From 6434cae21cfcc6c6ae89dce53015652a701f00e9 Mon Sep 17 00:00:00 2001 From: Jiang Date: Thu, 5 Feb 2026 15:39:56 +0800 Subject: [PATCH] =?UTF-8?q?=E7=BB=9F=E4=B8=80scheme=5Ftype=E5=91=BD?= =?UTF-8?q?=E5=90=8D?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- app/algorithms/simulations.py | 6 +- app/api/v1/endpoints/data_query.py | 4 +- app/infra/db/influxdb/api.py | 116 ++++++++++++++--------------- app/services/simulation.py | 8 +- scripts/main.py | 4 +- scripts/online_Analysis.py | 6 +- 6 files changed, 72 insertions(+), 72 deletions(-) diff --git a/app/algorithms/simulations.py b/app/algorithms/simulations.py index 4dd9b5c..d5dc235 100644 --- a/app/algorithms/simulations.py +++ b/app/algorithms/simulations.py @@ -261,7 +261,7 @@ def valve_close_analysis( modify_pattern_start_time=modify_pattern_start_time, modify_total_duration=modify_total_duration, modify_valve_opening=modify_valve_opening, - scheme_Type="valve_close_Analysis", + scheme_type="valve_close_Analysis", scheme_name=scheme_name, ) # step 3. restore the base model @@ -392,7 +392,7 @@ def flushing_analysis( modify_pattern_start_time=modify_pattern_start_time, modify_total_duration=modify_total_duration, modify_valve_opening=modify_valve_opening, - scheme_Type="flushing_Analysis", + scheme_type="flushing_analysis", scheme_name=scheme_name, ) # step 4. restore the base model @@ -711,7 +711,7 @@ def pressure_regulation( modify_tank_initial_level=modify_tank_initial_level, modify_fixed_pump_pattern=modify_fixed_pump_pattern, modify_variable_pump_pattern=modify_variable_pump_pattern, - scheme_Type="pressure_regulation", + scheme_type="pressure_regulation", scheme_name=scheme_name, ) if is_project_open(new_name): diff --git a/app/api/v1/endpoints/data_query.py b/app/api/v1/endpoints/data_query.py index c16ad40..2413ca3 100644 --- a/app/api/v1/endpoints/data_query.py +++ b/app/api/v1/endpoints/data_query.py @@ -316,7 +316,7 @@ async def fastapi_query_all_scheme_all_records( return loaded_dict results = influxdb_api.query_scheme_all_record( - scheme_Type=schemetype, scheme_name=schemename, query_date=querydate + scheme_type=schemetype, scheme_name=schemename, query_date=querydate ) packed = msgpack.packb(results, default=encode_datetime) redis_client.set(cache_key, packed) @@ -334,7 +334,7 @@ async def fastapi_query_all_scheme_all_records_property( all_results = msgpack.unpackb(data, object_hook=decode_datetime) else: all_results = influxdb_api.query_scheme_all_record( - scheme_Type=schemetype, scheme_name=schemename, query_date=querydate + scheme_type=schemetype, scheme_name=schemename, query_date=querydate ) packed = msgpack.packb(all_results, default=encode_datetime) redis_client.set(cache_key, packed) diff --git a/app/infra/db/influxdb/api.py b/app/infra/db/influxdb/api.py index 1ea6663..84c036f 100644 --- a/app/infra/db/influxdb/api.py +++ b/app/infra/db/influxdb/api.py @@ -404,7 +404,7 @@ def create_and_initialize_buckets(org_name: str) -> None: Point("link") .tag("date", None) .tag("ID", None) - .tag("scheme_Type", None) + .tag("scheme_type", None) .tag("scheme_name", None) .field("flow", 0.0) .field("leakage", 0.0) @@ -420,7 +420,7 @@ def create_and_initialize_buckets(org_name: str) -> None: Point("node") .tag("date", None) .tag("ID", None) - .tag("scheme_Type", None) + .tag("scheme_type", None) .tag("scheme_name", None) .field("head", 0.0) .field("pressure", 0.0) @@ -436,7 +436,7 @@ def create_and_initialize_buckets(org_name: str) -> None: .tag("date", None) .tag("description", None) .tag("device_ID", None) - .tag("scheme_Type", None) + .tag("scheme_type", None) .tag("scheme_name", None) .field("monitored_value", 0.0) .field("datacleaning_value", 0.0) @@ -1811,7 +1811,7 @@ def query_SCADA_data_by_device_ID_and_time( def query_scheme_SCADA_data_by_device_ID_and_time( query_ids_list: List[str], query_time: str, - scheme_Type: str, + scheme_type: str, scheme_name: str, bucket: str = "scheme_simulation_result", ) -> Dict[str, float]: @@ -1843,7 +1843,7 @@ def query_scheme_SCADA_data_by_device_ID_and_time( 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"] == "monitored_value" and r["scheme_Type"] == "{scheme_Type}" and r["scheme_name"] == "{scheme_name}") + |> filter(fn: (r) => r["device_ID"] == "{device_id}" and r["_field"] == "monitored_value" and r["scheme_type"] == "{scheme_type}" and r["scheme_name"] == "{scheme_name}") """ # 执行查询 try: @@ -3227,7 +3227,7 @@ def store_scheme_simulation_result_to_influxdb( link_result_list: List[Dict[str, any]], scheme_start_time: str, num_periods: int = 1, - scheme_Type: str = None, + scheme_type: str = None, scheme_name: str = None, bucket: str = "scheme_simulation_result", ): @@ -3237,7 +3237,7 @@ def store_scheme_simulation_result_to_influxdb( :param link_result_list: (List[Dict[str, any]]): 包含连接和结果数据的字典列表。 :param scheme_start_time: (str): 方案模拟开始时间。 :param num_periods: (int): 方案模拟的周期数 - :param scheme_Type: (str): 方案类型 + :param scheme_type: (str): 方案类型 :param scheme_name: (str): 方案名称 :param bucket: (str): InfluxDB 的 bucket 名称，默认值为 "scheme_simulation_result"。 :return: @@ -3298,7 +3298,7 @@ def store_scheme_simulation_result_to_influxdb( Point("node") .tag("date", date_str) .tag("ID", node_id) - .tag("scheme_Type", scheme_Type) + .tag("scheme_type", scheme_type) .tag("scheme_name", scheme_name) .field("head", data.get("head", 0.0)) .field("pressure", data.get("pressure", 0.0)) @@ -3322,7 +3322,7 @@ def store_scheme_simulation_result_to_influxdb( Point("link") .tag("date", date_str) .tag("ID", link_id) - .tag("scheme_Type", scheme_Type) + .tag("scheme_type", scheme_type) .tag("scheme_name", scheme_name) .field("flow", data.get("flow", 0.0)) .field("velocity", data.get("velocity", 0.0)) @@ -3409,13 +3409,13 @@ def query_corresponding_query_id_and_element_id(name: str) -> None: # 2025/03/11 def fill_scheme_simulation_result_to_SCADA( - scheme_Type: str = None, + scheme_type: str = None, scheme_name: str = None, query_date: str = None, bucket: str = "scheme_simulation_result", ): """ - :param scheme_Type: 方案类型 + :param scheme_type: 方案类型 :param scheme_name: 方案名称 :param query_date: 查询日期，格式为 'YYYY-MM-DD' :param bucket: InfluxDB 的 bucket 名称，默认值为 "scheme_simulation_result" @@ -3457,7 +3457,7 @@ def fill_scheme_simulation_result_to_SCADA( # 查找associated_element_id的对应值 for key, value in globals.scheme_source_outflow_ids.items(): scheme_source_outflow_result = query_scheme_curve_by_ID_property( - scheme_Type=scheme_Type, + scheme_type=scheme_type, scheme_name=scheme_name, query_date=query_date, ID=value, @@ -3470,7 +3470,7 @@ def