| /third_party/python/Tools/scripts/ |
| D | var_access_benchmark.py | 10 trials = [None] * 500 variable
26 def read_local(trials=trials): argument
28 for t in trials:
37 def inner(trials=trials): argument
38 for t in trials:
50 def read_global(trials=trials): argument
51 for t in trials:
58 def read_builtin(trials=trials): argument
59 for t in trials:
66 def read_classvar_from_class(trials=trials, A=A): argument
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| /third_party/boost/boost/math/distributions/ |
| D | binomial.hpp | 207 RealType trials = dist.trials(); in quantile_imp() local
211 trials, in quantile_imp()
230 return trials; in quantile_imp()
232 if (p <= pow(1 - success_fraction, trials)) in quantile_imp()
238 return p > 0.5f ? trials : 0; in quantile_imp()
243 …RealType guess = binomial_detail::inverse_binomial_cornish_fisher(trials, success_fraction, p, q, … in quantile_imp()
245 if(trials > 100) in quantile_imp()
247 else if((trials > 10) && (trials - 1 > guess) && (guess > 3)) in quantile_imp()
249 else if(trials < 10) in quantile_imp()
252 if(guess > trials / 64) in quantile_imp()
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| /third_party/boost/libs/local_function/example/ |
| D | profile_helpers.hpp | 16 void args(int argc, char* argv[], unsigned long& size, unsigned long& trials) { in args() argument
18 trials = 10; // Default. in args()
24 double(trials) << std::endl; in args()
28 if (argc >= 3) trials = atol(argv[2]); in args()
31 std::clog << "number of trials = " << double(trials) << std::endl; in args()
32 std::clog << "number of calls = " << double(size) * double(trials) << in args()
36 void display(const unsigned long& size, const unsigned long& trials, in display() argument
43 double avg_sec = decl_sec + trials_sec / trials; in display()
48 assert(sum == double(size) * double(trials)); in display()
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| D | profile_cxx11_lambda.cpp | 20 unsigned long size = 0, trials = 0; in main() local
21 profile::args(argc, argv, size, trials); in main()
30 for(unsigned long i = 0; i < trials; ++i) { in main()
39 profile::display(size, trials, sum, trials_sec.count()); in main()
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| D | profile_phoenix.cpp | 19 unsigned long size = 0, trials = 0; in main() local
20 profile::args(argc, argv, size, trials); in main()
29 for(unsigned long i = 0; i < trials; ++i) { in main()
42 profile::display(size, trials, sum, trials_sec.count()); in main()
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| D | profile_local_function_inline.cpp | 16 unsigned long size = 0, trials = 0; in main() local
17 profile::args(argc, argv, size, trials); in main()
35 for(unsigned long i = 0; i < trials; ++i) { in main()
42 profile::display(size, trials, sum, trials_sec.count(), decl_sec.count()); in main()
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| D | profile_local_function.cpp | 16 unsigned long size = 0, trials = 0; in main() local
17 profile::args(argc, argv, size, trials); in main()
35 for(unsigned long i = 0; i < trials; ++i) { in main()
42 profile::display(size, trials, sum, trials_sec.count(), decl_sec.count()); in main()
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| D | profile_global_functor.cpp | 25 unsigned long size = 0, trials =0; in main() local
26 profile::args(argc, argv, size, trials); in main()
41 for(unsigned long i = 0; i < trials; ++i) { in main()
48 profile::display(size, trials, sum, trials_sec.count(), decl_sec.count()); in main()
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| D | profile_local_functor.cpp | 15 unsigned long size = 0, trials = 0; in main() local
16 profile::args(argc, argv, size, trials); in main()
40 for(unsigned long i = 0; i < trials; ++i) { in main()
47 profile::display(size, trials, sum, trials_sec.count(), decl_sec.count()); in main()
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| /third_party/boost/libs/math/example/ |
| D | binomial_confidence_limits.cpp | 23 void confidence_limits_on_frequency(unsigned trials, unsigned successes) in confidence_limits_on_frequency() argument
42 cout << setw(40) << left << "Number of Observations" << "= " << trials << "\n"; in confidence_limits_on_frequency()
44 …etw(40) << left << "Sample frequency of occurrence" << "= " << double(successes) / trials << "\n"; in confidence_limits_on_frequency()
65 double l = binomial_distribution<>::find_lower_bound_on_p(trials, successes, alpha[i]/2); in confidence_limits_on_frequency()
66 double u = binomial_distribution<>::find_upper_bound_on_p(trials, successes, alpha[i]/2); in confidence_limits_on_frequency()
71 …l = binomial_distribution<>::find_lower_bound_on_p(trials, successes, alpha[i]/2, binomial_distrib… in confidence_limits_on_frequency()
72 …u = binomial_distribution<>::find_upper_bound_on_p(trials, successes, alpha[i]/2, binomial_distrib… in confidence_limits_on_frequency()
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| D | neg_binom_confidence_limits.cpp | 49 void confidence_limits_on_frequency(unsigned trials, unsigned successes) in confidence_limits_on_frequency() argument
61 cout << setw(40) << left << "Number of trials" << " = " << trials << "\n"; in confidence_limits_on_frequency()
63 cout << setw(40) << left << "Number of failures" << " = " << trials - successes << "\n"; in confidence_limits_on_frequency()
64 …(40) << left << "Observed frequency of occurrence" << " = " << double(successes) / trials << "\n"; in confidence_limits_on_frequency()
91 double lower = negative_binomial::find_lower_bound_on_p(trials, successes, alpha[i]/2); in confidence_limits_on_frequency()
92 double upper = negative_binomial::find_upper_bound_on_p(trials, successes, alpha[i]/2); in confidence_limits_on_frequency()
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| D | binomial_example_nag.cpp | 58 cout << setw(4) << (int)my_dist.trials() << " " << my_dist.success_fraction() in main()
63 cout << setw(4) << (int)two.trials() << " " << two.success_fraction() in main()
68 cout << setw(4) << (int)three.trials() << " " << three.success_fraction() in main()
72 cout << setw(4) << (int)four.trials() << " " << four.success_fraction() in main()
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| /third_party/boost/libs/compute/perf/ |
| D | perf_random_number_engine.cpp | 27 const size_t trials, in perf_random_number_engine() argument
41 for(size_t i = 0; i < trials; i++){ in perf_random_number_engine()
79 const size_t trials = vm["trials"].as<size_t>(); in main() local
84 perf_random_number_engine<compute::default_random_engine>(size, trials, queue); in main()
87 perf_random_number_engine<compute::mt19937>(size, trials, queue); in main()
90 perf_random_number_engine<compute::linear_congruential_engine<> >(size, trials, queue); in main()
93 perf_random_number_engine<compute::threefry_engine<> >(size, trials, queue); in main()
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| D | perf_accumulate.cpp | 34 const size_t trials, in perf_accumulate() argument
38 for(size_t trial = 0; trial < trials; trial++){ in perf_accumulate()
49 const size_t trials, in tune_accumulate() argument
71 const double t = perf_accumulate(data, trials, queue); in tune_accumulate()
112 const size_t trials = vm["trials"].as<size_t>(); in main() local
132 tune_accumulate(device_data, trials, queue); in main()
136 double t = perf_accumulate(device_data, trials, queue); in main()
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| D | perf_sort.cpp | 29 const size_t trials, in perf_sort() argument
35 for(size_t trial = 0; trial < trials; trial++){ in perf_sort()
51 const size_t trials, in tune_sort() argument
69 const double t = perf_sort(data, trials, queue); in tune_sort()
107 const size_t trials = vm["trials"].as<size_t>(); in main() local
122 tune_sort(data, trials, queue); in main()
126 double t = perf_sort(data, trials, queue); in main()
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| D | perf_saxpy.cpp | 37 const size_t trials, in perf_saxpy() argument
44 for(size_t trial = 0; trial < trials; trial++){ in perf_saxpy()
68 const size_t trials, in tune_saxpy() argument
90 const double t = perf_saxpy(x, y, alpha, trials, queue); in tune_saxpy()
132 const size_t trials = vm["trials"].as<size_t>(); in main() local
154 tune_saxpy(x, y, alpha, trials, queue); in main()
158 double t = perf_saxpy(x, y, alpha, trials, queue); in main()
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| /third_party/boost/boost/multiprecision/ |
| D | miller_rabin.hpp | 136 miller_rabin_test(const I& n, unsigned trials, Engine& gen) in miller_rabin_test() argument
172 for (unsigned i = 0; i < trials; ++i) in miller_rabin_test()
200 miller_rabin_test(const I& x, unsigned trials) in miller_rabin_test() argument
203 return miller_rabin_test(x, trials, gen); in miller_rabin_test()
207 bool miller_rabin_test(const detail::expression<tag, Arg1, Arg2, Arg3, Arg4>& n, unsigned trials, E… in miller_rabin_test() argument
210 return miller_rabin_test(number_type(n), trials, gen); in miller_rabin_test()
214 bool miller_rabin_test(const detail::expression<tag, Arg1, Arg2, Arg3, Arg4>& n, unsigned trials) in miller_rabin_test() argument
217 return miller_rabin_test(number_type(n), trials); in miller_rabin_test()
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| /third_party/boost/libs/math/doc/distributions/ |
| D | negative_binomial_example.qbk | 15 by /k/ \/ /N/, for /k/ successes out of /N/ trials.
17 However our confidence in that estimate will be shaped by how many trials were conducted,
30 success ratio, first for a mere 20 trials:
35 Number of trials = 20
57 2000 trials:
62 Number of trials = 2000
89 that you know will occur in 1 in N trials. You may want to know how many trials you need to
94 can be used to estimate the minimum number of trials required to be P% sure
104 [note Since we're calculating the /minimum/ number of trials required,
107 /maximum/ number of trials permitted to observe less than a certain
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| D | binomial.qbk | 28 RealType trials() const;
32 RealType trials,
37 RealType trials,
42 // estimate min/max number of trials:
62 the probability of observing k successes in N trials, with the
64 binomial distribution assumes that p is fixed for all trials.
67 (the number of trials is a fixed property of the distribution)
69 the random variable is the number of trials, for a fixed number of successes.]
94 Constructor: /n/ is the total number of trials, /p/ is the
105 RealType trials() const;
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| D | geometric.qbk | 28 RealType trials,
32 RealType trials,
36 // Estimate min/max number of trials:
55 For [@http://en.wikipedia.org/wiki/Bernoulli_trial Bernoulli trials]
57 the probability of observing /k/ trials (failures, events, occurrences, or arrivals)
60 [note For this implementation, the set of trials *includes zero*
61 (unlike another definition where the set of trials starts at one, sometimes named /shifted/).]
62 The geometric distribution assumes that success_fraction /p/ is fixed for all /k/ trials.
106 you must ensure that an integer value is provided for the number of trials
125 RealType success_fraction() const; // successes / trials (0 <= p <= 1)
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| D | negative_binomial.qbk | 28 RealType trials,
32 RealType trials,
36 // Estimate min/max number of trials:
55 For k + r Bernoulli trials each with success fraction p, the
59 assumes that success_fraction p is fixed for all (k + r) trials.
61 [note The random variable for the negative binomial distribution is the number of trials,
64 the random variable is the number of successes, for a fixed number of trials.]
124 RealType success_fraction() const; // successes / trials (0 <= p <= 1)
151 For example, if you observe /k/ failures and /r/ successes from /n/ = k + r trials
174 RealType trials,
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| D | binomial_example.qbk | 35 by /k/ \/ /N/, for /k/ successes out of /N/ trials. However our confidence in that
36 estimate will be shaped by how many trials were conducted, and how many successes
51 void confidence_limits_on_frequency(unsigned trials, unsigned successes)
54 // trials = Total number of trials.
70 cout << setw(40) << left << "Number of Observations" << "= " << trials << "\n";
72 …etw(40) << left << "Sample frequency of occurrence" << "= " << double(successes) / trials << "\n";
126 trials, successes, alpha[i]/2);
128 trials, successes, alpha[i]/2);
134 trials, successes, alpha[i]/2,
137 trials, successes, alpha[i]/2,
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| /third_party/boost/libs/random/test/ |
| D | test_bernoulli.cpp | 48 bool do_tests(int repeat, long long trials) { in do_tests() argument
53 if(!do_test(rdist(gen), trials)) { in do_tests()
82 long long trials = 1000000ll; in main() local
91 && !handle_option(argc, argv, 't', trials)) { in main()
99 if(do_tests(repeat, trials)) { in main()
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| D | test_discrete.cpp | 61 bool do_tests(int repeat, int max_n, long long trials) { in do_tests() argument
66 if(!do_test(idist(gen), trials)) { in do_tests()
96 long long trials = 1000000ll; in main() local
106 && !handle_option(argc, argv, 't', trials)) { in main()
114 if(do_tests(repeat, max_n, trials)) { in main()
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| D | test_piecewise_constant.cpp | 96 bool do_tests(int repeat, int max_n, int trials) { in do_tests() argument
101 if(!do_test(idist(gen), trials)) { in do_tests()
131 int trials = 1000000; in main() local
141 && !handle_option(argc, argv, 't', trials)) { in main()
149 if(do_tests(repeat, max_n, trials)) { in main()
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