Extracting Spectra using get_spectra

This notebook demonstrates how to grab 1D aperture summed HETDEX spectra for an input of ID, RA and DEC using the Extract Class API from hetdex_api. This can be done interactively using get_spectra from hte hetdex_tools.get_spec module.

Examples of what you might like to do with the spectra afterwards is shown later. The output is stored in an astropy table of spectra. For every HETDEX observation where spectra is found, a spectra is given. It is up to the user to combine the spectra afterwards.

import matplotlib.pyplot as plt
import numpy as np

import astropy.units as u
from astropy.io import fits
from astropy.coordinates import SkyCoord
from astropy.table import Table, join, vstack

from hetdex_tools.get_spec import get_spectra
%matplotlib inline

Getting all spectra at a specified RA/DEC. This will search through all shots in HDR3

If a shotid is not specified the program will search for any shot within the data release that overlaps within an 11 arcmin radius of the input coordinates. Because of the non-contiguous VIRUS footprint, there is no guarantee the aperture defined by the input ra/dec/rad will contain enough fibers to do a measurement. The aperture radius is 3.5” by default or can be specified with the –rad argument.

Open a catalog of IDs, RAs, DECs. We’ll use the public AGN catalog as an example.

url_to_agn1 = "http://web.corral.tacc.utexas.edu/hetdex/HETDEX/catalogs/agn_catalog_v1.0/hetdex_agn.fits"
# we'll just do the first 20 as an example. 
input_cat = Table.read(url_to_agn1)
# select a small RA range of the catalog as an example
sel_slice = (input_cat['ra']>12) * (input_cat['ra']<14) * (input_cat['field']=='dex-fall')
input_cat = input_cat[sel_slice]

get_spectra() requires an astropy coordinates object list as an input.

input_coords = SkyCoord(ra=input_cat['ra'], dec=input_cat['dec'])

Note that get_spectra will automatically use upto 32 processors to efficiently extract spectra from the fiber database. If you do not require parallel processing then set multiprocessing=False in the function call. If you would like to see logging info, set loglevel=’INFO’. Set loglevel=’WARNING’ or loglevel=’ERROR’ for unneccessary logging output.

sources = get_spectra(input_coords, ID=input_cat['agnid'], loglevel='INFO', survey='hdr4', apply_mask=True)
[INFO - 2024-04-11 15:53:44,425] Finding shots of interest
[INFO - 2024-04-11 15:53:50,473] Number of shots of interest: 56
[INFO - 2024-04-11 15:53:50,475] Extracting 184 sources
[INFO - 2024-04-11 15:53:50,787] Working on shot: 20171017007
[INFO - 2024-04-11 15:53:50,806] Working on shot: 20171024008
[INFO - 2024-04-11 15:53:50,819] Working on shot: 20181106008
[INFO - 2024-04-11 15:53:50,839] Working on shot: 20171120007
[INFO - 2024-04-11 15:53:50,841] Working on shot: 20171025013
[INFO - 2024-04-11 15:53:50,842] Working on shot: 20171213010
[INFO - 2024-04-11 15:53:50,843] Working on shot: 20171115010
[INFO - 2024-04-11 15:53:50,843] Working on shot: 20171019010
[INFO - 2024-04-11 15:53:50,843] Working on shot: 20181130012
[INFO - 2024-04-11 15:53:50,844] Working on shot: 20181010025
[INFO - 2024-04-11 15:53:50,845] Working on shot: 20180820018
[INFO - 2024-04-11 15:53:50,845] Working on shot: 20181104012
[INFO - 2024-04-11 15:53:50,847] Working on shot: 20180810009
[INFO - 2024-04-11 15:53:50,848] Working on shot: 20190730012
[INFO - 2024-04-11 15:53:50,847] Working on shot: 20181227003
[INFO - 2024-04-11 15:53:50,847] Working on shot: 20181102008
[INFO - 2024-04-11 15:53:50,847] Working on shot: 20181102013
[INFO - 2024-04-11 15:53:50,847] Working on shot: 20181014010
[INFO - 2024-04-11 15:53:50,849] Working on shot: 20180113006
[INFO - 2024-04-11 15:53:50,850] Working on shot: 20171121007
[INFO - 2024-04-11 15:53:50,849] Working on shot: 20171124010
[INFO - 2024-04-11 15:53:50,850] Working on shot: 20181109009
[INFO - 2024-04-11 15:53:50,850] Working on shot: 20181205015
[INFO - 2024-04-11 15:53:50,850] Working on shot: 20171018015
[INFO - 2024-04-11 15:53:50,851] Working on shot: 20190927019
[INFO - 2024-04-11 15:53:50,851] Working on shot: 20181102009
[INFO - 2024-04-11 15:53:50,851] Working on shot: 20171023013
[INFO - 2024-04-11 15:53:50,852] Working on shot: 20181128009
[INFO - 2024-04-11 15:53:50,854] Working on shot: 20181011008
[INFO - 2024-04-11 15:53:50,857] Working on shot: 20190923013
[INFO - 2024-04-11 15:53:50,853] Working on shot: 20190810015
[INFO - 2024-04-11 15:53:50,853] Working on shot: 20190902013
[INFO - 2024-04-11 15:53:52,220] Extracting 4294
[INFO - 2024-04-11 15:53:52,278] Extracting 161
[INFO - 2024-04-11 15:53:52,352] Extracting 2339
[INFO - 2024-04-11 15:53:52,479] Extracting 5156
[INFO - 2024-04-11 15:53:52,487] Extracting 4506
[INFO - 2024-04-11 15:53:52,543] Extracting 1736
[INFO - 2024-04-11 15:53:52,617] Extracting 2686
[INFO - 2024-04-11 15:53:52,659] Extracting 5300
[INFO - 2024-04-11 15:53:52,930] Extracting 3435
[INFO - 2024-04-11 15:53:53,021] Extracting 1754
[INFO - 2024-04-11 15:53:53,106] Extracting 2029
[INFO - 2024-04-11 15:53:53,150] Extracting 1672
[INFO - 2024-04-11 15:53:53,209] Extracting 3658
[INFO - 2024-04-11 15:53:53,236] Extracting 1695
[INFO - 2024-04-11 15:53:53,300] Extracting 3541
[INFO - 2024-04-11 15:53:53,343] Extracting 3482
[INFO - 2024-04-11 15:53:53,457] Extracting 2787
[INFO - 2024-04-11 15:53:53,463] Extracting 1968
[INFO - 2024-04-11 15:53:53,519] Extracting 4409
[INFO - 2024-04-11 15:53:53,564] Extracting 4586
[INFO - 2024-04-11 15:53:53,653] Extracting 5284
[INFO - 2024-04-11 15:53:53,795] Extracting 4070
[INFO - 2024-04-11 15:53:53,864] Extracting 2047
[INFO - 2024-04-11 15:53:54,027] Extracting 3881
[INFO - 2024-04-11 15:53:54,039] Extracting 2263
[INFO - 2024-04-11 15:53:54,260] Extracting 4811
[INFO - 2024-04-11 15:53:54,447] Extracting 4429
[INFO - 2024-04-11 15:53:54,557] Extracting 4536
[INFO - 2024-04-11 15:53:54,638] Extracting 4615
[INFO - 2024-04-11 15:53:54,858] Extracting 5036
[INFO - 2024-04-11 15:53:55,354] Extracting 4727
[INFO - 2024-04-11 15:53:55,962] Extracting 5296
[INFO - 2024-04-11 15:53:56,254] Working on shot: 20190927023
[INFO - 2024-04-11 15:53:56,257] Working on shot: 20190928016
[INFO - 2024-04-11 15:53:56,279] Working on shot: 20191006024
[INFO - 2024-04-11 15:53:56,278] Working on shot: 20190929013
[INFO - 2024-04-11 15:53:56,281] Working on shot: 20191024018
[INFO - 2024-04-11 15:53:56,284] Working on shot: 20191022016
[INFO - 2024-04-11 15:53:56,292] Working on shot: 20191027015
[INFO - 2024-04-11 15:53:56,291] Working on shot: 20191026016
[INFO - 2024-04-11 15:53:56,315] Working on shot: 20191027016
[INFO - 2024-04-11 15:53:56,316] Working on shot: 20191029016
[INFO - 2024-04-11 15:53:56,317] Working on shot: 20191028013
[INFO - 2024-04-11 15:53:56,327] Working on shot: 20191119020
[INFO - 2024-04-11 15:53:56,328] Working on shot: 20191119019
[INFO - 2024-04-11 15:53:56,350] Working on shot: 20191122015
[INFO - 2024-04-11 15:53:56,352] Working on shot: 20191201016
[INFO - 2024-04-11 15:53:56,365] Working on shot: 20191227010
[INFO - 2024-04-11 15:53:56,367] Working on shot: 20191221012
[INFO - 2024-04-11 15:53:56,369] Working on shot: 20191217014
[INFO - 2024-04-11 15:53:56,401] Working on shot: 20211108013
[INFO - 2024-04-11 15:53:56,401] Working on shot: 20220926014
[INFO - 2024-04-11 15:53:56,402] Working on shot: 20200916016
[INFO - 2024-04-11 15:53:56,403] Working on shot: 20221023017
[INFO - 2024-04-11 15:53:56,403] Working on shot: 20220926018
[INFO - 2024-04-11 15:53:56,403] Working on shot: 20221021013
[INFO - 2024-04-11 15:53:58,532] Extracting 2182
[INFO - 2024-04-11 15:53:58,834] Extracting 1683
[INFO - 2024-04-11 15:53:58,857] Extracting 1849
[INFO - 2024-04-11 15:53:58,930] Extracting 712
[INFO - 2024-04-11 15:53:58,947] Extracting 2894
[INFO - 2024-04-11 15:53:58,951] Extracting 1849
[INFO - 2024-04-11 15:53:59,046] Extracting 2592
[INFO - 2024-04-11 15:53:59,222] Extracting 2674
[INFO - 2024-04-11 15:53:59,256] Extracting 3206
[INFO - 2024-04-11 15:53:59,265] Extracting 223
[INFO - 2024-04-11 15:53:59,374] Extracting 1
[INFO - 2024-04-11 15:53:59,376] Extracting 5373
[INFO - 2024-04-11 15:53:59,380] Extracting 2966
[INFO - 2024-04-11 15:53:59,427] Extracting 1789
[INFO - 2024-04-11 15:53:59,576] Extracting 2192
[INFO - 2024-04-11 15:53:59,592] Extracting 2197
[INFO - 2024-04-11 15:53:59,637] Extracting 1354
[INFO - 2024-04-11 15:53:59,712] Extracting 3384
[INFO - 2024-04-11 15:53:59,744] Extracting 1931
[INFO - 2024-04-11 15:53:59,772] Extracting 1931
[INFO - 2024-04-11 15:53:59,877] Extracting 385
[INFO - 2024-04-11 15:53:59,978] Extracting 3440
[INFO - 2024-04-11 15:54:00,014] Extracting 2975
[INFO - 2024-04-11 15:54:00,039] Extracting 3392
[INFO - 2024-04-11 15:54:00,053] Extracting 2318
[INFO - 2024-04-11 15:54:00,265] Extracting 176
[INFO - 2024-04-11 15:54:00,283] Extracting 4362
[INFO - 2024-04-11 15:54:00,438] Extracting 3324
[INFO - 2024-04-11 15:54:00,518] Extracting 3025
[INFO - 2024-04-11 15:54:00,555] Extracting 4878
[INFO - 2024-04-11 15:54:00,619] Extracting 3025
[INFO - 2024-04-11 15:54:00,625] Extracting 3567
[INFO - 2024-04-11 15:54:00,662] Extracting 3106
[INFO - 2024-04-11 15:54:00,761] Extracting 4327
[INFO - 2024-04-11 15:54:00,848] Extracting 1932
[INFO - 2024-04-11 15:54:00,918] Extracting 4911
[INFO - 2024-04-11 15:54:00,930] Extracting 2963
[INFO - 2024-04-11 15:54:01,217] Extracting 4499
[INFO - 2024-04-11 15:54:01,264] Extracting 4499
[INFO - 2024-04-11 15:54:01,304] Extracting 5171
[INFO - 2024-04-11 15:54:01,366] Extracting 5053
[INFO - 2024-04-11 15:54:01,409] Extracting 3604
[INFO - 2024-04-11 15:54:01,749] Extracting 5280
[INFO - 2024-04-11 15:54:01,790] Extracting 2774
[INFO - 2024-04-11 15:54:01,796] Extracting 5280
[INFO - 2024-04-11 15:54:02,504] Extracting 2797
[INFO - 2024-04-11 15:54:03,076] Extracting 4608
[INFO - 2024-04-11 15:54:03,312] Extraction of sources completed in 0.21 minutes.
[INFO - 2024-04-11 15:54:03,589] Retrieved 79 spectra.
sources
Table length=79
IDshotidwavelengthspecspec_errapcorflaggal_flagamp_flagmeteor_flag
Angstrom1e-17 erg / (Angstrom s cm2)1e-17 erg / (Angstrom s cm2)
int64int64float64[1036]float64[1036]float64[1036]float64[1036]int64int64int64int64
4506201710230133470.0 .. 5540.013.070671318213519 .. 4.6269559440166337.696168523996925 .. 1.7739980360162930.936494814265974 .. 0.94326803412873641111
161201710240083470.0 .. 5540.0-2.2362675197463826 .. 0.534260220905264512.766469896041446 .. 2.87239096878054530.4681495581973753 .. 0.481083012775600951111
5156201710250133470.0 .. 5540.02.9709237604638483 .. 1.43355680771653864.04934908080845 .. 1.54365236206642150.9389218990553002 .. 0.94273265749773381111
2339201710190103470.0 .. 5540.03.096066603847864 .. 1.63898904409068569.264010238795601 .. 3.0450805877190360.8847841188994388 .. 0.88665372509979691111
4294201712130103470.0 .. 5540.03.2617290879947993 .. 1.00180505692903846.327588169006198 .. 1.38316807776725750.9253019904255423 .. 0.93588133350798091111
1736201710170073470.0 .. 5540.00.7542228470487529 .. 0.381295109375804244.632006152444206 .. 1.41358850336522930.9272322663657255 .. 0.93291755212847451111
5300201711240103470.0 .. 5540.01.398736070833743 .. 1.57502597885172583.346292424569998 .. 1.50427767224574560.9391887062625848 .. 0.94700664421277841111
2686201801130063470.0 .. 5540.06.4978516592276 .. 2.29945911829866927.36751844172225 .. 1.6570700694427310.9136096100086114 .. 0.92765026748514191111
3435201808200183470.0 .. 5540.06.3492345274818875 .. 1.81164657994140577.302624763152205 .. 3.6126603731130710.7552038657678171 .. 0.70902761882089881111
..............................
4499201910280133470.0 .. 5540.05.621542435321214 .. 1.81177881894084085.480576582696911 .. 1.52630668632033540.9280159223735657 .. 0.93375973720959131111
4499201910260163470.0 .. 5540.05.799225240155176 .. 1.8533298762338095.360090203802762 .. 1.49898692280279970.9155341038378271 .. 0.92940476856421331111
3604201911190193470.0 .. 5540.01.2116481663085668 .. 0.66278606677075743.5153370029336055 .. 1.48807482704100140.9266626713464705 .. 0.92945158583304211111
5171201910290163470.0 .. 5540.07.643632501449629 .. 3.4942876917314897.007213922561731 .. 1.60193209007581180.9327510790766259 .. 0.93888673615786331111
5053201910220163470.0 .. 5540.05.14897688550996 .. 2.3906202748582447.280924255948644 .. 1.86306439198333940.8921537982298235 .. 0.90995373119665011111
5280201910280133470.0 .. 5540.012.054409583198774 .. 6.2606782065725317.175601421149439 .. 2.0286944196141470.9297243124537918 .. 0.93816377478473881111
5280201910260163470.0 .. 5540.012.39104198030523 .. 6.2680205875967386.494806440859136 .. 1.85190634840029690.9210991427696392 .. 0.92994346634771641111
2774201909270233470.0 .. 5540.00.2283586365560561 .. 0.07043336848732813.419658537340928 .. 1.26240331214978750.9296370566788175 .. 0.94056064425009891111
2797201909270233470.0 .. 5540.00.1430703166257021 .. 0.164090457611572263.5644179551670705 .. 1.14898259178337340.9250880430616912 .. 0.93332820869441471111
4608201909270233470.0 .. 5540.05.03265689512644 .. 0.92466958726420844.228655958241803 .. 1.38176123733369560.9318305027502478 .. 0.93486609791091671111

get_spectra() options

There are a few options to consider when running get_spectra():

help(get_spectra)
Help on function get_spectra in module hetdex_tools.get_spec:

get_spectra(coords, ID=None, rad=3.5, multiprocess=True, shotid=None, survey='hdr4', tpmin=0.08, keep_bad_shots=False, ffsky=False, ffsky_rescor=False, fiberweights=False, return_fiber_info=False, loglevel='INFO', apply_update=True, fiber_flux_offset=None, apply_mask=False)
    Function to retrieve PSF-weighted, ADR and aperture corrected
    spectral extractions of HETDEX fibers. It will search all shots
    within a specific HETDEX Data Release and return a table of
    spectra for each extraction per shot in which more than 7 fibers
    are found in order to generate an extracted spectrum.
    
    Parameters
    ----------
    coords
        list astropy coordinates
    ID
        list of ID names (must be same length as coords). Will
        generate a running index if no ID is given
    rad
        radius of circular aperture to be extracted in arcsec.
        Default is 3.5
    multiprocess: bool
        boolean flag to use multiprocessing. This will greatly
        speed up its operation as it will extract on 32 shots at
        time. But only use this when on a compute node. Use
        idev, a jupyter notebook, or submit the job as a single
        python slurm job. Default is True
    shotid: int
        list of integer shotids to do extractions on. By default
        it will search the whole survey except for shots located
        in the bad.shotlist file
    survey: str
        Survey you want to access. User note that HDR1 extractions
        are much slower compared to HDR2.
    tpmin: float
        Include only shots above tpmin. Default is 0.08
    ffsky: bool
        Use the full frame 2D sky subtraction model. Default is
        to use the local sky subtracted, flux calibrated fibers.
    fiberweights: bool
        Boolean flag to include fiber_weights tuple in source
        dictionary. This is used in Elixer, but is slow
        when used on large source lists.
    fiber_info: bool
        returns the fiber_info and weights of the fibers used
        in the extraction
    keep_bad_shots: bool
        Set this to True if you want to include fibers from bad
        shots. This is dangerous as it can include fibers with
        bad astrometry, bad calibration. Default is False.
    loglevel: str
        Level to set logging. Options are ERROR, WARNING, INFO,
        DEBUG. Defaults to INFO
    apply_update: bool
        Apply relevent HDR calibration updates. Default is True.
    fiber_flux_offset: 1036 array
        array of values in units of 10**-17 ergs/s/cm2/AA to add
        to each fiber spectrum used in the extraction. Defaults
        to None
    ffsky_rescor: bool                                                                                       
        Flag to use updated spectra for ffsky with residual correction applied.                              
        Corrected fiber arrays generated by Maja Lujan Niemeyer 2023-12-14.                                  
        This is a post-HDR4 correction. Default is False  
    apply_mask: bool
        Apply HETDEX fiber mask model. This will mask all fibers contributing 
        to the spectral extraction before summation. Masked in place as NaNs
    
    Returns
    -------
    sources
        an astropy table object of source spectra for all input
        coords/ID that have spectra in the survey shots. There
        is one row per source ID/shotid observation.

Reading in the output - astropy FITS files

Join your input and output table so you can match up any properties you like

output_table = join(input_cat, sources, keys_left=['agnid'], keys_right=['ID'])
output_table
Table length=79
agnidradeczz_erzflagfieldnshotsdetectid_bestra_bestdec_bestroffnmemalphaalpha_erfpl0fpl0_erslopeslope_erinterceptintercept_erL1350L1350_erL1450L1450_erL3000L3000_erL5100L5100_erfwhm_LyAfwhm_LyA_erew_LyAew_LyA_erflux_LyAflux_LyA_ercont_LyAcont_LyA_ersnr_LyAsnr_LyA_erchi2_LyAchi2_LyA_erfwhm_NVfwhm_NV_erew_NVew_NV_erflux_NVflux_NV_ercont_NVcont_NV_erfwhm_SiOfwhm_SiO_erew_SiOew_SiO_erflux_SiOflux_SiO_ercont_SiOcont_SiO_ersnr_SiOsnr_SiO_erchi2_SiOchi2_SiO_erfwhm_CIVfwhm_CIV_erew_CIVew_CIV_erflux_CIVflux_CIV_ercont_CIVcont_CIV_ersnr_CIVsnr_CIV_erchi2_CIVchi2_CIV_erfwhm_HeIIfwhm_HeII_erew_HeIIew_HeII_erflux_HeIIflux_HeII_ercont_HeIIcont_HeII_ersnr_HeIIsnr_HeII_erchi2_HeIIchi2_HeII_erfwhm_CIIIfwhm_CIII_erew_CIIIew_CIII_erflux_CIIIflux_CIII_ercont_CIIIcont_CIII_ersnr_CIIIsnr_CIII_erchi2_CIIIchi2_CIII_erfwhm_MgIIfwhm_MgII_erew_MgIIew_MgII_erflux_MgIIflux_MgII_ercont_MgIIcont_MgII_ersnr_MgIIsnr_MgII_erchi2_MgIIchi2_MgII_erfwhm_OIIfwhm_OII_erew_OIIew_OII_erflux_OIIflux_OII_ercont_OIIcont_OII_ersnr_OIIsnr_OII_erchi2_OIIchi2_OII_erfwhm_OVIfwhm_OVI_erew_OVIew_OVI_erflux_OVIflux_OVI_ercont_OVIcont_OVI_ersnr_OVIsnr_OVI_erchi2_OVIchi2_OVI_erfiberidr_aperr_aper_err_radiusr_depthr_catg_aperg_aper_erg_radiusg_depthg_catu_aperu_aper_eru_radiusu_depthu_catrsep_dr14qid_dr14qz_dr14qrsep_dr16plate_dr16fiber_dr16mjd_dr16z_dr16sflagapcor_1IDshotidwavelengthspecspec_errapcor_2flaggal_flagamp_flagmeteor_flag
degdegdegdegarcsec1e+44 erg / s1e+44 erg / s1e+44 erg / s1e+44 erg / s1e+44 erg / s1e+44 erg / s1e+44 erg / s1e+44 erg / skm / skm / sAngstromAngstrom1e-17 erg / (s cm2)1e-17 erg / (s cm2)1e-17 erg / (Angstrom s cm2)1e-17 erg / (Angstrom s cm2)km / skm / sAngstromAngstrom1e-17 erg / (s cm2)1e-17 erg / (s cm2)1e-17 erg / (Angstrom s cm2)1e-17 erg / (Angstrom s cm2)km / skm / sAngstromAngstrom1e-17 erg / (s cm2)1e-17 erg / (s cm2)1e-17 erg / (Angstrom s cm2)1e-17 erg / (Angstrom s cm2)km / skm / sAngstromAngstrom1e-17 erg / (s cm2)1e-17 erg / (s cm2)1e-17 erg / (Angstrom s cm2)1e-17 erg / (Angstrom s cm2)km / skm / sAngstromAngstrom1e-17 erg / (s cm2)1e-17 erg / (s cm2)1e-17 erg / (Angstrom s cm2)1e-17 erg / (Angstrom s cm2)km / skm / sAngstromAngstrom1e-17 erg / (s cm2)1e-17 erg / (s cm2)1e-17 erg / (Angstrom s cm2)1e-17 erg / (Angstrom s cm2)km / skm / sAngstromAngstrom1e-17 erg / (s cm2)1e-17 erg / (s cm2)1e-17 erg / (Angstrom s cm2)1e-17 erg / (Angstrom s cm2)km / skm / sAngstromAngstrom1e-17 erg / (s cm2)1e-17 erg / (s cm2)1e-17 erg / (Angstrom s cm2)1e-17 erg / (Angstrom s cm2)km / skm / sAngstromAngstrom1e-17 erg / (s cm2)1e-17 erg / (s cm2)1e-17 erg / (Angstrom s cm2)1e-17 erg / (Angstrom s cm2)magmagarcsecarcsecmagmagarcsecarcsecmagmagarcsecarcsecarcsecarcsecAngstrom1e-17 erg / (Angstrom s cm2)1e-17 erg / (Angstrom s cm2)
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529613.8659980.0155410.3866e-051dex-fall1210049253513.8659980.0155410.01-0.090960.0119936116.3978980.7370656-0.00011351.22e-053.43480.03960.230.0020.250.0020.480.0010.780.004-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.02861.6672.76142.850.995133.172.9283.110.00618.6210.220.50.039846.3914.3164.20.11512.710.3383.030.0065.6040.1373.050.072-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.020181011008_3_multi_305_034_056_RL_053-99.0-99.0-99.0-99.0?21.00310.00992.239224.7DECAM/SHELA-99.0-99.0-99.0-99.0?221.128424224-55481-08182.173108.55929394552518120.0627385420.9215296201810110083470.0 .. 5540.02.467657317096909 .. 2.09131789501890353.309647084701572 .. 1.265230764651410.9410604678796834 .. 0.93979087595536031111
530012.3464910.03959860.3738e-051dex-fall1210010602912.3465560.0396410.27912-0.258770.01511860316.055771.0405476-0.00019261.46e-052.60920.04780.160.0020.170.0020.290.0010.430.003-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.02076.1166.58558.421.204120.292.3272.060.00710.0820.140.290.033841.8444.2827.60.74914.531.4041.910.0063.2840.1590.830.04-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.020171124010_3_multi_032_094_028_RU_111-99.0-99.0-99.0-99.0?20.41120.01162.241324.7DECAM/SHELA-99.0-99.0-99.0-99.0?87.6234747870-57016-09392.02235823.028408394392518120.1228197210.9135300201711240103470.0 .. 5540.01.398736070833743 .. 1.57502597885172583.346292424569998 .. 1.50427767224574560.9391887062625848 .. 0.94700664421277841111
537313.6922430.7011080.2345e-051dex-fall1210140227713.6922430.7011080.01-2.189950.0045590541375639000.050706564.0-0.01417522.79e-0574.4770.09984.240.0183.890.0151.640.0010.870.002-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0467.7618.4232.430.16450.323.38820.730.0135.0240.1470.570.044-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.0-99.020191027016_1_multi_330_092_075_LL_006-99.0-99.0-99.0-99.0?19.14460.00422.460124.7DECAM/SHELA-99.0-99.0-99.0-99.0?60.3303154224-55481-07963.9950.4018406394616518120.2340315400.8395373201910270163470.0 .. 5540.029.278803571588682 .. 12.37843569947324315.16674411736035 .. 3.23428146984298340.8051758556346719 .. 0.83421832275768031111
for row in output_table[np.arange(0,len(output_table), 10)]:
    plt.figure()
    wave = row['wavelength']
    spec = row['spec']
    spec_err = row['spec_err']
    plt.errorbar(wave, spec, yerr=spec_err)
    plt.xlim(3540, 5500)
    plt.xlabel('wave')
    plt.ylabel('spec')
    plt.title("agnid={} z={:3.2f}".format(row['ID'], row['z']))
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