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imagej-elphel
Commit 2ed1f2f7 authored by Andrey Filippov's avatar Andrey Filippov
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working on adjustment

parent ecdccabe
master cuda10.0 dct eyesis4pi393 foliage gpu lwir lwir-distort lwir-distort-test2 lwir16 lwir16-dbg1 nc393 nonradial orange phg21 radial v1.1
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Showing with 419 additions and 92 deletions
src/main/java/Aberration_Calibration.java
View file @ 2ed1f2f7
......@@ -4390,8 +4390,10 @@ if (MORE_BUTTONS) {
FOCUSING_FIELD.setDebugLevel(DEBUG_LEVEL);
if (PROPERTIES!=null) FOCUSING_FIELD.getProperties("FOCUSING_FIELD.", PROPERTIES);
System.out.println("Loaded FocusingField");
if (!FOCUSING_FIELD.configureDataVector("Configure curvature",true,true)) return;
/// FOCUSING_FIELD.fieldFitting.initSampleCorrChnParIndex(FOCUSING_FIELD.flattenSampleCoord()); //+
if (!FOCUSING_FIELD.configureDataVector("Configure curvature - TODO: fix many settings restored from properties",true,true)) return;
System.out.println("TODO: fix many settings restored from properties, overwriting entered fields. Currently run \"Modify LMA\" to re-enter values");
System.out.println("TODO: Probably need to make a separate dialog that enters number of parameters.");
/// FOCUSING_FIELD.fieldFitting.initSampleCorrChnParIndex(FOCUSING_FIELD.flattenSampleCoord()); //+
/// FOCUSING_FIELD.setDataVector(
/// true, // calibrate mode
/// FOCUSING_FIELD.createDataVector());
......
src/main/java/FocusingField.java
View file @ 2ed1f2f7
......@@ -81,6 +81,7 @@ public class FocusingField {
double filterInputConcaveScale;
boolean filterZ; // (adjustment mode)filter samples by Z
int minLeftSamples; // minimal number of samples (channel/dir/location) for adjustment
double targetRelFocalShift; // target focal shift relative to best composite "sharpness"
// when false - tangential is master
double [] minMeas; // pixels
......@@ -216,7 +217,7 @@ public class FocusingField {
filterInputConcaveScale=0.9;
filterZ=true; // (adjustment mode)filter samples by Z
minLeftSamples=10; // minimal number of samples (channel/dir/location) for adjustment
targetRelFocalShift=8.0; // target focal shift relative to best composite "sharpness"
// when false - tangential is master
double [] minMeasDflt= {0.5,0.5,0.5,0.5,0.5,0.5}; // pixels
minMeas= minMeasDflt; // pixels
......@@ -325,6 +326,7 @@ public class FocusingField {
properties.setProperty(prefix+"filterInputConcaveScale",filterInputConcaveScale+"");
properties.setProperty(prefix+"filterZ",filterZ+"");
properties.setProperty(prefix+"minLeftSamples",minLeftSamples+"");
properties.setProperty(prefix+"targetRelFocalShift",targetRelFocalShift+"");
for (int chn=0; chn<minMeas.length; chn++) properties.setProperty(prefix+"minMeas_"+chn,minMeas[chn]+"");
for (int chn=0; chn<maxMeas.length; chn++) properties.setProperty(prefix+"maxMeas_"+chn,maxMeas[chn]+"");
for (int chn=0; chn<thresholdMax.length; chn++) properties.setProperty(prefix+"thresholdMax_"+chn,thresholdMax[chn]+"");
......@@ -418,7 +420,9 @@ public class FocusingField {
filterZ=Boolean.parseBoolean(properties.getProperty(prefix+"filterZ"));
if (properties.getProperty(prefix+"minLeftSamples")!=null)
minLeftSamples=Integer.parseInt(properties.getProperty(prefix+"minLeftSamples"));
if (properties.getProperty(prefix+"targetRelFocalShift")!=null)
targetRelFocalShift=Double.parseDouble(properties.getProperty(prefix+"targetRelFocalShift"));
for (int chn=0; chn<minMeas.length; chn++) if (properties.getProperty(prefix+"minMeas_"+chn)!=null)
minMeas[chn]=Double.parseDouble(properties.getProperty(prefix+"minMeas_"+chn));
for (int chn=0; chn<maxMeas.length; chn++) if (properties.getProperty(prefix+"maxMeas_"+chn)!=null)
......@@ -687,8 +691,8 @@ public boolean configureDataVector(String title, boolean forcenew, boolean enabl
numCurvPars[0],
numCurvPars[1]);
if (savedProperties!=null){
if (debugLevel>1) System.out.println("configureDataVector(): Applying properties");
getProperties(propertiesPrefix,savedProperties);
if (debugLevel>0) System.out.println("configureDataVector(): Applying properties");
getProperties(propertiesPrefix,savedProperties); // overwrites parallelOnly!
