data/QUGS/convert.py

@@ -277,66 +277,66 @@ class DataProcessor:
                 )
 
 
-def create_damage_files(base_path, output_base, prefix):
-    # Initialize colorama
-    init(autoreset=True)
+# def create_damage_files(base_path, output_base, prefix):
+#     # Initialize colorama
+#     init(autoreset=True)
 
-    # Generate column labels based on expected duplication in input files
-    columns = ["Real"] + [
-        f"Real.{i}" for i in range(1, 30)
-    ]  # Explicitly setting column names
+#     # Generate column labels based on expected duplication in input files
+#     columns = ["Real"] + [
+#         f"Real.{i}" for i in range(1, 30)
+#     ]  # Explicitly setting column names
 
-    sensor_end_map = {
-        1: "Real.25",
-        2: "Real.26",
-        3: "Real.27",
-        4: "Real.28",
-        5: "Real.29",
-    }
+#     sensor_end_map = {
+#         1: "Real.25",
+#         2: "Real.26",
+#         3: "Real.27",
+#         4: "Real.28",
+#         5: "Real.29",
+#     }
 
-    # Define the damage scenarios and the corresponding original file indices
-    damage_scenarios = {
-        1: range(1, 6),  # Damage 1 files from zzzAD1.csv to zzzAD5.csv
-        2: range(6, 11),  # Damage 2 files from zzzAD6.csv to zzzAD10.csv
-        3: range(11, 16),  # Damage 3 files from zzzAD11.csv to zzzAD15.csvs
-        4: range(16, 21),  # Damage 4 files from zzzAD16.csv to zzzAD20.csv
-        5: range(21, 26),  # Damage 5 files from zzzAD21.csv to zzzAD25.csv
-        6: range(26, 31),  # Damage 6 files from zzzAD26.csv to zzzAD30.csv
-    }
-    damage_pad = len(str(len(damage_scenarios)))
-    test_pad = len(str(30))
+#     # Define the damage scenarios and the corresponding original file indices
+#     damage_scenarios = {
+#         1: range(1, 6),  # Damage 1 files from zzzAD1.csv to zzzAD5.csv
+#         2: range(6, 11),  # Damage 2 files from zzzAD6.csv to zzzAD10.csv
+#         3: range(11, 16),  # Damage 3 files from zzzAD11.csv to zzzAD15.csvs
+#         4: range(16, 21),  # Damage 4 files from zzzAD16.csv to zzzAD20.csv
+#         5: range(21, 26),  # Damage 5 files from zzzAD21.csv to zzzAD25.csv
+#         6: range(26, 31),  # Damage 6 files from zzzAD26.csv to zzzAD30.csv
+#     }
+#     damage_pad = len(str(len(damage_scenarios)))
+#     test_pad = len(str(30))
 
-    for damage, files in damage_scenarios.items():
-        for i, file_index in enumerate(files, start=1):
-            # Load original data file
-            file_path = os.path.join(base_path, f"zzz{prefix}D{file_index}.TXT")
-            df = pd.read_csv(
-                file_path, sep="\t", skiprows=10
-            )  # Read with explicit column names
+#     for damage, files in damage_scenarios.items():
+#         for i, file_index in enumerate(files, start=1):
+#             # Load original data file
+#             file_path = os.path.join(base_path, f"zzz{prefix}D{file_index}.TXT")
+#             df = pd.read_csv(
+#                 file_path, sep="\t", skiprows=10
+#             )  # Read with explicit column names
 
-            top_sensor = columns[i - 1]
-            print(top_sensor, type(top_sensor))
-            output_file_1 = os.path.join(
-                output_base, f"DAMAGE_{damage}", f"DAMAGE{damage}_TEST{i}_01.csv"
-            )
-            print(f"Creating {output_file_1} from taking zzz{prefix}D{file_index}.TXT")
-            print("Taking datetime column on index 0...")
-            print(f"Taking `{top_sensor}`...")
-            os.makedirs(os.path.dirname(output_file_1), exist_ok=True)
-            df[["Time", top_sensor]].to_csv(output_file_1, index=False)
-            print(Fore.GREEN + "Done")
+#             top_sensor = columns[i - 1]
+#             print(top_sensor, type(top_sensor))
+#             output_file_1 = os.path.join(
+#                 output_base, f"DAMAGE_{damage}", f"DAMAGE{damage}_TEST{i}_01.csv"
+#             )
+#             print(f"Creating {output_file_1} from taking zzz{prefix}D{file_index}.TXT")
+#             print("Taking datetime column on index 0...")
+#             print(f"Taking `{top_sensor}`...")
+#             os.makedirs(os.path.dirname(output_file_1), exist_ok=True)
+#             df[["Time", top_sensor]].to_csv(output_file_1, index=False)
+#             print(Fore.GREEN + "Done")
 
-            bottom_sensor = sensor_end_map[i]
-            output_file_2 = os.path.join(
-                output_base, f"DAMAGE_{damage}", f"DAMAGE{damage}_TEST{i}_02.csv"
-            )
-            print(f"Creating {output_file_2} from taking zzz{prefix}D{file_index}.TXT")
-            print("Taking datetime column on index 0...")
-            print(f"Taking `{bottom_sensor}`...")
-            os.makedirs(os.path.dirname(output_file_2), exist_ok=True)
-            df[["Time", bottom_sensor]].to_csv(output_file_2, index=False)
-            print(Fore.GREEN + "Done")
-            print("---")
+#             bottom_sensor = sensor_end_map[i]
+#             output_file_2 = os.path.join(
+#                 output_base, f"DAMAGE_{damage}", f"DAMAGE{damage}_TEST{i}_02.csv"
+#             )
+#             print(f"Creating {output_file_2} from taking zzz{prefix}D{file_index}.TXT")
+#             print("Taking datetime column on index 0...")
+#             print(f"Taking `{bottom_sensor}`...")
+#             os.makedirs(os.path.dirname(output_file_2), exist_ok=True)
+#             df[["Time", bottom_sensor]].to_csv(output_file_2, index=False)
+#             print(Fore.GREEN + "Done")
+#             print("---")
 
 
 def main():