I would like to split a matrix which has two columns into an array. Everything I have tested so far splits it by column, e.g.
mat <- rbind(c(5, 9),
c(3, 7),
c(2, 1),
c(4, 3),
c(8, 6))
ind <- gl(1,10)
>split(mat, ind)
[1] 5 3 2 4 8 9 7 1 3 6
But the desired output is:
5 9 3 7 2 1 4 3 8 6
There must be a super easy neat trick to do this. Any pointers are highly appreciated, thanks!
You can just use as.vector:
## what you presently have
as.vector(mat)
[1] 5 3 2 4 8 9 7 1 3 6
## What you are looking for
as.vector(t(mat))
# [1] 5 9 3 7 2 1 4 3 8 6
Related
I want to fuse two arrays without using more memory, it's posible?, for instance:
a=[1 2 3
4 5 6
7 8 9]
b=[11 12 13
14 15 16
17 18 19]
I need to get the array:
c=[a b]
but using the same memory as a and b, i.e, any change in a or b must be reflected in c.
There's also another package CatViews.jl
julia> x = CatView(a, b); # no copying!!!
julia> reshape(x, size(a, 1), :)
3×6 reshape(::CatView{2,Int64}, 3, 6) with eltype Int64:
1 2 3 11 12 13
4 5 6 14 15 16
7 8 9 17 18 19
If you start in reverse, define C first
julia> C = rand(0:9, 3, 6)
3×6 Array{Int64,2}:
3 2 4 4 9 8
8 8 6 5 5 9
0 7 5 8 7 5
then have A and B be views of C
julia> A = #view C[:, 1:3]
3×3 view(::Array{Int64,2}, :, 1:3) with eltype Int64:
3 2 4
8 8 6
0 7 5
julia> B = #view C[:, 4:6]
3×3 view(::Array{Int64,2}, :, 4:6) with eltype Int64:
4 9 8
5 5 9
8 7 5
then it works.
julia> A[2,2] = -1
-1
julia> C
3×6 Array{Int64,2}:
3 2 4 4 9 8
8 -1 6 5 5 9
0 7 5 8 7 5
I have a matrix like following,
A =
1 2 3
4 5 6
7 8 9
10 11 12
4 5 6
7 8 9
4 5 6
1 2 3
I could extract unique rows in this matrix using command A_unique = unique(A,'rows') and result as follows
A_unique =
1 2 3
4 5 6
7 8 9
10 11 12
I need to find number of times each rows exists in the main matrix A
Some thing like following
A_unique_count =
2
3
2
1
How can I find count of unique rows? Can anyone help? Thanks in Advance
Manu
The third output of unique gives you the index of the unique row in the original array. You can use this with accumarray to count the number of occurrences.
For example:
A = [1 2 3
4 5 6
7 8 9
10 11 12
4 5 6
7 8 9
4 5 6
1 2 3];
[uniquerow, ~, rowidx] = unique(A, 'rows');
noccurrences = accumarray(rowidx, 1)
Returns:
noccurrences =
2
3
2
1
As expected
I would recommend #excaza's approach. But just for variety:
A_unique_count = diff([0; find([any(diff(sortrows(A), [], 1), 2); 1])]);
Let c be 2D array, and x and y be 1D arrays of the same length (for instance, let's have x=1:7 and y=3:9).
I need to find a way to pass in arguments from x and y in the way I will describe below.
If I put simply c(x,y) it will give a 7 by 7 matrix. I don't want that.
Instead, I want to pass in the diagonal of the [x y] matrix: ((x(1), y(1)), (x(2), y(2))...(x(7), y(7)). Is there a way to do this without a for loop or any iterative statement?
You are looking for sub2ind function
res = c( sub2ind(size(c), x, y ) )
There's an easier way. If you're looking for a diagonal, use diag. If you have a matrix c:
c =
5 8 4 2 9 1 6 1 1
9 8 7 5 9 3 2 7 5
2 3 9 10 2 1 4 2 2
3 2 9 2 4 4 7 2 4
3 9 10 8 7 5 2 1 8
5 6 3 7 6 1 10 5 2
6 1 7 3 10 8 2 4 2
you can find the main diagonal by using diag with no extra arguments:
>> diag(c)
ans =
5
8
9
2
7
1
2
The second argument, though, indicates which diagonal you want as an offset from the main diagonal. So the default diagonal is equal to 0. If you want the diagonal starting at c(1,3), that's 2 above the main diagonal, so
>> diag(c,2)
ans =
4
5
2
4
2
5
2
Similarly, if you want the diagonal starting at c(4,1), the offset is -3:
>> diag(c,-3)
ans =
3
9
3
3
Hi may I know how i can perform this using matlab?
I tried nchoosek but only works on 1 type of combination. I would like to output all together in array
Let S={a,b,c,d,e}
I would like to get combinations as such which start from 3 combinations:
the 3-combinations : {a,b,c} , {a,b,d} , {a,b,e} , {a,c,d} , {a,c,e} , {a,d,e}
the 4-combinations : {a,b,c,d} , {a,b,c,e} , {a,c,d,e}
the 5-combinations : {a,b,c,d,e}
So the output would be like this:
{a,b,c} {a,b,d} {a,b,e} {a,c,d} {a,c,e} {a,d,e}{a,b,c,d} {a,b,c,e} {a,c,d,e}{a,b,c,d,e}
Thanks
You can use a loop there or arrayfun which is just a compact way to express such a loopy approach and not a vectorized approach -
combs = arrayfun(#(x) nchoosek(S,x),3:numel(S),'Uniform',0)
The output would be a cell array with each cell representing values for each combination. So, when you run the code, you would get -
>> combs{1}
ans =
2 7 4
2 7 1
2 7 9
2 4 1
2 4 9
2 1 9
7 4 1
7 4 9
7 1 9
4 1 9
which would be your 3-combinations set.
>> combs{2}
ans =
2 7 4 1
2 7 4 9
2 7 1 9
2 4 1 9
7 4 1 9
would be your 4-combinations set and so on.
Suppose I have a 2D array called A. I want to create a 3D array called B, whose "pages" are select columns of a stencil moving across A, column-by-column. For example, the first page of B might be the 1st, 3rd, and 5th columns of A. Then the second page would be the 2nd, 4th, and 6th columns of A, etc.
Anyone have an efficient way of doing this is MATLAB?
Thanks!
I am guessing you are looking for this -
%%// Given 2D array
A = randi(10,4,12)
t1 = reshape(A,size(A,1)*2,[]);
t2 = reshape(t1',size(A,2)/2,[],2); %%//'
B = permute(t2,[2 1 3]) %%// Output 3D array
Output -
A =
5 10 3 5 6 8 4 3 8 10 8 7
10 8 3 7 6 10 9 2 7 8 8 5
10 4 7 8 6 4 5 4 1 1 3 7
7 7 6 6 1 10 5 8 9 4 3 3
B(:,:,1) =
5 3 6 4 8 8
10 3 6 9 7 8
10 7 6 5 1 3
7 6 1 5 9 3
B(:,:,2) =
10 5 8 3 10 7
8 7 10 2 8 5
4 8 4 4 1 7
7 6 10 8 4 3
Of course, there is an alternative straight-forward approach for this special case -
B(:,:,1)=A(:,1:2:end);
B(:,:,2)=A(:,2:2:end);