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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Igor Pro 9

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Igor XOP Toolkit

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Igor NIDAQ Tools MX

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