_divideComplex, real part

Percentage Accurate: 61.9% → 85.4%

Time: 12.0s

Alternatives: 12

Speedup: 2.1×

Specification

Math

\[\begin{array}{l} \\ \frac{x.re \cdot y.re + x.im \cdot y.im}{y.re \cdot y.re + y.im \cdot y.im} \end{array} \]

FPCore

(FPCore (x.re x.im y.re y.im)
 :precision binary64
 (/ (+ (* x.re y.re) (* x.im y.im)) (+ (* y.re y.re) (* y.im y.im))))

C

double code(double x_46_re, double x_46_im, double y_46_re, double y_46_im) {
	return ((x_46_re * y_46_re) + (x_46_im * y_46_im)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
}

Fortran

real(8) function code(x_46re, x_46im, y_46re, y_46im)
    real(8), intent (in) :: x_46re
    real(8), intent (in) :: x_46im
    real(8), intent (in) :: y_46re
    real(8), intent (in) :: y_46im
    code = ((x_46re * y_46re) + (x_46im * y_46im)) / ((y_46re * y_46re) + (y_46im * y_46im))
end function

Java

public static double code(double x_46_re, double x_46_im, double y_46_re, double y_46_im) {
	return ((x_46_re * y_46_re) + (x_46_im * y_46_im)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
}

Python

def code(x_46_re, x_46_im, y_46_re, y_46_im):
	return ((x_46_re * y_46_re) + (x_46_im * y_46_im)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im))

Julia

function code(x_46_re, x_46_im, y_46_re, y_46_im)
	return Float64(Float64(Float64(x_46_re * y_46_re) + Float64(x_46_im * y_46_im)) / Float64(Float64(y_46_re * y_46_re) + Float64(y_46_im * y_46_im)))
end

MATLAB

function tmp = code(x_46_re, x_46_im, y_46_re, y_46_im)
	tmp = ((x_46_re * y_46_re) + (x_46_im * y_46_im)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
end

Wolfram

code[x$46$re_, x$46$im_, y$46$re_, y$46$im_] := N[(N[(N[(x$46$re * y$46$re), $MachinePrecision] + N[(x$46$im * y$46$im), $MachinePrecision]), $MachinePrecision] / N[(N[(y$46$re * y$46$re), $MachinePrecision] + N[(y$46$im * y$46$im), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Initial Program: 61.9% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ \frac{x.re \cdot y.re + x.im \cdot y.im}{y.re \cdot y.re + y.im \cdot y.im} \end{array} \]

FPCore

(FPCore (x.re x.im y.re y.im)
 :precision binary64
 (/ (+ (* x.re y.re) (* x.im y.im)) (+ (* y.re y.re) (* y.im y.im))))

C

double code(double x_46_re, double x_46_im, double y_46_re, double y_46_im) {
	return ((x_46_re * y_46_re) + (x_46_im * y_46_im)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
}

Fortran

real(8) function code(x_46re, x_46im, y_46re, y_46im)
    real(8), intent (in) :: x_46re
    real(8), intent (in) :: x_46im
    real(8), intent (in) :: y_46re
    real(8), intent (in) :: y_46im
    code = ((x_46re * y_46re) + (x_46im * y_46im)) / ((y_46re * y_46re) + (y_46im * y_46im))
end function

Java

public static double code(double x_46_re, double x_46_im, double y_46_re, double y_46_im) {
	return ((x_46_re * y_46_re) + (x_46_im * y_46_im)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
}

Python

def code(x_46_re, x_46_im, y_46_re, y_46_im):
	return ((x_46_re * y_46_re) + (x_46_im * y_46_im)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im))

Julia

function code(x_46_re, x_46_im, y_46_re, y_46_im)
	return Float64(Float64(Float64(x_46_re * y_46_re) + Float64(x_46_im * y_46_im)) / Float64(Float64(y_46_re * y_46_re) + Float64(y_46_im * y_46_im)))
end

MATLAB

function tmp = code(x_46_re, x_46_im, y_46_re, y_46_im)
	tmp = ((x_46_re * y_46_re) + (x_46_im * y_46_im)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
end

Wolfram

code[x$46$re_, x$46$im_, y$46$re_, y$46$im_] := N[(N[(N[(x$46$re * y$46$re), $MachinePrecision] + N[(x$46$im * y$46$im), $MachinePrecision]), $MachinePrecision] / N[(N[(y$46$re * y$46$re), $MachinePrecision] + N[(y$46$im * y$46$im), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Alternative 1: 85.4% accurate, 0.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \frac{\frac{\mathsf{fma}\left(x.re, y.re, x.im \cdot y.im\right)}{\mathsf{hypot}\left(y.re, y.im\right)}}{\mathsf{hypot}\left(y.re, y.im\right)}\\ \mathbf{if}\;y.re \leq -4.6 \cdot 10^{+86}:\\ \;\;\;\;\frac{\frac{-x.im}{\frac{y.re}{y.im}} - x.re}{\mathsf{hypot}\left(y.re, y.im\right)}\\ \mathbf{elif}\;y.re \leq -1.9 \cdot 10^{-49}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;y.re \leq 2.2 \cdot 10^{-246}:\\ \;\;\;\;\frac{x.im}{y.im} + \frac{\frac{y.re \cdot x.re}{y.im}}{y.im}\\ \mathbf{elif}\;y.re \leq 1.75 \cdot 10^{+93}:\\ \;\;\;\;t_0\\ \mathbf{else}:\\ \;\;\;\;\frac{x.re + \frac{x.im}{\frac{y.re}{y.im}}}{\mathsf{hypot}\left(y.re, y.im\right)}\\ \end{array} \end{array} \]

FPCore

(FPCore (x.re x.im y.re y.im)
 :precision binary64
 (let* ((t_0
         (/
          (/ (fma x.re y.re (* x.im y.im)) (hypot y.re y.im))
          (hypot y.re y.im))))
   (if (<= y.re -4.6e+86)
     (/ (- (/ (- x.im) (/ y.re y.im)) x.re) (hypot y.re y.im))
     (if (<= y.re -1.9e-49)
       t_0
       (if (<= y.re 2.2e-246)
         (+ (/ x.im y.im) (/ (/ (* y.re x.re) y.im) y.im))
         (if (<= y.re 1.75e+93)
           t_0
           (/ (+ x.re (/ x.im (/ y.re y.im))) (hypot y.re y.im))))))))

C

double code(double x_46_re, double x_46_im, double y_46_re, double y_46_im) {
	double t_0 = (fma(x_46_re, y_46_re, (x_46_im * y_46_im)) / hypot(y_46_re, y_46_im)) / hypot(y_46_re, y_46_im);
	double tmp;
	if (y_46_re <= -4.6e+86) {
		tmp = ((-x_46_im / (y_46_re / y_46_im)) - x_46_re) / hypot(y_46_re, y_46_im);
	} else if (y_46_re <= -1.9e-49) {
		tmp = t_0;
	} else if (y_46_re <= 2.2e-246) {
		tmp = (x_46_im / y_46_im) + (((y_46_re * x_46_re) / y_46_im) / y_46_im);
	} else if (y_46_re <= 1.75e+93) {
		tmp = t_0;
	} else {
		tmp = (x_46_re + (x_46_im / (y_46_re / y_46_im))) / hypot(y_46_re, y_46_im);
	}
	return tmp;
}

Julia

function code(x_46_re, x_46_im, y_46_re, y_46_im)
	t_0 = Float64(Float64(fma(x_46_re, y_46_re, Float64(x_46_im * y_46_im)) / hypot(y_46_re, y_46_im)) / hypot(y_46_re, y_46_im))
	tmp = 0.0
	if (y_46_re <= -4.6e+86)
		tmp = Float64(Float64(Float64(Float64(-x_46_im) / Float64(y_46_re / y_46_im)) - x_46_re) / hypot(y_46_re, y_46_im));
	elseif (y_46_re <= -1.9e-49)
		tmp = t_0;
	elseif (y_46_re <= 2.2e-246)
		tmp = Float64(Float64(x_46_im / y_46_im) + Float64(Float64(Float64(y_46_re * x_46_re) / y_46_im) / y_46_im));
	elseif (y_46_re <= 1.75e+93)
		tmp = t_0;
	else
		tmp = Float64(Float64(x_46_re + Float64(x_46_im / Float64(y_46_re / y_46_im))) / hypot(y_46_re, y_46_im));
	end
	return tmp
end

Wolfram

code[x$46$re_, x$46$im_, y$46$re_, y$46$im_] := Block[{t$95$0 = N[(N[(N[(x$46$re * y$46$re + N[(x$46$im * y$46$im), $MachinePrecision]), $MachinePrecision] / N[Sqrt[y$46$re ^ 2 + y$46$im ^ 2], $MachinePrecision]), $MachinePrecision] / N[Sqrt[y$46$re ^ 2 + y$46$im ^ 2], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y$46$re, -4.6e+86], N[(N[(N[((-x$46$im) / N[(y$46$re / y$46$im), $MachinePrecision]), $MachinePrecision] - x$46$re), $MachinePrecision] / N[Sqrt[y$46$re ^ 2 + y$46$im ^ 2], $MachinePrecision]), $MachinePrecision], If[LessEqual[y$46$re, -1.9e-49], t$95$0, If[LessEqual[y$46$re, 2.2e-246], N[(N[(x$46$im / y$46$im), $MachinePrecision] + N[(N[(N[(y$46$re * x$46$re), $MachinePrecision] / y$46$im), $MachinePrecision] / y$46$im), $MachinePrecision]), $MachinePrecision], If[LessEqual[y$46$re, 1.75e+93], t$95$0, N[(N[(x$46$re + N[(x$46$im / N[(y$46$re / y$46$im), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[Sqrt[y$46$re ^ 2 + y$46$im ^ 2], $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Alternative 2: 78.4% accurate, 0.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y.re \leq -4.5 \cdot 10^{+86}:\\ \;\;\;\;\frac{\frac{-x.im}{\frac{y.re}{y.im}} - x.re}{\mathsf{hypot}\left(y.re, y.im\right)}\\ \mathbf{elif}\;y.re \leq -1.05 \cdot 10^{-40}:\\ \;\;\;\;\frac{x.im \cdot y.im + y.re \cdot x.re}{y.re \cdot y.re + y.im \cdot y.im}\\ \mathbf{elif}\;y.re \leq 6.8 \cdot 10^{-199}:\\ \;\;\;\;\frac{x.im}{y.im} + \frac{\frac{y.re \cdot x.re}{y.im}}{y.im}\\ \mathbf{elif}\;y.re \leq 6 \cdot 10^{+70}:\\ \;\;\;\;\frac{y.im}{\mathsf{hypot}\left(y.re, y.im\right)} \cdot \frac{x.im}{\mathsf{hypot}\left(y.re, y.im\right)}\\ \mathbf{else}:\\ \;\;\;\;\frac{x.re + \frac{x.im}{\frac{y.re}{y.im}}}{\mathsf{hypot}\left(y.re, y.im\right)}\\ \end{array} \end{array} \]

FPCore

(FPCore (x.re x.im y.re y.im)
 :precision binary64
 (if (<= y.re -4.5e+86)
   (/ (- (/ (- x.im) (/ y.re y.im)) x.re) (hypot y.re y.im))
   (if (<= y.re -1.05e-40)
     (/ (+ (* x.im y.im) (* y.re x.re)) (+ (* y.re y.re) (* y.im y.im)))
     (if (<= y.re 6.8e-199)
       (+ (/ x.im y.im) (/ (/ (* y.re x.re) y.im) y.im))
       (if (<= y.re 6e+70)
         (* (/ y.im (hypot y.re y.im)) (/ x.im (hypot y.re y.im)))
         (/ (+ x.re (/ x.im (/ y.re y.im))) (hypot y.re y.im)))))))

C

double code(double x_46_re, double x_46_im, double y_46_re, double y_46_im) {
	double tmp;
	if (y_46_re <= -4.5e+86) {
		tmp = ((-x_46_im / (y_46_re / y_46_im)) - x_46_re) / hypot(y_46_re, y_46_im);
	} else if (y_46_re <= -1.05e-40) {
		tmp = ((x_46_im * y_46_im) + (y_46_re * x_46_re)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
	} else if (y_46_re <= 6.8e-199) {
		tmp = (x_46_im / y_46_im) + (((y_46_re * x_46_re) / y_46_im) / y_46_im);
	} else if (y_46_re <= 6e+70) {
		tmp = (y_46_im / hypot(y_46_re, y_46_im)) * (x_46_im / hypot(y_46_re, y_46_im));
	} else {
		tmp = (x_46_re + (x_46_im / (y_46_re / y_46_im))) / hypot(y_46_re, y_46_im);
	}
	return tmp;
}

Java

public static double code(double x_46_re, double x_46_im, double y_46_re, double y_46_im) {
	double tmp;
	if (y_46_re <= -4.5e+86) {
		tmp = ((-x_46_im / (y_46_re / y_46_im)) - x_46_re) / Math.hypot(y_46_re, y_46_im);
	} else if (y_46_re <= -1.05e-40) {
		tmp = ((x_46_im * y_46_im) + (y_46_re * x_46_re)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
	} else if (y_46_re <= 6.8e-199) {
		tmp = (x_46_im / y_46_im) + (((y_46_re * x_46_re) / y_46_im) / y_46_im);
	} else if (y_46_re <= 6e+70) {
		tmp = (y_46_im / Math.hypot(y_46_re, y_46_im)) * (x_46_im / Math.hypot(y_46_re, y_46_im));
	} else {
		tmp = (x_46_re + (x_46_im / (y_46_re / y_46_im))) / Math.hypot(y_46_re, y_46_im);
	}
	return tmp;
}

Python

def code(x_46_re, x_46_im, y_46_re, y_46_im):
	tmp = 0
	if y_46_re <= -4.5e+86:
		tmp = ((-x_46_im / (y_46_re / y_46_im)) - x_46_re) / math.hypot(y_46_re, y_46_im)
	elif y_46_re <= -1.05e-40:
		tmp = ((x_46_im * y_46_im) + (y_46_re * x_46_re)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im))
	elif y_46_re <= 6.8e-199:
		tmp = (x_46_im / y_46_im) + (((y_46_re * x_46_re) / y_46_im) / y_46_im)
	elif y_46_re <= 6e+70:
		tmp = (y_46_im / math.hypot(y_46_re, y_46_im)) * (x_46_im / math.hypot(y_46_re, y_46_im))
	else:
		tmp = (x_46_re + (x_46_im / (y_46_re / y_46_im))) / math.hypot(y_46_re, y_46_im)
	return tmp

Julia

function code(x_46_re, x_46_im, y_46_re, y_46_im)
	tmp = 0.0
	if (y_46_re <= -4.5e+86)
		tmp = Float64(Float64(Float64(Float64(-x_46_im) / Float64(y_46_re / y_46_im)) - x_46_re) / hypot(y_46_re, y_46_im));
	elseif (y_46_re <= -1.05e-40)
		tmp = Float64(Float64(Float64(x_46_im * y_46_im) + Float64(y_46_re * x_46_re)) / Float64(Float64(y_46_re * y_46_re) + Float64(y_46_im * y_46_im)));
	elseif (y_46_re <= 6.8e-199)
		tmp = Float64(Float64(x_46_im / y_46_im) + Float64(Float64(Float64(y_46_re * x_46_re) / y_46_im) / y_46_im));
	elseif (y_46_re <= 6e+70)
		tmp = Float64(Float64(y_46_im / hypot(y_46_re, y_46_im)) * Float64(x_46_im / hypot(y_46_re, y_46_im)));
	else
		tmp = Float64(Float64(x_46_re + Float64(x_46_im / Float64(y_46_re / y_46_im))) / hypot(y_46_re, y_46_im));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x_46_re, x_46_im, y_46_re, y_46_im)
	tmp = 0.0;
	if (y_46_re <= -4.5e+86)
		tmp = ((-x_46_im / (y_46_re / y_46_im)) - x_46_re) / hypot(y_46_re, y_46_im);
	elseif (y_46_re <= -1.05e-40)
		tmp = ((x_46_im * y_46_im) + (y_46_re * x_46_re)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
	elseif (y_46_re <= 6.8e-199)
		tmp = (x_46_im / y_46_im) + (((y_46_re * x_46_re) / y_46_im) / y_46_im);
	elseif (y_46_re <= 6e+70)
		tmp = (y_46_im / hypot(y_46_re, y_46_im)) * (x_46_im / hypot(y_46_re, y_46_im));
	else
		tmp = (x_46_re + (x_46_im / (y_46_re / y_46_im))) / hypot(y_46_re, y_46_im);
	end
	tmp_2 = tmp;
end

Wolfram

code[x$46$re_, x$46$im_, y$46$re_, y$46$im_] := If[LessEqual[y$46$re, -4.5e+86], N[(N[(N[((-x$46$im) / N[(y$46$re / y$46$im), $MachinePrecision]), $MachinePrecision] - x$46$re), $MachinePrecision] / N[Sqrt[y$46$re ^ 2 + y$46$im ^ 2], $MachinePrecision]), $MachinePrecision], If[LessEqual[y$46$re, -1.05e-40], N[(N[(N[(x$46$im * y$46$im), $MachinePrecision] + N[(y$46$re * x$46$re), $MachinePrecision]), $MachinePrecision] / N[(N[(y$46$re * y$46$re), $MachinePrecision] + N[(y$46$im * y$46$im), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y$46$re, 6.8e-199], N[(N[(x$46$im / y$46$im), $MachinePrecision] + N[(N[(N[(y$46$re * x$46$re), $MachinePrecision] / y$46$im), $MachinePrecision] / y$46$im), $MachinePrecision]), $MachinePrecision], If[LessEqual[y$46$re, 6e+70], N[(N[(y$46$im / N[Sqrt[y$46$re ^ 2 + y$46$im ^ 2], $MachinePrecision]), $MachinePrecision] * N[(x$46$im / N[Sqrt[y$46$re ^ 2 + y$46$im ^ 2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(x$46$re + N[(x$46$im / N[(y$46$re / y$46$im), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[Sqrt[y$46$re ^ 2 + y$46$im ^ 2], $MachinePrecision]), $MachinePrecision]]]]]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Alternative 3: 79.7% accurate, 0.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \frac{x.im \cdot y.im + y.re \cdot x.re}{y.re \cdot y.re + y.im \cdot y.im}\\ t_1 := \frac{x.im}{y.im} + \frac{\frac{y.re \cdot x.re}{y.im}}{y.im}\\ \mathbf{if}\;y.re \leq -4.2 \cdot 10^{+86}:\\ \;\;\;\;\frac{x.re}{y.re} + \frac{x.im}{\frac{{y.re}^{2}}{y.im}}\\ \mathbf{elif}\;y.re \leq -1.9 \cdot 10^{-49}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;y.re \leq 5.2 \cdot 10^{-89}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y.re \leq 5.1 \cdot 10^{-30}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;y.re \leq 6.4 \cdot 10^{+54}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;\frac{x.re + x.im \cdot \frac{y.im}{y.re}}{\mathsf{hypot}\left(y.re, y.im\right)}\\ \end{array} \end{array} \]

FPCore

(FPCore (x.re x.im y.re y.im)
 :precision binary64
 (let* ((t_0
         (/ (+ (* x.im y.im) (* y.re x.re)) (+ (* y.re y.re) (* y.im y.im))))
        (t_1 (+ (/ x.im y.im) (/ (/ (* y.re x.re) y.im) y.im))))
   (if (<= y.re -4.2e+86)
     (+ (/ x.re y.re) (/ x.im (/ (pow y.re 2.0) y.im)))
     (if (<= y.re -1.9e-49)
       t_0
       (if (<= y.re 5.2e-89)
         t_1
         (if (<= y.re 5.1e-30)
           t_0
           (if (<= y.re 6.4e+54)
             t_1
             (/ (+ x.re (* x.im (/ y.im y.re))) (hypot y.re y.im)))))))))

C

double code(double x_46_re, double x_46_im, double y_46_re, double y_46_im) {
	double t_0 = ((x_46_im * y_46_im) + (y_46_re * x_46_re)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
	double t_1 = (x_46_im / y_46_im) + (((y_46_re * x_46_re) / y_46_im) / y_46_im);
	double tmp;
	if (y_46_re <= -4.2e+86) {
		tmp = (x_46_re / y_46_re) + (x_46_im / (pow(y_46_re, 2.0) / y_46_im));
	} else if (y_46_re <= -1.9e-49) {
		tmp = t_0;
	} else if (y_46_re <= 5.2e-89) {
		tmp = t_1;
	} else if (y_46_re <= 5.1e-30) {
		tmp = t_0;
	} else if (y_46_re <= 6.4e+54) {
		tmp = t_1;
	} else {
		tmp = (x_46_re + (x_46_im * (y_46_im / y_46_re))) / hypot(y_46_re, y_46_im);
	}
	return tmp;
}

Java

public static double code(double x_46_re, double x_46_im, double y_46_re, double y_46_im) {
	double t_0 = ((x_46_im * y_46_im) + (y_46_re * x_46_re)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
	double t_1 = (x_46_im / y_46_im) + (((y_46_re * x_46_re) / y_46_im) / y_46_im);
	double tmp;
	if (y_46_re <= -4.2e+86) {
		tmp = (x_46_re / y_46_re) + (x_46_im / (Math.pow(y_46_re, 2.0) / y_46_im));
	} else if (y_46_re <= -1.9e-49) {
		tmp = t_0;
	} else if (y_46_re <= 5.2e-89) {
		tmp = t_1;
	} else if (y_46_re <= 5.1e-30) {
		tmp = t_0;
	} else if (y_46_re <= 6.4e+54) {
		tmp = t_1;
	} else {
		tmp = (x_46_re + (x_46_im * (y_46_im / y_46_re))) / Math.hypot(y_46_re, y_46_im);
	}
	return tmp;
}

Python

def code(x_46_re, x_46_im, y_46_re, y_46_im):
	t_0 = ((x_46_im * y_46_im) + (y_46_re * x_46_re)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im))
	t_1 = (x_46_im / y_46_im) + (((y_46_re * x_46_re) / y_46_im) / y_46_im)
	tmp = 0
	if y_46_re <= -4.2e+86:
		tmp = (x_46_re / y_46_re) + (x_46_im / (math.pow(y_46_re, 2.0) / y_46_im))
	elif y_46_re <= -1.9e-49:
		tmp = t_0
	elif y_46_re <= 5.2e-89:
		tmp = t_1
	elif y_46_re <= 5.1e-30:
		tmp = t_0
	elif y_46_re <= 6.4e+54:
		tmp = t_1
	else:
		tmp = (x_46_re + (x_46_im * (y_46_im / y_46_re))) / math.hypot(y_46_re, y_46_im)
	return tmp

Julia

function code(x_46_re, x_46_im, y_46_re, y_46_im)
	t_0 = Float64(Float64(Float64(x_46_im * y_46_im) + Float64(y_46_re * x_46_re)) / Float64(Float64(y_46_re * y_46_re) + Float64(y_46_im * y_46_im)))
	t_1 = Float64(Float64(x_46_im / y_46_im) + Float64(Float64(Float64(y_46_re * x_46_re) / y_46_im) / y_46_im))
	tmp = 0.0
	if (y_46_re <= -4.2e+86)
		tmp = Float64(Float64(x_46_re / y_46_re) + Float64(x_46_im / Float64((y_46_re ^ 2.0) / y_46_im)));
	elseif (y_46_re <= -1.9e-49)
		tmp = t_0;
	elseif (y_46_re <= 5.2e-89)
		tmp = t_1;
	elseif (y_46_re <= 5.1e-30)
		tmp = t_0;
	elseif (y_46_re <= 6.4e+54)
		tmp = t_1;
	else
		tmp = Float64(Float64(x_46_re + Float64(x_46_im * Float64(y_46_im / y_46_re))) / hypot(y_46_re, y_46_im));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x_46_re, x_46_im, y_46_re, y_46_im)
	t_0 = ((x_46_im * y_46_im) + (y_46_re * x_46_re)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
	t_1 = (x_46_im / y_46_im) + (((y_46_re * x_46_re) / y_46_im) / y_46_im);
	tmp = 0.0;
	if (y_46_re <= -4.2e+86)
		tmp = (x_46_re / y_46_re) + (x_46_im / ((y_46_re ^ 2.0) / y_46_im));
	elseif (y_46_re <= -1.9e-49)
		tmp = t_0;
	elseif (y_46_re <= 5.2e-89)
		tmp = t_1;
	elseif (y_46_re <= 5.1e-30)
		tmp = t_0;
	elseif (y_46_re <= 6.4e+54)
		tmp = t_1;
	else
		tmp = (x_46_re + (x_46_im * (y_46_im / y_46_re))) / hypot(y_46_re, y_46_im);
	end
	tmp_2 = tmp;
end

Wolfram

code[x$46$re_, x$46$im_, y$46$re_, y$46$im_] := Block[{t$95$0 = N[(N[(N[(x$46$im * y$46$im), $MachinePrecision] + N[(y$46$re * x$46$re), $MachinePrecision]), $MachinePrecision] / N[(N[(y$46$re * y$46$re), $MachinePrecision] + N[(y$46$im * y$46$im), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(N[(x$46$im / y$46$im), $MachinePrecision] + N[(N[(N[(y$46$re * x$46$re), $MachinePrecision] / y$46$im), $MachinePrecision] / y$46$im), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y$46$re, -4.2e+86], N[(N[(x$46$re / y$46$re), $MachinePrecision] + N[(x$46$im / N[(N[Power[y$46$re, 2.0], $MachinePrecision] / y$46$im), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y$46$re, -1.9e-49], t$95$0, If[LessEqual[y$46$re, 5.2e-89], t$95$1, If[LessEqual[y$46$re, 5.1e-30], t$95$0, If[LessEqual[y$46$re, 6.4e+54], t$95$1, N[(N[(x$46$re + N[(x$46$im * N[(y$46$im / y$46$re), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[Sqrt[y$46$re ^ 2 + y$46$im ^ 2], $MachinePrecision]), $MachinePrecision]]]]]]]]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Alternative 4: 79.7% accurate, 0.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \frac{x.im \cdot y.im + y.re \cdot x.re}{y.re \cdot y.re + y.im \cdot y.im}\\ t_1 := \frac{x.im}{y.im} + \frac{\frac{y.re \cdot x.re}{y.im}}{y.im}\\ \mathbf{if}\;y.re \leq -4.6 \cdot 10^{+86}:\\ \;\;\;\;\frac{x.re}{y.re} + \frac{x.im}{\frac{{y.re}^{2}}{y.im}}\\ \mathbf{elif}\;y.re \leq -1.9 \cdot 10^{-49}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;y.re \leq 5.1 \cdot 10^{-89}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y.re \leq 4.8 \cdot 10^{-30}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;y.re \leq 4.7 \cdot 10^{+54}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;\frac{x.re + \frac{x.im}{\frac{y.re}{y.im}}}{\mathsf{hypot}\left(y.re, y.im\right)}\\ \end{array} \end{array} \]

FPCore

(FPCore (x.re x.im y.re y.im)
 :precision binary64
 (let* ((t_0
         (/ (+ (* x.im y.im) (* y.re x.re)) (+ (* y.re y.re) (* y.im y.im))))
        (t_1 (+ (/ x.im y.im) (/ (/ (* y.re x.re) y.im) y.im))))
   (if (<= y.re -4.6e+86)
     (+ (/ x.re y.re) (/ x.im (/ (pow y.re 2.0) y.im)))
     (if (<= y.re -1.9e-49)
       t_0
       (if (<= y.re 5.1e-89)
         t_1
         (if (<= y.re 4.8e-30)
           t_0
           (if (<= y.re 4.7e+54)
             t_1
             (/ (+ x.re (/ x.im (/ y.re y.im))) (hypot y.re y.im)))))))))

