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#pragma once
#include "adaptive_histogram.h"
#include "fixed_bin_histogram.h"
#include "histogram.h"
#include <library/cpp/histogram/adaptive/protos/histo.pb.h>
#include <util/generic/ptr.h>
#include <util/generic/yexception.h>
namespace NKiwiAggr {
class TAutoHistogram: private TNonCopyable, public IHistogram {
private:
static const size_t DEFAULT_INTERVALS = 100;
ui64 Id;
size_t Intervals;
THolder<IHistogram> HistogramImpl;
public:
TAutoHistogram(size_t intervals, ui64 id = 0) {
Y_UNUSED(intervals);
Y_UNUSED(id);
ythrow yexception() << "Empty constructor is not defined for TAutoHistogram";
}
TAutoHistogram(const THistogram& histo, size_t defaultIntervals = DEFAULT_INTERVALS, ui64 defaultId = 0)
: Id(defaultId)
, Intervals(defaultIntervals)
{
FromProto(histo);
}
TAutoHistogram(IHistogram* histo, size_t defaultIntervals = DEFAULT_INTERVALS, ui64 defaultId = 0) {
Y_UNUSED(histo);
Y_UNUSED(defaultIntervals);
Y_UNUSED(defaultId);
ythrow yexception() << "IHistogram constructor is not defined for TAutoHistogram";
}
virtual ~TAutoHistogram() {
}
virtual void Clear() {
HistogramImpl->Clear();
}
virtual void Add(double value, double weight) {
HistogramImpl->Add(value, weight);
}
virtual void Add(const THistoRec& histoRec) {
HistogramImpl->Add(histoRec);
}
virtual void Merge(const THistogram& histo, double multiplier) {
HistogramImpl->Merge(histo, multiplier);
}
virtual void Merge(const TVector<THistogram>& histogramsToMerge) {
HistogramImpl->Merge(histogramsToMerge);
}
virtual void Merge(TVector<IHistogramPtr> histogramsToMerge) {
HistogramImpl->Merge(histogramsToMerge);
}
virtual void Multiply(double factor) {
HistogramImpl->Multiply(factor);
}
virtual void FromProto(const THistogram& histo) {
if (!histo.HasType() || histo.GetType() == HT_FIXED_BIN_HISTOGRAM) {
HistogramImpl.Reset(new TFixedBinHistogram(histo, Intervals, Id));
} else if (histo.GetType() == HT_ADAPTIVE_DISTANCE_HISTOGRAM) {
HistogramImpl.Reset(new TAdaptiveDistanceHistogram(histo, Intervals, Id));
} else if (histo.GetType() == HT_ADAPTIVE_WEIGHT_HISTOGRAM) {
HistogramImpl.Reset(new TAdaptiveWeightHistogram(histo, Intervals, Id));
} else if (histo.GetType() == HT_ADAPTIVE_WARD_HISTOGRAM) {
HistogramImpl.Reset(new TAdaptiveWardHistogram(histo, Intervals, Id));
} else {
ythrow yexception() << "Can't parse TAutoHistogram from a THistogram of type " << (ui32)histo.GetType();
}
}
virtual void ToProto(THistogram& histo) {
HistogramImpl->ToProto(histo);
}
virtual void SetId(ui64 id) {
HistogramImpl->SetId(id);
}
virtual ui64 GetId() {
return HistogramImpl->GetId();
}
virtual bool Empty() {
return HistogramImpl->Empty();
}
virtual double GetMinValue() {
return HistogramImpl->GetMinValue();
}
virtual double GetMaxValue() {
return HistogramImpl->GetMaxValue();
}
virtual double GetSum() {
return HistogramImpl->GetSum();
}
virtual double GetSumInRange(double leftBound, double rightBound) {
return HistogramImpl->GetSumInRange(leftBound, rightBound);
}
virtual double GetSumAboveBound(double bound) {
return HistogramImpl->GetSumAboveBound(bound);
}
virtual double GetSumBelowBound(double bound) {
return HistogramImpl->GetSumBelowBound(bound);
}
virtual double CalcUpperBound(double sum) {
return HistogramImpl->CalcUpperBound(sum);
}
virtual double CalcLowerBound(double sum) {
return HistogramImpl->CalcLowerBound(sum);
}
virtual double CalcUpperBoundSafe(double sum) {
return HistogramImpl->CalcUpperBoundSafe(sum);
}
virtual double CalcLowerBoundSafe(double sum) {
return HistogramImpl->CalcLowerBoundSafe(sum);
}
virtual void PrecomputePartialSums() {
return HistogramImpl->PrecomputePartialSums();
}
};
}
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