aepsych-client 0.3.0

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AEPsych Python client v0.2.0

This lets you use Python to interface with the AEPsych server to do model-based adaptive experimentation.

Installation

We recommend installing the client under a virtual environment like Anaconda. Once you've created a virtual environment for AEPsychClient and activated it, you can install through pip:

pip install aepsych_client

If you are a developer, you should also install the main AEPsych package so that you can run the tests.

Configuration

This interface uses AEPsych's ini-based config, which gets passed as a string to the server:

# Instantiate a client
client = AEPsychClient(ip="0.0.0.0", port=5555)

# Send a config message to the server, passing in a configuration filename
filename = 'configs/single_lse_2d.ini'
client.configure(config_path=filename)

Ask and tell

To get the next configuration from the server, we call ask; we report on the outcome with tell.

# Send an ask message to the server
trial_params = client.ask()

# Send a tell back
client.tell(config={"par1": [0], "par2": [1]}, outcome=1)

Resume functionality

We can run multiple interleaved experiments. When we call configure, we get back a strategy ID. The client keeps track of all these strategy IDs and we can use them to resume experiments. By doing this we can interleave different model runs.

# Configure the server using one config
client.configure(config_path=file1, config_name='config1')

# Run some stuff on this config
...

# Configure the server using another config
client.configure(config_path=file2, config_name='config2')

# Run some stuff on this other config
...

# Resume the past config
client.resume(config_name="config1)

Ending a session

When you are done with your experiment, you should call client.finalize(), which will stop the server and save your data to a database.