def plot_spec_templ(self, twa, tfl):
""" Initiate plots of the spectrum and a template, scaled to
matched the spectrum.
"""
sp = self.spec
ax2 = self.ax[2]
ax2.axhline(0, color='0.7')
if self.smoothed:
self.art_spec2, = ax2.plot(sp.wa, convolve_psf(sp.fl,5), 'k',lw=0.5,ls='steps-mid')
else:
self.art_spec2, = ax2.plot(sp.wa, sp.fl, 'k', lw=0.5, ls='steps-mid')
ax2.plot(sp.wa, sp.er, 'k', lw=0.25)
good = sp.er > 0
if (~good).any():
ax2.plot(sp.wa[~good], sp.er[~good], 'k.', ms=4)
mult = scale_by_median(twa, tfl, sp.wa, sp.fl, mask=MASKATMOS)
if mult is None:
self.art_templ2, = ax2.plot([], [], color='r', alpha=0.7)
else:
self.art_templ2, = ax2.plot(twa, mult*tfl, color='r', alpha=0.7)
ymax = np.abs(np.percentile(sp.fl[good & (sp.wa>5700)], 98))
offset = 0.15 * ymax
temp = max(np.median(sp.fl), np.median(sp.er))
sky = 0.15 * temp / np.median(sp.sky)*sp.sky - offset
axvfill(MASKATMOS, ax=ax2, color='y', alpha=0.3)
ax2.fill_between(sp.wa, sky, y2=-offset, color='g', lw=0, alpha=0.3, zorder=1)
#pdb.set_trace()
if self.msky is not None:
s = self.msky
msky = s * np.median(sky + offset) / np.median(s)
ax2.plot(sp.wa, msky - offset, color='g', lw=1.5, zorder=1)
ax2.set_ylim(-ymax*0.15, 1.5*ymax)
def plot_spec_templ(self, twa, tfl):
""" Initiate plots of the spectrum and a template, scaled to
matched the spectrum.
"""
sp = self.spec
ax2 = self.ax[2]
ax2.axhline(0, color='0.7')
if self.smoothed:
self.art_spec2, = ax2.plot(sp.wa,
convolve_psf(sp.fl, 5),
'k',
lw=0.5,
ls='steps-mid')
else:
self.art_spec2, = ax2.plot(sp.wa,
sp.fl,
'k',
lw=0.5,
ls='steps-mid')
ax2.plot(sp.wa, sp.er, 'k', lw=0.25)
good = sp.er > 0
if (~good).any():
ax2.plot(sp.wa[~good], sp.er[~good], 'k.', ms=4)
mult = scale_by_median(twa, tfl, sp.wa, sp.fl, mask=MASKATMOS)
if mult is None:
self.art_templ2, = ax2.plot([], [], color='r', alpha=0.7)
else:
self.art_templ2, = ax2.plot(twa, mult * tfl, color='r', alpha=0.7)
ymax = np.abs(np.percentile(sp.fl[good & (sp.wa > 5700)], 98))
offset = 0.15 * ymax
temp = max(np.median(sp.fl), np.median(sp.er))
sky = 0.15 * temp / np.median(sp.sky) * sp.sky - offset
axvfill(MASKATMOS, ax=ax2, color='y', alpha=0.3)
ax2.fill_between(sp.wa,
sky,
y2=-offset,
color='g',
lw=0,
alpha=0.3,
zorder=1)
#pdb.set_trace()
if self.msky is not None:
s = self.msky
msky = s * np.median(sky + offset) / np.median(s)
ax2.plot(sp.wa, msky - offset, color='g', lw=1.5, zorder=1)
ax2.set_ylim(-ymax * 0.15, 1.5 * ymax)
def prepare_templates(templates, convolve_pix=None, plot=0):
""" Add continua to templates and interpolate to log-linear wav
scale. Returns a new set of templates.
"""
tnew = []
for t in templates:
# fudge to remove bad template areas
print t.label
wgood = t.wa[t.fl > 1e-99]
w0, w1 = wgood[0], wgood[-1]
cond = between(t.wa, w0, w1)
wa0, fl0 = t.wa[cond], t.fl[cond]
if plot:
ax = pl.gca()
ax.cla()
pl.plot(wa0, fl0, 'b')
# rebin to a log-linear wavelength scale. To shift wavescale
# to redshift z, add log10(1+z) to wa or twa.
dw = (np.log10(wa0[-1]) - np.log10(wa0[0])) / (len(wa0) - 1)
logtwa = np.log10(wa0[0]) + dw * np.arange(len(wa0))
twa = 10**logtwa
tfl = np.interp(twa, wa0, fl0)
if t.label.startswith('sdss') and convolve_pix is not None:
# convolve to VIMOS resolution
tfl = convolve_psf(tfl, convolve_pix)
fwhm1 = len(wa0) // 7
fwhm2 = len(wa0) // 9
#print fwhm1, fwhm2
tco = find_cont(tfl, fwhm1=fwhm1, fwhm2=fwhm2)
if plot:
pl.plot(twa, tfl, 'r')
pl.plot(twa, tco, 'r--')
pl.show()
raw_input()
t1 = adict(logwa=logtwa, fl=tfl, co=tco, label=t.label)
tnew.append(t1)
return tnew
def prepare_templates(templates, convolve_pix=None, plot=0):
""" Add continua to templates and interpolate to log-linear wav
scale. Returns a new set of templates.
