| /frameworks/data-binding/integration-tests/App With Spaces/gradle/wrapper/ |
| gradle-wrapper.properties | 19 distributionPath=wrapper/dists
21 zipStorePath=wrapper/dists
|
| /frameworks/data-binding/integration-tests/IndependentLibrary/gradle/wrapper/ |
| gradle-wrapper.properties | 18 distributionPath=wrapper/dists
20 zipStorePath=wrapper/dists
|
| /frameworks/data-binding/integration-tests/MultiModuleTestApp/gradle/wrapper/ |
| gradle-wrapper.properties | 19 distributionPath=wrapper/dists
21 zipStorePath=wrapper/dists
|
| /external/opencv3/modules/flann/include/opencv2/flann/ |
| ground_truth.h | 49 std::vector<DistanceType> dists(n);
51 dists[0] = distance(dataset[0], query, dataset.cols);
60 dists[dcnt++] = tmp;
62 else if (tmp < dists[dcnt-1]) {
63 dists[dcnt-1] = tmp;
69 while (j>=1 && dists[j]<dists[j-1]) {
70 std::swap(dists[j],dists[j-1]);
|
| nn_index.h | 64 * \param[out] dists Distances to the nearest neighbors found
68 virtual void knnSearch(const Matrix<ElementType>& queries, Matrix<int>& indices, Matrix<DistanceType>& dists, int knn, const SearchParams& params)
72 assert(dists.rows >= queries.rows);
74 assert(int(dists.cols) >= knn);
79 resultSet.init(indices[i], dists[i]);
87 if (get_param(params,"sorted",true)) resultSet.sortAndCopy(indices[i], dists[i], knn);
88 else resultSet.copy(indices[i], dists[i], knn);
97 * \param[out] dists The distances to the nearest neighbors found
102 virtual int radiusSearch(const Matrix<ElementType>& query, Matrix<int>& indices, Matrix<DistanceType>& dists, float radius, const SearchParams& params)
109 assert(indices.cols == dists.cols)
[all...] |
| result_set.h | 88 DistanceType* dists; member in class:cvflann::KNNSimpleResultSet
101 dists = dists_;
104 dists[capacity-1] = worst_distance_;
124 if ( (dists[i-1]>dist) || ((dist==dists[i-1])&&(indices[i-1]>index)) )
126 if (dists[i-1]>dist)
130 dists[i] = dists[i-1];
137 dists[i] = dist;
139 worst_distance_ = dists[capacity-1]
155 DistanceType* dists; member in class:cvflann::KNNResultSet
233 DistanceType* dists; member in class:cvflann::RadiusResultSet
[all...] |
| kdtree_single_index.h | 208 * \param[out] dists Distances to the nearest neighbors found
212 void knnSearch(const Matrix<ElementType>& queries, Matrix<int>& indices, Matrix<DistanceType>& dists, int knn, const SearchParams& params)
216 assert(dists.rows >= queries.rows);
218 assert(int(dists.cols) >= knn);
222 resultSet.init(indices[i], dists[i]);
245 std::vector<DistanceType> dists(dim_,0);
246 DistanceType distsq = computeInitialDistances(vec, dists);
247 searchLevel(result, vec, root_node_, distsq, dists, epsError);
521 DistanceType computeInitialDistances(const ElementType* vec, std::vector<DistanceType>& dists)
527 dists[i] = distance_.accum_dist(vec[i], root_bbox_[i].low, (int)i)
[all...] |
| flann_base.hpp | 210 * \param[out] dists Distances to the nearest neighbors found
214 void knnSearch(const Matrix<ElementType>& queries, Matrix<int>& indices, Matrix<DistanceType>& dists, int knn, const SearchParams& params)
216 nnIndex_->knnSearch(queries, indices, dists, knn, params);
223 * \param[out] dists The distances to the nearest neighbors found
228 int radiusSearch(const Matrix<ElementType>& query, Matrix<int>& indices, Matrix<DistanceType>& dists, float radius, const SearchParams& params)
230 return nnIndex_->radiusSearch(query, indices, dists, radius, params);
|
| lsh_index.h | 186 * \param[out] dists Distances to the nearest neighbors found
190 virtual void knnSearch(const Matrix<ElementType>& queries, Matrix<int>& indices, Matrix<DistanceType>& dists, int knn, const SearchParams& params)
194 assert(dists.rows >= queries.rows);
196 assert(int(dists.cols) >= knn);
203 std::fill_n(dists[i], knn, std::numeric_limits<DistanceType>::max());
205 if (get_param(params,"sorted",true)) resultSet.sortAndCopy(indices[i], dists[i], knn);
206 else resultSet.copy(indices[i], dists[i], knn);
|
| miniflann.hpp | 137 OutputArray dists, int knn, const SearchParams& params=SearchParams());
140 OutputArray dists, double radius, int maxResults,
|
| /external/opencv3/modules/flann/include/opencv2/ |
| flann.hpp | 211 @param dists Vector that will contain the distances to the K-nearest neighbors found. It must have
217 std::vector<DistanceType>& dists, int knn, const ::cvflann::SearchParams& params);
218 void knnSearch(const Mat& queries, Mat& indices, Mat& dists, int knn, const ::cvflann::SearchParams& params);
221 std::vector<DistanceType>& dists, DistanceType radius, const ::cvflann::SearchParams& params);
222 int radiusSearch(const Mat& query, Mat& indices, Mat& dists,
271 void GenericIndex<Distance>::knnSearch(const std::vector<ElementType>& query, std::vector<int>& indices, std::vector<DistanceType>& dists, int knn, const ::cvflann::SearchParams& searchParams)
275 ::cvflann::Matrix<DistanceType> m_dists(&dists[0], 1, dists.size());
284 void GenericIndex<Distance>::knnSearch(const Mat& queries, Mat& indices, Mat& dists, int knn, const ::cvflann::SearchParams& searchParams)
294 CV_Assert(dists.type() == CvType<DistanceType>::type())
[all...] |
| /external/zopfli/src/zopfli/ |
| lz77.h | 37 Parameter dists: Contains the distances. A value is 0 to indicate that there is
39 Parameter size: The size of both the litlens and dists arrays.
46 unsigned short* dists; /* If 0: indicates literal in corresponding litlens, member in struct:ZopfliLZ77Store
106 dists: ll77 distances
107 start: where to begin counting in litlens and dists
108 end: where to stop counting in litlens and dists (not inclusive)
114 const unsigned short* dists,
|
| blocksplitter.c | 102 dists: ll77 distances
107 const unsigned short* dists,
109 return ZopfliCalculateBlockSize(litlens, dists, lstart, lend, 2);
114 const unsigned short* dists; member in struct:SplitCostContext
128 return EstimateCost(c->litlens, c->dists, c->start, i) +
129 EstimateCost(c->litlens, c->dists, i, c->end);
151 const unsigned short* dists,
162 size_t length = dists[i] == 0 ? 1 : litlens[i];
220 const unsigned short* dists,
246 c.dists = dists
[all...] |
| deflate.h | 74 dists: ll77 distances
79 const unsigned short* dists,
|
| blocksplitter.h | 40 dists: lz77 distances
41 llsize: size of litlens and dists
46 const unsigned short* dists,
|
| squeeze.c | 34 /* The 32 unique dist symbols, not the 32768 possible dists. */
35 size_t dists[32]; member in struct:SymbolStats
44 memset(stats->dists, 0, 32 * sizeof(stats->dists[0]));
52 memcpy(dest->dists, source->dists, 32 * sizeof(dest->dists[0]));
69 result->dists[i] =
70 (size_t) (stats1->dists[i] * w1 + stats2->dists[i] * w2)
[all...] |
| lz77.c | 30 store->dists = 0;
35 free(store->dists);
44 dest->dists = (unsigned short*)malloc(sizeof(*dest->dists) * source->size);
46 if (!dest->litlens || !dest->dists) exit(-1); /* Allocation failed. */
51 dest->dists[i] = source->dists[i];
63 ZOPFLI_APPEND_DATA(dist, &store->dists, &size2);
460 const unsigned short* dists,
473 if (dists[i] == 0)
[all...] |
| deflate.c | 298 const unsigned short* dists,
309 unsigned dist = dists[i];
351 const unsigned short* dists,
356 if (dists[i] == 0) {
360 result += d_lengths[ZopfliGetDistSymbol(dists[i])];
362 result += ZopfliGetDistExtraBits(dists[i]);
474 const unsigned short* dists,
480 ZopfliLZ77Counts(litlens, dists, lstart, lend, ll_counts, d_counts);
489 const unsigned short* dists,
501 GetDynamicLengths(litlens, dists, lstart, lend, ll_lengths, d_lengths)
[all...] |
| /external/opencv3/modules/flann/src/ |
| miniflann.cpp | 462 void runKnnSearch_(void* index, const Mat& query, Mat& indices, Mat& dists,
469 CV_Assert(query.type() == type && indices.type() == CV_32S && dists.type() == dtype);
470 CV_Assert(query.isContinuous() && indices.isContinuous() && dists.isContinuous());
474 ::cvflann::Matrix<DistanceType> _dists(dists.ptr<DistanceType>(), dists.rows, dists.cols);
481 void runKnnSearch(void* index, const Mat& query, Mat& indices, Mat& dists,
484 runKnnSearch_<Distance, ::cvflann::Index<Distance> >(index, query, indices, dists, knn, params);
488 int runRadiusSearch_(void* index, const Mat& query, Mat& indices, Mat& dists,
495 CV_Assert(query.type() == type && indices.type() == CV_32S && dists.type() == dtype)
554 Mat query = _query.getMat(), indices, dists; local
596 Mat query = _query.getMat(), indices, dists; local
[all...] |
| /external/opencv3/modules/features2d/src/ |
| blobdetector.cpp | 281 std::vector<double> dists; local
285 dists.push_back(norm(center.location - pt));
287 std::sort(dists.begin(), dists.end());
288 center.radius = (dists[(dists.size() - 1) / 2] + dists[dists.size() / 2]) / 2.;
|
| /cts/apps/CameraITS/tests/sensor_fusion/ |
| test_sensor_fusion.py | 146 dists = []
150 dists.append(scipy.spatial.distance.correlation(cam_rots, gyro_rots))
151 best_corr_dist = min(dists)
152 best_shift = candidates[dists.index(best_corr_dist)]
160 i = len(dists)/2 + best_shift
162 dists = dists[i-20:i+21]
163 a,b,c = numpy.polyfit(candidates, dists, 2)
172 pylab.plot(candidates, dists, 'r', label="data")
|
| /external/chromium-trace/catapult/third_party/gsutil/third_party/boto/bin/ |
| cfadmin | 7 def _print_distributions(dists):
11 for d in dists:
|
| /external/opencv3/modules/features2d/test/ |
| test_nearestneighbors.cpp | 193 vector<float> dists( dist.cols, 0 );
194 index->knnSearch( query, indices, dists, knn, SearchParams() );
226 vector<float> dists( dist.cols, 0 );
227 index->radiusSearch( query, indices, dists, radius, neighbors.cols, SearchParams() );
|
| /external/chromium-trace/catapult/telemetry/telemetry/internal/image_processing/ |
| cv_util_unittest.py | 107 dists = self.cv_util.SqDistance(p1, p2)
108 self.assertEqual(dists[0], 8)
109 self.assertEqual(dists[1], 13)
|
| /external/opencv3/modules/ml/src/ |
| knearest.cpp | 145 Mat* dists, float* presult ) const
222 if( dists )
224 float* dptr = dists->ptr<float>(testidx + range.start);
|
