Plotgenerator_for_plotdata.py

import matplotlib.pyplot as plt
import pandas as pd

# Global variables for columns to plot and y-axis limits
COLUMNS_TO_PLOT = [
    'cycles_done', 'cur_path', 'paths_total', 'pending_total',
    'pending_favs', 'map_size', 'unique_crashes', 'unique_hangs',
    'max_depth', 'execs_per_sec'
]

ALTERNATIVE_COLUMNS = {
    'cur_path': 'Current Path',
    'paths_total': 'Total Paths',
    'pending_total': 'Pending Paths',
    'pending_favs': 'Pending Favorites',
    'map_size': 'Map Size (%)',
    'unique_crashes': 'Unique Crashes',
    'unique_hangs': 'Unique Hangs',
    'max_depth': 'Max Depth',
    'execs_per_sec': 'Executions per Second',
    'cycles_done': 'Cycles Done'
}

Y_AXIS_LIMITS = {
    # Add others as needed, or leave out for auto-scaling
}

LABELS_LIGHTFTP = {
    'base': 'Log enabled, keepalive disabled',
    'keepalivemaster': 'Log enabled, keepalive enabled',
    'keepalivenologmaster': 'Log disabled, keepalive enabled',
    'nologmaster': 'Log disabled, keepalive disabled'
}

LABELS_CARPET = {
    'proftpd_25_3hour': 'ProFTPd A',
    'proftpd_52_3hour': 'ProFTPd B',
    'proftpd_57_3hour': 'ProFTPd C',
    'proftpd_74': 'ProFTPd D',
    'proftpd_81': 'ProFTPd E',
    'basic': 'ProFTPD Basic',
    'basic_rights': 'ProFTPD Basic w/ admin Rights'
}

LABELS_PROPHET = {
    'proftpd_20': 'ProFTPd F',
    'proftpd_33': 'ProFTPd G',
    'proftpd_34': 'ProFTPd H',
    'proftpd_37': 'ProFTPd I',
    'proftpd_46': 'ProFTPd J',
    'basic': 'ProFTPD Basic',
    'basic_rights': 'ProFTPD Basic w/ admin Rights'
}

def trim_csv_to_3_hours(folders, output_csv_path, root):
    for folder in folders:
        input_csv_path = f"/home/marthijnvd/master/docs/proftpdafterdry/{root}/{folder}/plot_data"
        output_csv_path = f"/home/marthijnvd/master/docs/proftpdafterdry/{root}/{folder}/plot_data_trimmed"

        df = pd.read_csv(input_csv_path, comment=None)
        df.columns = [col.lstrip('#').strip() for col in df.columns]
        start_time = df['unix_time'].iloc[0]
        end_time = start_time + 3 * 3600  # 3 hours in seconds
        trimmed_df = df[df['unix_time'] <= end_time]
        trimmed_df.to_csv(output_csv_path, index=False)

def plot_column_across_folders(column, folders, root, LABELS):
    plt.figure()
    for folder in folders:
        data_path = f"/home/marthijnvd/master/docs/proftpdafterdry/{root}/{folder}/plot_data_trimmed"
        df = pd.read_csv(data_path, comment=None)
        df.columns = [col.lstrip('#').strip() for col in df.columns]
        df['datetime'] = pd.to_datetime(df['unix_time'], unit='s')
        if column == 'map_size':
            df['map_size'] = df['map_size'].str.rstrip('%').astype(float)
        # Normalize time: seconds since first measurement in this folder
        start_time = df['unix_time'].iloc[0]
        end_time = df['unix_time'].iloc[-1]
        df['time_normalized'] = (df['unix_time'] - start_time) / (end_time - start_time) * 3
        plt.plot(df['time_normalized'], df[column], marker='o', label=LABELS[folder])
        
    titleprefix = 'CarpetFuzz' if root == 'carpet' else 'ProphetFuzz'
        
    plt.title(f"{titleprefix} - {ALTERNATIVE_COLUMNS[column]} over Time")
    plt.xlabel("Time (hours since start)")
    plt.ylabel(ALTERNATIVE_COLUMNS[column])
    plt.tight_layout()
    plt.grid(True)
    if column in Y_AXIS_LIMITS and Y_AXIS_LIMITS[column] is not None:
        plt.ylim(Y_AXIS_LIMITS[column])
    plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', borderaxespad=0.)
    plt.savefig(f"proftpdplots/{root}_proftpd_{column}_over_time_all.png", bbox_inches='tight')
    plt.close()

def plot_column_across_folders_light(column, folders, root, LABELS):
    plt.figure()
    for folder in folders:
        data_path = f"/home/marthijnvd/master/docs/lightftpfuzzerresults/lightftprun11062025/{folder}/plot_data"
        df = pd.read_csv(data_path, comment=None)
        df.columns = [col.lstrip('#').strip() for col in df.columns]
        df['datetime'] = pd.to_datetime(df['unix_time'], unit='s')
        if column == 'map_size':
            df['map_size'] = df['map_size'].str.rstrip('%').astype(float)
        # Normalize time: seconds since first measurement in this folder
        start_time = df['unix_time'].iloc[0]
        end_time = df['unix_time'].iloc[-1]
        df['time_normalized'] = (df['unix_time'] - start_time) / (end_time - start_time) * 3
        plt.plot(df['time_normalized'], df[column], marker='o', label=LABELS[folder])
        
    titleprefix = 'LightFTP'
        
    plt.title(f"{titleprefix} - {ALTERNATIVE_COLUMNS[column]} over Time")
    plt.xlabel("Time (hours since start)")
    plt.ylabel(ALTERNATIVE_COLUMNS[column])
    plt.tight_layout()
    plt.grid(True)
    if column in Y_AXIS_LIMITS and Y_AXIS_LIMITS[column] is not None:
        plt.ylim(Y_AXIS_LIMITS[column])
    plt.legend(bbox_to_anchor=(1.05, 1), loc='upper left', borderaxespad=0.)
    plt.savefig(f"lightftpplotsv3/{root}_{column}_over_time_all.png", bbox_inches='tight')
    plt.close()

if __name__ == "__main__":
    folders_lightftp = ['base', 'keepalivemaster', 'keepalivenologmaster', 'nologmaster']
    folders_carpet = ['proftpd_25_3hour', 'proftpd_52_3hour', 'proftpd_57_3hour', 'proftpd_74', 'proftpd_81', 'basic', 'basic_rights']
    folders_prophet = ['proftpd_20', 'proftpd_33', 'proftpd_34', 'proftpd_37', 'proftpd_46', 'basic', 'basic_rights']
    trim_csv_to_3_hours(folders_carpet, folders_carpet, 'carpet')
    trim_csv_to_3_hours(folders_prophet, folders_prophet, 'prophet')
    print("Trimmed CSV files successfully.")
    for column in COLUMNS_TO_PLOT:
        # plot_column_across_folders(column, folders_lightftp, 'lightftp', LABELS_LIGHTFTP)
        plot_column_across_folders(column, folders_carpet, 'carpet', LABELS_CARPET)
        print("Carpet plots generated successfully.")
        plot_column_across_folders(column, folders_prophet, 'prophet', LABELS_PROPHET)
        print("Prophet plots generated successfully.")
        plot_column_across_folders_light(column, folders_lightftp, 'lightftp', LABELS_LIGHTFTP)
    print("Plots generated successfully.")