I have a matrix A
1 1 0 0
0 1 0 0
1 0 0 1
0 0 1 0
0 0 0 0
0 1 1 1
1 1 0 0
1 0 0 0
0 0 0 1
if d=[1 2 3],
for i=2:length(d)
d(i) = d(i) + d(i-1); %d=[1 3 6]
end
then using,
d = [0, ceil((d./d(end))*length(x))]; %d=[2 5 9]
disp('The resultant split up is:')
for i=2:length(d)
disp(x((d(i-1)+1):d(i)));
end
the output has to be,
The split up is:
1st split up->
1 1 0 0 %first 2 rows in matrix A
0 1 0 0
2nd split up->
1 0 0 1 %next 3 rows
0 0 1 0
0 0 0 0
3rd split up->
0 1 1 1 %next 4 rows
1 1 0 0
1 0 0 0
0 0 0 1
If I understand your question correctly, then mat2cell is what you need: Here's a short example:
%// Bits and hops array
bits = '10001100';
hops = [3 2 3];
A = mat2cell(bits(:)', 1, hops)
The result is a cell array of strings:
A =
'100' '01' '100'
This approach works with number arrays as well (e.g bits = [1 0 0 0 1 1 0 0]).
Related
I've been struggling with this for a bit now. I have a small matrix s for example and a bigger matrix B as shown below.
B =
0 0 0 0 0 0 1 1
1 1 0 0 1 0 1 1
1 1 0 1 0 0 1 1
1 1 1 0 0 0 1 0
0 0 1 1 1 0 0 1
0 0 0 1 1 1 1 1
1 1 1 0 0 0 1 0
0 1 1 0 1 1 0 0
s =
1 1
1 1
What I want to do is iterate through B with s and compare the values. If all the values in s equal the values in B (the small section of B), then the answer is 1, if not then 0.
The 1's and 0's would be placed in a matrix as well.
This is what I've done so far but unfortunately, it doesn't iterate step by step and doesn't create a matrix either.
s = ones(2,2)
B = randi([0 1],8,8)
f = zeros(size(B))
[M,N]=size(B); % the larger array
[m,n]=size(s); % and the smaller...
for i=1:M/m-(m-1)
for j=1:N/n-(n-1)
if all(s==B(i:i+m-1,j:j+n-1))
disp("1")
else
disp("0")
end
end
end
Any help would be appreciated!
The following code works on the examples you supplied, I haven't tested it on anything else, and it will not work if the dimensions of the smaller matrix are not factors of the dimensions of the larger matrix, but you didn't indicate that it needed to do that in your description.
B =[0 0 0 0 0 0 1 1
1 1 0 0 1 0 1 1
1 1 0 1 0 0 1 1
1 1 1 0 0 0 1 0
0 0 1 1 1 0 0 1
0 0 0 1 1 1 1 1
1 1 1 0 0 0 1 0
0 1 1 0 1 1 0 0];
S =[1 1
1 1];
%check if array meets size requirements
numRowB = size(B,1);
numRowS = size(S,1);
numColB = size(B,2);
numColS = size(S,2);
%get loop multiples
incRows = numRowB/numRowS;
incCols = numColB/numColS;
%create output array
result = zeros(incRows, incCols);
%create rows and colums indices
rowsPull = 1:numRowS:numRowB;
colsPull = 1:numColS:numColB;
%iterate
for i= 1:incRows
for j= 1:incCols
result(i,j) = isequal(B(rowsPull(i):rowsPull(i)+numRowS-1, colsPull(j):colsPull(j)+numColS-1),S);
end
end
%print the resulting array
disp(result)
I need to effectively eliminate consecutive regions in vector "a" or better in rows/columns of matrix "A" with length of separate ones regions greater than positive integer N <= length(A):
See following example:
N = 2 % separate consecutive regions with length > 2 are zeroed
a = [0 1 1 0 0 1 1 1 0 0 1 1 1 1 0 1]
a_elim = [0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 1]
or 2D case:
N = 2
A = [1 0 1 …
1 1 0 …
1 1 0 …
0 0 1 …
1 1 1]
% elimination over columns
A_elim= 0 0 1
0 1 0
0 1 0
0 0 1
1 1 1
% elimination over rows
A_elim= 1 0 1
1 1 0
1 1 0
0 0 1
0 0 0
I am looking for effective vectorized MATLAB function performing this task for size(A) ~ [100000, 1000] (over columns case).
