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Update app.py
Browse files
app.py
CHANGED
@@ -23,7 +23,108 @@ sidebar_option = st.sidebar.radio("Select an option",
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"Drawing: Simple Path", "Drawing: Spectral Embedding", "Drawing: Traveling Salesman Problem",
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"Drawing: Weighted Graph", "3D Drawing: Animations of 3D Rotation", "3D Drawing: Basic Matplotlib",
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"Graph: DAG - Topological Layout", "Graph: Erdos Renyi", "Graph: Karate Club", "Graph: Minimum Spanning Tree",
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"Graph: Triads", "Algorithms: Cycle Detection", "Algorithms: Greedy Coloring"])
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def plot_greedy_coloring(graph):
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# Apply greedy coloring
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"Drawing: Simple Path", "Drawing: Spectral Embedding", "Drawing: Traveling Salesman Problem",
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"Drawing: Weighted Graph", "3D Drawing: Animations of 3D Rotation", "3D Drawing: Basic Matplotlib",
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"Graph: DAG - Topological Layout", "Graph: Erdos Renyi", "Graph: Karate Club", "Graph: Minimum Spanning Tree",
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"Graph: Triads", "Algorithms: Cycle Detection", "Algorithms: Greedy Coloring", "Algorithms: Find Shortest Path"])
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def plot_shortest_path(graph, start_node, end_node):
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# Find the shortest path from start_node to end_node
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path = nx.shortest_path(graph, start_node, end_node, weight="weight")
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st.write("Shortest Path:", path)
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# Create a list of edges in the shortest path
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path_edges = list(zip(path, path[1:]))
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# Create a list of all edges, and assign colors based on whether they are in the shortest path or not
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edge_colors = [
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"red" if edge in path_edges or tuple(reversed(edge)) in path_edges else "black"
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for edge in graph.edges()
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]
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# Visualize the graph
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pos = nx.spring_layout(graph)
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nx.draw_networkx_nodes(graph, pos)
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nx.draw_networkx_edges(graph, pos, edge_color=edge_colors)
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nx.draw_networkx_labels(graph, pos)
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nx.draw_networkx_edge_labels(
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graph, pos, edge_labels={(u, v): d["weight"] for u, v, d in graph.edges(data=True)}
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)
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plt.title(f"Shortest Path from {start_node} to {end_node}")
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st.pyplot(plt)
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def algorithms_shortest_path():
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st.title("Algorithms: Find Shortest Path")
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# Option to choose between creating your own or using the default example
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graph_mode = st.radio(
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"Choose a Mode:",
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("Default Example", "Create Your Own"),
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help="The default example shows a predefined graph, or you can create your own."
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)
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if graph_mode == "Default Example":
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# Create a predefined graph with nodes and weighted edges
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G = nx.Graph()
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G.add_nodes_from(["A", "B", "C", "D", "E", "F", "G", "H"])
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G.add_edge("A", "B", weight=4)
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G.add_edge("A", "H", weight=8)
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G.add_edge("B", "C", weight=8)
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G.add_edge("B", "H", weight=11)
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G.add_edge("C", "D", weight=7)
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G.add_edge("C", "F", weight=4)
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G.add_edge("C", "I", weight=2)
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G.add_edge("D", "E", weight=9)
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G.add_edge("D", "F", weight=14)
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G.add_edge("E", "F", weight=10)
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G.add_edge("F", "G", weight=2)
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G.add_edge("G", "H", weight=1)
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G.add_edge("G", "I", weight=6)
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G.add_edge("H", "I", weight=7)
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# Set default start and end nodes
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start_node = "A"
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end_node = "E"
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st.write(f"Finding the shortest path from {start_node} to {end_node}")
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plot_shortest_path(G, start_node, end_node)
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elif graph_mode == "Create Your Own":
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st.write("### Create Your Own Graph")
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# Input for nodes
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nodes_input = st.text_area("Enter nodes (e.g., A, B, C, D, E, F, G, H):")
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edges_input = st.text_area("Enter edges with weights (e.g., (A, B, 4), (B, C, 8)):").strip()
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# Input for start and end nodes
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start_node = st.text_input("Enter start node (e.g., A):")
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end_node = st.text_input("Enter end node (e.g., E):")
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if st.button("Generate Graph"):
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if nodes_input and edges_input and start_node and end_node:
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try:
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# Parse the input for nodes and edges
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nodes = nodes_input.split(",")
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edges = [
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tuple(edge.strip()[1:-1].split(",") + [edge.strip().split(",")[-1]])
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for edge in edges_input.split("),")
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]
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edges = [
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(edge[0], edge[1], int(edge[2])) for edge in edges if len(edge) == 3
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]
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# Create the graph and add nodes and edges
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G = nx.Graph()
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G.add_nodes_from(nodes)
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G.add_weighted_edges_from(edges)
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st.write("Custom Graph:", G.edges())
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plot_shortest_path(G, start_node, end_node)
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except Exception as e:
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st.error(f"Error creating the graph: {e}")
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else:
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st.error("Please enter valid nodes, edges, and start/end nodes.")
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if sidebar_option == "Algorithms: Find Shortest Path":
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algorithms_shortest_path()
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def plot_greedy_coloring(graph):
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# Apply greedy coloring
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