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imagej-elphel
Commit 05e7dbd3 authored by Andrey Filippov's avatar Andrey Filippov
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Implementing LMA to compare performance as a function of the number of 

sensors and interscene accumulation
parent b66e802e
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Showing with 1056 additions and 76 deletions
src/main/java/com/elphel/imagej/tileprocessor/InterIntraLMA.java
View file @ 05e7dbd3
package com.elphel.imagej.tileprocessor;
import java.util.Arrays;
import java.util.concurrent.atomic.AtomicInteger;
import com.elphel.imagej.common.ShowDoubleFloatArrays;
import Jama.Matrix;
/**
**
......@@ -27,8 +32,8 @@ import java.util.Arrays;
**
*/
public class InterIntraLMA {
public static int threadsMax = 100; // maximal number of threads to use
/**
* Estimate noise threshold for each combination of inter/intra and number of
* sensors.
......@@ -46,8 +51,14 @@ public class InterIntraLMA {
int [] sensor_mode_file,
boolean [] inter_file,
boolean [][] good_file_tile,
double min_inter16_noise_level,
int min_modes)
{
int dbg_tile = 1222;
// boolean remove_non_monotonic = false; // true;
boolean zero_all_bad = true; // set noise_level to zero if all noise levels result in bad tiles
boolean all_inter = true; // tile has to be defined for all inter
boolean need_same_inter = true; // do not use intra sample if same inter is bad for all noise levels
int num_sensor_modes = 0;
int num_tiles = good_file_tile[0].length;
for (int i = 0; i < sensor_mode_file.length; i++) {
......@@ -58,7 +69,7 @@ public class InterIntraLMA {
num_sensor_modes ++;
int num_modes = 2 * num_sensor_modes;
double [][] rslt = new double [num_tiles][]; // number of tiles
double [][][] noise_interval = new double[num_modes][num_tiles][2]; // [modes][tiles]
double [][][] noise_interval = new double[num_modes][num_tiles][2]; // [modes][tiles] {max_good, min_bad}
for (int i = 0; i < num_modes; i++) {
for (int j= 0; j < num_tiles; j++) {
noise_interval[i][j][0] =Double.NaN;
......@@ -69,6 +80,9 @@ public class InterIntraLMA {
double noise = noise_file[nf];
int mode = sensor_mode_file[nf] + (inter_file[nf] ? 0: num_sensor_modes);
for (int ntile = 0; ntile < num_tiles; ntile++) {
if (ntile == dbg_tile) {
System.out.println("ntile = "+ntile+", nf ="+nf);
}
if (good_file_tile[nf][ntile]) { // good tile
if (!(noise <= noise_interval[mode][ntile][0])){ // including Double.isNaN(noise_interval[mode][ntile][0]
noise_interval[mode][ntile][0] = noise;
......@@ -80,25 +94,744 @@ public class InterIntraLMA {
}
}
}
for (int ntile = 0; ntile < num_tiles; ntile++){
if (ntile == dbg_tile) {
System.out.println("ntile = "+ntile);
}
int num_defined = 0;
int num_defined_inter = 0;
for (int mode = 0; mode < num_modes; mode++) {
if (!Double.isNaN(noise_interval[mode][ntile][0]) && !Double.isNaN(noise_interval[mode][ntile][0])) {
if (!Double.isNaN(noise_interval[mode][ntile][0]) && !Double.isNaN(noise_interval[mode][ntile][1])) {
num_defined++;
if (mode < 4) {
num_defined_inter++;
}
}
}
if (num_defined >= min_modes) {
//all_inter
if ((num_defined >= min_modes) && (!all_inter || (num_defined_inter >= 4))) {
rslt[ntile] = new double [num_modes];
for (int mode = 0; mode < num_modes; mode++) {
if (!Double.isNaN(noise_interval[mode][ntile][0]) && !Double.isNaN(noise_interval[mode][ntile][0])) {
// if (need_same_inter && (mode >= 4) && Double.isNaN(noise_interval[mode & 3][ntile][0])) { // no good for same sensors inter
if (need_same_inter && Double.isNaN(noise_interval[mode & 3][ntile][0])) { // no good for same sensors inter
rslt[ntile][mode] = Double.NaN;
} else if (!Double.isNaN(noise_interval[mode][ntile][0]) && !Double.isNaN(noise_interval[mode][ntile][1])) {
/*
rslt[ntile][mode] = 0.5 * (noise_interval[mode][ntile][0] + noise_interval[mode][ntile][1]);
if (remove_non_monotonic && (noise_interval[mode][ntile][0] > noise_interval[mode][ntile][1])) {
rslt[ntile][mode] = Double.NaN;
}
*/
// use the lowest failed noise level assuming that false positive may happen even for much higher noise level
rslt[ntile][mode] = noise_interval[mode][ntile][1]; // lowest noise for bad
// } else if (zero_all_bad && Double.isNaN(noise_interval[mode][ntile][1])) {
} else if (zero_all_bad && Double.isNaN(noise_interval[mode][ntile][0])) {
rslt[ntile][mode] = 0.0;
} else {
rslt[ntile][mode] = Double.NaN;
}
}
}
if ((rslt[ntile] != null) && (min_inter16_noise_level >0)){ // filter by to weak inter-16 (mode 0)
if (!(rslt[ntile][0] >= min_inter16_noise_level)){
rslt[ntile] = null;
}
}
if (rslt[ntile] != null) {
boolean all_nan = true;
boolean has_nan = false;
boolean has_inter_nan = false;
for (int mode = 0; mode < rslt[ntile].length; mode++) {
if (Double.isNaN(rslt[ntile][mode])) {
has_nan = true;
if (mode < 4) {
has_inter_nan = true;
}
} else {
all_nan = false;
}
}
if (all_nan) {
System.out.println("All NaN for tile = "+ntile);
}
if (has_nan) {
System.out.println("Has NaN for tile = "+ntile);
}
if (has_inter_nan) {
System.out.println("Has has_inter_nan for tile = "+ntile);
}
}
}
return rslt;
}
//Monotonic function
public int debug_level = 0;
public double offset;
public double lambda = 1.0;
public double lambda_good = 0.5;
public double lambda_bad = 8.0;
// public double rms = Double.NaN;
// public double rms0 = Double.NaN;
public double [] vector; // N0, g[1]... [g7], St[i]
public int [][] sample_indx; // pairs of {tile_index, mode}
public double [] gi;
public double [][] last_jt;// this.last_jt = new double [num_pars][num_points];
public double N0;
public double [] Y;
public double [] K; // scale noise levels to make them near-relative
public int [] tile_index;
public double [] St;
public double [] weights;
public double [] fx;
public double last_rms = Double.NaN;
public double initial_rms = Double.NaN;
public double good_or_bad_rms = Double.NaN;
double [] last_ymfx;
boolean adjust_N0 = true;
boolean adjust_Gi = true;
boolean adjust_St = true;
int dbgTilesX = 80;
int dbgTilesY = 64;
public InterIntraLMA(
double [][] noise_thresh,
double offset, // initial value for N0
int tilesX, // debug images only
int debug_level)
{
boolean debug_img = (debug_level > -1);
// this.gi = g0.clone();
this.offset = offset;
this.debug_level = debug_level;
int num_samples = 0;
int num_tiles = 0;
int num_modes = 0;
for (double [] sample : noise_thresh) if (sample != null) {
for (double d:sample) if (!Double.isNaN(d)) {
num_samples++;
}
num_tiles++;
num_modes = sample.length;
}
this.gi = new double[num_modes];
this.gi[0] = 1.0; // all, inter - ga1n= 1.0
sample_indx = new int [num_samples][2];
tile_index = new int[num_tiles];
N0 = 0.03; // offset; // .01; // offset;
Y = new double[num_samples];
K = new double[num_samples];
weights = new double[num_samples];
St = new double [num_tiles];
Arrays.fill(St, Double.NaN);
last_rms = Double.NaN;
int indx = 0;
int t_indx = 0;
for (int ntile = 0; ntile < noise_thresh.length; ntile++) if (noise_thresh[ntile] != null) {
tile_index[t_indx] = ntile;
for (int mode = 0; mode < noise_thresh[ntile].length; mode++) {
if (!Double.isNaN(noise_thresh[ntile][mode])) {
sample_indx[indx][0] = t_indx; // ntile;
sample_indx[indx][1] = mode;
indx++;
}
}
t_indx++;
}
// create Y, K and weights vectors
for (int nsample = 0; nsample < num_samples; nsample++) {
int tile = tile_index[sample_indx[nsample][0]];
double d = noise_thresh[tile][sample_indx[nsample][1]];
K[nsample] = 1.0/(d + offset);
Y[nsample] = d * K[nsample];
