DrudeSCFIntegrator

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

This is a leap-frog Verlet Integrator that simulates systems with Drude particles. It uses the self-consistent field (SCF) method: at every time step, the positions of Drude particles are adjusted to minimize the potential energy.

This Integrator requires the System to include a DrudeForce, which it uses to identify the Drude particles.

__init__(self, stepSize) → DrudeSCFIntegrator

__init__(self, other) -> DrudeSCFIntegrator

Create a DrudeSCFIntegrator.

Parameters:stepSize (double) – the step size with which to integrator the system (in picoseconds)

Methods

__init__(self, stepSize)	__init__(self, other) -> DrudeSCFIntegrator
getConstraintTolerance(self)	Get the distance tolerance within which constraints are maintained, as a fraction of the constrained distance.
getMinimizationErrorTolerance(self)	Get the error tolerance to use when minimizing the potential energy.
getStepSize(self)	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.
setMinimizationErrorTolerance(self, tol)	Set the error tolerance to use when minimizing the potential energy.
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.

getMinimizationErrorTolerance(self) → double

Get the error tolerance to use when minimizing the potential energy. This roughly corresponds to the maximum allowed force magnitude on the Drude particles after minimization.

Returns:the error tolerance to use, measured in kJ/mol/nm Return type:double

setMinimizationErrorTolerance(self, tol)

Set the error tolerance to use when minimizing the potential energy. This roughly corresponds to the maximum allowed force magnitude on the Drude particles after minimization.

Parameters:tol (double) – the error tolerance to use, measured in kJ/mol/nm

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

__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 Return type: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