{"abstract":"Base-currency equivalents of pip premiums are spot-squared off.","category":"Options payoff and settlement","checks":8,"contract":"Inputs quote, quote type, base notional, spot and pip size. pips: term premium = quote*pip*notional, base = term/spot. pct_base: base = quote/100*notional, term = base*spot. pct_term: term = quote/100*notional*spot, base = term/spot. Exact fractions; return [term, base] rounded to 2 as floats.","evaluation_group":"w2-options_payoff_and_settlement-fx-premium-conversion","failed_approach":"Guessing the direction from the spot magnitude breaks for pairs quoted above one.","family":"w2-options_payoff_and_settlement-fx-premium-conversion-pip-base-conversion","id":"FA-61726","implementations":{"attempt":{"sha256":"2e22d2edb98aef36df03ddcdfdd5b2bef4d147fc340ef4eb605322b663915e0b","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nfrom fractions import Fraction\nN = 1\nobservations = []\ndef solve(quote, quote_type, notional, spot, pip):\n    q = Fraction(str(quote))\n    s = Fraction(str(spot))\n    N = Fraction(notional)\n    pp = Fraction(str(pip))\n    if quote_type == 'pips':\n        term = q * pp * N\n        base = term / s if s < 1 else term * s\n    elif quote_type == 'pct_base':\n        base = q / 100 * N\n        term = base * s\n    else:\n        term = q / 100 * N * s\n        base = term / s\n    return [float(round(term, 2)), float(round(base, 2))]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[['regression pip base conversion 1', [45.0, 'pips', 1000000, 149.35, 0.01], [450000.0, 3013.06]], ['regression pip base conversion 2', [110.0, 'pips', 5000000, 1.0845, 0.0001], [55000.0, 50714.62]], ['partial repair probe 1', [1.25, 'pips', 1000000, 1.2712, 0.0001], [125.0, 98.33]], ['partial repair probe 2', [12.5, 'pips', 5000000, 1.2712, 0.0001], [6250.0, 4916.61]], ['normal control 1', [1.25, 'pct_base', 5000000, 1.0845, 0.0001], [67781.25, 62500.0]], ['normal control 2', [1.25, 'pct_term', 1000000, 1.2712, 0.0001], [15890.0, 12500.0]], ['normal control 3', [0.85, 'pct_term', 1000000, 1.0845, 0.0001], [9218.25, 8500.0]], ['normal control 4', [12.5, 'pct_base', 5000000, 1.2712, 0.0001], [794500.0, 625000.0]]], [['regression pip base conversion 1', [12.5, 'pips', 250000, 1.2712, 0.0001], [312.5, 245.83]], ['regression pip base conversion 2', [0.85, 'pips', 1000000, 149.35, 0.01], [8500.0, 56.91]], ['partial repair probe 1', [1.25, 'pips', 250000, 149.35, 0.01], [3125.0, 20.92]], ['partial repair probe 2', [45.0, 'pips', 1000000, 1.2712, 0.0001], [4500.0, 3539.96]], ['normal control 1', [45.0, 'pct_term', 5000000, 1.2712, 0.0001], [2860200.0, 2250000.0]], ['normal control 2', [0.85, 'pct_base', 1000000, 1.0845, 0.0001], [9218.25, 8500.0]], ['normal control 3', [0.85, 'pct_base', 5000000, 1.0845, 0.0001], [46091.25, 42500.0]], ['normal control 4', [0.85, 'pct_term', 250000, 1.2712, 0.0001], [2701.3, 2125.0]]], [['regression pip base conversion 1', [12.5, 'pips', 1000000, 1.2712, 0.0001], [1250.0, 983.32]], ['regression pip base conversion 2', [12.5, 'pips', 5000000, 149.35, 0.01], [625000.0, 4184.8]], ['partial repair probe 1', [45.0, 'pips', 5000000, 149.35, 0.01], [2250000.0, 15065.28]], ['partial repair probe 2', [1.25, 'pips', 250000, 1.2712, 0.0001], [31.25, 24.58]], ['normal control 1', [12.5, 'pct_term', 5000000, 