hypercompetent

pearson_residuals <- function(counts, theta = 100) {
  counts_sum0 <- as(matrix(Matrix::colSums(counts),nrow=1),"dgCMatrix")
  counts_sum1 <- as(matrix(Matrix::rowSums(counts),ncol=1),"dgCMatrix")
  counts_sum <- sum(counts@x)
  
  #get residuals
  mu <- (counts_sum1 %*% counts_sum0) / counts_sum
  z <- (counts - mu) / sqrt(mu + mu^2/theta)
  
  #clip to sqrt(n)

slowkow

#!/usr/bin/env python
"""
The Needleman-Wunsch Algorithm
==============================

This is a dynamic programming algorithm for finding the optimal alignment of
two strings.

Example
-------

jimjam-slam

library(tidyverse)
library(ggrepel)      # substitude geom_text for geom_text_repel if you don't want to bother with this!

mydata =
  data_frame(
    x = 1:10,
    y = rnorm(10),
    name = c('Apple', 'Banana', 'Kiwi', 'Orange', 'Watermelon',
      'Grapes', 'Pear', 'Cantelope', 'Tomato', 'Satsauma')) %>%
  mutate(

1wheel

d3-jetpack's d3.conventions can now create canvas and html elements. Here d3.conventions({layers: 'csd'}) makes an canvas ctx, svg and div with a shared coordinate system. Yellow shapes are drawn on canvas, cyan on svg and purple on html.

Layers are position absolutely on top of each other in the order listed in the layer string. To create an svg with two canvas elements on top:

var {layers: [svg, bg_ctx, fg_ctx]} = d3.conventions({layers: 'scc'})

Hurricane How-To describes using multiple renders for something more practical than bouncing circles.

mcburton

Running Jupyter on a Supercomputer

This quick guide for getting a Jupyter Notebook up and running on Bridges, a supercomputer managed by the Pittsburgh Supercomputing Center. Bridges is a new machine designed to accommodate non-traditional uses of High Performance Computing (HPC) resources like data science and digital humanities. Bridges is available through XSEDE, which is the system that manages access to multiple supercomputing resources. Through XSEDE, Bridges is available researchers or educators at US academic or non-profit research institutions (see the XSEDE eligibility policies) Allocations are free, but there is a somewhat difficult to understand application process filled with jargon and acronyms that take time to understand. See the XSEDE getting started guide for more information about getting acc

slowkow

#!/usr/bin/env python
"""
optimize_html.py
Kamil Slowikowski
November 14, 2016

Optimize base64 encoded PNG images in an HTML file.

USAGE
    

nicksantamaria

<?php

/**
 * @file
 * Basic demonstration of how to do parallel threads in PHP.
 */

// This array of "tasks" could be anything. For demonstration purposes
// these are just strings, but they could be a callback, class or
// include file (hell, even code-as-a-string to pass to eval()).

mbq

#AUROC calculation code
auroc<-function(score,cls){
 n1<-sum(!cls); sum(cls)->n2;
 U<-sum(rank(score)[!cls])-n1*(n1+1)/2;
 return(1-U/n1/n2);
}

#... as a cryptic one-liner
auroc1l<-function(score,cls)
 mean(rank(score)[cls]-1:sum(cls))/sum(!cls)

mikelove

n <- 200
m <- 40
set.seed(1)
x <- runif(n, -1, 1)
library(rafalib)
bigpar(2,2,mar=c(3,3,3,1))
library(RColorBrewer)
cols <- brewer.pal(11, "Spectral")[as.integer(cut(x, 11))]
plot(x, rep(0,n), ylim=c(-1,1), yaxt="n", xlab="", ylab="", 
     col=cols, pch=20, main="underlying data")

adamrecsko

import {PipeTransform, Pipe} from 'angular2/core';

@Pipe({ name: 'highlight' })
export class HighLightPipe implements PipeTransform {
  transform(text: string, [search]): string {
    return search ? text.replace(new RegExp(search, 'i'), `<span class="highlight">${search}</span>`) : text;
  }
}

/** Usage: