<｜begin▁of▁sentence｜>### Instruction:
As a Substance Abuse Counselor, you're often tasked with evaluating and guiding individuals or groups dealing with substance abuse, addiction, or dependency issues. This involves providing support, therapy, and education to aid in their recovery journey. Imagine you're working with a client who is struggling with relapse prevention strategies. They're finding it difficult to visualize how certain patterns of behavior lead to relapse.

In this scenario, think of your role akin to that of an AbstractCairoDrawer creating a custom edge drawer. You need to find a way to illustrate to your client how certain actions loop back into the cycle of addiction. By utilizing the draw_loop_edge method, you can create visual aids that demonstrate these patterns effectively. This approach allows you to delve deeper into their triggers, behaviors, and coping mechanisms, ultimately aiding in the development of more robust relapse prevention strategies.
### Response:
from igraph import Graph, plot
from igraph.drawing import AbstractCairoDrawer

# Create a custom edge drawer class by inheriting from AbstractCairoDrawer
class CustomCairoEdgeDrawer(AbstractCairoDrawer):
    def draw_loop_edge(self, edge, vertex):
        # Implement custom loop edge drawing
        super().draw_loop_edge(edge, vertex)
        # Additional customizations can be made here

# Now we will use this custom edge drawer in plotting a graph
g = Graph([(0,0), (1,2), (2,3)])  # Example graph with a loop edge
g.vs['label'] = range(g.vcount())
g.es['color'] = 'black'

# We need to override the default plot function to use our custom edge drawer
original_plot = plot
plot = lambda graph, *args, **kwds: original_plot(graph, *args, **kwds, edge_drawer=CustomCairoEdgeDrawer)

plot(g, target='output.png')
plot = original_plot  # Reset plot to original after use
<|EOT|>
