pip install galaxComing soon. In the meantime, if you've used gala, then galax should be
familiar!
Let's compute an orbit!
import coordinax as cx
import galax.coordinates as gc
import galax.dynamics as gd
import galax.potential as gp
import jax.numpy as jnp
from unxt import Quantity
w = gc.PhaseSpacePosition(
q=Quantity([8, 0, 0], "kpc"),
p=Quantity([0, 220, 0], "km/s"),
t=Quantity(0, "Myr"),
)
pot = gp.MilkyWayPotential()
orbit = gd.evaluate_orbit(pot, w, Quantity(jnp.linspace(0, 1, 100), "Gyr"))
print(orbit)
# Orbit(
# q=<CartesianPos3D (x[kpc], y[kpc], z[kpc])
# [[ 8. 0. 0. ]
# ...
# [ 7.804 -0.106 0. ]]>,
# p=<CartesianVel3D (d_x[kpc / Myr], d_y[kpc / Myr], d_z[kpc / Myr])
# [[ 0. 0.225 0. ]
# ...
# [ 0.018 0.23 0. ]]>,
# t=Quantity['time'](Array([0., ..., 1000.], dtype=float64), unit='Myr'),
# potential=MilkyWayPotential(...)
# )
orbit_sph = orbit.represent_as(cx.LonLatSphericalPos)
print(orbit_sph)
# Orbit(
# q=<LonLatSphericalPos (lon[rad], lat[deg], distance[kpc])
# [[0.000e+00 3.858e-16 8.000e+00]
# ...
# [6.270e+00 3.858e-16 7.805e+00]]>,
# p=<LonLatSphericalVelocity (d_lon[rad / Myr], d_lat[deg / Myr], d_distance[kpc / Myr])
# [[ 0.028 0. 0. ]
# ...
# [ 0.03 0. 0.015]]>,
# t=Quantity['time'](Array([0., ..., 1000.], dtype=float64), unit='Myr'),
# potential=MilkyWayPotential(...})
# )
If you found this library to be useful in academic work, then please cite.
We welcome contributions!
See the AUTHORS.rst file for a complete list of contributors to the project.
The GalacticDynamics/galax
maintainers would like to thank
@Michael Anckaert for transferring the
galax project domain on PyPI for use by this package. Without
his generosity this package would have had a worse name.