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- .. doctest-skip-all
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-
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.. _astroquery.eso :
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******************************
@@ -40,12 +38,12 @@ store the password in your operating system. As such you should have to enter yo
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correct password only once, and later be able to use this package for automated
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interaction with the ESO archive.
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- .. code-block :: python
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+ .. doctest-skip ::
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>>> from astroquery.eso import Eso
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>>> eso = Eso()
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>>> # First example: TEST is not a valid username, it will fail
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- >> > eso.login(" TEST" ) # doctest: +SKIP
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+ >>> eso.login(" TEST" )
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TEST, enter your ESO password:
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Authenticating TEST on www.eso.org...
@@ -85,7 +83,7 @@ needs to be edited by adding ``username = ICONDOR`` in the ``[eso]`` section.
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When configured, the username in the ``login() `` method call can be omitted
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as follows:
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- .. code-block :: python
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+ .. doctest-skip ::
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>>> from astroquery.eso import Eso
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>>> eso = Eso()
@@ -107,12 +105,15 @@ authentication example above. The first thing to do is to identify the instrumen
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list of available instrument-specific queries can be obtained with the
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:meth: `~astroquery.eso.EsoClass.list_instruments ` method.
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- .. code-block :: python
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+ .. doctest-remote-data ::
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+
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+ >>> from astroquery.eso import Eso
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+ >>> eso = Eso()
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+ >>> eso.list_instruments()
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+ ['fors1', 'fors2', 'sphere', 'vimos', 'omegacam', 'hawki', 'isaac', 'naco', 'visir',
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+ 'vircam', 'apex', 'giraffe', 'uves', 'xshooter', 'espresso', 'muse', 'crires',
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+ 'kmos', 'sinfoni', 'amber', 'gravity', 'matisse', 'midi', 'pionier', 'wlgsu']
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- >> > eso.list_instruments()
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- [' fors1' , ' fors2' , ' vimos' , ' omegacam' , ' hawki' , ' isaac' , ' naco' , ' visir' , ' vircam' ,
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- ' apex' , ' uves' , ' giraffe' , ' xshooter' , ' muse, ' crires' , ' kmos' , ' sinfoni' ,
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- ' amber' , ' gravity' , ' midi' , ' pionier' ]
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In the example above, 22 instruments are available, they correspond to the instruments listed on
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the following web page: http://archive.eso.org/cms/eso-data/instrument-specific-query-forms.html.
@@ -124,9 +125,9 @@ Once an instrument is chosen, ``midi`` in our case, the query options for that i
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inspected by setting the ``help=True `` keyword of the :meth: `~astroquery.eso.EsoClass.query_instrument `
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method.
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- .. code-block :: python
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+ .. doctest-remote-data ::
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- >> > eso.query_instrument(' midi' , help = True )
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+ >>> eso.query_instrument(' midi' , help = True ) # doctest: +IGNORE_OUTPUT
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List of the column_filters parameters accepted by the midi instrument query.
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The presence of a column in the result table can be controlled if prefixed with a [ ] checkbox.
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The default columns in the result table are shown as already ticked: [x].
@@ -175,39 +176,40 @@ It is now time to query the ``midi`` instrument for datasets. In the following e
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target ``NGC 4151 `` between ``2007-01-01 `` and ``2008-01-01 `` are searched, and the query is configured to
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return the observation date column.
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- .. code-block :: python
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+ .. doctest-remote-data ::
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- >> > table = eso.query_instrument(' midi' , column_filters = {' target' :' NGC 4151' , ' stime' :' 2007-01-01' , ' etime' :' 2008-01-01' }, columns = [' night' ])
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+ >>> table = eso.query_instrument(' midi' , column_filters = {' target' :' NGC 4151' ,
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+ ... ' stime' :' 2007-01-01' ,
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+ ... ' etime' :' 2008-01-01' },
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+ ... columns= [' night' ])
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>>> print (len (table))
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>>> print (table.columns)
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- < TableColumns names= (' Object' ,' RA' , ' DEC' ,' Target l b' ,' DATE OBS' ,' ProgId' ,' DP.ID' ,' OB.ID' ,' OBS.TARG.NAME' ,' DPR.CATG' ,' DPR.TYPE' ,' DPR.TECH' ,' INS.MODE' ,' DIMM S -avg' )>
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+ <TableColumns names=('Release Date',' Object','RA','DEC','Target Ra Dec','Target l b','DATE OBS','ProgId','DP.ID','OB.ID','OBS.TARG.NAME','DPR.CATG','DPR.TYPE','DPR.TECH','INS.MODE','DIMM Seeing -avg')>
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>>> table.pprint(max_width = 100 )
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- Object Target Ra Dec Target l b ... INS .MODE DIMM S- avg
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- ---------------------- - ---------------------- - -------------------- ... -------- ---------- -
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- NGC4151 12 :10 :32.63 + 39 :24 :20.7 155.076719 75.063247 ... STARINTF 0.69 [0.01 ]
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- NGC4151 12 :10 :32.63 + 39 :24 :20.7 155.076719 75.063247 ... STARINTF 0.68 [0.01 ]
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- NGC4151 12 :10 :32.63 + 39 :24 :20.7 155.076719 75.063247 ... STARINTF 0.68 [0.01 ]
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- NGC4151 12 :10 :32.63 + 39 :24 :20.7 155.076719 75.063247 ... STARINTF 0.69 [0.01 ]
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- NGC4151 12 :10 :32.63 + 39 :24 :20.7 155.076719 75.063247 ... STARINTF 0.69 [0.01 ]
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- NGC4151 12 :10 :32.63 + 39 :24 :20.7 155.076719 75.063247 ... STARINTF 0.74 [0.01 ]
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- NGC4151 12 :10 :32.63 + 39 :24 :20.7 155.076719 75.063247 ... STARINTF 0.69 [0.01 ]
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- NGC4151 12 :10 :32.63 + 39 :24 :20.7 155.076719 75.063247 ... STARINTF 0.66 [0.01 ]
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- NGC4151 12 :10 :32.63 + 39 :24 :20.7 155.076719 75.063247 ... STARINTF 0.64 [0.01 ]
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- NGC4151 12 :10 :32.63 + 39 :24 :20.7 155.076719 75.063247 ... STARINTF 0.60 [0.01 ]
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- NGC4151 12 :10 :32.63 + 39 :24 :20.7 155.076719 75.063247 ... STARINTF 0.59 [0.01 ]
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- ... ... ... ... ... ...
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- TRACK ,OBJECT ,DISPERSED 12 :10 :32.63 + 39 :24 :20.7 155.076719 75.063247 ... STARINTF 0.70 [0.01 ]
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- TRACK ,OBJECT ,DISPERSED 12 :10 :32.63 + 39 :24 :20.7 155.076719 75.063247 ... STARINTF 0.72 [0.01 ]
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- SEARCH ,OBJECT ,DISPERSED 12 :10 :32.63 + 39 :24 :20.7 155.076719 75.063247 ... STARINTF 0.62 [0.01 ]
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- SEARCH ,OBJECT ,DISPERSED 12 :10 :32.63 + 39 :24 :20.7 155.076719 75.063247 ... STARINTF 0.61 [0.01 ]
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- SEARCH ,OBJECT ,DISPERSED 12 :10 :32.63 + 39 :24 :20.7 155.076719 75.063247 ... STARINTF 0.54 [0.01 ]
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- SEARCH ,OBJECT ,DISPERSED 12 :10 :32.63 + 39 :24 :20.7 155.076719 75.063247 ... STARINTF 0.53 [0.01 ]
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- TRACK ,OBJECT ,DISPERSED 12 :10 :32.63 + 39 :24 :20.7 155.076719 75.063247 ... STARINTF 0.51 [0.01 ]
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- TRACK ,OBJECT ,DISPERSED 12 :10 :32.63 + 39 :24 :20.7 155.076719 75.063247 ... STARINTF 0.51 [0.01 ]
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- TRACK ,OBJECT ,DISPERSED 12 :10 :32.63 + 39 :24 :20.7 155.076719 75.063247 ... STARINTF 0.51 [0.01 ]
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- PHOTOMETRY ,OBJECT 12 :10 :32.63 + 39 :24 :20.7 155.076719 75.063247 ... STARINTF 0.54 [0.01 ]
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- PHOTOMETRY ,OBJECT 12 :10 :32.63 + 39 :24 :20.7 155.076719 75.063247 ... STARINTF 0.54 [0.01 ]
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+ Release Date Object RA ... DPR.TECH INS.MODE DIMM Seeing-avg
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+ ------------ ----------------------- ---------- ... -------------------- -------- ---------------
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+ 2008-02-07 NGC4151 182.635969 ... IMAGE,WINDOW STARINTF 0.69 [0.01]
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+ 2008-02-07 NGC4151 182.635969 ... IMAGE,WINDOW STARINTF 0.68 [0.01]
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+ 2008-02-07 NGC4151 182.635969 ... IMAGE,WINDOW STARINTF 0.68 [0.01]
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+ 2008-02-07 NGC4151 182.635969 ... IMAGE,WINDOW STARINTF 0.69 [0.01]
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+ 2008-02-07 NGC4151 182.635969 ... IMAGE,WINDOW STARINTF 0.69 [0.01]
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+ 2008-02-07 NGC4151 182.635969 ... IMAGE,WINDOW STARINTF 0.74 [0.01]
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+ 2008-02-07 NGC4151 182.635969 ... IMAGE,WINDOW STARINTF 0.69 [0.01]
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+ 2008-02-07 NGC4151 182.635969 ... IMAGE,WINDOW STARINTF 0.66 [0.01]
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+ 2008-02-07 NGC4151 182.635969 ... IMAGE,WINDOW STARINTF 0.64 [0.01]
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+ 2008-02-07 NGC4151 182.635969 ... IMAGE,WINDOW STARINTF 0.60 [0.01]
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+ ... ... ... ... ... ... ...
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+ 2007-02-07 TRACK,OBJECT,DISPERSED 182.635969 ... INTERFEROMETRY STARINTF 0.72 [0.01]
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+ 2007-02-07 SEARCH,OBJECT,DISPERSED 182.635969 ... INTERFEROMETRY STARINTF 0.62 [0.01]
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+ 2007-02-07 SEARCH,OBJECT,DISPERSED 182.635969 ... INTERFEROMETRY STARINTF 0.61 [0.01]
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+ 2007-02-07 SEARCH,OBJECT,DISPERSED 182.635969 ... INTERFEROMETRY STARINTF 0.54 [0.01]
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+ 2007-02-07 SEARCH,OBJECT,DISPERSED 182.635969 ... INTERFEROMETRY STARINTF 0.53 [0.01]
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+ 2007-02-07 TRACK,OBJECT,DISPERSED 182.635969 ... INTERFEROMETRY STARINTF 0.51 [0.01]
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+ 2007-02-07 TRACK,OBJECT,DISPERSED 182.635969 ... INTERFEROMETRY STARINTF 0.51 [0.01]
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+ 2007-02-07 TRACK,OBJECT,DISPERSED 182.635969 ... INTERFEROMETRY STARINTF 0.51 [0.01]
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+ 2007-02-07 PHOTOMETRY,OBJECT 182.635969 ... IMAGE,WINDOW,CHOPNOD STARINTF 0.54 [0.01]
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+ 2007-02-07 PHOTOMETRY,OBJECT 182.635969 ... IMAGE,WINDOW,CHOPNOD STARINTF 0.54 [0.01]
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Length = 38 rows
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And indeed, 38 datasets are found, and the ``DATE OBS `` column is in the result table.
@@ -224,27 +226,42 @@ is identical to :meth:`~astroquery.eso.EsoClass.query_instrument`.
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ESO instruments without a specific query interface can be queried with
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:meth: `~astroquery.eso.EsoClass.query_main `, specifying the ``instrument `` constraint.
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This is the case of e.g. ``harps ``, ``feros `` or the all sky cameras APICAM and MASCOT. Here is an example to
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- query all-sky images from APICAM with ``luminance `` filter.
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+ query all-sky images from APICAM with ``luminance `` filter.
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- .. code-block :: python
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+ .. doctest-remote-data ::
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>>> eso.ROW_LIMIT = - 1 # Return all results
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>>> table = eso.query_main(column_filters = {' instrument' : ' APICAM' , ' filter_path' : ' LUMINANCE' ,
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... ' stime' :' 2019-04-26' , ' etime' :' 2019-04-27' }, cache= False )
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>>> print (len (table))
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>>> print (table.columns)
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- < TableColumns names= (' OBJECT' ,' RA' ,' DEC' ,' Program_ID' ,' Instrument' ,' Category' ,' Type' ,' Mode' ,' Dataset ID' ,' Release_Date' ,' TPL ID' ,' TPL START' ,' Exptime' ,' Exposure' ,' Filter ' ,' MJD-OBS' ,' Airmass' ,' DIMM Seeing at Start' )>
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+ <TableColumns names=('OBJECT','RA','DEC','Program_ID','Instrument','Category','Type','Mode','Dataset ID','Release_Date','TPL ID','TPL START','Exptime','Exposure','filter_lambda_min','filter_lambda_max ','MJD-OBS','Airmass','DIMM Seeing at Start')>
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>>> table.pprint(max_width = 100 )
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- OBJECT RA DEC Program_ID ... Filter MJD - OBS Airmass DIMM Seeing at Start
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- ------ - ---------- - ---------- - ------------ ... -------- - ------------ ------ - --------------------
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- ALL SKY 09 :18 :37.39 - 24 :32 :32.7 60. A- 9008 (A) ... LUMINANCE 58599.987766 1.0 N/ A
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- ALL SKY 09 :21 :07.68 - 24 :32 :30.1 60. A- 9008 (A) ... LUMINANCE 58599.989502 1.0 N/ A
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- ALL SKY 09 :23 :38.98 - 24 :32 :27.5 60. A- 9008 (A) ... LUMINANCE 58599.99125 1.0 N/ A
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- ... ... ... ... ... ... ... ... ...
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- ALL SKY 11 :47 :35.12 - 24 :31 :07.7 60. A- 9008 (A) ... LUMINANCE 58600.091019 1.0 N/ A
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- ALL SKY 11 :50 :07.40 - 24 :31 :07.6 60. A- 9008 (A) ... LUMINANCE 58600.092778 1.0 N/ A
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- Length = 50 rows
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+ OBJECT RA DEC Program_ID ... MJD-OBS Airmass DIMM Seeing at Start
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+ ------- ----------- ----------- ------------ ... ------------ ------- --------------------
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+ ALL SKY 09:18:37.39 -24:32:32.7 60.A-9008(A) ... 58599.987766 1.0 N/A
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+ ALL SKY 09:21:07.68 -24:32:30.1 60.A-9008(A) ... 58599.989502 1.0 N/A
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+ ALL SKY 09:23:38.98 -24:32:27.5 60.A-9008(A) ... 58599.99125 1.0 N/A
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+ ALL SKY 09:26:10.28 -24:32:24.9 60.A-9008(A) ... 58599.992998 1.0 N/A
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+ ALL SKY 09:28:40.58 -24:32:22.4 60.A-9008(A) ... 58599.994734 1.0 N/A
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+ ALL SKY 09:31:43.93 -24:32:19.4 60.A-9008(A) ... 58599.996852 1.0 N/A
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+ ALL SKY 09:34:15.23 -24:32:17.0 60.A-9008(A) ... 58599.9986 1.0 N/A
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+ ALL SKY 09:36:47.53 -24:32:14.5 60.A-9008(A) ... 58600.000359 1.0 N/A
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+ ALL SKY 09:39:18.82 -24:32:12.2 60.A-9008(A) ... 58600.002106 1.0 N/A
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+ ALL SKY 09:41:49.11 -24:32:09.9 60.A-9008(A) ... 58600.003843 1.0 N/A
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+ ... ... ... ... ... ... ... ...
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+ ALL SKY 19:07:39.21 -24:39:35.1 60.A-9008(A) ... 58600.395914 1.0 N/A
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+ ALL SKY 19:10:11.68 -24:39:39.1 60.A-9008(A) ... 58600.397674 1.0 N/A
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+ ALL SKY 19:12:44.15 -24:39:43.2 60.A-9008(A) ... 58600.399433 1.0 N/A
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+ ALL SKY 19:15:15.62 -24:39:47.1 60.A-9008(A) ... 58600.401181 1.0 N/A
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+ ALL SKY 19:17:46.09 -24:39:51.1 60.A-9008(A) ... 58600.402917 1.0 N/A
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+ ALL SKY 19:20:46.65 -24:39:55.8 60.A-9008(A) ... 58600.405 1.0 N/A
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+ ALL SKY 19:23:18.12 -24:39:59.7 60.A-9008(A) ... 58600.406748 1.0 N/A
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+ ALL SKY 19:25:51.60 -24:40:03.7 60.A-9008(A) ... 58600.408519 1.0 N/A
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+ ALL SKY 19:28:22.08 -24:40:07.6 60.A-9008(A) ... 58600.410255 1.0 N/A
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+ ALL SKY 19:30:52.55 -24:40:11.4 60.A-9008(A) ... 58600.411991 1.0 N/A
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+ Length = 207 rows
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Query the ESO archive for reduced data
@@ -258,7 +275,7 @@ Identify available surveys
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The list of available surveys can be obtained with :meth: `astroquery.eso.EsoClass.list_surveys ` as follows:
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- .. code-block :: python
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+ .. doctest-remote-data ::
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>>> surveys = eso.list_surveys()
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@@ -269,7 +286,8 @@ Let's assume that we work with the ``HARPS`` survey, and that we are interested
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target ``HD203608 ``.
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The archive can be queried as follows:
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- .. code-block :: python
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+
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+ .. doctest-remote-data ::
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>>> table = eso.query_surveys(' HARPS' , cache = False , target = " HD203608" )
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@@ -284,37 +302,40 @@ Only a small subset of the keywords presents in the data products can be obtaine
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with :meth: `~astroquery.eso.EsoClass.query_instrument ` or :meth: `~astroquery.eso.EsoClass.query_main `.
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There is however a way to get the full primary header of the FITS data products,
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using :meth: `~astroquery.eso.EsoClass.get_headers `.
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- This method is detailed in the example below, continuing with the previously obtained table.
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+ This method is detailed in the example below.
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+
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- .. code-block :: python
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+ .. doctest-remote-data ::
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+ >>> table = eso.query_instrument(' midi' , column_filters = {' target' :' NGC 4151' ,
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+ ... ' stime' :' 2007-01-01' ,
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+ ... ' etime' :' 2008-01-01' },
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+ ... columns= [' night' ])
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>>> table_headers = eso.get_headers(table[' DP.ID' ])
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- >> > table_headers.pprint()
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- ARCFILE BITPIX ... TELESCOP UTC
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- -------------------------------- - ------ ... ------------ ------ -
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- MIDI .2007- 02 - 07T07 :01 :51.000 .fits 16 ... ESO - VLTI - U23 25300.5
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- MIDI .2007- 02 - 07T07 :02 :49.000 .fits 16 ... ESO - VLTI - U23 25358.5
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- MIDI .2007- 02 - 07T07 :03 :30.695 .fits 16 ... ESO - VLTI - U23 25358.5
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- MIDI .2007- 02 - 07T07 :05 :47.000 .fits 16 ... ESO - VLTI - U23 25538.5
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- MIDI .2007- 02 - 07T07 :06 :28.695 .fits 16 ... ESO - VLTI - U23 25538.5
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- MIDI .2007- 02 - 07T07 :09 :03.000 .fits 16 ... ESO - VLTI - U23 25732.5
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- MIDI .2007- 02 - 07T07 :09 :44.695 .fits 16 ... ESO - VLTI - U23 25732.5
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- MIDI .2007- 02 - 07T07 :13 :09.000 .fits 16 ... ESO - VLTI - U23 25978.5
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- MIDI .2007- 02 - 07T07 :13 :50.695 .fits 16 ... ESO - VLTI - U23 25978.5
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- MIDI .2007- 02 - 07T07 :15 :55.000 .fits 16 ... ESO - VLTI - U23 26144.5
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- MIDI .2007- 02 - 07T07 :16 :36.694 .fits 16 ... ESO - VLTI - U23 26144.5
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- ... ... ... ... ...
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- MIDI .2007- 02 - 07T07 :51 :13.485 .fits 16 ... ESO - VLTI - U23 28190.5
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- MIDI .2007- 02 - 07T07 :52 :27.992 .fits 16 ... ESO - VLTI - U23 28190.5
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- MIDI .2007- 02 - 07T07 :56 :21.000 .fits 16 ... ESO - VLTI - U23 28572.5
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- MIDI .2007- 02 - 07T07 :57 :35.485 .fits 16 ... ESO - VLTI - U23 28572.5
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- MIDI .2007- 02 - 07T07 :59 :46.000 .fits 16 ... ESO - VLTI - U23 28778.5
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- MIDI .2007- 02 - 07T08 :01 :00.486 .fits 16 ... ESO - VLTI - U23 28778.5
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- MIDI .2007- 02 - 07T08 :03 :42.000 .fits 16 ... ESO - VLTI - U23 29014.5
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- MIDI .2007- 02 - 07T08 :04 :56.506 .fits 16 ... ESO - VLTI - U23 29014.5
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- MIDI .2007- 02 - 07T08 :06 :11.013 .fits 16 ... ESO - VLTI - U23 29014.5
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- MIDI .2007- 02 - 07T08 :08 :19.000 .fits 16 ... ESO - VLTI - U23 29288.5
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- MIDI .2007- 02 - 07T08 :09 :33.506 .fits 16 ... ESO - VLTI - U23 29288.5
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+ >>> table_headers.pprint() # doctest: +IGNORE_OUTPUT
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+ DP.ID SIMPLE BITPIX ... HIERARCH ESO OCS TPL NFILE HIERARCH ESO OCS EXPO1 FNAME3
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+ ---------------------------- ------ ------ ... -------------------------- ---------------------------------
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+ MIDI.2007-02-07T07:01:51.000 True 16 ... 0
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+ MIDI.2007-02-07T07:02:49.000 True 16 ... 0
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+ MIDI.2007-02-07T07:03:30.695 True 16 ... 0
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+ MIDI.2007-02-07T07:05:47.000 True 16 ... 0
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+ MIDI.2007-02-07T07:06:28.695 True 16 ... 0
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+ MIDI.2007-02-07T07:09:03.000 True 16 ... 0
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+ MIDI.2007-02-07T07:09:44.695 True 16 ... 0
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+ MIDI.2007-02-07T07:13:09.000 True 16 ... 0
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+ MIDI.2007-02-07T07:13:50.695 True 16 ... 0
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+ MIDI.2007-02-07T07:15:55.000 True 16 ... 0
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+ ... ... ... ... ... ...
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+ MIDI.2007-02-07T07:52:27.992 True 16 ... 8 MIDI.2007-02-07T07:52:27.992.fits
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+ MIDI.2007-02-07T07:56:21.000 True 16 ... 0
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+ MIDI.2007-02-07T07:57:35.485 True 16 ... 0
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+ MIDI.2007-02-07T07:59:46.000 True 16 ... 0
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+ MIDI.2007-02-07T08:01:00.486 True 16 ... 0
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+ MIDI.2007-02-07T08:03:42.000 True 16 ... 8
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+ MIDI.2007-02-07T08:04:56.506 True 16 ... 8
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+ MIDI.2007-02-07T08:06:11.013 True 16 ... 8 MIDI.2007-02-07T08:06:11.013.fits
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+ MIDI.2007-02-07T08:08:19.000 True 16 ... 8 MIDI.2007-02-07T08:06:11.013.fits
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+ MIDI.2007-02-07T08:09:33.506 True 16 ... 8 MIDI.2007-02-07T08:06:11.013.fits
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Length = 38 rows
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>>> len (table_headers.columns)
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@@ -329,7 +350,7 @@ Downloading datasets from the archive
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Continuing from the query with constraints example, the first two datasets are selected,
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using their data product IDs ``DP.ID `` (or ``ARCFILE `` for surveys), and retrieved from the ESO archive.
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- .. code-block :: python
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+ .. doctest-skip ::
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>>> data_files = eso.retrieve_data(table[' DP.ID' ][:2 ])
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Staging request...
@@ -354,12 +375,13 @@ would like to download datasets from an existing request, either submitted
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through the functions here or externally, call ``retrieve_data `` with the
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``request_id `` option:
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- .. code-block :: python
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+ .. doctest-skip ::
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>>> data_files = eso.retrieve_data(table[' DP.ID' ][:2 ], request_id = 999999 )
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The ``request_id `` can be found in the automatic email sent by the archive after
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- staging the initial request, i.e., https://dataportal.eso.org/rh/requests/[USERNAME]/{request_id}. A summary of your available requests is shown at https://dataportal.eso.org/rh/requests/[USERNAME]/recentRequests.
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+ staging the initial request, i.e., https://dataportal.eso.org/rh/requests/[USERNAME]/{request_id}.
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+ A summary of your available requests is shown at https://dataportal.eso.org/rh/requests/[USERNAME]/recentRequests.
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Note: The function does check that the specified retrieval URL based on
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``request_id `` is valid and then that the datasets indicated there are
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