JPL Horizons Queries (astroquery.jplhorizons/astroquery.solarsystem.jpl.horizons)¶
Warning
The default search behavior has changed. In v0.4.3 and earlier, the default
id_type was 'smallbody'. With v0.4.4, the default is None, which
implements JPL Horizons’s default behavior: search major bodies
first, and if no major bodies are found, then search small bodies.
Note
Due to serverside changes the jplhorizons module requires astroquery v0.4.1 or newer.
Previous versions are not expected to function, please upgrade the package if you observe any issues.
Overview¶
The HorizonsClass class provides an
interface to services provided by the Solar System Dynamics group at
the Jet Propulation Laboratory.
Because of its relevance to Solar System science, this service can
also be accessed from the topical submodule
astroquery.solarsystem.jpl. The functionality of that service is
identical to the one presented here.
In order to query information for a specific Solar System body, a
Horizons object has to be instantiated:
>>> from astroquery.jplhorizons import Horizons
>>> obj = Horizons(id='Ceres', location='568', epochs=2458133.33546)
>>> print(obj)
JPLHorizons instance "Ceres"; location=568, epochs=[2458133.33546], id_type=None
id refers to the target object and is mandatory. ``str and int values
are valid for all query types. Mapping (e.g. dict) values are valid for
observer (ephemerides) and vectors queries only. str or int values will be
passed directly to Horizons. See the description of the id_type argument below
for how Horizons interprets these values. See the paragraph below the description
of the location argument for valid dict formatting.
location refers to the coordinate center for the ephemeris, which has
slightly different physical interpretations depending on the query type:
observer (ephemerides) queries: observer location
vectors queries: coordinate origin for vectors
elements queries: relative body for orbital elements
str and int values are valid for all query types. Mapping
(e.g. dict) values are valid for observer (ephemerides) and vectors queries only. str or int
arguments will be passed directly to Horizons. See this section of the Horizons
manual for how Horizons interprets coordinate center codes; also note that,
unlike id, these include (most) MPC Observatory codes. See below for valid
dict formatting. The default is location=None, which uses Earth body center
for observer queries, and Sun body center for orbital elements and vectors queries.
dict-like arguments to id or location define a topocentric location
relative to a major body. Note that this is not possible for elements queries,
and will only work for bodies with defined rotation models (Horizons does not
have rotation models for many small or recently-discovered natural satellites).
The dictionary has to be formatted as follows: {'lon': longitude in degrees,
'lat': latitude in degrees (North positive, South negative), 'elevation':
elevation in km above the reference ellipsoid, body: Horizons ID of center body,
optional; default Earth}.
Horizons always interprets longitude values as eastward. However, there are two
major gotchas in this:
1. For most prograde rotators, which is to say most major bodies, Horizons
interprets west-longitude as positive and east-longitude as negative. However, values
must still be entered in east-longitude, which means they must be negative; Horizons
will raise an error if given any positive longitude value for such bodies. Instead enter
the west-longitude - 360. For instance, a site on Mars (id code 499) at 30 degrees
longitude, 30 degrees latitude, 0 km elevation should be specified as
{'body': 499, 'elevation': 0 * u.km, 'lon': -330 * u.deg, 'lat': 30 * u.deg}.
2. This does not apply to the Earth, Moon, and Sun. Although they are prograde,
Horizons interprets east-longitude as positive and west-longitude as negative for these
bodies.
Here is a complete list of retrograde major bodies in Horizons: Venus (299), Arial (701), Umbriel (702), Titania (703), Oberon (704), Miranda (705), Cordelia (706), Ophelia (707), Bianca (708), Cressida (709), Desdemona (710), Juliet (711), Portia (712), Rosalind (713), Belinda (714), Puck (715), Uranus (799), Triton (801). All other major bodies are prograde.
Two examples of usage for specified topocentric coordinates follow.
1. This observer (ephemerides) query uses the coordinates of the Statue of Liberty
as the observer’s location, and Ceres as the target:
>>> import astropy.units as u
>>> statue_of_liberty = {'lon': -74.0466891 * u.deg,
... 'lat': 40.6892534 * u.deg,
... 'elevation': 0.093 * u.km}
>>> obj = Horizons(id='Ceres',
... location=statue_of_liberty,
... epochs=2458133.33546)
>>> print(obj)
JPLHorizons instance "Ceres"; location={'lon': <Quantity -74.0466891 deg>, 'lat': <Quantity 40.6892534 deg>, 'elevation': <Quantity 0.093 km>, 'body': 399}, epochs=[2458133.33546], id_type=None
2. Specifying topocentric coordinates for both location and observer is often
useful when performing geometric calculations for artificial satellites without
completely-specified ephemeris data. For instance, published reduced data for the
lunar satellite Chang’e-2 include orbital height and lat/lon. Although there is no published
ephemeris for Chang’e-2, Horizons (combined with the fact that Chang’e-2 looked nadir),
can be used to compute vectors from Chang’e-2 to specific points on the lunar surface.
