Example of applying extinction corrections based on Balmer decrement¶

In this example we test out the PG16S metallicity calibrator before and after extinction correction.¶

[1]:

import numpy as np
from astropy import units as u
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
from edge_pydb import EdgeTable
from edge_pydb.plotting import xy2hist
from edge_pydb.conversion import get_Alambda
np.seterr(invalid='ignore')
plt.rcParams["scatter.edgecolors"] = 'none'

[2]:

fluxtab = EdgeTable('edge_carma.2d_smo7.hdf5', path='flux_elines_sm')
print(fluxtab.colnames)

['Name', 'ix', 'iy', 'ra_abs', 'dec_abs', 'ra_off', 'dec_off', 'rad_arc', 'azi_ang', 'flux_[OII]3727_sm', 'flux_[OIII]5007_sm', 'flux_[OIII]4959_sm', 'flux_Hbeta_sm', 'flux_[OI]6300_sm', 'flux_Halpha_sm', 'flux_[NII]6583_sm', 'flux_[NII]6548_sm', 'flux_[SII]6717_sm', 'flux_[SII]6731_sm', 'vel_[OII]3727_sm', 'vel_[OIII]5007_sm', 'vel_[OIII]4959_sm', 'vel_Hbeta_sm', 'vel_[OI]6300_sm', 'vel_Halpha_sm', 'vel_[NII]6583_sm', 'vel_[NII]6548_sm', 'vel_[SII]6717_sm', 'vel_[SII]6731_sm', 'disp_[OII]3727_sm', 'disp_[OIII]5007_sm', 'disp_[OIII]4959_sm', 'disp_Hbeta_sm', 'disp_[OI]6300_sm', 'disp_Halpha_sm', 'disp_[NII]6583_sm', 'disp_[NII]6548_sm', 'disp_[SII]6717_sm', 'disp_[SII]6731_sm', 'EW_[OII]3727_sm', 'EW_[OIII]5007_sm', 'EW_[OIII]4959_sm', 'EW_Hbeta_sm', 'EW_[OI]6300_sm', 'EW_Halpha_sm', 'EW_[NII]6583_sm', 'EW_[NII]6548_sm', 'EW_[SII]6717_sm', 'EW_[SII]6731_sm', 'e_flux_[OII]3727_sm', 'e_flux_[OIII]5007_sm', 'e_flux_[OIII]4959_sm', 'e_flux_Hbeta_sm', 'e_flux_[OI]6300_sm', 'e_flux_Halpha_sm', 'e_flux_[NII]6583_sm', 'e_flux_[NII]6548_sm', 'e_flux_[SII]6717_sm', 'e_flux_[SII]6731_sm', 'e_vel_[OII]3727_sm', 'e_vel_[OIII]5007_sm', 'e_vel_[OIII]4959_sm', 'e_vel_Hbeta_sm', 'e_vel_[OI]6300_sm', 'e_vel_Halpha_sm', 'e_vel_[NII]6583_sm', 'e_vel_[NII]6548_sm', 'e_vel_[SII]6717_sm', 'e_vel_[SII]6731_sm', 'e_disp_[OII]3727_sm', 'e_disp_[OIII]5007_sm', 'e_disp_[OIII]4959_sm', 'e_disp_Hbeta_sm', 'e_disp_[OI]6300_sm', 'e_disp_Halpha_sm', 'e_disp_[NII]6583_sm', 'e_disp_[NII]6548_sm', 'e_disp_[SII]6717_sm', 'e_disp_[SII]6731_sm', 'e_EW_[OII]3727_sm', 'e_EW_[OIII]5007_sm', 'e_EW_[OIII]4959_sm', 'e_EW_Hbeta_sm', 'e_EW_[OI]6300_sm', 'e_EW_Halpha_sm', 'e_EW_[NII]6583_sm', 'e_EW_[NII]6548_sm', 'e_EW_[SII]6717_sm', 'e_EW_[SII]6731_sm', 'flux_Hbeta_sm3_sm', 'flux_Halpha_sm3_sm', 'flux_sigsfr0_sm', 'e_flux_sigsfr0_sm', 'flux_sigsfr_corr_sm', 'e_flux_sigsfr_corr_sm', 'flux_AHa_corr_sm', 'e_flux_AHa_corr_sm', 'flux_AHa_smooth3_sm', 'flux_sigsfr_adopt_sm', 'BPT_sm', 'p_BPT_sm', 'SF_BPT_sm', 'ZOH_sm', 'e_ZOH_sm', 'ZOH_N2_sm', 'e_ZOH_N2_sm', 'ZOH_PP04_sm', 'alphsca_SL24_sm', 'alphsca_B13_sm']

