I have this 4 integer value output
example:
out = [ 8 7 6 5 ]
I would to save these 4 values in one place (in row i column j)
Such that when I try to access
array(i,j) I get the 4 values 8 7 6 5
I'm failing miserably. Any help is appreciated
If the number of values is the same for all i, and j, use a 3D array of size MxNx4:
array(1,1,:) = [8 7 6 5];
array(1,2,:) = [11 12 13 14];
You could imagine the four numbers are stacked on top of each other along a "depth" dimension in row i and column j.
array(i,j,:) gives the 1x1x4 array containing the four numbers corresponding to i, j. When accesing each group of four numbers, you may want to use squeeze to remove the singleton dimensions, i.e. to obtain the result as a column vector:
>> squeeze(array(1,1,:))
ans =
8
7
6
5
If the number of values may be different for each i and j, use a 2D cell array:
array{1,1} = [8 7 6 5];
array{1,2} = [11 12];
So array{i,j} gives the vector:
>> array{1,1}
ans =
8 7 6 5
Related
I have for example a=[1 2 3 4 5 6 7 8 9 10]; and I have to delete each 2 following numbers from 3.
like at the end it should be a=[1 4 7 10];
How to do this without a for loop.
And also if there is a way to guarantee that at the end the resulting array will have exact number of entries, like here it should be a with 4 entries at the end.
But for example we have b=[1 2 3 4 5 6 7 8 9 ]; and if I want make sure that at the end I still have 4 entries in the rest array, so that b can't be equal to [1 4 7] because I need 4 entries for sure.
You can use indexing for this:
A = 1:10;
B = A(1:3:end)
B =
[1 4 7 10]
Or, if you really want to remove elements:
A = 1:10;
A(2:3:end) = [];
A(3:3:end) = [];
For your second question regarding length checking, it's unclear what you're asking. Would an if comparison be enough ?
if numel(A) ~= 4
% ... Handle unexpected values here
end
Best,
As you mentioned in the question and in the comments that you need 4 elements at the end and if elements are less than 4 then you want to include the last element/s of b, the following should work:-
b=[1 2 3 4 5 6 7 8 9]
b_req=b(1:3:end);
temp=length(b_req);
if temp<4 b_req(end+1:4)=b(end-3+temp:end); % for including the elements of b so that total elements are 4 at the end
elseif temp>4 b_req=b_req(1:4); % for removing the extra elements
end
b_req
Output:-
b =
1 2 3 4 5 6 7 8 9
b_req =
1 4 7 9
and
if instead b=[1 2 3 4 5 6 7 8 9 10]; then the same code gives what you require, i.e. b_req = [1 4 7 10]
This code speaks for itself:
a = 1:15; % some vector
% returns every third element after the first one:
third_elemets = a(1:3:end);
% returns the missing elements for the vector to be in size 4 from the end of a
last_elements = a(end-3+length(third_elemets):end);
% take maximum 4 elements from a
logic_ind = true(min(4,length(third_elemets)),1);
% and concatanate them with last_elements (if there are any)
a = [third_elemets(logic_ind) last_elements]
and under the assumption that whenever there are less than 4 elements you simply take the last one(s) - it should always work.
I have a large array, which looks like this:
1
4
5
3
6
2
7
4
3
I want to rearrange this array that it looks like this:
7 4 3
3 6 2
1 4 5
My original array has the size 13700x1, so I cannot do it manually and if I use the reshape function, the array gets shaped in the wrong way:
1 3 7
4 6 4
5 2 3
I hope my intention is clear. Thanks!
Try
tmpArray = [1
4
5
3
6
2
7
4
3]
flipud(reshape(tmpArray, 3, 3).')
x = [1,4,5,3,6,2,7,4,3]';
A = flipud(reshape(x,3,3)');
The other answers assume your vector contains a square number of elements, 4, 9, 16 .... This is true for the example vector, but not for the one you're actually working with (it's 13700x1 according to the question).
This means that the flipud(reshape()) approach will give an error:
Product of known dimensions, 3, not divisible into total number of
elements, 13924.
This is not a problem if you don't want a square matrix, as numbers that can be represented as a product of any of the numbers: 2, 5, 137.
If you want a square matrix, you need to pad the vector with zeros, NaNs or something else. This can be done the following way:
A = randi(100,13700,1); %% Random 13700x1 matrix
n = numel(A); %% Number of elements in A (13700 in this case)
elements = ceil(sqrt(n))^2; %% Number of elements needed in order to make a square matrix
B = [A; zeros(elements-n,1)]; %% Pad the vectors with zeros.
%% You can also d0 B = [A; nan(elements-n,1)];
final_matrix = flipud(reshape(B, sqrt(elements),[]).'); %% Final operation
Suppose A is a 3-D matrix as below (2 rows-2 columns-2 pages).
A(:,:,1)=[1,2;3,4];
A(:,:,2)=[5,6;7,8];
I want to have a vector, say "a", whose inputs are the average of diagonal elements of matrices on each page. So in this simple case, a=[(1+4)/2;(5+8)/2].
But I have difficulties in matlab to do so. I tried the codes below but failed.
mean(A(1,1,:),A(2,2,:))
You can use "partially linear indexing" in the two dimensions that define the diagonal, as follows:
Since partially linear indexing can only be applied on trailing dimensions, you first need to apply permute to rearrange dimensions, so that the first and second dimensions become second and third.
Now you leave the first dimension untouched, linearly-index the diagonals in the second and third dimensions (which effectly reduces those two dimensions to one), and apply mean along the (combined) second dimension.
