Examples of how to use NAIF SPICE for planetary and satellite calculations
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README.md

spice-examples

Examples of how to use NAIF SPICE for planetary and satellite calculations

NAIF is NASA's Navigation and Ancillary Information Facility, and SPICE is their library for writing software.

Currently most of the examples here use the SpiceyPy Python bindings for SPICE.

There isn't much documentation for either SPICE or SpiceyPy. Two useful starting points:

Kernels

The tricky part about programming in SPICE is that most SPICE programs require SPICE "kernels" which must be downloaded from NAIF. Kernels contain models and data which are then used by the high-level SPICE functions. So, for instance, you can copy the occultation example from the Most Used APIs page, but it won't work unless you also have the "cas_2005_v17.tm" kernel used in the example -- and the page doesn't give you any hint where to get that. Even if you change the observer to EARTH instead of CASSINI, it still won't work because then you need other SPICE kernels to get the Saturn, Sun and Earth data.

Finding Kernels

So finding kernels is the key to learning to program in SPICE ... and none of the documentation tells you how to find them. There doesn't seem to be any document listing what kernels are available and what's in each of them, so plan on spending some time hunting. Here's what I've learned so far:

The SPICE Data page has three links:

For spacecraft data, click on the appropriate link (depending on whether the desired spacecraft is currently or recently operational or not), look for its name and try to guess which file to download. If you find a better way, let me know and I'll update this README.

Most of my programming involves planets and natural satellites, which only require the Generic Kernels.

Searching for a Specific Kernel

If you're just starting out, trying to get the examples to work, you may already know the filename you need. For instance, suppose an example uses de421.bsp and you just need to know where to find it.

Here's a handy trick. You can get a full listing of the directory structure of a remote file server with the lftp program's du command:

lftp https://naif.jpl.nasa.gov/pub/naif/generic_kernels/

Then, at the lftp prompt, type: du -a > generic_manifest.txt

Exit lftp, and you'll have a file called generic_manifest.txt containing the full structure of all the generic manifests. You will also have a directory called naif.jpl.nasa.gov containing only empty directories, which you can rm -rf since it doesn't do you any good.

(There ought to be some way to do this using wget or curl, but I couldn't find a way that actually worked. Even better, I'd like to fetch all files starting with aaa or AAA throughout the whole directory structure, but nothing else. Anyone know how to do that? I may eventually write a Python script.)

Now that you have generic_manifest.txt, you can grep for filenames:

$ grep de421.bsp generic_manifest.txt
16397   ./spk/planets/a_old_versions/de421.bsp

Append the pathname it gives you to https://naif.jpl.nasa.gov/pub/naif/generic_kernels/ so you can fetch the file with wget:

wget https://naif.jpl.nasa.gov/pub/naif/generic_kernels/spk/planets/a_old_versions/de421.bsp

You can do that for the spacecraft kernels too, but if you start at the root of the tree it'll be a big fetch, so you might want to do it just for the spacecraft you're interested in, like Cassini.

Exploring Generic Kernels

The Generic Kernels don't have a helpful page explaining what's what: you have to click around in the data, (https://naif.jpl.nasa.gov/pub/naif/generic_kernels/) to see what lives where.

There's a file called aareadme.txt that explains the other subdirectories:

  • dsk, Digital Shape Kernel (for modeling the shape of a few natural bodies)
  • fk, Frames Kernel (for specific missions, it's not clear what they contain)
  • lsk, Leapseconds Kernel (for accurate time calculations)
  • pck, Planetary Constants Kernel (data related to orbits of major natural solar system bodies)
  • spk, Spacecraft and Planet Kernel (orbits and other details of planets, natural satellites, and a few comets and asteroids, plus the location of the Deep Space Network (DSN) ground stations relative to the center of the earth).
  • stars, a few star catalogs.

In each of these directories (and most of their subdirectories) there should be files with names like AAA_README or file aa_summaries.txt (they're not consistent about filenames, but anything starting with aaa or AAA is probably useful) with information about what's there.

So, suppose I want to write a program to see when Ganymede transits Jupiter. Probably a lot of kernels have Jupiter in them, but Ganymede will be harder, so let's start by looking for that. It's a natural satellite, so I'll guess it will be somewhere in the Spacecraft and Planet Kernels since that's supposed to include natural satellites. So I go to https://naif.jpl.nasa.gov/pub/naif/generic_kernels/spk.

AAREADME_SPKs.txt in that directory isn't helpful, just generic information about kernels. There are subdirectories asteroids, comets, lagrange_point, planets, satellites, stations. satellites looks likely. In there, the file AAREADME_Satellite_SPKs tells me that there may be one or several files for each planet that has satellites, and that there's no overlap: so Ganymede will be in only one of the Jupiter SPK files. It also tells me that the aa_summaries file gives me a listing of which satellites are in which file.

So next, I read aa_summaries.txt in that directory, and right away I see that

GANYMEDE (503) w.r.t. JUPITER BARYCENTER (5)

is in jup310.bsp, so I'll try downloading that file (and cross my fingers).

You'll generally find you need several kernels. For instance, for Ganymede and Jupiter, when I tried it with just jup310.bsp I got an error about needing leap seconds, and when I added a kernel for that I got a different error. In the end, I needed naif0009.tls for leap seconds, jup310.bsp for Ganymede and Jupiter, and pck00008.tpc for a variable called BODY503_RADII -- I guess jup310.bsp has orbits but not sizes.

Figuring out what kernels you need is a fairly elaborate and mysterious process and is definitely the hardest part of using SPICE.

Specifying Kernels

Once you have your kernels downloaded, you can specify them in Python like this:

# Needed for leap seconds:
spiceypy.furnsh("/path/to/kernels/tls/naif0009.tls")

# Jupiter and its major moons:
spiceypy.furnsh("/path/to/kernels/bsp/jup310.bsp")

You don't have to use subdirectories like tls and bsp, but a lot of the code seems structured like that so I'm following suit. For the path on your filesystem, so you can either have a relative directory called kernels, or set up some known location like ~/.cache/SPICE/kernels or ~/SPICE/kernels or whatever you like. I'm going to use an absolute path.

In a lot of SPICE examples, you'll see furnsh called on a file ending in .tm. Such a file might look like this:

\begindata
KERNELS_TO_LOAD = ( 'kernels/tls/naif0009.tls',
                    'kernels/bsp/sat288.bsp',
                    'kernels/bsp/jup310.bsp',
                    'kernels/pck/pck00008.tpc' )
\begintext

I'm not sure I see the advantage of this; I think I'm going to stick to separate furnsh calls built into my Python scripts so my scripts can work without needing a .tm file. That's one of the problems with those otherwise useful examples on the Most Used APIs page -- since they assume a .tm file but they don't include that file, you have no idea what kernels you need to make the examples work.

RTFM

I know I've been negative about the documentation: the overviews, lessons and examples mostly poorly written and makes it very hard to get started or to figure out kernels. But the documentation for individual functions is quite extensive and well worth reading. For instance, there are some nice examples of how to find occultations of Titan by Saturn and vice versa in the gfoclt documentation page and that's fairly typical for documentation of SPICE functions. There's a lot of good information there even if some of the examples aren't clear about what kernels they use.