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Point Cloud Library (PCL)
1.6.0
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00001 /* 00002 * Software License Agreement (BSD License) 00003 * 00004 * Copyright (c) 2009, Willow Garage, Inc. 00005 * All rights reserved. 00006 * 00007 * Redistribution and use in source and binary forms, with or without 00008 * modification, are permitted provided that the following conditions 00009 * are met: 00010 * 00011 * * Redistributions of source code must retain the above copyright 00012 * notice, this list of conditions and the following disclaimer. 00013 * * Redistributions in binary form must reproduce the above 00014 * copyright notice, this list of conditions and the following 00015 * disclaimer in the documentation and/or other materials provided 00016 * with the distribution. 00017 * * Neither the name of Willow Garage, Inc. nor the names of its 00018 * contributors may be used to endorse or promote products derived 00019 * from this software without specific prior written permission. 00020 * 00021 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS 00022 * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT 00023 * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS 00024 * FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE 00025 * COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, 00026 * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, 00027 * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; 00028 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER 00029 * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT 00030 * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN 00031 * ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE 00032 * POSSIBILITY OF SUCH DAMAGE. 00033 * 00034 * $Id: random_sample.hpp 5026 2012-03-12 02:51:44Z rusu $ 00035 * 00036 */ 00037 00038 #ifndef PCL_FILTERS_IMPL_RANDOM_SAMPLE_H_ 00039 #define PCL_FILTERS_IMPL_RANDOM_SAMPLE_H_ 00040 00041 #include <pcl/filters/random_sample.h> 00042 00043 00045 template<typename PointT> void 00046 pcl::RandomSample<PointT>::applyFilter (PointCloud &output) 00047 { 00048 unsigned N = static_cast<unsigned> (input_->size ()); 00049 float one_over_N = 1.0f / float (N); 00050 00051 // If sample size is 0 or if the sample size is greater then input cloud size 00052 // then return entire copy of cloud 00053 if (sample_ >= N) 00054 { 00055 output = *input_; 00056 } 00057 else 00058 { 00059 // Resize output cloud to sample size 00060 output.points.resize (sample_); 00061 output.width = sample_; 00062 output.height = 1; 00063 00064 // Set random seed so derived indices are the same each time the filter runs 00065 std::srand (seed_); 00066 00067 unsigned top = N - sample_; 00068 unsigned i = 0; 00069 unsigned index = 0; 00070 00071 // Algorithm A 00072 for (size_t n = sample_; n >= 2; n--) 00073 { 00074 unsigned int V = unifRand (); 00075 unsigned S = 0; 00076 float quot = float (top) * one_over_N; 00077 while (quot > V) 00078 { 00079 S++; 00080 top--; 00081 N--; 00082 quot = quot * float (top) * one_over_N; 00083 } 00084 index += S; 00085 output.points[i++] = input_->points[index++]; 00086 N--; 00087 } 00088 00089 index += N * static_cast<unsigned> (unifRand ()); 00090 output.points[i++] = input_->points[index++]; 00091 } 00092 } 00093 00095 template<typename PointT> 00096 void 00097 pcl::RandomSample<PointT>::applyFilter (std::vector<int> &indices) 00098 { 00099 unsigned N = static_cast<unsigned> (input_->size ()); 00100 float one_over_N = 1.0f / float (N); 00101 00102 // If sample size is 0 or if the sample size is greater then input cloud size 00103 // then return all indices 00104 if (sample_ >= N) 00105 { 00106 indices = *indices_; 00107 } 00108 else 00109 { 00110 // Resize output indices to sample size 00111 indices.resize (sample_); 00112 00113 // Set random seed so derived indices are the same each time the filter runs 00114 std::srand (seed_); 00115 00116 // Algorithm A 00117 unsigned top = N - sample_; 00118 unsigned i = 0; 00119 unsigned index = 0; 00120 00121 for (size_t n = sample_; n >= 2; n--) 00122 { 00123 unsigned int V = unifRand (); 00124 unsigned S = 0; 00125 float quot = float (top) * one_over_N; 00126 while (quot > V) 00127 { 00128 S++; 00129 top--; 00130 N--; 00131 quot = quot * float (top) * one_over_N; 00132 } 00133 index += S; 00134 indices[i++] = (*indices_)[index++]; 00135 N--; 00136 } 00137 00138 index += N * static_cast<unsigned> (unifRand ()); 00139 indices[i++] = (*indices_)[index++]; 00140 } 00141 } 00142 00143 #define PCL_INSTANTIATE_RandomSample(T) template class PCL_EXPORTS pcl::RandomSample<T>; 00144 00145 #endif // PCL_FILTERS_IMPL_RANDOM_SAMPLE_H_
1.7.6.1