
#
# Now create a normalised version
#
kIm = self.psf.computeImage(ccdXY, False)
self.assertAlmostEqual(afwMath.makeStatistics(kIm, afwMath.SUM).getValue(), 1.0)
def showCamera(camera, imageSource=SynthesizeCcdImage(), imageFactory=afwImage.ImageU,
frame=None, overlay=True, bin=1):
"""Show a Camera on ds9 (with the specified frame); if overlay show the IDs and amplifier boundaries
If imageSource is provided its getImage method will be called to return a CCD image (e.g. a
cameraGeom.GetCcdImage object); if it is "", an image will be created based on the properties
of the detectors"""
if imageSource is None:
cameraImage = None
elif isinstance(imageSource, GetCcdImage):
cameraImage = makeImageFromCamera(camera, imageSource, bin=bin, imageFactory=imageFactory)
else:
cameraImage = imageSource
if cameraImage:
ds9.mtv(cameraImage, frame=frame, title=camera.getId().getName())
for det in camera:
raft = cameraGeom.cast_Raft(det)
center = camera.getCenterPixel() + afwGeom.Extent2D(raft.getCenterPixel())
if overlay:
bbox = raft.getAllPixels()
ds9.dot(raft.getId().getName(), center[0]/bin, center[1]/bin, frame=frame)
showRaft(raft, None, frame=frame, overlay=overlay,
raftOrigin=center - afwGeom.makeExtentD(raft.getAllPixels().getWidth()/2,
raft.getAllPixels().getHeight()/2),
bin=bin)
def testNaNFromMaskedImage(self):
"""Check that an extensively masked image doesn't lead to NaNs in the background estimation
"""
image = afwImage.MaskedImageF(800, 800)
msk = image.getMask()
bbox = afwGeom.BoxI(afwGeom.PointI(560, 0), afwGeom.PointI(799, 335))
smsk = msk.Factory(msk, bbox)
smsk.set(msk.getPlaneBitMask("DETECTED"))
binSize = 256
nx = image.getWidth()//binSize + 1
ny = image.getHeight()//binSize + 1
sctrl = afwMath.StatisticsControl()
sctrl.setAndMask(reduce(lambda x, y: x | image.getMask().getPlaneBitMask(y),
['EDGE', 'DETECTED', 'DETECTED_NEGATIVE'], 0x0))
bctrl = afwMath.BackgroundControl(nx, ny, sctrl, "MEANCLIP")
bkgd = afwMath.makeBackground(image, bctrl)
bkgdImage = bkgd.getImageF("NATURAL_SPLINE", "THROW_EXCEPTION")
if display:
ds9.mtv(image)
ds9.mtv(bkgdImage, frame=1)
self.assertFalse(np.isnan(bkgdImage.get(0,0)))
# Check that the non-string API works too
bkgdImage = bkgd.getImageF(afwMath.Interpolate.NATURAL_SPLINE, afwMath.THROW_EXCEPTION)
def measure(footprintSet, exposure):
"""Measure a set of Footprints, returning a SourceCatalog"""
schema = afwTable.SourceTable.makeMinimalSchema()
config = measBase.SingleFrameMeasurementConfig()
config.algorithms.names = ["base_PixelFlags",
"base_SdssCentroid",
"base_GaussianFlux",
"base_SdssShape",
"base_CircularApertureFlux",
"base_PsfFlux",
]
config.algorithms["base_CircularApertureFlux"].radii = [3.0]
config.slots.centroid = "base_SdssCentroid"
config.slots.psfFlux = "base_PsfFlux"
config.slots.apFlux = "base_CircularApertureFlux_3_0"
config.slots.modelFlux = None
config.slots.instFlux = None
config.slots.calibFlux = None
config.slots.shape = "base_SdssShape"
task = measBase.SingleFrameMeasurementTask(schema, config=config)
table = afwTable.SourceCatalog(schema)
footprintSet.makeSources(table)
# Then run the default SFM task. Results not checked
task.run(table, exposure)
if display:
ds9.mtv(exposure)
return table
def testInvarianceOfPixelToSky(self):
for deep in (True, False):
llc = afwGeom.Point2I(20, 30)
bbox = afwGeom.Box2I(llc, afwGeom.Extent2I(60, 50))
subImg = afwImage.ExposureF(self.parent, bbox, afwImage.LOCAL, deep)
xy0 = subImg.getMaskedImage().getXY0()
if False:
ds9.mtv(self.parent, frame=0)
ds9.mtv(subImg, frame=1)
for p in self.testPositions:
subP = p - afwGeom.Extent2D(llc[0], llc[1]) # pixel in subImg
if subP[0] < 0 or subP[0] >= bbox.getWidth() or subP[1] < 0 or subP[1] >= bbox.getHeight():
continue
adParent = self.parent.getWcs().pixelToSky(p)
adSub = subImg.getWcs().pixelToSky(subP + afwGeom.Extent2D(xy0[0], xy0[1]))
#
# Check that we're talking about the same pixel
#
self.assertEqual(
self.parent.getMaskedImage().get(int(p[0]), int(p[1])),
subImg.getMaskedImage().get(int(subP[0]), int(subP[1])),
)
self.assertEqual(adParent[0], adSub[0], "RAs are equal; deep = %s" % deep)
self.assertEqual(adParent[1], adSub[1], "DECs are equal; deep = %s" % deep)
def run(self, dataRef):
"""!Compute a few statistics on the image plane of an exposure
@param dataRef: data reference for a calibrated science exposure ("calexp")
@return a pipeBase Struct containing:
- mean: mean of image plane
- meanErr: uncertainty in mean
- stdDev: standard deviation of image plane
- stdDevErr: uncertainty in standard deviation
"""
self.log.info("Processing data ID %s" % (dataRef.dataId,))
if self.config.doFail:
raise pipeBase.TaskError("Raising TaskError by request (config.doFail=True)")
# Unpersist the raw exposure pointed to by the data reference
rawExp = dataRef.get("raw")
maskedImage = rawExp.getMaskedImage()
