/// <summary>Computations that depend on the observed value of FeatureIndexes and FeatureValues and InstanceCount and InstanceFeatureCounts and Labels and numberOfIterations and WeightConstraints and WeightPriors</summary>
/// <param name="numberOfIterations">The number of times to iterate each loop</param>
private void Changed_FeatureIndexes_FeatureValues_InstanceCount_InstanceFeatureCounts_Labels_numberOfIterations_W7(int numberOfIterations)
{
if (this.Changed_FeatureIndexes_FeatureValues_InstanceCount_InstanceFeatureCounts_Labels_numberOfIterations_W7_isDone)
{
return;
}
for (int iteration = this.numberOfIterationsDone; iteration < numberOfIterations; iteration++)
{
for (int InstanceRange = 0; InstanceRange < this.instanceCount; InstanceRange++)
{
this.Weights_FeatureIndexes_F[InstanceRange] = JaggedSubarrayWithMarginalOp <double> .ItemsAverageConditional <DistributionStructArray <Gaussian, double>, Gaussian, DistributionStructArray <Gaussian, double> >(this.IndexedWeights_B[InstanceRange], this.Weights_uses_F[1], this.Weights_marginal_F, this.featureIndexes, InstanceRange, this.Weights_FeatureIndexes_F[InstanceRange]);
for (int InstanceFeatureRanges = 0; InstanceFeatureRanges < this.instanceFeatureCounts[InstanceRange]; InstanceFeatureRanges++)
{
this.FeatureScores_F[InstanceRange][InstanceFeatureRanges] = GaussianProductOpBase.ProductAverageConditional(this.featureValues[InstanceRange][InstanceFeatureRanges], this.Weights_FeatureIndexes_F[InstanceRange][InstanceFeatureRanges]);
}
this.Score_F[InstanceRange] = FastSumOp.SumAverageConditional(this.FeatureScores_F[InstanceRange]);
this.NoisyScore_F[InstanceRange] = GaussianFromMeanAndVarianceOp.SampleAverageConditional(this.Score_F[InstanceRange], 1.0);
this.NoisyScore_use_B[InstanceRange] = IsPositiveOp_Proper.XAverageConditional(Bernoulli.PointMass(this.labels[InstanceRange]), this.NoisyScore_F[InstanceRange]);
this.Score_B[InstanceRange] = GaussianFromMeanAndVarianceOp.MeanAverageConditional(this.NoisyScore_use_B[InstanceRange], 1.0);
this.FeatureScores_B[InstanceRange] = FastSumOp.ArrayAverageConditional <DistributionStructArray <Gaussian, double> >(this.Score_B[InstanceRange], this.Score_F[InstanceRange], this.FeatureScores_F[InstanceRange], this.FeatureScores_B[InstanceRange]);
for (int InstanceFeatureRanges = 0; InstanceFeatureRanges < this.instanceFeatureCounts[InstanceRange]; InstanceFeatureRanges++)
{
this.IndexedWeights_B[InstanceRange][InstanceFeatureRanges] = GaussianProductOpBase.BAverageConditional(this.FeatureScores_B[InstanceRange][InstanceFeatureRanges], this.featureValues[InstanceRange][InstanceFeatureRanges]);
}
this.Weights_marginal_F = JaggedSubarrayWithMarginalOp <double> .MarginalIncrementItems <DistributionStructArray <Gaussian, double>, Gaussian, DistributionStructArray <Gaussian, double> >(this.IndexedWeights_B[InstanceRange], this.Weights_FeatureIndexes_F[InstanceRange], this.featureIndexes, InstanceRange, this.Weights_marginal_F);
}
this.OnProgressChanged(new ProgressChangedEventArgs(iteration));
}
for (int InstanceRange = 0; InstanceRange < this.instanceCount; InstanceRange++)
{
this.Weights_FeatureIndexes_B[InstanceRange] = ArrayHelper.SetTo <DistributionStructArray <Gaussian, double> >(this.Weights_FeatureIndexes_B[InstanceRange], this.IndexedWeights_B[InstanceRange]);
}
this.Weights_uses_B[1] = JaggedSubarrayWithMarginalOp <double> .ArrayAverageConditional <DistributionStructArray <Gaussian, double> >(this.Weights_uses_F[1], this.Weights_marginal_F, this.Weights_uses_B[1]);
this.Weights_uses_F[0] = ReplicateOp_NoDivide.UsesAverageConditional <DistributionStructArray <Gaussian, double> >(this.Weights_uses_B, this.weightPriors, 0, this.Weights_uses_F[0]);
this.ModelSelector_selector_cases_0_uses_B[3] = Bernoulli.FromLogOdds(ReplicateOp.LogEvidenceRatio <DistributionStructArray <Gaussian, double> >(this.Weights_uses_B, this.weightPriors, this.Weights_uses_F));
this.ModelSelector_selector_cases_0_uses_B[4] = Bernoulli.FromLogOdds(ConstrainEqualRandomOp <double[]> .LogEvidenceRatio <DistributionStructArray <Gaussian, double> >(this.Weights_uses_F[0], this.weightConstraints));
this.ModelSelector_selector_cases_0_uses_B[8] = Bernoulli.FromLogOdds(JaggedSubarrayWithMarginalOp <double> .LogEvidenceRatio <Gaussian, DistributionRefArray <DistributionStructArray <Gaussian, double>, double[]>, DistributionStructArray <Gaussian, double> >(this.Weights_FeatureIndexes_B, this.Weights_uses_F[1], this.featureIndexes, this.Weights_FeatureIndexes_F));
for (int InstanceRange = 0; InstanceRange < this.instanceCount; InstanceRange++)
{
this.ModelSelector_selector_cases_0_rep9_B[InstanceRange] = Bernoulli.FromLogOdds(IsPositiveOp.LogEvidenceRatio(this.labels[InstanceRange], this.NoisyScore_F[InstanceRange]));
}
this.ModelSelector_selector_cases_0_uses_B[16] = ReplicateOp_NoDivide.DefAverageConditional <Bernoulli>(this.ModelSelector_selector_cases_0_rep9_B, this.ModelSelector_selector_cases_0_uses_B[16]);
this.ModelSelector_selector_cases_0_B = ReplicateOp_NoDivide.DefAverageConditional <Bernoulli>(this.ModelSelector_selector_cases_0_uses_B, this.ModelSelector_selector_cases_0_B);
this.ModelSelector_selector_cases_B[0] = ArrayHelper.SetTo <Bernoulli>(this.ModelSelector_selector_cases_B[0], this.ModelSelector_selector_cases_0_B);
this.ModelSelector_selector_B = CasesOp.BAverageConditional(this.ModelSelector_selector_cases_B);
this.ModelSelector_marginal_F = VariableOp.MarginalAverageConditional <Bernoulli>(this.ModelSelector_selector_B, this.vBernoulli1, this.ModelSelector_marginal_F);
this.Weights_B = ReplicateOp_NoDivide.DefAverageConditional <DistributionStructArray <Gaussian, double> >(this.Weights_uses_B, this.Weights_B);
this.Changed_FeatureIndexes_FeatureValues_InstanceCount_InstanceFeatureCounts_Labels_numberOfIterations_W7_isDone = true;
}
/// <summary>Computations that depend on the observed value of FeatureCount and FeatureValues and InstanceCount and Labels and numberOfIterations and WeightConstraints and WeightPriors</summary>
/// <param name="numberOfIterations">The number of times to iterate each loop</param>
private void Changed_FeatureCount_FeatureValues_InstanceCount_Labels_numberOfIterations_WeightConstraints_WeightP8(int numberOfIterations)
{
if (this.Changed_FeatureCount_FeatureValues_InstanceCount_Labels_numberOfIterations_WeightConstraints_WeightP8_isDone)
{
return;
}
for (int iteration = this.numberOfIterationsDone; iteration < numberOfIterations; iteration++)
{
for (int FeatureRange = 0; FeatureRange < this.featureCount; FeatureRange++)
{
this.Weights_depth1_rep_F_marginal[FeatureRange] = ReplicateOp_Divide.Marginal <Gaussian>(this.Weights_depth1_rep_B_toDef[FeatureRange], this.Weights_uses_F[1][FeatureRange], this.Weights_depth1_rep_F_marginal[FeatureRange]);
}
for (int InstanceRange = 0; InstanceRange < this.instanceCount; InstanceRange++)
{
for (int FeatureRange = 0; FeatureRange < this.featureCount; FeatureRange++)
{
this.Weights_depth1_rep_F[FeatureRange][InstanceRange] = ReplicateOp_Divide.UsesAverageConditional <Gaussian>(this.Weights_depth1_rep_B[FeatureRange][InstanceRange], this.Weights_depth1_rep_F_marginal[FeatureRange], InstanceRange, this.Weights_depth1_rep_F[FeatureRange][InstanceRange]);
