<｜begin▁of▁sentence｜>### Instruction:
Imagine we're analyzing the interconnected pathways within a blossoming garden, where each node represents a distinct type of flowering plant, and the edges symbolize the pollination paths between them. We're observing the routes bees might traverse to spread pollen from one flower to the next, with the following pairs of plants showing established pollination paths: [(0,1),(1,2),(1,5),(5,4),(2,4),(2,3),(4,3),(3,6)]. Could we employ NetworkX to simulate and examine the vibrancy and efficiency of this pollination network by calculating the communicability between each pair of these floral nodes? This measure would provide us with insight into how effectively each flower can contribute to the pollination of others within our botanical network.
### Response:
import networkx as nx

# Create a graph
G = nx.Graph()
G.add_edges_from([(0, 1), (1, 2), (1, 5), (5, 4), (2, 4), (2, 3), (4, 3), (3, 6)])

# Compute the communicability between all pairs of nodes
comm = nx.communicability(G)

print(comm)
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