}
}
fieldFitting.setCenterXY(currentPX0,currentPY0);
......@@ -797,6 +801,7 @@ private int getNumEnabledSamples(
}
private boolean [] filterConcave(
boolean [] scanMask, // do not filter if false
double sigma,
boolean removeInsufficient,
int minSeries,
......@@ -806,11 +811,19 @@ private boolean [] filterConcave(
enable_in=new boolean [dataVector.length];
for (int i=0;i<enable_in.length;i++)enable_in[i]=true;
}
// int minPoints=minSeries;
if (scanMask==null) {
scanMask=new boolean [dataVector.length];
for (int i=0;i<scanMask.length;i++) scanMask[i]=true;
}
boolean [] enable_masked=enable_in.clone();
for (int i=0;i<enable_masked.length;i++) if ((i<scanMask.length) && !scanMask[i]) enable_masked[i]=false;
boolean [] enable_out=enable_masked.clone();
int debugThreshold=1;
double maxGap=sigma; // this point has this gap towards minimal
double kexp=-0.5/(sigma*sigma);
boolean [] enable_out=enable_in.clone();
// boolean [] enable_out=enable_in.clone();
double keepNearMin=sigma; // when removing non-concave points around min, skip very close ones
double [][] flatSampleCoordinates=fieldFitting.getSampleCoordinates();
......@@ -823,7 +836,7 @@ private boolean [] filterConcave(
z0EstData[chn][sample][0]=0.0;
z0EstData[chn][sample][1]=0.0;
}
for (int index=0;index<dataVector.length;index++) if ((index>=enable_in.length) ||enable_in[index]){
for (int index=0;index<dataVector.length;index++) if ((index>=enable_masked.length) ||enable_masked[index]){
numPoints[dataVector[index].channel][dataVector[index].sampleIndex]++;
}
int [][][] indices=new int[numPoints.length][numPoints[0].length][];
......@@ -831,7 +844,7 @@ private boolean [] filterConcave(
indices[chn][sample]=new int [numPoints[chn][sample]]; // may be 0 length
numPoints[chn][sample]=0; // will be used as a counter
}
for (int index=0;index<dataVector.length;index++) if ((index>=enable_in.length) ||enable_in[index]){
for (int index=0;index<dataVector.length;index++) if ((index>=enable_masked.length) ||enable_masked[index]){
int chn=dataVector[index].channel;
int sample=dataVector[index].sampleIndex;
// numPoints[dataVector[index].channel][dataVector[index].sampleIndex]++;
......@@ -1006,23 +1019,36 @@ private boolean [] filterConcave(
}
z0_estimates[chn]= (w>0.0)?z/w:Double.NaN;
}
// restore masked out data
for (int i=0;i<enable_out.length;i++) if (
(i<scanMask.length) &&
!scanMask[i] &&
enable_in[i]) enable_out[i]=true;
return enable_out;
}
private boolean [] filterTooFar(double ratio,boolean [] enable_in){
private boolean [] filterTooFar(
boolean [] scanMask, // do not filter if false
double ratio,
boolean [] enable_in){
if (enable_in==null) {
enable_in=new boolean [dataVector.length];
for (int i=0;i<enable_in.length;i++)enable_in[i]=true;
}
boolean [] enable_out=enable_in.clone();
if (scanMask==null) {
scanMask=new boolean [dataVector.length];
for (int i=0;i<scanMask.length;i++) scanMask[i]=true;
}
boolean [] enable_masked=enable_in.clone();
for (int i=0;i<enable_masked.length;i++) if ((i<scanMask.length) && !scanMask[i]) enable_masked[i]=false;
boolean [] enable_out=enable_masked.clone();
int numFiltered = 0;
double [][][] data=new double [getNumChannels()][getNumSamples()][3];
double [] z_sample=new double [dataVector.length];
for (int chn=0;chn<data.length;chn++)
for (int sample=0;sample<data[chn].length;sample++)
for (int i=0;i<data[chn][sample].length;i++)data[chn][sample][i]=0;
for (int index=0;index<dataVector.length;index++) if ((index>=enable_in.length) ||enable_in[index]){
for (int index=0;index<dataVector.length;index++) if (((index>=enable_masked.length) ||enable_masked[index])){
int chn=dataVector[index].channel;
int sample=dataVector[index].sampleIndex;