You can use a convolution:
For the 1D case:
N = 2 %tolerance
A = [0 1 1 0 0 1 1 1 0 0 1 1 1 1 0 1]
ind = conv(A,ones(N+1,1),'same');
%ind = 1 2 2 1 1 2 3 2 1 1 2 3 3 2 2 1
%A = 0 1 1 0 0 1 1 1 0 0 1 1 1 1 0 1
ind = conv(ind>N,ones(N+1,1),'same')>0;
%ind = 0 0 0 0 0 1 1 1 0 0 1 1 1 1 0 0
%A = 0 1 1 0 0 1 1 1 0 0 1 1 1 1 0 1
A(ind) = 0
if N is odd you need an extra step:
ind = conv(A,ones(N+1,1),'same');
ind(find(ind==N+1)+1) = N+1 %the extra step
ind = conv(ind>N,ones(N+1,1),'same')>0;
Generalization for nD dimension:
N = 3 %tolerance
A = round(rand(5,5,5));
for ii = 1:ndims(A)
conv_vec = permute(ones(N+1,1),circshift([1:ndims(A)],ii-1,2))
ind = convn(A,conv_vec,'same')
if mod(N,2) == 1
ind(find(ind==N+1)+1) = N+1
end
ind = convn(ind>N,conv_vec,'same')>0
X = A;
X(ind) = 0
end
I'm looking for a way to generate the spans of a given vector in MATLAB.
For example:
if a = [ 0 1 0 1] I need all vectors of the form [0 x 0 y], 1 <= x <= max1, 1 <= y <= max2,.
or if
a = [ 0 1 0 1 1 0] I need all vectors of the form [0 x 0 y z 0], 1 <= x <= max1, 1 <= y <= max2, 1<= z <= max3.
Note that the vector can have a variable number of 1's.
My first impression is that I would need a variable number of for loops, though I don't know if that is doable in MATLAB. Also any other ideas are welcome!
You don't need multiple for loops for this. The code below generates all required vectors as rows of a tall matrix. It actually creates the columns of the matrix one at a time. Each column will have numbers 1:m(i) arranged in the pattern where
each term repeats the number of times equal to the product of all m-numbers after m(i)
the whole pattern repeats the number of times equal to the product of all m-numbers before m(i)
This is what repmat(kron(1:m(i),ones(1,after)),1,before)' does. (Starting with R2015a you can use repelem to simplify this by replacing the kron command, but I don't have that release yet.)
a = [0 1 0 1 1 0];
m = [2 4 3]; // the numbers max1, max2, max3
A = zeros(prod(m), length(a));
i = 1; // runs through elements of m
for j=1:length(a) // runs through elements of a
if (a(j)>0)
before = prod(m(1:i-1));
after = prod(m(i+1:end));
A(:,j) = repmat(kron(1:m(i),ones(1,after)),1,before)';
i = i+1;
end
end
Output:
0 1 0 1 1 0
0 1 0 1 2 0
0 1 0 1 3 0
0 1 0 2 1 0
0 1 0 2 2 0
0 1 0 2 3 0
0 1 0 3 1 0
0 1 0 3 2 0
0 1 0 3 3 0
0 1 0 4 1 0
0 1 0 4 2 0
0 1 0 4 3 0
0 2 0 1 1 0
0 2 0 1 2 0
0 2 0 1 3 0
0 2 0 2 1 0
0 2 0 2 2 0
0 2 0 2 3 0
0 2 0 3 1 0
0 2 0 3 2 0
0 2 0 3 3 0
0 2 0 4 1 0
0 2 0 4 2 0
0 2 0 4 3 0
Let's have a M = [10 x 4 x 12] matrix. As example I take the M(:,:,4):
val(:,:,4) =
0 0 1 0
0 1 1 1
0 0 0 1
1 1 1 1
1 1 0 1
0 1 1 1
1 1 1 1
1 1 1 1
0 0 1 1
0 0 1 1
How can I obtain this:
val(:,:,4) =
0 0 3 0
0 2 2 2
0 0 0 4
1 1 1 1
1 1 0 1
0 2 2 2
1 1 1 1
1 1 1 1
0 0 3 3
0 0 3 3
If I have 1 in the first column then all the subsequent 1's should be 1.
