Cite as: Astrophysics Source Code Library, record ascl:1112.014 <https://ascl.net/1112.014>_

This package can load and use a Jet Propulsion Laboratory (JPL)
ephemeris for predicting the position and velocity of a planet or other
Solar System body. It currently supports binary SPK files (extension
.bsp) like those distributed by the Jet Propulsion Laboratory <https://ssd.jpl.nasa.gov/ftp/eph/planets/bsp/>_ that are:

Type 2 — positions stored as Chebyshev polynomials, with velocity
derived by computing their derivative.
Type 3 — positions and velocities both stored explicitly as
Chebyshev polynomials.
Type 9 — a series of discrete positions and velocities, with
separate timestamps that do not need to be equally spaced. Currently
there is only support for linear interpolation: for Type 9 ephemerides
of polynomial degree 1, not of any higher degrees.

Note that even if an ephemeris isn’t one of the above types, you can
still use jplephem to read its text comment and list the segments
inside, using the subcommands comment and daf described below.

Installation

The only third-party package that jplephem depends on is NumPy <http://www.numpy.org/>_, which pip will automatically attempt to
install alongside pyephem when you run::

$ pip install jplephem

If you see NumPy compilation errors, then try downloading and installing
NumPy directly from its web site <http://www.numpy.org/>_ or simply
use a distribution of Python with science tools already installed, like
Anaconda <http://continuum.io/downloads>_.

Note that jplephem offers only the logic necessary to produce plain
three-dimensional vectors. Most programmers interested in astronomy
will want to look at Skyfield <http://rhodesmill.org/skyfield/>_
instead, which uses jplephem but converts the numbers into more
traditional measurements like right ascension and declination.

Most users will use jplephem with the Satellite Planet Kernel (SPK)
files that the NAIF facility at NASA JPL offers for use with their own
SPICE toolkit. They have collected their most useful kernels beneath
the directory:

http://naif.jpl.nasa.gov/pub/naif/generic_kernels/spk/

To learn more about SPK files, the official SPK Required Reading <http://naif.jpl.nasa.gov/pub/naif/toolkit_docs/FORTRAN/req/spk.html>_
document is available from the NAIF facility’s web site under the NASA
JPL domain.

Command Line Tool

If you have downloaded a .bsp file, you can run jplephem from
the command line to display the data inside of it::

python -m jplephem comment de421.bsp
python -m jplephem daf de421.bsp
python -m jplephem spk de421.bsp
python -m jplephem spk -v de421.bsp

You can also take a large ephemeris and produce a smaller excerpt by
limiting the range of dates that it covers::

python -m jplephem excerpt 2018/1/1 2018/4/1 de421.bsp excerpt421.bsp

The comment text of the output ephemeris is copied verbatim from the
input ephemeris, with the addition of a few lines of text at the top
that identify the output file as a mere excerpt, and record the dates
the user asked for.

You will get an error if your starting year is negative, because Unix
commands expect a list of options when they see a dash. The fix is to
provide a special argument -- which says “I’m done passing options,
even if the next argument stars with a dash”::

python -m jplephem excerpt -- -800/1/1 800/1/1 de422.bsp excerpt422.bsp

You can also filter by the integer codes for the targets you need.
Unrecognized targets will not raise an error, to let you apply a master
list of targets to a whole series of SPK files that might or might not
each have all of the targets::

python -m jplephem excerpt --targets 1,2,3 2018/1/1 2018/4/1 de421.bsp excerpt421.bsp

If the input ephemeris is a URL, then jplephem will try to save
bandwidth by fetching only the blocks of the remote file that are
necessary to cover the dates you have specified. For example, the
Jupiter satellite ephemeris jup310.bsp is famously large, weighing
in a nearly a gigabyte. But if all you need are Jupiter's satellites
for a few months, you can download considerably less data::

$ python -m jplephem excerpt 2018/1/1 2018/4/1 \
    https://naif.jpl.nasa.gov/pub/naif/generic_kernels/spk/satellites/jup365.bsp \
    excerpt.bsp
$ ls -lh excerpt.bsp
-rw-r----- 1 brandon brandon 1.2M Feb 11 13:36 excerpt.bsp

In this case only about one-thousandth of the ephemeris's data needed to
be downloaded.

