def setUp(self):
baseDir = os.path.join(getPackageDir('sims_GalSimInterface'),
'tests', 'cameraData')
self.camera = ReturnCamera(baseDir)
ra = 145.0
dec = -73.0
self.epoch = 2000.0
mjd = 49250.0
rotSkyPos = 45.0
self.obs = ObservationMetaData(unrefractedRA=ra,
unrefractedDec=dec,
boundType='circle',
boundLength=1.0,
mjd=mjd,
rotSkyPos=rotSkyPos)
raPointing, \
decPointing = _observedFromICRS(numpy.array([numpy.radians(ra)]),
numpy.array([numpy.radians(dec)]),
obs_metadata=self.obs,
epoch=self.epoch)
self.ra = raPointing[0]
self.dec = decPointing[0]
def ssoInFov(self, interpfuncs, simdata, rFov=np.radians(1.75),
useCamera=True,
simdataRaCol = 'fieldRA', simdataDecCol='fieldDec'):
"""
Return the indexes of the simdata observations where the object was inside the fov.
"""
# See if the object is within 'rFov' of the center of the boresight.
raSso = np.radians(interpfuncs['ra'](simdata['expMJD']))
decSso = np.radians(interpfuncs['dec'](simdata['expMJD']))
sep = haversine(raSso, decSso, simdata[simdataRaCol], simdata[simdataDecCol])
if not useCamera:
idxObsRough = np.where(sep<rFov)[0]
return idxObsRough
# Or go on and use the camera footprint.
try:
self.camera
except AttributeError:
self._setupCamera()
idxObs = []
idxObsRough = np.where(sep<self.cameraFov)[0]
for idx in idxObsRough:
mjd = simdata[idx]['expMJD']
obs_metadata = ObservationMetaData(unrefractedRA=np.degrees(simdata[idx][simdataRaCol]),
unrefractedDec=np.degrees(simdata[idx][simdataDecCol]),
rotSkyPos=np.degrees(simdata[idx]['rotSkyPos']),
mjd=simdata[idx]['expMJD'])
raObj = np.radians(np.array([interpfuncs['ra'](simdata[idx]['expMJD'])]))
decObj = np.radians(np.array([interpfuncs['dec'](simdata[idx]['expMJD'])]))
raObj, decObj = _observedFromICRS(raObj, decObj, obs_metadata=obs_metadata, epoch=self.epoch)
chipNames = _chipNameFromRaDec(ra=raObj,dec=decObj, epoch=self.epoch, camera=self.camera, obs_metadata=obs_metadata)
if chipNames != [None]:
idxObs.append(idx)
idxObs = np.array(idxObs)
return idxObs
def setUp(self):
baseDir = os.path.join(getPackageDir('sims_GalSimInterface'), 'tests', 'cameraData')
self.camera = ReturnCamera(baseDir)
self.obs = ObservationMetaData(unrefractedRA=25.0, unrefractedDec=-10.0,
boundType='circle', boundLength=1.0,
mjd=49250.0, rotSkyPos=0.0)
self.epoch = 2000.0
self.raPointing, self.decPointing = _observedFromICRS(numpy.array([self.obs._unrefractedRA]),
numpy.array([self.obs._unrefractedDec]),
obs_metadata=self.obs,
epoch=self.epoch)
def ssoInFov(self,
interpfuncs,
simdata,
rFov=np.radians(1.75),
useCamera=True,
simdataRaCol='fieldRA',
simdataDecCol='fieldDec'):
"""
Return the indexes of the simdata observations where the object was inside the fov.
"""
# See if the object is within 'rFov' of the center of the boresight.
raSso = np.radians(interpfuncs['ra'](simdata['expMJD']))
decSso = np.radians(interpfuncs['dec'](simdata['expMJD']))
sep = haversine(raSso, decSso, simdata[simdataRaCol],
simdata[simdataDecCol])
if not useCamera:
idxObsRough = np.where(sep < rFov)[0]
