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Isere_test.R
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Isere_test.R
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# Isere - flowmap tests
#rm(list=ls())
setwd("D:/R/github/transcarto/rflows")
#Packages
library("dplyr")
library("spatstat")
library("sf")
library("cartograflow")
library("mapsf")
# Load data
#--------------------
fdc <- st_read("D:/R/github/transcarto/rflows/data/isere_com.shp", quiet = TRUE )
flow<- read.csv("D:/R/github/transcarto/rflows/data/isere/fij/mobpro_isere2017.csv",
header=TRUE,sep=",",
stringsAsFactors=FALSE,
encoding="UTF-8",dec=".", check.names=FALSE)
head(flow)
#Selecting useful variables
flow<-flow %>% select(CODGEO,DCLT,fij)
colnames(flow)<-c("i","j","fij")
# Variable typing
flow$i<-as.character(flow$i)
flow$j<-as.character(flow$j)
flow$fij<-as.numeric(flow$fij)
#Spaghetti
#--------------
# (1) Simple vizu du flux
flowmap(tab=flow,
origin.f = "i",
destination.f = "j",
bkg= fdc, #nodes= pt
code="INSEE_COM",
nodes.X="X",
nodes.Y="Y",
filter=F,
plota=fdc
)
#(2) Vizu with global filtering
#------------------------------------
# flow criterion selection
#---------------------------
summary(flow$fij)
mean<-mean(flow$fij) #as Tobler's said
Q3<-quantile(flow$fij,0.75) #25% of the most important migrations
Q95<-quantile(flow$fij, 0.95) # 5% of the most important migrations
Q98<-quantile(flow$fij, 0.98) # 2% of the most important migrations
max<-max(flow$fij)
plot.new()
par(bg = "NA")
plot(st_geometry(fdc), col=NA, border=NA)
mf_map(fdc, col = "#CCCCCC", border = "white", lwd = 0.5, add = TRUE)
#plot(st_geometry(fdc), col="#e3d0c1", border = "white", add=T)
flowmap(tab=flow,
origin.f = "i",
destination.f = "j",
bkg= fdc, #nodes= pt
code="INSEE_COM",
nodes.X="X",
nodes.Y="Y",
filter=T,
threshold=Q95, # plot the top 3% flow value
taille=20,
a.head=1,
a.length = 0.09,
a.angle = 30,
a.col="#636363",
add=TRUE
)
#--- variante bilateral flows ---------
#compute bilateral volum (gross) FSij
#---------
flow_vol<-flowtype(flow, format="L", origin="i", destination="j", fij="fij",x="bivolum")
head(flow_vol)
# Bivolum thresholding criterion
mean<-mean(flow_vol$FSij)
Q95<-quantile(flow_vol$FSij,0.95)
colnames(flow_vol)<-c("i","j","fij")
# Plot bivol
plot.new()
par(bg = "NA")
plot(st_geometry(fdc), col=NA, border=NA)
mf_map(fdc, col = "#CCCCCC", border = "white", lwd = 0.5, add = TRUE)
flowmap(tab=flow_vol,
origin.f = "i",
destination.f = "j",
bkg= fdc, #nodes= pt
code="INSEE_COM",
nodes.X="X",
nodes.Y="Y",
filter=T,
threshold=mean, # plot the up-mean bilateral volum of flows
taille=20,
a.head=0, #no arrow
a.col="#636363",
add=TRUE
)
#(3) Customize the map : add theme etc.
