Distinct eccentricity-driven dynamics in foveal and extrafoveal visual crowding.
The 2 matches
- [1] § STAR★Methods › Method details › Stimuli and apparatus ↔ private/tufteaxis.m, lines 112–217 · score 0.53 · aspect ratio, horizontal, vertically, background, edge, positioned
- [2] § Results › Crowding in the foveola ↔ demo_004.m, lines 56–144 · score 0.50 · staircase procedure, stimuli ranged, adaptive, width, threshold
Paper
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The authors' code
MATLAB · 309 lines · 14 KB · GPL-3.0 · 1 match
- function tufteaxis(mmx, mmy)
- %TUFTEAXIS changes the coordinate axis in a Tufte style.
- %
- % inputs:
- % mmx [min(x), max(x)], the existing XTick are used, OR
- % [min(x), t1, t2, t3, max(x)], use exactly these
- % mmy [min(y), max(y)], the existing YTick are used, OR
- % [min(y), t1, t2, t3, max(y)], use exactly these
- %
- % example:
- % xy = randn(100,2);
- % mmx = [min(xy(:,1)), max(xy(:,1))];
- % mmy = [min(xy(:,2)), max(xy(:,2))];
- % scatter(xy(:,1), xy(:,2));
- % tufteaxis(mmx, mmy);
- %
- % note:
- % the current implementation should be robust against the commands:
- % xlim
- % ylim
- % pbaspect
- % daspect
- %
- % using tricks from:
- % http://www.mathworks.de/matlabcentral/fileexchange/43905-kozak-scatterplot
- % http://undocumentedmatlab.com/blog/setting-axes-tick-labels-format/
- %
- % Stefan Harmeling * 2014-02-05
- % (0) remove existing tufte axis
- %tag = sprintf('%d', gca); % old version working till 2014a
- % new version, adding a random tag instead of the handle tag.
- tag = get(gca,'Tag');
- if strcmp(tag,'')
- tag = sprintf('%d',rand);
- else
- set(gca,'Tag','');
- delete(findall(gcf, 'Tag', tag))
- setappdata(gca, 'XLimListener', []);
- setappdata(gca, 'YLimListener', []);
- setappdata(gca, 'PositionListener', []);
- setappdata(gca, 'PlotBoxAspectRatioModeListener', []);
- setappdata(gca, 'PlotBoxAspectRatioListener', []);
- setappdata(gca, 'DataAspectRatioModeListener', []);
- setappdata(gca, 'DataAspectRatioListener', []);
- tag = sprintf('%d',rand);
- end
- set(gca,'Tag',tag);
- % (0a) sort input
- mmx = sort(mmx);
- mmy = sort(mmy);
- % (1) modify the current ticks
- if length(mmx) > 2
- XTick = get(gca, 'XTick'); % start with the current
- %XTick = mmx; % take the ticks from mmx
- offx = (mmx(end)-mmx(1))./10;
- for i = 1:length(mmx)
- % remove to crowded ticks
- XTick(XTick >= mmx(i) - offx & XTick <= mmx(i) + offx) = [];
- end
- XTick(XTick<mmx(1)) = [];
- XTick(XTick>mmx(end)) = [];
- XTick = [XTick,mmx];
- XTick = sort(XTick);
- mmx = [mmx(1), mmx(end)];
- else
- XTick = get(gca, 'XTick'); % start with the current
- if length(XTick) > 1
- offx = mean(diff(XTick))/2;
- else
- offx = 0;
- end % avoid crowded ticks
- XTick(XTick <= mmx(1) + offx) = []; % remove ticks that are smaller than min+off
- XTick(XTick >= mmx(2) - offx) = []; % remove ticks that are large than max-off
- XTick = [mmx(1), XTick, mmx(2)]; % add min and max
- end
- if length(mmy) > 2
- XTick = get(gca, 'YTick'); % start with the current
- %YTick = mmy;
- offy = (mmy(end)-mmy(1))./10;
- for i = 1:length(mmy)
- % remove to crowded ticks
- YTick(YTick >= mmy(i) - offy & YTick <= mmy(i) + offy) = [];
- end
- YTick(YTick<mmx(1)) = [];
- YTick(YTick>mmx(end)) = [];
- YTick = [YTick,mmy];
- YTick = sort(YTick);
- mmy = [mmy(1), mmy(end)];
- else
- YTick = get(gca, 'YTick');
- if length(YTick) > 1
- offy = mean(diff(YTick))/2;
- else
- offy = 0;
- end
