ozjimbob

library(tickle)


x11(type = 'dbcairo', antialias = 'none')
dev.control(displaylist = 'inhibit')

df = data.frame(x=runif(10,-1,1),y=runif(10,-1,1),size=rep(1,10))

size <- reactive_dbl(value=6)
rate <- reactive_dbl(value=10)

ozjimbob

# gdalinfo for a large, integer raster:

Driver: GTiff/GeoTIFF
Files: r_vegmax.tif
Size is 34269, 31580
Coordinate System is:
PROJCS["unknown",
    GEOGCS["unknown",
        DATUM["Unknown_based_on_GRS80_ellipsoid",
            SPHEROID["GRS 1980",6378137,298.2572221010042,

ozjimbob

remove_invalid_poly <- function(xx){
  to_fix=c()
  for(i in 1:nrow(xx)){
    mn <- min(sapply(st_geometry(xx)[[i]], function(x) nrow(x[[1]])))
    if(mn < 4){
      to_fix <- c(to_fix,i)
    }
  }
  
  for(fix_list in to_fix){

ozjimbob

library(tidyverse)
library(purrr)
library(readxl)
library(jsonlite)

# Read your spreadsheet
input <- read_excel("Book1-2.xlsx")

# Take your column C and put it into a list, by interpreting the JSON
data <- map(input$context,fromJSON)

ozjimbob

library(tidyverse)
library(purrr)


# Make a list that looks a bit like yours
# It has two entries
# Each entry has two "normal fields (application, user) - which have different lengths
# And a third field "custom" which contains the weird, staggered dataframe

data <- list()

ozjimbob

deb https://qgis.org/ubuntu-ltr focal main
deb-src https://qgis.org/ubuntu-ltr focal main

deb https://cloud.r-project.org/bin/linux/ubuntu focal-cran40/
deb-src https://cloud.r-project.org/bin/linux/ubuntu focal-cran40/

ozjimbob

# If you don't have them installed, install ggmap and ggplot2 packages

install.packages("ggmap")
install.packages("ggplot2")

# Load these packages

library(ggmap)
library(ggplot2)

ozjimbob

# Simple tibble
d <- tibble(a1="foo",
           a2="bar")

# Want to make a new column called "new" and unite all the "a*" columns together
newcol <- "new"
startchar <- "a"

unite(d,col=newcol,starts_with(startchar)) # Yay

ozjimbob

# General data manipulation
library(tidyverse)

# Spatial data
library(sf)

# Thematic maps
library(tmap)

ozjimbob

# ignoring time=t, just modelling on dx for simplicity

frecent3 <- function(rank,dx){
  a = 6.1625
  cc = 1.6724
  b = 0.2882
  return(( a/(1e-04 * dx + cc)+b) * rank)
}