/// <summary>
/// Tests EP and BP gate enter ops for Bernoulli random variable for correctness given message parameters.
/// </summary>
/// <param name="valueProbTrue">Probability of being true for the variable entering the gate.</param>
/// <param name="enterOneProbTrue">Probability of being true for the variable approximation inside the gate when the selector is true.</param>
/// <param name="selectorProbTrue">Probability of being true for the selector variable.</param>
private void DoBernoulliEnterTest(double valueProbTrue, double enterOneProbTrue, double selectorProbTrue)
{
var value = new Bernoulli(valueProbTrue);
var enterOne = new Bernoulli(enterOneProbTrue);
var selector = new Bernoulli(selectorProbTrue);
var selectorInverse = new Bernoulli(selector.GetProbFalse());
var discreteSelector = new Discrete(selector.GetProbTrue(), selector.GetProbFalse());
var discreteSelectorInverse = new Discrete(selector.GetProbFalse(), selector.GetProbTrue());
var cases = new[] { Bernoulli.FromLogOdds(selector.GetLogProbTrue()), Bernoulli.FromLogOdds(selector.GetLogProbFalse()) };
// Compute expected message
double logShift = enterOne.GetLogNormalizer() + value.GetLogNormalizer() - (value * enterOne).GetLogNormalizer();
double expectedProbTrue = selector.GetProbFalse() + (selector.GetProbTrue() * enterOne.GetProbTrue() * Math.Exp(logShift));
double expectedProbFalse = selector.GetProbFalse() + (selector.GetProbTrue() * enterOne.GetProbFalse() * Math.Exp(logShift));
double expectedNormalizer = expectedProbTrue + expectedProbFalse;
expectedProbTrue /= expectedNormalizer;
Bernoulli value1, value2;
// Enter partial (bernoulli selector, first case)
value1 = GateEnterPartialOp <bool> .ValueAverageConditional(
new[] { enterOne }, selector, value, new[] { 0 }, new Bernoulli());
value2 = BeliefPropagationGateEnterPartialOp.ValueAverageConditional(
new[] { enterOne }, selector, value, new[] { 0 }, new Bernoulli());
Assert.Equal(expectedProbTrue, value1.GetProbTrue(), 1e-4);
Assert.Equal(expectedProbTrue, value2.GetProbTrue(), 1e-4);
// Enter partial (bernoulli selector, second case)
value1 = GateEnterPartialOp <bool> .ValueAverageConditional(
new[] { enterOne }, selectorInverse, value, new[] { 1 }, new Bernoulli());
value2 = BeliefPropagationGateEnterPartialOp.ValueAverageConditional(
new[] { enterOne }, selectorInverse, value, new[] { 1 }, new Bernoulli());
Assert.Equal(expectedProbTrue, value1.GetProbTrue(), 1e-4);
Assert.Equal(expectedProbTrue, value2.GetProbTrue(), 1e-4);
// Enter partial (bernoulli selector, both cases)
value1 = GateEnterPartialOp <bool> .ValueAverageConditional(
new[] { enterOne, Bernoulli.Uniform() }, selector, value, new[] { 0, 1 }, new Bernoulli());
value2 = BeliefPropagationGateEnterPartialOp.ValueAverageConditional(
new[] { enterOne, Bernoulli.Uniform() }, selector, value, new[] { 0, 1 }, new Bernoulli());
Assert.Equal(expectedProbTrue, value1.GetProbTrue(), 1e-4);
Assert.Equal(expectedProbTrue, value2.GetProbTrue(), 1e-4);
// Enter partial (discrete selector, first case)
