plt.yscale('symlog', linthreshy = 1.)
plt.xlim(xmin = -val_max['scatter'], xmax = val_max['scatter'])
plt.axvline(val_req['bias'], lw = 0.5, ls = 'solid', color = 'black')
plt.xticks(ytick['scatter'], fontsize = 10)
gs1 = gridspec.GridSpec(3, 1)
gs1.update(bottom = 0.05, top = 0.6, hspace=0, wspace=0)
ax = plt.subplot(gs1[0])
i = 0
for o in od_cut:
mask = od > o
bias = pztls.Median(dz[mask])
err_bias = pztls.errmedian(dz[mask])
plt.errorbar(eff[i], bias_times * bias, bias_times * err_bias, c = cmap(tls.cmapind(eff_cut[i], eff_lim, id_lim)), mec = cmap(tls.cmapind(eff_cut[i], eff_lim, id_lim)), markersize = 3, fmt = 'o')
i += 1
plt.setp( ax.get_xticklabels(), visible=False)
ax.yaxis.set_major_locator(MaxNLocator(prune = 'both'))
#plt.ticklabel_format(style='sci', axis='y', scilimits=(0,0))
plt.xlim(xmin = 100, xmax = 0)
plt.axhline(val_req['bias'], lw = 0.5, ls = 'solid', color = 'black')
plt.ylabel(estim_label['bias'])
plt.ylim(ymin = -val_max['bias'], ymax = val_max['bias'])
plt.yticks(ytick['bias'])
plt.grid()
ax = plt.subplot(gs1[1])
i = 0
for o in od_cut:
print "\nodds>",o
cat = {}
dz_all = cat_all['redshift'] - zt_all
#dz_all = (cat_all['redshift'] - zt_all) / (1 + cat_all['redshift'])
mask = od_all > o
dz = dz_all[mask]
sigma68_all = tls.Sigma68(dz)
errsigma68_all = tls.errsigma68(dz)
bias_all = tls.Median(dz)
errbias_all = tls.errmedian(dz)
comp_all, errcomp1_all, errcomp2_all = tls.Completeness(0,len(dz),len(dz_all))
out_frac_all, errout_frac1_all, errout_frac2_all = tls.out_fract(dz, sigma68_all, 3)
print "\nResults using the entire catalog:"
print "Sigma68 = %.5f +/- %.5f" %(sigma68_all,errsigma68_all)
print "Bias = %.5f +/- %.5f" %(bias_all,errbias_all)
print "Completeness = %.5f +%.5f/-%.5f" %(comp_all, errcomp1_all, errcomp2_all)
print "Outliers fraction = %.5f +%.5f/-%.5f\n" %(out_frac_all, errout_frac1_all, errout_frac2_all)
print "Generation of plots...\n"
i = 1
for l in col_list:
print " %s" % l
cat[l] = cat_all[l][mask]