OpenMM

Given a Context, this class searches for a new set of particle positions that represent a local minimum of the potential energy. More...
Inherits _object.
Public Member Functions  
def  __init__ 
def  minimize 
Search for a new set of particle positions that represent a local potential energy minimum.  
Static Public Attributes  
tuple  minimize = staticmethod(minimize) 
Given a Context, this class searches for a new set of particle positions that represent a local minimum of the potential energy.
The search is performed with the LBFGS algorithm. Distance constraints are enforced during minimization by adding a harmonic restraining force to the potential function. The strength of the restraining force is steadily increased until the minimum energy configuration satisfies all constraints to within the tolerance specified by the Context's Integrator.
def __init__  (  self,  
args,  
kwargs  
) 
def minimize  (  context,  
tolerance = 10 , 

maxIterations = 0 

) 
Search for a new set of particle positions that represent a local potential energy minimum.
On exit, the Context will have been updated with the new positions.
context  (Context) a Context specifying the System to minimize and the initial particle positions 
tolerance  (double) this specifies how precisely the energy minimum must be located. Minimization will be halted once the rootmeansquare value of all force components reaches this tolerance. The default value is 10. 
maxIterations  (int) the maximum number of iterations to perform. If this is 0, minimation is continued until the results converge without regard to how many iterations it takes. The default value is 0. 