OpenMM

This is an Integrator which simulates a System using Brownian dynamics. More...
Public Member Functions  
def  getTemperature 
getTemperature(self) > double  
def  setTemperature 
Set the temperature of the heat bath (in Kelvin).  
def  getFriction 
getFriction(self) > double  
def  setFriction 
Set the friction coefficient which determines how strongly the system is coupled to the heat bath (in inverse ps).  
def  getRandomNumberSeed 
getRandomNumberSeed(self) > int  
def  setRandomNumberSeed 
Set the random number seed.  
def  step 
Advance a simulation through time by taking a series of time steps.  
def  __init__ 
__init__(self, temperature, frictionCoeff, stepSize) > BrownianIntegrator __init__(self, other) > BrownianIntegrator  
Public Attributes  
this 
This is an Integrator which simulates a System using Brownian dynamics.
def __init__  (  self,  
args  
) 
__init__(self, temperature, frictionCoeff, stepSize) > BrownianIntegrator __init__(self, other) > BrownianIntegrator
Create a BrownianIntegrator.
temperature  (double) the temperature of the heat bath (in Kelvin) 
frictionCoeff  (double) the friction coefficient which couples the system to the heat bath, measured in 1/ps 
stepSize  (double) the step size with which to integrate the system (in picoseconds) 
def getFriction  (  self  ) 
getFriction(self) > double
Get the friction coefficient which determines how strongly the system is coupled to the heat bath (in inverse ps).
def getRandomNumberSeed  (  self  ) 
getRandomNumberSeed(self) > int
Get the random number seed. See setRandomNumberSeed() for details.
def getTemperature  (  self  ) 
getTemperature(self) > double
Get the temperature of the heat bath (in Kelvin).
def setFriction  (  self,  
coeff  
) 
Set the friction coefficient which determines how strongly the system is coupled to the heat bath (in inverse ps).
coeff  (double) the friction coefficient, measured in 1/ps 
def setRandomNumberSeed  (  self,  
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 nondeterministic algorithms which produce different results on successive runs, even if those runs were initialized identically.
If seed is set to 0 (which is the default value assigned), a unique seed is chosen when a Context is created from this Force. This is done to ensure that each Context receives unique random seeds without you needing to set them explicitly.
def setTemperature  (  self,  
temp  
) 
Set the temperature of the heat bath (in Kelvin).
temp  (double) the temperature of the heat bath, measured in Kelvin. 
def step  (  self,  
steps  
) 
Advance a simulation through time by taking a series of time steps.
steps  (int) the number of time steps to take 
Reimplemented from Integrator.
Reimplemented from Integrator.