dots_for_matej.R

library(tidyverse)
library(sf)

#https://www.cultureofinsight.com/blog/2018/05/02/2018-04-08-multivariate-dot-density-maps-in-r-with-sf-ggplot2/

svk.dot <- st_read("shp/hranice_obce_3.shp", stringsAsFactors = FALSE, quiet = TRUE) %>% 
  st_transform(4326)

colnames(svk.dot)[1] <- "id"

nrsr<- read.csv("nrsrall.csv",fileEncoding = "UTF-8",check.names=TRUE, stringsAsFactors = FALSE)

colnames(nrsr)[2] <- "id"

svk.dot <- left_join(nrsr, svk.dot) %>% 
  st_as_sf()

random_round <- function(x) {
  v=as.integer(x)
  r=x-v
  test=runif(length(r), 0.0, 1.0)
  add=rep(as.integer(0),length(r))
  add[r>test] <- as.integer(1)
  value=v+add
  ifelse(is.na(value) | value<0,0,value)
  return(value)
}

num_dots <- as.data.frame(svk.dot) %>% 
  select(tip_16:sas_16) %>% 
  mutate_all(funs(. / 100)) %>% 
  mutate_all(random_round)

sf_dots <- map_df(names(num_dots), 
                  ~ st_sample(svk.dot, size = num_dots[,.x], type = "random") %>% 
                    st_cast("POINT") %>%                                          
                    st_coordinates() %>%                                          
                    as_tibble() %>%                                               
                    setNames(c("lon","lat")) %>%                                  
                    mutate(category = .x)
                  ) %>% 
  slice(sample(1:n()))