Here is an example of using jplhorizons to find the distance from Chang’e-2
at a particular point in time to the center of the crater Double:
>>> ce_2 = {'lon': 23.522 * u.deg, 'lat': 0.637 * u.deg, 'elevation': 181.2 * u.km, 'body': 301}
>>> double = {'lon': 23.47 * u.deg, 'lat': 0.67 * u.deg, 'elevation': 0 * u.km, 'body': 301}
>>> obj = Horizons(id=double, location=ce_2, epochs=2454483.84247)
>>> vecs = obj.vectors()
>>> distance_km = (vecs['x'] ** 2 + vecs['y'] ** 2 + vecs['z'] ** 2) ** 0.5 * 1.496e8
>>> print(f"{distance_km.value.data[0]:.3f}")
181.213
epochs is either a scalar or list of Julian dates (floats or strings) in the
case of discrete epochs, or, in the case of a range of epochs, a dictionary that
has to include the keywords start, stop (both using the following format
“YYYY-MM-DD [HH:MM:SS]”), and step (e.g., '1m' for one minute,
'3h' three hours, '10d' for ten days). Note that all input epochs, both
calendar dates/times and Julian Dates, refer to UTC for ephemerides queries, TDB
for element queries and vector queries. By default, epochs=None, which uses
the current date and time.
id_type controls how Horizons resolves the ‘id’
to match a Solar System body:
|
Query behavior |
|---|---|
|
Searches major bodies (planets, natural satellites, spacecraft, special cases) first, and if none are found, then searches small bodies. |
|
Limits the search to small solar system bodies (comets and asteroids). |
|
Limits the search to small body designations, e.g., 73P or 2014 MU69. |
|
Limits the search to asteroid or comet names, e.g., Halley will match 1P/Halley and (2688) Halley. |
|
Limits the search to asteroid names, e.g., Don Quixote. |
|
Limits the search to comet names, e.g., Encke will only match comet 2P/Encke, and not (9134) Encke. |
In the case of ambiguities in the name resolution, a list of matching objects
will be provided. In order to select an object from this list, provide the
respective id number or record number as id and use id_type=None:
>>> from astroquery.jplhorizons import Horizons
>>> print(Horizons(id='Encke').ephemerides())
Traceback (most recent call last):
...
ValueError: Ambiguous target name; provide unique id:
Record # Epoch-yr Primary Desig >MATCH NAME<
-------- -------- ------------- -------------------------
9134 4822 P-L Encke
90000031 1786 2P Encke
90000032 1796 2P Encke
90000033 1805 2P Encke
... ... ... ...
>>> print(Horizons(id='90000034', id_type=None).ephemerides())
targetname datetime_str datetime_jd ... RA_3sigma DEC_3sigma
--- --- d ... arcsec arcsec
---------- ------------------------ ----------------- ... --------- ----------
2P/Encke 2018-Jan-17 05:06:07.709 2458135.712589224 ... -- --
The JPL Horizons system provides ephemerides, orbital elements, and state
vectors for almost all known Solar System bodies. These queries are provided
through three functions:
ephemerides(),
elements(), and
vectors().
