<｜begin▁of▁sentence｜>### Instruction:
As a network analyst, you may encounter situations where you need to convert an undirected graph into a directed graph using Python's NetworkX library. Just as a psychiatrist diagnoses and manages mental illnesses, you can diagnose and manage the connections in a graph to ensure a clear understanding of the relationships between nodes.

In this analogy, consider the undirected graph as a network of interconnected individuals seeking mental health support. Your task is to transform these connections into a directed graph, reflecting the mutual understanding and support within the network.

By using the NetworkX library in Python, you can achieve this by creating two mutually opposite directed edges for each undirected edge in the graph. Once you have converted the graph, you can observe and analyze the new edge list to gain deeper insights into the network's dynamics and interconnected relationships.
### Response:
import igraph as ig

# Create an undirected graph with some edges
edges = [(0, 1), (0, 2), (1, 2), (1, 3)]
g = ig.Graph(edges=edges, directed=False)

# Convert the undirected graph to a directed graph
# with mutual edges for each undirected edge
directed_g = g.to_directed(mode='mutual')

# Print the directed edges
print(directed_g.get_edgelist())
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