ENH: Increase coverage for miscellaneous classes

Increase coverage for miscellaneous classes:
- Exercise the basic object methods using the
  `ITK_EXERCISE_BASIC_OBJECT_METHODS` macro.
- Test the Set/Get methods using the `ITK_TEST_SET_GET_VALUE` macro.
- Use other testing macros to check the expected value of a number of
  ivars and method return values.
- Test exceptions using the `ITK_TRY_EXPECT_EXCEPTION` macro.
- Remove explicit calls to the `Print` method and rely on the basic
  method exercising macro call.

Modules/Core/ImageFunction/test/itkRayCastInterpolateImageFunctionTest.cxx

@@ -124,7 +124,17 @@ itkRayCastInterpolateImageFunctionTest(int itkNotUsed(argc), char * itkNotUsed(a
   ITK_TEST_SET_GET_VALUE(threshold, interp->GetThreshold());
 
   /* Evaluate the function */
-  double    integral;
+  double integral;
+
+
+  // Evaluate the ray casting function at the same point as the focal point:
+  //   - Allows to increase coverage.
+  //   - Makes the ray be invalid.
+  //   - Sets the traversal direction to TraversalDirectionEnum::UNDEFINED_DIRECTION
+  //   - The integral should equal to 0.
+  integral = interp->Evaluate(focus);
+  ITK_TEST_EXPECT_TRUE(itk::Math::FloatAlmostEqual(integral, 0.0));
+
   PointType query;
   query[0] = 15.;
   query[1] = 15.;

Modules/Numerics/Statistics/test/itkImageToHistogramFilterTest.cxx

@@ -84,8 +84,11 @@ itkImageToHistogramFilterTest(int, char *[])
   itk::SimpleFilterWatcher watcher(filter, "filter");
 
   ITK_EXERCISE_BASIC_OBJECT_METHODS(filter, ImageToHistogramFilter, ImageSink);
-  // Exercise the method NameOfClass();
-  std::cout << filter->GetNameOfClass() << std::endl;
+
+
+  unsigned int numberOfStreamDivisions = 1;
+  filter->SetNumberOfStreamDivisions(numberOfStreamDivisions);
+  ITK_TEST_SET_GET_VALUE(numberOfStreamDivisions, filter->GetNumberOfStreamDivisions());
 
   // Testing the settings of the BinMaximum and BinMinimum methods.
   HistogramMeasurementVectorType histogramBinMinimum1(MeasurementVectorSize);

Modules/Segmentation/LabelVoting/test/itkMultiLabelSTAPLEImageFilterTest.cxx

@@ -16,6 +16,7 @@
  *
  *=========================================================================*/
 #include "itkMultiLabelSTAPLEImageFilter.h"
+#include "itkTestingMacros.h"
 
 int
 itkMultiLabelSTAPLEImageFilterTest(int, char *[])
@@ -118,6 +119,8 @@ itkMultiLabelSTAPLEImageFilterTest(int, char *[])
   // Create an LabelVoting Filter
   myFilterTypePointer filter = myFilterType::New();
 
+  ITK_EXERCISE_BASIC_OBJECT_METHODS(filter, MultiLabelSTAPLEImageFilter, ImageToImageFilter);
+
   // Get the Smart Pointer to the Filter Output
   myImageTypePointer outputImage = filter->GetOutput();
 
@@ -127,19 +130,54 @@ itkMultiLabelSTAPLEImageFilterTest(int, char *[])
   filter->SetInput(0, inputImageA);
   filter->SetInput(1, inputImageB);
 
+  ITK_TEST_EXPECT_TRUE(!filter->GetHasMaximumNumberOfIterations());
+
+  unsigned int maximumNumberOfIterations = 0;
+  filter->SetMaximumNumberOfIterations(maximumNumberOfIterations);
+  ITK_TEST_SET_GET_VALUE(maximumNumberOfIterations, filter->GetMaximumNumberOfIterations());
+
+  ITK_TEST_EXPECT_TRUE(filter->GetHasMaximumNumberOfIterations());
+
+  ITK_TEST_EXPECT_TRUE(!filter->GetHasLabelForUndecidedPixels());
+
+  typename myFilterType::WeightsType terminationUpdateThreshold = 1e-5;
+  filter->SetTerminationUpdateThreshold(terminationUpdateThreshold);
+  ITK_TEST_SET_GET_VALUE(terminationUpdateThreshold, filter->GetTerminationUpdateThreshold());
+
   // Set label for undecided pixels
-  filter->SetLabelForUndecidedPixels(255);
+  typename myFilterType::OutputPixelType labelForUndecidedPixels = 255;
+  filter->SetLabelForUndecidedPixels(labelForUndecidedPixels);
+  ITK_TEST_SET_GET_VALUE(labelForUndecidedPixels, filter->GetLabelForUndecidedPixels());
+
+  ITK_TEST_EXPECT_TRUE(filter->GetHasLabelForUndecidedPixels());
+
+  ITK_TEST_EXPECT_TRUE(!filter->GetHasPriorProbabilities());
+
+  typename myFilterType::PriorProbabilitiesType::ValueType priorProbabilitiesVal(0.0);
+  typename myFilterType::PriorProbabilitiesType            priorProbabilities(1);
+  priorProbabilities.Fill(priorProbabilitiesVal);
+  filter->SetPriorProbabilities(priorProbabilities);
+  ITK_TEST_SET_GET_VALUE(priorProbabilities, filter->GetPriorProbabilities());
+
+  ITK_TEST_EXPECT_TRUE(filter->GetHasPriorProbabilities());
+
+  ITK_TRY_EXPECT_EXCEPTION(filter->Update());
+
+
+  filter->UnsetPriorProbabilities();
 
   // Execute the filter
-  filter->Update();
+  ITK_TRY_EXPECT_NO_EXCEPTION(filter->Update());
+
+  std::cout << "ElapsedNumberOfIterations: " << filter->GetElapsedNumberOfIterations() << std::endl;
 
   // compare to correct results
   it = myIteratorType(outputImage, outputImage->GetBufferedRegion());
   for (unsigned int i = 0; i < 8; ++i, ++it)
   {
     if (combinationABundecided255[i] != it.Get())
     {
-      std::cout << "Incorrect result using images A,B and undecided=255: "
+      std::cout << "Incorrect result using images A,B and undecided=" << labelForUndecidedPixels << ": "
                 << "i = " << i << ", correct = " << combinationABundecided255[i] << ", got = " << it.Get() << "\n";
       return EXIT_FAILURE;
     }
@@ -185,7 +223,6 @@ itkMultiLabelSTAPLEImageFilterTest(int, char *[])
     }
   }
 
-  filter->Print(std::cout, 3);
 
   std::cout << "Prior probabilities: " << filter->GetPriorProbabilities() << std::endl;
   std::cout << "Confusion matrix 0 " << std::endl << filter->GetConfusionMatrix(0) << std::endl;