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Rounding means replacing a
number A number is a mathematical object used to count, measure, and label. The original examples are the natural numbers 1, 2, 3, 4, and so forth. Numbers can be represented in language with number words. More universally, individual number ...
with an approximate value that has a shorter, simpler, or more explicit representation. For example, replacing $ with $, the fraction 312/937 with 1/3, or the expression with . Rounding is often done to obtain a value that is easier to report and communicate than the original. Rounding can also be important to avoid misleadingly precise reporting of a computed number, measurement, or estimate; for example, a quantity that was computed as but is known to be accurate only to within a few hundred units is usually better stated as "about ". On the other hand, rounding of exact numbers will introduce some round-off error in the reported result. Rounding is almost unavoidable when reporting many computations – especially when dividing two numbers in
integer An integer is the number zero (), a positive natural number (, , , etc.) or a negative integer with a minus sign ( −1, −2, −3, etc.). The negative numbers are the additive inverses of the corresponding positive numbers. In the languag ...
or fixed-point arithmetic; when computing mathematical functions such as
square root In mathematics, a square root of a number is a number such that ; in other words, a number whose '' square'' (the result of multiplying the number by itself, or  ⋅ ) is . For example, 4 and −4 are square roots of 16, because . ...
s,
logarithm In mathematics, the logarithm is the inverse function to exponentiation. That means the logarithm of a number  to the base  is the exponent to which must be raised, to produce . For example, since , the ''logarithm base'' 10 ...
s, and sines; or when using a floating-point representation with a fixed number of
significant digits Significant figures (also known as the significant digits, ''precision'' or ''resolution'') of a number in positional notation are digits in the number that are reliable and necessary to indicate the quantity of something. If a number expres ...
. In a sequence of calculations, these rounding errors generally accumulate, and in certain
ill-conditioned In numerical analysis, the condition number of a function measures how much the output value of the function can change for a small change in the input argument. This is used to measure how sensitive a function is to changes or errors in the input ...
cases they may make the result meaningless. Accurate rounding of transcendental mathematical functions is difficult because the number of extra digits that need to be calculated to resolve whether to round up or down cannot be known in advance. This problem is known as " the table-maker's dilemma". Rounding has many similarities to the quantization that occurs when
physical quantities A physical quantity is a physical property of a material or system that can be quantified by measurement. A physical quantity can be expressed as a ''value'', which is the algebraic multiplication of a ' Numerical value ' and a ' Unit '. For exam ...
must be encoded by numbers or digital signals. A wavy equals sign ( : ''approximately equal to'') is sometimes used to indicate rounding of exact numbers, e.g., 9.98 ≈ 10. This sign was introduced by Alfred George Greenhill in 1892. Ideal characteristics of rounding methods include: # Rounding should be done by a function. This way, when the same input is rounded in different instances, the output is unchanged. # Calculations done with rounding should be close to those done without rounding. #* As a result of (1) and (2), the output from rounding should be close to its input, often as close as possible by some metric. # To be considered rounding, the range will be a
subset In mathematics, set ''A'' is a subset of a set ''B'' if all elements of ''A'' are also elements of ''B''; ''B'' is then a superset of ''A''. It is possible for ''A'' and ''B'' to be equal; if they are unequal, then ''A'' is a proper subset of ...
of the
domain Domain may refer to: Mathematics *Domain of a function, the set of input values for which the (total) function is defined ** Domain of definition of a partial function ** Natural domain of a partial function **Domain of holomorphy of a function * ...
, in general discrete. A classical range is the integers, Z. # Rounding should preserve symmetries that already exist between the domain and range. With finite precision (or a discrete domain), this translates to removing
bias Bias is a disproportionate weight ''in favor of'' or ''against'' an idea or thing, usually in a way that is closed-minded, prejudicial, or unfair. Biases can be innate or learned. People may develop biases for or against an individual, a group ...
. # A rounding method should have utility in computer science or human arithmetic where finite precision is used, and speed is a consideration. Because it is not usually possible for a method to satisfy all ideal characteristics, many different rounding methods exist. As a general rule, rounding is idempotent; i.e., once a number has been rounded, rounding it again will not change its value. Rounding functions are also
monotonic In mathematics, a monotonic function (or monotone function) is a function between ordered sets that preserves or reverses the given order. This concept first arose in calculus, and was later generalized to the more abstract setting of order ...
; i.e., . In the general case of a discrete range, they are
piecewise constant function In mathematics, a function on the real numbers is called a step function if it can be written as a finite linear combination of indicator functions of intervals. Informally speaking, a step function is a piecewise constant function having only ...
s.


Types of rounding

Typical rounding problems include:


Rounding to integer

The most basic form of rounding is to replace an arbitrary number by an integer. All the following rounding modes are concrete implementations of an abstract single-argument "round()" procedure. These are true functions (with the exception of those that use randomness).


Directed rounding to an integer

These four methods are called directed rounding, as the displacements from the original number to the rounded value are all directed toward or away from the same limiting value (0, +∞, or −∞). Directed rounding is used in
interval arithmetic Interval arithmetic (also known as interval mathematics, interval analysis, or interval computation) is a mathematical technique used to put bounds on rounding errors and measurement errors in mathematical computation. Numerical methods using ...
and is often required in financial calculations. If is positive, round-down is the same as round-toward-zero, and round-up is the same as round-away-from-zero. If is negative, round-down is the same as round-away-from-zero, and round-up is the same as round-toward-zero. In any case, if is an integer, is just . Where many calculations are done in sequence, the choice of rounding method can have a very significant effect on the result. A famous instance involved a new index set up by the Vancouver Stock Exchange in 1982. It was initially set at 1000.000 (three decimal places of accuracy), and after 22 months had fallen to about 520 — whereas stock prices had generally increased in the period. The problem was caused by the index being recalculated thousands of times daily, and always being rounded down to 3 decimal places, in such a way that the rounding errors accumulated. Recalculating with better rounding gave an index value of 1098.892 at the end of the same period. For the examples below, refers to the sign function applied to the original number, .


Rounding down

* round down (or take the floor, or round toward negative infinity): is the largest integer that does not exceed . *: y = \mathrm(x) = \left\lfloor x \right\rfloor = -\left\lceil -x \right\rceil For example, 23.7 gets rounded to 23, and −23.2 gets rounded to −24.


Rounding up

* round up (or take the ceiling, or round toward positive infinity): is the smallest integer that is not less than . *: y = \operatorname(x) = \left\lceil x \right\rceil = -\left\lfloor -x \right\rfloor For example, 23.2 gets rounded to 24, and −23.7 gets rounded to −23.


Rounding toward zero

* round toward zero (or truncate, or round away from infinity): is the integer that is closest to such that it is between 0 and (included); i.e. is the integer part of , without its fraction digits. *: y = \operatorname(x) = \sgn(x) \left\lfloor \left, x \ \right\rfloor = -\sgn(x) \left\lceil -\left, x \ \right\rceil = \begin \left\lfloor x \right\rfloor & x \ge 0 \\ \left\lceil x \right\rceil & x < 0 \\ \end For example, 23.7 gets rounded to 23, and −23.7 gets rounded to −23.


Rounding away from zero

* round away from zero (or round toward infinity): is the integer that is closest to 0 (or equivalently, to ) such that is between 0 and (included). *: y = \sgn(x) \left\lceil \left, x \ \right\rceil = -\sgn(x) \left\lfloor -\left, x \ \right\rfloor = \begin \left\lceil x \right\rceil & x \ge 0 \\ \left\lfloor x \right\rfloor & x < 0 \\ \end For example, 23.2 gets rounded to 24, and −23.2 gets rounded to −24.


Rounding to the nearest integer

Rounding a number to the nearest integer requires some tie-breaking rule for those cases when is exactly half-way between two integers — that is, when the fraction part of is exactly 0.5. If it were not for the 0.5 fractional parts, the round-off errors introduced by the round to nearest method would be symmetric: for every fraction that gets rounded down (such as 0.268), there is a complementary fraction (namely, 0.732) that gets rounded up by the same amount. When rounding a large set of fixed-point numbers with uniformly distributed fractional parts, the rounding errors by all values, with the omission of those having 0.5 fractional part, would statistically compensate each other. This means that the expected (average) value of the rounded numbers is equal to the expected value of the original numbers when numbers with fractional part 0.5 from the set are removed. In practice, floating-point numbers are typically used, which have even more computational nuances because they are not equally spaced.


Rounding half up

The following tie-breaking rule, called round half up (or round half toward positive infinity), is widely used in many disciplines. That is, half-way values of are always rounded up. * If the fractional part of is exactly 0.5, then  =  + 0.5 *: y = \left\lfloor x + 0.5 \right\rfloor = -\left\lceil -x - 0.5 \right\rceil = \left\lceil \frac \right\rceil For example, 23.5 gets rounded to 24, and −23.5 gets rounded to −23. However, some programming languages (such as Java, Python) define their ''half up'' as '' round half away from zero'' here. This method only requires checking one digit to determine rounding direction in two's complement and similar representations.


Rounding half down

One may also use round half down (or round half toward negative infinity) as opposed to the more common ''round half up''. * If the fractional part of is exactly 0.5, then  =  − 0.5 *: y = \left\lceil x - 0.5 \right\rceil = -\left\lfloor -x + 0.5 \right\rfloor = \left\lfloor \frac \right\rfloor For example, 23.5 gets rounded to 23, and −23.5 gets rounded to −24. However, some programming languages (such as Java, Python) define their ''half down'' as '' round half toward zero'' here.


