how can I count the number of elements on a vector?

Hello!!!!!

If I have a column lets imagine T=[105;105;105;106;106;106;107;107;107;107] how can I count the number of different elements in T? in this case 105 is 3 times, 106 appears 3 times and 107 is 4 times in T.

Thanks!!!

Answer 1

[CS Researcher]

Try this:

a = unique(T);
b = arrayfun(@(x)(x-T),a,'UniformOutput',false);
c = cell2mat(cellfun(@(x)(numel(find(x==0))),b,'UniformOutput',false));

Hope this helps!

[Viridiana Torres]

Super cool, thanks a lot!

[Ahmet Cecen]

This is reimplementing existing functionality in a roundabout way. Will be much slower (and require exponentially more memory) if you have on the order of millions or more numbers. If you just have 10s or 100s, then who cares, it still works.

[Stephen23]

Ahmet Cecen is correct: this is a very bizarre, indirect, and totally inefficient solution. Ahmet's solution is much better, neater, and faster (for 1000 iterations):

 Elapsed time is 1.607303 seconds. % this answer
 Elapsed time is 0.489061 seconds. % Ahmet's answer

Lets take a look at this code in detail. The first line uses unique, which is a good start ( although it ignores the other much more useful outputs):

 a = unique(T);

Then the weirdness starts:

 b = arrayfun(@(x)(x-T),a,'UniformOutput',false);

giving a relatively large cell array of numeric matrices: this is a total waste of memory, as b is going to have an effective size of numel(T)*numel(a). Ouch, this could get very large! Use whos to check the size or variables in memory: for this answer:

 >> whos
  Name       Size            Bytes  Class           
  T         10x1                80  double              
  a          3x1                24  double              
  b          3x1               420  cell       <- ouch!    
  c          3x1                24  double

While it might not cause a problem for small input vectors, this will be a total waste of memory for larger inputs, as it will expand quite quickly.

At this point the numeric matrices have value zero replacing the values of interest.

This is then followed by a slow cellfun call on this large intermediate variable b:

 c = cell2mat(cellfun(@(x)(numel(find(x==0))),b,'UniformOutput',false));

which checks where the zeros are in the numeric matrices inside b. Even here things are indirect:

 numel(find(x==0))

should really be

 nnz(x==0)

which would be much faster and simpler. But then, as Ahmet correctly pointed out, the concept is very indirect anyway: why not simply sum the indices in the first arrayfun anyway? Why bother converting the points of interest to zero, storing them in a huge matrix, and then checking counting those zeros by using find ?

Here is perhaps what the author really intended to write:

 z = arrayfun(@(x)nnz(x==T),unique(T));

which takes half the time than the authors answer (although still not as fast as Ahmet's), and simply counts how many values of T match each unique value using one arrayfun call.

Please read Ahmet's much better answer!

Answer 2

[Ahmet Cecen]

 [C,ia,ic] = unique(T);
 c = hist(ic,1:max(ic));
 CountArray = [T(ia) c'];