cdec cleanup, remove bayesian stuff, parsing stuff

1 files changed, 0 insertions, 148 deletions

diff --git a/gi/posterior-regularisation/prjava/src/util/MathUtil.java b/gi/posterior-regularisation/prjava/src/util/MathUtil.java
deleted file mode 100644
index 799b1faf..00000000
--- a/gi/posterior-regularisation/prjava/src/util/MathUtil.java
+++ /dev/null
@@ -1,148 +0,0 @@
-package util;
-
-import java.util.Random;
-
-public class MathUtil {
-	public static final boolean closeToOne(double number){
-		return Math.abs(number-1) < 1.E-10;
-	}
-	
-	public static final boolean closeToZero(double number){
-		return Math.abs(number) < 1.E-5;
-	}
-	
-	/**
-	 * Return a ramdom multinominal distribution.
-	 * 
-	 * @param size
-	 * @return
-	 */
-	public static final double[] randomVector(int size, Random r){
-		double[] random = new double[size];
-		double sum=0;
-		for(int i = 0; i < size; i++){
-			double number = r.nextDouble();
-			random[i] = number;
-			sum+=number;
-		}
-		for(int i = 0; i < size; i++){
-			random[i] = random[i]/sum;
-		}
-		return random;
-	}
-	
-	
-
-	public static double sum(double[] ds) {
-		double res = 0;
-		for (int i = 0; i < ds.length; i++) {
-			res+=ds[i];
-		}
-		return res;
-	}
-
-	public static double max(double[] ds) {
-		double res = Double.NEGATIVE_INFINITY;
-		for (int i = 0; i < ds.length; i++) {
-			res = Math.max(res, ds[i]);
-		}
-		return res;
-	}
-
-	public static double min(double[] ds) {
-		double res = Double.POSITIVE_INFINITY;
-		for (int i = 0; i < ds.length; i++) {
-			res = Math.min(res, ds[i]);
-		}
-		return res;
-	}
-
-	
-	public static double KLDistance(double[] p, double[] q) {
-		int len = p.length;
-		double kl = 0;
-		for (int j = 0; j < len; j++) {
-				if (p[j] == 0 || q[j] == 0) {
-					continue;
-				} else {
-					kl += q[j] * Math.log(q[j] / p[j]);
-				}
-
-		}
-		return kl;
-	}
-	
-	public static double L2Distance(double[] p, double[] q) {
-		int len = p.length;
-		double l2 = 0;
-		for (int j = 0; j < len; j++) {
-				if (p[j] == 0 || q[j] == 0) {
-					continue;
-				} else {
-					l2 += (q[j] - p[j])*(q[j] - p[j]);
-				}
-
-		}
-		return Math.sqrt(l2);
-	}
-	
-	public static double L1Distance(double[] p, double[] q) {
-		int len = p.length;
-		double l1 = 0;
-		for (int j = 0; j < len; j++) {
-				if (p[j] == 0 || q[j] == 0) {
-					continue;
-				} else {
-					l1 += Math.abs(q[j] - p[j]);
-				}
-
-		}
-		return l1;
-	}
-
-	public static double dot(double[] ds, double[] ds2) {
-		double res = 0;
-		for (int i = 0; i < ds2.length; i++) {
-			res+= ds[i]*ds2[i];
-		}
-		return res;
-	}
-	
-	public static double expDigamma(double number){
-		return Math.exp(digamma(number));
-	}
-	
-	public static double digamma(double number){
-		if(number > 7){
-			return digammApprox(number-0.5);
-		}else{
-			return digamma(number+1) - 1.0/number;
-		}
-	}
-	
-	private static double digammApprox(double value){
-		return Math.log(value) + 0.04167*Math.pow(value, -2) - 0.00729*Math.pow(value, -4) 
-		+  0.00384*Math.pow(value, -6) - 0.00413*Math.pow(value, -8);
-	}
-
-	public static double eulerGamma = 0.57721566490152386060651209008240243;
-	// FIXME -- so far just the initialization from Minka's paper "Estimating a Dirichlet distribution". 
-	public static double invDigamma(double y) {
-		if (y>= -2.22) return Math.exp(y)+0.5;
-		return -1.0/(y+eulerGamma);
-	}
-
-	
-	
-	public static void main(String[] args) {
-		for(double i = 0; i < 10 ; i+=0.1){
-			System.out.println(i+"\t"+expDigamma(i)+"\t"+(i-0.5));
-		}
-//		double gammaValue = (expDigamma(3)/expDigamma(10) + expDigamma(3)/expDigamma(10) + expDigamma(4)/expDigamma(10));
-//		double normalValue = 3/10+3/4+10/10;
-//		System.out.println("Gamma " + gammaValue + " normal " + normalValue);
-	}
-
-	
-	
-}