draw_interaction_network: Add stochasticity to in silico generated data
In lkshrsch/gLVInterNetworks: Inference of interaction networks based on generalised Lotka Volterra dynamics
Usage
1
draw_interaction_network(network, main=NULL)
Arguments
network
main
Examples
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11
##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function(network, main=NULL){
igraph::plot.igraph(network,layout = igraph::layout.fruchterman.reingold ,
vertex.label.color="black",edge.color="black", edge.curved=TRUE, main=main)
}
lkshrsch/gLVInterNetworks documentation built on May 21, 2019, 7:33 a.m.
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Usage
1 | draw_interaction_network(network, main=NULL)
|
Arguments
network |
|
main |
Examples
1 2 3 4 5 6 7 8 9 10 11 | ##---- Should be DIRECTLY executable !! ----
##-- ==> Define data, use random,
##-- or do help(data=index) for the standard data sets.
## The function is currently defined as
function(network, main=NULL){
igraph::plot.igraph(network,layout = igraph::layout.fruchterman.reingold ,
vertex.label.color="black",edge.color="black", edge.curved=TRUE, main=main)
}
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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