I want to count the number of different numbers in the matrix other than -1. For example the different numbers in the following matrix are 6 as the different numbers are 8 9 3 5 2 1
-1 -1 8 9
3 5 -1 3
2 3 3 1
How can I do that with MATLAB ?
I. Using unique
Use unique with its 'stable' option to keep the order -
A1 = reshape(A.',1,[]) %// A is your input matrix
out = unique(A1(A1~=-1),'stable') %// out is your desired output
Output -
out =
8 9 3 5 2 1
If you don't care about keeping the order of the unique numbers, you can use unique without the 'stable' option -
A1 = unique(A)
out = A1(A1~=-1)
which can be converted to a dense one-liner if you are into those -
out = nonzeros(unique(A).*(unique(A)~=-1))
II. Using setdiff
Use setdiff with 'stable' option to keep the order -
A1 = reshape(A.',1,[]) %// A is your input matrix
out = setdiff(A1,-1,'stable') %// out is your desired output
One-liner using default version of setdiff, if you don't care about the order -
out = setdiff(A,-1)
Finally, you can get the count of those unique numbers with numel(out).
Related
idx=randperm(5)
idx=[1,3,4,2,5]
I know this works like that but I'm curious about is there anyway to get something like this.
idx=[1,3,4,2,5,5,3,2,4,1]
adding one set of array after one array
Is there any way to make that?
One vectorized way would be to create a random array of size (m,n), sort it along each row and get the argsort indices. Each row of those indices would represent a group of randperm values. Here, m would be the number of groups needed and n being the number of elements in each group.
Thus, the implementation would look something like this -
[~,idx] = sort(rand(2,5),2);
out = reshape(idx.',1,[])
Sample run -
>> [~,idx] = sort(rand(2,5),2);
>> idx
idx =
5 1 3 2 4
4 3 2 5 1
>> out = reshape(idx.',1,[])
out =
5 1 3 2 4 4 3 2 5 1
You can use the modulo operation:
n = 5 %maximum value
r = 2 %each element are repeated r times.
res = mod(randperm(r*n),n)+1
I have a cell in Matlab A of dimension mx1, e.g. m=11
A={1 2 2 4 5 5 6 3 1 1 2}
Let D be the vector of unique elements in A, i.e.
D=unique(A,'stable')
that gives
D={1 2 4 5 6 3}
I want to find C that gives the number of repetitions of each element in D, i.e.
C={3 3 1 2 1 1}
I tried
count=histc(A,D);
but it tells me
"Error using histc
First Input must be a real non-sparse numeric array."
If I try to convert A and C in matrices using cell2mat it gives me
"Error using cat
Dimensions of matrices being concatenated are not consistent."
Any idea?
Matlab recommended histcount instead of histc
a = cell2mat(A) ;
count=histcounts(a, max(a) - min(a))
I've two matrix a and b and I'd like to combine the rows in a way that in the first row I got no duplicate value and in the second value, columns in a and b which have the same row value get the maximum value in new matrix. i.e.
a = 1 2 3
8 2 5
b = 1 2 5 7
2 4 6 1
Desired output
c = 1 2 3 5 7
8 4 5 6 1
Any help is welcomed,please.( the case for accumulation is asked here)
Accumarray accepts functions both anonymous as well as built-in functions. It uses sum function as default. But you could change this to any in-built or anonymous functions like this:
In this case you could use max function.
in = horzcat(a,b).';
[uVal,~,idx] = unique(in(:,1));
out = [uVal,accumarray(idx,in(:,2),[],#max)].'
Based upon your previous question and looking at the help file for accumarray, which has this exact example.
[ii, ~, kk] = unique([a(1,:) b(1,:)]);
result = [ ii; accumarray(kk(:), [a(2,:) b(2,:)], [], #max).'];
The only difference is the anonymous function.
I have a 250000x2-matrix in matlab, where in the first row I have a degree (int, 0-360°), and in the second a float-value corresponding to this value. My target is to count each occurence of a degree-value-pair (e.g. a row), and write the result in a nx3-matrix. n corresponds here with the number unique rows.
Thus my first step was to get all unique values (using unique(M, 'rows')) which works. But now I want to count all unique values. This was done by the following approach:
uniqu_val = unique(values, 'rows');
instance = histcounts(values(:), uniqu_val);
Here I have to enter a vector as second element, and not a matrix (uniqu_val is a nx2-dim-matrix). But I want to get the number of occurence for each unique row, therefore I can not use only one column of the matrix uniqu_val. In short: I want to use histcounts not only for a 1D-matrix as edge-value, but for a 2D-matrix. How can I solve this problem?
You can use the third output from unique and then use histcounts like so -
%// Find the unique rows and keep the order with 'stable' option
[uniq_val,~,row_labels] = unique(values, 'rows','stable')
%// Find the counts/instances
instances = histcounts(row_labels, max(row_labels))
%// OR with HISTC: instances = histc(row_labels, 1:max(row_labels))
%// Output the unique rows alongwith the counts
out = [uniq_val instances(:)]
Sample run -
>> values
values =
2 1
3 1
2 3
3 3
1 2
3 3
1 3
3 1
3 2
1 2
>> out
out =
2 1 1
3 1 2
2 3 1
3 3 2
1 2 2
1 3 1
3 2 1
I have two matrices, 22007x3 and 352x2. The first column in each is an index, most (but not all) of which are shared (i.e. x1 contains indices that aren't in x2).
I would like to combine the two matrices into a 22007x4 matrix, such that column 4 is filled in with the values that correspond to particular indices in both original matrices.
For example:
x1 =
1 1 5
1 2 4
1 3 5
2 1 1
2 2 1
2 3 2
x2 =
1 15.5
2 -5.6
becomes
x3 =
1 1 5 15.5
1 2 4 15.5
1 3 5 15.5
2 1 1 -5.6
2 2 1 -5.6
2 3 2 -5.6
I've tried something along the lines of
x3(1:numel(x1),1:3)=x1;
x3(1:numel(x2(:,2)),4)=x2(:,2);
but firstly I get the error
??? Subscripted assignment dimension mismatch.
and then I can't figure out I would fill the rest of it.
An important point is that there are not necessarily an equal number of rows per index in my data.
How might I make this work?
Taking Amro's answer from here
[~, loc] = ismember(x1(:,1), x2(:,1));
ismember's second argument returns the location in x2 where each element of x1 can be found (or 0 if it can't)
a = x2(loc(loc > 0), 2);
get the relevant values using these row indices but excluding the zeros, hence the loc > 0 mask. You have to exclude these as 1, they are not in x2 and 2 you can't index with 0.
Make a new column of default values to stick on the end of x1. I think NaN() is probably better but zeros() is also fine maybe
newCol = NaN(size(x1,1),1)
Now use logical indexing to get the locations of the non zero elements and put a in those locations
newCol(loc > 0) = a
Finnaly stick it on the end
x3 = [x1, newCol]