Linear.Quaternion:$clog from linear-1.19.1.3

Percentage Accurate: 70.1% → 99.9%

Time: 5.7s

Precision: binary64

Cost: 6984

Math

\[\sqrt{x \cdot x + y} \]

↓

\[\begin{array}{l} \mathbf{if}\;x \leq -2 \cdot 10^{+154}:\\ \;\;\;\;-x\\ \mathbf{elif}\;x \leq 1.2 \cdot 10^{+112}:\\ \;\;\;\;\sqrt{x \cdot x + y}\\ \mathbf{else}:\\ \;\;\;\;x\\ \end{array} \]

FPCore

(FPCore (x y) :precision binary64 (sqrt (+ (* x x) y)))

↓

(FPCore (x y)
 :precision binary64
 (if (<= x -2e+154) (- x) (if (<= x 1.2e+112) (sqrt (+ (* x x) y)) x)))

C

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

↓

double code(double x, double y) {
	double tmp;
	if (x <= -2e+154) {
		tmp = -x;
	} else if (x <= 1.2e+112) {
		tmp = sqrt(((x * x) + y));
	} else {
		tmp = x;
	}
	return tmp;
}

Fortran

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

↓

real(8) function code(x, y)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8) :: tmp
    if (x <= (-2d+154)) then
        tmp = -x
    else if (x <= 1.2d+112) then
        tmp = sqrt(((x * x) + y))
    else
        tmp = x
    end if
    code = tmp
end function

Java

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

↓

public static double code(double x, double y) {
	double tmp;
	if (x <= -2e+154) {
		tmp = -x;
	} else if (x <= 1.2e+112) {
		tmp = Math.sqrt(((x * x) + y));
	} else {
		tmp = x;
	}
	return tmp;
}

Python

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

↓

def code(x, y):
	tmp = 0
	if x <= -2e+154:
		tmp = -x
	elif x <= 1.2e+112:
		tmp = math.sqrt(((x * x) + y))
	else:
		tmp = x
	return tmp

Julia

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

↓

function code(x, y)
	tmp = 0.0
	if (x <= -2e+154)
		tmp = Float64(-x);
	elseif (x <= 1.2e+112)
		tmp = sqrt(Float64(Float64(x * x) + y));
	else
		tmp = x;
	end
	return tmp
end

MATLAB

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

↓

function tmp_2 = code(x, y)
	tmp = 0.0;
	if (x <= -2e+154)
		tmp = -x;
	elseif (x <= 1.2e+112)
		tmp = sqrt(((x * x) + y));
	else
		tmp = x;
	end
	tmp_2 = tmp;
end

Wolfram

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

↓

code[x_, y_] := If[LessEqual[x, -2e+154], (-x), If[LessEqual[x, 1.2e+112], N[Sqrt[N[(N[(x * x), $MachinePrecision] + y), $MachinePrecision]], $MachinePrecision], x]]

Target

Original	70.1%
Target	99.4%
Herbie	99.9%

\[\begin{array}{l} \mathbf{if}\;x < -1.5097698010472593 \cdot 10^{+153}:\\ \;\;\;\;-\left(0.5 \cdot \frac{y}{x} + x\right)\\ \mathbf{elif}\;x < 5.582399551122541 \cdot 10^{+57}:\\ \;\;\;\;\sqrt{x \cdot x + y}\\ \mathbf{else}:\\ \;\;\;\;0.5 \cdot \frac{y}{x} + x\\ \end{array} \]

Derivation

1. Split input into 3 regimes

2. if x < -2.00000000000000007e154

   1. Initial program 7.3%

      \[\sqrt{x \cdot x + y} \]

   2. Taylor expanded in x around -inf 100.0%

      \[\leadsto \color{blue}{-1 \cdot x} \]

   3. Simplified 100.0%

      \[\leadsto \color{blue}{-x} \]
      Step-by-step derivation

      [Start] 100.0%	\[ -1 \cdot x \]
      mul-1-neg [=>] 100.0%	\[ \color{blue}{-x} \]

   if -2.00000000000000007e154 < x < 1.2e112

   1. Initial program 100.0%

      \[\sqrt{x \cdot x + y} \]

   if 1.2e112 < x

   1. Initial program 26.7%

      \[\sqrt{x \cdot x + y} \]

   2. Taylor expanded in x around inf 100.0%

      \[\leadsto \color{blue}{x} \]
3. Recombined 3 regimes into one program.

4. Final simplification 100.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -2 \cdot 10^{+154}:\\ \;\;\;\;-x\\ \mathbf{elif}\;x \leq 1.2 \cdot 10^{+112}:\\ \;\;\;\;\sqrt{x \cdot x + y}\\ \mathbf{else}:\\ \;\;\;\;x\\ \end{array} \]

Alternatives

Alternative 1
Accuracy	99.9%
Cost	6984

\[\begin{array}{l} \mathbf{if}\;x \leq -2 \cdot 10^{+154}:\\ \;\;\;\;-x\\ \mathbf{elif}\;x \leq 1.2 \cdot 10^{+112}:\\ \;\;\;\;\sqrt{x \cdot x + y}\\ \mathbf{else}:\\ \;\;\;\;x\\ \end{array} \]

Alternative 2
Accuracy	89.0%
Cost	6728

\[\begin{array}{l} \mathbf{if}\;x \leq -8.8 \cdot 10^{-36}:\\ \;\;\;\;\frac{y \cdot -0.5}{x} - x\\ \mathbf{elif}\;x \leq 2.8 \cdot 10^{-79}:\\ \;\;\;\;\sqrt{y}\\ \mathbf{else}:\\ \;\;\;\;x + 0.5 \cdot \frac{y}{x}\\ \end{array} \]

Alternative 3
Accuracy	67.2%
Cost	580

\[\begin{array}{l} \mathbf{if}\;x \leq -4 \cdot 10^{-310}:\\ \;\;\;\;-x\\ \mathbf{else}:\\ \;\;\;\;x + 0.5 \cdot \frac{y}{x}\\ \end{array} \]

Alternative 4
Accuracy	67.4%
Cost	580

\[\begin{array}{l} \mathbf{if}\;x \leq -4 \cdot 10^{-310}:\\ \;\;\;\;\frac{y \cdot -0.5}{x} - x\\ \mathbf{else}:\\ \;\;\;\;x + 0.5 \cdot \frac{y}{x}\\ \end{array} \]

Alternative 5
Accuracy	67.0%
Cost	260

\[\begin{array}{l} \mathbf{if}\;x \leq -4 \cdot 10^{-310}:\\ \;\;\;\;-x\\ \mathbf{else}:\\ \;\;\;\;x\\ \end{array} \]

Alternative 6
Accuracy	34.6%
Cost	64

\[x \]

Reproduce

herbie shell --seed 2023272 
(FPCore (x y)
  :name "Linear.Quaternion:$clog from linear-1.19.1.3"
  :precision binary64

  :herbie-target
  (if (< x -1.5097698010472593e+153) (- (+ (* 0.5 (/ y x)) x)) (if (< x 5.582399551122541e+57) (sqrt (+ (* x x) y)) (+ (* 0.5 (/ y x)) x)))

  (sqrt (+ (* x x) y)))