def draw_reorg()

in scripts/figs.py [0:0]

• 46 lines of code
• 13 McCabe index (conditional complexity)

def draw_reorg():
    dfs = {
        "Redistribution cost unaware": pd.read_csv("../long_term/placement_unaware.csv"),
        "Moirai": pd.read_csv("../long_term/placement_moirai.csv"),
    }

    fig, ax = plt.subplots(figsize=(11, 5))

    # Define line styles and markers for black-and-white friendly plotting
    line_styles = ['--', '--', '-', '-']

    # Placeholder for cumulative data
    cumulative_data = {
        "Redistribution cost unaware (Ingress)": [],
        "Redistribution cost unaware (Egress)": [],
        "Moirai (Ingress)": [],
        "Moirai (Egress)": []
    }

    for label, df in dfs.items():
        # Convert Ingress and Egress to bytes
        df['Ingress_Bytes'] = df['Ingress'].apply(parse_size).cumsum()
        df['Egress_Bytes'] = df['Egress'].apply(parse_size).cumsum()

        cumulative_data[f"{label} (Ingress)"] = df['Ingress_Bytes']
        cumulative_data[f"{label} (Egress)"] = df['Egress_Bytes']

        # Plot the Ingress and Egress data
        ax.plot(df['On-premises'], df['Ingress_Bytes'], label=f'{label} (ingress)',
                linestyle=line_styles.pop(0), color='blue', linewidth=2, marker='x', markersize=12)
        ax.plot(df['On-premises'], df['Egress_Bytes'], label=f'{label} (egress)',
                linestyle=line_styles.pop(0), color='green', linewidth=2, marker='*', markersize=12)

        if label == "Redistribution cost unaware":
            best_case_x = df['On-premises']
            best_case_y = (1 - df['On-premises'] / 100) * (299.12 * 1024 ** 5)
            ax.plot(best_case_x, best_case_y, 'r-', label='Best case (ingress)', linewidth=6)

    # Customize the plot
    ax.set_xlabel('On-premises Storage Space / Total Data Size (%)', fontsize=font_size)
    ax.set_ylabel('Traffic Volume (PB)', fontsize=font_size)
    ax.tick_params(axis='x', labelsize=font_size - 2)
    ax.tick_params(axis='y', labelsize=font_size - 2)
    ax.grid(True)

    # Add legend
    ax.legend(loc='upper center',
              bbox_to_anchor=(0.5, 1.35), fontsize=font_size - 2,
              ncol=2, frameon=False)

    # Set y-axis ticks and labels
    ticks = [x for x in range(0, 55, 5)]
    yticks = [i * 10 * 1024 ** 5 for i in ticks]
    ytick_labels = ["0"] + [f"{i * 10}" if i % 2 == 0 else "" for i in ticks[1:]]
    ax.set_ylim(ymax=450 * 1024 ** 5)
    ax.set_yticks(yticks)
    ax.set_yticklabels(ytick_labels, fontsize=font_size - 2)

    ax.set_xlim(0, 90)
    ax.set_xticks([90, 80, 70, 60, 50, 40, 30, 20, 10, 0])
    ax.set_xticklabels(["90%", "80%", "70%", "60%", "50%", "40%", "30%", "20%", "10%", "0%"], fontsize=font_size - 2)

    # Invert x-axis to start from large to low
    ax.invert_xaxis()

    plt.tight_layout()
    plt.savefig('migration.pdf', bbox_inches='tight')