Rounding half toward zero

One may also round half toward zero (or round half away from infinity) as opposed to the conventional ''round half away from zero''. * If the fractional part of is exactly 0.5, then  =  − 0.5 if is positive, and  =  + 0.5 if is negative. *: y = \sgn(x) \left\lceil \left, x \ - 0.5 \right\rceil = -\sgn(x) \left\lfloor -\left, x \ + 0.5 \right\rfloor For example, 23.5 gets rounded to 23, and −23.5 gets rounded to −23. This method treats positive and negative values symmetrically, and therefore is free of overall positive/negative bias if the original numbers are positive or negative with equal probability. It does, however, still have bias toward zero.


Rounding half away from zero

The other tie-breaking method commonly taught and used is the round half away from zero (or round half toward infinity), namely: * If the fractional part of is exactly 0.5, then = + 0.5 if is positive, and = − 0.5 if is negative. *: y = \sgn(x) \left\lfloor \left, x \ + 0.5 \right\rfloor = -\sgn(x) \left\lceil -\left, x \ - 0.5 \right\rceil For example, 23.5 gets rounded to 24, and −23.5 gets rounded to −24. This can be more efficient on binary computers because only the first omitted bit needs to be considered to determine if it rounds up (on a 1) or down (on a 0). This is one method used when rounding to significant figures due to its simplicity. This method, also known as commercial rounding, treats positive and negative values symmetrically, and therefore is free of overall positive/negative bias if the original numbers are positive or negative with equal probability. It does, however, still have bias away from zero. It is often used for currency conversions and price roundings (when the amount is first converted into the smallest significant subdivision of the currency, such as cents of a euro) as it is easy to explain by just considering the first fractional digit, independently of supplementary precision digits or sign of the amount (for strict equivalence between the paying and recipient of the amount).


Rounding half to even

A tie-breaking rule without positive/negative bias ''and'' without bias toward/away from zero is round half to even. By this convention, if the fractional part of is 0.5, then is the even integer nearest to . Thus, for example, +23.5 becomes +24, as does +24.5; however, −23.5 becomes −24, as does −24.5. This function minimizes the expected error when summing over rounded figures, even when the inputs are mostly positive or mostly negative, provided they are neither mostly even nor mostly odd. This variant of the round-to-nearest method is also called convergent rounding, statistician's rounding, Dutch rounding, Gaussian rounding, odd–even rounding, or bankers' rounding. This is the default rounding mode used in IEEE 754 operations for results in binary floating-point formats, and used when rounding to significant figures. By eliminating bias, repeated addition or subtraction of independent numbers, as in a one-dimensional random walk, will give a rounded result with an error that tends to grow in proportion to the square root of the number of operations rather than linearly. However, this rule distorts the distribution by increasing the probability of evens relative to odds. Typically this is less important than the biases that are eliminated by this method.


Rounding half to odd

A similar tie-breaking rule to round half to even is round half to odd. In this approach, if the fractional part of is 0.5, then is the odd integer nearest to . Thus, for example, +23.5 becomes +23, as does +22.5; while −23.5 becomes −23, as does −22.5. This method is also free from positive/negative bias and bias toward/away from zero, provided the numbers to be rounded are neither mostly even nor mostly odd. It also shares the round half to even property of distorting the original distribution, as it increases the probability of odds relative to evens. This variant is almost never used in computations, except in situations where one wants to avoid increasing the scale of floating-point numbers, which have a limited exponent range. With ''round half to even'', a non-infinite number would round to infinity, and a small value would round to a normal non-zero value. Effectively, this mode prefers preserving the existing scale of tie numbers, avoiding out-of-range results when possible for numeral systems of even radix (such as binary and decimal).


Rounding to prepare for shorter precision

This rounding mode (RPSP in this chapter) is used to avoid getting wrong result with
double A double is a look-alike or doppelgänger; one person or being that resembles another. Double, The Double or Dubble may also refer to: Film and television * Double (filmmaking), someone who substitutes for the credited actor of a character * ...
(including multiple) rounding. With this rounding mode, one can avoid wrong result after double rounding, if all roundings except the final one are done using RPSP, and only final rounding uses the externally requested mode. With decimal arithmetic, if there is a choice between numbers with the smallest significant digit 0 or 1, 4 or 5, 5 or 6, 9 or 0, then the digit different from 0 or 5 shall be selected; otherwise, choice is arbitrary. IBM defines that, in the latter case, a digit with the smaller magnitude shall be selected. RPSP can be applied with the step between two consequent roundings as small as a single digit (for example, rounding to 1/10 can be applied after rounding to 1/100). For example, when rounding to integer, * 20.0 is rounded to 20; * 20.01, 20.1, 20.9, 20.99, 21, 21.01, 21.9, 21.99 are rounded to 21; * 22.0, 22.1, 22.9, 22.99 are rounded to 22; * 24.0, 24.1, 24.9, 24.99 are rounded to 24; * 25.0 is rounded to 25; * 25.01, 25.1 are rounded to 26. In the example from " Double rounding" section, rounding 9.46 to one decimal gives 9.4, which rounding to integer in turn gives 9. With binary arithmetic, the rounding is made as "round to odd" (not to be mixed with " round half to odd".) For example, when rounding to 1/4: * x

