| /third_party/abseil-cpp/absl/container/internal/ |
| D | hash_generator_testing.h | 82 auto variate = dist(*GetSharedRng());
83 if (variate != kEnumEmpty && variate != kEnumDeleted)
84 return static_cast<Enum>(variate);
96 EnumClass variate = static_cast<EnumClass>(dist(*GetSharedRng()));
97 if (variate != EnumClass::kEmpty && variate != EnumClass::kDeleted)
98 return static_cast<EnumClass>(variate);
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| /third_party/skia/third_party/externals/abseil-cpp/absl/container/internal/ |
| D | hash_generator_testing.h | 84 auto variate = dist(*GetSharedRng());
85 if (variate != kEnumEmpty && variate != kEnumDeleted)
86 return static_cast<Enum>(variate);
98 EnumClass variate = static_cast<EnumClass>(dist(*GetSharedRng()));
99 if (variate != EnumClass::kEmpty && variate != EnumClass::kDeleted)
100 return static_cast<EnumClass>(variate);
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| /third_party/skia/third_party/externals/abseil-cpp/absl/random/ |
| D | seed_sequences_test.cc | 106 for (auto& variate : variates) { in TestReproducibleVariateSequencesForNonsecureURBG() local
107 variate = child(); in TestReproducibleVariateSequencesForNonsecureURBG()
113 for (auto& variate : variates) { in TestReproducibleVariateSequencesForNonsecureURBG() local
114 ASSERT_EQ(variate, child()); in TestReproducibleVariateSequencesForNonsecureURBG()
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| D | beta_distribution_test.cc | 292 const double variate = dis(rng_); in SingleZTestOnMeanAndVariance() local
293 EXPECT_FALSE(std::isnan(variate)); in SingleZTestOnMeanAndVariance()
295 EXPECT_GE(variate, 0.0); in SingleZTestOnMeanAndVariance()
296 EXPECT_LE(variate, 1.0); in SingleZTestOnMeanAndVariance()
297 data.push_back(variate); in SingleZTestOnMeanAndVariance()
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| /third_party/abseil-cpp/absl/random/ |
| D | seed_sequences_test.cc | 106 for (auto& variate : variates) { in TestReproducibleVariateSequencesForNonsecureURBG() local
107 variate = child(); in TestReproducibleVariateSequencesForNonsecureURBG()
113 for (auto& variate : variates) { in TestReproducibleVariateSequencesForNonsecureURBG() local
114 ASSERT_EQ(variate, child()); in TestReproducibleVariateSequencesForNonsecureURBG()
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| D | beta_distribution_test.cc | 309 const double variate = dis(rng_); in SingleZTestOnMeanAndVariance() local
310 EXPECT_FALSE(std::isnan(variate)); in SingleZTestOnMeanAndVariance()
312 EXPECT_GE(variate, 0.0); in SingleZTestOnMeanAndVariance()
313 EXPECT_LE(variate, 1.0); in SingleZTestOnMeanAndVariance()
314 data.push_back(variate); in SingleZTestOnMeanAndVariance()
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| /third_party/boost/boost/graph/ |
| D | random.hpp | 85 boost::variate_generator< RandomNumGen&, ui_type > variate(gen, ui); in random_out_edge() local
88 std::advance(it, variate()); in random_out_edge()
102 boost::variate_generator< RandomNumGen&, ur_type > variate(gen, ur); in weighted_random_out_edge() local
103 weight_type chosen_weight = variate(); in weighted_random_out_edge()
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| /third_party/boost/libs/math/doc/distributions/ |
| D | lognormal.qbk | 60 random variate.
63 logarithm of the random variate.
93 /s/ is its scale parameter, /x/ is the random variate, /p/ is the probability
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| D | laplace.qbk | 57 The location parameter is the same as the mean of the random variate.
59 The scale parameter is proportional to the standard deviation of the random variate.
87 [sigma] is its scale parameter, /x/ is the random variate, /p/ is the probability
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| D | inverse_gamma.qbk | 86 The domain of the random variate is \[0,+[infin]\].
87 [note Unlike some definitions, this implementation supports a random variate
102 [alpha] is its scale parameter, /x/ is the random variate, /p/ is the probability
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| D | arcsine.qbk | 69 If random variate ['x] is ['x_min] or ['x_max], then the PDF is infinity.
70 If random variate ['x] is ['x_min] then the CDF is zero.
71 If random variate ['x] is ['x_max] then the CDF is unity.
137 The random variate ['x] is constrained to ['x_min] and ['x_max], (for our 'standard' distribution, …
145 The random variate ['x] is the fraction of time spent on the 'winning' side.
215 … a standard [0, 1] arcsine distribution ['as], the pdf is symmetric about random variate ['x = 0.5]
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| D | inverse_gaussian.qbk | 67 and random variate x,
114 The domain of the random variate is \[0,+[infin]).
115 [note Unlike some definitions, this implementation supports a random variate
130 /x/ is the random variate, /p/ is the probability and /q = 1-p/ its complement.
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| D | dist_tutorial.qbk | 166 a random variate is a particular value (outcome) of a random variable.
171 to separate the variate from the parameter(s) that defines the shape of the distribution.
185 and a second for the random variate. So taking our binomial distribution
199 of random variate x that has the cdf going from zero to unity.
204 to *exclude* random variate values like exact zero *if the end point is discontinuous*.
206 as the random variate x declines towards zero.
232 of the random variate.
239 or `ceil` functions on the random variate prior to calling the distribution
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| D | inverse_chi_squared.qbk | 124 The domain of the random variate is \[0,+[infin]\].
125 [note Unlike some definitions, this implementation supports a random variate
142 /x/ is the random variate, /p/ is the probability and /q = 1-p/ its complement.
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| D | uniform.qbk | 49 The [@http://en.wikipedia.org/wiki/Random_variate random variate]
101 /x/ is the random variate, /p/ is the probability and /q = 1-p/.
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| D | triangular.qbk | 55 The [@http://en.wikipedia.org/wiki/Random_variate random variate] x must also be finite, and is sup…
132 /x/ is the random variate, /p/ is the probability and /q = 1-p/.
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| D | exponential.qbk | 69 /x/ is the random variate, /p/ is the probability and /q = 1-p/.
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| D | bernoulli.qbk | 82 /k/ is the random variate, either 0 or 1.
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| D | non_members.qbk | 174 the probability that the variate has the value x.
180 variate takes the value x.
272 of random variate x that has the cdf going from zero to unity.
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| D | extreme_value.qbk | 94 /x/ is the random variate, /p/ is the probability and /q = 1-p/.
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| D | rayleigh.qbk | 90 /x/ is the random variate, /p/ is the probability and /q = 1-p/.
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| D | pareto.qbk | 87 [beta] is its scale parameter, /x/ is the random variate, /p/ is the probability
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| D | background.qbk | 7 to separate the variate from the parameter(s) that defines the shape of the distribution.
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| D | gamma.qbk | 112 [theta] is its scale parameter, /x/ is the random variate, /p/ is the probability
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| /third_party/python/Lib/test/ |
| D | test_random.py | 1023 for variate, args, mu, sigmasqrd in [
1036 y.append(variate(*args))
1045 msg='%s%r' % (variate.__name__, args))
1047 msg='%s%r' % (variate.__name__, args))
1052 for variate, args, expected in [
1067 self.assertEqual(variate(*args), expected)
|