--- a/inst/lscorrcoeff.m
+++ b/inst/lscorrcoeff.m
@@ -31,47 +31,51 @@
 ## 
 ## @end deftypefn
 
-## Demo with sin, cos as Nir suggested.
-%!demo
-%! x = 1:10;
-%! y = sin(x);
-%! z = cos(x);
-%! a = lscorrcoeff(x,y,x,z,0.5,0.9)
-%! ## This generates the correlation coefficient at time 0.5 and circular freq. 0.9
-
-
 ## nucorrcoeff, computes a coefficient of the wavelet correlation of two time series
 
-function coeff = lscorrcoeff(x1, y1, x2, y2, t, o, wgt = @cubicwgt, wgtrad = 1)
+function coeff = lscorrcoeff (x1, y1, x2, y2, t, o, wgt = @cubicwgt, wgtrad = 1)
+
   so = 0.05 * o;
-  ## This code can only, as of currently, work on vectors; I haven't figured out a way to make it work on a matrix.
-  if( ( ndims(x1) == 2 ) && ! ( rows(x1) == 1 ) )
-    x1 = reshape(x1,1,length(x1));
-    y1 = reshape(y1,1,length(y1));
-    x2 = reshape(x2,1,length(x2));
-    y2 = reshape(y2,1,length(y2));
+
+  ## This code can only, as of currently, work on vectors; 
+  ## I haven't figured out a way to make it work on a matrix.
+  if ((ndims (x1) == 2) && !(rows (x1) == 1))
+    x1 = reshape (x1, 1, length (x1));
+    y1 = reshape (y1, 1, length (y1));
+    x2 = reshape (x2, 1, length (x2));
+    y2 = reshape (y2, 1, length (y2));
   endif
-  ## The first solution that comes to mind is admittedly slightly ugly and has a data footprint of O(2n)
-  ## but it is vectorised.
-  mask = find( ( abs( x1 - t ) * so ) < wgtrad );
-  rx1 = x1(mask); ## I've kept the variable names from the R function here
-  ry1 = y1(mask); ## Needs to have a noisy error if length(y1) != length(x1) -- add this!
-  mask = find( ( abs( x2 - t ) * so ) < wgtrad );
+
+  ## The first solution that comes to mind is admittedly slightly 
+  ## ugly and has a data footprint of O(2n) but it is vectorised.
+  mask = (abs (x1 - t) * so) < wgtrad;
+  ## I've kept the variable names from the R function here
+  rx1 = x1(mask); 
+  ## FIXME : Needs to have a noisy error if length(y1) != length(x1) -- add this!
+  ry1 = y1(mask); 
+
+  ## I've used the same mask for all of these as it's an 
+  ## otherwise unimportant variable ... can this leak memory?
+  mask = (abs (x2 - t) * so ) < wgtrad;
   rx2 = x2(mask);
   ry2 = y2(mask);
-  ## I've used the same mask for all of these as it's an otherwise unimportant variable ... can this leak memory?
-  length(rx1) ##printing this length is probably used as a warning if 0 is returned; I included it
+
+  ## printing this length is probably used as a warning if 0 is returned; 
+  ## I included it
+  length (rx1) 
+
   ## in particular to maintain an exact duplicate of the R function.
-  s = sum ( wgt ( ( rx1 - t ) .* so ) ) * sum ( wgt ( ( rx2 - t ) .* so ) );
-  if s != 0
-    coeff = sum ( wgt ((rx1-t).*so).*exp(i*o.*rx1).*ry1) * sum(wgt((rx2-t).*so).*exp(i*o.*rx2).*conj(ry2)) / s;
+  s = sum (wgt ((rx1 - t) .* so)) * sum (wgt ((rx2 - t ) .* so ));
+  if (s != 0)
+    coeff = sum (wgt ((rx1 - t) .* so) .* exp (i * o .* rx1) .* ry1) * ...
+        sum (wgt ((rx2 - t) .* so) .* exp (i * o .* rx2) .* conj (ry2)) / s;
   else
     coeff = 0;
   endif
 
 endfunction
 
-%!test
+
 %!shared t, p, x, y, z, o, maxfreq
 %! maxfreq = 4 / (2 * pi);
 %! t = linspace (0, 8);
@@ -88,12 +92,18 @@
 %!      0.2 .* cos (maxfreq .* p) + 
 %!      cos ((1/4) * maxfreq .* p));
 %! o = [maxfreq , (3/4 * maxfreq) , (1/4 * maxfreq)];
-%!assert (lscorrcoeff (t, x, t, x, 0.5, maxfreq), -5.54390340863576 -
-%! 1.82439880893383i, 5e-10);
-%!assert (lscorrcoeff (t, x, t, y, 0.5, maxfreq), 5.54390340863576 +
-%! 1.82439880893383i, 5e-10);
-%!assert (lscorrcoeff (t, x, p, z, 0.5, maxfreq), -5.55636741054624 -
-%! 1.82803733863170i, 5e-10);
+%!assert (lscorrcoeff (t, x, t, x, 0.5, maxfreq), 
+%!                     -5.54390340863576 - 1.82439880893383i, 5e-10);
+%!assert (lscorrcoeff (t, x, t, y, 0.5, maxfreq), 
+%!                     5.54390340863576 + 1.82439880893383i, 5e-10);
+%!assert (lscorrcoeff (t, x, p, z, 0.5, maxfreq), 
+%!                     -5.55636741054624 - 1.82803733863170i, 5e-10);
 
+## Demo with sin, cos as Nir suggested.
+%!demo
+%! ## This generates the correlation coefficient at time 0.5 and circular freq. 0.9
+%! x = 1:10;
+%! y = sin (x);
+%! z = cos (x);
+%! a = lscorrcoeff (x, y, x, z, 0.5, 0.9)
 
-