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// Copyright 2009-2020 Intel Corporation
// SPDX-License-Identifier: Apache-2.0
#pragma once
#include "../default.h"
#include <algorithm>
namespace embree
{
/* calculates min/avg/max and sigma */
struct Statistics
{
public:
Statistics()
: v(0.0f), v2(0.0f), vmin(pos_inf), vmax(neg_inf), N(0) {}
void add(float a)
{
v += a;
v2 += a*a;
vmin = min(vmin,a);
vmax = max(vmax,a);
N++;
}
float getSigma() const
{
if (N == 0) return 0.0f;
else return (float) sqrt(max(0.0,v2/N - sqr(v/N)));
}
float getAvgSigma() const // standard deviation of average
{
if (N == 0) return 0.0f;
else return getSigma()/sqrt(float(N));
}
float getMin() const { return vmin; }
float getMax() const { return vmax; }
float getAvg() const { return float(v/N); }
private:
double v; // sum of all values
double v2; // sum of squares of all values
float vmin; // min of all values
float vmax; // max of all values
size_t N; // number of values
};
/* filters outlyers out */
struct FilteredStatistics
{
public:
FilteredStatistics(float fskip_small, float fskip_large)
: fskip_small(fskip_small), fskip_large(fskip_large) {}
void add(float a)
{
v.push_back(a);
std::sort(v.begin(),v.end(),std::less<float>());
size_t skip_small = (size_t) floor(0.5*fskip_small*double(v.size()));
size_t skip_large = (size_t) floor(0.5*fskip_large*double(v.size()));
stat = Statistics();
for (size_t i=skip_small; i<v.size()-skip_large; i++)
stat.add(v[i]);
}
float getSigma() const { return stat.getSigma(); }
float getAvgSigma() const { return stat.getAvgSigma(); }
float getMin() const { return stat.getMin(); }
float getMax() const { return stat.getMax(); }
float getAvg() const { return stat.getAvg(); }
Statistics getStatistics() const { return stat; }
private:
float fskip_small; // fraction of small outlyers to filter out
float fskip_large; // fraction of large outlyers to filter out
std::vector<float> v;
Statistics stat;
};
}
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