Update app.py

app.py

@@ -20,7 +20,8 @@ sidebar_option = st.sidebar.radio("Select an option",
                                   "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: Weighted Graph", "3D Drawing: Animations of 3D Rotation", "3D Drawing: Basic Matplotlib"])
+                                  "Drawing: Weighted Graph", "3D Drawing: Animations of 3D Rotation", "3D Drawing: Basic Matplotlib",
+                                  "Graphviz Layout: Decomposition"])
 
 # Helper function to draw and display graph
 def draw_graph(G, pos=None, title="Graph Visualization"):
@@ -28,6 +29,100 @@ 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)
 
+# Default example code
+def default_example_decomposition():
+    # Create a Directed Graph (Bayesian Network)
+    B = nx.DiGraph()
+    B.add_nodes_from(["A", "B", "C", "D", "E", "F"])
+    B.add_edges_from(
+        [("A", "B"), ("A", "C"), ("B", "D"), ("B", "F"), ("C", "E"), ("E", "F")]
+    )
+
+    options = {"with_labels": True, "node_color": "white", "edgecolors": "blue"}
+
+    fig = plt.figure(figsize=(6, 9))
+    axgrid = fig.add_gridspec(3, 2)
+
+    ax1 = fig.add_subplot(axgrid[0, 0])
+    ax1.set_title("Bayesian Network")
+    pos = nx.nx_agraph.graphviz_layout(B, prog="neato")
+    nx.draw_networkx(B, pos=pos, **options)
+
+    mg = nx.moral_graph(B)
+    ax2 = fig.add_subplot(axgrid[0, 1], sharex=ax1, sharey=ax1)
+    ax2.set_title("Moralized Graph")
+    nx.draw_networkx(mg, pos=pos, **options)
+
+    jt = nx.junction_tree(B)
+    ax3 = fig.add_subplot(axgrid[1:, :])
+    ax3.set_title("Junction Tree")
+    ax3.margins(0.15, 0.25)
+    nsize = [2000 * len(n) for n in list(jt.nodes())]
+    pos = nx.nx_agraph.graphviz_layout(jt, prog="neato")
+    nx.draw_networkx(jt, pos=pos, node_size=nsize, **options)
+
+    plt.tight_layout()
+    st.pyplot(fig)
+
+# Create your own graph option
+def create_own_graph_decomposition():
+    # Input fields to customize the graph
+    nodes = st.text_area("Enter nodes (comma separated)", "A, B, C, D, E, F")
+    edges = st.text_area("Enter edges (comma separated)", "A,B;A,C;B,D;B,F;C,E;E,F")
+    
+    # Add a button to generate the graph
+    generate_button = st.button("Generate Graph")
+
+    if generate_button:
+        # Generate graph and layout
+        G = nx.DiGraph()
+        node_list = nodes.split(",")
+        edge_list = edges.split(";")
+        G.add_nodes_from(node_list)
+        for edge in edge_list:
+            G.add_edge(*edge.split(","))
+        
+        options = {"with_labels": True, "node_color": "white", "edgecolors": "blue"}
+        fig = plt.figure(figsize=(6, 9))
+        axgrid = fig.add_gridspec(3, 2)
+
+        ax1 = fig.add_subplot(axgrid[0, 0])
+        ax1.set_title("Bayesian Network")
+        pos = nx.nx_agraph.graphviz_layout(G, prog="neato")
+        nx.draw_networkx(G, pos=pos, **options)
+
+        mg = nx.moral_graph(G)
+        ax2 = fig.add_subplot(axgrid[0, 1], sharex=ax1, sharey=ax1)
+        ax2.set_title("Moralized Graph")
+        nx.draw_networkx(mg, pos=pos, **options)
+
+        jt = nx.junction_tree(G)
+        ax3 = fig.add_subplot(axgrid[1:, :])
+        ax3.set_title("Junction Tree")
+        ax3.margins(0.15, 0.25)
+        nsize = [2000 * len(n) for n in list(jt.nodes())]
+        pos = nx.nx_agraph.graphviz_layout(jt, prog="neato")
+        nx.draw_networkx(jt, pos=pos, node_size=nsize, **options)
+
+        plt.tight_layout()
+        st.pyplot(fig)
+
+if sidebar_option == "Graphviz Layout: Decomposition":
+    st.title("Graphviz Layout: Decomposition")
+
+    # Provide options for Default Example or Custom Graph
+    graph_mode = st.radio(
+        "Choose a Mode:",
+        ("Default Example", "Create Your Own"),
+        help="Default example shows a decomposition of a Bayesian network, or you can create your own custom graph."
+    )
+
+    # Display the chosen option
+    if graph_mode == "Default Example":
+        default_example_decomposition()
+    elif graph_mode == "Create Your Own":
+        create_own_graph_decomposition()
+
 if sidebar_option == "3D Drawing: Animations of 3D Rotation":
     st.title("3D Drawing: Animations of 3D Rotation")