Error: Cannot set support to 'positive' with non-positive data.

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I continue to get the following error with my code:
Error using mvksdensity>compute_finite_support (line 274)
Cannot set support to 'positive' with non-positive data.
Error in mvksdensity (line 102)
[L,U] = compute_finite_support(support,ymin,ymax,d);
Error in ksdensity (line 226)
[fout,xout,u,plottype] = mvksdensity(yData,xi,varargin{:});
Error in collisions (line 537)
[f,xi] = ksdensity(cpdradial,'Support','positive','Censoring',cens,'NumPoints',10000);
I am running this code on data (attached file: 'dataset.met') to try and produce a density plot:
cpdcart = [];
for cpdtran2 = 1:particlecount
cpdcart = [cpdcart; collpos(cpdtran2).matrix(:,1:3)];
end
[cpdcol1,cpdrow1] = size(cpdcart);
cpdpolar = zeros(cpdcol1,2);
cpdradial = zeros(cpdcol1,1);
cpdphi = zeros(cpdcol1,1);
for cpdtran3 = 1:cpdcol1
cpdpolar(cpdtran3,1) = sqrt(cpdcart(cpdtran3,1).^2 + cpdcart(cpdtran3,2).^2 + cpdcart(cpdtran3,3).^2);
cpdradial(cpdtran3,1) = cpdpolar(cpdtran3,1);
cpdpolar(cpdtran3,2) = acos(cpdcart(cpdtran3,3)/cpdpolar(cpdtran3,1));
cpdphi(cpdtran3,1) = cpdpolar(cpdtran3,2);
end
figure
%Plot collisions depending only on radius
cens = (cpdradial<0.02);
[f,xi] = ksdensity(cpdradial,'Support','positive','Censoring',cens,'NumPoints',10000);
plot(xi,f,'w')
set(gca,'color','k')
xlabel 'Radial Distance (m) from Center of Sphere'
ylabel 'Collision Coordinate Density'
title({'Collision Coordinate Density vs Radial Distance',sprintf('Cross Section (m^2): %d',cs),sprintf('Temp (K): %d',ict),sprintf('Pressure (mTorr): %d',mTorr),sprintf('Time Span (sec): %d',tfin)})
hold on
grid on
grid minor
ax = gca;
ax.GridColor = 'w';
ax.MinorGridColor = 'w';
I know that my data is positive because I used the following for loop to determine if there were any negative values:
for checkneg = 1:164100
if cpdradial(checkneg,1) < 0
disp(cpdradial(checkneg,1))
else
end
end
Which did not find any values less than negative. Any ideas why its throwing this error?
Tom

采纳的回答

the cyclist
the cyclist 2019-5-30
编辑:the cyclist 2019-5-30
You've checked that your data are non-negative, not they're positive. I'm guessing that you have zeros, and the positive-support requirement means strictly positive, not just non-negative.
  3 个评论
the cyclist
the cyclist 2019-5-30
My intuition is that if you do not have a radical change in probability density between zero and very small values, then it should not be too bad as an approximation.
I suppose you could add a very tiny positive value to all your points, to nudge those zeros to positive, to see what the impact is.

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