/usr/share/psychtoolbox-3/PsychTests/HighPrecisionLuminanceOutputDriversImagingPipelineTest.m is in psychtoolbox-3-common 3.0.11.20131230.dfsg1-1build1.
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% HighPrecisionLuminanceOutputDriversImagingPipelineTest(whichDriver, [whichScreen][,plotdiffs=0][, forcesuccess=0])
%
% Tests correct function of a variety of high precision luminance output
% device drivers (so called "output formatters") with imaging pipeline.
%
% This test script needs to be run once after each graphics card or
% graphics driver or Psychtoolbox upgrade, or after any other major change
% in system configuration and display settings.
%
% This test verifies that the Psychtoolbox image processing pipeline is
% capable to correctly convert a high dynamic range / high bit precision
% luminance image into a output format suitable for driving one of the
% supported high precision luminance output devices, e.g., different Pelli,
% Zhang, Watson style video attenuators, Xiangru Li et al. VideoSwitchers,
% Pseudo-Gray output formatters, etc.
%
% It does so by generating a test stimulus, converting it into a properly
% formatted image via the "known good" Matlab reference implementation of
% an output driver, then again via the use of the imaging pipeline. Then
% it reads back and compares the conversion results of both to verify that
% the imaging pipeline produces exactly the same results as the Matlab
% routines.
%
% If the results are the same, it will write some info file to the
% filesystem to confirm this test was successfully run, otherwise it will
% fail with a description of the discrepancy. In case of failure, fast
% stimulus conversion will not work via the imaging pipeline.
%
% The required parameter 'whichDriver' defines the type of output driver to
% test. It can be any of the following:
%
% * 'GenericLUT': Test the generic lookup-table based driver that can handle
% arbitrary devices, albeit not with maximum speed. 'whichDriver' must be a
% struct with the following fields:
%
% whichDriver.name = 'GenericLUT'
%
% Then either one of these for testing of a generic LUT:
%
% whichDriver.bpc = Bitdepths of LUT to test - Anything between 1 and 16.
% whichDriver.nslots = Size of LUT in slots - Anything between 2 and 65536.
%
% Alternatively you can test with an existing self-created LUT:
% whichDriver.lut = A 3 rows by nslots column uint8 matrix which encodes
% the LUT: Rows 1,2 and 3 encode Red, Green and Blue channel, each of the
% 'nslots' columns encodes a LUT slot. The driver will map luminance values
% between 0.0 and 1.0 to the corresponding LUT slots in range 1 to nslots,
% then readout the stored column vector with the output RGBA8 pixels to
% poke into the framebuffer.
%
% * 'VideoSwitcherSimple': Test the "simple" driver for the VideoSwitcher
% video attenuator. The simple driver implements a closed-form solution, a
% formula, to map luminance values between 0.0 - 1.0 to output values for
% the Red and Blue channel, just using the 'BTRR' ratio as parameter. This
% is the fast driver, as it doesn't need any lookup tables.
%
% You should provide the whichDriver.btrr BTRR ratio when testing this
% driver. If you omit it, it will be loaded from the configuration file in
% the Psychtoolbox configuration directory.
%
% * 'VideoSwitcherCalibrated': Test the LUT based driver for the VideoSwitcher
% video attenuator. This driver computes the Blue channel value by
% searching for the given luminance value in a 256 entry lookup table, then
% uses a closed-form formula to compute the Red channel drive value from
% the luminance and the looked-up blue channel value. This is slower due to table
% lookups and requires more involved calibration procedures to build a
% lookup table, but it is also potentially more accurate.
%
% You should provide the whichDriver.btrr BTRR ratio when testing this
% driver, as well as the 257 slot whichDriver.lut lookup table for blue
% channel to measured luminance mapping. See help PsychVideoSwitcher for
% more info. If you omit these parameters, a default BTRR and LUT will be
% loaded from the Psychtoolbox configuration subdirectory.
%
% Optional parameters:
%
% whichScreen = Screen id of display to test on. Will be the secondardy
% display if none provided.
%
% plotdiffs = If set to one, plot diagnostic difference images, if any
% differences are detected. By default no such images are
% plotted. No images will be plotted if no differences
% exist.
%
% forcesuccess = Set this to one if you want to force the test to succeed,
% despite detected errors, ie., if you want the GPU
% conversion to be used. Only use this if you really know
% what you are doing!
