def get_anns(cal, nbright=0):
wcsfn = cal.get_wcs_file()
from astrometry.util.util import anwcs
wcs = anwcs(wcsfn,0)
catdir = settings.CAT_DIR
uzcfn = os.path.join(catdir, 'uzc2000.fits')
abellfn = os.path.join(catdir, 'abell-all.fits')
ngcfn = os.path.join(catdir, 'ngc2000.fits')
ngcnamesfn = os.path.join(catdir, 'ngc2000name.fits')
icfn = os.path.join(catdir, 'ic2000.fits')
brightfn = os.path.join(catdir, 'brightstars.fits')
hdfn = settings.HENRY_DRAPER_CAT
tycho2fn = settings.TYCHO2_KD
import astrometry.blind.plotann as plotann
opt = plotann.get_empty_opts()
if nbright:
opt.nbright = nbright
rad = cal.get_radius()
# These are the same limits used in views/image.py for annotations
if rad < 1.:
opt.abellcat = abellfn
opt.hdcat = hdfn
if rad < 0.25:
opt.t2cat = tycho2fn
if rad < 10:
opt.ngc = True
opt.ngccat = ngcfn
opt.ngcname = ngcnamesfn
opt.iccat = icfn
opt.brightcat = brightfn
jobjs = plotann.get_annotations_for_wcs(wcs, opt)
return jobjs
def skyplot():
plot = Plotstuff(size=(800, 800), rdw=(103.1, 37.45, 0.8), outformat='png')
plot.color = 'verydarkblue'
plot.plot('fill')
for ext in range(1, 17):
fn = 'mos3.68488.fits'
hdr = fitsio.read_header(fn, ext=ext)
wcs = wcs_pv2sip_hdr(hdr)
plot.color = 'red'
plot.outline.wcs = anwcs_new_sip(wcs)
plot.plot('outline')
plot.color = 'white'
plot.apply_settings()
rc, dc = wcs.radec_center()
plot.text_radec(rc, dc, hdr['EXTNAME'])
plot.color = 'white'
for ext in range(1, 17):
fn = 'an2/mos3.68488.ext%02i.wcs' % ext
plot.outline.wcs = anwcs(fn)
plot.plot('outline')
plot.rgb = (0.2, 0.2, 0.2)
plot.plot_grid(0.1, 0.1)
plot.color = 'gray'
plot.plot_grid(0.5, 0.5, 0.5, 0.5)
plot.write('plot.png')
def get_anns(cal, nbright=0):
wcsfn = cal.get_wcs_file()
from astrometry.util.util import anwcs
wcs = anwcs(wcsfn,0)
catdir = settings.CAT_DIR
uzcfn = os.path.join(catdir, 'uzc2000.fits')
abellfn = os.path.join(catdir, 'abell-all.fits')
ngcfn = os.path.join(catdir, 'ngc2000.fits')
ngcnamesfn = os.path.join(catdir, 'ngc2000name.fits')
icfn = os.path.join(catdir, 'ic2000.fits')
brightfn = os.path.join(catdir, 'brightstars.fits')
hdfn = settings.HENRY_DRAPER_CAT
tycho2fn = settings.TYCHO2_KD
import astrometry.blind.plotann as plotann
opt = plotann.get_empty_opts()
if nbright:
opt.nbright = nbright
rad = cal.get_radius()
# These are the same limits used in views/image.py for annotations
if rad < 1.:
opt.abellcat = abellfn
opt.hdcat = hdfn
if rad < 0.25:
opt.t2cat = tycho2fn
if rad < 10:
opt.ngc = True
opt.ngccat = ngcfn
opt.ngcname = ngcnamesfn
opt.iccat = icfn
opt.brightcat = brightfn
jobjs = plotann.get_annotations_for_wcs(wcs, opt)
return jobjs
def __init__(self, filename, hdu=0, wcs=None):
self.x0 = 0.
self.y0 = 0.
