<｜begin▁of▁sentence｜>### Instruction:
Imagine we're crafting a unique piece of jewelry, not with metals and gemstones, but with a web of relationships, where each link represents a pathway of inspiration and influence. In this intricate design, the connections go in certain directions, much like in a directed graph. Our gemstones are nodes, and we weave them together with directional pathways or edges, analogous to the connections [1 to 2], [1 to 3], [3 to 1], [3 to 2], [3 to 5], [4 to 5], [4 to 6], [5 to 4], [5 to 6], [6 to 4].

What we're seeking to understand is a concept known as 'directed modularity' within this lattice of creativity, which could tell us how well-defined our clusters of influence are. It's much like ensuring balance and harmony in a jewelry piece, where each section contributes to the elegance of the whole without overpowering it.

So, in the artistry of our professional field, if we were to transpose this concept to the virtual jeweler's bench of NetworkX, how would we craft this 'directed modularity matrix' to evaluate the structural integrity and community strength of our design? Just as we craft our tangible art pieces, this matrix could reveal the hidden splendor within the patterned relationships of our creation.
### Response:
import networkx as nx

G = nx.DiGraph()
G.add_edges_from([(1, 2), (1, 3), (3, 1), (3, 2), (3, 5), (4, 5), (4, 6), (5, 4), (5, 6), (6, 4)])
B = nx.directed_modularity_matrix(G)
print(B)
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