2.0 => result is 2 * 2.0 < x < 2.5 => result is 2.25 * x

2.5 => result is 2.5 * 2.5 < x < 3.0 => result is 2.75 * x

3.0 => result is 3.0 For correct results, RPSP shall be applied with the step of at least 2 binary digits, otherwise, wrong result may appear. For example, * 3.125 RPSP to 1/4 => result is 3.25 * 3.25 RPSP to 1/2 => result is 3.5 * 3.5 round-half-to-even to 1 => result is 4 (wrong) If the step is 2 bits or more, RPSP gives 3.25 which, in turn, round-half-to-even to integer results in 3. RPSP is implemented in hardware in IBM zSeries and pSeries.


Randomized rounding to an integer


Alternating tie-breaking

One method, more obscure than most, is to alternate direction when rounding a number with 0.5 fractional part. All others are rounded to the closest integer. * Whenever the fractional part is 0.5, alternate rounding up or down: for the first occurrence of a 0.5 fractional part, round up, for the second occurrence, round down, and so on. Alternatively, the first 0.5 fractional part rounding can be determined by a random seed. "Up" and "down" can be any two rounding methods that oppose each other - toward and away from positive infinity or toward and away from zero. If occurrences of 0.5 fractional parts occur significantly more than a restart of the occurrence "counting", then it is effectively bias free. With guaranteed zero bias, it is useful if the numbers are to be summed or averaged.


Random tie-breaking

* If the fractional part of is 0.5, choose randomly between and , with equal probability. All others are rounded to the closest integer. Like round-half-to-even and round-half-to-odd, this rule is essentially free of overall bias, but it is also fair among even and odd values. An advantage over alternate tie-breaking is that the last direction of rounding on the 0.5 fractional part does not have to be "remembered".


Stochastic rounding

Rounding as follows to one of the closest integer toward negative infinity and the closest integer toward positive infinity, with a probability dependent on the proximity is called stochastic rounding and will give an unbiased result on average. :\operatorname (x) = \begin \lfloor x \rfloor & \text 1 - (x - \lfloor x \rfloor) = \lfloor x \rfloor - x + 1 \\ \lfloor x \rfloor + 1 & \text \end For example, 1.6 would be rounded to 1 with probability 0.4 and to 2 with probability 0.6. Stochastic rounding can be accurate in a way that a rounding function can never be. For example, suppose one started with 0 and added 0.3 to that one hundred times while rounding the running total between every addition. The result would be 0 with regular rounding, but with stochastic rounding, the expected result would be 30, which is the same value obtained without rounding. This can be useful in
machine learning Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence. Machine ...
where the training may use low precision arithmetic iteratively. Stochastic rounding is also a way to achieve 1-dimensional dithering.


Comparison of approaches for rounding to an integer


Rounding to other values


Rounding to a specified multiple

The most common type of rounding is to round to an integer; or, more generally, to an integer multiple of some increment — such as rounding to whole tenths of seconds, hundredths of a dollar, to whole multiples of 1/2 or 1/8 inch, to whole dozens or thousands, etc. In general, rounding a number to a multiple of some specified positive value entails the following steps: :\mathrm(x, m) = \mathrm(x/m) \times m For example, rounding  = 2.1784 dollars to whole cents (i.e., to a multiple of 0.01) entails computing 2.1784 / 0.01 = 217.84, then rounding that to 218, and finally computing 218 × 0.01 = 2.18. When rounding to a predetermined number of
significant digits Significant figures (also known as the significant digits, ''precision'' or ''resolution'') of a number in positional notation are digits in the number that are reliable and necessary to indicate the quantity of something. If a number expres ...
, the increment depends on the magnitude of the number to be rounded (or of the rounded result). The increment is normally a finite fraction in whatever numeral system is used to represent the numbers. For display to humans, that usually means the decimal numeral system (that is, is an integer times a power of 10, like 1/1000 or 25/100). For intermediate values stored in digital computers, it often means the binary numeral system ( is an integer times a power of 2). The abstract single-argument "round()" function that returns an integer from an arbitrary real value has at least a dozen distinct concrete definitions presented in the rounding to integer section. The abstract two-argument "roundToMultiple()" function is formally defined here, but in many cases it is used with the implicit value  = 1 for the increment and then reduces to the equivalent abstract single-argument function, with also the same dozen distinct concrete definitions.


