sdtaylor

library(tidyverse)
library(neonUtilities)
library(geoNEON)

sites = c('JORN','TALL','BART','BARR', 'HARV','YELL')

for(site_id in sites){
woody_structure=tryCatch(neonUtilities::loadByProduct('DP1.10098.001', site=site_id,
                                                      startdate = '2018-01', enddate = '2018-12',

sdtaylor

# Adapted from https://stackoverflow.com/a/7267364/1036500 by Andrie de Vries

# This is it: theme(axis.text.x = element_text(angle = 90, hjust = 1, vjust = 0.5))

library(ggplot2)

td <- expand.grid(
  hjust=c(0, 0.5, 1),
  vjust=c(0, 0.5, 1),
  angle=c(0, 45, 90),

sdtaylor

# Run these first to get all the relevant packages
# For R 4.0 on ubuntio 18.04
# from https://www.digitalocean.com/community/tutorials/how-to-install-r-on-ubuntu-18-04

sudo apt-key adv --keyserver keyserver.ubuntu.com --recv-keys E298A3A825C0D65DFD57CBB651716619E084DAB9
sudo add-apt-repository 'deb https://cloud.r-project.org/bin/linux/ubuntu bionic-cran40/'
sudo apt-get update
sudo apt-get install r-base

# The following packages are also needed for various things in the tidyverse

sdtaylor

library(ggplot2)

# Make a vector of colors of size n based on an RColorBrewer palette
# or list of colors.
get_extended_palette = function(original_palette = 'Paired', n){
  brewer_palettes = rownames(RColorBrewer::brewer.pal.info)
  if(length(original_palette)>=2){
    original_palette_values = original_palette
  } else if(original_palette %in% brewer_palettes){
      original_palette_values = RColorBrewer::brewer.pal(9, original_palette) # most of the palettes have 9 colors to start with

sdtaylor

library(tidyverse)

basemap = map_data('state')

lat_range = c(20,60)
lon_range = c(-150,50)

ggplot() + 
  geom_polygon(data = basemap, aes(x=long, y = lat, group = group), fill=NA, color='black', size=1.5) +
  scale_x_continuous(breaks=seq(lon_range[1],lon_range[2],10), minor_breaks = seq(lon_range[1],lon_range[2],1)) +

sdtaylor

alias aptupdate='sudo apt-get update'
alias aptupgrade='sudo apt-get upgrade'
alias aptinstall='sudo apt-get install'
alias aptremove='sudo apt-get remove'

function csvhead { 
    head "$@" | sed 's/,,/, ,/g;s/,,/, ,/g' | column -t -s,
}

sdtaylor

library(bib2df)

x = bib2df('manuscript/sample.bib')
x$ANNOTE=NA
x$MENDELEY.GROUPS=NA
x$MENDELEY.TAGS=NA
x$ABSTRACT=NA
x$FILE=NA
x$KEYWORDS=NA

sdtaylor

sdtaylor

library(tidyverse)
library(cowplot)

#########################
# Get data
zipped_files = c("1997_daily.csv.zip", "1998_daily.csv.zip", "1999_daily.csv.zip", "2000_daily.csv.zip", "2001_daily.csv.zip", "2002_daily.csv.zip",
                 "2003_daily.csv.zip", "2004_daily.csv.zip", "2005_daily.csv.zip", "2006_daily.csv.zip", "2007_daily.csv.zip", "2008_daily.csv.zip",
                 "2009_daily.csv.zip", "2010_daily.csv.zip", "2011_daily.csv.zip", "2012_daily.csv.zip", "2013_daily.zip", "2014_daily.zip",
                 "2015_daily.zip", "2016_daily.zip", "2017_daily.zip", "2018_daily.zip","2019_daily.zip","2020_daily.zip")
data_folder = 'fawn_data/'

sdtaylor

library(lubridate)
library(dplyr)

####################################################################################
#' Download downscaled climate forecast data
#' 
#' Individual climate models available are are c('CFSv2','CMC1','CMC2','GFDL-FLOR','GFDL','NASA','NCAR'),
#' 'ENSMEAN' is the mean of all models.
#' lead_time is the months into the future to obtain forecasts. Max of 7
#' Default lat and lon are for Portal, AZ