diff --git a/.gitignore b/.gitignore
index 237de09242727825c182d3cb3e1d799a904c25ce..430120a229a113fe54a8b1711706b97707fded24 100644
--- a/.gitignore
+++ b/.gitignore
@@ -66,3 +66,4 @@ Python/build/*
**/src/Python/build/*
leversc/src/Python/dist/*
matlab/Yannick_oracle/001.png
+!matlab/cacheReferenceLoG.mat
\ No newline at end of file
diff --git a/elever/main.js b/elever/main.js
index 3a93b5aade3a40d37e7d9eaf544a18e89dd02c72..ef57995d73f699f14a9f2c1c25efc11f7f36059b 100644
--- a/elever/main.js
+++ b/elever/main.js
@@ -5,7 +5,6 @@ const app = electron.app
// Module to create native browser window.
const BrowserWindow = electron.BrowserWindow
-
const path = require('path')
const url = require('url')
const {ipcMain} = require('electron');
@@ -24,7 +23,9 @@ function createWindow ()
// Create the browser window.
mainWindow = new BrowserWindow({width: 800, height: 600, icon:path.join(__dirname,'..','leverjs/leverjs.ico'),
webPreferences: {
- nodeIntegration: true
+ nodeIntegration: true,
+ contextIsolation: false,
+ enableRemoteModule: true
}
});
diff --git a/leverjs/ImageWindowBuilder.js b/leverjs/ImageWindowBuilder.js
index e71de6acbb6793f4b305087f683cfba53e25837d..2c9cf23767bde48a14b6f0323001cf42f86edeb2 100644
--- a/leverjs/ImageWindowBuilder.js
+++ b/leverjs/ImageWindowBuilder.js
@@ -41,7 +41,8 @@ var miniMapmousedrag = false;
// database is read only
var gbReadOnlyDB=false;
-const IS_NODE = typeof module !== 'undefined' && module.exports;
+// const IS_NODE = typeof module !== 'undefined' && module.exports;
+var IS_NODE = navigator.userAgent.indexOf('Electron') >= 0
// set to tell render.js (reDraw) not to kick off a multires if we're in the experiment window
var gbExperimentRender=false;
@@ -144,6 +145,8 @@ function setLeverscUI()
document.getElementById('sbtabAlgorithms').style.display='none';
document.getElementById('sbtabWrangle').style.display='none';
document.getElementById('playPause').style.display='none';
+ document.getElementById('toolbarClip').style.display="";
+
sbtabClick('View');
}
// Runs when the window is first open
@@ -169,7 +172,7 @@ window.onload = function () {
ROOT=params[1].slice('ROOT='.length)
title=params[2].slice('TITLE='.length)
- console.log('lever figure window found :: port='+port+" :: root="+root)
+ console.log('lever figure window found :: port='+port+" :: root="+ROOT)
uiServer.init(port,window)
document.title='leversc '+title
setLeverscUI()
diff --git a/leverjs/uiServer.js b/leverjs/uiServer.js
index 036218d703079b1e56e25988c23eaa16e4f10e2d..74e81027a7a4c6bdc07f71ff81c2f9090be07a4f 100644
--- a/leverjs/uiServer.js
+++ b/leverjs/uiServer.js
@@ -77,7 +77,6 @@ app.post('/loadfig', fig_upload, function (req, res)
cx.renderParams=gWindow.gRenderParams;
gWindow.CONSTANTS=cx;
gWindow.initWebGL();
- gWindow.setToolUI(cx);
gWindow.UpdateTime();
gWindow.populateViewTab();
});
@@ -223,8 +222,9 @@ app.get('/uiParams', function (req, res) {
var logoDiv=gWindow.document.getElementById('logoDiv');
var clockButton=gWindow.document.getElementById('clockButton');
var time=document.getElementById('imageTimeDiv').innerHTML;
+ var scalebar = gWindow.gbScalebar;
var ui={sidebar:sidebar.style.display,webToolbar:webToolbar.children[1].style.display,logoDiv:logoDiv.style.display,
- clockButton:clockButton.style.display,time:time};
+ clockButton:clockButton.style.display,time:time,scalebar:scalebar};
res.send(ui);
});
@@ -235,14 +235,17 @@ app.post('/uiParams', jsonParser,function (req, res) {
var logoDiv=gWindow.document.getElementById('logoDiv');
var lineageControls=gWindow.document.getElementById('divLineageControls');
+ if (gWindow.gbScalebar != ui.scalebar)
+ drawScalebar(true);
+
lineageControls.style.display=ui.webToolbar;
sidebar.style.display=ui.sidebar;
// webToolbar.style.display=ui.webToolbar;
logoDiv.style.display=ui.logoDiv;
for (var i=0;i<webToolbar.children.length;i++) {
- if (webToolbar.children[i].id=='clockButton')
- continue;
+ // if (webToolbar.children[i].id=='clockButton')
+ // continue;
webToolbar.children[i].style.display=ui.webToolbar;
}
document.getElementById('imageTimeDiv').innerHTML=ui.time;
diff --git a/leversc/src/MATLAB/@leversc/getProperty.m b/leversc/src/MATLAB/@leversc/getProperty.m
index 516afc64e3b3d3f9d4e4de64484544d3eaecb94e..094a36b9675c42bf347ece2572ebe64d6d11dfa8 100644
--- a/leversc/src/MATLAB/@leversc/getProperty.m
+++ b/leversc/src/MATLAB/@leversc/getProperty.m
@@ -1,5 +1,7 @@
function rval=getProperty(obj,propertyName)
+rval = [];
+
if isempty(obj.check_server())
return;
end
diff --git a/leversc/src/MATLAB/@leversc/leversc.m b/leversc/src/MATLAB/@leversc/leversc.m
index 35ed034c9eb5ccf9bf815a7c9882ac72089aefe9..73a002abf3a6bcba691c3a09746de4fc5178f51a 100644
--- a/leversc/src/MATLAB/@leversc/leversc.m
+++ b/leversc/src/MATLAB/@leversc/leversc.m
@@ -30,6 +30,7 @@ classdef leversc <handle
optional_figNumber=1;
end
[im,imD,figNumber]=parseArgs(optional_im,optional_imD,optional_figNumber);
+ im = imPad4(im);
obj.figNumber=figNumber;
if isfield(imD,'imageData')
CONSTANTS=imD;
@@ -122,3 +123,19 @@ end
end
+function im = imPad4(im)
+
+pad = [0,0,0];
+for d = 1:3
+ if 0~=mod(size(im,d),4)
+ pad(d) = size(im,d) + 4-mod(size(im,d),4);
+ end
+end
+if any(pad)
+ sz = size(im);
+ sz = sz(1:3);
+ pad = max(pad,sz);
+ im(pad(1),pad(2),pad(3),:) = 0;
+end
+
+end
\ No newline at end of file
diff --git a/leversc/src/MATLAB/@leversc/loadImage.m b/leversc/src/MATLAB/@leversc/loadImage.m
index 511a935ace771fcf7eee31644aa95ad947678b39..dbdde44d01af0e7195d22999188ab9cb0f00e8f7 100644
--- a/leversc/src/MATLAB/@leversc/loadImage.m
+++ b/leversc/src/MATLAB/@leversc/loadImage.m
@@ -16,7 +16,7 @@ sz(1)=sz(2);
sz(2)=temp;
sz(4)=length(channels);
sz(5)=length(time);
-targetFile=strrep(strDB,'.LEVER','.h5');
+targetFile=[fullfile(CONSTANTS.imageData.imageDir,CONSTANTS.imageData.DatasetName) '.h5'];
im=h5read(targetFile,'/Images/Original',[1,1,1,channels(1),time(1)],sz);
% im=mat2gray(im);
end
diff --git a/leversc/src/MATLAB/@leversc/show.m b/leversc/src/MATLAB/@leversc/show.m
index e6a01af93108cc582559f8e6e017a0793bcaf918..2ad1d3bec242fb393e668cc2f3708f2d0a6cd036 100644
--- a/leversc/src/MATLAB/@leversc/show.m
+++ b/leversc/src/MATLAB/@leversc/show.m
@@ -106,9 +106,19 @@ end
function launch_electron_posix(port,fignum,workdir, leverpath,strDB)
elec_cmd = 'leverjs';
+px = getenv('PATH');
if ( ~isempty(leverpath) )
- elec_path = fullfile(leverpath,'node_modules','.bin','electron');
- elec_cmd = [elec_path ' ' fullfile(leverpath,'elever','main.js')];
+ % first try NVM
+ nvm_path = getenv('NVM_DIR');
+ if ~isempty(nvm_path)
+ [ret,elec_path] = system('source ~/.nvm/nvm.sh;which electron');
+ elec_path = replace(elec_path,newline,'');
+ nodePath = fileparts(elec_path);
+ px = [px ':' nodePath];
+ else
+ elec_path = fullfile(leverpath,'node_modules','.bin','electron');
+ end
+ elec_cmd = [elec_path ' ' fullfile(leverpath,'elever','main.js')];
else
[status,~] = system(['which ' elec_cmd]);
if ( status ~= 0 )
@@ -118,8 +128,8 @@ end
if exist('strDB','var') && ~isempty(strDB)
elec_cmd = [elec_cmd ' --leverFile=' strDB ' '];
end
-cmd = [elec_cmd ' --port=' num2str(port) ' --title="figure ' num2str(fignum) '"' ' &'];
-system(cmd);
+cmd = [elec_cmd ' --port=' num2str(port) ' --title="figure ' num2str(fignum) '"' ' &']
+system(cmd,'PATH',px);
end
function launch_electron_windows(port,fignum,workdir, leverpath, strDB)
diff --git a/leversc/src/MATLAB/ssf_kymo.m b/leversc/src/MATLAB/ssf_kymo.m
new file mode 100644
index 0000000000000000000000000000000000000000..91f062504be7dc25d16f6138f69b9c424350211a
--- /dev/null
+++ b/leversc/src/MATLAB/ssf_kymo.m
@@ -0,0 +1,104 @@
+%
+function ssf_kymo(bPreview)
+
+lsc = leversc();
+
+ %% Disable most UI elements
+ lsc.uiParams.time='none';
+ lsc.uiParams.sidebar='none';
+ lsc.uiParams.clockButton='none';
+ lsc.uiParams.webToolbar='none';
+
+ %% Reset view parameters (also set background to black)
+ lsc.viewParams.clipMode = 0;
+ lsc.viewParams.worldRot = reshape([1,0,0,0; 0,1,0,0; 0,0,1,0; 0,0,0,1], 16,1);
+ lsc.viewParams.zoom = 0;
+ lsc.viewParams.bgColor = [0,0,0];
+
+ if ( ~bPreview )
+ movieFile='pos3_erk_ssf.avi';
+ vidWrite=VideoWriter(movieFile,'Motion JPEG AVI');
+ vidWrite.FrameRate=10;
+ open(vidWrite)
+ end
+
+% %% Quick zoom from 0 to 0.4 (1 sec = 10 frames)
+% zlevels = linspace(0,0.4, 10);
+% for i=1:length(zlevels)
+% lsc.viewParams.zoom=zlevels(i);
+%
+% imCap = get_rendered_frame(lsc);
+% if ( bPreview )
+% imagesc(imCap);
+% axis image;
+% drawnow();
+% else
+% writeVideo(vidWrite,imCap);
+% end
+% end
+%
+% % Padding for 0.2 sec
+% if ( ~bPreview )
+% writeVideo(vidWrite,imCap);
+% writeVideo(vidWrite,imCap);
+% end
+
+
+ %% Rotate 1/3 way around in 5sec
+ angles = linspace(0,360,200);
+ for i=2:length(angles)
+ ry=[cosd(angles(i)), 0, sind(angles(i)),0;
+ 0,1,0,0;
+ -sind(angles(i)),0,cosd(angles(i)),0;
+ 0,0,0,1];
+
+ worldRot=ry;
+ lsc.viewParams.worldRot=worldRot(:);
+
+ imCap = get_rendered_frame(lsc);
+ if ( bPreview )
+ imagesc(imCap);
+ axis image;
+ drawnow();
+ else
+ writeVideo(vidWrite,imCap);
+ end
+ end
+% % Padding for 0.2 sec
+% if ( ~bPreview )
+% writeVideo(vidWrite,imCap);
+% writeVideo(vidWrite,imCap);
+% end
+% angles = linspace(120,0,50);
+% for i=2:length(angles)
+% ry=[cosd(angles(i)), 0, sind(angles(i)),0;
+% 0,1,0,0;
+% -sind(angles(i)),0,cosd(angles(i)),0;
+% 0,0,0,1];
+%
+% worldRot=ry;
+% lsc.viewParams.worldRot=worldRot(:);
+%
+% imCap = get_rendered_frame(lsc);
+% if ( bPreview )
+% imagesc(imCap);
+% axis image;
+% drawnow();
+% else
+% writeVideo(vidWrite,imCap);
+% end
+% end
+
+ if ( ~bPreview )
+ close(vidWrite)
+ end
+end
+
+function im = get_rendered_frame(lsc)
+ % We need to poll for draw-complete in order to avoid timeouts
+ while ~lsc.drawComplete()
+ pause(0.1);
+ end
+ im=lsc.captureImage();
+end
+
diff --git a/matlab/+AutoParam/imRadius.m b/matlab/+AutoParam/imRadius.m
index 8b9cecba1ff986f901366ae226e8005ac619b61a..25164deae9003626ad741287b2f7951572925ab4 100644
--- a/matlab/+AutoParam/imRadius.m
+++ b/matlab/+AutoParam/imRadius.m
@@ -2,24 +2,32 @@ function [radius,area]=imRadius(im,CONSTANTS)
radius=[];
area=[];
-bwp=bwperim(im);
for i=1:max(im(:))
- rx=[];
- idx=find(im==i & bwp);
+ idx=find(im==i);
if isempty(idx)
continue
end
+ sz=CONSTANTS.imageData.PixelPhysicalSize;
if is3D(im)
- [r,c,z]=ind2sub(size(im),idx);
+ [r,c,z]=ind2sub(size(im),idx);
+ iRadius= (std([r,c,z])) .* sqrt(3);
else
[r,c]=ind2sub(size(im),idx);
- z=[];
+ iRadius = (std([r,c])) .* sqrt(2);
+ sz = sz(1:2);
end
- rx = getRadius(CONSTANTS,r,c,z);
- radius=[radius;median(rx)];
-
- idxArea=find(im==i);
- area=[area;length(idxArea)];
+ if any(r==1) || any(c==1) || any(r==size(im,1)) || any(c==size(im,2))
+ continue;
+ end
+ if is3D(im) && (any(z==1) || any(z==size(im,3)))
+ continue
+ end
+ iRadius = norm(iRadius .* sz);
+ if iRadius<1
+ 4;
+ end
+ radius=[radius;iRadius];
+ area=[area;length(idx)];
end
4;
diff --git a/matlab/+Batch/batchProc.m b/matlab/+Batch/batchProc.m
new file mode 100644
index 0000000000000000000000000000000000000000..a2ddcb3fbf776dcac79f64bdbe8184999aca1497
--- /dev/null
+++ b/matlab/+Batch/batchProc.m
@@ -0,0 +1,14 @@
+
+function batchProc(ROOT,nproc,nthread)
+
+ljsStartParallel(nproc);
+
+flist = dir(fullfile(ROOT,'*.LEVER'));
+parfor ff=1:length(flist)
+ strDB = fullfile(flist(ff).folder,flist(ff).name);
+ cmd = ['matlab -batch "Batch.processMovie(''' strDB ''',0,' num2str(nthread) ')"'];
+ tx = tic();
+ [s,o] = system(cmd)
+ tElapsed = toc(tx);
+ ljsLog(['fini process ' strDB ' : tElapsed = ' num2str(tElapsed,'%0.0f')],0);
+end
\ No newline at end of file
diff --git a/matlab/+Batch/buildCompositeCache.m b/matlab/+Batch/buildCompositeCache.m
index 970bb6710857de1ed244a5566cd28f07f12c5eac..7e1e74a3cfe693f87af9edfd970a331816e14f0f 100644
--- a/matlab/+Batch/buildCompositeCache.m
+++ b/matlab/+Batch/buildCompositeCache.m
@@ -1,7 +1,5 @@
% cache imLoG here -- keeps spmd procs from using CUDA and burning the
-% ~ 500MB per process CUDA vram overhead. We keep im while we're here
-% to cut down the disk read too. store in composite so we don't
-% duplicate memory on every client
+% ~ 500MB per process CUDA vram overhead.
function imCompCache=buildCompositeCache(imCompCache,commandList, ...
idxCommandList,segParams,CONSTANTS,medianMask,tExistingSeg)
@@ -9,33 +7,40 @@ if ~exist('imCompCache','var')
imCompCache=Composite();
end
-for ix=1:length(imCompCache)
- icc=[];
- if ix+idxCommandList>size(commandList,1)
- continue
+imWorkingCache = Composite();
+GPU_THREADS = 4;
+nPass = ceil(length(imCompCache) / GPU_THREADS);
+for n = 1 : nPass
+ spmd
+ if labindex<=GPU_THREADS
+ icc=[];
+ workerindex = labindex + (n-1)*GPU_THREADS;
+ if workerindex+idxCommandList<=size(commandList,1)
+ t=commandList(workerindex+idxCommandList,1);
+ icc.t=t;
+ end
+ if t<=0 || t>CONSTANTS.imageData.NumberOfFrames || ~isempty(intersect(t,tExistingSeg))
+ icc.im=[];
+ icc.imLoG=[];
+ icc.sp = [];
+ icc.imnChannel = [];
+ imWorkingCache =icc;
+ else
+ sp=segParams;
+ sp.minimumRadius_um=commandList(workerindex+idxCommandList,2);
+ % copy the previous compCache entry if the t's match so we don't reload
+ icc.im = DenoiseCache.readImages(t,CONSTANTS,sp,medianMask);
+ [icc.imLoG, ~, ~] = LoG.getCompositeLoG(icc.im,CONSTANTS,sp);
+ icc.caChannelLoG = Segment.getChannelLoG(CONSTANTS, t, segParams);
+ icc.minimumRadius_um = sp.minimumRadius_um;
+ imWorkingCache =icc;
+ end
+ end
end
- t=commandList(ix+idxCommandList,1);
- icc.t=t;
- if t<=0 || t>CONSTANTS.imageData.NumberOfFrames || ~isempty(intersect(t,tExistingSeg))
- icc.im=[];
- icc.imLoG=[];
- imCompCache{ix}=icc;
- continue
- end
- sp=segParams;
- sp.minimumRadius_um=commandList(ix+idxCommandList,2);
- % copy the previous compCache entry if the t's match so we don't reload
- if ix>1
- imM1=imCompCache{ix-1};
- else
- imM1.t=-1;
- end
- if imM1.t==t
- icc.im=imM1.im;
- else
- icc.im=DenoiseCache.readImages(t,CONSTANTS,sp,medianMask);
- end
- icc.imLoG=Segment.getLoG(icc.im,CONSTANTS,sp);
- imCompCache{ix}=icc;
+ % only use gpu on working cache, first GPU_THREADS procs
+ % then copy results to full cache. Only a few procs can touch GPU
+ % without killing vram
+ imCompCache( (n-1)*GPU_THREADS + 1 : n*GPU_THREADS) = imWorkingCache(1:GPU_THREADS);
end
-4;
\ No newline at end of file
+4;
+
diff --git a/matlab/+Batch/goProcess.m b/matlab/+Batch/goProcess.m
index 09e16dfbbc44718b0d9ec8037b6e56a9e1a2aecb..e933d62efbfee90708a079fe8fc5c946d39a5abf 100644
--- a/matlab/+Batch/goProcess.m
+++ b/matlab/+Batch/goProcess.m
@@ -6,13 +6,12 @@ end
if ~exist('bForceSegment','var')
bForceSegment=false;
end
-processInfo=[];
[~,~,ext]=fileparts(strDB);
if strcmp(ext,'.LEVER')
processInfo=Batch.processMovie(strDB,bForceSegment,nProcessors);
else
folderName=strDB;
- flist=dir(fullfile(folderName,'**/*.LEVER'));
+ flist=dir(fullfile(folderName,'*.LEVER'));
% denoise first - this keeps our cuda work separate. cuda charges a
% sick overhead for each process
targetFolder=unique({flist.folder});
@@ -20,7 +19,7 @@ else
DenoiseCache.denoiseFolder(targetFolder{tt});
end
for ff=1:length(flist)
- strDB=fullfile(flist(ff).folder,flist(ff).name);
- processInfo=[processInfo;Batch.processMovie(strDB,bForceSegment,nProcessors)];
+ strDB=fullfile(flist(ff).folder,flist(ff).name);
+ processInfo = Batch.processMovie(strDB,bForceSegment,nProcessors);
end
end
\ No newline at end of file
diff --git a/matlab/+Batch/processMovie.m b/matlab/+Batch/processMovie.m
index bcf947a33d920f08302b2c93ec08601f7e52ae51..8bbce04fe7dfb4215df267d69c2cc6739b83af35 100644
--- a/matlab/+Batch/processMovie.m
+++ b/matlab/+Batch/processMovie.m
@@ -48,7 +48,9 @@ Smooth.Patch.patchOcclusion(conn);
processInfo.tPatch=getElapsed(tx);
tx=tic();
-nMerged = Smooth.Merge.goMerge(conn,CONSTANTS,segParams,nProcessors);
+% nMerged = Smooth.Merge.goMerge(conn,CONSTANTS,segParams,nProcessors);
+% nMerged = Smooth.Merge.goMerge2(conn, CONSTANTS, segParams);
+nMerged = -1;
processInfo.tMerge=getElapsed(tx);
tx=tic();
@@ -57,7 +59,9 @@ Smooth.extFamily(conn);
processInfo.tClassify=getElapsed(tx);
tx=tic();
-Batch.batchFeatures(conn,CONSTANTS,nProcessors);
+% batch features needs LoG in every frame...clip # procs to placate cuda
+nBatchProcessors = min(nProcessors,12); %
+Batch.batchFeatures(conn,CONSTANTS,nBatchProcessors);
processInfo.tFeatures=getElapsed(tx);
processInfo.nMerged = nMerged;
@@ -74,6 +78,10 @@ ljsLog(sz,0);
close(conn)
+if batchStartupOptionUsed
+ quit(0,'force')
+end
+
function tElapsed=getElapsed(timerID)
tElapsed=toc(timerID);
tElapsed=round(tElapsed,2);
diff --git a/matlab/+CellFeatures/channelLoG.m b/matlab/+CellFeatures/channelLoG.m
index 343ee156baa5534744aee2f8d2896443e0d64a29..7db1f3217fa270daeebb7ba773a1a51d50054ccb 100644
--- a/matlab/+CellFeatures/channelLoG.m
+++ b/matlab/+CellFeatures/channelLoG.m
@@ -22,30 +22,44 @@ im = MicroscopeData.Reader('imageData',CONSTANTS.imageData, 'chanList',...
if all(isnan(im(:)))
return;
end
+im = Segment.denoise(im,segParams,false);
im=mat2gray(im);
-rCell = cellfun(@(x) std(x),{cellList.pts},'UniformOutput',false);
-rCell = median(vertcat(rCell{:}));
-rCell = mean(rCell);
-rCell_um = rCell .* CONSTANTS.imageData.PixelPhysicalSize(1);
-
-segParams.minimumRadius_um=rCell_um;
-imLoG = Segment.getLoG(im,CONSTANTS,segParams);
+imp = [];
+imn = []; % h2b wants imn
+if is3D(im)
+ rdim = 4;
+else
+ rdim = 3;
+end
-% keep only positive imLoG - e.g. darker blob against bright boundary
-% or bright blob on dark boundary in complement
-% imLoG(imLoG<0)=0;
+rTarget_um = Ensemble.getEnsembleRadius(segParams.minimumRadius_um);
+for rr=1:length(rTarget_um)
+ sp = segParams;
+ sp.minimumRadius_um = rTarget_um(rr);
+ [~,imp_rr,imn_rr] = LoG.getCompositeLoG(im,CONSTANTS,sp);
+ imp = cat(rdim,imp,imp_rr);
+% imn = cat(rdim,imn,imn_rr);
+end
+% for now, we take dark nucleus against bright cytoplasm or nuclear rim.
+% this is for e. g. ERK or Oracle. This will show up on the positive LoG
+% response.
+imp_max = max(imp,[],3);
+%
+% imn_max = max(imn,[],3);
cellFeatures=[];
for i=1:length(cellList)
- bw=0*im;
- bw(cellList(i).idxPts)=1;
- bwd=bwdist(~bw);
- thresh=prctile(bwd(find(bwd)),95);
- bwd(bwd<thresh)=0;
- channelLoG = imLoG(find(bwd));
- channelLoG(channelLoG<=0)=0;
- channelLoG=median(channelLoG);
+% bw=0*im;
+% bw(cellList(i).idxPts)=1;
+% bwd=bwdist(~bw);
+% thresh=prctile(bwd(find(bwd)),95);
+% bwd(bwd<thresh)=0;
+% channelLoG = imn_max(find(bwd));
+% channelLoG=median(channelLoG);
+
+ center = round(cellList(i).centroid);
+ channelLoG = imp_max(center(2),center(1));
cellFeatures=[cellFeatures;cellList(i).cellID,channelLoG];
end
tblCellFeatures.cellID=cellFeatures(:,1);
diff --git a/matlab/+DenoiseCache/denoiseFolder.m b/matlab/+DenoiseCache/denoiseFolder.m
index 4bba6216fae32826fc3d4050ddd1a8e757d3f6f8..0d12c85aa0b395a4fd28c82d2aeb6201361ec179 100644
--- a/matlab/+DenoiseCache/denoiseFolder.m
+++ b/matlab/+DenoiseCache/denoiseFolder.m
@@ -8,6 +8,8 @@ if 2==length(nProcessors)
nProcessors=nProcessors(2);
end
+nProcessors = min(nProcessors,8);
+
flist=dir(fullfile(folderName,'*.h5'));
if 0==length(flist)
fprintf(2,'no lever files found to denoise\n');
diff --git a/matlab/+DenoiseCache/readImages.m b/matlab/+DenoiseCache/readImages.m
index 006b2026f24a4dc88f5f2e8df5025e3d2b1030ad..861e0a4af7a6aefed0c0f9fe9ac7bd0141c2e1e1 100644
--- a/matlab/+DenoiseCache/readImages.m
+++ b/matlab/+DenoiseCache/readImages.m
@@ -1,8 +1,7 @@
-function [im,imLog]=readImages(t,CONSTANTS,segParams,medianMask)
+function im = readImages(t,CONSTANTS,segParams,medianMask)
if t>CONSTANTS.imageData.NumberOfFrames
im=[];
- imLog=[];
return
end
@@ -14,11 +13,7 @@ end
targetFile=fullfile(CONSTANTS.imageData.imageDir,'cacheDenoise',...
[CONSTANTS.imageData.DatasetName '.h5']);
if ~segParams.denoise || ~exist(targetFile,'file')
- if 1==nargout
- im=Segment.getImages(CONSTANTS,t,segParams.channels(1),segParams,medianMask);
- else
- [im,imLog]=Segment.getImages(CONSTANTS,t,segParams.channels(1),segParams,medianMask);
- end
+ im=Segment.getImages(CONSTANTS,t,segParams.channels(1),segParams,medianMask);
return;
end
@@ -32,7 +27,7 @@ if size(nlm,1)~=1
nlm=nlm';
end
if length(nlm)~=length(segParams.NLM) || any(segParams.NLM~=nlm)
- [im,imLog]=Segment.getImages(CONSTANTS,t,segParams.channels(1),segParams,medianMask);
+ im=Segment.getImages(CONSTANTS,t,segParams.channels(1),segParams,medianMask);
return;
end
@@ -47,13 +42,5 @@ if 1==segParams.wellRadius && exist('medianMask','var') && ~isempty(medianMask)
im=im-medianMask;
im=mat2gray(im);
end
-if 2==nargout
- % try to grab imLog
- logTarget=['/Images/LoG/' num2str(segParams.minimumRadius_um)];
- try
- imLog=h5read(targetFile,logTarget,[1,1,1,1,t],sz);
- catch
- imLog=Segment.getLoG(im,CONSTANTS,segParams);
- end
-end
+
4;
diff --git a/matlab/+Ensemble/processEnsemble.m b/matlab/+Ensemble/processEnsemble.m
index 19c8881d37e89e2cf0d75b08d83673143002c54e..b58cf9c18bc33358b9dfd637a68dea64ca6f0b5e 100644
--- a/matlab/+Ensemble/processEnsemble.m
+++ b/matlab/+Ensemble/processEnsemble.m
@@ -76,6 +76,7 @@ ljsLog(sprintf('ensembleSegment: time=%d, found %d cells, elapsedTime=%2.3f ',..
function areaStats=getCellSizeStats(conn,CONSTANTS)
areaStats=[];
+return;
cmd='select area from tblCells';
q=ljsFetch(conn,cmd);
if length(q)<100
@@ -98,7 +99,7 @@ function score=ScoreCell(areaStats,cell)
cd=cell.ensemble.area/cell.ensemble.convexArea;
logEff=sum(cell.ensemble.logEfficiency);
score=cd+cell.ensemble.circularity + logEff + cell.ensemble.backgroundEfficiency;
-
+score = score + -1 * cell.LoG;
% for each bucket (nestedCells{i}) of overlapping cells, we evaluate the
% best subsets of cell combinations
@@ -150,7 +151,6 @@ for j=1:length(nestedCells{ic})
% question of combining function -- min,max,mean,etc. relates to
% cluster structure function. empirically chose min.
