diff options
Diffstat (limited to 'ipc/chromium/src/base/histogram.cc')
| -rw-r--r-- | ipc/chromium/src/base/histogram.cc | 640 |
1 files changed, 640 insertions, 0 deletions
diff --git a/ipc/chromium/src/base/histogram.cc b/ipc/chromium/src/base/histogram.cc new file mode 100644 index 0000000000..ffb9518466 --- /dev/null +++ b/ipc/chromium/src/base/histogram.cc @@ -0,0 +1,640 @@ +/* -*- Mode: C++; tab-width: 8; indent-tabs-mode: nil; c-basic-offset: 2 -*- */ +/* vim: set ts=8 sts=2 et sw=2 tw=80: */ +// Copyright (c) 2011 The Chromium Authors. All rights reserved. +// Use of this source code is governed by a BSD-style license that can be +// found in the LICENSE file. + +// Histogram is an object that aggregates statistics, and can summarize them in +// various forms, including ASCII graphical, HTML, and numerically (as a +// vector of numbers corresponding to each of the aggregating buckets). +// See header file for details and examples. + +#include "base/histogram.h" + +#include <math.h> + +#include <algorithm> +#include <string> + +#include "base/logging.h" +#include "base/pickle.h" +#include "base/string_util.h" +#include "base/logging.h" + +namespace base { + +#define CHECK_GT DCHECK_GT +#define CHECK_LT DCHECK_LT + +// Static table of checksums for all possible 8 bit bytes. +const uint32_t Histogram::kCrcTable[256] = { + 0x0, 0x77073096L, 0xee0e612cL, 0x990951baL, 0x76dc419L, + 0x706af48fL, 0xe963a535L, 0x9e6495a3L, 0xedb8832L, 0x79dcb8a4L, + 0xe0d5e91eL, 0x97d2d988L, 0x9b64c2bL, 0x7eb17cbdL, 0xe7b82d07L, + 0x90bf1d91L, 0x1db71064L, 0x6ab020f2L, 0xf3b97148L, 0x84be41deL, + 0x1adad47dL, 0x6ddde4ebL, 0xf4d4b551L, 0x83d385c7L, 0x136c9856L, + 0x646ba8c0L, 0xfd62f97aL, 0x8a65c9ecL, 0x14015c4fL, 0x63066cd9L, + 0xfa0f3d63L, 0x8d080df5L, 0x3b6e20c8L, 0x4c69105eL, 0xd56041e4L, + 0xa2677172L, 0x3c03e4d1L, 0x4b04d447L, 0xd20d85fdL, 0xa50ab56bL, + 0x35b5a8faL, 0x42b2986cL, 0xdbbbc9d6L, 0xacbcf940L, 0x32d86ce3L, + 0x45df5c75L, 0xdcd60dcfL, 0xabd13d59L, 0x26d930acL, 0x51de003aL, + 0xc8d75180L, 0xbfd06116L, 0x21b4f4b5L, 0x56b3c423L, 0xcfba9599L, + 0xb8bda50fL, 0x2802b89eL, 0x5f058808L, 0xc60cd9b2L, 0xb10be924L, + 0x2f6f7c87L, 0x58684c11L, 0xc1611dabL, 0xb6662d3dL, 0x76dc4190L, + 0x1db7106L, 0x98d220bcL, 0xefd5102aL, 0x71b18589L, 0x6b6b51fL, + 0x9fbfe4a5L, 0xe8b8d433L, 0x7807c9a2L, 0xf00f934L, 0x9609a88eL, + 0xe10e9818L, 0x7f6a0dbbL, 0x86d3d2dL, 0x91646c97L, 0xe6635c01L, + 0x6b6b51f4L, 0x1c6c6162L, 0x856530d8L, 0xf262004eL, 0x6c0695edL, + 0x1b01a57bL, 0x8208f4c1L, 0xf50fc457L, 0x65b0d9c6L, 0x12b7e950L, + 0x8bbeb8eaL, 0xfcb9887cL, 0x62dd1ddfL, 0x15da2d49L, 0x8cd37cf3L, + 0xfbd44c65L, 0x4db26158L, 0x3ab551ceL, 0xa3bc0074L, 0xd4bb30e2L, + 0x4adfa541L, 0x3dd895d7L, 0xa4d1c46dL, 0xd3d6f4fbL, 0x4369e96aL, + 0x346ed9fcL, 0xad678846L, 0xda60b8d0L, 0x44042d73L, 0x33031de5L, + 0xaa0a4c5fL, 0xdd0d7cc9L, 0x5005713cL, 0x270241aaL, 0xbe0b1010L, + 0xc90c2086L, 0x5768b525L, 0x206f85b3L, 0xb966d409L, 0xce61e49fL, + 0x5edef90eL, 0x29d9c998L, 0xb0d09822L, 0xc7d7a8b4L, 0x59b33d17L, + 0x2eb40d81L, 0xb7bd5c3bL, 0xc0ba6cadL, 0xedb88320L, 0x9abfb3b6L, + 0x3b6e20cL, 0x74b1d29aL, 0xead54739L, 0x9dd277afL, 0x4db2615L, + 0x73dc1683L, 0xe3630b12L, 0x94643b84L, 0xd6d6a3eL, 0x7a6a5aa8L, + 0xe40ecf0bL, 0x9309ff9dL, 0xa00ae27L, 0x7d079eb1L, 0xf00f9344L, + 0x8708a3d2L, 0x1e01f268L, 0x6906c2feL, 0xf762575dL, 0x806567cbL, + 0x196c3671L, 0x6e6b06e7L, 0xfed41b76L, 0x89d32be0L, 0x10da7a5aL, + 0x67dd4accL, 0xf9b9df6fL, 0x8ebeeff9L, 0x17b7be43L, 0x60b08ed5L, + 0xd6d6a3e8L, 0xa1d1937eL, 0x38d8c2c4L, 0x4fdff252L, 0xd1bb67f1L, + 0xa6bc5767L, 0x3fb506ddL, 0x48b2364bL, 0xd80d2bdaL, 0xaf0a1b4cL, + 0x36034af6L, 0x41047a60L, 0xdf60efc3L, 0xa867df55L, 0x316e8eefL, + 0x4669be79L, 0xcb61b38cL, 0xbc66831aL, 0x256fd2a0L, 0x5268e236L, + 0xcc0c7795L, 0xbb0b4703L, 0x220216b9L, 0x5505262fL, 0xc5ba3bbeL, + 0xb2bd0b28L, 0x2bb45a92L, 0x5cb36a04L, 0xc2d7ffa7L, 0xb5d0cf31L, + 0x2cd99e8bL, 0x5bdeae1dL, 0x9b64c2b0L, 0xec63f226L, 0x756aa39cL, + 0x26d930aL, 0x9c0906a9L, 0xeb0e363fL, 0x72076785L, 0x5005713L, + 0x95bf4a82L, 0xe2b87a14L, 0x7bb12baeL, 0xcb61b38L, 0x92d28e9bL, + 0xe5d5be0dL, 0x7cdcefb7L, 0xbdbdf21L, 0x86d3d2d4L, 0xf1d4e242L, + 0x68ddb3f8L, 0x1fda836eL, 0x81be16cdL, 0xf6b9265bL, 0x6fb077e1L, + 0x18b74777L, 0x88085ae6L, 0xff0f6a70L, 0x66063bcaL, 0x11010b5cL, + 0x8f659effL, 0xf862ae69L, 0x616bffd3L, 0x166ccf45L, 0xa00ae278L, + 0xd70dd2eeL, 0x4e048354L, 0x3903b3c2L, 0xa7672661L, 0xd06016f7L, + 0x4969474dL, 0x3e6e77dbL, 0xaed16a4aL, 0xd9d65adcL, 0x40df0b66L, + 0x37d83bf0L, 0xa9bcae53L, 0xdebb9ec5L, 0x47b2cf7fL, 0x30b5ffe9L, + 0xbdbdf21cL, 0xcabac28aL, 0x53b39330L, 0x24b4a3a6L, 0xbad03605L, + 0xcdd70693L, 0x54de5729L, 0x23d967bfL, 0xb3667a2eL, 0xc4614ab8L, + 0x5d681b02L, 0x2a6f2b94L, 0xb40bbe37L, 0xc30c8ea1L, 0x5a05df1bL, + 0x2d02ef8dL, +}; + +typedef Histogram::Count Count; + +// static +const size_t Histogram::kBucketCount_MAX = 16384u; + +Histogram* Histogram::FactoryGet(Sample minimum, Sample maximum, + size_t bucket_count, Flags flags, + const int* buckets) { + DCHECK(buckets); + Histogram* histogram(NULL); + + // Defensive code. + if (minimum < 1) minimum = 1; + if (maximum > kSampleType_MAX - 1) maximum = kSampleType_MAX - 1; + + histogram = new Histogram(minimum, maximum, bucket_count); + histogram->InitializeBucketRangeFromData(buckets); + histogram->SetFlags(flags); + + DCHECK_EQ(HISTOGRAM, histogram->histogram_type()); + DCHECK(histogram->HasConstructorArguments(minimum, maximum, bucket_count)); + return histogram; +} + +void Histogram::Add(int value) { + if (value > kSampleType_MAX - 1) value = kSampleType_MAX - 1; + if (value < 0) value = 0; + size_t index = BucketIndex(value); + DCHECK_GE(value, ranges(index)); + DCHECK_LT(value, ranges(index + 1)); + Accumulate(value, 1, index); +} + +void Histogram::Subtract(int value) { + if (value > kSampleType_MAX - 1) value = kSampleType_MAX - 1; + if (value < 0) value = 0; + size_t index = BucketIndex(value); + DCHECK_GE(value, ranges(index)); + DCHECK_LT(value, ranges(index + 1)); + Accumulate(value, -1, index); +} + +void Histogram::AddBoolean(bool value) { DCHECK(false); } + +void Histogram::AddSampleSet(const SampleSet& sample) { sample_.Add(sample); } + +void Histogram::Clear() { sample_.Clear(); } + +void Histogram::SetRangeDescriptions(const DescriptionPair descriptions[]) { + DCHECK(false); +} + +//------------------------------------------------------------------------------ +// Methods for the validating a sample and a related histogram. +//------------------------------------------------------------------------------ + +Histogram::Inconsistencies Histogram::FindCorruption( + const SampleSet& snapshot) const { + int inconsistencies = NO_INCONSISTENCIES; + Sample previous_range = -1; // Bottom range is always 0. + int64_t count = 0; + for (size_t index = 0; index < bucket_count(); ++index) { + count += snapshot.counts(index); + int new_range = ranges(index); + if (previous_range >= new_range) inconsistencies |= BUCKET_ORDER_ERROR; + previous_range = new_range; + } + + if (!HasValidRangeChecksum()) inconsistencies |= RANGE_CHECKSUM_ERROR; + + int64_t delta64 = snapshot.redundant_count() - count; + if (delta64 != 0) { + int delta = static_cast<int>(delta64); + if (delta != delta64) delta = INT_MAX; // Flag all giant errors as INT_MAX. + // Since snapshots of histograms are taken asynchronously relative to + // sampling (and snapped from different threads), it is pretty likely that + // we'll catch a redundant count that doesn't match the sample count. We + // allow for a certain amount of slop before flagging this as an + // inconsistency. Even with an inconsistency, we'll snapshot it again (for + // UMA in about a half hour, so we'll eventually get the data, if it was + // not the result of a corruption. If histograms show that 1 is "too tight" + // then we may try to use 2 or 3 for this slop value. + const int kCommonRaceBasedCountMismatch = 1; + if (delta > 0) { + if (delta > kCommonRaceBasedCountMismatch) + inconsistencies |= COUNT_HIGH_ERROR; + } else { + DCHECK_GT(0, delta); + if (-delta > kCommonRaceBasedCountMismatch) + inconsistencies |= COUNT_LOW_ERROR; + } + } + return static_cast<Inconsistencies>(inconsistencies); +} + +Histogram::ClassType Histogram::histogram_type() const { return HISTOGRAM; } + +Histogram::Sample Histogram::ranges(size_t i) const { return ranges_[i]; } + +size_t Histogram::bucket_count() const { return bucket_count_; } + +Histogram::SampleSet Histogram::SnapshotSample() const { + return sample_.Clone(); +} + +bool Histogram::HasConstructorArguments(Sample minimum, Sample maximum, + size_t bucket_count) { + return ((minimum == declared_min_) && (maximum == declared_max_) && + (bucket_count == bucket_count_)); +} + +bool Histogram::HasConstructorTimeDeltaArguments(TimeDelta minimum, + TimeDelta maximum, + size_t bucket_count) { + return ((minimum.InMilliseconds() == declared_min_) && + (maximum.InMilliseconds() == declared_max_) && + (bucket_count == bucket_count_)); +} + +bool Histogram::HasValidRangeChecksum() const { + return CalculateRangeChecksum() == range_checksum_; +} + +size_t Histogram::SizeOfIncludingThis(mozilla::MallocSizeOf aMallocSizeOf) { + size_t n = 0; + n += aMallocSizeOf(this); + n += sample_.SizeOfExcludingThis(aMallocSizeOf); + return n; +} + +size_t Histogram::SampleSet::SizeOfExcludingThis( + mozilla::MallocSizeOf aMallocSizeOf) { + return counts_.ShallowSizeOfExcludingThis(aMallocSizeOf); +} + +Histogram::Histogram(Sample minimum, Sample maximum, size_t bucket_count) + : sample_(), + declared_min_(minimum), + declared_max_(maximum), + bucket_count_(bucket_count), + flags_(kNoFlags), + range_checksum_(0) { + Initialize(); +} + +Histogram::Histogram(TimeDelta minimum, TimeDelta maximum, size_t bucket_count) + : sample_(), + declared_min_(static_cast<int>(minimum.InMilliseconds())), + declared_max_(static_cast<int>(maximum.InMilliseconds())), + bucket_count_(bucket_count), + flags_(kNoFlags), + range_checksum_(0) { + Initialize(); +} + +Histogram::~Histogram() { + // Just to make sure most derived class did this properly... + DCHECK(ValidateBucketRanges()); +} + +void Histogram::InitializeBucketRangeFromData(const int* buckets) { + ranges_ = buckets; + ResetRangeChecksum(); + DCHECK(ValidateBucketRanges()); +} + +bool Histogram::PrintEmptyBucket(size_t index) const { return true; } + +size_t Histogram::BucketIndex(Sample value) const { + // Use simple binary search. This is very general, but there are better + // approaches if we knew that the buckets were linearly distributed. + DCHECK_LE(ranges(0), value); + DCHECK_GT(ranges(bucket_count()), value); + size_t under = 0; + size_t over = bucket_count(); + size_t mid; + + do { + DCHECK_GE(over, under); + mid = under + (over - under) / 2; + if (mid == under) break; + if (ranges(mid) <= value) + under = mid; + else + over = mid; + } while (true); + + DCHECK_LE(ranges(mid), value); + CHECK_GT(ranges(mid + 1), value); + return mid; +} + +// Use the actual bucket widths (like a linear histogram) until the widths get +// over some transition value, and then use that transition width. Exponentials +// get so big so fast (and we don't expect to see a lot of entries in the large +// buckets), so we need this to make it possible to see what is going on and +// not have 0-graphical-height buckets. +double Histogram::GetBucketSize(Count current, size_t i) const { + DCHECK_GT(ranges(i + 1), ranges(i)); + static const double kTransitionWidth = 5; + double denominator = ranges(i + 1) - ranges(i); + if (denominator > kTransitionWidth) + denominator = kTransitionWidth; // Stop trying to normalize. + return current / denominator; +} + +void Histogram::ResetRangeChecksum() { + range_checksum_ = CalculateRangeChecksum(); +} + +const std::string Histogram::GetAsciiBucketRange(size_t i) const { + std::string result; + if (kHexRangePrintingFlag & flags_) + StringAppendF(&result, "%#x", ranges(i)); + else + StringAppendF(&result, "%d", ranges(i)); + return result; +} + +// Update histogram data with new sample. +void Histogram::Accumulate(Sample value, Count count, size_t index) { + sample_.Accumulate(value, count, index); +} + +bool Histogram::ValidateBucketRanges() const { + // Standard assertions that all bucket ranges should satisfy. + DCHECK_EQ(0, ranges_[bucket_count_ + 1]); + DCHECK_EQ(0, ranges_[0]); + DCHECK_EQ(declared_min(), ranges_[1]); + DCHECK_EQ(declared_max(), ranges_[bucket_count_ - 1]); + DCHECK_EQ(kSampleType_MAX, ranges_[bucket_count_]); + return true; +} + +uint32_t Histogram::CalculateRangeChecksum() const { + DCHECK_EQ(0, ranges_[bucket_count_ + 1]); + uint32_t checksum = + static_cast<uint32_t>(bucket_count_ + 1); // Seed checksum. + for (size_t index = 0; index < bucket_count(); ++index) + checksum = Crc32(checksum, ranges(index)); + return checksum; +} + +void Histogram::Initialize() { + sample_.Resize(*this); + if (declared_min_ < 1) declared_min_ = 1; + if (declared_max_ > kSampleType_MAX - 1) declared_max_ = kSampleType_MAX - 1; + DCHECK_LE(declared_min_, declared_max_); + DCHECK_GT(bucket_count_, 1u); + CHECK_LT(bucket_count_, kBucketCount_MAX); + size_t maximal_bucket_count = declared_max_ - declared_min_ + 2; + DCHECK_LE(bucket_count_, maximal_bucket_count); +} + +// We generate the CRC-32 using the low order bits to select whether to XOR in +// the reversed polynomial 0xedb88320L. This is nice and simple, and allows us +// to keep