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# ADAPTED FROM:
# - Spencer Schien's rayshader+kontur tutorial: https://justjensen.co/making-population-density-maps-with-rayrender-in-r/
# - Erik Jensen's adaptation of it: https://justjensen.co/making-population-density-maps-with-rayrender-in-r/ 

# INSTALL NECESSARY PACKAGES

install.packages("sf")
install.packages("rayrender")
install.packages("rayshader")
install.packages("R.utils")

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$(function(){
    var json_url = $('#json_url').attr('href');
    $.get(json_url, function(data){
        if(data.location.tz){

          var local_time = new Date( new Date().getTime() + data.location.tz_offset * 1000).toUTCString().replace( / GMT$/, "" ).substring(17,22);
          $("#local_time").html(local_time);
          $("#time_zone").html(data.location.tz);
          $("#time_info").removeClass('invisible');
        };

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<style>
  .flag {
  -webkit-filter: grayscale(100%); /* Safari 6.0 - 9.0 */
  filter: grayscale(100%);
	height: 0.7em;
  moz-border-radius: 0px;
  -webkit-border-radius: 0px;
  border-radius: 0px;
	}
</style>

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{'created': '2018-01-23T14:05:23.521397Z',
 'project_member_id': '92469662',
 'message_permission': True,
 'sources_shared': [],
 'username': 'gedankenstuecke',
 'data': [{'id': 36938,
   'basename': 'example_data1.txt',
   'created': '2018-04-03T04:28:53.193902Z',
   'download_url': 'https://example.com',
   'metadata': {'tags': ['example', 'text', 'demo'],

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sys.stdout.write("\r[%s%s]%d%s"%('.'*d,
                                 ''*(50-d),
                                 d*2,'%'))

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# get new directory for this

mkdir celery
cd celery

# create environment w/ py2.7
conda create -n celery python=2.7

# switch to environment
source activate celery

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library(ggplot2)

agree <- rnorm(15000, 3.72, 0.68)
concs <- rnorm(15000, 3.63, 0.72)
extra <- rnorm(15000, 3.27, 0.89)
neuro <- rnorm(15000, 3.21, 0.84)
openn <- rnorm(15000, 3.93, 0.67)

big5 <- data.frame(agreeableness=agree, 
                   conscientiousness=concs,

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DOI	is_open_access	best_open_access_host
10.1038/001009a0	False	NA
10.1038/001023a0	False	NA
10.1038/001043a0	False	NA
10.1038/001085b0	False	NA
10.1038/001112b0	False	NA
10.1038/001189c0	False	NA
10.1038/001213a0	False	NA
10.1038/001308a0	False	NA
10.1038/001315c0	False	NA

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library(taxize)
library(reshape2)

### stuff starts here

#### remove the rank filter from the clustering method

class2tree_helper_no_filter <- function(x){
  #x <- x[!x$rank == "no rank", ]
  df <- x[-nrow(x), 'id']