I need help with my code. The code is used to find the minumin of a square-distance problem. I am providing my code through an example, I believe this will be the easiest way to explain what I need.
clear all
clc
x=10.8; % is a fixed value
y=34; % is a fixed value
z=12; % is a fixed value
A = [11 14 1; 5 8 18; 10 8 19; 13 20 16]; % a (4x3) matrix
B = [2 3 10; 6 15 16; 7 3 15; 14 14 19]; % a (4x3) matrix
I create a new matrix C which is composed in this following way:
C1 = bsxfun(#minus, A(:,1)',B(:,1));
C1=C1(:); % this is the first column of the new matrix C
C2 = bsxfun(#minus, A(:,2)',B(:,2));
C2=C2(:); % this is the second column of the new matrix C
C3 = bsxfun(#minus, A(:,3)',B(:,3));
C3=C3(:); % this is the third column of the new matrix C
C = [C1 C2 C3]; % the new matrix C of size (16x3)
C has to be formed in this way! And this is what I meant when I wrote in my title a composed-matrix
Then:
[d,p] = min((C(:,1)-x).^2 + (C(:,2)-y).^2 + (C(:,3)-z).^2);
d = sqrt(d);
outputs:
d = 18.0289;
p = 13;
Gives me the distance (d) and position (p) which satisfies this min problem.
MY PROBLEM:
I need to find which combinations of A and B has given my this p value, in other words I need the index from ´A,B´ which gives me this optimal C1,C2,C3:
C1 = bsxfun(#minus, A(?,1)',B(?,1));
C2 = bsxfun(#minus, A(?,2)',B(?,2));
C3 = bsxfun(#minus, A(?,3)',B(?,3));
The ? is the index position I need, in this case the index position of the matrix A and the index position of B.
Calculated by hand I have the following illustration:
I know that:
C = [9 11 -9
5 -1 -15
4 11 -14
-3 0 -18
3 5 8
-1 -7 2
-2 5 3
-9 -6 -1
8 5 9
4 -7 3
3 5 4
-4 -6 0
11 17 6
7 5 0
6 17 1
-1 6 -3]
And I know that my optimal index is given in the position 13th. This index positions goes back to:
[13-2 20-3 16-10]
Which is A(4,:) - B(1,:)
I need a code which can help me to find this indexes from A and B
Thanks in advance!
PS. I am using the code in parameter estimation problems of ODEs.
First case: vector-matrix case
subvals = bsxfun(#minus,A,[x y z])
[distance,index] = min(sqrt(sum(subvals.^2,2)))
Second case: Two matrices case
subvals = bsxfun(#minus,A,permute(B,[3 2 1]));
[distances,indices] = min(sqrt(sum(subvals.^2,2)),[],3)
Testing for second case:
%%// Get some random data into A and B
A = randi(20,8,3)
B = randi(20,4,3)
%%// Just to test out out code for correctness,
%%// let us make any one one row of B, say 3rd row equal to
%%// any one row of A, say the 6th row -
B(3,:) = A(6,:)
%%// Use the earlier code
subvals = bsxfun(#minus,A,permute(B,[3 2 1]));
[distances,indices] = min(sqrt(sum(subvals.^2,2)),[],3)
%%// Get the minimum row index for A and B
[~,min_rowA] = min(distances)
min_rowB = indices(min_rowA)
Verification
min_rowA =
6
min_rowB =
3
Edit 1 [Response to simple example posted in question]:
The title says you are interested in finding the difference of two matrices and then find the shortest distance between it to a vector [x y z]. So I am hoping this is what you need -
x=10.8;
y=34;
z=12;
A = [11 14 1; 5 8 18; 10 8 19; 13 20 16];
B = [2 3 10; 6 15 16; 7 3 15; 14 14 19];
C = A -B; %%// Distance of two vectors as posted in title
subvals = bsxfun(#minus,C,[x y z])
[distance,index] = min(sqrt(sum(subvals.^2,2)))
Output
distance =
31.0780
index =
3
Edit 2: After you have done this -
[d,p] = min((C(:,1)-x).^2 + (C(:,2)-y).^2 + (C(:,3)-z).^2);
If you are looking to find the corresponding indices of A and B , you may do this -
[minindex_alongB,minindex_alongA] = ind2sub(size(A),p)
Related
I have a n x m array (could be any size array but it will not be a 1 x m) and I want to rotate / shift each square loop individually no matter the array size.
