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|---|---|---|---|
| 1 | // Copyright Contributors to the OpenVDB Project | ||
| 2 | // SPDX-License-Identifier: MPL-2.0 | ||
| 3 | |||
| 4 | #include <openvdb/points/IndexIterator.h> | ||
| 5 | #include <openvdb/points/IndexFilter.h> | ||
| 6 | #include <openvdb/points/PointAttribute.h> | ||
| 7 | #include <openvdb/points/PointConversion.h> | ||
| 8 | #include <openvdb/points/PointGroup.h> | ||
| 9 | #include <openvdb/points/PointCount.h> | ||
| 10 | |||
| 11 | #include <gtest/gtest.h> | ||
| 12 | |||
| 13 | #include <sstream> | ||
| 14 | #include <iostream> | ||
| 15 | #include <utility> | ||
| 16 | |||
| 17 | using namespace openvdb; | ||
| 18 | using namespace openvdb::points; | ||
| 19 | |||
| 20 | 7 | class TestIndexFilter: public ::testing::Test | |
| 21 | { | ||
| 22 | public: | ||
| 23 | 7 | void SetUp() override { openvdb::initialize(); } | |
| 24 | 7 | void TearDown() override { openvdb::uninitialize(); } | |
| 25 | |||
| 26 | void testRandomLeafFilterImpl(); | ||
| 27 | }; // class TestIndexFilter | ||
| 28 | |||
| 29 | |||
| 30 | //////////////////////////////////////// | ||
| 31 | |||
| 32 | |||
| 33 | struct OriginLeaf | ||
| 34 | { | ||
| 35 | 3 | OriginLeaf(const openvdb::Coord& _leafOrigin, const size_t _size = size_t(0)): | |
| 36 | 3 | leafOrigin(_leafOrigin), size(_size) { } | |
| 37 |
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3 | openvdb::Coord origin() const { return leafOrigin; } |
| 38 |
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3 | size_t pointCount() const { return size; } |
| 39 | const openvdb::Coord leafOrigin; | ||
| 40 | const size_t size; | ||
| 41 | }; | ||
| 42 | |||
| 43 | |||
| 44 | struct SimpleIter | ||
| 45 | { | ||
| 46 | 6 | SimpleIter() : i(0) { } | |
| 47 | 606 | int operator*() const { return i; } | |
| 48 | 600 | void operator++() { i++; } | |
| 49 | openvdb::Coord getCoord() const { return coord; } | ||
| 50 | int i; | ||
| 51 | openvdb::Coord coord; | ||
| 52 | }; | ||
| 53 | |||
| 54 | |||
| 55 | template <bool LessThan> | ||
| 56 | class ThresholdFilter | ||
| 57 | { | ||
| 58 | public: | ||
| 59 | 6 | ThresholdFilter(const int threshold) | |
| 60 |
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6 | : mThreshold(threshold) { } |
| 61 | |||
| 62 | bool isPositiveInteger() const { return mThreshold > 0; } | ||
| 63 | 10 | bool isMax() const { return mThreshold == std::numeric_limits<int>::max(); } | |
| 64 | |||
| 65 | static bool initialized() { return true; } | ||
| 66 | inline index::State state() const | ||
| 67 | { | ||
| 68 | if (LessThan) { | ||
| 69 |
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5 | if (isMax()) return index::ALL; |
| 70 |
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3 | else if (!isPositiveInteger()) return index::NONE; |
| 71 | } | ||
| 72 | else { | ||
| 73 |
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5 | if (isMax()) return index::NONE; |
| 74 |
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5 | else if (!isPositiveInteger()) return index::ALL; |
| 75 | } | ||
| 76 | return index::PARTIAL; | ||
| 77 | } | ||
| 78 | |||
| 79 | template <typename LeafT> | ||
| 80 | static index::State state(const LeafT&) { return index::PARTIAL; } | ||
| 81 | |||
| 82 | template <typename LeafT> | ||
| 83 | void reset(const LeafT&) { } | ||
| 84 | |||
| 85 | template <typename IterT> | ||
| 86 | bool valid(const IterT& iter) const { | ||
| 87 |
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200 | return LessThan ? *iter < mThreshold : *iter > mThreshold; |
| 88 | } | ||
| 89 | |||
| 90 | private: | ||
| 91 | const int mThreshold; | ||
| 92 | }; // class ThresholdFilter | ||
| 93 | |||
| 94 | |||
| 95 | /// @brief Generates the signed distance to a sphere located at @a center | ||
| 96 | /// and with a specified @a radius (both in world coordinates). Only voxels | ||
| 97 | /// in the domain [0,0,0] -> @a dim are considered. Also note that the | ||
| 98 | /// level set is either dense, dense narrow-band or sparse narrow-band. | ||
| 99 | /// | ||
| 100 | /// @note This method is VERY SLOW and should only be used for debugging purposes! | ||
| 101 | /// However it works for any transform and even with open level sets. | ||
| 102 | /// A faster approch for closed narrow band generation is to only set voxels | ||
| 103 | /// sparsely and then use grid::signedFloodFill to define the sign | ||
| 104 | /// of the background values and tiles! This is implemented in openvdb/tools/LevelSetSphere.h | ||
| 105 | template<class GridType> | ||
| 106 | inline void | ||
| 107 | 2 | makeSphere(const openvdb::Coord& dim, const openvdb::Vec3f& center, float radius, GridType& grid) | |
| 108 | { | ||
| 109 | using ValueT = typename GridType::ValueType; | ||
| 110 | const ValueT zero = openvdb::zeroVal<ValueT>(); | ||
| 111 | |||
| 112 | typename GridType::Accessor acc = grid.getAccessor(); | ||
| 113 | openvdb::Coord xyz; | ||
| 114 |
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52 | for (xyz[0]=0; xyz[0]<dim[0]; ++xyz[0]) { |
| 115 |
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1750 | for (xyz[1]=0; xyz[1]<dim[1]; ++xyz[1]) { |
| 116 |
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66700 | for (xyz[2]=0; xyz[2]<dim[2]; ++xyz[2]) { |
| 117 | const openvdb::Vec3R p = grid.transform().indexToWorld(xyz); | ||
| 118 | 65000 | const float dist = float((p-center).length() - radius); | |
| 119 | 65000 | ValueT val = ValueT(zero + dist); | |
| 120 |
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65000 | acc.setValue(xyz, val); |
| 121 | } | ||
| 122 | } | ||
| 123 | } | ||
| 124 | 2 | } | |
| 125 | |||
| 126 | |||
| 127 | template <typename LeafT> | ||
| 128 | bool | ||
| 129 | 11 | multiGroupMatches( const LeafT& leaf, const Index32 size, | |
| 130 | const std::vector<Name>& include, const std::vector<Name>& exclude, | ||
| 131 | const std::vector<int>& indices) | ||
| 132 | { | ||
| 133 | using IndexGroupIter = IndexIter<ValueVoxelCIter, MultiGroupFilter>; | ||
| 134 | ValueVoxelCIter indexIter(0, size); | ||
| 135 | 22 | MultiGroupFilter filter(include, exclude, leaf.attributeSet()); | |
| 136 |
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11 | filter.reset(leaf); |
| 137 |
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11 | IndexGroupIter iter(indexIter, filter); |
| 138 |
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35 | for (unsigned i = 0; i < indices.size(); ++i, ++iter) { |
| 139 |
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24 | if (!iter) return false; |
| 140 |
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24 | if (*iter != Index32(indices[i])) return false; |
| 141 | } | ||
| 142 | 11 | return !iter; | |
| 143 | } | ||
| 144 | |||
| 145 | |||
| 146 |
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1 | TEST_F(TestIndexFilter, testActiveFilter) |
| 147 | { | ||
| 148 | // create a point grid, three points are stored in two leafs | ||
| 149 | |||
| 150 |
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1 | PointDataGrid::Ptr points; |
| 151 |
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1 | std::vector<Vec3s> positions{{1, 1, 1}, {1, 2, 1}, {10.1f, 10, 1}}; |
| 152 | |||
| 153 | const double voxelSize(1.0); | ||
| 154 |
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1 | math::Transform::Ptr transform(math::Transform::createLinearTransform(voxelSize)); |
| 155 | |||
| 156 |
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1 | points = createPointDataGrid<NullCodec, PointDataGrid>(positions, *transform); |
| 157 | |||
| 158 | // check there are two leafs | ||
| 159 | |||
| 160 |
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1 | EXPECT_EQ(Index32(2), points->tree().leafCount()); |
| 161 | |||
| 162 | ActiveFilter activeFilter; | ||
| 163 | InactiveFilter inActiveFilter; | ||
| 164 | |||
| 165 |
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1 | EXPECT_EQ(index::PARTIAL, activeFilter.state()); |
| 166 |
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1 | EXPECT_EQ(index::PARTIAL, inActiveFilter.state()); |
| 167 | |||
| 168 | { // test default active / inactive values | ||
| 169 | auto leafIter = points->tree().cbeginLeaf(); | ||
| 170 | |||
| 171 |
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1 | EXPECT_EQ(index::PARTIAL, activeFilter.state(*leafIter)); |
| 172 |
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1 | EXPECT_EQ(index::PARTIAL, inActiveFilter.state(*leafIter)); |
| 173 | |||
| 174 | auto indexIter = leafIter->beginIndexAll(); | ||
| 175 | activeFilter.reset(*leafIter); | ||
| 176 | inActiveFilter.reset(*leafIter); | ||
| 177 | |||
| 178 |
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1 | EXPECT_TRUE(activeFilter.valid(indexIter)); |
| 179 |
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1 | EXPECT_TRUE(!inActiveFilter.valid(indexIter)); |
| 180 |
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1 | ++indexIter; |
| 181 |
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1 | EXPECT_TRUE(activeFilter.valid(indexIter)); |
| 182 |
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1 | EXPECT_TRUE(!inActiveFilter.valid(indexIter)); |
| 183 |
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1 | ++indexIter; |
| 184 |
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1 | EXPECT_TRUE(!indexIter); |
| 185 | ++leafIter; | ||
| 186 | |||
| 187 |
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1 | indexIter = leafIter->beginIndexAll(); |
| 188 | activeFilter.reset(*leafIter); | ||
| 189 | inActiveFilter.reset(*leafIter); | ||
| 190 | |||
| 191 |
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1 | EXPECT_TRUE(activeFilter.valid(indexIter)); |
| 192 |
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1 | EXPECT_TRUE(!inActiveFilter.valid(indexIter)); |
| 193 |
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1 | ++indexIter; |
| 194 |
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1 | EXPECT_TRUE(!indexIter); |
| 195 | } | ||
| 196 | |||
| 197 | auto firstLeaf = points->tree().beginLeaf(); | ||
| 198 | |||
| 199 | { // set all voxels to be inactive in the first leaf | ||
| 200 | firstLeaf->getValueMask().set(false); | ||
| 201 | |||
| 202 | auto leafIter = points->tree().cbeginLeaf(); | ||
| 203 | |||
| 204 |
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1 | EXPECT_EQ(index::NONE, activeFilter.state(*leafIter)); |
| 205 |
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1 | EXPECT_EQ(index::ALL, inActiveFilter.state(*leafIter)); |
| 206 | |||
| 207 | auto indexIter = leafIter->beginIndexAll(); | ||
| 208 | activeFilter.reset(*leafIter); | ||
| 209 | inActiveFilter.reset(*leafIter); | ||
| 210 | |||
| 211 |
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1 | EXPECT_TRUE(!activeFilter.valid(indexIter)); |
| 212 |
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1 | EXPECT_TRUE(inActiveFilter.valid(indexIter)); |
| 213 |
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1 | ++indexIter; |
| 214 |
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1 | EXPECT_TRUE(!activeFilter.valid(indexIter)); |
| 215 |
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1 | EXPECT_TRUE(inActiveFilter.valid(indexIter)); |
| 216 |
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1 | ++indexIter; |
| 217 |
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1 | EXPECT_TRUE(!indexIter); |
| 218 | ++leafIter; | ||
| 219 | |||
| 220 |
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1 | indexIter = leafIter->beginIndexAll(); |
| 221 | activeFilter.reset(*leafIter); | ||
| 222 | inActiveFilter.reset(*leafIter); | ||
| 223 | |||
| 224 |
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1 | EXPECT_TRUE(activeFilter.valid(indexIter)); |
| 225 |
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1 | EXPECT_TRUE(!inActiveFilter.valid(indexIter)); |
| 226 |
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1 | ++indexIter; |
| 227 |
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1 | EXPECT_TRUE(!indexIter); |
| 228 | } | ||
| 229 | |||
| 230 | { // set all voxels to be active in the first leaf | ||
| 231 | firstLeaf->getValueMask().set(true); | ||
| 232 | |||
| 233 | auto leafIter = points->tree().cbeginLeaf(); | ||
| 234 | |||
| 235 |
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1 | EXPECT_EQ(index::ALL, activeFilter.state(*leafIter)); |
| 236 |
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1 | EXPECT_EQ(index::NONE, inActiveFilter.state(*leafIter)); |
| 237 | |||
| 238 | auto indexIter = leafIter->beginIndexAll(); | ||
| 239 | activeFilter.reset(*leafIter); | ||
| 240 | inActiveFilter.reset(*leafIter); | ||
| 241 | |||
| 242 |
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1 | EXPECT_TRUE(activeFilter.valid(indexIter)); |
| 243 |
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1 | EXPECT_TRUE(!inActiveFilter.valid(indexIter)); |
| 244 |
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1 | ++indexIter; |
| 245 |
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1 | EXPECT_TRUE(activeFilter.valid(indexIter)); |
| 246 |
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1 | EXPECT_TRUE(!inActiveFilter.valid(indexIter)); |
| 247 |
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1 | ++indexIter; |
| 248 |
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1 | EXPECT_TRUE(!indexIter); |
| 249 | ++leafIter; | ||
| 250 | |||
| 251 |
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1 | indexIter = leafIter->beginIndexAll(); |
| 252 | activeFilter.reset(*leafIter); | ||
| 253 | inActiveFilter.reset(*leafIter); | ||
| 254 | |||
| 255 |
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1 | EXPECT_TRUE(activeFilter.valid(indexIter)); |
| 256 |
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1 | EXPECT_TRUE(!inActiveFilter.valid(indexIter)); |
| 257 |
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1 | ++indexIter; |
| 258 |
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1 | EXPECT_TRUE(!indexIter); |
| 259 | } | ||
| 260 | 1 | } | |
| 261 | |||
| 262 |
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1 | TEST_F(TestIndexFilter, testMultiGroupFilter) |
| 263 | { | ||
| 264 | using LeafNode = PointDataTree::LeafNodeType; | ||
| 265 | using AttributeVec3f = TypedAttributeArray<Vec3f>; | ||
| 266 | |||
| 267 | 2 | PointDataTree tree; | |
| 268 |
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1 | LeafNode* leaf = tree.touchLeaf(openvdb::Coord(0, 0, 0)); |
| 269 | |||
| 270 | using Descriptor = AttributeSet::Descriptor; | ||
| 271 |
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1 | Descriptor::Ptr descriptor = Descriptor::create(AttributeVec3f::attributeType()); |
| 272 | |||
| 273 | const Index size = 5; | ||
| 274 | |||
| 275 |
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1 | leaf->initializeAttributes(descriptor, size); |
| 276 | |||
| 277 |
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1 | appendGroup(tree, "even"); |
| 278 |
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1 | appendGroup(tree, "odd"); |
| 279 |
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1 | appendGroup(tree, "all"); |
| 280 |
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2 | appendGroup(tree, "first"); |
| 281 | |||
| 282 | { // construction, copy construction | ||
| 283 | 1 | std::vector<Name> includeGroups; | |
| 284 | 1 | std::vector<Name> excludeGroups; | |
