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Refactor and enhance various channel indicators for improved performance and stability

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- Updated Codacy instructions to streamline usage guidelines.
- Refactored Bbands class to utilize ArrayPool for memory management, preventing stack overflow on large series.
- Changed Fcb class to use long for monotonic deques to avoid truncation issues.
- Enhanced Kchannel class to ensure safe defaults for non-finite values.
- Improved Maenv class to prevent double-priming during calculations.
- Modified Mmchannel class to ensure non-negative buffer indices and removed unnecessary state tracking.
- Updated Pchannel class to correctly reference IsHot state.
- Refined Regchannel class to avoid double-processing during calculations.
- Enhanced Starchannel class to sanitize non-finite values during calculations.
- Adjusted Stbands.Quantower.cs to allow finer control over multiplier precision.
- Updated Ubands class to only update last valid values on new bars.
- Modified Uchannel.Quantower.cs to allow for finer multiplier precision.
- Enhanced Vwapbands classes to include standard deviation calculations and ensure consistent array lengths.
- Refactored Vwapsd classes to include standard deviation outputs and ensure consistent array lengths.
- Updated MonotonicDeque to use long for indices to prevent overflow.
- Improved Mdape class to handle zero actual values with a substitute value for error calculation.
- Enhanced Rae class to ensure correct state management during updates.
- Refined Wmape class to simplify the logic for finding last valid actual and predicted values.
- Updated Cmf.Quantower classes to ensure MinHistoryDepths reflects the current period.
This commit is contained in:
Miha Kralj
2026-01-27 23:48:33 -08:00
parent 8ac15f1efa
commit a9e72dae0d
29 changed files with 464 additions and 114 deletions
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lib/channels/bbands/Bbands.cs
+61 -21
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@@ -1,3 +1,4 @@
using System.Buffers;
using System.Runtime.CompilerServices;
using System.Runtime.InteropServices;
@@ -168,15 +169,30 @@ public sealed class Bbands : AbstractBase
int len = sourceSpan.Length;
TSeries middleSeries = new(capacity: len);
Span<double> middleSpan = stackalloc double[len];
Span<double> upperSpan = stackalloc double[len];
Span<double> lowerSpan = stackalloc double[len];
Calculate(sourceSpan, middleSpan, upperSpan, lowerSpan, _period, _multiplier);
// Use ArrayPool to avoid stack overflow for large series
double[] middleRented = ArrayPool<double>.Shared.Rent(len);
double[] upperRented = ArrayPool<double>.Shared.Rent(len);
double[] lowerRented = ArrayPool<double>.Shared.Rent(len);
for (int i = 0; i < len; i++)
try
{
middleSeries.Add(timeSpan[i], middleSpan[i], isNew: true);
Span<double> middleSpan = middleRented.AsSpan(0, len);
Span<double> upperSpan = upperRented.AsSpan(0, len);
Span<double> lowerSpan = lowerRented.AsSpan(0, len);
Calculate(sourceSpan, middleSpan, upperSpan, lowerSpan, _period, _multiplier);
for (int i = 0; i < len; i++)
{
middleSeries.Add(timeSpan[i], middleSpan[i], isNew: true);
}
}
finally
{
ArrayPool<double>.Shared.Return(middleRented);
ArrayPool<double>.Shared.Return(upperRented);
ArrayPool<double>.Shared.Return(lowerRented);
}
// Restore state from the last period values
@@ -257,8 +273,10 @@ public sealed class Bbands : AbstractBase
// Calculate standard deviation and bands using O(n) rolling sums
// Instead of O(n²) nested loop, maintain running sum and sumSq
// Track count of finite values to properly compute mean/variance
double rollingSum = 0.0;
double rollingSumSq = 0.0;
int finiteCount = 0;
// Initialize rolling sums for first window
for (int i = 0; i < Math.Min(period, len); i++)
@@ -268,6 +286,7 @@ public sealed class Bbands : AbstractBase
{
rollingSum += val;
rollingSumSq += val * val;
finiteCount++;
}
if (i < period - 1)
@@ -280,13 +299,22 @@ public sealed class Bbands : AbstractBase
// Process first complete window
if (len >= period)
{
double mean = rollingSum / period;
double variance = (rollingSumSq / period) - (mean * mean);
variance = Math.Max(0.0, variance); // Guard against negative due to floating point
double stdDev = Math.Sqrt(variance);
double offset = multiplier * stdDev;
upper[period - 1] = middle[period - 1] + offset;
lower[period - 1] = middle[period - 1] - offset;
if (finiteCount == period)
{
double mean = rollingSum / finiteCount;
double variance = (rollingSumSq / finiteCount) - (mean * mean);
variance = Math.Max(0.0, variance); // Guard against negative due to floating point
double stdDev = Math.Sqrt(variance);
double offset = multiplier * stdDev;
upper[period - 1] = middle[period - 1] + offset;
lower[period - 1] = middle[period - 1] - offset;
}
else
{
// Not all values in window are finite, emit NaN
upper[period - 1] = double.NaN;
lower[period - 1] = double.NaN;
}
}
// Process remaining bars with O(1) rolling update
@@ -298,6 +326,7 @@ public sealed class Bbands : AbstractBase
{
rollingSum -= outgoing;
rollingSumSq -= outgoing * outgoing;
finiteCount--;
}
// Add incoming value (current)
@@ -306,18 +335,29 @@ public sealed class Bbands : AbstractBase
{
rollingSum += incoming;
rollingSumSq += incoming * incoming;
finiteCount++;
}
// Calculate variance from rolling sums: Var = E[X²] - E[X]²
double mean = rollingSum / period;
double variance = (rollingSumSq / period) - (mean * mean);
variance = Math.Max(0.0, variance); // Guard against negative due to floating point
// Only compute bands when all values in window are finite
if (finiteCount == period)
{
// Calculate variance from rolling sums: Var = E[X²] - E[X]²
double mean = rollingSum / finiteCount;
double variance = (rollingSumSq / finiteCount) - (mean * mean);
variance = Math.Max(0.0, variance); // Guard against negative due to floating point
double stdDev = Math.Sqrt(variance);
double offset = multiplier * stdDev;
double stdDev = Math.Sqrt(variance);
double offset = multiplier * stdDev;
upper[i] = middle[i] + offset;
lower[i] = middle[i] - offset;
upper[i] = middle[i] + offset;
lower[i] = middle[i] - offset;
}
else
{
// Window contains non-finite values, emit NaN
upper[i] = double.NaN;
lower[i] = double.NaN;
}
}
}
}