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[CodeFactor] Apply fixes to commit 0606491

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codefactor-io
2026-03-12 19:37:50 +00:00
parent 060649192f
commit 8f79257155
384 changed files with 1197 additions and 1215 deletions
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lib/trends_FIR/nlma/tests/Nlma.Tests.cs
+15 -15
View File
@@ -82,7 +82,7 @@ public class NlmaTests
{
// DC gain = 1: constant input → output must equal that constant after warmup
var nlma = new Nlma(10);
int flen = 5 * 10 - 1; // 49
int flen = (5 * 10) - 1; // 49
TValue result = default;
for (int i = 0; i < flen + 10; i++)
{
@@ -96,7 +96,7 @@ public class NlmaTests
{
// period=2, flen=9. After warmup, constant input → output = input
var nlma = new Nlma(2);
int flen = 5 * 2 - 1; // 9
int flen = (5 * 2) - 1; // 9
TValue result = default;
for (int i = 0; i < flen + 5; i++)
{
@@ -111,7 +111,7 @@ public class NlmaTests
// Igorad kernel with any period: constant input must produce constant output
// This validates that signed-sum normalization preserves DC gain = 1
var nlma = new Nlma(4);
int flen = 5 * 4 - 1; // 19
int flen = (5 * 4) - 1; // 19
TValue result = default;
for (int i = 0; i < flen + 5; i++)
{
@@ -126,7 +126,7 @@ public class NlmaTests
// Igorad kernel with period 14 should have negative weights for lag cancellation
// Test: feed a step function and verify responsiveness
var nlma = new Nlma(14);
int flen = 5 * 14 - 1; // 69
int flen = (5 * 14) - 1; // 69
// Feed flen bars of 100, then flen bars of 200
for (int i = 0; i < flen; i++)
@@ -165,7 +165,7 @@ public class NlmaTests
{
// period=3, flen = 5*3-1 = 14
var nlma = new Nlma(3);
int flen = 5 * 3 - 1; // 14
int flen = (5 * 3) - 1; // 14
Assert.False(nlma.IsHot);
for (int i = 0; i < flen - 1; i++)
@@ -281,12 +281,12 @@ public class NlmaTests
public void AllModes_ProduceSameResults()
{
int period = 10;
int flen = 5 * period - 1; // 49
int flen = (5 * period) - 1; // 49
int len = flen + 30; // ensure enough bars for full kernel
var src = new TSeries([], []);
for (int i = 0; i < len; i++)
{
src.Add(new TValue(DateTime.MinValue.AddDays(i), 100 + Math.Sin(i) * 10));
src.Add(new TValue(DateTime.MinValue.AddDays(i), 100 + (Math.Sin(i) * 10)));
}
// Mode 1: streaming
@@ -343,12 +343,12 @@ public class NlmaTests
public void Batch_Span_MatchesTSeries()
{
int period = 7;
int flen = 5 * period - 1; // 34
int flen = (5 * period) - 1; // 34
int len = flen + 20;
var src = new TSeries([], []);
for (int i = 0; i < len; i++)
{
src.Add(new TValue(DateTime.MinValue.AddDays(i), 50 + i * 0.5));
src.Add(new TValue(DateTime.MinValue.AddDays(i), 50 + (i * 0.5)));
}
var tsBatch = Nlma.Batch(src, period);
@@ -388,12 +388,12 @@ public class NlmaTests
double[] output = new double[count];
for (int i = 0; i < count; i++)
{
source[i] = 100.0 + i * 0.1;
source[i] = 100.0 + (i * 0.1);
}
Nlma.Batch(source, output, 300);
// flen = 5*300 - 1 = 1499
int flen = 5 * 300 - 1;
int flen = (5 * 300) - 1;
for (int i = flen; i < count; i++)
{
Assert.True(double.IsFinite(output[i]), $"Output at index {i} should be finite");
@@ -406,7 +406,7 @@ public class NlmaTests
public void Calculate_ReturnsIndicatorAndResults()
{
int period = 5;
int flen = 5 * period - 1; // 24
int flen = (5 * period) - 1; // 24
int len = flen + 20;
var src = new TSeries([], []);
for (int i = 0; i < len; i++)
@@ -426,7 +426,7 @@ public class NlmaTests
public void Reset_ClearsState()
{
int period = 5;
int flen = 5 * period - 1; // 24
int flen = (5 * period) - 1; // 24
var nlma = new Nlma(period);
for (int i = 0; i < flen + 10; i++)
{
@@ -458,11 +458,11 @@ public class NlmaTests
public void LargePeriod_Handles()
{
int period = 500;
int flen = 5 * period - 1; // 2499
int flen = (5 * period) - 1; // 2499
var nlma = new Nlma(period);
for (int i = 0; i < flen + 100; i++)
{
nlma.Update(new TValue(DateTime.MinValue.AddDays(i), 100 + i * 0.01));
nlma.Update(new TValue(DateTime.MinValue.AddDays(i), 100 + (i * 0.01)));
}
Assert.True(double.IsFinite(nlma.Last.Value));
Assert.True(nlma.IsHot);
lib/trends_FIR/nlma/tests/Nlma.Validation.Tests.cs
+14 -14
View File
@@ -13,12 +13,12 @@ public class NlmaValidationTests
public void Batch_Matches_Streaming()
{
int period = 10;
int flen = 5 * period - 1; // 49
int flen = (5 * period) - 1; // 49
int len = flen + 30;
var src = new TSeries([], []);
for (int i = 0; i < len; i++)
{
src.Add(new TValue(DateTime.MinValue.AddDays(i), 100 + Math.Sin(i) * 20));
src.Add(new TValue(DateTime.MinValue.AddDays(i), 100 + (Math.Sin(i) * 20)));
}
var batchResult = Nlma.Batch(src, period);
@@ -35,12 +35,12 @@ public class NlmaValidationTests
public void Span_Matches_Streaming()
{
int period = 8;
int flen = 5 * period - 1; // 39
int flen = (5 * period) - 1; // 39
int len = flen + 20;
double[] values = new double[len];
for (int i = 0; i < len; i++)
{
values[i] = 50 + i * 0.7;
values[i] = 50 + (i * 0.7);
}
double[] spanOutput = new double[len];
@@ -58,12 +58,12 @@ public class NlmaValidationTests
public void Calculate_Matches_Batch()
{
int period = 12;
int flen = 5 * period - 1; // 59
int flen = (5 * period) - 1; // 59
int len = flen + 20;
var src = new TSeries([], []);
for (int i = 0; i < len; i++)
{
src.Add(new TValue(DateTime.MinValue.AddDays(i), 200 + i * 0.3));
src.Add(new TValue(DateTime.MinValue.AddDays(i), 200 + (i * 0.3)));
}
var batchResult = Nlma.Batch(src, period);
@@ -79,7 +79,7 @@ public class NlmaValidationTests
public void ConstantInput_ProducesConstant()
{
int period = 15;
int flen = 5 * period - 1; // 74
int flen = (5 * period) - 1; // 74
int len = flen + 20;
var src = new TSeries([], []);
for (int i = 0; i < len; i++)
@@ -108,12 +108,12 @@ public class NlmaValidationTests
public void LargePeriod_Handles()
{
int period = 200;
int flen = 5 * period - 1; // 999
int flen = (5 * period) - 1; // 999
int len = flen + 100;
var src = new TSeries([], []);
for (int i = 0; i < len; i++)
{
src.Add(new TValue(DateTime.MinValue.AddDays(i), 100 + Math.Sin(i * 0.1) * 10));
src.Add(new TValue(DateTime.MinValue.AddDays(i), 100 + (Math.Sin(i * 0.1) * 10)));
}
var result = Nlma.Batch(src, period);
@@ -128,7 +128,7 @@ public class NlmaValidationTests
[Fact]
public void DifferentPeriods_ProduceDifferentResults()
{
int maxFlen = 5 * 20 - 1; // 99 for period=20
int maxFlen = (5 * 20) - 1; // 99 for period=20
int len = maxFlen + 30;
var src = new TSeries([], []);
for (int i = 0; i < len; i++)
@@ -177,7 +177,7 @@ public class NlmaValidationTests
// Multiple corrections should not drift
for (int c = 0; c < 10; c++)
{
nlma.Update(new TValue(DateTime.MinValue.AddDays(29), 129.0 + c * 0.001), isNew: false);
nlma.Update(new TValue(DateTime.MinValue.AddDays(29), 129.0 + (c * 0.001)), isNew: false);
}
// Final correction with original value
@@ -192,13 +192,13 @@ public class NlmaValidationTests
// cancellation effect. Verify this by checking that NLMA on sinusoidal data
// differs from SMA and shows phase lead (less phase lag than SMA).
int period = 10;
int flen = 5 * period - 1; // 49
int flen = (5 * period) - 1; // 49
int len = 3 * flen;
var src = new TSeries([], []);
// Sinusoidal signal with period matching the filter period
for (int i = 0; i < len; i++)
{
src.Add(new TValue(DateTime.MinValue.AddDays(i), 100 + 10 * Math.Sin(2 * Math.PI * i / 20)));
src.Add(new TValue(DateTime.MinValue.AddDays(i), 100 + (10 * Math.Sin(2 * Math.PI * i / 20))));
}
var nlmaResult = Nlma.Batch(src, period);
@@ -235,7 +235,7 @@ public class NlmaValidationTests
{
// NLMA's negative weights can cause output to exceed input range
int period = 14;
int flen = 5 * period - 1; // 69
int flen = (5 * period) - 1; // 69
var nlma = new Nlma(period);
// Step function: all 0s then all 100s — enough data for full kernel