Code:
B = permute(A, [3 1 2]); %// step 1: permute
result = mean(B(:,1:size(A,1)+1:size(A,1)*size(A,2)), 2); %// step 2: index and mean
In your example,
A(:,:,1)=[1,2;3,4];
A(:,:,2)=[5,6;7,8];
this gives
result =
2.5000
6.5000
You can use bsxfun for a generic solution -
[m,n,r] = size(A)
mean(A(bsxfun(#plus,[1:n+1:n^2]',[0:r-1]*m*n)),1)
Sample run -
>> A
A(:,:,1) =
8 4 1
7 6 3
1 5 8
A(:,:,2) =
1 7 6
8 5 2
1 2 7
A(:,:,3) =
6 2 8
1 1 6
1 4 5
A(:,:,4) =
8 1 6
1 5 1
9 2 7
>> [m,n,r] = size(A);
>> sum(A(bsxfun(#plus,[1:n+1:n^2]',[0:r-1]*m*n)),1)
ans =
22 13 12 20
>> mean(A(bsxfun(#plus,[1:n+1:n^2]',[0:r-1]*m*n)),1)
ans =
7.3333 4.3333 4 6.6667
How can I remove elements in a matrix, that aren't all in a straight line, without going through a row at a time in a for loop?
Example:
[1 7 3 4;
1 4 4 6;
2 7 8 9]
Given a vector (e.g. [2,4,3]) How could I remove the elements in each row (where each number in the vector corresponds to the column number) without going through each row at a time and removing each element?
The example output would be:
[1 3 4;
1 4 4;
2 7 9]
It can be done using linear indexing at follows. Note that it's better to work down columns (because of Matlab's column-major order), which implies transposing at the beginning and at the end:
A = [ 1 7 3 4
1 4 4 6
2 7 8 9 ];
v = [2 4 3]; %// the number of elements of v must equal the number of rows of A
B = A.'; %'// transpose to work down columns
[m, n] = size(B);
ind = v + (0:n-1)*m; %// linear index of elements to be removed
B(ind) = []; %// remove those elements. Returns a vector
B = reshape(B, m-1, []).'; %'// reshape that vector into a matrix, and transpose back
Here's one approach using bsxfun and permute to solve for a 3D array case, assuming you want to remove indexed elements per row across all 3D slices -
%// Inputs
A = randi(9,3,4,3)
idx = [2 4 3]
%// Get size of input array, A
[M,N,P] = size(A)
%// Permute A to bring the columns as the first dimension
Ap = permute(A,[2 1 3])
%// Per 3D slice offset linear indices
offset = bsxfun(#plus,[0:M-1]'*N,[0:P-1]*M*N) %//'
%// Get 3D array linear indices and remove those from permuted array
Ap(bsxfun(#plus,idx(:),offset)) = []
%// Permute back to get the desired output
out = permute(reshape(Ap,3,3,3),[2 1 3])
Sample run -
>> A
A(:,:,1) =
4 4 1 4
2 9 7 5
5 9 3 9
A(:,:,2) =
4 7 7 2
9 6 6 9
3 5 2 2
A(:,:,3) =
1 7 5 8
6 2 9 6
8 4 2 4
>> out
out(:,:,1) =
4 1 4
2 9 7
5 9 9
out(:,:,2) =
4 7 2
9 6 6
3 5 2
out(:,:,3) =
1 5 8
6 2 9
8 4 4
I have an array A, and want to reshape the last four elements of each column into a 2x2 matrix. I would like the results to be stored in a cell array B.
For example, given:
A = [1:6; 3:8; 5:10]';
I would like B to contain three 2x2 arrays, such that:
B{1} = [3, 5; 4, 6];
B{2} = [5, 7; 6, 8];
B{3} = [7, 9; 8, 10];
I can obviously do this in a for loop using something like reshape(A(end-3:end, ii), 2, 2) and looping over ii. Can anyone propose a vectorized method, perhaps using something similar to cellfun that can apply an operation repeatedly to columns of an array?
The way I do this is to look at the desired indices and then figure out a way to generate them, usually using some form of repmat. For example, if you want the last 4 items in each column, the (absolute) indices into A are going to be 3,4,5,6, then add the number of rows to that to move to the next column to get 9,10,11,12 and so on. So the problem becomes generating that matrix in terms of your number of rows, number of columns, and the number of elements you want from each column (I'll call it n, in your case n=4).
octave:1> A = [1:6; 3:8; 5:10]'
A =
1 3 5
2 4 6
3 5 7
4 6 8
5 7 9
6 8 10
octave:2> dim=size(A)
dim =
6 3
octave:3> n=4
n = 4
octave:4> x=repmat((dim(1)-n+1):dim(1),[dim(2),1])'
x =
3 3 3
4 4 4
5 5 5
6 6 6
octave:5> y=repmat((0:(dim(2)-1)),[n,1])
y =
0 1 2
0 1 2
0 1 2
0 1 2
octave:6> ii=x+dim(1)*y
ii =
3 9 15
4 10 16
5 11 17
6 12 18
octave:7> A(ii)
ans =
3 5 7
4 6 8
5 7 9
6 8 10
octave:8> B=reshape(A(ii),sqrt(n),sqrt(n),dim(2))
B =
ans(:,:,1) =
3 5
4 6
ans(:,:,2) =
5 7
6 8
ans(:,:,3) =
7 9
8 10
Depending on how you generate x and y, you can even do away with the multiplication, but I'll leave that to you. :D
IMO you don't need a cell array to store them either, a 3D matrix works just as well and you index into it the same way (but don't forget to squeeze it before you use it).
I gave a similar answer in this question.