Error Message "Unrecognized function or variable"

Question

Mary Hemler 2020-6-2

0
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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/540523-error-message-unrecognized-function-or-variable

回答： Star Strider 2020-6-2

I have run this script several times successfully, but I made a few changes to the folders where I was storing files and variables, and now I am getting this error message:

Unrecognized function or variable 'pcaBinnedSpikes'.

Error in M28_PoS_PCA (line 27)

[coeff, score, latent, tsquared, explained, mu] = pca(pcaBinnedSpikes');

Here is the code:

% State Space Visualization and PCA
% Pre-Process Data
headangledeg = rad2deg(headangle); % convert from radians to degrees
startTime = trackingtimes(1);
stopTime = trackingtimes(end);
% Make a matrix of activity for all neurons that 'spiked' at least 1000 times during the session. The shape of the matrix should be N by T, where N is the number of neurons and T is the number of time bins. Use the binning from the tracked head direction. Smooth the activity of each neuron with a Gaussian with ? = 10 time bins and then standardize the activity: (activity-mean(activity))/standard deviation(activity). 
j=1; 
for c=1:length(M28_PoS_spikes)
    if ~idx(c)
        continue
    end
    spikes = M28_PoS_spikes{c};
    spikes = spikes(spikes > startTime & spikes < stopTime);
    if length(spikes) >= 1000
        edgesT = linspace(startTime,stopTime,numel(trackingtimes)+1);
        binnedSpikes = histcounts(spikes,edgesT);
        binnedSpikes = smoothdata(binnedSpikes,2,'gaussian',50);
        pcaBinnedSpikes(j,:) = zscore(binnedSpikes);
        j = j+1;
    end
end
% Run PCA 
% Reduce the dimensionality of the matrix from N by T to 2 using Principal Component Analysis (PCA)
[coeff, score, latent, tsquared, explained, mu] = pca(pcaBinnedSpikes');
% Visualize the Population Activity
% Make a plot of the time points of the experiment, color-coded according to tracked head direction angle
figure
colormap hsv
scatter(score(:,1),score(:,2),15,headangle,'.')
axis equal
xlabel('1st Principal Component')
ylabel('2nd Principal Component')
title('Mouse 28 PoS PCA - High MI','FontSize',12)