_divideComplex, imaginary part

Percentage Accurate: 62.0% → 84.8%

Time: 17.4s

Alternatives: 13

Speedup: 1.1×

Specification

Math

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

FPCore

(FPCore (x.re x.im y.re y.im)
 :precision binary64
 (/ (- (* x.im y.re) (* x.re 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_im * y_46_re) - (x_46_re * 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_46im * y_46re) - (x_46re * 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_im * y_46_re) - (x_46_re * 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_im * y_46_re) - (x_46_re * 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_im * y_46_re) - Float64(x_46_re * 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_im * y_46_re) - (x_46_re * 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$46$im * y$46$re), $MachinePrecision] - N[(x$46$re * 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: 62.0% accurate, 1.0× speedup

Math

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

FPCore

(FPCore (x.re x.im y.re y.im)
 :precision binary64
 (/ (- (* x.im y.re) (* x.re 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_im * y_46_re) - (x_46_re * 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_46im * y_46re) - (x_46re * 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_im * y_46_re) - (x_46_re * 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_im * y_46_re) - (x_46_re * 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_im * y_46_re) - Float64(x_46_re * 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_im * y_46_re) - (x_46_re * 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$46$im * y$46$re), $MachinePrecision] - N[(x$46$re * 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: 84.8% accurate, 0.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;\frac{x.im \cdot y.re - x.re \cdot y.im}{y.re \cdot y.re + y.im \cdot y.im} \leq 10^{+302}:\\ \;\;\;\;\frac{1}{\mathsf{hypot}\left(y.re, y.im\right)} \cdot \frac{\mathsf{fma}\left(x.im, y.re, x.re \cdot \left(-y.im\right)\right)}{\mathsf{hypot}\left(y.re, y.im\right)}\\ \mathbf{else}:\\ \;\;\;\;\frac{x.im}{y.re} - \frac{x.re}{\frac{y.re}{\frac{y.im}{y.re}}}\\ \end{array} \end{array} \]

FPCore

(FPCore (x.re x.im y.re y.im)
 :precision binary64
 (if (<=
      (/ (- (* x.im y.re) (* x.re y.im)) (+ (* y.re y.re) (* y.im y.im)))
      1e+302)
   (*
    (/ 1.0 (hypot y.re y.im))
    (/ (fma x.im y.re (* x.re (- y.im))) (hypot y.re y.im)))
   (- (/ x.im y.re) (/ x.re (/ y.re (/ y.im y.re))))))

C

double code(double x_46_re, double x_46_im, double y_46_re, double y_46_im) {
	double tmp;
	if ((((x_46_im * y_46_re) - (x_46_re * y_46_im)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im))) <= 1e+302) {
		tmp = (1.0 / hypot(y_46_re, y_46_im)) * (fma(x_46_im, y_46_re, (x_46_re * -y_46_im)) / hypot(y_46_re, y_46_im));
	} else {
		tmp = (x_46_im / y_46_re) - (x_46_re / (y_46_re / (y_46_im / y_46_re)));
	}
	return tmp;
}

Julia

function code(x_46_re, x_46_im, y_46_re, y_46_im)
	tmp = 0.0
	if (Float64(Float64(Float64(x_46_im * y_46_re) - Float64(x_46_re * y_46_im)) / Float64(Float64(y_46_re * y_46_re) + Float64(y_46_im * y_46_im))) <= 1e+302)
		tmp = Float64(Float64(1.0 / hypot(y_46_re, y_46_im)) * Float64(fma(x_46_im, y_46_re, Float64(x_46_re * Float64(-y_46_im))) / hypot(y_46_re, y_46_im)));
	else
		tmp = Float64(Float64(x_46_im / y_46_re) - Float64(x_46_re / Float64(y_46_re / Float64(y_46_im / y_46_re))));
	end
	return tmp
end

Wolfram

code[x$46$re_, x$46$im_, y$46$re_, y$46$im_] := If[LessEqual[N[(N[(N[(x$46$im * y$46$re), $MachinePrecision] - N[(x$46$re * y$46$im), $MachinePrecision]), $MachinePrecision] / N[(N[(y$46$re * y$46$re), $MachinePrecision] + N[(y$46$im * y$46$im), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 1e+302], N[(N[(1.0 / N[Sqrt[y$46$re ^ 2 + y$46$im ^ 2], $MachinePrecision]), $MachinePrecision] * N[(N[(x$46$im * y$46$re + N[(x$46$re * (-y$46$im)), $MachinePrecision]), $MachinePrecision] / N[Sqrt[y$46$re ^ 2 + y$46$im ^ 2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(x$46$im / y$46$re), $MachinePrecision] - N[(x$46$re / N[(y$46$re / N[(y$46$im / y$46$re), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