// may be modified, but sum (weights) should be == 1.0;
weights[nsample] = 1.0/num_samples;
}
// initial approximation
double N0 = offset;
double N02 = N0*N0;
// set St for tiles that are defined for mode==0 (inter16)
for (int nsample = 0; nsample < num_samples; nsample++) if (sample_indx[nsample][1] == 0){
double sqrt2 = Y[nsample]/K[nsample];
sqrt2 *= sqrt2;
double st2 = sqrt2 - N02;
int ntile = sample_indx[nsample][0]; // used tile index
if (st2 > 0.0) {
St[ntile] = Math.sqrt(st2);
}
}
// iteratively find gi (other than 0), then refine St
int num_initial_refines = 10; //5;
double [][] dbg_img = debug_img ? (new double [num_initial_refines+1][]) : null;
double [][] dbg_ratio = debug_img ? (new double [num_modes][noise_thresh.length]) : null;
if (dbg_img != null) {
double [] dbg_st = new double [noise_thresh.length];
Arrays.fill(dbg_st,Double.NaN);
for (int ntile = 0; ntile < tile_index.length; ntile++) {
dbg_st[tile_index[ntile]] = St[ntile];
}
dbg_img[0] = dbg_st;
for (int i = 0; i < dbg_ratio.length; i++) {
Arrays.fill(dbg_ratio[i], Double.NaN);
}
for (int ntile = 0; ntile < noise_thresh.length; ntile++) if (noise_thresh[ntile] != null) {
double [] noise_per_mode = noise_thresh[ntile];
for (int mode = 0; mode < num_modes; mode++) {
int mode_ref = (mode > 4) ? 4 : 0;
if (!Double.isNaN(noise_per_mode[mode]) && !Double.isNaN(noise_per_mode[mode_ref])) {
dbg_ratio[mode][ntile] = noise_per_mode[mode]/noise_per_mode[mode_ref];
}
}
}
String [] dbg_ratio_titles = {"0/0","1/0","2/0", "3/0", "4/0","5/4","6/4","7/4"};
(new ShowDoubleFloatArrays()).showArrays(
dbg_ratio,
tilesX,
noise_thresh.length/ tilesX,
true,
"dbg_ratio",
dbg_ratio_titles);
}
dbgTilesX = tilesX;
dbgTilesY = noise_thresh.length/ tilesX;
for (int nrefine = 0; nrefine < num_initial_refines; nrefine++) {
// finding g[i]
gi = new double[num_modes];
// gi[0] = 1.0; // all, inter - gain= 1.0
double [] wgi = new double [num_modes]; // weights
double scale_zero = 0.1; // weight of zero samples
for (int nsample = 0; nsample < num_samples; nsample++) { // if (sample_indx[nsample][1] != 0){
int ntile = sample_indx[nsample][0]; // used tile index
double st = St[ntile];
if (!Double.isNaN(st)) {
int mode = sample_indx[nsample][1];
double sqrt2 = Y[nsample]/K[nsample];
sqrt2 *= sqrt2;
double gi2 = (sqrt2 - N02) / (st * st);
if (gi2 > 0.0) {
wgi[mode] += weights[nsample];
gi[mode] += weights[nsample] * Math.sqrt(gi2);
} else {
wgi[mode] += weights[nsample] * scale_zero;
}
}
}
// for (int mode = 1; mode < num_modes; mode++) {
for (int mode = 0; mode < num_modes; mode++) {
gi[mode] /= wgi[mode];
}
if (debug_level > -1) {
System.out.println("Iteration "+nrefine+":");
for (int i = 0; i < gi.length; i++) {
System.out.println("g["+i+"] = "+gi[i]);
}
}
gi[0] = 1.0; // all, inter - gain= 1.0
// Recalculate St, using current gi
St = new double [num_tiles];
double [] stw = new double [num_tiles];
for (int nsample = 0; nsample < num_samples; nsample++) { // if (sample_indx[nsample][1] != 0){
int ntile = sample_indx[nsample][0]; // used tile index
int mode = sample_indx[nsample][1];
if (mode < 4) { // trying - only use inter data to adjust St
double w = weights[nsample];
double sqrt2 = Y[nsample]/K[nsample];
sqrt2 *= sqrt2;
double st2 = (sqrt2 - N02) / (gi[mode] * gi[mode]);
if (st2 > 0.0) {
stw[ntile] += w;
St[ntile] += w * Math.sqrt(st2);
}
}
}
for (int ntile = 0; ntile < num_tiles; ntile++) {
if (stw[ntile] > 0.0) {
St[ntile] /= stw[ntile];
} else {
St[ntile] = Double.NaN;
}
}
if (dbg_img != null) {
double [] dbg_st = new double [noise_thresh.length];
Arrays.fill(dbg_st,Double.NaN);
for (int ntile = 0; ntile < tile_index.length; ntile++) {
dbg_st[tile_index[ntile]] = St[ntile];
}
dbg_img[nrefine+1] = dbg_st;
}
}
if (dbg_img != null) {
(new ShowDoubleFloatArrays()).showArrays(
dbg_img,
tilesX,
noise_thresh.length/ tilesX,
true,
"pre_lma_st");
}
return;
}
private double [] getVector(
boolean adjust_N0,
boolean adjust_Gi,
boolean adjust_St,
double n0,
double [] gi,
double [] st) {
this.adjust_N0 = adjust_N0;
this.adjust_Gi = adjust_Gi;
this.adjust_St = adjust_St;
double [] v = new double [(adjust_N0 ? 1 : 0) + (adjust_Gi ? (gi.length - 1) : 0) + (adjust_St ? st.length : 0)];
if (adjust_N0) {
v[0] = n0;
}
if (adjust_Gi) {
System.arraycopy(gi, 1, v, (adjust_N0 ? 1 : 0), gi.length-1);
}
if (adjust_St) {
System.arraycopy(st, 0, v, (adjust_N0 ? 1 : 0) + (adjust_Gi ? (gi.length - 1) : 0), st.length);
}
return v;
}
private double getN0(double [] v) {
return adjust_N0 ? v[0] : N0;
}
private double [] getGi(double [] v) {
double [] gi = new double [this.gi.length];
gi[0] = 1.0;
if (adjust_Gi) {
System.arraycopy(v, (adjust_N0 ? 1 : 0), gi, 1, gi.length-1);
} else {
System.arraycopy(this.gi, 1, gi, 1, gi.length-1);
}
return gi;
}
private double [] getSt(double [] v) {
double [] st; // = new double [this.St.length]; // .length - this.gi.length];
if (adjust_St) {
st = new double [this.St.length]; // .length - this.gi.length];
System.arraycopy(v, (adjust_N0 ? 1 : 0) + (adjust_Gi ? (gi.length - 1) : 0), st, 0, st.length);
return st;
} else {
return St.clone();
}
}
private double [] getYminusFxWeighted(double [] fx)
{
double [] y_minus_fx_weighted = new double [fx.length];
for (int i = 0; i < fx.length; i++) {
y_minus_fx_weighted[i] = weights[i]*(Y[i] - fx[i]);
if (Double.isNaN(y_minus_fx_weighted[i])) {
System.out.println("y_minus_fx_weighted["+i+"]= NaN");
y_minus_fx_weighted[i] = 0.0;
}
}
return y_minus_fx_weighted;
}
private double [] getFxJt(
double [] vector,
double [][] jt) { // should be either [vector.length][samples.size()] or null - then only fx is calculated
double n0= getN0(vector);
double [] gi = getGi(vector);
double [] st = getSt(vector);
double [] fx = new double [sample_indx.length];
if (jt != null) { // calculate Jacobian
for (int i = 0; i < jt.length; i++) {
Arrays.fill(jt[i],0.0);
}
}
for (int i = 0; i < fx.length; i++) {
int itile = sample_indx[i][0];
int mode = sample_indx[i][1];
double nv2 = st[itile]*gi[mode];
nv2 *= nv2;
nv2 -= n0*n0;
if (nv2 > 0) { // if <=0 - keep 0.0
double sqrt = Math.sqrt(nv2);
fx[i] = K[i] * sqrt;
if (jt != null) {
double Amti = K[i]/sqrt;
int indx = 0;
if (adjust_N0) {
jt[indx++][i] = - Amti * n0;
}
double asg = Amti*st[itile]*gi[mode];
if (adjust_Gi && (mode > 0)) {
jt[indx + mode -1][i] = asg *st[itile];
indx += gi.length -1;
}
if (adjust_St) {
jt[indx + itile][i] = asg * gi[mode];
}
}
}
}
return fx;
}
public double [][] getYDbg() {
double [][] dbg_Y = new double [gi.length][dbgTilesX*dbgTilesY];
for (int mode = 0; mode < dbg_Y.length; mode++) {
Arrays.fill(dbg_Y[mode], Double.NaN);
}
for (int i = 0; i < Y.length; i++) {
int itile = sample_indx[i][0];
int mode = sample_indx[i][1];
int tile = tile_index[itile];
dbg_Y[mode][tile] = Y[i];
}
return dbg_Y;
}
public double [][] getFxDbg() {
double [][] dbg_Fx = new double [gi.length][dbgTilesX*dbgTilesY];
for (int mode = 0; mode < dbg_Fx.length; mode++) {
Arrays.fill(dbg_Fx[mode], Double.NaN);
}
double [] fx = getFxJt(
vector, // double [] vector,
null); // double [][] jt)
for (int i = 0; i < Y.length; i++) {
int itile = sample_indx[i][0];
int mode = sample_indx[i][1];
int tile = tile_index[itile];
dbg_Fx[mode][tile] = fx[i];
}
return dbg_Fx;
}
private double [] getWYMinusFx(
double [] vector,
double [] weights) {
double [] fx = getFxJt(vector, null);
double [] wymfx = new double [fx.length];
for (int i = 0; i < wymfx.length; i++) {
wymfx[i] = Y[i] - fx[i];
}
if (weights != null) {
for (int i = 0; i < wymfx.length; i++) {
wymfx[i] *= weights[i];
}
}
return wymfx;
}
private double getRms(
double [] fx) // weights should be normalized to sum==1.0
{
double swd2 = 0.0;
for (int i = 0; i < fx.length; i++) {
double d = Y[i] - fx[i];
if (Double.isNaN(d)) {
System.out.println("getRms(): Y["+i+"] - fx["+i+"] = NaN");
d=0.0;
}
swd2 += weights[i]*d *d;
}
return Math.sqrt(swd2);
}
/*
public double [][] getWJtJlambda_single(
double lambda,
double [][] jt){
int num_pars = jt.length;
int nup_points = (num_pars > 0)? jt[0].length : 0;
double [][] wjtjl = new double [num_pars][num_pars];
for (int i = 0; i < num_pars; i++) {
for (int j = i; j < num_pars; j++) {
double d = 0.0;
for (int k = 0; k < nup_points; k++) {
d += this.weights[k]*jt[i][k]*jt[j][k];
}
wjtjl[i][j] = d;
if (i == j) {
wjtjl[i][j] += d * lambda;
} else {
wjtjl[j][i] = d;
}
}
}
return wjtjl;
}
*/
//public static int threadsMax = 100; // maximal number of threads to use
public double [][] getWJtJlambda(
final double lambda,
final double [][] jt){
final int num_pars = jt.length;
final int num_points = (num_pars > 0)? jt[0].length : 0;
final Thread[] threads = ImageDtt.newThreadArray(threadsMax);
final AtomicInteger ai = new AtomicInteger(0);
final double [][] wjtjl = new double [num_pars][num_pars];
final int num_cells = num_pars * num_pars;
for (int ithread = 0; ithread < threads.length; ithread++) {
threads[ithread] = new Thread() {
@Override
public void run() {
for (int iCell = ai.getAndIncrement(); iCell < num_cells; iCell = ai.getAndIncrement()) {
int i = iCell / num_pars;
int j = iCell % num_pars;
if (j >= i) { // just skip unneeded
double d = 0.0;
for (int k = 0; k < num_points; k++) {
d += weights[k]*jt[i][k]*jt[j][k];
}
wjtjl[i][j] = d;
if (i == j) {
wjtjl[i][j] += d * lambda;
if (d == 0) {
System.out.println("Diagonal ZERO for i=j="+i+" absolute tile = "+tile_index[i-8]); // assuming N0, gi[1]...gi[7]
wjtjl[i][j] = 1.0; // Jt * (y-fx) will anyway be 0, so any value here should work.
}
} else {
wjtjl[j][i] = d;
}
}
}
}
};
}
ImageDtt.startAndJoin(threads);
return wjtjl;
}
//last_rms = Double.NaN;
public boolean runLma(
boolean adjust_N0,
boolean adjust_Gi,
boolean adjust_St,
double lambda, // 0.1
double lambda_scale_good,// 0.5
double lambda_scale_bad, // 8.0
double lambda_max, // 100
double rms_diff, // 0.001
int num_iter, // 20
int debug_level)
{
vector = getVector(
adjust_N0, // boolean adjust_N0,
adjust_Gi, // boolean adjust_Gi,
adjust_St, // boolean adjust_St,
N0, // double n0,
gi, // double [] gi,
St); // double [] st) {
boolean [] rslt = {false,false};
this.last_rms = Double.NaN;
int iter = 0;
for (iter = 0; iter < num_iter; iter++) {
rslt = lmaStep(
lambda,
rms_diff,
debug_level);
if (rslt == null) {
return false; // need to check
}
if (debug_level > 1) {
System.out.println("LMA step "+iter+": {"+rslt[0]+","+rslt[1]+"} full RMS= "+good_or_bad_rms+
" ("+initial_rms+"), lambda="+lambda);
}
if (rslt[1]) {
break;
}
if (rslt[0]) { // good
lambda *= lambda_scale_good;
} else {
lambda *= lambda_scale_bad;
if (lambda > lambda_max) {
break; // not used in lwir
}
}
}
if (rslt[0]) { // better, but num tries exceeded
if (iter >= num_iter) {
if (debug_level > 0) System.out.println("Step "+iter+": Improved, but number of steps exceeded maximal");
} else {
if (debug_level > 0) System.out.println("Step "+iter+": LMA: Success");
}
} else { // improved over initial ?
if (last_rms < initial_rms) {
rslt[0] = true;
if (debug_level > 0) System.out.println("Step "+iter+": Failed to converge, but result improved over initial");
} else {
if (debug_level > 0) System.out.println("Step "+iter+": Failed to converge");
}
}
if (debug_level > 0) {
System.out.println("LMA: full RMS="+last_rms+" ("+initial_rms+"), lambda="+lambda);
}
if (rslt[0]) { // success
if (adjust_N0) {
N0 = getN0(vector);
}
if (adjust_Gi) {
gi = getGi(vector);
}
if (adjust_St) {
St = getSt(vector);
}
}
return rslt[0];
}
public boolean [] lmaStep(
double lambda,
double rms_diff,
int debug_level) {
int num_points = this.weights.length; // includes 2 extra for regularization
int num_pars = vector.length;
boolean [] rslt = {false,false};
boolean dbg_img = debug_level > 2;
if (Double.isNaN(last_rms)) { //first time, need to calculate all (vector is valid)
last_jt = new double [num_pars][num_points];
double [] fx = getFxJt(
vector, // double [] vector,
last_jt); // double [][] jt) { // should be either [vector.length][samples.size()] or null - then only fx is calculated
if (fx == null) {
return null; // need to re-init/restart LMA
}
last_ymfx = getYminusFxWeighted (fx);
last_rms = getRms(fx);
initial_rms = last_rms;
good_or_bad_rms = last_rms;
if (dbg_img) {
double [][] dbg_Y = getYDbg();
(new ShowDoubleFloatArrays()).showArrays(
dbg_Y,
dbgTilesX,
dbgTilesY,
true,
"dbg_Y");
double [][] dbg_Fx = getFxDbg();
(new ShowDoubleFloatArrays()).showArrays(
dbg_Fx,
dbgTilesX,
dbgTilesY,
true,
"dbg_Fx");
}
/*
if (debug_level > 3) {
debugJt(
0.000001, // double delta, // 0.2, //
this.vector); // double [] vector);
}
*/
}
Matrix y_minus_fx_weighted = new Matrix(last_ymfx, last_ymfx.length);
Matrix wjtjlambda = new Matrix(getWJtJlambda(
lambda, // *10, // temporary
last_jt)); // double [][] jt)
if (debug_level>2) {
System.out.println("JtJ + lambda*diag(JtJ");
wjtjlambda.print(18, 6);
}
Matrix jtjl_inv = null;
try {
jtjl_inv = wjtjlambda.inverse(); // check for errors
} catch (RuntimeException e) {
rslt[1] = true;
if (debug_level > 0) {
System.out.println("Singular Matrix!");
}
return rslt;
}
if (debug_level>2) {
System.out.println("(JtJ + lambda*diag(JtJ)).inv()");
jtjl_inv.print(18, 6);
}
//last_jt has NaNs
Matrix jty = (new Matrix(this.last_jt)).times(y_minus_fx_weighted);
if (debug_level>2) {
System.out.println("Jt * (y-fx)");
jty.print(18, 6);
}
Matrix mdelta = jtjl_inv.times(jty);
if (debug_level>2) {
System.out.println("mdelta");
mdelta.print(18, 6);
}
double [] delta = mdelta.getColumnPackedCopy();
double [] new_vector = this.vector.clone();
for (int i = 0; i < num_pars; i++) new_vector[i]+= delta[i];
// being optimistic, modify jt and last_ymfx in place, restore if failed
double [] fx = getFxJt( //
new_vector, // double [] vector,
last_jt); // double [][] jt) { // should be either [vector.length][samples.size()] or null - then only fx is calculated
if (fx == null) {
return null; // need to re-init/restart LMA
}
double [] new_ymfx = getYminusFxWeighted (fx); // weighted
double rms = getRms(fx); // new rms
good_or_bad_rms = rms;
if (rms < last_rms) { // improved
rslt[0] = true;
rslt[1] = rms >=(last_rms * (1.0 - rms_diff));
last_rms = rms; // update
vector = new_vector.clone(); // update
last_ymfx = new_ymfx; // update
if (debug_level > 1) {
System.out.print("New vector: ");
for (int np = 0; np < vector.length; np++) {
System.out.print(this.vector[np]+" ");
}
System.out.println();
}
} else { // worsened
rslt[0] = false;
rslt[1] = false; // do not know, caller will decide
// restore state
/*
fx = getFxJt( //
vector, // it was not updated // new_vector, // double [] vector,
last_jt); // double [][] jt) { // should be either [vector.length][samples.size()] or null - then only fx is calculated
if (fx == null) {
return null; // need to re-init/restart LMA
}
last_ymfx = getYminusFxWeighted (fx);
last_rms = getRms(fx);
*/
/*
if (debug_level > 2) {
debugJt(
0.000001, // double delta,
this.vector); // double [] vector);
}
*/
}
return rslt;
}
}
src/main/java/com/elphel/imagej/tileprocessor/TwoQuadCLT.java
View file @ 05e7dbd3
......@@ -8715,7 +8715,6 @@ if (debugLevel > -100) return true; // temporarily !
