/// <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);
}