def on_keypress_smooth(self, event):
""" Smooth the flux with a gaussian. Requires attributes
self.fl and self.nsmooth, self.artists['fl'] and self.fig."""
if event.key == 'S':
if self.nsmooth > 0:
self.nsmooth += 0.5
else:
self.nsmooth = 1
sfl = convolve_psf(self.fl, self.nsmooth)
self.artists['fl'].set_ydata(sfl)
self.fig.canvas.draw()
elif event.key == 'U':
self.nsmooth = 0
self.artists['fl'].set_ydata(self.fl)
self.fig.canvas.draw()
def on_keypress_smooth(self, event):
""" Smooth the flux with a gaussian. Requires attributes
self.fl and self.nsmooth, self.artists['fl'] and self.fig."""
if event.key == 'S':
if self.nsmooth > 0:
self.nsmooth += 0.5
else:
self.nsmooth = 1
sfl = convolve_psf(self.fl, self.nsmooth)
self.artists['fl'].set_ydata(sfl)
self.fig.canvas.draw()
elif event.key == 'U':
self.nsmooth = 0
self.artists['fl'].set_ydata(self.fl)
self.fig.canvas.draw()
def get_new_spec(self, i):
""" Change to a new spectrum
"""
self.i = i
filename = self.filenames[i]
if self.spec[i] is None:
print 'Reading %s' % filename
self.spec[i] = barak.spec.read(filename)
self.models[i] = None
self.ticks = None
if self.opt.f26 is not None:
self.calc_model()
s = self.spec[i]
self.ax.cla()
co = s.co
if self.opt.co_is_sky:
co = s.co * np.median(s.fl) / np.median(s.co) * 0.1
self.artists['spec'] = barak.spec.plot(
s.wa, s.fl, s.er, co, ax=self.ax, show=0, yperc=0.90)
self.artists['fl'] = self.artists['spec'][0]
self.artists['co'] = self.artists['spec'][2]
if self.nsmooth > 0:
sfl = convolve_psf(s.fl, self.nsmooth, edge='reflect')
self.artists['fl'].set_data(s.wa, sfl)
self.artists['template'], = self.ax.plot([], [], 'y')
self.artists['contpoints'], = self.ax.plot(
[0], [0], 'x', mfc='None', mew=0.5, ms=8, mec='r')
line_artists = barak.spec.plotlines(
self.zp1-1, self.ax, labels=1, fontsize=10, lcolor='0.3',
offsets=False)
self.artists['lines'] = line_artists
self.fl = s.fl
self.wa = s.wa
self.co = co
self.name = self.filenames[i]
fnu = np.log10(X**alpha)
ind = X.searchsorted(0.99)
ax2.semilogx(X, fnu - fnu[ind] + N0, '--c', lw=2,
label=r'$J_\nu\propto\ \nu^{%.3g}$' % alpha)
# plot the starburst spectrum
x = (starburst.wa * u.AA).to(u.rydberg, equivalencies=u.equivalencies.spectral())
x = x.value
X = x[::-1]
F = starburst.logfnu[::-1]
ind = X.searchsorted(1.02)
from barak.convolve import convolve_psf
ax2.semilogx(X, convolve_psf(F - F[ind] + N0,50), 'r', lw=2,
label='$\mathrm{starburst}$')
# apply dust extinction
from barak.extinction import starburst_Calzetti00
ext = starburst_Calzetti00(starburst.wa, EBmV=0.2)
Fnu = np.log10(10**starburst.logfnu * np.exp(-ext.tau))
F = Fnu[::-1]
ax2.semilogx(X, convolve_psf(F - F[ind] + N0, 50), 'r', lw=0.5,
label='$\mathrm{starburst},\ E(B-V)=0.2$')
ax2.legend(frameon=0, loc='lower left', fontsize=12)
#plt.grid(ls='solid', lw=0.5, color='0.7')
xvals = (IP * u.eV).to(u.Ry).value
def update(self, z):
if self.opt.f26 is not None:
wa, nfl, ner, nco, model, artists, options = (self.wa, self.nfl,
self.ner, self.co,
self.model,
self.artists,
self.opt)
else:
wa, nfl, ner, nco, artists, options = (self.wa, self.nfl, self.ner,
self.co, self.artists,
self.opt)
self.z = z
ymult = self.ymult
zp1 = z + 1
