Getting started

Installing expyfun


The first step is to install a Python 3.8+ distribution. See tutorials on other sites for how to do this.


expyfun requires several libraries for full functionality:

  • Required Python libraries (can be installed via pip, or some with conda if preferred):

    • numpy

    • scipy

    • matplotlib

    • pyglet

    • pillow

  • Optional libraries:

    • rtmixer: High precision audio playback, can be installed with pip install rtmixer. On Linux you’ll also need the libportaudio2 system package.

    • pyparallel or inpout32.dll: Parallel port triggering, see Parallel port triggering.

    • TDTpy: Using the TDT (only available on Windows).

    • mne: Filtering and resampling stimuli.

    • pandas: Required for some plotting functions.

    • joblib: Parallel processing

    • h5py: HDF5-based writing and reading.

  • Optional system software:

    • git: Command-line tools needed for automated version downloading.

    • FFmpeg or AVBin: For playing compressed videos.

To get started quickly, this should suffice for conda users on most systems:

$ conda create -n expy mne "pyglet<1.6" -c conda-forge
$ conda activate expy
$ pip install pyparallel rtmixer
$ pip install git+

where expy can be replaced with whatever name you find convenient. If you cannot (or don’t want to) use conda-forge as a package source, you’ll have to do this instead:

$ conda create -n expy python=3 numpy scipy matplotlib pandas h5py joblib pillow
$ conda activate expy
$ pip install mne "pyglet<1.6" pyparallel rtmixer
$ pip install git+

If you prefer using pip for everything, here are the minimum requirements:

$ pip install mne matplotlib "pyglet<1.6" pillow
$ pip install git+

and this does a full pip install of all required and optional dependencies:

$ pip install mne matplotlib "pyglet<1.6" pillow
$ pip install rtmixer pyparallel pandas joblib h5py TDTPy
$ pip install git+

Note that the pyglet package for the recommended installs is constrained to version 1.5, as this will be the last version compatible with legacy OpenGL (see If you prefer to download pyglet via its github repository, please use the pyglet-1.5-maintenance branch.


The recommended way to install expyfun on development machines is to git clone the repository then do:

$ pip install -e .

This allows you to stay up to date with updates, changes, and bugfixes, and easily switch between versions.

Configuring expyfun

expyfun is designed to “just run” on user machines regardless of OS (Windows, macOS, or Linux) machines, and does not require additional configuration. In this state, the A/V/trigger timing is not guaranteed, but should be sufficient to work out most experiment logistics.

To configure expyfun on an experimental machine designed for precise A/V/trigger timing typically requires utilizing:

  • oscilloscope

  • photodiode

  • parallel port breakout, TDT trigger breakout, or sound card SPDIF-to-TTL converter

  • auditory connectors to go 1/4” or 1/8” output->BNC

  • Running Synchronization tests

To get this to work, you’ll need to set up the machine configuration file. This ensures that the following things (among others) work correctly:

  1. The interface for auditory stimuli.

  2. The interface for triggering.

  3. Units, e.g., 'deg' actually yields degrees.

  4. The display screen resolution in full-screen mode.

The keys that will always need to be set (using expyfun.set_config() or manual JSON editing) include, but are not limited to (all distances in cm; example values from a fairly typical desktop computer):


    Comma-separated full screen size in pixels, e.g., "1920,1200".


    Physical display distance from the subject, e.g., "83.0".


    Physical display width, e.g., "52.0".

Another settable parameter is "SCREEN_HEIGHT", but if you have square display pixels (a sane assumption for reasonable displays) then it’s inferred based on the screen size in pixels and physical screen width.

Other settings depend on whether you use TDT / sound card / parallel port for auditory stimuli and triggering. Possibilities can be seen by looking at expyfun.known_config_types. Your current system configuration can be viewed by doing:

>>> expyfun.get_config()
{'SCREEN_DISTANCE': '61.0', 'SCREEN_SIZE_PIX': '1920,1200', 'SCREEN_WIDTH': '52.0', 'SOUND_CARD_BACKEND': 'rtmixer'}


If this returns {}, you have not written any config values yet. This means that the standard expyfun.json file might not exist, and you might want to do something like:

>>> expyfun.set_config('SCREEN_SIZE_PIX', '1920,1200')

To initialize the expyfun.json file.

The fixed, hardware-dependent settings for a given system get written to an expyfun.json file. You can use expyfun.get_config_path() to get the path to your config file. Some sample configurations:

  • A TDT-based M/EEG+pupillometry machine:

    "AUDIO_CONTROLLER": "tdt",
    "RESPONSE_DEVICE": "keyboard",
    "SCREEN_DISTANCE": "100",
    "SCREEN_WIDTH": "51",
    "TDT_DELAY": "44",
    "TDT_MODEL": "RZ6",
    "TDT_TRIG_DELAY": "3",
  • A sound-card-based EEG system:

    "AUDIO_CONTROLLER": "sound_card",
    "RESPONSE_DEVICE": "keyboard",
    "SCREEN_DISTANCE": "50",
    "SCREEN_SIZE_PIX": "1920,1080",
    "SCREEN_WIDTH": "53",
    "SOUND_CARD_BACKEND": "rtmixer",
    "SOUND_CARD_FS": 48000,
    "SOUND_CARD_NAME": "ASIO Fireface USB",
    "TRIGGER_CONTROLLER": "sound_card"

Deploying experiments

The function expyfun.download_version() should be used to deploy a static version of expyfun once an experiment is in its finalized state.