- YTick(YTick <= mmy(1) + offy) = []; % remove ticks that are smaller than min+off
- YTick(YTick >= mmy(2) - offy) = []; % remove ticks that are large than max-off
- YTick = [mmy(1), YTick, mmy(2)]; % add min and max
- end
- % (2) switch off the current axis and add some new white background
- switch 1
- case 0
- % for debugging purposes: check whether the new axis align with the original ones
- case 1
- %% IN THIS SETTING ALSO THE WHITE AREA BELOW THE AXIS DISAPPEARS
- axis off % switch off the axis
- case 2
- %% WARNING THIS CASE LEADS TO GHOSTS IN PRINTOUTS
- box off % no box
- grid off % no grid
- set(gca, 'XTick', XTick); % change the ticks
- set(gca, 'YTick', YTick);
- set(gca, 'TickDir', 'out'); % the ticks should point out, otherwise we can not hide them
- Color = get(gcf, 'Color'); % get background color of the figure
- set(gca, 'XColor', Color); % hide the ticks and the axis
- set(gca, 'YColor', Color);
- end
- % (4) create conversion functions
- XLim = get(gca, 'XLim'); % get the coordinate system
- YLim = get(gca, 'YLim'); % get the coordinate system
- XLim = [min(mmx(1), XLim(1)), max(mmx(2), XLim(2))]; % increase limits if necessary
- YLim = [min(mmy(1), YLim(1)), max(mmy(2), YLim(2))]; % increase limits if necessary
- if strcmp(get(gca,'XScale'), 'linear')
- XLim(1) = min(XLim(1), mmx(1) - 0.1*(mmx(2)-mmx(1))); % to avoid points on the axis
- else %logspace
- XLim(1) = min(XLim(1), exp(log(mmx(1)) - 0.1*(log(mmx(2))-log(mmx(1)))));
- end
- if strcmp(get(gca,'YScale'), 'linear')
- YLim(1) = min(YLim(1), mmy(1) - 0.1*(mmy(2)-mmy(1))); % to avoid points on the axis
- else
- YLim(1) = min(YLim(1), exp(log(mmy(1)) - 0.1*(log(mmy(2))-log(mmy(1)))));
- end
- set(gca, 'XLim', XLim);
- set(gca, 'YLim', YLim);
- [left, bottom, width, height] = calcLimits(gca);
- if strcmp(get(gca,'XScale'), 'linear')
- tx = @(x) left + width * (x - XLim(1)) / diff(XLim); % convert to global position
- else % logscale
- tx = @(x) left + width * (log(x) - log(XLim(1))) / diff(log(XLim)); % convert to global position
- end
- if strcmp(get(gca,'YScale'), 'linear')
- ty = @(y) bottom + height * (y - YLim(1)) / diff(YLim); % convert to global position
- else % logscale
- ty = @(y) bottom + height * (log(y) - log(YLim(1))) / diff(log(YLim)); % convert to global position
- end
- % (5) draw new axis
- ax = annotation('line', tx(mmx), bottom*[1,1]); % x coordinate axis
- ay = annotation('line', left*[1,1], ty(mmy)); % y coordinate axis
- % (6) draw new ticks
- gcfpos = get(gcf, 'Position');
- ticklength = 7; % in pixel
- xticklength = ticklength / gcfpos(4); % in pixel / "number of vertical pixels"
- yticklength = ticklength / gcfpos(3); % in pixel / "number of horizontal pixels"
- nXTick = length(XTick);
- ttx = zeros(nXTick, 1); % to store ticks
- tlx = zeros(nXTick, 1); % to store labels
- for i = 1:nXTick
- ttx(i) = annotation('line', tx(XTick(i)*[1,1]), bottom-[0, xticklength]);
- tlx(i) = annotation('textbox', [tx(XTick(i)), bottom-xticklength, 0, 0], ...
- 'string', num2str(XTick(i),'%.3g'), ...
- 'VerticalAlignment', 'top', ...
- 'HorizontalAlignment', 'center', ...
- 'EdgeColor', 'none',...
- 'FontSize',get(gca,'FontSize'));
- end
- nYTick = length(YTick);
- tty = zeros(nYTick, 1); % to store ticks
- tly = zeros(nYTick, 1); % to store labels
- for i = 1:length(YTick)
- tty(i) = annotation('line', left-[0, yticklength], ty(YTick(i)*[1,1]));
- tly(i) = annotation('textbox', [left-yticklength, ty(YTick(i)), 0, 0], ...
