302 lines
16 KiB
Python
302 lines
16 KiB
Python
from datetime import datetime, date
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class OperatingModePredictor:
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"""
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工况预测类（处理二维倒序数据，返回一维列表，仅保留各内嵌列表最新记录）
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功能：根据输入的带时间序列的工况数据，推导每个监测点（point_id）的下一阶段工况
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特性：
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1. 输入为二维列表，每个内嵌列表对应一个point_id，且为倒序排列（最新记录在索引0）
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2. 输出为一维列表，仅保留每个内嵌列表的最新记录，新增工况推导结果字段
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3. 无需切换工况时，next_workinfo返回当前工况名称；需要切换时返回目标工况名称
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4. 时间计算仅按日期（天）维度，忽略时分秒
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"""
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def __init__(self):
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"""初始化类，加载内置的工况配置、分组规则和切换触发规则"""
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# 基础工况配置（键：工况名称，值：基础监测周期参考）
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self.base_periods = self._load_base_periods()
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# 工况分组（将同义不同格式的工况归类，共用切换规则）
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self.condition_group = self._load_condition_group()
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# 工况切换触发规则（键：分组ID，值：触发天数+目标工况候选）
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self.group_transition_rules = self._load_group_transition_rules()
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def _load_base_periods(self):
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"""加载基础工况配置（私有方法，内部使用）"""
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return {
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"仰拱（底板）施工完成后，第1个月": 7,
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"仰拱（底板）施工完成后，第2至3个月": 14,
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"仰拱（底板）施工完成后，3个月以后": 30,
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"仰拱(底板)施工完成后，第1个月": 7,
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"仰拱(底板)施工完成后，第2至3个月": 14,
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"仰拱(底板)施工完成后，3个月以后": 30,
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"无砟轨道铺设后，第1至3个月": 30,
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"无砟轨道铺设后，4至12个月": 90,
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"无砟轨道铺设后，12个月以后": 180,
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"墩台施工到一定高度": 30,
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"墩台混凝土施工": 30,
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"预制梁桥，架梁前": 30,
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"预制梁桥，预制梁架设前": 1,
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"预制梁桥，预制梁架设后": 7,
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"桥位施工桥梁，制梁前": 30,
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"桥位施工桥梁，上部结构施工中": 1,
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"架桥机(运梁车)通过": 7,
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"桥梁主体工程完工后，第1至3个月": 7,
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"桥梁主体工程完工后，第4至6个月": 14,
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"桥梁主体工程完工后，6个月以后": 30,
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"轨道铺设期间，前": 30,
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"轨道铺设期间，后": 14,
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"轨道铺设完成后，第1个月": 14,
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"轨道铺设完成后，2至3个月": 30,
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"轨道铺设完成后，4至12个月": 90,
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"轨道铺设完成后，12个月以后": 180,
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"铺路或堆载，一般情况": 1,
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"填筑或堆载，一般情况": 1,
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"铺路或堆载，沉降量突变情况": 1,
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"填筑或堆载，两次填筑间隔时间较长情况": 3,
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"铺路或堆载，两次铺路间隔时间较长情况": 3,
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"堆载预压或路基填筑完成，第1至3个月": 7,
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"堆载预压或路基填筑完成，第4至6个月": 14,
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"堆载预压或路基填筑完成，6个月以后": 30,
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"架桥机(运梁车) 首次通过前": 1,
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"架桥机(运梁车) 首次通过后，前3天": 1,
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"架桥机(运梁车) 首次通过后": 7,
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"轨道板(道床)铺设后，第1个月": 14,
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"轨道板(道床)铺设后，第2至3个月": 30,
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"轨道板(道床)铺设后，3个月以后": 90
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}
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def _load_condition_group(self):
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"""加载工况分组规则（私有方法，内部使用）"""
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return {
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"仰拱（底板）施工完成后，第1个月": "YG_DIBAN_1",
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"仰拱(底板)施工完成后，第1个月": "YG_DIBAN_1",
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"仰拱（底板）施工完成后，第2至3个月": "YG_DIBAN_2_3",
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"仰拱(底板)施工完成后，第2至3个月": "YG_DIBAN_2_3",
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"仰拱（底板）施工完成后，3个月以后": "YG_DIBAN_AFTER_3",
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"仰拱(底板)施工完成后，3个月以后": "YG_DIBAN_AFTER_3",
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"架桥机(运梁车) 首次通过前": "JQJ_FIRST_BEFORE",
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"架桥机(运梁车) 首次通过后，前3天": "JQJ_FIRST_AFTER_3D",