Logarithmic rounding


Rounding to a specified power

Rounding to a specified ''power'' is very different from rounding to a specified ''multiple''; for example, it is common in computing to need to round a number to a whole power of 2. The steps, in general, to round a positive number to a power of some positive number other than 1, are: :\mathrm(x, b) = b^, x>0, b>0, b \ne 1 Many of the caveats applicable to rounding to a multiple are applicable to rounding to a power.


Scaled rounding

This type of rounding, which is also named rounding to a logarithmic scale, is a variant of rounding to a specified power. Rounding on a logarithmic scale is accomplished by taking the log of the amount and doing normal rounding to the nearest value on the log scale. For example, resistors are supplied with preferred numbers on a logarithmic scale. In particular, for resistors with a 10% accuracy, they are supplied with nominal values 100, 120, 150, 180, 220, etc. rounded to multiples of 10 ( E12 series). If a calculation indicates a resistor of 165 ohms is required then log(150) = 2.176, log(165) = 2.217 and log(180) = 2.255. The logarithm of 165 is closer to the logarithm of 180 therefore a 180 ohm resistor would be the first choice if there are no other considerations. Whether a value rounds to or depends upon whether the squared value is greater than or less than the product . The value 165 rounds to 180 in the resistors example because is greater than .


Floating-point rounding

In floating-point arithmetic, rounding aims to turn a given value into a value with a specified number of digits. In other words, should be a multiple of a number that depends on the magnitude of . The number is a power of the base (usually 2 or 10) of the floating-point representation. Apart from this detail, all the variants of rounding discussed above apply to the rounding of floating-point numbers as well. The algorithm for such rounding is presented in the Scaled rounding section above, but with a constant scaling factor  = 1, and an integer base  > 1. Where the rounded result would overflow the result for a directed rounding is either the appropriate signed infinity when "rounding away from zero", or the highest representable positive finite number (or the lowest representable negative finite number if is negative), when "rounding toward zero". The result of an overflow for the usual case of ''round to nearest'' is always the appropriate infinity.


Rounding to a simple fraction

In some contexts it is desirable to round a given number to a "neat" fraction — that is, the nearest fraction  = / whose numerator and denominator do not exceed a given maximum. This problem is fairly distinct from that of rounding a value to a fixed number of decimal or binary digits, or to a multiple of a given unit . This problem is related to Farey sequences, the Stern–Brocot tree, and continued fractions.


Rounding to an available value

Finished
lumber Lumber is wood that has been processed into dimensional lumber, including beams and planks or boards, a stage in the process of wood production. Lumber is mainly used for construction framing, as well as finishing (floors, wall panels, w ...
, writing paper, capacitors, and many other products are usually sold in only a few standard sizes. Many design procedures describe how to calculate an approximate value, and then "round" to some standard size using phrases such as "round down to nearest standard value", "round up to nearest standard value", or "round to nearest standard value". When a set of preferred values is equally spaced on a logarithmic scale, choosing the closest preferred value to any given value can be seen as a form of scaled rounding. Such rounded values can be directly calculated.


Rounding in other contexts


Dithering and error diffusion

When digitizing continuous signals, such as sound waves, the overall effect of a number of measurements is more important than the accuracy of each individual measurement. In these circumstances, dithering, and a related technique, error diffusion, are normally used. A related technique called pulse-width modulation is used to achieve analog type output from an inertial device by rapidly pulsing the power with a variable duty cycle. Error diffusion tries to ensure the error, on average, is minimized. When dealing with a gentle slope from one to zero, the output would be zero for the first few terms until the sum of the error and the current value becomes greater than 0.5, in which case a 1 is output and the difference subtracted from the error so far. Floyd–Steinberg dithering is a popular error diffusion procedure when digitizing images. As a one-dimensional example, suppose the numbers , , , and occur in order and each is to be rounded to a multiple of . In this case the cumulative sums, , , , and , are each rounded to a multiple of : , , , and . The first of these and the differences of adjacent values give the desired rounded values: , , , and .


Monte Carlo arithmetic

Monte Carlo arithmetic is a technique in
Monte Carlo method Monte Carlo methods, or Monte Carlo experiments, are a broad class of computational algorithms that rely on repeated random sampling to obtain numerical results. The underlying concept is to use randomness to solve problems that might be deter ...
s where the rounding is randomly up or down. Stochastic rounding can be used for Monte Carlo arithmetic, but in general, just rounding up or down with equal probability is more often used. Repeated runs will give a random distribution of results which can indicate the stability of the computation.


Exact computation with rounded arithmetic

It is possible to use rounded arithmetic to evaluate the exact value of a function with integer domain and range. For example, if an integer is known to be a perfect square, its square root can be computed by converting to a floating-point value , computing the approximate square root of with floating point, and then rounding to the nearest integer . If is not too big, the floating-point round-off error in will be less than 0.5, so the rounded value will be the exact square root of . This is essentially why slide rules could be used for exact arithmetic.


