From 45d705937591a783f736982ea4354fbd5dad07df Mon Sep 17 00:00:00 2001 From: Meta Vens Date: Sun, 24 May 2026 23:24:40 +0100 Subject: [PATCH] Add bioacoustic physical calibration receipt --- .../scarlett-canary-packet-192k-rerun.json | 10824 ++++++++++++++++ docs/implementation-plan.md | 11 + notes/current-system-map.md | 12 + src/Mimir.BufferSmoke/Program.cs | 616 + state/evidence.jsonl | 1 + state/map.yaml | 9 + 6 files changed, 11473 insertions(+) create mode 100644 calibration/bioacoustic/scarlett-canary-packet-192k-rerun.json diff --git a/calibration/bioacoustic/scarlett-canary-packet-192k-rerun.json b/calibration/bioacoustic/scarlett-canary-packet-192k-rerun.json new file mode 100644 index 0000000..14098b7 --- /dev/null +++ b/calibration/bioacoustic/scarlett-canary-packet-192k-rerun.json @@ -0,0 +1,10824 @@ +{ + "Schema": "mimir.bioacoustic.physical-calibration.v1", + "CreatedUtc": "2026-05-24T22:22:45.9540673+00:00", + "InputPath": 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4.211302029967119E-05, + "Gain": 1, + "Usable": true + }, + { + "CenterHz": 10075, + "ObservedEnergy": 4.1415259456173156E-05, + "ExpectedEnergy": 4.127183835238381E-05, + "Gain": 1, + "Usable": true + }, + { + "CenterHz": 10500, + "ObservedEnergy": 4.056817469278618E-05, + "ExpectedEnergy": 4.056817723325287E-05, + "Gain": 1, + "Usable": true + } + ] + } + ] +} \ No newline at end of file diff --git a/docs/implementation-plan.md b/docs/implementation-plan.md index 04232f4..bf42897 100644 --- a/docs/implementation-plan.md +++ b/docs/implementation-plan.md @@ -145,6 +145,17 @@ a named invariant that the native runtime cannot protect yet. with two reliable symbols. Acoustic robustness remains separate from the clean loopback timing proof, but failed timing windows now leave usable response evidence instead of silence. +- `Mimir.BufferSmoke --calibrate-contestant-asio-f32` persists the active + packet-song physical calibration model under `calibration/bioacoustic/`. + It learns per-channel schedule offset, polarity, payload reliability, + response-normalization bands, gain, confidence, and pairwise propagation + delay from the same 192 kHz ASIO capture. The latest Scarlett receipt + `calibration/bioacoustic/scarlett-canary-packet-192k-rerun.json` clears the + current hot-loop budget at 10.7x realtime across four channels. Loopback + channels decode 37/37 with 2.524 us MAE; the co-streamer shotgun decodes + 37/37 payload with 58.785 us MAE; the cardioid decodes 26/37 with + 90.558 us MAE. This is a real response/propagation-delay model, but not yet + microsecond-accurate physical mic sync. - `config/mimir-runtime.asio.example.json` is the minimal continuous Scarlett runtime ingest proof. It loads `native/asio_capture` in process at 192 kHz and declares `asio-ch0` through `asio-ch3` as accepted audio sources. A diff --git a/notes/current-system-map.md b/notes/current-system-map.md index 8be26c1..f22aebb 100644 --- a/notes/current-system-map.md +++ b/notes/current-system-map.md @@ -191,6 +191,18 @@ artifact, but it leaves a concrete response profile: 14 frames, 12 anchors, 0.865 clock confidence, and strongest bins around 4525, 4075, and 7225 Hz. Acoustic robustness is now the open problem, not clean loopback timing, standalone decoder shape, or basic response evidence. +`Mimir.BufferSmoke --calibrate-contestant-asio-f32` now owns the active +packet-song physical calibration receipt. It runs the canary packet decoder +against interleaved ASIO Float32 captures, performs a fast per-channel global +delay hypothesis search, then tight scheduled packet scoring with sub-sample +refinement. The latest persisted model at +`calibration/bioacoustic/scarlett-canary-packet-192k-rerun.json` ran at 10.7x +realtime across four 192 kHz channels and records per-channel polarity, +schedule offset, payload