%%%%%%%%%%%%%%%%%%%%%% Plot reconstructed picture %%%%%%%%%%%%%%%%%%%%%%%%
%  Reconstruct the island picture, using a subset of the PCs
%
%  To run this program, execute the following two lines (change the value
%  around for 'last_eof':
%
%  last_eof = 1;
%  plot_island_demo;
%
%  last_eof:  is the last EOF to use in the reconstruction.  
%

ind = 1:last_eof;
y2 = pcs(:,ind)*lds(:,ind)';          %  Reconstruct by summing over EOF's
                                     %  and PC's
y2 = reshape(y2, ntim, nlat, nlon);  %  Reshape back to picture format

%  Plot the reconstructed data
global_axes(6.4*.6, 4.8*.6, .5, .75, 1.5);
subplot2(1,2)
image(uint8(y2));
title(['\bfModes 1 through ' num2str(last_eof) ':  ' ...
       num2str(round(10000*sum(per(ind)))/100) '% Var Expl.'], ...
      'fontsize', 14);
  
%  Plot the Principal Components:
global_axes(1.25, 4.8*.6, 6.4*.6+.5, .75, 1.5);
subplot2(2,4); cla;
pp = plot(pcs(:,last_eof), ntim:-1:1, 'k');

%  If we're plotting the first PC, make it look good (remember, we
%  haven't removed the mean)
if last_eof == 1; set(gca, 'XLim', [0 8000]); end;

%  Make it pretty:
set(pp, 'linewidth', 2);
set(gca, 'YTickLabel', [], 'YLim', [1 ntim]);
grid on;
t1 = title(['\bfPC' num2str(last_eof)], 'fontsize', 14);

%  And, plot the EOF's.  Remember that the EOF's are 2-dimensional:  row
%  dimension by color dimension.  So, plot three lines that correspond to
%  the three colors:
global_axes(6.4*.6, 1.25, .5, .5, 2*.6*4.8+0.5+0.5+1.5);
subplot2(1,1); cla;
tem = squeeze(reshape(lds(:,last_eof), nlat, nlon));
pp = plot(1:nlat, tem);
set(pp(1), 'color', 'r');
set(pp(2), 'color', 'g');
set(pp(3), 'color', 'b');

%  If we're plotting the first EOF, make it look good (remember, we
%  haven't removed the mean)
if last_eof == 1; set(gca, 'YLim', [0 0.03]); end;

%  Make it pretty:
set(pp, 'linewidth', 2);
set(gca, 'XLim', [1 nlat]);
grid on
xl = xlabel(['\bfEOF' num2str(last_eof) ...
     ', ' num2str(round(10000*per(last_eof))/100) '% Var Expl.'], ...
     'fontsize', 14);