def plot_mf_z(plt, outdir, snap, vol_eagle, histmtot, histm30, histmgas, histmall): ########################### total stellar mass function xtit = "$\\rm log_{10} (\\rm M_{\\star,\\rm tot}/M_{\odot})$" ytit = "$\\rm log_{10}(\Phi/dlog{\\rm M_{\\star}}/{\\rm Mpc}^{-3} )$" xmin, xmax, ymin, ymax = 7, 12, -6, 1 xleg = xmax - 0.2 * (xmax - xmin) yleg = ymax - 0.1 * (ymax - ymin) fig = plt.figure(figsize=(5, 10)) idx = [0, 1, 2] zins = [0, 1, 2] subplots = [311, 312, 313] sn, subgn, mstot, ms30, mgas30, mdm30, mbh30 = common.load_observation( '/fred/oz009/clagos/EAGLE/L0025N0376/REFERENCE/data/', 'SUBFIND-EAGLE-DATABASE.data', [2, 1, 29, 22, 23, 31, 32]) mall = ms30 + mgas30 + mdm30 + mbh30 for subplot, idx, z, s in zip(subplots, idx, zins, snap): ax = fig.add_subplot(subplot) if (idx == 2): xtitplot = xtit else: xtitplot = ' ' common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtitplot, ytit, locators=(0.1, 1, 0.1)) ax.text(xleg, yleg, 'z=%s' % (str(z))) #SMF from SUBFIND ind = np.where((mstot > 0) & (sn == s)) H, bins_edges = np.histogram(np.log10(mstot[ind]), bins=np.append(mbins, mupp)) histsfof = H y = histsfof[:] ind = np.where(y != 0.) if idx == 0: ax.plot(xmf[ind], np.log10(y[ind] / vol_eagle / dm), 'b', label='EAGLE L25') if idx > 0: ax.plot(xmf[ind], np.log10(y[ind] / vol_eagle / dm), 'b') #Predicted HMF y = histmtot[idx, :] ind = np.where(y != 0.) if idx == 0: ax.plot(xmf[ind], y[ind], 'r', linestyle='dashed', label='VR') if idx > 0: ax.plot(xmf[ind], y[ind], 'r', linestyle='dashed') if idx == 0: common.prepare_legend(ax, ['b', 'r']) common.savefig(outdir, fig, "smf_tot_z.pdf") ############################# stellar mass function (30kpc aperture) xtit = "$\\rm log_{10} (\\rm M_{\\star,\\rm 30kpc}/M_{\odot})$" ytit = "$\\rm log_{10}(\Phi/dlog{\\rm M_{\\star}}/{\\rm Mpc}^{-3} )$" xmin, xmax, ymin, ymax = 7, 12, -6, 1 xleg = xmax - 0.2 * (xmax - xmin) yleg = ymax - 0.1 * (ymax - ymin) fig = plt.figure(figsize=(5, 10)) idx = [0, 1, 2] zins = [0, 1, 2] subplots = [311, 312, 313] for subplot, idx, z, s in zip(subplots, idx, zins, snap): ax = fig.add_subplot(subplot) if (idx == 2): xtitplot = xtit else: xtitplot = ' ' common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtitplot, ytit, locators=(0.1, 1, 0.1)) ax.text(xleg, yleg, 'z=%s' % (str(z))) #SMF from SUBFIND ind = np.where((ms30 > 0) & (sn == s)) H, bins_edges = np.histogram(np.log10(ms30[ind]), bins=np.append(mbins, mupp)) histsfof = H y = histsfof[:] ind = np.where(y != 0.) if idx == 0: ax.plot(xmf[ind], np.log10(y[ind] / vol_eagle / dm), 'b', label='EAGLE L25') if idx > 0: ax.plot(xmf[ind], np.log10(y[ind] / vol_eagle / dm), 'b') #Predicted HMF y = histm30[idx, :] ind = np.where(y != 0.) if idx == 0: ax.plot(xmf[ind], y[ind], 'r', linestyle='dashed', label='VR') if idx > 0: ax.plot(xmf[ind], y[ind], 'r', linestyle='dashed') if idx == 0: common.prepare_legend(ax, ['b', 'r']) common.savefig(outdir, fig, "smf_30kpc_z.pdf") ############################# gas mass function (30kpc aperture) xtit = "$\\rm log_{10} (\\rm M_{\\rm gas, 30kpc}/M_{\odot})$" ytit = "$\\rm log_{10}(\Phi/dlog{\\rm M_{\\rm gas}}/{\\rm Mpc}^{-3} )$" xmin, xmax, ymin, ymax = 7, 12, -6, 1 xleg = xmax - 0.2 * (xmax - xmin) yleg = ymax - 0.1 * (ymax - ymin) fig = plt.figure(figsize=(5, 10)) idx = [0, 1, 2] zins = [0, 1, 2] subplots = [311, 312, 313] for subplot, idx, z, s in zip(subplots, idx, zins, snap): ax = fig.add_subplot(subplot) if (idx == 2): xtitplot = xtit else: xtitplot = ' ' common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtitplot, ytit, locators=(0.1, 1, 0.1)) ax.text(xleg, yleg, 'z=%s' % (str(z))) #SMF from SUBFIND ind = np.where((mgas30 > 0) & (sn == s)) H, bins_edges = np.histogram(np.log10(mgas30[ind]), bins=np.append(mbins, mupp)) histsfof = H y = histsfof[:] ind = np.where(y != 0.) if idx == 0: ax.plot(xmf[ind], np.log10(y[ind] / vol_eagle / dm), 'b', label='EAGLE L25') if idx > 0: ax.plot(xmf[ind], np.log10(y[ind] / vol_eagle / dm), 'b') #Predicted HMF y = histmgas[idx, :] ind = np.where(y != 0.) if idx == 0: ax.plot(xmf[ind], y[ind], 'r', linestyle='dashed', label='VR') if idx > 0: ax.plot(xmf[ind], y[ind], 'r', linestyle='dashed') if idx == 0: common.prepare_legend(ax, ['b', 'r']) common.savefig(outdir, fig, "gasmf_30kpc_z.pdf") ##################################### total mass function (30kpc aperture) xtit = "$\\rm log_{10} (\\rm M_{\\rm tot, 30kpc}/M_{\odot})$" ytit = "$\\rm log_{10}(\Phi/dlog{\\rm M_{\\rm ror}}/{\\rm Mpc}^{-3} )$" xmin, xmax, ymin, ymax = 7, 14, -6, 1 xleg = xmax - 0.2 * (xmax - xmin) yleg = ymax - 0.1 * (ymax - ymin) fig = plt.figure(figsize=(5, 10)) idx = [0, 1, 2] zins = [0, 1, 2] subplots = [311, 312, 313] for subplot, idx, z, s in zip(subplots, idx, zins, snap): ax = fig.add_subplot(subplot) if (idx == 2): xtitplot = xtit else: xtitplot = ' ' common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtitplot, ytit, locators=(0.1, 1, 0.1)) ax.text(xleg, yleg, 'z=%s' % (str(z))) #SMF from SUBFIND ind = np.where((mall > 0) & (sn == s)) H, bins_edges = np.histogram(np.log10(mall[ind]), bins=np.append(mbins, mupp)) histsfof = H y = histsfof[:] ind = np.where(y != 0.) if idx == 0: ax.plot(xmf[ind], np.log10(y[ind] / vol_eagle / dm), 'b', label='EAGLE L25') if idx > 0: ax.plot(xmf[ind], np.log10(y[ind] / vol_eagle / dm), 'b') #Predicted HMF y = histmall[idx, :] ind = np.where(y != 0.) if idx == 0: ax.plot(xmf[ind], y[ind], 'r', linestyle='dashed', label='VR') if idx > 0: ax.plot(xmf[ind], y[ind], 'r', linestyle='dashed') if idx == 0: common.prepare_legend(ax, ['b', 'r']) common.savefig(outdir, fig, "allmassmf_30kpc_z.pdf")
def load_observation(self, *args, **kwargs): obsdir = os.path.normpath( os.path.abspath(os.path.join(__file__, '..', '..', 'data'))) return common.load_observation(obsdir, *args, **kwargs)
def plot_bulge_BH(plt, outdir, obsdir, BH): fig = plt.figure(figsize=(5, 4.5)) xtit = "$\\rm log_{10} (\\rm M_{\\rm bulge}/M_{\odot})$" ytit = "$\\rm log_{10} (\\rm M_{\\rm BH}/M_{\odot})$" xmin, xmax, ymin, ymax = 8, 13, 5, 11 xleg = xmax - 0.2 * (xmax - xmin) yleg = ymax - 0.1 * (ymax - ymin) ax = fig.add_subplot(111) plt.subplots_adjust(bottom=0.15, left=0.15) common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtit, ytit, locators=(0.1, 1, 0.1)) ax.text(xleg, yleg, 'z=0') #Predicted SMHM ind = np.where(BH[0, 0, :] != 0) if (len(xmf[ind]) > 0): xplot = xmf[ind] yplot = BH[0, 0, ind] errdn = BH[0, 1, ind] errup = BH[0, 2, ind] ax.plot(xplot, yplot[0], color='k', label="Shark") ax.fill_between(xplot, yplot[0], yplot[0] - errdn[0], facecolor='grey', interpolate=True) ax.fill_between(xplot, yplot[0], yplot[0] + errup[0], facecolor='grey', interpolate=True) MBH_othermodels = common.load_observation( obsdir, 'Models/SharkVariations/BHBulgeRelation_OtherModels.dat', [0]) MBH_f_smbh0p008 = MBH_othermodels[0:29] MBH_f_smbh0p00008 = MBH_othermodels[30:60] ind = np.where(MBH_f_smbh0p008 != 0) xplot = xmf[ind] yplot = MBH_f_smbh0p008[ind] ax.plot(xplot, yplot, color='Goldenrod', linestyle='dashed', label='$f_{\\rm smbh}=8 \\times 10^{-3}$') ind = np.where(MBH_f_smbh0p00008 != 0) xplot = xmf[ind] yplot = MBH_f_smbh0p00008[ind] ax.plot(xplot, yplot, color='Orange', linestyle='dotted', label='$f_{\\rm smbh}=8 \\times 10^{-5}$') #BH-bulge relation mBH_M13, errup_M13, errdn_M13, mBH_power, mbulge_M13 = common.load_observation( obsdir, 'BHs/MBH_sigma_Mbulge_McConnelMa2013.dat', [0, 1, 2, 3, 7]) ind = np.where((mBH_M13 > 0) & (mbulge_M13 > 0)) xobs = np.log10(mbulge_M13[ind]) yobs = np.log10(mBH_M13[ind] * pow(10.0, mBH_power[ind])) lerr = np.log10( (mBH_M13[ind] - errdn_M13[ind]) * pow(10.0, mBH_power[ind])) herr = np.log10( (mBH_M13[ind] + errup_M13[ind]) * pow(10.0, mBH_power[ind])) ax.errorbar(xobs, yobs, yerr=[yobs - lerr, herr - yobs], ls='None', mfc='None', ecolor='r', mec='r', marker='^', label="McConnell & Ma 2013") #BH-bulge relation mBH_H04, errup_H04, errdn_H04, mbulge_H04 = common.load_observation( obsdir, 'BHs/MBH_sigma_Mbulge_HaeringRix2004.dat', [0, 1, 2, 4]) xobs = np.log10(mbulge_H04) yobs = xobs * 0. - 999. indx = np.where(mBH_H04 > 0) yobs[indx] = np.log10(mBH_H04[indx]) lerr = yobs * 0. - 999. indx = np.where((mBH_H04 - errdn_H04) > 0) lerr[indx] = np.log10(mBH_H04[indx] - errdn_H04[indx]) herr = yobs * 0. + 999. indx = np.where((mBH_H04 + errup_H04) > 0) herr[indx] = np.log10(mBH_H04[indx] + errup_H04[indx]) ax.errorbar(xobs, yobs, yerr=[yobs - lerr, herr - yobs], ls='None', mfc='None', ecolor='maroon', mec='maroon', marker='s', label="Haering+04") common.prepare_legend(ax, ['k', 'Goldenrod', 'Orange', 'r', 'maroon'], loc=2) common.savefig(outdir, fig, 'bulge-BH.pdf')
def plot_scaling_z(plt, outdir, snap, SFRMstar, R50Mstar, R50Mstar30, MBHMstar, SigmaMstar30, ZstarMstar, ZSFMstar, AgeSMstar, SFRMstar30, R50pMstar30, ZNSFMstar): bin_it = functools.partial(us.wmedians, xbins=xmf) ########################### will plot main sequence for all stellar particles in the subhalo xtit = "$\\rm log_{10} (\\rm M_{\\star, tot}/M_{\odot})$" ytit = "$\\rm log_{10}(\\rm SFR/M_{\odot} yr^{-1})$" xmin, xmax, ymin, ymax = 7, 12, -5, 1.5 xleg = xmax - 0.2 * (xmax - xmin) yleg = ymax - 0.1 * (ymax - ymin) fig = plt.figure(figsize=(5, 10)) idx = [0, 1, 2] zins = [0, 1, 2] subplots = [311, 312, 313] sn, mstot, sfr, r50, ms30, sfr30 = common.load_observation( '/fred/oz009/clagos/EAGLE/L0025N0376/REFERENCE/data/', 'SUBFIND-EAGLE-DATABASE.data', [2, 29, 30, 26, 22, 24]) for subplot, idx, z, s in zip(subplots, idx, zins, snap): ax = fig.add_subplot(subplot) if (idx == 2): xtitplot = xtit else: xtitplot = ' ' common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtitplot, ytit, locators=(0.1, 1, 0.1)) ax.text(xleg, yleg, 'z=%s' % (str(z))) #from SUBFIND ind = np.where((mstot > 0) & (sn == s) & (sfr > 0)) rplot = bin_it(x=np.log10(mstot[ind]), y=np.log10(sfr[ind])) ind = np.where(rplot[0, :] != 0.) xplot = xmf[ind] yplot = rplot[0, ind] errdn = rplot[1, ind] errup = rplot[2, ind] if idx == 0: ax.plot(xplot, yplot[0], 'b', linestyle='dashed', label='EAGLE L25') if idx > 0: ax.plot(xplot, yplot[0], 'b', linestyle='dashed') ax.fill_between(xplot, yplot[0], yplot[0] - errdn[0], facecolor='b', alpha=0.2, interpolate=True) ax.fill_between(xplot, yplot[0], yplot[0] + errup[0], facecolor='b', alpha=0.2, interpolate=True) #VR ind = np.where(SFRMstar[idx, 0, :] != 0.) xplot = xmf[ind] yplot = SFRMstar[idx, 0, ind] errdn = SFRMstar[idx, 1, ind] errup = SFRMstar[idx, 2, ind] if idx == 0: ax.plot(xplot, yplot[0], 'r', label='VR') if idx > 0: ax.plot(xplot, yplot[0], 'r') ax.fill_between(xplot, yplot[0], yplot[0] - errdn[0], facecolor='r', alpha=0.2, interpolate=True) ax.fill_between(xplot, yplot[0], yplot[0] + errup[0], facecolor='r', alpha=0.2, interpolate=True) if idx == 0: common.prepare_legend(ax, ['b', 'r']) common.savefig(outdir, fig, "main_sequence_z.pdf") ########################### will plot main sequence for 30kpc aperture xtit = "$\\rm log_{10} (\\rm M_{\\star, 30kpc}/M_{\odot})$" ytit = "$\\rm log_{10}(\\rm SFR_{\\rm 30kpc}/M_{\odot} yr^{-1})$" xmin, xmax, ymin, ymax = 7, 12, -5, 1.5 xleg = xmax - 0.2 * (xmax - xmin) yleg = ymax - 0.1 * (ymax - ymin) fig = plt.figure(figsize=(5, 10)) idx = [0, 1, 2] zins = [0, 1, 2] subplots = [311, 312, 313] for subplot, idx, z, s in zip(subplots, idx, zins, snap): ax = fig.add_subplot(subplot) if (idx == 2): xtitplot = xtit else: xtitplot = ' ' common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtitplot, ytit, locators=(0.1, 1, 0.1)) ax.text(xleg, yleg, 'z=%s' % (str(z))) #from SUBFIND ind = np.where((ms30 > 0) & (sn == s) & (sfr30 > 0)) rplot = bin_it(x=np.log10(ms30[ind]), y=np.log10(sfr30[ind])) ind = np.where(rplot[0, :] != 0.) xplot = xmf[ind] yplot = rplot[0, ind] errdn = rplot[1, ind] errup = rplot[2, ind] if idx == 0: ax.plot(xplot, yplot[0], 'b', linestyle='dashed', label='EAGLE L25') if idx > 0: ax.plot(xplot, yplot[0], 'b', linestyle='dashed') ax.fill_between(xplot, yplot[0], yplot[0] - errdn[0], facecolor='b', alpha=0.2, interpolate=True) ax.fill_between(xplot, yplot[0], yplot[0] + errup[0], facecolor='b', alpha=0.2, interpolate=True) #VR ind = np.where(SFRMstar30[idx, 0, :] != 0.) xplot = xmf[ind] yplot = SFRMstar30[idx, 0, ind] errdn = SFRMstar30[idx, 1, ind] errup = SFRMstar30[idx, 2, ind] if idx == 0: ax.plot(xplot, yplot[0], 'r', label='VR') if idx > 0: ax.plot(xplot, yplot[0], 'r') ax.fill_between(xplot, yplot[0], yplot[0] - errdn[0], facecolor='r', alpha=0.2, interpolate=True) ax.fill_between(xplot, yplot[0], yplot[0] + errup[0], facecolor='r', alpha=0.2, interpolate=True) if idx == 0: common.prepare_legend(ax, ['b', 'r']) common.savefig(outdir, fig, "main_sequence_30kpc_z.pdf") ########################### will plot r50 vs stellar mass for all stellar particles in the subhalo xtit = "$\\rm log_{10} (\\rm M_{\\star,tot}/M_{\odot})$" ytit = "$\\rm log_{10}(\\rm R_{\\rm 50}/pMpc)$" xmin, xmax, ymin, ymax = 7, 12, -3.3, -1 xleg = xmax - 0.2 * (xmax - xmin) yleg = ymax - 0.1 * (ymax - ymin) fig = plt.figure(figsize=(5, 10)) idx = [0, 1, 2] zins = [0, 1, 2] subplots = [311, 312, 313] for subplot, idx, z, s in zip(subplots, idx, zins, snap): ax = fig.add_subplot(subplot) if (idx == 2): xtitplot = xtit else: xtitplot = ' ' common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtitplot, ytit, locators=(0.1, 1, 0.1)) plt.subplots_adjust(left=0.2) ax.text(xleg, yleg, 'z=%s' % (str(z))) #from SUBFIND ind = np.where((mstot > 0) & (sn == s) & (r50 > 0)) rplot = bin_it(x=np.log10(mstot[ind]), y=np.log10(r50[ind]) - 3.0) ind = np.where(rplot[0, :] != 0.) xplot = xmf[ind] yplot = rplot[0, ind] errdn = rplot[1, ind] errup = rplot[2, ind] if idx == 0: ax.plot(xplot, yplot[0], 'b', linestyle='dashed', label='EAGLE L25') if idx > 0: ax.plot(xplot, yplot[0], 'b', linestyle='dashed') ax.fill_between(xplot, yplot[0], yplot[0] - errdn[0], facecolor='b', alpha=0.2, interpolate=True) ax.fill_between(xplot, yplot[0], yplot[0] + errup[0], facecolor='b', alpha=0.2, interpolate=True) #VR ind = np.where(R50Mstar[idx, 0, :] != 0.) xplot = xmf[ind] yplot = R50Mstar[idx, 0, ind] errdn = R50Mstar[idx, 1, ind] errup = R50Mstar[idx, 2, ind] if idx == 0: ax.plot(xplot, yplot[0], 'r', label='VR') if idx > 0: ax.plot(xplot, yplot[0], 'r') ax.fill_between(xplot, yplot[0], yplot[0] - errdn[0], facecolor='r', alpha=0.2, interpolate=True) ax.fill_between(xplot, yplot[0], yplot[0] + errup[0], facecolor='r', alpha=0.2, interpolate=True) if idx == 0: common.prepare_legend(ax, ['b', 'r']) common.savefig(outdir, fig, "r50_Mstar_z.pdf") ################## will plot r50 vs stellar mass for quantities measured within 30kpc sn, mstot, sfr, r50, r50p = common.load_observation( '/fred/oz009/clagos/EAGLE/L0025N0376/REFERENCE/data/', 'SUBFIND-EAGLE-DATABASE-REF.data', [2, 22, 30, 33, 34]) xtit = "$\\rm log_{10} (\\rm M_{\\star,30kpc}/M_{\odot})$" ytit = "$\\rm log_{10}(\\rm R_{\\rm 50,30kpc}/pMpc)$" xmin, xmax, ymin, ymax = 7, 12, -3.3, -1 xleg = xmax - 0.2 * (xmax - xmin) yleg = ymax - 0.1 * (ymax - ymin) fig = plt.figure(figsize=(5, 10)) idx = [0, 1, 2] zins = [0, 1, 2] subplots = [311, 312, 313] for subplot, idx, z, s in zip(subplots, idx, zins, snap): ax = fig.add_subplot(subplot) if (idx == 2): xtitplot = xtit else: xtitplot = ' ' common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtitplot, ytit, locators=(0.1, 1, 0.1)) plt.subplots_adjust(left=0.2) ax.text(xleg, yleg, 'z=%s' % (str(z))) #from SUBFIND ind = np.where((mstot > 0) & (sn == s) & (r50 > 0)) rplot = bin_it(x=np.log10(mstot[ind]), y=np.log10(r50[ind]) - 3.0) ind = np.where(rplot[0, :] != 0.) xplot = xmf[ind] yplot = rplot[0, ind] errdn = rplot[1, ind] errup = rplot[2, ind] if idx == 0: ax.plot(xplot, yplot[0], 'b', linestyle='dashed', label='EAGLE L25') if idx > 0: ax.plot(xplot, yplot[0], 'b', linestyle='dashed') ax.fill_between(xplot, yplot[0], yplot[0] - errdn[0], facecolor='b', alpha=0.2, interpolate=True) ax.fill_between(xplot, yplot[0], yplot[0] + errup[0], facecolor='b', alpha=0.2, interpolate=True) #VR ind = np.where(R50Mstar30[idx, 0, :] != 0.) xplot = xmf[ind] yplot = R50Mstar30[idx, 0, ind] errdn = R50Mstar30[idx, 1, ind] errup = R50Mstar30[idx, 2, ind] if idx == 0: ax.plot(xplot, yplot[0], 'r', label='VR') if idx > 0: ax.plot(xplot, yplot[0], 