Examples for LLSSurvey (v1.5)¶

# imports
import seaborn as sns; sns.set_style("white")

import imp
import h5py

from bokeh.io import output_notebook, show, hplot, output_file
from bokeh.plotting import figure
from bokeh.models import Range1d

output_notebook()

from linetools import utils as ltu

from pyigm.surveys.llssurvey import LLSSurvey
from pyigm.surveys import llssurvey as llss
from pyigm.abssys.igmsys import AbsSubSystem
from pyigm.abssys.lls import LLSSystem
from pyigm.abssys import lls as pylls
from pyigm.surveys import lls_literature as llit

/Users/xavier/anaconda/lib/python2.7/site-packages/matplotlib/__init__.py:872: UserWarning: axes.color_cycle is deprecated and replaced with axes.prop_cycle; please use the latter.
  warnings.warn(self.msg_depr % (key, alt_key))

BokehJS successfully loaded.

LLS Tree (JXP) – Likely to Deprecate¶

#reload(llsu)
lls_survey = LLSSurvey.from_flist('Lists/lls_metals.lst', tree=os.getenv('LLSTREE'))

Read 165 files from Lists/lls_metals.lst in the tree /u/xavier/LLS/

HD-LLS (Prochaska+15, ApJS, 221, 22)¶

Simple Init¶

# Includes metallicity PDFs from Fumagalli+16
reload(llss)
hdlls = llss.LLSSurvey.load_HDLLS(load_sys=False)
hdlls

HD-LLS: Loading summary file /Users/xavier/local/Python/pyigm/pyigm/data/LLS/HD-LLS/HD-LLS_DR1.fits
HD-LLS: Loading ions file /Users/xavier/local/Python/pyigm/pyigm/data/LLS/HD-LLS/HD-LLS_ions.json
HD-LLS: Loading metallicity file /Users/xavier/local/Python/pyigm/pyigm/data/LLS/HD-LLS/HD-LLS_DR1_dustnhi.hdf5

<IGMSurvey: nsys=157, type=LLS, ref=HD-LLS>

With Systems (takes ~2 min)¶

hdlls = LLSSurvey.load_HDLLS()
hdlls

HD-LLS: Loading summary file /Users/xavier/local/Python/pyigm/pyigm/data/LLS/HD-LLS/HD-LLS_DR1.fits
HD-LLS: Loading ions file /Users/xavier/local/Python/pyigm/pyigm/data/LLS/HD-LLS/HD-LLS_ions.json
HD-LLS: Loading metallicity file /Users/xavier/local/Python/pyigm/pyigm/data/LLS/HD-LLS/HD-LLS_DR1_dustnhi.hdf5
Loading systems from /Users/xavier/local/Python/pyigm/pyigm/data/LLS/HD-LLS/HD-LLS_sys.tar.gz
Skipping a likely folder: SYS

WARNING: UnitsWarning: The unit 'Angstrom' has been deprecated in the FITS standard. Suggested: 10**-1 nm. [astropy.units.format.utils]
WARNING:astropy:UnitsWarning: The unit 'Angstrom' has been deprecated in the FITS standard. Suggested: 10**-1 nm.

linetools.lists.parse: Reading linelist ---
   /Users/xavier/local/Python/linetools/linetools/data/lines/morton03_table2.fits.gz
linetools.lists.parse: Reading linelist ---
   /Users/xavier/local/Python/linetools/linetools/data/lines/morton00_table2.fits.gz
linetools.lists.parse: Reading linelist ---
   /Users/xavier/local/Python/linetools/linetools/data/lines/verner96_tab1.fits.gz
linetools.lists.parse: Reading linelist ---
   /Users/xavier/local/Python/linetools/linetools/data/lines/verner94_tab6.fits

WARNING: UnitsWarning: '0.1nm' did not parse as fits unit: Numeric factor not supported by FITS [astropy.units.core]
WARNING:astropy:UnitsWarning: '0.1nm' did not parse as fits unit: Numeric factor not supported by FITS

linetools.lists.parse: Reading linelist ---
   /Users/xavier/local/Python/linetools/linetools/data/lines/EUV_lines.ascii
read_sets: Using set file --
  /Users/xavier/local/Python/linetools/linetools/lists/sets/llist_v1.0.ascii

<IGMSurvey: nsys=157, type=LLS, ref=HD-LLS>

Spectra¶

hdlls = LLSSurvey.load_HDLLS(grab_spectra=True)