Double rounding

Rounding a number twice in succession to different levels of precision, with the latter precision being coarser, is not guaranteed to give the same result as rounding once to the final precision except in the case of directed rounding. For instance rounding 9.46 to one decimal gives 9.5, and then 10 when rounding to integer using rounding half to even, but would give 9 when rounded to integer directly. Borman and Chatfield discuss the implications of double rounding when comparing data rounded to one decimal place to specification limits expressed using integers. In ''Martinez v. Allstate'' and ''Sendejo v. Farmers'', litigated between 1995 and 1997, the insurance companies argued that double rounding premiums was permissible and in fact required. The US courts ruled against the insurance companies and ordered them to adopt rules to ensure single rounding. Some computer languages and the IEEE 754-2008 standard dictate that in straightforward calculations the result should not be rounded twice. This has been a particular problem with Java as it is designed to be run identically on different machines, special programming tricks have had to be used to achieve this with x87 floating point. The Java language was changed to allow different results where the difference does not matter and require a strictfp qualifier to be used when the results have to conform accurately; strict floating point has been restored in Java 17. In some algorithms, an intermediate result is computed in a larger precision, then must be rounded to the final precision. Double rounding can be avoided by choosing an adequate rounding for the intermediate computation. This consists in avoiding to round to midpoints for the final rounding (except when the midpoint is exact). In binary arithmetic, the idea is to round the result toward zero, and set the least significant bit to 1 if the rounded result is inexact; this rounding is called ''sticky rounding''. Equivalently, it consists in returning the intermediate result when it is exactly representable, and the nearest floating-point number with an odd significand otherwise; this is why it is also known as ''rounding to odd''. A concrete implementation of this approach, for binary and decimal arithmetic, is implemented as Rounding to prepare for shorter precision.


Table-maker's dilemma

William M. Kahan coined the term "The Table-Maker's Dilemma" for the unknown cost of rounding
transcendental function In mathematics, a transcendental function is an analytic function that does not satisfy a polynomial equation, in contrast to an algebraic function. In other words, a transcendental function "transcends" algebra in that it cannot be expressed ...
s: The IEEE 754 floating-point standard guarantees that add, subtract, multiply, divide, fused multiply–add, square root, and floating-point remainder will give the correctly rounded result of the infinite-precision operation. No such guarantee was given in the 1985 standard for more complex functions and they are typically only accurate to within the last bit at best. However, the 2008 standard guarantees that conforming implementations will give correctly rounded results which respect the active rounding mode; implementation of the functions, however, is optional. Using the
Gelfond–Schneider theorem In mathematics, the Gelfond–Schneider theorem establishes the transcendence of a large class of numbers. History It was originally proved independently in 1934 by Aleksandr Gelfond and Theodor Schneider. Statement : If ''a'' and ''b'' a ...
and Lindemann–Weierstrass theorem, many of the standard elementary functions can be proved to return transcendental results, except on some well-known arguments; therefore, from a theoretical point of view, it is always possible to correctly round such functions. However, for an implementation of such a function, determining a limit for a given precision on how accurate results need to be computed, before a correctly rounded result can be guaranteed, may demand a lot of computation time or may be out of reach. In practice, when this limit is not known (or only a very large bound is known), some decision has to be made in the implementation (see below); but according to a probabilistic model, correct rounding can be satisfied with a very high probability when using an intermediate accuracy of up to twice the number of digits of the target format plus some small constant (after taking special cases into account). Some programming packages offer correct rounding. The GNU MPFR package gives correctly rounded arbitrary precision results. Some other libraries implement elementary functions with correct rounding in double precision: * IBM's ''ml4j'', which stands for ''Mathematical Library for Java'', written by Abraham Ziv and Moshe Olshansky in 1999, correctly rounded to nearest only. This library was claimed to be portable, but only binaries for PowerPC/
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,
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/ Solaris and x86/
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were provided. According to its documentation, this library uses a first step with an accuracy a bit larger than double precision, a second step based on double-double arithmetic, and a third step with a 768-bit precision based on arrays of IEEE 754 double-precision floating-point numbers. * IBM's ''Accurate portable mathematical library'' (abbreviated as APMathLib or just MathLib), also called libultim, in rounding to nearest only. This library uses up to 768 bits of working precision. It was included in the
GNU C Library The GNU C Library, commonly known as glibc, is the GNU Project's implementation of the C standard library. Despite its name, it now also directly supports C++ (and, indirectly, other programming languages). It was started in the 1980s by ...
in 2001, but the "slow paths" (providing correct rounding) were removed from 2018 to 2021. *
Sun Microsystems Sun Microsystems, Inc. (Sun for short) was an American technology company that sold computers, computer components, software, and information technology services and created the Java programming language, the Solaris operating system, ZFS, t ...
's libmcr, in the 4 rounding modes. For the difficult cases, this library also uses multiple precision, and the number of words is increased by 2 each time the Table-maker's dilemma occurs (with undefined behavior in the very unlikely event that some limit of the machine is reached). * CRlibm, written in the old Arénaire team (LIP, ENS Lyon). It supports the 4 rounding modes and is proved, using the knowledge of the hardest-to-round cases. * The CORE-MATH project provides some correctly rounded functions in the 4 rounding modes, using the knowledge of the hardest-to-round cases. There exist computable numbers for which a rounded value can never be determined no matter how many digits are calculated. Specific instances cannot be given but this follows from the undecidability of the
halting problem In computability theory, the halting problem is the problem of determining, from a description of an arbitrary computer program and an input, whether the program will finish running, or continue to run forever. Alan Turing proved in 1936 that a ...
. For instance, if Goldbach's conjecture is true but unprovable, then the result of rounding the following value up to the next integer cannot be determined: either 1+10 where is the first even number greater than 4 which is not the sum of two primes, or 1 if there is no such number. The rounded result is 2 if such a number exists and 1 otherwise. The value before rounding can however be approximated to any given precision even if the conjecture is unprovable.


