essos.dynamics¶

Attributes¶

`mesh`
`spec`
`spec_index`
`sharding`
`sharding_index`

Classes¶

`Particles`
`Tracing`

Functions¶

`gc_to_fullorbit`(field, initial_xyz, initial_vparallel, ...)	Computes full orbit positions for given guiding center positions,
`GuidingCenterCollisionsDiffusionMu`(→ jax.numpy.ndarray)
`GuidingCenterCollisionsDriftMuStratonovich`(...)
`GuidingCenterCollisionsDriftMuIto`(→ jax.numpy.ndarray)
`GuidingCenterCollisionsDiffusion`(→ jax.numpy.ndarray)
`GuidingCenterCollisionsDrift`(→ jax.numpy.ndarray)
`GuidingCenter`(→ jax.numpy.ndarray)
`LorentzCollisionsDiffusion`(→ jax.numpy.ndarray)
`LorentzCollisionsDrift`(→ jax.numpy.ndarray)
`Lorentz`(→ jax.numpy.ndarray)
`FieldLine`(→ jax.numpy.ndarray)

Module Contents¶

essos.dynamics.mesh¶

essos.dynamics.spec¶

essos.dynamics.spec_index¶

essos.dynamics.sharding¶

essos.dynamics.sharding_index¶

essos.dynamics.gc_to_fullorbit(field, initial_xyz, initial_vparallel, total_speed, mass, charge, phase_angle_full_orbit=0)¶: Computes full orbit positions for given guiding center positions, parallel speeds, and total velocities using JAX for efficiency.

class essos.dynamics.Particles(initial_xyz=None, initial_vparallel_over_v=None, charge=ALPHA_PARTICLE_CHARGE, mass=ALPHA_PARTICLE_MASS, energy=FUSION_ALPHA_PARTICLE_ENERGY, min_vparallel_over_v=-1, max_vparallel_over_v=1, field=None, initial_vxvyvz=None, initial_xyz_fullorbit=None)¶

charge¶

mass¶

energy¶

initial_xyz¶

nparticles¶

initial_xyz_fullorbit = None¶

initial_vxvyvz = None¶

phase_angle_full_orbit = 0¶

particle_index¶

random_keys¶

total_speed¶

initial_vparallel¶

initial_vperpendicular¶

to_full_orbit(field)¶

essos.dynamics.GuidingCenterCollisionsDiffusionMu(t, initial_condition, args) → jax.numpy.ndarray¶

essos.dynamics.GuidingCenterCollisionsDriftMuStratonovich(t, initial_condition, args) → jax.numpy.ndarray¶

essos.dynamics.GuidingCenterCollisionsDriftMuIto(t, initial_condition, args) → jax.numpy.ndarray¶

essos.dynamics.GuidingCenterCollisionsDiffusion(t, initial_condition, args) → jax.numpy.ndarray¶

essos.dynamics.GuidingCenterCollisionsDrift(t, initial_condition, args) → jax.numpy.ndarray¶

essos.dynamics.GuidingCenter(t, initial_condition, args) → jax.numpy.ndarray¶

essos.dynamics.LorentzCollisionsDiffusion(t, initial_condition, args) → jax.numpy.ndarray¶

essos.dynamics.LorentzCollisionsDrift(t, initial_condition, args) → jax.numpy.ndarray¶

essos.dynamics.Lorentz(t, initial_condition, args) → jax.numpy.ndarray¶

essos.dynamics.FieldLine(t, initial_condition, field) → jax.numpy.ndarray¶

class essos.dynamics.Tracing(trajectories_input=None, initial_conditions=None, times_to_trace=None, field=None, electric_field=None, model=None, maxtime: float = 1e-07, timestep: int = 1e-08, rtol=1e-07, atol=1e-07, particles=None, condition=None, species=None, tag_gc=1.0, boundary=None, rejected_steps=None)¶

model = None¶

initial_conditions = None¶

times_to_trace = None¶

maxtime = 1e-07¶

timestep = 1e-08¶

rtol = 1e-07¶

atol = 1e-07¶

_trajectories = None¶

particles = None¶

species = None¶

tag_gc = 1.0¶

progress_meter = None¶

trajectories_xyz¶

trace()¶

property trajectories¶

_tree_flatten()¶

classmethod _tree_unflatten(aux_data, children)¶

to_vtk(filename)¶

plot(ax=None, show=True, axis_equal=True, n_trajectories_plot=5, **kwargs)¶

loss_fraction_BioSavart(boundary)¶

loss_fraction(r_max=0.99)¶

loss_fraction_BioSavart_collisions(boundary)¶

loss_fraction_collisions(r_max=0.99)¶

poincare_plot(shifts=[jnp.pi / 2], orientation='toroidal', length=1, ax=None, show=True, color=None, **kwargs)¶

Plot Poincare plots using scipy to find the roots of an interpolation. Can take particle trace or field lines. :param shifts: Apply a linear shift to dependent data. Default is [0]. :type shifts: list, optional :param orientation: ‘toroidal’ - find time values when toroidal angle = shift [0, 2pi].

‘z’ - find time values where z coordinate = shift. Default is ‘toroidal’.

Parameters:

length (float, optional) – A way to shorten data. 1 - plot full length, 0.1 - plot 1/10 of data length. Default is 1.
ax (matplotlib.axes._subplots.AxesSubplot, optional) – Matplotlib axis to plot on. Default is None.
show (bool, optional) – Whether to display the plot. Default is True.
color – Can be time, None or a color to plot Poincaré points
**kwargs – Additional keyword arguments for plotting.

Notes

If the data seem ill-behaved, there may not be enough steps in the trace for a good interpolation.
This will break if there are any NaNs.
Issues with toroidal interpolation: jnp.arctan2(Y, X) % (2 * jnp.pi) causes distortion in interpolation near phi = 0.
Maybe determine a lower limit on resolution needed per toroidal turn for “good” results.

To-Do:

Format colorbars.