value1 = GateEnterPartialOp <bool> .ValueAverageConditional(
new[] { enterOne }, discreteSelector, value, new[] { 0 }, new Bernoulli());
value2 = BeliefPropagationGateEnterPartialOp.ValueAverageConditional(
new[] { enterOne }, discreteSelector, value, new[] { 0 }, new Bernoulli());
Assert.Equal(expectedProbTrue, value1.GetProbTrue(), 1e-4);
Assert.Equal(expectedProbTrue, value2.GetProbTrue(), 1e-4);
// Enter partial (discrete selector, second case)
value1 = GateEnterPartialOp <bool> .ValueAverageConditional(
new[] { enterOne }, discreteSelectorInverse, value, new[] { 1 }, new Bernoulli());
value2 = BeliefPropagationGateEnterPartialOp.ValueAverageConditional(
new[] { enterOne }, discreteSelectorInverse, value, new[] { 1 }, new Bernoulli());
Assert.Equal(expectedProbTrue, value1.GetProbTrue(), 1e-4);
Assert.Equal(expectedProbTrue, value2.GetProbTrue(), 1e-4);
// Enter partial (discrete selector, both cases)
value1 = GateEnterPartialOp <bool> .ValueAverageConditional(
new[] { enterOne, Bernoulli.Uniform() }, discreteSelector, value, new[] { 0, 1 }, new Bernoulli());
value2 = BeliefPropagationGateEnterPartialOp.ValueAverageConditional(
new[] { enterOne, Bernoulli.Uniform() }, discreteSelector, value, new[] { 0, 1 }, new Bernoulli());
Assert.Equal(expectedProbTrue, value1.GetProbTrue(), 1e-4);
Assert.Equal(expectedProbTrue, value2.GetProbTrue(), 1e-4);
// Enter one (discrete selector, first case)
value1 = GateEnterOneOp <bool> .ValueAverageConditional(
enterOne, discreteSelector, value, 0, new Bernoulli());
value2 = BeliefPropagationGateEnterOneOp.ValueAverageConditional(
enterOne, discreteSelector, value, 0, new Bernoulli());
Assert.Equal(expectedProbTrue, value1.GetProbTrue(), 1e-4);
Assert.Equal(expectedProbTrue, value2.GetProbTrue(), 1e-4);
// Enter one (discrete selector, second case)
value1 = GateEnterOneOp <bool> .ValueAverageConditional(
enterOne, discreteSelectorInverse, value, 1, new Bernoulli());
value2 = BeliefPropagationGateEnterOneOp.ValueAverageConditional(
enterOne, discreteSelectorInverse, value, 1, new Bernoulli());
Assert.Equal(expectedProbTrue, value1.GetProbTrue(), 1e-4);
Assert.Equal(expectedProbTrue, value2.GetProbTrue(), 1e-4);
// Enter partial two (first case)
value1 = GateEnterPartialTwoOp.ValueAverageConditional(
new[] { enterOne }, cases[0], cases[1], value, new[] { 0 }, new Bernoulli());
value2 = BeliefPropagationGateEnterPartialTwoOp.ValueAverageConditional(
new[] { enterOne }, cases[0], cases[1], value, new[] { 0 }, new Bernoulli());
Assert.Equal(expectedProbTrue, value1.GetProbTrue(), 1e-4);
Assert.Equal(expectedProbTrue, value2.GetProbTrue(), 1e-4);
// Enter partial two (second case)
value1 = GateEnterPartialTwoOp.ValueAverageConditional(
new[] { enterOne }, cases[1], cases[0], value, new[] { 1 }, new Bernoulli());
value2 = BeliefPropagationGateEnterPartialTwoOp.ValueAverageConditional(
new[] { enterOne }, cases[1], cases[0], value, new[] { 1 }, new Bernoulli());
Assert.Equal(expectedProbTrue, value1.GetProbTrue(), 1e-4);
Assert.Equal(expectedProbTrue, value2.GetProbTrue(), 1e-4);
