Скачать или смотреть How to Create a Multigraph from Simple Graphs in R's igraph Package

Learn how to combine simple graphs into a `multigraph` using R's `igraph` package, allowing for the representation of multiple edges between nodes. Explore step-by-step methods to enhance your graph analysis.
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Understanding Multigraphs in R's igraph Package

Graph theory is a fascinating field that deals with the study of graphs, which are mathematical structures used to model pairwise relations. In R, the igraph package is a powerful tool for creating and analyzing graphs. But what happens when you want to combine multiple simple graphs that might have overlapping edges? This is where the concept of a multigraph comes into play. A multigraph allows multiple edges between the same pair of vertices.

In this guide, we'll answer the question: How to get a multigraph from two or more simple graphs in R igraph? We'll walk through a couple of methods, including one for merging graphs while preserving edge multiplicity.

Creating Simple Graphs

Let's start by creating two simple graphs using the igraph package. Here's how you can create the first graph:

[[See Video to Reveal this Text or Code Snippet]]

In this code:

We use the graph_from_literal() function to define the vertices and edges.

We then set an attribute at for each edge, assigning the identifier "a".

Now for the second graph:

[[See Video to Reveal this Text or Code Snippet]]

Similar to the first graph, we define another simple graph and assign the attribute at with values "b".

Merging Simple Graphs into a Multigraph

You might wonder if simply merging these two graphs using graph.union() would give you the desired multigraph. However, the graph.union() function will lead to a simple graph if both graphs share edges.

Here's how you can achieve the desired multigraph:

Method 1: Using graph.union()

While graph.union() works, it may not maintain the edge multiplicity:

[[See Video to Reveal this Text or Code Snippet]]

In this methodology:

You check if the resulting graph G3 is simple using is.simple(G3).

Finally, you plot the graph to visualize it. However, as noted, this will not generate a multigraph if edges overlap.

Method 2: Using graph_from_data_frame()

A more effective approach involves converting the graphs to data frames and then combining them.

Combine the Graphs as Data Frames:

[[See Video to Reveal this Text or Code Snippet]]

Create the Multigraph:

[[See Video to Reveal this Text or Code Snippet]]

In this process:

We use as_data_frame() to convert each graph into data frames, and then rbind() to combine them.

The function graph_from_data_frame() allows us to create a new graph (G3b) from the combined data frame while preserving edge multiplicity.

Plotting the Multigraph:

[[See Video to Reveal this Text or Code Snippet]]

Here, we create a new plotting window and visualize the multigraph. Different edge colors and labels help distinguish between the various edges originating from different graphs.

Conclusion

Creating a multigraph from two or more simple graphs can be easily accomplished with R’s igraph package using data frames. This method retains the distinct edges even when they connect the same nodes, facilitating a more nuanced representation of relationships.

Feel free to experiment further with the igraph library and discover many other functions that can enhance your graph analysis!