FA-70576 / GIS polygon topology / Open access

Grid snapping with ring collapse handling: collapse threshold · case 01

Rings collapsed to a doubled segment are kept.

Verified by executionVariant 1 · 8 checks per implementationDownload source bundle ↓JSON ↗

ROOT CAUSE

The collapse threshold counts 3 positions as a ring.

THE FAILURE

The collapse threshold counts 3 positions as a ring.

Unsuccessful approach: Requiring 5 positions discards valid snapped triangles.

Case contract

Input [rings, g]: polygon rings (exterior first), closed, numeric coordinates; grid size g > 0 anchored at 0. Each coordinate snaps to floor(v/g + 0.5)*g (halves round toward +infinity). Consecutive identical snapped positions are merged. A ring left with fewer than 4 positions has collapsed: if it is the exterior return None, otherwise drop that hole. Return the snapped rings.

Why this case matters

Precision reduction for storage, tiling and topology cleaning snaps vertices to a grid; collapse rules decide whether tiny holes vanish or the polygon is discarded.

1 / The failure

Exit 1

"""Failure Map reference implementation. Python standard library only."""
import json
import math
N = 1
observations = []
def solve(x):
    rings, g = x
    def snap(v):
        return math.floor(v / g + 0.5) * g
    out = []
    for k, ring in enumerate(rings):
        pts = []
        for p in ring:
            q = [snap(p[0]), snap(p[1])]
            if not pts or pts[-1] != q:
                pts.append(q)
        if len(pts) < 3:
            if k == 0:
                return None
            continue
        out.append(pts)
    return out
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('control #0', [[[[0.2, 0.1], [9.7, 0.4], [9.6, 9.8], [0.3, 9.9], [0.2, 0.1]]], 1], [[[0, 0], [10, 0], [10, 10], [0, 10], [0, 0]]]), ('regression #1', [[[[0.5, 0.5], [10.5, 0.5], [10.5, 10.5], [0.5, 10.5], [0.5, 0.5]]], 1], [[[1, 1], [11, 1], [11, 11], [1, 11], [1, 1]]]), ('regression #2', [[[[-2.5, -2.5], [7.5, -2.5], [7.5, 3.5], [-2.5, 3.5], [-2.5, -2.5]]], 1], [[[-2, -2], [8, -2], [8, 4], [-2, 4], [-2, -2]]]), ('regression #3', [[[[-1.4, -1.4], [6.2, -1.4], [6.2, 6.2], [-1.4, 6.2], [-1.4, -1.4]]], 2], [[[-2, -2], [6, -2], [6, 6], [-2, 6], [-2, -2]]]), ('boundary #4', [[[[0, 0], [0.4, 0.2], [0.3, 0.4], [0, 0]]], 1], None), ('boundary #5', [[[[0, 0], [2.2, 0], [2, 1.6], [0, 0]]], 1], [[[0, 0], [2, 0], [2, 2], [0, 0]]]), ('regression #6', [[[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[5.1, 5.1], [5.2, 5.3], [5.4, 5.1], [5.1, 5.1]]], 1], [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]]]), ('boundary #19', [[[[0, 0], [2.2, 0], [2, 0.4], [0, 0]]], 1], None)], [('regression #3', [[[[-1.4, -1.4], [6.2, -1.4], [6.2, 6.2], [-1.4, 6.2], [-1.4, -1.4]]], 2], [[[-2, -2], [6, -2], [6, 6], [-2, 6], [-2, -2]]]), ('boundary #4', [[[[0, 0], [0.4, 0.2], [0.3, 0.4], [0, 0]]], 1], None), ('boundary #5', [[[[0, 0], [2.2, 0], [2, 1.6], [0, 0]]], 1], [[[0, 0], [2, 0], [2, 2], [0, 0]]]), ('regression #6', [[[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[5.1, 5.1], [5.2, 5.3], [5.4, 5.1], [5.1, 5.1]]], 1], [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]]]), ('regression #7', [[[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[5.1, 5.1], [5.2, 5.3], [5.4, 5.1], [5.1, 5.1]], [[10, 10], [10, 14], [14, 14], [14, 10], [10, 10]]], 1], [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[10, 10], [10, 14], [14, 14], [14, 10], [10, 10]]]), ('control #8', [[[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[4, 4], [4, 8], [8, 8], [8, 4], [4, 4]]], 5], [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[5, 5], [5, 10], [10, 10], [10, 5], [5, 5]]]), ('control #11', [[[[1.26, 2.74], [8.33, 2.51], [7.9, 9.49], [1.26, 2.74]]], 0.5], [[[1.5, 2.5], [8.5, 2.5], [8.0, 9.5], [1.5, 2.5]]]), ('boundary #20', [[[[0, 0], [9, 0], [9, 9], [0, 9], [0, 0]], [[3, 3], [5.2, 3], [5, 3.4], [3, 3]]], 1], [[[0, 0], [9, 0], [9, 9], [0, 9], [0, 0]]])], [('regression #6', [[[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[5.1, 5.1], [5.2, 5.3], [5.4, 5.1], [5.1, 5.1]]], 