# Support extra debug output.
# -
import lsstDebug
display = lsstDebug.Info(__name__).display
if display:
frame = 1
mtv(rawExp, frame=frame, title="exposure")
# return the pipe_base Struct that is returned by self.stats.run
return self.stats.run(maskedImage)
def testFootprintFromEllipse(self):
"""Create an elliptical Footprint"""
cen = afwGeom.Point2D(23, 25)
a, b, theta = 25, 15, 30
ellipse = afwGeomEllipses.Ellipse(afwGeomEllipses.Axes(a, b, math.radians(theta)), cen)
foot = afwDetect.Footprint(ellipse, afwGeom.Box2I(afwGeom.Point2I(0, 0), afwGeom.Extent2I(50, 60)))
idImage = afwImage.ImageU(afwGeom.Extent2I(foot.getRegion().getWidth(), foot.getRegion().getHeight()))
idImage.set(0)
foot.insertIntoImage(idImage, foot.getId())
if display:
ds9.mtv(idImage, frame=2)
displayUtils.drawFootprint(foot, frame=2)
shape = foot.getShape()
shape.scale(2) # <r^2> = 1/2 for a disk
ds9.dot(shape, *cen, frame=2, ctype=ds9.RED)
shape = foot.getShape()
shape.scale(2) # <r^2> = 1/2 for a disk
ds9.dot(shape, *cen, frame=2, ctype=ds9.MAGENTA)
axes = afwGeom.ellipses.Axes(foot.getShape())
axes.scale(2) # <r^2> = 1/2 for a disk
self.assertEqual(foot.getCentroid(), cen)
self.assertTrue(abs(a - axes.getA()) < 0.15, "a: %g v. %g" % (a, axes.getA()))
self.assertTrue(abs(b - axes.getB()) < 0.02, "b: %g v. %g" % (b, axes.getB()))
self.assertTrue(abs(theta - math.degrees(axes.getTheta())) < 0.2,
"theta: %g v. %g" % (theta, math.degrees(axes.getTheta())))
def testGrowCircular(self):
"""Grow footprints in all 4 directions using the FootprintSet/FootprintControl constructor """
im = afwImage.MaskedImageF(11, 11)
im.set(5, 5, (10,))
fs = afwDetect.FootprintSet(im, afwDetect.Threshold(10))
self.assertEqual(len(fs.getFootprints()), 1)
radius = 3 # How much to grow by
for fctrl in (
afwDetect.FootprintControl(),
afwDetect.FootprintControl(True),
afwDetect.FootprintControl(True, True),
):
grown = afwDetect.FootprintSet(fs, radius, fctrl)
afwDetect.setMaskFromFootprintList(im.getMask(), grown.getFootprints(), 0x10)
if display:
ds9.mtv(im)
foot = grown.getFootprints()[0]
if not fctrl.isCircular()[0]:
self.assertEqual(foot.getNpix(), 1)
elif fctrl.isCircular()[0]:
assert radius == 3
if fctrl.isIsotropic()[1]:
self.assertEqual(foot.getNpix(), 29)
else:
self.assertEqual(foot.getNpix(), 25)
def testGrowLRUD2(self):
"""Grow footprints in various directions using the FootprintSet/FootprintControl constructor
Check that overlapping grown Footprints give the expected answers
"""
ngrow = 3 # How much to grow by
for fctrl, xy in [
(afwDetect.FootprintControl(True, True, False, False), [(4, 5), (5, 6), (6, 5)]),
(afwDetect.FootprintControl(False, False, True, True), [(5, 4), (6, 5), (5, 6)]),
]:
im = afwImage.MaskedImageF(11, 11)
for x, y in xy:
im.set(x, y, (10,))
fs = afwDetect.FootprintSet(im, afwDetect.Threshold(10))
self.assertEqual(len(fs.getFootprints()), 1)
grown = afwDetect.FootprintSet(fs, ngrow, fctrl)
im.getMask().set(0)
afwDetect.setMaskFromFootprintList(im.getMask(), grown.getFootprints(), 0x10)
if display:
ds9.mtv(im)
self.assertEqual(len(grown.getFootprints()), 1)
foot = grown.getFootprints()[0]
npix = 1 + 2 * ngrow
npix += 3 + 2 * ngrow # 3: distance between pair of set pixels 000X0X000
self.assertEqual(foot.getNpix(), npix)
def setUp(self):
self.ms = afwImage.MaskedImageF(afwGeom.Extent2I(12, 8))
im = self.ms.getImage()
#
# Objects that we should detect
#
self.objects = []
self.objects += [Object(10, [(1, 4, 4), (2, 3, 5), (3, 4, 4)])]
self.objects += [Object(20, [(5, 7, 8), (6, 8, 8)])]
self.objects += [Object(20, [(5, 10, 10)])]
self.objects += [Object(30, [(6, 3, 3)])]
im.set(0) # clear image
for obj in self.objects:
obj.insert(im)
self.NaN = float("NaN")
im.set(3, 7, self.NaN)
im.set(0, 0, self.NaN)
im.set(8, 2, self.NaN)
im.set(9, 6, self.NaN) # connects the two objects with value==20 together if NaN is detected
if False and display:
ds9.mtv(im, frame=0)
def doSetUp(self, dwidth=0, dheight=0, x0=0, y0=0):
width, height = 14 + x0 + dwidth, 10 + y0 + dheight
self.im = afwImage.MaskedImageF(afwGeom.Extent2I(width, height))
#
# Objects that we should detect
#
self.objects, self.peaks = [], []
self.objects.append([[4, 1, 10], [3, 2, 10], [4, 2, 20], [5, 2, 10], [4, 3, 10],])
self.peaks.append([[4, 2]])
self.objects.append([[9, 7, 30], [10, 7, 29], [12, 7, 25], [10, 8, 27], [11, 8, 26],])
self.peaks.append([[9, 7]])
self.objects.append([[3, 8, 10], [4, 8, 10],])
self.peaks.append([[3, 8], [4, 8],])
for pp in self.peaks: # allow for x0, y0
for p in pp:
p[0] += x0
p[1] += y0
for oo in self.objects:
for o in oo:
o[0] += x0
o[1] += y0
self.im.set((0, 0x0, 0)) # clear image
for obj in self.objects:
for x, y, I in obj:
self.im.getImage().set(x, y, I)
if False and display:
ds9.mtv(self.im, frame=0)
def measure(footprintSet, exposure):
"""Measure a set of Footprints, returning a SourceCatalog"""
config = measAlg.SourceMeasurementConfig()
config.prefix = "initial."
