(* * Exact real arithmetic (Constructive reals). * Copyright (C) 2000 Jean-Christophe FILLIATRE * * This software is free software; you can redistribute it and/or * modify it under the terms of the GNU Library General Public * License version 2, as published by the Free Software Foundation. * * This software is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. * * See the GNU Library General Public License version 2 for more details * (enclosed in the file LGPL). *) (*i $Id: creal.ml,v 1.28 2002/07/23 09:13:23 filliatr Exp $ i*) (*i*) open Gmp (*i*) (*s This module implements constructive reals (exact real numbers), following the algorithms given in Valérie Ménissier-Morain's thesis (\small\verb!http://www-calfor.lip6.fr/~vmm/!). In the following, pages refer to this document. *) (*s {\bf Representation.} A constructive real is represented by an approximation function (field [approximate]). If $x$ is a real number, its approximation function applied to an integer $n$ (in type [int]) returns an integer $\ap{x}{n}$ (in type [Z.t]) such that $|4^n\cdot x - \ap{x}{n}| < 1$. For efficiency, we add a field [cache] to keep the best approximation computed so far. (Notice that it is safe to use type [int] for the number of digits, since an integer with a number of digits exceeding the capacity of machine integers would exceed the memory capacity.) The field [msd] is a cache for the most significant digit (see section~\ref{msd} below). *) type t = { mutable cache : (int * Z.t) option; mutable msd : int option; approximate : int -> Z.t } let create f = { cache = None; msd = None; approximate = f } (*s Computing the approximation of [x] to precision [n] is easy: either we have already computed a better approximation and the result is just a ``shift'' of that value (Property 6 page 46), or we compute [x.approximate n] and we cache its result before returning it. *) let fdiv_Bexp z n = if n == 0 then z else if n > 0 then Z.fdiv_q_2exp z (n + n) else Z.mul2exp z (-(n + n)) (*i let max_prec = ref 0 let _ = at_exit (fun () -> Printf.printf "max_prec=%d\n" !max_prec) i*) let approx x n = let compute () = let z = x.approximate n in x.cache <- Some (n,z); z in match x.cache with | None -> compute () | Some (m,a) -> if n <= m then fdiv_Bexp a (m - n) else compute () (*s Some useful constants in [Z.t] and [Q.t]. *) let z_zero = Z.from_int 0 let z_one = Z.from_int 1 let z_two = Z.from_int 2 let z_three = Z.from_int 3 let z_four = Z.from_int 4 let q_half = Q.from_ints 1 2 let q_zero = Q.from_ints 0 1 let q_one = Q.from_ints 1 1 let q_two = Q.from_ints 2 1 let q_four = Q.from_ints 4 1 (*s Utility functions over [Z.t] and [Q.t]. *) let z_gt x y = Z.cmp x y > 0 let z_le x y = Z.cmp x y <= 0 let z_between lb x up = z_le lb x && z_le x up let z_even x = (Z.cmp (Z.cdiv_r_ui x 2) z_zero) == 0 let q_max q1 q2 = if Q.cmp q1 q2 >= 0 then q1 else q2 let q_abs q = if Q.sgn q < 0 then Q.neg q else q (*s Roundings. Floor, ceil and Gau\ss\ rounding over [Q.t]. The Gau\ss\ rounding of $x$, written $\gauss{x}$, is the (only) integer such that $\gauss{x} - \half \le x < \gauss{x} + \half$. *) let q_floor q = Z.fdiv_q (Q.get_num q) (Q.get_den q) let q_ceil q = Z.cdiv_q (Q.get_num q) (Q.get_den q) let gauss_round q = let q' = Q.add q q_half in Z.fdiv_q (Q.get_num q') (Q.get_den q') let gauss_round_z_over_4 z = Z.fdiv_q_2exp (Z.add_ui z 2) 2 (*s Addition (Algorithm 2 page 50). We have $\ap{(x+y)}{n} = \lfloor(\ap{x}{n+1}+\ap{y}{n+1})/4\rceil$. We do not try to cache a value for [x+y] given the cached values for [x] and [y], if any, since it may require some computation (some shifts). Moreover, this is exactly what will be done by the first call to [approx] on [x+y] if the precision asked is less than $min(x,y)-2$. *) let add x y = create (function n -> let sn = succ n in gauss_round_z_over_4 (Z.add (approx x sn) (approx y sn))) let (+!) = add (*s Negation is immediate and subtraction is the composition of addition and negation (Algorithm 3 page 51). The cached value for [x] is immediatly cached in [-x] (at no cost). *) let cache_neg = function | None -> None | Some (n,a) -> Some (n, Z.neg a) let neg x = { cache = cache_neg x.cache; msd = x.msd; approximate = function n -> Z.neg (approx x n) } let sub x y = x +! (neg y) let (-!) = sub (*s Absolute value. *) let abs x = create (function n -> Z.abs (approx x n)) (*s Most significant digit ([msd], Definition 9 page 47). \label{msd} It is defined by $$\msd{x} = \min\ \{n\in Z ~|~ |x_n|>1 \}$$ Note that it does not terminate in 0. *) let compute_msd x = let rec look_up n = (* $|\ap{x}{n-1}| \le 1$ *) let xn = Z.abs (approx x n) in if z_gt xn z_one then n else look_up (succ n) and look_down n = (* $|\ap{x}{n+1}| > 1$ *) let xn = Z.abs (approx x n) in if z_gt xn z_one then look_down (pred n) else succ n in let x0 = Z.abs (approx x 0) in if z_gt x0 z_one then look_down (-1) else look_up 1 let msd x = match x.msd with | None -> let m = compute_msd x in x.msd <- Some m; m | Some m -> m (*s Version of [msd] with a maximal bound on the iteration process (used in function [mul] to avoid non-termination when multiplicating by 0). *) let msd_with_max m x = let rec look_up n = if n >= m then n else let xn = Z.abs (approx x n) in if z_gt xn z_one then n else look_up (succ n) and look_down n = let xn = Z.abs (approx x n) in if z_gt xn z_one then look_down (pred n) else succ n in let x0 = Z.abs (approx x 0) in if z_gt x0 z_one then look_down (-1) else look_up 1 (*s [mul_Bexp] and [div_Bexp] respectively multiplies and divides an integer by $B^n$ (works whatever the sign of [n] is). The result is a rational. *) let mul_Bexp z n = if n == 0 then Q.from_z z else if n > 0 then Q.from_z (Z.mul2exp z (n + n)) else Q.from_zs z (Z.mul2exp z (-(n + n))) let bexp n = mul_Bexp z_one n let div_Bexp z n = if n == 0 then Q.from_z z else if n > 0 then Q.from_zs z (Z.mul2exp z_one (n + n)) else Q.from_z (Z.mul2exp z (-(n + n))) (*s Multiplication (Algorithm 4 page 51). *) let mul x y = create (function n -> let d = (n + 2) / 2 in let msd' = msd_with_max (n + 3 - d) in let px = max (n - (msd' y) + 3) d and py = max (n - (msd' x) + 3) d in let xpx = approx x px and ypy = approx y py in let z = gauss_round (div_Bexp (Z.add_ui (Z.abs (Z.mul xpx ypy)) 1) (px + py - n)) in if Z.sgn xpx = Z.sgn ypy then z else Z.neg z) let ( *! ) = mul (*s Inverse (Algorithm 5 page 53) and division. *) let inv x = create (function n -> let msdx = msd x in if n <= -msdx then z_zero else let k = n + 2 * msdx + 1 in let xk = approx x k in let q = Q.div (bexp (k + n)) (Q.from_z xk) in if z_gt xk z_one then q_ceil q else q_floor q) let div x y = x *! (inv y) let (/!) = div (*s Square root (Algorithm 6 page 