add optimization library source code

git-svn-id: https://ws10smt.googlecode.com/svn/trunk@204 ec762483-ff6d-05da-a07a-a48fb63a330f

1 files changed, 119 insertions, 0 deletions

diff --git a/gi/posterior-regularisation/prjava/src/optimization/gradientBasedMethods/AbstractGradientBaseMethod.java b/gi/posterior-regularisation/prjava/src/optimization/gradientBasedMethods/AbstractGradientBaseMethod.java
new file mode 100644
index 00000000..0a4a5445
--- /dev/null
+++ b/gi/posterior-regularisation/prjava/src/optimization/gradientBasedMethods/AbstractGradientBaseMethod.java
@@ -0,0 +1,119 @@
+package optimization.gradientBasedMethods;
+
+import optimization.gradientBasedMethods.stats.OptimizerStats;
+import optimization.linesearch.DifferentiableLineSearchObjective;
+import optimization.linesearch.LineSearchMethod;
+import optimization.stopCriteria.StopingCriteria;
+import optimization.util.MathUtils;
+
+/**
+ * 
+ * @author javg
+ *
+ */
+public abstract class AbstractGradientBaseMethod implements Optimizer{
+	
+	protected int maxNumberOfIterations=10000;
+	
+	
+	
+	protected int currentProjectionIteration;
+	protected double currValue;	
+	protected double previousValue = Double.MAX_VALUE;;
+	protected double step;
+	protected double[] gradient;
+	public double[] direction;
+	
+	//Original values
+	protected double originalGradientL2Norm;
+	
+	protected LineSearchMethod lineSearch;
+	DifferentiableLineSearchObjective lso;
+	
+	
+	public void reset(){
+		direction = null;
+		gradient = null;
+		previousValue = Double.MAX_VALUE;
+		currentProjectionIteration = 0;
+		originalGradientL2Norm = 0;
+		step = 0;
+		currValue = 0;
+	}
+	
+	public void initializeStructures(Objective o,OptimizerStats stats, StopingCriteria stop){
+		lso =   new DifferentiableLineSearchObjective(o);
+	}
+	public void updateStructuresBeforeStep(Objective o,OptimizerStats stats, StopingCriteria stop){
+	}
+	
+	public void updateStructuresAfterStep(Objective o,OptimizerStats stats, StopingCriteria stop){
+	}
+	
+	public boolean optimize(Objective o,OptimizerStats stats, StopingCriteria stop){
+		//Initialize structures
+			
+		stats.collectInitStats(this, o);
+		direction = new double[o.getNumParameters()];
+		initializeStructures(o, stats, stop);
+		for (currentProjectionIteration = 1; currentProjectionIteration < maxNumberOfIterations; currentProjectionIteration++){		
+//			System.out.println("starting iterations: parameters:" );
+//			o.printParameters();
+			previousValue = currValue;
+			currValue = o.getValue();
+			gradient = o.getGradient();
+			if(stop.stopOptimization(o)){
+				stats.collectFinalStats(this, o);
+				return true;
+			}	
+			
+			getDirection();
+			if(MathUtils.dotProduct(gradient, direction) > 0){
+				System.out.println("Not a descent direction");
+				System.out.println(" current stats " + stats.prettyPrint(1));
+				System.exit(-1);
+			}
+			updateStructuresBeforeStep(o, stats, stop);
+			lso.reset(direction);
+			step = lineSearch.getStepSize(lso);
+//			System.out.println("Leave with step: " + step);
+			if(step==-1){
+				System.out.println("Failed to find step");
+				stats.collectFinalStats(this, o);
+				return false;		
+			}
+			updateStructuresAfterStep( o, stats,  stop);
+//			previousValue = currValue;
+//			currValue = o.getValue();
+//			gradient = o.getGradient();
+			stats.collectIterationStats(this, o);
+		}
+		stats.collectFinalStats(this, o);
+		return false;
+	}
+	
+	
+	public int getCurrentIteration() {
+		return currentProjectionIteration;
+	}
+
+	
+	/**
+	 * Method specific
+	 */
+	public abstract double[] getDirection();
+
+	public double getCurrentStep() {
+		return step;
+	}
+
+
+
+	public void setMaxIterations(int max) {
+		maxNumberOfIterations = max;
+	}
+
+	public double getCurrentValue() {
+		return currValue;
+	}
+}