################## Install packages #####################################
# install.packages("cartography")
# install.packages("readxl")
# install.packages("SpatialPosition")
# install.packages("mapview")
################## Import geo layer #####################################
# load libraries
library(sf)
## Linking to GEOS 3.5.1, GDAL 2.1.2, proj.4 4.9.3
# import communes of Auvergne-Rhone-Alpes region
reg84 <- st_read(dsn = "data/communes_reg_84.geojson", stringsAsFactors = F)
## Reading layer `OGRGeoJSON' from data source `/home/tim/Documents/prz/tuto-mate/data/communes_reg_84.geojson' using driver `GeoJSON'
## Simple feature collection with 4141 features and 8 fields
## geometry type: MULTIPOLYGON
## dimension: XY
## bbox: xmin: 2.062908 ymin: 44.11565 xmax: 7.185633 ymax: 46.80403
## epsg (SRID): 4326
## proj4string: +proj=longlat +datum=WGS84 +no_defs
# view information on the geo layer com
head(reg84)
## Simple feature collection with 6 features and 8 fields
## geometry type: MULTIPOLYGON
## dimension: XY
## bbox: xmin: 4.020999 ymin: 44.4428 xmax: 5.879937 ymax: 46.14185
## epsg (SRID): 4326
## proj4string: +proj=longlat +datum=WGS84 +no_defs
## INSEE_COM NOM_COM SUPERFICIE POPULATION CODE_DEPT
## 1 38225 AUTRANS-MEAUDRE EN VERCORS 3371 2973 38
## 2 42070 CORDELLE 2667 901 42
## 3 38342 ROISSARD 1453 279 38
## 4 07110 JOYEUSE 1300 1689 07
## 5 38489 SIEVOZ 743 127 38
## 6 69242 TAPONAS 758 945 69
## NOM_DEPT CODE_REG NOM_REG geometry
## 1 ISERE 84 AUVERGNE-RHONE-ALPES MULTIPOLYGON (((5.577223 45...
## 2 LOIRE 84 AUVERGNE-RHONE-ALPES MULTIPOLYGON (((4.059906 45...
## 3 ISERE 84 AUVERGNE-RHONE-ALPES MULTIPOLYGON (((5.638294 44...
## 4 ARDECHE 84 AUVERGNE-RHONE-ALPES MULTIPOLYGON (((4.23897 44....
## 5 ISERE 84 AUVERGNE-RHONE-ALPES MULTIPOLYGON (((5.849843 44...
## 6 RHONE 84 AUVERGNE-RHONE-ALPES MULTIPOLYGON (((4.754758 46...
# display the layer
plot(st_geometry(reg84))
# Extract the Rhone Departement
dep69 <- reg84[reg84$CODE_DEPT==69,]
plot(st_geometry(dep69))
################## Import data #####################################
library(readxl)
# import data from an INSEE excel file
csp <- read_excel("data/pop-act2554-csp-cd-6814.xls",
sheet = "COM_2014", skip = 15)
head(csp)
