{"abstract":"Coastlines shift inland compared to the floor rule.","category":"Procedural level generation constraints","checks":8,"contract":"Each cell height becomes floor(mean) of the in-bounds cells in its 3x3 window (input values only). Class: '~' when v < sea, 's' beach when v < sea+2, 'g' when v < mountain, otherwise '^'. Returns strings per row.","evaluation_group":"w2-procedural-level-generation-constraints-height-classify","failed_approach":"Ceiling division raises every fractional mean.","family":"w2-procedural-level-generation-constraints-height-classify-mean-rounding","id":"FA-86711","implementations":{"attempt":{"sha256":"61cdb5545c54040c3c8b2ac4814a21bbf6d67fe948474a32a1cd196170b26ded","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(heights, sea, mountain):\n    h = len(heights)\n    w = len(heights[0])\n    out = []\n    for r in range(h):\n        row = []\n        for c in range(w):\n            total = 0\n            cnt = 0\n            for rr in range(max(0, r - 1), min(h, r + 2)):\n                for cc in range(max(0, c - 1), min(w, c + 2)):\n                    total += heights[rr][cc]\n                    cnt += 1\n            v = -(-total // cnt)\n            if v < sea:\n                row.append('~')\n            elif v < sea + 2:\n                row.append('s')\n            elif v < mountain:\n                row.append('g')\n            else:\n                row.append('^')\n        out.append(''.join(row))\n    return out\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\ncases = [[('regression mean rounding #1', [[[3], [4], [0]], 4, 10], ['~', '~', '~']),\n  ('regression mean rounding #2', [[[10, 11, 6, 11, 0], [9, 0, 9, 4, 4]], 5, 7], ['^^ss~', '^^ss~']),\n  ('regression mean rounding #3',\n   [[[5, 4, 2, 6, 4], [12, 10, 8, 2, 4], [4, 10, 11, 2, 6]], 2, 8],\n   ['ggggg', 'ggggg', '^^ggs']),\n  ('regression mean rounding #4', [[[6], [4], [8], [4], [8]], 5, 9], ['s', 's', 's', 's', 's']),\n  ('corner cell average #1', [[[9, 9], [9, 0]], 3, 8], ['gg', 'gg']),\n  ('beach band edge #1', [[[5]], 3, 9], ['g']),\n  ('single row #1', [[[0, 12, 0]], 3, 6], ['^s^']),\n  ('control #1', [[[0, 9], [7, 2]], 2, 11], ['gg', 'gg'])],\n [('regression mean rounding #1',\n   [[[5, 4, 2, 6, 4], [12, 10, 8, 2, 4], [4, 10, 11, 2, 6]], 2, 8],\n   ['ggggg', 'ggggg', '^^ggs']),\n  ('regression mean rounding #2', [[[6], [4], [8], [4], [8]], 5, 9], ['s', 's', 's', 's', 's']),\n  ('regression mean rounding #3', [[[9, 5, 6], [9, 0, 4]], 6, 10], ['~~~', '~~~']),\n  ('regression mean rounding #4',\n   [[[8, 6, 12, 10, 8], [6, 1, 1, 7, 5], [1, 6, 12, 6, 0], [3, 8, 3, 6, 0], [1, 7, 3, 2, 0]], 6, 9],\n   ['~~sss', '~~sss', '~~~~~', '~~~~~', '~~~~~']),\n  ('single row #1', [[[0, 12, 0]], 3, 6], ['^s^']),\n  ('corner cell average #1', [[[9, 9], [9, 0]], 3, 8], ['gg', 'gg']),\n  ('control #1', [[[0, 9], [7, 2]], 2, 11], ['gg', 'gg']),\n  ('control #2', [[[9], [8]], 6, 6], ['^', '^'])],\n [('regression mean rounding #1', [[[9, 5, 6], [9, 0, 4]], 6, 10], ['~~~', '~~~']),\n  ('regression mean rounding #2',\n   [[[8, 6, 12, 10, 8], [6, 1, 1, 7, 5], [1, 6, 12, 6, 0], [3, 8, 3, 6, 0], [1, 7, 3, 2, 0]], 6, 9],\n   ['~~sss', '~~sss', '~~~~~', '~~~~~', '~~~~~']),\n  ('regression mean rounding #3',\n   [[[2, 9, 4, 10, 11], [7, 7, 11, 1, 10], [11, 5, 12, 1, 12], [9, 4, 1, 0, 2]], 6, 8],\n   ['ssss^', 'sss^s', 'ss~~~', 'ss~~~']),\n  ('regression mean rounding #4', [[[0, 1], [3, 5], [10, 1]], 3, 10], ['~~', 'ss', 'ss']),\n  ('beach band edge #1', [[[5]], 3, 9], ['g']),\n  ('single row #1', [[[0, 12, 0]], 3, 6], ['^s^']),\n  ('control #1', [[[9], [8]], 6, 6], ['^', '^']),\n  ('control #2', [[[5, 5], [10, 3], [7, 0]], 2, 10], ['gg', 'gg', 'gg'])],\n [('regression mean rounding #1',\n   [[[2, 9, 4, 10, 11], [7, 7, 11, 1, 10], [11, 5, 12, 1, 12], [9, 4, 1, 0, 2]], 6, 8],\n   ['ssss^', 'sss^s', 'ss~~~', 'ss~~~']),\n  ('regression mean rounding #2', [[[0, 1], [3, 5], [10, 1]], 3, 10], ['~~', 'ss', 'ss']),\n  ('regression mean rounding #3',\n   [[[1, 2, 0, 4], [12, 1, 9, 7], [9, 3, 6, 5]], 2, 11],\n   ['ggsg', 'gggg', 'gggg']),\n  ('partial repair boundary #1',\n   [[[0, 3], [6, 9], [0, 3], [3, 12], [7, 10]], 5, 6],\n   ['~~', '~~', 'ss', 'ss', '^^']),\n  ('corner cell average #1', [[[9, 9], [9, 0]], 3, 8], ['gg', 'gg']),\n  ('beach band edge #1', [[[5]], 3, 9], ['g']),\n  ('control #1', [[[10, 11], [1, 0]], 3, 9], ['gg', 'gg']),\n  ('control #2', [[[9, 7]], 2, 6], ['^^'])],\n [('regression mean rounding #1',\n   [[[1, 2, 0, 4], [12, 1, 9, 7], [9, 3, 6, 5]], 2, 11],\n   ['ggsg', 'gggg', 'gggg']),\n  ('regression mean rounding #2',\n   [[[4, 3, 3, 1], [4, 1, 10, 9], [2, 2, 10, 5], [0, 0, 7, 2]], 6, 8],\n   ['~~~~', '~~~s', '~~~s', '~~~s']),\n  ('partial repair boundary #1',\n   [[[0, 3], [6, 9], [0, 3], [3, 12], [7, 10]], 5, 6],\n   ['~~', '~~', 'ss', 'ss', '^^']),\n  ('regression mean rounding #3',\n   [[[10, 1, 2, 12, 9], [8, 10, 5, 4, 8], [4, 3, 4, 4, 8], [2, 5, 12, 8, 7]], 5, 7],\n   ['^sss^', 'ssss^', 'sssss', '~ss^s']),\n  ('single row #1', [[[0, 12, 0]], 3, 6], ['^s^']),\n  ('corner cell average #1', [[[9, 9], [9, 0]], 3, 8], ['gg', 'gg']),\n  ('control #1', [[[1, 2, 10]], 6, 9], ['~~s']),\n  ('control #2', [[[11, 0, 4, 12]], 2, 7], ['ggg^'])]]\nfor label, args, expected in cases[N-1]:\n    check(label, solve(*args), expected)\nprint(json.dumps({\"observations\": observations, \"passed\": all(x[\"passed\"] for x in observations)}, ensure_ascii=False))\nraise SystemExit(0 if all(x[\"passed\"] for x in observations) else 1)\n"},"broken":{"sha256":"897537813f895e1970ecdf4517178996197dcfbd6c597025d04134f3de824731","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(heights, sea, mountain):\n    h = len(heights)\n    w = len(heights[0])\n    out = []\n    for r in range(h):\n        row = []\n        for c in range(w):\n            total = 0\n            cnt = 0\n            for rr in range(max(0, r - 1), min(h, r + 2)):\n                for cc in range(max(0, c - 1), min(w, c + 2)):\n                    total += heights[rr][cc]\n                    cnt += 1\n            v = round(total / cnt)\n            if v < sea:\n                row.append('~')\n            elif v < sea + 2:\n                row.append('s')\n            elif v < mountain:\n                row.append('g')\n            else:\n                row.append('^')\n        out.append(''.join(row))\n    return