XMM - Probabilistic Models for Motion Recognition and Mapping

xmmModelResults.hpp
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1 /*
2  * xmmModelResults.hpp
3  *
4  * Results structures for probabilistic models
5  *
6  * Contact:
7  * - Jules Francoise <jules.francoise@ircam.fr>
8  *
9  * This code has been initially authored by Jules Francoise
10  * <http://julesfrancoise.com> during his PhD thesis, supervised by Frederic
11  * Bevilacqua <href="http://frederic-bevilacqua.net>, in the Sound Music
12  * Movement Interaction team <http://ismm.ircam.fr> of the
13  * STMS Lab - IRCAM, CNRS, UPMC (2011-2015).
14  *
15  * Copyright (C) 2015 UPMC, Ircam-Centre Pompidou.
16  *
17  * This File is part of XMM.
18  *
19  * XMM is free software: you can redistribute it and/or modify
20  * it under the terms of the GNU General Public License as published by
21  * the Free Software Foundation, either version 3 of the License, or
22  * (at your option) any later version.
23  *
24  * XMM is distributed in the hope that it will be useful,
25  * but WITHOUT ANY WARRANTY; without even the implied warranty of
26  * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
27  * GNU General Public License for more details.
28  *
29  * You should have received a copy of the GNU General Public License
30  * along with XMM. If not, see <http://www.gnu.org/licenses/>.
31  */
32 
33 #ifndef xmmModelResults_h
34 #define xmmModelResults_h
35 
36 #include <string>
37 #include <vector>
38 
39 namespace xmm {
46 template <typename ModelType>
47 struct ClassResults {
52 
57 
62  std::vector<float> output_values;
63 
69  std::vector<float> output_covariance;
70 };
71 
79 template <typename ModelType>
80 struct Results {
84  std::vector<double> instant_likelihoods;
85 
89  std::vector<double> instant_normalized_likelihoods;
90 
94  std::vector<double> smoothed_likelihoods;
95 
99  std::vector<double> smoothed_normalized_likelihoods;
100 
104  std::vector<double> smoothed_log_likelihoods;
105 
109  std::string likeliest;
110 
115  std::vector<float> output_values;
116 
121  std::vector<float> output_covariance;
122 };
123 }
124 
125 #endif
Results of the filtering/inference process (for a Model with multiple classes).
Definition: xmmModelResults.hpp:80
std::vector< double > smoothed_likelihoods
Smoothed likelihood of each class.
Definition: xmmModelResults.hpp:94
std::vector< double > smoothed_normalized_likelihoods
Normalized smoothed likelihood of each class.
Definition: xmmModelResults.hpp:99
std::vector< float > output_covariance
Output variance over the values estimated by regression.
Definition: xmmModelResults.hpp:121
std::vector< double > instant_likelihoods
Instantaneous likelihood of each class.
Definition: xmmModelResults.hpp:84
std::vector< float > output_values
Output values estimated by regression.
Definition: xmmModelResults.hpp:115
std::vector< float > output_covariance
Predicted Output variance associated with the generated parameter vector (only used in regression mod...
Definition: xmmModelResults.hpp:69
Class-specific Results of the filtering/inference process.
Definition: xmmModelResults.hpp:47
std::string likeliest
Label of the likeliest class.
Definition: xmmModelResults.hpp:109
std::vector< double > instant_normalized_likelihoods
Normalized instantaneous likelihood of each class.
Definition: xmmModelResults.hpp:89
double log_likelihood
Cumulative log-likelihood computed on a sliding window.
Definition: xmmModelResults.hpp:56
std::vector< float > output_values
Predicted Output parameter vector (only used in regression mode)
Definition: xmmModelResults.hpp:62
Definition: xmmAttribute.hpp:42
double instant_likelihood
Instantaneous likelihood.
Definition: xmmModelResults.hpp:51
std::vector< double > smoothed_log_likelihoods
Cumulative smoothed log-likelihood of each class.
Definition: xmmModelResults.hpp:104