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 mosaic():
'''
> cp ~/cosmo/staging/mosaicz/MZLS_CP/CP20180102/k4m_180103_040423_ooi_zd_v1.fits.fz /tmp
> funpack /tmp/k4m_180103_040423_ooi_zd_v1.fits.fz
> fitsgetext -i /tmp/k4m_180103_040423_ooi_zd_v1.fits -o mosaic-%02i.wcs -a -H
> cat mosaic-??.wcs > mosaic.wcs
> for ((i=1; i<=4; i++)); do modhead mosaic.wcs+$i NAXIS2; modhead mosaic.wcs+$i NAXIS2 0; done
NAXIS2 = 4079 / Axis length
NAXIS2 = 4079 / Axis length
NAXIS2 = 4079 / Axis length
NAXIS2 = 4061 / Axis length
'''
plt.figure(figsize=(4, 3))
plt.subplots_adjust(left=0.15, right=0.99, top=0.99, bottom=0.15)
T = fits_table('obstatus/mosaic-tiles_obstatus.fits')
print(len(T), 'tiles')
T.rename('pass', 'passnum')
T.cut(T.passnum <= 3)
print(len(T), 'tiles with passnum <= 3')
ra, dec = 180.216, 40.191
#ra,dec = 180., 40.
I, J, d = match_radec(T.ra, T.dec, ra, dec, 2.)
print(len(I), 'tiles near', ra, dec)
T.cut(I)
T.dist = d
print('dists:', d)
print('Passes:', T.passnum)
F = fitsio.FITS(os.path.join(os.path.dirname(__file__), 'mosaic.wcs'))
wcs = []
heights = [4079, 4079, 4079, 4061]
for i in range(1, len(F)):
hdr = F[i].read_header()
W = hdr['NAXIS1']
wcs.append(wcs_pv2sip_hdr(hdr, H=heights[i - 1], W=W))
print('WCS:', wcs[-1])
# Rendering canvas
W, H = 2200, 2200
pixsc = 4. / 3600.
targetwcs = Tan(ra, dec, W / 2. + 0.5, H / 2. + 0.5, -pixsc, 0., 0., pixsc,
float(W), float(H))
II = np.lexsort((T.dist, T.passnum))
print('First tile center:', T.ra[II[0]], T.dec[II[0]])
# This is for making the (vector) PDF format tiling images.
for maxit in [0, 8, 36, 37, 44, 73, 74, 82, 112]:
plot = Plotstuff(outformat='pdf',
ra=ra,
dec=dec,
width=W * pixsc,
size=(W, H),
outfn='tile-mosaic-%02i.pdf' % maxit)
plot.color = 'white'
plot.alpha = 1.
plot.plot('fill')
out = plot.outline
out.fill = True
out.stepsize = 1024.
plot.color = 'black'
plot.alpha = 0.4
plot.apply_settings()
for it, t in enumerate(T[II]):
print('Tile', it, 'pass', t.passnum)
for w in wcs:
w.set_crval((t.ra, t.dec))
out.wcs = anwcs_new_sip(w)
plot.plot('outline')
if it == maxit:
print('Writing', it)
plot.write()
break
# # And this is for PNG-format tiling images and histograms.
cov = np.zeros((H, W), np.uint8)
for it, t in enumerate(T[II]):
print('Tile', it, 'pass', t.passnum)
for w in wcs:
w.set_crval((t.ra, t.dec))
try:
Yo, Xo, Yi, Xi, nil = resample_with_wcs(targetwcs, w)
except:
continue
cov[Yo, Xo] += 1
if it in [0, 8, 36, 37, 44, 73, 74, 82, 112]:
mx = {1: 2, 2: 4, 3: 6}[t.passnum]
# plt.clf()
# plt.imshow(cov, interpolation='nearest', origin='lower', vmin=0, vmax=mx)
# plt.colorbar()
# plt.savefig('tile-%02i.png' % it)
plt.imsave('tile-mosaic-%02i.png' % it,
cov,
origin='lower',
vmin=0,
vmax=mx,
cmap=antigray)
if it in [36, 73, 112]:
from collections import Counter
print('Coverage counts:', Counter(cov.ravel()).most_common())
bins = -0.5 + np.arange(8)
plt.clf()
n, b, p = plt.hist(cov.ravel(), bins=bins, normed=True)
#plt.hist(cov.ravel(), bins=bins, normed=True, cumulative=True, histtype='step')
# Cumulative histogram from the right...
xx, yy = [], []
for blo, bhi, ni in reversed(list(zip(bins, bins[1:], n))):
nc = float(np.sum(cov.ravel() > blo)) / len(cov.ravel())
yy.extend([nc, nc])
xx.extend([bhi, blo])
if ni > 0:
if nc != ni:
if nc > ni + 0.03:
# If there's room, label the histogram bin above, else below
plt.text((blo + bhi) / 2.,
ni,
'%.1f \%%' % (100. * ni),
ha='center',
va='bottom',
color='k')
else:
plt.text((blo + bhi) / 2.,
ni - 0.01,
'%.1f \%%' % (100. * ni),
ha='center',
va='top',
color='k')
plt.text((blo + bhi) / 2.,
nc,
'%.1f \%%' % (100. * nc),
ha='center',
va='bottom',
color='k')
plt.plot(xx, yy, 'k-')
plt.xlim(bins.min(), bins.max())
plt.ylim(0., 1.1)
plt.xlabel('Number of exposures')
plt.ylabel('Fraction of sky')
plt.savefig('hist-mosaic-%02i.pdf' % it)
def decam():
'''
cp ~/cosmo/staging/decam/DECam_CP/CP20170731/c4d_170801_080516_oki_g_v1.fits.fz /tmp
funpack /tmp/c4d_170801_080516_oki_g_v1.fits.fz
fitsgetext -i /tmp/c4d_170801_080516_oki_g_v1.fits -o decam-%02i.wcs -a -H
cat decam-??.wcs > decam.wcs
for ((i=1; i<=61; i++)); do modhead decam.wcs+$i NAXIS2 0; done
'''
plt.figure(figsize=(4, 3))
plt.subplots_adjust(left=0.15, right=0.99, top=0.99, bottom=0.15)
T = fits_table('obstatus/decam-tiles_obstatus.fits')
T.rename('pass', 'passnum')
ra, dec = 0.933, 0.