the quotient in a uint32_t. Since we're not concerned about the +// nature of corruptions (i.e., we don't care about bit sequencing, since we are +// handling memory changes, which are more grotesque) so we don't bother to +// get the CRC correct for big-endian vs little-ending calculations. All we +// need is a nice hash, that tends to depend on all the bits of the sample, with +// very little chance of changes in one place impacting changes in another +// place. +uint32_t Histogram::Crc32(uint32_t sum, Histogram::Sample range) { + const bool kUseRealCrc = true; // TODO(jar): Switch to false and watch stats. + if (kUseRealCrc) { + union { + Histogram::Sample range; + unsigned char bytes[sizeof(Histogram::Sample)]; + } converter; + converter.range = range; + for (size_t i = 0; i < sizeof(converter); ++i) + sum = kCrcTable[(sum & 0xff) ^ converter.bytes[i]] ^ (sum >> 8); + } else { + // Use hash techniques provided in ReallyFastHash, except we don't care + // about "avalanching" (which would worsten the hash, and add collisions), + // and we don't care about edge cases since we have an even number of bytes. + union { + Histogram::Sample range; + uint16_t ints[sizeof(Histogram::Sample) / 2]; + } converter; + DCHECK_EQ(sizeof(Histogram::Sample), sizeof(converter)); + converter.range = range; + sum += converter.ints[0]; + sum = (sum << 16) ^ sum ^ (static_cast<uint32_t>(converter.ints[1]) << 11); + sum += sum >> 11; + } + return sum; +} + +//------------------------------------------------------------------------------ +// Private methods + +double Histogram::GetPeakBucketSize(const SampleSet& snapshot) const { + double max = 0; + for (size_t i = 0; i < bucket_count(); ++i) { + double current_size = GetBucketSize(snapshot.counts(i), i); + if (current_size > max) max = current_size; + } + return max; +} + +//------------------------------------------------------------------------------ +// Methods for the Histogram::SampleSet class +//------------------------------------------------------------------------------ + +Histogram::SampleSet::SampleSet() : counts_(), sum_(0), redundant_count_(0) {} + +Histogram::SampleSet::~SampleSet() {} + +void Histogram::SampleSet::Resize(const Histogram& histogram) { + size_t oldSize = counts_.Length(); + counts_.SetLength(histogram.bucket_count()); + + for (size_t i = oldSize; i < histogram.bucket_count(); ++i) counts_[i] = 0; +} + +void Histogram::SampleSet::Accumulate(Sample value, Count count, size_t index) { + DCHECK(count == 1 || count == -1); + counts_[index] += count; + redundant_count_ += count; + sum_ += static_cast<int64_t>(count) * value; + DCHECK_GE(counts_[index], 0); + DCHECK_GE(sum_, 0); + DCHECK_GE(redundant_count_, 0); +} + +Count Histogram::SampleSet::TotalCount() const { + Count total = 0; + for (Counts::const_iterator it = counts_.begin(); it != counts_.end(); ++it) { + total += *it; + } + return total; +} + +void Histogram::SampleSet::Add(const SampleSet& other) { + DCHECK_EQ(counts_.Length(), other.counts_.Length()); + sum_ += other.sum_; + redundant_count_ += other.redundant_count_; + for (size_t index = 0; index < counts_.Length(); ++index) + counts_[index] += other.counts_[index]; +} + +//------------------------------------------------------------------------------ +// LinearHistogram: This histogram uses a traditional set of evenly