given
A=1 1 0
1 2 0.563826213141399
1 3 1.18321595677734
1 4 1.95685972913029
2 1 0.563826213141399
2 2 0
2 3 0.830602192143995
2 4 1.65196852337589
2 5 1.77172232586001
3 1 1.18321595677734
3 2 0.830602192143995
3 3 0
3 4 0.821522975656861
3 5 1.12716458303105
3 6 1.78117938413852
as seen row 2 and 5 are same in real but not in the matrix. how can I remove one of the same rows?
using unique I couldn't do this.
It seems like you have a representation of a graph using a weighted adjacency matrix.
If I understand correctly, you wish to have a single entry per edge.
You can do this by taking only the upper triangle of the adjacency matrix
A = sparse( A(:,1), A(:,2), A(:,3), max(A(:,2)), max(A(:,2)) );
[ii jj wij] = find( triu( A ) ) ;
disp( [ii jj wij] )
outputs:
1 2 0.563826
1 3 1.183216
2 3 0.830602
1 4 1.956860
2 4 1.651969
3 4 0.821523
2 5 1.771722
3 5 1.127165
3 6 1.781179
Related
I need some help please. I have an array, as shown below, 6 rows and 5 columns, none of the elements in any one row repeats. The elements are all single digit numbers.
I want to find out, per row, when a number, let's say 1 appears, I want to keep of how often the other numbers of the row appear. For example, 1 shows up 3 times in rows one, three and five. When 1 shows up, 2 shows up one time, 3 shows up two times, 4 shows up two times, 5 shows up one time, 6 shows up two times, 7 shows up one time, 8 shows up three times, and 9 shows up zero times. I want to keep a vector of this information that will look like, V = [3,1,2,2,1,2,1,3,0], by starting with a vector like N = [1,2,3,4,5,6,7,8,9]
ARRAY =
1 5 8 2 6
2 3 4 6 7
3 1 8 7 4
6 5 7 9 4
1 4 3 8 6
5 7 8 9 6
The code I have below does not give the feedback I am looking for, can someone help please? Thanks
for i=1:length(ARRAY)
for j=1:length(N)
ARRAY(i,:)==j
V(j) = sum(j)
end
end
Using indices that is in A creae a zero and one 6 * 9 matrix that [i,j] th element of it is 1 if i th row of A contains j.
Then multiply the zero and one matrix with its transpose to get desirable result:
A =[...
1 5 8 2 6
2 3 4 6 7
3 1 8 7 4
6 5 7 9 4
1 4 3 8 6
5 7 8 9 6]
% create a matrix with the size of A that each row contains the row number
rowidx = repmat((1 : size(A,1)).' , 1 , size(A , 2))
% z_o a zero and one 6 * 9 matrix that [i,j] th element of it is 1 if i th row of A contains j
z_o = full(sparse(rowidx , A, 1))
% matrix multiplication with its transpose to create desirable result. each column relates to number N
out = z_o.' * z_o
Result: each column relates to N
3 1 2 2 1 2 1 3 0
1 2 1 1 1 2 1 1 0
2 1 3 3 0 2 2 2 0
2 1 3 4 1 3 3 2 1
1 1 0 1 3 3 2 2 2
2 2 2 3 3 5 3 3 2
1 1 2 3 2 3 4 2 2
3 1 2 2 2 3 2 4 1
0 0 0 1 2 2 2 1 2
I don't understand how you are approaching the problem with your sample code but here is something that should work. This uses find, any and accumarray and in each iteration for the loop it will return a V corresponding to the ith element in N
for i=1:length(N)
rowIdx = find(any(A == N(i),2)); % Find all the rows contain N(j)
A_red = A(rowIdx,:); % Get only those rows
V = [accumarray(A_red(:),1)]'; % Count occurrences of the 9 numbers
V(end+1:9) = 0; % If some numbers don't exist place zeros on their counts
end
As the title says, I want to find all rows in a Matlab matrix that in certain columns the values in the row are equal with the values in the previous row, or in general, equal in some row in the matrix. For example I have a matrix
1 2 3 4
1 2 8 10
4 5 7 9
2 3 6 4
1 2 4 7
and I want to find the following rows:
1 2 3 4
1 2 3 10
1 2 4 7
How do I do something like that and how do I do it generally for all the possible pairs in columns 1 and 2, and have equal values in previous rows, that exist in the matrix?
