示例#1
0
def gaia_spitzer_errors():
    """ Visualize the observational errors from Gaia and Spitzer, along with
        dispersion and distance scale of Sgr and Orphan. 
    """
    
    rcparams = {'lines.linestyle' : '-', 
                'lines.linewidth' : 1.,
                'lines.color' : 'k',
                'lines.marker' : None,
                'axes.edgecolor' : '#444444',
                'axes.facecolor' : '#ffffff'}
    
    sgr_color = '#67A9CF'
    orp_color = '#EF8A62'
    
    with rc_context(rc=rcparams):
        fig,axes = plt.subplots(1, 2, figsize=(12, 6), sharex=True)
        
        # vertical lines for dwarf satellites
        axes[0].vlines([24,65,80,100], 0.001, 100, color='#888888', linestyles='--', zorder=-1)
        axes[1].vlines([24,65,80,100], [0.081,0.0465,0.025,0.014], 100, color='#888888', linestyles='--', zorder=-1)
        
        # label the vertical lines
        axes[1].text(17.1, 0.075, 'Sgr -', color='#888888', rotation=0)
        axes[1].text(29.5, 0.043, 'UMi, Boo -', color='#888888', rotation=0)
        axes[1].text(58., 0.023, 'Scl -', color='#888888', rotation=0)
        axes[1].text(69.75, 0.013, 'Car -', color='#888888', rotation=0)
        
        # Distance from 1kpc to ~100kpc
        D = np.logspace(0., 2., 50)*u.kpc
        
        # Sample metallicities from: http://arxiv.org/pdf/1211.7073v1.pdf
        fe_hs = np.random.normal(-1.67, 0.3, size=50)
        fe_hs = np.append(fe_hs, np.random.normal(-2.33, 0.3, size=len(fe_hs)//5))
        
        for fe_h in fe_hs:
            # Johnson/Cousins (V - I_C) color for RR Lyrae at *minimum*
            # Guldenschuh et al. (2005 PASP 117, 721), pg. 725
            rrl_V_minus_I = np.random.normal(0.579, 0.006)
            
            # Compute the apparent magnitude as a function of distance
            M_V = rrl_M_V(fe_h=fe_h)[0]
            m_V = apparent_magnitude(M_V, D)
            
            # Distance error
            dp = parallax_error(m_V, rrl_V_minus_I).arcsecond
            dD = D.to(u.pc).value**2 * dp * u.pc
            
            # Velocity error
            dpm = proper_motion_error(m_V, rrl_V_minus_I)
            dVtan = (dpm*D).to(u.km*u.radian/u.s).value
        
            # Plot Gaia distance errors
            axes[0].loglog(D.kiloparsec, (dD/D).decompose(), color='k', alpha=0.1)
                
            # Plot tangential velocity errors
            axes[1].loglog(D.kiloparsec, dVtan, color='k', alpha=0.1)
    
        # Add spitzer 2% line to distance plot
        axes[0].axhline(0.02, linestyle='-', linewidth=3, color='k', alpha=0.75)
    
    # Now add rectangles for Sgr, Orphan
    sgr_d = Rectangle((10., 0.15), 60., 0.15, 
                      color=sgr_color, alpha=1., label='Sgr stream range')
    axes[0].add_patch(sgr_d)
    
    # From fig. 3 in http://mnras.oxfordjournals.org/content/389/3/1391.full.pdf+html
    orp_d = Rectangle((10., 0.03), 35., 0.03,
                      color=orp_color, alpha=1., label='Orp stream range')
    axes[0].add_patch(orp_d)
    
    # Dispersion from Majewski 2004: 10 km/s
    sgr_v = Rectangle((10., 10), 60., 1., color=sgr_color, alpha=1.)
    axes[1].add_patch(sgr_v)
    
    orp_v = Rectangle((10., 8.), 35., 1., color=orp_color, alpha=1.)
    axes[1].add_patch(orp_v)
    
    axes[0].set_ylim(0.003, 10)
    axes[0].set_xlim(1, 105)
    
    axes[1].set_ylim(0.01, 100)
    #axes[1].set_xlim(10, 100)
    
    axes[0].set_xlabel("Distance [kpc]")
    axes[0].set_ylabel("Frac. distance error: $\epsilon_D/D$")
    axes[1].set_ylabel("$v_{tan}$ error: $\epsilon_v$ [km/s]")
    axes[1].set_xlabel("Distance [kpc]")
    
    axes[0].set_xticklabels(["1", "10", "100"])
    
    axes[0].set_yticklabels(["{:g}".format(yt) for yt in axes[0].get_yticks()])
    axes[1].set_yticklabels(["{:g}".format(yt) for yt in axes[1].get_yticks()])
    
    # add Gaia and Spitzer text to plots
    axes[0].text(4., 0.125, 'Gaia', fontsize=16, rotation=45, fontweight='normal')
    axes[0].text(4., 0.013, 'Spitzer', fontsize=16, color="k", alpha=0.75, fontweight='normal')
    axes[1].text(4., 0.06, 'Gaia', fontsize=16, rotation=45, fontweight='normal')
    
    # add legends
    axes[0].legend(loc='upper left', fancybox=True)
    #axes[1].legend(loc='upper left', fancybox=True)
    
    axes[0].yaxis.tick_left()
    axes[1].yaxis.tick_left()
    
    fig.subplots_adjust(hspace=0.1, wspace=0.1)
    plt.tight_layout()
    plt.savefig(os.path.join(plot_path, "gaia.pdf"))
示例#2
0
def fig2(**kwargs):
    """ Visualize the observational errors from Gaia and Spitzer, along with
        dispersion and distance scale of Sgr and Orphan.
    """

    rcparams = {'lines.linestyle' : '-',
                'lines.linewidth' : 1.,
                'lines.color' : 'k',
                'lines.marker' : None,
                'axes.facecolor' : '#ffffff',
                'xtick.major.size' : 16,
                'xtick.major.width' : 1.5,
                'xtick.minor.size' : 0,
                'ytick.major.size' : 16,
                'ytick.major.width' : 1.5,
                'ytick.minor.size' : 0}

    with rc_context(rc=rcparams):
        fig,axes = plt.subplots(2, 1, figsize=(8, 10), sharex=True)

        # Distance from 1kpc to ~100kpc
        D = np.logspace(0., 2., 50)*u.kpc

        # Sample metallicities from: http://arxiv.org/pdf/1211.7073v1.pdf
        fe_h = -1.67

        # Johnson/Cousins (V - I_C) color for RR Lyrae at *minimum*
        # Guldenschuh et al. (2005 PASP 117, 721), pg. 725
        rrl_V_minus_I = np.random.normal(0.579, 0.006)

        # Compute the apparent magnitude as a function of distance
        M_V = rrl_M_V(fe_h=fe_h)[0]
        m_V = apparent_magnitude(M_V, D)

        # Distance error
        dp = parallax_error(m_V, rrl_V_minus_I).to(u.arcsecond).value
        dD = D.to(u.pc).value**2 * dp * u.pc

        # Velocity error
        dpm = proper_motion_error(m_V, rrl_V_minus_I)
        dVtan = (dpm*D).to(u.km*u.radian/u.s).value
        #dVtan = (D*dpm + dD*1.*u.mas/u.yr).to(u.km*u.radian/u.s).value

        # Plot Gaia distance errors
        fracDist = (dD/D).decompose().value
        fracDist[fracDist > 0.1] = 0.1
        axes[0].loglog(D.to(u.kpc).value, fracDist, color='#000000', alpha=1., linewidth=4.)

        # Plot tangential velocity errors
        axes[1].loglog(D.to(u.kpc).value, dVtan, color='#000000', alpha=1., linewidth=4.)

        # Add spitzer 2% line to distance plot
        axes[0].axhline(0.02, linestyle='--', linewidth=3, color='k', alpha=0.75)

    # Now add rectangles for Sgr, Orphan
    sgr_d = Rectangle((10., 0.15), 60., 0.15,
                      color=sgr_color, alpha=0.75, label='Sgr stream')
    axes[0].add_patch(sgr_d)

    # From fig. 3 in http://mnras.oxfordjournals.org/content/389/3/1391.full.pdf+html
    orp_d = Rectangle((10., 0.03), 35., 0.03,
                      color=orp_color, alpha=0.75, label='Orp stream')
    axes[0].add_patch(orp_d)

    # Dispersion from Majewski 2004: 10 km/s
    sgr_v = Rectangle((10., 10), 60., 1., alpha=0.75, color=sgr_color)
    axes[1].add_patch(sgr_v)

    orp_v = Rectangle((10., 8.), 35., 1., alpha=0.75, color=orp_color)
    axes[1].add_patch(orp_v)

    axes[0].set_ylim(0.003, 1.3)
    axes[0].set_xlim(1, 100)
    axes[1].set_ylim(0.06, 130)

    axes[0].set_yticklabels([])
    axes[1].set_yticklabels([])
    axes[1].set_xticklabels([])

    axes[0].yaxis.tick_left()
    axes[0].xaxis.tick_bottom()
    axes[1].yaxis.tick_left()
    axes[1].xaxis.tick_bottom()

    plt.tight_layout()
    #fig.subplots_adjust(hspace=0.05)
    fig.savefig(os.path.join(plot_path, "fig2.pdf"))