/// <summary>EP message to <c>second</c>.</summary>
/// <param name="concat">Incoming message from <c>concat</c>. Must be a proper distribution. If any element is uniform, the result will be uniform.</param>
/// <param name="first">Incoming message from <c>first</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>second</c> as the random arguments are varied. The formula is <c>proj[p(second) sum_(concat,first) p(concat,first) factor(concat,first,second)]/p(second)</c>.</para>
/// </remarks>
/// <exception cref="ImproperMessageException">
/// <paramref name="concat" /> is not a proper distribution.</exception>
public static VectorGaussian SecondAverageConditional([SkipIfUniform] VectorGaussian concat, VectorGaussian first, VectorGaussian result)
{
if (first.IsPointMass)
{
return(SecondAverageConditional(concat, first.Point, result));
}
int dim1 = first.Dimension;
VectorGaussian concatTimesFirst = new VectorGaussian(concat.Dimension);
concatTimesFirst.MeanTimesPrecision.SetSubvector(0, first.MeanTimesPrecision);
concatTimesFirst.Precision.SetSubmatrix(0, 0, first.Precision);
concatTimesFirst.SetToProduct(concatTimesFirst, concat);
concatTimesFirst.GetMarginal(dim1, result);
return(result);
}
/// <summary>EP message to <c>first</c>.</summary>
/// <param name="concat">Incoming message from <c>concat</c>. Must be a proper distribution. If any element is uniform, the result will be uniform.</param>
/// <param name="second">Incoming message from <c>second</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>first</c> as the random arguments are varied. The formula is <c>proj[p(first) sum_(concat,second) p(concat,second) factor(concat,first,second)]/p(first)</c>.</para>
/// </remarks>
/// <exception cref="ImproperMessageException">
/// <paramref name="concat" /> is not a proper distribution.</exception>
public static VectorGaussian FirstAverageConditional([SkipIfUniform] VectorGaussian concat, VectorGaussian second, VectorGaussian result)
{
if (second.IsPointMass)
{
return(FirstAverageConditional(concat, second.Point, result));
}
int dim1 = result.Dimension;
VectorGaussian concatTimesSecond = new VectorGaussian(concat.Dimension);
concatTimesSecond.MeanTimesPrecision.SetSubvector(dim1, second.MeanTimesPrecision);
concatTimesSecond.Precision.SetSubmatrix(dim1, dim1, second.Precision);
concatTimesSecond.SetToProduct(concatTimesSecond, concat);
concatTimesSecond.GetMarginal(0, result);
return(result);
}
/// <summary>
/// EP message to 'second'
/// </summary>
/// <param name="concat">Incoming message from 'concat'. Must be a proper distribution. If any element is uniform, the result will be uniform.</param>
/// <param name="first">Incoming message from 'first'.</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 'second' as the random arguments are varied.
/// The formula is <c>proj[p(second) sum_(concat,first) p(concat,first) factor(concat,first,second)]/p(second)</c>.
/// </para></remarks>
/// <exception cref="ImproperMessageException"><paramref name="concat"/> is not a proper distribution</exception>
public static VectorGaussian SecondAverageConditional([SkipIfUniform] VectorGaussian concat, VectorGaussian first, VectorGaussian result)
{
if (first.IsPointMass) return SecondAverageConditional(concat, first.Point, result);
int dim1 = first.Dimension;
VectorGaussian concatTimesFirst = new VectorGaussian(concat.Dimension);
concatTimesFirst.MeanTimesPrecision.SetSubvector(0, first.MeanTimesPrecision);
concatTimesFirst.Precision.SetSubmatrix(0, 0, first.Precision);
concatTimesFirst.SetToProduct(concatTimesFirst, concat);
concatTimesFirst.GetMarginal(dim1, result);
return result;
}
/// <summary>
/// EP message to 'first'
/// </summary>
/// <param name="concat">Incoming message from 'concat'. Must be a proper distribution. If any element is uniform, the result will be uniform.</param>
/// <param name="second">Incoming message from 'second'.</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 'first' as the random arguments are varied.
/// The formula is <c>proj[p(first) sum_(concat,second) p(concat,second) factor(concat,first,second)]/p(first)</c>.
/// </para></remarks>
/// <exception cref="ImproperMessageException"><paramref name="concat"/> is not a proper distribution</exception>
public static VectorGaussian FirstAverageConditional([SkipIfUniform] VectorGaussian concat, VectorGaussian second, VectorGaussian result)
{
if (second.IsPointMass) return FirstAverageConditional(concat, second.Point, result);
int dim1 = result.Dimension;
VectorGaussian concatTimesSecond = new VectorGaussian(concat.Dimension);
concatTimesSecond.MeanTimesPrecision.SetSubvector(dim1, second.MeanTimesPrecision);
concatTimesSecond.Precision.SetSubmatrix(dim1, dim1, second.Precision);
concatTimesSecond.SetToProduct(concatTimesSecond, concat);
concatTimesSecond.GetMarginal(0, result);
return result;
}