solve merge conflict

data/cdflist.txt

@@ -1,40 +0,0 @@
-{"cdfgroups" : [{
-        "group" : "CCMC-3D-CDF",
-        "fieldlinefile" : "${OPENSPACE_DATA}/scene/iswa/cdf/fieldlines.json",
-        "cdfs" : [
-                {
-                    "name" : "CCMC-00:00:00",
-                    "path" : "../../GM_CDF/3d__var_1_e20000101-000000-000.out.cdf"
-                    "time" : "2000-01-01T00:00:00.00"
-                },
-                {
-                    "name" : "CCMC-00:30:00",
-                    "path" : "../../GM_CDF/3d__var_1_e20000101-003000-000.out.cdf"
-                    "time" : "2000-01-01T00:00:00.00"
-                },
-                {
-                    "name" : "CCMC-01:00:00",
-                    "path" : "../../GM_CDF/3d__var_1_e20000101-010000-000.out.cdf"
-                    "time" : "2000-01-01T10:00:00.00"
-                },
-                {
-                    "name" : "CCMC-01:30:00",
-                    "path" : "../../GM_CDF/3d__var_1_e20000101-013000-000.out.cdf"
-                    "time" : "2000-01-01T01:30:00.00"
-                },
-                {
-                    "name" : "CCMC-02:00:00",
-                    "path" : "../../GM_CDF/3d__var_1_e20000101-020000-000.out.cdf"
-                    "time" : "2000-01-01T02:00:00.00"
-                },
-            ]
-        }
-    ]
-}
-CCMC-3D-CDF
-${OPENSPACE_DATA}/scene/iswa/cdf/fieldlines.json
-CCMC-00:00:00 ../../GM_CDF/3d__var_1_e20000101-000000-000.out.cdf 2000-01-01T00:00:00.00
-CCMC-00:30:00 ../../GM_CDF/3d__var_1_e20000101-003000-000.out.cdf 2000-01-01T00:30:00.00
-CCMC-01:00:00 ../../GM_CDF/3d__var_1_e20000101-010000-000.out.cdf 2000-01-01T01:00:00.00
-CCMC-01:30:00 ../../GM_CDF/3d__var_1_e20000101-013000-000.out.cdf 2000-01-01T01:30:00.00
-CCMC-02:00:00 ../../GM_CDF/3d__var_1_e20000101-020000-000.out.cdf 2000-01-01T02:00:00.00

include/openspace/util/histogram.h

@@ -67,7 +67,7 @@ public:
 
     void normalize();
     void print() const;
-    void generateEqualizer();
+    void generateEqualizer(bool withoutHighestBin = false);
     Histogram equalize();
     float equalize (float);
 

modules/iswa/rendering/datacygnet.cpp

@@ -41,18 +41,18 @@ DataCygnet::DataCygnet(const ghoul::Dictionary& dictionary)
     :IswaCygnet(dictionary)
     ,_dataProcessor(nullptr)
     ,_dataOptions("dataOptions", "Data Options")
-    ,_useLog("useLog","Use Logarithm", false)
+    // ,_useLog("useLog","Use Logarithm", false)
     ,_useHistogram("useHistogram", "Auto Contrast", false)
     ,_autoFilter("autoFilter", "Auto Filter", true)
     ,_normValues("normValues", "Normalize Values", glm::vec2(1.0,1.0), glm::vec2(0), glm::vec2(5.0))
     ,_backgroundValues("backgroundValues", "Background Values", glm::vec2(0.0), glm::vec2(0), glm::vec2(1.0))
     ,_transferFunctionsFile("transferfunctions", "Transfer Functions", "${SCENE}/iswa/tfs/default.tf")
     //FOR TESTING
-    ,_numOfBenchmarks(0)
-    ,_avgBenchmarkTime(0.0f)
+    // ,_numOfBenchmarks(0)
+    // ,_avgBenchmarkTime(0.0f)
 {
     addProperty(_dataOptions);
-    addProperty(_useLog);
+    // addProperty(_useLog);
     addProperty(_useHistogram);
     addProperty(_autoFilter);
     addProperty(_normValues);
@@ -241,10 +241,10 @@ void DataCygnet::setPropertyCallbacks(){
         updateTexture();
     });
     