Getting Started With DE421

The DE421 ephemeris is a useful starting point. It weighs in at 17 MB,
but provides predictions over the years 1900–2050:

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

After the kernel has downloaded, you can use jplephem to load this
SPK file and learn about the segments it offers:

from jplephem.spk import SPK
kernel = SPK.open('de421.bsp')
print(kernel)
File type DAF/SPK and format LTL-IEEE with 15 segments:
1899-07-29..2053-10-09 Type 2 Solar System Barycenter (0) -> Mercury Barycenter (1)
1899-07-29..2053-10-09 Type 2 Solar System Barycenter (0) -> Venus Barycenter (2)
1899-07-29..2053-10-09 Type 2 Solar System Barycenter (0) -> Earth Barycenter (3)
1899-07-29..2053-10-09 Type 2 Solar System Barycenter (0) -> Mars Barycenter (4)
1899-07-29..2053-10-09 Type 2 Solar System Barycenter (0) -> Jupiter Barycenter (5)
1899-07-29..2053-10-09 Type 2 Solar System Barycenter (0) -> Saturn Barycenter (6)
1899-07-29..2053-10-09 Type 2 Solar System Barycenter (0) -> Uranus Barycenter (7)
1899-07-29..2053-10-09 Type 2 Solar System Barycenter (0) -> Neptune Barycenter (8)
1899-07-29..2053-10-09 Type 2 Solar System Barycenter (0) -> Pluto Barycenter (9)
1899-07-29..2053-10-09 Type 2 Solar System Barycenter (0) -> Sun (10)
1899-07-29..2053-10-09 Type 2 Earth Barycenter (3) -> Moon (301)
1899-07-29..2053-10-09 Type 2 Earth Barycenter (3) -> Earth (399)
1899-07-29..2053-10-09 Type 2 Mercury Barycenter (1) -> Mercury (199)
1899-07-29..2053-10-09 Type 2 Venus Barycenter (2) -> Venus (299)
1899-07-29..2053-10-09 Type 2 Mars Barycenter (4) -> Mars (499)

Since the next few examples involve vector output, let’s tell NumPy to
make vector output attractive.

import numpy as np
np.set_printoptions(precision=3)

Each segment of the file lets you predict the position of one body with
respect to another for a given Julian date. A small routine is provided
to convert Gregorian calendar dates to Julian dates:

from jplephem.calendar import compute_julian_date
compute_julian_date(2015, 2, 8)
2457061.5

Here is how to compute the coordinates of Mars (target 4) relative to
the Solar System barycenter (target 0) at midnight 2015 February 8 TDB
(Barycentric Dynamical Time), using the Julian date we just computed:

position = kernel[0,4].compute(2457061.5)
print(position)
[2.057e+08 4.251e+07 1.394e+07]

By contrast, it takes three steps to learn the position of Mars with
respect to the Earth: from Mars to the Solar System barycenter, to the
Earth-Moon barycenter (3), and finally to Earth itself (399).

position = kernel[0,4].compute(2457061.5)
position -= kernel[0,3].compute(2457061.5)
position -= kernel[3,399].compute(2457061.5)
print(position)
[ 3.161e+08 -4.679e+07 -2.476e+07]

You can see that the output of this ephemeris DE421 is in kilometers.
If you use another ephemeris, check its documentation to be sure of the
units that it employs.

