Data.Colour.Matrix:determinant from colour-2.3.3, A

Percentage Accurate: 73.0% → 82.8%

Time: 39.7s

Alternatives: 28

Speedup: 0.5×

• 58.8% of points produce a very large (infinite) output. You may want to add a precondition.

Specification

Math

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

FPCore

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

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

Python

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

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(t * i)))) + Float64(j * Float64(Float64(c * a) - Float64(y * i))))
end

MATLAB

function tmp = code(x, y, z, t, a, b, c, i, j)
	tmp = ((x * ((y * z) - (t * a))) - (b * ((c * z) - (t * i)))) + (j * ((c * a) - (y * i)));
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[(t * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(j * N[(N[(c * a), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Initial Program: 73.0% accurate, 1.0× speedup

Math

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

FPCore

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

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

Python

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

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(t * i)))) + Float64(j * Float64(Float64(c * a) - Float64(y * i))))
end

MATLAB

function tmp = code(x, y, z, t, a, b, c, i, j)
	tmp = ((x * ((y * z) - (t * a))) - (b * ((c * z) - (t * i)))) + (j * ((c * a) - (y * i)));
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[(t * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(j * N[(N[(c * a), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Alternative 1: 82.8% accurate, 0.2× speedup

Math

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

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (+ (* x (- (* y z) (* t a))) (* b (- (* t i) (* z c)))))
        (t_2 (- (* a c) (* y i))))
   (if (<= (+ t_1 (* j t_2)) INFINITY)
     (fma j t_2 t_1)
     (+ (* y (fma x z (* i (- j)))) (* a (- (* c j) (* x t)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = (x * ((y * z) - (t * a))) + (b * ((t * i) - (z * c)));
	double t_2 = (a * c) - (y * i);
	double tmp;
	if ((t_1 + (j * t_2)) <= ((double) INFINITY)) {
		tmp = fma(j, t_2, t_1);
	} else {
		tmp = (y * fma(x, z, (i * -j))) + (a * ((c * j) - (x * t)));
	}
	return tmp;
}

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(Float64(x * Float64(Float64(y * z) - Float64(t * a))) + Float64(b * Float64(Float64(t * i) - Float64(z * c))))
	t_2 = Float64(Float64(a * c) - Float64(y * i))
	tmp = 0.0
	if (Float64(t_1 + Float64(j * t_2)) <= Inf)
		tmp = fma(j, t_2, t_1);
	else
		tmp = Float64(Float64(y * fma(x, z, Float64(i * Float64(-j)))) + Float64(a * Float64(Float64(c * j) - Float64(x * t))));
	end
	return tmp
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(b * N[(N[(t * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(a * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[(t$95$1 + N[(j * t$95$2), $MachinePrecision]), $MachinePrecision], Infinity], N[(j * t$95$2 + t$95$1), $MachinePrecision], N[(N[(y * N[(x * z + N[(i * (-j)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(a * N[(N[(c * j), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]

Derivation

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

Alternative 2: 82.8% accurate, 0.2× speedup

Math

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

FPCore

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

C

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

Derivation

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

Alternative 3: 82.6% accurate, 0.5× speedup

Math

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

FPCore

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

C

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

Java

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

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = ((x * ((y * z) - (t * a))) + (b * ((t * i) - (z * c)))) + (j * ((a * c) - (y * i)))
	tmp = 0
	if t_1 <= math.inf:
		tmp = t_1
	else:
		tmp = (y * ((x * z) - (i * j))) + (a * ((c * j) - (x * t)))
	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(t * i) - Float64(z * c)))) + Float64(j * Float64(Float64(a * c) - Float64(y * i))))
	tmp = 0.0
	if (t_1 <= Inf)
		tmp = t_1;
	else
		tmp = Float64(Float64(y * Float64(Float64(x * z) - Float64(i * j))) + Float64(a * Float64(Float64(c * j) - Float64(x * t))));
	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 * ((t * i) - (z * c)))) + (j * ((a * c) - (y * i)));
	tmp = 0.0;
	if (t_1 <= Inf)
		tmp = t_1;
	else
		tmp = (y * ((x * z) - (i * j))) + (a * ((c * j) - (x * t)));
	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[(t * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(j * N[(N[(a * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$1, Infinity], t$95$1, N[(N[(y * N[(N[(x * z), $MachinePrecision] - N[(i * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(a * N[(N[(c * j), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]

Derivation

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

Alternative 4: 68.7% accurate, 0.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot \left(c \cdot j - x \cdot t\right)\\ t_2 := y \cdot \left(x \cdot z - i \cdot j\right) + t_1\\ t_3 := j \cdot \left(a \cdot c - y \cdot i\right)\\ t_4 := x \cdot \left(y \cdot z - t \cdot a\right)\\ t_5 := b \cdot \left(t \cdot i - z \cdot c\right)\\ \mathbf{if}\;a \leq -1.15 \cdot 10^{+28}:\\ \;\;\;\;t_5 + t_1\\ \mathbf{elif}\;a \leq -1.35 \cdot 10^{-55}:\\ \;\;\;\;t_2 - c \cdot \left(z \cdot b\right)\\ \mathbf{elif}\;a \leq -3.45 \cdot 10^{-177}:\\ \;\;\;\;t_4 + t_5\\ \mathbf{elif}\;a \leq 2.3 \cdot 10^{-151}:\\ \;\;\;\;\left(t_5 - t \cdot \left(x \cdot a\right)\right) + t_3\\ \mathbf{elif}\;a \leq 1.95 \cdot 10^{+80}:\\ \;\;\;\;\left(t_4 - z \cdot \left(b \cdot c\right)\right) + t_3\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* a (- (* c j) (* x t))))
        (t_2 (+ (* y (- (* x z) (* i j))) t_1))
        (t_3 (* j (- (* a c) (* y i))))
        (t_4 (* x (- (* y z) (* t a))))
        (t_5 (* b (- (* t i) (* z c)))))
   (if (<= a -1.15e+28)
     (+ t_5 t_1)
     (if (<= a -1.35e-55)
       (- t_2 (* c (* z b)))
       (if (<= a -3.45e-177)
         (+ t_4 t_5)
         (if (<= a 2.3e-151)
           (+ (- t_5 (* t (* x a))) t_3)
           (if (<= a 1.95e+80) (+ (- t_4 (* z (* b c))) t_3) 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 * ((c * j) - (x * t));
	double t_2 = (y * ((x * z) - (i * j))) + t_1;
	double t_3 = j * ((a * c) - (y * i));
	double t_4 = x * ((y * z) - (t * a));
	double t_5 = b * ((t * i) - (z * c));
	double tmp;
	if (a <= -1.15e+28) {
		tmp = t_5 + t_1;
	} else if (a <= -1.35e-55) {
		tmp = t_2 - (c * (z * b));
	} else if (a <= -3.45e-177) {
		tmp = t_4 + t_5;
	} else if (a <= 2.3e-151) {
		tmp = (t_5 - (t * (x * a))) + t_3;
	} else if (a <= 1.95e+80) {
		tmp = (t_4 - (z * (b * c))) + t_3;
	} else {
		tmp = t_2;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: t_5
    real(8) :: tmp
    t_1 = a * ((c * j) - (x * t))
    t_2 = (y * ((x * z) - (i * j))) + t_1
    t_3 = j * ((a * c) - (y * i))
    t_4 = x * ((y * z) - (t * a))
    t_5 = b * ((t * i) - (z * c))
    if (a <= (-1.15d+28)) then
        tmp = t_5 + t_1
    else if (a <= (-1.35d-55)) then
        tmp = t_2 - (c * (z * b))
    else if (a <= (-3.45d-177)) then
        tmp = t_4 + t_5
    else if (a <= 2.3d-151) then
        tmp = (t_5 - (t * (x * a))) + t_3
    else if (a <= 1.95d+80) then
        tmp = (t_4 - (z * (b * c))) + t_3
    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 * ((c * j) - (x * t));
	double t_2 = (y * ((x * z) - (i * j))) + t_1;
	double t_3 = j * ((a * c) - (y * i));
	double t_4 = x * ((y * z) - (t * a));
	double t_5 = b * ((t * i) - (z * c));
	double tmp;
	if (a <= -1.15e+28) {
		tmp = t_5 + t_1;
	} else if (a <= -1.35e-55) {
		tmp = t_2 - (c * (z * b));
	} else if (a <= -3.45e-177) {
		tmp = t_4 + t_5;
	} else if (a <= 2.3e-151) {
		tmp = (t_5 - (t * (x * a))) + t_3;
	} else if (a <= 1.95e+80) {
		tmp = (t_4 - (z * (b * c))) + t_3;
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = a * ((c * j) - (x * t))
	t_2 = (y * ((x * z) - (i * j))) + t_1
	t_3 = j * ((a * c) - (y * i))
	t_4 = x * ((y * z) - (t * a))
	t_5 = b * ((t * i) - (z * c))
	tmp = 0
	if a <= -1.15e+28:
		tmp = t_5 + t_1
	elif a <= -1.35e-55:
		tmp = t_2 - (c * (z * b))
	elif a <= -3.45e-177:
		tmp = t_4 + t_5
	elif a <= 2.3e-151:
		tmp = (t_5 - (t * (x * a))) + t_3
	elif a <= 1.95e+80:
		tmp = (t_4 - (z * (b * c))) + t_3
	else:
		tmp = t_2
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(a * Float64(Float64(c * j) - Float64(x * t)))
	t_2 = Float64(Float64(y * Float64(Float64(x * z) - Float64(i * j))) + t_1)
	t_3 = Float64(j * Float64(Float64(a * c) - Float64(y * i)))
	t_4 = Float64(x * Float64(Float64(y * z) - Float64(t * a)))
	t_5 = Float64(b * Float64(Float64(t * i) - Float64(z * c)))
	tmp = 0.0
	if (a <= -1.15e+28)
		tmp = Float64(t_5 + t_1);
	elseif (a <= -1.35e-55)
		tmp = Float64(t_2 - Float64(c * Float64(z * b)));
	elseif (a <= -3.45e-177)
		tmp = Float64(t_4 + t_5);
	elseif (a <= 2.3e-151)
		tmp = Float64(Float64(t_5 - Float64(t * Float64(x * a))) + t_3);
	elseif (a <= 1.95e+80)
		tmp = Float64(Float64(t_4 - Float64(z * Float64(b * c))) + t_3);
	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 * ((c * j) - (x * t));
	t_2 = (y * ((x * z) - (i * j))) + t_1;
	t_3 = j * ((a * c) - (y * i));
	t_4 = x * ((y * z) - (t * a));
	t_5 = b * ((t * i) - (z * c));
	tmp = 0.0;
	if (a <= -1.15e+28)
		tmp = t_5 + t_1;
	elseif (a <= -1.35e-55)
		tmp = t_2 - (c * (z * b));
	elseif (a <= -3.45e-177)
		tmp = t_4 + t_5;
	elseif (a <= 2.3e-151)
		tmp = (t_5 - (t * (x * a))) + t_3;
	elseif (a <= 1.95e+80)
		tmp = (t_4 - (z * (b * c))) + t_3;
	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[(c * j), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(y * N[(N[(x * z), $MachinePrecision] - N[(i * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision]}, Block[{t$95$3 = N[(j * N[(N[(a * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(b * N[(N[(t * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -1.15e+28], N[(t$95$5 + t$95$1), $MachinePrecision], If[LessEqual[a, -1.35e-55], N[(t$95$2 - N[(c * N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -3.45e-177], N[(t$95$4 + t$95$5), $MachinePrecision], If[LessEqual[a, 2.3e-151], N[(N[(t$95$5 - N[(t * N[(x * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$3), $MachinePrecision], If[LessEqual[a, 1.95e+80], N[(N[(t$95$4 - N[(z * N[(b * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$3), $MachinePrecision], t$95$2]]]]]]]]]]