return idxObsRough
# Or go on and use the camera footprint.
try:
self.camera
except AttributeError:
self._setupCamera()
idxObs = []
idxObsRough = np.where(sep < self.cameraFov)[0]
for idx in idxObsRough:
mjd = simdata[idx]['expMJD']
obs_metadata = ObservationMetaData(
unrefractedRA=np.degrees(simdata[idx][simdataRaCol]),
unrefractedDec=np.degrees(simdata[idx][simdataDecCol]),
rotSkyPos=np.degrees(simdata[idx]['rotSkyPos']),
mjd=simdata[idx]['expMJD'])
raObj = np.radians(
np.array([interpfuncs['ra'](simdata[idx]['expMJD'])]))
decObj = np.radians(
np.array([interpfuncs['dec'](simdata[idx]['expMJD'])]))
raObj, decObj = _observedFromICRS(raObj,
decObj,
obs_metadata=obs_metadata,
epoch=self.epoch)
chipNames = _chipNameFromRaDec(ra=raObj,
dec=decObj,
epoch=self.epoch,
camera=self.camera,
obs_metadata=obs_metadata)
if chipNames != [None]:
idxObs.append(idx)
idxObs = np.array(idxObs)
return idxObs
def tanWcsFromDetector(afwDetector, afwCamera, obs_metadata, epoch):
"""
Take an afw.cameraGeom detector and return a WCS which approximates
the focal plane as perfectly flat (i.e. it ignores optical distortions
that the telescope may impose on the image)
@param [in] afwDetector is an instantiation of afw.cameraGeom's Detector
class which characterizes the detector for which you wish to return th
WCS
@param [in] afwCamera is an instantiation of afw.cameraGeom's Camera
class which characterizes the camera containing afwDetector
@param [in] obs_metadata is an instantiation of ObservationMetaData
characterizing the telescope's current pointing
@param [in] epoch is the epoch in Julian years of the equinox against
which RA and Dec are measured
@param [out] tanWcs is an instantiation of afw.image's TanWcs class
representing the WCS of the detector as if there were no optical
distortions imposed by the telescope.
"""
xTanPixMin, xTanPixMax, \
yTanPixMin, yTanPixMax = _getTanPixelBounds(afwDetector, afwCamera)
xPixList = []
yPixList = []
nameList = []
#dx and dy are set somewhat heuristically
#setting them eqal to 0.1(max-min) lead to errors
#on the order of 0.7 arcsec in the WCS
dx = 0.5*(xTanPixMax-xTanPixMin)
dy = 0.5*(yTanPixMax-yTanPixMin)
for xx in numpy.arange(xTanPixMin, xTanPixMax+0.5*dx, dx):
for yy in numpy.arange(yTanPixMin, yTanPixMax+0.5*dx, dx):
xPixList.append(xx)
yPixList.append(yy)
nameList.append(afwDetector.getName())
raList, decList = _raDecFromPixelCoords(numpy.array(xPixList),
numpy.array(yPixList),
nameList,
camera=afwCamera,
obs_metadata=obs_metadata,
epoch=epoch,
includeDistortion=False)
raPointing, decPointing = _observedFromICRS(numpy.array([obs_metadata._unrefractedRA]),
numpy.array([obs_metadata._unrefractedDec]),
obs_metadata=obs_metadata, epoch=epoch)
crPix1, crPix2 = _pixelCoordsFromRaDec(raPointing, decPointing,
chipNames=[afwDetector.getName()], camera=afwCamera,
obs_metadata=obs_metadata, epoch=epoch,
includeDistortion=False)
lonList, latList = _nativeLonLatFromRaDec(raList, decList, raPointing[0], decPointing[0])
#convert from native longitude and latitude to intermediate world coordinates
#according to equations (12), (13), (54) and (55) of
#
#Calabretta and Greisen (2002), A&A 395, p. 1077
#
radiusList = 180.0/(numpy.tan(latList)*numpy.pi)
uList = radiusList*numpy.sin(lonList)
vList = -radiusList*numpy.cos(lonList)
delta_xList = xPixList - crPix1[0]
delta_yList = yPixList - crPix2[0]
bVector = numpy.array([
(delta_xList*uList).sum(),
(delta_yList*uList).sum(),
(delta_xList*vList).sum(),
(delta_yList*vList).sum()
])
offDiag = (delta_yList*delta_xList).sum()
xsq = numpy.power(delta_xList,2).sum()
ysq = numpy.power(delta_yList,2).sum()
aMatrix = numpy.array([
[xsq, offDiag, 0.0, 0.0],
[offDiag, ysq, 0.0, 0.0],
[0.0, 0.0, xsq, offDiag],
[0.0, 0.0, offDiag, ysq]
])
coeffs = numpy.linalg.solve(aMatrix, bVector)
crValPoint = afwGeom.Point2D(numpy.degrees(raPointing[0]), numpy.degrees(decPointing[0]))
crPixPoint = afwGeom.Point2D(crPix1[0], crPix2[0])
fitsHeader = dafBase.PropertyList()
fitsHeader.set("RADESYS", "ICRS")
fitsHeader.set("EQUINOX", epoch)
fitsHeader.set("CRVAL1", numpy.degrees(raPointing[0]))
fitsHeader.set("CRVAL2", numpy.degrees(decPointing[0]))
fitsHeader.set("CRPIX1", crPix1[0]+1) # the +1 is because LSST uses 0-indexed images
fitsHeader.set("CRPIX2", crPix2[0]+1) # FITS files use 1-indexed images
fitsHeader.set("CTYPE1", "RA---TAN")
fitsHeader.set("CTYPE2", "DEC--TAN")
fitsHeader.setDouble("CD1_1", coeffs[0])
fitsHeader.setDouble("CD1_2", coeffs[1])
fitsHeader.setDouble("CD2_1", coeffs[2])
fitsHeader.setDouble("CD2_2", coeffs[3])
tanWcs = afwImage.cast_TanWcs(afwImage.makeWcs(fitsHeader))
return tanWcs
