y_axis = np.linspace(0,len(data_skyloc_thetajn_dist)/float(len(data_skyloc_thetajn_dist)),num=len(data_skyloc_thetajn_dist)) plt.step(data_skyloc_thetajn_dist,y_axis,label='skyloc_thetajn_dist (KS: %1.2e)' % ks_val,linestyle=ls_keys[0],color=color_vals[0]) color_vals.append(color_vals.pop(0)) y_axis = np.linspace(0,len(data_none)/float(len(data_none)),num=len(data_none)) plt.step(data_none,y_axis,label='none',color=color_vals[0],linestyle=ls_keys[0]) color_vals.append(color_vals.pop(0)) if param == "mc": plt.semilogx() if i % len(param1) == 1: plt.ylabel('Cumulative Fraction') else: plt.gca().set_yticklabels([]) plt.xlim(0, common.range_from_param(param)) plt.ylim(0, 1) plt.grid() #plt.legend(loc=4,fontsize=10) # Add normalized axis """ if i == 1: ax2 = plt.twiny() ax2.set_xlim(0, 1) plt.xlabel('{0} normalized interval'.format(param)) """ if j == 0: plt.xlabel(common.LABELS[param]) plt.gca().xaxis.set_label_position('top')
plt.step(data_none,y_axis,label='none',color=color_vals[0],linestyle=ls_keys[0]) color_vals.append(color_vals.pop(0)) if param1 == "mc" or param2 == "mc": plt.semilogx() if i % num_plots == 1: plt.ylabel('Cumulative Fraction') ticks = plt.gca().yaxis.get_major_ticks() if j != 0: ticks[5].label1.set_visible(False) else: plt.gca().set_yticklabels([]) if arg.absolute_scale: plt.xlim(0, common.range_from_param(param1) * common.range_from_param(param2)) plt.ylim(0, 1) plt.grid() #plt.legend(loc=4,fontsize=10) # Add normalized axis #if i == 1: #ax2 = plt.twiny() #ax2.set_xlim(0, 1) #plt.xlabel('{0} normalized interval'.format(param)) if j == 0: plt.xlabel(common.LABELS[param1] + ', ' + common.LABELS[param2]) # FIX ME plt.gca().xaxis.set_label_position('top') if j == (ntypes-1):