<｜begin▁of▁sentence｜>### Instruction:
As an environmental scientist, you're working on a project to assess and manage the environmental impacts of a water distribution network in a city. You have data about the network's structure, including the connections between different water distribution points. Now, you want to visualize this network using a layered Sugiyama layout to better understand the flow of water within the system and identify potential areas of concern. How can you accomplish this using the visualization tools provided by the igraph API?
### Response:
import igraph as ig

# Create an example directed acyclic graph (DAG)
edges = [(0, 1), (0, 2), (1, 3), (2, 3), (3, 4)]
g = ig.Graph(edges, directed=True)

# Compute the Sugiyama layout
layout, extended_graph = g.layout_sugiyama(layers=None, weights=None, hgap=2.0, vgap=2.0, maxiter=100, return_extended_graph=True)

# Optionally plot the graph
ig.plot(extended_graph, layout=layout, bbox=(300, 300), margin=20)
<|EOT|>
