def std_raw(self, image, dataId):
"""Fix missing header keywords"""
md = image.getMetadata()
md.add('CRVAL2', 0.0)
if md.exists("BACKMEAN") and md.exists("ARAWGAIN"):
backmean = md.get("BACKMEAN")
gain = md.get("ARAWGAIN")
else:
backmean = 0.0
gain = 1.0
filterName = md.get("FILTER")[0]
if filterName == "Y":
filterName = "z"
# Not until the camera part gets worked out
#return super(DecamMapper, self).std_raw(image, dataId)
# we have to deal with the variance ourselves, at least for the test data I got # ACB
exp = exposureFromImage(image)
mi = exp.getMaskedImage()
var = mi.getVariance().Factory(mi.getImage())
var += backmean
var /= gain
mi2 = mi.Factory(mi.getImage(), mi.getMask(), var)
exp2 = exp.Factory(mi2, exp.getWcs())
# hacking around filter issues
exp2.setFilter(afwImage.Filter(filterName))
return exp2
def _standardizeDetrend(self, detrend, image, dataId, filter=False):
"""Hack up detrend images to remove troublesome keyword"""
md = image.getMetadata()
removeKeyword(
md, 'RADECSYS') # Irrelevant, and use of "GAPPT" breaks wcslib
exp = exposureFromImage(image)
return self._standardizeExposure(self.calibrations[detrend],
exp,
dataId,
filter=filter,
trimmed=False)
def _standardizeExposure(self, mapping, item, dataId, filter=True,
trimmed=True):
"""Default standardization function for images.
@param mapping (lsst.daf.butlerUtils.Mapping)
@param[in,out] item (lsst.afw.image.Exposure)
@param dataId (dict) Dataset identifier
@param filter (bool) Set filter?
@param trimmed (bool) Should detector be marked as trimmed?
@return (lsst.afw.image.Exposure) the standardized Exposure"""
if (re.search(r'Exposure', mapping.python) and re.search(r'Image',mapping.persistable)):
item = exposureFromImage(item)
return item
def bypass_raw(self, datasetType, pythonType, location, dataId):
ccd = dataId['ccd']
x, y = ccd % 6, ccd // 6
xSize, ySize = 2048, 4096
filename = location.getLocations()[0]
bbox = afwGeom.Box2I(afwGeom.Point2I(x * xSize, y * ySize),
afwGeom.Extent2I(xSize, ySize))
if False:
# XXX seems to be some sort of bug here for ccd=11
# cfitsio returns: READ_ERROR 108 /* error reading from FITS file */
hdu = 0
image = afwImage.DecoratedImageF(filename, hdu, bbox)
else:
# XXX this can't be at all efficient, but it works
raw = afwImage.ImageF(filename)
sub = raw.Factory(raw, bbox, True)
del raw
sub.setXY0(afwGeom.Point2I(0, 0))
image = afwImage.DecoratedImageF(sub)
del sub
exp = exposureFromImage(image)
del image
md = exp.getMetadata()
md.add("EXPTIME", 1.0)
md.add("FILTER", "OPEN")
# Install a basic (wrong, apart from pixel scale) WCS so the pixel scale can be used
md.add("RA", "00:00:00.00")
md.add("DEC", "00:00:00.0")
coord = afwCoord.IcrsCoord(afwGeom.Point2D(0, 0), afwGeom.radians)
point = afwGeom.Point2D(0, 0)
pixScale = (0.9 * afwGeom.arcseconds).asDegrees()
wcs = afwImage.makeWcs(coord, point, pixScale, 0, 0, pixScale)
wcsMd = wcs.getFitsMetadata()
for key in wcsMd.names():
md.add(key, wcsMd.get(key))
exp.setWcs(wcs)
return self._standardizeExposure(self.exposures['raw'],
exp,
dataId,
filter=True,
trimmed=False)
def bypass_raw(self, datasetType, pythonType, location, dataId):
ccd = dataId['ccd']
x, y = ccd % 6, ccd // 6
xSize, ySize = 2048, 4096
filename = location.getLocations()[0]
bbox = afwGeom.Box2I(afwGeom.Point2I(x * xSize, y * ySize), afwGeom.Extent2I(xSize, ySize))
if False:
# XXX seems to be some sort of bug here for ccd=11
# cfitsio returns: READ_ERROR 108 /* error reading from FITS file */
hdu = 0
image = afwImage.DecoratedImageF(filename, hdu, bbox)
else:
# XXX this can't be at all efficient, but it works
raw = afwImage.ImageF(filename)
sub = raw.Factory(raw, bbox, True)
del raw
sub.setXY0(afwGeom.Point2I(0,0))
image = afwImage.DecoratedImageF(sub)
del sub
exp = exposureFromImage(image)
del image
md = exp.getMetadata()
md.add("EXPTIME", 1.0)
md.add("FILTER", "OPEN")
# Install a basic (wrong, apart from pixel scale) WCS so the pixel scale can be used
md.add("RA", "00:00:00.00")
md.add("DEC", "00:00:00.0")
coord = afwCoord.IcrsCoord(afwGeom.Point2D(0, 0), afwGeom.radians)
point = afwGeom.Point2D(0, 0)
pixScale = (0.9 * afwGeom.arcseconds).asDegrees()
wcs = afwImage.makeWcs(coord, point, pixScale, 0, 0, pixScale)
wcsMd = wcs.getFitsMetadata()
for key in wcsMd.names():
md.add(key, wcsMd.get(key))
exp.setWcs(wcs)
return self._standardizeExposure(self.exposures['raw'], exp, dataId, filter=True, trimmed=False)
def std_raw(self, item, dataId):
"""Standardize a raw dataset by converting it to an Exposure.
Raw images are MEF files with one HDU for each detector.
Header keywords EXPTIME and MJD-OBS exist only in the zeroth
extension and are copied to metadata.
@param item: The image read by the butler
@param dataId: Data identifier
@return (lsst.afw.image.Exposure) the standardized Exposure
"""
# Convert the raw DecoratedImage to an Exposure, set metadata and wcs.
exp = exposureFromImage(item)
md = exp.getMetadata()
rawPath = self.map_raw(dataId).getLocations()[0]
headerPath = re.sub(r'[\[](\d+)[\]]$', "[0]", rawPath)
md0 = afwImage.readMetadata(headerPath)
# Keywords EXPTIME and MJD-OBS are used to set the calib object.
for kw in ('EXPTIME', 'MJD-OBS'):
if kw in md0.paramNames() and kw not in md.paramNames():
md.add(kw, md0.get(kw))
# As TPV is not supported yet, the wcs keywords are not pruned
# from the metadata. Once TPV is supported, the following keyword
# removal may not be necessary here and would probably be done at
# makeWcs() when the raw image is converted to an Exposure.
for kw in exp.getWcs().getFitsMetadata().paramNames():
md.remove(kw)
for kw in ('LTV1', 'LTV2'):
md.remove(kw)
# Currently the existence of some PV cards in the metadata combined
# with a CTYPE of TAN is interpreted as TPV (DM-2883).
for kw in md.paramNames():
if re.match(r'PV\d_\d', kw):
md.remove(kw)
# Standardize an Exposure, including setting the calib object
return self._standardizeExposure(self.exposures['raw'],
exp,
dataId,
trimmed=False)
def std_raw(self, item, dataId):
"""Standardize a raw dataset by converting it to an Exposure.
Raw images are MEF files with one HDU for each detector.
Header keywords EXPTIME and MJD-OBS exist only in the zeroth
extension and are copied to metadata.
@param item: The image read by the butler
@param dataId: Data identifier
@return (lsst.afw.image.Exposure) the standardized Exposure
"""
# Convert the raw DecoratedImage to an Exposure, set metadata and wcs.
exp = exposureFromImage(item)
md = exp.getMetadata()
rawPath = self.map_raw(dataId).getLocations()[0]
headerPath = re.sub(r'[\[](\d+)[\]]$', "[0]", rawPath)
md0 = afwImage.readMetadata(headerPath)
# Keywords EXPTIME and MJD-OBS are used to set the calib object.
for kw in ('EXPTIME', 'MJD-OBS'):
if kw in md0.paramNames() and kw not in md.paramNames():
md.add(kw, md0.get(kw))
# As TPV is not supported yet, the wcs keywords are not pruned
# from the metadata. Once TPV is supported, the following keyword
# removal may not be necessary here and would probably be done at
# makeWcs() when the raw image is converted to an Exposure.
for kw in exp.getWcs().getFitsMetadata().paramNames():
md.remove(kw)
for kw in ('LTV1', 'LTV2'):
md.remove(kw)
# Currently the existence of some PV cards in the metadata combined
# with a CTYPE of TAN is interpreted as TPV (DM-2883).
for kw in md.paramNames():
if re.match(r'PV\d_\d', kw):
md.remove(kw)
# Standardize an Exposure, including setting the calib object
return self._standardizeExposure(self.exposures['raw'], exp, dataId,
trimmed=False)
def _standardizeDetrend(self, detrend, image, dataId, filter=False):
"""Hack up detrend images to remove troublesome keyword"""
md = image.getMetadata()
removeKeyword(md, 'RADECSYS') # Irrelevant, and use of "GAPPT" breaks wcslib
exp = exposureFromImage(image)
return self._standardizeExposure(self.calibrations[detrend], exp, dataId, filter=filter, trimmed=False)