if wcs is not None:
self.wcs = wcs
else:
from astrometry.util.util import anwcs
wcs = anwcs(filename, hdu)
self.wcs = wcs
def __init__(self, filename, hdu=0, wcs=None):
self.x0 = 0.
self.y0 = 0.
if wcs is not None:
self.wcs = wcs
else:
from astrometry.util.util import anwcs
wcs = anwcs(filename, hdu)
self.wcs = wcs
import logging
logformat = '%(message)s'
from astrometry.util.util import log_init #, LOG_VERB, LOG_MSG
loglvl = 2
if opt.verbose:
logging.basicConfig(level=logging.DEBUG, format=logformat)
loglvl += 1
else:
logging.basicConfig(level=logging.INFO, format=logformat)
log_init(loglvl)
wcsfn = args[0]
if dojson:
from astrometry.util.util import anwcs
wcs = anwcs(wcsfn,0)
jobjs = get_annotations_for_wcs(wcs, opt)
import json
j = json.dumps(jobjs)
print(j)
sys.exit(0)
fmt = PLOTSTUFF_FORMAT_JPG
s = outfn.split('.')
if len(s):
s = s[-1].lower()
if s in Plotstuff.format_map:
fmt = s
plot = Plotstuff(outformat=fmt, wcsfn=wcsfn)
#plot.wcs_file = wcsfn
#plot.outformat = fmt
from astrometry.util.util import log_init # , LOG_VERB, LOG_MSG
loglvl = 2
if opt.verbose:
logging.basicConfig(level=logging.DEBUG, format=logformat)
loglvl += 1
else:
logging.basicConfig(level=logging.INFO, format=logformat)
log_init(loglvl)
wcsfn = args[0]
if dojson:
from astrometry.util.util import anwcs
wcs = anwcs(wcsfn, 0)
jobjs = get_annotations_for_wcs(wcs, opt)
import simplejson
json = simplejson.dumps(jobjs)
print json
sys.exit(0)
fmt = PLOTSTUFF_FORMAT_JPG
s = outfn.split(".")
if len(s):
s = s[-1].lower()
if s in Plotstuff.format_map:
fmt = s
plot = Plotstuff(outformat=fmt, wcsfn=wcsfn)
# plot.wcs_file = wcsfn
def __init__(self, filename, hdu=0):
self.x0 = 0.
self.y0 = 0.
from astrometry.util.util import anwcs
wcs = anwcs(filename, hdu)
self.wcs = wcs
def plot_unmatched():
from bigboss_test import radecroi
'''
select
run, rerun, camcol, field, nChild, probPSF,
psfFlux_u, psfFlux_g, psfFlux_r, psfFlux_i, psfFlux_z,
deVRad_u, deVRad_g, deVRad_r, deVRad_i, deVRad_z,
deVAB_u, deVAB_g, deVAB_r, deVAB_i, deVAB_z,
deVPhi_u, deVPhi_g, deVPhi_r, deVPhi_i, deVPhi_z,
deVFlux_u, deVFlux_g, deVFlux_r, deVFlux_i, deVFlux_z,
expRad_u, expRad_g, expRad_r, expRad_i, expRad_z,
expAB_u, expAB_g, expAB_r, expAB_i, expAB_z,
expPhi_u, expPhi_g, expPhi_r, expPhi_i, expPhi_z,
expFlux_u, expFlux_g, expFlux_r, expFlux_i, expFlux_z,
fracDeV_u, fracDeV_g, fracDeV_r, fracDeV_i, fracDeV_z,
flags_u, flags_g, flags_r, flags_i, flags_z,
