<｜begin▁of▁sentence｜>### Instruction:
As a corporate trainer, you are tasked with designing a team building exercise for a company retreat. Your goal is to create a network representation of the employees, grouping them into three different teams of sizes 10, 15, and 25 members. The connections within each team should be very strong, with a probability of 0.8, reflecting the close knit relationships within each team. However, connections between different teams should be much weaker, with a probability of 0.1, to represent limited interactions between the teams. How can you use the igraph's SBM function to generate this network representation for the exercise?
### Response:
import igraph as ig
import numpy as np

# Block sizes
sizes = [10, 15, 25]
# Block connection probabilities
probs = [[0.8, 0.1, 0.05],
          [0.1, 0.7, 0.1],
          [0.05, 0.1, 0.8]]

# Generate a graph based on a stochastic block model
block_model_graph = ig.Graph.SBM(n=sum(sizes), p=probs, block_sizes=sizes, directed=False)

print(block_model_graph)
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