Add more SCADA API

This commit is contained in:
DingZQ
2025-05-04 17:31:10 +08:00
parent 8dfd56456e
commit 3012ddab06
2 changed files with 115 additions and 20 deletions

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@@ -1612,6 +1612,10 @@ def query_scheme_SCADA_data_by_device_ID_and_time(query_ids_list: List[str], que
return SCADA_result_dict
# 2025/03/14
# DingZQ
# 返回SCADA数据的原始值其中可能包含了异常值跟缺失值我们需要再后续曲线中修复
# 缺失值
# 异常值
def query_SCADA_data_by_device_ID_and_timerange(query_ids_list: List[str], start_time: str, end_time: str, bucket: str="SCADA_data"):
"""
查询指定时间范围内多个SCADA设备的数据用于漏损定位
@@ -1674,6 +1678,8 @@ def query_SCADA_data_by_device_ID_and_timerange(query_ids_list: List[str], start
return SCADA_dict
# 2025/05/04 DingZQ
# SCADA 原始数据有异常偏离返回的是一个listlist的内容是清洗后的正常值表示为 time + value
def query_cleaning_SCADA_data_by_device_ID_and_timerange(query_ids_list: List[str], start_time: str, end_time: str, bucket: str="SCADA_data"):
"""
查询指定时间范围内多个SCADA设备的修复的单个的数据
@@ -1725,26 +1731,11 @@ def query_cleaning_SCADA_data_by_device_ID_and_timerange(query_ids_list: List[st
return SCADA_dict
# DingZQ, 2025-02-15
def query_SCADA_data_by_device_ID_and_date(query_ids_list: List[str], query_date: str, bucket: str="SCADA_data") -> list[dict[str, float]]:
# 2025/05/04 DingZQ
# SCADA 数据原版缺失,根据历史数据的平均值补上缺失的部分
def query_filling_SCADA_data_by_device_ID_and_timerange(query_ids_list: List[str], start_time: str, end_time: str, bucket: str="SCADA_data"):
"""
根据SCADA设备的ID和日期查询值
:param query_ids_list: SCADA设备ID的列表, 是api_query 而不是 普通的Id
:param query_date: 输入的日期,格式为 '2024-11-24', 日期是北京时间的日期
:param bucket: InfluxDB 的 bucket 名称,默认值为 "SCADA_data"
:param client: 已初始化的 InfluxDBClient 实例。
:return:
"""
start_time, end_time = time_api.parse_beijing_date_range(query_date)
return query_SCADA_data_by_device_ID_and_time_range(query_ids_list, str(start_time), str(end_time), bucket)
# 2025/04/17
def query_cleaned_SCADA_data_by_device_ID_and_timerange(query_ids_list: List[str], start_time: str, end_time: str, bucket: str="SCADA_data"):
"""
查询指定时间范围内多个SCADA设备的清洗后的数据
查询指定时间范围内多个SCADA设备的填补的单个的数据
:param query_ids_list: SCADA设备ID的列表
:param start_time: 输入的北京时间,格式为 '2024-11-24T17:30:00+08:00'
:param end_time: 输入的北京时间,格式为 '2024-11-24T17:30:00+08:00'
@@ -1772,7 +1763,7 @@ def query_cleaned_SCADA_data_by_device_ID_and_timerange(query_ids_list: List[str
flux_query = f'''
from(bucket: "{bucket}")
|> range(start: {utc_start_time.isoformat()}, stop: {utc_stop_time.isoformat()})
|> filter(fn: (r) => r["device_ID"] == "{device_id}" and r["_field"] == "datacleaning_value")
|> filter(fn: (r) => r["device_ID"] == "{device_id}" and r["_field"] == "datafilling_value")
|> sort(columns: ["_time"])
'''
# 执行查询,返回一个 FluxTable 列表
@@ -1787,9 +1778,80 @@ def query_cleaned_SCADA_data_by_device_ID_and_timerange(query_ids_list: List[str
"value": record["_value"]
})
SCADA_dict[device_id] = records_list
client.close()
return SCADA_dict
# 2025/05/04 DingZQ
# 是把原始数据跟清洗后的数据合并到一起暂时不需要用这个API
def query_cleaned_SCADA_data_by_device_ID_and_timerange(query_ids_list: List[str], start_time: str, end_time: str, bucket: str="SCADA_data"):
"""
查询指定时间范围内多个SCADA设备的清洗完毕后的完整数据
:param query_ids_list: SCADA设备ID的列表
:param start_time: 输入的北京时间,格式为 '2024-11-24T17:30:00+08:00'
:param end_time: 输入的北京时间,格式为 '2024-11-24T17:30:00+08:00'
:param bucket: InfluxDB 的 bucket 名称,默认值为 "SCADA_data"
:return:
"""
client = get_new_client()
if not client.ping():
print("{} -- Failed to connect to InfluxDB.".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S')))
query_api = client.query_api()
print('start_time', start_time)
print('end_time', end_time)
# 将北京时间转换为 UTC 时间
beijing_start_time = datetime.fromisoformat(start_time)
print('beijing_start_time', beijing_start_time)
utc_start_time = time_api.to_utc_time(beijing_start_time)
print('utc_start_time', utc_start_time)
beijing_end_time = datetime.fromisoformat(end_time)
print('beijing_end_time', beijing_end_time)
utc_stop_time = time_api.to_utc_time(beijing_end_time)
print('utc_stop_time', utc_stop_time)
SCADA_dict = {}
for device_id in query_ids_list:
flux_query = f'''
from(bucket: "{bucket}")
|> range(start: {utc_start_time.isoformat()}, stop: {utc_stop_time.isoformat()})
|> filter(fn: (r) => r["device_ID"] == "{device_id}" and r["_field"] == "cleaned_value")
|> sort(columns: ["_time"])
'''
# 执行查询,返回一个 FluxTable 列表
tables = query_api.query(flux_query)
print(tables)
records_list = []
for table in tables:
for record in table.records:
# 获取记录的时间和监测值
records_list.append({
"time": record["_time"],
"value": record["_value"]
})
SCADA_dict[device_id] = records_list
client.close()
return SCADA_dict
# DingZQ, 2025-02-15
def query_SCADA_data_by_device_ID_and_date(query_ids_list: List[str], query_date: str, bucket: str="SCADA_data") -> list[dict[str, float]]:
"""
根据SCADA设备的ID和日期查询值
:param query_ids_list: SCADA设备ID的列表, 是api_query 而不是 普通的Id
:param query_date: 输入的日期,格式为 '2024-11-24', 日期是北京时间的日期
:param bucket: InfluxDB 的 bucket 名称,默认值为 "SCADA_data"
:param client: 已初始化的 InfluxDBClient 实例。
:return:
"""
start_time, end_time = time_api.parse_beijing_date_range(query_date)
return query_SCADA_data_by_device_ID_and_timerange(query_ids_list, str(start_time), str(end_time), bucket)
# 2025/02/01
def store_realtime_simulation_result_to_influxdb(node_result_list: List[Dict[str, any]], link_result_list: List[Dict[str, any]],