config.algorithms.names = ["flags.pixel", "flux.psf", "flux.sinc", "flux.gaussian", "shape.sdss"]
config.centroider.name = "centroid.sdss"
config.algorithms["flux.naive"].radius = 3.0
config.slots.centroid = "initial.centroid.sdss"
config.slots.psfFlux = "initial.flux.psf"
config.slots.apFlux = "initial.flux.sinc"
config.slots.modelFlux = None
config.slots.instFlux = None
config.slots.calibFlux = None
config.slots.shape = "initial.shape.sdss"
schema = afwTable.SourceTable.makeMinimalSchema()
measureSources = config.makeMeasureSources(schema)
catalog = afwTable.SourceCatalog(schema)
config.slots.setupTable(catalog.table)
if display:
ds9.mtv(exposure, title="Original", frame=0)
footprintSet.makeSources(catalog)
for i, source in enumerate(catalog):
measureSources.applyWithPeak(source, exposure)
return catalog
def main(rootDir, visit, ccd, frame=1, title="", scale="zscale", zoom="to fit", trans=60, useEllipse=False):
# butler を開き読み込みたいデータの dataId を指定する
butler = dafPersist.Butler(rootDir)
dataId = {'visit': visit, 'ccd':ccd}
# butler から一次処理済データを読み込む
exposure = butler.get('calexp', dataId)
# 読み込みたい天体情報を設定し、ds9.mtv() を読み込む
settings = {'scale':scale, 'zoom': zoom, 'mask' : 'transparency %d' %(trans)}
ds9.mtv(exposure, frame=frame, title=title, settings=settings)
# 天体カタログを取得し、データ点を重ねて表示する
sources = butler.get('src', dataId)
with ds9.Buffering():
for i,source in enumerate(sources):
color = ds9.RED
size = 5.0
if useEllipse:
# 楕円体のシンボルで表示
symbol = "@:{ixx},{ixy},{iyy}".format(ixx=source.getIxx(),
ixy=source.getIxy(),
iyy=source.getIyy())
else:
# シンプルなシンボルで表示（例えば、 +, x, *, o が使える）
symbol = "o"
ds9.dot(symbol, source.getX(), source.getY(), ctype=color,
size=size, frame=frame, silent=True)
def setUp(self):
self.im = afwImage.DecoratedImageD(InputSmallImagePath)
self.wcs = afwImage.makeWcs(self.im.getMetadata())
if False:
ds9.mtv(self.im, wcs=self.wcs)
def testStatsZebra(self):
"""Add 1 to every other row"""
image2 = self.image.Factory(self.image, True)
#
# Add 1 to every other row, so the variance is 1/4
#
self.assertEqual(image2.getHeight()%2, 0)
width = image2.getWidth()
for y in range(1, image2.getHeight(), 2):
sim = image2.Factory(image2, afwGeom.Box2I(afwGeom.Point2I(0, y), afwGeom.Extent2I(width, 1)),
afwImage.LOCAL)
sim += 1
if display:
ds9.mtv(self.image, frame = 0)
ds9.mtv(image2, frame = 1)
stats = afwMath.makeStatistics(image2,
afwMath.NPOINT | afwMath.STDEV | afwMath.MEAN | afwMath.ERRORS)
mean = stats.getResult(afwMath.MEAN)
n = stats.getValue(afwMath.NPOINT)
sd = stats.getValue(afwMath.STDEV)
self.assertEqual(mean[0], image2.get(0, 0) + 0.5)
self.assertEqual(sd, 1/math.sqrt(4.0)*math.sqrt(n/(n - 1)))
self.assertAlmostEqual(mean[1], sd/math.sqrt(image2.getWidth()*image2.getHeight()), 10)
meanSquare = afwMath.makeStatistics(image2, afwMath.MEANSQUARE).getValue()
self.assertEqual(meanSquare, 0.5*(image2.get(0, 0)**2 + image2.get(0, 1)**2))
def setUp(self):
im = afwImage.ImageF(self.monetFile("small.fits"))
self.mi = afwImage.MaskedImageF(im, afwImage.MaskU(im.getDimensions()),
afwImage.ImageF(im.getDimensions()));
self.ds = afwDetection.FootprintSet(self.mi, afwDetection.Threshold(100))
if display:
ds9.mtv(self.mi.getImage())
ds9.erase()
for foot in self.ds.getFootprints():
bbox = foot.getBBox()
x0, y0 = bbox.getMinX(), bbox.getMinY()
x1, y1 = bbox.getMaxX(), bbox.getMaxY()
xc = (x0 + x1)/2.0
yc = (y0 + y1)/2.0
if display:
ds9.dot("+", xc, yc, ctype=ds9.BLUE)
if False:
x0 -= 0.5; y0 -= 0.5
x1 += 0.5; y1 += 0.5
ds9.line([(x0, y0), (x1, y0), (x1, y1), (x0, y1), (x0, y0)], ctype=ds9.RED)
self.control = algorithms.GaussianCentroidControl()
schema = afwTable.SourceTable.makeMinimalSchema()
self.centroider = algorithms.MeasureSourcesBuilder().addAlgorithm(self.control).build(schema)
self.ssMeasured = afwTable.SourceCatalog(schema)
self.ssMeasured.table.defineCentroid(self.control.name)
self.ssTruth = afwTable.SourceCatalog(schema)
self.readTruth(self.monetFile("positions.dat-original"))
def testDrawing(self):
"""Test drawing lines and glyphs"""
ds9.erase()
exp = afwImage.ExposureF(300, 350)
ds9.mtv(exp, title="parent") # tells display0 about the image's xy0
with ds9.Buffering():
ds9.dot('o', 200, 220)
vertices = [(200, 220), (210, 230), (224, 230), (214, 220), (200, 220)]
ds9.line(vertices, ctype=ds9.CYAN)
ds9.line(vertices[:-1], symbs="+x+x", size=3)
def measure(self, footprintSet, exposure):
"""Measure a set of Footprints, returning a SourceCatalog"""
table = afwTable.SourceCatalog(self.schema)
footprintSet.makeSources(table)
# Then run the default SFM task. Results not checked
self.measureTask.run(table, exposure)
if display:
ds9.mtv(exposure)
return table
def testKernel(self):
"""Test the creation of the dgPsf's kernel."""
