Fastest way to find the values and indices of the entries of a vector X that are closest to each entry of a matrix A.
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Basically wondering if there is a faster way to do something like this:
X = [0:.05:1]; % the vector
A = rand(100); % the matrix
result_val = zeros(100);
result_idx = zeros(100);
for i = 1:100
for j = 1:100
[result_val(i,j), result_idx(i,j)] = min( abs(A(i,j) - X) );
end
end
0 件のコメント
採用された回答
Githin George
2024 年 12 月 6 日
You can vectorize the operation as shown below:
X = 0:0.05:1; % the vector
A = rand(5000); % the matrix
%% Vectorized Approach
tic
% Reshape X to create 1x1xsize(X) array
X = reshape(X, 1, 1, []);
% Calculate the absolute differences NxNxsize(X)
differences = abs(A - X);
% Find the minimum differences and their indices along dim=3
[result_val, result_idx] = min(differences, [], 3);
toc
%% Non Vectorized Approach
tic
result_val1 = zeros(5000);
result_idx1 = zeros(5000);
for i = 1:5000
for j = 1:5000
[result_val1(i,j), result_idx1(i,j)] = min( abs(A(i,j) - X) );
end
end
toc
%%
disp("isequal(result_val,result_val1) output: "+ isequal(result_val1,result_val))
2 件のコメント
Image Analyst
2024 年 12 月 6 日
If you want to wait for additional answers using different approaches, you can.
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その他の回答 (1 件)
Matt J
2024 年 12 月 7 日
編集済み: Matt J
2024 年 12 月 7 日
result_idx = reshape( interp1(X,1:numel(X),A(:),'nearest','extrap') ,size(A));
result_val=abs(X(result_idx)-A);
2 件のコメント
Matt J
2024 年 12 月 7 日
編集済み: Matt J
2024 年 12 月 7 日
Speed comparison:
X = linspace(0,1,500); % the vector
A = rand(1000); % the matrix
%%Using min
tic
% Calculate the absolute differences NxNxsize(X)
differences = abs(A - reshape(X, 1, 1, []));
% Find the minimum differences and their indices along dim=3
[result_val, result_idx] = min(differences, [], 3);
toc
%%Using interp1
tic;
result_idx = reshape( interp1(X,1:numel(X),A(:),'nearest','extrap') ,size(A));
result_val=abs(X(result_idx)-A);
toc
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