PLearn 0.1
GaussianProcessNLLVariable.h
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00001 // -*- C++ -*-
00002 
00003 // GaussianProcessNLLVariable.h
00004 //
00005 // Copyright (C) 2006 Nicolas Chapados
00006 //
00007 // Redistribution and use in source and binary forms, with or without
00008 // modification, are permitted provided that the following conditions are met:
00009 //
00010 //  1. Redistributions of source code must retain the above copyright
00011 //     notice, this list of conditions and the following disclaimer.
00012 //
00013 //  2. Redistributions in binary form must reproduce the above copyright
00014 //     notice, this list of conditions and the following disclaimer in the
00015 //     documentation and/or other materials provided with the distribution.
00016 //
00017 //  3. The name of the authors may not be used to endorse or promote
00018 //     products derived from this software without specific prior written
00019 //     permission.
00020 //
00021 // THIS SOFTWARE IS PROVIDED BY THE AUTHORS ``AS IS'' AND ANY EXPRESS OR
00022 // IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
00023 // OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN
00024 // NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
00025 // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED
00026 // TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
00027 // PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
00028 // LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
00029 // NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
00030 // SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
00031 //
00032 // This file is part of the PLearn library. For more information on the PLearn
00033 // library, go to the PLearn Web site at www.plearn.org
00034 
00035 // Authors: Nicolas Chapados
00036 
00040 #ifndef GaussianProcessNLLVariable_INC
00041 #define GaussianProcessNLLVariable_INC
00042 
00043 #include <plearn/var/NaryVariable.h>
00044 #include <plearn/ker/Kernel.h>
00045 
00046 namespace PLearn {
00047 using namespace std;
00048 
00068 class GaussianProcessNLLVariable : public NaryVariable
00069 {
00070     typedef NaryVariable inherited;
00071 
00072 public:
00073     //#####  Public Build Options  ############################################
00074 
00077     bool m_save_gram_matrix;
00078 
00080     PPath m_expdir;
00081     
00082 public:
00083     //#####  Public Member Functions  #########################################
00084 
00086     GaussianProcessNLLVariable();
00087 
00105     GaussianProcessNLLVariable(Kernel* kernel, real noise,
00106                                Mat inputs, Mat targets,
00107                                const TVec<string>& hyperparam_names,
00108                                const VarArray& hyperparam_vars,
00109                                bool allow_bprop = true,
00110                                bool save_gram_matrix = false,
00111                                PPath expdir = "");
00112 
00113     
00114     //#####  PLearn::Variable methods #########################################
00115 
00116     virtual void recomputeSize(int& l, int& w) const;
00117     virtual void fprop();
00118     virtual void bprop();
00119     
00138     static void fbpropFragments(Kernel* kernel, real noise, const Mat& inputs,
00139                                 const Mat& targets, bool compute_inverse,
00140                                 bool save_gram_matrix, const PPath& expdir,
00141                                 Mat& gram, Mat& L, Mat& alpha, Mat& inv,
00142                                 Vec& tmpch, Mat& tmprhs);
00143 
00145     const Mat& alpha() const;
00146 
00148     const Mat& gram() const { return m_gram; }
00149     
00151     const Mat& gramInverse() const { return m_inverse_gram; }
00152 
00154     static void logVarray(const VarArray& varr, const string& title="",
00155                           bool debug=false);
00156     
00157 
00158     //#####  PLearn::Object Protocol  #########################################
00159 
00160     // Declares other standard object methods.
00161     PLEARN_DECLARE_OBJECT(GaussianProcessNLLVariable);
00162 
00163     // Simply calls inherited::build() then build_()
00164     virtual void build();
00165 
00167     virtual void makeDeepCopyFromShallowCopy(CopiesMap& copies);
00168 
00169 protected:
00171     Kernel* m_kernel;
00172 
00174     real m_noise;
00175     
00177     Mat m_inputs;
00178 
00180     Mat m_targets;
00181 
00184     TVec<string> m_hyperparam_names;
00185 
00188     VarArray m_hyperparam_vars;
00189 
00191     bool m_allow_bprop;
00192 
00194     Mat m_gram;
00195 
00198     Mat m_gram_derivative;
00199     
00201     Mat m_cholesky_gram;
00202 
00205     Mat m_alpha_t;
00206 
00209     mutable Mat m_alpha_buf;
00210     
00212     Mat m_inverse_gram;
00213     
00215     Vec m_cholesky_tmp;
00216 
00218     Mat m_rhs_tmp;
00219 
00220 protected:
00222     static void declareOptions(OptionList& ol);
00223 
00224 private:
00226     void build_();
00227 };
00228 
00229 // Declares a few other classes and functions related to this class
00230 DECLARE_OBJECT_PTR(GaussianProcessNLLVariable);
00231 
00232 } // end of namespace PLearn
00233 
00234 #endif
00235 
00236 
00237 /*
00238   Local Variables:
00239   mode:c++
00240   c-basic-offset:4
00241   c-file-style:"stroustrup"
00242   c-file-offsets:((innamespace . 0)(inline-open . 0))
00243   indent-tabs-mode:nil
00244   fill-column:79
00245   End:
00246 */
00247 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :
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