1], [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]]]), ('regression #7', [[[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[5.1, 5.1], [5.2, 5.3], [5.4, 5.1], [5.1, 5.1]], [[10, 10], [10, 14], [14, 14], [14, 10], [10, 10]]], 1], [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[10, 10], [10, 14], [14, 14], [14, 10], [10, 10]]]), ('control #8', [[[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[4, 4], [4, 8], [8, 8], [8, 4], [4, 4]]], 5], [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[5, 5], [5, 10], [10, 10], [10, 5], [5, 5]]]), ('regression #9', [[[[0, 0], [10.4, 0.3], [10.6, 0.2], [10.2, 10.2], [0, 10], [0, 0]]], 1], [[[0, 0], [10, 0], [11, 0], [10, 10], [0, 10], [0, 0]]]), ('regression #10', [[[[0, 0], [3, 0], [3.2, 0.2], [3, 3], [0, 3], [0, 0]]], 1], [[[0, 0], [3, 0], [3, 3], [0, 3], [0, 0]]]), ('control #11', [[[[1.26, 2.74], [8.33, 2.51], [7.9, 9.49], [1.26, 2.74]]], 0.5], [[[1.5, 2.5], [8.5, 2.5], [8.0, 9.5], [1.5, 2.5]]]), ('regression #12', [[[[1.25, 2.75], [8.25, 2.25], [7.75, 9.75], [1.25, 2.75]]], 0.5], [[[1.5, 3.0], [8.5, 2.5], [8.0, 10.0], [1.5, 3.0]]]), ('boundary #19', [[[[0, 0], [2.2, 0], [2, 0.4], [0, 0]]], 1], None)], [('regression #9', [[[[0, 0], [10.4, 0.3], [10.6, 0.2], [10.2, 10.2], [0, 10], [0, 0]]], 1], [[[0, 0], [10, 0], [11, 0], [10, 10], [0, 10], [0, 0]]]), ('regression #10', [[[[0, 0], [3, 0], [3.2, 0.2], [3, 3], [0, 3], [0, 0]]], 1], [[[0, 0], [3, 0], [3, 3], [0, 3], [0, 0]]]), ('control #11', [[[[1.26, 2.74], [8.33, 2.51], [7.9, 9.49], [1.26, 2.74]]], 0.5], [[[1.5, 2.5], [8.5, 2.5], [8.0, 9.5], [1.5, 2.5]]]), ('regression #12', [[[[1.25, 2.75], [8.25, 2.25], [7.75, 9.75], [1.25, 2.75]]], 0.5], [[[1.5, 3.0], [8.5, 2.5], [8.0, 10.0], [1.5, 3.0]]]), ('regression #13', [[[[-0.5, 0], [4, 0], [4, 4], [-0.5, 0]]], 1], [[[0, 0], [4, 0], [4, 4], [0, 0]]]), ('boundary #14', [[[[0, 0], [4.4, 0], [4.6, 0.4], [0, 0]]], 1], [[[0, 0], [4, 0], [5, 0], [0, 0]]]), ('control #15', [[[[12, 13], [48, 11], [51, 47], [9, 52], [12, 13]]], 10], [[[10, 10], [50, 10], [50, 50], [10, 50], [10, 10]]]), ('boundary #20', [[[[0, 0], [9, 0], [9, 9], [0, 9], [0, 0]], [[3, 3], [5.2, 3], [5, 3.4], [3, 3]]], 1], [[[0, 0], [9, 0], [9, 9], [0, 9], [0, 0]]])], [('regression #12', [[[[1.25, 2.75], [8.25, 2.25], [7.75, 9.75], [1.25, 2.75]]], 0.5], [[[1.5, 3.0], [8.5, 2.5], [8.0, 10.0], [1.5, 3.0]]]), ('regression #13', [[[[-0.5, 0], [4, 0], [4, 4], [-0.5, 0]]], 1], [[[0, 0], [4, 0], [4, 4], [0, 0]]]), ('boundary #14', [[[[0, 0], [4.4, 0], [4.6, 0.4], [0, 0]]], 1], [[[0, 0], [4, 0], [5, 0], [0, 0]]]), ('control #15', [[[[12, 13], [48, 11], [51, 47], [9, 52], [12, 13]]], 10], [[[10, 10], [50, 10], [50, 50], [10, 50], [10, 10]]]), ('regression #16', [[[[15, 25], [45, 25], [45, 55], [15, 55], [15, 25]]], 10], [[[20, 30], [50, 30], [50, 60], [20, 60], [20, 30]]]), ('boundary #17', [[[[0, 0], [1, 0], [1, 1], [0, 1], [0, 0]]], 5], None), ('regression #18', [[[[0, 0], [5, 0], [5, 5], [5.2, 0.1], [8, 0], [8, 8], [0, 8], [0, 0]]], 1], [[[0, 0], [5, 0], [5, 5], [5, 0], [8, 0], [8, 8], [0, 8], [0, 0]]]), ('boundary #19', [[[[0, 0], [2.2, 0], [2, 0.4], [0, 0]]], 1], None)]]
for label, args, expected in fixtures[N-1]:
    check(label, solve(args), expected)
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 fixture	Actual	Expected	Outcome
control #0	`[[[0, 0], [10, 0], [10, 10], [0, 10], [0, 0]]]`	`[[[0, 0], [10, 0], [10, 10], [0, 10], [0, 0]]]`	Passed
regression #1	`[[[1, 1], [11, 1], [11, 11], [1, 11], [1, 1]]]`	`[[[1, 1], [11, 1], [11, 11], [1, 11], [1, 1]]]`	Passed
regression #2	`[[[-2, -2], [8, -2], [8, 4], [-2, 4], [-2, -2]]]`	`[[[-2, -2], [8, -2], [8, 4], [-2, 4], [-2, -2]]]`	Passed
regression #3	`[[[-2, -2], [6, -2], [6, 6], [-2, 6], [-2, -2]]]`	`[[[-2, -2], [6, -2], [6, 6], [-2, 6], [-2, -2]]]`	Passed
boundary #4	`None`	`None`	Passed
boundary #5	`[[[0, 0], [2, 0], [2, 2], [0, 0]]]`	`[[[0, 0], [2, 0], [2, 2], [0, 0]]]`	Passed
regression #6	`[[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]]]`	`[[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]]]`	Passed
boundary #19	`[[[0, 0], [2, 0], [0, 0]]]`	`None`	Failed