probPSF_u, probPSF_g, probPSF_r, probPSF_i, probPSF_z,
ra, dec
from PhotoPrimary
where ra between 333.5 and 335.5 and dec between -0.5 and 1.5
'''
''' -> 124k rows. (sdss-cas-testarea.fits) Distinct runs:
2585, 2728, 7712, 4203, 2583, 4192, 4207, 4184, 2662, 7717
Run #sources
2583 663
2585 675
2662 4
2728 156
4184 762
4192 36135
4203 5
4207 44078
7712 12047
7717 29911
'''
'''
select
run, rerun, camcol, field, nChild, probPSF,
psfFlux_u, psfFlux_g, psfFlux_r, psfFlux_i, psfFlux_z,
deVRad_u, deVRad_g, deVRad_r, deVRad_i, deVRad_z,
deVAB_u, deVAB_g, deVAB_r, deVAB_i, deVAB_z,
deVPhi_u, deVPhi_g, deVPhi_r, deVPhi_i, deVPhi_z,
deVFlux_u, deVFlux_g, deVFlux_r, deVFlux_i, deVFlux_z,
expRad_u, expRad_g, expRad_r, expRad_i, expRad_z,
expAB_u, expAB_g, expAB_r, expAB_i, expAB_z,
expPhi_u, expPhi_g, expPhi_r, expPhi_i, expPhi_z,
expFlux_u, expFlux_g, expFlux_r, expFlux_i, expFlux_z,
fracDeV_u, fracDeV_g, fracDeV_r, fracDeV_i, fracDeV_z,
flags_u, flags_g, flags_r, flags_i, flags_z,
probPSF_u, probPSF_g, probPSF_r, probPSF_i, probPSF_z,
ra, dec, resolveStatus, score into mydb.wisetest from PhotoObjAll
where ra between 333.5 and 335.5 and dec between -0.5 and 1.5
and (resolveStatus & (
dbo.fResolveStatus('SURVEY_PRIMARY') |
dbo.fResolveStatus('SURVEY_BADFIELD') |
dbo.fResolveStatus('SURVEY_EDGE'))) != 0
--> sdss-cas-testarea-2.fits
select
run, rerun, camcol, field, nChild, probPSF,
psfFlux_u, psfFlux_g, psfFlux_r, psfFlux_i, psfFlux_z,
deVRad_u, deVRad_g, deVRad_r, deVRad_i, deVRad_z,
deVAB_u, deVAB_g, deVAB_r, deVAB_i, deVAB_z,
deVPhi_u, deVPhi_g, deVPhi_r, deVPhi_i, deVPhi_z,
deVFlux_u, deVFlux_g, deVFlux_r, deVFlux_i, deVFlux_z,
expRad_u, expRad_g, expRad_r, expRad_i, expRad_z,
expAB_u, expAB_g, expAB_r, expAB_i, expAB_z,
expPhi_u, expPhi_g, expPhi_r, expPhi_i, expPhi_z,
expFlux_u, expFlux_g, expFlux_r, expFlux_i, expFlux_z,
fracDeV_u, fracDeV_g, fracDeV_r, fracDeV_i, fracDeV_z,
flags_u, flags_g, flags_r, flags_i, flags_z,
probPSF_u, probPSF_g, probPSF_r, probPSF_i, probPSF_z,
ra, dec, resolveStatus, score into mydb.wisetest from PhotoObjAll
where ra between 333.5 and 335.5 and dec between -0.5 and 1.5
and (resolveStatus & (
dbo.fResolveStatus('SURVEY_PRIMARY') |
dbo.fResolveStatus('SURVEY_BADFIELD') |
dbo.fResolveStatus('SURVEY_EDGE') |
dbo.fResolveStatus('SURVEY_BEST')
)) != 0
--> sdss-cas-testarea-3.fits
'''
''' Check it out: spatial source density looks fine. No overlap between runs.
