Parents (calling functions)
| Function Name | Function Type | Calls |
| Bottom_Gravity_Current_Setup6DO | script | 1 |
Lines where the most time was spent
| Line Number | Code | Calls | Total Time | % Time | Time Plot |
| 42 | [Umat, Svals, Vmat] = svd (var... | 1 | 12.172 s | 82.9% |  |
| 24 | load (fullfile(app.DOicDir,num... | 120 | 1.203 s | 8.2% | |
| 25 | var_mat(:,n+1) = [u./app.sigma... | 120 | 0.446 s | 3.0% | |
| 36 | var_mat = var_mat - repmat ( v... | 1 | 0.375 s | 2.6% | |
| 18 | var_mat = repmat ( [u./app.sig... | 1 | 0.207 s | 1.4% | |
| All other lines | 0.278 s | 1.9% | | ||
| Totals | 14.681 s | 100% |
Children (called functions)
| Function Name | Function Type | Calls | Total Time | % Time | Time Plot |
| mean | function | 1 | 0.071 s | 0.5% | |
| num2str | function | 120 | 0.071 s | 0.5% | |
| fullfile | function | 121 | 0.032 s | 0.2% | |
| normrnd | function | 40 | 0.019 s | 0.1% | |
| Self time (built-ins, overhead, etc.) | 14.487 s | 98.7% | | ||
| Totals | 14.681 s | 100% |
Code Analyzer results
| Line number | Message |
| 2 | Extra semicolon is unnecessary. |
| 38 | Assignment to 'var_mat' might be unnecessary. |
| 42 | The value assigned to variable 'Vmat' might be unused. |
Coverage results
Show coverage for parent directory
Show coverage for parent directory
| Total lines in function | 71 |
| Non-code lines (comments, blank lines) | 43 |
| Code lines (lines that can run) | 28 |
| Code lines that did run | 28 |
| Code lines that did not run | 0 |
| Coverage (did run/can run) | 100.00 % |
Function listing
time | calls | line | |
|---|---|---|---|
2 | function [umean,vmean,rhomean,ui,vi,rhoi,Yi] = BGC_DO_simsvdIC (app); | ||
3 | |||
4 | %------------------------------------------------------------------------------- | ||
5 | % Load realizations. | ||
6 | %------------------------------------------------------------------------------- | ||
7 | |||
8 | % Load ICs. | ||
9 | |||
0.01 | 1 | 10 | load (fullfile(app.DOicDir,'000')); |
11 | |||
12 | % Set sizes & working storage. | ||
13 | |||
1 | 14 | Nu = length(u); | |
1 | 15 | Nv = length(v); | |
1 | 16 | Nrho = length(rho); | |
17 | |||
0.21 | 1 | 18 | var_mat = repmat ( [u./app.sigma_nd(1); v./app.sigma_nd(2); rho./app.sigma_nd(3)] , ... |
19 | [1 (app.DOnumIC+1)] ); | ||
20 | |||
21 | % Load remaining realizations. | ||
22 | |||
1 | 23 | for n = 1:app.DOnumIC | |
1.20 | 120 | 24 | load (fullfile(app.DOicDir,num2str(n,'%3.3d'))); |
0.45 | 120 | 25 | var_mat(:,n+1) = [u./app.sigma_nd(1); v./app.sigma_nd(2); rho./app.sigma_nd(3)]; |
< 0.01 | 120 | 26 | end; |
27 | |||
28 | %------------------------------------------------------------------------------- | ||
29 | % Create modes from SVD. | ||
30 | %------------------------------------------------------------------------------- | ||
31 | |||
32 | % Remove mean. | ||
33 | |||
0.08 | 1 | 34 | var_mean = mean(var_mat,2); |
35 | |||
0.38 | 1 | 36 | var_mat = var_mat - repmat ( var_mean , [1 (app.DOnumIC+1)] ); |
37 | |||
1 | 38 | var_mat = var_mat; | |
39 | |||
40 | % Take SVD. | ||
41 | |||
12.17 | 1 | 42 | [Umat, Svals, Vmat] = svd (var_mat, 0); |
43 | |||
1 | 44 | clear var_mat; | |
45 | |||
46 | % Extract redimensionalized modes. | ||
47 | |||
1 | 48 | umean = var_mean((1:Nu)).*app.sigma_nd(1); | |
1 | 49 | vmean = var_mean((Nu+(1:Nv))).*app.sigma_nd(2); | |
< 0.01 | 1 | 50 | rhomean = var_mean((Nu+Nv+(1:Nrho))).*app.sigma_nd(3); |
51 | |||
1 | 52 | clear var_mean | |
53 | |||
1 | 54 | mode_ind = 1:app.S(1); | |
55 | |||
0.05 | 1 | 56 | ui = Umat((1:Nu),mode_ind).*app.sigma_nd(1); |
0.04 | 1 | 57 | vi = Umat((Nu+(1:Nv)),mode_ind).*app.sigma_nd(2); |
0.05 | 1 | 58 | rhoi = Umat((Nu+Nv+(1:Nrho)),mode_ind).*app.sigma_nd(3); |
59 | |||
< 0.01 | 1 | 60 | clear Umat Vmat; |
61 | |||
62 | %------------------------------------------------------------------------------- | ||
63 | % Create coefficients from SVD. | ||
64 | %------------------------------------------------------------------------------- | ||
65 | |||
1 | 66 | Yi = zeros (app.MC,app.S(1)); | |
67 | |||
1 | 68 | for n=1:app.S(1) | |
0.03 | 40 | 69 | Yi(:,n) = sqrt(Svals(n,n)).*normrnd(0,1,app.MC,1); |
40 | 70 | end | |
71 | |||
1 | 72 | Yi = Yi.*(sqrt(app.varscale)/ (prod(app.sigma_nd)^(1/length(app.sigma_nd))) ); % if M is realiz matrix, then P=M*M^T/n_r. | |
Other subfunctions in this file are not included in this listing.