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Merge dev into main: v0.8.7 Kahan compensated summation

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Miha Kralj
2026-03-13 22:01:52 -07:00
parent 86a1db286c 67ad6f0cba
commit 9697facfb4
79 changed files with 2923 additions and 2495 deletions
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lib/errors/rsquared/Rsquared.cs
+30 -36
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@@ -20,6 +20,8 @@ namespace QuanTAlib;
/// - R² = 0 means predictions equal mean predictor
/// - R² < 0 means predictions worse than mean predictor
/// - Range: (-∞, 1]
///
/// Uses Kahan compensated summation to prevent floating-point drift without periodic resync.
/// </remarks>
[SkipLocalsInit]
public sealed class Rsquared : AbstractBase
@@ -33,14 +35,14 @@ public sealed class Rsquared : AbstractBase
double ActualSum,
double SqResidualSum,
double SqTotalSum,
double ActualComp,
double SqResidualComp,
double SqTotalComp,
double LastValidActual,
double LastValidPredicted,
int TickCount);
double LastValidPredicted);
private State _state;
private State _p_state;
private const int ResyncInterval = 1000;
public Rsquared(int period)
{
if (period <= 0)
@@ -85,9 +87,15 @@ public sealed class Rsquared : AbstractBase
{
_p_state = _state;
// Update actual buffer for mean calculation
// Update actual buffer for mean calculation — Kahan compensated
double removedActual = _actualBuffer.Count == _actualBuffer.Capacity ? _actualBuffer.Oldest : 0.0;
_state.ActualSum = _state.ActualSum - removedActual + actualVal;
{
double delta = actualVal - removedActual;
double y = delta - _state.ActualComp;
double t = _state.ActualSum + y;
_state.ActualComp = (t - _state.ActualSum) - y;
_state.ActualSum = t;
}
_actualBuffer.Add(actualVal);
// Calculate mean and errors
@@ -97,24 +105,27 @@ public sealed class Rsquared : AbstractBase
double sqResidual = residual * residual;
double sqTotal = totalDev * totalDev;
// Update squared residual buffer (RSS)
// Update squared residual buffer (RSS) — Kahan compensated
double removedResidual = _sqResidualBuffer.Count == _sqResidualBuffer.Capacity ? _sqResidualBuffer.Oldest : 0.0;
_state.SqResidualSum = _state.SqResidualSum - removedResidual + sqResidual;
{
double delta = sqResidual - removedResidual;
double y = delta - _state.SqResidualComp;
double t = _state.SqResidualSum + y;
_state.SqResidualComp = (t - _state.SqResidualSum) - y;
_state.SqResidualSum = t;
}
_sqResidualBuffer.Add(sqResidual);
// Update squared total buffer (TSS)
// Update squared total buffer (TSS) — Kahan compensated
double removedTotal = _sqTotalBuffer.Count == _sqTotalBuffer.Capacity ? _sqTotalBuffer.Oldest : 0.0;
_state.SqTotalSum = _state.SqTotalSum - removedTotal + sqTotal;
_sqTotalBuffer.Add(sqTotal);
_state.TickCount++;
if (_actualBuffer.IsFull && _state.TickCount >= ResyncInterval)
{
_state.TickCount = 0;
_state.ActualSum = _actualBuffer.RecalculateSum();
_state.SqResidualSum = _sqResidualBuffer.RecalculateSum();
_state.SqTotalSum = _sqTotalBuffer.RecalculateSum();
double delta = sqTotal - removedTotal;
double y = delta - _state.SqTotalComp;
double t = _state.SqTotalSum + y;
_state.SqTotalComp = (t - _state.SqTotalSum) - y;
_state.SqTotalSum = t;
}
_sqTotalBuffer.Add(sqTotal);
}
else
{
@@ -297,7 +308,6 @@ public sealed class Rsquared : AbstractBase
output[i] = sqTotalSum > 1e-10 ? 1.0 - (sqResidualSum / sqTotalSum) : 1.0;
}
int tickCount = 0;
for (; i < len; i++)
{
double act = actual[i];
@@ -342,22 +352,6 @@ public sealed class Rsquared : AbstractBase
}
output[i] = sqTotalSum > 1e-10 ? 1.0 - (sqResidualSum / sqTotalSum) : 1.0;
tickCount++;
if (tickCount >= ResyncInterval)
{
tickCount = 0;
double recalcActual = 0, recalcResidual = 0, recalcTotal = 0;
for (int k = 0; k < period; k++)
{
recalcActual += actualBuffer[k];
recalcResidual += sqResidualBuffer[k];
recalcTotal += sqTotalBuffer[k];
}
actualSum = recalcActual;
sqResidualSum = recalcResidual;
sqTotalSum = recalcTotal;
}
}
}
@@ -367,4 +361,4 @@ public sealed class Rsquared : AbstractBase
TSeries results = Batch(actual, predicted, period);
return (results, indicator);
}
}
}