<｜begin▁of▁sentence｜>### Instruction:
Imagine you're working on a video project that requires you to group a variety of shots represented by numbers 0 through 9 based on their visual style. As the videographer, you have identified that shots can be paired if the numerical difference between them is a multiple of 3. Your editing software has a feature similar to NetworkX's 'equivalence_classes' function, which can automatically sort these shots into distinct visual style groups for you.

Could you envision how you might employ this feature in your video editing software to categorize these shots into their respective style groups? Additionally, what would the outcome of this categorization look like for your project?
### Response:
import networkx as nx

# Define the set of integers from 0 to 9
X = set(range(10))

# Define the equivalence relation: congruence modulo 3
def mod3(x, y):
    return (x - y) % 3 == 0

# Get the equivalence classes for the integers 0-9 under congruence modulo 3
equiv_classes = nx.utils.equivalence_classes(X, mod3)

# Print the equivalence classes
print(set(map(frozenset, equiv_classes)))
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