C

double code(double x_46_re, double x_46_im, double y_46_re, double y_46_im) {
	double t_0 = ((x_46_im * y_46_im) + (y_46_re * x_46_re)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
	double t_1 = (x_46_im / y_46_im) + (((y_46_re * x_46_re) / y_46_im) / y_46_im);
	double tmp;
	if (y_46_re <= -4.6e+86) {
		tmp = (x_46_re / y_46_re) + (x_46_im / (pow(y_46_re, 2.0) / y_46_im));
	} else if (y_46_re <= -1.9e-49) {
		tmp = t_0;
	} else if (y_46_re <= 5.1e-89) {
		tmp = t_1;
	} else if (y_46_re <= 4.8e-30) {
		tmp = t_0;
	} else if (y_46_re <= 4.7e+54) {
		tmp = t_1;
	} else {
		tmp = (x_46_re + (x_46_im / (y_46_re / y_46_im))) / hypot(y_46_re, y_46_im);
	}
	return tmp;
}

Java

public static double code(double x_46_re, double x_46_im, double y_46_re, double y_46_im) {
	double t_0 = ((x_46_im * y_46_im) + (y_46_re * x_46_re)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
	double t_1 = (x_46_im / y_46_im) + (((y_46_re * x_46_re) / y_46_im) / y_46_im);
	double tmp;
	if (y_46_re <= -4.6e+86) {
		tmp = (x_46_re / y_46_re) + (x_46_im / (Math.pow(y_46_re, 2.0) / y_46_im));
	} else if (y_46_re <= -1.9e-49) {
		tmp = t_0;
	} else if (y_46_re <= 5.1e-89) {
		tmp = t_1;
	} else if (y_46_re <= 4.8e-30) {
		tmp = t_0;
	} else if (y_46_re <= 4.7e+54) {
		tmp = t_1;
	} else {
		tmp = (x_46_re + (x_46_im / (y_46_re / y_46_im))) / Math.hypot(y_46_re, y_46_im);
	}
	return tmp;
}

Python

def code(x_46_re, x_46_im, y_46_re, y_46_im):
	t_0 = ((x_46_im * y_46_im) + (y_46_re * x_46_re)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im))
	t_1 = (x_46_im / y_46_im) + (((y_46_re * x_46_re) / y_46_im) / y_46_im)
	tmp = 0
	if y_46_re <= -4.6e+86:
		tmp = (x_46_re / y_46_re) + (x_46_im / (math.pow(y_46_re, 2.0) / y_46_im))
	elif y_46_re <= -1.9e-49:
		tmp = t_0
	elif y_46_re <= 5.1e-89:
		tmp = t_1
	elif y_46_re <= 4.8e-30:
		tmp = t_0
	elif y_46_re <= 4.7e+54:
		tmp = t_1
	else:
		tmp = (x_46_re + (x_46_im / (y_46_re / y_46_im))) / math.hypot(y_46_re, y_46_im)
	return tmp

Julia

function code(x_46_re, x_46_im, y_46_re, y_46_im)
	t_0 = Float64(Float64(Float64(x_46_im * y_46_im) + Float64(y_46_re * x_46_re)) / Float64(Float64(y_46_re * y_46_re) + Float64(y_46_im * y_46_im)))
	t_1 = Float64(Float64(x_46_im / y_46_im) + Float64(Float64(Float64(y_46_re * x_46_re) / y_46_im) / y_46_im))
	tmp = 0.0
	if (y_46_re <= -4.6e+86)
		tmp = Float64(Float64(x_46_re / y_46_re) + Float64(x_46_im / Float64((y_46_re ^ 2.0) / y_46_im)));
	elseif (y_46_re <= -1.9e-49)
		tmp = t_0;
	elseif (y_46_re <= 5.1e-89)
		tmp = t_1;
	elseif (y_46_re <= 4.8e-30)
		tmp = t_0;
	elseif (y_46_re <= 4.7e+54)
		tmp = t_1;
	else
		tmp = Float64(Float64(x_46_re + Float64(x_46_im / Float64(y_46_re / y_46_im))) / hypot(y_46_re, y_46_im));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x_46_re, x_46_im, y_46_re, y_46_im)
	t_0 = ((x_46_im * y_46_im) + (y_46_re * x_46_re)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
	t_1 = (x_46_im / y_46_im) + (((y_46_re * x_46_re) / y_46_im) / y_46_im);
	tmp = 0.0;
	if (y_46_re <= -4.6e+86)
		tmp = (x_46_re / y_46_re) + (x_46_im / ((y_46_re ^ 2.0) / y_46_im));
	elseif (y_46_re <= -1.9e-49)
		tmp = t_0;
	elseif (y_46_re <= 5.1e-89)
		tmp = t_1;
	elseif (y_46_re <= 4.8e-30)
		tmp = t_0;
	elseif (y_46_re <= 4.7e+54)
		tmp = t_1;
	else
		tmp = (x_46_re + (x_46_im / (y_46_re / y_46_im))) / hypot(y_46_re, y_46_im);
	end
	tmp_2 = tmp;
end

Wolfram

code[x$46$re_, x$46$im_, y$46$re_, y$46$im_] := Block[{t$95$0 = N[(N[(N[(x$46$im * y$46$im), $MachinePrecision] + N[(y$46$re * x$46$re), $MachinePrecision]), $MachinePrecision] / N[(N[(y$46$re * y$46$re), $MachinePrecision] + N[(y$46$im * y$46$im), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(N[(x$46$im / y$46$im), $MachinePrecision] + N[(N[(N[(y$46$re * x$46$re), $MachinePrecision] / y$46$im), $MachinePrecision] / y$46$im), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y$46$re, -4.6e+86], N[(N[(x$46$re / y$46$re), $MachinePrecision] + N[(x$46$im / N[(N[Power[y$46$re, 2.0], $MachinePrecision] / y$46$im), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y$46$re, -1.9e-49], t$95$0, If[LessEqual[y$46$re, 5.1e-89], t$95$1, If[LessEqual[y$46$re, 4.8e-30], t$95$0, If[LessEqual[y$46$re, 4.7e+54], t$95$1, N[(N[(x$46$re + N[(x$46$im / N[(y$46$re / y$46$im), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[Sqrt[y$46$re ^ 2 + y$46$im ^ 2], $MachinePrecision]), $MachinePrecision]]]]]]]]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Alternative 5: 81.1% accurate, 0.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \frac{x.im \cdot y.im + y.re \cdot x.re}{y.re \cdot y.re + y.im \cdot y.im}\\ t_1 := \frac{x.im}{y.im} + \frac{\frac{y.re \cdot x.re}{y.im}}{y.im}\\ \mathbf{if}\;y.re \leq -4.4 \cdot 10^{+86}:\\ \;\;\;\;\frac{\frac{-x.im}{\frac{y.re}{y.im}} - x.re}{\mathsf{hypot}\left(y.re, y.im\right)}\\ \mathbf{elif}\;y.re \leq -1.9 \cdot 10^{-49}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;y.re \leq 5.2 \cdot 10^{-89}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y.re \leq 5.2 \cdot 10^{-30}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;y.re \leq 1.56 \cdot 10^{+59}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;\frac{x.re + \frac{x.im}{\frac{y.re}{y.im}}}{\mathsf{hypot}\left(y.re, y.im\right)}\\ \end{array} \end{array} \]

FPCore

(FPCore (x.re x.im y.re y.im)
 :precision binary64
 (let* ((t_0
         (/ (+ (* x.im y.im) (* y.re x.re)) (+ (* y.re y.re) (* y.im y.im))))
        (t_1 (+ (/ x.im y.im) (/ (/ (* y.re x.re) y.im) y.im))))
   (if (<= y.re -4.4e+86)
     (/ (- (/ (- x.im) (/ y.re y.im)) x.re) (hypot y.re y.im))
     (if (<= y.re -1.9e-49)
       t_0
       (if (<= y.re 5.2e-89)
         t_1
         (if (<= y.re 5.2e-30)
           t_0
           (if (<= y.re 1.56e+59)
             t_1
             (/ (+ x.re (/ x.im (/ y.re y.im))) (hypot y.re y.im)))))))))

C

double code(double x_46_re, double x_46_im, double y_46_re, double y_46_im) {
	double t_0 = ((x_46_im * y_46_im) + (y_46_re * x_46_re)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
	double t_1 = (x_46_im / y_46_im) + (((y_46_re * x_46_re) / y_46_im) / y_46_im);
	double tmp;
	if (y_46_re <= -4.4e+86) {
		tmp = ((-x_46_im / (y_46_re / y_46_im)) - x_46_re) / hypot(y_46_re, y_46_im);
	} else if (y_46_re <= -1.9e-49) {
		tmp = t_0;
	} else if (y_46_re <= 5.2e-89) {
		tmp = t_1;
	} else if (y_46_re <= 5.2e-30) {
		tmp = t_0;
	} else if (y_46_re <= 1.56e+59) {
		tmp = t_1;
	} else {
		tmp = (x_46_re + (x_46_im / (y_46_re / y_46_im))) / hypot(y_46_re, y_46_im);
	}
	return tmp;
}

Java

public static double code(double x_46_re, double x_46_im, double y_46_re, double y_46_im) {
	double t_0 = ((x_46_im * y_46_im) + (y_46_re * x_46_re)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
	double t_1 = (x_46_im / y_46_im) + (((y_46_re * x_46_re) / y_46_im) / y_46_im);
	double tmp;
	if (y_46_re <= -4.4e+86) {
		tmp = ((-x_46_im / (y_46_re / y_46_im)) - x_46_re) / Math.hypot(y_46_re, y_46_im);
	} else if (y_46_re <= -1.9e-49) {
		tmp = t_0;
	} else if (y_46_re <= 5.2e-89) {
		tmp = t_1;
	} else if (y_46_re <= 5.2e-30) {
		tmp = t_0;
	} else if (y_46_re <= 1.56e+59) {
		tmp = t_1;
	} else {
		tmp = (x_46_re + (x_46_im / (y_46_re / y_46_im))) / Math.hypot(y_46_re, y_46_im);
	}
	return tmp;
}

