math.polygonal_graph.polygonal_graph_model() - Code Metrics - Inspection of "add networkx_mermaid handler" - erivlis/graphinate - Measure and Improve Code Quality continuously with Scrutinizer

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by Eran

created 2025-03-02 00:47 UTC

math.polygonal_graph.polygonal_graph_model() A

↳ Parent: math.polygonal_graph

Complexity

Conditions

Size

Total Lines	21
Code Lines	6

Duplication

Lines	0
Ratio	0 %

Importance

Changes

Metric	Value
eloc	6
dl	0
loc	21
rs	10
c	0
b	0
f	0
cc	1
nop	2

import networkx as nx

import graphinate

# import graphinate.modeling
from graphinate import GraphModel


def polygonal_graph_edges(edges_count: int):
    for i in range(1, edges_count):
        yield {'source': i, 'target': i + 1}
    yield {'source': edges_count, 'target': 1}


def polygonal_graph_model(name: str, number_of_sides: int) -> graphinate.GraphModel:
    """
    Create a polygonal graph model.

    Args:
        name (str): The Graph's name.
        number_of_sides (int): Number of sides in the polygon.

    Returns:
        GraphModel: A graph model representing a polygonal graph.
    """

    # Define GraphModel
    graph_model: GraphModel = graphinate.model(name)

    # Register edges supplier function
    @graph_model.edge()
    def edge():
        yield from polygonal_graph_edges(number_of_sides)

    return graph_model


model = polygonal_graph_model("Octagonal Graph", 8)

if __name__ == '__main__':
    # 1. Define Graph Builder
    builder = graphinate.builders.NetworkxBuilder(model=model)

    # Then
    # 2. Build the Graph object
    graph: nx.Graph = builder.build()

    # Then
    # 3. Option A - Output to console
    print(graph)

    # Or
    # 3. Option B - Output as a plot
    graphinate.materializers.plot(graph)


1			import networkx as nx
2
3			import graphinate
4
5			# import graphinate.modeling
6			from graphinate import GraphModel
7
8
9			def polygonal_graph_edges(edges_count: int):
10			for i in range(1, edges_count):
11			yield {'source': i, 'target': i + 1}
12			yield {'source': edges_count, 'target': 1}
13
14
15			def polygonal_graph_model(name: str, number_of_sides: int) -> graphinate.GraphModel:
16			"""
17			Create a polygonal graph model.
18
19			Args:
20			name (str): The Graph's name.
21			number_of_sides (int): Number of sides in the polygon.
22
23			Returns:
24			GraphModel: A graph model representing a polygonal graph.
25			"""
26
27			# Define GraphModel
28			graph_model: GraphModel = graphinate.model(name)
29
30			# Register edges supplier function
31			@graph_model.edge()
32			def edge():
33			yield from polygonal_graph_edges(number_of_sides)
34
35			return graph_model
36
37
38			model = polygonal_graph_model("Octagonal Graph", 8)
39
40			if __name__ == '__main__':
41			# 1. Define Graph Builder
42			builder = graphinate.builders.NetworkxBuilder(model=model)
43
44			# Then
45			# 2. Build the Graph object
46			graph: nx.Graph = builder.build()
47
48			# Then
49			# 3. Option A - Output to console
50			print(graph)
51
52			# Or
53			# 3. Option B - Output as a plot
54			graphinate.materializers.plot(graph)
55

erivlis / graphinate

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math.polygonal_graph.polygonal_graph_model() A

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