133 lines
3.6 KiB
C++
133 lines
3.6 KiB
C++
/* ----------------------------------------------------------------------------
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* GTSAM Copyright 2010, Georgia Tech Research Corporation,
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* Atlanta, Georgia 30332-0415
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* All Rights Reserved
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* Authors: Frank Dellaert, et al. (see THANKS for the full author list)
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* See LICENSE for the license information
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* -------------------------------------------------------------------------- */
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/**
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* @file timeGaussianFactor.cpp
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* @brief time JacobianFactor.eliminate
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* @author Alireza Fathi
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*/
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#include <time.h>
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/*STL/C++*/
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#include <iostream>
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using namespace std;
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#include <gtsam/base/Matrix.h>
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#include <gtsam/linear/JacobianFactor.h>
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#include <gtsam/linear/JacobianFactor.h>
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#include <gtsam/linear/GaussianConditional.h>
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#include <gtsam/linear/NoiseModel.h>
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using namespace gtsam;
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static const Key _x1_=1, _x2_=2, _l1_=3;
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/*
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* Alex's Machine
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* Results for Eliminate:
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* Initial (1891): 17.91 sec, 55834.7 calls/sec
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* NoiseQR : 11.69 sec
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*
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* Results for matrix_augmented:
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* Initial (1891) : 0.85 sec, 1.17647e+06 calls/sec
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* int->size_t Version : 8.45 sec (for n1 reps) with memcpy version of collect()
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* w/ original collect(): 8.73 sec (for n1 reps)
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* b memcpy Version : 8.64 sec (for n1 reps) with original version of collect()
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* w/ memcpy collect() : 8.40 sec (for n1 reps)
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* Rev 2100 : 8.15 sec
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*/
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int main()
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{
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// create a linear factor
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Matrix Ax2 = (Matrix(8, 2) <<
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// x2
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-5., 0.,
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+0.,-5.,
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10., 0.,
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+0.,10.,
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-5., 0.,
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+0.,-5.,
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10., 0.,
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+0.,10.
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).finished();
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Matrix Al1 = (Matrix(8, 10) <<
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// l1
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5., 0.,1.,2.,3.,4.,5.,6.,7.,8.,
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0., 5.,1.,2.,3.,4.,5.,6.,7.,8.,
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0., 0.,1.,2.,3.,4.,5.,6.,7.,8.,
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0., 0.,1.,2.,3.,4.,5.,6.,7.,8.,
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5., 0.,1.,2.,3.,4.,5.,6.,7.,8.,
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0., 5.,1.,2.,3.,4.,5.,6.,7.,8.,
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0., 0.,1.,2.,3.,4.,5.,6.,7.,8.,
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0., 0.,1.,2.,3.,4.,5.,6.,7.,8.
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).finished();
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Matrix Ax1 = (Matrix(8, 2) <<
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// x1
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0.00, 0.,1.,2.,3.,4.,5.,6.,7.,8.,
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0.00, 0.,1.,2.,3.,4.,5.,6.,7.,8.,
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-10., 0.,1.,2.,3.,4.,5.,6.,7.,8.,
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0.00,-10.,1.,2.,3.,4.,5.,6.,7.,8.,
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0.00, 0.,1.,2.,3.,4.,5.,6.,7.,8.,
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0.00, 0.,1.,2.,3.,4.,5.,6.,7.,8.,
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-10., 0.,1.,2.,3.,4.,5.,6.,7.,8.,
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0.00,-10.,1.,2.,3.,4.,5.,6.,7.,8.
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).finished();
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// and a RHS
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Vector b2(8);
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b2(0) = -1;
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b2(1) = 1.5;
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b2(2) = 2;
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b2(3) = -1;
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b2(4) = -1;
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b2(5) = 1.5;
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b2(6) = 2;
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b2(7) = -1;
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// time eliminate
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JacobianFactor combined(_x2_, Ax2, _l1_, Al1, _x1_, Ax1, b2, noiseModel::Isotropic::Sigma(8,1));
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long timeLog = clock();
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int n = 1000000;
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GaussianConditional::shared_ptr conditional;
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JacobianFactor::shared_ptr factor;
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for(int i = 0; i < n; i++)
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std::tie(conditional, factor) =
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JacobianFactor(combined).eliminate(Ordering{_x2_});
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long timeLog2 = clock();
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double seconds = (double)(timeLog2-timeLog)/CLOCKS_PER_SEC;
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cout << "Single Eliminate Timing:" << endl;
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cout << seconds << " seconds" << endl;
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cout << ((double)n/seconds) << " calls/second" << endl;
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// time matrix_augmented
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// const Ordering ordering{_x2_, _l1_, _x1_};
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// size_t n1 = 10000000;
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// timeLog = clock();
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//
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// for(size_t i = 0; i < n1; i++)
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// Matrix Ab = combined.matrix_augmented(ordering, true);
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//
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// timeLog2 = clock();
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// seconds = (double)(timeLog2-timeLog)/CLOCKS_PER_SEC;
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// cout << "matrix_augmented Timing:" << endl;
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// cout << seconds << " seconds" << endl;
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// cout << ((double)n/seconds) << " calls/second" << endl;
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return 0;
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}
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