Linear.Matrix:det33 from linear-1.19.1.3

Percentage Accurate: 72.9% → 81.3%

Time: 27.3s

Alternatives: 21

Speedup: 0.5×

• 58.7% 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: 72.9% 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: 81.3% accurate, 0.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(a \cdot i - z \cdot c\right)\\ t_2 := t \cdot c - y \cdot i\\ \mathbf{if}\;j \cdot t_2 - \left(b \cdot \left(z \cdot c - a \cdot i\right) + x \cdot \left(t \cdot a - y \cdot z\right)\right) \leq \infty:\\ \;\;\;\;\mathsf{fma}\left(j, t_2, x \cdot \mathsf{fma}\left(y, z, t \cdot \left(-a\right)\right) + t_1\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* b (- (* a i) (* z c)))) (t_2 (- (* t c) (* y i))))
   (if (<=
        (- (* j t_2) (+ (* b (- (* z c) (* a i))) (* x (- (* t a) (* y z)))))
        INFINITY)
     (fma j t_2 (+ (* x (fma y z (* t (- a)))) t_1))
     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 = b * ((a * i) - (z * c));
	double t_2 = (t * c) - (y * i);
	double tmp;
	if (((j * t_2) - ((b * ((z * c) - (a * i))) + (x * ((t * a) - (y * z))))) <= ((double) INFINITY)) {
		tmp = fma(j, t_2, ((x * fma(y, z, (t * -a))) + t_1));
	} else {
		tmp = t_1;
	}
	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(Float64(t * c) - Float64(y * i))
	tmp = 0.0
	if (Float64(Float64(j * t_2) - Float64(Float64(b * Float64(Float64(z * c) - Float64(a * i))) + Float64(x * Float64(Float64(t * a) - Float64(y * z))))) <= Inf)
		tmp = fma(j, t_2, Float64(Float64(x * fma(y, z, Float64(t * Float64(-a)))) + t_1));
	else
		tmp = t_1;
	end
	return 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[(N[(t * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[(N[(j * t$95$2), $MachinePrecision] - N[(N[(b * N[(N[(z * c), $MachinePrecision] - N[(a * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(x * N[(N[(t * a), $MachinePrecision] - N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], Infinity], N[(j * t$95$2 + N[(N[(x * N[(y * z + N[(t * (-a)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision]), $MachinePrecision], t$95$1]]]

Derivation

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

Alternative 2: 81.3% accurate, 0.5× speedup

Math

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

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1
         (-
          (* j (- (* t c) (* y i)))
          (+ (* b (- (* z c) (* a i))) (* x (- (* t a) (* y z)))))))
   (if (<= t_1 INFINITY) 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 = (j * ((t * c) - (y * i))) - ((b * ((z * c) - (a * i))) + (x * ((t * a) - (y * z))));
	double tmp;
	if (t_1 <= ((double) INFINITY)) {
		tmp = t_1;
	} else {
		tmp = b * ((a * i) - (z * c));
	}
	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 = (j * ((t * c) - (y * i))) - ((b * ((z * c) - (a * i))) + (x * ((t * a) - (y * z))));
	double tmp;
	if (t_1 <= Double.POSITIVE_INFINITY) {
		tmp = t_1;
	} else {
		tmp = b * ((a * i) - (z * c));
	}
	return tmp;
}

Python

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

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(Float64(j * Float64(Float64(t * c) - Float64(y * i))) - Float64(Float64(b * Float64(Float64(z * c) - Float64(a * i))) + Float64(x * Float64(Float64(t * a) - Float64(y * z)))))
	tmp = 0.0
	if (t_1 <= Inf)
		tmp = t_1;
	else
		tmp = 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 = (j * ((t * c) - (y * i))) - ((b * ((z * c) - (a * i))) + (x * ((t * a) - (y * z))));
	tmp = 0.0;
	if (t_1 <= Inf)
		tmp = t_1;
	else
		tmp = 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[(N[(j * N[(N[(t * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(b * N[(N[(z * c), $MachinePrecision] - N[(a * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(x * N[(N[(t * a), $MachinePrecision] - N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$1, Infinity], t$95$1, N[(b * N[(N[(a * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]

Derivation

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

Alternative 3: 58.2% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(a \cdot i - z \cdot c\right)\\ t_2 := t_1 - a \cdot \left(x \cdot t\right)\\ t_3 := y \cdot \left(x \cdot z - i \cdot j\right)\\ \mathbf{if}\;y \leq -2.7 \cdot 10^{+53}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;y \leq -1.45 \cdot 10^{-137}:\\ \;\;\;\;x \cdot \left(y \cdot z\right) + t_1\\ \mathbf{elif}\;y \leq 3.4 \cdot 10^{-171}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y \leq 1.32 \cdot 10^{-110}:\\ \;\;\;\;t \cdot \left(c \cdot j - x \cdot a\right)\\ \mathbf{elif}\;y \leq 2.45 \cdot 10^{-9}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y \leq 2.7 \cdot 10^{+85} \lor \neg \left(y \leq 4 \cdot 10^{+152}\right):\\ \;\;\;\;t_3\\ \mathbf{else}:\\ \;\;\;\;t \cdot \left(c \cdot j\right) - b \cdot \left(z \cdot c - a \cdot i\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* b (- (* a i) (* z c))))
        (t_2 (- t_1 (* a (* x t))))
        (t_3 (* y (- (* x z) (* i j)))))
   (if (<= y -2.7e+53)
     t_3
     (if (<= y -1.45e-137)
       (+ (* x (* y z)) t_1)
       (if (<= y 3.4e-171)
         t_2
         (if (<= y 1.32e-110)
           (* t (- (* c j) (* x a)))
           (if (<= y 2.45e-9)
             t_2
             (if (or (<= y 2.7e+85) (not (<= y 4e+152)))
               t_3
               (- (* t (* c j)) (* b (- (* z c) (* a i))))))))))))

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 = t_1 - (a * (x * t));
	double t_3 = y * ((x * z) - (i * j));
	double tmp;
	if (y <= -2.7e+53) {
		tmp = t_3;
	} else if (y <= -1.45e-137) {
		tmp = (x * (y * z)) + t_1;
	} else if (y <= 3.4e-171) {
		tmp = t_2;
	} else if (y <= 1.32e-110) {
		tmp = t * ((c * j) - (x * a));
	} else if (y <= 2.45e-9) {
		tmp = t_2;
	} else if ((y <= 2.7e+85) || !(y <= 4e+152)) {
		tmp = t_3;
	} else {
		tmp = (t * (c * j)) - (b * ((z * c) - (a * 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) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: tmp
    t_1 = b * ((a * i) - (z * c))
    t_2 = t_1 - (a * (x * t))
    t_3 = y * ((x * z) - (i * j))
    if (y <= (-2.7d+53)) then
        tmp = t_3
    else if (y <= (-1.45d-137)) then
        tmp = (x * (y * z)) + t_1
    else if (y <= 3.4d-171) then
        tmp = t_2
    else if (y <= 1.32d-110) then
        tmp = t * ((c * j) - (x * a))
    else if (y <= 2.45d-9) then
        tmp = t_2
    else if ((y <= 2.7d+85) .or. (.not. (y <= 4d+152))) then
        tmp = t_3
    else
        tmp = (t * (c * j)) - (b * ((z * c) - (a * 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 t_1 = b * ((a * i) - (z * c));
	double t_2 = t_1 - (a * (x * t));
	double t_3 = y * ((x * z) - (i * j));
	double tmp;
	if (y <= -2.7e+53) {
		tmp = t_3;
	} else if (y <= -1.45e-137) {
		tmp = (x * (y * z)) + t_1;
	} else if (y <= 3.4e-171) {
		tmp = t_2;
	} else if (y <= 1.32e-110) {
		tmp = t * ((c * j) - (x * a));
	} else if (y <= 2.45e-9) {
		tmp = t_2;
	} else if ((y <= 2.7e+85) || !(y <= 4e+152)) {
		tmp = t_3;
	} else {
		tmp = (t * (c * j)) - (b * ((z * c) - (a * i)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = b * ((a * i) - (z * c))
	t_2 = t_1 - (a * (x * t))
	t_3 = y * ((x * z) - (i * j))
	tmp = 0
	if y <= -2.7e+53:
		tmp = t_3
	elif y <= -1.45e-137:
		tmp = (x * (y * z)) + t_1
	elif y <= 3.4e-171:
		tmp = t_2
	elif y <= 1.32e-110:
		tmp = t * ((c * j) - (x * a))
	elif y <= 2.45e-9:
		tmp = t_2
	elif (y <= 2.7e+85) or not (y <= 4e+152):
		tmp = t_3
	else:
		tmp = (t * (c * j)) - (b * ((z * c) - (a * i)))
	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(t_1 - Float64(a * Float64(x * t)))
	t_3 = Float64(y * Float64(Float64(x * z) - Float64(i * j)))
	tmp = 0.0
	if (y <= -2.7e+53)
		tmp = t_3;
	elseif (y <= -1.45e-137)
		tmp = Float64(Float64(x * Float64(y * z)) + t_1);
	elseif (y <= 3.4e-171)
		tmp = t_2;
	elseif (y <= 1.32e-110)
		tmp = Float64(t * Float64(Float64(c * j) - Float64(x * a)));
	elseif (y <= 2.45e-9)
		tmp = t_2;
	elseif ((y <= 2.7e+85) || !(y <= 4e+152))
		tmp = t_3;
	else
		tmp = Float64(Float64(t * Float64(c * j)) - Float64(b * Float64(Float64(z * c) - Float64(a * i))));
	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 = t_1 - (a * (x * t));
	t_3 = y * ((x * z) - (i * j));
	tmp = 0.0;
	if (y <= -2.7e+53)
		tmp = t_3;
	elseif (y <= -1.45e-137)
		tmp = (x * (y * z)) + t_1;
	elseif (y <= 3.4e-171)
		tmp = t_2;
	elseif (y <= 1.32e-110)
		tmp = t * ((c * j) - (x * a));
	elseif (y <= 2.45e-9)
		tmp = t_2;
	elseif ((y <= 2.7e+85) || ~((y <= 4e+152)))
		tmp = t_3;
	else
		tmp = (t * (c * j)) - (b * ((z * c) - (a * i)));
	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[(t$95$1 - N[(a * N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(y * N[(N[(x * z), $MachinePrecision] - N[(i * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y, -2.7e+53], t$95$3, If[LessEqual[y, -1.45e-137], N[(N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision], If[LessEqual[y, 3.4e-171], t$95$2, If[LessEqual[y, 1.32e-110], N[(t * N[(N[(c * j), $MachinePrecision] - N[(x * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 2.45e-9], t$95$2, If[Or[LessEqual[y, 2.7e+85], N[Not[LessEqual[y, 4e+152]], $MachinePrecision]], t$95$3, N[(N[(t * N[(c * j), $MachinePrecision]), $MachinePrecision] - N[(b * N[(N[(z * c), $MachinePrecision] - N[(a * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]