56). *) let sqrt x = create (function n -> let x2n = approx x (n + n) in if Z.sgn x2n < 0 then invalid_arg "Creal.sqrt"; Z.sqrt x2n) (*s Coercions from integers and rationals (Algorithm 1 page 49) and coercion to rationals. *) let fmul_Bexp q n = if n == 0 then q_floor q else if n > 0 then Z.fdiv_q (Z.mul2exp (Q.get_num q) (n + n)) (Q.get_den q) else q_floor (Q.div q (Q.from_z (Z.mul2exp z_one (-(n + n))))) let of_z z = { cache = Some (0,z); msd = None; approximate = function n -> fmul_Bexp (Q.from_z z) n } let of_q q = create (fmul_Bexp q) let to_q x n = let xn = approx x n in Q.div (Q.from_z xn) (bexp n) let of_int n = of_z (Z.from_int n) let zero = of_int 0 let one = of_int 1 let two = of_int 2 let four = of_int 4 (*s Power of a real to a small integer. *) let rec pow_int x n = if n == 0 then one else if n < 0 then inv (pow_int x (-n)) else let y = pow_int (mul x x) (n / 2) in if n mod 2 == 0 then y else mul y x let rec pow_z x n = let c = Z.cmp_si n 0 in if c == 0 then one else if c < 0 then inv (pow_z x (Z.neg n)) else let y = pow_z (mul x x) (Z.fdiv_q_2exp n 1) in if Z.cmp_si (Z.dmod_ui n 2) 0 == 0 then y else mul y x (*s Alternate power series. The following function [alternate_powerserie_] computes $B^p S$ where $S$ is the partial sum of an alternate power serie such that the remainder is less than $B^{-p}$, that is $S = \sum_{i=0}^{i=n}(-1)^ia_i$ with $a_{n+1} < B^{-p}$. The alternate power serie is given by its first term $a_0$ and a function [next] such that $a_{n+1} = \textit{next} ~ n ~ a_n$. *) let alternate_powerserie_ a0 next p = let eps = bexp (-p) in let rec sum s n an = (* [s] is already the sum up to $a_n$ *) let asn = next n an in if Q.cmp (q_abs asn) eps < 0 then s else sum (if n mod 2 == 0 then Q.sub s asn else Q.add s asn) (n + 1) asn in Q.div (sum a0 0 a0) eps (*s A specialized function to compute $atan(1/m)$ where [m] is a small integer. *) let arctan_reciproqual m = let m_inverse = Q.from_ints 1 m in let m_inverse_square = Q.mul m_inverse m_inverse in create (fun n -> let eps = bexp (-n) in let rec sum s sign k p = (* [s] is already the sum up to $a_k$ *) let p' = Q.mul p m_inverse_square in let t = Q.mul p' (Q.from_ints 1 (k + 2)) in if Q.cmp t eps < 0 then s else sum (if sign then Q.add s t else Q.sub s t) (not sign) (k + 2) p' in fmul_Bexp (sum m_inverse false 1 m_inverse) n) (*s $\pi$ is defined using [arctan], with the well-known formula (Algorithm 13 page 68) $$\frac{\pi}{4} = 12 \arctan\left(\frac{1}{18}\right) + 8 \arctan\left(\frac{1}{57}\right) - 5 \arctan\left(\frac{1}{239}\right)$$ *) let pi = (of_int 48 *! arctan_reciproqual 18) +! (of_int 32 *! arctan_reciproqual 57) -! (of_int 20 *! arctan_reciproqual 239) (*i let pi = (of_int 16 *! arctan_reciproqual 5) -! (of_int 4 *! arctan_reciproqual 239) i*) let pi_over_2 = pi /! two (*s Arctangent (Algorithm 12 page 64). *) let arctan_ x = let square_x = Q.mul x x in let next n an = Q.mul (Q.mul an square_x) (Q.from_ints (2 * n + 1) (2 * n + 3)) in alternate_powerserie_ x next let arctan_def x = create (function n -> let k = max 0 (n + 1) in let xk = approx x k in if Z.cmp_si xk 0 == 0 then z_zero else let q = Q.from_zs xk (Z.pow_ui_ui 4 k) in q_floor (Q.add (Q.div (Q.add (arctan_ q (n + 1)) q_one) q_four) (Q.div (bexp (n + k)) (Q.add (bexp (2 * n + 2)) (Q.from_z (Z.add (Z.mul xk xk) xk)))))) (*s The above