diff --git a/Modules/Applications/AppClassification/app/otbVectorRegression.cxx b/Modules/Applications/AppClassification/app/otbVectorRegression.cxx
index d1b8a02f66db1d9b509cb1a0408b6f5d18501177..d4e23d4e491a2aa83d21c2f5dde609c2e3eb7d2c 100644
--- a/Modules/Applications/AppClassification/app/otbVectorRegression.cxx
+++ b/Modules/Applications/AppClassification/app/otbVectorRegression.cxx
@@ -93,7 +93,7 @@ void VectorRegression::DoInitSpecialization()
SetOfficialDocLink();
}
-// Confidence map computation is not support for regression.
+// Confidence map computation is not supported for regression.
template <>
bool VectorRegression::shouldComputeConfidenceMap() const
{
diff --git a/Modules/Applications/AppClassification/include/otbVectorPrediction.h b/Modules/Applications/AppClassification/include/otbVectorPrediction.h
index 12cea014877dd05adc7a5f4c664e0d62f7ddbabd..916ace1ea6f6bbfff7ff33cd2785249be67c3139 100644
--- a/Modules/Applications/AppClassification/include/otbVectorPrediction.h
+++ b/Modules/Applications/AppClassification/include/otbVectorPrediction.h
@@ -49,36 +49,36 @@ class VectorPrediction : public Application
{
public:
/** Standard class typedefs. */
- typedef VectorPrediction Self;
- typedef Application Superclass;
- typedef itk::SmartPointer<Self> Pointer;
- typedef itk::SmartPointer<const Self> ConstPointer;
+ using Self = VectorPrediction;
+ using Superclass = Application;
+ using Pointer = itk::SmartPointer<Self>;
+ using ConstPointer = itk::SmartPointer<const Self>;
/** Standard macro */
itkNewMacro(Self);
itkTypeMacro(Self, Application)
- /** Filters typedef */
- typedef float ValueType;
+ /** Filters typedef */
+ using ValueType = float;
// Label type is float for regression and unsigned int for classification
- typedef typename std::conditional<RegressionMode, float, unsigned int>::type LabelType;
+ using LabelType = typename std::conditional<RegressionMode, float, unsigned int>::type;
- typedef itk::FixedArray<LabelType, 1> LabelSampleType;
- typedef itk::Statistics::ListSample<LabelSampleType> LabelListSampleType;
+ using LabelSampleType = itk::FixedArray<LabelType, 1>;
+ using LabelListSampleType = itk::Statistics::ListSample<LabelSampleType>;
- typedef otb::MachineLearningModel<ValueType, LabelType> MachineLearningModelType;
- typedef otb::MachineLearningModelFactory<ValueType, LabelType> MachineLearningModelFactoryType;
- typedef typename MachineLearningModelType::Pointer ModelPointerType;
- typedef typename MachineLearningModelType::ConfidenceListSampleType ConfidenceListSampleType;
+ using MachineLearningModelType = otb::MachineLearningModel<ValueType, LabelType>;
+ using MachineLearningModelFactoryType = otb::MachineLearningModelFactory<ValueType, LabelType>;
+ using ModelPointerType = typename MachineLearningModelType::Pointer;
+ using ConfidenceListSampleType = typename MachineLearningModelType::ConfidenceListSampleType;
/** Statistics Filters typedef */
- typedef itk::VariableLengthVector<ValueType> MeasurementType;
- typedef otb::StatisticsXMLFileReader<MeasurementType> StatisticsReader;
+ using MeasurementType = itk::VariableLengthVector<ValueType>;
+ using StatisticsReader = otb::StatisticsXMLFileReader<MeasurementType>;
- typedef itk::VariableLengthVector<ValueType> InputSampleType;
- typedef itk::Statistics::ListSample<InputSampleType> ListSampleType;
- typedef otb::Statistics::ShiftScaleSampleListFilter<ListSampleType, ListSampleType> ShiftScaleFilterType;
+ using InputSampleType = itk::VariableLengthVector<ValueType>;
+ using ListSampleType = itk::Statistics::ListSample<InputSampleType>;
+ using ShiftScaleFilterType = otb::Statistics::ShiftScaleSampleListFilter<ListSampleType, ListSampleType>;
~VectorPrediction() override
{
diff --git a/Modules/Applications/AppClassification/include/otbVectorPrediction.hxx b/Modules/Applications/AppClassification/include/otbVectorPrediction.hxx
index 1310fdfb291f1c7390001b36185b9cb29d3839ae..4d84e9e0fc01d4f70c93fbc3deed4629f9115cda 100644
--- a/Modules/Applications/AppClassification/include/otbVectorPrediction.hxx
+++ b/Modules/Applications/AppClassification/include/otbVectorPrediction.hxx
@@ -47,24 +47,23 @@ void VectorPrediction<RegressionMode>::DoUpdateParameters()
{
if (HasValue("in"))
{
- std::string shapefile = GetParameterString("in");
+ auto shapefileName = GetParameterString("in");
- otb::ogr::DataSource::Pointer ogrDS;
-
- ogrDS = otb::ogr::DataSource::New(shapefile, otb::ogr::DataSource::Modes::Read);
- otb::ogr::Layer layer = ogrDS->GetLayer(0);
+ auto ogrDS = otb::ogr::DataSource::New(shapefileName, otb::ogr::DataSource::Modes::Read);
+ auto layer = ogrDS->GetLayer(0);
OGRFeatureDefn& layerDefn = layer.GetLayerDefn();
-
+
ClearChoices("feat");
for (int iField = 0; iField < layerDefn.GetFieldCount(); iField++)
{
- std::string item = layerDefn.GetFieldDefn(iField)->GetNameRef();
+ auto fieldDefn = layerDefn.GetFieldDefn(iField);
+ std::string item = fieldDefn->GetNameRef();
std::string key(item);
key.erase(std::remove_if(key.begin(), key.end(), IsNotAlphaNum), key.end());
std::transform(key.begin(), key.end(), key.begin(), tolower);
- OGRFieldType fieldType = layerDefn.GetFieldDefn(iField)->GetType();
+ auto fieldType = fieldDefn->GetType();
if (fieldType == OFTInteger || fieldType == OFTInteger64 || fieldType == OFTReal)
{
std::string tmpKey = "feat." + key;
@@ -77,21 +76,17 @@ void VectorPrediction<RegressionMode>::DoUpdateParameters()
template <bool RegressionMode>
void VectorPrediction<RegressionMode>::DoExecute()
{
- clock_t tic = clock();
+ auto shapefileName = GetParameterString("in");
- std::string shapefile = GetParameterString("in");
-
- otb::ogr::DataSource::Pointer source = otb::ogr::DataSource::New(shapefile, otb::ogr::DataSource::Modes::Read);
- otb::ogr::Layer layer = source->GetLayer(0);
+ auto source = otb::ogr::DataSource::New(shapefileName, otb::ogr::DataSource::Modes::Read);
+ auto layer = source->GetLayer(0);
typename ListSampleType::Pointer input = ListSampleType::New();
const int nbFeatures = GetSelectedItems("feat").size();
input->SetMeasurementVectorSize(nbFeatures);
- otb::ogr::Layer::const_iterator it = layer.cbegin();
- otb::ogr::Layer::const_iterator itEnd = layer.cend();
- for (; it != itEnd; ++it)
+ for (auto const& feature : layer)
{
MeasurementType mv;
mv.SetSize(nbFeatures);
@@ -100,19 +95,18 @@ void VectorPrediction<RegressionMode>::DoExecute()
// Beware that itemIndex differs from ogr layer field index
unsigned int itemIndex = GetSelectedItems("feat")[idx];
std::string fieldName = GetChoiceNames("feat")[itemIndex];
- switch ((*it)[fieldName].GetType())
+
+ auto field = feature[fieldName];
+ switch (field.GetType())
{
- case OFTInteger:
