#low-latency #action #cognitive #experiment #interactive-applications #task #interaction

bin+lib cog-task

A general-purpose low-latency application to run cognitive tasks

21 releases (9 stable)

1.2.0 Nov 5, 2022
1.1.5 Nov 5, 2022
1.0.1 Oct 30, 2022
0.2.4 Oct 25, 2022
0.1.1 Aug 14, 2022

#125 in Video

MIT and maybe AGPL-3.0-or-later

1MB
11K SLoC

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CogTask

Crates.io Documentation License Build Status Crates.io Downloads

A general-purpose low-latency tool for designing cognitive tasks.

Description

This tool provides an easy way to write and execute different types of interactive actions that are usually useful in experiments involving cognitive sciences. E.g., display an image/video, play sounds, show text, measure reactions to events (through key presses or clicks), measure action completion times, ask questions, etc.

This application is written in Rust using the egui graphical framework. To generate a task, a description file in the rust object notation (RON; see "Tooling" section of its README for syntax highlighting) format should be created by the experiment designer. The task file consists of three main fields: name, configuration, and blocks (self-contained pieces of the experiment that should be run in one sitting). Each block in itself consists of three main fields: name, configuration (overriding the task configuration), and actions. The actions are specified in the form of a tree (graph) with nodes of type Action.

Actions are the fundamental building blocks of experiment design. There are many types of actions:

  • Some actions are containers, i.e., they contain other actions within. Container actions are how the tree is constructed. For example, the action Seq is a sequence container which stores a list of sub-actions that will be run in sequence, one after the other. Another example is the Par action which is a parallel container, storing a list of sub-actions that will start at the same time (but might end at different times).
  • Some actions are infinite which will never end on their own or through user interaction. These actions should be linked to other non-infinite actions. For example, Timeout is a container action that will run its inner sub-action for a fixed amount of time.
  • Some actions do not have any effect on the experiment, but store the results. For example, KeyLogger stores key presses by the user and their times. Another example, Logger stores any information it receives from other actions into a file.
  • ...

There are many more types of actions, which are not properly documented yet. But feel free to explore the types (each file corresponds to an action with the same name), or check out (and run) the multiple examples.

Installation

The most reliable way to install CogTask is by installing Cargo through rustup and compiling the binaries locally (check requirements section below).

Install Cargo:

curl https://sh.rustup.rs -sSf | sh

Build binaries (choose one):

  • Stable binaries from crates.io:
    cargo install cog-task [--features=...]
    
  • Nightly binaries from github (preferred):
    cargo install --git https://github.com/menoua/cog-task [--features=...]
    

To update the installation to the latest version, you can run the same commands.

Features

Some types of actions depend on optional features that can be enabled during installation. These features are not enabled by default because they rely on extra system libraries that might not be installed on the OS out-of-the-box.

Currently, there are 5 distinct features that can be enabled:

  1. rodio -- allows playing sounds via the CoreAudio sound library on macOS and ALSA on linux.
  2. gstreamer -- allows streaming audio/video files via the gstreamer backend.
  3. ffmpeg (incomplete) -- allows streaming audio/video files via the ffmpeg backend.
  4. savage -- enables using the savage interpreter for mathematical operations.
  5. python -- enables using python code snippets to perform calculations.

Examples:

  • Stable binaries with all features:
    cargo install cog-task --all-features
    
  • Nightly binaries with rodio and gstreamer support:
    cargo install --git https://github.com/menoua/cog-task --features=rodio,gstreamer
    

Requirements

macOS

Feature Requirements
(required) -
rodio -
savage -
gstreamer brew install gstreamer gst-plugins-base gst-plugins-good gst-plugins-bad gst-plugins-ugly gst-libav gst-rtsp-server
ffmpeg brew install ffmpeg
python (needs a working python installation; see below)
(--all-features) brew install gstreamer gst-plugins-base gst-plugins-good gst-plugins-bad gst-plugins-ugly gst-libav gst-rtsp-server ffmpeg

