Can sombody please show me how the forward slash operator applies to this?
Say we have
P = [3, 3, 1]
and A = zeros(3,3);
A(1,:) = [30, 15, 1];
A(2,:) = [10, 20, 1];
A(3,:) = [1, 1, 1];
what would:
x = A\P look like?
You need to use P.', the transpose.
Related
I am trying to find an efficient way of extracting groups of n consecutive columns in a matrix. Example:
A = [0, 1, 2, 3, 4; 0, 1, 2, 3, 4; 0, 1, 2, 3, 4];
n = 3;
should produce an output similar to this:
answer = cat(3, ...
[0, 1, 2; 0, 1, 2; 0, 1, 2], ...
[1, 2, 3; 1, 2, 3; 1, 2, 3], ...
[2, 3, 4; 2, 3, 4; 2, 3, 4]);
I know this is possible using a for loop, such as the following code snippet:
answer = zeros([3, 3, 3]);
for i=1:3
answer(:, :, i) = A(:, i:i+2);
endfor
However, I am trying to avoid using a for loop in this case - is there any possibility to vectorize this operation as well (using indexed expressions)?
Using just indexing
ind = reshape(1:size(A,1)*n, [], n) + reshape((0:size(A,2)-n)*size(A,1), 1, 1, []);
result = A(ind);
The index ind is built using linear indexing and implicit expansion.
Using the Image Package / Image Processing Toolbox
result = reshape(im2col(A, [size(A,1) n], 'sliding'), size(A,1), n, []);
Most of the work here is done by the im2col function with the 'sliding' option.
A=2;
for x=0:2:4
A=[A, A*x];
end
A
I'd appreciate any help! The for loop condition as well as the 3rd line and how they work together I can't quite piece together
So, here comes the walktrough.
A = 2;
A is an array of length 1, with 2 as the only element.
for x = 0:2:4
Have a look at the Examples section of the for help. You create an "iteration variable" x, which iterates through an array with the values [0, 2, 4]. See also the Examples section of the : operator help.
A = [A, A*x];
Concatenate array A with the value of A*x (multiplying an array with a scalar results in an array of the same length, in which each element is multiplied by the given scalar), and re-assign the result to A. See also the help on Concatenating Matrices.
Initially, A = [2].
For x = 0: A = [[2], [2] * 0], i.e. A = [2, 0].
For x = 2: A = [[2, 0], [2, 0] * 2], i.e. A = [2, 0, 4, 0].
For x = 4: A = [[2, 0, 4, 0], [2, 0, 4, 0] * 4], i.e. A = [2, 0, 4, 0, 8, 0, 16, 0].
end
End of for loop.
A
Output content of A by implicitly calling the display function by omitting the semicolon at the end of the line, see here for explanation.
Let's say I have a vector that looks as so (the numbers will always be > 0)...
[1, 2, 1, 4, 1, 2, 4, 3]
I need a vectorized implementation that sums the numbers together and uses the original number as the index to store the number. So if I run it I would get...
% step 1
[1+1+1, 2+2, 3, 4+4]
% step 2
[3, 4, 3, 8]
I have already implemented this using for loops, but I feel like there is a vectorized way to achieve this. I am still quite new at vectorizing functions so any help is appreciated.
This sounds like a job for accumarray:
v = [1, 2, 1, 4, 1, 2, 4, 3];
result = accumarray(v(:), v(:)).'
result =
3 4 3 8
Other approaches:
Using histcounts:
x = [1, 2, 1, 4, 1, 2, 4, 3];
u = unique(x);
result = u.*histcounts(x, [u inf]);
Using bsxfun (may be more memory-intensive):
x = [1, 2, 1, 4, 1, 2, 4, 3];
u = unique(x);
result = u .* sum(bsxfun(#eq, x(:), u(:).' ), 1);
Just came across this problem might be interesting in many applications, for example,
I have a vector A = [2; 5; 10], the values in vector A is sorted and unique.
I have got a matrix (2D or 3D), for example, B = [2, 8, 10; 2, 5, 5; 9, 1, 10];
Want to get a matrix C = [1, 0, 1; 1, 1, 1; 0, 0, 1].
It means if the element in B is also an element of A, we set it to one; otherwise, set the value to zero.
I did this in a for-loop, but for a large 3D matrix, it takes a long time to finish the loop.
Just wondering if there is a smarter method to do this without 'for' loop.
C = zeros(size(B));
for i = 1:size(A,1)
a = A(i);
C(B==a) = 1;
end
This is exactly what ismember does:
A = [2; 5; 10];
B = [2, 8, 10; 2, 5, 5; 9, 1, 10];
C = ismember(B,A)
C =
1 0 1
1 1 1
0 0 1
From the documentation:
ismember(A,B) returns an array containing 1 (true) where the data in A
is found in B. Elsewhere, it returns 0 (false).
I have two vectors, for example
A = [1, 3, 6, 7]
B = [2.0, 5.1, 2.2, 1]
I want to create a vector C and C1 so it would create the missing elements and assign to each of them the average of the corresponding surrounding elements in B.
C = [1, 2, 3, 4, 5, 6, 7]
C1 = [2.0, 3.55, 5.1, 3.65, 3.65, 2.2, 1]
What is the best way to that?
In order to use interp1 you would need
Ci = [1, 2, 3, 4.5, 4.5, 6, 7]
and then
C1 = interp1(A,B,Ci)
However generating that Ci is about as difficult as generating C1. I think in this case your best bet is to loop:
%// Assuming A is sorted
C = min(A):max(A);
C1 = zeros(size(C));
Acounter = 1;
for ii = 1:numel(C)
if C(ii)==A(Acounter)
C1(ii) = B(Acounter);
Acounter = Acounter + 1;
else
C1(ii) = (B(Acounter) + B(Acounter-1))/2;
end
end