This Integrator simulates systems that include Drude particles. More...

Inheritance diagram for DrudeLangevinIntegrator:

Public Member Functions
def	getTemperature
	getTemperature(DrudeLangevinIntegrator self) -> double More...

def	setTemperature
	setTemperature(DrudeLangevinIntegrator self, double temp) More...

def	getFriction
	getFriction(DrudeLangevinIntegrator self) -> double More...

def	setFriction
	setFriction(DrudeLangevinIntegrator self, double coeff) More...

def	getDrudeTemperature
	getDrudeTemperature(DrudeLangevinIntegrator self) -> double More...

def	setDrudeTemperature
	setDrudeTemperature(DrudeLangevinIntegrator self, double temp) More...

def	getDrudeFriction
	getDrudeFriction(DrudeLangevinIntegrator self) -> double More...

def	setDrudeFriction
	setDrudeFriction(DrudeLangevinIntegrator self, double coeff) More...

def	getRandomNumberSeed
	getRandomNumberSeed(DrudeLangevinIntegrator self) -> int More...

def	setRandomNumberSeed
	setRandomNumberSeed(DrudeLangevinIntegrator self, int seed) More...

def	step
	step(DrudeLangevinIntegrator self, int steps) More...

def	__init__
	init(OpenMM::DrudeLangevinIntegrator self, double temperature, double frictionCoeff, double drudeTemperature, double drudeFrictionCoeff, double stepSize) -> DrudeLangevinIntegrator init(OpenMM::DrudeLangevinIntegrator self, DrudeLangevinIntegrator other) -> DrudeLangevinIntegrator More...

def	__del__
	del(OpenMM::DrudeLangevinIntegrator self) More...

Public Member Functions inherited from Integrator
def	__init__

def	__del__
	del(OpenMM::Integrator self) More...

def	getStepSize
	getStepSize(Integrator self) -> double More...

def	setStepSize
	setStepSize(Integrator self, double size) More...

def	getConstraintTolerance
	getConstraintTolerance(Integrator self) -> double More...

def	setConstraintTolerance
	setConstraintTolerance(Integrator self, double tol) More...

def	step
	step(Integrator self, int steps) More...

Public Attributes
	this

Detailed Description

This Integrator simulates systems that include Drude particles.

It applies two different Langevin thermostats to different parts of the system. The first is applied to ordinary particles (ones that are not part of a Drude particle pair), as well as to the center of mass of each Drude particle pair. A second thermostat, typically with a much lower temperature, is applied to the relative internal displacement of each pair.

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

Constructor & Destructor Documentation

def __init__	(	self,
		args
	)

init(OpenMM::DrudeLangevinIntegrator self, double temperature, double frictionCoeff, double drudeTemperature, double drudeFrictionCoeff, double stepSize) -> DrudeLangevinIntegrator init(OpenMM::DrudeLangevinIntegrator self, DrudeLangevinIntegrator other) -> DrudeLangevinIntegrator

Create a DrudeLangevinIntegrator.

Parameters

temperature	the temperature of the main heat bath (in Kelvin)
frictionCoeff	the friction coefficient which couples the system to the main heat bath (in inverse picoseconds)
drudeTemperature	the temperature of the heat bath applied to internal coordinates of Drude particles (in Kelvin)
drudeFrictionCoeff	the friction coefficient which couples the system to the heat bath applied to internal coordinates of Drude particles (in inverse picoseconds)
stepSize	the step size with which to integrator the system (in picoseconds)

References simtk.openmm.openmm.stripUnits().

def __del__ ( self )

del(OpenMM::DrudeLangevinIntegrator self)

References simtk.openmm.openmm.stripUnits().

Member Function Documentation

def getDrudeFriction ( self )

getDrudeFriction(DrudeLangevinIntegrator self) -> double

Get the friction coefficient which determines how strongly the internal coordinates of Drude particles are coupled to the heat bath (in inverse ps).

References simtk.openmm.openmm.stripUnits().

def getDrudeTemperature ( self )

getDrudeTemperature(DrudeLangevinIntegrator self) -> double

Get the temperature of the heat bath applied to internal coordinates of Drude particles (in Kelvin).

References simtk.openmm.openmm.stripUnits().

def getFriction ( self )

getFriction(DrudeLangevinIntegrator self) -> double

Get the friction coefficient which determines how strongly the system is coupled to the main heat bath (in inverse ps).

References simtk.openmm.openmm.stripUnits().

def getRandomNumberSeed ( self )

getRandomNumberSeed(DrudeLangevinIntegrator self) -> int

Get the random number seed. See setRandomNumberSeed() for details.

References simtk.openmm.openmm.stripUnits().

def getTemperature ( self )

getTemperature(DrudeLangevinIntegrator self) -> double

Get the temperature of the main heat bath (in Kelvin).

References simtk.openmm.openmm.stripUnits().

def setDrudeFriction	(	self,
		args
	)

setDrudeFriction(DrudeLangevinIntegrator self, double coeff)

Set the friction coefficient which determines how strongly the internal coordinates of Drude particles are coupled to the heat bath (in inverse ps).

Parameters

coeff the friction coefficient, measured in 1/ps

References simtk.openmm.openmm.stripUnits().

def setDrudeTemperature	(	self,
		args
	)

setDrudeTemperature(DrudeLangevinIntegrator self, double temp)

Set the temperature of the heat bath applied to internal coordinates of Drude particles (in Kelvin).

Parameters

temp	the temperature of the heat bath, measured in Kelvin

References simtk.openmm.openmm.stripUnits().

def setFriction	(	self,
		args
	)

setFriction(DrudeLangevinIntegrator self, double coeff)

Set the friction coefficient which determines how strongly the system is coupled to the main heat bath (in inverse ps).

Parameters

coeff the friction coefficient, measured in 1/ps

References simtk.openmm.openmm.stripUnits().

def setRandomNumberSeed	(	self,
		args
	)

setRandomNumberSeed(DrudeLangevinIntegrator self, int seed)

Set the random number seed. The precise meaning of this parameter is undefined, and is left up to each Platform to interpret in an appropriate way. It is guaranteed that if two simulations are run with different random number seeds, the sequence of random forces will be different. On the other hand, no guarantees are made about the behavior of simulations that use the same seed. In particular, Platforms are permitted to use non-deterministic algorithms which produce different results on successive runs, even if those runs were initialized identically.

References simtk.openmm.openmm.stripUnits().