% and on Dec 13 2019 tried max and mean as well. chose mean for now..:)
-% scoreJ(j)=max([nestedCells{ic}(cellsJ{j}).score]);
scoreJ(j)=mean([nestedCells{ic}(cellsJ{j}).score]);
nestedCells{ic}(j).nest.score=scoreJ(j);
end
diff --git a/matlab/+Ensemble/setCellEfficiency.m b/matlab/+Ensemble/setCellEfficiency.m
index 040acfb167a8056efc17ae5c590f1888532c0841..b33e9a04669bb33470565935bcd2badd0faa5627 100644
--- a/matlab/+Ensemble/setCellEfficiency.m
+++ b/matlab/+Ensemble/setCellEfficiency.m
@@ -16,10 +16,11 @@ idxPts=vertcat(Cells.idxPts);
spx=segParams;
spx.minimumRadius_um=0;
% get foreground pixels with no minimum size
-[bw,bwLoG]=Segment.thresholdImages(im,imLoG,spx, 0,0,medianMask);
-bgEfficiency=length(idxPts)/length(find(bw));
-bgEfficiency=min(bgEfficiency,1);
+% [bw,bwLoG]=Segment.thresholdImages(im,imLoG,spx, 0,0,medianMask);
+% bgEfficiency=length(idxPts)/length(find(bw));
+% bgEfficiency=min(bgEfficiency,1);
%
+bgEfficiency = 0;
imLoG_p=imLoG;
imLoG_p(imLoG_p<0)=0;
diff --git a/matlab/+Ensemble/set_LoG_score.m b/matlab/+Ensemble/set_LoG_score.m
index eef0c58f794b80c14e914ca4dd6d6458d1415751..4dbf088fa71193e431e126fc420e31962d96ce01 100644
--- a/matlab/+Ensemble/set_LoG_score.m
+++ b/matlab/+Ensemble/set_LoG_score.m
@@ -1,12 +1,18 @@
-function cellList = set_LoG_score(cellList,CONSTANTS,im,segParams)
+function cellList = set_LoG_score(cellList,CONSTANTS,im,imLoG,segParams)
cellList = Read.setCellsIdxPts(cellList,CONSTANTS);
+load('cacheReferenceLoG.mat');
% figure;imagesc(im);hold on
-for i=1:length(cellList)
-
- cellList(i).log_score = LoG.referenceLoG(im,CONSTANTS,cellList(i),segParams);
-% center = round(cellList(i).centroid);
-% text(center(1),center(2),num2str(cellList(i).log_score,4),'color','k','BackgroundColor','w');
+for i=1:length(cellList)
+ [log_score] = LoG.referenceLoG(im,imLoG,CONSTANTS,cellList(i),cacheReferenceLoG);
+ % bright nucleus on dark background - take negative response
+ cellList(i).log_score = log_score;
+% if 1 || log_score > 0.5
+% center = cellList(i).surface(1,:);
+% text(center(1),center(2),[num2str(log_score,2)],'color','k','BackgroundColor','w');
+% end
end
+%cellList([cellList.log_score]>0.995)=[];
+4;
\ No newline at end of file
diff --git a/matlab/+Helpers/buildWrangleFile.m b/matlab/+Helpers/buildWrangleFile.m
index 01cdd3a35547e0c0e6493aa6a671f440767d2fe0..9d3cf4f801277cf671763c4a528e57c25fc742c4 100644
--- a/matlab/+Helpers/buildWrangleFile.m
+++ b/matlab/+Helpers/buildWrangleFile.m
@@ -1,5 +1,8 @@
function strTarget=buildWrangleFile(strDB,outfolder,dsName,segParams)
+if ~exist(outfolder,'dir')
+ mkdir(outfolder);
+end
strTarget=fullfile(outfolder,[dsName '.LEVER']);
if exist(strTarget,'file')
delete([strTarget '*']);
diff --git a/matlab/+Helpers/cellEccentricity.m b/matlab/+Helpers/cellEccentricity.m
new file mode 100644
index 0000000000000000000000000000000000000000..0f76c5e048e30167a23d4dcded626b238925212d
--- /dev/null
+++ b/matlab/+Helpers/cellEccentricity.m
@@ -0,0 +1,4 @@
+function ecc = cellEccentricity(cx)
+
+evals = eig(cov(cx.pts));
+ecc = min(evals)/max(evals);
\ No newline at end of file
diff --git a/matlab/+Helpers/drawSeg.m b/matlab/+Helpers/drawSeg.m
new file mode 100644
index 0000000000000000000000000000000000000000..2c0985219ed65bb62ac1357fb27a3003d4f7113b
--- /dev/null
+++ b/matlab/+Helpers/drawSeg.m
@@ -0,0 +1,7 @@
+function drawSeg(cellList)
+
+hold on
+for i=1:length(cellList)
+ ccc = Read.getTrackColor(conn,cellList(i).cellID);
+ plot(cellList(i).surface(:,1),cellList(i).surface(:,2),'Color',ccc);
+end
\ No newline at end of file
diff --git a/matlab/+Helpers/imMod4.m b/matlab/+Helpers/imMod4.m
new file mode 100644
index 0000000000000000000000000000000000000000..029fb3c30191fb710fc162c2d6199eae2c69730c
--- /dev/null
+++ b/matlab/+Helpers/imMod4.m
@@ -0,0 +1,9 @@
+function im=imMod4(im)
+
+d1 = mod(size(im,1) ,4);
+d2 = mod(size(im,2) ,4);
+
+if 0~=d1,d1=4-d1;end
+if 0~=d2,d2=4-d2;end
+
+im(size(im,1)+d1,size(im,2)+d2,end,end,end)=0;
\ No newline at end of file
diff --git a/matlab/+Helpers/imTransfer.m b/matlab/+Helpers/imTransfer.m
new file mode 100644
index 0000000000000000000000000000000000000000..1c2f99ce26a21fd0974970df2fe48970a2bd4665
--- /dev/null
+++ b/matlab/+Helpers/imTransfer.m
@@ -0,0 +1,44 @@
+% transfer is [dark, medium, bright] as in leverjs transfer function
+function imScale = imTransfer(im,transfer)
+x_min = transfer(1); % dark
+y_mid = transfer(2); % medium
+x_max = transfer(3); % bright
+x_mid = (x_max+x_min)/2;
+
+tm = [ x_min.^2, x_min, 1, 0;
+ x_mid.^2, x_mid, 1, 0;
+ x_max.^2, x_max, 1, 0;
+ 0, 0, 0, 1]';
+tm = tm^-1;
+
+y_mid = max(y_mid,0.01);
+y_mid = min(y_mid,0.99);
+
+yVal = [0, y_mid, 1, 1];
+
+coeffs = yVal * tm;
+a=coeffs(1);
+b=coeffs(2);
+c=coeffs(3);
+
+% so we now have a,b,c for ax^2+bx+c the actual transfer function
+% we want to find when the slope, 2ax+b of the transfer function goes negative
+% and make the range (minRange,maxRange) so that never happens
+if (a>0)
+ minRange = max(-b/(2*a),x_min);
+ maxRange = x_max;
+elseif (0==a)
+ minRange = x_min;
+ maxRange = x_max;
+else
+ minRange = x_min;
+ maxRange = min(-b/(2*a),x_max);
+end
+
+idx0 = find(im<minRange);
+idx1 = find(im>maxRange);
+imScale = a .* im.^2 + b .* im + c;
+imScale(idx0)=0;
+imScale(idx1)=1;
+imScale = max(imScale,0);
+imScale = min(imScale,1);
diff --git a/matlab/+Helpers/scaleBar.m b/matlab/+Helpers/scaleBar.m
index bfbf2ca2dbf4808c97283ee139e74a7808a2835a..83aab422f44cfc28b7b5545dc16f4c4672ccff1e 100644
--- a/matlab/+Helpers/scaleBar.m
+++ b/matlab/+Helpers/scaleBar.m
@@ -1,4 +1,4 @@
-function [nPixels,microns] = scaleBar(CONSTANTS,targetPixels)
+function [nPixels,microns] = scaleBar(CONSTANTS,targetPixels,szim)
if ~exist('targetPixels','var')
targetPixels = 100;
@@ -9,3 +9,10 @@ microns = targetPixels .* microns_per_pixel;
microns = 5 * round(microns/5);
nPixels = round(microns / microns_per_pixel);
+% rectangle('Position',[szim(2)-100,25,nPixels,10],'facecolor','w')
+% text(szim(2)-100+nPixels/2,25,'30um','color','w','HorizontalAlignment','center', ...
+% 'VerticalAlignment','bottom')
+
+rectangle('Position',[szim(2)-30-nPixels,40,nPixels,15],'FaceColor','w');
+% text(szim(2)-30-nPixels,15,[num2str(microns) '\mum'],'color','w','VerticalAlignment','top','fontsize',12)
+text(szim(2)-30-nPixels,5,[num2str(microns) '\mum'],'color','w','VerticalAlignment','top','fontsize',12)
diff --git a/matlab/+Helpers/swapXY.m b/matlab/+Helpers/swapXY.m
new file mode 100644
index 0000000000000000000000000000000000000000..d84c083fdb37a867d19eea8d105ada2fefc4775e
--- /dev/null
+++ b/matlab/+Helpers/swapXY.m
@@ -0,0 +1,5 @@
+function pts = swapXY(pts)
+
+tmp = pts(:,1);
+pts(:,1) = pts(:,2);
+pts(:,2) = tmp;
diff --git a/matlab/+Helpers/volumeSize.m b/matlab/+Helpers/volumeSize.m
new file mode 100644
index 0000000000000000000000000000000000000000..d68ec1efe305893ea40df836b4a4ccb9d8794cfa
--- /dev/null
+++ b/matlab/+Helpers/volumeSize.m
@@ -0,0 +1,5 @@
+% returns sz in bytes
+function sz = volumeSize (CONSTANTS)
+
+sz =[CONSTANTS.imageData.Dimensions, CONSTANTS.imageData.NumberOfChannels, CONSTANTS.imageData.NumberOfFrames];
+sz=[sz(2) sz(1) sz(3:end)];
diff --git a/matlab/+Import/prepareH5.m b/matlab/+Import/prepareH5.m
index 8096f0d20f05b9d48baa61d4965cde2a0bf8f570..dddace62f09c8b3b55afed21ddfdc9698acdc90a 100644
--- a/matlab/+Import/prepareH5.m
+++ b/matlab/+Import/prepareH5.m
@@ -4,6 +4,8 @@
%
% imageData=MicroscopeData.MakeMetadataFromImage(imx);
% remember to set imageData.NumberOfFrames and imageData.
+% IMPORTANT -- datasetName is e.g. Original, Denoise, etc., not your actual
+% datasetname
function prepareH5(h5File,imageData,datasetName,szChunk)
if ~exist('datasetName','var')
diff --git a/matlab/+Lineage/eraseLineage.m b/matlab/+Lineage/eraseLineage.m
new file mode 100644
index 0000000000000000000000000000000000000000..79116adb6bbfe7c6db1479c2034302740ac3621f
--- /dev/null
+++ b/matlab/+Lineage/eraseLineage.m
@@ -0,0 +1,9 @@
+function eraseLineage(conn)
+
+exec(conn,'delete from tblFamilies;delete from uiExtFamilies');
+strDB = conn.DataSource;
+Batch.batchTrack(strDB);
+Smooth.Patch.patch11(conn);
+Smooth.Patch.patch12(conn);
+Smooth.Patch.patch21(conn);
+Smooth.Patch.patchOcclusion(conn);
\ No newline at end of file
diff --git a/matlab/+LoG/+Reference/generateReferenceLoG.m b/matlab/+LoG/+Reference/generateReferenceLoG.m
new file mode 100644
index 0000000000000000000000000000000000000000..0aa752aa50286c0e56426af841fbe3eb70a1e4c0
--- /dev/null
+++ b/matlab/+LoG/+Reference/generateReferenceLoG.m
@@ -0,0 +1,43 @@
+function cacheReferenceLoG = generateReferenceLoG()
+
+b3D = false;
+
+if ~exist('szImage','var')
+ sz = [200,200];
+end
+if ~exist('rgRadius_pixels','var')
+ rgRadius = [1:0.5:20];
+end
+center=round(sz/2);
+cacheReferenceLoG = [];
+
+for xRadius = 1:length(rgRadius)
+ for yRadius = xRadius:length(rgRadius)
+ im = zeros(sz(1),sz(2));
+ rProjected = [rgRadius(xRadius),rgRadius(yRadius),0];
+ imref_small = HIP.MakeEllipsoidMask(rProjected);
+ refCenterSmall = size(imref_small)/2;
+ if b3D
+ idxRef = find(imref_small);
+ [r,c,z] = ind2sub(size(imref_small),idxRef);
+ idxRef = sub2ind(size(im),round(r+refCenter(1)-refCenterSmall(1)),...
+ round(c+refCenter(2)-refCenterSmall(2)),...
+ round(z+refCenter(3)-refCenterSmall(3)));
+ im(idxRef)=1;
+ d=3;
+ else
+ [r,c] = find(imref_small);
+ idxRef = sub2ind(size(im),round(r+center(1)-refCenterSmall(1)),...
+ round(c+center(2)-refCenterSmall(2)));
+ im(idxRef)=1;
+ d=2;
+ end
+ sigma = 1/sqrt(d) .* rProjected;
+ lr.imf = HIP.LoG(im,sigma,[]);
+ lr.radius = rProjected;
+ lr.maxResponse = max(abs(lr.imf(:)));
+ cacheReferenceLoG = [cacheReferenceLoG,lr];
+ end
+end
+save('cacheReferenceLoG.mat','cacheReferenceLoG');
+4;
\ No newline at end of file
diff --git a/matlab/+LoG/channelLoG_separate.m b/matlab/+LoG/channelLoG_separate.m
new file mode 100644
index 0000000000000000000000000000000000000000..8cc4a69d88aa2ae4f4408d30061fdae477de5321
--- /dev/null
+++ b/matlab/+LoG/channelLoG_separate.m
@@ -0,0 +1,18 @@
+function imOut = channelLoG_separate(caChannelLoG, bw, min_radius_pixels)
+
+bwd = bwdist(~bw);
+if is3D(bw)
+ bw = bw & (bwd > min(min_radius_pixels));
+else
+ bw = bw & (bwd > min_radius_pixels(1));
+end
+imOut = [];
+for cc=1:length(length(caChannelLoG))
+ [~,imp,imn] = LoG.separateLoG(caChannelLoG{cc});
+ if isempty(imOut)
+ imOut = max(imn.*bw, imp.*bw);
+ else
+ imOut = imOut + max(imn.*bw, imp.*bw);
+ end
+end
+4;
diff --git a/matlab/+LoG/cleanLoG.m b/matlab/+LoG/cleanLoG.m
new file mode 100644
index 0000000000000000000000000000000000000000..023ee70e3f12a99304381d0e37c3fad0d1562001
--- /dev/null
+++ b/matlab/+LoG/cleanLoG.m
@@ -0,0 +1,85 @@
+% remove spurious LoG noise
+function [bwLoG,bwLoG_gradient]=cleanLoG(bwLoG_pos,bwLoG_neg,min_area_pixels,min_radius_pixels)
+
+% bright cell, dark bg
+% LoG+ is gradiants
+% LoG- is blobs
+% hint - see LoG.separateLoG, imc is [imp,imn,0] -> (r,g,b)
+
+if 1 == length(min_radius_pixels)
+ nhood = HIP.MakeEllipsoidMask(ceil([min_radius_pixels,min_radius_pixels,0]));
+else
+ nhood = HIP.MakeEllipsoidMask(ceil(min_radius_pixels));
+end
+
+if min(min_radius_pixels)/max(min_radius_pixels) < 0.25
+ baniso = true;
+else
+ % isotropic - use faster approximations for dilate/erode at cell scale
+ baniso = false;
+end
+
+baniso = false;
+
+
+defConn = conndef(ndims(bwLoG_pos),'minimal');
+
+bwLoG_neg = bwareaopen(bwLoG_neg,min_area_pixels,defConn);
+% distance from blob voxels to bg
+bwd_neg = bwdist(~bwLoG_neg);
+bwd_pos = bwdist(~bwLoG_pos);
+
+% blob must go 1 radius deep
+bwd_blob = bwd_neg;
+if baniso
+ bwd_neg = imdilate(bwd_neg,nhood);
+ % pixels must be within 1 diameter (2 radii) of a pixel with
+ % depth>=min_radius
+ bwd_blob(bwd_neg<0.75*min(min_radius_pixels)) = 0;
+else
+ % imdilate with big 3-D nhood is toooo sloooooww
+ % so instead use distance tranform. lose anisotropy to gain speed
+ bwd_blob_deep = bwd_neg;
+ bwd_blob_deep(bwd_blob_deep<0.75*min(min_radius_pixels))=0;
+ bwd_deep_blob = bwdist(bwd_blob_deep);
+ % pixels must be within 1 diameter (2 radii) of a pixel with
+ % depth>=min_radius
+ bwd_blob(bwd_deep_blob>min(min_radius_pixels)) = 0;
+end
+% valid gradient must be adjacent to blobs
+bwLoG_gradient = bwLoG_pos;
+bwd_gradient_to_blob = bwdist(bwd_blob);
+bwLoG_gradient(bwd_gradient_to_blob > min_radius_pixels(1)) = 0;
+bwLoG_gradient = bwareaopen(bwLoG_gradient,ceil(pi * min(min_radius_pixels)),defConn);
+
+% % ACK - controversial! gradient should have diameter of blob?
+if baniso
+ bwd_pos=imdilate(bwd_pos,nhood);
+ bwLoG_gradient(bwd_pos<min(min_radius_pixels))=0;
+else
+ % dilate too slow! use istropic distance instead as above
+ bwd_deep_gradient = bwd_pos;
+ bwd_deep_gradient(bwd_deep_gradient<min(min_radius_pixels)) = 0;
+ bwd_gradient_to_deep_gradient = bwdist(bwd_deep_gradient);
+ bwLoG_gradient(bwd_gradient_to_deep_gradient>min(min_radius_pixels))=0;
+end
+
+% blobs have to be adjacent to gradient
+bwd_blob_to_gradient = bwdist(bwLoG_gradient);
+if baniso
+ bwd_blob_to_gradient = imerode(bwd_blob_to_gradient,nhood);
+ % as above, pixels must be within 1 diameter of a gradient pixel
+ bwd_blob(bwd_blob_to_gradient > min_radius_pixels(1)) = 0;
+else
+ % imerode too slow! use anisotropic instead
+ bwd_blob_to_gradient(bwd_blob_to_gradient>max(min_radius_pixels))=0;
+ bwd_blob_to_gradient = bwdist(bwd_blob_to_gradient);
+ bwd_blob(bwd_blob_to_gradient > max(min_radius_pixels(1))) = 0;
+end
+
+bwLoG = logical(bwd_blob) ;
+bwLoG = imfill(bwLoG,'holes');
+bwLoG = Segment.aiAreaOpen(bwLoG,min_radius_pixels,defConn);
+
+4;
+
diff --git a/matlab/+LoG/drawCellScores.m b/matlab/+LoG/drawCellScores.m
index 6a201eb57d946122d6257e81b15dd7061a1d2f8e..e5a7115075f7fa919bc84e519e351b94d3c523ee 100644
--- a/matlab/+LoG/drawCellScores.m
+++ b/matlab/+LoG/drawCellScores.m
@@ -1,17 +1,6 @@
-
-strDB='/f/leverjs/Olivier/Yannick/20210924/20210924_pos3.LEVER';
-[conn,CONSTANTS,segParams]=openDB(strDB);
-
-t=300;
-cellList = Read.getCellsTime(conn,t);
-[imLoG,imc] = LoG.getCombinedLoG(conn,CONSTANTS,segParams,t,[1,6]);
-
-im = DenoiseCache.readImages(t,CONSTANTS,segParams);
-imagesc(im);colormap(gray);hold on;
-for i=1:length(cellList)
- score = CellFeatures.sampleLoG(cellList(i),imLoG,CONSTANTS);
- ccc = Read.getTrackColor(conn,cellList(i).trackID);
- plot(cellList(i).surface(:,1),cellList(i).surface(:,2),'color',ccc);
- text(max(cellList(i).surface(:,1)),cellList(i).centroid(2),num2str(score(2),2),'color','k','BackgroundColor','w','FontSize',8);
+function drawCellScores(cellList)
+for i=1:length(cellList)
+ score = cellList(i).LoG;
+ text(max(cellList(i).surface(:,1)),cellList(i).centroid(2),num2str(score,2),'color','k','BackgroundColor','w','FontSize',8);
end
diff --git a/matlab/+LoG/evalLoG2.m b/matlab/+LoG/evalLoG2.m
new file mode 100644
index 0000000000000000000000000000000000000000..9781e2f915655995094552180dafa2ea6ae6e69a
--- /dev/null
+++ b/matlab/+LoG/evalLoG2.m
@@ -0,0 +1,65 @@
+% strDB='/f/leverjs/g/ctc2021_wrangle/Fluo-N2DL-HeLa_training_02.LEVER';
+% strDB = '/f/leverjs/Parsons/MCF7_ERK_KTR_29April22/mcf7 erk ktrsora hoescht33324 trial run_mcf7_withH_1.LEVER'
+% strDB = '/g/leverjs/ctc2021_manual/2d/Fluo-N2DL-HeLa_training_01.LEVER'
+% [conn,CONSTANTS,segParams]=openDB(strDB);
+cellList = Segment.frameSegment(conn,1,CONSTANTS,segParams)
+r=[1:0.5:12];
+res=[];
+
+t=1;
+res={};
+imLoG = [];
+parfor ir = 1:length(r)
+
+ res{ir} = [];
+ sp=segParams;
+ rr = r(ir);
+ sp.minimumRadius_um=rr;
+ [im,imf] = DenoiseCache.readImages(t,CONSTANTS,sp);
+ cx=Segment.frameSegment(conn,t,CONSTANTS,sp);
+
+ for i=1:length(cellList)
+ % find any cx that overlaps cellList(i)
+ targetPoint = cellList(i).centroid;
+ if ~is3D(im)
+ targetPoint = targetPoint(1:2);
+ end
+
+ [cx1,dmin,idxMin] = Segment.findNearestSegmentation(cx,targetPoint);
+ if dmin>2
+ % this cell did not get a segmentation at this radius
+ continue
+ end
+ % [cellScore,refVal] = LoG.referenceLoG(im,imf,CONSTANTS,cx(i),segParams);
+ % cx(i).cellScore = cellScore;
+ res{ir}=vertcat(res{ir},[r(ir),i,idxMin,cx1.LoG]);
+
+ end
+end
+
+cellRadii={};
+choice1=[];
+resR = vertcat(res{:});
+for i=1:length(cellList)
+ idx = find(resR(:,3)==i);
+ res1 = resR(idx,:);
+ res1 = sortrows(res1,4,'ascend');
+ cellRadii{i}=res1(:,1);
+ choice1(i)=res1(1,1);
+end
+
+
+% resR = vertcat(res{:});
+% resBest = [];
+% rHist = unique(resR(:,1))
+% histMap = containers.Map(rHist,repmat(0.0,size(rHist)));
+% for i=1:length(cellList)
+% idx = find(resR(:,3)==i);
+% for j=1:length(idx)
+% histMap(resR(idx(j),1)) = histMap(resR(idx(j),1)) + 1;
+% end
+% end
+%
+for i=1:length(cellList)
+ text(cellList(i).centroid(1),cellList(i).centroid(2),[num2str(i) ',' num2str(choice1(i),2)],'color','k','BackgroundColor','w');
+end
\ No newline at end of file
diff --git a/matlab/+LoG/getCombinedGradients.m b/matlab/+LoG/getCombinedGradients.m
new file mode 100644
index 0000000000000000000000000000000000000000..8795652327069e6fc6ce45a60d41ff71fcb94d7b
--- /dev/null
+++ b/matlab/+LoG/getCombinedGradients.m
@@ -0,0 +1,9 @@
+function imf = getCombinedGradients(im,CONSTANTS,rEval)
+
+imf = 0*im;
+for rr=1:length(rEval);
+ sp = Segment.getDefaultSegParams();
+ sp.minimumRadius_um = rEval(rr);
+ imf = Segment.getLoG(im,CONSTANTS,sp);
+end
+4;
\ No newline at end of file
diff --git a/matlab/+LoG/getCompositeLoG.m b/matlab/+LoG/getCompositeLoG.m
new file mode 100644
index 0000000000000000000000000000000000000000..bbf52b9348444c5b2b397d019bd16c2f7e08f4e9
--- /dev/null
+++ b/matlab/+LoG/getCompositeLoG.m
@@ -0,0 +1,38 @@
+function [imLoG, imp, imn] = getCompositeLoG(im,CONSTANTS,segParams)
+
+
+if is3D(im)
+ ndim = 4;
+ sampleSize = 10;
+else
+ ndim = 3;
+ sampleSize = 20;
+end
+
+if length(segParams.minimumRadius_um)>1
+ rgRadius = Ensemble.getEnsembleRadius(segParams.minimumRadius_um);
+else
+ rgRadius = linspace(0.75*segParams.minimumRadius_um,1.25*segParams.minimumRadius_um,sampleSize);
+end
+
+imLoG = [];
+
+for ir = 1:length(rgRadius)
+
+ sp=segParams;
+ rr = rgRadius(ir);
+ sp.minimumRadius_um=rr;
+
+ imf = Segment.getLoG(im,CONSTANTS,sp);
+
+ imLoG = cat(ndim,imLoG,imf);
+
+end
+imn = min(imLoG,[],ndim);
+imn(imn>0) = 0;
+imn=abs(imn);
+
+imp = max(imLoG,[],ndim);
+imp(imp<0) = 0;
+imCombine = imp>imn;
+imLoG = imCombine.*imp + -1.*~imCombine.*imn;
diff --git a/matlab/+LoG/getRadiusPixels.m b/matlab/+LoG/getRadiusPixels.m
index 45a15b1c6dddf4721971906f2d326edd2a541a74..7bbd364227a7c897f0d9329339f71c6a5ee05a1b 100644
--- a/matlab/+LoG/getRadiusPixels.m
+++ b/matlab/+LoG/getRadiusPixels.m
@@ -1,10 +1,10 @@
function radiusPixels = getRadiusPixels(CONSTANTS,segParams)
-radiusPixels = segParams.minimumRadius_um(1) .* CONSTANTS.imageData.PixelPhysicalSize;
+radiusPixels = segParams.minimumRadius_um(1) ./ CONSTANTS.imageData.PixelPhysicalSize;
if is3D(CONSTANTS)
- radiusPixels = radiusPixels ./ (1/sqrt(3));
+ radiusPixels = radiusPixels .* (1/sqrt(3));
else
- radiusPixels = radiusPixels ./ (1/sqrt(2));
+ radiusPixels = radiusPixels .* (1/sqrt(2));
radiusPixels(3) = 0;
end
diff --git a/matlab/+LoG/get_5d.m b/matlab/+LoG/get_5d.m
new file mode 100644
index 0000000000000000000000000000000000000000..647dfc91daf671887919f58231fd257512402cd6
--- /dev/null
+++ b/matlab/+LoG/get_5d.m
@@ -0,0 +1,19 @@
+% write a 5d lever file for this image
+strDB = '/f/leverjs/Parsons/MCF7_ERK_KTR_29April22/mcf7 erk ktrsora hoescht33324 trial run_mcf7_withH_2.LEVER'
+[conn,CONSTANTS,segParams] = openDB(strDB);
+rEval = [0.5:0.1:4];
+
+ljsStartParallel(24);
+for t = 1 : 1 %CONSTANTS.imageData.NumberOfFrames
+ logStack = [];
+ imp=[];
+ imn=[];
+ parfor rr = 1:length(rEval)
+ sp = segParams;
+ sp.minimumRadius_um=rEval(rr);
+ [im,imLoG] = DenoiseCache.readImages(t,CONSTANTS,sp);
+ [~, imp(:,:,rr), imn(:,:,rr)] = LoG.separateLoG(imLoG);
+ end
+ logStack(:,:,:,1,1) = imp;
+ logStack(:,:,:,2,1) = imn;
+end
diff --git a/matlab/+LoG/logStudy_perCell.m b/matlab/+LoG/logStudy_perCell.m
new file mode 100644
index 0000000000000000000000000000000000000000..89cc6cbeecd57a5593829408f3a94f696aba1682
--- /dev/null
+++ b/matlab/+LoG/logStudy_perCell.m
@@ -0,0 +1,146 @@
+% strDB ='/f/leverjs/Olivier/wrangle/20210924_pos3.LEVER'
+% H2B = 1;
+% ERK = 2;
+% Oracle = 3;
+%
+% strDB = '/g/leverjs/Olivier/Yannick/April_12_2021/20210129_20x_SD_LI2_HEO_3d_10s10t/20210129_20x_SD_LI2_HEO_3d_10s10t_s20.LEVER'
+% H2B = 3;
+% ERK = 2;
+% Oracle = 1;
+
+
+strDB = '/f/leverjs/Olivier/Yannick/April_12_2021/20210129_20x_SD_LI2_HEO_3d_10s10t/20210129_20x_SD_LI2_HEO_3d_10s10t_s02.LEVER'
+H2B = 3;
+ERK = 2;
+
+targetChannel = ERK;
+
+[conn,CONSTANTS,segParams]=openDB(strDB);
+[~,dsName,~] = fileparts(strDB);
+dsName = [dsName '_erk'];
+% need better naming convention! ACK
+outfolder = ['./tiffs_' dsName];
+prefix = 'erk_log_';
+if ~exist(outfolder,'dir')
+ mkdir(outfolder)
+
+end
+
+% clip limits
+im = MicroscopeData.Reader('imageData',CONSTANTS.imageData, 'chanList',...
+ targetChannel,'timeRange',[1,1], 'outType',CONSTANTS.imageData.PixelFormat,'prompt',false);
+clipMax = double(max(im(:)));
+clipMin = double(min(im(:)));
+
+for t=1:CONSTANTS.imageData.NumberOfFrames
+
+ cx=openDB(strDB);
+ cellList = Read.getCellsTime(cx,t,H2B,CONSTANTS);
+ close(cx);
+
+ if ~is3D(CONSTANTS)
+ d = 2;
+ sz_um = CONSTANTS.imageData.PixelPhysicalSize(1:2);
+ else
+ d=3;
+ sz_um = CONSTANTS.imageData.PixelPhysicalSize;
+ end
+ rCell_pixels = cellfun(@(x) (sqrt(d) .* std(double(x))),{cellList.pts},'UniformOutput',false);
+ rCell_um = cellfun(@(x) norm(x .* sz_um),rCell_pixels);
+ aCell_pixels = cellfun(@length,{cellList.pts});
+
+% r0 = segParams.minimumRadius_um(1); %min(rCell_um);
+% r1 = segParams.minimumRadius_um(3); %median(rCell_um);
+ r0 = min(rCell_um);
+ r1 = median(rCell_um);
+
+ rTarget_um = linspace(r0,r1,20);
+ rTarget_um = linspace(r0,r1,20);
+
+% if ~is3D(CONSTANTS)
+% d = 2;
+% sz_um = CONSTANTS.imageData.PixelPhysicalSize(1:2);
+% else
+% d=3;
+% sz_um = CONSTANTS.imageData.PixelPhysicalSize;
+% end
+% rCell_pixels = cellfun(@(x) (sqrt(d) .* std(double(x))),{cellList.pts},'UniformOutput',false);
+% rCell_um = cellfun(@(x) norm(x .* sz_um),rCell_pixels);
+% aCell_pixels = cellfun(@length,{cellList.pts});
+
+ r0 = min(rCell_um);
+ r1 = median(rCell_um);
+ rTarget_um = linspace(r0,r1,20);
+
+ % rTarget_um = [min(rTarget_um),mean(diff(rTarget_um)),max(rTarget_um)];
+ im = MicroscopeData.Reader('imageData',CONSTANTS.imageData, 'chanList',...
+ targetChannel,'timeRange',[t t], 'outType',CONSTANTS.imageData.PixelFormat,'prompt',false);
+ im = double(im);
+ im = (im-clipMin)./(clipMax-clipMin);
+ im = im - median(im(:));
+ im = max(im,0);
+ im = min(im,1);
+ im = Segment.denoise(im,segParams,false);
+
+ imp = [];
+ if is3D(im)
+ rdim = 4;
+ else
+ rdim = 3;
+ end
+ imn = []; % h2b wants imn
+ for rr=1:length(rTarget_um)
+ sp = segParams;
+ sp.minimumRadius_um = rTarget_um(rr);
+ [~,imp_rr,imn_rr] = LoG.getCompositeLoG(im,CONSTANTS,sp);
+ imp = cat(rdim,imp,imp_rr);
+ imn = cat(rdim,imn,imn_rr);
+ end
+ imp_max = max(imp,[],rdim);
+ imn_max = max(imn,[],rdim);
+
+ if H2B == targetChannel
+ imp_max = imn_max; % capture h2b
+ end
+
+
+ im_segLoG = 0 * im;
+ for i=1:length(cellList)
+ im_segLoG(cellList(i).idxPts) = imp_max(cellList(i).idxPts);
+ end
+
+ im_segLoG = mat2gray(im_segLoG);
+ vbar = 0.33 * ones(size(im,1),5,3);
+
+ if H2B == targetChannel
+ imcx = Helpers.imTransfer(mat2gray(im),[0,1,0.5]);
+ else
+ imcx = im; %
+ end
+ imc = [];
+ imc(:,:,1)=0*im;
+ imc(:,:,2)=mat2gray(imcx);
+ imc(:,:,3)=imc(:,:,2);
+
+ if H2B == targetChannel
+ imlx = Helpers.imTransfer(mat2gray(im_segLoG),[0,1,0.5]);
+ else
+ imlx = im_segLoG; %
+ end
+ imlc = [];
+ imlc(:,:,1)=imlx;
+ imlc(:,:,2)=imlx;
+ imlc(:,:,3)=imlx;
+
+ imOut = [imc,vbar,imlc];
+
+
+% imOut = mat2gray([im,vbar,im_segLoG]);
+
+% figure(1);imagesc(imOut);axis image
+% title(num2str(t))
+% drawnow
+
+ fname = fullfile(outfolder,[prefix num2str(t) '.tif']);
+ imwrite(imOut,fname);
+end
diff --git a/matlab/+LoG/logStudy_perCell_3d_vis.m b/matlab/+LoG/logStudy_perCell_3d_vis.m
new file mode 100644
index 0000000000000000000000000000000000000000..85561cccfab52a01074cc481edca24f3db6b32de
--- /dev/null
+++ b/matlab/+LoG/logStudy_perCell_3d_vis.m
@@ -0,0 +1,168 @@
+% strDB ='/f/leverjs/Olivier/wrangle/20210924_pos3.LEVER'
+% H2B = 1;
+% ERK = 2;
+% Oracle = 3;
+%
+% strDB = '/g/leverjs/Olivier/Yannick/April_12_2021/20210129_20x_SD_LI2_HEO_3d_10s10t/20210129_20x_SD_LI2_HEO_3d_10s10t_s20.LEVER'
+% H2B = 3;
+% ERK = 2;
+% Oracle = 1;
+
+
+strDB = '/g/leverjs/Olivier/mcf10a_3d_LoG/190827_wt_stage_1_00_movieS1.LEVER';
+H2B = 1;
+ERK = 2;
+
+bPreview = false;
+if ( ~bPreview )
+ movieFile='190827_wt_stage_1_00_movieS1_erk_ssf.avi';
+ vidWrite=VideoWriter(movieFile,'Motion JPEG AVI');
+ vidWrite.FrameRate=10;
+ open(vidWrite)
+end
+
+targetChannel = ERK;
+
+[conn,CONSTANTS,segParams]=openDB(strDB);
+
+% clip limits
+im = MicroscopeData.Reader('imageData',CONSTANTS.imageData, 'chanList',...
