STYLE: Replace T var; var = x with T var = x for arithmetic types

Following C++ Core Guidelines, Oct 3, 2024, "Always initialize an object",
https://isocpp.github.io/CppCoreGuidelines/CppCoreGuidelines#Res-always

Using Notepad++, Replace in Files, doing:

    Find what: ^( [ ]+)([a-z][a-z ]*[a-z])([ ]+)(\w+);[\r\n]+\1\4\ =
    Replace with: $1$2$3$4 =
    Filters: itk*.*
    Directory: D:\src\ITK\Modules
    [v] Match case
    (*) Regular expression

Excluded `delete` statements, even if they would match the regular expression
(as in `delete var; var = x`).

Modules/Core/Common/include/itkColorTable.hxx

@@ -349,8 +349,7 @@ ColorTable<TComponent>::GetClosestColorTableId(TComponent r, TComponent g, TComp
 
   for (unsigned int i = 0; i < m_NumberOfColors; ++i)
   {
-    double match;
-    match = (r - static_cast<double>(m_Color[i].GetRed())) * (r - static_cast<double>(m_Color[i].GetRed()));
+    double match = (r - static_cast<double>(m_Color[i].GetRed())) * (r - static_cast<double>(m_Color[i].GetRed()));
     match += (g - static_cast<double>(m_Color[i].GetGreen())) * (g - static_cast<double>(m_Color[i].GetGreen()));
     match += (b - static_cast<double>(m_Color[i].GetGreen())) * (b - static_cast<double>(m_Color[i].GetBlue()));
     if (i == 0 || match < bestMatch)

Modules/Core/Common/src/itkPlatformMultiThreaderPosix.cxx

@@ -191,8 +191,7 @@ PlatformMultiThreader::SpawnDispatchSingleMethodThread(PlatformMultiThreader::Wo
   pthread_attr_setscope(&attr, PTHREAD_SCOPE_SYSTEM);
 #endif
 
-  int threadError;
-  threadError = pthread_create(
+  int threadError = pthread_create(
     &threadHandle, &attr, reinterpret_cast<c_void_cast>(this->SingleMethodProxy), reinterpret_cast<void *>(threadInfo));
   if (threadError != 0)
   {

Modules/Core/Common/test/itkIteratorTests.cxx

@@ -124,8 +124,7 @@ itkIteratorTests(int, char *[])
   start = clock();
   itk::ImageRegionIterator<ScalarImage> it(o3, region);
 
-  unsigned short scalar;
-  scalar = 5;
+  unsigned short scalar = 5;
 
   i = 0;
   for (; !it.IsAtEnd(); ++it)

Modules/Core/ImageAdaptors/test/itkVectorImageTest.cxx

@@ -442,9 +442,9 @@ itkVectorImageTest(int, char * argv[])
         std::cerr << "[FAILED]" << std::endl;
         failed = true;
       }
-      bool adaptorTestResult;
-      adaptorTestResult = testVectorImageAdaptor<PixelType, Dimension, VectorImageToImageAdaptorType, VectorLength>(
-        vectorImageToImageAdaptor, vectorImage, region, componentToExtract);
+      bool adaptorTestResult =
+        testVectorImageAdaptor<PixelType, Dimension, VectorImageToImageAdaptorType, VectorLength>(
+          vectorImageToImageAdaptor, vectorImage, region, componentToExtract);
       if (adaptorTestResult)
       {
         failed = true;

Modules/Core/ImageFunction/include/itkBSplineInterpolateImageFunction.hxx

@@ -638,8 +638,7 @@ BSplineInterpolateImageFunction<TImageType, TCoordRep, TCoefficientType>::Evalua
       tempValue = 1.0;
       for (unsigned int n1 = 0; n1 < ImageDimension; ++n1)
       {
-        unsigned int indx;
-        indx = m_PointsToIndex[p][n1];
+        unsigned int indx = m_PointsToIndex[p][n1];
         coefficientIndex[n1] = (evaluateIndex)[n1][indx];
 
         if (n1 == n)

