garyfeng

# 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")
    }

garyfeng

// 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();

garyfeng

# 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 

garyfeng

# 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

garyfeng

# 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

garyfeng

# 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

garyfeng

# 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)

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.

A Pen by Gary Feng on CodePen.

License.

garyfeng

<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; }

garyfeng