<｜begin▁of▁sentence｜>### Instruction:
Imagine we're examining the political dynamics of coalition formation, akin to the strategic alliances in international relations, where each node represents a nation and the edges represent the partnerships. Here, we're conceptualizing a scenario where we have a regional coalition represented as a cycle graph (let's call this the "RegioCycle.gml") consisting of four allied nations. Similarly, we possess data on a mutual agreement between two nations, portrayed as a simple bilateral path graph (we'll refer to this as "BilatPath.gml").

In this intriguing case, we aim to explore a hypothetical diplomatic construct, the 'corona product' of these two distinct political structures—the cyclical alliance and the bilateral agreement. This fusion creates a new strategic configuration where each nation in the larger coalition forms a partnership with every nation from the smaller agreement. Could you assist us in quantifying the magnitude of this expanded diplomatic network through NetworkX? Specifically, we're interested in the overall count of nations (nodes) and agreements (edges) that would result from this complex political alliance formation process.
### Response:
import networkx as nx

# Define two graphs G and H
G = nx.cycle_graph(4)
H = nx.path_graph(2)

# Calculate the corona product of G and H
C = nx.corona_product(G, H)

# Output the number of nodes and edges in the corona product graph
print('Number of nodes:', len(C.nodes))
print('Number of edges:', len(C.edges))

# If you want to visualize the graph, you can use matplotlib (optional):
#import matplotlib.pyplot as plt
#nx.draw(C, with_labels=True)
#plt.show()
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