get x elements from center of vector - arrays

Question

How do I create a function (e.g. here, an anonymous one but I don't mind any) to get x elements from vec that are most centered (i.e. around the median)? In essence I want a function with same syntax as Matlab's randsample(n,k), but for non-random, with elements spanning around the center.
cntr=#(vec,x) vec(round(end*.5)+(-floor(x/2):floor(x/2))); %this function in question
cntr(1:10,3) % outputs 3 values around median 5.5 => [4 5 6];
cntr(1:11,5) % outputs => [4 5 6 7 8]
Note that vec is always sorted.
One part that I struggle with is not to output more than the limits of vec. For example, cntr(1:10, 10) should not throw an error.
edit: sorry to answer-ers for many updates of question

Answer 1

It's not a one-line anonymous function, but you can do this pretty simply with a couple calls to sort:
function vec = cntr(vec, x)
[~, index] = sort(abs(vec-median(vec)));
vec = vec(sort(index(1:min(x, end))));
end
The upside: it will still return the same set of values even if vec isn't sorted. Some examples:
>> cntr(1:10, 3)
ans =
4 5 6
>> cntr(1:11, 5)
ans =
4 5 6 7 8
>> cntr(1:10, 10) % No indexing errors
ans =
1 2 3 4 5 6 7 8 9 10
>> cntr([3 10 2 4 1 6 5 8 11 7 9], 5) % Unsorted version of example 2
ans =
4 6 5 8 7 % Same values, in their original order in vec
OLD ANSWER
NOTE: This applied to an earlier version of the question where a range of x values below and x values above the median were desired as output. Leaving it for posterity...
I broke it down into these steps (starting with a sorted vec):
Find the values in vec less than the median, get the last x indices of these, then take the first (smallest) of them. This is the starting index.
Find the values in vec greater than the median, get the first x indices of these, then take the last (largest) of them. This is the ending index.
Use the starting and ending indices to select the center portion of vec.
Here's the implementation of the above, using the functions find, min, and max:
cntr = #(vec, x) vec(min(find(vec < median(vec), x, 'last')):max(find(vec > median(vec), x)));
And a few tests:
>> cntr(1:10, 3) % 3 above and 3 below 5.5
ans =
3 4 5 6 7 8
>> cntr(1:11, 5) % 5 above and 5 below 6 (i.e. all of vec)
ans =
1 2 3 4 5 6 7 8 9 10 11
>> cntr(1:10, 10) % 10 above and 10 below 5.5 (i.e. all of vec, no indexing errors)
ans =
1 2 3 4 5 6 7 8 9 10

Answer 2

median requires sorting the array elements. Might as well sort manually, and pick out the middle block (edit: OP's comment indicates elements are already sorted, more justification for keeping it simple):
function data = cntr(data,x)
x = min(x,numel(data)); % don't pick more elements than exist
data = sort(data);
start = floor((numel(data)-x)/2) + 1;
data = data(start:start+x-1);
You could stick this into a single-line anonymous function with some tricks, but that just makes the code ugly. :)
Note that in the case of an uneven division (when we don't leave an even number of elements out), here we prioritize an element on the left. Here is what I mean:
0 0 0 0 0 0 0 0 0 0 0 => 11 elements, x=4
\_____/
picking these 4 values
This choice could be made more complex, for example shifting the interval left or right depending on which of those values is closest to the mean.
Given data (i.e. vec) is already sorted, the indexing operation can be kept to a single line:
cntr = #(data,x) data( floor((numel(data)-x)/2) + (1:x) );
The thing that is missing in that line is x = min(x,numel(data)), which we need to add twice becuase we can't change a variable in an anonymous function:
cntr = #(data,x) data( floor((numel(data)-min(x,numel(data)))/2) + (1:min(x,numel(data))) );
This we can simplify to:
cntr = #(data,x) data( floor(max(numel(data)-x,0)/2) + (1:min(x,numel(data))) );