// 1626032208_613623-results-rnd_0.003-fpn_0.0-sigma_1.5-offset1.0-sensors16-inter.tiff
double [][] noise_task = {
/*
{0.00, 0.0, 1.5, 1.4142, 0.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, inter
{0.00, 0.0, 1.5, 1.4142, 0.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, intra
{0.00, 0.0, 1.5, 1.4142, 3.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors8, inter
......@@ -8725,60 +8724,125 @@ if (debugLevel > -100) return true; // temporarily !
{0.00, 0.0, 1.5, 1.4142, 1.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, inter
{0.00, 0.0, 1.5, 1.4142, 1.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, intra
{0.003,0.0, 1.5, 1.4142, 0.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, inter
/*{0.003,0.0, 1.5, 1.4142, 0.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, inter
{0.003,0.0, 1.5, 1.4142, 0.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, intra
{0.003,0.0, 1.5, 1.4142, 3.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors8, inter
{0.003,0.0, 1.5, 1.4142, 3.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors8, intra
{0.003,0.0, 1.5, 1.4142, 2.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors4, inter
{0.003,0.0, 1.5, 1.4142, 2.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors4, intra
{0.003,0.0, 1.5, 1.4142, 1.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, inter
{0.003,0.0, 1.5, 1.4142, 1.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, intra
{0.003,0.0, 1.5, 1.4142, 1.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, intra*/
{0.01, 0.0, 1.5, 1.4142, 0.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, inter
/*{0.01, 0.0, 1.5, 1.4142, 0.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, inter
{0.01, 0.0, 1.5, 1.4142, 0.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, intra
{0.01, 0.0, 1.5, 1.4142, 3.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors8, inter
{0.01, 0.0, 1.5, 1.4142, 3.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors8, intra
{0.01, 0.0, 1.5, 1.4142, 2.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors4, inter
{0.01, 0.0, 1.5, 1.4142, 2.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors4, intra
{0.01, 0.0, 1.5, 1.4142, 1.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, inter
{0.01, 0.0, 1.5, 1.4142, 1.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, intra
{0.01, 0.0, 1.5, 1.4142, 1.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, intra*/
{0.02, 0.0, 1.5, 1.4142, 0.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, inter
{0.02, 0.0, 1.5, 1.4142, 0.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, intra
{0.02, 0.0, 1.5, 1.4142, 3.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors8, inter
{0.02, 0.0, 1.5, 1.4142, 3.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors8, intra
{0.02, 0.0, 1.5, 1.4142, 2.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors4, inter
{0.02, 0.0, 1.5, 1.4142, 2.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors4, intra
{0.02, 0.0, 1.5, 1.4142, 1.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, inter
{0.02, 0.0, 1.5, 1.4142, 1.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, intra
{0.03, 0.0, 1.5, 1.4142, 0.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, inter
/*{0.03, 0.0, 1.5, 1.4142, 0.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, inter
{0.03, 0.0, 1.5, 1.4142, 0.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, intra
{0.03, 0.0, 1.5, 1.4142, 3.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors8, inter
{0.03, 0.0, 1.5, 1.4142, 3.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors8, intra
{0.03, 0.0, 1.5, 1.4142, 2.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors4, inter
{0.03, 0.0, 1.5, 1.4142, 2.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors4, intra
{0.03, 0.0, 1.5, 1.4142, 1.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, inter
{0.03, 0.0, 1.5, 1.4142, 1.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, intra
{0.06, 0.0, 1.5, 1.4142, 0.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, inter
{0.03, 0.0, 1.5, 1.4142, 1.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, intra*/
/*{0.04, 0.0, 1.5, 1.4142, 0.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, inter
{0.04, 0.0, 1.5, 1.4142, 0.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, intra
{0.04, 0.0, 1.5, 1.4142, 3.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors8, inter
{0.04, 0.0, 1.5, 1.4142, 3.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors8, intra
{0.04, 0.0, 1.5, 1.4142, 2.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors4, inter
{0.04, 0.0, 1.5, 1.4142, 2.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors4, intra
{0.04, 0.0, 1.5, 1.4142, 1.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, inter
{0.04, 0.0, 1.5, 1.4142, 1.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, intra*/
{0.05, 0.0, 1.5, 1.4142, 0.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, inter
{0.05, 0.0, 1.5, 1.4142, 0.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, intra
{0.05, 0.0, 1.5, 1.4142, 3.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors8, inter
{0.05, 0.0, 1.5, 1.4142, 3.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors8, intra
{0.05, 0.0, 1.5, 1.4142, 2.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors4, inter
{0.05, 0.0, 1.5, 1.4142, 2.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors4, intra
{0.05, 0.0, 1.5, 1.4142, 1.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, inter
{0.05, 0.0, 1.5, 1.4142, 1.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, intra
/*{0.06, 0.0, 1.5, 1.4142, 0.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, inter
{0.06, 0.0, 1.5, 1.4142, 0.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, intra
{0.06, 0.0, 1.5, 1.4142, 3.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors8, inter
{0.06, 0.0, 1.5, 1.4142, 3.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors8, intra
{0.06, 0.0, 1.5, 1.4142, 2.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors4, inter
{0.06, 0.0, 1.5, 1.4142, 2.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors4, intra
{0.06, 0.0, 1.5, 1.4142, 1.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, inter
{0.06, 0.0, 1.5, 1.4142, 1.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, intra
{0.1, 0.0, 1.5, 1.4142, 0.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, inter
{0.06, 0.0, 1.5, 1.4142, 1.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, intra*/
/*{0.08, 0.0, 1.5, 1.4142, 0.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, inter
{0.08, 0.0, 1.5, 1.4142, 0.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, intra
{0.08, 0.0, 1.5, 1.4142, 3.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors8, inter
{0.08, 0.0, 1.5, 1.4142, 3.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors8, intra
{0.08, 0.0, 1.5, 1.4142, 2.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors4, inter
{0.08, 0.0, 1.5, 1.4142, 2.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors4, intra
{0.08, 0.0, 1.5, 1.4142, 1.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, inter
{0.08, 0.0, 1.5, 1.4142, 1.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, intra*/
/*{0.1, 0.0, 1.5, 1.4142, 0.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, inter
{0.1, 0.0, 1.5, 1.4142, 0.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, intra
{0.1, 0.0, 1.5, 1.4142, 3.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors8, inter
{0.1, 0.0, 1.5, 1.4142, 3.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors8, intra
{0.1, 0.0, 1.5, 1.4142, 2.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors4, inter
{0.1, 0.0, 1.5, 1.4142, 2.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors4, intra
{0.1, 0.0, 1.5, 1.4142, 1.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, inter
{0.1, 0.0, 1.5, 1.4142, 1.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, intra
{0.2, 0.0, 1.5, 1.4142, 0.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, inter
{0.1, 0.0, 1.5, 1.4142, 1.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, intra*/
/*{0.13, 0.0, 1.5, 1.4142, 0.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, inter
{0.13, 0.0, 1.5, 1.4142, 0.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, intra
{0.13, 0.0, 1.5, 1.4142, 3.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors8, inter
{0.13, 0.0, 1.5, 1.4142, 3.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors8, intra
