steveharoz

StatEndpoint <- ggproto("StatEndpoint", Stat,
  compute_group = function(data, scales) {
    # sort by x so indexing is meaningful
    data = arrange(data, x)
    # grab only the first and last row
    data[c(1,nrow(data)),]
  },
  
  required_aes = c("x", "y")
)

steveharoz

x,y,value
1,205,0.3125
1,204,0.3125
1,203,0.3125
1,202,0.3125
1,201,0.3125
1,200,0.3125
1,199,0.3125
1,198,0.3125
1,197,0.3125

steveharoz

painbow moved to github: https://github.com/steveharoz/painbow

steveharoz

library(tidyverse)

set.seed(999)

data = tibble(
  name = c("A1", "A2", "A3", "A4", "B1", "B2", "B3", "B4", "C1", "C2"),
  value = rnorm(10, 10, sd = 3),
  color = c(
    hcl(220, seq(60, 30, -10), seq(50, 80, 10)),
    hcl(0, seq(60, 30, -10), seq(50, 80, 10)),

steveharoz

library(tidyverse)

# arbitrary number
district_count = 38

# population from stephanie's figure
# https://twitter.com/evergreendata/status/1450862060972216320
population = c(
  rep("White", 40),
  rep("Latino", 39),

steveharoz

library(tidyverse)
library(magrittr)
library(afex)
library(Superpower)

set.seed(555)
SUBJECT_COUNT = 3 # per between-subject condition

#### ground-truth parameters for 3w x 2w x 2b (100 repetitions) 

steveharoz

library(tidyverse)
library(ggdist)

# make some data
expand_grid(
  condition = c("A", "B"),
  stimulus = seq(-3,3,0.3),
  repetitions = 1:20
) %>%
  # make some noisy response data

steveharoz

reference: https://dplyr.tidyverse.org/reference/storms.html

visualization: https://imgur.com/a/TMONnmS

source: https://www.nhc.noaa.gov/data/#hurdat

steveharoz

library(tidyverse)

PATH = "peerj_reviews_txt/"
ignored_words = c("the", "dear", "original")
filenames = dir(path = PATH, pattern="*.txt", recursive = TRUE)



preceeding_words = sapply(filenames, function(f) {
  words = read_file(paste0(PATH, f)) %>%

steveharoz