fill_scheme_simulation_result_to_SCADA( Point("scheme_source_outflow") .tag("date", query_date) .tag("device_ID", key) - .tag("scheme_Type", scheme_Type) + .tag("scheme_type", scheme_type) .tag("scheme_name", scheme_name) .field("monitored_value", data["value"]) .time(data["time"], write_precision="s") @@ -3480,7 +3480,7 @@ def fill_scheme_simulation_result_to_SCADA( for key, value in globals.scheme_pipe_flow_ids.items(): scheme_pipe_flow_result = query_scheme_curve_by_ID_property( - scheme_Type=scheme_Type, + scheme_type=scheme_type, scheme_name=scheme_name, query_date=query_date, ID=value, @@ -3492,7 +3492,7 @@ def fill_scheme_simulation_result_to_SCADA( Point("scheme_pipe_flow") .tag("date", query_date) .tag("device_ID", key) - .tag("scheme_Type", scheme_Type) + .tag("scheme_type", scheme_type) .tag("scheme_name", scheme_name) .field("monitored_value", data["value"]) .time(data["time"], write_precision="s") @@ -3502,7 +3502,7 @@ def fill_scheme_simulation_result_to_SCADA( for key, value in globals.scheme_pressure_ids.items(): scheme_pressure_result = query_scheme_curve_by_ID_property( - scheme_Type=scheme_Type, + scheme_type=scheme_type, scheme_name=scheme_name, query_date=query_date, ID=value, @@ -3514,7 +3514,7 @@ def fill_scheme_simulation_result_to_SCADA( Point("scheme_pressure") .tag("date", query_date) .tag("device_ID", key) - .tag("scheme_Type", scheme_Type) + .tag("scheme_type", scheme_type) .tag("scheme_name", scheme_name) .field("monitored_value", data["value"]) .time(data["time"], write_precision="s") @@ -3524,7 +3524,7 @@ def fill_scheme_simulation_result_to_SCADA( for key, value in globals.scheme_demand_ids.items(): scheme_demand_result = query_scheme_curve_by_ID_property( - scheme_Type=scheme_Type, + scheme_type=scheme_type, scheme_name=scheme_name, query_date=query_date, ID=value, @@ -3536,7 +3536,7 @@ def fill_scheme_simulation_result_to_SCADA( Point("scheme_demand") .tag("date", query_date) .tag("device_ID", key) - .tag("scheme_Type", scheme_Type) + .tag("scheme_type", scheme_type) .tag("scheme_name", scheme_name) .field("monitored_value", data["value"]) .time(data["time"], write_precision="s") @@ -3546,7 +3546,7 @@ def fill_scheme_simulation_result_to_SCADA( for key, value in globals.scheme_quality_ids.items(): scheme_quality_result = query_scheme_curve_by_ID_property( - scheme_Type=scheme_Type, + scheme_type=scheme_type, scheme_name=scheme_name, query_date=query_date, ID=value, @@ -3558,7 +3558,7 @@ def fill_scheme_simulation_result_to_SCADA( Point("scheme_quality") .tag("date", query_date) .tag("device_ID", key) - .tag("scheme_Type", scheme_Type) + .tag("scheme_type", scheme_type) .tag("scheme_name", scheme_name) .field("monitored_value", data["value"]) .time(data["time"], write_precision="s") @@ -3629,14 +3629,14 @@ def query_SCADA_data_curve( # 2025/02/18 def query_scheme_all_record_by_time( - scheme_Type: str, + scheme_type: str, scheme_name: str, query_time: str, bucket: str = "scheme_simulation_result", ) -> tuple: """ 查询指定方案某一时刻的所有记录，包括‘node'和‘link’，分别以指定格式返回。 - :param scheme_Type: 方案类型 + :param scheme_type: 方案类型 :param scheme_name: 方案名称 :param query_time: 输入的北京时间，格式为 '2024-11-24T17:30:00+08:00'。 :param bucket: 数据存储的 bucket 名称。 @@ -3660,7 +3660,7 @@ def query_scheme_all_record_by_time( flux_query = f""" from(bucket: "{bucket}") |> range(start: {utc_start_time.isoformat()}, stop: {utc_stop_time.isoformat()}) - |> filter(fn: (r) => r["scheme_Type"] == "{scheme_Type}" and r["scheme_name"] == "{scheme_name}" and r["_measurement"] == "node" or r["_measurement"] == "link") + |> filter(fn: (r) => r["scheme_type"] == "{scheme_type}" and r["scheme_name"] == "{scheme_name}" and r["_measurement"] == "node" or r["_measurement"] == "link") |> pivot( rowKey:["_time"], columnKey:["_field"], @@ -3710,7 +3710,7 @@ def query_scheme_all_record_by_time( # 2025/03/04 def query_scheme_all_record_by_time_property( - scheme_Type: str, + scheme_type: str, scheme_name: str, query_time: str, type: str, @@ -3719,7 +3719,7 @@ def query_scheme_all_record_by_time_property( ) -> list: """ 查询指定方案某一时刻‘node'或‘link’某一属性值，以指定格式返回。 - :param scheme_Type: 方案类型 + :param scheme_type: 方案类型 :param scheme_name: 方案名称 :param query_time: 输入的北京时间，格式为 '2024-11-24T17:30:00+08:00'。 :param type: 查询的类型（决定 measurement） @@ -3752,7 +3752,7 @@ def query_scheme_all_record_by_time_property( flux_query = f""" from(bucket: "{bucket}") |> range(start: {utc_start_time.isoformat()}, stop: {utc_stop_time.isoformat()}) - |> filter(fn: (r) => r["scheme_Type"] == "{scheme_Type}" and r["scheme_name"] == "{scheme_name}" and r["_measurement"] == "{measurement}" and r["_field"] == "{property}") + |> filter(fn: (r) => r["scheme_type"] == "{scheme_type}" and r["scheme_name"] == "{scheme_name}" and r["_measurement"] == "{measurement}" and r["_field"] == "{property}") """ # 执行查询 tables = query_api.query(flux_query) @@ -3767,7 +3767,7 @@ def query_scheme_all_record_by_time_property( # 2025/02/19 def query_scheme_curve_by_ID_property( - scheme_Type: str, + scheme_type: str, scheme_name: str, query_date: str, ID: str, @@ -3777,7 +3777,7 @@ def query_scheme_curve_by_ID_property( ) -> list: """ 根据scheme_Type和scheme_name,查询该模拟方案中，某一node或link的某一属性值的所有时间的结果 - :param scheme_Type: 方案类型 + :param scheme_type: 方案类型 :param scheme_name: 方案名称 :param query_date: 查询日期，格式为 'YYYY-MM-DD' :param ID: 元素的ID @@ -3817,7 +3817,7 @@ def query_scheme_curve_by_ID_property( flux_query = f""" from(bucket: "{bucket}") |> range(start: {start_time}, stop: {stop_time}) - |> filter(fn: (r) => r["_measurement"] == "{measurement}" and r["scheme_Type"] == "{scheme_Type}" and r["scheme_name"] == "{scheme_name}" and r["ID"] == "{ID}" and r["_field"] == "{property}") + |> filter(fn: (r) => r["_measurement"] == "{measurement}" and r["scheme_type"] == "{scheme_type}" and r["scheme_name"] == "{scheme_name}" and r["ID"] == "{ID}" and r["_field"] == "{property}") """ # 执行查询 tables = query_api.query(flux_query) @@ -3832,14 +3832,14 @@ def query_scheme_curve_by_ID_property( # 2025/02/21 def query_scheme_all_record( - scheme_Type: str, + scheme_type: str, scheme_name: str, query_date: str, bucket: str = "scheme_simulation_result", ) -> tuple: """ 查询指定方案的所有记录，包括‘node'和‘link’，分别以指定格式返回。 - :param scheme_Type: 方案类型 + :param scheme_type: 方案类型 :param scheme_name: 方案名称 :param query_date: 查询日期，格式为 'YYYY-MM-DD' :param bucket: 数据存储的 bucket 名称。 @@ -3867,7 +3867,7 @@ def query_scheme_all_record( flux_query = f""" from(bucket: "{bucket}") |> range(start: {utc_start_time.isoformat()}, stop: {utc_stop_time.isoformat()}) - |> filter(fn: (r) => r["scheme_Type"] == "{scheme_Type}" and r["scheme_name"] == "{scheme_name}" and r["_measurement"] == "node" or r["_measurement"] == "link") + |> filter(fn: (r) => r["scheme_type"] == "{scheme_type}" and r["scheme_name"] == "{scheme_name}" and r["_measurement"] == "node" or r["_measurement"] == "link") |> pivot( rowKey:["_time"], columnKey:["_field"], @@ -3917,7 +3917,7 @@ def query_scheme_all_record( # 2025/03/04 def query_scheme_all_record_property( - scheme_Type: str, + scheme_type: str, scheme_name: str, query_date: str, type: str, @@ -3926,7 +3926,7 @@ def query_scheme_all_record_property( ) -> list: """ 查询指定方案的‘node'或‘link’的某一属性值，以指定格式返回。 - :param scheme_Type: 方案类型 + :param scheme_type: 方案类型 :param scheme_name: 方案名称 :param query_date: 查询日期，格式为 'YYYY-MM-DD' :param type: 查询的类型（决定 measurement） @@ -3964,7 +3964,7 @@ def query_scheme_all_record_property( flux_query = f""" from(bucket: "{bucket}") |> range(start: {start_time}, stop: {stop_time}) - |> filter(fn: (r) => r["scheme_Type"] == "{scheme_Type}" and r["scheme_name"] == "{scheme_name}" and r["date"] == "{query_date}" and r["_measurement"] == "{measurement}" and r["_field"] == "{property}") + |> filter(fn: (r) => r["scheme_type"] == "{scheme_type}" and r["scheme_name"] == "{scheme_name}" and r["date"] == "{query_date}" and r["_measurement"] == "{measurement}" and r["_field"] == "{property}") """ # 执行查询 tables = query_api.query(flux_query) @@ -4245,7 +4245,7 @@ def export_scheme_simulation_result_to_csv_time( link_data[key][field] = record.get_value() link_data[key]["measurement"] = record.get_measurement() link_data[key]["date"] = record.values.get("date", None) - link_data[key]["scheme_Type"] = record.values.get("scheme_Type", None) + link_data[key]["scheme_type"] = record.values.get("scheme_type", None) link_data[key]["scheme_name"] = record.values.get("scheme_name", None) # 构建 Flux 查询语句，查询指定时间范围内的数据 flux_query_node = f""" @@ -4267,7 +4267,7 @@ def export_scheme_simulation_result_to_csv_time( node_data[key][field] = record.get_value() node_data[key]["measurement"] = record.get_measurement() node_data[key]["date"] = record.values.get("date", None) - node_data[key]["scheme_Type"] = record.values.get("scheme_Type", None) + node_data[key]["scheme_type"] = record.values.get("scheme_type", None) node_data[key]["scheme_name"] = record.values.get("scheme_name", None) for key in set(link_data.keys()): row = {"time": key[0], "ID": key[1]} @@ -4288,7 +4288,7 @@ def export_scheme_simulation_result_to_csv_time( "time", "measurement", "date", - "scheme_Type", + "scheme_type", "scheme_name", "ID", "flow", @@ -4311,7 +4311,7 @@ def export_scheme_simulation_result_to_csv_time( "time", "measurement", "date", - "scheme_Type", + "scheme_type", "scheme_name", "ID", "head", @@ -4330,14 +4330,14 @@ def export_scheme_simulation_result_to_csv_time( # 2025/02/18 def export_scheme_simulation_result_to_csv_scheme( - scheme_Type: str, + scheme_type: str, scheme_name: str, query_date: str, bucket: str = "scheme_simulation_result", ) -> None: """ 导出influxdb中scheme_simulation_result这个bucket的数据到csv中 - :param scheme_Type: 查询的方案类型 + :param scheme_type: 查询的方案类型 :param scheme_name: 查询的方案名 :param query_date: 查询日期，格式为 'YYYY-MM-DD' :param bucket: 数据存储的 bucket 名称，默认值为 "SCADA_data" @@ -4366,7 +4366,7 @@ def