choreo.segm.ODE.ExplicitSymplecticIVP#
- ExplicitSymplecticIVP()#
Explicit symplectic integration of a partitionned initial value problem.
- Parameters:
fun (
callable
orscipy.LowLevelCallable
) – Function defining the IVP.gun (
callable
orscipy.LowLevelCallable
) – Function defining the IVP.t_span (
tuple
(numpy.float64
,numpy.float64
)) – Initial and final time of integration.xo (
numpy.ndarray
(shape = (n), dtype = np.float64)
, optional) – Initial value for x. Overriden by reg_xo if provided. By default,None
.vo (
numpy.ndarray
(shape = (n), dtype = np.float64)
, optional) – Initial value for v. Overriden by reg_xo if provided. By default,None
.rk (
ExplicitSymplecticRKTable
, optional) – Runge-Kutta tables for the integration of the IVP. By default,choreo.segm.precomputed_tables.StormerVerlet
.grad_fun (
callable
orscipy.LowLevelCallable
, optional) – Gradient of the function defining the IVP, by defaultNone
.grad_gun (
callable
orscipy.LowLevelCallable
, optional) – Gradient of the function defining the IVP, by defaultNone
.mode (
str
, optional) – Whether to start the staggered integration with x or v, by default"VX"
.nint (
int
, optional) – Number of integration steps, by default1
.keep_freq (
int
, optional) – Number of integration steps to be taken before saving output, by default-1
.reg_xo (
numpy.ndarray
(shape = (nreg, n), dtype = np.float64)
) – Array of initial values for x for regular reset.reg_vo (
numpy.ndarray
(shape = (nreg, n), dtype = np.float64)
) – Array of initial values for v for regular reset.reg_init_freq (
int
, optional) – Number of timesteps before resetting initial values for x and v. Non-positive values disable the reset, by default-1
.keep_init (
bool
, optional) – Whether to save the initial values, by defaultFalse
.DoEFT (
bool
, optional) – Whether to use an error-free transformation for summation, by defaultTrue
.
- Returns:
Arrays containing the computed approximation of the solution to the IVP at evaluation points.
- Return type:
tuple
ofnumpy.ndarray
.