Python package to create and run ACT-R cognitive models.
This includes the (frozen) version of pyactr for the "Computational Cognitive Modeling and Linguistic Theory" book, with all the book code included in the folder book-code.
The book is available open-access here or by clicking on the link above.
Go to the folder notebooks, then:
- click on the notebook you want to work through
- wait (or refresh) until github renders it for you; if this doesn't work (sometimes github has issues rendering notebooks), download the corresponding pdf and open it locally on your computer
- open the notebook in Google Colab by clicking on the
Open In Colabbadge at the top of the notebook (this works for both the rendered ipynb file or the pdf file opened locally on your computer) - enjoy reading and running the code interactively.
The first two notebooks provide a basic introduction to Jupyter notebooks and Python3 based on various resources; feel free to skip them if you've worked with python and notebooks before. The remainder of the notebooks cover Chapters 2 through 7 of the "Computational Cognitive Modeling and Linguistic Theory" book.
Some notebook images might not display correctly in Google Colab, and you'll have to set up access to your google drive if you want to load/save files (e.g., data, models, figures etc.), but you should be able to go through a good number of notebooks by just opening them in Google Colab and working through them interactively.
To run the code, you need to install and use pyactr.
You have several options. The safest one is to install the pyactr version that is present in this repo (called 'pyactr-frozen'). This is the frozen version that should allow you to run all the code from the book.
To install this, clone this repo (or download it and unzip it), and then go to the folder pyactr-frozen and run:
python3 setup.py install
If you want the latest release of pyactr, you can also use pip:
pip3 install pyactr
The most recent pip version should work fine for all the code in the book. However, we cannot promise that all future pyactr updates available via pip will be backward compatible with the book code. (If you do encounter an incompatibility, please let us know.)
Using pyactr is explained in the book starting with Chapter 2. Again, all the code discussed in the book can be found here in the folder book-code.
[Recommended: Google Colab]
If you have a Google account, you already have access to an excellent Python3 environment. Just google for "Getting Started With Google Colab" to find a quick tutorial out there to get you started. Here's one that's available as of May 2019:
https://towardsdatascience.com/getting-started-with-google-colab-f2fff97f594c
Once you know a little about google colab, go to your drive and upload the notebook pyactr_on_google_colab.ipynb, which you can find in the docs folder of this very repo. Run the code cells in the notebook to make sure everything works, then you're off to the races.
[Alternative] To get started, you should consider a web-based service for Python3 like PythonAnywhere. In this type of services, computation is hosted on separate servers and you don't have to install anything on your computer (of course, you'll need internet access). pyactr is a library for Python3, and you will have to install it on the web-based Python3 service. If you find that you like working with Python3 and pyactr, you can install them on your computer at a later point, together with a good text editor for coding -- Sublime, gedit, Vim, Emacs etc. (not Word) are suitable editor for programming. Alternatively, you can install an integrated desktop environment (IDE) for Python -- a common choice is anaconda, which comes with a variety of ways of working interactively with Python (IDE with Spyder as the editor, ipython notebooks, nowadays known as jupyter notebooks etc.). But none of this is required to run pyactr and the code in this book.
Using PythonAnywhere: a. Go to www.pythonanywhere.com and sign up there. b. You'll receive a confirmation e-mail. Confirm your account / e-mail address. c. Log into your account on www.pythonanywhere.com. d. Click on Bash (below ``Start a new Console''). e. In Bash, type: $ pip3 install --user pyactr
This will install pyactr in your Python account (not on your computer).
f. Go back to Consoles. Start Python by clicking on any version 3.3 or higher.
g. A console should open. Type:
import pyactr
If no errors appear, you are set. You might get a warning about the lack of tkinter support and that the simulation GUI is set to false. You can ignore this message.
Throughout the book, we will introduce and discuss various ACT-R models coded in Python. You can either type them in line by line or even better, copy-paste them into code cells in a notebook while using Google Colab, or load them as files in your session on PythonAnywhere. Scripts are uploaded in PythonAnywhere under the tab Files.
You should be aware that a free account on PythonAnywhere allows you to run only two consoles, and there is a limit on the amount of CPU you might use per day. The limit should suffice for the tutorials but if you find this is too constraining, you should consider installing Python3 and pyactr on your computer and running scripts directly there.
Using the version of pyactr that you installed on Google Colab or PythonAnywhere should work fine for all the code in the book. However, what you just installed (pyactr) is an up-to-date package and we cannot promise that all future pyactr updates will remain backward compatible with the code that appeared in this book. If you do encounter an incompatibility, please let us know.
Using pyactr is explained in the book starting with Chapter 2. Again, all the code discussed in the book can be found here in the folder book-code.
If you find you like working with pyactr, we suggest you install it on your computer. You will first have to install Python version 3 on your computer. See here:
After that, you can install pyactr. This is described in the section Installing and using pyactr on your computer, see above.
More documentation about the pyactr package can be found in the pyactr GitHub repo. Go to:
https://github.com/jakdot/pyactr
Some of the documents are also available here in the folder docs.
pyactr requires Python3 (>=3.3), numpy, simpy and pyparsing; it also requires tkinter if you want to see visual output of how ACT-R models interact with environment, but this is not necessary to run any models.