Derivation

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

Alternative 4: 59.1% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(a \cdot i - z \cdot c\right)\\ t_2 := t_1 - a \cdot \left(x \cdot t\right)\\ t_3 := y \cdot \left(x \cdot z - i \cdot j\right)\\ \mathbf{if}\;y \leq -2.7 \cdot 10^{+53}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;y \leq -1.45 \cdot 10^{-137}:\\ \;\;\;\;x \cdot \left(y \cdot z\right) + t_1\\ \mathbf{elif}\;y \leq 3 \cdot 10^{-224}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y \leq 10^{-108}:\\ \;\;\;\;a \cdot \left(b \cdot i\right) + t \cdot \left(c \cdot j - x \cdot a\right)\\ \mathbf{elif}\;y \leq 6 \cdot 10^{-10}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y \leq 2.95 \cdot 10^{+85} \lor \neg \left(y \leq 1.35 \cdot 10^{+153}\right):\\ \;\;\;\;t_3\\ \mathbf{else}:\\ \;\;\;\;t \cdot \left(c \cdot j\right) - b \cdot \left(z \cdot c - a \cdot i\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* b (- (* a i) (* z c))))
        (t_2 (- t_1 (* a (* x t))))
        (t_3 (* y (- (* x z) (* i j)))))
   (if (<= y -2.7e+53)
     t_3
     (if (<= y -1.45e-137)
       (+ (* x (* y z)) t_1)
       (if (<= y 3e-224)
         t_2
         (if (<= y 1e-108)
           (+ (* a (* b i)) (* t (- (* c j) (* x a))))
           (if (<= y 6e-10)
             t_2
             (if (or (<= y 2.95e+85) (not (<= y 1.35e+153)))
               t_3
               (- (* t (* c j)) (* b (- (* z c) (* a i))))))))))))

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 = t_1 - (a * (x * t));
	double t_3 = y * ((x * z) - (i * j));
	double tmp;
	if (y <= -2.7e+53) {
		tmp = t_3;
	} else if (y <= -1.45e-137) {
		tmp = (x * (y * z)) + t_1;
	} else if (y <= 3e-224) {
		tmp = t_2;
	} else if (y <= 1e-108) {
		tmp = (a * (b * i)) + (t * ((c * j) - (x * a)));
	} else if (y <= 6e-10) {
		tmp = t_2;
	} else if ((y <= 2.95e+85) || !(y <= 1.35e+153)) {
		tmp = t_3;
	} else {
		tmp = (t * (c * j)) - (b * ((z * c) - (a * 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) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: tmp
    t_1 = b * ((a * i) - (z * c))
    t_2 = t_1 - (a * (x * t))
    t_3 = y * ((x * z) - (i * j))
    if (y <= (-2.7d+53)) then
        tmp = t_3
    else if (y <= (-1.45d-137)) then
        tmp = (x * (y * z)) + t_1
    else if (y <= 3d-224) then
        tmp = t_2
    else if (y <= 1d-108) then
        tmp = (a * (b * i)) + (t * ((c * j) - (x * a)))
    else if (y <= 6d-10) then
        tmp = t_2
    else if ((y <= 2.95d+85) .or. (.not. (y <= 1.35d+153))) then
        tmp = t_3
    else
        tmp = (t * (c * j)) - (b * ((z * c) - (a * 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 t_1 = b * ((a * i) - (z * c));
	double t_2 = t_1 - (a * (x * t));
	double t_3 = y * ((x * z) - (i * j));
	double tmp;
	if (y <= -2.7e+53) {
		tmp = t_3;
	} else if (y <= -1.45e-137) {
		tmp = (x * (y * z)) + t_1;
	} else if (y <= 3e-224) {
		tmp = t_2;
	} else if (y <= 1e-108) {
		tmp = (a * (b * i)) + (t * ((c * j) - (x * a)));
	} else if (y <= 6e-10) {
		tmp = t_2;
	} else if ((y <= 2.95e+85) || !(y <= 1.35e+153)) {
		tmp = t_3;
	} else {
		tmp = (t * (c * j)) - (b * ((z * c) - (a * i)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = b * ((a * i) - (z * c))
	t_2 = t_1 - (a * (x * t))
	t_3 = y * ((x * z) - (i * j))
	tmp = 0
	if y <= -2.7e+53:
		tmp = t_3
	elif y <= -1.45e-137:
		tmp = (x * (y * z)) + t_1
	elif y <= 3e-224:
		tmp = t_2
	elif y <= 1e-108:
		tmp = (a * (b * i)) + (t * ((c * j) - (x * a)))
	elif y <= 6e-10:
		tmp = t_2
	elif (y <= 2.95e+85) or not (y <= 1.35e+153):
		tmp = t_3
	else:
		tmp = (t * (c * j)) - (b * ((z * c) - (a * i)))
	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(t_1 - Float64(a * Float64(x * t)))
	t_3 = Float64(y * Float64(Float64(x * z) - Float64(i * j)))
	tmp = 0.0
	if (y <= -2.7e+53)
		tmp = t_3;
	elseif (y <= -1.45e-137)
		tmp = Float64(Float64(x * Float64(y * z)) + t_1);
	elseif (y <= 3e-224)
		tmp = t_2;
	elseif (y <= 1e-108)
		tmp = Float64(Float64(a * Float64(b * i)) + Float64(t * Float64(Float64(c * j) - Float64(x * a))));
	elseif (y <= 6e-10)
		tmp = t_2;
	elseif ((y <= 2.95e+85) || !(y <= 1.35e+153))
		tmp = t_3;
	else
		tmp = Float64(Float64(t * Float64(c * j)) - Float64(b * Float64(Float64(z * c) - Float64(a * i))));
	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 = t_1 - (a * (x * t));
	t_3 = y * ((x * z) - (i * j));
	tmp = 0.0;
	if (y <= -2.7e+53)
		tmp = t_3;
	elseif (y <= -1.45e-137)
		tmp = (x * (y * z)) + t_1;
	elseif (y <= 3e-224)
		tmp = t_2;
	elseif (y <= 1e-108)
		tmp = (a * (b * i)) + (t * ((c * j) - (x * a)));
	elseif (y <= 6e-10)
		tmp = t_2;
	elseif ((y <= 2.95e+85) || ~((y <= 1.35e+153)))
		tmp = t_3;
	else
		tmp = (t * (c * j)) - (b * ((z * c) - (a * i)));
	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[(t$95$1 - N[(a * N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(y * N[(N[(x * z), $MachinePrecision] - N[(i * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y, -2.7e+53], t$95$3, If[LessEqual[y, -1.45e-137], N[(N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision], If[LessEqual[y, 3e-224], t$95$2, If[LessEqual[y, 1e-108], N[(N[(a * N[(b * i), $MachinePrecision]), $MachinePrecision] + N[(t * N[(N[(c * j), $MachinePrecision] - N[(x * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 6e-10], t$95$2, If[Or[LessEqual[y, 2.95e+85], N[Not[LessEqual[y, 1.35e+153]], $MachinePrecision]], t$95$3, N[(N[(t * N[(c * j), $MachinePrecision]), $MachinePrecision] - N[(b * N[(N[(z * c), $MachinePrecision] - N[(a * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]