Ephemerides¶
ephemerides() returns ephemerides
for a given observer location (location) and epoch or range of epochs
(epochs) in the form of an astropy table. The following example queries the
ephemerides of asteroid (1) Ceres for a range of dates as seen from Mauna Kea:
>>> from astroquery.jplhorizons import Horizons
>>> obj = Horizons(id='Ceres', location='568',
... epochs={'start':'2010-01-01', 'stop':'2010-03-01',
... 'step':'10d'})
>>> eph = obj.ephemerides()
>>> print(eph)
targetname datetime_str datetime_jd ... alpha_true PABLon PABLat
--- --- d ... deg deg deg
----------------- ----------------- ----------- ... ---------- -------- ------
1 Ceres (A801 AA) 2010-Jan-01 00:00 2455197.5 ... 12.3609 238.2494 4.5532
1 Ceres (A801 AA) 2010-Jan-11 00:00 2455207.5 ... 14.1057 241.3339 4.2832
1 Ceres (A801 AA) 2010-Jan-21 00:00 2455217.5 ... 15.7313 244.3394 4.0089
1 Ceres (A801 AA) 2010-Jan-31 00:00 2455227.5 ... 17.2067 247.2518 3.7289
1 Ceres (A801 AA) 2010-Feb-10 00:00 2455237.5 ... 18.5029 250.0576 3.4415
1 Ceres (A801 AA) 2010-Feb-20 00:00 2455247.5 ... 19.5814 252.7383 3.1451
The following fields are available for each ephemerides query:
>>> print(eph.columns)
<TableColumns names=('targetname','datetime_str','datetime_jd','H','G','solar_presence','lunar_presence','RA','DEC','RA_app','DEC_app','RA_rate','DEC_rate','AZ','EL','AZ_rate','EL_rate','sat_X','sat_Y','sat_PANG','siderealtime','airmass','magextinct','V','surfbright','illumination','illum_defect','sat_sep','sat_vis','ang_width','PDObsLon','PDObsLat','PDSunLon','PDSunLat','SubSol_ang','SubSol_dist','NPole_ang','NPole_dist','EclLon','EclLat','r','r_rate','delta','delta_rate','lighttime','vel_sun','vel_obs','elong','elongFlag','alpha','lunar_elong','lunar_illum','sat_alpha','sunTargetPA','velocityPA','OrbPlaneAng','constellation','TDB-UT','ObsEclLon','ObsEclLat','NPole_RA','NPole_DEC','GlxLon','GlxLat','solartime','earth_lighttime','RA_3sigma','DEC_3sigma','SMAA_3sigma','SMIA_3sigma','Theta_3sigma','Area_3sigma','RSS_3sigma','r_3sigma','r_rate_3sigma','SBand_3sigma','XBand_3sigma','DoppDelay_3sigma','true_anom','hour_angle','alpha_true','PABLon','PABLat')>
The values in these columns are the same as those defined in the Horizons
Definition of Observer Table Quantities; names have been simplified in a few
cases. Quantities H and G are the target’s Solar System absolute
magnitude and photometric phase curve slope, respectively. In the case of
comets, H and G are replaced by M1, M2, k1, k2, and
phasecoeff; please refer to the Horizons documentation for definitions.
Optional parameters of ephemerides()
correspond to optional features of the Horizons system: airmass_lessthan
sets an upper limit to airmass, solar_elongation enables the definition of a
solar elongation range, max_hour_angle sets a cutoff of the hour angle,
skip_daylight=True rejects epochs during daylight, rate_cutoff rejects
targets with sky motion rates higher than provided (in units of arcsec/h),
refraction accounts for refraction in the computation of the ephemerides
(disabled by default), and refsystem defines the coordinate reference system
used (ICRF by default). For comets, the options closest_apparition and
no_fragments are available, which selects the closest apparition in time and
limits fragment matching (73P-B would only match 73P-B), respectively. Note
that these options should only be used for comets and will crash the query for
other object types. Extra precision in the queried properties can be requested
using the extra_precision option. Furthermore, get_query_payload=True
skips the query and only returns the query payload. To pass additional settings
to the request use the optional_settings passing a key-value
dictionary.
ephemerides() queries by default most
available quantities from the JPL Horizons servers. This might take a while. If
you are only interested in a subset of the available quantities, you can query
only those. The corresponding optional parameter to be set is quantities.
This parameter uses the same numerical codes as JPL Horizons defined in the JPL
Horizons User Manual Definition of Observer Table Quantities. For instance,
if you only want to query astrometric RA and Dec, you can use quantities=1;
if you only want the heliocentric and geocentric distances, you can use
quantities='19,20' (note that in this case a string with comma-separated
codes has to be provided).
Orbital elements¶
elements() returns orbital elements
relative to some Solar System body (location, referred to as “CENTER” in
Horizons) and for a given epoch or a range of epochs (epochs) in the form of
an astropy table. The following example queries the osculating elements of
asteroid (433) Eros for a given date relative to the Sun:
>>> from astroquery.jplhorizons import Horizons
>>> obj = Horizons(id='433', location='500@10',
... epochs=2458133.33546)
>>> el = obj.elements()
>>> print(el)
targetname datetime_jd ... Q P
--- d ... AU d
------------------ ------------- ... ---------------- ----------------
433 Eros (A898 PA) 2458133.33546 ... 1.78244269692907 642.938735130819
The following fields are queried:
>>> print(el.columns)
<TableColumns names=('targetname','datetime_jd','datetime_str','H','G','e','q','incl','Omega','w','Tp_jd','n','M','nu','a','Q','P')>
Optional parameters of elements()
include refsystem, which defines the coordinate reference system used (ICRF
by default), refplane which defines the reference plane of the orbital
elements queried, and tp_type, which switches between a relative and
absolute representation of the time of perihelion passage. For comets, the
options closest_apparition and no_fragments are available, which select
the closest apparition in time and reject fragments, respectively. Note that
these options should only be used for comets and will crash the query for other
object types. Also available is get_query_payload=True, which skips the
query and only returns the query payload.
Vectors¶
vectors() returns the
state vector of the target body in cartesian coordinates relative to
some Solar System body (location, referred to as “CENTER” in
Horizons) and for a given epoch or a range of epochs (epochs) in
the form of an astropy table. The following example queries the state
vector of asteroid 2012 TC4 as seen from Goldstone for a range of
epochs:
>>> from astroquery.jplhorizons import Horizons
>>> obj = Horizons(id='2012 TC4', location='257',
... epochs={'start':'2017-10-01', 'stop':'2017-10-02',
... 'step':'10m'})
>>> vec = obj.vectors()
>>> print(vec)
targetname datetime_jd ... range range_rate
--- d ... AU AU / d
---------- ----------------- ... ------------------- ---------------------
(2012 TC4) 2458027.5 ... 0.04293321034545636 -0.004080187115743425
(2012 TC4) 2458027.506944444 ... 0.04290487470540343 -0.004080407262389858
(2012 TC4) 2458027.513888889 ... 0.04287653899449449 -0.004080207473059529
... ... ... ... ...
(2012 TC4) 2458028.486111111 ... 0.03913618646225701 -0.004062675741730004
(2012 TC4) 2458028.493055556 ... 0.0391079700901548 -0.004063569819149637
(2012 TC4) 2458028.5 ... 0.03907974896127458 -0.004064045433438098
Length = 145 rows
The following fields are queried:
>>> print(vec.columns)
<TableColumns names=('targetname','datetime_jd','datetime_str','H','G','x','y','z','vx','vy','vz','lighttime','range','range_rate')>
Similar to the other HorizonsClass functions,
optional parameters of vectors() is
get_query_payload=True, which skips the query and only returns the query
payload. For comets, the options closest_apparation and
no_fragments are available, which select the closest apparition in time and
reject fragments, respectively. Note that these options should only be used for
comets and will crash the query for other object types. Options aberrations
and delta_T provide different choices for aberration corrections as well as
a measure for time-varying differences between TDB and UT time-scales,
respectively.
How to Use the Query Tables¶
Table objects created by the query functions are extremely versatile
and easy to use. Since all query functions return the same type of table, they
can all be used in the same way.
We provide some examples to illustrate how to use them based on the following JPL Horizons ephemerides query of near-Earth asteroid (3552) Don Quixote since its year of Discovery:
>>> from astroquery.jplhorizons import Horizons
>>> obj = Horizons(id='3552', location='568',
... epochs={'start':'2010-01-01', 'stop':'2019-12-31',
... 'step':'1y'})
>>> eph = obj.ephemerides()
As we have seen before, we can display a truncated version of table
eph by simply using
>>> print(eph)
targetname datetime_str ... PABLon PABLat
--- --- ... deg deg
-------------------------- ----------------- ... -------- --------
3552 Don Quixote (1983 SA) 2010-Jan-01 00:00 ... 8.0371 18.9349
3552 Don Quixote (1983 SA) 2011-Jan-01 00:00 ... 85.4082 34.5611
3552 Don Quixote (1983 SA) 2012-Jan-01 00:00 ... 109.2959 30.3834
3552 Don Quixote (1983 SA) 2013-Jan-01 00:00 ... 123.0777 26.136
3552 Don Quixote (1983 SA) 2014-Jan-01 00:00 ... 133.9392 21.8962
3552 Don Quixote (1983 SA) 2015-Jan-01 00:00 ... 144.2701 17.1908
3552 Don Quixote (1983 SA) 2016-Jan-01 00:00 ... 156.1007 11.1447
3552 Don Quixote (1983 SA) 2017-Jan-01 00:00 ... 174.0245 1.3487
3552 Don Quixote (1983 SA) 2018-Jan-01 00:00 ... 228.9956 -21.6723
3552 Don Quixote (1983 SA) 2019-Jan-01 00:00 ... 45.1979 32.3885
Please note the formatting of this table, which is done automatically. Above the
dashes in the first two lines, you have the column name and its unit. Every
column is assigned a unit from astropy.units. We will learn later how to use
these units.
