FAILURE MAP
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FA-11016 / Audio channel mixing / Open access

Mid side encode normalization · case 01

An unnormalized mid/side matrix doubles channel amplitudes.

Verified by executionVariant 1 · 4 checks per implementationDownload source bundle ↓JSON ↗

ROOT CAUSE

An unnormalized mid/side matrix doubles channel amplitudes.

VERIFIED REPAIR

Apply the explicit PCM/playback contract: Encode stereo left/right frames as normalized mid=(L+R)/2 and side=(L-R)/2 for a sum/difference channel representation.

Unsuccessful approach: Reversed subtraction swaps the spatial sign of the side channel.

Case contract

Encode stereo left/right frames as normalized mid=(L+R)/2 and side=(L-R)/2 for a sum/difference channel representation.

Why this case matters

A pure Python local audio pipeline stage with explicit sample formats and frame conventions; no real-time device or signal-spectrum claims.

1 / The failure

Exit 1
"""Failure Map reference implementation. Python standard library only."""
import json
import math
N = 1
observations = []
def solve(frames):
    return [[left+right,left-right] for left,right in frames]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('fixture 1',solve(*([[1, 1]],)),[[1, 0]])
check('fixture 2',solve(*([[1, -1]],)),[[0, 1]])
check('fixture 3',solve(*([[0, 1]],)),[[0.5, -0.5]])
check('fixture 4',solve(*([],)),[])
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)
Boundary fixtureActualExpectedOutcome
fixture 1[[2, 0]][[1, 0]]Failed
fixture 2[[0, 2]][[0, 1]]Failed
fixture 3[[1, -1]][[0.5, -0.5]]Failed
fixture 4[][]Passed

SHA-256 / 2ac788778a9d11777f2a6f7b3a851c2f78a0ba1c7fb8bcdf9806241b784aa283

2 / The unsuccessful fix

Exit 1
"""Failure Map reference implementation. Python standard library only."""
import json
import math
N = 1
observations = []
def solve(frames):
    return [[(left+right)/2,(right-left)/2] for left,right in frames]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('fixture 1',solve(*([[1, 1]],)),[[1, 0]])
check('fixture 2',solve(*([[1, -1]],)),[[0, 1]])
check('fixture 3',solve(*([[0, 1]],)),[[0.5, -0.5]])
check('fixture 4',solve(*([],)),[])
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)
Boundary fixtureActualExpectedOutcome
fixture 1[[1.0, 0.0]][[1, 0]]Passed
fixture 2[[0.0, -1.0]][[0, 1]]Failed
fixture 3[[0.5, 0.5]][[0.5, -0.5]]Failed
fixture 4[][]Passed

SHA-256 / 6b947d37b4134574e7b511ee71ba73f78d2fca09ab748ab3734763e57c2a1c52

3 / The verified repair

Exit 0
"""Failure Map reference implementation. Python standard library only."""
import json
import math
N = 1
observations = []
def solve(frames):
    return [[(left+right)/2,(left-right)/2] for left,right in frames]
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
check('fixture 1',solve(*([[1, 1]],)),[[1, 0]])
check('fixture 2',solve(*([[1, -1]],)),[[0, 1]])
check('fixture 3',solve(*([[0, 1]],)),[[0.5, -0.5]])
check('fixture 4',solve(*([],)),[])
print(json.dumps({"observations": observations, "passed": all(x["passed"] for x in observations)}, ensure_ascii=False))
raise SystemExit(0 if all(x["passed"] for x in observations) else 1)
Boundary fixtureActualExpectedOutcome
fixture 1[[1.0, 0.0]][[1, 0]]Passed
fixture 2[[0.0, 1.0]][[0, 1]]Passed
fixture 3[[0.5, -0.5]][[0.5, -0.5]]Passed
fixture 4[][]Passed

SHA-256 / d6d11469bef7a57bf76c611aa7cf3e2b794aee7ba18b5d68bb64f096325f2474

Verification & scope

This reproducer isolates one failure mechanism. Results cover the supplied fixtures. Variants within a family share a test contract and should remain grouped when constructing evaluation splits. Related mechanisms with a shared evaluation_group must also remain together; these controlled models are not independent production incidents.

Observations recorded using Python 3.12.14 at 2026-09-29T14:38:44.302927+00:00.

Case digest / 194a188348c564fab8a59f4f14bd9d10fa03b77299eb2e9dfa7edb84cbd13dad