<｜begin▁of▁sentence｜>### Instruction:
As a research analyst, you may be working on a project involving visualizing a tree graph representing a network structure. Let's say you have collected data on a tree graph with 5 vertices, where each vertex branches into 2 others. You are using the NetworkX library to create and visualize the graph, and now you want to scale the Kamada-Kawai layout uniformly by a factor of 2 to better present the graph. 

You may wonder if it's possible to achieve this using the `scale` method of the igraph Layout object. This question is important because it relates to the visual representation and understanding of the network structure, which can be crucial for decision-making, policy development, or academic research.
### Response:
from igraph import Graph, Layout

# Create a simple graph
g = Graph.Tree(5, 2)

# Generate a layout for the graph
layout = g.layout('kk')

# Scale the layout uniformly by a factor of 2
layout.scale(2)

# Print the scaled layout coordinates
print(layout.coords)
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