this.FeatureScores_F[InstanceRange][FeatureRange] = GaussianProductOpBase.ProductAverageConditional(this.featureValues[InstanceRange][FeatureRange], this.Weights_depth1_rep_F[FeatureRange][InstanceRange]);
}
this.Score_F[InstanceRange] = FastSumOp.SumAverageConditional(this.FeatureScores_F[InstanceRange]);
this.NoisyScore_F[InstanceRange] = GaussianFromMeanAndVarianceOp.SampleAverageConditional(this.Score_F[InstanceRange], 1.0);
this.NoisyScore_use_B[InstanceRange] = IsPositiveOp_Proper.XAverageConditional(Bernoulli.PointMass(this.labels[InstanceRange]), this.NoisyScore_F[InstanceRange]);
this.Score_B[InstanceRange] = GaussianFromMeanAndVarianceOp.MeanAverageConditional(this.NoisyScore_use_B[InstanceRange], 1.0);
this.FeatureScores_B[InstanceRange] = FastSumOp.ArrayAverageConditional <DistributionStructArray <Gaussian, double> >(this.Score_B[InstanceRange], this.Score_F[InstanceRange], this.FeatureScores_F[InstanceRange], this.FeatureScores_B[InstanceRange]);
for (int FeatureRange = 0; FeatureRange < this.featureCount; FeatureRange++)
{
this.Weights_depth1_rep_B[FeatureRange][InstanceRange] = GaussianProductOpBase.BAverageConditional(this.FeatureScores_B[InstanceRange][FeatureRange], this.featureValues[InstanceRange][FeatureRange]);
this.Weights_depth1_rep_F_marginal[FeatureRange] = ReplicateOp_Divide.MarginalIncrement <Gaussian>(this.Weights_depth1_rep_F_marginal[FeatureRange], this.Weights_depth1_rep_F[FeatureRange][InstanceRange], this.Weights_depth1_rep_B[FeatureRange][InstanceRange]);
}
}
for (int FeatureRange = 0; FeatureRange < this.featureCount; FeatureRange++)
{
this.Weights_depth1_rep_B_toDef[FeatureRange] = ReplicateOp_Divide.ToDef <Gaussian>(this.Weights_depth1_rep_B[FeatureRange], this.Weights_depth1_rep_B_toDef[FeatureRange]);
}
this.OnProgressChanged(new ProgressChangedEventArgs(iteration));
}
for (int _iv = 0; _iv < this.featureCount; _iv++)
{
this.Weights_uses_B[1][_iv] = ArrayHelper.SetTo <Gaussian>(this.Weights_uses_B[1][_iv], this.Weights_depth1_rep_B_toDef[_iv]);
}
this.Weights_uses_F[0] = ReplicateOp_NoDivide.UsesAverageConditional <DistributionStructArray <Gaussian, double> >(this.Weights_uses_B, this.weightPriors, 0, this.Weights_uses_F[0]);
this.ModelSelector_selector_cases_0_uses_B[6] = Bernoulli.FromLogOdds(ReplicateOp.LogEvidenceRatio <DistributionStructArray <Gaussian, double> >(this.Weights_uses_B, this.weightPriors, this.Weights_uses_F));
this.ModelSelector_selector_cases_0_uses_B[7] = Bernoulli.FromLogOdds(ConstrainEqualRandomOp <double[]> .LogEvidenceRatio <DistributionStructArray <Gaussian, double> >(this.Weights_uses_F[0], this.weightConstraints));
for (int FeatureRange = 0; FeatureRange < this.featureCount; FeatureRange++)
{
this.ModelSelector_selector_cases_0_rep3_uses_B[FeatureRange][1] = Bernoulli.FromLogOdds(ReplicateOp.LogEvidenceRatio <Gaussian>(this.Weights_depth1_rep_B[FeatureRange], this.Weights_uses_F[1][FeatureRange], this.Weights_depth1_rep_F[FeatureRange]));
this.ModelSelector_selector_cases_0_rep3_B[FeatureRange] = ReplicateOp_NoDivide.DefAverageConditional <Bernoulli>(this.ModelSelector_selector_cases_0_rep3_uses_B[FeatureRange], this.ModelSelector_selector_cases_0_rep3_B[FeatureRange]);
}
this.ModelSelector_selector_cases_0_uses_B[12] = ReplicateOp_NoDivide.DefAverageConditional <Bernoulli>(this.ModelSelector_selector_cases_0_rep3_B, this.ModelSelector_selector_cases_0_uses_B[12]);
for (int InstanceRange = 0; InstanceRange < this.instanceCount; InstanceRange++)
{
this.ModelSelector_selector_cases_0_rep8_B[InstanceRange] = Bernoulli.FromLogOdds(IsPositiveOp.LogEvidenceRatio(this.labels[InstanceRange], this.NoisyScore_F[InstanceRange]));
}
this.ModelSelector_selector_cases_0_uses_B[17] = ReplicateOp_NoDivide.DefAverageConditional <Bernoulli>(this.ModelSelector_selector_cases_0_rep8_B, this.ModelSelector_selector_cases_0_uses_B[17]);
this.ModelSelector_selector_cases_0_B = ReplicateOp_NoDivide.DefAverageConditional <Bernoulli>(this.ModelSelector_selector_cases_0_uses_B, this.ModelSelector_selector_cases_0_B);
this.ModelSelector_selector_cases_B[0] = ArrayHelper.SetTo <Bernoulli>(this.ModelSelector_selector_cases_B[0], this.ModelSelector_selector_cases_0_B);
this.ModelSelector_selector_B = CasesOp.BAverageConditional(this.ModelSelector_selector_cases_B);
this.ModelSelector_marginal_F = VariableOp.MarginalAverageConditional <Bernoulli>(this.ModelSelector_selector_B, this.vBernoulli0, this.ModelSelector_marginal_F);
this.Weights_use_B = ReplicateOp_NoDivide.DefAverageConditional <DistributionStructArray <Gaussian, double> >(this.Weights_uses_B, this.Weights_use_B);
this.Weights_marginal_F = VariableOp.MarginalAverageConditional <DistributionStructArray <Gaussian, double> >(this.Weights_use_B, this.weightPriors, this.Weights_marginal_F);
this.Changed_FeatureCount_FeatureValues_InstanceCount_Labels_numberOfIterations_WeightConstraints_WeightP8_isDone = true;
}
/// <summary>Computations that depend on the observed value of Cloudy and WetGrass</summary>
public void Changed_Cloudy_WetGrass()
{
if (this.Changed_Cloudy_WetGrass_iterationsDone == 1)
{
return;
}
// The constant 'vBernoulli18'
Bernoulli vBernoulli18 = Bernoulli.FromLogOdds(0);
this.Cloudy_marginal = ArrayHelper.MakeUniform <Bernoulli>(vBernoulli18);
this.Cloudy_marginal = Distribution.SetPoint <Bernoulli, bool>(this.Cloudy_marginal, this.cloudy);
// The constant 'vBernoulli23'
Bernoulli vBernoulli23 = Bernoulli.FromLogOdds(4.5951198501345889);
this.WetGrass_marginal = ArrayHelper.MakeUniform <Bernoulli>(vBernoulli23);
this.WetGrass_marginal = Distribution.SetPoint <Bernoulli, bool>(this.WetGrass_marginal, this.wetGrass);
// The constant 'vBernoulli21'
Bernoulli vBernoulli21 = Bernoulli.FromLogOdds(1.3862943611198908);
Bernoulli Rain_F = ArrayHelper.MakeUniform <Bernoulli>(vBernoulli21);
this.Rain_marginal_F = ArrayHelper.MakeUniform <Bernoulli>(vBernoulli21);
// Message to use of 'Rain'
Bernoulli Rain_use_F = ArrayHelper.MakeUniform <Bernoulli>(vBernoulli21);
// Message from use of 'Rain'
Bernoulli Rain_use_B = ArrayHelper.MakeUniform <Bernoulli>(vBernoulli21);
if (this.cloudy)
{
// Message to 'Rain' from Copy factor
Rain_F = Factor.Copy <Bernoulli>(vBernoulli21);
}
// The constant 'vBernoulli22'
Bernoulli vBernoulli22 = Bernoulli.FromLogOdds(0.28185115214098749);
if (!this.cloudy)
{
// Message to 'Rain' from Copy factor
Rain_F = Factor.Copy <Bernoulli>(vBernoulli22);
}
// Rain_F is now updated in all contexts
if (this.cloudy)
{
// Message to 'Rain_use' from DerivedVariable factor
Rain_use_F = Factor.Copy <Bernoulli>(Rain_F);
}
Bernoulli Rain_cond_Sprinkler_0_selector_cases_0_B = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
// Message to 'Rain_cond_Sprinkler_0_selector_cases_0' from Random factor
Rain_cond_Sprinkler_0_selector_cases_0_B = Bernoulli.FromLogOdds(UnaryOp <bool> .LogEvidenceRatio <Bernoulli>(this.wetGrass, vBernoulli23));
DistributionStructArray <Bernoulli, bool> Rain_cond_Sprinkler_0_selector_cases_B = default(DistributionStructArray <Bernoulli, bool>);
// Create array for 'Rain_cond_Sprinkler_0_selector_cases' Backwards messages.