'''
rng = ((333.5, 335.5), (-0.5, 1.5))
from astrometry.util.plotutils import PlotSequence
ps = PlotSequence('sdss')
if False:
r, d = np.mean(rng[0]), np.mean(rng[1])
RCF = radec_to_sdss_rcf(r, d, radius=2. * 60.,
tablefn='window_flist-DR9.fits')
print('Found', len(RCF), 'fields in range')
for run, c, f, ra, dec in RCF:
print(' ', run, c, f, 'at', ra, dec)
from astrometry.blind.plotstuff import PlotSequence
plot = Plotstuff(rdw=(r, d, 10), size=(1000, 1000), outformat='png')
plot.color = 'white'
plot.alpha = 0.5
plot.apply_settings()
T = fits_table('window_flist-DR9.fits')
I, J, d = match_radec(T.ra, T.dec, r, d, 10)
T.cut(I)
print('Plotting', len(T))
for i, (m0, m1, n0, n1, node, incl) in enumerate(zip(T.mu_start, T.mu_end, T.nu_start, T.nu_end, T.node, T.incl)):
#rr,dd = [],[]
for j, (m, n) in enumerate([(m0, n0), (m0, n1), (m1, n1), (m1, n0), (m0, n0)]):
ri, di = munu_to_radec_deg(m, n, node, incl)
# rr.append(ri)
# dd.append(di)
if j == 0:
plot.move_to_radec(ri, di)
else:
plot.line_to_radec(ri, di)
plot.stroke()
plot.plot_grid(2, 2, 5, 5)
plot.write('fields.png')
# CAS PhotoObjAll.resolveStatus bits
sprim = 0x100
sbad = 0x800
sedge = 0x1000
sbest = 0x200
if False:
T = fits_table('sdss-cas-testarea.fits')
plt.clf()
plothist(T.ra, T.dec, 200, range=rng)
plt.title('PhotoPrimary')
ps.savefig()
T = fits_table('sdss-cas-testarea-2.fits')
plt.clf()
plothist(T.ra, T.dec, 200, range=rng)
plt.title('PhotoObjAll: SURVEY_PRIMARY | SURVEY_BADFIELD | SURVEY_EDGE')
ps.savefig()
T = fits_table('sdss-cas-testarea-3.fits')
plt.clf()
plothist(T.ra, T.dec, 200, range=rng)
plt.title(
'PhotoObjAll: SURVEY_PRIMARY | SURVEY_BADFIELD | SURVEY_EDGE | SURVEY_BEST')
ps.savefig()
for j, (flags, txt) in enumerate([(sprim, 'PRIM'), (sbad, 'BAD'), (sedge, 'EDGE'),
(sbest, 'BEST')]):
I = np.flatnonzero(
(T.resolvestatus & (sprim | sbad | sedge | sbest)) == flags)
print(len(I), 'with', txt)
if len(I) == 0:
continue
plt.clf()
plothist(T.ra[I], T.dec[I], 200, range=rng)
plt.title('%i with %s' % (len(I), txt))
ps.savefig()
for j, (flags, txt) in enumerate([(sprim | sbad, 'PRIM + BAD'),
(sprim | sedge, 'PRIM + EDGE'),
(sprim | sbest, 'PRIM + BEST')]):
I = np.flatnonzero((T.resolvestatus & flags) > 0)
print(len(I), 'with', txt)
if len(I) == 0:
continue
plt.clf()
plothist(T.ra[I], T.dec[I], 200, range=rng)
plt.title('%i with %s' % (len(I), txt))
ps.savefig()
# for run in np.unique(T.run):
# I = (T.run == run)
# plt.clf()
# plothist(T.ra[I], T.dec[I], 200, range=rng)
# plt.title('Run %i' % run)
# ps.savefig()
R = 1. / 3600.
I, J, d = match_radec(T.ra, T.dec, T.ra, T.dec, R, notself=True)
print(len(I), 'matches')
plt.clf()
loghist((T.ra[I] - T.ra[J]) * 3600., (T.dec[I] - T.dec[J])
* 3600., 200, range=((-1, 1), (-1, 1)))
ps.savefig()
ps = PlotSequence('forced')
basedir = os.environ.get('BIGBOSS_DATA', '/project/projectdirs/bigboss')
wisedatadir = os.path.join(basedir, 'data', 'wise')
wisecat = fits_table(os.path.join(
wisedatadir, 'catalogs', 'wisecat2.fits'))
# plt.clf()
#plothist(wisecat.ra, wisecat.dec, 200, range=rng)
# plt.savefig('wisecat.png')
(ra0, ra1, dec0, dec1) = radecroi
ra = (ra0 + ra1) / 2.
dec = (dec0 + dec1) / 2.