1.2712, 0.0001], [794500.0, 625000.0]], ['normal control 2', [45.0, 'pct_term', 5000000, 1.2712, 0.0001], [2860200.0, 2250000.0]], ['normal control 3', [12.5, 'pct_base', 5000000, 1.0845, 0.0001], [677812.5, 625000.0]], ['normal control 4', [1.25, 'pct_term', 250000, 1.0845, 0.0001], [3389.06, 3125.0]]], [['regression pip base conversion 1', [45.0, 'pips', 250000, 1.0845, 0.0001], [1125.0, 1037.34]], ['regression pip base conversion 2', [12.5, 'pips', 1000000, 149.35, 0.01], [125000.0, 836.96]], ['partial repair probe 1', [110.0, 'pips', 1000000, 149.35, 0.01], [1100000.0, 7365.25]], ['partial repair probe 2', [12.5, 'pips', 250000, 1.0845, 0.0001], [312.5, 288.15]], ['normal control 1', [0.85, 'pct_base', 250000, 149.35, 0.01], [317368.75, 2125.0]], ['normal control 2', [45.0, 'pct_base', 1000000, 149.35, 0.01], [67207500.0, 450000.0]], ['normal control 3', [110.0, 'pct_base', 1000000, 149.35, 0.01], [164285000.0, 1100000.0]], ['normal control 4', [45.0, 'pct_base', 5000000, 149.35, 0.01], [336037500.0, 2250000.0]]], [['regression pip base conversion 1', [1.25, 'pips', 5000000, 149.35, 0.01], [62500.0, 418.48]], ['regression pip base conversion 2', [12.5, 'pips', 250000, 1.0845, 0.0001], [312.5, 288.15]], ['partial repair probe 1', [45.0, 'pips', 5000000, 1.2712, 0.0001], [22500.0, 17699.81]], ['partial repair probe 2', [0.85, 'pips', 1000000, 1.2712, 0.0001], [85.0, 66.87]], ['normal control 1', [12.5, 'pct_base', 5000000, 1.0845, 0.0001], [677812.5, 625000.0]], ['normal control 2', [1.25, 'pct_base', 250000, 149.35, 0.01], [466718.75, 3125.0]], ['normal control 3', [12.5, 'pct_term', 1000000, 149.35, 0.01], [18668750.0, 125000.0]], ['normal control 4', [1.25, 'pct_base', 1000000, 1.2712, 0.0001], [15890.0, 12500.0]]]]\nfor label, args, expected in fixtures[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":"13ed7948cecfade43ac054b0d3d1fdfefcbe066cb9ec2af92f88513e631471fa","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nfrom fractions import Fraction\nN = 1\nobservations = []\ndef solve(quote, quote_type, notional, spot, pip):\n    q = Fraction(str(quote))\n    s = Fraction(str(spot))\n    N = Fraction(notional)\n    pp = Fraction(str(pip))\n    if quote_type == 'pips':\n        term = q * pp * N\n        base = term * s\n    elif quote_type == 'pct_base':\n        base = q / 100 * N\n        term = base * s\n    else:\n        term = q / 100 * N * s\n        base = term / s\n    return [float(round(term, 2)), float(round(base, 2))]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[['regression pip base conversion 1', [45.0, 'pips', 1000000, 149.35, 0.01], [450000.0, 3013.06]], ['regression pip base conversion 2', [110.0, 'pips', 5000000, 1.0845, 0.0001], [55000.0, 50714.62]], ['partial repair probe 1', [1.25, 'pips', 1000000, 1.2712, 0.0001], [125.0, 98.33]], ['partial repair probe 2', [12.5, 'pips', 5000000, 1.2712, 0.0001], [6250.0, 4916.61]], ['normal control 1', [1.25, 'pct_base', 5000000, 1.0845, 0.0001], [67781.25, 62500.0]], ['normal control 2', [1.25, 'pct_term', 1000000, 1.2712, 0.0001], [15890.0, 12500.0]], ['normal control 3', [0.85, 'pct_term', 1000000, 1.0845, 0.0001], [9218.25, 8500.0]], ['normal control 4', [12.5, 'pct_base', 5000000, 1.2712, 0.0001], [794500.0, 625000.0]]], [['regression pip base conversion 1', [12.5, 'pips', 250000, 1.2712, 0.0001], [312.5, 245.83]], ['regression pip base conversion 2', [0.85, 'pips', 1000000, 149.35, 0.01], [8500.0, 56.91]], ['partial repair probe 1', [1.25, 'pips', 250000, 149.35, 0.01], [3125.0, 20.92]], ['partial repair probe 2', [45.0, 'pips', 1000000, 1.2712, 0.0001], [4500.0, 3539.96]], ['normal control 1', [45.0, 'pct_term', 5000000, 1.2712, 0.0001], [2860200.0, 2250000.0]], ['normal control 2', [0.85, 'pct_base', 1000000, 1.0845, 0.0001], [9218.25, 8500.0]], ['normal control 3', [0.85, 'pct_base', 5000000, 1.0845, 0.0001], [46091.25, 42500.0]], ['normal control 4', [0.85, 'pct_term', 250000, 1.2712, 0.0001], [2701.3, 2125.0]]], [['regression pip base conversion 1', [12.5, 'pips', 1000000, 1.2712, 0.0001], [1250.0, 983.32]], ['regression pip base conversion 2', [12.5, 'pips', 5000000, 149.35, 0.01], [625000.0, 4184.8]], ['partial repair probe 1', [45.0, 'pips', 5000000, 149.35, 0.01], [2250000.0, 15065.28]], ['partial repair probe 2', [1.25, 'pips', 250000, 1.2712, 0.0001], [31.25, 24.58]], ['normal control 1', [12.5, 'pct_term', 5000000, 1.2712, 0.0001], [794500.0, 625000.0]], ['normal control 2', [45.0, 'pct_term', 5000000, 1.2712, 0.0001], [2860200.0, 2250000.0]], ['normal control 3', [12.5, 'pct_base', 5000000, 1.0845, 0.0001], [677812.5, 625000.0]], ['normal control 4', [1.25, 'pct_term', 250000, 1.0845, 0.0001], [3389.06, 3125.0]]], [['regression pip base conversion 1', [45.0, 'pips', 250000, 1.0845, 0.0001], [1125.0, 1037.34]], ['regression pip base conversion 2', [12.5, 'pips', 1000000, 149.35, 0.01], [125000.0, 836.96]], ['partial repair probe 1', [110.0, 'pips', 1000000, 149.35, 0.01], [1100000.0, 7365.25]], ['partial repair probe 2', [12.5, 'pips', 250000, 1.0845, 0.0001], [312.5, 288.15]], ['normal control 1', [0.85, 'pct_base', 250000, 149.35, 0.01], [317368.75, 2125.0]], ['normal control 2', [45.0, 'pct_base', 1000000, 149.35, 0.01], [67207500.0, 450000.0]], ['normal control 3', [110.0, 'pct_base', 1000000, 149.35, 0.01], [164285000.0, 1100000.0]], ['normal control 4', [45.0, 'pct_base', 5000000, 149.35, 0.01], [336037500.0, 2250000.0]]], [['regression pip base conversion 1', [1.25, 'pips', 5000000, 149.35, 0.01], [62500.0, 418.48]], ['regression pip base conversion 2', [12.5, 'pips', 250000, 1.0845, 0.0001], [312.5, 288.15]], ['partial repair probe 1', [45.0, 'pips', 5000000, 1.2712, 0.0001], [22500.0, 17699.81]], ['partial repair probe 2', [0.85, 'pips', 1000000, 1.2712, 0.0001], [85.0, 66.87]], ['normal control 1', [12.5, 'pct_base', 5000000, 1.0845, 0.0001], [677812.5, 625000.0]], ['normal control 2', [1.25, 'pct_base', 250000, 149.35, 0.01], [466718.75, 3125.0]], ['normal control 3', [12.5, 'pct_term', 1000000, 149.35, 0.01], [18668750.0, 125000.0]], ['normal control 4', [1.25, 'pct_base', 1000000, 1.2712, 0.0001], [15890.0, 12500.0]]]]\nfor label, args, expected in fixtures[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":"64b36b5da6173e76fc88cc3ef3dbee9641f8e44fedc97f13730cc6338d809b49","source":"\"\"\"Failure Map reference implementation. Python standard library only.\"\"\"\nimport json\nfrom fractions import Fraction\nN = 1\nobservations = []\ndef solve(quote, quote_type, notional, spot, pip):\n    q = Fraction(str(quote))\n    s = Fraction(str(spot))\n    N = Fraction(notional)\n    pp = Fraction(str(pip))\n    if quote_type == 'pips':\n        term = q * pp * N\n        base = term / s\n    elif quote_type == 'pct_base':\n        base = q / 100 * N\n        term = base * s\n    else:\n        term = q / 100 * N * s\n        base = term / s\n    return [float(round(term, 2)), float(round(base, 2))]\ndef check(label, actual, expected):\n    observations.append({\"check\": label, \"actual\": actual, \"expected\": expected, \"passed\": actual == expected})\nfixtures = [[['regression pip base conversion 1', [45.0, 'pips', 1000000, 149.35, 0.01], [450000.0, 3013.06]], ['regression pip base conversion 2', [110.0, 'pips', 5000000, 1.0845, 0.0001], [55000.0, 50714.62]], ['partial repair probe 1', [1.25, 'pips', 1000000, 1.2712, 0.0001], [125.0, 98.33]], ['partial repair probe 2', [12.5, 'pips', 5000000, 1.2712, 0.0001], [6250.0, 4916.61]], ['normal control 1', [1.25, 'pct_base', 5000000, 1.0845, 0.0001], [67781.25, 62500.0]], ['normal control 2', [1.25, 'pct_term', 1000000, 1.2712, 0.0001], [15890.0, 12500.0]], ['normal control 3', [0.85, 'pct_term', 1000000, 1.0845, 0.0001], [9218.25, 8500.0]], ['normal control 4', [12.5, 'pct_base', 5000000, 1.2712, 0.0001], [794500.0, 625000.0]]], [['regression pip base conversion 1', [12.5, 'pips', 250000, 1.2712, 0.0001], [312.5, 245.83]], ['regression pip base conversion 2', [0.85, 'pips', 1000000, 149.35, 0.01], [8500.0, 56.91]], ['partial repair probe 1', [1.25, 'pips', 250000, 149.35, 0.01], [3125.0, 20.92]], ['partial repair probe 2', [45.0, 'pips', 1000000, 1.2712, 0.0001], [4500.0, 3539.96]], ['normal control 1', [45.0, 'pct_term', 5000000, 1.2712, 0.0001], [2860200.0, 2250000.0]], ['normal control 2', [0.85, 'pct_base', 1000000, 1.0845, 0.0001], [9218.25, 8500.0]], ['normal control 3', [0.85, 'pct_base', 5000000, 1.0845, 0.0001], [46091.25, 42500.0]], ['normal control 4', [0.85, 'pct_term', 250000, 1.2712, 0.0001], [2701.3, 2125.0]]], [['regression pip base conversion 1', [12.5, 'pips', 1000000, 1.2712, 0.0001], [1250.0, 983.32]], ['regression pip base conversion 2', [12.5, 'pips', 5000000, 149.35, 0.01], [625000.0, 4184.8]], ['partial repair probe 1', [45.0, 'pips', 5000000, 149.35, 0.01], [2250000.0, 15065.28]], ['partial repair probe 2', [1.25, 'pips', 250000, 1.2712, 0.0001], [31.25, 24.58]], ['normal control 1', [12.5, 'pct_term', 5000000, 1.2712, 0.0001], [794500.0, 625000.0]], ['normal control 2', [45.0, 'pct_term', 5000000, 1.2712, 0.0001], [2860200.0, 2250000.0]], ['normal control 3', [12.5, 'pct_base', 5000000, 1.0845, 0.0001], [677812.5, 625000.0]], ['normal control 4', [1.25, 'pct_term', 250000, 1.0845, 0.0001], [3389.06, 3125.0]]], [['regression pip base conversion 1', [45.0, 'pips', 250000, 1.0845, 0.0001], [1125.0, 1037.34]], ['regression pip base conversion 2', [12.5, 'pips', 1000000, 149.35, 0.01], [125000.0, 836.96]], ['partial repair probe 1', [110.0, 'pips', 1000000, 149.35, 0.01], [1100000.0, 7365.25]], ['partial repair probe 2', [12.5, 'pips', 250000, 1.0845, 0.0001], [312.5, 288.15]], ['normal control 1', [0.85, 'pct_base', 250000, 149.35, 0.01], [317368.75, 2125.0]], ['normal control 2', [45.0, 'pct_base', 1000000, 149.35, 0.01], [67207500.0, 450000.0]], ['normal control 3', [110.0, 'pct_base', 1000000, 149.35, 0.01], [164285000.0, 1100000.0]], ['normal control 4', [45.0, 'pct_base', 5000000, 149.35, 0.01], [336037500.0, 2250000.0]]], [['regression pip base conversion 1', [1.25, 'pips', 5000000, 149.35, 0.01], [62500.0, 418.48]], ['regression pip base conversion 2', [12.5, 'pips', 250000, 1.0845, 0.0001], [312.5, 288.15]], ['partial repair probe 1', [45.0, 'pips', 5000000, 1.2712, 0.0001], [22500.0, 17699.81]], ['partial repair probe 2', [0.85, 'pips', 1000000, 1.2712, 0.0001], [85.0, 66.87]], ['normal control 1', [12.5, 'pct_base', 5000000, 1.0845, 0.0001], [677812.5, 625000.0]], ['normal control 2', [1.25, 'pct_base', 250000, 149.35, 0.01], [466718.75, 3125.0]], ['normal control 3', [12.5, 'pct_term', 1000000, 149.35, 0.01], [18668750.0, 125000.0]], ['normal control 4', [1.25, 'pct_base', 1000000, 1.2712, 0.0001], [15890.0, 12500.0]]]]\nfor label, args, expected in fixtures[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":"A deterministic toy contract stated explicitly in the contract field; no claim of conformance to any exchange or clearing rulebook. 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-options_payoff_and_settlement-fx-premium-conversion-pip-base-conversion","generated_at":"2026-09-29T14:46:58.039788+00:00","license":"CC0-1.0","python":"3.12.14","seed":1,"split":"open-access"},"relevance":"Option expiry, exercise and settlement engines move cash and shares; a wrong branch misstates obligations.","repair":"Divide the term amount by spot.","root_cause":"The pips branch multiplies term by spot.","sha256":"ecf6afc6d4d0a23682be7593e785e1bdb7a98a76ea2fa6290cbbe90fc011b6c4","title":"FX option premium quote conversion: pip premiums are converted to base by multiplying by spot · case 01","variant":1,"variant_policy":"Five numbered records share a model and may reuse boundary fixtures.","verification":{"attempt":{"elapsed_ms":42.045,"exit_code":1,"observations":[{"actual":[450000.0,67207500.0],"check":"regression pip base conversion 1","expected":[450000.0,3013.06],"passed":false},{"actual":[55000.0,59647.5],"check":"regression pip base conversion 2","expected":[55000.0,50714.62],"passed":false},{"actual":[125.0,158.9],"check":"partial repair probe 1","expected":[125.0,98.33],"passed":false},{"actual":[6250.0,7945.0],"check":"partial repair probe 2","expected":[6250.0,4916.61],"passed":false},{"actual":[67781.25,62500.0],"check":"normal control 1","expected":[67781.25,62500.0],"passed":true},{"actual":[15890.0,12500.0],"check":"normal control 2","expected":[15890.0,12500.0],"passed":true},{"actual":[9218.25,8500.0],"check":"normal control 3","expected":[9218.25,8500.0],"passed":true},{"actual":[794500.0,625000.0],"check":"normal control 4","expected":[794500.0,625000.0],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression pip base conversion 1\", \"actual\": [450000.0, 67207500.0], \"expected\": [450000.0, 3013.06], \"passed\": false}, {\"check\": \"regression pip base conversion 2\", \"actual\": [55000.0, 59647.5], \"expected\": [55000.0, 50714.62], \"passed\": false}, {\"check\": \"partial repair probe 1\", \"actual\": [125.0, 158.9], \"expected\": [125.0, 98.33], \"passed\": false}, {\"check\": \"partial repair probe 2\", \"actual\": [6250.0, 7945.0], \"expected\": [6250.0, 4916.61], \"passed\": false}, {\"check\": \"normal control 1\", \"actual\": [67781.25, 62500.0], \"expected\": [67781.25, 62500.0], \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": [15890.0, 