SHA-256 / c64dffa91816f2edf5a9ee9f1afbe6e0c6dcd819d116367f48791941b0082a63

2 / The unsuccessful fix

Exit 1

"""Failure Map reference implementation. Python standard library only."""
import json
import math
N = 1
observations = []
def solve(x):
    rings, g = x
    def snap(v):
        return math.floor(v / g + 0.5) * g
    out = []
    for k, ring in enumerate(rings):
        pts = []
        for p in ring:
            q = [snap(p[0]), snap(p[1])]
            if not pts or pts[-1] != q:
                pts.append(q)
        if len(pts) < 5:
            if k == 0:
                return None
            continue
        out.append(pts)
    return out
def check(label, actual, expected):
    observations.append({"check": label, "actual": actual, "expected": expected, "passed": actual == expected})
fixtures = [[('control #0', [[[[0.2, 0.1], [9.7, 0.4], [9.6, 9.8], [0.3, 9.9], [0.2, 0.1]]], 1], [[[0, 0], [10, 0], [10, 10], [0, 10], [0, 0]]]), ('regression #1', [[[[0.5, 0.5], [10.5, 0.5], [10.5, 10.5], [0.5, 10.5], [0.5, 0.5]]], 1], [[[1, 1], [11, 1], [11, 11], [1, 11], [1, 1]]]), ('regression #2', [[[[-2.5, -2.5], [7.5, -2.5], [7.5, 3.5], [-2.5, 3.5], [-2.5, -2.5]]], 1], [[[-2, -2], [8, -2], [8, 4], [-2, 4], [-2, -2]]]), ('regression #3', [[[[-1.4, -1.4], [6.2, -1.4], [6.2, 6.2], [-1.4, 6.2], [-1.4, -1.4]]], 2], [[[-2, -2], [6, -2], [6, 6], [-2, 6], [-2, -2]]]), ('boundary #4', [[[[0, 0], [0.4, 0.2], [0.3, 0.4], [0, 0]]], 1], None), ('boundary #5', [[[[0, 0], [2.2, 0], [2, 1.6], [0, 0]]], 1], [[[0, 0], [2, 0], [2, 2], [0, 0]]]), ('regression #6', [[[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[5.1, 5.1], [5.2, 5.3], [5.4, 5.1], [5.1, 5.1]]], 1], [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]]]), ('boundary #19', [[[[0, 0], [2.2, 0], [2, 0.4], [0, 0]]], 1], None)], [('regression #3', [[[[-1.4, -1.4], [6.2, -1.4], [6.2, 6.2], [-1.4, 6.2], [-1.4, -1.4]]], 2], [[[-2, -2], [6, -2], [6, 6], [-2, 6], [-2, -2]]]), ('boundary #4', [[[[0, 0], [0.4, 0.2], [0.3, 0.4], [0, 0]]], 1], None), ('boundary #5', [[[[0, 0], [2.2, 0], [2, 1.6], [0, 0]]], 1], [[[0, 0], [2, 0], [2, 2], [0, 0]]]), ('regression #6', [[[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[5.1, 5.1], [5.2, 5.3], [5.4, 5.1], [5.1, 5.1]]], 1], [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]]]), ('regression #7', [[[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[5.1, 5.1], [5.2, 5.3], [5.4, 5.1], [5.1, 5.1]], [[10, 10], [10, 14], [14, 14], [14, 10], [10, 10]]], 1], [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[10, 10], [10, 14], [14, 14], [14, 10], [10, 10]]]), ('control #8', [[[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[4, 4], [4, 8], [8, 8], [8, 4], [4, 4]]], 