jebyrnes

make_data <- function(slope =1, int = 1, sd_e = 5, group=1, x=1:20){
  ret <- data.frame(x=x)
  ret <- within(ret, {
    y <- rnorm(length(x), int + slope*x, sd_e)
    group <- group
  })
  
  ret
}

jebyrnes

library(nlme)
library(ggplot2)
library(lubridate)
library(dplyr)

#download data from https://www.google.com/trends/explore#q=%22i%20cant%20even%22&cmpt=q&tz=Etc%2FGMT%2B5
i_cant_even <- read.csv("./i_cant_even.csv", skip=4)

#reformat weeks
i_cant_even$Week  <- as.character(i_cant_even$Week)

jebyrnes

#devtools::install_github("rstudio/leaflet", ref="feature/color-legend")
library(leaflet)
library(RColorBrewer)
set.seed(100)
pdf <- data.frame(Latitude = runif(100, -90,90), Longitude = runif(100, -180,180))

#make a property with colors
pdf$Study <- rep(1:10,10)

#need to create a pal using colorbin

jebyrnes

#Load the library and make a basic map
library(leaflet)
leaflet() %>% addTiles()


#Show a map with a satellite picture on it 
leaflet() %>% 
  addTiles(urlTemplate="http://server.arcgisonline.com/ArcGIS/rest/services/World_Imagery/MapServer/tile/{z}/{y}/{x}")

#Make a demo fake data set

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#########################################################################
# Code to import and make useful
# Spalding et al. 2007's Marine Ecoregions of the World
# Data provided by http://www.marineregions.org/downloads.php
# by Jarrett Byrnes
# last updated 3/26/2015
#########################################################################

######################
##### Load Libraries

jebyrnes

#just create a range of values
grdVals <- function(x, bound=0.01) seq(range(x)[1]-bound, range(x)[2]+bound, length.out=50)

#instantiate a new persp object for a scatterplot
makeScatterBox <- function(x,y,z, bound=0, ...){
  x <- grdVals(x, bound=bound)
  y <- grdVals(y, bound=bound)
  z <- grdVals(z, bound=bound)
  z <- matrix(rep(z, 50), nrow=50)

jebyrnes

\documentclass{article}

\begin{document}
<<echo=FALSE>>=
activityDF <- structure(list(julian_day = 1:365, food = c(92.6182247978374, 
                                                          199.361820535986, 128.619308542186, 131.048504694701, 44.6344539529983, 
                                                          139.02542881751, 118.815437972886, 85.5963235153311, 73.9459098960665, 
                                                          85.6671795660157, 195.954639346317, 192.942941724749, 193.341526021202, 
                                                          142.419581610027, 130.23002915561, 232.843857188757, 105.14817987285, 
                                                          131.58751463704, 123.30056211349, 150.447279408636, 138.40775613945, 

jebyrnes

library(multifunc)
data(all_biodepth)
allVars<-qw(biomassY3, root3, N.g.m2,  light3, N.Soil, wood3, cotton3)

germany<-subset(all_biodepth, all_biodepth$location=="Germany")

vars<-whichVars(germany, allVars)

#re-normalize N.Soil so that everything is on the same sign-scale (e.g. the maximum level of a function is the "best" function)
germany$N.Soil<- -1*germany$N.Soil +max(germany$N.Soil, na.rm=TRUE)

jebyrnes

############################################################################################
# 
# Script to turn lat/long data into
# marine ecoregions using Spalding's Marine Ecoregions
# of the World (MEOW).
#
# To run, first acquire the appropriate GIS files from 
# http://maps.tnc.org/gis_data.html and unzip them into
# a directory (MEOW-TNC) - then go from there.
#

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library(multifunc)
library(wesanderson)
data(all_biodepth)
allVars<-qw(biomassY3, root3, N.g.m2, light3, N.Soil, wood3, cotton3)
 
germany<-subset(all_biodepth, all_biodepth$location=="Germany")
 
vars<-whichVars(germany, allVars)
 
#re-normalize N.Soil so that everything is on the same sign-scale (e.g. the maximum level of a function is the "best" function)