reliability, gain, response-normalization bands, and +pairwise propagation delay. Current physical precision is loopback 2.524 us +MAE, co-streamer shotgun 58.785 us MAE, and cardioid 90.558 us MAE; do not +claim physical microsecond sync until those mic MAEs collapse by another order +of magnitude. The first actuator proof now exists: `faust/mimir_alignment_actuator.dsp` owns six channels of bounded fractional delay/gain controls for Faust/native DSP, and `Mimir.BufferSmoke --bioacoustic-actuator-self-test --sample-rate 48000 diff --git a/src/Mimir.BufferSmoke/Program.cs b/src/Mimir.BufferSmoke/Program.cs index da242e3..6483be8 100644 --- a/src/Mimir.BufferSmoke/Program.cs +++ b/src/Mimir.BufferSmoke/Program.cs @@ -168,6 +168,22 @@ if (args.Any(arg => string.Equals(arg, "--analyze-contestant-asio-f32", StringCo ParseStringOption(args, "--song", MimirBioacousticContestants.CanaryPacketTrill.Id)); } +if (args.Any(arg => string.Equals(arg, "--calibrate-contestant-asio-f32", StringComparison.OrdinalIgnoreCase))) +{ + return CalibrateContestantAsioFloat32( + ParseStringOption(args, "--input", "artifacts/asio/scarlett-canary-packet-f32.raw"), + ParseStringOption(args, "--output", "calibration/bioacoustic/latest.json"), + ParseIntOption(args, "--sample-rate", MimirBioacousticTimeline.SampleRate), + ParseIntOption(args, "--channels", 4), + ParseIntOption(args, "--reference-channel", 2), + ParseDoubleOption(args, "--seconds", 3.0), + ParseDoubleOption(args, "--schedule-offset-samples", 0.0), + ParseDoubleOption(args, "--search-radius-us", 180.0), + ParseDoubleOption(args, "--delay-search-us", 6_000.0), + ParseStringOption(args, "--song", MimirBioacousticContestants.CanaryPacketTrill.Id), + ParseDoubleOption(args, "--min-realtime-factor", 10.0)); +} + if (args.Any(arg => string.Equals(arg, "--calibrate-chirp-bin-asio-f32", StringComparison.OrdinalIgnoreCase))) { return CalibrateChirpBinAsioFloat32( @@ -1640,6 +1656,130 @@ static int AnalyzeContestantAsioFloat32( return failures == 0 ? 0 : 1; } +static int CalibrateContestantAsioFloat32( + string inputPath, + string outputPath, + int sampleRate, + int channels, + int referenceChannel, + double seconds, + double scheduleOffsetSamples, + double searchRadiusUs, + double delaySearchUs, + string songId, + double minRealtimeFactor) +{ + if (!File.Exists(inputPath)) + { + Console.Error.WriteLine($"contestant calibration failed: input not found: {inputPath}"); + return 1; + } + + var profile = MimirBioacousticContestants.BuiltIn.FirstOrDefault(profile => + string.Equals(profile.Id, songId, StringComparison.OrdinalIgnoreCase)); + if (profile == null) + { + Console.Error.WriteLine($"contestant calibration failed: unknown song '{songId}'"); + return 1; + } + + if (referenceChannel < 0 || referenceChannel >= channels) + { + Console.Error.WriteLine("contestant calibration failed: reference channel is outside the capture channel count"); + return 1; + } + + var channelSamples = ReadInterleavedFloat32(inputPath, channels, out var frameCount); + if (frameCount == 0) + { + Console.Error.WriteLine("contestant calibration failed: capture file contains no complete frames"); + return 1; + } + + var captureSeconds = seconds > 0.0 ? Math.Min(seconds, frameCount / (double)sampleRate) : frameCount / (double)sampleRate; + var renderer = new MimirBioacousticContestantRenderer(profile); + var expectedEvents = renderer.ExpectedEvents(captureSeconds) + .Order() + .ToArray(); + if (expectedEvents.Length == 0) + { + Console.Error.WriteLine("contestant calibration failed: no complete expected packet events in capture"); + return 1; + } + + var searchRadiusSamples = Math.Max(1, (int)Math.Round(searchRadiusUs * sampleRate / 1_000_000.0)); + var delaySearchSamples = Math.Max(0, (int)Math.Round(delaySearchUs * sampleRate / 1_000_000.0)); + var stopwatch = Stopwatch.StartNew(); + var