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

Alternative 2: 79.9% accurate, 0.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \frac{1}{\mathsf{hypot}\left(y.re, y.im\right)}\\ \mathbf{if}\;y.re \leq -3.3 \cdot 10^{+103}:\\ \;\;\;\;t_0 \cdot \mathsf{fma}\left(-1, x.im, y.im \cdot \frac{x.re}{y.re}\right)\\ \mathbf{elif}\;y.re \leq -1.2 \cdot 10^{-178}:\\ \;\;\;\;\mathsf{fma}\left(x.im, y.re, x.re \cdot \left(-y.im\right)\right) \cdot \frac{1}{{\left(\mathsf{hypot}\left(y.re, y.im\right)\right)}^{2}}\\ \mathbf{elif}\;y.re \leq 1.5 \cdot 10^{-162}:\\ \;\;\;\;\frac{y.re}{\frac{{y.im}^{2}}{x.im}} - \frac{x.re}{y.im}\\ \mathbf{elif}\;y.re \leq 2.9 \cdot 10^{+102}:\\ \;\;\;\;\frac{x.im \cdot y.re - x.re \cdot y.im}{y.re \cdot y.re + y.im \cdot y.im}\\ \mathbf{else}:\\ \;\;\;\;t_0 \cdot \left(x.im - \frac{x.re}{\frac{y.re}{y.im}}\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x.re x.im y.re y.im)
 :precision binary64
 (let* ((t_0 (/ 1.0 (hypot y.re y.im))))
   (if (<= y.re -3.3e+103)
     (* t_0 (fma -1.0 x.im (* y.im (/ x.re y.re))))
     (if (<= y.re -1.2e-178)
       (*
        (fma x.im y.re (* x.re (- y.im)))
        (/ 1.0 (pow (hypot y.re y.im) 2.0)))
       (if (<= y.re 1.5e-162)
         (- (/ y.re (/ (pow y.im 2.0) x.im)) (/ x.re y.im))
         (if (<= y.re 2.9e+102)
           (/ (- (* x.im y.re) (* x.re y.im)) (+ (* y.re y.re) (* y.im y.im)))
           (* t_0 (- x.im (/ x.re (/ 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 = 1.0 / hypot(y_46_re, y_46_im);
	double tmp;
	if (y_46_re <= -3.3e+103) {
		tmp = t_0 * fma(-1.0, x_46_im, (y_46_im * (x_46_re / y_46_re)));
	} else if (y_46_re <= -1.2e-178) {
		tmp = fma(x_46_im, y_46_re, (x_46_re * -y_46_im)) * (1.0 / pow(hypot(y_46_re, y_46_im), 2.0));
	} else if (y_46_re <= 1.5e-162) {
		tmp = (y_46_re / (pow(y_46_im, 2.0) / x_46_im)) - (x_46_re / y_46_im);
	} else if (y_46_re <= 2.9e+102) {
		tmp = ((x_46_im * y_46_re) - (x_46_re * y_46_im)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
	} else {
		tmp = t_0 * (x_46_im - (x_46_re / (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(1.0 / hypot(y_46_re, y_46_im))
	tmp = 0.0
	if (y_46_re <= -3.3e+103)
		tmp = Float64(t_0 * fma(-1.0, x_46_im, Float64(y_46_im * Float64(x_46_re / y_46_re))));
	elseif (y_46_re <= -1.2e-178)
		tmp = Float64(fma(x_46_im, y_46_re, Float64(x_46_re * Float64(-y_46_im))) * Float64(1.0 / (hypot(y_46_re, y_46_im) ^ 2.0)));
	elseif (y_46_re <= 1.5e-162)
		tmp = Float64(Float64(y_46_re / Float64((y_46_im ^ 2.0) / x_46_im)) - Float64(x_46_re / y_46_im));
	elseif (y_46_re <= 2.9e+102)
		tmp = Float64(Float64(Float64(x_46_im * y_46_re) - Float64(x_46_re * y_46_im)) / Float64(Float64(y_46_re * y_46_re) + Float64(y_46_im * y_46_im)));
	else
		tmp = Float64(t_0 * Float64(x_46_im - Float64(x_46_re / Float64(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[(1.0 / N[Sqrt[y$46$re ^ 2 + y$46$im ^ 2], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y$46$re, -3.3e+103], N[(t$95$0 * N[(-1.0 * x$46$im + N[(y$46$im * N[(x$46$re / y$46$re), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y$46$re, -1.2e-178], N[(N[(x$46$im * y$46$re + N[(x$46$re * (-y$46$im)), $MachinePrecision]), $MachinePrecision] * N[(1.0 / N[Power[N[Sqrt[y$46$re ^ 2 + y$46$im ^ 2], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y$46$re, 1.5e-162], N[(N[(y$46$re / N[(N[Power[y$46$im, 2.0], $MachinePrecision] / x$46$im), $MachinePrecision]), $MachinePrecision] - N[(x$46$re / y$46$im), $MachinePrecision]), $MachinePrecision], If[LessEqual[y$46$re, 2.9e+102], N[(N[(N[(x$46$im * y$46$re), $MachinePrecision] - N[(x$46$re * y$46$im), $MachinePrecision]), $MachinePrecision] / N[(N[(y$46$re * y$46$re), $MachinePrecision] + N[(y$46$im * y$46$im), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(t$95$0 * N[(x$46$im - N[(x$46$re / N[(y$46$re / y$46$im), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

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

Alternative 3: 79.9% accurate, 0.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \frac{x.im \cdot y.re - x.re \cdot y.im}{y.re \cdot y.re + y.im \cdot y.im}\\ t_1 := \frac{1}{\mathsf{hypot}\left(y.re, y.im\right)}\\ \mathbf{if}\;y.re \leq -1.05 \cdot 10^{+103}:\\ \;\;\;\;t_1 \cdot \mathsf{fma}\left(-1, x.im, y.im \cdot \frac{x.re}{y.re}\right)\\ \mathbf{elif}\;y.re \leq -3.8 \cdot 10^{-188}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;y.re \leq 1.2 \cdot 10^{-162}:\\ \;\;\;\;\frac{y.re}{\frac{{y.im}^{2}}{x.im}} - \frac{x.re}{y.im}\\ \mathbf{elif}\;y.re \leq 1.28 \cdot 10^{+101}:\\ \;\;\;\;t_0\\ \mathbf{else}:\\ \;\;\;\;t_1 \cdot \left(x.im - \frac{x.re}{\frac{y.re}{y.im}}\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x.re x.im y.re y.im)
 :precision binary64
 (let* ((t_0
         (/ (- (* x.im y.re) (* x.re y.im)) (+ (* y.re y.re) (* y.im y.im))))
        (t_1 (/ 1.0 (hypot y.re y.im))))
   (if (<= y.re -1.05e+103)
     (* t_1 (fma -1.0 x.im (* y.im (/ x.re y.re))))
     (if (<= y.re -3.8e-188)
       t_0
       (if (<= y.re 1.2e-162)
         (- (/ y.re (/ (pow y.im 2.0) x.im)) (/ x.re y.im))
         (if (<= y.re 1.28e+101)
           t_0
           (* t_1 (- x.im (/ x.re (/ 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_re) - (x_46_re * y_46_im)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
	double t_1 = 1.0 / hypot(y_46_re, y_46_im);
	double tmp;
	if (y_46_re <= -1.05e+103) {
		tmp = t_1 * fma(-1.0, x_46_im, (y_46_im * (x_46_re / y_46_re)));
	} else if (y_46_re <= -3.8e-188) {
		tmp = t_0;
	} else if (y_46_re <= 1.2e-162) {
		tmp = (y_46_re / (pow(y_46_im, 2.0) / x_46_im)) - (x_46_re / y_46_im);
	} else if (y_46_re <= 1.28e+101) {
		tmp = t_0;
	} else {
		tmp = t_1 * (x_46_im - (x_46_re / (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_re) - Float64(x_46_re * y_46_im)) / Float64(Float64(y_46_re * y_46_re) + Float64(y_46_im * y_46_im)))
	t_1 = Float64(1.0 / hypot(y_46_re, y_46_im))
	tmp = 0.0
	if (y_46_re <= -1.05e+103)
		tmp = Float64(t_1 * fma(-1.0, x_46_im, Float64(y_46_im * Float64(x_46_re / y_46_re))));
	elseif (y_46_re <= -3.8e-188)
		tmp = t_0;
	elseif (y_46_re <= 1.2e-162)
		tmp = Float64(Float64(y_46_re / Float64((y_46_im ^ 2.0) / x_46_im)) - Float64(x_46_re / y_46_im));
	elseif (y_46_re <= 1.28e+101)
		tmp = t_0;
	else
		tmp = Float64(t_1 * Float64(x_46_im - Float64(x_46_re / Float64(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$46$im * y$46$re), $MachinePrecision] - N[(x$46$re * y$46$im), $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[(1.0 / N[Sqrt[y$46$re ^ 2 + y$46$im ^ 2], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y$46$re, -1.05e+103], N[(t$95$1 * N[(-1.0 * x$46$im + N[(y$46$im * N[(x$46$re / y$46$re), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y$46$re, -3.8e-188], t$95$0, If[LessEqual[y$46$re, 1.2e-162], N[(N[(y$46$re / N[(N[Power[y$46$im, 2.0], $MachinePrecision] / x$46$im), $MachinePrecision]), $MachinePrecision] - N[(x$46$re / y$46$im), $MachinePrecision]), $MachinePrecision], If[LessEqual[y$46$re, 1.28e+101], t$95$0, N[(t$95$1 * N[(x$46$im - N[(x$46$re / N[(y$46$re / y$46$im), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]