HD-LLS: Loading summary file /Users/xavier/local/Python/pyigm/pyigm/data/LLS/HD-LLS/HD-LLS_DR1.fits
HD-LLS: Loading ions file /Users/xavier/local/Python/pyigm/pyigm/data/LLS/HD-LLS/HD-LLS_ions.json
HD-LLS: Loading metallicity file /Users/xavier/local/Python/pyigm/pyigm/data/LLS/HD-LLS/HD-LLS_DR1_dustnhi.hdf5
Loading systems from /Users/xavier/local/Python/pyigm/pyigm/data/LLS/HD-LLS/HD-LLS_sys.tar.gz
Skipping a likely folder: SYS
HD-LLS: Using files in /Users/xavier/local/Python/pyigm/pyigm/data/LLS/HD-LLS/Spectra/

hdlls.nsys

hdlls.NHI[0:10]

array([ 19.65,  20.05,  17.55,  19.1 ,  20.  ,  19.05,  19.1 ,  19.05,
        19.25,  20.2 ])

hdlls.name[0:5]

array([u'J000345-232346.5_z2.187', u'J003454.8+163920_z3.754',
       u'J004049.5-402514_z2.816', u'J010355.3-300946_z2.908',
       u'J010516.8-184642_z2.927'],
      dtype='<U27')

hdlls._abs_sys[77]._ionN

Z	ion	A	Ej	z	vmin	vmax	flag_N	logN	sig_logN
					km / s	km / s
int64	int64	int64	float64	float64	float64	float64	int64	float64	float64
6	1	0	0.0	3.72296	-150.460978217	225.539021783	3	13.061	0.0
6	2	0	0.0	3.72296	-150.460978217	225.539021783	2	14.68	0.01
6	2	0	63.42	3.72296	-74.4609782171	225.539021783	0	0.0	0.0
6	4	0	0.0	3.72296	-150.460978217	225.539021783	1	13.906	0.021
13	2	0	0.0	3.72296	-150.460978217	225.539021783	1	12.742	0.027
13	3	0	0.0	3.72296	-150.460978217	225.539021783	3	12.471	0.0
14	2	0	0.0	3.72296	-150.460978217	225.539021783	1	14.031	0.02
14	4	0	0.0	3.72296	-150.460978217	225.539021783	1	13.568	0.018
24	2	0	0.0	3.72296	-150.460978217	225.539021783	3	13.42	0.0
28	2	0	0.0	3.72296	-150.460978217	225.539021783	3	13.472	0.0
30	2	0	0.0	3.72296	-150.460978217	225.539021783	3	12.971	0.0

CII_clms = hdlls.ions((6,2))
CII_clms[70:80]

name	Z	ion	A	Ej	z	vmin	vmax	flag_N	logN	sig_logN
						km / s	km / s
unicode32	int64	int64	int64	float64	float64	float64	float64	int64	float64	float64
J111008.61+024458.1_z3.476	0	0	0	0.0	0.0	0.0	0.0	0	0.0	0.0
J111113.64-080402.47_z3.481	0	0	0	0.0	0.0	0.0	0.0	0	0.0	0.0
J111113.64-080402.47_z3.811	6	2	0	0.0	3.8112	-21.0	21.0	1	13.491	0.047
J113130.41+604420.7_z2.362	0	0	0	0.0	0.0	0.0	0.0	0	0.0	0.0
J113418.96+574204.7_z3.410	6	2	0	0.0	3.41	44.9584916	128.798769771	3	12.7996771908	0.0
J113621+005021_z3.248	6	2	0	0.0	3.24829	-89.2943220496	85.7056779504	1	13.934	0.03
J115659.59+551308.1_z2.616	0	0	0	0.0	0.0	0.0	0.0	0	0.0	0.0
J115906.48+133737.7_z3.723	6	2	0	0.0	3.72296	-150.460978217	225.539021783	2	14.68	0.01
J115940.7-003203.5_z1.904	6	2	0	0.0	1.9044	-380.0	90.0	2	15.379	0.909
J120331.29+152254.7_z2.708	6	2	0	0.0	2.708	-220.0	303.0	2	14.627	0.009

gdCII = CII_clms['flag_N']>0
np.sum(gdCII)

# NHI
p_NHI = figure(plot_width=400, plot_height=400, title='HD-LLS NHI')#,background_fill="#E8DDCB")
hist, edges = np.histogram(hdlls.NHI, range=(17.,20.4), density=True, bins=20)
p_NHI.quad(top=hist, bottom=0, left=edges[:-1], right=edges[1:],fill_color='blue')
p_NHI.xaxis.axis_label = 'N_HI'
# z
p_z = figure(plot_width=400, plot_height=400, title='HD-LLS z')#,background_fill="#E8DDCB")
hist, edges = np.histogram(hdlls.zabs, range=(2.4, 4.5), density=True, bins=20)
p_z.quad(top=hist, bottom=0, left=edges[:-1], right=edges[1:],fill_color='red')
p_z.xaxis.axis_label = 'z_LLS'
# Show
show(hplot(p_NHI,p_z))

print('Mean metallicity of {:s} is {:g}'.format(hdlls._abs_sys[0], hdlls._abs_sys[0].metallicity.meanZH))

Mean metallicity of <LLSSystem: 00:03:45 -23:23:46.5, zabs=2.1871, logNHI=19.65, tau_LL=283.16, [Z/H]=0 dex> is -1.47315