5], [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[5, 5], [5, 10], [10, 10], [10, 5], [5, 5]]]), ('control #11', [[[[1.26, 2.74], [8.33, 2.51], [7.9, 9.49], [1.26, 2.74]]], 0.5], [[[1.5, 2.5], [8.5, 2.5], [8.0, 9.5], [1.5, 2.5]]]), ('boundary #20', [[[[0, 0], [9, 0], [9, 9], [0, 9], [0, 0]], [[3, 3], [5.2, 3], [5, 3.4], [3, 3]]], 1], [[[0, 0], [9, 0], [9, 9], [0, 9], [0, 0]]])], [('regression #6', [[[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[5.1, 5.1], [5.2, 5.3], [5.4, 5.1], [5.1, 5.1]]], 1], [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]]]), ('regression #7', [[[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[5.1, 5.1], [5.2, 5.3], [5.4, 5.1], [5.1, 5.1]], [[10, 10], [10, 14], [14, 14], [14, 10], [10, 10]]], 1], [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[10, 10], [10, 14], [14, 14], [14, 10], [10, 10]]]), ('control #8', [[[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[4, 4], [4, 8], [8, 8], [8, 4], [4, 4]]], 5], [[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]], [[5, 5], [5, 10], [10, 10], [10, 5], [5, 5]]]), ('regression #9', [[[[0, 0], [10.4, 0.3], [10.6, 0.2], [10.2, 10.2], [0, 10], [0, 0]]], 1], [[[0, 0], [10, 0], [11, 0], [10, 10], [0, 10], [0, 0]]]), ('regression #10', [[[[0, 0], [3, 0], [3.2, 0.2], [3, 3], [0, 3], [0, 0]]], 1], [[[0, 0], [3, 0], [3, 3], [0, 3], [0, 0]]]), ('control #11', [[[[1.26, 2.74], [8.33, 2.51], [7.9, 9.49], [1.26, 2.74]]], 0.5], [[[1.5, 2.5], [8.5, 2.5], [8.0, 9.5], [1.5, 2.5]]]), ('regression #12', [[[[1.25, 2.75], [8.25, 2.25], [7.75, 9.75], [1.25, 2.75]]], 0.5], [[[1.5, 3.0], [8.5, 2.5], [8.0, 10.0], [1.5, 3.0]]]), ('boundary #19', [[[[0, 0], [2.2, 0], [2, 0.4], [0, 0]]], 1], None)], [('regression #9', [[[[0, 0], [10.4, 0.3], [10.6, 0.2], [10.2, 10.2], [0, 10], [0, 0]]], 1], [[[0, 0], [10, 0], [11, 0], [10, 10], [0, 10], [0, 0]]]), ('regression #10', [[[[0, 0], [3, 0], [3.2, 0.2], [3, 3], [0, 3], [0, 0]]], 1], [[[0, 0], [3, 0], [3, 3], [0, 3], [0, 0]]]), ('control #11', [[[[1.26, 2.74], [8.33, 2.51], [7.9, 9.49], [1.26, 2.74]]], 0.5], [[[1.5, 2.5], [8.5, 2.5], [8.0, 9.5], [1.5, 2.5]]]), ('regression #12', [[[[1.25, 2.75], [8.25, 2.25], [7.75, 9.75], [1.25, 2.75]]], 0.5], [[[1.5, 3.0], [8.5, 2.5], [8.0, 10.0], [1.5, 3.0]]]), ('regression #13', [[[[-0.5, 0], [4, 0], [4, 4], [-0.5, 0]]], 1], [[[0, 0], [4, 0], [4, 4], [0, 0]]]), ('boundary #14', [[[[0, 0], [4.4, 0], [4.6, 0.4], [0, 0]]], 1], [[[0, 0], [4, 0], [5, 0], [0, 0]]]), ('control #15', [[[[12, 13], [48, 11], [51, 47], [9, 52], [12, 13]]], 10], [[[10, 10], [50, 10], [50, 50], [10, 50], [10, 10]]]), ('boundary #20', [[[[0, 0], [9, 0], [9, 9], [0, 9], [0, 0]], [[3, 3], [5.2, 3], [5, 3.4], [3, 3]]], 1], [[[0, 0], [9, 0], [9, 9], [0, 9], [0, 0]]])], [('regression #12', [[[[1.25, 