'r') ax.fill_between(xplot, yplot[0], yplot[0] - errdn[0], facecolor='r', alpha=0.2, interpolate=True) ax.fill_between(xplot, yplot[0], yplot[0] + errup[0], facecolor='r', alpha=0.2, interpolate=True) if idx == 0: common.prepare_legend(ax, ['b', 'r']) common.savefig(outdir, fig, "r50_Mstar_30kpc_z.pdf") ################## will plot r50 vs stellar mass for quantities measured within 30kpc, but in this case the r50 is projected xtit = "$\\rm log_{10} (\\rm M_{\\star,30kpc}/M_{\odot})$" ytit = "$\\rm log_{10}(\\rm R_{\\rm 50,30kpc,2D}/pMpc)$" xmin, xmax, ymin, ymax = 7, 12, -3.3, -1 xleg = xmax - 0.2 * (xmax - xmin) yleg = ymax - 0.1 * (ymax - ymin) fig = plt.figure(figsize=(5, 10)) idx = [0, 1, 2] zins = [0, 1, 2] subplots = [311, 312, 313] for subplot, idx, z, s in zip(subplots, idx, zins, snap): ax = fig.add_subplot(subplot) if (idx == 2): xtitplot = xtit else: xtitplot = ' ' common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtitplot, ytit, locators=(0.1, 1, 0.1)) plt.subplots_adjust(left=0.2) ax.text(xleg, yleg, 'z=%s' % (str(z))) #from SUBFIND ind = np.where((mstot > 0) & (sn == s) & (r50p > 0)) rplot = bin_it(x=np.log10(mstot[ind]), y=np.log10(r50p[ind]) - 3.0) ind = np.where(rplot[0, :] != 0.) xplot = xmf[ind] yplot = rplot[0, ind] errdn = rplot[1, ind] errup = rplot[2, ind] if idx == 0: ax.plot(xplot, yplot[0], 'b', linestyle='dashed', label='EAGLE L25') if idx > 0: ax.plot(xplot, yplot[0], 'b', linestyle='dashed') ax.fill_between(xplot, yplot[0], yplot[0] - errdn[0], facecolor='b', alpha=0.2, interpolate=True) ax.fill_between(xplot, yplot[0], yplot[0] + errup[0], facecolor='b', alpha=0.2, interpolate=True) #VR ind = np.where(R50pMstar30[idx, 0, :] != 0.) xplot = xmf[ind] yplot = R50pMstar30[idx, 0, ind] errdn = R50pMstar30[idx, 1, ind] errup = R50pMstar30[idx, 2, ind] if idx == 0: ax.plot(xplot, yplot[0], 'r', label='VR') if idx > 0: ax.plot(xplot, yplot[0], 'r') ax.fill_between(xplot, yplot[0], yplot[0] - errdn[0], facecolor='r', alpha=0.2, interpolate=True) ax.fill_between(xplot, yplot[0], yplot[0] + errup[0], facecolor='r', alpha=0.2, interpolate=True) if idx == 0: common.prepare_legend(ax, ['b', 'r']) common.savefig(outdir, fig, "r50_projected_Mstar_30kpc_z.pdf") ########################### will plot stellar velocity dispersion vs. stellar mass sn, mstot, sfr, r50, vs = common.load_observation( '/fred/oz009/clagos/EAGLE/L0025N0376/REFERENCE/data/', 'SUBFIND-EAGLE-DATABASE-REF.data', [2, 22, 30, 33, 25]) xtit = "$\\rm log_{10} (\\rm M_{\\star,30kpc}/M_{\odot})$" ytit = "$\\rm log_{10}(\\sigma_{\\star,30kpc}/km s^{-1})$" xmin, xmax, ymin, ymax = 7, 12, 1, 3 xleg = xmax - 0.2 * (xmax - xmin) yleg = ymax - 0.1 * (ymax - ymin) fig = plt.figure(figsize=(5, 10)) idx = [0, 1, 2] zins = [0, 1, 2] subplots = [311, 312, 313] for subplot, idx, z, s in zip(subplots, idx, zins, snap): ax = fig.add_subplot(subplot) if (idx == 2): xtitplot = xtit else: xtitplot = ' ' common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtitplot, ytit, locators=(0.1, 1, 0.1)) plt.subplots_adjust(left=0.2) ax.text(xleg, yleg, 'z=%s' % (str(z))) #from SUBFIND ind = np.where((mstot > 0) & (sn == s) & (vs > 0)) rplot = bin_it(x=np.log10(mstot[ind]), y=np.log10(vs[ind])) ind = np.where(rplot[0, :] != 0.) xplot = xmf[ind] yplot = rplot[0, ind] errdn = rplot[1, ind] errup = rplot[2, ind] if idx == 0: ax.plot(xplot, yplot[0], 'b', linestyle='dashed', label='EAGLE L25') if idx > 0: ax.plot(xplot, yplot[0], 'b', linestyle='dashed') ax.fill_between(xplot, yplot[0], yplot[0] - errdn[0], facecolor='b', alpha=0.2, interpolate=True) ax.fill_between(xplot, yplot[0], yplot[0] + errup[0], facecolor='b', alpha=0.2, interpolate=True) #VR ind = np.where(SigmaMstar30[idx, 0, :] != 0.) xplot = xmf[ind] yplot = SigmaMstar30[idx, 0, ind] errdn = SigmaMstar30[idx, 1, ind] errup = SigmaMstar30[idx, 2, ind] if idx == 0: ax.plot(xplot, yplot[0], 'r', label='VR') if idx > 0: ax.plot(xplot, yplot[0], 'r') ax.fill_between(xplot, yplot[0], yplot[0] - errdn[0], facecolor='r', alpha=0.2, interpolate=True) ax.fill_between(xplot, yplot[0], yplot[0] + errup[0], facecolor='r', alpha=0.2, interpolate=True) if idx == 0: common.prepare_legend(ax, ['b', 'r']) common.savefig(outdir, fig, "vdisp_Mstar_30kpc_z.pdf") ############ will plot stellar metallicity-stellar mass xtit = "$\\rm log_{10} (\\rm M_{\\star, tot}/M_{\odot})$" ytit = "$\\rm log_{10}(\\rm Z_{\star})$" xmin, xmax, ymin, ymax = 7, 12, -5, -1 xleg = xmax - 0.2 * (xmax - xmin) yleg = ymax - 0.1 * (ymax - ymin) fig = plt.figure(figsize=(5, 10)) idx = [0, 1, 2] zins = [0, 1, 2] subplots = [311, 312, 313] sn, mstot, zsf, zs, age, znsf = common.load_observation( '/fred/oz009/clagos/EAGLE/L0025N0376/REFERENCE/data/', 'SUBFIND-EAGLE-DATABASE.data', [2, 29, 33, 34, 35, 36]) for subplot, idx, z, s in zip(subplots, idx, zins, snap): ax = fig.add_subplot(subplot) if (idx == 2): xtitplot = xtit else: xtitplot = ' ' common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtitplot, ytit, locators=(0.1, 1, 0.1)) ax.text(xleg, yleg, 'z=%s' % (str(z))) #from SUBFIND ind = np.where((mstot > 0) & (sn == s) & (zs > 0)) rplot = bin_it(x=np.log10(mstot[ind]), y=np.log10(zs[ind])) ind = np.where(rplot[0, :] != 0.) xplot = xmf[ind] yplot = rplot[0, ind] errdn = rplot[1, ind] errup = rplot[2, ind] if idx == 0: ax.plot(xplot, yplot[0], 'b', linestyle='dashed', label='EAGLE L25') if idx > 0: ax.plot(xplot, yplot[0], 'b', linestyle='dashed') ax.fill_between(xplot, yplot[0], yplot[0] - errdn[0], facecolor='b', alpha=0.2, interpolate=True) ax.fill_between(xplot, yplot[0], yplot[0] + errup[0], facecolor='b', alpha=0.2, interpolate=True) #VR ind = np.where(ZstarMstar[idx, 0, :] != 0.) xplot = xmf[ind] yplot = ZstarMstar[idx, 0, ind] errdn = ZstarMstar[idx, 1, ind] errup = ZstarMstar[idx, 2, ind] if idx == 0: ax.plot(xplot, yplot[0], 'r', label='VR') if idx > 0: ax.plot(xplot, yplot[0], 'r') ax.fill_between(xplot, yplot[0], yplot[0] - errdn[0], facecolor='r', alpha=0.2, interpolate=True) ax.fill_between(xplot, yplot[0], yplot[0] + errup[0], facecolor='r', alpha=0.2, interpolate=True) if idx == 0: common.prepare_legend(ax, ['b', 'r']) common.savefig(outdir, fig, "zstar_mstar_z.pdf") ################ will plot star-forming gas metallicity vs. stellar mass xtit = "$\\rm log_{10} (\\rm M_{\\star, tot}/M_{\odot})$" ytit = "$\\rm log_{10}(\\rm Z_{\\rm SF,gas})$" xmin, xmax, ymin, ymax = 7, 12, -5, -1 xleg = xmax - 0.2 * (xmax - xmin) yleg = ymax - 0.1 * (ymax - ymin) fig = plt.figure(figsize=(5, 10)) idx = [0, 1, 2] zins = [0, 1, 2] subplots = [311, 312, 313] for subplot, idx, z, s in zip(subplots, idx, zins, snap): ax = fig.add_subplot(subplot) if (idx == 2): xtitplot = xtit else: xtitplot = ' ' common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtitplot, ytit, locators=(0.1, 1, 0.1)) ax.text(xleg, yleg, 'z=%s' % (str(z))) #from SUBFIND ind = np.where((mstot > 0) & (sn == s) & (zsf > 0)) rplot = bin_it(x=np.log10(mstot[ind]), y=np.log10(zsf[ind])) ind = np.where(rplot[0, :] != 0.) xplot = xmf[ind] yplot = rplot[0, ind] errdn = rplot[1, ind] errup = rplot[2, ind] if idx == 0: ax.plot(xplot, yplot[0], 'b', linestyle='dashed', label='EAGLE L25') if idx > 0: ax.plot(xplot, yplot[0], 'b', linestyle='dashed') ax.fill_between(xplot, yplot[0], yplot[0] - errdn[0], facecolor='b', alpha=0.2, interpolate=True) ax.fill_between(xplot, yplot[0], yplot[0] + errup[0], facecolor='b', alpha=0.2, interpolate=True) #VR ind = np.where(ZSFMstar[idx, 0, :] != 0.) xplot = xmf[ind] yplot = ZSFMstar[idx, 0, ind] errdn = ZSFMstar[idx, 1, ind] errup = ZSFMstar[idx, 2, ind] if idx == 0: ax.plot(xplot, yplot[0], 'r', label='VR') if idx > 0: ax.plot(xplot, yplot[0], 'r') ax.fill_between(xplot, yplot[0], yplot[0] - errdn[0], facecolor='r', alpha=0.2, interpolate=True) ax.fill_between(xplot, yplot[0], yplot[0] + errup[0], facecolor='r', alpha=0.2, interpolate=True) if idx == 0: common.prepare_legend(ax, ['b', 'r']) common.savefig(outdir, fig, "zsfgas_mstar_z.pdf") ################ will plot non-star-forming gas metallicity vs. stellar mass xtit = "$\\rm log_{10} (\\rm M_{\\star, tot}/M_{\odot})$" ytit = "$\\rm log_{10}(\\rm Z_{\\rm non-SF,gas})$" xmin, xmax, ymin, ymax = 7, 12, -5, -1 xleg = xmax - 0.2 * (xmax - xmin) yleg = ymax - 0.1 * (ymax - ymin) fig = plt.figure(figsize=(5, 10)) idx = [0, 1, 2] zins = [0, 1, 2] subplots = [311, 312, 313] for subplot, idx, z, s in zip(subplots, idx, zins, snap): ax = fig.add_subplot(subplot) if (idx == 2): xtitplot = xtit else: xtitplot = ' ' common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtitplot, ytit, locators=(0.1, 1, 0.1)) ax.text(xleg, yleg, 'z=%s' % (str(z))) #from SUBFIND ind = np.where((mstot > 0) & (sn == s) & (znsf > 0)) rplot = bin_it(x=np.log10(mstot[ind]), y=np.log10(znsf[ind])) ind = np.where(rplot[0, :] != 0.) xplot = xmf[ind] yplot = rplot[0, ind] errdn = rplot[1, ind] errup = rplot[2, ind] if idx == 0: ax.plot(xplot, yplot[0], 'b', linestyle='dashed', label='EAGLE L25') if idx > 0: ax.plot(xplot, yplot[0], 'b', linestyle='dashed') ax.fill_between(xplot, yplot[0], yplot[0] - errdn[0], facecolor='b', alpha=0.2, interpolate=True) ax.fill_between(xplot, yplot[0], yplot[0] + errup[0], facecolor='b', alpha=0.2, interpolate=True) #VR ind = np.where(ZNSFMstar[idx, 0, :] != 0.) xplot = xmf[ind] yplot = ZNSFMstar[idx, 0, ind] errdn = ZNSFMstar[idx, 1, ind] errup = ZNSFMstar[idx, 2, ind] if idx == 0: ax.plot(xplot, yplot[0], 'r', label='VR') if idx > 0: ax.plot(xplot, yplot[0], 'r') ax.fill_between(xplot, yplot[0], yplot[0] - errdn[0], facecolor='r', alpha=0.2, interpolate=True) ax.fill_between(xplot, yplot[0], yplot[0] + errup[0], facecolor='r', alpha=0.2, interpolate=True) if idx == 0: common.prepare_legend(ax, ['b', 'r']) common.savefig(outdir, fig, "znsfgas_mstar_z.pdf") ################ will plot stellar ages vs stellar mass xtit = "$\\rm log_{10} (\\rm M_{\\star, tot}/M_{\odot})$" ytit = "$\\rm log_{10}(\\rm age_{\\star}/Gyr)$" xmin, xmax, ymin, ymax = 7, 12, 0, 1.1 xleg = xmax - 0.2 * (xmax - xmin) yleg = ymax - 0.1 * (ymax - ymin) fig = plt.figure(figsize=(5, 10)) idx = [0, 1, 2] zins = [0, 1, 2] subplots = [311, 312, 313] for subplot, idx, z, s in zip(subplots, idx, zins, snap): ax = fig.add_subplot(subplot) if (idx == 2): xtitplot = xtit else: xtitplot = ' ' common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtitplot, ytit, locators=(0.1, 1, 0.1)) ax.text(xleg, yleg, 'z=%s' % (str(z))) #from SUBFIND ind = np.where((mstot > 0) & (sn == s) & (age > 0)) rplot = bin_it(x=np.log10(mstot[ind]), y=np.log10(age[ind])) ind = np.where(rplot[0, :] != 0.) xplot = xmf[ind] yplot = rplot[0, ind] errdn = rplot[1, ind] errup = rplot[2, ind] if idx == 0: ax.plot(xplot, yplot[0], 'b', linestyle='dashed', label='EAGLE L25') if idx > 0: ax.plot(xplot, yplot[0], 'b', linestyle='dashed') ax.fill_between(xplot, yplot[0], yplot[0] - errdn[0], facecolor='b', alpha=0.2, interpolate=True) ax.fill_between(xplot, yplot[0], yplot[0] + errup[0], facecolor='b', alpha=0.2, interpolate=True) #VR ind = np.where(AgeSMstar[idx, 0, :] != 0.) xplot = xmf[ind] yplot = AgeSMstar[idx, 0, ind] errdn = AgeSMstar[idx, 1, ind] errup = AgeSMstar[idx, 2, ind] if idx == 0: ax.plot(xplot, yplot[0], 'r', label='VR') if idx > 0: ax.plot(xplot, yplot[0], 'r') ax.fill_between(xplot, yplot[0], yplot[0] - errdn[0], facecolor='r', alpha=0.2, interpolate=True) ax.fill_between(xplot, yplot[0], yplot[0] + errup[0], facecolor='r', alpha=0.2, interpolate=True) if idx == 0: common.prepare_legend(ax, ['b', 'r']) common.savefig(outdir, fig, "starage_mstar_z.pdf")
def plot_specific_am(plt, outdir, obsdir, sam_stars_disk, sam_gas_disk_atom, sam_gas_disk_mol, sam_halo, sam_bar, sam_stars): fig = plt.figure(figsize=(4.5,4.5)) xtit = "$\\rm log_{10} (\\rm M_{\\star}/M_{\odot})$" ytit = "$\\rm log_{10} (\\rm j_{\\rm disk}/kpc\\, km s^{-1})$" xmin, xmax, ymin, ymax = 8, 11.5, 1.5, 5 xleg = xmax - 0.5 * (xmax - xmin) yleg = ymax - 0.1 * (ymax - ymin) # choose type of selection: selec = 1 #disk-dominated galaxies s = 0 # LTG ################################## ax = fig.add_subplot(111) common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtit, ytit, locators=(0.1, 1, 0.1, 1)) ax.text(xleg, yleg, 'z=0 Shark-default', fontsize = 12) ind = np.where(sam_halo[s,0,:,selec] != 0) xplot = xmf[ind] yplot = sam_halo[s,0,ind,selec] + 3.0 errdn = sam_halo[s,1,ind,selec] errup = sam_halo[s,2,ind,selec] ax.plot(xplot,yplot[0],color='k',label="DM") ax.fill_between(xplot,yplot[0],yplot[0]-errdn[0], facecolor='k', alpha=0.2,interpolate=True) ax.fill_between(xplot,yplot[0],yplot[0]+errup[0], facecolor='k', alpha=0.2,interpolate=True) #Predicted sAM-mass for disks in disk=dominated galaxies ind = np.where(sam_stars[s,0,:,selec] != 0) xplot = xmf[ind] yplot = sam_stars[s,0,ind,selec]+ 3.0 errdn = sam_stars[s,1,ind,selec] errup = sam_stars[s,2,ind,selec] ax.plot(xplot,yplot[0],color='r',linestyle='dashed',label="stars") ax.fill_between(xplot,yplot[0],yplot[0]-errdn[0], facecolor='r', alpha=0.25,interpolate=True) ax.fill_between(xplot,yplot[0],yplot[0]+errup[0], facecolor='r', alpha=0.25,interpolate=True) #Predicted size-mass for disks in disk=dominated galaxies ind = np.where(sam_gas_disk_atom[s,0,:,selec] != 0) xplot = xmf[ind] yplot = sam_gas_disk_atom[s,0,ind,selec] + 3.0 errdn = sam_gas_disk_atom[s,1,ind,selec] errup = sam_gas_disk_atom[s,2,ind,selec] ax.plot(xplot,yplot[0],color='b',linestyle='dotted',label="atomic ISM") ax.fill_between(xplot,yplot[0],yplot[0]-errdn[0], facecolor='b', alpha=0.25,interpolate=True) ax.fill_between(xplot,yplot[0],yplot[0]+errup[0], facecolor='b', alpha=0.25,interpolate=True) #Predicted size-mass for disks in disk=dominated galaxies ind = np.where(sam_gas_disk_mol[s,0,:,selec] != 0) xplot = xmf[ind] yplot = sam_gas_disk_mol[s,0,ind,selec] + 3.0 errdn = sam_gas_disk_mol[s,1,ind,selec] errup = sam_gas_disk_mol[s,2,ind,selec] ax.plot(xplot,yplot[0],color='g',linestyle='dashdot',label="molecular ISM") ax.fill_between(xplot,yplot[0],yplot[0]-errdn[0], facecolor='g', alpha=0.25,interpolate=True) ax.fill_between(xplot,yplot[0],yplot[0]+errup[0], facecolor='g', alpha=0.25,interpolate=True) common.prepare_legend(ax, ['k'], loc=2) common.savefig(outdir, fig, 'specific_am_onlyz0.pdf') fig = plt.figure(figsize=(9.5,9.5)) xtit = "$\\rm log_{10} (\\rm M_{\\star}/M_{\odot})$" ytit = "$\\rm log_{10} (\\rm j_{\\rm disk}/kpc\\, km s^{-1})$" xmin, xmax, ymin, ymax = 8, 11.5, 1.5, 5 xleg = xmax - 0.2 * (xmax - xmin) yleg = ymax - 0.1 * (ymax - ymin) subplots = (221, 222, 223, 224) indz = (0, 1, 2, 3) # choose type of selection: selec = 1 #disk-dominated galaxies # LTG ################################## for z,s,p in zip(zlist, indz, subplots): ax = fig.add_subplot(p) common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtit, ytit, locators=(0.1, 1, 0.1, 1)) ax.text(xleg, yleg, 'z=%s' % str(z)) ind = np.where(sam_halo[s,0,:,selec] != 0) xplot = xmf[ind] yplot = sam_halo[s,0,ind,selec] + 3.0 errdn = sam_halo[s,1,ind,selec] errup = sam_halo[s,2,ind,selec] ax.plot(xplot,yplot[0],color='k',label="DM") ax.fill_between(xplot,yplot[0],yplot[0]-errdn[0], facecolor='k', alpha=0.2,interpolate=True) ax.fill_between(xplot,yplot[0],yplot[0]+errup[0], facecolor='k', alpha=0.2,interpolate=True) #Predicted sAM-mass for disks in disk=dominated galaxies ind = np.where(sam_stars[s,0,:,selec] != 0) xplot = xmf[ind] yplot = sam_stars[s,0,ind,selec]+ 3.0 errdn = sam_stars[s,1,ind,selec] errup = sam_stars[s,2,ind,selec] ax.plot(xplot,yplot[0],color='r',label="stars") ax.fill_between(xplot,yplot[0],yplot[0]-errdn[0], facecolor='r', alpha=0.5,interpolate=True) ax.fill_between(xplot,yplot[0],yplot[0]+errup[0], facecolor='r', alpha=0.5,interpolate=True) #Predicted size-mass for disks in disk=dominated galaxies ind = np.where(sam_gas_disk_atom[s,0,:,selec] != 0) xplot = xmf[ind] yplot = sam_gas_disk_atom[s,0,ind,selec] + 3.0 errdn = sam_gas_disk_atom[s,1,ind,selec] errup = sam_gas_disk_atom[s,2,ind,selec] ax.plot(xplot,yplot[0],color='b',label="atomic ISM") ax.fill_between(xplot,yplot[0],yplot[0]-errdn[0], facecolor='b', alpha=0.5,interpolate=True) ax.fill_between(xplot,yplot[0],yplot[0]+errup[0], facecolor='b', alpha=0.5,interpolate=True) #Predicted size-mass for disks in disk=dominated galaxies ind = np.where(sam_gas_disk_mol[s,0,:,selec] != 0) xplot = xmf[ind] yplot = sam_gas_disk_mol[s,0,ind,selec] + 3.0 errdn = sam_gas_disk_mol[s,1,ind,selec] errup = sam_gas_disk_mol[s,2,ind,selec] ax.plot(xplot,yplot[0],color='g',label="molecular ISM") ax.fill_between(xplot,yplot[0],yplot[0]-errdn[0], facecolor='g', alpha=0.5,interpolate=True) ax.fill_between(xplot,yplot[0],yplot[0]+errup[0], facecolor='g', alpha=0.5,interpolate=True) common.prepare_legend(ax, ['k'], loc=2) common.savefig(outdir, fig, 'specific_am.pdf') #plot angular momentum components separately. fig = plt.figure(figsize=(15,5)) s = 0 #plot stars xtit = "$\\rm log_{10} (\\rm M_{\\star}/M_{\odot})$" ytit = "$\\rm log_{10} (\\rm j_{\\star}/kpc\\, km s^{-1})$" xmin, xmax, ymin, ymax = 8, 11.5, 1.5, 4 xleg = xmax - 0.2 * (xmax - xmin) yleg = ymax - 0.1 * (ymax - ymin) ax = fig.add_subplot(141) common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtit, ytit, locators=(0.1, 1, 0.1, 1)) jst, jmole, jatomic, jbar = common.load_observation(obsdir, 'Models/SharkVariations/AngularMomentum.dat', [0,1,2,3]) jsL18 = np.zeros(shape = (3, len(xmf))) jmolL18 = np.zeros(shape = (3, len(xmf))) jatomL18 = np.zeros(shape = (3, len(xmf))) jbarL18 = np.zeros(shape = (3, len(xmf))) i = 0 p =0 for j in range(0,len(jst)/2): jsL18[i,p] = jst[j] jmolL18[i,p] = jmole[j] jatomL18[i,p] = jatomic[j] jbarL18[i,p] = jbar[j] p = p + 1 if(p >= len(xmf)): p = 0 i = i +1 #Predicted sAM-mass for disks in disk=dominated galaxies ind = np.where(sam_stars[s,0,:,selec] != 0) xplot = xmf[ind] yplot = sam_stars[s,0,ind,selec]+ 3.0 errdn = sam_stars[s,1,ind,selec] errup = sam_stars[s,2,ind,selec] ax.plot(xplot,yplot[0],color='r') ax.fill_between(xplot,yplot[0],yplot[0]-errdn[0], facecolor='r', alpha=0.35,interpolate=True) ax.fill_between(xplot,yplot[0],yplot[0]+errup[0], facecolor='r', alpha=0.35,interpolate=True) ind = np.where(sam_stars_disk[s,0,:,selec] != 0) xplot = xmf[ind] yplot = sam_stars_disk[s,0,ind,selec]+ 3.0 errdn = sam_stars_disk[s,1,ind,selec] errup = sam_stars_disk[s,2,ind,selec] ax.plot(xplot,yplot[0],color='r', linestyle='dotted') ind = np.where(jsL18[0,:] != 0) xplot = xmf[ind] yplot = jsL18[0,ind]+ 3.0 errdn = jsL18[1,ind] errup = jsL18[2,ind] ax.plot(xplot,yplot[0],color='r',linestyle='dashed') ax.fill_between(xplot,yplot[0],yplot[0]-errdn[0], facecolor='r', linestyle='dashed', alpha=0.2,interpolate=True) ax.fill_between(xplot,yplot[0],yplot[0]+errup[0], facecolor='r', linestyle='dashed', alpha=0.2,interpolate=True) #Read observational data. ms, mserr, js, jserr = common.load_observation(obsdir, 'SizesAndAM/Posti18_AMdata.dat', [3,5,6,8]) errmdn = np.log10(ms) - np.log10(ms - mserr) errmup = np.log10(ms + mserr) - np.log10(ms) errjdn = np.log10(js) - np.log10(js - jserr) errjup = np.log10(js + jserr) - np.log10(js) ax.errorbar(np.log10(ms), np.log10(js), yerr=[errjdn,errjup], xerr=[errmdn,errmup],ls='None', mfc='None', ecolor = 'r', mec='r',marker='+',label="Posti+18") bt, mbO14, msO14, mgO14, jbO14, jsO14, jgO14, jmolO14 = common.load_observation(obsdir, 'SizesAndAM/Obreschkow14_FP.dat', [2,6,7,8,11,12,14,15]) ax.plot(msO14, jsO14, 'ro',fillstyle='none', label="Obreschkow+14") mgB17, msB17, errmsB17, mbB17, errmbB17, jgB17, errjgB17, jsB17, errjsB17, jbB17, errjbB17 = common.load_observation(obsdir, 'SizesAndAM/LITTLETHINGS_Butler16.dat', [1,3,4,5,6,7,8,9,10,11,12]) ax.errorbar(msB17, jsB17, yerr=[errjsB17,errjsB17], xerr=[errmsB17,errmsB17], ls='None', mfc='None', ecolor = 'r', mec='r',marker='s',label="Butler+16") msC17, mgC17, mbC17, errupmbC17, errdnmbC17, JstarC17, JgasC17, errupJgasC17, errdnJgasC17, jbarC17, errupjbarC17, errdnjbarC17 = common.load_observation(obsdir, 'SizesAndAM/Chowdhury17.dat', [1,2,5,6,7,8,8,10,11,15,16,17]) ax.plot(msC17, JstarC17-msC17, 'rp', fillstyle='none',label="Chowdhury+17") mbE17, jbE17 = common.load_observation(obsdir, 'SizesAndAM/Elson17.dat', [5,7]) mbE17 = np.log10(mbE17 * 1e8) jbE17 = np.log10(jbE17) #IDGalaxy Mstar errup errdn Mgas errup errdn Mbar errup errdn jstar errup errdn jgas errup errdn jbar errup errdn (msK18, errupmsK18, errdnmsK18, mgK18, errupmgK18, errdnmgK18, mbK18, errupmbK18, errdnmbK18, jsK18, errupjsK18, errdnjsK18, jgK18, errupjgK18, errdnjgK18, jbarK18, errupjbarK18, errdnjbarK18) = common.load_observation(obsdir, 'SizesAndAM/Kurapati18.dat', [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18]) ax.errorbar(msK18, jsK18, yerr=[errdnjsK18,errupjsK18], xerr=[errdnmsK18,errupmsK18],ls='None', mfc='None', ecolor = 'r', mec='r',marker='*',label="Kurapati+18") common.prepare_legend(ax, ['r', 'r', 'r','r','r'], loc=2) #plot molecular gas xtit = "$\\rm log_{10} (\\rm M_{\\star}/M_{\odot})$" ytit = "$\\rm log_{10} (\\rm j_{\\rm H_2}/kpc\\, km s^{-1})$" ax = fig.add_subplot(142) common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtit, ytit, locators=(0.1, 1, 0.1, 1)) #Predicted size-mass for disks in disk=dominated galaxies ind = np.where(sam_gas_disk_mol[s,0,:,selec] != 0) xplot = xmf[ind] yplot = sam_gas_disk_mol[s,0,ind,selec] + 3.0 errdn = sam_gas_disk_mol[s,1,ind,selec] errup = sam_gas_disk_mol[s,2,ind,selec] ax.plot(xplot,yplot[0],color='g', label="ISM/stars AM transfer") ax.fill_between(xplot,yplot[0],yplot[0]-errdn[0], facecolor='g', alpha=0.35,interpolate=True) ax.fill_between(xplot,yplot[0],yplot[0]+errup[0], facecolor='g', alpha=0.35,interpolate=True) ind = np.where(jmolL18[0,:] != 0) xplot = xmf[ind] yplot = jmolL18[0,ind]+ 3.0 errdn = jmolL18[1,ind] errup = jmolL18[2,ind] ax.plot(xplot,yplot[0],color='g',linestyle='dashed', label="Lagos+18") ax.fill_between(xplot,yplot[0],yplot[0]-errdn[0], facecolor='g', linestyle='dashed', alpha=0.2,interpolate=True) ax.fill_between(xplot,yplot[0],yplot[0]+errup[0], facecolor='g', linestyle='dashed', alpha=0.2,interpolate=True) ax.plot(msO14, jmolO14, 'go',fillstyle='none') common.prepare_legend(ax, ['k'], loc=2) #plot atomic gas xtit = "$\\rm log_{10} (\\rm M_{\\star}/M_{\odot})$" ytit = "$\\rm log_{10} (\\rm j_{\\rm HI}/kpc\\, km s^{-1})$" ax = fig.add_subplot(143) common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtit, ytit, locators=(0.1, 1, 0.1, 1)) #Predicted size-mass for disks in disk=dominated galaxies ind = np.where(sam_gas_disk_atom[s,0,:,selec] != 0) xplot = xmf[ind] yplot = sam_gas_disk_atom[s,0,ind,selec] + 3.0 errdn = sam_gas_disk_atom[s,1,ind,selec] errup = sam_gas_disk_atom[s,2,ind,selec] ax.plot(xplot,yplot[0],color='b') ax.fill_between(xplot,yplot[0],yplot[0]-errdn[0], facecolor='b', alpha=0.35,interpolate=True) ax.fill_between(xplot,yplot[0],yplot[0]+errup[0], facecolor='b', alpha=0.35,interpolate=True) ind = np.where(jatomL18[0,:] != 0) xplot = xmf[ind] yplot = jatomL18[0,ind]+ 3.0 errdn = jatomL18[1,ind] errup = jatomL18[2,ind] ax.plot(xplot,yplot[0],color='b',linestyle='dashed') ax.fill_between(xplot,yplot[0],yplot[0]-errdn[0], facecolor='b', linestyle='dashed', alpha=0.2,interpolate=True) ax.fill_between(xplot,yplot[0],yplot[0]+errup[0], facecolor='b', linestyle='dashed', alpha=0.2,interpolate=True) ax.errorbar(msB17, jgB17, yerr=[errjgB17,errjgB17], xerr=[errmsB17,errmsB17,],ls='None', mfc='None', ecolor = 'b', mec='b',marker='s') ax.plot(msO14, jgO14, 'bo',fillstyle='none') ax.plot(msC17, JgasC17-mgC17, 'bp', fillstyle='none') ax.errorbar(msK18, jgK18, yerr=[errdnjgK18,errupjgK18], xerr=[errdnmsK18,errupmsK18],ls='None', mfc='None', ecolor = 'b', mec='b',marker='*') #plot total baryon xtit = "$\\rm log_{10} (\\rm M_{\\rm bar}/M_{\odot})$" ytit = "$\\rm log_{10} (\\rm j_{\\rm bar}/kpc\\, km s^{-1})$" ax = fig.add_subplot(144) common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtit, ytit, locators=(0.1, 1, 0.1, 1)) #Predicted size-mass for disks in disk=dominated galaxies ind = np.where(sam_bar[s,0,:,selec] != 0) xplot = xmf[ind] yplot = sam_bar[s,0,ind,selec] + 3.0 errdn = sam_bar[s,1,ind,selec] errup = sam_bar[s,2,ind,selec] ax.plot(xplot,yplot[0],color='k') ax.fill_between(xplot,yplot[0],yplot[0]-errdn[0], facecolor='k', alpha=0.25,interpolate=True) ax.fill_between(xplot,yplot[0],yplot[0]+errup[0], facecolor='k', alpha=0.25,interpolate=True) ind = np.where(jbarL18[0,:] != 0) xplot = xmf[ind] yplot = jbarL18[0,ind]+ 3.0 errdn = jbarL18[1,ind] errup = jbarL18[2,ind] ax.plot(xplot,yplot[0],color='k',linestyle='dashed') ax.fill_between(xplot,yplot[0],yplot[0]-errdn[0], facecolor='k', linestyle='dashed', alpha=0.1,interpolate=True) ax.fill_between(xplot,yplot[0],yplot[0]+errup[0], facecolor='k', linestyle='dashed', alpha=0.1,interpolate=True) ax.errorbar(mbB17, jbB17, yerr=[errjbB17,errjbB17], xerr=[errmbB17,errmbB17],ls='None', mfc='None', ecolor = 'k', mec='k',marker='s') ax.plot(mbO14, jbO14, 'ko',fillstyle='none') ax.errorbar(mbC17, jbarC17, yerr=[errdnjbarC17,errupjbarC17], xerr=[errdnmbC17,errupmbC17], ls='None', mfc='None', ecolor = 'k', mec='k',marker='p') ax.errorbar(mbK18, jbarK18, yerr=[errdnjbarK18,errupjbarK18], xerr=[errdnmbK18,errupmbK18],ls='None', mfc='None', ecolor = 'k', mec='k',marker='*') ax.plot(mbE17, jbE17, 'k^', fillstyle='none', label='Elson17') common.prepare_legend(ax, ['k'], loc=2) common.savefig(outdir, fig, 'specific_am_z0_components.pdf') for c in range (0,2): print 'will change selection' for i in range (0,3): print 'will change within the same sample' for x,y,z,a in zip(sam_stars_disk[s,i,:,c],sam_gas_disk_mol[s,i,:,c],sam_gas_disk_atom[s,i,:,c],sam_bar[s,i,:,c]): print x,y,z,a
def plot_r200_z(plt, outdir, r200, snap): bin_it = functools.partial(us.wmedians, xbins=xmf) xtit="$\\rm log_{10} (\\rm M_{\\rm 200crit}/M_{\odot})$" ytit="$\\rm log_{10}(\\rm R_{\\rm 200crit}/pMpc)$" xmin, xmax, ymin, ymax = 8, 14, -3, 1 xleg = xmax - 0.2 * (xmax-xmin) yleg = ymax - 0.1 * (ymax-ymin) fig = plt.figure(figsize=(5,10)) idx = [0,1,2] zins = [0, 1, 2] subplots = [311, 312, 313] sn, subgn, m200s, r200s = common.load_observation('/fred/oz009/clagos/EAGLE/L0025N0376/REFERENCE/data/', 'SUBFIND-EAGLE-DATABASE.data', [2, 1, 4, 5]) for subplot, idx, z, s in zip(subplots, idx, zins, snap): ax = fig.add_subplot(subplot) if (idx == 2): xtitplot = xtit else: xtitplot = ' ' common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtitplot, ytit, locators=(0.1, 1, 0.1)) ax.text(xleg,yleg, 'z=%s' % (str(z))) #HMF from SUBFIND ind = np.where((m200s > 0) & (subgn == 0) & (sn == s) & (r200s > 0)) rplot = bin_it(x= np.log10(m200s[ind]), y = np.log10(r200s[ind])-3.0) ind = np.where(rplot[0,:] != 0.) xplot = xmf[ind] yplot = rplot[0,ind] errdn = rplot[1,ind] errup = rplot[2,ind] if idx == 0: ax.plot(xplot,yplot[0],'b', linestyle='dashed', label ='SF') if idx > 0: ax.plot(xplot,yplot[0],'b', linestyle='dashed') ax.fill_between(xplot,yplot[0],yplot[0]-errdn[0], facecolor='b', alpha=0.2,interpolate=True) ax.fill_between(xplot,yplot[0],yplot[0]+errup[0], facecolor='b', alpha=0.2,interpolate=True) #Predicted HMF ind = np.where(r200[0,idx,0,:] != 0.) xplot = xmf[ind] yplot = r200[0,idx,0,ind] errdn = r200[0,idx,1,ind] errup = r200[0,idx,2,ind] if idx == 0: ax.plot(xplot,yplot[0],'r', label ='VR') if idx > 0: ax.plot(xplot,yplot[0],'r') ax.fill_between(xplot,yplot[0],yplot[0]-errdn[0], facecolor='r', alpha=0.2,interpolate=True) ax.fill_between(xplot,yplot[0],yplot[0]+errup[0], facecolor='r', alpha=0.2,interpolate=True) if idx == 0: common.prepare_legend(ax, ['b','r']) common.savefig(outdir, fig, "r200M200_crit_z.pdf") xtit="$\\rm log_{10} (\\rm M_{\\rm 200mean}/M_{\odot})$" ytit="$\\rm log_{10}(\\rm R_{\\rm 200mean}/pMpc)$" xmin, xmax, ymin, ymax = 8, 14, -3, 1 xleg = xmax - 0.2 * (xmax-xmin) yleg = ymax - 0.1 * (ymax-ymin) fig = plt.figure(figsize=(5,10)) idx = [0,1,2] zins = [0, 1, 2] subplots = [311, 312, 313] sn, subgn, m200s, r200s = common.load_observation('/fred/oz009/clagos/EAGLE/L0025N0376/REFERENCE/data/', 'SUBFIND-EAGLE-DATABASE.data', [2, 1, 6, 7]) for subplot, idx, z, s in zip(subplots, idx, zins, snap): ax = fig.add_subplot(subplot) if (idx == 2): xtitplot = xtit else: xtitplot = ' ' common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtitplot, ytit, locators=(0.1, 1, 0.1)) ax.text(xleg,yleg, 'z=%s' % (str(z))) #HMF from SUBFIND ind = np.where((m200s > 0) & (subgn == 0) & (sn == s) & (r200s > 0)) rplot = bin_it(x= np.log10(m200s[ind]), y = np.log10(r200s[ind])-3.0) ind = np.where(rplot[0,:] != 0.) xplot = xmf[ind] yplot = rplot[0,ind] errdn = rplot[1,ind] errup = rplot[2,ind] if idx == 0: ax.plot(xplot,yplot[0],'b', linestyle='dashed', label ='SF') if idx > 0: ax.plot(xplot,yplot[0],'b', linestyle='dashed') ax.fill_between(xplot,yplot[0],yplot[0]-errdn[0], facecolor='b', alpha=0.2,interpolate=True) ax.fill_between(xplot,yplot[0],yplot[0]+errup[0], facecolor='b', alpha=0.2,interpolate=True) #Predicted HMF ind = np.where(r200[1,idx,0,:] != 0.) xplot = xmf[ind] yplot = r200[1,idx,0,ind] errdn = r200[1,idx,1,ind] errup = r200[1,idx,2,ind] if idx == 0: ax.plot(xplot,yplot[0],'r', label ='VR') if idx > 0: ax.plot(xplot,yplot[0],'r') ax.fill_between(xplot,yplot[0],yplot[0]-errdn[0], facecolor='r', alpha=0.2,interpolate=True) ax.fill_between(xplot,yplot[0],yplot[0]+errup[0], facecolor='r', alpha=0.2,interpolate=True) if idx == 0: common.prepare_legend(ax, ['b','r']) common.savefig(outdir, fig, "r200M200_mean_z.pdf")
def plot_mass_densities(plt, outdir, obsdir, h0, redshifts, mstar, mcold, mhot, meje, mstarden, mcoldden, mhotden, mejeden): fig = plt.figure(figsize=(5, 15)) xtit = "$\\rm Lookback\, time/Gyr$" ytit = "$\\rm log_{10}(\\rho/\\rho_{\\rm bar,halos})$" ax = fig.add_subplot(411) plt.subplots_adjust(bottom=0.15, left=0.15) common.prepare_ax(ax, 0, 13.5, -5, 0.1, xtit, ytit, locators=(0.1, 1, 0.1, 1), fontsize=10) ax2 = ax.twiny() ax2.set_xlim(ax.get_xlim()) new_tick_locations = np.array([0., 2., 4., 6., 8., 10., 12.]) ax2.set_xticks(new_tick_locations) ax2.set_xticklabels(us.redshift(new_tick_locations), fontsize=12) ax2.set_xlabel("redshift", fontsize=13) ax.plot(us.look_back_time(redshifts), mstar, 'k', label='stars') ax.plot(us.look_back_time(redshifts), mcold, 'b', label='ISM gas') ax.plot(us.look_back_time(redshifts), mhot, 'r', label='halo gas') ax.plot(us.look_back_time(redshifts), meje, 'g', label='ejected gas') common.prepare_legend(ax, ['k', 'b', 'r', 'g'], fontsize=10) xtit = "$\\rm Lookback\, time/Gyr$" ytit = "$\\rm log_{10}(\\rho_{\\rm bar} /\\rm M_{\odot} \\rm Mpc^{-3})$" ax = fig.add_subplot(412) plt.subplots_adjust(bottom=0.15, left=0.15) common.prepare_ax(ax, 0, 13.5, 6, 10, xtit, ytit, locators=(0.1, 1, 0.1, 1), fontsize=10) msharktot = mstarden + mcoldden + mhotden + mejeden ind = np.where(mstarden > 0) ax.plot(us.look_back_time(redshifts), np.log10(mstarden[ind] * pow(h0, 2.0)), 'k', label='Shark') ind = np.where(mcoldden > 0) ax.plot(us.look_back_time(redshifts), np.log10(mcoldden[ind] * pow(h0, 2.0)), 'b') ind = np.where(mhotden > 0) ax.plot(us.look_back_time(redshifts), np.log10(mhotden[ind] * pow(h0, 2.0)), 'r') ind = np.where(mejeden > 0) ax.plot(us.look_back_time(redshifts), np.log10(mejeden[ind] * pow(h0, 2.0)), 'g') ind = np.where(msharktot > 0) ax.plot(us.look_back_time(redshifts), np.log10(msharktot[ind] * pow(h0, 2.0)), 'DarkMagenta') lbt, eaglesm, eaglesmout, eagleism, eaglehg, eagleejec = common.load_observation( obsdir, 'Models/OtherModels/EAGLE_BaryonGrowthTotal.dat', [0, 2, 3, 4, 5, 6]) eaglesm = np.log10(pow(10.0, eaglesm) + pow(10.0, eaglesmout)) eagletot = np.log10( pow(10.0, eaglesm) + pow(10.0, eagleism) + pow(10.0, eaglehg) + pow(10.0, eagleejec)) ind = np.where(eaglesm > 0) ax.plot(lbt[ind], eaglesm[ind] - 6.0, 'k', linestyle='dotted', label='EAGLE') ind = np.where(eagleism > 0) ax.plot(lbt[ind], eagleism[ind] - 6.0, 'b', linestyle='dotted') ind = np.where(eaglehg > 0) ax.plot(lbt[ind], eaglehg[ind] - 6.0, 'r', linestyle='dotted') ind = np.where(eagleejec > 0) ax.plot(lbt[ind], eagleejec[ind] - 6.0, 'g', linestyle='dotted') ind = np.where(eagletot > 0) ax.plot(lbt[ind], eagletot[ind] - 6.0, 'DarkMagenta', linestyle='dotted') common.prepare_legend(ax, ['k', 'k', 'k'], fontsize=10) ax = fig.add_subplot(413) plt.subplots_adjust(bottom=0.15, left=0.15) common.prepare_ax(ax, 0, 13.5, 6, 10, xtit, ytit, locators=(0.1, 1, 0.1, 1), fontsize=10) ind = np.where(mstarden > 0) ax.plot(us.look_back_time(redshifts), np.log10(mstarden[ind] * pow(h0, 2.0)), 'k', label='Shark') ind = np.where(mcoldden > 0) ax.plot(us.look_back_time(redshifts), np.log10(mcoldden[ind] * pow(h0, 2.0)), 'b') ind = np.where(mhotden > 0) ax.plot(us.look_back_time(redshifts), np.log10(mhotden[ind] * pow(h0, 2.0)), 'r') ind = np.where(mejeden > 0) ax.plot(us.look_back_time(redshifts), np.log10(mejeden[ind] * pow(h0, 2.0)), 'g') ind = np.where(msharktot > 0) ax.plot(us.look_back_time(redshifts), np.log10(msharktot[ind] * pow(h0, 2.0)), 'DarkMagenta') lbt, galsm, galism, galhg, galejec = common.load_observation( obsdir, 'Models/OtherModels/global_Mitchell18.dat', [0, 2, 3, 4, 5]) galtot = np.log10( pow(10.0, galsm) + pow(10.0, galism) + pow(10.0, galhg) + pow(10.0, galejec)) galsm = (galsm) galism = (galism) galhg = (galhg) galejec = (galejec) h = 0.704 vol = 6.0 #np.log10(1953125.0/pow(h,3.0)) ind = np.where(galsm > 0) ax.plot(lbt[ind], galsm[ind] - vol, 'k', linestyle='dashed', label='GALFORM M18', linewidth=1) ind = np.where(galism > 0) ax.plot(lbt[ind], galism[ind] - vol, 'b', linestyle='dashed', linewidth=1) ind = np.where(galhg > 0) ax.plot(lbt[ind], galhg[ind] - vol, 'r', linestyle='dashed', linewidth=1) ind = np.where(galejec > 0) ax.plot(lbt[ind], galejec[ind] - vol, 'g', linestyle='dashed', linewidth=1) ind = np.where(galtot > 0) ax.plot(lbt[ind], galtot[ind] - vol, 'DarkMagenta', linestyle='dashed', linewidth=1) common.prepare_legend(ax, ['k', 'k', 'k'], fontsize=10) ax = fig.add_subplot(414) plt.subplots_adjust(bottom=0.15, left=0.15) common.prepare_ax(ax, 0, 13.5, 6, 10, xtit, ytit, locators=(0.1, 1, 0.1, 1), fontsize=10) ind = np.where(mstarden > 0) ax.plot(us.look_back_time(redshifts), np.log10(mstarden[ind] * pow(h0, 2.0)), 'k', label='Shark') ind = np.where(mcoldden > 0) ax.plot(us.look_back_time(redshifts), np.log10(mcoldden[ind] * pow(h0, 2.0)), 'b') ind = np.where(mhotden > 0) ax.plot(us.look_back_time(redshifts), np.log10(mhotden[ind] * pow(h0, 2.0)), 'r') ind = np.where(mejeden > 0) ax.plot(us.look_back_time(redshifts), np.log10(mejeden[ind] * pow(h0, 2.0)), 'g') ind = np.where(msharktot > 0) ax.plot(us.look_back_time(redshifts), np.log10(msharktot[ind] * pow(h0, 2.0)), 'DarkMagenta') zbt, galism, galsm, galhg, galejec = common.load_observation( obsdir, 'Models/OtherModels/BaryonBudgetLgalaxies.dat', [1, 2, 3, 4, 5]) lbt = us.look_back_time(zbt) galtot = np.log10(galsm + galism + galhg + galejec) + 10.0 galsm = np.log10(galsm) + 10.0 galism = np.log10(galism) + 10.0 galhg = np.log10(galhg) + 10.0 galejec = np.log10(galejec) + 10.0 h = 0.673 vol = np.log10(125000000.0 / pow(h, 3.0)) ind = np.where(galsm > 0) ax.plot(lbt[ind], galsm[ind] - vol - np.log10(h), 'k', linestyle='dashdot', label='L-galaxies H15', linewidth=1) ind = np.where(galism > 0) ax.plot(lbt[ind], galism[ind] - vol - np.log10(h), 'b', linestyle='dashdot', linewidth=1) ind = np.where(galhg > 0) ax.plot(lbt[ind], galhg[ind] - vol - np.log10(h), 'r', linestyle='dashdot', linewidth=1) ind = np.where(galejec > 0) ax.plot(lbt[ind], galejec[ind] - vol - np.log10(h), 'g', linestyle='dashdot', linewidth=1) ind = np.where(galtot > 0) ax.plot(lbt[ind], galtot[ind] - vol - np.log10(h), 'DarkMagenta', linestyle='dashdot', linewidth=1) common.prepare_legend(ax, ['k', 'k', 'k'], fontsize=10) common.savefig(outdir, fig, "global.pdf") fig = plt.figure(figsize=(5, 4)) xtit = "$\\rm Lookback\, time/Gyr$" ytit = "$\\rm log_{10}(\\rho_{\\rm gas, halo} /\\rm M_{\odot} \\rm Mpc^{-3})$" ax = fig.add_subplot(111) plt.subplots_adjust(bottom=0.15, left=0.15) common.prepare_ax(ax, 0, 13.5, 5, 10, xtit, ytit, locators=(0.1, 1, 0.1, 1), fontsize=10) ind = np.where(mhotden > 0) ax.plot(us.look_back_time(redshifts), np.log10(mhotden[ind] * pow(h0, 2.0)), 'r', label='Shark') lbt, eaglesm, eaglesmout, eagleism, eaglehg, eagleejec = common.load_observation( obsdir, 'Models/OtherModels/EAGLE_BaryonGrowthTotal.dat', [0, 2, 3, 4, 5, 6]) eaglesm = np.log10(pow(10.0, eaglesm) + pow(10.0, eaglesmout)) eagletot = np.log10( pow(10.0, eaglesm) + pow(10.0, eagleism) + pow(10.0, eaglehg) + pow(10.0, eagleejec)) ind = np.where(eaglehg > 0) ax.plot(lbt[ind], eaglehg[ind] - 6.0, 'r', linestyle='dotted', label='EAGLE') lbt, galsm, galism, galhg, galejec = common.load_observation( obsdir, 'Models/OtherModels/global_Mitchell18.dat', [0, 2, 3, 4, 5]) galtot = np.log10( pow(10.0, galsm) + pow(10.0, galism) + pow(10.0, galhg) + pow(10.0, galejec)) galhg = (galhg) h = 0.704 vol = 6.0 #np.log10(1953125.0/pow(h,3.0)) ind = np.where(galhg > 0) ax.plot(lbt[ind], galhg[ind] - vol, 'r', linestyle='dashed', linewidth=1, label='GALFORM M18') ind = np.where(galejec > 0) zbt, galism, galsm, galhg, galejec = common.load_observation( obsdir, 'Models/OtherModels/BaryonBudgetLgalaxies.dat', [1, 2, 3, 4, 5]) lbt = us.look_back_time(zbt) galhg = np.log10(galhg) + 10.0 h = 0.673 vol = np.log10(125000000.0 / pow(h, 3.0)) ind = np.where(galhg > 0) ax.plot(lbt[ind], galhg[ind] - vol - np.log10(h), 'r', linestyle='dashdot', linewidth=1, label='L-galaxies H15') common.prepare_legend(ax, ['k', 'k', 'k', 'k'], fontsize=10) common.savefig(outdir, fig, "global_hotgas.pdf")
def plot_mf_z(plt, outdir, obsdir, snap, vol_eagle, histmtot, histm30): #construct relevant observational datasets for SMF z0obs = [] lm, p, dpdn, dpup = common.load_observation(obsdir, 'mf/SMF/GAMAII_BBD_GSMFs.dat', [0, 1, 2, 3]) xobs = lm indx = np.where(p > 0) yobs = np.log10(p[indx]) ydn = yobs - np.log10(p[indx] - dpdn[indx]) yup = np.log10(p[indx] + dpup[indx]) - yobs z0obs.append((observation("Wright+2017", xobs[indx], yobs, ydn, yup, err_absolute=False), 'o')) # Moustakas (Chabrier IMF), ['Moustakas+2013, several redshifts'] zdnM13, lmM13, pM13, dp_dn_M13, dp_up_M13 = common.load_observation( obsdir, 'mf/SMF/SMF_Moustakas2013.dat', [0, 3, 5, 6, 7]) xobsM13 = lmM13 yobsM13 = np.full(xobsM13.shape, -999.) lerrM13 = np.full(xobsM13.shape, -999.) herrM13 = np.full(xobsM13.shape, 999.) indx = np.where(pM13 < 1) yobsM13[indx] = (pM13[indx]) indx = np.where(dp_dn_M13 > 0) lerrM13[indx] = dp_dn_M13[indx] indx = np.where(dp_up_M13 > 0) herrM13[indx] = dp_up_M13[indx] # Muzzin (Kroupa IMF), ['Moustakas+2013, several redshifts'] zdnMu13, zupMu13, lmMu13, pMu13, dp_dn_Mu13, dp_up_Mu13 = common.load_observation( obsdir, 'mf/SMF/SMF_Muzzin2013.dat', [0, 1, 2, 4, 5, 5]) # -0.09 corresponds to the IMF correction xobsMu13 = lmMu13 - 0.09 yobsMu13 = np.full(xobsMu13.shape, -999.) lerrMu13 = np.full(xobsMu13.shape, -999.) herrMu13 = np.full(xobsMu13.shape, 999.) indx = np.where(pMu13 < 1) yobsMu13[indx] = (pMu13[indx]) indx = np.where(dp_dn_Mu13 > 0) lerrMu13[indx] = dp_dn_Mu13[indx] indx = np.where(dp_up_Mu13 > 0) herrMu13[indx] = dp_up_Mu13[indx] # Santini 2012 (Salpeter IMF) zdnS12, lmS12, pS12, dp_dn_S12, dp_up_S12 = common.load_observation( obsdir, 'mf/SMF/SMF_Santini2012.dat', [0, 2, 3, 4, 5]) hobs = 0.7 # factor 0.24 corresponds to the IMF correction. xobsS12 = lmS12 - 0.24 + np.log10(hobs / h0) yobsS12 = np.full(xobsS12.shape, -999.) lerrS12 = np.full(xobsS12.shape, -999.) herrS12 = np.full(xobsS12.shape, 999.) indx = np.where(pS12 < 1) yobsS12[indx] = (pS12[indx]) + np.log10(pow(h0 / hobs, 3.0)) indx = np.where(dp_dn_S12 > 0) lerrS12[indx] = dp_dn_S12[indx] indx = np.where(dp_up_S12 > 0) herrS12[indx] = dp_up_S12[indx] # Wright et al. (2018, several reshifts). Assumes Chabrier IMF. zD17, lmD17, pD17, dp_dn_D17, dp_up_D17 = common.load_observation( obsdir, 'mf/SMF/Wright18_CombinedSMF.dat', [0, 1, 2, 3, 4]) hobs = 0.7 pD17 = pD17 - 3.0 * np.log10(hobs) lmD17 = lmD17 - np.log10(hobs) # z0.5 obs z05obs = [] in_redshift = np.where(zdnM13 == 0.4) z05obs.append((observation("Moustakas+2013", xobsM13[in_redshift], yobsM13[in_redshift], lerrM13[in_redshift], herrM13[in_redshift], err_absolute=False), 'o')) in_redshift = np.where(zdnMu13 == 0.5) z05obs.append((observation("Muzzin+2013", xobsMu13[in_redshift], yobsMu13[in_redshift], lerrMu13[in_redshift], herrMu13[in_redshift], err_absolute=False), '+')) in_redshift = np.where(zD17 == 0.5) z05obs.append((observation("Wright+2018", lmD17[in_redshift], pD17[in_redshift], dp_dn_D17[in_redshift], dp_up_D17[in_redshift], err_absolute=False), 'D')) # z1 obs z1obs = [] in_redshift = np.where(zdnM13 == 0.8) z1obs.append((observation("Moustakas+2013", xobsM13[in_redshift], yobsM13[in_redshift], lerrM13[in_redshift], herrM13[in_redshift], err_absolute=False), 'o')) in_redshift = np.where(zdnMu13 == 1) z1obs.append((observation("Muzzin+2013", xobsMu13[in_redshift], yobsMu13[in_redshift], lerrMu13[in_redshift], herrMu13[in_redshift], err_absolute=False), '+')) in_redshift = np.where(zD17 == 1) z1obs.append((observation("Wright+2018", lmD17[in_redshift], pD17[in_redshift], dp_dn_D17[in_redshift], dp_up_D17[in_redshift], err_absolute=False), 'D')) #z2 obs z2obs = [] in_redshift = np.where(zupMu13 == 2.5) z2obs.append((observation("Muzzin+2013", xobsMu13[in_redshift], yobsMu13[in_redshift], lerrMu13[in_redshift], herrMu13[in_redshift], err_absolute=False), '+')) in_redshift = np.where(zdnS12 == 1.8) z2obs.append((observation("Santini+2012", xobsS12[in_redshift], yobsS12[in_redshift], lerrS12[in_redshift], herrS12[in_redshift], err_absolute=False), 'o')) in_redshift = np.where(zD17 == 2) z2obs.append((observation("Wright+2018", lmD17[in_redshift], pD17[in_redshift], dp_dn_D17[in_redshift], dp_up_D17[in_redshift], err_absolute=False), 'D')) # z3 obs z3obs = [] in_redshift = np.where(zupMu13 == 3.0) z3obs.append((observation("Muzzin+2013", xobsMu13[in_redshift], yobsMu13[in_redshift], lerrMu13[in_redshift], herrMu13[in_redshift], err_absolute=False), '+')) in_redshift = np.where(zdnS12 == 2.5) z3obs.append((observation("Santini+2012", xobsS12[in_redshift], yobsS12[in_redshift], lerrS12[in_redshift], herrS12[in_redshift], err_absolute=False), 'o')) in_redshift = np.where(zD17 == 3) z3obs.append((observation("Wright+2018", lmD17[in_redshift], pD17[in_redshift], dp_dn_D17[in_redshift], dp_up_D17[in_redshift], err_absolute=False), 'D')) # z4 obs z4obs = [] in_redshift = np.where(zupMu13 == 4.0) z4obs.append((observation("Muzzin+2013", xobsMu13[in_redshift], yobsMu13[in_redshift], lerrMu13[in_redshift], herrMu13[in_redshift], err_absolute=False), '+')) in_redshift = np.where(zdnS12 == 3.5) z4obs.append((observation("Santini+2012", xobsS12[in_redshift], yobsS12[in_redshift], lerrS12[in_redshift], herrS12[in_redshift], err_absolute=False), 'o')) in_redshift = np.where(zD17 == 4) z4obs.append((observation("Wright+2018", lmD17[in_redshift], pD17[in_redshift], dp_dn_D17[in_redshift], dp_up_D17[in_redshift], err_absolute=False), 'D')) ########################### total stellar mass function xtit = "$\\rm log_{10} (\\rm M_{\\star,\\rm tot}/M_{\odot})$" ytit = "$\\rm log_{10}(\Phi/dlog{\\rm M_{\\star}}/{\\rm Mpc}^{-3} )$" xmin, xmax, ymin, ymax = 7, 12, -6, 1 xleg = xmax - 0.2 * (xmax - xmin) yleg = ymax - 0.1 * (ymax - ymin) fig = plt.figure(figsize=(5, 10)) idx = [0, 1, 2] zins = [0, 1, 2] subplots = [311, 312, 313] observations = (z0obs, z1obs, z2obs) for subplot, idx, z, s, obs_and_markers in zip(subplots, idx, zins, snap, observations): ax = fig.add_subplot(subplot) if (idx == 2): xtitplot = xtit else: xtitplot = ' ' common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtitplot, ytit, locators=(0.1, 1, 0.1)) ax.text(xleg, yleg, 'z=%s' % (str(z))) # Observations for obs, marker in obs_and_markers: common.errorbars(ax, obs.x, obs.y, obs.yerrdn, obs.yerrup, 'grey', marker, err_absolute=obs.err_absolute, label=obs.label) #Predicted HMF y = histmtot[idx, :] ind = np.where(y != 0.) if idx == 0: ax.plot(xmf[ind], y[ind], 'r', linestyle='solid', label='VR') if idx > 0: ax.plot(xmf[ind], y[ind], 'r', linestyle='solid') if idx == 0: cols = ['r'] + ['grey', 'grey', 'grey'] common.prepare_legend(ax, cols) common.savefig(outdir, fig, "smf_tot_z_comp_obs.pdf") ############################# stellar mass function (30kpc aperture) xtit = "$\\rm log_{10} (\\rm M_{\\star,\\rm 30kpc}/M_{\odot})$" ytit = "$\\rm log_{10}(\Phi/dlog{\\rm M_{\\star}}/{\\rm Mpc}^{-3} )$" xmin, xmax, ymin, ymax = 7, 12, -6, 1 xleg = xmax - 0.2 * (xmax - xmin) yleg = ymax - 0.1 * (ymax - ymin) fig = plt.figure(figsize=(5, 10)) idx = [0, 1, 2] zins = [0, 1, 2] subplots = [311, 312, 313] for subplot, idx, z, s, obs_and_markers in zip(subplots, idx, zins, snap, observations): ax = fig.add_subplot(subplot) if (idx == 2): xtitplot = xtit else: xtitplot = ' ' common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtitplot, ytit, locators=(0.1, 1, 0.1)) ax.text(xleg, yleg, 'z=%s' % (str(z))) # Observations for obs, marker in obs_and_markers: common.errorbars(ax, obs.x, obs.y, obs.yerrdn, obs.yerrup, 'grey', marker, err_absolute=obs.err_absolute, label=obs.label) #Predicted HMF y = histm30[idx, :] ind = np.where(y != 0.) if idx == 0: ax.plot(xmf[ind], y[ind], 'r', linestyle='solid', label='VR') if idx > 0: ax.plot(xmf[ind], y[ind], 'r', linestyle='solid') if idx == 0: cols = ['r'] + ['grey', 'grey', 'grey'] common.prepare_legend(ax, cols) else: cols = ['grey', 'grey', 'grey'] common.prepare_legend(ax, cols) common.savefig(outdir, fig, "smf_30kpc_z_comp_obs.pdf")
def plot_cosmic_dust(plt, outdir, obsdir, redshifts, h0, mdustden, mdustden_mol): fig = plt.figure(figsize=(5, 4.5)) ax = fig.add_subplot(111) plt.subplots_adjust(bottom=0.15, left=0.15) xtit = "$\\rm Lookback\,time/Gyr$" ytit = "$\\rm log_{10}(\\rho_{\\rm dust}/ M_{\odot}\,cMpc^{-3})$" common.prepare_ax(ax, 0, 13.5, 4, 6.3, xtit, ytit, locators=(0.1, 1, 0.1, 1)) ax2 = ax.twiny() ax2.set_xlim(ax.get_xlim()) new_tick_locations = np.array([0., 2., 4., 6., 8., 10., 12.]) ax2.set_xticks(new_tick_locations) ax2.set_xticklabels(us.redshift(new_tick_locations), fontsize=12) ax2.set_xlabel("redshift", fontsize=13) #note that only h^2 is needed because the volume provides h^3, and the SFR h^-1. ind = np.where(mdustden > 0) ax.plot(us.look_back_time(redshifts[ind]), np.log10(mdustden[ind] * pow(h0, 2.0)), 'r', label='Shark all metals') ind = np.where(mdustden_mol > 0) ax.plot(us.look_back_time(redshifts[ind]), np.log10(mdustden_mol[ind] * pow(h0, 2.0)), 'r', linestyle='dashed', label='Shark metals in molecular gas') #Baldry (Chabrier IMF), ['Baldry+2012, z<0.06'] redD17d, redD17u, smdD17, err1, err2, err3, err4 = common.load_observation( obsdir, 'Global/Driver18_dust.dat', [1, 2, 3, 4, 5, 6, 7]) hobs = 0.7 xobs = (redD17d + redD17u) / 2.0 yobs = smdD17 + np.log10(hobs / h0) err = yobs * 0. - 999. err = np.sqrt( pow(err1, 2.0) + pow(err2, 2.0) + pow(err3, 2.0) + pow(err4, 2.0)) ax.errorbar(us.look_back_time(xobs), yobs, yerr=[err, err], ls='None', mfc='None', ecolor='grey', mec='grey', marker='o', label="Driver+18") common.prepare_legend(ax, ['r', 'r', 'grey']) common.savefig(outdir, fig, "cosmic_dust.pdf")
def plot_omega_HI(plt, outdir, obsdir, redshifts, h0, omegaHI): fig = plt.figure(figsize=(5, 4.5)) ax = fig.add_subplot(111) plt.subplots_adjust(bottom=0.15, left=0.15) xtit = "$\\rm Lookback\, time/Gyr$" ytit = "$\\rm log_{10}(\\Omega_{\\rm H_I})$" common.prepare_ax(ax, 0, 13.5, -5, -2, xtit, ytit, locators=(0.1, 1, 0.1, 1)) ax2 = ax.twiny() ax2.set_xlim(ax.get_xlim()) new_tick_locations = np.array([0., 2., 4., 6., 8., 10., 12.]) ax2.set_xticks(new_tick_locations) ax2.set_xticklabels(us.redshift(new_tick_locations), fontsize=12) ax2.set_xlabel("redshift", fontsize=13) # note that only h^2 is needed because the volume provides h^3, and the SFR h^-1. ind = np.where(omegaHI > 0) ax.plot(us.look_back_time(redshifts[ind]), np.log10(omegaHI[ind] * pow(h0, 2.0)) + np.log10(XH), 'r', label='Shark') z, hi_modelvar = common.load_observation( obsdir, 'Models/SharkVariations/Global_OtherModels.dat', [0, 1]) hi_modelvar_burst3 = hi_modelvar[0:179] hi_modelvar_nu0p5 = hi_modelvar[181:360] hi_modelvar_burst20 = hi_modelvar[360:539] ind = np.where(hi_modelvar_burst20 > -10) ax.plot(us.look_back_time(z[ind]), hi_modelvar_burst20[ind], 'Sienna', linestyle='dotted', label='$\\eta_{\\rm burst}=20$') ind = np.where(hi_modelvar_burst3 > -10) ax.plot(us.look_back_time(z[ind]), hi_modelvar_burst3[ind], 'Crimson', linestyle='dashdot', label='$\\eta_{\\rm burst}=3$') ind = np.where(hi_modelvar_nu0p5 > -10) ax.plot(us.look_back_time(z[ind]), hi_modelvar_nu0p5[ind], 'Salmon', linestyle='dotted', label='$\\nu_{\\rm SF}=0.5 \\rm Gyr^{-1}$') xcgm = np.zeros(shape=2) ycgm = np.zeros(shape=2) xcgm[:] = 2.0 ycgm[0] = -5.0 ycgm[1] = -2.0 ax.plot(us.look_back_time(xcgm), ycgm, 'k', linestyle='dotted', linewidth=0.85) ax.arrow(us.look_back_time(2.0), -2.5, 0.75, 0, head_width=0.05, head_length=0.1, fc='k', ec='k') ax.text(10.55, -2.4, 'CGM?', fontsize=12) # Rhee+18 compilation redR18, reddR18, reduR18, omegaR18, errdnR18, errupR18 = common.load_observation( obsdir, 'Global/HI_density_Rhee18.dat', [1, 2, 3, 7, 8, 9]) ax.errorbar(us.look_back_time(redR18), np.log10(omegaR18 * 1e-3), xerr=[reddR18, reduR18], yerr=[errdnR18, errupR18], ls='None', mfc='None', ecolor='grey', mec='grey', marker='o', label="Rhee+18 (comp)") common.prepare_legend(ax, ['r', 'Sienna', 'Crimson', 'Salmon', 'grey']) common.savefig(outdir, fig, "omega_HI.pdf")
def plot_sfr_mstars_z0(plt, outdir, obsdir, h0, sfr_seq, mainseqsf, sigmamainseqsf, slope_ms_z0, offset_ms_z0): fig = plt.figure(figsize=(5, 5)) xtit = "$\\rm log_{10} (\\rm M_{\\star}/M_{\odot})$" ytit = "$\\rm log_{10}(\\rm SFR/M_{\odot} yr^{-1})$" xmin, xmax, ymin, ymax = 8, 12, -5, 3 ax = fig.add_subplot(111) plt.subplots_adjust(bottom=0.15, left=0.15) common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtit, ytit, locators=(0.1, 1, 0.1, 1)) #predicted relation ind = np.where((sfr_seq[0, :] > 0) & (sfr_seq[1, :] != 0)) xdata = sfr_seq[0, ind] ydata = sfr_seq[1, ind] us.density_contour(ax, xdata[0], ydata[0], 30, 30) #, **contour_kwargs) ind = np.where(mainseqsf[0, 0, :] != 0) xplot = xmf[ind] yplot = mainseqsf[0, 0, ind] ax.plot(xplot, yplot[0], color='k', linestyle='solid', linewidth=1, label="Shark all galaxies") #SFR relation z=0 lm, SFR = common.load_observation(obsdir, 'SFR/Brinchmann04.dat', (0, 1)) hobs = 0.7 #add cosmology correction plus IMF correction that goes into the stellar mass. corr_cos = np.log10(pow(hobs, 2) / pow(h0, 2)) - 0.09 # apply correction to both stellar mass and SFRs. ax.plot(lm[0:35] + corr_cos, SFR[0:35] + corr_cos, color='PaleVioletRed', linewidth=3, linestyle='dashed', label='Brinchmann+04') ax.plot(lm[36:70] + corr_cos, SFR[36:70] + corr_cos, color='PaleVioletRed', linewidth=5, linestyle='dotted') ax.plot(lm[71:len(SFR)] + corr_cos, SFR[71:len(SFR)] + corr_cos, color='PaleVioletRed', linewidth=5, linestyle='dotted') xdataD16 = [9.3, 10.6] ydataD16 = [-0.39, 0.477] ax.plot(xdataD16, ydataD16, color='b', linestyle='dashdot', linewidth=4, label='Davies+16') ax.plot(xmf, (slope_ms_z0 * xmf + offset_ms_z0) + xmf - 9.0, linewidth=3, linestyle='solid', color='grey', label='MS fit Shark') # Legend common.prepare_legend(ax, ['k', 'PaleVioletRed', 'b', 'grey'], loc=2) common.savefig(outdir, fig, 'SFR_Mstars_z0_MSShark.pdf') #plot scatter of the MS for all different definitions. fig = plt.figure(figsize=(5, 5)) ytit = "$\\rm \\sigma_{\\rm SSFR}$" xtit = "$\\rm log_{10}(\\rm M_{\\star}/M_{\odot})$" xmin, xmax, ymin, ymax = 7, 11, 0, 1.4 ax = fig.add_subplot(111) plt.subplots_adjust(bottom=0.15, left=0.15) common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtit, ytit, locators=(0.1, 1, 0.1, 1)) ax.text(7.2, 1.3, '$\\rm SSFR>\\alpha MS(M_{\\star},fit)$') #predicted relation inputs = [0, 1, 2, 3, 4, 5] labels = [ '$\\rm all$', '$\\rm log_{10}(SSFR/Gyr^{-1})>-2$', '$\\alpha=0.1$', '$\\alpha=0.12$', '$\\alpha=0.158$', '$\\alpha=0.25$' ] colors = ['k', 'b', 'LightSteelBlue', 'Orange', 'Red', 'DarkSalmon'] lines = ['solid', 'dashed', 'dotted', 'dashdot', 'solid', 'dotted'] for j in zip(inputs[:]): i = j[0] ind = np.where(sigmamainseqsf[0, i, :] != 0) yplot = sigmamainseqsf[0, i, ind] ax.plot(xmf[ind], yplot[0], color=colors[i], linestyle=lines[i], linewidth=1, label=labels[i]) common.prepare_legend(ax, colors, bbox_to_anchor=(0.1, 0.45)) common.savefig(outdir, fig, 'Scatter_mainsquence_z0.pdf') #plot scatter of the MS across redshifts. fig = plt.figure(figsize=(5, 5)) ytit = "$\\rm \\sigma_{\\rm SSFR}$" xtit = "$\\rm log_{10}(\\rm M_{\\star}/M_{\odot})$" xmin, xmax, ymin, ymax = 7, 11, 0, 1.4 ax = fig.add_subplot(111) plt.subplots_adjust(bottom=0.15, left=0.15) common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtit, ytit, locators=(0.1, 1, 0.1, 1)) #predicted relation inputs = [0, 1, 2, 3, 4, 5] labels = ['z=0', 'z=0.5', 'z=1', 'z=2', 'z=3', 'z=4'] colors = ['k', 'b', 'DarkTurquoise', 'YellowGreen', 'Gold', 'red'] lines = ['solid', 'dashed', 'dotted', 'dashdot', 'solid', 'dotted'] for j in zip(inputs[:]): i = j[0] ind = np.where(sigmamainseqsf[i, 4, :] != 0) yplot = sigmamainseqsf[i, 4, ind] ax.plot(xmf[ind], yplot[0], color=colors[i], linestyle=lines[i], linewidth=1, label=labels[i]) common.prepare_legend(ax, colors, bbox_to_anchor=(0.1, 0.45)) common.savefig(outdir, fig, 'Scatter_mainsquence_z_evolution.pdf')
def plot_passive_fraction(plt, outdir, obsdir, passive_fractions, hist_ssfr, passive_fractions_cens_sats): fig = plt.figure(figsize=(5, 4.5)) xtit = "$\\rm log_{10} (\\rm M_{\\star}/M_{\odot})$" ytit = "$\\rm passive\,fraction$" xmin, xmax, ymin, ymax = 8, 12, 0, 1 ax = fig.add_subplot(111) plt.subplots_adjust(bottom=0.15, left=0.15) common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtit, ytit, locators=(0.1, 1, 0.1, 1)) ind = np.where(passive_fractions[0, 0, :] >= 0) xplot = xmf2[ind] yplot = passive_fractions[0, 0, ind] ax.plot(xplot, yplot[0], color='k', linestyle='solid', linewidth=1, label="Shark all galaxies") ind = np.where(passive_fractions[0, 1, :] >= 0) xplot = xmf2[ind] yplot = passive_fractions[0, 1, ind] ax.plot(xplot, yplot[0], color='b', linestyle='solid', linewidth=1, label="$\\rm M_{\\rm halo}<10^{12}\,M_{\odot}$") ind = np.where(passive_fractions[0, 2, :] >= 0) xplot = xmf2[ind] yplot = passive_fractions[0, 2, ind] ax.plot(xplot, yplot[0], color='r', linestyle='solid', linewidth=1, label="$\\rm M_{\\rm halo}> 10^{12}\,M_{\odot}$") #passive fraction z=0 lm, frac = common.load_observation( obsdir, 'SFR/PassiveFraction_Halpha_Davies16.dat', (0, 1)) ax.plot(lm[0:6], frac[0:6], color='k', linewidth=2, linestyle='dotted', label='Davies+16 all galaxies') ax.plot(lm[8:14], frac[8:14], color='b', linewidth=2, linestyle='dotted', label='Davies+16 isolated') ax.plot(lm[16:20], frac[16:20], color='r', linewidth=2, linestyle='dotted', label='Davies+16 groups') # Legend common.prepare_legend(ax, ['k', 'b', 'r', 'k', 'b', 'r'], loc=2) common.savefig(outdir, fig, 'passive_fraction_z0.pdf') #plot passive fraction for satellites/centrals in bins of stellar mass and halo mass fig = plt.figure(figsize=(12, 9)) xtit = "$\\rm log_{10} (\\rm M_{\\rm halo}/M_{\odot})$" ytit = "$\\rm passive\,fraction$" subplots = (231, 232, 233, 234, 235, 236) titles = ('$\\rm 9<log_{10} (\\rm M_{\\star}/M_{\odot})<9.4$', '$\\rm 9.4<log_{10} (\\rm M_{\\star}/M_{\odot})<9.8$', '$\\rm 9.8<log_{10} (\\rm M_{\\star}/M_{\odot})<10.2$', '$\\rm 10.2<log_{10} (\\rm M_{\\star}/M_{\odot})<10.6$', '$\\rm 10.6<log_{10} (\\rm M_{\\star}/M_{\odot})<11$', '$\\rm 11<log_{10} (\\rm M_{\\star}/M_{\odot})<11.4$') xmin, xmax, ymin, ymax = 11, 14.5, 0, 1 for j in range(0, 6): ax = fig.add_subplot(subplots[j]) plt.subplots_adjust(bottom=0.15, left=0.15) xtitin = xtit if (j < 3): xtitin = "" common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtitin, ytit, locators=(0.1, 1, 0.1, 1)) ax.text(11.1, 1.03, titles[j]) ind = np.where(passive_fractions_cens_sats[0, 0, j, :] != 0) xplot = xmf2[ind] yplot = passive_fractions_cens_sats[0, 0, j, ind] ax.plot(xplot, yplot[0], color='b', linestyle='solid', linewidth=1, label="centrals") ind = np.where(passive_fractions_cens_sats[0, 1, j, :] != 0) xplot = xmf2[ind] yplot = passive_fractions_cens_sats[0, 1, j, ind] ax.plot(xplot, yplot[0], color='r', linestyle='dashed', linewidth=1, label="satellites") if (j == 0): # Legend common.prepare_legend(ax, ['b', 'r'], loc=2) common.savefig(outdir, fig, 'passive_fraction_z0_mhalo-mstars.pdf')
def plot_bt_fractions(plt, outdir, obsdir, BT_fractions, BT_fractions_nodiskins, BT_fractions_centrals, BT_fractions_satellites): fig = plt.figure(figsize=(5, 4.5)) xtit = "$\\rm log_{10} (\\rm M_{\\star}/M_{\odot})$" ytit = "$\\rm f_{\\rm bulge}$" xmin, xmax, ymin, ymax = 8, 12, -0.1, 1.05 # LTG ################################## ax = fig.add_subplot(111) plt.subplots_adjust(bottom=0.15, left=0.15) common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtit, ytit, locators=(0.1, 1, 0.1, 1)) #Predicted size-mass for disks ind = np.where(BT_fractions[0, :] >= 0) if (len(xmf[ind]) > 0): xplot = xmf[ind] yplot = BT_fractions[0, ind] ax.plot(xplot, yplot[0], 'k', label='bulges built by all processes') #for i in zip(BT_fractions[0,:]): # print i ind = np.where(BT_fractions_nodiskins[0, :] >= 0) if (len(xmf[ind]) > 0): xplot = xmf[ind] yplot = BT_fractions_nodiskins[0, ind] ax.plot(xplot, yplot[0], 'r', linestyle='dashed', label='only by mergers') #ind = np.where(BT_fractions_centrals[0,:] >= 0) #if(len(xmf[ind]) > 0): # xplot = xmf[ind] # yplot = BT_fractions_centrals[0,ind] # ax.plot(xplot,yplot[0],'k', linestyle = 'dotted', label ='centrals') #ind = np.where(BT_fractions_satellites[0,:] >= 0) #if(len(xmf[ind]) > 0): # xplot = xmf[ind] # yplot = BT_fractions_satellites[0,ind] # ax.plot(xplot,yplot[0],'k', linestyle = 'dashed', label ='satellites') BT_othermodels = common.load_observation( obsdir, 'Models/SharkVariations/BTFractions_OtherModels.dat', [0]) BT_stable0 = BT_othermodels[0:29] BT_stable0p5 = BT_othermodels[30:60] BT_stable1 = BT_othermodels[91:120] ind = np.where(BT_stable0 >= 0) xplot = xmf[ind] yplot = BT_stable0[ind] ax.plot(xplot, yplot, color='Goldenrod', linestyle='dashdot', label='$\\epsilon_{\\rm disk}=0$') ind = np.where(BT_stable1 >= 0) xplot = xmf[ind] yplot = BT_stable1[ind] ax.plot(xplot, yplot, color='Orange', linestyle='dotted', label='$\\epsilon_{\\rm disk}=1$') #Baldry (Chabrier IMF), ['Baldry+2012, z<0.06'] mM16, fM16, errdnfM16, errupfM16 = common.load_observation( obsdir, 'Morph/Moffet16.dat', [0, 1, 2, 3]) errdnfM16 = np.abs(errdnfM16 - fM16) errupfM16 = np.abs(errupfM16 - fM16) ax.errorbar(mM16, fM16, yerr=[errdnfM16, errupfM16], ls='None', mfc='None', ecolor='grey', mec='grey', marker='^', label="Moffett+16") common.prepare_legend(ax, ['k', 'r', 'Goldenrod', 'Orange', 'grey'], loc=2) common.savefig(outdir, fig, 'BTfractions.pdf')
def _load_resolve_mf_obs(obsdir, fname, cols): return common.load_observation(obsdir, 'RESOLVE/massfuncs/' + fname, cols)
def plot_cosmic_sfr(plt, outdir, obsdir, redshifts, h0, sfr, sfrd, sfrb, history_interactions, mDMden): fig = plt.figure(figsize=(5, 9)) xtit = "$\\rm redshift$" ytit = "$\\rm log_{10}(CSFRD/ M_{\odot}\,yr^{-1}\,cMpc^{-3})$" ax = fig.add_subplot(211) plt.subplots_adjust(left=0.15) common.prepare_ax(ax, 0, 10, -3, -0.5, xtit, ytit, locators=(0.1, 1, 0.1, 1)) #Baldry (Chabrier IMF), ['Baldry+2012, z<0.06'] redK11, SFRK11, err_upK11, err_dnK11 = common.load_observation( obsdir, 'Global/SFRD_Karim11.dat', [0, 1, 2, 3]) hobs = 0.7 xobs = redK11 yobs = xobs * 0. - 999. indx = np.where(SFRK11 > 0) yobs[indx] = np.log10(SFRK11[indx] * pow(hobs / h0, 2.0)) lerr = yobs * 0. - 999. indx = np.where((SFRK11 - err_dnK11) > 0) lerr[indx] = np.log10(SFRK11[indx] - err_dnK11[indx]) herr = yobs * 0. + 999. indx = np.where((SFRK11 + err_upK11) > 0) herr[indx] = np.log10(SFRK11[indx] + err_upK11[indx]) ax.errorbar(xobs[0:8], yobs[0:8], yerr=[yobs[0:8] - lerr[0:8], herr[0:8] - yobs[0:8]], ls='None', mfc='None', ecolor='grey', mec='grey', marker='D') ax.errorbar(xobs[9:17], yobs[9:17], yerr=[yobs[9:17] - lerr[9:17], herr[9:17] - yobs[9:17]], ls='None', mfc='None', ecolor='grey', mec='grey', marker='x') #Driver (Chabrier IMF), ['Baldry+2012, z<0.06'] redD17d, redD17u, sfrD17, err1, err2, err3, err4 = common.load_observation( obsdir, 'Global/Driver18_sfr.dat', [0, 1, 2, 3, 4, 5, 6]) hobs = 0.7 xobsD17 = (redD17d + redD17u) / 2.0 yobsD17 = sfrD17 + np.log10(hobs / h0) errD17 = yobs * 0. - 999. errD17 = np.sqrt( pow(err1, 2.0) + pow(err2, 2.0) + pow(err3, 2.0) + pow(err4, 2.0)) ax.errorbar(xobsD17, yobsD17, yerr=[errD17, errD17], ls='None', mfc='None', ecolor='grey', mec='grey', marker='o') #note that only h^2 is needed because the volume provides h^3, and the SFR h^-1. ind = np.where(sfr > 0) ax.plot(redshifts[ind], np.log10(sfr[ind] * pow(h0, 2.0)), 'k', linewidth=1, label='total') ind = np.where(sfrd > 0) ax.plot(redshifts[ind], np.log10(sfrd[ind] * pow(h0, 2.0)), 'b', linestyle='dashed', linewidth=1, label='quiescent') ind = np.where(sfrb > 0) ax.plot(redshifts[ind], np.log10(sfrb[ind] * pow(h0, 2.0)), 'r', linestyle='dotted', linewidth=1, label='bursts') z, sfr_modelvar = common.load_observation( obsdir, 'Models/SharkVariations/Global_OtherModels.dat', [0, 3]) sfr_modelvar_burst3 = sfr_modelvar[0:179] sfr_modelvar_nu0p5 = sfr_modelvar[179:359] sfr_modelvar_burst20 = sfr_modelvar[360:539] ind = np.where(sfr_modelvar_burst20 > -10) ax.plot(z[ind], sfr_modelvar_burst20[ind], 'Sienna', linestyle='dotted', label='$\\eta_{\\rm burst}=20$') ind = np.where(sfr_modelvar_burst3 > -10) ax.plot(z[ind], sfr_modelvar_burst3[ind], 'DarkSlateGray', linestyle='dashdot', label='$\\eta_{\\rm burst}=3$') ind = np.where(sfr_modelvar_nu0p5 > -10) ax.plot(z[ind], sfr_modelvar_nu0p5[ind], 'SlateGray', linestyle='dotted', label='$\\nu_{\\rm SF}=0.5 \\rm Gyr^{-1}$') common.prepare_legend(ax, [ 'k', 'b', 'r', 'Sienna', 'DarkSlateGray', 'SlateGray', 'grey', 'grey', 'grey' ], bbox_to_anchor=(0.52, 0.47)) xtit = "$\\rm Lookback\, time/Gyr$" ax = fig.add_subplot(212) plt.subplots_adjust(left=0.15) common.prepare_ax(ax, 0, 13.5, -3, -0.5, xtit, ytit, locators=(0.1, 1, 0.1, 1)) ax.errorbar(us.look_back_time(xobs[0:8]), yobs[0:8], yerr=[yobs[0:8] - lerr[0:8], herr[0:8] - yobs[0:8]], ls='None', mfc='None', ecolor='grey', mec='grey', marker='D', label="Karim+11 obs") ax.errorbar(us.look_back_time(xobs[9:17]), yobs[9:17], yerr=[yobs[9:17] - lerr[9:17], herr[9:17] - yobs[9:17]], ls='None', mfc='None', ecolor='grey', mec='grey', marker='x', label="Karim+11 extr") ax.errorbar(us.look_back_time(xobsD17), yobsD17, yerr=[errD17, errD17], ls='None', mfc='None', ecolor='grey', mec='grey', marker='o', label="Driver+18") ind = np.where(sfr > 0) ax.plot(us.look_back_time(redshifts[ind]), np.log10(sfr[ind] * pow(h0, 2.0)), 'k', linewidth=1) ind = np.where(sfrd > 0) ax.plot(us.look_back_time(redshifts[ind]), np.log10(sfrd[ind] * pow(h0, 2.0)), 'b', linestyle='dashed', linewidth=1) ind = np.where(sfrb > 0) ax.plot(us.look_back_time(redshifts[ind]), np.log10(sfrb[ind] * pow(h0, 2.0)), 'r', linestyle='dotted', linewidth=1) ind = np.where(sfr_modelvar_burst20 > -10) ax.plot(us.look_back_time(z[ind]), sfr_modelvar_burst20[ind], 'Sienna', linestyle='dotted') ind = np.where(sfr_modelvar_burst3 > -10) ax.plot(us.look_back_time(z[ind]), sfr_modelvar_burst3[ind], 'DarkSlateGray', linestyle='dashdot') ind = np.where(sfr_modelvar_nu0p5 > -10) ax.plot(us.look_back_time(z[ind]), sfr_modelvar_nu0p5[ind], 'SlateGray', linestyle='dotted') common.prepare_legend(ax, ['grey', 'grey', 'grey'], loc=2) common.savefig(outdir, fig, "cosmic_sfr.pdf") #create plot with interaction history fig = plt.figure(figsize=(5, 4)) xtit = "$\\rm redshift$" ytit = "$\\rm log_{10}(density\,rate/Mpc^{-3} h^{-3} Gyr^{-1})$" ax = fig.add_subplot(111) plt.subplots_adjust(left=0.15) common.prepare_ax(ax, 0, 10, -4, 0, xtit, ytit, locators=(0.1, 1, 0.1, 1)) delta_time = np.zeros(shape=(len(redshifts))) for i in range(0, len(redshifts)): if (i == 0): delta_time[i] = 13.7969 - us.look_back_time(redshifts[i]) if (i < len(redshifts)): delta_time[i] = us.look_back_time( redshifts[i - 1]) - us.look_back_time(redshifts[i]) #note that only h^2 is needed because the volume provides h^3, and the SFR h^-1. ind = np.where(history_interactions[0, :] + history_interactions[1, :] > 0) yplot = np.log10( (history_interactions[0, ind] + history_interactions[1, ind]) / delta_time[ind]) ax.plot(redshifts[ind], yplot[0], 'k', linewidth=1, label='mergers') ind = np.where(history_interactions[2, :] > 0) yplot = np.log10(history_interactions[2, ind] / delta_time[ind]) ax.plot(redshifts[ind], yplot[0], 'b', linewidth=1, label='disk instabilities') ind = np.where(mDMden[:] > 0) yplot = np.log10(mDMden[ind]) - 11.0 ax.plot(redshifts[ind], yplot, 'r', linewidth=1, label='DM mass(-11dex)') common.prepare_legend(ax, ['k', 'b', 'r'], loc=3) common.savefig(outdir, fig, "interaction_history.pdf") #create plot with interaction history fig = plt.figure(figsize=(5, 4)) xtit = "$\\rm redshift$" ytit = "$\\rm delta\, time/Gyr$" ax = fig.add_subplot(111) plt.subplots_adjust(left=0.15) common.prepare_ax(ax, 0, 10, 0, 0.3, xtit, ytit, locators=(0.1, 1, 0.1, 0.1)) #note that only h^2 is needed because the volume provides h^3, and the SFR h^-1. ax.plot(redshifts, delta_time, 'k', linewidth=1) common.savefig(outdir, fig, "delta_time_history.pdf")