Load data from the HDF5 files¶

[3]:

fluxcols = ['Name','ix','iy',
            'flux_Halpha_sm','e_flux_Halpha_sm',
            'flux_Hbeta_sm','e_flux_Hbeta_sm',
            'flux_[OII]3727_sm',
            'flux_[OIII]5007_sm',
            'flux_[OIII]4959_sm',
            'flux_[NII]6583_sm',
            'flux_[NII]6548_sm',
            'flux_[SII]6717_sm',
            'flux_[SII]6731_sm',
            'flux_AHa_corr_sm','ZOH_sm','ZOH_PP04_sm']
sspcols = ['Name','ix','iy','sigstar_sm']

fluxtab = EdgeTable('edge_carma.2d_smo7.hdf5', path='flux_elines_sm', cols=fluxcols)
ssptab  = EdgeTable('edge_carma.2d_smo7.hdf5', path='SSP_sm', cols=sspcols)
print('Working on full EDGE database')

Working on full EDGE database

Build the table¶

[4]:

fluxtab.join(ssptab, keys=['Name', 'ix', 'iy'])
goodval = ((fluxtab['sigstar_sm']>0) & (fluxtab['ZOH_sm']>0) & (fluxtab['ZOH_PP04_sm']>0))
fluxtab = fluxtab[goodval]
print(fluxtab.colnames)

['Name', 'ix', 'iy', 'flux_[OII]3727_sm', 'flux_[OIII]5007_sm', 'flux_[OIII]4959_sm', 'flux_Hbeta_sm', 'flux_Halpha_sm', 'flux_[NII]6583_sm', 'flux_[NII]6548_sm', 'flux_[SII]6717_sm', 'flux_[SII]6731_sm', 'e_flux_Hbeta_sm', 'e_flux_Halpha_sm', 'flux_AHa_corr_sm', 'ZOH_sm', 'ZOH_PP04_sm', 'sigstar_sm']

[5]:

fluxtab

[5]:

