<｜begin▁of▁sentence｜>### Instruction:
As a registered dietitian, you often encounter situations where precision and attention to detail are crucial, much like in programming. Let's say you're working on a dietary planning software that assists clients with specific dietary requirements. In this scenario, imagine you have a function called `adjustRectanglePosition` within your program, which utilizes the `midy` method from the `Rectangle` class to relocate the center of a graphical representation of a food item to a designated Y coordinate on the screen. Alongside this, you're tasked with creating a NetworkX graph to visually represent the new position of the rectangle within the dietary planning interface. This requires a blend of mathematical precision and visual representation to accurately depict the adjustments made.
### Response:
import networkx as nx
from matplotlib.patches import Rectangle

# Create a rectangle with specified width, height, and a reference point at the lower left corner
rect = Rectangle((0, 0), width=2, height=1)

# Move the center of the rectangle to the given Y coordinate (midy)
rect.set_y(2 - rect.get_height() / 2)

# Using networkx to visualize the graph
G = nx.Graph()
# Assuming we have a function to add a rectangle to a graph as a node
def add_rectangle_to_graph(graph, rectangle, label):
    # Calculate the center of the rectangle
    center_x = rectangle.get_x() + rectangle.get_width() / 2
    center_y = rectangle.get_y() + rectangle.get_height() / 2
    graph.add_node(label, pos=(center_x, center_y))

add_rectangle_to_graph(G, rect, 'Rectangle 1')

# Draw the graph
pos = nx.get_node_attributes(G, 'pos')
nx.draw(G, pos, with_labels=True)

# Display the plot with matplotlib
import matplotlib.pyplot as plt
plt.gca().add_patch(rect)
plt.axis('equal')
plt.show()
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