def plot_scaling_z(plt, outdir, obsdir, snap, SFRMstar, R50Mstar, R50Mstar30, MBHMstar, SigmaMstar30, ZstarMstar, ZSFMstar, AgeSMstar, SFRMstar30, R50pMstar30): #define observaiton of the MS at z=0 to be plotted def obs_mainseq_z0(): #best fit from Davies et al. (2016) xdataD16 = [9.3, 10.6] ydataD16 = [-0.39, 0.477] ax.plot(xdataD16, ydataD16, color='b', linestyle='dashdot', linewidth=4, label='Davies+16') #SDSS z=0 relation lm, SFR = common.load_observation(obsdir, 'SFR/Brinchmann04.dat', (0, 1)) hobs = 0.7 #add cosmology correction plus IMF correction that goes into the stellar mass. corr_cos = np.log10(pow(hobs, 2) / pow(h0, 2)) - 0.09 # apply correction to both stellar mass and SFRs. ax.plot(lm[0:35] + corr_cos, SFR[0:35] + corr_cos, color='PaleVioletRed', linewidth=3, linestyle='dashed', label='Brinchmann+04') ax.plot(lm[36:70] + corr_cos, SFR[36:70] + corr_cos, color='PaleVioletRed', linewidth=5, linestyle='dotted') ax.plot(lm[71:len(SFR)] + corr_cos, SFR[71:len(SFR)] + corr_cos, color='PaleVioletRed', linewidth=5, linestyle='dotted') ########################### will plot main sequence for all stellar particles in the subhalo xtit = "$\\rm log_{10} (\\rm M_{\\star, tot}/M_{\odot})$" ytit = "$\\rm log_{10}(\\rm SFR/M_{\odot} yr^{-1})$" xmin, xmax, ymin, ymax = 7, 12, -5, 1.5 xleg = xmax - 0.2 * (xmax - xmin) yleg = ymax - 0.1 * (ymax - ymin) fig = plt.figure(figsize=(5, 10)) idx = [0, 1, 2] zins = [0, 1, 2] subplots = [311, 312, 313] for subplot, idx, z, s in zip(subplots, idx, zins, snap): ax = fig.add_subplot(subplot) if (idx == 2): xtitplot = xtit else: xtitplot = ' ' common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtitplot, ytit, locators=(0.1, 1, 0.1)) ax.text(xleg, yleg, 'z=%s' % (str(z))) #observations z=0 if (z == 0): obs_mainseq_z0() #VR ind = np.where(SFRMstar[idx, 0, :] != 0.) xplot = xmf[ind] yplot = SFRMstar[idx, 0, ind] errdn = SFRMstar[idx, 1, ind] errup = SFRMstar[idx, 2, ind] if idx == 0: ax.plot(xplot, yplot[0], 'k', label='VR') if idx > 0: ax.plot(xplot, yplot[0], 'k') ax.fill_between(xplot, yplot[0], yplot[0] - errdn[0], facecolor='k', alpha=0.2, interpolate=True) ax.fill_between(xplot, yplot[0], yplot[0] + errup[0], facecolor='k', alpha=0.2, interpolate=True) if idx == 0: common.prepare_legend(ax, ['b', 'PaleVioletRed', 'k']) common.savefig(outdir, fig, "main_sequence_z_comp_obs.pdf") ########################### will plot main sequence for 30kpc aperture xtit = "$\\rm log_{10} (\\rm M_{\\star, 30kpc}/M_{\odot})$" ytit = "$\\rm log_{10}(\\rm SFR_{\\rm 30kpc}/M_{\odot} yr^{-1})$" xmin, xmax, ymin, ymax = 7, 12, -5, 1.5 xleg = xmax - 0.2 * (xmax - xmin) yleg = ymax - 0.1 * (ymax - ymin) fig = plt.figure(figsize=(5, 10)) idx = [0, 1, 2] zins = [0, 1, 2] subplots = [311, 312, 313] for subplot, idx, z, s in zip(subplots, idx, zins, snap): ax = fig.add_subplot(subplot) if (idx == 2): xtitplot = xtit else: xtitplot = ' ' common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtitplot, ytit, locators=(0.1, 1, 0.1)) ax.text(xleg, yleg, 'z=%s' % (str(z))) #observations z=0 if (z == 0): obs_mainseq_z0() #VR ind = np.where(SFRMstar30[idx, 0, :] != 0.) xplot = xmf[ind] yplot = SFRMstar30[idx, 0, ind] errdn = SFRMstar30[idx, 1, ind] errup = SFRMstar30[idx, 2, ind] if idx == 0: ax.plot(xplot, yplot[0], 'k', label='VR') if idx > 0: ax.plot(xplot, yplot[0], 'k') ax.fill_between(xplot, yplot[0], yplot[0] - errdn[0], facecolor='k', alpha=0.2, interpolate=True) ax.fill_between(xplot, yplot[0], yplot[0] + errup[0], facecolor='k', alpha=0.2, interpolate=True) if idx == 0: common.prepare_legend(ax, ['b', 'PaleVioletRed', 'k']) common.savefig(outdir, fig, "main_sequence_30kpc_z_comp_obs.pdf") ########################### will plot r50 vs stellar mass for all stellar particles in the subhalo #define observations first def plot_gama_size_mass(): m, r = common.load_observation(obsdir, 'SizesAndAM/rdisk_L16.dat', [0, 1]) ax.plot(m[0:36], r[0:36], linestyle='dotted', color='b', label='L16 disks') ax.plot(m[38:83], r[38:83], linestyle='dotted', color='b') ax.plot(m[85:128], r[85:129], linestyle='dotted', color='b') m, r = common.load_observation(obsdir, 'SizesAndAM/rbulge_L16.dat', [0, 1]) ax.plot(m[0:39], r[0:39], linestyle='dotted', color='darkgreen', label='L16 bulges') ax.plot(m[41:76], r[41:76], linestyle='dotted', color='darkgreen') ax.plot(m[78:115], r[78:115], linestyle='dotted', color='darkgreen') xtit = "$\\rm log_{10} (\\rm M_{\\star,tot}/M_{\odot})$" ytit = "$\\rm log_{10}(\\rm R_{\\rm 50,tot}/pkpc)$" xmin, xmax, ymin, ymax = 7, 12, -0.3, 2 xleg = xmax - 0.2 * (xmax - xmin) yleg = ymax - 0.1 * (ymax - ymin) fig = plt.figure(figsize=(5, 10)) idx = [0, 1, 2] zins = [0, 1, 2] subplots = [311, 312, 313] for subplot, idx, z, s in zip(subplots, idx, zins, snap): ax = fig.add_subplot(subplot) if (idx == 2): xtitplot = xtit else: xtitplot = ' ' common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtitplot, ytit, locators=(0.1, 1, 0.1)) plt.subplots_adjust(left=0.2) ax.text(xleg, yleg, 'z=%s' % (str(z))) if (z == 0): plot_gama_size_mass() #VR ind = np.where(R50Mstar[idx, 0, :] != 0.) xplot = xmf[ind] yplot = R50Mstar[idx, 0, ind] + 3.0 errdn = R50Mstar[idx, 1, ind] errup = R50Mstar[idx, 2, ind] if idx == 0: ax.plot(xplot, yplot[0], 'k', label='VR') if idx > 0: ax.plot(xplot, yplot[0], 'k') ax.fill_between(xplot, yplot[0], yplot[0] - errdn[0], facecolor='k', alpha=0.2, interpolate=True) ax.fill_between(xplot, yplot[0], yplot[0] + errup[0], facecolor='k', alpha=0.2, interpolate=True) if idx == 0: common.prepare_legend(ax, ['b', 'darkgreen', 'k'], loc='upper left') common.savefig(outdir, fig, "r50_Mstar_z_comp_obs.pdf") ################## will plot r50 vs stellar mass for quantities measured within 30kpc xtit = "$\\rm log_{10} (\\rm M_{\\star,30kpc}/M_{\odot})$" ytit = "$\\rm log_{10}(\\rm R_{\\rm 50,30kpc}/pkpc)$" xmin, xmax, ymin, ymax = 7, 12, -0.3, 2 xleg = xmax - 0.2 * (xmax - xmin) yleg = ymax - 0.1 * (ymax - ymin) fig = plt.figure(figsize=(5, 10)) idx = [0, 1, 2] zins = [0, 1, 2] subplots = [311, 312, 313] for subplot, idx, z, s in zip(subplots, idx, zins, snap): ax = fig.add_subplot(subplot) if (idx == 2): xtitplot = xtit else: xtitplot = ' ' common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtitplot, ytit, locators=(0.1, 1, 0.1)) plt.subplots_adjust(left=0.2) ax.text(xleg, yleg, 'z=%s' % (str(z))) if (z == 0): plot_gama_size_mass() #VR ind = np.where(R50Mstar30[idx, 0, :] != 0.) xplot = xmf[ind] yplot = R50Mstar30[idx, 0, ind] + 3.0 errdn = R50Mstar30[idx, 1, ind] errup = R50Mstar30[idx, 2, ind] if idx == 0: ax.plot(xplot, yplot[0], 'k', label='VR') if idx > 0: ax.plot(xplot, yplot[0], 'k') ax.fill_between(xplot, yplot[0], yplot[0] - errdn[0], facecolor='k', alpha=0.2, interpolate=True) ax.fill_between(xplot, yplot[0], yplot[0] + errup[0], facecolor='k', alpha=0.2, interpolate=True) if idx == 0: common.prepare_legend(ax, ['b', 'darkgreen', 'k'], loc='upper left') common.savefig(outdir, fig, "r50_Mstar_30kpc_z_comp_obs.pdf") ################## will plot r50 vs stellar mass for quantities measured within 30kpc, but in this case the r50 is projected xtit = "$\\rm log_{10} (\\rm M_{\\star,30kpc}/M_{\odot})$" ytit = "$\\rm log_{10}(\\rm R_{\\rm 50,30kpc,2D}/pkpc)$" xmin, xmax, ymin, ymax = 7, 12, -0.3, 2 xleg = xmax - 0.2 * (xmax - xmin) yleg = ymax - 0.1 * (ymax - ymin) fig = plt.figure(figsize=(5, 10)) idx = [0, 1, 2] zins = [0, 1, 2] subplots = [311, 312, 313] for subplot, idx, z, s in zip(subplots, idx, zins, snap): ax = fig.add_subplot(subplot) if (idx == 2): xtitplot = xtit else: xtitplot = ' ' common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtitplot, ytit, locators=(0.1, 1, 0.1)) plt.subplots_adjust(left=0.2) ax.text(xleg, yleg, 'z=%s' % (str(z))) if (z == 0): plot_gama_size_mass() #VR ind = np.where(R50pMstar30[idx, 0, :] != 0.) xplot = xmf[ind] yplot = R50pMstar30[idx, 0, ind] + 3.0 errdn = R50pMstar30[idx, 1, ind] errup = R50pMstar30[idx, 2, ind] if idx == 0: ax.plot(xplot, yplot[0], 'k', label='VR') if idx > 0: ax.plot(xplot, yplot[0], 'k') ax.fill_between(xplot, yplot[0], yplot[0] - errdn[0], facecolor='k', alpha=0.2, interpolate=True) ax.fill_between(xplot, yplot[0], yplot[0] + errup[0], facecolor='k', alpha=0.2, interpolate=True) if idx == 0: common.prepare_legend(ax, ['b', 'darkgreen', 'k'], loc='upper left') common.savefig(outdir, fig, "r50_projected_Mstar_30kpc_z_comp_obs.pdf") ########################### will plot stellar velocity dispersion vs. stellar mass xtit = "$\\rm log_{10} (\\rm M_{\\star,30kpc}/M_{\odot})$" ytit = "$\\rm log_{10}(\\sigma_{\\star,30kpc}/km s^{-1})$" xmin, xmax, ymin, ymax = 7, 12, 1, 3 xleg = xmax - 0.2 * (xmax - xmin) yleg = ymax - 0.1 * (ymax - ymin) fig = plt.figure(figsize=(5, 10)) idx = [0, 1, 2] zins = [0, 1, 2] subplots = [311, 312, 313] for subplot, idx, z, s in zip(subplots, idx, zins, snap): ax = fig.add_subplot(subplot) if (idx == 2): xtitplot = xtit else: xtitplot = ' ' common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtitplot, ytit, locators=(0.1, 1, 0.1)) plt.subplots_adjust(left=0.2) ax.text(xleg, yleg, 'z=%s' % (str(z))) #VR ind = np.where(SigmaMstar30[idx, 0, :] != 0.) xplot = xmf[ind] yplot = SigmaMstar30[idx, 0, ind] errdn = SigmaMstar30[idx, 1, ind] errup = SigmaMstar30[idx, 2, ind] if idx == 0: ax.plot(xplot, yplot[0], 'k', label='VR') if idx > 0: ax.plot(xplot, yplot[0], 'k') ax.fill_between(xplot, yplot[0], yplot[0] - errdn[0], facecolor='k', alpha=0.2, interpolate=True) ax.fill_between(xplot, yplot[0], yplot[0] + errup[0], facecolor='k', alpha=0.2, interpolate=True) #observations if (z == 0): lm, sig, sigdn, sigup = common.load_observation( obsdir, 'StellarPops/vdS19-sigma.csv', [0, 1, 2, 3]) sig = np.log10(sig) sigdn = np.log10(sigdn) sigup = np.log10(sigup) common.errorbars(ax, lm, sig, sigdn, sigup, 'b', 'D', label='van de Sande+19') if idx == 0: common.prepare_legend(ax, ['k'], loc='upper left') common.savefig(outdir, fig, "vdisp_Mstar_30kpc_z_comp_obs.pdf") ############ will plot stellar metallicity-stellar mass xtit = "$\\rm log_{10} (\\rm M_{\\star, 30kpc}/M_{\odot})$" ytit = "$\\rm log_{10}(\\rm Z_{\star}/Z_{\\odot})$" xmin, xmax, ymin, ymax = 7, 12, -2, 1 xleg = xmax - 0.2 * (xmax - xmin) yleg = ymax - 0.1 * (ymax - ymin) fig = plt.figure(figsize=(5, 10)) idx = [0, 1, 2] zins = [0, 1, 2] subplots = [311, 312, 313] for subplot, idx, z, s in zip(subplots, idx, zins, snap): ax = fig.add_subplot(subplot) if (idx == 2): xtitplot = xtit else: xtitplot = ' ' common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtitplot, ytit, locators=(0.1, 1, 0.1)) ax.text(xleg, yleg, 'z=%s' % (str(z))) plt.subplots_adjust(left=0.2) #VR ind = np.where(ZstarMstar[idx, 0, :] != 0.) xplot = xmf[ind] yplot = ZstarMstar[idx, 0, ind] - log10zsun errdn = ZstarMstar[idx, 1, ind] errup = ZstarMstar[idx, 2, ind] if idx == 0: ax.plot(xplot, yplot[0], 'k', label='VR') if idx > 0: ax.plot(xplot, yplot[0], 'k') ax.fill_between(xplot, yplot[0], yplot[0] - errdn[0], facecolor='k', alpha=0.2, interpolate=True) ax.fill_between(xplot, yplot[0], yplot[0] + errup[0], facecolor='k', alpha=0.2, interpolate=True) #observations if (z == 0): lm, mz, mzdn, mzup = common.load_observation( obsdir, 'MZR/MSZR-Gallazzi05.dat', [0, 1, 2, 3]) common.errorbars(ax, lm[0:7], mz[0:7], mzdn[0:7], mzup[0:7], 'b', 'D', label='Kirby+13') common.errorbars(ax, lm[7:22], mz[7:22], mzdn[7:22], mzup[7:22], 'b', 'o', label='Gallazzi+05') if idx == 0: common.prepare_legend(ax, ['k', 'b', 'b'], loc='lower right') common.savefig(outdir, fig, "zstar_mstar_30kpc_z_comp_obs.pdf") ################ will plot star-forming gas metallicity vs. stellar mass xtit = "$\\rm log_{10} (\\rm M_{\\star, 30kpc}/M_{\odot})$" ytit = "$\\rm log_{10}(\\rm Z_{\\rm SF,gas}/Z_{\\odot})$" xmin, xmax, ymin, ymax = 7, 12, -2, 1 xleg = xmax - 0.2 * (xmax - xmin) yleg = ymax - 0.1 * (ymax - ymin) fig = plt.figure(figsize=(5, 10)) idx = [0, 1, 2] zins = [0, 1, 2] subplots = [311, 312, 313] for subplot, idx, z, s in zip(subplots, idx, zins, snap): ax = fig.add_subplot(subplot) if (idx == 2): xtitplot = xtit else: xtitplot = ' ' common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtitplot, ytit, locators=(0.1, 1, 0.1)) ax.text(xleg, yleg, 'z=%s' % (str(z))) plt.subplots_adjust(left=0.2) if (z == 0): #MZR z=0 corrzsun = 8.69 #solar oxygen abundance in units of 12 + log(O/H) hobs = 0.72 #add cosmology correction plus IMF correction that goes into the stellar mass. corr_cos = np.log10(pow(hobs, 2) / pow(h0, 2)) - 0.09 lm, mz, mzdn, mzup = common.load_observation( obsdir, 'MZR/MMAdrews13.dat', [0, 1, 2, 3]) hobs = 0.7 #add cosmology correction plus IMF correction that goes into the stellar mass. corr_cos = np.log10(pow(hobs, 2) / pow(h0, 2)) - 0.09 common.errorbars(ax, lm + corr_cos, mz - corrzsun, mzdn - corrzsun, mzup - corrzsun, 'b', 's', label='Andrews+13') #correction for Tremonti is the same. lm, mz, mzdn, mzup = common.load_observation( obsdir, 'MZR/Tremonti04.dat', [0, 1, 2, 3]) common.errorbars(ax, lm + corr_cos, mz - corrzsun, mzdn - corrzsun, mzup - corrzsun, 'b', 'o', label="Tremonti+04") #VR ind = np.where(ZSFMstar[idx, 0, :] != 0.) xplot = xmf[ind] yplot = ZSFMstar[idx, 0, ind] - log10zsun errdn = ZSFMstar[idx, 1, ind] errup = ZSFMstar[idx, 2, ind] if idx == 0: ax.plot(xplot, yplot[0], 'k', label='VR') if idx > 0: ax.plot(xplot, yplot[0], 'k') ax.fill_between(xplot, yplot[0], yplot[0] - errdn[0], facecolor='k', alpha=0.2, interpolate=True) ax.fill_between(xplot, yplot[0], yplot[0] + errup[0], facecolor='k', alpha=0.2, interpolate=True) if idx == 0: common.prepare_legend(ax, ['k', 'b', 'b'], loc='lower right') common.savefig(outdir, fig, "zsfgas_mstar_30kpc_z_comp_obs.pdf") ################ will plot stellar ages vs stellar mass xtit = "$\\rm log_{10} (\\rm M_{\\star, 30kpc}/M_{\odot})$" ytit = "$\\rm log_{10}(\\rm age_{\\star}/Gyr)$" xmin, xmax, ymin, ymax = 7, 12, 0, 1.1 xleg = xmax - 0.2 * (xmax - xmin) yleg = ymax - 0.1 * (ymax - ymin) fig = plt.figure(figsize=(5, 10)) idx = [0, 1, 2] zins = [0, 1, 2] subplots = [311, 312, 313] for subplot, idx, z, s in zip(subplots, idx, zins, snap): ax = fig.add_subplot(subplot) if (idx == 2): xtitplot = xtit else: xtitplot = ' ' common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtitplot, ytit, locators=(0.1, 1, 0.1)) ax.text(xleg, yleg, 'z=%s' % (str(z))) plt.subplots_adjust(left=0.2) #VR ind = np.where(AgeSMstar[idx, 0, :] != 0.) xplot = xmf[ind] yplot = AgeSMstar[idx, 0, ind] errdn = AgeSMstar[idx, 1, ind] errup = AgeSMstar[idx, 2, ind] if idx == 0: ax.plot(xplot, yplot[0], 'k', label='VR') if idx > 0: ax.plot(xplot, yplot[0], 'k') ax.fill_between(xplot, yplot[0], yplot[0] - errdn[0], facecolor='k', alpha=0.2, interpolate=True) ax.fill_between(xplot, yplot[0], yplot[0] + errup[0], facecolor='k', alpha=0.2, interpolate=True) #observations if (z == 0): lm, age, agedn, ageup = common.load_observation( obsdir, 'StellarPops/vdS19-age.csv', [0, 1, 2, 3]) common.errorbars(ax, lm, age, agedn, ageup, 'b', 'D', label='van de Sande+19') if idx == 0: common.prepare_legend(ax, ['k']) common.savefig(outdir, fig, "starage_mstar_z_comp_obs.pdf") ################ will plot black hole mass vs stellar mass xtit = "$\\rm log_{10} (\\rm M_{\\star, 30kpc}/M_{\odot})$" ytit = "$\\rm log_{10}(\\rm M_{\\rm BH}/M_{\odot})$" xmin, xmax, ymin, ymax = 7, 12, 6, 11 xleg = xmax - 0.2 * (xmax - xmin) yleg = ymax - 0.1 * (ymax - ymin) fig = plt.figure(figsize=(5, 10)) idx = [0, 1, 2] zins = [0, 1, 2] subplots = [311, 312, 313] for subplot, idx, z, s in zip(subplots, idx, zins, snap): ax = fig.add_subplot(subplot) if (idx == 2): xtitplot = xtit else: xtitplot = ' ' common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtitplot, ytit, locators=(0.1, 1, 0.1)) ax.text(xleg, yleg, 'z=%s' % (str(z))) plt.subplots_adjust(left=0.2) if (z == 0): #BH-bulge relation mBH_M13, errup_M13, errdn_M13, mBH_power, mbulge_M13 = common.load_observation( obsdir, 'BHs/MBH_sigma_Mbulge_McConnelMa2013.dat', [0, 1, 2, 3, 7]) ind = np.where((mBH_M13 > 0) & (mbulge_M13 > 0)) xobs = np.log10(mbulge_M13[ind]) yobs = np.log10(mBH_M13[ind] * pow(10.0, mBH_power[ind])) lerr = np.log10( (mBH_M13[ind] - errdn_M13[ind]) * pow(10.0, mBH_power[ind])) herr = np.log10( (mBH_M13[ind] + errup_M13[ind]) * pow(10.0, mBH_power[ind])) ax.errorbar(xobs, yobs, yerr=[yobs - lerr, herr - yobs], ls='None', mfc='None', ecolor='r', mec='r', marker='^', label="McConnell & Ma 2013") #BH-bulge relation mBH_H04, errup_H04, errdn_H04, mbulge_H04 = common.load_observation( obsdir, 'BHs/MBH_sigma_Mbulge_HaeringRix2004.dat', [0, 1, 2, 4]) xobs = np.log10(mbulge_H04) yobs = xobs * 0. - 999. indx = np.where(mBH_H04 > 0) yobs[indx] = np.log10(mBH_H04[indx]) lerr = yobs * 0. - 999. indx = np.where((mBH_H04 - errdn_H04) > 0) lerr[indx] = np.log10(mBH_H04[indx] - errdn_H04[indx]) herr = yobs * 0. + 999. indx = np.where((mBH_H04 + errup_H04) > 0) herr[indx] = np.log10(mBH_H04[indx] + errup_H04[indx]) ax.errorbar(xobs, yobs, yerr=[yobs - lerr, herr - yobs], ls='None', mfc='None', ecolor='maroon', mec='maroon', marker='s', label="Haering+04") #VR ind = np.where(MBHMstar[idx, 0, :] != 0.) xplot = xmf[ind] yplot = MBHMstar[idx, 0, ind] errdn = MBHMstar[idx, 1, ind] errup = MBHMstar[idx, 2, ind] if idx == 0: ax.plot(xplot, yplot[0], 'k', label='VR') if idx > 0: ax.plot(xplot, yplot[0], 'k') ax.fill_between(xplot, yplot[0], yplot[0] - errdn[0], facecolor='k', alpha=0.2, interpolate=True) ax.fill_between(xplot, yplot[0], yplot[0] + errup[0], facecolor='k', alpha=0.2, interpolate=True) if idx == 0: common.prepare_legend(ax, ['k', 'r', 'maroon'], loc='upper left') common.savefig(outdir, fig, "blackhole_stellarmass_z_comp_obs.pdf")
