4.4.3. pde.solvers.explicit module¶
Defines an explicit solver supporting various methods
- class ExplicitSolver(pde, scheme='euler', *, backend='auto', adaptive=False, tolerance=0.0001)[source]¶
Bases:
SolverBase
class for solving partial differential equations explicitly
- Parameters
pde (
PDEBase
) – The instance describing the pde that needs to be solvedscheme (str) – Defines the explicit scheme to use. Supported values are ‘euler’ and ‘runge-kutta’ (or ‘rk’ for short).
backend (str) – Determines how the function is created. Accepted values are ‘numpy` and ‘numba’. Alternatively, ‘auto’ lets the code decide for the most optimal backend.
adaptive (bool) – When enabled, the time step is adjusted during the simulation using the error tolerance set with tolerance.
tolerance (float) – The error tolerance used in adaptive time stepping. This is used in adaptive time stepping to choose a time step which is small enough so the truncation error of a single step is below tolerance.
- make_stepper(state, dt=None)[source]¶
return a stepper function using an explicit scheme
- Parameters
- Returns
Function that can be called to advance the state from time t_start to time t_end. The function call signature is (state: numpy.ndarray, t_start: float, t_end: float)
- Return type
- name = 'explicit'¶