ax = fig.add_subplot(jj)
ax.set_xlim(xmin, xmax)
ax.set_ylim(ymin, ymax)
ax.set_xlabel(xtit, fontsize=fs)
ax.set_ylabel(ytit, fontsize=fs)
ax.tick_params(labelsize=13)
start, end = ax.get_xlim()
ax.xaxis.set_ticks(np.arange(start, end, 1.))
ax.xaxis.set_ticks(np.arange(start, end, 0.2), minor=True)
ax.xaxis.set_major_formatter(ticker.FormatStrFormatter('%0.1f'))
ax.text(40.1, -1.3, zleg[iz])
# Plot the observations O2_3728-VVDSWIDEI21.5-z1.234.txt
ox, oy, el, eh = jc.read_jc_indlf(obs_dir,
zz,
h0=obsh0,
line='O2_3728',
survey=obsnom,
band=obands)
if hasattr(ox, "__len__"):
ax.errorbar(ox,
oy,
yerr=[el, eh],
fmt='o',
ecolor='grey',
color='grey',
mec='grey')
# Plot the model predictions
for index in range(len(inleg1)):
py1 = 0.
py1 = lf_ext[index, :]
oyr = oy[ind]
arrinds = oxr.argsort()
oxr = oxr[arrinds]
oyr = oyr[arrinds]
#if(isinstance(ox, (np.ndarray))):
# if (iz == 0):
# ax1.errorbar(ox,oy,yerr=[el,eh],fmt='o',\
# ecolor='grey',color='grey',mec='grey')
# else:
# ax.errorbar(ox,oy,yerr=[el,eh],fmt='o',\
# ecolor='grey',color='grey',mec='grey')
# Plot the observations O2_3728-*-z*.txt
for i, isurvey in enumerate(obsnom):
ox, oy, el, eh = jc.read_jc_indlf(
obs_dir+'lf_may16_comparat/individual_LF/',\
zz,h0=obsh0, line='O2_3728',\
survey=isurvey,band=obands[i])
if (isinstance(ox, (np.ndarray))):
col = cols[i + 1]
if (iz == 0):
ax1.errorbar(ox,oy,yerr=[el,eh],fmt='o',\
ecolor=col,color=col,mec=col)
else:
ax.errorbar(ox,oy,yerr=[el,eh],fmt='o',\
ecolor=col,color=col,mec=col)
## Plot Prabhakar Tiwari's LF
#if (zsnap == 41):
# oxh, oyh, oeh = np.loadtxt(obs_dir+'tiwari/OII_3728_LF_v11.dat',
# usecols=(0,1,2),unpack=True,skiprows=1)
#
oyr = oy[ind]
arrinds = oxr.argsort()
oxr = oxr[arrinds]
oyr = oyr[arrinds]
if (isinstance(ox, (np.ndarray))):
if (iz == 0):
ax1.errorbar(ox,oy,yerr=[el,eh],fmt='o',\
ecolor='grey',color='grey',mec='grey')
else:
ax.errorbar(ox,oy,yerr=[el,eh],fmt='o',\
ecolor='grey',color='grey',mec='grey')
# Plot the observations O2_3728-*-z*.txt
for i, isurvey in enumerate(obsnom):
ox, oy, el, eh = jc.read_jc_indlf(obs_dir+'individual_LF/',\
zz,h0=obsh0,\
line='O2_3728',\
survey=isurvey,band=obands[i])
if (isinstance(ox, (np.ndarray))):
col = cols[i + 1]
if (iz == 0):
ax1.errorbar(ox,oy,yerr=[el,eh],fmt='o',\
ecolor=col,color=col,mec=col)
else:
ax.errorbar(ox,oy,yerr=[el,eh],fmt='o',\
ecolor=col,color=col,mec=col)
# Plot the model predictions
for index in range(ntypes):
# Attenuated
py = 0.
py = lf_ext[index, :]