def update(self):
i = self.i
self.artists['mlines'] = []
a = self.ax
s = self.spec[i]
wa, fl, er, co = s.wa, s.fl, s.er, s.co
if self.models[i] is not None and (co > 0).any():
temp = co * self.models[i]
a.plot(wa, temp, color='orange')
a.set_title(self.filenames[i])
if self.zp1 is not None:
self.update_lines()
if self.ticks is not None:
if not np.isnan(co).all() and not self.opt.co_is_sky:
f = np.interp(self.ticks.wa, wa, co)
else:
f = np.interp(self.ticks.wa, wa, fl)
height = 0.08 * np.percentile(fl, 90)
for j, t in enumerate(self.ticks):
if self.opt.showticks:
T, Tlabels = plot_tick_wa(a, t.wa, f[j], height, t,
tickz=self.opt.tickz)
self.artists['ticks'].extend(T)
self.artists['ticklabels'].extend(Tlabels)
if self.opt.f26 is not None and self.opt.f26.regions is not None:
plotregions(a, self.opt.f26.regions.wmin,
self.opt.f26.regions.wmax)
if self.opt.features is not None:
f = self.opt.features
sortfl = np.sort(fl[er > 0])
ref = sortfl[int(len(sortfl)*0.95)] - sortfl[int(len(sortfl)*0.05)]
wedge = np.concatenate([f.wa0, f.wa1])
axvlines(wedge, ax=a, colors='k', alpha=0.7)
temp = co[np.array([indexnear(wa, wav) for wav in f.wac])]
ymin = temp + ref * 0.1
ymax = ymin + ref * 0.2
a.vlines(f.wac, ymin, ymax, colors='g')
for j, f in enumerate(f):
a.text(f['wac'], ymax[j] + ref * 0.05, f['num'], ha='center',
fontsize=12, color='g')
fl = self.tfl * np.median(s.fl) / np.median(self.tfl)
self.artists['template'].set_data(self.twa, fl)
if not self.opt.ticklabels:
for t in self.artists['ticklabels']:
t.set_visible(False)
barak.spec.plotatmos(a)
self.fig.canvas.draw()
def initvelplot(wa,
nfl,
ner,
nco,
transitions,
z,
fig,
atom,
ncol,
vmin=-1000.,
vmax=1000.,
nmodels=0,
osc=False,
residuals=False):
""" Vertical stacked plots of expected positions of absorption
lines at the given redshift on a velocity scale."""
colours = ('b', 'r', 'g', 'orangered', 'c', 'purple')
ions = [tr['name'].split()[0] for tr in transitions]
# want an ordered set
ionset = []
for ion in ions:
if ion not in ionset:
ionset.append(ion)
colour = dict(zip(ionset, colours * (len(ions) // len(colours) + 1)))
zp1 = z + 1
betamin = vmin / c_kms
betamax = vmax / c_kms
fig.subplots_adjust(wspace=0.0001,
left=0.03,
right=0.97,
top=0.95,
bottom=0.07)
axes = []
for i in range(ncol):
axes.append(pl.subplot(1, ncol, i + 1))
axes = axes[::-1]
for ax in axes:
ax.set_autoscale_on(0)
# plot top down, so we need reversed()
offsets = []
artists = dict(fl=[],
er=[],
co=[],
resid=[],
text=[],
model=[],
models={},
ew=None,
regions=[],
ticklabels=[],
ticks=[],
aod=[])
num_per_panel = int(ceil(1 / float(ncol) * len(transitions)))
for i, trans in enumerate(reversed(transitions)):
tr_id = trans['name'], tuple(trans['tr'])
iax, ioff = divmod(i, num_per_panel)
ax = axes[iax]
ion = trans['name'].split()[0]
offset = ioff * 1.5
#print i, offset
offsets.append(offset)
watrans = trans['wa']
obswa = watrans * zp1
wmin = obswa * (1 + 3 * betamin)
wmax = obswa * (1 + 3 * betamax)
cond = between(wa, wmin, wmax)
#good = ~np.isnan(fl) & (er > 0) & ~np.isnan(co)
fl = nfl[cond]
#er = ner[cond]
co = nco[cond]
vel = (wa[cond] / obswa - 1) * c_kms
#import pdb; pdb.set_trace()
ax.axhline(offset, color='gray', lw=0.5)
#artists['er'].extend(
# ax.plot(vel, er + offset, lw=1, color='orange', alpha=0.5) )
artists['fl'].extend(
ax.plot(vel,
fl + offset,
color=colour[ion],
lw=0.5,
ls='steps-mid'))
artists['co'].extend(
ax.plot(vel, co + offset, color='gray', lw=0.5, ls='dashed'))
artists['model'].extend(ax.plot(vel, co + offset, 'k', lw=1,
zorder=12))
artists['models'][tr_id] = {}
if residuals:
