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48c2ac22c0
This is a small, simple tutorial for testing the implementation of large, incomplete data bases. In this tutorial case, rStatAnalysis is used as post-processor and it uses a data base in memory, which is smaller than the number of snapshots on disk.
76 lines
954 B
Matlab
76 lines
954 B
Matlab
% open files
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fid1 = fopen('../recurrenceMatrix');
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% read dimensions
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A1 = fscanf(fid1, '%g %g');
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% skip the first two lines
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tline = fgetl(fid1);
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tline = fgetl(fid1);
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% get dimensions
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N1 = A1(1)
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M1 = A1(2)
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% allocate space
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B0 = zeros(M1,N1);
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% read data
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for i=1:N1
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B0(:,i) = fscanf(fid1, '%g', inf);
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tline = fgetl(fid1);
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tline = fgetl(fid1);
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end
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% close files
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fclose(fid1);
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% skip this many leading entries
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sle = 0;
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B1 = zeros(M1-sle,N1-sle);
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B1 = B0(1+sle:M1,1+sle:N1);
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maxval=0.0;
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%for i=1:M1
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% for j=1:N1
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% if(B1(i,j)>maxval)
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% maxval=B1(i,j);
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% endif
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% end
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%end
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maxval = 1.0;
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for i=1:M1-sle
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for j=1:N1-sle
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B1(i,j)=1-B1(i,j)/maxval;
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% B1(i,j)=B1(i,j)/maxval;
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end
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end
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% write full matrix to simple text file
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dlmwrite('myMatrix.txt',B1,'delimiter','\t','precision',3)
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%plot(C1)
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%saveas(gcf,'Plot','png')
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%B1=B1*1;
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%hold on
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%colormap(jet(50))
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%imagesc(B1)
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%colorbar
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%saveas(gcf,'Figure','png')
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