#--------------------------
# Theme - template Isere
#--------
communes<-fdc
col = "#37962a" #c291bc"
credits = paste0("Bahoken Françoise & Nicolas Lambert, 2021\n",
"Source: IGN & INSEE, 2021")
theme = mf_theme(x = "default", bg = "#f0f0f0", tab = FALSE,
pos = "center", line = 2, inner = FALSE,
fg = col, mar = c(0,0, 2, 0),cex = 1.9)
template = function(title, file, note = "", basemap = TRUE, scale = TRUE){
mf_export(
communes,
export = "png",
width = 1000,
filename = file,
res = 96,
theme = theme,
expandBB = c(-.02,0,-.02,0)
)
if (basemap == TRUE){
mf_shadow(x = communes, col = "grey50", cex = 1, add = TRUE)
mf_map(communes, col ="#CCCCCC", border = "white", lwd = 0.5, add = TRUE)
}
mf_title(title)
if (scale == TRUE){
mf_scale(size = 20, pos = "bottomright", lwd = 1.2, cex = 1, col = "#383838", unit = "km")
}
mf_credits(
txt = credits,
pos = "bottomleft",
col = "#1a2640",
cex = 0.8,
font = 3,
bg = "#ffffff30"
)
if(note != ""){
mf_annotation(
x = c(885000, 6435000),
txt = note,
pos = "bottomleft", cex = 1.2, font = 2,
halo = TRUE, s = 1.5
)
}
}
template("Template cartographique", "maps/template_isere_flow.png", note = "Département de\nl'Isère (38)")
mf_map(fdc, col = col, border = "white", lwd = 0.5, add = TRUE)
dev.off()
#----------------------
# 2% top flow
#----------------------
plot.new()
png("maps/isere_top5percentflow.png")
par(bg = "NA")
plot(st_geometry(fdc), col=NA, border=NA)
plot(st_geometry(fdc), col="grey", border="white",lwd = 0.5, bg="white", add = TRUE )
#mf_map(fdc, col = NA, border = "white", lwd = 0.5, bg="white", add = TRUE)
flowmap(tab=flow_vol,origin.f = "i", destination.f = "j",
bkg= fdc, code="INSEE_COM",nodes.X="X", nodes.Y="Y",
filter=T, threshold=Q95, # plot the top 5% flow value
taille=20,a.head=0,a.col="#37962a", #636363 (grey)
add=TRUE
)
mf_legend_pl( pos="topright",
val = c(Q95,Q98, max),
col=col,
lwd=20,
title="5 % de flux les plus importants\n (ie de l'interaction totale)",
title_cex=0.8,
val_cex= 0.8,
frame=F,
)
layoutLayer(title = "Mobilités professionnelles en Isère, 2019",
tabtitle = T,
frame = TRUE,
col = "#37962a", # coltitle ="#636363"
bg=NA,
)
mf_credits(
txt = "Bahoken Françoise & Lambert Nicolas, 2021\n Source : IGN & INSEE/MOBPRO 2019 ",
pos = "bottomleft",
col="#636363",
cex = 0.6,
font = 3,
)
dev.off()
#----------------------
# Bilateral volume Isere
#----------------------
# Overlay a spatial background
plot.new()
png("maps/isere_volflow.png")
par(bg = "NA")
plot(st_geometry(fdc), col=NA, border=NA)
plot(st_geometry(fdc), col="grey", border="white",lwd = 0.5, bg="white", add = TRUE )
flowmap(tab=flow_vol,origin.f = "i", destination.f = "j",
bkg= fdc, code="INSEE_COM",nodes.X="X", nodes.Y="Y",
filter=T, threshold=mean, # plot flow value > mean fij
taille=20,a.head=0,a.col="#37962a", #636363 (grey)
add=TRUE
)
mf_legend_pl( pos="topright",
val = c(mean, Q95,Q98, max),
col=col,
lwd=15,
title="Volume bilatéral de navetteurs\n (supérieur à la moyenne)",
title_cex=0.8,
val_cex= 0.8,
frame=F,
)
layoutLayer(title = "Mobilités professionnelles en Isère, 2019",
tabtitle = T,
frame = TRUE,
col = "#37962a", # coltitle ="#636363"
bg=NA,
)
mf_credits(
txt = "Bahoken Françoise & Lambert Nicolas, 2021\n Source : IGN & INSEE/MOBPRO 2019 ",
pos = "bottomleft",
col="#636363",
cex = 0.6,
font = 3,
)
dev.off()
#----------------------
# Bilateral volume Isere on fisheye
#----------------------
fish <- st_read("D:/R/github/transcarto/rflows/data/fisheye_grenoble1.gpkg", quiet = TRUE )
plot(st_geometry(fish), col="grey", border="white")
mean<-mean(flow_vol$FSij)
# plot
plot.new()
png("maps/isere_volflow_fish.png")
par(bg = "NA")
plot(st_geometry(fish), col=NA, border=NA)
plot(st_geometry(fish), col="grey", border="white",lwd = 0.5, bg="white", add = TRUE )
flowmap(tab=flow_vol,origin.f = "i", destination.f = "j",
bkg= fish, code="id",nodes.X="X", nodes.Y="Y",
filter=T, threshold=mean, # plot flow value > mean fij
taille=20,a.head=0,a.col="#37962a", #636363 (grey)
add=TRUE
)
mf_legend_pl( pos="topright",
val = c(mean, Q95,Q98, max),
col=col,
lwd=15,
title="Volume bilatéral de navetteurs\n (supérieur à la moyenne)",
title_cex=0.8,
val_cex= 0.8,
frame=F,
)
layoutLayer(title = "Mobilités professionnelles en Isère, 2019\n fond fisheye Grenoble",
tabtitle = T,
frame = TRUE,
col = "#37962a", # coltitle ="#636363"
bg=NA,
)
mf_credits(
txt = "Bahoken Françoise & Lambert Nicolas, 2021\n Source : IGN & INSEE/MOBPRO 2019 ",
pos = "bottomleft",
col="#636363",
cex = 0.6,
font = 3,
)
dev.off()