for psf in [self.psfDg, self.psfSg]:
kIm = afwImage.ImageD(psf.getKernel().getDimensions())
psf.getKernel().computeImage(kIm, False)
self.assertEqual(kIm.getWidth(), self.ksize)
self.assertAlmostEqual(
afwMath.makeStatistics(kIm, afwMath.SUM).getValue(), 1.0)
if False:
ds9.mtv(kIm)
def testText(self):
"""Test drawing text"""
ds9.erase()
exp = afwImage.ExposureF(300, 350)
ds9.mtv(exp, title="parent") # tells display0 about the image's xy0
with ds9.Buffering():
ds9.dot('hello', 200, 200)
ds9.dot('hello', 200, 210, size=1.25)
ds9.dot('hello', 200, 220, size=3, fontFamily="times")
ds9.dot('hello', 200, 230, fontFamily="helvetica bold italic")
def runBasicTest(self, kernel, convControl, refKernel=None, kernelDescr="", rtol=1.0e-05, atol=1e-08):
"""Assert that afwMath::convolve gives the same result as reference convolution for a given kernel.
Inputs:
- kernel: convolution kernel
- convControl: convolution control parameters (afwMath.ConvolutionControl)
- refKernel: kernel to use for refConvolve (if None then kernel is used)
- kernelDescr: description of kernel
- rtol: relative tolerance (see below)
- atol: absolute tolerance (see below)
rtol and atol are positive, typically very small numbers.
The relative difference (rtol * abs(b)) and the absolute difference "atol" are added together
to compare against the absolute difference between "a" and "b".
"""
if refKernel is None:
refKernel = kernel
# strip garbage characters (whitespace and punctuation) to make a short description for saving files
shortKernelDescr = self._removeGarbageChars(kernelDescr)
doNormalize = convControl.getDoNormalize()
doCopyEdge = convControl.getDoCopyEdge()
maxInterpDist = convControl.getMaxInterpolationDistance()
imMaskVar = self.maskedImage.getArrays()
xy0 = self.maskedImage.getXY0()
refCnvImMaskVarArr = refConvolve(imMaskVar, xy0, refKernel, doNormalize, doCopyEdge)
refMaskedImage = afwImage.makeMaskedImageFromArrays(*refCnvImMaskVarArr)
afwMath.convolve(self.cnvImage, self.maskedImage.getImage(), kernel, convControl)
self.assertEqual(self.cnvImage.getXY0(), self.xy0)
afwMath.convolve(self.cnvMaskedImage, self.maskedImage, kernel, convControl)
if display and False:
ds9.mtv(displayUtils.Mosaic().makeMosaic([
self.maskedImage, refMaskedImage, self.cnvMaskedImage]), frame=0)
if False:
for (x, y) in ((0, 0), (1, 0), (0, 1), (50, 50)):
print("Mask(%d,%d) 0x%x 0x%x" % (x, y, refMaskedImage.getMask().get(x, y),
self.cnvMaskedImage.getMask().get(x, y)))
self.assertImagesNearlyEqual(self.cnvImage, refMaskedImage.getImage(), atol=atol, rtol=rtol)
self.assertMaskedImagesNearlyEqual(self.cnvMaskedImage, refMaskedImage, atol=atol, rtol=rtol)
if not sameMaskPlaneDicts(self.cnvMaskedImage, self.maskedImage):
self.cnvMaskedImage.writeFits("act%s" % (shortKernelDescr,))
refMaskedImage.writeFits("des%s" % (shortKernelDescr,))
self.fail("convolve(MaskedImage, kernel=%s, doNormalize=%s, "
"doCopyEdge=%s, maxInterpDist=%s) failed:\n%s" %
(kernelDescr, doNormalize, doCopyEdge, maxInterpDist,
"convolved mask dictionary does not match input"))
def testNormalize(self):
"""Test Footprint.normalize"""
w, h = 12, 10
region = afwGeom.Box2I(afwGeom.Point2I(0, 0), afwGeom.Extent2I(w, h))
im = afwImage.ImageU(afwGeom.Extent2I(w, h))
im.set(0)
#
# Create a footprint; note that these Spans overlap
#
for spans, box in (([
(3, 5, 6),
(4, 7, 7),
], afwGeom.Box2I(afwGeom.Point2I(5, 3), afwGeom.Point2I(7, 4))), ([
(3, 3, 5),
(3, 6, 9),
(4, 2, 3),
(4, 5, 7),
(4, 8, 8),
(5, 2, 3),
(5, 5, 8),
(5, 6, 7),
(6, 3, 5),
], afwGeom.Box2I(afwGeom.Point2I(2, 3), afwGeom.Point2I(9, 6)))):
foot = afwDetect.Footprint(0, region)
for y, x0, x1 in spans:
foot.addSpan(y, x0, x1)
for x in range(x0, x1 + 1): # also insert into im
im.set(x, y, 1)
idImage = afwImage.ImageU(afwGeom.Extent2I(w, h))
idImage.set(0)
foot.insertIntoImage(idImage, 1)
if display: # overlaping pixels will be > 1
ds9.mtv(idImage)
#
# Normalise the Footprint, removing overlapping spans
#
foot.normalize()
idImage.set(0)
foot.insertIntoImage(idImage, 1)
if display:
ds9.mtv(idImage, frame=1)
idImage -= im
self.assertTrue(box == foot.getBBox())
self.assertEqual(
afwMath.makeStatistics(idImage, afwMath.MAX).getValue(), 0)
def testFootprintsMeasure(self):
"""Check that we can measure the objects in a detectionSet"""
xcentroid = [10.0, 14.0, 9.0]
ycentroid = [8.0, 11.5061728, 14.0]
flux = [51.0, 101.0, 20.0]
ds = afwDetection.FootprintSet(self.mi, afwDetection.Threshold(10), "DETECTED")
if display:
ds9.mtv(self.mi, frame=0)
ds9.mtv(self.mi.getVariance(), frame=1)
measureSourcesConfig = measBase.SingleFrameMeasurementConfig()
measureSourcesConfig.algorithms["base_CircularApertureFlux"].radii = [3.0]
measureSourcesConfig.algorithms.names = ["base_NaiveCentroid", "base_SdssShape", "base_PsfFlux",
"base_CircularApertureFlux"]
measureSourcesConfig.slots.centroid = "base_NaiveCentroid"
measureSourcesConfig.slots.psfFlux = "base_PsfFlux"
measureSourcesConfig.slots.apFlux = "base_CircularApertureFlux_3_0"
measureSourcesConfig.slots.modelFlux = None
measureSourcesConfig.slots.instFlux = None
measureSourcesConfig.slots.calibFlux = None
schema = afwTable.SourceTable.makeMinimalSchema()
task = measBase.SingleFrameMeasurementTask(schema, config=measureSourcesConfig)
measCat = afwTable.SourceCatalog(schema)
# now run the SFM task with the test plugin
sigma = 1e-10
psf = algorithms.DoubleGaussianPsf(11, 11, sigma) # i.e. a single pixel
self.exposure.setPsf(psf)
task.run(measCat, self.exposure)
for i, source in enumerate(measCat):
xc, yc = source.getX() - self.mi.getX0(), source.getY() - self.mi.getY0()
if display:
ds9.dot("+", xc, yc)
self.assertAlmostEqual(source.getX(), xcentroid[i], 6)
self.assertAlmostEqual(source.getY(), ycentroid[i], 6)
self.assertEqual(source.getApFlux(), flux[i])
