geotheory

#########################################################
#####  Script to load in KML and output to GeoJSON  #####
#####  Robin Edwards, geotheory.co.uk, @geotheory   #####
#########################################################

# This script accepts a simple KML file (e.g. from Google Earth or Scribblemaps.com) and converts to GeoJSON.
# It will not accept KMLs with multiple geometries - they must be entirely of points, paths or polygons, 
# or a primitive geometry (such as rectangle or circle)
# 
# How to run:

geotheory

require(HiveR)
require(plyr)
require(colorspace)
require(classInt)

d = ggplot2::diamonds
d = d[,c(1:4,7)]
head(d); dim(d)

# separate carat-size data into equal interval groups

geotheory

require(maptools)
require(fields)
require(ggplot2)
require(stringr)

bng = "+init=epsg:27700"

workdir = '[change to working directory path]'
setwd(workdir)
R.utils::mkdirs('wz')

geotheory

# read in csv file with headings labelled 'e' and 'n' and output latlons
# call script by command-line: 'RScript bng_to_latlon.R {bng_filename.csv}'

require(rgdal)
args=(commandArgs(TRUE))
datain = read.csv(args[1])
bng = datain
coordinates(bng) = ~ e + n
bng@proj4string = CRS("+init=epsg:27700")
latlon = spTransform(bng, CRS("+proj=longlat +datum=WGS84"))

geotheory

/*
 * Arduino Class for ArrayList
 * Written: Obed Isai Rios
 */


#include "Arduino.h"
#include "ArrayList.h"

ArrayList::ArrayList(char* init){

geotheory

library(shiny)
library(rCharts)
library(ggplot2)
 
data(uspop2000, package = 'leaflet')
base_df <- head(uspop2000[which(uspop2000$State == "AL"), ])
 
shinyServer(function(input, output){
  
  output$myChart <- renderMap({

geotheory

require(ggplot2)
require(stringr)

d = as.vector(round(abs(10 * sapply(1:4, function(n)rnorm(20, mean=n, sd=.6)))))

ggplot(data=NULL, aes(x=1:length(d), y=d, col=cut(d,quantile(d)))) + 
  geom_point(size=5) + scale_colour_manual(values=rainbow(5))

quantile_labels = function(d, qtls, units, round=2, minzero=F, maxplus=F, space=T){
  labs = levels(cut(d, qtls,include.lowest=T))

geotheory

require(grid)
require(scales)
require(reshape2)

# Notes:
# dat       should be a 3 column data.frame with fields in order as per example below
# wave      wavyness of curves defined in terms of x axis data range - experiment to get this right
# ygap      gap between items on each y axis
# col       a single colour or vector of colours for categories when listed in alphabetical order
# leg.mode  if true legend plotted in largest data observation, otherwise custom coordinates (leg.x/y [0,1])

geotheory

require(alluvial)
require(reshape2)

d <- read.table(text="Class,1991,2003,2005,2009,2011,2013
1,818,604,601,570,563,556
2,183,147,145,143,142,150
3,40,55,55,55,55,50
4,48,70,81,76,85,99
5,126,140,142,148,155,153
6,396,566,568,566,525,508

geotheory

require(shiny)
library(ggplot2)

shinyServer(function(input, output) {
  datasetInput <- reactive({
    switch(input$dataset,
           "rock" = rock,
           "pressure" = pressure,
           "cars" = cars)
  })