Description Usage Arguments Value See Also Examples
This function generates a bare graph object of type grapherator
.
The generated object does not contain nodes, edges or edge weights. It serves as a starting
point for a three step approach of grapherator graph construction:
1) Add nodes respectively coordinates via addNodes
, 2) add edges
via addEdges
and finally 3) add edge weights with the function
addWeights
.
1 | graph(lower, upper)
|
lower |
[ |
upper |
[ |
[grapherator
] Graph.
Other graph generators: addEdges
,
addNodes
, addWeights
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 | # complete graph with one U(10, 20) sampled weight per edge
g = graph(0, 10)
g = addNodes(g, n = 10, generator = addNodesUniform)
g = addEdges(g, generator = addEdgesComplete)
g = addWeights(g, generator = addWeightsRandom, method = runif, min = 10, max = 20)
## Not run:
do.call(gridExtra::grid.arrange, plot(g, show.edges = FALSE))
## End(Not run)
# we extend the graph by adding another weight which is based
# on the Euclidean distance between the node coordinates
g = addWeights(g, generator = addWeightsDistance, method = "euclidean")
## Not run:
do.call(gridExtra::grid.arrange, plot(g, show.edges = FALSE))
## End(Not run)
# next we generate a graph with each two weights per edge which resembles
# a street network. The edge weights have a positive correlation.
g = graph(0, 100)
g = addNodes(g, n = 5, generator = addNodesLHS)
g = addNodes(g, n = c(10, 10, 15, 20, 50), by.centers = TRUE,
generator = addNodesUniform, lower = c(0, 0), upper = c(10, 10))
g = addEdges(g, generator = addEdgesDelauney, type = "intracluster")
g = addEdges(g, generator = addEdgesDelauney, type = "intercluster", k = 4L)
g = addWeights(g, generator = addWeightsCorrelated, rho = 0.6)
## Not run:
print(g)
do.call(gridExtra::grid.arrange, plot(g, show.edges = FALSE))
## End(Not run)
|
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