Numerically solve ordinary differential equations, making possible simulations of dynamic systems.
Methods
| Runge-Kutta-Fehlberg | Robust workhorse |
| Bulirsch-Stoers | Fast and accurate for well-behaved systems |
| Adams-Moulton | Traditional |
| Backward Differentiation Formula | Best for stiff systems |
Features
Adaptive step sizing for maximum efficiency.
Control error magnitude. Scale errors by any combination of a constant, current value of output, current value of derivatives, current step size.
Output solution values at specified values of the independent variable, at fixed increments, or use "free-run" mode for largest possible step size.
User can interrupt a solution in progress and re-start.
Derivatives are specified by a user-defined function. They can include virtually any non-linear behavior, including IF statements and loops.
Derivatives can be calculated by C or C++ language plug-in modules for increased speed. To write your own module, you use the XOP Toolkit.
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