def qso_template(outfil='Figures/qso_template.pdf'):
""" van den berk
"""
pyigm_path = imp.find_module('pyigm')[1]
# Load
telfer = pyicq.get_telfer_spec()
clight = const.c.cgs
# Beta spliced to vanden Berk template with host galaxy removed
van_file = pyigm_path+'/data/quasar/VanDmeetBeta_fullResolution.txt'
van_tbl = Table.read(van_file,format='ascii')
isort = np.argsort(van_tbl['nu'])
nu_van = van_tbl['nu'][isort]
fnu_van = van_tbl['f_nu'][isort]
lam_van = (clight/(nu_van*u.Hz)).to('AA')
flam_van = fnu_van * clight / lam_van**2
nrm_pix = np.abs(lam_van-1450*u.AA) < 10*u.AA
nrm_van = np.median(flam_van[nrm_pix])
flam_van = flam_van / nrm_van
# Start the plot
xmnx = (1170., 2300)
pp = PdfPages(outfil)
fig = plt.figure(figsize=(8.0, 5.0))
plt.clf()
gs = gridspec.GridSpec(1,1)
# Lya line
ax = plt.subplot(gs[0])
#ax.xaxis.set_minor_locator(plt.MultipleLocator(0.5))
#ax.xaxis.set_major_locator(plt.MultipleLocator(20.))
#ax.yaxis.set_minor_locator(plt.MultipleLocator(0.1))
#ax.yaxis.set_major_locator(plt.MultipleLocator(0.2))
ax.set_xlim(xmnx)
#ax.set_ylim(ymnx)
ax.set_ylabel('Relative Flux')
ax.set_xlabel('Rest Wavelength (Angstroms)')
lw = 1.
ax.plot(telfer.wavelength, telfer.flux, 'k', linewidth=lw,
label='Telfer (z~1)')
ax.plot(lam_van, flam_van, 'b', linewidth=lw, label='SDSS (z~2)')
# Legend
legend = plt.legend(loc='upper right', scatterpoints=1, borderpad=0.3,
handletextpad=0.3, fontsize='large', numpoints=1)
# Layout and save
xputils.set_fontsize(ax, 17.)
print('Writing {:s}'.format(outfil))
plt.tight_layout(pad=0.2,h_pad=0.0,w_pad=0.4)
plt.subplots_adjust(hspace=0)
pp.savefig(bbox_inches='tight')
plt.close()
# Finish
pp.close()
def fig_lya(inp=('J1555+3628', '88_11'), outfil='fig_j1555_lya.png'):
# Init COS-Halos sightline
cos_halos = COSHalos()
#cos_halos.load_single( ('J0950+4831','177_27'))
cgm_abs = cos_halos[inp]
# ########################################
# Finder (out of order to avoid PDF issues)
#finder.main([cgm_abs.name, cgm_abs.galaxy.coord], imsize=2.*u.arcmin, show_circ=False)
lclr = 'blue'
lw = 2.
# Start the plot
#outfil='fig_j1555_lya.pdf'
#pp = PdfPages(outfil)
# Full QSO spectrum
spec = cos_halos.load_bg_cos_spec(inp, 1215.6700 * u.AA)
plt.figure(figsize=(5, 5))
plt.clf()
gs = gridspec.GridSpec(1, 1)
# Axes
ax = plt.subplot(gs[0])
#ax.xaxis.set_minor_locator(plt.MultipleLocator(0.5))
#ax.xaxis.set_major_locator(plt.MultipleLocator(1.))
#ax.get_xaxis().get_major_formatter().set_useOffset(False)
ax.set_xlim(1436., 1455.)
ax.set_ylim(-0.1, 1.3)
ax.set_ylabel('Normalized Flux')
ax.set_xlabel(r'Wavelength ($\AA$)')
for axis in ['top', 'bottom', 'left', 'right']:
ax.spines[axis].set_linewidth(2.0)
# Zero line
ax.plot([-1e9, 1e9], (0., 0.), 'g--', lw=lw)
wv_lya = 1215.670 * (1 + cgm_abs.zabs)
ax.plot([wv_lya] * 2, [-1e9, 1e9], 'b--', lw=lw)
# Data
ax.plot(spec.wavelength, spec.flux, 'k', drawstyle='steps-mid')
ax.plot(spec.wavelength, spec.sig, 'r:')
#ax.fill_between( [1455., 1490.], [ymnx[0]]*2, [ymnx[1]]*2, color='blue', alpha=0.3)
# Label
ax.text(1437., 0.3, r'HI Ly$\alpha$', ha='left',
fontsize=21.) #, color=lclr)
# Fonts
xputils.set_fontsize(ax, 17.)
# Write
plt.tight_layout(pad=0.2, h_pad=0., w_pad=0.1)
plt.savefig(outfil)
plt.close()
print("Wrote {:s}".format(outfil))
def dla_vary_NHI(outfil='Figures/dla_vary_NHI.pdf'):
""" DLA profiles with NHI varying
"""
# Wavelength array for my 'perfect' instrument
wave = np.linspace(1160., 1270., 20000) * u.AA
vel = (wave-1215.67*u.AA)/(1215.67*u.AA) * const.c.to('km/s')
# Lya line
lya = AbsLine(1215.6700*u.AA)
#lya.attrib['N'] = 10.**(13.6)/u.cm**2
lya.attrib['b'] = 30 * u.km/u.s
lya.attrib['z'] = 0.
aNHI = [20.3, 21., 21.5, 22.]
# Start the plot
xmnx = (-10000, 10000)
ymnx = (0., 1.0)
pp = PdfPages(outfil)
fig = plt.figure(figsize=(8.0, 5.0))
plt.clf()
gs = gridspec.GridSpec(1,1)
# Lya line
ax = plt.subplot(gs[0])
#ax.xaxis.set_minor_locator(plt.MultipleLocator(0.5))
#ax.xaxis.set_major_locator(plt.MultipleLocator(20.))
#ax.yaxis.set_minor_locator(plt.MultipleLocator(0.1))
#ax.yaxis.set_major_locator(plt.MultipleLocator(0.2))
ax.set_xlim(xmnx)
ax.set_ylim(ymnx)
ax.set_ylabel('Normalized Flux')
ax.set_xlabel('Relative Velocity (km/s)')
lw = 1.5
# Data
for NHI in aNHI:
lyai = copy.deepcopy(lya)
lyai.attrib['N'] = 10**NHI / u.cm**2
f_obsi = ltav.voigt_from_abslines(wave, [lyai])
ax.plot(vel, f_obsi.flux, linewidth=lw,
label=r'$\log N_{\rm HI} = $'+'{:0.2f}'.format(NHI))
# Legend
legend = plt.legend(loc='lower left', scatterpoints=1, borderpad=0.3,
handletextpad=0.3, fontsize='large', numpoints=1)
xputils.set_fontsize(ax, 17.)
# Layout and save
print('Writing {:s}'.format(outfil))
plt.tight_layout(pad=0.2,h_pad=0.0,w_pad=0.4)
plt.subplots_adjust(hspace=0)
pp.savefig(bbox_inches='tight')
plt.close()
# Finish
pp.close()
def sawtooth(outfil='Figures/sawtooth.pdf', all_tau=None):
""" Sawtooth opacity
"""
# Load fN
fN_model = FNModel.default_model()
fN_model.zmnx = (2.,4.1) # extrapolate a bit
# teff
zem = 4
wave = np.arange(4500., 6200., 10)
# Calculate
if all_tau is None:
all_tau = np.zeros_like(wave)
for qq,iwave in enumerate(wave):
all_tau[qq] = lyman_ew(iwave, zem, fN_model)
# Flux attenuation
flux = np.exp(-all_tau)
# Start the plot
xmnx = (4500, 6200)
pp = PdfPages(outfil)
fig = plt.figure(figsize=(8.0, 5.0))
plt.clf()
gs = gridspec.GridSpec(1,1)
# Lya line
ax = plt.subplot(gs[0])
#ax.xaxis.set_minor_locator(plt.MultipleLocator(0.5))
#ax.xaxis.set_major_locator(plt.MultipleLocator(20.))
#ax.yaxis.set_minor_locator(plt.MultipleLocator(0.1))
#ax.yaxis.set_major_locator(plt.MultipleLocator(0.2))
ax.set_xlim(xmnx)
ax.set_ylim(0., 1.1)
ax.set_ylabel('IGM Transmission')
ax.set_xlabel('Observed wavelength (z=4 source)')
lw = 2.
ax.plot(wave, flux, 'b', linewidth=lw)
# Label
csz = 17
ax.text(0.10, 0.90, 'f(N) from Prochaska+14', color='blue',
transform=ax.transAxes, size=csz, ha='left')
ax.text(0.10, 0.80, 'Ignores Lyman continuum opacity', color='blue',
transform=ax.transAxes, size=csz, ha='left')
xputils.set_fontsize(ax, 17.)
# Layout and save
print('Writing {:s}'.format(outfil))
plt.tight_layout(pad=0.2,h_pad=0.0,w_pad=0.4)
plt.subplots_adjust(hspace=0)
pp.savefig(bbox_inches='tight')
plt.close()
# Finish
pp.close()
return all_tau
def teff_LL(outfil='Figures/teff_LL.pdf'):
""" Plot teff_LL from z=3.5 down
"""
# z
zem = 3.5
z912 = 3.
# f(N)
fnmodel = FNModel.default_model()
fnmodel.zmnx = (0.5, 4) # extend default range
# Calculate
zval, teff_LL = lyman_limit(fnmodel, z912, zem)
# Start the plot
xmnx = (3.5, 3)
pp = PdfPages(outfil)
fig = plt.figure(figsize=(8.0, 5.0))
plt.clf()
gs = gridspec.GridSpec(1, 1)
# Lya line
ax = plt.subplot(gs[0])
#ax.xaxis.set_minor_locator(plt.MultipleLocator(0.5))
#ax.xaxis.set_major_locator(plt.MultipleLocator(20.))
#ax.yaxis.set_minor_locator(plt.MultipleLocator(0.1))
#ax.yaxis.set_major_locator(plt.MultipleLocator(0.2))
ax.set_xlim(xmnx)
ax.set_ylim(0., 2)
ax.set_ylabel(r'$\tau_{\rm eff}^{\rm LL}$')
ax.set_xlabel('z')
lw = 2.
# Data
ax.plot(zval, teff_LL, 'b', linewidth=lw) #, label='SDSS QSOs (z=4)')
# Label
csz = 17
ax.text(0.10,
0.80,
'Source at z=3.5',
color='black',
transform=ax.transAxes,
size=csz,
ha='left')
xputils.set_fontsize(ax, 17.)
# Layout and save
print('Writing {:s}'.format(outfil))
plt.tight_layout(pad=0.2, h_pad=0.0, w_pad=0.4)
plt.subplots_adjust(hspace=0)
pp.savefig(bbox_inches='tight')
plt.close()
# Finish
pp.close()
def q1422(outfil='Figures/q1422.pdf'):
""" Series of plots on Q1422
"""
q1422 = lsio.readspec('/Users/xavier/Keck/HIRES/RedData/Q1422+2309/Q1422+2309.fits')
axmnx = [ [4000, 6000],
[4900, 5500],
[5100, 5300],
[5150, 5250],
[5190, 5220],
]
aymnx = [ [0., 7300],
[0., 2000],
[0., 1700],
[0., 1100],
[0., 1100],
]
lw = 1.
csz = 19.
# Start the plot
pp = PdfPages(outfil)
fig = plt.figure(figsize=(8.0, 5.0))
plt.clf()
gs = gridspec.GridSpec(1,1)
# Loop
for qq, xmnx in enumerate(axmnx):
# Spectrum
ax = plt.subplot(gs[0])
ax.set_xlim(xmnx)
ax.set_ylim(aymnx[qq])
#ax.set_ylim(ymnx)
ax.set_ylabel('Relative Flux')
ax.set_xlabel("Wavelength (Ang)")
ax.plot(q1422.wavelength, q1422.flux, 'k', linewidth=lw)
#
ax.text(0.05, 0.9, 'Keck/HIRES: Q1422+2309', color='blue',
transform=ax.transAxes, size=csz, ha='left')#, bbox={'facecolor':'white'})
#
xputils.set_fontsize(ax, 17.)
# Layout and save
plt.tight_layout(pad=0.2,h_pad=0.0,w_pad=0.4)
plt.subplots_adjust(hspace=0)
pp.savefig(bbox_inches='tight', transparent=True)
plt.close()
# Finish
print('Writing {:s}'.format(outfil))
pp.close()
def xq100_example(outfil='fig_xq100_example.pdf'):
# Load spectrum
spec_fil = os.getenv('DROPBOX_DIR') + '/XQ-100/data/J0030-5159_uvb.fits'
spec = load_spectrum(spec_fil)
# Start the plot
if outfil is not None:
pp = PdfPages(outfil)
plt.figure(figsize=(8, 5))
plt.clf()
gs = gridspec.GridSpec(1, 1)
fsz = 17.
# Read and plot full spectrum
ax_full = plt.subplot(gs[0])
# Limits
wvmnx = [3500., 7000.]
gdpix = np.where(spec.dispersion < wvmnx[1] * u.AA)[0]
perc = xsb.perc(spec.flux[gdpix])
ax_full.set_xlim(wvmnx)
#ax_full.set_ylim(-0.05*perc[1], 1.1*perc[1])
ax_full.set_ylim(-1e-18, 7e-17)
# Plot
ax_full.plot(spec.dispersion, spec.flux, color='black', lw=1.0)
ax_full.plot(wvmnx, [0., 0.], '--', color='green')
# Label
ax_full.set_xlabel('Wavelength')
ax_full.set_ylabel('Relative Flux')
ax_full.text(0.05,
0.9,
'XQ100 J0030-5159',
transform=ax_full.transAxes,
color='black',
size='x-large',
ha='left',
va='center',
bbox={'facecolor': 'white'})
# Font size
xputils.set_fontsize(ax_full, fsz)
# Finish page
plt.tight_layout(pad=0.2, h_pad=0.3, w_pad=0.0)
pp.savefig()
plt.close()
print('Wrote: {:s}'.format(outfil))
# Finish
pp.close()
def dteff(outfil='Figures/dteff.pdf'):
""" Differential teff (Lya)
"""
# Load fN
fN_model = FNModel.default_model()
# teff
cumul = []
iwave = 1215.67 * (1+2.5)
zem = 2.6
teff_alpha = lyman_ew(iwave, zem, fN_model, cumul=cumul)
print('teff = {:g}'.format(teff_alpha))
dteff = cumul[1] - np.roll(cumul[1],1)
dteff[0] = dteff[1] # Fix first value
# Start the plot
xmnx = (12, 22)
pp = PdfPages(outfil)
fig = plt.figure(figsize=(8.0, 5.0))
plt.clf()
gs = gridspec.GridSpec(1,1)
# Lya line
ax = plt.subplot(gs[0])
#ax.xaxis.set_minor_locator(plt.MultipleLocator(0.5))
#ax.xaxis.set_major_locator(plt.MultipleLocator(20.))
#ax.yaxis.set_minor_locator(plt.MultipleLocator(0.1))
#ax.yaxis.set_major_locator(plt.MultipleLocator(0.2))
ax.set_xlim(xmnx)
#ax.set_ylim(ymnx)
ax.set_ylabel(r'$d\tau_{\rm eff, \alpha}/d\log N$')
ax.set_xlabel(r'$\log \, N_{\rm HI}$')
lw = 2.
ax.plot(cumul[0], dteff, 'k', linewidth=lw)
# Label
csz = 17
ax.text(0.60, 0.90, 'f(N) from Prochaska+14', color='blue',
transform=ax.transAxes, size=csz, ha='left')
ax.text(0.60, 0.80, 'z=2.5', color='blue',
transform=ax.transAxes, size=csz, ha='left')
xputils.set_fontsize(ax, 17.)
# Layout and save
print('Writing {:s}'.format(outfil))
plt.tight_layout(pad=0.2,h_pad=0.0,w_pad=0.4)
plt.subplots_adjust(hspace=0)
pp.savefig(bbox_inches='tight')
plt.close()
# Finish
pp.close()
def wfc3_qso(outfil='Figures/wfc3_qso.pdf'):
""" Show a QSO that is transmissive at the Lyman limit
"""
# WFC3
wfc3, _ = pyicq.wfc3_continuum(0)
#zem = 4.
# Start the plot
xmnx = (650, 1300)
pp = PdfPages(outfil)
fig = plt.figure(figsize=(8.0, 5.0))
plt.clf()
gs = gridspec.GridSpec(1, 1)
# Lya line
ax = plt.subplot(gs[0])
#ax.xaxis.set_minor_locator(plt.MultipleLocator(0.5))
#ax.xaxis.set_major_locator(plt.MultipleLocator(20.))
#ax.yaxis.set_minor_locator(plt.MultipleLocator(0.1))
#ax.yaxis.set_major_locator(plt.MultipleLocator(0.2))
ax.set_xlim(xmnx)
ax.set_ylim(0., 70)
ax.set_ylabel('Relative Flux')
ax.set_xlabel('Rest wavelength')
lw = 2.
# Data
ax.plot(wfc3.wavelength,
wfc3.flux,
'k',
linewidth=lw,
label='SDSS QSOs (z=4)')
# Label
csz = 17
ax.text(0.10,
0.80,
'HST/WFC3: QSO spectrum (z~2)',
color='black',
transform=ax.transAxes,
size=csz,
ha='left')
xputils.set_fontsize(ax, 17.)
# Layout and save
print('Writing {:s}'.format(outfil))
plt.tight_layout(pad=0.2, h_pad=0.0, w_pad=0.4)
plt.subplots_adjust(hspace=0)
pp.savefig(bbox_inches='tight')
plt.close()
# Finish
pp.close()
def qso_sed(outfil='Figures/qso_sed.pdf'):
""" Plots a few QSO examples
"""
sdss_dr7 = quasars.SdssQuasars()
#bal = sdss_dr7[(367, 506)]
#bal = sdss_dr7[(726, 60)]
bal = sdss_dr7[(668, 193)]
bal.load_spec(load_conti=False)
fj0812 = sdss_dr7[(861, 333)]
fj0812.load_spec(load_conti=False)
# Start the plot
xmnx = (1180., 1580)
pp = PdfPages(outfil)
fig = plt.figure(figsize=(8.0, 5.0))
plt.clf()
gs = gridspec.GridSpec(2, 1)
# Lya line
for qq in range(2):
if qq == 0:
qso = fj0812
elif qq == 1:
qso = bal
ax = plt.subplot(gs[qq])
#ax.xaxis.set_minor_locator(plt.MultipleLocator(0.5))
#ax.xaxis.set_major_locator(plt.MultipleLocator(20.))
#ax.yaxis.set_minor_locator(plt.MultipleLocator(0.1))
#ax.yaxis.set_major_locator(plt.MultipleLocator(0.2))
ax.set_xlim(xmnx)
#ax.set_ylim(ymnx)
ax.set_ylabel('Relative Flux')
if qq < 1:
ax.get_xaxis().set_ticks([])
else:
ax.set_xlabel('Rest Wavelength (Angstroms)')
lw = 1.
ax.plot(qso.spec.wavelength / (qso.z + 1),
qso.spec.flux,
'k',
linewidth=lw)
xputils.set_fontsize(ax, 17.)
# Layout and save
print('Writing {:s}'.format(outfil))
plt.tight_layout(pad=0.2, h_pad=0.0, w_pad=0.4)
plt.subplots_adjust(hspace=0)
pp.savefig(bbox_inches='tight')
plt.close()
# Finish
pp.close()
def real_dla_vary_NHI(outfil='Figures/real_dla_vary_NHI.pdf'):
""" DLA profiles with NHI varying
"""
# Wavelength array for my 'perfect' instrument
files = ['/Users/xavier/GRB/data/080607/LRIS/GRB080607_B600N.fits']
lbls = [r'GRB080607: $\log N_{\rm HI} = 22.7$']
zdlas = [3.03626]
# Start the plot
xmnx = (-20000, 20000)
ymnx = (0., 1.0)
pp = PdfPages(outfil)
fig = plt.figure(figsize=(8.0, 5.0))
plt.clf()
gs = gridspec.GridSpec(1, 1)
# Lya line
ax = plt.subplot(gs[0])
#ax.xaxis.set_minor_locator(plt.MultipleLocator(0.5))
#ax.xaxis.set_major_locator(plt.MultipleLocator(20.))
