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‎R/scrape_emoticons.R

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@@ -8,14 +8,22 @@ library(dplyr)
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# url <- "http://apps.timwhitlock.info/emoji/tables/unicode"
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# using a local copy due to connection issues with the above url
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<<<<<<<HEAD
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url<- paste0("~/projects/audiences", "/Emoji unicode characters for use on the web.html")
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=======
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url<- paste0(datadir, "/Emoji unicode characters for use on the web.html")
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>>>>>>>64cbec55ab53574be1346db0d0b7ae9cce410194
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# get emoticons
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emoticons<-url %>%
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read_html() %>%
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html_nodes(xpath='/html/body/div[2]/div/div/table[1]') %>%
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html_table()
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<<<<<<<HEAD
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# emoticons <- data.frame(emoticons[[1]]$Native, emoticons[[1]]$Unicode, emoticons[[1]]$Bytes,
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=======
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# emoticons <- data.frame(emoticons[[1]]$Native, emoticons[[1]]$Unicode, emoticons[[1]]$Bytes,
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>>>>>>>64cbec55ab53574be1346db0d0b7ae9cce410194
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# emoticons[[1]]$Description, stringsAsFactors = FALSE)
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# names(emoticons) <- c("Native", "Unicode", "Bytes", "Description")
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@@ -24,7 +32,11 @@ addemoticons <- url %>%
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read_html() %>%
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html_nodes(xpath='/html/body/div[2]/div/div/table[6]') %>%
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html_table()
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<<<<<<<HEAD
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# addemoticons <- data.frame(addemoticons[[1]]$Native, addemoticons[[1]]$Bytes,
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=======
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# addemoticons <- data.frame(addemoticons[[1]]$Native, addemoticons[[1]]$Bytes,
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>>>>>>>64cbec55ab53574be1346db0d0b7ae9cce410194
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# addemoticons[[1]]$Description, stringsAsFactors = FALSE)
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# names(addemoticons) <- c("Native", "Bytes", "Description")
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@@ -33,7 +45,11 @@ dingbats <- url %>%
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read_html() %>%
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html_nodes(xpath='/html/body/div[2]/div/div/table[2]') %>%
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html_table()
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<<<<<<<HEAD
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# dingbats <- data.frame(dingbats[[1]]$Native, dingbats[[1]]$Bytes,
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=======
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# dingbats <- data.frame(dingbats[[1]]$Native, dingbats[[1]]$Bytes,
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>>>>>>>64cbec55ab53574be1346db0d0b7ae9cce410194
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# dingbats[[1]]$Description, stringsAsFactors = FALSE)
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# names(dingbats) <- c("Native", "Bytes", "Description")
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@@ -86,4 +102,8 @@ addothers <- url %>%
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alltogether<- bind_rows(list(emoticons[[1]], addemoticons[[1]], dingbats[[1]], transport[[1]],
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addtransport[[1]], enclosed[[1]], uncategorized[[1]], addothers[[1]]))
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<<<<<<<HEAD
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names(alltogether) <- c("Native", "Apple", "Android", "Android2", "Symbola", "Twitter", "Unicode", "Bytes", "Description")
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=======
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names(alltogether) <- c("Native", "Apple", "Android", "Symbola", "Twitter", "Unicode", "Bytes", "Description")
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>>>>>>>64cbec55ab53574be1346db0d0b7ae9cce410194

‎config.toml

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@@ -8,8 +8,13 @@ Paginate = 6
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publishDir = "docs"
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# RelativeURLs = true
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CanonifyURLs = true
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<<<<<<< HEAD
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ignoreFiles = [ "reports/_.*" ]
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# ignorefiles = [ "reports/*" ]
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=======
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# ignoreFiles = [ "reports/_.*" ]
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ignoreFiles = [ "reports/*" ]
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>>>>>>> 64cbec55ab53574be1346db0d0b7ae9cce410194
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[taxonomies]

