thomasp85

library(ggplot2)
library(gganimate)
library(sf)
earth <- sf::st_as_sf(rnaturalearth::countries110)
views <- data.frame(rbind(
  st_bbox(earth[earth$name == 'Denmark',]),
  st_bbox(earth[earth$name == 'Australia',])
))
p <- ggplot() + 
  geom_sf(data = earth, fill = 'white') + 

thomasp85

library(sf)
library(ggplot2)
library(gganimate)

# Data from personal correspondance

# Collapse all dates to the same year
d$year <- format(d$date, '%Y')
d$stand_time <- as.POSIXct(paste0('2000-', format(d$date, '%m-%d %T')))

thomasp85

library(gapminder)
library(ggplot2)
library(gganimate)

p <- ggplot(gapminder, aes(gdpPercap, lifeExp, size = pop, colour = country)) +
  geom_point(alpha = 0.7) +
  scale_colour_manual(values = country_colors) +
  scale_size(range = c(2, 12)) +
  scale_x_log10() +
  facet_wrap(~continent) +

thomasp85

library(ggraph)
library(tidygraph)
library(gganimate)

# Data from http://konect.uni-koblenz.de/networks/sociopatterns-infectious
infect <- read.table('out.sociopatterns-infectious', skip = 2, sep = ' ', stringsAsFactors = FALSE)
infect$V3 <- NULL
names(infect) <- c('from', 'to', 'time')
infect$time <- as.POSIXct(infect$time, origin = Sys.time() - as.numeric(Sys.time()))

thomasp85

library(magick)
library(reshape2)
library(dplyr)
library(tidygraph)
library(particles)
library(animation)

plot_fun <- function(sim) {
  df <- as_tibble(sim)
  plot(df$x, df$y, col = df$color, pch = '.', axes = FALSE, xlim = c(-100, 317), ylim = c(-268, 100), xlab = NA, ylab = NA)

thomasp85

library(tidygraph)
library(particles)
library(jsonlite)
library(magick)

# Prepare text polygons
text <- read_json('text.json')
par_text <- text$layers[[3]]$paths
on_text <- text$layers[[2]]$paths
cran_text <- text$layers[[1]]$paths

thomasp85

---
title: "R Notebook"
output: html_notebook
---

# Difference in behavior between ggplot2 and patchwork plots in Notebooks

Consider the following ggplot

```{r}

thomasp85

library(future)
trim_model <- function(model, predictor = predict, ..., ignore_warnings = TRUE) {
  # Cache the correct output
  true_pred <- predictor(model, ...)
  
  # Treat prediction warnings as errors?
  if (!ignore_warnings) {
    old_ops <- options(warn = 2)
    on.exit(options(old_ops))
  }

thomasp85

Keybase proof

I hereby claim:

• I am thomasp85 on github.
• I am thomasp85 (https://keybase.io/thomasp85) on keybase.
• I have a public key ASDRGUror8ScAXuoC-MJVs06sOwPsdpyP9RU3GrLfkKU9Qo

To claim this, I am signing this object:

thomasp85

library(ggforce) # need github version
library(tweenr)
library(animation)

# Define the different states
controls <- list(
    data.frame(
        x = runif(6),
        y = runif(6),
        col = 'steelblue',