| 285 |
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2 | MultiGroupFilter filter(includeGroups, excludeGroups, leaf->attributeSet()); |
| 286 |
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1 | EXPECT_TRUE(!filter.initialized()); |
| 287 |
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2 | MultiGroupFilter filter2 = filter; |
| 288 |
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1 | EXPECT_TRUE(!filter2.initialized()); |
| 289 | |||
| 290 |
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1 | filter.reset(*leaf); |
| 291 |
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1 | EXPECT_TRUE(filter.initialized()); |
| 292 |
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2 | MultiGroupFilter filter3 = filter; |
| 293 |
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1 | EXPECT_TRUE(filter3.initialized()); |
| 294 | } | ||
| 295 | |||
| 296 | // group population | ||
| 297 | |||
| 298 | { // even | ||
| 299 |
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1 | GroupWriteHandle groupHandle = leaf->groupWriteHandle("even"); |
| 300 |
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1 | groupHandle.set(0, true); |
| 301 |
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1 | groupHandle.set(2, true); |
| 302 |
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1 | groupHandle.set(4, true); |
| 303 | } | ||
| 304 | |||
| 305 | { // odd | ||
| 306 |
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1 | GroupWriteHandle groupHandle = leaf->groupWriteHandle("odd"); |
| 307 |
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1 | groupHandle.set(1, true); |
| 308 |
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1 | groupHandle.set(3, true); |
| 309 | } | ||
| 310 | |||
| 311 |
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1 | setGroup(tree, "all", true); |
| 312 | |||
| 313 | { // first | ||
| 314 |
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1 | GroupWriteHandle groupHandle = leaf->groupWriteHandle("first"); |
| 315 |
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1 | groupHandle.set(0, true); |
| 316 | } | ||
| 317 | |||
| 318 | { // test state() | ||
| 319 | 1 | std::vector<Name> include; | |
| 320 | 1 | std::vector<Name> exclude; | |
| 321 |
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2 | MultiGroupFilter filter(include, exclude, leaf->attributeSet()); |
| 322 |
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2 | EXPECT_EQ(filter.state(), index::ALL); |
| 323 |
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2 | include.push_back("all"); |
| 324 |
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2 | MultiGroupFilter filter2(include, exclude, leaf->attributeSet()); |
| 325 |
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1 | EXPECT_EQ(filter2.state(), index::PARTIAL); |
| 326 | } | ||
| 327 | |||
| 328 | // test multi group iteration | ||
| 329 | |||
| 330 | { // all (implicit, no include or exclude) | ||
| 331 | 1 | std::vector<Name> include; | |
| 332 | 1 | std::vector<Name> exclude; | |
| 333 |
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1 | std::vector<int> indices{0, 1, 2, 3, 4}; |
| 334 |
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1 | EXPECT_TRUE(multiGroupMatches(*leaf, size, include, exclude, indices)); |
| 335 | } | ||
| 336 | |||
| 337 | { // all include | ||
| 338 |
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3 | std::vector<Name> include{"all"}; |
| 339 | 1 | std::vector<Name> exclude; | |
| 340 |
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1 | std::vector<int> indices{0, 1, 2, 3, 4}; |
| 341 |
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1 | EXPECT_TRUE(multiGroupMatches(*leaf, size, include, exclude, indices)); |
| 342 | } | ||
| 343 | |||
| 344 | { // all exclude | ||
| 345 | 1 | std::vector<Name> include; | |
| 346 |
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3 | std::vector<Name> exclude{"all"}; |
| 347 | std::vector<int> indices; | ||
| 348 |
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1 | EXPECT_TRUE(multiGroupMatches(*leaf, size, include, exclude, indices)); |
| 349 | } | ||
| 350 | |||
| 351 | { // all include and exclude | ||
| 352 |
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2 | std::vector<Name> include{"all"}; |
| 353 |
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3 | std::vector<Name> exclude{"all"}; |
| 354 | std::vector<int> indices; | ||
| 355 |
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1 | EXPECT_TRUE(multiGroupMatches(*leaf, size, include, exclude, indices)); |
| 356 | } | ||
| 357 | |||
| 358 | { // even include | ||
| 359 |
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3 | std::vector<Name> include{"even"}; |
| 360 | 1 | std::vector<Name> exclude; | |
| 361 |
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1 | std::vector<int> indices{0, 2, 4}; |
| 362 |
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1 | EXPECT_TRUE(multiGroupMatches(*leaf, size, include, exclude, indices)); |
| 363 | } | ||
| 364 | |||
| 365 | { // odd include | ||
| 366 |
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3 | std::vector<Name> include{"odd"}; |
| 367 | 1 | std::vector<Name> exclude; | |
| 368 |
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1 | std::vector<int> indices{1, 3}; |
| 369 |
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1 | EXPECT_TRUE(multiGroupMatches(*leaf, size, include, exclude, indices)); |
| 370 | } | ||
| 371 | |||
| 372 | { // odd include and exclude | ||
| 373 |
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2 | std::vector<Name> include{"odd"}; |
| 374 |
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3 | std::vector<Name> exclude{"odd"}; |
| 375 | std::vector<int> indices; | ||
| 376 |
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1 | EXPECT_TRUE(multiGroupMatches(*leaf, size, include, exclude, indices)); |
| 377 | } | ||
| 378 | |||
| 379 | { // odd and first include | ||
| 380 |
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3 | std::vector<Name> include{"odd", "first"}; |
| 381 | 1 | std::vector<Name> exclude; | |
| 382 |
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1 | std::vector<int> indices{0, 1, 3}; |
| 383 |
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1 | EXPECT_TRUE(multiGroupMatches(*leaf, size, include, exclude, indices)); |
| 384 | } | ||
| 385 | |||
| 386 | { // even include, first exclude | ||
| 387 |
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2 | std::vector<Name> include{"even"}; |
| 388 |
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2 | std::vector<Name> exclude{"first"}; |
| 389 |
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1 | std::vector<int> indices{2, 4}; |
| 390 |
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1 | EXPECT_TRUE(multiGroupMatches(*leaf, size, include, exclude, indices)); |
| 391 | } | ||
| 392 | |||
| 393 | { // all include, first and odd exclude | ||
| 394 |
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2 | std::vector<Name> include{"all"}; |
| 395 |
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2 | std::vector<Name> exclude{"first", "odd"}; |
| 396 |
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1 | std::vector<int> indices{2, 4}; |
| 397 |
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1 | EXPECT_TRUE(multiGroupMatches(*leaf, size, include, exclude, indices)); |
| 398 | } | ||
| 399 | |||
| 400 | { // odd and first include, even exclude | ||
| 401 |
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2 | std::vector<Name> include{"odd", "first"}; |
| 402 |
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2 | std::vector<Name> exclude{"even"}; |
| 403 |
