brainpy.integrators.ode.adaptive_rk.HeunEuler
brainpy.integrators.ode.adaptive_rk.HeunEuler#
- class brainpy.integrators.ode.adaptive_rk.HeunEuler(f, var_type=None, dt=None, name=None, adaptive=None, tol=None, show_code=False, state_delays=None, neutral_delays=None)[source]#
The Heun–Euler method for ODEs.
The simplest adaptive Runge–Kutta method involves combining Heun’s method, which is order 2, with the Euler method, which is order 1.
It has the characteristics of:
method stage = 2
method order = 1
Butcher Tables:
\[\begin{split}\begin{array}{c|cc} 0&\\ 1& 1 \\ \hline & 1/2& 1/2\\ & 1 & 0 \end{array}\end{split}\]- __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
()load_states
(filename[, verbose])Load the model states.
nodes
([method, level, include_self])Collect all children nodes.
register_implicit_nodes
(nodes)register_implicit_vars
(variables)save_states
(filename[, variables])Save the model states.
set_integral
(f)Set the integral function.
train_vars
([method, level, include_self])The shortcut for retrieving all trainable variables.
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
arg_names
arguments
All arguments when calling the numer integrator of the differential equation.
dt
The numerical integration precision.
integral
The integral function.
name
neutral_delays
neutral delays.
parameters
The parameters defined in the differential equation.
state_delays
State delays.
variables
The variables defined in the differential equation.