VandenBroeck and Keller, Equation (6)

Average Error: 16.8 → 0.9

Time: 13.4s

Precision: binary64

Cost: 32969

Math

\[\pi \cdot \ell - \frac{1}{F \cdot F} \cdot \tan \left(\pi \cdot \ell\right) \]

↓

\[\begin{array}{l} \mathbf{if}\;\pi \cdot \ell \leq -5 \cdot 10^{+28} \lor \neg \left(\pi \cdot \ell \leq 200000000\right):\\ \;\;\;\;\pi \cdot \ell\\ \mathbf{else}:\\ \;\;\;\;\pi \cdot \ell - \frac{\frac{\tan \left(\pi \cdot \ell\right)}{F}}{F}\\ \end{array} \]

FPCore

(FPCore (F l)
 :precision binary64
 (- (* PI l) (* (/ 1.0 (* F F)) (tan (* PI l)))))

↓

(FPCore (F l)
 :precision binary64
 (if (or (<= (* PI l) -5e+28) (not (<= (* PI l) 200000000.0)))
   (* PI l)
   (- (* PI l) (/ (/ (tan (* PI l)) F) F))))

C

double code(double F, double l) {
	return (((double) M_PI) * l) - ((1.0 / (F * F)) * tan((((double) M_PI) * l)));
}

↓

double code(double F, double l) {
	double tmp;
	if (((((double) M_PI) * l) <= -5e+28) || !((((double) M_PI) * l) <= 200000000.0)) {
		tmp = ((double) M_PI) * l;
	} else {
		tmp = (((double) M_PI) * l) - ((tan((((double) M_PI) * l)) / F) / F);
	}
	return tmp;
}

Java

public static double code(double F, double l) {
	return (Math.PI * l) - ((1.0 / (F * F)) * Math.tan((Math.PI * l)));
}

↓

public static double code(double F, double l) {
	double tmp;
	if (((Math.PI * l) <= -5e+28) || !((Math.PI * l) <= 200000000.0)) {
		tmp = Math.PI * l;
	} else {
		tmp = (Math.PI * l) - ((Math.tan((Math.PI * l)) / F) / F);
	}
	return tmp;
}

Python

def code(F, l):
	return (math.pi * l) - ((1.0 / (F * F)) * math.tan((math.pi * l)))

↓

def code(F, l):
	tmp = 0
	if ((math.pi * l) <= -5e+28) or not ((math.pi * l) <= 200000000.0):
		tmp = math.pi * l
	else:
		tmp = (math.pi * l) - ((math.tan((math.pi * l)) / F) / F)
	return tmp

Julia

function code(F, l)
	return Float64(Float64(pi * l) - Float64(Float64(1.0 / Float64(F * F)) * tan(Float64(pi * l))))
end

↓

function code(F, l)
	tmp = 0.0
	if ((Float64(pi * l) <= -5e+28) || !(Float64(pi * l) <= 200000000.0))
		tmp = Float64(pi * l);
	else
		tmp = Float64(Float64(pi * l) - Float64(Float64(tan(Float64(pi * l)) / F) / F));
	end
	return tmp
end

MATLAB

function tmp = code(F, l)
	tmp = (pi * l) - ((1.0 / (F * F)) * tan((pi * l)));
end

↓

function tmp_2 = code(F, l)
	tmp = 0.0;
	if (((pi * l) <= -5e+28) || ~(((pi * l) <= 200000000.0)))
		tmp = pi * l;
	else
		tmp = (pi * l) - ((tan((pi * l)) / F) / F);
	end
	tmp_2 = tmp;
end

Wolfram

code[F_, l_] := N[(N[(Pi * l), $MachinePrecision] - N[(N[(1.0 / N[(F * F), $MachinePrecision]), $MachinePrecision] * N[Tan[N[(Pi * l), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

↓

code[F_, l_] := If[Or[LessEqual[N[(Pi * l), $MachinePrecision], -5e+28], N[Not[LessEqual[N[(Pi * l), $MachinePrecision], 200000000.0]], $MachinePrecision]], N[(Pi * l), $MachinePrecision], N[(N[(Pi * l), $MachinePrecision] - N[(N[(N[Tan[N[(Pi * l), $MachinePrecision]], $MachinePrecision] / F), $MachinePrecision] / F), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if (*.f64 (PI.f64) l) < -4.99999999999999957e28 or 2e8 < (*.f64 (PI.f64) l)

   1. Initial program 23.2

      \[\pi \cdot \ell - \frac{1}{F \cdot F} \cdot \tan \left(\pi \cdot \ell\right) \]

   2. Simplified 23.2

      \[\leadsto \color{blue}{\pi \cdot \ell - \frac{\tan \left(\pi \cdot \ell\right)}{F \cdot F}} \]
      Proof
      (-.f64 (*.f64 (PI.f64) l) (/.f64 (tan.f64 (*.f64 (PI.f64) l)) (*.f64 F F))): 0 points increase in error, 0 points decrease in error
      (-.f64 (*.f64 (PI.f64) l) (/.f64 (Rewrite<= *-lft-identity_binary64 (*.f64 1 (tan.f64 (*.f64 (PI.f64) l)))) (*.f64 F F))): 0 points increase in error, 0 points decrease in error
      (-.f64 (*.f64 (PI.f64) l) (Rewrite<= associate-*l/_binary64 (*.f64 (/.f64 1 (*.f64 F F)) (tan.f64 (*.f64 (PI.f64) l))))): 0 points increase in error, 0 points decrease in error