spaced +// buckets. +//------------------------------------------------------------------------------ + +LinearHistogram::~LinearHistogram() {} + +Histogram* LinearHistogram::FactoryGet(Sample minimum, Sample maximum, + size_t bucket_count, Flags flags, + const int* buckets) { + Histogram* histogram(NULL); + + if (minimum < 1) minimum = 1; + if (maximum > kSampleType_MAX - 1) maximum = kSampleType_MAX - 1; + + LinearHistogram* linear_histogram = + new LinearHistogram(minimum, maximum, bucket_count); + linear_histogram->InitializeBucketRangeFromData(buckets); + linear_histogram->SetFlags(flags); + histogram = linear_histogram; + + DCHECK_EQ(LINEAR_HISTOGRAM, histogram->histogram_type()); + DCHECK(histogram->HasConstructorArguments(minimum, maximum, bucket_count)); + return histogram; +} + +Histogram::ClassType LinearHistogram::histogram_type() const { + return LINEAR_HISTOGRAM; +} + +void LinearHistogram::Accumulate(Sample value, Count count, size_t index) { + sample_.Accumulate(value, count, index); +} + +void LinearHistogram::SetRangeDescriptions( + const DescriptionPair descriptions[]) { + for (int i = 0; descriptions[i].description; ++i) { + bucket_description_[descriptions[i].sample] = descriptions[i].description; + } +} + +LinearHistogram::LinearHistogram(Sample minimum, Sample maximum, + size_t bucket_count) + : Histogram(minimum >= 1 ? minimum : 1, maximum, bucket_count) {} + +LinearHistogram::LinearHistogram(TimeDelta minimum, TimeDelta maximum, + size_t bucket_count) + : Histogram(minimum >= TimeDelta::FromMilliseconds(1) + ? minimum + : TimeDelta::FromMilliseconds(1), + maximum, bucket_count) {} + +double LinearHistogram::GetBucketSize(Count current, size_t i) const { + DCHECK_GT(ranges(i + 1), ranges(i)); + // Adjacent buckets with different widths would have "surprisingly" many (few) + // samples in a histogram if we didn't normalize this way. + double denominator = ranges(i + 1) - ranges(i); + return current / denominator; +} + +const std::string LinearHistogram::GetAsciiBucketRange(size_t i) const { + int range = ranges(i); + BucketDescriptionMap::const_iterator it = bucket_description_.find(range); + if (it == bucket_description_.end()) return Histogram::GetAsciiBucketRange(i); + return it->second; +} + +bool LinearHistogram::PrintEmptyBucket(size_t index) const { + return bucket_description_.find(ranges(index)) == bucket_description_.end(); +} + +//------------------------------------------------------------------------------ +// This section provides implementation for BooleanHistogram. +//------------------------------------------------------------------------------ + +Histogram* BooleanHistogram::FactoryGet(Flags flags, const int* buckets) { + Histogram* histogram(NULL); + + BooleanHistogram* tentative_histogram = new BooleanHistogram(); + tentative_histogram->InitializeBucketRangeFromData(buckets); + tentative_histogram->SetFlags(flags); + histogram = tentative_histogram; + + DCHECK_EQ(BOOLEAN_HISTOGRAM, histogram->histogram_type()); + return histogram; +} + +Histogram::ClassType BooleanHistogram::histogram_type() const { + return BOOLEAN_HISTOGRAM; +} + +void BooleanHistogram::AddBoolean(bool value) { Add(value ? 