#ax.yaxis.set_minor_locator(plt.MultipleLocator(0.1))
#ax.yaxis.set_major_locator(plt.MultipleLocator(0.2))
ax.set_xlim(xmnx)
ax.set_ylim(ymnx)
ax.set_ylabel('Normalized Flux')
ax.set_xlabel('Relative Velocity (km/s)')
lw = 1.5
# Data
for zdla, lbl, fil in zip(zdlas, lbls, files):
spec = lsio.readspec(fil)
vel = spec.relative_vel(1215.6701 * u.AA * (1 + zdla))
ax.plot(vel, spec.flux, linewidth=lw, label=lbl)
# Legend
legend = plt.legend(loc='lower left',
scatterpoints=1,
borderpad=0.3,
handletextpad=0.3,
fontsize='large',
numpoints=1)
xputils.set_fontsize(ax, 17.)
# Layout and save
print('Writing {:s}'.format(outfil))
plt.tight_layout(pad=0.2, h_pad=0.0, w_pad=0.4)
plt.subplots_adjust(hspace=0)
pp.savefig(bbox_inches='tight')
plt.close()
# Finish
pp.close()
def qso_fuv(outfil='Figures/qso_fuv.pdf'):
""" FUV flux from QSOs
"""
pyigm_path = imp.find_module('pyigm')[1]
# Load
telfer = pyicq.get_telfer_spec()
# Start the plot
xmnx = (900., 1220)
pp = PdfPages(outfil)
fig = plt.figure(figsize=(8.0, 5.0))
plt.clf()
gs = gridspec.GridSpec(1, 1)
# Lya line
ax = plt.subplot(gs[0])
#ax.xaxis.set_minor_locator(plt.MultipleLocator(0.5))
#ax.xaxis.set_major_locator(plt.MultipleLocator(20.))
#ax.yaxis.set_minor_locator(plt.MultipleLocator(0.1))
#ax.yaxis.set_major_locator(plt.MultipleLocator(0.2))
ax.set_xlim(xmnx)
#ax.set_ylim(ymnx)
ax.set_ylabel('Relative Flux')
ax.set_xlabel('Rest Wavelength (Angstroms)')
lw = 1.
ax.plot(telfer.wavelength,
telfer.flux,
'k',
linewidth=lw,
label='Telfer Average QSO SED (z~1)')
# Legend
legend = plt.legend(loc='upper left',
scatterpoints=1,
borderpad=0.3,
handletextpad=0.3,
fontsize='x-large',
numpoints=1)
# Layout and save
xputils.set_fontsize(ax, 17.)
print('Writing {:s}'.format(outfil))
plt.tight_layout(pad=0.2, h_pad=0.0, w_pad=0.4)
plt.subplots_adjust(hspace=0)
pp.savefig(bbox_inches='tight')
plt.close()
# Finish
pp.close()
def teff_LL(outfil='Figures/teff_LL.pdf'):
""" Plot teff_LL from z=3.5 down
"""
# z
zem = 3.5
z912 = 3.
# f(N)
fnmodel = FNModel.default_model()
fnmodel.zmnx = (0.5,4) # extend default range
# Calculate
zval, teff_LL = lyman_limit(fnmodel, z912, zem)
# Start the plot
xmnx = (3.5, 3)
pp = PdfPages(outfil)
fig = plt.figure(figsize=(8.0, 5.0))
plt.clf()
gs = gridspec.GridSpec(1,1)
# Lya line
ax = plt.subplot(gs[0])
#ax.xaxis.set_minor_locator(plt.MultipleLocator(0.5))
#ax.xaxis.set_major_locator(plt.MultipleLocator(20.))
#ax.yaxis.set_minor_locator(plt.MultipleLocator(0.1))
#ax.yaxis.set_major_locator(plt.MultipleLocator(0.2))
ax.set_xlim(xmnx)
ax.set_ylim(0., 2)
ax.set_ylabel(r'$\tau_{\rm eff}^{\rm LL}$')
ax.set_xlabel('z')
lw = 2.
# Data
ax.plot(zval, teff_LL, 'b', linewidth=lw)#, label='SDSS QSOs (z=4)')
# Label
csz = 17
ax.text(0.10, 0.80, 'Source at z=3.5',
color='black', transform=ax.transAxes, size=csz, ha='left')
xputils.set_fontsize(ax, 17.)
# Layout and save
print('Writing {:s}'.format(outfil))
plt.tight_layout(pad=0.2,h_pad=0.0,w_pad=0.4)
plt.subplots_adjust(hspace=0)
pp.savefig(bbox_inches='tight')
plt.close()
# Finish
pp.close()
def qso_sed(outfil='Figures/qso_sed.pdf'):
""" Plots a few QSO examples
"""
sdss_dr7 = quasars.SdssQuasars()
#bal = sdss_dr7[(367, 506)]
#bal = sdss_dr7[(726, 60)]
bal = sdss_dr7[(668, 193)]
bal.load_spec(load_conti=False)
fj0812 = sdss_dr7[(861,333)]
fj0812.load_spec(load_conti=False)
# Start the plot
xmnx = (1180., 1580)
pp = PdfPages(outfil)
fig = plt.figure(figsize=(8.0, 5.0))
plt.clf()
gs = gridspec.GridSpec(2,1)
# Lya line
for qq in range(2):
if qq == 0:
qso = fj0812
elif qq == 1:
qso = bal
ax = plt.subplot(gs[qq])
#ax.xaxis.set_minor_locator(plt.MultipleLocator(0.5))
#ax.xaxis.set_major_locator(plt.MultipleLocator(20.))
#ax.yaxis.set_minor_locator(plt.MultipleLocator(0.1))
#ax.yaxis.set_major_locator(plt.MultipleLocator(0.2))
ax.set_xlim(xmnx)
#ax.set_ylim(ymnx)
ax.set_ylabel('Relative Flux')
if qq < 1:
ax.get_xaxis().set_ticks([])
else:
ax.set_xlabel('Rest Wavelength (Angstroms)')
lw = 1.
ax.plot(qso.spec.wavelength/(qso.z+1), qso.spec.flux, 'k', linewidth=lw)
xputils.set_fontsize(ax, 17.)
# Layout and save
print('Writing {:s}'.format(outfil))
plt.tight_layout(pad=0.2,h_pad=0.0,w_pad=0.4)
plt.subplots_adjust(hspace=0)
pp.savefig(bbox_inches='tight')
plt.close()
# Finish
pp.close()
def real_dla_vary_NHI(outfil='Figures/real_dla_vary_NHI.pdf'):
""" DLA profiles with NHI varying
"""
# Wavelength array for my 'perfect' instrument
files = ['/Users/xavier/GRB/data/080607/LRIS/GRB080607_B600N.fits']
lbls = [r'GRB080607: $\log N_{\rm HI} = 22.7$']
zdlas = [3.03626]
# Start the plot
xmnx = (-20000, 20000)
ymnx = (0., 1.0)
pp = PdfPages(outfil)
fig = plt.figure(figsize=(8.0, 5.0))
plt.clf()
gs = gridspec.GridSpec(1,1)
# Lya line
ax = plt.subplot(gs[0])
#ax.xaxis.set_minor_locator(plt.MultipleLocator(0.5))
#ax.xaxis.set_major_locator(plt.MultipleLocator(20.))
#ax.yaxis.set_minor_locator(plt.MultipleLocator(0.1))
#ax.yaxis.set_major_locator(plt.MultipleLocator(0.2))
ax.set_xlim(xmnx)
ax.set_ylim(ymnx)
ax.set_ylabel('Normalized Flux')
ax.set_xlabel('Relative Velocity (km/s)')
lw = 1.5
# Data
for zdla,lbl,fil in zip(zdlas,lbls,files):
spec = lsio.readspec(fil)
vel = spec.relative_vel(1215.6701*u.AA*(1+zdla))
ax.plot(vel, spec.flux, linewidth=lw,
label=lbl)
# Legend
legend = plt.legend(loc='lower left', scatterpoints=1, borderpad=0.3,
handletextpad=0.3, fontsize='large', numpoints=1)
xputils.set_fontsize(ax, 17.)
# Layout and save
print('Writing {:s}'.format(outfil))
plt.tight_layout(pad=0.2,h_pad=0.0,w_pad=0.4)
plt.subplots_adjust(hspace=0)
pp.savefig(bbox_inches='tight')
plt.close()
# Finish
pp.close()
def dXdz(outfil='Figures/dXdz.pdf'):
""" Plot dXdz vs. z
"""
# z
zval = np.linspace(1., 5, 100)
# dX/dz
dXdz = pyiu.cosm_xz(zval, cosmo=Planck15, flg_return=1)
# Start the plot
xmnx = (1., 5)
pp = PdfPages(outfil)
fig = plt.figure(figsize=(8.0, 5.0))
plt.clf()
gs = gridspec.GridSpec(1,1)
# Lya line
ax = plt.subplot(gs[0])
#ax.xaxis.set_minor_locator(plt.MultipleLocator(0.5))
#ax.xaxis.set_major_locator(plt.MultipleLocator(20.))
#ax.yaxis.set_minor_locator(plt.MultipleLocator(0.1))
#ax.yaxis.set_major_locator(plt.MultipleLocator(0.2))
ax.set_xlim(xmnx)
ax.set_ylim(0., 5)
ax.set_ylabel('dX/dz')
ax.set_xlabel('z')
lw = 2.
# Data
ax.plot(zval, dXdz, 'k', linewidth=lw)#, label='SDSS QSOs (z=4)')
# Label
csz = 17
#ax.text(0.10, 0.80, 'HST/WFC3: QSO spectrum (z~2)', color='black',
# transform=ax.transAxes, size=csz, ha='left')
xputils.set_fontsize(ax, 17.)
# Layout and save
print('Writing {:s}'.format(outfil))
plt.tight_layout(pad=0.2,h_pad=0.0,w_pad=0.4)
plt.subplots_adjust(hspace=0)
pp.savefig(bbox_inches='tight')
plt.close()
# Finish
pp.close()
def drho_dNHI(outfil='Figures/drho_dNHI.pdf'):
""" Differential contribution to rho_HI
"""
# Wavelength array for my 'perfect' instrument
fnmodel = FNModel.default_model()
rhoHI, cumul, lgNHI = fnmodel.calculate_rhoHI(2.5, (12., 22.5), cumul=True)
cumul = cumul/cumul[-1] / (lgNHI[1]-lgNHI[0]) # dlogN
diff = cumul - np.roll(cumul,1)
diff[0] = diff[1]
# Start the plot
xmnx = (16., 22.5)
ymnx = (0., 1.0)
pp = PdfPages(outfil)
fig = plt.figure(figsize=(8.0, 5.0))
plt.clf()
gs = gridspec.GridSpec(1,1)
# Lya line
ax = plt.subplot(gs[0])
#ax.xaxis.set_minor_locator(plt.MultipleLocator(0.5))
#ax.xaxis.set_major_locator(plt.MultipleLocator(20.))
#ax.yaxis.set_minor_locator(plt.MultipleLocator(0.1))
#ax.yaxis.set_major_locator(plt.MultipleLocator(0.2))
ax.set_xlim(xmnx)
#ax.set_ylim(ymnx)
ax.set_ylabel(r'Normalized $d\rho_{\rm HI} / d\log N_{\rm HI}$')
ax.set_xlabel(r'$\log N_{\rm HI}$')
ax.plot(lgNHI, diff, 'b')
# Legend
#legend = plt.legend(loc='lower left', scatterpoints=1, borderpad=0.3,
# handletextpad=0.3, fontsize='large', numpoints=1)
xputils.set_fontsize(ax, 17.)
# Layout and save
print('Writing {:s}'.format(outfil))
plt.tight_layout(pad=0.2,h_pad=0.0,w_pad=0.4)
plt.subplots_adjust(hspace=0)
pp.savefig(bbox_inches='tight')
plt.close()
# Finish
pp.close()
def drho_dNHI(outfil='Figures/drho_dNHI.pdf'):
""" Differential contribution to rho_HI
"""
# Wavelength array for my 'perfect' instrument
fnmodel = FNModel.default_model()
rhoHI, cumul, lgNHI = fnmodel.calculate_rhoHI(2.5, (12., 22.5), cumul=True)
cumul = cumul / cumul[-1] / (lgNHI[1] - lgNHI[0]) # dlogN
diff = cumul - np.roll(cumul, 1)
diff[0] = diff[1]
# Start the plot
xmnx = (16., 22.5)
ymnx = (0., 1.0)
pp = PdfPages(outfil)
fig = plt.figure(figsize=(8.0, 5.0))
plt.clf()
gs = gridspec.GridSpec(1, 1)
# Lya line
ax = plt.subplot(gs[0])
#ax.xaxis.set_minor_locator(plt.MultipleLocator(0.5))
#ax.xaxis.set_major_locator(plt.MultipleLocator(20.))
#ax.yaxis.set_minor_locator(plt.MultipleLocator(0.1))
#ax.yaxis.set_major_locator(plt.MultipleLocator(0.2))
ax.set_xlim(xmnx)
#ax.set_ylim(ymnx)
ax.set_ylabel(r'Normalized $d\rho_{\rm HI} / d\log N_{\rm HI}$')
ax.set_xlabel(r'$\log N_{\rm HI}$')
ax.plot(lgNHI, diff, 'b')
# Legend
#legend = plt.legend(loc='lower left', scatterpoints=1, borderpad=0.3,
# handletextpad=0.3, fontsize='large', numpoints=1)
xputils.set_fontsize(ax, 17.)
# Layout and save
print('Writing {:s}'.format(outfil))
plt.tight_layout(pad=0.2, h_pad=0.0, w_pad=0.4)
plt.subplots_adjust(hspace=0)
pp.savefig(bbox_inches='tight')
plt.close()
# Finish
pp.close()
def dXdz(outfil='Figures/dXdz.pdf'):
""" Plot dXdz vs. z
"""
# z
zval = np.linspace(1., 5, 100)
# dX/dz
dXdz = pyiu.cosm_xz(zval, cosmo=Planck15, flg_return=1)
# Start the plot
xmnx = (1., 5)
pp = PdfPages(outfil)
fig = plt.figure(figsize=(8.0, 5.0))
plt.clf()
gs = gridspec.GridSpec(1, 1)
# Lya line
ax = plt.subplot(gs[0])
#ax.xaxis.set_minor_locator(plt.MultipleLocator(0.5))
#ax.xaxis.set_major_locator(plt.MultipleLocator(20.))
#ax.yaxis.set_minor_locator(plt.MultipleLocator(0.1))
#ax.yaxis.set_major_locator(plt.MultipleLocator(0.2))
ax.set_xlim(xmnx)
ax.set_ylim(0., 5)
ax.set_ylabel('dX/dz')
ax.set_xlabel('z')
lw = 2.
# Data
ax.plot(zval, dXdz, 'k', linewidth=lw) #, label='SDSS QSOs (z=4)')
# Label
csz = 17
#ax.text(0.10, 0.80, 'HST/WFC3: QSO spectrum (z~2)', color='black',
# transform=ax.transAxes, size=csz, ha='left')
xputils.set_fontsize(ax, 17.)
# Layout and save
print('Writing {:s}'.format(outfil))
plt.tight_layout(pad=0.2, h_pad=0.0, w_pad=0.4)
plt.subplots_adjust(hspace=0)
pp.savefig(bbox_inches='tight')
plt.close()
# Finish
pp.close()
def qso_fuv(outfil='Figures/qso_fuv.pdf'):
""" FUV flux from QSOs
"""
pyigm_path = imp.find_module('pyigm')[1]
# Load
telfer = pyicq.get_telfer_spec()
# Start the plot
xmnx = (900., 1220)
pp = PdfPages(outfil)
fig = plt.figure(figsize=(8.0, 5.0))
plt.clf()
gs = gridspec.GridSpec(1,1)
# Lya line
ax = plt.subplot(gs[0])
#ax.xaxis.set_minor_locator(plt.MultipleLocator(0.5))
#ax.xaxis.set_major_locator(plt.MultipleLocator(20.))
#ax.yaxis.set_minor_locator(plt.MultipleLocator(0.1))
#ax.yaxis.set_major_locator(plt.MultipleLocator(0.2))
ax.set_xlim(xmnx)
#ax.set_ylim(ymnx)
ax.set_ylabel('Relative Flux')
ax.set_xlabel('Rest Wavelength (Angstroms)')
lw = 1.
ax.plot(telfer.wavelength, telfer.flux, 'k', linewidth=lw,
label='Telfer Average QSO SED (z~1)')
# Legend
legend = plt.legend(loc='upper left', scatterpoints=1, borderpad=0.3,
handletextpad=0.3, fontsize='x-large', numpoints=1)
# Layout and save
xputils.set_fontsize(ax, 17.)
print('Writing {:s}'.format(outfil))
plt.tight_layout(pad=0.2,h_pad=0.0,w_pad=0.4)
plt.subplots_adjust(hspace=0)
pp.savefig(bbox_inches='tight')
plt.close()
# Finish
pp.close()
def wfc3_qso(outfil='Figures/wfc3_qso.pdf'):
""" Show a QSO that is transmissive at the Lyman limit
"""
# WFC3
wfc3, _ = pyicq.wfc3_continuum(0)
#zem = 4.
# Start the plot
xmnx = (650, 1300)
pp = PdfPages(outfil)
fig = plt.figure(figsize=(8.0, 5.0))
plt.clf()
gs = gridspec.GridSpec(1,1)
# Lya line
ax = plt.subplot(gs[0])
#ax.xaxis.set_minor_locator(plt.MultipleLocator(0.5))
#ax.xaxis.set_major_locator(plt.MultipleLocator(20.))
#ax.yaxis.set_minor_locator(plt.MultipleLocator(0.1))
#ax.yaxis.set_major_locator(plt.MultipleLocator(0.2))
ax.set_xlim(xmnx)
ax.set_ylim(0., 70)
ax.set_ylabel('Relative Flux')
ax.set_xlabel('Rest wavelength')
lw = 2.
# Data
ax.plot(wfc3.wavelength, wfc3.flux, 'k', linewidth=lw, label='SDSS QSOs (z=4)')
# Label
csz = 17
ax.text(0.10, 0.80, 'HST/WFC3: QSO spectrum (z~2)', color='black',
transform=ax.transAxes, size=csz, ha='left')
xputils.set_fontsize(ax, 17.)
# Layout and save
print('Writing {:s}'.format(outfil))
plt.tight_layout(pad=0.2,h_pad=0.0,w_pad=0.4)
plt.subplots_adjust(hspace=0)
pp.savefig(bbox_inches='tight')
plt.close()
# Finish
pp.close()
def fig_sngl_metPDF(system):
""" Shows a single metallicity PDF
"""
from matplotlib import transforms
# Read Metallicity input
mfile = '../Analysis/COS_Halos_MTL.ascii'
data = Table.read(mfile, format='ascii')
mtl_inps = np.where(data['name'] == system[0]+'_'+system[1])[0]
ion_lst = []
clrs = []
cdict = {0:'black', -1:'red', -2:'green'}
for inp in mtl_inps:
ion_lst.append(data[inp]['ion'])
clrs.append(cdict[data[inp]['flag']])
# Read COS-Halos
cos_halos = COSHalos()
cos_halos.load_single_fits(system, skip_ions=True)
orig_NHI = cos_halos.NHI
orig_fNHI = cos_halos.flag_NHI
# Read PDF
mtlfil = '../Analysis/COS_Halos_MTL.hdf5'
fh5 = h5py.File(mtlfil,'r')
mPDF = MetallicityPDF(fh5['met']['left_edge_bins']+
fh5['met']['left_edge_bins'].attrs['BINSIZE']/2.,
fh5['met'][system[0]+'_'+system[1]])
# KLUDGE
print("BIG KLUDGE HERE")
bad = np.where(mPDF.ZH < -2)[0]
mPDF.pdf_ZH[bad] = 0.
mPDF.normalize()
# Init
NHI_mnx = (14.8, 19.1)
# Start the plot
outfil = 'fig_metPDF_'+system[0]+'_'+system[1]+'.pdf'
pp = PdfPages(outfil)
fig = plt.figure(figsize=(7, 4))
plt.clf()
ax = plt.gca()
# Axes
#wvmnx = awvmnx[iuvq['instr']]
#ax.xaxis.set_minor_locator(plt.MultipleLocator(500.))
#ax.yaxis.set_major_locator(plt.MultipleLocator(1.))
#plt.ylim(0, nsys+1)
ax.set_xlim(-2,1)
# Labels
lsz = 19.
