# VariableVerletIntegrator¶

class simtk.openmm.openmm.VariableVerletIntegrator(*args)

This is an error contolled, variable time step Integrator that simulates a System using the leap-frog Verlet algorithm. It compares the result of the Verlet integrator to that of an explicit Euler integrator, takes the difference between the two as a measure of the integration error in each time step, and continuously adjusts the step size to keep the error below a specified tolerance. This both improves the stability of the integrator and allows it to take larger steps on average, while still maintaining comparable accuracy to a fixed step size integrator.

It is best not to think of the error tolerance as having any absolute meaning. It is just an adjustable parameter that affects the step size and integration accuracy. You should try different values to find the largest one that produces a trajectory sufficiently accurate for your purposes. 0.001 is often a good starting point.

Unlike a fixed step size Verlet integrator, variable step size Verlet is not symplectic. This means that at a given accuracy level, energy is not as precisely conserved over long time periods. This makes it most appropriate for constant temperate simulations. In constant energy simulations where precise energy conservation over long time periods is important, a fixed step size Verlet integrator may be more appropriate.

__init__(self, errorTol) → VariableVerletIntegrator

__init__(self, other) -> VariableVerletIntegrator

Create a VariableVerletIntegrator.

Parameters: errorTol (double) – the error tolerance

Methods

 __init__((self, ...) __init__(self, other) -> VariableVerletIntegrator getConstraintTolerance((self) -> double) Get the distance tolerance within which constraints are maintained, as a fraction of the constrained distance. getErrorTolerance((self) -> double) Get the error tolerance. getStepSize((self) -> double) Get the size of each time step, in picoseconds. setConstraintTolerance(self, tol) Set the distance tolerance within which constraints are maintained, as a fraction of the constrained distance. setErrorTolerance(self, tol) Set the error tolerance. setStepSize(self, size) Set the size of each time step, in picoseconds. step(self, steps) Advance a simulation through time by taking a series of time steps. stepTo(self, time) Advance a simulation through time by taking a series of steps until a specified time is reached.
getErrorTolerance(self) → double

Get the error tolerance.

setErrorTolerance(self, tol)

Set the error tolerance.

step(self, steps)

Advance a simulation through time by taking a series of time steps.

Parameters: steps (int) – the number of time steps to take
stepTo(self, time)

Advance a simulation through time by taking a series of steps until a specified time is reached. When this method returns, the simulation time will exactly equal the time which was specified. If you call this method and specify a time that is earlier than the current time, it will return without doing anything.

Parameters: time (double) – the time to which the simulation should be advanced
__copy__(self) → Integrator
getConstraintTolerance(self) → double

Get the distance tolerance within which constraints are maintained, as a fraction of the constrained distance.

getStepSize(self) → double

Get the size of each time step, in picoseconds. If this integrator uses variable time steps, the size of the most recent step is returned.

Returns: the step size, measured in ps double
setConstraintTolerance(self, tol)

Set the distance tolerance within which constraints are maintained, as a fraction of the constrained distance.

setStepSize(self, size)

Set the size of each time step, in picoseconds. If this integrator uses variable time steps, the effect of calling this method is undefined, and it may simply be ignored.

Parameters: size (double) – the step size, measured in ps