<｜begin▁of▁sentence｜>### Instruction:
Imagine you're sculpting a digital masterpiece, a dodecahedron—the kind that takes its shape from the realm of platonic solids, with equal pentagons gracing every face. In the blueprint of its virtual architecture, each corner point, or vertex, connects in harmonious geometry. Visualize this dodecahedron not just as a static object, but as a network of connections within your 3D modeling software.

As an artist, you understand that to bring out the intricacy of its design, you must understand the relationships within this interconnected web. Consider this your artistic challenge: can you delve into the essence of your dodecahedron and delineate the intricate web of its internal symmetries?

More specifically, can you draw out the character of this network, tracing how each vertex relates to the others through a set of numerical parameters—sort of a DNA for your digital sculpture—that will lay bare its hidden order, the underlying pattern that governs the distances within this polyhedral arrangement? 

This set of numbers, your task list, akin to an intersection array, will tell you the count of steps from each vertex to its neighbors, then the next set of neighbors, revealing the intimate dance of proximity and separation that makes your dodecahedron not just a structure, but a map of relationships. Unraveling this pattern is akin to finding the secret rhythm to which all elements of your visual symphony are choreographed. 

Incorporate this knowledge, and your digital creation will resonate with a harmony felt in every polygonal bond and every vertex kiss. This is your canvas, your network, your digital dodecahedron—unfold its mysteries.
### Response:
import networkx as nx

# Create a dodecahedral graph, which is distance-regular
G = nx.dodecahedral_graph()

# Get the intersection array of the graph
b, c = nx.intersection_array(G)

# Calculate the global parameters for the graph
parameters = list(nx.global_parameters(b, c))

print(parameters)
<|EOT|>