+ targetChannel,'timeRange',[1,1], 'outType',CONSTANTS.imageData.PixelFormat,'prompt',false);
+clipMax = double(max(im(:)));
+clipMin = double(min(im(:)));
+
+angles = linspace(0,360,CONSTANTS.imageData.NumberOfFrames);
+for t=1:CONSTANTS.imageData.NumberOfFrames
+
+ cx=openDB(strDB);
+ cellList = Read.getCellsTime(cx,t,H2B,CONSTANTS);
+ close(cx);
+
+% r0 = segParams.minimumRadius_um(1); %min(rCell_um);
+% r1 = segParams.minimumRadius_um(3); %median(rCell_um);
+% rTarget_um = linspace(r0,r1,20);
+
+ if ~is3D(CONSTANTS)
+ d = 2;
+ sz_um = CONSTANTS.imageData.PixelPhysicalSize(1:2);
+ else
+ d=3;
+ sz_um = CONSTANTS.imageData.PixelPhysicalSize;
+ end
+ rCell_pixels = cellfun(@(x) (sqrt(d) .* std(double(x))),{cellList.pts},'UniformOutput',false);
+ rCell_um = cellfun(@(x) norm(x .* sz_um),rCell_pixels);
+ aCell_pixels = cellfun(@length,{cellList.pts});
+% r0 = min(rCell_um);
+% r1 = median(rCell_um);
+r0=3;
+r1=5;
+ rTarget_um = linspace(r0,r1,20);
+
+ % rTarget_um = [min(rTarget_um),mean(diff(rTarget_um)),max(rTarget_um)];
+ im = MicroscopeData.Reader('imageData',CONSTANTS.imageData, 'chanList',...
+ targetChannel,'timeRange',[t t], 'outType',CONSTANTS.imageData.PixelFormat,'prompt',false);
+ im = double(im);
+ im = (im-clipMin)./(clipMax-clipMin);
+ im = im - median(im(:));
+ im = max(im,0);
+ im = min(im,1);
+ im = Segment.denoise(im,segParams,false);
+ if (all(0==im(:)))
+ continue
+ end
+ imp = [];
+ if is3D(im)
+ rdim = 4;
+ else
+ rdim = 3;
+ end
+ imn = []; % h2b wants imn
+ for rr=1:length(rTarget_um)
+ sp = segParams;
+ sp.minimumRadius_um = rTarget_um(rr);
+ [~,imp_rr,imn_rr] = LoG.getCompositeLoG(im,CONSTANTS,sp);
+ imp = cat(rdim,imp,imp_rr);
+ imn = cat(rdim,imn,imn_rr);
+ end
+ imp_max = max(imp,[],rdim);
+ imn_max = max(imn,[],rdim);
+
+ if H2B == targetChannel
+ imp_max = imn_max; % capture h2b
+ end
+
+
+ im_segLoG = 0 * im;
+ for i=1:length(cellList)
+ im_segLoG(cellList(i).idxPts) = imp_max(cellList(i).idxPts);
+ end
+
+ im_segLoG = mat2gray(im_segLoG);
+
+
+
+ % use leversc for [im,im_segLoG]
+ % setup original
+ if 1==t
+% imd = CONSTANTS.imageData;
+% imd.NumberOfChannels=1;
+% lsc = leversc(im,imd);
+ %% Disable most UI elements
+
+ imd = MicroscopeData.MakeMetadataFromImage(im);
+ imd.PixelPhysicalSize = [0.3700 0.3700 0.6000];
+ lsc = leversc(im,imd);
+ %% Reset view parameters (also set background to black)
+ lsc.viewParams.clipMode = 0;
+ lsc.viewParams.worldRot = reshape([1,0,0,0; 0,1,0,0; 0,0,1,0; 0,0,0,1], 16,1);
+ lsc.viewParams.zoom = 0;
+%
+ end
+ leversc(im,imd);
+ lsc.viewParams.bgColor = [0,0,0];
+ lsc.uiParams.sidebar='none';
+ lsc.uiParams.scalebar=false;
+ lsc.renderParams.color=[0,1,0];
+ lsc.uiParams.webToolbar='none';
+ lsc.uiParams.clockButton='';
+ lsc.uiParams.logoDiv='';
+ lsc.uiParams.time=num2str(t);
+ lsc.renderParams.alpha=0.1;
+ % first ,im
+ while ~lsc.drawComplete()
+ pause(0.1);
+ end
+ imRawCap=lsc.captureImage();
+
+ lsc.show(im_segLoG);
+ lsc.uiParams.clockButton='none';
+ lsc.uiParams.logoDiv='none';
+ lsc.renderParams.color=[1,1,1];
+ lsc.uiParams.scalebar=true;
+ lsc.uiParams.webToolbar='none';
+ lsc.renderParams.alpha=1;
+
+ while ~lsc.drawComplete()
+ pause(0.1);
+ end
+ imLoGcap=lsc.captureImage();
+ imCap = [imRawCap,64*ones(size(imLoGcap,1),5,3),imLoGcap];
+
+% ry=[cosd(angles(t)), 0, sind(angles(t)),0;
+% 0,1,0,0;
+% -sind(angles(t)),0,cosd(angles(t)),0;
+% 0,0,0,1];
+%
+% worldRot=ry;
+% lsc.viewParams.worldRot=worldRot(:);
+
+
+ if ( bPreview )
+ imagesc(imCap);
+ axis image;
+ drawnow();
+ else
+ writeVideo(vidWrite,imCap);
+ end
+end
+close(vidWrite)
\ No newline at end of file
diff --git a/matlab/+LoG/logStudy_perCell_kymo.m b/matlab/+LoG/logStudy_perCell_kymo.m
new file mode 100644
index 0000000000000000000000000000000000000000..11d56e2268b5da09b8dd9a924e7c9404e04b7323
--- /dev/null
+++ b/matlab/+LoG/logStudy_perCell_kymo.m
@@ -0,0 +1,77 @@
+strDB ='/g/leverjs/Olivier/pos3/20210924_pos3.LEVER'
+H2B = 1;
+ERK = 2;
+Oracle = 3;
+
+% strDB = '/g/leverjs/Olivier/Yannick/April_12_2021/20210129_20x_SD_LI2_HEO_3d_10s10t/20210129_20x_SD_LI2_HEO_3d_10s10t_s20.LEVER'
+% H2B = 3;
+% ERK = 2;
+% Oracle = 1;
+
+targetChannel = ERK;
+
+imKymo = [];
+
+[conn,CONSTANTS,segParams]=openDB(strDB);
+
+% clip limits
+im = MicroscopeData.Reader('imageData',CONSTANTS.imageData, 'chanList',...
+ targetChannel,'timeRange',[1,1], 'outType','uint16','prompt',false);
+clipMax = double(max(im(:)));
+clipMin = double(min(im(:)));
+
+
+parfor t=1:CONSTANTS.imageData.NumberOfFrames
+
+ imt = [];
+
+ cx=openDB(strDB);
+ cellList = Read.getCellsTime(cx,t,H2B,CONSTANTS);
+ close(cx);
+
+ rCell_pixels = cellfun(@(x) std(double(x)),{cellList.pts},'UniformOutput',false);
+ rCell_um = mean(vertcat(rCell_pixels{:}),2) .* CONSTANTS.imageData.PixelPhysicalSize(1);
+
+ r0 = prctile(mean(vertcat(rCell_pixels{:}),2),2.5);
+ r1 = prctile(mean(vertcat(rCell_pixels{:}),2),97.5);
+ rTarget_um = linspace(r0,r1,20);
+% rTarget_um = [min(rTarget_um),mean(diff(rTarget_um)),max(rTarget_um)];
+ im = MicroscopeData.Reader('imageData',CONSTANTS.imageData, 'chanList',...
+ targetChannel,'timeRange',[t t], 'outType','uint16','prompt',false);
+ im = double(im);
+ im = (im-clipMin)./(clipMax-clipMin);
+ im = im - median(im(:));
+ im = max(im,0);
+ im = min(im,1);
+ im = Segment.denoise(im,segParams,false);
+
+ imp = [];
+ if is3D(im)
+ rdim = 4;
+ else
+ rdim = 3;
+ end
+ imn = []; % h2b wants imn
+ for rr=1:length(rTarget_um)
+ sp = segParams;
+ sp.minimumRadius_um = rTarget_um(rr);
+ [~,imp_rr,imn_rr] = LoG.getCompositeLoG(im,CONSTANTS,sp);
+ imp = cat(rdim,imp,imp_rr);
+ imn = cat(rdim,imn,imn_rr);
+ end
+ imp_max = max(imp,[],3);
+ imn_max = max(imn,[],3);
+
+ if H2B == targetChannel
+ imp_max = imn_max; % capture h2b
+ end
+
+
+ im_segLoG = 0 * im;
+ for i=1:length(cellList)
+ im_segLoG(cellList(i).idxPts) = imp_max(cellList(i).idxPts);
+ end
+
+% im_segLoG = mat2gray(im_segLoG);
+ imKymo(:,:,t) = im_segLoG;
+end
diff --git a/matlab/+LoG/logStudy_perCell_sparse.m b/matlab/+LoG/logStudy_perCell_sparse.m
new file mode 100644
index 0000000000000000000000000000000000000000..2a35d711b65d40ca03cc24d8b7394b8c6603173e
--- /dev/null
+++ b/matlab/+LoG/logStudy_perCell_sparse.m
@@ -0,0 +1,143 @@
+% strDB ='/f/leverjs/Olivier/wrangle/20210924_pos3.LEVER'
+% H2B = 1;
+% ERK = 2;
+% Oracle = 3;
+
+% strDB = '/f/leverjs/Olivier/Yannick/April_12_2021/20210129_20x_SD_LI2_HEO_3d_10s10t/20210129_20x_SD_LI2_HEO_3d_10s10t_s01.LEVER'
+% H2B = 3;
+% ERK = 2;
+% Oracle = 1;
+
+
+strDB = '/f/leverjs/Parsons/May17_2022/mcf7 erk ktr on/mcf7 erk ktr on_s01.LEVER'
+ERK = 1;
+H2B = 2;
+targetChannel = ERK;
+
+[conn,CONSTANTS,segParams]=openDB(strDB);
+[~,dsName,~] = fileparts(strDB);
+dsName = [dsName '_erk'];
+% need better naming convention! ACK
+outfolder = ['./tiffs_' dsName];
+prefix = 'erk_log_';
+if ~exist(outfolder,'dir')
+ mkdir(outfolder)
+end
+
+% clip limits
+im = MicroscopeData.Reader('imageData',CONSTANTS.imageData, 'chanList',...
+ targetChannel,'timeRange',[1,1], 'outType','uint16','prompt',false);
+clipMax = double(max(im(:)));
+clipMin = double(min(im(:)));
+
+
+parfor t=1:CONSTANTS.imageData.NumberOfFrames
+
+ cx=openDB(strDB);
+ cellList = Read.getCellsTime(cx,t,H2B,CONSTANTS);
+ close(cx);
+
+ if ~is3D(CONSTANTS)
+ d = 2;
+ sz_um = CONSTANTS.imageData.PixelPhysicalSize(1:2);
+ else
+ d=3;
+ sz_um = CONSTANTS.imageData.PixelPhysicalSize;
+ end
+ rCell_pixels = cellfun(@(x) (sqrt(d) .* std(double(x))),{cellList.pts},'UniformOutput',false);
+ rCell_um = cellfun(@(x) norm(x .* sz_um),rCell_pixels);
+ aCell_pixels = cellfun(@length,{cellList.pts});
+
+ r0 = segParams.minimumRadius_um(1); %min(rCell_um);
+ r1 = segParams.minimumRadius_um(3); %median(rCell_um);
+ rTarget_um = linspace(r0,r1,20);
+ im = MicroscopeData.Reader('imageData',CONSTANTS.imageData, 'chanList',...
+ targetChannel,'timeRange',[t t], 'outType','uint16','prompt',false);
+ im = double(im);
+ im = (im-clipMin)./(clipMax-clipMin);
+ im = im - median(im(:));
+ im = max(im,0);
+ im = min(im,1);
+ im = Segment.denoise(im,segParams,false);
+ bw = imbinarize(im,'adaptive');
+ bw = imfill(bw,'holes');
+
+ imp = [];
+ if is3D(im)
+ rdim = 4;
+ else
+ rdim = 3;
+ end
+ imn = []; % h2b wants imn
+ bwp = [];
+ for rr=1:length(rTarget_um)
+ sp = segParams;
+ sp.minimumRadius_um = rTarget_um(rr);
+ [~,imp_rr,imn_rr] = LoG.getCompositeLoG(im,CONSTANTS,sp);
+ imp = cat(rdim,imp,imp_rr);
+ imn = cat(rdim,imn,imn_rr);
+ end
+ imp_max = max(imp,[],3);
+ imn_max = max(imn,[],3);
+
+ if H2B == targetChannel
+ imp_max = imn_max; % capture h2b
+ end
+
+
+ im_segLoG = 0 * im;
+ for i=1:length(cellList)
+% if length(find(bw(cellList(i).idxPts))) < 0.5*length(cellList(i).idxPts)
+% continue;
+% end
+ if sum(imp_max(cellList(i).idxPts)) < sum(imn_max(cellList(i).idxPts))
+ continue
+ end
+ im_segLoG(cellList(i).idxPts) = imp_max(cellList(i).idxPts);
+ end
+ rp = regionprops(logical(im_segLoG),'MajorAxisLength','MinorAxisLength','PixelIdxList','Area','ConvexArea');
+ ecc = [rp.MinorAxisLength]./[rp.MajorAxisLength];
+ cd = [rp.Area]./[rp.ConvexArea];
+ idxReset = find(ecc<0.25 | cd<0.5);
+ if ~isempty(idxReset)
+ pixelIdxReset=vertcat(rp(idxReset).PixelIdxList);
+ % [r,c] = ind2sub(size(im),pixelIdxReset);
+ % hold on;plot(c,r,'.r')
+ im_segLoG(pixelIdxReset)=0;
+ end
+ im_segLoG = mat2gray(im_segLoG);
+ vbar = 0.33 * ones(size(im,1),5,3);
+
+ if H2B == targetChannel
+ imcx = Helpers.imTransfer(mat2gray(im),[0,1,0.5]);
+ else
+ imcx = im; %
+ end
+ imc = [];
+ imc(:,:,1)=0*im;
+ imc(:,:,2)=mat2gray(imcx);
+ imc(:,:,3)=imc(:,:,2);
+
+ if H2B == targetChannel
+ imlx = Helpers.imTransfer(mat2gray(im_segLoG),[0,1,0.5]);
+ else
+ imlx = im_segLoG; %
+ end
+% imlc = [];
+% imlc(:,:,1)=imlx;
+% imlc(:,:,2)=imlx;
+% imlc(:,:,3)=imlx;
+ imlc = ind2rgb(gray2ind(imlx,255),hot(255));
+
+ imOut = [imc,vbar,imlc];
+
+
+% imOut = mat2gray([im,vbar,im_segLoG]);
+
+% figure(1);imagesc(imOut);axis image
+% title(num2str(t))
+% drawnow
+
+ fname = fullfile(outfolder,[prefix num2str(t) '.tif']);
+ imwrite(imOut,fname);
+end
diff --git a/matlab/+LoG/principalEllipse.m b/matlab/+LoG/principalEllipse.m
new file mode 100644
index 0000000000000000000000000000000000000000..30872627d84c853f6433d7013707274cd9d401a1
--- /dev/null
+++ b/matlab/+LoG/principalEllipse.m
@@ -0,0 +1,41 @@
+function [rcz, imref, idxRef, rProjected] = principalEllipse(projectedPts)
+
+% compute axes in SVD space
+rProjected = (max(projectedPts)-min(projectedPts)) / 2;
+
+if size(projectedPts,2)==2
+ b3D = false;
+ rProjected(3) = 0;
+else
+ b3D = true;
+end
+imref_small = HIP.MakeEllipsoidMask(rProjected);
+refCenterSmall = size(imref_small)/2;
+sz = 6.*ceil(rProjected);
+
+if b3D
+ idxRef = find(imref_small);
+ [r,c,z] = ind2sub(size(imref_small),idxRef);
+else
+ [r,c] = find(imref_small);
+ sz(3)=[];
+end
+
+refCenter = sz/2;
+imref = zeros(sz);
+
+if b3D
+ idxRef = sub2ind(size(imref),round(r+refCenter(1)-refCenterSmall(1)),...
+ round(c+refCenter(2)-refCenterSmall(2)),...
+ round(z+refCenter(3)-refCenterSmall(3)));
+ imref(idxRef)=1;
+ [r,c,z] = ind2sub(size(imref),idxRef);
+ rcz = [r,c,z];
+else
+ idxRef = sub2ind(size(imref),round(r+refCenter(1)-refCenterSmall(1)),...
+ round(c+refCenter(2)-refCenterSmall(2)));
+ imref(idxRef)=1;
+ [r,c] = ind2sub(size(imref),idxRef);
+ rcz = [r,c];
+end
+rcz = rcz - size(imref)./2 - 1;
diff --git a/matlab/+LoG/referenceLoG.m b/matlab/+LoG/referenceLoG.m
index dacd10bc1b862c2e2346ff4ea57846fbebaf9858..1ab3a99c5dc7c5edb02f376d749127f78ec41a5f 100644
--- a/matlab/+LoG/referenceLoG.m
+++ b/matlab/+LoG/referenceLoG.m
@@ -1,53 +1,33 @@
-function cellScore = referenceLoG(im,CONSTANTS,targetCell,segParams)
+function [cellScore] = referenceLoG(im,imLoG,CONSTANTS,targetCell,cacheReferenceLoG)
cellScore = 0;
-% targetRadius = std(targetCell.pts);
-targetRadius = max(segParams.minimumRadius_um);
-targetRadius = repmat(targetRadius,[1,3]);
-sz=5*ceil(max(targetCell.maxRadius,targetRadius));
-refCenter=round(sz/2);
-
-if is3D(im)
- targetRadius = 1/sqrt(3) * targetRadius;
- imref=zeros(sz);
- targetCentroid = targetCell.centroid;
+targetPts = double(targetCell.pts);
+targetPts = targetPts - mean(targetPts);
+[U,S,V] = svd(targetPts,'econ');
+projectedPts = targetPts * V;
+rProjected = (max(projectedPts)-min(projectedPts)) / 2;
+if size(projectedPts,2)==2
+ b3D = false;
+ rProjected = [min(rProjected),max(rProjected),0];
else
- imref=zeros(sz(1:2));
- targetRadius = 1/sqrt(2) * targetRadius;
- targetRadius(3) = 0;
- refCenter = refCenter(1:2);
- targetCentroid = targetCell.centroid(1:2);
-end
-targetCell = Read.setCellsIdxPts(targetCell,CONSTANTS);
-for y=1:size(imref,1)
- for x=1:size(imref,2)
- d = sqrt((y-refCenter(1))^2 + (x-refCenter(2))^2);
- if d<targetRadius(1) % ACK -- get a super-ellipse!
- imref(y,x)=1;
- end
- end
+ b3D = true;
+ % yikes TODO
end
-imRefLoG = HIP.LoG(imref,targetRadius,[]);
-imLoG = HIP.LoG(im,targetRadius,[]);
-
-% match smaller ref image to full size imLoG
-targetCentroid = repmat(targetCentroid,[size(targetCell.pts,1),1]);
-refOffset = targetCell.pts - targetCentroid + refCenter;
-refOffset = round(refOffset);
-srcIdx = sub2ind(size(imRefLoG),refOffset(:,1),refOffset(:,2));
-
-% cell score is NOT sum of square difference - 'cause...
-% ACK check for idx out of range...
-sourceStats = [mean(imLoG(targetCell.idxPts)), std(imLoG(targetCell.idxPts))];
-refStats = [mean(imRefLoG(srcIdx )), std(imRefLoG(srcIdx ))];
-
-% % use Fisher Discrim Dist
-% d = (sourceStats(1) - refStats(1)).^2 / (sourceStats(2) + refStats(2));
-% cellScore = 1-d;
+d = pdist2(vertcat(cacheReferenceLoG.radius),rProjected);
+[~,idx] = min(d);
+imref = cacheReferenceLoG(idx).imf;
+% projected points on reference image
+refProjectedPts = round(projectedPts + size(imref)./2);
+if is3D(CONSTANTS)
+ idxRefProjected = sub2ind(size(imref),refProjectedPts(:,1),refProjectedPts(:,2),refProjectedPts(:,3));
+else
+ idxRefProjected = sub2ind(size(imref),refProjectedPts(:,1),refProjectedPts(:,2));
+end
+imref = imref .* mean(im(targetCell.idxPts));
+% compute MAD
+cellScore = 1- mean( abs( imLoG(targetCell.idxPts) - imref(idxRefProjected) ) );
+4;
-% ok maybe it is MAD
-cellScore = 1- mean(abs(imLoG(targetCell.idxPts) - imRefLoG(srcIdx)));
-4;
\ No newline at end of file
diff --git a/matlab/+LoG/sampleCell.m b/matlab/+LoG/sampleCell.m
new file mode 100644
index 0000000000000000000000000000000000000000..626561c0fd339bfffc09c948d0b2769c613f80e3
--- /dev/null
+++ b/matlab/+LoG/sampleCell.m
@@ -0,0 +1,13 @@
+function cval = sampleCell(newCell,CONSTANTS,imLoG)
+center = round(newCell.centroid);
+
+if is3D(imLoG)
+ center = min(center,CONSTANTS.imageData.Dimensions);
+ center = max(center, [1,1,1]);
+ cval = imLoG(center(2),center(1),center(3));
+else
+ center = center(1:2);
+ center = min(center,CONSTANTS.imageData.Dimensions(1:2));
+ center = max(center, [1,1]);
+ cval = imLoG(center(2),center(1));
+end
diff --git a/matlab/+LoG/separateLoG.m b/matlab/+LoG/separateLoG.m
index 5f7d1a664f236aa2d3f735c74fdd1ac16aa30ebb..9b7516c07fb9e38d0e7f844d2858cb48e8195d6f 100644
--- a/matlab/+LoG/separateLoG.m
+++ b/matlab/+LoG/separateLoG.m
@@ -1,19 +1,24 @@
-function [imc, imp, imn] = separateLoG(imf)
+% returns color separated LoG
+% imc is scaled, as with leverjs transfer function [dark,medium,bright]
+function [imc, imp, imn] = separateLoG(imf,transfer)
+if ~exist('transfer','var')
+ transfer = [0,1,0.125];
+end
imp=imf;
imp(imp<0)=0;
imn=imf;
imn(imn>0)=0;
imn=abs(imn);
-imp1=mat2gray(imp);
-imn1=mat2gray(imn);
+imp1=Helpers.imTransfer(imp,transfer);
+imn1=Helpers.imTransfer(imn,transfer);
if is3D(imf)
imc(:,:,:,1)=imp1;
imc(:,:,:,2)=imn1;
- imc(:,:,:,3)=0*imf;
else
+ % 3 channels - pack to rgb 2-D
imc(:,:,1)=imp1;
imc(:,:,2)=imn1;
imc(:,:,3)=0*imf;
diff --git a/matlab/+LoG/show5d.m b/matlab/+LoG/show5d.m
new file mode 100644
index 0000000000000000000000000000000000000000..f04c2eec40babb564f3704f9dc83b4ef576b2dcd
--- /dev/null
+++ b/matlab/+LoG/show5d.m
@@ -0,0 +1,31 @@
+% write a 5d lever file for this image
+
+strDB = '/f/leverjs/Olivier/Yannick/20210924/20210924_pos3.LEVER';
+[conn,CONSTANTS,segParams] = openDB(strDB);
+rEval = [0.5:0.25:6];
+[~,dsName,~] = fileparts(strDB);
+datasetName = [dsName '_LoG_' mat2str([rEval(1),length(rEval),rEval(end)])];
+datasetName = strrep(datasetName,' ','_');
+datasetName = strrep(datasetName,'[','');
+datasetName = strrep(datasetName,']','');
+
+outfolder = '/f/leverjs/andy';
+if ~exist(outfolder,'dir')
+ mkdir(outfolder);
+end
+h5file = [fullfile(outfolder,datasetName) '.h5'];
+t = CONSTANTS.imageData.NumberOfFrames
+logStack = [];
+for rr = 1:length(rEval)
+ segParams.minimumRadius_um=rEval(rr);
+ [im,imLoG] = DenoiseCache.readImages(t,CONSTANTS,segParams);
+
+ [~, imp, imn] = LoG.separateLoG(imLoG);
+ logStack(:,:,rr,1,1) = imp;
+ logStack(:,:,rr,2,1) = imn;
+end
+imd = Import.makeMetaData(logStack);
+imd.ChannelNames={'LoG+','LoG-'};
+
+leversc(im,imd)
+
diff --git a/matlab/+LoG/write_5d.m b/matlab/+LoG/write_5d.m
new file mode 100644
index 0000000000000000000000000000000000000000..bac38575fbe1aca67c919f33ca53a46976b30035
--- /dev/null
+++ b/matlab/+LoG/write_5d.m
@@ -0,0 +1,41 @@
+% write a 5d lever file for this image
+
+% strDB = '/f/leverjs/Olivier/Yannick/20210924/20210924_pos3.LEVER';
+% [conn,CONSTANTS,segParams] = openDB(strDB);
+rEval = [1:0.25:4];
+[~,dsName,~] = fileparts(strDB);
+datasetName = [dsName '_h2b__LoG_' mat2str([rEval(1),length(rEval),rEval(end)])];
+datasetName = strrep(datasetName,' ','_');
+datasetName = strrep(datasetName,'[','');
+datasetName = strrep(datasetName,']','');
+datasetName = strrep(datasetName,'.','x');
+
+outfolder = '/f/leverjs/andy';
+if ~exist(outfolder,'dir')
+ mkdir(outfolder);
+end
+ljsStartParallel(24);
+h5file = [fullfile(outfolder,datasetName) '.h5'];
+for t = 1 : 1 %CONSTANTS.imageData.NumberOfFrames
+ logStack = [];
+ imp=[];
+ imn=[];
+ parfor rr = 1:length(rEval)
+ sp = segParams;
+ sp.minimumRadius_um=rEval(rr);
+ [im,imLoG] = DenoiseCache.readImages(t,CONSTANTS,sp);
+ [~, imp(:,:,rr), imn(:,:,rr)] = LoG.separateLoG(imLoG);
+ end
+ logStack(:,:,:,1,1) = imp;
+ logStack(:,:,:,2,1) = imn;
+
+ if 1==t
+ imageData = Import.makeMetaData(logStack);
+ imageData.DatasetName = datasetName;
+ imageData.ChannelNames = {'LoG+','LoG-'};
+ imageData.NumberOfFrames = CONSTANTS.imageData.NumberOfFrames;
+ Import.prepareH5(h5file,imageData);
+ end
+ Import.appendH5Frame(h5file,logStack,t);
+end
+Import.leverImport('',outfolder);
\ No newline at end of file
diff --git a/matlab/+MovieMaker/goFigureAnimation.m b/matlab/+MovieMaker/goFigureAnimation.m
index 7a6c8ad7a49e49f3f2d21a2421096653a218a950..cdf3798843e633a891c9d5badf6a6c94d5c25a7e 100644
--- a/matlab/+MovieMaker/goFigureAnimation.m
+++ b/matlab/+MovieMaker/goFigureAnimation.m
@@ -3,7 +3,7 @@
% periodicity toggle? if true remove final frame
% changing number of inbetweens to speed up or slow down the animation
-fileName = 'coralGraph'; % name of movie generated
+fileName = 'ssfClustering'; % name of movie generated
frameRate = 30; % desired frame rate
duration = 30; % desired length of movie in seconds
azimuthList = [-20,-110,-190,-290,-380]; % camera pan angle at key frames
@@ -46,4 +46,4 @@ for frame = 1:size(angleList,1)
writeVideo(v,getframe(gcf));
end
-close(v);
\ No newline at end of file
+close(v);
diff --git a/matlab/+MovieMaker/printLoG.m b/matlab/+MovieMaker/printLoG.m
new file mode 100644
index 0000000000000000000000000000000000000000..5c9e4d3c136d3fa3e48fba776dd003e1d16ca770
--- /dev/null
+++ b/matlab/+MovieMaker/printLoG.m
@@ -0,0 +1,41 @@
+% strDB ='/f/leverjs/Olivier/Yannick/20210924/20210924_pos2.LEVER'
+strDB = '/f/leverjs/Olivier/Yannick/April_12_2021/20210129_20x_SD_LI2_HEO_3d_10s10t*20210129_20x_SD_LI2_HEO_3d_10s10t_s01.LEVER'
+[conn,CONSTANTS,segParams]=openDB(strDB);
+rEval = [1,0.2,4];
+
+[~,dsName,~] = fileparts(strDB);
+outfolder = ['./tiffs_' dsName];
+
+if ~exist(outfolder,'dir')
+ mkdir(outfolder)
+end
+
+H2B_CHANNEL = 3;
+ERK_CHANNEL = 2;
+Oracle_CHANNEL = 1;
+
+prefix = '';
+for t=1:CONSTANTS.imageData.NumberOfFrames
+ % ACK !!! denoise?
