def combine_scinv(self):
from glob import glob
outfile=self.combined_file()
stdout.write("Will write to file: %s\n" % outfile)
dir=self.output_dir()
pattern = self.scinv_file_pattern()
pattern=path_join(dir, pattern)
flist = glob(pattern)
datalist = []
idmin = 0
for f in flist:
print f
tdata = esutil.io.read(f)
data = numpy_util.add_fields(tdata, [('zid','i4')])
data['zid'] = idmin + numpy.arange(data.size)
idmin += data.size
print data['zid'].min(), data['zid'].max()
datalist.append(data)
hdr = esutil.sfile.read_header(flist[0])
print 'combining data'
data = numpy_util.combine_arrlist(datalist)
print 'writing file: %s' % outfile
esutil.sfile.write(data, outfile, header=hdr)
def match(self, tilename):
"""
match and write the output file
"""
from esutil import numpy_util as nu
scat_data = read_orig_scat(self.scat_name, tilename)
print("matching")
mdg, msc = nu.match(scat_data["coadd_objects_id"], self.ids)
print(" matched: %d/%d" % (mdg.size, scat_data.size))
if mdg.size == 0:
print(" skipping")
return
scat_data = scat_data[mdg]
add_dt = [("scinv_flags", "i4"), ("scinv", "f8", self.nz)]
newdata = nu.add_fields(scat_data, add_dt)
newdata["scinv"] = self.data["scinv"][msc, :]
newdata["scinv_flags"] = self.data["flags"][msc]
self._write_data(newdata, tilename)
def doplot(serun, exposurename, example_wcs_byccd, nx=3,ny=3,diff=False,
imageformat='png', ptypes=['unbinned','comparebinned']):
stdout.write("serun: %s\n" % serun)
stdout.write("exposurename: %s\n" % exposurename)
stdout.write("\tReading checkpsf data\n")
alldata = []
allstats = []
for ccd in range(1,62+1):
try:
data = deswl.files.wlse_read(exposurename,ccd,'checkpsf',
serun=serun)
fields=['e1','e2','e1interp','e2interp']
stats = du.stats_xy(data, fields, nx=nx, ny=ny, typ='median')
ccd_wcs = example_wcs_byccd[ccd]
fx,fy = ccd_wcs.image2sky(data['x'], data['y'])
mfx,mfy = ccd_wcs.image2sky(stats['mx'],stats['my'])
newdata = numpy_util.add_fields(data, [('fx','f4'),('fy','f4')])
newdata['fx'] = fx - 337.3
newdata['fy'] = fy + 15.0
fadd=[('mfx','f4'),('mfy','f4'),('me1diff','f4'),('me2diff','f4')]
newstats = numpy_util.add_fields(stats,fadd)
newstats['mfx'] = mfx - 337.3
newstats['mfy'] = mfy + 15.0
newstats['me1diff'] = newstats['me1interp']-newstats['me1']
newstats['me2diff'] = newstats['me2interp']-newstats['me2']
alldata.append(newdata)
allstats.append(newstats)
except:
stdout.write("Failed ccd=%s\n" % ccd)
print sys.exc_info()
data = numpy_util.combine_arrlist(alldata)
stats = numpy_util.combine_arrlist(allstats)
stdout.write("\tPlotting whiskers\n")
plt = du.setuplot('Agg')
plt.clf()
nplots = len(ptypes)
xsize=8*nplots
fig=plt.figure(figsize=(xsize,7))
iplot = 1
u, v = polar2whisker(data['e1'], data['e2'])
uinterp, vinterp = polar2whisker(data['e1interp'], data['e2interp'])
mu, mv = polar2whisker(stats['me1'],stats['me2'])
muinterp, mvinterp = polar2whisker(stats['me1interp'],stats['me2interp'])
mudiff, mvdiff = polar2whisker(stats['me1diff'],stats['me2diff'])
# example size to plot
psize=0.01
if 'unbinned' in ptypes or 'compareunbinned' in ptypes:
stdout.write("\t\tDoing plot type 'unbinned'\n")
ax = fig.add_subplot(1,nplots,iplot)
iplot += 1
# plot individual stars
scale=3.
whiskers(ax, data['fx'], data['fy'], u, v, scale=scale,
linewidth=0.25)
# a measure of scale
xtext=-1.2
ax.text(xtext, 0.9, str(psize), verticalalignment='center')
whiskers(ax, xtext+0.18, 0.9, psize, 0.0, color='blue', scale=scale)
if 'compareunbinned' in ptypes:
stdout.write("\t\tOverplotting 'compareunbinned'\n")
whiskers(ax, data['fx'], data['fy'], uinterp, vinterp,
scale=scale, color='red', linewidth=0.25)
# add a legend
ypos = 1.1
ystep = 0.07
xtext = -1.1
ax.text(xtext, ypos-ystep, "data", verticalalignment='center')
whiskers(ax, xtext+0.23, ypos-ystep, psize, 0.0,
color='black', scale=scale)
ax.text(xtext, ypos-2*ystep, "interp", verticalalignment='center')
whiskers(ax, xtext+0.23, ypos-2*ystep, psize, 0.0,
color='red', scale=scale)
ax.set_xlim(-1.3,1.3)
ax.set_ylim(-1.3,1.3)
set_minor_ticks(ax)
if 'comparebinned' in ptypes:
# comparison plot for the binned data
ax = fig.add_subplot(1,nplots,iplot)
iplot += 1
scale=10.
whiskers(ax, stats['mfx'], stats['mfy'], mu, mv, scale=scale)
whiskers(ax, stats['mfx'], stats['mfy'], muinterp, mvinterp,
scale=scale, color='red')
# legend
ypos = 1.1
ystep = 0.07
xtext = -1.1
ax.text(xtext, ypos, str(psize), verticalalignment='center')
whiskers(ax, xtext+0.23, ypos, psize, 0.0, color='blue', scale=scale)
ax.text(xtext, ypos-ystep, "data", verticalalignment='center')
whiskers(ax, xtext+0.23, ypos-ystep, psize, 0.0,
color='black', scale=scale)
ax.text(xtext, ypos-2*ystep, "interp", verticalalignment='center')
whiskers(ax, xtext+0.23, ypos-2*ystep, psize, 0.0,
color='red', scale=scale)
ax.set_xlim(-1.3,1.3)
ax.set_ylim(-1.3,1.3)
set_minor_ticks(ax)
if 'diffbinned' in ptypes:
# comparison plot for the binned data
ax = fig.add_subplot(1,nplots,iplot)
iplot += 1
scale=50.
psize=0.001
whiskers(ax, stats['mfx'], stats['mfy'], mudiff, mvdiff, scale=scale)
ax.text(xtext, ypos, str(psize), verticalalignment='center')
whiskers(ax, xtext+0.23, ypos, psize, 0.0, color='blue', scale=scale)
ax.set_xlim(-1.3,1.3)
ax.set_ylim(-1.3,1.3)
set_minor_ticks(ax)
outdir='/home/users/esheldon/www/tmp/plots'
outdir=os.path.join(outdir, serun)
if not os.path.exists(outdir):
os.makedirs(outdir)
ptypes_string = '-'.join(ptypes)
outfile = "%s-checkpsf-%s.%s" % (exposurename,ptypes_string, imageformat)
outfile=os.path.join(outdir,outfile)
stdout.write("\tWriting plot file: %s\n" % outfile)
plt.savefig(outfile, bbox_inches='tight', pad_inches=0.1)
