<｜begin▁of▁sentence｜>### Instruction:
Imagine we're investigating a network of interactions within a patient's body, where the connections represent pathways of influence or the flow of substances between organs. We have a specific cluster of connections, which can be thought of as pathways in our investigation, including the following:

- Pathway from Organ 1 to Organ 2 with an influence score of 1.0
- Pathway from Organ 1 to Organ 3 with an influence score of 2.0
- Pathway from Organ 2 to Organ 4 with an influence score of 1.5
- Pathway from Organ 3 to Organ 4 with an influence score of 2.5
- Pathway from Organ 3 to Organ 5 with an influence score of 1.0

In the context of understanding the effects emanating from Organ 1, we are interested in creating a focused study that would map out all the pathways directly and indirectly connected to Organ 1, up to a secondary level of influence. Specifically, we want to visualize the impact Organ 1 has within a two-step radius, taking into account the influence scores of the pathways connected to it. Can we synthesize a visual representation that includes this specific subset of our overall network, ensuring we can observe the influence Organ 1 exerts on its immediate and secondary connections?
### Response:
import networkx as nx

# Create a graph
G = nx.Graph()
G.add_weighted_edges_from([(1, 2, 1.0), (1, 3, 2.0), (2, 4, 1.5), (3, 4, 2.5), (3, 5, 1.0)])

# Generate ego graph for node 1 with radius 2
H = nx.ego_graph(G, 1, radius=2)

# Print the edges of the ego graph
print(H.edges(data=True))
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