# Row combination for repeated values

조회 수: 2 (최근 30일)
Maha 2020년 2월 21일
댓글: Maha 2020년 2월 25일
Hello,
I have different variables (date, time, lat, lon) and X for different depths, where each column represents n times (number of different depths) the same variable at a different depth, let say 0 m, 100 m, 500 m. Here a more explicit example :
A = [20200101, NaN, NaN, 1200, NaN, NaN, 90, NaN, NaN, 45, NaN, NaN, 2, NaN, NaN; % 0 m
NaN, 20200101, NaN, NaN, 1200, NaN, NaN, 90, NaN, NaN, 45, NaN, NaN, 3, NaN; % 100 m
NaN, NaN, 20200101, NaN, NaN, 1200, NaN, NaN, 90, NaN, NaN, 45, NaN, NaN, 4 ]; % 500 m
How can I keep the repeated band combinations for date, time, latitude and longitude, so my final output would be, for each unique Date / Time / Lat / Lon :
B = [20200101, 1200, 90, 45, 2, 3, 4]; % Date / Time / Lat / Lon / Val 0m / Val100m / Val500m
I was thinking of using a for loop with find
find(A(i,1)==A(:,2) & A(i,1)==A(:,3) etc.)
But I if I have 50 different depths, it will be a lot of combinations. Does anyone has a simpler way in mind ?
Cheers
##### 댓글 수: 1이전 댓글 -1개 표시이전 댓글 -1개 숨기기
Jon 2020년 2월 21일
I'm not understanding what the columns in your A matrix represent. In particular how come the date appears in a different column in each row. Similarly why does the latitude appear in a different column. It looks like they shift over by 1 column in each succesive row, but I don't know if this is always the case, and what it means.

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### 답변 (1개)

Spencer Chen 2020년 2월 21일
Now, you were not very clear on your column structure. I understand it as in:
A = [date.depth1, date.depth2 .. date.depthNtime, lat.depth1, lat.depth2 ..lat.depthN, etc.]
% A = row X (depth and Var)
If that's the case, then something like this code would solve you problem:
nrows = size(A,1);
ndepth = 3;
A2 = reshape(A,nrows,ndepth,[]); % A2 = row X depth X Var
B = squeeze(nansum(A2,2));
The crux of it is to use nansum() to combine and ignore values from other depths. So we restructure the matrix so we can use nansum().
Blessings,
Spencer
##### 댓글 수: 5이전 댓글 3개 표시이전 댓글 3개 숨기기
Jon 2020년 2월 25일
I'm sorry, but I can not understand the problem description from the above. If you could please provide just one complete example of the input matrix or matrices that you actually would begin with and the final resulting matrix that you are looking for perhaps this would help. I see lots of matrices in the above discussion, but I can't follow what they are trying to illustrate. I think, one, simple, complete example would help.
Maha 2020년 2월 25일
My actual real matrix looks like A1, from my previous message, with 500k lines, and 10 different depths.
I need the B matrix as a result (every depth information for unique spatial and temporal information).
The solution I've shown just work for a consistent matrix A2, where each line would represent a depth. My A1 / True matrix isn't consistent.
I would like to either
1) switch from A1 to A2, then I could apply my previous solution
or
2) Find a direct solution to transform A1 into B

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