PLearn 0.1
ParzenWindow.cc
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00001 // -*- C++ -*-
00002 
00003 //
00004 // Copyright (C) 2004-2005 University of Montreal
00005 //
00006 // Redistribution and use in source and binary forms, with or without
00007 // modification, are permitted provided that the following conditions are met:
00008 //
00009 //  1. Redistributions of source code must retain the above copyright
00010 //     notice, this list of conditions and the following disclaimer.
00011 //
00012 //  2. Redistributions in binary form must reproduce the above copyright
00013 //     notice, this list of conditions and the following disclaimer in the
00014 //     documentation and/or other materials provided with the distribution.
00015 //
00016 //  3. The name of the authors may not be used to endorse or promote
00017 //     products derived from this software without specific prior written
00018 //     permission.
00019 //
00020 // THIS SOFTWARE IS PROVIDED BY THE AUTHORS ``AS IS'' AND ANY EXPRESS OR
00021 // IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
00022 // OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN
00023 // NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
00024 // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED
00025 // TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
00026 // PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
00027 // LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
00028 // NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
00029 // SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
00030 //
00031 // This file is part of the PLearn library. For more information on the PLearn
00032 // library, go to the PLearn Web site at www.plearn.org
00033 
00034 
00036 #include "ParzenWindow.h"
00037 
00038 //#include <plearn/math/plapack.h>
00039 //#include <plearn/base/general.h>
00040 //#include <plearn/math/TMat.h>
00041 //#include <plearn/math/TMat_maths.h>
00042 //#include <plearn/math/BottomNI.h>
00043 
00044 namespace PLearn {
00045 
00046 PLEARN_IMPLEMENT_OBJECT(ParzenWindow,
00047                         "Parzen Window density estimate.",
00048                         "Standard Parzen Window algorithm. The user only needs\n"
00049                         "to set the isotropic_sigma parameter"
00050     );
00051 
00052 // TODO Allow the user to specify the kernel.
00053 
00055 // ParzenWindow //
00057 ParzenWindow::ParzenWindow()
00058     : isotropic_sigma(1)
00059 {
00060     nstages = 1;
00061 }
00062 
00063 ParzenWindow::ParzenWindow(real the_isotropic_sigma)
00064     : isotropic_sigma(the_isotropic_sigma)
00065 {
00066 }
00067 
00068 // ### Nothing to add here, simply calls build_
00069 void ParzenWindow::build()
00070 {
00071     inherited::build();
00072     build_();
00073 }
00074 
00075 // TODO Hide the options from GaussMix that are overwritten.
00076 // TODO Yeah that's really needed!
00077 
00079 // declareOptions //
00081 void ParzenWindow::declareOptions(OptionList& ol)
00082 {
00083     declareOption(ol,"isotropic_sigma", &ParzenWindow::isotropic_sigma, OptionBase::buildoption,
00084                   "Spherical standard deviation parameter (NOTE: old implementation called this sigma_square, but it really was sigma, hence the renaming)");
00085 
00086     // Now call the parent class' declareOptions
00087     inherited::declareOptions(ol);
00088 }
00089 
00090 void ParzenWindow::build_()
00091 {}
00092 
00093 void ParzenWindow::makeDeepCopyFromShallowCopy(CopiesMap& copies)
00094 {
00095     inherited::makeDeepCopyFromShallowCopy(copies);
00096 
00097     // ### Call deepCopyField on all "pointer-like" fields
00098     // ### that you wish to be deepCopied rather than
00099     // ### shallow-copied.
00100     // ### ex:
00101     // deepCopyField(trainvec, copies);
00102 
00103     // ### Remove this line when you have fully implemented this method.
00104     //PLERROR("ParzenWindow::makeDeepCopyFromShallowCopy not fully (correctly) implemented yet!");
00105 }
00106 
00107 void ParzenWindow::train()
00108 {
00109     if(stage<1)
00110     {
00111         int l = train_set.length();
00112         type = "spherical";
00113         L = l;
00114         D = -1;
00115         GaussMix::build();  // rebuild because options chnged
00116         resizeDataBeforeTraining(); // TODO See exactly what this does.
00117     
00118         // new code proprly taking sample weights into account
00119         bool has_weights = train_set->hasWeights();
00120         real default_weight = 1.0/l;
00121         Vec target;    
00122         real weight = 0;
00123         real weight_sum = 0;
00124     
00125         for(int i=0; i<l; i++)
00126         {
00127             // if(i%100==0)
00128             //    cerr << "[SEQUENTIAL TRAIN: processing pattern #" << i << "/" << l << "]\n";            
00129             Vec input = center(i);
00130             train_set->getExample(i,input,target,weight);
00131             sigma[i] = isotropic_sigma;
00132             if(has_weights)
00133             {
00134                 alpha[i] = weight;
00135                 weight_sum += weight;
00136             }
00137             else
00138                 alpha[i] = default_weight;
00139             // resizeStuffBeforeTraining(); TODO Put back?
00140         }
00141         if(has_weights)
00142             alpha /= weight_sum;
00143         GaussMix::build();
00144         
00145         stage = 1;
00146         // precomputeStuff(); TODO Put back?
00147         build(); // rebuild
00148     }
00149 }
00150 
00151 } // end of namespace PLearn
00152 
00153 
00154 /*
00155   Local Variables:
00156   mode:c++
00157   c-basic-offset:4
00158   c-file-style:"stroustrup"
00159   c-file-offsets:((innamespace . 0)(inline-open . 0))
00160   indent-tabs-mode:nil
00161   fill-column:79
00162   End:
00163 */
00164 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :
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