/// <summary>EP message to <c>probTrue</c>.</summary>
/// <param name="sample">Incoming message from <c>sample</c>. Must be a proper distribution. If any element is uniform, the result will be uniform.</param>
/// <param name="probTrue">Incoming message from <c>probTrue</c>.</param>
/// <param name="result">Modified to contain the outgoing message.</param>
/// <returns>
/// <paramref name="result" />
/// </returns>
/// <remarks>
/// <para>The outgoing message is a distribution matching the moments of <c>probTrue</c> as the random arguments are varied. The formula is <c>proj[p(probTrue) sum_(sample) p(sample) factor(sample,probTrue)]/p(probTrue)</c>.</para>
/// </remarks>
/// <exception cref="ImproperMessageException">
/// <paramref name="sample" /> is not a proper distribution.</exception>
public static SparseBetaList ProbTrueAverageConditional([SkipIfUniform] BernoulliIntegerSubset sample, SparseBetaList probTrue, SparseBetaList result)
{
Func <Bernoulli, Beta, Beta> f = BernoulliFromBetaOp.ProbTrueAverageConditional;
result.SetTo(f.Map(sample.SparseBernoulliList, probTrue));
return(result);
}