Derivation

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

Alternative 5: 65.0% accurate, 1.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y \leq -10200 \lor \neg \left(y \leq 1.65 \cdot 10^{-9} \lor \neg \left(y \leq 5.8 \cdot 10^{+86}\right) \land y \leq 4 \cdot 10^{+152}\right):\\ \;\;\;\;y \cdot \left(x \cdot z - i \cdot j\right)\\ \mathbf{else}:\\ \;\;\;\;t \cdot \left(c \cdot j - x \cdot a\right) - b \cdot \left(z \cdot c - a \cdot i\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (or (<= y -10200.0)
         (not (or (<= y 1.65e-9) (and (not (<= y 5.8e+86)) (<= y 4e+152)))))
   (* y (- (* x z) (* i j)))
   (- (* t (- (* c j) (* x a))) (* b (- (* z c) (* a 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 ((y <= -10200.0) || !((y <= 1.65e-9) || (!(y <= 5.8e+86) && (y <= 4e+152)))) {
		tmp = y * ((x * z) - (i * j));
	} else {
		tmp = (t * ((c * j) - (x * a))) - (b * ((z * c) - (a * 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 ((y <= (-10200.0d0)) .or. (.not. (y <= 1.65d-9) .or. (.not. (y <= 5.8d+86)) .and. (y <= 4d+152))) then
        tmp = y * ((x * z) - (i * j))
    else
        tmp = (t * ((c * j) - (x * a))) - (b * ((z * c) - (a * 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 ((y <= -10200.0) || !((y <= 1.65e-9) || (!(y <= 5.8e+86) && (y <= 4e+152)))) {
		tmp = y * ((x * z) - (i * j));
	} else {
		tmp = (t * ((c * j) - (x * a))) - (b * ((z * c) - (a * i)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if (y <= -10200.0) or not ((y <= 1.65e-9) or (not (y <= 5.8e+86) and (y <= 4e+152))):
		tmp = y * ((x * z) - (i * j))
	else:
		tmp = (t * ((c * j) - (x * a))) - (b * ((z * c) - (a * i)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if ((y <= -10200.0) || !((y <= 1.65e-9) || (!(y <= 5.8e+86) && (y <= 4e+152))))
		tmp = Float64(y * Float64(Float64(x * z) - Float64(i * j)));
	else
		tmp = Float64(Float64(t * Float64(Float64(c * j) - Float64(x * a))) - Float64(b * Float64(Float64(z * c) - Float64(a * i))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0;
	if ((y <= -10200.0) || ~(((y <= 1.65e-9) || (~((y <= 5.8e+86)) && (y <= 4e+152)))))
		tmp = y * ((x * z) - (i * j));
	else
		tmp = (t * ((c * j) - (x * a))) - (b * ((z * c) - (a * i)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[Or[LessEqual[y, -10200.0], N[Not[Or[LessEqual[y, 1.65e-9], And[N[Not[LessEqual[y, 5.8e+86]], $MachinePrecision], LessEqual[y, 4e+152]]]], $MachinePrecision]], N[(y * N[(N[(x * z), $MachinePrecision] - N[(i * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(t * N[(N[(c * j), $MachinePrecision] - N[(x * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(b * N[(N[(z * c), $MachinePrecision] - N[(a * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

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

Alternative 6: 58.0% accurate, 1.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(a \cdot i - z \cdot c\right)\\ t_2 := t_1 - a \cdot \left(x \cdot t\right)\\ t_3 := y \cdot \left(x \cdot z - i \cdot j\right)\\ \mathbf{if}\;y \leq -2.7 \cdot 10^{+53}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;y \leq -4.1 \cdot 10^{-138}:\\ \;\;\;\;x \cdot \left(y \cdot z\right) + t_1\\ \mathbf{elif}\;y \leq 2.5 \cdot 10^{-168}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y \leq 1.35 \cdot 10^{-108}:\\ \;\;\;\;t \cdot \left(c \cdot j - x \cdot a\right)\\ \mathbf{elif}\;y \leq 9 \cdot 10^{-11}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y \leq 4.8 \cdot 10^{+109} \lor \neg \left(y \leq 2.26 \cdot 10^{+154}\right):\\ \;\;\;\;t_3\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(t \cdot j - z \cdot b\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* b (- (* a i) (* z c))))
        (t_2 (- t_1 (* a (* x t))))
        (t_3 (* y (- (* x z) (* i j)))))
   (if (<= y -2.7e+53)
     t_3
     (if (<= y -4.1e-138)
       (+ (* x (* y z)) t_1)
       (if (<= y 2.5e-168)
         t_2
         (if (<= y 1.35e-108)
           (* t (- (* c j) (* x a)))
           (if (<= y 9e-11)
             t_2
             (if (or (<= y 4.8e+109) (not (<= y 2.26e+154)))
               t_3
               (* c (- (* t j) (* z 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 = b * ((a * i) - (z * c));
	double t_2 = t_1 - (a * (x * t));
	double t_3 = y * ((x * z) - (i * j));
	double tmp;
	if (y <= -2.7e+53) {
		tmp = t_3;
	} else if (y <= -4.1e-138) {
		tmp = (x * (y * z)) + t_1;
	} else if (y <= 2.5e-168) {
		tmp = t_2;
	} else if (y <= 1.35e-108) {
		tmp = t * ((c * j) - (x * a));
	} else if (y <= 9e-11) {
		tmp = t_2;
	} else if ((y <= 4.8e+109) || !(y <= 2.26e+154)) {
		tmp = t_3;
	} else {
		tmp = c * ((t * j) - (z * 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) :: t_2
    real(8) :: t_3
    real(8) :: tmp
    t_1 = b * ((a * i) - (z * c))
    t_2 = t_1 - (a * (x * t))
    t_3 = y * ((x * z) - (i * j))
    if (y <= (-2.7d+53)) then
        tmp = t_3
    else if (y <= (-4.1d-138)) then
        tmp = (x * (y * z)) + t_1
    else if (y <= 2.5d-168) then
        tmp = t_2
    else if (y <= 1.35d-108) then
        tmp = t * ((c * j) - (x * a))
    else if (y <= 9d-11) then
        tmp = t_2
    else if ((y <= 4.8d+109) .or. (.not. (y <= 2.26d+154))) then
        tmp = t_3
    else
        tmp = c * ((t * j) - (z * 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 = b * ((a * i) - (z * c));
	double t_2 = t_1 - (a * (x * t));
	double t_3 = y * ((x * z) - (i * j));
	double tmp;
	if (y <= -2.7e+53) {
		tmp = t_3;
	} else if (y <= -4.1e-138) {
		tmp = (x * (y * z)) + t_1;
	} else if (y <= 2.5e-168) {
		tmp = t_2;
	} else if (y <= 1.35e-108) {
		tmp = t * ((c * j) - (x * a));
	} else if (y <= 9e-11) {
		tmp = t_2;
	} else if ((y <= 4.8e+109) || !(y <= 2.26e+154)) {
		tmp = t_3;
	} else {
		tmp = c * ((t * j) - (z * b));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = b * ((a * i) - (z * c))
	t_2 = t_1 - (a * (x * t))
	t_3 = y * ((x * z) - (i * j))
	tmp = 0
	if y <= -2.7e+53:
		tmp = t_3
	elif y <= -4.1e-138:
		tmp = (x * (y * z)) + t_1
	elif y <= 2.5e-168:
		tmp = t_2
	elif y <= 1.35e-108:
		tmp = t * ((c * j) - (x * a))
	elif y <= 9e-11:
		tmp = t_2
	elif (y <= 4.8e+109) or not (y <= 2.26e+154):
		tmp = t_3
	else:
		tmp = c * ((t * j) - (z * b))
	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(t_1 - Float64(a * Float64(x * t)))
	t_3 = Float64(y * Float64(Float64(x * z) - Float64(i * j)))
	tmp = 0.0
	if (y <= -2.7e+53)
		tmp = t_3;
	elseif (y <= -4.1e-138)
		tmp = Float64(Float64(x * Float64(y * z)) + t_1);
	elseif (y <= 2.5e-168)
		tmp = t_2;
	elseif (y <= 1.35e-108)
		tmp = Float64(t * Float64(Float64(c * j) - Float64(x * a)));
	elseif (y <= 9e-11)
		tmp = t_2;
	elseif ((y <= 4.8e+109) || !(y <= 2.26e+154))
		tmp = t_3;
	else
		tmp = Float64(c * Float64(Float64(t * j) - Float64(z * b)));
	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 = t_1 - (a * (x * t));
	t_3 = y * ((x * z) - (i * j));
	tmp = 0.0;
	if (y <= -2.7e+53)
		tmp = t_3;
	elseif (y <= -4.1e-138)
		tmp = (x * (y * z)) + t_1;
	elseif (y <= 2.5e-168)
		tmp = t_2;
	elseif (y <= 1.35e-108)
		tmp = t * ((c * j) - (x * a));
	elseif (y <= 9e-11)
		tmp = t_2;
	elseif ((y <= 4.8e+109) || ~((y <= 2.26e+154)))
		tmp = t_3;
	else
		tmp = c * ((t * j) - (z * b));
	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[(t$95$1 - N[(a * N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(y * N[(N[(x * z), $MachinePrecision] - N[(i * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y, -2.7e+53], t$95$3, If[LessEqual[y, -4.1e-138], N[(N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision], If[LessEqual[y, 2.5e-168], t$95$2, If[LessEqual[y, 1.35e-108], N[(t * N[(N[(c * j), $MachinePrecision] - N[(x * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 9e-11], t$95$2, If[Or[LessEqual[y, 4.8e+109], N[Not[LessEqual[y, 2.26e+154]], $MachinePrecision]], t$95$3, N[(c * N[(N[(t * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]