- 'string', num2str(YTick(i),'%.3g'), ...
- 'VerticalAlignment', 'middle', ...
- 'HorizontalAlignment', 'right', ...
- 'EdgeColor', 'none',...
- 'FontSize',get(gca,'FontSize'));
- end
- for h = [ax; ttx(:); tlx(:); ay; tty(:); tly(:)]'
- set(h, 'Tag', tag); % mark the annotations to find them on our next
- % call using axis specific tag should make
- % this compatible with SUBPLOT
- end
- % (7) and now some magic tricks (to auto update the axis after
- % changing parameters via XLIM, YLIM, DASPECT, PBASPECT)
- hhAxes = handle(gca); % gca is the Matlab handle of our axes
- hProp = findprop(hhAxes,'XLim'); % a schema.prop object
- hListener = handle.listener(hhAxes, hProp, 'PropertyPostSet', @updateAxis);
- setappdata(gca, 'XLimListener', hListener);
- hProp = findprop(hhAxes,'YLim'); % a schema.prop object
- hListener = handle.listener(hhAxes, hProp, 'PropertyPostSet', @updateAxis);
- setappdata(gca, 'YLimListener', hListener);
- hProp = findprop(hhAxes,'Position'); % a schema.prop object
- hListener = handle.listener(hhAxes, hProp, 'PropertyPostSet', @updateAxis);
- setappdata(gca, 'PositionListener', hListener);
- hProp = findprop(hhAxes,'PlotBoxAspectRatioMode'); % a schema.prop object
- hListener = handle.listener(hhAxes, hProp, 'PropertyPostSet', @updateAxis);
- setappdata(gca, 'PlotBoxAspectRatioModeListener', hListener);
- hProp = findprop(hhAxes,'PlotBoxAspectRatio'); % a schema.prop object
- hListener = handle.listener(hhAxes, hProp, 'PropertyPostSet', @updateAxis);
- setappdata(gca, 'PlotBoxAspectRatioListener', hListener);
- hProp = findprop(hhAxes,'DataAspectRatioMode'); % a schema.prop object
- hListener = handle.listener(hhAxes, hProp, 'PropertyPostSet', @updateAxis);
- setappdata(gca, 'DataAspectRatioModeListener', hListener);
- hProp = findprop(hhAxes,'DataAspectRatio'); % a schema.prop object
- hListener = handle.listener(hhAxes, hProp, 'PropertyPostSet', @updateAxis);
- setappdata(gca, 'DataAspectRatioListener', hListener);
- % (8) helper functions
- function [left, bottom, width, height] = calcLimits(axisHandle)
- % calculate the correct positions of the axes depending on
- % 'Position'
- % 'PlotBoxAspectRatioMode', 'PlotBoxAspectRatio'
- % 'DataAspectRatioMode', 'DataAspectRatio'
- % 'CameraViewAngleMode', 'CameraViewAngle'
- OrigUnits = get(gcf, 'Units');
- set(gcf, 'Units', 'pixels');
- fpos = get(gcf, 'Position'); % left, bottom, width, height
- factor = fpos(3)/fpos(4); % ratio between width and height
- set(gcf, 'Units', OrigUnits);
- pos = get(axisHandle, 'Position');
- left = pos(1); bottom = pos(2); width = pos(3); height = pos(4);
- if strcmp(get(gca, 'PlotBoxAspectRatioMode'), 'manual') || strcmp(get(gca, 'DataAspectRatioMode'), 'manual')
- % PlotBoxAspectRatio influences the exact position
- % curiously for DataAspectRatioMode the following also works
- pbar = pbaspect();
- pbar12 = pbar(1)/pbar(2)/factor;
- wh = width/height;
- if pbar12 < wh
- % adjust left and width
- widthnew = height * pbar12;
- left = left + width/2 - widthnew/2;
- width = widthnew;
- elseif pbar12 > wh
- % adjust bottom and height
- heightnew = width / pbar12;
- bottom = bottom + height/2 - heightnew/2;
- height = heightnew;
- end
- end
- if strcmp(get(gca, 'CameraViewAngleMode'), 'manual')
- error('manual CameraViewAngleMode not support yet')
- end
- end
- function updateAxis(hProp,eventData)
- XLim = get(eventData.AffectedObject, 'XLim'); % get the coordinate system
- YLim = get(eventData.AffectedObject, 'YLim'); % get the coordinate system
- [left, bottom, width, height] = calcLimits(eventData.AffectedObject);
