DistanceLimit.cpp
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00001 // kate: replace-tabs off; indent-width 4; indent-mode normal
00002 // vim: ts=4:sw=4:noexpandtab
00003 /*
00004 
00005 Copyright (c) 2010--2018,
00006 François Pomerleau and Stephane Magnenat, ASL, ETHZ, Switzerland
00007 You can contact the authors at <f dot pomerleau at gmail dot com> and
00008 <stephane at magnenat dot net>
00009 
00010 All rights reserved.
00011 
00012 Redistribution and use in source and binary forms, with or without
00013 modification, are permitted provided that the following conditions are met:
00014     * Redistributions of source code must retain the above copyright
00015       notice, this list of conditions and the following disclaimer.
00016     * Redistributions in binary form must reproduce the above copyright
00017       notice, this list of conditions and the following disclaimer in the
00018       documentation and/or other materials provided with the distribution.
00019     * Neither the name of the <organization> nor the
00020       names of its contributors may be used to endorse or promote products
00021       derived from this software without specific prior written permission.
00022 
00023 THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
00024 ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
00025 WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
00026 DISCLAIMED. IN NO EVENT SHALL ETH-ASL BE LIABLE FOR ANY
00027 DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
00028 (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
00029 LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
00030 ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
00031 (INCLUDING 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 */
00035 #include "DistanceLimit.h"
00036 #include "pointmatcher/Functions.h"
00037 
00038 // DistanceLimitDataPointsFilter
00039 // Constructor
00040 template<typename T>
00041 DistanceLimitDataPointsFilter<T>::DistanceLimitDataPointsFilter(const Parameters& params) :
00042                 PointMatcher<T>::DataPointsFilter("DistanceLimitDataPointsFilter",
00043                                                                                   DistanceLimitDataPointsFilter::availableParameters(), params),
00044                 dim(Parametrizable::get<unsigned>("dim")),
00045                 dist(Parametrizable::get<T>("dist")),
00046                 removeInside(Parametrizable::get<bool>("removeInside"))
00047 {
00048 }
00049 
00050 template<typename T>
00051 typename PointMatcher<T>::DataPoints DistanceLimitDataPointsFilter<T>::filter(
00052         const DataPoints& input)
00053 {
00054         DataPoints output(input);
00055         inPlaceFilter(output);
00056         return output;
00057 }
00058 
00059 // In-place filter
00060 template<typename T>
00061 void DistanceLimitDataPointsFilter<T>::inPlaceFilter(
00062         DataPoints& cloud)
00063 {
00064         using namespace PointMatcherSupport;
00065 
00066         if(dim >= cloud.features.rows() - 1)
00067         {
00068                 throw InvalidParameter(
00069                                 (boost::format("DistanceLimitDataPointsFilter: Error, filtering on dimension number %1%, larger than authorized axis id %2%") % dim % (cloud.features.rows() - 2)).str());
00070         }
00071 
00072         const int nbPointsIn = cloud.features.cols();
00073         const int nbRows = cloud.features.rows();
00074 
00075         int j = 0;
00076         if(dim == -1) // Euclidean distance
00077         {
00078                 const T absMaxDist = anyabs(dist);
00079                 for(int i = 0; i < nbPointsIn; ++i)
00080                 {
00081                         if(removeInside)
00082                         {
00083                                 if(cloud.features.col(i).head(nbRows-1).norm() > absMaxDist)
00084                                 {
00085                                         cloud.setColFrom(j, cloud, i);
00086                                         ++j;
00087                                 }
00088                         }
00089                         else
00090                         {
00091                                 if(cloud.features.col(i).head(nbRows-1).norm() < absMaxDist)
00092                                 {
00093                                         cloud.setColFrom(j, cloud, i);
00094                                         ++j;
00095                                 }
00096                         }
00097                 }
00098         }
00099         else // Single-axis distance
00100         {
00101                 for(int i = 0; i < nbPointsIn; ++i)
00102                 {
00103                         if(removeInside)
00104                         {
00105                                 if((cloud.features(dim, i)) > dist)
00106                                 {
00107                                         cloud.setColFrom(j, cloud, i);
00108                                         ++j;
00109                                 }
00110                         }
00111                         else
00112                         {
00113                                 if((cloud.features(dim, i)) < dist)
00114                                 {
00115                                         cloud.setColFrom(j, cloud, i);
00116                                         ++j;
00117                                 }
00118                         }
00119                 }
00120         }
00121 
00122         cloud.conservativeResize(j);
00123 }
00124 
00125 template struct DistanceLimitDataPointsFilter<float>;
00126 template struct DistanceLimitDataPointsFilter<double>;


libpointmatcher
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autogenerated on Thu Jun 20 2019 19:51:29