#cas = fits_table('sdss-cas-testarea.fits')
#cas = fits_table('sdss-cas-testarea-2.fits')
cas = fits_table('sdss-cas-testarea-3.fits')
print('Read', len(cas), 'CAS sources')
cas.cut((cas.resolvestatus & sedge) == 0)
print('Cut to ', len(cas), 'without SURVEY_EDGE set')
# Check out WISE / SDSS matches.
wise = wisecat
sdss = cas
print(len(sdss), 'SDSS sources')
print(len(wise), 'WISE sources')
R = 10.
I, J, d = match_radec(wise.ra, wise.dec, sdss.ra, sdss.dec,
R / 3600., nearest=True)
print(len(I), 'matches')
print('max dist:', d.max())
plt.clf()
plt.hist(d * 3600., 100, range=(0, R), log=True)
plt.xlabel('Match distance (arcsec)')
plt.ylabel('Number of matches')
plt.title('SDSS-WISE astrometric matches')
ps.savefig()
plt.clf()
loghist((wise.ra[I] - sdss.ra[J]) * 3600., (wise.dec[I] - sdss.dec[J]) * 3600.,
200, range=((-R, R), (-R, R)))
plt.title('SDSS-WISE astrometric matches')
plt.xlabel('dRA (arcsec)')
plt.ylabel('dDec (arcsec)')
ps.savefig()
R = 4.
I, J, d = match_radec(wise.ra, wise.dec, sdss.ra, sdss.dec,
R / 3600., nearest=True)
print(len(I), 'matches')
unmatched = np.ones(len(wise), bool)
unmatched[I] = False
wun = wise[unmatched]
plt.clf()
plothist(sdss.ra, sdss.dec, 200, range=rng)
plt.title('SDSS source density')
ps.savefig()
plt.clf()
plothist(wise.ra, wise.dec, 200, range=rng)
plt.title('WISE source density')
ps.savefig()
plt.clf()
#plt.plot(wun.ra, wun.dec, 'r.')
#plt.axis(rng[0] + rng[1])
plothist(wun.ra, wun.dec, 200, range=rng)
plt.title('Unmatched WISE sources')
ps.savefig()
for band in 'ugriz':
sdss.set('psfmag_' + band,
NanoMaggies.nanomaggiesToMag(sdss.get('psfflux_' + band)))
# plt.clf()
# loghist(wise.w1mpro[I], sdss.psfmag_r[J], 200)
# plt.xlabel('WISE w1mpro')
# plt.ylabel('SDSS psfflux_r')
# ps.savefig()
for band in 'riz':
ax = [0, 10, 25, 5]
plt.clf()
mag = sdss.get('psfmag_' + band)[J]
loghist(mag - wise.w1mpro[I], mag, 200,
range=((ax[0], ax[1]), (ax[3], ax[2])))
plt.xlabel('SDSS %s - WISE w1' % band)
plt.ylabel('SDSS ' + band)
plt.axis(ax)
ps.savefig()
for w, t in [(wise[I], 'Matched'), (wun, 'Unmatched')]:
plt.clf()
w1 = w.get('w1mpro')
w2 = w.get('w2mpro')
ax = [-1, 3, 18, 6]
loghist(w1 - w2, w1, 200,
range=((ax[0], ax[1]), (ax[3], ax[2])))
plt.xlabel('W1 - W2')
plt.ylabel('W1')
plt.title('WISE CMD for %s sources' % t)
plt.axis(ax)
ps.savefig()
sdssobj = DR9()
band = 'r'
RCF = np.unique(zip(sdss.run, sdss.camcol, sdss.field))
wcses = []
fns = []
pfn = 'wcses.pickle'
if os.path.exists(pfn):
print('Reading', pfn)
wcses, fns = unpickle_from_file(pfn)
else:
for r, c, f in RCF:
fn = sdssobj.retrieve('frame', r, c, f, band)