How can I alternate the rotation / shift each square loop no matter the size of the array.
Please note: I'm not trying to calculate the values in the array but shift the values.
My thought process was to get the values of each "square loop" and place them into one row and do a circshift then place them back into another array.
I ran into problems trying to get the values back into the original n x m array size and I wasn't sure how I could loop through the process for different n x m arrays.
The pink highlighted section, left of the arrows is the starting position of the array and it's "loops" and the green highlighted section, right of the arrows is the type of rotation / shift of the values that I'm trying to create. The array could have more than 3 "loops" this is just an example.
Code below:
I=[1:5;6:10;11:15;16:20;21:25;26:30]
[rw,col] = size(I);
outer_1=[I(1,:),I(2:end-1,end).',I(end,end:-1:1),I(end-1:-1:2,1).'] %get values in one row (so I can shift values)
outer_1_shift=circshift(outer_1,[0 1]) %shift values
new_array=zeros(rw,col);
Ps: I'm using Octave 4.2.2 Ubuntu 18.04
Edit: The circshift function was changed for Octave 5.0, the last edit made it compatible with previous versions
1;
function r = rndtrip (n, m, v)
rv = #(x) x - 2 * (v - 1);
r = [v * ones(1,rv(m)-1) v:n-v+1 (n-v+1)*ones(1,rv(m)-2)];
if (rv(m) > 1)
r = [r n-v+1:-1:v+1];
endif
endfunction
function idx = ring (n, m , v)
if (2*(v-1) > min (n, m))
r = [];
else
r = rndtrip (n, m, v);
c = circshift (rndtrip (m, n, v)(:), - n + 2 * v - 1).';
idx = sub2ind ([n m], r, c);
endif
endfunction
# your I
I = reshape (1:30, 5, 6).';
# positive is clockwise, negative ccw
r = [1 -1 1];
for k = 1:numel(r)
idx = ring (rows(I), columns(I), k);
I(idx) = I(circshift(idx(:), r(k)));
endfor
I
gives
I =
6 1 2 3 4
11 8 9 14 5
16 7 18 19 10
21 12 13 24 15
26 17 22 23 20
27 28 29 30 25
run it on tio
So, I had the same idea as in Andy's comment. Nevertheless, since I was already preparing some code, here is my suggestion:
% Input.
I = reshape(1:30, 5, 6).'
[m, n] = size(I);
% Determine number of loops.
nLoops = min(ceil([m, n] / 2));
% Iterate loops.
for iLoop = 1:nLoops
% Determine number of repetitions per row / column.
row = n - 2 * (iLoop - 1);
col = m - 2 * (iLoop - 1);
% Initialize indices.
idx = [];
% Add top row indices.
idx = [idx, [repelem(iLoop, row).']; iLoop:(n-(iLoop-1))];
% Add right column indices.
idx = [idx, [[iLoop+1:(m-(iLoop-1))]; repelem(n-(iLoop-1), col-1).']];
if (iLoop != m-(iLoop-1))
% Add bottom row indices.
idx = [idx, [repelem(m-(iLoop-1), row-1).'; (n-(iLoop-1)-1:-1:iLoop)]]
end
if (iLoop != n-(iLoop-1))
% Add left column indices.
idx = [idx, [[(m-(iLoop-1))-1:-1:iLoop+1]; repelem(iLoop, col-2).']]
end
% Convert subscript indices to linear indices.
idx = sub2ind(size(I), idx(1, :), idx(2, :));
% Determine direction for circular shift operation.
if (mod(iLoop, 2) == 1)
direction = [0 1];
else
direction = [0 -1];
end
% Replace values in I.
I(idx) = circshift(I(idx), direction);
end
% Output.
I
Unfortunately, I couldn't think of a smarter way to generate the indices, since you need to maintain the right order and avoid double indices. As you can see, I obtain subscript indices with respect to I, since this can be done quite easy using the matrix dimensions and number of loops. Nevertheless, for the circshift operation and later replacing of the values in I, linear indices are more handy, so that's why the sub2ind operation.
Input and output look like this:
I =
1 2 3 4 5
6 7 8 9 10
11 12 13 14 15
16 17 18 19 20
21 22 23 24 25
26 27 28 29 30
I =
6 1 2 3 4
11 8 9 14 5
16 7 18 19 10
21 12 13 24 15
26 17 22 23 20
27 28 29 30 25
I was right, that the "shift direction" changes with every loop?
Hope that helps!
Caution: I haven't tested for generality, yet. So, please report any errors you might come across.
Suppose I have a matrix of dimension [4x4], and a vector of [16x1], I need to multiply every 4 element in the vector in one element in the matrix, (instead of multiplying element in row by element in vector), how can I do that using loop ?
For example here below, the results of the first four elements in the resulted vector as shown in the below example, then the same thing for the second, third and fourth rows in the matrix. :
So the results in that example is supposed to be [16x1]
Thank you
Using kron you can use this one-liner:
%A = [1 2 3 4; 5 6 7 8; 9 10 11 12; 13 14 15 16];
%v = [2 2 2 2 0 0 0 0 1 1 1 1 3 3 3 3].';
sum(kron(A,ones(4,4)).'.*v).'/4
I use the kronecker tensor product to "replicate" 4x4 time the A matrice. After that it's pure algebra.
This is just matrix multiplication in disguise... If your tall vector was a matrix of the same size as the matrix shown, where each highlighted block is a row, it's matrix multiplication. We can set this up, then reshape back into a vector.
You can use indexing to turn this into simple matrix multiplication. A question I answered already today details how the below indexing works using bsxfun, then we just reshape at the end:
% Setup
A = [1 2 3 4; 5 6 7 8; 9 10 11 12; 13 14 15 16];
v = [2 2 2 2 0 0 0 0 1 1 1 1 3 3 3 3].';
% Matrix mutliplication
r = numel(v)/size(A,1);
b = A * v( bsxfun( #plus, (1:r:numel(v)).', 0:r-1 ) );
% Make result a column vector
b = reshape( b.', [], 1 );
See if this is what you want:
A = [1 2 3 4; 5 6 7 8; 9 10 11 12; 13 14 15 16];
v = [2 2 2 2 0 0 0 0 1 1 1 1 3 3 3 3].';
r = reshape(sum(bsxfun(#times, permute(A, [3 2 1]), permute(reshape(v, 1, [], size(A,2)), [2 3 1])), 2), [], 1);
which gives
r =
17
17
17
17
41
41
41
41
65
65
65
65
89
89
89
89
There are details that I assumed, but this shoudl do the trick:
A=reshape(1:16,4,4).';
b=repelem([2,0,1,3],1,4).';
c=[];
for row=1:size(A,1)
c=[ c; sum(reshape(repelem(A(row,:),4).*b.',4,[]),2)];
end
I am assuming here that your demo for the vector is just a bad example and that you wont have repeated values, otherwise an easier version can be achieved by just not doing 3/4ths of the multiplications.
If you do not have access to repelem, have a look at alterative codes that do the same thing:Element-wise array replication in Matlab
Say I have an array the size 100x150x30, a geographical grid 100x150 with 30 values for each grid point, and want to find consecutive elements along the third dimension with a congruous length of minimum 3.
I would like to find the maximum length of consecutive elements blocks, as well as the number of occurrences.
I have tried this on a simple vector:
var=[20 21 50 70 90 91 92 93];
a=diff(var);
q = diff([0 a 0] == 1);
v = find(q == -1) - find(q == 1);
v = v+1;
v2 = v(v>3);
v3 = max(v2); % maximum length: 4
z = numel(v2); % number: 1
Now I'd like to apply this to the 3rd dimension of my array.