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1 | std::vector<int> indices{1, 3}; |
| 404 |
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1 | EXPECT_TRUE(multiGroupMatches(*leaf, size, include, exclude, indices)); |
| 405 | } | ||
| 406 | 1 | } | |
| 407 | |||
| 408 | |||
| 409 | void | ||
| 410 | 1 | TestIndexFilter::testRandomLeafFilterImpl() | |
| 411 | { | ||
| 412 | { // generateRandomSubset | ||
| 413 | std::vector<int> values = index_filter_internal::generateRandomSubset<std::mt19937, int>( | ||
| 414 | 1 | /*seed*/unsigned(0), 1, 20); | |
| 415 | |||
| 416 |
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1 | EXPECT_EQ(values.size(), size_t(1)); |
| 417 | |||
| 418 | // different seed | ||
| 419 | |||
| 420 | std::vector<int> values2 = index_filter_internal::generateRandomSubset<std::mt19937, int>( | ||
| 421 |
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1 | /*seed*/unsigned(1), 1, 20); |
| 422 | |||
| 423 |
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1 | EXPECT_EQ(values2.size(), size_t(1)); |
| 424 |
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1 | EXPECT_TRUE(values[0] != values2[0]); |
| 425 | |||
| 426 | // different integer type | ||
| 427 | |||
| 428 | std::vector<long> values3 = index_filter_internal::generateRandomSubset<std::mt19937, long>( | ||
| 429 |
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1 | /*seed*/unsigned(0), 1, 20); |
| 430 | |||
| 431 |
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1 | EXPECT_EQ(values3.size(), size_t(1)); |
| 432 |
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1 | EXPECT_TRUE(values[0] == values3[0]); |
| 433 | |||
| 434 | // different random number generator | ||
| 435 | |||
| 436 |
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1 | values = index_filter_internal::generateRandomSubset<std::mt19937_64, int>( |
| 437 | /*seed*/unsigned(1), 1, 20); | ||
| 438 | |||
| 439 |
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1 | EXPECT_EQ(values.size(), size_t(1)); |
| 440 |
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1 | EXPECT_TRUE(values[0] != values2[0]); |
| 441 | |||
| 442 | // no values | ||
| 443 | |||
| 444 |
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1 | values = index_filter_internal::generateRandomSubset<std::mt19937, int>( |
| 445 | /*seed*/unsigned(0), 0, 20); | ||
| 446 | |||
| 447 |
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1 | EXPECT_EQ(values.size(), size_t(0)); |
| 448 | |||
| 449 | // all values | ||
| 450 | |||
| 451 |
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1 | values = index_filter_internal::generateRandomSubset<std::mt19937, int>( |
| 452 | /*seed*/unsigned(0), 1000, 1000); | ||
| 453 | |||
| 454 |
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1 | EXPECT_EQ(values.size(), size_t(1000)); |
| 455 | |||
| 456 | // ensure all numbers are represented | ||
| 457 | |||
| 458 | 1 | std::sort(values.begin(), values.end()); | |
| 459 | |||
| 460 |
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1001 | for (int i = 0; i < 1000; i++) { |
| 461 |
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1000 | EXPECT_EQ(values[i], i); |
| 462 | } | ||
| 463 | } | ||
| 464 | |||
| 465 | { // RandomLeafFilter | ||
| 466 | using RandFilter = RandomLeafFilter<PointDataTree, std::mt19937>; | ||
| 467 | |||
| 468 | 2 | PointDataTree tree; | |
| 469 | |||
| 470 |
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2 | RandFilter filter(tree, 0); |
| 471 | |||
| 472 | EXPECT_TRUE(filter.state() == index::PARTIAL); | ||
| 473 | |||
| 474 |
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1 | filter.mLeafMap[Coord(0, 0, 0)] = std::make_pair(0, 10); |
| 475 |
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1 | filter.mLeafMap[Coord(0, 0, 8)] = std::make_pair(1, 1); |
| 476 |
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1 | filter.mLeafMap[Coord(0, 8, 0)] = std::make_pair(2, 50); |
| 477 | |||
| 478 | { // construction, copy construction | ||
| 479 |
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1 | EXPECT_TRUE(filter.initialized()); |
| 480 |
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2 | RandFilter filter2 = filter; |
| 481 |
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1 | EXPECT_TRUE(filter2.initialized()); |
| 482 | |||
| 483 |
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1 | filter.reset(OriginLeaf(Coord(0, 0, 0), 10)); |
| 484 |
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1 | EXPECT_TRUE(filter.initialized()); |
| 485 |
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2 | RandFilter filter3 = filter; |
| 486 |
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1 | EXPECT_TRUE(filter3.initialized()); |
| 487 | } | ||
| 488 | |||
| 489 | { // all 10 values | ||
| 490 |
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1 | filter.reset(OriginLeaf(Coord(0, 0, 0), 10)); |
| 491 | std::vector<int> values; | ||
| 492 | |||
| 493 |
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101 | for (SimpleIter iter; *iter < 100; ++iter) { |
| 494 |
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100 | if (filter.valid(iter)) values.push_back(*iter); |
| 495 | } | ||
| 496 | |||
| 497 |
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1 | EXPECT_EQ(values.size(), size_t(10)); |
| 498 | |||
| 499 |
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11 | for (int i = 0; i < 10; i++) { |
| 500 |
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10 | EXPECT_EQ(values[i], i); |
| 501 | } | ||
| 502 | } | ||
| 503 | |||
| 504 | { // 50 of 100 | ||
| 505 |
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1 | filter.reset(OriginLeaf(Coord(0, 8, 0), 100)); |
| 506 | std::vector<int> values; | ||
| 507 | |||
| 508 |
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101 | for (SimpleIter iter; *iter < 100; ++iter) { |
| 509 |
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100 | if (filter.valid(iter)) values.push_back(*iter); |
| 510 | } | ||
| 511 | |||
| 512 |
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1 | EXPECT_EQ(values.size(), size_t(50)); |
| 513 | |||
| 514 | // ensure no duplicates | ||
| 515 | |||
| 516 | 1 | std::sort(values.begin(), values.end()); | |
| 517 |
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1 | auto it = std::adjacent_find(values.begin(), values.end()); |
| 518 | |||
| 519 |
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1 | EXPECT_TRUE(it == values.end()); |
| 520 | } | ||
| 521 | } | ||
| 522 | 1 | } | |
| 523 |
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2 | TEST_F(TestIndexFilter, testRandomLeafFilter) { testRandomLeafFilterImpl(); } |
| 524 | |||
| 525 | |||
| 526 | inline void | ||
| 527 | 1 | setId(PointDataTree& tree, const size_t index, const std::vector<int>& ids) | |
| 528 | { | ||
| 529 | int offset = 0; | ||
| 530 |
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3 | for (auto leafIter = tree.beginLeaf(); leafIter; ++leafIter) { |
| 531 | 2 | auto id = AttributeWriteHandle<int>::create(leafIter->attributeArray(index)); | |
| 532 | |||
| 533 |
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10 | for (auto iter = leafIter->beginIndexAll(); iter; ++iter) { |
| 534 |
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4 | if (offset >= int(ids.size())) throw std::runtime_error("Out of range"); |
| 535 | |||
| 536 |
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4 | id->set(*iter, ids[offset++]); |
| 537 | } | ||
| 538 | } | ||
| 539 | 1 | } | |
| 540 | |||
| 541 | |||
| 542 |
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2 | TEST_F(TestIndexFilter, testAttributeHashFilter) |
| 543 | { | ||
| 544 | 1 | std::vector<Vec3s> positions{{1, 1, 1}, {2, 2, 2}, {11, 11, 11}, {12, 12, 12}}; | |