{0.13, 0.0, 1.5, 1.4142, 2.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors4, inter
{0.13, 0.0, 1.5, 1.4142, 2.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors4, intra
{0.13, 0.0, 1.5, 1.4142, 1.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, inter
{0.13, 0.0, 1.5, 1.4142, 1.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, intra*/
/*{0.16, 0.0, 1.5, 1.4142, 0.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, inter
{0.16, 0.0, 1.5, 1.4142, 0.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, intra
{0.16, 0.0, 1.5, 1.4142, 3.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors8, inter
{0.16, 0.0, 1.5, 1.4142, 3.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors8, intra
{0.16, 0.0, 1.5, 1.4142, 2.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors4, inter
{0.16, 0.0, 1.5, 1.4142, 2.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors4, intra
{0.16, 0.0, 1.5, 1.4142, 1.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, inter
{0.16, 0.0, 1.5, 1.4142, 1.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, intra*/
/*{0.2, 0.0, 1.5, 1.4142, 0.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, inter
{0.2, 0.0, 1.5, 1.4142, 0.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, intra
{0.2, 0.0, 1.5, 1.4142, 3.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors8, inter
{0.2, 0.0, 1.5, 1.4142, 3.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors8, intra
{0.2, 0.0, 1.5, 1.4142, 2.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors4, inter
{0.2, 0.0, 1.5, 1.4142, 2.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors4, intra
{0.2, 0.0, 1.5, 1.4142, 1.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, inter
{0.2, 0.0, 1.5, 1.4142, 1.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, intra
{0.3, 0.0, 1.5, 1.4142, 0.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, inter
{0.2, 0.0, 1.5, 1.4142, 1.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, intra*/
/*{0.25, 0.0, 1.5, 1.4142, 0.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, inter
{0.25, 0.0, 1.5, 1.4142, 0.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, intra
{0.25, 0.0, 1.5, 1.4142, 3.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors8, inter
{0.25, 0.0, 1.5, 1.4142, 3.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors8, intra
{0.25, 0.0, 1.5, 1.4142, 2.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors4, inter
{0.25, 0.0, 1.5, 1.4142, 2.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors4, intra
{0.25, 0.0, 1.5, 1.4142, 1.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, inter
{0.25, 0.0, 1.5, 1.4142, 1.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, intra*/
/*{0.3, 0.0, 1.5, 1.4142, 0.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, inter
{0.3, 0.0, 1.5, 1.4142, 0.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, intra
{0.3, 0.0, 1.5, 1.4142, 3.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors8, inter
{0.3, 0.0, 1.5, 1.4142, 3.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors8, intra
......@@ -8813,7 +8877,7 @@ if (debugLevel > -100) return true; // temporarily !
{0.6, 0.0, 1.5, 1.4142, 2.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors4, intra
{0.6, 0.0, 1.5, 1.4142, 1.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, inter
{0.6, 0.0, 1.5, 1.4142, 1.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, intra
*/
{0.7, 0.0, 1.5, 1.4142, 0.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, inter
{0.7, 0.0, 1.5, 1.4142, 0.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, intra
{0.7, 0.0, 1.5, 1.4142, 3.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors8, inter
......@@ -8821,17 +8885,35 @@ if (debugLevel > -100) return true; // temporarily !
{0.7, 0.0, 1.5, 1.4142, 2.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors4, inter
{0.7, 0.0, 1.5, 1.4142, 2.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors4, intra
{0.7, 0.0, 1.5, 1.4142, 1.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, inter
{0.7, 0.0, 1.5, 1.4142, 1.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, intra
{0.7, 0.0, 1.5, 1.4142, 1.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, intra*/
{0.8, 0.0, 1.5, 1.4142, 0.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, inter
/*{0.8, 0.0, 1.5, 1.4142, 0.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, inter
{0.8, 0.0, 1.5, 1.4142, 0.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, intra
{0.8, 0.0, 1.5, 1.4142, 3.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors8, inter
{0.8, 0.0, 1.5, 1.4142, 3.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors8, intra
{0.8, 0.0, 1.5, 1.4142, 2.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors4, inter
{0.8, 0.0, 1.5, 1.4142, 2.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors4, intra
{0.8, 0.0, 1.5, 1.4142, 1.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, inter
{0.8, 0.0, 1.5, 1.4142, 1.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, intra
{0.8, 0.0, 1.5, 1.4142, 1.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, intra*/
{0.9, 0.0, 1.5, 1.4142, 0.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, inter
{0.9, 0.0, 1.5, 1.4142, 0.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, intra
{0.9, 0.0, 1.5, 1.4142, 3.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors8, inter
{0.9, 0.0, 1.5, 1.4142, 3.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors8, intra
{0.9, 0.0, 1.5, 1.4142, 2.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors4, inter
{0.9, 0.0, 1.5, 1.4142, 2.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors4, intra
{0.9, 0.0, 1.5, 1.4142, 1.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, inter
{0.9, 0.0, 1.5, 1.4142, 1.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, intra
{1.0, 0.0, 1.5, 1.4142, 0.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, inter
{1.0, 0.0, 1.5, 1.4142, 0.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors16, intra
{1.0, 0.0, 1.5, 1.4142, 3.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors8, inter
{1.0, 0.0, 1.5, 1.4142, 3.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors8, intra
{1.0, 0.0, 1.5, 1.4142, 2.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors4, inter
{1.0, 0.0, 1.5, 1.4142, 2.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors4, intra
{1.0, 0.0, 1.5, 1.4142, 1.0, 1.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, inter
{1.0, 0.0, 1.5, 1.4142, 1.0, 0.0}, // rnad = 0.06, fpn = 0.0, sigma = 1.5, offset = 1.0, sensors2, intra
};
System.out.println ("\n\n\n");
System.out.println("Noise parameters for this batch run are hard-wired in the code above this line");
......@@ -9049,6 +9131,7 @@ if (debugLevel > -100) return true; // temporarily !
"-results-rnd_0.003-fpn_0.0-sigma_1.5-offset1.4142-sensors4-nointer-nolma",
"-results-rnd_0.003-fpn_0.0-sigma_1.5-offset1.4142-sensors8-inter-nolma",
"-results-rnd_0.003-fpn_0.0-sigma_1.5-offset1.4142-sensors8-nointer-nolma",
"-results-rnd_0.01-fpn_0.0-sigma_1.5-offset1.4142-sensors16-inter-nolma",
"-results-rnd_0.01-fpn_0.0-sigma_1.5-offset1.4142-sensors16-nointer-nolma",
"-results-rnd_0.01-fpn_0.0-sigma_1.5-offset1.4142-sensors2-inter-nolma",
......@@ -9057,6 +9140,16 @@ if (debugLevel > -100) return true; // temporarily !
"-results-rnd_0.01-fpn_0.0-sigma_1.5-offset1.4142-sensors4-nointer-nolma",
"-results-rnd_0.01-fpn_0.0-sigma_1.5-offset1.4142-sensors8-inter-nolma",
"-results-rnd_0.01-fpn_0.0-sigma_1.5-offset1.4142-sensors8-nointer-nolma",
"-results-rnd_0.02-fpn_0.0-sigma_1.5-offset1.4142-sensors16-inter-nolma",
"-results-rnd_0.02-fpn_0.0-sigma_1.5-offset1.4142-sensors16-nointer-nolma",
"-results-rnd_0.02-fpn_0.0-sigma_1.5-offset1.4142-sensors2-inter-nolma",
"-results-rnd_0.02-fpn_0.0-sigma_1.5-offset1.4142-sensors2-nointer-nolma",
"-results-rnd_0.02-fpn_0.0-sigma_1.5-offset1.4142-sensors4-inter-nolma",
"-results-rnd_0.02-fpn_0.0-sigma_1.5-offset1.4142-sensors4-nointer-nolma",
"-results-rnd_0.02-fpn_0.0-sigma_1.5-offset1.4142-sensors8-inter-nolma",
"-results-rnd_0.02-fpn_0.0-sigma_1.5-offset1.4142-sensors8-nointer-nolma",
"-results-rnd_0.03-fpn_0.0-sigma_1.5-offset1.4142-sensors16-inter-nolma",
"-results-rnd_0.03-fpn_0.0-sigma_1.5-offset1.4142-sensors16-nointer-nolma",
"-results-rnd_0.03-fpn_0.0-sigma_1.5-offset1.4142-sensors2-inter-nolma",
......@@ -9065,6 +9158,25 @@ if (debugLevel > -100) return true; // temporarily !