Derivation

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

Alternative 5: 69.4% accurate, 0.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(y \cdot z - t \cdot a\right)\\ t_2 := t \cdot \left(b \cdot i - x \cdot a\right)\\ \mathbf{if}\;t \leq -2.2 \cdot 10^{+100}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t \leq -1 \cdot 10^{-20}:\\ \;\;\;\;t_1 + b \cdot \left(t \cdot i - z \cdot c\right)\\ \mathbf{elif}\;t \leq -1.32 \cdot 10^{-133}:\\ \;\;\;\;a \cdot \left(c \cdot j - x \cdot t\right) - z \cdot \left(b \cdot c - x \cdot y\right)\\ \mathbf{elif}\;t \leq 3 \cdot 10^{+204}:\\ \;\;\;\;\left(t_1 - z \cdot \left(b \cdot c\right)\right) + j \cdot \left(a \cdot c - y \cdot i\right)\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* x (- (* y z) (* t a)))) (t_2 (* t (- (* b i) (* x a)))))
   (if (<= t -2.2e+100)
     t_2
     (if (<= t -1e-20)
       (+ t_1 (* b (- (* t i) (* z c))))
       (if (<= t -1.32e-133)
         (- (* a (- (* c j) (* x t))) (* z (- (* b c) (* x y))))
         (if (<= t 3e+204)
           (+ (- t_1 (* z (* b c))) (* j (- (* a c) (* y i))))
           t_2))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = x * ((y * z) - (t * a));
	double t_2 = t * ((b * i) - (x * a));
	double tmp;
	if (t <= -2.2e+100) {
		tmp = t_2;
	} else if (t <= -1e-20) {
		tmp = t_1 + (b * ((t * i) - (z * c)));
	} else if (t <= -1.32e-133) {
		tmp = (a * ((c * j) - (x * t))) - (z * ((b * c) - (x * y)));
	} else if (t <= 3e+204) {
		tmp = (t_1 - (z * (b * c))) + (j * ((a * c) - (y * i)));
	} else {
		tmp = t_2;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = x * ((y * z) - (t * a))
    t_2 = t * ((b * i) - (x * a))
    if (t <= (-2.2d+100)) then
        tmp = t_2
    else if (t <= (-1d-20)) then
        tmp = t_1 + (b * ((t * i) - (z * c)))
    else if (t <= (-1.32d-133)) then
        tmp = (a * ((c * j) - (x * t))) - (z * ((b * c) - (x * y)))
    else if (t <= 3d+204) then
        tmp = (t_1 - (z * (b * c))) + (j * ((a * c) - (y * i)))
    else
        tmp = t_2
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = x * ((y * z) - (t * a));
	double t_2 = t * ((b * i) - (x * a));
	double tmp;
	if (t <= -2.2e+100) {
		tmp = t_2;
	} else if (t <= -1e-20) {
		tmp = t_1 + (b * ((t * i) - (z * c)));
	} else if (t <= -1.32e-133) {
		tmp = (a * ((c * j) - (x * t))) - (z * ((b * c) - (x * y)));
	} else if (t <= 3e+204) {
		tmp = (t_1 - (z * (b * c))) + (j * ((a * c) - (y * i)));
	} 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 = t * ((b * i) - (x * a))
	tmp = 0
	if t <= -2.2e+100:
		tmp = t_2
	elif t <= -1e-20:
		tmp = t_1 + (b * ((t * i) - (z * c)))
	elif t <= -1.32e-133:
		tmp = (a * ((c * j) - (x * t))) - (z * ((b * c) - (x * y)))
	elif t <= 3e+204:
		tmp = (t_1 - (z * (b * c))) + (j * ((a * c) - (y * i)))
	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(t * Float64(Float64(b * i) - Float64(x * a)))
	tmp = 0.0
	if (t <= -2.2e+100)
		tmp = t_2;
	elseif (t <= -1e-20)
		tmp = Float64(t_1 + Float64(b * Float64(Float64(t * i) - Float64(z * c))));
	elseif (t <= -1.32e-133)
		tmp = Float64(Float64(a * Float64(Float64(c * j) - Float64(x * t))) - Float64(z * Float64(Float64(b * c) - Float64(x * y))));
	elseif (t <= 3e+204)
		tmp = Float64(Float64(t_1 - Float64(z * Float64(b * c))) + Float64(j * Float64(Float64(a * c) - Float64(y * i))));
	else
		tmp = t_2;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = x * ((y * z) - (t * a));
	t_2 = t * ((b * i) - (x * a));
	tmp = 0.0;
	if (t <= -2.2e+100)
		tmp = t_2;
	elseif (t <= -1e-20)
		tmp = t_1 + (b * ((t * i) - (z * c)));
	elseif (t <= -1.32e-133)
		tmp = (a * ((c * j) - (x * t))) - (z * ((b * c) - (x * y)));
	elseif (t <= 3e+204)
		tmp = (t_1 - (z * (b * c))) + (j * ((a * c) - (y * i)));
	else
		tmp = t_2;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(t * N[(N[(b * i), $MachinePrecision] - N[(x * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -2.2e+100], t$95$2, If[LessEqual[t, -1e-20], N[(t$95$1 + N[(b * N[(N[(t * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -1.32e-133], N[(N[(a * N[(N[(c * j), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(z * N[(N[(b * c), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 3e+204], N[(N[(t$95$1 - N[(z * N[(b * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(j * N[(N[(a * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$2]]]]]]

Derivation

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

Alternative 6: 69.8% accurate, 0.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot \left(c \cdot j - x \cdot t\right)\\ t_2 := j \cdot \left(a \cdot c - y \cdot i\right)\\ t_3 := x \cdot \left(y \cdot z - t \cdot a\right)\\ t_4 := b \cdot \left(t \cdot i - z \cdot c\right)\\ \mathbf{if}\;x \leq -7.5 \cdot 10^{+203}:\\ \;\;\;\;y \cdot \left(x \cdot z - i \cdot j\right) + t_1\\ \mathbf{elif}\;x \leq -8.2 \cdot 10^{-7}:\\ \;\;\;\;\left(t_3 - z \cdot \left(b \cdot c\right)\right) + t_2\\ \mathbf{elif}\;x \leq 2.15 \cdot 10^{-119}:\\ \;\;\;\;\left(t_4 - t \cdot \left(x \cdot a\right)\right) + t_2\\ \mathbf{elif}\;x \leq 10^{-34}:\\ \;\;\;\;t_1 - z \cdot \left(b \cdot c - x \cdot y\right)\\ \mathbf{elif}\;x \leq 1.6 \cdot 10^{+60}:\\ \;\;\;\;t_3 + t_4\\ \mathbf{else}:\\ \;\;\;\;t_3 + t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* a (- (* c j) (* x t))))
        (t_2 (* j (- (* a c) (* y i))))
        (t_3 (* x (- (* y z) (* t a))))
        (t_4 (* b (- (* t i) (* z c)))))
   (if (<= x -7.5e+203)
     (+ (* y (- (* x z) (* i j))) t_1)
     (if (<= x -8.2e-7)
       (+ (- t_3 (* z (* b c))) t_2)
       (if (<= x 2.15e-119)
         (+ (- t_4 (* t (* x a))) t_2)
         (if (<= x 1e-34)
           (- t_1 (* z (- (* b c) (* x y))))
           (if (<= x 1.6e+60) (+ t_3 t_4) (+ t_3 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 * ((c * j) - (x * t));
	double t_2 = j * ((a * c) - (y * i));
	double t_3 = x * ((y * z) - (t * a));
	double t_4 = b * ((t * i) - (z * c));
	double tmp;
	if (x <= -7.5e+203) {
		tmp = (y * ((x * z) - (i * j))) + t_1;
	} else if (x <= -8.2e-7) {
		tmp = (t_3 - (z * (b * c))) + t_2;
	} else if (x <= 2.15e-119) {
		tmp = (t_4 - (t * (x * a))) + t_2;
	} else if (x <= 1e-34) {
		tmp = t_1 - (z * ((b * c) - (x * y)));
	} else if (x <= 1.6e+60) {
		tmp = t_3 + t_4;
	} else {
		tmp = t_3 + t_2;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: tmp
    t_1 = a * ((c * j) - (x * t))
    t_2 = j * ((a * c) - (y * i))
    t_3 = x * ((y * z) - (t * a))
    t_4 = b * ((t * i) - (z * c))
    if (x <= (-7.5d+203)) then
        tmp = (y * ((x * z) - (i * j))) + t_1
    else if (x <= (-8.2d-7)) then
        tmp = (t_3 - (z * (b * c))) + t_2
    else if (x <= 2.15d-119) then
        tmp = (t_4 - (t * (x * a))) + t_2
    else if (x <= 1d-34) then
        tmp = t_1 - (z * ((b * c) - (x * y)))
    else if (x <= 1.6d+60) then
        tmp = t_3 + t_4
    else
        tmp = t_3 + 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 * ((c * j) - (x * t));
	double t_2 = j * ((a * c) - (y * i));
	double t_3 = x * ((y * z) - (t * a));
	double t_4 = b * ((t * i) - (z * c));
	double tmp;
	if (x <= -7.5e+203) {
		tmp = (y * ((x * z) - (i * j))) + t_1;
	} else if (x <= -8.2e-7) {
		tmp = (t_3 - (z * (b * c))) + t_2;
	} else if (x <= 2.15e-119) {
		tmp = (t_4 - (t * (x * a))) + t_2;
	} else if (x <= 1e-34) {
		tmp = t_1 - (z * ((b * c) - (x * y)));
	} else if (x <= 1.6e+60) {
		tmp = t_3 + t_4;
	} else {
		tmp = t_3 + t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = a * ((c * j) - (x * t))
	t_2 = j * ((a * c) - (y * i))
	t_3 = x * ((y * z) - (t * a))
	t_4 = b * ((t * i) - (z * c))
	tmp = 0
	if x <= -7.5e+203:
		tmp = (y * ((x * z) - (i * j))) + t_1
	elif x <= -8.2e-7:
		tmp = (t_3 - (z * (b * c))) + t_2
	elif x <= 2.15e-119:
		tmp = (t_4 - (t * (x * a))) + t_2
	elif x <= 1e-34:
		tmp = t_1 - (z * ((b * c) - (x * y)))
	elif x <= 1.6e+60:
		tmp = t_3 + t_4
	else:
		tmp = t_3 + t_2
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(a * Float64(Float64(c * j) - Float64(x * t)))
	t_2 = Float64(j * Float64(Float64(a * c) - Float64(y * i)))
	t_3 = Float64(x * Float64(Float64(y * z) - Float64(t * a)))
	t_4 = Float64(b * Float64(Float64(t * i) - Float64(z * c)))
	tmp = 0.0
	if (x <= -7.5e+203)
		tmp = Float64(Float64(y * Float64(Float64(x * z) - Float64(i * j))) + t_1);
	elseif (x <= -8.2e-7)
		tmp = Float64(Float64(t_3 - Float64(z * Float64(b * c))) + t_2);
	elseif (x <= 2.15e-119)
		tmp = Float64(Float64(t_4 - Float64(t * Float64(x * a))) + t_2);
	elseif (x <= 1e-34)
		tmp = Float64(t_1 - Float64(z * Float64(Float64(b * c) - Float64(x * y))));
	elseif (x <= 1.6e+60)
		tmp = Float64(t_3 + t_4);
	else
		tmp = Float64(t_3 + t_2);
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = a * ((c * j) - (x * t));
	t_2 = j * ((a * c) - (y * i));
	t_3 = x * ((y * z) - (t * a));
	t_4 = b * ((t * i) - (z * c));
	tmp = 0.0;
	if (x <= -7.5e+203)
		tmp = (y * ((x * z) - (i * j))) + t_1;
	elseif (x <= -8.2e-7)
		tmp = (t_3 - (z * (b * c))) + t_2;
	elseif (x <= 2.15e-119)
		tmp = (t_4 - (t * (x * a))) + t_2;
	elseif (x <= 1e-34)
		tmp = t_1 - (z * ((b * c) - (x * y)));
	elseif (x <= 1.6e+60)
		tmp = t_3 + t_4;
	else
		tmp = t_3 + 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[(c * j), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(j * N[(N[(a * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(b * N[(N[(t * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[x, -7.5e+203], N[(N[(y * N[(N[(x * z), $MachinePrecision] - N[(i * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision], If[LessEqual[x, -8.2e-7], N[(N[(t$95$3 - N[(z * N[(b * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$2), $MachinePrecision], If[LessEqual[x, 2.15e-119], N[(N[(t$95$4 - N[(t * N[(x * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$2), $MachinePrecision], If[LessEqual[x, 1e-34], N[(t$95$1 - N[(z * N[(N[(b * c), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 1.6e+60], N[(t$95$3 + t$95$4), $MachinePrecision], N[(t$95$3 + t$95$2), $MachinePrecision]]]]]]]]]]

Derivation

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

Alternative 7: 49.4% accurate, 1.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(y \cdot z - t \cdot a\right)\\ t_2 := j \cdot \left(a \cdot c - y \cdot i\right)\\ \mathbf{if}\;j \leq -2.25 \cdot 10^{+18}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;j \leq -7.6 \cdot 10^{-258}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;j \leq 3.1 \cdot 10^{-296}:\\ \;\;\;\;a \cdot \left(c \cdot j - x \cdot t\right)\\ \mathbf{elif}\;j \leq 2.15 \cdot 10^{-275}:\\ \;\;\;\;x \cdot \left(y \cdot z\right)\\ \mathbf{elif}\;j \leq 2.5 \cdot 10^{-199}:\\ \;\;\;\;t \cdot \left(b \cdot i - x \cdot a\right)\\ \mathbf{elif}\;j \leq 1.7 \cdot 10^{-146}:\\ \;\;\;\;c \cdot \left(a \cdot j - z \cdot b\right)\\ \mathbf{elif}\;j \leq 1.05 \cdot 10^{-84}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;j \leq 1.6 \cdot 10^{+76}:\\ \;\;\;\;b \cdot \left(t \cdot i - z \cdot c\right)\\ \mathbf{elif}\;j \leq 5.8 \cdot 10^{+92}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* x (- (* y z) (* t a)))) (t_2 (* j (- (* a c) (* y i)))))
   (if (<= j -2.25e+18)
     t_2
     (if (<= j -7.6e-258)
       t_1
       (if (<= j 3.1e-296)
         (* a (- (* c j) (* x t)))
         (if (<= j 2.15e-275)
           (* x (* y z))
           (if (<= j 2.5e-199)
             (* t (- (* b i) (* x a)))
             (if (<= j 1.7e-146)
               (* c (- (* a j) (* z b)))
               (if (<= j 1.05e-84)
                 t_1
                 (if (<= j 1.6e+76)
                   (* b (- (* t i) (* z c)))
                   (if (<= j 5.8e+92) 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));
	double t_2 = j * ((a * c) - (y * i));
	double tmp;
	if (j <= -2.25e+18) {
		tmp = t_2;
	} else if (j <= -7.6e-258) {
		tmp = t_1;
	} else if (j <= 3.1e-296) {
		tmp = a * ((c * j) - (x * t));
	} else if (j <= 2.15e-275) {
		tmp = x * (y * z);
	} else if (j <= 2.5e-199) {
		tmp = t * ((b * i) - (x * a));
	} else if (j <= 1.7e-146) {
		tmp = c * ((a * j) - (z * b));
	} else if (j <= 1.05e-84) {
		tmp = t_1;
	} else if (j <= 1.6e+76) {
		tmp = b * ((t * i) - (z * c));
	} else if (j <= 5.8e+92) {
		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))
    t_2 = j * ((a * c) - (y * i))
    if (j <= (-2.25d+18)) then
        tmp = t_2
    else if (j <= (-7.6d-258)) then
        tmp = t_1
    else if (j <= 3.1d-296) then
        tmp = a * ((c * j) - (x * t))
    else if (j <= 2.15d-275) then
        tmp = x * (y * z)
    else if (j <= 2.5d-199) then
        tmp = t * ((b * i) - (x * a))
    else if (j <= 1.7d-146) then
        tmp = c * ((a * j) - (z * b))
    else if (j <= 1.05d-84) then
        tmp = t_1
    else if (j <= 1.6d+76) then
        tmp = b * ((t * i) - (z * c))
    else if (j <= 5.8d+92) 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));
	double t_2 = j * ((a * c) - (y * i));
	double tmp;
	if (j <= -2.25e+18) {
		tmp = t_2;
	} else if (j <= -7.6e-258) {
		tmp = t_1;
	} else if (j <= 3.1e-296) {
		tmp = a * ((c * j) - (x * t));
	} else if (j <= 2.15e-275) {
		tmp = x * (y * z);
	} else if (j <= 2.5e-199) {
		tmp = t * ((b * i) - (x * a));
	} else if (j <= 1.7e-146) {
		tmp = c * ((a * j) - (z * b));
	} else if (j <= 1.05e-84) {
		tmp = t_1;
	} else if (j <= 1.6e+76) {
		tmp = b * ((t * i) - (z * c));
	} else if (j <= 5.8e+92) {
		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))
	t_2 = j * ((a * c) - (y * i))
	tmp = 0
	if j <= -2.25e+18:
		tmp = t_2
	elif j <= -7.6e-258:
		tmp = t_1
	elif j <= 3.1e-296:
		tmp = a * ((c * j) - (x * t))
	elif j <= 2.15e-275:
		tmp = x * (y * z)
	elif j <= 2.5e-199:
		tmp = t * ((b * i) - (x * a))
	elif j <= 1.7e-146:
		tmp = c * ((a * j) - (z * b))
	elif j <= 1.05e-84:
		tmp = t_1
	elif j <= 1.6e+76:
		tmp = b * ((t * i) - (z * c))
	elif j <= 5.8e+92:
		tmp = t_1
	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(j * Float64(Float64(a * c) - Float64(y * i)))
	tmp = 0.0
	if (j <= -2.25e+18)
		tmp = t_2;
	elseif (j <= -7.6e-258)
		tmp = t_1;
	elseif (j <= 3.1e-296)
		tmp = Float64(a * Float64(Float64(c * j) - Float64(x * t)));
	elseif (j <= 2.15e-275)
		tmp = Float64(x * Float64(y * z));
	elseif (j <= 2.5e-199)
		tmp = Float64(t * Float64(Float64(b * i) - Float64(x * a)));
	elseif (j <= 1.7e-146)
		tmp = Float64(c * Float64(Float64(a * j) - Float64(z * b)));
	elseif (j <= 1.05e-84)
		tmp = t_1;
	elseif (j <= 1.6e+76)
		tmp = Float64(b * Float64(Float64(t * i) - Float64(z * c)));
	elseif (j <= 5.8e+92)
		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));
	t_2 = j * ((a * c) - (y * i));
	tmp = 0.0;
	if (j <= -2.25e+18)
		tmp = t_2;
	elseif (j <= -7.6e-258)
		tmp = t_1;
	elseif (j <= 3.1e-296)
		tmp = a * ((c * j) - (x * t));
	elseif (j <= 2.15e-275)
		tmp = x * (y * z);
	elseif (j <= 2.5e-199)
		tmp = t * ((b * i) - (x * a));
	elseif (j <= 1.7e-146)
		tmp = c * ((a * j) - (z * b));
	elseif (j <= 1.05e-84)
		tmp = t_1;
	elseif (j <= 1.6e+76)
		tmp = b * ((t * i) - (z * c));
	elseif (j <= 5.8e+92)
		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[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(j * N[(N[(a * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -2.25e+18], t$95$2, If[LessEqual[j, -7.6e-258], t$95$1, If[LessEqual[j, 3.1e-296], N[(a * N[(N[(c * j), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 2.15e-275], N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 2.5e-199], N[(t * N[(N[(b * i), $MachinePrecision] - N[(x * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 1.7e-146], N[(c * N[(N[(a * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 1.05e-84], t$95$1, If[LessEqual[j, 1.6e+76], N[(b * N[(N[(t * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 5.8e+92], t$95$1, t$95$2]]]]]]]]]]]