Modules/Core/Mesh/include/itkBinaryMask3DMeshSource.hxx

@@ -431,9 +431,7 @@ template <typename TInputImage, typename TOutputMesh>
 void
 BinaryMask3DMeshSource<TInputImage, TOutputMesh>::inverse(unsigned char * x)
 {
-  unsigned char tmp;
-
-  tmp = x[2];
+  unsigned char tmp = x[2];
   x[2] = x[1];
   x[1] = tmp;
 }

Modules/Core/Mesh/include/itkSimplexMeshAdaptTopologyFilter.hxx

@@ -225,9 +225,7 @@ SimplexMeshAdaptTopologyFilter<TInputMesh, TOutputMesh>::ComputeCellParameters()
       CovariantVectorType lineTwoFirstNormal = outputMesh->ComputeNormal(lineTwoFirstIdx);
       CovariantVectorType secondNewNormal = outputMesh->ComputeNormal(secondNewIndex);
 
-      double prod;
-
-      prod = dot_product(firstNewNormal.GetVnlVector(), lineOneFirstNormal.GetVnlVector());
+      double prod = dot_product(firstNewNormal.GetVnlVector(), lineOneFirstNormal.GetVnlVector());
 
       if (prod < 0)
       {

Modules/Core/Transform/test/itkBSplineDeformableTransformTest.cxx

@@ -687,9 +687,7 @@ itkBSplineDeformableTransformTest3()
 int
 itkBSplineDeformableTransformTest(int, char *[])
 {
-  bool failed;
-
-  failed = itkBSplineDeformableTransformTest1();
+  bool failed = itkBSplineDeformableTransformTest1();
   if (failed)
   {
     return EXIT_FAILURE;

Modules/Core/Transform/test/itkBSplineTransformTest.cxx

@@ -715,9 +715,7 @@ itkBSplineTransformTest3()
 int
 itkBSplineTransformTest(int, char *[])
 {
-  bool failed;
-
-  failed = itkBSplineTransformTest1();
+  bool failed = itkBSplineTransformTest1();
   if (failed)
   {
     return EXIT_FAILURE;

Modules/Core/Transform/test/itkTestTransformGetInverse.cxx

@@ -106,8 +106,7 @@ TransformTest()
 int
 itkTestTransformGetInverse(int, char *[])
 {
-  unsigned int errorCount;
-  errorCount = TransformTest<itk::AffineTransform<double, 3>>();
+  unsigned int errorCount = TransformTest<itk::AffineTransform<double, 3>>();
   errorCount += TransformTest<itk::AzimuthElevationToCartesianTransform<double, 3>>();
   errorCount += TransformTest<itk::BSplineTransform<double, 3>>();
   errorCount += TransformTest<itk::CenteredAffineTransform<double, 3>>();

Modules/Filtering/AntiAlias/test/itkAntiAliasBinaryImageFilterTest.cxx

@@ -40,13 +40,12 @@ constexpr int V_DEPTH = 64;
 float
 sphere(float x, float y, float z)
 {
-  float dis;
-  dis = (x - static_cast<float>(V_WIDTH) / 2.0) * (x - static_cast<float>(V_WIDTH) / 2.0) /
-          ((0.2f * V_WIDTH) * (0.2f * V_WIDTH)) +
-        (y - static_cast<float>(V_HEIGHT) / 2.0) * (y - static_cast<float>(V_HEIGHT) / 2.0) /
-          ((0.2f * V_HEIGHT) * (0.2f * V_HEIGHT)) +
-        (z - static_cast<float>(V_DEPTH) / 2.0) * (z - static_cast<float>(V_DEPTH) / 2.0) /
-          ((0.2f * V_DEPTH) * (0.2f * V_DEPTH));
+  float dis = (x - static_cast<float>(V_WIDTH) / 2.0) * (x - static_cast<float>(V_WIDTH) / 2.0) /
+                ((0.2f * V_WIDTH) * (0.2f * V_WIDTH)) +
+              (y - static_cast<float>(V_HEIGHT) / 2.0) * (y - static_cast<float>(V_HEIGHT) / 2.0) /
+                ((0.2f * V_HEIGHT) * (0.2f * V_HEIGHT)) +
+              (z - static_cast<float>(V_DEPTH) / 2.0) * (z - static_cast<float>(V_DEPTH) / 2.0) /
+                ((0.2f * V_DEPTH) * (0.2f * V_DEPTH));
   return (1.0f - dis);
 }
 

Modules/Filtering/ImageFeature/include/itkBilateralImageFilter.hxx

@@ -209,8 +209,7 @@ BilateralImageFilter<TInputImage, TOutputImage>::BeforeThreadedGenerateData()
   double rangeVariance = m_RangeSigma * m_RangeSigma;
 
   // denominator (normalization factor) for Gaussian used for range
-  double rangeGaussianDenom;
-  rangeGaussianDenom = m_RangeSigma * std::sqrt(2.0 * itk::Math::pi);
+  double rangeGaussianDenom = m_RangeSigma * std::sqrt(2.0 * itk::Math::pi);
 
   // Maximum delta for the dynamic range
   double tableDelta;

Modules/Filtering/ImageGrid/include/itkMirrorPadImageFilter.hxx

@@ -151,9 +151,7 @@ int
 MirrorPadImageFilter<TInputImage, TOutputImage>::FindRegionsInArea(long start, long end, long size, long offset)
 {
   int  result = 1;
-  long regionsize;
-
-  regionsize = end - start;
+  long regionsize = end - start;
   if (regionsize > 0) // Find out home many regions we have,
   {
     result = regionsize / size;

Modules/Filtering/ImageGrid/test/itkInterpolateImagePointsFilterTest.cxx

@@ -255,8 +255,7 @@ test3DInterpolateImagePointsFilter()
   using OutputIterator = itk::ImageRegionIterator<CoordImageType3D>;
   InputIterator  inIter(image, region);
   OutputIterator outIter(outputImage, region);
-  double         rmse;
-  rmse = 0.0;
+  double         rmse = 0.0;
   while (!outIter.IsAtEnd())
   {
     double temp = inIter.Get() - outIter.Get();

Modules/Filtering/LabelMap/test/itkLabelImageToLabelMapFilterTest.cxx

@@ -112,8 +112,7 @@ itkLabelImageToLabelMapFilterTest(int, char *[])
       IndexType index;
       index[0] = ctrI;
       index[1] = ctrJ;
-      unsigned long val;
-      val = map->GetPixel(index);
+      unsigned long val = map->GetPixel(index);
       std::cout << "Pixel[" << ctrI << ',' << ctrJ << "]: " << val << std::endl;
       if (((ctrI == 5) || (ctrJ == 5)) && (ctrI != 7) && (ctrJ != 7))
       {

Modules/Filtering/LabelMap/test/itkLabelMapToLabelImageFilterTest.cxx

@@ -82,8 +82,7 @@ itkLabelMapToLabelImageFilterTest(int argc, char * argv[])
       IndexType index;
       index[0] = ctrI;
       index[1] = ctrJ;
-      unsigned char val;
-      val = image->GetPixel(index);
+      unsigned char val = image->GetPixel(index);
       if ((ctrI == 5) || (ctrJ == 5))
       {
         itkAssertOrThrowMacro((val == 1), "Error in Label Image.");

Modules/Filtering/LabelMap/test/itkShiftLabelObjectTest.cxx

@@ -86,8 +86,7 @@ itkShiftLabelObjectTest(int argc, char * argv[])
       IndexType index;
       index[0] = ctrI;
       index[1] = ctrJ;
-      unsigned long val;
-      val = map->GetPixel(index);
+      unsigned long val = map->GetPixel(index);
       std::cout << "Pixel[" << ctrI << ',' << ctrJ << "]: " << val << std::endl;
       if ((ctrI == 5) || (ctrJ == 5))
       {

Modules/Filtering/Path/include/itkFourierSeriesPath.hxx

@@ -28,9 +28,7 @@ FourierSeriesPath<VDimension>::Evaluate(const InputType & input) const -> Output
 {
   InputType  theta;
   OutputType output;
-  int        numHarmonics;
-
-  numHarmonics = m_CosCoefficients->Size();
+  int        numHarmonics = m_CosCoefficients->Size();
   output.Fill(0);
 
   const double PI = 4.0 * std::atan(1.0);
@@ -57,9 +55,7 @@ FourierSeriesPath<VDimension>::EvaluateDerivative(const InputType & input) const
 {
   InputType  theta;
   VectorType output;
-  int        numHarmonics;
-
-  numHarmonics = m_CosCoefficients->Size();
+  int        numHarmonics = m_CosCoefficients->Size();
   output.Fill(0);
 
   const double PI = 4.0 * std::atan(1.0);