"""
tnew = []
for t in templates:
# fudge to remove bad template areas
print t.label
wgood = t.wa[t.fl > 1e-99]
w0,w1 = wgood[0], wgood[-1]
cond = between(t.wa, w0, w1)
wa0, fl0 = t.wa[cond], t.fl[cond]
if plot:
ax = pl.gca()
ax.cla()
pl.plot(wa0, fl0, 'b')
# rebin to a log-linear wavelength scale. To shift wavescale
# to redshift z, add log10(1+z) to wa or twa.
dw = (np.log10(wa0[-1]) - np.log10(wa0[0])) / (len(wa0) - 1)
logtwa = np.log10(wa0[0]) + dw * np.arange(len(wa0))
twa = 10**logtwa
tfl = np.interp(twa, wa0, fl0)
if t.label.startswith('sdss') and convolve_pix is not None:
# convolve to VIMOS resolution
tfl = convolve_psf(tfl, convolve_pix)
fwhm1 = len(wa0) // 7
fwhm2 = len(wa0) // 9
#print fwhm1, fwhm2
tco = find_cont(tfl, fwhm1=fwhm1, fwhm2=fwhm2)
if plot:
pl.plot(twa, tfl, 'r')
pl.plot(twa, tco, 'r--')
pl.show()
raw_input()
t1 = adict(logwa=logtwa, fl=tfl, co=tco, label=t.label)
tnew.append(t1)
return tnew
def on_keypress(self, event):
if event.key == '?':
print self.help
elif event.key == 'y':
print 'Redshift = %.3f' % self.z
self.zgood = self.z
self.zconf = 'a'
self.disconnect()
elif event.key == 'm':
print 'Maybe redshift = %.3f' % self.z
self.zgood = self.z
self.zconf = 'b'
self.disconnect()
elif event.key == 'n':
print 'Rejecting, z set to -1'
self.zgood = -1.
self.zconf = 'c'
self.disconnect()
elif event.key == 'f': # NT code
print 'Rejecting fake object, z set to -1'
self.zgood = -1.
self.zconf = 'f'
self.disconnect()
elif event.key == 'k':
print 'Skipping, not writing anything'
self.zconf = 'k'
self.disconnect()
elif event.key == 's':
if self.smoothed:
self.art_spec2.set_data(self.spec.wa, self.spec.fl)
self.smoothed = False
else:
fl = convolve_psf(self.spec.fl, 5)
self.art_spec2.set_data(self.spec.wa, fl)
self.smoothed = True
self.fig.canvas.draw()
elif event.inaxes == self.ax[1]:
if event.key == ' ':
self.z = event.xdata
self.update()
self.fig.canvas.draw()
elif event.key == 'x':
self.z = event.xdata
self.update(fitpeak=False)
self.fig.canvas.draw()
elif event.inaxes == self.ax[0]:
if event.key == ' ':
i = int(np.round(event.xdata))
self.i = min(max(i, 0), len(self.zatmax) - 1)
self.z = self.zatmax[self.i]
self.update()
self.fig.canvas.draw()
elif event.inaxes == self.ax[2]:
try:
j = self.keys.index(event.key)
except ValueError:
return
line = self.lines_sel[j]
zp1 = event.xdata / line['wa']
#print 'z=%.3f, %s %f' % (zp1 - 1, line['name'], line['wa'])
self.z = zp1 - 1
self.update(fitpeak=False)
self.fig.canvas.draw()
def on_keypress(self, event):
if event.key == '?':
print self.help
elif event.key == 'y':
print 'Redshift = %.3f' % self.z
self.zgood = self.z
self.zconf = 'a'
self.disconnect()
elif event.key == 'm':
print 'Maybe redshift = %.3f' % self.z
self.zgood = self.z
self.zconf = 'b'
self.disconnect()
elif event.key == 'n':
print 'Rejecting, z set to -1'
self.zgood = -1.
self.zconf = 'c'
self.disconnect()
elif event.key == 'f': # NT code
print 'Rejecting fake object, z set to -1'
self.zgood = -1.
self.zconf = 'f'
self.disconnect()
elif event.key == 'k':
print 'Skipping, not writing anything'
self.zconf = 'k'
self.disconnect()
elif event.key == 's':
if self.smoothed:
self.art_spec2.set_data(self.spec.wa, self.spec.fl)
self.smoothed = False
else:
fl = convolve_psf(self.spec.fl, 5)
self.art_spec2.set_data(self.spec.wa, fl)
self.smoothed = True
self.fig.canvas.draw()
elif event.inaxes == self.ax[1]:
if event.key == ' ':
self.z = event.xdata
self.update()
self.fig.canvas.draw()
elif event.key == 'x':
self.z = event.xdata
self.update(fitpeak=False)
self.fig.canvas.draw()
elif event.inaxes == self.ax[0]:
if event.key == ' ':
i = int(np.round(event.xdata))
self.i = min(max(i, 0), len(self.zatmax)-1)
self.z = self.zatmax[self.i]
self.update()
self.fig.canvas.draw()
elif event.inaxes == self.ax[2]:
try:
j = self.keys.index(event.key)
except ValueError:
return
line = self.lines_sel[j]
zp1 = event.xdata / line['wa']
#print 'z=%.3f, %s %f' % (zp1 - 1, line['name'], line['wa'])
self.z = zp1 - 1
self.update(fitpeak=False)
self.fig.canvas.draw()
