Data.Approximate.Numerics:blog from approximate-0.2.2.1

Average Error: 0.39% → 0.07%

Time: 9.7s

Precision: binary64

Cost: 7232

Math

\[\frac{6 \cdot \left(x - 1\right)}{\left(x + 1\right) + 4 \cdot \sqrt{x}} \]

↓

\[\frac{1 - x}{\frac{1 + \left(x + 4 \cdot \sqrt{x}\right)}{-6}} \]

FPCore

(FPCore (x)
 :precision binary64
 (/ (* 6.0 (- x 1.0)) (+ (+ x 1.0) (* 4.0 (sqrt x)))))

↓

(FPCore (x)
 :precision binary64
 (/ (- 1.0 x) (/ (+ 1.0 (+ x (* 4.0 (sqrt x)))) -6.0)))

C

double code(double x) {
	return (6.0 * (x - 1.0)) / ((x + 1.0) + (4.0 * sqrt(x)));
}

↓

double code(double x) {
	return (1.0 - x) / ((1.0 + (x + (4.0 * sqrt(x)))) / -6.0);
}

Fortran

real(8) function code(x)
    real(8), intent (in) :: x
    code = (6.0d0 * (x - 1.0d0)) / ((x + 1.0d0) + (4.0d0 * sqrt(x)))
end function

↓

real(8) function code(x)
    real(8), intent (in) :: x
    code = (1.0d0 - x) / ((1.0d0 + (x + (4.0d0 * sqrt(x)))) / (-6.0d0))
end function

Java

public static double code(double x) {
	return (6.0 * (x - 1.0)) / ((x + 1.0) + (4.0 * Math.sqrt(x)));
}

↓

public static double code(double x) {
	return (1.0 - x) / ((1.0 + (x + (4.0 * Math.sqrt(x)))) / -6.0);
}

Python

def code(x):
	return (6.0 * (x - 1.0)) / ((x + 1.0) + (4.0 * math.sqrt(x)))

↓

def code(x):
	return (1.0 - x) / ((1.0 + (x + (4.0 * math.sqrt(x)))) / -6.0)

Julia

function code(x)
	return Float64(Float64(6.0 * Float64(x - 1.0)) / Float64(Float64(x + 1.0) + Float64(4.0 * sqrt(x))))
end

↓

function code(x)
	return Float64(Float64(1.0 - x) / Float64(Float64(1.0 + Float64(x + Float64(4.0 * sqrt(x)))) / -6.0))
end

MATLAB

function tmp = code(x)
	tmp = (6.0 * (x - 1.0)) / ((x + 1.0) + (4.0 * sqrt(x)));
end

↓

function tmp = code(x)
	tmp = (1.0 - x) / ((1.0 + (x + (4.0 * sqrt(x)))) / -6.0);
end

Wolfram

code[x_] := N[(N[(6.0 * N[(x - 1.0), $MachinePrecision]), $MachinePrecision] / N[(N[(x + 1.0), $MachinePrecision] + N[(4.0 * N[Sqrt[x], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

↓

code[x_] := N[(N[(1.0 - x), $MachinePrecision] / N[(N[(1.0 + N[(x + N[(4.0 * N[Sqrt[x], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / -6.0), $MachinePrecision]), $MachinePrecision]

Target

Original	0.39%
Target	0.08%
Herbie	0.07%

\[\frac{6}{\frac{\left(x + 1\right) + 4 \cdot \sqrt{x}}{x - 1}} \]

Derivation

1. Initial program 0.39

   \[\frac{6 \cdot \left(x - 1\right)}{\left(x + 1\right) + 4 \cdot \sqrt{x}} \]

2. Applied egg-rr 0.54

   \[\leadsto \color{blue}{\left(\left(x + -1\right) \cdot -6\right) \cdot \frac{1}{-1 - \left(x + \sqrt{x \cdot 16}\right)}} \]

3. Simplified 0.31

   \[\leadsto \color{blue}{-6 \cdot \frac{x + -1}{\left(-1 - x\right) - \sqrt{x \cdot 16}}} \]
   Proof

