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

Percentage Accurate: 73.6% → 82.1%

Time: 30.2s

Alternatives: 20

Speedup: 0.5×

• 58.0% 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: 73.6% 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: 82.1% accurate, 0.5× speedup

Math

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

FPCore

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

Java

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

Python

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

Julia

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

Derivation

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

Alternative 2: 41.1% accurate, 1.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(y \cdot z\right)\\ t_2 := a \cdot \left(c \cdot j - x \cdot t\right)\\ \mathbf{if}\;a \leq -2.25 \cdot 10^{+55}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq -1.02 \cdot 10^{-21}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -2.1 \cdot 10^{-34}:\\ \;\;\;\;a \cdot \left(c \cdot j\right)\\ \mathbf{elif}\;a \leq -1.15 \cdot 10^{-138}:\\ \;\;\;\;c \cdot \left(z \cdot \left(-b\right)\right)\\ \mathbf{elif}\;a \leq -3.6 \cdot 10^{-202}:\\ \;\;\;\;\left(y \cdot i\right) \cdot \left(-j\right)\\ \mathbf{elif}\;a \leq 2.5 \cdot 10^{-188}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 1.35 \cdot 10^{-18}:\\ \;\;\;\;b \cdot \left(t \cdot i\right)\\ \mathbf{elif}\;a \leq 1.5 \cdot 10^{+43}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* x (* y z))) (t_2 (* a (- (* c j) (* x t)))))
   (if (<= a -2.25e+55)
     t_2
     (if (<= a -1.02e-21)
       t_1
       (if (<= a -2.1e-34)
         (* a (* c j))
         (if (<= a -1.15e-138)
           (* c (* z (- b)))
           (if (<= a -3.6e-202)
             (* (* y i) (- j))
             (if (<= a 2.5e-188)
               t_1
               (if (<= a 1.35e-18)
                 (* b (* t i))
                 (if (<= a 1.5e+43) 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);
	double t_2 = a * ((c * j) - (x * t));
	double tmp;
	if (a <= -2.25e+55) {
		tmp = t_2;
	} else if (a <= -1.02e-21) {
		tmp = t_1;
	} else if (a <= -2.1e-34) {
		tmp = a * (c * j);
	} else if (a <= -1.15e-138) {
		tmp = c * (z * -b);
	} else if (a <= -3.6e-202) {
		tmp = (y * i) * -j;
	} else if (a <= 2.5e-188) {
		tmp = t_1;
	} else if (a <= 1.35e-18) {
		tmp = b * (t * i);
	} else if (a <= 1.5e+43) {
		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_2 = a * ((c * j) - (x * t))
    if (a <= (-2.25d+55)) then
        tmp = t_2
    else if (a <= (-1.02d-21)) then
        tmp = t_1
    else if (a <= (-2.1d-34)) then
        tmp = a * (c * j)
    else if (a <= (-1.15d-138)) then
