Creation of LTS branch "lts_2019_08_08"20190808

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GitOrigin-RevId: 9ee91d3e430fb33a4590486573792eb0fa146c2d
Change-Id: Ia06e548bc106cc9d136f6c65714be6645317aced

1 files changed, 159 insertions, 0 deletions

diff --git a/absl/random/exponential_distribution.h b/absl/random/exponential_distribution.h
new file mode 100644
index 00000000..ed5551ae
--- /dev/null
+++ b/absl/random/exponential_distribution.h
@@ -0,0 +1,159 @@
+// 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.
+
+#ifndef ABSL_RANDOM_EXPONENTIAL_DISTRIBUTION_H_
+#define ABSL_RANDOM_EXPONENTIAL_DISTRIBUTION_H_
+
+#include <cassert>
+#include <cmath>
+#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::exponential_distribution:
+// Generates a number conforming to an exponential distribution and is
+// equivalent to the standard [rand.dist.pois.exp] distribution.
+template <typename RealType = double>
+class exponential_distribution {
+ public:
+  using result_type = RealType;
+
+  class param_type {
+   public:
+    using distribution_type = exponential_distribution;
+
+    explicit param_type(result_type lambda = 1) : lambda_(lambda) {
+      assert(lambda > 0);
+      neg_inv_lambda_ = -result_type(1) / lambda_;
+    }
+
+    result_type lambda() const { return lambda_; }
+
+    friend bool operator==(const param_type& a, const param_type& b) {
+      return a.lambda_ == b.lambda_;
+    }
+
+    friend bool operator!=(const param_type& a, const param_type& b) {
+      return !(a == b);
+    }
+
+   private:
+    friend class exponential_distribution;
+
+    result_type lambda_;
+    result_type neg_inv_lambda_;
+
+    static_assert(
+        std::is_floating_point<RealType>::value,
+        "Class-template absl::exponential_distribution<> must be parameterized "
+        "using a floating-point type.");
+  };
+
+  exponential_distribution() : exponential_distribution(1) {}
+
+  explicit exponential_distribution(result_type lambda) : param_(lambda) {}
+
+  explicit exponential_distribution(const param_type& p) : param_(p) {}
+
+  void reset() {}
+
+  // Generating functions
+  template <typename URBG>
+  result_type operator()(URBG& g) {  // NOLINT(runtime/references)
+    return (*this)(g, param_);
+  }
+
+  template <typename URBG>
+  result_type operator()(URBG& g,  // NOLINT(runtime/references)
+                         const param_type& p);
+
+  param_type param() const { return param_; }
+  void param(const param_type& p) { param_ = p; }
+
+  result_type(min)() const { return 0; }
+  result_type(max)() const {
+    return std::numeric_limits<result_type>::infinity();
+  }
+
+  result_type lambda() const { return param_.lambda(); }
+
+  friend bool operator==(const exponential_distribution& a,
+                         const exponential_distribution& b) {
+    return a.param_ == b.param_;
+  }
+  friend bool operator!=(const exponential_distribution& a,
+                         const exponential_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 exponential_distribution<RealType>::result_type
+exponential_distribution<RealType>::operator()(
+    URBG& g,  // NOLINT(runtime/references)
+    const param_type& p) {
+  using random_internal::NegativeValueT;
+  const result_type u = random_internal::RandU64ToReal<
+      result_type>::template Value<NegativeValueT, false>(fast_u64_(g));
+  // log1p(-x) is mathematically equivalent to log(1 - x) but has more
+  // accuracy for x near zero.
+  return p.neg_inv_lambda_ * std::log1p(u);
+}
+
+template <typename CharT, typename Traits, typename RealType>
+std::basic_ostream<CharT, Traits>& operator<<(
+    std::basic_ostream<CharT, Traits>& os,  // NOLINT(runtime/references)
+    const exponential_distribution<RealType>& x) {
+  auto saver = random_internal::make_ostream_state_saver(os);
+  os.precision(random_internal::stream_precision_helper<RealType>::kPrecision);
+  os << x.lambda();
+  return os;
+}
+
+template <typename CharT, typename Traits, typename RealType>
+std::basic_istream<CharT, Traits>& operator>>(
+    std::basic_istream<CharT, Traits>& is,    // NOLINT(runtime/references)
+    exponential_distribution<RealType>& x) {  // NOLINT(runtime/references)
+  using result_type = typename exponential_distribution<RealType>::result_type;
+  using param_type = typename exponential_distribution<RealType>::param_type;
+  result_type lambda;
+
+  auto saver = random_internal::make_istream_state_saver(is);
+  lambda = random_internal::read_floating_point<result_type>(is);
+  if (!is.fail()) {
+    x.param(param_type(lambda));
+  }
+  return is;
+}
+
+}  // inline namespace lts_2019_08_08
+}  // namespace absl
+
+#endif  // ABSL_RANDOM_EXPONENTIAL_DISTRIBUTION_H_