   [Start] 0.54	\[ \left(\left(x + -1\right) \cdot -6\right) \cdot \frac{1}{-1 - \left(x + \sqrt{x \cdot 16}\right)} \]
   *-commutative [=>] 0.54	\[ \color{blue}{\frac{1}{-1 - \left(x + \sqrt{x \cdot 16}\right)} \cdot \left(\left(x + -1\right) \cdot -6\right)} \]
   associate-*r* [=>] 0.42	\[ \color{blue}{\left(\frac{1}{-1 - \left(x + \sqrt{x \cdot 16}\right)} \cdot \left(x + -1\right)\right) \cdot -6} \]
   *-commutative [=>] 0.42	\[ \color{blue}{-6 \cdot \left(\frac{1}{-1 - \left(x + \sqrt{x \cdot 16}\right)} \cdot \left(x + -1\right)\right)} \]
   associate-*l/ [=>] 0.31	\[ -6 \cdot \color{blue}{\frac{1 \cdot \left(x + -1\right)}{-1 - \left(x + \sqrt{x \cdot 16}\right)}} \]
   *-lft-identity [=>] 0.31	\[ -6 \cdot \frac{\color{blue}{x + -1}}{-1 - \left(x + \sqrt{x \cdot 16}\right)} \]
   associate--r+ [=>] 0.31	\[ -6 \cdot \frac{x + -1}{\color{blue}{\left(-1 - x\right) - \sqrt{x \cdot 16}}} \]

4. Applied egg-rr 0.07

   \[\leadsto \color{blue}{\frac{1 - x}{\frac{1 + \left(x + 4 \cdot \sqrt{x}\right)}{-6}}} \]

5. Final simplification 0.07

   \[\leadsto \frac{1 - x}{\frac{1 + \left(x + 4 \cdot \sqrt{x}\right)}{-6}} \]

Alternatives

Alternative 1
Error	3.71%
Cost	7236

\[\begin{array}{l} \mathbf{if}\;x \leq 1.5:\\ \;\;\;\;\frac{\left(1 - x\right) \cdot \left(\left(1 + x\right) \cdot -0.16666666666666666\right)}{-1 - x} \cdot \left(6 \cdot \frac{-6}{1 + x}\right)\\ \mathbf{else}:\\ \;\;\;\;\frac{x \cdot 6}{4 \cdot \sqrt{x} + \left(1 + x\right)}\\ \end{array} \]

Alternative 2
Error	0.31%
Cost	7232

\[-6 \cdot \frac{x + -1}{\left(-1 - x\right) - \sqrt{x \cdot 16}} \]

Alternative 3
Error	0.14%
Cost	7232

\[\left(x + -1\right) \cdot \frac{6}{x - \left(-1 - 4 \cdot \sqrt{x}\right)} \]

Alternative 4
Error	0.08%
Cost	7232

\[\frac{6}{\frac{x - \left(-1 - 4 \cdot \sqrt{x}\right)}{x + -1}} \]

Alternative 5
Error	4.7%
Cost	576

\[\frac{1 - x}{\frac{1 + x}{-6}} \]

Alternative 6
Error	4.71%
Cost	452

\[\begin{array}{l} \mathbf{if}\;x \leq 0.5:\\ \;\;\;\;-6\\ \mathbf{else}:\\ \;\;\;\;6 - \frac{6}{x}\\ \end{array} \]

Alternative 7
Error	4.7%
Cost	452

\[\begin{array}{l} \mathbf{if}\;x \leq 0.5:\\ \;\;\;\;x \cdot 12 - 6\\ \mathbf{else}:\\ \;\;\;\;6 - \frac{6}{x}\\ \end{array} \]

Alternative 8
Error	4.71%
Cost	452

\[\begin{array}{l} \mathbf{if}\;x \leq 1:\\ \;\;\;\;\frac{1 - x}{-0.16666666666666666}\\ \mathbf{else}:\\ \;\;\;\;6 - \frac{6}{x}\\ \end{array} \]

Alternative 9
Error	4.71%
Cost	452

\[\begin{array}{l} \mathbf{if}\;x \leq 1:\\ \;\;\;\;6 \cdot \left(x + -1\right)\\ \mathbf{else}:\\ \;\;\;\;6 - \frac{6}{x}\\ \end{array} \]

Alternative 10
Error	4.71%
Cost	196

\[\begin{array}{l} \mathbf{if}\;x \leq 1:\\ \;\;\;\;-6\\ \mathbf{else}:\\ \;\;\;\;6\\ \end{array} \]

Alternative 11
Error	51.12%
Cost	64

\[-6 \]

Reproduce

herbie shell --seed 2023089 
(FPCore (x)
  :name "Data.Approximate.Numerics:blog from approximate-0.2.2.1"
  :precision binary64

  :herbie-target
  (/ 6.0 (/ (+ (+ x 1.0) (* 4.0 (sqrt x))) (- x 1.0)))

  (/ (* 6.0 (- x 1.0)) (+ (+ x 1.0) (* 4.0 (sqrt x)))))