Untitled

from matplotlib import pyplot as plt
import networkx as nx

# Create a mindmap structure for the linguistic principles
mindmap = {
    "Linguistic Principles": {
        "General Principles of Language Teaching": {
            "Naturalness": ["Listening and speaking before writing", "Natural exposure to language"],
            "Learning by Self-Doing": ["Active participation", "Practical exercises"],
            "Speaking": ["Focus on oral skills", "Auditory capabilities"],
            "Ratio and Sequence": ["Logical progression", "From simple to complex"],
            "Context and Situation": ["Real-world contexts", "Meaningful learning"]
        },
        "Principle of Selection": {
            "Focus Areas": ["Frequency", "Range", "Availability", "Teachability"],
            "Gradation": ["Simple to complex", "Logical sequencing"]
        },
        "Maxims of Teaching": {
            "Known to Unknown": [],
            "Simple to Complex": [],
            "Concrete to Abstract": [],
            "Particular to General": []
        },
        "Summary": ["Natural teaching methods", "Skill progression", "Context-based learning"]
    }
}

# Initialize a graph
G = nx.DiGraph()

# Recursive function to add nodes and edges
def add_nodes_edges(graph, parent, children):
    for key, value in children.items():
        graph.add_edge(parent, key)
        if isinstance(value, dict):
            add_nodes_edges(graph, key, value)
        elif isinstance(value, list):
            for item in value:
                graph.add_edge(key, item)

# Add nodes and edges to the graph
add_nodes_edges(G, "Linguistic Principles", mindmap["Linguistic Principles"])

# Draw the mindmap
plt.figure(figsize=(14, 10))
pos = nx.spring_layout(G, k=0.6)  # Positioning the nodes
nx.draw(G, pos, with_labels=True, node_size=5000, node_color="lightblue", font_size=10, font_weight="bold")
plt.title("Mindmap of Linguistic Principles", fontsize=15)
plt.show()