--- /dev/null
+// 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_LOG_UNIFORM_INT_DISTRIBUTION_H_
+#define ABSL_RANDOM_LOG_UNIFORM_INT_DISTRIBUTION_H_
+
+#include <algorithm>
+#include <cassert>
+#include <cmath>
+#include <istream>
+#include <limits>
+#include <ostream>
+#include <type_traits>
+
+#include "absl/random/internal/distribution_impl.h"
+#include "absl/random/internal/fastmath.h"
+#include "absl/random/internal/iostream_state_saver.h"
+#include "absl/random/internal/traits.h"
+#include "absl/random/uniform_int_distribution.h"
+
+namespace absl {
+
+// log_uniform_int_distribution:
+//
+// Returns a random variate R in range [min, max] such that
+// floor(log(R-min, base)) is uniformly distributed.
+// We ensure uniformity by discretization using the
+// boundary sets [0, 1, base, base * base, ... min(base*n, max)]
+//
+template <typename IntType = int>
+class log_uniform_int_distribution {
+ private:
+ using unsigned_type =
+ typename random_internal::make_unsigned_bits<IntType>::type;
+
+ public:
+ using result_type = IntType;
+
+ class param_type {
+ public:
+ using distribution_type = log_uniform_int_distribution;
+
+ explicit param_type(
+ result_type min = 0,
+ result_type max = (std::numeric_limits<result_type>::max)(),
+ result_type base = 2)
+ : min_(min),
+ max_(max),
+ base_(base),
+ range_(static_cast<unsigned_type>(max_) -
+ static_cast<unsigned_type>(min_)),
+ log_range_(0) {
+ assert(max_ >= min_);
+ assert(base_ > 1);
+
+ if (base_ == 2) {
+ // Determine where the first set bit is on range(), giving a log2(range)
+ // value which can be used to construct bounds.
+ log_range_ = (std::min)(random_internal::LeadingSetBit(range()),
+ std::numeric_limits<unsigned_type>::digits);
+ } else {
+ // NOTE: Computing the logN(x) introduces error from 2 sources:
+ // 1. Conversion of int to double loses precision for values >=
+ // 2^53, which may cause some log() computations to operate on
+ // different values.
+ // 2. The error introduced by the division will cause the result
+ // to differ from the expected value.
+ //
+ // Thus a result which should equal K may equal K +/- epsilon,
+ // which can eliminate some values depending on where the bounds fall.
+ const double inv_log_base = 1.0 / std::log(base_);
+ const double log_range = std::log(static_cast<double>(range()) + 0.5);
+ log_range_ = static_cast<int>(std::ceil(inv_log_base * log_range));
+ }
+ }
+
+ result_type(min)() const { return min_; }
+ result_type(max)() const { return max_; }
+ result_type base() const { return base_; }
+
+ friend bool operator==(const param_type& a, const param_type& b) {
+ return a.min_ == b.min_ && a.max_ == b.max_ && a.base_ == b.base_;
+ }
+
+ friend bool operator!=(const param_type& a, const param_type& b) {
+ return !(a == b);
+ }
+
+ private:
+ friend class log_uniform_int_distribution;
+
+ int log_range() const { return log_range_; }
+ unsigned_type range() const { return range_; }
+
+ result_type min_;
+ result_type max_;
+ result_type base_;
+ unsigned_type range_; // max - min
+ int log_range_; // ceil(logN(range_))
+
+ static_assert(std::is_integral<IntType>::value,
+ "Class-template absl::log_uniform_int_distribution<> must be "
+ "parameterized using an integral type.");
+ };
+
+ log_uniform_int_distribution() : log_uniform_int_distribution(0) {}
+
+ explicit log_uniform_int_distribution(
+ result_type min,
+ result_type max = (std::numeric_limits<result_type>::max)(),
+ result_type base = 2)
+ : param_(min, max, base) {}
+
+ explicit log_uniform_int_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) {
+ return (p.min)() + Generate(g, p);
+ }
+
+ result_type(min)() const { return (param_.min)(); }
+ result_type(max)() const { return (param_.max)(); }
+ result_type base() const { return param_.base(); }
+
+ param_type param() const { return param_; }
+ void param(const param_type& p) { param_ = p; }
+
+ friend bool operator==(const log_uniform_int_distribution& a,
+ const log_uniform_int_distribution& b) {
+ return a.param_ == b.param_;
+ }
+ friend bool operator!=(const log_uniform_int_distribution& a,
+ const log_uniform_int_distribution& b) {
+ return a.param_ != b.param_;
+ }
+
+ private:
+ // Returns a log-uniform variate in the range [0, p.range()]. The caller
+ // should add min() to shift the result to the correct range.
+ template <typename URNG>
+ unsigned_type Generate(URNG& g, // NOLINT(runtime/references)
+ const param_type& p);
+
+ param_type param_;
+};
+
+template <typename IntType>
+template <typename URBG>
+typename log_uniform_int_distribution<IntType>::unsigned_type
+log_uniform_int_distribution<IntType>::Generate(
+ URBG& g, // NOLINT(runtime/references)
+ const param_type& p) {
+ // sample e over [0, log_range]. Map the results of e to this:
+ // 0 => 0
+ // 1 => [1, b-1]
+ // 2 => [b, (b^2)-1]
+ // n => [b^(n-1)..(b^n)-1]
+ const int e = absl::uniform_int_distribution<int>(0, p.log_range())(g);
+ if (e == 0) {
+ return 0;
+ }
+ const int d = e - 1;
+
+ unsigned_type base_e, top_e;
+ if (p.base() == 2) {
+ base_e = static_cast<unsigned_type>(1) << d;
+
+ top_e = (e >= std::numeric_limits<unsigned_type>::digits)
+ ? (std::numeric_limits<unsigned_type>::max)()
+ : (static_cast<unsigned_type>(1) << e) - 1;
+ } else {
+ const double r = std::pow(p.base(), d);
+ const double s = (r * p.base()) - 1.0;
+
+ base_e = (r > (std::numeric_limits<unsigned_type>::max)())
+ ? (std::numeric_limits<unsigned_type>::max)()
+ : static_cast<unsigned_type>(r);
+
+ top_e = (s > (std::numeric_limits<unsigned_type>::max)())
+ ? (std::numeric_limits<unsigned_type>::max)()
+ : static_cast<unsigned_type>(s);
+ }
+
+ const unsigned_type lo = (base_e >= p.range()) ? p.range() : base_e;
+ const unsigned_type hi = (top_e >= p.range()) ? p.range() : top_e;
+
+ // choose uniformly over [lo, hi]
+ return absl::uniform_int_distribution<result_type>(lo, hi)(g);
+}
+
+template <typename CharT, typename Traits, typename IntType>
+std::basic_ostream<CharT, Traits>& operator<<(
+ std::basic_ostream<CharT, Traits>& os, // NOLINT(runtime/references)
+ const log_uniform_int_distribution<IntType>& x) {
+ using stream_type =
+ typename random_internal::stream_format_type<IntType>::type;
+ auto saver = random_internal::make_ostream_state_saver(os);
+ os << static_cast<stream_type>((x.min)()) << os.fill()
+ << static_cast<stream_type>((x.max)()) << os.fill()
+ << static_cast<stream_type>(x.base());
+ return os;
+}
+
+template <typename CharT, typename Traits, typename IntType>
+std::basic_istream<CharT, Traits>& operator>>(
+ std::basic_istream<CharT, Traits>& is, // NOLINT(runtime/references)
+ log_uniform_int_distribution<IntType>& x) { // NOLINT(runtime/references)
+ using param_type = typename log_uniform_int_distribution<IntType>::param_type;
+ using result_type =
+ typename log_uniform_int_distribution<IntType>::result_type;
+ using stream_type =
+ typename random_internal::stream_format_type<IntType>::type;
+
+ stream_type min;
+ stream_type max;
+ stream_type base;
+
+ auto saver = random_internal::make_istream_state_saver(is);
+ is >> min >> max >> base;
+ if (!is.fail()) {
+ x.param(param_type(static_cast<result_type>(min),
+ static_cast<result_type>(max),
+ static_cast<result_type>(base)));
+ }
+ return is;
+}
+
+} // namespace absl
+
+#endif // ABSL_RANDOM_LOG_UNIFORM_INT_DISTRIBUTION_H_
git://repos.xcallymotion.com / motion2.git / blobdiff