datagistips

library(RCurl)
library(rjson)

whatGoogleSuggestsFor <- function(question, domain="fr") {

# Domain : here, just France or USA
# You could add URLs for some other countries
if (domain == "fr") {
	baseU <- "https://www.google.fr/s?gs_rn=45&sclient=psy-ab"
} else {

datagistips

library(rgdal)
library(maptools)
library(classInt)

setwd("F:/METHODES/1205_CAMPAGNE_PRES")

#########################
## READING SOURCE DATA ##
#########################
# on intègre les contours des communes GEOFLA

datagistips

## ATTENTION !!: l'utilisation de ce code nécessite d'avoir 
# lancé le code précédent (https://gist.github.com/2857180) , 
# en gros d'avoir créé l'objet spatial comm2 avec les résultats du vote. 

library(rgdal)
library(spatstat)
library(maptools)

## COERCING DATA for SPATSTAT ##
# on lit le trait de côte téléchargé depuis

datagistips

library(rgdal)

# DATA
# http://professionnels.ign.fr/ficheProduitCMS.do?idDoc=6185461
cities <- readOGR("C:/DATAS/GEOFLA/COMMUNES/COMMUNE.SHP", "COMMUNE")
# http://www.data-publica.com/opendata/13495--resultats-du-deuxieme-tour-de-l-election-presidentielle-2012
votes <- read.csv2("IN/votesResults2012.csv",sep=",", quote="\"") 

# VOTES TO SPATIAL DATA "
votes$pc.sar <- votes$results.sarkozy /  votes$results.exprimes

datagistips

library(gdata)
library(reshape)
library(classInt)

###############
# INTEGRATING #
###############

f <- read.xls("IN/Leg 2012 Candidatures T1 31 05 2012.xls", sheet=1)
nuances <- read.xls("IN/Leg 2012 Candidatures T1 31 05 2012.xls", sheet=2, skip=2, header=FALSE)

datagistips

library(gdata)
library(stringr)

#Fichier source : http://www.data-publica.com/data/13622--resultat-par-circonscription-du-2nd-tour-des-elections-legislatives-17-juin-2012
res <- read.xls("IN/Leg 2012 Résultats CirLG FE T2.xls") # résultats législatifs

###########################
# RECUPERATION DU GAGNANT #
###########################

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##[datagistips]=group
##polygons=vector
##distance=number 10
##output=output vector

library("spdep")

nb = poly2nb(polygons, snap=distance)
 
polygons[["nNeigh"]] = card(nb)

datagistips

library(rgdal)
library(spdep)

pol <- readOGR(".", "buildings") # read the data using rgdal

nb <- poly2nb(pol, snap=50) # create a graph. Two buildings are connected if they are 50 meters apart from one another.

pol$nNeigh <- card(nb) # card(nb) gives the neighbor counts

pol$neighGroup <- n.comp.nb(nb)$comp.id # n.comp.nb contains the informations about the disconnected compontents

datagistips

library(rgdal)
library(wordcloud)
library(reshape)
library(maptools)
library(classInt)
library(FactoMineR)
library(FNN)

### LOAD DATA ###
f <- readOGR(".", "COMMUNE")

datagistips

creerGrille = function(pol, size=50000) {
  r = raster(extend(extent(pol), size)); res(r) = size; r[]=1
  grille = rasterToPolygons(r)
  grille = grille[which(gIntersects(grille, pol, byid=T)), ]
  grille = grille[-which(gTouches(grille, reg, byid=T)), ]
  return(grille)
}

extractFrequencies = function(grille, r, values) {