/third_party/boost/libs/math/test/ |
D | univariate_statistics_test.cpp | 107 double mu = boost::math::statistics::mean(v); in test_integer_mean() 112 mu = boost::math::statistics::mean(w); in test_integer_mean() 118 double m1 = scale*boost::math::statistics::mean(v); in test_integer_mean() 123 double m2 = boost::math::statistics::mean(v); in test_integer_mean() 143 Real mu = boost::math::statistics::mean(v.begin(), v.end()); in test_mean() 147 mu = boost::math::statistics::mean(v); in test_mean() 151 mu = boost::math::statistics::mean(v.begin(), v.begin() + 3); in test_mean() 155 mu = boost::math::statistics::mean(v.cbegin(), v.cend()); in test_mean() 160 mu = boost::math::statistics::mean(u.begin(), u.end()); in test_mean() 165 mu = boost::math::statistics::mean(l.begin(), l.end()); in test_mean() [all …]
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D | signal_statistics_test.cpp | 42 Real hs = boost::math::statistics::hoyer_sparsity(v.begin(), v.end()); in test_hoyer_sparsity() 45 hs = boost::math::statistics::hoyer_sparsity(v); in test_hoyer_sparsity() 49 hs = boost::math::statistics::hoyer_sparsity(v.cbegin(), v.cend()); in test_hoyer_sparsity() 55 hs = boost::math::statistics::hoyer_sparsity(v.cbegin(), v.cend()); in test_hoyer_sparsity() 59 hs = boost::math::statistics::hoyer_sparsity(w); in test_hoyer_sparsity() 72 hs = boost::math::statistics::hoyer_sparsity(v); in test_hoyer_sparsity() 78 hs = boost::math::statistics::hoyer_sparsity(u1); in test_hoyer_sparsity() 86 hs = boost::math::statistics::hoyer_sparsity(u2); in test_hoyer_sparsity() 97 double hs = boost::math::statistics::hoyer_sparsity(v); in test_integer_hoyer_sparsity() 103 hs = boost::math::statistics::hoyer_sparsity(v); in test_integer_hoyer_sparsity() [all …]
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D | bivariate_statistics_test.cpp | 35 using boost::math::statistics::means_and_covariance; 36 using boost::math::statistics::covariance; 97 Real mu_u = boost::math::statistics::mean(u); in test_covariance() 98 Real mu_v = boost::math::statistics::mean(v); in test_covariance() 99 Real sigma_u_sq = boost::math::statistics::variance(u); in test_covariance() 100 Real sigma_v_sq = boost::math::statistics::variance(v); in test_covariance() 119 using boost::math::statistics::correlation_coefficient; in test_correlation_coefficient()
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/third_party/python/Lib/test/ |
D | test_statistics.py | 25 import statistics 673 module = statistics 698 failed, tried = doctest.testmod(statistics, optionflags=doctest.ELLIPSIS) 708 self.assertTrue(hasattr(statistics, 'StatisticsError')) 710 issubclass(statistics.StatisticsError, ValueError), 711 errmsg % statistics.StatisticsError.__base__ 722 self.assertEqual(statistics._exact_ratio(i), (i, 1)) 728 self.assertEqual(statistics._exact_ratio(f), (n, 37)) 731 self.assertEqual(statistics._exact_ratio(0.125), (1, 8)) 732 self.assertEqual(statistics._exact_ratio(1.125), (9, 8)) [all …]
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/third_party/vk-gl-cts/external/vulkancts/modules/vulkan/pipeline/ |
D | vktPipelineExecutablePropertiesTests.cpp | 630 std::vector<VkPipelineExecutableStatisticKHR> statistics[PIPELINE_CACHE_NDX_COUNT]; in verifyStatistics() local 650 statistics[ndx].resize(statisticCount); in verifyStatistics() 653 deMemset(&statistics[ndx][statNdx], 0, sizeof(statistics[ndx][statNdx])); in verifyStatistics() 654 statistics[ndx][statNdx].sType = VK_STRUCTURE_TYPE_PIPELINE_EXECUTABLE_STATISTIC_KHR; in verifyStatistics() 655 statistics[ndx][statNdx].pNext = DE_NULL; in verifyStatistics() 657 …eExecutableStatisticsKHR(vkDevice, &pipelineExecutableInfo, &statisticCount, &statistics[ndx][0])); in verifyStatistics() 661 …if (!checkString(statistics[ndx][statNdx].name, DE_LENGTH_OF_ARRAY(statistics[ndx][statNdx].name))) in verifyStatistics() 668 if (deMemCmp(statistics[ndx][statNdx].name, statistics[ndx][otherNdx].name, in verifyStatistics() 669 DE_LENGTH_OF_ARRAY(statistics[ndx][statNdx].name)) == 0) in verifyStatistics() 675 …if (!checkString(statistics[ndx][statNdx].description, DE_LENGTH_OF_ARRAY(statistics[ndx][statNdx]… in verifyStatistics() [all …]
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/third_party/mindspore/mindspore/ccsrc/minddata/mindrecord/meta/ |
D | shard_statistics.cc | 26 std::shared_ptr<Statistics> Statistics::Build(std::string desc, const json &statistics) { in Build() argument 28 if (!Validate(statistics)) { in Build() 33 object_statistics.statistics_ = statistics; in Build() 51 bool Statistics::Validate(const json &statistics) { in Validate() argument 52 if (statistics.size() != kInt1) { in Validate() 56 if (statistics.find("level") == statistics.end()) { in Validate() 60 return LevelRecursive(statistics["level"]); in Validate()
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/third_party/node/benchmark/ |
D | compare.R | 54 statistics = ddply(dat, "name", function(subdat) { globalVar 103 row.names(statistics) = statistics$name; 104 statistics$name = NULL; 107 print(statistics); 117 nrow(statistics), 118 nrow(statistics) * 0.05, 119 nrow(statistics) * 0.01, 120 nrow(statistics) * 0.001))
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/third_party/boost/libs/math/example/daubechies_wavelets/ |
D | regress_daubechies_accuracy.cpp | 86 …auto q = boost::math::statistics::simple_ordinary_least_squares_with_R_squared(r, matched_holder); in main() 90 q = boost::math::statistics::simple_ordinary_least_squares_with_R_squared(r, linear); in main() 94 … q = boost::math::statistics::simple_ordinary_least_squares_with_R_squared(r, quadratic_b_spline); in main() 98 q = boost::math::statistics::simple_ordinary_least_squares_with_R_squared(r, cubic_b_spline); in main() 102 q = boost::math::statistics::simple_ordinary_least_squares_with_R_squared(r, quintic_b_spline); in main() 106 q = boost::math::statistics::simple_ordinary_least_squares_with_R_squared(r, cubic_hermite); in main() 110 q = boost::math::statistics::simple_ordinary_least_squares_with_R_squared(r, pchip); in main() 114 q = boost::math::statistics::simple_ordinary_least_squares_with_R_squared(r, makima); in main() 118 q = boost::math::statistics::simple_ordinary_least_squares_with_R_squared(r, fotaylor); in main() 124 q = boost::math::statistics::simple_ordinary_least_squares_with_R_squared(r, quintic_hermite); in main() [all …]
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/third_party/mindspore/tests/ut/cpp/mindrecord/ |
D | ut_shard_schema_test.cc | 136 std::shared_ptr<Statistics> statistics = Statistics::Build(desc, statistic_json); in TEST_F() local 138 ASSERT_NE(statistics, nullptr); in TEST_F() 140 MS_LOG(INFO) << "test GetDesc(), result: " << statistics->GetDesc(); in TEST_F() 141 MS_LOG(INFO) << "test GetStatistics, result: " << statistics->GetStatistics().dump(); in TEST_F() 144 statistics = Statistics::Build(desc, statistic_json); in TEST_F() 145 ASSERT_EQ(statistics, nullptr); in TEST_F() 148 statistics = Statistics::Build(desc, statistic_json); in TEST_F() 149 ASSERT_EQ(statistics, nullptr); in TEST_F()
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D | ut_shard.cc | 72 std::shared_ptr<Statistics> statistics = Statistics::Build(desc, statistic_json); in TEST_F() local 73 ASSERT_TRUE(statistics != nullptr); in TEST_F() 74 MS_LOG(INFO) << "test get_desc(), result: " << statistics->GetDesc(); in TEST_F() 75 MS_LOG(INFO) << "test get_statistics, result: " << statistics->GetStatistics().dump(); in TEST_F()
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/third_party/boost/libs/math/doc/statistics/ |
D | univariate_statistics.qbk | 14 #include <boost/math/statistics/univariate_statistics.hpp> 16 namespace boost{ namespace math{ namespace statistics { 98 The file `boost/math/statistics/univariate_statistics.hpp` is a set of facilities for computing sca… 116 double mu = boost::math::statistics::mean(v.cbegin(), v.cend()); 118 mu = boost::math::statistics::mean(v); 128 Real sigma_sq = boost::math::statistics::variance(v.cbegin(), v.cend()); 133 Real sigma_sq = boost::math::statistics::variance(v); 140 `boost::math::statistics::variance` returns the population variance. 144 Real sn_sq = boost::math::statistics::sample_variance(v); 152 double skewness = boost::math::statistics::skewness(v); [all …]
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D | bivariate_statistics.qbk | 14 #include <boost/math/statistics/bivariate_statistics.hpp> 16 namespace boost{ namespace math{ namespace statistics { 32 This file provides functions for computing bivariate statistics. 40 double cov_uv = boost::math::statistics::covariance(u, v); 52 auto [mu_u, mu_v, cov_uv] = boost::math::statistics::means_and_covariance(u, v); 60 double rho_uv = boost::math::statistics::correlation_coefficient(u, v); 72 * Bennett, Janine, et al. ['Numerically stable, single-pass, parallel statistics algorithms.] Clust…
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D | ljung_box.qbk | 13 #include <boost/math/statistics/ljung_box.hpp> 15 namespace boost::math::statistics { 47 #include <boost/math/statistics/ljung_box.hpp> 48 using boost::math::statistics::ljung_box;
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D | signal_statistics.qbk | 14 #include <boost/math/statistics/signal_statistics.hpp> 16 namespace boost::math::statistics { 59 The file `boost/math/statistics/signal_statistics.hpp` is a set of facilities for computing quantit… 73 using boost::math::statistics::sample_absolute_gini_coefficient; 74 using boost::math::statistics::absolute_gini_coefficient; 116 Real hs = boost::math::statistics::hoyer_sparsity(v); 119 Real hs = boost::math::statistics::hoyer_sparsity(v.begin(), v.end()); 139 double snr_db = boost::math::statistics::oracle_snr_db(signal, noisy_signal); 140 double snr = boost::math::statistics::oracle_snr(signal, noisy_signal); 153 double est_snr_db = boost::math::statistics::m2m4_snr_estimator_db(noisy_signal); [all …]
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/third_party/node/lib/internal/ |
D | http.js | 29 constructor(statistics) { argument 33 const startTime = statistics.startTime; 40 function emitStatistics(statistics) { argument 41 notify('http', new HttpRequestTiming(statistics));
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/third_party/boost/boost/math/statistics/ |
D | linear_regression.hpp | 17 namespace boost::math::statistics { namespace 34 auto [mu_x, mu_y, cov_xy] = boost::math::statistics::means_and_covariance(x, y); in simple_ordinary_least_squares() 36 auto var_x = boost::math::statistics::variance(x); in simple_ordinary_least_squares() 63 auto [mu_x, mu_y, cov_xy] = boost::math::statistics::means_and_covariance(x, y); in simple_ordinary_least_squares_with_R_squared() 65 auto var_x = boost::math::statistics::variance(x); in simple_ordinary_least_squares_with_R_squared()
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D | signal_statistics.hpp | 17 namespace boost::math::statistics { namespace 52 return boost::math::statistics::absolute_gini_coefficient(v.begin(), v.end()); in absolute_gini_coefficient() 59 return n*boost::math::statistics::absolute_gini_coefficient(first, last)/(n-1); in sample_absolute_gini_coefficient() 65 return boost::math::statistics::sample_absolute_gini_coefficient(v.begin(), v.end()); in sample_absolute_gini_coefficient() 123 return boost::math::statistics::hoyer_sparsity(v.cbegin(), v.cend()); in hoyer_sparsity() 202 Real mu = boost::math::statistics::mean(signal); in mean_invariant_oracle_snr() 228 return 10*log10(boost::math::statistics::mean_invariant_oracle_snr(signal, noisy_signal)); in mean_invariant_oracle_snr_db() 237 return 10*log10(boost::math::statistics::oracle_snr(signal, noisy_signal)); in oracle_snr_db() 262 auto [M1, M2, M3, M4] = boost::math::statistics::first_four_moments(first, last); in m2m4_snr_estimator()
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D | anderson_darling.hpp | 16 namespace boost { namespace math { namespace statistics { namespace 29 mu = boost::math::statistics::mean(v); in anderson_darling_normality_statistic() 32 sd = sqrt(boost::math::statistics::sample_variance(v)); in anderson_darling_normality_statistic()
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/third_party/mesa3d/src/vulkan/overlay-layer/ |
D | README | 8 List the available statistics : 12 Turn on some statistics : 19 Dump statistics into a file: 23 Dump statistics into a file, controlling when such statistics will start 36 The client connected to the overlay layer can enable statistics
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/third_party/skia/third_party/externals/abseil-cpp/absl/strings/internal/ |
D | cordz_info_test.cc | 294 CordzStatistics statistics = info->GetCordzStatistics(); in TEST() local 295 EXPECT_THAT(statistics.size, Eq(data.rep.rep->length)); in TEST() 296 EXPECT_THAT(statistics.method, Eq(kTrackCordMethod)); in TEST() 297 EXPECT_THAT(statistics.parent_method, Eq(kUnknownMethod)); in TEST() 298 EXPECT_THAT(statistics.update_tracker.Value(kTrackCordMethod), Eq(1)); in TEST() 312 CordzStatistics statistics = info->GetCordzStatistics(); in TEST() local 313 EXPECT_THAT(statistics.update_tracker.Value(kUpdateMethod), Eq(2)); in TEST() 328 CordzStatistics statistics = info_child->GetCordzStatistics(); in TEST() local 329 EXPECT_THAT(statistics.size, Eq(child.rep.rep->length)); in TEST() 330 EXPECT_THAT(statistics.method, Eq(kChildMethod)); in TEST() [all …]
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/third_party/boost/boost/geometry/index/detail/rtree/utilities/ |
D | statistics.hpp | 27 struct statistics struct 33 inline statistics() in statistics() argument 91 statistics(Rtree const& tree) in statistics() function 96 visitors::statistics< in statistics()
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/third_party/python/Lib/ |
D | tracemalloc.py | 121 statistics = [] 132 statistics.append(stat) 136 statistics.append(stat) 137 return statistics 528 def statistics(self, key_type, cumulative=False): member in Snapshot 534 statistics = list(grouped.values()) 535 statistics.sort(reverse=True, key=Statistic._sort_key) 536 return statistics 546 statistics = _compare_grouped_stats(old_group, new_group) 547 statistics.sort(reverse=True, key=StatisticDiff._sort_key) [all …]
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/third_party/mesa3d/src/amd/compiler/ |
D | aco_statistics.cpp | 43 program->statistics[statistic_sgpr_presched] = presched_demand.sgpr; in collect_presched_stats() 44 program->statistics[statistic_vgpr_presched] = presched_demand.vgpr; in collect_presched_stats() 441 program->statistics[statistic_instructions] += block.instructions.size(); in collect_preasm_stats() 445 program->statistics[statistic_branches]++; in collect_preasm_stats() 448 program->statistics[statistic_instructions] += 2; in collect_preasm_stats() 454 program->statistics[statistic_vmem_clauses]++; in collect_preasm_stats() 464 program->statistics[statistic_smem_clauses]++; in collect_preasm_stats() 547 program->statistics[statistic_latency] = round(latency); in collect_preasm_stats() 548 program->statistics[statistic_inv_throughput] = round(1.0 / wave64_per_cycle); in collect_preasm_stats() 573 program->statistics[aco::statistic_hash] = util_hash_crc32(code.data(), code.size() * 4); in collect_postasm_stats()
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/third_party/mindspore/mindspore/ccsrc/minddata/mindrecord/include/ |
D | shard_statistics.h | 40 static std::shared_ptr<Statistics> Build(std::string desc, const json &statistics); 69 static bool Validate(const json &statistics);
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/third_party/flutter/flutter/packages/flutter_tools/lib/src/reporting/ |
D | README.md | 3 1. Anonymous usage statistics are reported to Google Analytics (for statistics
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