Merge branch 'master' of https://github.com/redpony/cdec

1 files changed, 0 insertions, 185 deletions

diff --git a/gi/posterior-regularisation/prjava/src/optimization/linesearch/DifferentiableLineSearchObjective.java b/gi/posterior-regularisation/prjava/src/optimization/linesearch/DifferentiableLineSearchObjective.java
deleted file mode 100644
index a5bc958e..00000000
--- a/gi/posterior-regularisation/prjava/src/optimization/linesearch/DifferentiableLineSearchObjective.java
+++ /dev/null
@@ -1,185 +0,0 @@
-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) {
-		
-	}
-	
-}