-    _useLog.onChange([this](){
-        _dataProcessor->useLog(_useLog.value());
-        updateTexture();
-    });
+    // _useLog.onChange([this](){
+    //     _dataProcessor->useLog(_useLog.value());
+    //     updateTexture();
+    // });
 
     _useHistogram.onChange([this](){
         _dataProcessor->useHistogram(_useHistogram.value());
@@ -266,6 +266,8 @@ void DataCygnet::setPropertyCallbacks(){
     _autoFilter.onChange([this](){ 
         if(_autoFilter.value())
             _backgroundValues.setValue(_dataProcessor->filterValues());
+        else
+            _backgroundValues.setValue(glm::vec2(0.f));
         updateTexture();
     });
 }
@@ -305,10 +307,10 @@ void DataCygnet::subscribeToGroup(){
         _transferFunctionsFile.setValue(dict.value<std::string>("transferFunctions"));
     });
 
-    groupEvent->subscribe(name(), "useLogChanged", [&](const ghoul::Dictionary& dict){
-        LDEBUG(name() + " Event useLogChanged");
-        _useLog.setValue(dict.value<bool>("useLog"));
-    });
+    // groupEvent->subscribe(name(), "useLogChanged", [&](const ghoul::Dictionary& dict){
+    //     LDEBUG(name() + " Event useLogChanged");
+    //     _useLog.setValue(dict.value<bool>("useLog"));
+    // });
 
     groupEvent->subscribe(name(), "useHistogramChanged", [&](ghoul::Dictionary dict){
         LDEBUG(name() + " Event useHistogramChanged");
@@ -329,8 +331,20 @@ void DataCygnet::subscribeToGroup(){
 }
 
 void DataCygnet::getGroupPropertyValues(){
-    if(!_group)
+    if(!_group){
+        _backgroundValues.onChange([this]{
+            glm::vec2 bv = _backgroundValues.value();
+
+            if(bv.x > bv.y){
+                float y = bv.y;
+                bv.y = bv.x;
+                bv.x = y;
+
+                _backgroundValues.setValue(bv);
+            }
+        });
         return;
+    }
 
     std::unique_ptr<ghoul::Dictionary> properties = _group->propertyValues();
 

modules/iswa/rendering/datacygnet.h

@@ -103,7 +103,7 @@ protected:
     properties::StringProperty _transferFunctionsFile;
     properties::Vec2Property _backgroundValues;
     properties::Vec2Property _normValues;
-    properties::BoolProperty _useLog;
+    // properties::BoolProperty _useLog;
     properties::BoolProperty _useHistogram;
     properties::BoolProperty _autoFilter;
 
@@ -112,8 +112,8 @@ protected:
     glm::size3_t _textureDimensions;
 
     //FOR TESTING
-    int _numOfBenchmarks;
-    double _avgBenchmarkTime;
+    // int _numOfBenchmarks;
+    // double _avgBenchmarkTime;
 
 private:
     bool readyToRender() const override;

modules/iswa/rendering/dataplane.cpp

@@ -50,7 +50,7 @@ bool DataPlane::initialize(){
         _dataProcessor = _group->dataProcessor();
         subscribeToGroup();
     }else{
-        OsEng.gui()._iswa.registerProperty(&_useLog);
+        // OsEng.gui()._iswa.registerProperty(&_useLog);
         OsEng.gui()._iswa.registerProperty(&_useHistogram);
         OsEng.gui()._iswa.registerProperty(&_autoFilter);
         OsEng.gui()._iswa.registerProperty(&_normValues);
@@ -158,25 +158,25 @@ std::vector<float*> DataPlane::textureData(){
     }
     // _textureDimensions = _dataProcessor->dimensions();
 
-    // FOR TESTING
-    // ===========
-    std::chrono::time_point<std::chrono::system_clock> start, end;
-    start = std::chrono::system_clock::now();
-    // ===========
-    std::vector<float*> d = _dataProcessor->processData(_dataBuffer, _dataOptions, _textureDimensions);
+    // // FOR TESTING
+    // // ===========
+    // std::chrono::time_point<std::chrono::system_clock> start, end;
+    // start = std::chrono::system_clock::now();
+    // // ===========
+    // std::vector<float*> d = _dataProcessor->processData(_dataBuffer, _dataOptions, _textureDimensions);
 