channelCalibrations = new List(channels); + for (var channel = 0; channel < channels; channel++) + { + channelCalibrations.Add(CalibrateContestantChannel( + $"asio-ch{channel}", + channelSamples[channel], + sampleRate, + renderer, + expectedEvents, + scheduleOffsetSamples, + searchRadiusSamples, + delaySearchSamples)); + } + + stopwatch.Stop(); + var reference = channelCalibrations[referenceChannel]; + var paths = channelCalibrations + .Select(channel => BuildContestantPathCalibration(reference, channel, sampleRate)) + .ToArray(); + var analyzedAudioSeconds = captureSeconds * channels; + var realtimeFactor = analyzedAudioSeconds / Math.Max(stopwatch.Elapsed.TotalSeconds, 1.0e-9); + var model = new BioacousticPhysicalCalibrationModel( + Schema: "mimir.bioacoustic.physical-calibration.v1", + CreatedUtc: DateTimeOffset.UtcNow, + InputPath: inputPath, + SongId: profile.Id, + SampleRate: sampleRate, + Channels: channels, + ReferenceSourceId: reference.SourceId, + CaptureSeconds: captureSeconds, + SearchRadiusSamples: searchRadiusSamples, + ScheduleOffsetSamples: scheduleOffsetSamples, + DecodeMilliseconds: stopwatch.Elapsed.TotalMilliseconds, + RealtimeFactor: realtimeFactor, + ChannelsModel: channelCalibrations.ToArray(), + Paths: paths); + + var outputDirectory = Path.GetDirectoryName(outputPath); + if (!string.IsNullOrWhiteSpace(outputDirectory)) + { + Directory.CreateDirectory(outputDirectory); + } + + File.WriteAllText( + outputPath, + JsonSerializer.Serialize(model, new JsonSerializerOptions { WriteIndented = true })); + + Console.WriteLine( + $"contestant-calibration path={outputPath} input={inputPath} song={profile.Id} sampleRate={sampleRate} channels={channels} events={expectedEvents.Length} decodeMs={stopwatch.Elapsed.TotalMilliseconds:0.000} realtime={realtimeFactor:0.0}x budget={minRealtimeFactor:0.0}x"); + foreach (var channel in channelCalibrations) + { + Console.WriteLine( + $"contestant-calibration-channel {channel.SourceId}: events={channel.DetectedEvents}/{channel.ExpectedEvents} payload={channel.PayloadAccuracy:0.000} confidence={channel.Confidence:0.000} polarity={channel.Polarity:+0;-0;0} scheduleOffsetSamples={channel.ScheduleOffsetSamples:0.000} offsetSamples={channel.SourceOffsetSamples:0.000000} offsetUs={channel.SourceOffsetSamples * 1_000_000.0 / sampleRate:0.000} maeSamples={channel.MeanAbsoluteErrorSamples:0.000000} maeUs={channel.MeanAbsoluteErrorSamples * 1_000_000.0 / sampleRate:0.000} rms={channel.Rms:0.000000} peak={channel.Peak:0.000000} usableBands={channel.Bands.Count(band => band.Usable)}/{channel.Bands.Length}"); + } + + foreach (var path in paths) + { + Console.WriteLine( + $"contestant-calibration-path {path.ReferenceSourceId}->{path.SourceId}: delaySamples={path.DelaySamples:0.000000} delayUs={path.DelayMicroseconds:0.000} syncMaeUs={path.SyncMeanAbsoluteErrorMicroseconds:0.000} confidence={path.Confidence:0.000} gain={path.RelativeGain:0.000} polarity={path.RelativePolarity:+0;-0;0} normalizedBands={path.ResponseNormalizationBands.Count(band => band.Usable)}/{path.ResponseNormalizationBands.Length}"); + } + + if (realtimeFactor < minRealtimeFactor) + { + Console.Error.WriteLine($"contestant calibration failed budget: realtime={realtimeFactor:0.000}x below required {minRealtimeFactor:0.000}x"); + return 2; + } + + return 0; +} + static IReadOnlyList BioacousticTrainingHypotheses() { var baseProfiles = MimirBioacousticDecoderConfiguration.BuiltInProfiles @@ -2415,6 +2555,418 @@ static double ScoreContestantOffset(float[] samples, float[] template, int offse : dot / Math.Sqrt(sampleEnergy * templateEnergy); } +static BioacousticPhysicalChannelCalibration CalibrateContestantChannel( + string sourceId, + float[] samples, + int sampleRate, + MimirBioacousticContestantRenderer renderer, + IReadOnlyList expectedEvents, + double