%
% Please note that this test script can only test if the correct output to
% your systems framebuffer is generated by Psychtoolbox. It can't detect if
% the electronic high precision converter device itself is working
% correctly with this data. Only visual inspection and a
% photometer/colorimeter test can really tell you if the whole system is
% working correctly!
%
% History:
% 05/24/08 mk Initial implementation.
oldverbosity = Screen('Preference', 'Verbosity', 2);
oldsynclevel = Screen('Preference', 'SkipSyncTests', 2);
% Which driver to test?
if nargin < 1 || isempty(whichDriver)
error('You must provide a valid "whichDriver" argument!');
end
% Define screen:
if nargin < 2 || isempty(whichScreen)
whichScreen=max(Screen('Screens'));
end
if nargin < 3 || isempty(plotdiffs)
plotdiffs = 0;
end
if nargin < 4 || isempty(forcesuccess)
forcesuccess = 0;
end
if isstruct(whichDriver)
% Extract 'bpc' subfield, if any:
if isfield(whichDriver, 'bpc')
driverBpc = whichDriver.bpc;
if ~isscalar(driverBpc) || driverBpc < 1 || driverBpc > 16
error('"whichDriver.bpc" argument is not a integral bitdepths value in valid range 1 - 16!');
end
else
driverBpc = [];
end
% Extract 'nslots' subfield, if any:
if isfield(whichDriver, 'nslots')
driverNSlots = whichDriver.nslots;
if ~isscalar(driverNSlots) || driverNSlots < 2 || driverNSlots > 2^16
error('"whichDriver.nslots" argument is not an integral value in valid range 2 - 65536!');
end
else
driverNSlots = [];
end
% Extract 'lut' subfield, if any:
if isfield(whichDriver, 'lut')
driverLUT = whichDriver.lut;
if ~isa(driverLUT, 'uint8') || size(driverLUT, 1) < 3 || size(driverLUT, 1) > 4 || size(driverLUT, 2) < 2 || size(driverLUT, 2) > 65536
error('"whichDriver.lut" argument is not a LUT definition matrix: Must be a matrix of class uint8 with 3 or 4 rows and between 2 and 65536 columns!');
end
if size(driverLUT, 1)~=4
% Extend with 4th row of all zero bytes:
driverLUT = [driverLUT ; uint8(zeros(1, size(driverLUT, 2)))];
end
else
driverLUT = [];
end
% Extract 'bpc' subfield, if any:
if isfield(whichDriver, 'btrr')
driverBTRR = whichDriver.btrr;
if ~isscalar(driverBTRR) || ~isnumeric(driverBTRR) || driverBTRR < 0
error('"whichDriver.btrr" argument is not a scalar Blue-To-Red-Ratio value greater than zero.');
end
else
driverBTRR = [];
end
% This comes last! Check if .name subfield provided and replace whole
% struct with that name:
if isfield(whichDriver, 'name')
whichDriver = whichDriver.name;
else
error('Argument "whichDriver" is a struct, but lacks the mandatory subfield "name"!');
end
else
driverBpc = [];
driverNSlots = [];
driverLUT = [];
driverBTRR = [];
end
if ~ischar(whichDriver)
error('"whichDriver" or "whichDriver.name" is not a driver name string!');
end
if isempty(driverNSlots) && ~isempty(driverBpc)
driverNSlots = 2^driverBpc;
end
if ~isempty(driverLUT)
driverNSlots = size(driverLUT, 2);
end
% Prepare imaging pipeline setup:
PsychImaging('PrepareConfiguration');
% Make sure we run with our default color correction mode for this test:
% 'ClampOnly' is the default, but we set it here explicitely, so no state
% from previously running scripts can bleed through. This will also setup
% the default clamping range to our wanted 0.0 - 1.0 range:
PsychImaging('AddTask', 'FinalFormatting', 'DisplayColorCorrection', 'ClampOnly');
fprintf('Testing output formatting driver of type: %s\n', whichDriver);
fprintf('Number of slots (if any): %i\n', driverNSlots);
fprintf('Number of bpc bits (if any): %i\n', driverBpc);
fprintf('BTRR (if any): %i\n', driverBTRR);
fprintf('\n\n\n');
% Select whichDriver to test:
switch (whichDriver)
case {'GenericLUT'}
% Generic LUT conversion with a LUT that has driverNSlots slots
% to map the 0.0 - 1.0 input range into 0 - driverNSlots - 1
% integral range, then lookup the value:
if isempty(driverNSlots)
error('Driver type "GenericLUT" selected, but "whichDriver.nslots" argument missing!');
end
if isempty(driverLUT)
% Build standard testing LUT with driverNSlots slots for testing:
lut = uint8(zeros(4, driverNSlots));
theRange = 0:driverNSlots-1;
theInverseRange = (driverNSlots-1) - theRange;
lut(1, 1:driverNSlots) = uint8(floor(theRange/256)); % Red channel: High Byte.
lut(2, 1:driverNSlots) = uint8(floor(mod(theRange, 256))); % Green channel: Low Byte.
lut(3, 1:driverNSlots) = uint8(floor(theInverseRange/256)); % Blue channel: Inverse range High Byte.
lut(4, 1:driverNSlots) = uint8(floor(mod(theInverseRange, 256))); % Alpha channel: Inverse range Low Byte.
plotchannel = [1,1,1,1];
else
% LUT provided: Just use it "as is":
lut = driverLUT;
plotchannel = [1,1,1,0];
end
% Enable generic LUT luminance output formatter and provide it with
% our lut:
PsychImaging('AddTask', 'General', 'EnableGenericHighPrecisionLuminanceOutput', lut);
% Build test image:
theInImage = reshape(linspace(0, 1, 2^16), 256, 256);
% Build reference image:
theIntImage = uint32( floor(theInImage * (driverNSlots-1)) );
theRefImage = zeros(256, 256, 4);
% Recompute theInImage from the theIntImage -- theInImage shall
% become a quantized version of itself - quantized to
% driverNSlots-1 levels. This way we can be sure that the GPU and
% CPU get initially fed with the same data for conversion:
theInImage = double(theIntImage) / (driverNSlots-1);
uniqueValsA = length(unique(theInImage));
uniqueValsB = length(unique(theIntImage));
if (uniqueValsA~=uniqueValsB) || (uniqueValsA~=driverNSlots)
fprintf('Ouch! Number of unique test samples in different images is not the same! Bug in test code?!?\n');
fprintf('Input to GPU (float) = %i, Input to CPU (uint32) = %i, Reference Expected (nr. slots) = %i\n', uniqueValsA, uniqueValsB, driverNSlots);
error('Mismatch in unique values count! Likely a bug in this test code!');
end
theRefImage(:,:,1:3) = ind2rgb(theIntImage, double(lut(1:3,:)'));
% Need to treat alpha channel separately, as ind2rgb can only
% handle 3 layer images...
theAlphaImage = ind2rgb(theIntImage, double(repmat(lut(4,:)', 1, 3)));
theRefImage(:,:,4) = theAlphaImage(:,:,1);
% Convert to uint8:
theRefImage = uint8(theRefImage);
case {'VideoSwitcherSimple'}
% Select simple VideoSwitcher output formatter:
PsychImaging('AddTask', 'General', 'EnableVideoSwitcherSimpleLuminanceOutput', driverBTRR);
if isempty(driverBTRR)
% Fetch default from file:
driverBTRR = PsychVideoSwitcher('GetDefaultConfig', whichScreen);
end
% Build test image:
theInImage = reshape(linspace(0, 1, 2^16), 256, 256);
% Build reference image:
theRefImage = uint8(zeros(256, 256, 4));
theRefImage(:,:,1:3) = PsychVideoSwitcher('MapLuminanceToRGB', theInImage, driverBTRR, 0);
plotchannel = [1,0,1,0];
case {'VideoSwitcherCalibrated'}
if isempty(driverBTRR) || isempty(driverLUT)
[mydriverBTRR, mydriverLUT] = PsychVideoSwitcher('GetDefaultConfig', whichScreen);
if isempty(driverBTRR)
driverBTRR = mydriverBTRR;
end
if isempty(driverLUT)
driverLUT = mydriverLUT;
end
end
% Select calibrated VideoSwitcher output formatter:
PsychImaging('AddTask', 'General', 'EnableVideoSwitcherCalibratedLuminanceOutput', driverBTRR, driverLUT);
% Build test image:
theInImage = reshape(linspace(0, 1, 2^16), 256, 256);
% Build reference image:
theRefImage = uint8(zeros(256, 256, 4));
theRefImage(:,:,1:3) = PsychVideoSwitcher('MapLuminanceToRGBCalibrated', theInImage, driverBTRR, driverLUT, 0);
plotchannel = [1,0,1,1];
otherwise
error('Unknown drivername provided. Not supported! Typo?!?');
end
% Common code for testing:
% Perform GPU conversion and readback results:
[m,n,p] = size(theRefImage);
rect = [0 0 m n];
% Show the image
window = PsychImaging('OpenWindow', whichScreen, 0);
% Double-Check for bugs in PsychImaging:
winfo = Screen('GetWindowInfo', window);
if ~bitand(winfo.ImagingMode, kPsychNeed32BPCFloat)
Screen('CloseAll');
RestoreCluts;
error('Onscreen window not configured for 32 bpc float drawing! This should not happen and is a bug in PsychImaging.m setup code for this formatter!!');
end
% Find out how big the window is:
[screenWidth, screenHeight]=Screen('WindowSize', window);
% Build HDR input texture as 32 bpc float luminance texture:
hdrtexIndex= Screen('MakeTexture', window, double(theInImage), [], [], 2);
% Draw image as generated by PTB GPU imaging pipeline:
dstRect = Screen('Rect', hdrtexIndex);
% Draw with nearest neighbour filtering - no bilinear filtering!
