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Reshaping a matrix based on the first row

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Kendall Galvez
Kendall Galvez 2024-4-24
评论： Voss 2024-4-27
I am trying to make a for loop that creates a new array that groups row data into corresponding columns:
My current arrays are something like this (both same size):
[270 270 270 271 272 272 273 273 273]
[12 2 3 14 5 2 6 8 11]
I want 4 columns (each representing 270, 271, 272, 273 respectively) that will produce something like this:
[12 14 5 6; 2 NAN 2 8; 3 NAN NAN 11]
my for loop is currently creating a 9 by 3 array that has the correct values in each column but is producing a bigger shape (more NANs).
for i = 1:length(data1)
for j = 1:length(number)
if data1(i) == number(j) % my dataset == a number array [270, 271, 272, 273]
newArray(i,j) = data2(i);
end
end
end

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回答（2 个）

Voss
Voss 2024-4-24
Ran in:
Here's one way:
A = [270 270 270 271 272 272 273 273 273];
B = [ 12 2 3 14 5 2 6 8 11];
[~,~,cidx] = unique(A,'stable');
ridx = accumarray(cidx,A,[],@(x){1:numel(x)});
ridx = [ridx{:}].';
NR = max(ridx);
NC = max(cidx);
result = NaN(NR,NC);
result(sub2ind([NR,NC],ridx,cidx)) = B
result = 3x4
12 14 5 6 2 NaN 2 8 3 NaN NaN 11
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Voss
Voss 2024-4-27
Ran in:
A = load('EventDays.mat').doy_e
A = 1x2065
270 270 270 270 270 NaN 270 270 270 270 270 270 270 270 270 270 270 270 270 270 270 270 270 270 270 270 270 270 270 270
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B = load('Events.mat').events
B = 1x2065
15 2 5 4 5 0 0 3 4 9 1 5 5 10 10 11 11 9 7 3 4 6 1 3 6 0 7 0 3 2
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idx = ~isnan(A);
[~,~,cidx] = unique(A(idx),'stable');
ridx = accumarray(cidx,A(idx),[],@(x){1:numel(x)});
ridx = [ridx{:}].';
NR = max(ridx);
NC = max(cidx);
result = NaN(NR,NC);
result(sub2ind([NR,NC],ridx,cidx)) = B(idx)
result = 72x31
15 7 1 4 4 3 9 2 1 6 2 5 4 1 1 1 0 2 1 3 3 2 3 3 1 5 2 1 0 0 2 1 3 0 3 4 2 1 6 13 2 3 2 1 0 0 1 0 5 4 16 14 5 25 0 0 0 0 0 0 5 2 9 1 5 1 0 2 3 7 0 0 3 0 0 2 7 2 1 13 1 1 2 5 2 0 0 0 7 0 4 6 4 1 8 1 0 0 0 1 2 3 3 0 0 4 1 8 3 3 2 8 6 2 9 0 5 0 3 0 5 4 8 6 4 1 4 4 4 4 1 1 3 6 9 1 0 3 12 4 7 2 1 10 0 1 1 0 0 3 0 2 1 2 3 2 8 3 14 5 1 3 2 0 0 0 0 2 3 9 4 6 4 3 0 0 0 0 0 0 3 4 4 3 8 5 6 4 3 5 0 3 0 1 5 3 2 8 10 4 7 6 3 5 1 0 0 0 1 0 4 3 2 6 5 5 1 1 10 0 1 1 1 3 8 1 2 1 3 19 7 2 2 4 0 5 2 1 5 1 9 1 2 7 12 2 2 2 1 0 10 7 6 0 0 0 2 1 16 12 0 5 1 1 0 0 1 0 0 1 1 5 0 1 10 1 3 4 6 4 1 3 23 1 3 0 4 9 12 9 15 11 7 0 0 1 0 0 0 0
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Stephen23
Stephen23 2024-4-27
编辑：Stephen23 2024-4-27
Ran in:
A = [270,270,270,271,272,272,273,273,273];
B = [ 12, 2, 3, 14, 5, 2, 6, 8, 11];
X = ~isnan(A);
C = findgroups(A(X));
R = grouptransform(ones(nnz(X),1),C(:),@cumsum);
M = accumarray([R,C(:)],B(X),[],[],NaN)
M = 3x4
12 14 5 6 2 NaN 2 8 3 NaN NaN 11
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  1 个评论
Stephen23
Stephen23 2024-4-27
Ran in:
Using your uploaded data (my code is unchanged). Note that your data also has NaNs in it, which so far you have not explained how you want to handle. I will remove them.
A = load('EventDays.mat').doy_e
A = 1x2065
270 270 270 270 270 NaN 270 270 270 270 270 270 270 270 270 270 270 270 270 270 270 270 270 270 270 270 270 270 270 270
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B = load('Events.mat').events
B = 1x2065
15 2 5 4 5 0 0 3 4 9 1 5 5 10 10 11 11 9 7 3 4 6 1 3 6 0 7 0 3 2
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X = ~isnan(A);
C = findgroups(A(X));
R = grouptransform(ones(nnz(X),1),C(:),@cumsum);
M = accumarray([R,C(:)],B(X),[],[],NaN)
M = 72x31
15 7 1 4 4 3 9 2 1 6 2 5 4 1 1 1 0 2 1 3 3 2 3 3 1 5 2 1 0 0 2 1 3 0 3 4 2 1 6 13 2 3 2 1 0 0 1 0 5 4 16 14 5 25 0 0 0 0 0 0 5 2 9 1 5 1 0 2 3 7 0 0 3 0 0 2 7 2 1 13 1 1 2 5 2 0 0 0 7 0 4 6 4 1 8 1 0 0 0 1 2 3 3 0 0 4 1 8 3 3 2 8 6 2 9 0 5 0 3 0 5 4 8 6 4 1 4 4 4 4 1 1 3 6 9 1 0 3 12 4 7 2 1 10 0 1 1 0 0 3 0 2 1 2 3 2 8 3 14 5 1 3 2 0 0 0 0 2 3 9 4 6 4 3 0 0 0 0 0 0 3 4 4 3 8 5 6 4 3 5 0 3 0 1 5 3 2 8 10 4 7 6 3 5 1 0 0 0 1 0 4 3 2 6 5 5 1 1 10 0 1 1 1 3 8 1 2 1 3 19 7 2 2 4 0 5 2 1 5 1 9 1 2 7 12 2 2 2 1 0 10 7 6 0 0 0 2 1 16 12 0 5 1 1 0 0 1 0 0 1 1 5 0 1 10 1 3 4 6 4 1 3 23 1 3 0 4 9 12 9 15 11 7 0 0 1 0 0 0 0
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