I need a function that splits a vector in smaller frames with an overlap, like buffer, but instead of column-wise, it should be done row-wise.
This is how buffer works:
x = 1:20
x = buffer(x, 10, 5);
x = 0 1 6 11
0 2 7 12
0 3 8 13
0 4 9 14
0 5 10 15
1 6 11 16
2 7 12 17
3 8 13 18
4 9 14 19
5 10 15 20
What I want would be this though:
x = 0 0 1 2
1 2 3 4
3 4 5 6
5 6 7 8
7 8 9 10
9 10 11 12
11 12 13 14
13 14 15 16
15 16 17 18
17 18 19 20
Is there any function or way to achieve that? Maybe combination of buffer + some rearranging?
First figure out the answer in columns, then transpose the resulting matrix:
buffer(x, 4, 2).'
Related
Is there a MATLAB function to generate this matrix?:
[1 2 3 4 5 6 7 ... n;
2 3 4 5 6 7 8 ... n+1;
3 4 5 6 7 8 9 ... n+2;
...;
n n+1 n+2 ... 2*n-1];
Is there a name for it?
Thanks.
Yes indeed there's a name for that matrix. It's known as the Hankel matrix.
Use the hankel function in MATLAB:
out = hankel(1:n,n:2*n-1);
Example with n=10:
out =
1 2 3 4 5 6 7 8 9 10
2 3 4 5 6 7 8 9 10 11
3 4 5 6 7 8 9 10 11 12
4 5 6 7 8 9 10 11 12 13
5 6 7 8 9 10 11 12 13 14
6 7 8 9 10 11 12 13 14 15
7 8 9 10 11 12 13 14 15 16
8 9 10 11 12 13 14 15 16 17
9 10 11 12 13 14 15 16 17 18
10 11 12 13 14 15 16 17 18 19
Alternatively, you may be inclined to want a bsxfun based approach. That is certainly possible:
out = bsxfun(#plus, (1:n), (0:n-1).');
The reason why I wanted to show you this approach is because in your answer, you used repmat to generate the two matrices to add together to create the right result. You can replace the two repmat calls with bsxfun as it does the replication under the hood.
The above solution is for older MATLAB versions that did not have implicit broadcasting. For recent versions of MATLAB, you can simply do the above by:
out = (1:n) + (0:n-1).';
My standard approach is
repmat(1:n,n,1)+repmat((1:n)',1,n)-1
My data matrix is large: smt like 180:3000 size.
Each element value is between 0 to 255;
I have to find areas in this matrix where average value is higher than some threshold (lets call it 'P'). And reset each element in these areas to '0'. Another words filter my matrix.
I have width and heigth of filter area.
So I need to loop over data matrix to find appropriate areas (As many as exist).
EDIT:
Please, see an example:
4 6 7 5 6 6 7
10 8 9 8 9 10 9
10 8 9 8 9 10 9
7 4 6 9 7 8 7
4 5 5 5 5 5 5
4 5 5 5 5 5 5
10 12 12 12 13 10 11
14 15 15 16 14 15 15
13 15 15 15 14 14 13
This is given matrix. Lets try to find areas (2, 3) of size where average value is > 15.
So the result will be:
4 6 7 5 6 6 7
10 8 9 8 9 10 9
10 8 9 8 9 10 9
7 4 6 9 7 8 7
4 5 5 5 5 5 5
4 5 5 5 5 5 5
10 12 12 12 13 10 11
14 0 0 0 14 15 15
13 0 0 0 14 14 13
Please, look at bottom of matrix
Please, give me some tips how it is possible to loop throw.
Thank you very much.
One way of doint this is as follows:
% example A with more areas of mean greater than 15
% there are four such areas as shown here: http://i.imgur.com/V6m0NfL.jpg
A = [16 16 16 5 16 16 16
16 16 16 8 16 16 16
10 8 9 8 9 10 9
7 4 6 9 7 8 7
4 5 15.1 15 15 5 5
4 5 15 15 15 5 5
10 12 12 12 13 10 11
14 15 15 16 14 15 15
13 15 15 15 14 14 13];
% filter size
[n,m] = deal(2,3);
% filter center
center = floor(([n,m]+1)/2);
% find where we have areas greater than 15
B = nlfilter(A, [n,m], #(b) mean(b(:)) > 15);
% get coordinates of areas with mean > 15
[rows,cols] = find(B);
% zero out elements in all found areas
for i = 1:size(rows,1)
% calculate starting coordinates for the area to be set to 0
row = rows(i) - center(1) + 1;
col = cols(i) - center(2) + 1;
A(row:row+n-1 , col:col+m-1) = 0;
end
Results in:
A =
0 0 0 5 0 0 0
0 0 0 8 0 0 0
10 8 9 8 9 10 9
7 4 6 9 7 8 7
4 5 0 0 0 5 5
4 5 0 0 0 5 5
10 12 12 12 13 10 11
14 0 0 0 14 15 15
13 0 0 0 14 14 13
try this
a = input_matrix;
ii = 2 ; jj = 3;
threshold = 15;
x = ones(ii,jj)/(ii*jj);
%\\create matrix temp2 with average value of block a(i:i+ii-1,j:j+jj-1) at temp2(i,j)
temp1 = conv2(a,x,'full');
temp2 = temp1(ii:end-ii+1,jj:end-jj+1);
%\\find row and column indices of temp2 with value > threshold
[row_ col_] = find(temp2>threshold);
out = a;
%\\assign zero value to the corresponding blocks
for iii = 1:length(row_)
out(row_(iii):row_(iii)+ii-1,col_(iii):col_(iii)+jj-1) = 0;
end
I have an array A, I want to arrange each row in descending order to get a new array B. How could I do this ?