SDSS LLS (Prochaska+10, ApJ, 718, 391)¶

All¶

sdss_dr7_all = LLSSurvey.load_SDSS_DR7(sample='all')
sdss_dr7_all

SDSS-DR7: Loading LLS file /Users/xavier/local/Python/pyigm/pyigm/data/LLS/SDSS/lls_dr7_stat_LLS.fits.gz
SDSS-DR7: Loading QSOs file /Users/xavier/local/Python/pyigm/pyigm/data/LLS/SDSS/lls_dr7_qsos_sn2050.fits.gz

<IGMSurvey: nsys=1935, type=LLS, ref=SDSS-DR7, nsightlines=3759>

sdss_dr7_all.sightlines[0:5]

DR	PLATE	FIBER	MJD	RA	DEC	IMAG	U	UG	GR	SNR	FLG_LLS	FLG_EXTRA	LLS_FLUX	ZT2	ZT0	ZLLS	ZEM	FLG_QSO
str3	int32	int32	int32	float64	float64	float32	float32	float32	float32	float32	int16	int16	float32	float32	float32	float32	float32	int16
DR7	1187	324	52708	129.1273	6.3457866	19.8499	23.6163	2.88079	0.763817	1.46418	3	0	0.0	3.45469	4.81323	0.0	3.40001	0
DR7	1697	44	53142	199.16685	10.982457	20.1359	25.715	4.93595	0.562878	1.52782	2	0	0.0	3.45469	4.79319	0.0	3.40006	0
DR7	1291	182	52735	226.38853	41.329546	19.1578	23.7557	3.8441	0.631777	2.45875	2	0	0.0452141	3.44956	3.90137	3.30447	3.40018	0
DR7	1742	292	53053	145.02499	10.988845	19.522	24.9317	4.601	0.613277	1.33537	3	0	0.0	3.45469	4.75993	0.0	3.40044	0
DR7	2137	599	54206	220.78203	28.0573	19.8515	25.7578	5.3715	0.449001	1.64206	4	0	0.0	3.45469	4.76126	0.0	3.4006	0

Stat¶

sdss_dr7_stat = LLSSurvey.load_SDSS_DR7()

SDSS-DR7: Loading LLS file /Users/xavier/local/Python/pyigm/pyigm/data/LLS/SDSS/lls_dr7_stat_LLS.fits.gz
SDSS-DR7: Loading QSOs file /Users/xavier/local/Python/pyigm/pyigm/data/LLS/SDSS/lls_dr7_qsos_sn2050.fits.gz
SDSS-DR7: Performing stats (~60s)
SDSS-DR7: Loaded

len(sdss_dr7_stat.NHI)

Sky Map¶

all_coord = sdss_dr7_all.coord
stat_coord = sdss_dr7_stat.coord

%matplotlib inline

plt.figure(figsize=(12, 7))
plt.clf()
# Setup
ax = plt.axes(projection='mollweide')
ax = plt.axes()
ax.set_xlabel('RA')
ax.set_ylabel('DEC')
ax.set_xticklabels(np.arange(30,331,30))
ax.grid(True)
# All
plt.scatter((all_coord.ra.value-180.)*np.pi/180., all_coord.dec.value*np.pi/180.,
            marker='o', s=3., lw=0.5, edgecolors='gray', facecolors='none',
            label='all')
# Stat
plt.scatter((stat_coord.ra.value-180.)*np.pi/180., stat_coord.dec.value*np.pi/180.,
            marker='o', s=3., lw=0.5, edgecolors='blue', facecolors='blue',
            label='stat')
# Legend
legend = plt.legend(loc='upper right', scatterpoints=1, borderpad=0.2,
                        handletextpad=0.1, fontsize='large')
plt.show()

LLSSurvey_examples_files/LLSSurvey_examples_33_0.png

\(z \sim 2.5\) HST (O’Meara et al. 2013, ApJ, 765, 137)¶

ACS¶

acs = LLSSurvey.load_HST_ACS()
acs

HST-ACS: Loaded

<IGMSurvey: nsys=34, type=LLS, ref=HST-ACS, nsightlines=18>

WFC3¶

wfc3 = LLSSurvey.load_HST_WFC3()
wfc3

HST-WFC3: Loaded

<IGMSurvey: nsys=91, type=LLS, ref=HST-WFC3, nsightlines=53>

Combined¶

HST_LLS = wfc3 + acs
HST_LLS

<IGMSurvey: nsys=125, type=LLS, ref=HST-WFC3,HST-ACS, nsightlines=71>

\(z \sim 3\) MagE (Fumagalli et al. 2013, ApJ, 775, 78)¶

Load¶

z3mage = LLSSurvey.load_mage_z3()
z3mage

<IGMSurvey: nsys=60, type=LLS, ref=z3_MagE, nsightlines=105>

z3mage_NC = LLSSurvey.load_mage_z3(sample='non-color')
z3mage_NC

<IGMSurvey: nsys=32, type=LLS, ref=z3_MagE, nsightlines=61>

g(z) plot¶

zeval, gz = z3mage.calculate_gz()

zeval[4000], gz[4000]