Derivation

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

Alternative 7: 67.2% accurate, 1.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;j \leq -5.3 \cdot 10^{+104}:\\ \;\;\;\;j \cdot \left(t \cdot c - y \cdot i\right)\\ \mathbf{elif}\;j \leq 1.5 \cdot 10^{+72}:\\ \;\;\;\;x \cdot \left(y \cdot z - t \cdot a\right) - b \cdot \left(z \cdot c - a \cdot i\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(b \cdot i\right) - \left(a \cdot \left(x \cdot t\right) + j \cdot \left(y \cdot i - t \cdot c\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (<= j -5.3e+104)
   (* j (- (* t c) (* y i)))
   (if (<= j 1.5e+72)
     (- (* x (- (* y z) (* t a))) (* b (- (* z c) (* a i))))
     (- (* a (* b i)) (+ (* a (* x t)) (* j (- (* y i) (* 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 (j <= -5.3e+104) {
		tmp = j * ((t * c) - (y * i));
	} else if (j <= 1.5e+72) {
		tmp = (x * ((y * z) - (t * a))) - (b * ((z * c) - (a * i)));
	} else {
		tmp = (a * (b * i)) - ((a * (x * t)) + (j * ((y * i) - (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 (j <= (-5.3d+104)) then
        tmp = j * ((t * c) - (y * i))
    else if (j <= 1.5d+72) then
        tmp = (x * ((y * z) - (t * a))) - (b * ((z * c) - (a * i)))
    else
        tmp = (a * (b * i)) - ((a * (x * t)) + (j * ((y * i) - (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 (j <= -5.3e+104) {
		tmp = j * ((t * c) - (y * i));
	} else if (j <= 1.5e+72) {
		tmp = (x * ((y * z) - (t * a))) - (b * ((z * c) - (a * i)));
	} else {
		tmp = (a * (b * i)) - ((a * (x * t)) + (j * ((y * i) - (t * c))));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if j <= -5.3e+104:
		tmp = j * ((t * c) - (y * i))
	elif j <= 1.5e+72:
		tmp = (x * ((y * z) - (t * a))) - (b * ((z * c) - (a * i)))
	else:
		tmp = (a * (b * i)) - ((a * (x * t)) + (j * ((y * i) - (t * c))))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if (j <= -5.3e+104)
		tmp = Float64(j * Float64(Float64(t * c) - Float64(y * i)));
	elseif (j <= 1.5e+72)
		tmp = Float64(Float64(x * Float64(Float64(y * z) - Float64(t * a))) - Float64(b * Float64(Float64(z * c) - Float64(a * i))));
	else
		tmp = Float64(Float64(a * Float64(b * i)) - Float64(Float64(a * Float64(x * t)) + Float64(j * Float64(Float64(y * i) - 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 (j <= -5.3e+104)
		tmp = j * ((t * c) - (y * i));
	elseif (j <= 1.5e+72)
		tmp = (x * ((y * z) - (t * a))) - (b * ((z * c) - (a * i)));
	else
		tmp = (a * (b * i)) - ((a * (x * t)) + (j * ((y * i) - (t * c))));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[LessEqual[j, -5.3e+104], N[(j * N[(N[(t * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 1.5e+72], N[(N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(b * N[(N[(z * c), $MachinePrecision] - N[(a * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(a * N[(b * i), $MachinePrecision]), $MachinePrecision] - N[(N[(a * N[(x * t), $MachinePrecision]), $MachinePrecision] + N[(j * N[(N[(y * i), $MachinePrecision] - N[(t * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]

Derivation

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

Alternative 8: 55.1% accurate, 1.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(y \cdot z\right) + b \cdot \left(a \cdot i - z \cdot c\right)\\ \mathbf{if}\;j \leq -5.8 \cdot 10^{+104}:\\ \;\;\;\;j \cdot \left(t \cdot c - y \cdot i\right)\\ \mathbf{elif}\;j \leq -1.3 \cdot 10^{-242}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;j \leq -9.6 \cdot 10^{-296}:\\ \;\;\;\;a \cdot \left(b \cdot i - x \cdot t\right)\\ \mathbf{elif}\;j \leq 1.8 \cdot 10^{+87}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;j \leq 8.5 \cdot 10^{+249}:\\ \;\;\;\;y \cdot \left(x \cdot z - i \cdot j\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(t \cdot j - z \cdot b\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (+ (* x (* y z)) (* b (- (* a i) (* z c))))))
   (if (<= j -5.8e+104)
     (* j (- (* t c) (* y i)))
     (if (<= j -1.3e-242)
       t_1
       (if (<= j -9.6e-296)
         (* a (- (* b i) (* x t)))
         (if (<= j 1.8e+87)
           t_1
           (if (<= j 8.5e+249)
             (* y (- (* x z) (* i j)))
             (* c (- (* t j) (* z 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 = (x * (y * z)) + (b * ((a * i) - (z * c)));
	double tmp;
	if (j <= -5.8e+104) {
		tmp = j * ((t * c) - (y * i));
	} else if (j <= -1.3e-242) {
		tmp = t_1;
	} else if (j <= -9.6e-296) {
		tmp = a * ((b * i) - (x * t));
	} else if (j <= 1.8e+87) {
		tmp = t_1;
	} else if (j <= 8.5e+249) {
		tmp = y * ((x * z) - (i * j));
	} else {
		tmp = c * ((t * j) - (z * 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 = (x * (y * z)) + (b * ((a * i) - (z * c)))
    if (j <= (-5.8d+104)) then
        tmp = j * ((t * c) - (y * i))
    else if (j <= (-1.3d-242)) then
        tmp = t_1
    else if (j <= (-9.6d-296)) then
        tmp = a * ((b * i) - (x * t))
    else if (j <= 1.8d+87) then
        tmp = t_1
    else if (j <= 8.5d+249) then
        tmp = y * ((x * z) - (i * j))
    else
        tmp = c * ((t * j) - (z * 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 = (x * (y * z)) + (b * ((a * i) - (z * c)));
	double tmp;
	if (j <= -5.8e+104) {
		tmp = j * ((t * c) - (y * i));
	} else if (j <= -1.3e-242) {
		tmp = t_1;
	} else if (j <= -9.6e-296) {
		tmp = a * ((b * i) - (x * t));
	} else if (j <= 1.8e+87) {
		tmp = t_1;
	} else if (j <= 8.5e+249) {
		tmp = y * ((x * z) - (i * j));
	} else {
		tmp = c * ((t * j) - (z * b));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = (x * (y * z)) + (b * ((a * i) - (z * c)))
	tmp = 0
	if j <= -5.8e+104:
		tmp = j * ((t * c) - (y * i))
	elif j <= -1.3e-242:
		tmp = t_1
	elif j <= -9.6e-296:
		tmp = a * ((b * i) - (x * t))
	elif j <= 1.8e+87:
		tmp = t_1
	elif j <= 8.5e+249:
		tmp = y * ((x * z) - (i * j))
	else:
		tmp = c * ((t * j) - (z * b))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(Float64(x * Float64(y * z)) + Float64(b * Float64(Float64(a * i) - Float64(z * c))))
	tmp = 0.0
	if (j <= -5.8e+104)
		tmp = Float64(j * Float64(Float64(t * c) - Float64(y * i)));
	elseif (j <= -1.3e-242)
		tmp = t_1;
	elseif (j <= -9.6e-296)
		tmp = Float64(a * Float64(Float64(b * i) - Float64(x * t)));
	elseif (j <= 1.8e+87)
		tmp = t_1;
	elseif (j <= 8.5e+249)
		tmp = Float64(y * Float64(Float64(x * z) - Float64(i * j)));
	else
		tmp = Float64(c * Float64(Float64(t * j) - Float64(z * b)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = (x * (y * z)) + (b * ((a * i) - (z * c)));
	tmp = 0.0;
	if (j <= -5.8e+104)
		tmp = j * ((t * c) - (y * i));
	elseif (j <= -1.3e-242)
		tmp = t_1;
	elseif (j <= -9.6e-296)
		tmp = a * ((b * i) - (x * t));
	elseif (j <= 1.8e+87)
		tmp = t_1;
	elseif (j <= 8.5e+249)
		tmp = y * ((x * z) - (i * j));
	else
		tmp = c * ((t * j) - (z * b));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision] + N[(b * N[(N[(a * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -5.8e+104], N[(j * N[(N[(t * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -1.3e-242], t$95$1, If[LessEqual[j, -9.6e-296], N[(a * N[(N[(b * i), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 1.8e+87], t$95$1, If[LessEqual[j, 8.5e+249], N[(y * N[(N[(x * z), $MachinePrecision] - N[(i * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(c * N[(N[(t * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]

