<｜begin▁of▁sentence｜>### Instruction:
As a Philanthropy Advisor, imagine you're assisting a donor who wants to visually represent the connections within their network of charitable initiatives. Suppose they've utilized the Geometric Random Graph (GRG) model to simulate these connections among 100 entities, symbolizing various philanthropic projects and partners. The graph was generated with a specified radius of 0.2, reflecting the spatial distribution of these initiatives.

Now, the donor seeks your expertise in creating a visual depiction of this network using Python's NetworkX library. They request the graph to be drawn onto a 600x600 pixel image surface, with a comfortable 20-pixel margin around the figure, ensuring clarity and readability. The image will serve as a visual aid in analyzing the interconnections and identifying potential collaboration opportunities within their philanthropic ecosystem.

Your task is to employ the CairoGraphDrawer API to translate this abstract network structure into a visually appealing representation, saving the resulting image as 'graph.png' for the donor's reference and strategic planning purposes.
### Response:
```python
from igraph.drawing import Plot
from igraph.drawing.graph import CairoGraphDrawer
from igraph import Graph
import cairo

# Create an igraph graph
graph = Graph.GRG(100, 0.2)

# Set up Cairo context and bounding box
surface = cairo.ImageSurface(cairo.FORMAT_ARGB32, 600, 600)
context = cairo.Context(surface)
bbox = (20, 20, 580, 580)

# Create a CairoGraphDrawer
graph_drawer = CairoGraphDrawer(context, bbox)

# Draw the graph
graph_drawer.draw(graph)

# Save the image to a file
surface.write_to_png('graph.png')
```
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