With A being my 100x150x30 array, I've come this far:
aa = diff(A, 1, 3);
b1 = diff((aa == 1),1,3);
b2 = zeros(100,150,1);
qq = cat(3,b2,b1,b2);
But I'm stuck on the next step, which would be: find(qq == -1) - find(qq == 1);. I can't make it work.
Is there a way to put it in a loop, or do I have to find the consecutive values another way?
Thanks for any help!
A = randi(25,100,150,30); %// generate random array
tmpsize = size(A); %// get its size
B = diff(A,1,3); %// difference
v3 = zeros(tmpsize([1 2])); %//initialise
z = zeros(tmpsize([1 2]));
for ii = 1:100 %// double loop over all entries
for jj = 1:150
q = diff([0 squeeze(B(ii,jj,:)).' 0] == 1);%'//
v = find(q == -1) - find(q == 1);
v=v+1;
v2=v(v>3);
try %// if v2 is empty, set to nan
v3(ii,jj)=max(v2);
catch
v3(ii,jj)=nan;
end
z(ii,jj)=numel(v2);
end
end
The above seems to work. It just doubly loops over both dimensions you want to get the difference over.
The part where I think you were stuck was using squeeze to get the vector to put in your variable q.
The try/catch is there solely to prevent empty consecutive arrays in v2 throwing an error in the assignment to v3, since that would remove its entry. Now it simply sets it to nan, though you can switch that to 0 of course.
Here's one vectorized approach -
%// Parameters
[m,n,r] = size(var);
max_occ_thresh = 2 %// Threshold for consecutive occurrences
% Get indices of start and stop of consecutive number islands
df = diff(var,[],3)==1;
A = reshape(df,[],size(df,3));
dfA = diff([zeros(size(A,1),1) A zeros(size(A,1),1)],[],2).'; %//'
[R1,C1] = find(dfA==1);
[R2,C2] = find(dfA==-1);
%// Get interval lengths
interval_lens = R2 - R1+1;
%// Get max consecutive occurrences across dim-3
max_len = zeros(m,n);
maxIDs = accumarray(C1,interval_lens,[],#max);
max_len(1:numel(maxIDs)) = maxIDs
%// Get number of consecutive occurrences that are a bove max_occ_thresh
num_occ = zeros(m,n);
counts = accumarray(C1,interval_lens>max_occ_thresh);
num_occ(1:numel(counts)) = counts
Sample run -
var(:,:,1) =
2 3 1 4 1
1 4 1 5 2
var(:,:,2) =
2 2 3 1 2
1 3 5 1 4
var(:,:,3) =
5 2 4 1 2
1 5 1 5 1
var(:,:,4) =
3 5 5 1 5
5 1 3 4 3
var(:,:,5) =
5 5 4 4 4
3 4 5 2 2
var(:,:,6) =
3 4 4 5 3
2 5 4 2 2
max_occ_thresh =
2
max_len =
0 0 3 2 2
0 2 0 0 0
num_occ =
0 0 1 0 0
0 0 0 0 0
If there is a vector like this,
T = [1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16]
(the size of vector T can be flexible)
How can I get a array of 'sum of divisions'?
For example,
fn(T, 5) = [ (1+2+3+4+5) , (6+7+8+9+10), (11+12+13+14+15) , 16]
One option, which doesn't require the padding of zeros on the original array, is the use of accumarray and ceil:
div = 5;
out = accumarray(ceil((1:numel(T))/div).',T(:))
Another option using cumsum and diff instead:
div = 5;
T(ceil(numel(T)/div)*div) = 0;
cs = cumsum(T)
out = diff( [0 cs(div:div:end) ] )
Edit: once the padding is done, cumsum and diff are a little overkill and one should proceed as in Bentoy's answer.