        tmp = c * (z * -b)
    else if (a <= (-3.6d-202)) then
        tmp = (y * i) * -j
    else if (a <= 2.5d-188) then
        tmp = t_1
    else if (a <= 1.35d-18) then
        tmp = b * (t * i)
    else if (a <= 1.5d+43) 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);
	double t_2 = a * ((c * j) - (x * t));
	double tmp;
	if (a <= -2.25e+55) {
		tmp = t_2;
	} else if (a <= -1.02e-21) {
		tmp = t_1;
	} else if (a <= -2.1e-34) {
		tmp = a * (c * j);
	} else if (a <= -1.15e-138) {
		tmp = c * (z * -b);
	} else if (a <= -3.6e-202) {
		tmp = (y * i) * -j;
	} else if (a <= 2.5e-188) {
		tmp = t_1;
	} else if (a <= 1.35e-18) {
		tmp = b * (t * i);
	} else if (a <= 1.5e+43) {
		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_2 = a * ((c * j) - (x * t))
	tmp = 0
	if a <= -2.25e+55:
		tmp = t_2
	elif a <= -1.02e-21:
		tmp = t_1
	elif a <= -2.1e-34:
		tmp = a * (c * j)
	elif a <= -1.15e-138:
		tmp = c * (z * -b)
	elif a <= -3.6e-202:
		tmp = (y * i) * -j
	elif a <= 2.5e-188:
		tmp = t_1
	elif a <= 1.35e-18:
		tmp = b * (t * i)
	elif a <= 1.5e+43:
		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(y * z))
	t_2 = Float64(a * Float64(Float64(c * j) - Float64(x * t)))
	tmp = 0.0
	if (a <= -2.25e+55)
		tmp = t_2;
	elseif (a <= -1.02e-21)
		tmp = t_1;
	elseif (a <= -2.1e-34)
		tmp = Float64(a * Float64(c * j));
	elseif (a <= -1.15e-138)
		tmp = Float64(c * Float64(z * Float64(-b)));
	elseif (a <= -3.6e-202)
		tmp = Float64(Float64(y * i) * Float64(-j));
	elseif (a <= 2.5e-188)
		tmp = t_1;
	elseif (a <= 1.35e-18)
		tmp = Float64(b * Float64(t * i));
	elseif (a <= 1.5e+43)
		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_2 = a * ((c * j) - (x * t));
	tmp = 0.0;
	if (a <= -2.25e+55)
		tmp = t_2;
	elseif (a <= -1.02e-21)
		tmp = t_1;
	elseif (a <= -2.1e-34)
		tmp = a * (c * j);
	elseif (a <= -1.15e-138)
		tmp = c * (z * -b);
	elseif (a <= -3.6e-202)
		tmp = (y * i) * -j;
	elseif (a <= 2.5e-188)
		tmp = t_1;
	elseif (a <= 1.35e-18)
		tmp = b * (t * i);
	elseif (a <= 1.5e+43)
		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[(y * z), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(a * N[(N[(c * j), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -2.25e+55], t$95$2, If[LessEqual[a, -1.02e-21], t$95$1, If[LessEqual[a, -2.1e-34], N[(a * N[(c * j), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -1.15e-138], N[(c * N[(z * (-b)), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -3.6e-202], N[(N[(y * i), $MachinePrecision] * (-j)), $MachinePrecision], If[LessEqual[a, 2.5e-188], t$95$1, If[LessEqual[a, 1.35e-18], N[(b * N[(t * i), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 1.5e+43], t$95$1, t$95$2]]]]]]]]]]