definition of [arctan] converges very slowly when $|x|\ge 1$. The convergence is accelerated using the following identities: \begin{displaymath} \begin{array}{lll} \arctan(x) & = -\pi/2 - \arctan(1/x) & \mbox{ when }x<-1 \\ & = -\pi/4 - \arctan((1-x^2)/(2x))/2 & \mbox{ when }x\approx-1 \\ & = +\pi/4 - \arctan((1-x^2)/(2x))/2 & \mbox{ when }x\approx1 \\ & = +\pi/2 - \arctan(1/x) & \mbox{ when }x>1 \end{array} \end{displaymath} We use the approximation of $x$ at order 1 to discriminate between the cases. *) let arctan x = let x1 = approx x 1 in let cmp_x1_neg_4 = Z.cmp_si x1 (-4) in let cmp_x1_4 = Z.cmp_si x1 4 in if cmp_x1_neg_4 < 0 then (* $x < -1$ *) neg (pi_over_2 +! arctan_def (inv x)) else if cmp_x1_neg_4 == 0 then (* $x$ close to $-1$ *) neg (pi_over_2 +! arctan_def ((one -! x *! x) /! (two *! x))) /! two else if cmp_x1_4 == 0 then (* $x$ close to 1 *) (pi_over_2 -! arctan_def ((one -! x *! x) /! (two *! x))) /! two else if cmp_x1_4 > 0 then (* $x > 1$ *) pi_over_2 -! arctan_def (inv x) else (* $x$ close to 0 *) arctan_def x (*s Arcsinus and arccosinus are derived from arctangent (Algorithm 14 page 69). We use $\arcsin(x)+\arccos(x)=\pi/2$ to avoid non-termination of $\arcsin(1)$ and $\arccos(0)$. *) let arcsin_def x = arctan (x /! (sqrt (one -! (x *! x)))) let arccos_def x = arctan ((sqrt (one -! (x *! x))) /! x) let arcsin x = let x1 = approx x 1 in if z_le (Z.abs x1) z_two then arcsin_def x else pi_over_2 -! arccos_def x let arccos x = let x1 = approx x 1 in if z_le (Z.abs x1) z_two then pi_over_2 -! arcsin_def x else arccos_def x (*s Sinus (Algorithm 15 page 69). *) let rec sin_ x p = if Q.cmp x q_zero >= 0 then let square_x = Q.mul x x in let next n an = Q.mul (Q.mul (Q.mul an square_x) (Q.from_ints 1 (2 * n + 2))) (Q.from_ints 1 (2 * n + 3)) in alternate_powerserie_ x next p else Q.neg (sin_ (Q.neg x) p) let sin x = let p = Z.sub_ui (approx (x /! pi) 0) 1 in let theta = if Z.cmp_si p 0 == 0 then x else x -! ((of_z p) *! pi) in let z = pi_over_2 in create (fun n -> let k = max 2 (n + 2) in let zk = approx z k in let twozk = Z.mul2exp zk 1 in let threezk = Z.mul_ui zk 3 in let fourzk = Z.mul2exp zk 2 in let thetak = approx theta k in if (z_between z_zero thetak z_one) || (z_between (Z.sub_ui fourzk 4) thetak (Z.add_ui fourzk 4)) || (z_between (Z.sub_ui twozk 2) thetak (Z.add_ui twozk 2)) then z_zero else if z_between (Z.sub_ui zk 1) thetak (Z.add_ui zk 1) then let bn = Z.mul2exp z_one (n + n) in if z_even p then bn else Z.neg bn else if z_between (Z.sub_ui threezk 3) thetak (Z.add_ui threezk 3) then let bn = Z.mul2exp z_one (n + n) in if z_even p then Z.neg bn else bn else let q = Q.from_zs thetak (Z.pow_ui_ui 4 k) in let s = sin_ q (n + 2) in let bw = Q.from_ints 16 1 in let bn_k = bexp (n - k) in let r = if (z_between z_two thetak (Z.sub_ui zk 2)) || (z_between (Z.add_ui zk 2) thetak (Z.sub_ui twozk 3)) then q_floor (Q.add (Q.div (Q.add s q_one) bw) bn_k) else q_ceil (Q.sub (Q.div (Q.sub s q_one) bw) bn_k) in if z_even p then r else Z.neg r) (*s Cosinus and tangent are derived from sinus (Algorithm 16 page 78). *) let cos x = sin (pi_over_2 -! x) let tan x = (sin x) /! (cos x) (*s Euler constant [e]. *) type sum_cache = { mutable order : int; mutable sum : Q.t; (* sum up to [order] *) mutable term : Q.t; (* last term $a_{order}$ *) mutable prec : int } let e = let e_cache = { order = 1; sum = q_two; term = q_one; prec = 0 } in create (fun p -> if p <= e_cache.prec then fmul_Bexp e_cache.sum p else let eps = bexp (-p) in let rec sum s n an = let rn = Q.mul (Q.from_ints 1 n) an in if Q.cmp rn eps <= 0 then begin e_cache.order <- n; e_cache.sum <- s; e_cache.term <- an; e_cache.prec <- p; fmul_Bexp s p end else let asn = Q.mul (Q.from_ints 1 (n + 1)) an in sum (Q.add s asn) (n + 1) asn in sum e_cache.sum e_cache.order e_cache.term) (*s Natural logarithm (Algorithm 9 page 62). *) let ln_above_1 r = let y = Q.div (Q.sub r q_one) (Q.add r q_one) in let y_square = Q.mul y y in let one_minus_y_square = Q.sub q_one y_square in fun n -> let eps = bexp (-n) in let rec sum s k p = (* [s] is already the sum up to $a_k$ *) let p' = Q.mul p y_square in let t = Q.mul p' (Q.from_ints 1 (k + 2)) in if Q.cmp (Q.div t one_minus_y_square) eps < 0 then Q.mul q_two s else sum (Q.add s t) (k + 2) p' in Q.div (sum y 1 y) eps let rec ln_ r = if Q.cmp r q_zero <= 0 then invalid_arg "Creal.ln"; let cmp1 = Q.cmp r q_one in if cmp1 < 0 then (* $r < 1$ *) let ln_inverse_r = ln_ (Q.inv r) in (fun n -> Q.neg (ln_inverse_r n)) else if cmp1 == 0 then (* $r = 1$ *) (fun n -> q_zero) else (* $r > 1$ *) ln_above_1 r let ln_4 = let f = ln_above_1 q_four in create (fun n -> q_floor (f n)) let rec ln x = let msd_x = msd x in let k = -msd_x + 1 in if k != 0 then ln (x /! (of_q (bexp k))) +! (of_int k) *! ln_4 else create (fun n -> let w = 2 - min 0 n in let k = n + msd_x + w in let xk = Q.from_z (approx x k) in let q = Q.div xk (bexp k) in q_floor (Q.add (Q.div (Q.add (ln_ q (n + w)) q_one) (bexp w)) (Q.div (bexp n) xk))) let log x y = ln y /! ln x (*s Inverses of hyperbolic functions. *) let arcsinh x = ln (x +! sqrt (x *! x +! one)) let arccosh x = ln (x +! sqrt (x *! x -! one)) let arctanh x = ln ((one +! x) /! (one -! x)) /! two (*s Exponential (Algorithm 7 page 57). *) let exp_neg_ r = (* $-1 \le r < 0$ *) let r = q_abs r in let next n an = Q.mul (Q.mul an r) (Q.from_ints 1 (n + 1)) in create (fun n -> q_floor (alternate_powerserie_ q_one next n)) let exp_ r = if Q.cmp r q_zero == 0 then one else let s_floor_r = Z.add_ui (q_floor r) 1 in mul (pow_z e s_floor_r) (exp_neg_ (Q.sub r (Q.from_z s_floor_r))) let exp x = create (fun n -> let qbn = bexp n in let bn = of_q qbn in let invqbn = Q.inv qbn in let one_plus_invqbn = Q.add q_one invqbn in let test1 () = let lsup = log four (of_int 7 /! ln ((bn +! one) /! (bn -! one))) in let l = Z.int_from (approx lsup 0) + 1 in let xl = approx x l in let log1 = q_floor (ln_ (Q.sub q_one invqbn) l) in let log2 = q_floor (ln_ one_plus_invqbn l) in (Z.cmp (Z.add log1 z_two) xl < 0) && (Z.cmp xl (Z.sub log2 z_two) < 0) in let test2 () = let x0 = approx x 0 in let m = Z.sub (q_floor (ln_ one_plus_invqbn 0)) z_two in Z.cmp x0 m <= 0 in if (n > 0 && test1 ()) || (n <= 0 && test2 ()) then fmul_Bexp q_one n else let msd_x = msd x in let clogBe = if Z.cmp (approx x msd_x) z_one >= 0 then Q.from_ints 577080 100000 else Q.from_ints (-72134) 100000 in let d2 = Q.div clogBe (bexp msd_x) in let p = max 0 (n + 1) in let d = q_max (Q.from_ints (-p) 1) d2 in let k2 = q_ceil (Q.add d (Q.from_ints 44732 100000)) in let k = max 1 (max msd_x (p + 1 + Z.int_from k2)) in let bk = bexp k in let xk = approx x k in let xkBk = Q.div (Q.from_z xk) bk in let exp_xkBk_p = approx (exp_ xkBk) p in if Z.cmp exp_xkBk_p z_zero <= 0 then z_zero else q_ceil (Q.mul (Q.sub (Q.div (Q.from_z exp_xkBk_p) q_four) q_one) (Q.sub q_one (Q.inv bk)))) let pow x y = exp (y *! ln x) (*s Hyperbolic functions. *) let sinh x = (exp x -! exp (neg x)) /! two let cosh x = (exp x +! exp (neg x)) /! two let tanh x = sinh x /! cosh x (*s Comparisons. [cmp] is absolute comparison and [rel_cmp] is comparison up to $4^{-k}$. *) let cmp x y = let rec cmp_rec n = let xn = approx x n in let yn = approx y n in if z_gt (Z.add_ui xn 1) (Z.sub_ui yn 1) && z_gt (Z.add_ui yn 1) (Z.sub_ui xn 1) then cmp_rec (succ n) else if z_le (Z.add_ui xn 1) (Z.sub_ui yn 1) then -1 else 1 in cmp_rec 0 let rel_cmp k x y = let rec cmp_rec n = let xn = approx x n in let yn = approx y n in if z_gt (Z.add_ui xn 1) (Z.sub_ui yn 1) && z_gt (Z.add_ui yn 1) (Z.sub_ui xn 1) && n <= k + 2 then cmp_rec (succ n) else if z_le (Z.add_ui xn 1) (Z.sub_ui yn 1) then -1 else if z_le (Z.add_ui yn 1) (Z.sub_ui xn 1) then 1 else 0 in cmp_rec 0 (*s Coercions to and from type [float]. *) let of_float f = of_q (Q.from_float f) let to_float x n = Q.float_from (to_q x n) (*s Coercion to and from type [string]. *) let of_string s base = try begin try let n = String.length s in let p = String.index s '.' in let dec = n - p - 1 in let s' = (String.sub s 0 p) ^ (String.sub s (p + 1) dec) in of_q (Q.from_zs (Z.from_string_base base s') (Z.pow_ui_ui base dec)) with Not_found -> of_z (Z.from_string_base base s) end with Invalid_argument _ -> invalid_arg "Creal.of_string" (*s Decimal approximation of [x] at order [p]. We look for an integer [n] such that $|10^px - n| < 1/2$ i.e. the integer closest to $10^px$. There is sometimes no such integer but then we can find a decimal approximation at order [p+1]. We first compute $y = 10^px$ and [approx y 3] i.e. an approximation $y_3/64$ of $y$. Let $q$ and $r$ be the quotient and remainder of the division $y_3/64$ such that $y_3 = 64q+r$ and $0\le r<63$. If $r\le 31$ then $n$ is $q$; If $r\ge 33$ then $n$ is $q+1$; Otherwise $10q+5$ is a decimal approximation of $x$ at order $p+1$. *) let to_string_aux x p = if p < 0 then invalid_arg "Creal.to_string"; let tenp = Z.pow_ui_ui 10 p in let y = mul (of_z tenp) x in let y3 = approx y 3 in let q,r = Z.fdiv_qr_ui y3 64 in let r = Z.int_from r in let n,p = if r <= 31 then q, p else if r >= 33 then Z.add_ui q 1, p else Z.add_ui (Z.mul_ui q 10) 5, succ p in let ns = Z.string_from (Z.abs n) in let lns = String.length ns in let ins,dns = if lns >= p+1 then String.sub ns 0 (lns - p), String.sub ns (lns - p) p else "0", String.make (p - lns) '0' ^ ns in Z.sgn n, ins, dns let to_string x p = let sgn,i,f = to_string_aux x p in (if sgn < 0 then "-" else "") ^ i ^ "." ^ f (*s Coercion to type [string] with digits packed 5 by 5. *) let string_concat = String.concat "" let beautiful s = let n = String.length s in let eol i = if (i + 5) mod 65 == 0 then "\n" else " " in let rec cut i = String.sub s i (min 5 (n - i)) :: if i < n - 5 then eol i :: cut (i + 5) else [] in string_concat (cut 0) let to_beautiful_string x p = let sgn,i,f = to_string_aux x p in let nl = if String.length i + String.length f > 75 then "\n" else "" in (if sgn < 0 then "-" else "") ^ i ^ "." ^ nl ^ beautiful f module Infixes = struct let (+!) = add let (-!) = sub let ( *! ) = mul let (/!) = div end