Update app.py

app.py

@@ -5,7 +5,9 @@ import networkx as nx
 import numpy as np
 from operator import itemgetter
 import math  # Import the math module
-
+from mayavi import mlab
+from mayavi.mlab import pipeline
+from tempfile import TemporaryDirectory
 
 # Sidebar for selecting an option
 sidebar_option = st.sidebar.radio("Select an option", 
@@ -18,7 +20,7 @@ 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"])
+                                  "Drawing: Weighted Graph", "3D Drawing: Mayavi2"])
 
 # Helper function to draw and display graph
 def draw_graph(G, pos=None, title="Graph Visualization"):
@@ -26,6 +28,75 @@ 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)
 
+def create_3d_graph(graph_type="cycle_graph", num_nodes=20):
+    if graph_type == "cycle_graph":
+        G = nx.cycle_graph(num_nodes)
+    elif graph_type == "kite_graph":
+        G = nx.krackhardt_kite_graph()
+    elif graph_type == "grid_graph":
+        G = nx.grid_2d_graph(4, 5)
+    else:
+        G = nx.Graph()
+        G.add_edge('a', 'b')
+        G.add_edge('a', 'c')
+        G.add_edge('a', 'd')
+
+    # Reorder nodes from 0 to len(G) - 1
+    G = nx.convert_node_labels_to_integers(G)
+
+    # 3D spring layout
+    pos = nx.spring_layout(G, dim=3, seed=1001)
+    xyz = np.array([pos[v] for v in sorted(G)])
+    scalars = np.array(list(G.nodes())) + 5
+
+    mlab.figure(size=(800, 600), bgcolor=(1, 1, 1))
+
+    pts = mlab.points3d(
+        xyz[:, 0],
+        xyz[:, 1],
+        xyz[:, 2],
+        scalars,
+        scale_factor=0.1,
+        scale_mode="none",
+        colormap="Blues",
+        resolution=20,
+    )
+
+    pts.mlab_source.dataset.lines = np.array(list(G.edges()))
+    tube = pipeline.tube(pts, tube_radius=0.01)
+    pipeline.surface(tube, color=(0.8, 0.8, 0.8))
+    mlab.orientation_axes()
+
+    # Save to temporary file
+    with TemporaryDirectory() as temp_dir:
+        file_path = os.path.join(temp_dir, "graph.png")
+        mlab.savefig(file_path)
+        mlab.close()
+        return file_path
+
+if sidebar_option == "3D Drawing: Mayavi2":
+    st.title("3D Drawing: Mayavi2")
+
+    st.sidebar.subheader("Graph Settings")
+    graph_type = st.sidebar.selectbox(
+        "Select Graph Type", ["cycle_graph", "kite_graph", "grid_graph", "custom"]
+    )
+
+    if graph_type == "cycle_graph":
+        num_nodes = st.sidebar.slider("Number of Nodes", min_value=3, max_value=50, value=20)
+        file_path = create_3d_graph(graph_type, num_nodes=num_nodes)
+    elif graph_type == "grid_graph":
+        st.sidebar.write("Grid graph is preconfigured as a 4x5 grid.")
+        file_path = create_3d_graph(graph_type)
+    elif graph_type == "kite_graph":
+        st.sidebar.write("Krackhardt kite graph is preconfigured.")
+        file_path = create_3d_graph(graph_type)
+    elif graph_type == "custom":
+        st.sidebar.write("Custom graph example with predefined edges.")
+        file_path = create_3d_graph(graph_type)
+
+    st.image(file_path, caption="3D Graph Visualization", use_container_width=True)
+
 # Function to display Weighted Graph
 def display_weighted_graph():
     st.title("Drawing: Weighted Graph")