#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: mask = od > o sig68 = pztls.Sigma68(dz[mask]) err_sig68 = pztls.errsigma68(dz[mask]) plt.errorbar(eff[i], 100 * sig68, 100 * err_sig68, 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.ylabel(estim_label['sigma']) plt.xlim(xmin = 100, xmax = 0) plt.ylim(ymin = 0., ymax = val_max['sigma']) plt.yticks(ytick['sigma']) plt.axhline(val_req['sigma'], lw = 0.5, ls = 'solid', color = 'black') plt.grid() ax = plt.subplot(gs1[2]) i = 0 for o in od_cut:
mycolors = tools.spectral(n_od, 0.2, 1.0)
i_od = 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: