<｜begin▁of▁sentence｜>### Instruction:
Imagine you're developing an innovative packaging design concept where the theme revolves around connectivity and sequence. Inspired by the idea of nodes and connections, you decide to represent a sequence of connections—like those in a network—across the surfaces of the packaging.

As part of this, your packaging design includes a sequence of symbols, each representing a node numbered from 0 to 4. These symbols are connected in a way that reflects the sequence of actual connections in a network: consecutive symbols are paired, forming connections akin to edges in a graph, specifically along the lines of (0, 1), (1, 2), (2, 3), and (3, 4).

You wish to add another layer of intrigue to the design by highlighting only certain connections—those where the sum of the symbol numbers at both ends is even, thus bringing a sense of balance and harmony to your design narrative.

In our digital representation of this concept using a graph, could you consider how to use NetworkX's FilterAtlas to create and present a view that emphasizes just those connections where the combined symbol numbers are even? This would then be transformed into a selective pattern on your physical packaging, presenting an engaging and mysterious visual for the customer to decode.

Your creative process would involve mapping this digital graph onto the physical space of your packaging. This way, you will create a design that tells a story not just through its aesthetic appeal, but also through the underlying narrative of connections it represents.
### Response:
import networkx as nx

# Create and populate a graph
G = nx.Graph()
G.add_nodes_from(range(5))
G.add_edges_from([(0, 1), (1, 2), (2, 3), (3, 4)])

# Define a filter function to filter edges
# This function will keep only the edges where the sum of the nodes is even
def filter_func(node1, node2):
    return (node1 + node2) % 2 == 0

# Apply the filter to the edge view of our graph
filtered_edges = nx.classes.coreviews.FilterAtlas(G._adj, filter_func)

# Print out the edges that meet our condition
for edge in filtered_edges:
    print(edge, list(filtered_edges[edge]))
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