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Performance 带顺序限制的置换_Performance_Matlab_Permutation - Fatal编程技术网

Performance 带顺序限制的置换

Performance 带顺序限制的置换,performance,matlab,permutation,Performance,Matlab,Permutation,让L成为对象列表。此外,让C成为一组约束条件,例如: C(1)=t1位于t2之前,其中t1和t2属于L C(2)=t3位于t2之后,其中t3和t2属于L 如何(在MATLAB中)找到不违反C中约束的置换集 我的第一个解决方案很幼稚: orderings = perms(L); toBeDeleted = zeros(1,size(orderings,1)); for ii = 1:size(orderings,1) for jj = 1:size

L
成为对象列表。此外,让
C
成为一组约束条件,例如:

  • C(1)=t1位于t2之前,其中
    t1
    t2
    属于
    L
  • C(2)=t3位于t2之后,其中
    t3
    t2
    属于
    L
如何(在MATLAB中)找到不违反
C
中约束的置换集

我的第一个解决方案很幼稚:

    orderings = perms(L);
    toBeDeleted = zeros(1,size(orderings,1));
    for ii = 1:size(orderings,1)
           for jj = 1:size(constraints,1)
                   idxA = find(orderings(ii,:) == constraints(jj,1));
                   idxB = find(orderings(ii,:) == constraints(jj,2));
                   if idxA > idxB
                           toBeDeleted(ii) = 1;
                   end
           end
    end
其中
约束
是一组约束(每个约束位于两个元素的行上,指定第一个元素位于第二个元素之前)

我想知道是否存在更简单(更有效)的解决方案


提前谢谢。

我想说,到目前为止,这是一个非常好的解决方案

不过,我看到了一些优化。以下是我的变体:

% INITIALIZE

NN = 9;
L = rand(1,NN-1);
while numel(L) ~= NN;
    L = unique( randi(100,1,NN) ); end

% Some bogus constraints
constraints = [...
    L(1) L(2)
    L(3) L(6)
    L(3) L(5)
    L(8) L(4)];


% METHOD 0 (your original method)

tic

orderings = perms(L);

p = size(orderings,1);
c = size(constraints,1);

toKeep = true(p,1);
for perm = 1:p
    for constr = 1:c        
        idxA = find(orderings(perm,:) == constraints(constr,1));
        idxB = find(orderings(perm,:) == constraints(constr,2));
        if idxA > idxB
            toKeep(perm) = false;
        end
    end
end

orderings0 = orderings(toKeep,:);

toc

% METHOD 1 (your original, plus a few optimizations)

tic

orderings = perms(L);

p = size(orderings,1);
c = size(constraints,1);

toKeep = true(p,1);
for perm = 1:p    
    for constr = 1:c
        % break on first condition breached
        if toKeep(perm)
            % find only *first* entry
            toKeep(perm) = ...
                find(orderings(perm,:) == constraints(constr,1), 1) < ...
                find(orderings(perm,:) == constraints(constr,2), 1);
        else
            break
        end
    end    
end

orderings1 = orderings(toKeep,:);

toc


% METHOD 2

tic

orderings = perms(L);

p = size(orderings,1);
c = size(constraints,1);

toKeep = true(p,1);
for constr = 1:c

    % break on first condition breached1
    if any(toKeep)

        % Vectorized search for constraint values
        [i1, j1] = find(orderings == constraints(constr,1));
        [i2, j2] = find(orderings == constraints(constr,2));

        % sort by rows
        [i1, j1i] = sort(i1);   
        [i2, j2i] = sort(i2);   

        % Check if columns meet condition 
        toKeep = toKeep & j1(j1i) < j2(j2i);

    else
        break
    end   

end
orderings2 = orderings(toKeep,:);

toc

% Check for equality 
all(orderings2(:) == orderings1(:))
然而,整个方法有一个基本缺陷,即IMHO;直接使用
perms
。由于内存限制(
NN<10
,如
help perms
中所述),这本身就造成了限制


我强烈怀疑,当您将定制的
烫发
组合在一起时,您可以在时间和内存方面获得更好的性能。幸运的是,
perms
不是内置的,所以您可以先将该代码复制粘贴到自定义函数中

无论何时在向量或矩阵中查找某些内容,都应该使用find或ismember.Sure。建议的解决方案是伪代码(perms指令除外)。然而,我认为这不是可能的最佳解决方案,因为我必须迭代所有排序和所有约束。但是,我已经更新了代码(现在不是伪代码)。这是最好的。这个问题与。
Elapsed time is 17.911469 seconds.  % your method
Elapsed time is 10.477549 seconds.  % your method + optimizations
Elapsed time is 2.184242 seconds.   % vectorized outer loop
ans =
     1
ans =
     1