+ [im,CONSTANTS] = leversc.loadImage(strDB,t,H2B_CHANNEL);
+ im = leversc.loadImage(strDB,t,H2B_CHANNEL);
+ im = mat2gray(im);
+ imLoG = LoG.getCombinedGradients(im,CONSTANTS,rEval);
+ imc_H2B = LoG.separateLoG(imLoG);
+
+ [im,CONSTANTS] = leversc.loadImage(strDB,t,ERK_CHANNEL);
+ im = mat2gray(im);
+ imLoG = LoG.getCombinedGradients(im,CONSTANTS,rEval);
+ imc_ERK = LoG.separateLoG(imLoG);
+
+ [im,CONSTANTS] = leversc.loadImage(strDB,t,Oracle_CHANNEL);
+ im = mat2gray(im);
+ imLoG = LoG.getCombinedGradients(im,CONSTANTS,rEval);
+ imc_Oracle = LoG.separateLoG(imLoG);
+
+ vbar = 0.33* ones(size(im,1),5,3);
+ imc = double([imc_H2B,vbar,imc_ERK,vbar,imc_Oracle]);
+
+ fname = fullfile(outfolder,[prefix num2str(t) '.tif']);
+ imwrite(imc,fname);
+end
diff --git a/matlab/+MovieMaker/ssfMovie1.m b/matlab/+MovieMaker/ssfMovie1.m
new file mode 100644
index 0000000000000000000000000000000000000000..87cea0b80da17d901b371e372d38215d4de861be
--- /dev/null
+++ b/matlab/+MovieMaker/ssfMovie1.m
@@ -0,0 +1,127 @@
+% called from breakpoint on Segment.frameSegment after cleanLoG
+% strDB = '/g/leverjs/Olivier/mcf10a_3d_LoG/190827_wt_stage_1_00_movieS1.LEVER';
+function ssfMovie1(im,bwLoG_pos,bwLoG_neg)
+
+bPreview = false
+
+bwx = bwLoG_pos;
+bwx(:,:,:,2) = bwLoG_neg;
+imd = MicroscopeData.MakeMetadataFromImage(bwx);
+imd.PixelPhysicalSize = [0.3700 0.3700 0.6000];
+lsc = leversc(bwx,imd);
+
+
+
+ %% Set up pre-selected render properties
+ %% Disable most UI elements
+ lsc.uiParams.time='none';
+ lsc.uiParams.sidebar='none';
+ lsc.uiParams.clockButton='none';
+ lsc.uiParams.webToolbar='none';
+
+ %% Reset view parameters (also set background to black)
+ lsc.viewParams.clipMode = 0;
+ lsc.viewParams.worldRot = reshape([1,0,0,0; 0,1,0,0; 0,0,1,0; 0,0,0,1], 16,1);
+ lsc.viewParams.zoom = 0;
+ lsc.viewParams.bgColor = [0,0,0];
+
+ if ( ~bPreview )
+ movieFile='h2b_ssf_movie1.avi';
+ vidWrite=VideoWriter(movieFile,'Motion JPEG AVI');
+ vidWrite.FrameRate=10;
+ open(vidWrite)
+ end
+
+ %% Rotate 360 around in 15sec
+ angles = linspace(0,360,150);
+ for i=2:length(angles)
+ ry=[cosd(angles(i)), 0, sind(angles(i)),0;
+ 0,1,0,0;
+ -sind(angles(i)),0,cosd(angles(i)),0;
+ 0,0,0,1];
+
+ worldRot=ry;
+ lsc.viewParams.worldRot=worldRot(:);
+
+ lsc.renderParams(1).alpha=1;
+ lsc.uiParams.logoDiv='';
+ lsc.uiParams.scalebar=false;
+ lsc.renderParams(1).medium=1;
+ lsc.show(im);
+ imRaw = get_rendered_frame(lsc);
+
+ lsc.renderParams(1).alpha=0.02;
+ lsc.uiParams.logoDiv='none';
+ lsc.uiParams.scalebar=true;
+ lsc.renderParams(1).medium=0.5;
+ lsc.show(bwx);
+ imX = get_rendered_frame(lsc);
+
+ imCap = [imRaw,128*ones(size(imRaw,1),5,3),imX];
+ if ( bPreview )
+ imagesc(imCap);
+ axis image;
+ drawnow();
+ else
+ writeVideo(vidWrite,imCap);
+ end
+ end
+
+ % Padding for 0.2 sec
+ if ( ~bPreview )
+ writeVideo(vidWrite,imCap);
+ writeVideo(vidWrite,imCap);
+ end
+
+ %% Put sample plane at the back of the volume and set to planar clipping mode,
+ %% then animate plane movement into just back from center
+ % in 10 seconds
+ planeZs = linspace(0,35, 100);
+ lsc.viewParams.planeCenter(3) = planeZs(1);
+ lsc.viewParams.clipMode = 1; % Plane-clipping mode
+ for i=1:length(planeZs)
+ lsc.viewParams.planeCenter(3) = planeZs(i);
+
+ lsc.uiParams.logoDiv='';
+ lsc.uiParams.scalebar=false;
+ lsc.renderParams(1).medium=1;
+ lsc.renderParams(1).alpha=1;
+ lsc.show(im);
+ imRaw = get_rendered_frame(lsc);
+
+ lsc.uiParams.logoDiv='none';
+ lsc.uiParams.scalebar=true;
+ lsc.renderParams(1).medium=0.5;
+ lsc.renderParams(1).alpha=0.02;
+ lsc.show(bwx);
+ imX = get_rendered_frame(lsc);
+
+ imCap = [imRaw,128*ones(size(imRaw,1),5,3),imX];
+ if ( bPreview )
+ imagesc(imCap);
+ axis image;
+ drawnow();
+ else
+ writeVideo(vidWrite,imCap);
+ end
+ end
+
+ % Padding for 0.2 sec
+ if ( ~bPreview )
+ writeVideo(vidWrite,imCap);
+ writeVideo(vidWrite,imCap);
+ end
+
+ if ( ~bPreview )
+ close(vidWrite)
+ end
+end
+
+function im = get_rendered_frame(lsc)
+ % We need to poll for draw-complete in order to avoid timeouts
+ while ~lsc.drawComplete()
+ pause(0.1);
+ end
+ im=lsc.captureImage();
+end
+
diff --git a/matlab/+MovieMaker/ssfMovie_erk.m b/matlab/+MovieMaker/ssfMovie_erk.m
new file mode 100644
index 0000000000000000000000000000000000000000..7b850a4a63f18275100ecfa88c7c70371e62c495
--- /dev/null
+++ b/matlab/+MovieMaker/ssfMovie_erk.m
@@ -0,0 +1,128 @@
+% called from breakpoint on Segment.frameSegment after cleanLoG
+% strDB = '/g/leverjs/Olivier/mcf10a_3d_LoG/190827_wt_stage_1_00_movieS1.LEVER';
+function ssfMovie1(strDB)
+
+bPreview = true
+
+
+bwx = bwLoG_pos;
+bwx(:,:,:,2) = bwLoG_neg;
+imd = MicroscopeData.MakeMetadataFromImage(bwx);
+imd.PixelPhysicalSize = [0.3700 0.3700 0.6000];
+lsc = leversc(bwx,imd);
+
+
+
+ %% Set up pre-selected render properties
+ %% Disable most UI elements
+ lsc.uiParams.time='none';
+ lsc.uiParams.sidebar='none';
+ lsc.uiParams.clockButton='none';
+ lsc.uiParams.webToolbar='none';
+
+ %% Reset view parameters (also set background to black)
+ lsc.viewParams.clipMode = 0;
+ lsc.viewParams.worldRot = reshape([1,0,0,0; 0,1,0,0; 0,0,1,0; 0,0,0,1], 16,1);
+ lsc.viewParams.zoom = 0;
+ lsc.viewParams.bgColor = [0,0,0];
+
+ if ( ~bPreview )
+ movieFile='h2b_ssf_movie1.avi';
+ vidWrite=VideoWriter(movieFile,'Motion JPEG AVI');
+ vidWrite.FrameRate=10;
+ open(vidWrite)
+ end
+
+ %% Rotate 360 around in 15sec
+ angles = linspace(0,360,150);
+ for i=2:length(angles)
+ ry=[cosd(angles(i)), 0, sind(angles(i)),0;
+ 0,1,0,0;
+ -sind(angles(i)),0,cosd(angles(i)),0;
+ 0,0,0,1];
+
+ worldRot=ry;
+ lsc.viewParams.worldRot=worldRot(:);
+
+ lsc.renderParams(1).alpha=1;
+ lsc.uiParams.logoDiv='';
+ lsc.uiParams.scalebar=false;
+ lsc.renderParams(1).medium=1;
+ lsc.show(im);
+ imRaw = get_rendered_frame(lsc);
+
+ lsc.renderParams(1).alpha=0.02;
+ lsc.uiParams.logoDiv='none';
+ lsc.uiParams.scalebar=true;
+ lsc.renderParams(1).medium=0.5;
+ lsc.show(bwx);
+ imX = get_rendered_frame(lsc);
+
+ imCap = [imRaw,128*ones(size(imRaw,1),5,3),imX];
+ if ( bPreview )
+ imagesc(imCap);
+ axis image;
+ drawnow();
+ else
+ writeVideo(vidWrite,imCap);
+ end
+ end
+
+ % Padding for 0.2 sec
+ if ( ~bPreview )
+ writeVideo(vidWrite,imCap);
+ writeVideo(vidWrite,imCap);
+ end
+
+ %% Put sample plane at the back of the volume and set to planar clipping mode,
+ %% then animate plane movement into just back from center
+ % in 10 seconds
+ planeZs = linspace(0,35, 100);
+ lsc.viewParams.planeCenter(3) = planeZs(1);
+ lsc.viewParams.clipMode = 1; % Plane-clipping mode
+ for i=1:length(planeZs)
+ lsc.viewParams.planeCenter(3) = planeZs(i);
+
+ lsc.uiParams.logoDiv='';
+ lsc.uiParams.scalebar=false;
+ lsc.renderParams(1).medium=1;
+ lsc.renderParams(1).alpha=1;
+ lsc.show(im);
+ imRaw = get_rendered_frame(lsc);
+
+ lsc.uiParams.logoDiv='none';
+ lsc.uiParams.scalebar=true;
+ lsc.renderParams(1).medium=0.5;
+ lsc.renderParams(1).alpha=0.02;
+ lsc.show(bwx);
+ imX = get_rendered_frame(lsc);
+
+ imCap = [imRaw,128*ones(size(imRaw,1),5,3),imX];
+ if ( bPreview )
+ imagesc(imCap);
+ axis image;
+ drawnow();
+ else
+ writeVideo(vidWrite,imCap);
+ end
+ end
+
+ % Padding for 0.2 sec
+ if ( ~bPreview )
+ writeVideo(vidWrite,imCap);
+ writeVideo(vidWrite,imCap);
+ end
+
+ if ( ~bPreview )
+ close(vidWrite)
+ end
+end
+
+function im = get_rendered_frame(lsc)
+ % We need to poll for draw-complete in order to avoid timeouts
+ while ~lsc.drawComplete()
+ pause(0.1);
+ end
+ im=lsc.captureImage();
+end
+
diff --git a/matlab/+MovieMaker/ssfRatio.m b/matlab/+MovieMaker/ssfRatio.m
new file mode 100644
index 0000000000000000000000000000000000000000..3e95c3df505e03e7988234b3afaab24cab8d6b54
--- /dev/null
+++ b/matlab/+MovieMaker/ssfRatio.m
@@ -0,0 +1,43 @@
+strDB = '/f/leverjs/Olivier/Yannick/April_12_2021/20210129_20x_SD_LI2_HEO_3d_10s10t/20210129_20x_SD_LI2_HEO_3d_10s10t_s01.LEVER';
+[conn,CONSTANTS,segParams]=openDB(strDB);
+outfolder = './tiffs/';
+if ~exist(outfolder,'dir')
+ mkdir(outfolder)
+end
+
+cmd = 'select max(erkRatio) as erk_max,min(erkRatio) as erk_min from tblCellFeatures';
+q = fetch(conn,cmd);
+erk_max = q.erk_max;
+erk_min = q.erk_min;
+
+erk_min = 1.0;
+erk_max = 2.5;
+
+erk_channel = 2;
+for t=1:CONSTANTS.imageData.NumberOfFrames
+ im = MicroscopeData.Reader('imageData',CONSTANTS.imageData, 'chanList',erk_channel,'timeRange',[t t], 'outType','double','prompt',false);
+ im = Segment.denoise(im,segParams,false);
+ cellList = Read.getCellsTime(conn,t,segParams.channels(1),CONSTANTS);
+ imBlob = 0*im;
+
+ ids = Helpers.sqlEncodeVector([cellList.cellID]);
+ cmd = ['select cellID,erkRatio from tblCellFeatures where cellID in ' ids];
+ q=fetch(conn,cmd);
+
+ for i=1:length(cellList)
+ idx = find(q.cellID == cellList(i).cellID);
+ fval = q.erkRatio(idx);
+ fval = min(fval,erk_max);
+ fval = max(fval,erk_min);
+ fval = (fval - erk_min) / (erk_max - erk_min);
+ imBlob(cellList(i).idxPts) = fval;
+ end
+ outname = fullfile(outfolder,['ratio_' num2str(t),'.tiff']);
+ imBlob = double(imBlob);
+ imwrite(imBlob,outname);
+
+% outname = fullfile(outfolder,['raw_' num2str(t),'.tiff']);
+% imwrite(im,outname);
+ t
+end
+close(v)
\ No newline at end of file
diff --git a/matlab/+MovieMaker/ssf_2d_movie.m b/matlab/+MovieMaker/ssf_2d_movie.m
new file mode 100644
index 0000000000000000000000000000000000000000..9a8226fc45574aa4db91a2a1909cd22b0885a520
--- /dev/null
+++ b/matlab/+MovieMaker/ssf_2d_movie.m
@@ -0,0 +1,45 @@
+% strDB = '/f/leverjs/Olivier/Yannick/April_12_2021/20210129_20x_SD_LI2_HEO_3d_10s10t/20210129_20x_SD_LI2_HEO_3d_10s10t_s01.LEVER';
+strDB = '/f/leverjs/Olivier/Agne/2022-06-04_ibidi-insert-setup1/2022-06-04_ibidi-insert-setup1_37.LEVER'
+[conn,CONSTANTS,segParams]=openDB(strDB);
+outfolder = './tiffs/';
+if ~exist(outfolder,'dir')
+ mkdir(outfolder)
+end
+
+refMax = 0.7; % from cacheReferenceLoG
+erk_channel = 1;
+h2b_channel = 3;
+for t=1:CONSTANTS.imageData.NumberOfFrames
+ im = MicroscopeData.Reader('imageData',CONSTANTS.imageData, 'chanList',erk_channel,'timeRange',[t t], 'outType','uint16','prompt',false);
+ im = Segment.denoise(im,segParams,false);
+ im = double(im)./2^16;
+ [imLoG, imp, imn] = LoG.getCompositeLoG(im,CONSTANTS,segParams);
+ imMax = max(im(:));
+ cellList = Read.getCellsTime(conn,t,segParams.channels(1),CONSTANTS);
+ imBlob = 0*im;
+ for i=1:length(cellList)
+ cx = round(cellList(i).centroid);
+ val = imp(cx(2),cx(1));
+ % 0 nucleus against 1 cytoplasm for erk activation
+ % so use complement of intensity in scaling ref
+ refVal = (imMax-max(im(cellList(i).idxPts))).*refMax;
+ refVal = min(refVal,1);
+ refVal = max(refVal,0);
+ imBlob(cellList(i).idxPts) = val./refVal;
+ end
+
+ imBlob = gray2ind(imBlob,256);
+ imBlob = ind2rgb(imBlob,parula(256));
+ im = gray2ind(im,256);
+ im = ind2rgb(im,gray(256));
+
+ im_h2b = MicroscopeData.Reader('imageData',CONSTANTS.imageData, 'chanList',h2b_channel,'timeRange',[t t], 'outType','uint16','prompt',false);
+ im_h2b = double(im_h2b)./2^16;
+ im(:,:,2) = im(:,:,2) + im_h2b;
+ im(:,:,3) = im(:,:,3) + im_h2b;
+ im = min(im,1);
+ imOut = [im,ones(size(im,1),5,3),imBlob];
+ outname = fullfile(outfolder,[num2str(t),'.tiff']);
+ imwrite(imOut,outname)
+ t
+end
diff --git a/matlab/+MovieMaker/tiffs2movie.m b/matlab/+MovieMaker/tiffs2movie.m
new file mode 100644
index 0000000000000000000000000000000000000000..1bdba4d5587b3a25b11562240a90a1c07ad2f7c3
--- /dev/null
+++ b/matlab/+MovieMaker/tiffs2movie.m
@@ -0,0 +1,34 @@
+
+strDB = '/f/leverjs/Olivier/Yannick/April_12_2021/20210129_20x_SD_LI2_HEO_3d_10s10t/20210129_20x_SD_LI2_HEO_3d_10s10t_s01.LEVER';
+[conn,CONSTANTS,segParams]=openDB(strDB);
+outfolder = './tiffs/';
+
+v = VideoWriter('20210129_20x_SD_LI2_HEO_3d_10s10t_erk_ssf_nlm.avi');
+open(v);
+
+for t=1:CONSTANTS.imageData.NumberOfFrames
+ fname = fullfile(outfolder,[num2str(t),'.tiff']);
+ if ~exist(fname,'file')
+ break
+ end
+ im = imread(fname);
+ hold off;imshow(im); hold on; axis image;axis off; colormap default
+ % scale bar
+ [nPixels,microns] = Helpers.scaleBar(CONSTANTS);
+ rectangle('Position',[size(im,2)-50-nPixels,50,nPixels,25],'FaceColor','w');
+ text(size(im,2)-50-nPixels,75,[num2str(microns) '\mum'],'color','w','VerticalAlignment','top','fontsize',8)
+ % time
+ % time
+ tout = t - 1;
+ hours = floor(tout / 12);
+ minutes = mod(tout, 12)*5;
+ text(50,50,[num2str(hours) ' : ' num2str(minutes)],'color','w','fontsize',8);
+ drawnow
+
+ f = getframe()
+ writeVideo(v,f);
+
+
+end
+
+close(v)
\ No newline at end of file
diff --git a/matlab/+Read/findImageFolder.m b/matlab/+Read/findImageFolder.m
index 7c77d95bca10871e33666766a195b1325a6b1d0e..095c95256764feef690e5baef9c3b5acfcf0bebe 100644
--- a/matlab/+Read/findImageFolder.m
+++ b/matlab/+Read/findImageFolder.m
@@ -42,7 +42,7 @@ if ~exist(ljs,'file')
end
[fid,message]=fopen(fullfile(leverFolder,'lever.json'));
if (fid<=0)
- fprintf(1,'ERROR -- getConstants.m -- image path invalid and no lever.json ROOT override (message=%s)\n',message);
+ fprintf(1,'ERROR %s -- getConstants.m -- image path invalid and no lever.json ROOT override (message=%s)\n',CONSTANTS.imageData.DatasetName,message);
return;
end
diff --git a/matlab/+Read/getCell.m b/matlab/+Read/getCell.m
index 863eee99192a3e809fdefb9830f1a19080e65ea6..72e20413e3ab5dbb8e7d1d5f55b96588ec07e52c 100644
--- a/matlab/+Read/getCell.m
+++ b/matlab/+Read/getCell.m
@@ -1,13 +1,21 @@
-function Cell=getCell(conn,cellID)
+function Cell=getCell(conn,cellID,CONSTANTS)
Cell=[];
-
+qTable=fetch(conn,'pragma table_info(tblCells)');
+bLoG = any(cellfun(@length,(strfind(qTable.name,'LoG'))));
try
- cmd=['SELECT cellID,time,trackID,centroid,u16pixels,maxRadius,channel,area,surface,segCC '...
- ' FROM tblCells WHERE cellID=' num2str(cellID)];
+ cmd=['SELECT cellID,time,trackID,centroid,u16pixels,maxRadius,channel,area,surface,segCC '];
+ if bLoG
+ cmd = [cmd ' ,LoG '];
+ end
+ cmd =[cmd ' FROM tblCells WHERE cellID=' num2str(cellID)];
Q=ljsFetch(conn,cmd);
catch
- Cell=Read.getCell3D(conn,cellID);
+ try
+ Cell=Read.getCell3D(conn,cellID);
+ catch
+ fprintf(2,'unable to read cell from %s\n',CONSTANTS.imageData.DatasetName);
+ end
return
end
if isempty(Q)
@@ -28,3 +36,10 @@ Cell.area=Q{8};
Cell.surface=jsondecode(Q{9});
Cell.segCC=Q{10};
+if bLoG
+ Cell.LoG = Q{11};
+end
+if exist('CONSTANTS','var')
+ Cell = Read.setCellsIdxPts(Cell,CONSTANTS);
+end
+
diff --git a/matlab/+Read/getCell3D.m b/matlab/+Read/getCell3D.m
index c8d9b0b2919572c970b2b12b8a97fd08aee12e27..7ade71dea7999ec240c7d9df7a07f64cb5fd3126 100644
--- a/matlab/+Read/getCell3D.m
+++ b/matlab/+Read/getCell3D.m
@@ -1,8 +1,15 @@
-function Cell=getCell3D(conn,cellID)
+function Cell=getCell3D(conn,cellID,CONSTANTS)
Cell=[];
-cmd=['SELECT time,trackID,centroid,channel,area,maxRadius,verts,faces,edges,normals,u16pixels FROM tblCells WHERE cellID=' num2str(cellID)];
+qTable=fetch(conn,'pragma table_info(tblCells)');
+bLoG = any(cellfun(@length,(strfind(qTable.name,'LoG'))));
+
+cmd=['SELECT time,trackID,centroid,channel,area,maxRadius,verts,faces,edges,normals,u16pixels '];
+if bLoG
+ cmd = [cmd ',LoG '];
+end
+cmd = [cmd ' FROM tblCells WHERE cellID=' num2str(cellID)];
Q=ljsFetch(conn,cmd);
% cellid time trackID centroid channel area, maxRadius,
% verts,edges,normals,faces,u16pixels
@@ -27,12 +34,15 @@ Cell.edges=reshape(Cell.edges,2,[])';
Cell.normals=typecast(Q{10},'single');
Cell.normals=reshape(Cell.normals,3,[])';
-
points=Q{11};
points = typecast(points,'uint16');
points=reshape(points,3,[])';
Cell.pts=points;
+if exist('CONSTANTS','var')
+ Cell = Read.setCellsIdxPts(Cell,CONSTANTS);
+end
+
diff --git a/matlab/+SSF/catKymographs.m b/matlab/+SSF/catKymographs.m
new file mode 100644
index 0000000000000000000000000000000000000000..dbc4f2d70f775cd11f7a9f6532e2595af19f3ca5
--- /dev/null
+++ b/matlab/+SSF/catKymographs.m
@@ -0,0 +1,26 @@
+% pads time between images
+function i12 = catKymographs(i1,i2,dim)
+[i1,i2] = padIm(i1,i2);
+i12 = cat(dim,i1,i2);
+4;
+
+function [i1,i2] = padIm(i1,i2)
+
+if size(i1,3)>size(i2,3)
+ i2(:,:,end:size(i1,3),:)=0;
+else
+ i1(:,:,end:size(i2,3),:)=0;
+end
+
+if size(i1,2)>size(i2,2)
+ i2(:,end:size(i1,2),:,:)=0;
+else
+ i1(:,end:size(i2,2),:,:)=0;
+end
+
+if size(i1,1)>size(i2,1)
+ i2(end:size(i1,1),:,:,:)=0;
+else
+ i1(end:size(i2,1),:,:,:)=0;
+end
+
diff --git a/matlab/+SSF/cropKymo.m b/matlab/+SSF/cropKymo.m
new file mode 100644
index 0000000000000000000000000000000000000000..c86c14812892d6bd762924e73d6f8b84ce784d1e
--- /dev/null
+++ b/matlab/+SSF/cropKymo.m
@@ -0,0 +1,22 @@
+function im_crop = cropKymo(imSrc,idxPixels)
+
+% first copy over target pixels
+im = 0 * imSrc;
+im(idxPixels) = imSrc(idxPixels);
+
+[r,c,z]=ind2sub(size(im),idxPixels);
+
+r = cropDim(r,size(im,1));
+c = cropDim(c,size(im,2));
+z = cropDim(z,size(im,3));
+
+im_crop = im(min(r):max(r),min(c):max(c),min(z):max(z),:);
+
+
+function y = cropDim(x,sz)
+
+y = [min(x)-1:max(x)+1];
+y = min(y,sz);
+y = max(y,1);
+
+
diff --git a/matlab/+SSF/drawMitoticSSFtracks.m b/matlab/+SSF/drawMitoticSSFtracks.m
new file mode 100644
index 0000000000000000000000000000000000000000..d852790910a56a878784506820612d26d6e40fd7
--- /dev/null
+++ b/matlab/+SSF/drawMitoticSSFtracks.m
@@ -0,0 +1,57 @@
+% erk1D = Y(:,1);
+% [~,idxSort] = sort(erk1D);
+% qMitoSorted = qMitotic(idxSort,:);
+%
+function imx = drawMitoticSSFtracks(qMitotic,erkClipLimits,bDraw)
+
+if ~exist('bDraw','var')
+ bDraw = false;
+end
+
+for i = 1:height(qMitotic)
+ if ~isa(qMitotic.erk{i},'uint8')
+ qMitotic.erk{i} = SSF.quantize8(qMitotic.erk{i},erkClipLimits);
+ end
+end
+
+tmax = max(cellfun(@length,qMitotic.erk));
+imx = zeros(2*height(qMitotic),tmax);
+for i = 1:height(qMitotic)
+ erk_i = qMitotic.erk{i};
+ imx(2*i,end-length(erk_i)+1:end) = erk_i;
+end
+
+if ~bDraw
+ return
+end
+
+
+cmPos = colormap('parula');
+cmNeg = colormap('cool');
+cm = [cmNeg(1:2:end,:);cmPos(1:2:end,:)];
+cm(1,:) = [1,1,1];
+
+
+figure;imagesc(imx);colormap(cm);
+c = colorbar();
+clim = [min(c.Ticks),max(c.Ticks)];
+cticks = [clim(1), mean([clim(1),mean(clim)]), mean(clim), mean([clim(2),mean(clim)]),clim(2)];
+c.Ticks = cticks;
+c.TickLabels = {'BG','-0.5','0','0.5','1'}
+c.Label.String = 'Erk SSF';
+
+% close all
+
+% cm = colormap('parula');
+% cm(1:13,:)=repmat([1,1,1],13,1);
+% % c = colorbar('ticks',round(linspace(double(erkLimits(1)),double(erkLimits(2)),10)));
+% c = colorbar
+% c.Label.String = 'Erk SSF (8 bit, clipped to 95%)'
+%
+% xx = round(linspace(50,size(imx,2),5));
+% set(gca,'XTickLabel',arrayfun(@(y) num2str((y-308),xx,'UniformOutput',false))
+% xlabel('frames before mitosis');
+% ylabel('mitotic parent track sorted by NCD principal component')
+% yy = yticks();
+% set(gca,'YTickLabel',arrayfun(@(y) num2str(y/2),yticks()))
+% 4;
diff --git a/matlab/+SSF/drawSSFclusters.m b/matlab/+SSF/drawSSFclusters.m
new file mode 100644
index 0000000000000000000000000000000000000000..2e71a714a664dab1a0852ce74a93214d0ab0a191
--- /dev/null
+++ b/matlab/+SSF/drawSSFclusters.m
@@ -0,0 +1,68 @@
+% erk1D = Y(:,1);
+% [~,idxSort] = sort(erk1D);
+% qMitoSorted = qMitotic(idxSort,:);
+%
+% function imx = drawSSFtracks(qMitotic,idx,bDraw)
+
+% if ~exist('bDraw','var')
+% bDraw = false;
+% end
+tmax = max(cellfun(@length,qMitotic.erk));
+imx = [];
+imxH = 1;
+clusterPts = [];
+for k = 1:max(idx)
+ idxk = find(idx==k);
+ qk = qMitotic(idxk,:);
+ qk.yk = Y(idxk,1);
+ qk = sortrows(qk,'yk');
+ for i = 1:height(qk)
+ erk_i = qk.erk{i};
+ imx(imxH,tmax-length(erk_i)+1:tmax) = erk_i;
+ imxH = imxH+2;
+ end
+ imxH = imxH + 2;
+ clusterPts=[clusterPts,imxH];
+ imxH = imxH + 4;
+
+end
+
+
+
+% if ~bDraw
+% return
+% end
+
+
+close all
+
+cm = colormap('parula');
+cm(1,:) = [1,1,1];
+
+figure;imagesc(imx);colormap(cm);hold on
+c = colorbar('ticks',[2,64,128,192,255], 'ticklabels',{'-1.0','-0.5','0','0.5','1'});
+c.Label.String = 'Erk SSF';
+for p = 1:length(clusterPts)
+ plot([1,size(imx,2)],[clusterPts(p),clusterPts(p)],'-..k')
+end
+
+%
+
+% cm = colormap('parula');
+% cm(1:13,:)=repmat([1,1,1],13,1);
+% % c = colorbar('ticks',round(linspace(double(erkLimits(1)),double(erkLimits(2)),10)));
+% c = colorbar
+% c.Label.String = 'Erk SSF (8 bit, clipped to 95%)'
+%
+xx = round(linspace(50,size(imx,2),5));
+set(gca,'XTick',xx);
+set(gca,'XTickLabel',arrayfun(@(y) num2str(y-308),xx,'UniformOutput',false))
+xlabel('frames before mitosis');
+ylabel('mitotic parent track sorted by cluster and NCD principal component')
+yy = yticks();
+set(gca,'YTickLabel',arrayfun(@(y) num2str(y/2),yticks(),'uniformOutput',false))
+% h=gca; h.YAxis.TickLength = [0 0];
+yticks([])
+% 4;
+set(gcf,'color','w')
+% exportgraphics(gcf,'erk ssf heat map tracks NCD sorted cluster FLIF1d.pdf','Resolution',600,'contenttype','image')
diff --git a/matlab/+SSF/drawSSFtracks.m b/matlab/+SSF/drawSSFtracks.m
new file mode 100644
index 0000000000000000000000000000000000000000..1578eb1ffe731c9d7b4c7fdc167cf34188d461c4
--- /dev/null
+++ b/matlab/+SSF/drawSSFtracks.m
@@ -0,0 +1,85 @@
+% strDB = '/g/leverjs/Olivier/Agne/march_2023_20x/2022-04-05_steady_state_48h_deprived_13_ori.LEVER';
+
+function drawSSFtracks(ROOT,cache, kymo_channel, channel_description,fnames)
+
+[~,dsName,ext] = fileparts(ROOT);
+if ~exist('fnames','var')
+ fnames = [];
+end
+
+outfile = [dsName ' ' channel_description ' SSF projection_y_t.pdf'];
+if isempty(ext)
+ flist = dir(fullfile(ROOT,'*.LEVER'));
+else
+ flist = dir(ROOT);
+end
+f=figure(1);
+f.WindowState = 'maximized';
+pause(1)
+
+kymoPixels = {};
+for ff=1:length(flist)
+ strDB = fullfile(flist(ff).folder,flist(ff).name);
+ [ROOT,lf] = fileparts(strDB);
+ strKymoDB = fullfile(ROOT,cache,[lf '.LEVER_ssf_cache.LEVER']);
+ if ~exist(strKymoDB,'file')
+ continue
+ end
+ imKymo = SSF.loadImage(strKymoDB,kymo_channel);
+ kymoPixels{ff} = imKymo(find(imKymo));
+end
+kymoPixels = vertcat(kymoPixels{:});
+erkClipLimits = [prctile(kymoPixels,2.5),prctile(kymoPixels,97.5)];
+
+for ff = 1:length(flist)
+ strDB = fullfile(flist(ff).folder,flist(ff).name);
+ [ROOT,lf] = fileparts(strDB);
+ strKymoDB = fullfile(ROOT,cache,[lf '.LEVER_ssf_cache.LEVER']);
+ if ~exist(strKymoDB,'file')
+ continue
+ end
+ imKymo = SSF.loadImage(strKymoDB,kymo_channel);
+ %
+ imp = squeeze(max(imKymo,[],2));
+ imn = squeeze(min(imKymo,[],2));
+ imn = abs(imn);
+ idx = find(imn>imp);
+ imp(idx) = -1 .* imn(idx);
+% imp(imp<-0.5) = 0;
+ impq = SSF.quantize8(imp,erkClipLimits);
+% impq(imp==0 & imn==0) = 0;
+
+% % keep just [0,1] SSF
+% imp = squeeze(max(imKymo,[],2));
+% erkClipLimits = [0,prctile(kymoPixels,99.9)];
+% impq = SSF.quantize8(imp,erkClipLimits);
+% impq(imp==0) = 0; % set the background
+%
+
+ clf;imagesc(impq)
+ cm = colormap('parula');
+ cm(1,:) = [1,1,1]; % make the background white!
+ colormap(cm)
+ c = colorbar();
+ clim = [min(impq(:)),max(impq(:))];
+ cticks = [clim(1)+1, mean([clim(1),mean(clim)]), mean(clim), mean([clim(2),mean(clim)]),clim(2)];
+ c.Ticks = cticks;
+ % c.TickLabels = {'-1','-0.5','0','0.5','1'}
+
+ ticksSSF = linspace(erkClipLimits(1),erkClipLimits(2),5);
+ ticksSSF = arrayfun(@(x) num2str(x,2),ticksSSF,'UniformOutput',false);
+ c.TickLabels = ticksSSF;
+ c.Label.String = [channel_description ' SSF (dataset reference)'];
+ if ~isempty(fnames)
+ lf = fnames{ff};
+ end
+ hold on
+ yl = ylim();
+ plot([62,62],[yl(1),yl(2)],'--r','linewidth',2)
+ title([lf ' ' channel_description ' SSF projection to (Y/2,time)'],'interpreter','none')
+ xlabel('time (frames)')
+ ylabel('Y (max intensity projection along X)')
+ bAppend = ff>1;
+ exportgraphics(gcf,outfile,'Resolution',600,'contenttype','image','append',bAppend);
+
+end
\ No newline at end of file
diff --git a/matlab/+SSF/drawSubsets.m b/matlab/+SSF/drawSubsets.m
new file mode 100644
index 0000000000000000000000000000000000000000..eb058607c103b3357a896ddfc05cd19126c4e130
--- /dev/null
+++ b/matlab/+SSF/drawSubsets.m
@@ -0,0 +1,78 @@
+% andy and layton. jul 3 2023. very preliminary.
+kROOT = '/g/leverjs/Olivier/Agne/2022-06-03_48h-depr-transcr-drugs/kymo_combined_downsize_steady_state';
+flist = dir(fullfile(kROOT,'*.LEVER'));
+transcr_class = readtable('expDescr-2022-06-03.xlsx');
+steady_state_class = load('../agne_20x_classMap.mat');
+
+className = {};
+for ff = 1:length(flist)
+ cn = regexp(flist(ff).name,'(\d+-\d+-\d+)_.*(\d\d)_ori*','tokens');
+ if isempty(cn)
+ re = regexp(flist(ff).name,'^(\d+)_.*(\d).LEVER','tokens');
+ idx = str2double(re{1}{1});
+ part = str2double(re{1}{2});
+ if part == 1
+ className{ff} = ['pre_' transcr_class.Cell_Type{idx}];
+ else
+ className{ff} = ['post_' transcr_class.Cell_Type{idx}];
+ end
+ else
+ cn = [cn{1}{1} '_' cn{1}{2}];
+ className{ff} = steady_state_class.classMap(cn);
+ end
+end
+
+ssClassList = unique(steady_state_class.classMap.values);
+idx = contains(ssClassList,'E17K');
+ssClassList(idx) = [];
+idx = contains(ssClassList,'E545K');
+ssClassList(idx) = [];
+ssClassList(end+1) = {'pre_ErbB2_overexpr'};
+
+idx = cellfun(@(x) any(contains(ssClassList,x)),className,'UniformOutput',false);
+idx = find([idx{:}]);
+
+d2 = d(idx,idx);
+className = className(idx);
+
+A = d2;
+K=3;
+
+
+
+[idx,Y] = Cluster.SpectralCluster(A,K);
+% Y = tsne(Y,'Algorithm','exact','NumDimensions',3);
+clf;hold off;
+% if size(Y,2) == 3
+% plot3(Y(:,1),Y(:,2),Y(:,3),'.')
+% else
+% plot(Y(:,1),Y(:,2),'.')
