blob: 1a4b26c334fc2f27c6f69adb2716aeaeab97bfcd [file] [log] [blame]
// Copyright 2023 The Chromium Authors
// Use of this source code is governed by a BSD-style license that can be
// found in the LICENSE file.
#include "content/browser/tpcd_heuristics/opener_heuristic_metrics.h"
#include <algorithm>
#include <cstdint>
#include <memory>
#include "base/metrics/histogram.h"
namespace content {
int32_t Bucketize3PCDHeuristicSample(int64_t sample, int64_t maximum) {
static constexpr size_t kBucketCount = 50;
// Clamp the sample between 0 and maximum, and to the max int32 value (only
// int32 is supported by histograms).
if (sample <= 0) {
return 0;
}
if (sample > std::min(maximum, static_cast<int64_t>(INT32_MAX))) {
return std::min(maximum, static_cast<int64_t>(INT32_MAX));
}
// This bucketing implementation is based heavily on
// base::Histogram::InitializeBucketRanges, but without allocating extra
// memory.
base::Histogram::Sample32 current = 1;
double log_current = 0;
double log_max = log(static_cast<double>(maximum));
// Iterate over buckets and return the one closest to the sample.
// Two of the buckets are 0 and `maximum`. Loop over the remaining buckets.
static constexpr size_t kCutoffCount = kBucketCount - 2;
for (size_t cutoff_index = 0; cutoff_index < kCutoffCount; ++cutoff_index) {
// Increment the log of the bucket proportional to the current log over the
// number of remaining buckets.
double log_next =
log_current + (log_max - log_current) / (kCutoffCount - cutoff_index);
base::Histogram::Sample32 next = static_cast<int>(std::round(exp(log_next)));
// If the difference between the buckets is too close, just add 1 to the
// previous bucket.
if (next <= current) {
next = current + 1;
}
// Check if the sample falls in the bucket, and return the lower bound if
// it does.
if (sample < next) {
return current;
}
// Increment the current values to the next values.
current = next;
log_current = log_next;
}
return maximum;
}
} // namespace content