Linear.Projection:perspective from linear-1.19.1.3, B

Average Accuracy: 76.1% → 99.8%

Time: 3.9s

Precision: binary64

Cost: 841

Math

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

↓

\[\begin{array}{l} \mathbf{if}\;y \leq -1 \cdot 10^{+22} \lor \neg \left(y \leq 10^{-48}\right):\\ \;\;\;\;x \cdot \left(-2 \cdot \frac{y}{y - x}\right)\\ \mathbf{else}:\\ \;\;\;\;y \cdot \frac{x \cdot 2}{x - y}\\ \end{array} \]

FPCore

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

↓

(FPCore (x y)
 :precision binary64
 (if (or (<= y -1e+22) (not (<= y 1e-48)))
   (* x (* -2.0 (/ y (- y x))))
   (* y (/ (* x 2.0) (- x y)))))

C

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

↓

double code(double x, double y) {
	double tmp;
	if ((y <= -1e+22) || !(y <= 1e-48)) {
		tmp = x * (-2.0 * (y / (y - x)));
	} else {
		tmp = y * ((x * 2.0) / (x - y));
	}
	return tmp;
}

Fortran

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

↓

real(8) function code(x, y)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8) :: tmp
    if ((y <= (-1d+22)) .or. (.not. (y <= 1d-48))) then
        tmp = x * ((-2.0d0) * (y / (y - x)))
    else
        tmp = y * ((x * 2.0d0) / (x - y))
    end if
    code = tmp
end function

Java

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

↓

public static double code(double x, double y) {
	double tmp;
	if ((y <= -1e+22) || !(y <= 1e-48)) {
		tmp = x * (-2.0 * (y / (y - x)));
	} else {
		tmp = y * ((x * 2.0) / (x - y));
	}
	return tmp;
}

Python

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

↓

def code(x, y):
	tmp = 0
	if (y <= -1e+22) or not (y <= 1e-48):
		tmp = x * (-2.0 * (y / (y - x)))
	else:
		tmp = y * ((x * 2.0) / (x - y))
	return tmp

Julia

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

↓

function code(x, y)
	tmp = 0.0
	if ((y <= -1e+22) || !(y <= 1e-48))
		tmp = Float64(x * Float64(-2.0 * Float64(y / Float64(y - x))));
	else
		tmp = Float64(y * Float64(Float64(x * 2.0) / Float64(x - y)));
	end
	return tmp
end

MATLAB

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

↓

function tmp_2 = code(x, y)
	tmp = 0.0;
	if ((y <= -1e+22) || ~((y <= 1e-48)))
		tmp = x * (-2.0 * (y / (y - x)));
	else
		tmp = y * ((x * 2.0) / (x - y));
	end
	tmp_2 = tmp;
end

Wolfram

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

↓

code[x_, y_] := If[Or[LessEqual[y, -1e+22], N[Not[LessEqual[y, 1e-48]], $MachinePrecision]], N[(x * N[(-2.0 * N[(y / N[(y - x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(y * N[(N[(x * 2.0), $MachinePrecision] / N[(x - y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Target

Original	76.1%
Target	99.6%
Herbie	99.8%

\[\begin{array}{l} \mathbf{if}\;x < -1.7210442634149447 \cdot 10^{+81}:\\ \;\;\;\;\frac{2 \cdot x}{x - y} \cdot y\\ \mathbf{elif}\;x < 83645045635564430:\\ \;\;\;\;\frac{x \cdot 2}{\frac{x - y}{y}}\\ \mathbf{else}:\\ \;\;\;\;\frac{2 \cdot x}{x - y} \cdot y\\ \end{array} \]

