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(XML)
library(RCurl)
library(rgdal)

source("DORLING.R")

# GEOGLA DEPARTEMENTS
deps <- readOGR(".", "DEPARTEMENT.shp")

# LIST URLS

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library(rgeos)
library(spdep)


# DISTANCE

distance <- function(pt1, pt2) {
  dx <- pt1[1] - pt2[1]
  dy <- pt1[2] - pt2[2]
  l <- sqrt(dx^2 + dy^2)  

datagistips

library(rgeos)
library(maptools)
 
load("F:/DATAS/DEPARTEMENT.rda")
 
foret <- read.csv2("IN/foret.csv")
 
 
######################
## SCALED CARTOGRAM ##

datagistips

Map {
  background-color: rgb(50,50,50);
}


#deps {
	
  line-color:white;
  line-width:1;
  line-opacity:.8;

datagistips

library(rgdal)

countries <- readOGR("D:/DATAS/NATURAL EARTH/ne_110m_admin_0_countries_lakes/ne_110m_admin_0_countries_lakes.shp", "ne_110m_admin_0_countries_lakes")

first <- substr(as.character(countries$name),0,1) # on détermine la première lettre du nom du pays
first[grep("Sahara", countries$name)] <- "S"
first[grep("Guinea", countries$name)] <- "G"
first[grep("Korea", countries$name)] <- "K"
first[grep("Congo", countries$name)] <- "C"
first[grep("Antarctic", countries$name)] <- "A"

datagistips

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

setwd("D:/METHODES/1211_ELONGATEDCOUNTRIES/")

countries <- readOGR("D:/DATAS/NATURAL EARTH/ne_110m_admin_0_countries_lakes/ne_110m_admin_0_countries_lakes.shp", "ne_110m_admin_0_countries_lakes")

datagistips

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

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

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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

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

library("spdep")

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