<｜begin▁of▁sentence｜>### Instruction:
Picture this: You're in the studio, and you've got a mix that's represented by a network of sound channels, each channel connecting with others, just like a web of cables and patch points. Now, this network is laid out like so: channels are linked as pairs [(1, 2), (1, 3), (2, 3), (3, 4), (4, 2), (5, 1), (5, 4)]. Each channel's connection count is like a degree in a graph.

You're thinking about a hypothetical new mixing console that could automatically check the feasibility of this network based on its degree sequence—basically, if this pattern of channels could actually be plugged in without any mismatch in the number of cables and ports. In geek terms, that's whether the degree sequence is pseudographical.

The software could use a function, something akin to NetworkX's is_pseudographical, to quickly tell us if this connectivity map checks out. Now, without diving into the technicals, does this scenario paint a clear picture of what we're looking to figure out here with that function and our network of channels?
### Response:
import networkx as nx

# Create a graph
G = nx.Graph()
G.add_edges_from([(1, 2), (1, 3), (2, 3), (3, 4), (4, 2), (5, 1), (5, 4)])

# Get the degree sequence of the graph
sequence = [d for _, d in G.degree()]

# Check if the degree sequence is pseudographical
valid = nx.is_pseudographical(sequence)

print('Is the degree sequence pseudographical?', valid)
<|EOT|>
