Update app.py

app.py

@@ -17,7 +17,8 @@ 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: Traveling Salesman Problem"])
+                                  "Drawing: Simple Path", "Drawing: Spectral Embedding", "Drawing: Traveling Salesman Problem",
+                                  "Drawing: Weighted Graph"])
 
 # Helper function to draw and display graph
 def draw_graph(G, pos=None, title="Graph Visualization"):
@@ -25,6 +26,88 @@ 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 Weighted Graph
+def display_weighted_graph():
+    st.title("Drawing: Weighted Graph")
+
+    option = st.radio("Choose a graph type:", ("Default Example", "Create your own"))
+
+    if option == "Default Example":
+        # Default weighted graph example
+        G = nx.Graph()
+
+        G.add_edge("a", "b", weight=0.6)
+        G.add_edge("a", "c", weight=0.2)
+        G.add_edge("c", "d", weight=0.1)
+        G.add_edge("c", "e", weight=0.7)
+        G.add_edge("c", "f", weight=0.9)
+        G.add_edge("a", "d", weight=0.3)
+
+        elarge = [(u, v) for (u, v, d) in G.edges(data=True) if d["weight"] > 0.5]
+        esmall = [(u, v) for (u, v, d) in G.edges(data=True) if d["weight"] <= 0.5]
+
+        pos = nx.spring_layout(G, seed=7)  # positions for all nodes - seed for reproducibility
+
+        # nodes
+        nx.draw_networkx_nodes(G, pos, node_size=700)
+
+        # edges
+        nx.draw_networkx_edges(G, pos, edgelist=elarge, width=6)
+        nx.draw_networkx_edges(
+            G, pos, edgelist=esmall, width=6, alpha=0.5, edge_color="b", style="dashed"
+        )
+
+        # node labels
+        nx.draw_networkx_labels(G, pos, font_size=20, font_family="sans-serif")
+        # edge weight labels
+        edge_labels = nx.get_edge_attributes(G, "weight")
+        nx.draw_networkx_edge_labels(G, pos, edge_labels)
+
+        ax = plt.gca()
+        ax.margins(0.08)
+        plt.axis("off")
+        plt.tight_layout()
+        st.pyplot(plt)
+
+    elif option == "Create your own":
+        # User can create their own graph
+        nodes = st.text_input("Enter nodes (comma-separated):", "a,b,c,d,e,f").split(',')
+        nodes = [node.strip() for node in nodes]
+
+        G_custom = nx.Graph()
+
+        for i in range(len(nodes)):
+            for j in range(i + 1, len(nodes)):
+                weight = st.number_input(f"Weight between {nodes[i]} and {nodes[j]}:", min_value=0.0, value=1.0)
+                G_custom.add_edge(nodes[i], nodes[j], weight=weight)
+
+        # Create layout for visualization
+        pos = nx.spring_layout(G_custom, seed=7)
+        
+        # Determine edges based on weight
+        elarge = [(u, v) for (u, v, d) in G_custom.edges(data=True) if d["weight"] > 0.5]
+        esmall = [(u, v) for (u, v, d) in G_custom.edges(data=True) if d["weight"] <= 0.5]
+
+        # Draw the graph
+        nx.draw_networkx_nodes(G_custom, pos, node_size=700)
+        nx.draw_networkx_edges(G_custom, pos, edgelist=elarge, width=6)
+        nx.draw_networkx_edges(
+            G_custom, pos, edgelist=esmall, width=6, alpha=0.5, edge_color="b", style="dashed"
+        )
+        nx.draw_networkx_labels(G_custom, pos, font_size=20, font_family="sans-serif")
+        edge_labels = nx.get_edge_attributes(G_custom, "weight")
+        nx.draw_networkx_edge_labels(G_custom, pos, edge_labels)
+
+        ax = plt.gca()
+        ax.margins(0.08)
+        plt.axis("off")
+        plt.tight_layout()
+        st.pyplot(plt)
+
+# Display Drawing: Weighted Graph if selected
+if sidebar_option == "Drawing: Weighted Graph":
+    display_weighted_graph()
+
 from networkx.algorithms.approximation import christofides
 
 # Function to display Traveling Salesman Problem