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new tests
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@@ -0,0 +1,183 @@
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using System;
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using System.Collections.Generic;
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using System.Globalization;
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using System.Linq;
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namespace Esiur.Tests.Queueing.Client
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{
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/// <summary>
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/// Point estimate accompanied by a 95% confidence-interval half-width
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/// (computed with Student's t for small samples). Use ToString() to
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/// render as "mean ± half" in print output.
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/// </summary>
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public readonly record struct MeanCi(double Mean, double Ci95HalfWidth, int N)
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{
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public static MeanCi From(IEnumerable<double> xs)
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{
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var arr = xs.ToArray();
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int n = arr.Length;
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if (n == 0) return new MeanCi(0, 0, 0);
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if (n == 1) return new MeanCi(arr[0], 0, 1);
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double mean = arr.Average();
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double sumSq = 0;
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for (int i = 0; i < n; i++)
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{
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double d = arr[i] - mean;
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sumSq += d * d;
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}
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double std = Math.Sqrt(sumSq / (n - 1));
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double sem = std / Math.Sqrt(n);
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// Student's t two-sided 95% for small df. df = n - 1.
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// Values from standard tables; ≥10 falls back to normal (1.960).
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double t = (n - 1) switch
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{
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1 => 12.706,
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2 => 4.303,
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3 => 3.182,
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4 => 2.776,
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5 => 2.571,
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6 => 2.447,
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7 => 2.365,
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8 => 2.306,
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9 => 2.262,
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10 => 2.228,
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11 => 2.201,
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12 => 2.179,
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13 => 2.160,
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14 => 2.145,
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15 => 2.131,
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16 => 2.120,
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17 => 2.110,
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18 => 2.101,
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19 => 2.093,
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20 => 2.086,
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_ => 1.960 // normal approximation for df > 20
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};
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return new MeanCi(mean, t * sem, n);
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}
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public override string ToString() =>
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N <= 1
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? Mean.ToString("F2", CultureInfo.InvariantCulture)
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: string.Create(CultureInfo.InvariantCulture,
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$"{Mean:F2}±{Ci95HalfWidth:F2}");
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}
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/// <summary>
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/// Aggregated result over K replications of the same (delay, alpha)
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/// configuration. Carries point estimates plus per-metric 95% CI
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/// half-widths for the headline metrics reported in the paper:
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/// arrival rate λ, service rate μ, mean readiness R̄, mean HOL δ̄,
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/// and mean end-to-end latency D̄.
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///
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/// The companion <see cref="EsiurQueueEval.EvalResult"/> field
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/// (PerRepMean) holds the existing-style averaged point estimates
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/// so downstream code that already consumed EvalResult continues
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/// to work unchanged.
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/// </summary>
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public sealed record ReplicatedResult(
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int Delay,
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double Alpha,
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int Replications,
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MeanCi Lambda,
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MeanCi Mu,
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MeanCi ReadinessMeanMs,
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MeanCi HolMeanMs,
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MeanCi EndToEndMeanMs,
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MeanCi EndToEndP99Ms,
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MeanCi QueueLengthMean,
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MeanCi BatchSizeMean,
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EsiurQueueEval.EvalResult PerRepMean);
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public static class ReplicatedEvalAggregator
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{
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/// <summary>
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/// Combine K per-replication EvalResult objects into a single
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/// ReplicatedResult, computing point estimates and 95% CIs.
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/// </summary>
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public static ReplicatedResult Aggregate(
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int delay,
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double alpha,
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IReadOnlyList<EsiurQueueEval.EvalResult> reps)
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{
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if (reps == null) throw new ArgumentNullException(nameof(reps));
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if (reps.Count == 0) throw new ArgumentException("reps is empty.", nameof(reps));
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var lambda = MeanCi.From(reps.Select(r => r.LambdaEventsPerSecond));
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var mu = MeanCi.From(reps.Select(r => r.MuEventsPerSecond));
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var readiness = MeanCi.From(reps.Select(r => r.Latency.ReadinessMs.Mean));
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var hol = MeanCi.From(reps.Select(r => r.Latency.HolMs.Mean));
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var e2eMean = MeanCi.From(reps.Select(r => r.Latency.EndToEndMs.Mean));
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var e2eP99 = MeanCi.From(reps.Select(r => r.Latency.EndToEndMs.P99));
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var qLen = MeanCi.From(reps.Select(r => r.QueueLength.Mean));
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var batch = MeanCi.From(reps.Select(
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r => r.FlushSizeStats?.Mean ?? double.NaN)
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.Where(v => !double.IsNaN(v)));
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// Use the existing Average helper for the carry-along point estimates.