EdgeTable length=18718

Name	ix	iy	flux_[OII]3727_sm	flux_[OIII]5007_sm	flux_[OIII]4959_sm	flux_Hbeta_sm	flux_Halpha_sm	flux_[NII]6583_sm	flux_[NII]6548_sm	flux_[SII]6717_sm	flux_[SII]6731_sm	e_flux_Hbeta_sm	e_flux_Halpha_sm	flux_AHa_corr_sm	ZOH_sm	ZOH_PP04_sm	sigstar_sm
			1e-16 erg / (s cm2)	1e-16 erg / (s cm2)	1e-16 erg / (s cm2)	1e-16 erg / (s cm2)	1e-16 erg / (s cm2)	1e-16 erg / (s cm2)	1e-16 erg / (s cm2)	1e-16 erg / (s cm2)	1e-16 erg / (s cm2)	1e-16 erg / (s cm2)	1e-16 erg / (s cm2)	mag	dex	dex	solMass / pc2
bytes13	int32	int32	float32	float32	float32	float32	float32	float32	float32	float32	float32	float32	float32	float32	float32	float32	float32
IC0480	49	73	0.0870074	0.029897282	0.00988701	0.090097725	0.1102351	0.039026078	0.03247296	0.052571528	0.07800524	0.04135729	0.021687174	-2.1596358	8.539017	8.738997	12.573614
IC0480	52	37	0.18770462	0.0006616841	0.020474317	0.077797696	0.13354938	0.04970629	-0.0033357728	-0.008401535	0.0081396485	0.050240315	0.015807211	-1.2983286	8.884192	9.255148	26.140268
IC0480	52	40	0.032523226	0.015297297	0.019732146	0.095175065	0.24623917	0.08073771	0.0021618328	0.06013462	0.03042223	0.038109075	0.015223875	-0.2549448	8.59926	8.829081	24.226116
IC0480	52	43	0.20427044	0.035552263	0.021748396	0.06439884	0.3144415	0.091267064	0.014382704	0.10108422	0.055692498	0.053109188	0.015992831	1.360436	8.473248	8.640651	31.621964
IC0480	52	46	0.40225303	0.04589472	0.014781727	0.042140394	0.29628724	0.06591417	0.017525518	0.10502746	0.09001239	0.026825199	0.01795241	2.2878246	8.385384	8.509265	54.41814
IC0480	52	49	0.5109807	0.04305821	-0.016751453	0.08713781	0.31298056	0.050059613	0.03223156	0.10246124	0.107932776	0.047718827	0.021215593	0.5794677	8.428165	8.573238	27.101135
IC0480	52	52	0.7282568	0.046769876	-0.025693739	0.11716338	0.32595628	0.06137293	0.02597816	0.1093184	0.10446421	0.03686725	0.021137634	-0.07026943	8.46316	8.625566	23.207003
IC0480	52	55	0.9046924	0.07557559	-0.035164747	0.10379839	0.32900062	0.085429996	0.03418405	0.1176154	0.09720425	0.0544134	0.026175255	0.26143375	8.437176	8.586711	21.871445
IC0480	52	58	0.4987465	0.0561907	-0.006440433	0.09428996	0.30832374	0.11387592	0.039778575	0.13490917	0.11439781	0.042590417	0.021340411	0.34070367	8.488536	8.663512	31.224186
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
UGC10710	82	76	0.16022621	0.045934264	0.012153165	0.04992086	0.20847397	0.045280185	0.050486285	0.05896868	0.029508669	0.01349069	0.012928446	0.9628274	8.398823	8.529361	36.96709
UGC10710	82	79	0.22628286	0.094267435	0.023497574	0.07827878	0.43349308	0.112873405	0.06372519	0.10970437	0.06536664	0.016440732	0.01558738	1.6806467	8.390667	8.517165	77.58735
UGC10710	82	82	0.24255791	0.10042375	0.038316406	0.105462566	0.543226	0.15856762	0.060785186	0.13626258	0.08480374	0.012412386	0.013737223	1.4964257	8.42311	8.565679	94.70222
UGC10710	82	85	0.2684362	0.098271005	0.04123951	0.14911671	0.6230887	0.20278955	0.056196235	0.15960133	0.093449906	0.014324837	0.016215729	0.96431386	8.46743	8.631951	116.5556
UGC10710	82	88	0.32751876	0.1449957	0.05287768	0.1994595	0.9371745	0.3011065	0.077674896	0.21659751	0.17035489	0.018179536	0.016626917	1.2626557	8.457115	8.616528	124.4806
UGC10710	82	91	0.43588564	0.1830026	0.050604194	0.22881901	1.1491003	0.3589186	0.08512357	0.25932652	0.20814663	0.0137946075	0.016688244	1.4319085	8.445618	8.599336	115.169174
UGC10710	82	94	0.35743794	0.12879373	0.029977286	0.19854747	0.7901539	0.24986327	0.06776654	0.19456595	0.14232908	0.017470453	0.017791692	0.8402957	8.466224	8.630147	49.670353
UGC10710	85	88	0.12335152	0.054074615	0.0071914415	0.061936155	0.34665504	0.11250467	0.028205257	0.09589571	0.06051258	0.018478405	0.009063306	1.7076753	8.441028	8.592472	66.131744
UGC10710	85	91	0.13177331	0.07718527	0.011539073	0.075996235	0.42656717	0.1386436	0.03133806	0.108054236	0.09056572	0.013616693	0.010843548	1.7149495	8.427107	8.571654	67.18998