-    // FOR TESTING
-    // ===========
-    end = std::chrono::system_clock::now();
-    _numOfBenchmarks++;
-    std::chrono::duration<double> elapsed_seconds = end-start;
-    _avgBenchmarkTime = ( (_avgBenchmarkTime * (_numOfBenchmarks-1)) + elapsed_seconds.count() ) / _numOfBenchmarks;
-    std::cout << " processData() " << name() << std::endl;
-    std::cout << "avg elapsed time: " << _avgBenchmarkTime << "s\n";
-    std::cout << "num Benchmarks: " << _numOfBenchmarks << "\n";
+    // // FOR TESTING
+    // // ===========
+    // end = std::chrono::system_clock::now();
+    // _numOfBenchmarks++;
+    // std::chrono::duration<double> elapsed_seconds = end-start;
+    // _avgBenchmarkTime = ( (_avgBenchmarkTime * (_numOfBenchmarks-1)) + elapsed_seconds.count() ) / _numOfBenchmarks;
+    // std::cout << " processData() " << name() << std::endl;
+    // std::cout << "avg elapsed time: " << _avgBenchmarkTime << "s\n";
+    // std::cout << "num Benchmarks: " << _numOfBenchmarks << "\n";
     // ===========
 
-    return d;
+    return _dataProcessor->processData(_dataBuffer, _dataOptions, _textureDimensions);
 }
 
 }// namespace openspace

modules/iswa/rendering/datasphere.cpp

@@ -69,7 +69,7 @@ bool DataSphere::initialize(){
         subscribeToGroup();
         //getGroupPropertyValues();
     }else{
-        OsEng.gui()._iswa.registerProperty(&_useLog);
+        // OsEng.gui()._iswa.registerProperty(&_useLog);
         OsEng.gui()._iswa.registerProperty(&_useHistogram);
         OsEng.gui()._iswa.registerProperty(&_autoFilter);
         OsEng.gui()._iswa.registerProperty(&_normValues);

modules/iswa/rendering/iswadatagroup.cpp

@@ -41,8 +41,7 @@ namespace {
 namespace openspace{
 IswaDataGroup::IswaDataGroup(std::string name, std::string type)
     :IswaBaseGroup(name, type)    
-    ,_useLog("useLog","Use Logarithm", false)
-
+    // ,_useLog("useLog","Use Logarithm", false)
     ,_useHistogram("useHistogram", "Auto Contrast", false)
     ,_autoFilter("autoFilter", "Auto Filter", true)
     ,_normValues("normValues", "Normalize Values", glm::vec2(1.0,1.0), glm::vec2(0), glm::vec2(5.0))
@@ -50,7 +49,7 @@ IswaDataGroup::IswaDataGroup(std::string name, std::string type)
     ,_transferFunctionsFile("transferfunctions", "Transfer Functions", "${SCENE}/iswa/tfs/default.tf")
     ,_dataOptions("dataOptions", "Data Options")
 {
-    addProperty(_useLog);
+    // addProperty(_useLog);
     addProperty(_useHistogram);
     addProperty(_autoFilter);
     addProperty(_normValues);
@@ -65,7 +64,7 @@ IswaDataGroup::IswaDataGroup(std::string name, std::string type)
 IswaDataGroup::~IswaDataGroup(){}
 
 void IswaDataGroup::registerProperties(){
-    OsEng.gui()._iswa.registerProperty(&_useLog);
+    // OsEng.gui()._iswa.registerProperty(&_useLog);
     OsEng.gui()._iswa.registerProperty(&_useHistogram);
     OsEng.gui()._iswa.registerProperty(&_autoFilter);
     OsEng.gui()._iswa.registerProperty(&_normValues);
@@ -75,10 +74,10 @@ void IswaDataGroup::registerProperties(){
         OsEng.gui()._iswa.registerProperty(&_backgroundValues);
 