Derivation

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

Alternative 9: 63.7% accurate, 1.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;j \leq -5.3 \cdot 10^{+103}:\\ \;\;\;\;j \cdot \left(t \cdot c - y \cdot i\right)\\ \mathbf{elif}\;j \leq 1.3 \cdot 10^{+89}:\\ \;\;\;\;x \cdot \left(y \cdot z - t \cdot a\right) - b \cdot \left(z \cdot c - a \cdot i\right)\\ \mathbf{elif}\;j \leq 8.1 \cdot 10^{+248}:\\ \;\;\;\;y \cdot \left(x \cdot z - i \cdot j\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(t \cdot j - z \cdot b\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (<= j -5.3e+103)
   (* j (- (* t c) (* y i)))
   (if (<= j 1.3e+89)
     (- (* x (- (* y z) (* t a))) (* b (- (* z c) (* a i))))
     (if (<= j 8.1e+248)
       (* y (- (* x z) (* i j)))
       (* c (- (* t j) (* z 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 (j <= -5.3e+103) {
		tmp = j * ((t * c) - (y * i));
	} else if (j <= 1.3e+89) {
		tmp = (x * ((y * z) - (t * a))) - (b * ((z * c) - (a * i)));
	} else if (j <= 8.1e+248) {
		tmp = y * ((x * z) - (i * j));
	} else {
		tmp = c * ((t * j) - (z * 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 (j <= (-5.3d+103)) then
        tmp = j * ((t * c) - (y * i))
    else if (j <= 1.3d+89) then
        tmp = (x * ((y * z) - (t * a))) - (b * ((z * c) - (a * i)))
    else if (j <= 8.1d+248) then
        tmp = y * ((x * z) - (i * j))
    else
        tmp = c * ((t * j) - (z * 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 (j <= -5.3e+103) {
		tmp = j * ((t * c) - (y * i));
	} else if (j <= 1.3e+89) {
		tmp = (x * ((y * z) - (t * a))) - (b * ((z * c) - (a * i)));
	} else if (j <= 8.1e+248) {
		tmp = y * ((x * z) - (i * j));
	} else {
		tmp = c * ((t * j) - (z * b));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if j <= -5.3e+103:
		tmp = j * ((t * c) - (y * i))
	elif j <= 1.3e+89:
		tmp = (x * ((y * z) - (t * a))) - (b * ((z * c) - (a * i)))
	elif j <= 8.1e+248:
		tmp = y * ((x * z) - (i * j))
	else:
		tmp = c * ((t * j) - (z * b))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if (j <= -5.3e+103)
		tmp = Float64(j * Float64(Float64(t * c) - Float64(y * i)));
	elseif (j <= 1.3e+89)
		tmp = Float64(Float64(x * Float64(Float64(y * z) - Float64(t * a))) - Float64(b * Float64(Float64(z * c) - Float64(a * i))));
	elseif (j <= 8.1e+248)
		tmp = Float64(y * Float64(Float64(x * z) - Float64(i * j)));
	else
		tmp = Float64(c * Float64(Float64(t * j) - Float64(z * b)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0;
	if (j <= -5.3e+103)
		tmp = j * ((t * c) - (y * i));
	elseif (j <= 1.3e+89)
		tmp = (x * ((y * z) - (t * a))) - (b * ((z * c) - (a * i)));
	elseif (j <= 8.1e+248)
		tmp = y * ((x * z) - (i * j));
	else
		tmp = c * ((t * j) - (z * b));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[LessEqual[j, -5.3e+103], N[(j * N[(N[(t * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 1.3e+89], N[(N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(b * N[(N[(z * c), $MachinePrecision] - N[(a * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 8.1e+248], N[(y * N[(N[(x * z), $MachinePrecision] - N[(i * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(c * N[(N[(t * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]

Derivation

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

Alternative 10: 51.1% accurate, 1.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(y \cdot z - t \cdot a\right)\\ t_2 := b \cdot \left(a \cdot i - z \cdot c\right)\\ \mathbf{if}\;b \leq -5.6 \cdot 10^{-14}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;b \leq -6.2 \cdot 10^{-229}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;b \leq -5.8 \cdot 10^{-237}:\\ \;\;\;\;c \cdot \left(t \cdot j - z \cdot b\right)\\ \mathbf{elif}\;b \leq 2.4 \cdot 10^{-151}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;b \leq 1.85 \cdot 10^{+40}:\\ \;\;\;\;a \cdot \left(b \cdot i - x \cdot t\right)\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* x (- (* y z) (* t a)))) (t_2 (* b (- (* a i) (* z c)))))
   (if (<= b -5.6e-14)
     t_2
     (if (<= b -6.2e-229)
       t_1
       (if (<= b -5.8e-237)
         (* c (- (* t j) (* z b)))
         (if (<= b 2.4e-151)
           t_1
           (if (<= b 1.85e+40) (* a (- (* b i) (* x t))) 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));
	double t_2 = b * ((a * i) - (z * c));
	double tmp;
	if (b <= -5.6e-14) {
		tmp = t_2;
	} else if (b <= -6.2e-229) {
		tmp = t_1;
	} else if (b <= -5.8e-237) {
		tmp = c * ((t * j) - (z * b));
	} else if (b <= 2.4e-151) {
		tmp = t_1;
	} else if (b <= 1.85e+40) {
		tmp = a * ((b * i) - (x * t));
	} 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))
    t_2 = b * ((a * i) - (z * c))
    if (b <= (-5.6d-14)) then
        tmp = t_2
    else if (b <= (-6.2d-229)) then
        tmp = t_1
    else if (b <= (-5.8d-237)) then
        tmp = c * ((t * j) - (z * b))
    else if (b <= 2.4d-151) then
        tmp = t_1
    else if (b <= 1.85d+40) then
        tmp = a * ((b * i) - (x * t))
    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));
	double t_2 = b * ((a * i) - (z * c));
	double tmp;
	if (b <= -5.6e-14) {
		tmp = t_2;
	} else if (b <= -6.2e-229) {
		tmp = t_1;
	} else if (b <= -5.8e-237) {
		tmp = c * ((t * j) - (z * b));
	} else if (b <= 2.4e-151) {
		tmp = t_1;
	} else if (b <= 1.85e+40) {
		tmp = a * ((b * i) - (x * t));
	} 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))
	t_2 = b * ((a * i) - (z * c))
	tmp = 0
	if b <= -5.6e-14:
		tmp = t_2
	elif b <= -6.2e-229:
		tmp = t_1
	elif b <= -5.8e-237:
		tmp = c * ((t * j) - (z * b))
	elif b <= 2.4e-151:
		tmp = t_1
	elif b <= 1.85e+40:
		tmp = a * ((b * i) - (x * t))
	else:
		tmp = t_2
	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)))
	t_2 = Float64(b * Float64(Float64(a * i) - Float64(z * c)))
	tmp = 0.0
	if (b <= -5.6e-14)
		tmp = t_2;
	elseif (b <= -6.2e-229)
		tmp = t_1;
	elseif (b <= -5.8e-237)
		tmp = Float64(c * Float64(Float64(t * j) - Float64(z * b)));
	elseif (b <= 2.4e-151)
		tmp = t_1;
	elseif (b <= 1.85e+40)
		tmp = Float64(a * Float64(Float64(b * i) - Float64(x * t)));
	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));
	t_2 = b * ((a * i) - (z * c));
	tmp = 0.0;
	if (b <= -5.6e-14)
		tmp = t_2;
	elseif (b <= -6.2e-229)
		tmp = t_1;
	elseif (b <= -5.8e-237)
		tmp = c * ((t * j) - (z * b));
	elseif (b <= 2.4e-151)
		tmp = t_1;
	elseif (b <= 1.85e+40)
		tmp = a * ((b * i) - (x * t));
	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[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(b * N[(N[(a * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[b, -5.6e-14], t$95$2, If[LessEqual[b, -6.2e-229], t$95$1, If[LessEqual[b, -5.8e-237], N[(c * N[(N[(t * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[b, 2.4e-151], t$95$1, If[LessEqual[b, 1.85e+40], N[(a * N[(N[(b * i), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$2]]]]]]]

