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otvamotvam
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Small bugfixes
1 parent bafda07 commit aa41ea2

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4 files changed

+20
-20
lines changed

4 files changed

+20
-20
lines changed

‎source_ann/ann_example/ann_data/get_ann_param.m

+2-2
Original file line numberDiff line numberDiff line change
@@ -52,8 +52,8 @@
5252
% - 'rel_abs': relative error (absolute value)
5353
% - 'rel_sign': relative error (with sign)
5454
var_out = {};
55-
var_out{end+1} = struct('name', 'y_1', 'use_nrm', true, 'var_trf', 'none', 'var_norm', 'min_max', 'var_err', 'rel_sign');
56-
var_out{end+1} = struct('name', 'y_2', 'use_nrm', true, 'var_trf', 'none', 'var_norm', 'min_max', 'var_err', 'rel_sign');
55+
var_out{end+1} = struct('name', 'y_1', 'use_nrm', true, 'var_trf', 'none', 'var_norm', 'min_max', 'var_err', 'rel_abs');
56+
var_out{end+1} = struct('name', 'y_2', 'use_nrm', true, 'var_trf', 'none', 'var_norm', 'min_max', 'var_err', 'rel_abs');
5757

5858
% control the splitting of the samples between training and testing:
5959
% - ratio_train: ratio of the samples used for training

‎source_ann/ann_matlab/@AnnManager/disp_fom_train.m

+3-3
Original file line numberDiff line numberDiff line change
@@ -105,7 +105,7 @@ function disp_hist(tag, fom_train, fom_test, type)
105105
% tag (str): name of the variable
106106
% fom_train (struct): figures of merit of the variable (training)
107107
% fom_test (struct): figures of merit of the variable (testing)
108-
% type (str): type of the variable ('set' or 'abs' or 'rel')
108+
% type (str): type of the variable ('set' or 'rel_abs' or 'abs_abs' or 'rel_sign' or 'abs_sign')
109109

110110
hold('on')
111111
switch type
@@ -116,14 +116,14 @@ function disp_hist(tag, fom_train, fom_test, type)
116116
ylabel('n [1]')
117117
vec_train = [fom_train.v_min fom_train.v_max];
118118
vec_test = [fom_test.v_min fom_test.v_max];
119-
case 'abs'
119+
case {'abs_abs', 'abs_sign'}
120120
histogram(fom_train.vec)
121121
histogram(fom_test.vec)
122122
xlabel('x [1]')
123123
ylabel('n [1]')
124124
vec_train = [fom_train.v_min fom_train.v_max fom_train.v_avg fom_train.v_prc_99];
125125
vec_test = [fom_test.v_min fom_test.v_max fom_test.v_avg fom_test.v_prc_99];
126-
case 'rel'
126+
case {'rel_abs', 'rel_sign'}
127127
histogram(1e2.*fom_train.vec)
128128
histogram(1e2.*fom_test.vec)
129129
xlabel('err [%]')

‎source_inductor/inductor_fem_ann/master_assemble.m

+6-6
Original file line numberDiff line numberDiff line change
@@ -19,12 +19,6 @@ function master_assemble(file_assemble, folder_fem, make_zip)
1919
fprintf('assemble\n')
2020
[diff, n_tot, n_sol, model_type, file_model, inp, out_fem] = fem_ann.get_assemble(folder_fem);
2121

22-
% make a zip file and remove the folder
23-
if make_zip==true
24-
fprintf('zip\n')
25-
fem_ann.get_zip(folder_fem);
26-
end
27-
2822
% compute the analytical results
2923
fprintf('approx\n')
3024
out_approx = fem_ann.get_out_approx(model_type, inp);
@@ -35,6 +29,12 @@ function master_assemble(file_assemble, folder_fem, make_zip)
3529
fprintf(' n_tot = %d\n', n_tot)
3630
fprintf(' n_sol = %d\n', n_sol)
3731

32+
% make a zip file and remove the folder
33+
if make_zip==true
34+
fprintf('zip\n')
35+
fem_ann.get_zip(folder_fem);
36+
end
37+
3838
% save data
3939
fprintf('save\n')
4040
save(file_assemble, '-v7.3', 'diff', 'n_sol', 'n_tot', 'inp', 'out_fem', 'out_approx', 'model_type', 'file_model')