 
-    _useLog.onChange([this]{
-        LDEBUG("Group " + name() + " published useLogChanged");
-        _groupEvent->publish("useLogChanged", ghoul::Dictionary({{"useLog", _useLog.value()}}));
-    });
+    // _useLog.onChange([this]{
+    //     LDEBUG("Group " + name() + " published useLogChanged");
+    //     _groupEvent->publish("useLogChanged", ghoul::Dictionary({{"useLog", _useLog.value()}}));
+    // });
 
     _useHistogram.onChange([this]{
         LDEBUG("Group " + name() + " published useHistogramChanged");
@@ -95,6 +94,7 @@ void IswaDataGroup::registerProperties(){
             OsEng.gui()._iswa.unregisterProperty(&_backgroundValues); 
         // else if autofilter is turned off, register backgroundValues 
         } else {
+            _backgroundValues.setValue(glm::vec2(0.f));
             OsEng.gui()._iswa.registerProperty(&_backgroundValues, &_autoFilter);            
         }
         _groupEvent->publish("autoFilterChanged", ghoul::Dictionary({{"autoFilter", _autoFilter.value()}}));
@@ -106,6 +106,16 @@ void IswaDataGroup::registerProperties(){
     });
 
     _backgroundValues.onChange([this]{
+        glm::vec2 bv = _backgroundValues.value();
+
+        if(bv.x > bv.y){
+            float y = bv.y;
+            bv.y = bv.x;
+            bv.x = y;
+
+            _backgroundValues.setValue(bv);
+        }
+
         LDEBUG("Group " + name() + " published backgroundValuesChanged");
         _groupEvent->publish("backgroundValuesChanged", ghoul::Dictionary({{"backgroundValues", _backgroundValues.value()}}));
     });

modules/iswa/rendering/iswadatagroup.h

@@ -43,7 +43,7 @@ protected:
     void registerProperties();
     void createDataProcessor();
 
-    properties::BoolProperty _useLog;
+    // properties::BoolProperty _useLog;
     properties::BoolProperty _useHistogram;
     properties::BoolProperty _autoFilter;
     properties::Vec2Property _normValues;

modules/iswa/rendering/kameleonplane.cpp

@@ -105,7 +105,7 @@ bool KameleonPlane::initialize(){
         _dataProcessor = _group->dataProcessor();
         subscribeToGroup();
     }else{
-        OsEng.gui()._iswa.registerProperty(&_useLog);
+        // OsEng.gui()._iswa.registerProperty(&_useLog);
         OsEng.gui()._iswa.registerProperty(&_useHistogram);
         OsEng.gui()._iswa.registerProperty(&_autoFilter);
         OsEng.gui()._iswa.registerProperty(&_normValues);

modules/iswa/shaders/dataplane_fs.glsl

@@ -60,18 +60,17 @@ Fragment getFragment() {
         v /= numTextures;
         
         vec4 color = texture(transferFunctions[0], vec2(v,0));
-        if((v<(x+y)) && v>(x-y))
+        if(v >= x  && v <= y)
             color = transparent;
-            // color = mix(transparent, color, clamp(1,0,abs(v-x)));
 
         diffuse = color;
     }else{
         for(int i=0; i<numTextures; i++){
             v = texture(textures[i], vs_st).r;
             vec4 color = texture(transferFunctions[i], vec2(v,0));
-            if((v<(x+y)) && v>(x-y))
+            if(v >= x  && v <= y)
                 color = transparent;
-                // color = mix(transparent, color, clamp(1,0,abs(v-x)));
+
             diffuse += color;
         }
     }

modules/iswa/shaders/datasphere_fs.glsl

@@ -60,16 +60,16 @@ Fragment getFragment() {
         v /= numTextures;
         
         vec4 color = texture(transferFunctions[0], vec2(v,0));
-        if((v<(x+y)) && v>(x-y))
-            color = mix(transparent, color, clamp(1,0,abs(v-x)));
+        if(v >= x  && v <= y)
+            color = transparent;
 
         diffuse = color;
     }else{
         for(int i=0; i<numTextures; i++){
             v = texture(textures[i], vec2(vs_st.t, vs_st.s)).r;
             vec4 color = texture(transferFunctions[i], vec2(v,0));
-            if((v<(x+y)) && v>(x-y))
-                color = mix(transparent, color, clamp(1,0,abs(v-x)));
+            if(v >= x  && v <= y)
+                color = transparent;
             diffuse += color;
         }
     }
@@ -79,7 +79,6 @@ Fragment getFragment() {
 
     diffuse.a *= transparency;
     
