def slit_trace_qa(slf, frame, ltrace, rtrace, extslit, desc="", root='trace', outfil=None, normalize=True):
"""
Generate a QA plot for the traces
Parameters
----------
slf : class
An instance of the Science Exposure Class
frame : ndarray
trace image
ltrace : ndarray
Left slit edge traces
rtrace : ndarray
Right slit edge traces
extslit : ndarray
Mask of extrapolated slits (True = extrapolated)
desc : str, optional
A description to be used as a title for the page
root : str, optional
Root name for generating output file, e.g. msflat_01blue_000.fits
outfil : str, optional
Output file
normalize: bool, optional
Normalize the flat? If not, use zscale for output
"""
# Outfil
# if outfil is None:
# if '.fits' in root: # Expecting name of msflat FITS file
# outfil = root.replace('.fits', '_trc.pdf')
# outfil = outfil.replace('MasterFrames', 'Plots')
# else:
# outfil = root+'.pdf'
ntrc = ltrace.shape[1]
ycen = np.arange(frame.shape[0])
# Normalize flux in the traces
if normalize:
nrm_frame = np.zeros_like(frame)
for ii in xrange(ntrc):
xtrc = (ltrace[:,ii] + rtrace[:,ii])/2.
ixtrc = np.round(xtrc).astype(int)
# Simple 'extraction'
dumi = np.zeros( (frame.shape[0],3) )
for jj in xrange(3):
dumi[:,jj] = frame[ycen,ixtrc-1+jj]
trc = np.median(dumi, axis=1)
# Find portion of the image and normalize
for yy in ycen:
xi = max(0, int(ltrace[yy,ii])-3)
xe = min(frame.shape[1], int(rtrace[yy,ii])+3)
# Fill + normalize
nrm_frame[yy, xi:xe] = frame[yy, xi:xe] / trc[yy]
sclmin, sclmax = 0.4, 1.1
else:
nrm_frame = frame.copy()
sclmin, sclmax = zscale(nrm_frame)
# Plot
plt.clf()
fig = plt.figure(dpi=1200)
#fig.set_size_inches(10.0,6.5)
ax = plt.gca()
set_fonts(ax)
for label in ax.get_yticklabels() :
label.set_fontproperties(ticks_font)
for label in ax.get_xticklabels() :
label.set_fontproperties(ticks_font)
cmm = cm.Greys_r
mplt = plt.imshow(nrm_frame, origin='lower', cmap=cmm, interpolation=None,
extent=(0., frame.shape[1], 0., frame.shape[0]))
mplt.set_clim(vmin=sclmin, vmax=sclmax)
# Axes
plt.xlim(0., frame.shape[1])
plt.ylim(0., frame.shape[0])
plt.tick_params(axis='both', which='both', bottom='off', top='off', left='off', right='off',
labelbottom='off', labelleft='off')
# Traces
for ii in xrange(ntrc):
if extslit[ii] is True: ptyp = ':'
else: ptyp = '--'
# Left
plt.plot(ltrace[:,ii]+0.5, ycen, 'r'+ptyp, alpha=0.7)
# Right
plt.plot(rtrace[:,ii]+0.5, ycen, 'g'+ptyp, alpha=0.7)
# Label
iy = int(frame.shape[0]/2.)
plt.text(ltrace[iy,ii], ycen[iy], '{:d}'.format(ii+1), color='red', ha='center')
plt.text(rtrace[iy,ii], ycen[iy], '{:d}'.format(ii+1), color='green', ha='center')
if desc != "":
plt.suptitle(desc)
slf._qa.savefig(dpi=1200, orientation='portrait', bbox_inches='tight')
#pp.savefig()
#pp.close()
plt.close()
def obj_trace_qa(slf, frame, ltrace, rtrace, root='trace', outfil=None, normalize=True):
""" Generate a QA plot for the object trace
Parameters
----------
frame : ndarray
image
ltrace : ndarray
Left edge traces
rtrace : ndarray
Right edge traces
root : str, optional
Root name for generating output file, e.g. msflat_01blue_000.fits
outfil : str, optional
Output file
normalize : bool, optional
Normalize the flat? If not, use zscale for output
"""
# Outfil
if outfil is None:
if 'fits' in root: # Expecting name of msflat FITS file
outfil = root.replace('.fits', '_trc.pdf')
outfil = outfil.replace('MasterFrames', 'Plots')
else:
outfil = root+'.pdf'
ntrc = ltrace.shape[1]
ycen = np.arange(frame.shape[0])
# Normalize flux in the traces
if normalize:
nrm_frame = np.zeros_like(frame)
for ii in xrange(ntrc):
xtrc = (ltrace[:,ii] + rtrace[:,ii])/2.
ixtrc = np.round(xtrc).astype(int)
# Simple 'extraction'
dumi = np.zeros( (frame.shape[0],3) )
for jj in xrange(3):
dumi[:,jj] = frame[ycen,ixtrc-1+jj]
trc = np.median(dumi, axis=1)
# Find portion of the image and normalize
for yy in ycen:
xi = max(0, int(ltrace[yy,ii])-3)
xe = min(frame.shape[1],int(rtrace[yy,ii])+3)
# Fill + normalize
nrm_frame[yy, xi:xe] = frame[yy,xi:xe] / trc[yy]
sclmin, sclmax = 0.4, 1.1
else:
nrm_frame = frame.copy()
sclmin, sclmax = zscale(nrm_frame)
# Plot
plt.clf()
fig = plt.figure(dpi=1200)
plt.rcParams['font.family']= 'times new roman'
ticks_font = matplotlib.font_manager.FontProperties(family='times new roman',
style='normal', size=16, weight='normal', stretch='normal')
ax = plt.gca()
for label in ax.get_yticklabels() :
label.set_fontproperties(ticks_font)
for label in ax.get_xticklabels() :
label.set_fontproperties(ticks_font)
cmm = cm.Greys_r
mplt = plt.imshow(nrm_frame,origin='lower', cmap=cmm, extent=(0., frame.shape[1], 0., frame.shape[0]))
mplt.set_clim(vmin=sclmin, vmax=sclmax)
# Axes
plt.xlim(0., frame.shape[1])
plt.ylim(0., frame.shape[0])
plt.tick_params(axis='both', which='both', bottom='off', top='off', left='off', right='off', labelbottom='off', labelleft='off')
# Traces
for ii in xrange(ntrc):
# Left
plt.plot(ltrace[:,ii]+0.5, ycen, 'r--',alpha=0.7)
# Right
plt.plot(rtrace[:,ii]+0.5, ycen, 'g--',alpha=0.7)
# Label
iy = int(frame.shape[0]/2.)
plt.text(ltrace[iy,ii], ycen[iy], '{:d}'.format(ii+1), color='red', ha='center')
plt.text(rtrace[iy,ii], ycen[iy], '{:d}'.format(ii+1), color='green', ha='center')
slf._qa.savefig(bbox_inches='tight')
plt.close()
