--- a/scripts/sparse/spstats.m
+++ b/scripts/sparse/spstats.m
@@ -21,12 +21,12 @@
 ## @deftypefnx {Function File} {[@var{count}, @var{mean}, @var{var}] =} spstats (@var{S}, @var{j})
 ## Return the stats for the non-zero elements of the sparse matrix @var{S}.
 ## @var{count} is the number of non-zeros in each column, @var{mean}
-## is the mean of the non-zeros in each column, and @var{var} is the  
+## is the mean of the non-zeros in each column, and @var{var} is the
 ## variance of the non-zeros in each column.
 ##
 ## Called with two input arguments, if @var{S} is the data and @var{j}
-## is the bin number for the data, compute the stats for each bin.  In 
-## this case, bins can contain data values of zero, whereas with 
+## is the bin number for the data, compute the stats for each bin.  In
+## this case, bins can contain data values of zero, whereas with
 ## @code{spstats (@var{S})} the zeros may disappear.
 ## @end deftypefn
 
@@ -39,19 +39,19 @@
   if (nargin == 1)
     [i, j, v] = find (S);
   else
-    v = S;    
+    v = S;
     i = 1:length (v);
     S = sparse (i, j, v);
-  endif 
+  endif
   [n, m] = size (S);
 
   count = sum (sparse (i, j, 1, n, m));
-  if (nargout > 1) 
-    mean = sum (S) ./ count; 
+  if (nargout > 1)
+    mean = sum (S) ./ count;
   endif
-  if (nargout > 2) 
+  if (nargout > 2)
     ## FIXME Variance with count = 0 or 1?
-    diff = S - sparse (i, j, mean(j), n, m); 
+    diff = S - sparse (i, j, mean(j), n, m);
     var = sum (diff .* diff) ./ (count - 1);
   endif