psychophysics.Detect - dstolz/epsych_v1.1 GitHub Wiki
Detect Class
Analyzes psychophysical detection task data, decodes trial outcomes, and computes performance metrics such as d-prime and bias.
Overview
The Detect
class processes trial data from psychophysical experiments, extracting, decoding, and summarizing key outcomes and performance statistics. It uses information from the trial structure and parameter definitions to provide detailed performance analysis for a specified trial type.
Example Usage
% Suppose you have RUNTIME.TRIALS and a parameter object "param"
D = psychophysics.Detect(RUNTIME.TRIALS, param, epsych.BitMask.TrialType_0);
% Get the total number of stimulus trials
numTrials = D.trialCount;
% Get hit and false alarm rates for each stimulus value
rates = D.Rate;
% Get d-prime and bias values
dprimes = D.DPrime;
biases = D.Bias;
% Get summary count of hits/misses/etc. for each value
counts = D.Count;
% Recompute for TrialType_1 (typically catch trials; see epsych.BitMask)
D.targetTrialType = epsych.BitMask.TrialType_1;
catchTrials = D.Rate;
Properties
Main Properties
TRIALS
: Structure containing trial data (e.g.,RUNTIME.TRIALS
).Parameter
: The parameter object that defines trial parameters (e.g., a stimulus property).infCorrection
: Correction bounds for infinite z-scores, as[lower upper]
. Default:[0.05 0.95]
.targetTrialType
: The trial type to analyze (as aBitMask
).ttStimulus
: BitMask for stimulus trials.ttCatch
: BitMask for catch trials.Bits
: Array of BitMask values for responses.BitColors
: Colors for each outcome type.Helper
: Helper object (for event management and utilities).
Dependent Properties (read-only, calculated automatically)
DATA
: Extracted trial data fromTRIALS
.trialCount
: Number of trials matchingtargetTrialType
.trialType
: Array of trial types inDATA
.trialValues
: Parameter values fortargetTrialType
trials.uniqueValues
: Unique parameter values amongtrialValues
.countUniqueValues
: Count of each unique parameter value.Count
: Struct with counts of trial outcomes (e.g., Hit, Miss).Rate
: Struct with rates of trial outcomes (proportion).DPrime
: d-prime values for each unique parameter value.Bias
: Bias values for each unique parameter value.
Read-only/Protected
decodedTrials
: Decoded trial outcomes (as adecodeTrials
object).
Key Methods
-
Constructor:
obj = Detect(TRIALS, Parameter, targetTrialType)
Initializes theDetect
object with the given trial data, parameter object, and target trial type. -
update_data:
Updates trial data and decoded outcomes on new data events. -
d_prime (static):
Computes d-prime given hit and false alarm rates. -
bias (static):
Computes bias given hit and false alarm rates. -
norminv (static):
Bounded inverse normal transform to avoid infinite values.