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PyVis Graph Visualiser
Builds interactive network visualisations for account investigation.
"""
import json
import tempfile
import os
import streamlit.components.v1 as components
import pandas as pd
import networkx as nx
from pyvis.network import Network
# Constants
NODE_SIZE_CENTER = 35
NODE_SIZE_HIGH_RISK = 22
NODE_SIZE_NORMAL = 14
NODE_SIZE_HIGH_PAGERANK = 26
EDGE_WIDTH_MAX = 8
EDGE_WIDTH_SCALE = 1_000_000
PAGERANK_TOP_PCT = 0.01
PHYSICS_GRAVITY = -50
PHYSICS_SPRING = 100
PHYSICS_ITERATIONS = 150
# Color palette
COLOR_CENTER = '#FFD700' # Gold for center node
COLOR_FRAUD = '#FF4136' # Red for confirmed fraud
COLOR_HIGH_PR = '#FF851B' # Orange for high PageRank
COLOR_NORMAL = '#0074D9' # Blue for normal
COLOR_FRAUD_EDGE = '#FF4136' # Red for fraudulent edges
COLOR_NORMAL_EDGE = '#AAAAAA' # Grey for normal edges
PHYSICS_OPTIONS = json.dumps({
"nodes": {"borderWidth": 2, "shadow": True},
"edges": {
"smooth": {"type": "curvedCW", "roundness": 0.2},
"shadow": True,
"arrows": {"to": {"enabled": True, "scaleFactor": 0.8}},
},
"physics": {
"forceAtlas2Based": {
"gravitationalConstant": PHYSICS_GRAVITY,
"springLength": PHYSICS_SPRING,
},
"solver": "forceAtlas2Based",
"stabilization": {"iterations": PHYSICS_ITERATIONS},
},
"interaction": {"hover": True, "tooltipDelay": 100},
})
def build_pyvis_graph(
subgraph: nx.DiGraph,
df: pd.DataFrame,
center_node: str,
fraud_accounts: set,
pagerank_scores: dict,
louvain_partition: dict,
) -> Network:
"""
Build an interactive PyVis network from a NetworkX subgraph.
Nodes are sized and colored based on their role (center, fraud, high-PR, normal).
Edges are scaled by transaction amount and colored by fraud status.
Returns:
A pyvis.network.Network instance ready for rendering.
"""
net = Network(
height='570px',
width='100%',
directed=True,
notebook=False,
)
net.set_options(PHYSICS_OPTIONS)
# Compute pagerank threshold for highlighting top nodes
all_pr = sorted(pagerank_scores.values(), reverse=True)
top_n = max(1, int(len(all_pr) * PAGERANK_TOP_PCT))
pagerank_threshold = all_pr[min(top_n, len(all_pr) - 1)]
# --- Add nodes ---
for node in subgraph.nodes():
node_data = subgraph.nodes[node]
is_center = (node == center_node)
is_fraud = node in fraud_accounts
is_high_pr = pagerank_scores.get(node, 0) >= pagerank_threshold
# Size and shape
if is_center:
size = NODE_SIZE_CENTER
shape = 'star'
color = COLOR_CENTER
elif is_high_pr:
size = NODE_SIZE_HIGH_PAGERANK
shape = 'diamond'
color = COLOR_HIGH_PR
elif is_fraud:
size = NODE_SIZE_HIGH_RISK
shape = 'dot'
color = COLOR_FRAUD
else:
size = NODE_SIZE_NORMAL
shape = 'dot'
color = COLOR_NORMAL
# Tooltip
total_sent = node_data.get('total_sent', 0)
total_received = node_data.get('total_received', 0)
count_sent = node_data.get('count_sent', 0)
community = louvain_partition.get(node, 'N/A')
status = 'FLAGGED' if is_fraud else 'Normal'
tooltip = (
f"Account: {node}\n"
f"Total Sent: {total_sent:,.0f}\n"
f"Total Received: {total_received:,.0f}\n"
f"Transactions: {count_sent}\n"
f"Community: {community}\n"
f"Status: {status}"
)
label = str(node)[:12]
net.add_node(
str(node),
label=label,
size=size,
shape=shape,
color=color,
title=tooltip,
borderWidth=2,
borderWidthSelected=4,
)
# --- Add edges ---
for src, tgt, data in subgraph.edges(data=True):
amount = data.get('amount', 0)
is_fraud_edge = data.get('is_laundering', 0) == 1
edge_width = min(amount / EDGE_WIDTH_SCALE, EDGE_WIDTH_MAX)
edge_width = max(edge_width, 0.5)
edge_color = COLOR_FRAUD_EDGE if is_fraud_edge else COLOR_NORMAL_EDGE
tooltip = (
f"Amount: {amount:,.0f}\n"
f"Channel: {data.get('payment_type', '')}\n"
f"Suspicious: {'Yes' if is_fraud_edge else 'No'}"
)
net.add_edge(
str(src),
str(tgt),
value=edge_width,
title=tooltip,
color=edge_color,
arrows='to',
)
return net
def render_pyvis(net: Network) -> None:
"""
Render a PyVis network inside a Streamlit app using an HTML component.
"""
with tempfile.NamedTemporaryFile(delete=False, suffix='.html', mode='w') as f:
tmp_path = f.name
net.save_graph(tmp_path)
with open(tmp_path, 'r') as f:
html_content = f.read()
os.unlink(tmp_path)
components.html(html_content, height=580, scrolling=False)
def save_pyvis_html(net: Network, path: str) -> None:
"""
Save a PyVis network to an HTML file on disk.
"""
net.save_graph(path)
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