299 lines
9.8 KiB
JSON
299 lines
9.8 KiB
JSON
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}
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}
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},
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"type": "object",
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"description": "数据体检始终返回诊断产物；命中 fail_on 时 diagnostics.passed=false，但 Job 本身成功完成，供调用方决定是否继续分析。",
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"non_finite",
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"uneven_spacing"
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}
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},
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"type": "object",
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"description": "max_abs 使用最大绝对值；area 使用有符号梯形积分；reference 在数据范围内按 X 线性插值得到归一化除数。",
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{
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}
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]
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},
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"smooth_parameters": {
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"type": "object",
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"description": "固定局部多项式平滑；窗口必须为奇数，边界使用平移后的完整窗口，不补造数据点。",
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"required": ["method", "window", "polynomial_order"],
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"method": {"const": "savitzky_golay"},
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}
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},
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"type": "object",
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"description": "使用支持非等间距 X 的二阶边界数值梯度，按 order 重复求导。",
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"required": ["order"],
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"additionalProperties": false,
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"order": {"type": "integer", "enum": [1, 2]}
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}
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},
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"integrate_parameters": {
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"type": "object",
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"description": "使用梯形积分输出从首个 X 开始的累计积分；from/to 省略时报告完整范围积分。",
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}
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},
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"type": "object",
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"description": "固定最小二乘线性拟合并输出 95% t 置信区间、R²、RMSE 和残差；同时在 OPJU 中生成 Origin 原生线性拟合报告。",
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"required": ["include_intercept", "confidence_level"],
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