/// <summary>
/// Returns the maximum difference between the parameters of this sparse Gaussian list
/// and another
/// </summary>
/// <param name="thatd">The other sparse Gaussian list</param>
/// <returns>The maximum difference</returns>
/// <remarks><c>a.MaxDiff(b) == b.MaxDiff(a)</c></remarks>
public double MaxDiff(object thatd)
{
SparseGaussianList that = (SparseGaussianList)thatd;
return(Reduce <double, Gaussian>(
double.NegativeInfinity, that, (x, y, z) => Math.Max(x, y.MaxDiff(z))));
}
/// <summary>
/// Creates a sparse Gaussian list of a given size, with given mean and precision vectors.
/// </summary>
/// <param name="mean">The desired mean.</param>
/// <param name="precision">The desired precision.</param>
/// <param name="tolerance">The tolerance for the approximation</param>
public static SparseGaussianList FromMeanAndPrecision(
IList <double> mean, IList <double> precision, double tolerance)
{
var result = new SparseGaussianList(mean.Count, tolerance);
result.SetToFunction(mean, precision, (m, p) => Gaussian.FromMeanAndPrecision(m, p));
return(result);
}
/// <summary>
/// Copy constructor
/// </summary>
/// <param name="that"></param>
protected SparseGaussianList(SparseGaussianList that) : base(that)
{
}
/// <summary>
/// The expected logarithm of that sparse Gaussian list under this sparse Gaussian list.
/// </summary>
/// <param name="that"></param>
/// <returns></returns>
public double GetAverageLog(SparseGaussianList that)
{
return(Reduce <double, Gaussian>(0.0, that, (x, y, z) => x + y.GetAverageLog(z)));
}
/// <summary>
/// Returns the log of the integral of the product of this sparse Gaussian list and another sparse Gaussian list raised to a power
/// </summary>
/// <param name="that"></param>
public double GetLogAverageOfPower(SparseGaussianList that, double power)
{
return(Reduce <double, Gaussian>(0.0, that, (x, y, z) => x + y.GetLogAverageOfPower(z, power)));
}
/// <summary>
/// Creates a sparse Gaussian list whose elements match the means and variances
/// of the weighted sums of the elements of two other sparse Gaussian lists.
/// </summary>
/// <param name="weight1">The first weight</param>
/// <param name="value1">The first sparse Gaussian list</param>
/// <param name="weight2">The second weight</param>
/// <param name="value2">The second sparse Gaussian list</param>
public void SetToSum(double weight1, SparseGaussianList value1, double weight2, SparseGaussianList value2)
{
SetToFunction(value1, value2, (g1, g2) => { var g = new Gaussian(); g.SetToSum(weight1, g1, weight2, g2); return(g); });
}
/// <summary>
/// Sets this sparse Gaussian list to the ratio of two other sparse Gaussian lists
/// </summary>
/// <param name="numerator"></param>
/// <param name="denominator"></param>
public void SetToRatio(SparseGaussianList numerator, SparseGaussianList denominator)
{
SetToFunction(numerator, denominator, (gn, gd) => gn / gd);
}
/// <summary>
/// Sets this sparse Gaussian list to the power of another sparse Gaussian list
/// </summary>
/// <param name="value"></param>
/// <param name="exponent"></param>
public void SetToPower(SparseGaussianList value, double exponent)
{
SetToFunction(value, g => g ^ exponent);
}
/// <summary>
/// Sets this sparse Gaussian list to the product of two other sparse Gaussian lists
/// </summary>
/// <param name="a"></param>
/// <param name="b"></param>
public void SetToProduct(SparseGaussianList a, SparseGaussianList b)
{
SetToFunction(a, b, (ga, gb) => ga * gb);
}
/// <summary>
/// Sets this sparse Gaussian list to another sparse Gaussian list
/// </summary>
/// <param name="value"></param>
public void SetTo(SparseGaussianList value)
{
base.SetTo(value);
}
