BinaryDecisionMaker

class Python_modules.mmcomplexity.BinaryDecisionMaker(stimulus_object, sources_prior=(0.5, 0.5))

Bases: object

Base class to simulate an observer performing our Auditory change-point 2AFC task. Note that the bulk of the decision process algorithm is intentionally not implemented in this class. Thus, classes inheriting from it must re-implement the process() method. This model uses the true probability that the sound occurs on same side as the source.

Attributes Summary

bias	probability with which observer picks ‘right’ when guessing.
mislocalization_noise	probability with which the observer hears a tone on the wrong side

Methods Summary

observe([list_of_sounds])	Generate subjective observations of a given stimulus
process()	must be implemented in subclasses

Attributes Documentation

bias = 0.5

probability with which observer picks ‘right’ when guessing. Unbiased corresponds to 0.5

mislocalization_noise = 0

probability with which the observer hears a tone on the wrong side

Methods Documentation

observe(list_of_sounds=None)

Generate subjective observations of a given stimulus

todo: what to do if list_of_sounds is not None but distinct from self.stimulus_object.sound_sequence?

Args:

list_of_sounds (list): list of sound locations (str). If None, uses self.stimulus_object.sound_sequence

Returns:

None: But sets self.observations

process()

must be implemented in subclasses