double z= fieldFitting.getMotorsZ(
......@@ -1046,7 +1072,7 @@ private boolean [] filterTooFar(double ratio,boolean [] enable_in){
sample+", r_av="+IJ.d2s(Math.sqrt(z2),3)+" z_av="+IJ.d2s(z_av,3));
}
}
for (int index=0;index<dataVector.length;index++) if ((index>=enable_in.length) ||enable_in[index]){
for (int index=0;index<dataVector.length;index++) if ((index>=enable_masked.length) || enable_masked[index]){
int chn=dataVector[index].channel;
int sample=dataVector[index].sampleIndex;
if (data[chn][sample][0]>0.0) {
......@@ -1059,11 +1085,17 @@ private boolean [] filterTooFar(double ratio,boolean [] enable_in){
}
if (debugLevel>0) System.out.println("filterTooFar(): removed "+numFiltered+" samples");
// restore masked out data
for (int i=0;i<enable_out.length;i++) if (
(i<scanMask.length) &&
!scanMask[i] &&
enable_in[i]) enable_out[i]=true;
return enable_out;
}
private boolean [] filterCrazyInput(
boolean [] scanMask, // do not filter if false
boolean [] enable_in, // [meas][cjn][sample] (or null) // can be shorter or longer than dataVector
double maxMotDiff,
double diff,
......@@ -1073,6 +1105,10 @@ private boolean [] filterCrazyInput(
enable_in=new boolean [dataVector.length];
for (int i=0;i<enable_in.length;i++)enable_in[i]=true;
}
if (scanMask==null) {
scanMask=new boolean [dataVector.length];
for (int i=0;i<scanMask.length;i++)scanMask[i]=true;
}
boolean [] enable_out=enable_in.clone();
// int lastIndex=-1;
int numFiltered=0;
......@@ -1087,7 +1123,7 @@ private boolean [] filterCrazyInput(
int lastIndexAny=-1;
boolean smallMove=false;
// for (int index=0;index<dataVector.length;index++) if ((index>=enable_in.length) ||enable_in[index]){
for (int index=0;index<dataVector.length;index++) { // crazy neighbor still kills even if is ignored itself - needed
for (int index=0;index<dataVector.length;index++) if (scanMask[index]){ // crazy neighbor still kills even if is ignored itself - needed
int chn=dataVector[index].channel;
int sample=dataVector[index].sampleIndex;
if (lastTimestamp==null) lastTimestamp=dataVector[index].timestamp;
......@@ -1155,82 +1191,140 @@ private int [] getParallelDiff(MeasuredSample [] vector){
int [] result= {parallelDiff.x,parallelDiff.y};
return result;
}
private boolean [] createScanMask(MeasuredSample [] vector){
int [] diffs=getParallelDiff(vector);
int longestStart=0;
int longestRun=0;
int thisStart=0;
int thisRun=0;
// boolean [] chanSel=fieldFitting.getSelectedChannels();
// int numSamples=0;
for (int i=0;i<vector.length+1;i++) { // if (chanSel[vector[i].channel]) {
boolean diffMatch= (i>=vector.length)? false:
(
((vector[i].motors[1]-vector[i].motors[0]) == diffs[0]) &&
((vector[i].motors[2]-vector[i].motors[0]) == diffs[1]));
if (diffMatch){
if (thisRun>0){
thisRun++;
} else {
thisStart=i;
thisRun=1;
}
} else {
if (thisRun>0){
if (thisRun>longestRun){
longestRun=thisRun;
longestStart=thisStart;
}
thisRun=0;
}
}
// numSamples++;
}
// numSamples--;
boolean []scanMask=new boolean[vector.length]; // numSamples];
int index=0;
for (int i=0;i<vector.length;i++) { //if (chanSel[vector[i].channel]) {
scanMask[index]=(index>=longestStart) && ((index<(longestStart+longestRun)));
index++;
}
return scanMask;
}
// includes deselected channels
public void setDataVector(
boolean calibrateMode,
MeasuredSample [] vector){ // remove unused channels if any. vector is already corrected from input data, FWHM psf
if (debugLevel>1) System.out.println("+++++ (Re)calculating sample weights +++++");
int [] diffs=null;
if (calibrateMode && parallelOnly) diffs=getParallelDiff(vector);
boolean [] chanSel=fieldFitting.getSelectedChannels();
int numSamples=0;
