import os
import pandas as pd
from datetime import datetime, timedelta
import numpy as np

# Base path for the folder structure
base_path = "data"

# Create the folder structure
raw_path = os.path.join(base_path, "raw")
processed_path = os.path.join(base_path, "processed")

os.makedirs(raw_path, exist_ok=True)
os.makedirs(processed_path, exist_ok=True)

# Define the number of zeros to pad
num_damages = 5
num_tests = 10
damage_pad = len(str(num_damages))
test_pad = len(str(num_tests))

for damage in range(1, num_damages + 1):  # 5 Damage levels starts from 1
    damage_folder = f"DAMAGE_{damage:0{damage_pad}}"
    damage_path = os.path.join(raw_path, damage_folder)
    os.makedirs(damage_path, exist_ok=True)

    for test in range(1, 11):  # 10 Tests per damage level
        # Filename for the CSV
        csv_filename = f"D{damage:0{damage_pad}}_TEST{test:0{test_pad}}.csv"
        csv_path = os.path.join(damage_path, csv_filename)

        # Generate dummy data
        num_rows = 10
        start_time = datetime.now()
        timestamps = [start_time + timedelta(seconds=i*0.0078125) for i in range(num_rows)]
        values = np.random.randn(num_rows)  # Random float values

        # Create DataFrame
        df = pd.DataFrame({
            "Time": timestamps,
            "Value": values
        })

        # Save the CSV file with a custom header
        with open(csv_path, 'w') as file:
            file.write('sep=,\n')  # Writing the separator hint
            df.to_csv(file, index=False)