def plot_stellar_mass_cosmic_density(plt, outdir, obsdir, redshifts, h0, mstarden, mstarbden_mergers, mstarbden_diskins): # Plots stellar mass cosmic density xtit = "$\\rm redshift$" ytit = "$\\rm log_{10}(\\rho_{\\rm star}/ M_{\odot}\,cMpc^{-3})$" fig = plt.figure(figsize=(5, 9)) ax = fig.add_subplot(211) plt.subplots_adjust(left=0.15) common.prepare_ax(ax, 0, 10, 5, 8.7, xtit, ytit, locators=(0.1, 1, 0.1, 1)) #note that only h^2 is needed because the volume provides h^3, and the SFR h^-1. ind = np.where(mstarden > 0) ax.plot(redshifts[ind], np.log10(mstarden[ind] * pow(h0, 2.0)), 'k') ind = np.where(mstarbden_mergers > 0) ax.plot(redshifts[ind], np.log10(mstarbden_mergers[ind] * pow(h0, 2.0)), 'r', linestyle='dashed') ind = np.where(mstarbden_diskins > 0) ax.plot(redshifts[ind], np.log10(mstarbden_diskins[ind] * pow(h0, 2.0)), 'b', linestyle='dotted') z, sm_modelvar = common.load_observation( obsdir, 'Models/SharkVariations/Global_OtherModels.dat', [0, 4]) sm_modelvar_burst3 = sm_modelvar[0:179] sm_modelvar_nu0p5 = sm_modelvar[181:360] sm_modelvar_burst20 = sm_modelvar[360:539] ind = np.where(sm_modelvar_burst20 > -10) ax.plot(z[ind], sm_modelvar_burst20[ind], 'Sienna', linestyle='dotted') ind = np.where(sm_modelvar_burst3 > -10) ax.plot(z[ind], sm_modelvar_burst3[ind], 'DarkSlateGray', linestyle='dashdot') ind = np.where(sm_modelvar_nu0p5 > -10) ax.plot(z[ind], sm_modelvar_nu0p5[ind], 'SlateGray', linestyle='dotted') #Baldry (Chabrier IMF), ['Baldry+2012, z<0.06'] redD17d, redD17u, smdD17, err1, err2, err3, err4 = common.load_observation( obsdir, 'Global/Driver18_smd.dat', [1, 2, 3, 4, 5, 6, 7]) hobs = 0.7 xobs = (redD17d + redD17u) / 2.0 yobs = smdD17 + np.log10(hobs / h0) err = yobs * 0. - 999. err = np.sqrt( pow(err1, 2.0) + pow(err2, 2.0) + pow(err3, 2.0) + pow(err4, 2.0)) ax.errorbar(xobs, yobs, yerr=[err, err], ls='None', mfc='None', ecolor='grey', mec='grey', marker='o', label="Driver+18") common.prepare_legend(ax, ['grey'], loc=3) xtit = "$\\rm Lookback\, time/Gyr$" ax = fig.add_subplot(212) plt.subplots_adjust(left=0.15) common.prepare_ax(ax, 0, 13.5, 5, 8.7, xtit, ytit, locators=(0.1, 1, 0.1, 1)) #note that only h^2 is needed because the volume provides h^3, and the SFR h^-1. ind = np.where(mstarden > 0) ax.plot(us.look_back_time(redshifts[ind]), np.log10(mstarden[ind] * pow(h0, 2.0)), 'k', label='Shark all galaxies') ind = np.where(mstarbden_mergers > 0) ax.plot(us.look_back_time(redshifts[ind]), np.log10(mstarbden_mergers[ind] * pow(h0, 2.0)), 'r', linestyle='dashed', label='formed in galaxy mergers') ind = np.where(mstarbden_diskins > 0) ax.plot(us.look_back_time(redshifts[ind]), np.log10(mstarbden_diskins[ind] * pow(h0, 2.0)), 'b', linestyle='dotted', label='formed in disk instabilities') ind = np.where(sm_modelvar_burst20 > -10) ax.plot(us.look_back_time(z[ind]), sm_modelvar_burst20[ind], 'Sienna', linestyle='dotted', label='$\\eta_{\\rm burst}=20$') ind = np.where(sm_modelvar_burst3 > -10) ax.plot(us.look_back_time(z[ind]), sm_modelvar_burst3[ind], 'DarkSlateGray', linestyle='dashdot', label='$\\eta_{\\rm burst}=3$') ind = np.where(sm_modelvar_nu0p5 > -10) ax.plot(us.look_back_time(z[ind]), sm_modelvar_nu0p5[ind], 'SlateGray', linestyle='dotted', label='$\\nu_{\\rm SF}=0.5 \\rm Gyr^{-1}$') ax.errorbar(us.look_back_time(xobs), yobs, yerr=[err, err], ls='None', mfc='None', ecolor='grey', mec='grey', marker='o') common.prepare_legend( ax, ['k', 'r', 'b', 'Sienna', 'DarkSlateGray', 'SlateGray'], loc=3) common.savefig(outdir, fig, "cosmic_smd.pdf")
def plot_sizes(plt, outdir, obsdir, disk_size_cen, disk_size_sat, bulge_size, vmax_halo_gal): print 'sizes disk centrals' for i,j,p in zip(disk_size_cen[0,0,:],disk_size_cen[0,1,:],disk_size_cen[0,2,:]): print i,j,p print 'disk sizes satellites' for i,j,p in zip(disk_size_sat[0,0,:],disk_size_sat[0,1,:],disk_size_sat[0,2,:]): print i,j,p print 'sizes bulges' for i,j,p in zip(bulge_size[0,0,:],bulge_size[0,1,:],bulge_size[0,2,:]): print i,j,p rb, r16, r84 = common.load_observation(obsdir, 'Models/SharkVariations/SizeDisksAndBulges_OtherModels.dat', [0,1,2]) fig = plt.figure(figsize=(5,11.5)) xtit = "$\\rm log_{10} (\\rm M_{\\star,disk}/M_{\odot})$" ytit = "$\\rm log_{10} (\\rm r_{\\star,disk}/kpc)$" xmin, xmax, ymin, ymax = 8, 12, -0.1, 2 xleg = xmax - 0.2 * (xmax - xmin) yleg = ymax - 0.1 * (ymax - ymin) # LTG ################################## ax = fig.add_subplot(311) common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtit, ytit, locators=(0.1, 1, 0.1, 1)) ax.text(8.1,1.7,'disks of centrals',fontsize=12) #Predicted size-mass for disks in disk=dominated galaxies ind = np.where(disk_size_cen[0,0,:] != 0) xplot = xmf[ind] yplot = disk_size_cen[0,0,ind] errdn = disk_size_cen[0,1,ind] errup = disk_size_cen[0,2,ind] ax.plot(xplot,yplot[0],color='b',linestyle='solid',label="ISM/stars AM transfer") ax.fill_between(xplot,yplot[0],yplot[0]-errdn[0], facecolor='b', alpha=0.3,interpolate=True) ax.fill_between(xplot,yplot[0],yplot[0]+errup[0], facecolor='b', alpha=0.3,interpolate=True) rdisk_am = rb[30:59] rdisk_am16 = r16[30:59] rdisk_am84 = r84[30:59] ind = np.where(rdisk_am != 0) xplot = xmf[ind] yplot = rdisk_am[ind] errdn = rdisk_am16[ind] errup = rdisk_am84[ind] ax.plot(xplot,yplot,color='b',linestyle='dashed', label="Lagos+18") ax.fill_between(xplot,yplot,yplot-errdn, facecolor='b', linestyle='solid', alpha=0.4,interpolate=True) ax.fill_between(xplot,yplot,yplot+errup, facecolor='b', linestyle='solid', alpha=0.4,interpolate=True) #Lange et al. (2016) m,r = common.load_observation(obsdir, 'SizesAndAM/rdisk_L16.dat', [0,1]) ax.plot(m[0:36], r[0:36], linestyle='dotted',color='k') ax.plot(m[38:83], r[38:83], linestyle='dotted',color='k') ax.plot(m[85:128], r[85:129], linestyle='dotted',color='k') common.prepare_legend(ax, ['b','b'], bbox_to_anchor=(0.005, 0.62)) ax = fig.add_subplot(312) common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtit, ytit, locators=(0.1, 1, 0.1, 1)) ax.text(8.1,1.7,'disks of satellites',fontsize=12) #Predicted size-mass for disks in disk=dominated galaxies satellites ind = np.where(disk_size_sat[0,0,:] != 0) xplot = xmf[ind] yplot = disk_size_sat[0,0,ind] errdn = disk_size_sat[0,1,ind] errup = disk_size_sat[0,2,ind] ax.plot(xplot,yplot[0],color='g',linestyle='solid') ax.fill_between(xplot,yplot[0],yplot[0]-errdn[0], facecolor='g', alpha=0.3,interpolate=True) ax.fill_between(xplot,yplot[0],yplot[0]+errup[0], facecolor='g', alpha=0.3,interpolate=True) rdisk_am = rb[0:29] rdisk_am16 = r16[0:29] rdisk_am84 = r84[0:29] ind = np.where(rdisk_am != 0) xplot = xmf[ind] yplot = rdisk_am[ind] errdn = rdisk_am16[ind] errup = rdisk_am84[ind] ax.plot(xplot,yplot,color='g',linestyle='dashed') ax.fill_between(xplot,yplot,yplot-errdn, facecolor='g', linestyle='solid', alpha=0.4,interpolate=True) ax.fill_between(xplot,yplot,yplot+errup, facecolor='g', linestyle='solid', alpha=0.4,interpolate=True) #Lange et al. (2016) m,r = common.load_observation(obsdir, 'SizesAndAM/rdisk_L16.dat', [0,1]) ax.plot(m[0:36], r[0:36], linestyle='dotted',color='k',label="L16 50th, 68th, 90th") ax.plot(m[38:83], r[38:83], linestyle='dotted',color='k') ax.plot(m[85:128], r[85:129], linestyle='dotted',color='k') common.prepare_legend(ax, ['k'], bbox_to_anchor=(0.005, 0.67)) # ETGs ################################## xtit = "$\\rm log_{10} (\\rm M_{\\star,bulge}/M_{\odot})$" ytit = "$\\rm log_{10} (\\rm r_{\\star,bulge}/kpc)$" xmin, xmax, ymin, ymax = 8, 12, -0.35, 2 xleg = xmax - 0.2 * (xmax - xmin) yleg = ymax - 0.1 * (ymax - ymin) ax = fig.add_subplot(313) common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtit, ytit, locators=(0.1, 1, 0.1, 1)) ax.text(8.1,1.7,'bulges of all galaxies',fontsize=12) #Predicted size-mass for bulges in bulge-dominated systems ind = np.where(bulge_size[0,0,:] != 0) if(len(xmf[ind]) > 0): xplot = xmf[ind] yplot = bulge_size[0,0,ind] errdn = bulge_size[0,1,ind] errup = bulge_size[0,2,ind] ax.plot(xplot,yplot[0],color='r',linestyle='solid') ax.fill_between(xplot,yplot[0],yplot[0]-errdn[0], facecolor='r', alpha=0.3,interpolate=True) ax.fill_between(xplot,yplot[0],yplot[0]+errup[0], facecolor='r', alpha=0.3,interpolate=True) rdisk_am = rb[60:99] rdisk_am16 = r16[60:99] rdisk_am84 = r84[60:99] ind = np.where(rdisk_am != 0) xplot = xmf[ind] yplot = rdisk_am[ind] errdn = rdisk_am16[ind] errup = rdisk_am84[ind] ax.plot(xplot,yplot,color='r',linestyle='dashed') ax.fill_between(xplot,yplot,yplot-errdn, facecolor='LightCoral', linestyle='solid', alpha=0.4,interpolate=True) ax.fill_between(xplot,yplot,yplot+errup, facecolor='LightCoral', linestyle='solid', alpha=0.4,interpolate=True) #Lange et al. (2016) m,r = common.load_observation(obsdir, 'SizesAndAM/rbulge_L16.dat', [0,1]) ax.plot(m[0:39], r[0:39], linestyle='dotted',color='k') ax.plot(m[41:76], r[41:76], linestyle='dotted',color='k') ax.plot(m[78:115], r[78:115], linestyle='dotted',color='k') common.savefig(outdir, fig, 'sizes_angular_momentum_model.pdf') fig = plt.figure(figsize=(9.5,9.5)) xtit = "$\\rm log_{10} (\\rm M_{\\rm halo}/M_{\odot})$" ytit = "$\\rm log_{10} (\\rm v_{\\rm max}/km s^{-1}$)" xmin, xmax, ymin, ymax = 10, 15, 1.3, 3.5 xleg = xmax - 0.2 * (xmax - xmin) yleg = ymax - 0.1 * (ymax - ymin) subplots = (221, 222, 223, 224) indz = (0, 1, 2, 3) # choose type of selection: selec = 0 #all galaxies # LTG ################################## for z,s,p in zip(zlist, indz, subplots): ax = fig.add_subplot(p) common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtit, ytit, locators=(0.1, 1, 0.1, 1)) ax.text(xleg, yleg, 'z=%s' % str(z)) ind = np.where(vmax_halo_gal[s,0,:,selec] != 0) xplot = xmfh[ind] yplot = vmax_halo_gal[s,0,ind,selec] errdn = vmax_halo_gal[s,1,ind,selec] errup = vmax_halo_gal[s,2,ind,selec] ax.plot(xplot,yplot[0],color='k',label="central subhalos") ax.fill_between(xplot,yplot[0],yplot[0]-errdn[0], facecolor='k', alpha=0.2,interpolate=True) ax.fill_between(xplot,yplot[0],yplot[0]+errup[0], facecolor='k', alpha=0.2,interpolate=True) common.prepare_legend(ax, ['k'], loc=2) common.savefig(outdir, fig, 'vmax_vs_subhalo.pdf')
def plot_omega_h2(plt, outdir, obsdir, redshifts, h0, mH2den): fig = plt.figure(figsize=(5, 4.5)) ax = fig.add_subplot(111) plt.subplots_adjust(bottom=0.15, left=0.15) xtit = "$\\rm Lookback\, time/Gyr$" ytit = "$\\rm log_{10}(\\rho_{\\rm H_2}/ M_{\odot}\,cMpc^{-3})$" common.prepare_ax(ax, 0, 13.5, 6.2, 8.4, xtit, ytit, locators=(0.1, 1, 0.1, 1)) ax2 = ax.twiny() ax2.set_xlim(ax.get_xlim()) new_tick_locations = np.array([0., 2., 4., 6., 8., 10., 12.]) ax2.set_xticks(new_tick_locations) ax2.set_xticklabels(us.redshift(new_tick_locations), fontsize=12) ax2.set_xlabel("redshift", fontsize=13) #note that only h^2 is needed because the volume provides h^3, and the SFR h^-1. ind = np.where(mH2den > 0) ax.plot(us.look_back_time(redshifts[ind]), np.log10(mH2den[ind] * pow(h0, 2.0)) + np.log10(XH), 'r') z, h2_modelvar = common.load_observation( obsdir, 'Models/SharkVariations/Global_OtherModels.dat', [0, 2]) h2_modelvar_burst3 = h2_modelvar[0:179] h2_modelvar_nu0p5 = h2_modelvar[181:360] h2_modelvar_burst20 = h2_modelvar[360:539] ind = np.where(h2_modelvar_burst20 > -10) ax.plot(us.look_back_time(z[ind]), h2_modelvar_burst20[ind], 'Sienna', linestyle='dotted') ind = np.where(h2_modelvar_burst3 > -10) ax.plot(us.look_back_time(z[ind]), h2_modelvar_burst3[ind], 'Crimson', linestyle='dashdot') ind = np.where(h2_modelvar_nu0p5 > -10) ax.plot(us.look_back_time(z[ind]), h2_modelvar_nu0p5[ind], 'Salmon', linestyle='dotted') #Walter ASPECS ALMA program zD16, zloD16, zupD16, rhoH2D16, rhoH2loD16, rhoH2upD16 = common.load_observation( obsdir, 'Global/Walter17_H2.dat', [0, 1, 2, 3, 4, 5]) hobs = 0.7 xobs = zD16 errxlow = zD16 - zloD16 errxup = zupD16 - zD16 yobs = np.log10(rhoH2D16) + np.log10(pow(hobs / h0, 3.0)) errylow = np.log10(rhoH2D16) - np.log10(rhoH2loD16) erryup = np.log10(rhoH2upD16) - np.log10(rhoH2D16) ax.errorbar(us.look_back_time(xobs), yobs, xerr=[errxlow, errxup], yerr=[errylow, erryup], ls='None', mfc='None', ecolor='grey', mec='grey', marker='+', label="Decarli+16") ax.errorbar(us.look_back_time(xobs[0:1]), yobs[0:1], xerr=[errxlow[0:1], errxup[0:1]], yerr=[errylow[0:1], erryup[0:1]], ls='None', mfc='None', ecolor='grey', mec='grey', marker='o', label="Boselli+14") # Legend common.prepare_legend(ax, ['grey', 'grey', 'grey'], loc=0) common.savefig(outdir, fig, "omega_H2.pdf")
def plot_halomf_z(plt, outdir, obsdir, z, h0, hist, histsh, plotz): xtit = "$\\rm log_{10} (\\rm M_{\\rm halo}/M_{\odot})$" ytit = "$\\rm log_{10}(\Phi/dlog{\\rm M_{\\rm halo}}/{\\rm Mpc}^{-3} )$" xmin, xmax, ymin, ymax = 10.1, 15, -6, -1 xleg = xmax - 0.2 * (xmax - xmin) yleg = ymax - 0.1 * (ymax - ymin) fig = plt.figure(figsize=(7, 7)) subplots = (221, 222, 223, 224) idx = (0, 1, 2, 3) for subplot, idx, z, plot_this_z in zip(subplots, idx, z, plotz): ax = fig.add_subplot(subplot) if (idx == 0 or idx == 2): ytitplot = ytit else: ytitplot = ' ' common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtit, ytitplot, locators=(0.1, 1, 0.1)) ax.text(xleg, yleg, 'z=%s' % (str(z))) #HMF calc HMF calculated by Sheth & Tormen (2001) lmp, dp = common.load_observation( obsdir, 'mf/HMF/mVector_PLANCK-SMT_z%s.dat' % str(z).replace('.', ''), [0, 7]) lmp_plot = np.log10(lmp) - np.log10(h0) dp_plot = np.log10(dp) + np.log10(pow(h0, 3.)) if idx == 0: ax.plot(lmp_plot, dp_plot, 'b', label='HMF calc') elif idx > 0: ax.plot(lmp_plot, dp_plot, 'b') #Predicted HMF if plot_this_z: y = hist[idx, :] ind = np.where(y < 0.) if idx == 0: ax.plot(xmf[ind], y[ind], 'r', label='HMF Shark') if idx > 0: ax.plot(xmf[ind], y[ind], 'r') y = histsh[idx, :] ind = np.where(y < 0.) if idx == 0: ax.plot(xmf[ind], y[ind], 'r', linestyle='dashed', label='SHMF Shark') if idx > 0: ax.plot(xmf[ind], y[ind], 'r', linestyle='dashed') if idx == 0: common.prepare_legend(ax, ['b', 'r', 'r']) common.savefig(outdir, fig, "halomf_z.pdf") xtit = "$\\rm log_{10}(\\rm M/M_{\odot})$" ytit = "$\\rm log_{10}(\Phi/dlog{\\rm M}/{\\rm Mpc}^{-3})$" xmin, xmax, ymin, ymax = 8, 15, -6, 1.2 xleg = xmax - 0.2 * (xmax - xmin) yleg = ymax - 0.1 * (ymax - ymin) fig = plt.figure(figsize=(5, 5)) idx = 0 ax = fig.add_subplot(111) ytitplot = ytit common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtit, ytitplot, locators=(0.1, 1, 0.1)) #lmp, dp = common.load_observation(obsdir, 'mf/HMF/mVector_PLANCK-SMT_z0_extended.dat', [0, 7]) #lmp_plot = np.log10(lmp) - np.log10(h0) #dp_plot = np.log10(dp) + np.log10(pow(h0,3.)) #ax.plot(lmp_plot,dp_plot,'k') #ax.plot(lmp_plot+np.log10(fb),dp_plot,'b', linestyle='dashed') y = hist[idx, :] ind = np.where((y < 0.) & (xmf > 10.3)) ax.plot(xmf[ind], y[ind], 'k') ax.plot(xmf[ind] + np.log10(fb), y[ind], 'b', linestyle='dashed') lm, p, dpdn, dpup = common.load_observation(obsdir, 'mf/SMF/GAMAII_BBD_GSMFs.dat', [0, 1, 2, 3]) xobs = lm indx = np.where(p > 0) yobs = np.log10(p[indx]) ydn = yobs - np.log10(p[indx] - dpdn[indx]) yup = np.log10(p[indx] + dpup[indx]) - yobs ax.errorbar(xobs[indx], yobs, ydn, yup, 'ro', label='Wright+17') smfdensity = common.load_observation( obsdir, 'Models/SharkVariations/SMF_FeedbackExperiment.dat', [0]) ynofeed = smfdensity[0:len(xsmf) - 1] yreio = smfdensity[len(xsmf):2 * len(xsmf) - 1] ystarf = smfdensity[2 * len(xsmf):3 * len(xsmf) - 1] yfinal = smfdensity[3 * len(xsmf):4 * len(xsmf) - 1] ind = np.where(ynofeed != 0) ax.plot(xsmf[ind], ynofeed[ind], 'DarkRed') ind = np.where(ystarf != 0) ax.plot(xsmf[ind], ystarf[ind], 'LightCoral') ind = np.where(yfinal != 0) ax.plot(xsmf[ind], yfinal[ind], 'Orange') common.prepare_legend(ax, ['r']) common.savefig(outdir, fig, "halomf_z0.pdf")