(2.8705998897560931, 67)

plt.clf()
plt.plot(zeval, gz)
plt.xlabel('z')
plt.ylabel('g(z)')
plt.show()

LLSSurvey_examples_files/LLSSurvey_examples_50_0.png

Literature¶

from pyigm.surveys.lls_literature import log_sum

reload(llit)
zonak04 = llit.zonak2004()
print(zonak04)
zonak04._ionN

<LLSSystem: 16:34:28.9897 +70:31:32.422, zabs=1.0414, logNHI=17.23, tau_LL=1.07654, [Z/H]=0 dex>

logN	sig_logN	flag_N	Z	ion
float64	float64	int64	int64	int64
12.4473519121	0.129178793071	1	14	4
13.4329439428	0.170997184174	1	14	3
12.415294802	0.05	1	12	2

reload(llit)
jenkins05 = llit.jenkins2005()
jenkins05._ionN

No error for N I
No error for O I
No error for O I
WARNING: Using 1393.7550 Angstrom for your input 1393.7600 Angstrom
WARNING: Using 1402.7700 Angstrom for your input 1402.7730 Angstrom
WARNING: Using 1012.4950 Angstrom for your input 1012.5010 Angstrom
WARNING: Using 1190.2030 Angstrom for your input 1190.1910 Angstrom

ion	Z	sig_logN	flag_N	logN
int64	int64	float64	int64	float64
3	16	0.06	1	14.19
1	1	0.05	1	17.98
4	6	0.4	1	13.9
2	14	0.05	1	13.95
2	7	0.4	1	13.92
2	16	0.2	1	13.7
1	8	0.05	1	14.47
3	6	0.0	2	13.5
1	7	0.0	3	12.44
4	14	0.25	1	13.53
1	18	0.0	3	12.6
2	6	0.0	2	14.7
2	26	0.12	1	13.59

reload(llit)
tripp05 = llit.tripp2005()
tripp05._ionN

logN	ion	sig_logN	Z	flag_N
float64	int64	float64	int64	int64
13.36	4	0.0	6	3
13.5066831639	2	0.0521636459228	14	1
14.4059239514	1	0.075591125682	8	1
13.28	1	0.0	7	3
12.88	4	0.0	14	3
14.2673822193	2	0.263055215693	6	1
13.43	2	0.11	26	1

reload(llit)
peroux06a = llit.peroux06a()
print(peroux06a)
peroux06a._ionN

<LLSSystem: 01:34:05.75 +00:51:09.4, zabs=0.842, logNHI=19.93, tau_LL=539.55, [Z/H]=0 dex>

ion	Z	sig_logN	flag_N	logN
int64	int64	float64	int64	float64
2	24	0.0	3	12.6380948725
2	30	0.0	3	12.0878283736
1	12	0.0333114495397	1	12.2347702952
2	26	0.0165813621851	1	14.4774468535
2	12	0.0	2	13.6989700043

reload(llit)
peroux06b = llit.peroux06b()
print(peroux06b)
peroux06b._ionN

<LLSSystem: 13:23:23.78 -00:21:55.2, zabs=0.716, logNHI=20.21, tau_LL=1028.09, [Z/H]=0 dex>

ion	Z	sig_logN	flag_N	logN
int64	int64	float64	int64	float64
2	24	0.161460798648	1	13.0820669343
2	25	0.0187835949381	1	13.3100982719
2	12	0.0	2	15.1537904822
1	12	0.0129070876912	1	13.2627950666
2	22	0.0656476491959	1	12.4092739152
2	30	0.044243954439	1	13.4082908562
2	26	0.0260564242229	1	15.1549410447

reload(llit)
meiring06 = llit.meiring06()
print(meiring06)
meiring06._ionN

<LLSSystem: 11:07:36.6552 +00:03:28.62, zabs=0.9542, logNHI=20.26, tau_LL=1153.54, [Z/H]=0 dex>

ion	Z	sig_logN	flag_N	logN
int64	int64	float64	int64	float64
2	22	0.0	3	13.01
2	24	0.0	3	12.76
2	30	0.0	3	12.08

reload(llit)
meiring07 = llit.meiring07()
for imeiring07 in meiring07:
    print(imeiring07)
    print(imeiring07._ionN)

