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GainMatrixSmootherTests.cpp
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1 // This file is part of the Acts project.
2 //
3 // Copyright (C) 2019 CERN for the benefit of the Acts project
4 //
5 // This Source Code Form is subject to the terms of the Mozilla Public
6 // License, v. 2.0. If a copy of the MPL was not distributed with this
7 // file, You can obtain one at http://mozilla.org/MPL/2.0/.
8 
9 #include <boost/test/unit_test.hpp>
10 
11 #include "Acts/EventData/Measurement.hpp"
12 #include "Acts/EventData/MeasurementHelpers.hpp"
13 #include "Acts/Surfaces/CylinderSurface.hpp"
14 #include "Acts/Tests/CommonHelpers/FloatComparisons.hpp"
15 #include "Acts/TrackFitting/GainMatrixSmoother.hpp"
16 #include "Acts/Utilities/ParameterDefinitions.hpp"
17 
18 #include <memory>
19 
20 #include <boost/optional/optional_io.hpp>
21 
22 namespace Acts {
23 namespace Test {
24 
25 using Jacobian = BoundMatrix;
26 using Covariance = BoundSymMatrix;
27 using SourceLink = MinimalSourceLink;
28 template <BoundIndices... params>
29 using MeasurementType = Measurement<SourceLink, BoundIndices, params...>;
30 
31 // Create a test context
32 GeometryContext tgContext = GeometryContext();
33 
34 BOOST_AUTO_TEST_CASE(gain_matrix_smoother) {
35  // Make dummy measurement
36  auto plane1 = Surface::makeShared<PlaneSurface>(Vector3D::UnitX() * 1,
37  Vector3D::UnitX());
38  auto plane2 = Surface::makeShared<PlaneSurface>(Vector3D::UnitX() * 2,
39  Vector3D::UnitX());
40  auto plane3 = Surface::makeShared<PlaneSurface>(Vector3D::UnitX() * 3,
41  Vector3D::UnitX());
42 
43  SymMatrix2D cov;
44  cov << 0.04, 0, 0, 0.1;
45  FittableMeasurement<SourceLink> meas1(
46  MeasurementType<BoundIndices::eBoundLoc0, BoundIndices::eBoundLoc1>(
47  plane1, {}, std::move(cov), -0.1, 0.45));
48 
49  cov << 0.04, 0, 0, 0.1;
50  FittableMeasurement<SourceLink> meas2(
51  MeasurementType<BoundIndices::eBoundLoc0, BoundIndices::eBoundLoc1>(
52  plane2, {}, std::move(cov), -0.2, 0.35));
53 
54  cov << 0.04, 0, 0, 0.1;
55  FittableMeasurement<SourceLink> meas3(
56  MeasurementType<BoundIndices::eBoundLoc0, BoundIndices::eBoundLoc1>(
57  plane3, {}, std::move(cov), -0.05, 0.25));
58 
59  MultiTrajectory<SourceLink> traj;
60 
61  size_t ts_idx;
62 
63  ts_idx = traj.addTrackState(TrackStatePropMask::All);
64  auto ts = traj.getTrackState(ts_idx);
65  ts.setReferenceSurface(plane1);
66 
67  // Make dummy track parameter
68  Covariance covTrk;
69  covTrk.setIdentity();
70  covTrk.diagonal() << 0.08, 0.3, 1, 1, 1, 1;
71  BoundVector parValues;
72  parValues << 0.3, 0.5, 0.5 * M_PI, 0., 1 / 100., 0.;
73 
74  ts.predicted() = parValues;
75  ts.predictedCovariance() = covTrk;
76 
77  parValues << 0.301, 0.503, 0.5 * M_PI, 0., 1 / 100., 0.;
78 
79  ts.filtered() = parValues;
80  ts.filteredCovariance() = covTrk;
81  ts.pathLength() = 1.;
82  ts.jacobian().setIdentity();
83 
84  ts_idx = traj.addTrackState(TrackStatePropMask::All, ts_idx);
85  ts = traj.getTrackState(ts_idx);
86  ts.setReferenceSurface(plane2);
87 
88  parValues << 0.2, 0.5, 0.5 * M_PI, 0., 1 / 100., 0.;
89  ts.predicted() = parValues;
90  ts.predictedCovariance() = covTrk;
91 
92  parValues << 0.27, 0.53, 0.5 * M_PI, 0., 1 / 100., 0.;
93  ts.filtered() = parValues;
94  ts.filteredCovariance() = covTrk;
95  ts.pathLength() = 2.;
96  ts.jacobian().setIdentity();
97 
98  ts_idx = traj.addTrackState(TrackStatePropMask::All, ts_idx);
99  ts = traj.getTrackState(ts_idx);
100  ts.setReferenceSurface(plane3);
101 
102  parValues << 0.35, 0.49, 0.5 * M_PI, 0., 1 / 100., 0.;
103  ts.predicted() = parValues;
104  ts.predictedCovariance() = covTrk;
105 
106  parValues << 0.33, 0.43, 0.5 * M_PI, 0., 1 / 100., 0.;
107  ts.filtered() = parValues;
108  ts.filteredCovariance() = covTrk;
109  ts.pathLength() = 3.;
110  ts.jacobian().setIdentity();
111 
112  // "smooth" these three track states
113 
114  GainMatrixSmoother gms;
115  BOOST_CHECK(gms(tgContext, traj, ts_idx).ok());
116 
117  // Regression tests, only tests very basic correctness of the math, but tests
118  // for regressions in the result.
119 
120  auto ts1 = traj.getTrackState(0);
121  BOOST_CHECK(ts1.hasSmoothed());
122  BOOST_CHECK_NE(ts1.filtered(), ts1.smoothed());
123 
124  double tol = 1e-6;
125 
126  BoundVector expPars;
127  expPars << 0.3510000, 0.4730000, 1.5707963, 0.0000000, 0.0100000, 0.0000000;
128  CHECK_CLOSE_ABS(ts1.smoothed(), expPars, tol);
129  Covariance expCov;
130  expCov.setIdentity();
131  expCov.diagonal() << 0.0800000, 0.3000000, 1.0000000, 1.0000000, 1.0000000,
132  1.0000000;
133  CHECK_CLOSE_ABS(ts1.smoothedCovariance(), expCov, tol);
134 
135  auto ts2 = traj.getTrackState(1);
136  BOOST_CHECK(ts2.hasSmoothed());
137  BOOST_CHECK_NE(ts2.filtered(), ts2.smoothed());
138 
139  expPars << 0.2500000, 0.4700000, 1.5707963, 0.0000000, 0.0100000, 0.0000000;
140  CHECK_CLOSE_ABS(ts2.smoothed(), expPars, tol);
141  CHECK_CLOSE_ABS(ts2.smoothedCovariance(), expCov, tol);
142 
143  auto ts3 = traj.getTrackState(2);
144  BOOST_CHECK(ts3.hasSmoothed());
145  // last one, smoothed == filtered
146  BOOST_CHECK_EQUAL(ts3.filtered(), ts3.smoothed());
147 
148  expPars << 0.3300000, 0.4300000, 1.5707963, 0.0000000, 0.0100000, 0.0000000;
149  CHECK_CLOSE_ABS(ts3.smoothed(), expPars, tol);
150  CHECK_CLOSE_ABS(ts3.smoothedCovariance(), expCov, tol);
151 }
152 
153 } // namespace Test
154 } // namespace Acts