artists['resid'].extend(
ax.plot([], [], '.', ms=3, mew=0, color='forestgreen'))
#ax.axhline(offset-0.1, color='k', lw=0.3)
ax.axhline(offset - 0.05, color='k', lw=0.3)
ax.axhline(offset - 0.15, color='k', lw=0.3)
bbox = dict(facecolor='k', edgecolor='None')
transf = mtransforms.blended_transform_factory(ax.transAxes,
ax.transData)
name = trans['name']
#import pdb; pdb.set_trace()
if name.startswith('HI'):
ind = indexnear(HIwavs, trans['wa'])
lynum = len(HIwavs) - ind
name = 'Ly' + str(lynum) + ' ' + name[2:]
# find Ly transition number
if 'tr' in trans and osc:
name = name + ' %.3g' % trans['tr']['osc']
artists['text'].append(
ax.text(
0.03,
offset + 0.5,
name,
fontsize=15, #bbox=bbox,
transform=transf,
zorder=20))
for ax in axes:
ax.axvline(0, color='k', lw=0.5, zorder=20)
ax.set_xlim(vmin, vmax)
ax.set_ylim(-0.5, num_per_panel * 1.5)
ax.set_yticks([])
ax.set_xlabel(r'$\Delta v\ \mathrm{(km/s)}$', fontsize=16)
artists['title'] = pl.suptitle('$z = %.5f$' % z, fontsize=18)
artists['sky'] = []
return artists, np.array(offsets[:num_per_panel]), num_per_panel, axes
def on_keypress(self, event):
""" Process a keypress event.
"""
if event.key == 'S':
pl.savefig('junk.png', dpi=300)
elif event.key == '?':
print help
elif event.key == 'T':
if self.opt.ticklabels:
for t in self.artists['ticklabels']:
t.set_visible(False)
self.opt.ticklabels = False
else:
self.opt.ticklabels = True
for t in self.artists['ticklabels']:
t.set_visible(True)
self.fig.canvas.draw()
elif event.key == 'R':
self.refresh_f26()
self.update_model()
if self.opt.f26 is not None:
self.convolve_LSF()
self.apply_zero_offsets()
self.apply_cont_adjustments()
self.update(self.z)
elif event.key == 'i':
for ax in self.axes:
v0, v1 = ax.get_xlim()
ax.set_xlim(0.66 * v0, 0.66 * v1)
self.fig.canvas.draw()
elif event.key == 'o':
for ax in self.axes:
v0, v1 = ax.get_xlim()
ax.set_xlim(1.33 * v0, 1.33 * v1)
self.fig.canvas.draw()
elif event.key == 'y':
self.ymult *= 1.33
self.update(self.z)
elif event.key == 'Y':
self.ymult = 1
self.update(self.z)
elif event.key == ' ' and event.inaxes is not None:
z = self.z
# get new redshift
dz = (event.xdata / c_kms) * (1 + z)
# and new axis limits, if any
vmin, vmax = event.inaxes.get_xlim()
self.vmin = min(0, vmin)
self.vmax = max(0, vmax)
self.update(z + dz)
if event.key == 'z':
c = raw_input('Enter redshift: ')
self.update(float(c))
if event.key in 'blepH':
i = self.offsets.searchsorted(event.ydata)
if i == 0:
i = len(self.opt.linelist)
off = self.offsets[i - 1]
iax = self.axes.index(event.inaxes)
i += iax * self.num_per_panel
#if event.inaxes == self.axes[1]:
# i += self.num_per_panel
tr = self.opt.linelist[-i]
z = (1 + event.xdata / c_kms) * (1 + self.z) - 1
wa = tr['wa'] * (1 + z)
ind = indexnear(self.wa, wa)
#print 'transition', tr['name'], tr['wa'], wa
if event.key == 'b':
# print fitting region
if self.prev_keypress == 'b' and self.prev_wa is not None:
wmin = self.prev_wa
wmax = wa
if wmin > wmax:
wmin, wmax = wmax, wmin
vsig = 6.38
if isinstance(self.opt.Rfwhm, float):
vsig = self.opt.Rfwhm / 2.35
print '%%%% %s 1 %.3f %.3f vsig=%.3f' % (self.filename, wmin,
wmax, vsig)
self.prev_keypress = None
self.prev_wa = None
else:
self.prev_wa = wa
elif event.key == 'p':
s = ''
if self.opt.f26 is not None:
i = indexnear(self.allticks.wa, wa)
tick = self.allticks[i]
s = '\nclosest tick: %-s %.1f z=%.5f' % (
tick['name'], tick['wa0'], tick['z'])
print '%12s dv=%.1f wa=%.3f zlya=%.4f, zlyb=%.4f, zlyg=%.4f' % (
tr['name'], event.xdata, wa, wa / wlya - 1, wa / wlyb - 1,
wa / wlyg - 1) + s
elif event.key == 'l':
