Asymptote B

Average Error: 0.0 → 0.0

Time: 4.4s

Precision: binary64

Cost: 960

Math

\[\frac{1}{x - 1} + \frac{x}{x + 1} \]

↓

\[\frac{\frac{x + \frac{1}{x}}{x + -1}}{1 + \frac{1}{x}} \]

FPCore

(FPCore (x) :precision binary64 (+ (/ 1.0 (- x 1.0)) (/ x (+ x 1.0))))

↓

(FPCore (x)
 :precision binary64
 (/ (/ (+ x (/ 1.0 x)) (+ x -1.0)) (+ 1.0 (/ 1.0 x))))

C

double code(double x) {
	return (1.0 / (x - 1.0)) + (x / (x + 1.0));
}

↓

double code(double x) {
	return ((x + (1.0 / x)) / (x + -1.0)) / (1.0 + (1.0 / x));
}

Fortran

real(8) function code(x)
    real(8), intent (in) :: x
    code = (1.0d0 / (x - 1.0d0)) + (x / (x + 1.0d0))
end function

↓

real(8) function code(x)
    real(8), intent (in) :: x
    code = ((x + (1.0d0 / x)) / (x + (-1.0d0))) / (1.0d0 + (1.0d0 / x))
end function

Java

public static double code(double x) {
	return (1.0 / (x - 1.0)) + (x / (x + 1.0));
}

↓

public static double code(double x) {
	return ((x + (1.0 / x)) / (x + -1.0)) / (1.0 + (1.0 / x));
}

Python

def code(x):
	return (1.0 / (x - 1.0)) + (x / (x + 1.0))

↓

def code(x):
	return ((x + (1.0 / x)) / (x + -1.0)) / (1.0 + (1.0 / x))

Julia

function code(x)
	return Float64(Float64(1.0 / Float64(x - 1.0)) + Float64(x / Float64(x + 1.0)))
end

↓

function code(x)
	return Float64(Float64(Float64(x + Float64(1.0 / x)) / Float64(x + -1.0)) / Float64(1.0 + Float64(1.0 / x)))
end

MATLAB

function tmp = code(x)
	tmp = (1.0 / (x - 1.0)) + (x / (x + 1.0));
end

↓

function tmp = code(x)
	tmp = ((x + (1.0 / x)) / (x + -1.0)) / (1.0 + (1.0 / x));
end

Wolfram

code[x_] := N[(N[(1.0 / N[(x - 1.0), $MachinePrecision]), $MachinePrecision] + N[(x / N[(x + 1.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

↓

code[x_] := N[(N[(N[(x + N[(1.0 / x), $MachinePrecision]), $MachinePrecision] / N[(x + -1.0), $MachinePrecision]), $MachinePrecision] / N[(1.0 + N[(1.0 / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 0.0

   \[\frac{1}{x - 1} + \frac{x}{x + 1} \]

2. Applied egg-rr 0.0

   \[\leadsto \color{blue}{\frac{\frac{x + \frac{1}{x}}{x + -1}}{1 + \frac{1}{x}}} \]

3. Final simplification 0.0

   \[\leadsto \frac{\frac{x + \frac{1}{x}}{x + -1}}{1 + \frac{1}{x}} \]

Alternatives

Alternative 1
Error	0.6
Cost	840

\[\begin{array}{l} \mathbf{if}\;x \leq -1:\\ \;\;\;\;1\\ \mathbf{elif}\;x \leq 1:\\ \;\;\;\;\left(x \cdot -2 - \frac{1}{x}\right) \cdot x\\ \mathbf{else}:\\ \;\;\;\;1\\ \end{array} \]

Alternative 2
Error	0.4
Cost	840

\[\begin{array}{l} t_0 := \frac{x}{x - 2 \cdot \frac{1}{x}}\\ \mathbf{if}\;x \leq -1:\\ \;\;\;\;t_0\\ \mathbf{elif}\;x \leq 1:\\ \;\;\;\;\left(x \cdot -2 - \frac{1}{x}\right) \cdot x\\ \mathbf{else}:\\ \;\;\;\;t_0\\ \end{array} \]

Alternative 3
Error	0.7
Cost	712

\[\begin{array}{l} \mathbf{if}\;x \leq -1:\\ \;\;\;\;1\\ \mathbf{elif}\;x \leq 1.92:\\ \;\;\;\;\frac{1}{x - 1} + x\\ \mathbf{else}:\\ \;\;\;\;1\\ \end{array} \]

Alternative 4
Error	0.0
Cost	704

\[\frac{1}{x - 1} + \frac{x}{x + 1} \]

Alternative 5
Error	0.0
Cost	704

\[\frac{x + \frac{1}{x}}{x + \frac{-1}{x}} \]

Alternative 6
Error	0.7
Cost	328

\[\begin{array}{l} \mathbf{if}\;x \leq -1:\\ \;\;\;\;1\\ \mathbf{elif}\;x \leq 1:\\ \;\;\;\;-1\\ \mathbf{else}:\\ \;\;\;\;1\\ \end{array} \]

Alternative 7
Error	31.8
Cost	64

\[-1 \]

Reproduce

herbie shell --seed 2023067 
(FPCore (x)
  :name "Asymptote B"
  :precision binary64
  (+ (/ 1.0 (- x 1.0)) (/ x (+ x 1.0))))