Update app.py

app.py

@@ -15,7 +15,7 @@ sidebar_option = st.sidebar.radio("Select an option",
                                   "Drawing: House With Colors", "Drawing: Labels And Colors", 
                                   "Drawing: Multipartite Layout", "Drawing: Node Colormap",
                                   "Drawing: Rainbow Coloring", "Drawing: Random Geometric Graph","Drawing: Self-loops",
-                                  "Drawing: Simple Path", "Drawing: Spectral Embedding"])
+                                  "Drawing: Simple Path", "Drawing: Spectral Embedding", "Drawing: Traveling Salesman Problem"])
 
 # Helper function to draw and display graph
 def draw_graph(G, pos=None, title="Graph Visualization"):
@@ -23,6 +23,95 @@ def draw_graph(G, pos=None, title="Graph Visualization"):
     nx.draw(G, pos=pos, with_labels=True, node_color='lightblue', node_size=500, font_size=10, font_weight='bold')
     st.pyplot(plt)
 
+# Function to display Traveling Salesman Problem
+def display_tsp():
+    st.title("Drawing: Traveling Salesman Problem")
+
+    option = st.radio("Choose a graph type:", ("Default Example", "Create your own"))
+
+    if option == "Default Example":
+        # Default example of random geometric graph with TSP solution
+        G = nx.random_geometric_graph(20, radius=0.4, seed=3)
+        pos = nx.get_node_attributes(G, "pos")
+
+        # Depot should be at (0.5, 0.5)
+        pos[0] = (0.5, 0.5)
+
+        H = G.copy()
+
+        # Calculating the distances between the nodes as edge's weight.
+        for i in range(len(pos)):
+            for j in range(i + 1, len(pos)):
+                dist = math.hypot(pos[i][0] - pos[j][0], pos[i][1] - pos[j][1])
+                dist = dist
+                G.add_edge(i, j, weight=dist)
+
+        cycle = nx_app.christofides(G, weight="weight")
+        edge_list = list(nx.utils.pairwise(cycle))
+
+        # Draw closest edges on each node only
+        nx.draw_networkx_edges(H, pos, edge_color="blue", width=0.5)
+
+        # Draw the route
+        nx.draw_networkx(
+            G,
+            pos,
+            with_labels=True,
+            edgelist=edge_list,
+            edge_color="red",
+            node_size=200,
+            width=3,
+        )
+
+        st.pyplot(plt)
+        st.write("The route of the traveler is:", cycle)
+
+    elif option == "Create your own":
+        # User can create their own graph
+        num_nodes = st.slider("Number of nodes:", min_value=3, max_value=30, value=20)
+        radius = st.slider("Edge radius:", min_value=0.1, max_value=1.0, value=0.4)
+
+        # Create random geometric graph based on user input
+        G_custom = nx.random_geometric_graph(num_nodes, radius, seed=3)
+        pos = nx.get_node_attributes(G_custom, "pos")
+
+        # Depot should be at (0.5, 0.5)
+        pos[0] = (0.5, 0.5)
+
+        H = G_custom.copy()
+
+        # Calculating the distances between the nodes as edge's weight.
+        for i in range(len(pos)):
+            for j in range(i + 1, len(pos)):
+                dist = math.hypot(pos[i][0] - pos[j][0], pos[i][1] - pos[j][1])
+                dist = dist
+                G_custom.add_edge(i, j, weight=dist)
+
+        # Find TSP cycle using Christofides' approximation
+        cycle = nx_app.christofides(G_custom, weight="weight")
+        edge_list = list(nx.utils.pairwise(cycle))
+
+        # Draw closest edges on each node only
+        nx.draw_networkx_edges(H, pos, edge_color="blue", width=0.5)
+
+        # Draw the TSP route
+        nx.draw_networkx(
+            G_custom,
+            pos,
+            with_labels=True,
+            edgelist=edge_list,
+            edge_color="red",
+            node_size=200,
+            width=3,
+        )
+
+        st.pyplot(plt)
+        st.write("The route of the traveler is:", cycle)
+
+# Display Drawing: Traveling Salesman Problem if selected
+if sidebar_option == "Drawing: Traveling Salesman Problem":
+    display_tsp()
+
 # Function to display Drawing: Spectral Embedding
 def display_spectral_embedding():
     st.title("Drawing: Spectral Embedding")