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The diameter of a graph is the length of the longest geodesic.


diameter(graph, directed = TRUE, unconnected = TRUE, weights = NULL)

get_diameter(graph, directed = TRUE, unconnected = TRUE, weights = NULL)

farthest_vertices(graph, directed = TRUE, unconnected = TRUE, weights = NULL)



The graph to analyze.


Logical, whether directed or undirected paths are to be considered. This is ignored for undirected graphs.


Logical, what to do if the graph is unconnected. If FALSE, the function will return a number that is one larger the largest possible diameter, which is always the number of vertices. If TRUE, the diameters of the connected components will be calculated and the largest one will be returned.


Optional positive weight vector for calculating weighted distances. If the graph has a weight edge attribute, then this is used by default.


A numeric constant for diameter(), a numeric vector for get_diameter(). farthest_vertices() returns a list with two entries:

  • vertices The two vertices that are the farthest.

  • distance Their distance.


The diameter is calculated by using a breadth-first search like method.

get_diameter() returns a path with the actual diameter. If there are many shortest paths of the length of the diameter, then it returns the first one found.

farthest_vertices() returns two vertex ids, the vertices which are connected by the diameter path.


Gabor Csardi


g <- make_ring(10)
g2 <- delete_edges(g, c(1, 2, 1, 10))
diameter(g2, unconnected = TRUE)
#> [1] 7
diameter(g2, unconnected = FALSE)
#> [1] Inf

## Weighted diameter
g <- make_ring(10)
E(g)$weight <- sample(seq_len(ecount(g)))
#> [1] 27
#> + 5/10 vertices, from 38d7ccd:
#> [1]  1 10  9  8  7
diameter(g, weights = NA)
#> [1] 5
get_diameter(g, weights = NA)
#> + 6/10 vertices, from 38d7ccd:
#> [1] 1 2 3 4 5 6