Rain_cond_Sprinkler_0_selector_cases_B = new DistributionStructArray <Bernoulli, bool>(2);
for (int _ind0 = 0; _ind0 < 2; _ind0++)
{
Rain_cond_Sprinkler_0_selector_cases_B[_ind0] = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
}
// Message to 'Rain_cond_Sprinkler_0_selector_cases' from Copy factor
Rain_cond_Sprinkler_0_selector_cases_B[0] = Factor.Copy <Bernoulli>(Rain_cond_Sprinkler_0_selector_cases_0_B);
// The constant 'vBernoulli24'
Bernoulli vBernoulli24 = Bernoulli.FromLogOdds(2.1972245773362196);
Bernoulli Rain_cond_Sprinkler_0_selector_cases_1_B = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
// Message to 'Rain_cond_Sprinkler_0_selector_cases_1' from Random factor
Rain_cond_Sprinkler_0_selector_cases_1_B = Bernoulli.FromLogOdds(UnaryOp <bool> .LogEvidenceRatio <Bernoulli>(this.wetGrass, vBernoulli24));
// Message to 'Rain_cond_Sprinkler_0_selector_cases' from Copy factor
Rain_cond_Sprinkler_0_selector_cases_B[1] = Factor.Copy <Bernoulli>(Rain_cond_Sprinkler_0_selector_cases_1_B);
if (!this.cloudy)
{
// Message to 'Rain_use' from DerivedVariable factor
Rain_use_F = Factor.Copy <Bernoulli>(vBernoulli22);
}
// Rain_use_F is now updated in all contexts
Bernoulli[] Sprinkler_selector_cases_0_uses_B = default(Bernoulli[]);
// Create array for 'Sprinkler_selector_cases_0_uses' Backwards messages.
Sprinkler_selector_cases_0_uses_B = new Bernoulli[5];
for (int _ind = 0; _ind < 5; _ind++)
{
Sprinkler_selector_cases_0_uses_B[_ind] = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
}
// Message to 'Sprinkler_selector_cases_0_uses' from Cases factor
Sprinkler_selector_cases_0_uses_B[4] = Bernoulli.FromLogOdds(CasesOp.LogEvidenceRatio(Rain_cond_Sprinkler_0_selector_cases_B, Rain_use_F));
Bernoulli Sprinkler_selector_cases_0_B = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
// Message to 'Sprinkler_selector_cases_0' from Replicate factor
Sprinkler_selector_cases_0_B = ReplicateOp.DefAverageConditional <Bernoulli>(Sprinkler_selector_cases_0_uses_B, Sprinkler_selector_cases_0_B);
DistributionStructArray <Bernoulli, bool> Sprinkler_selector_cases_B = default(DistributionStructArray <Bernoulli, bool>);
// Create array for 'Sprinkler_selector_cases' Backwards messages.
Sprinkler_selector_cases_B = new DistributionStructArray <Bernoulli, bool>(2);
for (int _ind0 = 0; _ind0 < 2; _ind0++)
{
Sprinkler_selector_cases_B[_ind0] = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
}
// Message to 'Sprinkler_selector_cases' from Copy factor
Sprinkler_selector_cases_B[0] = Factor.Copy <Bernoulli>(Sprinkler_selector_cases_0_B);
Bernoulli Rain_cond_Sprinkler_1_selector_cases_0_B = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
// Message to 'Rain_cond_Sprinkler_1_selector_cases_0' from Random factor
Rain_cond_Sprinkler_1_selector_cases_0_B = Bernoulli.FromLogOdds(UnaryOp <bool> .LogEvidenceRatio <Bernoulli>(this.wetGrass, vBernoulli24));
DistributionStructArray <Bernoulli, bool> Rain_cond_Sprinkler_1_selector_cases_B = default(DistributionStructArray <Bernoulli, bool>);
// Create array for 'Rain_cond_Sprinkler_1_selector_cases' Backwards messages.
Rain_cond_Sprinkler_1_selector_cases_B = new DistributionStructArray <Bernoulli, bool>(2);
for (int _ind0 = 0; _ind0 < 2; _ind0++)
{
Rain_cond_Sprinkler_1_selector_cases_B[_ind0] = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
}
// Message to 'Rain_cond_Sprinkler_1_selector_cases' from Copy factor
Rain_cond_Sprinkler_1_selector_cases_B[0] = Factor.Copy <Bernoulli>(Rain_cond_Sprinkler_1_selector_cases_0_B);
// The constant 'vBernoulli26'
Bernoulli vBernoulli26 = Bernoulli.FromLogOdds(-2.4423470353692043);
Bernoulli Rain_cond_Sprinkler_1_selector_cases_1_B = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
// Message to 'Rain_cond_Sprinkler_1_selector_cases_1' from Random factor
Rain_cond_Sprinkler_1_selector_cases_1_B = Bernoulli.FromLogOdds(UnaryOp <bool> .LogEvidenceRatio <Bernoulli>(this.wetGrass, vBernoulli26));
// Message to 'Rain_cond_Sprinkler_1_selector_cases' from Copy factor
Rain_cond_Sprinkler_1_selector_cases_B[1] = Factor.Copy <Bernoulli>(Rain_cond_Sprinkler_1_selector_cases_1_B);
Bernoulli[] Sprinkler_selector_cases_1_uses_B = default(Bernoulli[]);
// Create array for 'Sprinkler_selector_cases_1_uses' Backwards messages.
Sprinkler_selector_cases_1_uses_B = new Bernoulli[5];
for (int _ind = 0; _ind < 5; _ind++)
{
Sprinkler_selector_cases_1_uses_B[_ind] = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
}
// Message to 'Sprinkler_selector_cases_1_uses' from Cases factor
Sprinkler_selector_cases_1_uses_B[4] = Bernoulli.FromLogOdds(CasesOp.LogEvidenceRatio(Rain_cond_Sprinkler_1_selector_cases_B, Rain_use_F));
Bernoulli Sprinkler_selector_cases_1_B = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
// Message to 'Sprinkler_selector_cases_1' from Replicate factor
Sprinkler_selector_cases_1_B = ReplicateOp.DefAverageConditional <Bernoulli>(Sprinkler_selector_cases_1_uses_B, Sprinkler_selector_cases_1_B);
// Message to 'Sprinkler_selector_cases' from Copy factor
Sprinkler_selector_cases_B[1] = Factor.Copy <Bernoulli>(Sprinkler_selector_cases_1_B);
Bernoulli[] Sprinkler_selector_uses_B = default(Bernoulli[]);
// Create array for 'Sprinkler_selector_uses' Backwards messages.
