matt-dray

print_perlin_dungeon <- function(
    m,  # matrix of perlin noise via ambient::noise_perlin()
    invert = FALSE  # flips tile positions (use set.seed before generating noise)
) {
  
  tile_wall = "#"
  tile_floor = "."
  
  # Standardise noise values from 0 to 1
  m_bin <- round((m - min(m)) / (max(m) - min(m)))

matt-dray

# Use R's edit() function and generate code to reproduce it
#
# This is now being developed into the tide() function of the {tide} package:
#     https://github.com/matt-dray/tide
#
# Original tweet:
#     https://twitter.com/mattdray/status/1518374831993069570?s=20&t=L-xQ74slFk0UtlZ-nIs3Fg
#
# Question from @erdistats re edit + code creation:
#    https://twitter.com/erdirstats/status/1518529179892994049

matt-dray

library(dplyr, warn.conflicts = FALSE)

x <- mtcars[1:5, 1:5]

x
#>                    mpg cyl disp  hp drat
#> Mazda RX4         21.0   6  160 110 3.90
#> Mazda RX4 Wag     21.0   6  160 110 3.90
#> Datsun 710        22.8   4  108  93 3.85
#> Hornet 4 Drive    21.4   6  258 110 3.08

matt-dray

# Web Dissemination Committee Q1
# Matt Dray, March 2022


# Packages ----------------------------------------------------------------


# Install {a11ytables} from GitHub
install.packages(remotes)  # if not yet installed
remotes::install_github("co-analysis/a11ytables")  # v0.0.0.90012 at time of demo

matt-dray

# Goal: put 1 in new col where 1 appears across other cols

library(dplyr)

df <- tibble(
  x1 = c(1, NA, NA), 
  x2 = c(NA, 1, NA), 
  x3 = c(NA, 1, NA)
)

matt-dray

link_walk_cycle <- function(cycles = 5) {
  
  link_v_top <- c(
    0,0,0,0,0,1,1,1,1,1,1,0,0,0,0,0,
    0,0,0,0,1,1,1,1,1,1,1,1,0,0,0,0,
    0,0,2,0,1,3,3,3,3,3,3,1,0,2,0,0,
    0,0,2,0,3,3,3,3,3,3,3,3,0,2,0,0,
    
    0,0,2,2,3,2,1,2,2,1,2,3,2,2,0,0,
    0,0,2,2,3,2,3,2,2,3,2,3,2,2,0,0,

matt-dray

# I tweeted about this:
#     https://twitter.com/mattdray/status/1481561924202553346
# Then I blogged about it:
#     https://www.rostrum.blog/2022/01/14/wordle/

# remotes::install_github("coolbutuseless/wordle")

eldrow <- function(guess, answer, words = wordle::wordle_dict){
  
  answer <- tolower(answer)

matt-dray

# I tweeted about this:
#     https://twitter.com/mattdray/status/1481071849891057668?s=20
# Then I blogged about it:
#     https://www.rostrum.blog/2022/01/14/wordle/

# Function to extract Wordle results from tweet data
twirdle <- function(tweets) {
  
  g   <- "\U1F7E9"
  o   <- "\U1F7E7"

matt-dray

# Create a 3D ggplot with {ggrgl} and colour the extrusion by some variable
#
# Motivation via @geoff_tewierik:
#   https://twitter.com/geoff_tewierik/status/1476662279437369346?s=20
# See blog about the {gpx3d} package:
#   https://www.rostrum.blog/2021/12/30/gpx3d/
# See {gpx3d} package source:
#   https://github.com/matt-dray/gpx3d

library(gpx3d)

matt-dray

# Blogpost:
#   https://www.rostrum.blog/2020/06/06/acnh-swipe/
#
# App:
#   https://mattdray.shinyapps.io/acnh-swipe/

x <- readr::read_csv("~/Desktop/acnh-swipe_results - Sheet1.csv")

x %>%
  filter(swipe %in% c("left", "right"), name != "TEST") %>%