Scipy-based integrators#

Implements integrator based on scipy’s solve_ivp method.

class atomsmltr.simulation.simulator.scipy.ScipyIVP_3D(config: Configuration = None, method: str = 'Radau', **solve_ivp_args)[source]#

Bases: Simulation

A simulation class based on Scipy’s solve_ivp solver

Parameters:

config (Configuration, optional) – the configuration to consider for the simulation
method (str, optional) – method used for the solve_ivp solver, by default “Radau”
**solve_ivp_args – all other arguments are directly passed to solve_ivp

References

https://docs.scipy.org/doc/scipy/reference/generated/scipy.integrate.solve_ivp.html

dudt(t, u)[source]#: should return the derivative of the position/speed vector u

get_force(u)[source]#

returns the force felt at a position/speed vector u

Parameters:: u (array, shape (6,) or (n1, n2, .., 6)) – array of cartesian coordinates (position and speed) in the lab frame
Returns:: force – the force at the coordinates given by pos_speed_vector
Return type:: array, shape (3,) or (n1, n2, .., 3)

atomsmltr.simulation.simulator.scipy.get_force_vec_scipy(pos_speed_vector: ndarray, config: Configuration) → ndarray[source]#

Computes the force on an atom, by adding all radiations pressures, in a Scipy compatible vectorization style

Parameters:

pos_speed_vector (array, shape (6,) or (6,k)) – cartesian position and speed vector
config (Configuration) – a configuration object

Returns:

force – the force at the coordinates given by pos_speed_vector

Return type:

array, shape (3,) or (3,k)

Notes

The position/speed vector ‘pos_speed_vector’ should be of shape (6,) or (6,k) with the first dimension containing (x, y, z, vx, vy, vz) in the lab frame

Note

The function is vectorized to be compatible with Scipy’s solve_ivp function. Hence, it does not satisfy the functionnal vectorization used in the rest of this module

Examples

# ... init a config object with the `Configuration` class
from atomsmltr.simulation.simulator import get_force_vec_scipy
import numpy as np

# - init a position & speed vector grid
# vx spans from -10 to 30
# x, y, z, vy, vz set to 0
vx_list = np.linspace(-10, 30, 301)
pos_speed_vector = np.array([(0,0,0,vx,0,0,) for vx in vx_list]).T

# - compute the force
force = get_force_vec_scipy(pos_speed_vector, config)
FX, FY, FZ = force

# - print shapes for illustration
print(f"{FX.shape=}")
print(f"{pos_speed_vector.shape=}")
print(f"{force.shape=}")

This returns

FX.shape=(301,)
pos_speed_vector.shape=(6, 301)
force.shape=(3, 301)

atomsmltr.simulation.simulator.scipy.stop_position_event_scipy(t: float, u: ndarray, stop_position: list, offset: float = 0.0)[source]#

Implements ‘stop’ events for Scipy’s solve_ivp, based on atom’s position

Parameters:

t (float) – time, not used here but required for the events functions in solve_ivp
u (array, shape (6,k)) – position/speed vector, according to solve_ivp vectorization convention
stop_position (list) – list of Zones objects targetting position with actions set to stop

Returns:

res – whether to stop the simulation

Return type:

bool

Scipy-based integrators#

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