Derivation

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

Alternative 4: 78.6% accurate, 0.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \frac{x.im \cdot y.re - x.re \cdot y.im}{y.re \cdot y.re + y.im \cdot y.im}\\ \mathbf{if}\;y.re \leq -1.46 \cdot 10^{+130}:\\ \;\;\;\;\frac{x.im}{y.re} - \frac{x.re}{\frac{y.re}{\frac{y.im}{y.re}}}\\ \mathbf{elif}\;y.re \leq -1.05 \cdot 10^{-178}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;y.re \leq 9 \cdot 10^{-163}:\\ \;\;\;\;\frac{y.re}{\frac{{y.im}^{2}}{x.im}} - \frac{x.re}{y.im}\\ \mathbf{elif}\;y.re \leq 9.4 \cdot 10^{+101}:\\ \;\;\;\;t_0\\ \mathbf{else}:\\ \;\;\;\;\frac{1}{\mathsf{hypot}\left(y.re, y.im\right)} \cdot \left(x.im - \frac{x.re}{\frac{y.re}{y.im}}\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x.re x.im y.re y.im)
 :precision binary64
 (let* ((t_0
         (/ (- (* x.im y.re) (* x.re y.im)) (+ (* y.re y.re) (* y.im y.im)))))
   (if (<= y.re -1.46e+130)
     (- (/ x.im y.re) (/ x.re (/ y.re (/ y.im y.re))))
     (if (<= y.re -1.05e-178)
       t_0
       (if (<= y.re 9e-163)
         (- (/ y.re (/ (pow y.im 2.0) x.im)) (/ x.re y.im))
         (if (<= y.re 9.4e+101)
           t_0
           (* (/ 1.0 (hypot y.re y.im)) (- x.im (/ x.re (/ 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_re) - (x_46_re * y_46_im)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
	double tmp;
	if (y_46_re <= -1.46e+130) {
		tmp = (x_46_im / y_46_re) - (x_46_re / (y_46_re / (y_46_im / y_46_re)));
	} else if (y_46_re <= -1.05e-178) {
		tmp = t_0;
	} else if (y_46_re <= 9e-163) {
		tmp = (y_46_re / (pow(y_46_im, 2.0) / x_46_im)) - (x_46_re / y_46_im);
	} else if (y_46_re <= 9.4e+101) {
		tmp = t_0;
	} else {
		tmp = (1.0 / hypot(y_46_re, y_46_im)) * (x_46_im - (x_46_re / (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_re) - (x_46_re * y_46_im)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
	double tmp;
	if (y_46_re <= -1.46e+130) {
		tmp = (x_46_im / y_46_re) - (x_46_re / (y_46_re / (y_46_im / y_46_re)));
	} else if (y_46_re <= -1.05e-178) {
		tmp = t_0;
	} else if (y_46_re <= 9e-163) {
		tmp = (y_46_re / (Math.pow(y_46_im, 2.0) / x_46_im)) - (x_46_re / y_46_im);
	} else if (y_46_re <= 9.4e+101) {
		tmp = t_0;
	} else {
		tmp = (1.0 / Math.hypot(y_46_re, y_46_im)) * (x_46_im - (x_46_re / (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_re) - (x_46_re * y_46_im)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im))
	tmp = 0
	if y_46_re <= -1.46e+130:
		tmp = (x_46_im / y_46_re) - (x_46_re / (y_46_re / (y_46_im / y_46_re)))
	elif y_46_re <= -1.05e-178:
		tmp = t_0
	elif y_46_re <= 9e-163:
		tmp = (y_46_re / (math.pow(y_46_im, 2.0) / x_46_im)) - (x_46_re / y_46_im)
	elif y_46_re <= 9.4e+101:
		tmp = t_0
	else:
		tmp = (1.0 / math.hypot(y_46_re, y_46_im)) * (x_46_im - (x_46_re / (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_re) - Float64(x_46_re * y_46_im)) / Float64(Float64(y_46_re * y_46_re) + Float64(y_46_im * y_46_im)))
	tmp = 0.0
	if (y_46_re <= -1.46e+130)
		tmp = Float64(Float64(x_46_im / y_46_re) - Float64(x_46_re / Float64(y_46_re / Float64(y_46_im / y_46_re))));
	elseif (y_46_re <= -1.05e-178)
		tmp = t_0;
	elseif (y_46_re <= 9e-163)
		tmp = Float64(Float64(y_46_re / Float64((y_46_im ^ 2.0) / x_46_im)) - Float64(x_46_re / y_46_im));
	elseif (y_46_re <= 9.4e+101)
		tmp = t_0;
	else
		tmp = Float64(Float64(1.0 / hypot(y_46_re, y_46_im)) * Float64(x_46_im - Float64(x_46_re / Float64(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_re) - (x_46_re * y_46_im)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
	tmp = 0.0;
	if (y_46_re <= -1.46e+130)
		tmp = (x_46_im / y_46_re) - (x_46_re / (y_46_re / (y_46_im / y_46_re)));
	elseif (y_46_re <= -1.05e-178)
		tmp = t_0;
	elseif (y_46_re <= 9e-163)
		tmp = (y_46_re / ((y_46_im ^ 2.0) / x_46_im)) - (x_46_re / y_46_im);
	elseif (y_46_re <= 9.4e+101)
		tmp = t_0;
	else
		tmp = (1.0 / hypot(y_46_re, y_46_im)) * (x_46_im - (x_46_re / (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$46$re), $MachinePrecision] - N[(x$46$re * y$46$im), $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, -1.46e+130], N[(N[(x$46$im / y$46$re), $MachinePrecision] - N[(x$46$re / N[(y$46$re / N[(y$46$im / y$46$re), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y$46$re, -1.05e-178], t$95$0, If[LessEqual[y$46$re, 9e-163], N[(N[(y$46$re / N[(N[Power[y$46$im, 2.0], $MachinePrecision] / x$46$im), $MachinePrecision]), $MachinePrecision] - N[(x$46$re / y$46$im), $MachinePrecision]), $MachinePrecision], If[LessEqual[y$46$re, 9.4e+101], t$95$0, N[(N[(1.0 / N[Sqrt[y$46$re ^ 2 + y$46$im ^ 2], $MachinePrecision]), $MachinePrecision] * N[(x$46$im - N[(x$46$re / N[(y$46$re / y$46$im), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

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

Alternative 5: 79.0% accurate, 0.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \frac{x.im \cdot y.re - x.re \cdot y.im}{y.re \cdot y.re + y.im \cdot y.im}\\ t_1 := \frac{1}{\mathsf{hypot}\left(y.re, y.im\right)}\\ \mathbf{if}\;y.re \leq -1.75 \cdot 10^{+106}:\\ \;\;\;\;t_1 \cdot \left(\frac{x.re \cdot y.im}{y.re} - x.im\right)\\ \mathbf{elif}\;y.re \leq -3.2 \cdot 10^{-176}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;y.re \leq 1.4 \cdot 10^{-162}:\\ \;\;\;\;\frac{y.re}{\frac{{y.im}^{2}}{x.im}} - \frac{x.re}{y.im}\\ \mathbf{elif}\;y.re \leq 4.8 \cdot 10^{+101}:\\ \;\;\;\;t_0\\ \mathbf{else}:\\ \;\;\;\;t_1 \cdot \left(x.im - \frac{x.re}{\frac{y.re}{y.im}}\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x.re x.im y.re y.im)
 :precision binary64
 (let* ((t_0
         (/ (- (* x.im y.re) (* x.re y.im)) (+ (* y.re y.re) (* y.im y.im))))
        (t_1 (/ 1.0 (hypot y.re y.im))))
   (if (<= y.re -1.75e+106)
     (* t_1 (- (/ (* x.re y.im) y.re) x.im))
     (if (<= y.re -3.2e-176)
       t_0
       (if (<= y.re 1.4e-162)
         (- (/ y.re (/ (pow y.im 2.0) x.im)) (/ x.re y.im))
         (if (<= y.re 4.8e+101)
           t_0
           (* t_1 (- x.im (/ x.re (/ 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_re) - (x_46_re * y_46_im)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
	double t_1 = 1.0 / hypot(y_46_re, y_46_im);
	double tmp;
	if (y_46_re <= -1.75e+106) {
		tmp = t_1 * (((x_46_re * y_46_im) / y_46_re) - x_46_im);
	} else if (y_46_re <= -3.2e-176) {
		tmp = t_0;
	} else if (y_46_re <= 1.4e-162) {
		tmp = (y_46_re / (pow(y_46_im, 2.0) / x_46_im)) - (x_46_re / y_46_im);
	} else if (y_46_re <= 4.8e+101) {
		tmp = t_0;
	} else {
		tmp = t_1 * (x_46_im - (x_46_re / (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_re) - (x_46_re * y_46_im)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
	double t_1 = 1.0 / Math.hypot(y_46_re, y_46_im);
	double tmp;
	if (y_46_re <= -1.75e+106) {
		tmp = t_1 * (((x_46_re * y_46_im) / y_46_re) - x_46_im);
	} else if (y_46_re <= -3.2e-176) {
		tmp = t_0;
	} else if (y_46_re <= 1.4e-162) {
		tmp = (y_46_re / (Math.pow(y_46_im, 2.0) / x_46_im)) - (x_46_re / y_46_im);
	} else if (y_46_re <= 4.8e+101) {
		tmp = t_0;
	} else {
		tmp = t_1 * (x_46_im - (x_46_re / (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_re) - (x_46_re * y_46_im)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im))
	t_1 = 1.0 / math.hypot(y_46_re, y_46_im)
	tmp = 0
	if y_46_re <= -1.75e+106:
		tmp = t_1 * (((x_46_re * y_46_im) / y_46_re) - x_46_im)
	elif y_46_re <= -3.2e-176:
		tmp = t_0
	elif y_46_re <= 1.4e-162:
		tmp = (y_46_re / (math.pow(y_46_im, 2.0) / x_46_im)) - (x_46_re / y_46_im)
	elif y_46_re <= 4.8e+101:
		tmp = t_0
	else:
		tmp = t_1 * (x_46_im - (x_46_re / (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_re) - Float64(x_46_re * y_46_im)) / Float64(Float64(y_46_re * y_46_re) + Float64(y_46_im * y_46_im)))
	t_1 = Float64(1.0 / hypot(y_46_re, y_46_im))
	tmp = 0.0
	if (y_46_re <= -1.75e+106)
		tmp = Float64(t_1 * Float64(Float64(Float64(x_46_re * y_46_im) / y_46_re) - x_46_im));
	elseif (y_46_re <= -3.2e-176)
		tmp = t_0;
	elseif (y_46_re <= 1.4e-162)
		tmp = Float64(Float64(y_46_re / Float64((y_46_im ^ 2.0) / x_46_im)) - Float64(x_46_re / y_46_im));
	elseif (y_46_re <= 4.8e+101)
		tmp = t_0;
	else
		tmp = Float64(t_1 * Float64(x_46_im - Float64(x_46_re / Float64(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_re) - (x_46_re * y_46_im)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
	t_1 = 1.0 / hypot(y_46_re, y_46_im);
	tmp = 0.0;
	if (y_46_re <= -1.75e+106)
		tmp = t_1 * (((x_46_re * y_46_im) / y_46_re) - x_46_im);
	elseif (y_46_re <= -3.2e-176)
		tmp = t_0;
	elseif (y_46_re <= 1.4e-162)
		tmp = (y_46_re / ((y_46_im ^ 2.0) / x_46_im)) - (x_46_re / y_46_im);
	elseif (y_46_re <= 4.8e+101)
		tmp = t_0;
	else
		tmp = t_1 * (x_46_im - (x_46_re / (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$46$re), $MachinePrecision] - N[(x$46$re * y$46$im), $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[(1.0 / N[Sqrt[y$46$re ^ 2 + y$46$im ^ 2], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y$46$re, -1.75e+106], N[(t$95$1 * N[(N[(N[(x$46$re * y$46$im), $MachinePrecision] / y$46$re), $MachinePrecision] - x$46$im), $MachinePrecision]), $MachinePrecision], If[LessEqual[y$46$re, -3.2e-176], t$95$0, If[LessEqual[y$46$re, 1.4e-162], N[(N[(y$46$re / N[(N[Power[y$46$im, 2.0], $MachinePrecision] / x$46$im), $MachinePrecision]), $MachinePrecision] - N[(x$46$re / y$46$im), $MachinePrecision]), $MachinePrecision], If[LessEqual[y$46$re, 4.8e+101], t$95$0, N[(t$95$1 * N[(x$46$im - N[(x$46$re / N[(y$46$re / y$46$im), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]

