diff --git a/modules/iswa/util/dataprocessor.cpp b/modules/iswa/util/dataprocessor.cpp
index e2ac38055b..f643e402e5 100644
--- a/modules/iswa/util/dataprocessor.cpp
+++ b/modules/iswa/util/dataprocessor.cpp
@@ -74,7 +74,6 @@ void DataProcessor::clear(){
     _unNormalizedhistograms.clear();
 }
 
-
 float DataProcessor::processDataPoint(float value, int option){
     if(_numValues.empty()) return 0.0f;
     std::shared_ptr<Histogram> histogram = _histograms[option];
@@ -101,16 +100,6 @@ float DataProcessor::normalizeWithStandardScore(float value, float mean, float s
     return ( standardScore + zScoreMin )/(zScoreMin + zScoreMax );  
 }
 
-// float DataProcessor::unnormalizeWithStandardScore(float standardScore, float mean, float sd, glm::vec2 normalizationValues){
-//     float zScoreMin = normalizationValues.x;
-//     float zScoreMax = normalizationValues.y; 
-
-//     float value = standardScore*(zScoreMax+zScoreMin)-zScoreMin;
-//     value = value*sd+mean; 
-
-//     return value; 
-// }
-
 void DataProcessor::initializeVectors(int numOptions){
     if(_min.empty()) _min = std::vector<float>(numOptions, std::numeric_limits<float>::max());
     if(_max.empty()) _max = std::vector<float>(numOptions, std::numeric_limits<float>::min());
diff --git a/modules/iswa/util/dataprocessor.h b/modules/iswa/util/dataprocessor.h
index 1b6d2c8405..2bdbca1cc6 100644
--- a/modules/iswa/util/dataprocessor.h
+++ b/modules/iswa/util/dataprocessor.h
@@ -50,7 +50,7 @@ public:
     /**
      * Function that initializes the dataprocessor for a new data variable by 
      * calculating its min & max value, standard deviation, sum and histogram for a 
-     * given data file. This file will then be used as reference when normalizing, filtering
+     * given data file. This data will then be used as reference when normalizing, filtering
      * and give auto-contrast 
      * 
      * @param data The data file content to add data from
@@ -90,10 +90,8 @@ protected:
     std::set<std::string> _coordinateVariables;
     glm::size3_t _dimensions;
 
-    //glm::vec2 _histNormValues;
 private:
     float normalizeWithStandardScore(float value, float mean, float sd, glm::vec2 normalizationValues = glm::vec2(1.0f, 1.0f));
-    //float unnormalizeWithStandardScore(float value, float mean, float sd, glm::vec2 normalizationValues = glm::vec2(1.0f, 1.0f));
 
     bool _useLog;
     bool _useHistogram;
diff --git a/shaders/postRender.frag b/shaders/postrender.frag
similarity index 100%
rename from shaders/postRender.frag
rename to shaders/postrender.frag