Modules/IO/NIFTI/test/itkNiftiImageIOTest.cxx

@@ -155,8 +155,7 @@ itkNiftiImageIOTest(int argc, char * argv[])
   }
   else // This is the mechanism for doing internal testing of all data types.
   {
-    int cur_return;
-    cur_return = MakeNiftiImage<char>(testFileName);
+    int cur_return = MakeNiftiImage<char>(testFileName);
     if (cur_return != 0)
     {
       std::cerr << "Error writing Nifti file type char" << std::endl;

Modules/Nonunit/IntegratedTest/test/itkMaximumDecisionRuleTest.cxx

@@ -35,16 +35,13 @@ itkMaximumDecisionRuleTest(int, char *[])
 
   MembershipVectorType membershipScoreVector;
 
-  double membershipScore1;
-  membershipScore1 = 0.1;
+  double membershipScore1 = 0.1;
   membershipScoreVector.push_back(membershipScore1);
 
-  double membershipScore2;
-  membershipScore2 = 0.5;
+  double membershipScore2 = 0.5;
   membershipScoreVector.push_back(membershipScore2);
 
-  double membershipScore3;
-  membershipScore3 = 1.9;
+  double membershipScore3 = 1.9;
   membershipScoreVector.push_back(membershipScore3);
 
   // the maximum score is the third component. The decision rule should

Modules/Nonunit/IntegratedTest/test/itkMaximumRatioDecisionRuleTest.cxx

@@ -35,21 +35,17 @@ itkMaximumRatioDecisionRuleTest(int, char *[])
 
   MembershipVectorType membershipScoreVector;
 
-  double membershipScore1;
-  membershipScore1 = 0.1;
+  double membershipScore1 = 0.1;
   membershipScoreVector.push_back(membershipScore1);
 
-  double membershipScore2;
-  membershipScore2 = 0.5;
+  double membershipScore2 = 0.5;
   membershipScoreVector.push_back(membershipScore2);
 
-  double membershipScore3;
-  membershipScore3 = 1.9;
+  double membershipScore3 = 1.9;
   membershipScoreVector.push_back(membershipScore3);
 
   // add discriminantscore with a value of zero
-  double membershipScore4;
-  membershipScore4 = 0.0;
+  double membershipScore4 = 0.0;
   membershipScoreVector.push_back(membershipScore4);
 
 

Modules/Nonunit/IntegratedTest/test/itkMinimumDecisionRuleTest.cxx

@@ -35,16 +35,13 @@ itkMinimumDecisionRuleTest(int, char *[])
 
   MembershipVectorType membershipScoreVector;
 
-  double membershipScore1;
-  membershipScore1 = 1.1;
+  double membershipScore1 = 1.1;
   membershipScoreVector.push_back(membershipScore1);
 
-  double membershipScore2;
-  membershipScore2 = 0.5;
+  double membershipScore2 = 0.5;
   membershipScoreVector.push_back(membershipScore2);
 
-  double membershipScore3;
-  membershipScore3 = 1.9;
+  double membershipScore3 = 1.9;
   membershipScoreVector.push_back(membershipScore3);
 
   // the minimum score is the third component. The decision rule should

Modules/Numerics/Optimizers/src/itkFRPROptimizer.cxx

@@ -132,8 +132,7 @@ FRPROptimizer::StartOptimization()
   {
     this->SetCurrentIteration(currentIteration);
 
-    double fret;
-    fret = fp;
+    double fret = fp;
     this->LineOptimize(&p, xi, &fret, tempCoord);
 
     if (2.0 * itk::Math::abs(fret - fp) <=

Modules/Numerics/Optimizers/src/itkPowellOptimizer.cxx

@@ -120,9 +120,7 @@ PowellOptimizer::SetCurrentLinePoint(double x, double fx)
 void
 PowellOptimizer::Swap(double * a, double * b) const
 {
-  double tf;
-
-  tf = *a;
+  double tf = *a;
   *a = *b;
   *b = tf;
 }
@@ -294,8 +292,7 @@ PowellOptimizer::BracketedLineOptimize(double           ax,
     /* Decide if the interpolation can be tried  */
     if (itk::Math::abs(x - w) >= tolerance1) /* If x and w are distinct      */
     {
-      double t;
-      t = (x - w) * (functionValueOfX - functionValueOfV);
+      double t = (x - w) * (functionValueOfX - functionValueOfV);
 