# guess a line N, z and b and print to screen need to know
# which transition we want, and what the central index is.
ner = self.ner[ind - 1:ind + 1]
nfl = self.nfl[ind - 1:ind + 1]
c0 = (ner > 0) & ~np.isnan(nfl)
if not c0.sum():
print 'No good pixels!'
return
f = np.median(nfl[c0])
e = np.median(ner[c0])
if f < e:
f = e
elif f > 1 - e:
f = 1 - e
tau0 = -np.log(f)
logN, b = guess_logN_b(tr['name'].split()[0], tr['wa'],
tr['tr'][1], tau0)
print '%-6s %8.6f 0.0 %4.1f 0.0 %4.1f 0.0' % (
tr['name'].split()[0], z, b, logN)
elif event.key == 'H':
# same as 'l' but always HI
ner = self.ner[ind - 1:ind + 1]
nfl = self.nfl[ind - 1:ind + 1]
c0 = (ner > 0) & ~np.isnan(nfl)
if not c0.sum():
print 'No good pixels!'
return
f = np.median(nfl[c0])
e = np.median(ner[c0])
if f < e:
f = e
elif f > 1 - e:
f = 1 - e
tau0 = -np.log(f)
logN, b = guess_logN_b('HI', 1215.6701, 0.416400, tau0)
redshift = wa / 1215.6701 - 1.
print '%-6s %8.6f 0.0 %4.1f 0.0 %4.1f 0.0' % ('HI', redshift, b,
logN)
elif event.key == 'e':
wa = self.wa
if self.indprev is not None:
i0, i1 = self.indprev, ind
if i0 > i1:
i0, i1 = i1, i0
f = calc_Wr(i0, i1, wa, tr['tr'], self.ew, self.ewer)
print '%s z=%.6f Wr=%.3f+/-%.3fA ngoodpix=%3i wa=%.3f %.3f v=%.1f-%.1f' % (
tr['name'], self.z, f.Wr, f.Wre, f.ngoodpix, wa[i0],
wa[i1], self.xprev, event.xdata)
print ' Opt. thin approx: logN=%.4f (%.3f-%.3f) 1sig detect lim %.4f' % (
f.logN[1], f.logN[0], f.logN[2], f.Ndetlim)
# Assume continuum error of 0.5 sigma, zero point error
# of 0.5 sigma.
logNlo, logN, logNhi, saturated = calc_N_AOD(
self.wa[i0:i1],
self.nfl[i0:i1],
self.ner[i0:i1],
tr['tr']['wa'],
tr['tr']['osc'],
colo_nsig=0.05,
cohi=0.05,
#colo_nsig=0.5, cohi_nsig=0.5,
#zerolo_nsig=0.5, zerohi_nsig=0.5,
zerolo_nsig=1,
zerohi_nsig=1,
)
s = ' AOD: logN=%.4f %.3f %.3f' % (logN, logN - logNlo,
logNhi - logN)
if saturated:
s += ' Saturated'
print s
self.artists['ew'].remove()
self.artists['ew'] = event.inaxes.fill_between(
(wa[i0:i1 + 1] / tr['wa'] / (1 + self.z) - 1) * c_kms,
self.ymult * (self.nfl[i0:i1 + 1] - 1) + 1 + off,
y2=off + 1,
color='r',
alpha=0.5)
pl.draw()
self.indprev = None
self.xprev = None
return
else:
if self.artists['ew'] is not None:
self.artists['ew'].remove()
vpos = [(wa[ind] / tr['wa'] / (1 + self.z) - 1) * c_kms] * 2
#print tr, [off, off+1], vpos
self.artists['ew'], = event.inaxes.plot(vpos, [off, off + 1],
'k',
alpha=0.3)
pl.draw()
self.indprev = ind
self.xprev = event.xdata
elif event.key == 'P':
