JEFworks

# playing stairway to heaven using R

# hand transcribed notes
notes <- list(
  'A3', 'C4', 'E4', 'A4', 
  c('B4', 'G#3'), 'E4', 'C4', 'B4', 
  c('C4', 'G3'), 'E4', 'C4', 'C5', 
  c('F#4', 'F#3'), 'D4', 'A3', 'F#4', 
  c('E4', 'F3'), 'C4', 'A3', 'C4', 
  NA, 'E4', 'C4', 'A3', 

JEFworks

## following https://alistaire.rbind.io/blog/fireworks/
## but manually convert to polar coordinates to be able to add
## background image, which cannot be used with coord_polar()

library(ggplot2)
library(gganimate)
theme_set(theme_void())

## create set of points in polar coordinates
set.seed(0)

JEFworks

##################### Visualizing parameters for clustering PBMCs using gganimate
library(ggplot2)
library(gganimate)

## PBMC dataset
library(MUDAN)
data("pbmcA")

## Downsample to run faster
cd <- MUDAN::cleanCounts(pbmcA)[, 1:2000]

JEFworks

#' Hatching photo filter
#'
#' @param img matrix representation of black and white image
#' @param N number of points to be used for hatching
#' @param size average size of points
#' @param var variability in size of points
#' @param step step size between shades of grey
#' @param pch point shape (note pch=4 is a hatch but other shapes can be used as well)
#'
#' @examples

JEFworks

## Use flickr API to get 20 public images for flowers
data1 = paste0(readLines('https://api.flickr.com/services/feeds/photos_public.gne?tags=lilacs'), collapse="")
data2 = paste0(readLines('https://api.flickr.com/services/feeds/photos_public.gne?tags=cherryblossoms'), collapse="")
data3 = paste0(readLines('https://api.flickr.com/services/feeds/photos_public.gne?tags=marigolds'), collapse="")
data4 = paste0(readLines('https://api.flickr.com/services/feeds/photos_public.gne?tags=daffodils'), collapse="")
dataLines = c(
  strsplit(data1, "<entry>")[[1]][-1],
  strsplit(data2, "<entry>")[[1]][-1],
  strsplit(data3, "<entry>")[[1]][-1],
  strsplit(data4, "<entry>")[[1]][-1]

JEFworks

library(jpeg)
library(rvest)

## Image urls
urls <- c(
  "http://www.instagram.com/p/BWIKgiuADnP/media/?size=m",
  "http://www.instagram.com/p/BXY2LnqgB-g/media/?size=m", 
  "http://www.instagram.com/p/BZhL7zlg0cE/media/?size=m", 
  "http://www.instagram.com/p/BaHDmk5AOYe/media/?size=m", 
  "http://www.instagram.com/p/BcDKJywAMh4/media/?size=m", 

JEFworks

library(Rcpp)

#' Floyd-Steinberg dithering
#' 
#' @description Rcpp C++ function for Floyd-Steinberg dithering 
#'     More info: https://en.wikipedia.org/wiki/Floyd%E2%80%93Steinberg_dithering
#'     Note, this is a C++ translation of the FloydConvolution function by Todos Logos
#'     from https://www.r-bloggers.com/r-is-a-cool-image-editor-2-dithering-algorithms/
#' 
#' @param x Greyscaled 2D image matrix

JEFworks

#' Pointillism filter
#'
#' @description Convert an image (RGB array) into array of points in a style reminiscent of pointillism
#' 
#' @param img Image array. 
#' @param k Point size. Bigger k means bigger point / less detail. 
#' @param seed Random seed for voxel color sampling.
#' 
#' @examples {
#' ## Read image

JEFworks

#' Plots a series of barplots and connects them 
#' Modified from https://stackoverflow.com/questions/22560850/barplot-with-connected-series
#' 
#' @param dat NxM matrix with N rows as features and M columns as samples
#' @param color Vector of N colors
#' @param space Space between barplots
#' @param alpha Alpha for area connecting barplots
#' 
#' @examples
#' dat <- matrix(rnorm(100),10,10)