From 5aa5d282eac56a21e74611c1cdbaa97bb5db2dca Mon Sep 17 00:00:00 2001 From: Vincent Ambo Date: Tue, 8 Feb 2022 02:05:36 +0300 Subject: chore(3p/abseil_cpp): unvendor abseil_cpp we weren't actually using these sources anymore, okay? Change-Id: If701571d9716de308d3512e1eb22c35db0877a66 Reviewed-on: https://cl.tvl.fyi/c/depot/+/5248 Tested-by: BuildkiteCI Reviewed-by: grfn Autosubmit: tazjin --- .../absl/random/internal/distribution_test_util.cc | 418 --------------------- 1 file changed, 418 deletions(-) delete mode 100644 third_party/abseil_cpp/absl/random/internal/distribution_test_util.cc (limited to 'third_party/abseil_cpp/absl/random/internal/distribution_test_util.cc') diff --git a/third_party/abseil_cpp/absl/random/internal/distribution_test_util.cc b/third_party/abseil_cpp/absl/random/internal/distribution_test_util.cc deleted file mode 100644 index e9005658c0a7..000000000000 --- a/third_party/abseil_cpp/absl/random/internal/distribution_test_util.cc +++ /dev/null @@ -1,418 +0,0 @@ -// Copyright 2017 The Abseil Authors. -// -// Licensed under the Apache License, Version 2.0 (the "License"); -// you may not use this file except in compliance with the License. -// You may obtain a copy of the License at -// -// https://www.apache.org/licenses/LICENSE-2.0 -// -// Unless required by applicable law or agreed to in writing, software -// distributed under the License is distributed on an "AS IS" BASIS, -// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -// See the License for the specific language governing permissions and -// limitations under the License. - -#include "absl/random/internal/distribution_test_util.h" - -#include -#include -#include -#include - -#include "absl/base/internal/raw_logging.h" -#include "absl/base/macros.h" -#include "absl/strings/str_cat.h" -#include "absl/strings/str_format.h" - -namespace absl { -ABSL_NAMESPACE_BEGIN -namespace random_internal { -namespace { - -#if defined(__EMSCRIPTEN__) -// Workaround __EMSCRIPTEN__ error: llvm_fma_f64 not found. -inline double fma(double x, double y, double z) { return (x * y) + z; } -#endif - -} // namespace - -DistributionMoments ComputeDistributionMoments( - absl::Span data_points) { - DistributionMoments result; - - // Compute m1 - for (double x : data_points) { - result.n++; - result.mean += x; - } - result.mean /= static_cast(result.n); - - // Compute m2, m3, m4 - for (double x : data_points) { - double v = x - result.mean; - result.variance += v * v; - result.skewness += v * v * v; - result.kurtosis += v * v * v * v; - } - result.variance /= static_cast(result.n - 1); - - result.skewness /= static_cast(result.n); - result.skewness /= std::pow(result.variance, 1.5); - - result.kurtosis /= static_cast(result.n); - result.kurtosis /= std::pow(result.variance, 2.0); - return result; - - // When validating the min/max count, the following confidence intervals may - // be of use: - // 3.291 * stddev = 99.9% CI - // 2.576 * stddev = 99% CI - // 1.96 * stddev = 95% CI - // 1.65 * stddev = 90% CI -} - -std::ostream& operator<<(std::ostream& os, const DistributionMoments& moments) { - return os << absl::StrFormat("mean=%f, stddev=%f, skewness=%f, kurtosis=%f", - moments.mean, std::sqrt(moments.variance), - moments.skewness, moments.kurtosis); -} - -double InverseNormalSurvival(double x) { - // inv_sf(u) = -sqrt(2) * erfinv(2u-1) - static constexpr double kSqrt2 = 1.4142135623730950488; - return -kSqrt2 * absl::random_internal::erfinv(2 * x - 1.0); -} - -bool Near(absl::string_view msg, double actual, double expected, double bound) { - assert(bound > 0.0); - double delta = fabs(expected - actual); - if (delta < bound) { - return true; - } - - std::string formatted = absl::StrCat( - msg, " actual=", actual, " expected=", expected, " err=", delta / bound); - ABSL_RAW_LOG(INFO, "%s", formatted.c_str()); - return false; -} - -// TODO(absl-team): Replace with an "ABSL_HAVE_SPECIAL_MATH" and try -// to use std::beta(). As of this writing P0226R1 is not implemented -// in libc++: http://libcxx.llvm.org/cxx1z_status.html -double beta(double p, double q) { - // Beta(x, y) = Gamma(x) * Gamma(y) / Gamma(x+y) - double lbeta = std::lgamma(p) + std::lgamma(q) - std::lgamma(p + q); - return std::exp(lbeta); -} - -// Approximation to inverse of the Error Function in double precision. -// (http://people.maths.ox.ac.uk/gilesm/files/gems_erfinv.pdf) -double erfinv(double x) { -#if !defined(__EMSCRIPTEN__) - using std::fma; -#endif - - double w = 0.0; - double p = 0.0; - w = -std::log((1.0 - x) * (1.0 + x)); - if (w < 6.250000) { - w = w - 3.125000; - p = -3.6444120640178196996e-21; - p = fma(p, w, -1.685059138182016589e-19); - p = fma(p, w, 1.2858480715256400167e-18); - p = fma(p, w, 1.115787767802518096e-17); - p = fma(p, w, -1.333171662854620906e-16); - p = fma(p, w, 2.0972767875968561637e-17); - p = fma(p, w, 6.6376381343583238325e-15); - p = fma(p, w, -4.0545662729752068639e-14); - p = fma(p, w, -8.1519341976054721522e-14); - p = fma(p, w, 2.6335093153082322977e-12); - p = fma(p, w, -1.2975133253453532498e-11); - p = fma(p, w, -5.4154120542946279317e-11); - p = fma(p, w, 1.051212273321532285e-09); - p = fma(p, w, -4.1126339803469836976e-09); - p = fma(p, w, -2.9070369957882005086e-08); - p = fma(p, w, 4.2347877827932403518e-07); - p = fma(p, w, -1.3654692000834678645e-06); - p = fma(p, w, -1.3882523362786468719e-05); - p = fma(p, w, 0.0001867342080340571352); - p = fma(p, w, -0.00074070253416626697512); - p = fma(p, w, -0.0060336708714301490533); - p = fma(p, w, 0.24015818242558961693); - p = fma(p, w, 1.6536545626831027356); - } else if (w < 16.000000) { - w = std::sqrt(w) - 3.250000; - p = 2.2137376921775787049e-09; - p = fma(p, w, 9.0756561938885390979e-08); - p = fma(p, w, -2.7517406297064545428e-07); - p = fma(p, w, 1.8239629214389227755e-08); - p = fma(p, w, 1.5027403968909827627e-06); - p = fma(p, w, -4.013867526981545969e-06); - p = fma(p, w, 2.9234449089955446044e-06); - p = fma(p, w, 1.2475304481671778723e-05); - p = fma(p, w, -4.7318229009055733981e-05); - p = fma(p, w, 6.8284851459573175448e-05); - p = fma(p, w, 2.4031110387097893999e-05); - p = fma(p, w, -0.0003550375203628474796); - p = fma(p, w, 0.00095328937973738049703); - p = fma(p, w, -0.0016882755560235047313); - p = fma(p, w, 0.0024914420961078508066); - p = fma(p, w, -0.0037512085075692412107); - p = fma(p, w, 0.005370914553590063617); - p = fma(p, w, 1.0052589676941592334); - p = fma(p, w, 3.0838856104922207635); - } else { - w = std::sqrt(w) - 5.000000; - p = -2.7109920616438573243e-11; - p = fma(p, w, -2.5556418169965252055e-10); - p = fma(p, w, 1.5076572693500548083e-09); - p = fma(p, w, -3.7894654401267369937e-09); - p = fma(p, w, 7.6157012080783393804e-09); - p = fma(p, w, -1.4960026627149240478e-08); - p = fma(p, w, 2.9147953450901080826e-08); - p = fma(p, w, -6.7711997758452339498e-08); - p = fma(p, w, 2.2900482228026654717e-07); - p = fma(p, w, -9.9298272942317002539e-07); - p = fma(p, w, 4.5260625972231537039e-06); - p = fma(p, w, -1.9681778105531670567e-05); - p = fma(p, w, 7.5995277030017761139e-05); - p = fma(p, w, -0.00021503011930044477347); - p = fma(p, w, -0.00013871931833623122026); - p = fma(p, w, 1.0103004648645343977); - p = fma(p, w, 4.8499064014085844221); - } - return p * x; -} - -namespace { - -// Direct implementation of AS63, BETAIN() -// https://www.jstor.org/stable/2346797?seq=3#page_scan_tab_contents. -// -// BETAIN(x, p, q, beta) -// x: the value of the upper limit x. -// p: the value of the parameter p. -// q: the value of the parameter q. -// beta: the value of ln B(p, q) -// -double BetaIncompleteImpl(const double x, const double p, const double q, - const double beta) { - if (p < (p + q) * x) { - // Incomplete beta function is symmetrical, so return the complement. - return 1. - BetaIncompleteImpl(1.0 - x, q, p, beta); - } - - double psq = p + q; - const double kErr = 1e-14; - const double xc = 1. - x; - const double pre = - std::exp(p * std::log(x) + (q - 1.) * std::log(xc) - beta) / p; - - double term = 1.; - double ai = 1.; - double result = 1.; - int ns = static_cast(q + xc * psq); - - // Use the soper reduction forumla. - double rx = (ns == 0) ? x : x / xc; - double temp = q - ai; - for (;;) { - term = term * temp * rx / (p + ai); - result = result + term; - temp = std::fabs(term); - if (temp < kErr && temp < kErr * result) { - return result * pre; - } - ai = ai + 1.; - --ns; - if (ns >= 0) { - temp = q - ai; - if (ns == 0) { - rx = x; - } - } else { - temp = psq; - psq = psq + 1.; - } - } - - // NOTE: See also TOMS Alogrithm 708. - // http://www.netlib.org/toms/index.html - // - // NOTE: The NWSC library also includes BRATIO / ISUBX (p87) - // https://archive.org/details/DTIC_ADA261511/page/n75 -} - -// Direct implementation of AS109, XINBTA(p, q, beta, alpha) -// https://www.jstor.org/stable/2346798?read-now=1&seq=4#page_scan_tab_contents -// https://www.jstor.org/stable/2346887?seq=1#page_scan_tab_contents -// -// XINBTA(p, q, beta, alhpa) -// p: the value of the parameter p. -// q: the value of the parameter q. -// beta: the value of ln B(p, q) -// alpha: the value of the lower tail area. -// -double BetaIncompleteInvImpl(const double p, const double q, const double beta, - const double alpha) { - if (alpha < 0.5) { - // Inverse Incomplete beta function is symmetrical, return the complement. - return 1. - BetaIncompleteInvImpl(q, p, beta, 1. - alpha); - } - const double kErr = 1e-14; - double value = kErr; - - // Compute the initial estimate. - { - double r = std::sqrt(-std::log(alpha * alpha)); - double y = - r - fma(r, 0.27061, 2.30753) / fma(r, fma(r, 0.04481, 0.99229), 1.0); - if (p > 1. && q > 1.) { - r = (y * y - 3.) / 6.; - double s = 1. / (p + p - 1.); - double t = 1. / (q + q - 1.); - double h = 2. / s + t; - double w = - y * std::sqrt(h + r) / h - (t - s) * (r + 5. / 6. - t / (3. * h)); - value = p / (p + q * std::exp(w + w)); - } else { - r = q + q; - double t = 1.0 / (9. * q); - double u = 1.0 - t + y * std::sqrt(t); - t = r * (u * u * u); - if (t <= 0) { - value = 1.0 - std::exp((std::log((1.0 - alpha) * q) + beta) / q); - } else { - t = (4.0 * p + r - 2.0) / t; - if (t <= 1) { - value = std::exp((std::log(alpha * p) + beta) / p); - } else { - value = 1.0 - 2.0 / (t + 1.0); - } - } - } - } - - // Solve for x using a modified newton-raphson method using the function - // BetaIncomplete. - { - value = std::max(value, kErr); - value = std::min(value, 1.0 - kErr); - - const double r = 1.0 - p; - const double t = 1.0 - q; - double y; - double yprev = 0; - double sq = 1; - double prev = 1; - for (;;) { - if (value < 0 || value > 1.0) { - // Error case; value went infinite. - return std::numeric_limits::infinity(); - } else if (value == 0 || value == 1) { - y = value; - } else { - y = BetaIncompleteImpl(value, p, q, beta); - if (!std::isfinite(y)) { - return y; - } - } - y = (y - alpha) * - std::exp(beta + r * std::log(value) + t * std::log(1.0 - value)); - if (y * yprev <= 0) { - prev = std::max(sq, std::numeric_limits::min()); - } - double g = 1.0; - for (;;) { - const double adj = g * y; - const double adj_sq = adj * adj; - if (adj_sq >= prev) { - g = g / 3.0; - continue; - } - const double tx = value - adj; - if (tx < 0 || tx > 1) { - g = g / 3.0; - continue; - } - if (prev < kErr) { - return value; - } - if (y * y < kErr) { - return value; - } - if (tx == value) { - return value; - } - if (tx == 0 || tx == 1) { - g = g / 3.0; - continue; - } - value = tx; - yprev = y; - break; - } - } - } - - // NOTES: See also: Asymptotic inversion of the incomplete beta function. - // https://core.ac.uk/download/pdf/82140723.pdf - // - // NOTE: See the Boost library documentation as well: - // https://www.boost.org/doc/libs/1_52_0/libs/math/doc/sf_and_dist/html/math_toolkit/special/sf_beta/ibeta_function.html -} - -} // namespace - -double BetaIncomplete(const double x, const double p, const double q) { - // Error cases. - if (p < 0 || q < 0 || x < 0 || x > 1.0) { - return std::numeric_limits::infinity(); - } - if (x == 0 || x == 1) { - return x; - } - // ln(Beta(p, q)) - double beta = std::lgamma(p) + std::lgamma(q) - std::lgamma(p + q); - return BetaIncompleteImpl(x, p, q, beta); -} - -double BetaIncompleteInv(const double p, const double q, const double alpha) { - // Error cases. - if (p < 0 || q < 0 || alpha < 0 || alpha > 1.0) { - return std::numeric_limits::infinity(); - } - if (alpha == 0 || alpha == 1) { - return alpha; - } - // ln(Beta(p, q)) - double beta = std::lgamma(p) + std::lgamma(q) - std::lgamma(p + q); - return BetaIncompleteInvImpl(p, q, beta, alpha); -} - -// Given `num_trials` trials each with probability `p` of success, the -// probability of no failures is `p^k`. To ensure the probability of a failure -// is no more than `p_fail`, it must be that `p^k == 1 - p_fail`. This function -// computes `p` from that equation. -double RequiredSuccessProbability(const double p_fail, const int num_trials) { - double p = std::exp(std::log(1.0 - p_fail) / static_cast(num_trials)); - ABSL_ASSERT(p > 0); - return p; -} - -double ZScore(double expected_mean, const DistributionMoments& moments) { - return (moments.mean - expected_mean) / - (std::sqrt(moments.variance) / - std::sqrt(static_cast(moments.n))); -} - -double MaxErrorTolerance(double acceptance_probability) { - double one_sided_pvalue = 0.5 * (1.0 - acceptance_probability); - const double max_err = InverseNormalSurvival(one_sided_pvalue); - ABSL_ASSERT(max_err > 0); - return max_err; -} - -} // namespace random_internal -ABSL_NAMESPACE_END -} // namespace absl -- cgit 1.4.1