Update app.py

app.py

@@ -217,87 +217,93 @@ if sidebar_option == "Drawing: Traveling Salesman Problem":
     display_tsp()
 
 # Function to display Drawing: Spectral Embedding
-# Function to display Drawing: Spectral Embedding
+import matplotlib.pyplot as plt
+import networkx as nx
+import streamlit as st
+import numpy as np
+
 def display_spectral_embedding():
     st.title("Drawing: Spectral Embedding")
 
     option = st.radio("Choose a graph type:", ("Default Example", "Create your own"))
 
+    def draw_graph_with_arrows(G, ax, pos, labels, options):
+        """
+        Draws the graph with arrows pointing to nodes and avoids label overlap.
+        """
+        # Draw nodes and edges
+        nx.draw_networkx_nodes(G, pos, ax=ax, **options)
+        nx.draw_networkx_edges(G, pos, ax=ax)
+
+        # Add labels with arrows
+        for node, (x, y) in pos.items():
+            label = labels[node]
+            ax.annotate(
+                label,
+                xy=(x, y),  # Node position
+                xytext=(x + 0.05, y + 0.05),  # Offset for arrow
+                arrowprops=dict(arrowstyle="->", color="gray", lw=1),
+                fontsize=8,
+                bbox=dict(boxstyle="round,pad=0.3", edgecolor="gray", facecolor="white", alpha=0.8)
+            )
+
     if option == "Default Example":
-        # Default example of spectral embedding with a grid graph
-        options = {"node_color": "C0", "node_size": 100, "with_labels": True}
+        options = {"node_color": "C0", "node_size": 100}
         G = nx.grid_2d_graph(6, 6)
+        pos = nx.spectral_layout(G)
+        labels = {node: str(node) for node in G.nodes()}
 
         fig, axs = plt.subplots(3, 3, figsize=(12, 12))
         axs = axs.flatten()
 
-        for i in range(7):  # Looping over 7 images
-            if i == 0:
-                nx.draw_spectral(G, **options, ax=axs[i])
-            elif i == 1:
-                G.remove_edge((2, 2), (2, 3))
-                nx.draw_spectral(G, **options, ax=axs[i])
-            elif i == 2:
-                G.remove_edge((3, 2), (3, 3))
-                nx.draw_spectral(G, **options, ax=axs[i])
-            elif i == 3:
-                G.remove_edge((2, 2), (3, 2))
-                nx.draw_spectral(G, **options, ax=axs[i])
-            elif i == 4:
-                G.remove_edge((2, 3), (3, 3))
-                nx.draw_spectral(G, **options, ax=axs[i])
-            elif i == 5:
-                G.remove_edge((1, 2), (1, 3))
-                nx.draw_spectral(G, **options, ax=axs[i])
-            elif i == 6:
-                G.remove_edge((4, 2), (4, 3))
-                nx.draw_spectral(G, **options, ax=axs[i])
-
-        # Hide the last two subplots (8th and 9th)
+        for i in range(7):
+            if i > 0:
+                # Remove edges in sequence to modify the graph
+                edges_to_remove = [((2, 2), (2, 3)), ((3, 2), (3, 3)), ((2, 2), (3, 2)),
+                                   ((2, 3), (3, 3)), ((1, 2), (1, 3)), ((4, 2), (4, 3))]
+                if i <= len(edges_to_remove):
+                    G.remove_edge(*edges_to_remove[i - 1])
+            draw_graph_with_arrows(G, axs[i], pos, labels, options)
+
         for j in range(7, 9):
-            fig.delaxes(axs[j])  # Delete the extra axes
+            fig.delaxes(axs[j])  # Delete unused subplots
 
         st.pyplot(fig)
 
     elif option == "Create your own":
-        # User can interactively modify the grid and see the results
         grid_size = st.slider("Choose grid size (n x n):", min_value=3, max_value=10, value=6)
         G_custom = nx.grid_2d_graph(grid_size, grid_size)
-
-        # List all edges to allow removal
+        pos = nx.spectral_layout(G_custom)
+        labels = {node: str(node) for node in G_custom.nodes()}
         all_edges = list(G_custom.edges())
 
-        # Collect user input for edges to remove (before showing the "Generate" button)
         selected_edges_per_graph = []
-        for i in range(7):  # Loop over 7 graphs
-            selected_edges = st.multiselect(f"Select edges to remove for graph {i+1}:",
-                                            options=[str(edge) for edge in all_edges])
+        for i in range(7):
+            selected_edges = st.multiselect(
+                f"Select edges to remove for graph {i + 1}:",
+                options=[str(edge) for edge in all_edges]
+            )
             selected_edges_per_graph.append(selected_edges)
 
-        # Add "Generate" button after edge selection
         generate_button = st.button("Generate Graph")
 
         if generate_button:
             fig, axs = plt.subplots(3, 3, figsize=(12, 12))
             axs = axs.flatten()
 
-            # Loop through each subplot and allow edge removal individually
-            for i in range(7):  # Loop over 7 graphs
+            for i in range(7):
                 edges_to_remove = [tuple(eval(edge)) for edge in selected_edges_per_graph[i]]
-
-                # Remove the selected edges
                 G_custom_copy = G_custom.copy()
                 G_custom_copy.remove_edges_from(edges_to_remove)
 
-                # Draw the graph with removed edges and labels
-                nx.draw_spectral(G_custom_copy, **{"node_color": "C0", "node_size": 100, "with_labels": True}, ax=axs[i])
+                draw_graph_with_arrows(G_custom_copy, axs[i], pos, labels, options)
 
-            # Hide the last two subplots (8th and 9th)
             for j in range(7, 9):
-                fig.delaxes(axs[j])  # Delete the extra axes
+                fig.delaxes(axs[j])  # Delete unused subplots
 
             st.pyplot(fig)
 
+
 # Display Drawing: Spectral Embedding if selected
 if sidebar_option == "Drawing: Spectral Embedding":
     display_spectral_embedding()