/// <include file='FactorDocs.xml' path='factor_docs/message_op_class[@name="DoublePlusOp"]/message_doc[@name="AAverageConditional(Gaussian, Gaussian)"]/*'/>
public static Gaussian AAverageConditional([SkipIfUniform] Gaussian Sum, [SkipIfUniform] Gaussian b)
{
if (Sum.IsPointMass)
{
return(AAverageConditional(Sum.Point, b));
}
if (b.IsPointMass)
{
return(AAverageConditional(Sum, b.Point));
}
if (Sum.IsUniform() || b.IsUniform())
{
return(Gaussian.Uniform());
}
if (Sum.Precision == b.Precision)
{
// This formula works even when Precision == 0
return(Gaussian.FromNatural(MMath.Average(Sum.MeanTimesPrecision, -b.MeanTimesPrecision), Sum.Precision / 2));
}
double prec = Sum.Precision + b.Precision;
if (prec == 0)
{
throw new ImproperDistributionException(Sum.IsProper() ? b : Sum);
}
return(Gaussian.FromNatural((Sum.MeanTimesPrecision * b.Precision - b.MeanTimesPrecision * Sum.Precision) / prec, Sum.Precision * b.Precision / prec));
}
/// <summary>
/// Returns the value x such that GetProbLessThan(x) == probability.
/// </summary>
/// <param name="probability">A real number in [0,1].</param>
/// <returns></returns>
public double GetQuantile(double probability)
{
if (probability < 0)
{
throw new ArgumentOutOfRangeException("probability < 0");
}
if (probability > 1)
{
throw new ArgumentOutOfRangeException("probability > 1");
}
if (this.IsPointMass)
{
return((probability == 1.0) ? MMath.NextDouble(this.Point) : this.Point);
}
else if (!IsProper())
{
throw new ImproperDistributionException(this);
}
else if (MMath.AreEqual(probability, 0))
{
return(0);
}
else if (MMath.AreEqual(probability, 1))
{
return(double.PositiveInfinity);
}
else if (Shape == 1)
{
// cdf is 1 - exp(-x*rate)
return(-Math.Log(1 - probability) / Rate);
}
else
{
// Binary search
double lowerBound = 0;
double upperBound = double.MaxValue;
while (lowerBound < upperBound)
{
double average = MMath.Average(lowerBound, upperBound);
double p = GetProbLessThan(average);
if (p == probability)
{
return(average);
}
else if (p < probability)
{
lowerBound = MMath.NextDouble(average);
}
else
{
upperBound = MMath.PreviousDouble(average);
}
}
return(lowerBound);
}
}
public void WeightedAverageTest()
{
Assert.Equal(Environment.Is64BitProcess ? 3.86361619394904E-311 : 3.86361619394162E-311, MMath.WeightedAverage(0.82912896852490248, 2.5484859206000203E-311, 3.50752234977395E-313, 31.087830618727477));
Assert.Equal(MMath.WeightedAverage(0.1, double.MinValue, 0.01, double.MinValue), double.MinValue);
Assert.Equal(MMath.WeightedAverage(0.1, -double.Epsilon, double.MaxValue, -double.Epsilon), -double.Epsilon);
Assert.Equal(MMath.WeightedAverage(1e-100, 2e-250, 1e-100, 4e-250), MMath.Average(2e-250, 4e-250));
Assert.Equal(MMath.WeightedAverage(1e100, 2e250, 1e100, 4e250), MMath.Average(2e250, 4e250));
Assert.Equal(MMath.WeightedAverage(0, 0, 0.1, -double.Epsilon), -double.Epsilon);
Assert.Equal(MMath.WeightedAverage(0.1, -double.Epsilon, 0, double.NegativeInfinity), -double.Epsilon);
Assert.False(double.IsNaN(MMath.WeightedAverage(1.7976931348623157E+308, double.NegativeInfinity, 4.94065645841247E-324, double.NegativeInfinity)));
Assert.False(double.IsNaN(MMath.WeightedAverage(0.01, double.NegativeInfinity, double.MaxValue, double.MaxValue)));