scheduleOffsetSamples, + int searchRadiusSamples, + int delaySearchSamples) +{ + var motifSamples = renderer.RenderEventMonoFloat(0, sampleRate).Length; + var channelScheduleOffsetSamples = delaySearchSamples <= 0 + ? scheduleOffsetSamples + : EstimateContestantScheduleOffset( + samples, + sampleRate, + renderer, + expectedEvents, + scheduleOffsetSamples, + delaySearchSamples, + motifSamples); + var observations = new List(expectedEvents.Count); + var payloadCorrect = 0; + foreach (var eventIndex in expectedEvents) + { + var expectedPayload = renderer.PayloadSymbolForEvent(eventIndex); + var template = renderer.RenderEventMonoFloat(eventIndex, sampleRate, expectedPayload); + var center = (int)Math.Round(renderer.EventStartSeconds(eventIndex) * sampleRate + channelScheduleOffsetSamples); + var start = Math.Max(0, center - searchRadiusSamples); + var end = Math.Min(samples.Length - motifSamples, center + searchRadiusSamples); + if (start > end) + { + continue; + } + + var bestOffset = center; + var bestScore = double.NegativeInfinity; + for (var offset = start; offset <= end; offset += 2) + { + var score = ScoreStreamingPacketOffset(samples, template, offset, motifSamples); + if (score > bestScore) + { + bestScore = score; + bestOffset = offset; + } + } + + if (bestScore < 0.06) + { + continue; + } + + var refinedOffset = RefineContestantExpectedPayloadOffset(samples, template, bestOffset, motifSamples); + var signedScore = ScoreContestantOffset(samples, template, (int)Math.Round(refinedOffset), motifSamples); + var polarity = signedScore < 0.0 ? -1 : 1; + var payload = ClassifyContestantPayloadAt(samples, sampleRate, renderer, eventIndex, refinedOffset, motifSamples); + if (payload == expectedPayload) + { + payloadCorrect++; + } + + var residual = ComputeContestantResidual(samples, template, (int)Math.Round(refinedOffset), motifSamples, signedScore); + var delaySamples = refinedOffset - renderer.EventStartSeconds(eventIndex) * sampleRate; + observations.Add(new BioacousticPhysicalEventCalibration( + eventIndex, + expectedPayload, + payload, + refinedOffset, + delaySamples, + Math.Clamp(Math.Abs(signedScore), 0.0, 1.0), + polarity, + residual, + EstimateContestantEventBands(samples, template, renderer, eventIndex, sampleRate, (int)Math.Round(refinedOffset), motifSamples))); + } + + var clock = FitContestantClockHypothesis( + observations + .Select(observation => new CepstralWordObservation( + observation.EventIndex, + observation.SampleOffset, + observation.Confidence, + observation.ExpectedPayloadSymbol, + observation.Confidence)) + .ToArray(), + renderer, + sampleRate, + expectedEvents.Count); + var sourceOffsetSamples = clock?.SourceOffsetSamples ?? 0.0; + var meanAbsoluteErrorSamples = clock?.MeanAbsoluteErrorSamples ?? 0.0; + var confidence = observations.Count == 0 + ? 0.0 + : (clock?.Confidence ?? 0.0) * 0.55 + observations.Average(observation => observation.Confidence) * 0.30 + Math.Clamp(observations.Count / (double)expectedEvents.Count, 0.0, 1.0) * 0.15; + var polarityVote = observations.Sum(observation => observation.Polarity * observation.Confidence); + return new BioacousticPhysicalChannelCalibration( + sourceId, + expectedEvents.Count, + observations.Count, + expectedEvents.Count == 0 ? 0.0 : payloadCorrect / (double)expectedEvents.Count, + confidence, + polarityVote < 0.0 ? -1 : 1, + channelScheduleOffsetSamples, + sourceOffsetSamples, + sourceOffsetSamples * 1_000_000.0 / sampleRate, + meanAbsoluteErrorSamples, + meanAbsoluteErrorSamples * 1_000_000.0 / sampleRate, + samples.Length, + RootMeanSquare(samples), + samples.Length == 0 ? 