how to vectorize these "for loop"?

1 次查看（过去 30 天）
nelson
nelson 2017-8-5
评论： nelson 2017-8-5
clear all;
close all;
clc;
i=1;
for k=1:0.5:10;
for a=1:0.5:10;
for b= 1:0.5:10;
num(i,:)=[ k k*a];
den(i,:)=[1 b 0];
i=i+1;
end
end
end
[EDITED, Jan, Code formatted]

请先登录，再回答此问题。

采纳的回答

Andrei Bobrov
Andrei Bobrov 2017-8-5
My "ruble".
[b,a,k] = ndgrid(1:.5:10);
n = numel(k);
num1 = [k(:),k(:).*a(:)];
den1 = [ones(n,1), b(:), zeros(n,1)];
  2 个评论
Jan
Jan 2017-8-5
+1: This looks nice and clean. It is just 0.008 sec slower (for 100 iterations!) than the fastest solution I've found, but expanding, debugging and maintaining this nicer code will save at least minutes.
30% faster with explicite pre-allocation:
[b,a,k] = ndgrid(1:.5:10);
n = numel(k);
num = zeros(n, 2);
num(:,1) = k(:);
num(:,2) = k(:) .* a(:);
den = zeros(n, 3);
den(:,1) = 1;
den(:,2) = b(:);
But again: less nice and more prone to typos.

请先登录，再进行评论。

更多回答（1 个）

Jan
Jan 2017-8-5
编辑：Jan 2017-8-5
The loops are not the main problem here, but the missing pre-allocation.
n = 19^3;
num = zeros(n, 2); % <-- Inserted
den = zeros(n, 3); % <-- Inserted
i = 1;
for k = 1:0.5:10
for a = 1:0.5:10
for b = 1:0.5:10
num(i, :) = [k, k*a];
den(i, :) = [1, b, 0];
i = i + 1;
end
end
end
Now take a look in the data: all den(:, 1) are 1, all den(:, 3) are 0, and the 2nd component is a repeated 1:0.5:10. This can be abbreviated:
v = 1:0.5:10;
n = length(v);
den = zeros(n^3, 3);
den(:, 1) = 1;
den(:, 2) = repmat(v, 1, n^2);
For num:
num = zeros(n^3, 2);
num(:, 1) = repelem(v.', n^2, 1); % REPELEM in >= R2015a
tmp = repelem(v.', n, 1) * v; % Auto-Expand in >= R2016b
num(:, 2) = tmp(:);
For older Matlab versions:
num = zeros(n^3, 2);
num(:, 1) = reshape(repmat(v, n^2, 1), [], 1);
tmp1 = repmat(v, n, 1);
tmp2 = bsxfun(@times, tmp1(:), v);
num(:, 2) = tmp2(:);
Some timings (R2016b/64, Win7, Core2Duo):
tic; for k = 1:100, [d,n] = Untitled; end; toc
Elapsed time is 12.222231 seconds. % Original
Elapsed time is 0.779765 seconds. % Original with pre-allocation !!!
Elapsed time is 0.012142 seconds. % Vectorized >= 2016b
Elapsed time is 0.013797 seconds. % Vectorized <= 2015a
Elapsed time is 0.020055 seconds. % Andrei's solution
Pre-allocation yields a speed gain of factor 16, the vectorization a factor of 1000. Nice!
  3 个评论
显示 1更早的评论
Jan
Jan 2017-8-5
编辑：Jan 2017-8-5
@nelson: Please try it again. I've fixed some typos since the first posting. I get:
v = 1:0.5:10;
n = length(v);
i=1;
for k=v, for a=v, for b=v
num(i,:)=[ k k*a];
i=i+1;
end, end, end
num2 = zeros(n^3, 2);
num2(:, 1) = repelem(v.', n^2, 1); % >= R2015a
tmp = repelem(v.', n, 1) * v; % >= R2016b
num2(:, 2) = tmp(:);
isequal(num, num2) % 1: okay

请先登录，再进行评论。

类别

在 Help Center 和 File Exchange 中查找有关 Startup and Shutdown 的更多信息

标签

产品

Community Treasure Hunt

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

Start Hunting!

Translated by