sdtaylor

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

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(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

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

# 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

# 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

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

library(tidyverse)
library(sf)

# where lon, lat are columns for longitude, latitude, respectively.
# Any other columns are retained in the sf data.frame.

read_csv('site_list.csv') %>%
  st_as_sf(coords = c('lon','lat'), crs=4326)

sdtaylor

library(tidyverse)

# Create a "date bin" data.frame with columns c('start','end')
# start_date, and last_date are dates
# time_bin_size should be string like '1 year','6 month', etc. see ?seq.Date for more examples
bin_dates = function(first_date, last_date, time_bin_size='1 year'){
  if(!(lubridate::is.Date(first_date) & lubridate::is.Date(last_date))) stop('first_date and last_date must be dates')
  if(first_date>=last_date) stop('first_date must come before last date')
  
  full_range = seq.Date(first_date,last_date, by=time_bin_size)