# save redshift, logN, and plot.
f = self.filename.rsplit('.', 1)
f = f[0] + '_z%.4f.' % self.z + f[1]
print "printing to", f
pl.savefig(f)
elif event.key == 's':
c = raw_input('New FWHM in pixels of Gaussian to convolve with? '
'(blank for no smoothing) ')
if c == '':
# restore spectrum
self.smoothby = 1
else:
try:
fwhm = float(c)
except TypeError:
print 'FWHM must be a float'
if fwhm < 1:
self.smoothby = 1
else:
self.smoothby = fwhm
self.update(self.z)
self.prev_keypress = event.key
if 1:
##################################################################
# plot the predicted column densities as a function of NHI, and
# compare to observed values for the maximum likelihood model
##################################################################
# for solar abundances, plotting vs logU/lognH
# OVI, CaI, AlI, FeI are very low (logN = 9-10)
# SiIV, CIV consistent with upper limits.
imax = where(prob == prob.max())
nHbest = nH[imax[1][0]]
iZ = indexnear(M.Z, Z[imax[2][0]])
inH = indexnear(M.nH, nH[imax[1][0]])
#iNHI = indexnear(M.NHI, 19.5)
iNHI = indexnear(M.NHI, NHI[imax[0][0]])
pl.rc('font', size=14)
pl.rc('legend', fontsize=10.5)
if 0:
trans1 = ('FeII MgI MgII OI OVI NI NII').split()
fig = pl.figure(figsize=(4.3, 6))
fig.subplots_adjust(right=0.97, top=0.92,bottom=0.09)
ax = pl.subplot(111)
plot_trans_vs_U(iZ, iNHI, M, trans1, ax)
def on_keypress(self, event):
""" Process a keypress event.
"""
if event.key == 'S':
pl.savefig('junk.png', dpi=300)
elif event.key == 'f5':
if self.opt.ticklabels:
for t in self.artists['ticklabels']:
t.set_visible(False)
self.opt.ticklabels = False
else:
self.opt.ticklabels = True
for t in self.artists['ticklabels']:
t.set_visible(True)
self.fig.canvas.draw()
elif event.key == 'R':
self.refresh_f26()
self.update_model()
if self.opt.f26 is not None:
self.convolve_LSF()
self.apply_zero_offsets()
self.apply_cont_adjustments()
self.update(self.z)
elif event.key == ' ' and event.inaxes is not None:
z = self.z
# get new redshift
dz = (event.xdata / c_kms) * (1 + z)
# and new axis limits, if any
vmin, vmax = event.inaxes.get_xlim()
self.vmin = min(0, vmin)
self.vmax = max(0, vmax)
self.update(z + dz)
if event.key == 'z':
c = raw_input('Enter redshift: ')
self.update(float(c))
if event.key in 'blepH':
i = self.offsets.searchsorted(event.ydata)
if i == 0:
i = len(self.opt.linelist)
off = self.offsets[i - 1]
if event.inaxes == self.axes[1]:
i += self.num_per_panel
tr = self.opt.linelist[-i]
z = (1 + event.xdata / c_kms) * (1 + self.z) - 1
wa = tr['wa'] * (1 + z)
ind = indexnear(self.wa, wa)
#print 'transition', tr['name'], tr['wa'], wa
if event.key == 'b':
# print fitting region
if self.prev_keypress == 'b' and self.prev_wa is not None:
wmin = self.prev_wa
wmax = wa
if wmin > wmax:
wmin, wmax = wmax, wmin
vsig = 6.38
if isinstance(self.opt.Rfwhm, float):
vsig = self.opt.Rfwhm / 2.35
print '%%%% %s 1 %.3f %.3f vsig=%.3f' % (
self.filename, wmin, wmax, vsig)
self.prev_keypress = None
self.prev_wa = None
else:
self.prev_wa = wa
elif event.key == 'p':
s = ''
if self.opt.f26 is not None:
i = indexnear(self.allticks.wa, wa)
tick = self.allticks[i]
s = '\nclosest tick: %-s %.1f z=%.5f' % (
tick['name'], tick['wa0'], tick['z'])
print '%12s dv=%.1f wa=%.3f zlya=%.4f, zlyb=%.4f, zlyg=%.4f' % (
tr['name'], event.xdata, wa, wa/wlya-1, wa/wlyb-1, wa/wlyg-1) + s
elif event.key == 'l':
# guess a line N, z and b and print to screen need to know
# which transition we want, and what the central index is.
ner = self.ner[ind - 1:ind + 1]
nfl = self.nfl[ind - 1:ind + 1]
c0 = (ner > 0) & ~np.isnan(nfl)
if not c0.sum():
print 'No good pixels!'
return
f = np.median(nfl[c0])
e = np.median(ner[c0])
if f < e:
f = e
elif f > 1 - e:
f = 1 - e
tau0 = -np.log(f)
logN, b = guess_logN_b(tr['name'].split()[0], tr['wa'], tr['tr'][1], tau0)
print '%-6s %8.6f 0.0 %4.1f 0.0 %4.1f 0.0' % (
tr['name'].split()[0], z, b, logN)
elif event.key == 'H':
# same as 'l' but always HI
ner = self.ner[ind - 1:ind + 1]
nfl = self.nfl[ind - 1:ind + 1]
c0 = (ner > 0) & ~np.isnan(nfl)
if not c0.sum():
print 'No good pixels!'
