Windows build fix

Author: tveasey

lib/maths/CNaiveBayes.cc

@@ -121,12 +121,13 @@ CNaiveBayes::CNaiveBayes(const CNaiveBayesFeatureDensity& exemplar,
                          double decayRate,
                          TOptionalDouble minMaxLogLikelihoodToUseFeature)
     : m_MinMaxLogLikelihoodToUseFeature{minMaxLogLikelihoodToUseFeature},
-      m_DecayRate{decayRate}, m_Exemplar{exemplar.clone()}, m_ClassConditionalDensities{2} {
+      m_DecayRate{decayRate}, m_Exemplar{exemplar.clone()},
+      m_ClassConditionalDensities(2) {
 }
 
 CNaiveBayes::CNaiveBayes(const SDistributionRestoreParams& params,
                          core::CStateRestoreTraverser& traverser)
-    : m_DecayRate{params.s_DecayRate}, m_ClassConditionalDensities{2} {
+    : m_DecayRate{params.s_DecayRate}, m_ClassConditionalDensities(2) {
     traverser.traverseSubLevel(boost::bind(&CNaiveBayes::acceptRestoreTraverser,
                                            this, boost::cref(params), _1));
 }
@@ -186,7 +187,8 @@ bool CNaiveBayes::initialized() const {
 
 void CNaiveBayes::initialClassCounts(const TDoubleSizePrVec& counts) {
     for (const auto& count : counts) {
-        m_ClassConditionalDensities[count.second] = SClass{count.first, TFeatureDensityPtrVec{}};
+        m_ClassConditionalDensities[count.second] =
+            SClass{count.first, TFeatureDensityPtrVec{}};
     }
 }
 
@@ -348,8 +350,8 @@ bool CNaiveBayes::validate(const TDouble1VecVec& x) const {
     return true;
 }
 
-CNaiveBayes::SClass::SClass(double count, const TFeatureDensityPtrVec& conditionalDensities) :
-    s_Count{count}, s_ConditionalDensities(conditionalDensities) {
+CNaiveBayes::SClass::SClass(double count, const TFeatureDensityPtrVec& conditionalDensities)
+    : s_Count{count}, s_ConditionalDensities(conditionalDensities) {
 }
 
 bool CNaiveBayes::SClass::acceptRestoreTraverser(const SDistributionRestoreParams& params,

lib/maths/CTimeSeriesChangeDetector.cc

@@ -60,7 +60,7 @@ const double WINSORISATION_DERATE{1.0};
 }
 
 SChangeDescription::SChangeDescription(EDescription description, double value, const TPriorPtr& residualModel)
-    : s_Description{description}, s_Value{value}, s_ResidualModel{residualModel} {
+    : s_Description{description}, s_Value(1, value), s_ResidualModel{residualModel} {
 }
 
 std::string SChangeDescription::print() const {
@@ -86,14 +86,16 @@ CUnivariateTimeSeriesChangeDetector::CUnivariateTimeSeriesChangeDetector(
     core_t::TTime maximumTimeToDetect,
     double minimumDeltaBicToDetect)
     : m_MinimumTimeToDetect{minimumTimeToDetect}, m_MaximumTimeToDetect{maximumTimeToDetect},
-      m_MinimumDeltaBicToDetect{minimumDeltaBicToDetect}, m_SampleCount{0}, m_CurrentEvidenceOfChange{0.0},
-      m_ChangeModels{
-          std::make_shared<CUnivariateNoChangeModel>(trendModel, residualModel),
-          std::make_shared<CUnivariateLevelShiftModel>(trendModel, residualModel),
-          std::make_shared<CUnivariateTimeShiftModel>(trendModel, residualModel, -core::constants::HOUR),
-          std::make_shared<CUnivariateTimeShiftModel>(trendModel,
-                                                      residualModel,
-                                                      +core::constants::HOUR)} {
+      m_MinimumDeltaBicToDetect{minimumDeltaBicToDetect}, m_SampleCount{0}, m_CurrentEvidenceOfChange{0.0} {
+    m_ChangeModels.push_back(
+        std::make_shared<CUnivariateNoChangeModel>(trendModel, residualModel));
+    m_ChangeModels.push_back(
+        std::make_shared<CUnivariateLevelShiftModel>(trendModel, residualModel));
+    m_ChangeModels.push_back(std::make_shared<CUnivariateTimeShiftModel>(
+        trendModel, residualModel, -core::constants::HOUR));
+    m_ChangeModels.push_back(std::make_shared<CUnivariateTimeShiftModel>(
+        trendModel, residualModel, +core::constants::HOUR));
+
     if (trendModel->seasonalComponents().size() > 0) {
         m_ChangeModels.push_back(std::make_shared<CUnivariateLinearScaleModel>(
             trendModel, residualModel));

lib/maths/CTimeSeriesModel.cc

@@ -1283,7 +1283,7 @@ maths_t::EDataType CUnivariateTimeSeriesModel::dataType() const {
 
 CUnivariateTimeSeriesModel::TDoubleWeightsAry
 CUnivariateTimeSeriesModel::unpack(const TDouble2VecWeightsAry& weights) {
-    TDoubleWeightsAry result{maths_t::CUnitWeights::UNIT};
+    TDoubleWeightsAry result(maths_t::CUnitWeights::UNIT);
     for (std::size_t i = 0u; i < weights.size(); ++i) {
         result[i] = weights[i][0];
     }
@@ -1347,7 +1347,7 @@ CUnivariateTimeSeriesModel::testAndApplyChange(const CModelAddSamplesParams& par
                                                const TSizeVec& order,
                                                const TTimeDouble2VecSizeTrVec& values) {
     std::size_t median{order[order.size() / 2]};
-    TDoubleWeightsAry weights{unpack(params.priorWeights()[median])};
+    TDoubleWeightsAry weights(unpack(params.priorWeights()[median]));
     core_t::TTime time{values[median].first};
 
     if (m_ChangeDetector == nullptr) {
@@ -1440,7 +1440,7 @@ CUnivariateTimeSeriesModel::updateTrend(const TTimeDouble2VecSizeTrVec& samples,
     for (auto i : timeorder) {
         core_t::TTime time{samples[i].first};
         double value{samples[i].second[0]};
-        TDoubleWeightsAry weight{unpack(weights[i])};
+        TDoubleWeightsAry weight(unpack(weights[i]));
         if (m_TrendModel->addPoint(time, value, weight)) {
             result = E_Reset;
         }
@@ -2250,7 +2250,7 @@ CMultivariateTimeSeriesModel::confidenceInterval(core_t::TTime time,
 
     TDouble2Vec3Vec result(3, TDouble2Vec(dimension));
 
-    maths_t::TDoubleWeightsAry weights{maths_t::CUnitWeights::UNIT};
+    maths_t::TDoubleWeightsAry weights(maths_t::CUnitWeights::UNIT);
     for (std::size_t d = 0u; d < dimension;
          --marginalize[std::min(d, dimension - 2)], ++d) {
         double trend{m_TrendModel[d]->initialized()