Sprinkler_selector_uses_B = new Bernoulli[2];
// The constant 'vBernoulli19'
Bernoulli vBernoulli19 = Bernoulli.FromLogOdds(-2.1972245773362191);
for (int _ind = 0; _ind < 2; _ind++)
{
Sprinkler_selector_uses_B[_ind] = ArrayHelper.MakeUniform <Bernoulli>(vBernoulli19);
}
// Message to 'Sprinkler_selector_uses' from Cases factor
Sprinkler_selector_uses_B[0] = CasesOp.BAverageConditional(Sprinkler_selector_cases_B);
Bernoulli Sprinkler_F = ArrayHelper.MakeUniform <Bernoulli>(vBernoulli19);
if (this.cloudy)
{
// Message to 'Sprinkler' from Copy factor
Sprinkler_F = Factor.Copy <Bernoulli>(vBernoulli19);
}
if (!this.cloudy)
{
// Message to 'Sprinkler' from Copy factor
Sprinkler_F = Factor.Copy <Bernoulli>(vBernoulli18);
}
// Sprinkler_F is now updated in all contexts
// Message to use of 'Sprinkler'
Bernoulli Sprinkler_use_F = ArrayHelper.MakeUniform <Bernoulli>(vBernoulli19);
if (this.cloudy)
{
// Message to 'Sprinkler_use' from DerivedVariable factor
Sprinkler_use_F = Factor.Copy <Bernoulli>(Sprinkler_F);
}
if (!this.cloudy)
{
// Message to 'Sprinkler_use' from DerivedVariable factor
Sprinkler_use_F = Factor.Copy <Bernoulli>(vBernoulli18);
}
// Sprinkler_use_F is now updated in all contexts
// Buffer for Replicate2BufferOp.UsesAverageConditional<Bernoulli>
Bernoulli Sprinkler_selector_uses_B_marginal = default(Bernoulli);
// Message to 'Sprinkler_selector_uses' from Replicate factor
Sprinkler_selector_uses_B_marginal = Replicate2BufferOp.MarginalInit <Bernoulli>(Sprinkler_use_F);
// Message to 'Sprinkler_selector_uses' from Replicate factor
Sprinkler_selector_uses_B_marginal = Replicate2BufferOp.Marginal <Bernoulli>(Sprinkler_selector_uses_B, Sprinkler_use_F, Sprinkler_selector_uses_B_marginal);
Bernoulli[] Sprinkler_selector_uses_F = default(Bernoulli[]);
// Create array for 'Sprinkler_selector_uses' Forwards messages.
Sprinkler_selector_uses_F = new Bernoulli[2];
for (int _ind = 0; _ind < 2; _ind++)
{
Sprinkler_selector_uses_F[_ind] = ArrayHelper.MakeUniform <Bernoulli>(vBernoulli19);
}
// Message to 'Sprinkler_selector_uses' from Replicate factor
Sprinkler_selector_uses_F[1] = Replicate2BufferOp.UsesAverageConditional <Bernoulli>(Sprinkler_selector_uses_B, Sprinkler_use_F, Sprinkler_selector_uses_B_marginal, 1, Sprinkler_selector_uses_F[1]);
Bernoulli Rain_cond_Sprinkler_0_selector_B = ArrayHelper.MakeUniform <Bernoulli>(vBernoulli21);
// Message to 'Rain_cond_Sprinkler_0_selector' from Cases factor
Rain_cond_Sprinkler_0_selector_B = CasesOp.BAverageConditional(Rain_cond_Sprinkler_0_selector_cases_B);
DistributionStructArray <Bernoulli, bool> Rain_cond_Sprinkler_B = default(DistributionStructArray <Bernoulli, bool>);
// Create array for 'Rain_cond_Sprinkler' Backwards messages.
Rain_cond_Sprinkler_B = new DistributionStructArray <Bernoulli, bool>(2);
for (int _gateind = 0; _gateind < 2; _gateind++)
{
Rain_cond_Sprinkler_B[_gateind] = ArrayHelper.MakeUniform <Bernoulli>(vBernoulli21);
}
// Message to 'Rain_cond_Sprinkler' from Copy factor
Rain_cond_Sprinkler_B[0] = Factor.Copy <Bernoulli>(Rain_cond_Sprinkler_0_selector_B);
Bernoulli Rain_cond_Sprinkler_1_selector_B = ArrayHelper.MakeUniform <Bernoulli>(vBernoulli21);
// Message to 'Rain_cond_Sprinkler_1_selector' from Cases factor
Rain_cond_Sprinkler_1_selector_B = CasesOp.BAverageConditional(Rain_cond_Sprinkler_1_selector_cases_B);
// Message to 'Rain_cond_Sprinkler' from Copy factor
Rain_cond_Sprinkler_B[1] = Factor.Copy <Bernoulli>(Rain_cond_Sprinkler_1_selector_B);
// Message to 'Rain_use' from EnterPartial factor
Rain_use_B = GateEnterPartialOp <bool> .ValueAverageConditional <Bernoulli>(Rain_cond_Sprinkler_B, Sprinkler_selector_uses_F[1], Rain_use_F, new int[2] {
0, 1
}, Rain_use_B);
if (this.cloudy)
{
// Message to 'Rain_marginal' from DerivedVariable factor
this.Rain_marginal_F = DerivedVariableOp.MarginalAverageConditional <Bernoulli>(Rain_use_B, Rain_F, this.Rain_marginal_F);
}
if (!this.cloudy)
{
// Message to 'Rain_marginal' from DerivedVariable factor
this.Rain_marginal_F = DerivedVariableOp.MarginalAverageConditional <Bernoulli>(Rain_use_B, vBernoulli22, this.Rain_marginal_F);
}
// Rain_marginal_F is now updated in all contexts
this.Sprinkler_marginal_F = ArrayHelper.MakeUniform <Bernoulli>(vBernoulli19);
Bernoulli Sprinkler_selector_B = ArrayHelper.MakeUniform <Bernoulli>(vBernoulli19);
// Message to 'Sprinkler_selector' from Replicate factor
Sprinkler_selector_B = ReplicateOp.DefAverageConditional <Bernoulli>(Sprinkler_selector_uses_B, Sprinkler_selector_B);
if (this.cloudy)
{
// Message to 'Sprinkler_marginal' from DerivedVariable factor
this.Sprinkler_marginal_F = DerivedVariableOp.MarginalAverageConditional <Bernoulli>(Sprinkler_selector_B, Sprinkler_F, this.Sprinkler_marginal_F);
}
if (!this.cloudy)
{
// Message to 'Sprinkler_marginal' from DerivedVariable factor
this.Sprinkler_marginal_F = DerivedVariableOp.MarginalAverageConditional <Bernoulli>(Sprinkler_selector_B, vBernoulli18, this.Sprinkler_marginal_F);
}
// Sprinkler_marginal_F is now updated in all contexts
this.Changed_Cloudy_WetGrass_iterationsDone = 1;
}
/// <summary>Computations that depend on the observed value of numberOfIterationsDecreased and WetGrass</summary>
/// <param name="numberOfIterations">The number of times to iterate each loop</param>
public void Changed_numberOfIterationsDecreased_WetGrass(int numberOfIterations)
{
if (this.Changed_numberOfIterationsDecreased_WetGrass_iterationsDone == numberOfIterations)
{
return;
}
// The constant 'vBernoulli32'
Bernoulli vBernoulli32 = Bernoulli.FromLogOdds(4.5951198501345889);
this.WetGrass_marginal = ArrayHelper.MakeUniform <Bernoulli>(vBernoulli32);
this.WetGrass_marginal = Distribution.SetPoint <Bernoulli, bool>(this.WetGrass_marginal, this.wetGrass);
Bernoulli Rain_F = ArrayHelper.MakeUniform <Bernoulli>(this.vBernoulli30);
// The constant 'vBernoulli27'
Bernoulli vBernoulli27 = Bernoulli.FromLogOdds(0);
this.Cloudy_marginal_F = ArrayHelper.MakeUniform <Bernoulli>(vBernoulli27);
DistributionStructArray <Bernoulli, bool> Rain_cond_Cloudy_F = default(DistributionStructArray <Bernoulli, bool>);
// Create array for 'Rain_cond_Cloudy' Forwards messages.
Rain_cond_Cloudy_F = new DistributionStructArray <Bernoulli, bool>(2);
for (int _gateind = 0; _gateind < 2; _gateind++)
{
Rain_cond_Cloudy_F[_gateind] = ArrayHelper.MakeUniform <Bernoulli>(this.vBernoulli30);
}
// Message to 'Rain_cond_Cloudy' from Copy factor
Rain_cond_Cloudy_F[0] = Factor.Copy <Bernoulli>(this.vBernoulli30);
// The constant 'vBernoulli31'
Bernoulli vBernoulli31 = Bernoulli.FromLogOdds(-1.3862943611198906);
// Message to 'Rain_cond_Cloudy' from Copy factor
Rain_cond_Cloudy_F[1] = Factor.Copy <Bernoulli>(vBernoulli31);
DistributionStructArray <Bernoulli, bool> Cloudy_selector_cases_F = default(DistributionStructArray <Bernoulli, bool>);
// Create array for 'Cloudy_selector_cases' Forwards messages.
Cloudy_selector_cases_F = new DistributionStructArray <Bernoulli, bool>(2);
for (int _iv0 = 0; _iv0 < 2; _iv0++)
{
Cloudy_selector_cases_F[_iv0] = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
}
// Message to 'Cloudy_selector_cases' from Cases factor
Cloudy_selector_cases_F = CasesOp.CasesAverageConditional <DistributionStructArray <Bernoulli, bool> >(vBernoulli27, Cloudy_selector_cases_F);
// The constant 'vBernoulli28'
Bernoulli vBernoulli28 = Bernoulli.FromLogOdds(-2.1972245773362191);
DistributionStructArray <Bernoulli, bool> Sprinkler_cond_Cloudy_F = default(DistributionStructArray <Bernoulli, bool>);
// Create array for 'Sprinkler_cond_Cloudy' Forwards messages.