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"架桥机(运梁车) 首次通过后": "JQJ_FIRST_AFTER",
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"堆载预压或路基填筑完成，第1至3个月": "DZYY_1_3",
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"堆载预压或路基填筑完成，第4至6个月": "DZYY_4_6",
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"堆载预压或路基填筑完成，6个月以后": "DZYY_AFTER_6",
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"轨道板(道床)铺设后，第1个月": "GDB_1",
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"轨道板(道床)铺设后，第2至3个月": "GDB_2_3",
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"轨道板(道床)铺设后，3个月以后": "GDB_AFTER_3",
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"预制梁桥，预制梁架设前": "YZLQ_BEFORE_JS",
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"预制梁桥，预制梁架设后": "YZLQ_AFTER_JS",
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"桥梁主体工程完工后,第1至3个月": "QL_ZHUTI_1_3",
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"桥梁主体工程完工后，第4至6个月": "QL_ZHUTI_4_6",
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"桥梁主体工程完工后,6个月以后": "QL_ZHUTI_AFTER_6",
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"轨道铺设完成后，第1个月": "GD_1",
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"轨道铺设完成后，2至3个月": "GD_2_3",
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"轨道铺设完成后，4至12个月": "GD_4_12",
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"轨道铺设完成后，12个月以后": "GD_AFTER_12",
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"无砟轨道铺设后，第1至3个月": "WZGD_1_3",
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"无砟轨道铺设后，4至12个月": "WZGD_4_12",
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"无砟轨道铺设后，12个月以后": "WZGD_AFTER_12",
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"墩台施工到一定高度": "STATIC",
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"墩台混凝土施工": "STATIC",
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"预制梁桥，架梁前": "STATIC",
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"桥位施工桥梁，制梁前": "STATIC",
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"桥位施工桥梁，上部结构施工中": "STATIC",
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"架桥机(运梁车)通过": "STATIC",
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"轨道铺设期间，前": "STATIC",
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"轨道铺设期间，后": "STATIC",
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"铺路或堆载，一般情况": "STATIC",
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"填筑或堆载，一般情况": "STATIC",
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"铺路或堆载，沉降量突变情况": "STATIC",
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"填筑或堆载，两次填筑间隔时间较长情况": "STATIC",
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"铺路或堆载，两次铺路间隔时间较长情况": "STATIC"
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}
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def _load_group_transition_rules(self):
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"""加载工况切换触发规则（私有方法，内部使用）"""
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return {
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"YG_DIBAN_1": {"trigger_days": 30, "next_candidates": ["仰拱（底板）施工完成后，第2至3个月", "仰拱(底板)施工完成后，第2至3个月"]},
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"YG_DIBAN_2_3": {"trigger_days": 60, "next_candidates": ["仰拱（底板）施工完成后，3个月以后", "仰拱(底板)施工完成后，3个月以后"]},
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"YG_DIBAN_AFTER_3": {"trigger_days": None, "next_candidates": None},
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"JQJ_FIRST_BEFORE": {"trigger_days": 1, "next_candidates": ["架桥机(运梁车) 首次通过后，前3天"]},
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"JQJ_FIRST_AFTER_3D": {"trigger_days": 3, "next_candidates": ["架桥机(运梁车) 首次通过后"]},
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"JQJ_FIRST_AFTER": {"trigger_days": None, "next_candidates": None},
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"DZYY_1_3": {"trigger_days": 90, "next_candidates": ["堆载预压或路基填筑完成，第4至6个月"]},
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"DZYY_4_6": {"trigger_days": 90, "next_candidates": ["堆载预压或路基填筑完成，6个月以后"]},
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"DZYY_AFTER_6": {"trigger_days": None, "next_candidates": None},
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"GDB_1": {"trigger_days": 30, "next_candidates": ["轨道板(道床)铺设后，第2至3个月"]},
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"GDB_2_3": {"trigger_days": 30, "next_candidates": ["轨道板(道床)铺设后，3个月以后"]},
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"GDB_AFTER_3": {"trigger_days": None, "next_candidates": None},
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"YZLQ_BEFORE_JS": {"trigger_days": 1, "next_candidates": ["架桥机(运梁车)通过"]},
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"YZLQ_AFTER_JS": {"trigger_days": 7, "next_candidates": ["桥梁主体工程完工后，第1至3个月"]},
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"QL_ZHUTI_1_3": {"trigger_days": 90, "next_candidates": ["桥梁主体工程完工后，第4至6个月"]},
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"QL_ZHUTI_4_6": {"trigger_days": 90, "next_candidates": ["桥梁主体工程完工后，6个月以后"]},
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"QL_ZHUTI_AFTER_6": {"trigger_days": None, "next_candidates": None},
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"GD_1": {"trigger_days": 30, "next_candidates": ["轨道铺设完成后，2至3个月"]},
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"GD_2_3": {"trigger_days": 60, "next_candidates": ["轨道铺设完成后，4至12个月"]},
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"GD_4_12": {"trigger_days": 240, "next_candidates": ["轨道铺设完成后，12个月以后"]},
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"GD_AFTER_12": {"trigger_days": None, "next_candidates": None},
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"WZGD_1_3": {"trigger_days": 90, "next_candidates": ["无砟轨道铺设后，4至12个月"]},
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"WZGD_4_12": {"trigger_days": 240, "next_candidates": ["无砟轨道铺设后，12个月以后"]},