betamin = self.vmin / c_kms
betamax = self.vmax / c_kms
for t in artists['ticklabels']:
t.remove()
for t in artists['ticks']:
t.remove()
artists['ticklabels'] = []
artists['ticks'] = []
if artists['ew'] is not None:
artists['ew'].remove()
artists['ew'] = None
for r in artists['regions']:
r.remove()
for s in artists['sky']:
s.remove()
for s in artists['aod']:
s.remove()
artists['regions'] = []
artists['sky'] = []
artists['aod'] = []
# want plots to appear from top down, so we need reversed()
for i, trans in enumerate(reversed(options.linelist)):
atom, ion = split_trans_name(trans['name'].split()[0])
iax, ioff = divmod(i, self.num_per_panel)
ax = self.axes[iax]
offset = ioff * 1.5
#if i >= self.num_per_panel:
# offset = (i - self.num_per_panel) * 1.5
# ax = self.axes[1]
watrans = trans['wa']
obswa = watrans * zp1
wmin = obswa * (1 + 3 * betamin)
wmax = obswa * (1 + 3 * betamax)
if self.opt.showticks and len(self.allticks) > 0:
ticks = self.allticks
tickwmin = obswa * (1 + betamin)
tickwmax = obswa * (1 + betamax)
wticks = ticks.wa
cond = between(wticks, tickwmin, tickwmax)
if cond.any():
vel = (wticks[cond] / obswa - 1) * c_kms
for j, t in enumerate(ticks[cond]):
T, Tlabels = plot_tick_vel(ax,
vel[j],
offset,
t,
tickz=options.tickz)
artists['ticklabels'].extend(Tlabels)
artists['ticks'].extend(T)
cond = between(wa, wmin, wmax)
#good = ~np.isnan(fl) & (er > 0) & ~np.isnan(co)
# remove ultra-low S/N regions to help plotting
cond &= ner < 1.5
cond &= ymult * (nfl - 1) + 1 > -0.1
fl = nfl[cond]
co = nco[cond]
vel = (wa[cond] / obswa - 1) * c_kms
if options.f26 is not None and options.f26.regions is not None:
artists['regions'].extend(
plot_velocity_regions(wmin, wmax, options.f26.regions.wmin,
options.f26.regions.wmax, obswa, ax,
offset, vel,
ymult * (fl - 1) + 1))
#import pdb; pdb.set_trace()
if hasattr(options, 'aod'):
# print ranges used for AOD calculation.
# find the right transition
c0 = ((np.abs(options.aod['wrest'] - trans['wa']) < 0.01) &
(options.aod['atom'] == atom))
itrans = np.flatnonzero(c0)
for row in options.aod[itrans]:
c0 = between(wa[cond], row['wmin'], row['wmax'])
if np.any(c0):
artists['aod'].append(
ax.fill_between(vel[c0],
offset,
offset + 1.5,
facecolor='0.8',
lw=0,
zorder=0))
vranges = []
for w0, w1 in unrelated:
c0 = between(wa[cond], w0, w1)
if c0.any():
vranges.append(c0)
for w0, w1 in ATMOS:
c0 = between(wa[cond], w0, w1)
if c0.any():
artists['sky'].append(
ax.fill_between(vel[c0],
offset,
offset + 1.5,
facecolor='0.9',
lw=0))
if self.smoothby > 1:
if len(fl) > 3 * self.smoothby:
fl = convolve_psf(fl, self.smoothby)
artists['fl'][i].set_xdata(vel)
artists['fl'][i].set_ydata(ymult * (fl - 1) + 1 + offset)
artists['co'][i].set_xdata(vel)
artists['co'][i].set_ydata(ymult * (co - 1) + 1 + offset)
#pdb.set_trace()
if self.opt.residuals:
resid = (fl - model[cond]) / ner[cond]
c0 = np.abs(resid) < 5
artists['resid'][i].set_xdata(vel[c0])
artists['resid'][i].set_ydata(resid[c0] * 0.05 + offset - 0.1)
if self.opt.f26 is not None:
artists['model'][i].set_xdata(vel)
artists['model'][i].set_ydata(ymult * (model[cond] - 1) + 1 +
offset)
tr_id = trans['name'], tuple(trans['tr'])
#import pdb; pdb.set_trace()