## # A tibble: 6 x 18
## RR DR CR STABLE DR16 LIBELLE csx_rec1taxtypa… csx_rec1taxtypa…
## <chr> <chr> <chr> <chr> <chr> <chr> <dbl> <dbl>
## 1 84 01 001 1 01 Aberge… 5.00 0.
## 2 84 01 002 1 01 Aberge… 0. 0.
## 3 84 01 003 0 01 Amarei… NA NA
## 4 84 01 004 1 01 Ambéri… 2.09 0.
## 5 84 01 005 1 01 Ambéri… 5.02 0.
## 6 84 01 006 1 01 Ambléon 0. 0.
## # ... with 10 more variables: csx_rec2taxtypac_rec1rpop2014 <dbl>,
## # csx_rec2taxtypac_rec2rpop2014 <dbl>,
## # csx_rec3taxtypac_rec1rpop2014 <dbl>,
## # csx_rec3taxtypac_rec2rpop2014 <dbl>,
## # csx_rec4taxtypac_rec1rpop2014 <dbl>,
## # csx_rec4taxtypac_rec2rpop2014 <dbl>,
## # csx_rec5taxtypac_rec1rpop2014 <dbl>,
## # csx_rec5taxtypac_rec2rpop2014 <dbl>,
## # csx_rec6taxtypac_rec1rpop2014 <dbl>,
## # csx_rec6taxtypac_rec2rpop2014 <dbl>
# select data for Rhone
csp69 <- data.frame(csp[csp$DR %in% 69,])
head(csp69)
## RR DR CR STABLE DR16 LIBELLE csx_rec1taxtypac_rec1rpop2014
## 1 84 69 001 1 69 Affoux 12.069767
## 2 84 69 002 1 69 Aigueperse 16.192771
## 3 84 69 003 1 69 Albigny-Sur-Saône 4.982330
## 4 84 69 004 1 69 Alix 7.963209
## 5 84 69 005 1 69 Ambérieux 0.000000
## 6 84 69 006 1 69 Amplepuis 55.434356
## csx_rec1taxtypac_rec2rpop2014 csx_rec2taxtypac_rec1rpop2014
## 1 0 16.093023
## 2 0 8.096386
## 3 0 64.770286
## 4 0 11.944813
## 5 0 29.136531
## 6 0 98.927175
## csx_rec2taxtypac_rec2rpop2014 csx_rec3taxtypac_rec1rpop2014
## 1 0.00000 12.06977
## 2 0.00000 0.00000
## 3 4.98233 209.25785
## 4 0.00000 27.87123
## 5 0.00000 20.81181
## 6 11.89678 106.84847
## csx_rec3taxtypac_rec2rpop2014 csx_rec4taxtypac_rec1rpop2014
## 1 0.000000 20.11628
## 2 0.000000 12.14458
## 3 9.964659 209.25785
## 4 0.000000 71.66888
## 5 0.000000 83.24723
## 6 3.975539 352.42410
## csx_rec4taxtypac_rec2rpop2014 csx_rec5taxtypac_rec1rpop2014
## 1 0.00000 48.27907
## 2 0.00000 20.24096
## 3 14.94699 209.25785
## 4 0.00000 63.70567
## 5 0.00000 45.78598
## 6 35.69072 348.48096
## csx_rec5taxtypac_rec2rpop2014 csx_rec6taxtypac_rec1rpop2014
## 1 4.023256 32.18605
## 2 4.048193 28.33735
## 3 9.964659 109.61125
## 4 7.963209 51.76086
## 5 16.649446 37.46125
## 6 59.365750 474.98472
## csx_rec6taxtypac_rec2rpop2014
## 1 0.000000
## 2 0.000000
## 3 9.964659
## 4 0.000000
## 5 0.000000
## 6 31.656059
# create INSEE_COM code
csp69$INSEE_COM <- paste0(csp69$DR, csp69$CR)
# suppress unused fields (the first 5 fields)
csp69 <- csp69[,-c(1:5)]
## ATTENTION ##
dep69[substr(dep69$NOM_COM, 1,4) =="LYON", ]