Sprinkler_cond_Cloudy_F = new DistributionStructArray <Bernoulli, bool>(2);
for (int _gateind = 0; _gateind < 2; _gateind++)
{
Sprinkler_cond_Cloudy_F[_gateind] = ArrayHelper.MakeUniform <Bernoulli>(vBernoulli28);
}
// Message to 'Sprinkler_cond_Cloudy' from Copy factor
Sprinkler_cond_Cloudy_F[0] = Factor.Copy <Bernoulli>(vBernoulli28);
// Message to 'Sprinkler_cond_Cloudy' from Copy factor
Sprinkler_cond_Cloudy_F[1] = Factor.Copy <Bernoulli>(vBernoulli27);
Bernoulli Rain_cond_Sprinkler_0_selector_cases_0_B = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
// Message to 'Rain_cond_Sprinkler_0_selector_cases_0' from Random factor
Rain_cond_Sprinkler_0_selector_cases_0_B = Bernoulli.FromLogOdds(UnaryOp <bool> .LogEvidenceRatio <Bernoulli>(this.wetGrass, vBernoulli32));
DistributionStructArray <Bernoulli, bool> Rain_cond_Sprinkler_0_selector_cases_B = default(DistributionStructArray <Bernoulli, bool>);
// Create array for 'Rain_cond_Sprinkler_0_selector_cases' Backwards messages.
Rain_cond_Sprinkler_0_selector_cases_B = new DistributionStructArray <Bernoulli, bool>(2);
for (int _ind0 = 0; _ind0 < 2; _ind0++)
{
Rain_cond_Sprinkler_0_selector_cases_B[_ind0] = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
}
// Message to 'Rain_cond_Sprinkler_0_selector_cases' from Copy factor
Rain_cond_Sprinkler_0_selector_cases_B[0] = Factor.Copy <Bernoulli>(Rain_cond_Sprinkler_0_selector_cases_0_B);
// The constant 'vBernoulli33'
Bernoulli vBernoulli33 = Bernoulli.FromLogOdds(2.1972245773362196);
Bernoulli Rain_cond_Sprinkler_0_selector_cases_1_B = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
// Message to 'Rain_cond_Sprinkler_0_selector_cases_1' from Random factor
Rain_cond_Sprinkler_0_selector_cases_1_B = Bernoulli.FromLogOdds(UnaryOp <bool> .LogEvidenceRatio <Bernoulli>(this.wetGrass, vBernoulli33));
// Message to 'Rain_cond_Sprinkler_0_selector_cases' from Copy factor
Rain_cond_Sprinkler_0_selector_cases_B[1] = Factor.Copy <Bernoulli>(Rain_cond_Sprinkler_0_selector_cases_1_B);
Bernoulli[] Sprinkler_selector_cases_0_uses_B = default(Bernoulli[]);
// Create array for 'Sprinkler_selector_cases_0_uses' Backwards messages.
Sprinkler_selector_cases_0_uses_B = new Bernoulli[5];
for (int _ind = 0; _ind < 5; _ind++)
{
Sprinkler_selector_cases_0_uses_B[_ind] = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
}
Bernoulli Sprinkler_selector_cases_0_B = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
DistributionStructArray <Bernoulli, bool> Sprinkler_selector_cases_B = default(DistributionStructArray <Bernoulli, bool>);
// Create array for 'Sprinkler_selector_cases' Backwards messages.
Sprinkler_selector_cases_B = new DistributionStructArray <Bernoulli, bool>(2);
for (int _ind0 = 0; _ind0 < 2; _ind0++)
{
Sprinkler_selector_cases_B[_ind0] = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
}
Bernoulli Rain_cond_Sprinkler_1_selector_cases_0_B = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
// Message to 'Rain_cond_Sprinkler_1_selector_cases_0' from Random factor
Rain_cond_Sprinkler_1_selector_cases_0_B = Bernoulli.FromLogOdds(UnaryOp <bool> .LogEvidenceRatio <Bernoulli>(this.wetGrass, vBernoulli33));
DistributionStructArray <Bernoulli, bool> Rain_cond_Sprinkler_1_selector_cases_B = default(DistributionStructArray <Bernoulli, bool>);
// Create array for 'Rain_cond_Sprinkler_1_selector_cases' Backwards messages.
Rain_cond_Sprinkler_1_selector_cases_B = new DistributionStructArray <Bernoulli, bool>(2);
for (int _ind0 = 0; _ind0 < 2; _ind0++)
{
Rain_cond_Sprinkler_1_selector_cases_B[_ind0] = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
}
// Message to 'Rain_cond_Sprinkler_1_selector_cases' from Copy factor
Rain_cond_Sprinkler_1_selector_cases_B[0] = Factor.Copy <Bernoulli>(Rain_cond_Sprinkler_1_selector_cases_0_B);
// The constant 'vBernoulli35'
Bernoulli vBernoulli35 = Bernoulli.FromLogOdds(Double.NegativeInfinity);
Bernoulli Rain_cond_Sprinkler_1_selector_cases_1_B = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
// Message to 'Rain_cond_Sprinkler_1_selector_cases_1' from Random factor
Rain_cond_Sprinkler_1_selector_cases_1_B = Bernoulli.FromLogOdds(UnaryOp <bool> .LogEvidenceRatio <Bernoulli>(this.wetGrass, vBernoulli35));
// Message to 'Rain_cond_Sprinkler_1_selector_cases' from Copy factor
Rain_cond_Sprinkler_1_selector_cases_B[1] = Factor.Copy <Bernoulli>(Rain_cond_Sprinkler_1_selector_cases_1_B);
Bernoulli[] Sprinkler_selector_cases_1_uses_B = default(Bernoulli[]);
// Create array for 'Sprinkler_selector_cases_1_uses' Backwards messages.
Sprinkler_selector_cases_1_uses_B = new Bernoulli[5];
for (int _ind = 0; _ind < 5; _ind++)
{
Sprinkler_selector_cases_1_uses_B[_ind] = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
}
Bernoulli Sprinkler_selector_cases_1_B = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
Bernoulli[] Sprinkler_selector_uses_B = default(Bernoulli[]);
// Create array for 'Sprinkler_selector_uses' Backwards messages.
Sprinkler_selector_uses_B = new Bernoulli[2];
for (int _ind = 0; _ind < 2; _ind++)
{
Sprinkler_selector_uses_B[_ind] = ArrayHelper.MakeUniform <Bernoulli>(vBernoulli28);
}
Bernoulli Sprinkler_selector_B = ArrayHelper.MakeUniform <Bernoulli>(vBernoulli28);
// Buffer for Replicate2BufferOp.UsesAverageConditional<DistributionStructArray<Bernoulli,bool>>
DistributionStructArray <Bernoulli, bool> Cloudy_selector_cases_uses_B_marginal = default(DistributionStructArray <Bernoulli, bool>);
// Message to 'Cloudy_selector_cases_uses' from Replicate factor
Cloudy_selector_cases_uses_B_marginal = Replicate2BufferOp.MarginalInit <DistributionStructArray <Bernoulli, bool> >(Cloudy_selector_cases_F);
DistributionStructArray <Bernoulli, bool>[] Cloudy_selector_cases_uses_F = default(DistributionStructArray <Bernoulli, bool>[]);
// Create array for 'Cloudy_selector_cases_uses' Forwards messages.
Cloudy_selector_cases_uses_F = new DistributionStructArray <Bernoulli, bool> [4];
for (int _ind = 0; _ind < 4; _ind++)
{
// Create array for 'Cloudy_selector_cases_uses' Forwards messages.
Cloudy_selector_cases_uses_F[_ind] = new DistributionStructArray <Bernoulli, bool>(2);
for (int _iv0 = 0; _iv0 < 2; _iv0++)
{
Cloudy_selector_cases_uses_F[_ind][_iv0] = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
}
}
Bernoulli Sprinkler_F = ArrayHelper.MakeUniform <Bernoulli>(vBernoulli28);
// Buffer for Replicate2BufferOp.UsesAverageConditional<Bernoulli>
Bernoulli Sprinkler_selector_uses_B_marginal = default(Bernoulli);
// Message to 'Sprinkler_selector_uses' from Replicate factor
Sprinkler_selector_uses_B_marginal = Replicate2BufferOp.MarginalInit <Bernoulli>(Sprinkler_F);
Bernoulli[] Sprinkler_selector_uses_F = default(Bernoulli[]);
// Create array for 'Sprinkler_selector_uses' Forwards messages.
Sprinkler_selector_uses_F = new Bernoulli[2];
for (int _ind = 0; _ind < 2; _ind++)
{
Sprinkler_selector_uses_F[_ind] = ArrayHelper.MakeUniform <Bernoulli>(vBernoulli28);
}
Bernoulli Rain_cond_Sprinkler_0_selector_B = ArrayHelper.MakeUniform <Bernoulli>(this.vBernoulli30);
// Message to 'Rain_cond_Sprinkler_0_selector' from Cases factor
Rain_cond_Sprinkler_0_selector_B = CasesOp.BAverageConditional(Rain_cond_Sprinkler_0_selector_cases_B);
DistributionStructArray <Bernoulli, bool> Rain_cond_Sprinkler_B = default(DistributionStructArray <Bernoulli, bool>);
// Create array for 'Rain_cond_Sprinkler' Backwards messages.
Rain_cond_Sprinkler_B = new DistributionStructArray <Bernoulli, bool>(2);
for (int _gateind = 0; _gateind < 2; _gateind++)
{
Rain_cond_Sprinkler_B[_gateind] = ArrayHelper.MakeUniform <Bernoulli>(this.vBernoulli30);
}
// Message to 'Rain_cond_Sprinkler' from Copy factor
Rain_cond_Sprinkler_B[0] = Factor.Copy <Bernoulli>(Rain_cond_Sprinkler_0_selector_B);
Bernoulli Rain_cond_Sprinkler_1_selector_B = ArrayHelper.MakeUniform <Bernoulli>(this.vBernoulli30);
// Message to 'Rain_cond_Sprinkler_1_selector' from Cases factor
Rain_cond_Sprinkler_1_selector_B = CasesOp.BAverageConditional(Rain_cond_Sprinkler_1_selector_cases_B);
// Message to 'Rain_cond_Sprinkler' from Copy factor
Rain_cond_Sprinkler_B[1] = Factor.Copy <Bernoulli>(Rain_cond_Sprinkler_1_selector_B);
for (int iteration = this.Changed_numberOfIterationsDecreased_WetGrass_iterationsDone; iteration < numberOfIterations; iteration++)
{
// Message to 'Cloudy_selector_cases_uses' from Replicate factor
Cloudy_selector_cases_uses_B_marginal = Replicate2BufferOp.Marginal <DistributionStructArray <Bernoulli, bool> >(this.Cloudy_selector_cases_uses_B, Cloudy_selector_cases_F, Cloudy_selector_cases_uses_B_marginal);
// Message to 'Cloudy_selector_cases_uses' from Replicate factor
Cloudy_selector_cases_uses_F[1] = Replicate2BufferOp.UsesAverageConditional <DistributionStructArray <Bernoulli, bool> >(this.Cloudy_selector_cases_uses_B, Cloudy_selector_cases_F, Cloudy_selector_cases_uses_B_marginal, 1, Cloudy_selector_cases_uses_F[1]);
// Message to 'Rain' from Exit factor
Rain_F = GateExitOp <bool> .ExitAverageConditional <Bernoulli>(this.Rain_use_B, Cloudy_selector_cases_uses_F[1], Rain_cond_Cloudy_F, Rain_F);
// Message to 'Sprinkler_selector_cases_1_uses' from Cases factor
Sprinkler_selector_cases_1_uses_B[4] = Bernoulli.FromLogOdds(CasesOp.LogEvidenceRatio(Rain_cond_Sprinkler_1_selector_cases_B, Rain_F));
// Message to 'Sprinkler_selector_cases_1' from Replicate factor
Sprinkler_selector_cases_1_B = ReplicateOp.DefAverageConditional <Bernoulli>(Sprinkler_selector_cases_1_uses_B, Sprinkler_selector_cases_1_B);
// Message to 'Sprinkler_selector_cases' from Copy factor
Sprinkler_selector_cases_B[1] = Factor.Copy <Bernoulli>(Sprinkler_selector_cases_1_B);
// Message to 'Sprinkler_selector_cases_0_uses' from Cases factor
Sprinkler_selector_cases_0_uses_B[4] = Bernoulli.FromLogOdds(CasesOp.LogEvidenceRatio(Rain_cond_Sprinkler_0_selector_cases_B, Rain_F));
// Message to 'Sprinkler_selector_cases_0' from Replicate factor
Sprinkler_selector_cases_0_B = ReplicateOp.DefAverageConditional <Bernoulli>(Sprinkler_selector_cases_0_uses_B, Sprinkler_selector_cases_0_B);
// Message to 'Sprinkler_selector_cases' from Copy factor
Sprinkler_selector_cases_B[0] = Factor.Copy <Bernoulli>(Sprinkler_selector_cases_0_B);
// Message to 'Sprinkler_selector_uses' from Cases factor
Sprinkler_selector_uses_B[0] = CasesOp.BAverageConditional(Sprinkler_selector_cases_B);
// Message to 'Sprinkler_selector' from Replicate factor
Sprinkler_selector_B = ReplicateOp.DefAverageConditional <Bernoulli>(Sprinkler_selector_uses_B, Sprinkler_selector_B);
// Message to 'Cloudy_selector_cases_uses' from Exit factor
this.Cloudy_selector_cases_uses_B[3] = GateExitOp <bool> .CasesAverageConditional <Bernoulli, DistributionStructArray <Bernoulli, bool> >(Sprinkler_selector_B, Sprinkler_cond_Cloudy_F, this.Cloudy_selector_cases_uses_B[3]);
// Message to 'Cloudy_selector_cases_uses' from Replicate factor
Cloudy_selector_cases_uses_B_marginal = Replicate2BufferOp.Marginal <DistributionStructArray <Bernoulli, bool> >(this.Cloudy_selector_cases_uses_B, Cloudy_selector_cases_F, Cloudy_selector_cases_uses_B_marginal);
// Message to 'Cloudy_selector_cases_uses' from Replicate factor
Cloudy_selector_cases_uses_F[3] = Replicate2BufferOp.UsesAverageConditional <DistributionStructArray <Bernoulli, bool> >(this.Cloudy_selector_cases_uses_B, Cloudy_selector_cases_F, Cloudy_selector_cases_uses_B_marginal, 3, Cloudy_selector_cases_uses_F[3]);
// Message to 'Sprinkler' from Exit factor
Sprinkler_F = GateExitOp <bool> .ExitAverageConditional <Bernoulli>(Sprinkler_selector_B, Cloudy_selector_cases_uses_F[3], Sprinkler_cond_Cloudy_F, Sprinkler_F);
// Message to 'Sprinkler_selector_uses' from Replicate factor
Sprinkler_selector_uses_B_marginal = Replicate2BufferOp.Marginal <Bernoulli>(Sprinkler_selector_uses_B, Sprinkler_F, Sprinkler_selector_uses_B_marginal);
// Message to 'Sprinkler_selector_uses' from Replicate factor
Sprinkler_selector_uses_F[1] = Replicate2BufferOp.UsesAverageConditional <Bernoulli>(Sprinkler_selector_uses_B, Sprinkler_F, Sprinkler_selector_uses_B_marginal, 1, Sprinkler_selector_uses_F[1]);
// Message to 'Rain_use' from EnterPartial factor
this.Rain_use_B = GateEnterPartialOp <bool> .ValueAverageConditional <Bernoulli>(Rain_cond_Sprinkler_B, Sprinkler_selector_uses_F[1], Rain_F, new int[2] {
0, 1
}, this.Rain_use_B);
// Message to 'Cloudy_selector_cases_uses' from Exit factor
this.Cloudy_selector_cases_uses_B[1] = GateExitOp <bool> .CasesAverageConditional <Bernoulli, DistributionStructArray <Bernoulli, bool> >(this.Rain_use_B, Rain_cond_Cloudy_F, this.Cloudy_selector_cases_uses_B[1]);
this.OnProgressChanged(new ProgressChangedEventArgs(iteration));
}
DistributionStructArray <Bernoulli, bool> Cloudy_selector_cases_B = default(DistributionStructArray <Bernoulli, bool>);
// Create array for 'Cloudy_selector_cases' Backwards messages.
