GratingDemo from PsychDemos

function GratingDemo
% GratingDemo shows how to use WhiteIndex, BlackIndex, and 'PutImage' to
% display a grating of known contrast at any orientation and pixelSize.
...
% grating
[x,y]=meshgrid(-100:100,-100:100);
orientation=17; % tilt (deg)
f=0.03; % spatial frequency (cycles/pixel)
lambda=1.5/f; % gaussian space constant (pixels); "1.5/f" yields 1.5 cycle
a=cos(orientation*pi/180)*2*pi*f;
b=sin(orientation*pi/180)*2*pi*f;
m=exp(-((x/lambda).^2)-((y/lambda).^2)).*sin(a*x+b*y);
Screen(window,'PutImage',gray+inc*m);
...

SpriteDemo from PsychDemos

PsychToolBox
SpriteDemo：画面処理の短い例 (function)
while ~any(buttons)
[mX,mY,buttons] = GetMouse;
Screen(w,'WaitBlanking');
% erase the sprite drawn at the previous location
r=CenterRectOnPoint(spriteRect,previousX, previousY);
Screen('CopyWindow',wCopy,w,r,r);
% draw the sprite at the new location.
Screen('CopyWindow',wSprite,w,spriteRect,CenterRectOnPoint(spriteRect,mX, mY));
previousX = mX;
previousY = mY;
end

QUESTdemo by PsychToolBox

Simulate QUEST threshold measurement.

When you test a real human observer, instead of a simulated observer,
you won't know the true threshold. However you can still guess. You
must provide Quest with an initial threshold estimate as a mean and
standard deviation, which we call your "guess" and "sd". Be generous
with the sd, as Quest will have trouble finding threshold if it's more
than one sd from your guess.
Estimate threshold (e.g. -1): -1
Estimate the standard deviation of your guess, above, (e.g. 2): 2
...
4 ms/trial
Final threshold estimate (meanアsd) is -1.93 ア 0.10

You set the true threshold to -2.00.
Quest knew only your guess: -1.00 ア 2.00.

BETA. Many people ask, so here's how to analyze the data with beta as a free
parameter. However, we don't recommend it as a daily practice. The data
collected to estimate threshold are typically concentrated at one
contrast and don't constrain beta. To estimate beta, it is better to use
100 trials per intensity (typically log contrast) at several uniformly
spaced intensities. We recommend using such data to estimate beta once,
and then using that beta in your daily threshold meausurements. With
that disclaimer, here's the analysis with beta as a free parameter.
Now re-analyzing with both threshold and beta as free parameters. ...
logC アsd beta アsd gamma
-1.93 0.10 4.0 3.7 0.500
Actual parameters of simulated observer:
logC beta gamma
-2.00 3.5 0.50

smooth, curved interpolation

Kellman & Shipley (1991) Appendix 2, Ullman (1976)
Fontani & Gerbino (2003)
...
The exact form of smooth, interpolated contours has proven difficult to determine, as many models make similar predictions in many circumstances.
...
Saidpour, Braunstein, & Hoffman (1994): the shape of surface interpolation in structure from motion display

<3D extensions of the models proposed by Ullman (1976) and Kellman and Shipley (1991) <3D model of interpolation based on minimization of the quadratic variation function: Gimson (1981)
References
Kellman, Garrigan, & Shipley in press.
(p.14)