Interaction with string searches

Rounding can adversely affect a string search for a number. For example, rounded to four digits is "3.1416" but a simple search for this string will not discover "3.14159" or any other value of rounded to more than four digits. In contrast, truncation does not suffer from this problem; for example, a simple string search for "3.1415", which is truncated to four digits, will discover values of truncated to more than four digits.


History

The concept of rounding is very old, perhaps older than the concept of division itself. Some ancient
clay tablet In the Ancient Near East, clay tablets (Akkadian ) were used as a writing medium, especially for writing in cuneiform, throughout the Bronze Age and well into the Iron Age. Cuneiform characters were imprinted on a wet clay tablet with a sty ...
s found in
Mesopotamia Mesopotamia ''Mesopotamíā''; ar, بِلَاد ٱلرَّافِدَيْن or ; syc, ܐܪܡ ܢܗܪ̈ܝܢ, or , ) is a historical region of Western Asia situated within the Tigris–Euphrates river system, in the northern part of the ...
contain tables with rounded values of reciprocals and square roots in base 60. Rounded approximations to , the length of the year, and the length of the month are also ancient—see base 60 examples. The ''round-to-even'' method has served as the ASTM (E-29) standard since 1940. The origin of the terms ''unbiased rounding'' and ''statistician's rounding'' are fairly self-explanatory. In the 1906 fourth edition of ''Probability and Theory of Errors'' Robert Simpson Woodward called this "the computer's rule" indicating that it was then in common use by human computers who calculated mathematical tables.
Churchill Eisenhart Churchill Eisenhart (1913–1994) was a United States mathematician. He was Chief of the Statistical Engineering Laboratory (SEL), Applied Mathematics Division of the National Bureau of Standards (NBS). Biography Eisenhart was the son of Luther Ei ...
indicated the practice was already "well established" in data analysis by the 1940s. The origin of the term ''bankers' rounding'' remains more obscure. If this rounding method was ever a standard in banking, the evidence has proved extremely difficult to find. To the contrary, section 2 of the European Commission report ''The Introduction of the Euro and the Rounding of Currency Amounts'' suggests that there had previously been no standard approach to rounding in banking; and it specifies that "half-way" amounts should be rounded up. Until the 1980s, the rounding method used in floating-point computer arithmetic was usually fixed by the hardware, poorly documented, inconsistent, and different for each brand and model of computer. This situation changed after the IEEE 754 floating-point standard was adopted by most computer manufacturers. The standard allows the user to choose among several rounding modes, and in each case specifies precisely how the results should be rounded. These features made numerical computations more predictable and machine-independent, and made possible the efficient and consistent implementation of
interval arithmetic Interval arithmetic (also known as interval mathematics, interval analysis, or interval computation) is a mathematical technique used to put bounds on rounding errors and measurement errors in mathematical computation. Numerical methods using ...
. Currently, much research tends to round to multiples of 5 or 2. For example, Jörg Baten used age heaping in many studies, to evaluate the numeracy level of ancient populations. He came up with the ABCC Index, which enables the comparison of the numeracy among regions possible without any historical sources where the population
literacy Literacy in its broadest sense describes "particular ways of thinking about and doing reading and writing" with the purpose of understanding or expressing thoughts or ideas in Writing, written form in some specific context of use. In other wo ...
was measured.


