{"record":{"id":"b7c78502694097ab","repo":"HKUDS/Vibe-Trading","slug":"returns-and-var-must-be-the-same-length-got-ret","errorCode":null,"errorMessage":"returns and var must be the same length, got {ret_values.size} and {var_values.size}","messagePattern":"returns and var must be the same length, got (.+?) and (.+?)","errorType":"validation","errorClass":"ValueError","httpStatus":null,"severity":"error","filePath":"agent/src/quantlib/var_backtest.py","lineNumber":286,"sourceCode":"                \"partial join silently compares each day against another day's \"\n                \"forecast.\"\n            )\n\n    ret_values = np.asarray(returns, dtype=float)\n    if ret_values.ndim > 1:\n        raise ValueError(f\"returns must be 1-D, got shape {ret_values.shape}\")\n    ret_values = ret_values.ravel()\n\n    var_values = np.asarray(var, dtype=float)\n    if var_values.ndim == 0:\n        var_values = np.full(ret_values.shape, float(var_values))\n    else:\n        if var_values.ndim > 1:\n            raise ValueError(f\"var must be 1-D or scalar, got shape {var_values.shape}\")\n        var_values = var_values.ravel()\n\n    if ret_values.size != var_values.size:\n        raise ValueError(\n            f\"returns and var must be the same length, got {ret_values.size} \"\n            f\"and {var_values.size}\"\n        )\n    if ret_values.size == 0:\n        raise ValueError(\"returns is empty\")\n\n    keep = np.isfinite(ret_values) & np.isfinite(var_values)\n    dropped = int((~keep).sum())\n    if not keep.any():\n        raise ValueError(\"no observation has a finite return and a finite var\")\n\n    index = ret_index if ret_index is not None else var_index\n    kept_index = index[keep] if index is not None else None\n    return ret_values[keep], var_values[keep], kept_index, dropped\n\n\ndef violation_indicator(\n    returns: pd.Series | np.ndarray | Sequence[float],","sourceCodeStart":268,"sourceCodeEnd":304,"githubUrl":"https://github.com/HKUDS/Vibe-Trading/blob/80ffdda44c5c4db0dd84d70e051cca591cea67df/agent/src/quantlib/var_backtest.py#L268-L304","documentation":"Once both inputs are 1-D (and var was not a broadcast scalar), _align requires equal element counts; a length mismatch raises ValueError showing both sizes. This typically happens when one side lost rows (dropna, rolling-window warmup) or plain arrays without indexes were passed with different lengths.","triggerScenarios":"Passing a numpy returns array of 500 values and a var array of 480 (e.g. after a 20-day rolling warmup dropped rows), or lists built from different date ranges when indexes are absent so the earlier label check cannot fire.","commonSituations":"Rolling VaR estimators that return shorter series than the input returns; dropping NaNs from one array only; concatenating train/test segments inconsistently.","solutions":["Trim returns to the var series' valid range or re-attach indexes and use pandas alignment.","Regenerate var over the full returns sample so lengths match by construction.","Slice both to the overlapping suffix: rets[-len(var):]."],"exampleFix":"# before\nvar_backtest(rets, var)  # 500 vs 480\n# after\nvar_backtest(rets[-len(var):], var)  # aligned tail sample","handlingStrategy":"validation","validationCode":"import numpy as np\nassert np.asarray(returns).size == np.asarray(var).size","typeGuard":"def same_length(returns, var) -> bool:\n    import numpy as np\n    return np.asarray(returns).size == np.asarray(var).size","tryCatchPattern":"except ValueError as e:\n    if 'same length' in str(e): trim both to the overlapping tail","preventionTips":["Trim returns to the VaR warmup window before backtesting","Use indexed Series so alignment errors surface as label errors early"],"tags":["var-backtest","shape-mismatch","length"],"backgroundTag":"length-mismatch","analyzedSha":"80ffdda44c5c4db0dd84d70e051cca591cea67df","analyzedAt":"2026-08-28T12:46:38.989Z","schemaVersion":2},"datasetVersion":"2026-08-28T16:17:29.566Z"}