<｜begin▁of▁sentence｜>### Instruction:
As a Quality Control Inspector tasked with scrutinizing the integrity of product shipment networks, we have a scenario where the strength of connections between distribution centers is catalogued in a detailed format; specifically, a nested dictionary structure that quantitatively outlines the weight of trade lanes connecting these hubs. This data manifest requires conversion into a NumPy array to facilitate quantitative analyses and to perform complex matrix manipulations, which are necessary to forecast network stresses and identify potential points of failure within our logistics framework. Could you advise on the method for translating this nested dictionary adjacency representation into a numerical array suitable for such advanced evaluation?
### Response:
import networkx as nx
import numpy as np

# Create a dictionary of dictionaries representing a graph
adj_dict = {
    0: {1: 1, 2: 1},
    1: {0: 1, 2: 1},
    2: {0: 1, 1: 1}
}

# Convert the dictionary representation to a NumPy array
array = nx.to_numpy_array(G=adj_dict)

print(array)
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