def sdss_coadd(targetwcs, bands):
from astrometry.sdss import DR9, band_index
from astrometry.sdss import AsTransWrapper
#sdss = DR9(basedir=photoobjdir)
#sdss.useLocalTree()
sdss = DR9(basedir='tmp')
sdss.saveUnzippedFiles('tmp')
#wfn = sdss.filenames.get('window_flist', None)
wfn = os.path.join(os.environ.get('PHOTO_RESOLVE', ''),
'window_flist.fits')
from astrometry.sdss.fields import radec_to_sdss_rcf
ra, dec = targetwcs.radec_center()
rad = targetwcs.radius()
rad = rad + np.hypot(10., 14.) / 2. / 60.
print('Searching for run,camcol,fields with radius', rad, 'deg')
RCF = radec_to_sdss_rcf(ra, dec, radius=rad * 60., tablefn=wfn)
print('Found %i fields possibly in range' % len(RCF))
H, W = targetwcs.shape
sdsscoimgs = [np.zeros((H, W), np.float32) for band in bands]
sdsscons = [np.zeros((H, W), np.float32) for band in bands]
for run, camcol, field, r, d in RCF:
for iband, band in enumerate(bands):
bandnum = band_index(band)
sdss.retrieve('frame', run, camcol, field, band)
frame = sdss.readFrame(run, camcol, field, bandnum)
print('Got frame', frame)
h, w = frame.getImageShape()
simg = frame.getImage()
wcs = AsTransWrapper(frame.astrans, w, h, 0.5, 0.5)
try:
Yo, Xo, Yi, Xi, nil = resample_with_wcs(targetwcs, wcs)
except OverlapError:
continue
sdsscoimgs[iband][Yo, Xo] += simg[Yi, Xi]
sdsscons[iband][Yo, Xo] += 1
for co, n in zip(sdsscoimgs, sdsscons):
co /= np.maximum(1e-6, n)
return sdsscoimgs, sdsscons
def sdss_coadd(targetwcs, bands):
from astrometry.sdss import DR9, band_index
from astrometry.sdss import AsTransWrapper
#sdss = DR9(basedir=photoobjdir)
#sdss.useLocalTree()
sdss = DR9(basedir='tmp')
sdss.saveUnzippedFiles('tmp')
#wfn = sdss.filenames.get('window_flist', None)
wfn = os.path.join(os.environ.get('PHOTO_RESOLVE',''), 'window_flist.fits')
from astrometry.sdss.fields import radec_to_sdss_rcf
ra,dec = targetwcs.radec_center()
rad = targetwcs.radius()
rad = rad + np.hypot(10.,14.)/2./60.
print 'Searching for run,camcol,fields with radius', rad, 'deg'
RCF = radec_to_sdss_rcf(ra, dec, radius=rad*60., tablefn=wfn)
print 'Found %i fields possibly in range' % len(RCF)
H,W = targetwcs.shape
sdsscoimgs = [np.zeros((H,W),np.float32) for band in bands]
sdsscons = [np.zeros((H,W),np.float32) for band in bands]
for run,camcol,field,r,d in RCF:
for iband,band in enumerate(bands):
bandnum = band_index(band)
sdss.retrieve('frame', run, camcol, field, band)
frame = sdss.readFrame(run, camcol, field, bandnum)
print 'Got frame', frame
h,w = frame.getImageShape()
simg = frame.getImage()
wcs = AsTransWrapper(frame.astrans, w, h, 0.5, 0.5)
try:
Yo,Xo,Yi,Xi,nil = resample_with_wcs(targetwcs, wcs, [], 3)
except OverlapError:
continue
sdsscoimgs[iband][Yo,Xo] += simg[Yi,Xi]
sdsscons [iband][Yo,Xo] += 1
for co,n in zip(sdsscoimgs, sdsscons):
co /= np.maximum(1e-6, n)
return sdsscoimgs, sdsscons
def stage_initplots(
coimgs=None, cons=None, bands=None, ps=None,
targetwcs=None,
blobs=None,
T=None, cat=None, tims=None, tractor=None, **kwargs):
# RGB image
# plt.clf()
# dimshow(get_rgb(coimgs, bands))
# ps.savefig()
print 'T:'
T.about()
# cluster zoom-in
#x0,x1, y0,y1 = 1700,2700, 200,1200
#x0,x1, y0,y1 = 1900,2500, 400,1000
#x0,x1, y0,y1 = 1900,2400, 450,950
x0,x1, y0,y1 = 0,500, 0,500
clco = [co[y0:y1, x0:x1] for co in coimgs]
clW, clH = x1-x0, y1-y0
clwcs = targetwcs.get_subimage(x0, y0, clW, clH)
plt.figure(figsize=(6,6))
plt.subplots_adjust(left=0.005, right=0.995, bottom=0.005, top=0.995)
ps.suffixes = ['png','pdf']
# cluster zoom-in
rgb = get_rgb(clco, bands)
plt.clf()
dimshow(rgb, ticks=False)
ps.savefig()
# blobs
#b0 = blobs
#b1 = binary_dilation(blobs, np.ones((3,3)))
#bout = np.logical_and(b1, np.logical_not(b0))