// Enter partial two (both cases)
value1 = GateEnterPartialTwoOp.ValueAverageConditional(
new[] { enterOne, Bernoulli.Uniform() }, cases[0], cases[1], value, new[] { 0, 1 }, new Bernoulli());
value2 = BeliefPropagationGateEnterPartialTwoOp.ValueAverageConditional(
new[] { enterOne, Bernoulli.Uniform() }, cases[0], cases[1], value, new[] { 0, 1 }, new Bernoulli());
Assert.Equal(expectedProbTrue, value1.GetProbTrue(), 1e-4);
Assert.Equal(expectedProbTrue, value2.GetProbTrue(), 1e-4);
// Enter (discrete selector)
value1 = GateEnterOp <bool> .ValueAverageConditional(
new[] { enterOne, Bernoulli.Uniform() }, discreteSelector, value, new Bernoulli());
value2 = BeliefPropagationGateEnterOp.ValueAverageConditional(
new[] { enterOne, Bernoulli.Uniform() }, discreteSelector, value, new Bernoulli());
Assert.Equal(expectedProbTrue, value1.GetProbTrue(), 1e-4);
Assert.Equal(expectedProbTrue, value2.GetProbTrue(), 1e-4);
}
/// <summary>Computations that depend on the observed value of numberOfIterationsDecreased and vGamma__1 and vGaussian__1 and vDirichlet1</summary>
/// <param name="numberOfIterations">The number of times to iterate each loop</param>
private void Changed_numberOfIterationsDecreased_vGamma__1_vGaussian__1_vDirichlet1(int numberOfIterations)
{
if (this.Changed_numberOfIterationsDecreased_vGamma__1_vGaussian__1_vDirichlet1_iterationsDone == numberOfIterations)
{
return;
}
// Create array for 'vdouble__3_marginal' Forwards messages.
this.vdouble__3_marginal_F = new DistributionStructArray <Gaussian, double>(2);
for (int index2 = 0; index2 < 2; index2++)
{
this.vdouble__3_marginal_F[index2] = Gaussian.Uniform();
}
this.vVector1_marginal_F = ArrayHelper.MakeUniform <Dirichlet>(this.VDirichlet1);
Discrete vint9_F = ArrayHelper.MakeUniform <Discrete>(Discrete.Uniform(2));
Discrete[] vint9_selector_uses_B = default(Discrete[]);
// Create array for 'vint9_selector_uses' Backwards messages.
vint9_selector_uses_B = new Discrete[3];
for (int _ind = 0; _ind < 3; _ind++)
{
vint9_selector_uses_B[_ind] = ArrayHelper.MakeUniform <Discrete>(Discrete.Uniform(2));
}
DistributionStructArray <Bernoulli, bool>[] vint9_selector_cases_uses_B = default(DistributionStructArray <Bernoulli, bool>[]);
// Create array for 'vint9_selector_cases_uses' Backwards messages.
vint9_selector_cases_uses_B = new DistributionStructArray <Bernoulli, bool> [2];
for (int _ind = 0; _ind < 2; _ind++)
{
// Create array for 'vint9_selector_cases_uses' Backwards messages.
vint9_selector_cases_uses_B[_ind] = new DistributionStructArray <Bernoulli, bool>(2);
for (int _iv = 0; _iv < 2; _iv++)
{
vint9_selector_cases_uses_B[_ind][_iv] = Bernoulli.Uniform();
}
}
DistributionStructArray <Bernoulli, bool>[] vint9_selector_cases_depth1_uses_B = default(DistributionStructArray <Bernoulli, bool>[]);
// Create array for 'vint9_selector_cases_depth1_uses' Backwards messages.
vint9_selector_cases_depth1_uses_B = new DistributionStructArray <Bernoulli, bool> [2];
for (int _iv = 0; _iv < 2; _iv++)
{
// Create array for 'vint9_selector_cases_depth1_uses' Backwards messages.
