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merge conflict + update ghoul ref

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This commit is contained in:
Michael Nilsson
2016-06-20 13:46:38 -04:00
parent c285f4b156
commit 294a29d99a
5 changed files with 41 additions and 20 deletions
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ext/ghoul
+1 -1
Submodule ext/ghoul updated: 9bb5ce6bf4...5ef066647c
include/openspace/util/histogram.h
+6 -1
View File
@@ -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();
modules/iswa/rendering/datasphere.cpp
+1 -1
View File
@@ -91,7 +91,7 @@ bool DataSphere::initialize(){
readTransferFunctions(_transferFunctionsFile.value());
setPropertyCallbacks();
_useHistogram.setValue(true);
//_useHistogram.setValue(true);
_autoFilter.setValue(true);
return true;
modules/iswa/util/dataprocessor.cpp
+27 -11
View File
@@ -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
}
}
src/util/histogram.cpp
+6 -6
View File
@@ -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){