def testConstructImage(self):
"""Test construction of image from the spectrum
Reverse process of extraction.
"""
spectrum = drpStella.Spectrum(self.fullDims.getY(), self.fiberId)
spectrum.spectrum[self.xy0.getY():self.xy0.getY() + self.height] = 1.0
image = self.fiberTrace.constructImage(spectrum, self.bbox)
self.assertEqual(image.getBBox(), self.bbox)
self.assertImagesEqual(image[self.bbox, lsst.afw.image.PARENT], self.subimage.image)
image[self.bbox, lsst.afw.image.PARENT].set(0.0)
self.assertFloatsEqual(image.array, 0.0)
# Modify provided image
image.set(0.0)
self.fiberTrace.constructImage(image, spectrum)
self.assertImagesEqual(image[self.bbox, lsst.afw.image.PARENT], self.subimage.image)
# Check that we're actually adding, not simply setting
self.fiberTrace.constructImage(image, spectrum)
self.image += self.image
self.assertImagesEqual(image[self.bbox, lsst.afw.image.PARENT], self.subimage.image)
image[self.bbox, lsst.afw.image.PARENT].set(0.0)
self.assertFloatsEqual(image.array, 0.0)
def setUp(self):
width, height = 250, 500
self.numAmps = 4
numPixelsPerAmp = 1000
# crosstalk[i][j] is the fraction of the j-th amp present on the i-th
# amp.
self.crosstalk = [[0.0, 1e-4, 2e-4, 3e-4], [3e-4, 0.0, 2e-4, 1e-4],
[4e-4, 5e-4, 0.0, 6e-4], [7e-4, 8e-4, 9e-4, 0.0]]
self.value = 12345
self.crosstalkStr = "XTLK"
# A bit of noise is important, because otherwise the pixel
# distributions are razor-thin and then rejection doesn't work.
rng = np.random.RandomState(12345)
self.noise = rng.normal(0.0, 0.1, (2 * height, 2 * width))
# Create amp images
withoutCrosstalk = [
lsst.afw.image.ImageF(width, height) for _ in range(self.numAmps)
]
for image in withoutCrosstalk:
image.set(0)
xx = rng.randint(0, width, numPixelsPerAmp)
yy = rng.randint(0, height, numPixelsPerAmp)
image.getArray()[yy, xx] = self.value
# Add in crosstalk
withCrosstalk = [
image.Factory(image, True) for image in withoutCrosstalk
]
for ii, iImage in enumerate(withCrosstalk):
for jj, jImage in enumerate(withoutCrosstalk):
value = self.crosstalk[ii][jj]
iImage.scaledPlus(value, jImage)
# Put amp images together
def construct(imageList):
image = lsst.afw.image.ImageF(2 * width, 2 * height)
image.getArray()[:height, :width] = imageList[0].getArray()
image.getArray()[:height,
width:] = imageList[1].getArray()[:, ::
-1] # flip in x
image.getArray()[height:, :width] = imageList[2].getArray(
)[::-1, :] # flip in y
image.getArray()[height:, width:] = imageList[3].getArray(
)[::-1, ::-1] # flip in x and y
image.getArray()[:] += self.noise
return image
# Construct detector
detName = 'detector 1'
detId = 1
detSerial = 'serial 1'
orientation = cameraGeom.Orientation()
pixelSize = lsst.geom.Extent2D(1, 1)
bbox = lsst.geom.Box2I(lsst.geom.Point2I(0, 0),
lsst.geom.Extent2I(2 * width, 2 * height))
crosstalk = np.array(self.crosstalk, dtype=np.float32)
camBuilder = cameraGeom.Camera.Builder("fakeCam")
detBuilder = camBuilder.add(detName, detId)
detBuilder.setSerial(detSerial)
detBuilder.setBBox(bbox)
detBuilder.setOrientation(orientation)
detBuilder.setPixelSize(pixelSize)
detBuilder.setCrosstalk(crosstalk)
# Construct second detector in this fake camera
detName = 'detector 2'
detId = 2
detSerial = 'serial 2'
orientation = cameraGeom.Orientation()
pixelSize = lsst.geom.Extent2D(1, 1)
bbox = lsst.geom.Box2I(lsst.geom.Point2I(0, 0),
lsst.geom.Extent2I(2 * width, 2 * height))
crosstalk = np.array(self.crosstalk, dtype=np.float32)
detBuilder2 = camBuilder.add(detName, detId)
detBuilder2.setSerial(detSerial)
detBuilder2.setBBox(bbox)
detBuilder2.setOrientation(orientation)
detBuilder2.setPixelSize(pixelSize)
detBuilder2.setCrosstalk(crosstalk)