<LLSSystem: 03:54:05.9 -27:24:25.7, zabs=1.4051, logNHI=20.18, tau_LL=959.471, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  2     0.04  24      1 13.25
  2     0.03  25      1 12.82
  1     0.01  12      1  12.7
  2     0.01  26      1 15.03
  2      0.0  12      2 14.39
<LLSSystem: 08:26:01.5 -22:30:26.2, zabs=0.911, logNHI=19.04, tau_LL=69.5076, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  2     0.04  20      1 11.42
  1     0.02  12      1 12.06
  2     0.12  26      1 13.43
  2      0.0  12      2 13.71
<LLSSystem: 10:09:30.4 -00:26:19.1, zabs=0.8426, logNHI=20.2, tau_LL=1004.69, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  2     0.03  26      1 14.37
  2     0.04  25      1 12.28
  1     0.05  12      1  11.8
  3     0.03  13      1 12.74
  2      0.0  12      2 13.87
<LLSSystem: 10:09:30.4 -00:26:19.1, zabs=0.8866, logNHI=19.48, tau_LL=191.44, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  2     0.06  26      1 14.33
  2     0.04  20      1  12.1
  1     0.02  12      1 12.43
  3     0.02  13      1  13.0
  2      0.0  12      2 14.32
<LLSSystem: 10:10:33.4 -00:47:24.5, zabs=1.327, logNHI=19.81, tau_LL=409.291, [Z/H]=0 dex>
ion  Z  sig_logN flag_N  logN
--- --- -------- ------ -----
  2  13      0.0      2 13.72
  3  13     0.02      1 13.29
  2  14     0.15      1 14.86
  1  12     0.02      1 12.49
  2  12      0.0      2 14.26
  2  26     0.02      1  14.5
<LLSSystem: 12:24:14.3 +00:37:09, zabs=1.2665, logNHI=20, tau_LL=633.916, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  2     0.04  26      1 14.36
  3     0.14  13      1 12.74
  1     0.08  12      1 12.21
  2      0.0  13      2 13.56
  2      0.0  12      2 14.25
<LLSSystem: 23:31:21.8 +00:38:07.4, zabs=1.1414, logNHI=20, tau_LL=633.916, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  2     0.05  26      1 14.44
  3     0.14  13      1 12.86
  1     0.03  12      1 12.47
  2      0.0  13      2 13.33
  2      0.0  12      2 14.39

reload(llit)
meiring08 = llit.meiring08()
for imeiring08 in meiring08:
    print(imeiring08)
    print(imeiring08._ionN)

<LLSSystem: 10:37:44.4 +00:28:09.2, zabs=1.4244, logNHI=20.04, tau_LL=695.076, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  2     0.11  25      1 12.57
  2      0.0  13      2  13.6
  3     0.03  13      1 13.15
  2     0.05  14      1 15.05
  2      0.0  12      2 14.44
  2     0.09  26      1 14.96
<LLSSystem: 10:54:40.98 -00:20:48.4, zabs=0.8301, logNHI=18.95, tau_LL=56.4979, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  2     0.01  26      1 14.35
  2      0.1  25      1 12.31
  1     0.02  12      1 12.54
  3     0.04  13      1 13.65
  2      0.0  12      2  14.3
<LLSSystem: 10:54:40.98 -00:20:48.4, zabs=0.9514, logNHI=19.28, tau_LL=120.79, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  1     0.07  12      1 12.04
  2     0.08  26      1 13.49
  2      0.0  12      2 13.59
<LLSSystem: 12:15:49.81 -00:34:32.1, zabs=1.5543, logNHI=19.56, tau_LL=230.161, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  2     0.11  26      1 14.35
  2      0.0  12      2 14.25
<LLSSystem: 12:20:37 -00:40:32.4, zabs=0.9746, logNHI=20.2, tau_LL=1004.69, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  2     0.01  26      1 14.35
  1     0.05  12      1  12.1
  3     0.12  13      1 12.68
  2      0.0  12      2 14.37
<LLSSystem: 12:28:36.8 +10:18:41.7, zabs=0.9376, logNHI=19.41, tau_LL=162.942, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  1     0.05  12      1 12.32
  2     0.02  26      1 14.55
  2      0.0  12      2 14.36
<LLSSystem: 13:30:07.7 -20:56:16.4, zabs=0.8526, logNHI=19.4, tau_LL=159.233, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  2     0.07  26      1 13.76
  1     0.09  12      1 12.37
  3     0.15  13      1 12.52
  2      0.0  12      2 14.12
<LLSSystem: 14:36:45.03 -00:51:50.6, zabs=0.7377, logNHI=20.08, tau_LL=762.135, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  2     0.01  20      1 12.79
  2     0.03  25      1 13.05
  1      0.0  12      2  12.9
  2     0.02  26      1 14.92
  2      0.0  12      2 14.26
<LLSSystem: 14:55:08.14 -00:45:07.5, zabs=1.0929, logNHI=20.08, tau_LL=762.135, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  2     0.17  24      1 12.75
  2      0.1  25      1  12.2
  2      0.0  13      2 13.71
  3     0.01  13      1 13.67
  2     0.12  14      1 14.84
  1     0.02  12      1 12.51
  2      0.0  12      2 14.45
  2     0.02  26      1 14.61

reload(llit)
nestor08 = llit.nestor08()
print(nestor08)
nestor08._ionN

<LLSSystem: 21:51:45.8304 +21:30:13.5, zabs=1.0023, logNHI=19.3, tau_LL=126.483, [Z/H]=0 dex>

ion	Z	sig_logN	flag_N	logN
int64	int64	float64	int64	float64
2	24	0.0	3	12.59
2	30	0.0	3	12.13

reload(llit)
meiring09 = llit.meiring09()
for imeiring09 in meiring09:
    print(imeiring09)
    print(imeiring09._ionN)