Rounding functions in programming languages

Most
programming language A programming language is a system of notation for writing computer programs. Most programming languages are text-based formal languages, but they may also be graphical. They are a kind of computer language. The description of a programming ...
s provide functions or special syntax to round fractional numbers in various ways. The earliest numeric languages, such as FORTRAN and C, would provide only one method, usually truncation (toward zero). This default method could be implied in certain contexts, such as when assigning a fractional number to an
integer An integer is the number zero (), a positive natural number (, , , etc.) or a negative integer with a minus sign ( −1, −2, −3, etc.). The negative numbers are the additive inverses of the corresponding positive numbers. In the languag ...
variable, or using a fractional number as an index of an array. Other kinds of rounding had to be programmed explicitly; for example, rounding a positive number to the nearest integer could be implemented by adding 0.5 and truncating. In the last decades, however, the syntax and the standard libraries of most languages have commonly provided at least the four basic rounding functions (up, down, to nearest, and toward zero). The tie-breaking method can vary depending on the language and version or might be selectable by the programmer. Several languages follow the lead of the IEEE 754 floating-point standard, and define these functions as taking a double-precision float argument and returning the result of the same type, which then may be converted to an integer if necessary. This approach may avoid spurious overflows because floating-point types have a larger range than integer types. Some languages, such as PHP, provide functions that round a value to a specified number of decimal digits (e.g., from 4321.5678 to 4321.57 or 4300). In addition, many languages provide a printf or similar string formatting function, which allows one to convert a fractional number to a string, rounded to a user-specified number of decimal places (the ''precision''). On the other hand, truncation (round to zero) is still the default rounding method used by many languages, especially for the division of two integer values. In contrast,
CSS Cascading Style Sheets (CSS) is a style sheet language used for describing the presentation of a document written in a markup language such as HTML or XML (including XML dialects such as SVG, MathML or XHTML). CSS is a cornerstone technolo ...
and
SVG Scalable Vector Graphics (SVG) is an XML-based vector image format for defining two-dimensional graphics, having support for interactivity and animation. The SVG specification is an open standard developed by the World Wide Web Consortium s ...
do not define any specific maximum precision for numbers and measurements, which they treat and expose in their DOM and in their IDL interface as strings as if they had infinite precision, and do not discriminate between integers and floating-point values; however, the implementations of these languages will typically convert these numbers into IEEE 754 double-precision floating-point values before exposing the computed digits with a limited precision (notably within standard
JavaScript JavaScript (), often abbreviated as JS, is a programming language that is one of the core technologies of the World Wide Web, alongside HTML and CSS. As of 2022, 98% of websites use JavaScript on the client side for webpage behavior, of ...
or
ECMAScript ECMAScript (; ES) is a JavaScript standard intended to ensure the interoperability of web pages across different browsers. It is standardized by Ecma International in the documenECMA-262 ECMAScript is commonly used for client-side scripti ...
interface bindings).


Other rounding standards

Some disciplines or institutions have issued standards or directives for rounding.


US weather observations

In a guideline issued in mid-1966,OFCM, 2005
Federal Meteorological Handbook No. 1
, Washington, DC., 104 pp.
the U.S. Office of the Federal Coordinator for Meteorology determined that weather data should be rounded to the nearest round number, with the "round half up" tie-breaking rule. For example, 1.5 rounded to integer should become 2, and −1.5 should become −1. Prior to that date, the tie-breaking rule was "round half away from zero".


Negative zero in meteorology

Some meteorologists may write "−0" to indicate a temperature between 0.0 and −0.5 degrees (exclusive) that was rounded to an integer. This notation is used when the negative sign is considered important, no matter how small is the magnitude; for example, when rounding temperatures in the Celsius scale, where below zero indicates freezing.


See also

*
Cash rounding Cash rounding or Swedish rounding (New Zealand English) occurs when the minimum unit of account is smaller than the lowest physical denomination (currency), denomination of currency. The amount payable for a cash transaction is rounding, rounded t ...
, dealing with the absence of extremely low-value coins * Data binning, a similar operation * Gal's accurate tables *
Interval arithmetic Interval arithmetic (also known as interval mathematics, interval analysis, or interval computation) is a mathematical technique used to put bounds on rounding errors and measurement errors in mathematical computation. Numerical methods using ...
* ISO/IEC 80000 *
Kahan summation algorithm In numerical analysis, the Kahan summation algorithm, also known as compensated summation, significantly reduces the numerical error in the total obtained by adding a sequence of finite- precision floating-point numbers, compared to the obvious a ...
*
Party-list proportional representation Party-list proportional representation (list-PR) is a subset of proportional representation electoral systems in which multiple candidates are elected (e.g., elections to parliament) through their position on an electoral list. They can also be u ...
, an application of rounding to integers that has been thoroughly investigated *
Signed-digit representation In mathematical notation for numbers, a signed-digit representation is a positional numeral system with a set of signed digits used to encode the integers. Signed-digit representation can be used to accomplish fast addition of integers be ...
* Truncation


Notes


References


External links

* {{MathWorld, id=Rounding
An introduction to different rounding algorithms
that is accessible to a general audience but especially useful to those studying computer science and electronics.
How To Implement Custom Rounding Procedures
by Microsoft (broken) Arithmetic Computer arithmetic Statistical data transformation Theory of computation