• How are things going?

• Data science community meeting, Monday, March 30, 2020, 10:00a, https://psu.zoom.us/j/677349894

• Tools for reproducible data-gathering
• Deeper dive into PsychoPy
• In-class jsPsych quests

• E-Prime
• Matlab-based (Psychophysics Toolbox)
• PsychoPy

• jsPsych
• jaysire
• psychTestR

• MTurk
  • psiTurk

• Windows only, commercial
• System for Teaching Experimental Psychology (STEP)
  • (MacWhinney, St James, Schunn, Li, & Schneider, 2001)
  • STEP script libraries: https://step.talkbank.org/scripts-plus/ and https://step.talkbank.org/scripts-student/
• Journal of Neurobehavioral Experiments and Stimuli (JONES)

• Matlab-based, but also runs Octave (open source port of Matlab)
• Runs on Linux, Windows, Mac OS X
  • Linux (Ubuntu) now recommended

• Script libraries:
  • http://www.kehinger.com/PTBexamples.html
  • Introduction to Psychtoolbox on Matlab, http://www.jonaskaplan.com/psych599.php
• YouTube tutorial channel: https://www.youtube.com/watch?v=5Sskr9m-UtQ
• Brad Wyble’s Stream environment for “rapid, precise experimental development”

• Python-based
• Runs on Linux, Windows, Mac OS X
• Script libraries:
  • PyHab for habituation/looking time studies. (Kominsky, 2019)
  • Pavlovia.org for online studies.
• Timing evaluation study. (Bridges, Pitiot, MacAskill, & Peirce, 2020)

• JavaScript (js)-based
• Runs in browser, locally or via the web

https://github.com/topics/psychology-experiments?l=javascript

• Amazon’s system for matching workers “turkers” with tasks
• Demographics of user base
  • http://demographics.mturk-tracker.com/#/gender/all
• LookIt, looking time studies using web cameras
  • See also (Tran, Cabral, Patel, & Cusack, 2017)

• psiTurk
  • Experiment exchange

• Prolific
• Centiment
• Qualtrics
• Medallia

• Commercial vs. non-commercial tools
• Computers vary, OS’s vary, versions change
• Hard to ensure scripts run on different hardware, software
• Desktop-based (better timing) vs. web-based (less hardware/software dependent)
• Programming practices vary

• Citing resources is inconsistent
  • Resource Identification Initiative’s Research Resource Identifiers (RRIDs)
  • https://www.force11.org/group/resource-identification-initiative
  • (Vasilevsky et al., 2013)
• Terminology for tasks is inconsistent
  • Poldrack’s Cognitive Atlas

• Open code sharing
  • https://github.com/gilmore-lab/peep-II
  • https://github.com/gilmore-lab/planforms
  • https://github.com/gilmore-lab/sex-differences-in-motion-perception
• Psychology Department script library

• Share videos, stills of displays
  • (Gilmore & Adolph, 2017)
  • e.g., https://doi.org/10.17910/B7.272
  • Journal of Visualized Experiments (JOVE)
• PLAY Project

• Use Open Science Framework (OSF) or Databrary as a project “hub”
• Future: “containerize” experiment apps
  • Docker.com

• What tool(s) are you using now?
• Do you use shared code? What was the source?
• Do you alter shared display code? How do you document the changes?
• Do you share display code? How?
• Barriers to greater sharing?

• Use standalone version 3 (“batteries included”)
• Visit https://github.com/psychopy/psychopy/releases/
• Download version for your OS
• Open app

"""
Demo: show a very basic program: hello world
"""

from __future__ import absolute_import, division, print_function

# Import key parts of the PsychoPy library:
from psychopy import visual, core

# Create a visual window:
win = visual.Window()

# Create (but not yet display) some text:
msg1 = visual.TextStim(win, text=u"Hello world!")  # default position = centered
msg2 = visual.TextStim(win, text=u"\u00A1Hola mundo!", pos=(0, -0.3))

# Draw the text to the hidden visual buffer:
msg1.draw()
msg2.draw()

# Show the hidden buffer--everything that has been drawn since the last win.flip():
win.flip()

# Wait 3 seconds so people can see the message, then exit gracefully:
core.wait(3)

win.close()
core.quit()

# The contents of this file are in the public domain.

#!/usr/bin/env python
# -*- coding: utf-8 -*-

"""
This demo shows you different image presentation using visual.ImageStim and
visual.GratinGstim. It introduces some of the many attributes of these stimulus
types.
"""

from __future__ import division

# Import the modules that we need in this script
from psychopy import core, visual, event

# Create a window to draw in
win = visual.Window(size=(600, 600), color='black')

# An image using ImageStim.
image = visual.ImageStim(win, image='face.jpg')

# We can also use the image as a mask (mask="face.jpg") for other stimuli!
grating = visual.GratingStim(win,
    pos=(-0.5, 0),
    tex='sin',
    mask='face.jpg',
    color='green')
grating.size = (0.5, 0.5)  # attributes can be changed after initialization
grating.sf = 1.0