# Giddy up
ax.bar(mPDF.ZH-mPDF.dZH/2., mPDF.pdf_ZH, width=mPDF.dZH)
ax.set_xlabel("[Z/H]", size=lsz)
ax.set_ylabel("PDF", size=lsz)
# Label system
csz = 18.
lbl = '{:s}_{:s}'.format(system[0], system[1])
ax.text(0.1, 0.87, lbl, transform=ax.transAxes, color='black',
size=csz, ha='left')
# Ions
x = -1.8
ymnx = ax.get_ylim()
y = 0.75 * ymnx[1]
isz = 14.
t = plt.gca().transData
for s,c in zip(ion_lst,clrs):
text = plt.text(x,y," "+s+" ",color=c, transform=t, size=isz)
text.draw(fig.canvas.get_renderer())
ex = text.get_window_extent()
t = transforms.offset_copy(text._transform, x=ex.width*0.9, units='dots')
# End
xputils.set_fontsize(ax, 16.)
print('Writing {:s}'.format(outfil))
plt.tight_layout(pad=0.2,h_pad=0.,w_pad=0.1)
pp.savefig()
pp.close()
plt.close()
def mfp_spec(outfil='Figures/mfp_spec.pdf', all_tau=None, scl=1.):
""" Stacked spectrum for MFP
"""
# SDSS
zq = 4.
hdu = fits.open(
'/Users/xavier/paper/LLS/taueff/Analysis/stack_DR7_z3.92_z4.02.fits')
sdss_fx = hdu[0].data
sdss_wave = hdu[2].data
zem = 4.
# Start the plot
xmnx = (800, 1000)
ymnx = (0., 1.0)
pp = PdfPages(outfil)
fig = plt.figure(figsize=(8.0, 5.0))
plt.clf()
gs = gridspec.GridSpec(1, 1)
# Lya line
ax = plt.subplot(gs[0])
#ax.xaxis.set_minor_locator(plt.MultipleLocator(0.5))
#ax.xaxis.set_major_locator(plt.MultipleLocator(20.))
#ax.yaxis.set_minor_locator(plt.MultipleLocator(0.1))
#ax.yaxis.set_major_locator(plt.MultipleLocator(0.2))
ax.set_xlim(xmnx)
ax.set_ylim(ymnx)
ax.set_ylabel('Relative Flux')
ax.set_xlabel('Rest Wavelength (Ang)')
lw = 1.5
# Data
ax.plot(sdss_wave, sdss_fx, 'k', linewidth=lw, label='SDSS QSOs (z=4)')
# Label
xexp = 860.
headl = 6.
ax.plot([911.7] * 2, ymnx, '--', color='red', linewidth=1.5)
ax.arrow(911.7,
0.6,
xexp - 911.7 + headl,
0.,
linewidth=2,
head_width=0.03,
head_length=headl,
fc='blue',
ec='blue')
csz = 19.
ax.text(890.,
0.63,
r'r = $\lambda_{\rm mfp}$',
color='blue',
size=csz,
ha='center')
# exp(-1)
y1 = 0.43
y2 = np.exp(-1) * y1
yplt = (y1 + y2) / 2.
yerr = (y2 - y1) / 2.
ax.errorbar([xexp], [yplt],
yerr=yerr,
color='green',
linewidth=2,
capthick=2)
ax.plot([xexp, 911.7], [y1] * 2, ':', color='green', linewidth=2)
ax.text(855., yplt, 'exp(-1)', color='green', size=csz, ha='right')
#
ax.text(0.05,
0.90,
'SDSS QSO stack (z=4)',
color='black',
transform=ax.transAxes,
size=csz,
ha='left')
xputils.set_fontsize(ax, 17.)
# Layout and save
print('Writing {:s}'.format(outfil))
plt.tight_layout(pad=0.2, h_pad=0.0, w_pad=0.4)
plt.subplots_adjust(hspace=0)
pp.savefig(bbox_inches='tight')
plt.close()
# Finish
pp.close()
return all_tau
def on_draw(self, replot=True, in_wrest=None, rescale=True, fig_clear=False):
""" Redraws the figure
"""
#
if replot is True:
if fig_clear:
self.fig.clf()
# Loop on windows
all_idx = self.llist['show_line']
nplt = self.sub_xy[0]*self.sub_xy[1]
if len(all_idx) <= nplt:
self.idx_line = 0
subp = np.arange(nplt) + 1
subp_idx = np.hstack(subp.reshape(self.sub_xy[0],self.sub_xy[1]).T)
#print('idx_l={:d}, nplt={:d}, lall={:d}'.format(self.idx_line,nplt,len(all_idx)))
for jj in range(min(nplt, len(all_idx))):
try:
idx = all_idx[jj+self.idx_line]
except IndexError:
continue # Likely too few lines
#print('jj={:d}, idx={:d}'.format(jj,idx))
# Grab line
wrest = self.llist[self.llist['List']].wrest[idx]
kwrest = wrest.value # For the Dict
# Single window?
if in_wrest is not None:
if np.abs(wrest-in_wrest) > (1e-3*u.AA):
continue
# Abs_Sys: Color the lines
if self.abs_sys is not None:
absline = self.grab_line(wrest)
# Generate plot
self.ax = self.fig.add_subplot(self.sub_xy[0],self.sub_xy[1], subp_idx[jj])
self.ax.clear()
#QtCore.pyqtRemoveInputHook()
#xdb.set_trace()
#QtCore.pyqtRestoreInputHook()
# Zero line
self.ax.plot( [0., 0.], [-1e9, 1e9], ':', color='gray')
# Velocity
wvobs = (1+self.z) * wrest
velo = (self.spec.dispersion/wvobs - 1.)*const.c.to('km/s')
# Plot
self.ax.plot(velo, self.spec.flux, 'k-',drawstyle='steps-mid')
# GID for referencing
self.ax.set_gid(wrest)
# Labels
#if jj >= (self.sub_xy[0]-1)*(self.sub_xy[1]):
if (((jj+1) % self.sub_xy[0]) == 0) or ((jj+1) == len(all_idx)):
self.ax.set_xlabel('Relative Velocity (km/s)')
else:
self.ax.get_xaxis().set_ticks([])
lbl = self.llist[self.llist['List']].name[idx]
# Kinematics
kinl = ''
if absline is not None:
if (absline.analy['flag_kin'] % 2) >= 1:
kinl = kinl + 'L'
if (absline.analy['flag_kin'] % 4) >= 2:
kinl = kinl + 'H'
self.ax.text(0.1, 0.05, lbl+kinl, color='blue', transform=self.ax.transAxes,
size='x-small', ha='left')
# Reset window limits
#QtCore.pyqtRemoveInputHook()
#xdb.set_trace()
#QtCore.pyqtRestoreInputHook()
self.ax.set_xlim(self.psdict['xmnx'])
# Rescale?
if (rescale is True) & (self.norm is False):
gdp = np.where( (velo.value > self.psdict['xmnx'][0]) &
(velo.value < self.psdict['xmnx'][1]))[0]
if len(gdp) > 5:
per = xstats.basic.perc(self.spec.flux[gdp])
self.ax.set_ylim((0., 1.1*per[1]))
else:
self.ax.set_ylim(self.psdict['ymnx'])
else:
self.ax.set_ylim(self.psdict['ymnx'])
# Fonts
xputils.set_fontsize(self.ax,6.)
clr='black'
if absline is not None:
try:
vlim = absline.analy['vlim']
except KeyError:
pass
# Color coding
try: # .clm style
flag = absline.analy['FLAGS'][0]
except KeyError:
flag = None
else:
if flag <= 1: # Standard detection
clr = 'green'
elif flag in [2,3]:
clr = 'blue'
elif flag in [4,5]:
clr = 'purple'
# ABS ID
try: # NG?
flagA = absline.analy['do_analysis']
except KeyError:
flagA = None
else:
if (flagA>0) & (clr == 'black'):
clr = 'green'
try: # Limit?
flagL = absline.analy['flg_limit']
except KeyError:
flagL = None
else:
if flagL == 2:
clr = 'blue'
if flagL == 3:
clr = 'purple'
try: # Blends?
flagE = absline.analy['flg_eye']
except KeyError:
flagE = None
else:
if flagE == 1:
clr = 'orange'
if flagA == 0:
clr = 'red'
pix = np.where( (velo > vlim[0]) & (velo < vlim[1]))[0]
self.ax.plot(velo[pix], self.spec.flux[pix], '-',
drawstyle='steps-mid', color=clr)
# Draw
self.canvas.draw()
def on_draw(self,
replot=True,
in_wrest=None,
rescale=True,
fig_clear=False):
""" Redraws the figure
"""
#
if replot is True:
if fig_clear:
self.fig.clf()
# Loop on windows
all_idx = self.llist['show_line']
nplt = self.sub_xy[0] * self.sub_xy[1]
if len(all_idx) <= nplt:
self.idx_line = 0
subp = np.arange(nplt) + 1
subp_idx = np.hstack(
subp.reshape(self.sub_xy[0], self.sub_xy[1]).T)
#print('idx_l={:d}, nplt={:d}, lall={:d}'.format(self.idx_line,nplt,len(all_idx)))
for jj in range(min(nplt, len(all_idx))):
try:
idx = all_idx[jj + self.idx_line]
except IndexError:
continue # Likely too few lines
#print('jj={:d}, idx={:d}'.format(jj,idx))
# Grab line
wrest = self.llist[self.llist['List']].wrest[idx]
kwrest = wrest.value # For the Dict
# Single window?
if in_wrest is not None:
if np.abs(wrest - in_wrest) > (1e-3 * u.AA):
continue
# Abs_Sys: Color the lines
if self.abs_sys is not None:
absline = self.grab_line(wrest)
# Generate plot
self.ax = self.fig.add_subplot(self.sub_xy[0], self.sub_xy[1],
subp_idx[jj])
self.ax.clear()
#QtCore.pyqtRemoveInputHook()
#xdb.set_trace()
#QtCore.pyqtRestoreInputHook()
# Zero line
self.ax.plot([0., 0.], [-1e9, 1e9], ':', color='gray')
# Velocity
wvobs = (1 + self.z) * wrest
velo = (self.spec.dispersion / wvobs - 1.) * const.c.to('km/s')
# Plot
self.ax.plot(velo, self.spec.flux, 'k-', drawstyle='steps-mid')
# GID for referencing
self.ax.set_gid(wrest)
# Labels
#if jj >= (self.sub_xy[0]-1)*(self.sub_xy[1]):
if (((jj + 1) % self.sub_xy[0]) == 0) or ((jj + 1)
== len(all_idx)):
self.ax.set_xlabel('Relative Velocity (km/s)')
else:
self.ax.get_xaxis().set_ticks([])
lbl = self.llist[self.llist['List']].name[idx]
# Kinematics
kinl = ''
if absline is not None:
if (absline.analy['flag_kin'] % 2) >= 1:
kinl = kinl + 'L'
if (absline.analy['flag_kin'] % 4) >= 2:
kinl = kinl + 'H'
self.ax.text(0.1,
0.05,
lbl + kinl,
color='blue',
transform=self.ax.transAxes,
size='x-small',
ha='left')
# Reset window limits
#QtCore.pyqtRemoveInputHook()
#xdb.set_trace()
#QtCore.pyqtRestoreInputHook()
self.ax.set_xlim(self.psdict['xmnx'])
# Rescale?
if (rescale is True) & (self.norm is False):
gdp = np.where((velo.value > self.psdict['xmnx'][0])
& (velo.value < self.psdict['xmnx'][1]))[0]
if len(gdp) > 5:
per = xstats.basic.perc(self.spec.flux[gdp])
self.ax.set_ylim((0., 1.1 * per[1]))
else:
self.ax.set_ylim(self.psdict['ymnx'])
else:
self.ax.set_ylim(self.psdict['ymnx'])
# Fonts
xputils.set_fontsize(self.ax, 6.)
clr = 'black'
if absline is not None:
try:
vlim = absline.analy['vlim']
except KeyError:
pass
# Color coding
try: # .clm style
flag = absline.analy['FLAGS'][0]
except KeyError:
flag = None
else:
if flag <= 1: # Standard detection
clr = 'green'
elif flag in [2, 3]:
clr = 'blue'
elif flag in [4, 5]:
clr = 'purple'
# ABS ID
try: # NG?
flagA = absline.analy['do_analysis']
except KeyError:
flagA = None
else:
if (flagA > 0) & (clr == 'black'):
clr = 'green'
try: # Limit?
flagL = absline.analy['flg_limit']
except KeyError:
flagL = None
else:
if flagL == 2:
clr = 'blue'
if flagL == 3:
clr = 'purple'
try: # Blends?
flagE = absline.analy['flg_eye']
except KeyError:
flagE = None
else:
if flagE == 1:
clr = 'orange'
if flagA == 0:
clr = 'red'
pix = np.where((velo > vlim[0]) & (velo < vlim[1]))[0]
self.ax.plot(velo[pix],
self.spec.flux[pix],
'-',
drawstyle='steps-mid',
color=clr)
# Draw
self.canvas.draw()
def fig_boss_pca_coeff(outfil=None, boss_fil=None,scl=100.):
# Todo
# Include NHI on the label
# Imports
# Read FITS table
if boss_fil is None:
boss_fil = 'BOSS_DR10Lya_PCA_values_nocut.fits.gz'
hdu = fits.open(boss_fil)
pca_coeff = hdu[1].data
#xdb.set_trace()
# Initialize
#if 'xmnx' not in locals():
# xmnx = (17.0, 20.4)
#ymnx = ((-1.9, 2.3),
# (-1.9, 1.4),
# (-1.1, 1.4),
# (-2.1, 0.9))
ms = 1. # point size
allxi = [0,0,0,1,1,2]
allyi = [1,2,3,2,3,3]
rngi = ([-0.02, 0.3],
[-0.2,0.4],
[-0.2, 0.5],
[-0.2, 0.4])
# Start the plot
if outfil != None:
pp = PdfPages(outfil)
plt.figure(figsize=(5.5, 4))
plt.clf()
gs = gridspec.GridSpec(2, 3)
# Looping
for ii in range(6):
# Axis
ax = plt.subplot(gs[ii])
#ax = plt.subplot(gs[ii//2,ii%2])
'''
ax.xaxis.set_minor_locator(plt.MultipleLocator(0.5))
ax.xaxis.set_major_locator(plt.MultipleLocator(1.))
#ax.yaxis.set_minor_locator(plt.MultipleLocator(0.5))
ax.yaxis.set_major_locator(plt.MultipleLocator(0.5))
ax.set_xlim(xmnx)
ax.set_ylim((-0.5, 0.5))
'''
xi = allxi[ii]
xlbl=str('PCA'+str(xi))
yi = allyi[ii]
ylbl=str('PCA'+str(yi))
# Labels
ax.set_xlabel(xlbl)
ax.set_ylabel(ylbl)
# Data
# Values
#ax.scatter(pca_coeff[xlbl], pca_coeff[ylbl], color='black', s=ms)#, marker=mark)
ax.hist2d(scl*pca_coeff[xlbl], scl*pca_coeff[ylbl], bins=100, norm=LogNorm(),
range=[rngi[xi],rngi[yi]])
# Font size
xputils.set_fontsize(ax,8.)
# Layout and save
plt.tight_layout(pad=0.2,h_pad=0.1,w_pad=0.25)
if outfil != None:
pp.savefig(bbox_inches='tight')
pp.close()
else:
plt.show()
def obs_sawtooth(outfil='Figures/obs_sawtooth.pdf', all_tau=None, scl=1.):
""" Sawtooth opacity
"""
# SDSS
hdu = fits.open('/Users/xavier/paper/LLS/taueff/Analysis/stack_DR7_z3.92_z4.02.fits')
sdss_fx = hdu[0].data
sdss_wave = hdu[2].data
# Telfer
telfer = pyicq.get_telfer_spec()
i1450 = np.argmin(np.abs(telfer.wavelength.value - 1450.))
nrm = np.median(telfer.flux[i1450-5:i1450+5])
telfer.flux = telfer.flux / nrm
trebin = telfer.rebin(sdss_wave*u.AA)
# Load fN
fN_model = FNModel.default_model()
fN_model.zmnx = (2.,4.1) # extrapolate a bit
# teff
zem = 4.
wave = np.arange(4500., 6200., 10)
# Calculate
if all_tau is None:
all_tau = np.zeros_like(wave)
for qq,iwave in enumerate(wave):
all_tau[qq] = lyman_ew(iwave, zem, fN_model)
# Flux attenuation
trans = np.exp(-all_tau)
ftrans = interp1d(wave, trans, fill_value=1.,
bounds_error=False)
# Start the plot
xmnx = (4500, 6200)
pp = PdfPages(outfil)
fig = plt.figure(figsize=(8.0, 5.0))
plt.clf()
gs = gridspec.GridSpec(1,1)
# Lya line
ax = plt.subplot(gs[0])
#ax.xaxis.set_minor_locator(plt.MultipleLocator(0.5))
#ax.xaxis.set_major_locator(plt.MultipleLocator(20.))
#ax.yaxis.set_minor_locator(plt.MultipleLocator(0.1))
#ax.yaxis.set_major_locator(plt.MultipleLocator(0.2))
ax.set_xlim(xmnx)
ax.set_ylim(0., 1.5)
ax.set_ylabel('Relative Flux')
ax.set_xlabel('Observed wavelength')
lw = 2.
# Data
ax.plot(sdss_wave*(1+zem), sdss_fx, 'k', linewidth=lw, label='SDSS QSOs (z=4)')
# Model
model = trebin.flux * ftrans(sdss_wave*(1+zem)) * scl
ax.plot(sdss_wave*(1+zem), model, 'r', linewidth=lw, label='IGM+Telfer model')
# Label
csz = 17
#ax.text(0.10, 0.10, 'SDSS quasar stack at z=4', color='black',
# transform=ax.transAxes, size=csz, ha='left')
# Legend
legend = plt.legend(loc='upper left', scatterpoints=1, borderpad=0.3,
handletextpad=0.3, fontsize='large', numpoints=1)
xputils.set_fontsize(ax, 17.)
# Layout and save
print('Writing {:s}'.format(outfil))
plt.tight_layout(pad=0.2,h_pad=0.0,w_pad=0.4)
plt.subplots_adjust(hspace=0)
pp.savefig(bbox_inches='tight')
plt.close()
# Finish
pp.close()
return all_tau
def fig_z_vs_dNHI(cos_halos=None, outfil='fig_z_vs_dNHI.pdf'):
""" Shows change in NHI vs. z
"""
# Read LLS
jfile = '../Analysis/COS_Halos_LLS.json'
with open(jfile) as json_file:
fdict = json.load(json_file)
keys = fdict.keys()
nsys = len(keys)
zabs = np.array([fdict[key]['z'] for key in keys])
srt = np.argsort(zabs)
# Read COS-Halos
if cos_halos is None:
cos_halos = load_ch(load_mtl=False)
orig_NHI = cos_halos.NHI
orig_fNHI = cos_halos.flag_NHI
werk_NHI = cos_halos.werk14_NHI
# Init
NHI_mnx = (14.8, 19.1)
# Start the plot
if outfil is not None:
pp = PdfPages(outfil)
plt.figure(figsize=(5, 5))
plt.clf()
gs = gridspec.GridSpec(1, 1)
ax = plt.subplot(gs[0])
# Axes
#wvmnx = awvmnx[iuvq['instr']]
#ax.xaxis.set_minor_locator(plt.MultipleLocator(500.))
