def make_fits_images(run, camcol, field):
"""gets field files from local cache (or sdss), returns UGRIZ dict of
fits images"""
print """==================================================\n\n
Grabbing image files from the cache.
TODO: turn off the tractor printing... """
imgs = {}
for band in BANDS:
print "reading in band %s" % band
imgs[band] = sdss.get_tractor_image_dr9(run, camcol, field, band)
fn = asdss.DR9().retrieve('photoField', run, camcol, field)
F = aufits.fits_table(fn)
# convert to FitsImage's
imgfits = {}
for iband,band in enumerate(BANDS):
print "converting images %s" % band
frame = asdss.DR9().readFrame(run, camcol, field, band)
calib = np.median(frame.getCalibVec())
gain = F[0].gain[iband]
darkvar = F[0].dark_variance[iband]
sky = np.median(frame.getSky())
imgfits[band] = celeste.FitsImage(iband,
timg=imgs[band],
calib=calib,
gain=gain,
darkvar=darkvar,
sky=sky)
return imgfits
def make_fits_images(run, camcol, field):
"""gets field files from local cache (or sdss), returns UGRIZ dict of
fits images"""
print """==================================================\n\n
Grabbing image files from the cache.
TODO: turn off the tractor printing... """
imgs = {}
for band in BANDS:
print "reading in band %s" % band
imgs[band] = sdss.get_tractor_image_dr9(run, camcol, field, band)
fn = asdss.DR9().retrieve('photoField', run, camcol, field)
F = aufits.fits_table(fn)
# convert to FitsImage's
imgfits = {}
for iband,band in enumerate(BANDS):
print "converting images %s" % band
frame = asdss.DR9().readFrame(run, camcol, field, band)
calib = np.median(frame.getCalibVec())
gain = F[0].gain[iband]
darkvar = F[0].dark_variance[iband]
sky = np.median(frame.getSky())
imgfits[band] = celeste.FitsImage(band,
timg=imgs[band],
calib=calib,
gain=gain,
darkvar=darkvar,
sky=sky)
return imgfits
def make_fits_images(run, camcol, field):
"""gets field files from local cache (or sdss), returns UGRIZ dict of
fits images"""
print """==================================================\n\n
Grabbing image files from the cache.
TODO: turn off the tractor printing... """
# grab photo field objects - cache in 'sdss_data' if possible
if not os.path.exists('sdss_data'):
os.makedirs('sdss_data')
sdssobj = asdss.DR9(basedir='sdss_data')
# grab images
imgs = {}
for band in BANDS:
print "reading in band %s" % band
imgs[band] = sdss.get_tractor_image_dr9(run,
camcol,
field,
band,
sdss=sdssobj)
# grab photo field
fn = sdssobj.retrieve('photoField', run, camcol, field)
F = aufits.fits_table(fn)
# convert to FitsImage's
imgfits = {}
for iband, band in enumerate(BANDS):
print "converting images %s" % band
frame = sdssobj.readFrame(run, camcol, field, band)
calib = np.median(frame.getCalibVec())
gain = F[0].gain[iband]
darkvar = F[0].dark_variance[iband]
sky = np.median(frame.getSky())
imgfits[band] = FitsImage(band,
timg=imgs[band],
calib=calib,
gain=gain,
darkvar=darkvar,
sky=sky,
frame=frame,
fits_table=F)
return imgfits
def make_fits_images(run, camcol, field):
"""gets field files from local cache (or sdss), returns UGRIZ dict of
fits images"""
print """==================================================\n\n
Grabbing image files from the cache.
TODO: turn off the tractor printing... """
# grab photo field objects - cache in 'sdss_data' if possible
if not os.path.exists('sdss_data'):
os.makedirs('sdss_data')
sdssobj = asdss.DR9(basedir='sdss_data')
# grab images
imgs = {}
for band in BANDS:
print "reading in band %s" % band
imgs[band] = sdss.get_tractor_image_dr9(run, camcol, field, band, sdss=sdssobj)
# grab photo field
fn = sdssobj.retrieve('photoField', run, camcol, field)
F = aufits.fits_table(fn)
# convert to FitsImage's
imgfits = {}
for iband,band in enumerate(BANDS):
print "converting images %s" % band
frame = sdssobj.readFrame(run, camcol, field, band)
calib = np.median(frame.getCalibVec())
gain = F[0].gain[iband]
darkvar = F[0].dark_variance[iband]
sky = np.median(frame.getSky())
imgfits[band] = FitsImage(band,
timg=imgs[band],
calib=calib,
gain=gain,
darkvar=darkvar,
sky=sky,
frame=frame,
fits_table=F)
return imgfits
def getSDSSdata(rcf,roi,datadir,vb=False):
'''
INPUTS
rcf A list of number, specifying the SDSS run, camcol and field ids, ra and dec
roi Width of region of interest (in arcsec)
datadir Name of directory where fits images will be written to (for posterity)
vb Verbose operation?