0.0 : samples.Max(sample => Math.Abs(sample)), + CollapseContestantBands(observations), + observations.ToArray()); +} + +static double EstimateContestantScheduleOffset( + float[] samples, + int sampleRate, + MimirBioacousticContestantRenderer renderer, + IReadOnlyList expectedEvents, + double seedOffsetSamples, + int delaySearchSamples, + int motifSamples) +{ + var coarseStep = Math.Max(4, sampleRate / 6_000); + var stride = Math.Max(4, sampleRate / 24_000); + var scoringEvents = expectedEvents + .Take(Math.Min(14, expectedEvents.Count)) + .ToArray(); + var scoringTemplates = scoringEvents + .Select(eventIndex => ( + EventIndex: eventIndex, + Template: renderer.RenderEventMonoFloat(eventIndex, sampleRate, renderer.PayloadSymbolForEvent(eventIndex)), + TimelineSamples: renderer.EventStartSeconds(eventIndex) * sampleRate)) + .ToArray(); + var bestOffset = seedOffsetSamples; + var bestScore = double.NegativeInfinity; + for (var candidate = (int)Math.Round(seedOffsetSamples) - delaySearchSamples; + candidate <= (int)Math.Round(seedOffsetSamples) + delaySearchSamples; + candidate += coarseStep) + { + var score = 0.0; + var count = 0; + foreach (var scoringTemplate in scoringTemplates) + { + var offset = (int)Math.Round(scoringTemplate.TimelineSamples + candidate); + var eventScore = ScoreContestantOffsetStrided(samples, scoringTemplate.Template, offset, motifSamples, stride); + if (!double.IsFinite(eventScore)) + { + continue; + } + + score += Math.Abs(eventScore); + count++; + } + + if (count == 0) + { + continue; + } + + score /= count; + if (score > bestScore) + { + bestScore = score; + bestOffset = candidate; + } + } + + var fineStart = (int)Math.Round(bestOffset) - coarseStep; + var fineEnd = (int)Math.Round(bestOffset) + coarseStep; + for (var candidate = fineStart; candidate <= fineEnd; candidate += 2) + { + var score = 0.0; + var count = 0; + foreach (var scoringTemplate in scoringTemplates) + { + var offset = (int)Math.Round(scoringTemplate.TimelineSamples + candidate); + var eventScore = ScoreContestantOffsetStrided(samples, scoringTemplate.Template, offset, motifSamples, stride); + if (!double.IsFinite(eventScore)) + { + continue; + } + + score += Math.Abs(eventScore); + count++; + } + + if (count > 0 && score / count > bestScore) + { + bestScore = score / count; + bestOffset = candidate; + } + } + + return bestOffset; +} + +static double ScoreContestantOffsetStrided(float[] samples, float[] template, int offset, int motifSamples, int stride) +{ + if (offset < 0 || offset + motifSamples > samples.Length) + { + return double.NegativeInfinity; + } + + var dot = 0.0; + var sampleEnergy = 0.0; + var templateEnergy = 0.0; + for (var index = 0; index < Math.Min(motifSamples, template.Length); index += Math.Max(1, stride)) + { + var sample = samples[offset + index]; + var expected = template[index]; + dot += sample * expected; + sampleEnergy += sample * sample; + templateEnergy += expected * expected; + } + + return sampleEnergy <= 1.0e-12 || templateEnergy <= 1.0e-12 + ? double.NegativeInfinity + : dot / Math.Sqrt(sampleEnergy * templateEnergy); +} + +static double RefineContestantExpectedPayloadOffset(float[] samples, float[] template, int bestOffset, int motifSamples) +{ + if (bestOffset <= 0 || bestOffset >= samples.Length - motifSamples - 1) + { + return bestOffset; + } + + var left = ScoreStreamingPacketOffset(samples, template, bestOffset - 1, motifSamples); + var center = ScoreStreamingPacketOffset(samples, template, bestOffset, motifSamples); + var right = ScoreStreamingPacketOffset(samples, template, bestOffset + 1, motifSamples); + var denominator = left - 2.0 * center + right; + return Math.Abs(denominator) <= 1.0e-12 + ? bestOffset + : bestOffset + Math.Clamp(0.5 * (left - right) / denominator, -0.5, 0.5); +} + +static int ClassifyContestantPayloadAt( + float[] samples, + int sampleRate, + MimirBioacousticContestantRenderer renderer, + ulong eventIndex, + double sampleOffset, + int motifSamples) +{ + var payloadCount = 1 << Math.Clamp(renderer.Profile.PayloadBitsPerEvent, 0, 8); + var offset = (int)Math.Round(sampleOffset); + var bestPayload = 0; + var bestScore = double.NegativeInfinity; + for (var payload = 0; payload < payloadCount; payload++) + { + var template = renderer.RenderEventMonoFloat(eventIndex, sampleRate, payload); + var score = ScoreStreamingPacketOffset(samples, template, offset, motifSamples); + if (score > bestScore) + { + bestScore = score; + bestPayload = payload; + } + } + + return bestPayload; +} + +static double ComputeContestantResidual(float[] samples, float[] template, int offset, int motifSamples, double signedCorrelation) +{ + if (offset < 0 || offset + motifSamples > samples.Length) + { + return 1.0; + } + + var sampleEnergy = 0.0; + var templateEnergy = 0.0; + var dot = 0.0; + for (var index = 0; index < Math.Min(motifSamples, template.Length); index++) + { + var sample = samples[offset + index]; + var expected = template[index]; + sampleEnergy += sample * sample; + templateEnergy += expected * expected; + dot += sample * expected; + } + + if (sampleEnergy <= 1.0e-12 || templateEnergy <= 1.0e-12) + { + return 1.0; + } + + var gain = dot / templateEnergy; + var residual = Math.Max(0.0, sampleEnergy - 2.0 * gain * dot + gain * gain * templateEnergy); + return Math.Sqrt(residual / sampleEnergy) * (signedCorrelation < 0.0 ? -1.0 : 1.0); +} + +static BioacousticPhysicalBandCalibration[] EstimateContestantEventBands( + float[] samples, + float[] template, + MimirBioacousticContestantRenderer renderer, + ulong eventIndex, + int sampleRate, + int offset, + int motifSamples) +{ + if (offset < 0 || offset + motifSamples > samples.Length) + { + return []; + } + + var bands = EstimateContestantBandCenters(renderer, eventIndex); + var output = new BioacousticPhysicalBandCalibration[bands.Length]; + for (var index = 0; index < bands.Length; index++) + { + var centerHz = bands[index]; + var bandStart = (int)Math.Round(index * motifSamples / (double)Math.Max(1, bands.Length + 1)); + var bandLength = Math.Max(1, Math.Min(motifSamples - bandStart, motifSamples / Math.Max(3, bands.Length))); + var observed = WindowMeanSquare(samples.AsSpan(offset + bandStart, bandLength)); + var expected = WindowMeanSquare(template.AsSpan(bandStart, Math.Min(bandLength, template.Length - bandStart))); + var gain = expected <= 1.0e-12 ? 0.0 : Math.Sqrt(Math.Max(0.0, observed) / expected); + output[index] = new BioacousticPhysicalBandCalibration(centerHz, observed, expected, gain, observed > expected * 0.08); + } + + return output; +} + +static double[] EstimateContestantBandCenters(MimirBioacousticContestantRenderer renderer, ulong eventIndex) +{ + var symbolId = (int)((eventIndex * 73UL + eventIndex / 5UL * 19UL) % MimirBioacousticContestants.SymbolCount); + var t = symbolId / (double)(MimirBioacousticContestants.SymbolCount - 1); + var root = Math.Exp(Math.Log(renderer.Profile.LowestRootHz) + (Math.Log(renderer.Profile.HighestRootHz) - Math.Log(renderer.Profile.LowestRootHz)) * t); + var centers = new double[Math.Min(renderer.Profile.SyllableCount, 8)]; + for (var index = 0; index < centers.Length; index++) + { + centers[index] = Math.Clamp(root * Math.Pow(2.0, (-0.5 + index * 0.72) / 12.0), 200.0, renderer.Profile.HighestRootHz * 1.8); + } + + return centers; +} + +static double WindowMeanSquare(ReadOnlySpan samples) +{ + if (samples.Length == 0) + { + return 0.0; + } + + var energy = 0.0; + for (var index = 0; index < samples.Length; index++) + { + energy += samples[index] * samples[index]; + } + + return energy / samples.Length; +} + +static BioacousticPhysicalBandCalibration[] CollapseContestantBands(IReadOnlyList observations) +{ + return observations + .SelectMany(observation => observation.Bands) + .GroupBy(band => Math.Round(band.CenterHz / 25.0) * 25.0) + .Select(group => new BioacousticPhysicalBandCalibration( + group.Key, + group.Average(band => band.ObservedEnergy), + group.Average(band => band.ExpectedEnergy), + group.Average(band => band.Gain), + group.Count(band => band.Usable) >= Math.Max(1, group.Count() / 2))) + .OrderBy(band => band.CenterHz) + .ToArray(); +} + +static BioacousticPhysicalPathCalibration BuildContestantPathCalibration( + BioacousticPhysicalChannelCalibration reference, + BioacousticPhysicalChannelCalibration candidate, + int sampleRate) +{ + var candidateByEvent = candidate.Events.ToDictionary(observation => observation.EventIndex); + var matched = reference.Events + .Where(observation => candidateByEvent.ContainsKey(observation.EventIndex)) + .Select(observation => + { + var other = candidateByEvent[observation.EventIndex]; + var weight = Math.Sqrt(observation.Confidence * other.Confidence); + return (Delay: other.SampleOffset - observation.SampleOffset, Weight: weight); + }) + .ToArray(); + var delay = matched.Length == 0 + ? candidate.SourceOffsetSamples - reference.SourceOffsetSamples + : matched.Sum(pair => pair.Delay * Math.Max(pair.Weight, 1.0e-6)) / matched.Sum(pair => Math.Max(pair.Weight, 1.0e-6)); + var mae = matched.Length == 0 + ? Math.Abs(candidate.MeanAbsoluteErrorSamples - reference.MeanAbsoluteErrorSamples) + : matched.Sum(pair => Math.Abs(pair.Delay - delay) * Math.Max(pair.Weight, 1.0e-6)) / matched.Sum(pair => Math.Max(pair.Weight, 1.0e-6)); + var relativeGain = reference.Rms <= 1.0e-12 ? 0.0 : candidate.Rms / reference.Rms; + var referenceBands = reference.Bands.ToDictionary(band => band.CenterHz); + var normalizedBands = candidate.Bands + .Select(band => + { + var normalizer = referenceBands.TryGetValue(band.CenterHz, out var referenceBand) && referenceBand.Gain > 1.0e-12 + ? referenceBand.Gain + : 1.0; + return band with { Gain = band.Gain / normalizer }; + }) + .ToArray(); + var confidence = Math.Sqrt(reference.Confidence * candidate.Confidence) * + (1.0 / (1.0 + mae / Math.Max(1.0, sampleRate * 0.00010))); + return new BioacousticPhysicalPathCalibration( + reference.SourceId, + candidate.SourceId, + delay, + delay * 1_000_000.0 / sampleRate, + mae, + mae * 1_000_000.0 / sampleRate, + confidence, + relativeGain, + reference.Polarity * candidate.Polarity, + normalizedBands); +} + static IReadOnlyDictionary ClassifyContestantPayloads( float[] samples, int sampleRate, @@ -3563,3 +4115,67 @@ public sealed record BioacousticContestantObservation( double SampleOffset, double Confidence, double ShapeAccuracy); + +public sealed record BioacousticPhysicalCalibrationModel( + string Schema, + DateTimeOffset CreatedUtc, + string InputPath, + string SongId, + int SampleRate, + int Channels, + string ReferenceSourceId, + double CaptureSeconds, + int SearchRadiusSamples, + double ScheduleOffsetSamples, + double DecodeMilliseconds, + double RealtimeFactor, + BioacousticPhysicalChannelCalibration[] ChannelsModel, + BioacousticPhysicalPathCalibration[] Paths); + +public sealed record BioacousticPhysicalChannelCalibration( + string SourceId, + int ExpectedEvents, + int DetectedEvents, + double PayloadAccuracy, + double Confidence, + int Polarity, + double ScheduleOffsetSamples, + double SourceOffsetSamples, + double SourceOffsetMicroseconds, + double MeanAbsoluteErrorSamples, + double MeanAbsoluteErrorMicroseconds, + int SampleCount, + double Rms, + double Peak, + BioacousticPhysicalBandCalibration[] Bands, + BioacousticPhysicalEventCalibration[] Events); + +public sealed record BioacousticPhysicalPathCalibration( + string ReferenceSourceId, + string SourceId, + double DelaySamples, + double DelayMicroseconds, + double SyncMeanAbsoluteErrorSamples, + double SyncMeanAbsoluteErrorMicroseconds, + double Confidence, + double RelativeGain, + int RelativePolarity, + BioacousticPhysicalBandCalibration[] ResponseNormalizationBands); + +public sealed record BioacousticPhysicalEventCalibration( + ulong EventIndex, + int