Diagrams.TwoD.Apollonian:initialConfig from diagrams-contrib-1.3.0.5, B

Average Error: 24.6 → 0.8

Time: 4.9s

Precision: binary64

Cost: 964

Math

\[x \cdot \sqrt{y \cdot y - z \cdot z} \]

↓

\[\begin{array}{l} \mathbf{if}\;y \leq -1.4 \cdot 10^{-240}:\\ \;\;\;\;y \cdot \left(-x\right)\\ \mathbf{else}:\\ \;\;\;\;x \cdot \left(\left(z \cdot \frac{z}{y}\right) \cdot -0.5\right) + y \cdot x\\ \end{array} \]

FPCore

(FPCore (x y z) :precision binary64 (* x (sqrt (- (* y y) (* z z)))))

↓

(FPCore (x y z)
 :precision binary64
 (if (<= y -1.4e-240) (* y (- x)) (+ (* x (* (* z (/ z y)) -0.5)) (* y x))))

C

double code(double x, double y, double z) {
	return x * sqrt(((y * y) - (z * z)));
}

↓

double code(double x, double y, double z) {
	double tmp;
	if (y <= -1.4e-240) {
		tmp = y * -x;
	} else {
		tmp = (x * ((z * (z / y)) * -0.5)) + (y * x);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    code = x * sqrt(((y * y) - (z * z)))
end function

↓

real(8) function code(x, y, z)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8) :: tmp
    if (y <= (-1.4d-240)) then
        tmp = y * -x
    else
        tmp = (x * ((z * (z / y)) * (-0.5d0))) + (y * x)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z) {
	return x * Math.sqrt(((y * y) - (z * z)));
}

↓

public static double code(double x, double y, double z) {
	double tmp;
	if (y <= -1.4e-240) {
		tmp = y * -x;
	} else {
		tmp = (x * ((z * (z / y)) * -0.5)) + (y * x);
	}
	return tmp;
}

Python

def code(x, y, z):
	return x * math.sqrt(((y * y) - (z * z)))

↓

def code(x, y, z):
	tmp = 0
	if y <= -1.4e-240:
		tmp = y * -x
	else:
		tmp = (x * ((z * (z / y)) * -0.5)) + (y * x)
	return tmp

Julia

function code(x, y, z)
	return Float64(x * sqrt(Float64(Float64(y * y) - Float64(z * z))))
end

↓

function code(x, y, z)
	tmp = 0.0
	if (y <= -1.4e-240)
		tmp = Float64(y * Float64(-x));
	else
		tmp = Float64(Float64(x * Float64(Float64(z * Float64(z / y)) * -0.5)) + Float64(y * x));
	end
	return tmp
end

MATLAB

function tmp = code(x, y, z)
	tmp = x * sqrt(((y * y) - (z * z)));
end

↓

function tmp_2 = code(x, y, z)
	tmp = 0.0;
	if (y <= -1.4e-240)
		tmp = y * -x;
	else
		tmp = (x * ((z * (z / y)) * -0.5)) + (y * x);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_] := N[(x * N[Sqrt[N[(N[(y * y), $MachinePrecision] - N[(z * z), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]

↓

code[x_, y_, z_] := If[LessEqual[y, -1.4e-240], N[(y * (-x)), $MachinePrecision], N[(N[(x * N[(N[(z * N[(z / y), $MachinePrecision]), $MachinePrecision] * -0.5), $MachinePrecision]), $MachinePrecision] + N[(y * x), $MachinePrecision]), $MachinePrecision]]

Target

Original	24.6
Target	0.6
Herbie	0.8

\[\begin{array}{l} \mathbf{if}\;y < 2.5816096488251695 \cdot 10^{-278}:\\ \;\;\;\;-x \cdot y\\ \mathbf{else}:\\ \;\;\;\;x \cdot \left(\sqrt{y + z} \cdot \sqrt{y - z}\right)\\ \end{array} \]