Assert.False(double.IsNaN(MMath.WeightedAverage(0.01, double.NegativeInfinity, double.Epsilon, double.NegativeInfinity)));
Assert.Equal(double.MaxValue, MMath.WeightedAverage(double.MaxValue, double.MaxValue, double.MaxValue, double.MaxValue));
const int limit = 2_000_000;
int count = 0;
Parallel.ForEach(OperatorTests.DoublesAtLeastZero(), wa =>
{
Parallel.ForEach(OperatorTests.DoublesAtLeastZero(), wb =>
{
if (count > limit)
{
return;
}
Trace.WriteLine($"wa = {wa}, wb = {wb}");
foreach (var a in OperatorTests.Doubles())
{
if (count > limit)
{
break;
}
foreach (var b in OperatorTests.Doubles())
{
if (count > limit)
{
break;
}
if (double.IsNaN(a + b))
{
continue;
}
double midpoint = MMath.WeightedAverage(wa, a, wb, b);
Assert.True(midpoint >= System.Math.Min(a, b), $"Failed assertion: MMath.WeightedAverage({wa:r}, {a:r}, {wb:r}, {b:r}) {midpoint} >= {System.Math.Min(a, b)}");
Assert.True(midpoint <= System.Math.Max(a, b), $"Failed assertion: MMath.WeightedAverage({wa:r}, {a:r}, {wb:r}, {b:r}) {midpoint} <= {System.Math.Max(a, b)}");
if (wa == wb)
{
Assert.Equal(MMath.Average(a, b), midpoint);
}
Interlocked.Add(ref count, 1);
}
}
});
});
}
public void WeightedAverageTest()
{
Assert.Equal(MMath.WeightedAverage(0.1, double.MinValue, 0.01, double.MinValue), double.MinValue);
Assert.Equal(MMath.WeightedAverage(0.1, -double.Epsilon, double.MaxValue, -double.Epsilon), -double.Epsilon);
Assert.Equal(MMath.WeightedAverage(1e-100, 2e-250, 1e-100, 4e-250), MMath.Average(2e-250, 4e-250));
Assert.Equal(MMath.WeightedAverage(1e100, 2e250, 1e100, 4e250), MMath.Average(2e250, 4e250));
Assert.Equal(MMath.WeightedAverage(0, 0, 0.1, -double.Epsilon), -double.Epsilon);
Assert.Equal(MMath.WeightedAverage(0.1, -double.Epsilon, 0, double.NegativeInfinity), -double.Epsilon);
Assert.False(double.IsNaN(MMath.WeightedAverage(1.7976931348623157E+308, double.NegativeInfinity, 4.94065645841247E-324, double.NegativeInfinity)));
Assert.False(double.IsNaN(MMath.WeightedAverage(0.01, double.NegativeInfinity, double.MaxValue, double.MaxValue)));
Assert.False(double.IsNaN(MMath.WeightedAverage(0.01, double.NegativeInfinity, double.Epsilon, double.NegativeInfinity)));
Assert.Equal(double.MaxValue, MMath.WeightedAverage(double.MaxValue, double.MaxValue, double.MaxValue, double.MaxValue));
const int limit = 2_000_000;
int count = 0;
Parallel.ForEach(OperatorTests.DoublesAtLeastZero(), wa =>
{
Parallel.ForEach(OperatorTests.DoublesAtLeastZero(), wb =>
{
if (count > limit)
{
return;
}
Trace.WriteLine($"wa = {wa}, wb = {wb}");
foreach (var a in OperatorTests.Doubles())
{
if (count > limit)
{
break;
}
foreach (var b in OperatorTests.Doubles())
{
if (count > limit)
{
break;
}
if (double.IsNaN(a + b))
{
continue;
}
double midpoint = MMath.WeightedAverage(wa, a, wb, b);
Assert.True(midpoint >= System.Math.Min(a, b), $"Failed assertion: {midpoint} >= {System.Math.Min(a, b)}, wa={wa:r}, a={a:r}, wb={wb:r}, b={b:r}");
Assert.True(midpoint <= System.Math.Max(a, b), $"Failed assertion: {midpoint} <= {System.Math.Max(a, b)}, wa={wa:r}, a={a:r}, wb={wb:r}, b={b:r}");
if (wa == wb)
{
Assert.Equal(MMath.Average(a, b), midpoint);
}
Interlocked.Add(ref count, 1);
}
}
});
});
}
public static double GetMidpoint(double lower, double upper)
{
double midpoint;
if (double.IsNegativeInfinity(lower))
{
if (double.IsPositiveInfinity(upper))
{
midpoint = 0.0;
}