| 545 | |||
| 546 | const float voxelSize(1.0); | ||
| 547 |
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1 | math::Transform::Ptr transform(math::Transform::createLinearTransform(voxelSize)); |
| 548 | |||
| 549 |
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1 | PointDataGrid::Ptr grid = createPointDataGrid<NullCodec, PointDataGrid>(positions, *transform); |
| 550 | PointDataTree& tree = grid->tree(); | ||
| 551 | |||
| 552 | // four points, two leafs | ||
| 553 | |||
| 554 |
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1 | EXPECT_EQ(tree.leafCount(), Index32(2)); |
| 555 | |||
| 556 |
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2 | appendAttribute<int>(tree, "id"); |
| 557 | |||
| 558 |
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1 | const size_t index = tree.cbeginLeaf()->attributeSet().descriptor().find("id"); |
| 559 | |||
| 560 | // ascending integers, block one | ||
| 561 |
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1 | std::vector<int> ids{1, 2, 3, 4}; |
| 562 |
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1 | setId(tree, index, ids); |
| 563 | |||
| 564 | using HashFilter = AttributeHashFilter<std::mt19937, int>; | ||
| 565 | |||
| 566 | { // construction, copy construction | ||
| 567 | HashFilter filter(index, 0.0f); | ||
| 568 | EXPECT_TRUE(filter.state() == index::PARTIAL); | ||
| 569 | EXPECT_TRUE(!filter.initialized()); | ||
| 570 |
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1 | HashFilter filter2 = filter; |
| 571 |
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1 | EXPECT_TRUE(!filter2.initialized()); |
| 572 | |||
| 573 |
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1 | filter.reset(*tree.cbeginLeaf()); |
| 574 |
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1 | EXPECT_TRUE(filter.initialized()); |
| 575 |
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1 | HashFilter filter3 = filter; |
| 576 |
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1 | EXPECT_TRUE(filter3.initialized()); |
| 577 | } | ||
| 578 | |||
| 579 | { // zero percent | ||
| 580 | HashFilter filter(index, 0.0f); | ||
| 581 | |||
| 582 | auto leafIter = tree.cbeginLeaf(); | ||
| 583 | |||
| 584 | auto indexIter = leafIter->beginIndexAll(); | ||
| 585 |
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1 | filter.reset(*leafIter); |
| 586 | |||
| 587 |
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1 | EXPECT_TRUE(!filter.valid(indexIter)); |
| 588 |
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1 | ++indexIter; |
| 589 |
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1 | EXPECT_TRUE(!filter.valid(indexIter)); |
| 590 |
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1 | ++indexIter; |
| 591 |
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1 | EXPECT_TRUE(!indexIter); |
| 592 | ++leafIter; | ||
| 593 | |||
| 594 |
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1 | indexIter = leafIter->beginIndexAll(); |
| 595 |
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1 | filter.reset(*leafIter); |
| 596 |
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1 | EXPECT_TRUE(!filter.valid(indexIter)); |
| 597 |
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1 | ++indexIter; |
| 598 |
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1 | EXPECT_TRUE(!filter.valid(indexIter)); |
| 599 |
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1 | ++indexIter; |
| 600 |
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1 | EXPECT_TRUE(!indexIter); |
| 601 | } | ||
| 602 | |||
| 603 | { // one hundred percent | ||
| 604 | HashFilter filter(index, 100.0f); | ||
| 605 | |||
| 606 | auto leafIter = tree.cbeginLeaf(); | ||
| 607 | |||
| 608 | auto indexIter = leafIter->beginIndexAll(); | ||
| 609 |
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1 | filter.reset(*leafIter); |
| 610 | |||
| 611 |
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1 | EXPECT_TRUE(filter.valid(indexIter)); |
| 612 |
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1 | ++indexIter; |
| 613 |
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1 | EXPECT_TRUE(filter.valid(indexIter)); |
| 614 |
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1 | ++indexIter; |
| 615 |
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1 | EXPECT_TRUE(!indexIter); |
| 616 | ++leafIter; | ||
| 617 | |||
| 618 |
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1 | indexIter = leafIter->beginIndexAll(); |
| 619 |
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1 | filter.reset(*leafIter); |
| 620 |
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1 | EXPECT_TRUE(filter.valid(indexIter)); |
| 621 |
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1 | ++indexIter; |
| 622 |
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1 | EXPECT_TRUE(filter.valid(indexIter)); |
| 623 |
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1 | ++indexIter; |
| 624 |
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1 | EXPECT_TRUE(!indexIter); |
| 625 | } | ||
| 626 | |||
| 627 | { // fifty percent | ||
| 628 | HashFilter filter(index, 50.0f); | ||
| 629 | |||
| 630 | auto leafIter = tree.cbeginLeaf(); | ||
| 631 | |||
| 632 | auto indexIter = leafIter->beginIndexAll(); | ||
| 633 |
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1 | filter.reset(*leafIter); |
| 634 | |||
| 635 |
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1 | EXPECT_TRUE(!filter.valid(indexIter)); |
| 636 |
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1 | ++indexIter; |
| 637 |
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1 | EXPECT_TRUE(filter.valid(indexIter)); |
| 638 |
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1 | ++indexIter; |
| 639 |
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1 | EXPECT_TRUE(!indexIter); |
| 640 | ++leafIter; | ||
| 641 | |||
| 642 |
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1 | indexIter = leafIter->beginIndexAll(); |
| 643 |
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1 | filter.reset(*leafIter); |
| 644 |
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1 | EXPECT_TRUE(filter.valid(indexIter)); |
| 645 |
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1 | ++indexIter; |
| 646 |
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1 | EXPECT_TRUE(!filter.valid(indexIter)); |
| 647 |
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1 | ++indexIter; |
| 648 |
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1 | EXPECT_TRUE(!indexIter); |
| 649 | } | ||
| 650 | |||
| 651 | { // fifty percent, new seed | ||
| 652 | HashFilter filter(index, 50.0f, /*seed=*/100); | ||
| 653 | |||
| 654 | auto leafIter = tree.cbeginLeaf(); | ||
| 655 | |||
| 656 | auto indexIter = leafIter->beginIndexAll(); | ||
| 657 |
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1 | filter.reset(*leafIter); |
| 658 | |||
| 659 |
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1 | EXPECT_TRUE(!filter.valid(indexIter)); |
| 660 |
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1 | ++indexIter; |
| 661 |
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1 | EXPECT_TRUE(filter.valid(indexIter)); |
| 662 |
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1 | ++indexIter; |
| 663 |
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1 | EXPECT_TRUE(!indexIter); |
| 664 | ++leafIter; | ||
| 665 | |||
| 666 |
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1 | indexIter = leafIter->beginIndexAll(); |
| 667 |
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1 | filter.reset(*leafIter); |
| 668 |
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1 | EXPECT_TRUE(filter.valid(indexIter)); |
| 669 |
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1 | ++indexIter; |
| 670 |
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1 | EXPECT_TRUE(filter.valid(indexIter)); |
| 671 |
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1 | ++indexIter; |
| 672 |
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1 | EXPECT_TRUE(!indexIter); |
| 673 | } | ||
| 674 | 1 | } | |
| 675 | |||
| 676 | |||
| 677 |
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1 | TEST_F(TestIndexFilter, testLevelSetFilter) |
| 678 | { | ||
| 679 | // create a point grid | ||
| 680 | |||
| 681 |
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1 | PointDataGrid::Ptr points; |
| 682 | |||
| 683 | { | ||
| 684 |
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1 | std::vector<Vec3s> positions{{1, 1, 1}, {1, 2, 1}, {10.1f, 10, 1}}; |
| 685 | |||
| 686 | const double voxelSize(1.0); | ||
| 687 |
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1 | math::Transform::Ptr transform(math::Transform::createLinearTransform(voxelSize)); |
| 688 | |||
| 689 |
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1 | points = createPointDataGrid<NullCodec, PointDataGrid>(positions, *transform); |
| 690 | } | ||
| 691 | |||
| 692 | // create a sphere levelset | ||
| 693 | |||
| 694 | 1 | FloatGrid::Ptr sphere; | |
| 695 | |||
| 696 | { | ||
| 697 | double voxelSize = 0.5; | ||
| 698 |
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1 | sphere = FloatGrid::create(/*backgroundValue=*/5.0); |
| 699 |
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2 | sphere->setTransform(math::Transform::createLinearTransform(voxelSize)); |
| 700 | |||
| 701 | const openvdb::Coord dim(10, 10, 10); | ||
| 702 | const openvdb::Vec3f center(0.0f, 0.0f, 0.0f); | ||
| 703 | const float radius = 2; | ||
| 704 |
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1 | makeSphere<FloatGrid>(dim, center, radius, *sphere); |
| 705 | } | ||
| 706 | |||
| 707 | using LSFilter = LevelSetFilter<FloatGrid>; | ||
| 708 | |||
| 709 | { // construction, copy construction | ||
| 710 | 1 | LSFilter filter(*sphere, points->transform(), -4.0f, 4.0f); | |
| 711 | EXPECT_TRUE(filter.state() == index::PARTIAL); | ||
| 712 | EXPECT_TRUE(!filter.initialized()); | ||
| 713 |
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2 | LSFilter filter2 = filter; |
| 714 |
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1 | EXPECT_TRUE(!filter2.initialized()); |
| 715 | |||
| 716 |
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1 | filter.reset(* points->tree().cbeginLeaf()); |
| 717 |
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1 | EXPECT_TRUE(filter.initialized()); |
| 718 |
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2 | LSFilter filter3 = filter; |
| 719 |
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1 | EXPECT_TRUE(filter3.initialized()); |
| 720 | } | ||
| 721 | |||
| 722 | { // capture both points near origin | ||
| 723 | 1 | LSFilter filter(*sphere, points->transform(), -4.0f, 4.0f); | |
| 724 | auto leafIter = points->tree().cbeginLeaf(); | ||
| 725 |
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1 | auto iter = leafIter->beginIndexOn(); |
| 726 |
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1 | filter.reset(*leafIter); |
| 727 | |||
| 728 |
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1 | EXPECT_TRUE(filter.valid(iter)); |
| 729 |
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1 | ++iter; |
| 730 |
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1 | EXPECT_TRUE(filter.valid(iter)); |
| 731 |
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1 | ++iter; |
| 732 |
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1 | EXPECT_TRUE(!iter); |
| 733 | |||
| 734 | ++leafIter; | ||
| 735 |
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1 | iter = leafIter->beginIndexOn(); |
| 736 |
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1 | filter.reset(*leafIter); |
| 737 | |||
| 738 |
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1 | EXPECT_TRUE(iter); |
| 739 |
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1 | EXPECT_TRUE(!filter.valid(iter)); |
| 740 |
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1 | ++iter; |
| 741 |
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1 | EXPECT_TRUE(!iter); |
| 742 | } | ||
| 743 | |||
| 744 | { // capture just the inner-most point | ||
| 745 | 1 | LSFilter filter(*sphere, points->transform(), -0.3f, -0.25f); | |
| 746 | auto leafIter = points->tree().cbeginLeaf(); | ||
| 747 |
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1 | auto iter = leafIter->beginIndexOn(); |
| 748 |
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1 | filter.reset(*leafIter); |
| 749 | |||
| 750 |
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1 | EXPECT_TRUE(filter.valid(iter)); |
| 751 |
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1 | ++iter; |
| 752 |
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1 | EXPECT_TRUE(!filter.valid(iter)); |
| 753 |
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1 | ++iter; |
| 754 |
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1 | EXPECT_TRUE(!iter); |
| 755 | |||
| 756 | ++leafIter; | ||
| 757 |
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1 | iter = leafIter->beginIndexOn(); |
| 758 |
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1 | filter.reset(*leafIter); |
| 759 | |||
| 760 |
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1 | EXPECT_TRUE(iter); |
| 761 |
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1 | EXPECT_TRUE(!filter.valid(iter)); |
| 762 |
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1 | ++iter; |
| 763 |
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1 | EXPECT_TRUE(!iter); |
| 764 | } | ||
| 765 | |||
| 766 | { // capture everything but the second point (min > max) | ||
| 767 | 1 | LSFilter filter(*sphere, points->transform(), -0.25f, -0.3f); | |
| 768 | auto leafIter = points->tree().cbeginLeaf(); | ||
| 769 |
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1 | auto iter = leafIter->beginIndexOn(); |
| 770 |
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1 | filter.reset(*leafIter); |
| 771 | |||
| 772 |
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1 | EXPECT_TRUE(!filter.valid(iter)); |
| 773 |
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1 | ++iter; |
| 774 |
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1 | EXPECT_TRUE(filter.valid(iter)); |
| 775 |
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1 | ++iter; |
| 776 |
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1 | EXPECT_TRUE(!iter); |
| 777 | |||
| 778 | ++leafIter; | ||
| 779 |
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1 | iter = leafIter->beginIndexOn(); |
| 780 |
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1 | filter.reset(*leafIter); |
| 781 | |||
| 782 |
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1 | EXPECT_TRUE(iter); |
| 783 |
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1 | EXPECT_TRUE(filter.valid(iter)); |
| 784 |
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1 | ++iter; |
| 785 |
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1 | EXPECT_TRUE(!iter); |
| 786 | } | ||
| 787 | |||
| 788 | { | ||
| 789 |
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1 | std::vector<Vec3s> positions{{1, 1, 1}, {1, 2, 1}, {10.1f, 10, 1}}; |
| 790 | |||
| 791 | const double voxelSize(0.25); | ||
| 792 |
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1 | math::Transform::Ptr transform(math::Transform::createLinearTransform(voxelSize)); |
| 793 | |||
| 794 |
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2 | points = createPointDataGrid<NullCodec, PointDataGrid>(positions, *transform); |
| 795 | } | ||
| 796 | |||
| 797 | { | ||
| 798 | double voxelSize = 1.0; | ||
| 799 |
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1 | sphere = FloatGrid::create(/*backgroundValue=*/5.0); |
| 800 |
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2 | sphere->setTransform(math::Transform::createLinearTransform(voxelSize)); |
| 801 | |||
| 802 | const openvdb::Coord dim(40, 40, 40); | ||
| 803 | const openvdb::Vec3f center(10.0f, 10.0f, 0.1f); | ||
| 804 | const float radius = 0.2f; | ||
| 805 |
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1 | makeSphere<FloatGrid>(dim, center, radius, *sphere); |
| 806 | } | ||
| 807 | |||
| 808 | { // capture only the last point using a different transform and a new sphere | ||
| 809 | 1 | LSFilter filter(*sphere, points->transform(), 0.5f, 1.0f); | |
| 810 | auto leafIter = points->tree().cbeginLeaf(); | ||
| 811 |
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1 | auto iter = leafIter->beginIndexOn(); |
| 812 |
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1 | filter.reset(*leafIter); |
| 813 | |||
| 814 |
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1 | EXPECT_TRUE(!filter.valid(iter)); |
| 815 |
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1 | ++iter; |
| 816 |
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1 | EXPECT_TRUE(!iter); |
| 817 | |||
| 818 | ++leafIter; | ||
| 819 |
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1 | iter = leafIter->beginIndexOn(); |
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1 | filter.reset(*leafIter); |
| 821 | |||
| 822 |
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1 | EXPECT_TRUE(!filter.valid(iter)); |
| 823 |
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1 | ++iter; |
| 824 |
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1 | EXPECT_TRUE(!iter); |
| 825 | |||
| 826 | ++leafIter; | ||
| 827 |
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1 | iter = leafIter->beginIndexOn(); |
| 828 |
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1 | filter.reset(*leafIter); |
| 829 | |||
| 830 |
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1 | EXPECT_TRUE(iter); |
| 831 |
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1 | EXPECT_TRUE(filter.valid(iter)); |
| 832 |
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1 | ++iter; |
| 833 |
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1 | EXPECT_TRUE(!iter); |
| 834 | } | ||
| 835 | 1 | } | |
| 836 | |||
| 837 | |||
| 838 |
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2 | TEST_F(TestIndexFilter, testBBoxFilter) |
| 839 | { | ||
| 840 | 1 | std::vector<Vec3s> positions{{1, 1, 1}, {1, 2, 1}, {10.1f, 10, 1}}; | |
| 841 | |||
| 842 | const float voxelSize(0.5); | ||
| 843 |
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1 | math::Transform::Ptr transform(math::Transform::createLinearTransform(voxelSize)); |
| 844 | |||
| 845 |
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1 | PointDataGrid::Ptr grid = createPointDataGrid<NullCodec, PointDataGrid>(positions, *transform); |
| 846 | PointDataTree& tree = grid->tree(); | ||
| 847 | |||
| 848 | // check one leaf per point | ||
| 849 |
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1 | EXPECT_EQ(tree.leafCount(), Index32(2)); |
| 850 | |||
| 851 | // build some bounding box filters to test | ||
| 852 | |||
| 853 |
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1 | BBoxFilter filter1(*transform, BBoxd({0.5, 0.5, 0.5}, {1.5, 1.5, 1.5})); |
| 854 |
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1 | BBoxFilter filter2(*transform, BBoxd({0.5, 0.5, 0.5}, {1.5, 2.01, 1.5})); |
| 855 |
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1 | BBoxFilter filter3(*transform, BBoxd({0.5, 0.5, 0.5}, {11, 11, 1.5})); |
| 856 |
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1 | BBoxFilter filter4(*transform, BBoxd({-10, 0, 0}, {11, 1.2, 1.2})); |
| 857 | |||
| 858 | { // construction, copy construction | ||
| 859 |
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1 | EXPECT_TRUE(!filter1.initialized()); |
| 860 |
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1 | BBoxFilter filter5 = filter1; |
| 861 |
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1 | EXPECT_TRUE(!filter5.initialized()); |
| 862 | |||
| 863 |
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1 | filter1.reset(*tree.cbeginLeaf()); |
| 864 |
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1 | EXPECT_TRUE(filter1.initialized()); |
| 865 |
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1 | BBoxFilter filter6 = filter1; |
| 866 |
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1 | EXPECT_TRUE(filter6.initialized()); |
| 867 | } | ||
| 868 | |||
| 869 | // leaf 1 | ||
| 870 | |||
| 871 | auto leafIter = tree.cbeginLeaf(); | ||
| 872 | |||
| 873 | { | ||
| 874 |
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1 | auto iter(leafIter->beginIndexOn()); |
| 875 | |||
| 876 | // point 1 | ||
| 877 | |||
| 878 |
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1 | filter1.reset(*leafIter); |
| 879 |
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1 | EXPECT_TRUE(filter1.valid(iter)); |
| 880 |
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1 | filter2.reset(*leafIter); |
| 881 |
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1 | EXPECT_TRUE(filter2.valid(iter)); |
| 882 |
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1 | filter3.reset(*leafIter); |
| 883 |
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1 | EXPECT_TRUE(filter3.valid(iter)); |
| 884 |
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1 | filter4.reset(*leafIter); |
| 885 |
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1 | EXPECT_TRUE(filter4.valid(iter)); |
| 886 | |||
| 887 |
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1 | ++iter; |
| 888 | |||
| 889 | // point 2 | ||
| 890 | |||
| 891 |
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1 | filter1.reset(*leafIter); |
| 892 |
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1 | EXPECT_TRUE(!filter1.valid(iter)); |
| 893 |
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1 | filter2.reset(*leafIter); |
| 894 |
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1 | EXPECT_TRUE(filter2.valid(iter)); |
| 895 |
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1 | filter3.reset(*leafIter); |
| 896 |
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1 | EXPECT_TRUE(filter3.valid(iter)); |
| 897 |
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1 | filter4.reset(*leafIter); |
| 898 |
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1 | EXPECT_TRUE(!filter4.valid(iter)); |
| 899 | |||
| 900 |
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1 | ++iter; |
| 901 |
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1 | EXPECT_TRUE(!iter); |
| 902 | } | ||
| 903 | |||
| 904 | ++leafIter; | ||
| 905 | |||
| 906 | // leaf 2 | ||
| 907 | |||
| 908 | { | ||
| 909 |
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1 | auto iter(leafIter->beginIndexOn()); |
| 910 | |||
| 911 | // point 3 | ||
| 912 | |||
| 913 |
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1 | filter1.reset(*leafIter); |
| 914 |
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1 | EXPECT_TRUE(!filter1.valid(iter)); |
| 915 |
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1 | filter2.reset(*leafIter); |
| 916 |
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1 | EXPECT_TRUE(!filter2.valid(iter)); |
| 917 |
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1 | filter3.reset(*leafIter); |
| 918 |
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1 | EXPECT_TRUE(filter3.valid(iter)); |
| 919 |
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1 | filter4.reset(*leafIter); |
| 920 |
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1 | EXPECT_TRUE(!filter4.valid(iter)); |
| 921 | |||
| 922 |
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1 | ++iter; |
| 923 |
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1 | EXPECT_TRUE(!iter); |
| 924 | } | ||
| 925 | 1 | } | |
| 926 | |||
| 927 | |||
| 928 | struct NeedsInitializeFilter | ||
| 929 | { | ||
| 930 |
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1 | inline bool initialized() const { return mInitialized; } |
| 931 | static index::State state() { return index::PARTIAL; } | ||
| 932 | template <typename LeafT> | ||
| 933 | inline index::State state(const LeafT&) { return index::PARTIAL; } | ||
| 934 | template <typename LeafT> | ||
| 935 | void reset(const LeafT&) { mInitialized = true; } | ||
| 936 | private: | ||
| 937 | bool mInitialized = false; | ||
| 938 | }; | ||
| 939 | |||
| 940 | |||
| 941 |
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1 | TEST_F(TestIndexFilter, testBinaryFilter) |
| 942 | { | ||
| 943 | const int intMax = std::numeric_limits<int>::max(); | ||
| 944 | |||
| 945 | { // construction, copy construction | ||
| 946 | using InitializeBinaryFilter = BinaryFilter<NeedsInitializeFilter, NeedsInitializeFilter, /*And=*/true>; | ||
| 947 | |||
| 948 | 1 | NeedsInitializeFilter needs1; | |
| 949 |
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1 | NeedsInitializeFilter needs2; |
| 950 | InitializeBinaryFilter filter(needs1, needs2); | ||
| 951 | EXPECT_TRUE(filter.state() == index::PARTIAL); | ||
| 952 |
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1 | EXPECT_TRUE(!filter.initialized()); |
| 953 |
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1 | InitializeBinaryFilter filter2 = filter; |
| 954 |
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1 | EXPECT_TRUE(!filter2.initialized()); |
| 955 | |||
| 956 | filter.reset(OriginLeaf(Coord(0, 0, 0))); | ||
| 957 | EXPECT_TRUE(filter.initialized()); | ||
| 958 | InitializeBinaryFilter filter3 = filter; | ||
| 959 | EXPECT_TRUE(filter3.initialized()); | ||
| 960 | } | ||
| 961 | |||
| 962 | using LessThanFilter = ThresholdFilter<true>; | ||
| 963 | using GreaterThanFilter = ThresholdFilter<false>; | ||
| 964 | |||
| 965 | { // less than | ||
| 966 | LessThanFilter zeroFilter(0); // all invalid | ||
| 967 | EXPECT_TRUE(zeroFilter.state() == index::NONE); | ||
| 968 | LessThanFilter maxFilter(intMax); // all valid | ||
| 969 | EXPECT_TRUE(maxFilter.state() == index::ALL); | ||
| 970 | |||
| 971 | LessThanFilter filter(5); | ||
| 972 | filter.reset(OriginLeaf(Coord(0, 0, 0))); | ||
| 973 | std::vector<int> values; | ||
| 974 | |||
| 975 |
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101 | for (SimpleIter iter; *iter < 100; ++iter) { |
| 976 |
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100 | if (filter.valid(iter)) values.push_back(*iter); |
| 977 | } | ||
| 978 | |||
| 979 |
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1 | EXPECT_EQ(values.size(), size_t(5)); |
| 980 | |||
| 981 |
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6 | for (int i = 0; i < 5; i++) { |
| 982 |
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5 | EXPECT_EQ(values[i], i); |
| 983 | } | ||
| 984 | } | ||
| 985 | |||
| 986 | { // greater than | ||
| 987 | GreaterThanFilter zeroFilter(0); // all valid | ||
| 988 | EXPECT_TRUE(zeroFilter.state() == index::ALL); | ||
| 989 | GreaterThanFilter maxFilter(intMax); // all invalid | ||
| 990 | EXPECT_TRUE(maxFilter.state() == index::NONE); | ||
| 991 | |||
| 992 | GreaterThanFilter filter(94); | ||
| 993 | filter.reset(OriginLeaf(Coord(0, 0, 0))); | ||
| 994 | std::vector<int> values; | ||
| 995 | |||
| 996 |
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101 | for (SimpleIter iter; *iter < 100; ++iter) { |
| 997 |
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100 | if (filter.valid(iter)) values.push_back(*iter); |
| 998 | } | ||
| 999 | |||
| 1000 |
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1 | EXPECT_EQ(values.size(), size_t(5)); |
| 1001 | |||
| 1002 | int offset = 0; | ||
| 1003 |
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6 | for (int i = 95; i < 100; i++) { |
| 1004 |
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5 | EXPECT_EQ(values[offset++], i); |
| 1005 | } | ||
| 1006 | } | ||
| 1007 | |||
| 1008 | { // binary and | ||
| 1009 | using RangeFilter = BinaryFilter<LessThanFilter, GreaterThanFilter, /*And=*/true>; | ||
| 1010 | |||
| 1011 | 1 | RangeFilter zeroFilter(LessThanFilter(0), GreaterThanFilter(10)); // all invalid | |
| 1012 |
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1 | EXPECT_TRUE(zeroFilter.state() == index::NONE); |
| 1013 | 1 | RangeFilter maxFilter(LessThanFilter(intMax), GreaterThanFilter(0)); // all valid | |
| 1014 |
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1 | EXPECT_TRUE(maxFilter.state() == index::ALL); |
| 1015 | |||
| 1016 | 1 | RangeFilter filter(LessThanFilter(55), GreaterThanFilter(45)); | |
| 1017 |
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1 | EXPECT_TRUE(filter.state() == index::PARTIAL); |
| 1018 | |||
| 1019 | filter.reset(OriginLeaf(Coord(0, 0, 0))); | ||
| 1020 | |||
| 1021 | std::vector<int> values; | ||
| 1022 | |||
| 1023 |
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101 | for (SimpleIter iter; *iter < 100; ++iter) { |
| 1024 |
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9 | if (filter.valid(iter)) values.push_back(*iter); |
| 1025 | } | ||
| 1026 | |||
| 1027 |
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1 | EXPECT_EQ(values.size(), size_t(9)); |
| 1028 | |||
| 1029 | int offset = 0; | ||
| 1030 |
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10 | for (int i = 46; i < 55; i++) { |
| 1031 |
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9 | EXPECT_EQ(values[offset++], i); |
| 1032 | } | ||
| 1033 | } | ||
| 1034 | |||
| 1035 | { // binary or | ||
| 1036 | using HeadTailFilter = BinaryFilter<LessThanFilter, GreaterThanFilter, /*And=*/false>; | ||
| 1037 | |||
| 1038 | 1 | HeadTailFilter zeroFilter(LessThanFilter(0), GreaterThanFilter(10)); // some valid | |
| 1039 |
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1 | EXPECT_TRUE(zeroFilter.state() == index::PARTIAL); |
| 1040 | 1 | HeadTailFilter maxFilter(LessThanFilter(intMax), GreaterThanFilter(0)); // all valid | |
| 1041 |
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1 | EXPECT_TRUE(maxFilter.state() == index::ALL); |
| 1042 | |||
| 1043 | 1 | HeadTailFilter filter(LessThanFilter(5), GreaterThanFilter(95)); | |
| 1044 | filter.reset(OriginLeaf(Coord(0, 0, 0))); | ||
| 1045 | |||
| 1046 | std::vector<int> values; | ||
| 1047 | |||
| 1048 |
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101 | for (SimpleIter iter; *iter < 100; ++iter) { |
| 1049 |
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9 | if (filter.valid(iter)) values.push_back(*iter); |
| 1050 | } | ||
| 1051 | |||
| 1052 |
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1 | EXPECT_EQ(values.size(), size_t(9)); |
| 1053 | |||
| 1054 | int offset = 0; | ||
| 1055 |
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6 | for (int i = 0; i < 5; i++) { |
| 1056 |
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5 | EXPECT_EQ(values[offset++], i); |
| 1057 | } | ||
| 1058 |
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5 | for (int i = 96; i < 100; i++) { |
| 1059 |
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4 | EXPECT_EQ(values[offset++], i); |
| 1060 | } | ||
| 1061 | } | ||
| 1062 | 1 | } | |
| 1063 |