-    // diffuse = vec4(vs_st.s, 0,0,1);
     Fragment frag;
     frag.color = diffuse;
     frag.depth = depth;

modules/iswa/util/dataprocessor.cpp

@@ -28,14 +28,14 @@ namespace {
 	const std::string _loggerCat = "DataProcessor";
     const int NumBins = 512;
 }
-
+// const float normVal = 1.0;
 namespace openspace {
 DataProcessor::DataProcessor()
     :_useLog(false)
     ,_useHistogram(false)
+    // ,_normValues(glm::vec2(normVal))
     ,_normValues(glm::vec2(1.0))
     ,_filterValues(glm::vec2(0.0))
-    //,_histNormValues(glm::vec2(4.f, 4.f))
 {
     _coordinateVariables = {"x", "y", "z", "phi", "theta"};
 }
@@ -70,6 +70,7 @@ void DataProcessor::clear(){
     _histograms.clear();
     _numValues.clear();
     _fitValues.clear();
+    _unNormalizedhistograms.clear();
 }
 
 
@@ -84,7 +85,7 @@ float DataProcessor::processDataPoint(float value, int option){
         v = histogram->equalize(normalizeWithStandardScore(value, mean, sd, glm::vec2(_fitValues[option])))/(float)NumBins;
         // v = histogram->equalize(value)/(float)512;
     }else{
-        v = normalizeWithStandardScore(value, mean, sd, glm::vec2(_fitValues[option]));
+        v = normalizeWithStandardScore(value, mean, sd, _normValues);
     }
     return v;
 }
@@ -119,6 +120,7 @@ void DataProcessor::initializeVectors(int numOptions){
     if(_numValues.empty()) _numValues  = std::vector<float>(numOptions, 0.0f);
     if(_fitValues.empty()) _fitValues  = std::vector<float>(numOptions, 0.0f);
     if(_histograms.empty())_histograms = std::vector<std::shared_ptr<Histogram>>(numOptions, nullptr);
+    if(_unNormalizedhistograms.empty())_unNormalizedhistograms = std::vector<std::shared_ptr<Histogram>>(numOptions, nullptr);
 }
 
 void DataProcessor::calculateFilterValues(std::vector<int> selectedOptions){
@@ -139,14 +141,14 @@ void DataProcessor::calculateFilterValues(std::vector<int> selectedOptions){
                 filterMid = histogram->highestBinValue(_useHistogram);
                 filterWidth = histogram->binWidth();
 
-                //atleast one pixel value width. 1/512 above mid and 1/512 below mid => 1/256 filtered
+                //at least one pixel value width. 1/512 above mid and 1/512 below mid => 1/256 filtered
                 filterWidth = std::max(filterWidth, 1.0f/512.0f);
             }else{
                 Histogram hist = _histograms[option]->equalize();
                 filterMid = hist.highestBinValue(true);
                 filterWidth = std::min(1.f / (float)NumBins, 1.0f/512.0f);
             }
-            _filterValues += glm::vec2(filterMid, filterWidth);
+            _filterValues += glm::vec2(filterMid-filterWidth, filterMid+filterWidth);
 
         }
         _filterValues /= numSelected;   
@@ -162,12 +164,21 @@ void DataProcessor::add(std::vector<std::vector<float>>& optionValues, std::vect
         std::vector<float> values = optionValues[i];
         numValues = values.size();
 
+        //set min, max for the unnormalized histogram
+        if(!_unNormalizedhistograms[i]){
+             _unNormalizedhistograms[i] = std::make_shared<Histogram>(_min[i], _max[i], NumBins);
+        }else{
+            _unNormalizedhistograms[i]->changeRange(_min[i], _max[i]);
+        }
+
         variance = 0;
         mean = (1.0f/numValues)*sum[i];
 
