Update app.py

app.py

@@ -2,13 +2,15 @@ import streamlit as st
 import matplotlib.pyplot as plt
 import networkx as nx
 import numpy as np
+from operator import itemgetter
 
 # Sidebar for selecting an option
 sidebar_option = st.sidebar.radio("Select an option", 
                                  ["Select an option", "Basic: Properties", 
                                   "Basic: Read and write graphs", "Basic: Simple graph", 
                                   "Basic: Simple graph Directed", "Drawing: Custom Node Position",
-                                  "Drawing: Cluster Layout", "Drawing: Degree Analysis"])
+                                  "Drawing: Cluster Layout", "Drawing: Degree Analysis",
+                                  "Drawing: Ego Graph"])
 
 # Helper function to draw and display graph
 def draw_graph(G, pos=None, title="Graph Visualization"):
@@ -226,8 +228,67 @@ def display_degree_analysis():
                 fig.tight_layout()
                 st.pyplot(fig)
 
+# Function to display Ego Graph for Drawing: Ego Graph
+def display_ego_graph():
+    st.title("Drawing: Ego Graph")
+
+    option = st.radio("Choose a graph type:", ("Default Example", "Create your own"))
+
+    if option == "Default Example":
+        # Create a BA model graph - use seed for reproducibility
+        n = 1000
+        m = 2
+        seed = 20532
+        G = nx.barabasi_albert_graph(n, m, seed=seed)
+
+        # Find node with largest degree
+        node_and_degree = G.degree()
+        (largest_hub, degree) = sorted(node_and_degree, key=itemgetter(1))[-1]
+
+        # Create ego graph of main hub
+        hub_ego = nx.ego_graph(G, largest_hub)
+
+        # Draw graph
+        pos = nx.spring_layout(hub_ego, seed=seed)  # Seed layout for reproducibility
+        nx.draw(hub_ego, pos, node_color="b", node_size=50, with_labels=False)
+
+        # Draw ego as large and red
+        options = {"node_size": 300, "node_color": "r"}
+        nx.draw_networkx_nodes(hub_ego, pos, nodelist=[largest_hub], **options)
+        plt.tight_layout()
+        st.pyplot(plt)
+
+    elif option == "Create your own":
+        n_nodes = st.number_input("Number of nodes:", min_value=2, max_value=1000, value=100)
+        m_edges = st.number_input("Edges per node:", min_value=1, max_value=10, value=2)
+
+        if st.button("Generate"):
+            if n_nodes >= 2:
+                G_custom = nx.barabasi_albert_graph(n_nodes, m_edges, seed=20532)
+
+                # Find node with largest degree
+                node_and_degree = G_custom.degree()
+                (largest_hub, degree) = sorted(node_and_degree, key=itemgetter(1))[-1]
+
+                # Create ego graph of main hub
+                hub_ego = nx.ego_graph(G_custom, largest_hub)
+
+                # Draw graph
+                pos = nx.spring_layout(hub_ego, seed=20532)  # Seed layout for reproducibility
+                nx.draw(hub_ego, pos, node_color="b", node_size=50, with_labels=False)
+
+                # Draw ego as large and red
+                options = {"node_size": 300, "node_color": "r"}
+                nx.draw_networkx_nodes(hub_ego, pos, nodelist=[largest_hub], **options)
+                plt.tight_layout()
+                st.pyplot(plt)
+
+# Display Drawing: Ego Graph if selected
+if sidebar_option == "Drawing: Ego Graph":
+    display_ego_graph()
+
 # Display Basic: Properties if selected
-if sidebar_option == "Basic: Properties":
+elif sidebar_option == "Basic: Properties":
     st.title("Basic: Properties")
     option = st.radio("Choose a graph type:", ("Default Example", "Create your own"))