pyshqg.core.integration module

Submodule dedicated to integration schemes.

class pyshqg.core.integration.RungeKuttaModelIntegrator(model, dt, method)

Bases: object

Runge–Kutta integration class.

The purpose of this class is to implement Runge–Kutta integration schemes.

model

The model to integrate.

Type:

pyshqg.core_numpy.model.QGModel

dt

The integration time step.

Type:

float

steps

The scheme integration sub time steps.

Type:

list of float

weights

The weights of each integration sub time step.

Type:

list of float

__init__(model, dt, method)

Constructor for the Runge–Kutta integration class.

The list of integration sub time steps and the associated weights are constructed for each available schemes. The list of currently available schemes is: - RK4; - RK2; - ABM; - EE.

Parameters:

• model (pyshqg.core_numpy.model.QGModel) – The model to integrate.

• dt (float) – The integration time step.

• method (str) – The method name.

forward(state)

Applies an integration step forward in time.

Parameters:

state (dict of str to numpy.ndarray) – The current QG model state.

Returns:

state – The integrated QG model state.

Return type:

dict of str to numpy.ndarray

run(state, t_start, num_snapshots, num_steps_per_snapshot, variables, use_tqdm=True)

Computes a full trajectory.

Parameters:

• state (dict of str to numpy.ndarray) – The initial QG model state.

• t_start (float) – The time of the initial state.

• num_snapshots (int) – Number of snapshots to compute.

• num_steps_per_snapshot (int) – Number of integration steps between snapshots.

• variables (list of str) – List of variables to record.

• use_tqdm (bool) – Whether to use tqdm for the main integration loop.

Returns:

trajectory – The model trajectory.

Return type:

pyshqg.core_numpy.model.QGModelTrajectory