Derivation

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

Alternative 6: 77.6% accurate, 0.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \frac{x.im \cdot y.re - x.re \cdot y.im}{y.re \cdot y.re + y.im \cdot y.im}\\ t_1 := \frac{x.im}{y.re} - \frac{x.re}{\frac{y.re}{\frac{y.im}{y.re}}}\\ \mathbf{if}\;y.re \leq -9.6 \cdot 10^{+129}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y.re \leq -3 \cdot 10^{-181}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;y.re \leq 9.6 \cdot 10^{-163}:\\ \;\;\;\;\frac{y.re}{\frac{{y.im}^{2}}{x.im}} - \frac{x.re}{y.im}\\ \mathbf{elif}\;y.re \leq 9 \cdot 10^{+101}:\\ \;\;\;\;t_0\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x.re x.im y.re y.im)
 :precision binary64
 (let* ((t_0
         (/ (- (* x.im y.re) (* x.re y.im)) (+ (* y.re y.re) (* y.im y.im))))
        (t_1 (- (/ x.im y.re) (/ x.re (/ y.re (/ y.im y.re))))))
   (if (<= y.re -9.6e+129)
     t_1
     (if (<= y.re -3e-181)
       t_0
       (if (<= y.re 9.6e-163)
         (- (/ y.re (/ (pow y.im 2.0) x.im)) (/ x.re y.im))
         (if (<= y.re 9e+101) 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_re) - (x_46_re * y_46_im)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
	double t_1 = (x_46_im / y_46_re) - (x_46_re / (y_46_re / (y_46_im / y_46_re)));
	double tmp;
	if (y_46_re <= -9.6e+129) {
		tmp = t_1;
	} else if (y_46_re <= -3e-181) {
		tmp = t_0;
	} else if (y_46_re <= 9.6e-163) {
		tmp = (y_46_re / (pow(y_46_im, 2.0) / x_46_im)) - (x_46_re / y_46_im);
	} else if (y_46_re <= 9e+101) {
		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_46re) - (x_46re * y_46im)) / ((y_46re * y_46re) + (y_46im * y_46im))
    t_1 = (x_46im / y_46re) - (x_46re / (y_46re / (y_46im / y_46re)))
    if (y_46re <= (-9.6d+129)) then
        tmp = t_1
    else if (y_46re <= (-3d-181)) then
        tmp = t_0
    else if (y_46re <= 9.6d-163) then
        tmp = (y_46re / ((y_46im ** 2.0d0) / x_46im)) - (x_46re / y_46im)
    else if (y_46re <= 9d+101) 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_re) - (x_46_re * y_46_im)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
	double t_1 = (x_46_im / y_46_re) - (x_46_re / (y_46_re / (y_46_im / y_46_re)));
	double tmp;
	if (y_46_re <= -9.6e+129) {
		tmp = t_1;
	} else if (y_46_re <= -3e-181) {
		tmp = t_0;
	} else if (y_46_re <= 9.6e-163) {
		tmp = (y_46_re / (Math.pow(y_46_im, 2.0) / x_46_im)) - (x_46_re / y_46_im);
	} else if (y_46_re <= 9e+101) {
		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_re) - (x_46_re * y_46_im)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im))
	t_1 = (x_46_im / y_46_re) - (x_46_re / (y_46_re / (y_46_im / y_46_re)))
	tmp = 0
	if y_46_re <= -9.6e+129:
		tmp = t_1
	elif y_46_re <= -3e-181:
		tmp = t_0
	elif y_46_re <= 9.6e-163:
		tmp = (y_46_re / (math.pow(y_46_im, 2.0) / x_46_im)) - (x_46_re / y_46_im)
	elif y_46_re <= 9e+101:
		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_re) - Float64(x_46_re * y_46_im)) / Float64(Float64(y_46_re * y_46_re) + Float64(y_46_im * y_46_im)))
	t_1 = Float64(Float64(x_46_im / y_46_re) - Float64(x_46_re / Float64(y_46_re / Float64(y_46_im / y_46_re))))
	tmp = 0.0
	if (y_46_re <= -9.6e+129)
		tmp = t_1;
	elseif (y_46_re <= -3e-181)
		tmp = t_0;
	elseif (y_46_re <= 9.6e-163)
		tmp = Float64(Float64(y_46_re / Float64((y_46_im ^ 2.0) / x_46_im)) - Float64(x_46_re / y_46_im));
	elseif (y_46_re <= 9e+101)
		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_re) - (x_46_re * y_46_im)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
	t_1 = (x_46_im / y_46_re) - (x_46_re / (y_46_re / (y_46_im / y_46_re)));
	tmp = 0.0;
	if (y_46_re <= -9.6e+129)
		tmp = t_1;
	elseif (y_46_re <= -3e-181)
		tmp = t_0;
	elseif (y_46_re <= 9.6e-163)
		tmp = (y_46_re / ((y_46_im ^ 2.0) / x_46_im)) - (x_46_re / y_46_im);
	elseif (y_46_re <= 9e+101)
		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$46$re), $MachinePrecision] - N[(x$46$re * y$46$im), $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$46$re), $MachinePrecision] - N[(x$46$re / N[(y$46$re / N[(y$46$im / y$46$re), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y$46$re, -9.6e+129], t$95$1, If[LessEqual[y$46$re, -3e-181], t$95$0, If[LessEqual[y$46$re, 9.6e-163], N[(N[(y$46$re / N[(N[Power[y$46$im, 2.0], $MachinePrecision] / x$46$im), $MachinePrecision]), $MachinePrecision] - N[(x$46$re / y$46$im), $MachinePrecision]), $MachinePrecision], If[LessEqual[y$46$re, 9e+101], t$95$0, t$95$1]]]]]]

Derivation

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

Alternative 7: 76.8% accurate, 0.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_0 := \frac{x.im \cdot y.re - x.re \cdot y.im}{y.re \cdot y.re + y.im \cdot y.im}\\ t_1 := \frac{x.im}{y.re} - \frac{x.re}{\frac{y.re}{\frac{y.im}{y.re}}}\\ \mathbf{if}\;y.re \leq -9.6 \cdot 10^{+129}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y.re \leq -5 \cdot 10^{-168}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;y.re \leq 1.7 \cdot 10^{-261}:\\ \;\;\;\;-\frac{x.re}{y.im}\\ \mathbf{elif}\;y.re \leq 5.4 \cdot 10^{+101}:\\ \;\;\;\;t_0\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x.re x.im y.re y.im)
 :precision binary64
 (let* ((t_0
         (/ (- (* x.im y.re) (* x.re y.im)) (+ (* y.re y.re) (* y.im y.im))))
        (t_1 (- (/ x.im y.re) (/ x.re (/ y.re (/ y.im y.re))))))
   (if (<= y.re -9.6e+129)
     t_1
     (if (<= y.re -5e-168)
       t_0
       (if (<= y.re 1.7e-261)
         (- (/ x.re y.im))
         (if (<= y.re 5.4e+101) 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_re) - (x_46_re * y_46_im)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
	double t_1 = (x_46_im / y_46_re) - (x_46_re / (y_46_re / (y_46_im / y_46_re)));
	double tmp;
	if (y_46_re <= -9.6e+129) {
		tmp = t_1;
	} else if (y_46_re <= -5e-168) {
		tmp = t_0;
	} else if (y_46_re <= 1.7e-261) {
		tmp = -(x_46_re / y_46_im);
	} else if (y_46_re <= 5.4e+101) {
		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_46re) - (x_46re * y_46im)) / ((y_46re * y_46re) + (y_46im * y_46im))
    t_1 = (x_46im / y_46re) - (x_46re / (y_46re / (y_46im / y_46re)))
    if (y_46re <= (-9.6d+129)) then
        tmp = t_1
    else if (y_46re <= (-5d-168)) then
        tmp = t_0
    else if (y_46re <= 1.7d-261) then
        tmp = -(x_46re / y_46im)
    else if (y_46re <= 5.4d+101) 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_re) - (x_46_re * y_46_im)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
	double t_1 = (x_46_im / y_46_re) - (x_46_re / (y_46_re / (y_46_im / y_46_re)));
	double tmp;
	if (y_46_re <= -9.6e+129) {
		tmp = t_1;
	} else if (y_46_re <= -5e-168) {
		tmp = t_0;
	} else if (y_46_re <= 1.7e-261) {
		tmp = -(x_46_re / y_46_im);
	} else if (y_46_re <= 5.4e+101) {
		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_re) - (x_46_re * y_46_im)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im))
	t_1 = (x_46_im / y_46_re) - (x_46_re / (y_46_re / (y_46_im / y_46_re)))
	tmp = 0
	if y_46_re <= -9.6e+129:
		tmp = t_1
	elif y_46_re <= -5e-168:
		tmp = t_0
	elif y_46_re <= 1.7e-261:
		tmp = -(x_46_re / y_46_im)
	elif y_46_re <= 5.4e+101:
		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_re) - Float64(x_46_re * y_46_im)) / Float64(Float64(y_46_re * y_46_re) + Float64(y_46_im * y_46_im)))
	t_1 = Float64(Float64(x_46_im / y_46_re) - Float64(x_46_re / Float64(y_46_re / Float64(y_46_im / y_46_re))))
	tmp = 0.0
	if (y_46_re <= -9.6e+129)
		tmp = t_1;
	elseif (y_46_re <= -5e-168)
		tmp = t_0;
	elseif (y_46_re <= 1.7e-261)
		tmp = Float64(-Float64(x_46_re / y_46_im));
	elseif (y_46_re <= 5.4e+101)
		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_re) - (x_46_re * y_46_im)) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
	t_1 = (x_46_im / y_46_re) - (x_46_re / (y_46_re / (y_46_im / y_46_re)));
	tmp = 0.0;
	if (y_46_re <= -9.6e+129)
		tmp = t_1;
	elseif (y_46_re <= -5e-168)
		tmp = t_0;
	elseif (y_46_re <= 1.7e-261)
		tmp = -(x_46_re / y_46_im);
	elseif (y_46_re <= 5.4e+101)
		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$46$re), $MachinePrecision] - N[(x$46$re * y$46$im), $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$46$re), $MachinePrecision] - N[(x$46$re / N[(y$46$re / N[(y$46$im / y$46$re), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y$46$re, -9.6e+129], t$95$1, If[LessEqual[y$46$re, -5e-168], t$95$0, If[LessEqual[y$46$re, 1.7e-261], (-N[(x$46$re / y$46$im), $MachinePrecision]), If[LessEqual[y$46$re, 5.4e+101], t$95$0, t$95$1]]]]]]

Derivation

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

Alternative 8: 70.8% accurate, 0.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_0 := -\frac{x.re}{y.im}\\ \mathbf{if}\;y.im \leq -1.35 \cdot 10^{+129}:\\ \;\;\;\;t_0\\ \mathbf{elif}\;y.im \leq -2.7 \cdot 10^{-59}:\\ \;\;\;\;\frac{x.re \cdot \left(-y.im\right)}{y.re \cdot y.re + y.im \cdot y.im}\\ \mathbf{elif}\;y.im \leq 3.3 \cdot 10^{+67}:\\ \;\;\;\;\frac{x.im}{y.re} - \frac{x.re}{\frac{y.re}{\frac{y.im}{y.re}}}\\ \mathbf{else}:\\ \;\;\;\;t_0\\ \end{array} \end{array} \]

FPCore

(FPCore (x.re x.im y.re y.im)
 :precision binary64
 (let* ((t_0 (- (/ x.re y.im))))
   (if (<= y.im -1.35e+129)
     t_0
     (if (<= y.im -2.7e-59)
       (/ (* x.re (- y.im)) (+ (* y.re y.re) (* y.im y.im)))
       (if (<= y.im 3.3e+67)
         (- (/ x.im y.re) (/ x.re (/ y.re (/ y.im y.re))))
         t_0)))))