art = self.artists['models'][tr_id]
for line in self.models:
m = self.models[line]
if line not in art:
art[line] = ax.plot(vel,
ymult * (m[cond] - 1) + 1 + offset,
'k',
lw=0.2)[0]
else:
art[line].set_xdata(vel)
art[line].set_ydata(ymult * (m[cond] - 1) + 1 + offset)
for ax in self.axes:
ax.set_xlim(self.vmin, self.vmax)
ax.set_ylim(-0.5, self.num_per_panel * 1.5)
self.artists['title'].set_text('$z = %.5f$' % self.z)
if not self.opt.ticklabels:
for t in artists['ticklabels']:
t.set_visible(False)
self.fig.canvas.draw()
self.artists = artists
'--c',
lw=2,
label=r'$J_\nu\propto\ \nu^{%.3g}$' % alpha)
# plot the starburst spectrum
x = (starburst.wa * u.AA).to(u.rydberg,
equivalencies=u.equivalencies.spectral())
x = x.value
X = x[::-1]
F = starburst.logfnu[::-1]
ind = X.searchsorted(1.02)
from barak.convolve import convolve_psf
ax2.semilogx(X,
convolve_psf(F - F[ind] + N0, 50),
'r',
lw=2,
label='$\mathrm{starburst}$')
# apply dust extinction
from barak.extinction import starburst_Calzetti00
ext = starburst_Calzetti00(starburst.wa, EBmV=0.2)
Fnu = np.log10(10**starburst.logfnu * np.exp(-ext.tau))
F = Fnu[::-1]
ax2.semilogx(X,
convolve_psf(F - F[ind] + N0, 50),
'r',
lw=0.5,
label='$\mathrm{starburst},\ E(B-V)=0.2$')
def update(self, z):
if self.opt.f26 is not None:
wa, nfl, ner, nco, model, artists, options = (
self.wa, self.nfl, self.ner, self.co, self.model,
self.artists, self.opt)
else:
wa, nfl, ner, nco, artists, options = (
self.wa, self.nfl, self.ner, self.co,
self.artists, self.opt)
self.z = z
zp1 = z + 1
betamin = self.vmin / c_kms
betamax = self.vmax / c_kms
for t in artists['ticklabels']:
t.remove()
for t in artists['ticks']:
t.remove()
artists['ticklabels'] = []
artists['ticks'] = []
if artists['ew'] is not None:
artists['ew'].remove()
artists['ew'] = None
for r in artists['regions']:
r.remove()
for s in artists['sky']:
s.remove()
artists['regions'] = []
artists['sky'] = []
# want plots to appear from top down, so we need reversed()
for i, trans in enumerate(reversed(options.linelist)):
ax = self.axes[0]
offset = i * 1.5
if i >= self.num_per_panel:
offset = (i - self.num_per_panel) * 1.5
ax = self.axes[1]
watrans = trans['wa']
obswa = watrans * zp1
wmin = obswa * (1 + 3*betamin)
wmax = obswa * (1 + 3*betamax)
if self.opt.showticks and len(self.allticks) > 0:
ticks = self.allticks
tickwmin = obswa * (1 + betamin)
tickwmax = obswa * (1 + betamax)
wticks = ticks.wa
cond = between(wticks, tickwmin, tickwmax)
if cond.any():
vel = (wticks[cond] / obswa - 1) * c_kms
for j,t in enumerate(ticks[cond]):
T,Tlabels = plot_tick_vel(ax, vel[j], offset, t,
tickz=options.tickz)
artists['ticklabels'].extend(Tlabels)
artists['ticks'].extend(T)
if options.f26 is not None and options.f26.regions is not None:
artists['regions'].extend(plot_velocity_regions(
wmin, wmax, options.f26.regions.wmin,
options.f26.regions.wmax,
obswa, ax, offset))
cond = between(wa, wmin, wmax)
#good = ~np.isnan(fl) & (er > 0) & ~np.isnan(co)
# remove ultra-low S/N regions to help plotting
cond &= ner < 1.5
fl = nfl[cond]
co = nco[cond]
vel = (wa[cond] / obswa - 1) * c_kms
vranges = []
for w0, w1 in unrelated:
c0 = between(wa[cond], w0, w1)
if c0.any():
