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

Average Accuracy: 100.0% → 100.0%

Time: 8.0s

Precision: binary64

Cost: 960

• Unsound rule application detected in e-graph. Results may not be sound.

Math

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

↓

\[\begin{array}{l} t_0 := 2 - \left(x + y\right)\\ \frac{x}{t_0} - \frac{y}{t_0} \end{array} \]

FPCore

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

↓

(FPCore (x y)
 :precision binary64
 (let* ((t_0 (- 2.0 (+ x y)))) (- (/ x t_0) (/ y t_0))))

C

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

↓

double code(double x, double y) {
	double t_0 = 2.0 - (x + y);
	return (x / t_0) - (y / t_0);
}

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
    real(8) :: t_0
    t_0 = 2.0d0 - (x + y)
    code = (x / t_0) - (y / t_0)
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) {
	double t_0 = 2.0 - (x + y);
	return (x / t_0) - (y / t_0);
}

Python

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

↓

def code(x, y):
	t_0 = 2.0 - (x + y)
	return (x / t_0) - (y / t_0)

Julia

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

↓

function code(x, y)
	t_0 = Float64(2.0 - Float64(x + y))
	return Float64(Float64(x / t_0) - Float64(y / t_0))
end

MATLAB

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

↓

function tmp = code(x, y)
	t_0 = 2.0 - (x + y);
	tmp = (x / t_0) - (y / t_0);
end

Wolfram

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

↓

code[x_, y_] := Block[{t$95$0 = N[(2.0 - N[(x + y), $MachinePrecision]), $MachinePrecision]}, N[(N[(x / t$95$0), $MachinePrecision] - N[(y / t$95$0), $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. Simplified 100.0%

   \[\leadsto \color{blue}{\frac{x - y}{\left(2 - x\right) - y}} \]
   Proof

   [Start] 100.0	\[ \frac{x - y}{2 - \left(x + y\right)} \]
   associate--r+ [=>] 100.0	\[ \frac{x - y}{\color{blue}{\left(2 - x\right) - y}} \]

3. Applied egg-rr 100.0%

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

   [Start] 100.0	\[ \frac{x - y}{\left(2 - x\right) - y} \]
   div-sub [=>] 100.0	\[ \color{blue}{\frac{x}{\left(2 - x\right) - y} - \frac{y}{\left(2 - x\right) - y}} \]
   associate--l- [=>] 100.0	\[ \frac{x}{\color{blue}{2 - \left(x + y\right)}} - \frac{y}{\left(2 - x\right) - y} \]
   associate--l- [=>] 100.0	\[ \frac{x}{2 - \left(x + y\right)} - \frac{y}{\color{blue}{2 - \left(x + y\right)}} \]

4. Final simplification 100.0%

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

Alternatives

Alternative 1
Accuracy	73.4%
Cost	848

\[\begin{array}{l} t_0 := \frac{y}{y + -2}\\ \mathbf{if}\;x \leq -9.5 \cdot 10^{+108}:\\ \;\;\;\;-1\\ \mathbf{elif}\;x \leq -3 \cdot 10^{+38}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;x \leq -6.4 \cdot 10^{-52}:\\ \;\;\;\;\frac{x}{2 - x}\\ \mathbf{elif}\;x \leq 7.8 \cdot 10^{+62}:\\ \;\;\;\;t_0\\ \mathbf{else}:\\ \;\;\;\;-1\\ \end{array} \]

Alternative 2
Accuracy	61.5%
Cost	592

\[\begin{array}{l} \mathbf{if}\;x \leq -2 \cdot 10^{+110}:\\ \;\;\;\;-1\\ \mathbf{elif}\;x \leq -0.049:\\ \;\;\;\;1\\ \mathbf{elif}\;x \leq -8.2 \cdot 10^{-54}:\\ \;\;\;\;x \cdot 0.5\\ \mathbf{elif}\;x \leq 1.75 \cdot 10^{+61}:\\ \;\;\;\;1\\ \mathbf{else}:\\ \;\;\;\;-1\\ \end{array} \]

Alternative 3
Accuracy	74.0%
Cost	584

\[\begin{array}{l} \mathbf{if}\;y \leq -3.8 \cdot 10^{+39}:\\ \;\;\;\;1\\ \mathbf{elif}\;y \leq 2.4 \cdot 10^{+94}:\\ \;\;\;\;\frac{x}{2 - x}\\ \mathbf{else}:\\ \;\;\;\;1\\ \end{array} \]

Alternative 4
Accuracy	100.0%
Cost	576

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

Alternative 5
Accuracy	61.8%
Cost	328

\[\begin{array}{l} \mathbf{if}\;x \leq -6 \cdot 10^{+108}:\\ \;\;\;\;-1\\ \mathbf{elif}\;x \leq 2.45 \cdot 10^{+63}:\\ \;\;\;\;1\\ \mathbf{else}:\\ \;\;\;\;-1\\ \end{array} \]

Alternative 6
Accuracy	39.2%
Cost	64

\[-1 \]

Reproduce

herbie shell --seed 2023160 
(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))))