#ax.yaxis.set_major_locator(plt.MultipleLocator(1.))
ax.minorticks_on()
ax.set_xlim(NHI_mnx)
ax.set_ylim(0, nsys+1)
# Labels
lsz = 16.
ax.set_xlabel(r'$\log_{10} \, N_{\rm HI}$', size=lsz)
ax.set_ylabel(r'System (Ordered by $z$)', size=lsz)
new_lbl = False
# Loop on Systems
for jj, isrt in enumerate(srt):
key = keys[isrt]
# Original
mt = np.where((cos_halos.field == fdict[key]['quasar']) &
(cos_halos.gal_id == fdict[key]['galaxy']))[0]
if len(mt) != 1:
raise ValueError("Not a proper match")
# Plot original
if orig_fNHI[mt] == 1:
warnings.warn("Assuming the value for {:s}_{:s} is a lower limit".format(
fdict[key]['quasar'],fdict[key]['galaxy']))
#ax.quiver(orig_NHI[mt], fdict[key]['fit_NHI'][0], 1, 0,
# units='x', width=0.03, headwidth=2., headlength=5.)
elif orig_fNHI[mt] == 2:
pass
#ax.quiver(orig_NHI[mt], fdict[key]['fit_NHI'][0], 1, 0,
# units='x', width=0.03, headwidth=2., headlength=5.)
elif orig_fNHI[mt] == 3:
xdb.set_trace()
raise ValueError("Very Unlikely")
else:
xdb.set_trace()
raise ValueError("Nope")
# Tumlinson NHI
if jj == 0:
lbl = 'Tumlinson+13'
else:
lbl = None
ax.scatter([orig_NHI[mt]], [jj+1], marker='o', edgecolor='gray',
facecolor='none', label=lbl)
# Werk+14 NHI
if jj == 0:
lbl2 = 'Werk+14'
else:
lbl2 = None
ax.scatter([werk_NHI[mt]], [jj+1], marker='s', edgecolor='red',
facecolor='none', label=lbl2)
# New value
if fdict[key]['flag_NHI'] == 1:
xerr=[[fdict[key]['fit_NHI'][0]-fdict[key]['fit_NHI'][1]],
[fdict[key]['fit_NHI'][2]-fdict[key]['fit_NHI'][0]]]
if new_lbl is False:
lbl = 'New'
new_lbl = True
else:
lbl = None
ax.errorbar([fdict[key]['fit_NHI'][0]], [jj+1], xerr=xerr,
capthick=2, fmt='o', color='blue', label=lbl)
elif fdict[key]['flag_NHI'] == 2: # Lower limit
ax.plot([fdict[key]['fit_NHI'][1]], [jj+1], '>', color='blue')
elif fdict[key]['flag_NHI'] == 3: # Upper limit
ax.plot([fdict[key]['fit_NHI'][2]], [jj+1], '<', color='blue')
legend = plt.legend(loc='upper right', scatterpoints=1, borderpad=0.3,
handletextpad=0.3, fontsize='small', numpoints=1)
# End
xputils.set_fontsize(ax,15.)
print('Writing {:s}'.format(outfil))
plt.tight_layout(pad=0.2,h_pad=0.,w_pad=0.1)
pp.savefig()
pp.close()
plt.close()
def fig_sngl_cldy_model(sys, dpath=os.getenv('COSHALOS_DATA')+'/Cloudy/', ax=None, outfil=None,
lsz=15., show_sys=False):
""" Compare columns between model and data
"""
# Read
fh5 = h5py.File(dpath+sys+'_emcee.hd5', 'r')
ions = fh5['inputs']['ions'].value
data = fh5['inputs']['data'].value
fit = fh5['outputs']['best_fit'].value
fh5.close()
# IP values
IPs = np.zeros(len(ions))
for ii,ion in enumerate(ions):
Zion = lai.name_ion(ion)
elm = ELEMENTS[Zion[0]]
IPs[ii] = elm.ionenergy[Zion[1]-1]
#xdb.set_trace()
resid = data[:,1].astype(float) - fit
# Start the plot
if outfil is not None:
pp = PdfPages(outfil)
plt.figure(figsize=(7, 7))
plt.clf()
gs = gridspec.GridSpec(1, 1)
ax = plt.subplot(gs[0])
# Axes
#wvmnx = awvmnx[iuvq['instr']]
#ax.yaxis.set_major_locator(plt.MultipleLocator(1.))
ax.minorticks_on()
xlim = (5., np.max(IPs)+4)
ax.set_xlim(xlim)
ylim = (-1., 1.)
ax.set_ylim(ylim)
# Labels
ax.set_xlabel('IP (eV)', size=lsz)
ax.set_ylabel(r'$\Delta \, \log \, N$', size=lsz)
ax.xaxis.set_major_locator(plt.MultipleLocator(10.))
# Values
gdv = np.where(data[:,3].astype(int) == 0)[0]
if len(gdv) > 0:
ax.errorbar(IPs[gdv],resid[gdv], xerr=0, linestyle='None',
yerr=data[:,2].astype(float)[gdv], color='blue', marker='o')
# Limits
limsz = 50.
ulim = np.where(data[:,3].astype(int) == -1)[0]
ax.scatter(IPs[ulim],resid[ulim], color='red', marker='v', s=limsz)
llim = np.where(data[:,3].astype(int) == -2)[0]
ax.scatter(IPs[llim],resid[llim], color='green', marker='^', s=limsz)
# Label
for kk,ion in enumerate(ions):
if (resid[kk] < ylim[1]) & (resid[kk] > ylim[0]):
ax.text(IPs[kk]+1, resid[kk], ion, color='k', size=lsz) # Only if on page
if show_sys:
ax.text(0.04, 0.04, sys, transform=ax.transAxes, size=lsz-1, ha='left')
#bbox={'facecolor':'white'})
#legend = plt.legend(loc='upper right', scatterpoints=1, borderpad=0.3,
# handletextpad=0.3, fontsize='small', numpoints=1)
ax.plot(xlim, [0.,0.], 'g:')
# End
xputils.set_fontsize(ax,lsz)
if outfil is not None:
print('Writing {:s}'.format(outfil))
plt.tight_layout(pad=0.2,h_pad=0.,w_pad=0.1)
pp.savefig()
pp.close()
plt.close()
def on_draw(self, replot=True, in_wrest=None, rescale=True, fig_clear=False):
""" Redraws the figure
"""
#
if replot is True:
if fig_clear:
self.fig.clf()
# Title
self.fig.suptitle('z={:g}'.format(self.z),fontsize=7.)
# Components
#components = self.parent.comps_widg.all_comp
components = self.parent.comps_widg.selected_components()
iwrest = np.array([comp.init_wrest.value for comp in components])*u.AA
# Loop on windows
all_idx = self.llist['show_line']
#QtCore.pyqtRemoveInputHook()
#xdb.set_trace()
#QtCore.pyqtRestoreInputHook()
# Labels
if self.flag_idlbl:
line_wvobs = []
line_lbl = []
for comp in components:
for line in comp.lines:
line_wvobs.append(line.wrest.value*(line.attrib['z']+1))
line_lbl.append(line.trans+',{:.4f}'.format(line.attrib['z']))
line_wvobs = np.array(line_wvobs)*u.AA
line_lbl = np.array(line_lbl)
# Subplots
nplt = self.sub_xy[0]*self.sub_xy[1]
if len(all_idx) <= nplt:
self.idx_line = 0
subp = np.arange(nplt) + 1
subp_idx = np.hstack(subp.reshape(self.sub_xy[0],self.sub_xy[1]).T)
#print('idx_l={:d}, nplt={:d}, lall={:d}'.format(self.idx_line,nplt,len(all_idx)))
for jj in range(min(nplt, len(all_idx))):
try:
idx = all_idx[jj+self.idx_line]
except IndexError:
continue # Likely too few lines
#print('jj={:d}, idx={:d}'.format(jj,idx))
# Grab line
wrest = self.llist[self.llist['List']].wrest[idx]
kwrest = wrest.value # For the Dict
# Single window?
#if in_wrest is not None:
# if np.abs(wrest-in_wrest) > (1e-3*u.AA):
# continue
# Generate plot
self.ax = self.fig.add_subplot(self.sub_xy[0],self.sub_xy[1], subp_idx[jj])
self.ax.clear()
# GID for referencing
self.ax.set_gid(wrest)
# Zero line
self.ax.plot( [0., 0.], [-1e9, 1e9], ':', color='gray')
# Velocity
wvobs = (1+self.z) * wrest
wvmnx = wvobs*(1 + np.array(self.psdict['xmnx'])/3e5)
velo = (self.spec.dispersion/wvobs - 1.)*const.c.to('km/s')
# Plot
self.ax.plot(velo, self.spec.flux, 'k-',drawstyle='steps-mid')
# Model
self.ax.plot(velo, self.model.flux, 'b-')
# Labels
if (((jj+1) % self.sub_xy[0]) == 0) or ((jj+1) == len(all_idx)):
self.ax.set_xlabel('Relative Velocity (km/s)')
else:
self.ax.get_xaxis().set_ticks([])
lbl = self.llist[self.llist['List']].name[idx]
self.ax.text(0.05, 0.90, lbl, color='blue', transform=self.ax.transAxes,
size='x-small', ha='left')
if self.flag_idlbl:
# Any lines inside?
mtw = np.where((line_wvobs > wvmnx[0]) & (line_wvobs<wvmnx[1]))[0]
for imt in mtw:
v = 3e5*(line_wvobs[imt]/wvobs - 1)
self.ax.text(v, 0.90, line_lbl[imt], color='green',
size='x-small', rotation=90.)
# Analysis regions
if np.sum(self.spec.mask) > 0.:
gdp = self.spec.mask==1
if len(gdp) > 0:
self.ax.scatter(velo[gdp],self.spec.flux[gdp],
marker='o',color='gray',s=10.)
# Reset window limits
self.ax.set_ylim(self.psdict['ymnx'])
self.ax.set_xlim(self.psdict['xmnx'])
# Add line?
if self.wrest == wrest:
self.ax.plot([self.vtmp]*2,self.psdict['ymnx'], '--',
color='red')
# Components
mtc = np.where(wrest == iwrest)[0]
if len(mtc) > 0:
#QtCore.pyqtRemoveInputHook()
#xdb.set_trace()
#QtCore.pyqtRestoreInputHook()
for mt in mtc:
comp = components[mt]
#QtCore.pyqtRemoveInputHook()
#xdb.set_trace()
#QtCore.pyqtRestoreInputHook()
dvz = const.c.to('km/s')*(self.z-comp.zcomp)/(1+self.z)
if dvz.value < np.max(np.abs(self.psdict['xmnx'])):
if comp is self.parent.fiddle_widg.component:
lw = 1.5
else:
lw = 1.
# Plot
for vlim in comp.vlim:
self.ax.plot([vlim.value-dvz.value]*2,self.psdict['ymnx'],
'--', color='gray',linewidth=lw)
self.ax.plot([-1.*dvz.value]*2,[1.0,1.05],
'-', color='gray',linewidth=lw)
# Fonts
xputils.set_fontsize(self.ax,6.)
# Draw
self.canvas.draw()
def qso_template(outfil='Figures/qso_template.pdf'):
""" van den berk
"""
pyigm_path = imp.find_module('pyigm')[1]
# Load
telfer = pyicq.get_telfer_spec()
clight = const.c.cgs
# Beta spliced to vanden Berk template with host galaxy removed
van_file = pyigm_path + '/data/quasar/VanDmeetBeta_fullResolution.txt'
van_tbl = Table.read(van_file, format='ascii')
isort = np.argsort(van_tbl['nu'])
nu_van = van_tbl['nu'][isort]
fnu_van = van_tbl['f_nu'][isort]
lam_van = (clight / (nu_van * u.Hz)).to('AA')
flam_van = fnu_van * clight / lam_van**2
nrm_pix = np.abs(lam_van - 1450 * u.AA) < 10 * u.AA
nrm_van = np.median(flam_van[nrm_pix])
flam_van = flam_van / nrm_van
# Start the plot
xmnx = (1170., 2300)
pp = PdfPages(outfil)
fig = plt.figure(figsize=(8.0, 5.0))
plt.clf()
gs = gridspec.GridSpec(1, 1)
# Lya line
ax = plt.subplot(gs[0])
#ax.xaxis.set_minor_locator(plt.MultipleLocator(0.5))
#ax.xaxis.set_major_locator(plt.MultipleLocator(20.))
#ax.yaxis.set_minor_locator(plt.MultipleLocator(0.1))
#ax.yaxis.set_major_locator(plt.MultipleLocator(0.2))
ax.set_xlim(xmnx)
#ax.set_ylim(ymnx)
ax.set_ylabel('Relative Flux')
ax.set_xlabel('Rest Wavelength (Angstroms)')
lw = 1.
ax.plot(telfer.wavelength,
telfer.flux,
'k',
linewidth=lw,
label='Telfer (z~1)')
ax.plot(lam_van, flam_van, 'b', linewidth=lw, label='SDSS (z~2)')
# Legend
legend = plt.legend(loc='upper right',
scatterpoints=1,
borderpad=0.3,
handletextpad=0.3,
fontsize='large',
numpoints=1)
# Layout and save
xputils.set_fontsize(ax, 17.)
print('Writing {:s}'.format(outfil))
plt.tight_layout(pad=0.2, h_pad=0.0, w_pad=0.4)
plt.subplots_adjust(hspace=0)
pp.savefig(bbox_inches='tight')
plt.close()
# Finish
pp.close()
def fig_full_nH_PDF(cos_halos=None, outfil = 'fig_full_nH_PDF.pdf'):
""" Shows the combined PDF
"""
# Read COS-Halos
if cos_halos is None:
cos_halos = load_ch()
# Init
nH_mnx = (-5., 1)
# Start the plot
pp = PdfPages(outfil)
plt.figure(figsize=(5, 5))
plt.clf()
ax = plt.gca()
# Axes
#wvmnx = awvmnx[iuvq['instr']]
#ax.xaxis.set_minor_locator(plt.MultipleLocator(500.))
#ax.yaxis.set_major_locator(plt.MultipleLocator(1.))
#plt.ylim(0, nsys+1)
ax.set_xlim(nH_mnx)
sumPDF = None
# Loop on the systems
nsys = 0
for cgm_abs in cos_halos.cgm_abs:
# Cut on quality
qual = chmtl.mtl_quality(cgm_abs)
if qual < 1:
continue
# Sum the PDF
nsys += 1
if sumPDF is None:
sumPDF = cgm_abs.igm_sys.density
else:
sumPDF = sumPDF + cgm_abs.igm_sys.density
print("We are using {:d} systems in COS-Halos".format(nsys))
sumPDF.normalize()
# Giddy up
lsz = 19.
ax.bar(sumPDF.nH-sumPDF.dnH/2., sumPDF.pdf_nH, width=sumPDF.dnH, color='green')
ax.set_xlabel(r"$\log \, n_{\rm H}$", size=lsz)
ax.set_ylabel("Normalized PDF", size=lsz)
# Label
csz = 18.
lbl = 'COS-Halos'
ax.text(0.05, 0.87, lbl, transform=ax.transAxes, color='black', size=csz, ha='left')
lbl2 = '({:d} systems)'.format(nsys)
ax.text(0.05, 0.75, lbl2, transform=ax.transAxes, color='black', size=csz, ha='left')
# End
xputils.set_fontsize(ax, 16.)
print('Writing {:s}'.format(outfil))
plt.tight_layout(pad=0.2,h_pad=0.,w_pad=0.1)
pp.savefig()
pp.close()
plt.close()
def xq100_plls_ex(outfil='fig_xq100_plls_ex.pdf'):
# Load spectrum
spec_fil = os.getenv('DROPBOX_DIR') + '/XQ-100/data/J0030-5159_uvb.fits'
spec = load_spectrum(spec_fil)
# Generate model
model_file = os.getenv(
'DROPBOX_DIR') + '/XQ-100/LLS/convg_J0030-5159_llsfit.json'
with open(model_file) as data_file:
lls_dict = json.load(data_file)
# Continuum
basec = Quantity(lls_dict['conti'])
telfer_spec = XSpectrum1D.from_tuple((spec.dispersion.value, basec.value))
# Start the plot
if outfil is not None:
pp = PdfPages(outfil)
plt.figure(figsize=(8, 4))
plt.clf()
gs = gridspec.GridSpec(1, 1)
fsz = 17.
# Read and plot full spectrum
ax_full = plt.subplot(gs[0])
# Limits
wvmnx = [3600., 5000.]
gdpix = np.where(spec.dispersion < wvmnx[1] * u.AA)[0]
perc = xsb.perc(spec.flux[gdpix])
ax_full.set_xlim(wvmnx)
#ax_full.set_ylim(-0.05*perc[1], 1.1*perc[1])
ax_full.set_ylim(-1e-18, 4e-17)
# Plot
ax_full.plot(spec.dispersion, spec.flux, color='black', lw=1.0)
ax_full.plot(wvmnx, [0., 0.], '--', color='green')
# Label
ax_full.set_xlabel('Wavelength')
ax_full.set_ylabel('Relative Flux')
ax_full.text(0.05,
0.9,
'XQ100 J0030-5159',
transform=ax_full.transAxes,
color='black',
size='x-large',
ha='left',
va='center',
bbox={'facecolor': 'white'})
all_ills = []
all_lls = []
all_zlls = []
for key in lls_dict['LLS'].keys():
new_sys = LLSSystem(NHI=lls_dict['LLS'][key]['NHI'])
new_sys.zabs = lls_dict['LLS'][key]['z']
new_sys.fill_lls_lines(bval=lls_dict['LLS'][key]['bval'] * u.km / u.s)
#
all_ills.append(new_sys)
all_lls.append(new_sys)
all_zlls.append(new_sys.zabs)
# Model
norm_flux = lls_model(spec.dispersion, all_ills, smooth=lls_dict['smooth'])
continuum = telfer_spec.flux * lls_dict['conti_model']['Norm'] * (
spec.dispersion.value /
lls_dict['conti_model']['piv_wv'])**lls_dict['conti_model']['tilt']
# Model
ax_full.plot(spec.dispersion, continuum * norm_flux)
# Font size
xputils.set_fontsize(ax_full, fsz)
# Finish page
plt.tight_layout(pad=0.2, h_pad=0.3, w_pad=0.0)
pp.savefig()
plt.close()
print('Wrote: {:s}'.format(outfil))
# Finish
pp.close()
def fig_x_vs_ZH(x, xmnx, xlbl, cos_halos=None, msk=None,
outfil = None, lsz=16., ax=None, log=None):
""" Plot ZH vs. a input quantity
"""
# Read COS-Halos
if cos_halos is None:
cos_halos = load_ch()
# Init
ZH_mnx = (-2., 1)
# Start the plot
if ax is None:
pp = PdfPages(outfil)
plt.figure(figsize=(5, 5))
plt.clf()
ax = plt.gca()
# Axes
#wvmnx = awvmnx[iuvq['instr']]
#ax.xaxis.set_minor_locator(plt.MultipleLocator(500.))
#ax.yaxis.set_major_locator(plt.MultipleLocator(1.))
#plt.ylim(0, nsys+1)
ax.set_xlim(xmnx)
ax.set_ylim(ZH_mnx)
# Loop on the systems
for ii, cgm_abs in enumerate(cos_halos.cgm_abs):
if msk is None:
# Cut on quality
try:
flgs = cgm_abs.igm_sys.metallicity.inputs['data'][:, 3]
except IndexError:
print('No constraint for {:s}'.format(cgm_abs.name))
print('Skipping')
continue
indices = np.where(flgs != "-1")[0]
if len(indices) == 0:
print('No constraint for {:s}'.format(cgm_abs.name))
print('Skipping')
continue
else:
if msk[ii] is False:
continue
#
ZH = cgm_abs.igm_sys.metallicity.medianZH
sig = cgm_abs.igm_sys.metallicity.confidence_limits(0.68)
yerr = [[ZH-sig[0]], [sig[1]-ZH]]
if np.sum(np.array(yerr)) > 1.:
pcolor='lightgray'
eclr = 'none'
else:
pcolor='blue'
fclr ='blue'
eclr = 'black'
if x == 'NHI':
xval = cgm_abs.igm_sys.NHIPDF.median
elif x == 'nH':
xval = cgm_abs.igm_sys.density.median
else:
xval = getattr(cgm_abs, x)
if isinstance(xval, Quantity):
xval = xval.value
if log:
xval = np.log10(xval)
#if (x == 'NHI') and (xval < 16) and (ZH < -1):
# xdb.set_trace()
ax.errorbar([xval], [ZH], yerr=yerr, capthick=2, fmt='o', color=pcolor)
#edgecolor=eclr)
# Labels
ax.set_xlabel(xlbl)
ax.set_ylabel("[Z/H]")
ax.plot(xmnx, [0., 0.], '--', color='green')
# End
xputils.set_fontsize(ax, lsz)
if outfil is not None:
print('Writing {:s}'.format(outfil))
plt.tight_layout(pad=0.2,h_pad=0.,w_pad=0.1)
pp.savefig()
pp.close()
plt.close()
def fig_boss_x_vs_pca(outfil=None, boss_fil=None, flg=0):
'''
flg = 0: Redshift
flg = 1: imag
'''
# Todo
# Include NHI on the label
# Imports
# Read PCA FITS table
if boss_fil is None:
boss_fil = 'BOSS_DR10Lya_PCA_values_nocut.fits.gz'
hdu = fits.open(boss_fil)
pca_coeff = hdu[1].data
# Read BOSS catalog table
boss_cat_fil = os.environ.get('BOSSPATH')+'/DR10/BOSSLyaDR10_cat_v2.1.fits.gz'
bcat_hdu = fits.open(boss_cat_fil)
t_boss = bcat_hdu[1].data
#xdb.set_trace()
if flg == 0:
xparm = t_boss['z_pipe']
xmnx = [2., 4.]
xlbl=str(r'$z_{\rm QSO}$')
elif flg == 1:
tmp = t_boss['PSFMAG']
xparm = tmp[:,3] # i-band mag
xlbl=str('i mag')
xmnx = [17.,22.5]
else:
raise ValueError('fig_boss_x_vs_pca: flg={:d} not allowed'.format(flg))
# Initialize
#if 'xmnx' not in locals():
# xmnx = (17.0, 20.4)
ymnx = ((-0.02, 0.3),
(-0.2,0.4),
(-0.2, 0.5),
(-0.2, 0.4))
ms = 1. # point size
scl = 100.
