PLearn 0.1
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00001 // -*- C++ -*- 00002 00003 // StochasticBinarizeVMatrix.cc 00004 // 00005 // Copyright (C) 2008 Olivier Delalleau 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: Olivier Delalleau 00036 00040 #include "StochasticBinarizeVMatrix.h" 00041 #include <plearn/vmat/ShiftAndRescaleVMatrix.h> 00042 00043 namespace PLearn { 00044 using namespace std; 00045 00046 PLEARN_IMPLEMENT_OBJECT( 00047 StochasticBinarizeVMatrix, 00048 "Transform its source data into stochastically sampled binary data.", 00049 "Each column of the source data is first rescaled into the [0, 1] range,\n" 00050 "then when accessing a sample, each variable is taken to be 1 with\n" 00051 "probability given by its real value (and 0 otherwise). Constant columns\n" 00052 "are given a uniform distribution in {0, 1}.\n" 00053 "Since sampling is performed every time a sample is accessed, one should\n" 00054 "precompute the data if a constant dataset is desired.\n" 00055 "In the current implementation, only the input part is binarized." 00056 ); 00057 00059 // StochasticBinarizeVMatrix // 00061 StochasticBinarizeVMatrix::StochasticBinarizeVMatrix(): 00062 rescale_to_0_1(true), 00063 seed(1827), 00064 random_gen(new PRandom()) 00065 { 00066 } 00067 00069 // declareOptions // 00071 void StochasticBinarizeVMatrix::declareOptions(OptionList& ol) 00072 { 00073 declareOption(ol, "rescale_to_0_1", 00074 &StochasticBinarizeVMatrix::rescale_to_0_1, 00075 OptionBase::buildoption, 00076 "Whether to rescale to [0,1] before sampling. If set to False, then\n" 00077 "the data is assumed to already be in the [0,1] range (no check will\n" 00078 "be performed to enforce it, though)."); 00079 00080 declareOption(ol, "seed", &StochasticBinarizeVMatrix::seed, 00081 OptionBase::buildoption, 00082 "Seed of random number generator."); 00083 00084 // Now call the parent class' declareOptions 00085 inherited::declareOptions(ol); 00086 } 00087 00089 // build // 00091 void StochasticBinarizeVMatrix::build() 00092 { 00093 inherited::build(); 00094 build_(); 00095 } 00096 00098 // build_ // 00100 void StochasticBinarizeVMatrix::build_() 00101 { 00102 if (source) { 00103 if (rescale_to_0_1) { 00104 PP<ShiftAndRescaleVMatrix> rd = 00105 new ShiftAndRescaleVMatrix(source, false); 00106 rd->min_max = Vec(2); 00107 rd->min_max[1] = 1; 00108 rd->build(); 00109 rescaled_data = get_pointer(rd); 00110 } else 00111 rescaled_data = source; 00112 setMetaInfoFromSource(); 00113 } 00114 random_gen->manual_seed(seed); 00115 } 00116 00118 // getNewRow // 00120 void StochasticBinarizeVMatrix::getNewRow(int i, const Vec& v) const 00121 { 00122 rescaled_data->getRow(i, v); 00123 for (int j = 0; j < source->inputsize(); j++) 00124 v[j] = random_gen->uniform_sample() <= v[j] ? 1 : 0; 00125 } 00126 00128 // makeDeepCopyFromShallowCopy // 00130 void StochasticBinarizeVMatrix::makeDeepCopyFromShallowCopy(CopiesMap& copies) 00131 { 00132 inherited::makeDeepCopyFromShallowCopy(copies); 00133 00134 // ### Call deepCopyField on all "pointer-like" fields 00135 // ### that you wish to be deepCopied rather than 00136 // ### shallow-copied. 00137 // ### ex: 00138 // deepCopyField(trainvec, copies); 00139 00140 // ### Remove this line when you have fully implemented this method. 00141 PLERROR("StochasticBinarizeVMatrix::makeDeepCopyFromShallowCopy not fully (correctly) implemented yet!"); 00142 } 00143 00144 } // end of namespace PLearn 00145 00146 00147 /* 00148 Local Variables: 00149 mode:c++ 00150 c-basic-offset:4 00151 c-file-style:"stroustrup" 00152 c-file-offsets:((innamespace . 0)(inline-open . 0)) 00153 indent-tabs-mode:nil 00154 fill-column:79 00155 End: 00156 */ 00157 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :