R/graph-plots.R

In robertness/pathflow: Converts biochemical reaction networks to pathway maps.

#' A graphing function for invariants.
drawGraphWithInvariants <- function(graph, g.layout){
  #Did this as a function so I could apply to multiple graphs
  #Takes in a graph as described above, with a type attribute labeled "place" or "transition"
  places <- V(graph)[V(graph)$type == "place"]$name
  transitions <- V(graph)[V(graph)$type == "transition"]$name
  ## Get adjacency 
  adjMat <- as.matrix(get.adjacency(graph))
  ## Incidence matrix is derived by taking reactant - reaction relationship matrix
  ## and product - reaction relation matrix and subtracting former from latter. 
  pre <- adjMat[places, transitions]
  post <- t(adjMat[transitions, places])
  S <- post - pre
  # Invariant calculation matrix
  pInvariants <- getMinimalInvariants(S)
  tInvariants <- getMinimalInvariants(t(S))
  # Name them
  names(pInvariants) <- unlist(lapply(pInvariants, function(p) paste(p, collapse = "--")))
  names(tInvariants) <- unlist(lapply(tInvariants, function(t) paste(t, collapse = "--")))
  # Label nodes in the graph
  require(reshape, quietly=TRUE)
  invariantMap <- rbind(melt(pInvariants), melt(tInvariants))
  names(invariantMap) <- c("name", "invariant")
  rownames(invariantMap) <- as.character(invariantMap$name)
  V(graph)$invariant <- invariantMap[V(graph)$name, "invariant"]
  invariantVertex <- lapply(c(pInvariants, tInvariants), function(inv){
    V(graph)[V(graph)$name %in% inv]
  })
  V(graph)$color <- "lightblue"
  V(graph)[is.na(V(graph)$invariant)]$color <- "pink"
  V(graph)[V(graph)$name == "E1"]$color <- "blue"
  V(graph)[V(graph)$name == "PP_K"]$color <- "red" 
  plot.igraph(graph, layout = g.layout, vertex.size =3, vertex.label.dist=-.37, 
              edge.arrow.size=.4, mark.groups=invariantVertex)
}