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[NFC] complexity_n is not of IterationCount type (#1709)

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There is no bug here, but it gave me a scare the other day.
It is not incorrect to use `IterationCount` here,
since it's just an `int64_t` either way,
but it's wildly confusing. Let's not do that.

Co-authored-by: dominic <510002+dmah42@users.noreply.github.com>
This commit is contained in:
Roman Lebedev 2023-12-07 13:40:56 +03:00 committed by GitHub
parent 68689bf966
commit 50560985db
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2 changed files with 13 additions and 9 deletions
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14
include/benchmark/benchmark.h
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@ -672,13 +672,15 @@ typedef std::map<std::string, Counter> UserCounters;
// calculated automatically to the best fit.
enum BigO { oNone, o1, oN, oNSquared, oNCubed, oLogN, oNLogN, oAuto, oLambda };
typedef int64_t ComplexityN;
typedef int64_t IterationCount;
enum StatisticUnit { kTime, kPercentage };
// BigOFunc is passed to a benchmark in order to specify the asymptotic
// computational complexity for the benchmark.
typedef double(BigOFunc)(IterationCount);
typedef double(BigOFunc)(ComplexityN);
// StatisticsFunc is passed to a benchmark in order to compute some descriptive
// statistics over all the measurements of some type
@ -875,10 +877,12 @@ class BENCHMARK_EXPORT State {
// and complexity_n will
// represent the length of N.
BENCHMARK_ALWAYS_INLINE
void SetComplexityN(int64_t complexity_n) { complexity_n_ = complexity_n; }
void SetComplexityN(ComplexityN complexity_n) {
complexity_n_ = complexity_n;
}
BENCHMARK_ALWAYS_INLINE
int64_t complexity_length_n() const { return complexity_n_; }
ComplexityN complexity_length_n() const { return complexity_n_; }
// If this routine is called with items > 0, then an items/s
// label is printed on the benchmark report line for the currently
@ -967,7 +971,7 @@ class BENCHMARK_EXPORT State {
// items we don't need on the first cache line
std::vector<int64_t> range_;
int64_t complexity_n_;
ComplexityN complexity_n_;
public:
// Container for user-defined counters.
@ -1805,7 +1809,7 @@ class BENCHMARK_EXPORT BenchmarkReporter {
// Keep track of arguments to compute asymptotic complexity
BigO complexity;
BigOFunc* complexity_lambda;
int64_t complexity_n;
ComplexityN complexity_n;
// what statistics to compute from the measurements
const std::vector<internal::Statistics>* statistics;

8
src/complexity.cc
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@ -77,12 +77,12 @@ std::string GetBigOString(BigO complexity) {
// given by the lambda expression.
// - n : Vector containing the size of the benchmark tests.
// - time : Vector containing the times for the benchmark tests.
// - fitting_curve : lambda expression (e.g. [](int64_t n) {return n; };).
// - fitting_curve : lambda expression (e.g. [](ComplexityN n) {return n; };).
// For a deeper explanation on the algorithm logic, please refer to
// https://en.wikipedia.org/wiki/Least_squares#Least_squares,_regression_analysis_and_statistics
LeastSq MinimalLeastSq(const std::vector<int64_t>& n,
LeastSq MinimalLeastSq(const std::vector<ComplexityN>& n,
const std::vector<double>& time,
BigOFunc* fitting_curve) {
double sigma_gn_squared = 0.0;
@ -124,7 +124,7 @@ LeastSq MinimalLeastSq(const std::vector<int64_t>& n,
// - complexity : If different than oAuto, the fitting curve will stick to
// this one. If it is oAuto, it will be calculated the best
// fitting curve.
LeastSq MinimalLeastSq(const std::vector<int64_t>& n,
LeastSq MinimalLeastSq(const std::vector<ComplexityN>& n,
const std::vector<double>& time, const BigO complexity) {
BM_CHECK_EQ(n.size(), time.size());
BM_CHECK_GE(n.size(), 2); // Do not compute fitting curve is less than two
@ -164,7 +164,7 @@ std::vector<BenchmarkReporter::Run> ComputeBigO(
if (reports.size() < 2) return results;
// Accumulators.
std::vector<int64_t> n;
std::vector<ComplexityN> n;
std::vector<double> real_time;
std::vector<double> cpu_time;