Python

def code(x_46_re, x_46_im, y_46_re, y_46_im):
	t_0 = ((x_46_im * y_46_im) + (y_46_re * x_46_re)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im))
	t_1 = (x_46_im / y_46_im) + (((y_46_re * x_46_re) / y_46_im) / y_46_im)
	tmp = 0
	if y_46_re <= -4.4e+86:
		tmp = ((-x_46_im / (y_46_re / y_46_im)) - x_46_re) / math.hypot(y_46_re, y_46_im)
	elif y_46_re <= -1.9e-49:
		tmp = t_0
	elif y_46_re <= 5.2e-89:
		tmp = t_1
	elif y_46_re <= 5.2e-30:
		tmp = t_0
	elif y_46_re <= 1.56e+59:
		tmp = t_1
	else:
		tmp = (x_46_re + (x_46_im / (y_46_re / y_46_im))) / math.hypot(y_46_re, y_46_im)
	return tmp

Julia

function code(x_46_re, x_46_im, y_46_re, y_46_im)
	t_0 = Float64(Float64(Float64(x_46_im * y_46_im) + Float64(y_46_re * x_46_re)) / Float64(Float64(y_46_re * y_46_re) + Float64(y_46_im * y_46_im)))
	t_1 = Float64(Float64(x_46_im / y_46_im) + Float64(Float64(Float64(y_46_re * x_46_re) / y_46_im) / y_46_im))
	tmp = 0.0
	if (y_46_re <= -4.4e+86)
		tmp = Float64(Float64(Float64(Float64(-x_46_im) / Float64(y_46_re / y_46_im)) - x_46_re) / hypot(y_46_re, y_46_im));
	elseif (y_46_re <= -1.9e-49)
		tmp = t_0;
	elseif (y_46_re <= 5.2e-89)
		tmp = t_1;
	elseif (y_46_re <= 5.2e-30)
		tmp = t_0;
	elseif (y_46_re <= 1.56e+59)
		tmp = t_1;
	else
		tmp = Float64(Float64(x_46_re + Float64(x_46_im / Float64(y_46_re / y_46_im))) / hypot(y_46_re, y_46_im));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x_46_re, x_46_im, y_46_re, y_46_im)
	t_0 = ((x_46_im * y_46_im) + (y_46_re * x_46_re)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
	t_1 = (x_46_im / y_46_im) + (((y_46_re * x_46_re) / y_46_im) / y_46_im);
	tmp = 0.0;
	if (y_46_re <= -4.4e+86)
		tmp = ((-x_46_im / (y_46_re / y_46_im)) - x_46_re) / hypot(y_46_re, y_46_im);
	elseif (y_46_re <= -1.9e-49)
		tmp = t_0;
	elseif (y_46_re <= 5.2e-89)
		tmp = t_1;
	elseif (y_46_re <= 5.2e-30)
		tmp = t_0;
	elseif (y_46_re <= 1.56e+59)
		tmp = t_1;
	else
		tmp = (x_46_re + (x_46_im / (y_46_re / y_46_im))) / hypot(y_46_re, y_46_im);
	end
	tmp_2 = tmp;
end

Wolfram

code[x$46$re_, x$46$im_, y$46$re_, y$46$im_] := Block[{t$95$0 = N[(N[(N[(x$46$im * y$46$im), $MachinePrecision] + N[(y$46$re * x$46$re), $MachinePrecision]), $MachinePrecision] / N[(N[(y$46$re * y$46$re), $MachinePrecision] + N[(y$46$im * y$46$im), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(N[(x$46$im / y$46$im), $MachinePrecision] + N[(N[(N[(y$46$re * x$46$re), $MachinePrecision] / y$46$im), $MachinePrecision] / y$46$im), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y$46$re, -4.4e+86], N[(N[(N[((-x$46$im) / N[(y$46$re / y$46$im), $MachinePrecision]), $MachinePrecision] - x$46$re), $MachinePrecision] / N[Sqrt[y$46$re ^ 2 + y$46$im ^ 2], $MachinePrecision]), $MachinePrecision], If[LessEqual[y$46$re, -1.9e-49], t$95$0, If[LessEqual[y$46$re, 5.2e-89], t$95$1, If[LessEqual[y$46$re, 5.2e-30], t$95$0, If[LessEqual[y$46$re, 1.56e+59], t$95$1, N[(N[(x$46$re + N[(x$46$im / N[(y$46$re / y$46$im), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[Sqrt[y$46$re ^ 2 + y$46$im ^ 2], $MachinePrecision]), $MachinePrecision]]]]]]]]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Alternative 6: 79.8% accurate, 0.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \frac{x.im \cdot y.im + y.re \cdot x.re}{y.re \cdot y.re + y.im \cdot y.im}\\ t_1 := \frac{x.re}{y.re} + \frac{x.im}{\frac{{y.re}^{2}}{y.im}}\\ \mathbf{if}\;y.re \leq -4.6 \cdot 10^{+86}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y.re \leq -1.4 \cdot 10^{-39}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;y.re \leq 5.3 \cdot 10^{-89}:\\ \;\;\;\;\frac{x.im}{y.im} + \frac{\frac{y.re \cdot x.re}{y.im}}{y.im}\\ \mathbf{elif}\;y.re \leq 9.2 \cdot 10^{+136}:\\ \;\;\;\;t_0\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x.re x.im y.re y.im)
 :precision binary64
 (let* ((t_0
         (/ (+ (* x.im y.im) (* y.re x.re)) (+ (* y.re y.re) (* y.im y.im))))
        (t_1 (+ (/ x.re y.re) (/ x.im (/ (pow y.re 2.0) y.im)))))
   (if (<= y.re -4.6e+86)
     t_1
     (if (<= y.re -1.4e-39)
       t_0
       (if (<= y.re 5.3e-89)
         (+ (/ x.im y.im) (/ (/ (* y.re x.re) y.im) y.im))
         (if (<= y.re 9.2e+136) t_0 t_1))))))

C

double code(double x_46_re, double x_46_im, double y_46_re, double y_46_im) {
	double t_0 = ((x_46_im * y_46_im) + (y_46_re * x_46_re)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
	double t_1 = (x_46_re / y_46_re) + (x_46_im / (pow(y_46_re, 2.0) / y_46_im));
	double tmp;
	if (y_46_re <= -4.6e+86) {
		tmp = t_1;
	} else if (y_46_re <= -1.4e-39) {
		tmp = t_0;
	} else if (y_46_re <= 5.3e-89) {
		tmp = (x_46_im / y_46_im) + (((y_46_re * x_46_re) / y_46_im) / y_46_im);
	} else if (y_46_re <= 9.2e+136) {
		tmp = t_0;
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x_46re, x_46im, y_46re, y_46im)
    real(8), intent (in) :: x_46re
    real(8), intent (in) :: x_46im
    real(8), intent (in) :: y_46re
    real(8), intent (in) :: y_46im
    real(8) :: t_0
    real(8) :: t_1
    real(8) :: tmp
    t_0 = ((x_46im * y_46im) + (y_46re * x_46re)) / ((y_46re * y_46re) + (y_46im * y_46im))
    t_1 = (x_46re / y_46re) + (x_46im / ((y_46re ** 2.0d0) / y_46im))
    if (y_46re <= (-4.6d+86)) then
        tmp = t_1
    else if (y_46re <= (-1.4d-39)) then
        tmp = t_0
    else if (y_46re <= 5.3d-89) then
        tmp = (x_46im / y_46im) + (((y_46re * x_46re) / y_46im) / y_46im)
    else if (y_46re <= 9.2d+136) then
        tmp = t_0
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x_46_re, double x_46_im, double y_46_re, double y_46_im) {
	double t_0 = ((x_46_im * y_46_im) + (y_46_re * x_46_re)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
	double t_1 = (x_46_re / y_46_re) + (x_46_im / (Math.pow(y_46_re, 2.0) / y_46_im));
	double tmp;
	if (y_46_re <= -4.6e+86) {
		tmp = t_1;
	} else if (y_46_re <= -1.4e-39) {
		tmp = t_0;
	} else if (y_46_re <= 5.3e-89) {
		tmp = (x_46_im / y_46_im) + (((y_46_re * x_46_re) / y_46_im) / y_46_im);
	} else if (y_46_re <= 9.2e+136) {
		tmp = t_0;
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x_46_re, x_46_im, y_46_re, y_46_im):
	t_0 = ((x_46_im * y_46_im) + (y_46_re * x_46_re)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im))
	t_1 = (x_46_re / y_46_re) + (x_46_im / (math.pow(y_46_re, 2.0) / y_46_im))
	tmp = 0
	if y_46_re <= -4.6e+86:
		tmp = t_1
	elif y_46_re <= -1.4e-39:
		tmp = t_0
	elif y_46_re <= 5.3e-89:
		tmp = (x_46_im / y_46_im) + (((y_46_re * x_46_re) / y_46_im) / y_46_im)
	elif y_46_re <= 9.2e+136:
		tmp = t_0
	else:
		tmp = t_1
	return tmp

