Merge pull request #2721 from bsipocz/DOC_fixing_failing_doc_examples

DOC: fixing examples that caused remote test failures

Author: bsipocz

docs/casda/casda.rst

@@ -29,11 +29,11 @@ For example:
     obs_publisher_did       s_ra           s_dec           obs_release_date
                             deg             deg
     ----------------- --------------- ---------------- ------------------------
-           cube-11460 326.52250211117 -43.891190432671 2020-11-18T09:49:27.134Z
-           cube-11461 326.52250211117 -43.891190432671 2020-11-18T09:49:27.134Z
-           cube-11462 326.52250211117 -43.891190432671 2020-11-18T09:49:27.134Z
-           cube-11463 326.52250211117 -43.891190432671 2020-11-18T09:49:27.134Z
-           cube-11464 326.52250211117 -43.891190432671 2020-11-18T09:49:27.134Z
+            cube-1170 333.70448386919 -45.966341151806 2019-01-30T13:00:00.000Z
+           cube-60339 333.74878924962  -46.50601666028 2022-03-18T00:32:52.674Z
+           cube-60338 333.74878924962  -46.50601666028 2022-03-18T00:32:52.674Z
+           cube-60337 333.74878924962  -46.50601666028 2022-03-18T00:32:52.674Z
+           cube-60336 333.74878924962  -46.50601666028 2022-03-18T00:32:52.674Z
 
 
 In most cases only public data is required. While most ASKAP data is public, some data products may not be released for quality reasons.
@@ -49,11 +49,11 @@ For example to filter out the 30 non-public results from the above data set:
     obs_publisher_did       s_ra           s_dec           obs_release_date
                             deg             deg
     ----------------- --------------- ---------------- ------------------------
-           cube-11460 326.52250211117 -43.891190432671 2020-11-18T09:49:27.134Z
-           cube-11461 326.52250211117 -43.891190432671 2020-11-18T09:49:27.134Z
-           cube-11462 326.52250211117 -43.891190432671 2020-11-18T09:49:27.134Z
-           cube-11463 326.52250211117 -43.891190432671 2020-11-18T09:49:27.134Z
-           cube-11464 326.52250211117 -43.891190432671 2020-11-18T09:49:27.134Z
+            cube-1170 333.70448386919 -45.966341151806 2019-01-30T13:00:00.000Z
+           cube-60339 333.74878924962  -46.50601666028 2022-03-18T00:32:52.674Z
+           cube-60338 333.74878924962  -46.50601666028 2022-03-18T00:32:52.674Z
+           cube-60337 333.74878924962  -46.50601666028 2022-03-18T00:32:52.674Z
+           cube-60336 333.74878924962  -46.50601666028 2022-03-18T00:32:52.674Z
 
 
 Authentication
@@ -71,7 +71,7 @@ date. To change user-registration details, or to request a new OPAL password,
 use the link to 'Log in or reset password'.
 
 To use download tasks, you should create an instance of the ``Casda`` class
-and call the :meth:`~astroquery.casda.CasdaClass.login` method with a username. The password will either be taken 
+and call the :meth:`~astroquery.casda.CasdaClass.login` method with a username. The password will either be taken
 from the keyring, or if in an interactive environment then it will be requested. e.g.:
 
 .. doctest-skip::
@@ -90,14 +90,14 @@ Data Access
 
 .. versionadded:: 0.4.4
 
-In order to access data in CASDA you must first stage the data using the :meth:`~astroquery.casda.CasdaClass.stage_data` 
+In order to access data in CASDA you must first stage the data using the :meth:`~astroquery.casda.CasdaClass.stage_data`
 method.
 This is because only some of the data in CASDA is held on disc at any particular time.
-The :meth:`~astroquery.casda.CasdaClass.stage_data` method should be passed an astropy Table object containing an 
+The :meth:`~astroquery.casda.CasdaClass.stage_data` method should be passed an astropy Table object containing an
 'access_url' column.
 This column should contain the datalink address of the data product.
 
-Once the data has been assembled you can then download the data using the :meth:`~astroquery.casda.CasdaClass.download_files` 
+Once the data has been assembled you can then download the data using the :meth:`~astroquery.casda.CasdaClass.download_files`
 method, or using tools such as wget.
 Authentication is required when staging the data, but not for the download.
 