OUTPUTS
images A list of tractor image objects, one per image
centroids List of flux centroids, one per image
total_mags List of total magnitudes, one per image
bands List of filter names, one per image
'''
run,camcol,field,ra,dec = rcf[0],rcf[1],rcf[2],rcf[3],rcf[4]
roipix = int(roi/0.396)
geometry = (ra, dec, 0.5*roipix)
SDSSbands = ['u','g','r','i','z']
bands = []
images = []
centroids = []
total_mags = []
if vb:
print "Querying SDSS skyserver for data at ra,dec = ",ra,dec
print " in run, camcol, field = ",[run,camcol,field]
print "Looking to make cutouts that are ",roi," arcsec (",roipix," pixels) across"
# Ideally we would have first grabbed SDSS run, camcol and field id:
# rcf = radec_to_sdss_rcf(ra,dec,radius=math.hypot(fieldradius,13./2.),tablefn="dr9fields.fits")
# but, we do not have this table. So need an rcf passed in as an argument.
for band in SDSSbands:
if vb:
print " "
print "--------"+band+"-band--------"
# Get SDSS image:
image,info = st.get_tractor_image_dr9(run, camcol, field, band, roiradecsize=geometry)
bands.append(band)
images.append(image)
# Compute flux centroid for this image (dummy for now):
centroid = tractor.RaDecPos(ra,dec)
centroids.append(centroid)
# Compute total magnitude for this image:
background = np.median(image.data)
diffimage = image.data - background
total_flux = np.sum(diffimage)
total_mag = image.photocal.countsToMag(total_flux)
total_mags.append(total_mag)
if vb:
print "Got pixel data in the "+band+" band"
print "Image size: ",image.data.shape,"pixels"
print "Total brighness of image (mags): ",total_mag
return images,centroids,np.array(total_mags),np.array(bands)
axarr[0].set_title("Celeste Render")
##########################
# plot tractor rendering #
#########################
print "\n========== tractor render ===============\n"
from tractor import sdss as st
from tractor import Tractor
from astrometry.sdss import DR9
# get images
sdss = DR9(basedir='sdss_data')
tim, tinf = st.get_tractor_image_dr9(run,
camcol,
field,
fimg.band,
curl=True,
roi=(xlim[0], xlim[1] - 1, ylim[0],
ylim[1] - 1),
sdss=sdss,
psf='kl-gm')
#patch = ts.getModelPatch(tim)
px, py = fimg.equa2pixel(s.params.u) - np.array([xlim[0], ylim[0]])
patch = ts.getUnitFluxModelPatch(tim) #, px, py)
mod = patch.getImage()
# get corresponding sources
from CelestePy.util.misc import plot_util
#tractor = Tractor(images = [tim], catalog=[ts])
#mod = tractor.getModelImage(tim, srcs=[ts])
cim = axarr[1].imshow(mod, extent=xlim + ylim)
plot_util.add_colorbar_to_axis(axarr[1], cim)
###########################
simg, ylim, xlim = s.compute_scatter_on_pixels(fimg)
print "\n========== celeste render ===============\n"
s.plot(fimg, ax=axarr[0], unit_flux=True)
axarr[0].set_title("Celeste Render")
##########################
# plot tractor rendering #
#########################
print "\n========== tractor render ===============\n"
from tractor import sdss as st
from tractor import Tractor
from astrometry.sdss import DR9
# get images
sdss = DR9(basedir='sdss_data')
tim,tinf = st.get_tractor_image_dr9(run, camcol, field, fimg.band,
curl=True, roi=(xlim[0], xlim[1]-1, ylim[0], ylim[1]-1), sdss=sdss, psf='kl-gm')
#patch = ts.getModelPatch(tim)
px, py = fimg.equa2pixel(s.params.u) - np.array([xlim[0], ylim[0]])
patch = ts.getUnitFluxModelPatch(tim) #, px, py)
mod = patch.getImage()
# get corresponding sources
from CelestePy.util.misc import plot_util