Julia

function code(x_46_re, x_46_im, y_46_re, y_46_im)
	t_0 = Float64(Float64(Float64(x_46_im * y_46_im) + Float64(y_46_re * x_46_re)) / Float64(Float64(y_46_re * y_46_re) + Float64(y_46_im * y_46_im)))
	t_1 = Float64(Float64(x_46_re / y_46_re) + Float64(x_46_im / Float64((y_46_re ^ 2.0) / y_46_im)))
	tmp = 0.0
	if (y_46_re <= -4.6e+86)
		tmp = t_1;
	elseif (y_46_re <= -1.4e-39)
		tmp = t_0;
	elseif (y_46_re <= 5.3e-89)
		tmp = Float64(Float64(x_46_im / y_46_im) + Float64(Float64(Float64(y_46_re * x_46_re) / y_46_im) / y_46_im));
	elseif (y_46_re <= 9.2e+136)
		tmp = t_0;
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x_46_re, x_46_im, y_46_re, y_46_im)
	t_0 = ((x_46_im * y_46_im) + (y_46_re * x_46_re)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
	t_1 = (x_46_re / y_46_re) + (x_46_im / ((y_46_re ^ 2.0) / y_46_im));
	tmp = 0.0;
	if (y_46_re <= -4.6e+86)
		tmp = t_1;
	elseif (y_46_re <= -1.4e-39)
		tmp = t_0;
	elseif (y_46_re <= 5.3e-89)
		tmp = (x_46_im / y_46_im) + (((y_46_re * x_46_re) / y_46_im) / y_46_im);
	elseif (y_46_re <= 9.2e+136)
		tmp = t_0;
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x$46$re_, x$46$im_, y$46$re_, y$46$im_] := Block[{t$95$0 = N[(N[(N[(x$46$im * y$46$im), $MachinePrecision] + N[(y$46$re * x$46$re), $MachinePrecision]), $MachinePrecision] / N[(N[(y$46$re * y$46$re), $MachinePrecision] + N[(y$46$im * y$46$im), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(N[(x$46$re / y$46$re), $MachinePrecision] + N[(x$46$im / N[(N[Power[y$46$re, 2.0], $MachinePrecision] / y$46$im), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y$46$re, -4.6e+86], t$95$1, If[LessEqual[y$46$re, -1.4e-39], t$95$0, If[LessEqual[y$46$re, 5.3e-89], N[(N[(x$46$im / y$46$im), $MachinePrecision] + N[(N[(N[(y$46$re * x$46$re), $MachinePrecision] / y$46$im), $MachinePrecision] / y$46$im), $MachinePrecision]), $MachinePrecision], If[LessEqual[y$46$re, 9.2e+136], t$95$0, t$95$1]]]]]]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Alternative 7: 79.6% accurate, 0.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \frac{x.im \cdot y.im + y.re \cdot x.re}{y.re \cdot y.re + y.im \cdot y.im}\\ \mathbf{if}\;y.re \leq -1 \cdot 10^{+93}:\\ \;\;\;\;\frac{-x.re}{\mathsf{hypot}\left(y.re, y.im\right)}\\ \mathbf{elif}\;y.re \leq -1.25 \cdot 10^{-40}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;y.re \leq 5.1 \cdot 10^{-89}:\\ \;\;\;\;\frac{x.im}{y.im} + \frac{\frac{y.re \cdot x.re}{y.im}}{y.im}\\ \mathbf{elif}\;y.re \leq 3 \cdot 10^{+135}:\\ \;\;\;\;t_0\\ \mathbf{else}:\\ \;\;\;\;\frac{x.re}{y.re}\\ \end{array} \end{array} \]

FPCore

(FPCore (x.re x.im y.re y.im)
 :precision binary64
 (let* ((t_0
         (/ (+ (* x.im y.im) (* y.re x.re)) (+ (* y.re y.re) (* y.im y.im)))))
   (if (<= y.re -1e+93)
     (/ (- x.re) (hypot y.re y.im))
     (if (<= y.re -1.25e-40)
       t_0
       (if (<= y.re 5.1e-89)
         (+ (/ x.im y.im) (/ (/ (* y.re x.re) y.im) y.im))
         (if (<= y.re 3e+135) t_0 (/ x.re y.re)))))))

C

double code(double x_46_re, double x_46_im, double y_46_re, double y_46_im) {
	double t_0 = ((x_46_im * y_46_im) + (y_46_re * x_46_re)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
	double tmp;
	if (y_46_re <= -1e+93) {
		tmp = -x_46_re / hypot(y_46_re, y_46_im);
	} else if (y_46_re <= -1.25e-40) {
		tmp = t_0;
	} else if (y_46_re <= 5.1e-89) {
		tmp = (x_46_im / y_46_im) + (((y_46_re * x_46_re) / y_46_im) / y_46_im);
	} else if (y_46_re <= 3e+135) {
		tmp = t_0;
	} else {
		tmp = x_46_re / y_46_re;
	}
	return tmp;
}

Java

public static double code(double x_46_re, double x_46_im, double y_46_re, double y_46_im) {
	double t_0 = ((x_46_im * y_46_im) + (y_46_re * x_46_re)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
	double tmp;
	if (y_46_re <= -1e+93) {
		tmp = -x_46_re / Math.hypot(y_46_re, y_46_im);
	} else if (y_46_re <= -1.25e-40) {
		tmp = t_0;
	} else if (y_46_re <= 5.1e-89) {
		tmp = (x_46_im / y_46_im) + (((y_46_re * x_46_re) / y_46_im) / y_46_im);
	} else if (y_46_re <= 3e+135) {
		tmp = t_0;
	} else {
		tmp = x_46_re / y_46_re;
	}
	return tmp;
}

Python

def code(x_46_re, x_46_im, y_46_re, y_46_im):
	t_0 = ((x_46_im * y_46_im) + (y_46_re * x_46_re)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im))
	tmp = 0
	if y_46_re <= -1e+93:
		tmp = -x_46_re / math.hypot(y_46_re, y_46_im)
	elif y_46_re <= -1.25e-40:
		tmp = t_0
	elif y_46_re <= 5.1e-89:
		tmp = (x_46_im / y_46_im) + (((y_46_re * x_46_re) / y_46_im) / y_46_im)
	elif y_46_re <= 3e+135:
		tmp = t_0
	else:
		tmp = x_46_re / y_46_re
	return tmp

Julia

function code(x_46_re, x_46_im, y_46_re, y_46_im)
	t_0 = Float64(Float64(Float64(x_46_im * y_46_im) + Float64(y_46_re * x_46_re)) / Float64(Float64(y_46_re * y_46_re) + Float64(y_46_im * y_46_im)))
	tmp = 0.0
	if (y_46_re <= -1e+93)
		tmp = Float64(Float64(-x_46_re) / hypot(y_46_re, y_46_im));
	elseif (y_46_re <= -1.25e-40)
		tmp = t_0;
	elseif (y_46_re <= 5.1e-89)
		tmp = Float64(Float64(x_46_im / y_46_im) + Float64(Float64(Float64(y_46_re * x_46_re) / y_46_im) / y_46_im));
	elseif (y_46_re <= 3e+135)
		tmp = t_0;
	else
		tmp = Float64(x_46_re / y_46_re);
	end
	return tmp
end

MATLAB

function tmp_2 = code(x_46_re, x_46_im, y_46_re, y_46_im)
	t_0 = ((x_46_im * y_46_im) + (y_46_re * x_46_re)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
	tmp = 0.0;
	if (y_46_re <= -1e+93)
		tmp = -x_46_re / hypot(y_46_re, y_46_im);
	elseif (y_46_re <= -1.25e-40)
		tmp = t_0;
	elseif (y_46_re <= 5.1e-89)
		tmp = (x_46_im / y_46_im) + (((y_46_re * x_46_re) / y_46_im) / y_46_im);
	elseif (y_46_re <= 3e+135)
		tmp = t_0;
	else
		tmp = x_46_re / y_46_re;
	end
	tmp_2 = tmp;
end

Wolfram

code[x$46$re_, x$46$im_, y$46$re_, y$46$im_] := Block[{t$95$0 = N[(N[(N[(x$46$im * y$46$im), $MachinePrecision] + N[(y$46$re * x$46$re), $MachinePrecision]), $MachinePrecision] / N[(N[(y$46$re * y$46$re), $MachinePrecision] + N[(y$46$im * y$46$im), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y$46$re, -1e+93], N[((-x$46$re) / N[Sqrt[y$46$re ^ 2 + y$46$im ^ 2], $MachinePrecision]), $MachinePrecision], If[LessEqual[y$46$re, -1.25e-40], t$95$0, If[LessEqual[y$46$re, 5.1e-89], N[(N[(x$46$im / y$46$im), $MachinePrecision] + N[(N[(N[(y$46$re * x$46$re), $MachinePrecision] / y$46$im), $MachinePrecision] / y$46$im), $MachinePrecision]), $MachinePrecision], If[LessEqual[y$46$re, 3e+135], t$95$0, N[(x$46$re / y$46$re), $MachinePrecision]]]]]]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Alternative 8: 79.7% accurate, 0.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \frac{x.im \cdot y.im + y.re \cdot x.re}{y.re \cdot y.re + y.im \cdot y.im}\\ \mathbf{if}\;y.re \leq -1.65 \cdot 10^{+95}:\\ \;\;\;\;\frac{x.re}{y.re}\\ \mathbf{elif}\;y.re \leq -2 \cdot 10^{-49}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;y.re \leq 5.3 \cdot 10^{-89}:\\ \;\;\;\;\frac{x.im}{y.im} + \frac{\frac{y.re \cdot x.re}{y.im}}{y.im}\\ \mathbf{elif}\;y.re \leq 3.1 \cdot 10^{+144}:\\ \;\;\;\;t_0\\ \mathbf{else}:\\ \;\;\;\;\frac{x.re}{y.re}\\ \end{array} \end{array} \]