vranges.append(c0)
for w0, w1 in ATMOS:
c0 = between(wa[cond], w0, w1)
if c0.any():
artists['sky'].append(
ax.fill_between(vel[c0], offset,
offset + 1.5, facecolor='0.9', lw=0))
if self.smoothby > 1:
if len(fl) > 3 * self.smoothby:
fl = convolve_psf(fl, self.smoothby)
artists['fl'][i].set_xdata(vel)
artists['fl'][i].set_ydata(fl + offset)
artists['co'][i].set_xdata(vel)
artists['co'][i].set_ydata(co + offset)
#pdb.set_trace()
if self.opt.residuals:
resid = (fl - model[cond]) / ner[cond]
c0 = np.abs(resid) < 5
artists['resid'][i].set_xdata(vel[c0])
artists['resid'][i].set_ydata(resid[c0] * 0.05 + offset - 0.1)
if self.opt.f26 is not None:
artists['model'][i].set_xdata(vel)
artists['model'][i].set_ydata(model[cond] + offset)
for ax in self.axes:
ax.set_xlim(self.vmin, self.vmax)
ax.set_ylim(-0.5, self.num_per_panel * 1.5)
self.artists['title'].set_text('$z = %.5f$' % self.z)
if not self.opt.ticklabels:
for t in artists['ticklabels']:
t.set_visible(False)
self.fig.canvas.draw()
self.artists = artists
def update(self, z):
if self.opt.f26 is not None:
wa, nfl, ner, nco, model, artists, options = (
self.wa, self.nfl, self.ner, self.co, self.model,
self.artists, self.opt)
else:
wa, nfl, ner, nco, artists, options = (
self.wa, self.nfl, self.ner, self.co,
self.artists, self.opt)
self.z = z
ymult = self.ymult
zp1 = z + 1
betamin = self.vmin / c_kms
betamax = self.vmax / c_kms
for t in artists['ticklabels']:
t.remove()
for t in artists['ticks']:
t.remove()
artists['ticklabels'] = []
artists['ticks'] = []
if artists['ew'] is not None:
artists['ew'].remove()
artists['ew'] = None
for r in artists['regions']:
r.remove()
for s in artists['sky']:
s.remove()
for s in artists['aod']:
s.remove()
artists['regions'] = []
artists['sky'] = []
artists['aod'] = []
# want plots to appear from top down, so we need reversed()
for i, trans in enumerate(reversed(options.linelist)):
atom, ion = split_trans_name(trans['name'].split()[0])
iax, ioff = divmod(i, self.num_per_panel)
ax = self.axes[iax]
offset = ioff * 1.5
#if i >= self.num_per_panel:
# offset = (i - self.num_per_panel) * 1.5
# ax = self.axes[1]
watrans = trans['wa']
obswa = watrans * zp1
wmin = obswa * (1 + 3*betamin)
wmax = obswa * (1 + 3*betamax)
if self.opt.showticks and len(self.allticks) > 0:
ticks = self.allticks
tickwmin = obswa * (1 + betamin)
tickwmax = obswa * (1 + betamax)
wticks = ticks.wa
cond = between(wticks, tickwmin, tickwmax)
if cond.any():
vel = (wticks[cond] / obswa - 1) * c_kms
for j,t in enumerate(ticks[cond]):
T,Tlabels = plot_tick_vel(ax, vel[j], offset, t,
tickz=options.tickz)
artists['ticklabels'].extend(Tlabels)
artists['ticks'].extend(T)
cond = between(wa, wmin, wmax)
#good = ~np.isnan(fl) & (er > 0) & ~np.isnan(co)
# remove ultra-low S/N regions to help plotting
cond &= ner < 1.5
cond &= ymult*(nfl-1) + 1 > -0.1
fl = nfl[cond]
co = nco[cond]
vel = (wa[cond] / obswa - 1) * c_kms
if options.f26 is not None and options.f26.regions is not None:
artists['regions'].extend(plot_velocity_regions(
wmin, wmax, options.f26.regions.wmin,
options.f26.regions.wmax,
obswa, ax, offset, vel, ymult*(fl-1) + 1))
#import pdb; pdb.set_trace()
if hasattr(options, 'aod'):