ExpectedPayloadSymbol, + int ObservedPayloadSymbol, + double SampleOffset, + double DelaySamples, + double Confidence, + int Polarity, + double NormalizedResidual, + BioacousticPhysicalBandCalibration[] Bands); + +public sealed record BioacousticPhysicalBandCalibration( + double CenterHz, + double ObservedEnergy, + double ExpectedEnergy, + double Gain, + bool Usable); diff --git a/state/evidence.jsonl b/state/evidence.jsonl index 0d9bbb6..fb514a7 100644 --- a/state/evidence.jsonl +++ b/state/evidence.jsonl @@ -93,3 +93,4 @@ {"ts": "2026-05-24T22:47:10+01:00", "type": "verification", "status": "ok", "note": "Verified faust/mimir_packet_razor_frontend.dsp with Faust 2.85.5 C++ generation. The DSP front-end exposes 16 log-spaced resonant band-energy outputs plus 16 positive-flux outputs for the packet razor streaming receiver lowering target."} {"ts": "2026-05-24T23:04:57+01:00", "type": "experiment", "status": "partial", "note": "First real-world packet razor ASIO test: rendered canary-packet-trill at 192 kHz, played through Focusrite ASIO, captured four inputs. Corrected probe needed --set-sample-rate 192000; first run stayed at 44.1 kHz. Loopback channels 2/3 correlated at +1623 samples and decoded 37/37 events with payload=1.000, timing=1.000, delay=8453.125 us. Acoustic channel 1 decoded only 1/37 and channel 0 none, so room/mic path still needs acquisition/level/channel work."} {"ts": "2026-05-24T23:10:02+01:00", "type": "experiment", "status": "partial", "note": "Second physical 192 kHz packet run with cardioid and co-streamer shotgun: loopback channels 2/3 still decode 37/37 payload=1.000 at offset 1623 samples. Shotgun channel 1 locks with per-channel offset 2122 samples: 37/37 payload=1.000, timing=0.828, delay=11166.397 us. Cardioid channel 0 partially decodes at offset 2519: 26/37 payload=0.595. Added polarity-invariant scoring for the streaming packet-local path because mic correlations were inverted."} +{"ts": "2026-05-24T23:22:46+01:00", "type": "experiment", "status": "partial", "note": "Promoted canary-packet physical ASIO calibration into a persisted bioacoustic response model at calibration/bioacoustic/scarlett-canary-packet-192k-rerun.json. The command clears the hot-loop budget at 10.7x realtime across four 192 kHz channels after template caching and two-sample coarse search with sub-sample refinement. Loopback channels remain 37/37 with 2.524 us MAE. Co-streamer shotgun reaches 37/37 payload=1.000 with 58.785 us MAE and 2.940 ms acoustic delay relative to loopback. Cardioid reaches 26/37 payload=0.703 with 90.558 us MAE and 4.636 ms acoustic delay. This is exact enough to build response normalization and propagation-delay profiles, but not yet true microsecond sync for physical mics."} diff --git a/state/map.yaml b/state/map.yaml index 65849cb..0dfc674 100644 --- a/state/map.yaml +++ b/state/map.yaml @@ -174,6 +174,15 @@ accepted_design: 192 kHz ingested more than 12,000 sample-bearing blocks across `asio-ch0` through `asio-ch3` and retained 2,048 blocks per channel, all from the Focusrite ASIO callback stream. + `Mimir.BufferSmoke --calibrate-contestant-asio-f32` now persists the active + packet-song physical response model under `calibration/bioacoustic/`, + including per-channel delay search, polarity, payload reliability, + response-normalization bands, gain, confidence, and pairwise propagation + delay. The latest canary-packet Scarlett receipt runs at 10.7x realtime + across four 192 kHz channels: loopback is 37/37 with 2.524 us MAE, + co-streamer shotgun is 37/37 payload with 58.785 us MAE, and the cardioid + is 26/37 with 90.558 us MAE. This is a serious calibration surface, not yet + true physical microsecond sync. Acoustic robustness remains open. The old arbitrary-chirplet matcher is a diagnostic/reference artifact only, not the runtime hot path.