def plot_model(pars):
""" Plot the observed values and errors, along with the predicted
model values.
"""
import matplotlib.pyplot as pl
from barak.plot import draw_arrows, puttext
fig = pl.figure(figsize=(6.4, 3.4))
ax = fig.add_subplot(111)
ms = 6
ipot = [get_ionization_energy(t) for t in tr_plot]
for i,tr in enumerate(tr_plot):
if use_ipot:
ind = ipot[i]
else:
ind = i
if tr in obs:
colour = 'k' if tr in trans else 'w'
fmt = 'o' + colour
val, siglo, sighi = obs[tr]
if siglo == 0:
draw_arrows(ind, val, direction='up', ax=ax,lw=1)
ax.plot(ind, val, fmt,ms=ms)
elif sighi == 0:
draw_arrows(ind, val, direction='down', ax=ax,lw=1)
ax.plot(ind, val, fmt,ms=ms)
else:
ax.plot([ind, ind], [val-siglo, val+sighi], 'k',lw=1)
ax.plot(ind, val, fmt,ms=ms)
ax.text(ind, val + 0.8, tr,
fontsize=10, ha='center')
else:
puttext(ind, 0.02, tr, ax=ax, xcoord='data',
fontsize=10, ha='center')
puttext(0.9,0.1, 'Model', ax, color='r', ha='right')
xvals = list(range(len(tr_plot)))
#print np.asarray(pars).shape
for par in pars:
Nmodel = model(par, for_plot=True)
if use_ipot:
if len(pars) == 1:
ax.plot(ipot, Nmodel, 'r.-', lw=1, zorder=0)
else:
ax.plot(ipot, Nmodel, 'r-', lw=0.2, zorder=0)
else:
if len(pars) == 1:
ax.plot(xvals, Nmodel, 'r.-', lw=1, zorder=0)
else:
ax.plot(xvals, Nmodel, 'r-', lw=0.2, zorder=0)
if use_ipot:
ax.set_xlabel('Ionization potential (eV)')
ax.set_xlim(ipot[0]-1, ipot[-1] + 1)
else:
ax.set_xlim(-0.5, xvals[-1] + 0.5)
ax.set_xticks([])
ax.set_ylabel(r'$\log_{10}\ N$')
fig.tight_layout()
#return fig, ax
return fig
for tr in dont_use:
if tr in trans:
trans.remove(tr)
print 'Using these transitions'
print trans
if 1:
################################################################
# Read the cloudy grids and make the interpolators
################################################################
tr_plot = ('MgI CaII OI OII OIII OIV MgII FeII FeIII SiII AlII CII AlIII '
'NI NII NIII NIV SiIII SII SIV SV '
'SiIV CIII CIV NV OVI').split()
ipot = [get_ionization_energy(t) for t in tr_plot]
isort = np.argsort(ipot)
tr_plot = [tr_plot[i] for i in isort]
assert all(tr in tr_plot for tr in trans)
Ncloudy, Ncloudy_raw, Models, aUV = make_interpolators_uvbtilt(
tr_plot, simnames)
M = Models[0]
if 0 and testing:
# check they look ok
nrows, ncols = get_nrows_ncols(len(trans) * 2)
fig = pl.figure(figsize=(8.4, 8.4))
Z = np.linspace(M.Z[0], M.Z[-1], 100)
nH = np.linspace(M.nH[0], M.nH[-1], 101)
nH1, Z1 = np.meshgrid(nH, Z, indexing='ij')
from barak.sed import flambda_to_fnu
logfnu = np.log10(flambda_to_fnu(wa, 10**logFlam))
wa1 = 10**np.linspace(np.log10(wa[0]), np.log10(wa[-1]), 10*len(wa))
logfnu1 = np.interp(wa1, wa, logfnu)
starburst = np.rec.fromarrays(
[wa1, logfnu1], names='wa,logfnu')
trans = ('CII CIII CIV SiII SiIII SiIV HI AlII '
'AlIII NV OVI MgII NII').split() # MgI
trans = ('CII CIII CIV SiII SiIII SiIV HI AlII '
'AlIII NV OVI MgII NII FeII FeIII MgI OI OII OIII '
'CaII NI CI').split() # MgI
IP = np.array(get_ionization_energy(trans))
import pylab as plt
from atpy import Table
prefix = "/Users/ncrighton/Projects/MPIA_QSO_LBG/Cloudy/J0004/comp1"
names = sorted(glob(prefix + "/uvb_k0[0246]/*tilted*tbl"))
fig1 = pl.figure(figsize=(5.1,4.7))
fig1.subplots_adjust(left=0.2, bottom=0.15, top=0.96,right=0.96)
fig2 = pl.figure(figsize=(5.1,4.7))
fig2.subplots_adjust(left=0.2, bottom=0.15, top=0.96,right=0.96)
ax1 = fig1.add_subplot(111)
ax2 = fig2.add_subplot(111)
import numpy as np
import astropy.units as u
import astropy.constants as c
import barak.absorb
from barak.absorb import get_ionization_energy
from barak.plot import puttext, axvlines, make_log_xlabels
plt.rc('xtick.major',pad=8)
plt.rc('ytick.major',pad=7)
from barak.sed import flambda_to_fnu
get_ionization_energy('HI')
T = barak.absorb.ION_CACHE['table'].data
prob = 8
c0 = (T['P'] > prob) & (T['wrest'] > 600)
trans = T['species'][c0]
tr_wrest = T['wrest'][c0]
# trans = ('CII CIII CIV SiII SiIII SiIV HI AlII '
# 'AlIII NV OVI MgII NII').split() # MgI
# trans = ('CI CII CIII CIV SiII SiIII SiIV HI AlII '
# 'AlIII NI NII NIII NIV NV MgII FeII FeIII MgI OI OII OIII OIV OV OVI '
# 'CaII MnII CrII NeVIII ZnII MgX').split() # MgI
IP = np.array(get_ionization_energy(trans))
def plot_model(pars):
""" Plot the observed values and errors, along with the predicted
model values.
