How to solve the .mat file sorting? - matlab

Question

I have three .mat files, A.mat, B.mat and C.mat. And the content of the .mat files look like this:
![enter image description here][1]
It is in r2 = [rs2,cs2,sortedValues2] format. How can I sort rs2(e.g, 3468, 3909...) of the three
.mat files together in increasing order, and count the number of appearance of each element of rs2?
Anyone can give me any suggestion?

Answer 1

Original
First, you're going to want load each files r2, then pull out it's rs(1, :) value into a column vector, then sort that column vector. Once you have the vector, use logical indexing to determine how many times each element repeats. Finally, attach those tow columns together to attach each element to it's corresponding count. The output vector will have duplicate rows, but I assume that won't be a problem.
allData = [load('A.mat',r2); load('B.mat',r2)l; load('C.mat',r2)];
colVector = allData(:, 1);
sortedVec = sort(colVector);
countVec = zeros(size(sortedVec));
for ii = 1:length(sortedVec)
countVec(ii) = sum(sortedVec==sortedVec(ii));
end
outputVec = [sortedVec, countVec]
Edit
Since your edited question is easy, and almost the same as your original, I'll answer it here. Most of the code is the same, you just need to get the data out of the cell array instead of the files. Like so:
colVector = [yourCellArray{:}];
sortedVec = sort(colVector);
countVec = zeros(size(sortedVec));
for ii = 1:length(sortedVec)
countVec(ii) = sum(sortedVec==sortedVec(ii));
end
outputVec = [sortedVec, countVec]

Answer 2

load A
rs2_1 = r2(:,1);
clearvars r2
load B
rs2_2 = r2(:,1);
clearvars r2
load C
rs2_3 = r2(:,1);
clearvars r2
% to combine
rs2_combined = [rs2_1;rs2_2;rs2_3];
% to sort
rs2_sorted = sort(rs2_combined);
% to count for appearance
rs2_count = hist(rs2_combined, min(rs2_combined):1:max(rs2_combined));
EDIT: using cell arrays
% recreate your situation
R = cell(11,10);
R = cellfun(#(x) [randi(3000,50,1),ones(50,1),ones(50,1)*-.008], R,'UniformOutput', false);
% extract rs2
r = cell2mat( reshape(R, [1,1,11,10]) );
rs2 = reshape( r(:,1,:,:), [50*11*10,1] );
% do what you want
rs2_sorted = sort(rs2);
rs2_count = hist(rs2, min(rs2):1:max(rs2));
note - I assumed you have 50x3 arrays. If merely 50x1, then reshape(R, [1,11,10]) and reshape( r, [50*11*10,1] ); also works.
hist put all numbers into different bins of different values. It's equivalent to do
rs2_scale = min(rs2_combined):1:max(rs2_combined);
rs2_count = zeros(1, length(rs2_scale));
for ii = 1:length(rs2_scale)
rs2_count(ii) = sum( rs2_combined == rs2_scale(ii) );
end
To remove zero-count numbers -
rs2_count(rs2_count==0) = [];
Then you can calculate the probability -
rs2_prob = rs2_count / sum(rs2_count);
Validate this answer by
>> sum(rs2_prob)
ans =
1.0000