<｜begin▁of▁sentence｜>### Instruction:
As a network analyst at a healthcare facility, you are often tasked with visualizing patient care pathways and healthcare network structures. Recently, you have been asked to create a visualization of a specific network graph using LCF notation to represent the connections between different healthcare facilities. The graph is described by the number of vertices, which in this case is 8, and a list of shifts indicating how edges are added to form a 3-regular Hamiltonian graph.

Using your expertise in network analysis, you will need to utilize the networkx library to generate the graph based on the provided shifts and then visualize it using the igraph library. This visualization will help stakeholders understand the interconnectedness of healthcare facilities and optimize resource allocation for patient care.

Your knowledge and skills in applying evidence-based practices and collaborating with other professionals will be crucial in accurately representing the healthcare network structure in the visualization, ultimately contributing to improved health outcomes and quality of life for patients and communities.
### Response:
from igraph import Graph

# Generate a cubic graph using LCF notation
vertex_count = 8
shifts = [1, -2, 2, -1, 2, -2, 1, -1]
repeats = 1

# Create the graph from LCF notation
graph = Graph.LCF(vertex_count, shifts, repeats)

# Print vertex and edge count
print(f'Vertices: {graph.vcount()}')
print(f'Edges: {graph.ecount()}')

# Draw the graph
graph.vs['label'] = range(graph.vcount())
plot = ig.plot(graph)
plot.show()
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