Linear.Matrix:det33 from linear-1.19.1.3

Percentage Accurate: 74.0% → 82.8%

Time: 30.3s

Alternatives: 24

Speedup: 0.5×

• 57.6% of points produce a very large (infinite) output. You may want to add a precondition.

Specification

Math

\[\begin{array}{l} \\ \left(x \cdot \left(y \cdot z - t \cdot a\right) - b \cdot \left(c \cdot z - i \cdot a\right)\right) + j \cdot \left(c \cdot t - i \cdot y\right) \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (+
  (- (* x (- (* y z) (* t a))) (* b (- (* c z) (* i a))))
  (* j (- (* c t) (* i y)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	return ((x * ((y * z) - (t * a))) - (b * ((c * z) - (i * a)))) + (j * ((c * t) - (i * y)));
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    code = ((x * ((y * z) - (t * a))) - (b * ((c * z) - (i * a)))) + (j * ((c * t) - (i * y)))
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	return ((x * ((y * z) - (t * a))) - (b * ((c * z) - (i * a)))) + (j * ((c * t) - (i * y)));
}

Python

def code(x, y, z, t, a, b, c, i, j):
	return ((x * ((y * z) - (t * a))) - (b * ((c * z) - (i * a)))) + (j * ((c * t) - (i * y)))

Julia

function code(x, y, z, t, a, b, c, i, j)
	return Float64(Float64(Float64(x * Float64(Float64(y * z) - Float64(t * a))) - Float64(b * Float64(Float64(c * z) - Float64(i * a)))) + Float64(j * Float64(Float64(c * t) - Float64(i * y))))
end

MATLAB

function tmp = code(x, y, z, t, a, b, c, i, j)
	tmp = ((x * ((y * z) - (t * a))) - (b * ((c * z) - (i * a)))) + (j * ((c * t) - (i * y)));
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := N[(N[(N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(b * N[(N[(c * z), $MachinePrecision] - N[(i * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(j * N[(N[(c * t), $MachinePrecision] - N[(i * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Initial Program: 74.0% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ \left(x \cdot \left(y \cdot z - t \cdot a\right) - b \cdot \left(c \cdot z - i \cdot a\right)\right) + j \cdot \left(c \cdot t - i \cdot y\right) \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (+
  (- (* x (- (* y z) (* t a))) (* b (- (* c z) (* i a))))
  (* j (- (* c t) (* i y)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	return ((x * ((y * z) - (t * a))) - (b * ((c * z) - (i * a)))) + (j * ((c * t) - (i * y)));
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    code = ((x * ((y * z) - (t * a))) - (b * ((c * z) - (i * a)))) + (j * ((c * t) - (i * y)))
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	return ((x * ((y * z) - (t * a))) - (b * ((c * z) - (i * a)))) + (j * ((c * t) - (i * y)));
}

Python

def code(x, y, z, t, a, b, c, i, j):
	return ((x * ((y * z) - (t * a))) - (b * ((c * z) - (i * a)))) + (j * ((c * t) - (i * y)))

Julia

function code(x, y, z, t, a, b, c, i, j)
	return Float64(Float64(Float64(x * Float64(Float64(y * z) - Float64(t * a))) - Float64(b * Float64(Float64(c * z) - Float64(i * a)))) + Float64(j * Float64(Float64(c * t) - Float64(i * y))))
end

MATLAB

function tmp = code(x, y, z, t, a, b, c, i, j)
	tmp = ((x * ((y * z) - (t * a))) - (b * ((c * z) - (i * a)))) + (j * ((c * t) - (i * y)));
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := N[(N[(N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(b * N[(N[(c * z), $MachinePrecision] - N[(i * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(j * N[(N[(c * t), $MachinePrecision] - N[(i * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Alternative 1: 82.8% accurate, 0.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \left(x \cdot \left(y \cdot z - t \cdot a\right) + b \cdot \left(a \cdot i - z \cdot c\right)\right) + j \cdot \left(t \cdot c - y \cdot i\right)\\ \mathbf{if}\;t_1 \leq \infty:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;y \cdot \left(x \cdot z - i \cdot j\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1
         (+
          (+ (* x (- (* y z) (* t a))) (* b (- (* a i) (* z c))))
          (* j (- (* t c) (* y i))))))
   (if (<= t_1 INFINITY) t_1 (* y (- (* x z) (* i j))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = ((x * ((y * z) - (t * a))) + (b * ((a * i) - (z * c)))) + (j * ((t * c) - (y * i)));
	double tmp;
	if (t_1 <= ((double) INFINITY)) {
		tmp = t_1;
	} else {
		tmp = y * ((x * z) - (i * j));
	}
	return tmp;
}

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = ((x * ((y * z) - (t * a))) + (b * ((a * i) - (z * c)))) + (j * ((t * c) - (y * i)));
	double tmp;
	if (t_1 <= Double.POSITIVE_INFINITY) {
		tmp = t_1;
	} else {
		tmp = y * ((x * z) - (i * j));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = ((x * ((y * z) - (t * a))) + (b * ((a * i) - (z * c)))) + (j * ((t * c) - (y * i)))
	tmp = 0
	if t_1 <= math.inf:
		tmp = t_1
	else:
		tmp = y * ((x * z) - (i * j))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(Float64(Float64(x * Float64(Float64(y * z) - Float64(t * a))) + Float64(b * Float64(Float64(a * i) - Float64(z * c)))) + Float64(j * Float64(Float64(t * c) - Float64(y * i))))
	tmp = 0.0
	if (t_1 <= Inf)
		tmp = t_1;
	else
		tmp = Float64(y * Float64(Float64(x * z) - Float64(i * j)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = ((x * ((y * z) - (t * a))) + (b * ((a * i) - (z * c)))) + (j * ((t * c) - (y * i)));
	tmp = 0.0;
	if (t_1 <= Inf)
		tmp = t_1;
	else
		tmp = y * ((x * z) - (i * j));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(N[(N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(b * N[(N[(a * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(j * N[(N[(t * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$1, Infinity], t$95$1, N[(y * N[(N[(x * z), $MachinePrecision] - N[(i * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]

Derivation

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

Alternative 2: 48.9% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y \cdot \left(x \cdot z - i \cdot j\right)\\ t_2 := j \cdot \left(t \cdot c - y \cdot i\right)\\ t_3 := z \cdot \left(x \cdot y - b \cdot c\right)\\ t_4 := t \cdot \left(c \cdot j - x \cdot a\right)\\ \mathbf{if}\;t \leq -6.4 \cdot 10^{+32}:\\ \;\;\;\;t_4\\ \mathbf{elif}\;t \leq -2.7 \cdot 10^{-24}:\\ \;\;\;\;b \cdot \left(a \cdot i - z \cdot c\right)\\ \mathbf{elif}\;t \leq -5.2 \cdot 10^{-60}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t \leq -3.4 \cdot 10^{-156}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;t \leq -7.5 \cdot 10^{-213}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq 4.5 \cdot 10^{-300}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;t \leq 1.3 \cdot 10^{-242}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq 1.05 \cdot 10^{-116}:\\ \;\;\;\;c \cdot \left(t \cdot j - z \cdot b\right)\\ \mathbf{elif}\;t \leq 0.048:\\ \;\;\;\;a \cdot \left(b \cdot i - x \cdot t\right)\\ \mathbf{elif}\;t \leq 1.8 \cdot 10^{+120}:\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;t_4\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* y (- (* x z) (* i j))))
        (t_2 (* j (- (* t c) (* y i))))
        (t_3 (* z (- (* x y) (* b c))))
        (t_4 (* t (- (* c j) (* x a)))))
   (if (<= t -6.4e+32)
     t_4
     (if (<= t -2.7e-24)
       (* b (- (* a i) (* z c)))
       (if (<= t -5.2e-60)
         t_2
         (if (<= t -3.4e-156)
           t_3
           (if (<= t -7.5e-213)
             t_1
             (if (<= t 4.5e-300)
               t_3
               (if (<= t 1.3e-242)
                 t_1
                 (if (<= t 1.05e-116)
                   (* c (- (* t j) (* z b)))
                   (if (<= t 0.048)
                     (* a (- (* b i) (* x t)))
                     (if (<= t 1.8e+120) t_2 t_4))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = y * ((x * z) - (i * j));
	double t_2 = j * ((t * c) - (y * i));
	double t_3 = z * ((x * y) - (b * c));
	double t_4 = t * ((c * j) - (x * a));
	double tmp;
	if (t <= -6.4e+32) {
		tmp = t_4;
	} else if (t <= -2.7e-24) {
		tmp = b * ((a * i) - (z * c));
	} else if (t <= -5.2e-60) {
		tmp = t_2;
	} else if (t <= -3.4e-156) {
		tmp = t_3;
	} else if (t <= -7.5e-213) {
		tmp = t_1;
	} else if (t <= 4.5e-300) {
		tmp = t_3;
	} else if (t <= 1.3e-242) {
		tmp = t_1;
	} else if (t <= 1.05e-116) {
		tmp = c * ((t * j) - (z * b));
	} else if (t <= 0.048) {
		tmp = a * ((b * i) - (x * t));
	} else if (t <= 1.8e+120) {
		tmp = t_2;
	} else {
		tmp = t_4;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: tmp
    t_1 = y * ((x * z) - (i * j))
    t_2 = j * ((t * c) - (y * i))
    t_3 = z * ((x * y) - (b * c))
    t_4 = t * ((c * j) - (x * a))
    if (t <= (-6.4d+32)) then
        tmp = t_4
    else if (t <= (-2.7d-24)) then
        tmp = b * ((a * i) - (z * c))
    else if (t <= (-5.2d-60)) then
        tmp = t_2
    else if (t <= (-3.4d-156)) then
        tmp = t_3
    else if (t <= (-7.5d-213)) then
        tmp = t_1
    else if (t <= 4.5d-300) then
        tmp = t_3
    else if (t <= 1.3d-242) then
        tmp = t_1
    else if (t <= 1.05d-116) then
        tmp = c * ((t * j) - (z * b))
    else if (t <= 0.048d0) then
        tmp = a * ((b * i) - (x * t))
    else if (t <= 1.8d+120) then
        tmp = t_2
    else
        tmp = t_4
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = y * ((x * z) - (i * j));
	double t_2 = j * ((t * c) - (y * i));
	double t_3 = z * ((x * y) - (b * c));
	double t_4 = t * ((c * j) - (x * a));
	double tmp;
	if (t <= -6.4e+32) {
		tmp = t_4;
	} else if (t <= -2.7e-24) {
		tmp = b * ((a * i) - (z * c));
	} else if (t <= -5.2e-60) {
		tmp = t_2;
	} else if (t <= -3.4e-156) {
		tmp = t_3;
	} else if (t <= -7.5e-213) {
		tmp = t_1;
	} else if (t <= 4.5e-300) {
		tmp = t_3;
	} else if (t <= 1.3e-242) {
		tmp = t_1;
	} else if (t <= 1.05e-116) {
		tmp = c * ((t * j) - (z * b));
	} else if (t <= 0.048) {
		tmp = a * ((b * i) - (x * t));
	} else if (t <= 1.8e+120) {
		tmp = t_2;
	} else {
		tmp = t_4;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = y * ((x * z) - (i * j))
	t_2 = j * ((t * c) - (y * i))
	t_3 = z * ((x * y) - (b * c))
	t_4 = t * ((c * j) - (x * a))
	tmp = 0
	if t <= -6.4e+32:
		tmp = t_4
	elif t <= -2.7e-24:
		tmp = b * ((a * i) - (z * c))
	elif t <= -5.2e-60:
		tmp = t_2
	elif t <= -3.4e-156:
		tmp = t_3
	elif t <= -7.5e-213:
		tmp = t_1
	elif t <= 4.5e-300:
		tmp = t_3
	elif t <= 1.3e-242:
		tmp = t_1
	elif t <= 1.05e-116:
		tmp = c * ((t * j) - (z * b))
	elif t <= 0.048:
		tmp = a * ((b * i) - (x * t))
	elif t <= 1.8e+120:
		tmp = t_2
	else:
		tmp = t_4
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(y * Float64(Float64(x * z) - Float64(i * j)))
	t_2 = Float64(j * Float64(Float64(t * c) - Float64(y * i)))
	t_3 = Float64(z * Float64(Float64(x * y) - Float64(b * c)))
	t_4 = Float64(t * Float64(Float64(c * j) - Float64(x * a)))
	tmp = 0.0
	if (t <= -6.4e+32)
		tmp = t_4;
	elseif (t <= -2.7e-24)
		tmp = Float64(b * Float64(Float64(a * i) - Float64(z * c)));
	elseif (t <= -5.2e-60)
		tmp = t_2;
	elseif (t <= -3.4e-156)
		tmp = t_3;
	elseif (t <= -7.5e-213)
		tmp = t_1;
	elseif (t <= 4.5e-300)
		tmp = t_3;
	elseif (t <= 1.3e-242)
		tmp = t_1;
	elseif (t <= 1.05e-116)
		tmp = Float64(c * Float64(Float64(t * j) - Float64(z * b)));
	elseif (t <= 0.048)
		tmp = Float64(a * Float64(Float64(b * i) - Float64(x * t)));
	elseif (t <= 1.8e+120)
		tmp = t_2;
	else
		tmp = t_4;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = y * ((x * z) - (i * j));
	t_2 = j * ((t * c) - (y * i));
	t_3 = z * ((x * y) - (b * c));
	t_4 = t * ((c * j) - (x * a));
	tmp = 0.0;
	if (t <= -6.4e+32)
		tmp = t_4;
	elseif (t <= -2.7e-24)
		tmp = b * ((a * i) - (z * c));
	elseif (t <= -5.2e-60)
		tmp = t_2;
	elseif (t <= -3.4e-156)
		tmp = t_3;
	elseif (t <= -7.5e-213)
		tmp = t_1;
	elseif (t <= 4.5e-300)
		tmp = t_3;
	elseif (t <= 1.3e-242)
		tmp = t_1;
	elseif (t <= 1.05e-116)
		tmp = c * ((t * j) - (z * b));
	elseif (t <= 0.048)
		tmp = a * ((b * i) - (x * t));
	elseif (t <= 1.8e+120)
		tmp = t_2;
	else
		tmp = t_4;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(y * N[(N[(x * z), $MachinePrecision] - N[(i * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(j * N[(N[(t * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(z * N[(N[(x * y), $MachinePrecision] - N[(b * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(t * N[(N[(c * j), $MachinePrecision] - N[(x * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -6.4e+32], t$95$4, If[LessEqual[t, -2.7e-24], N[(b * N[(N[(a * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -5.2e-60], t$95$2, If[LessEqual[t, -3.4e-156], t$95$3, If[LessEqual[t, -7.5e-213], t$95$1, If[LessEqual[t, 4.5e-300], t$95$3, If[LessEqual[t, 1.3e-242], t$95$1, If[LessEqual[t, 1.05e-116], N[(c * N[(N[(t * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 0.048], N[(a * N[(N[(b * i), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.8e+120], t$95$2, t$95$4]]]]]]]]]]]]]]