# Start the plot
if outfil != None:
pp = PdfPages(outfil)
plt.figure(figsize=(4, 4))
plt.clf()
gs = gridspec.GridSpec(2, 2)
# Looping
for ii in range(4):
# Axis
ax = plt.subplot(gs[ii])
#ax = plt.subplot(gs[ii//2,ii%2])
ylbl=str('PCA'+str(ii))
# Labels
ax.set_xlabel(xlbl)
ax.set_ylabel(ylbl)
# Data
# Values
#xdb.set_trace()
ax.hist2d(xparm, scl*pca_coeff[ylbl], bins=100, norm=LogNorm(),
range=[xmnx, [ymnx[ii][0], ymnx[ii][1]]])
# Font size
xputils.set_fontsize(ax,8.)
# Layout and save
plt.tight_layout(pad=0.2,h_pad=0.1,w_pad=0.25)
if outfil != None:
pp.savefig(bbox_inches='tight')
pp.close()
else:
plt.show()
def fig_NH_hist(cos_halos=None, outfil = 'fig_NH_hist.pdf', lsz=17.):
""" Shows a histogram of NH values
"""
# Read COS-Halos
if cos_halos is None:
cos_halos = load_ch()
# Read the grid
model = os.getenv('DROPBOX_DIR')+'/cosout/grid_minextended.pkl'
fil=open(model)
modl=pickle.load(fil)
fil.close()
# Init
NH_mnx = (18., 23)
ymnx = (0., 9)
binsz = 0.25
nbins = (NH_mnx[1]-NH_mnx[0])/binsz
# Start the plot
pp = PdfPages(outfil)
plt.figure(figsize=(5, 5))
plt.clf()
ax = plt.gca()
# Axes
#wvmnx = awvmnx[iuvq['instr']]
#ax.xaxis.set_minor_locator(plt.MultipleLocator(500.))
#ax.yaxis.set_major_locator(plt.MultipleLocator(1.))
#plt.ylim(0, nsys+1)
ax.set_xlim(NH_mnx)
ax.set_ylim(ymnx)
sumPDF = None
# Loop on the systems
nsys = 0
NH_val = []
for cgm_abs in cos_halos.cgm_abs:
# Cut on quality
try:
flgs = cgm_abs.igm_sys.metallicity.inputs['data'][:, 3]
except IndexError:
print('No constraint for {:s}'.format(cgm_abs.name))
print('Skipping')
continue
indices = np.where(flgs != "-1")[0]
if len(indices) == 0:
print('No constraint for {:s}'.format(cgm_abs.name))
print('Skipping')
continue
# Find best indices
mtl = cgm_abs.igm_sys.metallicity.medianZH
imet = np.argmin(np.abs(modl[1]['met']-mtl))
dens = cgm_abs.igm_sys.density.mediannH
idens = np.argmin(np.abs(modl[1]['dens']-dens))
ired = np.argmin(np.abs(modl[1]['red']-cgm_abs.zabs))
icol = np.argmin(np.abs(modl[1]['col']-cgm_abs.igm_sys.NHI))
# xHI, NH
xHI = modl[2]['HI'][icol][idens][imet][ired]
NH = cgm_abs.igm_sys.NHI - xHI
NH_val.append(NH)
print("We are using {:d} systems in COS-Halos".format(nsys))
# Histogram
lsz = 19.
hist, edges = np.histogram(np.array(NH_val), range=NH_mnx, bins=nbins)
ax.bar(edges[:-1], hist, width=binsz, color='green')
ax.set_xlabel(r'$\log \, N_{\rm H}$')
ax.set_ylabel(r"$N_{\rm sys}$")
# Label
prev_medNH = 19.1 # Eyeball
ax.plot([prev_medNH]*2, ymnx, '--', color='red')
'''
csz = 18.
lbl = 'COS-Halos'
ax.text(0.05, 0.87, lbl, transform=ax.transAxes, color='black', size=csz, ha='left')
lbl2 = '({:d} systems)'.format(nsys)
ax.text(0.05, 0.75, lbl2, transform=ax.transAxes, color='black', size=csz, ha='left')
'''
# End
xputils.set_fontsize(ax, lsz)
print('Writing {:s}'.format(outfil))
plt.tight_layout(pad=0.2,h_pad=0.,w_pad=0.1)
pp.savefig()
pp.close()
plt.close()
def on_draw(self, replot=True, in_wrest=None, rescale=True, fig_clear=False):
""" Redraws the figure
"""
#
if replot is True:
if fig_clear:
self.fig.clf()
# Title
self.fig.suptitle('z={:.5f}'.format(self.z),fontsize='large')
# Components
components = self.parent.comps_widg.all_comp
iwrest = np.array([comp.init_wrest.value for comp in components])*u.AA
# Loop on windows
all_idx = self.llist['show_line']
#QtCore.pyqtRemoveInputHook()
#xdb.set_trace()
#QtCore.pyqtRestoreInputHook()
# Labels
if self.flag_idlbl:
line_wvobs = []
line_lbl = []
for comp in components:
if comp.attrib['Quality'] == 'None':
la = ''
else:
la = comp.attrib['Quality']
for line in comp.lines:
line_wvobs.append(line.wrest.value*(line.attrib['z']+1))
line_lbl.append(line.trans+',{:.3f}{:s}'.format(line.attrib['z'],la))
line_wvobs = np.array(line_wvobs)*u.AA
line_lbl = np.array(line_lbl)
# Subplots
nplt = self.sub_xy[0]*self.sub_xy[1]
if len(all_idx) <= nplt:
self.idx_line = 0
subp = np.arange(nplt) + 1
subp_idx = np.hstack(subp.reshape(self.sub_xy[0],self.sub_xy[1]).T)
#print('idx_l={:d}, nplt={:d}, lall={:d}'.format(self.idx_line,nplt,len(all_idx)))
#try different color per ion species
color_model = '#999966'
colors = ['#0066FF','#339933','#CC3300','#660066','#FF9900','#B20047']
color_ind = 0
#loop over individual velplot axes
for jj in range(min(nplt, len(all_idx))):
try:
idx = all_idx[jj+self.idx_line]
except IndexError:
continue # Likely too few lines
#print('jj={:d}, idx={:d}'.format(jj,idx))
# Grab line
wrest = self.llist[self.llist['List']].wrest[idx]
kwrest = wrest.value # For the Dict
#define colors for visually grouping same species
if jj > 0:
name_aux = self.llist[self.llist['List']].name[idx].split(' ')[0]
name_aux2 = self.llist[self.llist['List']].name[idx-1].split(' ')[0]
if name_aux != name_aux2:
color_ind += 1
color = colors[color_ind % len(colors)]
# Single window?
#if in_wrest is not None:
# if np.abs(wrest-in_wrest) > (1e-3*u.AA):
# continue
# Generate plot
self.ax = self.fig.add_subplot(self.sub_xy[0],self.sub_xy[1], subp_idx[jj])
self.ax.clear()
# GID for referencing
self.ax.set_gid(wrest)
# Zero velocity line
self.ax.plot( [0., 0.], [-1e9, 1e9], ':', color='gray')
# Velocity
wvobs = (1+self.z) * wrest
wvmnx = wvobs*(1 + np.array(self.psdict['xmnx'])/3e5)
velo = (self.spec.dispersion/wvobs - 1.)*const.c.to('km/s')
# Plot
self.ax.plot(velo, self.spec.flux, '-',color=color,drawstyle='steps-mid',lw=0.5)
# Model
self.ax.plot(velo, self.model.flux, '-',color=color_model,lw=0.5)
#Error & residuals
if self.plot_residuals:
self.ax.plot(velo, self.residual_limit, 'k-',drawstyle='steps-mid',lw=0.5)
self.ax.plot(velo, -self.residual_limit, 'k-',drawstyle='steps-mid',lw=0.5)
self.ax.plot(velo, self.residual, '.',color='grey',ms=2)
#import pdb
#pdb.set_trace()
# Labels
if (((jj+1) % self.sub_xy[0]) == 0) or ((jj+1) == len(all_idx)):
self.ax.set_xlabel('Relative Velocity (km/s)')
else:
self.ax.get_xaxis().set_ticks([])
lbl = self.llist[self.llist['List']].name[idx]
self.ax.text(0.01, 0.15, lbl, color=color, transform=self.ax.transAxes,
size='x-small', ha='left',va='center',backgroundcolor='w',bbox={'pad':0,'edgecolor':'none'})
if self.flag_idlbl:
# Any lines inside?
mtw = np.where((line_wvobs > wvmnx[0]) & (line_wvobs<wvmnx[1]))[0]
for imt in mtw:
v = 3e5*(line_wvobs[imt]/wvobs - 1)
self.ax.text(v, 0.5, line_lbl[imt], color=color_model,backgroundcolor='w',
bbox={'pad':0,'edgecolor':'none'}, size='xx-small', rotation=90.,ha='center',va='center')
# Analysis regions
if np.sum(self.spec.mask) > 0.:
gdp = self.spec.mask==1
if len(gdp) > 0:
self.ax.scatter(velo[gdp],self.spec.flux[gdp],
marker='o',color=color,s=3.,alpha=0.5)
# Reset window limits
self.ax.set_ylim(self.psdict['ymnx'])
self.ax.set_xlim(self.psdict['xmnx'])
# Add line?
if self.wrest == wrest:
self.ax.plot([self.vtmp]*2,self.psdict['ymnx'], '--',
color='red')
# Components
mtc = np.where(wrest == iwrest)[0]
if len(mtc) > 0:
#QtCore.pyqtRemoveInputHook()
#xdb.set_trace()
#QtCore.pyqtRestoreInputHook()
for mt in mtc:
comp = components[mt]
#QtCore.pyqtRemoveInputHook()
#xdb.set_trace()
#QtCore.pyqtRestoreInputHook()
dvz = const.c.to('km/s')*(self.z-comp.zcomp)/(1+self.z)
if dvz.value < np.max(np.abs(self.psdict['xmnx'])):
if comp is self.parent.fiddle_widg.component:
lw = 1.5
else:
lw = 1.
# Plot
for vlim in comp.vlim:
self.ax.plot([vlim.value-dvz.value]*2,self.psdict['ymnx'],
'--', color='r',linewidth=lw)
self.ax.plot([-1.*dvz.value]*2,[1.0,1.05],
'-', color='grey',linewidth=lw)
# Fonts
xputils.set_fontsize(self.ax,6.)
# Draw
self.canvas.draw()
def fig_mtlPDF_cuts(cos_halos=None, outfil = 'fig_mtlPDF_cuts.pdf',
qcut=1):
""" Shows the metallicity PDF for various cuts
Avoids 0 detection systems
"""
# Read COS-Halos
if cos_halos is None:
cos_halos = load_ch()
# Quality cut
msk = [False]*len(cos_halos.cgm_abs)
for ii,cgm_abs in enumerate(cos_halos.cgm_abs):
# Cut on quality
if chmtl.mtl_quality(cgm_abs) <= qcut:
print('No constraint for {:s}'.format(cgm_abs.name))
print('Skipping')
continue
msk[ii] = True
mska = np.array(msk)
# Init
ZH_mnx = (-2., 1)
# Start the plot
pp = PdfPages(outfil)
plt.figure(figsize=(5, 5))
plt.clf()
gs = gridspec.GridSpec(2, 2)
for qq in range(4):
ax = plt.subplot(gs[qq])
if qq == 0: # Mstar
lbl = r'$\log \, M_*$'
xval = getattr(cos_halos, 'stellar_mass')
medx = 0
elif qq == 1: # sSFR
lbl = 'sSFR'
xval = getattr(cos_halos, 'ssfr')
medx = 1e-11
elif qq == 2: # Rperp
lbl = r'$R_\perp$'
xval = getattr(cos_halos, 'rho').value
medx = 0
elif qq == 3: # NHI
lbl = r'$N_{\rm HI}$'
#xval = getattr(cos_halos, 'NHI')
xarr = getattr(cos_halos, 'NHIPDF') # USE THE PDF
xval = np.array([ixa.median for ixa in xarr])
medx = 0
# Stats (as needed)
if medx == 0:
medx = np.median(xval[mska])
# Build PDFs
lowPDF, hiPDF = None, None
for ii, cgm_abs in enumerate(cos_halos.cgm_abs):
if msk[ii] is False:
continue
# Sum the PDF
if xval[ii] > medx:
if hiPDF is None:
hiPDF = cgm_abs.igm_sys.metallicity
else:
hiPDF = hiPDF + cgm_abs.igm_sys.metallicity
else:
if lowPDF is None:
lowPDF = cgm_abs.igm_sys.metallicity
else:
lowPDF = lowPDF + cgm_abs.igm_sys.metallicity
ax.set_xlim(ZH_mnx)
lowPDF.normalize()
hiPDF.normalize()
# Giddy up
lsz = 19.
ax.bar(lowPDF.ZH-lowPDF.dZH/2., lowPDF.pdf_ZH, width=lowPDF.dZH, color='red', alpha=0.5)
ax.bar(hiPDF.ZH-hiPDF.dZH/2., hiPDF.pdf_ZH, width=hiPDF.dZH, color='blue', alpha=0.5)
ax.set_xlabel("[Z/H]", size=lsz)
ax.set_ylabel("Normalized PDFs", size=lsz)
# Label
csz = 14.
ax.text(0.05, 0.87, lbl, transform=ax.transAxes, color='black', size=csz, ha='left')
#lbl2 = '({:d} systems)'.format(nsys)
#ax.text(0.05, 0.75, lbl2, transform=ax.transAxes, color='black', size=csz, ha='left')
# Axes
ax.xaxis.set_major_locator(plt.MultipleLocator(1.))
xputils.set_fontsize(ax, 13.)
# End
print('Writing {:s}'.format(outfil))
plt.tight_layout(pad=0.2,h_pad=0.,w_pad=0.1)
pp.savefig()
pp.close()
plt.close()
def pdf_1dspec(uvq, spec, pdf_fil, title=None, ymnx=None):
'''
Generate a 1D spec file
Parameters:
-----------
uvq: QTable row
From UVQ summary
spec: Spectrum1D
Spectrum to plot
pdf_fil: string
Name of the PDF file
title: string
Title for the plot
'''
# Import
import matplotlib as mpl
mpl.rcParams['font.family'] = 'stixgeneral'
from matplotlib.backends.backend_pdf import PdfPages
from matplotlib import pyplot as plt
import matplotlib.gridspec as gridspec
from xastropy.plotting import utils as xputils
# b-spline for limits
gd = np.where( (spec.sig > 0.) & (spec.flux > 0.))[0]
try:
xmnx = [np.min(spec.wavelength.value[gd]), np.max(spec.wavelength.value[gd])]
except ValueError:
if uvq['SCI_FILE'] in ['August2014/CAHA_none.fits']: # None file for CAHA stars
ymnx = np.array([-0.05,1.])
# Special
if uvq['OBSV'] == 'CAHA':
xmnx = (3800., 9000.)
gd = np.where( (spec.sig > 0.) & (spec.flux > 0.) &
(spec.wavelength > xmnx[0]*u.AA))[0]
elif uvq['instr'] == 'MagE':
xmnx = (3300., 9000.)
gd = np.where( (spec.sig > 0.) & (spec.flux > 0.) &
(spec.wavelength > xmnx[0]*u.AA))[0]
elif uvq['instr'] == 'Kast':
xmnx[1] = 7500.
elif uvq['instr'] == 'ESI':
xmnx = (4200., 8000.)
gd = np.where( (spec.sig > 0.) & (spec.flux > 0.) &
(spec.wavelength > xmnx[0]*u.AA))[0]
if ymnx is None:
ymnx = bspline_ymnx(spec,gd)
yscl = 10.**(int(np.log10(ymnx[1])))
# Start the plot
#pp = PdfPages(pdf_fil)
plt.figure(figsize=(8, 5))
plt.clf()
gs = gridspec.GridSpec(1, 1)
ax = plt.subplot(gs[0,0])
# Axes
#ax.xaxis.set_minor_locator(plt.MultipleLocator(0.5))
#ax.xaxis.set_major_locator(plt.MultipleLocator(1.))
ax.yaxis.set_minor_locator(plt.MultipleLocator(0.5))
#ax.yaxis.set_major_locator(plt.MultipleLocator(1.))
ax.set_xlim(xmnx)
ax.set_ylim(ymnx/yscl)
ax.set_xlabel(r'Wavelength ($\AA$)')
ax.set_ylabel('Relative Flux')
# Plot
ax.plot(spec.wavelength, spec.flux/yscl, 'k-',drawstyle='steps-mid', linewidth=0.9)
ax.plot(spec.wavelength, spec.sig/yscl, 'r:')
# Title
y0 = 0.92
if title is not None:
ax.text(0.5, y0, title, transform=ax.transAxes, size=18, color='blue',
ha='center', bbox={'facecolor':'white', 'edgecolor':'white'})
# Other data
x1_lbl = 0.94
yoff = 0.05
ax.text(x1_lbl, y0, uvq['OBSV'], transform=ax.transAxes, size=14, color='black', ha='right')
ax.text(x1_lbl, y0-yoff, uvq['instr'], transform=ax.transAxes, size=14, color='black', ha='right')
ax.text(x1_lbl, y0-2*yoff, uvq['OBS_DATE'], transform=ax.transAxes, size=14, color='black',
ha='right')
ax.text(x1_lbl, y0-3*yoff, 'z={:0.3f}'.format(uvq['Z']), transform=ax.transAxes, size=14,
color='black', ha='right')
ax.text(x1_lbl, y0-4*yoff, r'$z_Q=$'+'{:d}'.format(uvq['Z_QUAL']), transform=ax.transAxes,
size=14, color='black', ha='right')
ax.text(x1_lbl, y0-5*yoff, r'$S_Q=$'+'{:d}'.format(uvq['SPEC_QUAL']), transform=ax.transAxes,
size=14, color='black', ha='right')
# Template
#xdb.set_trace()
zfil = os.getenv('UVQ_DATA')+'2D_Spectra/'+uvq['dbx_path']+'/'+uvq['ZASS_FIL']
try:
new_eigen = fits.open(zfil)[2].data
except:
pass
else:
rebin_wv2 = fits.open(zfil)[3].data
sz_eigen = new_eigen.shape
model_flux = np.dot(new_eigen.transpose(), uvq['THETA'][0:sz_eigen[0]])
ax.plot(rebin_wv2*(1+uvq['Z']), model_flux/yscl, 'g-', linewidth=0.5, alpha=0.6)
#xdb.set_trace()
# Label a few lines
line_lbls = {1903.91: 'CIII]', 4341.69: r'H$\gamma$', 4862.70: r'H$\beta$',
5008.24: '[OIII]', 2799.40: 'MgII', 6564.63: r'H$\alpha$'}
for key in line_lbls.keys():
xplt = (1+uvq['Z'])*key
if (xplt>xmnx[0]) & (xplt<xmnx[1]):
ax.text((1+uvq['Z'])*key, 0.8*ymnx[1]/yscl, line_lbls[key], size=11, color='green', ha='center')
# Font size
xputils.set_fontsize(ax,15.)
# Layout and save
plt.tight_layout(pad=0.2,h_pad=0.,w_pad=0.1)
plt.savefig(pdf_fil)
#pp.savefig(bbox_inches='tight')
#pp.close()
plt.close()
print('Wrote spectrum to {:s}'.format(pdf_fil))
def q1422(outfil='Figures/q1422.pdf'):
""" Series of plots on Q1422
"""
q1422 = lsio.readspec(
'/Users/xavier/Keck/HIRES/RedData/Q1422+2309/Q1422+2309.fits')
axmnx = [
[4000, 6000],
[4900, 5500],
[5100, 5300],
[5150, 5250],
[5190, 5220],
]
aymnx = [
[0., 7300],
[0., 2000],
[0., 1700],
[0., 1100],
[0., 1100],
]
lw = 1.
csz = 19.
