fix GD

lista_gd.txt

@@ -0,0 +1 @@
+select count(id) from RAWDATACOR where date(created_at) = '2025-07-27' and concat(UnitName,ToolNameID) in ('ID0005_DT0000','ID0005_DT0036','ID0005_DT0037','ID0005_DT0038','ID0005_DT0039','ID0005_DT0040','ID0005_DT0041','ID0005_DT0042','ID0005_DT0043','ID0006_DT0044','ID0006_DT0045','ID0006_DT0046','ID0006_DT0047','ID0006_DT0048','ID0006_DT0049','ID0007_DT0050','ID0007_DT0051','ID0007_DT0052','ID0007_DT0053','ID0010_DT0054','ID0010_DT0055','ID0012_DT0001','ID0012_DT0102','ID0012_DT0103','ID0012_DT0104','ID0013_DT0001','ID0034_DT0002','ID0039_DT0001','ID0039_DT0002','ID0039_DT0003','ID0039_DT0004','ID0039_DT0005','ID0039_DT0006','ID0039_DT0007','ID0039_DT0008','ID0190_DT0001','ID0190_DT0002','ID0190_DT0003','ID0190_DT0004','ID0190_DT0005','ID0198_DT0229','ID0198_DT0230','ID0199_DT0010','ID0215_DT0234','ID0215_DT0235','ID0215_DT0236','ID0215_DT0237','ID0226_DT0000','ID0226_DT0239','ID0226_DT0240','ID0226_DT0241','ID0226_DT0242','ID0226_DT0243','ID0226_DT0244','ID0226_DT0245','ID0226_DT0246','ID0226_DT0247','ID0226_DT0248','ID0226_DT0249','ID0226_DT0250','ID0226_DT0251')

utils/csv/data_preparation.py

@@ -1,6 +1,7 @@
 #!.venv/bin/python
 from utils.database.nodes_query import get_nodes_type
 from utils.timestamp.date_check import normalizza_data, normalizza_orario
+from utils.database.loader_action import find_nearest_timestamp
 import logging
 import re
 
@@ -224,8 +225,11 @@ async def make_gd_matrix(cfg: object, id: int, pool: object) -> list:
             unit_metrics, data = rilevazioni.split(';|;')
             batlevel, temperature = unit_metrics.split(';')
             #logger.debug(f"GD id {id}: {EventDate}, {EventTime}, {batlevel}, {temperature}, {data}")
+
+            dt_timestamp, dt_batlevel, dt_temperature = await find_nearest_timestamp(cfg, {"timestamp": f"{normalizza_data(EventDate)} {normalizza_orario(EventTime)}", "unit": UnitName, "tool": ToolNameID.replace("GD", "DT"), "node_num": 1}, pool)
+            EventDate, EventTime = dt_timestamp.strftime('%Y-%m-%d %H:%M:%S').split(' ')
             valori = data.split(';')
-            matrice_valori.append([UnitName, ToolNameID.replace("GD", "DT"), 2, normalizza_data(EventDate), normalizza_orario(EventTime), batlevel, temperature] + valori + ([None] * (19 - len(valori))))
+            matrice_valori.append([UnitName, ToolNameID.replace("GD", "DT"), 2, EventDate, EventTime, float(dt_batlevel), float(dt_temperature)] + valori + ([None] * (16 - len(valori))) + [batlevel, temperature, None])
         else:
             logger.warning(f"GD id {id}: dati non trattati - {rilevazioni}")
 

utils/database/loader_action.py

@@ -3,6 +3,7 @@ import logging
 import asyncio
 
 from utils.database import FLAG_TO_TIMESTAMP, BATCH_SIZE
+from datetime import datetime, timedelta
 
 logger = logging.getLogger(__name__)
 
@@ -189,6 +190,43 @@ async def get_matlab_cmd(cfg: object, unit: str, tool: str, pool: object) -> tup
                             inner join units as u on u.id = t.unit_id
                             inner join statustools as s on t.statustool_id = s.id
                             where t.name = "{tool}" and u.name = "{unit}"''')
-                return cur.fetchone()
+                return await cur.fetchone()
+            except Exception as e:
+                logger.error(f"Error: {e}")
+
+async def find_nearest_timestamp(cfg: object, unit_tool_data: dict, pool: object) -> tuple:
+    """
+    Finds the nearest timestamp in the raw data table based on a reference timestamp
+    and unit/tool/node information.
+
+    Args:
+        cfg (object): Configuration object containing database table name (`cfg.dbrawdata`).
+        unit_tool_data (dict): A dictionary containing:
+            - "timestamp" (str): The reference timestamp string in "%Y-%m-%d %H:%M:%S" format.
+            - "unit" (str): The UnitName to filter by.
+            - "tool" (str): The ToolNameID to filter by.
+            - "node_num" (int): The NodeNum to filter by.
+        pool (object): The database connection pool.
+
+    Returns:
+        tuple: A tuple containing the event timestamp, BatLevel, and Temperature of the
+               nearest record, or None if an error occurs or no record is found.
+    """
+
+    ref_timestamp = datetime.strptime(unit_tool_data["timestamp"], "%Y-%m-%d %H:%M:%S")
+    start_timestamp = ref_timestamp - timedelta(seconds=45)
+    end_timestamp = ref_timestamp + timedelta(seconds=45)
+    logger.info(f"Find nearest timestamp: {ref_timestamp}")
+    async with pool.acquire() as conn:
+        async with conn.cursor() as cur:
+            try:
+                await cur.execute(f'''SELECT TIMESTAMP(`EventDate`, `EventTime`) AS event_timestamp, BatLevel, Temperature
+                                  FROM {cfg.dbrawdata}
+                                  WHERE UnitName = "{unit_tool_data["unit"]}" AND ToolNameID = "{unit_tool_data["tool"]}" AND NodeNum = {unit_tool_data["node_num"]}
+                                    AND TIMESTAMP(`EventDate`, `EventTime`) BETWEEN "{start_timestamp}" AND "{end_timestamp}"
+                                  ORDER BY ABS(TIMESTAMPDIFF(SECOND, TIMESTAMP(`EventDate`, `EventTime`), "{ref_timestamp}"))
+                                  LIMIT 1
+                                  ''')
+                return await cur.fetchone()
             except Exception as e:
                 logger.error(f"Error: {e}")