#tractor = Tractor(images = [tim], catalog=[ts])
#mod = tractor.getModelImage(tim, srcs=[ts])
cim = axarr[1].imshow(mod, extent=xlim+ylim)
plot_util.add_colorbar_to_axis(axarr[1], cim)
axarr[1].set_title("Tractor Render")
cim = axarr[2].imshow(mod - simg)
plot_util.add_colorbar_to_axis(axarr[2], cim)
def make_resampled_psf_images(RCF, band, ra, dec, sdss,
targetwcs, W, H, addToHeader, plots=False,
max_exposures=1):
""" Given a list of (Run, Camcol, Field) tuples, returns a list of
(img, imgvar, and header) info for stamp sized imgs centered at ra, dec
"""
# populate list of resampled images and their new psf's
output_imgs = []
# zip through each frame, cut out the relevatn patch
for ifield, (run,camcol,field) in enumerate(RCF[:max_exposures]):
print """=============================
RCF %d of %d
======================== """%(ifield, len(RCF))
# get photofield filename from SDSS, cut it down to relevent RCF
fn = sdss.retrieve('photoField', run, camcol, field)
F = aufits.fits_table(fn)
F.cut((F.run == run) * (F.camcol == camcol) * (F.field == field))
print len(F), 'fields'
assert(len(F) == 1)
F = F[0]
# actually get the tractor image (check if it's in cache!)
boundpixradius = int(np.ceil(np.sqrt(2.) * pixradius))
print 'RA,Dec,size', (ra, dec, boundpixradius)
tim, tinfo = tsdss.get_tractor_image_dr9(
run, camcol, field, band, sdss=sdss, nanomaggies=True,
roiradecsize=(ra, dec, boundpixradius))
print 'Got tim:', tim
frame = sdss.readFrame(run, camcol, field, band)
if tim is None:
continue
# find pixel position for input RA, DEC in tractor image (original field)
x,y = tim.getWcs().positionToPixel(tsdss.RaDecPos(ra, dec))
x,y = int(x), int(y)
# Grab calibration information for header
tim.sdss_calib = np.median(frame.getCalibVec())
tim.sdss_sky = frame.getSkyAt(x,y)
iband = tsdss.band_index(band)
tim.sdss_gain = F.gain[iband]
tim.sdss_darkvar = F.dark_variance[iband]
# get region of interest in the original frame
roi = tinfo['roi']
x0,x1,y0,y1 = roi
# Resample to common grid
th,tw = tim.shape
wwcs = tsdss.TractorWCSWrapper(tim.getWcs(), tw, th)
try:
Yo,Xo,Yi,Xi,[rim] = aresample.resample_with_wcs(
targetwcs, wwcs, [tim.getImage()], Lanczos)
except aresample.OverlapError:
continue
img = np.zeros((H,W))
img[Yo,Xo] = rim
iv = np.zeros((H,W))
iv[Yo,Xo] = tim.getInvvar()[Yi,Xi]
# Convert old PSF to new stamp-specific PSF
newpsf = convert_psf_between_imgs(tim, targetwcs)
# create the image's header
hdr = construct_new_header(tim, tinfo, targetwcs, newpsf,
run, camcol, field, band, addToHeader)
# add to the list of resampled imgs,
output_imgs.append((img, iv, hdr))
return output_imgs
x0, y0 = roi[0], roi[2]
# rd1 is near the position of the SDSS-catalog object
# rd2 is four pixels above.
rd1 = RaDecPos(225.67954, 11.265948)
rd2 = RaDecPos(225.67991, 11.265852)
lvl = logging.INFO
logging.basicConfig(level=lvl, format='%(message)s', stream=sys.stdout)
bandname = band
sdssprefix = '%06i-%s%i-%04i' % (run, bandname, camcol, field)
timg, info = st.get_tractor_image_dr9(run,
camcol,
field,
bandname,
roi=roi)
sources = st.get_tractor_sources_dr9(run, camcol, field, bandname, roi=roi)
wcs = timg.getWcs()
for source in sources:
x, y = wcs.positionToPixel(source.getPosition(), src=source)
print(' (%.2f, %.2f):' % (x + x0, y + y0), source)
tractor = Tractor([timg], sources)
lnlorig = tractor.getLogLikelihood()
zr = np.array([-5., +20.]) * info['skysig']
save(sdssprefix + '-orig', tractor, zr)