Derivation

1. Split input into 2 regimes

2. if y < -1.4e-240

   1. Initial program 24.8

      \[x \cdot \sqrt{y \cdot y - z \cdot z} \]

   2. Taylor expanded in y around -inf 0.6

      \[\leadsto \color{blue}{-1 \cdot \left(y \cdot x\right)} \]

   3. Simplified 0.6

      \[\leadsto \color{blue}{y \cdot \left(-x\right)} \]
      Proof
      (*.f64 y (neg.f64 x)): 0 points increase in error, 0 points decrease in error
      (Rewrite<= distribute-rgt-neg-in_binary64 (neg.f64 (*.f64 y x))): 0 points increase in error, 0 points decrease in error
      (Rewrite<= mul-1-neg_binary64 (*.f64 -1 (*.f64 y x))): 0 points increase in error, 0 points decrease in error

   if -1.4e-240 < y

   1. Initial program 24.5

      \[x \cdot \sqrt{y \cdot y - z \cdot z} \]

   2. Taylor expanded in y around inf 3.6

      \[\leadsto x \cdot \color{blue}{\left(y + -0.5 \cdot \frac{{z}^{2}}{y}\right)} \]

   3. Simplified 1.0

      \[\leadsto x \cdot \color{blue}{\mathsf{fma}\left(-0.5, \frac{z}{y} \cdot z, y\right)} \]
      Proof
      (fma.f64 -1/2 (*.f64 (/.f64 z y) z) y): 0 points increase in error, 0 points decrease in error
      (fma.f64 -1/2 (Rewrite<= associate-/r/_binary64 (/.f64 z (/.f64 y z))) y): 0 points increase in error, 0 points decrease in error
      (fma.f64 -1/2 (Rewrite<= associate-/l*_binary64 (/.f64 (*.f64 z z) y)) y): 9 points increase in error, 0 points decrease in error
      (fma.f64 -1/2 (/.f64 (Rewrite<= unpow2_binary64 (pow.f64 z 2)) y) y): 0 points increase in error, 0 points decrease in error
      (Rewrite<= fma-def_binary64 (+.f64 (*.f64 -1/2 (/.f64 (pow.f64 z 2) y)) y)): 0 points increase in error, 0 points decrease in error
      (Rewrite<= +-commutative_binary64 (+.f64 y (*.f64 -1/2 (/.f64 (pow.f64 z 2) y)))): 0 points increase in error, 0 points decrease in error

   4. Applied egg-rr 1.0

      \[\leadsto \color{blue}{\left(\left(z \cdot \frac{z}{y}\right) \cdot -0.5\right) \cdot x + y \cdot x} \]
3. Recombined 2 regimes into one program.

4. Final simplification 0.8

   \[\leadsto \begin{array}{l} \mathbf{if}\;y \leq -1.4 \cdot 10^{-240}:\\ \;\;\;\;y \cdot \left(-x\right)\\ \mathbf{else}:\\ \;\;\;\;x \cdot \left(\left(z \cdot \frac{z}{y}\right) \cdot -0.5\right) + y \cdot x\\ \end{array} \]

Alternatives

Alternative 1
Error	1.1
Cost	388

\[\begin{array}{l} \mathbf{if}\;y \leq -1.45 \cdot 10^{-223}:\\ \;\;\;\;y \cdot \left(-x\right)\\ \mathbf{else}:\\ \;\;\;\;y \cdot x\\ \end{array} \]

Alternative 2
Error	30.1
Cost	192

\[y \cdot x \]

Reproduce

herbie shell --seed 2022308 
(FPCore (x y z)
  :name "Diagrams.TwoD.Apollonian:initialConfig from diagrams-contrib-1.3.0.5, B"
  :precision binary64

  :herbie-target
  (if (< y 2.5816096488251695e-278) (- (* x y)) (* x (* (sqrt (+ y z)) (sqrt (- y z)))))

  (* x (sqrt (- (* y y) (* z z)))))