/// <summary>EP 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 a distribution matching the moments of <c>sample</c> as the random arguments are varied. The formula is <c>proj[p(sample) sum_(probTrue) p(probTrue) factor(sample,probTrue)]/p(sample)</c>.</para>
/// </remarks>
/// <exception cref="ImproperMessageException">
/// <paramref name="probTrue" /> is not a proper distribution.</exception>
public static SparseBernoulliList SampleAverageConditional([SkipIfUniform] SparseBetaList probTrue, SparseBernoulliList result)
{
result.SetToFunction(probTrue, pt => BernoulliFromBetaOp.SampleAverageConditional(pt));
return(result);
}
/// <summary>EP 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 SampleAverageConditional(ISparseList <double> probTrue, SparseBernoulliList result)
{
result.SetToFunction(probTrue, pt => BernoulliFromBetaOp.SampleAverageConditional(pt));
return(result);
}