for (int i=0;i<vector.length;i++) if (chanSel[vector[i].channel]){
if ((diffs!=null) && (
((vector[i].motors[1]-vector[i].motors[0]) != diffs[0]) ||
((vector[i].motors[2]-vector[i].motors[0]) != diffs[1]))) continue;
numSamples++;
}
dataVector=new MeasuredSample [numSamples];
int n=0;
for (int i=0;i<vector.length;i++) if (chanSel[vector[i].channel]) {
if ((diffs!=null) && (
((vector[i].motors[1]-vector[i].motors[0]) != diffs[0]) ||
((vector[i].motors[2]-vector[i].motors[0]) != diffs[1]))) continue;
dataVector[n++]=vector[i];
}
int corrLength=fieldFitting.getNumberOfCorrParameters();
dataValues = new double [dataVector.length+corrLength];
dataWeights = new double [dataVector.length+corrLength];
double kw= (weightRadius>0.0)?(-0.5*getPixelMM()*getPixelMM()/(weightRadius*weightRadius)):0;
for (int i=0;i<dataVector.length;i++){
MeasuredSample ms=dataVector[i];
dataValues[i]=ms.value;
dataWeights[i]=1.0/Math.pow(ms.value,weightMode);
if (weightRadius>0.0){
double r2=(ms.px-currentPX0)*(ms.px-currentPX0)+(ms.py-currentPY0)*(ms.py-currentPY0);
dataWeights[i]*=Math.exp(kw*r2);
}
}
for (int i=0;i<corrLength;i++){
dataValues[i+dataVector.length]=0.0; // correction target is always 0
dataWeights[i+dataVector.length]=1.0; // improve?
}
if (calibrateMode && filterInput){
boolean [] en=dataWeightsToBoolean();
en= filterCrazyInput(
en, // [meas][cjn][sample] (or null) // can be shorter or longer than dataVector
filterInputMotorDiff,
filterInputDiff,
filterInputFirstLast
);
maskDataWeights(en);
}
if (calibrateMode && filterInputTooFar){
boolean [] en=dataWeightsToBoolean();
en= filterTooFar(
filterInputFarRatio,
en);
maskDataWeights(en);
}
if (debugLevel>1) System.out.println("+++++ (Re)calculating sample weights +++++");
// int [] diffs=null;
// if (calibrateMode && parallelOnly) diffs=getParallelDiff(vector);
boolean [] chanSel=fieldFitting.getSelectedChannels();
boolean [] fullScanMask=createScanMask(vector);
int numSamples=0;
// int index=0;
for (int i=0;i<vector.length;i++) if (chanSel[vector[i].channel]){
if (calibrateMode && parallelOnly && !fullScanMask[i]) continue; // skip non-scan
// if ((diffs!=null) && (
// ((vector[i].motors[1]-vector[i].motors[0]) != diffs[0]) ||
// ((vector[i].motors[2]-vector[i].motors[0]) != diffs[1]))) continue;
numSamples++;
}
dataVector=new MeasuredSample [numSamples];
boolean [] scanMask=new boolean[numSamples];
int n=0;
for (int i=0;i<vector.length;i++) if (chanSel[vector[i].channel]) {
if (calibrateMode && parallelOnly && !fullScanMask[i]) continue;
// if ((diffs!=null) && (
// ((vector[i].motors[1]-vector[i].motors[0]) != diffs[0]) ||
// ((vector[i].motors[2]-vector[i].motors[0]) != diffs[1]))) continue;
scanMask[n]=fullScanMask[i];
dataVector[n++]=vector[i];
}
// if (calibrateMode) {
// if (parallelOnly){
// scanMask=new boolean [numSamples];
// for (int i=0;i<scanMask.length;i++) scanMask[i]=true;
// }
// } else {
// scanMask=new boolean [numSamples];
// for (int i=0;i<scanMask.length;i++) scanMask[i]=false;
// }
int corrLength=fieldFitting.getNumberOfCorrParameters();
dataValues = new double [dataVector.length+corrLength];
dataWeights = new double [dataVector.length+corrLength];
double kw= (weightRadius>0.0)?(-0.5*getPixelMM()*getPixelMM()/(weightRadius*weightRadius)):0;
for (int i=0;i<dataVector.length;i++){
MeasuredSample ms=dataVector[i];
dataValues[i]=ms.value;
dataWeights[i]=1.0/Math.pow(ms.value,weightMode);
if (weightRadius>0.0){
double r2=(ms.px-currentPX0)*(ms.px-currentPX0)+(ms.py-currentPY0)*(ms.py-currentPY0);
dataWeights[i]*=Math.exp(kw*r2);
}
}
for (int i=0;i<corrLength;i++){
dataValues[i+dataVector.length]=0.0; // correction target is always 0
dataWeights[i+dataVector.length]=1.0; // improve?
