please help simplify this for-loop-hell
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Martin
el 31 de Oct. de 2018
Comentada: Martin
el 1 de Nov. de 2018
The code below works as it should, but its slooow. I have a data variable with x number of cells. I want every row in column 6 of each cell, to match up and leave the respectively row value from column 3, in those rows. If the value from column 6 not match between the cells in data, I instead place a zero. I describe the data first:
data = 5; % data: cells with different size of rows e.g. 2000x6, 4000x6, 8000x6.
biggest_data_size = 8000; % can be other size as well (the one cell in data with most rows)
biggest_data_series = % this is 8000x1 series the 6. column in data{biggest_data_idx}. Unique increasing number (the one cell in data with most rows). I want this one as the first column in the result.
data_qty = 5; % can be other size as well, its the number of cells in data
result= [ biggest_data_series zeros(biggest_data_size,data_qty) ];
for i = 1 : data_qty
data_current_size = size(data{i},1);
for j = 1 : biggest_data_size
for h = 1 : data_current_size
if result(j,1) == data{i}(h,6)
result(j,i+1) = data{i}(h,3);
end
end
end
end
Hope I am clear enough. Any suggestions is very appreciated...
4 comentarios
Stephen23
el 1 de Nov. de 2018
@Martin: your example is not clear. You wrote in your question that you want the first column of result to be from "...(the one cell in data with most rows)", but in your example data{2} has the most rows yet you used data{1} for the first column. Please explain how this works.
Respuesta aceptada
Bruno Luong
el 1 de Nov. de 2018
Editada: Bruno Luong
el 1 de Nov. de 2018
data = {ceil(20*rand(100,6)) ceil(20*rand(50,6)) ceil(10*rand(20,6))};
biggest_data_series = randperm(15)';
biggest_data_size = length(biggest_data_series)
data_qty = length(data);
result= [ biggest_data_series zeros(biggest_data_size,data_qty) ];
% Your for-loop
for i = 1 : data_qty
data_current_size = size(data{i},1);
for j = 1 : biggest_data_size
for h = 1 : data_current_size
if result(j,1) == data{i}(h,6)
result(j,i+1) = data{i}(h,3);
end
end
end
end
result
% vectorize way
data_qty = length(data);
A = arrayfun(@(i) [i+zeros(size(data{i},1),1), data{i}(:,[6 3])], 1:data_qty, 'unif', 0);
A = cat(1,A{:});
[b,J] = ismember(A(:,2), biggest_data_series);
picklastrowfun = @(r) A(max(r),3);
rs = accumarray([J(b),A(b,1)],find(b),[biggest_data_size,data_qty],picklastrowfun);
rs = [biggest_data_series, rs]
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