"-results-rnd_0.03-fpn_0.0-sigma_1.5-offset1.4142-sensors4-nointer-nolma",
"-results-rnd_0.03-fpn_0.0-sigma_1.5-offset1.4142-sensors8-inter-nolma",
"-results-rnd_0.03-fpn_0.0-sigma_1.5-offset1.4142-sensors8-nointer-nolma",
"-results-rnd_0.04-fpn_0.0-sigma_1.5-offset1.4142-sensors16-inter-nolma",
"-results-rnd_0.04-fpn_0.0-sigma_1.5-offset1.4142-sensors16-nointer-nolma",
"-results-rnd_0.04-fpn_0.0-sigma_1.5-offset1.4142-sensors2-inter-nolma",
"-results-rnd_0.04-fpn_0.0-sigma_1.5-offset1.4142-sensors2-nointer-nolma",
"-results-rnd_0.04-fpn_0.0-sigma_1.5-offset1.4142-sensors4-inter-nolma",
"-results-rnd_0.04-fpn_0.0-sigma_1.5-offset1.4142-sensors4-nointer-nolma",
"-results-rnd_0.04-fpn_0.0-sigma_1.5-offset1.4142-sensors8-inter-nolma",
"-results-rnd_0.04-fpn_0.0-sigma_1.5-offset1.4142-sensors8-nointer-nolma",
"-results-rnd_0.05-fpn_0.0-sigma_1.5-offset1.4142-sensors16-inter-nolma",
"-results-rnd_0.05-fpn_0.0-sigma_1.5-offset1.4142-sensors16-nointer-nolma",
"-results-rnd_0.05-fpn_0.0-sigma_1.5-offset1.4142-sensors2-inter-nolma",
"-results-rnd_0.05-fpn_0.0-sigma_1.5-offset1.4142-sensors2-nointer-nolma",
"-results-rnd_0.05-fpn_0.0-sigma_1.5-offset1.4142-sensors4-inter-nolma",
"-results-rnd_0.05-fpn_0.0-sigma_1.5-offset1.4142-sensors4-nointer-nolma",
"-results-rnd_0.05-fpn_0.0-sigma_1.5-offset1.4142-sensors8-inter-nolma",
"-results-rnd_0.05-fpn_0.0-sigma_1.5-offset1.4142-sensors8-nointer-nolma",
"-results-rnd_0.06-fpn_0.0-sigma_1.5-offset1.4142-sensors16-inter-nolma",
"-results-rnd_0.06-fpn_0.0-sigma_1.5-offset1.4142-sensors16-nointer-nolma",
"-results-rnd_0.06-fpn_0.0-sigma_1.5-offset1.4142-sensors2-inter-nolma",
......@@ -9073,6 +9185,16 @@ if (debugLevel > -100) return true; // temporarily !
"-results-rnd_0.06-fpn_0.0-sigma_1.5-offset1.4142-sensors4-nointer-nolma",
"-results-rnd_0.06-fpn_0.0-sigma_1.5-offset1.4142-sensors8-inter-nolma",
"-results-rnd_0.06-fpn_0.0-sigma_1.5-offset1.4142-sensors8-nointer-nolma",
"-results-rnd_0.08-fpn_0.0-sigma_1.5-offset1.4142-sensors16-inter-nolma",
"-results-rnd_0.08-fpn_0.0-sigma_1.5-offset1.4142-sensors16-nointer-nolma",
"-results-rnd_0.08-fpn_0.0-sigma_1.5-offset1.4142-sensors2-inter-nolma",
"-results-rnd_0.08-fpn_0.0-sigma_1.5-offset1.4142-sensors2-nointer-nolma",
"-results-rnd_0.08-fpn_0.0-sigma_1.5-offset1.4142-sensors4-inter-nolma",
"-results-rnd_0.08-fpn_0.0-sigma_1.5-offset1.4142-sensors4-nointer-nolma",
"-results-rnd_0.08-fpn_0.0-sigma_1.5-offset1.4142-sensors8-inter-nolma",
"-results-rnd_0.08-fpn_0.0-sigma_1.5-offset1.4142-sensors8-nointer-nolma",
"-results-rnd_0.1-fpn_0.0-sigma_1.5-offset1.4142-sensors16-inter-nolma",
"-results-rnd_0.1-fpn_0.0-sigma_1.5-offset1.4142-sensors16-nointer-nolma",
"-results-rnd_0.1-fpn_0.0-sigma_1.5-offset1.4142-sensors2-inter-nolma",
......@@ -9081,6 +9203,24 @@ if (debugLevel > -100) return true; // temporarily !
"-results-rnd_0.1-fpn_0.0-sigma_1.5-offset1.4142-sensors4-nointer-nolma",
"-results-rnd_0.1-fpn_0.0-sigma_1.5-offset1.4142-sensors8-inter-nolma",
"-results-rnd_0.1-fpn_0.0-sigma_1.5-offset1.4142-sensors8-nointer-nolma",
"-results-rnd_0.13-fpn_0.0-sigma_1.5-offset1.4142-sensors16-inter-nolma",
"-results-rnd_0.13-fpn_0.0-sigma_1.5-offset1.4142-sensors16-nointer-nolma",
"-results-rnd_0.13-fpn_0.0-sigma_1.5-offset1.4142-sensors2-inter-nolma",
"-results-rnd_0.13-fpn_0.0-sigma_1.5-offset1.4142-sensors2-nointer-nolma",
"-results-rnd_0.13-fpn_0.0-sigma_1.5-offset1.4142-sensors4-inter-nolma",
"-results-rnd_0.13-fpn_0.0-sigma_1.5-offset1.4142-sensors4-nointer-nolma",
"-results-rnd_0.13-fpn_0.0-sigma_1.5-offset1.4142-sensors8-inter-nolma",
"-results-rnd_0.13-fpn_0.0-sigma_1.5-offset1.4142-sensors8-nointer-nolma",
"-results-rnd_0.16-fpn_0.0-sigma_1.5-offset1.4142-sensors16-inter-nolma",
"-results-rnd_0.16-fpn_0.0-sigma_1.5-offset1.4142-sensors16-nointer-nolma",
"-results-rnd_0.16-fpn_0.0-sigma_1.5-offset1.4142-sensors2-inter-nolma",
"-results-rnd_0.16-fpn_0.0-sigma_1.5-offset1.4142-sensors2-nointer-nolma",
"-results-rnd_0.16-fpn_0.0-sigma_1.5-offset1.4142-sensors4-inter-nolma",
"-results-rnd_0.16-fpn_0.0-sigma_1.5-offset1.4142-sensors4-nointer-nolma",
"-results-rnd_0.16-fpn_0.0-sigma_1.5-offset1.4142-sensors8-inter-nolma",
"-results-rnd_0.16-fpn_0.0-sigma_1.5-offset1.4142-sensors8-nointer-nolma",
"-results-rnd_0.2-fpn_0.0-sigma_1.5-offset1.4142-sensors16-inter-nolma",
"-results-rnd_0.2-fpn_0.0-sigma_1.5-offset1.4142-sensors16-nointer-nolma",
......@@ -9091,6 +9231,15 @@ if (debugLevel > -100) return true; // temporarily !
"-results-rnd_0.2-fpn_0.0-sigma_1.5-offset1.4142-sensors8-inter-nolma",
"-results-rnd_0.2-fpn_0.0-sigma_1.5-offset1.4142-sensors8-nointer-nolma",
"-results-rnd_0.25-fpn_0.0-sigma_1.5-offset1.4142-sensors16-inter-nolma",
"-results-rnd_0.25-fpn_0.0-sigma_1.5-offset1.4142-sensors16-nointer-nolma",
"-results-rnd_0.25-fpn_0.0-sigma_1.5-offset1.4142-sensors2-inter-nolma",
"-results-rnd_0.25-fpn_0.0-sigma_1.5-offset1.4142-sensors2-nointer-nolma",
"-results-rnd_0.25-fpn_0.0-sigma_1.5-offset1.4142-sensors4-inter-nolma",
"-results-rnd_0.25-fpn_0.0-sigma_1.5-offset1.4142-sensors4-nointer-nolma",
"-results-rnd_0.25-fpn_0.0-sigma_1.5-offset1.4142-sensors8-inter-nolma",
"-results-rnd_0.25-fpn_0.0-sigma_1.5-offset1.4142-sensors8-nointer-nolma",
"-results-rnd_0.3-fpn_0.0-sigma_1.5-offset1.4142-sensors16-inter-nolma",
"-results-rnd_0.3-fpn_0.0-sigma_1.5-offset1.4142-sensors16-nointer-nolma",
"-results-rnd_0.3-fpn_0.0-sigma_1.5-offset1.4142-sensors2-inter-nolma",
......@@ -9118,14 +9267,50 @@ if (debugLevel > -100) return true; // temporarily !