# b0 = blobs
# b1 = binary_erosion(b0, np.ones((3,3)))
# bout = np.logical_and(b0, np.logical_not(b1))
# # set green
# rgb[:,:,0][bout] = 0.
# rgb[:,:,1][bout] = 1.
# rgb[:,:,2][bout] = 0.
# plt.clf()
# dimshow(rgb, ticks=False)
# ps.savefig()
# Initial model (SDSS only)
try:
# convert from string to int
T.objid = np.array([int(x) if len(x) else 0 for x in T.objid])
except:
pass
scat = Catalog(*[cat[i] for i in np.flatnonzero(T.objid)])
sedcat = Catalog(*[cat[i] for i in np.flatnonzero(T.objid == 0)])
print len(cat), 'total sources'
print len(scat), 'SDSS sources'
print len(sedcat), 'SED-matched sources'
tr = Tractor(tractor.images, scat)
comods = []
comods2 = []
for iband,band in enumerate(bands):
comod = np.zeros((clH,clW))
comod2 = np.zeros((clH,clW))
con = np.zeros((clH,clW))
for itim,tim in enumerate(tims):
if tim.band != band:
continue
(Yo,Xo,Yi,Xi) = tim.resamp
mod = tr.getModelImage(tim)
Yo -= y0
Xo -= x0
K, = np.nonzero((Yo >= 0) * (Yo < clH) * (Xo >= 0) * (Xo < clW))
Xo,Yo,Xi,Yi = Xo[K],Yo[K],Xi[K],Yi[K]
comod[Yo,Xo] += mod[Yi,Xi]
ie = tim.getInvError()
noise = np.random.normal(size=ie.shape) / ie
noise[ie == 0] = 0.
comod2[Yo,Xo] += mod[Yi,Xi] + noise[Yi,Xi]
con[Yo,Xo] += 1
comod /= np.maximum(con, 1)
comods.append(comod)
comod2 /= np.maximum(con, 1)
comods2.append(comod2)
plt.clf()
dimshow(get_rgb(comods2, bands), ticks=False)
ps.savefig()
plt.clf()
dimshow(get_rgb(comods, bands), ticks=False)
ps.savefig()
# Overplot SDSS sources
ax = plt.axis()
for src in scat:
rd = src.getPosition()
ok,x,y = clwcs.radec2pixelxy(rd.ra, rd.dec)
cc = (0,1,0)
if isinstance(src, PointSource):
plt.plot(x-1, y-1, 'o', mec=cc, mfc='none', ms=10, mew=1.5)
else:
plt.plot(x-1, y-1, 'o', mec='r', mfc='none', ms=10, mew=1.5)
plt.axis(ax)
ps.savefig()
# Add SED-matched detections
for src in sedcat:
rd = src.getPosition()
ok,x,y = clwcs.radec2pixelxy(rd.ra, rd.dec)
plt.plot(x-1, y-1, 'o', mec='c', mfc='none', ms=10, mew=1.5)
plt.axis(ax)
ps.savefig()
# Mark SED-matched detections on image
plt.clf()
dimshow(get_rgb(clco, bands), ticks=False)
ax = plt.axis()
for src in sedcat:
rd = src.getPosition()
ok,x,y = clwcs.radec2pixelxy(rd.ra, rd.dec)
#plt.plot(x-1, y-1, 'o', mec='c', mfc='none', ms=10, mew=1.5)
x,y = x-1, y-1
hi,lo = 20,7
# plt.plot([x-lo,x-hi],[y,y], 'c-')
# plt.plot([x+lo,x+hi],[y,y], 'c-')
# plt.plot([x,x],[y+lo,y+hi], 'c-')
# plt.plot([x,x],[y-lo,y-hi], 'c-')
plt.annotate('', (x,y+lo), xytext=(x,y+hi),
arrowprops=dict(color='c', width=1, frac=0.3, headwidth=5))
plt.axis(ax)
ps.savefig()
# plt.clf()
# dimshow(get_rgb([gaussian_filter(x,1) for x in clco], bands), ticks=False)
# ps.savefig()
# Resid
# plt.clf()
# dimshow(get_rgb([im-mo for im,mo in zip(clco,comods)], bands), ticks=False)
# ps.savefig()
# find SDSS fields within that WCS
#sdss = DR9(basedir=photoobjdir)
#sdss.useLocalTree()
sdss = DR9(basedir='tmp')
sdss.saveUnzippedFiles('tmp')
#wfn = sdss.filenames.get('window_flist', None)
wfn = os.path.join(os.environ['PHOTO_RESOLVE'], 'window_flist.fits')
from astrometry.sdss.fields import radec_to_sdss_rcf
clra,cldec = clwcs.radec_center()
clrad = clwcs.radius()
clrad = clrad + np.hypot(10.,14.)/2./60.
print 'Searching for run,camcol,fields with radius', clrad, 'deg'
RCF = radec_to_sdss_rcf(clra, cldec, radius=clrad*60., tablefn=wfn)
print 'Found %i fields possibly in range' % len(RCF)
sdsscoimgs = [np.zeros((clH,clW),np.float32) for band in bands]
sdsscons = [np.zeros((clH,clW),np.float32) for band in bands]
for run,camcol,field,r,d in RCF:
for iband,band in enumerate(bands):
bandnum = band_index(band)
sdss.retrieve('frame', run, camcol, field, band)
frame = sdss.readFrame(run, camcol, field, bandnum)
print 'Got frame', frame
h,w = frame.getImageShape()
simg = frame.getImage()
wcs = AsTransWrapper(frame.astrans, w, h, 0.5, 0.5)
try:
Yo,Xo,Yi,Xi,nil = resample_with_wcs(clwcs, wcs, [], 3)
except OverlapError:
continue
sdsscoimgs[iband][Yo,Xo] += simg[Yi,Xi]
sdsscons [iband][Yo,Xo] += 1
for co,n in zip(sdsscoimgs, sdsscons):
co /= np.maximum(1e-6, n)
plt.clf()
dimshow(get_rgb(sdsscoimgs, bands, **rgbkwargs), ticks=False)
#plt.title('SDSS')
ps.savefig()