## Simple feature collection with 9 features and 8 fields
## geometry type: MULTIPOLYGON
## dimension: XY
## bbox: xmin: 4.771712 ymin: 45.70731 xmax: 4.899021 ymax: 45.80818
## epsg (SRID): 4326
## proj4string: +proj=longlat +datum=WGS84 +no_defs
## INSEE_COM NOM_COM SUPERFICIE POPULATION CODE_DEPT
## 1007 69384 LYON-4E-ARRONDISSEMENT 289 36336 69
## 1357 69386 LYON-6E-ARRONDISSEMENT 378 50364 69
## 1757 69382 LYON-2E-ARRONDISSEMENT 343 30804 69
## 2054 69388 LYON-8E-ARRONDISSEMENT 683 81531 69
## 2286 69389 LYON-9E-ARRONDISSEMENT 750 48926 69
## 2523 69387 LYON-7E-ARRONDISSEMENT 944 77855 69
## 2694 69385 LYON-5E-ARRONDISSEMENT 622 46630 69
## 2748 69381 LYON-1ER-ARRONDISSEMENT 153 29313 69
## 3363 69383 LYON-3E-ARRONDISSEMENT 632 98956 69
## NOM_DEPT CODE_REG NOM_REG geometry
## 1007 RHONE 84 AUVERGNE-RHONE-ALPES MULTIPOLYGON (((4.812872 45...
## 1357 RHONE 84 AUVERGNE-RHONE-ALPES MULTIPOLYGON (((4.839947 45...
## 1757 RHONE 84 AUVERGNE-RHONE-ALPES MULTIPOLYGON (((4.839947 45...
## 2054 RHONE 84 AUVERGNE-RHONE-ALPES MULTIPOLYGON (((4.849723 45...
## 2286 RHONE 84 AUVERGNE-RHONE-ALPES MULTIPOLYGON (((4.836936 45...
## 2523 RHONE 84 AUVERGNE-RHONE-ALPES MULTIPOLYGON (((4.849181 45...
## 2694 RHONE 84 AUVERGNE-RHONE-ALPES MULTIPOLYGON (((4.819694 45...
## 2748 RHONE 84 AUVERGNE-RHONE-ALPES MULTIPOLYGON (((4.819694 45...
## 3363 RHONE 84 AUVERGNE-RHONE-ALPES MULTIPOLYGON (((4.839947 45...
csp69[csp69$LIBELLE=="Lyon", ]
## LIBELLE csx_rec1taxtypac_rec1rpop2014 csx_rec1taxtypac_rec2rpop2014
## 123 Lyon 47.23109 4.200817
## csx_rec2taxtypac_rec1rpop2014 csx_rec2taxtypac_rec2rpop2014
## 123 7860.952 730.1241
## csx_rec3taxtypac_rec1rpop2014 csx_rec3taxtypac_rec2rpop2014
## 123 60758.81 3232.642
## csx_rec4taxtypac_rec1rpop2014 csx_rec4taxtypac_rec2rpop2014
## 123 50614.36 6667.904
## csx_rec5taxtypac_rec1rpop2014 csx_rec5taxtypac_rec2rpop2014
## 123 35653.98 7277.054
## csx_rec6taxtypac_rec1rpop2014 csx_rec6taxtypac_rec2rpop2014 INSEE_COM
## 123 15633.92 4697.168 69123
# aggregate Lyon arrondissements in dep69 into 1 commune
dep69[substr(dep69$NOM_COM, 1,4) =="LYON", "INSEE_COM" ] <- "69123"
dep69 <- aggregate(dep69, by=list(dep69$INSEE_COM), FUN = head, 1)
#st_geometry(dep69) <- st_cast(dep69$geometry, "MULTIPOLYGON")
dep69 <- dep69[,"INSEE_COM"]
plot(st_geometry(dep69))
# merge com layer and data
dep69 <- merge(dep69, csp69, by="INSEE_COM", all.x=TRUE)
head(dep69)