I, J, d = match_radec(T.ra, T.dec, ra, dec, 5.) #2.8)
print(len(I), 'tiles near 0,0')
T.cut(I)
T.dist = d
print('dists:', d)
print('Passes:', T.passnum)
F = fitsio.FITS(os.path.join(os.path.dirname(__file__), 'decam.wcs'))
wcs = []
for i in range(1, len(F)):
hdr = F[i].read_header()
wcs.append(wcs_pv2sip_hdr(hdr, W=2046, H=4094))
W, H = 5000, 5000
pixsc = 4. / 3600.
targetwcs = Tan(ra, dec, W / 2. + 0.5, H / 2. + 0.5, -pixsc, 0., 0., pixsc,
float(W), float(H))
II = np.lexsort((T.dist, T.passnum))
# This is for making the (vector) PDF format tiling images.
for maxit in [0, 6, 30, 31, 37, 61, 62, 68, 90]:
#mx = { 1: 2, 2: 4, 3: 6 }[t.passnum]
plot = Plotstuff(outformat='pdf',
ra=ra,
dec=dec,
width=W * pixsc,
size=(W, H),
outfn='tile-%02i.pdf' % maxit)
plot.color = 'white'
plot.alpha = 1.
plot.plot('fill')
out = plot.outline
out.fill = True
out.stepsize = 1024.
plot.color = 'black'
plot.alpha = 0.4
plot.apply_settings()
for it, t in enumerate(T[II]):
print('Tile', it, 'pass', t.passnum)
for w in wcs:
w.set_crval((t.ra, t.dec))
out.wcs = anwcs_new_sip(w)
plot.plot('outline')
if it == maxit:
print('Writing', it)
plot.write()
break
# And this is for PNG-format tiling images and histograms.
cov = np.zeros((H, W), np.uint8)
for it, t in enumerate(T[II]):
print('Tile', it, 'pass', t.passnum)
for w in wcs:
w.set_crval((t.ra, t.dec))
#print('WCS:', w)
try:
Yo, Xo, Yi, Xi, nil = resample_with_wcs(targetwcs, w)
except:
#import traceback
#traceback.print_exc()
continue
cov[Yo, Xo] += 1
if it in [0, 6, 30, 31, 37, 61, 62, 68, 90]:
mx = {1: 2, 2: 4, 3: 6}[t.passnum]
# plt.clf()
# plt.imshow(cov, interpolation='nearest', origin='lower', vmin=0, vmax=mx)
# plt.colorbar()
# plt.savefig('tile-%02i.png' % it)
plt.imsave('tile-%02i.png' % it,
cov,
origin='lower',
vmin=0,
vmax=mx,
cmap=antigray)
#plt.imsave('tile-%02i.pdf' % it, cov, origin='lower', vmin=0, vmax=mx, cmap=antigray, format='pdf')
if it in [30, 61, 90]:
from collections import Counter
print('Coverage counts:', Counter(cov.ravel()).most_common())
bins = -0.5 + np.arange(8)
plt.clf()
n, b, p = plt.hist(cov.ravel(), bins=bins, normed=True)
#plt.hist(cov.ravel(), bins=bins, normed=True, cumulative=True, histtype='step')
# Cumulative histogram from the right...
xx, yy = [], []
for blo, bhi, ni in reversed(zip(bins, bins[1:], n)):
nc = float(np.sum(cov.ravel() > blo)) / len(cov.ravel())
yy.extend([nc, nc])
xx.extend([bhi, blo])
if ni > 0:
if nc != ni:
if nc > ni + 0.03:
# If there's room, label the histogram bin above, else below
plt.text((blo + bhi) / 2.,
ni,
'%.1f \%%' % (100. * ni),
ha='center',
va='bottom',
color='k')
else:
plt.text((blo + bhi) / 2.,
ni - 0.01,
'%.1f \%%' % (100. * ni),
ha='center',
va='top',
color='k')
plt.text((blo + bhi) / 2.,
nc,
'%.1f \%%' % (100. * nc),
ha='center',
va='bottom',
color='k')
plt.plot(xx, yy, 'k-')
plt.xlim(bins.min(), bins.max())
plt.ylim(0., 1.1)
plt.xlabel('Number of exposures')
plt.ylabel('Fraction of sky')
#plt.title('DECaLS tiling, %i pass%s' % (t.passnum, t.passnum > 1 and 'es' or ''))
#plt.savefig('hist-%02i.png' % it)
plt.savefig('hist-%02i.pdf' % it)