### Question:
ConvolutionKernels { public static FloatProcessor genGradientY(int xSize, int ySize) { assert xSize>=0; assert ySize>0; int width = (2*xSize+1); int height = (2*ySize+1); float [] kernel = new float[width*height]; for (int j=-ySize;j<=ySize;j++){ for (int i=-xSize;i<=xSize;i++){ if (j<0) { kernel[(ySize+j)*width+(xSize+i)] = -1; } if (j>0) { kernel[(ySize+j)*width+(xSize+i)] = 1; } } } return new FloatProcessor(width, height, kernel); }  static FloatProcessor genGaussianKernel(double sigma); static FloatProcessor genGaussianERFKernel(double sigma); static FloatProcessor genGaussianERFKernel(double sigma, double xShift, double yShift); static FloatProcessor genGaussianKernel(double sigma, float xDelta, float yDelta); static FloatProcessor genLaplacianOfGaussianKernel(double sigma); static FloatProcessor genDifferenceOfGaussiansKernel(double sigmaSmall, double sigmaBig); static FloatProcessor genSmooth(int xSize, int ySize); static FloatProcessor genIntegration(int xSize, int ySize); static FloatProcessor genCircularIntegration(double radius); static FloatProcessor genCircularSmooth(double radius); static FloatProcessor genLaplacian1(); static FloatProcessor genLaplacian2(); static FloatProcessor genLaplacian3(); static FloatProcessor genExtendedLaplacian(); static FloatProcessor genExtendedLaplacian2(); static FloatProcessor genGradientX(int xSize, int ySize); static FloatProcessor genGradientY(int xSize, int ySize); static ImageStack gen3DTemporalFrameSubtraction(int xSize, int ySize, int innerTRadius, int outerTDelta); static ImageStack gen3DSmooth(); static ImageStack gen3DSmooth(int xSize, int ySize, int tSize); static void normalizeToOne(float [] pixels); static void normalizeToOne(ImageStack ims); static void normalizeToOne(FloatProcessor fp); static boolean isNormalizedToOne(float [] pixels, double allowedError); static boolean isNormalizedToOne(ImageStack ims, double allowedError); static boolean isNormalizedToOne(FloatProcessor fp, double allowedError); static boolean isNormalizedToZero(float [] pixels, double allowedError); static boolean isNormalizedToZero(ImageStack ims, double allowedError); static boolean isNormalizedToZero(FloatProcessor fp, double allowedError);  }### Answer:
@Test public void testGenGradientY() throws Exception { assertTrue (ConvolutionKernels.isNormalizedToZero(ConvolutionKernels.genGradientY(5,5), 0.05f)); }