return
f = np.median(nfl[c0])
e = np.median(ner[c0])
if f < e:
f = e
elif f > 1 - e:
f = 1 - e
tau0 = -np.log(f)
logN, b = guess_logN_b('HI', 1215.6701, 0.416400, tau0)
redshift = wa / 1215.6701 - 1.
print '%-6s %8.6f 0.0 %4.1f 0.0 %4.1f 0.0' % ('HI', redshift, b, logN)
elif event.key == 'e':
wa = self.wa
if self.indprev is not None:
i0, i1 = self.indprev, ind
if i0 > i1:
i0, i1 = i1, i0
f = calc_Wr(i0, i1, wa, tr['tr'], self.ew, self.ewer)
print '%s z=%.6f Wr=%.3f+/-%.3fA ngoodpix=%3i wa=%.3f-%.3f ' % (
tr['name'], f.zp1-1, f.Wr, f.Wre, f.ngoodpix, wa[i0], wa[i1])
print ' Optically thin approx: logN=%.4f (%.3f-%.3f) 5sig detect lim %.4f' % (
f.logN[1], f.logN[0], f.logN[2], f.Ndetlim)
# Assume continuum error of 2 sigma, zero point error
# of two sigma. Currently this is done per pixel,
# would be better to do it per region. No problem as
# long as error doesn't vary much over the region.
logNlo, logN, logNhi, saturated = calc_N_AOD(
self.wa[i0:i1], self.nfl[i0:i1], self.ner[i0:i1],
2, 2, 1, 1, tr['tr']['wa'], tr['tr']['osc'])
print ' AOD: logN=%.4f (%.3f-%.3f) Saturated? %s' % (
logN, logNlo, logNhi, saturated)
self.artists['ew'].remove()
self.artists['ew'] = event.inaxes.fill_between(
(wa[i0:i1 + 1] / tr['wa'] / (1 + self.z) - 1) * c_kms,
self.nfl[i0:i1 + 1] + off, y2=off + 1,
color='r', alpha=0.5)
pl.draw()
self.indprev = None
return
else:
if self.artists['ew'] is not None:
self.artists['ew'].remove()
vpos = [(wa[ind] / tr['wa'] / (1 + self.z) - 1) * c_kms] * 2
#print tr, [off, off+1], vpos
self.artists['ew'], = event.inaxes.plot(
vpos, [off, off + 1], 'k', alpha=0.3)
pl.draw()
self.indprev = ind
elif event.key == 'P':
# save redshift, logN, and plot.
f = self.filename.rsplit('.', 1)
f = f[0] + '_z%.4f.' % self.z + f[1]
print "printing to", f
pl.savefig(f)
elif event.key == 's':
c = raw_input('New FWHM in pixels of Gaussian to convolve with? '
'(blank for no smoothing) ')
if c == '':
# restore spectrum
self.smoothby = 1
else:
try:
fwhm = float(c)
except TypeError:
print 'FWHM must be a float'
if fwhm < 1:
self.smoothby = 1
else:
self.smoothby = fwhm
self.update(self.z)
self.prev_keypress = event.key
def on_keypress_custom(self, event):
if event.key == 'right':
if self.i == self.n - 1:
print 'At the last spectrum.'
return
self.artists['zlines'] = []
self.get_new_spec(self.i + 1)
self.update()
elif event.key == 'left':
if self.i == 0:
print 'At the first spectrum.'