Derivation

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

Alternative 3: 29.1% accurate, 1.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := i \cdot \left(a \cdot b\right)\\ t_2 := a \cdot \left(t \cdot \left(-x\right)\right)\\ t_3 := x \cdot \left(y \cdot z\right)\\ t_4 := z \cdot \left(c \cdot \left(-b\right)\right)\\ \mathbf{if}\;t \leq -3.6 \cdot 10^{+90}:\\ \;\;\;\;t \cdot \left(c \cdot j\right)\\ \mathbf{elif}\;t \leq -2 \cdot 10^{-39}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t \leq -9.2 \cdot 10^{-83}:\\ \;\;\;\;c \cdot \left(t \cdot j\right)\\ \mathbf{elif}\;t \leq -1.1 \cdot 10^{-209}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq -5.5 \cdot 10^{-249}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;t \leq -2.5 \cdot 10^{-291}:\\ \;\;\;\;t_4\\ \mathbf{elif}\;t \leq 1.15 \cdot 10^{-259}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;t \leq 1.4 \cdot 10^{-127}:\\ \;\;\;\;t_4\\ \mathbf{elif}\;t \leq 1.4 \cdot 10^{+15}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq 2.1 \cdot 10^{+203}:\\ \;\;\;\;j \cdot \left(t \cdot c\right)\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* i (* a b)))
        (t_2 (* a (* t (- x))))
        (t_3 (* x (* y z)))
        (t_4 (* z (* c (- b)))))
   (if (<= t -3.6e+90)
     (* t (* c j))
     (if (<= t -2e-39)
       t_2
       (if (<= t -9.2e-83)
         (* c (* t j))
         (if (<= t -1.1e-209)
           t_1
           (if (<= t -5.5e-249)
             t_3
             (if (<= t -2.5e-291)
               t_4
               (if (<= t 1.15e-259)
                 t_3
                 (if (<= t 1.4e-127)
                   t_4
                   (if (<= t 1.4e+15)
                     t_1
                     (if (<= t 2.1e+203) (* j (* t c)) t_2))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = i * (a * b);
	double t_2 = a * (t * -x);
	double t_3 = x * (y * z);
	double t_4 = z * (c * -b);
	double tmp;
	if (t <= -3.6e+90) {
		tmp = t * (c * j);
	} else if (t <= -2e-39) {
		tmp = t_2;
	} else if (t <= -9.2e-83) {
		tmp = c * (t * j);
	} else if (t <= -1.1e-209) {
		tmp = t_1;
	} else if (t <= -5.5e-249) {
		tmp = t_3;
	} else if (t <= -2.5e-291) {
		tmp = t_4;
	} else if (t <= 1.15e-259) {
		tmp = t_3;
	} else if (t <= 1.4e-127) {
		tmp = t_4;
	} else if (t <= 1.4e+15) {
		tmp = t_1;
	} else if (t <= 2.1e+203) {
		tmp = j * (t * c);
	} else {
		tmp = t_2;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: tmp
    t_1 = i * (a * b)
    t_2 = a * (t * -x)
    t_3 = x * (y * z)
    t_4 = z * (c * -b)
    if (t <= (-3.6d+90)) then
        tmp = t * (c * j)
    else if (t <= (-2d-39)) then
        tmp = t_2
    else if (t <= (-9.2d-83)) then
        tmp = c * (t * j)
    else if (t <= (-1.1d-209)) then
        tmp = t_1
    else if (t <= (-5.5d-249)) then
        tmp = t_3
    else if (t <= (-2.5d-291)) then
        tmp = t_4
    else if (t <= 1.15d-259) then
        tmp = t_3
    else if (t <= 1.4d-127) then
        tmp = t_4
    else if (t <= 1.4d+15) then
        tmp = t_1
    else if (t <= 2.1d+203) then
        tmp = j * (t * c)
    else
        tmp = t_2
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = i * (a * b);
	double t_2 = a * (t * -x);
	double t_3 = x * (y * z);
	double t_4 = z * (c * -b);
	double tmp;
	if (t <= -3.6e+90) {
		tmp = t * (c * j);
	} else if (t <= -2e-39) {
		tmp = t_2;
	} else if (t <= -9.2e-83) {
		tmp = c * (t * j);
	} else if (t <= -1.1e-209) {
		tmp = t_1;
	} else if (t <= -5.5e-249) {
		tmp = t_3;
	} else if (t <= -2.5e-291) {
		tmp = t_4;
	} else if (t <= 1.15e-259) {
		tmp = t_3;
	} else if (t <= 1.4e-127) {
		tmp = t_4;
	} else if (t <= 1.4e+15) {
		tmp = t_1;
	} else if (t <= 2.1e+203) {
		tmp = j * (t * c);
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = i * (a * b)
	t_2 = a * (t * -x)
	t_3 = x * (y * z)
	t_4 = z * (c * -b)
	tmp = 0
	if t <= -3.6e+90:
		tmp = t * (c * j)
	elif t <= -2e-39:
		tmp = t_2
	elif t <= -9.2e-83:
		tmp = c * (t * j)
	elif t <= -1.1e-209:
		tmp = t_1
	elif t <= -5.5e-249:
		tmp = t_3
	elif t <= -2.5e-291:
		tmp = t_4
	elif t <= 1.15e-259:
		tmp = t_3
	elif t <= 1.4e-127:
		tmp = t_4
	elif t <= 1.4e+15:
		tmp = t_1
	elif t <= 2.1e+203:
		tmp = j * (t * c)
	else:
		tmp = t_2
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(i * Float64(a * b))
	t_2 = Float64(a * Float64(t * Float64(-x)))
	t_3 = Float64(x * Float64(y * z))
	t_4 = Float64(z * Float64(c * Float64(-b)))
	tmp = 0.0
	if (t <= -3.6e+90)
		tmp = Float64(t * Float64(c * j));
	elseif (t <= -2e-39)
		tmp = t_2;
	elseif (t <= -9.2e-83)
		tmp = Float64(c * Float64(t * j));
	elseif (t <= -1.1e-209)
		tmp = t_1;
	elseif (t <= -5.5e-249)
		tmp = t_3;
	elseif (t <= -2.5e-291)
		tmp = t_4;
	elseif (t <= 1.15e-259)
		tmp = t_3;
	elseif (t <= 1.4e-127)
		tmp = t_4;
	elseif (t <= 1.4e+15)
		tmp = t_1;
	elseif (t <= 2.1e+203)
		tmp = Float64(j * Float64(t * c));
	else
		tmp = t_2;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = i * (a * b);
	t_2 = a * (t * -x);
	t_3 = x * (y * z);
	t_4 = z * (c * -b);
	tmp = 0.0;
	if (t <= -3.6e+90)
		tmp = t * (c * j);
	elseif (t <= -2e-39)
		tmp = t_2;
	elseif (t <= -9.2e-83)
		tmp = c * (t * j);
	elseif (t <= -1.1e-209)
		tmp = t_1;
	elseif (t <= -5.5e-249)
		tmp = t_3;
	elseif (t <= -2.5e-291)
		tmp = t_4;
	elseif (t <= 1.15e-259)
		tmp = t_3;
	elseif (t <= 1.4e-127)
		tmp = t_4;
	elseif (t <= 1.4e+15)
		tmp = t_1;
	elseif (t <= 2.1e+203)
		tmp = j * (t * c);
	else
		tmp = t_2;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(i * N[(a * b), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(a * N[(t * (-x)), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(z * N[(c * (-b)), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -3.6e+90], N[(t * N[(c * j), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -2e-39], t$95$2, If[LessEqual[t, -9.2e-83], N[(c * N[(t * j), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -1.1e-209], t$95$1, If[LessEqual[t, -5.5e-249], t$95$3, If[LessEqual[t, -2.5e-291], t$95$4, If[LessEqual[t, 1.15e-259], t$95$3, If[LessEqual[t, 1.4e-127], t$95$4, If[LessEqual[t, 1.4e+15], t$95$1, If[LessEqual[t, 2.1e+203], N[(j * N[(t * c), $MachinePrecision]), $MachinePrecision], t$95$2]]]]]]]]]]]]]]

Derivation

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

Alternative 4: 50.0% accurate, 1.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(t \cdot c - y \cdot i\right)\\ t_2 := c \cdot \left(t \cdot j - z \cdot b\right)\\ t_3 := a \cdot \left(b \cdot i - x \cdot t\right)\\ \mathbf{if}\;a \leq -6.8 \cdot 10^{+132}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;a \leq -1.1 \cdot 10^{+93}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq -2.3 \cdot 10^{-125}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -1.65 \cdot 10^{-212}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq -8.5 \cdot 10^{-242}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -1.7 \cdot 10^{-271}:\\ \;\;\;\;x \cdot \left(y \cdot z\right)\\ \mathbf{elif}\;a \leq 10^{-180}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 3.4 \cdot 10^{-8}:\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;t_3\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* j (- (* t c) (* y i))))
        (t_2 (* c (- (* t j) (* z b))))
        (t_3 (* a (- (* b i) (* x t)))))
   (if (<= a -6.8e+132)
     t_3
     (if (<= a -1.1e+93)
       t_2
       (if (<= a -2.3e-125)
         t_1
         (if (<= a -1.65e-212)
           t_2
           (if (<= a -8.5e-242)
             t_1
             (if (<= a -1.7e-271)
               (* x (* y z))
               (if (<= a 1e-180) t_1 (if (<= a 3.4e-8) t_2 t_3))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = j * ((t * c) - (y * i));
	double t_2 = c * ((t * j) - (z * b));
	double t_3 = a * ((b * i) - (x * t));
	double tmp;
	if (a <= -6.8e+132) {
		tmp = t_3;
	} else if (a <= -1.1e+93) {
		tmp = t_2;
	} else if (a <= -2.3e-125) {
		tmp = t_1;
	} else if (a <= -1.65e-212) {
		tmp = t_2;
	} else if (a <= -8.5e-242) {
		tmp = t_1;
	} else if (a <= -1.7e-271) {
		tmp = x * (y * z);
	} else if (a <= 1e-180) {
		tmp = t_1;
	} else if (a <= 3.4e-8) {
		tmp = t_2;
	} else {
		tmp = t_3;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: tmp
    t_1 = j * ((t * c) - (y * i))
    t_2 = c * ((t * j) - (z * b))
    t_3 = a * ((b * i) - (x * t))
    if (a <= (-6.8d+132)) then
        tmp = t_3
    else if (a <= (-1.1d+93)) then
        tmp = t_2
    else if (a <= (-2.3d-125)) then
        tmp = t_1
    else if (a <= (-1.65d-212)) then
        tmp = t_2
    else if (a <= (-8.5d-242)) then
        tmp = t_1
    else if (a <= (-1.7d-271)) then
        tmp = x * (y * z)
    else if (a <= 1d-180) then
        tmp = t_1
    else if (a <= 3.4d-8) then
        tmp = t_2
    else
        tmp = t_3
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = j * ((t * c) - (y * i));
	double t_2 = c * ((t * j) - (z * b));
	double t_3 = a * ((b * i) - (x * t));
	double tmp;
	if (a <= -6.8e+132) {
		tmp = t_3;
	} else if (a <= -1.1e+93) {
		tmp = t_2;
	} else if (a <= -2.3e-125) {
		tmp = t_1;
	} else if (a <= -1.65e-212) {
		tmp = t_2;
	} else if (a <= -8.5e-242) {
		tmp = t_1;
	} else if (a <= -1.7e-271) {
		tmp = x * (y * z);
	} else if (a <= 1e-180) {
		tmp = t_1;
	} else if (a <= 3.4e-8) {
		tmp = t_2;
	} else {
		tmp = t_3;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = j * ((t * c) - (y * i))
	t_2 = c * ((t * j) - (z * b))
	t_3 = a * ((b * i) - (x * t))
	tmp = 0
	if a <= -6.8e+132:
		tmp = t_3
	elif a <= -1.1e+93:
		tmp = t_2
	elif a <= -2.3e-125:
		tmp = t_1
	elif a <= -1.65e-212:
		tmp = t_2
	elif a <= -8.5e-242:
		tmp = t_1
	elif a <= -1.7e-271:
		tmp = x * (y * z)
	elif a <= 1e-180:
		tmp = t_1
	elif a <= 3.4e-8:
		tmp = t_2
	else:
		tmp = t_3
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(j * Float64(Float64(t * c) - Float64(y * i)))
	t_2 = Float64(c * Float64(Float64(t * j) - Float64(z * b)))
	t_3 = Float64(a * Float64(Float64(b * i) - Float64(x * t)))
	tmp = 0.0
	if (a <= -6.8e+132)
		tmp = t_3;
	elseif (a <= -1.1e+93)
		tmp = t_2;
	elseif (a <= -2.3e-125)
		tmp = t_1;
	elseif (a <= -1.65e-212)
		tmp = t_2;
	elseif (a <= -8.5e-242)
		tmp = t_1;
	elseif (a <= -1.7e-271)
		tmp = Float64(x * Float64(y * z));
	elseif (a <= 1e-180)
		tmp = t_1;
	elseif (a <= 3.4e-8)
		tmp = t_2;
	else
		tmp = t_3;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = j * ((t * c) - (y * i));
	t_2 = c * ((t * j) - (z * b));
	t_3 = a * ((b * i) - (x * t));
	tmp = 0.0;
	if (a <= -6.8e+132)
		tmp = t_3;
	elseif (a <= -1.1e+93)
		tmp = t_2;
	elseif (a <= -2.3e-125)
		tmp = t_1;
	elseif (a <= -1.65e-212)
		tmp = t_2;
	elseif (a <= -8.5e-242)
		tmp = t_1;
	elseif (a <= -1.7e-271)
		tmp = x * (y * z);
	elseif (a <= 1e-180)
		tmp = t_1;
	elseif (a <= 3.4e-8)
		tmp = t_2;
	else
		tmp = t_3;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(j * N[(N[(t * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(c * N[(N[(t * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(a * N[(N[(b * i), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -6.8e+132], t$95$3, If[LessEqual[a, -1.1e+93], t$95$2, If[LessEqual[a, -2.3e-125], t$95$1, If[LessEqual[a, -1.65e-212], t$95$2, If[LessEqual[a, -8.5e-242], t$95$1, If[LessEqual[a, -1.7e-271], N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 1e-180], t$95$1, If[LessEqual[a, 3.4e-8], t$95$2, t$95$3]]]]]]]]]]]

