From 290791049916a6b4654f9eac10799cbb81e7ae37 Mon Sep 17 00:00:00 2001 From: Michael Nilsson Date: Mon, 27 Jun 2016 17:39:13 -0400 Subject: [PATCH] add comments and removed unnesesary code --- modules/iswa/util/dataprocessor.cpp | 25 ++++++++++++------------- modules/iswa/util/dataprocessor.h | 3 ++- modules/iswa/util/dataprocessorjson.cpp | 1 + modules/iswa/util/iswamanager.cpp | 1 + 4 files changed, 16 insertions(+), 14 deletions(-) diff --git a/modules/iswa/util/dataprocessor.cpp b/modules/iswa/util/dataprocessor.cpp index c5acc30d17..2428c0f44a 100644 --- a/modules/iswa/util/dataprocessor.cpp +++ b/modules/iswa/util/dataprocessor.cpp @@ -101,15 +101,15 @@ 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 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; +// float value = standardScore*(zScoreMax+zScoreMin)-zScoreMin; +// value = value*sd+mean; - return value; -} +// return value; +// } void DataProcessor::initializeVectors(int numOptions){ if(_min.empty()) _min = std::vector(numOptions, std::numeric_limits::max()); @@ -141,16 +141,16 @@ void DataProcessor::calculateFilterValues(std::vector selectedOptions){ filterMid = histogram->highestBinValue(_useHistogram); filterWidth = histogram->binWidth(); - //at least one pixel value width. 1/numBins above mid and 1/numBins below mid => 1/(numBins/2) filtered - // filterWidth = std::max(filterWidth, 1.0f/(float)NumBins); - filterMid = normalizeWithStandardScore(filterMid, mean, standardDeviation, _normValues); filterWidth = fabs(0.5-normalizeWithStandardScore(mean+filterWidth, mean, standardDeviation, _normValues)); + // at least one pixel value width. 1/512 above mid and 1/512 below mid => 1/(numBins/2) 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/(float)NumBins); + filterWidth = std::min(1.0f / (float)NumBins, 1.0f / 512.0f); } _filterValues += glm::vec2(filterMid-filterWidth, filterMid+filterWidth); @@ -203,7 +203,7 @@ void DataProcessor::add(std::vector>& optionValues, std::vect _numValues[i] += numValues; mean = (1.0f/_numValues[i])*_sum[i]; - const float* histData = _unNormalizedhistograms[i]->data(); + //const float* histData = _unNormalizedhistograms[i]->data(); float histMin = _unNormalizedhistograms[i]->minValue(); float histMax = _unNormalizedhistograms[i]->maxValue(); int numBins = _unNormalizedhistograms[i]->numBins(); @@ -215,7 +215,6 @@ void DataProcessor::add(std::vector>& optionValues, std::vect float fit = _unNormalizedhistograms[i]->entropy(); _fitValues[i] = fit; - float max = normalizeWithStandardScore(histMax, mean, _standardDeviation[i], glm::vec2(_fitValues[i])); float min = normalizeWithStandardScore(histMin, mean, _standardDeviation[i], glm::vec2(_fitValues[i])); diff --git a/modules/iswa/util/dataprocessor.h b/modules/iswa/util/dataprocessor.h index 52bd962628..5e36d27f1b 100644 --- a/modules/iswa/util/dataprocessor.h +++ b/modules/iswa/util/dataprocessor.h @@ -93,7 +93,7 @@ protected: //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)); + //float unnormalizeWithStandardScore(float value, float mean, float sd, glm::vec2 normalizationValues = glm::vec2(1.0f, 1.0f)); bool _useLog; bool _useHistogram; @@ -101,6 +101,7 @@ private: glm::vec2 _normValues; glm::vec2 _filterValues; + // Using vectors to store each data option seperatly std::vector _sum; std::vector _standardDeviation; std::vector _numValues; diff --git a/modules/iswa/util/dataprocessorjson.cpp b/modules/iswa/util/dataprocessorjson.cpp index dd8a3f3fed..6755cfa42f 100644 --- a/modules/iswa/util/dataprocessorjson.cpp +++ b/modules/iswa/util/dataprocessorjson.cpp @@ -67,6 +67,7 @@ void DataProcessorJson::addDataValues(const std::string& data, const properties: int numOptions = dataOptions.options().size(); initializeVectors(numOptions); + // parse json and calculate min, max and sum if(!data.empty()){ json j = json::parse(data); json variables = j["variables"]; diff --git a/modules/iswa/util/iswamanager.cpp b/modules/iswa/util/iswamanager.cpp index 9f665cc639..4e18760a05 100644 --- a/modules/iswa/util/iswamanager.cpp +++ b/modules/iswa/util/iswamanager.cpp @@ -334,6 +334,7 @@ void IswaManager::createIswaCygnet(std::shared_ptr metadata){ } } metadata->name = metadata->group + "_" + metadata->name; + // create the luaTable for script std::string luaTable = _luaConverter.toLuaTable(metadata);