+% end
+sym = {'ko','cv','m^','r*','gx','<k','b>','gs','bd'};
+
+
+classList = unique(className);
+hx = zeros(size(classList));
+hold on
+
+for ff=1:size(Y,1)
+
+ idxSym = find(strcmp(classList,className{ff}));
+ if K==3
+ h1 = plot3(Y(ff,1),Y(ff,2),Y(ff,3),sym{idxSym});
+ else
+ h1 = plot(Y(ff,1),Y(ff,2),sym{idxSym},'UserData',ff);
+ end
+ if ~hx(idxSym)
+ hx(idxSym) = h1;
+ end
+ % if size(Y,2) == 3
+ % text(Y(i,1),Y(i,2),Y(i,3),num2str(i),'FontSize',12)
+ %
+ % else
+ % text(Y(i,1),Y(i,2),num2str(i),'FontSize',12)
+ % end
+end
+set(gcf,'color','w')
+xlabel('u1');ylabel('u2'),zlabel('u3')
+legend(hx(find(hx)),classList(find(hx)),'interpreter','none');
\ No newline at end of file
diff --git a/matlab/+SSF/draw_ssf_ncd.m b/matlab/+SSF/draw_ssf_ncd.m
new file mode 100644
index 0000000000000000000000000000000000000000..4c4acb5b8ef8caf077c51efbc45355a800b9dbcc
--- /dev/null
+++ b/matlab/+SSF/draw_ssf_ncd.m
@@ -0,0 +1,55 @@
+% load('agne_72_8bpp.mat')
+flist = dir(fullfile(ROOT,'*.LEVER'));
+
+% className = {};
+% for ff=1:length(flist)
+% cn = regexp(flist(ff).name,'(\d+-\d+-\d+)_.*(\d\d)_ori*','tokens');
+% cn = [cn{1}{1} '_' cn{1}{2}];
+% className{ff} = classMap(cn);
+% end
+% targetClass = {'AKT1_E17K','WT','PIK3CA_E545K'}
+% idx = find(cellfun(@(x) ~isempty(find(strcmp(targetClass,x))),className));
+% A=d(idx,idx);
+% className = className(idx);
+
+A = d;
+K=3;
+
+
+
+[idx,Y] = Cluster.SpectralCluster(A,K);
+% Y = tsne(Y,'Algorithm','exact','NumDimensions',3);
+clf;hold off;
+% if size(Y,2) == 3
+% plot3(Y(:,1),Y(:,2),Y(:,3),'.')
+% else
+% plot(Y(:,1),Y(:,2),'.')
+% end
+sym = {'ko','cv','m^','r*','gx','<k','b>','gs','bd'};
+
+
+classList = unique(className);
+hx = zeros(size(classList));
+hold on
+
+for ff=1:size(Y,1)
+
+ idxSym = find(strcmp(classList,className{ff}));
+ if K==3
+ h1 = plot3(Y(ff,1),Y(ff,2),Y(ff,3),sym{idxSym});
+ else
+ h1 = plot(Y(ff,1),Y(ff,2),sym{idxSym},'UserData',ff);
+ end
+ if ~hx(idxSym)
+ hx(idxSym) = h1;
+ end
+ % if size(Y,2) == 3
+ % text(Y(i,1),Y(i,2),Y(i,3),num2str(i),'FontSize',12)
+ %
+ % else
+ % text(Y(i,1),Y(i,2),num2str(i),'FontSize',12)
+ % end
+end
+set(gcf,'color','w')
+xlabel('u1');ylabel('u2'),zlabel('u3')
+legend(hx(find(hx)),classList(find(hx)),'interpreter','none');
\ No newline at end of file
diff --git a/matlab/+SSF/erkTrackingGraph.m b/matlab/+SSF/erkTrackingGraph.m
new file mode 100644
index 0000000000000000000000000000000000000000..e58da9ff71ed4b427c164a51dc721929d5160376
--- /dev/null
+++ b/matlab/+SSF/erkTrackingGraph.m
@@ -0,0 +1,38 @@
+ROOT = '/g/leverjs/Olivier/Agne/2022-06-04_ibidi-insert-setup1/';
+cacheFolder = fullfile(ROOT,'logCache2');
+
+strDB = '/g/leverjs/Olivier/Agne/2022-06-04_ibidi-insert-setup1/2022-06-04_ibidi-insert-setup1_37.LEVER';
+[conn,CONSTANTS,segParams]=openDB(strDB);
+
+str_imd = strrep(strDB,'.LEVER','.json');
+imd = MicroscopeData.ReadMetadata(str_imd,false);
+imLoG = MicroscopeData.Reader('imageData',imd);
+cmd = ['select A.cellID as cid_src,A.time as t_src,A.centroid as cx_src, '...
+ 'B.cellID as cid_dst,B.time as t_dst,B.centroid as cx_dst FROM tblDistCC '...
+ 'inner join tblCells as A on A.cellID = cellID_src '...
+ 'inner join tblCells as B on B.cellID = cellID_dst'];
+q = fetch(conn,cmd);
+
+erkCost = [];
+parfor i = 1:length(q.cid_src)
+ cx_src = jsondecode(q.cx_src{i});
+ cx_src(3) = q.t_src(i)
+ cx_src = round(cx_src);
+ val_src = imLoG(cx_src(2),cx_src(1),cx_src(3));
+
+ cx_dst = jsondecode(q.cx_src{i});
+ cx_dst(3) = q.t_dst(i)
+ cx_dst = round(cx_dst);
+ val_dst = imLoG(cx_dst(2),cx_dst(1),cx_dst(3));
+ logCost = abs(val_src-val_dst);
+ erkCost(i,:) = [q.cid_src(i),q.cid_dst(i),logCost] ;
+end
+
+tblErkDstCC = table();
+tblErkDstCC.cellID_src = erkCost(:,1);
+tblErkDstCC.cellID_dst = erkCost(:,2);
+tblErkDstCC.cost = erkCost(:,3);
+
+exec(conn,'drop table if exists tblErkDstCC;create table tblErkDstCC(cellID_src,cellID_dst,cost)');
+insert(conn,'tblErkDstCC',{'cellID_src','cellID_dst','cost'},tblErkDstCC);
+close(conn)
diff --git a/matlab/+SSF/gen_SSF_kymo.m b/matlab/+SSF/gen_SSF_kymo.m
new file mode 100644
index 0000000000000000000000000000000000000000..0c01c39bee3f2dfc285b3308ee41b4df9f9fc3c1
--- /dev/null
+++ b/matlab/+SSF/gen_SSF_kymo.m
@@ -0,0 +1,59 @@
+
+% BE CAREFUL HERE! BE DRAGONS! GET THESE target names & numbers RIGHT OR PERISH
+% targetChannelNames = {'Erk SSF'; 'Akt SSF' ; 'DHB SSF'; 'H2B SSF'; 'velocity SSF'}; % channel names in the kymo
+% targetChannelNames = {'Erk SSF'; 'Oct4 SSF' ; 'H2B SSF'; 'velocity SSF'}; % channel names in the kymo
+% targetChannelNumbers = [2, 3, -1]; % maps image channel names to kymo channel names
+function gen_SSF_kymo(strDB,targetChannelNames,targetChannelNumbers,outfolder,bDownscale, startFrame)
+
+if ~exist('bDownscale','var')
+ bDownscale = false;
+end
+if ~exist('startFrame','var')
+ startFrame = 1;
+end
+
+[fx,nx,ext]=fileparts(strDB);
+if strcmp(ext,'.LEVER')
+ flist = dir(strDB);
+ ROOT = fx;
+else
+ ROOT = strDB;
+ flist = dir(fullfile(strDB,'*.LEVER'));
+end
+L = length(flist);
+
+
+if ~exist(outfolder,'dir')
+ mkdir(outfolder);
+end
+
+imd={};
+nGPU = HIP.Cuda.DeviceCount();
+p = ljsStartParallel(8*nGPU);
+
+parfor ff=1:L
+% for ff=1:L
+ str_ff = fullfile(flist(ff).folder,flist(ff).name);
+ if exist(fullfile(outfolder,[flist(ff).name '_ssf_cache.json']),'file')
+ fprintf(1,'genKymo skipping %s kymo exists\n',str_ff);
+ continue
+ end
+ t0 = tic();
+ imVolume = SSF.ssf_volume(str_ff,targetChannelNumbers, bDownscale);
+ if isempty(imVolume)
+ continue
+ end
+ if contains(targetChannelNames{end},'velocity ssf','IgnoreCase',true)
+ imVolume(:,:,:,length(targetChannelNumbers)+1) = SSF.velocity_kymo(str_ff,bDownscale);
+ end
+ imVolume = imVolume(:,:,startFrame:end,:); % trim off first 30 frames
+ imd{ff}=MicroscopeData.MakeMetadataFromImage(imVolume);
+ imd{ff}.DatasetName=[flist(ff).name '_ssf_cache'];
+ imd{ff}.imageDir = outfolder;
+ imd{ff}.ChannelNames = targetChannelNames;
+ MicroscopeData.WriterH5(imVolume,'imageData',imd{ff},'path',outfolder);
+
+ tElapsed = toc(t0);
+ fprintf(1,'ssf_volume %d tElapsed=%0.2f\n',ff,tElapsed);
+end
+Import.leverImport('',outfolder);
\ No newline at end of file
diff --git a/matlab/+SSF/goErkCN.m b/matlab/+SSF/goErkCN.m
new file mode 100644
index 0000000000000000000000000000000000000000..1c7ae124eb937c61971f4571c2c873fe3c298117
--- /dev/null
+++ b/matlab/+SSF/goErkCN.m
@@ -0,0 +1,42 @@
+% strDB = '/f/leverjs/Olivier/Yannick/20210924/20210924_pos3.LEVER';
+% tblCN = goErkCN(strDB,174279)
+% tblCN = goErkCN(strDB,224589)
+function tblCN = goErkCN(strDB,targetTrack)
+
+[conn,CONSTANTS,segParams]=openDB(strDB);
+[ROOT,lf] = fileparts(strDB);
+strKymo = fullfile(ROOT,'kymoV',[lf '.LEVER_ssf_cache.LEVER']);
+imKymo = leversc.loadImage(strKymo,1,1);
+
+cmd = ['select cellID,trackID,centroid,time,LoG from tblCells where trackID = '...
+ num2str(targetTrack)];
+q=fetch(conn,cmd);
+
+erkSSF = [];
+for i = 1:height(q)
+ centroid = jsondecode(q.centroid{i});
+ centroid = [round(centroid(1:2))', q.time(i)];
+ sample_value = SSF.ssf_sample(imKymo,centroid);
+ erkSSF(i) = sample_value;
+end
+
+featureParams.channel = 2;
+featureParams.name='CytoToNuclearRatio';
+featureParams.color="#00ffff";
+tblCN = table();
+for i = 1:height(q)
+ t = q.time(i);
+ cellList = Read.getCellsTime(conn,t,segParams.channels(1),CONSTANTS);
+ nt = SSF.cytoToNuclearRatio(cellList,q.cellID(i),t,CONSTANTS,featureParams,segParams);
+ nt.erkSSF = erkSSF(i);
+ tblCN = [tblCN;nt]
+end
+ee = imKymo(find(imKymo));
+erkClipLimits = [prctile(ee,2.5), prctile(ee,97.5)];
+
+erk = tblCN.erkSSF;
+erk = SSF.quantize8(erk,erkClipLimits);
+erk = 2 * (double(erk) / 255) -1;
+figure;plot(erk)
+hold on
+plot(tblCN.cnRatio)
\ No newline at end of file
diff --git a/matlab/+SSF/goTrackSSFkymo.m b/matlab/+SSF/goTrackSSFkymo.m
new file mode 100644
index 0000000000000000000000000000000000000000..6461c99111f6b7e7ace956edf4da2fbd94be7224
--- /dev/null
+++ b/matlab/+SSF/goTrackSSFkymo.m
@@ -0,0 +1,117 @@
+
+ROOT = '/f/leverjs/Olivier/Yannick/20210924/';
+flist = dir(fullfile(ROOT,'*.LEVER'));
+
+cxKymo = {};
+qMitotic = {};
+
+for ff = 1:length(flist)
+ strDB = fullfile(flist(ff).folder,flist(ff).name);
+ [ROOT,lf] = fileparts(strDB);
+ strKymoDB = fullfile(ROOT,'kymoV',[lf '.LEVER_ssf_cache.LEVER']);
+ cxKymo{ff} = SSF.loadImage(strKymoDB,1);
+ [conn,CONSTANTS,segParams]=openDB(strDB);
+ imErk = cxKymo{ff}(:,:,:,1);
+ qm = fetch(conn,'select * from (select cellID,trackID,count(time) as nt from tblCells where trackID in (select trackID from tblCells inner join tblFamilies on cellID_parent=cellID) group by trackID) where nt>23');
+ for i = 1:length(qm.trackID)
+ qcx = fetch(conn,['select centroid,time from tblCells where trackID = ' num2str(qm.trackID(i))]);
+ centroids = cellfun(@jsondecode,qcx.centroid,'UniformOutput',false);
+ centroids = reshape(vertcat(centroids{:}),3,[])';
+ centroids = round(centroids);
+ qm.centroids{i} = [centroids(:,1:2),qcx.time];
+ qm.idxCentroids{i} = sub2ind(size(cxKymo{ff}),centroids(:,2),centroids(:,1),qcx.time);
+ qm.movieID(i) = ff;
+ qm.erk{i} = SSF.ssf_sample_idx(imErk,qm.idxCentroids{i});
+ qm.isEmpty(i) = all(0==qm.erk{i});
+ end
+ qm(qm.isEmpty,:)=[];
+ qMitotic = [qMitotic;qm];
+end
+% qMitotic.erk is the signal. quantize it to 8 bit now
+erkCombined =[qMitotic.erk{:}]' ;
+erkClipLimits = [prctile(erkCombined,2.5), prctile(erkCombined,97.5)];
+for c = 1:length(cxKymo)
+ cxKymo{c} = SSF.quantize8(cxKymo{c},erkClipLimits);
+end
+% % a bit slow, but steady. find distancefrom each mitotis
+for i = 1:height(qMitotic)
+
+ strDB = fullfile(flist(qMitotic.movieID(i)).folder,flist(qMitotic.movieID(i)).name);
+ [conn,CONSTANTS,segParams]=openDB(strDB);
+ q1 = fetch(conn,['select centroid,time from tblCells where cellID = ' num2str(qMitotic.cellID(i))]);
+ colony = Read.getCellsTime(conn,q1.time,4,CONSTANTS);
+ for c = 1:length(colony)
+ bw = zeros(CONSTANTS.imageData.Dimensions(2),CONSTANTS.imageData.Dimensions(1));
+ bw(colony(c).idxPts) = 1;
+ centroid1 = round(jsondecode(q1.centroid{1}));
+ if ~bw(centroid1(2),centroid1(1))
+ continue
+ end
+ bwd = bwdist(~bw);
+ bwd = bwd./max(bwd(:));
+ qMitotic.dNormalized(i) = bwd(centroid1(2),centroid1(1));
+ qMitotic.time(i) = q1.time;
+ end
+end
+
+
+
+for i = 1:height(qMitotic)
+ erk_i = medfilt1(qMitotic.erk{i}, 5);
+ erk_i = SSF.quantize8(erk_i, erkClipLimits);
+ qMitotic.erk{i} = erk_i;
+end
+
+d = [];
+L = height(qMitotic);
+parfor i = 1:L
+% im_i = SSF.cropKymo(cxKymo{qMitotic.movieID(i)},qMitotic.idxCentroids{i});
+ for j = 1:L
+% im_j = SSF.cropKymo(cxKymo{qMitotic.movieID(j)},qMitotic.idxCentroids{j});
+ erk_j = medfilt1(qMitotic.erk{j},5)
+ im_j = SSF.quantize8(erk_j,erkClipLimits);
+ d(i,j) = SSF.ncd_ssf_volume(im_i,im_j);
+ end
+end
+
+% for i = 1:length(d)
+% for j = 1 : length(d)
+% d(i,j)=max(d(i,j),d(j,i));
+% end
+% d(i,i) = max(d(i,i),0);
+% end
+
+close all
+A = d;
+K=3;
+[idx,Y] = Cluster.SpectralCluster(A,K);
+% Y(:,3) = [erkMitotic.d];
+figure;hold on
+hred = [];
+hgreen = [];
+for i = 1 : height(qMitotic)
+ if qMitotic.dNormalized(i)<.2929
+ hred = [hred,plot3(Y(i,1),Y(i,2),Y(i,3),'.r')];
+ else
+ hgreen = [hgreen,plot3(Y(i,1),Y(i,2),Y(i,3),'.g')];
+ end
+end
+xlabel('u1')
+ylabel('u2')
+zlabel('u3')
+legend([hred(1),hgreen(1)],'d_{normalized} < 0.29','d_{normalized} \geq .2929')
+
+set(gcf,'color','w')
+figure;hold on
+for i = 1 : height(qMitotic)
+ if qMitotic.dNormalized(i)<.2929
+ plot(Y(i,1),Y(i,2),'.r');
+ else
+ plot(Y(i,1),Y(i,2),'.g');
+ end
+end
+xlabel('u1')
+ylabel('u2')
+legend({'d_{normalized}>.2929','d_{normalized}<.2929'})
+set(gcf,'color','w')
+% exportgraphics(gcf,'erkMitoticParentTracksEmbedding_medfilt.pdf','Resolution',300,'contenttype','image')
\ No newline at end of file
diff --git a/matlab/+SSF/go_ssf_ncd.m b/matlab/+SSF/go_ssf_ncd.m
new file mode 100644
index 0000000000000000000000000000000000000000..f6dd59cc9741d5c09589aa4788ff92b16d8d9784
--- /dev/null
+++ b/matlab/+SSF/go_ssf_ncd.m
@@ -0,0 +1,90 @@
+% ROOT = '/g/leverjs/Olivier/Agne/2022-06-04_ibidi-insert-setup1/kymo3/';
+% % ROOT = '/g/leverjs/Olivier/Agne/2022-04-05_steady_state_48h_deprived/kymo3';
+% ERK_CHANNEL = 1; % ERK is channel 1 on kymograph
+% AKT_CHANNEL = 2;
+% H2B_CHANNEL = 3;
+% targetChannels = [ERK_CHANNEL,AKT_CHANNEL];
+function d=go_ssf_ncd(kROOT,targetChannels)
+
+tStart = tic();
+
+flist = dir(fullfile(kROOT,'*.LEVER'));
+d = zeros(length(flist));
+kymoPixels = {};
+
+p = ljsStartParallel();
+%
+parfor ff=1:length(flist)
+ strDB_ff = fullfile(flist(ff).folder,flist(ff).name);
+ im_ff = SSF.loadImage(strDB_ff,targetChannels);
+ kp = im_ff(find(im_ff));
+ kymoPixels{ff} = kp;
+end
+kymoPixels = vertcat(kymoPixels{:});
+% erkClipLimits = [prctile(kymoPixels,2.5),prctile(kymoPixels,97.5)]
+erkClipLimits = [0,prctile(kymoPixels,99)];
+% erkClipLimits = [-1,1];
+
+%
+cmdList = NCD.dParallelCommandList(ones(length(flist)),p.NumWorkers);
+W = size(cmdList,2); % for slicing j in parfor
+H = size(cmdList,1);
+dxx = zeros(H,W);
+parfor i=1:H
+ str_ff_prev = '';
+ im_ff = [];
+
+ for j = 1:W
+ t0 = tic();
+ ff = cmdList(i,j,2); % ff is the row var -- repeats
+ gg = cmdList(i,j,1);
+ if 0 == ff || 0 == gg
+ continue
+ end
+ strDB_ff = fullfile(flist(ff).folder,flist(ff).name);
+ if ~strcmp(strDB_ff,str_ff_prev)
+ im_ff = SSF.loadImage(strDB_ff,targetChannels);
+ im_ff = SSF.quantize8(im_ff,erkClipLimits);
+ str_ff_prev = strDB_ff;
+ end
+
+ if ff == gg
+ d1 = SSF.ncd_ssf_volume(im_ff,im_ff);
+ dxx(i,j) = d1;
+ else
+ strDB_gg = fullfile(flist(gg).folder,flist(gg).name);
+ im_gg = SSF.loadImage(strDB_gg,targetChannels);
+ im_gg = SSF.quantize8(im_gg,erkClipLimits);
+
+ d1 = SSF.ncd_ssf_volume(im_ff,im_gg);
+ d2 = SSF.ncd_ssf_volume(im_gg,im_ff);
+
+
+ dxx(i,j) = min(d1,d2);
+ end
+ tElapsed = toc(t0);
+ fprintf('%s tElapsed = %0.2f\n',mat2str([ff,gg,dxx(i,j)]),tElapsed);
+ end
+end
+% convert dxx to distance matrix d
+d = [];
+for i = 1 : size(dxx,1)
+ for j = 1 : size(dxx,2)
+ c = cmdList(i,j,1);
+ r = cmdList(i,j,2);
+ if 0 == r || 0 == c
+ continue
+ end
+ d(r,c) = dxx(i,j);
+ end
+end
+
+for i = 1 : size(d,1)
+ for j = 1 : size(d,2)
+ if 0 == d(i,j)
+ d(i,j) = d(j,i);
+ end
+ end
+end
+tElapsed = toc(tStart);
+fprintf('total time tElapsed = %0.2f\n',tElapsed);
diff --git a/matlab/+SSF/loadImage.m b/matlab/+SSF/loadImage.m
new file mode 100644
index 0000000000000000000000000000000000000000..9e149c8d140985dc9473b36273bbf4483b2c4841
--- /dev/null
+++ b/matlab/+SSF/loadImage.m
@@ -0,0 +1,11 @@
+
+function im = loadImage(strDB,channelList)
+
+if ~exist('bDouble','var')
+ bDouble = false;
+end
+im = [];
+time = 1; % kymo is single time point
+for c=1:length(channelList)
+ im(:,:,:,c) = leversc.loadImage(strDB,time,channelList(c));
+end
diff --git a/matlab/+SSF/mapCentroids.m b/matlab/+SSF/mapCentroids.m
new file mode 100644
index 0000000000000000000000000000000000000000..db3605526f40a56e60ea5b57dc01a745f8a6df2d
--- /dev/null
+++ b/matlab/+SSF/mapCentroids.m
@@ -0,0 +1,22 @@
+function centroidMap = mapCentroids(conn,CONSTANTS)
+
+q = fetch(conn,'select cellID,centroid,time from tblCells');
+cx = cellfun(@jsondecode,q.centroid,'UniformOutput',false);
+cx = [cx{:}]';
+
+d = squareform(pdist(cx));
+[~,u123] = Cluster.SpectralCluster(d,2);
+
+
+for dim=1:2
+ % normalize to [0,1]
+ u123(:,dim) = (max(u123(:,dim)) - u123(:,dim))./(max(u123(:,dim)) - min(u123(:,dim)));
+ % scale to image range
+ u123(:,dim) = (u123(:,dim) .* (max(cx(:,dim))-min(cx(:,dim))) + min(cx(:,dim)) ) ;
+end
+
+u123 = round(u123);
+u123 = max(u123,1);
+u123 = min(u123,[CONSTANTS.imageData.Dimensions(1:2)]);
+u123 = mat2cell(u123,ones(length(u123),1));
+centroidMap = containers.Map([q.cellID],u123);
diff --git a/matlab/+SSF/ncd_ssf_volume.m b/matlab/+SSF/ncd_ssf_volume.m
new file mode 100644
index 0000000000000000000000000000000000000000..0c3427a496154cf7e7ca3f8e62c3e5f32c32eb74
--- /dev/null
+++ b/matlab/+SSF/ncd_ssf_volume.m
@@ -0,0 +1,24 @@
+% i1 and i2 are signal kymos (x,y,t,c)outdir
+% we want images {t}(x,y,c)
+% package to cell array by t and then pass to in memory FLI%F compressor
+function ncd = ncd_ssf_volume(i1,i2)
+
+im12 = SSF.catKymographs(i1,i2,1);
+im12 = squeeze(num2cell(im12,[1,2,4]));
+s12 = NCD.flifPress(im12);
+
+im21 = SSF.catKymographs(i1,i2,2);
+im21 = squeeze(num2cell(im21,[1,2,4]));
+s21 = NCD.flifPress(im21);
+
+s12 = min(s12,s21);
+
+i1 = squeeze(num2cell(i1,[1,2,4]));
+i2 = squeeze(num2cell(i2,[1,2,4]));
+
+s1 = NCD.flifPress(i1);
+s2 = NCD.flifPress(i2);
+
+ncd = ( s12-min(s1,s2)) / (max(s1,s2));
+
+4;
diff --git a/matlab/+SSF/quantize8.m b/matlab/+SSF/quantize8.m
new file mode 100644
index 0000000000000000000000000000000000000000..1a2a0f119da3e86867c2433fc4da199bb0480fd6
--- /dev/null
+++ b/matlab/+SSF/quantize8.m
@@ -0,0 +1,14 @@
+% clipLimits = [minVal,maxVal];
+function im = quantize8(im,clipLimits)
+
+if isa(im,'uint8')
+ return
+end
+im = max(im,clipLimits(1));
+im = min(im,clipLimits(2));
+
+im = (im - clipLimits(1)) ./ (clipLimits(2) - clipLimits(1));
+
+im = im2uint8(im);
+im = max(im,1); % exclude 0 -- only for background
+im(1,1) = 0; % make sure at least 1 pixel hits background
\ No newline at end of file
diff --git a/matlab/+SSF/ssfTracks.m b/matlab/+SSF/ssfTracks.m
new file mode 100644
index 0000000000000000000000000000000000000000..0b3e0ba13879f64cf17353818c81430654c44bf5
--- /dev/null
+++ b/matlab/+SSF/ssfTracks.m
@@ -0,0 +1,38 @@
+% function ssfTracks(strDB)
+
+ROOT = '/g/leverjs/Olivier/Agne/2022-02-19_1h_starved_steady_state_exp1/';
+ERK_CHANNEL = 2;
+DHB_CHANNEL = 3;
+ref_max = 0.7;
+movie_tracks = {};
+
+flist = dir(fullfile(ROOT,'*.LEVER'));
+for ff=1:length(flist)
+ strDB = fullfile(flist(ff).folder,flist(ff).name);
+ [conn,CONSTANTS,segParams] = openDB(strDB);
+
+ ssf_tracks = containers.Map('KeyType','double','ValueType','any');
+
+ for t = 1:CONSTANTS.imageData.NumberOfFrames
+ cellList = Read.getCellsTime(conn,t,1,CONSTANTS);
+ imSSF = SSF.ssf_channel(cellList,CONSTANTS,DHB_CHANNEL,t,ref_max,segParams,[]);
+
+ for i = 1:length(cellList)
+ cx = round(cellList(i).centroid);
+ cx = [cx(2),cx(1)]; % [y,x]
+ cxSSF = imSSF(cx(1),cx(2));
+ trackID = cellList(i).trackID;
+ if isKey(ssf_tracks,trackID)
+ ssf_vals = ssf_tracks(trackID);
+ ssf_vals = [ssf_vals, [cxSSF ; t]];
+ ssf_tracks(trackID) = ssf_vals;
+ else
+ ssf_tracks(trackID) = [cxSSF ; t];
+ end
+ end
+ 4;
+ end
+ close(conn);
+ movie_tracks{ff} = ssf_tracks;
+end
+
diff --git a/matlab/+SSF/ssf_channel.m b/matlab/+SSF/ssf_channel.m
new file mode 100644
index 0000000000000000000000000000000000000000..70e0970e191a7a460837eb3a8e2865a4bf566767
--- /dev/null
+++ b/matlab/+SSF/ssf_channel.m
@@ -0,0 +1,64 @@
+function imSSF = ssf_channel(cellList,CONSTANTS,channel,t,refMax,segParams,centroidMap,bDownscale)
+
+im = MicroscopeData.Reader('imageData',CONSTANTS.imageData, 'chanList',abs(channel),'timeRange',[t t], 'outType','uint16','prompt',false);
+im = Segment.denoise(im,segParams,false);
+im = double(im)./2^16;
+% scale refMax by actual image statistics. median estimates background,
+% 99.99% represents max foreground intensity.
+ %refMax * ( prctile(im(:),99.99) - median(im(:)));
+
+[imLoG, imp, imn] = LoG.getCompositeLoG(im,CONSTANTS,segParams);
+
+bw = logical(0*imp);
+for i=1:length(cellList)
+ bw(cellList(i).idxPts)=1;
+end
+d = bwdist(~bw);
+imp(d<3)=0;
+imn(d<3)=0;
+
+szim = ceil(size(imp));
+if bDownscale
+ szim = szim ./ 2;
+end
+imSSF = zeros(szim(1),szim(2));
+for i=1:length(cellList)
+ if is3D(CONSTANTS)
+ cx = centroidMap(cellList(i).cellID);
+ else
+ cx = round(cellList(i).centroid);
+ cx = [cx(2),cx(1)]; % [y,x]
+ end
+ if bDownscale
+ cx = round(cx/2);
+ end
+ val_Pos = max(imp(cellList(i).idxPts));
+ val_Neg = max(imn(cellList(i).idxPts));
+ if val_Pos > val_Neg
+ % dark nucleus, bright cytoplasm
+ % ssf sign is in direction of intensity gradient
+ val = val_Pos;
+ else
+ % bright nucleus, dark cytoplasm
+ val = -1 * val_Neg;
+ end
+ ratio = val./refMax;
+ ratio = min(ratio,1);
+ ratio = max(ratio,-1);
+
+ imSSF(cx(1),cx(2)) = ratio;
+
+end
+
+% if channel < 0
+% % negative channel, keep negative LoG response
+% imSSF(imSSF>0) = 0;
+% imSSF = abs(imSSF);
+% else
+% % positive channel, keep positive LoG response
+% imSSF(imSSF<0) = 0;
+% end
+
+% imSSF = max(imSSF,0);
+% imSSF = min(imSSF,1);
+4;
diff --git a/matlab/+SSF/ssf_sample.m b/matlab/+SSF/ssf_sample.m
new file mode 100644
index 0000000000000000000000000000000000000000..d39f114804581513bda4597295cc072da8592ca4
--- /dev/null
+++ b/matlab/+SSF/ssf_sample.m
@@ -0,0 +1,10 @@
+% check the neighborhood around centeroid in imkymo. used to eliminate
+% round off errors in kymo / cell centroid
+function sample_value = ssf_sample(imKymo,centroid,idxCentroid)
+
+sample_value = imKymo(centroid(1)-1:centroid(1)+1,centroid(2)-1:centroid(2)+1,centroid(3));
+if length(find(sample_value))>1
+ fprintf(2,'ack SSF kymo ack more than one ssf sample found at centroid. send help.\n');
+end
+sample_value = sample_value(find(sample_value));
+sample_value = sample_value(1);
\ No newline at end of file
diff --git a/matlab/+SSF/ssf_sample_idx.m b/matlab/+SSF/ssf_sample_idx.m
new file mode 100644
index 0000000000000000000000000000000000000000..0d3d500c518a55f21dd3e67f132852220bbd33af
--- /dev/null
+++ b/matlab/+SSF/ssf_sample_idx.m
@@ -0,0 +1,17 @@
+% check the neighborhood around centeroid in imkymo. used to eliminate
+% round off errors in kymo / cell centroid
+function sampleList = ssf_sample_idx(imKymo,idxCentroid)
+sampleList = [];
+for i = 1:length(idxCentroid)
+ [centroid(1),centroid(2),centroid(3)] = ind2sub(size(imKymo),idxCentroid(i));
+ sv = imKymo(centroid(1)-1:centroid(1)+1,centroid(2)-1:centroid(2)+1,centroid(3));
+ if length(find(sv))>1
+ fprintf(2,'ack SSF kymo ack more than one ssf sample found at centroid. send help.\n');
+ end
+ sv = sv(find(sv));
+ if isempty(sv)
+ sv = 0;
+ end
+ sv = sv(1);
+ sampleList(i) = sv;
+end
\ No newline at end of file
diff --git a/matlab/+SSF/ssf_volume.m b/matlab/+SSF/ssf_volume.m
new file mode 100644
index 0000000000000000000000000000000000000000..7e2927ea01a46987baed927ab1d189cf7dd9c757
--- /dev/null
+++ b/matlab/+SSF/ssf_volume.m
@@ -0,0 +1,42 @@
+function im_ssf = ssf_volume(strDB,targetChannelNumbers, bDownscale)
+
+refMax = 0.7; % from cacheReferenceLoG
+
+[connx,CONSTANTS,segParams]=openDB(strDB);
+if isempty(CONSTANTS)
+ im_ssf = [];
+ return
+end
+cmd = ['select count(cellID) as nCells from tblCells where time =' num2str(CONSTANTS.imageData.NumberOfFrames)];
+q=fetch(connx,cmd);
+if 0==q.nCells
+ fprintf(2,'genKymo::ssf_volume skipping %s no segmentations in final frame\n',strDB);
+ close(connx);
+ im_ssf = [];
+ return
+end
+% x,y,1,c,t -> x,y,t,c,1
+xyzct_size = Helpers.volumeSize(CONSTANTS);
+% FUN NOTE :: if you compute kymo_size wrong here, then when we iterate
+% below you will propagate that mistake exponentially and run out of memory
+kymo_size = [xyzct_size(1:2) xyzct_size(5) xyzct_size(4) 1];
+if bDownscale
+ kymo_size(1:2) = ceil(kymo_size(1:2) ./ 2);
+end
+if is3D(CONSTANTS)
+ centroidMap = SSF.mapCentroids(connx,CONSTANTS);
+else
+ centroidMap = [];
+end
+
+
+im_ssf = zeros(kymo_size);
+
+for t=1:CONSTANTS.imageData.NumberOfFrames
+ cellList = Read.getCellsTime(connx,t,segParams.channels(1),CONSTANTS);
+ for c=1:length(targetChannelNumbers)
+ % 5-D x,y,1,c,t -> 3-D x,y,t(z),c
+ im_ssf(:,:,t,c) = SSF.ssf_channel(cellList,CONSTANTS,targetChannelNumbers(c),t,refMax,segParams,centroidMap,bDownscale);
+ end
+end
+close(connx);
\ No newline at end of file
diff --git a/matlab/+SSF/trackDistance.m b/matlab/+SSF/trackDistance.m
new file mode 100644
index 0000000000000000000000000000000000000000..4f018e942bae2444aafe3a2dc62234220edd76fd
--- /dev/null
+++ b/matlab/+SSF/trackDistance.m
@@ -0,0 +1,18 @@
+function d = trackDistance(ci,cj)
+tOverlap = intersect(ci(:,3),cj(:,3));
+if isempty(tOverlap)
+ d = Inf;
+ return
+end
+idxDel = find(arrayfun(@(x) isempty(intersect(x,tOverlap)),ci(:,3)));
+ci(idxDel,:) = [];
+idxDel = find(arrayfun(@(x) isempty(intersect(x,tOverlap)),cj(:,3)));
+cj(idxDel,:) = [];
+
+
+if isempty(ci) || isempty(cj)
+ d = Inf;
+ return
+end
+dx = sqrt( (ci(:,1) - cj(:,1)).^2 + (ci(:,2)-cj(:,2)).^2);
+d = median(dx);
\ No newline at end of file
diff --git a/matlab/+SSF/velocity_kymo.m b/matlab/+SSF/velocity_kymo.m
new file mode 100644
index 0000000000000000000000000000000000000000..cf5dd267069bfd9269829ea0a00a3d9045580442
--- /dev/null
+++ b/matlab/+SSF/velocity_kymo.m
@@ -0,0 +1,42 @@
+function im_v_kymo = velocity_kymo(strDB,bDownscale)
+[conn,CONSTANTS,segParams]=openDB(strDB);
+
+szIm = Helpers.volumeSize(CONSTANTS);
+% kymo is (x,y,t)
+if bDownscale
+ szIm(1:2) = round(szIm(1:2) ./ 2);
+end
+im_v_kymo = zeros([szIm(2),szIm(1),szIm(5)]);
+
+for time = 1:CONSTANTS.imageData.NumberOfFrames
+ cmd = ['select srcCell.centroid as src_centroid,srcCell.time src_time, srcCell.maxRadius as src_maxRadius, '...
+ 'dstCell.centroid as dst_centroid,dstCell.time as dst_time,dstCell.maxRadius as dst_maxRadius, CC.* from '...
+ '(select * from (select tblCells.centroid,tblCells.maxRadius,cellID_src,cellID,time,min(cost) from tblCells '...
+ ' inner join tblDistCC on cellID=cellID_dst where time = ' num2str(time)...
+ ' group by cellID) as src inner join'...
+ '(select cellID_dst,cellID,time,min(cost) from tblCells '...
+ ' inner join tblDistCC on cellID=cellID_src where time = ' num2str(time)...
+ ' group by cellID) as dst on src.cellID=dst.cellID) as CC' ...
+ ' inner join tblCells as srcCell on CC.cellID_src = srcCell.cellID '...
+ ' inner join tblCells as dstCell on CC.cellID_dst = dstCell.cellID'];
+ q=fetch(conn,cmd);
+%
+ for i = 1:height(q)
+ csrc = jsondecode(q.src_centroid{i});
+ cdst = jsondecode(q.dst_centroid{i});
+ cx = jsondecode(q.centroid{i});
+ vsrc = norm(cx-csrc); % in velocity
+ vdst = norm(cdst-cx); % out velocity
+ v = (vsrc+vdst)/2.0; % average in velocity and out velocity
+ maxRadius = max([q.maxRadius(i),q.dst_maxRadius(i),q.src_maxRadius(i)]);
+ v = v / (3*maxRadius); % 3*maxRadius is the velocity gate
+ if bDownscale
+ cx = cx ./2;
+ end
+ cx = round(cx);
+
+ im_v_kymo(cx(2),cx(1),time) = v;
+ end
+end
+close(conn);
+%
\ No newline at end of file
diff --git a/matlab/+SSF/write_ssf_tracks.m b/matlab/+SSF/write_ssf_tracks.m
new file mode 100644
index 0000000000000000000000000000000000000000..e72523a058e4b8ad430748313a5e2eade1325762
--- /dev/null
+++ b/matlab/+SSF/write_ssf_tracks.m
@@ -0,0 +1,31 @@
+
+% classList = unique(classMap.values);
+for ff = 1:1 %length(flist)
+ strDB = fullfile(flist(ff).folder,flist(ff).name);
+ [conn,CONSTANTS,segParams]=openDB(strDB);
+
+ cmd = 'select trackID from tblCells inner join tblFamilies on cellID = cellID_parent';
+ q = fetch(conn,cmd);
+ close(conn);
+
+ ssf_tracks = movie_tracks{ff};
+ tids = ssf_tracks.keys;
+ tids = [tids{:}];
+ tids = intersect(tids,q.trackID);
+ tblSSF = table();
+ for i = 1:length(tids)
+ ssf = ssf_tracks(tids(i));
+
+ if size(ssf,2) <= 10 || all(0==ssf(1,:))
+ continue
+ end
+ x=zeros(1,CONSTANTS.imageData.NumberOfFrames);
+ x(ssf(2,:)) = ssf(1,:);
+ nt = table();
+ nt.trackID = tids(i);
+ nt.SSF = {x};
+ tblSSF = [tblSSF ; nt];
+ end
+end
+[~,fname,~] = fileparts(flist(ff).name);
+writetable(tblSSF,[fname '_dhb_full.csv'])
\ No newline at end of file
diff --git a/matlab/+Segment/aiAreaOpen.m b/matlab/+Segment/aiAreaOpen.m
index d2d04ce2436a2f58ab9c59e4a034efc899f221a1..6aed349bc36e64ca48f04da8fed93fff6dbb50fc 100644
--- a/matlab/+Segment/aiAreaOpen.m
+++ b/matlab/+Segment/aiAreaOpen.m
@@ -1,19 +1,22 @@
function bw=aiAreaOpen(bw,min_radius_pixels,bFill)
-if numel(bw)>25e6 % && ~is3D(bw)
- % 2d huge image - use pi*r^2 approximation for speed
- radius=min_radius_pixels(1);
- area = radius^2 * pi;
- area=round(area);
- bw=bwareaopen(bw,area);
+if min(min_radius_pixels)/max(min_radius_pixels) < 0.25
+ baniso = true;
+else
+ % isotropic - use faster approximation bwareaopen
+ baniso = false;
+end
+if ~baniso
+ min_area_pixels = Segment.getPixelArea(min_radius_pixels,is3D(bw));
+ bw=bwareaopen(bw,min_area_pixels);
return;
end
if ~exist('bFill','var')
bFill=false;
end
-% maskRadius=0.5*min_radius_pixels;
-maskRadius=min_radius_pixels;
+maskRadius=floor(min_radius_pixels);
+% maskRadius=ceil(min_radius_pixels);
maskRadius=max(maskRadius,[1,1,1]);
if ~is3D(bw)
maskRadius(3)=0;
diff --git a/matlab/+Segment/allocateShake.m b/matlab/+Segment/allocateShake.m
deleted file mode 100644
index 22a7c4728870aaa48c7f89d6a17699a9807ae66b..0000000000000000000000000000000000000000
--- a/matlab/+Segment/allocateShake.m
+++ /dev/null
@@ -1,33 +0,0 @@
-function [L,num,bwBoundary]=allocateShake(bw,bw2,min_radius_pixels,segParams)
-
-bwBoundary=assignShake(bw,bw2,true);
-bwReduce=Segment.aiAreaOpen(bwBoundary,min_radius_pixels);
-% any components that were not big enough?
-if find(bwBoundary & ~bwReduce,1,'first')
- % "re-absorb" components too small to exist on their own
- % allow disconnected components in case whole CC was removed
- bwBoundary=assignShake(bwReduce,bw2,false);
- bwBoundary=Segment.aiAreaOpen(bwBoundary,min_radius_pixels);
-end
-bwBoundary=imfill(bwBoundary,'holes');
-% now, the boundary has been resent, label that and done
-[L,num]=bwlabeln(bwBoundary);
-return
-
-function bwBoundary=assignShake(bw,bw2,bNoDisconnected)
-d=bwdist(bw);
-L=watershed(d);
-L(~bw2)=0;
-bwBoundary=logical(L); % cell image with boundaries set to 0
-% don't allow disconnected components
-if bNoDisconnected
- [LX,nx]=bwlabeln(bwBoundary);
- idx=unique(LX(bw));
- % the boundary image, remove the connected components not from bw (e.g.
- % bw2 only)
- bwBoundary=bwBoundary&ismember(LX,idx);
-end
-bwBoundary=bwBoundary|bw;
-
-
-
diff --git a/matlab/+Segment/denoise.m b/matlab/+Segment/denoise.m
new file mode 100644
index 0000000000000000000000000000000000000000..e8aad9605f3799ca8abe7e897e2c3974eb5fd8c7
--- /dev/null
+++ b/matlab/+Segment/denoise.m
@@ -0,0 +1,55 @@
+function im=denoise(im,segParams,bNorm)
+
+if ~exist('bNorm','var')
+ bNorm=true;
+end
+
+if false==segParams.denoise
+ im=im2single(mat2gray(im));
+ return
+end
+
+bUseCuda=segParams.useCuda&&~ismac && HIP.Cuda.DeviceCount>0;
+if 4~=length(segParams.NLM)
+ bUseCuda=false;
+else
+ nlm_h=segParams.NLM(1);
+ nlm_sw_radius=segParams.NLM(2);
+ nlm_nh_radius=segParams.NLM(3);
+ nlm_hpf=segParams.NLM(4);
+ szFilter=size(im).*nlm_hpf;
+end
+if is3D(im)
+ % 3D
+ if bUseCuda
+ targetDevice = getCudaTarget();
+ imx=HIP.Cuda.NLMeans(im,nlm_h,nlm_sw_radius,nlm_nh_radius,targetDevice);
+ if nlm_hpf
+ imx=imx-HIP.Cuda.Gaussian(im,szFilter,1,targetDevice);
+ end
+ else
+ imx = medfilt3(im);
+ for i=1:30
+ imx=medfilt3(imx);
+ end
+ end
+else
+ % 2D
+ if bUseCuda
+ targetDevice = getCudaTarget();
+ imx=HIP.Cuda.NLMeans(im,nlm_h,nlm_sw_radius,nlm_nh_radius,targetDevice);
+ if nlm_hpf
+ imx=imx-HIP.Cuda.Gaussian(im,[szFilter,1],1,targetDevice);
+ end
+ else
+ imx=imnlmfilt(im);
+ end
+end
+
+if bNorm
+ im = im2single(mat2gray(imx));
+else
+ im = imx;
+end
+
+
diff --git a/matlab/+Segment/findNearestSegmentation.m b/matlab/+Segment/findNearestSegmentation.m
index 4775ce061e7f492850d572192468700c6feb4449..e989ba10bf2aec31ce8123d54752e29c82ef7202 100644
--- a/matlab/+Segment/findNearestSegmentation.m
+++ b/matlab/+Segment/findNearestSegmentation.m
@@ -1,9 +1,10 @@
-function cxCell = findNearestSegmentation(cellList,targetPoint)
-
+function [cxCell,dMin,idxMin] = findNearestSegmentation(cellList,targetPoint)
+dMin = 0;
for i=1:length(cellList)
if intersect(cellList(i).pts,targetPoint,'rows')
cxCell = cellList(i);
+ idxMin = i;
return
end
end
@@ -13,5 +14,5 @@ if length(targetPoint)==2
targetPoint(3)=0;
end
dd = pdist2(vertcat(cellList.centroid),targetPoint);
-[~,idx] = min(dd);
-cxCell = cellList(idx);
+[dMin,idxMin] = min(dd);
+cxCell = cellList(idxMin);
diff --git a/matlab/+Segment/frameSegment.m b/matlab/+Segment/frameSegment.m
index 055b7cca86234dc195349463375bed9b6247f0a2..58756230a73dbb0f87c25dd2734cd0cc6728d7bf 100644
--- a/matlab/+Segment/frameSegment.m
+++ b/matlab/+Segment/frameSegment.m
@@ -14,11 +14,6 @@ if isdeployed()
segParams.draw=false;
end
-if prod(CONSTANTS.imageData.Dimensions*8)>1e9
- % huge image -- force cuda to use the mutex
-% setenv('HYDRA_ENABLE_MUTEX','1');
-end
-
global DRAW
DRAW=segParams.draw;
@@ -44,26 +39,23 @@ min_radius_pixels = segParams.minimumRadius_um ./ resolution_um;
chan=segParams.channels(1); % default channel
if exist('imCompCache','var')
- im=imCompCache.im;
- imLoG=imCompCache.imLoG;
+ im = imCompCache.im;
+ imLoG = imCompCache.imLoG;
+ caChannelLoG = imCompCache.caChannelLoG;
else
- [im,imLoG]=DenoiseCache.readImages(t,CONSTANTS,segParams,medianMask);
+ im = DenoiseCache.readImages(t,CONSTANTS,segParams,medianMask);
+ [imLoG, ~, ~] = LoG.getCompositeLoG(im,CONSTANTS,segParams);
+ caChannelLoG = Segment.getChannelLoG(CONSTANTS, t, segParams);
end
if isempty(im) || all(im(:)==0)
ljsLog(sprintf('frameSegment: empty image at time=%d -- skipping\n',t));
return;
end
-if is3D(im)
- min_area_pixels = 4/3*pi* mean(min_radius_pixels)^3;
-else
- min_radius_pixels=min_radius_pixels(1);
- min_area_pixels = min_radius_pixels^2 * pi;
-end
+[min_area_pixels,min_radius_pixels] = Segment.getPixelArea(min_radius_pixels,is3D(CONSTANTS));
if segParams.bCytoplasmic
min_area_pixels=min_area_pixels*4;
end
-min_area_pixels = ceil(min_area_pixels);
if DRAW
imRaw=MicroscopeData.Reader('imageData',CONSTANTS.imageData, 'chanList',segParams.channels(1),'timeRange',[t t], 'outType','single','prompt',false);
@@ -78,41 +70,35 @@ if DRAW
drawnow
end
-[bw,bwLog]=Segment.thresholdImages(im,imLoG,segParams, min_radius_pixels,min_area_pixels,...
- medianMask);
+[bw, bwLoG_pos, imn, imp] = Segment.thresholdLoG_negative(imLoG,segParams);
+bw = bwareaopen(bw,ceil(min_area_pixels));
+
+bwLoG_pos = bwareaopen(bwLoG_pos,ceil(min_area_pixels));
-if segParams.membraneChannel>0
- bwMembrane=Segment.getMembrane(CONSTANTS,segParams.membraneChannel,t);
- if ~isempty(bwMembrane)
- bwLog=bwLog|bwMembrane;
- end
-end
-bwChannelLoG=Segment.getChannelLoG(segParams,CONSTANTS,t);
-if ~isempty(bwChannelLoG)
- bwLog=bwLog|bwChannelLoG;
+% [bw, bwLoG_pos] = LoG.cleanLoG(bwLoG_pos, bw, min_area_pixels, min_radius_pixels);
+if all(0==bw(:))
+ return
end
-% bw2 is all the pixels in our foreground image. after we mask, some
-% of those pixels will be discarded in resolving the underlying cells.
-% allocateShake (below) assigns each discarded pixel to it's closest
-% touching segmentation using a morphological region fill
-bw2=bw;
+% % bw2 is all the pixels in our foreground image. after we mask, some
+% % of those pixels will be discarded in resolving the underlying cells.
+% % allocateShake (below) assigns each discarded pixel to it's closest
+% % touching segmentation using a morphological region fill
+bw2 = bw;
-bw=Segment.segReduce(bw,bwLog,segParams,min_radius_pixels);
-if is3D(bw)
- % fill on a slice by slice basis
- for z=1:CONSTANTS.imageData.Dimensions(3)
- bw(:,:,z)=bw(:,:,z)|imfill(bw(:,:,z),'holes');
- end
-else
- if ~segParams.isPhase
- bw=bw|imfill(bw,'holes');
- end
+% combine blob image from non-seg channels if specified
+if ~isempty(caChannelLoG)
+ imChannel_LoG = LoG.channelLoG_separate(caChannelLoG, bw, min_radius_pixels);
+ imn = imn+imChannel_LoG;
end
-[L,num,bwBoundary]=Segment.allocateShake(bw,bw2,min_radius_pixels,segParams);
-[L2]=bwlabeln(bw2); % used to mark original cc for segCC field
+L = Segment.segReduce(bw, imn, min_area_pixels);
+[L2] = bwlabeln(bw2); % used to mark original cc for segCC field
+
+if ~is3D(CONSTANTS)
+ [bounds,L] = bwboundaries(L);
+end
if bEnsemble
if size(bw,3)>1
@@ -124,24 +110,27 @@ else
rp=[];
end
-% final CC pass
-if ~is3D(im)
- bounds=bwboundaries(bwBoundary,'noholes');
- if length(bounds)~=num
- fprintf(2,'ACK frameSegment: boundaries and num components !=\n');
- end
-end
-CC=bwconncomp(L);
-for n=1:num
- idx=CC.PixelIdxList{n};
- if length(idx)<3
+
+for n=1:max(L(:))
+
+ idx=find(L==n);
+ if length(idx)<min_area_pixels
continue
end
if is3D(im)
newCell=Segment.frameSegment_create_3D(idx,size(bw),chan,t);
else
- newCell=Segment.frameSegment_create(idx,size(bw),chan,t,[],[],bounds(n));
+ if isempty(bounds{n})
+ ljsLog(' ACK!! empty bounds! tough to repro! find me!!!\n',0);
+ continue
+ end
+ newCell=Segment.frameSegment_create(idx,size(bw),chan,t,[],[],bounds(n));
+ if isempty(intersect(newCell.surface,newCell.pts,'rows'))
+ fprintf('bad surface, n=%d,r=%d\n',n,segParams.minimumRadius_um);
+ end
end
+ newCell.idxPts = idx;
+ newCell.n = n;
segL=unique(L2(idx));
segL(0==segL)=[];
if length(segL)>1
@@ -151,30 +140,53 @@ for n=1:num
if bEnsemble
newCell=Ensemble.setCellFeatures(newCell,rp,n,segParams);
end
-
- if DRAW && ~is3D(im)
- for i=1:length(newCell)
- nc=newCell(i);
- cmap=hsv(255);
- cidx=1+round(rand()*254);
- plot(nc.surface(:,1),nc.surface(:,2),'color',cmap(cidx,:),'linewidth',1);
-% drawnow
- end
+ newCell.LoG = LoG.sampleCell(newCell,CONSTANTS,imLoG);
+
+ % check ecc
+ v = eig(cov(newCell.pts));
+ ecc = max(v)/min(v);
+ if ecc>50
+ continue
end
+% if is3D(imLoG)
+% threshLoG = -1e-2;
+% else
+% threshLoG = -1e-3;
+% end
+% if (newCell.LoG >threshLoG)
+% % disallow segmentation based on centroid LoG thresholding
+% continue
+% end
+
Cells=[Cells newCell];
end
+if ~isempty(Cells)
+ threshLoG = mean([Cells.LoG])/10;
+ idx = find([Cells.LoG]>threshLoG); % use > since LoG is negative on nuclear channel
+% Cells(idx) = [];
+ % % on ensembleSeg
+ if 1 || bEnsemble
+ Cells=Ensemble.setCellEfficiency(Cells,CONSTANTS,im,imLoG,segParams,medianMask);
+ % Cells = Ensemble.set_LoG_score(Cells,CONSTANTS,im,imLoG,segParams);
+ end
+end
+
+if DRAW && ~is3D(im)
+ for i=1:length(Cells)
+ nc=Cells(i);
+ cmap=hsv(255);
+ cidx=1+round(rand()*254);
+ plot(nc.surface(:,1),nc.surface(:,2),'color',cmap(cidx,:),'linewidth',1);
+% drawnow
+ end
+end
-% % on ensembleSeg
-if bEnsemble
- Cells=Ensemble.setCellEfficiency(Cells,CONSTANTS,im,imLoG,segParams,medianMask);
- Cells = Ensemble.set_LoG_score(Cells,CONSTANTS,imLoG,segParams);
-end
tElapsed=toc;
sz=sprintf('segmented frame %d found %d hulls, minRadius=%f time=%0.0f\n',t,length(Cells),segParams.minimumRadius_um,tElapsed);
ljsLog(sz,3);
if DRAW
- title([num2str(tElapsed,'%0.0f') 'seconds']);
+ title([num2str(segParams.minimumRadius_um) 'um']);
drawnow
end
4;
diff --git a/matlab/+Segment/frameSegment_create.m b/matlab/+Segment/frameSegment_create.m
index a7157dc0cdb8d375ed20f4974a36ae4d4b20e726..a15abb9b47568efede00e3eebe67ebe3bd6ce0d4 100644
--- a/matlab/+Segment/frameSegment_create.m
+++ b/matlab/+Segment/frameSegment_create.m
@@ -7,14 +7,20 @@ function newCell=frameSegment_create(idxPixels, imSize, channel, time, ...
return;
end
- if ~exist('bounds','var')
+ if ~exist('bounds','var') || isempty(bounds)
bw=logical(zeros(imSize));
bw(idxPixels)=1;
bounds=bwboundaries(bw);
end
newCell=[];
- newCell.surface=[bounds{1}(:,2),bounds{1}(:,1)];
+ if isempty(bounds) || length(bounds{1})<2
+ fprintf(2,'ACK!');
+ newCell
+ newCell.surface = newCell.centroid;
+ else
+ newCell.surface=[bounds{1}(:,2),bounds{1}(:,1)];
+ end
[r,c]=ind2sub(imSize,idxPixels);
diff --git a/matlab/+Segment/frameSegment_create_3D.m b/matlab/+Segment/frameSegment_create_3D.m
index 53c0162f64f17321c7a0a24b0a5bddef03c3852e..cb516ff8e4520b2872a1bf3f219a43691584675b 100644
--- a/matlab/+Segment/frameSegment_create_3D.m
+++ b/matlab/+Segment/frameSegment_create_3D.m
@@ -46,15 +46,11 @@ szCrop=[max(r)+PAD,max(c)+PAD,max(z)+PAD];
bwCrop=zeros(szCrop);
idxScale=sub2ind(szCrop,round(r),round(c),round(z));
bwCrop(idxScale)=1;
-bwResize=imresize3(bwCrop,scaleFactor);
-[faces,verts]=isosurface(bwResize,graythresh(bwResize));
-norms = isonormals(bwResize,verts);
-
-% put verts back into image space
-verts=verts-0.25;
-% first unscale
-unscale=szCrop./size(bwResize);
-verts=verts.*unscale;
+
+[faces,verts] = isosurface(bwCrop,graythresh(bwCrop));
+[faces,verts] = reducepatch(faces,verts,scaleFactor);
+norms = isonormals(bwCrop,verts);
+
% now uncrop
verts=verts+[cl,rl,zl]-PAD;
diff --git a/matlab/+Segment/getChannelLoG.m b/matlab/+Segment/getChannelLoG.m
index 050e1fad99f299fd59f048ceb39dddb68c33e1b8..55657b93f507117dff083cdf36a65686b509e94a 100644
--- a/matlab/+Segment/getChannelLoG.m
+++ b/matlab/+Segment/getChannelLoG.m
@@ -1,38 +1,16 @@
-function [bwLoG,imc]=getChannelLoG(segParams,CONSTANTS,t)
-bwLoG=[];
-if isempty(segParams.logChannels)
+% returns a cell array of LoG images, 1 per channel
+function caChannelLoG = getChannelLoG(CONSTANTS, t, segParams)
+
+caChannelLoG = [];
+logChannels=segParams.logChannels;
+if isempty(logChannels)
return
end
-logChannels=segParams.logChannels;
+
for cc=1:length(logChannels)
channel=abs(logChannels(cc));
- im = MicroscopeData.Reader('imageData',CONSTANTS.imageData, 'chanList',channel,...
- 'timeRange',[t t], 'outType','single','prompt',false);
- if isempty(im) || all(im(:)==0)
- return;
- end
- imf = 0*im;
- for rr=1:0.1:1.4
- radiusPixels = rr .* LoG.getRadiusPixels(CONSTANTS,segParams);
- imf = imf + HIP.LoG(im,radiusPixels,[]);
- end
- imp=imf;
- imp(imp<0)=0;
- imn=imf;
- imn(imn>0)=0;
- imn=abs(imn);
- imc(:,:,1)=mat2gray(imp);
- imc(:,:,2)=mat2gray(imn);
- imc(:,:,3)=0*imn;
-
- if logChannels(cc)>0
- % nuclear channel - bright blob - use + side
-% continue
- bwLoG=imbinarize(imp);
- else
- bwLoG=imbinarize(imn);
- end
+ im = Segment.getImages(CONSTANTS,t,channel,segParams);
- %
+ [caChannelLoG{cc}, ~, ~ ] = LoG.getCompositeLoG(im,CONSTANTS,segParams);
end
4;
\ No newline at end of file
diff --git a/matlab/+Segment/getDefaultSegParams.m b/matlab/+Segment/getDefaultSegParams.m
index 4aa13f496417083891c076f0a754bd2cbd037635..ccb992553cf363734f70a16fcdacc749564a800a 100644
--- a/matlab/+Segment/getDefaultSegParams.m
+++ b/matlab/+Segment/getDefaultSegParams.m
@@ -1,7 +1,7 @@
function segParams=getDefaultSegParams()
segParams=[];
segParams.draw=false;
-segParams.minimumRadius_um=[1.5,0.25,2.5];
+segParams.minimumRadius_um=5;
segParams.channels=1;
segParams.colonyChannel=-1;
segParams.logChannels=[];
@@ -11,7 +11,7 @@ segParams.wellRadius=-1;
segParams.useCuda=true;
segParams.nCores=feature('numcores'); % for ensemble seg only
segParams.storeEnsemble=true;
-segParams.sensitivity=0.5;
+segParams.sensitivity=0;
segParams.denoise=true;
segParams.bCytoplasmic=false;
segParams.bCircular=false;
diff --git a/matlab/+Segment/getImages.m b/matlab/+Segment/getImages.m
index 8da11624437087cab3f1f4814bb8b6f35a5f7f6a..562998b4d3489fccad5928325b17aa480c3d0ac5 100644
--- a/matlab/+Segment/getImages.m
+++ b/matlab/+Segment/getImages.m
@@ -9,55 +9,10 @@ if 1==segParams.wellRadius && exist('medianMask','var') && ~isempty(medianMask)
im=im-medianMask;
im=mat2gray(im);
end
-im=denoise(im,segParams);
+im=Segment.denoise(im,segParams);
if 1==nargout
return
end
imLog=Segment.getLoG(im,CONSTANTS,segParams);
4;
-function im=denoise(im,segParams)
-
-if false==segParams.denoise
- im=im2single(mat2gray(im));
- return
-end
-
-bUseCuda=segParams.useCuda&&~ismac && HIP.Cuda.DeviceCount>0;
-if 4~=length(segParams.NLM)
- bUseCuda=false;
-else
- nlm_h=segParams.NLM(1);
- nlm_sw_radius=segParams.NLM(2);
- nlm_nh_radius=segParams.NLM(3);
- nlm_hpf=segParams.NLM(4);
- szFilter=size(im).*nlm_hpf;
-end
-if is3D(im)
- % 3D
- if bUseCuda
- imx=HIP.Cuda.NLMeans(im,nlm_h,nlm_sw_radius,nlm_nh_radius,[]);
- if nlm_hpf
- imx=imx-HIP.Cuda.Gaussian(im,szFilter,1,[]);
- end
- else
- imx = medfilt3(im);
- for i=1:30
- imx=medfilt3(imx);
- end
- end
-else
- % 2D
- if bUseCuda
- imx=HIP.Cuda.NLMeans(im,nlm_h,nlm_sw_radius,nlm_nh_radius,[]);
- if nlm_hpf
- imx=imx-HIP.Cuda.Gaussian(im,[szFilter,1],1,[]);
- end
- else
- imx=imnlmfilt(im);
- end
-end
-
-im=im2single(mat2gray(imx));
-
-
diff --git a/matlab/+Segment/getLoG.m b/matlab/+Segment/getLoG.m
index accff54d53b0b82ac1d96a38b296700df43ec9c1..e45ff5562082dd47aa8c25bb31b45b705d539225 100644
--- a/matlab/+Segment/getLoG.m
+++ b/matlab/+Segment/getLoG.m
@@ -14,7 +14,7 @@ if isempty(im)
return;
end
-bUseCuda=segParams.useCuda&&~ismac && HIP.Cuda.DeviceCount>0;
+bUseCuda=true;
resolution_um=CONSTANTS.imageData.PixelPhysicalSize; % um per pixel
min_radius_pixels = segParams.minimumRadius_um ./ resolution_um;
@@ -50,6 +50,7 @@ else
logRadius=((1/sqrt(2)).*min_radius_pixels);
end
-imLoG=HIP.LoG(im,logRadius,[]);
+targetDevice = getCudaTarget();
+imLoG=HIP.LoG(im,logRadius,targetDevice);
4;
diff --git a/matlab/+Segment/getPixelArea.m b/matlab/+Segment/getPixelArea.m
new file mode 100644
index 0000000000000000000000000000000000000000..b5e962464468a4c8c7d1c8d142cbae7a13ac8c62
--- /dev/null
+++ b/matlab/+Segment/getPixelArea.m
@@ -0,0 +1,10 @@
+function [min_area_pixels,min_radius_pixels] = getPixelArea(min_radius_pixels,b3D)
+
+if b3D
+ min_area_pixels = 4/3*pi* min(min_radius_pixels)^3;
+else
+ min_radius_pixels=min_radius_pixels(1);
+ min_area_pixels = (min_radius_pixels)^2 * pi;
+end
+min_area_pixels = ceil(min_area_pixels);
+
diff --git a/matlab/+Segment/label2boundary.m b/matlab/+Segment/label2boundary.m
new file mode 100644
index 0000000000000000000000000000000000000000..d681bc99ae582646f55dcc2afe52c2511b1cc073
--- /dev/null
+++ b/matlab/+Segment/label2boundary.m
@@ -0,0 +1,49 @@
+function boundsL = label2boundary(L)
+warning('off','images:bwfilt:tie');
+boundsL={};
+lmask = L.*boundarymask(L);
+for i=1:max(lmask(:))
+ bw = (lmask==i);
+ % if a segmentation has multiple CCs, keep only the largest
+ bw = bwareafilt(bw,1);
+ [r,c] = find(bw,1,'first');
+% bi = bwboundaries(bw);
+ bi = bwtraceboundary(bw,[r,c],'N');
+ if length(bi)>1
+% [~,idxMax] = max(cellfun(@length,bi));
+% bi = bi(idxMax);
+ end
+% plot(bi(:,2),bi(:,1),'-r')
+ boundsL{i} = bi;
+end
+4;
+%
+%
+% lx = L.*~boundarymask(L);
+% bounds = bwboundaries(lx);
+% boundsKey=cell(max(L(:)),1);
+% for i=1:length(bounds)
+% idx = sub2ind(size(L),bounds{i}(:,1),bounds{i}(:,2));
+% lkey = unique(L(idx));
+% boundsKey{lkey}=[boundsKey{lkey},i];
+% end
+% % if there are >1 boundary component, take the one with the most pixels
+% for i=1:length(boundsKey)
+% if 1==length(boundsKey{i})
+% continue
+% end
+% lx = arrayfun(@(x) length(find(L==x)), boundsKey{i});
+% [~,idxMax]=max(lx);
+% boundsKey{i} = [boundsKey{i}(idxMax)];
+% end
+%
+% boundsL = cell(max(L(:)),1);
+% for i=1:max(L(:))
+% if isempty(boundsKey{i})
+% ljsLog('ack! empty boundary label : %d\n',2);
+% continue
+% end
+% boundsL(i) = bounds(boundsKey{i}(1));
+% end
+% 4;
+%
diff --git a/matlab/+Segment/segReduce.m b/matlab/+Segment/segReduce.m
index 001af6cb25768159c73512e7b325dc1ae321bf66..654da8f96e0c52d15a57230ffb19fe0c7e64a27a 100644
--- a/matlab/+Segment/segReduce.m
+++ b/matlab/+Segment/segReduce.m
@@ -1,84 +1,32 @@
-
-function bwOut=segReduce(bw,bwLog,segParams,min_radius_pixels)
-%
-% if segParams.isPhase
-% bwOut=phaseReduce(bw,bwLog,min_radius_pixels);
-% return;
-% end
-
-if is3D(bw)
- % anisotropic dilater
- % seZ dilates bwLoG in 3-D
- seZ=strel('sphere',1);
- seZ=seZ.Neighborhood;
- % se dilates bwLoG in 2-D only
- se=seZ;
- se(:,:,1)=0;
- se(:,:,3)=0;
- % zDilate controls so we use seZ only every zDilate iterations
- zDilate=round(min_radius_pixels(1)/min_radius_pixels(3));
- zDilate=max(1,zDilate);
-else
- se=strel('disk',1);
-end
-
-bwOut=bw;
-if segParams.isPhase
- nIter=1;
-elseif segParams.bCytoplasmic
- nIter=3;
-else
- nIter=ceil(pi*min_radius_pixels(1));
- nIter=max(nIter,10);
-end
-
-for nDilate=1:nIter
- bwKernels=bwOut&~bwLog;
- bwKernels=imfill(bwKernels,'holes');
-% bwKernels=Segment.aiAreaOpen(bwKernels,0.5*min_radius_pixels);
-bwKernels=Segment.aiAreaOpen(bwKernels,min_radius_pixels);
- L=bwlabeln(bwKernels);
- CC=bwconncomp(bwOut);
- workingL=double(labelmatrix(CC));
- % 3 things can happen: (0) CC s (1) CC disappears (2) CC splits
- idxWL=vertcat(CC.PixelIdxList{:});
- map=unique([workingL(idxWL),L(idxWL)],'rows');
- if isempty(map)
- break;
- end
- map(map(:,2)==0,:)=[];
- mapCounts=hist(map(:,1),[1:max(map(:,1))])';
- idxChange=find(mapCounts>1);
- for i=1:length(idxChange)
- % copy over new objects to bwOut
- idxMap=find(map(:,1)==idxChange(i),1,'first');
- idx=CC.PixelIdxList{map(idxMap,1)};
- bwOut(idx)=logical(L(idx));
- end
-
- if isempty(find(bwKernels, 1))
- break;
- end
- % dilate anisotropically
- if is3D(bwLog) && 0==mod(nDilate,zDilate)
- bwLog=imdilate(bwLog,seZ);
- else
- bwLog=imdilate(bwLog,se);
- end
-end
-4;
-
-function bwReduce=phaseReduce(bw,bwLog,min_radius_pixels)
-bwLogHoles=bwLog;
-bwLogHoles=imfill(bwLogHoles,'holes')&~bwLogHoles;
-bwReduce=bw&bwLogHoles;
-bwReduce=imfill(bwReduce,'holes');
-bwReduce=Segment.aiAreaOpen(bwReduce,min_radius_pixels);
-[L,num]=bwlabeln(bw);
-for n=1:num
- idx=find(L==n);
- if all(bwReduce(idx)==0)
- bwReduce(idx)=1;
- end
-end
-4;
\ No newline at end of file
+
+function L = segReduce(bw,imn,min_area_pixels)
+% use the LoG image instead of distance for watershed xform
+% empirical maxima surpression with first watershed
+hmax = 0.01;
+L = watershed(-1 * imhmax(imn,hmax));
+% % L=watershed(-1 * imn);
+L(~bw)=0;
+
+rp = regionprops(L,'Area','Centroid');
+% take the LoG response at the centroid of each region
+cx = round(vertcat(rp.Centroid));
+cx(isnan(cx))=1; % lost components have nan centroids and 0 area - removed below
+if is3D(bw)
+ cx_idx = sub2ind(size(bw),cx(:,2),cx(:,1),cx(:,3));
+else
+ cx_idx = sub2ind(size(bw),cx(:,2),cx(:,1));
+end
+% pick out segmentations that are large enough and high enough LoG response
+cx_LoG = imn(cx_idx);
+idx = find([rp.Area]' >= 1 * min_area_pixels & cx_LoG>1e-2);
+bwOut = ismember(L,idx);
+
+% use good segmentations as seeds for marker controlled watershed
+dLoG = imn .* bw;
+dLoG = -1 .* dLoG;
+dLoG2 = imimposemin(dLoG,bwOut); % marker controlled
+L = watershed(dLoG2);
+L(~bw) = 0;
+
+L = bwlabeln(L); % make sure separate CCs are kept separate
+4;
diff --git a/matlab/+Segment/thresholdImages.m b/matlab/+Segment/thresholdImages.m
index bb7131fd0c9dbde257e97a19f4f87a1dbbf28142..8dac1f399aef3cace955c4e164b8d25a4c70ca85 100644
--- a/matlab/+Segment/thresholdImages.m
+++ b/matlab/+Segment/thresholdImages.m
@@ -46,7 +46,7 @@ else
end
% bwLog=Segment.aiAreaOpen(bwLog,2*min_radius_pixels,true);
% bwLog=bwareaopen(bwLog,floor(2*pi*min_radius_pixels));
-bwLoG=cleanLoG(bwLoG);
+bwLoG=LoG.cleanLoG(logical(0*bwLoG), bwLoG, min_area_pixels,min_radius_pixels);
bw=Segment.aiAreaOpen(bw,min_radius_pixels);
4;
@@ -102,20 +102,3 @@ bwMask=bwareaopen(bwMask,500);
bw=bw&~bwMask;
bwLoG=bwLoG&~bwMask;
-% remove spurious LoG noise
-function bwLoG=cleanLoG(bwLoG)
-
-if is3D(bwLoG)
- rp=regionprops3(bwLoG,'ConvexVolume','Volume','VoxelIdxList');
- convDef=[rp.ConvexVolume]./[rp.Volume];
- pixelIdxList=rp.VoxelIdxList;
-else
- rp=regionprops(bwLoG,'ConvexArea','Area','PixelIdxList');
- convDef=[rp.ConvexArea]./[rp.Area];
- pixelIdxList={rp.PixelIdxList};
-end
-idxReset=find(convDef<1.25);
-if ~isempty(idxReset)
- pixelIdxReset=vertcat(pixelIdxList{idxReset});
- bwLoG(pixelIdxReset)=0;
-end
diff --git a/matlab/+Segment/thresholdLoG_negative.m b/matlab/+Segment/thresholdLoG_negative.m
new file mode 100644
index 0000000000000000000000000000000000000000..29aa79124ee71827f938a801a954a8c2f6038a11
--- /dev/null
+++ b/matlab/+Segment/thresholdLoG_negative.m
@@ -0,0 +1,37 @@
+% threshold bright signal on dark background (e. g. H2B, etc.)
