<｜begin▁of▁sentence｜>### Instruction:
Given a stochastic model where the probability of an edge gaining a new node is determined by the number of edges gained in a recent time window, how would you use igraph's Graph.Recent_Degree function to generate an undirected graph with 100 nodes, where the time window is set to 2 units and each new node is expected to connect to 1 existing node?
### Response:
import igraph as ig

# Generate a graph where the probability of a node connecting to an edge is based on recent activity within a time window
g = ig.Graph.Recent_Degree(100, window=2, k=1, directed=False)

# Print summary of the generated graph
print(g.summary())

# Plot the graph
g.plot('recent_degree_graph.png')
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