# Start the plot
pp = PdfPages(outfil)
fig = plt.figure(figsize=(8.0, 5.0))
plt.clf()
gs = gridspec.GridSpec(1, 1)
# Loop
for qq, xmnx in enumerate(axmnx):
# Spectrum
ax = plt.subplot(gs[0])
ax.set_xlim(xmnx)
ax.set_ylim(aymnx[qq])
#ax.set_ylim(ymnx)
ax.set_ylabel('Relative Flux')
ax.set_xlabel("Wavelength (Ang)")
ax.plot(q1422.wavelength, q1422.flux, 'k', linewidth=lw)
#
ax.text(0.05,
0.9,
'Keck/HIRES: Q1422+2309',
color='blue',
transform=ax.transAxes,
size=csz,
ha='left') #, bbox={'facecolor':'white'})
#
xputils.set_fontsize(ax, 17.)
# Layout and save
plt.tight_layout(pad=0.2, h_pad=0.0, w_pad=0.4)
plt.subplots_adjust(hspace=0)
pp.savefig(bbox_inches='tight', transparent=True)
plt.close()
# Finish
print('Writing {:s}'.format(outfil))
pp.close()
def dteff(outfil='Figures/dteff.pdf'):
""" Differential teff (Lya)
"""
# Load fN
fN_model = FNModel.default_model()
# teff
cumul = []
iwave = 1215.67 * (1 + 2.5)
zem = 2.6
teff_alpha = lyman_ew(iwave, zem, fN_model, cumul=cumul)
print('teff = {:g}'.format(teff_alpha))
dteff = cumul[1] - np.roll(cumul[1], 1)
dteff[0] = dteff[1] # Fix first value
# Start the plot
xmnx = (12, 22)
pp = PdfPages(outfil)
fig = plt.figure(figsize=(8.0, 5.0))
plt.clf()
gs = gridspec.GridSpec(1, 1)
# Lya line
ax = plt.subplot(gs[0])
#ax.xaxis.set_minor_locator(plt.MultipleLocator(0.5))
#ax.xaxis.set_major_locator(plt.MultipleLocator(20.))
#ax.yaxis.set_minor_locator(plt.MultipleLocator(0.1))
#ax.yaxis.set_major_locator(plt.MultipleLocator(0.2))
ax.set_xlim(xmnx)
#ax.set_ylim(ymnx)
ax.set_ylabel(r'$d\tau_{\rm eff, \alpha}/d\log N$')
ax.set_xlabel(r'$\log \, N_{\rm HI}$')
lw = 2.
ax.plot(cumul[0], dteff, 'k', linewidth=lw)
# Label
csz = 17
ax.text(0.60,
0.90,
'f(N) from Prochaska+14',
color='blue',
transform=ax.transAxes,
size=csz,
ha='left')
ax.text(0.60,
0.80,
'z=2.5',
color='blue',
transform=ax.transAxes,
size=csz,
ha='left')
xputils.set_fontsize(ax, 17.)
# Layout and save
print('Writing {:s}'.format(outfil))
plt.tight_layout(pad=0.2, h_pad=0.0, w_pad=0.4)
plt.subplots_adjust(hspace=0)
pp.savefig(bbox_inches='tight')
plt.close()
# Finish
pp.close()
def obs_sawtooth(outfil='Figures/obs_sawtooth.pdf', all_tau=None, scl=1.):
""" Sawtooth opacity
"""
# SDSS
hdu = fits.open(
'/Users/xavier/paper/LLS/taueff/Analysis/stack_DR7_z3.92_z4.02.fits')
sdss_fx = hdu[0].data
sdss_wave = hdu[2].data
# Telfer
telfer = pyicq.get_telfer_spec()
i1450 = np.argmin(np.abs(telfer.wavelength.value - 1450.))
nrm = np.median(telfer.flux[i1450 - 5:i1450 + 5])
telfer.flux = telfer.flux / nrm
trebin = telfer.rebin(sdss_wave * u.AA)
# Load fN
fN_model = FNModel.default_model()
fN_model.zmnx = (2., 4.1) # extrapolate a bit
# teff
zem = 4.
wave = np.arange(4500., 6200., 10)
# Calculate
if all_tau is None:
all_tau = np.zeros_like(wave)
for qq, iwave in enumerate(wave):
all_tau[qq] = lyman_ew(iwave, zem, fN_model)
# Flux attenuation
trans = np.exp(-all_tau)
ftrans = interp1d(wave, trans, fill_value=1., bounds_error=False)
# Start the plot
xmnx = (4500, 6200)
pp = PdfPages(outfil)
fig = plt.figure(figsize=(8.0, 5.0))
plt.clf()
gs = gridspec.GridSpec(1, 1)
# Lya line
ax = plt.subplot(gs[0])
#ax.xaxis.set_minor_locator(plt.MultipleLocator(0.5))
#ax.xaxis.set_major_locator(plt.MultipleLocator(20.))
#ax.yaxis.set_minor_locator(plt.MultipleLocator(0.1))
#ax.yaxis.set_major_locator(plt.MultipleLocator(0.2))
ax.set_xlim(xmnx)
ax.set_ylim(0., 1.5)
ax.set_ylabel('Relative Flux')
ax.set_xlabel('Observed wavelength')
lw = 2.
# Data
ax.plot(sdss_wave * (1 + zem),
sdss_fx,
'k',
linewidth=lw,
label='SDSS QSOs (z=4)')
# Model
model = trebin.flux * ftrans(sdss_wave * (1 + zem)) * scl
ax.plot(sdss_wave * (1 + zem),
model,
'r',
linewidth=lw,
label='IGM+Telfer model')
# Label
csz = 17
#ax.text(0.10, 0.10, 'SDSS quasar stack at z=4', color='black',
# transform=ax.transAxes, size=csz, ha='left')
# Legend
legend = plt.legend(loc='upper left',
scatterpoints=1,
borderpad=0.3,
handletextpad=0.3,
fontsize='large',
numpoints=1)
xputils.set_fontsize(ax, 17.)
# Layout and save
print('Writing {:s}'.format(outfil))
plt.tight_layout(pad=0.2, h_pad=0.0, w_pad=0.4)
plt.subplots_adjust(hspace=0)
pp.savefig(bbox_inches='tight')
plt.close()
# Finish
pp.close()
return all_tau
def dla_deviation(outfil='Figures/dla_deviation.pdf'):
""" Deviations from Voigt (Lee 2003)
"""
# Wavelength array for my 'perfect' instrument
wave = np.linspace(1140., 1290., 20000) * u.AA
vel = (wave-1215.67*u.AA)/(1215.67*u.AA) * const.c.to('km/s')
nu = (const.c/wave).to('Hz')
# Lya line
lya = AbsLine(1215.6700*u.AA)
lya.attrib['N'] = 10.**(22)/u.cm**2
lya.attrib['b'] = 30 * u.km/u.s
lya.attrib['z'] = 0.
# Lee
sigmaT = (6.65e-29 * u.m**2).to('cm**2') # Approximate!
f_jk = 0.4162
nu_jk = (const.c/lya.wrest).to('Hz')
def eval_cross_Lee(nu):
return sigmaT * (f_jk/2)**2 * (nu_jk/(nu-nu_jk))**2 * (1-1.792*(nu-nu_jk)/nu_jk)
tau_lee = lya.attrib['N']*eval_cross_Lee(nu)
flux_lee = np.exp(-1*tau_lee.value)
# Start the plot
xmnx = (-15000, 15000)
ymnx = (0., 1.0)
pp = PdfPages(outfil)
fig = plt.figure(figsize=(8.0, 5.0))
plt.clf()
gs = gridspec.GridSpec(1,1)
# Lya line
ax = plt.subplot(gs[0])
#ax.xaxis.set_minor_locator(plt.MultipleLocator(0.5))
#ax.xaxis.set_major_locator(plt.MultipleLocator(20.))
#ax.yaxis.set_minor_locator(plt.MultipleLocator(0.1))
#ax.yaxis.set_major_locator(plt.MultipleLocator(0.2))
ax.set_xlim(xmnx)
ax.set_ylim(ymnx)
ax.set_ylabel('Normalized Flux')
ax.set_xlabel('Relative Velocity (km/s)')
f_voigt = ltav.voigt_from_abslines(wave, [lya])
lw = 2
ax.plot(vel, f_voigt.flux, 'k', linewidth=lw,
label=r'Voigt: $\log N_{\rm HI} = 22$')
ax.plot(vel, flux_lee, 'r', linewidth=lw,
label=r'Lee2003: $\log N_{\rm HI} = 22$')
# Legend
legend = plt.legend(loc='lower left', scatterpoints=1, borderpad=0.3,
handletextpad=0.3, fontsize='large', numpoints=1)
xputils.set_fontsize(ax, 17.)
# Layout and save
print('Writing {:s}'.format(outfil))
plt.tight_layout(pad=0.2,h_pad=0.0,w_pad=0.4)
plt.subplots_adjust(hspace=0)
pp.savefig(bbox_inches='tight')
plt.close()
# Finish
pp.close()
def fig_mtlPDF_cuts(cos_halos=None, outfil='fig_mtlPDF_cuts.pdf', qcut=1):
""" Shows the metallicity PDF for various cuts
Avoids 0 detection systems
"""
# Read COS-Halos
if cos_halos is None:
cos_halos = load_ch()
# Quality cut
msk = [False] * len(cos_halos.cgm_abs)
for ii, cgm_abs in enumerate(cos_halos.cgm_abs):
# Cut on quality
if chmtl.mtl_quality(cgm_abs) <= qcut:
print('No constraint for {:s}'.format(cgm_abs.name))
print('Skipping')
continue
msk[ii] = True
mska = np.array(msk)
# Init
ZH_mnx = (-2., 1)
# Start the plot
pp = PdfPages(outfil)
plt.figure(figsize=(5, 5))
plt.clf()
gs = gridspec.GridSpec(2, 2)
for qq in range(4):
ax = plt.subplot(gs[qq])
if qq == 0: # Mstar
lbl = r'$\log \, M_*$'
xval = getattr(cos_halos, 'stellar_mass')
medx = 0
elif qq == 1: # sSFR
lbl = 'sSFR'
xval = getattr(cos_halos, 'ssfr')
medx = 1e-11
elif qq == 2: # Rperp
lbl = r'$R_\perp$'
xval = getattr(cos_halos, 'rho').value
medx = 0
elif qq == 3: # NHI
lbl = r'$N_{\rm HI}$'
#xval = getattr(cos_halos, 'NHI')
xarr = getattr(cos_halos, 'NHIPDF') # USE THE PDF
xval = np.array([ixa.median for ixa in xarr])
medx = 0
# Stats (as needed)
if medx == 0:
medx = np.median(xval[mska])
# Build PDFs
lowPDF, hiPDF = None, None
for ii, cgm_abs in enumerate(cos_halos.cgm_abs):
if msk[ii] is False:
continue
# Sum the PDF
if xval[ii] > medx:
if hiPDF is None:
hiPDF = cgm_abs.igm_sys.metallicity
else:
hiPDF = hiPDF + cgm_abs.igm_sys.metallicity
else:
if lowPDF is None:
lowPDF = cgm_abs.igm_sys.metallicity
else:
lowPDF = lowPDF + cgm_abs.igm_sys.metallicity
ax.set_xlim(ZH_mnx)
lowPDF.normalize()
hiPDF.normalize()
# Giddy up
lsz = 19.
ax.bar(lowPDF.ZH - lowPDF.dZH / 2.,
lowPDF.pdf_ZH,
width=lowPDF.dZH,
color='red',
alpha=0.5)
ax.bar(hiPDF.ZH - hiPDF.dZH / 2.,
hiPDF.pdf_ZH,
width=hiPDF.dZH,
color='blue',
alpha=0.5)
ax.set_xlabel("[Z/H]", size=lsz)
ax.set_ylabel("Normalized PDFs", size=lsz)
# Label
csz = 14.
ax.text(0.05,
0.87,
lbl,
transform=ax.transAxes,
color='black',
size=csz,
ha='left')
#lbl2 = '({:d} systems)'.format(nsys)
#ax.text(0.05, 0.75, lbl2, transform=ax.transAxes, color='black', size=csz, ha='left')
# Axes
ax.xaxis.set_major_locator(plt.MultipleLocator(1.))
xputils.set_fontsize(ax, 13.)
# End
print('Writing {:s}'.format(outfil))
plt.tight_layout(pad=0.2, h_pad=0., w_pad=0.1)
pp.savefig()
pp.close()
plt.close()
def dla_vary_NHI(outfil='Figures/dla_vary_NHI.pdf'):
""" DLA profiles with NHI varying
"""
# Wavelength array for my 'perfect' instrument
wave = np.linspace(1160., 1270., 20000) * u.AA
vel = (wave - 1215.67 * u.AA) / (1215.67 * u.AA) * const.c.to('km/s')
# Lya line
lya = AbsLine(1215.6700 * u.AA)
#lya.attrib['N'] = 10.**(13.6)/u.cm**2
lya.attrib['b'] = 30 * u.km / u.s
lya.attrib['z'] = 0.
aNHI = [20.3, 21., 21.5, 22.]
# Start the plot
xmnx = (-10000, 10000)
ymnx = (0., 1.0)
pp = PdfPages(outfil)
fig = plt.figure(figsize=(8.0, 5.0))
plt.clf()
gs = gridspec.GridSpec(1, 1)
# Lya line
ax = plt.subplot(gs[0])
#ax.xaxis.set_minor_locator(plt.MultipleLocator(0.5))
#ax.xaxis.set_major_locator(plt.MultipleLocator(20.))
#ax.yaxis.set_minor_locator(plt.MultipleLocator(0.1))
#ax.yaxis.set_major_locator(plt.MultipleLocator(0.2))
ax.set_xlim(xmnx)
ax.set_ylim(ymnx)
ax.set_ylabel('Normalized Flux')
ax.set_xlabel('Relative Velocity (km/s)')
lw = 1.5
# Data
for NHI in aNHI:
lyai = copy.deepcopy(lya)
lyai.attrib['N'] = 10**NHI / u.cm**2
f_obsi = ltav.voigt_from_abslines(wave, [lyai])
ax.plot(vel,
f_obsi.flux,
linewidth=lw,
label=r'$\log N_{\rm HI} = $' + '{:0.2f}'.format(NHI))
# Legend
legend = plt.legend(loc='lower left',
scatterpoints=1,
borderpad=0.3,
handletextpad=0.3,
fontsize='large',
numpoints=1)
xputils.set_fontsize(ax, 17.)
# Layout and save
print('Writing {:s}'.format(outfil))
plt.tight_layout(pad=0.2, h_pad=0.0, w_pad=0.4)
plt.subplots_adjust(hspace=0)
pp.savefig(bbox_inches='tight')
plt.close()
# Finish
pp.close()
def fig_images(outfil=None):
from xastropy.obs import x_getsdssimg as xgs
# Init COS-Halos sightline
cos_halos = COSHalos()
cos_halos.load_mega(skip_ions=True)
#xdb.set_trace()
# Start the plot
if outfil is None:
outfil = 'fig_coshalo_images.pdf'
pp = PdfPages(outfil)
dx = 0.2
dy = 0.55
imsize = 1.2
for ss in range(5):
fig = plt.figure(figsize=(8, 5))
fig.clf()
# Setup for dark
xpsimp.dark_bkgd(plt)
gs = gridspec.GridSpec(1, 1)
# Axes
ax = plt.subplot(gs[0, 0])
ax.set_xlim(9.4, 11.7)
#ax.xaxis.set_major_locator(plt.MultipleLocator(300.))
ax.set_ylim(-13, -9)
ax.set_ylabel('sSFR')
ax.set_xlabel('log M*')
# Plot
if ss == 0:
mstar = [
cgm_abs.galaxy.stellar_mass for cgm_abs in cos_halos.cgm_abs
]
sSFR = [
np.log10(cgm_abs.galaxy.sfr[1]) - cgm_abs.galaxy.stellar_mass
for cgm_abs in cos_halos.cgm_abs
]
ax.scatter(mstar, sSFR)
elif ss == 1: # Show our first one
cgm_abs = cos_halos[('J0950+4831', '177_27')]
img, oBW = xgs.getimg(cgm_abs.galaxy.coord.ra.deg,
cgm_abs.galaxy.coord.dec.deg,
imsize=imsize)
# Figure out placement
ximg = cgm_abs.galaxy.stellar_mass
yimg = np.log10(
cgm_abs.galaxy.sfr[1]) - cgm_abs.galaxy.stellar_mass
# Show
ax.imshow(img,
extent=(ximg - dx, ximg + dx, yimg - dy, yimg + dy),
aspect=dx / dy)
elif ss == 2: # Show two
cgm_list = [('J0950+4831', '177_27'), ('J1245+3356', '236_36')]
for icgm in cgm_list:
cgm_abs = cos_halos[icgm]
img, oBW = xgs.getimg(cgm_abs.galaxy.coord.ra.deg,
cgm_abs.galaxy.coord.dec.deg,
imsize=imsize)
# Figure out placement
ximg = cgm_abs.galaxy.stellar_mass
yimg = np.log10(
cgm_abs.galaxy.sfr[1]) - cgm_abs.galaxy.stellar_mass
# Show
ax.imshow(img,
extent=(ximg - dx, ximg + dx, yimg - dy, yimg + dy),
aspect=dx / dy)
elif ss >= 3: # Show half
if ss == 3:
iend = 20
else:
iend = -1
for cgm_abs in cos_halos.cgm_abs[0:iend]:
img, oBW = xgs.getimg(cgm_abs.galaxy.coord.ra.deg,
cgm_abs.galaxy.coord.dec.deg,
imsize=1.2)
# Figure out placement
ximg = cgm_abs.galaxy.stellar_mass
yimg = np.log10(
cgm_abs.galaxy.sfr[1]) - cgm_abs.galaxy.stellar_mass
# Show
scl = 2.
ax.imshow(img,
extent=(ximg - dx / scl, ximg + dx / scl,
yimg - dy / scl, yimg + dy / scl),
aspect=dx / dy)
xputils.set_fontsize(ax, 17.)
# Write
fig.tight_layout(pad=0.2, h_pad=0., w_pad=0.1)
pp.savefig()
plt.close()
# Finish
print('tlk_coshalos: Wrote {:s}'.format(outfil))
pp.close()
def dla_deviation(outfil='Figures/dla_deviation.pdf'):
""" Deviations from Voigt (Lee 2003)
"""
# Wavelength array for my 'perfect' instrument
wave = np.linspace(1140., 1290., 20000) * u.AA
vel = (wave - 1215.67 * u.AA) / (1215.67 * u.AA) * const.c.to('km/s')
nu = (const.c / wave).to('Hz')
# Lya line
lya = AbsLine(1215.6700 * u.AA)
lya.attrib['N'] = 10.**(22) / u.cm**2
lya.attrib['b'] = 30 * u.km / u.s
lya.attrib['z'] = 0.
# Lee
sigmaT = (6.65e-29 * u.m**2).to('cm**2') # Approximate!
f_jk = 0.4162
nu_jk = (const.c / lya.wrest).to('Hz')
def eval_cross_Lee(nu):
return sigmaT * (f_jk /
2)**2 * (nu_jk /
(nu - nu_jk))**2 * (1 - 1.792 *
(nu - nu_jk) / nu_jk)
tau_lee = lya.attrib['N'] * eval_cross_Lee(nu)
flux_lee = np.exp(-1 * tau_lee.value)
# Start the plot
xmnx = (-15000, 15000)
ymnx = (0., 1.0)
pp = PdfPages(outfil)
fig = plt.figure(figsize=(8.0, 5.0))
plt.clf()
gs = gridspec.GridSpec(1, 1)
# Lya line
ax = plt.subplot(gs[0])
#ax.xaxis.set_minor_locator(plt.MultipleLocator(0.5))
#ax.xaxis.set_major_locator(plt.MultipleLocator(20.))
#ax.yaxis.set_minor_locator(plt.MultipleLocator(0.1))
#ax.yaxis.set_major_locator(plt.MultipleLocator(0.2))
ax.set_xlim(xmnx)
ax.set_ylim(ymnx)
ax.set_ylabel('Normalized Flux')
ax.set_xlabel('Relative Velocity (km/s)')
f_voigt = ltav.voigt_from_abslines(wave, [lya])
lw = 2
ax.plot(vel,
f_voigt.flux,
'k',
linewidth=lw,
label=r'Voigt: $\log N_{\rm HI} = 22$')
ax.plot(vel,
flux_lee,
'r',
linewidth=lw,
label=r'Lee2003: $\log N_{\rm HI} = 22$')
# Legend
legend = plt.legend(loc='lower left',
scatterpoints=1,
borderpad=0.3,
handletextpad=0.3,
fontsize='large',
numpoints=1)
xputils.set_fontsize(ax, 17.)
