extract_log.py

import re
import matplotlib.pyplot as plt
import numpy as np

if __name__ == '__main__':

# Initialize empty arrays
    block_nums = []
    coins = []
    msg_lengths = []
    validation_times = []

    # Open the text file
    with open('data/log.txt', 'r') as file:
        # Read each line
        for line in file:
            # Extract numbers using regular expressions
            match = re.match(r".*block (\d+), (\d+) coins, msg of (\d+) bytes validated in (\d+\.\d+)", line)
            if match:
                if float(match.group(4)) < 30 and int(match.group(2)) > 0:
                    # Extract numbers from the matched groups
                    block_num = int(match.group(1))
                    coin_num = int(match.group(2))
                    msg_length = int(match.group(3))
                    validation_time = float(match.group(4))

                    # Append the numbers to their respective arrays
                    block_nums.append(block_num)
                    coins.append(coin_num)
                    msg_lengths.append(msg_length)
                    validation_times.append(validation_time)

    # Calculate statistics
    max_validation_time = max(validation_times)
    max_coins = max(coins)
    mean_coins = np.mean(coins)
    mean_validation_time = np.mean(validation_times)

    # Create the dot plot
    plt.figure(figsize=(19, 14))  # Set the figure size (adjust as needed)
    plt.scatter(block_nums, validation_times, color='blue', label='Validation Time, s', s=6)
    plt.axhline(mean_validation_time, color='red', linestyle='--', label='Mean Validation Time')
    plt.xlabel('Block index, i', fontsize=18)
    plt.ylabel('Validation Time, s', fontsize=18)
    plt.title('Validation time per block', fontsize=20)
    plt.legend(fontsize=16)

    # Set custom x-axis tick positions and labels
    block_nums_ticks = np.arange(min(block_nums), max(block_nums)+1, 50000)
    plt.xticks(block_nums_ticks)
    plt.xticks(rotation=45)  # Rotate the x-axis tick labels by 45 degrees (adjust as needed)


    # Print the statistics
    print("Max Validation Time:", max_validation_time)
    print("Mean Validation Time:", mean_validation_time)
    print("Max Coins:", max_coins)
    print("Mean Coins:", mean_coins)

    # Display the plot
    plt.tight_layout()  # Ensures that all elements are properly displayed
    plt.show()