‎source_input/get_fem_ann_data_train.m

+9-9
Original file line numberDiff line numberDiff line change
@@ -98,32 +98,32 @@
9898
var_out = {};
9999
if strcmp(model_type, 'mf')
100100
% inductance (for a single turn)
101-
var_out{end+1} = struct('name', 'L_norm', 'use_nrm', true, 'var_trf', 'none', 'var_norm', 'min_max', 'var_err', 'rel_sign');
101+
var_out{end+1} = struct('name', 'L_norm', 'use_nrm', true, 'var_trf', 'none', 'var_norm', 'min_max', 'var_err', 'rel_abs');
102102

103103
% quasi-RMS flux density, integral of B^beta, normalized for one turn and 1A, for the core losses
104-
var_out{end+1} = struct('name', 'B_norm', 'use_nrm', true, 'var_trf', 'none', 'var_norm', 'min_max', 'var_err', 'rel_sign');
104+
var_out{end+1} = struct('name', 'B_norm', 'use_nrm', true, 'var_trf', 'none', 'var_norm', 'min_max', 'var_err', 'rel_abs');
105105

106106
% RMS current density, integral of J^2, normalized for one turn and 1A, for the LF winding losses
107-
var_out{end+1} = struct('name', 'J_norm', 'use_nrm', true, 'var_trf', 'none', 'var_norm', 'min_max', 'var_err', 'rel_sign');
107+
var_out{end+1} = struct('name', 'J_norm', 'use_nrm', true, 'var_trf', 'none', 'var_norm', 'min_max', 'var_err', 'rel_abs');
108108

109109
% RMS magnetic density, integral of H^2, normalized for one turn and 1A, for the HF winding losses
110-
var_out{end+1} = struct('name', 'H_norm', 'use_nrm', true, 'var_trf', 'none', 'var_norm', 'min_max', 'var_err', 'rel_sign');
110+
var_out{end+1} = struct('name', 'H_norm', 'use_nrm', true, 'var_trf', 'none', 'var_norm', 'min_max', 'var_err', 'rel_abs');
111111
end
112112
if strcmp(model_type, 'ht')
113113
% maximum temperature elevation of the core, for the thermal limit
114-
var_out{end+1} = struct('name', 'dT_core_max', 'use_nrm', true, 'var_trf', 'none', 'var_norm', 'min_max', 'var_err', 'rel_sign');
114+
var_out{end+1} = struct('name', 'dT_core_max', 'use_nrm', true, 'var_trf', 'none', 'var_norm', 'min_max', 'var_err', 'rel_abs');
115115

116116
% average temperature elevation of the core, for the losses
117-
var_out{end+1} = struct('name', 'dT_core_avg', 'use_nrm', true, 'var_trf', 'none', 'var_norm', 'min_max', 'var_err', 'rel_sign');
117+
var_out{end+1} = struct('name', 'dT_core_avg', 'use_nrm', true, 'var_trf', 'none', 'var_norm', 'min_max', 'var_err', 'rel_abs');
118118

119119
% maximum temperature elevation of the winding, for the thermal limit
120-
var_out{end+1} = struct('name', 'dT_winding_max', 'use_nrm', true, 'var_trf', 'none', 'var_norm', 'min_max', 'var_err', 'rel_sign');
120+
var_out{end+1} = struct('name', 'dT_winding_max', 'use_nrm', true, 'var_trf', 'none', 'var_norm', 'min_max', 'var_err', 'rel_abs');
121121

122122
% average temperature elevation of the winding, for the losses
123-
var_out{end+1} = struct('name', 'dT_winding_avg', 'use_nrm', true, 'var_trf', 'none', 'var_norm', 'min_max', 'var_err', 'rel_sign');
123+
var_out{end+1} = struct('name', 'dT_winding_avg', 'use_nrm', true, 'var_trf', 'none', 'var_norm', 'min_max', 'var_err', 'rel_abs');
124124

125125
% maximum temperature elevation of the insulation, for the thermal limit
126-
var_out{end+1} = struct('name', 'dT_iso_max', 'use_nrm', true, 'var_trf', 'none', 'var_norm', 'min_max', 'var_err', 'rel_sign');
126+
var_out{end+1} = struct('name', 'dT_iso_max', 'use_nrm', true, 'var_trf', 'none', 'var_norm', 'min_max', 'var_err', 'rel_abs');
127127
end
128128

129129
% control the splitting of the samples between training and testing:

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