- if strcmp(get(eventData.AffectedObject,'XScale'), 'linear')
- tx = @(x) left + width * (x - XLim(1)) / diff(XLim); % convert to global position
- else % logscale
- tx = @(x) left + width * (log(x) - log(XLim(1))) / diff(log(XLim)); % convert to global position
- end
- if strcmp(get(eventData.AffectedObject,'YScale'), 'linear')
- ty = @(y) bottom + height * (y - YLim(1)) / diff(YLim); % convert to global position
- else % logscale
- ty = @(y) bottom + height * (log(y) - log(YLim(1))) / diff(log(YLim)); % convert to global position
- end
- set(ax, 'X', max(min(tx(mmx), left+width), left));
- set(ax, 'Y', bottom*[1,1]);
- for i = 1:nXTick
- XTicki = XTick(i);
- if XTicki < XLim(1) || XLim(2) < XTicki
- set(ttx(i), 'Visible', 'off');
- set(tlx(i), 'Visible', 'off');
- else
- set(ttx(i), 'Visible', 'on');
- set(tlx(i), 'Visible', 'on');
- thex = tx(XTicki);
- set(ttx(i), 'X', thex*[1,1]);
- set(ttx(i), 'Y', bottom-[0,xticklength]);
- tlxPos = get(tlx(i), 'Position');
- tlxPos(1) = thex;
- tlxPos(2) = bottom-xticklength;
- set(tlx(i), 'Position', tlxPos);
- end
- end
- set(ay, 'X', left*[1,1]);
- set(ay, 'Y', max(min(ty(mmy), bottom+height), bottom));
- for i = 1:nYTick
- YTicki = YTick(i);
- if YTicki < YLim(1) || YLim(2) < YTicki
- set(tty(i), 'Visible', 'off');
- set(tly(i), 'Visible', 'off');
- else
- set(tty(i), 'Visible', 'on');
- set(tly(i), 'Visible', 'on');
- they = ty(YTicki);
- set(tty(i), 'X', left-[0,yticklength]);
- set(tty(i), 'Y', they*[1,1]);
- tlyPos = get(tly(i), 'Position');
- tlyPos(1) = left-yticklength;
- tlyPos(2) = they;
- set(tly(i), 'Position', tlyPos);
- end
- end
- end
- end
tufteaxis.m at commit 5f7241f, under GPL-3.0 · at the source
Overview
- Department of Brain and Cognitive Sciences, University of Rochester, Meliora Hall, Rochester, NY 14627, USA
- Center for Visual Science, University of Rochester, 361 Meliora Hall, Rochester, NY 14627, USA
- Department of Neuroscience, University of Rochester, 601 Elmwood Avenue, Rochester, NY 14642, USA
Abstract
The abstract is not reproduced here: the paper's license (CC BY-NC-ND) does not allow it. Read it in the paper, at the publisher or on Europe PMC.
Repository
Its files are read in the Code ↔ Paper reader above, with 2 matches between paragraphs and lines of code.
wichmann-lab/psignifit
5f7241f6288c7dd3e1b34353118ca919ad28e51b, 4 January 2025Availability: 1 check, the latest on 30 September 2026: the link answers
- 30 September 2026: the link answers
59 files
- PsignifitLegacyOptionsCo
nverter.m , MATLAB, 287 lines - biasAna.m, MATLAB, 107 lines
- demo_001.m, MATLAB, 117 lines
- demo_002.m, MATLAB, 290 lines
- demo_003.m, MATLAB, 79 lines
- demo_004.m, MATLAB, 261 lines, 1 match
- demo_005.m, MATLAB, 116 lines
- demo_006.m, MATLAB, 306 lines
- demo_007.m, MATLAB, 72 lines
- demo_008.m, MATLAB, 486 lines
- generateTests.m, MATLAB, 36 lines
- getConfRegion.m, MATLAB, 138 lines
- getCor.m, MATLAB, 11 lines
- getDeviance.m, MATLAB, 39 lines
- getInformationCriteria.m
, MATLAB, 97 lines - getSlope.m, MATLAB, 81 lines
- getSlopeMarginal.m, MATLAB, 71 lines
- getSlopePC.m, MATLAB, 103 lines
- getStandardParameters.m, MATLAB, 84 lines
- getStandardPriors.m, MATLAB, 46 lines
- getThreshold.m, MATLAB, 168 lines
- marginalize.m, MATLAB, 61 lines
- plot2D.m, MATLAB, 108 lines
- plotBayes.m, MATLAB, 117 lines
- plotMarginal.m, MATLAB, 127 lines
- plotPosteriorScatter.m, MATLAB, 80 lines
- plotPrior.m, MATLAB, 229 lines
- plotPsych.m, MATLAB, 176 lines
- plotsModelfit.m, MATLAB, 96 lines
- private/
checkPriors.m , MATLAB, 76 lines - private/
