Skip to main content

Adaptive experimetation for psychophysics

Project description

AEPsych

AEPsych is a framework and library for adaptive experimetation in psychophysics and related domains.

Installation

AEPsych only supports python 3.8+. We recommend installing AEPsych under a virtual environment like Anaconda. Once you've created a virtual environment for AEPsych and activated it, you can install AEPsych using pip:

pip install aepsych

If you're a developer or want to use the latest features, you can install from GitHub using:

git clone https://github.com/facebookresearch/aepsych.git
cd aepsych
pip install -r requirements.txt
pip install -e .

Usage

See the code examples here.

The canonical way of using AEPsych is to launch it in server mode (you can run aepsych_server --help to see additional arguments):

aepsych_server --port 5555 --ip 0.0.0.0 database --db mydatabase.db

The server accepts messages over either a unix socket or ZMQ, and all messages are formatted using JSON. All messages have the following format:

{
     "type":<TYPE>,
     "version":<VERSION>,
     "message":<MESSAGE>,
}

Version can be omitted, in which case we default to the oldest / unversioned handler for this message type. There are five message types: setup, resume, ask, tell and exit.

Setup

The setup message prepares the server for making suggestions and accepting data. The setup message can be formatted as either INI or a python dict (similar to JSON) format, and an example for psychometric threshold estimation is given in configs/single_lse_example.ini. It looks like this:

{
    "type":"setup",
    "version":"0.01",
    "message":{"config_str":<PASTED CONFIG STRING>}
}

After receiving a setup message, the server responds with a strategy index that can be used to resume this setup (for example, for interleaving multiple experiments).

Resume

The resume message tells the server to resume a strategy from earlier in the same run. It looks like this:

{
    "type":"resume",
    "version":"0.01",
    "message":{"strat_id":"0"}
}

After receiving a resume message, the server responds with the strategy index resumed.

Ask

The ask message queries the server for the next trial configuration. It looks like this:

{
    "type":"ask",
    "version":"0.01",
    "message":""
}

After receiving an ask message, the server responds with a configuration in JSON format, for example {"frequency":100, "intensity":0.8}

Tell

The tell message updates the server with the outcome for a trial configuration. Note that the tell does not need to match with a previously ask'd trial. For example, if you are interleaving AEPsych runs with a classical staircase, you can still feed AEPsych with the staircase data. A message looks like this:

{
    "type":"tell",
    "version":"0.01",
    "message":{
        "config":{
                "frequency":100,
                "intensity":0.8
            },
        "outcome":"1",
    }
}

Exit

The exit message tells the server to close the socket connection, write strats into the database and terminate current session. The message is:

{
    "type":"exit",
}

The server closes the connection.

Data export and visualization

The data is logged to a SQLite database on disk (by default, databases/default.db). The database has one table containing all experiment sessions that were run. Then, for each experiment there is a table containing all messages sent and received by the server, capable of supporting a full replay of the experiment from the server's perspective. This table can be summarized into a data frame output (docs forthcoming) and used to visualize data (docs forthcoming).

Contributing

See the CONTRIBUTING file for how to help out.

License

AEPsych licensed CC-BY-NC 4.0, as found in the LICENSE file.

Citing

The AEPsych paper is currently under review. In the meanwhile, you can cite our preprint:

Owen, L., Browder, J., Letham, B., Stocek, G., Tymms, C., & Shvartsman, M. (2021). Adaptive Nonparametric Psychophysics. http://arxiv.org/abs/2104.09549

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

aepsych-0.2.0.tar.gz (114.4 kB view details)

Uploaded Source

Built Distribution

aepsych-0.2.0-py3-none-any.whl (160.5 kB view details)

Uploaded Python 3

File details

Details for the file aepsych-0.2.0.tar.gz.

File metadata

  • Download URL: aepsych-0.2.0.tar.gz
  • Upload date:
  • Size: 114.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.7

File hashes

Hashes for aepsych-0.2.0.tar.gz
Algorithm Hash digest
SHA256 7c2644dc4404a0cbf2743b72e9e654edc2d8f54baeb16cf02b56e8dd39b21752
MD5 1a58750126fa41a41f63f02a3ed3014c
BLAKE2b-256 edca889f5bce2c873789774750014108041baab251e346e187c1ee0ebf095f3e

See more details on using hashes here.

Provenance

File details

Details for the file aepsych-0.2.0-py3-none-any.whl.

File metadata

  • Download URL: aepsych-0.2.0-py3-none-any.whl
  • Upload date:
  • Size: 160.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.7

File hashes

Hashes for aepsych-0.2.0-py3-none-any.whl
Algorithm Hash digest
SHA256 bb9a7d31eff7a08f7abd1454d83588f59017e8353d143eb2ee6e7f72e7b88699
MD5 b5b47a087bc268e56cc6b132e76a705b
BLAKE2b-256 53321b050425dff0ca563eaa955d15143e5945549ffd6346afc39a1c85d3733c

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page