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diff --git a/gi/posterior-regularisation/prjava/src/optimization/linesearch/DifferentiableLineSearchObjective.java b/gi/posterior-regularisation/prjava/src/optimization/linesearch/DifferentiableLineSearchObjective.java
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--- a/gi/posterior-regularisation/prjava/src/optimization/linesearch/DifferentiableLineSearchObjective.java
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-package optimization.linesearch;
-
-import gnu.trove.TDoubleArrayList;
-import gnu.trove.TIntArrayList;
-
-import java.util.ArrayList;
-import java.util.Arrays;
-import java.util.Collections;
-import java.util.Comparator;
-
-import optimization.gradientBasedMethods.Objective;
-import optimization.util.MathUtils;
-import optimization.util.StaticTools;
-
-
-
-import util.MathUtil;
-import util.Printing;
-
-
-/**
- * A wrapper class for the actual objective in order to perform
- * line search. The optimization code assumes that this does a lot
- * of caching in order to simplify legibility. For the applications
- * we use it for, caching the entire history of evaluations should be
- * a win.
- *
- * Note: the lastEvaluatedAt value is very important, since we will use
- * it to avoid doing an evaluation of the gradient after the line search.
- *
- * The differentiable line search objective defines a search along the ray
- * given by a direction of the main objective.
- * It defines the following function,
- * where f is the original objective function:
- * g(alpha) = f(x_0 + alpha*direction)
- * g'(alpha) = f'(x_0 + alpha*direction)*direction
- *
- * @author joao
- *
- */
-public class DifferentiableLineSearchObjective {
-
-
-
- Objective o;
- int nrIterations;
- TDoubleArrayList steps;
- TDoubleArrayList values;
- TDoubleArrayList gradients;
-
- //This variables cannot change
- public double[] originalParameters;
- public double[] searchDirection;
-
-
- /**
- * Defines a line search objective:
- * Receives:
- * Objective to each we are performing the line search, is used to calculate values and gradients
- * Direction where to do the ray search, note that the direction does not depend of the
- * objective but depends from the method.
- * @param o
- * @param direction
- */
- public DifferentiableLineSearchObjective(Objective o) {
- this.o = o;
- originalParameters = new double[o.getNumParameters()];
- searchDirection = new double[o.getNumParameters()];
- steps = new TDoubleArrayList();
- values = new TDoubleArrayList();
- gradients = new TDoubleArrayList();
- }
- /**
- * Called whenever we start a new iteration.
- * Receives the ray where we are searching for and resets all values
- *
- */
- public void reset(double[] direction){
- //Copy initial values
- System.arraycopy(o.getParameters(), 0, originalParameters, 0, o.getNumParameters());
- System.arraycopy(direction, 0, searchDirection, 0, o.getNumParameters());
-
- //Initialize variables
- nrIterations = 0;
- steps.clear();
- values.clear();
- gradients.clear();
-
- values.add(o.getValue());
- gradients.add(MathUtils.dotProduct(o.getGradient(),direction));
- steps.add(0);
- }
-
-
- /**
- * update the current value of alpha.
- * Takes a step with that alpha in direction
- * Get the real objective value and gradient and calculate all required information.
- */
- public void updateAlpha(double alpha){
- if(alpha < 0){
- System.out.println("alpha may not be smaller that zero");
- throw new RuntimeException();
- }
- nrIterations++;
- steps.add(alpha);
- //x_t+1 = x_t + alpha*direction
- System.arraycopy(originalParameters,0, o.getParameters(), 0, originalParameters.length);
- MathUtils.plusEquals(o.getParameters(), searchDirection, alpha);
- o.setParameters(o.getParameters());
-// System.out.println("Took a step of " + alpha + " new value " + o.getValue());
- values.add(o.getValue());
- gradients.add(MathUtils.dotProduct(o.getGradient(),searchDirection));
- }
-
-
-
- public int getNrIterations(){
- return nrIterations;
- }
-
- /**
- * return g(alpha) for the current value of alpha
- * @param iter
- * @return
- */
- public double getValue(int iter){
- return values.get(iter);
- }
-
- public double getCurrentValue(){
- return values.get(nrIterations);
- }
-
- public double getOriginalValue(){
- return values.get(0);
- }
-
- /**
- * return g'(alpha) for the current value of alpha
- * @param iter
- * @return
- */
- public double getGradient(int iter){
- return gradients.get(iter);
- }
-
- public double getCurrentGradient(){
- return gradients.get(nrIterations);
- }
-
- public double getInitialGradient(){
- return gradients.get(0);
- }
-
-
-
-
- public double getAlpha(){
- return steps.get(nrIterations);
- }
-
- public void printLineSearchSteps(){
- System.out.println(
- " Steps size "+steps.size() +
- "Values size "+values.size() +
- "Gradeients size "+gradients.size());
- for(int i =0; i < steps.size();i++){
- System.out.println("Iter " + i + " step " + steps.get(i) +
- " value " + values.get(i) + " grad " + gradients.get(i));
- }
- }
-
- public void printSmallLineSearchSteps(){
- for(int i =0; i < steps.size();i++){
- System.out.print(StaticTools.prettyPrint(steps.get(i), "0.0000E00",8) + " ");
- }
- System.out.println();
- }
-
- public static void main(String[] args) {
-
- }
-
-}