vis.py

#!/usr/bin/env python3
import json
import matplotlib.pyplot as plt
import numpy as np

FILES = {
    "oBGP": "report_obgp.json",
    "BGP": "report_bgp.json"
}

MODE_COLORS = {
    "oBGP": "#f15bb5",
    "BGP": "#00f5d4",
}

def load_data(filename):
    with open(filename, "r") as f:
        return json.load(f)

def aggregate_percentiles(data, field, steps=None):
    if steps is None:
        steps = list(range(10, 91, 5))
    observers = data.get("observers", {})
    max_len = max(len(obs["series"]) for obs in observers.values())
    all_series = []
    for obs in observers.values():
        series = [s.get(field, 0) for s in obs["series"]]
        if len(series) < max_len:
            series += [0] * (max_len - len(series))
        all_series.append(series)
    all_series = np.array(all_series)
    percentiles = {p: np.percentile(all_series, p, axis=0) for p in steps}
    return percentiles

def plot_density_gradient(ax, perc, color, title, ylabel):
    x = range(len(next(iter(perc.values()))))
    steps = sorted(perc.keys())
    mid = len(steps) // 2
    for i in range(mid):
        low = steps[i]
        high = steps[-(i+1)]
        alpha = 0.1 + 0.15 * (1 - i/mid)
        ax.fill_between(x, perc[low], perc[high], color=color, alpha=alpha)
    ax.set_title(title, fontsize=13, weight="bold")
    ax.set_xlabel("Sample index", fontsize=11)
    ax.set_ylabel(ylabel, fontsize=11)
    ax.grid(True, alpha=0.3)

if __name__ == "__main__":
    fig, axes = plt.subplots(4, 2, figsize=(16, 16), sharex=True, sharey="row")

    data_obgp = load_data(FILES["oBGP"])
    perc_paths_obgp = aggregate_percentiles(data_obgp, "num_paths")
    perc_dests_obgp = aggregate_percentiles(data_obgp, "num_destinations")
    perc_len_min_obgp = aggregate_percentiles(data_obgp, "path_len_min")
    perc_len_max_obgp = aggregate_percentiles(data_obgp, "path_len_max")

    data_bgp = load_data(FILES["BGP"])
    perc_paths_bgp = aggregate_percentiles(data_bgp, "num_paths")
    perc_dests_bgp = aggregate_percentiles(data_bgp, "num_destinations")
    perc_len_min_bgp = aggregate_percentiles(data_bgp, "path_len_min")
    perc_len_max_bgp = aggregate_percentiles(data_bgp, "path_len_max")

    plot_density_gradient(
        axes[0, 0], perc_paths_obgp, MODE_COLORS["oBGP"],
        "oBGP – Routes", "Number of routes"
    )
    plot_density_gradient(
        axes[0, 1], perc_paths_bgp, MODE_COLORS["BGP"],
        "BGP – Routes", "Number of routes"
    )

    plot_density_gradient(
        axes[1, 0], perc_dests_obgp, MODE_COLORS["oBGP"],
        "oBGP – Destinations", "Number of destinations"
    )
    plot_density_gradient(
        axes[1, 1], perc_dests_bgp, MODE_COLORS["BGP"],
        "BGP – Destinations", "Number of destinations"
    )

    plot_density_gradient(
        axes[2, 0], perc_len_min_obgp, MODE_COLORS["oBGP"],
        "oBGP – Minimum path length", "Path length"
    )
    plot_density_gradient(
        axes[2, 1], perc_len_min_bgp, MODE_COLORS["BGP"],
        "BGP – Minimum path length", "Path length"
    )

    plot_density_gradient(
        axes[3, 0], perc_len_max_obgp, MODE_COLORS["oBGP"],
        "oBGP – Maximum path length", "Path length"
    )
    plot_density_gradient(
        axes[3, 1], perc_len_max_bgp, MODE_COLORS["BGP"],
        "BGP – Maximum path length", "Path length"
    )

    plt.tight_layout(rect=[0, 0, 1, 0.97])
    plt.show()