# Integers too big for floats

(Difference between revisions)

Although floating point types can represent a large range of magnitudes,

you will sometimes have to cope with integers that are larger than what is representable by
Double
.

## 1 Dividing large integers to floats

Consider

factorial :: (Enum a, Num a) => a -> a
factorial k = product [1..k]
You will find that
factorial 777
is not representable by
Double
. However it is representable by an
Integer
. You will find that
factorial 777 / factorial 778
is representable as
Double
but not as
Integer
, but the temporary results are representable by
Integer
s and not by
Double
s.

Is there a variant of division which accepts big integers and emits floating point numbers?

Actually you can represent the fraction
factorial 777 / factorial 778
as
Rational

and convert that to a floating point number:

fromRational (factorial 777 % factorial 778)
Fortunately
fromRational
is clever enough to handle big numerators and denominators.

But there is an efficiency problem:

Before
fromRational
can perform the imprecise division, the
%
operator will cancel the fraction precisely. You may use the
Rational
constructor
:%

However that's a hack, since it is not sure that other operations work well on non-cancelled fractions.

GHC.Real
.

But since we talk about efficiency let's go on to the next paragraph, where we talk about real performance.

## 2 Avoid big integers at all

The example seems to be stupid, because you may think that nobody divides
factorial 777
by
factorial 778

without noticing, that this can be greatly simplified. So let's take the original task which led to the problem above. The problem is to compute the reciprocal of π using Chudnovsky's algorithm:

$\frac{1}{\pi} = 12 \sum^\infty_{k=0} \frac{(-1)^k (6k)! (13591409 + 545140134k)}{(3k)!(k!)^3 640320^{3k + 3/2}}\ .$

-- An exact division
-- Courtesy of Max Rabkin
(/.) :: (Real a, Fractional b) => a -> a -> b
x /. y = fromRational $toRational x / toRational y -- Compute n! fac :: Integer -> Integer fac n = product [1..n] -- Compute n! / m! efficiently facDiv :: Integer -> Integer -> Integer facDiv n m | n > m = product [n, n - 1 .. m + 1] | n == m = 1 | otherwise = facDiv m n -- Compute pi using the specified number of iterations pi' :: Integer -> Double pi' steps = 1.0 / (12.0 * s / f) where s = sum [chudnovsky n | n <- [0..steps]] f = fromIntegral c ** (3.0 / 2.0) -- Common factor in the sum -- k-th term of the Chudnovsky serie chudnovsky :: Integer -> Double chudnovsky k | even k = num /. den | otherwise = -num /. den where num = (facDiv (6 * k) (3 * k)) * (a + b * k) den = (fac k) ^ 3 * (c ^ (3 * k)) a = 13591409 b = 545140134 c = 640320 main = print$ pi' 1000

To be honest, this program doesn't really need much more optimization than limiting the number of terms to 2,

since the subsequent terms are much below the precision of
Double
. For these two terms it is not a problem to convert the
Integer
s to
Double
s.

But assume these conversions are a problem. We will show a way to avoid them. The trick is to compute the terms incrementally. We do not need to compute the factorials from scratch for each term, instead we compute each term using the term before.

start :: Floating a => a
start =
12 / sqrt 640320 ^ 3

arithmeticSeq :: Num a => [a]
arithmeticSeq =
iterate (545140134+) 13591409

factors :: Floating a => [a]
factors =
-- note canceling of product[(6*k+1)..6*(k+1)] / product[(3*k+1)..3*(k+1)]
map (\k -> -(6*k+1)*(6*k+3)*(6*k+5)/(320160*(k+1))^3) $iterate (1+) 0 summands :: Floating a => [a] summands = zipWith (*) arithmeticSeq$ scanl (*) start factors

recipPi :: Floating a => a
recipPi =
sum \$ take 2 summands