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### Plot length summary
data=read.csv("plotBAincr.csv",stringsAsFactors=F)
data$Date.start=as.Date(data$Date.start)
data$Date.end=as.Date(data$Date.end)
plotlist=unique(data$Plot)
out_frame=data.frame(Plot="",Date.start="",Date.end="",length=0,stringsAsFactors=F)
@ozjimbob
ozjimbob / engine.r
Created December 11, 2012 23:55
SPAM Model
# Run model simulation with given values for:
# initial cull, maintenance cull, cell target density, allocated budget,
# area to cull, and "control area" (area for which proportional population is calculated)
# (last two are kept separate for the spatial optimisation, where we may choose to cull a subset
# of the target control area for efficiency)
run.sim = function(curr.init.cull, curr.maint.cull, curr.target.density, budget, C.mask, ctrl.mask)
{
Nx = ncol(K); Ny = nrow(K); # gauge size of map
IC = K # note - initial population is set to carrying capacity
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@ozjimbob
ozjimbob / demiowa.r
Created February 2, 2016 02:39
R Dem Iowa Caucus Graph
library(rjson)
library(httr)
turl="https://iowadems-caucussitecdn-prod2.azureedge.net/api/statecandidateresults"
a=GET(turl)
arr=c(content(a)$StateResults[[1]]$WinPercentage,content(a)$StateResults[[2]]$WinPercentage,content(a)$StateResults[[3]]$WinPercentage)
nam=c(content(a)$StateResults[[1]]$Candidate$DisplayName,content(a)$StateResults[[2]]$Candidate$DisplayName,content(a)$StateResults[[3]]$Candidate$DisplayName)
colr=c(content(a)$StateResults[[1]]$Candidate$Color,content(a)$StateResults[[2]]$Candidate$Color,content(a)$StateResults[[3]]$Candidate$Color)
rar=round(arr,3)*100
barplot(arr,names.arg=nam,col=colr)
@ozjimbob
ozjimbob / sph_hillshade.r
Last active August 16, 2016 05:44
Example code to great a hillshade raster from a DEM in R using spherical environment mapping for the colour scheme.
library(raster)
library(jpeg)
# Spherical environment mapping hillshade function
getv=function(i,a,s){
ct = dim(i)[1:2]/2
sx = values(s)/90 * ct[1]
sy = values(s)/90 * ct[2]
a = values(a) * 0.01745
px = floor(ct[1] + sx * -sin(a))
@ozjimbob
ozjimbob / blitz.r
Last active November 29, 2017 01:09
## Load required packages
# you will need to install these, first do
# eg. install.packages("tidyverse")
# etc. to install them one by one
library(tidyverse)
library(httr)
library(sf)
library(tmap)
data = tibble(foo=c("Bah","Fuzz"))
my_column="foo"
data %>% filter(!!my_column := "Bah")
library("reticulate")
library(tidyverse)
library(purrr)
# We use the python "holidays" package for the basic holidays
# Installed it using pip first
holidays <- import("holidays")
tas_holidays <- holidays$Australia(prov="TAS")
# List of all dates from 2000 to 2018
@ozjimbob
ozjimbob / access.r
Last active November 21, 2018 10:47
Example of downloading and plotting ACCESS met model data in R
# Demonstration - Downloading and animating ACCESS forecast data
# grant.williamson@utas.edu.au
# General functions, including str_replace, map
library(tidyverse)
# threddscrawler is a useful package for parsing THREDDS data servers
# Install it with:
# devtools::install_github("BigelowLab/threddscrawler")
library(threddscrawler)