Derivation

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

Alternative 3: 54.5% accurate, 1.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(y \cdot z - t \cdot a\right)\\ t_2 := c \cdot \left(a \cdot j - z \cdot b\right)\\ \mathbf{if}\;c \leq -4 \cdot 10^{+67}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;c \leq -1.16 \cdot 10^{-177}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;c \leq 5.5 \cdot 10^{-167}:\\ \;\;\;\;y \cdot \left(x \cdot z - i \cdot j\right)\\ \mathbf{elif}\;c \leq 2.65 \cdot 10^{-93}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;c \leq 3.3 \cdot 10^{+76}:\\ \;\;\;\;j \cdot \left(a \cdot c - y \cdot i\right) - b \cdot \left(z \cdot c\right)\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* x (- (* y z) (* t a)))) (t_2 (* c (- (* a j) (* z b)))))
   (if (<= c -4e+67)
     t_2
     (if (<= c -1.16e-177)
       t_1
       (if (<= c 5.5e-167)
         (* y (- (* x z) (* i j)))
         (if (<= c 2.65e-93)
           t_1
           (if (<= c 3.3e+76)
             (- (* j (- (* a c) (* y i))) (* b (* z c)))
             t_2)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = x * ((y * z) - (t * a));
	double t_2 = c * ((a * j) - (z * b));
	double tmp;
	if (c <= -4e+67) {
		tmp = t_2;
	} else if (c <= -1.16e-177) {
		tmp = t_1;
	} else if (c <= 5.5e-167) {
		tmp = y * ((x * z) - (i * j));
	} else if (c <= 2.65e-93) {
		tmp = t_1;
	} else if (c <= 3.3e+76) {
		tmp = (j * ((a * c) - (y * i))) - (b * (z * c));
	} else {
		tmp = t_2;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = x * ((y * z) - (t * a))
    t_2 = c * ((a * j) - (z * b))
    if (c <= (-4d+67)) then
        tmp = t_2
    else if (c <= (-1.16d-177)) then
        tmp = t_1
    else if (c <= 5.5d-167) then
        tmp = y * ((x * z) - (i * j))
    else if (c <= 2.65d-93) then
        tmp = t_1
    else if (c <= 3.3d+76) then
        tmp = (j * ((a * c) - (y * i))) - (b * (z * c))
    else
        tmp = t_2
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = x * ((y * z) - (t * a));
	double t_2 = c * ((a * j) - (z * b));
	double tmp;
	if (c <= -4e+67) {
		tmp = t_2;
	} else if (c <= -1.16e-177) {
		tmp = t_1;
	} else if (c <= 5.5e-167) {
		tmp = y * ((x * z) - (i * j));
	} else if (c <= 2.65e-93) {
		tmp = t_1;
	} else if (c <= 3.3e+76) {
		tmp = (j * ((a * c) - (y * i))) - (b * (z * c));
	} 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 = c * ((a * j) - (z * b))
	tmp = 0
	if c <= -4e+67:
		tmp = t_2
	elif c <= -1.16e-177:
		tmp = t_1
	elif c <= 5.5e-167:
		tmp = y * ((x * z) - (i * j))
	elif c <= 2.65e-93:
		tmp = t_1
	elif c <= 3.3e+76:
		tmp = (j * ((a * c) - (y * i))) - (b * (z * c))
	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(c * Float64(Float64(a * j) - Float64(z * b)))
	tmp = 0.0
	if (c <= -4e+67)
		tmp = t_2;
	elseif (c <= -1.16e-177)
		tmp = t_1;
	elseif (c <= 5.5e-167)
		tmp = Float64(y * Float64(Float64(x * z) - Float64(i * j)));
	elseif (c <= 2.65e-93)
		tmp = t_1;
	elseif (c <= 3.3e+76)
		tmp = Float64(Float64(j * Float64(Float64(a * c) - Float64(y * i))) - Float64(b * Float64(z * c)));
	else
		tmp = t_2;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = x * ((y * z) - (t * a));
	t_2 = c * ((a * j) - (z * b));
	tmp = 0.0;
	if (c <= -4e+67)
		tmp = t_2;
	elseif (c <= -1.16e-177)
		tmp = t_1;
	elseif (c <= 5.5e-167)
		tmp = y * ((x * z) - (i * j));
	elseif (c <= 2.65e-93)
		tmp = t_1;
	elseif (c <= 3.3e+76)
		tmp = (j * ((a * c) - (y * i))) - (b * (z * c));
	else
		tmp = t_2;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(c * N[(N[(a * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[c, -4e+67], t$95$2, If[LessEqual[c, -1.16e-177], t$95$1, If[LessEqual[c, 5.5e-167], N[(y * N[(N[(x * z), $MachinePrecision] - N[(i * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 2.65e-93], t$95$1, If[LessEqual[c, 3.3e+76], N[(N[(j * N[(N[(a * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(b * N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$2]]]]]]]