export_scheme_simulation_result_to_csv_scheme( flux_query_link = f""" from(bucket: "{bucket}") |> range(start: {start_time}, stop: {stop_time}) - |> filter(fn: (r) => r["_measurement"] == "link" and r["scheme_Type"] == "{scheme_Type}" and r["scheme_name"] == "{scheme_name}") + |> filter(fn: (r) => r["_measurement"] == "link" and r["scheme_type"] == "{scheme_type}" and r["scheme_name"] == "{scheme_name}") """ # 执行查询 link_tables = query_api.query(flux_query_link) @@ -4382,13 +4382,13 @@ def export_scheme_simulation_result_to_csv_scheme( link_data[key][field] = record.get_value() link_data[key]["measurement"] = record.get_measurement() link_data[key]["date"] = record.values.get("date", None) - link_data[key]["scheme_Type"] = record.values.get("scheme_Type", None) + link_data[key]["scheme_type"] = record.values.get("scheme_type", None) link_data[key]["scheme_name"] = record.values.get("scheme_name", None) # 构建 Flux 查询语句，查询指定时间范围内的数据 flux_query_node = f""" from(bucket: "{bucket}") |> range(start: {start_time}, stop: {stop_time}) - |> filter(fn: (r) => r["_measurement"] == "node" and r["scheme_Type"] == "{scheme_Type}" and r["scheme_name"] == "{scheme_name}") + |> filter(fn: (r) => r["_measurement"] == "node" and r["scheme_type"] == "{scheme_type}" and r["scheme_name"] == "{scheme_name}") """ # 执行查询 node_tables = query_api.query(flux_query_node) @@ -4404,7 +4404,7 @@ def export_scheme_simulation_result_to_csv_scheme( node_data[key][field] = record.get_value() node_data[key]["measurement"] = record.get_measurement() node_data[key]["date"] = record.values.get("date", None) - node_data[key]["scheme_Type"] = record.values.get("scheme_Type", None) + node_data[key]["scheme_type"] = record.values.get("scheme_type", None) node_data[key]["scheme_name"] = record.values.get("scheme_name", None) for key in set(link_data.keys()): row = {"time": key[0], "ID": key[1]} @@ -4416,10 +4416,10 @@ def export_scheme_simulation_result_to_csv_scheme( node_rows.append(row) # 动态生成 CSV 文件名 csv_filename_link = ( - f"scheme_simulation_link_result_{scheme_name}_of_{scheme_Type}.csv" + f"scheme_simulation_link_result_{scheme_name}_of_{scheme_type}.csv" ) csv_filename_node = ( - f"scheme_simulation_node_result_{scheme_name}_of_{scheme_Type}.csv" + f"scheme_simulation_node_result_{scheme_name}_of_{scheme_type}.csv" ) # 写入到 CSV 文件 with open(csv_filename_link, mode="w", newline="") as file: @@ -4429,7 +4429,7 @@ def export_scheme_simulation_result_to_csv_scheme( "time", "measurement", "date", - "scheme_Type", + "scheme_type", "scheme_name", "ID", "flow", @@ -4452,7 +4452,7 @@ def export_scheme_simulation_result_to_csv_scheme( "time", "measurement", "date", - "scheme_Type", + "scheme_type", "scheme_name", "ID", "head", @@ -4878,15 +4878,15 @@ if __name__ == "__main__": # export_scheme_simulation_result_to_csv_time(start_date='2025-02-13', end_date='2025-02-15') # 示例9：export_scheme_simulation_result_to_csv_scheme - # export_scheme_simulation_result_to_csv_scheme(scheme_Type='burst_Analysis', scheme_name='scheme1', query_date='2025-03-10') + # export_scheme_simulation_result_to_csv_scheme(scheme_type='burst_Analysis', scheme_name='scheme1', query_date='2025-03-10') # 示例10：query_scheme_all_record_by_time - # node_records, link_records = query_scheme_all_record_by_time(scheme_Type='burst_Analysis', scheme_name='scheme1', query_time="2025-02-14T10:30:00+08:00") + # node_records, link_records = query_scheme_all_record_by_time(scheme_type='burst_Analysis', scheme_name='scheme1', query_time="2025-02-14T10:30:00+08:00") # print("Node 数据：", node_records) # print("Link 数据：", link_records) # 示例11：query_scheme_curve_by_ID_property - # curve_result = query_scheme_curve_by_ID_property(scheme_Type='burst_Analysis', scheme_name='scheme1', ID='ZBBDTZDP000022', + # curve_result = query_scheme_curve_by_ID_property(scheme_type='burst_Analysis', scheme_name='scheme1', ID='ZBBDTZDP000022', # type='node', property='head') # print(curve_result) @@ -4896,7 +4896,7 @@ if __name__ == "__main__": # print("Link 数据：", link_records) # 示例13：query_scheme_all_record - # node_records, link_records = query_scheme_all_record(scheme_Type='burst_Analysis', scheme_name='scheme1', query_date='2025-03-10') + # node_records, link_records = query_scheme_all_record(scheme_type='burst_Analysis', scheme_name='scheme1', query_date='2025-03-10') # print("Node 数据：", node_records) # print("Link 数据：", link_records) @@ -4909,16 +4909,16 @@ if __name__ == "__main__": # print(result_records) # 示例16：query_scheme_all_record_by_time_property - # result_records = query_scheme_all_record_by_time_property(scheme_Type='burst_Analysis', scheme_name='scheme1', + # result_records = query_scheme_all_record_by_time_property(scheme_type='burst_Analysis', scheme_name='scheme1', # query_time='2025-02-14T10:30:00+08:00', type='node', property='head') # print(result_records) # 示例17：query_scheme_all_record_property - # result_records = query_scheme_all_record_property(scheme_Type='burst_Analysis', scheme_name='scheme1', query_date='2025-03-10', type='node', property='head') + # result_records = query_scheme_all_record_property(scheme_type='burst_Analysis', scheme_name='scheme1', query_date='2025-03-10', type='node', property='head') # print(result_records) # 示例18：fill_scheme_simulation_result_to_SCADA - # fill_scheme_simulation_result_to_SCADA(scheme_Type='burst_Analysis', scheme_name='burst0330', query_date='2025-03-30') + # fill_scheme_simulation_result_to_SCADA(scheme_type='burst_Analysis', scheme_name='burst0330', query_date='2025-03-30') # 示例19：query_SCADA_data_by_device_ID_and_timerange # result = query_SCADA_data_by_device_ID_and_timerange(query_ids_list=globals.pressure_non_realtime_ids, start_time='2025-04-16T00:00:00+08:00', @@ -4926,7 +4926,7 @@ if __name__ == "__main__": # print(result) # 示例：manually_get_burst_flow - # leakage = manually_get_burst_flow(scheme_Type='burst_Analysis', scheme_name='burst_scheme', scheme_start_time='2025-03-10T12:00:00+08:00') + # leakage = manually_get_burst_flow(scheme_type='burst_Analysis', scheme_name='burst_scheme', scheme_start_time='2025-03-10T12:00:00+08:00') # print(leakage) # 示例：upload_cleaned_SCADA_data_to_influxdb diff --git a/app/services/simulation.py b/app/services/simulation.py index 0bc891c..ec651e3 100644 --- a/app/services/simulation.py +++ b/app/services/simulation.py @@ -1249,7 +1249,7 @@ def run_simulation( endtime = time.time() logging.info("store time: %f", endtime - starttime) # 暂不需要再次存储 SCADA 模拟信息 - # TimescaleInternalQueries.fill_scheme_simulation_result_to_SCADA(scheme_Type=scheme_Type, scheme_name=scheme_name) + # TimescaleInternalQueries.fill_scheme_simulation_result_to_SCADA(scheme_type=scheme_type, scheme_name=scheme_name) # if simulation_type.upper() == "REALTIME": # influxdb_api.store_realtime_simulation_result_to_influxdb( @@ -1261,11 +1261,11 @@ def run_simulation( # link_result, # modify_pattern_start_time, # num_periods_result, - # scheme_Type, + # scheme_type, # scheme_name, # ) # 暂不需要再次存储 SCADA 模拟信息 - # influxdb_api.fill_scheme_simulation_result_to_SCADA(scheme_Type=scheme_Type, scheme_name=scheme_name) + # influxdb_api.fill_scheme_simulation_result_to_SCADA(scheme_type=scheme_type, scheme_name=scheme_name) print("after store result") @@ -1345,7 +1345,7 @@ if __name__ == "__main__": # run_simulation(name='bb', simulation_type="realtime", modify_pattern_start_time='2025-02-25T23:45:00+08:00') # 模拟示例2 # run_simulation(name='bb', simulation_type="extended", modify_pattern_start_time='2025-03-10T12:00:00+08:00', - # modify_total_duration=1800, scheme_Type="burst_Analysis", scheme_name="scheme1") + # modify_total_duration=1800, scheme_type="burst_Analysis", scheme_name="scheme1") # 查询示例1：query_SCADA_ID_corresponding_info # result = query_SCADA_ID_corresponding_info(name='bb', SCADA_ID='P10755') diff --git a/scripts/main.py b/scripts/main.py index 4a71ed8..77ec41e 100644 --- a/scripts/main.py +++ b/scripts/main.py @@ -3233,7 +3233,7 @@ async def fastapi_query_all_scheme_all_records( return loaded_dict results = influxdb_api.query_scheme_all_record( - scheme_Type=schemetype, scheme_name=schemename, query_date=querydate + scheme_type=schemetype, scheme_name=schemename, query_date=querydate ) packed = msgpack.packb(results, default=encode_datetime) redis_client.set(cache_key, packed) @@ -3257,7 +3257,7 @@ async def fastapi_query_all_scheme_all_records_property( all_results = msgpack.unpackb(data, object_hook=decode_datetime) else: all_results = influxdb_api.query_scheme_all_record( - scheme_Type=schemetype, scheme_name=schemename, query_date=querydate + scheme_type=schemetype, scheme_name=schemename, query_date=querydate ) packed = msgpack.packb(all_results, default=encode_datetime) redis_client.set(cache_key, packed) diff --git a/scripts/online_Analysis.py b/scripts/online_Analysis.py index d3e1dbf..a1aed4f 100644 --- a/scripts/online_Analysis.py +++ b/scripts/online_Analysis.py @@ -396,7 +396,7 @@ def flushing_analysis( modify_pattern_start_time=modify_pattern_start_time, modify_total_duration=modify_total_duration, modify_valve_opening=modify_valve_opening, - scheme_Type="flushing_Analysis", + scheme_type="flushing_Analysis", scheme_name=scheme_name, ) # step 4. restore the base model @@ -533,7 +533,7 @@ def contaminant_simulation( simulation_type="extended", modify_pattern_start_time=modify_pattern_start_time, modify_total_duration=modify_total_duration, - scheme_Type="contaminant_Analysis", + scheme_type="contaminant_Analysis", scheme_name=scheme_name, ) @@ -692,7 +692,7 @@ def pressure_regulation( modify_tank_initial_level=modify_tank_initial_level, modify_fixed_pump_pattern=modify_fixed_pump_pattern, modify_variable_pump_pattern=modify_variable_pump_pattern, - scheme_Type="pressure_regulation", + scheme_type="pressure_regulation", scheme_name=scheme_name, ) if is_project_open(new_name):