<｜begin▁of▁sentence｜>### Instruction:
As a network engineer tasked with visualizing the topology of a network, you've deployed a series of probes that record interactions between various network nodes. The recorded log "interactions_log.gml" indicates multiple recorded connections between certain pairs of nodes, such as redundant pathways or multiple types of connections (e.g., Ethernet, Wi-Fi). This is represented as a set of tuples [(1, 2), (1, 2), (2, 3), (3, 4), (4, 2), (4, 2)], with each tuple signifying a direct link between the two nodes.

To streamline the network diagram and enhance readability for management review, you are tasked with transforming this multigraph data into a simplified graph representation that consolidates these multiple connections into single, undirected edges between nodes. This would result in a clear, deduplicated overview of the network structure.

Could you describe the process of converting the multigraph from our "interactions_log.gml" into a simplified graph that combines any parallel connections between the same nodes into a single connection, using NetworkX, while retaining the overall connectivity of the network?
### Response:
import networkx as nx

# Create a multi-graph with multiple edges between the same nodes
G = nx.MultiGraph()
G.add_edges_from([(1, 2), (1, 2), (2, 3), (3, 4), (4, 2), (4, 2)])

# Draw the multi-graph with edges visible
nx.draw(G, with_labels=True)

# Convert the multi-graph to a simple graph, hiding multiple edges
G_simple = nx.Graph(G)

# Draw the simple graph with multiple edges hidden
nx.draw(G_simple, with_labels=True)
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