12500.0], \"expected\": [15890.0, 12500.0], \"passed\": true}, {\"check\": \"normal control 3\", \"actual\": [9218.25, 8500.0], \"expected\": [9218.25, 8500.0], \"passed\": true}, {\"check\": \"normal control 4\", \"actual\": [794500.0, 625000.0], \"expected\": [794500.0, 625000.0], \"passed\": true}], \"passed\": false}\n"},"broken":{"elapsed_ms":42.876,"exit_code":1,"observations":[{"actual":[450000.0,67207500.0],"check":"regression pip base conversion 1","expected":[450000.0,3013.06],"passed":false},{"actual":[55000.0,59647.5],"check":"regression pip base conversion 2","expected":[55000.0,50714.62],"passed":false},{"actual":[125.0,158.9],"check":"partial repair probe 1","expected":[125.0,98.33],"passed":false},{"actual":[6250.0,7945.0],"check":"partial repair probe 2","expected":[6250.0,4916.61],"passed":false},{"actual":[67781.25,62500.0],"check":"normal control 1","expected":[67781.25,62500.0],"passed":true},{"actual":[15890.0,12500.0],"check":"normal control 2","expected":[15890.0,12500.0],"passed":true},{"actual":[9218.25,8500.0],"check":"normal control 3","expected":[9218.25,8500.0],"passed":true},{"actual":[794500.0,625000.0],"check":"normal control 4","expected":[794500.0,625000.0],"passed":true}],"passed":false,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression pip base conversion 1\", \"actual\": [450000.0, 67207500.0], \"expected\": [450000.0, 3013.06], \"passed\": false}, {\"check\": \"regression pip base conversion 2\", \"actual\": [55000.0, 59647.5], \"expected\": [55000.0, 50714.62], \"passed\": false}, {\"check\": \"partial repair probe 1\", \"actual\": [125.0, 158.9], \"expected\": [125.0, 98.33], \"passed\": false}, {\"check\": \"partial repair probe 2\", \"actual\": [6250.0, 7945.0], \"expected\": [6250.0, 4916.61], \"passed\": false}, {\"check\": \"normal control 1\", \"actual\": [67781.25, 62500.0], \"expected\": [67781.25, 62500.0], \"passed\": true}, {\"check\": \"normal control 2\", \"actual\": [15890.0, 12500.0], \"expected\": [15890.0, 12500.0], \"passed\": true}, {\"check\": \"normal control 3\", \"actual\": [9218.25, 8500.0], \"expected\": [9218.25, 8500.0], \"passed\": true}, {\"check\": \"normal control 4\", \"actual\": [794500.0, 625000.0], \"expected\": [794500.0, 625000.0], \"passed\": true}], \"passed\": false}\n"},"fixed":{"elapsed_ms":44.022,"exit_code":0,"observations":[{"actual":[450000.0,3013.06],"check":"regression pip base conversion 1","expected":[450000.0,3013.06],"passed":true},{"actual":[55000.0,50714.62],"check":"regression pip base conversion 2","expected":[55000.0,50714.62],"passed":true},{"actual":[125.0,98.33],"check":"partial repair probe 1","expected":[125.0,98.33],"passed":true},{"actual":[6250.0,4916.61],"check":"partial repair probe 2","expected":[6250.0,4916.61],"passed":true},{"actual":[67781.25,62500.0],"check":"normal control 1","expected":[67781.25,62500.0],"passed":true},{"actual":[15890.0,12500.0],"check":"normal control 2","expected":[15890.0,12500.0],"passed":true},{"actual":[9218.25,8500.0],"check":"normal control 3","expected":[9218.25,8500.0],"passed":true},{"actual":[794500.0,625000.0],"check":"normal control 4","expected":[794500.0,625000.0],"passed":true}],"passed":true,"stderr":"","stdout":"{\"observations\": [{\"check\": \"regression pip base 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