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Avoid auto for Eigen expressions. (#899) 

While harmless in most cases, auto can delay evaluation
of expressions in unexpected ways.
So it is better to avoid auto for Eigen expressions.
https://eigen.tuxfamily.org/dox/TopicPitfalls.html
master
gaschler 2018-02-13 12:34:43 +01:00 committed by Wally B. Feed
parent 2a74484be1
commit 7448f93b50
13 changed files with 20 additions and 17 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
cartographer/internal/mapping_3d/local_trajectory_builder.cc
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@ -229,7 +229,7 @@ LocalTrajectoryBuilder::InsertIntoSubmap(
} }
active_submaps_.InsertRangeData(filtered_range_data_in_local, active_submaps_.InsertRangeData(filtered_range_data_in_local,
gravity_alignment); gravity_alignment);
const auto rotational_scan_matcher_histogram = const Eigen::VectorXf rotational_scan_matcher_histogram =
scan_matching::RotationalScanMatcher::ComputeHistogram( scan_matching::RotationalScanMatcher::ComputeHistogram(
sensor::TransformPointCloud( sensor::TransformPointCloud(
filtered_range_data_in_tracking.returns, filtered_range_data_in_tracking.returns,

5
cartographer/io/outlier_removing_points_processor.cc
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@ -94,7 +94,7 @@ void OutlierRemovingPointsProcessor::ProcessInPhaseTwo(
const Eigen::Vector3f delta = batch.points[i] - batch.origin; const Eigen::Vector3f delta = batch.points[i] - batch.origin;
const float length = delta.norm(); const float length = delta.norm();
for (float x = 0; x < length; x += voxel_size_) { for (float x = 0; x < length; x += voxel_size_) {
const auto index = const Eigen::Array3i index =
voxels_.GetCellIndex(batch.origin + (x / length) * delta); voxels_.GetCellIndex(batch.origin + (x / length) * delta);
if (voxels_.value(index).hits > 0) { if (voxels_.value(index).hits > 0) {
++voxels_.mutable_value(index)->rays; ++voxels_.mutable_value(index)->rays;
@ -108,7 +108,8 @@ void OutlierRemovingPointsProcessor::ProcessInPhaseThree(
constexpr double kMissPerHitLimit = 3; constexpr double kMissPerHitLimit = 3;
std::unordered_set<int> to_remove; std::unordered_set<int> to_remove;
for (size_t i = 0; i < batch->points.size(); ++i) { for (size_t i = 0; i < batch->points.size(); ++i) {
const auto voxel = voxels_.value(voxels_.GetCellIndex(batch->points[i])); const VoxelData voxel =
voxels_.value(voxels_.GetCellIndex(batch->points[i]));
if (!(voxel.rays < kMissPerHitLimit * voxel.hits)) { if (!(voxel.rays < kMissPerHitLimit * voxel.hits)) {
to_remove.insert(i); to_remove.insert(i);
} }

4
cartographer/io/probability_grid_points_processor.cc
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@ -134,9 +134,9 @@ std::unique_ptr<Image> DrawProbabilityGrid(
} }
auto image = common::make_unique<Image>(cell_limits.num_x_cells, auto image = common::make_unique<Image>(cell_limits.num_x_cells,
cell_limits.num_y_cells); cell_limits.num_y_cells);
for (const auto& xy_index : for (const Eigen::Array2i& xy_index :
cartographer::mapping_2d::XYIndexRangeIterator(cell_limits)) { cartographer::mapping_2d::XYIndexRangeIterator(cell_limits)) {
const auto index = xy_index + *offset; const Eigen::Array2i index = xy_index + *offset;
constexpr uint8 kUnknownValue = 128; constexpr uint8 kUnknownValue = 128;
const uint8 value = const uint8 value =
probability_grid.IsKnown(index) probability_grid.IsKnown(index)

3
cartographer/io/xray_points_processor.cc
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@ -149,7 +149,8 @@ void XRayPointsProcessor::WriteVoxels(const Aggregation& aggregation,
} }
// Returns the (x, y) pixel of the given 'index'. // Returns the (x, y) pixel of the given 'index'.
const auto voxel_index_to_pixel = [this](const Eigen::Array3i& index) { const auto voxel_index_to_pixel =
[this](const Eigen::Array3i& index) -> Eigen::Array2i {
// We flip the y axis, since matrices rows are counted from the top. // We flip the y axis, since matrices rows are counted from the top.
return Eigen::Array2i(bounding_box_.max()[1] - index[1], return Eigen::Array2i(bounding_box_.max()[1] - index[1],
bounding_box_.max()[2] - index[2]); bounding_box_.max()[2] - index[2]);

2
cartographer/mapping_3d/scan_matching/ceres_scan_matcher_test.cc
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@ -37,7 +37,7 @@ class CeresScanMatcherTest : public ::testing::Test {
: hybrid_grid_(1.f), : hybrid_grid_(1.f),
expected_pose_( expected_pose_(
transform::Rigid3d::Translation(Eigen::Vector3d(-1., 0., 0.))) { transform::Rigid3d::Translation(Eigen::Vector3d(-1., 0., 0.))) {
for (const auto& point : for (const Eigen::Vector3f& point :
{Eigen::Vector3f(-3.f, 2.f, 0.f), Eigen::Vector3f(-4.f, 2.f, 0.f), {Eigen::Vector3f(-3.f, 2.f, 0.f), Eigen::Vector3f(-4.f, 2.f, 0.f),
Eigen::Vector3f(-5.f, 2.f, 0.f), Eigen::Vector3f(-6.f, 2.f, 0.f), Eigen::Vector3f(-5.f, 2.f, 0.f), Eigen::Vector3f(-6.f, 2.f, 0.f),
Eigen::Vector3f(-6.f, 3.f, 1.f), Eigen::Vector3f(-6.f, 4.f, 2.f), Eigen::Vector3f(-6.f, 3.f, 1.f), Eigen::Vector3f(-6.f, 4.f, 2.f),

2
cartographer/mapping_3d/scan_matching/interpolated_grid_test.cc
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@ -29,7 +29,7 @@ class InterpolatedGridTest : public ::testing::Test {
protected: protected:
InterpolatedGridTest() InterpolatedGridTest()
: hybrid_grid_(0.1f), interpolated_grid_(hybrid_grid_) { : hybrid_grid_(0.1f), interpolated_grid_(hybrid_grid_) {
for (const auto& point : for (const Eigen::Vector3f& point :
{Eigen::Vector3f(-3.f, 2.f, 0.f), Eigen::Vector3f(-4.f, 2.f, 0.f), {Eigen::Vector3f(-3.f, 2.f, 0.f), Eigen::Vector3f(-4.f, 2.f, 0.f),
Eigen::Vector3f(-5.f, 2.f, 0.f), Eigen::Vector3f(-6.f, 2.f, 0.f), Eigen::Vector3f(-5.f, 2.f, 0.f), Eigen::Vector3f(-6.f, 2.f, 0.f),
Eigen::Vector3f(-6.f, 3.f, 1.f), Eigen::Vector3f(-6.f, 4.f, 2.f), Eigen::Vector3f(-6.f, 3.f, 1.f), Eigen::Vector3f(-6.f, 4.f, 2.f),

3
cartographer/mapping_3d/scan_matching/low_resolution_matcher.cc
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@ -24,7 +24,8 @@ std::function<float(const transform::Rigid3f&)> CreateLowResolutionMatcher(
const HybridGrid* low_resolution_grid, const sensor::PointCloud* points) { const HybridGrid* low_resolution_grid, const sensor::PointCloud* points) {
return [=](const transform::Rigid3f& pose) { return [=](const transform::Rigid3f& pose) {
float score = 0.f; float score = 0.f;
for (const auto& point : sensor::TransformPointCloud(*points, pose)) { for (const Eigen::Vector3f& point :
sensor::TransformPointCloud(*points, pose)) {
// TODO(zhengj, whess): Interpolate the Grid to get better score. // TODO(zhengj, whess): Interpolate the Grid to get better score.
score += low_resolution_grid->GetProbability( score += low_resolution_grid->GetProbability(
low_resolution_grid->GetCellIndex(point)); low_resolution_grid->GetCellIndex(point));

2
cartographer/mapping_3d/scan_matching/real_time_correlative_scan_matcher_test.cc
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@ -39,7 +39,7 @@ class RealTimeCorrelativeScanMatcherTest : public ::testing::Test {
: hybrid_grid_(0.1f), : hybrid_grid_(0.1f),
expected_pose_(Eigen::Vector3d(-1., 0., 0.), expected_pose_(Eigen::Vector3d(-1., 0., 0.),
Eigen::Quaterniond::Identity()) { Eigen::Quaterniond::Identity()) {
for (const auto& point : for (const Eigen::Vector3f& point :
{Eigen::Vector3f(-3.f, 2.f, 0.f), Eigen::Vector3f(-4.f, 2.f, 0.f), {Eigen::Vector3f(-3.f, 2.f, 0.f), Eigen::Vector3f(-4.f, 2.f, 0.f),
Eigen::Vector3f(-5.f, 2.f, 0.f), Eigen::Vector3f(-6.f, 2.f, 0.f), Eigen::Vector3f(-5.f, 2.f, 0.f), Eigen::Vector3f(-6.f, 2.f, 0.f),
Eigen::Vector3f(-6.f, 3.f, 1.f), Eigen::Vector3f(-6.f, 4.f, 2.f), Eigen::Vector3f(-6.f, 3.f, 1.f), Eigen::Vector3f(-6.f, 4.f, 2.f),

2
cartographer/sensor/compressed_point_cloud_test.cc
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@ -106,7 +106,7 @@ TEST(CompressPointCloudTest, CompressesNoGaps) {
EXPECT_EQ(decompressed.size(), recompressed.size()); EXPECT_EQ(decompressed.size(), recompressed.size());
std::vector<float> x_coord; std::vector<float> x_coord;
for (const auto& p : compressed) { for (const Eigen::Vector3f& p : compressed) {
x_coord.push_back(p[0]); x_coord.push_back(p[0]);
} }
std::sort(x_coord.begin(), x_coord.end()); std::sort(x_coord.begin(), x_coord.end());

4
cartographer/sensor/point_cloud.cc
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@ -48,7 +48,7 @@ TimedPointCloud TransformTimedPointCloud(const TimedPointCloud& point_cloud,
PointCloud CropPointCloud(const PointCloud& point_cloud, const float min_z, PointCloud CropPointCloud(const PointCloud& point_cloud, const float min_z,
const float max_z) { const float max_z) {
PointCloud cropped_point_cloud; PointCloud cropped_point_cloud;
for (const auto& point : point_cloud) { for (const Eigen::Vector3f& point : point_cloud) {
if (min_z <= point.z() && point.z() <= max_z) { if (min_z <= point.z() && point.z() <= max_z) {
cropped_point_cloud.push_back(point); cropped_point_cloud.push_back(point);
} }
@ -59,7 +59,7 @@ PointCloud CropPointCloud(const PointCloud& point_cloud, const float min_z,
TimedPointCloud CropTimedPointCloud(const TimedPointCloud& point_cloud, TimedPointCloud CropTimedPointCloud(const TimedPointCloud& point_cloud,
const float min_z, const float max_z) { const float min_z, const float max_z) {
TimedPointCloud cropped_point_cloud; TimedPointCloud cropped_point_cloud;
for (const auto& point : point_cloud) { for (const Eigen::Vector4f& point : point_cloud) {
if (min_z <= point.z() && point.z() <= max_z) { if (min_z <= point.z() && point.z() <= max_z) {
cropped_point_cloud.push_back(point); cropped_point_cloud.push_back(point);
} }

4
cartographer/sensor/range_data.cc
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@ -58,11 +58,11 @@ proto::RangeData ToProto(const RangeData& range_data) {
proto::RangeData proto; proto::RangeData proto;
*proto.mutable_origin() = transform::ToProto(range_data.origin); *proto.mutable_origin() = transform::ToProto(range_data.origin);
proto.mutable_returns()->Reserve(range_data.returns.size()); proto.mutable_returns()->Reserve(range_data.returns.size());
for (const auto& point : range_data.returns) { for (const Eigen::Vector3f& point : range_data.returns) {
*proto.add_returns() = transform::ToProto(point); *proto.add_returns() = transform::ToProto(point);
} }
proto.mutable_misses()->Reserve(range_data.misses.size()); proto.mutable_misses()->Reserve(range_data.misses.size());
for (const auto& point : range_data.misses) { for (const Eigen::Vector3f& point : range_data.misses) {
*proto.add_misses() = transform::ToProto(point); *proto.add_misses() = transform::ToProto(point);
} }
return proto; return proto;

2
cartographer/sensor/timed_point_cloud_data.cc
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@ -28,7 +28,7 @@ proto::TimedPointCloudData ToProto(
proto.set_timestamp(common::ToUniversal(timed_point_cloud_data.time)); proto.set_timestamp(common::ToUniversal(timed_point_cloud_data.time));
*proto.mutable_origin() = transform::ToProto(timed_point_cloud_data.origin); *proto.mutable_origin() = transform::ToProto(timed_point_cloud_data.origin);
proto.mutable_point_data()->Reserve(timed_point_cloud_data.ranges.size()); proto.mutable_point_data()->Reserve(timed_point_cloud_data.ranges.size());
for (const auto& range : timed_point_cloud_data.ranges) { for (const Eigen::Vector4f& range : timed_point_cloud_data.ranges) {
*proto.add_point_data() = transform::ToProto(range); *proto.add_point_data() = transform::ToProto(range);
} }
return proto; return proto;

2
cartographer/sensor/voxel_filter.cc
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@ -81,7 +81,7 @@ PointCloudType FilterPointCloudUsingVoxels(
const PointCloudType& point_cloud, const PointCloudType& point_cloud,
mapping_3d::HybridGridBase<uint8>* voxels) { mapping_3d::HybridGridBase<uint8>* voxels) {
PointCloudType results; PointCloudType results;
for (const auto& point : point_cloud) { for (const typename PointCloudType::value_type& point : point_cloud) {
auto* const value = auto* const value =
voxels->mutable_value(voxels->GetCellIndex(point.template head<3>())); voxels->mutable_value(voxels->GetCellIndex(point.template head<3>()));
if (*value == 0) { if (*value == 0) {