## Simple feature collection with 6 features and 14 fields
## geometry type: POLYGON
## dimension: XY
## bbox: xmin: 4.24347 ymin: 45.82755 xmax: 4.837852 ymax: 46.30282
## epsg (SRID): 4326
## proj4string: +proj=longlat +datum=WGS84 +no_defs
## INSEE_COM LIBELLE csx_rec1taxtypac_rec1rpop2014
## 1 69001 Affoux 12.069767
## 2 69002 Aigueperse 16.192771
## 3 69003 Albigny-Sur-Saône 4.982330
## 4 69004 Alix 7.963209
## 5 69005 Ambérieux 0.000000
## 6 69006 Amplepuis 55.434356
## csx_rec1taxtypac_rec2rpop2014 csx_rec2taxtypac_rec1rpop2014
## 1 0 16.093023
## 2 0 8.096386
## 3 0 64.770286
## 4 0 11.944813
## 5 0 29.136531
## 6 0 98.927175
## csx_rec2taxtypac_rec2rpop2014 csx_rec3taxtypac_rec1rpop2014
## 1 0.00000 12.06977
## 2 0.00000 0.00000
## 3 4.98233 209.25785
## 4 0.00000 27.87123
## 5 0.00000 20.81181
## 6 11.89678 106.84847
## csx_rec3taxtypac_rec2rpop2014 csx_rec4taxtypac_rec1rpop2014
## 1 0.000000 20.11628
## 2 0.000000 12.14458
## 3 9.964659 209.25785
## 4 0.000000 71.66888
## 5 0.000000 83.24723
## 6 3.975539 352.42410
## csx_rec4taxtypac_rec2rpop2014 csx_rec5taxtypac_rec1rpop2014
## 1 0.00000 48.27907
## 2 0.00000 20.24096
## 3 14.94699 209.25785
## 4 0.00000 63.70567
## 5 0.00000 45.78598
## 6 35.69072 348.48096
## csx_rec5taxtypac_rec2rpop2014 csx_rec6taxtypac_rec1rpop2014
## 1 4.023256 32.18605
## 2 4.048193 28.33735
## 3 9.964659 109.61125
## 4 7.963209 51.76086
## 5 16.649446 37.46125
## 6 59.365750 474.98472
## csx_rec6taxtypac_rec2rpop2014 geometry
## 1 0.000000 POLYGON ((4.396142 45.85982...
## 2 0.000000 POLYGON ((4.439457 46.29305...
## 3 9.964659 POLYGON ((4.837265 45.85363...
## 4 0.000000 POLYGON ((4.670139 45.90537...
## 5 0.000000 POLYGON ((4.732623 45.92053...
## 6 31.656059 POLYGON ((4.346022 45.92994...
# use friendly names
cs <- c("agr1", "agr0", "art1", "art0",
"cad1", "cad0", "int1","int0",
"emp1", "emp0","ouv1", "ouv0")
names(dep69)[3:14] <- cs
head(dep69)
## Simple feature collection with 6 features and 14 fields
## geometry type: POLYGON
## dimension: XY
## bbox: xmin: 4.24347 ymin: 45.82755 xmax: 4.837852 ymax: 46.30282
## epsg (SRID): 4326
## proj4string: +proj=longlat +datum=WGS84 +no_defs
## INSEE_COM LIBELLE agr1 agr0 art1 art0 cad1
## 1 69001 Affoux 12.069767 0 16.093023 0.00000 12.06977
## 2 69002 Aigueperse 16.192771 0 8.096386 0.00000 0.00000
## 3 69003 Albigny-Sur-Saône 4.982330 0 64.770286 4.98233 209.25785
## 4 69004 Alix 7.963209 0 11.944813 0.00000 27.87123
## 5 69005 Ambérieux 0.000000 0 29.136531 0.00000 20.81181
## 6 69006 Amplepuis 55.434356 0 98.927175 11.89678 106.84847
## cad0 int1 int0 emp1 emp0 ouv1 ouv0
## 1 0.000000 20.11628 0.00000 48.27907 4.023256 32.18605 0.000000
## 2 0.000000 12.14458 0.00000 20.24096 4.048193 28.33735 0.000000
## 3 9.964659 209.25785 14.94699 209.25785 9.964659 109.61125 9.964659
## 4 0.000000 71.66888 0.00000 63.70567 7.963209 51.76086 0.000000
## 5 0.000000 83.24723 0.00000 45.78598 16.649446 37.46125 0.000000
## 6 3.975539 352.42410 35.69072 348.48096 59.365750 474.98472 31.656059
## geometry
## 1 POLYGON ((4.396142 45.85982...
## 2 POLYGON ((4.439457 46.29305...
## 3 POLYGON ((4.837265 45.85363...
## 4 POLYGON ((4.670139 45.90537...
## 5 POLYGON ((4.732623 45.92053...
## 6 POLYGON ((4.346022 45.92994...
for (i in 3:14){
dep69[,i] <- round(dep69[,i, drop=T],0)
}
# agregate field (employed + unemployed)
dep69$agr <- dep69$agr0 + dep69$agr1
dep69$art <- dep69$art0 + dep69$art1
dep69$cad <- dep69$cad0 + dep69$cad1
dep69$int <- dep69$int0 + dep69$int1
dep69$emp <- dep69$emp0 + dep69$emp1
dep69$ouv <- dep69$ouv0 + dep69$ouv1
dep69$act <- dep69$agr + dep69$art + dep69$cad +
dep69$int + dep69$emp + dep69$ouv
head(dep69)