+        //add values to unnormalized histogram and calculate variance
         for(int j=0; j<numValues; j++){
             value = values[j];
             variance +=  pow(value-mean, 2);
+            _unNormalizedhistograms[i]->add(value, 1);
         }
 
         standardDeviation = sqrt(variance/ numValues);
@@ -179,22 +190,22 @@ void DataProcessor::add(std::vector<std::vector<float>>& optionValues, std::vect
         _standardDeviation[i] = sqrt(pow(standardDeviation, 2) + pow(_standardDeviation[i], 2));
         _numValues[i] += numValues;
         
+        _unNormalizedhistograms[i]->generateEqualizer();
 
-        float fit = 10.0f*_standardDeviation[i]/(_max[i]-_min[i]);
+        //set the normalization fit value
+        float fit = _unNormalizedhistograms[i]->entropy();
         float oldFit = _fitValues[i];
         _fitValues[i] = fit;
 
         mean = (1.0f/_numValues[i])*_sum[i];
-
-
-        float min = normalizeWithStandardScore(_min[i], mean, _standardDeviation[i], glm::vec2(_fitValues[i]));
         float max = normalizeWithStandardScore(_max[i], mean, _standardDeviation[i], glm::vec2(_fitValues[i]));
+        float min = normalizeWithStandardScore(_min[i], mean, _standardDeviation[i], glm::vec2(_fitValues[i]));
 
         if(!_histograms[i]){
              _histograms[i] = std::make_shared<Histogram>(min, max, NumBins);
         }
         else{
-            //Re normalize all the values in the old histogram
+            //Renormalize all the values in the old histogram
             const float* histData = _histograms[i]->data();
             float histMin = _histograms[i]->minValue();
             float histMax = _histograms[i]->maxValue();
@@ -217,15 +228,14 @@ void DataProcessor::add(std::vector<std::vector<float>>& optionValues, std::vect
             _histograms[i] = newHist;
         }
 
+        //add the new values to the histogram
         for(int j=0; j<numValues; j++){
             value = values[j];
             _histograms[i]->add(normalizeWithStandardScore(value, mean, _standardDeviation[i], glm::vec2(_fitValues[i])), 1);
-
         }
-
-        _histograms[i]->generateEqualizer();
-
+        _histograms[i]->generateEqualizer(true);
     }
+
 }
 
 }

modules/iswa/util/dataprocessor.h

@@ -109,6 +109,7 @@ private:
 
     std::vector<std::shared_ptr<Histogram>> _histograms;
 
+    std::vector<std::shared_ptr<Histogram>> _unNormalizedhistograms;
 };
 
 } // namespace openspace

src/util/histogram.cpp

@@ -248,12 +248,29 @@ void Histogram::normalize() {
  * Old histogram value is the index of the array, and the new equalized
  * value will be the value at the index.
  */
-void Histogram::generateEqualizer(){
+void Histogram::generateEqualizer(bool withoutHighestBin){
     float previousCdf = 0.0f;
     _equalizer = std::vector<float>(_numBins, 0.0f);
+
+    int highestBin = -1;
+    float highestProbability = 0;
+
+    if(withoutHighestBin){
+        highestBin = 0; 
+        for(int i=0; i<_numBins; i++){
+            if(_data[i] > _data[highestBin]){
+                highestBin = i;
+            }
+        }
+        highestProbability = _data[highestBin] / (float)_numValues;
+    }
+
+
     for(int i = 0; i < _numBins; i++){
-        
-        float probability = _data[i] / (float)_numValues; 
+        float probability = highestProbability/(float)_numBins;
+        if(i != highestBin)
+             probability += _data[i] / (float)_numValues;
+
         float cdf  = previousCdf + probability;
         cdf = std::min(1.0f, cdf);
         _equalizer[i] = cdf * (_numBins-1);
@@ -292,7 +309,8 @@ float Histogram::equalize(float value){
 }
 
 float Histogram::entropy() const {
-    float entropy;
+    float entropy = 0.f;
+
     for(int i = 0; i < _numBins; i++){
         if(_data[i] != 0)
             entropy -= ((float)_data[i]/_numValues) * log2((float)_data[i]/_numValues);