Compare metallicity estimates without extinction¶

[6]:

N2F  = fluxtab['flux_[NII]6583_sm']
N2Fb = fluxtab['flux_[NII]6548_sm']
S2F  = fluxtab['flux_[SII]6717_sm']
S2Fb = fluxtab['flux_[SII]6731_sm']
O2F  = fluxtab['flux_[OII]3727_sm']
O3F  = fluxtab['flux_[OIII]5007_sm']
O3Fb = fluxtab['flux_[OIII]4959_sm']
HaF  = fluxtab['flux_Halpha_sm']
HbF  = fluxtab['flux_Hbeta_sm']

R2 = np.log10(O2F)      - np.log10(HbF)
N2 = np.log10(N2Fb+N2F) - np.log10(HbF)
S2 = np.log10(S2F+S2Fb) - np.log10(HbF)
R3 = np.log10(O3Fb+O3F) - np.log10(HbF)
O3N2 = np.log10(O3F) - np.log10(HbF) - (np.log10(N2F) - np.log10(HaF))
snrcut = 3
Hbg = (abs(fluxtab['e_flux_Hbeta_sm']/fluxtab['flux_Hbeta_sm']) < 1/snrcut)
cond = Hbg & (HaF>0) & (HbF>0) & (N2F>0) & (N2Fb>0) & (S2F>0) & (S2Fb>0) & (O2F>0) & (O3F>0) & (O3Fb>0)

[7]:

# Equation (2) of 2013A&A...559A.114M
ZOH_M13 = 8.533 - 0.214 * O3N2[cond]
# Equation (3) of 2004MNRAS.348L..59P
ZOH_PP04 = 8.73 - 0.32 * O3N2[cond]
# Equation (9) of 2016MNRAS.457.3678P
ZOH_PG16S = 8.445 + 0.699*N2[cond] + S2[cond]*(0.217*N2[cond] - 0.253)
# Stellar surface density
sigstar = np.log10(fluxtab['sigstar_sm'][cond])

x_det, y_det, z_det, *hist = xy2hist(sigstar, ZOH_M13, log=False)
x_pp, y_pp, z_pp, *hist_pp = xy2hist(sigstar, ZOH_PP04, log=False)
x_pg, y_pg, z_pg, *hist_pg = xy2hist(sigstar, ZOH_PG16S, log=False)

fig, (ax1, ax2, ax3) = plt.subplots(ncols=3, figsize=(15,6))
sc1 = ax1.scatter(x_det, y_det, c=z_det, s=20, cmap='jet')
cb1 = plt.colorbar(sc1)
sc2 = ax2.scatter(x_pp, y_pp, c=z_pp, s=20, cmap='jet')
cb2 = plt.colorbar(sc2)
sc3 = ax3.scatter(x_pg, y_pg, c=z_pg, s=20, cmap='jet')
cb3 = plt.colorbar(sc3)
ax1.set_title('O3N2, Marino+13')
ax2.set_title('O3N2, PP04')
ax3.set_title('PG16S')
plt.subplots_adjust(wspace=0.15)

for ax in [ax1, ax2, ax3]:
    ax.axhline(8.69, ls=':', color='k', label='solar')
    if ax == ax1:
        # From MaNGA paper, doi:10.1093/mnras/stw1984
        xmod = np.linspace(1,3,num=50)
        ymod = 8.55 + 0.014*(xmod-3.14)*np.exp(-(xmod-3.14))
        ax.plot(xmod,ymod,color='magenta',ls='--',lw=4,label='JKBB+16')
        ax.set_ylabel('12 + log(O/H)',fontsize=14,labelpad=8)
    ax.legend(loc='upper left',fontsize=12)
    ax.set_xlabel('log $\Sigma_*$ ['+str(fluxtab['sigstar_sm'].unit)+']',fontsize=14)
    ax.set_ylim([8.0, 9.5])