‎docs/index.html

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‎fig_1.R

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@@ -61,6 +61,7 @@ for(panel in 1:4){
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rowwise() %>%
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mutate(gamma=gamma+runif(1,0,0.0001))
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<<<<<<<HEAD
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userlookup<- lookup_users(unique(bios_lda_gamma$document))
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fig_dat<- left_join(bios_lda_gamma, userlookup %>%
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write_tsv(fig_dat, paste0("audiences/paper_data/fig1", letters[panel], ".txt"))
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=======
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>>>>>>>64cbec55ab53574be1346db0d0b7ae9cce410194
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docs_order<-bios_lda_gamma %>%
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group_by(document) %>%
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arrange(topic, -gamma) %>%

‎paper_data/README.md

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# Supplementary Data for the paper “Quantifying and contextualizing the impact of bioRxiv preprints through automated social media audience segmentation”
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## S1_Data.xlsx
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This file contains underlying data (Twitter IDs and the inferred audience sector breakdown for each user) for the audience segmentations of each of the 4 preprints displayed in Fig 1, with data for each preprint in a separate sheet.
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## S2_Data.txt
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This file contains summary data and metadata (title, DOI, date posted, bioRxiv category, Altmetric’s estimated academic audience fraction, our estimated academic audience fraction, fractions of users exceeding the 2%, 5%, 10%, and 20% extremist network homophily thresholds, number of tweets analyzed, Altmetric score, number of citations in mainstream media, number of citations in the academic literature) for the 1,800 preprints analyzed. Information for each preprint is replicated across 12 rows (1 per audience sector), with additional columns indicating the topic number and top 30 keywords and fraction of audience associated with that topic. These data underlie Figs 1-4, Table 1, and Supplementary Figs S1-S6.

‎render_reports.R

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@@ -34,7 +34,11 @@ options(timeout = 600)
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# set relative path for calling external files from within this script
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# datadir <- dirname(sys.frame(1)$ofile)
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<<<<<<<HEAD
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datadir<- paste0(getwd(), "/projects/audiences")
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=======
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datadir<- paste0(getwd(), "/audiences")
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>>>>>>>64cbec55ab53574be1346db0d0b7ae9cce410194
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# Twitter oauth keys, email, other private data (e.g., hf_path)
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keys<- yaml.load_file(paste0(datadir, "/_config.yaml"))
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dir.create(outdir, recursive=TRUE, showWarnings=FALSE)
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# handles of training data
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<<<<<<<HEAD
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td_handles<- readRDS(paste0(datadir, "/training_data/training_data_handles.rds")) %>% pull(account)
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=======
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td_handles<- read.table("~/td_handles.txt") %>% pull
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>>>>>>>64cbec55ab53574be1346db0d0b7ae9cce410194
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# biorxiv categories, excluding scicomm and clinical trials
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categories_trim<- c("animal-behavior-and-cognition",
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files_to_scan<- update_follower_files(datadir)
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<<<<<<<HEAD
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readRDS_safe<- possibly(readRDS, otherwise= tibble())
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high_followers<-files_to_scan %>%
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map_dfr(readRDS_safe) %>%
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=======
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high_followers<-files_to_scan %>%
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map_dfr(readRDS) %>%
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>>>>>>>64cbec55ab53574be1346db0d0b7ae9cce410194
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rowwise() %>%
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mutate(nfollowers= length(followers)) %>%
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arrange(desc(nfollowers)) %>%

‎report_template.rmd

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@@ -540,9 +540,14 @@ plot_embedding_bars <- function(plotdat, docs_order){
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p <- plotdat %>%
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mutate(topic=factor(topic, levels=unique(plotdat$topic))) %>%
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<<<<<<< HEAD
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ggplmutate(url=paste0("https://twitter.com/", document)) %>%
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ot(aes(x=document, y=gamma, fill=topic))+
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, customdata=url geom_bar(stat="identity", position="stack")+
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=======
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ggplot(aes(x=document, y=gamma, fill=topic))+
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geom_bar(stat="identity", position="stack")+
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>>>>>>> 64cbec55ab53574be1346db0d0b7ae9cce410194
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scale_fill_manual(values=cols)+
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scale_y_continuous(expand = c(0,0))+
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scale_x_discrete(position = "top")+
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yanchor = "bottom",
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x = 0, y=-1))
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# Clickable points link to profile URL using onRender: https://stackoverflow.com/questions/51681079
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<<<<<<< HEAD
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for(# for(i in 1:12){
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# ply$x$data[[i]]$customdata <- paste0("https://twitter.com/", docs_order$document)
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# #pp <- add_markers(pp, customdata = ~url)
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=======
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for(i in 1:12){
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ply$x$data[[i]]$customdata <- paste0("https://twitter.com/", docs_order$document)
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}
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#pp <- add_markers(pp, customdata = ~url)
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>>>>>>> 64cbec55ab53574be1346db0d0b7ae9cce410194
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plyout <- onRender(ply, "
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function(el, x) {
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el.on('plotly_click', function(d) {

