• And the Solar System, too

  2017-03-30 Markus Demleitner

  Virtual Observatory technologies are increasingly being adopted outside of “core” astronomy in the vicinity of the optical band (to which they have had, I'll have to admit, a certain slant) . An excellent example for that trend is the Europlanet community. Their goal is to make solar system data accessible without fiddling, and they are employing a wide range of VO standards for that. At the heart of their efforts are TAP and the VO Registry.

  While the usual VO client software will of course work fine with their services, they are offering a nice web-based discovery tool executing queries against an increasing number of services. Such uniform quering over many services is possible is because all of them implement TAP and host EPNcore tables. The resulting interface, also known as EPN-TAP, allows for very flexible discovery and retrieval of solar system data products, much like ObsTAP does for astronomical observations outside of the solar system.

  Since quite a few EPN-TAP services are built using GAVO's DaCHS publication suite, I was invited to this week's VESPA implementation workshop 2017 in Graz to help the data providers set up their services.

  I can't deny that I'm somewhat excited when I see how our software is used to publish spectra of the ice blocks in Saturn's ring taken by the lonely Cassini spacecraft still orbiting the gas giant, or data transmitted by Rosetta, now (and for who knows how long) sitting on comet 67P/Churyumov-Gerasimenko. There's even an upcoming archive of solar system alerts that may, according to its builders, include events like meteor showers on Mars. I can almost hear my code whisper “I've archived signals of C-beams glitter in the dark near the Tannhäuser Gate”.

  Even documentation can become otherworldly in this business: Already in February, DaCHS has learnt to procude GeoJSON, a format common in the GIS community and also adopted by Europlanet – planetology has lots of common ground with geoinformatics. And in the reference documentation on annotating tables to enable that, when I wrote “standards-compliant GeoJSON clients will interpret your coordinates as WGS84 on Earth if you leave [frame annotation] out”, I was severely tempted to add “which is probably not what you want” and feel like Spaceman Spiff.

  Romantic space adventures aside, after this intense week, not only are there several additional or improved EPN-TAP services from places ranging from Pasadena to Villafranca to Warsaw in the pipeline, the close interaction with the data providers has also led to very significant improvements to DaCHS' EPN-TAP support. The tutorial chapter on EPN-TAP and the reference documentation linked from there already reflect the results of this workshop. You'll need a current DaCHS beta package for that to work, though; we expect this stuff to go into our release packages around July.

  If any of the workshop participants read this: Thanks a lot for your patience with DaCHS' sometimes somewhat cryptic diagnostics. If, on the other hand, you missed the Graz workshop and have solar system data: Please talk to us or the kind and friendly Europlanet folks – either us will be delighted to support your publication project. And perhaps we'll meet you at the next such workshop, planned for 2018 in the Czech Republic.

• Updated Proper Motion Tutorial

  2017-03-24 Markus Demleitner

  At the risk of turning this into a blog on nice TAP tricks (which it's not supposed to be): Our classic short tutorial on adding proper motions to almost arbitrary object lists has just gotten a facelift today.

  And there's new content, too – I now show what to do when you don't even have positions but just object names. In order to keep this sufficiently geeky, here's the query as a spoiler:

  SELECT col1, ra, dec
  FROM TAP_UPLOAD.t1
  LEFT OUTER JOIN ident
  ON (id=normId(col1))
  LEFT OUTER JOIN basic
  ON (oidref=oid)
  

  But to close on a non-TAP topic: Registry! There's an experimental facility to have this kind of thing in the Registry; the PM tutorial is in, for instance, with the ivoid ivo://edu.gavo.org/hd/gavo_addpms). One thing you can do with this is generate a list of registred documents that essentially updates itself from the registry.

  Another is figure out where the source code of the document is (if the authors choose to share it, which is of course a very smart thing to do); in our example it's in Volute, the IVOA's semi-official version control system. So, if you find a bug (defined as “superset of typo”) in the linked document, you're most welcome to supply patches as diffs or just directly fix things if you have commit privileges in Volute.

• See Who's Kinking the Sky

  2017-03-14 Markus Demleitner

  A new arrival in the GAVO Data Center is UCAC5, another example of a slew of new catalogs combining pre-existing astrometry with Gaia DR1, just like the HSOY catalog we've featured here a couple of weeks back.

  That's a nice opportunity to show how to use ADQL's JOIN operator for something else than the well-known CONTAINS-type crossmatch. Since both UCAC5 and HSOY reference Gaia DR1, both have, for each object, a notion which element of the Gaia source catalog they correspond to. For HSOY, that's the gaia_id column, in UCAC5, it's just source_id. Hence, to compare results from both efforts, all you have to do is to join on source_id=gaia_id (you can save yourself the explicit table references here because the column names are unique to each table.

