gapnet.psychoacoustics.updown.UpDownDetector

class documentation

class UpDownDetector: (source)

UpDownDetector

A class for handling an x-up y-down experiment setup Detects and counts reversals and whether the stimulus parameter should be increased or decreased

Method	`__init__`	No summary
Method	`__len__`	Undocumented
Method	`get_from_log`	Returns the log for the given parameter.
Method	`get_mean_parameter_value`	No summary
Method	`next`	Takes the answer, can be anything, but should be either equal to `correct` or `wrong`, provided in `__init__` (default is int(1) for correct and int(0) for wrong).
Method	`reset`	Reset the internal counters, as if a new experiment is started
Instance Variable	`consecutive_correct`	Undocumented
Instance Variable	`consecutive_wrong`	Undocumented
Instance Variable	`correct`	Undocumented
Instance Variable	`entry`	Undocumented
Instance Variable	`experiment_log`	Undocumented
Instance Variable	`last_parameter_change`	Undocumented
Instance Variable	`number_of_reversals`	Undocumented
Instance Variable	`response_sequence_dict`	Undocumented
Instance Variable	`wrong`	Undocumented
Method	`_update_experiment_log`	Undocumented

def __init__(self, entry=2, correct=1, wrong=0): (source) ¶

Parameters
entry:`int`	refers to the "Entry" column in Table 1 of Levitt 1971 (default: 2)
correct	response that represents a correct answer
wrong	response that represents an incorrect answer

def __len__(self): (source) ¶

Undocumented

def get_from_log(self, parameter): (source) ¶

Returns the log for the given parameter.

If log is empty, None is returned

Parameters
parameter	parameter to return from log
Raises
`ValueError`	if parameter is not in log keys

def get_mean_parameter_value(self, n_reversals=1): (source) ¶

Parameters
n_reversals	number of reversals to include
Returns
the mean parameter value from the last n_reversals

def next(self, answer, parameter_value=None): (source) ¶

Takes the answer, can be anything, but should be either equal to `correct` or `wrong`, provided in `__init__` (default is int(1) for correct and int(0) for wrong).

Parameters
answer	Any type, but must be compatible with `answer == self.correct` and `answer == self.correct`
parameter_value	Any type that can be summed and calculated the mean of.
Returns
0 : whether the stimulus parameter should be updated up or down (1 or -1), or kept as is (0) 1 : whether a reversal occurred (True or False)