Screen('DrawTexture', window, hdrtexIndex, [], dstRect, [], 0);
% Finalize image before we take a screenshot:
Screen('DrawingFinished', window, 0, 1);
% Take screenshot of GPU converted image:
convImage=Screen('GetImage', window, dstRect, 'backBuffer', 0, 4);
% Show GPU converted image. Should obviously not make any visual difference if
% it is the same as the Matlab converted image.
vbl = Screen('Flip', window);
% Disable output formatters:
Screen('HookFunction', window, 'Disable', 'FinalOutputFormattingBlit');
% Build and draw texture from reference image - This is just for
% visualization, not used for comparison:
texpacked= Screen('MakeTexture', window, theRefImage);
dstRect = Screen('Rect', texpacked);
Screen('DrawTexture', window, texpacked, [], dstRect, [], 0);
% Show it:
vbl = Screen('Flip', window, vbl + 1);
% Keep it onscreen for 2 seconds, then blank screen:
Screen('Flip', window, vbl + 2);
% Done. Close everything down:
Screen('CloseAll');
RestoreCluts;
% Comparisons...
% Compute difference images between Matlab converted packedImage and GPU converted
% HDR image:
diffred = (double(theRefImage(:,:,1)) - double(convImage(:,:,1)));
diffgreen = (double(theRefImage(:,:,2)) - double(convImage(:,:,2)));
diffblue = (double(theRefImage(:,:,3)) - double(convImage(:,:,3)));
diffalpha = (double(theRefImage(:,:,4)) - double(convImage(:,:,4)));
% Compute maximum deviation of framebuffer raw data:
mdr = max(max(abs(diffred)));
mdg = max(max(abs(diffgreen)));
mdb = max(max(abs(diffblue)));
mda = max(max(abs(diffalpha)));
fprintf('\n\nMaximum raw data difference: red= %f green = %f blue = %f alpha = %f\n', mdr, mdg, mdb, mda);
% If there is a difference, show plotted difference if requested:
if (mdr>0 || mdg>0 || mdb>0 || mda>0) && plotdiffs
% Differences detected!
close all;
if plotchannel(1), figure; imagesc(diffred); title('Difference map - Channel 1 (Red):'); end
if plotchannel(2), figure; imagesc(diffgreen); title('Difference map - Channel 2 (Green):'); end
if plotchannel(3), figure; imagesc(diffblue);title('Difference map - Channel 3 (Blue):'); end
if plotchannel(4), figure; imagesc(diffalpha);title('Difference map - Channel 4 (Alpha):'); end
end
if (mdr>0 || mdg>0 || mdb>0 || mda>0) || (plotdiffs > 1)
% Now compute a more meaningful difference: The difference between the
% stimulus as the Bits++ box would see it (i.e. how much do the 16 bit
% intensity values of each color channel differ?):
c=1;
convImage = double(convImage);
packedImage = double(theRefImage);
switch (whichDriver)
case {'GenericLUT'}
% Test of generic LUT conversion:
deconvImage = zeros(size(convImage,1), size(convImage,2));
depackImage = zeros(size(packedImage,1), size(packedImage,2));
if isempty(driverLUT)
% Invert conversion: Compute 16 bpc color values from high/low byte
% pixel data:
deconvImage(:,:) = 256 * convImage(:, :, 1) + convImage(:, :, 2);
depackImage(:,:) = 256 * packedImage(:, :, 1) + packedImage(:, :, 2);
else
% Invert conversion by use of 'driverLUT':
fprintf('Inverting user provided LUT mapping - This can take very long...\n');
for row=1:size(convImage,1)
fprintf('Pass 1 of 2: Row %i of %i...\n', row, size(convImage,1));
for col=1:size(convImage,2)
candidatesa = find(lut(1, :) == convImage(row,col,1));
candidatesb = find(lut(2, :) == convImage(row,col,2));
candidatesc = find(lut(3, :) == convImage(row,col,3));
candidatesd = find(lut(4, :) == convImage(row,col,4));
candidates1 = intersect(candidatesa, candidatesb);
candidates2 = intersect(candidatesc, candidatesd);
deconvImage(row,col) = min(intersect(candidates1, candidates2) - 1);
end
end
for row=1:size(packedImage,1)
fprintf('Pass 2 of 2: Row %i of %i...\n', row, size(convImage,1));
for col=1:size(convImage,2)
candidatesa = find(lut(1, :) == packedImage(row,col,1));
candidatesb = find(lut(2, :) == packedImage(row,col,2));
candidatesc = find(lut(3, :) == packedImage(row,col,3));
candidatesd = find(lut(4, :) == packedImage(row,col,4));
candidates1 = intersect(candidatesa, candidatesb);
candidates2 = intersect(candidatesc, candidatesd);
depackImage(row,col) = min(intersect(candidates1, candidates2) - 1);
end
end
end
case {'VideoSwitcherSimple'}
% Test of simple VideoSwitcher driver:
% This is the (kind of) real value range of the device:
driverNSlots = 256 * driverBTRR;
% Remap:
deconvImage = ((convImage(:, :, 1) + convImage(:, :, 3) * driverBTRR) / (driverBTRR + 1)) / 255 * (driverNSlots - 1);
depackImage = ((packedImage(:, :, 1) + packedImage(:, :, 3) * driverBTRR) / (driverBTRR + 1)) / 255 * (driverNSlots - 1);
figure;
hiconvImage = convImage(:,:,3);
loconvImage = convImage(:,:,1);
higpu = hiconvImage(:);
lowgpu = loconvImage(:);
lumi = theInImage(:);
j = 1:length(higpu);
plot(lumi, higpu, '-', lumi, lowgpu, '--');
legend('High-Byte', 'Low-Byte');
title('GPU results in raw bytes: (x=Normalized Luminance (Req.) No., y = Byte value)');
case {'VideoSwitcherCalibrated'}
% Test of LUT calibrated VideoSwitcher driver:
% This is the (kind of) real value range of the device:
driverNSlots = 256 * driverBTRR;
% Remap:
deconvImage = ((convImage(:, :, 1) + convImage(:, :, 3) * driverBTRR) / (driverBTRR + 1)) / 255 * (driverNSlots - 1);
depackImage = ((packedImage(:, :, 1) + packedImage(:, :, 3) * driverBTRR) / (driverBTRR + 1)) / 255 * (driverNSlots - 1);
figure;
hiconvImage = convImage(:,:,3);
loconvImage = convImage(:,:,1);
higpu = hiconvImage(:);
lowgpu = loconvImage(:);
lumi = theInImage(:);
j = 1:length(higpu);
plot(lumi, higpu, '-', lumi, lowgpu, '--');
legend('High-Byte', 'Low-Byte');
title('GPU results in raw bytes: (x=Normalized Luminance (Req.) No., y = Byte value)');
% Compute average iteration count in shader etc.:
meaniterations = mean(mean(convImage(:,:,4)));
miniterations = min(min(convImage(:,:,4)));
maxiterations = max(max(convImage(:,:,4)));
fprintf('Per-Pixel search iterations in conversion shader: Min = %i, Max = %i, Mean = %f.\n', miniterations, maxiterations, meaniterations);
otherwise
error('Switch statement in deconversion part does not recognize driver name! Implementation bug!?!');
end
% Difference image:
diffImage = (deconvImage - depackImage);
% Find locations where pixels differ:
