diff options
Diffstat (limited to 'absl/random/exponential_distribution_test.cc')
| -rw-r--r-- | absl/random/exponential_distribution_test.cc | 44 |
1 files changed, 21 insertions, 23 deletions
diff --git a/absl/random/exponential_distribution_test.cc b/absl/random/exponential_distribution_test.cc index 3c44d9ec..fb9a0d16 100644 --- a/absl/random/exponential_distribution_test.cc +++ b/absl/random/exponential_distribution_test.cc @@ -29,8 +29,8 @@ #include "gmock/gmock.h" #include "gtest/gtest.h" -#include "absl/base/internal/raw_logging.h" #include "absl/base/macros.h" +#include "absl/log/log.h" #include "absl/numeric/internal/representation.h" #include "absl/random/internal/chi_square.h" #include "absl/random/internal/distribution_test_util.h" @@ -115,9 +115,8 @@ TYPED_TEST(ExponentialDistributionTypedTest, SerializeTest) { if (sample < sample_min) sample_min = sample; } if (!std::is_same<TypeParam, long double>::value) { - ABSL_INTERNAL_LOG(INFO, - absl::StrFormat("Range {%f}: %f, %f, lambda=%f", lambda, - sample_min, sample_max, lambda)); + LOG(INFO) << "Range {" << lambda << "}: " << sample_min << ", " + << sample_max << ", lambda=" << lambda; } std::stringstream ss; @@ -219,17 +218,16 @@ bool ExponentialDistributionTests::SingleZTest(const double p, const bool pass = absl::random_internal::Near("z", z, 0.0, max_err); if (!pass) { - ABSL_INTERNAL_LOG( - INFO, absl::StrFormat("p=%f max_err=%f\n" - " lambda=%f\n" - " mean=%f vs. %f\n" - " stddev=%f vs. %f\n" - " skewness=%f vs. %f\n" - " kurtosis=%f vs. %f\n" - " z=%f vs. 0", - p, max_err, lambda(), m.mean, mean(), - std::sqrt(m.variance), stddev(), m.skewness, - skew(), m.kurtosis, kurtosis(), z)); + // clang-format off + LOG(INFO) + << "p=" << p << " max_err=" << max_err << "\n" + " lambda=" << lambda() << "\n" + " mean=" << m.mean << " vs. " << mean() << "\n" + " stddev=" << std::sqrt(m.variance) << " vs. " << stddev() << "\n" + " skewness=" << m.skewness << " vs. " << skew() << "\n" + " kurtosis=" << m.kurtosis << " vs. " << kurtosis() << "\n" + " z=" << z << " vs. 0"; + // clang-format on } return pass; } @@ -274,16 +272,16 @@ double ExponentialDistributionTests::SingleChiSquaredTest() { double p = absl::random_internal::ChiSquarePValue(chi_square, dof); if (chi_square > threshold) { - for (int i = 0; i < cutoffs.size(); i++) { - ABSL_INTERNAL_LOG( - INFO, absl::StrFormat("%d : (%f) = %d", i, cutoffs[i], counts[i])); + for (size_t i = 0; i < cutoffs.size(); i++) { + LOG(INFO) << i << " : (" << cutoffs[i] << ") = " << counts[i]; } - ABSL_INTERNAL_LOG(INFO, - absl::StrCat("lambda ", lambda(), "\n", // - " expected ", expected, "\n", // - kChiSquared, " ", chi_square, " (", p, ")\n", - kChiSquared, " @ 0.98 = ", threshold)); + // clang-format off + LOG(INFO) << "lambda " << lambda() << "\n" + " expected " << expected << "\n" + << kChiSquared << " " << chi_square << " (" << p << ")\n" + << kChiSquared << " @ 0.98 = " << threshold; + // clang-format on } return p; } |