Derivation

1. Split input into 2 regimes

2. if y < -1e22 or 9.9999999999999997e-49 < y

   1. Initial program 74.9%

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

   2. Simplified 99.8%

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

      [Start] 74.9	\[ \frac{\left(x \cdot 2\right) \cdot y}{x - y} \]
      *-lft-identity [<=] 74.9	\[ \color{blue}{1 \cdot \frac{\left(x \cdot 2\right) \cdot y}{x - y}} \]
      *-inverses [<=] 74.9	\[ \color{blue}{\frac{y}{y}} \cdot \frac{\left(x \cdot 2\right) \cdot y}{x - y} \]
      associate-/l* [=>] 99.7	\[ \frac{y}{y} \cdot \color{blue}{\frac{x \cdot 2}{\frac{x - y}{y}}} \]
      *-commutative [=>] 99.7	\[ \frac{y}{y} \cdot \frac{\color{blue}{2 \cdot x}}{\frac{x - y}{y}} \]
      associate-*l/ [<=] 99.6	\[ \frac{y}{y} \cdot \color{blue}{\left(\frac{2}{\frac{x - y}{y}} \cdot x\right)} \]
      associate-*r* [=>] 99.6	\[ \color{blue}{\left(\frac{y}{y} \cdot \frac{2}{\frac{x - y}{y}}\right) \cdot x} \]
      *-commutative [<=] 99.6	\[ \color{blue}{\left(\frac{2}{\frac{x - y}{y}} \cdot \frac{y}{y}\right)} \cdot x \]
      *-commutative [=>] 99.6	\[ \color{blue}{x \cdot \left(\frac{2}{\frac{x - y}{y}} \cdot \frac{y}{y}\right)} \]
      *-inverses [=>] 99.6	\[ x \cdot \left(\frac{2}{\frac{x - y}{y}} \cdot \color{blue}{1}\right) \]
      *-rgt-identity [=>] 99.6	\[ x \cdot \color{blue}{\frac{2}{\frac{x - y}{y}}} \]
      associate-/l* [<=] 99.7	\[ x \cdot \color{blue}{\frac{2 \cdot y}{x - y}} \]
      sub-neg [=>] 99.7	\[ x \cdot \frac{2 \cdot y}{\color{blue}{x + \left(-y\right)}} \]
      +-commutative [=>] 99.7	\[ x \cdot \frac{2 \cdot y}{\color{blue}{\left(-y\right) + x}} \]
      neg-sub0 [=>] 99.7	\[ x \cdot \frac{2 \cdot y}{\color{blue}{\left(0 - y\right)} + x} \]
      associate-+l- [=>] 99.7	\[ x \cdot \frac{2 \cdot y}{\color{blue}{0 - \left(y - x\right)}} \]
      sub0-neg [=>] 99.7	\[ x \cdot \frac{2 \cdot y}{\color{blue}{-\left(y - x\right)}} \]
      neg-mul-1 [=>] 99.7	\[ x \cdot \frac{2 \cdot y}{\color{blue}{-1 \cdot \left(y - x\right)}} \]
      times-frac [=>] 99.8	\[ x \cdot \color{blue}{\left(\frac{2}{-1} \cdot \frac{y}{y - x}\right)} \]
      metadata-eval [=>] 99.8	\[ x \cdot \left(\color{blue}{-2} \cdot \frac{y}{y - x}\right) \]

   if -1e22 < y < 9.9999999999999997e-49

   1. Initial program 77.6%

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

   2. Simplified 99.8%

      \[\leadsto \color{blue}{\frac{x \cdot 2}{x - y} \cdot y} \]
      Proof

      [Start] 77.6	\[ \frac{\left(x \cdot 2\right) \cdot y}{x - y} \]
      associate-*l/ [<=] 99.8	\[ \color{blue}{\frac{x \cdot 2}{x - y} \cdot y} \]

3. Recombined 2 regimes into one program.

4. Final simplification 99.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y \leq -1 \cdot 10^{+22} \lor \neg \left(y \leq 10^{-48}\right):\\ \;\;\;\;x \cdot \left(-2 \cdot \frac{y}{y - x}\right)\\ \mathbf{else}:\\ \;\;\;\;y \cdot \frac{x \cdot 2}{x - y}\\ \end{array} \]

Alternatives

Alternative 1
Accuracy	94.0%
Cost	841

\[\begin{array}{l} \mathbf{if}\;y \leq -8 \cdot 10^{-134} \lor \neg \left(y \leq 1.1 \cdot 10^{-215}\right):\\ \;\;\;\;x \cdot \left(-2 \cdot \frac{y}{y - x}\right)\\ \mathbf{else}:\\ \;\;\;\;y \cdot 2\\ \end{array} \]

Alternative 2
Accuracy	75.3%
Cost	456

\[\begin{array}{l} \mathbf{if}\;y \leq -1.55 \cdot 10^{-6}:\\ \;\;\;\;x \cdot -2\\ \mathbf{elif}\;y \leq 5.4 \cdot 10^{-47}:\\ \;\;\;\;y \cdot 2\\ \mathbf{else}:\\ \;\;\;\;x \cdot -2\\ \end{array} \]

Alternative 3
Accuracy	50.1%
Cost	192

\[y \cdot 2 \]

Reproduce

herbie shell --seed 2023133 
(FPCore (x y)
  :name "Linear.Projection:perspective from linear-1.19.1.3, B"
  :precision binary64

  :herbie-target
  (if (< x -1.7210442634149447e+81) (* (/ (* 2.0 x) (- x y)) y) (if (< x 83645045635564430.0) (/ (* x 2.0) (/ (- x y) y)) (* (/ (* 2.0 x) (- x y)) y)))

  (/ (* (* x 2.0) y) (- x y)))