from data_preprocessing import *
from joblib import dump, load

# b = generate_damage_files_index(
#     num_damage=6,
#     file_index_start=1,
#     col=5,
#     base_path="D:/thesis/data/dataset_B",
#     prefix="zzzBD",
#     # undamage_file="zzzBU.TXT"
# )
# Example: Generate tuples with a special group of df0 at the beginning
# special_groups_A = [
#     {'df_name': 'zzzAU.TXT', 'position': 0, 'size': 5}  # Add at beginning
# ]

# special_groups_B = [
#     {'df_name': 'zzzBU.TXT', 'position': 0, 'size': 5}  # Add at beginning
# ]

# Generate the tuples with the special group
# a_complement = [(comp)
#                 for n in range(1, 31)
#                 for comp in complement_pairs(n, prefix="zzzAD", extension="TXT")]
# a = generate_df_tuples(special_groups=a_complement, prefix="zzzAD", undamage_file="zzzAU.TXT")

b_complement = [(comp)
                for n in range(1, 31)
                for comp in complement_pairs(n, prefix="zzzBD", extension="TXT")]
b = generate_df_tuples(special_groups=b_complement, prefix="zzzBD", undamage_file="zzzBU.TXT")


# a = generate_damage_files_index(
#     num_damage=6,
#     file_index_start=1,
#     col=5,
#     base_path="D:/thesis/data/dataset_A",
#     prefix="zzzAD",
#     # undamage_file="zzzBU.TXT"
# )

# data_A = DataProcessor(file_index=a, base_path="D:/thesis/data/dataset_A", include_time=True)
# data_A.create_vector_column(overwrite=True)
# # data_A.create_limited_sensor_vector_column(overwrite=True)
# data_A.export_to_csv("D:/thesis/data/converted/raw")

data_B = DataProcessor(file_index=b, base_path="D:/thesis/data/dataset_B", include_time=True)
# data_B.create_vector_column(overwrite=True)
# # data_B.create_limited_sensor_vector_column(overwrite=True)
data_B.export_to_csv("D:/thesis/data/converted/raw_B")
# a = load("D:/cache.joblib")
# breakpoint()