Data.Colour.RGB:hslsv from colour-2.3.3, C

Percentage Accurate: 100.0% → 100.0%

Time: 8.7s

Precision: binary64

Cost: 576

Math

\[\frac{x - y}{2 - \left(x + y\right)} \]

↓

\[\frac{x - y}{2 - \left(x + y\right)} \]

FPCore

(FPCore (x y) :precision binary64 (/ (- x y) (- 2.0 (+ x y))))

↓

(FPCore (x y) :precision binary64 (/ (- x y) (- 2.0 (+ x y))))

C

double code(double x, double y) {
	return (x - y) / (2.0 - (x + y));
}

↓

double code(double x, double y) {
	return (x - y) / (2.0 - (x + y));
}

Fortran

real(8) function code(x, y)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    code = (x - y) / (2.0d0 - (x + y))
end function

↓

real(8) function code(x, y)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    code = (x - y) / (2.0d0 - (x + y))
end function

Java

public static double code(double x, double y) {
	return (x - y) / (2.0 - (x + y));
}

↓

public static double code(double x, double y) {
	return (x - y) / (2.0 - (x + y));
}

Python

def code(x, y):
	return (x - y) / (2.0 - (x + y))

↓

def code(x, y):
	return (x - y) / (2.0 - (x + y))

Julia

function code(x, y)
	return Float64(Float64(x - y) / Float64(2.0 - Float64(x + y)))
end

↓

function code(x, y)
	return Float64(Float64(x - y) / Float64(2.0 - Float64(x + y)))
end

MATLAB

function tmp = code(x, y)
	tmp = (x - y) / (2.0 - (x + y));
end

↓

function tmp = code(x, y)
	tmp = (x - y) / (2.0 - (x + y));
end

Wolfram

code[x_, y_] := N[(N[(x - y), $MachinePrecision] / N[(2.0 - N[(x + y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

↓

code[x_, y_] := N[(N[(x - y), $MachinePrecision] / N[(2.0 - N[(x + y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Target

Original	100.0%
Target	100.0%
Herbie	100.0%

\[\frac{x}{2 - \left(x + y\right)} - \frac{y}{2 - \left(x + y\right)} \]

Derivation

1. Initial program 100.0%

   \[\frac{x - y}{2 - \left(x + y\right)} \]

2. Final simplification 100.0%

   \[\leadsto \frac{x - y}{2 - \left(x + y\right)} \]

Alternatives

Alternative 1
Accuracy	100.0%
Cost	576

\[\frac{x - y}{2 - \left(x + y\right)} \]

Alternative 2
Accuracy	74.0%
Cost	712

\[\begin{array}{l} \mathbf{if}\;y \leq -4.6 \cdot 10^{-64}:\\ \;\;\;\;\frac{-y}{2 - y}\\ \mathbf{elif}\;y \leq 8.6 \cdot 10^{+56}:\\ \;\;\;\;\frac{x}{2 - x}\\ \mathbf{else}:\\ \;\;\;\;1 + \frac{x \cdot -2}{y}\\ \end{array} \]

Alternative 3
Accuracy	61.4%
Cost	592

\[\begin{array}{l} \mathbf{if}\;y \leq -1.1 \cdot 10^{+55}:\\ \;\;\;\;1\\ \mathbf{elif}\;y \leq -3.4 \cdot 10^{-292}:\\ \;\;\;\;-1\\ \mathbf{elif}\;y \leq 1.7 \cdot 10^{-276}:\\ \;\;\;\;x \cdot 0.5\\ \mathbf{elif}\;y \leq 6.5 \cdot 10^{+56}:\\ \;\;\;\;-1\\ \mathbf{else}:\\ \;\;\;\;1\\ \end{array} \]

Alternative 4
Accuracy	61.9%
Cost	592

\[\begin{array}{l} \mathbf{if}\;y \leq -48000:\\ \;\;\;\;1 + \frac{2}{y}\\ \mathbf{elif}\;y \leq -6.5 \cdot 10^{-292}:\\ \;\;\;\;-1\\ \mathbf{elif}\;y \leq 6.2 \cdot 10^{-274}:\\ \;\;\;\;x \cdot 0.5\\ \mathbf{elif}\;y \leq 1.05 \cdot 10^{+57}:\\ \;\;\;\;-1\\ \mathbf{else}:\\ \;\;\;\;1\\ \end{array} \]

Alternative 5
Accuracy	74.1%
Cost	584

\[\begin{array}{l} \mathbf{if}\;y \leq -100000:\\ \;\;\;\;1 + \frac{2}{y}\\ \mathbf{elif}\;y \leq 3 \cdot 10^{+64}:\\ \;\;\;\;\frac{x}{2 - x}\\ \mathbf{else}:\\ \;\;\;\;1\\ \end{array} \]

Alternative 6
Accuracy	73.6%
Cost	584

\[\begin{array}{l} \mathbf{if}\;y \leq -3.2 \cdot 10^{-65}:\\ \;\;\;\;\frac{-y}{2 - y}\\ \mathbf{elif}\;y \leq 1.65 \cdot 10^{+65}:\\ \;\;\;\;\frac{x}{2 - x}\\ \mathbf{else}:\\ \;\;\;\;1\\ \end{array} \]

Alternative 7
Accuracy	61.1%
Cost	328

\[\begin{array}{l} \mathbf{if}\;y \leq -6.8 \cdot 10^{+53}:\\ \;\;\;\;1\\ \mathbf{elif}\;y \leq 8 \cdot 10^{+56}:\\ \;\;\;\;-1\\ \mathbf{else}:\\ \;\;\;\;1\\ \end{array} \]

Alternative 8
Accuracy	37.8%
Cost	64

\[-1 \]

Reproduce

herbie shell --seed 2023263 
(FPCore (x y)
  :name "Data.Colour.RGB:hslsv from colour-2.3.3, C"
  :precision binary64

  :herbie-target
  (- (/ x (- 2.0 (+ x y))) (/ y (- 2.0 (+ x y))))

  (/ (- x y) (- 2.0 (+ x y))))