‎themes/mondrian

Submodule mondrian deleted from f1e8075

‎themes/mondrian/LICENSE

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The MIT License (MIT)
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Copyright (c) 2019 YOUR_NAME_HERE
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Permission is hereby granted, free of charge, to any person obtaining a copy of
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this software and associated documentation files (the "Software"), to deal in
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the Software without restriction, including without limitation the rights to
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use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of
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the Software, and to permit persons to whom the Software is furnished to do so,
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subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS
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FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
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COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER
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IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
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CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

‎themes/mondrian/README.md

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# hugo-mondrian-theme
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Mondrian-like minimal theme for Hugo static site generator.
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![](https://raw.githubusercontent.com/redraw/hugo-mondrian-theme/master/images/screenshot.gif)
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# Using
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Copy the theme in `themes/mondrian` folder or add it as a git submodule,
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```bash
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$ git submodule add https://github.com/redraw/hugo-mondrian-theme.git themes/mondrian
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$ hugo server -t mondrian
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```
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Colors are configurable per [content-type](https://gohugo.io/content-management/types/) and you can modify them in your `config.toml`, along with minor settings
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```toml
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[params]
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showHeader = true
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showTags = true
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debug = false
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[params.colors]
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post = "orangered"
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page = "gold"
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sketch = "limegreen"
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```
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If you want to test the `exampleSite`, run
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```bash
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$ cd themes/mondrian/exampleSite
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$ hugo server --themesDir ../..
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```
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### Notes
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[Beerware](https://gitter.im/hugo-mondrian-theme) (?)

‎themes/mondrian/archetypes/default.md

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+++
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+++

‎themes/mondrian/archetypes/sketch.html

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---
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title: "{{ replace .Name "-" " " | title }}"
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date: {{ .Date }}
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description: ""
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libs:
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js:
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- https://cdnjs.cloudflare.com/ajax/libs/p5.js/0.7.3/p5.min.js
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---
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<script>
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functionsetup(){
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varcanvas=createCanvas(windowWidth,windowHeight)
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canvas.parent('main')
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}
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functiondraw(){}
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functionwindowResized(){
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resizeCanvas(windowWidth,windowHeight);
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}
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</script>

‎themes/mondrian/data/default.toml

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showHeader = true
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showTags = true
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debug = false
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[colors]
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post = "orangered"
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posts = "gold"
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page = "blue"
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sketch = "limegreen"

‎themes/mondrian/exampleSite/config.toml

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# this setting is relevant for the theme demo on the Hugo Themes website
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ignoreFiles = [
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"content/posts/\\.*",
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"content/portfolio/\\.*",
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"content/product/\\.*",
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"content/en/\\.*",
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"content/fr/\\.*",
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"content/es/\\.*",
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"content/de/\\.*",
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"content/zh-tw/\\.*",
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"content/zh-cn/\\.*"
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]
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baseURL = "http://example.org/"
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languageCode = "en"
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title = "hugo-mondrian-theme"
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theme = "mondrian"
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[taxonomies]
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tag = "tags"
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[params]
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showHeader = true
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showTags = true
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debug = false
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[params.colors]
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post = "orangered"
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posts = "gold"
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page = "blue"
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sketch = "limegreen"
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[menu]
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[[menu.main]]
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name = "posts"
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url = "/post"
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weight = 1
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[[menu.main]]
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name = "sketches"
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url = "/sketch"
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weight = 2
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‎themes/mondrian/exampleSite/content/about.md

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---
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title: "Single Page"
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date: 2019-03-04T23:37:33-03:00
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---
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Single Page

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