ESPResSo
Extensible Simulation Package for Research on Soft Matter Systems
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Accumulator.hpp
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1/*
2 * Copyright (C) 2010-2022 The ESPResSo project
3 *
4 * This file is part of ESPResSo.
5 *
6 * ESPResSo is free software: you can redistribute it and/or modify
7 * it under the terms of the GNU General Public License as published by
8 * the Free Software Foundation, either version 3 of the License, or
9 * (at your option) any later version.
10 *
11 * ESPResSo is distributed in the hope that it will be useful,
12 * but WITHOUT ANY WARRANTY; without even the implied warranty of
13 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
14 * GNU General Public License for more details.
15 *
16 * You should have received a copy of the GNU General Public License
17 * along with this program. If not, see <http://www.gnu.org/licenses/>.
18 */
19#ifndef CORE_UTILS_ACCUMULATOR
20#define CORE_UTILS_ACCUMULATOR
21
22#include <boost/serialization/access.hpp>
23#include <boost/serialization/vector.hpp>
24
25#include <algorithm>
26#include <cmath>
27#include <cstddef>
28#include <limits>
29#include <stdexcept>
30#include <vector>
31
32namespace Utils {
33
34template <typename T> struct AccumulatorData {
35 T mean = T{};
36 T m = T{};
37
38private:
39 // Allow serialization to access non-public data members.
41
42 template <typename Archive>
43 void serialize(Archive &ar, const unsigned /*version*/) {
44 ar & mean & m;
45 }
46};
47
49public:
50 explicit Accumulator(std::size_t N) : m_n(0u), m_acc_data(N) {}
51 void operator()(const std::vector<double> &);
52 std::vector<double> mean() const;
53 std::vector<double> variance() const;
54 std::vector<double> std_error() const;
55
56private:
57 std::size_t m_n;
58 std::vector<AccumulatorData<double>> m_acc_data;
59 // Allow serialization to access non-public data members.
61
62 template <typename Archive>
63 void serialize(Archive &ar, const unsigned /*version*/) {
64 ar & m_n & m_acc_data;
65 }
66};
67
68inline void Accumulator::operator()(const std::vector<double> &data) {
69 if (data.size() != m_acc_data.size())
70 throw std::runtime_error(
71 "The given data size does not fit the initialized size!");
72 ++m_n;
73 if (m_n == 1u) {
74 std::ranges::transform(
75 data, m_acc_data.begin(),
76 [](double d) -> AccumulatorData<double> { return {d, 0.0}; });
77 } else {
78 auto const denominator = static_cast<double>(m_n);
79 std::ranges::transform(m_acc_data, data, m_acc_data.begin(),
80 [denominator](auto const &a, double d) {
81 auto const old_mean = a.mean;
82 auto const new_mean =
83 old_mean + (d - old_mean) / denominator;
84 auto const new_m =
85 a.m + (d - old_mean) * (d - new_mean);
86 return AccumulatorData<double>{new_mean, new_m};
87 });
88 }
89}
90
91/**
92 * @brief Compute the sample mean.
93 */
94inline std::vector<double> Accumulator::mean() const {
95 std::vector<double> res{};
96 std::ranges::transform(m_acc_data, std::back_inserter(res),
97 [](auto const &acc_data) { return acc_data.mean; });
98 return res;
99}
100
101/**
102 * @brief Compute the Bessel-corrected sample variance,
103 * assuming uncorrelated data.
104 */
105inline std::vector<double> Accumulator::variance() const {
106 std::vector<double> res{};
107 if (m_n == 1u) {
108 res = std::vector<double>(m_acc_data.size(),
109 std::numeric_limits<double>::max());
110 } else {
111 auto const denominator = static_cast<double>(m_n) - 1.;
112 std::ranges::transform(m_acc_data, std::back_inserter(res),
113 [denominator](auto const &acc_data) {
114 return acc_data.m / denominator;
115 });
116 }
117 return res;
118}
119
120/**
121 * @brief Compute the standard error of the mean, assuming uncorrelated data.
122 */
123inline std::vector<double> Accumulator::std_error() const {
124 auto const var = variance();
125 std::vector<double> err{};
126 auto const denominator = static_cast<double>(m_n);
127 std::ranges::transform(var, std::back_inserter(err), [denominator](double d) {
128 return std::sqrt(d / denominator);
129 });
130 return err;
131}
132
133} // namespace Utils
134
135#endif
std::vector< double > std_error() const
Compute the standard error of the mean, assuming uncorrelated data.
Accumulator(std::size_t N)
std::vector< double > variance() const
Compute the Bessel-corrected sample variance, assuming uncorrelated data.
void operator()(const std::vector< double > &)
std::vector< double > mean() const
Compute the sample mean.
friend class boost::serialization::access
cudaStream_t stream[1]
CUDA streams for parallel computing on CPU and GPU.
friend class boost::serialization::access