Grouping unique values in a vector and putting them in a matrix

Question

I have a vector that contains repeated numbers like so:

[1 1 1 1 5 5 5 5 93 93 93 6 6 6 6 6 6] and so on. What I want to do is to group the similar values (1's, 5's, etc.). I would like to have each of the unique values in a row of a big matrix, like:

[ 1  1  1  1  0  0

  5  5  5  5  0  0

 93 93 93  0  0  0

  6  6  6  6  6  6]

I don't know the maximum number of occurrence of a unique value, so it is ok to create an initial zero matrix with a large number of columns (that I am sure is bigger than the maximum number of occurrence of a unique value). Any help is highly appreciated.

Answer 1

How about this?

A = [1 1 1 1 5 5 5 5 93 93 93 6 6 6 6 6 6];
[a,b] = hist(A,unique(A))

f = @(x) [ones(1,a(x)) zeros(1,max(a)-a(x))]

X = cell2mat( arrayfun(@(x) {f(x)*b(x)}, 1:numel(b) )' )

returns:

X =

     1     1     1     1     0     0
     5     5     5     5     0     0
     6     6     6     6     6     6
    93    93    93     0     0     0

I know the order is different, is that important? Otherwise:

n = hist(A,1:max(A))           % counts how often every number apperas
[a b] = unique(A,'stable')     % gets all unique numbers
n = n(a)                       % correlates count and numbers

f = @(x) [ones(1,n(x)) zeros(1,max(n)-n(x))]     % creates the logical index 
                                                 % vector for every single row

X = cell2mat( arrayfun(@(x) {f(x)*b(x)}, 1:numel(b) )' )  %fills the rows

---

or inspired by Luis Mendo's Answer a little shorter:

n = hist(A,1:max(A));
a = unique(A,'stable')
n = n(a)
Y = repmat(a',1,max(n)).*bsxfun(@le, cumsum(ones(max(n),numel(n))), n)'

returns:

X =

     1     1     1     1     0     0
     5     5     5     5     0     0
    93    93    93     0     0     0
     6     6     6     6     6     6

---

For the bored people out there, there is a one-line solution:

X = getfield(cell2mat(arrayfun(@(x,y) padarray( padarray(x,[0 y],'replicate','pre'),[0 max(hist(A,1:max(A)))-y],'post'),1:max(A),hist(A,1:max(A)),'uni',0)'),{unique(A,'stable'),2:1+max(hist(A,1:max(A)))})

Or an almost lovely two-liner:

n = hist(A,1:max(A))
X = getfield(cell2mat(arrayfun(@(x,y) padarray( padarray(x,[0 y],'replicate',...
    'pre'),[0 max(n)-y],'post'),1:max(A),n,'uni',0)'),...
    {unique(A,'stable'),2:1+max(n)})

just for fun ;)