Another way, close to the 2nd option of thewaywewalk:
div = 5;
T(ceil(numel(T)/div)*div) = 0;
out = sum(reshape(T,div,[])).'; % transpose if you really want a column vector
Also, one one-liner solution (I prefer this one):
out = blockproc(T,[1 5], #(blk) sum(blk.data), 'PadPartialBlocks',true);
Don't forget to set the parameter 'PadPartialBlocks', this is the key of avoiding explicit padding.
There is an in-built function vec2mat in Communications System Toolbox to convert a vector into a 2D matrix that cuts off after every N elements and puts into separate rows, padding the leftover places at the end with zeros to maintain 2D size . So, after using vec2mat, summing all the rows would be enough to give you the desired output. Here's the implementation -
sum(vec2mat(T,5),2)
Sample run -
>> T = 1:16;
>> vec2mat(T,5)
ans =
1 2 3 4 5
6 7 8 9 10
11 12 13 14 15
16 0 0 0 0
>> sum(vec2mat(T,5),2)
ans =
15
40
65
16
I am trying to allocate (x, y) points to the cells of a non-uniform rectangular grid. Simply speaking, I have a grid defined as a sorted non-equidistant array
xGrid = [x1, x2, x3, x4];
and an array of numbers x lying between x1 and x4. For each x, I want to find its position in xGrid, i.e. such i that
xGrid(i) <= xi <= xGrid(i+1)
Is there a better (faster/simpler) way to do it than arrayfun(#(x) find(xGrid <= x, 1, 'last'), x)?
You are looking for the second output of histc:
[~,where] = histc(x, xGrid)
This returns the array where such that xGrid(where(i)) <= x(i) < xGrid(where(i)+1) holds.
Example:
xGrid = [2,4,6,8,10];
x = [3,5,6,9,11];
[~,where] = histc(x, xGrid)
Yields the following output:
where =
1 2 3 4 0
If you want xGrid(where(i)) < x(i) <= xGrid(where(i)+1), you need to do some trickery of negating the values:
[~,where] = histc(-x,-flip(xGrid));
where(where~=0) = numel(xGrid)-where(where~=0)
This yields:
where =
1 2 2 4 0
Because x(3)==6 is now counted for the second interval (4,6] instead of [6,8) as before.
Using bsxfun for the comparisons and exploiting find-like capabilities of max's second output:
xGrid = [2 4 6 8]; %// example data
x = [3 6 5.5 10 -10]; %// example data
comp = bsxfun(#gt, xGrid(:), x(:).'); %'// see if "x" > "xGrid"
[~, result] = max(comp, [], 1); %// index of first "xGrid" that exceeds each "x"
result = result-1; %// subtract 1 to find the last "xGrid" that is <= "x"
This approach gives 0 for values of x that lie outside xGrid. With the above example values,
result =
1 3 2 0 0
See if this works for you -
matches = bsxfun(#le,xGrid(1:end-1),x(:)) & bsxfun(#ge,xGrid(2:end),x(:))
[valid,pos] = max(cumsum(matches,2),[],2)
pos = pos.*(valid~=0)
Sample run -
xGrid =
5 2 1 6 8 9 2 1 6
x =
3 7 14
pos =
8
4
0
Explanation on the sample run -
First element of x, 3 occurs last between ...1 6 with the criteria of xGrid(i) <= xi <= xGrid(i+1) at the backend of xGrid and that 1 is at the eight position, so the first element of the output pos is 8. This continues for the second element 7, which is found between 6 and 8 and that 6 is at the fourth place in xGrid, so the second element of the output is 4. For the third element 14 which doesn't find any neighbours to satisfy the criteria xGrid(i) <= xi <= xGrid(i+1) and is therefore outputted as 0.
If x is a column this might help
xg1=meshgrid(xGrid,1:length(x));
xg2=ndgrid(x,1:length(xGrid));
[~,I]=min(floor(abs(xg1-xg2)),[],2);
or a single line implementation
[~,I]=min(floor(abs(meshgrid(xGrid,1:length(x))-ndgrid(x,1:length(xGrid)))),[],2);
Example: xGrid=[1 2 3 4 5], x=[2.5; 1.3; 1.7; 4.8; 3.3]
Result:
I =
2
1
1
4
3