function [] = matchedPCAplot(dFF, M, sttype, i1, i2, r, c, ind)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%Performs the PCA for matching neurons between 2 dFF matrics and plots the
%output
% Inputs:
%     - dFF: Cell array of the dFF matrics for a mouse
%     - M: the nx2 matric of matching neurons
%     - il: The cell corresponding to column 1 of M in dFF
%     - i2: the cell corresponding to column 2 of M in dFF
%     - r: Number of rows in the subplot matrix
%     - c: number of columns in the subplot matrix
%     - ind: the 4 indices in the subplot matrix to plot the data on. Done
%     this way to allow for multiple comparisons on a single figure (r and
%     c can result in a large matrix than the indexes in ind)
% Output:

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
ndFF = cat(2, dFF{i1}(M(:, 1), :), dFF{i2}(M(:, 2), :)); %Concatenate the 2 relevant dFF matrices
nframe = size(dFF{i1}(M(:, 1), :), 2); %Number of frames in video 1

[coeff,score,latent,tsquared,explained,mu] = pca(ndFF','Centered', 'off');
[B, I] = sort(coeff(:, 1));
%Show the matrix of concatenated neural activity
subplot(r, c, ind(1))
imagesc(ndFF(I, :))
hold on
xline(size(dFF{i1}(M(:, 1), :), 2))
hold off
title(strcat(sttype{i1}, 32, 'vs', 32, sttype{i2}));
ylabel('Cell Number')
colorbar
%Plot the temporal evolution of the PCs for video 1
subplot(r, c, ind(2))

x = score(1:nframe, 1)';
y = score(1:nframe, 2)';
z = score(1:nframe, 3)';
col = 1:length(x);  % This is the color, vary with x in this case.
surface([x;x],[y;y],[z;z],[col;col],...
    'facecol','no',...
    'edgecol','interp',...
    'linew',2);
colormap(squeeze(cat(3, linspace(0, 1, 255), zeros(1, 255), linspace(1, 0, 255))))
view([-37.5 30])
%         plot(score(:, 1:min([size(coeff, 1) 3])));
%         xlabel('Frame')
%         xlim([0 size(score, 1)])
title(sttype{i1})
xlabel('PC 1')
ylabel('PC 2')
zlabel('PC 3')
y1 = ylim;
x1 = xlim;
z1 = zlim;
%Plot the temporal evolution of the PCs for video 2
subplot(r, c, ind(3))
x = score((nframe+1):end, 1)';
y = score((nframe+1):end, 2)';
z = score((nframe+1):end, 3)';
col = 1:length(x);  % This is the color, vary with x in this case.
surface([x;x],[y;y],[z;z],[col;col],...
    'facecol','no',...
    'edgecol','interp',...
    'linew',2);
colormap(squeeze(cat(3, linspace(0, 1, 255), zeros(1, 255), linspace(1, 0, 255))))
view([-37.5 30])
title(sttype{i2})
xlabel('PC 1')
ylabel('PC 2')
zlabel('PC 3')
y2 = ylim;
x2 = xlim;
z2 = zlim;

yn(1) = min([y1(1) y2(1)]);
yn(2) = max([y1(2) y2(2)]);
xn(1) = min([x1(1) x2(1)]);
xn(2) = max([x1(2) x2(2)]);
zn(1) = min([z1(1) z2(1)]);
zn(2) = max([z1(2) z2(2)]);
subplot(r, c, ind(2))
xlim(xn)
ylim(yn)
zlim(zn)
subplot(r, c, ind(3))
xlim(xn)
ylim(yn)
zlim(zn)
%Plot the temporal evolution for videos 1 and 2 merged. Colormap assumes
%videos 1 and 2 are the same length
subplot(r, c, ind(4))
x = score(:, 1)';
y = score(:, 2)';
z = score(:, 3)';
col = 1:length(x);  % This is the color, vary with x in this case.
ax1 = gca;
surface(ax1, [x;x],[y;y],[z;z],[col;col],...
    'facecol','no',...
    'edgecol','interp',...
    'linew',2);
cmap = squeeze(cat(3, linspace(0, 1, 127), zeros(1, 127), linspace(1, 0, 127)));
cmap2 = squeeze(cat(3, linspace(1, 0, 128), linspace(0, 1, 128), linspace(0, 1, 128)));

colormap(ax1, squeeze(cat(1, cmap, cmap2)))
view([-37.5 30])
title(strcat(sttype{i1}, 32, 'to', 32, sttype{i2}))
xlabel('PC 1')
ylabel('PC 2')
zlabel('PC 3')