# Layout and save
print('Writing {:s}'.format(outfil))
plt.tight_layout(pad=0.2, h_pad=0.0, w_pad=0.4)
plt.subplots_adjust(hspace=0)
pp.savefig(bbox_inches='tight')
plt.close()
# Finish
pp.close()
def fig_abs_gallery(wrest=None,
lbl=None,
outfil=None,
cos_halos=None,
passback=False,
axes_flg=0):
# import tlk_coshalos as tch
# reload(tch)
# cos_halos = tch.fig_abs_gallery(passback=True)
'''Gallery of absorption lines
Default is M* vs. sSFR
But you can do rho vs. M* too
axes_flg: int, optional
0: M* vs. sSFR
1: rho vs. M*
'''
# Linelist
llist = lll.LineList('Strong')
if wrest is None:
wrest = 1215.670 * u.AA
Zion = (llist[wrest]['Z'], llist[wrest]['ion'])
if lbl is None:
lbl = r'HI Ly$\alpha$'
if outfil is None:
outfil = 'fig_HI_gallery.pdf'
# Init COS-Halos (slow)
if cos_halos is None:
cos_halos = COSHalos()
cos_halos.load_mega() #skip_ions=True)
if passback:
return cos_halos
if axes_flg == 0:
xmnx = (9.4, 11.7)
ymnx = (-13., -9.)
elif axes_flg == 1:
ymnx = (9.4, 11.7) # log Msun
xmnx = (15., 163) # kpc
vmnx = (-600., 600.) # km/s
wbox = {'facecolor': 'white', 'edgecolor': 'white'}
lclr = 'blue'
# To help with looping
def sngl_abs(ax,
field_gal,
wbox=wbox,
lclr=lclr,
vmnx=vmnx,
xmnx=xmnx,
ymnx=ymnx,
cos_halos=cos_halos,
show_xylbl=True,
srect=0.2,
show_ewlbl=True,
lw=1.3,
axes_flg=axes_flg):
#
cgm_abs = cos_halos[field_gal]
if axes_flg == 0:
xplt = cgm_abs.galaxy.stellar_mass
yplt = np.log10(
cgm_abs.galaxy.sfr[1]) - cgm_abs.galaxy.stellar_mass
elif axes_flg == 1:
yplt = cgm_abs.galaxy.stellar_mass
xplt = cgm_abs.rho.value
# Spec
spec = cos_halos.load_bg_cos_spec(field_gal, wrest)
velo = spec.relative_vel(wrest * (cgm_abs.galaxy.z + 1))
# EW
data = cgm_abs.abs_sys.ions[Zion]
itrans = np.where(np.abs(data['LAMBDA'] - wrest.value) < 1e-3)[0]
if len(itrans) == 0:
print('No measurement of {:g} for {:s} {:s}'.format(
wrest, field_gal[0], field_gal[1]))
return
EW = data['WREST'][itrans][0] * u.AA / 1e3
sigEW = data['SIGWREST'][itrans][0] * u.AA / 1e3
if sigEW <= 0.: # Something must be wrong
return
if EW > 3 * sigEW:
sclr = 'k'
else:
sclr = 'r'
#
xrect = (xplt - xmnx[0]) / (xmnx[1] - xmnx[0])
yrect = (yplt - ymnx[0]) / (ymnx[1] - ymnx[0])
rect = [xrect, yrect, srect, srect]
axsp = xpsimp.add_subplot_axes(ax, rect) #,axisbg=axisbg)
axsp.set_xlim(vmnx)
axsp.set_ylim(-0.1, 1.3)
if show_xylbl:
axsp.set_xlabel('Relative Velocity (km/s)', fontsize=9.)
axsp.set_ylabel('Normalized Flux', fontsize=9.)
# Plot
axsp.plot(velo, spec.flux, sclr, drawstyle='steps', lw=lw)
# Label
#llbl = (r'$W_\lambda = $'+'{:0.2f} A \n'.format(EW.value)+
# '$z=${:.3f}\n'.format(cgm_abs.galaxy.z)+
# r'$\rho=$'+'{:d}kpc'.format(int(np.round(cgm_abs.rho.to('kpc').value))))
if show_ewlbl:
llbl = r'$W_\lambda = $' + '{:0.2f} A'.format(EW.value)
axsp.text(-300.,
1.1,
llbl,
ha='left',
fontsize=7.,
color=lclr,
bbox=wbox) #multialignment='left')
# Start the plot
pp = PdfPages(outfil)
if axes_flg == 0:
loop = range(4)
else:
loop = range(3, 4)
for ss in loop:
plt.figure(figsize=(8, 5))
plt.clf()
gs = gridspec.GridSpec(1, 1)
# Axes
ax = plt.subplot(gs[0, 0])
ax.set_xlim(xmnx)
ax.set_ylim(ymnx)
if axes_flg == 0:
ax.set_ylabel('sSFR')
ax.set_xlabel('log M*')
ax.text(9.75, -12., lbl, color=lclr, fontsize=21.)
elif axes_flg == 1:
ax.set_ylabel('log M*')
ax.set_xlabel('Impact Parameter (kpc)')
ax.text(40., 11.5, lbl, color=lclr, fontsize=21.)
#ax.xaxis.set_major_locator(plt.MultipleLocator(300.))
#
if ss == 0: # Single system
field_gal = ('J0950+4831', '177_27')
sngl_abs(ax, field_gal)
elif ss == 1: # Two systems
cgm_list = [('J0950+4831', '177_27'), ('J1245+3356', '236_36')]
for field_gal in cgm_list:
sngl_abs(ax, field_gal)
elif ss > 1: # Half systems
if ss == 2:
iend = 20
else:
iend = -1
for cgm_abs in cos_halos.cgm_abs[0:iend]:
field_gal = (cgm_abs.field, cgm_abs.gal_id)
sngl_abs(ax,
field_gal,
show_xylbl=False,
srect=0.1,
show_ewlbl=False,
lw=0.5)
else:
pass
xputils.set_fontsize(ax, 17.)
# Write
plt.tight_layout(pad=0.2, h_pad=0., w_pad=0.1)
pp.savefig()
plt.close()
# Finish
print('tlk_coshalos: Wrote {:s}'.format(outfil))
pp.close()
def mfp_spec(outfil='Figures/mfp_spec.pdf', all_tau=None, scl=1.):
""" Stacked spectrum for MFP
"""
# SDSS
zq = 4.
hdu = fits.open('/Users/xavier/paper/LLS/taueff/Analysis/stack_DR7_z3.92_z4.02.fits')
sdss_fx = hdu[0].data
sdss_wave = hdu[2].data
zem = 4.
# Start the plot
xmnx = (800, 1000)
ymnx = (0., 1.0)
pp = PdfPages(outfil)
fig = plt.figure(figsize=(8.0, 5.0))
plt.clf()
gs = gridspec.GridSpec(1,1)
# Lya line
ax = plt.subplot(gs[0])
#ax.xaxis.set_minor_locator(plt.MultipleLocator(0.5))
#ax.xaxis.set_major_locator(plt.MultipleLocator(20.))
#ax.yaxis.set_minor_locator(plt.MultipleLocator(0.1))
#ax.yaxis.set_major_locator(plt.MultipleLocator(0.2))
ax.set_xlim(xmnx)
ax.set_ylim(ymnx)
ax.set_ylabel('Relative Flux')
ax.set_xlabel('Rest Wavelength (Ang)')
lw = 1.5
# Data
ax.plot(sdss_wave, sdss_fx, 'k', linewidth=lw, label='SDSS QSOs (z=4)')
# Label
xexp = 860.
headl = 6.
ax.plot([911.7]*2, ymnx, '--', color='red', linewidth=1.5)
ax.arrow(911.7, 0.6, xexp-911.7+headl, 0., linewidth=2,
head_width=0.03, head_length=headl, fc='blue', ec='blue')
csz = 19.
ax.text(890., 0.63, r'r = $\lambda_{\rm mfp}$', color='blue', size=csz,
ha='center')
# exp(-1)
y1 = 0.43
y2 = np.exp(-1)*y1
yplt = (y1+y2)/2.
yerr = (y2-y1)/2.
ax.errorbar([xexp], [yplt], yerr=yerr, color='green', linewidth=2,
capthick=2)
ax.plot([xexp,911.7], [y1]*2, ':', color='green', linewidth=2)
ax.text(855., yplt, 'exp(-1)', color='green', size=csz, ha='right')
#
ax.text(0.05, 0.90, 'SDSS QSO stack (z=4)', color='black',
transform=ax.transAxes, size=csz, ha='left')
xputils.set_fontsize(ax, 17.)
# Layout and save
print('Writing {:s}'.format(outfil))
plt.tight_layout(pad=0.2,h_pad=0.0,w_pad=0.4)
plt.subplots_adjust(hspace=0)
pp.savefig(bbox_inches='tight')
plt.close()
# Finish
pp.close()
return all_tau
def fig_experiment(outfil=None):
# Init COS-Halos sightline
cos_halos = COSHalos()
cos_halos.load_single(('J0950+4831', '177_27'))
cgm_abs = cos_halos.cgm_abs[0]
print('zem = {:g}'.format(cgm_abs.abs_sys.zem))
# ########################################
# Finder (out of order to avoid PDF issues)
#finder.main([cgm_abs.name, cgm_abs.galaxy.coord], imsize=2.*u.arcmin, show_circ=False)
lclr = 'blue'
# Start the plot
if outfil is None:
outfil = 'fig_experiment.pdf'
pp = PdfPages(outfil)
# Full QSO spectrum
spec_fil = os.getenv(
'DROPBOX_DIR'
) + '/COS-Halos/Targets/J0950+4831/Data/J0950+4831_nbin6_coadd.fits'
spec = lsio.readspec(spec_fil)
xmnx = (1135., 1750.)
ymnx = (-0.0002, 0.0106)
for ss in range(2):
plt.figure(figsize=(8, 5))
plt.clf()
gs = gridspec.GridSpec(1, 1)
# Axes
ax = plt.subplot(gs[0, 0])
#ax.xaxis.set_minor_locator(plt.MultipleLocator(0.5))
#ax.xaxis.set_major_locator(plt.MultipleLocator(1.))
#ax.get_xaxis().get_major_formatter().set_useOffset(False)
ax.set_xlim(1135., 1750.)
ax.set_ylim(-0.0002, 0.0106)
ax.set_ylabel('Relative Flux')
ax.set_xlabel(r'Wavelength ($\AA$)')
# Zero line
ax.plot(xmnx, (0., 0.), 'g--')
# Data
ax.plot(spec.dispersion, spec.flux, 'k')
ax.plot(spec.dispersion, spec.sig, 'r:')
if ss > 0:
ax.fill_between([1455., 1490.], [ymnx[0]] * 2, [ymnx[1]] * 2,
color='blue',
alpha=0.3)
# Label
ax.text(1500.,
0.008,
cgm_abs.field,
ha='left',
fontsize=21.,
color=lclr)
# Fonts
xputils.set_fontsize(ax, 17.)
# Write
plt.tight_layout(pad=0.2, h_pad=0., w_pad=0.1)
pp.savefig()
plt.close()
# Lya spec
for ss in range(3):
plt.figure(figsize=(8, 5))
plt.clf()
gs = gridspec.GridSpec(1, 1)
# Axes
if ss == 0:
spec = cos_halos.load_bg_cos_spec(0, 1215.6700 * u.AA)
wvmnx = np.array([1455., 1490.]) * u.AA
scl_wv = 1.
elif ss == 1:
scl_wv = (1 + cgm_abs.galaxy.z)
elif ss == 2:
spec = cos_halos.load_bg_cos_spec(0, 1025.7222 * u.AA)
scl_wv = (1 + cgm_abs.galaxy.z)
wvmnx = np.array([1015., 1037.]) * u.AA * scl_wv # convoluted, yes
ax = plt.subplot(gs[0, 0])
#ax.xaxis.set_minor_locator(plt.MultipleLocator(0.5))
#ax.xaxis.set_major_locator(plt.MultipleLocator(1.))
#ax.get_xaxis().get_major_formatter().set_useOffset(False)
ax.set_xlim(wvmnx.value / scl_wv)
ax.set_ylim(-0.1, 1.3)
ax.set_ylabel('Normalized Flux')
# Zero line
ax.plot(wvmnx.value / scl_wv, (0., 0.), 'g--')
# Data
ax.plot(spec.dispersion / scl_wv, spec.flux, 'k')
ax.plot(spec.dispersion / scl_wv, spec.sig, 'r:')
# Label
if ss == 0:
ax.set_xlabel(r'Wavelength ($\AA$)')
ax.text(1480.,
0.4,
cgm_abs.field,
ha='left',
fontsize=21.,
color=lclr)
elif ss == 1:
ax.set_xlabel(r'Rest Wavelength ($\AA$)')
ax.text(1220.,
0.4,
r'HI Ly$\alpha$' + ' \n ' +
r'$z=${:0.4f}'.format(cgm_abs.galaxy.z),
ha='left',
fontsize=21.,
multialignment='center',
color=lclr)
elif ss == 2:
ax.set_xlabel(r'Rest Wavelength ($\AA$)')
ax.text(1017.,
0.4,
r'HI Ly$\beta$' + ' \n ' +
r'$z=${:0.4f}'.format(cgm_abs.galaxy.z),
ha='left',
fontsize=21.,
multialignment='center',
color=lclr)
# Fonts
xputils.set_fontsize(ax, 17.)
# Write
plt.tight_layout(pad=0.2, h_pad=0., w_pad=0.1)
pp.savefig()
plt.close()
# ########################################
# Galaxy spectrum
plt.figure(figsize=(8, 5))
plt.clf()
gs = gridspec.GridSpec(1, 1)
# Load
spec = cos_halos.load_gal_spec(0)
# Axes
ax = plt.subplot(gs[0, 0])
ax.set_xlim(4000., 8000.)
ax.set_ylim(-0.1, 25.)
ax.set_xlabel(r'Wavelength ($\AA$)')
ax.set_ylabel('Relative Flux')
# Velo
ax.plot(spec.dispersion, spec.flux, 'k') #, lw=1.3)
ax.plot(spec.dispersion, spec.sig, 'r:') #, lw=1.3)
# Label
#ax.text(-800., 0.2, lbl, ha='left', fontsize=21., color=lclr)
# Fonts
xputils.set_fontsize(ax, 17.)
# Write
plt.tight_layout(pad=0.2, h_pad=0., w_pad=0.1)
pp.savefig()
plt.close()
# ########################################
# Simple HI stack plot
trans = np.array([1215.6701, 1025.7223]) * u.AA
lbls = [r'HI Ly$\alpha$', r'HI Ly$\beta$']
plt.figure(figsize=(8, 5))
plt.clf()
gs = gridspec.GridSpec(2, 1)
for qq, itran, lbl in zip(range(len(trans)), trans, lbls):
# Load
spec = cos_halos.load_bg_cos_spec(0, itran)
# Axes
ax = plt.subplot(gs[qq, 0])
ax.set_xlim(-1000., 1000.)
ax.set_ylim(-0.1, 1.3)
ax.set_ylabel('Normalized Flux')
if qq == 0:
ax.xaxis.set_ticklabels([])
else:
ax.set_xlabel('Relative Velocity (km/s)')
# Velo
velo = spec.relative_vel(itran * (cgm_abs.galaxy.z + 1))
ax.plot(velo, spec.flux, 'k', drawstyle='steps', lw=1.3)
# Label
ax.text(-800., 0.2, lbl, ha='left', fontsize=21., color=lclr)
# Fonts
xputils.set_fontsize(ax, 17.)
# Write
plt.tight_layout(pad=0.2, h_pad=0., w_pad=0.1)
pp.savefig()
plt.close()
# ########################################
# Greater stack plot
trans = np.array([
1215.6701, 1025.7223, 2852.9642, 2803.5315, 1083.9937, 1206.5,
1393.755, 1037.6167
]) * u.AA
lbls = [
r'HI Ly$\alpha$', r'HI Ly$\beta$', 'MgI 2852', 'MgII 2796', 'NII 1083',
'SiIII 1206', 'SiIV 1393', 'OVI 1037'
]
plt.figure(figsize=(8, 5))
plt.clf()
gs = gridspec.GridSpec(2, 4)
xmnx = (-500., 500.)
ymnx = (-0.1, 1.3)
wbox = {'facecolor': 'white', 'edgecolor': 'white'}
for qq, itran, lbl in zip(range(len(trans)), trans, lbls):
# Load
spec = cos_halos.load_bg_cos_spec(0, itran)
# Axes
ax = plt.subplot(gs[qq % 2, qq // 2])
ax.set_xlim(xmnx)
ax.xaxis.set_major_locator(plt.MultipleLocator(300.))
ax.set_ylim(ymnx)
if qq % 2 == 0:
ax.xaxis.set_ticklabels([])
if qq < 2:
ax.set_ylabel('Normalized Flux')
else:
ax.yaxis.set_ticklabels([])
#if qq == 3:
# ax.set_xlabel('Relative Velocity (km/s)')
# Velo
velo = spec.relative_vel(itran * (cgm_abs.galaxy.z + 1))
ax.plot(velo, spec.flux, 'k', drawstyle='steps', lw=1.3)
ax.plot([0., 0.], ymnx, 'g:')
# Label
ax.text(10., 1.15, lbl, ha='left', fontsize=15., color=lclr, bbox=wbox)
# Fonts
xputils.set_fontsize(ax, 17.)
# Write
plt.tight_layout(pad=0.2, h_pad=0., w_pad=0.1)
pp.savefig()
plt.close()
# Finish
print('tlk_coshalos: Wrote {:s}'.format(outfil))
pp.close()
def fig_boss_x_vs_pca(outfil=None, boss_fil=None, flg=0):
'''
flg = 0: Redshift
flg = 1: imag
'''
# Todo
# Include NHI on the label
# Imports
# Read PCA FITS table
if boss_fil is None:
boss_fil = 'BOSS_DR10Lya_PCA_values_nocut.fits.gz'
hdu = fits.open(boss_fil)
pca_coeff = hdu[1].data
# Read BOSS catalog table
boss_cat_fil = os.environ.get(
'BOSSPATH') + '/DR10/BOSSLyaDR10_cat_v2.1.fits.gz'
bcat_hdu = fits.open(boss_cat_fil)
t_boss = bcat_hdu[1].data
#xdb.set_trace()
if flg == 0:
xparm = t_boss['z_pipe']
xmnx = [2., 4.]
xlbl = str(r'$z_{\rm QSO}$')
elif flg == 1:
tmp = t_boss['PSFMAG']
xparm = tmp[:, 3] # i-band mag
xlbl = str('i mag')
xmnx = [17., 22.5]
else:
raise ValueError('fig_boss_x_vs_pca: flg={:d} not allowed'.format(flg))
# Initialize
#if 'xmnx' not in locals():
# xmnx = (17.0, 20.4)
ymnx = ((-0.02, 0.3), (-0.2, 0.4), (-0.2, 0.5), (-0.2, 0.4))
ms = 1. # point size
scl = 100.
# Start the plot
if outfil != None:
pp = PdfPages(outfil)
plt.figure(figsize=(4, 4))
plt.clf()
gs = gridspec.GridSpec(2, 2)
# Looping
for ii in range(4):
# Axis
ax = plt.subplot(gs[ii])
#ax = plt.subplot(gs[ii//2,ii%2])
ylbl = str('PCA' + str(ii))
# Labels
ax.set_xlabel(xlbl)
ax.set_ylabel(ylbl)
# Data
# Values
#xdb.set_trace()
ax.hist2d(xparm,
scl * pca_coeff[ylbl],
bins=100,
norm=LogNorm(),
range=[xmnx, [ymnx[ii][0], ymnx[ii][1]]])
# Font size
xputils.set_fontsize(ax, 8.)
