rexim

#!/usr/bin/env python
# -*- coding: utf-8 -*-

# Copyright (c) 2014 Alexey Kutepov a.k.a. rexim

# Permission is hereby granted, free of charge, to any person
# obtaining a copy of this software and associated documentation files
# (the "Software"), to deal in the Software without restriction,
# including without limitation the rights to use, copy, modify, merge,
# publish, distribute, sublicense, and/or sell copies of the Software,

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],

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(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

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,

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)

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))

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

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

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)