<｜begin▁of▁sentence｜>### Instruction:
As a science teacher, you're likely familiar with teaching students about networks and patterns within them. Imagine you're teaching a class about ecosystems, and you want to illustrate how different organisms interact with each other. You've created a model using a directed graph where each edge represents a relationship between two organisms. Now, you want to identify which relationships involve a single organism interacting with itself, essentially forming a loop within the ecosystem.

To accomplish this task, you'd use the `is_loop` function in the NetworkX Python library, which is like your toolset for analyzing the ecosystem model. By applying this function to your graph, you can determine which edges represent these self-interactions, providing insight into the dynamics of the ecosystem.
### Response:
import igraph as ig

# Creating a simple graph
edges = [(0, 1), (1, 2), (2, 3), (3, 0), (2, 2)]
g = ig.Graph(edges=edges, directed=True)

# Check for loops in the graph
loops = g.is_loop()
print('Loops:', loops)
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