else if (upper > 0)
{
midpoint = -upper;
}
else if (upper < 0)
{
midpoint = 2 * upper;
}
else
{
midpoint = -1;
}
}
else if (double.IsPositiveInfinity(upper))
{
if (lower > 0)
{
midpoint = 2 * lower;
}
else if (lower < 0)
{
midpoint = -lower;
}
else
{
midpoint = 1;
}
}
else
{
midpoint = MMath.Average(lower, upper);
}
return(midpoint);
}
/// <include file='FactorDocs.xml' path='factor_docs/message_op_class[@name="DoublePlusOp"]/message_doc[@name="AAverageConditional(Gaussian, Gaussian)"]/*'/>
public static Gaussian AAverageConditional([SkipIfUniform] Gaussian Sum, [SkipIfUniform] Gaussian b)
{
if (Sum.IsPointMass)
{
return(AAverageConditional(Sum.Point, b));
}
if (b.IsPointMass)
{
return(AAverageConditional(Sum, b.Point));
}
if (Sum.IsUniform() || b.IsUniform())
{
return(Gaussian.Uniform());
}
if (Sum.Precision == b.Precision)
{
// This formula works even when Precision == 0
return(Gaussian.FromNatural(MMath.Average(Sum.MeanTimesPrecision, -b.MeanTimesPrecision), Sum.Precision / 2));
}
double meanTimesPrec, prec;
if (Sum.Precision >= b.Precision)
{
double precOverSumPrec = 1 + b.Precision / Sum.Precision; // can overflow if b.Precision > Sum.Precision
if (precOverSumPrec == 0)
{
throw new ImproperDistributionException(Sum.IsProper() ? b : Sum);
}
meanTimesPrec = (Sum.MeanTimesPrecision / Sum.Precision * b.Precision - b.MeanTimesPrecision) / precOverSumPrec;
prec = b.Precision / precOverSumPrec;
}
else // Sum.Precision < b.Precision
{
double precOverbPrec = Sum.Precision / b.Precision + 1; // can overflow if Sum.Precision > b.Precision
if (precOverbPrec == 0)
{
throw new ImproperDistributionException(Sum.IsProper() ? b : Sum);
}
meanTimesPrec = (Sum.MeanTimesPrecision - b.MeanTimesPrecision / b.Precision * Sum.Precision) / precOverbPrec;
prec = Sum.Precision / precOverbPrec;
}
return(Gaussian.FromNatural(meanTimesPrec, prec));
}
/// <include file='FactorDocs.xml' path='factor_docs/message_op_class[@name="DoublePlusOp"]/message_doc[@name="SumAverageConditional(Gaussian, Gaussian)"]/*'/>
public static Gaussian SumAverageConditional([SkipIfUniform] Gaussian a, [SkipIfUniform] Gaussian b)
{
if (a.IsPointMass)
{
return(SumAverageConditional(a.Point, b));
}
if (b.IsPointMass)
{
return(SumAverageConditional(a, b.Point));
}
if (a.IsUniform() || b.IsUniform())
{
return(Gaussian.Uniform());
}
if (a.Precision == b.Precision)
{
// This formula works even when Precision == 0
return(Gaussian.FromNatural(MMath.Average(a.MeanTimesPrecision, b.MeanTimesPrecision), a.Precision / 2));
}
double meanTimesPrec, prec;
if (a.Precision >= b.Precision)
{
double precOverAPrec = 1 + b.Precision / a.Precision;
if (precOverAPrec == 0)
{
throw new ImproperDistributionException(a.IsProper() ? b : a);
}
meanTimesPrec = (a.MeanTimesPrecision / a.Precision * b.Precision + b.MeanTimesPrecision) / precOverAPrec;
prec = b.Precision / precOverAPrec;
}
else
{
double precOverBPrec = a.Precision / b.Precision + 1;
if (precOverBPrec == 0)
{
throw new ImproperDistributionException(a.IsProper() ? b : a);
}
meanTimesPrec = (a.MeanTimesPrecision + b.MeanTimesPrecision / b.Precision * a.Precision) / precOverBPrec;
prec = a.Precision / precOverBPrec;
}
return(Gaussian.FromNatural(meanTimesPrec, prec));
}
/// <summary>
/// Returns the largest value x such that GetProbLessThan(x) <= probability.
/// </summary>
/// <param name="probability">A real number in [0,1].</param>
/// <returns></returns>
public double GetQuantile(double probability)
{
if (probability < 0)
{
throw new ArgumentOutOfRangeException(nameof(probability), "probability < 0");
}
if (probability > 1.0)
{
throw new ArgumentOutOfRangeException(nameof(probability), "probability > 1.0");
}
// compute the min and max of the retained items
double lowerBound = double.PositiveInfinity, upperBound = double.NegativeInfinity;
for (int bufferIndex = 0; bufferIndex < buffers.Length; bufferIndex++)
{
double[] buffer = buffers[bufferIndex];
int count = countInBuffer[bufferIndex];
for (int i = 0; i < count; i++)
{
double item = buffer[i];
if (item < lowerBound)
{
lowerBound = item;
}
if (item > upperBound)
{
upperBound = item;
}
}
}
if (probability == 1.0)
{
return(MMath.NextDouble(upperBound));
}
if (probability == 0.0)
{
return(lowerBound);
}
if (double.IsPositiveInfinity(lowerBound))
{
throw new Exception("QuantileEstimator has no data");
}
if (lowerBound == upperBound)
{
return(upperBound);
}
// use bisection
while (true)
{
double x = MMath.Average(lowerBound, upperBound);
double lowerItem;
double upperItem;
long lowerRank;
long lowerWeight, minLowerWeight, upperWeight, minUpperWeight;
long itemCount;
GetAdjacentItems(x, out lowerItem, out upperItem, out lowerRank, out lowerWeight, out upperWeight, out minLowerWeight, out minUpperWeight, out itemCount);
if (InterpolationType == 0)
{
double probabilityLessThanLowerItem = (double)(lowerRank - lowerWeight) / itemCount;
if (probability < probabilityLessThanLowerItem)
{
upperBound = MMath.PreviousDouble(lowerItem);
}
else
{
double probabilityLessThanUpperItem = (double)lowerRank / itemCount;
if (probability < probabilityLessThanUpperItem)
{
return(lowerItem);
}
double probabilityLessThanOrEqualUpperItem = (double)(lowerRank + upperWeight) / itemCount;
if (probability < probabilityLessThanOrEqualUpperItem)
{
return(upperItem);
}
lowerBound = MMath.NextDouble(upperItem);
}
}
else if (InterpolationType == 1)
{
// Find frac such that (lowerRank - 0.5 + frac) / itemCount == probability
double scaledProbability = MMath.LargestDoubleProduct(itemCount, probability);
if (scaledProbability < 0.5)
{
return(lowerBound);
}
if (scaledProbability >= itemCount - 0.5)
{
return(upperBound);
}
// probability of lowerItem ranges from (lowerRank-lowerWeight+0.5) / itemCount
// to (lowerRank - 0.5) / itemCount
//if (scaledProbability == lowerRank - lowerWeight + 0.5) return lowerItem;
if ((scaledProbability > lowerRank - lowerWeight + 0.5) && (scaledProbability < lowerRank - 0.5))
{
return(lowerItem);
}
// probability of upperItem ranges from (lowerRank + 0.5) / itemCount
// to (lowerRank + upperWeight - 0.5) / itemCount
if (scaledProbability == lowerRank + 0.5)
{
return(upperItem);
}
if ((scaledProbability > lowerRank + 0.5) && (scaledProbability < lowerRank + upperWeight - 0.5))
{
return(upperItem);
}
double frac = scaledProbability - (lowerRank - 0.5);
if (frac < 0)
{
upperBound = MMath.PreviousDouble(x);
}
else if (frac > 1)
{
lowerBound = MMath.NextDouble(x);
}
else
{
return(OuterQuantiles.GetQuantile(probability, lowerRank - 0.5, lowerItem, upperItem, itemCount + 1));
}
}
else
{
double scaledProbability = MMath.LargestDoubleProduct(itemCount - 1, probability);
// probability of lowerItem ranges from (lowerRank-lowerWeight) / (itemCount - 1)
// to (lowerRank - 1) / (itemCount - 1).
if (scaledProbability == lowerRank - lowerWeight)
{
return(lowerItem);
}
if ((scaledProbability > lowerRank - lowerWeight) && (scaledProbability < lowerRank - 1))
{
return(lowerItem);
}
// probability of upperItem ranges from lowerRank / (itemCount - 1)
// to (lowerRank + upperWeight-1) / (itemCount - 1)
if (scaledProbability == lowerRank)
{
return(upperItem);
}
if ((scaledProbability > lowerRank) && (scaledProbability < lowerRank + upperWeight - 1))
{
return(upperItem);
}
// solve for frac in (lowerRank-1 + frac) / (itemCount - 1) == probability
double frac = scaledProbability - (lowerRank - 1);
if (frac < 0)
{
upperBound = MMath.PreviousDouble(x);
}
else if (frac > 1)
{
lowerBound = MMath.NextDouble(x);
}
else
{
return(OuterQuantiles.GetQuantile(probability, lowerRank - 1, lowerItem, upperItem, itemCount));
}
}
}
}
