nugrid_set.py 文件源码

def set_plot_core_lum_relation(self,symb='o',linestyle='--',sparsity=500,label=''):

        '''
            Plots the core luminosity relation. Mean core mass
            from first TP till last TP in model steps of sparsity
            Mean lum derived first TP to last TP in model steps of sparsity
            time-weighted averages
        '''


                m=self.run_historydata
        core_mean=[]
        lum=[]
                for case in m:
                peak_lum_model,h1_mass_min_DUP_model=case.find_TP_attributes(t0_model=case.find_first_TP(),fig=3, color='r', marker_type='o')
            modelrange=range(int(peak_lum_model[0]),int(peak_lum_model[-1]+sparsity),int(sparsity))
            core_mean1=[]
            lum1=[]
            #weight for mean value
            ages=case.get('star_age')
            weight_sum=0.
            for h in range(len(modelrange)):
                mod=modelrange[h]
                if h==0:
                    weight=(ages[modelrange[h+1]] - ages[mod])/2.
                elif h == len(modelrange)-1:
                    weight=(ages[mod]-ages[modelrange[h-1]])/2.
                else:
                    weight=(ages[modelrange[h+1]] - ages[mod])/2. + (ages[mod]-ages[modelrange[h-1]])/2.
                weight_sum+=weight

                core_mean1.append(case.get('h1_boundary_mass')[mod]*weight)
                lum1.append(case.get('log_L')[mod]*weight)

            core_mean.append(sum(core_mean1)/weight_sum)
            lum.append(sum(lum1)/weight_sum)

        plt.plot(core_mean,lum,marker=symb,linestyle=linestyle,label=label)
        print core_mean,lum
        plt.xlabel("M/M$_{\odot}$")
        plt.ylabel('log L/L$_{\odot}$')