<｜begin▁of▁sentence｜>### Instruction:
As a network analysis expert, you might be interested in using the CohesiveBlocks module in the networkx library to visualize the cohesive block structure of a given undirected graph. Imagine you are working on a project to analyze interactions in a social network, and you want to visualize the different levels of cohesion among groups of users in the network. By using the CohesiveBlocks module in networkx, you can effectively visualize the cohesive block structure and gain insights into the varying levels of cohesion within the network. This can be particularly useful for identifying subgroups with strong internal connections and understanding their interrelationships within the larger network.
### Response:
from igraph import Graph, plot
import igraph as ig
from igraph.drawing.text import TextDrawer

# read the graph file
graph = ig.read('graph_cohesion.gml')

# Get the cohesive block structure of the graph
blocks = graph.community_optimal_modularity().as_cover()

# Create a plot with 600x600 pixels
visual_style = {'vertex_size': 20, 'bbox': (600, 600), 'margin': 20}

# Now plot the graph
plot(blocks, **visual_style)
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