+% LoG response is negative (gradiant points down)
+% bwn is the blobs
+% bwp is the gradients
+function [bwn, bwp, imn, imp] = thresholdLoG_negative(imLoG,segParams)
+
+if ~exist('segParams','var') || ~isfield(segParams,'sensitivity')
+ sensitivity = 0.5;
+else
+ sensitivity = segParams.sensitivity;
+end
+
+% ACK! hardcode! ACK!
+sensitivity = 0;
+
+imn = imLoG;
+imn(imn>0)=0;
+imn=abs(imn);
+
+imp = imLoG;
+imp(imp<0) = 0;
+
+if 0== sensitivity
+ if is3D(imLoG)
+ % 3D generally stronger gradients -- more better dimensions
+ % this number is controversial! ACK! set it directly via reference
+ % distribution?
+ epsThresh = 0.05;
+ else
+ epsThresh = 1e-3;
+ end
+ bwn = logical(imn>epsThresh);
+ bwp = logical(imp>0);
+else
+ bwn = imbinarize(imn,'adaptive','sensitivity',sensitivity);
+ bwp = imbinarize(imp,'adaptive','sensitivity',sensitivity);
+end
diff --git a/matlab/+Smooth/+Classify/getMitosisFeatures.m b/matlab/+Smooth/+Classify/getMitosisFeatures.m
index e47ce7446ca54d136c91d425ae6eaa42a7548f73..204e9fcbc8cbe172bb28c634aa14dbced2fd37b5 100644
--- a/matlab/+Smooth/+Classify/getMitosisFeatures.m
+++ b/matlab/+Smooth/+Classify/getMitosisFeatures.m
@@ -44,15 +44,12 @@ centroids=cellfun(@jsondecode,q(:,3),'uniformoutput',false);
centroids=reshape(cell2mat(centroids),3,[])';
parentCandidates=[cell2mat(q(:,1:2)) centroids];
-d1=Read.getCell(conn,d1CellID);
+d1=Read.getCell(conn,d1CellID,CONSTANTS);
costs=findD2Candidates(conn,parentCandidates,time,d1);
if isempty(costs)
return
end
-[~,idx]=min([costs.ratioD1D2]);
-if costs(idx).ratioD1D2>25
- return
-end
+[~,idx]=min(abs(1-[costs.ratioD1D2]));
mitosisNode.ratioD1D2=costs(idx).ratioD1D2;
% make sure daughter is not already in family tree. if density is high
@@ -70,20 +67,20 @@ end
cmd=['select max(time) from tblCells where trackID IN(' num2str(costs(idx).parentDaughterTID(2)), ',' num2str(costs(idx).parentDaughterCID(2)) ') '];
q=ljsFetch(conn,cmd);
t1=q{1};
-if (t1-time)<5 && ~bDebug
- return
-end
+% if (t1-time)<5 && ~bDebug
+% return
+% end
mitosisNode.parentCellID=costs(idx).parentDaughterCID(1);
mitosisNode.siblingCellID=costs(idx).parentDaughterCID(2);
mitosisNode.parentDaughterTID=costs(idx).parentDaughterTID;
-d2=Read.getCell(conn,mitosisNode.siblingCellID);
-p=Read.getCell(conn,mitosisNode.parentCellID);
+d2=Read.getCell(conn,mitosisNode.siblingCellID,CONSTANTS);
+p=Read.getCell(conn,mitosisNode.parentCellID,CONSTANTS);
-% for parent area, select max over last 3 frames
+% for parent area, select max over last 2 frames
cmd=['select area from tblCells where trackID=' num2str(mitosisNode.parentDaughterTID(1))...
- ' and time<' num2str(d1.time) ' and time>=' num2str(p.time-3)];
+ ' and time<' num2str(d1.time) ' and time>=' num2str(d1.time-2)];
q=ljsFetch(conn,cmd);
aparent=cell2mat(q);
@@ -95,40 +92,43 @@ else
areaRatio=ar2;
end
mitosisNode.areaRatio=areaRatio;
-if areaRatio<minAreaRatio || areaRatio>2.5
- return
-end
+
bOcclusionEdge1=Mitosis.checkOcclusionEdge(conn,d1);
bOcclusionEdge2=Mitosis.checkOcclusionEdge(conn,d2);
if bOcclusionEdge1 || bOcclusionEdge2
+ % ???
+ mitosisNode.areaRatio = Inf;
return
end
mitosisNode.sibAreaRatio=max([d1.area,d2.area])/min([d1.area,d2.area]);
+% parent LoG
+cmd=['select LoG from tblCells where trackID=' num2str(p.trackID)...
+ ' and time<' num2str(d1.time) ' and time>=' num2str(p.time-3)];
+q=ljsFetch(conn,cmd);
+parentLoG = min(cell2mat(q));
+% d1 LoG
+cmd=['select LoG from tblCells where trackID=' num2str(d1.trackID)...
+ ' and time>=' num2str(d1.time) ' and time<' num2str(d1.time+3)];
+q=ljsFetch(conn,cmd);
+d1LoG = min(cell2mat(q));
-segParams=Read.getSegmentationParams(conn);
-imCache=Mitosis.getImageCache(conn,CONSTANTS,time,segParams);
-if isempty(imCache)
- return;
-end
+% d1 LoG
+cmd=['select LoG from tblCells where trackID=' num2str(d2.trackID)...
+ ' and time>=' num2str(d1.time) ' and time<' num2str(d2.time+3)];
+q=ljsFetch(conn,cmd);
+d2LoG = min(cell2mat(q));
-d1br=brightShape(d1,imCache.im);
-d2br=brightShape(d2,imCache.im);
-d1t1=getNextDaughter(conn,d1);
-if ~isempty(d1t1)
- d1br=max([d1br,brightShape(d1t1,imCache.imP1)]);
-end
-d2t1=getNextDaughter(conn,d2);
-if ~isempty(d2t1)
- d2br=max([d2br,brightShape(d2t1,imCache.imP1)]);
-end
+mitosisNode.pd1d2LoG = [parentLoG,d1LoG,d2LoG];
-pbr=getParentBR(conn,CONSTANTS,p,imCache);
-mitosisNode.brightRatio=[d1br,d2br,pbr];
-eccParent=getParentECC(conn,imCache,p);
-mitosisNode.eccParent=eccParent;
+mitosisNode.pd1d2Ecc = [Helpers.cellEccentricity(p),Helpers.cellEccentricity(d1),...
+ Helpers.cellEccentricity(d2)];
+
+o1 = length(intersect(p.idxPts,d1.idxPts))/min(length(p.idxPts),length(d1.idxPts));
+o2 = length(intersect(p.idxPts,d2.idxPts))/min(length(p.idxPts),length(d2.idxPts));
+mitosisNode.pd1d2overlap = [o1,o2];
4;
% end of find family
@@ -140,113 +140,41 @@ for i=1:size(parentCandidates,1)
% % target sibling 2 is the cell parent candidate tracked 2
% parentCandidates are [cellID,trackID,centroid]
- [d2TrackID,d2CellID,d2Centroid]=getDaughter2(conn,parentCandidates(i,:),time,d1);
- if isempty(d2TrackID)
+ d2 = getDaughter2(conn,parentCandidates(i,:),time,d1);
+ if isempty(d2)
continue
end
- if d2CellID==d1.cellID
+ if d2.cellID==d1.cellID
% need to come in via the other sibling!
return
end
-
+ d1d2LoG = abs([d1.LoG,d2.LoG]);
+ d1d2LoG = min(d1d2LoG)/max(d1d2LoG);
+% if d1d2LoG < 0.5
+% continue
+% end
pCentroid=parentCandidates(i,3:5);
% midpoint of line between daughters -- this is where we'd like to see
% the parent
- pmid=(d2Centroid+d1.centroid)/2;
+ pmid=(d2.centroid+d1.centroid)/2;
nc=[];
- nc.parentDaughterCID=[parentCandidates(i,1),d2CellID,];
+ nc.parentDaughterCID=[parentCandidates(i,1),d2.cellID,];
nc.parentToDaughterMidpoint=norm(pCentroid-pmid);
nc.dParentD1=Mitosis.cellDistance(conn,d1.cellID,parentCandidates(i,1));
- nc.dParentD2=Mitosis.cellDistance(conn,d2CellID,parentCandidates(i,1));
- nc.parentDaughterTID=[parentCandidates(i,2),d2TrackID];
+ nc.dParentD2=Mitosis.cellDistance(conn,d2.cellID,parentCandidates(i,1));
+ nc.parentDaughterTID=[parentCandidates(i,2),d2.trackID];
+
+ ratioD1D2 = min(nc.dParentD1,nc.dParentD2) / max(nc.dParentD1,nc.dParentD2);
nc.ratioD1D2=nc.dParentD1/nc.dParentD2;
+ nc.d1d2LoG = d1d2LoG;
costs=[costs nc];
end
-function eccParent=getParentECC(conn,imCache,p)
-eccParent=getEcc(size(imCache.im),p);
-cmd=['select cellID from tblCells where time=' num2str(p.time-1) ' and '...
- ' trackID= ' num2str(p.trackID)];
-q=ljsFetch(conn,cmd);
-if isempty(q)
- return
-end
-p1=Read.getCell(conn,q{1});
-eccParent1=getEcc(size(imCache.im),p1);
-eccParent=min([eccParent,eccParent1]);
-
-
-function pbr=getParentBR(conn,CONSTANTS,p,imCache)
-
-% parent needs to be in frame t-1
-pbr=brightShape(p,imCache.imM1);
-cmd=['select cellID from tblCells where time=' num2str(p.time-1) ' and '...
- ' trackID= ' num2str(p.trackID)];
-q=ljsFetch(conn,cmd);
-if isempty(q)
- return
-end
-p1=Read.getCell(conn,q{1});
-pbr1=brightShape(p1,imCache.imM2);
-pbr=max([pbr,pbr1]);
-
-function d=getNextDaughter(conn,cell)
-
-cmd=['select cellID from tblCells where trackID=' num2str(cell.trackID) ' and time=' num2str(cell.time)];
-q=ljsFetch(conn,cmd);
-if isempty(q)
- d=[];
- return;
-end
-nextID=q{1};
-d=Read.getCell(conn,nextID);
-
-% mse between distance transform and intensity profile
-function br=brightShape(cell,im)
-
-if isempty(im)
- br=0;
- return;
-end
-imx=0*im;
-if (size(im,3))>1
- idx=sub2ind(size(im),cell.pts(:,2),cell.pts(:,1),cell.pts(:,3));
-else
- idx=sub2ind(size(im),cell.pts(:,2),cell.pts(:,1));
-end
-imx(idx)=im(idx);
-if (0==max(imx(:)))
- br=0;
- return
-end
-
-bwd=bwdist(~imx);
-imx=imx.*max(bwd(:))/max(imx(:));
-br=sum(bwd(:)-imx(:))/length(find(bwd));
-
-function ecc=getEcc(szImage,cell)
-
-if length(szImage)>2 && szImage(3)>1
- ecc=0;
- return;
-end
-imx=zeros(szImage);
-idx=sub2ind(szImage,cell.pts(:,2),cell.pts(:,1));
-imx(idx)=1;
-if (0==max(imx(:)))
- ecc=1;
- return
-end
-rp=regionprops(imx,'Eccentricity');
-ecc=rp.Eccentricity;
-
-function [d2TrackID,d2CellID,d2Centroid]=getDaughter2(conn,parentCandidate,time,d1)
+function d2 = getDaughter2(conn,parentCandidate,time,d1)
-d2TrackID=[];
-d2CellID=[];
-d2Centroid=[];
+d2 = [];
itid=parentCandidate(2); % trackID for parent/daughter 2
% try to use parent trackID in time t-1 to find daughter in time t
@@ -257,9 +185,7 @@ if size(q,1)>1
fprintf(2,'rut roh! duplicate track entries conn=%s time=%d\n',conn.DataSource,time);
end
if ~isempty(q)
- d2TrackID=itid;
- d2CellID=q{1};
- d2Centroid=jsondecode(q{1,2})';
+ d2 = Read.getCell(conn,q{1});
else
% parent did not track to a d2
% so, there first choice is still out there and is not d1 (since d1 is
@@ -272,26 +198,24 @@ else
% to find a daughter that the parent wanted, but later the parent may
% get the track they actually wanted. pfad.
% for now, no go
- return;
-
- cmd=['select * from tblDistCC where cellID_src=' num2str(parentCandidate(1)) ...
- ' and cellID_dst in (select cellID from (select cellID,trackID,min(time) ' ...
- ' as tStart from tblCells group by trackID)) and cellID_dst<>' num2str(d1.cellID)];
- q=fetch(conn,cmd);
- if ~isempty(q)
- % make sure d2 is not already in table
- cmd=['select * from tblFamilies where cellID_child1=' num2str(q.cellID_dst(1))];
- qfamily=fetch(conn,cmd);
- if isempty(qfamily)
- d2=Read.getCell(conn,q.cellID_dst(1));
- if d2.time~=d1.time
- return
- end
- d2TrackID=d2.trackID;
- d2CellID=d2.cellID;
- d2Centroid=d2.centroid;
+ cmd = ['select * from tblDistCC where cellID_src = ' num2str(parentCandidate(1)) ' order by cost asc'];
+ qp = fetch(conn,cmd);
+ cmd = ['select cellID,LoG from tblCells where cellID in ' Helpers.sqlEncodeVector(qp.cellID_dst)];
+ qd = fetch(conn,cmd);
+ qd(qd.LoG>-0.1,:) = [];
+ qd(qd.cellID == d1.cellID,:) = [];
+ i = 1;
+ while i <= length(qp.cellID_dst)
+ if isempty(intersect(qp.cellID_dst(i),qd.cellID))
+ qp(i,:) = [];
+ else
+ i = i+1;
end
end
+ if ~isempty(qp)
+ d2 = Read.getCell(conn,qp.cellID_dst(1));
+ end
+
end
diff --git a/matlab/+Smooth/+Classify/goClassifyMitosis.m b/matlab/+Smooth/+Classify/goClassifyMitosis.m
index b1dd86c29e34ff999064fa38a9d0c29304627025..b2542ead4a500033e82d7f29cd2991f149e144cb 100644
--- a/matlab/+Smooth/+Classify/goClassifyMitosis.m
+++ b/matlab/+Smooth/+Classify/goClassifyMitosis.m
@@ -13,43 +13,23 @@ end
if ~exist('nProcessors','var') || isempty(nProcessors)
nProcessors=ljsNProcs();
end
-p=ljsStartParallel(nProcessors);
+% p=ljsStartParallel(nProcessors);
mParams=Read.getMitosisParams(conn);
+segParams = Read.getSegmentationParams(conn);
targetTracks=Smooth.getTargetTracks(conn,5);
-strDB=conn.DataSource;
-mnode=Smooth.Classify.newMitosisNode(-1);
-cxComp=Composite();
-spmd
- cxComp=openDB(strDB);
-end
-mnode=[];
-for i=1:ceil(size(targetTracks,1)/p.NumWorkers)
- mx=[];
- spmd
- idx = ((i - 1) * numlabs) + labindex;
- if idx<=size(targetTracks,1)
- if targetTracks.t0(idx)==1
- mx=Smooth.Classify.newMitosisNode(targetTracks.trackID(idx));
- else
- mx=Smooth.Classify.getMitosisFeatures(cxComp,CONSTANTS,mParams,targetTracks.trackID(idx));
- end
- end
- end
- mres=[mx{:}]';
- mnode=[mnode;mres];
-end
-spmd
- close(cxComp);
-end
+mnode = [];
+
+for i = 1:length(targetTracks.trackID)
+ mn = Smooth.Classify.getMitosisFeatures(conn,CONSTANTS,mParams,targetTracks.trackID(i)) ;
-for i=1:length(mnode)
- if Smooth.Classify.isValidMitosis(mnode(i),mParams)
- c1=Read.getCell(conn,mnode(i).d1CellID);
- c2=Read.getCell(conn,mnode(i).siblingCellID);
- p=Read.getCell(conn,mnode(i).parentCellID);
- ljsLog('resegMitosis: adding new mitosis at child = %d\n',mnode(i).d1CellID);
- Mitosis.addMitosis(conn,p,c1,c2);
+ if Smooth.Classify.isValidMitosis(mn,mParams)
+ c1=Read.getCell(conn,mn.d1CellID);
+ c2=Read.getCell(conn,mn.siblingCellID);
+ p=Read.getCell(conn,mn.parentCellID);
+% drawMitosis(conn.DataSource,p,c1,c2,segParams,mn);
+ ljsLog('resegMitosis: adding new mitosis at child = %d\n',mn.d1CellID);
+ Mitosis.addMitosis(conn,p,c1,c2);
end
end
\ No newline at end of file
diff --git a/matlab/+Smooth/+Classify/isValidMitosis.m b/matlab/+Smooth/+Classify/isValidMitosis.m
index 154d6d3b13ab94d8a7fbe3c12077310e11b74470..f2eb47765e065a8865d969c1263e9832354a48c9 100644
--- a/matlab/+Smooth/+Classify/isValidMitosis.m
+++ b/matlab/+Smooth/+Classify/isValidMitosis.m
@@ -3,19 +3,27 @@ bValid=false;
if mnode.parentCellID<0
return;
end
-if any(isinf(mnode.brightRatio))
+threshLoG = [-0.05,-0.1,-0.35];
+if any(mnode.pd1d2LoG > threshLoG(1))
return;
end
-if ~isinf(mParams.brightThreshold)
- if any(mnode.brightRatio<mParams.brightThreshold)
- return;
- end
+if any(mnode.pd1d2LoG < threshLoG(3))
+ return;
end
-if ~isinf(mParams.eccentricityThreshold)
- if mnode.eccParent>mParams.eccentricityThreshold
- return;
+if ~any(mnode.pd1d2LoG < threshLoG(2))
+ return
+end
+if any(mnode.pd1d2overlap>0.25)
+ if ~all(mnode.pd1d2LoG<threshLoG(2))
+ return
end
end
+
+daughterLoG = abs(mnode.pd1d2LoG(2:3));
+dRatio = min(daughterLoG)/max(daughterLoG);
+if dRatio < 0.5
+ return
+end
if ~isinf(mParams.parentDaughterAreaRatio)
if mnode.areaRatio<mParams.parentDaughterAreaRatio
return;
diff --git a/matlab/+Smooth/+Classify/newMitosisNode.m b/matlab/+Smooth/+Classify/newMitosisNode.m
index 599f7716a7fdeecf93f26e268363d45682122f7e..7ee0e1dc4030806221d5d86245ac6781cfd5e702 100644
--- a/matlab/+Smooth/+Classify/newMitosisNode.m
+++ b/matlab/+Smooth/+Classify/newMitosisNode.m
@@ -6,7 +6,8 @@ mitosisNode.parentCellID=-1;
mitosisNode.siblingCellID=-1;
mitosisNode.parentDaughterTID=[-1,d1CellID];
mitosisNode.areaRatio=0;
-mitosisNode.brightRatio=[-Inf,-Inf,-Inf];
+mitosisNode.pd1d2LoG=[-Inf,-Inf,-Inf];
mitosisNode.sibAreaRatio=0;
-mitosisNode.eccParent=2;
+mitosisNode.pd1d2Ecc=[-Inf,-Inf,-Inf];
mitosisNode.d1CellID=d1CellID;
+mitosisNode.pd1d2overlap = [-Inf,-Inf];
diff --git a/matlab/+Smooth/+Merge/goMerge.m b/matlab/+Smooth/+Merge/goMerge.m
index 173baa8e000ab2ca8d8d6dba1874b9cdf050b7c1..98e2482c60da6d9931a74054119ceed8c0bcbd74 100644
--- a/matlab/+Smooth/+Merge/goMerge.m
+++ b/matlab/+Smooth/+Merge/goMerge.m
@@ -1,6 +1,7 @@
function nMerged = goMerge(conn,CONSTANTS,segParams,nProcessors)
nMerged=0;
+
r=Ensemble.getEnsembleRadius(segParams.minimumRadius_um);
if 1==length(r)
% ensemble merge uses ensemble results. if no ensemble, no results.
@@ -20,7 +21,7 @@ fragmentTracks = Smooth.Merge.getTargetFragments(conn,10);
tx={};
strDB=conn.DataSource;
p=ljsStartParallel(nProcessors);
-parfor i=1:length(fragmentTracks.trackID)
+for i=1:length(fragmentTracks.trackID)
cx=openDB(strDB);
mergeTarget = Smooth.Merge.getMergeTarget(cx,fragmentTracks.trackID(i),CONSTANTS);
@@ -57,7 +58,7 @@ srcCellIDs=vertcat(targets.srcCellID{:});
% find the unique destCellIDs in the targets table
targetCIDs=unique(destCellIDs);
mergeQ=table();
-parfor i=1:length(targetCIDs)
+for i=1:length(targetCIDs)
idx=find(destCellIDs==targetCIDs(i));
mergeList=[targetCIDs(i);srcCellIDs(idx)];
cx=openDB(strDB);
diff --git a/matlab/+Smooth/+Merge/goMerge2.m b/matlab/+Smooth/+Merge/goMerge2.m
new file mode 100644
index 0000000000000000000000000000000000000000..b9c1569f132202a5cd3151e9858b926b7dd4733e
--- /dev/null
+++ b/matlab/+Smooth/+Merge/goMerge2.m
@@ -0,0 +1,91 @@
+
+% strDB = '/g/leverjs/ctc2022/2d_Fluo-N2DL-HeLa_training_02.LEVER';
+% [conn,CONSTANTS,segParams]=openDB(strDB);
+
+function nMerge = goMerge2(conn,CONSTANTS, segParams)
+
+nMerge = 0;
+if 1 == CONSTANTS.imageData.NumberOfFrames
+ return
+end
+
+warning('off','images:bwfilt:tie');
+q = fetch(conn,'select trackID,count(trackID) as lifespan from tblCells group by trackID');
+
+MIN_LIFESPAN = 5;
+imSize = [CONSTANTS.imageData.Dimensions(2),CONSTANTS.imageData.Dimensions(1),CONSTANTS.imageData.Dimensions(3)];
+for t=1:CONSTANTS.imageData.NumberOfFrames
+
+ cellList = Read.getCellsTime(conn,t,segParams.channels,CONSTANTS);
+ if isempty(cellList)
+ continue
+ end
+ [tTracks,idxtTracks] = intersect(q.trackID,[cellList.trackID],'stable');
+ qt = q(idxtTracks,:);
+
+ labelIm = zeros(imSize);
+ qtFragments = table();
+ for i=1:height(qt)
+ if qt.lifespan(i)<MIN_LIFESPAN
+ qtFragments = [qtFragments;qt(i,:)];
+ else
+ cx = cellList(find([cellList.trackID] == qt.trackID(i)));
+ labelIm(horzcat(cx.idxPts)) = cx.trackID;
+ end
+ end
+ % go through each merge-able track iteratively. every time one gets
+ % absorbed, we need to check all again
+ bMergedIteration = true;
+ while bMergedIteration
+ bMergedIteration = false;
+ [d,idxd] = bwdist(labelIm);
+ for i=1:height(qtFragments)
+ if qtFragments.lifespan(i)>=MIN_LIFESPAN
+ continue
+
+ end
+ cx = cellList(find([cellList.trackID] == qtFragments.trackID(i)));
+ if isempty(cx)
+ continue
+ end
+ dx = [d(cx.idxPts),labelIm(idxd(cx.idxPts))];
+ dx(dx(:,1)>2,:) = [];
+ if isempty(dx)
+ continue
+ end
+ % take smallest distance
+ dx(dx(:,1)>min(dx(:,1)),:)=[];
+ % merge cells
+ bMergedIteration = true;
+ qtFragments(i,:) = [];
+ mergeTarget = mode(dx(:,2));
+ cxTarget = cellList(find([cellList.trackID] == mergeTarget));
+ cxTarget.pts = [cxTarget.pts;cx.pts];
+ cxTarget.idxPts = [cxTarget.idxPts;cx.idxPts];
+ cxTarget.centroid = mean(cxTarget.pts);
+ if is3D(CONSTANTS)
+ newCell = Segment.frameSegment_create_3D(cxTarget.idxPts, imSize, segParams.channels(1), cxTarget.time);
+ cxTarget.edges = newCell.edges;
+ cxTarget.faces = newCell.faces;
+ cxTarget.verts = newCell.verts;
+ cxTarget.normals = newCell.normals;
+ else
+ bx = logical(0*labelIm);
+ bx(cxTarget.idxPts) = 1;
+ bx = bwareafilt(bx,1);
+ bounds = bwboundaries(bx);
+ cxTarget.surface = [bounds{1}(:,2),bounds{1}(:,1)];
+ cxTarget.centroid(3)=0;
+ end
+ % update cxTarget in cellList
+ cellList(find([cellList.trackID] == mergeTarget)) = cxTarget;
+ labelIm(cx.idxPts) = mergeTarget;
+ [d,idxd] = bwdist(labelIm);
+ Write.ReplaceCell(conn,cxTarget,cxTarget.cellID,cxTarget.trackID);
+ exec(conn,['delete from tblCells where cellID=',num2str(cx.cellID)]);
+ nMerge = nMerge + 1;
+ break; % start over, allowing cx+cxTarget to absorb other fragments
+ end
+ end
+end
+ljsLog(['goMerge2 :: nMerged = ', num2str(nMerge)],0);
diff --git a/matlab/+Smooth/getTargetTracks.m b/matlab/+Smooth/getTargetTracks.m
index de010390f3c6b8a40e1f160880e1af4167d26e5c..bbdf4640e4bd55b9017c81420f127b1910fea5e7 100644
--- a/matlab/+Smooth/getTargetTracks.m
+++ b/matlab/+Smooth/getTargetTracks.m
@@ -1,9 +1,16 @@
function targetTracks=getTargetTracks(conn,nFrames)
-cmd=['select * from (select trackID,min(time) as t0,max(time) as t1,count(time) as lifespan '...
- ' from tblCells group by trackID) where lifespan>' num2str(nFrames)];
-targetTracks=fetch(conn,cmd);
+% cmd=['select * from (select trackID,min(time) as t0,max(time) as t1,count(time) as lifespan '...
+% ' from tblCells group by trackID) where lifespan>' num2str(nFrames)];
+% targetTracks=fetch(conn,cmd);
+cmd = ['select tblCells.trackID,tblCells.time,tblCells.LoG from tblCells '...
+ ' inner join (select trackID,count(time) as nt '...
+ ' from tblCells group by trackID) as qx on tblCells.trackID = qx.trackID '...
+ ' where nt>5 and tblCells.cellID=tblCells.trackID and tblCells.time>1 and '...
