Skip to main content

ADAM Core Propagator class using ASSIST

Project description

adam-assist

PyPI - Version PyPI - Python Version


Table of Contents

Overview

adam-assist is a pluggable propagator class for the adam-core package that uses ASSIST for propagating orbits.

Installation

pip install adam-assist

Usage

Propagating Orbits

Here we initialize a set of adam_core.orbit.Orbit objects from the JPL Small Bodies Database and propagate them using the AdamAssistPropagator class. You can manually initialize the orbits as well.

from adam_core.orbits.query.sbdb import query_sbdb
from adam_core.time import Timestamp
from adam_assist import ASSISTPropagator

# Query the JPL Small Bodies Database for a set of orbits
sbdb_orbits = query_sbdb(["2020 AV2", "A919 FB", "1993 SB"])
times = Timestamp.from_mjd([60000, 60365, 60730], scale="tdb")


propagator = ASSISTPropagator()

propagated = propagator.propagate_orbits(sbdb_orbits, times)

Of course you can define your own orbits as well.

import pyarrow as pa
from adam_core.orbits import Orbit
from adam_core.coordinates import CartesianCoordinates, Origin
from adam_core.time import Timestamp
from adam_assist import ASSISTPropagator

# Define an orbit
orbits = Orbit.from_kwargs(
  orbit_id=["1", "2", "3"],
  coordinates=CartesianCoordinates.from_kwargs(
    # use realistic cartesian coords in AU and AU/day
    x=[-1.0, 0.0, 1.0],
    y=[-1.0, 0.0, 1.0],
    z=[-1.0, 0.0, 1.0],
    vx=[-0.1, 0.0, 0.1],
    vy=[-0.1, 0.0, 0.1],
    vz=[-0.1, 0.0, 0.1],
    time=Timestamp.from_mjd([60000, 60365, 60730], scale="tdb"),
    origin=Origin.from_kwargs(code=pa.repeat("SUN", 3)),
    frame="eliptic"
  ),
)

propagator = ASSISTPropagator()

propagated = propagator.propagate_orbits(orbits)

Generating Ephemerides

The ASSISTPropagator class uses the adam-core default ephemeris generator to generate ephemerides from the ASSIST propagated orbits. The default ephemeris generator accounts for light travel time and aberration. See adam_core.propagator.propagator.EphemerisMixin for implementation details.

from adam_core.orbits.query.sbdb import query_sbdb
from adam_core.time import Timestamp
from adam_core.observers import Observers
from adam_assist import ASSISTPropagator

# Query the JPL Small Bodies Database for a set of orbits
sbdb_orbits = query_sbdb(["2020 AV2", "A919 FB", "1993 SB"])
times = Timestamp.from_mjd([60000, 60365, 60730], scale="utc")
observers = Observers.from_code("399", times)
propagator = ASSISTPropagator()

ephemerides = propagator.generate_ephemeris(sbdb_orbits, observers)

Configuration

When initializing the ASSISTPropagator, you can configure several parameters that control the integration. These parameters are passed directly to REBOUND's IAS15 integrator. The IAS15 integrator is a high accuracy integrator that uses adaptive timestepping to maintain precision while optimizing performance.

  • min_dt: Minimum timestep for the integrator (default: 1e-12 days)
  • initial_dt: Initial timestep for the integrator (default: 0.001 days)
  • epsilon: Controls the adaptive timestep behavior (default: 1e-6)
  • adaptive_mode: Controls the adaptive timestep behavior (default: 1)

These parameters are passed directly to REBOUND's IAS15 integrator. The IAS15 integrator is a high accuracy integrator that uses adaptive timestepping to maintain precision while optimizing performance.

Example:

propagator = ASSISTPropagator(
  min_dt=1e-12,
  initial_dt=0.0001,
  epsilon=1e-6,
  adaptive_mode=1
)

When initializing the ASSISTPropagator, you can configure several parameters that control the integration. These parameters are passed directly to REBOUND's IAS15 integrator. The IAS15 integrator is a high accuracy integrator that uses adaptive timestepping to maintain precision while optimizing performance.

Default SPK Files

The asteroids SPK file sb441-n16.bsp contains the 16 largest asteroids in the solar system. They are listed here by number for reference:

1 Ceres 3 Juno 4 Vesta 7 Iris 10 Hygiea 15 Eunomia 16 Psyche 31 Euphrosyne 52 Europa 65 Cybele 70 Panopaea 87 Sylvia 88 Thisbe 107 Camilla 511 Davida 704 Interamnia

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

adam_assist-0.3.3.tar.gz (27.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

adam_assist-0.3.3-py3-none-any.whl (17.8 kB view details)

Uploaded Python 3

File details

Details for the file adam_assist-0.3.3.tar.gz.

File metadata

  • Download URL: adam_assist-0.3.3.tar.gz
  • Upload date:
  • Size: 27.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: pdm/2.25.6 CPython/3.12.11 Darwin/23.6.0

File hashes

Hashes for adam_assist-0.3.3.tar.gz
Algorithm Hash digest
SHA256 10dcf3554c2fe161831239e2db1faadad291427b6068f9b891c7abad98f0a44d
MD5 9121903809749691c93140baa7b09d97
BLAKE2b-256 60f7c375bfa95292333c7cce16ee05af76c5bbcda498d06d996958f9b7c33a25

See more details on using hashes here.

File details

Details for the file adam_assist-0.3.3-py3-none-any.whl.

File metadata

  • Download URL: adam_assist-0.3.3-py3-none-any.whl
  • Upload date:
  • Size: 17.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: pdm/2.25.6 CPython/3.12.11 Darwin/23.6.0

File hashes

Hashes for adam_assist-0.3.3-py3-none-any.whl
Algorithm Hash digest
SHA256 ffa7c762b97e6042d240606e2412b8fe64b3a65c41d4e66ce711ac56375443a7
MD5 e9fb8517237b2033590cd2f7d5d5d1f1
BLAKE2b-256 7bd701cf46578da73fe650f25870dfe46bc788daab45f8ae707a58467257db7b

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page