I have two matrices that are related and I need to sort one matrix while sorting the corresponding matrix the same way.

Hi again,

I have two matrices, A and B. A is failure times and B is censoring (all 0s and 1s). I need to sort the failure times (A) from smallest to largest but I need to keep the parts that are censored corresponding.

I need to sort both matrices with the exact same shift so all pieces stay connected and they get sorted smallest to largest.

For example, if I had:

A = [3, 5, 2, 7, 8;
     2, 3, 7, 3, 4;
     7, 3, 2, 6, 2];

B = [1, 0, 1, 1, 0;
     1, 1, 1, 0, 1;
     0, 1, 1, 0, 1];

sort(A) = [2, 3, 2, 3, 2;
           3, 3, 2, 6, 4;
           7, 5, 7, 7, 8]; %sorted by columns

and I need then,

B = [1, 1, 1, 0, 1;
     1, 1, 1, 0, 1;
     0, 0, 1, 1, 0]; %corresponding to the right censoring/failing category for sort(A)

I then need help making a new vector, C, which would rank sort(A) like this:

A = [3, 5, 2, 7, 8;
     2, 3, 7, 3, 4;
     7, 3, 2, 6, 2];

C = [1, 1, 1, 1, 1;
     2, 2, 2, 2, 2;
     3, 3, 3, 3, 3];

(just label the smallest as 1, the second smallest as 2, ..., the largest as n (where n is the total number of units in A).

Can someone help?

Answer 1

[James Tursa]

E.g.,

>> A = [3, 5, 2, 7, 8;
        2, 3, 7, 3, 4;
        7, 3, 2, 6, 2];
>> B = [1, 0, 1, 1, 0;
        1, 1, 1, 0, 1;
        0, 1, 1, 0, 1];
>> [SA,I] = sort(A)
SA =
     2     3     2     3     2
     3     3     2     6     4
     7     5     7     7     8
I =
     2     2     1     2     3
     1     3     3     3     2
     3     1     2     1     1
>> J = 0:size(A,2)-1
J =
     0     1     2     3     4
>> x = I + J*size(A,1) % or x = bsxfun(@plus,I,J*size(A,1))
x =
     2     5     7    11    15
     1     6     9    12    14
     3     4     8    10    13
>> SB = B(x)
SB =
     1     1     1     0     1
     1     1     1     0     1
     0     0     1     1     0
>> C = repmat((1:size(A,1))',1,size(A,2))
C =
     1     1     1     1     1
     2     2     2     2     2
     3     3     3     3     3