Derivation

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

Alternative 8: 67.4% accurate, 1.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(t \cdot i - z \cdot c\right)\\ \mathbf{if}\;b \leq -1.65 \cdot 10^{+118}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;b \leq -3.5 \cdot 10^{-137} \lor \neg \left(b \leq -3.3 \cdot 10^{-165}\right) \land b \leq 6.7 \cdot 10^{+56}:\\ \;\;\;\;x \cdot \left(y \cdot z - t \cdot a\right) + j \cdot \left(a \cdot c - y \cdot i\right)\\ \mathbf{else}:\\ \;\;\;\;t_1 + a \cdot \left(c \cdot j - x \cdot t\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* b (- (* t i) (* z c)))))
   (if (<= b -1.65e+118)
     t_1
     (if (or (<= b -3.5e-137) (and (not (<= b -3.3e-165)) (<= b 6.7e+56)))
       (+ (* x (- (* y z) (* t a))) (* j (- (* a c) (* y i))))
       (+ t_1 (* a (- (* c j) (* x t))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = b * ((t * i) - (z * c));
	double tmp;
	if (b <= -1.65e+118) {
		tmp = t_1;
	} else if ((b <= -3.5e-137) || (!(b <= -3.3e-165) && (b <= 6.7e+56))) {
		tmp = (x * ((y * z) - (t * a))) + (j * ((a * c) - (y * i)));
	} else {
		tmp = t_1 + (a * ((c * j) - (x * t)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: tmp
    t_1 = b * ((t * i) - (z * c))
    if (b <= (-1.65d+118)) then
        tmp = t_1
    else if ((b <= (-3.5d-137)) .or. (.not. (b <= (-3.3d-165))) .and. (b <= 6.7d+56)) then
        tmp = (x * ((y * z) - (t * a))) + (j * ((a * c) - (y * i)))
    else
        tmp = t_1 + (a * ((c * j) - (x * t)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = b * ((t * i) - (z * c));
	double tmp;
	if (b <= -1.65e+118) {
		tmp = t_1;
	} else if ((b <= -3.5e-137) || (!(b <= -3.3e-165) && (b <= 6.7e+56))) {
		tmp = (x * ((y * z) - (t * a))) + (j * ((a * c) - (y * i)));
	} else {
		tmp = t_1 + (a * ((c * j) - (x * t)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = b * ((t * i) - (z * c))
	tmp = 0
	if b <= -1.65e+118:
		tmp = t_1
	elif (b <= -3.5e-137) or (not (b <= -3.3e-165) and (b <= 6.7e+56)):
		tmp = (x * ((y * z) - (t * a))) + (j * ((a * c) - (y * i)))
	else:
		tmp = t_1 + (a * ((c * j) - (x * t)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(b * Float64(Float64(t * i) - Float64(z * c)))
	tmp = 0.0
	if (b <= -1.65e+118)
		tmp = t_1;
	elseif ((b <= -3.5e-137) || (!(b <= -3.3e-165) && (b <= 6.7e+56)))
		tmp = Float64(Float64(x * Float64(Float64(y * z) - Float64(t * a))) + Float64(j * Float64(Float64(a * c) - Float64(y * i))));
	else
		tmp = Float64(t_1 + Float64(a * Float64(Float64(c * j) - Float64(x * t))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = b * ((t * i) - (z * c));
	tmp = 0.0;
	if (b <= -1.65e+118)
		tmp = t_1;
	elseif ((b <= -3.5e-137) || (~((b <= -3.3e-165)) && (b <= 6.7e+56)))
		tmp = (x * ((y * z) - (t * a))) + (j * ((a * c) - (y * i)));
	else
		tmp = t_1 + (a * ((c * j) - (x * t)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(b * N[(N[(t * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[b, -1.65e+118], t$95$1, If[Or[LessEqual[b, -3.5e-137], And[N[Not[LessEqual[b, -3.3e-165]], $MachinePrecision], LessEqual[b, 6.7e+56]]], N[(N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(j * N[(N[(a * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(t$95$1 + N[(a * N[(N[(c * j), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]

Derivation

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

Alternative 9: 67.5% accurate, 1.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(y \cdot z - t \cdot a\right) + j \cdot \left(a \cdot c - y \cdot i\right)\\ t_2 := a \cdot \left(c \cdot j - x \cdot t\right)\\ t_3 := b \cdot \left(t \cdot i - z \cdot c\right)\\ \mathbf{if}\;b \leq -1.25 \cdot 10^{+120}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;b \leq 4.6 \cdot 10^{-242}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;b \leq 9 \cdot 10^{-200}:\\ \;\;\;\;t_2 - z \cdot \left(b \cdot c - x \cdot y\right)\\ \mathbf{elif}\;b \leq 2.3 \cdot 10^{+56}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;t_3 + t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (+ (* x (- (* y z) (* t a))) (* j (- (* a c) (* y i)))))
        (t_2 (* a (- (* c j) (* x t))))
        (t_3 (* b (- (* t i) (* z c)))))
   (if (<= b -1.25e+120)
     t_3
     (if (<= b 4.6e-242)
       t_1
       (if (<= b 9e-200)
         (- t_2 (* z (- (* b c) (* x y))))
         (if (<= b 2.3e+56) t_1 (+ t_3 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))) + (j * ((a * c) - (y * i)));
	double t_2 = a * ((c * j) - (x * t));
	double t_3 = b * ((t * i) - (z * c));
	double tmp;
	if (b <= -1.25e+120) {
		tmp = t_3;
	} else if (b <= 4.6e-242) {
		tmp = t_1;
	} else if (b <= 9e-200) {
		tmp = t_2 - (z * ((b * c) - (x * y)));
	} else if (b <= 2.3e+56) {
		tmp = t_1;
	} else {
		tmp = t_3 + t_2;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: tmp
    t_1 = (x * ((y * z) - (t * a))) + (j * ((a * c) - (y * i)))
    t_2 = a * ((c * j) - (x * t))
    t_3 = b * ((t * i) - (z * c))
    if (b <= (-1.25d+120)) then
        tmp = t_3
    else if (b <= 4.6d-242) then
        tmp = t_1
    else if (b <= 9d-200) then
        tmp = t_2 - (z * ((b * c) - (x * y)))
    else if (b <= 2.3d+56) then
        tmp = t_1
    else
        tmp = t_3 + 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))) + (j * ((a * c) - (y * i)));
	double t_2 = a * ((c * j) - (x * t));
	double t_3 = b * ((t * i) - (z * c));
	double tmp;
	if (b <= -1.25e+120) {
		tmp = t_3;
	} else if (b <= 4.6e-242) {
		tmp = t_1;
	} else if (b <= 9e-200) {
		tmp = t_2 - (z * ((b * c) - (x * y)));
	} else if (b <= 2.3e+56) {
		tmp = t_1;
	} else {
		tmp = t_3 + t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = (x * ((y * z) - (t * a))) + (j * ((a * c) - (y * i)))
	t_2 = a * ((c * j) - (x * t))
	t_3 = b * ((t * i) - (z * c))
	tmp = 0
	if b <= -1.25e+120:
		tmp = t_3
	elif b <= 4.6e-242:
		tmp = t_1
	elif b <= 9e-200:
		tmp = t_2 - (z * ((b * c) - (x * y)))
	elif b <= 2.3e+56:
		tmp = t_1
	else:
		tmp = t_3 + t_2
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(Float64(x * Float64(Float64(y * z) - Float64(t * a))) + Float64(j * Float64(Float64(a * c) - Float64(y * i))))
	t_2 = Float64(a * Float64(Float64(c * j) - Float64(x * t)))
	t_3 = Float64(b * Float64(Float64(t * i) - Float64(z * c)))
	tmp = 0.0
	if (b <= -1.25e+120)
		tmp = t_3;
	elseif (b <= 4.6e-242)
		tmp = t_1;
	elseif (b <= 9e-200)
		tmp = Float64(t_2 - Float64(z * Float64(Float64(b * c) - Float64(x * y))));
	elseif (b <= 2.3e+56)
		tmp = t_1;
	else
		tmp = Float64(t_3 + 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))) + (j * ((a * c) - (y * i)));
	t_2 = a * ((c * j) - (x * t));
	t_3 = b * ((t * i) - (z * c));
	tmp = 0.0;
	if (b <= -1.25e+120)
		tmp = t_3;
	elseif (b <= 4.6e-242)
		tmp = t_1;
	elseif (b <= 9e-200)
		tmp = t_2 - (z * ((b * c) - (x * y)));
	elseif (b <= 2.3e+56)
		tmp = t_1;
	else
		tmp = t_3 + t_2;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(j * N[(N[(a * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(a * N[(N[(c * j), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(b * N[(N[(t * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[b, -1.25e+120], t$95$3, If[LessEqual[b, 4.6e-242], t$95$1, If[LessEqual[b, 9e-200], N[(t$95$2 - N[(z * N[(N[(b * c), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[b, 2.3e+56], t$95$1, N[(t$95$3 + t$95$2), $MachinePrecision]]]]]]]]

