[
    {
        "name": "预处理算子",
        "version": "1.1.0",
        "author": "Antigravity",
        "description": "去直流、带通滤波（默认10-400Hz）",
        "type": "python",
        "module": "src.sample_algorithms",
        "function": "dc_removal_and_bandpass",
        "inputs": {
            "raw_data": {
                "field": "raw_data",
                "type": "ndarray",
                "description": "原始声呐数据"
            },
            "fs": {
                "field": "sample_rate",
                "type": "float",
                "description": "采样率"
            }
        },
        "outputs": {
            "clean_data": {
                "index": 0,
                "type": "ndarray",
                "description": "预处理后数据"
            }
        }
    },
    {
        "name": "时频分析",
        "version": "1.1.0",
        "author": "Antigravity",
        "description": "STFT 幅度谱计算",
        "type": "python",
        "module": "src.sample_algorithms",
        "function": "stft_magnitude",
        "inputs": {
            "clean_data": {
                "field": "clean_data",
                "type": "ndarray",
                "description": "清洗后数据"
            }
        },
        "outputs": {
            "stft_data": {
                "index": 0,
                "type": "ndarray",
                "description": "STFT矩阵"
            }
        }
    },
    {
        "name": "SNR估计",
        "version": "1.1.0",
        "author": "Antigravity",
        "description": "基于 RMS/Var 的简易信噪比估计",
        "type": "python",
        "module": "src.sample_algorithms",
        "function": "snr_estimation",
        "inputs": {
            "raw_data": {
                "field": "raw_data",
                "type": "ndarray",
                "description": "待评估数据"
            }
        },
        "outputs": {
            "snr_value": {
                "index": 0,
                "type": "float",
                "description": "信噪比(dB)"
            }
        }
    },
    {
        "name": "质量巡检",
        "version": "1.1.0",
        "author": "Antigravity",
        "description": "掉点、饱和与数据完整性检测",
        "type": "python",
        "module": "src.sample_algorithms",
        "function": "quality_check",
        "inputs": {
            "raw_data": {
                "field": "raw_data",
                "type": "ndarray",
                "description": "待校验原始数据"
            }
        },
        "outputs": {
            "core_index": {
                "index": 0,
                "type": "dict",
                "description": "质量指标集"
            }
        }
    },
    {
        "name": "C++ 增益算子",
        "version": "1.0.0",
        "author": "Antigravity",
        "description": "使用 C++ 侧实现的高效增益处理(1.5x)",
        "type": "cpp",
        "lib_path": "src/sample_algos_cpp/simple_ops.so",
        "function": "multiply_by_factor_cpp",
        "inputs": {
            "in_data": {
                "field": "clean_data",
                "type": "ndarray",
                "description": "输入数据"
            }
        },
        "outputs": {
            "gain_data": {
                "type": "ndarray",
                "index": 0,
                "description": "增益后数据"
            }
        }
    },
    {
        "name": "MATLAB 带通算子",
        "version": "1.0.0",
        "author": "Antigravity",
        "description": "基于 MATLAB .m 实现的带通滤波",
        "type": "matlab",
        "m_path": "src/sample_algos_matlab",
        "function": "bandpass_filter_m",
        "inputs": {
            "in_data": {
                "field": "raw_data",
                "type": "ndarray",
                "description": "输入数据"
            },
            "fs": {
                "field": "sample_rate",
                "type": "float",
                "description": "采样率"
            }
        },
        "outputs": {
            "m_filtered": {
                "type": "ndarray",
                "index": 0,
                "description": "滤波后数据"
            }
        }
    }
]