# Initiate clock to keep track of time
clock = core.Clock()
while clock.getTime() < 12 and not event.getKeys():
    # Set dynamic attributes. There's a lot of different possibilities.
    # so look at the documentation and try playing around here.
    grating.phase += 0.01  # Advance phase by 1/100th of a cycle
    grating.pos += (0.001, 0)  # Advance on x but not y
    image.ori *=  1.01  # Accelerating orientation (1% on every frame)
    image.size -= 0.001  # Decrease size uniformly on x and y
    if image.opacity >=  0:  # attributes can be referenced
        image.opacity -= 0.001  # Decrease opacity

    # Show the result of all the above
    image.draw()
    grating.draw()
    win.flip()

win.close()
core.quit()

# The contents of this file are in the public domain.

• Study the demos; tweak them.
• Choose top down (builder) or bottom-up (script-first) approach at the outset.
• Make experimental parameters explicit.

• Choose GUI or script-based approach
• Design your data outputs for reproducible post-processing.
  • Think: ‘What data frame am I going to want to have?’
• Write and test import & cleaning code as you finalize your study.

• Go a bit deeper into jsPsych
  • jsPsych documentation.
• “Hello, World” demo.
• Why jsPsych?
  • No platform dependencies!
  • Can run/test from within RStudio!

• Make a local copy/clone of https://github.com/psu-psychology/jsPsych-resources

<!doctype html>
<html>
    <head>
        <title>My page</title>
    </head>
    <body>
    <h1>This is a top-level header.</h1>
    <h2>This is a second level header.</h2>
    <p>This is a paragraph.</p>
    </body>
</html>

• Nested tags: <html></html>, <head></head>, <body></body>
• Resources: links (<a></a>), imgs (<img></img>), video (<video></video>), etc.
• Tag + src + parameter syntax: <img src="https://upload.wikimedia.org/wikipedia/commons/thumb/6/61/HTML5_logo_and_wordmark.svg/200px-HTML5_logo_and_wordmark.svg.png" width = 200px></img>

• Hypertext Markup Language (HTML)
  • Structure of web pages
• Cascading Style Sheets (CSS)
  • Style of web page elements

• JavaScript
  • Programming language for web pages
  • Frameworks/libraries are collections of useful commands
• Web application framework
  • Integration with other resources and services (e.g., databases)

<!DOCTYPE html>
<html>
    <head>
        <title>My experiment</title>
        <script src="jspsych-6.1.0/jspsych.js"></script>
        <script src="jspsych-6.1.0/plugins/jspsych-html-keyboard-response.js"></script>
        <link href="jspsych-6.1.0/css/jspsych.css" rel="stylesheet" type="text/css"></link>
    </head>
    <body></body>
    
    <script>
    var hello_trial = {
        type: 'html-keyboard-response',
        stimulus: 'Hello world!'
    }

    jsPsych.init({
        timeline: [hello_trial]
    })
    </script>
</html>

<!--- From local directories --->
<script src="jspsych-6.1.0/jspsych.js"></script>

<link href="jspsych-6.1.0/css/jspsych.css" rel="stylesheet" type="text/css"></link>

<script>
  var hello_trial = {
    type: 'html-keyboard-response',
    stimulus: 'Hello world!'
  }

  jsPsych.init({
    timeline: [hello_trial]
  })
</script>

Here’s what the data look like in JavaScript Object Notation (JSON)

 {
  "rt": 1219,
  "stimulus": "img/orange.png",
  "key_press": 70,
  "response": "no-go",
  "trial_type": "single-stim",
  "trial_index": 2,
  "time_elapsed": 13924,
  "internal_node_id": "0.0-2.0-0.0",
  "correct": false
 },
 {
  "rt": -1,
  "stimulus": "img/orange.png",
  "key_press": -1,
  "response": "no-go",
  "trial_type": "single-stim",
  "trial_index": 3,
  "time_elapsed": 16305,
  "internal_node_id": "0.0-2.0-1.0",
  "correct": true
 },

• Copy data file manually (if running locally)
• Save to web server (if running on server)

• Importing and visualizing data from jsPsych

• Work through jsPsych Hello, World! demo.
• Work through jsPsych simple RT demo.

• Gathering info from afar: Using APIs

This talk was produced on 2020-03-24 in RStudio using R Markdown. The code and materials used to generate the slides may be found at https://github.com/psu-psychology/psy-525-reproducible-research-2020. Information about the R Session that produced the code is as follows:

## R version 3.6.2 (2019-12-12)
## Platform: x86_64-apple-darwin15.6.0 (64-bit)
## Running under: macOS Mojave 10.14.6
## 
## Matrix products: default
## BLAS:   /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib
## 
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## loaded via a namespace (and not attached):
##  [1] compiler_3.6.2  magrittr_1.5    tools_3.6.2     htmltools_0.4.0
##  [5] yaml_2.2.1      Rcpp_1.0.3      stringi_1.4.6   rmarkdown_2.1  
##  [9] knitr_1.28      stringr_1.4.0   xfun_0.12       digest_0.6.25  
## [13] rlang_0.4.5     evaluate_0.14