Derivation

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

Alternative 10: 62.7% accurate, 1.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(y \cdot z - t \cdot a\right)\\ t_2 := b \cdot \left(t \cdot i - z \cdot c\right)\\ \mathbf{if}\;c \leq -2.4 \cdot 10^{-91}:\\ \;\;\;\;t_2 + a \cdot \left(c \cdot j - x \cdot t\right)\\ \mathbf{elif}\;c \leq -2.3 \cdot 10^{-157}:\\ \;\;\;\;i \cdot \left(t \cdot b - y \cdot j\right)\\ \mathbf{elif}\;c \leq -6.2 \cdot 10^{-268}:\\ \;\;\;\;t_1 + t_2\\ \mathbf{elif}\;c \leq 2 \cdot 10^{+113}:\\ \;\;\;\;t_1 + j \cdot \left(a \cdot c - y \cdot i\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(a \cdot j - z \cdot b\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* x (- (* y z) (* t a)))) (t_2 (* b (- (* t i) (* z c)))))
   (if (<= c -2.4e-91)
     (+ t_2 (* a (- (* c j) (* x t))))
     (if (<= c -2.3e-157)
       (* i (- (* t b) (* y j)))
       (if (<= c -6.2e-268)
         (+ t_1 t_2)
         (if (<= c 2e+113)
           (+ t_1 (* j (- (* a c) (* y i))))
           (* c (- (* a 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) - (t * a));
	double t_2 = b * ((t * i) - (z * c));
	double tmp;
	if (c <= -2.4e-91) {
		tmp = t_2 + (a * ((c * j) - (x * t)));
	} else if (c <= -2.3e-157) {
		tmp = i * ((t * b) - (y * j));
	} else if (c <= -6.2e-268) {
		tmp = t_1 + t_2;
	} else if (c <= 2e+113) {
		tmp = t_1 + (j * ((a * c) - (y * i)));
	} else {
		tmp = c * ((a * 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) :: tmp
    t_1 = x * ((y * z) - (t * a))
    t_2 = b * ((t * i) - (z * c))
    if (c <= (-2.4d-91)) then
        tmp = t_2 + (a * ((c * j) - (x * t)))
    else if (c <= (-2.3d-157)) then
        tmp = i * ((t * b) - (y * j))
    else if (c <= (-6.2d-268)) then
        tmp = t_1 + t_2
    else if (c <= 2d+113) then
        tmp = t_1 + (j * ((a * c) - (y * i)))
    else
        tmp = c * ((a * 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) - (t * a));
	double t_2 = b * ((t * i) - (z * c));
	double tmp;
	if (c <= -2.4e-91) {
		tmp = t_2 + (a * ((c * j) - (x * t)));
	} else if (c <= -2.3e-157) {
		tmp = i * ((t * b) - (y * j));
	} else if (c <= -6.2e-268) {
		tmp = t_1 + t_2;
	} else if (c <= 2e+113) {
		tmp = t_1 + (j * ((a * c) - (y * i)));
	} else {
		tmp = c * ((a * j) - (z * b));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = x * ((y * z) - (t * a))
	t_2 = b * ((t * i) - (z * c))
	tmp = 0
	if c <= -2.4e-91:
		tmp = t_2 + (a * ((c * j) - (x * t)))
	elif c <= -2.3e-157:
		tmp = i * ((t * b) - (y * j))
	elif c <= -6.2e-268:
		tmp = t_1 + t_2
	elif c <= 2e+113:
		tmp = t_1 + (j * ((a * c) - (y * i)))
	else:
		tmp = c * ((a * j) - (z * b))
	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(t * i) - Float64(z * c)))
	tmp = 0.0
	if (c <= -2.4e-91)
		tmp = Float64(t_2 + Float64(a * Float64(Float64(c * j) - Float64(x * t))));
	elseif (c <= -2.3e-157)
		tmp = Float64(i * Float64(Float64(t * b) - Float64(y * j)));
	elseif (c <= -6.2e-268)
		tmp = Float64(t_1 + t_2);
	elseif (c <= 2e+113)
		tmp = Float64(t_1 + Float64(j * Float64(Float64(a * c) - Float64(y * i))));
	else
		tmp = Float64(c * Float64(Float64(a * 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) - (t * a));
	t_2 = b * ((t * i) - (z * c));
	tmp = 0.0;
	if (c <= -2.4e-91)
		tmp = t_2 + (a * ((c * j) - (x * t)));
	elseif (c <= -2.3e-157)
		tmp = i * ((t * b) - (y * j));
	elseif (c <= -6.2e-268)
		tmp = t_1 + t_2;
	elseif (c <= 2e+113)
		tmp = t_1 + (j * ((a * c) - (y * i)));
	else
		tmp = c * ((a * j) - (z * b));
	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[(t * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[c, -2.4e-91], N[(t$95$2 + N[(a * N[(N[(c * j), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, -2.3e-157], N[(i * N[(N[(t * b), $MachinePrecision] - N[(y * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, -6.2e-268], N[(t$95$1 + t$95$2), $MachinePrecision], If[LessEqual[c, 2e+113], N[(t$95$1 + N[(j * N[(N[(a * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(c * N[(N[(a * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]

Derivation

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

Alternative 11: 48.5% accurate, 1.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := i \cdot \left(t \cdot b - y \cdot j\right)\\ \mathbf{if}\;c \leq -1.1 \cdot 10^{+147}:\\ \;\;\;\;b \cdot \left(t \cdot i - z \cdot c\right)\\ \mathbf{elif}\;c \leq -1.7 \cdot 10^{-85}:\\ \;\;\;\;a \cdot \left(c \cdot j - x \cdot t\right)\\ \mathbf{elif}\;c \leq -1.1 \cdot 10^{-214}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;c \leq -6.8 \cdot 10^{-258}:\\ \;\;\;\;x \cdot \left(y \cdot z - t \cdot a\right)\\ \mathbf{elif}\;c \leq 9 \cdot 10^{-283}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;c \leq 6 \cdot 10^{-19} \lor \neg \left(c \leq 2.5 \cdot 10^{+27}\right) \land c \leq 2.6 \cdot 10^{+112}:\\ \;\;\;\;y \cdot \left(x \cdot z - i \cdot j\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(a \cdot j - z \cdot b\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* i (- (* t b) (* y j)))))
   (if (<= c -1.1e+147)
     (* b (- (* t i) (* z c)))
     (if (<= c -1.7e-85)
       (* a (- (* c j) (* x t)))
       (if (<= c -1.1e-214)
         t_1
         (if (<= c -6.8e-258)
           (* x (- (* y z) (* t a)))
           (if (<= c 9e-283)
             t_1
             (if (or (<= c 6e-19) (and (not (<= c 2.5e+27)) (<= c 2.6e+112)))
               (* y (- (* x z) (* i j)))
               (* c (- (* a 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 = i * ((t * b) - (y * j));
	double tmp;
	if (c <= -1.1e+147) {
		tmp = b * ((t * i) - (z * c));
	} else if (c <= -1.7e-85) {
		tmp = a * ((c * j) - (x * t));
	} else if (c <= -1.1e-214) {
		tmp = t_1;
	} else if (c <= -6.8e-258) {
		tmp = x * ((y * z) - (t * a));
	} else if (c <= 9e-283) {
		tmp = t_1;
	} else if ((c <= 6e-19) || (!(c <= 2.5e+27) && (c <= 2.6e+112))) {
		tmp = y * ((x * z) - (i * j));
	} else {
		tmp = c * ((a * 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 = i * ((t * b) - (y * j))
    if (c <= (-1.1d+147)) then
        tmp = b * ((t * i) - (z * c))
    else if (c <= (-1.7d-85)) then
        tmp = a * ((c * j) - (x * t))
    else if (c <= (-1.1d-214)) then
        tmp = t_1
    else if (c <= (-6.8d-258)) then
        tmp = x * ((y * z) - (t * a))
    else if (c <= 9d-283) then
        tmp = t_1
    else if ((c <= 6d-19) .or. (.not. (c <= 2.5d+27)) .and. (c <= 2.6d+112)) then
        tmp = y * ((x * z) - (i * j))
    else
        tmp = c * ((a * 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 = i * ((t * b) - (y * j));
	double tmp;
	if (c <= -1.1e+147) {
		tmp = b * ((t * i) - (z * c));
	} else if (c <= -1.7e-85) {
		tmp = a * ((c * j) - (x * t));
	} else if (c <= -1.1e-214) {
		tmp = t_1;
	} else if (c <= -6.8e-258) {
		tmp = x * ((y * z) - (t * a));
	} else if (c <= 9e-283) {
		tmp = t_1;
	} else if ((c <= 6e-19) || (!(c <= 2.5e+27) && (c <= 2.6e+112))) {
		tmp = y * ((x * z) - (i * j));
	} else {
		tmp = c * ((a * j) - (z * b));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = i * ((t * b) - (y * j))
	tmp = 0
	if c <= -1.1e+147:
		tmp = b * ((t * i) - (z * c))
	elif c <= -1.7e-85:
		tmp = a * ((c * j) - (x * t))
	elif c <= -1.1e-214:
		tmp = t_1
	elif c <= -6.8e-258:
		tmp = x * ((y * z) - (t * a))
	elif c <= 9e-283:
		tmp = t_1
	elif (c <= 6e-19) or (not (c <= 2.5e+27) and (c <= 2.6e+112)):
		tmp = y * ((x * z) - (i * j))
	else:
		tmp = c * ((a * j) - (z * b))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(i * Float64(Float64(t * b) - Float64(y * j)))
	tmp = 0.0
	if (c <= -1.1e+147)
		tmp = Float64(b * Float64(Float64(t * i) - Float64(z * c)));
	elseif (c <= -1.7e-85)
		tmp = Float64(a * Float64(Float64(c * j) - Float64(x * t)));
	elseif (c <= -1.1e-214)
		tmp = t_1;
	elseif (c <= -6.8e-258)
		tmp = Float64(x * Float64(Float64(y * z) - Float64(t * a)));
	elseif (c <= 9e-283)
		tmp = t_1;
	elseif ((c <= 6e-19) || (!(c <= 2.5e+27) && (c <= 2.6e+112)))
		tmp = Float64(y * Float64(Float64(x * z) - Float64(i * j)));
	else
		tmp = Float64(c * Float64(Float64(a * j) - Float64(z * b)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = i * ((t * b) - (y * j));
	tmp = 0.0;
	if (c <= -1.1e+147)
		tmp = b * ((t * i) - (z * c));
	elseif (c <= -1.7e-85)
		tmp = a * ((c * j) - (x * t));
	elseif (c <= -1.1e-214)
		tmp = t_1;
	elseif (c <= -6.8e-258)
		tmp = x * ((y * z) - (t * a));
	elseif (c <= 9e-283)
		tmp = t_1;
	elseif ((c <= 6e-19) || (~((c <= 2.5e+27)) && (c <= 2.6e+112)))
		tmp = y * ((x * z) - (i * j));
	else
		tmp = c * ((a * j) - (z * b));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(i * N[(N[(t * b), $MachinePrecision] - N[(y * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[c, -1.1e+147], N[(b * N[(N[(t * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, -1.7e-85], N[(a * N[(N[(c * j), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, -1.1e-214], t$95$1, If[LessEqual[c, -6.8e-258], N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 9e-283], t$95$1, If[Or[LessEqual[c, 6e-19], And[N[Not[LessEqual[c, 2.5e+27]], $MachinePrecision], LessEqual[c, 2.6e+112]]], N[(y * N[(N[(x * z), $MachinePrecision] - N[(i * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(c * N[(N[(a * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]

Derivation

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

Alternative 12: 48.7% accurate, 1.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := i \cdot \left(t \cdot b - y \cdot j\right)\\ t_2 := y \cdot \left(x \cdot z - i \cdot j\right)\\ \mathbf{if}\;c \leq -2.1 \cdot 10^{+148}:\\ \;\;\;\;b \cdot \left(t \cdot i - z \cdot c\right)\\ \mathbf{elif}\;c \leq -1.24 \cdot 10^{-79}:\\ \;\;\;\;a \cdot \left(c \cdot j - x \cdot t\right)\\ \mathbf{elif}\;c \leq -3.3 \cdot 10^{-217}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;c \leq -2.2 \cdot 10^{-258}:\\ \;\;\;\;x \cdot \left(y \cdot z - t \cdot a\right)\\ \mathbf{elif}\;c \leq 1.35 \cdot 10^{-282}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;c \leq 2.5 \cdot 10^{-20}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;c \leq 5.8 \cdot 10^{+26}:\\ \;\;\;\;a \cdot \left(c \cdot j\right) - b \cdot \left(z \cdot c\right)\\ \mathbf{elif}\;c \leq 3.8 \cdot 10^{+109}:\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(a \cdot j - z \cdot b\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* i (- (* t b) (* y j)))) (t_2 (* y (- (* x z) (* i j)))))
   (if (<= c -2.1e+148)
     (* b (- (* t i) (* z c)))
     (if (<= c -1.24e-79)
       (* a (- (* c j) (* x t)))
       (if (<= c -3.3e-217)
         t_1
         (if (<= c -2.2e-258)
           (* x (- (* y z) (* t a)))
           (if (<= c 1.35e-282)
             t_1
             (if (<= c 2.5e-20)
               t_2
               (if (<= c 5.8e+26)
                 (- (* a (* c j)) (* b (* z c)))
                 (if (<= c 3.8e+109) t_2 (* c (- (* a 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 = i * ((t * b) - (y * j));
	double t_2 = y * ((x * z) - (i * j));
	double tmp;
	if (c <= -2.1e+148) {
		tmp = b * ((t * i) - (z * c));
	} else if (c <= -1.24e-79) {
		tmp = a * ((c * j) - (x * t));
	} else if (c <= -3.3e-217) {
		tmp = t_1;
	} else if (c <= -2.2e-258) {
		tmp = x * ((y * z) - (t * a));
	} else if (c <= 1.35e-282) {
		tmp = t_1;
	} else if (c <= 2.5e-20) {
		tmp = t_2;
	} else if (c <= 5.8e+26) {
		tmp = (a * (c * j)) - (b * (z * c));
	} else if (c <= 3.8e+109) {
		tmp = t_2;
	} else {
		tmp = c * ((a * 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) :: tmp
    t_1 = i * ((t * b) - (y * j))
    t_2 = y * ((x * z) - (i * j))
    if (c <= (-2.1d+148)) then
        tmp = b * ((t * i) - (z * c))
    else if (c <= (-1.24d-79)) then
        tmp = a * ((c * j) - (x * t))
    else if (c <= (-3.3d-217)) then
        tmp = t_1
    else if (c <= (-2.2d-258)) then
        tmp = x * ((y * z) - (t * a))
    else if (c <= 1.35d-282) then
        tmp = t_1
    else if (c <= 2.5d-20) then
        tmp = t_2
    else if (c <= 5.8d+26) then
        tmp = (a * (c * j)) - (b * (z * c))
    else if (c <= 3.8d+109) then
        tmp = t_2
    else
        tmp = c * ((a * 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 = i * ((t * b) - (y * j));
	double t_2 = y * ((x * z) - (i * j));
	double tmp;
	if (c <= -2.1e+148) {
		tmp = b * ((t * i) - (z * c));
	} else if (c <= -1.24e-79) {
		tmp = a * ((c * j) - (x * t));
	} else if (c <= -3.3e-217) {
		tmp = t_1;
	} else if (c <= -2.2e-258) {
		tmp = x * ((y * z) - (t * a));
	} else if (c <= 1.35e-282) {
		tmp = t_1;
	} else if (c <= 2.5e-20) {
		tmp = t_2;
	} else if (c <= 5.8e+26) {
		tmp = (a * (c * j)) - (b * (z * c));
	} else if (c <= 3.8e+109) {
		tmp = t_2;
	} else {
		tmp = c * ((a * j) - (z * b));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = i * ((t * b) - (y * j))
	t_2 = y * ((x * z) - (i * j))
	tmp = 0
	if c <= -2.1e+148:
		tmp = b * ((t * i) - (z * c))
	elif c <= -1.24e-79:
		tmp = a * ((c * j) - (x * t))
	elif c <= -3.3e-217:
		tmp = t_1
	elif c <= -2.2e-258:
		tmp = x * ((y * z) - (t * a))
	elif c <= 1.35e-282:
		tmp = t_1
	elif c <= 2.5e-20:
		tmp = t_2
	elif c <= 5.8e+26:
		tmp = (a * (c * j)) - (b * (z * c))
	elif c <= 3.8e+109:
		tmp = t_2
	else:
		tmp = c * ((a * j) - (z * b))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(i * Float64(Float64(t * b) - Float64(y * j)))
	t_2 = Float64(y * Float64(Float64(x * z) - Float64(i * j)))
	tmp = 0.0
	if (c <= -2.1e+148)
		tmp = Float64(b * Float64(Float64(t * i) - Float64(z * c)));
	elseif (c <= -1.24e-79)
		tmp = Float64(a * Float64(Float64(c * j) - Float64(x * t)));
	elseif (c <= -3.3e-217)
		tmp = t_1;
	elseif (c <= -2.2e-258)
		tmp = Float64(x * Float64(Float64(y * z) - Float64(t * a)));
	elseif (c <= 1.35e-282)
		tmp = t_1;
	elseif (c <= 2.5e-20)
		tmp = t_2;
	elseif (c <= 5.8e+26)
		tmp = Float64(Float64(a * Float64(c * j)) - Float64(b * Float64(z * c)));
	elseif (c <= 3.8e+109)
		tmp = t_2;
	else
		tmp = Float64(c * Float64(Float64(a * j) - Float64(z * b)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = i * ((t * b) - (y * j));
	t_2 = y * ((x * z) - (i * j));
	tmp = 0.0;
	if (c <= -2.1e+148)
		tmp = b * ((t * i) - (z * c));
	elseif (c <= -1.24e-79)
		tmp = a * ((c * j) - (x * t));
	elseif (c <= -3.3e-217)
		tmp = t_1;
	elseif (c <= -2.2e-258)
		tmp = x * ((y * z) - (t * a));
	elseif (c <= 1.35e-282)
		tmp = t_1;
	elseif (c <= 2.5e-20)
		tmp = t_2;
	elseif (c <= 5.8e+26)
		tmp = (a * (c * j)) - (b * (z * c));
	elseif (c <= 3.8e+109)
		tmp = t_2;
	else
		tmp = c * ((a * j) - (z * b));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(i * N[(N[(t * b), $MachinePrecision] - N[(y * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(y * N[(N[(x * z), $MachinePrecision] - N[(i * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[c, -2.1e+148], N[(b * N[(N[(t * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, -1.24e-79], N[(a * N[(N[(c * j), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, -3.3e-217], t$95$1, If[LessEqual[c, -2.2e-258], N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 1.35e-282], t$95$1, If[LessEqual[c, 2.5e-20], t$95$2, If[LessEqual[c, 5.8e+26], N[(N[(a * N[(c * j), $MachinePrecision]), $MachinePrecision] - N[(b * N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 3.8e+109], t$95$2, N[(c * N[(N[(a * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]

Derivation

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

Alternative 13: 58.2% accurate, 1.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(t \cdot i - z \cdot c\right)\\ \mathbf{if}\;b \leq -1.6 \cdot 10^{+108}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;b \leq -3.1 \cdot 10^{-23}:\\ \;\;\;\;y \cdot \left(x \cdot z - i \cdot j\right)\\ \mathbf{elif}\;b \leq -1.85 \cdot 10^{-163}:\\ \;\;\;\;a \cdot \left(c \cdot j - x \cdot t\right) - y \cdot \left(i \cdot j\right)\\ \mathbf{elif}\;b \leq 3.9 \cdot 10^{+59}:\\ \;\;\;\;j \cdot \left(a \cdot c - y \cdot i\right) - t \cdot \left(x \cdot a\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* b (- (* t i) (* z c)))))
   (if (<= b -1.6e+108)
     t_1
     (if (<= b -3.1e-23)
       (* y (- (* x z) (* i j)))
       (if (<= b -1.85e-163)
         (- (* a (- (* c j) (* x t))) (* y (* i j)))
         (if (<= b 3.9e+59)
           (- (* j (- (* a c) (* y i))) (* t (* x a)))
           t_1))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = b * ((t * i) - (z * c));
	double tmp;
	if (b <= -1.6e+108) {
		tmp = t_1;
	} else if (b <= -3.1e-23) {
		tmp = y * ((x * z) - (i * j));
	} else if (b <= -1.85e-163) {
		tmp = (a * ((c * j) - (x * t))) - (y * (i * j));
	} else if (b <= 3.9e+59) {
		tmp = (j * ((a * c) - (y * i))) - (t * (x * a));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: tmp
    t_1 = b * ((t * i) - (z * c))
    if (b <= (-1.6d+108)) then
        tmp = t_1
    else if (b <= (-3.1d-23)) then
        tmp = y * ((x * z) - (i * j))
    else if (b <= (-1.85d-163)) then
        tmp = (a * ((c * j) - (x * t))) - (y * (i * j))
    else if (b <= 3.9d+59) then
        tmp = (j * ((a * c) - (y * i))) - (t * (x * a))
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = b * ((t * i) - (z * c));
	double tmp;
	if (b <= -1.6e+108) {
		tmp = t_1;
	} else if (b <= -3.1e-23) {
		tmp = y * ((x * z) - (i * j));
	} else if (b <= -1.85e-163) {
		tmp = (a * ((c * j) - (x * t))) - (y * (i * j));
	} else if (b <= 3.9e+59) {
		tmp = (j * ((a * c) - (y * i))) - (t * (x * a));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = b * ((t * i) - (z * c))
	tmp = 0
	if b <= -1.6e+108:
		tmp = t_1
	elif b <= -3.1e-23:
		tmp = y * ((x * z) - (i * j))
	elif b <= -1.85e-163:
		tmp = (a * ((c * j) - (x * t))) - (y * (i * j))
	elif b <= 3.9e+59:
		tmp = (j * ((a * c) - (y * i))) - (t * (x * a))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(b * Float64(Float64(t * i) - Float64(z * c)))
	tmp = 0.0
	if (b <= -1.6e+108)
		tmp = t_1;
	elseif (b <= -3.1e-23)
		tmp = Float64(y * Float64(Float64(x * z) - Float64(i * j)));
	elseif (b <= -1.85e-163)
		tmp = Float64(Float64(a * Float64(Float64(c * j) - Float64(x * t))) - Float64(y * Float64(i * j)));
	elseif (b <= 3.9e+59)
		tmp = Float64(Float64(j * Float64(Float64(a * c) - Float64(y * i))) - Float64(t * Float64(x * a)));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = b * ((t * i) - (z * c));
	tmp = 0.0;
	if (b <= -1.6e+108)
		tmp = t_1;
	elseif (b <= -3.1e-23)
		tmp = y * ((x * z) - (i * j));
	elseif (b <= -1.85e-163)
		tmp = (a * ((c * j) - (x * t))) - (y * (i * j));
	elseif (b <= 3.9e+59)
		tmp = (j * ((a * c) - (y * i))) - (t * (x * a));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(b * N[(N[(t * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[b, -1.6e+108], t$95$1, If[LessEqual[b, -3.1e-23], N[(y * N[(N[(x * z), $MachinePrecision] - N[(i * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[b, -1.85e-163], N[(N[(a * N[(N[(c * j), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y * N[(i * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[b, 3.9e+59], N[(N[(j * N[(N[(a * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(t * N[(x * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]

Derivation

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

Alternative 14: 63.5% accurate, 1.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y \leq -4.8 \cdot 10^{+145}:\\ \;\;\;\;y \cdot \left(x \cdot z - i \cdot j\right)\\ \mathbf{elif}\;y \leq 9.5 \cdot 10^{-11}:\\ \;\;\;\;b \cdot \left(t \cdot i - z \cdot c\right) + a \cdot \left(c \cdot j - x \cdot t\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(a \cdot c - y \cdot i\right) - t \cdot \left(x \cdot a\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (<= y -4.8e+145)
   (* y (- (* x z) (* i j)))
   (if (<= y 9.5e-11)
     (+ (* b (- (* t i) (* z c))) (* a (- (* c j) (* x t))))
     (- (* j (- (* a c) (* y i))) (* t (* x a))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if (y <= -4.8e+145) {
		tmp = y * ((x * z) - (i * j));
	} else if (y <= 9.5e-11) {
		tmp = (b * ((t * i) - (z * c))) + (a * ((c * j) - (x * t)));
	} else {
		tmp = (j * ((a * c) - (y * i))) - (t * (x * a));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: tmp
    if (y <= (-4.8d+145)) then
        tmp = y * ((x * z) - (i * j))
    else if (y <= 9.5d-11) then
        tmp = (b * ((t * i) - (z * c))) + (a * ((c * j) - (x * t)))
    else
        tmp = (j * ((a * c) - (y * i))) - (t * (x * a))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if (y <= -4.8e+145) {
		tmp = y * ((x * z) - (i * j));
	} else if (y <= 9.5e-11) {
		tmp = (b * ((t * i) - (z * c))) + (a * ((c * j) - (x * t)));
	} else {
		tmp = (j * ((a * c) - (y * i))) - (t * (x * a));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if y <= -4.8e+145:
		tmp = y * ((x * z) - (i * j))
	elif y <= 9.5e-11:
		tmp = (b * ((t * i) - (z * c))) + (a * ((c * j) - (x * t)))
	else:
		tmp = (j * ((a * c) - (y * i))) - (t * (x * a))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if (y <= -4.8e+145)
		tmp = Float64(y * Float64(Float64(x * z) - Float64(i * j)));
	elseif (y <= 9.5e-11)
		tmp = Float64(Float64(b * Float64(Float64(t * i) - Float64(z * c))) + Float64(a * Float64(Float64(c * j) - Float64(x * t))));
	else
		tmp = Float64(Float64(j * Float64(Float64(a * c) - Float64(y * i))) - Float64(t * Float64(x * a)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0;
	if (y <= -4.8e+145)
		tmp = y * ((x * z) - (i * j));
	elseif (y <= 9.5e-11)
		tmp = (b * ((t * i) - (z * c))) + (a * ((c * j) - (x * t)));
	else
		tmp = (j * ((a * c) - (y * i))) - (t * (x * a));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[LessEqual[y, -4.8e+145], N[(y * N[(N[(x * z), $MachinePrecision] - N[(i * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 9.5e-11], N[(N[(b * N[(N[(t * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(a * N[(N[(c * j), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(j * N[(N[(a * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(t * N[(x * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]

Derivation

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

Alternative 15: 50.8% accurate, 1.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot \left(c \cdot j - x \cdot t\right)\\ \mathbf{if}\;a \leq -6.5 \cdot 10^{-54}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 3.5 \cdot 10^{-149}:\\ \;\;\;\;b \cdot \left(t \cdot i - z \cdot c\right)\\ \mathbf{elif}\;a \leq 6.5 \cdot 10^{-91}:\\ \;\;\;\;x \cdot \left(y \cdot z\right)\\ \mathbf{elif}\;a \leq 4.4 \cdot 10^{+44}:\\ \;\;\;\;i \cdot \left(t \cdot b - y \cdot j\right)\\ \mathbf{elif}\;a \leq 2.6 \cdot 10^{+118}:\\ \;\;\;\;j \cdot \left(a \cdot c - y \cdot i\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* a (- (* c j) (* x t)))))
   (if (<= a -6.5e-54)
     t_1
     (if (<= a 3.5e-149)
       (* b (- (* t i) (* z c)))
       (if (<= a 6.5e-91)
         (* x (* y z))
         (if (<= a 4.4e+44)
           (* i (- (* t b) (* y j)))
           (if (<= a 2.6e+118) (* j (- (* a 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 = a * ((c * j) - (x * t));
	double tmp;
	if (a <= -6.5e-54) {
		tmp = t_1;
	} else if (a <= 3.5e-149) {
		tmp = b * ((t * i) - (z * c));
	} else if (a <= 6.5e-91) {
		tmp = x * (y * z);
	} else if (a <= 4.4e+44) {
		tmp = i * ((t * b) - (y * j));
	} else if (a <= 2.6e+118) {
		tmp = j * ((a * 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 = a * ((c * j) - (x * t))
    if (a <= (-6.5d-54)) then
        tmp = t_1
    else if (a <= 3.5d-149) then
        tmp = b * ((t * i) - (z * c))
    else if (a <= 6.5d-91) then
        tmp = x * (y * z)
    else if (a <= 4.4d+44) then
        tmp = i * ((t * b) - (y * j))
    else if (a <= 2.6d+118) then
        tmp = j * ((a * 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 = a * ((c * j) - (x * t));
	double tmp;
	if (a <= -6.5e-54) {
		tmp = t_1;
	} else if (a <= 3.5e-149) {
		tmp = b * ((t * i) - (z * c));
	} else if (a <= 6.5e-91) {
		tmp = x * (y * z);
	} else if (a <= 4.4e+44) {
		tmp = i * ((t * b) - (y * j));
	} else if (a <= 2.6e+118) {
		tmp = j * ((a * c) - (y * i));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = a * ((c * j) - (x * t))
	tmp = 0
	if a <= -6.5e-54:
		tmp = t_1
	elif a <= 3.5e-149:
		tmp = b * ((t * i) - (z * c))
	elif a <= 6.5e-91:
		tmp = x * (y * z)
	elif a <= 4.4e+44:
		tmp = i * ((t * b) - (y * j))
	elif a <= 2.6e+118:
		tmp = j * ((a * c) - (y * i))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(a * Float64(Float64(c * j) - Float64(x * t)))
	tmp = 0.0
	if (a <= -6.5e-54)
		tmp = t_1;
	elseif (a <= 3.5e-149)
		tmp = Float64(b * Float64(Float64(t * i) - Float64(z * c)));
	elseif (a <= 6.5e-91)
		tmp = Float64(x * Float64(y * z));
	elseif (a <= 4.4e+44)
		tmp = Float64(i * Float64(Float64(t * b) - Float64(y * j)));
	elseif (a <= 2.6e+118)
		tmp = Float64(j * Float64(Float64(a * 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 = a * ((c * j) - (x * t));
	tmp = 0.0;
	if (a <= -6.5e-54)
		tmp = t_1;
	elseif (a <= 3.5e-149)
		tmp = b * ((t * i) - (z * c));
	elseif (a <= 6.5e-91)
		tmp = x * (y * z);
	elseif (a <= 4.4e+44)
		tmp = i * ((t * b) - (y * j));
	elseif (a <= 2.6e+118)
		tmp = j * ((a * 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[(a * N[(N[(c * j), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -6.5e-54], t$95$1, If[LessEqual[a, 3.5e-149], N[(b * N[(N[(t * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 6.5e-91], N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 4.4e+44], N[(i * N[(N[(t * b), $MachinePrecision] - N[(y * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 2.6e+118], N[(j * N[(N[(a * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]

Derivation

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

Alternative 16: 59.1% accurate, 1.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;b \leq -2.4 \cdot 10^{+118} \lor \neg \left(b \leq 1.52 \cdot 10^{+59}\right):\\ \;\;\;\;b \cdot \left(t \cdot i - z \cdot c\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(a \cdot c - y \cdot i\right) - t \cdot \left(x \cdot a\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (or (<= b -2.4e+118) (not (<= b 1.52e+59)))
   (* b (- (* t i) (* z c)))
   (- (* j (- (* a c) (* y i))) (* t (* x a)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if ((b <= -2.4e+118) || !(b <= 1.52e+59)) {
		tmp = b * ((t * i) - (z * c));
	} else {
		tmp = (j * ((a * c) - (y * i))) - (t * (x * a));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: tmp
    if ((b <= (-2.4d+118)) .or. (.not. (b <= 1.52d+59))) then
        tmp = b * ((t * i) - (z * c))
    else
        tmp = (j * ((a * c) - (y * i))) - (t * (x * a))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if ((b <= -2.4e+118) || !(b <= 1.52e+59)) {
		tmp = b * ((t * i) - (z * c));
	} else {
		tmp = (j * ((a * c) - (y * i))) - (t * (x * a));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if (b <= -2.4e+118) or not (b <= 1.52e+59):
		tmp = b * ((t * i) - (z * c))
	else:
		tmp = (j * ((a * c) - (y * i))) - (t * (x * a))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if ((b <= -2.4e+118) || !(b <= 1.52e+59))
		tmp = Float64(b * Float64(Float64(t * i) - Float64(z * c)));
	else
		tmp = Float64(Float64(j * Float64(Float64(a * c) - Float64(y * i))) - Float64(t * Float64(x * a)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0;
	if ((b <= -2.4e+118) || ~((b <= 1.52e+59)))
		tmp = b * ((t * i) - (z * c));
	else
		tmp = (j * ((a * c) - (y * i))) - (t * (x * a));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[Or[LessEqual[b, -2.4e+118], N[Not[LessEqual[b, 1.52e+59]], $MachinePrecision]], N[(b * N[(N[(t * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(j * N[(N[(a * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(t * N[(x * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

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

Alternative 17: 30.1% accurate, 1.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y \leq -8 \cdot 10^{+99}:\\ \;\;\;\;x \cdot \left(y \cdot z\right)\\ \mathbf{elif}\;y \leq -4.8 \cdot 10^{-31}:\\ \;\;\;\;c \cdot \left(a \cdot j\right)\\ \mathbf{elif}\;y \leq -4.4 \cdot 10^{-117}:\\ \;\;\;\;b \cdot \left(z \cdot \left(-c\right)\right)\\ \mathbf{elif}\;y \leq 5.1 \cdot 10^{-263}:\\ \;\;\;\;a \cdot \left(t \cdot \left(-x\right)\right)\\ \mathbf{elif}\;y \leq 8.6 \cdot 10^{-176}:\\ \;\;\;\;j \cdot \left(a \cdot c\right)\\ \mathbf{elif}\;y \leq 32500000000:\\ \;\;\;\;x \cdot \left(t \cdot \left(-a\right)\right)\\ \mathbf{else}:\\ \;\;\;\;i \cdot \left(y \cdot \left(-j\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (<= y -8e+99)
   (* x (* y z))
   (if (<= y -4.8e-31)
     (* c (* a j))
     (if (<= y -4.4e-117)
       (* b (* z (- c)))
       (if (<= y 5.1e-263)
         (* a (* t (- x)))
         (if (<= y 8.6e-176)
           (* j (* a c))
           (if (<= y 32500000000.0) (* x (* t (- a))) (* i (* y (- j))))))))))

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 <= -8e+99) {
		tmp = x * (y * z);
	} else if (y <= -4.8e-31) {
		tmp = c * (a * j);
	} else if (y <= -4.4e-117) {
		tmp = b * (z * -c);
	} else if (y <= 5.1e-263) {
		tmp = a * (t * -x);
	} else if (y <= 8.6e-176) {
		tmp = j * (a * c);
	} else if (y <= 32500000000.0) {
		tmp = x * (t * -a);
	} else {
		tmp = i * (y * -j);
	}
	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 <= (-8d+99)) then
        tmp = x * (y * z)
    else if (y <= (-4.8d-31)) then
        tmp = c * (a * j)
    else if (y <= (-4.4d-117)) then
        tmp = b * (z * -c)
    else if (y <= 5.1d-263) then
        tmp = a * (t * -x)
    else if (y <= 8.6d-176) then
        tmp = j * (a * c)
    else if (y <= 32500000000.0d0) then
        tmp = x * (t * -a)
    else
        tmp = i * (y * -j)
    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 <= -8e+99) {
		tmp = x * (y * z);
	} else if (y <= -4.8e-31) {
		tmp = c * (a * j);
	} else if (y <= -4.4e-117) {
		tmp = b * (z * -c);
	} else if (y <= 5.1e-263) {
		tmp = a * (t * -x);
	} else if (y <= 8.6e-176) {
		tmp = j * (a * c);
	} else if (y <= 32500000000.0) {
		tmp = x * (t * -a);
	} else {
		tmp = i * (y * -j);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if y <= -8e+99:
		tmp = x * (y * z)
	elif y <= -4.8e-31:
		tmp = c * (a * j)
	elif y <= -4.4e-117:
		tmp = b * (z * -c)
	elif y <= 5.1e-263:
		tmp = a * (t * -x)
	elif y <= 8.6e-176:
		tmp = j * (a * c)
	elif y <= 32500000000.0:
		tmp = x * (t * -a)
	else:
		tmp = i * (y * -j)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if (y <= -8e+99)
		tmp = Float64(x * Float64(y * z));
	elseif (y <= -4.8e-31)
		tmp = Float64(c * Float64(a * j));
	elseif (y <= -4.4e-117)
		tmp = Float64(b * Float64(z * Float64(-c)));
	elseif (y <= 5.1e-263)
		tmp = Float64(a * Float64(t * Float64(-x)));
	elseif (y <= 8.6e-176)
		tmp = Float64(j * Float64(a * c));
	elseif (y <= 32500000000.0)
		tmp = Float64(x * Float64(t * Float64(-a)));
	else
		tmp = Float64(i * Float64(y * Float64(-j)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0;
	if (y <= -8e+99)
		tmp = x * (y * z);
	elseif (y <= -4.8e-31)
		tmp = c * (a * j);
	elseif (y <= -4.4e-117)
		tmp = b * (z * -c);
	elseif (y <= 5.1e-263)
		tmp = a * (t * -x);
	elseif (y <= 8.6e-176)
		tmp = j * (a * c);
	elseif (y <= 32500000000.0)
		tmp = x * (t * -a);
	else
		tmp = i * (y * -j);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[LessEqual[y, -8e+99], N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -4.8e-31], N[(c * N[(a * j), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -4.4e-117], N[(b * N[(z * (-c)), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 5.1e-263], N[(a * N[(t * (-x)), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 8.6e-176], N[(j * N[(a * c), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 32500000000.0], N[(x * N[(t * (-a)), $MachinePrecision]), $MachinePrecision], N[(i * N[(y * (-j)), $MachinePrecision]), $MachinePrecision]]]]]]]

Derivation

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

Alternative 18: 40.7% accurate, 1.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot \left(c \cdot j - x \cdot t\right)\\ \mathbf{if}\;y \leq -4.5 \cdot 10^{+111}:\\ \;\;\;\;x \cdot \left(y \cdot z\right)\\ \mathbf{elif}\;y \leq 49000000000:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y \leq 3.6 \cdot 10^{+109}:\\ \;\;\;\;i \cdot \left(y \cdot \left(-j\right)\right)\\ \mathbf{elif}\;y \leq 5.8 \cdot 10^{+164}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;\left(i \cdot j\right) \cdot \left(-y\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* a (- (* c j) (* x t)))))
   (if (<= y -4.5e+111)
     (* x (* y z))
     (if (<= y 49000000000.0)
       t_1
       (if (<= y 3.6e+109)
         (* i (* y (- j)))
         (if (<= y 5.8e+164) t_1 (* (* i j) (- y))))))))

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 * ((c * j) - (x * t));
	double tmp;
	if (y <= -4.5e+111) {
		tmp = x * (y * z);
	} else if (y <= 49000000000.0) {
		tmp = t_1;
	} else if (y <= 3.6e+109) {
		tmp = i * (y * -j);
	} else if (y <= 5.8e+164) {
		tmp = t_1;
	} else {
		tmp = (i * j) * -y;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: tmp
    t_1 = a * ((c * j) - (x * t))
    if (y <= (-4.5d+111)) then
        tmp = x * (y * z)
    else if (y <= 49000000000.0d0) then
        tmp = t_1
    else if (y <= 3.6d+109) then
        tmp = i * (y * -j)
    else if (y <= 5.8d+164) then
        tmp = t_1
    else
        tmp = (i * j) * -y
    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 * ((c * j) - (x * t));
	double tmp;
	if (y <= -4.5e+111) {
		tmp = x * (y * z);
	} else if (y <= 49000000000.0) {
		tmp = t_1;
	} else if (y <= 3.6e+109) {
		tmp = i * (y * -j);
	} else if (y <= 5.8e+164) {
		tmp = t_1;
	} else {
		tmp = (i * j) * -y;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = a * ((c * j) - (x * t))
	tmp = 0
	if y <= -4.5e+111:
		tmp = x * (y * z)
	elif y <= 49000000000.0:
		tmp = t_1
	elif y <= 3.6e+109:
		tmp = i * (y * -j)
	elif y <= 5.8e+164:
		tmp = t_1
	else:
		tmp = (i * j) * -y
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(a * Float64(Float64(c * j) - Float64(x * t)))
	tmp = 0.0
	if (y <= -4.5e+111)
		tmp = Float64(x * Float64(y * z));
	elseif (y <= 49000000000.0)
		tmp = t_1;
	elseif (y <= 3.6e+109)
		tmp = Float64(i * Float64(y * Float64(-j)));
	elseif (y <= 5.8e+164)
		tmp = t_1;
	else
		tmp = Float64(Float64(i * j) * Float64(-y));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = a * ((c * j) - (x * t));
	tmp = 0.0;
	if (y <= -4.5e+111)
		tmp = x * (y * z);
	elseif (y <= 49000000000.0)
		tmp = t_1;
	elseif (y <= 3.6e+109)
		tmp = i * (y * -j);
	elseif (y <= 5.8e+164)
		tmp = t_1;
	else
		tmp = (i * j) * -y;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(a * N[(N[(c * j), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y, -4.5e+111], N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 49000000000.0], t$95$1, If[LessEqual[y, 3.6e+109], N[(i * N[(y * (-j)), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 5.8e+164], t$95$1, N[(N[(i * j), $MachinePrecision] * (-y)), $MachinePrecision]]]]]]

Derivation

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

Alternative 19: 50.4% accurate, 1.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(t \cdot i - z \cdot c\right)\\ t_2 := a \cdot \left(c \cdot j - x \cdot t\right)\\ \mathbf{if}\;a \leq -9.8 \cdot 10^{-58}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq 3.5 \cdot 10^{-151}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 8.5 \cdot 10^{-63}:\\ \;\;\;\;x \cdot \left(y \cdot z\right)\\ \mathbf{elif}\;a \leq 3.8 \cdot 10^{+42}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* b (- (* t i) (* z c)))) (t_2 (* a (- (* c j) (* x t)))))
   (if (<= a -9.8e-58)
     t_2
     (if (<= a 3.5e-151)
       t_1
       (if (<= a 8.5e-63) (* x (* y z)) (if (<= a 3.8e+42) 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 = b * ((t * i) - (z * c));
	double t_2 = a * ((c * j) - (x * t));
	double tmp;
	if (a <= -9.8e-58) {
		tmp = t_2;
	} else if (a <= 3.5e-151) {
		tmp = t_1;
	} else if (a <= 8.5e-63) {
		tmp = x * (y * z);
	} else if (a <= 3.8e+42) {
		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 = b * ((t * i) - (z * c))
    t_2 = a * ((c * j) - (x * t))
    if (a <= (-9.8d-58)) then
        tmp = t_2
    else if (a <= 3.5d-151) then
        tmp = t_1
    else if (a <= 8.5d-63) then
        tmp = x * (y * z)
    else if (a <= 3.8d+42) 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 = b * ((t * i) - (z * c));
	double t_2 = a * ((c * j) - (x * t));
	double tmp;
	if (a <= -9.8e-58) {
		tmp = t_2;
	} else if (a <= 3.5e-151) {
		tmp = t_1;
	} else if (a <= 8.5e-63) {
		tmp = x * (y * z);
	} else if (a <= 3.8e+42) {
		tmp = t_1;
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = b * ((t * i) - (z * c))
	t_2 = a * ((c * j) - (x * t))
	tmp = 0
	if a <= -9.8e-58:
		tmp = t_2
	elif a <= 3.5e-151:
		tmp = t_1
	elif a <= 8.5e-63:
		tmp = x * (y * z)
	elif a <= 3.8e+42:
		tmp = t_1
	else:
		tmp = t_2
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(b * Float64(Float64(t * i) - Float64(z * c)))
	t_2 = Float64(a * Float64(Float64(c * j) - Float64(x * t)))
	tmp = 0.0
	if (a <= -9.8e-58)
		tmp = t_2;
	elseif (a <= 3.5e-151)
		tmp = t_1;
	elseif (a <= 8.5e-63)
		tmp = Float64(x * Float64(y * z));
	elseif (a <= 3.8e+42)
		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 = b * ((t * i) - (z * c));
	t_2 = a * ((c * j) - (x * t));
	tmp = 0.0;
	if (a <= -9.8e-58)
		tmp = t_2;
	elseif (a <= 3.5e-151)
		tmp = t_1;
	elseif (a <= 8.5e-63)
		tmp = x * (y * z);
	elseif (a <= 3.8e+42)
		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[(b * N[(N[(t * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(a * N[(N[(c * j), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -9.8e-58], t$95$2, If[LessEqual[a, 3.5e-151], t$95$1, If[LessEqual[a, 8.5e-63], N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 3.8e+42], t$95$1, t$95$2]]]]]]