## Simple feature collection with 6 features and 21 fields
## geometry type: POLYGON
## dimension: XY
## bbox: xmin: 4.24347 ymin: 45.82755 xmax: 4.837852 ymax: 46.30282
## epsg (SRID): 4326
## proj4string: +proj=longlat +datum=WGS84 +no_defs
## INSEE_COM LIBELLE agr1 agr0 art1 art0 cad1 cad0 int1 int0 emp1
## 1 69001 Affoux 12 0 16 0 12 0 20 0 48
## 2 69002 Aigueperse 16 0 8 0 0 0 12 0 20
## 3 69003 Albigny-Sur-Saône 5 0 65 5 209 10 209 15 209
## 4 69004 Alix 8 0 12 0 28 0 72 0 64
## 5 69005 Ambérieux 0 0 29 0 21 0 83 0 46
## 6 69006 Amplepuis 55 0 99 12 107 4 352 36 348
## emp0 ouv1 ouv0 agr art cad int emp ouv act
## 1 4 32 0 12 16 12 20 52 32 144
## 2 4 28 0 16 8 0 12 24 28 88
## 3 10 110 10 5 70 219 224 219 120 857
## 4 8 52 0 8 12 28 72 72 52 244
## 5 17 37 0 0 29 21 83 63 37 233
## 6 59 475 32 55 111 111 388 407 507 1579
## geometry
## 1 POLYGON ((4.396142 45.85982...
## 2 POLYGON ((4.439457 46.29305...
## 3 POLYGON ((4.837265 45.85363...
## 4 POLYGON ((4.670139 45.90537...
## 5 POLYGON ((4.732623 45.92053...
## 6 POLYGON ((4.346022 45.92994...
################## Cartography #####################################
library(cartography)
# change projection (lambert93)
dep69 <- st_transform(dep69, 2154)
plot(st_geometry(dep69))
# Map of active population
plot(st_geometry(dep69), col="lightblue", border="ivory")
propSymbolsLayer(dep69, var = "act", col="red")
title("Population active")
# Custom map of active population
par(mar=c(0.2,0.2,1.4,0.2), bg="grey95")
plot(st_geometry(dep69), col="lightblue", border="ivory")
propSymbolsLayer(dep69, var = "act", col="darkblue", inches = 0.6,
border = "white", lwd=0.7, symbols = "square",
legend.style = "e", legend.pos="topright",
legend.title.txt = "Nombre d'actifs\n(2014)",
legend.values.rnd = -1)
barscale(size = 10)
north(pos = "topleft", col = "darkblue")
layoutLayer(title = "Population active dans le département du Rhône",
sources = "Insee, 2018", author = "cartography 2.0.2",
col = "darkblue", coltitle = "white",
frame = TRUE, scale = NULL, north = FALSE)
# get ideal output ratio for the dep69 layer
exp_dim <- getFigDim(x = dep69, width = 600,
mar = c(0.2,0.2,1.4,0.2), res = 100)
png(filename = "output/pop_act.png",
width = exp_dim[1], height = exp_dim[2], res = 100)
# Custom map of active population
par(mar=c(0.2,0.2,1.4,0.2), bg="grey95")
plot(st_geometry(dep69), col="lightblue", border="ivory")
propSymbolsLayer(dep69, var = "act", col="darkblue", inches = 0.6,
border = "white", lwd=0.7, symbols = "square",
legend.style = "e", legend.pos="topright",
legend.title.txt = "Nombre d'actifs\n(2014)",
legend.values.rnd = -1)
barscale(size = 10)
north(pos = "topleft", col = "darkblue")
layoutLayer(title = "Population active dans le département du Rhône",
sources = "Insee, 2018", author = "cartography 2.0.2",
col = "darkblue", coltitle = "white",
frame = TRUE, scale = NULL, north = FALSE)
dev.off()
## png
## 2
## Compare two maps
# use fixmax param
par(mar=c(0,0,1.2,0), bg="grey95", mfrow=c(1,2))
plot(st_geometry(dep69), col="lightblue", border="ivory")
propSymbolsLayer(dep69, var = "cad", col="darkblue",
inches = 0.4, fixmax=63991,
border = "white", lwd=0.5,
legend.pos="n")
north(pos = "topleft", col = "darkblue")
layoutLayer(title = "Cadres",
sources = "Insee, 2018",
author = "cartography 2.0.2",
col = "darkblue", coltitle = "white",
postitle = "center",
frame = F, scale = NULL, north = FALSE)
plot(st_geometry(dep69), col="lightblue", border="ivory")
propSymbolsLayer(dep69, var = "ouv", col="darkred",
inches = 0.4, fixmax=63991,
border = "white", lwd=0.7,
legend.pos="n")
barscale(size = 10)
layoutLayer(title = "Ouvriers",
sources = "", author = "",
col = "darkred", coltitle = "white",
