boost/histogram/utility/binomial_proportion_interval.hpp
// Copyright 2022 Jay Gohil, Hans Dembinski
//
// Distributed under the Boost Software License, version 1.0.
// (See accompanying file LICENSE_1_0.txt
// or copy at http://www.boost.org/LICENSE_1_0.txt)
#ifndef BOOST_HISTOGRAM_UTILITY_BINOMIAL_PROPORTION_INTERVAL_HPP
#define BOOST_HISTOGRAM_UTILITY_BINOMIAL_PROPORTION_INTERVAL_HPP
#include <boost/histogram/detail/normal.hpp>
#include <boost/histogram/fwd.hpp>
#include <boost/throw_exception.hpp>
#include <cmath>
#include <stdexcept>
#include <type_traits>
namespace boost {
namespace histogram {
namespace utility {
/**
Common base class for interval calculators.
*/
template <class ValueType>
class binomial_proportion_interval {
static_assert(std::is_floating_point<ValueType>::value,
"Value must be a floating point!");
public:
using value_type = ValueType;
using interval_type = std::pair<value_type, value_type>;
/** Compute interval for given number of successes and failures.
@param successes Number of successful trials.
@param failures Number of failed trials.
*/
virtual interval_type operator()(value_type successes,
value_type failures) const noexcept = 0;
/** Compute interval for a fraction accumulator.
@param fraction Fraction accumulator.
*/
template <class T>
interval_type operator()(const accumulators::fraction<T>& fraction) const noexcept {
return operator()(fraction.successes(), fraction.failures());
}
};
class deviation;
class confidence_level;
/** Confidence level in units of deviations for intervals.
Intervals become wider as the deviation value increases. The standard deviation
corresponds to a value of 1 and corresponds to 68.3 % confidence level. The conversion
between confidence level and deviations is based on a two-sided interval on the normal
distribution.
*/
class deviation {
public:
/// constructor from units of standard deviations
explicit deviation(double d) : d_{d} {
if (d <= 0)
BOOST_THROW_EXCEPTION(std::invalid_argument("scaling factor must be positive"));
}
/// explicit conversion to units of standard deviations
template <class T, class = std::enable_if_t<std::is_floating_point<T>::value>>
explicit operator T() const noexcept {
return static_cast<T>(d_);
}
/// implicit conversion to confidence level
operator confidence_level() const noexcept; // need to implement confidence_level first
friend deviation operator*(deviation d, double z) noexcept {
return deviation(d.d_ * z);
}
friend deviation operator*(double z, deviation d) noexcept { return d * z; }
friend bool operator==(deviation a, deviation b) noexcept { return a.d_ == b.d_; }
friend bool operator!=(deviation a, deviation b) noexcept { return !(a == b); }
private:
double d_;
};
/** Confidence level for intervals.
Intervals become wider as the deviation value increases.
*/
class confidence_level {
public:
/// constructor from confidence level (a probability)
explicit confidence_level(double cl) : cl_{cl} {
if (cl <= 0 || cl >= 1)
BOOST_THROW_EXCEPTION(std::invalid_argument("0 < cl < 1 is required"));
}
/// explicit conversion to numerical confidence level
template <class T, class = std::enable_if_t<std::is_floating_point<T>::value>>
explicit operator T() const noexcept {
return static_cast<T>(cl_);
}
/// implicit conversion to units of standard deviation
operator deviation() const noexcept {
return deviation{detail::normal_ppf(std::fma(0.5, cl_, 0.5))};
}
friend bool operator==(confidence_level a, confidence_level b) noexcept {
return a.cl_ == b.cl_;
}
friend bool operator!=(confidence_level a, confidence_level b) noexcept {
return !(a == b);
}
private:
double cl_;
};
inline deviation::operator confidence_level() const noexcept {
// solve normal cdf(z) - cdf(-z) = 2 (cdf(z) - 0.5)
return confidence_level{std::fma(2.0, detail::normal_cdf(d_), -1.0)};
}
} // namespace utility
} // namespace histogram
} // namespace boost
#endif