public void CompareWeightsReturnsExpectedResultOfDifferent()
{
// Arrange
const int nInputs = 9;
const int nOutputs = 1;
int[] hiddenLayers = new int[] { 9 };
Dna dna1 = Dna.GenerateRandomDnaEncoding(nInputs, hiddenLayers, nOutputs, ActivationType.LeakyRelu, true);
dna1.WeightsAndBiases.Should().HaveCount(100);
dna1.WeightsAndBiases.Clear();
dna1.WeightsAndBiases.AddRange(Enumerable.Repeat(1.00, 100));
Dna dna2 = Dna.Clone(dna1);
dna1.WeightsAndBiases.Should().Equal(dna2.WeightsAndBiases);
dna2.WeightsAndBiases[2] = -49.00; // aggregate absolute weight difference of dna2 vs dna1 should now be 50
dna1.WeightsAndBiases.Should().NotEqual(dna2.WeightsAndBiases);
// Act
var comparisonResult = DnaUtils.CompareWeights(dna1, dna2);
// Assert
float percentWeightDiff = comparisonResult.Item1;
double percentWeightValueDiff = comparisonResult.Item2;
percentWeightDiff.Should().Be(0.01f); // ie. 1% of weights differ in value
percentWeightValueDiff.Should().Be(0.5f); // ie. total weight values of dna2 differ by 50% (NOT 50% bigger)
}
public void CompareWeightsReturnsExpectedResultOfIdentical()
{
// Arrange
const int nInputs = 20;
const int nOutputs = 8;
int[] hiddenLayers = new int[] { 30, 4, 12 };
Dna dna1 = Dna.GenerateRandomDnaEncoding(nInputs, hiddenLayers, nOutputs, ActivationType.LeakyRelu, true);
Dna dna2 = Dna.Clone(dna1);
// Act
var comparisonResult = DnaUtils.CompareWeights(dna1, dna2);
// Assert
float percentWeightDiff = comparisonResult.Item1;
double percentWeightValueDiff = comparisonResult.Item2;
percentWeightDiff.Should().Be(0);
percentWeightValueDiff.Should().Be(0);
}
