def plot_SM_DM(redshift_low, redshift_high, filename):
fig, axs = plt.subplots(nrows=3,
ncols=3,
sharex=True,
sharey=True,
figsize=(9, 9))
ax = axs.reshape(-1)
normalize = 0
fig.subplots_adjust(hspace=0)
fig.subplots_adjust(wspace=0)
redshift_range = list(range(redshift_low, redshift_high))
for loop, redshift in enumerate(redshift_range):
try:
bin_centres, median, per_50, per_16, per_84, per_25, per_75 = np.loadtxt(
'./binned_data/' + filename + '_z' + str(redshift) + '.txt',
unpack=True,
comments='#')
ax[loop] = cloudpickle.load(
open('./pkl_hists/' + filename + '_z' + str(redshift) + '.pkl',
'rb'))
except IOError:
bin_centres, median, per_50, per_16, per_84, per_25, per_75, normalize = bin_data(
'SM', 'DM', ax, normalize, redshift, filename, nbins=30)
ax[loop].set_xlim([9, 11.98])
ax[loop].set_ylim([0, 9.98])
if loop == 8:
ax[loop].set_xlim([9, 12])
ax[loop].text(9.2, 0.3, "z = " + str(loop), fontsize=16)
plot_params(ax[loop], loop, 'SM', 'DM')
plot_observations(ax[loop], loop, "SM_DM")
ax[loop].plot(bin_centres,
per_50,
c='k',
zorder=10,
linewidth=2,
label='L-Galaxies')
ax[loop].plot(bin_centres, per_16, 'k--', zorder=10, linewidth=2)
ax[loop].plot(bin_centres, per_84, 'k--', zorder=10, linewidth=2)
[i.set_linewidth(2.1) for i in ax[loop].spines.values()]
pylab.savefig('./figs/' + filename + '.eps', bbox_inches=0)
fig.subplots_adjust(wspace=0)
for loop in range(0,9):
try:
bin_centres,median,per_50,per_16,per_84,per_25,per_75 = np.loadtxt('./binned_data/SM_DTG_z'+str(loop)+'.txt',unpack=True,comments='#')
ax[loop] = cloudpickle.load(open('./pkl_hists/SM_DTG_z'+str(loop)+'.pkl','rb'))
except IOError:
bin_centres,median,per_50,per_16,per_84,per_25,per_75,normalize = bin_data('SM','DTG',ax,normalize,loop,'SM_DTG',nbins=30)
ax[loop].set_xlim([8.,11.98])
ax[loop].set_ylim([-5.98,-1.])
plot_params(ax[loop],loop,'SM','DTG')
plot_observations(ax[loop],loop,"DTG_SM")
ax[loop].plot(bin_centres,per_50,c='k',zorder=10,linewidth=2,label='L-Galaxies')
ax[loop].plot(bin_centres,per_16,'k--',zorder=10,linewidth=2)
ax[loop].plot(bin_centres,per_84,'k--',zorder=10,linewidth=2)
axes = fig.get_axes()
for ax in axes:
[i.set_linewidth(2.1) for i in ax.spines.values()]
pylab.savefig('./figs/DTG_stellar.eps', bbox_inches=0)
plt.close()
normalize=0
fig.subplots_adjust(hspace=0)
fig.subplots_adjust(wspace=0)
for loop in range(0,9):
try:
bin_centres,median,per_50,per_16,per_84,per_25,per_75 = np.loadtxt('./binned_data/OX_DTM_z'+str(loop)+'.txt',unpack=True,comments='#')
ax[loop] = cloudpickle.load(open('./pkl_hists/OX_DTM_z'+str(loop)+'.pkl','rb'))
except IOError:
bin_centres,median,per_50,per_16,per_84,per_25,per_75,normalize = bin_data('OX_Z','DTM',ax,normalize,loop,'OX_DTM',nbins=30)
ax[loop].set_xlim([6.,9.98])
ax[loop].set_ylim([-2.98,1])
plot_params(ax[loop],loop,'O','DTM')
plot_observations(ax[loop],loop,"DTM_Oxy")
#ax[loop].errorbar(x_bins,y_median,yerr=(y_mederr),color='k',label='L-Galaxies Median',linewidth=2)
ax[loop].plot(bin_centres,per_50,c='k',zorder=10,linewidth=2,label='L-Galaxies')
ax[loop].plot(bin_centres,per_16,'k--',zorder=10,linewidth=2)
ax[loop].plot(bin_centres,per_84,'k--',zorder=10,linewidth=2)
axes = fig.get_axes()
for ax in axes:
[i.set_linewidth(2.1) for i in ax.spines.values()]
pylab.savefig('./figs/DTM_oxygen.eps', bbox_inches=0)
plt.close()
volume_MR = (480.279 / 0.673)**3.0
hist = hist / (volume_MR * binsize)
np.savetxt('./binned_data/DMF_z' + str(loop) + '.txt',
np.c_[bin_centers, hist])
ax[loop].set_xlim([6., 9.99])
ax[loop].set_ylim([-6., -0.02])
#if loop == 0:
# ax[loop].set_ylim([-6,0.05])
#if loop == 8:
# ax[loop].set_xlim([6.0,10.0])
plot_params(ax[loop], loop, 'DMF', 'DMF')
plot_observations(ax[loop], loop, "DMF")
ax[loop].plot(bin_centers,
np.log10(hist),
c='k',
zorder=10,
linewidth=2,
label='L-Galaxies')
ax[loop].text(8.5, -2, "z = " + str(loop), fontsize=16)
[i.set_linewidth(2.1) for i in ax[loop].spines.values()]
pylab.savefig('./figs/DMF.eps', bbox_inches=0)
plt.close()
plt.show()