PLearn 0.1
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00001 // -*- C++ -*- 00002 00003 // SoftHistogramBinner.cc 00004 // 00005 // Copyright (C) 2004 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 /* ******************************************************* 00036 * $Id: SoftHistogramBinner.cc 6861 2007-04-09 19:04:15Z saintmlx $ 00037 ******************************************************* */ 00038 00039 // Authors: Olivier Delalleau 00040 00044 #include "SoftHistogramBinner.h" 00045 00046 namespace PLearn { 00047 using namespace std; 00048 00050 // SoftHistogramBinner // 00052 SoftHistogramBinner::SoftHistogramBinner() 00053 /* ### Initialize all fields to their default value */ 00054 { 00055 // ... 00056 // ### You may or may not want to call build_() to finish building the object 00057 // build_(); 00058 } 00059 00060 PLEARN_IMPLEMENT_OBJECT(SoftHistogramBinner, 00061 "Computes bins which may overlap, but contain the same number of elements.", 00062 "This binner does not compute a mapping to each bin, because a sample may\n" 00063 "appear in different bins. Instead, one should use it directly through the\n" 00064 "getBins() method.\n" 00065 "The number of bins is given through the 'n_bins' option. The bins split\n" 00066 "uniformly the interval [min_val, max_val] defined by the data. Each bin\n" 00067 "contains 'samples_per_bin' samples (if this value is >= 1), or this fraction\n" 00068 "of the total number of samples (if it is < 1). The value '-1' can be used\n" 00069 "to specify that each bin contains all samples (though this is probably\n" 00070 "not very useful).\n" 00071 ); 00072 00074 // declareOptions // 00076 void SoftHistogramBinner::declareOptions(OptionList& ol) 00077 { 00078 declareOption(ol, "samples_per_bin", &SoftHistogramBinner::samples_per_bin, OptionBase::buildoption, 00079 "The number of samples in each bin (if >= 1), or as a fraction (if < 1)."); 00080 00081 declareOption(ol, "n_bins", &SoftHistogramBinner::n_bins, OptionBase::buildoption, 00082 "The number of bins computed."); 00083 00084 // Now call the parent class' declareOptions 00085 inherited::declareOptions(ol); 00086 } 00087 00089 // build // 00091 void SoftHistogramBinner::build() 00092 { 00093 inherited::build(); 00094 build_(); 00095 } 00096 00098 // build_ // 00100 void SoftHistogramBinner::build_() 00101 { 00102 // ### This method should do the real building of the object, 00103 // ### according to set 'options', in *any* situation. 00104 // ### Typical situations include: 00105 // ### - Initial building of an object from a few user-specified options 00106 // ### - Building of a "reloaded" object: i.e. from the complete set of all serialised options. 00107 // ### - Updating or "re-building" of an object after a few "tuning" options have been modified. 00108 // ### You should assume that the parent class' build_() has already been called. 00109 00110 // Check validity of the 'samples_per_bin' option. 00111 if (!is_equal(samples_per_bin, -1) && 00112 !(samples_per_bin >= 0 && samples_per_bin < 1) && 00113 !(samples_per_bin >= 1 && fabs(samples_per_bin - int(samples_per_bin)) < 1e-8)) 00114 PLERROR("In SoftHistogramBinner::build_ - Invalid value for 'samples_per_bin'"); 00115 } 00116 00118 // getBins // 00120 TVec< TVec<int> > SoftHistogramBinner::getBins(const Vec& v) const { 00121 // Find out how many samples we have in each bin. 00122 int n; 00123 if (is_equal(samples_per_bin, -1)) 00124 n = v.length(); 00125 else if (samples_per_bin < 1) 00126 n = int(samples_per_bin * v.length()); 00127 else 00128 n = int(round(samples_per_bin)); 00129 if (n == 0) 00130 PLERROR("In SoftHistogramBinner::getBins - You can't ask for empty bins"); 00131 // Sort the data to make things easier. 00132 Mat w(v.length(), 2); 00133 w.column(0) << v; 00134 w.column(1) << TVec<int>(0, w.length() - 1, 1); 00135 sortRows(w); 00136 // Construct bins. 00137 TVec< TVec<int> > bins(n_bins); 00138 real min_w = w(0,0); 00139 real max_w = w(w.length() - 1, 0); 00140 real bin_width = (max_w - min_w) / real(n_bins); 00141 for (int i = 0; i < n_bins; i++) { 00142 real bin_left = min_w + i * bin_width; 00143 real bin_right = bin_left + bin_width; 00144 real bin_mid = (bin_left + bin_right) / 2; // Center of the bin. 00145 // Find data point closest to bin_mid. 00146 int k = 0; 00147 int min; 00148 while (bin_mid > w(k,0)) k++; 00149 if (w(k,0) - bin_mid > bin_mid - w(k-1,0)) 00150 min = k -1; 00151 else 00152 min = k; 00153 bins[i].append(int(w(min, 1))); 00154 // Expand to get n samples in the bin. 00155 int count = 1; 00156 int right = min; 00157 int left = min; 00158 int to_add; 00159 while (count < n) { 00160 if (right + 1 < w.length()) { 00161 // We can get more data on our right. 00162 if (left - 1 >= 0) { 00163 // We can get more data on our left. 00164 if (w(right + 1,0) - bin_mid < bin_mid - w(left - 1,0)) { 00165 // Next point to add is on our right. 00166 right++; 00167 to_add = right; 00168 } else { 00169 // Next point to add is on our left. 00170 left--; 00171 to_add = left; 00172 } 00173 } else { 00174 // No more data on the left. 00175 right++; 00176 to_add = right; 00177 } 00178 } else { 00179 // No more data on the right. 00180 left--; 00181 to_add = left; 00182 } 00183 bins[i].append(int(w(to_add, 1))); 00184 count++; 00185 } 00186 } 00187 return bins; 00188 } 00189 00191 // makeDeepCopyFromShallowCopy // 00193 void SoftHistogramBinner::makeDeepCopyFromShallowCopy(CopiesMap& copies) 00194 { 00195 inherited::makeDeepCopyFromShallowCopy(copies); 00196 00197 // ### Call deepCopyField on all "pointer-like" fields 00198 // ### that you wish to be deepCopied rather than 00199 // ### shallow-copied. 00200 // ### ex: 00201 // deepCopyField(trainvec, copies); 00202 00203 // ### Remove this line when you have fully implemented this method. 00204 PLERROR("SoftHistogramBinner::makeDeepCopyFromShallowCopy not fully (correctly) implemented yet!"); 00205 } 00206 00208 // nBins // 00210 int SoftHistogramBinner::nBins() const { 00211 return n_bins; 00212 } 00213 00214 } // end of namespace PLearn 00215 00216 00217 /* 00218 Local Variables: 00219 mode:c++ 00220 c-basic-offset:4 00221 c-file-style:"stroustrup" 00222 c-file-offsets:((innamespace . 0)(inline-open . 0)) 00223 indent-tabs-mode:nil 00224 fill-column:79 00225 End: 00226 */ 00227 // vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :