import pickle
import matplotlib.pyplot as plt


def load_pickle_data(path):
    """Read and load data from a pickle file."""
    with open(path, "rb") as f:
        return pickle.load(f)


def adjust_indices_based_on_condition(data, start_idx, end_idx):
    """Modify start and end indices until the data at those points satisfies specific conditions."""
    while data[1][start_idx] > 1:
        start_idx += 1
    while data[1][end_idx] > 1:
        end_idx -= 1
    return start_idx, end_idx


def analyze_data_segments(data, start_idx, end_idx, window_size):
    """Process segments of data and construct a result string based on the sum conditions."""
    current_idx = start_idx + window_size
    previous_idx = current_idx
    result_string = ""
    while current_idx < end_idx:
        # Find segment start where sum exceeds threshold
        while sum(data[1][current_idx - window_size:current_idx]) > window_size:
            current_idx += 1
        segment_start = current_idx
        
        # Find segment end where sum drops below threshold
        while sum(data[1][current_idx - window_size:current_idx]) < window_size:
            current_idx += 1
        segment_end = current_idx

        middle_idx = (segment_start + segment_end) // 2
        
        # Evaluate the average for data[2] in the segment and check if it exceeds threshold
        avg_value = sum(data[2][previous_idx:middle_idx]) // (middle_idx - previous_idx)
        result_string += "1" if avg_value > 1 else "0"
        
        previous_idx = middle_idx

    return result_string[1:], data[1][start_idx:end_idx], data[2][start_idx:end_idx], data[0][start_idx:end_idx]


def binary_to_bytes(binary_string):
    """Convert the binary string into a bytes object."""
    byte_data = b""
    for i in range(0, len(binary_string), 9):
        byte_chunk = int(binary_string[i:i + 8], 2).to_bytes(1, byteorder='big')
        byte_data += byte_chunk
    return byte_data


def main():
    file_path = "trace.pckl"
    data = load_pickle_data(file_path)

    start_index = 68000
    end_index = 240000
    window_size = 20

    # Adjust indices based on the conditions
    start_index, end_index = adjust_indices_based_on_condition(data, start_index, end_index)

    # Process the data and get the result string
    result_string, data_segment1, data_segment2, x_values = analyze_data_segments(data, start_index, end_index, window_size)

    # Convert the result string to bytes and print the decoded output
    byte_data = binary_to_bytes(result_string)
    print(byte_data.split(b'\xa1')[1].decode())


if __name__ == "__main__":
    main()