- mv[idx] = static_cast<ValueType>((*it)[fieldName].GetValue<int>());
- break;
- case OFTInteger64:
- mv[idx] = static_cast<ValueType>((*it)[fieldName].GetValue<int>());
+ case OFTInteger || OFTInteger64:
+ mv[idx] = static_cast<ValueType>(field.template GetValue<int>());
break;
case OFTReal:
- mv[idx] = static_cast<ValueType>((*it)[fieldName].GetValue<double>());
+ mv[idx] = static_cast<ValueType>(field.template GetValue<double>());
break;
default:
- itkExceptionMacro(<< "incorrect field type: " << (*it)[fieldName].GetType() << ".");
+ itkExceptionMacro(<< "incorrect field type: " << field.GetType() << ".");
}
}
input->PushBack(mv);
@@ -202,7 +196,7 @@ void VectorPrediction<RegressionMode>::DoExecute()
// close input data source
source->Clear();
// Re-open input data source in update mode
- output = otb::ogr::DataSource::New(shapefile, otb::ogr::DataSource::Modes::Update_LayerUpdate);
+ output = otb::ogr::DataSource::New(shapefileName, otb::ogr::DataSource::Modes::Update_LayerUpdate);
}
otb::ogr::Layer outLayer = output->GetLayer(0);
@@ -217,11 +211,7 @@ void VectorPrediction<RegressionMode>::DoExecute()
// Add the field of prediction in the output layer if field not exist
- OGRFieldType labelType;
- if (RegressionMode == true)
- labelType = OFTReal;
- else
- labelType = OFTInteger;
+ const OGRFieldType labelType = RegressionMode ? OFTReal : OFTInteger;
int idx = layerDefn.GetFieldIndex(GetParameterString("cfield").c_str());
if (idx >= 0)
@@ -259,29 +249,25 @@ void VectorPrediction<RegressionMode>::DoExecute()
// Fill output layer
unsigned int count = 0;
std::string classfieldname = GetParameterString("cfield");
- it = layer.cbegin();
- itEnd = layer.cend();
- for (; it != itEnd; ++it, ++count)
+ for (auto const& feature : layer)
{
ogr::Feature dstFeature(outLayer.GetLayerDefn());
- dstFeature.SetFrom(*it, TRUE);
- dstFeature.SetFID(it->GetFID());
- switch (dstFeature[classfieldname].GetType())
+ dstFeature.SetFrom(feature, TRUE);
+ dstFeature.SetFID(feature.GetFID());
+ auto field = dstFeature[classfieldname];
+ switch (field.GetType())
{
- case OFTInteger:
- dstFeature[classfieldname].SetValue<int>(target->GetMeasurementVector(count)[0]);
- break;
- case OFTInteger64:
- dstFeature[classfieldname].SetValue<int>(target->GetMeasurementVector(count)[0]);
+ case OFTInteger || OFTInteger64:
+ field.template SetValue<int>(target->GetMeasurementVector(count)[0]);
break;
case OFTReal:
- dstFeature[classfieldname].SetValue<double>(target->GetMeasurementVector(count)[0]);
+ field.template SetValue<double>(target->GetMeasurementVector(count)[0]);
break;
case OFTString:
- dstFeature[classfieldname].SetValue<std::string>(std::to_string(target->GetMeasurementVector(count)[0]));
+ field.template SetValue<std::string>(std::to_string(target->GetMeasurementVector(count)[0]));
break;
default:
- itkExceptionMacro(<< "incorrect field type: " << dstFeature[classfieldname].GetType() << ".");
+ itkExceptionMacro(<< "incorrect field type: " << field.GetType() << ".");
}
if (computeConfidenceMap)
dstFeature[confFieldName].SetValue<double>(quality->GetMeasurementVector(count)[0]);
@@ -305,9 +291,6 @@ void VectorPrediction<RegressionMode>::DoExecute()
}
output->SyncToDisk();
-
- clock_t toc = clock();
- otbAppLogINFO("Elapsed: " << ((double)(toc - tic) / CLOCKS_PER_SEC) << " seconds.");
}
} // end namespace wrapper