Gary Feng garyfeng

Keystroke logging implementation

A sample of a simple implementation of keystroke logging required for plain text entry fields in SBTs

Forked from Lonnie Smith's Pen Keystroke logging implementation. Reimplemented using JsDiff.

	# r code to test and install libraries if not already installed.
	# code taking from stackoverflow

	pkgInstall <- function(x)
	{
	if (!require(x,character.only = TRUE))
	{
	install.packages(x,dep=TRUE)
	if(!require(x,character.only = TRUE)) stop("Package not found")
	}

	// see range.js and selection.js for the source
	// so we have 3 things to work with:
	// CKEditor.dom selections, ranges, and bookmarks

	// first, to get the CKeditor instance, use
	var editor = CKEDITOR.instances.editor1;

	// selection something in the editor, and get the selection:
	var sel = editor.getSelection();

	# A function that takes a vector or a list of strings and a regex pattern,
	# and returns a vector of strings that matches the regex patterns. Don't
	# have parameter checking, error handling, etc.

	# The key lesson learned is that regmatches() is badly designed
	# as it silently drops any non-matched elements. As a result, the length
	# of the returned vector may nor may not be the same as the input.
	# had to use the good-o substring() trick.

	# The second lesson is that when the regex pattern contains several (), such

	# I am mystified by how Traminer handles the data format.
	# Here's the data from the 2015 NAEP Reading tryout study, SC block
	# where I transformed the data to simplify the structure.
	# Then I try to use seqformat() or seqdef() to turn the existing data frame
	# in to a TraMineR object.

	sc %>% filter(readingTime>0) %>% group_by(student) %>% arrange(readingTime) %>%
	mutate(c1=1:n(), c2=2:(n()+1), t0=c(1, readingTime[1:n()-1])) %>%
	select(student, c1, c2, state2, t0, readingTime, event2) %>% na.omit() ->scSPELL

	# A function to back fill NAs in a vector with the last non-NA value
	# https://gist.github.com/garyfeng/27e7f8e406192a8cb33a

	backFillNA<- function (x) {
	nas<- which(is.na(x))
	# trick from http://stackoverflow.com/questions/24837401/find-consecutive-values-in-vector-in-r
	naList<-split(nas, cumsum(c(1, diff(nas) != 1)))
	# get the backfill values
	valueList<-lapply(naList, function(nalist) {
	prev<- nalist[1]-1

	# taken from
	# http://cran.rstudio.com/web/packages/dplyr/vignettes/nse.html
	# What if you need to mingle constants and variables? Use the handy lazyeval::interp():

	library(lazyeval)
	# Interp works with formulas, quoted calls and strings (but formulas are best)
	interp(~ x + y, x = 10)
	#> ~10 + y
	interp(quote(x + y), x = 10)
	#> 10 + y

	# To create an operator to extract a named member of a list that is in a list.
	# This may sound confusing, but imagine you have a data.frame where a variable/column is a list of lists,
	# and the lists have named members, e.g.,
	# df$itinary <- list(list(from="NYC", to="LA", via="train"), list(from="LA", to="SF"), ...)
	# You want to get the "from" value of itinary as a vector. You can do
	# df$itinary@"from" or `@`(df$itinary, "via")
	# Typically you'd use ```sapply(x, function(m) {m[["from"]]})```. The following is an extention to the idea in 2 ways:
	# 1). We define a in-fix operator `@` that does so in a way that is syntactically more natural
	# 2). We added error handling, in the case of bad indecies, etc.
	require(testthat)

	<style>
	/*
	Taken from http://moderndata.plot.ly/custom-styling-for-ipython-notebooks-with-3-lines-of-code/
	Modified for Gary Feng's Jupyter notebooks
	*/


	/*
	html {
	font-size: 62.5% !important; }