return
self.artists['zlines'] = []
self.get_new_spec(self.i - 1)
self.update()
elif event.key == '?':
print help
elif event.key == 'T':
if self.opt.ticklabels:
for t in self.artists['ticklabels']:
t.set_visible(False)
self.opt.ticklabels = False
else:
self.opt.ticklabels = True
x0, x1 = self.ax.get_xlim()
for t in self.artists['ticklabels']:
if x0 < t.get_position()[0] < x1:
t.set_visible(True)
self.fig.canvas.draw()
elif event.key == ' ' and event.inaxes is not None:
print '%.4f %.4f %i' % (
event.xdata, event.ydata,
indexnear(self.spec[self.i].wa, event.xdata))
elif event.key == 'm' and event.inaxes is not None:
if self.wlim1 is not None:
self.artists['mlines'].append(plt.gca().axvline(
event.xdata, color='k', alpha=0.3))
plt.draw()
w0, w1 = self.wlim1, event.xdata
if w0 > w1:
w0, w1 = w1, w0
sp = self.spec[self.i]
good = between(sp.wa, w0, w1) & (sp.er > 0) & ~np.isnan(sp.fl)
fmt1 = 'Median flux {:.3g}, rms {:.2g}, er {:.2g}. {:.2g} A/pix'
fmt2 = ('SNR {:.2g}/pix, {:.2g}/A (RMS), {:.2g}/pix, {:.2g}/A '
'(er)')
if good.sum() < 2:
print 'Too few good pixels in range'
self.wlim1 = None
return
medfl = np.median(sp.fl[good])
stdfl = sp.fl[good].std()
meder = np.median(sp.er[good])
pixwidth = np.mean(sp.wa[good][1:] - sp.wa[good][:-1])
mult = sqrt(1. / pixwidth)
snr1 = medfl / stdfl
snr2 = medfl / meder
print fmt1.format(medfl, stdfl, meder, pixwidth)
print fmt2.format(snr1, snr1 * mult, snr2, snr2 * mult)
self.wlim1 = None
else:
for l in self.artists['mlines']:
try:
l.remove()
except ValueError:
# plot has been removed
pass
self.artists['mlines'].append(plt.gca().axvline(
event.xdata, color='k', alpha=0.3))
plt.draw()
self.wlim1 = event.xdata
print "press 'm' again..."
elif event.key == 'C':
# fit dodgy continuum
sp = self.spec[self.i]
co = barak.spec.find_cont(sp.fl)
temp, = plt.gca().plot(sp.wa, co, 'm')
plt.draw()
c = raw_input('Accept continuum? (y) ')
if (c + ' ').lower()[0] != 'n':
print 'Accepted'
sp.co = co
self.update()
else:
temp.remove()
elif event.key == 'B' and event.inaxes is not None:
# print fitting region
wa = event.xdata
if self.prev_wa != None:
wmin = self.prev_wa
wmax = wa
if wmin > wmax:
wmin, wmax = wmax, wmin
print '%%%% %s 1 %.3f %.3f vsig=x.x' % (self.filenames[self.i], wmin, wmax)
self.prev_wa = None
else:
self.prev_wa = wa
elif event.key == 'h' and event.inaxes is not None:
# print HI line
wa = event.xdata
z = wa / 1215.6701 - 1
print '%-6s %8.6f 0.0 %3.0f 0.0 %4.1f 0.0' % ('HI', z, 20, 14.0)
elif event.key == 'E':
# overplot a template
c = '0'
while c not in '1234':
c = raw_input("""\
1: LBG
2: QSO
3: LRG
4: Starburst galaxy
""")
temp = get_SEDs('LBG', 'lbg_em.dat')
temp.redshift_to(self.zp1 - 1)
self.twa = temp.wa
self.tfl = temp.fl
self.update()
def initvelplot(wa, nfl, ner, nco, transitions, z, fig, atom, ncol,
vmin=-1000., vmax=1000., nmodels=0,
osc=False, residuals=False):
""" Vertical stacked plots of expected positions of absorption
lines at the given redshift on a velocity scale."""
colours = ('b', 'r', 'g', 'orangered', 'c', 'purple')
ions = [tr['name'].split()[0] for tr in transitions]
# want an ordered set
ionset = []
for ion in ions:
if ion not in ionset:
ionset.append(ion)
colour = dict(zip(ionset, colours * (len(ions) // len(colours) + 1)))
zp1 = z + 1
betamin = vmin / c_kms
betamax = vmax / c_kms
fig.subplots_adjust(wspace=0.0001, left=0.03, right=0.97, top=0.95,
bottom=0.07)
axes = []
for i in range(ncol):
axes.append(pl.subplot(1, ncol, i+1))
axes = axes[::-1]
for ax in axes:
ax.set_autoscale_on(0)
# plot top down, so we need reversed()
offsets = []
artists = dict(fl=[], er=[], co=[], resid=[], text=[], model=[], models={},
ew=None, regions=[], ticklabels=[], ticks=[], aod=[])
num_per_panel = int(ceil(1/float(ncol) * len(transitions)))
for i, trans in enumerate(reversed(transitions)):
tr_id = trans['name'], tuple(trans['tr'])
iax, ioff = divmod(i, num_per_panel)
ax = axes[iax]
ion = trans['name'].split()[0]
offset = ioff * 1.5
#print i, offset
offsets.append(offset)
watrans = trans['wa']
obswa = watrans * zp1
wmin = obswa * (1 + 3 * betamin)
wmax = obswa * (1 + 3 * betamax)
cond = between(wa, wmin, wmax)
#good = ~np.isnan(fl) & (er > 0) & ~np.isnan(co)
fl = nfl[cond]
#er = ner[cond]
co = nco[cond]
vel = (wa[cond] / obswa - 1) * c_kms
#import pdb; pdb.set_trace()
ax.axhline(offset, color='gray', lw=0.5)
#artists['er'].extend(
# ax.plot(vel, er + offset, lw=1, color='orange', alpha=0.5) )
artists['fl'].extend(
ax.plot(vel, fl + offset, color=colour[ion], lw=0.5,
ls='steps-mid'))
artists['co'].extend(
ax.plot(vel, co + offset, color='gray', lw=0.5, ls='dashed'))
artists['model'].extend(
ax.plot(vel, co + offset, 'k', lw=1, zorder=12))
artists['models'][tr_id] = {}
if residuals:
artists['resid'].extend(
ax.plot([], [], '.', ms=3, mew=0, color='forestgreen'))
#ax.axhline(offset-0.1, color='k', lw=0.3)
ax.axhline(offset - 0.05, color='k', lw=0.3)
ax.axhline(offset - 0.15, color='k', lw=0.3)
bbox = dict(facecolor='k', edgecolor='None')
transf = mtransforms.blended_transform_factory(
ax.transAxes, ax.transData)
name = trans['name']
#import pdb; pdb.set_trace()
if name.startswith('HI'):
ind = indexnear(HIwavs, trans['wa'])
lynum = len(HIwavs) - ind
name = 'Ly' + str(lynum) + ' ' + name[2:]
# find Ly transition number
if 'tr' in trans and osc:
name = name + ' %.3g' % trans['tr']['osc']
artists['text'].append(
ax.text(0.03, offset + 0.5, name, fontsize=15, #bbox=bbox,
transform=transf, zorder=20))
for ax in axes:
ax.axvline(0, color='k', lw=0.5, zorder=20)
ax.set_xlim(vmin, vmax)
ax.set_ylim(-0.5, num_per_panel * 1.5)
ax.set_yticks([])
ax.set_xlabel(r'$\Delta v\ \mathrm{(km/s)}$', fontsize=16)
artists['title'] = pl.suptitle('$z = %.5f$' % z, fontsize=18)
artists['sky'] = []
return artists, np.array(offsets[:num_per_panel]), num_per_panel, axes
def on_keypress_custom(self, event):
if event.key == 'pagedown':
if self.i == self.n - 1:
print('At the last spectrum.')
return
self.artists['zlines'] = []
self.get_new_spec(self.i + 1)
self.update()
elif event.key == 'pageup':
if self.i == 0:
print('At the first spectrum.')
return
self.artists['zlines'] = []
self.get_new_spec(self.i - 1)
self.update()
elif event.key == '?':
print(help)
elif event.key == 'T':
if self.opt.ticklabels:
for t in self.artists['ticklabels']:
t.set_visible(False)
self.opt.ticklabels = False
else:
self.opt.ticklabels = True
x0, x1 = self.ax.get_xlim()
for t in self.artists['ticklabels']:
if x0 < t.get_position()[0] < x1:
t.set_visible(True)
self.fig.canvas.draw()
elif event.key == ' ' and event.inaxes is not None:
print('%.4f %.4f %i' % (
event.xdata, event.ydata,
indexnear(self.spec[self.i].wa, event.xdata)))
elif event.key == 'm' and event.inaxes is not None:
if self.wlim1 is not None:
self.artists['mlines'].append(plt.gca().axvline(
event.xdata, color='k', alpha=0.3))
plt.draw()
w0, w1 = self.wlim1, event.xdata
if w0 > w1:
w0, w1 = w1, w0
sp = self.spec[self.i]
good = between(sp.wa, w0, w1) & (sp.er > 0) & ~np.isnan(sp.fl)
fmt1 = 'Median flux {:.3g}, rms {:.2g}, er {:.2g}. {:.2g} A/pix'
fmt2 = ('SNR {:.3g}/pix, {:.3g}/A (RMS), {:.3g}/pix, {:.3g}/A '
'(er)')
if good.sum() < 2:
print('Too few good pixels in range')
self.wlim1 = None
return
medfl = np.median(sp.fl[good])
stdfl = sp.fl[good].std()
meder = np.median(sp.er[good])
pixwidth = np.mean(sp.wa[good][1:] - sp.wa[good][:-1])
mult = sqrt(1. / pixwidth)
snr1 = medfl / stdfl
snr2 = medfl / meder
print(fmt1.format(medfl, stdfl, meder, pixwidth))
print(fmt2.format(snr1, snr1 * mult, snr2, snr2 * mult))
self.wlim1 = None
else:
for l in self.artists['mlines']:
try:
l.remove()
except ValueError:
# plot has been removed
pass
self.artists['mlines'].append(plt.gca().axvline(
event.xdata, color='k', alpha=0.3))
plt.draw()
self.wlim1 = event.xdata
print("press 'm' again...")
