brainpy.integrators.ode.BogackiShampine

class brainpy.integrators.ode.BogackiShampine(f, var_type=None, dt=None, name=None, adaptive=None, tol=None, show_code=False, state_delays=None, neutral_delays=None)

The Bogacki–Shampine method for ODEs.

The Bogacki–Shampine method was proposed by Przemysław Bogacki and Lawrence F. Shampine in 1989 (Bogacki & Shampine 1989). The Bogacki–Shampine method is a Runge–Kutta method of order three with four stages with the First Same As Last (FSAL) property, so that it uses approximately three function evaluations per step. It has an embedded second-order method which can be used to implement adaptive step size.

It has the characteristics of:

• method stage = 4

• method order = 3

• Butcher Tables:

\[\begin{split}\begin{array}{l|lll} 0 & & & \\ 1 / 2 & 1 / 2 & & \\ 3 / 4 & 0 & 3 / 4 & \\ 1 & 2 / 9 & 1 / 3 & 4 / 9 \\ \hline & 2 / 9 & 1 / 3 & 4 / 90 \\ & 7 / 24 & 1 / 4 & 1 / 3 & 1 / 8 \end{array}\end{split}\]

References

[1]

https://en.wikipedia.org/wiki/Bogacki%E2%80%93Shampine_method

[2]

Bogacki, Przemysław; Shampine, Lawrence F. (1989), “A 3(2) pair of Runge–Kutta formulas”, Applied Mathematics Letters, 2 (4): 321–325, doi:10.1016/0893-9659(89)90079-7

__init__(f, var_type=None, dt=None, name=None, adaptive=None, tol=None, show_code=False, state_delays=None, neutral_delays=None)

Methods

__init__(f[, var_type, dt, name, adaptive, ...])
build()
cpu()	Move all variable into the CPU device.
cuda()	Move all variables into the GPU device.
load_state_dict(state_dict[, warn, compatible])	Copy parameters and buffers from state_dict into this module and its descendants.
load_states(filename[, verbose])	Load the model states.
nodes([method, level, include_self])	Collect all children nodes.
register_implicit_nodes(*nodes[, node_cls])
register_implicit_vars(*variables[, var_cls])
save_states(filename[, variables])	Save the model states.
set_integral(f)	Set the integral function.
state_dict()	Returns a dictionary containing a whole state of the module.
to(device)	Moves all variables into the given device.
tpu()	Move all variables into the TPU device.
train_vars([method, level, include_self])	The shortcut for retrieving all trainable variables.
tree_flatten()	Flattens the object as a PyTree.
tree_unflatten(aux, dynamic_values)	Unflatten the data to construct an object of this class.
unique_name([name, type_])	Get the unique name for this object.
vars([method, level, include_self, ...])	Collect all variables in this node and the children nodes.

Attributes

A
B1
B2
C
arguments	All arguments when calling the numer integrator of the differential equation.
dt	The numerical integration precision.
integral	The integral function.
name	Name of the model.
neutral_delays	neutral delays.
parameters	The parameters defined in the differential equation.
state_delays	State delays.
variables	The variables defined in the differential equation.