adding TRX database

README.md

@@ -40,6 +40,7 @@ You can access the hosted version of the app at [https://davmelchi-db-query.hf.s
 - [x] Add page to update physical db
 - [x] Add Core dump checking App
 - [x] Add site config band in database
+- [x] Add TRX database
 - [ ] Add dashboards for each database (Count of NE)
 - [ ] Add the ability to select columns
 - [ ] Error handling

apps/database_page.py

@@ -9,6 +9,7 @@ from queries.process_neighbors import (
     process_neighbors_data,
     process_neighbors_data_to_excel,
 )
+from queries.process_trx import process_trx_with_bts_name_data_to_excel
 from queries.process_wcdma import process_wcdma_data_to_excel
 from utils.check_sheet_exist import Technology, execute_checks_sheets_exist
 from utils.utils_vars import UtilsVars
@@ -46,6 +47,9 @@ def download_button(database_type):
     elif database_type == "NEI":
         data = UtilsVars.neighbors_database
         file_name = f"Neighbors database_{time.time()}.xlsx"
+    elif database_type == "TRX":
+        data = UtilsVars.final_trx_database
+        file_name = f"TRX database_{time.time()}.xlsx"
     st.download_button(
         type="primary",
         label=f"Download {database_type} Database File",
@@ -76,6 +80,8 @@ if uploaded_file is not None:
             Technology.gsm == False
             and Technology.wcdma == False
             and Technology.lte == False
+            and Technology.neighbors == False
+            and Technology.trx == False
         ):
             st.error(
                 """
@@ -84,6 +90,7 @@ if uploaded_file is not None:
                     "wcdma": ["WCEL", "WBTS", "WNCEL"],
                     "lte": ["LNBTS", "LNCEL", "LNCEL_FDD", "LNCEL_TDD"],
                     "neighbors": ["ADCE", "ADJS", "ADJI", "ADJG", "ADJW", "BTS", "WCEL"],
+                    "trx": ["TRX", "BTS"],
                 """
             )
 
@@ -122,6 +129,14 @@ if uploaded_file is not None:
                     ),
                     # on_click=lambda: process_neighbors_data(uploaded_file),
                 )
+        if Technology.trx == True:
+            with col6:
+                st.button(
+                    "Generate TRX DB",
+                    on_click=lambda: process_database(
+                        process_trx_with_bts_name_data_to_excel, "TRX"
+                    ),
+                )
 
     except Exception as e:
         st.error(f"Error: {e}")

queries/process_all_db.py

@@ -1,5 +1,6 @@
 from queries.process_gsm import process_gsm_data
 from queries.process_lte import process_lte_data
+from queries.process_trx import trx_with_bts_name
 from queries.process_wcdma import process_wcdma_data
 from utils.convert_to_excel import convert_dfs
 from utils.utils_vars import UtilsVars
@@ -10,7 +11,8 @@ def process_all_tech_db(filepath: str):
     process_gsm_data(filepath)
     process_wcdma_data(filepath)
     process_lte_data(filepath)
+    trx_with_bts_name(filepath)
 
     UtilsVars.final_all_database = convert_dfs(
-        UtilsVars.all_db_dfs, ["GSM", "WCDMA", "LTE_FDD", "LTE_TDD"]
+        UtilsVars.all_db_dfs, ["GSM", "WCDMA", "LTE_FDD", "LTE_TDD", "TRX"]
     )

queries/process_gsm.py

@@ -63,7 +63,7 @@ def process_gsm_data(file_path: str):
     # Read the specific sheet into a DataFrame
     dfs = pd.read_excel(
         file_path,
-        sheet_name=["BTS", "BCF", "TRX"],
+        sheet_name=["BTS", "BCF"],
         engine="calamine",
         skiprows=[0],
     )
@@ -112,6 +112,7 @@ def process_gsm_data(file_path: str):
     df_bcf.rename(columns={"name": "site_name"}, inplace=True)
     df_bcf = df_bcf[BCF_COLUMNS]
 
+    # Process TRX data
     df_trx = process_trx_data(file_path)
 
     # create band dataframe

queries/process_trx.py

@@ -13,7 +13,52 @@ TRX_COLUMNS = [
 ]
 
 
-def process_trx_data(file_path: str):
+TRX_BTS_COLUMNS = [
+    "BSC",
+    "BCF",
+    "BTS",
+    "TRX",
+    "ID_BTS",
+    "number_trx_per_cell",
+    "number_trx_per_site",
+    "code",
+    "name",
+    "adminState",
+    "bbUnitSupportsEdge",
+    "channel0Maio",
+    "channel0Type",
+    "channel1Maio",
+    "channel1Type",
+    "channel2Maio",
+    "channel2Type",
+    "channel3Maio",
+    "channel3Type",
+    "channel4Maio",
+    "channel4Type",
+    "channel5Maio",
+    "channel5Type",
+    "channel6Maio",
+    "channel6Type",
+    "channel7Maio",
+    "channel7Type",
+    "initialFrequency",
+    "lapdLinkName",
+    "lapdLinkNumber",
+    "mcpaTrxNumber",
+    "mcpaTrxPortId",
+    "mcpaTrxPosition",
+    "numberOfTrxRfPowerLevels",
+    "optimumRxLevDL",
+    "optimumRxLevUL",
+    "preferredBcchMark",
+    "trxAbilities",
+    "trxFrequencyType",
+    "trxRfPower",
+    "tsc",
+]
+
+
+def process_brute_trx_data(file_path: str):
     """
     Process data from the specified file path.
 