Derivation

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

Alternative 4: 64.3% accurate, 1.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := c \cdot \left(a \cdot j - z \cdot b\right)\\ \mathbf{if}\;c \leq -3.9 \cdot 10^{+92}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;c \leq 5.5 \cdot 10^{-79}:\\ \;\;\;\;y \cdot \left(x \cdot z - i \cdot j\right) - a \cdot \left(x \cdot t - c \cdot j\right)\\ \mathbf{elif}\;c \leq 1.2 \cdot 10^{+66}:\\ \;\;\;\;x \cdot \left(y \cdot z - t \cdot a\right) + b \cdot \left(t \cdot i - z \cdot c\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* c (- (* a j) (* z b)))))
   (if (<= c -3.9e+92)
     t_1
     (if (<= c 5.5e-79)
       (- (* y (- (* x z) (* i j))) (* a (- (* x t) (* c j))))
       (if (<= c 1.2e+66)
         (+ (* x (- (* y z) (* t a))) (* b (- (* t i) (* z c))))
         t_1)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = c * ((a * j) - (z * b));
	double tmp;
	if (c <= -3.9e+92) {
		tmp = t_1;
	} else if (c <= 5.5e-79) {
		tmp = (y * ((x * z) - (i * j))) - (a * ((x * t) - (c * j)));
	} else if (c <= 1.2e+66) {
		tmp = (x * ((y * z) - (t * a))) + (b * ((t * i) - (z * c)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: tmp
    t_1 = c * ((a * j) - (z * b))
    if (c <= (-3.9d+92)) then
        tmp = t_1
    else if (c <= 5.5d-79) then
        tmp = (y * ((x * z) - (i * j))) - (a * ((x * t) - (c * j)))
    else if (c <= 1.2d+66) then
        tmp = (x * ((y * z) - (t * a))) + (b * ((t * i) - (z * c)))
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = c * ((a * j) - (z * b));
	double tmp;
	if (c <= -3.9e+92) {
		tmp = t_1;
	} else if (c <= 5.5e-79) {
		tmp = (y * ((x * z) - (i * j))) - (a * ((x * t) - (c * j)));
	} else if (c <= 1.2e+66) {
		tmp = (x * ((y * z) - (t * a))) + (b * ((t * i) - (z * c)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = c * ((a * j) - (z * b))
	tmp = 0
	if c <= -3.9e+92:
		tmp = t_1
	elif c <= 5.5e-79:
		tmp = (y * ((x * z) - (i * j))) - (a * ((x * t) - (c * j)))
	elif c <= 1.2e+66:
		tmp = (x * ((y * z) - (t * a))) + (b * ((t * i) - (z * c)))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(c * Float64(Float64(a * j) - Float64(z * b)))
	tmp = 0.0
	if (c <= -3.9e+92)
		tmp = t_1;
	elseif (c <= 5.5e-79)
		tmp = Float64(Float64(y * Float64(Float64(x * z) - Float64(i * j))) - Float64(a * Float64(Float64(x * t) - Float64(c * j))));
	elseif (c <= 1.2e+66)
		tmp = Float64(Float64(x * Float64(Float64(y * z) - Float64(t * a))) + Float64(b * Float64(Float64(t * i) - Float64(z * c))));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = c * ((a * j) - (z * b));
	tmp = 0.0;
	if (c <= -3.9e+92)
		tmp = t_1;
	elseif (c <= 5.5e-79)
		tmp = (y * ((x * z) - (i * j))) - (a * ((x * t) - (c * j)));
	elseif (c <= 1.2e+66)
		tmp = (x * ((y * z) - (t * a))) + (b * ((t * i) - (z * c)));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(c * N[(N[(a * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[c, -3.9e+92], t$95$1, If[LessEqual[c, 5.5e-79], N[(N[(y * N[(N[(x * z), $MachinePrecision] - N[(i * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(a * N[(N[(x * t), $MachinePrecision] - N[(c * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 1.2e+66], 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], t$95$1]]]]

Derivation

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

Alternative 5: 64.6% accurate, 1.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;c \leq -7.2 \cdot 10^{+66} \lor \neg \left(c \leq 5.6 \cdot 10^{+70}\right):\\ \;\;\;\;c \cdot \left(a \cdot j - z \cdot b\right)\\ \mathbf{else}:\\ \;\;\;\;x \cdot \left(y \cdot z - t \cdot a\right) + b \cdot \left(t \cdot i - z \cdot c\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (or (<= c -7.2e+66) (not (<= c 5.6e+70)))
   (* c (- (* a j) (* z b)))
   (+ (* x (- (* y z) (* t a))) (* b (- (* t i) (* z c))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if ((c <= -7.2e+66) || !(c <= 5.6e+70)) {
		tmp = c * ((a * j) - (z * b));
	} else {
		tmp = (x * ((y * z) - (t * a))) + (b * ((t * i) - (z * c)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: tmp
    if ((c <= (-7.2d+66)) .or. (.not. (c <= 5.6d+70))) then
        tmp = c * ((a * j) - (z * b))
    else
        tmp = (x * ((y * z) - (t * a))) + (b * ((t * i) - (z * c)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if ((c <= -7.2e+66) || !(c <= 5.6e+70)) {
		tmp = c * ((a * j) - (z * b));
	} else {
		tmp = (x * ((y * z) - (t * a))) + (b * ((t * i) - (z * c)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if (c <= -7.2e+66) or not (c <= 5.6e+70):
		tmp = c * ((a * j) - (z * b))
	else:
		tmp = (x * ((y * z) - (t * a))) + (b * ((t * i) - (z * c)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if ((c <= -7.2e+66) || !(c <= 5.6e+70))
		tmp = Float64(c * Float64(Float64(a * j) - Float64(z * b)));
	else
		tmp = Float64(Float64(x * Float64(Float64(y * z) - Float64(t * a))) + Float64(b * Float64(Float64(t * i) - Float64(z * c))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0;
	if ((c <= -7.2e+66) || ~((c <= 5.6e+70)))
		tmp = c * ((a * j) - (z * b));
	else
		tmp = (x * ((y * z) - (t * a))) + (b * ((t * i) - (z * c)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[Or[LessEqual[c, -7.2e+66], N[Not[LessEqual[c, 5.6e+70]], $MachinePrecision]], N[(c * N[(N[(a * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 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]]