@@ -128,9 +128,9 @@ Cutouts
 
 As well as accessing full data products, the CASDA service can produce cutout images and cubes from larger data products.
 The cutout support in AstroQuery allows both spatial and spectral cutouts.
-To produce a spatial cutout, pass in a coordinate and either a radius or a height and a width to the 
+To produce a spatial cutout, pass in a coordinate and either a radius or a height and a width to the
 :meth:`~astroquery.casda.CasdaClass.cutout` method.
-To produce a spectral cutout, pass in either a band or a channel value. 
+To produce a spectral cutout, pass in either a band or a channel value.
 For band, the value must be a list or tuple of two `astropy.units.Quantity` objects specifying a low and high frequency
 or wavelength. For an open ended range use `None` as the open value.
 For channel, the value must be a list or tuple of two integers specifying the low and high channels (i.e. planes of a
@@ -176,7 +176,7 @@ is shown below:
     >>> url_list = casda.cutout(eridanus_cube, coordinates=centre, radius=9*u.arcmin, band=freq)
     >>> filelist = casda.download_files(url_list, savedir='/tmp')
 
-An example script to download a 3D cutout of a spectral channel range from the WALLABY Pre-Pilot Eridanus cube 
+An example script to download a 3D cutout of a spectral channel range from the WALLABY Pre-Pilot Eridanus cube
 is shown below:
 
 .. doctest-skip::

docs/imcce/imcce.rst

@@ -39,8 +39,8 @@ looks like this:
    >>> epoch = Time('2019-05-29 21:42', format='iso')
    >>> results = Skybot.cone_search(field, 5*u.arcmin, epoch)
    >>> results.pprint(max_width=80)  # doctest: +IGNORE_OUTPUT
-    Number    Name             RA          ...      vy          vz       epoch  
-                              deg          ...    AU / d      AU / d       d    
+    Number    Name             RA          ...      vy          vz       epoch
+                              deg          ...    AU / d      AU / d       d
     ------ ---------- -------------------- ... ----------- ----------- ---------
         --  2012 BO42 0.019414999999999998 ... 0.009345668 0.005003011 2458630.0
     516566  2007 DH36 0.005546249999999999 ...  0.00855646 0.002875928 2458630.0
@@ -184,31 +184,22 @@ Pallas over an entire year with a time step of 1 day:
    >>> from astroquery.imcce import Miriade
    >>> Miriade.get_ephemerides('Pallas', epoch='2019-01-01',
    ...                         epoch_step='1d', epoch_nsteps=365)
-    <Table length=365>
-    target        epoch                 RA         ...   DEC_rate    delta_rate 
-                    d                  deg         ... arcsec / min    km / s   
-    str20        float64             float64       ...   float64      float64   
-    ------ -------------------- ------------------ ... ------------ ------------
-    Pallas            2458484.5 200.58650874999998 ...      0.15854  -19.3678463
-    Pallas            2458485.5 200.92693874999998 ...      0.16727  -19.4137948
-    Pallas            2458486.5  201.2641095833333 ...      0.17613  -19.4552689
-    Pallas            2458487.5       201.59795375 ...      0.18511  -19.4921153
-    Pallas            2458488.5  201.9284045833333 ...      0.19421  -19.5242013
-    Pallas            2458489.5 202.25539499999996 ...      0.20344  -19.5514142
-    Pallas            2458490.5 202.57885874999997 ...      0.21278  -19.5736602
-    Pallas            2458491.5 202.89872916666664 ...      0.22224  -19.5908624
-    Pallas            2458492.5 203.21494124999998 ...      0.23181  -19.6029579
-       ...                  ...                ... ...          ...          ...
-    Pallas            2458839.5  259.6145529166667 ...    0.0069182   -1.4120214
-    Pallas            2458840.5  259.9944454166666 ...     0.011429   -1.6321428
-    Pallas            2458841.5 260.37380541666664 ...     0.015948     -1.85224
-    Pallas            2458842.5 260.75260416666663 ...     0.020475   -2.0721423
-    Pallas            2458843.5 261.13081083333327 ...     0.025007   -2.2916829
-    Pallas            2458844.5  261.5083958333333 ...     0.029542   -2.5107107
-    Pallas            2458845.5 261.88532958333326 ...     0.034077    -2.729099
-    Pallas            2458846.5        262.2615825 ...     0.038612    -2.946749
-    Pallas            2458847.5 262.63712708333327 ...     0.043144   -3.1635882
-    Pallas            2458848.5         263.011935 ...     0.047672   -3.3795665
+   <Table length=365>
+   target        epoch                 RA         ...   DEC_rate    delta_rate
+                   d                  deg         ... arcsec / min    km / s
+   str20        float64             float64       ...   float64      float64
+   ------ -------------------- ------------------ ... ------------ ------------
+   Pallas            2458484.5 200.58653041666665 ...      0.15854  -19.3678426
+   Pallas            2458485.5 200.92696041666662 ...      0.16727  -19.4137911
+   Pallas            2458486.5  201.2641308333333 ...      0.17613  -19.4552654
+   Pallas            2458487.5 201.59797541666663 ...      0.18511  -19.4921119
+   Pallas            2458488.5 201.92842624999997 ...      0.19421  -19.5241979
+      ...                  ...                ... ...          ...          ...
+   Pallas            2458844.5  261.5083995833333 ...     0.029542   -2.5107101
+   Pallas            2458845.5  261.8853333333333 ...     0.034077   -2.7290984
+   Pallas            2458846.5       262.26158625 ...     0.038612   -2.9467484
+   Pallas            2458847.5 262.63713083333334 ...     0.043144   -3.1635878
+   Pallas            2458848.5       263.01193875 ...     0.047672   -3.3795661
 