# 29 pixels in 3pixel circular ap.
self.assertAlmostEqual(source.getApFluxErr(), math.sqrt(29), 6)
# We're using a delta-function PSF, so the psfFlux should be the pixel under the centroid,
# iff the object's centred in the pixel
if xc == int(xc) and yc == int(yc):
self.assertAlmostEqual(source.getPsfFlux(),
self.exposure.getMaskedImage().getImage().get(int(xc + 0.5),
int(yc + 0.5)))
self.assertAlmostEqual(source.getPsfFluxErr(),
self.exposure.getMaskedImage().getVariance().get(int(xc + 0.5),
int(yc + 0.5)))
def testImageSliceFromBox(self):
"""Test using a Box2I to index an Image"""
im = afwImage.ImageF(10, 20)
bbox = afwGeom.BoxI(afwGeom.PointI(1, 3), afwGeom.PointI(6, 9))
im[bbox] = -1
if display:
ds9.mtv(im)
self.assertEqual(im.get(0, 6), 0)
self.assertEqual(im.get(1, 6), -1)
self.assertEqual(im.get(3, 9), -1)
def writeDefects(self, maskFile, ccd, format=None):
"""Given a Mask, find the defects for each amp in the specified CCD (0-indexed).
If format is provided, it's expected to be used as "format % (ccd, amp)" to generate
a .paf filename to write the defects too. If it's "-", write to stdout"""
# Metadata should have validity range keywords, but it doesn't.
if False:
metaData = afwImage.readMetadata(maskFile, 0)
hdu = ccd + 2
im = afwImage.ImageF(maskFile, hdu)
im -= 1
im *= -1
mask = afwImage.MaskU(im.getBBox(afwImage.PARENT))
mask.set(0x0)
mask = afwImage.makeMaskedImage(im, mask)
for amp in self.ampList():
subMask = mask.Factory(mask, self.getTrimSecBBox(amp),
afwImage.LOCAL)
ds = afwDetection.makeFootprintSet(subMask,
afwDetection.Threshold(0.5),
"INTRP")
if False:
ds9.setDefaultFrame(amp)
ds9.mtv(subMask)
ds9.dot("Amp %d" % amp, 0, 0)
if not format:
return
if format == "-":
fd = sys.stdout
else:
fd = open(format % (ccd, amp), "w")
print >> fd, """\
#<?cfg paf policy ?>
#
# Defects for CCD%03d amp %02d generated from %s, HDU %d
#
# Coordinates are trimmed and per-amp not per-CCD. If you change this, the ISR will have to change
#
# Generated by $HeadURL$
#
""" % (ccd, amp, maskFile, hdu),
for foot in ds.getFootprints():
afwDetectionUtils.writeFootprintAsDefects(fd, foot)
def run(display=False):
exposure = loadData()
schema = afwTable.SourceTable.makeMinimalSchema()
#
# Create the detection task
#
config = SourceDetectionTask.ConfigClass()
config.thresholdPolarity = "both"
config.background.isNanSafe = True
config.thresholdValue = 3
detectionTask = SourceDetectionTask(config=config, schema=schema)
#
# And the measurement Task
#
config = SingleFrameMeasurementTask.ConfigClass()
config.algorithms.names = ["base_SdssCentroid", "base_SdssShape", "base_CircularApertureFlux"]
config.algorithms["base_CircularApertureFlux"].radii = [1, 2, 4, 8, 16] # pixels
config.slots.instFlux = None
config.slots.modelFlux = None
config.slots.psfFlux = None
algMetadata = dafBase.PropertyList()
measureTask = SingleFrameMeasurementTask(schema, algMetadata=algMetadata, config=config)
radii = algMetadata.get("base_CircularApertureFlux_radii")
#
# Create the output table
#
tab = afwTable.SourceTable.make(schema)
#
# Process the data
#
result = detectionTask.run(tab, exposure)
sources = result.sources
print("Found %d sources (%d +ve, %d -ve)" % (len(sources), result.fpSets.numPos, result.fpSets.numNeg))
measureTask.run(sources, exposure)
if display: # display on ds9 (see also --debug argparse option)
frame = 1
ds9.mtv(exposure, frame=frame)
with ds9.Buffering():
for s in sources:
xy = s.getCentroid()
ds9.dot('+', *xy, ctype=ds9.CYAN if s.get("flags.negative") else ds9.GREEN, frame=frame)
ds9.dot(s.getShape(), *xy, ctype=ds9.RED, frame=frame)
for i in range(s.get("flux.aperture.nProfile")):
ds9.dot('o', *xy, size=radii[i], ctype=ds9.YELLOW, frame=frame)
def selectStars(self, exposure, sourceCat, matches=None):
"""!Return a list of PSF candidates that represent likely stars
A list of PSF candidates may be used by a PSF fitter to construct a PSF.