"-results-rnd_0.5-fpn_0.0-sigma_1.5-offset1.4142-sensors8-inter-nolma",
"-results-rnd_0.5-fpn_0.0-sigma_1.5-offset1.4142-sensors8-nointer-nolma",
"-results-rnd_0.5-fpn_0.0-sigma_1.5-offset1.4142-sensors16-inter-nolma",
"-results-rnd_0.5-fpn_0.0-sigma_1.5-offset1.4142-sensors16-nointer-nolma",
"-results-rnd_0.5-fpn_0.0-sigma_1.5-offset1.4142-sensors2-inter-nolma",
"-results-rnd_0.5-fpn_0.0-sigma_1.5-offset1.4142-sensors2-nointer-nolma",
"-results-rnd_0.5-fpn_0.0-sigma_1.5-offset1.4142-sensors4-inter-nolma",
"-results-rnd_0.5-fpn_0.0-sigma_1.5-offset1.4142-sensors4-nointer-nolma",
"-results-rnd_0.5-fpn_0.0-sigma_1.5-offset1.4142-sensors8-inter-nolma",
"-results-rnd_0.5-fpn_0.0-sigma_1.5-offset1.4142-sensors8-nointer-nolma",
"-results-rnd_0.6-fpn_0.0-sigma_1.5-offset1.4142-sensors16-inter-nolma",
"-results-rnd_0.6-fpn_0.0-sigma_1.5-offset1.4142-sensors16-nointer-nolma",
"-results-rnd_0.6-fpn_0.0-sigma_1.5-offset1.4142-sensors2-inter-nolma",
"-results-rnd_0.6-fpn_0.0-sigma_1.5-offset1.4142-sensors2-nointer-nolma",
"-results-rnd_0.6-fpn_0.0-sigma_1.5-offset1.4142-sensors4-inter-nolma",
"-results-rnd_0.6-fpn_0.0-sigma_1.5-offset1.4142-sensors4-nointer-nolma",
"-results-rnd_0.6-fpn_0.0-sigma_1.5-offset1.4142-sensors8-inter-nolma",
"-results-rnd_0.6-fpn_0.0-sigma_1.5-offset1.4142-sensors8-nointer-nolma",
"-results-rnd_0.7-fpn_0.0-sigma_1.5-offset1.4142-sensors16-inter-nolma",
"-results-rnd_0.7-fpn_0.0-sigma_1.5-offset1.4142-sensors16-nointer-nolma",
"-results-rnd_0.7-fpn_0.0-sigma_1.5-offset1.4142-sensors2-inter-nolma",
"-results-rnd_0.7-fpn_0.0-sigma_1.5-offset1.4142-sensors2-nointer-nolma",
"-results-rnd_0.7-fpn_0.0-sigma_1.5-offset1.4142-sensors4-inter-nolma",
"-results-rnd_0.7-fpn_0.0-sigma_1.5-offset1.4142-sensors4-nointer-nolma",
"-results-rnd_0.7-fpn_0.0-sigma_1.5-offset1.4142-sensors8-inter-nolma",
"-results-rnd_0.7-fpn_0.0-sigma_1.5-offset1.4142-sensors8-nointer-nolma",
"-results-rnd_0.8-fpn_0.0-sigma_1.5-offset1.4142-sensors16-inter-nolma",
"-results-rnd_0.8-fpn_0.0-sigma_1.5-offset1.4142-sensors16-nointer-nolma",
"-results-rnd_0.8-fpn_0.0-sigma_1.5-offset1.4142-sensors2-inter-nolma",
"-results-rnd_0.8-fpn_0.0-sigma_1.5-offset1.4142-sensors2-nointer-nolma",
"-results-rnd_0.8-fpn_0.0-sigma_1.5-offset1.4142-sensors4-inter-nolma",
"-results-rnd_0.8-fpn_0.0-sigma_1.5-offset1.4142-sensors4-nointer-nolma",
"-results-rnd_0.8-fpn_0.0-sigma_1.5-offset1.4142-sensors8-inter-nolma",
"-results-rnd_0.8-fpn_0.0-sigma_1.5-offset1.4142-sensors8-nointer-nolma",
"-results-rnd_0.9-fpn_0.0-sigma_1.5-offset1.4142-sensors16-inter-nolma",
"-results-rnd_0.9-fpn_0.0-sigma_1.5-offset1.4142-sensors16-nointer-nolma",
"-results-rnd_0.9-fpn_0.0-sigma_1.5-offset1.4142-sensors2-inter-nolma",
"-results-rnd_0.9-fpn_0.0-sigma_1.5-offset1.4142-sensors2-nointer-nolma",
"-results-rnd_0.9-fpn_0.0-sigma_1.5-offset1.4142-sensors4-inter-nolma",
"-results-rnd_0.9-fpn_0.0-sigma_1.5-offset1.4142-sensors4-nointer-nolma",
"-results-rnd_0.9-fpn_0.0-sigma_1.5-offset1.4142-sensors8-inter-nolma",
"-results-rnd_0.9-fpn_0.0-sigma_1.5-offset1.4142-sensors8-nointer-nolma",
"-results-rnd_1.0-fpn_0.0-sigma_1.5-offset1.4142-sensors16-inter-nolma",
"-results-rnd_1.0-fpn_0.0-sigma_1.5-offset1.4142-sensors16-nointer-nolma",
"-results-rnd_1.0-fpn_0.0-sigma_1.5-offset1.4142-sensors2-inter-nolma",
"-results-rnd_1.0-fpn_0.0-sigma_1.5-offset1.4142-sensors2-nointer-nolma",
"-results-rnd_1.0-fpn_0.0-sigma_1.5-offset1.4142-sensors4-inter-nolma",
"-results-rnd_1.0-fpn_0.0-sigma_1.5-offset1.4142-sensors4-nointer-nolma",
"-results-rnd_1.0-fpn_0.0-sigma_1.5-offset1.4142-sensors8-inter-nolma",
"-results-rnd_1.0-fpn_0.0-sigma_1.5-offset1.4142-sensors8-nointer-nolma",
/*
"-results-rnd_0.0-fpn_0.0-sigma_1.5-offset1.0-sensors16-inter",
"-results-rnd_0.0-fpn_0.0-sigma_1.5-offset1.0-sensors16-nointer",
......@@ -9442,6 +9627,8 @@ if (debugLevel > -100) return true; // temporarily !
String [] noise_files,
int debug_level)
{
int dbg_tile = 1222; // 737;
/*
"disp-last",
"str_last",
......@@ -9450,9 +9637,9 @@ if (debugLevel > -100) return true; // temporarily !
final int tilesX = ref_scene.tp.getTilesX();
// final int tilesY = ref_scene.tp.getTilesY();
double max_diff = 0.04; // 0.01; // last diff >
double max_err = 2.0; // 1.0; // 0.5; // pix
double max_err1 =0.25; // pix
double max_diff = 0.01; // 0.001; // 0.01; // 0.04; // 0.01; // last diff >
double max_err = 2.0; // 2.5; // 1.5; // 2.0; // 1.0; // 0.5; // pix
double max_err1 =0.250; // pix
double min_strength = 0.0; // minimal strength to calculate rmse (ignore weaker)
int indx_used = 3;
int indx_last = 0;
......@@ -9474,10 +9661,14 @@ if (debugLevel > -100) return true; // temporarily !
boolean use_edges = false; // true; // false; // do not filter out edges
boolean all_converge = false; // true; // false; // use only tiles that converge for all variants (intra, inter, used sensors)
boolean all_max_err = false; // true; // false; // use only tiles that have limited error for all variants (intra, inter, used sensors)
boolean same_num_sensors = false; // true; // compare performance to same number of sensors, inter, no-noise
boolean same_num_sensors = true; // false; // true; // compare performance to same number of sensors, inter, no-noise
int min_modes = 4; // 5; // 6; // 5; // 4;//at least half are meaningfull
double min_inter16_noise_level = 0.1; // 0.3; // tile should have at least this noise level for 1nter16 (mode 0)
if (use_edges) {
disp_max_rel = 10.0;
disp_max_abs = 10.0;
disp_max_rel = 100.0;
disp_max_abs = 100.0;
}
final double[][] sky_map = ref_scene.readDoubleArrayFromModelDirectory(
......@@ -9486,7 +9677,8 @@ if (debugLevel > -100) return true; // temporarily !
null); // int [] wh);
double [][] ref_dsn = ref_scene.readDoubleArrayFromModelDirectory(
"-results-nonoise", // String suffix,
// "-results-nonoise", // String suffix,
"-results-nonoise-nolma", // String suffix,
0, // int num_slices, // (0 - all)
null); // int [] wh);
......@@ -9615,11 +9807,11 @@ if (debugLevel > -100) return true; // temporarily !
good_tiles_mode[sensor_mode_file[nf]] = getGoodTiles(
max_diff, // double max_diff,
// disable edges filtering - use only common edges
100.0,// disp_near_rel, // double disp_near_rel,
100.0,//disp_max_rel, // double disp_max_rel,
disp_near_rel, // double disp_near_rel,
100.0, //disp_max_rel, // double disp_max_rel,
disp_max_inter, // double disp_max_inter
disp_far_abs, // double disp_far_abs,
disp_max_abs, // double disp_max_abs,
100.0, // disp_max_abs, // double disp_max_abs,
min_scenes_used, // double min_scenes
noise_dsn[indx_last], // double [] disp,
noise_dsn[indx_lma_last], // double [] disp_lma,
......@@ -9674,7 +9866,7 @@ if (debugLevel > -100) return true; // temporarily !
// For each file find boolean good/bad, comparing to zero noise of the same number of sensors, itnerscene
boolean [][] good_file_tile = new boolean[noise_files.length][]; // [good_tiles.length];
// double max_err1 =0.25; // pix
double max_diff_from_ref = 0.1; // max_err1; // 0.25 pix
double max_diff_from_ref = 0.2; // 0.06; // 5; // 0.1; // max_err1; // 0.25 pix
for (int nf = 0; nf < noise_files.length; nf++) {
// common or per number of sensors reference data
String fn = noise_files[nf];
......@@ -9687,6 +9879,13 @@ if (debugLevel > -100) return true; // temporarily !
// boolean [] good_ref = good_tiles_mode[sensor_mode]; // good tile without noise for this number of sensors
good_file_tile[nf] = good_tiles_mode[sensor_mode].clone();
for (int ntile = 0; ntile < good_file_tile[nf].length; ntile++) if (good_file_tile[nf][ntile]) {
if (ntile == dbg_tile) {
System.out.println("Finding good tiles: ntile = "+ntile+", nf="+nf+" ("+fn+")");
System.out.println("noise_dsn["+indx_last+"]["+ntile+"]="+noise_dsn[indx_last][ntile]+
", ref_var["+indx_last+"]["+ntile+"]="+ref_var[indx_last][ntile]);
}
boolean converged = (Math.abs(noise_dsn[indx_last_diff][ntile]) < max_diff);
if (!converged) {
good_file_tile[nf][ntile] = false;
......@@ -9700,7 +9899,6 @@ if (debugLevel > -100) return true; // temporarily !
}
}
// show number of noise values for each tile, num sensors and intra/inter, discarding tiles that are good/bad for all noise levels
int min_modes = 4;//at least half are meaningfull
{
boolean use_fpn = false;
double [][] dbg_num_noise_val = new double [good_tiles_mode.length*2][good_tiles.length];
......@@ -9709,32 +9907,38 @@ if (debugLevel > -100) return true; // temporarily !
dbg_num_noise_titles[i]= "inter"+(new int [] {16,8,4,2})[i];
dbg_num_noise_titles[i+good_tiles_mode.length]="intra"+(new int [] {16,8,4,2})[i];
}
for (int i = 0; i < dbg_num_noise_val.length; i++) {
for (int i = 00; i < dbg_num_noise_val.length; i++) {
Arrays.fill(dbg_num_noise_val[i], Double.NaN);
}
for (int ntile = 0; ntile < good_tiles.length; ntile++) if (good_tiles[ntile]) { // do not bother with obviously bad
int [] num_good = new int [dbg_num_noise_val.length];
boolean [] has_bad = new boolean [dbg_num_noise_val.length];
for (int nf = 0; nf < noise_files.length; nf++) {
int results_index = sensor_mode_file[nf] + (inter_file[nf]? 0 : 4); // inter; // ? 0 : (intra? 1 : 2);
if (good_file_tile[nf][ntile]) {
num_good[results_index]++;
} else {
has_bad[results_index] = true;
}
for (int ntile = 0; ntile < good_tiles.length; ntile++) {
if (ntile == dbg_tile) {
System.out.println("Finding good tiles: ntile = "+ntile);
}
// only keep tiles that have noise threshold for all modalities
int num_full = 0;
for (int i = 0; i < dbg_num_noise_val.length; i++) {
if (has_bad[i] && (num_good[i] > 0)) {
num_full++;
}
}
if (num_full < min_modes) {
continue;
}
for (int i = 0; i < dbg_num_noise_val.length; i++) if (has_bad[i]) {
dbg_num_noise_val[i][ntile] = num_good[i];
if (good_tiles[ntile]) { // do not bother with obviously bad
int [] num_good = new int [dbg_num_noise_val.length];
boolean [] has_bad = new boolean [dbg_num_noise_val.length];
for (int nf = 0; nf < noise_files.length; nf++) {
int results_index = sensor_mode_file[nf] + (inter_file[nf]? 0 : 4); // inter; // ? 0 : (intra? 1 : 2);
if (good_file_tile[nf][ntile]) {
num_good[results_index]++;
} else {
has_bad[results_index] = true;
}
}
// only keep tiles that have noise threshold for all modalities
int num_full = 0;
for (int i = 0; i < dbg_num_noise_val.length; i++) {
if (has_bad[i] && (num_good[i] > 0)) {
num_full++;
}
}
if (num_full < min_modes) {
continue;
}
for (int i = 0; i < dbg_num_noise_val.length; i++) if (has_bad[i]) {
dbg_num_noise_val[i][ntile] = num_good[i];
}
}
}
(new ShowDoubleFloatArrays()).showArrays(
......@@ -9746,11 +9950,12 @@ if (debugLevel > -100) return true; // temporarily !
dbg_num_noise_titles);
double [] noise_file = use_fpn ? noise_fpn_file : noise_rnd_file;
double [][] noise_levels = InterIntraLMA.getNoiseThreshold(
noise_file, // double [] noise_file, // = new double [noise_files.length];
sensor_mode_file, // int [] sensor_mode_file,
inter_file, // boolean [] inter_file,
good_file_tile, // boolean [][] good_file_tile,
min_modes); // int min_modes,
noise_file, // double [] noise_file, // = new double [noise_files.length];
sensor_mode_file, // int [] sensor_mode_file,
inter_file, // boolean [] inter_file,
good_file_tile, // boolean [][] good_file_tile,
min_inter16_noise_level, // double min_inter16_noise_level,
min_modes); // int min_modes,
double [][] dbg_noise_levels = new double [dbg_num_noise_titles.length][good_tiles.length];
for (int i = 0; i < dbg_noise_levels.length; i++) {
Arrays.fill(dbg_noise_levels[i], Double.NaN);
......@@ -9767,8 +9972,50 @@ if (debugLevel > -100) return true; // temporarily !
true,
"noise_levels",
dbg_num_noise_titles);
double noise_offset = 0.03; // 0.10; // 0.03; // 50;
InterIntraLMA interIntraLMA = new InterIntraLMA(
noise_levels, // double [][] noise_thresh,
noise_offset, // double offset, // initial value for N0
tilesX, // int tilesX, // debug images only
1); // int debug_level)
boolean adjust_N0 = true;
boolean adjust_Gi = true;
boolean adjust_St = true; // false;
boolean LMA_OK = interIntraLMA.runLma(
adjust_N0, // boolean adjust_N0,
adjust_Gi, // boolean adjust_Gi,
adjust_St, // boolean adjust_St,
0.1, // double lambda, // 0.1
0.5, // double lambda_scale_good,// 0.5
8.0, // double lambda_scale_bad, // 8.0
100, // double lambda_max, // 100
0.001, // double rms_diff, // 0.001
20, // int num_iter, // 20
2); // 0); // int debug_level)
System.out.println("LMA_OK = "+LMA_OK);
System.out.println("N0 = "+interIntraLMA.N0+" (natural noise level)");
for (int i = 0; i < interIntraLMA.gi.length; i++) {
System.out.println("g["+i+"]= "+ interIntraLMA.gi[i]);
}
double [] dbg_st = new double [good_tiles.length]; // good_tiles.length/ tilesX
Arrays.fill(dbg_st, Double.NaN);
for (int [] indices : interIntraLMA.sample_indx) {
int itile = indices[0];
int atile = interIntraLMA.tile_index[itile];
dbg_st[atile] = interIntraLMA.St[itile];
}
(new ShowDoubleFloatArrays()).showArrays(
dbg_st,
tilesX,
good_tiles.length/ tilesX,
"lma_st_out");
}
//good_tiles_mode
System.out.println("num_converged_global="+num_converged_global+", num_good_global="+num_good_global);
for (int j = 0; j < num_good_mode.length; j++) {
......
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