jlehtoma

# Author: Joona Lehtomäki <joona.lehtomaki@gmail.com>
# Updated: 13.11.2011
# Version: 0.0.1

if (!require("rgdal")) {
	install.packages("rgdal")
}

if (!require("raster")) {
	install.packages("raster")

ziadoz

Awesome PHP

Awesome PHP has been relocated permanently to its own Github repository. No further updates will made to this gist.

Please open an issue for any new suggestions.

Robsteranium

/*
 * NAME
 * 
 * statistics-distributions.js - JavaScript library for calculating
 *   critical values and upper probabilities of common statistical
 *   distributions
 * 
 * SYNOPSIS
 * 
 * 

MohamedAlaa

tmux shortcuts & cheatsheet

start new:

tmux

start new with session name:

tmux new -s myname

fabianp

import numpy as np

# Author : Alexandre Gramfort
# license : BSD


def pav(y):
    """
    PAV uses the pair adjacent violators method to produce a monotonic
    smoothing of y

dsparks

doInstall <- TRUE
toInstall <- c("sna", "igraph")
if(doInstall){install.packages(toInstall, repos = "http://cran.us.r-project.org")}
lapply(toInstall, library, character.only = TRUE)

adjacencyList <- read.csv("https://dl.dropbox.com/s/8wabcrtqxysp03u/Twitter_network.R.csv?dl=1")
head(adjacencyList)

adjacencyMatrix <- table(adjacencyList)
as.matrix(sort(rowSums(adjacencyMatrix)))  # Out-degree

fawda123

plot.nnet<-function(mod.in,nid=T,all.out=T,all.in=T,wts.only=F,rel.rsc=5,circle.cex=5,node.labs=T,
  line.stag=NULL,cex.val=1,alpha.val=1,circle.col='lightgrey',pos.col='black',neg.col='grey',...){

  require(scales)
	
  #gets weights for neural network, output is list
  #if rescaled argument is true, weights are returned but rescaled based on abs value
  nnet.vals<-function(mod.in,nid,rel.rsc){

    library(scales)

mages

## Add an alpha value to a colour
add.alpha <- function(col, alpha=1){
  if(missing(col))
    stop("Please provide a vector of colours.")
  apply(sapply(col, col2rgb)/255, 2, 
                     function(x) 
                       rgb(x[1], x[2], x[3], alpha=alpha))  
}

mathematicalcoffee

# Include the following in a chunk up the top of your document
# Then in your plot chunk, use 'fig.cap=cap()'.
# Set the title of your ggplot via `labs(title="mytitle")`, and
#  it will automatically be substituted into the chunk options
#  as 'fig.cap'
library(knitr)
opts_knit$set(eval.after='fig.cap')
cap <- function () {
    p <- last_plot()
    if (!is.null(p) && !is.null(p$labels$title)) {

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,