@param[in] exposure the exposure containing the sources
@param[in] sourceCat catalog of sources that may be stars (an lsst.afw.table.SourceCatalog)
@param[in] matches a match vector as produced by meas_astrom; required
(defaults to None to match the StarSelector API and improve error handling)
@return an lsst.pipe.base.Struct containing:
- starCat catalog of selected stars (a subset of sourceCat)
"""
import lsstDebug
debugInfo = lsstDebug.Info(__name__)
display = debugInfo.display
pauseAtEnd = debugInfo.pauseAtEnd # pause when done
if matches is None:
raise RuntimeError("CatalogStarSelectorTask requires matches")
mi = exposure.getMaskedImage()
if display:
frame = 1
ds9.mtv(mi, frame=frame, title="PSF candidates")
isGoodSource = CheckSource(sourceCat, self.config.fluxLim,
self.config.fluxMax, self.config.badFlags)
starCat = SourceCatalog(sourceCat.schema)
with ds9.Buffering():
for ref, source, d in matches:
if not ref.get("resolved"):
if not isGoodSource(source):
symb, ctype = "+", ds9.RED
else:
starCat.append(source)
symb, ctype = "+", ds9.GREEN
if display:
ds9.dot(symb,
source.getX() - mi.getX0(),
source.getY() - mi.getY0(),
size=4,
frame=frame,
ctype=ctype)
if display and pauseAtEnd:
input("Continue? y[es] p[db] ")
return Struct(starCat=starCat, )
def testFlip(self):
"""Test that we end up with the correct image after flipping it"""
frame = 2
for flipLR, flipTB, x, y in [(True, False, 19, 0),
(True, True, 19, 9),
(False, True, 0, 9),
(False, False, 0, 0)]:
outImage = afwMath.flipImage(self.inImage, flipLR, flipTB)
if display:
ds9.mtv(outImage, frame=frame, title="%s %s" % (flipLR, flipTB))
frame += 1
self.assertEqual(self.inImage.get(0, 0), outImage.get(x, y))
def testImageSliceFromBoxOrigin(self):
"""Test using a Box2I to index an Image"""
im = afwImage.ImageF(10, 20)
im.setXY0(50, 100)
bbox = afwGeom.BoxI(afwGeom.PointI(51, 103), afwGeom.ExtentI(6, 7))
im[bbox, afwImage.PARENT] = -1
if display:
ds9.mtv(im)
self.assertEqual(im.get(0, 6), 0)
self.assertEqual(im.get(1, 6), -1)
self.assertEqual(im.get(3, 9), -1)
def testFootprintSetImageId(self):
"""Check that we can insert a FootprintSet into an Image, setting relative IDs"""
ds = afwDetect.FootprintSet(self.ms, afwDetect.Threshold(10))
objects = ds.getFootprints()
idImage = ds.insertIntoImage(True)
if display:
ds9.mtv(idImage, frame=2)
for i in range(len(objects)):
for sp in objects[i].getSpans():
for x in range(sp.getX0(), sp.getX1() + 1):
self.assertEqual(idImage.get(x, sp.getY()), i + 1)
def testComputeImage(self):
"""Test the computation of the PSF's image at a point"""
ccdXY = afwGeom.Point2D(0, 0)
kIm = self.psf.computeImage(ccdXY)
if False:
ds9.mtv(kIm)
self.assertTrue(kIm.getWidth() == self.ksize)
xcen, ycen = self.ksize/2, self.ksize/2
kIm = self.psf.computeImage(ccdXY)
self.assertAlmostEqual(afwMath.makeStatistics(kIm, afwMath.SUM).getValue(), 1.0)
def OpenTimepixInDS9(filename, binary=False):
import lsst.afw.display.ds9 as ds9
if binary:
image, dummy = TimepixToExposure_binary(filename, 0, 255, 0, 255)
else:
image = TimepixToExposure(filename, 0, 255, 0, 255)
try:
ds9.initDS9(False)
except ds9.Ds9Error:
print('DS9 launch bug error thrown away (probably)')
ds9.mtv(image)
def testImageSliceFromBoxOrigin(self):
"""Test using a Box2I to index an Image"""
im = afwImage.ImageF(10, 20)
im.setXY0(50, 100)
bbox = lsst.geom.BoxI(lsst.geom.PointI(51, 103), lsst.geom.ExtentI(6, 7))
im[bbox] = -1
if display:
ds9.mtv(im)
self.assertEqual(im[0, 6, afwImage.LOCAL], 0)
self.assertEqual(im[1, 6, afwImage.LOCAL], -1)
self.assertEqual(im[3, 9, afwImage.LOCAL], -1)
def testFootprints(self):
"""Check that we found the correct number of objects using FootprintSet"""
ds = afwDetect.FootprintSet(self.ms, afwDetect.Threshold(10),
"DETECTED")
objects = ds.getFootprints()
if display:
ds9.mtv(self.ms, frame=0)
self.assertEqual(len(objects), len(self.objects))
for i in range(len(objects)):
self.assertEqual(objects[i], self.objects[i])
def fft(im1, im2, fftSize):
arr1 = im1.getArray()
arr2 = im2.getArray()
fft1 = num.fft.rfft2(arr1)
fft2 = num.fft.rfft2(arr2)
rat = fft2 / fft1
kfft = num.fft.irfft2(rat, s=fftSize)
kim = afwImage.ImageF(fftSize)
kim.getArray()[:] = kfft
ds9.mtv(kim, frame=5)
def showPeaks(im=None, fs=None, frame=0):
"""Show the image and peaks"""
if frame is None:
return
if im:
ds9.mtv(im, frame=frame)
if fs:
with ds9.Buffering(): # turn on buffering of ds9's slow "region" writes