Derivation

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

Alternative 5: 50.2% accurate, 1.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(a \cdot i - z \cdot c\right)\\ t_2 := a \cdot \left(b \cdot i - x \cdot t\right)\\ t_3 := x \cdot \left(y \cdot z - t \cdot a\right)\\ t_4 := j \cdot \left(t \cdot c - y \cdot i\right)\\ \mathbf{if}\;j \leq -1.22 \cdot 10^{+69}:\\ \;\;\;\;t_4\\ \mathbf{elif}\;j \leq -9.1 \cdot 10^{-125}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;j \leq -1.4 \cdot 10^{-199}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;j \leq 2.45 \cdot 10^{-185}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;j \leq 2.55 \cdot 10^{-107}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;j \leq 1.9 \cdot 10^{-6}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;j \leq 2.4 \cdot 10^{+137}:\\ \;\;\;\;c \cdot \left(t \cdot j - z \cdot b\right)\\ \mathbf{elif}\;j \leq 2.9 \cdot 10^{+184}:\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;t_4\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* b (- (* a i) (* z c))))
        (t_2 (* a (- (* b i) (* x t))))
        (t_3 (* x (- (* y z) (* t a))))
        (t_4 (* j (- (* t c) (* y i)))))
   (if (<= j -1.22e+69)
     t_4
     (if (<= j -9.1e-125)
       t_2
       (if (<= j -1.4e-199)
         t_1
         (if (<= j 2.45e-185)
           t_3
           (if (<= j 2.55e-107)
             t_1
             (if (<= j 1.9e-6)
               t_3
               (if (<= j 2.4e+137)
                 (* c (- (* t j) (* z b)))
                 (if (<= j 2.9e+184) t_2 t_4))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = b * ((a * i) - (z * c));
	double t_2 = a * ((b * i) - (x * t));
	double t_3 = x * ((y * z) - (t * a));
	double t_4 = j * ((t * c) - (y * i));
	double tmp;
	if (j <= -1.22e+69) {
		tmp = t_4;
	} else if (j <= -9.1e-125) {
		tmp = t_2;
	} else if (j <= -1.4e-199) {
		tmp = t_1;
	} else if (j <= 2.45e-185) {
		tmp = t_3;
	} else if (j <= 2.55e-107) {
		tmp = t_1;
	} else if (j <= 1.9e-6) {
		tmp = t_3;
	} else if (j <= 2.4e+137) {
		tmp = c * ((t * j) - (z * b));
	} else if (j <= 2.9e+184) {
		tmp = t_2;
	} else {
		tmp = t_4;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: tmp
    t_1 = b * ((a * i) - (z * c))
    t_2 = a * ((b * i) - (x * t))
    t_3 = x * ((y * z) - (t * a))
    t_4 = j * ((t * c) - (y * i))
    if (j <= (-1.22d+69)) then
        tmp = t_4
    else if (j <= (-9.1d-125)) then
        tmp = t_2
    else if (j <= (-1.4d-199)) then
        tmp = t_1
    else if (j <= 2.45d-185) then
        tmp = t_3
    else if (j <= 2.55d-107) then
        tmp = t_1
    else if (j <= 1.9d-6) then
        tmp = t_3
    else if (j <= 2.4d+137) then
        tmp = c * ((t * j) - (z * b))
    else if (j <= 2.9d+184) then
        tmp = t_2
    else
        tmp = t_4
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = b * ((a * i) - (z * c));
	double t_2 = a * ((b * i) - (x * t));
	double t_3 = x * ((y * z) - (t * a));
	double t_4 = j * ((t * c) - (y * i));
	double tmp;
	if (j <= -1.22e+69) {
		tmp = t_4;
	} else if (j <= -9.1e-125) {
		tmp = t_2;
	} else if (j <= -1.4e-199) {
		tmp = t_1;
	} else if (j <= 2.45e-185) {
		tmp = t_3;
	} else if (j <= 2.55e-107) {
		tmp = t_1;
	} else if (j <= 1.9e-6) {
		tmp = t_3;
	} else if (j <= 2.4e+137) {
		tmp = c * ((t * j) - (z * b));
	} else if (j <= 2.9e+184) {
		tmp = t_2;
	} else {
		tmp = t_4;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = b * ((a * i) - (z * c))
	t_2 = a * ((b * i) - (x * t))
	t_3 = x * ((y * z) - (t * a))
	t_4 = j * ((t * c) - (y * i))
	tmp = 0
	if j <= -1.22e+69:
		tmp = t_4
	elif j <= -9.1e-125:
		tmp = t_2
	elif j <= -1.4e-199:
		tmp = t_1
	elif j <= 2.45e-185:
		tmp = t_3
	elif j <= 2.55e-107:
		tmp = t_1
	elif j <= 1.9e-6:
		tmp = t_3
	elif j <= 2.4e+137:
		tmp = c * ((t * j) - (z * b))
	elif j <= 2.9e+184:
		tmp = t_2
	else:
		tmp = t_4
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(b * Float64(Float64(a * i) - Float64(z * c)))
	t_2 = Float64(a * Float64(Float64(b * i) - Float64(x * t)))
	t_3 = Float64(x * Float64(Float64(y * z) - Float64(t * a)))
	t_4 = Float64(j * Float64(Float64(t * c) - Float64(y * i)))
	tmp = 0.0
	if (j <= -1.22e+69)
		tmp = t_4;
	elseif (j <= -9.1e-125)
		tmp = t_2;
	elseif (j <= -1.4e-199)
		tmp = t_1;
	elseif (j <= 2.45e-185)
		tmp = t_3;
	elseif (j <= 2.55e-107)
		tmp = t_1;
	elseif (j <= 1.9e-6)
		tmp = t_3;
	elseif (j <= 2.4e+137)
		tmp = Float64(c * Float64(Float64(t * j) - Float64(z * b)));
	elseif (j <= 2.9e+184)
		tmp = t_2;
	else
		tmp = t_4;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = b * ((a * i) - (z * c));
	t_2 = a * ((b * i) - (x * t));
	t_3 = x * ((y * z) - (t * a));
	t_4 = j * ((t * c) - (y * i));
	tmp = 0.0;
	if (j <= -1.22e+69)
		tmp = t_4;
	elseif (j <= -9.1e-125)
		tmp = t_2;
	elseif (j <= -1.4e-199)
		tmp = t_1;
	elseif (j <= 2.45e-185)
		tmp = t_3;
	elseif (j <= 2.55e-107)
		tmp = t_1;
	elseif (j <= 1.9e-6)
		tmp = t_3;
	elseif (j <= 2.4e+137)
		tmp = c * ((t * j) - (z * b));
	elseif (j <= 2.9e+184)
		tmp = t_2;
	else
		tmp = t_4;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(b * N[(N[(a * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(a * N[(N[(b * i), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(j * N[(N[(t * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -1.22e+69], t$95$4, If[LessEqual[j, -9.1e-125], t$95$2, If[LessEqual[j, -1.4e-199], t$95$1, If[LessEqual[j, 2.45e-185], t$95$3, If[LessEqual[j, 2.55e-107], t$95$1, If[LessEqual[j, 1.9e-6], t$95$3, If[LessEqual[j, 2.4e+137], N[(c * N[(N[(t * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 2.9e+184], t$95$2, t$95$4]]]]]]]]]]]]

Derivation

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

Alternative 6: 64.4% accurate, 1.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;j \leq -1.9 \cdot 10^{-115} \lor \neg \left(j \leq 2.25 \cdot 10^{-120}\right):\\ \;\;\;\;x \cdot \left(y \cdot z - t \cdot a\right) + j \cdot \left(t \cdot c - y \cdot i\right)\\ \mathbf{else}:\\ \;\;\;\;z \cdot \left(x \cdot y - b \cdot c\right) - x \cdot \left(t \cdot a\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (or (<= j -1.9e-115) (not (<= j 2.25e-120)))
   (+ (* x (- (* y z) (* t a))) (* j (- (* t c) (* y i))))
   (- (* z (- (* x y) (* b c))) (* x (* t a)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if ((j <= -1.9e-115) || !(j <= 2.25e-120)) {
		tmp = (x * ((y * z) - (t * a))) + (j * ((t * c) - (y * i)));
	} else {
		tmp = (z * ((x * y) - (b * c))) - (x * (t * a));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: tmp
    if ((j <= (-1.9d-115)) .or. (.not. (j <= 2.25d-120))) then
        tmp = (x * ((y * z) - (t * a))) + (j * ((t * c) - (y * i)))
    else
        tmp = (z * ((x * y) - (b * c))) - (x * (t * a))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if ((j <= -1.9e-115) || !(j <= 2.25e-120)) {
		tmp = (x * ((y * z) - (t * a))) + (j * ((t * c) - (y * i)));
	} else {
		tmp = (z * ((x * y) - (b * c))) - (x * (t * a));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if (j <= -1.9e-115) or not (j <= 2.25e-120):
		tmp = (x * ((y * z) - (t * a))) + (j * ((t * c) - (y * i)))
	else:
		tmp = (z * ((x * y) - (b * c))) - (x * (t * a))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if ((j <= -1.9e-115) || !(j <= 2.25e-120))
		tmp = Float64(Float64(x * Float64(Float64(y * z) - Float64(t * a))) + Float64(j * Float64(Float64(t * c) - Float64(y * i))));
	else
		tmp = Float64(Float64(z * Float64(Float64(x * y) - Float64(b * c))) - Float64(x * Float64(t * a)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0;
	if ((j <= -1.9e-115) || ~((j <= 2.25e-120)))
		tmp = (x * ((y * z) - (t * a))) + (j * ((t * c) - (y * i)));
	else
		tmp = (z * ((x * y) - (b * c))) - (x * (t * a));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[Or[LessEqual[j, -1.9e-115], N[Not[LessEqual[j, 2.25e-120]], $MachinePrecision]], N[(N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(j * N[(N[(t * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(z * N[(N[(x * y), $MachinePrecision] - N[(b * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(x * N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