 
 The observer location is defined through the ``location`` keyword,

docs/index.rst

@@ -141,10 +141,10 @@ queries based on coordinates or object names.  Some simple examples, using SIMBA
     >>> from astroquery.simbad import Simbad
     >>> result_table = Simbad.query_object("m1")
     >>> result_table.pprint()
-    MAIN_ID    RA      DEC    ... COO_WAVELENGTH COO_BIBCODE SCRIPT_NUMBER_ID
-            "h:m:s"  "d:m:s"  ...
-    ------- -------- -------- ... -------------- ----------- ----------------
-      M   1 05 34 32 +22 00.8 ...              R                            1
+    MAIN_ID     RA        DEC    ...    COO_BIBCODE      SCRIPT_NUMBER_ID
+             "h:m:s"    "d:m:s"  ...
+    ------- ---------- --------- ... ------------------- ----------------
+      M   1 05 34 30.9 +22 00 53 ... 1995AuJPh..48..143S                1
 
 All query tools allow coordinate-based queries:
 

docs/ipac/ned/ned.rst

@@ -29,7 +29,7 @@ instance if you want to query NGC 224
     No. Object Name     RA     ... Redshift Points Diameter Points Associations
                      degrees   ...
     --- ----------- ---------- ... --------------- --------------- ------------
-      1 MESSIER 031   10.68479 ...              39              13            2
+      1 MESSIER 031   10.68479 ...              40              13            2
 
 
 Query a region
@@ -58,11 +58,11 @@ specified. By default this is J2000.0 but can also be set to B1950.0.
       3 SSTSL2 J122855.23+020341.5  187.23013 ...               0            0
       4 SSTSL2 J122855.36+020346.9  187.23068 ...               0            0
     ...                        ...        ... ...             ...          ...
-    863 SSTSL2 J122918.24+020330.7    187.326 ...               0            0
-    864   SDSS J122918.38+020323.4   187.3266 ...               4            0
-    865 SSTSL2 J122918.52+020338.9  187.32718 ...               0            0
-    866 SSTSL2 J122918.64+020326.7  187.32767 ...               0            0
-    Length = 866 rows
+    864 SSTSL2 J122918.24+020330.7    187.326 ...               0            0
+    865   SDSS J122918.38+020323.4   187.3266 ...               4            0
+    866 SSTSL2 J122918.52+020338.9  187.32718 ...               0            0
+    867 SSTSL2 J122918.64+020326.7  187.32767 ...               0            0
+    Length = 867 rows
 
 
 Instead of using the name, the target may also be specified via
@@ -220,7 +220,8 @@ Similarly the list of URLs for spectra of a particular object may be fetched:
     >>> spectra_list
     ['http://ned.ipac.caltech.edu/spc1/1992/1992ApJS...80..109B/PG_1226+023:S:B_V:bg1992.fits.gz',
      'http://ned.ipac.caltech.edu/spc1/2009/2009A+A...495.1033B/3C_273:S:B:bcc2009.fits.gz',
-     'http://ned.ipac.caltech.edu/spc1/2009/2009A+A...495.1033B/3C_273:S:RI:bcc2009.fits.gz']
+     ...
+     'http://ned.ipac.caltech.edu/spc1/2016/2016ApJS..226...19F/3C_273:S:CII158.3x3.fits.gz']
 
 
 Fetching other data tables for an object
@@ -251,17 +252,17 @@ for the specified object. We look at a simple example:
       8 12h29m06.7001s ...                                   Uncertain origin
       9 12h29m06.7001s ...                                   Uncertain origin
     ...            ... ...                      ...                       ...
-    138   12h29m06.05s ...   Broad-band measurement        From new, raw data
-    139    12h29m06.5s ...   Broad-band measurement        From new, raw data
-    140    12h29m06.5s ...   Broad-band measurement From reprocessed raw data
-    141    12h29m09.0s ...                                   Uncertain origin
-    142    12h29m08.9s ...                                   Uncertain origin
-    143    12h29m07.9s ...                                   Uncertain origin
-    144      12h29m04s ...                                   Uncertain origin
-    145      12h29m06s ...                                   Uncertain origin
-    146      12h29m08s ...                                   Uncertain origin
-    147      12h29m06s ...                                   Uncertain origin
-    Length = 148 rows
+    144   12h29m06.05s ...   Broad-band measurement        From new, raw data
+    145    12h29m06.5s ...   Broad-band measurement        From new, raw data
+    146    12h29m06.5s ...   Broad-band measurement From reprocessed raw data
+    147    12h29m09.0s ...                                   Uncertain origin
+    148    12h29m08.9s ...                                   Uncertain origin
+    149    12h29m07.9s ...                                   Uncertain origin
+    150      12h29m04s ...                                   Uncertain origin
+    151      12h29m06s ...                                   Uncertain origin
+    152      12h29m08s ...                                   Uncertain origin
+    153      12h29m06s ...                                   Uncertain origin
+    Length = 154 rows
 