If I have 0 in the first column but 1 in the second, all the subsequent 1's should be 2.
If I have 0 in the first and second column but 1 in the third then all the subsequent 1's should be 3.
If I have 0 in the first 3 columns but 1 in the forth then this one should be four.
Note: The logical matrix M is constructed:
Tab = [reshape(Avg_1step.',10,1,[]) reshape(Avg_2step.',10,1,[]) ...
reshape(Avg_4step.',10,1,[]) reshape(Avg_6step.',10,1,[])];
M = Tab>=repmat([20 40 60 80],10,1,size(Tab,3));
This is a very simple approach that works for both 2D and 3D matrices.
%// Find the column index of the first element in each "slice".
[~, idx] = max(val,[],2);
%// Multiply the column index with each row of the initial matrix
bsxfun(#times, val, idx);
This could be one approach -
%// Concatenate input array along dim3 to create a 2D array for easy work ahead
M2d = reshape(permute(M,[1 3 2]),size(M,1)*size(M,3),[]);
%// Find matches for each case, index into each matching row and
%// elementwise multiply all elements with the corresponding multiplying
%// factor of 2 or 3 or 4 and thus obtain the desired output but as 2D array
%// NOTE: Case 1 would not change any value, so it was skipped.
case2m = all(bsxfun(#eq,M2d(:,1:2),[0 1]),2);
M2d(case2m,:) = bsxfun(#times,M2d(case2m,:),2);
case3m = all(bsxfun(#eq,M2d(:,1:3),[0 0 1]),2);
M2d(case3m,:) = bsxfun(#times,M2d(case3m,:),3);
case4m = all(bsxfun(#eq,M2d(:,1:4),[0 0 0 1]),2);
M2d(case4m,:) = bsxfun(#times,M2d(case4m,:),4);
%// Cut the 2D array thus obtained at every size(a,1) to give us back a 3D
%// array version of the expected values
Mout = permute(reshape(M2d,size(M,1),size(M,3),[]),[1 3 2])
Code run with a random 6 x 4 x 2 sized input array -
M(:,:,1) =
1 1 0 1
1 0 1 1
1 0 0 1
0 0 1 1
1 0 0 0
1 0 1 1
M(:,:,2) =
0 1 0 1
1 1 0 0
1 1 0 0
0 0 1 1
0 0 0 1
0 0 1 0
Mout(:,:,1) =
1 1 0 1
1 0 1 1
1 0 0 1
0 0 3 3
1 0 0 0
1 0 1 1
Mout(:,:,2) =
0 2 0 2
1 1 0 0
1 1 0 0
0 0 3 3
0 0 0 4
0 0 3 0
I have matrix A
A= [0 0 2 2 2 2 0 0 1 1 1 0 3 3;
2 2 2 2 0 0 1 1 1 0 0 3 3 0;
As you can see, there are consecutive numbers in it; notice for example the 2 2 2 2 on the first and second row.
For each number occuring in this matrix (or at least for every number from 1 to the maximum number in my matrix) I want to have an output matrix that indicates sequences of this number and this number only in the original matrix.
So for example, for 1: there are three consecutive numbers on the first row and three on the second row: I want to indicate this in the first output matrix as follows:
Matrix 1 = [ 0 0 0 0 0 0 0 0 1 2 3 0 0 0;
0 0 0 0 0 0 0 1 2 3 0 0 0 0]
Same for number 2:
Matrix 2 = [ 0 0 1 2 3 4 0 0 0 0 0 0 0 0;
1 2 3 4 0 0 0 0 0 0 0 0 0 0]
and 3:
Matrix 3 = [ 0 0 0 0 0 0 0 0 0 0 0 0 1 2;
0 0 0 0 0 0 0 0 0 0 0 1 2 0]
As you can see, each output matrix shows counting forward for the consecutive occurrences of a number.