_images/Alambda_demo_10_0.png

Compare metallicity estimates with extinction¶

[8]:

fluxcols=['flux_Hbeta_sm','flux_Halpha_sm','flux_[OII]3727_sm','flux_[NII]6548_sm','flux_[NII]6583_sm',
          'flux_[SII]6717_sm','flux_[SII]6731_sm','flux_[OIII]4959_sm','flux_[OIII]5007_sm']

[9]:

get_Alambda(fluxtab, fluxcols, fluxtab['flux_AHa_corr_sm'])
fluxtab

[9]:

EdgeTable length=18718

Name	ix	iy	flux_[OII]3727_sm	flux_[OII]3727_avcor_sm	flux_[OIII]5007_sm	flux_[OIII]5007_avcor_sm	flux_[OIII]4959_sm	flux_[OIII]4959_avcor_sm	flux_Hbeta_sm	flux_Hbeta_avcor_sm	flux_Halpha_sm	flux_Halpha_avcor_sm	flux_[NII]6583_sm	flux_[NII]6583_avcor_sm	flux_[NII]6548_sm	flux_[NII]6548_avcor_sm	flux_[SII]6717_sm	flux_[SII]6717_avcor_sm	flux_[SII]6731_sm	flux_[SII]6731_avcor_sm	e_flux_Hbeta_sm	e_flux_Halpha_sm	flux_AHa_corr_sm	ZOH_sm	ZOH_PP04_sm	sigstar_sm
			1e-16 erg / (s cm2)	1e-16 erg / (s cm2)	1e-16 erg / (s cm2)	1e-16 erg / (s cm2)	1e-16 erg / (s cm2)	1e-16 erg / (s cm2)	1e-16 erg / (s cm2)	1e-16 erg / (s cm2)	1e-16 erg / (s cm2)	1e-16 erg / (s cm2)	1e-16 erg / (s cm2)	1e-16 erg / (s cm2)	1e-16 erg / (s cm2)	1e-16 erg / (s cm2)	1e-16 erg / (s cm2)	1e-16 erg / (s cm2)	1e-16 erg / (s cm2)	1e-16 erg / (s cm2)	1e-16 erg / (s cm2)	1e-16 erg / (s cm2)	mag	dex	dex	solMass / pc2
bytes13	int32	int32	float32	float32	float32	float32	float32	float32	float32	float32	float32	float32	float32	float32	float32	float32	float32	float32	float32	float32	float32	float32	float32	float32	float32	float32
IC0480	49	73	0.0870074	0.0870074	0.029897282	0.029897282	0.00988701	0.00988701	0.090097725	0.090097725	0.1102351	0.1102351	0.039026078	0.039026078	0.03247296	0.03247296	0.052571528	0.052571528	0.07800524	0.07800524	0.04135729	0.021687174	0.0	8.539017	8.738997	12.573614
IC0480	52	37	0.18770462	0.18770462	0.0006616841	0.0006616841	0.020474317	0.020474317	0.077797696	0.077797696	0.13354938	0.13354938	0.04970629	0.04970629	-0.0033357728	-0.0033357728	-0.008401535	-0.008401535	0.0081396485	0.0081396485	0.050240315	0.015807211	0.0	8.884192	9.255148	26.140268
IC0480	52	40	0.032523226	0.032523226	0.015297297	0.015297297	0.019732146	0.019732146	0.095175065	0.095175065	0.24623917	0.24623917	0.08073771	0.08073771	0.0021618328	0.0021618328	0.06013462	0.06013462	0.03042223	0.03042223	0.038109075	0.015223875	0.0	8.59926	8.829081	24.226116
IC0480	52	43	0.20427044	2.160007	0.035552263	0.19784589	0.021748396	0.1236623	0.06439884	0.38339454	0.3144415	1.1008148	0.091267064	0.31800622	0.014382704	0.050530653	0.10108422	0.34123284	0.055692498	0.18738125	0.053109188	0.015992831	1.360436	8.473248	8.640651	31.621964
IC0480	52	46	0.40225303	21.230713	0.04589472	0.8229836	0.014781727	0.27483875	0.042140394	0.8464748	0.29628724	2.4369287	0.06591417	0.53784406	0.017525518	0.14500754	0.10502746	0.81255066	0.09001239	0.69251883	0.026825199	0.01795241	2.2878246	8.385384	8.509265	54.41814
IC0480	52	49	0.5109807	1.3953276	0.04305821	0.08944974	-0.016751453	-0.035120312	0.08713781	0.1863002	0.31298056	0.53370893	0.050059613	0.08519226	0.03223156	0.05504583	0.10246124	0.17203383	0.107932776	0.1809652	0.047718827	0.021215593	0.5794677	8.428165	8.573238	27.101135