}
if (calibrateMode && filterInput){
boolean [] en=dataWeightsToBoolean();
en= filterCrazyInput(
scanMask,
en, // [meas][cjn][sample] (or null) // can be shorter or longer than dataVector
filterInputMotorDiff,
filterInputDiff,
filterInputFirstLast
);
maskDataWeights(en);
}
if (calibrateMode && filterInputTooFar){
boolean [] en=dataWeightsToBoolean();
en= filterTooFar(
scanMask,
filterInputFarRatio,
en);
maskDataWeights(en);
}
if (calibrateMode && filterInputConcave){
boolean [] en=dataWeightsToBoolean();
en= filterConcave(
filterInputConcaveSigma,
filterInputConcaveRemoveFew,
filterInputConcaveMinSeries,
filterInputConcaveScale,
en);
maskDataWeights(en);
}
fieldFitting.initSampleCorrVector(
flattenSampleCoord(), //double [][] sampleCoordinates,
getSeriesWeights()); //double [][] sampleSeriesWeights);
if (calibrateMode && filterInputConcave){
boolean [] en=dataWeightsToBoolean();
en= filterConcave(
scanMask,
filterInputConcaveSigma,
filterInputConcaveRemoveFew,
filterInputConcaveMinSeries,
filterInputConcaveScale,
en);
maskDataWeights(en);
}
// TODO: add filtering for tilt motor calibration
fieldFitting.initSampleCorrVector(
flattenSampleCoord(), //double [][] sampleCoordinates,
getSeriesWeights()); //double [][] sampleSeriesWeights);
}
// for compatibility with Distortions class\
......@@ -3608,6 +3702,29 @@ public boolean LevenbergMarquardt(
double zMin=-40.0;
double zMax= 40.0;
double zStep=2.0;
double targetTiltX=0.0; // for testing, normally should be 0 um/mm
double targetTiltY=0.0; // for testing, normally should be 0 um/mm
double [] center_z=fieldFitting.getZCenters(false);
double [] centerFWHM={
fieldFitting.getCalcValuesForZ(center_z[0],0.0,null)[1],
fieldFitting.getCalcValuesForZ(center_z[1],0.0,null)[3],
fieldFitting.getCalcValuesForZ(center_z[2],0.0,null)[5]
};
double [] best_qb_corr= fieldFitting.getBestQualB(
k_red,
k_blue,
true);
// double targetRelZShift=8.0; // focus by this closer to lens to compensate for closer tested than used
gd.addMessage("Best composite distance for FWHM^4 "+ IJ.d2s(best_qb_corr[0],3)+" um"+
", FWHM="+IJ.d2s(best_qb_corr[1],3)+"um, MTF50="+IJ.d2s(fwhm_to_mtf50/best_qb_corr[1],2)+" lp/mm");
gd.addMessage("Best center focus for Red (relative to best composite) = "+ IJ.d2s(center_z[0]-best_qb_corr[0],3)+" um"+
", FWHM="+IJ.d2s(centerFWHM[0],3)+"um, MTF50="+IJ.d2s(fwhm_to_mtf50/centerFWHM[0],2)+" lp/mm");
gd.addMessage("Best center focus for Green (relative to best composite) = "+ IJ.d2s(center_z[1]-best_qb_corr[0],3)+" um"+
", FWHM="+IJ.d2s(centerFWHM[1],3)+"um, MTF50="+IJ.d2s(fwhm_to_mtf50/centerFWHM[1],2)+" lp/mm");
gd.addMessage("Best center focus for Blue (relative to best composite) = "+ IJ.d2s(center_z[2]-best_qb_corr[0],3)+" um"+
", FWHM="+IJ.d2s(centerFWHM[2],3)+"um, MTF50="+IJ.d2s(fwhm_to_mtf50/centerFWHM[2],2)+" lp/mm");
filterZ=true; // (adjustment mode)filter samples by Z
minLeftSamples=10; // minimal number of samples (channel/dir/location) for adjustment
......@@ -3620,7 +3737,11 @@ public boolean LevenbergMarquardt(
gd.addNumericField("Z min",zMin,2,5,"um");
gd.addNumericField("Z max",zMax,2,5,"um");
