Create visualization.py

visualization.py

@@ -0,0 +1,137 @@
+# genesis/visualization.py
+import networkx as nx
+import plotly.graph_objects as go
+from typing import List, Dict
+
+def generate_pathway_graph(entities: List[str], relationships: List[Dict]) -> go.Figure:
+    """
+    Create an interactive graph visualization using Plotly.
+    entities: List of node labels
+    relationships: List of dicts {source: str, target: str, type: str}
+    """
+    # Create graph
+    G = nx.Graph()
+    for entity in entities:
+        G.add_node(entity)
+    for rel in relationships:
+        G.add_edge(rel["source"], rel["target"], type=rel.get("type", ""))
+
+    pos = nx.spring_layout(G, seed=42)
+
+    # Build edge traces
+    edge_x, edge_y = [], []
+    for edge in G.edges():
+        x0, y0 = pos[edge[0]]
+        x1, y1 = pos[edge[1]]
+        edge_x.extend([x0, x1, None])
+        edge_y.extend([y0, y1, None])
+
+    edge_trace = go.Scatter(
+        x=edge_x, y=edge_y,
+        line=dict(width=1, color="#888"),
+        hoverinfo='none',
+        mode='lines'
+    )
+
+    # Build node traces
+    node_x, node_y, text_labels = [], [], []
+    for node in G.nodes():
+        x, y = pos[node]
+        node_x.append(x)
+        node_y.append(y)
+        text_labels.append(node)
+
+    node_trace = go.Scatter(
+        x=node_x, y=node_y,
+        mode='markers+text',
+        text=text_labels,
+        textposition="top center",
+        hoverinfo='text',
+        marker=dict(
+            showscale=True,
+            colorscale='Viridis',
+            size=20,
+            color=[len(G.adj[n]) for n in G.nodes()],
+            colorbar=dict(
+                thickness=15,
+                title='Connections',
+                xanchor='left',
+                titleside='right'
+            )
+        )
+    )
+
+    fig = go.Figure(data=[edge_trace, node_trace],
+                    layout=go.Layout(
+                        title="Biological Pathway / Network",
+                        title_x=0.5,
+                        showlegend=False,
+                        hovermode='closest',
+                        margin=dict(b=0, l=0, r=0, t=40),
+                        annotations=[dict(
+                            text="GENESIS-AI Interactive Graph",
+                            showarrow=False,
+                            xref="paper", yref="paper",
+                            x=0.005, y=-0.002
+                        )]
+                    ))
+    return fig
+
+def generate_funding_network(companies: List[Dict]) -> go.Figure:
+    """
+    Visualize funding relationships between biotech companies and investors.
+    companies: list of {name, investors}
+    """
+    G = nx.Graph()
+    for c in companies:
+        company_node = c["name"]
+        G.add_node(company_node, type="company")
+        investors = c.get("investors", "").split(", ")
+        for inv in investors:
+            if inv.strip():
+                G.add_node(inv, type="investor")
+                G.add_edge(company_node, inv)
+
+    pos = nx.spring_layout(G, seed=42)
+
+    edge_x, edge_y = [], []
+    for edge in G.edges():
+        x0, y0 = pos[edge[0]]
+        x1, y1 = pos[edge[1]]
+        edge_x.extend([x0, x1, None])
+        edge_y.extend([y0, y1, None])
+
+    edge_trace = go.Scatter(
+        x=edge_x, y=edge_y,
+        line=dict(width=1, color="#888"),
+        hoverinfo='none',
+        mode='lines'
+    )
+
+    node_x, node_y, text_labels = [], [], []
+    colors = []
+    for node, data in G.nodes(data=True):
+        x, y = pos[node]
+        node_x.append(x)
+        node_y.append(y)
+        text_labels.append(node)
+        colors.append("#FF5733" if data["type"] == "company" else "#1F77B4")
+
+    node_trace = go.Scatter(
+        x=node_x, y=node_y,
+        mode='markers+text',
+        text=text_labels,
+        textposition="top center",
+        hoverinfo='text',
+        marker=dict(size=15, color=colors)
+    )
+
+    fig = go.Figure(data=[edge_trace, node_trace],
+                    layout=go.Layout(
+                        title="Biotech Funding Network",
+                        title_x=0.5,
+                        showlegend=False,
+                        hovermode='closest',
+                        margin=dict(b=0, l=0, r=0, t=40)
+                    ))
+    return fig