idxdiff = find(abs(diffImage) > 0);
numdiff(c) = length(idxdiff);
numtot(c) = size(diffImage,1)*size(diffImage,2);
maxdiff(c) = max(max(abs(diffImage)));
if plotdiffs > 1
idxdiff = find(diffImage~=inf);
end
[row col] = ind2sub(size(diffImage), idxdiff);
% Print out all pixels values which differ, and their difference:
if plotdiffs
figure;
dgpu = deconvImage(:);
dcpu = depackImage(:);
lumi = theInImage(:);
j = 1:length(dgpu);
plot(lumi, dgpu, '-', lumi, dcpu, '--');
legend('GPU', 'Matlab/Octave');
title('GPU vs. CPU results in device units: (x=Normalized Luminance (Req.) No., y = Luminance units)');
for j=1:length(row)
fprintf('Diff: %.2f Requested: %.10f Actual: GPU %f vs. CPU %f\n', diffImage(row(j), col(j)), theInImage(row(j), col(j)) * (driverNSlots-1), deconvImage(row(j), col(j)), depackImage(row(j), col(j)));
end
end
totalmaxdiff = max(maxdiff);
% Summarize for this color channel:
fprintf('\n\nIn remapped image: %i out of %i pixels differ. The maximum absolute difference is %f device units.\nTotal difference range: [%f - %f]\n', numdiff(c), numtot(c), maxdiff(c), min(min(diffImage)), max(max(diffImage)));
fprintf('The maximum absolute difference corresponds to %f %% of the total operating range of the device.\n', maxdiff(c) / (driverNSlots-1) * 100);
fprintf('Displayed differences and values are in "device units". They are proportional to levels of luminance (by an unknown factor)');
else
% No difference in raw values implies no difference at all:
totalmaxdiff = 0;
end
if (mdr>0 || mdg>0 || mdb>0 || mda>0) && (totalmaxdiff > 1.1) && ~forcesuccess
fprintf('\n\n');
fprintf('------------------ SIGNIFICANT DIFFERENCE IN CONVERSION DETECTED -----------------------\n');
fprintf('The difference is %f, ie., it is more than 1 device unit.\n', totalmaxdiff);
fprintf('This should not happen on properly and accurately working graphics hardware.\n');
fprintf('Either there is a bug in the graphics driver, or something is misconfigured or\n');
fprintf('your hardware is too old and not capable of performing the calculations in sufficient\n');
fprintf('precision.\nYou may want to check your configuration and upgrade your driver. If that\n');
fprintf('does not help, upgrade your graphics hardware. Alternatively you may want to use the old\n');
fprintf('Matlab-based conversion function for slow conversion of images.\n\n');
fprintf('Please report this failure with a description of your hardware setup to the Psychtoolbox\n');
fprintf('forum (http://psychtoolbox.org --> Link to the forum.)\n\n');
fprintf('You can force this test to succeed if you set the optional "forcesuccess" flag for this\n');
fprintf('script to one and rerun it.\n\n');
Screen('Preference', 'Verbosity', oldverbosity);
Screen('Preference', 'SkipSyncTests', oldsynclevel);
error('Conversion test failed. Results of Matlab code and GPU conversion differ!');
end
if (mdr>0 || mdg>0 || mdb>0 || mda>0) && (totalmaxdiff <= 1.1)
fprintf('\n\n');
fprintf('------------------ SMALL, PROBABLY INSIGNIFICANT DIFFERENCE IN CONVERSION DETECTED -----\n');
fprintf('The difference is %f, ie., it is only 1 device unit or less.\n', totalmaxdiff);
fprintf('Such a small deviation between Matlab''s/Octave''s result and the GPU result is usually \n');
fprintf('within the tolerable range of deviations. It is likely an artifact of the test procedure\n');
fprintf('itself or smallish numeric precision error on either GPU or CPU. Anyway, this minimal \n');
fprintf('difference will likely introduce an error that is much smaller than the error introduced\n');
fprintf('by drift and tolerances of your converter and display device, and errors in calibration.\n');
fprintf('You should inspect the numeric output above, and the plots and stimuli, but likely you \n');
fprintf('do not need to worry about this off-by-one difference.\n\n');
end
if (mdr==0 && mdg==0 && mdb==0 && mda==0)
fprintf('\n\n');
fprintf('------------------ PERFECT CONVERSION DETECTED -------------------------------\n');
fprintf('The difference is zero - All implementations deliver exactly the same results.\n');
end
fprintf('\n\n------------------- Conversion test success! -------------------------------------\n\n');
fprintf('Imaging pipeline conversion verified to work correctly. Validation info stored.\n');
% Done for now.
return;
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