FPCore

(FPCore (x.re x.im y.re y.im)
 :precision binary64
 (let* ((t_0
         (/ (+ (* x.im y.im) (* y.re x.re)) (+ (* y.re y.re) (* y.im y.im)))))
   (if (<= y.re -1.65e+95)
     (/ x.re y.re)
     (if (<= y.re -2e-49)
       t_0
       (if (<= y.re 5.3e-89)
         (+ (/ x.im y.im) (/ (/ (* y.re x.re) y.im) y.im))
         (if (<= y.re 3.1e+144) t_0 (/ x.re y.re)))))))

C

double code(double x_46_re, double x_46_im, double y_46_re, double y_46_im) {
	double t_0 = ((x_46_im * y_46_im) + (y_46_re * x_46_re)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
	double tmp;
	if (y_46_re <= -1.65e+95) {
		tmp = x_46_re / y_46_re;
	} else if (y_46_re <= -2e-49) {
		tmp = t_0;
	} else if (y_46_re <= 5.3e-89) {
		tmp = (x_46_im / y_46_im) + (((y_46_re * x_46_re) / y_46_im) / y_46_im);
	} else if (y_46_re <= 3.1e+144) {
		tmp = t_0;
	} else {
		tmp = x_46_re / y_46_re;
	}
	return tmp;
}

Fortran

real(8) function code(x_46re, x_46im, y_46re, y_46im)
    real(8), intent (in) :: x_46re
    real(8), intent (in) :: x_46im
    real(8), intent (in) :: y_46re
    real(8), intent (in) :: y_46im
    real(8) :: t_0
    real(8) :: tmp
    t_0 = ((x_46im * y_46im) + (y_46re * x_46re)) / ((y_46re * y_46re) + (y_46im * y_46im))
    if (y_46re <= (-1.65d+95)) then
        tmp = x_46re / y_46re
    else if (y_46re <= (-2d-49)) then
        tmp = t_0
    else if (y_46re <= 5.3d-89) then
        tmp = (x_46im / y_46im) + (((y_46re * x_46re) / y_46im) / y_46im)
    else if (y_46re <= 3.1d+144) then
        tmp = t_0
    else
        tmp = x_46re / y_46re
    end if
    code = tmp
end function

Java

public static double code(double x_46_re, double x_46_im, double y_46_re, double y_46_im) {
	double t_0 = ((x_46_im * y_46_im) + (y_46_re * x_46_re)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
	double tmp;
	if (y_46_re <= -1.65e+95) {
		tmp = x_46_re / y_46_re;
	} else if (y_46_re <= -2e-49) {
		tmp = t_0;
	} else if (y_46_re <= 5.3e-89) {
		tmp = (x_46_im / y_46_im) + (((y_46_re * x_46_re) / y_46_im) / y_46_im);
	} else if (y_46_re <= 3.1e+144) {
		tmp = t_0;
	} else {
		tmp = x_46_re / y_46_re;
	}
	return tmp;
}

Python

def code(x_46_re, x_46_im, y_46_re, y_46_im):
	t_0 = ((x_46_im * y_46_im) + (y_46_re * x_46_re)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im))
	tmp = 0
	if y_46_re <= -1.65e+95:
		tmp = x_46_re / y_46_re
	elif y_46_re <= -2e-49:
		tmp = t_0
	elif y_46_re <= 5.3e-89:
		tmp = (x_46_im / y_46_im) + (((y_46_re * x_46_re) / y_46_im) / y_46_im)
	elif y_46_re <= 3.1e+144:
		tmp = t_0
	else:
		tmp = x_46_re / y_46_re
	return tmp

Julia

function code(x_46_re, x_46_im, y_46_re, y_46_im)
	t_0 = Float64(Float64(Float64(x_46_im * y_46_im) + Float64(y_46_re * x_46_re)) / Float64(Float64(y_46_re * y_46_re) + Float64(y_46_im * y_46_im)))
	tmp = 0.0
	if (y_46_re <= -1.65e+95)
		tmp = Float64(x_46_re / y_46_re);
	elseif (y_46_re <= -2e-49)
		tmp = t_0;
	elseif (y_46_re <= 5.3e-89)
		tmp = Float64(Float64(x_46_im / y_46_im) + Float64(Float64(Float64(y_46_re * x_46_re) / y_46_im) / y_46_im));
	elseif (y_46_re <= 3.1e+144)
		tmp = t_0;
	else
		tmp = Float64(x_46_re / y_46_re);
	end
	return tmp
end

MATLAB

function tmp_2 = code(x_46_re, x_46_im, y_46_re, y_46_im)
	t_0 = ((x_46_im * y_46_im) + (y_46_re * x_46_re)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
	tmp = 0.0;
	if (y_46_re <= -1.65e+95)
		tmp = x_46_re / y_46_re;
	elseif (y_46_re <= -2e-49)
		tmp = t_0;
	elseif (y_46_re <= 5.3e-89)
		tmp = (x_46_im / y_46_im) + (((y_46_re * x_46_re) / y_46_im) / y_46_im);
	elseif (y_46_re <= 3.1e+144)
		tmp = t_0;
	else
		tmp = x_46_re / y_46_re;
	end
	tmp_2 = tmp;
end

Wolfram

code[x$46$re_, x$46$im_, y$46$re_, y$46$im_] := Block[{t$95$0 = N[(N[(N[(x$46$im * y$46$im), $MachinePrecision] + N[(y$46$re * x$46$re), $MachinePrecision]), $MachinePrecision] / N[(N[(y$46$re * y$46$re), $MachinePrecision] + N[(y$46$im * y$46$im), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y$46$re, -1.65e+95], N[(x$46$re / y$46$re), $MachinePrecision], If[LessEqual[y$46$re, -2e-49], t$95$0, If[LessEqual[y$46$re, 5.3e-89], N[(N[(x$46$im / y$46$im), $MachinePrecision] + N[(N[(N[(y$46$re * x$46$re), $MachinePrecision] / y$46$im), $MachinePrecision] / y$46$im), $MachinePrecision]), $MachinePrecision], If[LessEqual[y$46$re, 3.1e+144], t$95$0, N[(x$46$re / y$46$re), $MachinePrecision]]]]]]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Alternative 9: 72.7% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y.re \leq -5 \cdot 10^{+95} \lor \neg \left(y.re \leq 3.3 \cdot 10^{+93}\right):\\ \;\;\;\;\frac{x.re}{y.re}\\ \mathbf{else}:\\ \;\;\;\;\frac{1}{y.im} \cdot \left(x.im + \frac{y.re}{\frac{y.im}{x.re}}\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x.re x.im y.re y.im)
 :precision binary64
 (if (or (<= y.re -5e+95) (not (<= y.re 3.3e+93)))
   (/ x.re y.re)
   (* (/ 1.0 y.im) (+ x.im (/ y.re (/ y.im x.re))))))

C

double code(double x_46_re, double x_46_im, double y_46_re, double y_46_im) {
	double tmp;
	if ((y_46_re <= -5e+95) || !(y_46_re <= 3.3e+93)) {
		tmp = x_46_re / y_46_re;
	} else {
		tmp = (1.0 / y_46_im) * (x_46_im + (y_46_re / (y_46_im / x_46_re)));
	}
	return tmp;
}

Fortran

real(8) function code(x_46re, x_46im, y_46re, y_46im)
    real(8), intent (in) :: x_46re
    real(8), intent (in) :: x_46im
    real(8), intent (in) :: y_46re
    real(8), intent (in) :: y_46im
    real(8) :: tmp
    if ((y_46re <= (-5d+95)) .or. (.not. (y_46re <= 3.3d+93))) then
        tmp = x_46re / y_46re
    else
        tmp = (1.0d0 / y_46im) * (x_46im + (y_46re / (y_46im / x_46re)))
    end if
    code = tmp
end function

Java

public static double code(double x_46_re, double x_46_im, double y_46_re, double y_46_im) {
	double tmp;
	if ((y_46_re <= -5e+95) || !(y_46_re <= 3.3e+93)) {
		tmp = x_46_re / y_46_re;
	} else {
		tmp = (1.0 / y_46_im) * (x_46_im + (y_46_re / (y_46_im / x_46_re)));
	}
	return tmp;
}

Python

def code(x_46_re, x_46_im, y_46_re, y_46_im):
	tmp = 0
	if (y_46_re <= -5e+95) or not (y_46_re <= 3.3e+93):
		tmp = x_46_re / y_46_re
	else:
		tmp = (1.0 / y_46_im) * (x_46_im + (y_46_re / (y_46_im / x_46_re)))
	return tmp

