/// <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); }