LocalEnergyMinimizer Class Reference

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.

List of all members.

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)

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Detailed Description

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 L-BFGS 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.

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Constructor & Destructor Documentation

def __init__	(		self,
			args,
			kwargs
	)

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Member Function Documentation

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.

Parameters:

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 root-mean-square 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.

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Member Data Documentation

tuple minimize = staticmethod(minimize) [static]

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The documentation for this class was generated from the following file:

• openmm.py