public static void MaxOfOthers_Linear(IList <Gaussian> array, IList <Gaussian> result)
{
if (array.Count == 0)
{
return;
}
if (array.Count == 1)
{
result[0] = Gaussian.Uniform();
return;
}
var maxBefore = result;
// initialize maxBefore[i] to max(array[0..i-1])
maxBefore[1] = array[0];
for (int i = 2; i < array.Count; i++)
{
maxBefore[i] = MaxGaussianOp.MaxAverageConditional(Gaussian.Uniform(), maxBefore[i - 1], array[i - 1]);
}
Gaussian maxAfter = array[array.Count - 1];
for (int i = array.Count - 2; i >= 1; i--)
{
result[i] = MaxGaussianOp.MaxAverageConditional(Gaussian.Uniform(), maxAfter, maxBefore[i]);
maxAfter = MaxGaussianOp.MaxAverageConditional(Gaussian.Uniform(), maxAfter, array[i]);
}
result[0] = maxAfter;
}
/// <include file='FactorDocs.xml' path='factor_docs/message_op_class[@name="IndexOfMaximumOp_Fast"]/message_doc[@name="IndexOfMaximumDoubleAverageConditional(IList{Gaussian}, Discrete)"]/*'/>
public static Discrete IndexOfMaximumDoubleAverageConditional2(IList <Gaussian> list, Discrete result)
{
// Fast approximate calculation of downward message
// TODO: sort list first
// best accuracy is achieved by processing in decreasing order of means
Gaussian max = list[0];
Vector probs = result.GetWorkspace();
probs[0] = 1.0;
for (int i = 1; i < list.Count; i++)
{
Gaussian A = max;
Gaussian B = list[i];
double pMax = ProbGreater(A, B).GetProbTrue();
for (int j = 0; j < i; j++)
{
probs[j] *= pMax;
}
probs[i] = 1 - pMax;
max = MaxGaussianOp.MaxAverageConditional(Gaussian.Uniform(), A, B);
}
result.SetProbs(probs);
return(result);
}
public static void MaxOfOthers_Quadratic(IList <Gaussian> array, IList <Gaussian> result)
{
if (array.Count == 0)
{
return;
}
if (array.Count == 1)
{
result[0] = Gaussian.Uniform();
return;
}
var maxBefore = Gaussian.Uniform();
for (int i = 0; i < array.Count - 1; i++)
{
// maxBefore is max(array[..i-1])
Gaussian maxBeforeAndNext, maxBeforeAndCurrent;
if (i == 0)
{
maxBeforeAndNext = array[i + 1];
maxBeforeAndCurrent = array[i];
}
else
{
maxBeforeAndNext = MaxGaussianOp.MaxAverageConditional(Gaussian.Uniform(), maxBefore, array[i + 1]);
maxBeforeAndCurrent = MaxGaussianOp.MaxAverageConditional(Gaussian.Uniform(), maxBefore, array[i]);
}
// maxBeforeAndNext is max(array[..i-1], array[i+1])
var max = maxBeforeAndNext;
for (int j = i + 2; j < array.Count; j++)
{
// max is max(array[..j-1] except i)
max = MaxGaussianOp.MaxAverageConditional(Gaussian.Uniform(), max, array[j]);
}
result[i] = max;
maxBefore = maxBeforeAndCurrent;
}
result[array.Count - 1] = maxBefore;
}