Columns¶
We can get at list of all the columns in this table with:
>>> print(eph.columns)
<TableColumns names=('targetname','datetime_str','datetime_jd','H','G','solar_presence','lunar_presence','RA','DEC','RA_app','DEC_app','RA_rate','DEC_rate','AZ','EL','AZ_rate','EL_rate','sat_X','sat_Y','sat_PANG','siderealtime','airmass','magextinct','V','surfbright','illumination','illum_defect','sat_sep','sat_vis','ang_width','PDObsLon','PDObsLat','PDSunLon','PDSunLat','SubSol_ang','SubSol_dist','NPole_ang','NPole_dist','EclLon','EclLat','r','r_rate','delta','delta_rate','lighttime','vel_sun','vel_obs','elong','elongFlag','alpha','lunar_elong','lunar_illum','sat_alpha','sunTargetPA','velocityPA','OrbPlaneAng','constellation','TDB-UT','ObsEclLon','ObsEclLat','NPole_RA','NPole_DEC','GlxLon','GlxLat','solartime','earth_lighttime','RA_3sigma','DEC_3sigma','SMAA_3sigma','SMIA_3sigma','Theta_3sigma','Area_3sigma','RSS_3sigma','r_3sigma','r_rate_3sigma','SBand_3sigma','XBand_3sigma','DoppDelay_3sigma','true_anom','hour_angle','alpha_true','PABLon','PABLat')>
We can address each column individually by indexing it using its name as provided in this list. For instance, we can get all RAs for Don Quixote by using
>>> print(eph['RA'])
RA
deg
---------
345.50204
78.77158
119.85659
136.60021
147.44947
156.58967
166.32129
180.6992
232.11974
16.1066
This column is formatted like the entire table; it has a column name and a unit. We can select several columns at a time, for instance RA and DEC for each epoch
>>> print(eph['datetime_str', 'RA', 'DEC'])
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, let’s calculate the total rate of the object by summing ‘RA_rate’ and ‘DEC_rate’ in quadrature:
>>> import numpy as np
>>> print(np.sqrt(eph['RA_rate']**2 + eph['DEC_rate']**2))
dRA*cosD
------------------
86.18728068796985
26.337249029653798
21.520859656742434
17.679843758686584
14.775809055378625
11.874886005626538
7.183281978025435
7.295600209387093
94.84824546372009
23.952470898018017
Please note that the column name is wrong (copied from the name of the first column used), and that the unit is lost.
Units¶
Columns have units assigned to them. For instance, the RA column has
the unit deg assigned to it, i.e., degrees. More complex units are
available, too, e.g., the RA_rate column is expressed in arcsec /
h - arcseconds per hour:
>>> print(eph['RA_rate'])
RA_rate
arcsec / h
----------
72.35438
-23.8239
-20.7151
-15.5509
-12.107
-9.32616
-5.80004
3.115853
85.22719
19.02548
The unit of this column can be easily converted to any other unit describing the
same dimensions. For instance, we can turn RA_rate into arcsec / s:
>>> eph['RA_rate'].convert_unit_to('arcsec/s')
>>> print(eph['RA_rate'])
RA_rate
arcsec / s
----------------------
0.02009843888888889
-0.0066177499999999995
-0.005754194444444445
-0.004319694444444445
-0.0033630555555555553
-0.0025905999999999998
-0.0016111222222222222
0.0008655147222222222
0.023674219444444443
0.005284855555555556
Please refer to the astropy.table and astropy.units documentations for
more information.
Hints and Tricks¶
Checking the original JPL Horizons output¶
Once either of the query methods has been called, the retrieved raw response is
stored in the attribute raw_response. Inspecting this response can help to
understand issues with your query, or you can process the results differently.
For all query types, the query URI (the URI is what you would put into the URL
field of your web browser) that is used to request the data from the JPL
Horizons server can be obtained from the
HorizonsClass object after a query has been
performed (before the query only None would be returned):
>>> print(obj.uri)
https://ssd.jpl.nasa.gov/api/horizons.api?format=text&EPHEM_TYPE=OBSERVER&QUANTITIES=%271%2C2%2C3%2C4%2C5%2C6%2C7%2C8%2C9%2C10%2C11%2C12%2C13%2C14%2C15%2C16%2C17%2C18%2C19%2C20%2C21%2C22%2C23%2C24%2C25%2C26%2C27%2C28%2C29%2C30%2C31%2C32%2C33%2C34%2C35%2C36%2C37%2C38%2C39%2C40%2C41%2C42%2C43%27&COMMAND=%223552%22&SOLAR_ELONG=%220%2C180%22&LHA_CUTOFF=0&CSV_FORMAT=YES&CAL_FORMAT=BOTH&ANG_FORMAT=DEG&APPARENT=AIRLESS&REF_SYSTEM=ICRF&EXTRA_PREC=NO&CENTER=%27568%27&START_TIME=%222010-01-01%22&STOP_TIME=%222019-12-31%22&STEP_SIZE=%221y%22&SKIP_DAYLT=NO
If your query failed, it might be useful for you to put the URI into a web
browser to get more information why it failed. Please note that uri is an
attribute of HorizonsClass and not the results
table.
Date Formats¶
JPL Horizons puts somewhat strict guidelines on the date formats: individual
epochs have to be provided as Julian dates, whereas epoch ranges have to be
provided as ISO dates (YYYY-MM-DD HH-MM UT). If you have your epoch dates in one
of these formats but you need the other format, make use of
astropy.time.Time for the conversion. An example is provided here:
>>> from astropy.time import Time
>>> mydate_fromiso = Time('2018-07-23 15:55:23') # pass date as string
>>> print(mydate_fromiso.jd) # convert Time object to Julian date
2458323.163460648
>>> mydate_fromjd = Time(2458323.163460648, format='jd')
>>> print(mydate_fromjd.iso) # convert Time object to ISO
2018-07-23 15:55:23.000
astropy.time.Time allows you to convert dates across a wide range of
formats. Please note that when reading in Julian dates, you have to specify the
date format as 'jd', as number passed to Time is
ambiguous.
Keep Queries Short¶
Keep in mind that queries are sent as URIs to the Horizons server. If you query a large number of epochs (in the form of a list), this list might be truncated as URIs are typically expected to be shorter than 2,000 symbols and your results might be compromised. If your query URI is longer than this limit, a warning is given. In that case, please try using a range of dates instead of a list of individual dates.
Reference Frames¶
The coordinate reference frame for Horizons output is controlled by the
refplane and refsystem keyword arguments. See the Horizons
documentation for details. Some output reference frames are included in
astropy’s coordinates:
Method |
|
|
|
astropy frame |
|---|---|---|---|---|
|
|
|
N/A |
|
|
|
|
N/A |
|
|
|
|
N/A |
|
For example, get the barycentric coordinates of Jupiter as an astropy
SkyCoord object:
>>> from astropy.coordinates import SkyCoord
>>> from astropy.time import Time
>>> from astroquery.jplhorizons import Horizons
>>> epoch = Time('2021-01-01')
>>> q = Horizons('599', location='@0', epochs=epoch.tdb.jd)
>>> tab = q.vectors(refplane='earth')
>>> c = SkyCoord(tab['x'].quantity, tab['y'].quantity, tab['z'].quantity,
... representation_type='cartesian', frame='icrs',
... obstime=epoch)
>>> print(c)
<SkyCoord (ICRS): (x, y, z) in AU
[(3.03483263, -3.72503309, -1.67054586)]>
Acknowledgements¶
This submodule makes use of the JPL Horizons system.
The development of this submodule is in part funded through NASA PDART Grant No. 80NSSC18K0987 to the sbpy project.
Troubleshooting¶
If you are repeatedly getting failed queries, or bad/out-of-date results, try clearing your cache:
>>> from astroquery.jplhorizons import Horizons
>>> Horizons.clear_cache()
If this function is unavailable, upgrade your version of astroquery.
The clear_cache function was introduced in version 0.4.7.dev8479.
Reference/API¶
astroquery.jplhorizons Package¶
JPLHorizons¶
- author:
Michael Mommert (mommermiscience@gmail.com)
Classes¶
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Configuration parameters for |