IC0480	52	52	0.7282568	0.7282568	0.046769876	0.046769876	-0.025693739	-0.025693739	0.11716338	0.11716338	0.32595628	0.32595628	0.06137293	0.06137293	0.02597816	0.02597816	0.1093184	0.1093184	0.10446421	0.10446421	0.03686725	0.021137634	0.0	8.46316	8.625566	23.207003
IC0480	52	55	0.9046924	1.4234103	0.07557559	0.10510802	-0.035164747	-0.049108725	0.10379839	0.14624368	0.32900062	0.41857204	0.085429996	0.10858989	0.03418405	0.043520406	0.1176154	0.1485936	0.09720425	0.12272833	0.0544134	0.026175255	0.26143375	8.437176	8.586711	21.871445
IC0480	52	58	0.4987465	0.90030575	0.0561907	0.08636848	-0.006440433	-0.0099528525	0.09428996	0.14739953	0.30832374	0.42197666	0.11387592	0.15566798	0.039778575	0.054489944	0.13490917	0.18296345	0.11439781	0.15501738	0.042590417	0.021340411	0.34070367	8.488536	8.663512	31.224186
...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...	...
UGC10710	82	76	0.16022621	0.8504139	0.045934264	0.1547834	0.012153165	0.041580964	0.04992086	0.17644608	0.20847397	0.5060376	0.045280185	0.10954342	0.050486285	0.12285542	0.05896868	0.13949715	0.029508669	0.06964272	0.01349069	0.012928446	0.9628274	8.398823	8.529361	36.96709
UGC10710	82	79	0.22628286	4.168528	0.094267435	0.78574765	0.023497574	0.20113866	0.07827878	0.7092051	0.43349308	2.038172	0.112873405	0.5276115	0.06372519	0.30093467	0.10970437	0.4931229	0.06536664	0.29262465	0.016440732	0.01558738	1.6806467	8.390667	8.517165	77.58735
UGC10710	82	82	0.24255791	3.2467554	0.10042375	0.6634569	0.038316406	0.25920656	0.105462566	0.75043374	0.543226	2.155514	0.15856762	0.6259314	0.060785186	0.24213743	0.13626258	0.5194693	0.08480374	0.32211915	0.012412386	0.013737223	1.4964257	8.42311	8.565679	94.70222
UGC10710	82	85	0.2684362	1.4284235	0.098271005	0.33176264	0.04123951	0.14136548	0.14911671	0.5280838	0.6230887	1.5145216	0.20278955	0.4912652	0.056196235	0.13693812	0.15960133	0.3780574	0.093449906	0.22084153	0.014324837	0.016215729	0.96431386	8.46743	8.631951	116.5556
UGC10710	82	88	0.32751876	2.9232683	0.1449957	0.71323985	0.05287768	0.26535735	0.1994595	1.0445682	0.9371745	2.998353	0.3011065	0.95912915	0.077674896	0.24932869	0.21659751	0.66995394	0.17035489	0.52530485	0.018179536	0.016626917	1.2626557	8.457115	8.616528	124.4806
UGC10710	82	91	0.43588564	5.2171426	0.1830026	1.1145021	0.050604194	0.31524754	0.22881901	1.4961102	1.1491003	4.2965646	0.3589186	1.3353608	0.08512357	0.31947297	0.25932652	0.93319625	0.20814663	0.7464175	0.0137946075	0.016688244	1.4319085	8.445618	8.599336	115.169174
UGC10710	82	94	0.35743794	1.5340706	0.12879373	0.37182644	0.029977286	0.08770275	0.19854747	0.5976026	0.7901539	1.7132865	0.24986327	0.5401976	0.06776654	0.14726	0.19456595	0.41249788	0.14232908	0.30113435	0.017470453	0.017791692	0.8402957	8.466224	8.630147	49.670353
UGC10710	85	88	0.12335152	2.3813593	0.054074615	0.46636426	0.0071914415	0.063721314	0.061936155	0.5813864	0.34665504	1.6709661	0.11250467	0.5390932	0.028205257	0.13656305	0.09589571	0.44159874	0.06051258	0.277504	0.018478405	0.009063306	1.7076753	8.441028	8.592472	66.131744
UGC10710	85	91	0.13177331	2.5762289	0.07718527	0.6718189	0.011539073	0.103199035	0.075996235	0.72020364	0.42656717	2.0699852	0.1386436	0.66879314	0.03133806	0.1527542	0.108054236	0.500836	0.09056572	0.4180275	0.013616693	0.010843548	1.7149495	8.427107	8.571654	67.18998

[10]:

N2F  = fluxtab['flux_[NII]6583_avcor_sm']
N2Fb = fluxtab['flux_[NII]6548_avcor_sm']
S2F  = fluxtab['flux_[SII]6717_avcor_sm']
S2Fb = fluxtab['flux_[SII]6731_avcor_sm']
O2F  = fluxtab['flux_[OII]3727_avcor_sm']
O3F  = fluxtab['flux_[OIII]5007_avcor_sm']
O3Fb = fluxtab['flux_[OIII]4959_avcor_sm']
HaF  = fluxtab['flux_Halpha_avcor_sm']
HbF  = fluxtab['flux_Hbeta_avcor_sm']

R2 = np.log10(O2F)      - np.log10(HbF)
N2 = np.log10(N2Fb+N2F) - np.log10(HbF)
S2 = np.log10(S2F+S2Fb) - np.log10(HbF)
R3 = np.log10(O3Fb+O3F) - np.log10(HbF)
O3N2 = np.log10(O3F) - np.log10(HbF) - (np.log10(N2F) - np.log10(HaF))
snrcut = 3
Hbg = (abs(fluxtab['e_flux_Hbeta_sm']/fluxtab['flux_Hbeta_sm']) < 1/snrcut)
cond = Hbg & (HaF>0) & (HbF>0) & (N2F>0) & (N2Fb>0) & (S2F>0) & (S2Fb>0) & (O2F>0) & (O3F>0) & (O3Fb>0)

[11]:

# Equation (2) of 2013A&A...559A.114M
ZOH_M13 = 8.533 - 0.214 * O3N2[cond]
# Equation (3) of 2004MNRAS.348L..59P
ZOH_PP04 = 8.73 - 0.32 * O3N2[cond]
# Equation (9) of 2016MNRAS.457.3678P
ZOH_PG16S = 8.445 + 0.699*N2[cond] + S2[cond]*(0.217*N2[cond] - 0.253)
# Stellar surface density
sigstar = np.log10(fluxtab['sigstar_sm'][cond])

x_det, y_det, z_det, *hist = xy2hist(sigstar, ZOH_M13, log=False)
x_pp, y_pp, z_pp, *hist_pp = xy2hist(sigstar, ZOH_PP04, log=False)
x_pg, y_pg, z_pg, *hist_pg = xy2hist(sigstar, ZOH_PG16S, log=False)

