idot

#!/usr/bin/env python
#
# Copyright (c) 2007, Hans Meine <[email protected]>
#  All rights reserved.
#
# This is licensed according to the new BSD license.
# Please send patches / comments, I would be happy about any feedback.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions

even4void

tufte.boxplot <- function(x, g) {
  k <- nlevels(g)
  crit.val <- tapply(x, g, median)
  plot(1:k, crit.val, ylim=c(min(x)*1.1, max(x)*1.1), pch=19,
       xlab=deparse(substitute(g)), ylab=deparse(substitute(x)))
  for (i in 1:k) {
    tmp <- boxplot.stats(x[as.numeric(g)==i])
    segments(i, tmp$stats[1], i, tmp$stats[2])
    segments(i, tmp$stats[4], i, tmp$stats[5])
    points(rep(i, length(tmp$out)), tmp$out, cex=.8)

stephenturner

# Note: using the devel versions of both packages!
library(DESeq) # version 1.9.11
library(edgeR) # version 2.99.8
library(VennDiagram)

# Read in data ------------------------------------------------------------

## Use pasilla data
datafile = system.file( "extdata/pasilla_gene_counts.tsv", package="pasilla" )
datafile

malcook

pvec2<-function(v, FUN, ..., mc.set.seed = TRUE, mc.silent = FALSE, 
                mc.cores = getOption("mc.cores", 2L), mc.cleanup = TRUE
                ,combineFUN = `c`
                ) {
### AUTHOR: [email protected]
### PURPOSE: an improvement(?) on parallel:pvec which
###  (1) does not require v to be a vector, rather, v must
###      implement `[`, `length`.  Thus, i.e. BioConductor List (including
###      GRangesList) is supported.
###  (2) uses `parallel:splitIndices` to compute indices into v

dsparks

doInstall <- TRUE  # Change to FALSE if you don't want packages installed.
toInstall <- c("ggplot2", "proxy")
if(doInstall){install.packages(toInstall, repos = "http://cran.r-project.org")}
lapply(toInstall, library, character.only = TRUE)

nIncrements <- 36
eachIncrement <- seq(0, 1, len = nIncrements)
colorSweep <- expand.grid(eachIncrement, eachIncrement, eachIncrement)
moduloRemainder <- with(colorSweep, Var1*(nIncrements-1)) %%
  floor(sqrt(nIncrements))

dsparks

doInstall <- TRUE  # Change to FALSE if you don't want packages installed.
toInstall <- c("ggplot2")
if(doInstall){install.packages(toInstall, repos = "http://cran.r-project.org")}
lapply(toInstall, library, character.only = TRUE)

# Generate some randomly-distributed data
nObs <- 5000
myData <- data.frame(X = rnorm(nObs), Y = rnorm(nObs))
nClusters <- 7  # Cluster it
kMeans <- kmeans(myData, centers = nClusters)

hadley

library(httr)
library(digest)
library(XML)

s3_request <- function(verb, bucket, path = "/", query = NULL,
                       content = NULL, date = NULL) {
  list(
    verb = verb,
    bucket = bucket,
    path = path,

hadley

library(base64enc)
library(RJSONIO)
library(httr)

default_key <- function () {
  key <- Sys.getenv("POSTMARKAPP_API_KEY")
  if (key == "") {
    stop("Either provide key or set envvar POSTMARKAPP_API_KEY", call. = FALSE)
  }
  key

hadley

• UseMethod() has a special way of calling methods which has some weird consequences. Predict what the following code will return, then run it and read the help for UseMethod() to figure out what's going on. Write down the rules in the simplest form possible.

  y <- 1
  g <- function(x) { 
    y <- 2
    UseMethod("g")
  }
  g.numeric <- function(x) y

g(10)

hadley

library(microbenchmark)

microbenchmark(
  mtcars["Volvo 142E", "carb"],
  mtcars[32, 11],
  mtcars[[c(11, 32)]],
  mtcars[["carb"]][32],
  mtcars[[11]][32],
  mtcars$carb[32],
  .subset2(mtcars, "carb")[32],