Julia

function code(x_46_re, x_46_im, y_46_re, y_46_im)
	tmp = 0.0
	if ((y_46_re <= -5e+95) || !(y_46_re <= 3.3e+93))
		tmp = Float64(x_46_re / y_46_re);
	else
		tmp = Float64(Float64(1.0 / y_46_im) * Float64(x_46_im + Float64(y_46_re / Float64(y_46_im / x_46_re))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x_46_re, x_46_im, y_46_re, y_46_im)
	tmp = 0.0;
	if ((y_46_re <= -5e+95) || ~((y_46_re <= 3.3e+93)))
		tmp = x_46_re / y_46_re;
	else
		tmp = (1.0 / y_46_im) * (x_46_im + (y_46_re / (y_46_im / x_46_re)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x$46$re_, x$46$im_, y$46$re_, y$46$im_] := If[Or[LessEqual[y$46$re, -5e+95], N[Not[LessEqual[y$46$re, 3.3e+93]], $MachinePrecision]], N[(x$46$re / y$46$re), $MachinePrecision], N[(N[(1.0 / y$46$im), $MachinePrecision] * N[(x$46$im + N[(y$46$re / N[(y$46$im / x$46$re), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Alternative 10: 72.7% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y.re \leq -3.4 \cdot 10^{+95} \lor \neg \left(y.re \leq 5.5 \cdot 10^{+70}\right):\\ \;\;\;\;\frac{x.re}{y.re}\\ \mathbf{else}:\\ \;\;\;\;\frac{x.im}{y.im} + \frac{\frac{y.re \cdot x.re}{y.im}}{y.im}\\ \end{array} \end{array} \]

FPCore

(FPCore (x.re x.im y.re y.im)
 :precision binary64
 (if (or (<= y.re -3.4e+95) (not (<= y.re 5.5e+70)))
   (/ x.re y.re)
   (+ (/ x.im y.im) (/ (/ (* y.re x.re) y.im) y.im))))

C

double code(double x_46_re, double x_46_im, double y_46_re, double y_46_im) {
	double tmp;
	if ((y_46_re <= -3.4e+95) || !(y_46_re <= 5.5e+70)) {
		tmp = x_46_re / y_46_re;
	} else {
		tmp = (x_46_im / y_46_im) + (((y_46_re * x_46_re) / y_46_im) / y_46_im);
	}
	return tmp;
}

Fortran

real(8) function code(x_46re, x_46im, y_46re, y_46im)
    real(8), intent (in) :: x_46re
    real(8), intent (in) :: x_46im
    real(8), intent (in) :: y_46re
    real(8), intent (in) :: y_46im
    real(8) :: tmp
    if ((y_46re <= (-3.4d+95)) .or. (.not. (y_46re <= 5.5d+70))) then
        tmp = x_46re / y_46re
    else
        tmp = (x_46im / y_46im) + (((y_46re * x_46re) / y_46im) / y_46im)
    end if
    code = tmp
end function

Java

public static double code(double x_46_re, double x_46_im, double y_46_re, double y_46_im) {
	double tmp;
	if ((y_46_re <= -3.4e+95) || !(y_46_re <= 5.5e+70)) {
		tmp = x_46_re / y_46_re;
	} else {
		tmp = (x_46_im / y_46_im) + (((y_46_re * x_46_re) / y_46_im) / y_46_im);
	}
	return tmp;
}

Python

def code(x_46_re, x_46_im, y_46_re, y_46_im):
	tmp = 0
	if (y_46_re <= -3.4e+95) or not (y_46_re <= 5.5e+70):
		tmp = x_46_re / y_46_re
	else:
		tmp = (x_46_im / y_46_im) + (((y_46_re * x_46_re) / y_46_im) / y_46_im)
	return tmp

Julia

function code(x_46_re, x_46_im, y_46_re, y_46_im)
	tmp = 0.0
	if ((y_46_re <= -3.4e+95) || !(y_46_re <= 5.5e+70))
		tmp = Float64(x_46_re / y_46_re);
	else
		tmp = Float64(Float64(x_46_im / y_46_im) + Float64(Float64(Float64(y_46_re * x_46_re) / y_46_im) / y_46_im));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x_46_re, x_46_im, y_46_re, y_46_im)
	tmp = 0.0;
	if ((y_46_re <= -3.4e+95) || ~((y_46_re <= 5.5e+70)))
		tmp = x_46_re / y_46_re;
	else
		tmp = (x_46_im / y_46_im) + (((y_46_re * x_46_re) / y_46_im) / y_46_im);
	end
	tmp_2 = tmp;
end

Wolfram

code[x$46$re_, x$46$im_, y$46$re_, y$46$im_] := If[Or[LessEqual[y$46$re, -3.4e+95], N[Not[LessEqual[y$46$re, 5.5e+70]], $MachinePrecision]], N[(x$46$re / y$46$re), $MachinePrecision], N[(N[(x$46$im / y$46$im), $MachinePrecision] + N[(N[(N[(y$46$re * x$46$re), $MachinePrecision] / y$46$im), $MachinePrecision] / y$46$im), $MachinePrecision]), $MachinePrecision]]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Alternative 11: 63.9% accurate, 2.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y.re \leq -5.7 \cdot 10^{-15} \lor \neg \left(y.re \leq 8.2 \cdot 10^{+71}\right):\\ \;\;\;\;\frac{x.re}{y.re}\\ \mathbf{else}:\\ \;\;\;\;\frac{x.im}{y.im}\\ \end{array} \end{array} \]

FPCore

(FPCore (x.re x.im y.re y.im)
 :precision binary64
 (if (or (<= y.re -5.7e-15) (not (<= y.re 8.2e+71)))
   (/ x.re y.re)
   (/ x.im y.im)))

C

double code(double x_46_re, double x_46_im, double y_46_re, double y_46_im) {
	double tmp;
	if ((y_46_re <= -5.7e-15) || !(y_46_re <= 8.2e+71)) {
		tmp = x_46_re / y_46_re;
	} else {
		tmp = x_46_im / y_46_im;
	}
	return tmp;
}

Fortran

real(8) function code(x_46re, x_46im, y_46re, y_46im)
    real(8), intent (in) :: x_46re
    real(8), intent (in) :: x_46im
    real(8), intent (in) :: y_46re
    real(8), intent (in) :: y_46im
    real(8) :: tmp
    if ((y_46re <= (-5.7d-15)) .or. (.not. (y_46re <= 8.2d+71))) then
        tmp = x_46re / y_46re
    else
        tmp = x_46im / y_46im
    end if
    code = tmp
end function

Java

public static double code(double x_46_re, double x_46_im, double y_46_re, double y_46_im) {
	double tmp;
	if ((y_46_re <= -5.7e-15) || !(y_46_re <= 8.2e+71)) {
		tmp = x_46_re / y_46_re;
	} else {
		tmp = x_46_im / y_46_im;
	}
	return tmp;
}

Python

def code(x_46_re, x_46_im, y_46_re, y_46_im):
	tmp = 0
	if (y_46_re <= -5.7e-15) or not (y_46_re <= 8.2e+71):
		tmp = x_46_re / y_46_re
	else:
		tmp = x_46_im / y_46_im
	return tmp

Julia

function code(x_46_re, x_46_im, y_46_re, y_46_im)
	tmp = 0.0
	if ((y_46_re <= -5.7e-15) || !(y_46_re <= 8.2e+71))
		tmp = Float64(x_46_re / y_46_re);
	else
		tmp = Float64(x_46_im / y_46_im);
	end
	return tmp
end

MATLAB

function tmp_2 = code(x_46_re, x_46_im, y_46_re, y_46_im)
	tmp = 0.0;
	if ((y_46_re <= -5.7e-15) || ~((y_46_re <= 8.2e+71)))
		tmp = x_46_re / y_46_re;
	else
		tmp = x_46_im / y_46_im;
	end
	tmp_2 = tmp;
end

Wolfram

code[x$46$re_, x$46$im_, y$46$re_, y$46$im_] := If[Or[LessEqual[y$46$re, -5.7e-15], N[Not[LessEqual[y$46$re, 8.2e+71]], $MachinePrecision]], N[(x$46$re / y$46$re), $MachinePrecision], N[(x$46$im / y$46$im), $MachinePrecision]]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Alternative 12: 42.1% accurate, 5.0× speedup

Math

\[\begin{array}{l} \\ \frac{x.im}{y.im} \end{array} \]

FPCore

(FPCore (x.re x.im y.re y.im) :precision binary64 (/ x.im y.im))

C

double code(double x_46_re, double x_46_im, double y_46_re, double y_46_im) {
	return x_46_im / y_46_im;
}

Fortran

real(8) function code(x_46re, x_46im, y_46re, y_46im)
    real(8), intent (in) :: x_46re
    real(8), intent (in) :: x_46im
    real(8), intent (in) :: y_46re
    real(8), intent (in) :: y_46im
    code = x_46im / y_46im
end function

Java

public static double code(double x_46_re, double x_46_im, double y_46_re, double y_46_im) {
	return x_46_im / y_46_im;
}

Python

def code(x_46_re, x_46_im, y_46_re, y_46_im):
	return x_46_im / y_46_im

Julia

function code(x_46_re, x_46_im, y_46_re, y_46_im)
	return Float64(x_46_im / y_46_im)
end

MATLAB

function tmp = code(x_46_re, x_46_im, y_46_re, y_46_im)
	tmp = x_46_im / y_46_im;
end

Wolfram

code[x$46$re_, x$46$im_, y$46$re_, y$46$im_] := N[(x$46$im / y$46$im), $MachinePrecision]

Derivation

&prev;&pcontext;&pcontext2;&ctx;
1. Add Preprocessing

Reproduce

herbie shell --seed 2023350 
(FPCore (x.re x.im y.re y.im)
  :name "_divideComplex, real part"
  :precision binary64
  (/ (+ (* x.re y.re) (* x.im y.im)) (+ (* y.re y.re) (* y.im y.im))))