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# genesis/visualization.py
import networkx as nx
import matplotlib.pyplot as plt
import io
import base64
def _graph_to_image_bytes(G, layout_func=nx.spring_layout):
"""Helper: Convert NetworkX graph to PNG bytes."""
plt.figure(figsize=(8, 6))
pos = layout_func(G)
nx.draw_networkx_nodes(G, pos, node_size=1500, node_color="#34d399", alpha=0.9)
nx.draw_networkx_edges(G, pos, width=2, alpha=0.5, edge_color="#6b7280")
nx.draw_networkx_labels(G, pos, font_size=10, font_family="sans-serif", font_color="white")
plt.axis("off")
buf = io.BytesIO()
plt.savefig(buf, format="png", bbox_inches="tight")
plt.close()
buf.seek(0)
return buf
def generate_pathway_graph(entities, relationships):
"""
Create a pathway relationship graph for synthetic biology concepts.
entities: list of strings
relationships: list of dicts {source, target, type}
Returns: file path to PNG
"""
G = nx.DiGraph()
for entity in entities:
G.add_node(entity)
for rel in relationships:
G.add_edge(rel["source"], rel["target"], label=rel["type"])
buf = _graph_to_image_bytes(G)
file_path = "/tmp/pathway_graph.png"
with open(file_path, "wb") as f:
f.write(buf.read())
return file_path
def generate_funding_network(companies):
"""
Create a funding network graph.
companies: list of dicts {name, investors}
Returns: file path to PNG
"""
G = nx.Graph()
for comp in companies:
company_node = f"🏢 {comp['name']}"
G.add_node(company_node)
investors = [i.strip() for i in comp["investors"].split(",")]
for inv in investors:
inv_node = f"💰 {inv}"
G.add_node(inv_node)
G.add_edge(company_node, inv_node)
buf = _graph_to_image_bytes(G, layout_func=nx.kamada_kawai_layout)
file_path = "/tmp/funding_network.png"
with open(file_path, "wb") as f:
f.write(buf.read())
return file_path
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