C

double code(double x_46_re, double x_46_im, double y_46_re, double y_46_im) {
	double t_0 = -(x_46_re / y_46_im);
	double tmp;
	if (y_46_im <= -1.35e+129) {
		tmp = t_0;
	} else if (y_46_im <= -2.7e-59) {
		tmp = (x_46_re * -y_46_im) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
	} else if (y_46_im <= 3.3e+67) {
		tmp = (x_46_im / y_46_re) - (x_46_re / (y_46_re / (y_46_im / y_46_re)));
	} else {
		tmp = t_0;
	}
	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_46re / y_46im)
    if (y_46im <= (-1.35d+129)) then
        tmp = t_0
    else if (y_46im <= (-2.7d-59)) then
        tmp = (x_46re * -y_46im) / ((y_46re * y_46re) + (y_46im * y_46im))
    else if (y_46im <= 3.3d+67) then
        tmp = (x_46im / y_46re) - (x_46re / (y_46re / (y_46im / y_46re)))
    else
        tmp = t_0
    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_re / y_46_im);
	double tmp;
	if (y_46_im <= -1.35e+129) {
		tmp = t_0;
	} else if (y_46_im <= -2.7e-59) {
		tmp = (x_46_re * -y_46_im) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
	} else if (y_46_im <= 3.3e+67) {
		tmp = (x_46_im / y_46_re) - (x_46_re / (y_46_re / (y_46_im / y_46_re)));
	} else {
		tmp = t_0;
	}
	return tmp;
}

Python

def code(x_46_re, x_46_im, y_46_re, y_46_im):
	t_0 = -(x_46_re / y_46_im)
	tmp = 0
	if y_46_im <= -1.35e+129:
		tmp = t_0
	elif y_46_im <= -2.7e-59:
		tmp = (x_46_re * -y_46_im) / ((y_46_re * y_46_re) + (y_46_im * y_46_im))
	elif y_46_im <= 3.3e+67:
		tmp = (x_46_im / y_46_re) - (x_46_re / (y_46_re / (y_46_im / y_46_re)))
	else:
		tmp = t_0
	return tmp

Julia

function code(x_46_re, x_46_im, y_46_re, y_46_im)
	t_0 = Float64(-Float64(x_46_re / y_46_im))
	tmp = 0.0
	if (y_46_im <= -1.35e+129)
		tmp = t_0;
	elseif (y_46_im <= -2.7e-59)
		tmp = Float64(Float64(x_46_re * Float64(-y_46_im)) / Float64(Float64(y_46_re * y_46_re) + Float64(y_46_im * y_46_im)));
	elseif (y_46_im <= 3.3e+67)
		tmp = Float64(Float64(x_46_im / y_46_re) - Float64(x_46_re / Float64(y_46_re / Float64(y_46_im / y_46_re))));
	else
		tmp = t_0;
	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_re / y_46_im);
	tmp = 0.0;
	if (y_46_im <= -1.35e+129)
		tmp = t_0;
	elseif (y_46_im <= -2.7e-59)
		tmp = (x_46_re * -y_46_im) / ((y_46_re * y_46_re) + (y_46_im * y_46_im));
	elseif (y_46_im <= 3.3e+67)
		tmp = (x_46_im / y_46_re) - (x_46_re / (y_46_re / (y_46_im / y_46_re)));
	else
		tmp = t_0;
	end
	tmp_2 = tmp;
end

Wolfram

code[x$46$re_, x$46$im_, y$46$re_, y$46$im_] := Block[{t$95$0 = (-N[(x$46$re / y$46$im), $MachinePrecision])}, If[LessEqual[y$46$im, -1.35e+129], t$95$0, If[LessEqual[y$46$im, -2.7e-59], N[(N[(x$46$re * (-y$46$im)), $MachinePrecision] / N[(N[(y$46$re * y$46$re), $MachinePrecision] + N[(y$46$im * y$46$im), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y$46$im, 3.3e+67], N[(N[(x$46$im / y$46$re), $MachinePrecision] - N[(x$46$re / N[(y$46$re / N[(y$46$im / y$46$re), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$0]]]]

Derivation

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

Alternative 9: 70.7% accurate, 0.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y.im \leq -0.0034 \lor \neg \left(y.im \leq 3.2 \cdot 10^{+67}\right):\\ \;\;\;\;-\frac{x.re}{y.im}\\ \mathbf{else}:\\ \;\;\;\;\frac{x.im}{y.re} - \frac{x.re}{\frac{y.re}{\frac{y.im}{y.re}}}\\ \end{array} \end{array} \]

FPCore

(FPCore (x.re x.im y.re y.im)
 :precision binary64
 (if (or (<= y.im -0.0034) (not (<= y.im 3.2e+67)))
   (- (/ x.re y.im))
   (- (/ x.im y.re) (/ x.re (/ y.re (/ y.im y.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_im <= -0.0034) || !(y_46_im <= 3.2e+67)) {
		tmp = -(x_46_re / y_46_im);
	} else {
		tmp = (x_46_im / y_46_re) - (x_46_re / (y_46_re / (y_46_im / 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) :: tmp
    if ((y_46im <= (-0.0034d0)) .or. (.not. (y_46im <= 3.2d+67))) then
        tmp = -(x_46re / y_46im)
    else
        tmp = (x_46im / y_46re) - (x_46re / (y_46re / (y_46im / 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 tmp;
	if ((y_46_im <= -0.0034) || !(y_46_im <= 3.2e+67)) {
		tmp = -(x_46_re / y_46_im);
	} else {
		tmp = (x_46_im / y_46_re) - (x_46_re / (y_46_re / (y_46_im / y_46_re)));
	}
	return tmp;
}

Python

def code(x_46_re, x_46_im, y_46_re, y_46_im):
	tmp = 0
	if (y_46_im <= -0.0034) or not (y_46_im <= 3.2e+67):
		tmp = -(x_46_re / y_46_im)
	else:
		tmp = (x_46_im / y_46_re) - (x_46_re / (y_46_re / (y_46_im / y_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_im <= -0.0034) || !(y_46_im <= 3.2e+67))
		tmp = Float64(-Float64(x_46_re / y_46_im));
	else
		tmp = Float64(Float64(x_46_im / y_46_re) - Float64(x_46_re / Float64(y_46_re / Float64(y_46_im / y_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_im <= -0.0034) || ~((y_46_im <= 3.2e+67)))
		tmp = -(x_46_re / y_46_im);
	else
		tmp = (x_46_im / y_46_re) - (x_46_re / (y_46_re / (y_46_im / y_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$46$im, -0.0034], N[Not[LessEqual[y$46$im, 3.2e+67]], $MachinePrecision]], (-N[(x$46$re / y$46$im), $MachinePrecision]), N[(N[(x$46$im / y$46$re), $MachinePrecision] - N[(x$46$re / N[(y$46$re / N[(y$46$im / y$46$re), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

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

Alternative 10: 42.9% accurate, 1.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y.im \leq -1.66 \cdot 10^{+94} \lor \neg \left(y.im \leq 1.2 \cdot 10^{+196}\right):\\ \;\;\;\;\frac{-x.im}{y.im}\\ \mathbf{else}:\\ \;\;\;\;\frac{x.im}{y.re}\\ \end{array} \end{array} \]

FPCore

(FPCore (x.re x.im y.re y.im)
 :precision binary64
 (if (or (<= y.im -1.66e+94) (not (<= y.im 1.2e+196)))
   (/ (- x.im) y.im)
   (/ x.im y.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_im <= -1.66e+94) || !(y_46_im <= 1.2e+196)) {
		tmp = -x_46_im / y_46_im;
	} else {
		tmp = x_46_im / 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) :: tmp
    if ((y_46im <= (-1.66d+94)) .or. (.not. (y_46im <= 1.2d+196))) then
        tmp = -x_46im / y_46im
    else
        tmp = x_46im / 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 tmp;
	if ((y_46_im <= -1.66e+94) || !(y_46_im <= 1.2e+196)) {
		tmp = -x_46_im / y_46_im;
	} else {
		tmp = x_46_im / y_46_re;
	}
	return tmp;
}

Python

def code(x_46_re, x_46_im, y_46_re, y_46_im):
	tmp = 0
	if (y_46_im <= -1.66e+94) or not (y_46_im <= 1.2e+196):
		tmp = -x_46_im / y_46_im
	else:
		tmp = x_46_im / y_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_im <= -1.66e+94) || !(y_46_im <= 1.2e+196))
		tmp = Float64(Float64(-x_46_im) / y_46_im);
	else
		tmp = Float64(x_46_im / y_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_im <= -1.66e+94) || ~((y_46_im <= 1.2e+196)))
		tmp = -x_46_im / y_46_im;
	else
		tmp = x_46_im / y_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$46$im, -1.66e+94], N[Not[LessEqual[y$46$im, 1.2e+196]], $MachinePrecision]], N[((-x$46$im) / y$46$im), $MachinePrecision], N[(x$46$im / y$46$re), $MachinePrecision]]

Derivation

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

Alternative 11: 62.6% accurate, 1.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y.im \leq -2.5 \cdot 10^{-59} \lor \neg \left(y.im \leq 2.35 \cdot 10^{+64}\right):\\ \;\;\;\;-\frac{x.re}{y.im}\\ \mathbf{else}:\\ \;\;\;\;\frac{x.im}{y.re}\\ \end{array} \end{array} \]

FPCore

(FPCore (x.re x.im y.re y.im)
 :precision binary64
 (if (or (<= y.im -2.5e-59) (not (<= y.im 2.35e+64)))
   (- (/ x.re y.im))
   (/ x.im y.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_im <= -2.5e-59) || !(y_46_im <= 2.35e+64)) {
		tmp = -(x_46_re / y_46_im);
	} else {
		tmp = x_46_im / 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) :: tmp
    if ((y_46im <= (-2.5d-59)) .or. (.not. (y_46im <= 2.35d+64))) then
        tmp = -(x_46re / y_46im)
    else
        tmp = x_46im / 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 tmp;
	if ((y_46_im <= -2.5e-59) || !(y_46_im <= 2.35e+64)) {
		tmp = -(x_46_re / y_46_im);
	} else {
		tmp = x_46_im / y_46_re;
	}
	return tmp;
}

Python

def code(x_46_re, x_46_im, y_46_re, y_46_im):
	tmp = 0
	if (y_46_im <= -2.5e-59) or not (y_46_im <= 2.35e+64):
		tmp = -(x_46_re / y_46_im)
	else:
		tmp = x_46_im / y_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_im <= -2.5e-59) || !(y_46_im <= 2.35e+64))
		tmp = Float64(-Float64(x_46_re / y_46_im));
	else
		tmp = Float64(x_46_im / y_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_im <= -2.5e-59) || ~((y_46_im <= 2.35e+64)))
		tmp = -(x_46_re / y_46_im);
	else
		tmp = x_46_im / y_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$46$im, -2.5e-59], N[Not[LessEqual[y$46$im, 2.35e+64]], $MachinePrecision]], (-N[(x$46$re / y$46$im), $MachinePrecision]), N[(x$46$im / y$46$re), $MachinePrecision]]

Derivation

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

Alternative 12: 43.2% accurate, 1.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y.im \leq -1.75 \cdot 10^{+109} \lor \neg \left(y.im \leq 6 \cdot 10^{+194}\right):\\ \;\;\;\;\frac{x.im}{y.im}\\ \mathbf{else}:\\ \;\;\;\;\frac{x.im}{y.re}\\ \end{array} \end{array} \]

FPCore

(FPCore (x.re x.im y.re y.im)
 :precision binary64
 (if (or (<= y.im -1.75e+109) (not (<= y.im 6e+194)))
   (/ x.im y.im)
   (/ x.im y.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_im <= -1.75e+109) || !(y_46_im <= 6e+194)) {
		tmp = x_46_im / y_46_im;
	} else {
		tmp = x_46_im / 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) :: tmp
    if ((y_46im <= (-1.75d+109)) .or. (.not. (y_46im <= 6d+194))) then
        tmp = x_46im / y_46im
    else
        tmp = x_46im / 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 tmp;
	if ((y_46_im <= -1.75e+109) || !(y_46_im <= 6e+194)) {
		tmp = x_46_im / y_46_im;
	} else {
		tmp = x_46_im / y_46_re;
	}
	return tmp;
}

Python

def code(x_46_re, x_46_im, y_46_re, y_46_im):
	tmp = 0
	if (y_46_im <= -1.75e+109) or not (y_46_im <= 6e+194):
		tmp = x_46_im / y_46_im
	else:
		tmp = x_46_im / y_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_im <= -1.75e+109) || !(y_46_im <= 6e+194))
		tmp = Float64(x_46_im / y_46_im);
	else
		tmp = Float64(x_46_im / y_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_im <= -1.75e+109) || ~((y_46_im <= 6e+194)))
		tmp = x_46_im / y_46_im;
	else
		tmp = x_46_im / y_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$46$im, -1.75e+109], N[Not[LessEqual[y$46$im, 6e+194]], $MachinePrecision]], N[(x$46$im / y$46$im), $MachinePrecision], N[(x$46$im / y$46$re), $MachinePrecision]]

Derivation

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

Alternative 13: 9.4% 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 2024006 
(FPCore (x.re x.im y.re y.im)
  :name "_divideComplex, imaginary part"
  :precision binary64
  (/ (- (* x.im y.re) (* x.re y.im)) (+ (* y.re y.re) (* y.im y.im))))