2.75], [8.25, 2.25], [7.75, 9.75], [1.25, 2.75]]], 0.5], [[[1.5, 3.0], [8.5, 2.5], [8.0, 10.0], [1.5, 3.0]]]), ('regression #13', [[[[-0.5, 0], [4, 0], [4, 4], [-0.5, 0]]], 1], [[[0, 0], [4, 0], [4, 4], [0, 0]]]), ('boundary #14', [[[[0, 0], [4.4, 0], [4.6, 0.4], [0, 0]]], 1], [[[0, 0], [4, 0], [5, 0], [0, 0]]]), ('control #15', [[[[12, 13], [48, 11], [51, 47], [9, 52], [12, 13]]], 10], [[[10, 10], [50, 10], [50, 50], [10, 50], [10, 10]]]), ('regression #16', [[[[15, 25], [45, 25], [45, 55], [15, 55], [15, 25]]], 10], [[[20, 30], [50, 30], [50, 60], [20, 60], [20, 30]]]), ('boundary #17', [[[[0, 0], [1, 0], [1, 1], [0, 1], [0, 0]]], 5], None), ('regression #18', [[[[0, 0], [5, 0], [5, 5], [5.2, 0.1], [8, 0], [8, 8], [0, 8], [0, 0]]], 1], [[[0, 0], [5, 0], [5, 5], [5, 0], [8, 0], [8, 8], [0, 8], [0, 0]]]), ('boundary #19', [[[[0, 0], [2.2, 0], [2, 0.4], [0, 0]]], 1], None)]]
for label, args, expected in fixtures[N-1]:
    check(label, solve(args), expected)
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 fixture	Actual	Expected	Outcome
control #0	`[[[0, 0], [10, 0], [10, 10], [0, 10], [0, 0]]]`	`[[[0, 0], [10, 0], [10, 10], [0, 10], [0, 0]]]`	Passed
regression #1	`[[[1, 1], [11, 1], [11, 11], [1, 11], [1, 1]]]`	`[[[1, 1], [11, 1], [11, 11], [1, 11], [1, 1]]]`	Passed
regression #2	`[[[-2, -2], [8, -2], [8, 4], [-2, 4], [-2, -2]]]`	`[[[-2, -2], [8, -2], [8, 4], [-2, 4], [-2, -2]]]`	Passed
regression #3	`[[[-2, -2], [6, -2], [6, 6], [-2, 6], [-2, -2]]]`	`[[[-2, -2], [6, -2], [6, 6], [-2, 6], [-2, -2]]]`	Passed
boundary #4	`None`	`None`	Passed
boundary #5	`None`	`[[[0, 0], [2, 0], [2, 2], [0, 0]]]`	Failed
regression #6	`[[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]]]`	`[[[0, 0], [20, 0], [20, 20], [0, 20], [0, 0]]]`	Passed
boundary #19	`None`	`None`	Passed

SHA-256 / 5d0bd9ffbbcf092732760d316800fa2f3e64c5bbc7986359d4eb22b184de42bf

HELD IN THE MEMBER ARCHIVE

The verified repair and its recorded checks are member-only.

This mechanism has 8 recorded checks per implementation. The open-access tier publishes the failure and the unsuccessful fix; the repaired source that passes every check, and the observations that prove it, are available to members.

Every case sharing this mechanism uses the same contract and the same repair, so this one record is held back for all of them.

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Verification & scope

Stipulated deterministic toy contract on a bounded input domain; results are rounded as stated and no conformance with any published standard or library is claimed. 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 2026-09-29T14:48:21.953047+00:00.

Case digest / 2f4fa184d5b9b3ea1ca44bcb719fef0249bbb5c3f122c9feee2d7c8aaa5802cb