vint9_selector_cases_depth1_uses_B[_iv] = new DistributionStructArray <Bernoulli, bool>(10);
for (int _ind = 0; _ind < 10; _ind++)
{
vint9_selector_cases_depth1_uses_B[_iv][_ind] = Bernoulli.Uniform();
}
}
// Create array for replicates of 'vdouble17__index2__F'
DistributionStructArray <Gaussian, double> vdouble17__index2__F = new DistributionStructArray <Gaussian, double>(2);
for (int index2 = 0; index2 < 2; index2++)
{
vdouble17__index2__F[index2] = Gaussian.Uniform();
}
// Message from use of 'vdouble17'
Gaussian vdouble17_use_B = Gaussian.Uniform();
// Message to marginal of 'vdouble17__index2_'
// Create array for replicates of 'vdouble17__index2__marginal_F'
DistributionStructArray <Gaussian, double> vdouble17__index2__marginal_F = new DistributionStructArray <Gaussian, double>(2);
for (int index2 = 0; index2 < 2; index2++)
{
vdouble17__index2__marginal_F[index2] = Gaussian.Uniform();
}
// Create array for replicates of 'vdouble__4_index2__B'
DistributionStructArray <Gamma, double> vdouble__4_index2__B = new DistributionStructArray <Gamma, double>(2);
for (int index2 = 0; index2 < 2; index2++)
{
vdouble__4_index2__B[index2] = Gamma.Uniform();
}
// Create array for 'vdouble__4_marginal' Forwards messages.
this.vdouble__4_marginal_F = new DistributionStructArray <Gamma, double>(2);
for (int index2 = 0; index2 < 2; index2++)
{
this.vdouble__4_marginal_F[index2] = Gamma.Uniform();
}
DistributionStructArray <Bernoulli, bool> vint9_selector_cases_depth1_B = default(DistributionStructArray <Bernoulli, bool>);
// Create array for 'vint9_selector_cases_depth1' Backwards messages.
vint9_selector_cases_depth1_B = new DistributionStructArray <Bernoulli, bool>(2);
for (int _iv = 0; _iv < 2; _iv++)
{
vint9_selector_cases_depth1_B[_iv] = Bernoulli.Uniform();
}
DistributionStructArray <Bernoulli, bool> vint9_selector_cases_B = default(DistributionStructArray <Bernoulli, bool>);
// Create array for 'vint9_selector_cases' Backwards messages.
vint9_selector_cases_B = new DistributionStructArray <Bernoulli, bool>(2);
for (int _iv = 0; _iv < 2; _iv++)
{
vint9_selector_cases_B[_iv] = Bernoulli.Uniform();
}
this.vint9_marginal_F = ArrayHelper.MakeUniform <Discrete>(Discrete.Uniform(2));
// Create array for replicates of 'vdouble__3_index2__B'
DistributionStructArray <Gaussian, double> vdouble__3_index2__B = new DistributionStructArray <Gaussian, double>(2);
for (int index2 = 0; index2 < 2; index2++)
{
vdouble__3_index2__B[index2] = Gaussian.Uniform();
// Message to 'vdouble__3_marginal' from Variable factor
this.vdouble__3_marginal_F[index2] = VariableVmpOp.MarginalAverageLogarithm <Gaussian>(this.vdouble__3_use_B[index2], this.VGaussian__1[index2], this.vdouble__3_marginal_F[index2]);
// Message to 'vdouble__4_marginal' from Variable factor
this.vdouble__4_marginal_F[index2] = VariableVmpOp.MarginalAverageLogarithm <Gamma>(this.vdouble__4_use_B[index2], this.VGamma__1[index2], this.vdouble__4_marginal_F[index2]);
// Message to 'vdouble17__index2_' from Gaussian factor
vdouble17__index2__F[index2] = GaussianOp.SampleAverageLogarithm(this.vdouble__3_marginal_F[index2], this.vdouble__4_marginal_F[index2]);
// Message to 'vdouble17__index2__marginal' from Variable factor
vdouble17__index2__marginal_F[index2] = VariableVmpOp.MarginalAverageLogarithm <Gaussian>(vdouble17_use_B, vdouble17__index2__F[index2], vdouble17__index2__marginal_F[index2]);
}
// Message to 'vVector1_marginal' from Variable factor
this.vVector1_marginal_F = VariableVmpOp.MarginalAverageLogarithm <Dirichlet>(this.vVector1_use_B, this.VDirichlet1, this.vVector1_marginal_F);
// Message to 'vint9' from Discrete factor
vint9_F = DiscreteFromDirichletOp.SampleAverageLogarithm(this.vVector1_marginal_F, vint9_F);
// Message to 'vint9_marginal' from Variable factor
this.vint9_marginal_F = VariableVmpOp.MarginalAverageLogarithm <Discrete>(this.vint9_selector_B, vint9_F, this.vint9_marginal_F);
for (int iteration = this.Changed_numberOfIterationsDecreased_vGamma__1_vGaussian__1_vDirichlet1_iterationsDone; iteration < numberOfIterations; iteration++)
{
for (int index2 = 0; index2 < 2; index2++)
{
// Message to 'vdouble__4_marginal' from Variable factor
this.vdouble__4_marginal_F[index2] = VariableVmpOp.MarginalAverageLogarithm <Gamma>(this.vdouble__4_use_B[index2], this.VGamma__1[index2], this.vdouble__4_marginal_F[index2]);
// Message to 'vdouble__3_index2_' from Gaussian factor
vdouble__3_index2__B[index2] = GaussianOp.MeanAverageLogarithm(vdouble17__index2__marginal_F[index2], this.vdouble__4_marginal_F[index2]);
// Message to 'vdouble__3_use' from EnterOne factor
this.vdouble__3_use_B[index2] = GateEnterOneOp <double> .ValueAverageLogarithm <Gaussian>(vdouble__3_index2__B[index2], this.vint9_marginal_F, index2, this.vdouble__3_use_B[index2]);
// Message to 'vdouble__3_marginal' from Variable factor
this.vdouble__3_marginal_F[index2] = VariableVmpOp.MarginalAverageLogarithm <Gaussian>(this.vdouble__3_use_B[index2], this.VGaussian__1[index2], this.vdouble__3_marginal_F[index2]);
// Message to 'vdouble17__index2_' from Gaussian factor
vdouble17__index2__F[index2] = GaussianOp.SampleAverageLogarithm(this.vdouble__3_marginal_F[index2], this.vdouble__4_marginal_F[index2]);
// Message to 'vdouble17__index2__marginal' from Variable factor
vdouble17__index2__marginal_F[index2] = VariableVmpOp.MarginalAverageLogarithm <Gaussian>(vdouble17_use_B, vdouble17__index2__F[index2], vdouble17__index2__marginal_F[index2]);
// Message to 'vint9_selector_cases_depth1_uses' from Variable factor
vint9_selector_cases_depth1_uses_B[index2][8] = Bernoulli.FromLogOdds(VariableVmpOp.AverageLogFactor <Gaussian>(vdouble17__index2__marginal_F[index2]));
// Message to 'vint9_selector_cases_depth1_uses' from Gaussian factor
vint9_selector_cases_depth1_uses_B[index2][7] = Bernoulli.FromLogOdds(GaussianOp.AverageLogFactor(vdouble17__index2__marginal_F[index2], this.vdouble__3_marginal_F[index2], this.vdouble__4_marginal_F[index2]));
}
for (int _iv = 0; _iv < 2; _iv++)
{
// Message to 'vint9_selector_cases_depth1' from Replicate factor
vint9_selector_cases_depth1_B[_iv] = ReplicateOp.DefAverageLogarithm <Bernoulli>(vint9_selector_cases_depth1_uses_B[_iv], vint9_selector_cases_depth1_B[_iv]);
