2 ///////////////////////////////////////////////////////////////////////////
3 // This program is free software: you can redistribute it and/or modify //
4 // it under the terms of the version 3 of the GNU General Public License //
5 // as published by the Free Software Foundation. //
7 // This program is distributed in the hope that it will be useful, but //
8 // WITHOUT ANY WARRANTY; without even the implied warranty of //
9 // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU //
10 // General Public License for more details. //
12 // You should have received a copy of the GNU General Public License //
13 // along with this program. If not, see <http://www.gnu.org/licenses/>. //
15 // Written by Francois Fleuret //
16 // (C) Idiap Research Institute //
18 // Contact <francois.fleuret@idiap.ch> for comments & bug reports //
19 ///////////////////////////////////////////////////////////////////////////
23 A SampleSet stands for a set of samples from R^d with their
24 labels. It abstracts the notion features and is what the machine
25 learning techniques of this software see.
32 #include "pose_cell.h"
33 #include "pi_feature_family.h"
34 #include "shared_responses.h"
39 SharedResponses *_shared_feature_values;
40 scalar_t **_feature_values;
45 inline int nb_samples() { return _nb_samples; }
46 inline int nb_features() { return _nb_features; }
48 inline int label(int n_sample) {
49 ASSERT(n_sample >= 0 && n_sample < _nb_samples);
50 return _labels[n_sample];
53 inline scalar_t feature_value(int n_sample, int n_feature) {
54 ASSERT(n_sample >= 0 && n_sample < _nb_samples &&
55 n_feature >= 0 && n_feature < _nb_features);
56 ASSERT(!isnan(_feature_values[n_sample][n_feature]));
57 return _feature_values[n_sample][n_feature];
60 SampleSet(int nb_features, int nb_samples);
61 SampleSet(SampleSet *father, int nb, int *indexes);
65 void set_sample(int n,
66 PiFeatureFamily *pi_feature_family,