kleinschmidt

/* collect a one-off keyboard response, using JQuery namespaces to allow multiple, overlapping responses
 *   fcn(e): function to be called with event on key press
 *   keys:   vector of allowed keys (as characters, uppercase for alphanumeric) (optional)
 *   to:     timeout for response, in ms (optinal)
 *   tofcn:  function to be called on timeout (optional)
 */

function collect_keyboard_resp(fcn, keys, to, tofcn) {
    // create unique namespace for this response
    var namespace = '._resp' + (new Date()).getTime();

kleinschmidt

require(plyr)
require(ggplot2)

# say dat is a data.frame with the predictor x, grouping variables z1, z2, and z3 (factors or discrete numeric values)
# and the observed values are in the variable y.  then I would do:

dat.summ <- ddply(dat, .(x, z1, z2, z3), summarise,
                  y.mean=mean(y), y.se=sd(y)/sqrt(length(y)))

# this is equivalent to

kleinschmidt

#!/bin/bash
# knit.sh -- Dave Kleinschmidt, April 2013
# streamline knitting of Rnw files from the command line.

usage="Usage: $0 input-filename.Rnw [-nolatex] [-notangle]"

if [ $# -lt 1 ]; then
    echo $usage
    exit 1
fi 

kleinschmidt

mod.to.table <- function(mod.all=NA, prednames=NA, pred_name_subs=NA, file="",
                         coefs=as.data.frame(summary(mod.all)@coefs),
                         ...) {
  if (is.na(prednames)) {
    if (is.na(pred_name_subs)) {
      prednames <- row.names(coefs)
    } else {
      prednames <- str_replace_multi(row.names(coefs), pred_name_subs, replace.all=T)
    }
  }

kleinschmidt

#!/bin/bash

# Author: Dave Kleinschmidt
#
#!/bin/bash

# Author: Dave Kleinschmidt
#
# concatenate all *.results files in the directory, printing one line
# per unique assignment id (first encountered). NOTE: the header isn't

kleinschmidt

<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE plist PUBLIC "-//Apple Computer//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
<plist version="1.0">
<dict>
    <key>Label</key>
    <string>auto-clean-mendeley-library</string>
    <key>ProgramArguments</key>
    <array>
        <string>/Users/dkleinschmidt/Documents/papers/clean-library-auto.sh</string>
    </array>

kleinschmidt

kleinschmidt

using Stats, Distributions, Gadfly

import Gadfly.ElementOrFunction

# First add a method to the basic Gadfly.plot function for QQPair types (generated by Distributions.qqbuild())
Gadfly.plot(qq::QQPair, elements::ElementOrFunction...) = Gadfly.plot(x=qq.qx, y=qq.qy, Geom.point, Theme(highlight_width=0px), elements...)

# Now some shorthand functions
qqplot(x, y, elements::ElementOrFunction...) = Gadfly.plot(qqbuild(x, y), elements...)
qqnorm(x, elements::ElementOrFunction...) = qqplot(Normal(), x, Guide.xlabel("Theoretical Normal quantiles"), Guide.ylabel("Observed quantiles"), elements...)

kleinschmidt

{
  "accessKey": "your access key",
  "secretKey": "your secret key"
}

kleinschmidt

library(dplyr)
data.frame(a=factor(c('10', '20', '30', '40'))) %>% 
  mutate(b=as.character(a)) %>% 
  rowwise() %>% 
  mutate(c=as.character(a)) %>% 
  str