# print ranges used for AOD calculation.
# find the right transition
c0 = ((np.abs(options.aod['wrest'] - trans['wa']) < 0.01) &
(options.aod['atom'] == atom))
itrans = np.flatnonzero(c0)
for row in options.aod[itrans]:
c0 = between(wa[cond], row['wmin'], row['wmax'])
if np.any(c0):
artists['aod'].append(
ax.fill_between(vel[c0], offset, offset+1.5, facecolor='0.8', lw=0,
zorder=0)
)
vranges = []
for w0, w1 in unrelated:
c0 = between(wa[cond], w0, w1)
if c0.any():
vranges.append(c0)
for w0, w1 in ATMOS:
c0 = between(wa[cond], w0, w1)
if c0.any():
artists['sky'].append(
ax.fill_between(vel[c0], offset,
offset + 1.5, facecolor='0.9', lw=0))
if self.smoothby > 1:
if len(fl) > 3 * self.smoothby:
fl = convolve_psf(fl, self.smoothby)
artists['fl'][i].set_xdata(vel)
artists['fl'][i].set_ydata(ymult*(fl-1) + 1 + offset)
artists['co'][i].set_xdata(vel)
artists['co'][i].set_ydata(ymult*(co-1) + 1 + offset)
#pdb.set_trace()
if self.opt.residuals:
resid = (fl - model[cond]) / ner[cond]
c0 = np.abs(resid) < 5
artists['resid'][i].set_xdata(vel[c0])
artists['resid'][i].set_ydata(resid[c0] * 0.05 + offset - 0.1)
if self.opt.f26 is not None:
artists['model'][i].set_xdata(vel)
artists['model'][i].set_ydata(ymult*(model[cond]-1) + 1 + offset)
tr_id = trans['name'], tuple(trans['tr'])
#import pdb; pdb.set_trace()
art = self.artists['models'][tr_id]
for line in self.models:
m = self.models[line]
if line not in art:
art[line] = ax.plot(vel, ymult*(m[cond]-1) + 1 + offset, 'k', lw=0.2)[0]
else:
art[line].set_xdata(vel)
art[line].set_ydata(ymult*(m[cond]-1) + 1 + offset)
for ax in self.axes:
ax.set_xlim(self.vmin, self.vmax)
ax.set_ylim(-0.5, self.num_per_panel * 1.5)
self.artists['title'].set_text('$z = %.5f$' % self.z)
if not self.opt.ticklabels:
for t in artists['ticklabels']:
t.set_visible(False)
self.fig.canvas.draw()
self.artists = artists
# comoponents in wings?
npix = 1.39 / dw * 0.8
tau, ticks = find_tau(wa, lines, atom)
taulo, ticks = find_tau(wa, lineslo, atom)
tauhi, ticks = find_tau(wa, lineshi, atom)
fig = pl.figure(figsize=(4.3, 3))
fig.subplots_adjust(bottom=0.16, left=0.16, right=0.98, top=0.96)
ax = fig.add_subplot(111)
ax.plot(wa, sp.fl,color='0.3', lw=0.5,drawstyle='steps-mid')
ax.plot(wa, sp.co, '0.7', ls='dashed')
ax.plot(wa, sp.co*convolve_psf(np.exp(-taulo), npix), 'r', lw=0.3)
ax.plot(wa, sp.co*convolve_psf(np.exp(-tau), npix), 'r')
ax.plot(wa, sp.co*convolve_psf(np.exp(-tauhi), npix), 'r', lw=0.3)
ax.axhline(0, color='k', lw=0.3)
ax.minorticks_on()
ax.set_xlim(1881, 1904.9)
#ax.set_xlim(1861, 1924.9)
ymax = 3.49
resid = (sp.fl - sp.co*convolve_psf(np.exp(-tau), npix)) / sp.er
ax.axhline((-0.12-0.03)*ymax, color='0.7', lw=0.5)
ax.axhline((-0.12+0.03)*ymax, color='0.7', lw=0.5)
ax.scatter(wa, -0.12*ymax + 0.03*ymax*resid, c='g', marker='.', s=20,
faceted=False)
ax.set_ylim(-0.22*ymax, ymax)
ax.set_xlabel('$\mathrm{Wavelength}\ (\AA)$')
pl.figtext(0.012, 0.55,