Working on new LMA correlation

src/main/java/com/elphel/imagej/tileprocessor/Correlations2dLMA.java

 package com.elphel.imagej.tileprocessor;
 /**
  **
- ** Correlation2dLMA - Fit multi - baseline correaltion pairs to the model
+ ** Correlation2dLMA - Fit multi - baseline correlation pairs to the model
  **
  ** Copyright (C) 2018 Elphel, Inc.
  **
@@ -84,7 +84,7 @@ public class Correlations2dLMA {
 	double []   poly_coeff =      null;  // 6 elements - Xc, Yx, f(x,y), A, B, C (from A*x^2 + B*y^2 +C*x*y+...)
 	double []   poly_xyvwh =      null;  // result of 2-d polynomial approximation instead of the LMA - used for lazy eye correction
 
-	public class NumDiag{
+	public class NumDiag{ // USED in lwir
 		int     num;
 		boolean diag;
 		public NumDiag(int num, boolean diag) {
@@ -93,7 +93,7 @@ public class Correlations2dLMA {
 		}
 	}
 
-	public class Sample{
+	public class Sample{ // USED in lwir
 		double x;      // x coordinate on the common scale (corresponding to the largest baseline), along the disparity axis
 		double y;      // y coordinate (0 - disparity axis)
 		double v;      // correlation value at that point
@@ -117,7 +117,7 @@ public class Correlations2dLMA {
 			}
 	}
 
-	public void printParams() {
+	public void printParams() { // not used in lwir
 		for (int np = 0; np < all_pars.length; np++) {
 			System.out.println(String.format("%2d%1s %22s %f",
 					np,
@@ -127,7 +127,7 @@ public class Correlations2dLMA {
 		}
 	}
 
-	public void printInputDataFx(boolean show_fx){
+	public void printInputDataFx(boolean show_fx){ // not used in lwir
 		if 	(show_fx) {
 			Sample s = null;
 			double [] fx = getPolyFx();
@@ -151,18 +151,18 @@ public class Correlations2dLMA {
 		}
 	}
 
-	public double [] getRMS() {
+	public double [] getRMS() { // USED in lwir
 		return last_rms;
 	}
-	public double [] getGoodOrBadRMS() {
+	public double [] getGoodOrBadRMS() { // not used in lwir
 		return good_or_bad_rms;
 	}
 
-	public double [] getAllPars() {
+	public double [] getAllPars() { // not used in lwir
 		return all_pars;
 	}
 
-	public double [] getDisparityStrength() {
+	public double [] getDisparityStrength() { // USED in lwir
 		if (group_weights == null) return null;
 		double disparity = -all_pars[X0_INDEX];
 		double sum_amp = 0.0;
@@ -176,7 +176,7 @@ public class Correlations2dLMA {
 		double [] ds = {disparity, sum_amp};
 		return ds;
 	}
-	public double [] getDisparityStrengthWidth() {
+	public double [] getDisparityStrengthWidth() { // USED in lwir
 		double [] ds = getDisparityStrength();
 		if (ds == null) return null;
 		double [] dsw = {ds[0], ds[1], all_pars[WM_INDEX], all_pars[WXY_INDEX]}; // asymmetry
@@ -184,16 +184,16 @@ public class Correlations2dLMA {
 	}
 
 
-	public Correlations2dLMA (
+	public Correlations2dLMA ( // USED in lwir
 			double [] scales // null - use default table
 			) {
 		if (scales != null)	this.scales = scales.clone();
 	}
 
-	public void setDiag(boolean diag_in) {
+	public void setDiag(boolean diag_in) { // USED in lwir
 		this.input_diag = diag_in;
 	}
-	public void addSample(
+	public void addSample( // USED in lwir
 			double x,      // x coordinate on the common scale (corresponding to the largest baseline), along the disparity axis
 			double y,      // y coordinate (0 - disparity axis)
 			double v,      // correlation value at that point
@@ -209,7 +209,7 @@ public class Correlations2dLMA {
 //NumDiag
 // TODO: add auto x0, half-width?
 // should be called ater all samples are entered (to list groups)
-	public void initVector(
+	public void initVector( // USED in lwir
 			boolean adjust_wm,
 			boolean adjust_wy,
 			boolean adjust_wxy,
@@ -242,7 +242,7 @@ public class Correlations2dLMA {
 		toVector();
 	}
 
-	public void setWeightsValues(
+	public void setWeightsValues( // USED in lwir
 			double half_width,   // expected width
 			double  cost_wm,     // cost of non-zero this.all_pars[WYD_INDEX]
 			double  cost_wxy) {  // cost of non-zero this.all_pars[WXY_INDEX]
@@ -260,7 +260,7 @@ public class Correlations2dLMA {
 			weights[i] = s.w;
 			values[i] =  s.v;
 			group_weights[groups.get(s.gi).num] += s.w;
-			if (Double.isNaN(values[i]) || Double.isNaN(weights[i])) {
+			if (Double.isNaN(values[i]) || Double.isNaN(weights[i])) { // not used in lwir
 				weights[i] = 0.0;
 				values[i] = 0.0;
 			}
@@ -277,7 +277,7 @@ public class Correlations2dLMA {
 		pure_weight *= sw;
 	}
 
-	public void toVector() {
+	public void toVector() { // USED in lwir
 		int np = 0;
 		for (int i = 0; i < par_mask.length; i++) if (par_mask[i]) np++;
 		vector = new double[np];
@@ -285,12 +285,12 @@ public class Correlations2dLMA {
 		for (int i = 0; i < par_mask.length; i++) if (par_mask[i]) vector[np++] = all_pars[i];
 	}
 
-	public void updateFromVector() {
+	public void updateFromVector() { // USED in lwir
 		int np = 0;
 		for (int i = 0; i < par_mask.length; i++) if (par_mask[i]) all_pars[i] = vector[np++];
 	}
 
-	public double [] fromVector(double [] vector) { // mix fixed and variable parameters
+	public double [] fromVector(double [] vector) { // mix fixed and variable parameters // USED in lwir
 		if ( all_pars == null) return null;
 		double [] ap = all_pars.clone();
 		int np = 0;
@@ -298,7 +298,7 @@ public class Correlations2dLMA {
 		return ap;
 	}
 
-    public void debugJt(
+    public void debugJt( // not used in lwir
     		double      delta,
     		double []   vector) {
     	int num_points = this.values.length;
@@ -338,7 +338,7 @@ public class Correlations2dLMA {
     }
 
 
-	public double [] getFxJt(
+	public double [] getFxJt( // not used in lwir
 			double      delta, // for testing derivatives: calculates as delta-F/delta_x
 			double []   vector,
 			double [][] jt) { // should be either [vector.length][samples.size()] or null - then only fx is calculated
@@ -361,11 +361,11 @@ public class Correlations2dLMA {
 
 
 
-	public double [] getFx() {
+	public double [] getFx() { // not used in lwir
 		return getFxJt(this.vector, null);
 	}
 
-	public double [] getFxJt(
+	public double [] getFxJt( // USED in lwir
 			double []   vector,
 			double [][] jt) { // should be either [vector.length][samples.size()] or null - then only fx is calculated
 		if (vector == null) return null;
@@ -415,7 +415,7 @@ public class Correlations2dLMA {
 		return fx;
 	}
 
-	public double [][] getWJtJlambda(
+	public double [][] getWJtJlambda( // USED in lwir
 			double      lambda,
 			double [][] jt){
 		int num_pars = jt.length;
@@ -439,7 +439,7 @@ public class Correlations2dLMA {
 	}
 
 	// returns {rms, rms_pure}
-	public double [] getWYmFxRms(
+	public double [] getWYmFxRms( // USED in lwir
 			double []   fx) { // will be replaced with y-fx
 		int num_samples = samples.size();
 		int num_points = fx.length; // includes 2 extra for regularization
@@ -460,7 +460,7 @@ public class Correlations2dLMA {
 		return rslt;
 	}
 
-	public double [] getJtWdiff(
+	public double [] getJtWdiff( // not used in lwir
 			double []   wdiff,
 			double [][] jt){
 		int num_pars = jt.length;
@@ -474,7 +474,7 @@ public class Correlations2dLMA {
 		return wjtymfx;
 	}
 
-	public boolean runLma(
+	public boolean runLma( // USED in lwir
 			double lambda,           // 0.1
 			double lambda_scale_good,// 0.5
 			double lambda_scale_bad, // 8.0
@@ -502,7 +502,7 @@ public class Correlations2dLMA {
 			} else {
 				lambda *= lambda_scale_bad;
 				if (lambda > lambda_max) {
-					break;
+					break; // not used in lwir
 				}
 			}
 		}
@@ -530,7 +530,7 @@ public class Correlations2dLMA {
 
 
 	// returns {success, done}
-	public boolean [] lmaStep(
+	public boolean [] lmaStep( // USED in lwir
 			double lambda,
 			double rms_diff,
 			int debug_level) {
@@ -640,7 +640,7 @@ public class Correlations2dLMA {
 	}
 
 // modify to reuse Samples and apply polynomial approximation to resolve x0,y0 and strength?
-	public double [] getMaxXYPoly( // get interpolated maximum coordinates using 2-nd degree polynomial
+	public double [] getMaxXYPoly( // get interpolated maximum coordinates using 2-nd degree polynomial  // not used in lwir
 ///			double  outside, // how much solution may be outside of the samples
 			boolean debug
      ) {
@@ -703,11 +703,11 @@ public class Correlations2dLMA {
 		this.poly_xyvwh = xyvwh;
 		return xyvwh; // rslt;
 	}
-	public double [] getPoly() {
+	public double [] getPoly() { // not used in lwir
 		return poly_xyvwh;
 	}
-	public double [] getPolyFx() {return getPolyFx(this.poly_coeff);}
-	public double [] getPolyFx(
+	public double [] getPolyFx() {return getPolyFx(this.poly_coeff);} // not used in lwir
+	public double [] getPolyFx( // not used in lwir
 			double [] coeff) { // 6 elements - Xc, Yx, f(x,y), A, B, C (from A*x^2 + B*y^2 +C*x*y+...)
 		if (coeff == null) {
 			return null;