Profile Summary

get_admm_matrix (Calls: 1, Time: 108.380 s)
Generated 20-Jul-2018 02:24:59 using performance time.
function in file C:\Users\yz\Dropbox\Workspace\Researches\PhD Research\My Papers\2018_symmtry_reduction\18groupsymmetrySDPSlaterHaoRenata.d\codesgroupsymmetrySDPSlaterHaoRenata.d\admm\get_admm_matrix.m
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This function changed during profiling or before generation of this report. Results may be incomplete or inaccurate.

Parents (calling functions)

Function Name	Function Type	Calls
qap_admm_blkdiag	function	1

Lines where the most time was spent

Line Number	Code	Calls	Total Time	% Time	Time Plot
45	temp = Bhat{j}(idx,idx);	649836	90.831 s	83.8%
46	Bhat_blk{i}(:,j) = temp(:);	649836	11.000 s	10.1%
22	idx = find(B{i}(:));	3282	4.158 s	3.8%
40	Bhat_blk{i} = zeros(block_size...	198	0.900 s	0.8%
48	end	198	0.415 s	0.4%
All other lines			1.076 s	1.0%
Totals			108.380 s	100%

Children (called functions)
No children

Code Analyzer results
No Code Analyzer messages.

Coverage results
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Total lines in function	65
Non-code lines (comments, blank lines)	27
Code lines (lines that can run)	38
Code lines that did run	38
Code lines that did not run	0
Coverage (did run/can run)	100.00 %

Function listing

time	Calls	line
		1	function [Bmat, Bmat_mean, Bhat_blk, V] = get_admm_matrix(B, Bhat, Wbar, block_sizes)
		2
		3
		4	% load the data
		5	% block_sizes = output.block_sizes;
		6	% block_pattern = output.block_pattern;
		7
		8
		9
0.006	1	10	orbit_size = length(B); % number of orbits
0.002	1	11	nr_blocks = length(block_sizes); % number of blocks
0.007	1	12	bt = cumsum(block_sizes); % the end index of each blocks
0.020	1	13	bs = [1; bt(1:end-1)+1]; % the begin index of each blocks
		14
< 0.001	1	15	m = length(Wbar) - 1;
		16
		17	% stack B_{i} as columns of the sparse matrix B_mat
< 0.001	1	18	k = 0;
0.009	1	19	I = zeros((m+1)^2,1);
0.002	1	20	J = zeros((m+1)^2,1);
0.002	1	21	for i = 1:orbit_size
4.158	3282	22	idx = find(B{i}(:));
0.004	3282	23	idx_size = length(idx);
0.027	3282	24	I(k+1:k+idx_size) = idx;
0.085	3282	25	J(k+1:k+idx_size) = i*ones(idx_size,1);
0.002	3282	26	k = k+idx_size;
0.010	3282	27	end
0.006	1	28	I = I(1:k);
0.006	1	29	J = J(1:k);
0.038	1	30	Bmat = sparse(I,J,ones(k,1),(m+1)^2,orbit_size);
		31
		32	% stack B{i} as rows and divide by #1s
0.007	1	33	vr=sum(Bmat);
0.167	1	34	Bmat_mean = (Bmat/diag(vr))';
		35
		36	% the k-th cell contains the matrix Bhat_blk{k} such that
		37	% Bhat_blk{k}x is the k-th block of B_hat(x)
0.012	1	38	Bhat_blk = cell(nr_blocks,1);
< 0.001	1	39	for i = 1:nr_blocks
0.900	198	40	Bhat_blk{i} = zeros(block_sizes(i)^2,orbit_size);
		41
		42	% stack the columns of the i-th block of Bhat
0.013	198	43	for j = 1:orbit_size
0.343	649836	44	idx = bs(i):bt(i); % idx for the i-th block of Y
90.831	649836	45	temp = Bhat{j}(idx,idx);
11.000	649836	46	Bhat_blk{i}(:,j) = temp(:);
0.071	649836	47	end
0.415	198	48	end
		49
		50	% obtain the orthogonal complement of the exposing vector Wbar
0.009	1	51	V = cell(nr_blocks,1);
0.003	1	52	V_dim = zeros(nr_blocks,1); % the dim. of each block in symmetry reduced program
0.006	1	53	for ii = 1:nr_blocks
0.020	198	54	idx = bs(ii):bt(ii); % idx for the i-th block
0.136	198	55	[v,d] = eig(Wbar(idx,idx));
0.019	198	56	V{ii} = v(:,diag(d)<1e-5);
0.013	198	57	V_dim(ii) = size(V{ii},2);
0.006	198	58	end
		59
		60	%
		61	% % save the output
		62	% output.V_dim = V_dim;
		63
		64
0.013	1	65	end

Other subfunctions in this file are not included in this listing.