print('got', fn)
fns.append(fn)
wcs = Tan(fn, 0)
print('got wcs', wcs)
wcses.append(wcs)
pickle_to_file((wcses, fns), pfn)
print('Wrote to', pfn)
wisefns = glob(os.path.join(wisedatadir, 'level3', '*w1-int-3.fits'))
wisewcs = []
for fn in wisefns:
print('Reading', fn)
wcs = anwcs(fn, 0)
print('Got', wcs)
wisewcs.append(wcs)
I = np.argsort(wun.w1mpro)
wun.cut(I)
for i in range(len(wun)):
ra, dec = wun.ra[i], wun.dec[i]
insdss = -1
for j, wcs in enumerate(wcses):
if wcs.is_inside(ra, dec):
insdss = j
break
inwise = -1
for j, wcs in enumerate(wisewcs):
if wcs.is_inside(ra, dec):
inwise = j
break
N = 0
if insdss != -1:
N += 1
if inwise != -1:
N += 1
if N == 0:
continue
if N != 2:
continue
plt.clf()
ss = 1
plt.subplot(2, N, ss)
ss += 1
M = 0.02
I = np.flatnonzero((sdss.ra > (ra - M)) * (sdss.ra < (ra + M)) *
(sdss.dec > (dec - M)) * (sdss.dec < (dec + M)))
sdssnear = sdss[I]
plt.plot(sdss.ra[I], sdss.dec[I], 'b.', alpha=0.7)
I = np.flatnonzero((wise.ra > (ra - M)) * (wise.ra < (ra + M)) *
(wise.dec > (dec - M)) * (wise.dec < (dec + M)))
wisenear = wise[I]
plt.plot(wise.ra[I], wise.dec[I], 'rx', alpha=0.7)
if insdss:
wcs = wcses[j]
w, h = wcs.imagew, wcs.imageh
rd = np.array([wcs.pixelxy2radec(x, y) for x, y in
[(1, 1), (w, 1), (w, h), (1, h), (1, 1)]])
plt.plot(rd[:, 0], rd[:, 1], 'b-', alpha=0.5)
if inwise:
wcs = wisewcs[j]
w, h = wcs.imagew, wcs.imageh
rd = np.array([wcs.pixelxy2radec(x, y) for x, y in
[(1, 1), (w, 1), (w, h), (1, h), (1, 1)]])
plt.plot(rd[:, 0], rd[:, 1], 'r-', alpha=0.5)
plt.plot([ra], [dec], 'o', mec='k',
mfc='none', mew=3, ms=20, alpha=0.5)
#plt.axis([ra+M, ra-M, dec-M, dec+M])
plt.axis([ra - M, ra + M, dec - M, dec + M])
plt.xticks([ra], ['RA = %0.3f' % ra])
plt.yticks([dec], ['Dec = %0.3f' % dec])
SW = 20
ss = N + 1
plt.subplot(2, N, ss)
if insdss != -1:
ss += 1
j = insdss
wcs = wcses[j]
xc, yc = wcs.radec2pixelxy(ra, dec)
r, c, f = RCF[j]
frame = sdssobj.readFrame(r, c, f, band)
#S = 50
S = SW * 3.472
im = frame.image
H, W = im.shape
y0, x0 = max(0, yc - S), max(0, xc - S)
y1, x1 = min(H, yc + S), min(W, xc + S)
subim = im[y0:y1, x0:x1]
# plt.imshow(subim, interpolation='nearest', origin='lower',
# vmax=0.3, extent=[x0,x1,y0,y1])
plt.imshow(subim.T, interpolation='nearest', origin='lower',
vmax=0.3, extent=[y0, y1, x0, x1])
# vmax=subim.max()*1.01)
ax = plt.axis()
sx, sy = wcs.radec2pixelxy(sdssnear.ra, sdssnear.dec)
#plt.plot(x, y, 'o', mec='b', mfc='none', ms=15)
plt.plot(sy, sx, 'o', mec='b', mfc='none', ms=15)
x, y = wcs.radec2pixelxy(wisenear.ra, wisenear.dec)
#plt.plot(x, y, 'rx', ms=10)
plt.plot(y, x, 'rx', ms=10)