# Layout and save
plt.tight_layout(pad=0.2, h_pad=0.1, w_pad=0.25)
if outfil != None:
pp.savefig(bbox_inches='tight')
pp.close()
else:
plt.show()
def evolving_forest(outfil='Figures/evolving_forest.pdf'):
""" Show varying IGM transmission
"""
hdlls_path = '/Users/xavier/paper/LLS/Optical/Data/DR1/Spectra/'
esi_path = '/Users/xavier/Keck/ESI/RedData/'
hst_path = '/Users/xavier/HST/Cycle23/z1IGM/Archive/PG1206+459/'
dat_files = [
hdlls_path+'HD-LLS_J212329.50-005052.9_HIRES.fits',
hdlls_path+'HD-LLS_J020951.10-000513.0_HIRES.fits',
hdlls_path+'HD-LLS_J113621.00+005021.0_MIKE.fits',
hdlls_path+'HD-LLS_J094932.27+033531.7_MIKE.fits',
esi_path+'PSS0134+3307/PSS0134+3307_f.fits',
esi_path+'J0831+4046/J0831+4046a_f.fits',
esi_path+'J1132+1209/J1132+1209a_f.fits',
esi_path+'J1148+5251/SDSSJ1148+5251_stack.fits',
hdlls_path+'HD-LLS_J212329.50-005052.9_HIRES.fits',
hst_path+'PG1206+459_E230M_f.fits',
'/Users/xavier/MLSS/data/3C273/STIS/E140M/3C273_STIS_E140M_F.fits',
]
conti_fil = '/Users/xavier/MLSS/data/3C273/STIS/E140M/3C273_STIS_E140M_c.fits'
conti_3c273 = fits.open(conti_fil)[0].data
lbls = [
'Keck/HIRES: J2123-0050',
'Keck/HIRES: J0209-0005',
'Magellan/MIKE: J1136+0050',
'Magellan/MIKE: J0949+0335',
'Keck/ESI: PSS0134+3307',
'Keck/ESI: J0831+4046',
'Keck/ESI: J1132+1209',
'Keck/ESI: J1148+5251',
'Keck/HIRES: J2123-0050',
'HST/STIS: PG1206+459',
'HST/STIS: 3C273',
]
zems = [2.26, 2.86, 3.43, 4.05, 4.52, 4.89, 5.17, 6.4, 2.26, 1.16, 0.17]
xrest = np.array([1080, 1200.])
ymnx = [-0.1, 1.1]
lw = 1.
csz = 19.
# Start the plot
pp = PdfPages(outfil)
fig = plt.figure(figsize=(8.0, 5.0))
plt.clf()
gs = gridspec.GridSpec(1,1)
# Loop
for qq, lbl in enumerate(lbls):
spec = lsio.readspec(dat_files[qq])
if lbl == 'HST/STIS: 3C273':
spec.co = conti_3c273
spec.normed = True
# Spectrum
ax = plt.subplot(gs[0])
ax.set_xlim(xrest*(1+zems[qq])/1215.67 - 1)
ax.set_ylim(ymnx)
ax.set_ylabel('Normalized Flux')
ax.set_xlabel(r'Redshift of Ly$\alpha$')
ax.plot(spec.wavelength.value/1215.6701 - 1, spec.flux, 'k', linewidth=lw)
#
ax.text(0.05, 0.95, lbl+' zem={:0.1f}'.format(zems[qq]), color='blue',
transform=ax.transAxes, size=csz, ha='left', bbox={'facecolor':'white'})
#
xputils.set_fontsize(ax, 17.)
# Layout and save
plt.tight_layout(pad=0.2,h_pad=0.0,w_pad=0.4)
plt.subplots_adjust(hspace=0)
pp.savefig(bbox_inches='tight', transparent=True)
plt.close()
# Finish
print('Writing {:s}'.format(outfil))
pp.close()
def evolving_forest(outfil='Figures/evolving_forest.pdf'):
""" Show varying IGM transmission
"""
hdlls_path = '/Users/xavier/paper/LLS/Optical/Data/DR1/Spectra/'
esi_path = '/Users/xavier/Keck/ESI/RedData/'
hst_path = '/Users/xavier/HST/Cycle23/z1IGM/Archive/PG1206+459/'
dat_files = [
hdlls_path + 'HD-LLS_J212329.50-005052.9_HIRES.fits',
hdlls_path + 'HD-LLS_J020951.10-000513.0_HIRES.fits',
hdlls_path + 'HD-LLS_J113621.00+005021.0_MIKE.fits',
hdlls_path + 'HD-LLS_J094932.27+033531.7_MIKE.fits',
esi_path + 'PSS0134+3307/PSS0134+3307_f.fits',
esi_path + 'J0831+4046/J0831+4046a_f.fits',
esi_path + 'J1132+1209/J1132+1209a_f.fits',
esi_path + 'J1148+5251/SDSSJ1148+5251_stack.fits',
hdlls_path + 'HD-LLS_J212329.50-005052.9_HIRES.fits',
hst_path + 'PG1206+459_E230M_f.fits',
'/Users/xavier/MLSS/data/3C273/STIS/E140M/3C273_STIS_E140M_F.fits',
]
conti_fil = '/Users/xavier/MLSS/data/3C273/STIS/E140M/3C273_STIS_E140M_c.fits'
conti_3c273 = fits.open(conti_fil)[0].data
lbls = [
'Keck/HIRES: J2123-0050',
'Keck/HIRES: J0209-0005',
'Magellan/MIKE: J1136+0050',
'Magellan/MIKE: J0949+0335',
'Keck/ESI: PSS0134+3307',
'Keck/ESI: J0831+4046',
'Keck/ESI: J1132+1209',
'Keck/ESI: J1148+5251',
'Keck/HIRES: J2123-0050',
'HST/STIS: PG1206+459',
'HST/STIS: 3C273',
]
zems = [2.26, 2.86, 3.43, 4.05, 4.52, 4.89, 5.17, 6.4, 2.26, 1.16, 0.17]
xrest = np.array([1080, 1200.])
ymnx = [-0.1, 1.1]
lw = 1.
csz = 19.
# Start the plot
pp = PdfPages(outfil)
fig = plt.figure(figsize=(8.0, 5.0))
plt.clf()
gs = gridspec.GridSpec(1, 1)
# Loop
for qq, lbl in enumerate(lbls):
spec = lsio.readspec(dat_files[qq])
if lbl == 'HST/STIS: 3C273':
spec.co = conti_3c273
spec.normed = True
# Spectrum
ax = plt.subplot(gs[0])
ax.set_xlim(xrest * (1 + zems[qq]) / 1215.67 - 1)
ax.set_ylim(ymnx)
ax.set_ylabel('Normalized Flux')
ax.set_xlabel(r'Redshift of Ly$\alpha$')
ax.plot(spec.wavelength.value / 1215.6701 - 1,
spec.flux,
'k',
linewidth=lw)
#
ax.text(0.05,
0.95,
lbl + ' zem={:0.1f}'.format(zems[qq]),
color='blue',
transform=ax.transAxes,
size=csz,
ha='left',
bbox={'facecolor': 'white'})
#
xputils.set_fontsize(ax, 17.)
# Layout and save
plt.tight_layout(pad=0.2, h_pad=0.0, w_pad=0.4)
plt.subplots_adjust(hspace=0)
pp.savefig(bbox_inches='tight', transparent=True)
plt.close()
# Finish
print('Writing {:s}'.format(outfil))
pp.close()
def fig_boss_pca_coeff(outfil=None, boss_fil=None, scl=100.):
# Todo
# Include NHI on the label
# Imports
# Read FITS table
if boss_fil is None:
boss_fil = 'BOSS_DR10Lya_PCA_values_nocut.fits.gz'
hdu = fits.open(boss_fil)
pca_coeff = hdu[1].data
#xdb.set_trace()
# Initialize
#if 'xmnx' not in locals():
# xmnx = (17.0, 20.4)
#ymnx = ((-1.9, 2.3),
# (-1.9, 1.4),
# (-1.1, 1.4),
# (-2.1, 0.9))
ms = 1. # point size
allxi = [0, 0, 0, 1, 1, 2]
allyi = [1, 2, 3, 2, 3, 3]
rngi = ([-0.02, 0.3], [-0.2, 0.4], [-0.2, 0.5], [-0.2, 0.4])
# Start the plot
if outfil != None:
pp = PdfPages(outfil)
plt.figure(figsize=(5.5, 4))
plt.clf()
gs = gridspec.GridSpec(2, 3)
# Looping
for ii in range(6):
# Axis
ax = plt.subplot(gs[ii])
#ax = plt.subplot(gs[ii//2,ii%2])
'''
ax.xaxis.set_minor_locator(plt.MultipleLocator(0.5))
ax.xaxis.set_major_locator(plt.MultipleLocator(1.))
#ax.yaxis.set_minor_locator(plt.MultipleLocator(0.5))
ax.yaxis.set_major_locator(plt.MultipleLocator(0.5))
ax.set_xlim(xmnx)
ax.set_ylim((-0.5, 0.5))
'''
xi = allxi[ii]
xlbl = str('PCA' + str(xi))
yi = allyi[ii]
ylbl = str('PCA' + str(yi))
# Labels
ax.set_xlabel(xlbl)
ax.set_ylabel(ylbl)
# Data
# Values
#ax.scatter(pca_coeff[xlbl], pca_coeff[ylbl], color='black', s=ms)#, marker=mark)
ax.hist2d(scl * pca_coeff[xlbl],
scl * pca_coeff[ylbl],
bins=100,
norm=LogNorm(),
range=[rngi[xi], rngi[yi]])
# Font size
xputils.set_fontsize(ax, 8.)
# Layout and save
plt.tight_layout(pad=0.2, h_pad=0.1, w_pad=0.25)
if outfil != None:
pp.savefig(bbox_inches='tight')
pp.close()
else:
plt.show()
def sawtooth(outfil='Figures/sawtooth.pdf', all_tau=None):
""" Sawtooth opacity
"""
# Load fN
fN_model = FNModel.default_model()
fN_model.zmnx = (2., 4.1) # extrapolate a bit
# teff
zem = 4
wave = np.arange(4500., 6200., 10)
# Calculate
if all_tau is None:
all_tau = np.zeros_like(wave)
for qq, iwave in enumerate(wave):
all_tau[qq] = lyman_ew(iwave, zem, fN_model)
# Flux attenuation
flux = np.exp(-all_tau)
# Start the plot
xmnx = (4500, 6200)
pp = PdfPages(outfil)
fig = plt.figure(figsize=(8.0, 5.0))
plt.clf()
gs = gridspec.GridSpec(1, 1)
# Lya line
ax = plt.subplot(gs[0])
#ax.xaxis.set_minor_locator(plt.MultipleLocator(0.5))
#ax.xaxis.set_major_locator(plt.MultipleLocator(20.))
#ax.yaxis.set_minor_locator(plt.MultipleLocator(0.1))
#ax.yaxis.set_major_locator(plt.MultipleLocator(0.2))
ax.set_xlim(xmnx)
ax.set_ylim(0., 1.1)
ax.set_ylabel('IGM Transmission')
ax.set_xlabel('Observed wavelength (z=4 source)')
lw = 2.
ax.plot(wave, flux, 'b', linewidth=lw)
# Label
csz = 17
ax.text(0.10,
0.90,
'f(N) from Prochaska+14',
color='blue',
transform=ax.transAxes,
size=csz,
ha='left')
ax.text(0.10,
0.80,
'Ignores Lyman continuum opacity',
color='blue',
transform=ax.transAxes,
size=csz,
ha='left')
xputils.set_fontsize(ax, 17.)
# Layout and save
print('Writing {:s}'.format(outfil))
plt.tight_layout(pad=0.2, h_pad=0.0, w_pad=0.4)
plt.subplots_adjust(hspace=0)
pp.savefig(bbox_inches='tight')
plt.close()
# Finish
pp.close()
return all_tau
def mean_sdss_spec(outfil=None):
# Init
mean_spec_fil = '/u/xavier/paper/LLS/taueff/Analysis/stack_DR7_z3.59_z3.63.fits'
mean_hdu = fits.open(mean_spec_fil)
head = mean_hdu[0].header
zqso = head['AVG_Z']
mean_wrest = mean_hdu[2].data * u.AA
mean_flux = mean_hdu[0].data
# Single QSO
dr7 = xsq.SdssQuasars()
qso = dr7[(2161, 206)]
qso.load_spec()
# Plot boundaries
print('zqso = {:g}'.format(zqso))
#wvmnx = np.array((850., 1205.))*u.AA*(1+zqso)
wvmnx = (3400., 5700) * u.AA
mean_ymnx = (0.0, 2.0)
if outfil == None:
outfil = 'fig_mean_sdss_spec.pdf'
elbl_dict = {
r'Ly$\alpha$ (QSO)': [5450., 1.5],
r'Ly$\beta$ (QSO)': [4750., 1.6]
}
albl_dict = {
r'Ly$\alpha$': [5200., 0.6],
r'Ly$\beta$': [4600., 0.6],
r'Ly$\gamma$': [4420., 0.50],
r'Ly$\delta$': [4350., 0.4],
'LL': [912. * (1 + zqso), 0.25]
}
# Start the plot
if outfil != None:
pp = PdfPages(outfil)
# Make the plots
for ss in range(2):
if ss == 0:
ymnx = [0., 25.]
wave = qso.spec.dispersion
flux = qso.spec.flux.value
title = 'Individual QSO at z=3.6'
elif ss == 1:
ymnx = mean_ymnx
wave = mean_wrest * (1 + zqso)
flux = mean_flux
title = '150 QSOs at z=3.6'
plt.figure(figsize=(8, 4))
plt.clf()
gs = gridspec.GridSpec(1, 1)
# Axes
ax = plt.subplot(gs[0, 0])
#ax.xaxis.set_minor_locator(plt.MultipleLocator(0.5))
#ax.xaxis.set_major_locator(plt.MultipleLocator(1.))
#ax.get_xaxis().get_major_formatter().set_useOffset(False)
ax.set_xlim(wvmnx.value)
ax.set_ylim(ymnx)
ax.set_ylabel('Relative Flux')
ax.set_xlabel(r'Observed Wavelength ($\AA$)')
# Zero line
ax.plot(wave, flux, 'b')
# Label
if ss == 1:
for key in albl_dict.keys():
ax.text(albl_dict[key][0],
albl_dict[key][1],
key,
color='green',
ha='center')
for key in elbl_dict.keys():
ax.text(elbl_dict[key][0],
elbl_dict[key][1],
key,
color='red',
ha='center')
ax.text(3550.,
ymnx[1] * 0.85,
title,
color='black',
ha='left',
size=17.)
# Data
'''
if ss > 0:
#ax.fill_between( vmodel.dispersion, vmodel.flux, [1.]*len(wave),
# color='blue', alpha=0.3)
csz = 20.
ax.text(1215.670, 0.5, 'EW', color='black', ha='center',
size=csz)
ax.text(1214.8, 0.2,
r'$W_\lambda = \, $'+'{:.2f}'.format(EW.value)+r' $\AA$',
color='blue', ha='left', size=csz)
'''
# Fonts
xputils.set_fontsize(ax, 15.)
# Write
plt.tight_layout(pad=0.2, h_pad=0., w_pad=0.1)
pp.savefig()
plt.close()
# Finish
print('tlk_spectra.fig_ew: Wrote {:s}'.format(outfil))
pp.close()
def fig_cos_dwarfs_images(outfil=None):
from xastropy.obs import x_getsdssimg as xgs
# Init COS-Dwarfs, COS-Halos
cos_dwarfs = COSDwarfs()
cos_dwarfs.load_mega(skip_ions=True)
cos_halos = COSHalos()
cos_halos.load_mega(skip_ions=True)
# Start the plot
if outfil is None:
outfil='fig_cos_dwarfs_images.pdf'
pp = PdfPages(outfil)
dx = 0.2
dy = 0.40
fig = plt.figure(figsize=(8, 5))
fig.clf()
# Setup for dark
xpsimp.dark_bkgd(plt)
gs = gridspec.GridSpec(1, 1)
# Axes
ax = plt.subplot(gs[0,0])
ax.set_xlim(8.0, 11.7)
#ax.xaxis.set_major_locator(plt.MultipleLocator(300.))
ax.set_ylim(-13,-8.2)
ax.set_ylabel('sSFR')
ax.set_xlabel('log M*')
iend = -1
#iend = 5
imsize = 0.3 # arcmin
for cgm_abs in cos_halos.cgm_abs[0:iend]:
img, oBW = xgs.getimg(cgm_abs.galaxy.coord.ra.deg,
cgm_abs.galaxy.coord.dec.deg, imsize=imsize)
# Figure out placement
ximg = cgm_abs.galaxy.stellar_mass
yimg = np.log10(cgm_abs.galaxy.sfr[1])-cgm_abs.galaxy.stellar_mass
# Show
scl=2.
ax.imshow(img,extent=(ximg-dx/scl, ximg+dx/scl, yimg-dy/scl, yimg+dy/scl),aspect=dx/dy)
iend = -1
#iend = 5
imsize = 0.8 # arcmin
for cgm_abs in cos_dwarfs.cgm_abs[0:iend]:
img, oBW = xgs.getimg(cgm_abs.galaxy.coord.ra.deg,
cgm_abs.galaxy.coord.dec.deg, imsize=imsize)
# Figure out placement
ximg = cgm_abs.galaxy.stellar_mass
yimg = np.log10(cgm_abs.galaxy.sfr[1])-cgm_abs.galaxy.stellar_mass
# Show
scl=2.
ax.imshow(img,extent=(ximg-dx/scl, ximg+dx/scl, yimg-dy/scl, yimg+dy/scl),aspect=dx/dy)
xputils.set_fontsize(ax,17.)
# Write
fig.tight_layout(pad=0.2,h_pad=0.,w_pad=0.1)
pp.savefig()
plt.close()
# Finish
print('tlk_coshalos: Wrote {:s}'.format(outfil))
pp.close()
def fig_NH_hist(cos_halos=None, outfil='fig_NH_hist.pdf', lsz=17.):
""" Shows a histogram of NH values
"""
# Read COS-Halos
if cos_halos is None:
cos_halos = load_ch()
# Read the grid
model = os.getenv('DROPBOX_DIR') + '/cosout/grid_minextended.pkl'
fil = open(model)
modl = pickle.load(fil)
fil.close()
# Init
NH_mnx = (18., 23)
ymnx = (0., 9)
binsz = 0.25
nbins = (NH_mnx[1] - NH_mnx[0]) / binsz
# Start the plot
pp = PdfPages(outfil)
plt.figure(figsize=(5, 5))
plt.clf()
ax = plt.gca()
# Axes
#wvmnx = awvmnx[iuvq['instr']]
#ax.xaxis.set_minor_locator(plt.MultipleLocator(500.))
#ax.yaxis.set_major_locator(plt.MultipleLocator(1.))
#plt.ylim(0, nsys+1)
ax.set_xlim(NH_mnx)
ax.set_ylim(ymnx)
sumPDF = None
# Loop on the systems
nsys = 0
NH_val = []
for cgm_abs in cos_halos.cgm_abs:
# Cut on quality
try:
flgs = cgm_abs.igm_sys.metallicity.inputs['data'][:, 3]
except IndexError:
print('No constraint for {:s}'.format(cgm_abs.name))
print('Skipping')
continue
indices = np.where(flgs != "-1")[0]
if len(indices) == 0:
print('No constraint for {:s}'.format(cgm_abs.name))
print('Skipping')
continue
# Find best indices
mtl = cgm_abs.igm_sys.metallicity.medianZH
imet = np.argmin(np.abs(modl[1]['met'] - mtl))
dens = cgm_abs.igm_sys.density.mediannH
idens = np.argmin(np.abs(modl[1]['dens'] - dens))
ired = np.argmin(np.abs(modl[1]['red'] - cgm_abs.zabs))
icol = np.argmin(np.abs(modl[1]['col'] - cgm_abs.igm_sys.NHI))
# xHI, NH
xHI = modl[2]['HI'][icol][idens][imet][ired]
NH = cgm_abs.igm_sys.NHI - xHI
NH_val.append(NH)
print("We are using {:d} systems in COS-Halos".format(nsys))
# Histogram
lsz = 19.
hist, edges = np.histogram(np.array(NH_val), range=NH_mnx, bins=nbins)
ax.bar(edges[:-1], hist, width=binsz, color='green')
ax.set_xlabel(r'$\log \, N_{\rm H}$')
ax.set_ylabel(r"$N_{\rm sys}$")
# Label
prev_medNH = 19.1 # Eyeball
ax.plot([prev_medNH] * 2, ymnx, '--', color='red')
'''
csz = 18.
lbl = 'COS-Halos'
ax.text(0.05, 0.87, lbl, transform=ax.transAxes, color='black', size=csz, ha='left')
lbl2 = '({:d} systems)'.format(nsys)
ax.text(0.05, 0.75, lbl2, transform=ax.transAxes, color='black', size=csz, ha='left')
'''
# End
xputils.set_fontsize(ax, lsz)
print('Writing {:s}'.format(outfil))
plt.tight_layout(pad=0.2, h_pad=0., w_pad=0.1)
pp.savefig()
pp.close()
plt.close()