E.g.
Array A (original array):
11 9 13 10
12 4 1 6
13 5 12 11
Array B (rearranged array):
13 11 10 9
12 6 4 1
13 12 11 5
>> A=[11 9 13 10;12 4 1 6;13 5 12 11]
A =
11 9 13 10
12 4 1 6
13 5 12 11
>> sort(A,2,'descend')
ans =
13 11 10 9
12 6 4 1
13 12 11 5
For details type: help sort at Matlab command window
I have a pretty large matrix M and I am only interested in a few of the columns. I have a boolean vector V where a value of 1 represents a column that is of interest. Example:
-1 -1 -1 7 7 -1 -1 -1 7 7 7
M = -1 -1 7 7 7 -1 -1 7 7 7 7
-1 -1 7 7 7 -1 -1 -1 7 7 -1
V = 0 0 1 1 1 0 0 1 1 1 1
If multiple adjacent values of V are all 1, then I want the corresponding columns of M to be extracted into another matrix. Here's an example, using the matrices from before.
-1 7 7 -1 7 7 7
M1 = 7 7 7 M2 = 7 7 7 7
7 7 7 -1 7 7 -1
How might I do this efficiently? I would like all these portions of the matrix M to be stored in a cell array, or at least have an efficient way to generate them one after the other. Currently I'm doing this in a while loop and it is not as efficient as I'd like it to be.
(Note that my examples only include the values -1 and 7 just for clarity; this isn't the actual data I use.)
You can utilize the diff function for this, to break your V vector into blocks
% find where block differences exist
diffs = diff(V);
% move start index one value forward, as first value in
% diff represents diff between first and second in original vector
startPoints = find(diffs == 1) + 1;
endPoints = find(diffs == -1);
% if the first block begins with the first element diff won't have
% found start
if V(1) == 1
startPoints = [1 startPoints];
end
% if last block lasts until the end of the array, diff won't have found end
if length(startPoints) > length(endPoints)
endPoints(end+1) = length(V);
end
% subset original matrix into cell array with indices
results = cell(size(startPoints));
for c = 1:length(results)
results{c} = M(:,startPoints(c):endPoints(c));
end
The one thing I'm not sure of is if there's a better way to find the being_indices and end_indices.
Code:
X = [1 2 3 4 5 1 2 3 4 5
6 7 8 9 10 6 7 8 9 10
11 12 13 14 15 11 12 13 14 15
16 17 18 19 20 16 17 18 19 20
1 2 3 4 5 1 2 3 4 5
6 7 8 9 10 6 7 8 9 10
11 12 13 14 15 11 12 13 14 15
16 17 18 19 20 16 17 18 19 20];
V = logical([ 1 1 0 0 1 1 1 0 1 1]);
find_indices = find(V);
begin_indices = [find_indices(1) find_indices(find(diff(find_indices) ~= 1)+1)];
end_indices = [find_indices(find(diff(find_indices) ~= 1)) find_indices(end)];
X_truncated = mat2cell(X(:,V),size(X,1),[end_indices-begin_indices]+1);
X_truncated{:}
Output:
ans =
1 2
6 7
11 12
16 17
1 2
6 7
11 12
16 17
ans =
5 1 2
10 6 7
15 11 12
20 16 17
5 1 2
10 6 7
15 11 12
20 16 17
ans =
4 5
9 10
14 15
19 20
4 5
9 10
14 15
19 20
We have the following case:
Q = [idxcell{:,1}];
Sort = sort(Q,'descend')
Sort =
Columns 1 through 13
23 23 22 22 20 19 18 18 18 18 17 17 17
Columns 14 through 26
15 15 14 14 13 13 13 12 12 12 11 10 9
Columns 27 through 39
9 9 8 8 8 8 8 7 7 7 7 7 7
Columns 40 through 52
7 6 6 6 5 4 4 3 3 3 3 2 2
Columns 53 through 64
2 2 2 2 2 2 2 1 1 1 1 1
How can we sort matrix Sort according to how many times its values are repeated?
Awaiting result should be:
repeatedSort = 2(9) 7(7) 1(5) 8(5) 3(4) 18(4) 6(3) 9(3) 12(3) 13(3) 17(3) 4(2) 14(2) 15(2) 22(2) 23(2) 5(1) 10(1) 11(1) 19(1) 20(1)
or
repeatedSort = 2 7 1 8 3 18 6 9 12 13 17 4 14 15 22 23 5 10 11 19 20
Thank you in advance.
You can use the TABULATE function from the Statistics Toolbox, then call SORTROWS to sort by the frequency.
Example:
x = randi(10, [20 1]); %# random values
t = tabulate(x); %# unique values and counts
t = t(find(t(:,2)),1:2); %# get rid of entries with zero count
t = sortrows(t, -2) %# sort according to frequency
the result, where first column are the unique values, second is their count:
t =
2 4 %# value 2 appeared four times
5 4 %# etc...
1 3
8 3
7 2
9 2
4 1
6 1
Here's one way of doing it:
d = randi(10,1,30); %Some fake data
n = histc(d,1:10);
[y,ii] = sort(n,'descend');
disp(ii) % ii is now sorted according to frequency