Here's a start to see if we're headed in the right direction:
>> M = [1 2 3 4;
1 2 8 10;
4 5 7 9;
2 3 6 4;
1 2 4 7];
>> N = M; %// copy M into a new matrix so we can modify it
>> idx = ismember(N(:,1:2), N(1,1:2), 'rows')
idx =
1
1
0
0
1
>> N(idx, :)
ans =
1 2 3 4
1 2 8 10
1 2 4 7
Then you can remove those rows from the original matrix and repeat.
>> N = N(~idx,:)
N =
4 5 7 9
2 3 6 4
this will give you the results
data1 =[1 2 3 4
1 2 8 10
4 5 7 9
2 3 6 4
1 2 4 7];
data2 = [1 2 3 4
1 2 3 10
1 2 4 7];
[exists,position] = ismember(data1,data2, 'rows')
where the exists vector tells you wheter the row is on the other matrix and position gives you the position...
a less elegant and simpler version would be
array_data1 = reshape (data1',[],1);
array_data2 = reshape (data2',[],1);
matchmatrix = zeros(size(data2,1),size(data1,1));
for irow1 = 1: size(data2,1)
for irow2 = 1: size(data1,1)
matchmatrix(irow1,irow2) = min(data2(irow1,:) == data1(irow2,:))~= 0;
end
end
the matchmatrix is to read as a connectivity matrix where value of 1 indicates which row of data1 matches with which row of data2
Let's assume A be,
1 1 1 1 1 1
1 2 2 3 3 3
4 4 2 2 3 3
4 4 2 2 2 3
4 4 4 4 3 3
5 5 5 5 5 5
I need to identify all the numbers which are adjacent to a particular intensity value. E.g. the intensities 1, 3, and 4 are adjacent to the intensity value 2.
What is the effective way to do it in Matlab?
I can use the following,
glcm = graycomatrix(A)
But if A have a larger number of intensity values e.g. 10000 graycomatrix will not be an efficient method.
You can build a mask with a 2D convolution, select the values according to that mask, and then reduce them to unique values:
% // Data:
A = [ 1 1 1 1 1 1
1 2 2 3 3 3
4 4 2 2 3 3
4 4 2 2 2 3
4 4 4 4 3 3
5 5 5 5 5 5 ];
value = 2;
adj = [0 1 0; 1 0 1; 0 1 0]; %// define adjacency. [1 1 1;1 0 1;1 1 1] to include diagonals
%// Let's go
mask = conv2(double(A==value), adj, 'same')>0; %// pixels adjacent to those equal to `value`
result = unique(A(mask));
In the example, this produces
result =
1
2
3
4
Note that the result includes 2 because some pixels with value 2 have adjacent pixels with that value.
given matrix A of size 6 by 6 contain blocks of numbers,each block of size 2 by 2, and outher reference matrix R of size 2 by 12 also contain blocks of numbers, each block of size 2 by 2. the perpse of the whole process is to form a new matrix, called the Index matrix, contain index's that refer to the position of the blocks within the matrix A based on the order of the blocks within the reference matrix R. and here is an exemple
matrix A:
A =[1 1 2 2 3 3;
1 1 2 2 3 3;
1 1 3 3 4 4;
1 1 3 3 4 4;
4 4 5 5 6 6;
4 4 5 5 6 6 ]
matrix R:
R=[1 1 2 2 3 3 4 4 5 5 6 6;
1 1 2 2 3 3 4 4 5 5 6 6 ]
the new matrix is:
Index =[1 2 3;
1 3 4;
4 5 6]
any ideas ?
With my favourite three guys - bsxfun, permute, reshape for an efficient and generic solution -
blksz = 2; %// blocksize
num_rowblksA = size(A,1)/blksz; %// number of blocks along rows in A
%// Create blksz x blksz sized blocks for A and B
A1 = reshape(permute(reshape(A,blksz,num_rowblksA,[]),[1 3 2]),blksz^2,[])
R1 = reshape(R,blksz^2,1,[])
%// Find the matches with "bsxfun(#eq" and corresponding indices
[valid,idx] = max(all(bsxfun(#eq,A1,R1),1),[],3)
%// Or with PDIST2:
%// [valid,idx] = max(pdist2(A1.',reshape(R,blksz^2,[]).')==0,[],2)
idx(~valid) = 0
%// Reshape the indices to the shapes of blocked shapes in A
Index = reshape(idx,[],num_rowblksA).'
