PLearn 0.1
SVDVariable.cc
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00001 // -*- C++ -*-
00002 
00003 // PLearn (A C++ Machine Learning Library)
00004 // Copyright (C) 1998 Pascal Vincent
00005 // Copyright (C) 1999-2002 Pascal Vincent, Yoshua Bengio, Rejean Ducharme and University of Montreal
00006 // Copyright (C) 2001-2002 Nicolas Chapados, Ichiro Takeuchi, Jean-Sebastien Senecal
00007 // Copyright (C) 2002 Xiangdong Wang, Christian Dorion
00008 
00009 // Redistribution and use in source and binary forms, with or without
00010 // modification, are permitted provided that the following conditions are met:
00011 // 
00012 //  1. Redistributions of source code must retain the above copyright
00013 //     notice, this list of conditions and the following disclaimer.
00014 // 
00015 //  2. Redistributions in binary form must reproduce the above copyright
00016 //     notice, this list of conditions and the following disclaimer in the
00017 //     documentation and/or other materials provided with the distribution.
00018 // 
00019 //  3. The name of the authors may not be used to endorse or promote
00020 //     products derived from this software without specific prior written
00021 //     permission.
00022 // 
00023 // THIS SOFTWARE IS PROVIDED BY THE AUTHORS ``AS IS'' AND ANY EXPRESS OR
00024 // IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
00025 // OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN
00026 // NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
00027 // SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED
00028 // TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
00029 // PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
00030 // LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
00031 // NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
00032 // SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
00033 // 
00034 // This file is part of the PLearn library. For more information on the PLearn
00035 // library, go to the PLearn Web site at www.plearn.org
00036 
00037 
00038 /* *******************************************************      
00039  * $Id: SVDVariable.cc 3994 2005-08-25 13:35:03Z chapados $
00040  * This file is part of the PLearn library.
00041  ******************************************************* */
00042 
00043 #include "SVDVariable.h"
00044 #include "Var_operators.h"
00045 #include <plearn/math/plapack.h>
00046 
00047 namespace PLearn {
00048 using namespace std;
00049 
00050 
00053 PLEARN_IMPLEMENT_OBJECT(SVDVariable, "A SVD decomposition variable.", 
00054                         "This variable does SVD decomposition of the input matrix variable A=U.D.Vt\n"
00055                         "The resulting U,D,Vt of the decomposition are stored in a vector as folows:\n"
00056                         "   - the first MxM elements of the vector are the elements of U\n"
00057                         "   - the following NxN elements are the elemets of Vt\n"
00058                         "   - the remaining min(M,N) elements are the elemets of D\n");
00059 
00060 SVDVariable::SVDVariable(Variable* input)
00061     : inherited(input, input->length()*input->length()+input->width()*input->width()+min(input->length(),input->width()),1), 
00062       m(input->length()),
00063       n(input->width())
00064 {
00065     input_copy.resize(input->length(), input->width());
00066 }
00067 
00068 void SVDVariable::recomputeSize(int& l, int& w) const
00069 {
00070     if (input) {
00071         l = m*m+n*n+min(m,n);
00072         w = 1;
00073     } else
00074         l = w = 0;
00075 }
00076 
00077 
00078 void SVDVariable::fprop()
00079 {
00080     input_copy << input->matValue ;
00081 
00082     U = value->subVec(0,m*m)->toMat(m,m);
00083     Vt = value->subVec(m*m,n*n)->toMat(n,n);
00084     S = value->subVec(m*m+n*n,min(m,n));
00085 
00086     SVD(input_copy,U,S,Vt);
00087 }
00088 
00089 
00090 void SVDVariable::bprop() {}
00091 
00092 void SVDVariable::symbolicBprop()
00093 {
00094     PLERROR("In SVDVariable::symbolicBprop: feature not implemented");
00095 }
00096 
00097 
00098 void SVDVariable::rfprop()
00099 {
00100     PLERROR("In SVDVariable::rfprop: feature not implemented");
00101 }
00102 
00103 
00104 
00105 } // end of namespace PLearn
00106 
00107 
00108 /*
00109   Local Variables:
00110   mode:c++
00111   c-basic-offset:4
00112   c-file-style:"stroustrup"
00113   c-file-offsets:((innamespace . 0)(inline-open . 0))
00114   indent-tabs-mode:nil
00115   fill-column:79
00116   End:
00117 */
00118 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :
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