@@ -23,7 +68,7 @@ def process_trx_data(file_path: str):
     # Read the specific sheet into a DataFrame
     dfs = pd.read_excel(
         file_path,
-        sheet_name=["BTS", "BCF", "TRX"],
+        sheet_name=["TRX"],
         engine="calamine",
         skiprows=[0],
     )
@@ -40,8 +85,15 @@ def process_trx_data(file_path: str):
         "count"
     )
 
-    bcch = df_trx[df_trx["channel0Type"] == 4]
-    tch = df_trx[df_trx["channel0Type"] == 3][["ID_BTS", "initialFrequency"]]
+    return df_trx
+
+
+def process_trx_data(file_path: str):
+
+    df_gsm_trx = process_brute_trx_data(file_path=file_path).copy()
+
+    bcch = df_gsm_trx[df_gsm_trx["channel0Type"] == 4]
+    tch = df_gsm_trx[df_gsm_trx["channel0Type"] == 3][["ID_BTS", "initialFrequency"]]
 
     tch = tch.pivot_table(
         index="ID_BTS",
@@ -54,19 +106,46 @@ def process_trx_data(file_path: str):
     # rename the columns
     tch.columns = ["ID_BTS", "TCH"]
 
-    # Merge dataframes
-
-    df_trx = pd.merge(bcch, tch, on="ID_BTS", how="left")
+    df_gsm_trx = pd.merge(bcch, tch, on="ID_BTS", how="left")
     # rename "initialFrequency" to "BCCH"
-    df_trx = df_trx.rename(columns={"initialFrequency": "BCCH"})
-    df_trx = df_trx[TRX_COLUMNS]
+    df_gsm_trx = df_gsm_trx.rename(columns={"initialFrequency": "BCCH"})
+    df_gsm_trx = df_gsm_trx[TRX_COLUMNS]
 
-    # Save dataframes
-    # save_dataframe(df_trx, "trx")
-    # df_2g2 = save_dataframe(df_2g, "2g")
+    return df_gsm_trx
 
-    # UtilsVars.final_gsm_database = convert_dfs([df_2g], ["GSM"])
-    return df_trx
 
+def trx_with_bts_name(file_path: str):
+
+    df_gsm_trx = process_brute_trx_data(file_path=file_path).copy()
+    df_gsm_trx.drop(["name"], axis=1, inplace=True)
 
-# process_trx_data(r"data2\20240805_5810_05082024_Dump.xml.gz.xlsb")
+    # Process TRX data
+    dfs = pd.read_excel(
+        file_path,
+        sheet_name=["BTS"],
+        engine="calamine",
+        skiprows=[0],
+    )
+    df_bts = dfs["BTS"]
+    df_bts.columns = df_bts.columns.str.replace(r"[ ]", "", regex=True)
+    df_bts["code"] = df_bts["name"].str.split("_").str[0].astype(int)
+    df_bts["ID_BTS"] = df_bts[["BSC", "BCF", "BTS"]].astype(str).apply("_".join, axis=1)
+    df_bts = df_bts[["ID_BTS", "code", "name"]]
+
+    df_trx_bts_name = pd.merge(df_gsm_trx, df_bts, on="ID_BTS", how="left")
+    df_trx_bts_name = df_trx_bts_name[TRX_BTS_COLUMNS]
+
+    UtilsVars.all_db_dfs.append(df_trx_bts_name)
+
+    return df_trx_bts_name
+
+
+def process_trx_with_bts_name_data_to_excel(file_path: str):
+    """
+    Process data from the specified file path and save it to a excel file.
+
+    Args:
+        file_path (str): The path to the file.
+    """
+    trx_bts_name = trx_with_bts_name(file_path)
+    UtilsVars.final_trx_database = convert_dfs([trx_bts_name], ["TRX"])

utils/check_sheet_exist.py

@@ -6,6 +6,7 @@ class Technology:
     wcdma = False
     lte = False
     neighbors = False
+    trx = False
 
 
 # Dictionary of sheet groups to check
@@ -14,6 +15,7 @@ sheets_to_check = {
     "neighbors": ["ADCE", "ADJS", "ADJI", "ADJG", "ADJW", "BTS", "WCEL"],
     "wcdma": ["WCEL", "WBTS", "WNCEL"],
     "lte": ["LNBTS", "LNCEL", "LNCEL_FDD", "LNCEL_TDD"],
+    "trx": ["TRX", "BTS"],
 }
 
 

utils/utils_vars.py

@@ -40,6 +40,7 @@ class UtilsVars:
     final_lte_database = ""
     final_gsm_database = ""
     final_wcdma_database = ""
+    final_trx_database = ""
     all_db_dfs = []
     final_all_database = ""
     neighbors_database = ""