for foot in fs.getFootprints():
for p in foot.getPeaks():
ds9.dot("+", p.getIx(), p.getIy(), size=0.4, ctype=ds9.RED, frame=frame)
def testFootprintsMasks(self):
"""Check that detectionSets have the proper mask bits set"""
ds = afwDetect.FootprintSet(self.ms, afwDetect.Threshold(10), "OBJECT")
objects = ds.getFootprints()
if display:
ds9.mtv(self.ms, frame=1)
mask = self.ms.getMask()
for i in range(len(objects)):
for sp in objects[i].getSpans():
for x in range(sp.getX0(), sp.getX1() + 1):
self.assertEqual(mask.get(x, sp.getY()), mask.getPlaneBitMask("OBJECT"))
def testGrow(self):
"""Test growing a footprint"""
x0, y0 = 20, 20
width, height = 20, 30
foot1 = afwDetect.Footprint(
afwGeom.Box2I(afwGeom.Point2I(x0, y0),
afwGeom.Extent2I(width, height)),
afwGeom.Box2I(afwGeom.Point2I(0, 0), afwGeom.Extent2I(100, 100)))
bbox1 = foot1.getBBox()
self.assertEqual(bbox1.getMinX(), x0)
self.assertEqual(bbox1.getMaxX(), x0 + width - 1)
self.assertEqual(bbox1.getWidth(), width)
self.assertEqual(bbox1.getMinY(), y0)
self.assertEqual(bbox1.getMaxY(), y0 + height - 1)
self.assertEqual(bbox1.getHeight(), height)
ngrow = 5
for isotropic in (True, False):
foot2 = afwDetect.growFootprint(foot1, ngrow, isotropic)
# Check that the grown footprint is normalized
self.assertTrue(foot2.isNormalized())
# Check that the grown footprint is bigger than the original
self.assertGreater(foot2.getArea(), foot1.getArea())
bbox2 = foot2.getBBox()
if False and display:
idImage = afwImage.ImageU(width, height)
idImage.set(0)
i = 1
for foot in [foot1, foot2]:
foot.insertIntoImage(idImage, i)
i += 1
metricImage = afwImage.ImageF("foo.fits")
ds9.mtv(metricImage, frame=1)
ds9.mtv(idImage)
# check bbox2
self.assertEqual(bbox2.getMinX(), x0 - ngrow)
self.assertEqual(bbox2.getWidth(), width + 2 * ngrow)
self.assertEqual(bbox2.getMinY(), y0 - ngrow)
self.assertEqual(bbox2.getHeight(), height + 2 * ngrow)
# Check that region was preserved
self.assertEqual(foot1.getRegion(), foot2.getRegion())
def getBackground(image, backgroundConfig, nx=0, ny=0, algorithm=None):
"""
Make a new Exposure which is exposure - background
"""
backgroundConfig.validate()
if not nx:
nx = image.getWidth() // backgroundConfig.binSize + 1
if not ny:
ny = image.getHeight() // backgroundConfig.binSize + 1
displayBackground = lsstDebug.Info(__name__).displayBackground
if displayBackground:
import itertools
ds9.mtv(image, frame=1)
xPosts = numpy.rint(
numpy.linspace(0, image.getWidth() + 1, num=nx, endpoint=True))
yPosts = numpy.rint(
numpy.linspace(0, image.getHeight() + 1, num=ny, endpoint=True))
with ds9.Buffering():
for (xMin, xMax), (yMin, yMax) in itertools.product(
zip(xPosts[:-1], xPosts[1:]), zip(yPosts[:-1],
yPosts[1:])):
ds9.line([(xMin, yMin), (xMin, yMax), (xMax, yMax),
(xMax, yMin), (xMin, yMin)],
frame=1)
sctrl = afwMath.StatisticsControl()
sctrl.setAndMask(
reduce(lambda x, y: x | image.getMask().getPlaneBitMask(y),
backgroundConfig.ignoredPixelMask, 0x0))
sctrl.setNanSafe(backgroundConfig.isNanSafe)
pl = pexLogging.Debug("meas.utils.sourceDetection.getBackground")
pl.debug(
3, "Ignoring mask planes: %s" %
", ".join(backgroundConfig.ignoredPixelMask))
if not algorithm:
algorithm = backgroundConfig.algorithm
bctrl = afwMath.BackgroundControl(algorithm, nx, ny,
backgroundConfig.undersampleStyle, sctrl,
backgroundConfig.statisticsProperty)
if backgroundConfig.useApprox:
actrl = afwMath.ApproximateControl(
afwMath.ApproximateControl.CHEBYSHEV, backgroundConfig.approxOrder)
bctrl.setApproximateControl(actrl)
return afwMath.makeBackground(image, bctrl)
def setUp(self):
# We create an image that has a ramp (unique values for each pixel),
# with a single high pixel that allows for centering
self.width, self.height = 50, 50
self.xcen, self.ycen = self.width // 2, self.height // 2
self.image = afwImage.ImageF(afwGeom.ExtentI(self.width, self.height))
for y in range(self.height):
for x in range(self.width):
self.image.set(x, y, self.width * y + x)
self.image.set(self.xcen, self.ycen, 1234567.89)
self.exp = afwImage.makeExposure(afwImage.makeMaskedImage(self.image))
self.exp.getMaskedImage().getVariance().set(1.0)
scale = 0.2 / 3600
wcs = afwImage.makeWcs(
afwCoord.Coord(0 * afwGeom.degrees, 0 * afwGeom.degrees),
afwGeom.Point2D(self.xcen, self.ycen), scale, 0, 0, scale)
self.exp.setWcs(wcs)
if display:
frame = 1
ds9.mtv(self.exp, frame=frame, title="Single pixel")