<LLSSystem: 00:05:20.21 +05:24:10.8, zabs=0.8514, logNHI=19.08, tau_LL=76.2135, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  2     0.02  26      1 13.75
  1     0.04  12      1 12.24
  3     0.06  13      1 13.13
  2      0.0  12      2 14.13
<LLSSystem: 00:12:10.89 -01:22:07.5, zabs=1.3862, logNHI=20.26, tau_LL=1153.54, [Z/H]=0 dex>
ion  Z  sig_logN flag_N  logN
--- --- -------- ------ -----
  2  13      0.0      2 13.07
  3  13     0.04      1 12.83
  2  14     0.04      1 14.45
  1  12     0.05      1 11.75
  2  12      0.0      2 13.81
  2  26     0.01      1 14.25
<LLSSystem: 00:21:27.88 +01:04:20.1, zabs=1.3259, logNHI=20.04, tau_LL=695.076, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  2     0.04  26      1 14.68
  2      0.0  14      2 14.86
  1     0.06  12      1 12.26
  2      0.0  13      2 13.68
  2      0.0  12      2  14.5
<LLSSystem: 04:27:07.32 -13:02:53.6, zabs=1.408, logNHI=19.04, tau_LL=69.5076, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  2     0.04  14      1 13.56
  2     0.02  26      1 13.33
  2     0.03  13      1 12.21
  2      0.0  12      2 13.25
<LLSSystem: 16:31:45.24 +11:56:02.9, zabs=0.9004, logNHI=19.7, tau_LL=317.711, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  2      0.1  20      1 12.22
  1     0.05  12      1 12.44
  2     0.03  26      1 14.17
  2      0.0  12      2 14.04
<LLSSystem: 20:51:45.87 +19:50:06.3, zabs=1.1157, logNHI=20, tau_LL=633.916, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  2      0.1  24      1 13.08
  2     0.04  25      1 13.24
  2      0.0  13      2 13.77
  3     0.02  13      1 13.52
  2     0.12  14      1 15.31
  1     0.02  12      1 12.67
  2     0.04  20      1 12.59
  2      0.0  12      2 14.44
  2     0.02  26      1  15.0
<LLSSystem: 23:52:53.51 -00:28:51.3, zabs=0.873, logNHI=19.18, tau_LL=95.9471, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  1     0.14  12      1 11.84
  2     0.02  26      1 13.47
  2      0.0  12      2 14.05
<LLSSystem: 23:52:53.51 -00:28:51.3, zabs=1.0318, logNHI=19.81, tau_LL=409.291, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  2     0.26  24      1 12.94
  3     0.05  13      1 13.41
  2     0.06  14      1 15.49
  1     0.03  12      1  12.6
  2      0.0  12      2 14.58
  2     0.01  26      1 14.88
<LLSSystem: 23:52:53.51 -00:28:51.3, zabs=1.2467, logNHI=19.6, tau_LL=252.367, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  2     0.09  26      1 14.19
  3     0.03  13      1 13.43
  1     0.07  12      1 12.32
  2     0.02  13      1 13.42
  2      0.0  12      2 14.39

reload(llit)
dessauges09 = llit.dessauges09()
for ills in dessauges09:
    print(ills)
    print(ills._ionN)