  So, if you want to compare proper motions, all you need to do is to point your favourite TAP client's interface to http://dc.g-vo.org/tap and run:

  SELECT
      in_unit(avg(uc.pmra-hsoy.pmra), 'mas/yr') AS pmradiff,
      in_unit(avg(uc.pmde-hsoy.pmde), 'mas/yr') AS pmdediff,
      count(*) as n,
      ivo_healpix_index (6, raj2000, dej2000) AS hpx
      FROM hsoy.main AS hsoy
      JOIN ucac5.main as uc
      ON (uc.source_id=hsoy.gaia_id)
      WHERE comp IS NULL    -- hsoy junk filter
      AND clone IS NULL     -- again, hsoy junk filter
      GROUP BY hpx
  

  (see Taylor et al's All of the Sky if you're unsure what do make of the healpix/GROUP BY magic).

  Of course, the fact that both tables are in the same service helps, but with a bit of upload magic you could do about the same analysis across TAP services.

  Just so there's a colourful image in this post, too, here's what this query shows for the differences in proper motion in RA:

  (equatorial coordinates, and the aux axis is a bit cropped here; try for yourself to see how things look for PM in declination or when plotted in galactic coordinates).

  What does this image mean? Well, it means that probably both UCAC5 and HSOY would still putt kinks into the sky if you wait long enough.

  In the brightest and darkest points, if you waited 250 years, the coordinate system induced by each catalog on the sky would be off by 1 arcsec with respect to the other (on a sphere, that means there's kinks somewhere). It may seem amazing that there's agreement to at least this level between the two catalogs – mind you, 1 arcsec is still more than 100 times smaller than you could see by eye; you'd have to go back to the Mesolithic age to have the slightest chance of spotting the disagreement without serious optical aids. But when Gaia DR2 will come around (hopefully around April 2018), our sky will be more stable even than that.

  Of course, both UCAC5 and HSOY are, indirectly, standing on the shoulders of the same giant, namely Hipparcos and Tycho, so the agreement may be less surprising, and we strongly suspect that a similar image will look a whole lot less pleasant when Gaia has straightened out the sky, in particular towards weaker stars.

  But still: do you want to bet if UCAC5 or HSOY will turn out to be closer to a non-kinking sky? Let us know. Qualifications („For bright stars...”) are allowed.

• Automating TAP queries

  2017-02-24 Markus Demleitner

  TOPCAT is a great tool – in particular, for prototyping and ad-hoc analyses, it's hard to beat. But say you've come up with this great TAP query, and you want to preserve it, perhaps generate plots, then maybe fix them when you (or referees) have spotted problems.

  Then it's time to get acquainted with TOPCAT's command line sister STILTS. This tool lets you do most of what TOPCAT can, but without user intervention. Since the command lines usually take a bit of twiddling I usually wrap stilts calls with GNU make, so I just need to run something like make fig3.pdf or make fig3.png and make figures out what to do, potentially starting with a query. Call it workflow preservation if you want.

  How does it work? Well, of course with a makefile. In that, you'll first want to define some variables that allow more concise rules later. Here's how I usually start one:

  STILTS?=stilts
  
  # VOTables are the results of remote queries, so don't wantonly throw
  # them away
  .PRECIOUS: %.vot
  
  # in this particular application, it helps to have this global
  HEALPIX_ORDER=6
  
  # A macro that contains common stuff for stilts TAP query -- essentially,
  # just add adql=
  TAPQUERY=$(STILTS) tapquery \
    tapurl='http://dc.g-vo.org/tap' \
    maxrec=200000000 \
    omode=out \
    out=$@ \
    ofmt=vot \
    executionduration=14400
  
  # A sample plot macro.  Here, we do a healpix plot of some order. Also
  # add value_1=<column to plot>
  HEALPIXPLOT=$(STILTS) plot2sky \
    auxmap=inferno \
    auxlabel='$*'\
    auxvisible=true \
    legend=false \
    omode=out \
    out=$@ \
    projection=aitoff \
    sex=false \
    layer_1=healpix \
      datalevel_1=$(HEALPIX_ORDER) \
      datasys_1=equatorial \
      viewsys_1=equatorial \
      degrade_1=0 \
      transparency_1=0 \
      healpix_1=hpx \
      in_1=$< \
      ifmt_1=votable \
      istream_1=true \
  

  For the somewhat scary STILS command lines, see the STILTS documentation or just use your intution (which mostly should give you the right idea what something is for).

