app.py

app.py

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+import streamlit as st
+import networkx as nx
+import plotly.graph_objects as go
+import string
+import random
+import heapq
+
+
+# generate the graph
+def generate_graph():
+    alphabet = list(string.ascii_uppercase)
+    node_labels = alphabet + ['A' + letter for letter in alphabet[:22]]
+
+    G = nx.Graph()
+    G.add_nodes_from(node_labels)
+
+    for _ in range(94):
+        node1, node2 = random.sample(node_labels, 2)
+        weight = random.randint(1, 10)
+        G.add_edge(node1, node2, weight=weight)
+
+    pos = {node: (random.uniform(-10, 10), random.uniform(-10, 10), random.uniform(-10, 10)) for node in node_labels}
+
+    return G, pos
+
+
+# visualise the 3D graph
+def visualize_3d_graph_plotly(G, pos, path=None):
+    edge_trace = []
+    path_edge_trace = []
+    node_x, node_y, node_z = [], [], []
+    node_text = []
+
+    for node in G.nodes():
+        x, y, z = pos[node]
+        node_x.append(x)
+        node_y.append(y)
+        node_z.append(z)
+        node_text.append(node)
+
+    for edge in G.edges():
+        x0, y0, z0 = pos[edge[0]]
+        x1, y1, z1 = pos[edge[1]]
+        edge_trace.append(go.Scatter3d(x=[x0, x1], y=[y0, y1], z=[z0, z1],
+                                       mode='lines', line=dict(color='gray', width=2)))
+
+    if path:
+        path_edges = list(zip(path, path[1:]))
+        for edge in path_edges:
+            x0, y0, z0 = pos[edge[0]]
+            x1, y1, z1 = pos[edge[1]]
+            path_edge_trace.append(go.Scatter3d(x=[x0, x1], y=[y0, y1], z=[z0, z1],
+                                                mode='lines', line=dict(color='blue', width=4)))
+
+    node_trace = go.Scatter3d(x=node_x, y=node_y, z=node_z,
+                              mode='markers+text',
+                              text=node_text,
+                              textposition='top center',
+                              marker=dict(size=8, color='skyblue'),
+                              hoverinfo='text')
+
+    fig = go.Figure(data=edge_trace + path_edge_trace + [node_trace],
+                    layout=go.Layout(title='3D Graph Visualization',
+                                     showlegend=False,
+                                     width=1000,
+                                     height=800,
+                                     scene=dict(xaxis=dict(showbackground=False),
+                                                yaxis=dict(showbackground=False),
+                                                zaxis=dict(showbackground=False))))
+    return fig
+
+
+# Dijkstra's Algorithm implementation
+def dijkstra_3d(graph, start, goal):
+    queue = [(0, start)]
+    distances = {node: float('inf') for node in graph.nodes}
+    distances[start] = 0
+    previous_nodes = {node: None for node in graph.nodes}
+
+    while queue:
+        current_distance, current_node = heapq.heappop(queue)
+
+        if current_node == goal:
+            break
+
+        for neighbor, attributes in graph[current_node].items():
+            weight = attributes['weight']
+            distance = current_distance + weight
+
+            if distance < distances[neighbor]:
+                distances[neighbor] = distance
+                previous_nodes[neighbor] = current_node
+                heapq.heappush(queue, (distance, neighbor))
+
+    path = []
+    current_node = goal
+    while current_node is not None:
+        path.insert(0, current_node)
+        current_node = previous_nodes[current_node]
+
+    return path, distances[goal]
+
+
+# Streamlit app
+def main():
+    st.title("3D Graph Dijkstra's Algorithm Visualization")
+
+    st.sidebar.header("Graph Options")
+    G, pos = generate_graph()
+
+    nodes = list(G.nodes)
+    start_node = st.sidebar.selectbox("Select Start Point:", nodes)
+    goal_node = st.sidebar.selectbox("Select Goal Point:", nodes)
+
+    if st.sidebar.button("Run Algorithm"):
+        shortest_path, shortest_distance = dijkstra_3d(G, start_node, goal_node)
+        st.write(f"**Shortest path from {start_node} to {goal_node}:** {shortest_path}")
+        st.write(f"**Shortest distance:** {shortest_distance}")
+        fig = visualize_3d_graph_plotly(G, pos, path=shortest_path)
+    else:
+        fig = visualize_3d_graph_plotly(G, pos)
+
+    st.plotly_chart(fig)
+
+
+if __name__ == "__main__":
+    main()