Package ffx.potential.bonded
Interface LambdaInterface
- All Known Implementing Classes:
AngleTorsion,ANIEnergy,COMRestraint,DualTopologyEnergy,ForceFieldEnergy,GeneralizedKirkwood,NCSRestraint,OpenMMDualTopologyEnergy,OpenMMEnergy,OrthogonalSpaceTempering,ParticleMeshEwald,PiOrbitalTorsion,QuadTopologyEnergy,RealSpaceEnergy,RefinementEnergy,RestrainDistance,RestrainPosition,RestrainTorsion,StretchTorsion,Torsion,TorsionTorsion,VanDerWaals,VanDerWaalsTornado,XRayEnergy
public interface LambdaInterface
The LambdaInterface should be implemented by potential energy terms that can accept a lambda
value from [0 .. 1] that defines a twice differentiable path between states 0 and 1.
- Since:
- 1.0
- Author:
- Michael J. Schnieders
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Method Summary
Modifier and TypeMethodDescriptiondefault booleanReturns true if dUdL is guaranteed to be zero at 0 and 1.doubleGet the 2nd partial derivative of the energy with respect to lambda.doublegetdEdL()Get the partial derivative of the energy with respect to lambda.voidgetdEdXdL(double[] gradient) Get the gradient of dEdL with respect to each parameter.doubleGet the current value of the state variable.voidsetLambda(double lambda) Set the current value of the state variable.
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Method Details
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dEdLZeroAtEnds
default boolean dEdLZeroAtEnds()Returns true if dUdL is guaranteed to be zero at 0 and 1. Default implementation is to return false.- Returns:
- True if dUdL is guaranteed 0 at endpoints.
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getLambda
double getLambda()Get the current value of the state variable.- Returns:
- state
- Since:
- 1.0
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setLambda
void setLambda(double lambda) Set the current value of the state variable. May be ignored if lambda is not being applied.- Parameters:
lambda- a double.- Since:
- 1.0
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getd2EdL2
double getd2EdL2()Get the 2nd partial derivative of the energy with respect to lambda.- Returns:
- d2EdL2
- Since:
- 1.0
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getdEdL
double getdEdL()Get the partial derivative of the energy with respect to lambda.- Returns:
- dEdL
- Since:
- 1.0
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getdEdXdL
void getdEdXdL(double[] gradient) Get the gradient of dEdL with respect to each parameter.- Parameters:
gradient- - A double array of length the number of parameters in the model (commonly 3 * number of atoms).- Since:
- 1.0
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