// Message to 'vint9_selector_cases_uses' from Copy factor
vint9_selector_cases_uses_B[0][_iv] = ArrayHelper.SetTo <Bernoulli>(vint9_selector_cases_uses_B[0][_iv], vint9_selector_cases_depth1_B[_iv]);
}
// Message to 'vint9_selector_cases' from Replicate factor
vint9_selector_cases_B = ReplicateOp.DefAverageLogarithm <DistributionStructArray <Bernoulli, bool> >(vint9_selector_cases_uses_B, vint9_selector_cases_B);
// Message to 'vint9_selector_uses' from CasesInt factor
vint9_selector_uses_B[0] = IntCasesOp.IAverageLogarithm(vint9_selector_cases_B, vint9_selector_uses_B[0]);
// Message to 'vint9_selector' from Replicate factor
this.vint9_selector_B = ReplicateOp.DefAverageLogarithm <Discrete>(vint9_selector_uses_B, this.vint9_selector_B);
// Message to 'vVector1_marginal' from Variable factor
this.vVector1_marginal_F = VariableVmpOp.MarginalAverageLogarithm <Dirichlet>(this.vVector1_use_B, this.VDirichlet1, this.vVector1_marginal_F);
// Message to 'vint9' from Discrete factor
vint9_F = DiscreteFromDirichletOp.SampleAverageLogarithm(this.vVector1_marginal_F, vint9_F);
// Message to 'vint9_marginal' from Variable factor
this.vint9_marginal_F = VariableVmpOp.MarginalAverageLogarithm <Discrete>(this.vint9_selector_B, vint9_F, this.vint9_marginal_F);
for (int index2 = 0; index2 < 2; index2++)
{
// Message to 'vdouble__4_index2_' from Gaussian factor
vdouble__4_index2__B[index2] = GaussianOp.PrecisionAverageLogarithm(vdouble17__index2__marginal_F[index2], this.vdouble__3_marginal_F[index2]);
// Message to 'vdouble__4_use' from EnterOne factor
this.vdouble__4_use_B[index2] = GateEnterOneOp <double> .ValueAverageLogarithm <Gamma>(vdouble__4_index2__B[index2], this.vint9_marginal_F, index2, this.vdouble__4_use_B[index2]);
}
// Message to 'vVector1_use' from Discrete factor
this.vVector1_use_B = DiscreteFromDirichletOp.ProbsAverageLogarithm(this.vint9_marginal_F, this.vVector1_use_B);
this.OnProgressChanged(new ProgressChangedEventArgs(iteration));
}
for (int index2 = 0; index2 < 2; index2++)
{
// Message to 'vdouble__3_index2_' from Gaussian factor
vdouble__3_index2__B[index2] = GaussianOp.MeanAverageLogarithm(vdouble17__index2__marginal_F[index2], this.vdouble__4_marginal_F[index2]);
// Message to 'vdouble__3_use' from EnterOne factor
this.vdouble__3_use_B[index2] = GateEnterOneOp <double> .ValueAverageLogarithm <Gaussian>(vdouble__3_index2__B[index2], this.vint9_marginal_F, index2, this.vdouble__3_use_B[index2]);
// Message to 'vdouble__3_marginal' from Variable factor
this.vdouble__3_marginal_F[index2] = VariableVmpOp.MarginalAverageLogarithm <Gaussian>(this.vdouble__3_use_B[index2], this.VGaussian__1[index2], this.vdouble__3_marginal_F[index2]);
// Message to 'vint9_selector_cases_depth1_uses' from Gaussian factor
vint9_selector_cases_depth1_uses_B[index2][7] = Bernoulli.FromLogOdds(GaussianOp.AverageLogFactor(vdouble17__index2__marginal_F[index2], this.vdouble__3_marginal_F[index2], this.vdouble__4_marginal_F[index2]));
}
for (int _iv = 0; _iv < 2; _iv++)
{
// Message to 'vint9_selector_cases_depth1' from Replicate factor