Derivation

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

Alternative 20: 50.1% accurate, 1.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot \left(c \cdot j - x \cdot t\right)\\ \mathbf{if}\;a \leq -2.8 \cdot 10^{-57}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 1.28 \cdot 10^{-148}:\\ \;\;\;\;b \cdot \left(t \cdot i - z \cdot c\right)\\ \mathbf{elif}\;a \leq 5.2 \cdot 10^{-91}:\\ \;\;\;\;x \cdot \left(y \cdot z\right)\\ \mathbf{elif}\;a \leq 2.8 \cdot 10^{+118}:\\ \;\;\;\;i \cdot \left(t \cdot b - y \cdot j\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* a (- (* c j) (* x t)))))
   (if (<= a -2.8e-57)
     t_1
     (if (<= a 1.28e-148)
       (* b (- (* t i) (* z c)))
       (if (<= a 5.2e-91)
         (* x (* y z))
         (if (<= a 2.8e+118) (* i (- (* t b) (* y 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 = a * ((c * j) - (x * t));
	double tmp;
	if (a <= -2.8e-57) {
		tmp = t_1;
	} else if (a <= 1.28e-148) {
		tmp = b * ((t * i) - (z * c));
	} else if (a <= 5.2e-91) {
		tmp = x * (y * z);
	} else if (a <= 2.8e+118) {
		tmp = i * ((t * b) - (y * 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 = a * ((c * j) - (x * t))
    if (a <= (-2.8d-57)) then
        tmp = t_1
    else if (a <= 1.28d-148) then
        tmp = b * ((t * i) - (z * c))
    else if (a <= 5.2d-91) then
        tmp = x * (y * z)
    else if (a <= 2.8d+118) then
        tmp = i * ((t * b) - (y * 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 = a * ((c * j) - (x * t));
	double tmp;
	if (a <= -2.8e-57) {
		tmp = t_1;
	} else if (a <= 1.28e-148) {
		tmp = b * ((t * i) - (z * c));
	} else if (a <= 5.2e-91) {
		tmp = x * (y * z);
	} else if (a <= 2.8e+118) {
		tmp = i * ((t * b) - (y * j));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = a * ((c * j) - (x * t))
	tmp = 0
	if a <= -2.8e-57:
		tmp = t_1
	elif a <= 1.28e-148:
		tmp = b * ((t * i) - (z * c))
	elif a <= 5.2e-91:
		tmp = x * (y * z)
	elif a <= 2.8e+118:
		tmp = i * ((t * b) - (y * j))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(a * Float64(Float64(c * j) - Float64(x * t)))
	tmp = 0.0
	if (a <= -2.8e-57)
		tmp = t_1;
	elseif (a <= 1.28e-148)
		tmp = Float64(b * Float64(Float64(t * i) - Float64(z * c)));
	elseif (a <= 5.2e-91)
		tmp = Float64(x * Float64(y * z));
	elseif (a <= 2.8e+118)
		tmp = Float64(i * Float64(Float64(t * b) - Float64(y * 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 = a * ((c * j) - (x * t));
	tmp = 0.0;
	if (a <= -2.8e-57)
		tmp = t_1;
	elseif (a <= 1.28e-148)
		tmp = b * ((t * i) - (z * c));
	elseif (a <= 5.2e-91)
		tmp = x * (y * z);
	elseif (a <= 2.8e+118)
		tmp = i * ((t * b) - (y * 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[(a * N[(N[(c * j), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -2.8e-57], t$95$1, If[LessEqual[a, 1.28e-148], N[(b * N[(N[(t * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 5.2e-91], N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 2.8e+118], N[(i * N[(N[(t * b), $MachinePrecision] - N[(y * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]

Derivation

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

Alternative 21: 30.1% accurate, 1.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(t \cdot \left(-a\right)\right)\\ \mathbf{if}\;y \leq -2.5 \cdot 10^{+97}:\\ \;\;\;\;x \cdot \left(y \cdot z\right)\\ \mathbf{elif}\;y \leq -5.8 \cdot 10^{-127}:\\ \;\;\;\;c \cdot \left(a \cdot j\right)\\ \mathbf{elif}\;y \leq 1.7 \cdot 10^{-265}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y \leq 8 \cdot 10^{-176}:\\ \;\;\;\;j \cdot \left(a \cdot c\right)\\ \mathbf{elif}\;y \leq 880000000000:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;i \cdot \left(y \cdot \left(-j\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* x (* t (- a)))))
   (if (<= y -2.5e+97)
     (* x (* y z))
     (if (<= y -5.8e-127)
       (* c (* a j))
       (if (<= y 1.7e-265)
         t_1
         (if (<= y 8e-176)
           (* j (* a c))
           (if (<= y 880000000000.0) t_1 (* i (* y (- j))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = x * (t * -a);
	double tmp;
	if (y <= -2.5e+97) {
		tmp = x * (y * z);
	} else if (y <= -5.8e-127) {
		tmp = c * (a * j);
	} else if (y <= 1.7e-265) {
		tmp = t_1;
	} else if (y <= 8e-176) {
		tmp = j * (a * c);
	} else if (y <= 880000000000.0) {
		tmp = t_1;
	} else {
		tmp = i * (y * -j);
	}
	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 * (t * -a)
    if (y <= (-2.5d+97)) then
        tmp = x * (y * z)
    else if (y <= (-5.8d-127)) then
        tmp = c * (a * j)
    else if (y <= 1.7d-265) then
        tmp = t_1
    else if (y <= 8d-176) then
        tmp = j * (a * c)
    else if (y <= 880000000000.0d0) then
        tmp = t_1
    else
        tmp = i * (y * -j)
    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 * (t * -a);
	double tmp;
	if (y <= -2.5e+97) {
		tmp = x * (y * z);
	} else if (y <= -5.8e-127) {
		tmp = c * (a * j);
	} else if (y <= 1.7e-265) {
		tmp = t_1;
	} else if (y <= 8e-176) {
		tmp = j * (a * c);
	} else if (y <= 880000000000.0) {
		tmp = t_1;
	} else {
		tmp = i * (y * -j);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = x * (t * -a)
	tmp = 0
	if y <= -2.5e+97:
		tmp = x * (y * z)
	elif y <= -5.8e-127:
		tmp = c * (a * j)
	elif y <= 1.7e-265:
		tmp = t_1
	elif y <= 8e-176:
		tmp = j * (a * c)
	elif y <= 880000000000.0:
		tmp = t_1
	else:
		tmp = i * (y * -j)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(x * Float64(t * Float64(-a)))
	tmp = 0.0
	if (y <= -2.5e+97)
		tmp = Float64(x * Float64(y * z));
	elseif (y <= -5.8e-127)
		tmp = Float64(c * Float64(a * j));
	elseif (y <= 1.7e-265)
		tmp = t_1;
	elseif (y <= 8e-176)
		tmp = Float64(j * Float64(a * c));
	elseif (y <= 880000000000.0)
		tmp = t_1;
	else
		tmp = Float64(i * Float64(y * Float64(-j)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = x * (t * -a);
	tmp = 0.0;
	if (y <= -2.5e+97)
		tmp = x * (y * z);
	elseif (y <= -5.8e-127)
		tmp = c * (a * j);
	elseif (y <= 1.7e-265)
		tmp = t_1;
	elseif (y <= 8e-176)
		tmp = j * (a * c);
	elseif (y <= 880000000000.0)
		tmp = t_1;
	else
		tmp = i * (y * -j);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(x * N[(t * (-a)), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y, -2.5e+97], N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -5.8e-127], N[(c * N[(a * j), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 1.7e-265], t$95$1, If[LessEqual[y, 8e-176], N[(j * N[(a * c), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 880000000000.0], t$95$1, N[(i * N[(y * (-j)), $MachinePrecision]), $MachinePrecision]]]]]]]

Derivation

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

Alternative 22: 29.9% accurate, 1.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y \leq -1 \cdot 10^{+97}:\\ \;\;\;\;x \cdot \left(y \cdot z\right)\\ \mathbf{elif}\;y \leq -2.1 \cdot 10^{-128}:\\ \;\;\;\;c \cdot \left(a \cdot j\right)\\ \mathbf{elif}\;y \leq 5.2 \cdot 10^{-266}:\\ \;\;\;\;a \cdot \left(t \cdot \left(-x\right)\right)\\ \mathbf{elif}\;y \leq 1.22 \cdot 10^{-175}:\\ \;\;\;\;j \cdot \left(a \cdot c\right)\\ \mathbf{elif}\;y \leq 25000000000:\\ \;\;\;\;x \cdot \left(t \cdot \left(-a\right)\right)\\ \mathbf{else}:\\ \;\;\;\;i \cdot \left(y \cdot \left(-j\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (<= y -1e+97)
   (* x (* y z))
   (if (<= y -2.1e-128)
     (* c (* a j))
     (if (<= y 5.2e-266)
       (* a (* t (- x)))
       (if (<= y 1.22e-175)
         (* j (* a c))
         (if (<= y 25000000000.0) (* x (* t (- a))) (* i (* y (- j)))))))))

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 <= -1e+97) {
		tmp = x * (y * z);
	} else if (y <= -2.1e-128) {
		tmp = c * (a * j);
	} else if (y <= 5.2e-266) {
		tmp = a * (t * -x);
	} else if (y <= 1.22e-175) {
		tmp = j * (a * c);
	} else if (y <= 25000000000.0) {
		tmp = x * (t * -a);
	} else {
		tmp = i * (y * -j);
	}
	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 <= (-1d+97)) then
        tmp = x * (y * z)
    else if (y <= (-2.1d-128)) then
        tmp = c * (a * j)
    else if (y <= 5.2d-266) then
        tmp = a * (t * -x)
    else if (y <= 1.22d-175) then
        tmp = j * (a * c)
    else if (y <= 25000000000.0d0) then
        tmp = x * (t * -a)
    else
        tmp = i * (y * -j)
    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 <= -1e+97) {
		tmp = x * (y * z);
	} else if (y <= -2.1e-128) {
		tmp = c * (a * j);
	} else if (y <= 5.2e-266) {
		tmp = a * (t * -x);
	} else if (y <= 1.22e-175) {
		tmp = j * (a * c);
	} else if (y <= 25000000000.0) {
		tmp = x * (t * -a);
	} else {
		tmp = i * (y * -j);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if y <= -1e+97:
		tmp = x * (y * z)
	elif y <= -2.1e-128:
		tmp = c * (a * j)
	elif y <= 5.2e-266:
		tmp = a * (t * -x)
	elif y <= 1.22e-175:
		tmp = j * (a * c)
	elif y <= 25000000000.0:
		tmp = x * (t * -a)
	else:
		tmp = i * (y * -j)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if (y <= -1e+97)
		tmp = Float64(x * Float64(y * z));
	elseif (y <= -2.1e-128)
		tmp = Float64(c * Float64(a * j));
	elseif (y <= 5.2e-266)
		tmp = Float64(a * Float64(t * Float64(-x)));
	elseif (y <= 1.22e-175)
		tmp = Float64(j * Float64(a * c));
	elseif (y <= 25000000000.0)
		tmp = Float64(x * Float64(t * Float64(-a)));
	else
		tmp = Float64(i * Float64(y * Float64(-j)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0;
	if (y <= -1e+97)
		tmp = x * (y * z);
	elseif (y <= -2.1e-128)
		tmp = c * (a * j);
	elseif (y <= 5.2e-266)
		tmp = a * (t * -x);
	elseif (y <= 1.22e-175)
		tmp = j * (a * c);
	elseif (y <= 25000000000.0)
		tmp = x * (t * -a);
	else
		tmp = i * (y * -j);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[LessEqual[y, -1e+97], N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -2.1e-128], N[(c * N[(a * j), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 5.2e-266], N[(a * N[(t * (-x)), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 1.22e-175], N[(j * N[(a * c), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 25000000000.0], N[(x * N[(t * (-a)), $MachinePrecision]), $MachinePrecision], N[(i * N[(y * (-j)), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

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

Alternative 23: 50.5% accurate, 1.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := t \cdot \left(b \cdot i - x \cdot a\right)\\ \mathbf{if}\;t \leq -400000000000:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq 2.9 \cdot 10^{+29}:\\ \;\;\;\;j \cdot \left(a \cdot c - y \cdot i\right)\\ \mathbf{elif}\;t \leq 9.5 \cdot 10^{+199}:\\ \;\;\;\;a \cdot \left(c \cdot j - x \cdot t\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* t (- (* b i) (* x a)))))
   (if (<= t -400000000000.0)
     t_1
     (if (<= t 2.9e+29)
       (* j (- (* a c) (* y i)))
       (if (<= t 9.5e+199) (* a (- (* c j) (* x t))) t_1)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = t * ((b * i) - (x * a));
	double tmp;
	if (t <= -400000000000.0) {
		tmp = t_1;
	} else if (t <= 2.9e+29) {
		tmp = j * ((a * c) - (y * i));
	} else if (t <= 9.5e+199) {
		tmp = a * ((c * j) - (x * t));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: tmp
    t_1 = t * ((b * i) - (x * a))
    if (t <= (-400000000000.0d0)) then
        tmp = t_1
    else if (t <= 2.9d+29) then
        tmp = j * ((a * c) - (y * i))
    else if (t <= 9.5d+199) then
        tmp = a * ((c * j) - (x * t))
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = t * ((b * i) - (x * a));
	double tmp;
	if (t <= -400000000000.0) {
		tmp = t_1;
	} else if (t <= 2.9e+29) {
		tmp = j * ((a * c) - (y * i));
	} else if (t <= 9.5e+199) {
		tmp = a * ((c * j) - (x * t));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = t * ((b * i) - (x * a))
	tmp = 0
	if t <= -400000000000.0:
		tmp = t_1
	elif t <= 2.9e+29:
		tmp = j * ((a * c) - (y * i))
	elif t <= 9.5e+199:
		tmp = a * ((c * j) - (x * t))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(t * Float64(Float64(b * i) - Float64(x * a)))
	tmp = 0.0
	if (t <= -400000000000.0)
		tmp = t_1;
	elseif (t <= 2.9e+29)
		tmp = Float64(j * Float64(Float64(a * c) - Float64(y * i)));
	elseif (t <= 9.5e+199)
		tmp = Float64(a * Float64(Float64(c * j) - Float64(x * t)));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = t * ((b * i) - (x * a));
	tmp = 0.0;
	if (t <= -400000000000.0)
		tmp = t_1;
	elseif (t <= 2.9e+29)
		tmp = j * ((a * c) - (y * i));
	elseif (t <= 9.5e+199)
		tmp = a * ((c * j) - (x * t));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(t * N[(N[(b * i), $MachinePrecision] - N[(x * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -400000000000.0], t$95$1, If[LessEqual[t, 2.9e+29], N[(j * N[(N[(a * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 9.5e+199], N[(a * N[(N[(c * j), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]

