/src/hermes/include/hermes/Support/StatsAccumulator.h
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1 | | /* |
2 | | * Copyright (c) Meta Platforms, Inc. and affiliates. |
3 | | * |
4 | | * This source code is licensed under the MIT license found in the |
5 | | * LICENSE file in the root directory of this source tree. |
6 | | */ |
7 | | |
8 | | #ifndef HERMES_SUPPORT_STATSACCUMULATOR_H |
9 | | #define HERMES_SUPPORT_STATSACCUMULATOR_H |
10 | | |
11 | | #include <algorithm> |
12 | | #include <cmath> |
13 | | |
14 | | namespace hermes { |
15 | | |
16 | | /// Gathers summary statistics for a sequence of samples for a |
17 | | /// statistic of type T. The statistic type T must be convertible to |
18 | | /// double. SumT is provided for cases where the sum of the samples |
19 | | /// might overflow the type T. T must be convertible to SumT, and |
20 | | /// SumT must be convertible to double. |
21 | | template <typename T, typename SumT = T> |
22 | | class StatsAccumulator { |
23 | | public: |
24 | 1.18k | StatsAccumulator() = default; hermes::StatsAccumulator<double, double>::StatsAccumulator() Line | Count | Source | 24 | 594 | StatsAccumulator() = default; |
hermes::StatsAccumulator<unsigned int, unsigned long>::StatsAccumulator() Line | Count | Source | 24 | 594 | StatsAccumulator() = default; |
|
25 | | |
26 | | /// Update the summary stats with the addition of a new \p value. |
27 | 3.76k | inline void record(T value) { |
28 | 3.76k | if (n_ == 0) { |
29 | 87 | min_ = value; |
30 | 87 | max_ = value; |
31 | 3.67k | } else { |
32 | 3.67k | min_ = std::min(min_, value); |
33 | 3.67k | max_ = std::max(max_, value); |
34 | 3.67k | } |
35 | 3.76k | n_++; |
36 | 3.76k | sum_ += value; |
37 | 3.76k | double valD = static_cast<double>(value); |
38 | 3.76k | sumOfSquares_ += valD * valD; |
39 | 3.76k | } hermes::StatsAccumulator<double, double>::record(double) Line | Count | Source | 27 | 1.74k | inline void record(T value) { | 28 | 1.74k | if (n_ == 0) { | 29 | 41 | min_ = value; | 30 | 41 | max_ = value; | 31 | 1.70k | } else { | 32 | 1.70k | min_ = std::min(min_, value); | 33 | 1.70k | max_ = std::max(max_, value); | 34 | 1.70k | } | 35 | 1.74k | n_++; | 36 | 1.74k | sum_ += value; | 37 | 1.74k | double valD = static_cast<double>(value); | 38 | 1.74k | sumOfSquares_ += valD * valD; | 39 | 1.74k | } |
hermes::StatsAccumulator<unsigned int, unsigned long>::record(unsigned int) Line | Count | Source | 27 | 2.01k | inline void record(T value) { | 28 | 2.01k | if (n_ == 0) { | 29 | 46 | min_ = value; | 30 | 46 | max_ = value; | 31 | 1.97k | } else { | 32 | 1.97k | min_ = std::min(min_, value); | 33 | 1.97k | max_ = std::max(max_, value); | 34 | 1.97k | } | 35 | 2.01k | n_++; | 36 | 2.01k | sum_ += value; | 37 | 2.01k | double valD = static_cast<double>(value); | 38 | 2.01k | sumOfSquares_ += valD * valD; | 39 | 2.01k | } |
|
40 | | |
41 | | /// Accessors |
42 | | |
43 | | /// \return the number of samples recorded. |
44 | | inline unsigned count() const { |
45 | | return n_; |
46 | | } |
47 | | |
48 | | /// \return the minimum of the samples recorded. |
49 | | inline T min() const { |
50 | | return min_; |
51 | | } |
52 | | |
53 | | /// \return the maximum of the samples recorded. |
54 | 0 | inline T max() const { |
55 | 0 | return max_; |
56 | 0 | } Unexecuted instantiation: hermes::StatsAccumulator<unsigned int, unsigned long>::max() const Unexecuted instantiation: hermes::StatsAccumulator<double, double>::max() const |
57 | | |
58 | | /// \return the sum of the samples recorded. |
59 | 0 | inline SumT sum() const { |
60 | 0 | return sum_; |
61 | 0 | } |
62 | | |
63 | | /// Returns the average of the recorded samples. |
64 | 0 | inline double average() const { |
65 | 0 | return n_ == 0 ? 0.0 : static_cast<double>(sum_) / n_; |
66 | 0 | } |
67 | | |
68 | | /// \return the sum of the squares of the samples recorded. |
69 | 0 | inline double sumOfSquares() const { |
70 | 0 | return sumOfSquares_; |
71 | 0 | } |
72 | | |
73 | | /// Returns the standard deviation of the recorded samples. |
74 | | inline double stddev() const; |
75 | | |
76 | | private: |
77 | | /// Number of samples recorded. |
78 | | unsigned n_{0}; |
79 | | /// Sum of the samples. |
80 | | SumT sum_{0}; |
81 | | /// Minimum sample. |
82 | | T min_{0}; |
83 | | /// Maximum sample. |
84 | | T max_{0}; |
85 | | /// Sum of the squares of the durations (necessary for standard |
86 | | /// devation). We assume that because of the squaring, it may grow |
87 | | /// large, so always use double for this value. |
88 | | double sumOfSquares_{0.0}; |
89 | | }; |
90 | | |
91 | | template <typename T, typename SumT> |
92 | | inline double StatsAccumulator<T, SumT>::stddev() const { |
93 | | if (n_ == 0) { |
94 | | return 0.0; |
95 | | } |
96 | | double avg = average(); |
97 | | // See, e.g., |
98 | | // https://math.stackexchange.com/questions/198336/how-to-calculate-standard-deviation-with-streaming-inputs |
99 | | // for an explanation. |
100 | | double variance = (sumOfSquares_ / n_) - (avg * avg); |
101 | | return std::sqrt(variance); |
102 | | } |
103 | | |
104 | | } // namespace hermes |
105 | | |
106 | | #endif // HERMES_SUPPORT_STATSACCUMULATOR_H |