measurePeripheralThresholdsClass.m

% measurePeripheralThresholds
% February 28, 2017, denis.pelli@nyu.edu
% Script for Ning and Chen to measure equivalent noise in the periphery.

clear o
o.durationSec=0.5; % signal duration. [0.05, 0.5]
o.trialsDesired=40;

% NOISE
o.isNoiseDynamic = 1; % 0 for static noise
o.moviePreSec = 0.1; % ignored for static noise
o.moviePostSec = 0.2; % ignored for static noise
o.noiseType='binary'; % 'gaussian' or 'uniform' or 'binary'
o.noiseSpectrum='white'; % pink or white
o.noiseCheckDeg=0.09;
o.noiseSD=0.5; % max is 0.16 for gaussian, 0.5 for binary.
o.noiseEnvelopeSpaceConstantDeg=128; % always Inf for hard edge top-hat noise
o.noiseRadiusDeg=inf; % noise decay radius [1 1.7 3 5.2 9 Inf]

% LETTER
o.targetHeightDeg=7.64; % Target size, range 0 to inf.
o.eccentricityXYDeg=[0 0]; % [0 8 16 32]
o.targetKind='letter';
o.targetFont='Sloan';
o.alphabet='DHKNORSVZ';
o.alternatives=length(o.alphabet); % number of letters to use from o.alphabet

% TO REPLICATE MANOJ
% o.targetFont='ITC Bookman Std';
% o.alphabet='abcdefghijklmnopqrstuvwxyz';
% o.alternatives=length(o.alphabet); % number of letters to use from o.alphabet
% o.targetHeightDeg=2*7.64; % Manoj used xHeight of 7.64 deg.

% FIXATION
o.fixationMarkDeg = 1; % Typically 1 or inf. Make this at least 4 deg for scotopic testing, since the fovea is blind scotopically.
o.targetCross=1;
o.fixationThicknessDeg = 0.05; % target line thickness
o.isFixationBlankedNearTarget = 0; % 0 or 1.
o.fixationMarkBlankedUntilSecAfterTarget = 0.6; % Pause after stimulus before display of fixation.
% Skipped when isFixationBlankedNearTarget. Not needed when eccentricity is bigger than the target.

% USER INTERFACE
o.alphabetPlacement='top'; % show possible answers on 'top' or 'right' for letters and gabors.
% o.fixationThicknessDeg=0.05; % target line thickness
o.isKbLegacy=0; % Uses KbWait, KbCheck, KbStrokeWait functions, instead of GetChar, for Linux compatibility.
% o.tGuess=log10(0.2); % Optionally tell Quest the initial log contrast on first trial.

% SNAPSHOT
o.saveSnapshot=0; % 0 or 1.  If true (1), take snapshot for public presentation.
o.saveStimulus=0;
o.snapshotLetterContrast=0.01; % nan to request program default. If set, this determines o.tSnapshot.
o.cropSnapshot=1; % If true (1), show only the target and noise, without unnecessary gray background.
o.snapshotCaptionTextSizeDeg=0.5;
o.snapshotShowsFixationBefore=1;
o.snapshotShowsFixationAfter=0;
o.speakInstructions=0;

% DEBUGGING
o.useFractionOfScreenToDebug=0; % 0: normal, 0.5: small for debugging.
o.flipClick=0;
o.assessContrast=0;
o.assessLoadGamma=0;
o.showCropMarks=0; % mark the bounding box of the target
o.printDurations=0;

% Please measure:
% Sloan
% Eccentricities = 0, 3, 10, 30 deg
% Duration = 0.05, 0.5 s
% targetHeightDeg = 1, 4, 16 deg
% ?(Note: at 30 deg ecc, omit 1 deg. Substitute 2 deg.)?
% WITH AND WITHOUT NOISE
% gaussian
% noiseSD = 0.16
% checkHeightDeg = targetHeightDeg/20
% checkSec = 1/60 s.
% PreSecs = 0.1 s.
% PostSecs = 0.2 s.
% REPEAT
% If the two threshold contrasts, after repetition, differ by 2x or more,
% then please collect a third point.

% IMPORTANT: Use a tape measure or meter stick to measure the distance from
% your eye to the screen. The number below must be accurate.
o.observer='Chen'; % use your name
o.distanceCm=70; % viewing distance
o.targetFont='Sloan';
o.alphabet='DHKNORSVZ';
o.noiseType='gaussian'; % 'gaussian' or 'uniform' or 'binary'
% o.durationSec=0.5;
% o.noiseSD=0.0;
% o.targetHeightDeg=16;
% o.eccentricityXYDeg=[10 0];
if 0
    cnt = 0;
    for ecc=[0, 3, 10]
        for dur=[0.05 0.5]
            for height=[1 4 16]
                for nSD=[0 0.16]
                    o.eccentricityXYDeg=[ecc 0];
                    o.durationSec=dur;
                    o.targetHeightDeg=height;
                    o.noiseCheckDeg=height/20;
                    o.noiseSD=nSD;
                    for a = 1:2
                        o=NoiseDiscrimination(o);
                        cnt = cnt + 1;
                        Data{cnt}=o;
                        %o=NoiseDiscrimination(o); % REPEAT
                    end
                end
            end
        end
    end
end
% letter size at eccentricity of 30 too small if it is 1
if 0
    cnt = 72;
    for ecc=[30]
        for dur=[0.05 0.5]
            for height=[2 4 16]
                for nSD=[0 0.16]
                    o.eccentricityXYDeg=[ecc 0];
                    o.durationSec=dur;
                    o.targetHeightDeg=height;
                    o.noiseCheckDeg=height/20;
                    o.noiseSD=nSD;
                    for a = 1:2
                        o=NoiseDiscrimination(o);
                        cnt = cnt + 1;
                        Data{cnt}=o;
                        %o=NoiseDiscrimination(o); % REPEAT
                    end
                end
            end
        end
    end
end

% DO THIS FIRST:
% Before collecting a lot of data we need to be sure that this noise is
% strong enough to always elevate threshold, so we should FIRST try the
% toughest threshold:
% Eccentricity = 30 deg
% Duration = 0.5 s
% targetHeightDeg = 16 deg
% checkHeightDeg = targetHeightDeg/20 =  0.8 deg
% With and without noise
if 0
    for nSD=[0 0.16]
        o.eccentricityXYDeg=[30 0];
        o.durationSec=0.5;
        o.targetHeightDeg=16;
        o.noiseCheckDeg=o.targetHeightDeg/20;
        o.noiseSD=nSD;
        o=NoiseDiscrimination(o);
        o=NoiseDiscrimination(o); % REPEAT
    end
end


% We want threshold with noise at least twice threshold without noise. If
% not, we may need to increase the check size or switch to binary noise.
% Please let us know!

% The dark filter is important, but will play only a small role, so we only
% need a bit of data with it.
% WITH DARK FILTER
% targetHeightDeg = 1 deg
% Eccentricities = 0, 3, 10, 30 deg
% WITH AND WITHOUT NOISE
if 0
    for ecc=[0, 3, 10, 30]
        for dur=0.5
            for height=1
                for nSD=[0 0.16]
                    o.eccentricityXYDeg=[ecc 0];
                    o.durationSec=dur;
                    o.targetHeightDeg=height;
                    o.noiseCheckDeg=height/20;
                    o.noiseSD=nSD;
                    o=NoiseDiscrimination(o);
                    o=NoiseDiscrimination(o); % REPEAT
                end
            end
        end
    end
end

% new collecting data
% duration .2s
% size 2 4 7 16
% eccentricity 0 3 10 30
% noiseSD 0 and 016
% gaissian noise
o.durationSec = 0.2;
sizes = [2 4 8 16];
eccenticityDeg = [0 3 10 30];
noiseSD = [0];
if 0
    for ecc = eccenticityDeg
        o.observer='ning';
        for LetterSize = sizes
            for noise = noiseSD
                o.eccentricityXYDeg=[ecc 0];
                o.targetHeightDeg=LetterSize;
                o.noiseCheckDeg=o.targetHeightDeg/20;
                o.noiseSD=noise;
                o=NoiseDiscrimination(o);
            end
        end
    end
end


if 0
    noiseSD=[0];
    lettersize = [16];
    o.observer='ning';
    for letter_size = lettersize
        for noise = noiseSD
            o.targetHeightDeg= letter_size;
            o.eccentricityXYDeg = [10 0];
            o.noiseSD=noise;
            o.noiseCheckDeg=o.targetHeightDeg/20;
            o=NoiseDiscrimination(o);
        end
    end
end

% o.useFractionOfScreenToDebug=.3;
o.isNoiseDynamic = 1; % 0 for static noise
o.durationSec = 1;
o.observer='class';
o.assessContrast=0;
o.assessLoadGamma=0;
o.assessGray=0;
o.assessTargetLuminance=0;
o.tGuess=log10(0.01);
o.eccentricityXYDeg=[0 0];
o.targetHeightDeg=8;
o.noiseCheckDeg=o.targetHeightDeg/20;
o.noiseType='binary'; % 'gaussian' or 'uniform' or 'binary'
o.noiseSD=0.5;
o.screen=0;
o.nearPointXYInUnitSquare=[0.5 0.5];
o=NoiseDiscrimination(o);
% imshow(o.actualStimulus);