# Create amp info
for ii, (xx, yy, corner) in enumerate([
(0, 0, lsst.afw.cameraGeom.ReadoutCorner.LL),
(width, 0, lsst.afw.cameraGeom.ReadoutCorner.LR),
(0, height, lsst.afw.cameraGeom.ReadoutCorner.UL),
(width, height, lsst.afw.cameraGeom.ReadoutCorner.UR)
]):
amp = cameraGeom.Amplifier.Builder()
amp.setName("amp %d" % ii)
amp.setBBox(
lsst.geom.Box2I(lsst.geom.Point2I(xx, yy),
lsst.geom.Extent2I(width, height)))
amp.setRawDataBBox(
lsst.geom.Box2I(lsst.geom.Point2I(xx, yy),
lsst.geom.Extent2I(width, height)))
amp.setReadoutCorner(corner)
detBuilder.append(amp)
detBuilder2.append(amp)
cam = camBuilder.finish()
ccd1 = cam.get('detector 1')
ccd2 = cam.get('detector 2')
self.exposure = lsst.afw.image.makeExposure(
lsst.afw.image.makeMaskedImage(construct(withCrosstalk)))
self.exposure.setDetector(ccd1)
# Create a single ctSource that will be used for interChip CT
# correction.
self.ctSource = lsst.afw.image.makeExposure(
lsst.afw.image.makeMaskedImage(construct(withCrosstalk)))
self.ctSource.setDetector(ccd2)
self.corrected = construct(withoutCrosstalk)
if display:
disp = lsst.afw.display.Display(frame=1)
disp.mtv(self.exposure, title="exposure")
disp = lsst.afw.display.Display(frame=0)
disp.mtv(self.corrected, title="corrected exposure")
def makeImage(self, ImageClass, scaling, addNoise=True):
"""Make an image for testing
We create an image, persist and unpersist it, returning
some data to the caller.
Parameters
----------
ImageClass : `type`, an `lsst.afw.image.Image` class
Class of image to create.
scaling : `lsst.afw.fits.ImageScalingOptions`
Scaling to apply during persistence.
addNoise : `bool`
Add noise to image?
Returns
-------
image : `lsst.afw.image.Image` (ImageClass)
Created image.
unpersisted : `lsst.afw.image.Image` (ImageClass)
Unpersisted image.
bscale, bzero : `float`
FITS scale factor and zero used.
minValue, maxValue : `float`
Minimum and maximum value given the nominated scaling.
"""
image = ImageClass(self.bbox)
mask = lsst.afw.image.Mask(self.bbox)
mask.addMaskPlane(self.badMask)
bad = mask.getPlaneBitMask(self.badMask)
image.set(self.base)
image[self.highPixel, LOCAL] = self.highValue
image[self.lowPixel, LOCAL] = self.lowValue
image[self.maskedPixel, LOCAL] = self.maskedValue
mask[self.maskedPixel, LOCAL] = bad
rng = np.random.RandomState(12345)
dtype = image.getArray().dtype
if addNoise:
image.getArray()[:] += rng.normal(
0.0, self.stdev,
image.getArray().shape).astype(dtype)
with lsst.utils.tests.getTempFilePath(".fits") as filename:
with lsst.afw.fits.Fits(filename, "w") as fits:
options = lsst.afw.fits.ImageWriteOptions(scaling)
header = lsst.daf.base.PropertyList()
image.writeFits(fits, options, header, mask)
unpersisted = ImageClass(filename)
self.assertEqual(image.getBBox(), unpersisted.getBBox())
header = lsst.afw.fits.readMetadata(filename)
bscale = header.getScalar("BSCALE")
bzero = header.getScalar("BZERO")
if scaling.algorithm != ImageScalingOptions.NONE:
self.assertEqual(header.getScalar("BITPIX"), scaling.bitpix)
if scaling.bitpix == 8: # unsigned, says FITS
maxValue = bscale * (2**scaling.bitpix - 1) + bzero
minValue = bzero
else:
maxValue = bscale * (2**(scaling.bitpix - 1) - 1) + bzero
if scaling.bitpix == 32:
# cfitsio pads 10 values, and so do we
minValue = -bscale * (2**(scaling.bitpix - 1) - 10) + bzero
else:
minValue = -bscale * (2**(scaling.bitpix - 1)) + bzero
# Convert scalars to the appropriate type
maxValue = np.array(maxValue, dtype=image.getArray().dtype)
minValue = np.array(minValue, dtype=image.getArray().dtype)
checkAstropy(unpersisted, filename)
return image, unpersisted, bscale, bzero, minValue, maxValue
def setUp(self):
width, height = 250, 500
self.numAmps = 4
numPixelsPerAmp = 1000
# crosstalk[i][j] is the fraction of the j-th amp present on the i-th amp.
self.crosstalk = [[0.0, 1e-4, 2e-4, 3e-4], [3e-4, 0.0, 2e-4, 1e-4],
[4e-4, 5e-4, 0.0, 6e-4], [7e-4, 8e-4, 9e-4, 0.0]]
self.value = 12345
self.crosstalkStr = "XTLK"
# A bit of noise is important, because otherwise the pixel distributions are razor-thin
# and then rejection doesn't work
rng = np.random.RandomState(12345)
self.noise = rng.normal(0.0, 0.1, (2 * height, 2 * width))
# Create amp images
withoutCrosstalk = [
lsst.afw.image.ImageF(width, height) for _ in range(self.numAmps)
]
for image in withoutCrosstalk:
image.set(0)
xx = rng.randint(0, width, numPixelsPerAmp)
yy = rng.randint(0, height, numPixelsPerAmp)
image.getArray()[yy, xx] = self.value
# Add in crosstalk
withCrosstalk = [
image.Factory(image, True) for image in withoutCrosstalk
]
for ii, iImage in enumerate(withCrosstalk):
for jj, jImage in enumerate(withoutCrosstalk):
value = self.crosstalk[ii][jj]
iImage.scaledPlus(value, jImage)
# Put amp images together
def construct(imageList):
image = lsst.afw.image.ImageF(2 * width, 2 * height)
image.getArray()[:height, :width] = imageList[0].getArray()
image.getArray()[:height,
width:] = imageList[1].getArray()[:, ::
-1] # flip in x
image.getArray()[height:, :width] = imageList[2].getArray(
)[::-1, :] # flip in y
image.getArray()[height:, width:] = imageList[3].getArray(
)[::-1, ::-1] # flip in x and y
image.getArray()[:] += self.noise
return image
# Create amp info
schema = lsst.afw.table.AmpInfoTable.makeMinimalSchema()
amplifiers = lsst.afw.table.AmpInfoCatalog(schema)
for ii, (xx, yy, corner) in enumerate([(0, 0, LL), (width, 0, LR),
(0, height, UL),
(width, height, UR)]):
amp = amplifiers.addNew()
amp.setName("amp %d" % ii)
amp.setBBox(
lsst.afw.geom.Box2I(lsst.afw.geom.Point2I(xx, yy),
lsst.afw.geom.Extent2I(width, height)))
amp.setRawDataBBox(
lsst.afw.geom.Box2I(lsst.afw.geom.Point2I(xx, yy),
lsst.afw.geom.Extent2I(width, height)))
amp.setReadoutCorner(corner)
# Put everything together
ccd = lsst.afw.cameraGeom.Detector(
"detector", 123, lsst.afw.cameraGeom.SCIENCE, "serial",
lsst.afw.geom.Box2I(lsst.afw.geom.Point2I(0, 0),
lsst.afw.geom.Extent2I(2 * width, 2 * height)),
amplifiers, lsst.afw.cameraGeom.Orientation(),
lsst.afw.geom.Extent2D(1, 1), {},
np.array(self.crosstalk, dtype=np.float32))
self.exposure = lsst.afw.image.makeExposure(
lsst.afw.image.makeMaskedImage(construct(withCrosstalk)))
self.exposure.setDetector(ccd)
self.corrected = construct(withoutCrosstalk)
if display:
disp = lsst.afw.display.Display(frame=1)
disp.mtv(self.exposure, title="exposure")
disp = lsst.afw.display.Display(frame=0)
disp.mtv(self.corrected, title="corrected exposure")
def setUp(self):