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var perRepMean = EsiurQueueEval.Average(reps);
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return new ReplicatedResult(
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Delay: delay,
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Alpha: alpha,
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Replications: reps.Count,
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Lambda: lambda,
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Mu: mu,
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ReadinessMeanMs: readiness,
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HolMeanMs: hol,
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EndToEndMeanMs: e2eMean,
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EndToEndP99Ms: e2eP99,
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QueueLengthMean: qLen,
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BatchSizeMean: batch,
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PerRepMean: perRepMean);
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}
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public static string CsvHeader =>
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"delay_ms,alpha,replications," +
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"lambda_mean,lambda_ci95," +
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"mu_mean,mu_ci95," +
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"readiness_mean_ms,readiness_ci95," +
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"hol_mean_ms,hol_ci95," +
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"e2e_mean_ms,e2e_ci95," +
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"e2e_p99_ms,e2e_p99_ci95," +
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"queue_len_mean,queue_len_ci95," +
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"batch_mean,batch_ci95";
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public static string ToCsvRow(ReplicatedResult r)
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{
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var inv = CultureInfo.InvariantCulture;
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return string.Create(inv,
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$"{r.Delay},{r.Alpha:F3},{r.Replications}," +
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$"{r.Lambda.Mean:F3},{r.Lambda.Ci95HalfWidth:F3}," +
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$"{r.Mu.Mean:F3},{r.Mu.Ci95HalfWidth:F3}," +
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$"{r.ReadinessMeanMs.Mean:F3},{r.ReadinessMeanMs.Ci95HalfWidth:F3}," +
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$"{r.HolMeanMs.Mean:F3},{r.HolMeanMs.Ci95HalfWidth:F3}," +
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$"{r.EndToEndMeanMs.Mean:F3},{r.EndToEndMeanMs.Ci95HalfWidth:F3}," +
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$"{r.EndToEndP99Ms.Mean:F3},{r.EndToEndP99Ms.Ci95HalfWidth:F3}," +
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$"{r.QueueLengthMean.Mean:F3},{r.QueueLengthMean.Ci95HalfWidth:F3}," +
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$"{r.BatchSizeMean.Mean:F3},{r.BatchSizeMean.Ci95HalfWidth:F3}");
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}
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/// <summary>
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/// Console-friendly compact summary, one configuration per call.
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/// </summary>
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public static void PrintSummary(ReplicatedResult r)
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{
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Console.WriteLine();
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Console.WriteLine($"=== Configuration: delay={r.Delay} ms, α={r.Alpha:F2}, " +
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$"replications={r.Replications} ===");
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Console.WriteLine("Metric | Mean ± 95% CI half-width");
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Console.WriteLine("----------------+----------------------------------------");
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Console.WriteLine($"λ (/s) | {r.Lambda}");
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Console.WriteLine($"μ (/s) | {r.Mu}");
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Console.WriteLine($"R̄ (ms) | {r.ReadinessMeanMs}");
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Console.WriteLine($"δ̄ (ms) | {r.HolMeanMs}");
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Console.WriteLine($"D̄ (ms) | {r.EndToEndMeanMs}");
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Console.WriteLine($"P99(D) (ms) | {r.EndToEndP99Ms}");
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Console.WriteLine($"Queue length | {r.QueueLengthMean}");
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Console.WriteLine($"Batch size B | {r.BatchSizeMean}");
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}
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}
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}
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