gd.addNumericField("Z step",zStep,2,5,"um");
gd.addNumericField("Target focus (relative to best composirte)",targetRelFocalShift,2,5,"um");
gd.addNumericField("Target horizontal tilt (normally 0)",targetTiltX,2,5,"um/mm");
gd.addNumericField("Target vertical tilt (normally 0)",targetTiltY,2,5,"um/mm");
gd.showDialog();
if (gd.wasCanceled()) return;
nMeas=(int) gd.getNextNumber();
......@@ -3631,15 +3752,25 @@ public boolean LevenbergMarquardt(
zMin= gd.getNextNumber();
zMax= gd.getNextNumber();
zStep=gd.getNextNumber();
targetRelFocalShift=gd.getNextNumber();
targetTiltX=gd.getNextNumber(); // for testing, normally should be 0 um/mm
targetTiltY=gd.getNextNumber(); // for testing, normally should be 0 um/mm
boolean OK;
/*
double targetRelFocalShift,
double targetTiltX, // for testing, normally should be 0 um/mm
double targetTiltY // for testing, normally should be 0 um/mm
*/
if (nMeas>=0){
OK=testMeasurement(
measurements.get(nMeas),
// nMeas,
zMin,
zMax,
zStep);
zStep
);
if (!OK){
if (debugLevel>0) System.out.println("testMeasurement("+nMeas+") failed");
} else {
......@@ -3652,8 +3783,12 @@ public boolean LevenbergMarquardt(
fieldFitting.mechanicalFocusingModel.getUnits(i));
}
}
double [] dm= getAdjustedMotors(
targetRelFocalShift+best_qb_corr[0],
targetTiltX, // for testing, normally should be 0 um/mm
targetTiltY);
System.out.println("Suggested motor positions: "+IJ.d2s(dm[0],0)+":"+IJ.d2s(dm[1],0)+":"+IJ.d2s(dm[2],0));
}
} else {
for (nMeas=0;nMeas<measurements.size();nMeas++){
if (debugLevel>0) System.out.print("======== testMeasurement("+nMeas+") ======== ");
......@@ -3675,16 +3810,43 @@ public boolean LevenbergMarquardt(
fieldFitting.mechanicalFocusingModel.getUnits(i));
}
}
double [] dm= getAdjustedMotors(
targetRelFocalShift+best_qb_corr[0],
targetTiltX, // for testing, normally should be 0 um/mm
targetTiltY);
System.out.println("Suggested motor positions: "+IJ.d2s(dm[0],0)+":"+IJ.d2s(dm[1],0)+":"+IJ.d2s(dm[2],0));
}
}
}
}
public double [] getAdjustedMotors(
double targetRelFocalShift,
double targetTiltX, // for testing, normally should be 0 um/mm
double targetTiltY){ // for testing, normally should be 0 um/mm
double [] zM=fieldFitting.mechanicalFocusingModel.getZM(
currentPX0, //fieldFitting.getCenterXY()[0],
currentPY0, //fieldFitting.getCenterXY()[1],
targetRelFocalShift,
targetTiltX,
targetTiltY);
if (zM==null) return null; // not yet used
if (debugLevel>0) System.out.println("Suggested motor linearized positions: "+IJ.d2s(zM[0],2)+":"+IJ.d2s(zM[1],2)+":"+IJ.d2s(zM[2],2));
double [] dm=new double[zM.length];
for (int index=0;index<dm.length;index++){
dm[index]=fieldFitting.mechanicalFocusingModel.zmToM(
zM[index],
index);
}
return dm;
}
public boolean testMeasurement(
FocusingFieldMeasurement measurement, // null in calibrate mode
// int nMeas,
double zMin,
double zMax,
double zStep){
double zStep
){
int retryLimit=20;
setDataVector(
false,
......@@ -4278,7 +4440,7 @@ public boolean LevenbergMarquardt(
numBad[i]++;
hasBad=true;
}
if ((debugLevel>0) && hasBad){
if ((debugLevel>1) && hasBad){ // was 0