Derivation

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

Alternative 24: 30.2% accurate, 2.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y \leq -1.26 \cdot 10^{+98}:\\ \;\;\;\;x \cdot \left(y \cdot z\right)\\ \mathbf{elif}\;y \leq -4.7 \cdot 10^{-32}:\\ \;\;\;\;c \cdot \left(a \cdot j\right)\\ \mathbf{elif}\;y \leq -1.5 \cdot 10^{-85}:\\ \;\;\;\;y \cdot \left(x \cdot z\right)\\ \mathbf{elif}\;y \leq 5.5 \cdot 10^{-51}:\\ \;\;\;\;j \cdot \left(a \cdot c\right)\\ \mathbf{else}:\\ \;\;\;\;i \cdot \left(y \cdot \left(-j\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (<= y -1.26e+98)
   (* x (* y z))
   (if (<= y -4.7e-32)
     (* c (* a j))
     (if (<= y -1.5e-85)
       (* y (* x z))
       (if (<= y 5.5e-51) (* j (* a c)) (* i (* y (- j))))))))

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 <= -1.26e+98) {
		tmp = x * (y * z);
	} else if (y <= -4.7e-32) {
		tmp = c * (a * j);
	} else if (y <= -1.5e-85) {
		tmp = y * (x * z);
	} else if (y <= 5.5e-51) {
		tmp = j * (a * c);
	} else {
		tmp = i * (y * -j);
	}
	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 <= (-1.26d+98)) then
        tmp = x * (y * z)
    else if (y <= (-4.7d-32)) then
        tmp = c * (a * j)
    else if (y <= (-1.5d-85)) then
        tmp = y * (x * z)
    else if (y <= 5.5d-51) then
        tmp = j * (a * c)
    else
        tmp = i * (y * -j)
    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 <= -1.26e+98) {
		tmp = x * (y * z);
	} else if (y <= -4.7e-32) {
		tmp = c * (a * j);
	} else if (y <= -1.5e-85) {
		tmp = y * (x * z);
	} else if (y <= 5.5e-51) {
		tmp = j * (a * c);
	} else {
		tmp = i * (y * -j);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if y <= -1.26e+98:
		tmp = x * (y * z)
	elif y <= -4.7e-32:
		tmp = c * (a * j)
	elif y <= -1.5e-85:
		tmp = y * (x * z)
	elif y <= 5.5e-51:
		tmp = j * (a * c)
	else:
		tmp = i * (y * -j)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if (y <= -1.26e+98)
		tmp = Float64(x * Float64(y * z));
	elseif (y <= -4.7e-32)
		tmp = Float64(c * Float64(a * j));
	elseif (y <= -1.5e-85)
		tmp = Float64(y * Float64(x * z));
	elseif (y <= 5.5e-51)
		tmp = Float64(j * Float64(a * c));
	else
		tmp = Float64(i * Float64(y * Float64(-j)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0;
	if (y <= -1.26e+98)
		tmp = x * (y * z);
	elseif (y <= -4.7e-32)
		tmp = c * (a * j);
	elseif (y <= -1.5e-85)
		tmp = y * (x * z);
	elseif (y <= 5.5e-51)
		tmp = j * (a * c);
	else
		tmp = i * (y * -j);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[LessEqual[y, -1.26e+98], N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -4.7e-32], N[(c * N[(a * j), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -1.5e-85], N[(y * N[(x * z), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 5.5e-51], N[(j * N[(a * c), $MachinePrecision]), $MachinePrecision], N[(i * N[(y * (-j)), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

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

Alternative 25: 29.5% accurate, 3.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;c \leq -3.5 \cdot 10^{-23}:\\ \;\;\;\;a \cdot \left(c \cdot j\right)\\ \mathbf{elif}\;c \leq 1.7 \cdot 10^{+79}:\\ \;\;\;\;x \cdot \left(y \cdot z\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(a \cdot c\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (<= c -3.5e-23)
   (* a (* c j))
   (if (<= c 1.7e+79) (* x (* y z)) (* j (* a 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 (c <= -3.5e-23) {
		tmp = a * (c * j);
	} else if (c <= 1.7e+79) {
		tmp = x * (y * z);
	} else {
		tmp = j * (a * 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 (c <= (-3.5d-23)) then
        tmp = a * (c * j)
    else if (c <= 1.7d+79) then
        tmp = x * (y * z)
    else
        tmp = j * (a * 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 (c <= -3.5e-23) {
		tmp = a * (c * j);
	} else if (c <= 1.7e+79) {
		tmp = x * (y * z);
	} else {
		tmp = j * (a * c);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if c <= -3.5e-23:
		tmp = a * (c * j)
	elif c <= 1.7e+79:
		tmp = x * (y * z)
	else:
		tmp = j * (a * c)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if (c <= -3.5e-23)
		tmp = Float64(a * Float64(c * j));
	elseif (c <= 1.7e+79)
		tmp = Float64(x * Float64(y * z));
	else
		tmp = Float64(j * Float64(a * c));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0;
	if (c <= -3.5e-23)
		tmp = a * (c * j);
	elseif (c <= 1.7e+79)
		tmp = x * (y * z);
	else
		tmp = j * (a * c);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[LessEqual[c, -3.5e-23], N[(a * N[(c * j), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 1.7e+79], N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision], N[(j * N[(a * c), $MachinePrecision]), $MachinePrecision]]]

Derivation

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

Alternative 26: 30.1% accurate, 3.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;c \leq -0.00017:\\ \;\;\;\;a \cdot \left(c \cdot j\right)\\ \mathbf{elif}\;c \leq 1.7 \cdot 10^{+75}:\\ \;\;\;\;z \cdot \left(x \cdot y\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(a \cdot c\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (<= c -0.00017)
   (* a (* c j))
   (if (<= c 1.7e+75) (* z (* x y)) (* j (* a 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 (c <= -0.00017) {
		tmp = a * (c * j);
	} else if (c <= 1.7e+75) {
		tmp = z * (x * y);
	} else {
		tmp = j * (a * 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 (c <= (-0.00017d0)) then
        tmp = a * (c * j)
    else if (c <= 1.7d+75) then
        tmp = z * (x * y)
    else
        tmp = j * (a * 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 (c <= -0.00017) {
		tmp = a * (c * j);
	} else if (c <= 1.7e+75) {
		tmp = z * (x * y);
	} else {
		tmp = j * (a * c);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if c <= -0.00017:
		tmp = a * (c * j)
	elif c <= 1.7e+75:
		tmp = z * (x * y)
	else:
		tmp = j * (a * c)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if (c <= -0.00017)
		tmp = Float64(a * Float64(c * j));
	elseif (c <= 1.7e+75)
		tmp = Float64(z * Float64(x * y));
	else
		tmp = Float64(j * Float64(a * c));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0;
	if (c <= -0.00017)
		tmp = a * (c * j);
	elseif (c <= 1.7e+75)
		tmp = z * (x * y);
	else
		tmp = j * (a * c);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[LessEqual[c, -0.00017], N[(a * N[(c * j), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 1.7e+75], N[(z * N[(x * y), $MachinePrecision]), $MachinePrecision], N[(j * N[(a * c), $MachinePrecision]), $MachinePrecision]]]

Derivation

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

Alternative 27: 22.3% accurate, 5.8× speedup

Math

\[\begin{array}{l} \\ a \cdot \left(c \cdot j\right) \end{array} \]

FPCore

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

C

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

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 * (c * j)
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 * (c * j);
}

Python

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

Julia

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

MATLAB

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

Wolfram

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

Derivation

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

Alternative 28: 22.4% accurate, 5.8× speedup

Math

\[\begin{array}{l} \\ c \cdot \left(a \cdot j\right) \end{array} \]

FPCore

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

C

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

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 = c * (a * j)
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 c * (a * j);
}

Python

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

Julia

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

MATLAB

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

Wolfram

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

Derivation

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

Developer target: 58.8% accurate, 0.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(c \cdot a - y \cdot i\right)\\ t_2 := \left(x \cdot \left(y \cdot z - t \cdot a\right) - \frac{b \cdot \left({\left(c \cdot z\right)}^{2} - {\left(t \cdot i\right)}^{2}\right)}{c \cdot z + t \cdot i}\right) + t_1\\ \mathbf{if}\;x < -1.469694296777705 \cdot 10^{-64}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;x < 3.2113527362226803 \cdot 10^{-147}:\\ \;\;\;\;\left(b \cdot i - x \cdot a\right) \cdot t - \left(z \cdot \left(c \cdot b\right) - t_1\right)\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* j (- (* c a) (* y i))))
        (t_2
         (+
          (-
           (* x (- (* y z) (* t a)))
           (/
            (* b (- (pow (* c z) 2.0) (pow (* t i) 2.0)))
            (+ (* c z) (* t i))))
          t_1)))
   (if (< x -1.469694296777705e-64)
     t_2
     (if (< x 3.2113527362226803e-147)
       (- (* (- (* b i) (* x a)) t) (- (* z (* c b)) 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 = j * ((c * a) - (y * i));
	double t_2 = ((x * ((y * z) - (t * a))) - ((b * (pow((c * z), 2.0) - pow((t * i), 2.0))) / ((c * z) + (t * i)))) + t_1;
	double tmp;
	if (x < -1.469694296777705e-64) {
		tmp = t_2;
	} else if (x < 3.2113527362226803e-147) {
		tmp = (((b * i) - (x * a)) * t) - ((z * (c * b)) - 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 = j * ((c * a) - (y * i))
    t_2 = ((x * ((y * z) - (t * a))) - ((b * (((c * z) ** 2.0d0) - ((t * i) ** 2.0d0))) / ((c * z) + (t * i)))) + t_1
    if (x < (-1.469694296777705d-64)) then
        tmp = t_2
    else if (x < 3.2113527362226803d-147) then
        tmp = (((b * i) - (x * a)) * t) - ((z * (c * b)) - 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 = j * ((c * a) - (y * i));
	double t_2 = ((x * ((y * z) - (t * a))) - ((b * (Math.pow((c * z), 2.0) - Math.pow((t * i), 2.0))) / ((c * z) + (t * i)))) + t_1;
	double tmp;
	if (x < -1.469694296777705e-64) {
		tmp = t_2;
	} else if (x < 3.2113527362226803e-147) {
		tmp = (((b * i) - (x * a)) * t) - ((z * (c * b)) - t_1);
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = j * ((c * a) - (y * i))
	t_2 = ((x * ((y * z) - (t * a))) - ((b * (math.pow((c * z), 2.0) - math.pow((t * i), 2.0))) / ((c * z) + (t * i)))) + t_1
	tmp = 0
	if x < -1.469694296777705e-64:
		tmp = t_2
	elif x < 3.2113527362226803e-147:
		tmp = (((b * i) - (x * a)) * t) - ((z * (c * b)) - t_1)
	else:
		tmp = t_2
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(j * Float64(Float64(c * a) - Float64(y * i)))
	t_2 = Float64(Float64(Float64(x * Float64(Float64(y * z) - Float64(t * a))) - Float64(Float64(b * Float64((Float64(c * z) ^ 2.0) - (Float64(t * i) ^ 2.0))) / Float64(Float64(c * z) + Float64(t * i)))) + t_1)
	tmp = 0.0
	if (x < -1.469694296777705e-64)
		tmp = t_2;
	elseif (x < 3.2113527362226803e-147)
		tmp = Float64(Float64(Float64(Float64(b * i) - Float64(x * a)) * t) - Float64(Float64(z * Float64(c * b)) - 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 = j * ((c * a) - (y * i));
	t_2 = ((x * ((y * z) - (t * a))) - ((b * (((c * z) ^ 2.0) - ((t * i) ^ 2.0))) / ((c * z) + (t * i)))) + t_1;
	tmp = 0.0;
	if (x < -1.469694296777705e-64)
		tmp = t_2;
	elseif (x < 3.2113527362226803e-147)
		tmp = (((b * i) - (x * a)) * t) - ((z * (c * b)) - 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[(j * N[(N[(c * a), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(b * N[(N[Power[N[(c * z), $MachinePrecision], 2.0], $MachinePrecision] - N[Power[N[(t * i), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(N[(c * z), $MachinePrecision] + N[(t * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision]}, If[Less[x, -1.469694296777705e-64], t$95$2, If[Less[x, 3.2113527362226803e-147], N[(N[(N[(N[(b * i), $MachinePrecision] - N[(x * a), $MachinePrecision]), $MachinePrecision] * t), $MachinePrecision] - N[(N[(z * N[(c * b), $MachinePrecision]), $MachinePrecision] - t$95$1), $MachinePrecision]), $MachinePrecision], t$95$2]]]]

Reproduce

herbie shell --seed 2023343 
(FPCore (x y z t a b c i j)
  :name "Data.Colour.Matrix:determinant from colour-2.3.3, A"
  :precision binary64

  :herbie-target
  (if (< x -1.469694296777705e-64) (+ (- (* x (- (* y z) (* t a))) (/ (* b (- (pow (* c z) 2.0) (pow (* t i) 2.0))) (+ (* c z) (* t i)))) (* j (- (* c a) (* y i)))) (if (< x 3.2113527362226803e-147) (- (* (- (* b i) (* x a)) t) (- (* z (* c b)) (* j (- (* c a) (* y i))))) (+ (- (* x (- (* y z) (* t a))) (/ (* b (- (pow (* c z) 2.0) (pow (* t i) 2.0))) (+ (* c z) (* t i)))) (* j (- (* c a) (* y i))))))

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