 
 Reference/API

docs/ipac/nexsci/nasa_exoplanet_archive.rst

@@ -95,6 +95,7 @@ A list of accessible tables can be found in the ``TAP_TABLES`` attribute:
     >>> NasaExoplanetArchive.TAP_TABLES
     ['superwasptimeseries',
     'kelttimeseries',
+    'DI_STARS_EXEP',
     'transitspec',
     'emissionspec',
     'ps',

docs/jplhorizons/jplhorizons.rst

@@ -434,19 +434,19 @@ We can select several columns at a time, for instance RA and DEC for each epoch
 .. code-block:: python
 
    >>> print(eph['datetime_str', 'RA', 'DEC'])    # doctest: +REMOTE_DATA
-       datetime_str       RA      DEC
-           ---           deg      deg
-    ----------------- --------- --------
-    2010-Jan-01 00:00 345.50204 13.43621
-    2011-Jan-01 00:00  78.77158 61.48831
-    2012-Jan-01 00:00 119.85659 54.21955
-    2013-Jan-01 00:00 136.60021  45.8241
-    2014-Jan-01 00:00 147.44947 37.79876
-    2015-Jan-01 00:00 156.58967 29.23058
-    2016-Jan-01 00:00 166.32129 18.48174
-    2017-Jan-01 00:00  180.6992  1.20453
-    2018-Jan-01 00:00 232.11974 -37.9554
-    2019-Jan-01 00:00   16.1066 45.50296
+      datetime_str       RA      DEC
+          ---           deg      deg
+   ----------------- --------- --------
+   2010-Jan-01 00:00 345.50204 13.43621
+   2011-Jan-01 00:00  78.77158 61.48831
+   2012-Jan-01 00:00 119.85659 54.21955
+   2013-Jan-01 00:00 136.60021 45.82409
+   2014-Jan-01 00:00 147.44947 37.79876
+   2015-Jan-01 00:00 156.58967 29.23058
+   2016-Jan-01 00:00 166.32129 18.48174
+   2017-Jan-01 00:00  180.6992  1.20453
+   2018-Jan-01 00:00 232.11974 -37.9554
+   2019-Jan-01 00:00   16.1066 45.50296
 
 
 We can use the same representation to do math with these columns. For instance,
@@ -646,4 +646,4 @@ Reference/API
 .. _astropy units: http://docs.astropy.org/en/stable/units/index.html
 .. _Definition of Observer Table Quantities: https://ssd.jpl.nasa.gov/horizons/manual.html#observer-table
 .. _Horizons documentation: https://ssd.jpl.nasa.gov/horizons/manual.html#observer-table
-.. _this section of the Horizons manual: <https://ssd.jpl.nasa.gov/horizons/manual.html#center>
+.. _this section of the Horizons manual: <https://ssd.jpl.nasa.gov/horizons/manual.html#center>

docs/linelists/cdms/cdms.rst

@@ -35,7 +35,7 @@ each setting yields:
    ...                             get_query_payload=False)
    >>> response.pprint(max_width=120)
         FREQ     ERR    LGINT   DR   ELO    GUP MOLWT TAG QNFMT  Ju  Ku  vu F1u F2u F3u  Jl  Kl  vl F1l F2l F3l   name  Lab
-        MHz      MHz   MHz nm2      1 / cm        u
+        MHz      MHz   nm2 MHz      1 / cm        u
     ----------- ------ ------- --- -------- --- ----- --- ----- --- --- --- --- --- --- --- --- --- --- --- --- ------- ----
     115271.2018 0.0005 -5.0105   2      0.0   3    28 503   101   1  --  --  --  --  --   0  --  --  --  --  -- CO, v=0 True
        230538.0 0.0005 -4.1197   2    3.845   5    28 503   101   2  --  --  --  --  --   1  --  --  --  --  -- CO, v=0 True
@@ -76,7 +76,7 @@ The units of the columns of the query can be displayed by calling
    ----- ------- ------- ------------ -----
     FREQ float64     MHz       Column     0
      ERR float64     MHz       Column     0
-   LGINT float64 MHz nm2       Column     0
+   LGINT float64 nm2 MHz       Column     0
       DR   int64               Column     0
      ELO float64  1 / cm       Column     0
      GUP   int64               Column     0