<｜begin▁of▁sentence｜>### Instruction:
As a market research analyst, you are tasked with understanding the connections and relationships between different types of consumers in a given market. Imagine you have collected data on three different types of consumers, and you want to analyze their interactions. Using network analysis techniques, you can create a graph where vertices representing consumers of the same type have a higher likelihood of being connected than vertices of different types. This would help you gain insights into how consumers within each type are more likely to engage with each other, which can guide decision-making and support marketing strategies.
### Response:
from igraph import Graph

# Define the vertex types, there should be one type per vertex
vertex_types = [0, 0, 1, 1, 2, 2]

# Define the connection probabilities
# Here it is defined that the vertices of same type (diagonal) have a higher chance of connections
type_probabilities = [[0.8, 0.1, 0.05], [0.1, 0.7, 0.05], [0.05, 0.05, 0.9]]

# Generate the graph
preference_graph = Graph.Preference(len(vertex_types), type_probabilities, vertex_types)

# Print its summary
print(preference_graph.summary())
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