Simbad to KStars import
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Makefile
README.rst
example_location.json
example_obswindow.json
observable.py
query.py

README.rst

Simbad to KStars import

Grepping through Simbad to look for interesting objects you could observe.

  • Queries Simbad for objects. Supports arbitrary user-defined criteria.
  • The names, positions and types are stored in a KStars catalogue
  • Can trim out objects that can not be observed from your location (see below)
  • The catalogue can then be loaded in KStars, and viewed.
  • Caches Simbad queries, so a request is not repeated to the servers. To clear cache, remove joblib directory.

Example Use Cases

General questions:

  • Where are exoplanets? (Simbad query: otype='Pl').

    The list is updated all the time, so it makes sense to just load from simbad.

  • What are the brightest Globular Clusters? (Vmag<8.5&otype='GlC')

    A magnitude-cut.

Lets say you have a telecope available, for example for a student, but are not sure what object to point to.

If you have a spectrograph:

  • Where are bright spectroscopic binaries? (Vmag<5&otype = 'SB*')
  • What is a good, bright peculiar star to look at? (Vmag<7&otype = 'Pe*')

Hint: Search exoplanet.eu for planets with short-period (<5 days) and high-amplitude (K>50). You might be able to detect those with a few nights of observations!

Usage

  1. Create a KStars catalogue from an arbitrary Simbad query:

    $ python query.py "Vmag<8.5&otype='GlC'" outputfile.kstarscat
    
  2. Open KStars, go to KStars Settings -> Advanced -> Load catalogue.

    Loading catalogues is slow, but finally you will have all objects in KStars.

Observable objects

To trim the catalogue to objects you can actually observe in your part of the world in a given time window, I have included some simple ephemeris calculations.

  1. Define your location in location.json:

    {
            "lat": -33.459229,
            "lon": -70.645348,
            "height": 0
    }
    

    Latitude and longitude in degrees, height in meters.

  2. Define when you want to do your observations (time window, minimum elevation):

    {
            "start": "2015-09-12 18:00:00",
            "stop":  "2015-09-20 02:00:00",
            "steps": 1200,
            "minalt": 15,
            "hourranges": [[20, 24], [0,2]],
            "timezone": "America/Santiago"
    }
    

    When you run query.py, the RA/Dec will be sampled in the time window. Between start and stop one point every steps seconds (in the Example above, every 20 minutes) is created. Points outside the hour ranges are discarded (in the example the night is between 8pm and 2am). The timezone is in the common tz format.

    At every remaining point the altitude of each object is computed.

    Objects get scores for the maximum altitude reached, and if the altitude is never above minalt (in degrees), they are removed from the catalogue.

  3. Run query.py as above. This is of course a very crude tool. KStars has a observability tool which you can use to compare the objects in more detail.

Example

Looking for brighter than magnitude 7 stars, which are peculiar (Pe*):

$ python query.py "Vmag<7&otype='Pe*'" peculiar.kstarcat

Objects will be graded by observability:
    Column 1: Name
    Column 2: Fraction of time when above minimum elevation
    Column 3: Maximum elevation

* zet Cyg            0.8 26.2
HD 175674            1.0 75.0
* omi Vir            0.0 -0.2
* 56 Peg             0.7 31.0
* eps Peg            1.0 46.6
HD 199394            0.0 10.1
* ksi Cap            1.0 69.1
HR 4862              1.0 36.8
* tet Aur            0.0 -11.3
* 53 Cam             0.0 -37.6
HR 3612              0.0 -45.6
V* alf02 CVn         0.0 -7.8
* 58 Leo             0.0 -10.8
HD 198590            1.0 84.4
* 55 Cam             0.0 -38.7
HR 3166              0.0 10.3
HD 223617            0.8 54.2
HR 5058              0.3 39.2
HR 774               0.0 -26.0
* 16 Ser             0.3 37.2
V* TZ Lyn            0.0 -39.3
HD 41701             0.2 30.2
V* HR CMa            0.0 9.3
* o Vir              0.1 20.7
* zet Cap            1.0 78.9
* ups02 Cas          0.0 -2.7
V* GO And            0.0 11.5
HD 77247             0.0 -46.1
HR 4474              0.0 -26.0
HD 205011            0.9 32.6
* 12 Pup             0.0 -0.9
* 49 Cam             0.0 -36.0
HD 100012            0.0 11.5
* y Vel              0.0 3.6
* ksi Cyg            0.0 12.5

14 objects in output catalogue
21 unobservable objects trimmed from output catalogue
Top 10: HD 198590, * zet Cap, HD 175674, * ksi Cap, * eps Peg, HR 4862, HD 205011, HD 223617, * zet Cyg, * 56 Peg

HD 198590 is easy to observe -- it goes up to 84 degrees and never sets.