out\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\ncases = [[('regression mean rounding #1', [[[3], [4], [0]], 4, 10], ['~', '~', '~']),\n  ('regression mean rounding #2', [[[10, 11, 6, 11, 0], [9, 0, 9, 4, 4]], 5, 7], ['^^ss~', '^^ss~']),\n  ('regression mean rounding #3',\n   [[[5, 4, 2, 6, 4], [12, 10, 8, 2, 4], [4, 10, 11, 2, 6]], 2, 8],\n   ['ggggg', 'ggggg', '^^ggs']),\n  ('regression mean rounding #4', [[[6], [4], [8], [4], [8]], 5, 9], ['s', 's', 's', 's', 's']),\n  ('corner cell average #1', [[[9, 9], [9, 0]], 3, 8], ['gg', 'gg']),\n  ('beach band edge #1', [[[5]], 3, 9], ['g']),\n  ('single row #1', [[[0, 12, 0]], 3, 6], ['^s^']),\n  ('control #1', [[[0, 9], [7, 2]], 2, 11], ['gg', 'gg'])],\n [('regression mean rounding #1',\n   [[[5, 4, 2, 6, 4], [12, 10, 8, 2, 4], [4, 10, 11, 2, 6]], 2, 8],\n   ['ggggg', 'ggggg', '^^ggs']),\n  ('regression mean rounding #2', [[[6], [4], [8], [4], [8]], 5, 9], ['s', 's', 's', 's', 's']),\n  ('regression mean rounding #3', [[[9, 5, 6], [9, 0, 4]], 6, 10], ['~~~', '~~~']),\n  ('regression mean rounding #4',\n   [[[8, 6, 12, 10, 8], [6, 1, 1, 7, 5], [1, 6, 12, 6, 0], [3, 8, 3, 6, 0], [1, 7, 3, 2, 0]], 6, 9],\n   ['~~sss', '~~sss', '~~~~~', '~~~~~', '~~~~~']),\n  ('single row #1', [[[0, 12, 0]], 3, 6], ['^s^']),\n  ('corner cell average #1', [[[9, 9], [9, 0]], 3, 8], ['gg', 'gg']),\n  ('control #1', [[[0, 9], [7, 2]], 2, 11], ['gg', 'gg']),\n  ('control #2', [[[9], [8]], 6, 6], ['^', '^'])],\n [('regression mean rounding #1', [[[9, 5, 6], [9, 0, 4]], 6, 10], ['~~~', '~~~']),\n  ('regression mean rounding #2',\n   [[[8, 6, 12, 10, 8], [6, 1, 1, 7, 5], [1, 6, 12, 6, 0], [3, 8, 3, 6, 0], [1, 7, 3, 2, 0]], 6, 9],\n   ['~~sss', '~~sss', '~~~~~', '~~~~~', '~~~~~']),\n  ('regression mean rounding #3',\n   [[[2, 9, 4, 10, 11], [7, 7, 11, 1, 10], [11, 5, 12, 1, 12], [9, 4, 1, 0, 2]], 6, 8],\n   ['ssss^', 'sss^s', 'ss~~~', 'ss~~~']),\n  ('regression mean rounding #4', [[[0, 1], [3, 5], [10, 1]], 3, 10], ['~~', 'ss', 'ss']),\n  ('beach band edge #1', [[[5]], 3, 9], ['g']),\n  ('single row #1', [[[0, 12, 0]], 3, 6], ['^s^']),\n  ('control #1', [[[9], [8]], 6, 6], ['^', '^']),\n  ('control #2', [[[5, 5], [10, 3], [7, 0]], 2, 10], ['gg', 'gg', 'gg'])],\n [('regression mean rounding #1',\n   [[[2, 9, 4, 10, 11], [7, 7, 11, 1, 10], [11, 5, 12, 1, 12], [9, 4, 1, 0, 2]], 6, 8],\n   ['ssss^', 'sss^s', 'ss~~~', 'ss~~~']),\n  ('regression mean rounding #2', [[[0, 1], [3, 5], [10, 1]], 3, 10], ['~~', 'ss', 'ss']),\n  ('regression mean rounding #3',\n   [[[1, 2, 0, 4], [12, 1, 9, 7], [9, 3, 6, 5]], 2, 11],\n   ['ggsg', 'gggg', 'gggg']),\n  ('partial repair boundary #1',\n   [[[0, 3], [6, 9], [0, 3], [3, 12], [7, 10]], 5, 6],\n   ['~~', '~~', 'ss', 'ss', '^^']),\n  ('corner cell average #1', [[[9, 9], [9, 0]], 3, 8], ['gg', 'gg']),\n  ('beach band edge #1', [[[5]], 3, 9], ['g']),\n  ('control #1', [[[10, 11], [1, 0]], 3, 9], ['gg', 'gg']),\n  ('control #2', [[[9, 7]], 2, 6], ['^^'])],\n [('regression mean rounding #1',\n   [[[1, 2, 0, 4], [12, 1, 9, 7], [9, 3, 6, 5]], 2, 11],\n   ['ggsg', 'gggg', 'gggg']),\n  ('regression mean rounding #2',\n   [[[4, 3, 3, 1], [4, 1, 10, 9], [2, 2, 10, 5], [0, 0, 7, 2]], 6, 8],\n   ['~~~~', '~~~s', '~~~s', '~~~s']),\n  ('partial repair boundary #1',\n   [[[0, 3], [6, 9], [0, 3], [3, 12], [7, 10]], 5, 6],\n   ['~~', '~~', 'ss', 'ss', '^^']),\n  ('regression mean rounding #3',\n   [[[10, 1, 2, 12, 9], [8, 10, 5, 4, 8], [4, 3, 4, 4, 8], [2, 5, 12, 8, 7]], 5, 7],\n   ['^sss^', 'ssss^', 'sssss', '~ss^s']),\n  ('single row #1', [[[0, 12, 0]], 3, 6], ['^s^']),\n  ('corner cell average #1', [[[9, 9], [9, 0]], 3, 8], ['gg', 'gg']),\n  ('control #1', [[[1, 2, 10]], 6, 9], ['~~s']),\n  ('control #2', [[[11, 0, 4, 12]], 2, 7], ['ggg^'])]]\nfor label, args, expected in cases[N-1]:\n    check(label, solve(*args), expected)\nprint(json.dumps({\"observations\": observations, \"passed\": all(x[\"passed\"] for x in observations)}, ensure_ascii=False))\nraise SystemExit(0 if all(x[\"passed\"] for x in observations) else 1)\n"},"fixed":{"sha256":"6cfa0fa452018eabb0aa5a9bcfe1cadb8294fd9ddb6bccaeee9b1fb0504f99f6","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\n\nN = 1\nobservations = []\ndef solve(heights, sea, mountain):\n    h = len(heights)\n    w = len(heights[0])\n    out = []\n    for r in range(h):\n        row = []\n        for c in range(w):\n            total = 0\n            cnt = 0\n            for rr in range(max(0, r - 1), min(h, r + 2)):\n                for cc in range(max(0, c - 1), min(w, c + 2)):\n                    total += heights[rr][cc]\n                    cnt += 1\n            v = total // cnt\n            if v < sea:\n                row.append('~')\n            elif v < sea + 2:\n                row.append('s')\n            elif v < mountain:\n                row.append('g')\n            else:\n                row.append('^')\n        out.append(''.join(row))\n    return out\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\ncases = [[('regression mean rounding #1', [[[3], [4], [0]], 4, 10], ['~', '~', '~']),\n  ('regression mean rounding #2', [[[10, 11, 6, 11, 0], [9, 0, 9, 4, 4]], 5, 7], ['^^ss~', '^^ss~']),\n  ('regression mean rounding #3',\n   [[[5, 4, 2, 6, 4], [12, 10, 8, 2, 4], [4, 10, 11, 2, 6]], 2, 8],\n   ['ggggg', 'ggggg', '^^ggs']),\n  ('regression mean rounding #4', [[[6], [4], [8], [4], [8]], 5, 9], ['s', 's', 's', 's', 's']),\n  ('corner cell average #1', [[[9, 9], [9, 0]], 3, 8], ['gg', 'gg']),\n  ('beach band edge #1', [[[5]], 3, 9], ['g']),\n  ('single row #1', [[[0, 12, 0]], 3, 6], ['^s^']),\n  ('control #1', [[[0, 9], [7, 2]], 2, 11], ['gg', 'gg'])],\n [('regression mean rounding #1',\n   [[[5, 4, 2, 6, 4], [12, 10, 8, 2, 4], [4, 10, 11, 2, 6]], 2, 8],\n   ['ggggg', 'ggggg', '^^ggs']),\n  ('regression mean rounding #2', [[[6], [4], [8], [4], [8]], 5, 9], ['s', 's', 's', 's', 's']),\n  ('regression mean rounding #3', [[[9, 5, 6], [9, 0, 4]], 6, 10], ['~~~', '~~~']),\n  ('regression mean rounding #4',\n   [[[8, 6, 12, 10, 8], [6, 1, 1, 7, 5], [1, 6, 12, 6, 0], [3, 8, 3, 6, 0], [1, 7, 3, 2, 0]], 6, 9],\n   ['~~sss', '~~sss', '~~~~~', '~~~~~', '~~~~~']),\n  ('single row #1', [[[0, 12, 0]], 3, 6], ['^s^']),\n  ('corner cell average #1', [[[9, 9], [9, 0]], 3, 8], ['gg', 'gg']),\n  ('control #1', [[[0, 9], [7, 2]], 2, 11], ['gg', 'gg']),\n  ('control #2', [[[9], [8]], 6, 6], ['^', '^'])],\n [('regression mean rounding #1', [[[9, 5, 6], [9, 0, 4]], 6, 10], ['~~~', '~~~']),\n  ('regression mean rounding #2',\n   [[[8, 6, 12, 10, 8], [6, 1, 1, 7, 5], [1, 6, 12, 6, 0], [3, 8, 3, 6, 0], [1, 7, 3, 2, 0]], 6, 9],\n   ['~~sss', '~~sss', '~~~~~', '~~~~~', '~~~~~']),\n  ('regression mean rounding #3',\n   [[[2, 9, 4, 10, 11], [7, 7, 11, 1, 10], [11, 5, 12, 1, 12], [9, 4, 1, 0, 2]], 6, 8],\n   ['ssss^', 'sss^s', 'ss~~~', 'ss~~~']),\n  ('regression mean rounding #4', [[[0, 1], [3, 5], [10, 1]], 3, 10], ['~~', 'ss', 'ss']),\n  ('beach band edge #1', [[[5]], 3, 9], ['g']),\n  ('single row #1', [[[0, 12, 0]], 3, 6], ['^s^']),\n  ('control #1', [[[9], [8]], 6, 6], ['^', '^']),\n  ('control #2', [[[5, 5], [10, 3], [7, 0]], 2, 10], ['gg', 'gg', 'gg'])],\n [('regression mean rounding #1',\n   [[[2, 9, 4, 10, 11], [7, 7, 11, 1, 10], [11, 5, 12, 1, 12], [9, 4, 1, 0, 2]], 6, 8],\n   ['ssss^', 'sss^s', 'ss~~~', 'ss~~~']),\n  ('regression mean rounding #2', [[[0, 1], [3, 5], [10, 1]], 3, 10], ['~~', 'ss', 'ss']),\n  ('regression mean rounding #3',\n   [[[1, 2, 0, 4], [12, 1, 9, 7], [9, 3, 6, 5]], 2, 11],\n   ['ggsg', 'gggg', 'gggg']),\n  ('partial repair boundary #1',\n   [[[0, 3], [6, 9], [0, 3], [3, 12], [7, 10]], 5, 6],\n   ['~~', '~~', 'ss', 'ss', '^^']),\n  ('corner cell average #1', [[[9, 9], [9, 0]], 3, 8], ['gg', 'gg']),\n  ('beach band edge #1', [[[5]], 3, 9], ['g']),\n  ('control #1', [[[10, 11], [1, 0]], 3, 9], ['gg', 'gg']),\n  ('control #2', [[[9, 7]], 2, 6], ['^^'])],\n [('regression mean rounding #1',\n   [[[1, 2, 0, 4], [12, 1, 9, 7], [9, 3, 6, 5]], 2, 11],\n   ['ggsg', 'gggg', 'gggg']),\n  ('regression mean rounding #2',\n   [[[4, 3, 3, 1], [4, 1, 10, 9], [2, 2, 10, 5], [0, 0, 7, 2]], 6, 8],\n   ['~~~~', '~~~s', '~~~s', '~~~s']),\n  ('partial repair boundary #1',\n   [[[0, 3], [6, 9], [0, 3], [3, 12], [7, 10]], 5, 6],\n   ['~~', '~~', 'ss', 'ss', '^^']),\n  ('regression mean rounding #3',\n   [[[10, 1, 2, 12, 9], [8, 10, 5, 4, 8], [4, 3, 4, 4, 8], [2, 5, 12, 8, 7]], 5, 7],\n   ['^sss^', 'ssss^', 'sssss', '~ss^s']),\n  ('single row #1', [[[0, 12, 0]], 3, 6], ['^s^']),\n  ('corner cell average #1', [[[9, 9], [9, 0]], 3, 8], ['gg', 'gg']),\n  ('control #1', [[[1, 2, 10]], 6, 9], ['~~s']),\n  ('control #2', [[[11, 0, 4, 12]], 2, 7], ['ggg^'])]]\nfor label, args, expected in cases[N-1]:\n    check(label, solve(*args), expected)\nprint(json.dumps({\"observations\": observations, \"passed\": all(x[\"passed\"] for x in observations)}, ensure_ascii=False))\nraise SystemExit(0 if all(x[\"passed\"] for x in observations) else 1)\n"}},"limitations":"Deterministic toy contract stipulated for this model; integer or exact arithmetic only, not a reproduction of any specific game engine. 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.","method":"Deterministic executable model with adversarial boundary fixtures.","provenance":{"created_by":"Failure Map","dependencies":"Python standard library","family":"w2-procedural-level-generation-constraints-height-classify-mean-rounding","generated_at":"2026-09-29T14:50:52.084163+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"Procedural generators silently emit unplayable or unfair levels when a single constraint check uses the wrong boundary, axis, neighborhood or update order; the defect is visible in exact generated geometry.","repair":"Restore `v = total // cnt` at the mean rounding step.","root_cause":"The window mean is rounded instead of floored.","sha256":"afd6767e267c4d90651ed700a5dd2673a5ec20c2e65388606494d09eb1eea039","title":"Heightmap smoothing and biome classes: Smoothed heights round to nearest · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verification":{"attempt":{"elapsed_ms":42.507,"exit_code":1,"observations":[{"actual":["s","~","~"],"check":"regression mean rounding #1","expected":["~","~","~"],"passed":false},{"actual":["^^^ss","^^^ss"],"check":"regression mean rounding #2","expected":["^^ss~","^^ss~"],"passed":false},{"actual":["^gggg","^^ggg","^^^gg"],"check":"regression mean rounding #3","expected":["ggggg","ggggg","^^ggs"],"passed":false},{"actual":["s","s","s","g","s"],"check":"regression mean rounding #4","expected":["s","s","s","s","s"],"passed":false},{"actual":["gg","gg"],"check":"corner cell average #1","expected":["gg","gg"],"passed":true},{"actual":["g"],"check":"beach band edge #1","expected":["g"],"passed":true},{"actual":["^s^"],"check":"single row #1","expected":["^s^"],"passed":true},{"actual":["gg","gg"],"check":"control #1","expected":["gg","gg"],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression mean rounding #1\", \"actual\": [\"s\", \"~\", \"~\"], \"expected\": [\"~\", \"~\", \"~\"], \"passed\": false}, {\"check\": \"regression mean rounding #2\", \"actual\": [\"^^^ss\", \"^^^ss\"], \"expected\": [\"^^ss~\", \"^^ss~\"], \"passed\": false}, {\"check\": \"regression mean rounding #3\", \"actual\": [\"^gggg\", \"^^ggg\", \"^^^gg\"], \"expected\": [\"ggggg\", \"ggggg\", \"^^ggs\"], \"passed\": false}, {\"check\": \"regression mean rounding #4\", \"actual\": [\"s\", \"s\", \"s\", \"g\", \"s\"], \"expected\": [\"s\", \"s\", \"s\", \"s\", \"s\"], \"passed\": false}, {\"check\": \"corner cell average #1\", \"actual\": [\"gg\", \"gg\"], \"expected\": [\"gg\", \"gg\"], \"passed\": true}, {\"check\": \"beach band edge #1\", \"actual\": [\"g\"], \"expected\": [\"g\"], \"passed\": true}, {\"check\": \"single row #1\", \"actual\": [\"^s^\"], \"expected\": [\"^s^\"], \"passed\": true}, {\"check\": \"control #1\", \"actual\": [\"gg\", \"gg\"], \"expected\": [\"gg\", \"gg\"], \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":44.748,"exit_code":1,"observations":[{"actual":["s","~","~"],"check":"regression mean rounding #1","expected":["~","~","~"],"passed":false},{"actual":["^^^ss","^^^ss"],"check":"regression mean rounding #2","expected":["^^ss~","^^ss~"],"passed":false},{"actual":["^gggg","^gggg","^^ggg"],"check":"regression mean rounding #3","expected":["ggggg","ggggg","^^ggs"],"passed":false},{"actual":["s","s","s","g","s"],"check":"regression mean rounding #4","expected":["s","s","s","s","s"],"passed":false},{"actual":["gg","gg"],"check":"corner cell average #1","expected":["gg","gg"],"passed":true},{"actual":["g"],"check":"beach band edge #1","expected":["g"],"passed":true},{"actual":["^s^"],"check":"single row #1","expected":["^s^"],"passed":true},{"actual":["gg","gg"],"check":"control 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