diff --git a/ext/ghoul b/ext/ghoul
index 9bb5ce6bf4..5ef066647c 160000
--- a/ext/ghoul
+++ b/ext/ghoul
@@ -1 +1 @@
-Subproject commit 9bb5ce6bf45478f933189b98ef05dac17d8a6739
+Subproject commit 5ef066647c6e37af4391ca6890cf20b29f4a22be
diff --git a/include/openspace/util/histogram.h b/include/openspace/util/histogram.h
index 5e8136d848..0a7e517852 100644
--- a/include/openspace/util/histogram.h
+++ b/include/openspace/util/histogram.h
@@ -70,7 +70,12 @@ public:
     void generateEqualizer();
     Histogram equalize();
     float equalize (float);
-    float entropy();
+
+    /**
+     * Entropy is a measure of histogram dispersion.
+     * @return entropy value
+     */
+    float entropy() const;
 
     float highestBinValue(bool equalized, int overBins=0);
     float binWidth();
diff --git a/modules/iswa/rendering/datasphere.cpp b/modules/iswa/rendering/datasphere.cpp
index b96b2f7fee..03a24dfa94 100644
--- a/modules/iswa/rendering/datasphere.cpp
+++ b/modules/iswa/rendering/datasphere.cpp
@@ -91,7 +91,7 @@ bool DataSphere::initialize(){
     readTransferFunctions(_transferFunctionsFile.value());
 
     setPropertyCallbacks();
-    _useHistogram.setValue(true);
+    //_useHistogram.setValue(true);
     _autoFilter.setValue(true);
 
     return true;
diff --git a/modules/iswa/util/dataprocessor.cpp b/modules/iswa/util/dataprocessor.cpp
index 38bf21b0b8..15a7897136 100644
--- a/modules/iswa/util/dataprocessor.cpp
+++ b/modules/iswa/util/dataprocessor.cpp
@@ -28,6 +28,7 @@
 
 namespace {
 	const std::string _loggerCat = "DataProcessor";
+    const int NumBins = 512;
 }
 
 namespace openspace {
@@ -82,7 +83,7 @@ float DataProcessor::processDataPoint(float value, int option){
 
     float v;
     if(_useHistogram){
-        v = histogram->equalize(normalizeWithStandardScore(value, mean, sd, glm::vec2(_fitValues[option])))/(float)512;
+        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, _normValues);
@@ -128,27 +129,32 @@ void DataProcessor::calculateFilterValues(std::vector<int> selectedOptions){
     float mean, standardDeviation, filterMid, filterWidth;
 
     _filterValues = glm::vec2(0.0);
-    if(numSelected <= 0) return;
+    if (numSelected <= 0) return;
 
-    if(!_histograms.empty()){
-        for(int option : selectedOptions){
-            if(!_useHistogram){
+    if (!_histograms.empty()) {
+        for (int option : selectedOptions) {
+            if (!_useHistogram) {
                 mean = (1.0/_numValues[option])*_sum[option];
                 standardDeviation = _standardDeviation[option];
                 histogram = _histograms[option];
                 
                 filterMid = histogram->highestBinValue(_useHistogram);
                 filterWidth = mean+histogram->binWidth();
-                
-                filterMid = normalizeWithStandardScore(filterMid, mean, standardDeviation, _normValues);
+                //filterWidth = histogram->binWidth();
+
                 filterWidth = fabs(0.5-normalizeWithStandardScore(filterWidth, mean, standardDeviation, _normValues));
+                //filterWidth = fabs(normalizeWithStandardScore(filterWidth, mean, standardDeviation, _normValues));
+                //atleast one pixel value width. 1/512 above mid and 1/512 below mid => 1/256 filtered
+                filterWidth = std::min(filterWidth, 1.0f/512.0f);
+                filterMid = normalizeWithStandardScore(filterMid, mean, standardDeviation, _normValues);
+                //filterMid += filterWidth;
             }else{
                 Histogram hist = _histograms[option]->equalize();
                 filterMid = hist.highestBinValue(true);
-                std::cout << filterMid << std::endl;
-                filterWidth = 1.f/512.f;
+                filterWidth = std::min(1.f / (float)NumBins, 1.0f/512.0f);
             }
-
+            std::cout << "filtermid: " << filterMid << std::endl;
+            std::cout << "filterwidth: " << filterWidth << std::endl;
              _filterValues += glm::vec2(filterMid, filterWidth);
 
         }
@@ -194,7 +200,7 @@ void DataProcessor::add(std::vector<std::vector<float>>& optionValues, std::vect
         float max = normalizeWithStandardScore(_max[i], mean, _standardDeviation[i], glm::vec2(_fitValues[i]));
 
         if(!_histograms[i]){
-             _histograms[i] = std::make_shared<Histogram>(min, max, 512);
+             _histograms[i] = std::make_shared<Histogram>(min, max, NumBins);
         }
         else{
             //Re normalize all the values in the old histogram
@@ -227,7 +233,17 @@ void DataProcessor::add(std::vector<std::vector<float>>& optionValues, std::vect
         }
 
         _histograms[i]->generateEqualizer();
+<<<<<<< Updated upstream
 
+=======
+        
+        // std::cout << std::endl;
+        // _histograms[i]->print();
+        // std::cout << std::endl;
+        // std::cout << "Eq: ";
+        Histogram hist = _histograms[i]->equalize();
+        hist.print();
+>>>>>>> Stashed changes
     }
 }
 
diff --git a/src/util/histogram.cpp b/src/util/histogram.cpp
index f8416e41eb..ba2f147afe 100644
--- a/src/util/histogram.cpp
+++ b/src/util/histogram.cpp
@@ -291,7 +291,7 @@ float Histogram::equalize(float value){
     return _equalizer[bin];
 }
 
-float Histogram::entropy(){
+float Histogram::entropy() const {
     float entropy;
     for(int i = 0; i < _numBins; i++){
         if(_data[i] != 0)
@@ -316,10 +316,10 @@ void Histogram::print() const {
 
 float Histogram::highestBinValue(bool equalized, int overBins){
     int highestBin = 0;
-    float highestValue = 0;
+    float highestValue = 0.0f;
 
     for(int i=0; i<_numBins; i++){
-        float value = 0;
+        float value = 0.0f;
         int num = 0;
         for(int j=0; j<overBins; j++){
             if(i-j>0){
@@ -334,6 +334,7 @@ float Histogram::highestBinValue(bool equalized, int overBins){
 
         value += _data[i];
         value /= (float)++num;
+        //value = _data[i];
 
         if(value > highestValue){
             highestBin = i;
@@ -341,9 +342,8 @@ float Histogram::highestBinValue(bool equalized, int overBins){
         }
     }
 
-
     if(!equalized){
-        float low = _minValue + float(highestBin) / _numBins * (_maxValue - _minValue);
+        float low = _minValue + (float(highestBin) / _numBins) * (_maxValue - _minValue);
         float high = low + (_maxValue - _minValue) / float(_numBins);
         return (high+low)/2.0;
     }else{
@@ -353,7 +353,7 @@ float Histogram::highestBinValue(bool equalized, int overBins){
 }
 
 float Histogram::binWidth(){
-    return (_maxValue-_minValue)/_numBins;
+    return (_maxValue-_minValue)/float(_numBins);
 }
 
 std::ostream& operator<<(std::ostream& os, const Histogram& hist){