Cloudy_selector_cases_B = new DistributionStructArray <Bernoulli, bool>(2);
for (int _iv0 = 0; _iv0 < 2; _iv0++)
{
Cloudy_selector_cases_B[_iv0] = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
}
// Message to 'Cloudy_selector_cases' from Replicate factor
Cloudy_selector_cases_B = ReplicateOp.DefAverageConditional <DistributionStructArray <Bernoulli, bool> >(this.Cloudy_selector_cases_uses_B, Cloudy_selector_cases_B);
Bernoulli Cloudy_selector_B = ArrayHelper.MakeUniform <Bernoulli>(vBernoulli27);
// Message to 'Cloudy_selector' from Cases factor
Cloudy_selector_B = CasesOp.BAverageConditional(Cloudy_selector_cases_B);
// Message to 'Cloudy_marginal' from Variable factor
this.Cloudy_marginal_F = VariableOp.MarginalAverageConditional <Bernoulli>(Cloudy_selector_B, vBernoulli27, this.Cloudy_marginal_F);
this.Rain_marginal_F = ArrayHelper.MakeUniform <Bernoulli>(this.vBernoulli30);
// Message to 'Rain_marginal' from DerivedVariable factor
this.Rain_marginal_F = DerivedVariableOp.MarginalAverageConditional <Bernoulli>(this.Rain_use_B, Rain_F, this.Rain_marginal_F);
this.Sprinkler_marginal_F = ArrayHelper.MakeUniform <Bernoulli>(vBernoulli28);
// Message to 'Sprinkler_marginal' from DerivedVariable factor
this.Sprinkler_marginal_F = DerivedVariableOp.MarginalAverageConditional <Bernoulli>(Sprinkler_selector_B, Sprinkler_F, this.Sprinkler_marginal_F);
this.Changed_numberOfIterationsDecreased_WetGrass_iterationsDone = numberOfIterations;
}
/// <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;
}
/// <summary>Computations that depend on the observed value of Sprinkler and WetGrass</summary>
public void Changed_Sprinkler_WetGrass()
{
if (this.Changed_Sprinkler_WetGrass_iterationsDone == 1)
{
return;
}
// The constant 'vBernoulli1'
Bernoulli vBernoulli1 = Bernoulli.FromLogOdds(-2.1972245773362191);
this.Sprinkler_marginal = ArrayHelper.MakeUniform <Bernoulli>(vBernoulli1);
this.Sprinkler_marginal = Distribution.SetPoint <Bernoulli, bool>(this.Sprinkler_marginal, this.sprinkler);
// The constant 'vBernoulli5'
Bernoulli vBernoulli5 = Bernoulli.FromLogOdds(4.5951198501345889);
this.WetGrass_marginal = ArrayHelper.MakeUniform <Bernoulli>(vBernoulli5);
this.WetGrass_marginal = Distribution.SetPoint <Bernoulli, bool>(this.WetGrass_marginal, this.wetGrass);
// The constant 'vBernoulli3'
Bernoulli vBernoulli3 = Bernoulli.FromLogOdds(1.3862943611198908);
Bernoulli Rain_F = ArrayHelper.MakeUniform <Bernoulli>(vBernoulli3);
// The constant 'vBernoulli0'
Bernoulli vBernoulli0 = Bernoulli.FromLogOdds(0);
this.Cloudy_marginal_F = ArrayHelper.MakeUniform <Bernoulli>(vBernoulli0);
Bernoulli[] Cloudy_selector_cases_0_uses_B = default(Bernoulli[]);
// Create array for 'Cloudy_selector_cases_0_uses' Backwards messages.
Cloudy_selector_cases_0_uses_B = new Bernoulli[7];
for (int _ind = 0; _ind < 7; _ind++)
{
Cloudy_selector_cases_0_uses_B[_ind] = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
}
// Message to 'Cloudy_selector_cases_0_uses' from Random factor
Cloudy_selector_cases_0_uses_B[6] = Bernoulli.FromLogOdds(UnaryOp <bool> .LogEvidenceRatio <Bernoulli>(this.sprinkler, vBernoulli1));
Bernoulli Cloudy_selector_cases_0_B = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
// Message to 'Cloudy_selector_cases_0' from Replicate factor
Cloudy_selector_cases_0_B = ReplicateOp.DefAverageConditional <Bernoulli>(Cloudy_selector_cases_0_uses_B, Cloudy_selector_cases_0_B);
DistributionStructArray <Bernoulli, bool>[] Cloudy_selector_cases_uses_B = default(DistributionStructArray <Bernoulli, bool>[]);
// Create array for 'Cloudy_selector_cases_uses' Backwards messages.
Cloudy_selector_cases_uses_B = new DistributionStructArray <Bernoulli, bool> [3];
for (int _ind = 0; _ind < 3; _ind++)
{
// Create array for 'Cloudy_selector_cases_uses' Backwards messages.
Cloudy_selector_cases_uses_B[_ind] = new DistributionStructArray <Bernoulli, bool>(2);
for (int _iv0 = 0; _iv0 < 2; _iv0++)
{
Cloudy_selector_cases_uses_B[_ind][_iv0] = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
}
}
// Message to 'Cloudy_selector_cases_uses' from Copy factor
Cloudy_selector_cases_uses_B[0][0] = Factor.Copy <Bernoulli>(Cloudy_selector_cases_0_B);
DistributionStructArray <Bernoulli, bool> Rain_cond_Cloudy_F = default(DistributionStructArray <Bernoulli, bool>);
// Create array for 'Rain_cond_Cloudy' Forwards messages.
Rain_cond_Cloudy_F = new DistributionStructArray <Bernoulli, bool>(2);
for (int _gateind = 0; _gateind < 2; _gateind++)
{
Rain_cond_Cloudy_F[_gateind] = ArrayHelper.MakeUniform <Bernoulli>(vBernoulli3);
}
// Message to 'Rain_cond_Cloudy' from Copy factor
Rain_cond_Cloudy_F[0] = Factor.Copy <Bernoulli>(vBernoulli3);
// The constant 'vBernoulli4'
Bernoulli vBernoulli4 = Bernoulli.FromLogOdds(-1.3862943611198906);
// Message to 'Rain_cond_Cloudy' from Copy factor
Rain_cond_Cloudy_F[1] = Factor.Copy <Bernoulli>(vBernoulli4);
if (this.sprinkler)
{
this.Rain_cond_Sprinkler_0_selector_cases_0_B = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
// Message to 'Rain_cond_Sprinkler_0_selector_cases_0' from Random factor
this.Rain_cond_Sprinkler_0_selector_cases_0_B = Bernoulli.FromLogOdds(UnaryOp <bool> .LogEvidenceRatio <Bernoulli>(this.wetGrass, vBernoulli5));
// Create array for 'Rain_cond_Sprinkler_0_selector_cases' Backwards messages.
this.Rain_cond_Sprinkler_0_selector_cases_B = new DistributionStructArray <Bernoulli, bool>(2);
for (int _ind0 = 0; _ind0 < 2; _ind0++)
{
this.Rain_cond_Sprinkler_0_selector_cases_B[_ind0] = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
}
// Message to 'Rain_cond_Sprinkler_0_selector_cases' from Copy factor
this.Rain_cond_Sprinkler_0_selector_cases_B[0] = Factor.Copy <Bernoulli>(this.Rain_cond_Sprinkler_0_selector_cases_0_B);
}
// The constant 'vBernoulli6'
Bernoulli vBernoulli6 = Bernoulli.FromLogOdds(2.1972245773362196);
if (this.sprinkler)
{
this.Rain_cond_Sprinkler_0_selector_cases_1_B = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
// Message to 'Rain_cond_Sprinkler_0_selector_cases_1' from Random factor
this.Rain_cond_Sprinkler_0_selector_cases_1_B = Bernoulli.FromLogOdds(UnaryOp <bool> .LogEvidenceRatio <Bernoulli>(this.wetGrass, vBernoulli6));
// Message to 'Rain_cond_Sprinkler_0_selector_cases' from Copy factor
this.Rain_cond_Sprinkler_0_selector_cases_B[1] = Factor.Copy <Bernoulli>(this.Rain_cond_Sprinkler_0_selector_cases_1_B);
this.Rain_cond_Sprinkler_0_selector_B = ArrayHelper.MakeUniform <Bernoulli>(vBernoulli3);
// Message to 'Rain_cond_Sprinkler_0_selector' from Cases factor
this.Rain_cond_Sprinkler_0_selector_B = CasesOp.BAverageConditional(this.Rain_cond_Sprinkler_0_selector_cases_B);
}
// Message from use of 'Rain'
Bernoulli Rain_use_B = ArrayHelper.MakeUniform <Bernoulli>(vBernoulli3);
if (this.sprinkler)
{
// Message to 'Rain_use' from Copy factor
Rain_use_B = Factor.Copy <Bernoulli>(this.Rain_cond_Sprinkler_0_selector_B);
}
if (!this.sprinkler)
{
this.Rain_cond_Sprinkler_1_selector_cases_0_B = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
// Message to 'Rain_cond_Sprinkler_1_selector_cases_0' from Random factor
this.Rain_cond_Sprinkler_1_selector_cases_0_B = Bernoulli.FromLogOdds(UnaryOp <bool> .LogEvidenceRatio <Bernoulli>(this.wetGrass, vBernoulli6));
// Create array for 'Rain_cond_Sprinkler_1_selector_cases' Backwards messages.
