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Multidimensional scaling of some distance matrix defined on the vertices of a graph.


layout_with_mds(graph, dist = NULL, dim = 2, options = arpack_defaults())




The input graph.


The distance matrix for the multidimensional scaling. If NULL (the default), then the unweighted shortest path matrix is used.


layout_with_mds() supports dimensions up to the number of nodes minus one, but only if the graph is connected; for unconnected graphs, the only possible value is 2. This is because merge_coords() only works in 2D.


This is currently ignored, as ARPACK is not used any more for solving the eigenproblem


Passed to layout_with_mds().


A numeric matrix with dim columns.


layout_with_mds() uses classical multidimensional scaling (Torgerson scaling) for generating the coordinates. Multidimensional scaling aims to place points from a higher dimensional space in a (typically) 2 dimensional plane, so that the distances between the points are kept as much as this is possible.

By default igraph uses the shortest path matrix as the distances between the nodes, but the user can override this via the dist argument.

Warning: If the graph is symmetric to the exchange of two vertices (as is the case with leaves of a tree connecting to the same parent), classical multidimensional scaling may assign the same coordinates to these vertices.

This function generates the layout separately for each graph component and then merges them via merge_coords().


Cox, T. F. and Cox, M. A. A. (2001) Multidimensional Scaling. Second edition. Chapman and Hall.


Tamas Nepusz and Gabor Csardi


g <- sample_gnp(100, 2 / 100)
l <- layout_with_mds(g)
plot(g, layout = l, vertex.label = NA, vertex.size = 3)