Faster alternate to all() function

5 次查看（过去 30 天）
Abinesh G
Abinesh G 2024-8-22
评论： Abinesh G 2024-8-24
I am running a simulation of 100s of thousands loop and I am noticing that inside the each loop an all() function consumes almost 95% of the time. I want a faster alternate to this.
So here is my algorithm:
varname=rand([24665846,4])
for i=1:1000000
idx=idxkeep(i);
ind1=all(varname(:,1:4)==varname(idx,1:4),2);
ind=find(ind1);
end

请先登录，再回答此问题。

采纳的回答

Stephen23
Stephen23 2024-8-22
Ran in:
N = 10000;
varname = rand(246658,4)
varname = 246658x4
0.4250 0.9945 0.8854 0.7153 0.3372 0.4636 0.6927 0.0979 0.8001 0.5691 0.8808 0.8928 0.2207 0.6044 0.5163 0.3355 0.4153 0.7160 0.5742 0.4115 0.3663 0.2421 0.6953 0.7484 0.8841 0.4988 0.9958 0.3616 0.6892 0.5110 0.4978 0.6139 0.2841 0.1725 0.5703 0.7684 0.9457 0.2001 0.3747 0.8266
<mw-icon class=""></mw-icon>
<mw-icon class=""></mw-icon>
idxkeep = randi(size(varname,1),1,N);
tic
for i=1:N
idx = idxkeep(i);
idy = all(varname(:,1:4)==varname(idx,1:4),2);
idz = find(idy);
end
toc
Elapsed time is 15.020756 seconds.
tic
for i=1:N
idx = idxkeep(i);
idy = ...
varname(:,1)==varname(idx,1) & ...
varname(:,2)==varname(idx,2) & ...
varname(:,3)==varname(idx,3) & ...
varname(:,4)==varname(idx,4);
idz = find(idy);
end
toc
Elapsed time is 2.358080 seconds.
  3 个评论
显示 1更早的评论
Stephen23
Stephen23 2024-8-22
@Abinesh G: if my answer works for you then please remember to click the accept button!

请先登录，再进行评论。

更多回答（2 个）

Steven Lord
Steven Lord 2024-8-22
Ran in:
Are you sure the longest time is spent in all? Reducing the size of the varname variable and the number of iterations a bit (so it doesn't time out in MATLAB Answers) and looking at the times for the == operation and the all call:
varname=rand([246658,4]);
n = 10000;
timingData = zeros(n, 2);
% You never defined the variable idxkeep, so defining it here using random data
idxkeep = randi(size(varname,1),1,n);
for i=1:n
idx=idxkeep(i);
tic
x = varname(:,1:4)==varname(idx,1:4);
timingData(i, 1) = toc;
tic
ind1=all(x,2);
timingData(i, 2) = toc;
ind=find(ind1);
end
format longg
seconds(sum(timingData, 1))
ans = 1x2 duration array
12.990059 sec 3.09445199999994 sec
So it looks like the all call does not take the majority of the time. Most of the time is spent creating the logical array (named x in the modified example above.)
Now my choice of idxkeep is somewhat arbitrary. I'm guessing you have an alternate purpose for idxkeep. If you tell us in words not code what the purpose of this whole block of code is, we may be able to offer a more performant solution (perhaps one that avoids creating the large logical array.)
  3 个评论
显示 1更早的评论
Steven Lord
Steven Lord 2024-8-22
So you want the rows with unique entries for the first four columns? What happens if you call unique with the 'rows' and 'stable' options? Or use groupsummary or grouptransform to perform your filtering on the rows based on unique combinations of the elements in the first four columns?
Abinesh G
Abinesh G 2024-8-22
I have tried unique function infact idxkeep is the result from the unique function. But in my case I want rows with repeatations and perform filter only on them.
Also, groupsummary will not work in my case since I have to put multiple filter (for example: each row has a region id, I have to check whether the regions share boundary or not and some more) to decide whether to retain the rows with repeatations/or delete.
So I believe I cannot avoid loop. For the case of logical array, it would have been better if I reduce the time further. So far @Stephen23 solution is faster I would be happy if it can be further reduced.

请先登录，再进行评论。

arushi
arushi 2024-8-22
Hi Abhinesh,
Here’s a possible approach that uses vectorized operations and logical indexing to improve performance:
% Assuming idxkeep is a pre-defined vector of indices
% Precompute the subset of varname
varname_subset = varname(:, 1:4);
% Preallocate for results if needed
results = cell(1, 1000000);
for i = 1:1000000
idx = idxkeep(i);
target_row = varname_subset(idx, :);
% Compare using vectorized operations
% Use implicit expansion (broadcasting) for comparison
ind1 = sum(varname_subset == target_row, 2) == 4;
% Find the indices
ind = find(ind1);
% Store results if needed
results{i} = ind;
end
Hope this helps.
  1 个评论
Abinesh G
Abinesh G 2024-8-22
Hi Arushi,
Thank you for your quick response and for writing an improved script for my query. However, this approach does not solve my problem. When I ran the profiler, I noticed that this approach takes a little more time than the original. I am exploring faster alternatives, if any.

请先登录，再进行评论。

类别

在 Help Center 和 File Exchange 中查找有关 Troubleshooting in Polyspace Products for Ada 的更多信息

标签

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by