vint9_selector_cases_depth1_B[_iv] = ReplicateOp.DefAverageLogarithm <Bernoulli>(vint9_selector_cases_depth1_uses_B[_iv], vint9_selector_cases_depth1_B[_iv]);
// Message to 'vint9_selector_cases_uses' from Copy factor
vint9_selector_cases_uses_B[0][_iv] = ArrayHelper.SetTo <Bernoulli>(vint9_selector_cases_uses_B[0][_iv], vint9_selector_cases_depth1_B[_iv]);
}
// Message to 'vint9_selector_cases' from Replicate factor
vint9_selector_cases_B = ReplicateOp.DefAverageLogarithm <DistributionStructArray <Bernoulli, bool> >(vint9_selector_cases_uses_B, vint9_selector_cases_B);
// Message to 'vint9_selector_uses' from CasesInt factor
vint9_selector_uses_B[0] = IntCasesOp.IAverageLogarithm(vint9_selector_cases_B, vint9_selector_uses_B[0]);
// Message to 'vint9_selector' from Replicate factor
this.vint9_selector_B = ReplicateOp.DefAverageLogarithm <Discrete>(vint9_selector_uses_B, this.vint9_selector_B);
// Message to 'vint9_marginal' from Variable factor
this.vint9_marginal_F = VariableVmpOp.MarginalAverageLogarithm <Discrete>(this.vint9_selector_B, vint9_F, this.vint9_marginal_F);
for (int index2 = 0; index2 < 2; index2++)
{
// Message to 'vdouble__4_index2_' from Gaussian factor
vdouble__4_index2__B[index2] = GaussianOp.PrecisionAverageLogarithm(vdouble17__index2__marginal_F[index2], this.vdouble__3_marginal_F[index2]);
// Message to 'vdouble__4_use' from EnterOne factor
this.vdouble__4_use_B[index2] = GateEnterOneOp <double> .ValueAverageLogarithm <Gamma>(vdouble__4_index2__B[index2], this.vint9_marginal_F, index2, this.vdouble__4_use_B[index2]);
// Message to 'vdouble__4_marginal' from Variable factor
this.vdouble__4_marginal_F[index2] = VariableVmpOp.MarginalAverageLogarithm <Gamma>(this.vdouble__4_use_B[index2], this.VGamma__1[index2], this.vdouble__4_marginal_F[index2]);
}
// Message to 'vVector1_use' from Discrete factor
this.vVector1_use_B = DiscreteFromDirichletOp.ProbsAverageLogarithm(this.vint9_marginal_F, this.vVector1_use_B);
// Message to 'vVector1_marginal' from Variable factor
this.vVector1_marginal_F = VariableVmpOp.MarginalAverageLogarithm <Dirichlet>(this.vVector1_use_B, this.VDirichlet1, this.vVector1_marginal_F);
this.vdouble17_F = Gaussian.Uniform();
DistributionStructArray <Bernoulli, bool> vint9_selector_cases_F = default(DistributionStructArray <Bernoulli, bool>);
// Create array for 'vint9_selector_cases' Forwards messages.
vint9_selector_cases_F = new DistributionStructArray <Bernoulli, bool>(2);
for (int _iv = 0; _iv < 2; _iv++)
{
vint9_selector_cases_F[_iv] = Bernoulli.Uniform();
}
// Message to 'vint9_selector_cases' from CasesInt factor
vint9_selector_cases_F = IntCasesOp.CasesAverageLogarithm <DistributionStructArray <Bernoulli, bool> >(this.vint9_marginal_F, vint9_selector_cases_F);
// Message to 'vdouble17' from Exit factor
this.vdouble17_F = GateExitOp <double> .ExitAverageLogarithm <Gaussian>(vint9_selector_cases_F, vdouble17__index2__marginal_F, this.vdouble17_F);
this.Changed_numberOfIterationsDecreased_vGamma__1_vGaussian__1_vDirichlet1_iterationsDone = numberOfIterations;
}
