showDecimal -> decimal10 (maximal precision to survive round-trip through decimal representation= showComplete -> max_decimal10 (enough decimal places to capture each possible distinct floating-point value) Use these new functions to rewrite the format4csv() helper
180 lines
7 KiB
C++
180 lines
7 KiB
C++
/*
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RATIONAL.hpp - support for precise rational arithmetics
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Copyright (C) Lumiera.org
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2022, Hermann Vosseler <Ichthyostega@web.de>
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This program is free software; you can redistribute it and/or
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modify it under the terms of the GNU General Public License as
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published by the Free Software Foundation; either version 2 of
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the License, or (at your option) any later version.
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This program is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public License
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along with this program; if not, write to the Free Software
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Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
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*/
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/** @file rational.hpp
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** Rational number support, based on `boost::rational`.
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** As an extension to integral arithmetics, rational numbers can be defined
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** as a pair (numerator, denominator); since most calculations imply multiplication
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** by common factors, each calculation will be followed by normalisation to greatest
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** common denominator, to keep numbers within value range. Obviously, this incurs
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** a significant performance penalty — while on the other hand allowing for lossless
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** computations on fractional scales, which can be notoriously difficult to handle
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** with floating point numbers. The primary motivation for using this number format
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** is for handling fractional time values properly, e.g 1/30 sec or 1/44100 sec.
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**
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** The underlying implementation from boost::rational can be parametrised with various
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** integral data types; since our time handling is based on 64bit integers, we mainly
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** use the specialisation `boost::rational<int64_t>`.
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**
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** @note all compatible integral types can be automatically converted to rational
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** numbers, which is a lossless conversion. The opposite is not true: to get
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** a "ordinary" number — be it integral or floating point — an explicit
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** conversion using `rational_cast<NUM> (fraction)` is necessary, which
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** performs the division of `numerator/denominator` in the target value domain.
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**
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** # Perils of fractional arithmetics
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**
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** While the always precise results of integral numbers might seem compelling, the
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** danger of _numeric overflow_ is significantly increased by fractional computations.
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** Most notably, this danger is *not limited to large numbers*. Adding two fractional
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** number requires multiplications with both denominators, which can overflow easily.
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** Thus, for every given fractional number, there is a class of »dangerous counterparts«
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** which can not be added without derailing the computation, leading to arbitrary wrong
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** results without detectable failure. And these problematic counterparts are distributed
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** _over the whole valid numeric range._ To give an extreme example, any numbers of the
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** form `n / INT_MAX` can not be added or subtracted with any other rational number > 1,
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** while being themselves perfectly valid and representable.
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** \par rule of thumb
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** Use fractional arithmetics only where it is possible to control the denominators involved.
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** Never use them for computations drawing from arbitrary (external) input.
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**
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** @see Rational_test
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** @see zoom-window.hpp
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** @see timevalue.hpp
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*/
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#ifndef LIB_RATIONAL_H
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#define LIB_RATIONAL_H
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#include "lib/integral.hpp"
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#include "lib/util-quant.hpp"
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#include <cmath>
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#include <limits>
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#include <stdint.h>
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#include <boost/rational.hpp>
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namespace util {
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using Rat = boost::rational<int64_t>;
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using boost::rational_cast;
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using std::abs;
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inline bool
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can_represent_Product (int64_t a, int64_t b)
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{
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return ilog2(abs(a))+1
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+ ilog2(abs(b))+1
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< 63;
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}
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inline bool
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can_represent_Product (Rat a, Rat b)
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{
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return can_represent_Product(a.numerator(), b.numerator())
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and can_represent_Product(a.denominator(), b.denominator());
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}
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inline bool
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can_represent_Sum (Rat a, Rat b)
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{
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return can_represent_Product(a.numerator(), b.denominator())
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and can_represent_Product(b.numerator(), a.denominator());
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}
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/**
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* Re-Quantise a number into a new grid, truncating to the next lower grid point.
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* @remark Grid-aligned values can be interpreted as rational numbers (integer fractions),
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* where the quantiser corresponds to the denominator and the numerator counts
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* the number of grid steps. To work both around precision problems and the
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* danger of integer wrap-around, the integer division is performed on the
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* old value and then the re-quantisation done on the remainder, using
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* 128bit floating point for maximum precision. This operation can
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* also be used to re-form a fraction to be cast in terms of the
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* new quantiser; this introduces a tiny error, but typically
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* allows for safe or simplified calculations.
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* @param num the count in old grid-steps (#den) or the numerator
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* @param den the old quantiser or the denominator of a fraction
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* @param u the new quantiser or the new denominator to use
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* @return the adjusted numerator, so that the fraction with u
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* will be almost the same than dividing #num by #den
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*/
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inline int64_t
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reQuant (int64_t num, int64_t den, int64_t u)
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{
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u = 0!=u? u:1;
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auto [d,r] = util::iDiv (num, den);
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// round to smallest integer fraction, to shake off "number dust"
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f128 const ROUND_ULP = 1 + 1/(f128(std::numeric_limits<int64_t>::max()) * 2);
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// construct approximation quantised to 1/u
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f128 frac = f128(r) / den;
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int64_t res = d*u + int64_t(frac*u * ROUND_ULP);
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ENSURE (abs (f128(res)/u - rational_cast<f128>(Rat{num,den})) <= 1.0/abs(u)
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,"Requantisation error exceeded num=%li / den=%li -> res=%li / quant=%li"
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, num, den, res, u);
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return res;
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}
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/**
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* re-Quantise a rational number to a (typically smaller) denominator.
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* @param u the new denominator to use
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* @warning this is a lossy operation and possibly introduces an error
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* of up to 1/u
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* @remark Rational numbers with large numerators can be »poisonous«,
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* causing numeric overflow when used, even just additively.
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* This function can thus be used to _"sanitise"_ a number,
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* and thus accept a small error while preventing overflow.
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* @note using extended-precision floating point to get close to the
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* quantiser even for large denominator. Some platforms
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* fall back to double, leading to extended error bounds
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*/
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inline Rat
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reQuant (Rat src, int64_t u)
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{
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return Rat{reQuant (src.numerator(), src.denominator(), u), u};
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}
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} // namespace util
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/**
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* user defined literal for constant rational numbers.
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* \code
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* Rat twoThirds = 2_r/3;
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* \endcode
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*/
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inline util::Rat
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operator""_r (unsigned long long num)
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{
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return util::Rat{num};
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}
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#endif /*LIB_RATIONAL_H*/
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