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

Alternative 7: 68.1% accurate, 1.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(y \cdot z - t \cdot a\right)\\ \mathbf{if}\;j \leq -3.1 \cdot 10^{-70} \lor \neg \left(j \leq 6.8 \cdot 10^{-134}\right):\\ \;\;\;\;t_1 + j \cdot \left(t \cdot c - y \cdot i\right)\\ \mathbf{else}:\\ \;\;\;\;t_1 + b \cdot \left(a \cdot i - z \cdot c\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* x (- (* y z) (* t a)))))
   (if (or (<= j -3.1e-70) (not (<= j 6.8e-134)))
     (+ t_1 (* j (- (* t c) (* y i))))
     (+ t_1 (* b (- (* a i) (* z c)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = x * ((y * z) - (t * a));
	double tmp;
	if ((j <= -3.1e-70) || !(j <= 6.8e-134)) {
		tmp = t_1 + (j * ((t * c) - (y * i)));
	} else {
		tmp = t_1 + (b * ((a * i) - (z * c)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: tmp
    t_1 = x * ((y * z) - (t * a))
    if ((j <= (-3.1d-70)) .or. (.not. (j <= 6.8d-134))) then
        tmp = t_1 + (j * ((t * c) - (y * i)))
    else
        tmp = t_1 + (b * ((a * i) - (z * c)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = x * ((y * z) - (t * a));
	double tmp;
	if ((j <= -3.1e-70) || !(j <= 6.8e-134)) {
		tmp = t_1 + (j * ((t * c) - (y * i)));
	} else {
		tmp = t_1 + (b * ((a * i) - (z * c)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = x * ((y * z) - (t * a))
	tmp = 0
	if (j <= -3.1e-70) or not (j <= 6.8e-134):
		tmp = t_1 + (j * ((t * c) - (y * i)))
	else:
		tmp = t_1 + (b * ((a * i) - (z * c)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(x * Float64(Float64(y * z) - Float64(t * a)))
	tmp = 0.0
	if ((j <= -3.1e-70) || !(j <= 6.8e-134))
		tmp = Float64(t_1 + Float64(j * Float64(Float64(t * c) - Float64(y * i))));
	else
		tmp = Float64(t_1 + Float64(b * Float64(Float64(a * i) - Float64(z * c))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = x * ((y * z) - (t * a));
	tmp = 0.0;
	if ((j <= -3.1e-70) || ~((j <= 6.8e-134)))
		tmp = t_1 + (j * ((t * c) - (y * i)));
	else
		tmp = t_1 + (b * ((a * i) - (z * c)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[j, -3.1e-70], N[Not[LessEqual[j, 6.8e-134]], $MachinePrecision]], N[(t$95$1 + N[(j * N[(N[(t * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(t$95$1 + N[(b * N[(N[(a * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]

Derivation

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

Alternative 8: 29.2% accurate, 1.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := z \cdot \left(c \cdot \left(-b\right)\right)\\ t_2 := x \cdot \left(y \cdot z\right)\\ \mathbf{if}\;t \leq -2.2 \cdot 10^{+73}:\\ \;\;\;\;t \cdot \left(c \cdot j\right)\\ \mathbf{elif}\;t \leq -1.7 \cdot 10^{-115}:\\ \;\;\;\;\left(z \cdot c\right) \cdot \left(-b\right)\\ \mathbf{elif}\;t \leq -1.1 \cdot 10^{-250}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t \leq -2.5 \cdot 10^{-291}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq 7.2 \cdot 10^{-262}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t \leq 2.9 \cdot 10^{-126}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq 1.75 \cdot 10^{+15}:\\ \;\;\;\;i \cdot \left(a \cdot b\right)\\ \mathbf{elif}\;t \leq 1.65 \cdot 10^{+204}:\\ \;\;\;\;j \cdot \left(t \cdot c\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(t \cdot \left(-x\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* z (* c (- b)))) (t_2 (* x (* y z))))
   (if (<= t -2.2e+73)
     (* t (* c j))
     (if (<= t -1.7e-115)
       (* (* z c) (- b))
       (if (<= t -1.1e-250)
         t_2
         (if (<= t -2.5e-291)
           t_1
           (if (<= t 7.2e-262)
             t_2
             (if (<= t 2.9e-126)
               t_1
               (if (<= t 1.75e+15)
                 (* i (* a b))
                 (if (<= t 1.65e+204) (* j (* t c)) (* a (* t (- x)))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = z * (c * -b);
	double t_2 = x * (y * z);
	double tmp;
	if (t <= -2.2e+73) {
		tmp = t * (c * j);
	} else if (t <= -1.7e-115) {
		tmp = (z * c) * -b;
	} else if (t <= -1.1e-250) {
		tmp = t_2;
	} else if (t <= -2.5e-291) {
		tmp = t_1;
	} else if (t <= 7.2e-262) {
		tmp = t_2;
	} else if (t <= 2.9e-126) {
		tmp = t_1;
	} else if (t <= 1.75e+15) {
		tmp = i * (a * b);
	} else if (t <= 1.65e+204) {
		tmp = j * (t * c);
	} else {
		tmp = a * (t * -x);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = z * (c * -b)
    t_2 = x * (y * z)
    if (t <= (-2.2d+73)) then
        tmp = t * (c * j)
    else if (t <= (-1.7d-115)) then
        tmp = (z * c) * -b
    else if (t <= (-1.1d-250)) then
        tmp = t_2
    else if (t <= (-2.5d-291)) then
        tmp = t_1
    else if (t <= 7.2d-262) then
        tmp = t_2
    else if (t <= 2.9d-126) then
        tmp = t_1
    else if (t <= 1.75d+15) then
        tmp = i * (a * b)
    else if (t <= 1.65d+204) then
        tmp = j * (t * c)
    else
        tmp = a * (t * -x)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = z * (c * -b);
	double t_2 = x * (y * z);
	double tmp;
	if (t <= -2.2e+73) {
		tmp = t * (c * j);
	} else if (t <= -1.7e-115) {
		tmp = (z * c) * -b;
	} else if (t <= -1.1e-250) {
		tmp = t_2;
	} else if (t <= -2.5e-291) {
		tmp = t_1;
	} else if (t <= 7.2e-262) {
		tmp = t_2;
	} else if (t <= 2.9e-126) {
		tmp = t_1;
	} else if (t <= 1.75e+15) {
		tmp = i * (a * b);
	} else if (t <= 1.65e+204) {
		tmp = j * (t * c);
	} else {
		tmp = a * (t * -x);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = z * (c * -b)
	t_2 = x * (y * z)
	tmp = 0
	if t <= -2.2e+73:
		tmp = t * (c * j)
	elif t <= -1.7e-115:
		tmp = (z * c) * -b
	elif t <= -1.1e-250:
		tmp = t_2
	elif t <= -2.5e-291:
		tmp = t_1
	elif t <= 7.2e-262:
		tmp = t_2
	elif t <= 2.9e-126:
		tmp = t_1
	elif t <= 1.75e+15:
		tmp = i * (a * b)
	elif t <= 1.65e+204:
		tmp = j * (t * c)
	else:
		tmp = a * (t * -x)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(z * Float64(c * Float64(-b)))
	t_2 = Float64(x * Float64(y * z))
	tmp = 0.0
	if (t <= -2.2e+73)
		tmp = Float64(t * Float64(c * j));
	elseif (t <= -1.7e-115)
		tmp = Float64(Float64(z * c) * Float64(-b));
	elseif (t <= -1.1e-250)
		tmp = t_2;
	elseif (t <= -2.5e-291)
		tmp = t_1;
	elseif (t <= 7.2e-262)
		tmp = t_2;
	elseif (t <= 2.9e-126)
		tmp = t_1;
	elseif (t <= 1.75e+15)
		tmp = Float64(i * Float64(a * b));
	elseif (t <= 1.65e+204)
		tmp = Float64(j * Float64(t * c));
	else
		tmp = Float64(a * Float64(t * Float64(-x)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = z * (c * -b);
	t_2 = x * (y * z);
	tmp = 0.0;
	if (t <= -2.2e+73)
		tmp = t * (c * j);
	elseif (t <= -1.7e-115)
		tmp = (z * c) * -b;
	elseif (t <= -1.1e-250)
		tmp = t_2;
	elseif (t <= -2.5e-291)
		tmp = t_1;
	elseif (t <= 7.2e-262)
		tmp = t_2;
	elseif (t <= 2.9e-126)
		tmp = t_1;
	elseif (t <= 1.75e+15)
		tmp = i * (a * b);
	elseif (t <= 1.65e+204)
		tmp = j * (t * c);
	else
		tmp = a * (t * -x);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(z * N[(c * (-b)), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -2.2e+73], N[(t * N[(c * j), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -1.7e-115], N[(N[(z * c), $MachinePrecision] * (-b)), $MachinePrecision], If[LessEqual[t, -1.1e-250], t$95$2, If[LessEqual[t, -2.5e-291], t$95$1, If[LessEqual[t, 7.2e-262], t$95$2, If[LessEqual[t, 2.9e-126], t$95$1, If[LessEqual[t, 1.75e+15], N[(i * N[(a * b), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.65e+204], N[(j * N[(t * c), $MachinePrecision]), $MachinePrecision], N[(a * N[(t * (-x)), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]

Derivation

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

Alternative 9: 29.4% accurate, 1.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := z \cdot \left(c \cdot \left(-b\right)\right)\\ t_2 := x \cdot \left(y \cdot z\right)\\ \mathbf{if}\;t \leq -3.7 \cdot 10^{+93}:\\ \;\;\;\;t \cdot \left(c \cdot j\right)\\ \mathbf{elif}\;t \leq -2.8 \cdot 10^{-217}:\\ \;\;\;\;i \cdot \left(y \cdot \left(-j\right)\right)\\ \mathbf{elif}\;t \leq -5 \cdot 10^{-249}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t \leq -2.6 \cdot 10^{-291}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq 5.8 \cdot 10^{-258}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t \leq 8.2 \cdot 10^{-126}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq 4.5 \cdot 10^{+15}:\\ \;\;\;\;i \cdot \left(a \cdot b\right)\\ \mathbf{elif}\;t \leq 5 \cdot 10^{+204}:\\ \;\;\;\;j \cdot \left(t \cdot c\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(t \cdot \left(-x\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* z (* c (- b)))) (t_2 (* x (* y z))))
   (if (<= t -3.7e+93)
     (* t (* c j))
     (if (<= t -2.8e-217)
       (* i (* y (- j)))
       (if (<= t -5e-249)
         t_2
         (if (<= t -2.6e-291)
           t_1
           (if (<= t 5.8e-258)
             t_2
             (if (<= t 8.2e-126)
               t_1
               (if (<= t 4.5e+15)
                 (* i (* a b))
                 (if (<= t 5e+204) (* j (* t c)) (* a (* t (- x)))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = z * (c * -b);
	double t_2 = x * (y * z);
	double tmp;
	if (t <= -3.7e+93) {
		tmp = t * (c * j);
	} else if (t <= -2.8e-217) {
		tmp = i * (y * -j);
	} else if (t <= -5e-249) {
		tmp = t_2;
	} else if (t <= -2.6e-291) {
		tmp = t_1;
	} else if (t <= 5.8e-258) {
		tmp = t_2;
	} else if (t <= 8.2e-126) {
		tmp = t_1;
	} else if (t <= 4.5e+15) {
		tmp = i * (a * b);
	} else if (t <= 5e+204) {
		tmp = j * (t * c);
	} else {
		tmp = a * (t * -x);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = z * (c * -b)
    t_2 = x * (y * z)
    if (t <= (-3.7d+93)) then
        tmp = t * (c * j)
    else if (t <= (-2.8d-217)) then
        tmp = i * (y * -j)
    else if (t <= (-5d-249)) then
        tmp = t_2
    else if (t <= (-2.6d-291)) then
        tmp = t_1
    else if (t <= 5.8d-258) then
        tmp = t_2
    else if (t <= 8.2d-126) then
        tmp = t_1
    else if (t <= 4.5d+15) then
        tmp = i * (a * b)
    else if (t <= 5d+204) then
        tmp = j * (t * c)
    else
        tmp = a * (t * -x)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = z * (c * -b);
	double t_2 = x * (y * z);
	double tmp;
	if (t <= -3.7e+93) {
		tmp = t * (c * j);
	} else if (t <= -2.8e-217) {
		tmp = i * (y * -j);
	} else if (t <= -5e-249) {
		tmp = t_2;
	} else if (t <= -2.6e-291) {
		tmp = t_1;
	} else if (t <= 5.8e-258) {
		tmp = t_2;
	} else if (t <= 8.2e-126) {
		tmp = t_1;
	} else if (t <= 4.5e+15) {
		tmp = i * (a * b);
	} else if (t <= 5e+204) {
		tmp = j * (t * c);
	} else {
		tmp = a * (t * -x);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = z * (c * -b)
	t_2 = x * (y * z)
	tmp = 0
	if t <= -3.7e+93:
		tmp = t * (c * j)
	elif t <= -2.8e-217:
		tmp = i * (y * -j)
	elif t <= -5e-249:
		tmp = t_2
	elif t <= -2.6e-291:
		tmp = t_1
	elif t <= 5.8e-258:
		tmp = t_2
	elif t <= 8.2e-126:
		tmp = t_1
	elif t <= 4.5e+15:
		tmp = i * (a * b)
	elif t <= 5e+204:
		tmp = j * (t * c)
	else:
		tmp = a * (t * -x)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(z * Float64(c * Float64(-b)))
	t_2 = Float64(x * Float64(y * z))
	tmp = 0.0
	if (t <= -3.7e+93)
		tmp = Float64(t * Float64(c * j));
	elseif (t <= -2.8e-217)
		tmp = Float64(i * Float64(y * Float64(-j)));
	elseif (t <= -5e-249)
		tmp = t_2;
	elseif (t <= -2.6e-291)
		tmp = t_1;
	elseif (t <= 5.8e-258)
		tmp = t_2;
	elseif (t <= 8.2e-126)
		tmp = t_1;
	elseif (t <= 4.5e+15)
		tmp = Float64(i * Float64(a * b));
	elseif (t <= 5e+204)
		tmp = Float64(j * Float64(t * c));
	else
		tmp = Float64(a * Float64(t * Float64(-x)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = z * (c * -b);
	t_2 = x * (y * z);
	tmp = 0.0;
	if (t <= -3.7e+93)
		tmp = t * (c * j);
	elseif (t <= -2.8e-217)
		tmp = i * (y * -j);
	elseif (t <= -5e-249)
		tmp = t_2;
	elseif (t <= -2.6e-291)
		tmp = t_1;
	elseif (t <= 5.8e-258)
		tmp = t_2;
	elseif (t <= 8.2e-126)
		tmp = t_1;
	elseif (t <= 4.5e+15)
		tmp = i * (a * b);
	elseif (t <= 5e+204)
		tmp = j * (t * c);
	else
		tmp = a * (t * -x);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(z * N[(c * (-b)), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -3.7e+93], N[(t * N[(c * j), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -2.8e-217], N[(i * N[(y * (-j)), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -5e-249], t$95$2, If[LessEqual[t, -2.6e-291], t$95$1, If[LessEqual[t, 5.8e-258], t$95$2, If[LessEqual[t, 8.2e-126], t$95$1, If[LessEqual[t, 4.5e+15], N[(i * N[(a * b), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 5e+204], N[(j * N[(t * c), $MachinePrecision]), $MachinePrecision], N[(a * N[(t * (-x)), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]