Derivation

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

Alternative 11: 45.7% accurate, 1.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot \left(b \cdot i - x \cdot t\right)\\ t_2 := b \cdot \left(a \cdot i - z \cdot c\right)\\ \mathbf{if}\;b \leq -2.05 \cdot 10^{-28}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;b \leq -6 \cdot 10^{-229}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;b \leq 7 \cdot 10^{-272}:\\ \;\;\;\;c \cdot \left(t \cdot j\right)\\ \mathbf{elif}\;b \leq 1.2 \cdot 10^{+46}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* a (- (* b i) (* x t)))) (t_2 (* b (- (* a i) (* z c)))))
   (if (<= b -2.05e-28)
     t_2
     (if (<= b -6e-229)
       t_1
       (if (<= b 7e-272) (* c (* t j)) (if (<= b 1.2e+46) 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 = a * ((b * i) - (x * t));
	double t_2 = b * ((a * i) - (z * c));
	double tmp;
	if (b <= -2.05e-28) {
		tmp = t_2;
	} else if (b <= -6e-229) {
		tmp = t_1;
	} else if (b <= 7e-272) {
		tmp = c * (t * j);
	} else if (b <= 1.2e+46) {
		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 = a * ((b * i) - (x * t))
    t_2 = b * ((a * i) - (z * c))
    if (b <= (-2.05d-28)) then
        tmp = t_2
    else if (b <= (-6d-229)) then
        tmp = t_1
    else if (b <= 7d-272) then
        tmp = c * (t * j)
    else if (b <= 1.2d+46) 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 = a * ((b * i) - (x * t));
	double t_2 = b * ((a * i) - (z * c));
	double tmp;
	if (b <= -2.05e-28) {
		tmp = t_2;
	} else if (b <= -6e-229) {
		tmp = t_1;
	} else if (b <= 7e-272) {
		tmp = c * (t * j);
	} else if (b <= 1.2e+46) {
		tmp = t_1;
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = a * ((b * i) - (x * t))
	t_2 = b * ((a * i) - (z * c))
	tmp = 0
	if b <= -2.05e-28:
		tmp = t_2
	elif b <= -6e-229:
		tmp = t_1
	elif b <= 7e-272:
		tmp = c * (t * j)
	elif b <= 1.2e+46:
		tmp = t_1
	else:
		tmp = t_2
	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)))
	t_2 = Float64(b * Float64(Float64(a * i) - Float64(z * c)))
	tmp = 0.0
	if (b <= -2.05e-28)
		tmp = t_2;
	elseif (b <= -6e-229)
		tmp = t_1;
	elseif (b <= 7e-272)
		tmp = Float64(c * Float64(t * j));
	elseif (b <= 1.2e+46)
		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 = a * ((b * i) - (x * t));
	t_2 = b * ((a * i) - (z * c));
	tmp = 0.0;
	if (b <= -2.05e-28)
		tmp = t_2;
	elseif (b <= -6e-229)
		tmp = t_1;
	elseif (b <= 7e-272)
		tmp = c * (t * j);
	elseif (b <= 1.2e+46)
		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[(a * N[(N[(b * i), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(b * N[(N[(a * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[b, -2.05e-28], t$95$2, If[LessEqual[b, -6e-229], t$95$1, If[LessEqual[b, 7e-272], N[(c * N[(t * j), $MachinePrecision]), $MachinePrecision], If[LessEqual[b, 1.2e+46], t$95$1, t$95$2]]]]]]

Derivation

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

Alternative 12: 28.5% accurate, 1.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := -i \cdot \left(y \cdot j\right)\\ \mathbf{if}\;b \leq -5.5 \cdot 10^{+103}:\\ \;\;\;\;z \cdot \left(b \cdot \left(-c\right)\right)\\ \mathbf{elif}\;b \leq -3.6 \cdot 10^{-108}:\\ \;\;\;\;z \cdot \left(x \cdot y\right)\\ \mathbf{elif}\;b \leq -3.9 \cdot 10^{-219}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;b \leq 2.1 \cdot 10^{-272}:\\ \;\;\;\;c \cdot \left(t \cdot j\right)\\ \mathbf{elif}\;b \leq 2 \cdot 10^{-124}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(a \cdot i\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (- (* i (* y j)))))
   (if (<= b -5.5e+103)
     (* z (* b (- c)))
     (if (<= b -3.6e-108)
       (* z (* x y))
       (if (<= b -3.9e-219)
         t_1
         (if (<= b 2.1e-272)
           (* c (* t j))
           (if (<= b 2e-124) t_1 (* b (* a i)))))))))

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 * (y * j));
	double tmp;
	if (b <= -5.5e+103) {
		tmp = z * (b * -c);
	} else if (b <= -3.6e-108) {
		tmp = z * (x * y);
	} else if (b <= -3.9e-219) {
		tmp = t_1;
	} else if (b <= 2.1e-272) {
		tmp = c * (t * j);
	} else if (b <= 2e-124) {
		tmp = t_1;
	} else {
		tmp = b * (a * 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) :: t_1
    real(8) :: tmp
    t_1 = -(i * (y * j))
    if (b <= (-5.5d+103)) then
        tmp = z * (b * -c)
    else if (b <= (-3.6d-108)) then
        tmp = z * (x * y)
    else if (b <= (-3.9d-219)) then
        tmp = t_1
    else if (b <= 2.1d-272) then
        tmp = c * (t * j)
    else if (b <= 2d-124) then
        tmp = t_1
    else
        tmp = b * (a * 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 t_1 = -(i * (y * j));
	double tmp;
	if (b <= -5.5e+103) {
		tmp = z * (b * -c);
	} else if (b <= -3.6e-108) {
		tmp = z * (x * y);
	} else if (b <= -3.9e-219) {
		tmp = t_1;
	} else if (b <= 2.1e-272) {
		tmp = c * (t * j);
	} else if (b <= 2e-124) {
		tmp = t_1;
	} else {
		tmp = b * (a * i);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = -(i * (y * j))
	tmp = 0
	if b <= -5.5e+103:
		tmp = z * (b * -c)
	elif b <= -3.6e-108:
		tmp = z * (x * y)
	elif b <= -3.9e-219:
		tmp = t_1
	elif b <= 2.1e-272:
		tmp = c * (t * j)
	elif b <= 2e-124:
		tmp = t_1
	else:
		tmp = b * (a * i)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(-Float64(i * Float64(y * j)))
	tmp = 0.0
	if (b <= -5.5e+103)
		tmp = Float64(z * Float64(b * Float64(-c)));
	elseif (b <= -3.6e-108)
		tmp = Float64(z * Float64(x * y));
	elseif (b <= -3.9e-219)
		tmp = t_1;
	elseif (b <= 2.1e-272)
		tmp = Float64(c * Float64(t * j));
	elseif (b <= 2e-124)
		tmp = t_1;
	else
		tmp = Float64(b * Float64(a * i));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = -(i * (y * j));
	tmp = 0.0;
	if (b <= -5.5e+103)
		tmp = z * (b * -c);
	elseif (b <= -3.6e-108)
		tmp = z * (x * y);
	elseif (b <= -3.9e-219)
		tmp = t_1;
	elseif (b <= 2.1e-272)
		tmp = c * (t * j);
	elseif (b <= 2e-124)
		tmp = t_1;
	else
		tmp = b * (a * i);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = (-N[(i * N[(y * j), $MachinePrecision]), $MachinePrecision])}, If[LessEqual[b, -5.5e+103], N[(z * N[(b * (-c)), $MachinePrecision]), $MachinePrecision], If[LessEqual[b, -3.6e-108], N[(z * N[(x * y), $MachinePrecision]), $MachinePrecision], If[LessEqual[b, -3.9e-219], t$95$1, If[LessEqual[b, 2.1e-272], N[(c * N[(t * j), $MachinePrecision]), $MachinePrecision], If[LessEqual[b, 2e-124], t$95$1, N[(b * N[(a * i), $MachinePrecision]), $MachinePrecision]]]]]]]