postitle = "center",
frame = F, scale = NULL, north = FALSE)
# use custom legend
legendCirclesSymbols(pos = "topright",
title.txt = "Nombre d'actifs\n(2014)",
var = c(10,10000,25000,64000),
inches = 0.4, col = "lightgrey")
## explore a map interactively
library(mapview)
mapview(dep69)
# add a few toponymes
labelLayer(x = dep69[dep69$INSEE_COM %in% c("69091",
"69243",
"69256",
"69264"),],
txt = "LIBELLE",
pos=3,
halo=TRUE)
# Carte de Typologie
par(mar=c(0,0,1.2,0), bg="grey95", mfrow=c(1,1))
dep69$dom <- "Indéterminé"
dep69$r <- dep69$ouv / dep69$cad
dep69$r[is.na(dep69$r)] <- 0
dep69[dep69$r > 1.1,"dom"] <- "Plus d'ouvriers que de cadres"
dep69[dep69$r < 0.91,"dom"] <- "Plus de cadres que d'ouvriers"
typoLayer(dep69, var="dom",
legend.values.order = c("Plus d'ouvriers que de cadres",
"Plus de cadres que d'ouvriers",
"Indéterminé" ),
col = c('darkred', 'darkblue', 'grey'),
border = "white", lwd=0.5,
legend.title.txt = "Type dominant")
layoutLayer(title = "Ouvriers vs. Cadres",
sources = "", author = "",
col = "darkred", coltitle = "white",
postitle = "center",
frame = F, scale = NULL, north = FALSE)
par(mar=c(0,0,1.2,0), bg="grey95", mfrow=c(1,1))
plot(st_geometry(dep69), col="lightblue", border="ivory")
propSymbolsTypoLayer(dep69, var = "act",var2="dom",
legend.var2.values.order = c("Plus d'ouvriers que de cadres",
"Plus de cadres que d'ouvriers",
"Indéterminé" ),
col = c('darkred', 'darkblue', 'grey'),
inches = 0.45,
legend.var.title.txt = "Nb. actifs",
legend.var.pos = "right",
border = "white", lwd=0.8,
legend.var2.title.txt = "Type dominant")
layoutLayer(title = "Ouvriers vs. Cadres",
sources = "", author = "",
col = "darkred", coltitle = "white",
postitle = "center",
frame = F, scale = NULL, north = FALSE)
# Cartes choroplèthes
dep69$pcad <- 100 * dep69$cad / dep69$act
summary(dep69$pcad)
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.000 9.639 15.504 17.205 23.939 42.151
par(mfrow=c(1,1), mar=c(4,4,4,4))
boxplot(dep69$pcad)
hist(dep69$pcad, 20)
rug(dep69$pcad)
bks <- getBreaks(v = dep69$pcad, method = "q6")
cols <- carto.pal("green.pal", 3,"wine.pal",3)
par(mar = c(0.2,0.2,1.4,0.2), bg="grey95", mfrow=c(1,1))
choroLayer(dep69, var = "pcad", breaks = bks,
col = cols, border = "grey80",
lwd = 0.4, legend.pos = "topright",
legend.title.txt = "Part des cadres\n(en %)")
layoutLayer(title = "Les cadres",
sources = "", author = "", theme = "green.pal",
col = "darkred", coltitle = "white",
postitle = "center",
frame = TRUE, scale = 10)
north(pos = "topleft", south = TRUE)
# Grid map
grid <- getGridLayer(x = dep69, cellsize = 3000*3000,
type = "regular", var = c('cad', 'act'))
grid$pcad <- 100*grid$cad/grid$act
par(mar=c(0.2,0.2,1.4,0.2), bg="grey95", mfrow=c(1,1))
choroLayer(grid, var = "pcad", breaks=bks,
col = cols, border = "grey80",
lwd = 0.4, legend.pos = "topright",
legend.title.txt = "Part des cadres\n(en %)")
layoutLayer(title = "Les cadres",
sources = "", author = "", theme = "green.pal",
col = "darkred", coltitle = "white",
postitle = "center",
frame = TRUE, scale = 10)
north(pos = "topleft", south = TRUE)
# Smooth Map
grid$cad100 <- grid$cad * 100
smoothLayer(x = grid, var = "cad100", var2 = "act",
typefct = "exponential",
span = 2500, beta = 2, breaks = bks, col = cols,
legend.pos = "topright", mask =dep69,
legend.title.txt = "Part des cadres\n(en %)",
border = "grey90", lwd = 0.2)
north(pos = "topleft", south = TRUE)
layoutLayer(title = "Les cadres",
sources = "", author = "", theme = "green.pal",
col = "darkred", coltitle = "white",
postitle = "center",
frame = TRUE, scale = 10)
text(x = 867000, y = 6490000,
labels = "Lissage par potentiels\n fonction exponnentielle\n span = 2.5km, beta = 2",
font = 3, cex = 0.8)