for (int i=0;i<numBad.length;i++) if (numBad[i]>0){
System.out.println(numBad[i]+" sample locations are missing data for "+fieldFitting.getDescription(i));
}
......@@ -5313,7 +5475,7 @@ public boolean LevenbergMarquardt(
{"Ly", "Half vertical distance between M1 and M2 supports", "mm","10.0"},
{"mpX0","pixel X coordinate of mechanical center","px","1296.0"},
{"mpY0","pixel Y coordinate of mechanical center","px","968.0"},
{"z0", "center shift, positive away form the lens","um","0.0"},
{"z0", "center shift, positive away from the lens","um","0.0"},
{"tx", "horizontal tilt", "um/mm","0.0"},
{"ty", "vertical tilt", "um/mm","0.0"}};
public double PERIOD=3584.0; // steps/revolution
......@@ -5442,6 +5604,7 @@ public boolean LevenbergMarquardt(
double px,
double py,
double[] deriv){
// double[][] adjData){
double debugMot=6545;
int debugThreshold=2;
boolean dbg = (debugLevel>debugThreshold);
......@@ -5593,6 +5756,168 @@ public boolean LevenbergMarquardt(
}
return z;
}
/**
* Calculate linearized mount (motor) displacement from motor position in steps
* @param m motor position in steps
* @param index motor number (0..2)
* @return mount displacement (in microns)
*/
public double mToZm(
double m,
int index) {
double p2pi= PERIOD/2/Math.PI;
double kM=Double.NaN,aM=Double.NaN;
switch (index){
case 0:
kM= getValue(MECH_PAR.K0)+getValue(MECH_PAR.KD1)-getValue(MECH_PAR.KD3);
aM=(m + getValue(MECH_PAR.sM1)*p2pi*Math.sin(m/p2pi) + getValue(MECH_PAR.cM1)*p2pi*Math.cos(m/p2pi));
break;
case 1:
kM= getValue(MECH_PAR.K0)-getValue(MECH_PAR.KD1)-getValue(MECH_PAR.KD3);
aM=(m + getValue(MECH_PAR.sM2)*p2pi*Math.sin(m/p2pi) + getValue(MECH_PAR.cM2)*p2pi*Math.cos(m/p2pi));
break;
case 2:
kM= getValue(MECH_PAR.K0)+getValue(MECH_PAR.KD3);
aM=(m + getValue(MECH_PAR.sM3)*p2pi*Math.sin(m/p2pi) + getValue(MECH_PAR.cM3)*p2pi*Math.cos(m/p2pi));
break;
}
return kM*aM;
}
private double getDzmDm(
double m,
double kM,
double s,
double c) {
double p2pi= PERIOD/2/Math.PI;
return kM*(1.0+ s*Math.cos(m/p2pi)-c*Math.sin(m/p2pi));
}
/**
* Convert linearized motor position to motor steps using current mechanical parameter values
* @param zm linear motor position
* @param index motor index (0..2)
* @return motor position in steps
*/
public double zmToM(
double zm,
int index) {
double p2pi= PERIOD/2/Math.PI;
double kM=Double.NaN, m=0,s=0.0,c=1.0;
switch (index){
case 0:
kM= getValue(MECH_PAR.K0)+getValue(MECH_PAR.KD1)-getValue(MECH_PAR.KD3);
s=getValue(MECH_PAR.sM1);
c=getValue(MECH_PAR.cM1);
break;
case 1:
kM= getValue(MECH_PAR.K0)-getValue(MECH_PAR.KD1)-getValue(MECH_PAR.KD3);
s=getValue(MECH_PAR.sM2);
c=getValue(MECH_PAR.cM2);
break;
case 2:
kM= getValue(MECH_PAR.K0)+getValue(MECH_PAR.KD3);
s=getValue(MECH_PAR.sM3);
c=getValue(MECH_PAR.cM3);
break;
}
m=zm/kM; // without thread sin/cos
double eps=0.1;
int maxRetries=100;
// aM=(m + getValue(MECH_PAR.sM3)*p2pi*Math.sin(m/p2pi) + getValue(MECH_PAR.cM3)*p2pi*Math.cos(m/p2pi));
// double dzM1_dm1=kM1*(1.0+getValue(MECH_PAR.sM1)*Math.cos(m1/p2pi)-getValue(MECH_PAR.cM1)*Math.sin(m1/p2pi));
double a=Math.sqrt(s*s+c*c);
double phase=0.0;
double extrenPhase=0.0;
if (a>1.0){
