import pandas as pd
import glob
import os


# ---------------------------------------------------------
# STEP 1 - Ask user which spring to process
# ---------------------------------------------------------
spring_name = input("Enter spring number (example: 1040_01): ").strip()


# ---------------------------------------------------------
# STEP 2 - Find all matching test files
# ---------------------------------------------------------
file_pattern = f"Spring_{spring_name}_Test_*.csv"

file_list = glob.glob(file_pattern)

# Make sure files are processed in order
file_list.sort()

if len(file_list) == 0:
    print(f"No files found matching: {file_pattern}")
    exit()


# ---------------------------------------------------------
# STEP 3 - Variables used while combining files
# ---------------------------------------------------------
combined_data = []

time_offset = 0


# ---------------------------------------------------------
# STEP 4 - Process each test file
# ---------------------------------------------------------
for test_number, file in enumerate(file_list, start=1):

    print(f"Processing: {file}")

    # Read CSV
    df = pd.read_csv(file)

    # Remove rows containing empty data
    df = df.dropna()

    # Time column name
    time_column = "Time (s)"

    # Create Test column
    df["Test"] = test_number

    # Create continuous time column
    df["Continuous Time (s)"] = df[time_column] + time_offset

    # Determine ending time for next test
    last_time = df[time_column].iloc[-1]

    time_offset += last_time

    # Store cleaned data
    combined_data.append(df)


# ---------------------------------------------------------
# STEP 5 - Combine all tests into one dataframe
# ---------------------------------------------------------
final_df = pd.concat(combined_data, ignore_index=True)


# ---------------------------------------------------------
# STEP 6 - Create output filename
# ---------------------------------------------------------
output_file = f"Spring_{spring_name}_Cleaned.csv"


# ---------------------------------------------------------
# STEP 7 - Save cleaned data
# ---------------------------------------------------------
final_df.to_csv(output_file, index=False)

print()
print(f"Finished!")
print(f"Output saved as: {output_file}")