elif event.key == 'C':
# fit dodgy continuum
sp = self.spec[self.i]
co = barak.spec.find_cont(sp.fl)
temp, = plt.gca().plot(sp.wa, co, 'm')
plt.draw()
c = raw_input('Accept continuum? (y) ')
if (c + ' ').lower()[0] != 'n':
print('Accepted')
sp.co = co
self.update()
else:
temp.remove()
elif event.key == 'B' and event.inaxes is not None:
# print fitting region
wa = event.xdata
if self.prev_wa != None:
wmin = self.prev_wa
wmax = wa
if wmin > wmax:
wmin, wmax = wmax, wmin
print('%%%% %s 1 %.3f %.3f vsig=x.x' % (
self.filenames[self.i], wmin, wmax))
self.prev_wa = None
else:
self.prev_wa = wa
elif event.key == 'h' and event.inaxes is not None:
# print HI line
wa = event.xdata
z = wa / 1215.6701 - 1
print('%-6s %8.6f 0.0 %3.0f 0.0 %4.1f 0.0' % ('HI', z, 20, 14.0))
elif event.key == 'E':
# overplot a template
c = '0'
while c not in '1234':
c = raw_input("""\
1: LBG
2: QSO
3: LRG
4: Starburst galaxy
""")
temp = get_SEDs('LBG', 'lbg_em.dat')
temp.redshift_to(self.zp1 - 1)
self.twa = temp.wa
self.tfl = temp.fl
self.update()
elif event.key == ')':
self.ax.set_xlabel('$\mathrm{Wavelength\ (\AA)}$')
self.ax.set_ylabel('$F_\lambda\ \mathrm{(arbitrary)}$')
self.update()
def update(self):
i = self.i
self.artists['mlines'] = []
a = self.ax
s = self.spec[i]
wa, fl, er, co = s.wa, s.fl, s.er, s.co
if self.models[i] is not None and (co > 0).any():
if 'norm' in self.opt and self.opt.norm:
temp = self.models[i]
else:
temp = co * self.models[i]
a.plot(wa, temp, color='k')
#a.set_title(self.filenames[i])
if self.zp1 is not None:
self.update_lines()
if self.ticks is not None:
if not np.isnan(co).all() and not self.opt.co_is_sky:
if 'norm' in self.opt and self.opt.norm:
f = np.ones_like(self.ticks.wa)
else:
f = np.interp(self.ticks.wa, wa, co)
else:
if 'norm' in self.opt and self.opt.norm:
f = np.interp(self.ticks.wa, wa, fl/co)
else:
f = np.interp(self.ticks.wa, wa, fl)
if 'norm' in self.opt and self.opt.norm:
height = 0.08
else:
height = 0.08 * np.percentile(fl, 90)
for j, t in enumerate(self.ticks):
if self.opt.showticks:
T, Tlabels = plot_tick_wa(a, t.wa, f[j], height, t,
tickz=self.opt.tickz)
self.artists['ticks'].extend(T)
self.artists['ticklabels'].extend(Tlabels)
if self.opt.f26 is not None and self.opt.f26.regions is not None and \
self.opt.show_regions:
f = fl
if 'norm' in self.opt and self.opt.norm:
f = self.fl / self.co
plotregions(a, self.opt.f26.regions.wmin,
self.opt.f26.regions.wmax, wa, f)
if self.opt.features is not None:
f = self.opt.features
sortfl = np.sort(fl[er > 0])
ref = sortfl[int(len(sortfl)*0.95)] - sortfl[int(len(sortfl)*0.05)]
wedge = np.concatenate([f.wa0, f.wa1])
axvlines(wedge, ax=a, colors='k', alpha=0.7)
temp = co[np.array([indexnear(wa, wav) for wav in f.wac])]
ymin = temp + ref * 0.1
ymax = ymin + ref * 0.2
a.vlines(f.wac, ymin, ymax, colors='g')
for j, f in enumerate(f):
a.text(f['wac'], ymax[j] + ref * 0.05, f['num'], ha='center',
fontsize=12, color='g')
if self.tfl is not None:
fl = self.tfl * np.median(s.fl[er > 0]) / np.median(self.tfl)
self.artists['template'].set_data(self.twa, fl)
if not self.opt.ticklabels:
for t in self.artists['ticklabels']:
t.set_visible(False)
barak.spec.plotatmos(a)
self.fig.canvas.draw()