width, height = 250, 500
self.numAmps = 4
numPixelsPerAmp = 1000
# crosstalk[i][j] is the fraction of the j-th amp present on the i-th amp.
self.crosstalk = [[0.0, 1e-4, 2e-4, 3e-4],
[3e-4, 0.0, 2e-4, 1e-4],
[4e-4, 5e-4, 0.0, 6e-4],
[7e-4, 8e-4, 9e-4, 0.0]]
self.value = 12345
self.crosstalkStr = "XTLK"
# A bit of noise is important, because otherwise the pixel distributions are razor-thin
# and then rejection doesn't work
rng = np.random.RandomState(12345)
self.noise = rng.normal(0.0, 0.1, (2*height, 2*width))
# Create amp images
withoutCrosstalk = [lsst.afw.image.ImageF(width, height) for _ in range(self.numAmps)]
for image in withoutCrosstalk:
image.set(0)
xx = rng.randint(0, width, numPixelsPerAmp)
yy = rng.randint(0, height, numPixelsPerAmp)
image.getArray()[yy, xx] = self.value
# Add in crosstalk
withCrosstalk = [image.Factory(image, True) for image in withoutCrosstalk]
for ii, iImage in enumerate(withCrosstalk):
for jj, jImage in enumerate(withoutCrosstalk):
value = self.crosstalk[ii][jj]
iImage.scaledPlus(value, jImage)
# Put amp images together
def construct(imageList):
image = lsst.afw.image.ImageF(2*width, 2*height)
image.getArray()[:height, :width] = imageList[0].getArray()
image.getArray()[:height, width:] = imageList[1].getArray()[:, ::-1] # flip in x
image.getArray()[height:, :width] = imageList[2].getArray()[::-1, :] # flip in y
image.getArray()[height:, width:] = imageList[3].getArray()[::-1, ::-1] # flip in x and y
image.getArray()[:] += self.noise
return image
# Create amp info
schema = lsst.afw.table.AmpInfoTable.makeMinimalSchema()
amplifiers = lsst.afw.table.AmpInfoCatalog(schema)
for ii, (xx, yy, corner) in enumerate([(0, 0, LL),
(width, 0, LR),
(0, height, UL),
(width, height, UR)]):
amp = amplifiers.addNew()
amp.setName("amp %d" % ii)
amp.setBBox(lsst.afw.geom.Box2I(lsst.afw.geom.Point2I(xx, yy),
lsst.afw.geom.Extent2I(width, height)))
amp.setRawDataBBox(lsst.afw.geom.Box2I(lsst.afw.geom.Point2I(xx, yy),
lsst.afw.geom.Extent2I(width, height)))
amp.setReadoutCorner(corner)
# Put everything together
ccd = lsst.afw.cameraGeom.Detector("detector", 123, lsst.afw.cameraGeom.SCIENCE, "serial",
lsst.afw.geom.Box2I(lsst.afw.geom.Point2I(0, 0),
lsst.afw.geom.Extent2I(2*width, 2*height)),
amplifiers, lsst.afw.cameraGeom.Orientation(),
lsst.afw.geom.Extent2D(1, 1), {},
np.array(self.crosstalk, dtype=np.float32))
self.exposure = lsst.afw.image.makeExposure(lsst.afw.image.makeMaskedImage(construct(withCrosstalk)))
self.exposure.setDetector(ccd)
self.corrected = construct(withoutCrosstalk)
if display:
disp = lsst.afw.display.Display(frame=1)
disp.mtv(self.exposure, title="exposure")
disp = lsst.afw.display.Display(frame=0)
disp.mtv(self.corrected, title="corrected exposure")
