You are an expert in writing code in many different languages. Your goal is to perform code completion for the following code, keeping in mind the rest of the code and the file meta data.
    Metadata details:
    filename: randomize_graph_partial_und.m
    path of file: ./repos/EEGapp/EEGapp/custom_stuff/BCT/2017_01_15_BCT
    
    the code of the file until where you have to start completion: function A = randomize_graph_partial_und(A,B,maxswap)
% RANDOMIZE_GRAPH_PARTIAL_UND    Swap edges with preserved degree sequence
%
%   A = RANDOMIZE_GRAPH_PARTIAL_UND(A,B,MAXSWAP) takes adjacency matrices A 
%   and B and attempts to randomize matrix A by performing MAXSWAP 
%   rewirings. The rewirings will avoid any spots where matrix B is 
%   nonzero.
%
%   Inputs:       A,      undirected adjacency matrix
%                 B,      edges to avoid
%           MAXSWAP,      number of rewirings
%
%   Outputs:      A,      randomized matrix
%
%   Richard Betzel, Indiana University, 2013
%
%   Notes:
%   1. Based on the script randmio_und.m.
%   2. Graph may become disconnected as a result of rewiring. Always
%      important to check.
%   3. A can be weighted, though the weighted degree sequence will not be
%      preserved.
%

[i,j] = find(triu(A,1));
m = length(i);
nswap = 0;

    
function A = randomize_graph_partial_und(A,B,maxswap)
% RANDOMIZE_GRAPH_PARTIAL_UND    Swap edges with preserved degree sequence
%
%   A = RANDOMIZE_GRAPH_PARTIAL_UND(A,B,MAXSWAP) takes adjacency matrices A 
%   and B and attempts to randomize matrix A by performing MAXSWAP 
%   rewirings. The rewirings will avoid any spots where matrix B is 
%   nonzero.
%
%   Inputs:       A,      undirected adjacency matrix
%                 B,      edges to avoid
%           MAXSWAP,      number of rewirings
%
%   Outputs:      A,      randomized matrix
%
%   Richard Betzel, Indiana University, 2013
%
%   Notes:
%   1. Based on the script randmio_und.m.
%   2. Graph may become disconnected as a result of rewiring. Always
%      important to check.
%   3. A can be weighted, though the weighted degree sequence will not be
%      preserved.
%

[i,j] = find(triu(A,1));
m = length(i);
nswap = 0;
while nswap < maxswap
    while 1
        e1 = randi(m); e2 = randi(m);
        while e2 == e1
            e2 = randi(m);
        end