PLearn 0.1
ExtractVariable.cc
Go to the documentation of this file.
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: ExtractVariable.cc 3994 2005-08-25 13:35:03Z chapados $
00040  * This file is part of the PLearn library.
00041  ******************************************************* */
00042 
00043 #include "ExtendedVariable.h"
00044 #include "ExtractVariable.h"
00045 //#include "Var_utils.h"
00046 
00047 namespace PLearn {
00048 using namespace std;
00049 
00050 
00053 PLEARN_IMPLEMENT_OBJECT(ExtractVariable,
00054                         "Variable extracted from a vector variable.",
00055                         "NO HELP");
00056 
00057 ExtractVariable::ExtractVariable(Variable* v, int the_offset, int the_length, int the_width)
00058     : inherited(v, the_length, the_width),
00059       offset_(the_offset),
00060       length_(the_length),
00061       width_(the_width)
00062 {
00063     build_();
00064 }
00065 
00066 void ExtractVariable::build()
00067 {
00068     inherited::build();
00069     build_();
00070 }
00071 
00072 void ExtractVariable::build_()
00073 {
00074     if (input) {
00075         // input is v from constructor
00076         if(offset_ < 0)
00077             PLERROR("In ExtractVariable: requested matrix is out of bounds");
00078     }
00079 }
00080 
00081 void ExtractVariable::recomputeSize(int& l, int& w) const
00082 { l=length_; w=width_; }
00083 
00084 void ExtractVariable::fprop()
00085 {
00086     real* inputdata = input->valuedata+offset_;
00087     int cnt = min(input->length()-offset_,length()*width());
00088     for(int i=0; i<cnt; i++)
00089     {
00090         valuedata[i] = inputdata[i];
00091     }
00092 }
00093 
00094 
00095 void ExtractVariable::bprop()
00096 {
00097     real* inputgradient = input->gradientdata+offset_;
00098     int cnt = min(input->length()-offset_,length()*width());
00099     for(int i=0; i<cnt; i++)
00100     {
00101         inputgradient[i] += gradientdata[i];
00102     }
00103 
00104 }
00105 
00106 
00107 void ExtractVariable::bbprop()
00108 {
00109     PLERROR("In SVDVariable::bbprop: feature not implemented");
00110 }
00111 
00112 void ExtractVariable::symbolicBprop()
00113 {
00114     PLERROR("In SVDVariable::symbolicBprop: feature not implemented");
00115 }
00116 
00117 
00118 void ExtractVariable::rfprop()
00119 {
00120     PLERROR("In SVDVariable::rfprop: feature not implemented");
00121 }
00122 
00123 } // end of namespace PLearn
00124 
00125 
00126 /*
00127   Local Variables:
00128   mode:c++
00129   c-basic-offset:4
00130   c-file-style:"stroustrup"
00131   c-file-offsets:((innamespace . 0)(inline-open . 0))
00132   indent-tabs-mode:nil
00133   fill-column:79
00134   End:
00135 */
00136 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :
 All Classes Namespaces Files Functions Variables Typedefs Enumerations Enumerator Friends Defines