Package wsh.opt

Interface Vect

  • All Superinterfaces:
    java.lang.Cloneable, java.io.Serializable, VectConst
    All Known Implementing Classes:
    ArrayVect1
    public interface Vect
extends VectConst
    Implement a vector supporting linear vector-space methods Test your implementation with VectUtil.test().

    • Method Summary

      All Methods Instance Methods Abstract Methods 
      Modifier and Type Method Description
      void add​(double scaleThis, double scaleOther, VectConst other)
      Add a scaled version of another vector to a scaled version of this vector.
      Vect clone()  
      void constrain()
      Optionally apply a hard constraint (such as an inequality) to the current vector.
      void dispose()
      Optionally free any resources held by this object.
      void multiplyInverseCovariance()
      Optionally multiply a vector by the inverse covariance matrix.
      void postCondition()
      Apply a linear filter that enhances components that should be optimized first, and suppresses components of lesser importance.
      void project​(double scaleThis, double scaleOther, VectConst other)
      Project another vector onto the space of this vector, then scale, and add to a scaled version of this vector.

    • Method Detail

      • add

        void add​(double scaleThis,
         double scaleOther,
         VectConst other)
        Add a scaled version of another vector to a scaled version of this vector. [If this==other, then the result should be the same as scaling this by (scaleThis+scaleOther)]
        Parameters:
        scaleThis - Multiply this vector by this scalar before adding.
        scaleOther - Multiply the other vector by this scalar before adding.
        other - The other vector to be multiplied.

      • project

        void project​(double scaleThis,
             double scaleOther,
             VectConst other)
        Project another vector onto the space of this vector, then scale, and add to a scaled version of this vector. (Useful for perturbing one vector with a constrained subspace.) This method should give the same result as add(), if the other Vect is an instance of the same class as this Vect. This operation need not be supported for any any types other than this Vect.
        Parameters:
        other - The other vector to be projected, scaled, and added.
        scaleThis - Multiply this vector by this scalar before adding.
        scaleOther - Multiply the other vector by this scalar before adding.

      • dispose

        void dispose()
        Optionally free any resources held by this object. Will not be used again. This method can safely do nothing.

      • multiplyInverseCovariance

        void multiplyInverseCovariance()
        Optionally multiply a vector by the inverse covariance matrix. Also called preconditioning. A method that does nothing is equivalent to an identity. [vect.magnitude() should return the same value as vect.dot(((Vect)vect.clone()).multiplyInverseCovariance()); This should enhance components that should be discouraged in the model and suppress components that are preferred. This operation slows convergence. This filter must be linear. For inversions, you should at least implement a scaling operation that correctly weights errors in the data versus the magnitude of the model.]

      • constrain

        void constrain()
        Optionally apply a hard constraint (such as an inequality) to the current vector. This is used only by a non-linear optimization. This method can safely do nothing.

      • postCondition

        void postCondition()
        Apply a linear filter that enhances components that should be optimized first, and suppresses components of lesser importance. Also called post-conditioning. This filter prefilters all perturbations of the model and speeds convergence on components of most importance in the model. The same result can be accomplished by Transform.inverseHessian(), but this location may be more convenient. Use this location if the conditioning is independent of the Transform and dependent on the implementation of the model. This method can safely do nothing.