def doplot(x, y, e1, e2, ccd, ewcs, scale=5.0,
plt=None, color='black'):
"""
Just plot the e1/e2 whiskers for the input objects
"""
if plt is None:
plt = biggles.FramedPlot()
ra = x.copy()
dec = x.copy()
ra[:] = -9999
dec[:] = -9999
for this_ccd in xrange(1,62+1):
# put the x,y from each ccd onto the camera location
# of our fiducial pointing, held in ewcs
ccd_wcs = ewcs[this_ccd]
wccd, = where(ccd == this_ccd)
if wccd.size > 0:
tra, tdec = ccd_wcs.image2sky(x[wccd],y[wccd])
tra -= 337.3
tdec += 15.0
ra[wccd] = numpy.float32( tra )
dec[wccd] = numpy.float32( tdec)
# ok, let's make a plot
# add whiskers for each e1/e2 to the plot
u,v = polar2whisker(e1,e2)
plt = bwhiskers(ra, dec, u, v, plt=plt, color=color, scale=scale)
one_percent = 0.01*scale
one_percent_x = numpy.array([0.9,0.9],dtype='f4')
one_percent_y = numpy.array([1.0,1.0],dtype='f4')
one_percent_x[0] -= one_percent*0.5
one_percent_x[1] += one_percent*0.5
one_percent_curve = biggles.Curve(one_percent_x,one_percent_y,color='blue',
linewidth=2)
plt.add(one_percent_curve)
one_percent_label = biggles.PlotLabel(0.935,0.885,"0.01")
plt.add(one_percent_label)
plt.xrange = -1.3,1.3
plt.yrange = -1.3,1.3
plt.xlabel = r'$\Delta$RA'
plt.ylabel = r'$\Delta$DEC'
return plt
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)