Sample run with more random inputs -
>> A
A =
2 1 1 2
1 2 2 1
1 1 1 1
2 2 2 2
1 2 2 1
1 2 1 1
>> R
R =
2 1 1 1 1 2 2 2 1 1 1 1
2 1 2 1 1 2 2 1 2 2 2 1
>> Index
Index =
0 0
5 5
3 0
This question already has answers here:
Generate all possible combinations of the elements of some vectors (Cartesian product)
(4 answers)
Closed 8 years ago.
So I'm writing a program to determine the unique combinations of a beaded necklace, but I can't seem to get it right. The rules are you can't have the same necklace forwards and backwards, and you can't have the same necklace with one bead being slid around to the other end. I've attached some pictures to clarify.
I wrote the code for it, and I thought I had achieved what I was trying to do, but it's not working correctly.
n = [1 2 3 4 2 4];
% green = 1
% blue = 2
% yellow = 3
% red = 4
p = perms(n);
total = max(size(p));
for i = 1:max(size(p))
q = p;
q(i) = [];
for j = 1:max(size(q))
if isequal(p(i),fliplr(q(j)))
total = total - 1;
elseif isequal(p(i),circshift(q(j),[1,1]))
total = total - 1;
elseif isequal(p(i),circshift(q(j),[length(q(j))-1,length(q(j))-1]))
total = total - 1;
end
disp(total)
end
end
Logically, this makes sense to me, but I could just be crazy.
If the problem size is small, you can vectorize all the comparisons (using bsxfun):
n = [1 2 3 4 2 4];
%// green = 1
%// blue = 2
%// yellow = 3
%// red = 4
N = numel(n);
p = perms(n).'; %'// generate all permutations
p2 = NaN([size(p) N+1]); %// this will store permutations with flips and shifts
p2(:,:,1) = p; %// original
p2(:,:,2) = flipud(p); %// flips
for k = 1:N-1
p2(:,:,2+k) = circshift(p,k); %// circular shifts
end
eqElem = bsxfun(#eq, p, permute(p2, [1 4 2 3]));
eqMat = squeeze(any(all(eqElem, 1), 4)); %// 1 if equal
remove = any(tril(eqMat, -1), 1); %// remove permutations that are "similar"
%// to a previous one, where "similar" means "equal up to circular shifts or
%// flips"
result = p(:,~remove).'; %'// all valid arrangements; one per row
resultNum = size(result, 1); %// number of arrangements
Results:
result =
1 3 2 2 4 4
1 3 2 4 4 2
1 3 2 4 2 4
1 3 4 2 2 4
1 3 4 2 4 2
1 3 4 4 2 2
1 2 3 2 4 4
1 2 3 4 2 4
1 2 3 4 4 2
1 2 2 3 4 4
1 2 2 4 4 3
1 2 2 4 3 4
1 2 4 3 2 4
1 2 4 3 4 2
1 2 4 2 3 4
1 2 4 2 4 3
1 2 4 4 2 3
1 2 4 4 3 2
1 4 4 3 2 2
1 4 4 2 2 3
1 4 4 2 3 2
1 4 3 4 2 2
1 4 3 2 2 4
1 4 3 2 4 2
1 4 2 3 2 4
1 4 2 3 4 2
1 4 2 2 3 4
1 4 2 2 4 3
1 4 2 4 2 3
1 4 2 4 3 2
resultNum =
30
You should do p = unique(p,'rows') before any loops. To see why, call perms([1 1 1]) at the command line.
There are a few issues here:
1) p, the perms, is a 2D matrix, so to get each perm you need to do p(i,:) to get the row. p(i) is just a single number.
2) You don't remove wrong answers from your list, so you will check against them twice. For example, say the first in the list is [1 2 3 4 2 4]; and the second is [4 2 4 3 2 1];. The fliplr check will compare these two combinations twice, once in the first loop around, once in the second.
3) If you want to make sure that any permutation which is a rotation is excluded (not just moving one bead around), you'll need some more circshift.
Consider using ismember with rows option again to compare a single row (e.g. a flipped version of the row you're checking) to an entire matrix.