Python astropy.units 模块，Hz() 实例源码

def integrated_luminosities(self,out ,all_nus_rest, nuLnus4plotting):

        """
        Calculates the integrated luminosities for 
        all model templates chosen by the user in out['intlum_models'], 
        within the integration ranges given by out['intlum_freqranges'].

        ##input: 
        - settings dictionary out[]
        - all_nus_rest
        - nuLnus4plotting: nu*luminosities for the four models corresponding
                            to each element of the total chain
        """

        SBnuLnu, BBnuLnu, GAnuLnu, TOnuLnu, TOTALnuLnu, BBnuLnu_deredd =nuLnus4plotting
        out['intlum_freqranges'] = (out['intlum_freqranges']*out['intlum_freqranges_unit']).to(u.Hz, equivalencies=u.spectral())
        int_lums = []
        for m in range(len(out['intlum_models'])):

            if out['intlum_models'][m] == 'sb':    
                nuLnu= SBnuLnu
            elif out['intlum_models'][m] == 'bbb':    
                nuLnu= BBnuLnu
            elif out['intlum_models'][m] == 'bbbdered':    
                nuLnu=BBnuLnu_deredd
            elif out['intlum_models'][m] == 'gal':    
                 nuLnu=GAnuLnu
            elif out['intlum_models'][m] == 'tor':    
                 nuLnu=TOnuLnu

            index  = ((all_nus_rest >= np.log10(out['intlum_freqranges'][m][1].value)) & (all_nus_rest<= np.log10(out['intlum_freqranges'][m][0].value)))            
            all_nus_rest_int = 10**(all_nus_rest[index])
            Lnu = nuLnu[:,index] / all_nus_rest_int
            Lnu_int = scipy.integrate.trapz(Lnu, x=all_nus_rest_int)
            int_lums.append(Lnu_int)

        return np.array(int_lums)

def test_from_fnu(self):
        fluxd = 6.161081515869728 * u.mJy
        nu = 2.998e14 / 11.7 * u.Hz
        aper = 1 * u.arcsec
        eph = dict(rh=1.5 * u.au, delta=1.0 * u.au)
        S = 1.711e14 * u.Jy
        afrho = Afrho.from_fluxd(nu, fluxd, aper, eph, S=S)
        assert np.isclose(afrho.cm, 1000.0)

def test_from_fnu(self):
        fluxd = 6.0961896974549115 * u.mJy
        nu = 2.998e14 / 11.7 * u.Hz
        aper = 1 * u.arcsec
        eph = dict(rh=1.5 * u.au, delta=1.0 * u.au)
        S = 1.711e14 * u.Jy
        efrho = Efrho.from_fluxd(nu, fluxd, aper, eph)
        assert np.isclose(efrho.cm, 33.0)

def SED_plotting_settings(x, ydata):

    """
    This function produces the setting for the figures for SED plotting.
    **Input:
    - all nus, and data (to make the plot limits depending on the data)
    """
    fig = plt.figure()
    ax1 = fig.add_subplot(111)
    ax2 = ax1.twiny()

    #-- Latex -------------------------------------------------
    rc('text', usetex=True)
    rc('font', family='serif')
    rc('axes', linewidth=1.5)
    #-------------------------------------------------------------

    #    ax1.set_title(r"\textbf{SED of Type 2}" + r"\textbf{ AGN }"+ "Source Nr. "+ source + "\n . \n . \n ." , fontsize=17, color='k')    
    ax1.set_xlabel(r'rest-frame $\mathbf{log \  \nu} [\mathtt{Hz}] $', fontsize=13)
    ax2.set_xlabel(r'$\mathbf{\lambda} [\mathtt{\mu m}] $', fontsize=13)
    ax1.set_ylabel(r'$\mathbf{\nu L(\nu) [\mathtt{erg \ } \mathtt{ s}^{-1}]}$',fontsize=13)

    ax1.tick_params(axis='both',reset=False,which='major',length=8,width=1.5)
    ax1.tick_params(axis='both',reset=False,which='minor',length=4,width=1.5)

    ax1.set_autoscalex_on(True) 
    ax1.set_autoscaley_on(True) 
    ax1.set_xscale('linear')
    ax1.set_yscale('log')


    mediandata = np.median(ydata)
    ax1.set_ylim(mediandata /50.,mediandata * 50.)

    ax2.set_xscale('log')
    ax2.set_yscale('log')
    ax2.set_ylim( mediandata /50., mediandata * 50.)


    ax2.get_xaxis().set_major_formatter(ticker.ScalarFormatter())
    ax2.tick_params(axis='both',reset=False,which='major',length=8,width=1.5)
    ax2.tick_params(axis='both',reset=False,which='minor',length=4,width=1.5)

    x2 = (2.98e14/ x)[::-1] # Wavelenght axis

    ax2.plot(x2, np.ones(len(x2)), alpha=0)
    ax2.invert_xaxis()
    ax2.set_xticks([100., 10.,1., 0.1]) 


    return fig, ax1, ax2