1 : 0); } + +BooleanHistogram::BooleanHistogram() : LinearHistogram(1, 2, 3) {} + +void BooleanHistogram::Accumulate(Sample value, Count count, size_t index) { + // Callers will have computed index based on the non-booleanified value. + // So we need to adjust the index manually. + LinearHistogram::Accumulate(!!value, count, value ? 1 : 0); +} + +//------------------------------------------------------------------------------ +// FlagHistogram: +//------------------------------------------------------------------------------ + +Histogram* FlagHistogram::FactoryGet(Flags flags, const int* buckets) { + Histogram* h(nullptr); + + FlagHistogram* fh = new FlagHistogram(); + fh->InitializeBucketRangeFromData(buckets); + fh->SetFlags(flags); + size_t zero_index = fh->BucketIndex(0); + fh->LinearHistogram::Accumulate(0, 1, zero_index); + h = fh; + + return h; +} + +FlagHistogram::FlagHistogram() : BooleanHistogram(), mSwitched(false) {} + +Histogram::ClassType FlagHistogram::histogram_type() const { + return FLAG_HISTOGRAM; +} + +void FlagHistogram::Accumulate(Sample value, Count count, size_t index) { + if (mSwitched) { + return; + } + + mSwitched = true; + DCHECK_EQ(value, 1); + LinearHistogram::Accumulate(value, 1, index); + size_t zero_index = BucketIndex(0); + LinearHistogram::Accumulate(0, -1, zero_index); +} + +void FlagHistogram::AddSampleSet(const SampleSet& sample) { + DCHECK_EQ(bucket_count(), sample.size()); + // We can't be sure the SampleSet provided came from another FlagHistogram, + // so we take the following steps: + // - If our flag has already been set do nothing. + // - Set our flag if the following hold: + // - The sum of the counts in the provided SampleSet is 1. + // - The bucket index for that single value is the same as the index + // where we + // would place our set flag. + // - Otherwise, take no action. + + if (mSwitched) { + return; + } + + if (sample.sum() != 1) { + return; + } + + size_t one_index = BucketIndex(1); + if (sample.counts(one_index) == 1) { + Accumulate(1, 1, one_index); + } +} + +void FlagHistogram::Clear() { + Histogram::Clear(); + + mSwitched = false; + size_t zero_index = BucketIndex(0); + LinearHistogram::Accumulate(0, 1, zero_index); +} + +//------------------------------------------------------------------------------ +// CountHistogram: +//------------------------------------------------------------------------------ + +Histogram* CountHistogram::FactoryGet(Flags flags, const int* buckets) { + Histogram* h(nullptr); + + CountHistogram* fh = new CountHistogram(); + fh->InitializeBucketRangeFromData(buckets); + fh->SetFlags(flags); + h = fh; + + return h; +} + +CountHistogram::CountHistogram() : LinearHistogram(1, 2, 3) {} + +Histogram::ClassType CountHistogram::histogram_type() const { + return COUNT_HISTOGRAM; +} + +void CountHistogram::Accumulate(Sample value, Count count, size_t index) { + size_t zero_index = BucketIndex(0); + LinearHistogram::Accumulate(value, 1, zero_index); +} + +void CountHistogram::AddSampleSet(const SampleSet& sample) { + DCHECK_EQ(bucket_count(), sample.size()); + // We can't be sure the SampleSet provided came from another CountHistogram, + // so we at least check that the unused buckets are empty. + + const size_t indices[] = {BucketIndex(0), BucketIndex(1), BucketIndex(2)}; + + if (sample.counts(indices[1]) != 0 || sample.counts(indices[2]) != 0) { + return; + } + + if (sample.counts(indices[0]) != 0) { + Histogram::AddSampleSet(sample); + } +} + +} // namespace base |