Creation of LTS branch "lts_2019_08_08"20190808

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GitOrigin-RevId: 9ee91d3e430fb33a4590486573792eb0fa146c2d
Change-Id: Ia06e548bc106cc9d136f6c65714be6645317aced

1 files changed, 195 insertions, 0 deletions

diff --git a/absl/random/uniform_real_distribution.h b/absl/random/uniform_real_distribution.h
new file mode 100644
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--- /dev/null
+++ b/absl/random/uniform_real_distribution.h
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+// 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.
+//
+// -----------------------------------------------------------------------------
+// File: uniform_real_distribution.h
+// -----------------------------------------------------------------------------
+//
+// This header defines a class for representing a uniform floating-point
+// distribution over a half-open interval [a,b). You use this distribution in
+// combination with an Abseil random bit generator to produce random values
+// according to the rules of the distribution.
+//
+// `absl::uniform_real_distribution` is a drop-in replacement for the C++11
+// `std::uniform_real_distribution` [rand.dist.uni.real] but is considerably
+// faster than the libstdc++ implementation.
+//
+// Note: the standard-library version may occasionally return `1.0` when
+// default-initialized. See https://bugs.llvm.org//show_bug.cgi?id=18767
+// `absl::uniform_real_distribution` does not exhibit this behavior.
+
+#ifndef ABSL_RANDOM_UNIFORM_REAL_DISTRIBUTION_H_
+#define ABSL_RANDOM_UNIFORM_REAL_DISTRIBUTION_H_
+
+#include <cassert>
+#include <cmath>
+#include <cstdint>
+#include <istream>
+#include <limits>
+#include <type_traits>
+
+#include "absl/random/internal/distribution_impl.h"
+#include "absl/random/internal/fast_uniform_bits.h"
+#include "absl/random/internal/iostream_state_saver.h"
+
+namespace absl {
+inline namespace lts_2019_08_08 {
+
+// absl::uniform_real_distribution<T>
+//
+// This distribution produces random floating-point values uniformly distributed
+// over the half-open interval [a, b).
+//
+// Example:
+//
+//   absl::BitGen gen;
+//
+//   // Use the distribution to produce a value between 0.0 (inclusive)
+//   // and 1.0 (exclusive).
+//   int value = absl::uniform_real_distribution<double>(0, 1)(gen);
+//
+template <typename RealType = double>
+class uniform_real_distribution {
+ public:
+  using result_type = RealType;
+
+  class param_type {
+   public:
+    using distribution_type = uniform_real_distribution;
+
+    explicit param_type(result_type lo = 0, result_type hi = 1)
+        : lo_(lo), hi_(hi), range_(hi - lo) {
+      // [rand.dist.uni.real] preconditions 2 & 3
+      assert(lo <= hi);
+      // NOTE: For integral types, we can promote the range to an unsigned type,
+      // which gives full width of the range. However for real (fp) types, this
+      // is not possible, so value generation cannot use the full range of the
+      // real type.
+      assert(range_ <= (std::numeric_limits<result_type>::max)());
+    }
+
+    result_type a() const { return lo_; }
+    result_type b() const { return hi_; }
+
+    friend bool operator==(const param_type& a, const param_type& b) {
+      return a.lo_ == b.lo_ && a.hi_ == b.hi_;
+    }
+
+    friend bool operator!=(const param_type& a, const param_type& b) {
+      return !(a == b);
+    }
+
+   private:
+    friend class uniform_real_distribution;
+    result_type lo_, hi_, range_;
+
+    static_assert(std::is_floating_point<RealType>::value,
+                  "Class-template absl::uniform_real_distribution<> must be "
+                  "parameterized using a floating-point type.");
+  };
+
+  uniform_real_distribution() : uniform_real_distribution(0) {}
+
+  explicit uniform_real_distribution(result_type lo, result_type hi = 1)
+      : param_(lo, hi) {}
+
+  explicit uniform_real_distribution(const param_type& param) : param_(param) {}
+
+  // uniform_real_distribution<T>::reset()
+  //
+  // Resets the uniform real distribution. Note that this function has no effect
+  // because the distribution already produces independent values.
+  void reset() {}
+
+  template <typename URBG>
+  result_type operator()(URBG& gen) {  // NOLINT(runtime/references)
+    return operator()(gen, param_);
+  }
+
+  template <typename URBG>
+  result_type operator()(URBG& gen,  // NOLINT(runtime/references)
+                         const param_type& p);
+
+  result_type a() const { return param_.a(); }
+  result_type b() const { return param_.b(); }
+
+  param_type param() const { return param_; }
+  void param(const param_type& params) { param_ = params; }
+
+  result_type(min)() const { return a(); }
+  result_type(max)() const { return b(); }
+
+  friend bool operator==(const uniform_real_distribution& a,
+                         const uniform_real_distribution& b) {
+    return a.param_ == b.param_;
+  }
+  friend bool operator!=(const uniform_real_distribution& a,
+                         const uniform_real_distribution& b) {
+    return a.param_ != b.param_;
+  }
+
+ private:
+  param_type param_;
+  random_internal::FastUniformBits<uint64_t> fast_u64_;
+};
+
+// -----------------------------------------------------------------------------
+// Implementation details follow
+// -----------------------------------------------------------------------------
+template <typename RealType>
+template <typename URBG>
+typename uniform_real_distribution<RealType>::result_type
+uniform_real_distribution<RealType>::operator()(
+    URBG& gen, const param_type& p) {  // NOLINT(runtime/references)
+  using random_internal::PositiveValueT;
+  while (true) {
+    const result_type sample = random_internal::RandU64ToReal<
+        result_type>::template Value<PositiveValueT, true>(fast_u64_(gen));
+    const result_type res = p.a() + (sample * p.range_);
+    if (res < p.b() || p.range_ <= 0 || !std::isfinite(p.range_)) {
+      return res;
+    }
+    // else sample rejected, try again.
+  }
+}
+
+template <typename CharT, typename Traits, typename RealType>
+std::basic_ostream<CharT, Traits>& operator<<(
+    std::basic_ostream<CharT, Traits>& os,  // NOLINT(runtime/references)
+    const uniform_real_distribution<RealType>& x) {
+  auto saver = random_internal::make_ostream_state_saver(os);
+  os.precision(random_internal::stream_precision_helper<RealType>::kPrecision);
+  os << x.a() << os.fill() << x.b();
+  return os;
+}
+
+template <typename CharT, typename Traits, typename RealType>
+std::basic_istream<CharT, Traits>& operator>>(
+    std::basic_istream<CharT, Traits>& is,     // NOLINT(runtime/references)
+    uniform_real_distribution<RealType>& x) {  // NOLINT(runtime/references)
+  using param_type = typename uniform_real_distribution<RealType>::param_type;
+  using result_type = typename uniform_real_distribution<RealType>::result_type;
+  auto saver = random_internal::make_istream_state_saver(is);
+  auto a = random_internal::read_floating_point<result_type>(is);
+  if (is.fail()) return is;
+  auto b = random_internal::read_floating_point<result_type>(is);
+  if (!is.fail()) {
+    x.param(param_type(a, b));
+  }
+  return is;
+}
+}  // inline namespace lts_2019_08_08
+}  // namespace absl
+
+#endif  // ABSL_RANDOM_UNIFORM_REAL_DISTRIBUTION_H_