fig, (ax1, ax2, ax3) = plt.subplots(ncols=3, figsize=(15,6))
sc1 = ax1.scatter(x_det, y_det, c=z_det, s=20, cmap='jet')
cb1 = plt.colorbar(sc1)
sc2 = ax2.scatter(x_pp, y_pp, c=z_pp, s=20, cmap='jet')
cb2 = plt.colorbar(sc2)
sc3 = ax3.scatter(x_pg, y_pg, c=z_pg, s=20, cmap='jet')
cb3 = plt.colorbar(sc3)
ax1.set_title('O3N2, Marino+13')
ax2.set_title('O3N2, PP04')
ax3.set_title('PG16S')
plt.subplots_adjust(wspace=0.15)

for ax in [ax1, ax2, ax3]:
    ax.axhline(8.69, ls=':', color='k', label='solar')
    ax.axhline(8.5, ls='--', color='k', label='$R_G$=8 kpc')
    if ax == ax1:
        # From MaNGA paper, doi:10.1093/mnras/stw1984
        xmod = np.linspace(1,3,num=50)
        ymod = 8.55 + 0.014*(xmod-3.14)*np.exp(-(xmod-3.14))
        ax.plot(xmod,ymod,color='magenta',ls='--',lw=4,label='JKBB+16')
        ax.set_ylabel('12 + log(O/H)',fontsize=14,labelpad=8)
    ax.legend(loc='upper left',fontsize=12)
    ax.set_xlabel('log $\Sigma_*$ ['+str(fluxtab['sigstar_sm'].unit)+']',fontsize=14)
    ax.set_ylim([8.0, 9.5])

_images/Alambda_demo_15_0.png

Histograms of strong-line ratios in Pilyugin & Grebel 2016¶

[12]:

fig = plt.figure(tight_layout=True)
gs = gridspec.GridSpec(2, 2)
ax00 = fig.add_subplot(gs[0, 0])
ax00.hist(R2[cond], bins='scott')
ax00.set_xlabel(r'log([O II]/H$\beta$)', size='x-large')
ax01 = fig.add_subplot(gs[0, 1])
ax01.hist(N2[cond], bins='scott')
ax01.set_xlabel(r'log([N II]/H$\beta$)', size='x-large')
ax10 = fig.add_subplot(gs[1, 0])
ax10.hist(S2[cond], bins='scott')
ax10.set_xlabel(r'log([S II]/H$\beta$)', size='x-large')
ax11 = fig.add_subplot(gs[1, 1])
ax11.hist(R3[cond], bins='scott')
ax11.set_xlabel(r'log([O III]/H$\beta$)', size='x-large')

[12]:

Text(0.5, 0, 'log([O III]/H$\\beta$)')

_images/Alambda_demo_17_1.png

Histograms of O3N2 and Metallicity¶

[13]:

fig = plt.figure(tight_layout=True)
gs = gridspec.GridSpec(2, 2)
ax = fig.add_subplot(gs[:, 0])
ax.hist(O3N2, bins='scott')
ax.set_xlabel(r'log[([O III]/H$\beta$)/([NII]/H$\alpha$)]', size='x-large')
ax1 = fig.add_subplot(gs[0, 1])
ax1.hist(ZOH_M13, bins='scott')
ax1.set_xlabel('12 + log(O/H)', size='x-large')
ax1.set_xlim([8,9.5])
ax1.text(0.95,0.85, 'Marino+13', ha='right', transform=ax1.transAxes)
ax1.axvline(8.55, ls=':', color='k')
ax2 = fig.add_subplot(gs[1, 1])
ax2.hist(ZOH_PG16S, bins='scott')
ax2.set_xlabel('12 + log(O/H)', size='x-large')
ax2.set_xlim([8,9.5])
ax2.text(0.95,0.85, 'PG16S', ha='right', transform=ax2.transAxes)
ax2.axvline(8.55, ls=':', color='k')

[13]:

<matplotlib.lines.Line2D at 0x17b728e20>

_images/Alambda_demo_19_1.png

[ ]: