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/third_party/boost/libs/math/test/
Dunivariate_statistics_test.cpp107 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()
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Dsignal_statistics_test.cpp42 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()
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Dbivariate_statistics_test.cpp35 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()
/third_party/python/Lib/test/
Dtest_statistics.py25 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))
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/third_party/vk-gl-cts/external/vulkancts/modules/vulkan/pipeline/
DvktPipelineExecutablePropertiesTests.cpp630 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()
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/third_party/mindspore/mindspore/ccsrc/minddata/mindrecord/meta/
Dshard_statistics.cc26 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()
/third_party/node/benchmark/
Dcompare.R54 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))
/third_party/boost/libs/math/example/daubechies_wavelets/
Dregress_daubechies_accuracy.cpp86 …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()
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/third_party/mindspore/tests/ut/cpp/mindrecord/
Dut_shard_schema_test.cc136 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()
Dut_shard.cc72 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()
/third_party/boost/libs/math/doc/statistics/
Dunivariate_statistics.qbk14 #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);
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Dbivariate_statistics.qbk14 #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…
Dljung_box.qbk13 #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;
Dsignal_statistics.qbk14 #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);
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/third_party/node/lib/internal/
Dhttp.js29 constructor(statistics) { argument
33 const startTime = statistics.startTime;
40 function emitStatistics(statistics) { argument
41 notify('http', new HttpRequestTiming(statistics));
/third_party/boost/boost/math/statistics/
Dlinear_regression.hpp17 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()
Dsignal_statistics.hpp17 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()
Danderson_darling.hpp16 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()
/third_party/mesa3d/src/vulkan/overlay-layer/
DREADME8 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
/third_party/skia/third_party/externals/abseil-cpp/absl/strings/internal/
Dcordz_info_test.cc294 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()
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/third_party/boost/boost/geometry/index/detail/rtree/utilities/
Dstatistics.hpp27 struct statistics struct
33 inline statistics() in statistics() argument
91 statistics(Rtree const& tree) in statistics() function
96 visitors::statistics< in statistics()
/third_party/python/Lib/
Dtracemalloc.py121 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)
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/third_party/mesa3d/src/amd/compiler/
Daco_statistics.cpp43 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()
/third_party/mindspore/mindspore/ccsrc/minddata/mindrecord/include/
Dshard_statistics.h40 static std::shared_ptr<Statistics> Build(std::string desc, const json &statistics);
69 static bool Validate(const json &statistics);
/third_party/flutter/flutter/packages/flutter_tools/lib/src/reporting/
DREADME.md3 1. Anonymous usage statistics are reported to Google Analytics (for statistics

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