Remove kymo language

readme.md

@@ -54,7 +54,7 @@ To create a new synethetic dataset:
     - phantomVelocity_mu: the different mean velocity values per class i.e., the number of means determines the number of classes.
     - phantomVelocity_sigma: the standard deviation for velocity per class.
     - numOutput: how many phantom images to generate per class.
-2. Run phantomVelocitySS\goFigure.m, specifying the saved .mat file as the input.
+2. Run phantomVelocitySSF\goFigure.m, specifying the saved .mat file as the input.
 
 ## Notes
 1. The NCD code uses the [FLIF](https://flif.info/) compression library. The thunker file for the FLIF library was generated on Ubuntu 22.04 and **may not work** on other Unix platforms.  

src/MATLAB/phantomKymograph/createPhantom.m

-function phantomKymo = createPhantom(phSize,phTracks,phVel_mu,phVel_sigma)
+function phantomVelcocityOutput = createPhantom(phSize,phTracks,phVel_mu,phVel_sigma)
 
 tmp = zeros(phSize,'uint8');
 
@@ -39,6 +39,6 @@ for i = 1:length(trackSrcPts)
 
 end
 
-phantomKymo = tmp;
+phantomVelcocityOutput = tmp;
 
 end
\ No newline at end of file

src/MATLAB/phantomKymograph/createSyntheticDataset.m

@@ -10,7 +10,7 @@ for i = 1:length(datasetParameters.phantomVelocity_mu)
     phVel_mu = datasetParameters.phantomVelocity_mu(i);
     phVel_sigma = datasetParameters.phantomVelocity_sigma(i);
 
-    for j = 1:datasetParameters.numKymos
+    for j = 1:datasetParameters.numOutput
 
         tmp = [];
         tmp.phantomName = strcat(num2str(i),'_',num2str(j));
@@ -19,7 +19,7 @@ for i = 1:length(datasetParameters.phantomVelocity_mu)
         tmp.phantomSize = phSize;
         tmp.numTracks = phTracks;
         tmp.phantomVelocity = [phVel_mu;phVel_sigma];
-        tmp.phantomKymo = createPhantom(phSize,phTracks,phVel_mu,phVel_sigma);
+        tmp.phantomVelocityOutput = createPhantom(phSize,phTracks,phVel_mu,phVel_sigma);
 
         syntheticDataset = [syntheticDataset;tmp];
 

src/MATLAB/phantomKymograph/getPhantomClipLimits.m

 function clipLimits = getPhantomClipLimits(syntheticDataset,targetChannel)
 
 for ff = 1:length(syntheticDataset)
-    im_ff = syntheticDataset(ff).phantomKymo(:,:,:,targetChannel);
+    im_ff = syntheticDataset(ff).phantomVelocityOutput(:,:,:,targetChannel);
     
     kp = im_ff(find(im_ff));
 

src/MATLAB/phantomKymograph/goFigure.m

@@ -2,9 +2,9 @@ load('sampleDataset_01.mat');
 
 K = 3;
 
-tmp_xy(:,:,1) = squeeze(max(syntheticDataset(1).phantomKymo(:,:,:,1),[],2));
-tmp_xy(:,:,2) = squeeze(max(syntheticDataset(11).phantomKymo(:,:,:,1),[],2));
-tmp_xy(:,:,3) = squeeze(max(syntheticDataset(21).phantomKymo(:,:,:,1),[],2));
+tmp_xy(:,:,1) = squeeze(max(syntheticDataset(1).phantomVelocityOutput(:,:,:,1),[],2));
+tmp_xy(:,:,2) = squeeze(max(syntheticDataset(11).phantomVelocityOutput(:,:,:,1),[],2));
+tmp_xy(:,:,3) = squeeze(max(syntheticDataset(21).phantomVelocityOutput(:,:,:,1),[],2));
 
 figure('Position',[300,200,900,300]);
 layout1 = tiledlayout(1,3,'TileSpacing','compact','Padding','tight');

src/MATLAB/phantomKymograph/goSyntheticDataset.m

@@ -6,7 +6,7 @@ synthDatasetParameters.phantomSize = [200,200,25];
 synthDatasetParameters.phantomTracks = 10;
 synthDatasetParameters.phantomVelocity_mu = [1,3,5];
 synthDatasetParameters.phantomVelocity_sigma = [.5,.5,.5];
-synthDatasetParameters.numKymos = 50;
+synthDatasetParameters.numOutput = 50;
 
 syntheticDataset = createSyntheticDataset(synthDatasetParameters);
 

src/MATLAB/phantomKymograph/goSyntheticSSF.m

@@ -21,14 +21,14 @@ parfor i=1:H
             continue
         end
 
-        im_ff = syntheticDataset(ff).phantomKymo(:,:,:,targetChannel);
+        im_ff = syntheticDataset(ff).phantomVelocityOutput(:,:,:,targetChannel);
 
         if ff == gg
             d1 = SSF.ncd_ssf_volume(im_ff,im_ff);
             dxx(i,j) = d1;
         else
-            im_ff = syntheticDataset(ff).phantomKymo(:,:,:,targetChannel);
-            im_gg = syntheticDataset(gg).phantomKymo(:,:,:,targetChannel);
+            im_ff = syntheticDataset(ff).phantomVelocityOutput(:,:,:,targetChannel);
+            im_gg = syntheticDataset(gg).phantomVelocityOutput(:,:,:,targetChannel);
 
             d1 = SSF.ncd_ssf_volume(im_ff,im_gg);
             d2 = SSF.ncd_ssf_volume(im_gg,im_ff);