Derivation

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

Alternative 6: 30.2% accurate, 1.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(y \cdot z\right)\\ t_2 := j \cdot \left(a \cdot c\right)\\ \mathbf{if}\;a \leq -4 \cdot 10^{+59}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq -5.3 \cdot 10^{-36}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -2.2 \cdot 10^{-138}:\\ \;\;\;\;c \cdot \left(z \cdot \left(-b\right)\right)\\ \mathbf{elif}\;a \leq -5.8 \cdot 10^{-202}:\\ \;\;\;\;\left(y \cdot i\right) \cdot \left(-j\right)\\ \mathbf{elif}\;a \leq 1.9 \cdot 10^{-188}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 1.3 \cdot 10^{-18}:\\ \;\;\;\;b \cdot \left(t \cdot i\right)\\ \mathbf{elif}\;a \leq 6.8 \cdot 10^{+43}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 1.55 \cdot 10^{+195}:\\ \;\;\;\;a \cdot \left(t \cdot \left(-x\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* x (* y z))) (t_2 (* j (* a c))))
   (if (<= a -4e+59)
     t_2
     (if (<= a -5.3e-36)
       t_1
       (if (<= a -2.2e-138)
         (* c (* z (- b)))
         (if (<= a -5.8e-202)
           (* (* y i) (- j))
           (if (<= a 1.9e-188)
             t_1
             (if (<= a 1.3e-18)
               (* b (* t i))
               (if (<= a 6.8e+43)
                 t_1
                 (if (<= a 1.55e+195) (* a (* t (- x))) 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);
	double t_2 = j * (a * c);
	double tmp;
	if (a <= -4e+59) {
		tmp = t_2;
	} else if (a <= -5.3e-36) {
		tmp = t_1;
	} else if (a <= -2.2e-138) {
		tmp = c * (z * -b);
	} else if (a <= -5.8e-202) {
		tmp = (y * i) * -j;
	} else if (a <= 1.9e-188) {
		tmp = t_1;
	} else if (a <= 1.3e-18) {
		tmp = b * (t * i);
	} else if (a <= 6.8e+43) {
		tmp = t_1;
	} else if (a <= 1.55e+195) {
		tmp = a * (t * -x);
	} 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_2 = j * (a * c)
    if (a <= (-4d+59)) then
        tmp = t_2
    else if (a <= (-5.3d-36)) then
        tmp = t_1
    else if (a <= (-2.2d-138)) then
        tmp = c * (z * -b)
    else if (a <= (-5.8d-202)) then
        tmp = (y * i) * -j
    else if (a <= 1.9d-188) then
        tmp = t_1
    else if (a <= 1.3d-18) then
        tmp = b * (t * i)
    else if (a <= 6.8d+43) then
        tmp = t_1
    else if (a <= 1.55d+195) then
        tmp = a * (t * -x)
    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);
	double t_2 = j * (a * c);
	double tmp;
	if (a <= -4e+59) {
		tmp = t_2;
	} else if (a <= -5.3e-36) {
		tmp = t_1;
	} else if (a <= -2.2e-138) {
		tmp = c * (z * -b);
	} else if (a <= -5.8e-202) {
		tmp = (y * i) * -j;
	} else if (a <= 1.9e-188) {
		tmp = t_1;
	} else if (a <= 1.3e-18) {
		tmp = b * (t * i);
	} else if (a <= 6.8e+43) {
		tmp = t_1;
	} else if (a <= 1.55e+195) {
		tmp = a * (t * -x);
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = x * (y * z)
	t_2 = j * (a * c)
	tmp = 0