phase=Math.atan2(s,c);
// double rd=1.0+ s*Math.cos(m/p2pi)-c*Math.sin(m/p2pi);
// double rd=1.0+ a*Math.cos((m+p2pi*phase)/p2pi);
// rd==0 => Math.cos((m+p2pi*phase)/p2pi)=-1.0/a
extrenPhase=phase-Math.asin(1.0/a);
// minPhase-=(2*Math.PI)*Math.floor(minPhase/(2*Math.PI));
extrenPhase-=Math.PI*Math.floor(extrenPhase/Math.PI); // min/max 0<=hase<PI of the min/max zm(m)
}
for (int retry=0;retry<maxRetries;retry++){
double zm1=mToZm(m, index);
if (Math.abs(zm1-zm)<eps) break;
double dzm_dm=getDzmDm(m,kM,s,c);
if (dzm_dm<=0.0){
if (debugLevel>0) System.out.println("Negative derivative dzm_dm");
double mPhase=m/p2pi;
double halfPeriods=Math.floor(mPhase/Math.PI);
double fractPhase=mPhase-Math.PI*halfPeriods;
double mirrExtrenFractPhase=extrenPhase;
if (mirrExtrenFractPhase<fractPhase) mirrExtrenFractPhase+=Math.PI;
if (zm1>zm) mirrExtrenFractPhase-=Math.PI;
double mirrPhase=Math.PI*halfPeriods+mirrExtrenFractPhase;
double mirrM=p2pi*mirrPhase;
m=2*mirrM-m; // symmetrical aqround extrenum, up if needed more, down - if needed less
}
double l=1.0;
double m2=m;
for (int retry2=0;retry2<maxRetries;retry2++){
m2 = m+l*((zm-zm1)/dzm_dm);
double zm2= mToZm(m2, index);
if (Math.abs(zm2-zm)<Math.abs(zm1-zm)) break;
l*=0.5;
}
m=m2;
}
return m;
}
/**
* Calculate three linearized values of motor positions for current parameters, target center focal shift and tilt
* @param px lens center X (pixels)
* @param py lens center Y (pixels)
* @param targetZ target focal shift uin the center, microns, positive - away
* @param targetTx target horizontal tilt (normally 0)
* @param targetTy target vertical tilt (normallty 0)
* @return array of 3 linearized motor positions (microns)
*/
public double [] getZM(
double px,
double py,
double targetZ,
double targetTx,
double targetTy){
double dx=PIXEL_SIZE*(px-getValue(MECH_PAR.mpX0));
double dy=PIXEL_SIZE*(py-getValue(MECH_PAR.mpY0));
// double zc= 0.25* zM1+ 0.25* zM2+ 0.5 * zM3+getValue(MECH_PAR.z0);
// double zx=dx*(getValue(MECH_PAR.tx)+(2*zM3-zM1-zM2)/(4*getValue(MECH_PAR.Lx))) ;
// double zy=dy*(getValue(MECH_PAR.ty)+(zM2-zM1)/(2*getValue(MECH_PAR.Ly)));
// double z=zc+zx+zy
// A*{zM1,zM2,zM3}={targetZ,targetTx,targetTy}
// A*{zM1,zM2,zM3}={targetZ-getValue(MECH_PAR.z0),targetTx-dx*getValue(MECH_PAR.tx),targetTy-dy*getValue(MECH_PAR.ty)}
double [][] A={
{
0.25 - dx/(4*getValue(MECH_PAR.Lx)) -dy/(2*getValue(MECH_PAR.Ly)),
0.25 - dx/(4*getValue(MECH_PAR.Lx)) +dy/(2*getValue(MECH_PAR.Ly)),
0.5 + dx/(2*getValue(MECH_PAR.Lx))
} , {
-1.0/(4*getValue(MECH_PAR.Lx)),
-1.0/(4*getValue(MECH_PAR.Lx)),
1.0/ (2*getValue(MECH_PAR.Lx))
} , {
-1.0/(2*getValue(MECH_PAR.Ly)),
1.0/ (2*getValue(MECH_PAR.Ly)),
0.0
}
};
double [][] B={
{targetZ-getValue(MECH_PAR.z0)},
{targetTx-dx*getValue(MECH_PAR.tx)},
{targetTy-dy*getValue(MECH_PAR.ty)}
};
Matrix MA=new Matrix(A);
Matrix MB=new Matrix(B);
Matrix S=MA.solve(MB);
return S.getColumnPackedCopy();
}
public boolean[] getDefaultMask(){
boolean [] mask = new boolean[this.paramValues.length];
for (int i=0;i<mask.length;i++) mask[i]=false;
......
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