# Which way up?
x, y = wcs.radec2pixelxy(np.array([ra, ra]), np.array(
[0.5, 2.0]) * S * 0.396 / 3600. + dec)
#plt.plot(x, y, 'b-', alpha=0.5, lw=2)
plt.plot(y, x, 'b-', alpha=0.5, lw=2)
plt.axis(ax)
plt.gray()
plt.title('SDSS %s (%i/%i/%i)' % (band, r, c, f))
# Try to guess the PRIMARY run from the nearest object.
for I in np.argsort((sx - xc)**2 + (sy - yc)**2):
r, c, f = sdssnear.run[I], sdssnear.camcol[I], sdssnear.field[I]
jj = None
for j, (ri, ci, fi) in enumerate(RCF):
if ri == r and ci == c and fi == f:
jj = j
break
assert(jj is not None)
wcs = wcses[jj]
xc, yc = wcs.radec2pixelxy(ra, dec)
frame = sdssobj.readFrame(r, c, f, band)
S = SW * 3.472
im = frame.image
H, W = im.shape
y0, x0 = max(0, yc - S), max(0, xc - S)
y1, x1 = min(H, yc + S), min(W, xc + S)
subim = im[y0:y1, x0:x1]
if np.prod(subim.shape) == 0:
continue
print('subim shape', subim.shape)
plt.subplot(2, N, 2)
plt.imshow(subim.T, interpolation='nearest', origin='lower',
vmax=0.3, extent=[y0, y1, x0, x1])
plt.gray()
plt.title('SDSS %s (%i/%i/%i)' % (band, r, c, f))
break
if inwise != -1:
plt.subplot(2, N, ss)
ss += 1
j = inwise
wcs = wisewcs[j]
ok, x, y = wcs.radec2pixelxy(ra, dec)
im = pyfits.open(wisefns[j])[0].data
S = SW
H, W = im.shape
y0, x0 = max(0, y - S), max(0, x - S)
subim = im[y0: min(H, y + S), x0: min(W, x + S)]
plt.imshow(subim, interpolation='nearest', origin='lower',
vmax=subim.max() * 1.01)
ax = plt.axis()
x, y = [], []
for r, d in zip(wisenear.ra, wisenear.dec):
ok, xi, yi = wcs.radec2pixelxy(r, d)
x.append(xi)
y.append(yi)
x = np.array(x)
y = np.array(y)
plt.plot(x - x0, y - y0, 'rx', ms=15)
x, y = [], []
for r, d in zip(sdssnear.ra, sdssnear.dec):
ok, xi, yi = wcs.radec2pixelxy(r, d)
x.append(xi)
y.append(yi)
x = np.array(x)
y = np.array(y)
plt.plot(x - x0, y - y0, 'o', mec='b', mfc='none', ms=10)
# Which way up?
pixscale = 1.375 / 3600.
ok, x1, y1 = wcs.radec2pixelxy(ra, dec + 0.5 * S * pixscale)
ok, x2, y2 = wcs.radec2pixelxy(ra, dec + 2.0 * S * pixscale)
plt.plot([x1 - x0, x2 - x0], [y1 - y0, y2 - y0],
'r-', alpha=0.5, lw=2)
plt.axis([ax[1], ax[0], ax[2], ax[3]])
# plt.axis(ax)
plt.gray()
plt.title('WISE W1 (coadd)')
plt.suptitle('WISE unmatched source: w1=%.1f, RA,Dec = (%.3f, %.3f)' %
(wun.w1mpro[i], ra, dec))
ps.savefig()
rcfs = zip(sdssnear.run, sdssnear.camcol, sdssnear.field)
print('Nearby SDSS sources are from:', np.unique(rcfs))
return