Derivation

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

Alternative 13: 51.5% accurate, 1.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := c \cdot \left(t \cdot j - z \cdot b\right)\\ \mathbf{if}\;c \leq -1.58 \cdot 10^{+44}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;c \leq 2.7 \cdot 10^{-5}:\\ \;\;\;\;a \cdot \left(b \cdot i - x \cdot t\right)\\ \mathbf{elif}\;c \leq 3.7 \cdot 10^{+83}:\\ \;\;\;\;j \cdot \left(t \cdot c - y \cdot i\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* c (- (* t j) (* z b)))))
   (if (<= c -1.58e+44)
     t_1
     (if (<= c 2.7e-5)
       (* a (- (* b i) (* x t)))
       (if (<= c 3.7e+83) (* 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 = c * ((t * j) - (z * b));
	double tmp;
	if (c <= -1.58e+44) {
		tmp = t_1;
	} else if (c <= 2.7e-5) {
		tmp = a * ((b * i) - (x * t));
	} else if (c <= 3.7e+83) {
		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 = c * ((t * j) - (z * b))
    if (c <= (-1.58d+44)) then
        tmp = t_1
    else if (c <= 2.7d-5) then
        tmp = a * ((b * i) - (x * t))
    else if (c <= 3.7d+83) 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 = c * ((t * j) - (z * b));
	double tmp;
	if (c <= -1.58e+44) {
		tmp = t_1;
	} else if (c <= 2.7e-5) {
		tmp = a * ((b * i) - (x * t));
	} else if (c <= 3.7e+83) {
		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 = c * ((t * j) - (z * b))
	tmp = 0
	if c <= -1.58e+44:
		tmp = t_1
	elif c <= 2.7e-5:
		tmp = a * ((b * i) - (x * t))
	elif c <= 3.7e+83:
		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(c * Float64(Float64(t * j) - Float64(z * b)))
	tmp = 0.0
	if (c <= -1.58e+44)
		tmp = t_1;
	elseif (c <= 2.7e-5)
		tmp = Float64(a * Float64(Float64(b * i) - Float64(x * t)));
	elseif (c <= 3.7e+83)
		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 = c * ((t * j) - (z * b));
	tmp = 0.0;
	if (c <= -1.58e+44)
		tmp = t_1;
	elseif (c <= 2.7e-5)
		tmp = a * ((b * i) - (x * t));
	elseif (c <= 3.7e+83)
		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[(c * N[(N[(t * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[c, -1.58e+44], t$95$1, If[LessEqual[c, 2.7e-5], N[(a * N[(N[(b * i), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 3.7e+83], 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 14: 51.4% accurate, 1.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := c \cdot \left(t \cdot j - z \cdot b\right)\\ \mathbf{if}\;c \leq -5 \cdot 10^{+44}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;c \leq 1.55 \cdot 10^{-282}:\\ \;\;\;\;a \cdot \left(b \cdot i - x \cdot t\right)\\ \mathbf{elif}\;c \leq 1.45 \cdot 10^{+83}:\\ \;\;\;\;y \cdot \left(x \cdot z - i \cdot j\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* c (- (* t j) (* z b)))))
   (if (<= c -5e+44)
     t_1
     (if (<= c 1.55e-282)
       (* a (- (* b i) (* x t)))
       (if (<= c 1.45e+83) (* y (- (* x z) (* i j))) 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 = c * ((t * j) - (z * b));
	double tmp;
	if (c <= -5e+44) {
		tmp = t_1;
	} else if (c <= 1.55e-282) {
		tmp = a * ((b * i) - (x * t));
	} else if (c <= 1.45e+83) {
		tmp = y * ((x * z) - (i * j));
	} 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 = c * ((t * j) - (z * b))
    if (c <= (-5d+44)) then
        tmp = t_1
    else if (c <= 1.55d-282) then
        tmp = a * ((b * i) - (x * t))
    else if (c <= 1.45d+83) then
        tmp = y * ((x * z) - (i * j))
    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 = c * ((t * j) - (z * b));
	double tmp;
	if (c <= -5e+44) {
		tmp = t_1;
	} else if (c <= 1.55e-282) {
		tmp = a * ((b * i) - (x * t));
	} else if (c <= 1.45e+83) {
		tmp = y * ((x * z) - (i * j));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = c * ((t * j) - (z * b))
	tmp = 0
	if c <= -5e+44:
		tmp = t_1
	elif c <= 1.55e-282:
		tmp = a * ((b * i) - (x * t))
	elif c <= 1.45e+83:
		tmp = y * ((x * z) - (i * j))
	else:
		tmp = t_1
	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)))
	tmp = 0.0
	if (c <= -5e+44)
		tmp = t_1;
	elseif (c <= 1.55e-282)
		tmp = Float64(a * Float64(Float64(b * i) - Float64(x * t)));
	elseif (c <= 1.45e+83)
		tmp = Float64(y * Float64(Float64(x * z) - Float64(i * j)));
	else
		tmp = t_1;
	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));
	tmp = 0.0;
	if (c <= -5e+44)
		tmp = t_1;
	elseif (c <= 1.55e-282)
		tmp = a * ((b * i) - (x * t));
	elseif (c <= 1.45e+83)
		tmp = y * ((x * z) - (i * j));
	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[(c * N[(N[(t * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[c, -5e+44], t$95$1, If[LessEqual[c, 1.55e-282], N[(a * N[(N[(b * i), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 1.45e+83], N[(y * N[(N[(x * z), $MachinePrecision] - N[(i * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]

Derivation

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

Alternative 15: 29.0% accurate, 2.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;b \leq -4.5 \cdot 10^{+109}:\\ \;\;\;\;z \cdot \left(b \cdot \left(-c\right)\right)\\ \mathbf{elif}\;b \leq -4.1 \cdot 10^{-32}:\\ \;\;\;\;z \cdot \left(x \cdot y\right)\\ \mathbf{elif}\;b \leq -9.2 \cdot 10^{-263}:\\ \;\;\;\;\left(-a\right) \cdot \left(x \cdot t\right)\\ \mathbf{elif}\;b \leq 7.2 \cdot 10^{-124}:\\ \;\;\;\;-i \cdot \left(y \cdot j\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(a \cdot i\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (<= b -4.5e+109)
   (* z (* b (- c)))
   (if (<= b -4.1e-32)
     (* z (* x y))
     (if (<= b -9.2e-263)
       (* (- a) (* x t))
       (if (<= b 7.2e-124) (- (* i (* y j))) (* b (* a 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 (b <= -4.5e+109) {
		tmp = z * (b * -c);
	} else if (b <= -4.1e-32) {
		tmp = z * (x * y);
	} else if (b <= -9.2e-263) {
		tmp = -a * (x * t);
	} else if (b <= 7.2e-124) {
		tmp = -(i * (y * j));
	} else {
		tmp = b * (a * 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 (b <= (-4.5d+109)) then
        tmp = z * (b * -c)
    else if (b <= (-4.1d-32)) then
        tmp = z * (x * y)
    else if (b <= (-9.2d-263)) then
        tmp = -a * (x * t)
    else if (b <= 7.2d-124) then
        tmp = -(i * (y * j))
    else
        tmp = b * (a * 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 (b <= -4.5e+109) {
		tmp = z * (b * -c);
	} else if (b <= -4.1e-32) {
		tmp = z * (x * y);
	} else if (b <= -9.2e-263) {
		tmp = -a * (x * t);
	} else if (b <= 7.2e-124) {
		tmp = -(i * (y * j));
	} else {
		tmp = b * (a * i);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if b <= -4.5e+109:
		tmp = z * (b * -c)
	elif b <= -4.1e-32:
		tmp = z * (x * y)
	elif b <= -9.2e-263:
		tmp = -a * (x * t)
	elif b <= 7.2e-124:
		tmp = -(i * (y * j))
	else:
		tmp = b * (a * i)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if (b <= -4.5e+109)
		tmp = Float64(z * Float64(b * Float64(-c)));
	elseif (b <= -4.1e-32)
		tmp = Float64(z * Float64(x * y));
	elseif (b <= -9.2e-263)
		tmp = Float64(Float64(-a) * Float64(x * t));
	elseif (b <= 7.2e-124)
		tmp = Float64(-Float64(i * Float64(y * j)));
	else
		tmp = Float64(b * Float64(a * i));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0;
	if (b <= -4.5e+109)
		tmp = z * (b * -c);
	elseif (b <= -4.1e-32)
		tmp = z * (x * y);
	elseif (b <= -9.2e-263)
		tmp = -a * (x * t);
	elseif (b <= 7.2e-124)
		tmp = -(i * (y * j));
	else
		tmp = b * (a * i);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[LessEqual[b, -4.5e+109], N[(z * N[(b * (-c)), $MachinePrecision]), $MachinePrecision], If[LessEqual[b, -4.1e-32], N[(z * N[(x * y), $MachinePrecision]), $MachinePrecision], If[LessEqual[b, -9.2e-263], N[((-a) * N[(x * t), $MachinePrecision]), $MachinePrecision], If[LessEqual[b, 7.2e-124], (-N[(i * N[(y * j), $MachinePrecision]), $MachinePrecision]), N[(b * N[(a * i), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

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

Alternative 16: 29.7% accurate, 2.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;x \leq -2 \cdot 10^{+25} \lor \neg \left(x \leq 8 \cdot 10^{-152} \lor \neg \left(x \leq 6.5 \cdot 10^{-72}\right) \land x \leq 1.35 \cdot 10^{+25}\right):\\ \;\;\;\;x \cdot \left(y \cdot z\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(b \cdot i\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (or (<= x -2e+25)
         (not (or (<= x 8e-152) (and (not (<= x 6.5e-72)) (<= x 1.35e+25)))))
   (* x (* y z))
   (* 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 ((x <= -2e+25) || !((x <= 8e-152) || (!(x <= 6.5e-72) && (x <= 1.35e+25)))) {
		tmp = x * (y * z);
	} 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 ((x <= (-2d+25)) .or. (.not. (x <= 8d-152) .or. (.not. (x <= 6.5d-72)) .and. (x <= 1.35d+25))) then
        tmp = x * (y * z)
    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 ((x <= -2e+25) || !((x <= 8e-152) || (!(x <= 6.5e-72) && (x <= 1.35e+25)))) {
		tmp = x * (y * z);
	} else {
		tmp = a * (b * i);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if (x <= -2e+25) or not ((x <= 8e-152) or (not (x <= 6.5e-72) and (x <= 1.35e+25))):
		tmp = x * (y * z)
	else:
		tmp = a * (b * i)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if ((x <= -2e+25) || !((x <= 8e-152) || (!(x <= 6.5e-72) && (x <= 1.35e+25))))
		tmp = Float64(x * Float64(y * z));
	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 ((x <= -2e+25) || ~(((x <= 8e-152) || (~((x <= 6.5e-72)) && (x <= 1.35e+25)))))
		tmp = x * (y * z);
	else
		tmp = a * (b * i);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[Or[LessEqual[x, -2e+25], N[Not[Or[LessEqual[x, 8e-152], And[N[Not[LessEqual[x, 6.5e-72]], $MachinePrecision], LessEqual[x, 1.35e+25]]]], $MachinePrecision]], N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision], N[(a * N[(b * i), $MachinePrecision]), $MachinePrecision]]

Derivation

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

Alternative 17: 28.1% accurate, 2.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;b \leq -5.5 \cdot 10^{+107}:\\ \;\;\;\;z \cdot \left(b \cdot \left(-c\right)\right)\\ \mathbf{elif}\;b \leq -7.2 \cdot 10^{-229}:\\ \;\;\;\;z \cdot \left(x \cdot y\right)\\ \mathbf{elif}\;b \leq 4.2 \cdot 10^{-222}:\\ \;\;\;\;c \cdot \left(t \cdot j\right)\\ \mathbf{elif}\;b \leq 5 \cdot 10^{-146}:\\ \;\;\;\;x \cdot \left(y \cdot z\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(a \cdot i\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (<= b -5.5e+107)
   (* z (* b (- c)))
   (if (<= b -7.2e-229)
     (* z (* x y))
     (if (<= b 4.2e-222)
       (* c (* t j))
       (if (<= b 5e-146) (* x (* y z)) (* b (* a 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 (b <= -5.5e+107) {
		tmp = z * (b * -c);
	} else if (b <= -7.2e-229) {
		tmp = z * (x * y);
	} else if (b <= 4.2e-222) {
		tmp = c * (t * j);
	} else if (b <= 5e-146) {
		tmp = x * (y * z);
	} else {
		tmp = b * (a * 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 (b <= (-5.5d+107)) then
        tmp = z * (b * -c)
    else if (b <= (-7.2d-229)) then
        tmp = z * (x * y)
    else if (b <= 4.2d-222) then
        tmp = c * (t * j)
    else if (b <= 5d-146) then
        tmp = x * (y * z)
    else
        tmp = b * (a * 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 (b <= -5.5e+107) {
		tmp = z * (b * -c);
	} else if (b <= -7.2e-229) {
		tmp = z * (x * y);
	} else if (b <= 4.2e-222) {
		tmp = c * (t * j);
	} else if (b <= 5e-146) {
		tmp = x * (y * z);
	} else {
		tmp = b * (a * i);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if b <= -5.5e+107:
		tmp = z * (b * -c)
	elif b <= -7.2e-229:
		tmp = z * (x * y)
	elif b <= 4.2e-222:
		tmp = c * (t * j)
	elif b <= 5e-146:
		tmp = x * (y * z)
	else:
		tmp = b * (a * i)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if (b <= -5.5e+107)
		tmp = Float64(z * Float64(b * Float64(-c)));
	elseif (b <= -7.2e-229)
		tmp = Float64(z * Float64(x * y));
	elseif (b <= 4.2e-222)
		tmp = Float64(c * Float64(t * j));
	elseif (b <= 5e-146)
		tmp = Float64(x * Float64(y * z));
	else
		tmp = Float64(b * Float64(a * i));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0;
	if (b <= -5.5e+107)
		tmp = z * (b * -c);
	elseif (b <= -7.2e-229)
		tmp = z * (x * y);
	elseif (b <= 4.2e-222)
		tmp = c * (t * j);
	elseif (b <= 5e-146)
		tmp = x * (y * z);
	else
		tmp = b * (a * i);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[LessEqual[b, -5.5e+107], N[(z * N[(b * (-c)), $MachinePrecision]), $MachinePrecision], If[LessEqual[b, -7.2e-229], N[(z * N[(x * y), $MachinePrecision]), $MachinePrecision], If[LessEqual[b, 4.2e-222], N[(c * N[(t * j), $MachinePrecision]), $MachinePrecision], If[LessEqual[b, 5e-146], N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision], N[(b * N[(a * i), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

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

Alternative 18: 51.4% accurate, 2.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;c \leq -9 \cdot 10^{+44} \lor \neg \left(c \leq 2.5 \cdot 10^{+64}\right):\\ \;\;\;\;c \cdot \left(t \cdot j - z \cdot b\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(b \cdot i - x \cdot t\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (or (<= c -9e+44) (not (<= c 2.5e+64)))
   (* c (- (* t j) (* z b)))
   (* 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 tmp;
	if ((c <= -9e+44) || !(c <= 2.5e+64)) {
		tmp = c * ((t * j) - (z * b));
	} 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) :: tmp
    if ((c <= (-9d+44)) .or. (.not. (c <= 2.5d+64))) then
        tmp = c * ((t * j) - (z * b))
    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 tmp;
	if ((c <= -9e+44) || !(c <= 2.5e+64)) {
		tmp = c * ((t * j) - (z * b));
	} else {
		tmp = a * ((b * i) - (x * t));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if (c <= -9e+44) or not (c <= 2.5e+64):
		tmp = c * ((t * j) - (z * b))
	else:
		tmp = a * ((b * i) - (x * t))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if ((c <= -9e+44) || !(c <= 2.5e+64))
		tmp = Float64(c * Float64(Float64(t * j) - Float64(z * b)));
	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)
	tmp = 0.0;
	if ((c <= -9e+44) || ~((c <= 2.5e+64)))
		tmp = c * ((t * j) - (z * b));
	else
		tmp = a * ((b * i) - (x * t));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[Or[LessEqual[c, -9e+44], N[Not[LessEqual[c, 2.5e+64]], $MachinePrecision]], N[(c * N[(N[(t * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(a * N[(N[(b * i), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

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

Alternative 19: 40.7% accurate, 2.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -2.4 \cdot 10^{+202}:\\ \;\;\;\;x \cdot \left(y \cdot z\right)\\ \mathbf{elif}\;z \leq 2.6 \cdot 10^{-9}:\\ \;\;\;\;a \cdot \left(b \cdot i - x \cdot t\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(z \cdot \left(-c\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (<= z -2.4e+202)
   (* x (* y z))
   (if (<= z 2.6e-9) (* a (- (* b i) (* x t))) (* b (* z (- 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 (z <= -2.4e+202) {
		tmp = x * (y * z);
	} else if (z <= 2.6e-9) {
		tmp = a * ((b * i) - (x * t));
	} else {
		tmp = b * (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) :: tmp
    if (z <= (-2.4d+202)) then
        tmp = x * (y * z)
    else if (z <= 2.6d-9) then
        tmp = a * ((b * i) - (x * t))
    else
        tmp = b * (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 tmp;
	if (z <= -2.4e+202) {
		tmp = x * (y * z);
	} else if (z <= 2.6e-9) {
		tmp = a * ((b * i) - (x * t));
	} else {
		tmp = b * (z * -c);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if z <= -2.4e+202:
		tmp = x * (y * z)
	elif z <= 2.6e-9:
		tmp = a * ((b * i) - (x * t))
	else:
		tmp = b * (z * -c)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if (z <= -2.4e+202)
		tmp = Float64(x * Float64(y * z));
	elseif (z <= 2.6e-9)
		tmp = Float64(a * Float64(Float64(b * i) - Float64(x * t)));
	else
		tmp = Float64(b * Float64(z * Float64(-c)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0;
	if (z <= -2.4e+202)
		tmp = x * (y * z);
	elseif (z <= 2.6e-9)
		tmp = a * ((b * i) - (x * t));
	else
		tmp = b * (z * -c);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[LessEqual[z, -2.4e+202], N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 2.6e-9], N[(a * N[(N[(b * i), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(z * (-c)), $MachinePrecision]), $MachinePrecision]]]

Derivation

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

Alternative 20: 29.7% accurate, 3.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;b \leq -6.5 \cdot 10^{+38}:\\ \;\;\;\;a \cdot \left(b \cdot i\right)\\ \mathbf{elif}\;b \leq 3.1 \cdot 10^{-121}:\\ \;\;\;\;c \cdot \left(t \cdot j\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(a \cdot i\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (<= b -6.5e+38)
   (* a (* b i))
   (if (<= b 3.1e-121) (* c (* t j)) (* b (* a 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 (b <= -6.5e+38) {
		tmp = a * (b * i);
	} else if (b <= 3.1e-121) {
		tmp = c * (t * j);
	} else {
		tmp = b * (a * 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 (b <= (-6.5d+38)) then
        tmp = a * (b * i)
    else if (b <= 3.1d-121) then
        tmp = c * (t * j)
    else
        tmp = b * (a * 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 (b <= -6.5e+38) {
		tmp = a * (b * i);
	} else if (b <= 3.1e-121) {
		tmp = c * (t * j);
	} else {
		tmp = b * (a * i);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if b <= -6.5e+38:
		tmp = a * (b * i)
	elif b <= 3.1e-121:
		tmp = c * (t * j)
	else:
		tmp = b * (a * i)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if (b <= -6.5e+38)
		tmp = Float64(a * Float64(b * i));
	elseif (b <= 3.1e-121)
		tmp = Float64(c * Float64(t * j));
	else
		tmp = Float64(b * Float64(a * i));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0;
	if (b <= -6.5e+38)
		tmp = a * (b * i);
	elseif (b <= 3.1e-121)
		tmp = c * (t * j);
	else
		tmp = b * (a * i);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[LessEqual[b, -6.5e+38], N[(a * N[(b * i), $MachinePrecision]), $MachinePrecision], If[LessEqual[b, 3.1e-121], N[(c * N[(t * j), $MachinePrecision]), $MachinePrecision], N[(b * N[(a * i), $MachinePrecision]), $MachinePrecision]]]

Derivation

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

Alternative 21: 23.1% 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

Developer target: 68.5% 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 2023343 
(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)))))