Derivation

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

Alternative 10: 50.8% accurate, 1.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y \cdot \left(x \cdot z - i \cdot j\right)\\ t_2 := t \cdot \left(c \cdot j - x \cdot a\right)\\ \mathbf{if}\;t \leq -50000000000000:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t \leq -8.5 \cdot 10^{-250}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq -2.6 \cdot 10^{-291}:\\ \;\;\;\;c \cdot \left(t \cdot j - z \cdot b\right)\\ \mathbf{elif}\;t \leq 4 \cdot 10^{-266}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq 0.044:\\ \;\;\;\;b \cdot \left(a \cdot i - z \cdot c\right)\\ \mathbf{elif}\;t \leq 5.8 \cdot 10^{+120}:\\ \;\;\;\;j \cdot \left(t \cdot c - y \cdot i\right)\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* y (- (* x z) (* i j)))) (t_2 (* t (- (* c j) (* x a)))))
   (if (<= t -50000000000000.0)
     t_2
     (if (<= t -8.5e-250)
       t_1
       (if (<= t -2.6e-291)
         (* c (- (* t j) (* z b)))
         (if (<= t 4e-266)
           t_1
           (if (<= t 0.044)
             (* b (- (* a i) (* z c)))
             (if (<= t 5.8e+120) (* j (- (* t c) (* y i))) t_2))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = y * ((x * z) - (i * j));
	double t_2 = t * ((c * j) - (x * a));
	double tmp;
	if (t <= -50000000000000.0) {
		tmp = t_2;
	} else if (t <= -8.5e-250) {
		tmp = t_1;
	} else if (t <= -2.6e-291) {
		tmp = c * ((t * j) - (z * b));
	} else if (t <= 4e-266) {
		tmp = t_1;
	} else if (t <= 0.044) {
		tmp = b * ((a * i) - (z * c));
	} else if (t <= 5.8e+120) {
		tmp = j * ((t * c) - (y * i));
	} else {
		tmp = t_2;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = y * ((x * z) - (i * j))
    t_2 = t * ((c * j) - (x * a))
    if (t <= (-50000000000000.0d0)) then
        tmp = t_2
    else if (t <= (-8.5d-250)) then
        tmp = t_1
    else if (t <= (-2.6d-291)) then
        tmp = c * ((t * j) - (z * b))
    else if (t <= 4d-266) then
        tmp = t_1
    else if (t <= 0.044d0) then
        tmp = b * ((a * i) - (z * c))
    else if (t <= 5.8d+120) then
        tmp = j * ((t * c) - (y * i))
    else
        tmp = t_2
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = y * ((x * z) - (i * j));
	double t_2 = t * ((c * j) - (x * a));
	double tmp;
	if (t <= -50000000000000.0) {
		tmp = t_2;
	} else if (t <= -8.5e-250) {
		tmp = t_1;
	} else if (t <= -2.6e-291) {
		tmp = c * ((t * j) - (z * b));
	} else if (t <= 4e-266) {
		tmp = t_1;
	} else if (t <= 0.044) {
		tmp = b * ((a * i) - (z * c));
	} else if (t <= 5.8e+120) {
		tmp = j * ((t * c) - (y * i));
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = y * ((x * z) - (i * j))
	t_2 = t * ((c * j) - (x * a))
	tmp = 0
	if t <= -50000000000000.0:
		tmp = t_2
	elif t <= -8.5e-250:
		tmp = t_1
	elif t <= -2.6e-291:
		tmp = c * ((t * j) - (z * b))
	elif t <= 4e-266:
		tmp = t_1
	elif t <= 0.044:
		tmp = b * ((a * i) - (z * c))
	elif t <= 5.8e+120:
		tmp = j * ((t * c) - (y * i))
	else:
		tmp = t_2
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(y * Float64(Float64(x * z) - Float64(i * j)))
	t_2 = Float64(t * Float64(Float64(c * j) - Float64(x * a)))
	tmp = 0.0
	if (t <= -50000000000000.0)
		tmp = t_2;
	elseif (t <= -8.5e-250)
		tmp = t_1;
	elseif (t <= -2.6e-291)
		tmp = Float64(c * Float64(Float64(t * j) - Float64(z * b)));
	elseif (t <= 4e-266)
		tmp = t_1;
	elseif (t <= 0.044)
		tmp = Float64(b * Float64(Float64(a * i) - Float64(z * c)));
	elseif (t <= 5.8e+120)
		tmp = Float64(j * Float64(Float64(t * c) - Float64(y * i)));
	else
		tmp = t_2;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = y * ((x * z) - (i * j));
	t_2 = t * ((c * j) - (x * a));
	tmp = 0.0;
	if (t <= -50000000000000.0)
		tmp = t_2;
	elseif (t <= -8.5e-250)
		tmp = t_1;
	elseif (t <= -2.6e-291)
		tmp = c * ((t * j) - (z * b));
	elseif (t <= 4e-266)
		tmp = t_1;
	elseif (t <= 0.044)
		tmp = b * ((a * i) - (z * c));
	elseif (t <= 5.8e+120)
		tmp = j * ((t * c) - (y * i));
	else
		tmp = t_2;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(y * N[(N[(x * z), $MachinePrecision] - N[(i * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(t * N[(N[(c * j), $MachinePrecision] - N[(x * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -50000000000000.0], t$95$2, If[LessEqual[t, -8.5e-250], t$95$1, If[LessEqual[t, -2.6e-291], N[(c * N[(N[(t * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 4e-266], t$95$1, If[LessEqual[t, 0.044], N[(b * N[(N[(a * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 5.8e+120], N[(j * N[(N[(t * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$2]]]]]]]]

Derivation

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

Alternative 11: 57.7% accurate, 1.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(t \cdot c - y \cdot i\right)\\ \mathbf{if}\;j \leq -8.6 \cdot 10^{+68}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;j \leq -1.45 \cdot 10^{-124}:\\ \;\;\;\;a \cdot \left(b \cdot i - x \cdot t\right)\\ \mathbf{elif}\;j \leq 2.8 \cdot 10^{+104}:\\ \;\;\;\;y \cdot \left(x \cdot z\right) + b \cdot \left(a \cdot i - z \cdot c\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* j (- (* t c) (* y i)))))
   (if (<= j -8.6e+68)
     t_1
     (if (<= j -1.45e-124)
       (* a (- (* b i) (* x t)))
       (if (<= j 2.8e+104) (+ (* y (* x z)) (* b (- (* a i) (* z c)))) t_1)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = j * ((t * c) - (y * i));
	double tmp;
	if (j <= -8.6e+68) {
		tmp = t_1;
	} else if (j <= -1.45e-124) {
		tmp = a * ((b * i) - (x * t));
	} else if (j <= 2.8e+104) {
		tmp = (y * (x * z)) + (b * ((a * i) - (z * c)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: tmp
    t_1 = j * ((t * c) - (y * i))
    if (j <= (-8.6d+68)) then
        tmp = t_1
    else if (j <= (-1.45d-124)) then
        tmp = a * ((b * i) - (x * t))
    else if (j <= 2.8d+104) then
        tmp = (y * (x * z)) + (b * ((a * i) - (z * c)))
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = j * ((t * c) - (y * i));
	double tmp;
	if (j <= -8.6e+68) {
		tmp = t_1;
	} else if (j <= -1.45e-124) {
		tmp = a * ((b * i) - (x * t));
	} else if (j <= 2.8e+104) {
		tmp = (y * (x * z)) + (b * ((a * i) - (z * c)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = j * ((t * c) - (y * i))
	tmp = 0
	if j <= -8.6e+68:
		tmp = t_1
	elif j <= -1.45e-124:
		tmp = a * ((b * i) - (x * t))
	elif j <= 2.8e+104:
		tmp = (y * (x * z)) + (b * ((a * i) - (z * c)))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(j * Float64(Float64(t * c) - Float64(y * i)))
	tmp = 0.0
	if (j <= -8.6e+68)
		tmp = t_1;
	elseif (j <= -1.45e-124)
		tmp = Float64(a * Float64(Float64(b * i) - Float64(x * t)));
	elseif (j <= 2.8e+104)
		tmp = Float64(Float64(y * Float64(x * z)) + Float64(b * Float64(Float64(a * i) - Float64(z * c))));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = j * ((t * c) - (y * i));
	tmp = 0.0;
	if (j <= -8.6e+68)
		tmp = t_1;
	elseif (j <= -1.45e-124)
		tmp = a * ((b * i) - (x * t));
	elseif (j <= 2.8e+104)
		tmp = (y * (x * z)) + (b * ((a * i) - (z * c)));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(j * N[(N[(t * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -8.6e+68], t$95$1, If[LessEqual[j, -1.45e-124], N[(a * N[(N[(b * i), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 2.8e+104], N[(N[(y * N[(x * z), $MachinePrecision]), $MachinePrecision] + N[(b * N[(N[(a * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]

Derivation

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

Alternative 12: 57.9% accurate, 1.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(t \cdot c - y \cdot i\right)\\ \mathbf{if}\;j \leq -5.6 \cdot 10^{+68}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;j \leq -1.45 \cdot 10^{-124}:\\ \;\;\;\;a \cdot \left(b \cdot i - x \cdot t\right)\\ \mathbf{elif}\;j \leq 520:\\ \;\;\;\;z \cdot \left(x \cdot y - b \cdot c\right) - x \cdot \left(t \cdot a\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* j (- (* t c) (* y i)))))
   (if (<= j -5.6e+68)
     t_1
     (if (<= j -1.45e-124)
       (* a (- (* b i) (* x t)))
       (if (<= j 520.0) (- (* z (- (* x y) (* b c))) (* x (* t a))) t_1)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = j * ((t * c) - (y * i));
	double tmp;
	if (j <= -5.6e+68) {
		tmp = t_1;
	} else if (j <= -1.45e-124) {
		tmp = a * ((b * i) - (x * t));
	} else if (j <= 520.0) {
		tmp = (z * ((x * y) - (b * c))) - (x * (t * a));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: tmp
    t_1 = j * ((t * c) - (y * i))
    if (j <= (-5.6d+68)) then
        tmp = t_1
    else if (j <= (-1.45d-124)) then
        tmp = a * ((b * i) - (x * t))
    else if (j <= 520.0d0) then
        tmp = (z * ((x * y) - (b * c))) - (x * (t * a))
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = j * ((t * c) - (y * i));
	double tmp;
	if (j <= -5.6e+68) {
		tmp = t_1;
	} else if (j <= -1.45e-124) {
		tmp = a * ((b * i) - (x * t));
	} else if (j <= 520.0) {
		tmp = (z * ((x * y) - (b * c))) - (x * (t * a));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = j * ((t * c) - (y * i))
	tmp = 0
	if j <= -5.6e+68:
		tmp = t_1
	elif j <= -1.45e-124:
		tmp = a * ((b * i) - (x * t))
	elif j <= 520.0:
		tmp = (z * ((x * y) - (b * c))) - (x * (t * a))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(j * Float64(Float64(t * c) - Float64(y * i)))
	tmp = 0.0
	if (j <= -5.6e+68)
		tmp = t_1;
	elseif (j <= -1.45e-124)
		tmp = Float64(a * Float64(Float64(b * i) - Float64(x * t)));
	elseif (j <= 520.0)
		tmp = Float64(Float64(z * Float64(Float64(x * y) - Float64(b * c))) - Float64(x * Float64(t * a)));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = j * ((t * c) - (y * i));
	tmp = 0.0;
	if (j <= -5.6e+68)
		tmp = t_1;
	elseif (j <= -1.45e-124)
		tmp = a * ((b * i) - (x * t));
	elseif (j <= 520.0)
		tmp = (z * ((x * y) - (b * c))) - (x * (t * a));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(j * N[(N[(t * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -5.6e+68], t$95$1, If[LessEqual[j, -1.45e-124], N[(a * N[(N[(b * i), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 520.0], N[(N[(z * N[(N[(x * y), $MachinePrecision] - N[(b * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(x * N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]

Derivation

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

Alternative 13: 29.1% accurate, 1.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := i \cdot \left(a \cdot b\right)\\ t_2 := a \cdot \left(t \cdot \left(-x\right)\right)\\ \mathbf{if}\;t \leq -1.72 \cdot 10^{+90}:\\ \;\;\;\;t \cdot \left(c \cdot j\right)\\ \mathbf{elif}\;t \leq -2 \cdot 10^{-39}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t \leq -8.2 \cdot 10^{-88}:\\ \;\;\;\;c \cdot \left(t \cdot j\right)\\ \mathbf{elif}\;t \leq -1.05 \cdot 10^{-215}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq 7.2 \cdot 10^{-220}:\\ \;\;\;\;x \cdot \left(y \cdot z\right)\\ \mathbf{elif}\;t \leq 3.7 \cdot 10^{+14}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq 6.5 \cdot 10^{+203}:\\ \;\;\;\;j \cdot \left(t \cdot c\right)\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* i (* a b))) (t_2 (* a (* t (- x)))))
   (if (<= t -1.72e+90)
     (* t (* c j))
     (if (<= t -2e-39)
       t_2
       (if (<= t -8.2e-88)
         (* c (* t j))
         (if (<= t -1.05e-215)
           t_1
           (if (<= t 7.2e-220)
             (* x (* y z))
             (if (<= t 3.7e+14)
               t_1
               (if (<= t 6.5e+203) (* j (* t c)) t_2)))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = i * (a * b);
	double t_2 = a * (t * -x);
	double tmp;
	if (t <= -1.72e+90) {
		tmp = t * (c * j);
	} else if (t <= -2e-39) {
		tmp = t_2;
	} else if (t <= -8.2e-88) {
		tmp = c * (t * j);
	} else if (t <= -1.05e-215) {
		tmp = t_1;
	} else if (t <= 7.2e-220) {
		tmp = x * (y * z);
	} else if (t <= 3.7e+14) {
		tmp = t_1;
	} else if (t <= 6.5e+203) {
		tmp = j * (t * c);
	} else {
		tmp = t_2;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = i * (a * b)
    t_2 = a * (t * -x)
    if (t <= (-1.72d+90)) then
        tmp = t * (c * j)
    else if (t <= (-2d-39)) then
        tmp = t_2
    else if (t <= (-8.2d-88)) then
        tmp = c * (t * j)
    else if (t <= (-1.05d-215)) then
        tmp = t_1
    else if (t <= 7.2d-220) then
        tmp = x * (y * z)
    else if (t <= 3.7d+14) then
        tmp = t_1
    else if (t <= 6.5d+203) then
        tmp = j * (t * c)
    else
        tmp = t_2
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = i * (a * b);
	double t_2 = a * (t * -x);
	double tmp;
	if (t <= -1.72e+90) {
		tmp = t * (c * j);
	} else if (t <= -2e-39) {
		tmp = t_2;
	} else if (t <= -8.2e-88) {
		tmp = c * (t * j);
	} else if (t <= -1.05e-215) {
		tmp = t_1;
	} else if (t <= 7.2e-220) {
		tmp = x * (y * z);
	} else if (t <= 3.7e+14) {
		tmp = t_1;
	} else if (t <= 6.5e+203) {
		tmp = j * (t * c);
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = i * (a * b)
	t_2 = a * (t * -x)
	tmp = 0
	if t <= -1.72e+90:
		tmp = t * (c * j)
	elif t <= -2e-39:
		tmp = t_2
	elif t <= -8.2e-88:
		tmp = c * (t * j)
	elif t <= -1.05e-215:
		tmp = t_1
	elif t <= 7.2e-220:
		tmp = x * (y * z)
	elif t <= 3.7e+14:
		tmp = t_1
	elif t <= 6.5e+203:
		tmp = j * (t * c)
	else:
		tmp = t_2
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(i * Float64(a * b))
	t_2 = Float64(a * Float64(t * Float64(-x)))
	tmp = 0.0
	if (t <= -1.72e+90)
		tmp = Float64(t * Float64(c * j));
	elseif (t <= -2e-39)
		tmp = t_2;
	elseif (t <= -8.2e-88)
		tmp = Float64(c * Float64(t * j));
	elseif (t <= -1.05e-215)
		tmp = t_1;
	elseif (t <= 7.2e-220)
		tmp = Float64(x * Float64(y * z));
	elseif (t <= 3.7e+14)
		tmp = t_1;
	elseif (t <= 6.5e+203)
		tmp = Float64(j * Float64(t * c));
	else
		tmp = t_2;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = i * (a * b);
	t_2 = a * (t * -x);
	tmp = 0.0;
	if (t <= -1.72e+90)
		tmp = t * (c * j);
	elseif (t <= -2e-39)
		tmp = t_2;
	elseif (t <= -8.2e-88)
		tmp = c * (t * j);
	elseif (t <= -1.05e-215)
		tmp = t_1;
	elseif (t <= 7.2e-220)
		tmp = x * (y * z);
	elseif (t <= 3.7e+14)
		tmp = t_1;
	elseif (t <= 6.5e+203)
		tmp = j * (t * c);
	else
		tmp = t_2;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(i * N[(a * b), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(a * N[(t * (-x)), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -1.72e+90], N[(t * N[(c * j), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -2e-39], t$95$2, If[LessEqual[t, -8.2e-88], N[(c * N[(t * j), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -1.05e-215], t$95$1, If[LessEqual[t, 7.2e-220], N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 3.7e+14], t$95$1, If[LessEqual[t, 6.5e+203], N[(j * N[(t * c), $MachinePrecision]), $MachinePrecision], t$95$2]]]]]]]]]

Derivation

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

Alternative 14: 47.3% accurate, 1.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := t \cdot \left(c \cdot j - x \cdot a\right)\\ \mathbf{if}\;t \leq -7.5 \cdot 10^{+32}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq -1.18 \cdot 10^{-268}:\\ \;\;\;\;b \cdot \left(a \cdot i - z \cdot c\right)\\ \mathbf{elif}\;t \leq 1.3 \cdot 10^{-117}:\\ \;\;\;\;c \cdot \left(t \cdot j - z \cdot b\right)\\ \mathbf{elif}\;t \leq 0.023:\\ \;\;\;\;a \cdot \left(b \cdot i - x \cdot t\right)\\ \mathbf{elif}\;t \leq 1.15 \cdot 10^{+120}:\\ \;\;\;\;j \cdot \left(t \cdot c - y \cdot i\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* t (- (* c j) (* x a)))))
   (if (<= t -7.5e+32)
     t_1
     (if (<= t -1.18e-268)
       (* b (- (* a i) (* z c)))
       (if (<= t 1.3e-117)
         (* c (- (* t j) (* z b)))
         (if (<= t 0.023)
           (* a (- (* b i) (* x t)))
           (if (<= t 1.15e+120) (* j (- (* t c) (* y i))) t_1)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = t * ((c * j) - (x * a));
	double tmp;
	if (t <= -7.5e+32) {
		tmp = t_1;
	} else if (t <= -1.18e-268) {
		tmp = b * ((a * i) - (z * c));
	} else if (t <= 1.3e-117) {
		tmp = c * ((t * j) - (z * b));
	} else if (t <= 0.023) {
		tmp = a * ((b * i) - (x * t));
	} else if (t <= 1.15e+120) {
		tmp = j * ((t * c) - (y * i));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: tmp
    t_1 = t * ((c * j) - (x * a))
    if (t <= (-7.5d+32)) then
        tmp = t_1
    else if (t <= (-1.18d-268)) then
        tmp = b * ((a * i) - (z * c))
    else if (t <= 1.3d-117) then
        tmp = c * ((t * j) - (z * b))
    else if (t <= 0.023d0) then
        tmp = a * ((b * i) - (x * t))
    else if (t <= 1.15d+120) then
        tmp = j * ((t * c) - (y * i))
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = t * ((c * j) - (x * a));
	double tmp;
	if (t <= -7.5e+32) {
		tmp = t_1;
	} else if (t <= -1.18e-268) {
		tmp = b * ((a * i) - (z * c));
	} else if (t <= 1.3e-117) {
		tmp = c * ((t * j) - (z * b));
	} else if (t <= 0.023) {
		tmp = a * ((b * i) - (x * t));
	} else if (t <= 1.15e+120) {
		tmp = j * ((t * c) - (y * i));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = t * ((c * j) - (x * a))
	tmp = 0
	if t <= -7.5e+32:
		tmp = t_1
	elif t <= -1.18e-268:
		tmp = b * ((a * i) - (z * c))
	elif t <= 1.3e-117:
		tmp = c * ((t * j) - (z * b))
	elif t <= 0.023:
		tmp = a * ((b * i) - (x * t))
	elif t <= 1.15e+120:
		tmp = j * ((t * c) - (y * i))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(t * Float64(Float64(c * j) - Float64(x * a)))
	tmp = 0.0
	if (t <= -7.5e+32)
		tmp = t_1;
	elseif (t <= -1.18e-268)
		tmp = Float64(b * Float64(Float64(a * i) - Float64(z * c)));
	elseif (t <= 1.3e-117)
		tmp = Float64(c * Float64(Float64(t * j) - Float64(z * b)));
	elseif (t <= 0.023)
		tmp = Float64(a * Float64(Float64(b * i) - Float64(x * t)));
	elseif (t <= 1.15e+120)
		tmp = Float64(j * Float64(Float64(t * c) - Float64(y * i)));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = t * ((c * j) - (x * a));
	tmp = 0.0;
	if (t <= -7.5e+32)
		tmp = t_1;
	elseif (t <= -1.18e-268)
		tmp = b * ((a * i) - (z * c));
	elseif (t <= 1.3e-117)
		tmp = c * ((t * j) - (z * b));
	elseif (t <= 0.023)
		tmp = a * ((b * i) - (x * t));
	elseif (t <= 1.15e+120)
		tmp = j * ((t * c) - (y * i));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(t * N[(N[(c * j), $MachinePrecision] - N[(x * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -7.5e+32], t$95$1, If[LessEqual[t, -1.18e-268], N[(b * N[(N[(a * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.3e-117], N[(c * N[(N[(t * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 0.023], N[(a * N[(N[(b * i), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.15e+120], N[(j * N[(N[(t * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]

Derivation

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

Alternative 15: 39.4% accurate, 1.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot \left(b \cdot i - x \cdot t\right)\\ \mathbf{if}\;c \leq -5.2 \cdot 10^{+68}:\\ \;\;\;\;c \cdot \left(t \cdot j\right)\\ \mathbf{elif}\;c \leq -4.5 \cdot 10^{-179}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;c \leq 5.4 \cdot 10^{-278}:\\ \;\;\;\;i \cdot \left(y \cdot \left(-j\right)\right)\\ \mathbf{elif}\;c \leq 3.9 \cdot 10^{+169}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;z \cdot \left(c \cdot \left(-b\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* a (- (* b i) (* x t)))))
   (if (<= c -5.2e+68)
     (* c (* t j))
     (if (<= c -4.5e-179)
       t_1
       (if (<= c 5.4e-278)
         (* i (* y (- j)))
         (if (<= c 3.9e+169) t_1 (* z (* c (- b)))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = a * ((b * i) - (x * t));
	double tmp;
	if (c <= -5.2e+68) {
		tmp = c * (t * j);
	} else if (c <= -4.5e-179) {
		tmp = t_1;
	} else if (c <= 5.4e-278) {
		tmp = i * (y * -j);
	} else if (c <= 3.9e+169) {
		tmp = t_1;
	} else {
		tmp = z * (c * -b);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: tmp
    t_1 = a * ((b * i) - (x * t))
    if (c <= (-5.2d+68)) then
        tmp = c * (t * j)
    else if (c <= (-4.5d-179)) then
        tmp = t_1
    else if (c <= 5.4d-278) then
        tmp = i * (y * -j)
    else if (c <= 3.9d+169) then
        tmp = t_1
    else
        tmp = z * (c * -b)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = a * ((b * i) - (x * t));
	double tmp;
	if (c <= -5.2e+68) {
		tmp = c * (t * j);
	} else if (c <= -4.5e-179) {
		tmp = t_1;
	} else if (c <= 5.4e-278) {
		tmp = i * (y * -j);
	} else if (c <= 3.9e+169) {
		tmp = t_1;
	} else {
		tmp = z * (c * -b);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = a * ((b * i) - (x * t))
	tmp = 0
	if c <= -5.2e+68:
		tmp = c * (t * j)
	elif c <= -4.5e-179:
		tmp = t_1
	elif c <= 5.4e-278:
		tmp = i * (y * -j)
	elif c <= 3.9e+169:
		tmp = t_1
	else:
		tmp = z * (c * -b)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(a * Float64(Float64(b * i) - Float64(x * t)))
	tmp = 0.0
	if (c <= -5.2e+68)
		tmp = Float64(c * Float64(t * j));
	elseif (c <= -4.5e-179)
		tmp = t_1;
	elseif (c <= 5.4e-278)
		tmp = Float64(i * Float64(y * Float64(-j)));
	elseif (c <= 3.9e+169)
		tmp = t_1;
	else
		tmp = Float64(z * Float64(c * Float64(-b)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = a * ((b * i) - (x * t));
	tmp = 0.0;
	if (c <= -5.2e+68)
		tmp = c * (t * j);
	elseif (c <= -4.5e-179)
		tmp = t_1;
	elseif (c <= 5.4e-278)
		tmp = i * (y * -j);
	elseif (c <= 3.9e+169)
		tmp = t_1;
	else
		tmp = z * (c * -b);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(a * N[(N[(b * i), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[c, -5.2e+68], N[(c * N[(t * j), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, -4.5e-179], t$95$1, If[LessEqual[c, 5.4e-278], N[(i * N[(y * (-j)), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 3.9e+169], t$95$1, N[(z * N[(c * (-b)), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

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

Alternative 16: 41.1% accurate, 1.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(a \cdot i - z \cdot c\right)\\ \mathbf{if}\;t \leq -9 \cdot 10^{+73}:\\ \;\;\;\;t \cdot \left(c \cdot j\right)\\ \mathbf{elif}\;t \leq -2.5 \cdot 10^{-291}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq 1.8 \cdot 10^{-266}:\\ \;\;\;\;x \cdot \left(y \cdot z\right)\\ \mathbf{elif}\;t \leq 2.8 \cdot 10^{-137}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(b \cdot i - x \cdot t\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* b (- (* a i) (* z c)))))
   (if (<= t -9e+73)
     (* t (* c j))
     (if (<= t -2.5e-291)
       t_1
       (if (<= t 1.8e-266)
         (* x (* y z))
         (if (<= t 2.8e-137) t_1 (* a (- (* b i) (* x t)))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = b * ((a * i) - (z * c));
	double tmp;
	if (t <= -9e+73) {
		tmp = t * (c * j);
	} else if (t <= -2.5e-291) {
		tmp = t_1;
	} else if (t <= 1.8e-266) {
		tmp = x * (y * z);
	} else if (t <= 2.8e-137) {
		tmp = t_1;
	} else {
		tmp = a * ((b * i) - (x * t));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: tmp
    t_1 = b * ((a * i) - (z * c))
    if (t <= (-9d+73)) then
        tmp = t * (c * j)
    else if (t <= (-2.5d-291)) then
        tmp = t_1
    else if (t <= 1.8d-266) then
        tmp = x * (y * z)
    else if (t <= 2.8d-137) then
        tmp = t_1
    else
        tmp = a * ((b * i) - (x * t))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = b * ((a * i) - (z * c));
	double tmp;
	if (t <= -9e+73) {
		tmp = t * (c * j);
	} else if (t <= -2.5e-291) {
		tmp = t_1;
	} else if (t <= 1.8e-266) {
		tmp = x * (y * z);
	} else if (t <= 2.8e-137) {
		tmp = t_1;
	} else {
		tmp = a * ((b * i) - (x * t));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = b * ((a * i) - (z * c))
	tmp = 0
	if t <= -9e+73:
		tmp = t * (c * j)
	elif t <= -2.5e-291:
		tmp = t_1
	elif t <= 1.8e-266:
		tmp = x * (y * z)
	elif t <= 2.8e-137:
		tmp = t_1
	else:
		tmp = a * ((b * i) - (x * t))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(b * Float64(Float64(a * i) - Float64(z * c)))
	tmp = 0.0
	if (t <= -9e+73)
		tmp = Float64(t * Float64(c * j));
	elseif (t <= -2.5e-291)
		tmp = t_1;
	elseif (t <= 1.8e-266)
		tmp = Float64(x * Float64(y * z));
	elseif (t <= 2.8e-137)
		tmp = t_1;
	else
		tmp = Float64(a * Float64(Float64(b * i) - Float64(x * t)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = b * ((a * i) - (z * c));
	tmp = 0.0;
	if (t <= -9e+73)
		tmp = t * (c * j);
	elseif (t <= -2.5e-291)
		tmp = t_1;
	elseif (t <= 1.8e-266)
		tmp = x * (y * z);
	elseif (t <= 2.8e-137)
		tmp = t_1;
	else
		tmp = a * ((b * i) - (x * t));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(b * N[(N[(a * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -9e+73], N[(t * N[(c * j), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -2.5e-291], t$95$1, If[LessEqual[t, 1.8e-266], N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 2.8e-137], t$95$1, N[(a * N[(N[(b * i), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

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

Alternative 17: 50.5% accurate, 1.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := c \cdot \left(t \cdot j - z \cdot b\right)\\ t_2 := a \cdot \left(b \cdot i - x \cdot t\right)\\ \mathbf{if}\;a \leq -9.5 \cdot 10^{+133}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq -1.3 \cdot 10^{+70}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -3.45 \cdot 10^{-37}:\\ \;\;\;\;b \cdot \left(a \cdot i - z \cdot c\right)\\ \mathbf{elif}\;a \leq 3.4 \cdot 10^{-8}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* c (- (* t j) (* z b)))) (t_2 (* a (- (* b i) (* x t)))))
   (if (<= a -9.5e+133)
     t_2
     (if (<= a -1.3e+70)
       t_1
       (if (<= a -3.45e-37)
         (* b (- (* a i) (* z c)))
         (if (<= a 3.4e-8) t_1 t_2))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = c * ((t * j) - (z * b));
	double t_2 = a * ((b * i) - (x * t));
	double tmp;
	if (a <= -9.5e+133) {
		tmp = t_2;
	} else if (a <= -1.3e+70) {
		tmp = t_1;
	} else if (a <= -3.45e-37) {
		tmp = b * ((a * i) - (z * c));
	} else if (a <= 3.4e-8) {
		tmp = t_1;
	} else {
		tmp = t_2;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = c * ((t * j) - (z * b))
    t_2 = a * ((b * i) - (x * t))
    if (a <= (-9.5d+133)) then
        tmp = t_2
    else if (a <= (-1.3d+70)) then
        tmp = t_1
    else if (a <= (-3.45d-37)) then
        tmp = b * ((a * i) - (z * c))
    else if (a <= 3.4d-8) then
        tmp = t_1
    else
        tmp = t_2
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = c * ((t * j) - (z * b));
	double t_2 = a * ((b * i) - (x * t));
	double tmp;
	if (a <= -9.5e+133) {
		tmp = t_2;
	} else if (a <= -1.3e+70) {
		tmp = t_1;
	} else if (a <= -3.45e-37) {
		tmp = b * ((a * i) - (z * c));
	} else if (a <= 3.4e-8) {
		tmp = t_1;
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = c * ((t * j) - (z * b))
	t_2 = a * ((b * i) - (x * t))
	tmp = 0
	if a <= -9.5e+133:
		tmp = t_2
	elif a <= -1.3e+70:
		tmp = t_1
	elif a <= -3.45e-37:
		tmp = b * ((a * i) - (z * c))
	elif a <= 3.4e-8:
		tmp = t_1
	else:
		tmp = t_2
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(c * Float64(Float64(t * j) - Float64(z * b)))
	t_2 = Float64(a * Float64(Float64(b * i) - Float64(x * t)))
	tmp = 0.0
	if (a <= -9.5e+133)
		tmp = t_2;
	elseif (a <= -1.3e+70)
		tmp = t_1;
	elseif (a <= -3.45e-37)
		tmp = Float64(b * Float64(Float64(a * i) - Float64(z * c)));
	elseif (a <= 3.4e-8)
		tmp = t_1;
	else
		tmp = t_2;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = c * ((t * j) - (z * b));
	t_2 = a * ((b * i) - (x * t));
	tmp = 0.0;
	if (a <= -9.5e+133)
		tmp = t_2;
	elseif (a <= -1.3e+70)
		tmp = t_1;
	elseif (a <= -3.45e-37)
		tmp = b * ((a * i) - (z * c));
	elseif (a <= 3.4e-8)
		tmp = t_1;
	else
		tmp = t_2;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(c * N[(N[(t * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(a * N[(N[(b * i), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -9.5e+133], t$95$2, If[LessEqual[a, -1.3e+70], t$95$1, If[LessEqual[a, -3.45e-37], N[(b * N[(N[(a * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 3.4e-8], t$95$1, t$95$2]]]]]]

Derivation

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

Alternative 18: 29.5% accurate, 2.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;t \leq -6 \cdot 10^{+17}:\\ \;\;\;\;t \cdot \left(c \cdot j\right)\\ \mathbf{elif}\;t \leq 4.6 \cdot 10^{-220}:\\ \;\;\;\;x \cdot \left(y \cdot z\right)\\ \mathbf{elif}\;t \leq 1.95 \cdot 10^{+15}:\\ \;\;\;\;i \cdot \left(a \cdot b\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(t \cdot c\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (<= t -6e+17)
   (* t (* c j))
   (if (<= t 4.6e-220)
     (* x (* y z))
     (if (<= t 1.95e+15) (* i (* a b)) (* j (* t c))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if (t <= -6e+17) {
		tmp = t * (c * j);
	} else if (t <= 4.6e-220) {
		tmp = x * (y * z);
	} else if (t <= 1.95e+15) {
		tmp = i * (a * b);
	} else {
		tmp = j * (t * c);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: tmp
    if (t <= (-6d+17)) then
        tmp = t * (c * j)
    else if (t <= 4.6d-220) then
        tmp = x * (y * z)
    else if (t <= 1.95d+15) then
        tmp = i * (a * b)
    else
        tmp = j * (t * c)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if (t <= -6e+17) {
		tmp = t * (c * j);
	} else if (t <= 4.6e-220) {
		tmp = x * (y * z);
	} else if (t <= 1.95e+15) {
		tmp = i * (a * b);
	} else {
		tmp = j * (t * c);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if t <= -6e+17:
		tmp = t * (c * j)
	elif t <= 4.6e-220:
		tmp = x * (y * z)
	elif t <= 1.95e+15:
		tmp = i * (a * b)
	else:
		tmp = j * (t * c)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if (t <= -6e+17)
		tmp = Float64(t * Float64(c * j));
	elseif (t <= 4.6e-220)
		tmp = Float64(x * Float64(y * z));
	elseif (t <= 1.95e+15)
		tmp = Float64(i * Float64(a * b));
	else
		tmp = Float64(j * Float64(t * c));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0;
	if (t <= -6e+17)
		tmp = t * (c * j);
	elseif (t <= 4.6e-220)
		tmp = x * (y * z);
	elseif (t <= 1.95e+15)
		tmp = i * (a * b);
	else
		tmp = j * (t * c);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[LessEqual[t, -6e+17], N[(t * N[(c * j), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 4.6e-220], N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.95e+15], N[(i * N[(a * b), $MachinePrecision]), $MachinePrecision], N[(j * N[(t * c), $MachinePrecision]), $MachinePrecision]]]]

Derivation

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

Alternative 19: 29.6% accurate, 3.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;t \leq -1.45 \cdot 10^{+52} \lor \neg \left(t \leq 6.5 \cdot 10^{+14}\right):\\ \;\;\;\;c \cdot \left(t \cdot j\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(b \cdot i\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (or (<= t -1.45e+52) (not (<= t 6.5e+14))) (* c (* t j)) (* a (* b i))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if ((t <= -1.45e+52) || !(t <= 6.5e+14)) {
		tmp = c * (t * j);
	} else {
		tmp = a * (b * i);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: tmp
    if ((t <= (-1.45d+52)) .or. (.not. (t <= 6.5d+14))) then
        tmp = c * (t * j)
    else
        tmp = a * (b * i)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if ((t <= -1.45e+52) || !(t <= 6.5e+14)) {
		tmp = c * (t * j);
	} else {
		tmp = a * (b * i);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if (t <= -1.45e+52) or not (t <= 6.5e+14):
		tmp = c * (t * j)
	else:
		tmp = a * (b * i)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if ((t <= -1.45e+52) || !(t <= 6.5e+14))
		tmp = Float64(c * Float64(t * j));
	else
		tmp = Float64(a * Float64(b * i));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0;
	if ((t <= -1.45e+52) || ~((t <= 6.5e+14)))
		tmp = c * (t * j);
	else
		tmp = a * (b * i);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[Or[LessEqual[t, -1.45e+52], N[Not[LessEqual[t, 6.5e+14]], $MachinePrecision]], N[(c * N[(t * j), $MachinePrecision]), $MachinePrecision], N[(a * N[(b * i), $MachinePrecision]), $MachinePrecision]]

Derivation

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

Alternative 20: 29.4% accurate, 3.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;t \leq -9 \cdot 10^{+51} \lor \neg \left(t \leq 1.2 \cdot 10^{+15}\right):\\ \;\;\;\;c \cdot \left(t \cdot j\right)\\ \mathbf{else}:\\ \;\;\;\;i \cdot \left(a \cdot b\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (or (<= t -9e+51) (not (<= t 1.2e+15))) (* c (* t j)) (* i (* a b))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if ((t <= -9e+51) || !(t <= 1.2e+15)) {
		tmp = c * (t * j);
	} else {
		tmp = i * (a * b);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: tmp
    if ((t <= (-9d+51)) .or. (.not. (t <= 1.2d+15))) then
        tmp = c * (t * j)
    else
        tmp = i * (a * b)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if ((t <= -9e+51) || !(t <= 1.2e+15)) {
		tmp = c * (t * j);
	} else {
		tmp = i * (a * b);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if (t <= -9e+51) or not (t <= 1.2e+15):
		tmp = c * (t * j)
	else:
		tmp = i * (a * b)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if ((t <= -9e+51) || !(t <= 1.2e+15))
		tmp = Float64(c * Float64(t * j));
	else
		tmp = Float64(i * Float64(a * b));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0;
	if ((t <= -9e+51) || ~((t <= 1.2e+15)))
		tmp = c * (t * j);
	else
		tmp = i * (a * b);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[Or[LessEqual[t, -9e+51], N[Not[LessEqual[t, 1.2e+15]], $MachinePrecision]], N[(c * N[(t * j), $MachinePrecision]), $MachinePrecision], N[(i * N[(a * b), $MachinePrecision]), $MachinePrecision]]

Derivation

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

Alternative 21: 29.6% accurate, 3.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;t \leq -6.4 \cdot 10^{+53}:\\ \;\;\;\;c \cdot \left(t \cdot j\right)\\ \mathbf{elif}\;t \leq 5.8 \cdot 10^{+15}:\\ \;\;\;\;i \cdot \left(a \cdot b\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(t \cdot c\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (<= t -6.4e+53)
   (* c (* t j))
   (if (<= t 5.8e+15) (* i (* a b)) (* j (* t c)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if (t <= -6.4e+53) {
		tmp = c * (t * j);
	} else if (t <= 5.8e+15) {
		tmp = i * (a * b);
	} else {
		tmp = j * (t * c);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: tmp
    if (t <= (-6.4d+53)) then
        tmp = c * (t * j)
    else if (t <= 5.8d+15) then
        tmp = i * (a * b)
    else
        tmp = j * (t * c)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if (t <= -6.4e+53) {
		tmp = c * (t * j);
	} else if (t <= 5.8e+15) {
		tmp = i * (a * b);
	} else {
		tmp = j * (t * c);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if t <= -6.4e+53:
		tmp = c * (t * j)
	elif t <= 5.8e+15:
		tmp = i * (a * b)
	else:
		tmp = j * (t * c)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if (t <= -6.4e+53)
		tmp = Float64(c * Float64(t * j));
	elseif (t <= 5.8e+15)
		tmp = Float64(i * Float64(a * b));
	else
		tmp = Float64(j * Float64(t * c));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0;
	if (t <= -6.4e+53)
		tmp = c * (t * j);
	elseif (t <= 5.8e+15)
		tmp = i * (a * b);
	else
		tmp = j * (t * c);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[LessEqual[t, -6.4e+53], N[(c * N[(t * j), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 5.8e+15], N[(i * N[(a * b), $MachinePrecision]), $MachinePrecision], N[(j * N[(t * c), $MachinePrecision]), $MachinePrecision]]]

Derivation

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

Alternative 22: 29.4% accurate, 3.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;t \leq -9 \cdot 10^{+51}:\\ \;\;\;\;t \cdot \left(c \cdot j\right)\\ \mathbf{elif}\;t \leq 1.25 \cdot 10^{+15}:\\ \;\;\;\;i \cdot \left(a \cdot b\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(t \cdot c\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (<= t -9e+51)
   (* t (* c j))
   (if (<= t 1.25e+15) (* i (* a b)) (* j (* t c)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if (t <= -9e+51) {
		tmp = t * (c * j);
	} else if (t <= 1.25e+15) {
		tmp = i * (a * b);
	} else {
		tmp = j * (t * c);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: tmp
    if (t <= (-9d+51)) then
        tmp = t * (c * j)
    else if (t <= 1.25d+15) then
        tmp = i * (a * b)
    else
        tmp = j * (t * c)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if (t <= -9e+51) {
		tmp = t * (c * j);
	} else if (t <= 1.25e+15) {
		tmp = i * (a * b);
	} else {
		tmp = j * (t * c);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if t <= -9e+51:
		tmp = t * (c * j)
	elif t <= 1.25e+15:
		tmp = i * (a * b)
	else:
		tmp = j * (t * c)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if (t <= -9e+51)
		tmp = Float64(t * Float64(c * j));
	elseif (t <= 1.25e+15)
		tmp = Float64(i * Float64(a * b));
	else
		tmp = Float64(j * Float64(t * c));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0;
	if (t <= -9e+51)
		tmp = t * (c * j);
	elseif (t <= 1.25e+15)
		tmp = i * (a * b);
	else
		tmp = j * (t * c);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[LessEqual[t, -9e+51], N[(t * N[(c * j), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.25e+15], N[(i * N[(a * b), $MachinePrecision]), $MachinePrecision], N[(j * N[(t * c), $MachinePrecision]), $MachinePrecision]]]

Derivation

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

Alternative 23: 22.2% accurate, 5.8× speedup

Math

\[\begin{array}{l} \\ a \cdot \left(b \cdot i\right) \end{array} \]

FPCore

(FPCore (x y z t a b c i j) :precision binary64 (* a (* b i)))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	return a * (b * i);
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    code = a * (b * i)
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	return a * (b * i);
}

Python

def code(x, y, z, t, a, b, c, i, j):
	return a * (b * i)

Julia

function code(x, y, z, t, a, b, c, i, j)
	return Float64(a * Float64(b * i))
end

MATLAB

function tmp = code(x, y, z, t, a, b, c, i, j)
	tmp = a * (b * i);
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := N[(a * N[(b * i), $MachinePrecision]), $MachinePrecision]

Derivation

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

Alternative 24: 22.6% accurate, 5.8× speedup

Math

\[\begin{array}{l} \\ b \cdot \left(a \cdot i\right) \end{array} \]

FPCore

(FPCore (x y z t a b c i j) :precision binary64 (* b (* a i)))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	return b * (a * i);
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    code = b * (a * i)
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	return b * (a * i);
}

Python

def code(x, y, z, t, a, b, c, i, j):
	return b * (a * i)

Julia

function code(x, y, z, t, a, b, c, i, j)
	return Float64(b * Float64(a * i))
end

MATLAB

function tmp = code(x, y, z, t, a, b, c, i, j)
	tmp = b * (a * i);
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := N[(b * N[(a * i), $MachinePrecision]), $MachinePrecision]

Derivation

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

Developer target: 69.3% accurate, 0.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \left(x \cdot \left(y \cdot z - t \cdot a\right) - b \cdot \left(c \cdot z - i \cdot a\right)\right) + \frac{j \cdot \left({\left(c \cdot t\right)}^{2} - {\left(i \cdot y\right)}^{2}\right)}{c \cdot t + i \cdot y}\\ t_2 := x \cdot \left(z \cdot y - a \cdot t\right) - \left(b \cdot \left(z \cdot c - a \cdot i\right) - \left(c \cdot t - y \cdot i\right) \cdot j\right)\\ \mathbf{if}\;t < -8.120978919195912 \cdot 10^{-33}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t < -4.712553818218485 \cdot 10^{-169}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t < -7.633533346031584 \cdot 10^{-308}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t < 1.0535888557455487 \cdot 10^{-139}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1
         (+
          (- (* x (- (* y z) (* t a))) (* b (- (* c z) (* i a))))
          (/
           (* j (- (pow (* c t) 2.0) (pow (* i y) 2.0)))
           (+ (* c t) (* i y)))))
        (t_2
         (-
          (* x (- (* z y) (* a t)))
          (- (* b (- (* z c) (* a i))) (* (- (* c t) (* y i)) j)))))
   (if (< t -8.120978919195912e-33)
     t_2
     (if (< t -4.712553818218485e-169)
       t_1
       (if (< t -7.633533346031584e-308)
         t_2
         (if (< t 1.0535888557455487e-139) t_1 t_2))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = ((x * ((y * z) - (t * a))) - (b * ((c * z) - (i * a)))) + ((j * (pow((c * t), 2.0) - pow((i * y), 2.0))) / ((c * t) + (i * y)));
	double t_2 = (x * ((z * y) - (a * t))) - ((b * ((z * c) - (a * i))) - (((c * t) - (y * i)) * j));
	double tmp;
	if (t < -8.120978919195912e-33) {
		tmp = t_2;
	} else if (t < -4.712553818218485e-169) {
		tmp = t_1;
	} else if (t < -7.633533346031584e-308) {
		tmp = t_2;
	} else if (t < 1.0535888557455487e-139) {
		tmp = t_1;
	} else {
		tmp = t_2;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = ((x * ((y * z) - (t * a))) - (b * ((c * z) - (i * a)))) + ((j * (((c * t) ** 2.0d0) - ((i * y) ** 2.0d0))) / ((c * t) + (i * y)))
    t_2 = (x * ((z * y) - (a * t))) - ((b * ((z * c) - (a * i))) - (((c * t) - (y * i)) * j))
    if (t < (-8.120978919195912d-33)) then
        tmp = t_2
    else if (t < (-4.712553818218485d-169)) then
        tmp = t_1
    else if (t < (-7.633533346031584d-308)) then
        tmp = t_2
    else if (t < 1.0535888557455487d-139) then
        tmp = t_1
    else
        tmp = t_2
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = ((x * ((y * z) - (t * a))) - (b * ((c * z) - (i * a)))) + ((j * (Math.pow((c * t), 2.0) - Math.pow((i * y), 2.0))) / ((c * t) + (i * y)));
	double t_2 = (x * ((z * y) - (a * t))) - ((b * ((z * c) - (a * i))) - (((c * t) - (y * i)) * j));
	double tmp;
	if (t < -8.120978919195912e-33) {
		tmp = t_2;
	} else if (t < -4.712553818218485e-169) {
		tmp = t_1;
	} else if (t < -7.633533346031584e-308) {
		tmp = t_2;
	} else if (t < 1.0535888557455487e-139) {
		tmp = t_1;
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = ((x * ((y * z) - (t * a))) - (b * ((c * z) - (i * a)))) + ((j * (math.pow((c * t), 2.0) - math.pow((i * y), 2.0))) / ((c * t) + (i * y)))
	t_2 = (x * ((z * y) - (a * t))) - ((b * ((z * c) - (a * i))) - (((c * t) - (y * i)) * j))
	tmp = 0
	if t < -8.120978919195912e-33:
		tmp = t_2
	elif t < -4.712553818218485e-169:
		tmp = t_1
	elif t < -7.633533346031584e-308:
		tmp = t_2
	elif t < 1.0535888557455487e-139:
		tmp = t_1
	else:
		tmp = t_2
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(Float64(Float64(x * Float64(Float64(y * z) - Float64(t * a))) - Float64(b * Float64(Float64(c * z) - Float64(i * a)))) + Float64(Float64(j * Float64((Float64(c * t) ^ 2.0) - (Float64(i * y) ^ 2.0))) / Float64(Float64(c * t) + Float64(i * y))))
	t_2 = Float64(Float64(x * Float64(Float64(z * y) - Float64(a * t))) - Float64(Float64(b * Float64(Float64(z * c) - Float64(a * i))) - Float64(Float64(Float64(c * t) - Float64(y * i)) * j)))
	tmp = 0.0
	if (t < -8.120978919195912e-33)
		tmp = t_2;
	elseif (t < -4.712553818218485e-169)
		tmp = t_1;
	elseif (t < -7.633533346031584e-308)
		tmp = t_2;
	elseif (t < 1.0535888557455487e-139)
		tmp = t_1;
	else
		tmp = t_2;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = ((x * ((y * z) - (t * a))) - (b * ((c * z) - (i * a)))) + ((j * (((c * t) ^ 2.0) - ((i * y) ^ 2.0))) / ((c * t) + (i * y)));
	t_2 = (x * ((z * y) - (a * t))) - ((b * ((z * c) - (a * i))) - (((c * t) - (y * i)) * j));
	tmp = 0.0;
	if (t < -8.120978919195912e-33)
		tmp = t_2;
	elseif (t < -4.712553818218485e-169)
		tmp = t_1;
	elseif (t < -7.633533346031584e-308)
		tmp = t_2;
	elseif (t < 1.0535888557455487e-139)
		tmp = t_1;
	else
		tmp = t_2;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(N[(N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(b * N[(N[(c * z), $MachinePrecision] - N[(i * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(j * N[(N[Power[N[(c * t), $MachinePrecision], 2.0], $MachinePrecision] - N[Power[N[(i * y), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(N[(c * t), $MachinePrecision] + N[(i * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(x * N[(N[(z * y), $MachinePrecision] - N[(a * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(b * N[(N[(z * c), $MachinePrecision] - N[(a * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(N[(c * t), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision] * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[Less[t, -8.120978919195912e-33], t$95$2, If[Less[t, -4.712553818218485e-169], t$95$1, If[Less[t, -7.633533346031584e-308], t$95$2, If[Less[t, 1.0535888557455487e-139], t$95$1, t$95$2]]]]]]

Reproduce

herbie shell --seed 2023350 
(FPCore (x y z t a b c i j)
  :name "Linear.Matrix:det33 from linear-1.19.1.3"
  :precision binary64

  :herbie-target
  (if (< t -8.120978919195912e-33) (- (* x (- (* z y) (* a t))) (- (* b (- (* z c) (* a i))) (* (- (* c t) (* y i)) j))) (if (< t -4.712553818218485e-169) (+ (- (* x (- (* y z) (* t a))) (* b (- (* c z) (* i a)))) (/ (* j (- (pow (* c t) 2.0) (pow (* i y) 2.0))) (+ (* c t) (* i y)))) (if (< t -7.633533346031584e-308) (- (* x (- (* z y) (* a t))) (- (* b (- (* z c) (* a i))) (* (- (* c t) (* y i)) j))) (if (< t 1.0535888557455487e-139) (+ (- (* x (- (* y z) (* t a))) (* b (- (* c z) (* i a)))) (/ (* j (- (pow (* c t) 2.0) (pow (* i y) 2.0))) (+ (* c t) (* i y)))) (- (* x (- (* z y) (* a t))) (- (* b (- (* z c) (* a i))) (* (- (* c t) (* y i)) j)))))))

  (+ (- (* x (- (* y z) (* t a))) (* b (- (* c z) (* i a)))) (* j (- (* c t) (* i y)))))