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停顿开始时间指从有水流到无水流，停顿结束时间指从无水流到有水流\n for i in range(len(data)-1):\n if (data.loc[i,\"volume_water\"] != 0) & (data.loc[i + 1,\"volume_water\"] == 0) :\n data.loc[i + 1,\"stop_start_time\"] = data.loc[i +1, \"time\"] - timeDel\n if (data.loc[i,\"volume_water\"] == 0) & (data.loc[i + 1,\"volume_water\"] != 0) :\n data.loc[i,\"stop_end_time\"] = data.loc[i , \"time\"] + timeDel\n # 提取停顿开始时间与结束时间所对应行号，放在数据框Stop中\n indStopStart = data.index[data[\"stop_start_time\"].notnull()]+1\n indStopEnd = data.index[data[\"stop_end_time\"].notnull()]+1\n Stop = pd.DataFrame(data = {\"stop_start_id\":indStopStart[:-1],\n \"stop_end_id\":indStopEnd[1:]}) \n # 计算停顿时长，并放在数据框stop中，停顿时长=停顿结束时间-停顿结束时间\n tmp2 = data.loc[indStopEnd[1:]-1,\"stop_end_time\"]\n tmp3 = data.loc[indStopStart[:-1]-1,\"stop_start_time\"]\n tmp4 = tmp2.values-tmp3.values\n Stop[\"stop_period\"] = np.int64(tmp4)/1000000000 \n # 将每次停顿与事件匹配,停顿的开始时间要大于事件的开始时间，\n # 且停顿的结束时间要小于事件的结束时间\n for i in range(len(sj)):\n Stop.loc[(Stop[\"stop_start_id\"] > sj.loc[i,\"start_id\"]) & \n (Stop[\"stop_end_id\"] < sj.loc[i,\"end_id\"]),\n \"stop_belong_event\"] = i+1\n \n # 删除停顿次数为0的事件\n Stop = Stop[Stop[\"stop_belong_event\"].notnull()]\n\n # 构造特征 用水事件停顿总时长、停顿次数、停顿平均时长、\n # 用水时长，用水/总时长\n stopAgg = Stop.groupby(\"stop_belong_event\").agg({\"stop_period\":sum,\n \"stop_start_id\":len})\n sj.loc[stopAgg.index - 1,\"sum_stop_period\"] = stopAgg.loc[:,\"stop_period\"].values \n sj.loc[stopAgg.index-1,\"stop_num\"] = stopAgg.loc[:,\"stop_start_id\"].values\n sj.fillna(0,inplace=True) # 对缺失值用0插补\n stopNo0 = sj[\"stop_num\"] != 0 # 判断用水事件是否存在停顿\n sj.loc[stopNo0,\"mean_stop_period\"] = \\\n sj.loc[stopNo0,\"sum_stop_period\"]/sj.loc[stopNo0,\"stop_num\"] \n sj.fillna(0,inplace=True) # 对缺失值用0插补\n sj[\"water_time\"] = sj[\"whole_time\"] - sj[\"sum_stop_period\"] # 定义特征用水时长\n # 定义特征 用水/总时长\n sj[\"perc_water_time\"] = sj[\"water_time\"] / sj[\"whole_time\"]\n \n \n data[\"volume_water\"] = data[\"volume_water\"] / 60 # 原单位L/min，现转换为L/sec\n sj[\"sum_volume_water\"] = 0 # 给总用水量赋一个初始值0\n for i in range(len(sj)):\n Start = sj.loc[i,\"start_id\"]-1\n End = sj.loc[i,\"end_id\"]-1\n if Start != End:\n for j in range(Start,End):\n if data.loc[j,\"volume_water\"] != 0:\n sj.loc[i,\"sum_volume_water\"] = (data.loc[j + 1,\"time\"] - \n data.loc[j,\"time\"]).seconds* data.loc[j,\"volume_water\"] + sj.loc[i,\"sum_volume_water\"]\n sj.loc[i,\"sum_volume_water\"] = sj.loc[i,\"sum_volume_water\"] + data.loc[End,\"volume_water\"] * 2\n else:\n sj.loc[i,\"sum_volume_water\"] = data.loc[Start,\"volume_water\"] * 2\n \n sj[\"mean_volume_water\"] = sj[\"sum_volume_water\"] / sj[\"water_time\"] # 定义特征 平均水流量\n # 构造特征：水流量波动\n # 水流量波动=∑(((单次水流的值-平均水流量)^2)*持续时间)/用水时长\n sj[\"volatility_volume_water\"] = 0 # 给水流量波动赋一个初始值0\n for i in range(len(sj)):\n Start = sj.loc[i,\"start_id\"] - 1\n End = sj.loc[i,\"end_id\"] - 1\n for j in range(Start,End + 1):\n if data.loc[j,\"volume_water\"] != 0:\n slbd = (data.loc[j,\"volume_water\"] - sj.loc[i,\"mean_volume_water\"])**2\n slsj = (data.loc[j + 1,\"time\"] - data.loc[j,\"time\"]).seconds\n sj.loc[i,\"volatility_volume_water\"] = slbd * slsj + sj.loc[i,\"volatility_volume_water\"]\n sj.loc[i,\"volatility_volume_water\"] = sj.loc[i,\"volatility_volume_water\"] / sj.loc[i,\"water_time\"]\n\n # 构造特征：停顿时长波动\n # 停顿时长波动=∑(((单次停顿时长-平均停顿时长)^2)*持续时间)/总停顿时长\n sj[\"volatility_stop_time\"] = 0 # 给停顿时长波动赋一个初始值0\n for i in range(len(sj)):\n # 当停顿次数为0或1时，停顿时长波动值为0，故排除\n if sj.loc[i,\"stop_num\"] > 1:\n for j in Stop.loc[Stop[\"stop_belong_event\"] == (i+1),\"stop_period\"].values:\n sj.loc[i,\"volatility_stop_time\"] = ((j - sj.loc[i,\"mean_stop_period\"])**2) * j + sj.loc[i,\"volatility_stop_time\"]\n sj.loc[i,\"volatility_stop_time\"] = sj.loc[i,\"volatility_stop_time\"] / sj.loc[i,\"sum_stop_period\"]\n \n return(sj)\n 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