   3. Taylor expanded in l around inf 0.4

      \[\leadsto \color{blue}{\ell \cdot \pi} \]

   if -4.99999999999999957e28 < (*.f64 (PI.f64) l) < 2e8

   1. Initial program 10.3

      \[\pi \cdot \ell - \frac{1}{F \cdot F} \cdot \tan \left(\pi \cdot \ell\right) \]

   2. Applied egg-rr 1.4

      \[\leadsto \pi \cdot \ell - \color{blue}{\frac{\frac{\tan \left(\pi \cdot \ell\right)}{F}}{F}} \]
3. Recombined 2 regimes into one program.

4. Final simplification 0.9

   \[\leadsto \begin{array}{l} \mathbf{if}\;\pi \cdot \ell \leq -5 \cdot 10^{+28} \lor \neg \left(\pi \cdot \ell \leq 200000000\right):\\ \;\;\;\;\pi \cdot \ell\\ \mathbf{else}:\\ \;\;\;\;\pi \cdot \ell - \frac{\frac{\tan \left(\pi \cdot \ell\right)}{F}}{F}\\ \end{array} \]

Alternatives

Alternative 1
Error	1.2
Cost	26569

\[\begin{array}{l} \mathbf{if}\;\pi \cdot \ell \leq -5 \cdot 10^{+28} \lor \neg \left(\pi \cdot \ell \leq 200000000\right):\\ \;\;\;\;\pi \cdot \ell\\ \mathbf{else}:\\ \;\;\;\;\pi \cdot \ell - \frac{\pi}{F \cdot \frac{F}{\ell}}\\ \end{array} \]

Alternative 2
Error	13.6
Cost	7640

\[\begin{array}{l} t_0 := \left(\pi \cdot \ell + 1\right) + -1\\ t_1 := \frac{\pi}{F} \cdot \left(-\frac{\ell}{F}\right)\\ \mathbf{if}\;F \leq -8.6 \cdot 10^{-47}:\\ \;\;\;\;\pi \cdot \ell\\ \mathbf{elif}\;F \leq -8.6 \cdot 10^{-106}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;F \leq -1 \cdot 10^{-162}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;F \leq -1.4 \cdot 10^{-189}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;F \leq 5.2 \cdot 10^{-179}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;F \leq 3.3 \cdot 10^{-107}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;\pi \cdot \ell\\ \end{array} \]

Alternative 3
Error	13.7
Cost	7640

\[\begin{array}{l} t_0 := \left(\pi \cdot \ell + 1\right) + -1\\ t_1 := -\frac{\ell}{F}\\ t_2 := \frac{\pi \cdot t_1}{F}\\ \mathbf{if}\;F \leq -7.4 \cdot 10^{-47}:\\ \;\;\;\;\pi \cdot \ell\\ \mathbf{elif}\;F \leq -5.2 \cdot 10^{-107}:\\ \;\;\;\;\frac{\pi}{F} \cdot t_1\\ \mathbf{elif}\;F \leq -2.45 \cdot 10^{-161}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;F \leq -3.8 \cdot 10^{-190}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;F \leq 2 \cdot 10^{-177}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;F \leq 10^{-106}:\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;\pi \cdot \ell\\ \end{array} \]

Alternative 4
Error	13.7
Cost	7640

\[\begin{array}{l} t_0 := \left(\pi \cdot \ell + 1\right) + -1\\ t_1 := \frac{\pi \cdot \left(-\frac{\ell}{F}\right)}{F}\\ \mathbf{if}\;F \leq -5.5 \cdot 10^{-47}:\\ \;\;\;\;\pi \cdot \ell\\ \mathbf{elif}\;F \leq -1.3 \cdot 10^{-105}:\\ \;\;\;\;\frac{\pi}{F \cdot F} \cdot \left(-\ell\right)\\ \mathbf{elif}\;F \leq -1.22 \cdot 10^{-159}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;F \leq -6.2 \cdot 10^{-190}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;F \leq 6.2 \cdot 10^{-177}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;F \leq 3.4 \cdot 10^{-107}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;\pi \cdot \ell\\ \end{array} \]

Alternative 5
Error	0.7
Cost	7177

\[\begin{array}{l} \mathbf{if}\;\ell \leq -8 \cdot 10^{+14} \lor \neg \left(\ell \leq 57000000\right):\\ \;\;\;\;\pi \cdot \ell\\ \mathbf{else}:\\ \;\;\;\;\pi \cdot \left(\ell - \frac{\frac{\ell}{F}}{F}\right)\\ \end{array} \]

Alternative 6
Error	13.8
Cost	6528

\[\pi \cdot \ell \]

Reproduce

herbie shell --seed 2022343 
(FPCore (F l)
  :name "VandenBroeck and Keller, Equation (6)"
  :precision binary64
  (- (* PI l) (* (/ 1.0 (* F F)) (tan (* PI l)))))