+ ' tblCells.LoG<-0.05 order by tblCells.LoG asc'];
+
+targetTracks = fetch(conn,cmd);
diff --git a/matlab/+UI/channelExtFamily.m b/matlab/+UI/channelExtFamily.m
index 316061a28ee2fbfcbe6f13ac46547da50eabcae9..913e724de955985089a08f094a01b46bd398abfb 100644
--- a/matlab/+UI/channelExtFamily.m
+++ b/matlab/+UI/channelExtFamily.m
@@ -16,7 +16,9 @@ for ff=1:length(flist)
bw=imbinarize(im);
cellList = Read.getCellsTime(conn,1,channelSeg,CONSTANTS);
-
+ if isempty(cellList)
+ continue
+ end
exec(conn,'delete from uiExtFamilies');
extFamily=[];
for i=1:length(cellList)
diff --git a/matlab/+UI/lifsepanExtFamily.m b/matlab/+UI/lifsepanExtFamily.m
index b7eaa120c44f0ff152cfd9ee54dec91c8f6ac74d..6f0b2e5a714ce43d2383fe5bdd4f66a249d8eb71 100644
--- a/matlab/+UI/lifsepanExtFamily.m
+++ b/matlab/+UI/lifsepanExtFamily.m
@@ -7,6 +7,7 @@ cmd=['select trackID,min(time) as t0,max(time) as t1 from tblCells group by trac
q=fetch(conn,cmd);
q.ls=q.t1-q.t0+1;
q=sortrows(q,'ls','descend');
-
+idx=find(q.ls<tmin);
+q(idx,:)=[];
exec(conn,'delete from uiExtFamilies');
-insert(conn,'uiExtFamilies','trackID',q.trackID(1:tmin));
\ No newline at end of file
+insert(conn,'uiExtFamilies','trackID',q.trackID);
\ No newline at end of file
diff --git a/matlab/+Write/CreateCells.m b/matlab/+Write/CreateCells.m
index 94eb5644662538dbb3ae71a2599b22514b4b37c0..221f409341693f376d3d21df6a5baba3d2049a5a 100644
--- a/matlab/+Write/CreateCells.m
+++ b/matlab/+Write/CreateCells.m
@@ -9,16 +9,27 @@ if isempty(Cells)
end
[~,tblFields]=Write.prepareCell([],Cells(1));
+qTable=fetch(conn,'pragma table_info(tblCells)');
if isfield(Cells,'nest')
- tblFields.iNest=max(tblFields{1,:})+1;
- q=fetch(conn,'pragma table_info(tblCells)');
- if ~any(cellfun(@length,(strfind(q.name,'iNest'))))
+ tblFields.iNest=max(tblFields{1,:})+1;
+ if ~any(cellfun(@length,(strfind(qTable.name,'iNest'))))
cmd = ['ALTER TABLE tblCells ADD COLUMN iNest INTEGER default -1'];
exec(conn,cmd);
cmd = ['ALTER TABLE tblZombies ADD COLUMN iNest INTEGER'];
exec(conn,cmd);
end
end
+
+if isfield(Cells,'LoG')
+ tblFields.LoG=max(tblFields{1,:})+1;
+ if ~any(cellfun(@length,(strfind(qTable.name,'LoG'))))
+ cmd = ['ALTER TABLE tblCells ADD COLUMN LoG REAL'];
+ exec(conn,cmd);
+ cmd = ['ALTER TABLE tblZombies ADD COLUMN LoG REAL'];
+ exec(conn,cmd);
+ end
+end
+
cmd=Write.buildPreparedStatement(tblFields,'tblCells');
insertCells = conn.handle.prepareStatement(cmd);
@@ -33,6 +44,11 @@ for i=1:length(Cells)
insertCells.setInt(tblFields.iNest,-1);
end
end
+ if isfield(Cells,'LoG')
+ if ~isempty(Cells(i).nest)
+ insertCells.setDouble(tblFields.LoG,Cells(i).LoG);
+ end
+ end
Write.tryUpdateDB(insertCells);
end
diff --git a/matlab/+Write/setSegParamsFolder.m b/matlab/+Write/setSegParamsFolder.m
index 570c301e79f3d6c3aa50d74820b4b322ca446e5f..c8ace14465d3f66d3e9b3b5a2e4dc89133a74554 100644
--- a/matlab/+Write/setSegParamsFolder.m
+++ b/matlab/+Write/setSegParamsFolder.m
@@ -4,7 +4,7 @@ flist=dir(fullfile(folder,'*.LEVER'));
for ff=1:length(flist)
strDB=fullfile(flist(ff).folder,flist(ff).name);
conn = database(strDB, '','', 'org.sqlite.JDBC', 'jdbc:sqlite:');
- setSegParams(conn,segParams);
+ Write.setSegParams(conn,segParams);
close(conn);
end
diff --git a/matlab/+im2lever/im2lever.m b/matlab/+im2lever/im2lever.m
new file mode 100644
index 0000000000000000000000000000000000000000..a548c92355ced9338f4d5e60cf3038eef6a99dd9
--- /dev/null
+++ b/matlab/+im2lever/im2lever.m
@@ -0,0 +1,4 @@
+function im2lever(im,CONSTANTS,outdir)
+
+imageData = MicroscopeData.MakeMetadataFromImage(im);
+MicroscopeData.WriterH5(im,CONSTANTS.imageData);
\ No newline at end of file
diff --git a/matlab/.gitattributes b/matlab/.gitattributes
new file mode 100644
index 0000000000000000000000000000000000000000..f0ff11a66ed781b66edf41fa3b97a142bdada0e0
--- /dev/null
+++ b/matlab/.gitattributes
@@ -0,0 +1 @@
+cacheReferenceLoG.mat filter=lfs diff=lfs merge=lfs -text
diff --git a/matlab/batchMitosis.m b/matlab/batchMitosis.m
new file mode 100644
index 0000000000000000000000000000000000000000..227c4b05daf0db332e4dea3b2a6ab22d40bf8f96
--- /dev/null
+++ b/matlab/batchMitosis.m
@@ -0,0 +1,13 @@
+ROOT = '/g/leverjs/Olivier/Agne/2022-02-19_1h_starved_steady_state_exp1/';
+
+flist = dir(fullfile(ROOT,'*.LEVER'));
+nProcessors = 128;
+
+for ff=1:length(flist)
+ strDB = fullfile(flist(ff).folder,flist(ff).name);
+ [conn,CONSTANTS,segParams]=openDB(strDB);
+
+ Smooth.Classify.goClassifyMitosis(conn,CONSTANTS,nProcessors);
+
+ close(conn);
+end
diff --git a/matlab/cacheReferenceLoG.mat b/matlab/cacheReferenceLoG.mat
new file mode 100644
index 0000000000000000000000000000000000000000..552dab96604fc508ade65f3057d47505916548e4
--- /dev/null
+++ b/matlab/cacheReferenceLoG.mat
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a5ed0553e0c15ea60c2f5f909ee0445086c4c4f45fe6ee9add6bb46787aee704
+size 20274469
diff --git a/matlab/getCudaTarget.m b/matlab/getCudaTarget.m
new file mode 100644
index 0000000000000000000000000000000000000000..db83991b8c4337ecfcdf7086579982a79f1d6361
--- /dev/null
+++ b/matlab/getCudaTarget.m
@@ -0,0 +1,26 @@
+function targetGPU = getCudaTarget()
+persistent nGPU
+targetGPU = [];
+if ~isempty(nGPU)
+ if nGPU > 1
+ targetGPU = randi(nGPU)-1;
+ end
+ return
+end
+
+nGPU = length(HIP.Cuda.DeviceStats);
+if nGPU<=1
+ return
+end
+% if more than 1 GPU, enable multiGPU use via environment variable
+% NOTE - tested only on Ubuntu 20.04, not windows yet! AC Jan 10 2023.
+
+gpuStr = '';
+for i=0:nGPU-1
+ gpuStr = [gpuStr num2str(i) ','];
+end
+gpuStr(end) = [];
+
+setenv('CUDA_VISIBLE_DEVICE',gpuStr);
+
+targetGPU = randi(nGPU)-1;
\ No newline at end of file
diff --git a/matlab/logStudy2.m b/matlab/logStudy2.m
new file mode 100644
index 0000000000000000000000000000000000000000..ec6b9c6bb001cdd866bcf4d3818a2f56f0191787
--- /dev/null
+++ b/matlab/logStudy2.m
@@ -0,0 +1,46 @@
+% strDB ='/f/leverjs/Olivier/wrangle/20210924_pos3.LEVER'
+% [conn,CONSTANTS,segParams]=openDB(strDB);
+[~,dsName,~] = fileparts(strDB);
+outfolder = ['./tiffs_' dsName];
+prefix = '';
+if ~exist(outfolder,'dir')
+ mkdir(outfolder)
+end
+
+H2B = 1;
+ERK = 2;
+Oracle = 3;
+for t=1:CONSTANTS.imageData.NumberOfFrames
+
+ cellList = Read.getCellsTime(conn,t,H2B,CONSTANTS);
+
+ rCell = cellfun(@(x) std(double(x)),{cellList.pts},'UniformOutput',false);
+ rCell = median(vertcat(rCell{:}));
+ rCell = mean(rCell);
+ rCell_um = rCell .* CONSTANTS.imageData.PixelPhysicalSize(1);
+
+ im = MicroscopeData.Reader('imageData',CONSTANTS.imageData, 'chanList',...
+ ERK,'timeRange',[t t], 'outType','single','prompt',false);
+ if all(isnan(im(:)))
+ return;
+ end
+
+ sp = segParams;
+ sp.minimumRadius_um = rCell_um;
+ imLoG = Segment.getLoG(im,CONSTANTS,sp);
+
+ imp = imLoG;
+ imp(imp<0)=0;
+ imp = mat2gray(imp);
+ imSegment = 0*im;
+ imSegment(vertcat(cellList.idxPts)) = 1;
+ im_erkLoG = imSegment .* imp;
+ vbar = 0.33 * ones(size(im,1),5);
+ imOut = mat2gray([im,vbar,im_erkLoG]);
+
+ figure(1);imagesc(imOut);axis image
+ title(num2str(t))
+ drawnow
+ fname = fullfile(outfolder,[prefix num2str(t) '.tif']);
+ imwrite(imOut,fname);
+end
diff --git a/package-lock.json b/package-lock.json
index cd633b34241451f2a2217d009e66774391285c95..37d82ac109c3a80e999b30b9dfa7eb3ac1d4ca33 100644
--- a/package-lock.json
+++ b/package-lock.json
@@ -10,23 +10,23 @@
"hasInstallScript": true,
"license": "UNLICENSED",
"dependencies": {
- "auth0-lock": "^11.30.0",
+ "auth0-lock": "^11.31.0",
"electron-log": "^3.0.8",
"electron-updater": "^4.3.9",
"express-jwt": "^5.3.3",
"express.js": "^1.0.0",
"http-parser": "^1.0.3",
"jwks-rsa": "^1.12.3",
- "keypair": "^1.0.3",
+ "keypair": "^1.0.4",
"minimist": "^1.2.5",
- "multer": "^1.4.2",
+ "multer": "^1.4.3",
"semver": "^6.3.0",
- "sqlite3": "^4.1.1",
+ "sqlite3": "^5.1.6",
"xlsx": "^0.15.6"
},
"devDependencies": {
"electron": "^6.1.12",
- "electron-builder": "^22.11.3",
+ "electron-builder": "^22.13.1",
"sync-package-pom": "^1.0.1"
}
},
@@ -72,9 +72,9 @@
}
},
"node_modules/@electron/universal/node_modules/debug": {
- "version": "4.3.1",
- "resolved": "https://registry.npmjs.org/debug/-/debug-4.3.1.tgz",
- "integrity": "sha512-doEwdvm4PCeK4K3RQN2ZC2BYUBaxwLARCqZmMjtF8a51J2Rb0xpVloFRnCODwqjpwnAoao4pelN8l3RJdv3gRQ==",
+ "version": "4.3.4",
+ "resolved": "https://registry.npmjs.org/debug/-/debug-4.3.4.tgz",
+ "integrity": "sha512-PRWFHuSU3eDtQJPvnNY7Jcket1j0t5OuOsFzPPzsekD52Zl8qUfFIPEiswXqIvHWGVHOgX+7G/vCNNhehwxfkQ==",
"dev": true,
"dependencies": {
"ms": "2.1.2"
@@ -130,6 +130,12 @@
"node": ">= 10.0.0"
}
},
+ "node_modules/@gar/promisify": {
+ "version": "1.1.3",
+ "resolved": "https://registry.npmjs.org/@gar/promisify/-/promisify-1.1.3.tgz",
+ "integrity": "sha512-k2Ty1JcVojjJFwrg/ThKi2ujJ7XNLYaFGNB/bWT9wGR+oSMJHMa5w+CUq6p/pVrKeNNgA7pCqEcjSnHVoqJQFw==",
+ "optional": true
+ },
"node_modules/@malept/cross-spawn-promise": {
"version": "1.1.1",
"resolved": "https://registry.npmjs.org/@malept/cross-spawn-promise/-/cross-spawn-promise-1.1.1.tgz",
@@ -168,9 +174,9 @@
}
},
"node_modules/@malept/flatpak-bundler/node_modules/debug": {
- "version": "4.3.1",
- "resolved": "https://registry.npmjs.org/debug/-/debug-4.3.1.tgz",
- "integrity": "sha512-doEwdvm4PCeK4K3RQN2ZC2BYUBaxwLARCqZmMjtF8a51J2Rb0xpVloFRnCODwqjpwnAoao4pelN8l3RJdv3gRQ==",
+ "version": "4.3.4",
+ "resolved": "https://registry.npmjs.org/debug/-/debug-4.3.4.tgz",
+ "integrity": "sha512-PRWFHuSU3eDtQJPvnNY7Jcket1j0t5OuOsFzPPzsekD52Zl8qUfFIPEiswXqIvHWGVHOgX+7G/vCNNhehwxfkQ==",
"dev": true,
"dependencies": {
"ms": "2.1.2"
@@ -226,6 +232,109 @@
"node": ">= 10.0.0"
}
},
+ "node_modules/@mapbox/node-pre-gyp": {
+ "version": "1.0.10",
+ "resolved": "https://registry.npmjs.org/@mapbox/node-pre-gyp/-/node-pre-gyp-1.0.10.tgz",
+ "integrity": "sha512-4ySo4CjzStuprMwk35H5pPbkymjv1SF3jGLj6rAHp/xT/RF7TL7bd9CTm1xDY49K2qF7jmR/g7k+SkLETP6opA==",
+ "dependencies": {
+ "detect-libc": "^2.0.0",
+ "https-proxy-agent": "^5.0.0",
+ "make-dir": "^3.1.0",
+ "node-fetch": "^2.6.7",
+ "nopt": "^5.0.0",
+ "npmlog": "^5.0.1",
+ "rimraf": "^3.0.2",
+ "semver": "^7.3.5",
+ "tar": "^6.1.11"
+ },
+ "bin": {
+ "node-pre-gyp": "bin/node-pre-gyp"
+ }
+ },
+ "node_modules/@mapbox/node-pre-gyp/node_modules/node-fetch": {
+ "version": "2.6.11",
+ "resolved": "https://registry.npmjs.org/node-fetch/-/node-fetch-2.6.11.tgz",
+ "integrity": "sha512-4I6pdBY1EthSqDmJkiNk3JIT8cswwR9nfeW/cPdUagJYEQG7R95WRH74wpz7ma8Gh/9dI9FP+OU+0E4FvtA55w==",
+ "dependencies": {
+ "whatwg-url": "^5.0.0"
+ },
+ "engines": {
+ "node": "4.x || >=6.0.0"
+ },
+ "peerDependencies": {
+ "encoding": "^0.1.0"
+ },
+ "peerDependenciesMeta": {
+ "encoding": {
+ "optional": true
+ }
+ }
+ },
+ "node_modules/@mapbox/node-pre-gyp/node_modules/semver": {
+ "version": "7.5.1",
+ "resolved": "https://registry.npmjs.org/semver/-/semver-7.5.1.tgz",
+ "integrity": "sha512-Wvss5ivl8TMRZXXESstBA4uR5iXgEN/VC5/sOcuXdVLzcdkz4HWetIoRfG5gb5X+ij/G9rw9YoGn3QoQ8OCSpw==",
+ "dependencies": {
+ "lru-cache": "^6.0.0"
+ },
+ "bin": {
+ "semver": "bin/semver.js"
+ },
+ "engines": {
+ "node": ">=10"
+ }
+ },
+ "node_modules/@npmcli/fs": {
+ "version": "1.1.1",
+ "resolved": "https://registry.npmjs.org/@npmcli/fs/-/fs-1.1.1.tgz",
+ "integrity": "sha512-8KG5RD0GVP4ydEzRn/I4BNDuxDtqVbOdm8675T49OIG/NGhaK0pjPX7ZcDlvKYbA+ulvVK3ztfcF4uBdOxuJbQ==",
+ "optional": true,
+ "dependencies": {
+ "@gar/promisify": "^1.0.1",
+ "semver": "^7.3.5"
+ }
+ },
+ "node_modules/@npmcli/fs/node_modules/semver": {
+ "version": "7.5.1",
+ "resolved": "https://registry.npmjs.org/semver/-/semver-7.5.1.tgz",
+ "integrity": "sha512-Wvss5ivl8TMRZXXESstBA4uR5iXgEN/VC5/sOcuXdVLzcdkz4HWetIoRfG5gb5X+ij/G9rw9YoGn3QoQ8OCSpw==",
+ "optional": true,
+ "dependencies": {
+ "lru-cache": "^6.0.0"
+ },
+ "bin": {
+ "semver": "bin/semver.js"
+ },
+ "engines": {
+ "node": ">=10"
+ }
+ },
+ "node_modules/@npmcli/move-file": {
+ "version": "1.1.2",
+ "resolved": "https://registry.npmjs.org/@npmcli/move-file/-/move-file-1.1.2.tgz",
+ "integrity": "sha512-1SUf/Cg2GzGDyaf15aR9St9TWlb+XvbZXWpDx8YKs7MLzMH/BCeopv+y9vzrzgkfykCGuWOlSu3mZhj2+FQcrg==",
+ "deprecated": "This functionality has been moved to @npmcli/fs",
+ "optional": true,
+ "dependencies": {
+ "mkdirp": "^1.0.4",
+ "rimraf": "^3.0.2"
+ },
+ "engines": {
+ "node": ">=10"
+ }
+ },
+ "node_modules/@npmcli/move-file/node_modules/mkdirp": {
+ "version": "1.0.4",
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@@ -797,6 +1014,16 @@
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@@ -826,14 +1053,14 @@
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@@ -1222,6 +1518,20 @@
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- "integrity": "sha1-+hN8S9aY7fVc1c0CrFWfkaTEups=",
- "bin": {
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@@ -2018,6 +2444,12 @@
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+ "deprecated": "Disk image license agreements are deprecated by Apple and will probably be removed in a future macOS release. Discussion at: https://github.com/argv-minus-one/dmg-license/issues/11",
"dev": true,
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@@ -2062,6 +2494,11 @@
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@@ -2180,10 +2617,40 @@
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},
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@@ -2210,6 +2677,12 @@
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@@ -3355,6 +3885,12 @@
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@@ -3443,6 +3986,12 @@
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@@ -4019,6 +4502,33 @@
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- "deprecated": "Please upgrade to @mapbox/node-pre-gyp: the non-scoped node-pre-gyp package is deprecated and only the @mapbox scoped package will recieve updates in the future",
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+ "integrity": "sha1-Ca5p+9YJnfuGAoHaZv8nkPoAmVQ=",
+ "dev": true,
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"dependencies": {
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+ "abbrev": "1"
},
"bin": {
"nopt": "bin/nopt.js"
+ },
+ "engines": {
+ "node": ">=6"
}
},
"node_modules/normalize-package-data": {
@@ -4339,38 +5002,15 @@
"node": ">=8"
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- "console-control-strings": "~1.1.0",
- "gauge": "~2.7.3",
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+ "are-we-there-yet": "^2.0.0",
+ "console-control-strings": "^1.1.0",
+ "gauge": "^3.0.0",
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}
},
"node_modules/nugget": {
@@ -4426,9 +5066,9 @@
}
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@@ -4709,14 +5336,33 @@
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@@ -5095,15 +5742,27 @@
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@@ -5414,6 +6142,18 @@
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+ "dev": true,
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@@ -5564,10 +6306,23 @@
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@@ -7473,6 +8394,17 @@
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- "integrity": "sha1-BKEGZywYsIWrd02YPfo+oTjyIgU=",
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- "resolved": "https://registry.npmjs.org/wide-align/-/wide-align-1.1.3.tgz",
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+ "resolved": "https://registry.npmjs.org/wide-align/-/wide-align-1.1.5.tgz",
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"requires": {
- "string-width": "^1.0.2 || 2"
+ "string-width": "^1.0.2 || 2 || 3 || 4"
}
},
"widest-line": {
@@ -11591,9 +12750,15 @@
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- "resolved": "https://registry.npmjs.org/ansi-regex/-/ansi-regex-5.0.1.tgz",
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+ "version": "5.0.0",
+ "resolved": "https://registry.npmjs.org/ansi-regex/-/ansi-regex-5.0.0.tgz",
+ "integrity": "sha512-bY6fj56OUQ0hU1KjFNDQuJFezqKdrAyFdIevADiqrWHwSlbmBNMHp5ak2f40Pm8JTFyM2mqxkG6ngkHO11f/lg==",
+ "dev": true
+ },
+ "emoji-regex": {
+ "version": "8.0.0",
+ "resolved": "https://registry.npmjs.org/emoji-regex/-/emoji-regex-8.0.0.tgz",
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"dev": true
},
"is-fullwidth-code-point": {
@@ -11603,23 +12768,23 @@
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- "resolved": "https://registry.npmjs.org/string-width/-/string-width-4.2.3.tgz",
- "integrity": "sha512-wKyQRQpjJ0sIp62ErSZdGsjMJWsap5oRNihHhu6G7JVO/9jIB6UyevL+tXuOqrng8j/cxKTWyWUwvSTriiZz/g==",
+ "version": "4.2.2",
+ "resolved": "https://registry.npmjs.org/string-width/-/string-width-4.2.2.tgz",
+ "integrity": "sha512-XBJbT3N4JhVumXE0eoLU9DCjcaF92KLNqTmFCnG1pf8duUxFGwtP6AD6nkjw9a3IdiRtL3E2w3JDiE/xi3vOeA==",
"dev": true,
"requires": {
"emoji-regex": "^8.0.0",
"is-fullwidth-code-point": "^3.0.0",
- "strip-ansi": "^6.0.1"
+ "strip-ansi": "^6.0.0"
}
},
"strip-ansi": {
- "version": "6.0.1",
- "resolved": "https://registry.npmjs.org/strip-ansi/-/strip-ansi-6.0.1.tgz",
- "integrity": "sha512-Y38VPSHcqkFrCpFnQ9vuSXmquuv5oXOKpGeT6aGrr3o3Gc9AlVa6JBfUSOCnbxGGZF+/0ooI7KrPuUSztUdU5A==",
+ "version": "6.0.0",
+ "resolved": "https://registry.npmjs.org/strip-ansi/-/strip-ansi-6.0.0.tgz",
+ "integrity": "sha512-AuvKTrTfQNYNIctbR1K/YGTR1756GycPsg7b9bdV9Duqur4gv6aKqHXah67Z8ImS7WEz5QVcOtlfW2rZEugt6w==",
"dev": true,
"requires": {
- "ansi-regex": "^5.0.1"
+ "ansi-regex": "^5.0.0"
}
}
}
@@ -11646,9 +12811,15 @@
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- "resolved": "https://registry.npmjs.org/ansi-regex/-/ansi-regex-5.0.1.tgz",
- "integrity": "sha512-quJQXlTSUGL2LH9SUXo8VwsY4soanhgo6LNSm84E1LBcE8s3O0wpdiRzyR9z/ZZJMlMWv37qOOb9pdJlMUEKFQ==",
+ "version": "5.0.0",
+ "resolved": "https://registry.npmjs.org/ansi-regex/-/ansi-regex-5.0.0.tgz",
+ "integrity": "sha512-bY6fj56OUQ0hU1KjFNDQuJFezqKdrAyFdIevADiqrWHwSlbmBNMHp5ak2f40Pm8JTFyM2mqxkG6ngkHO11f/lg==",
+ "dev": true
+ },
+ "emoji-regex": {
+ "version": "8.0.0",
+ "resolved": "https://registry.npmjs.org/emoji-regex/-/emoji-regex-8.0.0.tgz",
+ "integrity": "sha512-MSjYzcWNOA0ewAHpz0MxpYFvwg6yjy1NG3xteoqz644VCo/RPgnr1/GGt+ic3iJTzQ8Eu3TdM14SawnVUmGE6A==",
"dev": true
},
"is-fullwidth-code-point": {
@@ -11658,23 +12829,23 @@
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},
"string-width": {
- "version": "4.2.3",
- "resolved": "https://registry.npmjs.org/string-width/-/string-width-4.2.3.tgz",
- "integrity": "sha512-wKyQRQpjJ0sIp62ErSZdGsjMJWsap5oRNihHhu6G7JVO/9jIB6UyevL+tXuOqrng8j/cxKTWyWUwvSTriiZz/g==",
+ "version": "4.2.2",
+ "resolved": "https://registry.npmjs.org/string-width/-/string-width-4.2.2.tgz",
+ "integrity": "sha512-XBJbT3N4JhVumXE0eoLU9DCjcaF92KLNqTmFCnG1pf8duUxFGwtP6AD6nkjw9a3IdiRtL3E2w3JDiE/xi3vOeA==",
"dev": true,
"requires": {
"emoji-regex": "^8.0.0",
"is-fullwidth-code-point": "^3.0.0",
- "strip-ansi": "^6.0.1"
+ "strip-ansi": "^6.0.0"
}
},
"strip-ansi": {
- "version": "6.0.1",
- "resolved": "https://registry.npmjs.org/strip-ansi/-/strip-ansi-6.0.1.tgz",
- "integrity": "sha512-Y38VPSHcqkFrCpFnQ9vuSXmquuv5oXOKpGeT6aGrr3o3Gc9AlVa6JBfUSOCnbxGGZF+/0ooI7KrPuUSztUdU5A==",
+ "version": "6.0.0",
+ "resolved": "https://registry.npmjs.org/strip-ansi/-/strip-ansi-6.0.0.tgz",
+ "integrity": "sha512-AuvKTrTfQNYNIctbR1K/YGTR1756GycPsg7b9bdV9Duqur4gv6aKqHXah67Z8ImS7WEz5QVcOtlfW2rZEugt6w==",
"dev": true,
"requires": {
- "ansi-regex": "^5.0.1"
+ "ansi-regex": "^5.0.0"
}
}
}
@@ -11718,10 +12889,11 @@
}
},
"xmlbuilder": {
- "version": "9.0.7",
- "resolved": "https://registry.npmjs.org/xmlbuilder/-/xmlbuilder-9.0.7.tgz",
- "integrity": "sha1-Ey7mPS7FVlxVfiD0wi35rKaGsQ0=",
- "dev": true
+ "version": "15.1.1",
+ "resolved": "https://registry.npmjs.org/xmlbuilder/-/xmlbuilder-15.1.1.tgz",
+ "integrity": "sha512-yMqGBqtXyeN1e3TGYvgNgDVZ3j84W4cwkOXQswghol6APgZWaff9lnbvN7MHYJOiXsvGPXtjTYJEiC9J2wv9Eg==",
+ "dev": true,
+ "optional": true
},
"xtend": {
"version": "2.1.2",
@@ -11744,9 +12916,9 @@
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},
"yargs": {
- "version": "17.2.1",
- "resolved": "https://registry.npmjs.org/yargs/-/yargs-17.2.1.tgz",
- "integrity": "sha512-XfR8du6ua4K6uLGm5S6fA+FIJom/MdJcFNVY8geLlp2v8GYbOXD4EB1tPNZsRn4vBzKGMgb5DRZMeWuFc2GO8Q==",
+ "version": "17.0.1",
+ "resolved": "https://registry.npmjs.org/yargs/-/yargs-17.0.1.tgz",
+ "integrity": "sha512-xBBulfCc8Y6gLFcrPvtqKz9hz8SO0l1Ni8GgDekvBX2ro0HRQImDGnikfc33cgzcYUSncapnNcZDjVFIH3f6KQ==",
"dev": true,
"requires": {
"cliui": "^7.0.2",
@@ -11759,9 +12931,15 @@
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"dependencies": {
"ansi-regex": {
- "version": "5.0.1",
- "resolved": "https://registry.npmjs.org/ansi-regex/-/ansi-regex-5.0.1.tgz",
- "integrity": "sha512-quJQXlTSUGL2LH9SUXo8VwsY4soanhgo6LNSm84E1LBcE8s3O0wpdiRzyR9z/ZZJMlMWv37qOOb9pdJlMUEKFQ==",
+ "version": "5.0.0",
+ "resolved": "https://registry.npmjs.org/ansi-regex/-/ansi-regex-5.0.0.tgz",
+ "integrity": "sha512-bY6fj56OUQ0hU1KjFNDQuJFezqKdrAyFdIevADiqrWHwSlbmBNMHp5ak2f40Pm8JTFyM2mqxkG6ngkHO11f/lg==",
+ "dev": true
+ },
+ "emoji-regex": {
+ "version": "8.0.0",
+ "resolved": "https://registry.npmjs.org/emoji-regex/-/emoji-regex-8.0.0.tgz",
+ "integrity": "sha512-MSjYzcWNOA0ewAHpz0MxpYFvwg6yjy1NG3xteoqz644VCo/RPgnr1/GGt+ic3iJTzQ8Eu3TdM14SawnVUmGE6A==",
"dev": true
},
"is-fullwidth-code-point": {
@@ -11771,31 +12949,31 @@
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},
"string-width": {
- "version": "4.2.3",
- "resolved": "https://registry.npmjs.org/string-width/-/string-width-4.2.3.tgz",
- "integrity": "sha512-wKyQRQpjJ0sIp62ErSZdGsjMJWsap5oRNihHhu6G7JVO/9jIB6UyevL+tXuOqrng8j/cxKTWyWUwvSTriiZz/g==",
+ "version": "4.2.2",
+ "resolved": "https://registry.npmjs.org/string-width/-/string-width-4.2.2.tgz",
+ "integrity": "sha512-XBJbT3N4JhVumXE0eoLU9DCjcaF92KLNqTmFCnG1pf8duUxFGwtP6AD6nkjw9a3IdiRtL3E2w3JDiE/xi3vOeA==",
"dev": true,
"requires": {
"emoji-regex": "^8.0.0",
"is-fullwidth-code-point": "^3.0.0",
- "strip-ansi": "^6.0.1"
+ "strip-ansi": "^6.0.0"
}
},
"strip-ansi": {
- "version": "6.0.1",
- "resolved": "https://registry.npmjs.org/strip-ansi/-/strip-ansi-6.0.1.tgz",
- "integrity": "sha512-Y38VPSHcqkFrCpFnQ9vuSXmquuv5oXOKpGeT6aGrr3o3Gc9AlVa6JBfUSOCnbxGGZF+/0ooI7KrPuUSztUdU5A==",
+ "version": "6.0.0",
+ "resolved": "https://registry.npmjs.org/strip-ansi/-/strip-ansi-6.0.0.tgz",
+ "integrity": "sha512-AuvKTrTfQNYNIctbR1K/YGTR1756GycPsg7b9bdV9Duqur4gv6aKqHXah67Z8ImS7WEz5QVcOtlfW2rZEugt6w==",
"dev": true,
"requires": {
- "ansi-regex": "^5.0.1"
+ "ansi-regex": "^5.0.0"
}
}
}
},
"yargs-parser": {
- "version": "20.2.9",
- "resolved": "https://registry.npmjs.org/yargs-parser/-/yargs-parser-20.2.9.tgz",
- "integrity": "sha512-y11nGElTIV+CT3Zv9t7VKl+Q3hTQoT9a1Qzezhhl6Rp21gJ/IVTW7Z3y9EWXhuUBC2Shnf+DX0antecpAwSP8w==",
+ "version": "20.2.7",
+ "resolved": "https://registry.npmjs.org/yargs-parser/-/yargs-parser-20.2.7.tgz",
+ "integrity": "sha512-FiNkvbeHzB/syOjIUxFDCnhSfzAL8R5vs40MgLFBorXACCOAEaWu0gRZl14vG8MR9AOJIZbmkjhusqBYZ3HTHw==",
"dev": true
},
"yauzl": {
diff --git a/package.json b/package.json
index 59d64bdd0d9d59fec0eb08c05532f40c2fa587e2..f5e43ff94b0bda9740506e31e107f45816e47de0 100644
--- a/package.json
+++ b/package.json
@@ -29,7 +29,7 @@
"minimist": "^1.2.5",
"multer": "^1.4.3",
"semver": "^6.3.0",
- "sqlite3": "^4.1.1",
+ "sqlite3": "^5.1.6",
"xlsx": "^0.15.6"
},
"devDependencies": {