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package org.apache.commons.math3.optimization.general;

This interface represents a preconditioner for differentiable scalar
objective function optimizers.
Deprecated:
As of 3.1 (to be removed in 4.0).
Since:
2.0/**
 * This interface represents a preconditioner for differentiable scalar
 * objective function optimizers.
 * @deprecated As of 3.1 (to be removed in 4.0).
 * @since 2.0
 */
@Deprecated
public interface Preconditioner {
    
Precondition a search direction.

The returned preconditioned search direction must be computed fast or
the algorithm performances will drop drastically. A classical approach
is to compute only the diagonal elements of the hessian and to divide
the raw search direction by these elements if they are all positive.
If at least one of them is negative, it is safer to return a clone of
the raw search direction as if the hessian was the identity matrix. The
rationale for this simplified choice is that a negative diagonal element
means the current point is far from the optimum and preconditioning will
not be efficient anyway in this case.

Params:
point – current point at which the search direction was computed
r – raw search direction (i.e. opposite of the gradient)
Returns:
approximation of H-1r where H is the objective function hessian/**
     * Precondition a search direction.
     * <p>
     * The returned preconditioned search direction must be computed fast or
     * the algorithm performances will drop drastically. A classical approach
     * is to compute only the diagonal elements of the hessian and to divide
     * the raw search direction by these elements if they are all positive.
     * If at least one of them is negative, it is safer to return a clone of
     * the raw search direction as if the hessian was the identity matrix. The
     * rationale for this simplified choice is that a negative diagonal element
     * means the current point is far from the optimum and preconditioning will
     * not be efficient anyway in this case.
     * </p>
     * @param point current point at which the search direction was computed
     * @param r raw search direction (i.e. opposite of the gradient)
     * @return approximation of H<sup>-1</sup>r where H is the objective function hessian
     */
    double[] precondition(double[] point, double[] r);
}