getColormap.m , MATLAB, 18 lines - private/
getCov.m , MATLAB, 48 lines - private/
getSeed.m , MATLAB, 60 lines - private/
getSigmoidHandle.m , MATLAB, 94 lines - private/
getSigmoidValue.m , MATLAB, 15 lines - private/
getWeights.m , MATLAB, 36 lines - private/
gridSetting.m , MATLAB, 119 lines - private/
likelihood.m , MATLAB, 17 lines - private/
logLikelihood.m , MATLAB, 203 lines - private/
moveBorders.m , MATLAB, 98 lines - private/
my_betapdf.m , MATLAB, 44 lines - private/
my_normcdf.m , MATLAB, 20 lines - private/
my_norminv.m , MATLAB, 16 lines - private/
my_normpdf.m , MATLAB, 6 lines - private/
my_t1cdf.m , MATLAB, 13 lines - private/
my_t1icdf.m , MATLAB, 11 lines - private/
normalizePriors.m , MATLAB, 26 lines - private/
poolData.m , MATLAB, 51 lines - private/
psignifitCore.m , MATLAB, 129 lines - private/
setBorders.m , MATLAB, 48 lines - private/
strToDim.m , MATLAB, 16 lines - private/
tufteaxis.m , MATLAB, 309 lines, 1 match - private/
tufteaxisdemo.m , MATLAB, 6 lines - psignifit.m, MATLAB, 299 lines
- psignifitFast.m, MATLAB, 19 lines
- simulate_data.m, MATLAB, 328 lines
- tests/
testConsistency.m , MATLAB, 66 lines - LICENSE, License, 674 lines
- README.md, Text, 21 lines
The paper's code and data availability statement is in the Data section.
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Data
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Code and data availability statement
The paper has a code and data availability statement. Its license (CC BY-NC-ND) does not allow reproducing it here; in short, from what the harvester recognized in it:
- it points to a dataset: OSF e9k6q
- it says that the data are available on request
- it says that the code is available on request
Read it in the paper: doi.org/10.1016/j.isci.2026.115168.
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Version 1, 30 September 2026: the first record
Recorded: type, language, journal, volume, issue, pages, dates, 3 authors, 2 keywords, 2 funders, 87 references.
Cite
This paper
Clark, A. M., Prahalad, K. S., & Poletti, M. (2026). Distinct eccentricity-driven dynamics in foveal and extrafoveal visual crowding. iScience, 29(4), 115168. https://
BibTeX
@article{clark2026distin
author = {Clark, Ashley M and Prahalad, Krishnamachari S and Poletti, Martina},
title = {{Distinct eccentricity-driven dynamics in foveal and extrafoveal visual crowding}},
journal = {iScience},
year = {2026},
month = mar,
volume = {29},
number = {4},
pages = {115168},
publisher = {Elsevier},
issn = {2589-0042},
doi = {10.1016/
url = {https://
pmid = {41858623},
pmcid = {PMC12995875}
}
RIS
TY - JOUR
AU - Clark, Ashley M
AU - Prahalad, Krishnamachari S
AU - Poletti, Martina
TI - Distinct eccentricity-driven dynamics in foveal and extrafoveal visual crowding
T2 - iScience
J2 - iScience
PY - 2026
DA - 2026/
VL - 29
IS - 4
SP - 115168
SN - 2589-0042
PB - Elsevier
DO - 10.1016/
UR - https://
LA - en
ER -
CSL-JSON
{
"id": "10.1016/
"type": "article-journal",
"title": "Distinct eccentricity-driven dynamics in foveal and extrafoveal visual crowding",
"container-title": "iScience",
"author": [
{
"family": "Clark",
"given": "Ashley M"
},
{
"family": "Prahalad",
"given": "Krishnamachari S"
},
{
"family": "Poletti",
"given": "Martina"
}
],
"container-title-short":
"volume": "29",
"issue": "4",
"page": "115168",
"DOI": "10.1016/
"PMID": "41858623",
"PMCID": "PMC12995875",
"ISSN": "2589-0042",
"publisher": "Elsevier",
"URL": "https://
"language": "en",
"issued": {
"date-parts": [
[
2026,
3,
2
]
]
}
}
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