Core libraries for the ADAM platform
Project description
Asteroid Institute ADAM Core
A set of shared astrodynamics libraries and utilities.
adam_core
is used by a variety of library and services at Asteroid Institute. Sharing these common classes, types, and conversions amongst our tools ensures consistency and accuracy.
Usage
Orbits
To define an orbit:
from astropy.time import Time
from adam_core.coordinates import KeplerianCoordinates
from adam_core.coordinates import Times
from adam_core.coordinates import Origin
from adam_core.orbits import Orbits
keplerian_elements = KeplerianCoordinates.from_kwargs(
times=Times.from_astropy(
Time([59000.0], scale="tdb", format="mjd")
),
a=[1.0],
e=[0.002],
i=[10.],
raan=[50.0],
ap=[20.0],
M=[30.0],
origin=Origin.from_kwargs(code=["SUN"]),
frame="ecliptic"
)
orbits = Orbits.from_kwargs(
orbit_ids=["1"],
object_ids=["Test Orbit"],
coordinates=keplerian_elements.to_cartesian(),
)
Note that internally, all orbits are stored in Cartesian coordinates. Cartesian coordinates do not have any
singularities and are thus more robust for numerical integration. Any orbital element conversions to Cartesian
can be done on demand by calling to_cartesian()
on the coordinates object.
The underlying orbits class is 2 dimensional and can store elements and covariances for multiple orbits.
from astropy.time import Time
from adam_core.coordinates import KeplerianCoordinates
from adam_core.coordinates import Times
from adam_core.coordinates import Origin
from adam_core.orbits import Orbits
keplerian_elements = KeplerianCoordinates.from_kwargs(
times=Times.from_astropy(
Time([59000.0, 60000.0], scale="tdb", format="mjd")
),
a=[1.0, 3.0],
e=[0.002, 0.0],
i=[10., 30.],
raan=[50.0, 32.0],
ap=[20.0, 94.0],
M=[30.0, 159.0],
origin=Origin.from_kwargs(code=["SUN", "SUN"]),
frame="ecliptic"
)
orbits = Orbits.from_kwargs(
orbit_ids=["1", "2"],
object_ids=["Test Orbit 1", "Test Orbit 2"],
coordinates=keplerian_elements.to_cartesian(),
)
Orbits can be easily converted to a pandas DataFrame:
orbits.to_dataframe()
orbit_ids object_ids times.jd1 times.jd2 x y z vx vy vz ... cov_vy_y cov_vy_z cov_vy_vx cov_vy_vy cov_vz_x cov_vz_y cov_vz_z cov_vz_vx cov_vz_vy cov_vz_vz
0 1 Test Orbit 1 2459000.0 0.5 -0.166403 0.975273 0.133015 -0.016838 -0.003117 0.001921 ... NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
1 2 Test Orbit 2 2460000.0 0.5 0.572777 -2.571820 -1.434457 0.009387 0.002900 -0.001452 ... NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
Orbits can also be defined with uncertainties.
import numpy as np
from astropy.time import Time
from adam_core.coordinates import KeplerianCoordinates
from adam_core.coordinates import Times
from adam_core.coordinates import Origin
from adam_core.coordinates import CoordinateCovariances
from adam_core.orbits import Orbits
keplerian_elements = KeplerianCoordinates.from_kwargs(
times=Times.from_astropy(
Time([59000.0], scale="tdb", format="mjd")
),
a=[1.0],
e=[0.002],
i=[10.],
raan=[50.0],
ap=[20.0],
M=[30.0],
covariances=CoordinateCovariances.from_sigmas(
np.array([[0.002, 0.001, 0.01, 0.01, 0.1, 0.1]])
),
origin=Origin.from_kwargs(code=["SUN"]),
frame="ecliptic"
)
orbits = Orbits.from_kwargs(
orbit_ids=["1"],
object_ids=["Test Orbit with Uncertainties"],
coordinates=keplerian_elements.to_cartesian(),
)
orbits.to_dataframe(sigmas=True)
orbit_ids object_ids times.jd1 times.jd2 x y z vx vy vz ... cov_vy_y cov_vy_z cov_vy_vx cov_vy_vy cov_vz_x cov_vz_y cov_vz_z cov_vz_vx cov_vz_vy cov_vz_vz
0 1 Test Orbit with Uncertainties 2459000.0 0.5 -0.166403 0.975273 0.133015 -0.016838 -0.003117 0.001921 ... 3.625729e-08 -1.059731e-08 -9.691716e-11 1.872922e-09 1.392222e-08 -1.759744e-09 -1.821839e-09 -7.865582e-11 2.237521e-10 3.971297e-11
To query orbits from JPL Horizons:
from astropy.time import Time
from adam_core.orbits.query import query_horizons
times = Time([60000.0], scale="tdb", format="mjd")
object_ids = ["Duende", "Eros", "Ceres"]
orbits = query_horizons(object_ids, times)
To query orbits from JPL SBDB:
from adam_core.orbits.query import query_sbdb
object_ids = ["Duende", "Eros", "Ceres"]
orbits = query_sbdb(object_ids)
Orbital Element Conversions
Orbital elements can be accessed via the corresponding attribute. All conversions, including covariances, are done on demand and stored.
# Cartesian Elements
orbits.coordinates
# To convert to other representations
cometary_elements = orbits.coordinates.to_cometary()
keplerian_elements = orbits.coordinates.to_keplerian()
spherical_elements = orbits.coordinates.to_spherical()
Propagator
The propagator class in adam_core
provides a generalized interface to the supported orbit integrators and ephemeris generators. By default,
adam_core
ships with PYOORB.
To propagate orbits with PYOORB (here we grab some orbits from Horizons first):
import numpy as np
from astropy.time import Time
from astropy import units as u
from adam_core.orbits.query import query_horizons
from adam_core.propagator import PYOORB
# Get orbit to propagate
initial_time = Time([60000.0], scale="tdb", format="mjd")
object_ids = ["Duende", "Eros", "Ceres"]
orbits = query_horizons(object_ids, initial_time)
# Make sure PYOORB is ready
propagator = PYOORB()
# Define propagation times
times = initial_time + np.arange(0, 100) * u.d
# Propagate orbits! This function supports multiprocessing for large
# propagation jobs.
propagated_orbits = propagator.propagate_orbits(
orbits,
times,
chunk_size=100,
num_jobs=1,
)
Low-level APIs
Getting the heliocentric ecliptic state vector of a DE440 body at a given set of times (in this case the barycenter of the Jovian system):
import numpy as np
from astropy.time import Time
from adam_core.coordinates.origin import OriginCodes
from adam_core.utils.spice import get_perturber_state
states = get_perturber_state(
OriginCodes.JUPITER_BARYCENTER,
Time(np.arange(59000, 60000), format="mjd", scale="tdb"),
frame="ecliptic",
origin=OriginCodes.SUN,
)
Package Structure
adam_core
├── constants.py # Shared constants
├── coordinates # Coordinate classes and transformations
├── dynamics # Numerical solutions
├── orbits # Orbits class and query utilities
└── utils # Utility classes like Indexable or conversions like times_from_df
Installation
ADAM Core is available on PyPI
pip install adam_core
Development
Development is made easy with our Docker container environment.
# Build the container
docker compose build
# Run tests in the container
docker compose run adam_core pytest .
# Run a shell in the container
docker compose run adam_core bash
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