def plot_molecular_gas_fraction( plt, output_dir, obs_dir, mgas_gals, mgas_relation, mh1_gals, mh1_relation, mh2_gals, mh2_relation, mgas_relation_ltg, mh2_relation_ltg, mh1_relation_ltg, mgas_relation_etg, mh2_relation_etg, mh1_relation_etg, mgas_ms_relation_ltg, mh2_ms_relation_ltg, mh1_ms_relation_ltg, mgas_ms_relation_etg, mh2_ms_relation_etg, mh1_ms_relation_etg): xmin, xmax, ymin, ymax = 9, 12, -3, 1 fig = plt.figure(figsize=(11, 11)) # First subplot ax = fig.add_subplot(321) plt.subplots_adjust(left=0.15) xtit = "$\\rm log_{10} (\\rm M_{\\star}/M_{\odot})$" ytit = "$\\rm log_{10}(M_{\\rm HI+H_2}/M_{\\star})$" prepare_ax(ax, xmin, xmax, ymin, ymax, xtit, ytit) #Predicted relation for all galaxies ind = np.where((mgas_gals[0, :] > 0) & (mgas_gals[1, :] != 0)) xdata = mgas_gals[0, ind] ydata = mgas_gals[1, ind] us.density_contour(ax, xdata[0], ydata[0], 30, 30) #, **contour_kwargs) def plot_mrelation(mrelation, color, label=None, linestyle=None): ind = np.where(mrelation[0, :] != 0) xplot = xmf[ind] yplot = mrelation[0, ind] linestyle = linestyle or '' ax.plot(xplot, yplot[0], color=color, label=label, linestyle=linestyle) def plot_mrelation_fill(mrelation, color, colorfill, label=None, linestyle=None): ind = np.where(mrelation[0, :] != 0) xplot = xmf[ind] yplot = mrelation[0, ind] errdn = mrelation[1, ind] errup = mrelation[2, ind] ax.plot(xplot, yplot[0], color=color, label=label, linestyle=linestyle) ax.fill_between(xplot, yplot[0], yplot[0] - errdn[0], facecolor=colorfill, alpha=0.2, interpolate=True) ax.fill_between(xplot, yplot[0], yplot[0] + errup[0], facecolor=colorfill, alpha=0.2, interpolate=True) plot_mrelation(mgas_relation, 'k', linestyle='solid', label="Shark all galaxies") #Baldry (Chabrier IMF), ['Baldry+2012, z<0.06'] add_observations_to_plot(obs_dir, 'NeutralGasRatio_NonDetEQZero.dat', ax, '^', "xCOLDGAS+xGASS(0)", color='grey') add_observations_to_plot(obs_dir, 'NeutralGasRatio_NonDetEQUpperLimits.dat', ax, 'v', "xCOLDGAS+xGASS(UL)") common.prepare_legend(ax, ['k', 'k', 'k']) # Second subplot ax = fig.add_subplot(322) xmin, xmax, ymin, ymax = 9, 12, -4.5, 1 prepare_ax(ax, xmin, xmax, ymin, ymax, xtit, ytit) plot_mrelation_fill(mgas_relation_ltg, 'b', 'b', label="Shark LTGs $(\\rm B/T)_{\\rm bar}$", linestyle='solid') plot_mrelation_fill(mgas_relation_etg, 'r', 'r', label="Shark ETGs $(\\rm B/T)_{\\rm bar}$", linestyle='solid') plot_mrelation(mgas_ms_relation_ltg, 'b', label="Shark LTGs $(\\rm B/T)_{\star}$", linestyle='dotted') plot_mrelation(mgas_ms_relation_etg, 'r', label="Shark ETGs $(\\rm B/T)_{\star}$", linestyle='dotted') # Legend common.prepare_legend(ax, ['b', 'r', 'b', 'r', 'k'], loc=3) # Third subplot ax = fig.add_subplot(323) plt.subplots_adjust(left=0.15) xtit = "$\\rm log_{10} (\\rm M_{\\star}/M_{\odot})$" ytit = "$\\rm log_{10}(M_{\\rm HI}/M_{\\star})$" xmin, xmax, ymin, ymax = 9, 12, -3, 1 prepare_ax(ax, xmin, xmax, ymin, ymax, xtit, ytit) #Predicted relation ind = np.where((mh1_gals[0, :] > 0) & (mh1_gals[1, :] != 0)) xdata = mh1_gals[0, ind] ydata = mh1_gals[1, ind] us.density_contour(ax, xdata[0], ydata[0], 30, 30) #, **contour_kwargs) plot_mrelation(mh1_relation, 'k', linestyle='solid') #Baldry (Chabrier IMF), ['Baldry+2012, z<0.06'] add_observations_to_plot(obs_dir, 'HIGasRatio_NonDetEQZero.dat', ax, '^', "xGASS(0)", color='grey') add_observations_to_plot(obs_dir, 'HIGasRatio_NonDetEQUpperLimits.dat', ax, 'v', "xGASS(UL)") x, y, yerr_down, yerr_up = common.load_observation(obs_dir, 'Gas/Parkash18.dat', (0, 1, 2, 3)) ax.errorbar(x, y - x, yerr=[(y - x) - (yerr_down - x), (yerr_up - x) - (y - x)], ls='None', mfc='r', fillstyle='full', ecolor='r', mec='r', marker='s', markersize=7, label="Parkash+18") m, mrat, merr = common.load_observation(obs_dir, 'Gas/RHI-Mstars_Brown15.dat', [0, 1, 2]) errdn = np.log10(mrat) - np.log10(mrat - merr) errup = np.log10(mrat + merr) - np.log10(mrat) ax.errorbar(m, np.log10(mrat), yerr=[errdn, errup], ls='None', mfc='Salmon', fillstyle='full', ecolor='Salmon', mec='Salmon', marker='o', markersize=7, label="Brown+15") # Legend common.prepare_legend(ax, ['k', 'k', 'r', 'Salmon'], loc=1) # Fourth subplot ax = fig.add_subplot(324) xmin, xmax, ymin, ymax = 9, 12, -4.5, 1 prepare_ax(ax, xmin, xmax, ymin, ymax, xtit, ytit) plot_mrelation_fill(mh1_relation_ltg, 'b', 'b', linestyle='solid') plot_mrelation_fill(mh1_relation_etg, 'r', 'r', linestyle='solid') plot_mrelation(mh1_ms_relation_ltg, 'b', linestyle='dotted') plot_mrelation(mh1_ms_relation_etg, 'r', linestyle='dotted') add_observations_to_plot(obs_dir, 'RHI-Mstars_Callette18-LTGs.dat', ax, 's', "Calette+18 LTGs", color='grey', err_absolute=True) add_observations_to_plot(obs_dir, 'RHI-Mstars_Callette18-ETGs.dat', ax, 'o', "Calette+18 ETGs", color='grey', err_absolute=True) # Legend common.prepare_legend(ax, ['grey', 'grey', 'grey'], loc=1) # Fifth subplot ax = fig.add_subplot(325) plt.subplots_adjust(left=0.15) xtit = "$\\rm log_{10} (\\rm M_{\\star}/M_{\odot})$" ytit = "$\\rm log_{10}(M_{\\rm H_2}/M_{\\star})$" xmin, xmax, ymin, ymax = 9, 12, -3, 1 prepare_ax(ax, xmin, xmax, ymin, ymax, xtit, ytit) #Predicted relation ind = np.where((mh2_gals[0, :] > 0) & (mh2_gals[1, :] != 0)) xdata = mh2_gals[0, ind] ydata = mh2_gals[1, ind] us.density_contour(ax, xdata[0], ydata[0], 30, 30) #, **contour_kwargs) plot_mrelation(mh2_relation, 'k', linestyle='solid') #Baldry (Chabrier IMF), ['Baldry+2012, z<0.06'] add_observations_to_plot(obs_dir, 'MolecularGasRatio_NonDetEQZero.dat', ax, '^', "xCOLDGASS(0)", color='grey') add_observations_to_plot(obs_dir, 'MolecularGasRatio_NonDetEQUpperLimits.dat', ax, 'v', "xCOLDGASS(UL)") common.prepare_legend(ax, ['k', 'k', 'k'], loc=1) # Fourth subplot ax = fig.add_subplot(326) xmin, xmax, ymin, ymax = 9, 12, -4.5, 1 prepare_ax(ax, xmin, xmax, ymin, ymax, xtit, ytit) plot_mrelation_fill(mh2_relation_ltg, 'b', 'b', linestyle='solid') plot_mrelation_fill(mh2_relation_etg, 'r', 'r', linestyle='solid') plot_mrelation(mh2_ms_relation_ltg, 'b', linestyle='dotted') plot_mrelation(mh2_ms_relation_etg, 'r', linestyle='dotted') add_observations_to_plot(obs_dir, 'RH2-Mstars_Callette18-LTGs.dat', ax, 's', "Calette+18 LTGs", color='grey', err_absolute=True) add_observations_to_plot(obs_dir, 'RH2-Mstars_Callette18-ETGs.dat', ax, 'o', "Calette+18 ETGs", color='grey', err_absolute=True) # Legend common.prepare_legend(ax, ['grey', 'grey', 'grey'], loc=1) common.savefig(output_dir, fig, "molecular_gas_fraction.pdf")
def plot_rivmax_vmax_z(plt, outdir, rvmax, hist, snap, vol_eagle): bin_it = functools.partial(us.wmedians, xbins=xvf) xtit="$\\rm log_{10} (\\rm V_{\\rm max}/km s^{-1})$" ytit="$\\rm log_{10}(\\rm R_{\\rm V_{max}}/pMpc)$" xmin, xmax, ymin, ymax = 1, 3.2, -3, 1 xleg = xmax - 0.2 * (xmax-xmin) yleg = ymax - 0.1 * (ymax-ymin) fig = plt.figure(figsize=(5,10)) idx = [0,1,2] zins = [0, 1, 2] subplots = [311, 312, 313] sn, subgn, rvs, vs = common.load_observation('/fred/oz009/clagos/EAGLE/L0025N0376/REFERENCE/data/', 'SUBFIND-EAGLE-DATABASE.data', [2, 1, 18, 19]) for subplot, idx, z, s in zip(subplots, idx, zins, snap): ax = fig.add_subplot(subplot) if (idx == 2): xtitplot = xtit else: xtitplot = ' ' common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtitplot, ytit, locators=(0.1, 1, 0.1)) ax.text(xleg,yleg, 'z=%s' % (str(z))) #HMF from SUBFIND ind = np.where((rvs > 0) & (subgn == 0) & (sn == s) & (vs> 0)) rplot = bin_it(x= np.log10(vs[ind]), y = np.log10(rvs[ind])-3.0) ind = np.where((rvs > 0) & (subgn > 0) & (sn == s) & (vs> 0)) rplotsubh = bin_it(x= np.log10(vs[ind]), y = np.log10(rvs[ind])-3.0) ind = np.where(rplot[0,:] != 0.) xplot = xvf[ind] yplot = rplot[0,ind] errdn = rplot[1,ind] errup = rplot[2,ind] if idx == 0: ax.plot(xplot,yplot[0],'b', linestyle='solid', label ='SF hosts') if idx > 0: ax.plot(xplot,yplot[0],'b', linestyle='solid') ax.fill_between(xplot,yplot[0],yplot[0]-errdn[0], facecolor='b', alpha=0.2,interpolate=True) ax.fill_between(xplot,yplot[0],yplot[0]+errup[0], facecolor='b', alpha=0.2,interpolate=True) ind = np.where(rplotsubh[0,:] != 0.) xplot = xvf[ind] yplot = rplotsubh[0,ind] errdn = rplotsubh[1,ind] errup = rplotsubh[2,ind] if idx == 0: ax.plot(xplot,yplot[0],'b', linestyle='dashed', label ='SF subh') if idx > 0: ax.plot(xplot,yplot[0],'b', linestyle='dashed') #Predicted HMF ind = np.where(rvmax[0,idx,0,:] != 0.) xplot = xvf[ind] yplot = rvmax[0,idx,0,ind] errdn = rvmax[0,idx,1,ind] errup = rvmax[0,idx,2,ind] if idx == 0: ax.plot(xplot,yplot[0],'r', label ='VR hosts') if idx > 0: ax.plot(xplot,yplot[0],'r') ax.fill_between(xplot,yplot[0],yplot[0]-errdn[0], facecolor='r', alpha=0.2,interpolate=True) ax.fill_between(xplot,yplot[0],yplot[0]+errup[0], facecolor='r', alpha=0.2,interpolate=True) ind = np.where(rvmax[1,idx,0,:] != 0.) xplot = xvf[ind] yplot = rvmax[1,idx,0,ind] errdn = rvmax[1,idx,1,ind] errup = rvmax[1,idx,2,ind] if idx == 0: ax.plot(xplot,yplot[0],'r', linestyle='dashed', label ='VR subh') if idx > 0: ax.plot(xplot,yplot[0],'r', linestyle='dashed') if idx == 0: common.prepare_legend(ax, ['b','b','r','r'], loc='upper left') common.savefig(outdir, fig, "rvmax_vmax_z.pdf") xtit="$\\rm log_{10} (\\rm V_{\\rm max}/km s^{-1})$" ytit="$\\rm log_{10}(\Phi/dlog{\\rm M_{\\rm halo}}/{\\rm Mpc}^{-3} )$" xmin, xmax, ymin, ymax = 1, 3.2, -6, 1 xleg = xmax - 0.2 * (xmax-xmin) yleg = ymax - 0.1 * (ymax-ymin) fig = plt.figure(figsize=(5,10)) idx = [0,1,2] zins = [0, 1, 2] subplots = [311, 312, 313] for subplot, idx, z, s in zip(subplots, idx, zins, snap): ax = fig.add_subplot(subplot) if (idx == 2): xtitplot = xtit else: xtitplot = ' ' common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtitplot, ytit, locators=(0.1, 1, 0.1)) ax.text(xleg,yleg, 'z=%s' % (str(z))) #HMF from SUBFIND ind = np.where((rvs > 0) & (subgn == 0) & (sn == s) & (vs> 0)) H, bins_edges = np.histogram(np.log10(vs[ind]),bins=np.append(vbins,vupp)) histsvh = H ind = np.where((rvs > 0) & (subgn > 0) & (sn == s) & (vs> 0)) H, bins_edges = np.histogram(np.log10(vs[ind]),bins=np.append(vbins,vupp)) histsvsubh = H y = histsvh[:] ind = np.where(y != 0.) if idx == 0: ax.plot(xvf[ind],np.log10(y[ind]/vol_eagle/dm),'g', label ='EAGLE L25 SF hosts') if idx > 0: ax.plot(xvf[ind],np.log10(y[ind]/vol_eagle/dm),'g') y = histsvsubh[:] ind = np.where(y != 0.) if idx == 0: ax.plot(xvf[ind],np.log10(y[ind]/vol_eagle/dm),'g', linestyle='dashed', label ='SF subh') if idx > 0: ax.plot(xvf[ind],np.log10(y[ind]/vol_eagle/dm),'g', linestyle='dashed') #Predicted HMF y = hist[0,idx,:] ind = np.where(y != 0.) if idx == 0: ax.plot(xvf[ind],y[ind],'r', linestyle='solid', label ='VR hosts') if idx > 0: ax.plot(xvf[ind],y[ind],'r', linestyle='solid') y = hist[1,idx,:] ind = np.where(y != 0.) if idx == 0: ax.plot(xvf[ind],y[ind],'r', linestyle='dashed', label ='VR subh') if idx > 0: ax.plot(xvf[ind],y[ind],'r', linestyle='dashed') if idx == 0: common.prepare_legend(ax, ['g','g','r','r']) common.savefig(outdir, fig, "vmaxf_z.pdf")
def plot_sizes(plt, outdir, obsdir, disk_size_cen, disk_size_sat, bulge_size, bulge_size_mergers, bulge_size_diskins): fig = plt.figure(figsize=(5, 9.5)) xtit = "$\\rm log_{10} (\\rm M_{\\star,disk}/M_{\odot})$" ytit = "$\\rm log_{10} (\\rm r_{\\star,disk}/kpc)$" xmin, xmax, ymin, ymax = 8, 12, -0.1, 2 xleg = xmax - 0.2 * (xmax - xmin) yleg = ymax - 0.1 * (ymax - ymin) # LTG ################################## ax = fig.add_subplot(211) common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtit, ytit, locators=(0.1, 1, 0.1, 1)) #Predicted size-mass for disks in disk=dominated galaxies ind = np.where(disk_size_cen[0, 0, :] != 0) xplot = xmf[ind] yplot = disk_size_cen[0, 0, ind] errdn = disk_size_cen[0, 1, ind] errup = disk_size_cen[0, 2, ind] ax.errorbar(xplot, yplot[0], yerr=[errdn[0], errup[0]], ls='None', mfc='None', ecolor='k', mec='k', marker='o', label="Shark centrals") #Predicted size-mass for disks in disk=dominated galaxies satellites ind = np.where(disk_size_sat[0, 0, :] != 0) xplot = xmf[ind] yplot = disk_size_sat[0, 0, ind] errdn = disk_size_sat[0, 1, ind] errup = disk_size_sat[0, 2, ind] ax.errorbar(xplot, yplot[0], yerr=[errdn[0], errup[0]], ls='None', mfc='None', ecolor='r', mec='r', marker='v', markersize=5, label="Shark satellites") #Lange et al. (2016) a = 5.56 aerr = 1.745 b = 0.274 ind = np.where(xmf < 10.3) rL16 = np.log10(a * pow((pow(10.0, xmf) / 1e10), b)) ax.plot(xmf[ind], rL16[ind], 'b', linestyle='solid', label='L16 disks') m, r = common.load_observation(obsdir, 'SizesAndAM/rdisk_L16.dat', [0, 1]) ax.plot(m[0:36], r[0:36], linestyle='dotted', color='b', label="50th, 68th, 90th") ax.plot(m[38:83], r[38:83], linestyle='dotted', color='b') ax.plot(m[85:128], r[85:129], linestyle='dotted', color='b') common.prepare_legend(ax, ['b', 'b', 'k', 'r'], loc=2) # ETGs ################################## xtit = "$\\rm log_{10} (\\rm M_{\\star,bulge}/M_{\odot})$" ytit = "$\\rm log_{10} (\\rm r_{\\star,bulge}/kpc)$" xmin, xmax, ymin, ymax = 8, 12, -0.35, 2 xleg = xmax - 0.2 * (xmax - xmin) yleg = ymax - 0.1 * (ymax - ymin) ax = fig.add_subplot(212) common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtit, ytit, locators=(0.1, 1, 0.1, 1)) #Predicted size-mass for bulges in bulge-dominated systems ind = np.where(bulge_size[0, 0, :] != 0) if (len(xmf[ind]) > 0): xplot = xmf[ind] yplot = bulge_size[0, 0, ind] errdn = bulge_size[0, 1, ind] errup = bulge_size[0, 2, ind] ax.errorbar(xplot, yplot[0], yerr=[errdn[0], errup[0]], ls='None', mfc='None', ecolor='k', mec='k', marker='o', label="Shark bulges") #for i in zip(bulge_size[0,0,:]): # print i ind = np.where((bulge_size_diskins[0, 0, :] != 0) & (xmf > 10.2)) if (len(xmf[ind]) > 0): xplot = xmf[ind] yplot = bulge_size_diskins[0, 0, ind] err = bulge_size[0, 1, ind] err[:] = 0 ax.errorbar(xplot, yplot[0], yerr=[err[0], err[0]], ls='None', mfc='None', ecolor='Orange', mec='Orange', marker='s', markersize=4, label="disk instability driven") ind = np.where((bulge_size_mergers[0, 0, :] != 0) & (xmf > 10.2)) if (len(xmf[ind]) > 0): xplot = xmf[ind] yplot = bulge_size_mergers[0, 0, ind] err = bulge_size[0, 1, ind] err[:] = 0 ax.errorbar(xplot, yplot[0], yerr=[err[0], err[0]], ls='None', mfc='None', ecolor='DarkCyan', mec='DarkCyan', marker='D', markersize=4, label="merger driven") rb_nodissipation = common.load_observation( obsdir, 'Models/SharkVariations/SizeBulges_OtherModels.dat', [0]) ind = np.where(rb_nodissipation != 0) xplot = xmf[ind] yplot = rb_nodissipation[ind] err = xmf[ind] err[:] = 0 ax.errorbar(xplot, yplot, yerr=[err, err], ls='None', mfc='None', ecolor='LightSlateGray', mec='LightSlateGray', marker='x', markersize=6, label="no dissipation") #Lange et al. (2016) a = 2.319 aerr = 1.186 b = 0.19565217391 a2 = 1.390 aerr2 = 0.9 b2 = 0.624 ind = np.where(xmf <= 10.3) rL16 = np.log10(a * pow((pow(10.0, xmf[ind]) / 1e10), b)) ax.plot(xmf[ind], rL16, 'r', linestyle='solid', label='L16 $M_{\\star}<2\\times 10^{10}\\rm M_{\odot}$') ind = np.where((xmf >= 10.3) & (xmf < 11.5)) rL16_2 = np.log10(a2 * pow((pow(10.0, xmf[ind]) / 1e10), b2)) ax.plot(xmf[ind], rL16_2, 'm', linestyle='solid', label='L16 $M_{\\star}>2\\times 10^{10}\\rm M_{\odot}$') m, r = common.load_observation(obsdir, 'SizesAndAM/rbulge_L16.dat', [0, 1]) ax.plot(m[0:39], r[0:39], linestyle='dotted', color='r') ax.plot(m[41:76], r[41:76], linestyle='dotted', color='r') ax.plot(m[78:115], r[78:115], linestyle='dotted', color='r') common.prepare_legend( ax, ['r', 'm', 'k', 'Orange', 'DarkCyan', 'LightSlateGray'], loc=2) common.savefig(outdir, fig, 'sizes.pdf')