<LLSSystem: 00:12:10.9 -01:22:08, zabs=1.3861, logNHI=20.26, tau_LL=1153.54, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  2     0.04  26      1 14.32
  2      0.0  30      3 10.87
<LLSSystem: 00:21:33.3 +00:43:00, zabs=0.5203, logNHI=19.54, tau_LL=219.802, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  2     0.05  26      1 13.17
<LLSSystem: 00:21:33.3 +00:43:00, zabs=0.9424, logNHI=19.38, tau_LL=152.066, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  2     0.14  26      1 14.62
  2      0.0  30      3  11.6
<LLSSystem: 01:57:33.8 -00:48:24, zabs=1.4157, logNHI=19.9, tau_LL=503.538, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  2     0.08  26      1 14.57
  2     0.11  30      1  12.1
<LLSSystem: 02:18:57.3 +08:17:28, zabs=1.7687, logNHI=20.2, tau_LL=1004.69, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  2      0.1  26      1 14.48
  2     0.16  30      1 12.02
<LLSSystem: 03:54:05.6 -27:24:20, zabs=1.4054, logNHI=20.18, tau_LL=959.471, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  2     0.15  26      1  15.1
  2     0.15  30      1 12.86
<LLSSystem: 04:27:07.3 -13:02:54, zabs=1.408, logNHI=19.04, tau_LL=69.5076, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  2     0.04  26      1 13.45
  2      0.0  30      3 10.83
<LLSSystem: 10:09:30.5 -00:26:18, zabs=0.8428, logNHI=20.2, tau_LL=1004.69, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  2     0.06  26      1 14.48
  2      0.0  30      3 11.42
<LLSSystem: 10:09:30.5 -00:26:18, zabs=0.8865, logNHI=19.48, tau_LL=191.44, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  2     0.09  26      1 14.37
  2     0.15  30      1 12.35
<LLSSystem: 10:28:37.1 -01:00:28, zabs=0.6321, logNHI=19.95, tau_LL=564.979, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  2     0.08  26      1 15.06
  2      0.0  30      3 12.38
<LLSSystem: 10:28:37.1 -01:00:28, zabs=0.7089, logNHI=20.04, tau_LL=695.076, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  2     0.07  26      1  15.1
  2      0.0  30      3 12.49
<LLSSystem: 10:39:21.9 -27:19:16, zabs=2.1395, logNHI=19.6, tau_LL=252.367, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  2      0.1  26      1  14.7
  2      0.1  30      1 12.18
<LLSSystem: 10:54:41 -00:20:48, zabs=0.9513, logNHI=19.28, tau_LL=120.79, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  2     0.02  26      1 13.71
  2      0.0  30      3 11.25
<LLSSystem: 13:30:07.8 -20:56:17, zabs=0.8514, logNHI=19.4, tau_LL=159.233, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  2     0.04  26      1  13.9
  2      0.0  30      3 11.57
<LLSSystem: 15:25:10.6 +00:26:33, zabs=0.5674, logNHI=19.78, tau_LL=381.972, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  2      0.1  26      1 14.19
<LLSSystem: 20:51:12.7 +19:50:07, zabs=1.1161, logNHI=20, tau_LL=633.916, [Z/H]=0 dex>
ion  Z  sig_logN flag_N  logN
--- --- -------- ------ -----
  2  26      0.0      2 15.22
  2  30     0.09      1 12.96
<LLSSystem: 23:52:53.5 -00:28:52, zabs=0.873, logNHI=19.18, tau_LL=95.9471, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  2     0.11  26      1  13.5
  2      0.0  30      3 12.03
<LLSSystem: 23:52:53.5 -00:28:52, zabs=1.0318, logNHI=19.81, tau_LL=409.291, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  2     0.14  26      1 14.96
  2      0.0  30      3 11.94
<LLSSystem: 23:52:53.5 -00:28:52, zabs=1.2468, logNHI=19.6, tau_LL=252.367, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
  2     0.24  26      1 14.28
  2      0.0  30      3  11.1

reload(llit)
tumlinson11 = llit.tumlinson11()
print(tumlinson11)
tumlinson11._ionN

<LLSSystem: 10:09:02.06 +07:13:43.8, zabs=0.3558, logNHI=18.4, tau_LL=15.9233, [Z/H]=0 dex>

logN	ion	sig_logN	Z	flag_N
float64	int64	float64	int64	int64
14.770236614	3	0.0	6	2
14.9524118892	2	0.188792267532	6	1
13.9906616703	2	0.0196862138948	12	1
14.8	2	0.0	16	3
14.0	4	0.1	16	1
13.7	1	0.0	7	3
14.153901891	2	0.142347356383	14	1
14.2089659478	3	0.0	14	2
11.3	1	0.0	26	3
11.7	1	0.0	14	3
12.0806287223	1	0.0336401521748	12	1
13.6	5	0.0	7	3
14.4	1	0.0	6	3
14.6243968801	3	0.0623370581385	16	1
13.9275410226	2	0.0242723547038	26	1
11.753901891	2	0.0835967450643	20	1
14.3996934555	2	0.0640512848413	7	1
14.7806287223	1	0.138387739685	8	1
14.553901891	3	0.0711736781914	26	1
15.0899365116	3	0.0513060596102	7	1
11.5	2	0.0	22	3
14.941396905	6	0.0517850930501	8	1

reload(llit)
kacprzak12 = llit.kacprzak12()
print(kacprzak12)
kacprzak12._ionN

<LLSSystem: 13:19:56.2209 +27:28:08.271, zabs=1.0023, logNHI=18.3, tau_LL=12.6483, [Z/H]=0 dex>

ion	Z	sig_logN	flag_N	logN
int64	int64	float64	int64	float64
2	14	0.11	1	13.16
1	12	0.06	1	11.54
4	6	0.05	1	14.41
2	12	0.07	1	13.11
4	14	0.0	3	12.4
2	6	0.0	2	13.39
1	14	0.0	3	11.8
6	8	0.05	1	14.49

reload(llit)
battisti12 = llit.battisti12()
for ills in battisti12:
    print(ills)
    print(ills._ionN)

<LLSSystem: 09:25:54.7 +40:04:14.1, zabs=0.2477, logNHI=19.5, tau_LL=200.462, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
    0.0  15      3  13.5
   0.06  14      1 14.62
    0.0   7      2 14.95
    0.0  14      2 13.74
    0.0  16      3 14.72
   0.09   8      1 15.95
    0.0   6      2 14.17
   0.04   7      1 14.75
    0.0  26      3 14.23
   0.11  14      1 13.54
    0.0  28      3 14.41
    0.0   6      2 15.18
   0.09  26      1 14.22
<LLSSystem: 09:28:37.98 +60:25:21, zabs=0.1538, logNHI=19.3, tau_LL=126.483, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
    0.0   6      2  14.1
    0.0  15      3 14.17
    0.0  14      2 14.39
    0.0   7      2 14.85
    0.0  14      2 13.77
    0.0  16      3 14.65
    0.0   8      2 15.08
   0.06  12      1  12.7
    0.0  22      3 11.94
   0.06  20      1 12.81
   0.09   7      1  14.1
   0.11  26      1 14.59
    0.0  12      2 13.99
   0.12  14      1 13.86
    0.0  28      3 13.67
    0.0   6      2 14.91
   0.08  26      1  14.9
<LLSSystem: 10:01:02.55 +59:44:14.3, zabs=0.3035, logNHI=19.3, tau_LL=126.483, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
   0.07  15      1 12.81
   0.03  14      1 14.73
    0.0   7      2 14.95
    0.0  14      2  14.0
    0.0  16      3 14.53
   0.09  26      1 14.14
   0.02   8      1 15.64
    0.0   6      2 14.52
   0.17   7      1 13.65
   0.04  26      1  14.3
    0.0  28      3 14.23
    0.0   6      2 15.06
   0.05   8      1 14.34
<LLSSystem: 14:35:11.53 +36:04:37.2, zabs=0.2026, logNHI=19.8, tau_LL=399.974, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
    0.0  15      3 12.79
    0.0  14      2 14.11
    0.0  14      2 13.41
   0.12  16      1  14.6
    0.0   8      2 15.58
    0.0   6      2 14.33
   0.14   7      1  14.6
    0.0  26      3 13.69
   0.13  14      1  13.2
    0.0  28      3 13.99
    0.0   6      2 14.52
   0.08  26      1  14.2
<LLSSystem: 15:53:04.92 +35:48:28.6, zabs=0.083, logNHI=19.5, tau_LL=200.462, [Z/H]=0 dex>
ion sig_logN  Z  flag_N  logN
--- -------- --- ------ -----
   0.08   6      1 13.99
   0.05  14      1 14.22
   0.07   7      1 14.16
    0.0  14      2  13.3
    0.0  16      3 14.24
    0.0   8      2 14.56
    0.0   7      3 13.74
   0.08  14      1 13.59
    0.0  28      3 13.92
    0.0   6      2 14.35
   0.07  26      1 14.01

Load them All¶

lls_lit = llit.load_lls_lit()
lls_lit

No error for N I
No error for O I
No error for O I
WARNING: Using 1393.7550 Angstrom for your input 1393.7600 Angstrom
WARNING: Using 1402.7700 Angstrom for your input 1402.7730 Angstrom
WARNING: Using 1012.4950 Angstrom for your input 1012.5010 Angstrom
WARNING: Using 1190.2030 Angstrom for your input 1190.1910 Angstrom

<IGMSurvey: nsys=58, type=LLS, ref=Zon04,Jen05,Tri05,Prx06a,Prx06b,Mei06,Mei07,Mei08,Nes08,Mei09,DZ09,Tum11,Kcz12,Bat12>

lls_lit.ref

u'Zon04,Jen05,Tri05,Prx06a,Prx06b,Mei06,Mei07,Mei08,Nes08,Mei09,DZ09,Tum11,Kcz12,Bat12'

Plot¶

# NHI
p_NHI = figure(plot_width=400, plot_height=400, title='Lit-LLS NHI')#,background_fill="#E8DDCB")
hist, edges = np.histogram(lls_lit.NHI, range=(17.,20.4), density=True, bins=20)
p_NHI.quad(top=hist, bottom=0, left=edges[:-1], right=edges[1:],fill_color='blue')
p_NHI.xaxis.axis_label = 'N_HI'
# z
p_z = figure(plot_width=400, plot_height=400, title='Lit-LLS z')#,background_fill="#E8DDCB")
hist, edges = np.histogram(lls_lit.zabs, range=(0., 4.5), bins=20)
p_z.quad(top=hist, bottom=0, left=edges[:-1], right=edges[1:],fill_color='red')
p_z.xaxis.axis_label = 'z_LLS'
# Show
show(hplot(p_NHI,p_z))

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Examples for LLSSurvey (v1.5)¶

LLS Tree (JXP) – Likely to Deprecate¶

HD-LLS (Prochaska+15, ApJS, 221, 22)¶

Simple Init¶

With Systems (takes ~2 min)¶

Spectra¶

SDSS LLS (Prochaska+10, ApJ, 718, 391)¶

All¶

Stat¶

Sky Map¶

\(z \sim 2.5\) HST (O’Meara et al. 2013, ApJ, 765, 137)¶

ACS¶

WFC3¶

Combined¶

\(z \sim 3\) MagE (Fumagalli et al. 2013, ApJ, 775, 78)¶

Load¶

g(z) plot¶

Literature¶

Load them All¶

Plot¶