public Histogram Build(IReadOnlyList <double> values, double binSize)
{
if (binSize < 1e-9)
{
throw new ArgumentException($"binSize ({binSize.ToString("0.##", DefaultCultureInfo.Instance)}) should be a positive number", nameof(binSize));
}
var list = values.CopyToArray();
if (list.Length == 0)
{
throw new ArgumentException("Values should be non-empty", nameof(values));
}
Array.Sort(list);
int firstBin = GetBinIndex(list.First(), binSize);
int lastBin = GetBinIndex(list.Last(), binSize);
int binCount = lastBin - firstBin + 1;
var bins = new HistogramBin[binCount];
int counter = 0;
for (int i = 0; i < bins.Length; i++)
{
var bin = new List <double>();
double lower = (firstBin + i) * binSize;
double upper = (firstBin + i + 1) * binSize;
while (counter < list.Length && (list[counter] < upper || i == bins.Length - 1))
{
bin.Add(list[counter++]);
}
bins[i] = new HistogramBin(lower, upper, bin.ToArray());
}
return(new Histogram(binSize, bins));
}
public static HistogramBin Union(HistogramBin bin1, HistogramBin bin2) => new HistogramBin(
Math.Min(bin1.Lower, bin2.Lower),
Math.Max(bin1.Upper, bin2.Upper),
bin1.Values.Union(bin2.Values).OrderBy(value => value).ToArray());
// TODO: Optimize
public Histogram Build(IReadOnlyList <double> values, double binSize)
{
const double eps = 1e-9;
const double margin = 0.1;
const double adaptiveFactor = 0.02;
if (binSize < eps)
{
throw new ArgumentException(
$"binSize ({binSize.ToString("0.##", DefaultCultureInfo.Instance)}) should be a positive number",
nameof(binSize));
}
if (binSize < Resolution)
{
binSize = Resolution;
}
binSize = NiceCeiling(binSize);
var list = values.ToList();
if (list.Count == 0)
{
throw new ArgumentException("Values should be non-empty", nameof(values));
}
list.Sort();
if (list.Last() - list.First() < binSize)
{
double center = (list.First() + list.Last()) / 2;
double lower = center - binSize / 2;
double upper = center + binSize / 2;
return(new Histogram(binSize, new[] { new HistogramBin(lower, upper, list.ToArray()) }));
}
var points = new List <double> {
NiceFloor(list.Min() - binSize / 2), NiceCeiling(list.Max() + binSize / 2)
};
int processedPointCount = 0;
while (true)
{
if (points.Count > 10 * list.Count)
{
var errorMessage = new StringBuilder();
errorMessage.AppendLine("Failed to run AdaptiveHistogramBuilder.BuildWithFixedBinSize");
errorMessage.AppendLine("BinSize: " + binSize.ToString("N12", DefaultCultureInfo.Instance));
errorMessage.AppendLine("Values: ");
foreach (double value in list)
{
errorMessage.AppendLine(" " + value.ToString("N12", DefaultCultureInfo.Instance));
}
throw new InvalidOperationException(errorMessage.ToString());
}
int pointIndex = -1;
for (int i = processedPointCount; i < points.Count - 1; i++)
{
double adaptiveBinSize = (points[i] + points[i + 1]) / 2.0 * adaptiveFactor;
double maxSize = Math.Max(binSize * (1.0 + 2 * margin), adaptiveBinSize);
if (points[i + 1] - points[i] > maxSize)
{
pointIndex = i;
break;
}
}
if (pointIndex == -1)
{
break;
}
double lower = points[pointIndex];
double upper = points[pointIndex + 1];
int bestIndex1 = -1;
int bestIndex2 = -1;
int bestCount = -1;
double bestDist = double.MaxValue;
bool Inside(double x) => x > lower - eps && x < upper - eps;
for (int i = 0; i < list.Count; i++)
{
if (Inside(list[i]))
{
int j = i;
while (j < list.Count && Inside(list[j]) && list[j] - list[i] < binSize)
{
j++;
}
int count = j - i;
double dist = list[j - 1] - list[i];
if (count > bestCount || count == bestCount && dist < bestDist)
{
bestCount = count;
bestIndex1 = i;
bestIndex2 = j - 1;
bestDist = dist;
}
}
}
if (bestIndex1 != -1)
{
double center = (list[bestIndex1] + list[bestIndex2]) / 2.0;
double adaptiveBinSize = Math.Max(binSize, center * adaptiveFactor);
double left = NiceFloor(center - adaptiveBinSize / 2);
double right = NiceFloor(Math.Min(center + adaptiveBinSize / 2, upper));
if (left > lower + binSize * margin)
{
points.Insert(pointIndex + 1, left);
}
else if (right < upper - binSize * margin && right > lower + binSize * margin)
{
points.Insert(pointIndex + 1, right);
processedPointCount++;
}
else
{
processedPointCount++;
}
}
else
{
points.Insert(pointIndex + 1, NiceFloor(lower + binSize));
processedPointCount++;
}
}
var bins = new List <HistogramBin>(points.Count - 1);
int counter = 0;
for (int i = 0; i < points.Count - 1; i++)
{
var bin = new List <double>();
double lower = points[i];
double upper = points[i + 1];
while (counter < list.Count && (list[counter] < upper || i == points.Count - 1))
{
bin.Add(list[counter++]);
}
bins.Add(new HistogramBin(lower, upper, bin.ToArray()));
}
// Trim
while (bins.Any() && bins.First().IsEmpty)
{
bins.RemoveAt(0);
}
while (bins.Any() && bins.Last().IsEmpty)
{
bins.RemoveAt(bins.Count - 1);
}
// Join small bins to neighbors
counter = 0;
double lastValue = 0;
while (counter < bins.Count)
{
if (bins[counter].HasAny)
{
lastValue = Math.Max(lastValue, bins[counter].Values.Last());
}
double adaptiveThreshold = Math.Max(binSize / 2, lastValue * adaptiveFactor);
if (bins[counter].Gap < adaptiveThreshold)
{
double leftGap = counter > 0 ? bins[counter - 1].Gap : double.MaxValue;
double rightGap = counter < bins.Count - 1 ? bins[counter + 1].Gap : double.MaxValue;
if (leftGap < rightGap && counter > 0)
{
bins[counter - 1] = HistogramBin.Union(bins[counter - 1], bins[counter]);
bins.RemoveAt(counter);
}
else if (counter < bins.Count - 1)
{
bins[counter] = HistogramBin.Union(bins[counter], bins[counter + 1]);
bins.RemoveAt(counter + 1);
}
else
{
counter++;
}
}
else
{
counter++;
}
}
return(new Histogram(binSize, bins.ToArray()));
}
