/// <summary>VMP message to <c>sample</c>.</summary>
/// <param name="probTrue">Incoming message from <c>probTrue</c>. Must be a proper distribution. If any element is uniform, the result will be uniform.</param>
/// <param name="result">Modified to contain the outgoing message.</param>
/// <returns>
/// <paramref name="result" />
/// </returns>
/// <remarks>
/// <para>The outgoing message is the exponential of the average log-factor value, where the average is over all arguments except <c>sample</c>. The formula is <c>exp(sum_(probTrue) p(probTrue) log(factor(sample,probTrue)))</c>.</para>
/// </remarks>
/// <exception cref="ImproperMessageException">
/// <paramref name="probTrue" /> is not a proper distribution.</exception>
public static SparseBernoulliList SampleAverageLogarithm([SkipIfUniform] SparseBetaList probTrue, SparseBernoulliList result)
{
result.SetToFunction(probTrue, pt => BernoulliFromBetaOp.SampleAverageLogarithm(pt));
return(result);
}
/// <summary>VMP message to <c>sample</c>.</summary>
/// <param name="probTrue">Constant value for <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 the factor viewed as a function of <c>sample</c> conditioned on the given values.</para>
/// </remarks>
public static SparseBernoulliList SampleAverageLogarithm(ISparseList <double> probTrue, SparseBernoulliList result)
{
result.SetToFunction(probTrue, pt => BernoulliFromBetaOp.SampleAverageLogarithm(pt));
return(result);
}