structs
- class snafu.structs.Data(data)[source]
Bases:
objectContainer for fluency data used in SNAFU analyses.
This class processes hierarchical and non-hierarchical list data structures into formats that are convenient for analysis, including labeled responses, corrected spellings, intrusions, and IRTs.
- Parameters:
data (dict) – Dictionary containing keys: - ‘Xs’ : nested dict of fluency responses - ‘items’ : dict of item labels - ‘structure’ : bool, True if hierarchical - ‘spell_corrected’, ‘perseverations’, ‘intrusions’, ‘categories’, ‘irts’ (optional)
- hierarchical()[source]
Process hierarchical (nested) fluency data structure.
- Returns:
self – The Data object with hierarchical attributes populated.
- Return type:
- snafu.structs.DataModel(data)[source]
Fill in missing parameters in a data dictionary for generative model configuration.
This sets default values for generative search parameters, such as jump probability, priming effects, and censoring faults.
- Parameters:
data (dict) – Dictionary with optional keys like ‘trim’, ‘jump’, ‘jumptype’, ‘priming’, ‘jumponcensored’, ‘censor_fault’, ‘emission_fault’, etc.
- Returns:
A dictionary-like object with attribute access to the parameters.
- Return type:
- snafu.structs.Fitinfo(fitinfo)[source]
Fill in missing fields in a dictionary of model-fitting configuration.
Sets default values for priors, graph options, and Conceptual Network parameters.
- Parameters:
fitinfo (dict) – Dictionary of model fitting options.
- Returns:
Dictionary with all required fitting parameters populated.
- Return type:
- snafu.structs.Irts(irts)[source]
Fill in missing parameters in IRT configuration dictionary.
Supports gamma and ex-Gaussian IRT types. Sets default parameter values if missing.
- Parameters:
irts (dict) – Dictionary with keys like ‘irttype’, ‘gamma_beta’, ‘exgauss_lambda’, etc.
- Returns:
A dictionary-like object with completed IRT configuration.
- Return type: