<｜begin▁of▁sentence｜>### Instruction:
As an Intensive Care Nurse, you're accustomed to analyzing critical patient data to make informed decisions. Imagine you're in charge of monitoring vital signs for patients in the ICU. Today, you're tasked with understanding the network of symptoms and conditions affecting a group of patients. You have access to a specialized tool called GraphAnalyzer, which can read patient data from a file called graph_data.gml. Using GraphAnalyzer's Laplacian function, you need to generate the Laplacian matrix for this patient network, specifically the symmetric normalized version suitable for spectral analysis. This will help you gain deeper insights into the interconnectedness of symptoms and conditions, aiding in more targeted and effective treatment strategies.
### Response:
from igraph import Graph
import numpy as np

# Read the graph from a file
graph = Graph.Read_GML('graph_data.gml')

# Calculate the Laplacian matrix of the graph
laplacian_matrix = graph.laplacian(weights=None, normalized=True, mode='all')

# Convert to a numpy array for further processing or analysis
laplacian_matrix_np = np.array(laplacian_matrix)
print(laplacian_matrix_np)
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