tinevez / msdanalyzer

A MATLAB class for Mean Square Displacement analysis.
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fitMeanMSD has NaN values? #6

Closed mr-september closed 2 years ago

mr-september commented 2 years ago

Hi, I have been trying to do MSD analysis, following parts of this manual and this tutorial. However, I am hitting a wall with NaN values:

Error using fit>iFit (line 232)
X, Y and WEIGHTS cannot have NaN values.

Error in fit (line 116)
[fitobj, goodness, output, convmsg] = iFit( xdatain, ydatain, fittypeobj, ...

Error in msdanalyzer/fitMeanMSD (line 44)
[fo, gof] = fit(t, y, ft, 'Weights', w);

Error in MSD_a (line 63)
[fo, gof] = ma.fitMeanMSD;

My whole Matlab script (the error comes from the very last section % calculate diffusion coefficiency):

% housekeeping
addpath('C:\Users\...\MSD-a\Fiji.app\scripts' )

% import track

file_path_tracks = 'PEI_chan00_Tracks.xml';
tracks = importTrackMateTracks(file_path_tracks);
n_tracks = numel( tracks );
fprintf('Found %d tracks in the file.\n', n_tracks)

% remove Z set time scale

clipZ = true; % Remove Z coordinates, if you know you can.
scaleT = true; % Use physical time for T.
tracks = importTrackMateTracks(file_path_tracks, clipZ, scaleT);
tracks{1}(5, :)

[ tracks, md ] = importTrackMateTracks(file_path_tracks, ...
clipZ, scaleT);
md

% plot figure

figure
hold on
c = jet(n_tracks);
for s = 1 : n_tracks
x = tracks{s}(:, 2);
y = tracks{s}(:, 3);
plot(x, y, '.-', 'Color', c(s, :))
end
axis equal
xlabel( [ 'X (' md.spaceUnits ')' ] )
ylabel( [ 'Y (' md.spaceUnits ')' ] )

% MSD calculation
SPACE_UNITS = 'µm';
TIME_UNITS = 's';
ma = msdanalyzer(2, SPACE_UNITS, TIME_UNITS);
ma = ma.addAll(tracks);

disp(ma)
ma = ma.computeMSD;
ma.msd

% Plot MSD
figure
ma.plotMSD;

% weighted average

cla
ma.plotMeanMSD(gca, true)
mmsd = ma.getMeanMSD;
t = mmsd(:,1);
x = mmsd(:,2);
dx = mmsd(:,3) ./ sqrt(mmsd(:,4));
errorbar(t, x, dx, 'k')

% calculate diffusion coefficiency
[fo, gof] = ma.fitMeanMSD;
plot(fo)
ma.labelPlotMSD;
legend off

And my PEI_chan00_Tracks.xml as outputted from TrackMate on FIJI (sorry about the mess, GitHub doesn't allow attaching this format):

<?xml version="1.0" encoding="UTF-8"?>
<Tracks nTracks="1" spaceUnits="pixel" frameInterval="1.0" timeUnits="frame" generationDateTime="Fri, 31 Dec 2021 00:44:16" from="TrackMate v7.4.0">
  <particle nSpots="423">
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    <detection t="410" x="243.0183864691459" y="344.26253253042063" z="0.0" />
    <detection t="411" x="244.16996138307113" y="342.57292842666914" z="0.0" />
    <detection t="412" x="244.13527769590496" y="342.0666091951257" z="0.0" />
    <detection t="413" x="243.026431280147" y="342.424675183517" z="0.0" />
    <detection t="414" x="244.17478407619075" y="341.53275460008894" z="0.0" />
    <detection t="415" x="243.8382276918444" y="342.7102356575479" z="0.0" />
    <detection t="416" x="244.13947269149944" y="342.0957901406573" z="0.0" />
    <detection t="417" x="244.05220740421703" y="341.31859106947417" z="0.0" />
    <detection t="418" x="243.85793638400204" y="340.8446018674191" z="0.0" />
    <detection t="419" x="244.09058094003132" y="341.76507450664" z="0.0" />
    <detection t="420" x="244.73533480541968" y="341.2792053882503" z="0.0" />
    <detection t="421" x="243.58544871761143" y="342.9334984777053" z="0.0" />
    <detection t="422" x="243.431320056101" y="343.2301651661782" z="0.0" />
    <detection t="423" x="244.10975559275707" y="340.14118211428126" z="0.0" />
  </particle>
</Tracks>

Apologies in advance because this sounds like a rather trivial problem on the surface, but I am quite new to Matlab, and I have no clue how to even begin looking for these NaN values.

mr-september commented 2 years ago

Not sure if I am on the right track, but I did notice that the mmsd object generated from mmsd = ma.getMeanMSD contains only Inf or NaN values.

In the getMeanMSD.m, lines 109-110 appear to be relevant:

% Standard deviation
mstd = sqrt( sum_weight ./ (sum_weight.^2 - sum_square_weight) .* sum_weighted_variance );
mr-september commented 2 years ago

After some more thought on this, I think it's a misunderstanding on my part on what is being done.

Typically, there are multiple particles/spots and tracks, from which statistics like mean, std deviation arise.

In my case, since only 1 particle is tracked, inf/NaN values should be expected for std deviation.

In a similar vein, it also makes no sense to "fit" a graph onto a single sampled curve.

Assuming this misunderstanding is the cause, I will close this issue. Please re-open if I am wrong!