So in this case, I have 3 output matrices because matrix A has 3 as the biggest value there.
You can try this:
A= [0 0 2 2 2 2 0 0 1 1 1 0 3 3;
2 2 2 2 0 0 1 1 1 0 0 3 3 0];
result = arrayfun(#(b) (A == b).*cumsum((A == b),2),nonzeros(unique(A)), 'UniformOutput', false);
For this example, there will be 3 submatrices in the variable result.
result =
[2x14 double]
[2x14 double]
[2x14 double]
To access them, use the following syntax:
result{1}
result{2}
result{3}
Then you get:
ans =
0 0 0 0 0 0 0 0 1 2 3 0 0 0
0 0 0 0 0 0 1 2 3 0 0 0 0 0
ans =
0 0 1 2 3 4 0 0 0 0 0 0 0 0
1 2 3 4 0 0 0 0 0 0 0 0 0 0
ans =
0 0 0 0 0 0 0 0 0 0 0 0 1 2
0 0 0 0 0 0 0 0 0 0 0 1 2 0
~edit~
If, as asked in the comments, A is a 3D matrix, this code works just the same, but the structure of result is a bit different:
result =
[2x14x2 double]
[2x14x2 double]
[2x14x2 double]
To access these matrices, use for instance
result{1}(:,:,1) % for the results of comparing A(:,:,1) with value 1
result{1}(:,:,2) % for the results of comparing A(:,:,2) with value 1
Edited because the question changed
This is nowhere near to optimal but will do what you want
V = 1;
C = A' == V;
D = cumsum(C).*C
E = D'
now E will be Matrix1 in your example. Change V to 2 and 3 to obtain Matrix2 and Matrix3. If you have something like
A = [2 2 2 0 0 0 0 0 2 2 2]
then you will get
[1 2 3 0 0 0 0 0 4 5 6]
so it may not be what you want. It is not clear from your question if this is the case or not, but if not tell me and I will delete the answer
This is a loop-based solution to get you started:
A = [
0 0 2 2 2 2 0 0 1 1 1 0 3 3;
2 2 2 2 0 0 1 1 1 0 0 3 3 0
];
mx = max(A(:));
AA = cell(mx,1);
for num=1:mx
AA{num} = zeros(size(A));
for r=1:size(A,1)
idx = ( A(r,:) == num );
AA{num}(r,idx) = sum(idx):-1:1;
end
end
The result:
>> AA{1}
ans =
0 0 0 0 0 0 0 0 3 2 1 0 0 0
0 0 0 0 0 0 3 2 1 0 0 0 0 0
>> AA{2}
ans =
0 0 4 3 2 1 0 0 0 0 0 0 0 0
4 3 2 1 0 0 0 0 0 0 0 0 0 0
>> AA{3}
ans =
0 0 0 0 0 0 0 0 0 0 0 0 2 1
0 0 0 0 0 0 0 0 0 0 0 2 1 0
EDIT:
Updated code to work on matrix with three dimensions:
A = zeros(2,7,2);
A(:,:,1) = [2 2 2 0 0 1 1 ; 0 0 2 2 2 1 1];
A(:,:,2) = [1 1 2 2 2 0 0 ; 0 1 1 0 2 2 2];
mx = max(A(:));
AA = cell(mx,1);
for num=1:mx
AA{num} = zeros(size(A));
for p=1:size(A,3)
for r=1:size(A,1)
idx = ( A(r,:,p) == num );
AA{num}(r,idx,p) = 1:sum(idx);
end
end
end
The result:
%# contains consecutive numbers corresponding to number 1 in all slices
>> AA{1}
ans(:,:,1) =
0 0 0 0 0 1 2
0 0 0 0 0 1 2
ans(:,:,2) =
1 2 0 0 0 0 0
0 1 2 0 0 0 0
%# contains consecutive numbers corresponding to number 2 in all slices
>> AA{2}
ans(:,:,1) =
1 2 3 0 0 0 0
0 0 1 2 3 0 0
ans(:,:,2) =
0 0 1 2 3 0 0
0 0 0 0 1 2 3