public void testSensitivityMatrixCalculationFromSucceedingLayer()
{
Matrix weightMatrix1 = new Matrix(2, 1);
weightMatrix1.Set(0, 0, -0.27);
weightMatrix1.Set(1, 0, -0.41);
Vector biasVector1 = new Vector(2);
biasVector1.SetValue(0, -0.48);
biasVector1.SetValue(1, -0.13);
Layer layer1 = new Layer(weightMatrix1, biasVector1,
new LogSigActivationFunction());
LayerSensitivity layer1Sensitivity = new LayerSensitivity(layer1);
Vector inputVector1 = new Vector(1);
inputVector1.SetValue(0, 1);
layer1.FeedForward(inputVector1);
Matrix weightMatrix2 = new Matrix(1, 2);
weightMatrix2.Set(0, 0, 0.09);
weightMatrix2.Set(0, 1, -0.17);
Vector biasVector2 = new Vector(1);
biasVector2.SetValue(0, 0.48);
Layer layer2 = new Layer(weightMatrix2, biasVector2,
new PureLinearActivationFunction());
Vector inputVector2 = layer1.GetLastActivationValues();
layer2.FeedForward(inputVector2);
Vector errorVector = new Vector(1);
errorVector.SetValue(0, 1.261);
LayerSensitivity layer2Sensitivity = new LayerSensitivity(layer2);
layer2Sensitivity.SensitivityMatrixFromErrorMatrix(errorVector);
layer1Sensitivity
.SensitivityMatrixFromSucceedingLayer(layer2Sensitivity);
Matrix sensitivityMatrix = layer1Sensitivity.GetSensitivityMatrix();
Assert.AreEqual(2, sensitivityMatrix.GetRowDimension());
Assert.AreEqual(1, sensitivityMatrix.GetColumnDimension());
Assert.AreEqual(-0.0495, sensitivityMatrix.Get(0, 0), 0.001);
Assert.AreEqual(0.0997, sensitivityMatrix.Get(1, 0), 0.001);
}
