<｜begin▁of▁sentence｜>### Instruction:
As a software architect, envision you're designing a system for analyzing network data. Imagine you're tasked with developing a feature that computes the distribution of cluster sizes within a given vertex cover of a graph. Now, suppose you're working with a specific graph represented by the edges [(0, 1), (0, 2), (1, 2), (2, 3)], and you've been provided with a vertex cover comprising the vertices [0, 1, 2]. Your objective is to implement functionality that generates a histogram illustrating the sizes of clusters within this vertex cover. How would you approach integrating this feature into your system's architecture, ensuring it efficiently analyzes network data and accurately represents cluster distributions?
### Response:
from igraph import Graph
from igraph.clustering import VertexCover

# Create the graph
edges = [(0, 1), (0, 2), (1, 2), (2, 3)]
graph = Graph(edges=edges)

# Find a vertex cover for the graph
vertex_cover = VertexCover(graph, [0, 1, 2])

# Get the histogram of cluster sizes from the vertex cover
size_histogram = vertex_cover.size_histogram()

print(size_histogram)
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