how to compute the mean value of non-zero elements in each row of a sparse matrix

I built the following sparse matrix:

o=[1 1 1 3];
C = sparse(o',1:length(o),ones(length(o),1),4,4);
C =

   (1,1)        1
   (1,2)        1
   (1,3)        1
   (3,4)        1

I would like to write a function in order to compute the mean value of non-zero elements in each row. I was wondering how it should be done because the usual built-in mean function of matlab does not work.

Thanks.

Answer 1

[Matt J]

rowmeans = sum(C,2)./sum(logical(C),2);

[Adam Danz]

+1 neat, tidy & efficient

Answer 2

[David Hill]

a=C;
a(a==0)=nan;
mean(a,2,'omitnan');

Answer 3

[Adam Danz]

Assuming you want to preserve row-number in the case were entire rows are 0s,

mu = zeros(size(C,1),1); 
mu(any(C~=0,2)) = mean(C(C~=0),2);

If you don't want to preserve row number,

mu = mean(C(C~=0),2);

Demo with a different sparse matrix,

i = [6 6 6 5 10 10 9 9]';
j = [1 1 1 2 3 3 10 10]';
v = [100 202 173 305 410 550 323 121]';
C = sparse(i,j,v) %note: row numbers are not sorted

C = 
   (6,1)      475
   (5,2)      305
  (10,3)      960
   (9,10)     444

mu = zeros(size(C,1),1); 
mu(any(C~=0,2)) = mean(C(C~=0),2)

mu = 10×1

0 0 0 0 475 305 0 0 960 444