If you supply the date as a NumPy array, then each component that is
returned will itself be a vector as long as your date:

jd = np.array([2457061.5, 2457062.5, 2457063.5, 2457064.5])
position = kernel[0,4].compute(jd)
print(position)
[[2.057e+08 2.053e+08 2.049e+08 2.045e+08]
[4.251e+07 4.453e+07 4.654e+07 4.855e+07]
[1.394e+07 1.487e+07 1.581e+07 1.674e+07]]

Some ephemerides include velocity inline by returning a 6-vector instead
of a 3-vector. For an ephemeris that does not, you can ask for the
Chebyshev polynomial to be differentiated to produce a velocity, which
is delivered as a second return value:

position, velocity = kernel[0,4].compute_and_differentiate(2457061.5)
print(position)
[2.057e+08 4.251e+07 1.394e+07]

print(velocity)
[-363896.059 2019662.996 936169.773]

The velocity will by default be distance traveled per day, in whatever
units for distance the ephemeris happens to use. To get a velocity per
second, simply divide by the number of seconds in a day:

velocity_per_second = velocity / 86400.0
print(velocity_per_second)
[-4.212 23.376 10.835]

Details of the API

Here are a few details for people ready to go beyond the high-level API
provided above and read through the code to learn more.

Instead of reading an entire ephemeris into memory, jplephem
memory-maps the underlying file so that the operating system can
efficiently page into RAM only the data that your code is using.
Once the metadata has been parsed from the binary SPK file, the
polynomial coefficients themselves are loaded by building a NumPy
array object that has access to the raw binary file contents.
Happily, NumPy already knows how to interpret a packed array of
double-precision floats. You can learn about the underlying DAF
“Double Precision Array File” format, in case you ever need to open
other such array files in Python, through the DAF class in the
module jplephem.daf.
An SPK file is made of segments. When you first create an SPK
kernel object k, it examines the file and creates a list of
Segment objects that it keeps in a list under an attribute named
k.segments which you are free to examine in your own code by
looping over it.
There is more information about each segment beyond the one-line
summary that you get when you print out the SPK file, which you can
see by asking the segment to print itself verbosely:

segment = kernel[3,399]
print(segment.describe())
1899-07-29..2053-10-09 Type 2 Earth Barycenter (3) -> Earth (399)
frame=1 source=DE-0421LE-0421
Each Segment loaded from the kernel has a number of attributes
that are loaded from the SPK file:

from jplephem.spk import BaseSegment
help(BaseSegment)
Help on class BaseSegment in module jplephem.spk:
...
| segment.source - official ephemeris name, like 'DE-0430LE-0430'
| segment.start_second - initial epoch, as seconds from J2000
| segment.end_second - final epoch, as seconds from J2000
| segment.start_jd - start_second, converted to a Julian Date
| segment.end_jd - end_second, converted to a Julian Date
| segment.center - integer center identifier
| segment.target - integer target identifier
| segment.frame - integer frame identifier
| segment.data_type - integer data type identifier
| segment.start_i - index where segment starts
| segment.end_i - index where segment ends
...
If you want to access the raw coefficients, use the segment
load_array() method. It returns two floats and a NumPy array:

initial_epoch, interval_length, coefficients = segment.load_array()
print(coefficients.shape)
(3, 14080, 13)
The square-bracket lookup mechanism kernel[3,399] is a
non-standard convenience that returns only the last matching segment
in the file. While the SPK standard does say that the last segment
takes precedence, it also says that earlier segments for a particular
center-target pair should be fallen back upon for dates that the last
segment does not cover. So, if you ever tackle a complicated kernel,
you will need to implement fallback rules that send some dates to the
final segment for a given center and target, but that send other dates
to earlier segments that are qualified to cover them.
If you are accounting for light travel time and require repeated
computation of the position, but then need the velocity at the end,
and want to avoid repeating the expensive position calculation, then
try out the segment.generate() method - it will let you ask for
the position, and then only proceed to the velocity once you are sure
that the light-time error is now small enough.

High-Precision Dates

Since all modern Julian dates are numbers larger than 2.4 million, a
standard 64-bit Python or NumPy float necessarily leaves only a limited
number of bits available for the fractional part. Technical Note
2011-02 from the United States Naval Observatory's Astronomical
Applications Department suggests that the precision possible with a 64-bit floating point Julian date is around 20.1 µs <http://jplephem.s3.amazonaws.com/JD_precision_test.pdf>_.

If you need to supply times and receive back planetary positions with
greater precision than 20.1 µs, then you have two options.