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"WZGD_AFTER_12": {"trigger_days": None, "next_candidates": None},
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"STATIC": {"trigger_days": None, "next_candidates": None}
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}
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def _parse_to_date(self, time_str):
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"""
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私有辅助方法：将时间字符串解析为日期对象，仅保留年月日，忽略时分秒
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:param time_str: 时间字符串，格式为 "YYYY-MM-DD HH:MM:SS"
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:return: date对象 / None（解析失败时）
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"""
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if not time_str:
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return None
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try:
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dt = datetime.strptime(str(time_str).strip(), "%Y-%m-%d %H:%M:%S")
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return dt.date()
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except ValueError:
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return None
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def _get_time_statistics_from_reversed(self, data, workinfo):
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"""
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私有辅助方法：从倒序数据中提取时间统计信息
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:param data: 单个point_id的倒序数据列表
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:param workinfo: 当前工况名称
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:return: 元组 (首次测量日期date对象, 首次到末次持续天数, 今日与首次测量天数差)
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"""
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# 筛选当前工况的有效记录
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reversed_records = [d for d in data if d.get("workinfoname") == workinfo]
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if not reversed_records:
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return None, 0, 0
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# 解析所有有效记录的日期
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reversed_dates = []
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for item in reversed_records:
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d = self._parse_to_date(item.get("MTIME_W"))
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if d:
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reversed_dates.append(d)
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if not reversed_dates:
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return None, 0, 0
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# 提取倒序数据的最新、最旧日期
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last_date = reversed_dates[0]
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first_date = reversed_dates[-1]
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# 计算累计天数和今日与首次测量的天数差
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cumulative_days = (last_date - first_date).days
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today = date.today()
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days_to_today = (today - first_date).days if first_date else 0
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return first_date, cumulative_days, days_to_today
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def _match_next_condition(self, current_name, candidates):
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"""
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私有辅助方法：按符号风格匹配下一个工况名称（全角/半角括号对应）
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:param current_name: 当前工况名称
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:param candidates: 目标工况候选列表
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:return: 匹配的工况名称 / 当前工况名称（无候选时）
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"""
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if not candidates:
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return current_name
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# 优先匹配全角括号工况
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if "（" in current_name:
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for cand in candidates:
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if "（" in cand:
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return cand
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# 再匹配半角括号工况
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if "(" in current_name:
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for cand in candidates:
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if "(" in cand:
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return cand
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# 无对应符号时，返回第一个候选工况
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return candidates[0]
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def _validate_point_id(self, inner_list):
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"""
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私有辅助方法：校验内嵌列表内所有元素的point_id是否一致
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:param inner_list: 单个point_id的倒序数据列表
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:return: point_id / None（校验失败或列表为空时）
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"""
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if not inner_list:
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return None
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base_point_id = inner_list[0].get("point_id")
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for item in inner_list:
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if item.get("point_id") != base_point_id:
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return None
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return base_point_id
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def predict(self, data_2d_list):
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"""
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公有核心方法：执行工况预测，处理二维输入数据，返回一维结果列表
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:param data_2d_list: 二维倒序数据列表，格式 [[{},{},{}], [{},{},{}]]
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:return: 一维结果列表，格式 [{}, {}, {}]，每个元素为对应内嵌列表的最新记录+推导字段
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"""
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final_result_1d = []
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# 遍历二维列表，逐个处理每个point_id的内嵌数据
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for inner_data_list in data_2d_list:
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# 跳过空列表
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if not isinstance(inner_data_list, list) or len(inner_data_list) == 0:
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continue
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# 1. 提取当前内嵌列表的最新记录（倒序数据索引0为最新）
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latest_record = inner_data_list[0].copy()
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# 2. 校验point_id一致性
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point_id = self._validate_point_id(inner_data_list)
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if not point_id:
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latest_record.update({
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"status": "fail",
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"current_workinfo": None,
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"first_measure_date": None,
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"days_from_first_to_today": None,
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"next_workinfo": None,
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"error_msg": "point_id不一致或缺失"
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})
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final_result_1d.append(latest_record)
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continue
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# 3. 提取并校验当前工况
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current_workinfo = latest_record.get("workinfoname")
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if not current_workinfo or current_workinfo not in self.base_periods:
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latest_record.update({
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"status": "fail",
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"current_workinfo": None,
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"first_measure_date": None,
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"days_from_first_to_today": None,
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"next_workinfo": None,
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"error_msg": "工况无效或缺失"
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})
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final_result_1d.append(latest_record)
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continue
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# 4. 提取时间统计信息
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first_dt, cumulative_days, days_to_today = self._get_time_statistics_from_reversed(
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inner_data_list, current_workinfo
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)
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first_measure_date = first_dt.strftime("%Y-%m-%d") if first_dt else None
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# 5. 判断工况切换条件，推导下一工况
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group_id = self.condition_group.get(current_workinfo, "STATIC")
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rule = self.group_transition_rules.get(group_id, {})
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trigger_days = rule.get("trigger_days")
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next_candidates = rule.get("next_candidates", [])
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if trigger_days is not None and cumulative_days >= trigger_days:
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# 满足切换条件：返回目标工况
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next_workname = self._match_next_condition(current_workinfo, next_candidates)
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else:
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# 不满足切换条件：返回当前工况
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next_workname = current_workinfo
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# 6. 组装结果字段，更新最新记录
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latest_record.update({
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"status": "success",
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"current_workinfo": current_workinfo,
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"first_measure_date": first_measure_date,
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"days_from_first_to_today": days_to_today,
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"next_workinfo": next_workname,
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"point_id": point_id
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})
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# 7. 加入最终结果列表
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final_result_1d.append(latest_record)
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return final_result_1d |