Matches.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--2012,
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 
00036 #include "PointMatcher.h"
00037 #include "PointMatcherPrivate.h"
00038 
00039 using namespace std;
00040 
00042 template<typename T>
00043 PointMatcher<T>::Matches::Matches() {}
00044 
00046 template<typename T>
00047 PointMatcher<T>::Matches::Matches(const Dists& dists, const Ids ids):
00048         dists(dists),
00049         ids(ids)
00050 {}
00051 
00053 template<typename T>
00054 PointMatcher<T>::Matches::Matches(const int knn, const int pointsCount):
00055         dists(Dists(knn, pointsCount)),
00056         ids(Ids(knn, pointsCount))
00057 {}
00058 
00060 template<typename T>
00061 T PointMatcher<T>::Matches::getDistsQuantile(const T quantile) const
00062 {
00063         // build array
00064         vector<T> values;
00065         values.reserve(dists.rows() * dists.cols());
00066         for (int x = 0; x < dists.cols(); ++x)
00067         {
00068                 for (int y = 0; y < dists.rows(); ++y)
00069                 {
00070                         if (dists(y, x) != numeric_limits<T>::infinity())
00071                         {
00072                                 values.push_back(dists(y, x));
00073                         }
00074                 }
00075         }
00076         if (values.size() == 0)
00077                 throw ConvergenceError("no outlier to filter");
00078 
00079         if (quantile < 0.0 || quantile > 1.0)
00080                 throw ConvergenceError("quantile must be between 0 and 1");
00081 
00082         // get quantile
00083         if (quantile == 1.0)
00084                 return *max_element(values.begin(), values.end());
00085         nth_element(values.begin(), values.begin() + (values.size() * quantile), values.end());
00086         return values[values.size() * quantile];
00087 }
00088 
00090 template<typename T>
00091 T PointMatcher<T>::Matches::getMedianAbsDeviation() const
00092 {
00093         vector<T> values;
00094         values.reserve(dists.rows() * dists.cols());
00095         const long cols = dists.cols();
00096         const long rows = dists.rows();
00097         for (int x = 0; x < cols; ++x)
00098         {
00099                 for (int y = 0; y < rows; ++y)
00100                 {
00101                         if (dists(y, x) != numeric_limits<T>::infinity())
00102                         {
00103                                 values.push_back(dists(y, x));
00104                         }
00105                 }
00106         }
00107         if (values.size() == 0)
00108                 throw ConvergenceError("no outlier to filter");
00109 
00110         nth_element(values.begin(), values.begin() + (values.size() / 2), values.end());
00111         const T median =  values[values.size() / 2];
00112 
00113         // Compute absolute deviation
00114         const unsigned size = values.size();
00115         for (unsigned i = 0; i < size; ++i)
00116         {
00117                 values[i] = fabs(values[i] - median);
00118         }
00119         // Median of the absolute deviation
00120         nth_element(values.begin(), values.begin() + (values.size() / 2), values.end());
00121         return values[values.size() / 2];
00122 }
00123 
00124 template<typename T>
00125 T PointMatcher<T>::Matches::getStandardDeviation() const
00126 {
00127         auto d = dists.array();
00128         return std::sqrt((d - d.mean()).square().sum()/(d.size()-1));
00129 }
00130 
00131 
00132 template struct PointMatcher<float>::Matches;
00133 template struct PointMatcher<double>::Matches;


libpointmatcher
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autogenerated on Thu Jun 20 2019 19:51:31