Matplotlib 및 networkx를 사용하여 방향성 그래프를 그리는 Python 코드를 작성합니다. 예시 데이터를 사용하여 코드를 사용하는 방법을 보여줍니다. 필요한 모든 import 문을 포함하세요.
응답
importmatplotlib.pyplotaspltimportnetworkxasnx# Example data: a directed graph with nodes and edgesnodes=['A','B','C','D','E']edges=[('A','B'),('A','C'),('B','D'),('C','E'),('D','E')]# Create a directed graph objectgraph=nx.DiGraph()# Add nodes to the graphgraph.add_nodes_from(nodes)# Add edges to the graphgraph.add_edges_from(edges)# Draw the graph using matplotlibnx.draw(graph,with_labels=True,node_color='lightblue',node_size=500,font_size=10,arrowsize=20)# Display the graphplt.show()
설명:
필요한 라이브러리 가져오기:
그래프를 표시하기 위한 matplotlib.pyplot
그래프를 만들고 조작하기 위한 networkx
예시 데이터 정의:
nodes: 노드 이름의 목록
edges: 각 튜플이 있는 방향성 에지를 나타내는 튜플 목록(소스 노드, 타겟 노드)
방향 그래프 객체 만들기:
graph = nx.DiGraph(): 빈 지향 그래프 객체를 만듭니다.
노드 및 에지 추가:
graph.add_nodes_from(nodes): nodes 목록의 모든 노드를 그래프에 추가합니다.
graph.add_edges_from(edges): edges 목록의 모든 에지를 그래프에 추가합니다.
그래프 그리기:
nx.draw(graph, ...): Matplotlib을 사용하여 그래프를 그립니다.
with_labels=True: 노드 라벨을 표시합니다.
node_color='lightblue': 노드 색상을 연한 파란색으로 설정합니다.
node_size=500: 노드 크기를 설정합니다.
font_size=10: 라벨의 글꼴 크기를 설정합니다.
arrowsize=20: 가장자리의 화살표 크기를 설정합니다.
그래프 표시:
plt.show(): 표시된 그래프를 보여줍니다.
출력:
이 코드는 지정된 노드와 에지로 방향 그래프 시각화를 생성합니다. 노드는 라벨이 지정되고 연한 파란색으로 표시되며, 에지의 방향을 나타내는 화살표로 연결됩니다.
[[["이해하기 쉬움","easyToUnderstand","thumb-up"],["문제가 해결됨","solvedMyProblem","thumb-up"],["기타","otherUp","thumb-up"]],[["이해하기 어려움","hardToUnderstand","thumb-down"],["잘못된 정보 또는 샘플 코드","incorrectInformationOrSampleCode","thumb-down"],["필요한 정보/샘플이 없음","missingTheInformationSamplesINeed","thumb-down"],["번역 문제","translationIssue","thumb-down"],["기타","otherDown","thumb-down"]],["최종 업데이트: 2025-09-04(UTC)"],[],[],null,["Write Python code to visualize a weighted directed graph with example data\n\n|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| You can query a model directly and test the results returned when using different parameter values with the Cloud console, or by calling the Vertex AI API directly. - For an example of using the Vertex AI API, see [Quickstart using the Vertex AI API](/vertex-ai/generative-ai/docs/start/quickstarts/api-quickstart). - To view this sample in the Cloud console: [Go to Google Cloud console](https://console.cloud.google.com/vertex-ai/generative/language/prompt-examples/Python%20visualization) \u003cbr /\u003e ||\n| Prompt Freeform Write Python code to draw a directed graph using matplotlib and networkx. Show how to use the code with some example data. Include all necessary import statements. Response import matplotlib.pyplot as plt import networkx as nx # Example data: a directed graph with nodes and edges nodes = ['A', 'B', 'C', 'D', 'E'] edges = [('A', 'B'), ('A', 'C'), ('B', 'D'), ('C', 'E'), ('D', 'E')] # Create a directed graph object graph = nx.DiGraph() # Add nodes to the graph graph.add_nodes_from(nodes) # Add edges to the graph graph.add_edges_from(edges) # Draw the graph using matplotlib nx.draw(graph, with_labels=True, node_color='lightblue', node_size=500, font_size=10, arrowsize=20) # Display the graph plt.show() **Explanation:** 1. **Import necessary libraries:** 2. `matplotlib.pyplot` for plotting the graph. 3. `networkx` for creating and manipulating the graph. 4. **Define example data:** 5. `nodes`: A list of node names. 6. `edges`: A list of tuples representing directed edges, where each tuple is (source node, target node). 7. **Create a directed graph object:** 8. `graph = nx.DiGraph()`: Creates an empty directed graph object. 9. **Add nodes and edges:** 10. `graph.add_nodes_from(nodes)`: Adds all nodes from the `nodes` list to the graph. 11. `graph.add_edges_from(edges)`: Adds all edges from the `edges` list to the graph. 12. **Draw the graph:** 13. `nx.draw(graph, ...)`: Draws the graph using matplotlib. 14. `with_labels=True`: Displays node labels. 15. `node_color='lightblue'`: Sets the node color to light blue. 16. `node_size=500`: Sets the node size. 17. `font_size=10`: Sets the font size for labels. 18. `arrowsize=20`: Sets the arrow size for edges. 19. **Display the graph:** 20. `plt.show()`: Shows the plotted graph. **Output:** This code will generate a directed graph visualization with the specified nodes and edges. The nodes will be labeled, colored light blue, and connected by arrows representing the direction of the edges. | |------------------------|----------------------| | **Model:** | gemini-1.5-flash-001 | | **Temperature:** | 1 | | **Max output tokens:** | 8192 | | **TopK:** | 40 | | **TopP:** | 0.95 | |"]]
