cpm.datasets
cpm.datasets.load_bandit_data()
Load the 2-arm bandit dataset from a CSV file.
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Examples:
>>> data = load_bandit_data()
>>> print(data.head())
Notes
The dataset will include the following columns:
- `index`: variable to identify each row - this variable is clutter.
- `left`: the stimulus presented on the left side.
- `right`: the stimulus presented on the right side.
- `reward_left`: the reward received when the left stimulus is selected.
- `reward_right`: the reward received when the right stimulus is selected.
- `ppt`: the participant number.
- `responses`: the response of the participant (1 for right, 0 for left).
cpm.datasets.load_risky_choices()
Load the risky choices dataset from a CSV file.
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Examples:
>>> data = load_risky_choices()
>>> print(data.head())
Notes
The dataset will include the following columns:
- `ppt`: the participant number.
- `safe_magnitudes`: the magnitudes of the safe option.
- `risky_magnitudes`: the magnitudes of the risky options.
- `risky_probability`: the probabilities of the risky options.
- `choice`: the choice of the participant (1 for risky, 0 for safe).
- `optimal`: the optimal choice based on expected value (1 for risky, 0 for safe).
- `feedback`: the feedback (reward) given to the participant.
- `ambiguity`: whether the choice was ambiguous (1 for yes, 0 for no).
- `attempt`: the number of the experimental session for a given participant (e.g. 2 here means that participant is completing the experiment the second time).
- `rt_flip`: the reaction time for the choice, measured in seconds, multiplied by -1 if the choice is not an optimal choice. It is used for fitting various drift diffusion models.