How to sort rows of a 2D array, such that all elements along a diagonal are non-zero?
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Thank you for looking at my question.
The problem: I have a square matrix containing random 0s and 1s, and I need to swap the rows around, so that all elements along one of the diagonals are 1s. (every row and column contains at least one 1, to make sure this is possible)
Is there any function that will be able to do this automatically or can you suggest how to go about doing it with code...?
11 件のコメント
Image Analyst
2014 年 4 月 13 日
I think this might be one of those problems that looks deceptively easy at first but once you get into it, it is revealed to be a lot harder, kind of like the knapsack problem or the traveling salesman problem.
Alberto
2014 年 4 月 14 日
I will comment my answer (somebody has to).
You can prove by induction that the property of 'having a 1 in each row and each column' can be transformed in the desired way (really easy prof, i promise).
So you have to cross the matrix, looking in every step k a row :
1) with an element 1 in the k-th and
2) the remaining matrix has the same property I talked before.
It will return how the matrix's rows has to be reordered.
回答 (3 件)
lvn
2014 年 4 月 16 日
For reference, here is a solution using the backtracking. The main algorithm part is around 20 lines.
This is the initial solution
xoriginal =
1 1 0 0 1
1 1 0 0 1
0 0 1 0 0
0 1 1 1 0
0 1 0 0 1
Shuffled version
x =
0 0 1 0 0
0 1 0 0 1
1 1 0 0 1
1 1 0 0 1
0 1 1 1 0
This is the solution found
xsol =
1 1 0 0 1
0 1 0 0 1
0 0 1 0 0
0 1 1 1 0
1 1 0 0 1
Order of the rows:
per =
3 2 1 5 4
Code:
function answw2
n=5 ; %Generate a matrix that fulfills the requirements
xoriginal=diag(ones(n,1));
y=rand(n,n);
xoriginal(y<(n/2-1)/(n-1))=1; %so that on average as much 0's as 1's (so sum(x(:))/n^2 = 0.5 on average)
x=xoriginal(randperm(n),:); %And permute it so that we have a challenge
%Alternatively use x=round(rand(n,n)) for a random 1/0 matrix with no guaranteed solution
%Now put the rows with fewest 1's on top, as it is best to start with these
[~,isorted]=sort(sum(x,2));
x=x(isorted,:);
%And now find the solution
per=first(x,0,1:n);
%Output the solution
disp('This is the initial solution'); xoriginal
disp('Shuffled version'); x
if ~isnan(per)
disp('This is the solution found'); xsol(per,:)=x
disp('Order of the rows: '); per
assert(all(diag(xsol)==1)) %Sanity test
else
disp('No solution found !');
return
end;
end
function solution=first(X, row, whichrowstoplace) %For a single root, loop over all leaves
solution=[];
for nr=1:length(X)-row %Try all possibilities to place the row + 1 in the correct position
solution=next(X, row+1, nr, whichrowstoplace);
if ~isnan(solution) %We got ourselves a solution, we can go back up a level
return
end
end
end
function solution=next(X, row, nr, whichrowstoplace)
firstrow=X(row,:); %Take the row
onelocation=find(firstrow); %And find the location of the ones
leaves=onelocation(ismember(onelocation,whichrowstoplace)); %We are only interested in the ones that we still need
if nr>length(leaves) %You exhausted all possible tests, the row cannot be placed and therefore root must be bad
solution=NaN;
else %Otherwise leaves(nr) is the next (candidate) solution
solution=[leaves(nr) first(X, row, whichrowstoplace(whichrowstoplace~=leaves(nr)))];
end;
end
0 件のコメント
Alberto
2014 年 4 月 12 日
編集済み: Alberto
2014 年 4 月 15 日
I created the function check(A), so i can check if the property 'every row and column are not all zeros'. Its useful later:
function condition=check(A)
cf=zeros(1,length(A));
for k=1:length(A) if sum(find(A(k,:)))==0 sum(find(A(:,k)))==0 cf(k)=0;
else
cf(k)=1;
end
end
if sum(cf)==length(A) condition=1;
else condition=0; end
end
Now you have a matrix A, use this script:
rowspermute=zeros(1,length(A));
B=A
mirango=1:length(A)
for k=1:length(A) % kth column
for j=mirango
miraux=mirango;
miraux(find(mirango==j))=[];
if A(j,k)==1 && check( A(miraux , k+1:end) )
rowspermute(k)=j;
mirango=miraux;
break
end
end
if rowspermute(k)
A(rowspermute(k), :)=zeros(1,length(A));
end
end
rowspermute % has the rows to reorder
4 件のコメント
Alberto
2014 年 4 月 15 日
The idea behind the code is selecting a row with 1 in the desired position, and that can be eliminated in the matrix without loosing the property (ones in every row and column).
At first i tried to erase the row in the matrix so the same row couldn't be chosen twice, but it was tricky to track which number of the original rows in matrix A.
I thought putting zeroes in that row was an elegant solution to prevent that row to be chosen again.
The if block has the porpose to be sure a row was selected before.
Image Analyst
2014 年 4 月 13 日
If you're willing to use circshift, then try this:
clc;
rows = 20;
columns = 20;
m = randi(2, [rows, columns])-1
output = zeros(size(m));
for row = 1 : rows
% Get this row.
thisRow = m(row, :);
% Shift it until we get a 1 in column "row".
for colShift = 0 : columns - 1
% Shift this row by some amount.
shiftedRow = circshift(thisRow, colShift, 2)
% See if we shiftwed a 1 into the diagonal element at column "row"
if shiftedRow(row) == 1
% It's a 1, so we're done.
output(row, :) = shiftedRow;
% Quit shifting this row.
break;
end
end
end
output % Display in command window.
6 件のコメント
Image Analyst
2014 年 4 月 16 日
Good information. I think you're right. Nice to know there's an organized way for solving it. Seems a bit tough for a homework problem though - glad I don't have that teacher. I started thinking about graph solving algorithms and thought it had to be like one of them. Personally I only know about Djikstra and A* though there are lots of similar kinds of graph search algorithms. (Funny, after I had independently "discovered" A* as part of my Ph.D. research, I found out that it had already been invented. Bummer. Lost out on that glory.)
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