DSAP/visualise.py at main · BadKarma6969/DSAP · GitHub

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import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.animation as animation
import numpy as np
import networkx as nx
from scipy.spatial import ConvexHull
import glob

#Load edges
edges_df = pd.read_csv("edges.csv")
edges = list(zip(edges_df.u, edges_df.v))

#Load snapshots
files = sorted(
    glob.glob("nodes_step_*.csv"),
    key=lambda x: int(x.split("_")[-1].split(".")[0])
)

snapshots = [pd.read_csv(f) for f in files]
steps = len(snapshots)

N = len(snapshots[0])
G = nx.Graph()
G.add_nodes_from(range(N))
G.add_edges_from(edges)

pos = {}
for _, row in snapshots[0].iterrows():
    pos[row.id] = (row.x, row.y)

fig, ax = plt.subplots(figsize=(10, 8))
plt.axis('off')

def frame(t):
    ax.clear()
    ax.set_title(f"Opinion Graph — Step {t}", fontsize=14)
    ax.axis('off')

    snap = snapshots[t]
    colors = []
    sizes = []

    for _, row in snap.iterrows():
        op = row.opinion

        # Node color by polarity
        if op > 0.05:
            colors.append((1, 0.4, 0.4)) #red
        elif op < -0.05:
            colors.append((0.4, 0.4, 1)) #blue
        else:
            colors.append((0.5, 0.5, 0.5)) #gray

        sizes.append(50 + 300 * abs(op))

    nx.draw_networkx_edges(G, pos, alpha=0.1, width=0.4, ax=ax)
    nx.draw_networkx_nodes(G, pos, node_color=colors, node_size=sizes, ax=ax)

ani = animation.FuncAnimation(
    fig, frame, frames=steps, interval=50, repeat=False
)

plt.show()

ghetto_df = pd.read_csv("ghettos.csv") #ghetto_id, node
final_snap = snapshots[-1]

ghettos = {}
for _, row in ghetto_df.iterrows():
    gid = row.ghetto_id
    ghettos.setdefault(gid, []).append(row.node)

plt.figure(figsize=(10, 8))
plt.title("Ideological Communities")

colors = []
sizes = []

for _, row in final_snap.iterrows():
    op = row.opinion

    if op > 0.01:
        colors.append((1, 0.4, 0.4))
    elif op < -0.01:
        colors.append((0.4, 0.4, 1))
    else:
        colors.append((0.5, 0.5, 0.5))

    sizes.append(50 + 300*abs(op))

nx.draw_networkx_edges(G, pos, alpha=0.1)
nx.draw_networkx_nodes(G, pos, node_color=colors, node_size=sizes)

for gid, nodes_list in ghettos.items():
    pts = np.array([pos[n] for n in nodes_list])

    if len(pts) < 3:
        continue

    try:
        hull = ConvexHull(pts)
        hull_pts = pts[hull.vertices]
    except:
        hull_pts = pts

    avg_opinion = np.mean([final_snap.loc[n].opinion for n in nodes_list])

    if avg_opinion > 0.05:
        blob = (1, 0.3, 0.3, 0.25)
    elif avg_opinion < -0.05:
        blob = (0.3, 0.3, 1, 0.25)
    else:
        blob = (0.7, 0.7, 0.7, 0.25)

    plt.fill(hull_pts[:, 0], hull_pts[:, 1], color=blob)

plt.axis('off')
plt.show()