# For command in function

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Charms on 3 Sep 2019
Commented: Charms on 5 Sep 2019
I have a function attached and would like it to automatically run it with x = 2:4 & y = 2:4, that is, the function to run 8 times & have 8 outputs, with inputs
x =2, y = 2
x = 2, y = 3
x = 2, y = 4
x = 3, y = 2
...
Should I write a 'for' command with the function? It does not seem to work the best this way.

darova on 4 Sep 2019
Each value of (x,y) you want to compare to rowsncolumn?
>> combvec([2:4],[2:4])
ans =
2 3 4 2 3 4 2 3 4
2 2 2 3 3 3 4 4 4
If i understood you correctly output matrix should be of size 621 x 9 ?
Charms on 4 Sep 2019
yes, for each value, i would compare it to rowsncolumn. the output at the end should only give me 9 x 1, or 1x 9, basically 9 values as the last line of code is the mean.
Walter Roberson on 4 Sep 2019
After you use ndgrid to build x y you can
x = permute(x, [3 1 2])
and the same for y. Then assuming R2016b or later, the & would give a 3d result, 621 by 3 by 3
Now take that and .* by dataset and sum along the first dimension. Then sum the result of the & itself along the first dimension to get counts. ./ the two qualities. You should now have a 1 x 3 x 3 array of means.

darova on 4 Sep 2019
You can use pdist2()
[X,Y] = meshgrid(2:4);
x = X(:);
y = Y(:);
D = pdist2(rowsncolumns,[x y]);
% D(:,1) - first column of D - distance from (rowscolumns) to (x1,y1) point
Indices you want: D == 0
Size of D: 621 x 9

Walter Roberson on 4 Sep 2019
Ah, but how do you proceed from here to vectorize the mean() that has to be done for each x y pair?
darova on 4 Sep 2019
Maybe not to use mean()
ix = D == 0;
data = repmat(dataset_pfc_tar_57_n1,[1 9]);
result = sum(data.*ix) ./ sum(ix);
size of result is 1 x 9
Charms on 5 Sep 2019
thank you so much, I really appreaciate everyone's help :D