Merge remote-tracking branch 'origin/feature-stopSaccadeEating'

Author: dcnieho

functions/I2MC/I2MCfunc.m

@@ -34,6 +34,7 @@
 par.maxerrors       = 100;      % maximum number of errors allowed in k-means clustering procedure before proceeding to next file
 % FIXATION DETERMINATION
 par.cutoffstd       = 2;        % number of standard deviations above mean k-means weights will be used as fixation cutoff
+par.onoffsetThresh  = 3;        % number of MAD away from median fixation duration. Will be used to walk forward at fixation starts and backward at fixation ends to refine their placement and stop algorithm from eating into saccades
 par.maxMergeDist    = 30;       % maximum Euclidean distance in pixels between fixations for merging
 par.maxMergeTime    = 30;       % maximum time in ms between fixations for merging
 par.minFixDur       = 40;       % minimum fixation duration (ms) after merging, fixations with shorter duration are removed from output
@@ -51,7 +52,7 @@
     end
     value = varargin{p+1};
     switch key
-        case {'xres','yres','freq','missingx','missingy','disttoscreen','windowtimeInterp','maxdisp','windowtime','steptime','cutoffstd','maxMergeDist','maxMergeTime','minFixDur'}
+        case {'xres','yres','freq','missingx','missingy','disttoscreen','windowtimeInterp','maxdisp','windowtime','steptime','cutoffstd','onoffsetThresh','maxMergeDist','maxMergeTime','minFixDur'}
             checkNumeric(value,key);
             checkScalar(value,key);
             par.(key) = value;
@@ -195,6 +196,6 @@
 
 %% DETERMINE FIXATIONS BASED ON FINALWEIGHTS_AVG
 fprintf('Determining fixations based on clustering weight mean for averaged signal and separate eyes + 2*std \n')
-[fix.cutoff,fix.start,fix.end,fix.startT,fix.endT,fix.dur,fix.xpos,fix.ypos,fix.flankdataloss,fix.fracinterped] = getFixations(data.finalweights,data.time,xpos,ypos,missing,par.cutoffstd,par.maxMergeDist,par.maxMergeTime,par.minFixDur);
+[fix.cutoff,fix.start,fix.end,fix.startT,fix.endT,fix.dur,fix.xpos,fix.ypos,fix.flankdataloss,fix.fracinterped] = getFixations(data.finalweights,data.time,xpos,ypos,missing,par.cutoffstd,par.onoffsetThresh,par.maxMergeDist,par.maxMergeTime,par.minFixDur);
 [fix.RMSxy,fix.BCEA,fix.fixRangeX,fix.fixRangeY] = getFixStats(xpos,ypos,missing,fix.start,fix.end,pixperdeg);
 

functions/I2MC/getFixations.m

@@ -1,4 +1,4 @@
-function [cutoff,fixstart,fixend,starttime,endtime,fixdur,xmedian,ymedian,flankdataloss,fracinterped] = getFixations(finalweights,timestamp,xpos,ypos,missing,cutoffstd,maxMergeDist,maxMergeTime,minFixDur)
+function [cutoff,fixstart,fixend,starttime,endtime,fixdur,xmedian,ymedian,flankdataloss,fracinterped] = getFixations(finalweights,timestamp,xpos,ypos,missing,cutoffstd,onoffsetThresh,maxMergeDist,maxMergeTime,minFixDur)
 % determine fixations based on finalweights from 2-means clustering
 
 % Roy Hessels - 2014
@@ -12,6 +12,8 @@
 %                             missing (originally, before interpolation!)
 % cutoffstd                 = number of std above mean clustering-weight to
 %                               use as fixation cutoff
+% onoffsetThresh            = threshold (x*MAD of fixation) for walking 
+%                               forward/back for saccade off- and onsets
 % maxMergeDist              = maximum Euclidean distance in pixels between fixations for merging
 % maxMergeTime              = maximum time in ms between fixations for merging
 
@@ -43,6 +45,40 @@
 % get indices of where fixations start and end
 [fixstart,fixend] = bool2bounds(fixbool);
 
+% for each fixation start, walk forward until recorded position is below a
+% threshold of lambda*MAD away from median fixation position.
+% same for each fixation end, but walk backward
+for p=1:length(fixstart)
+    xmedThis = median(xpos(fixstart(p):fixend(p)));
+    ymedThis = median(ypos(fixstart(p):fixend(p)));
+    % MAD = median(abs(x_i-median({x}))). For the 2D version, I'm using
+    % median 2D distance of a point from the median fixation position. Not
+    % exactly MAD, but makes more sense to me for 2D than city block,
+    % especially given that we use 2D distance in our walk here
+    MAD = median(hypot(xpos(fixstart(p):fixend(p))-xmedThis, ypos(fixstart(p):fixend(p))-ymedThis));
+    
+    thresh = MAD*onoffsetThresh;
+    
+    % walk until distance less than threshold away from median fixation
+    % position. No walking occurs when we're already below threshold.
+    i = fixstart(p);
+    if i>1  % don't walk when fixation starting at start of data
+        while hypot(xpos(i)-xmedThis,ypos(i)-ymedThis)>thresh
+            i = i+1;
+        end
+        fixstart(p) = i;
+    end
+    
+    % and now fixation end.
+    i = fixend(p);
+    if i<length(xpos)   % don't walk when fixation ending at end of data
+        while hypot(xpos(i)-xmedThis,ypos(i)-ymedThis)>thresh
+            i = i-1;
+        end
+        fixend(p) = i;
+    end
+end
+
 % get start time, end time, and fix duration
 starttime   = timestamp(fixstart);
 endtime     = timestamp(fixend);