rmarrotte

####################################
# Run zonal statistics in parallel #
####################################

# Clear workspace
rm(list=ls())

# Libraries
library(raster)
library(gstat)

rmarrotte

########################################
####        Getting started         ####
########################################

 # Make a place holder for the cs_run.exe path
 CS_exe <- 'C:/"Program Files"/Circuitscape/cs_run.exe' # Don't forget the "Program Files" problem

# We want to run one of the CS examples found in /examples/, first we need to fix the .ini file
# We first read in the .ini file and then we change the arguments
Example_lines <- readLines("C:/Program Files/Circuitscape/examples/eight_neighbor_example.ini")

sckott

Example parallel workflow

In this example, we use the rgbif package to search for occurrence (lat/long) data for 1000 species

Install and load rgbif

install.packages("rgbif")
library("rgbif")

florianhartig

library(mvtnorm)   # to draw multivariate normal outcomes
library(R2jags)    # JAGS-R interface

# function that makes distance matrix for a side*side 2D array  
dist.matrix <- function(side)
{
  row.coords <- rep(1:side, times=side)
  col.coords <- rep(1:side, each=side)
  row.col <- data.frame(row.coords, col.coords)
  D <- dist(row.col, method="euclidean", diag=TRUE, upper=TRUE)

josecarlosgonz

Using Google Maps API and R

This script uses RCurl and RJSONIO to download data from Google's API to get the latitude, longitude, location type, and formatted address

library(RCurl)
library(RJSONIO)
library(plyr)

fawda123

#import relevant packages
library(gstat)
library(sp)
library(nlme)

#create simulated data, lat and lon from uniformly distributed variable, exp1 and exp2 from random normal
set.seed(2)
samp.sz<-400
lat<-runif(samp.sz,-4,4)
lon<-runif(samp.sz,-4,4)