this.Rain_cond_Sprinkler_1_selector_cases_B = new DistributionStructArray <Bernoulli, bool>(2);
for (int _ind0 = 0; _ind0 < 2; _ind0++)
{
this.Rain_cond_Sprinkler_1_selector_cases_B[_ind0] = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
}
// Message to 'Rain_cond_Sprinkler_1_selector_cases' from Copy factor
this.Rain_cond_Sprinkler_1_selector_cases_B[0] = Factor.Copy <Bernoulli>(this.Rain_cond_Sprinkler_1_selector_cases_0_B);
}
// The constant 'vBernoulli8'
Bernoulli vBernoulli8 = Bernoulli.FromLogOdds(Double.NegativeInfinity);
if (!this.sprinkler)
{
this.Rain_cond_Sprinkler_1_selector_cases_1_B = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
// Message to 'Rain_cond_Sprinkler_1_selector_cases_1' from Random factor
this.Rain_cond_Sprinkler_1_selector_cases_1_B = Bernoulli.FromLogOdds(UnaryOp <bool> .LogEvidenceRatio <Bernoulli>(this.wetGrass, vBernoulli8));
// Message to 'Rain_cond_Sprinkler_1_selector_cases' from Copy factor
this.Rain_cond_Sprinkler_1_selector_cases_B[1] = Factor.Copy <Bernoulli>(this.Rain_cond_Sprinkler_1_selector_cases_1_B);
this.Rain_cond_Sprinkler_1_selector_B = ArrayHelper.MakeUniform <Bernoulli>(vBernoulli3);
// Message to 'Rain_cond_Sprinkler_1_selector' from Cases factor
this.Rain_cond_Sprinkler_1_selector_B = CasesOp.BAverageConditional(this.Rain_cond_Sprinkler_1_selector_cases_B);
// Message to 'Rain_use' from Copy factor
Rain_use_B = Factor.Copy <Bernoulli>(this.Rain_cond_Sprinkler_1_selector_B);
}
// Rain_use_B is now updated in all contexts
// Message to 'Cloudy_selector_cases_uses' from Exit factor
Cloudy_selector_cases_uses_B[1] = GateExitOp <bool> .CasesAverageConditional <Bernoulli, DistributionStructArray <Bernoulli, bool> >(Rain_use_B, Rain_cond_Cloudy_F, Cloudy_selector_cases_uses_B[1]);
Bernoulli[] Cloudy_selector_cases_1_uses_B = default(Bernoulli[]);
// Create array for 'Cloudy_selector_cases_1_uses' Backwards messages.
Cloudy_selector_cases_1_uses_B = new Bernoulli[7];
for (int _ind = 0; _ind < 7; _ind++)
{
Cloudy_selector_cases_1_uses_B[_ind] = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
}
// Message to 'Cloudy_selector_cases_1_uses' from Random factor
Cloudy_selector_cases_1_uses_B[6] = Bernoulli.FromLogOdds(UnaryOp <bool> .LogEvidenceRatio <Bernoulli>(this.sprinkler, vBernoulli0));
Bernoulli Cloudy_selector_cases_1_B = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
// Message to 'Cloudy_selector_cases_1' from Replicate factor
Cloudy_selector_cases_1_B = ReplicateOp.DefAverageConditional <Bernoulli>(Cloudy_selector_cases_1_uses_B, Cloudy_selector_cases_1_B);
// Message to 'Cloudy_selector_cases_uses' from Copy factor
Cloudy_selector_cases_uses_B[2][1] = Factor.Copy <Bernoulli>(Cloudy_selector_cases_1_B);
DistributionStructArray <Bernoulli, bool> Cloudy_selector_cases_B = default(DistributionStructArray <Bernoulli, bool>);
// Create array for 'Cloudy_selector_cases' Backwards messages.
Cloudy_selector_cases_B = new DistributionStructArray <Bernoulli, bool>(2);
for (int _iv0 = 0; _iv0 < 2; _iv0++)
{
Cloudy_selector_cases_B[_iv0] = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
}
// Message to 'Cloudy_selector_cases' from Replicate factor
Cloudy_selector_cases_B = ReplicateOp.DefAverageConditional <DistributionStructArray <Bernoulli, bool> >(Cloudy_selector_cases_uses_B, Cloudy_selector_cases_B);
Bernoulli Cloudy_selector_B = ArrayHelper.MakeUniform <Bernoulli>(vBernoulli0);
// Message to 'Cloudy_selector' from Cases factor
Cloudy_selector_B = CasesOp.BAverageConditional(Cloudy_selector_cases_B);
// Message to 'Cloudy_marginal' from Variable factor
this.Cloudy_marginal_F = VariableOp.MarginalAverageConditional <Bernoulli>(Cloudy_selector_B, vBernoulli0, this.Cloudy_marginal_F);
DistributionStructArray <Bernoulli, bool> Cloudy_selector_cases_F = default(DistributionStructArray <Bernoulli, bool>);
// Create array for 'Cloudy_selector_cases' Forwards messages.
Cloudy_selector_cases_F = new DistributionStructArray <Bernoulli, bool>(2);
for (int _iv0 = 0; _iv0 < 2; _iv0++)
{
Cloudy_selector_cases_F[_iv0] = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
}
DistributionStructArray <Bernoulli, bool>[] Cloudy_selector_cases_uses_F = default(DistributionStructArray <Bernoulli, bool>[]);
// Create array for 'Cloudy_selector_cases_uses' Forwards messages.
Cloudy_selector_cases_uses_F = new DistributionStructArray <Bernoulli, bool> [3];
for (int _ind = 0; _ind < 3; _ind++)
{
// Create array for 'Cloudy_selector_cases_uses' Forwards messages.
Cloudy_selector_cases_uses_F[_ind] = new DistributionStructArray <Bernoulli, bool>(2);
for (int _iv0 = 0; _iv0 < 2; _iv0++)
{
Cloudy_selector_cases_uses_F[_ind][_iv0] = ArrayHelper.MakeUniform <Bernoulli>(new Bernoulli());
}
}
// Message to 'Cloudy_selector_cases' from Cases factor
Cloudy_selector_cases_F = CasesOp.CasesAverageConditional <DistributionStructArray <Bernoulli, bool> >(vBernoulli0, Cloudy_selector_cases_F);
// Buffer for Replicate2BufferOp.UsesAverageConditional<DistributionStructArray<Bernoulli,bool>>
DistributionStructArray <Bernoulli, bool> Cloudy_selector_cases_uses_B_marginal = default(DistributionStructArray <Bernoulli, bool>);
// Message to 'Cloudy_selector_cases_uses' from Replicate factor
Cloudy_selector_cases_uses_B_marginal = Replicate2BufferOp.MarginalInit <DistributionStructArray <Bernoulli, bool> >(Cloudy_selector_cases_F);
// Message to 'Cloudy_selector_cases_uses' from Replicate factor
Cloudy_selector_cases_uses_B_marginal = Replicate2BufferOp.Marginal <DistributionStructArray <Bernoulli, bool> >(Cloudy_selector_cases_uses_B, Cloudy_selector_cases_F, Cloudy_selector_cases_uses_B_marginal);
// Message to 'Cloudy_selector_cases_uses' from Replicate factor
Cloudy_selector_cases_uses_F[1] = Replicate2BufferOp.UsesAverageConditional <DistributionStructArray <Bernoulli, bool> >(Cloudy_selector_cases_uses_B, Cloudy_selector_cases_F, Cloudy_selector_cases_uses_B_marginal, 1, Cloudy_selector_cases_uses_F[1]);
this.Rain_marginal_F = ArrayHelper.MakeUniform <Bernoulli>(vBernoulli3);
// Message to 'Rain' from Exit factor
Rain_F = GateExitOp <bool> .ExitAverageConditional <Bernoulli>(Rain_use_B, Cloudy_selector_cases_uses_F[1], Rain_cond_Cloudy_F, Rain_F);
// Message to 'Rain_marginal' from DerivedVariable factor
this.Rain_marginal_F = DerivedVariableOp.MarginalAverageConditional <Bernoulli>(Rain_use_B, Rain_F, this.Rain_marginal_F);
this.Changed_Sprinkler_WetGrass_iterationsDone = 1;
}
