solve_ivp_abm
solve_ivp_abm¶
- solve_ivp_abm(fun, t_span, y0, Nt, ys=None, dys=None, dcp=None, save_memory=False, start_factor=2)[source]¶
Solve the specified IVP using a 5th order predictor-corrector method.
This is the algorithm presented at the end of Section 23.10 of Hamming’s book. It is an average of the Milne and Adams-Bashforth cases.
- Parameters
Nt (int) – Number of steps. The time-step will be
np.diff(t_span)/Nt.ys ([y0, y1, y2, y3] or None) – First four steps to get the process started. If not provided, then these will be computed using
solve_ivp_rk4().dys ([dy0, dy1, dy2, dy3] or None) – Derivatives at the corresponding previous steps. Will be computed if not provided.
dcp (array, None) – Previous corrector-predictor difference (with a factor 161/170).
save_memory (bool) – If True, then only keep the last four steps.
- Returns
res (OdeResult) – Bunch object.
The remaining arguments should match those of
scipy.integrate.solve_ivp().Don’t worry about optimizations like allowing fun to be vectorized etc.
Notes
This method requires four initial values to get started.