public void TestAccumulatorAddRemove()
{
Accumulator accumulator = new Accumulator();
for(int i = 0; i <= 10; i++)
{
accumulator.Add(i);
}
Assert.That(accumulator.Mean, NumericIs.AlmostEqualTo((double) 5), "A Mean");
Assert.That(accumulator.Variance, NumericIs.AlmostEqualTo((double) 11), "A Variance");
Assert.That(accumulator.Sum, NumericIs.AlmostEqualTo((double) 55), "A Sum");
accumulator.Remove(9);
accumulator.Remove(4);
Assert.That(accumulator.Mean, NumericIs.AlmostEqualTo(14d / 3), "B Mean");
Assert.That(accumulator.Variance, NumericIs.AlmostEqualTo(23d / 2), "B Variance");
Assert.That(accumulator.Sum, NumericIs.AlmostEqualTo((double) 42), "B Sum");
accumulator.Add(9);
accumulator.Add(4);
Assert.That(accumulator.Mean, NumericIs.AlmostEqualTo((double) 5), "C Mean");
Assert.That(accumulator.Variance, NumericIs.AlmostEqualTo((double) 11), "C Variance");
Assert.That(accumulator.Sum, NumericIs.AlmostEqualTo((double) 55), "C Sum");
}
public void TestAccumulatorNumericStability()
{
/* NOTE: Statistically it is possible that this test fails even
* if everything works as expected. However, it's very unlikely to happen,
* and even more unlikely to happen in a series. */
Accumulator accumulator = new Accumulator();
NormalDistribution gaussian = new NormalDistribution();
// Test around 0, no stability issues expected
gaussian.SetDistributionParameters(0, 1);
for(int i = 0; i < 10000; i++)
{
accumulator.Add(gaussian.NextDouble());
}
Assert.That(accumulator.Mean, NumericIs.AlmostEqualTo((double) 0, 0.2), "Mean of (0,1)");
Assert.That(accumulator.Variance, NumericIs.AlmostEqualTo((double) 1, 0.5), "Variance of (0,1)");
// Test around 10^9, potential stability issues
accumulator.Clear();
gaussian.SetDistributionParameters(1e+9, 1);
for(int i = 0; i < 10000; i++)
{
accumulator.Add(gaussian.NextDouble());
}
Assert.That(accumulator.Mean, NumericIs.AlmostEqualTo(1e+9, 0.2), "Mean of (1e+9,1)");
Assert.That(accumulator.Variance, NumericIs.AlmostEqualTo((double) 1, 0.5), "Variance of (1e+9,1)");
}
static void Main(string[] args)
{
Dictionary<string, Accumulator> vals = new Dictionary<string, Accumulator>();
Model m = new Model(args[0]);
JupiterXL JXL = new JupiterXL(args[1]);
JXL.ReadWells(true, false);
JXL.ReadInLithology();
foreach (var geo in JXL.LITHSAMP)
{
if (!geo.IsROCKSYMBOLNull() && !geo.IsBOTTOMNull() && !geo.IsTOPNull() && geo.ROCKSYMBOL.Trim() != "")
{
var Boring = JXL.BOREHOLE.FindByBOREHOLENO(geo.BOREHOLENO);
if (Boring != null && !Boring.IsXUTMNull() && !Boring.IsYUTMNull())
{
int Column = m.GridInfo.GetColumnIndex(Boring.XUTM);
int row = m.GridInfo.GetRowIndex(Boring.YUTM);
if (row >= 0 & Column >= 0)
{
int Layer = m.GridInfo.GetLayer(Column, row, m.GridInfo.SurfaceTopography.Data[row, Column] - (geo.TOP + geo.BOTTOM) / 2);
if (Layer >= 0)
{
Accumulator Ledningsevner;
if (!vals.TryGetValue(geo.ROCKSYMBOL, out Ledningsevner))
{
Ledningsevner = new Accumulator();
vals.Add(geo.ROCKSYMBOL, Ledningsevner);
}
Ledningsevner.Add(Math.Log10(m.Processed.HorizontalConductivity.Data[row, Column, Layer]));
}
}
}
}
}//End of loop
Accumulator all = new Accumulator();
for (int lay = 0; lay < m.GridInfo.NumberOfLayers; lay++)
for (int row = 0; row < m.GridInfo.NumberOfRows; row++)
for (int col = 0; col < m.GridInfo.NumberOfColumns; col++)
if (m.GridInfo.ModelDomainAndGrid.Data[row, col] == 1)
all.Add(Math.Log10(m.Processed.HorizontalConductivity.Data[row, col, lay]));
vals.Add("All", all);
using (StreamWriter sw = new StreamWriter(@"F:\temp\out.txt", false, Encoding.Default))
{
sw.WriteLine("Rocksymbol\tNoOfEntries\tMean\tVariance\tStandard Deviation");
foreach (KeyValuePair<string, Accumulator> KVP in vals.OrderByDescending((acc) => acc.Value.Count))
{
sw.WriteLine(KVP.Key + "\t" + KVP.Value.Count + "\t" + KVP.Value.Mean + "\t" + KVP.Value.Variance + "\t" + KVP.Value.Sigma);
}
}
JXL.Dispose();
}
public double EstimateMeanSquaredError()
{
Accumulator accu = new Accumulator();
foreach(Sample s in _provider)
{
double v = EvaluateFunction(s.Coordinate);
accu.Add(v - s.Value);
}
return accu.MeanSquared;
}
EstimateDistributionParameters(
IEnumerable<double> samples
)
{
Accumulator accumulator = new Accumulator(samples);
SetDistributionParameters(accumulator.Mean, accumulator.Sigma);
}