# We will use a GaussianCentroid to tweak the center (it should not, for forced measurement)
# and a NaiveFlux to measure the single pixel. We'll start offset from the high pixel,
# so that a forced measurement should yield a flux of zero, while a measurement that was allowed to
# center should yield a flux of unity.
# Note that previous versions used NaiveCentroid, which was so nonrobust that it failed to get
# right answer when the input value was round-tripped through Wcs and modified by ~1E-8.
gaussianCentroid = measAlg.GaussianCentroidControl()
naiveFlux = measAlg.NaiveFluxControl()
naiveFlux.radius = 0.5
self.x, self.y = self.xcen - 1, self.ycen - 1
self.foot = afwDetection.Footprint(afwGeom.Point2I(self.x, self.y), 2)
self.foot.addPeak(self.x, self.y, float("NaN"))
schema = afwTable.SourceTable.makeMinimalSchema()
msb = measAlg.MeasureSourcesBuilder()
msb.addAlgorithm(naiveFlux)
msb.setCentroider(gaussianCentroid)
self.measurer = msb.build(schema)
self.table = afwTable.SourceTable.make(schema)
self.table.defineCentroid("centroid.gaussian")
schemaF = afwTable.SourceTable.makeMinimalSchema()
msbF = measAlg.MeasureSourcesBuilder("", True)
msbF.addAlgorithm(naiveFlux)
msbF.setCentroider(gaussianCentroid)
self.measurerF = msbF.build(schemaF)
self.tableF = afwTable.SourceTable.make(schemaF)
self.tableF.defineCentroid("centroid.gaussian")
def testOffsetGaussian(self):
"""Insert a Gaussian, offset, and check the residuals"""
size = 50
refIm = afwImage.ImageF(size, size)
unshiftedIm = afwImage.ImageF(size, size)
xc, yc = size/2.0, size/2.0
amp, sigma1 = 1.0, 3
#
# Calculate Gaussian directly at (xc, yc)
#
self.calcGaussian(refIm, xc, yc, amp, sigma1)
for dx in (-55.5, -1.500001, -1.5, -1.499999, -1.00001, -1.0, -0.99999, -0.5,
0.0, 0.5, 0.99999, 1.0, 1.00001, 1.499999, 1.5, 1.500001, 99.3):
for dy in (-3.7, -1.500001, -1.5, -1.499999, -1.00001, -1.0, -0.99999, -0.5,
0.0, 0.5, 0.99999, 1.0, 1.00001, 1.499999, 1.5, 1.500001, 2.99999):
dOrigX, dOrigY, dFracX, dFracY = getOrigFracShift(dx, dy)
self.calcGaussian(unshiftedIm, xc - dFracX, yc - dFracY, amp, sigma1)
for algorithm, maxMean, maxLim in (
("lanczos5", 1e-8, 0.0015),
("bilinear", 1e-8, 0.03),
("nearest", 1e-8, 0.2),
):
im = afwImage.ImageF(size, size)
im = afwMath.offsetImage(unshiftedIm, dx, dy, algorithm)
if display:
ds9.mtv(im, frame=0)
im -= refIm
if display:
ds9.mtv(im, frame=1)
imArr = im.getArray()
imGoodVals = np.ma.array(imArr, copy=False, mask=np.isnan(imArr)).compressed()
try:
imXY0 = tuple(im.getXY0())
self.assertEqual(imXY0, (dOrigX, dOrigY))
self.assertLess(abs(imGoodVals.mean()), maxMean*amp)
self.assertLess(abs(imGoodVals.max()), maxLim*amp)
self.assertLess(abs(imGoodVals.min()), maxLim*amp)
except:
print("failed on algorithm=%s; dx = %s; dy = %s" % (algorithm, dx, dy))
raise
def main(rootDir,
visit,
ccd,
frame=1,
title="",
scale="zscale",
zoom="to fit",
trans=60,
useEllipse=False):
# butler を開き読み込みたいデータの dataId を指定する
butler = dafPersist.Butler(rootDir)
dataId = {'visit': visit, 'ccd': ccd}
# butler から一次処理済データを読み込む
exposure = butler.get('calexp', dataId)
# 読み込みたい天体情報を設定し、ds9.mtv() を読み込む
settings = {
'scale': scale,
'zoom': zoom,
'mask': 'transparency %d' % (trans)
}
ds9.mtv(exposure, frame=frame, title=title, settings=settings)
# 天体カタログを取得し、データ点を重ねて表示する
sources = butler.get('src', dataId)
with ds9.Buffering():
for i, source in enumerate(sources):
color = ds9.RED
size = 5.0
if useEllipse:
# 楕円体のシンボルで表示
symbol = "@:{ixx},{ixy},{iyy}".format(ixx=source.getIxx(),
ixy=source.getIxy(),
iyy=source.getIyy())
else:
# シンプルなシンボルで表示（例えば、 +, x, *, o が使える）
symbol = "o"
ds9.dot(symbol,
source.getX(),
source.getY(),
ctype=color,
size=size,
frame=frame,
silent=True)
def testImage(self):
"""Test Polygon.createImage"""
for i, num in enumerate(range(3, 30)):
poly = self.polygon(num, 25, 75, 75)
box = afwGeom.Box2I(afwGeom.Point2I(15, 15),
afwGeom.Extent2I(115, 115))
image = poly.createImage(box)
if DEBUG:
import lsst.afw.display.ds9 as ds9
ds9.mtv(image, frame=i + 1, title="Polygon nside=%d" % num)
for p1, p2 in poly.getEdges():
ds9.line((p1, p2), frame=i + 1)
self.assertAlmostEqual(
image.getArray().sum() / poly.calculateArea(), 1.0, 6)
def testTwoDisplays(self):
"""Test that we can do things with two frames"""
exp = afwImage.ExposureF(300, 350)
for frame in (0, 1):
ds9.setMaskTransparency(50, frame=frame)
if frame == 1:
ds9.setMaskPlaneColor("CROSSTALK", "ignore", frame=frame)
ds9.mtv(exp, title="parent", frame=frame)
ds9.erase(frame=frame)
ds9.dot('o', 205, 180, size=6, ctype=ds9.RED, frame=frame)
def testComputeImage(self):
"""Test the computation of the PSF's image at a point."""
for psf in [self.psfDg, self.psfSg]:
ccdXY = afwGeom.Point2D(0, 0)
kIm = psf.computeImage(ccdXY)
if False:
ds9.mtv(kIm)
self.assertEqual(kIm.getWidth(), self.ksize)
kIm = psf.computeImage(ccdXY)
self.assertAlmostEqual(
afwMath.makeStatistics(kIm, afwMath.SUM).getValue(), 1.0)
def testTicket1040(self):
""" How to repeat from #1040"""
image = afwImage.ImageD(afwGeom.Extent2I(6, 6))
image.set(2, 2, 100)
bbox = afwGeom.Box2I(afwGeom.Point2I(1, 1), afwGeom.Extent2I(5, 5))
subImage = image.Factory(image, bbox)
subImageF = subImage.convertFloat()
if display:
ds9.mtv(subImage, frame=0, title="subImage")
ds9.mtv(subImageF, frame=1, title="converted subImage")
self.assertEqual(subImage.get(1, 1), subImageF.get(1, 1))