       double q; /* ted as p/q; division operation*/
       q = (x - v) * (functionValueOfX - functionValueOfW);
@@ -343,9 +340,7 @@ PowellOptimizer::BracketedLineOptimize(double           ax,
     /* and reduce the enveloping range  */
     double t = x + new_step; /* Tentative point for the min  */
 
-    double functionValueOft;
-
-    functionValueOft = this->GetLineValue(t, tempCoord);
+    double functionValueOft = this->GetLineValue(t, tempCoord);
 
     if (functionValueOft <= functionValueOfX)
     {

Modules/Numerics/Optimizersv4/include/itkPowellOptimizerv4.hxx

@@ -105,9 +105,7 @@ template <typename TInternalComputationValueType>
 void
 PowellOptimizerv4<TInternalComputationValueType>::Swap(double * a, double * b) const
 {
-  double tf;
-
-  tf = *a;
+  double tf = *a;
   *a = *b;
   *b = tf;
 }
@@ -289,8 +287,7 @@ PowellOptimizerv4<TInternalComputationValueType>::BracketedLineOptimize(double
     /* Decide if the interpolation can be tried  */
     if (itk::Math::abs(x - w) >= tolerance1) /* If x and w are distinct      */
     {
-      double t;
-      t = (x - w) * (functionValueOfX - functionValueOfV);
+      double t = (x - w) * (functionValueOfX - functionValueOfV);
 
       double q; /* ted as p/q; division operation*/
       q = (x - v) * (functionValueOfX - functionValueOfW);
@@ -338,9 +335,7 @@ PowellOptimizerv4<TInternalComputationValueType>::BracketedLineOptimize(double
     /* and reduce the enveloping range  */
     double t = x + new_step; /* Tentative point for the min  */
 
-    double functionValueOft;
-
-    functionValueOft = this->GetLineValue(t, tempCoord);
+    double functionValueOft = this->GetLineValue(t, tempCoord);
 
     if (functionValueOft <= functionValueOfX)
     {

Modules/Numerics/Statistics/include/itkImageClassifierFilter.hxx

@@ -169,8 +169,7 @@ ImageClassifierFilter<TSample, TInputImage, TOutputImage>::GenerateData()
       discriminantScores[i] = membershipFunctionsWeightsArray[i] * membershipFunctions[i]->Evaluate(measurements);
     }
 
-    unsigned int classIndex;
-    classIndex = static_cast<unsigned int>(m_DecisionRule->Evaluate(discriminantScores));
+    unsigned int classIndex = static_cast<unsigned int>(m_DecisionRule->Evaluate(discriminantScores));
 
     auto value = static_cast<OutputPixelType>(classLabels[classIndex]);
     outItr.Set(value);

Modules/Numerics/Statistics/include/itkMahalanobisDistanceMetric.hxx

@@ -160,8 +160,7 @@ MahalanobisDistanceMetric<TVector>::Evaluate(const MeasurementVectorType & measu
   tempMat = tempVec * m_InverseCovariance;
 
   // Compute |y - mean | * inverse(cov) * |y - mean|^T
-  double temp;
-  temp = std::sqrt(dot_product(tempMat.as_ref(), tempVec.as_ref()));
+  double temp = std::sqrt(dot_product(tempMat.as_ref(), tempVec.as_ref()));
 
   return temp;
 }
@@ -193,8 +192,7 @@ MahalanobisDistanceMetric<TVector>::Evaluate(const MeasurementVectorType & x1, c
   tempMat = tempVec * m_InverseCovariance;
 
   // Compute |x1 - x2 | * inverse(cov) * |x1 - x2|^T
-  double temp;
-  temp = std::sqrt(dot_product(tempMat.as_ref(), tempVec.as_ref()));
+  double temp = std::sqrt(dot_product(tempMat.as_ref(), tempVec.as_ref()));
 
   return temp;
 }