Linux

Feature Requirements
(required) sudo apt install build-essential cmake pkg-config libfontconfig1-dev
rodio sudo apt install libasound2-dev
savage -
gstreamer sudo apt install libgstreamer1.0-dev libgstreamer-plugins-base1.0-dev libgstreamer-plugins-bad1.0-dev gstreamer1.0-plugins-base gstreamer1.0-plugins-good gstreamer1.0-plugins-bad gstreamer1.0-plugins-ugly gstreamer1.0-libav gstreamer1.0-tools gstreamer1.0-alsa gstreamer1.0-pulseaudio
ffmpeg sudo apt install libavfilter-dev libavdevice-dev ffmpeg
python (needs a working python installation; see below)
(--all-features) sudo apt install build-essential cmake pkg-config libfontconfig1-dev libasound2-dev libgstreamer1.0-dev libgstreamer-plugins-base1.0-dev libgstreamer-plugins-bad1.0-dev gstreamer1.0-plugins-base gstreamer1.0-plugins-good gstreamer1.0-plugins-bad gstreamer1.0-plugins-ugly gstreamer1.0-libav gstreamer1.0-tools gstreamer1.0-alsa gstreamer1.0-pulseaudio libavfilter-dev libavdevice-dev ffmpeg

//@ python

Enabling the python feature can be tricky. You need a working installation of python3, which generally comes preinstalled with recent versions of both macOS and Linux. If you installed python using anaconda, you generally don't need to do anything else. If you installed python using a different method, you might need to set up the PYTHONHOME environment variable manually. The variable needs to be set to the location of the desired python environment:

export PYTHONHOME=path_to_python_env

This should be set before running cog-launcher or cog-server in the same shell environment. It might take some trial and error to get it going.

Usage

This crate installs two binaries: cog-launcher and cog-server.

cog-launcher is a launcher that provides a graphical interface to find and load tasks from disk.

cog-server /path/to/task is used to run a specific task by providing the path to its directory. cog-launcher runs this binary when starting a task, so make sure both binaries are in the same directory.

For example, to run the Basic task in this repo, you would do the following:

git clone https://github.com/menoua/cog-task
cog-server cog-task/example/basic

Alternatively, you can run:

cog-launcher

Then use the leftmost control icon to load the example/basic/ directory. Or, you can use the second button to open the parent example/ directory which contains all the example tasks within. The former, directly runs cog-server on the chosen task. The latter, displays a list of all tasks located in the chosen directory, which can be started by clicking the corresponding button.

Changelog

The SemVer version will follow these guidelines: If the new version is backwards compatible (task written for last version will behave the same on the new version), even if there are (1) new action types, or (2) new attributes for an existing action type introduced, the third number will increase. If an existing action type is removed entirely or an existing action's attributes (or their default values) have changed such that it is no longer backwards compatible, the second number will increase. If there is a fundamental change to the structure of the program (how tasks/actions are defined or executed), the first number will increase. Bug fixes will generally increase the third number, unless they are big, in which case they will increase the second number.

v1.2.0:

  • New action Until which wraps another (usually infinite) action and ends it when a signal arrives or condition is met.
  • New action Repeat which wraps another finite action and restarts it as soon as it ends.
  • KeyLogger now has a out_key attribute which emits the name of the pressed key as a string.
  • KeyLogger is now in map form instead of tuple form, so group should be provided as a key-value pair.

v1.1.5:

  • Fixed a bug recently introduced in v1.1.4 where block would crash if Process ended before the action started,

v1.1.4:

  • Process now has a drop_early attribute which if set will drop/ignore all incoming responses before the corresponding action starts. This is incompatible with response_type of raw_all.
  • Fixed a bug in Porcess which if multiple responses were received before action started, only one was consumed, keeping a list of unconsumed responses forever.

v1.1.3:

  • Using a python function no longer requires manually setting the PYTHONHOME environment variable IF python has been set up using anaconda.

v1.1.2:

  • New action Stack runs actions in parallel and displays them either in a horizontal or vertical stack.
  • New action Horizontal is a shorthand for a horizontal Stack.
  • New action Vertical is a shorthand for a vertical Stack.

v1.1.1:

  • Process now has a passive attribute which if set does not send anything to child process.
  • Process now has a response_type attribute which determines whether response content should be read: (a) value = read a line and convert it to claimed type, (b) raw = read a line and treat it as string, (c) raw_all = read full output and treat it as a single string.

v1.1.0:

  • New action Process that can run an externally compiled binary in blocking or non-blocking mode.
  • Function now has a lo_response attribute which if set, will run in non-blocking mode.
  • Function attribute persistent is replaced by the opposite attribute once, which if true will only run the function once (be it at start or update).
  • Fixed a bug in Delayed.

v1.0.1:

  • Clock now sends incrementing tic number instead of a null in its output signal.
  • Clock has on_start attribute that determines whether a "zero" signal will be emitted at start of action.

Dependencies

~25–62MB
~1M SLoC