"""
import matplotlib.pyplot as pl
from barak.plot import draw_arrows, puttext
fig = pl.figure(figsize=(6.4, 3.4))
ax = fig.add_subplot(111)
ms = 6
ipot = [get_ionization_energy(t) for t in tr_plot]
for i, tr in enumerate(tr_plot):
if use_ipot:
ind = ipot[i]
else:
ind = i
if tr in obs:
colour = 'k' if tr in trans else 'w'
fmt = 'o' + colour
val, siglo, sighi = obs[tr]
if siglo == 0:
draw_arrows(ind, val, direction='up', ax=ax, lw=1)
ax.plot(ind, val, fmt, ms=ms)
elif sighi == 0:
draw_arrows(ind, val, direction='down', ax=ax, lw=1)
ax.plot(ind, val, fmt, ms=ms)
else:
ax.plot([ind, ind], [val - siglo, val + sighi], 'k', lw=1)
ax.plot(ind, val, fmt, ms=ms)
ax.text(ind, val + 0.8, tr, fontsize=10, ha='center')
else:
puttext(ind,
0.02,
tr,
ax=ax,
xcoord='data',
fontsize=10,
ha='center')
puttext(0.9, 0.1, 'Model', ax, color='r', ha='right')
xvals = list(range(len(tr_plot)))
#print np.asarray(pars).shape
for par in pars:
Nmodel = model(par, for_plot=True)
if use_ipot:
if len(pars) == 1:
ax.plot(ipot, Nmodel, 'r.-', lw=1, zorder=0)
else:
ax.plot(ipot, Nmodel, 'r-', lw=0.2, zorder=0)
else:
if len(pars) == 1:
ax.plot(xvals, Nmodel, 'r.-', lw=1, zorder=0)
else:
ax.plot(xvals, Nmodel, 'r-', lw=0.2, zorder=0)
if use_ipot:
ax.set_xlabel('Ionization potential (eV)')
ax.set_xlim(ipot[0] - 1, ipot[-1] + 1)
else:
ax.set_xlim(-0.5, xvals[-1] + 0.5)
ax.set_xticks([])
ax.set_ylabel(r'$\log_{10}\ N$')
fig.tight_layout()
#return fig, ax
return fig
print dont_use
for tr in dont_use:
if tr in trans:
trans.remove(tr)
print 'Using these transitions'
print trans
if 1:
################################################################
# Read the cloudy grids and make the interpolators
################################################################
tr_plot = ('MgI CaII OI OII OIII OIV MgII FeII FeIII SiII AlII CII AlIII '
'NI NII NIII NIV SiIII SII SIV SV '
'SiIV CIII CIV NV OVI').split()
ipot = [get_ionization_energy(t) for t in tr_plot]
isort = np.argsort(ipot)
tr_plot = [tr_plot[i] for i in isort]
assert all(tr in tr_plot for tr in trans)
Ncloudy, Ncloudy_raw, Models, aUV = make_interpolators_uvbtilt(
tr_plot, simnames)
M = Models[0]
if 0 and testing:
# check they look ok
nrows, ncols = get_nrows_ncols(len(trans) * 2)
fig = pl.figure(figsize=(8.4, 8.4))
Z = np.linspace(M.Z[0], M.Z[-1], 100)
nH = np.linspace(M.nH[0], M.nH[-1], 101)
nH1, Z1 = np.meshgrid(nH, Z, indexing='ij')