  The next step is to define some pattern rules; these are a (in the syntax here, GNU) make feature that let you say „to make a file matching the destination pattern when you have one with the source pattern, use the following commands”. You can use a number of variables in the rules, in particular $@ (the current target) and $< (the first prerequisite). These are already used in the definitions of TAPQUERY and HEALPIXPLOT above, so they don't necessarily turn up here:

  # healpix plots from VOTables; these will plot obs
  %.png: %.vot
        $(HEALPIXPLOT) \
                value_1=obs \
                ofmt=png \
                xpix=600 ypix=380
  
   %.pdf: %.vot
         $(HEALPIXPLOT) \
                 value_1=obs \
                 ofmt=pdf
  
   # turn SQL statements into VOTables using TAP
   %.vot: %.sql
         $(TAPQUERY) \
                adql="`cat $<`"
  

  Careful with cut and paste: The leading whitespace here must be a Tab in rules, not just some blanks (this is probably the single most annoying feature of make. You'll get used to it.)

  What can you do with it? Well, for instance you can write an ADQL query into a file density.sql; say:

  SELECT
    count(*) as obs,
    -- "6" in the next line must match HEALPIX_ORDER in the Makefile
    ivo_healpix_index (6, alphaFloat, deltaFloat) AS hpx
  FROM ppmx.data
  GROUP BY hpx
  

  And with this, you can say:

  make density.pdf
  

  and get a nice PDF with the plot resulting from that query. Had you just said make density.vot, make would just have executed the query and left the VOTable, e.g., for investigation with TOPCAT, and if you were to type make density.png, you'd get a nice PNG without querying the service again. Like this:

  

  Unless of course you changed the SQL in the meantime, in which case make would figure out it had to go back to the service.

  In particular for the plots you'll often have to override the defaults. Make is smart enough to figure this out. For instance, you could have two files like this:

  $ cat pm_histogram.sql
  SELECT
    round(pmtot/10)*10 as bin, count(*) as n
  FROM (
    SELECT sqrt(pmra*pmra+pmde*pmde)*3.6e6 as pmtot
    FROM hsoy.main) AS q
  group by bin
  $ cat pm_histogram_cleaned.vot
  SELECT
    round(pmtot/10)*10 as bin,
    count(*) as n
    FROM (
      SELECT sqrt(pmra*pmra+pmde*pmde)*3.6e6 as pmtot
      FROM hsoy.main
      WHERE no_sc IS NULL) AS q
    group by bin
  

  (these were used to analyse the overall proper motions distributions in HSOY properties; note that each of these will run about 30 minutes or so, so better adapt them to what's actually interesting to you before trying this).

  No special handling in terms of queries is necessary for these, but the plot needs to be hand-crafted:

  pm_histograms.png: pm_histogram.vot pm_histogram_cleaned.vot
       $(STILTS) plot2plane legend=false \
               omode=out ofmt=png out=$@ \
                title="All-sky" \
                xpix=800 ypix=600 \
                ylog=True xlog=True\
                xlabel="PM bin [mas/yr, bin size=10]" \
                xmax=4000 \
                layer1=mark \
                       color1=blue \
                       in1=pm_histogram.vot \
                       x1=bin \
                       y1=n \
               layer2=mark \
                       in2=pm_histogram_cleaned.vot \
                       x2=bin \
                       y2=n
  

  – that way, even if you go back to the stuff six months later, you can still figure out what you queried (the files are still there) and what you did then.

  A makefile to play with (and safe from cut-and-paste problems) is available from Makefile_tapsample (rename to Makefile to reproduce the examples).

• PPMXL+Gaia DR1=HSOY in the Heidelberg Data Center

  2017-01-17 Markus Demleitner

  The stunning precision of Gaia's astrometry is already apparent in the first release of the data obtained by the satellite, available since last September. However, apart from the small TGAS subset (objects already observed by the 90ies HIPPARCOS astrometry satellite) there is no information on the objects' proper motions in DR1.

  Until Gaia-quality proper motions will become available in DR2, the HSOY catalog – described in Altmann et al's paper Hot Stuff for One Year (HSOY) freshly up in arXiv and online at http://dc.g-vo.org/hsoy – can help if you can live with somewhat lesser-quality kinematics.

  It derives proper motions for roughly half a billion stars from PPMXL and Gaia DR1, which already gives an unprecedented source for 4D astrometry around J2015. And you can start working with it right now. The catalog is available in GAVO's Heidelberg data center (TAP access URL: http://dc.g-vo.org/tap; there's also an SCS service). Fire up your favourite TAP or SCS client (our preference: TOPCAT) and search for HSOY.

  

  Oh, and in case you're new to the whole TAP/ADQL game: There's our ADQL introduction, and if you're at a German astronomical institution, we'd be happy to hold one of our VO Days at your institute – just drop us a mail.

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