A markdown-based webpage is now online, with all the codes.
For practicals on networks and flows, we will use the R package flows dedicated to flows on networks
myflows <- prepflows(mat = nav, i = "i", j = "j", fij = "fij")
diag(myflows) <- 0
Select flows that represent at least 20% of the sum of outgoing flows for each urban area.
flowSel1 <- firstflows(mat = myflows/rowSums(myflows)*100, method = "xfirst",k = 20)
Then select the dominant flows (incoming flows criterion)
flowSel2 <- domflows(mat = myflows, w = colSums(myflows), k = 1)
flowSel <- myflows * flowSel1 * flowSel2
inflows <- data.frame(id = colnames(myflows), w = colSums(myflows))
and finally plot dominant flows map
opar <- par(mar = c(0,0,2,0))
sp::plot(GE, col = "#cceae7", border = NA)
plotMapDomFlows(mat = flowSel, spdf = UA, spdfid = "ID", w = inflows, wid = "id",wvar = "w", wcex = 0.05, add = TRUE,legend.flows.pos = "topright",legend.flows.title = "Nb. of commuters")
title("Dominant Flows of Commuters")
The code to get the background map is based on the GE object, defined in that package.
We will discuss in the last course, next week two extensions that were not mentioned in the course. The first one is about congestion models. The second one is a nice application of flow to discuss sports issues in NBA (or NHL).
This week, we will start the first graduate course on graphs and networks. Slides are available online.
Later on, we will see additional applications, in the context of flows, matching, transportation, etc.