/dports/math/mlpack/mlpack-3.4.2/src/mlpack/methods/neighbor_search/ |
H A D | knn_main.cpp | 193 KNNModel* knn; in mlpackMain() local 256 knn->Tau() = tau; in mlpackMain() 257 knn->Rho() = rho; in mlpackMain() 284 << knn->Dataset().n_rows << "x" << knn->Dataset().n_cols in mlpackMain() 304 delete knn; in mlpackMain() 318 delete knn; in mlpackMain() 331 delete knn; in mlpackMain() 350 if (knn->TreeType() != KNNModel::SPILL_TREE && knn->Epsilon() == 0) in mlpackMain() 362 delete knn; in mlpackMain() 374 if (knn->TreeType() != KNNModel::SPILL_TREE && knn->Epsilon() == 0) in mlpackMain() [all …]
|
/dports/biology/py-biopython/biopython-1.79/Bio/ |
H A D | kNN.py | 66 knn = kNN() 67 knn.classes = set(ys) 69 knn.ys = ys 70 knn.k = k 71 return knn 94 for i in range(len(knn.xs)): 102 for i in range(len(knn.xs)): 103 temp[:] = x - knn.xs[i] 110 for k in knn.classes: 112 for dist, i in order[: knn.k]: [all …]
|
/dports/math/R-cran-spdep/spdep/R/ |
H A D | knn2nb.R | 5 knn2nb <- function(knn, row.names=NULL, sym=FALSE) { argument 6 if (class(knn) != "knn") stop("Not a knn object") 7 res <- vector(mode="list", length=knn$np) 9 if(length(row.names) != knn$np) 14 if (knn$np < 1) stop("non-positive number of spatial units") 15 if (is.null(row.names)) row.names <- as.character(1:knn$np) 17 to<-as.vector(knn$nn) 18 from<-rep(1:knn$np,knn$k) 22 for (i in 1:knn$np) res[[i]] <- sort(knn$nn[i,]) 25 attr(res, "call") <- attr(knn, "call") [all …]
|
/dports/graphics/appleseed/appleseed-2.1.0-beta/src/appleseed/foundation/meta/tests/ |
H A D | test_knn.cpp | 56 knn::Tree3d tree; in TEST_SUITE() 66 knn::Tree3d tree; in TEST_SUITE() 68 knn::Builder3d builder(tree); in TEST_SUITE() 91 knn::Tree3d tree; in TEST_SUITE() 93 knn::Builder3d builder(tree); in TEST_SUITE() 127 knn::Tree3d tree; in TEST_SUITE() 140 knn::Tree3d tree; in TEST_SUITE() 254 knn::Tree3d tree; in TEST_SUITE() 275 knn::Tree3d tree; in TEST_SUITE() 311 knn::Tree3d tree; in TEST_SUITE() [all …]
|
/dports/math/R-cran-igraph/igraph/tests/testthat/ |
H A D | test_graph.knn.R | 10 expect_that(knn(g), equals(list(knn=rep(2,10), knnk=c(NaN, 2)))) nameattr 13 expect_that(knn(g2), equals(list(knn=c(1, rep(9,9)), nameattr in c 18 r3 <- knn(g3) 19 expect_that(r3$knn[43], equals(46)) 20 expect_that(r3$knn[1000], equals(192.4)) 26 r4 <- knn(g4) 27 expect_that(r4$knn[1000], equals(20/3)) 34 r5 <- knn(g5) 35 expect_that(r5, equals(structure(list(knn = c(1, rep(9, 9)), knnk = nameattr in c
|
/dports/math/flann/flann-1.9.1-29-g1d04523/test/ |
H A D | flann_kmeans_test.cpp | 25 query, indices, dists, knn, flann::SearchParams(128), 0.75, gt_indices); in TEST_F() 31 query, indices, dists, knn, flann::SearchParams(128), 0.75, gt_indices); in TEST_F() 38 query, indices, dists, knn, flann::SearchParams(110), 0.75, gt_indices); in TEST_F() 44 query, indices, dists, knn, flann::SearchParams(110), 0.75, gt_indices); in TEST_F() 50 query, indices, dists, knn, flann::SearchParams(128)); in TEST_F() 58 query, indices, dists, knn, flann::SearchParams(128), 0.75, gt_indices); in TEST_F() 65 query, indices, dists, knn, flann::SearchParams(128), 0.75, gt_indices); in TEST_F() 72 query, indices, dists, knn, flann::SearchParams(128), 0.75, gt_indices); in TEST_F() 87 query, indices, dists, knn, flann::SearchParams(96), 0.75, gt_indices); in TEST_F() 107 dists, knn, flann::SearchParams(128) ); in TEST_F() [all …]
|
H A D | flann_kdtree_test.cpp | 22 dists, knn, flann::SearchParams(256), 0.75, gt_indices); in TEST_F() 28 dists, knn, flann::SearchParams(256), 0.75, gt_indices); in TEST_F() 35 dists, knn, flann::SearchParams(256), 0.75, gt_indices); in TEST_F() 41 dists, knn, flann::SearchParams(256), 0.75, gt_indices); in TEST_F() 47 dists, knn, flann::SearchParams(256) ); in TEST_F() 54 dists, knn, flann::SearchParams(256), 0.75, gt_indices); in TEST_F() 61 dists, knn, flann::SearchParams(256), 0.75, gt_indices); in TEST_F() 67 dists, knn, flann::SearchParams(256), 0.75, gt_indices); in TEST_F() 82 dists, knn, flann::SearchParams(128), 0.75, gt_indices); in TEST_F() 89 dists, knn, flann::SearchParams(256), 0.75, gt_indices); in TEST_F() [all …]
|
H A D | flann_tests.h | 137 size_t knn, 174 size_t knn, 210 size_t knn, 261 flann::Matrix<size_t> indices2(new size_t[query.rows*knn], query.rows, knn); 282 size_t knn, 355 size_t knn, 427 size_t knn, 499 size_t knn, 570 size_t knn, in TestRemove() argument 688 int knn; variable [all …]
|
H A D | flann_linear_test.cpp | 23 query, indices, dists, knn, flann::SearchParams(0), 1.0, gt_indices); in TEST_F() 29 query, indices, dists, knn, flann::SearchParams(0), 1.0, gt_indices); in TEST_F() 35 query, indices, dists, knn, flann::SearchParams(0)); in TEST_F() 42 query, indices, dists, knn, flann::SearchParams(0), 1.0, gt_indices); in TEST_F() 48 query, indices, dists, knn, flann::SearchParams(0), 1.0, gt_indices); in TEST_F() 55 query, indices, dists, knn, flann::SearchParams(0), 1.0, gt_indices); in TEST_F() 71 query, indices, dists, knn, flann::SearchParams(0), 1.0, gt_indices); in TEST_F() 88 query, indices, dists, knn, flann::SearchParams(0), 1.0, gt_indices); in TEST_F() 104 query, indices, dists, knn, flann::SearchParams(0), 1.0, gt_indices); in TEST_F()
|
/dports/math/R-cran-dimRed/dimRed/R/ |
H A D | graph_embed.R | 53 knn = 100, 66 knn = pars$knn, 136 knn = 100, 149 knn = pars$knn, 212 knn = 100, 225 knn = pars$knn, 247 knn = 50, d = stats::dist, argument 252 data.graph <- construct_knn_graph(data.dist, knn) 262 construct_knn_graph <- function (data.dist, knn) { argument 272 if (is.infinite(knn) || is.na(knn)) [all …]
|
/dports/graphics/colmap/colmap-3.6/lib/FLANN/algorithms/ |
H A D | kdtree_cuda_3d_index.h | 197 return knn*queries.rows; // hack... in knnSearch() 211 size_t knn, in knnSearch() argument 215 return knn*queries.rows; // hack... in knnSearch() 231 size_t knn, in knnSearchGpu() argument 234 flann::Matrix<int> ind( new int[knn*queries.rows], queries.rows,knn); in knnSearchGpu() 235 flann::Matrix<DistanceType> dist( new DistanceType[knn*queries.rows], queries.rows,knn); in knnSearchGpu() 236 knnSearchGpu(queries,ind,dist,knn,params); in knnSearchGpu() 238 indices[i].resize(knn); in knnSearchGpu() 239 dists[i].resize(knn); in knnSearchGpu() 240 for( size_t j=0; j<knn; j++ ) { in knnSearchGpu() [all …]
|
/dports/math/flann/flann-1.9.1-29-g1d04523/src/cpp/flann/algorithms/ |
H A D | kdtree_cuda_3d_index.h | 197 return knn*queries.rows; // hack... in knnSearch() 211 size_t knn, in knnSearch() argument 215 return knn*queries.rows; // hack... in knnSearch() 231 size_t knn, in knnSearchGpu() argument 234 flann::Matrix<int> ind( new int[knn*queries.rows], queries.rows,knn); in knnSearchGpu() 235 flann::Matrix<DistanceType> dist( new DistanceType[knn*queries.rows], queries.rows,knn); in knnSearchGpu() 236 knnSearchGpu(queries,ind,dist,knn,params); in knnSearchGpu() 238 indices[i].resize(knn); in knnSearchGpu() 239 dists[i].resize(knn); in knnSearchGpu() 240 for( size_t j=0; j<knn; j++ ) { in knnSearchGpu() [all …]
|
/dports/misc/openmvg/openMVG-2.0/src/third_party/flann/src/cpp/flann/algorithms/ |
H A D | kdtree_cuda_3d_index.h | 197 return knn*queries.rows; // hack... in knnSearch() 211 size_t knn, in knnSearch() argument 215 return knn*queries.rows; // hack... in knnSearch() 231 size_t knn, in knnSearchGpu() argument 234 flann::Matrix<int> ind( new int[knn*queries.rows], queries.rows,knn); in knnSearchGpu() 235 flann::Matrix<DistanceType> dist( new DistanceType[knn*queries.rows], queries.rows,knn); in knnSearchGpu() 236 knnSearchGpu(queries,ind,dist,knn,params); in knnSearchGpu() 238 indices[i].resize(knn); in knnSearchGpu() 239 dists[i].resize(knn); in knnSearchGpu() 240 for( size_t j=0; j<knn; j++ ) { in knnSearchGpu() [all …]
|
/dports/misc/vxl/vxl-3.3.2/contrib/mul/clsfy/tests/ |
H A D | test_k_nearest_neighbour.cxx | 133 clsfy_k_nearest_neighbour knn; in test_k_nearest_neighbour() local 134 knn.set(data, labels); in test_k_nearest_neighbour() 135 knn.set_k(3); in test_k_nearest_neighbour() 142 knn.class_probabilities(out, x); in test_k_nearest_neighbour() 152 std::cout << knn.classify(x); in test_k_nearest_neighbour() 278 vsl_b_write(bfs_out,knn); in test_k_nearest_neighbour() 301 std::cout<<"Saved KNN: " << knn << std::endl in test_k_nearest_neighbour() 313 knn.n_classes() == knn_in.n_classes() && in test_k_nearest_neighbour() 314 knn.n_dims() == knn_in.n_dims() && in test_k_nearest_neighbour() 317 knn.k() == knn_in.k(), in test_k_nearest_neighbour() [all …]
|
/dports/misc/elki/elki-release0.7.1-1166-gfb1fffdf3/elki-index-preprocessed/src/main/resources/META-INF/elki/ |
H A D | de.lmu.ifi.dbs.elki.index.IndexFactory | 1 de.lmu.ifi.dbs.elki.index.preprocessed.knn.NNDescent$Factory 2 de.lmu.ifi.dbs.elki.index.preprocessed.knn.MaterializeKNNAndRKNNPreprocessor$Factory 3 de.lmu.ifi.dbs.elki.index.preprocessed.knn.MaterializeKNNPreprocessor$Factory 4 de.lmu.ifi.dbs.elki.index.preprocessed.knn.PartitionApproximationMaterializeKNNPreprocessor$Factory 5 de.lmu.ifi.dbs.elki.index.preprocessed.knn.RandomSampleKNNPreprocessor$Factory 6 de.lmu.ifi.dbs.elki.index.preprocessed.knn.SpacefillingMaterializeKNNPreprocessor$Factory 7 de.lmu.ifi.dbs.elki.index.preprocessed.knn.SpacefillingKNNPreprocessor$Factory 8 de.lmu.ifi.dbs.elki.index.preprocessed.knn.NaiveProjectedKNNPreprocessor$Factory
|
/dports/math/mlpack/mlpack-3.4.2/src/mlpack/tests/ |
H A D | knn_test.cpp | 328 KNN knn; variable 1286 KNN knn2(knn); 1460 delete knn; 1487 delete knn; 1521 delete knn; 1554 delete knn; 1587 delete knn; 1620 delete knn; 1651 delete knn; 1706 delete knn; [all …]
|
/dports/graphics/opencv/opencv-4.5.3/modules/ml/test/ |
H A D | test_knearest.cpp | 33 Ptr<KNearest> knn = KNearest::create(); in TEST() local 34 knn->train(trainData, ml::ROW_SAMPLE, trainLabels); in TEST() 35 knn->findNearest(testData, 4, bestLabels); in TEST() 43 Ptr<KNearest> knn = KNearest::create(); in TEST() local 44 knn->setAlgorithmType(KNearest::KDTREE); in TEST() 45 knn->train(trainData, ml::ROW_SAMPLE, trainLabels); in TEST() 46 knn->findNearest(testData, 4, neighborIndexes); in TEST() 72 Ptr<KNearest> knn = KNearest::create(); in TEST() local 73 knn->train(xTrainData, ml::ROW_SAMPLE, yTrainLabels); in TEST() 79 knn->findNearest(xTestData, K, zBestLabels, neighbours, dist); in TEST() [all …]
|
/dports/graphics/py-pointpats/pointpats-2.2.0/pointpats/tests/ |
H A D | test_pointpattern.py | 50 knn = self.pp.knn(1) 57 np.testing.assert_array_equal(knn[0], nn) 58 np.testing.assert_array_almost_equal(knn[1], nnd) 61 self.assertRaises(ValueError, self.pp.knn, k=0) 64 knn = self.pp.knn_other(self.pp) 67 np.testing.assert_array_equal(knn[0], nn) 68 np.testing.assert_array_equal(knn[1], nnd) 70 knn = self.pp.knn_other([0, 0], k=12) 75 np.testing.assert_array_equal(knn[0], nn) 76 np.testing.assert_array_almost_equal(knn[1], nnd)
|
/dports/graphics/embree/embree-3.13.2/tutorials/voronoi/ |
H A D | voronoi_device.cpp | 87 if (d < query->radius && (result->knn.size() < result->k || d < result->knn.top().d)) in pointQueryFunc() 94 result->knn.pop(); in pointQueryFunc() 96 result->knn.push(neighbour); in pointQueryFunc() 193 unsigned int primID = result.knn.empty() ? RTC_INVALID_GEOMETRY_ID : result.knn.top().primID; in renderTileStandard() 285 if (result.knn.empty()) in device_render() 289 result.knn.pop(); in device_render() 297 while (!result.knn.empty()) in device_render() 301 result.knn.pop(); in device_render() 340 if (!result.knn.empty()) in device_render() 384 while (!result.knn.empty()) in device_render() [all …]
|
/dports/math/mlpack/mlpack-3.4.2/src/mlpack/methods/lmnn/ |
H A D | constraints_impl.hpp | 91 KNN knn; in TargetNeighbors() local 100 knn.Train(dataset.cols(indexSame[i])); in TargetNeighbors() 101 knn.Search(k, neighbors, distances); in TargetNeighbors() 133 KNN knn; in TargetNeighbors() local 148 knn.Train(dataset.cols(indexSame[i])); in TargetNeighbors() 175 KNN knn; in Impostors() local 184 knn.Train(dataset.cols(indexDiff[i])); in Impostors() 213 KNN knn; in Impostors() local 256 KNN knn; in Impostors() local 305 KNN knn; in Impostors() local [all …]
|
/dports/graphics/opencv/opencv-4.5.3/modules/video/perf/ |
H A D | perf_bgfg_knn.cpp | 37 Ptr<cv::BackgroundSubtractorKNN> knn = createBackgroundSubtractorKNN(); in TEST_CYCLE() local 38 knn->setDetectShadows(false); in TEST_CYCLE() 42 knn->apply(frame_buffer[i], foreground); in TEST_CYCLE() 71 Ptr<cv::BackgroundSubtractorKNN> knn = createBackgroundSubtractorKNN(); in TEST_CYCLE() local 72 knn->setDetectShadows(false); in TEST_CYCLE() 77 knn->apply(frame_buffer[i], foreground); in TEST_CYCLE() 79 knn->getBackgroundImage(background); in TEST_CYCLE()
|
/dports/graphics/opencv/opencv-4.5.3/modules/video/perf/opencl/ |
H A D | perf_bgfg_knn.cpp | 42 Ptr<cv::BackgroundSubtractorKNN> knn = createBackgroundSubtractorKNN(); in OCL_TEST_CYCLE() local 43 knn->setDetectShadows(false); in OCL_TEST_CYCLE() 47 knn->apply(frame_buffer[i], u_foreground); in OCL_TEST_CYCLE() 76 Ptr<cv::BackgroundSubtractorKNN> knn = createBackgroundSubtractorKNN(); in OCL_TEST_CYCLE() local 77 knn->setDetectShadows(false); in OCL_TEST_CYCLE() 82 knn->apply(frame_buffer[i], u_foreground); in OCL_TEST_CYCLE() 84 knn->getBackgroundImage(u_background); in OCL_TEST_CYCLE()
|
/dports/graphics/appleseed/appleseed-2.1.0-beta/src/appleseed/foundation/meta/benchmarks/ |
H A D | benchmark_knn.cpp | 61 knn::Answer<float> m_answer; in BENCHMARK_SUITE() 170 knn::Query3f query(m_tree, m_answer); in BENCHMARK_SUITE() 189 knn::Tree3f m_tree; in BENCHMARK_SUITE() 190 knn::Answer<float> m_answer; in BENCHMARK_SUITE() 194 knn::QueryStatistics m_query_stats; in BENCHMARK_SUITE() 206 knn::Builder3f builder(m_tree); in BENCHMARK_SUITE() 213 knn::TreeStatistics<knn::Tree3f>(m_tree)).to_string().c_str()); in BENCHMARK_SUITE() 218 knn::Answer<float> answer(4); in BENCHMARK_SUITE() 219 knn::Query3f query(m_tree, answer); in BENCHMARK_SUITE()
|
/dports/math/R-cran-igraph/igraph/man/ |
H A D | knn.Rd | 3 \name{knn} 4 \alias{knn} 5 \alias{graph.knn} 8 knn( 21 both \sQuote{\code{knn}} and \sQuote{\code{knnk}} will be calculated based 41 A list with two members: \item{knn}{A numeric vector giving the 70 knn(g) 72 knn(g2) 76 knn(g3) 80 knn(g4) [all …]
|
/dports/graphics/hugin/hugin-2020.0.0/src/foreign/flann/algorithms/ |
H A D | nn_index.h | 88 assert(indices.cols >= knn); in knnSearch() 89 assert(dists.cols >= knn); in knnSearch() 93 use_heap = (knn>KNN_HEAP_THRESHOLD)?true:false; in knnSearch() 106 KNNResultSet2<DistanceType> resultSet(knn); in knnSearch() 115 KNNSimpleResultSet<DistanceType> resultSet(knn); in knnSearch() 159 size_t knn, in knnSearch() argument 165 use_heap = (knn>KNN_HEAP_THRESHOLD)?true:false; in knnSearch() 181 KNNResultSet2<DistanceType> resultSet(knn); in knnSearch() 185 size_t n = std::min(resultSet.size(), knn); in knnSearch() 193 KNNSimpleResultSet<DistanceType> resultSet(knn); in knnSearch() [all …]
|