jebyrnes

###########
# Calculate a Dunnett's test
# using information from a meta-analysis
# using definitions at http://davidmlane.com/hyperstat/B112114.html
#
# Jarrett Byrnes
# 12/8/2013
###########

#helper functions

jebyrnes

#the range of possible snow
minsnow <- 0
maxsnow <- 12 #1 foot - WOOOO!!!

#a range of snow values
snowdist <- seq(minsnow, maxsnow, 0.01)
len <- length(snowdist)

#let's assume a log normal distribution of the snow
#we might get, with a conservative mean of ~1

jebyrnes

library(Reol)


getOrder <- function(binom_taxa, db = "NCBI Taxonomy"){
  MyEOLs <- DownloadSearchedTaxa(binom_taxa, to.file=FALSE)
  hier <- DownloadHierarchy(MyEOLs, FALSE, database=db)
  taxonomic_info <- CombineHierarchyInfo(hier)
  ord <- which(taxonomic_info[[2]]=="Order")
  return(taxonomic_info[[1]][ord,1])
}

jebyrnes

################################
# Problem: You have a ragged
# data frame where species that have not
# been seen as a site simply don't have a 
# line in your data frame. You have a long
# data frame, but you want a long data frame
# where missing species have proper zeroes
#
# Solution: a combination of dcast and melt
# from the reshape2 package

jebyrnes

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)

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.
#

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

\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

#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

#########################################################################
# 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