First, you can supply times using the special float96 NumPy type,
which is also aliased to the name longfloat. If you provide either
a float96 scalar or a float96 array as your tdb parameter to
any jplephem routine, you should get back a high-precision result.

Second, you can split your date or dates into two pieces, and supply
them as a pair of arguments two tdb and tdb2. One popular
approach for how to split your date is to use the tdb float for the
integer Julian date, and tdb2 for the fraction that specifies the
time of day. Nearly all jplephem routines accept this optional
tdb2 argument if you wish to provide it, thanks to the work of
Marten van Kerkwijk!

Support for Binary PCKs

You can also load and produce rotation matrices from a binary PCK file.
Its segments are available through the segments attributes of the
returned object.

from jplephem.pck import PCK
p = PCK.open('moon_pa_de421_1900-2050.bpc')
p.segments[0].body
31006

p.segments[0].frame
1

p.segments[0].data_type
2

Given a solary system barycenter Julian date, the segment will return
the three angles necessary to build a rotation matrix: right ascension
of the pole, declination of the pole, and cumulative rotation of the
body’s axis. Typically these will all be in radians.

tdb = 2454540.34103
print(p.segments[0].compute(tdb, 0.0, False))
[3.928e-02 3.878e-01 3.253e+03]

You can ask for velocity as well.

r, v = p.segments[0].compute(tdb, 0.0, True)
print(r)
[3.928e-02 3.878e-01 3.253e+03]

print(v)
[6.707e-09 4.838e-10 2.655e-06]

Closing an ephemeris

To release all open files and memory maps associated with an ephemeris,
call its close() method.

kernel.close()
p.close()

Reporting issues

You can report any issues, bugs, or problems at the GitHub repository:

https://github.com/brandon-rhodes/python-jplephem/

Changelog

2025 June 22 — Version 2.23

An ephemeris created with the excerpt command, instead of simply
copying verbatim the comments area of the original ephemeris, now adds
text declaring “This is an ephemeris excerpt created by jplephem” and
recording the dates that the user asked for.
The segments of an excerpt ephemeris now advertise exactly the start
date and end date that the user asked for, even if the underlying
polynomials cover a wider range of dates.
A new -v (“verbose”) command-line option to the spk
sub-command prints not only each segment’s descriptor, but the
dimensions and date range of its underlying polynomial array.

2024 April 24 — Version 2.22

When printed, segments now print their start and end dates using the
Gregorian calendar instead of printing raw Julian dates.
A small compute_julian_date routine is now provided for converting
calendar dates into Julian dates.
Fixed the text of the ValueError that is raised when the PCK
segment compute() method is given an out-of-range date; it was
reporting incorrectly large numbers for the Julian date range, because
a PCK counts time using seconds before or after J2000, not years.

2023 December 1 — Version 2.21

Tweaked an import to avoid a fatal exception under Python 2, in case
anyone is still using it.

2023 November 13 — Version 2.20

Each segment is now protected by a lock, in case two threads
simultaneously trigger the code that performs the initial load of the
segment’s data; the symptom was a rare exception ValueError: cannot reshape array.

2023 September 6 — Version 2.19

Fixed a bug in the excerpt command that was causing it to truncate
its output when the input ephemeris had more than about two dozen
segments. The command’s output should now include all matching
segments from even a very large ephemeris.
Fixed the excerpt command so the calendar dates specified on the
command line produce Julian dates ending with the fraction .5,
which makes excerpt endpoints more exact.

2022 September 28 — Version 2.18

Added support for big-endian processors, and created a GitHub Actions
CI build that includes both a big- and a little-endian architecture.

2021 December 31 — Version 2.17

Fixed an AttributeError in the excerpt command.

2021 July 3 — Version 2.16

Fixed a ValueError raised in the excerpt command when an
ephemeris segment needs to be entirely skipped because it has no
overlap with the user-specified range of dates.
Added a __version__ constant to the package’s top level.

2020 September 2 — Version 2.15

The excerpt subcommand now accepts a --targets option to save
space by copying only matching segments into the output SPK file.
The Julian day fraction tdb2 is handled even more carefully than
before, providing a smoother delta between successive positions when
the difference between successive times is down around 0.1 µs.

2020 March 26 — Version 2.14

Fall back to plain file I/O on platforms that support fileno() but
that don’t support mmap(), like the Pyodide platform <https://github.com/iodide-project/pyodide>_.

2020 February 22 — Version 2.13

The exception raised when a segment is given a Julian date outside the
segment’s date range is now an instance of the ValueError subclass
OutOfRangeError that reminds the caller of the range of dates
supported by the SPK segment, and carries an array attribute
indicating which input dates were at fault.

2019 December 13 — Version 2.12

Replaced use of NumPy flip() with a reverse slice [::-1] after
discovering the function was a recent addition that some user installs
of NumPy do not support.

2019 December 13 — Version 2.11

Reverse the order in which Chebyshev polynomials are computed to
slightly increase speed, to simplify the code, and in one case
(comparing PCK output to NASA) to gain a partial digit of extra
precision.

2019 December 11 — Version 2.10

Document and release support for .bcp binary PCK kernel files
through the new jplephem.pck module.

2019 January 3 — Version 2.9

Added the load_array() method to the segment class.

2018 July 22 — Version 2.8

Switched to a making a single memory map of the entire file, to avoid
running out of file descriptors when users load an ephemeris with
hundreds of segments.

2018 February 11 — Version 2.7

Expanded the command line tool, most notably with the ability to fetch
over HTTP only those sections of a large ephemeris that cover a
specific range of dates, producing a smaller .bsp file.

2016 December 19 — Version 2.6

Fixed the ability to invoke the module from the command line with
python -m jplephem, and added a test to keep it fixed.

2015 November 9 — Version 2.5

Move fileno() call out of the DAF constructor to support
fetching at least summary information from StringIO objects.

2015 November 1 — Version 2.4

Add Windows compatibility by switching mmap() from using
PAGESIZE to ALLOCATIONGRANULARITY.
Avoid a new NumPy deprecation warning by being careful to use only
integers in the NumPy shape tuple.
Add names "TDB" and "TT" to the names database for DE430.

2015 August 16 — Version 2.3

Added auto-detection and support for old NAIF/DAF kernels like
de405.bsp to the main DAF class itself, instead of requiring
the awkward use of an entirely different alternative class.

2015 August 5 — Version 2.2

You can now invoke jplephem from the command line.
Fixes an exception that was raised for SPK segments with a coefficient
count of only 2, like the DE421 and DE430 segments that provide the
offset of Mercury from the Mercury barycenter.
Supports old NAIF/DAF kernels like de405.bsp.
The SPK() constructor is now simpler, taking a DAF object
instead of an open file. This is considered an internal API change —
the public API is the constructor SPK.open().

2015 February 24 — Version 2.1

Switched from mapping an entire SPK file into memory at once to
memory-mapping each segment separately on demand.

2015 February 8 — Version 2.0

Added support for SPICE SPK kernel files downloaded directly from
NASA, and designated old Python-packaged ephemerides as “legacy.”

2013 November 26 — Version 1.2

Helge Eichhorn fixed the default for the position_and_velocity()
argument tdb2 so it defaults to zero days instead of 2.0 days.
Tests were added to prevent any future regression.

2013 July 10 — Version 1.1

Deprecates the old compute() method in favor of separate
position() and position_and_velocity() methods.
Supports computing position and velocity in two separate phases by
saving a “bundle” of coefficients returned by compute_bundle().
From Marten van Kerkwijk: a second tdb2 time argument, for users
who want to build higher precision dates out of two 64-bit floats.

2013 January 18 — Version 1.0

Initial release

References

The Jet Propulsion Laboratory's “Solar System Dynamics” page introduces
the various options for doing solar system position computations:
http://ssd.jpl.nasa.gov/?ephemerides

Equivalent FORTRAN code for using the ephemerides be found at the same
FTP site: ftp://ssd.jpl.nasa.gov/pub/eph/planets/fortran/

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