	if a <= -4e+59:
		tmp = t_2
	elif a <= -5.3e-36:
		tmp = t_1
	elif a <= -2.2e-138:
		tmp = c * (z * -b)
	elif a <= -5.8e-202:
		tmp = (y * i) * -j
	elif a <= 1.9e-188:
		tmp = t_1
	elif a <= 1.3e-18:
		tmp = b * (t * i)
	elif a <= 6.8e+43:
		tmp = t_1
	elif a <= 1.55e+195:
		tmp = a * (t * -x)
	else:
		tmp = t_2
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(x * Float64(y * z))
	t_2 = Float64(j * Float64(a * c))
	tmp = 0.0
	if (a <= -4e+59)
		tmp = t_2;
	elseif (a <= -5.3e-36)
		tmp = t_1;
	elseif (a <= -2.2e-138)
		tmp = Float64(c * Float64(z * Float64(-b)));
	elseif (a <= -5.8e-202)
		tmp = Float64(Float64(y * i) * Float64(-j));
	elseif (a <= 1.9e-188)
		tmp = t_1;
	elseif (a <= 1.3e-18)
		tmp = Float64(b * Float64(t * i));
	elseif (a <= 6.8e+43)
		tmp = t_1;
	elseif (a <= 1.55e+195)
		tmp = Float64(a * Float64(t * Float64(-x)));
	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_2 = j * (a * c);
	tmp = 0.0;
	if (a <= -4e+59)
		tmp = t_2;
	elseif (a <= -5.3e-36)
		tmp = t_1;
	elseif (a <= -2.2e-138)
		tmp = c * (z * -b);
	elseif (a <= -5.8e-202)
		tmp = (y * i) * -j;
	elseif (a <= 1.9e-188)
		tmp = t_1;
	elseif (a <= 1.3e-18)
		tmp = b * (t * i);
	elseif (a <= 6.8e+43)
		tmp = t_1;
	elseif (a <= 1.55e+195)
		tmp = a * (t * -x);
	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[(y * z), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(j * N[(a * c), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -4e+59], t$95$2, If[LessEqual[a, -5.3e-36], t$95$1, If[LessEqual[a, -2.2e-138], N[(c * N[(z * (-b)), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -5.8e-202], N[(N[(y * i), $MachinePrecision] * (-j)), $MachinePrecision], If[LessEqual[a, 1.9e-188], t$95$1, If[LessEqual[a, 1.3e-18], N[(b * N[(t * i), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 6.8e+43], t$95$1, If[LessEqual[a, 1.55e+195], N[(a * N[(t * (-x)), $MachinePrecision]), $MachinePrecision], t$95$2]]]]]]]]]]

Derivation

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

Alternative 7: 30.4% accurate, 1.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(y \cdot z\right)\\ t_2 := j \cdot \left(a \cdot c\right)\\ \mathbf{if}\;a \leq -5.5 \cdot 10^{+59}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq -3.8 \cdot 10^{-35}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -1.6 \cdot 10^{-138}:\\ \;\;\;\;c \cdot \left(z \cdot \left(-b\right)\right)\\ \mathbf{elif}\;a \leq -1 \cdot 10^{-201}:\\ \;\;\;\;\left(y \cdot i\right) \cdot \left(-j\right)\\ \mathbf{elif}\;a \leq 1.3 \cdot 10^{-187}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 1.6 \cdot 10^{-15}:\\ \;\;\;\;b \cdot \left(t \cdot i\right)\\ \mathbf{elif}\;a \leq 7.8 \cdot 10^{+43}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 2.5 \cdot 10^{+194}:\\ \;\;\;\;x \cdot \left(t \cdot \left(-a\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* x (* y z))) (t_2 (* j (* a c))))
   (if (<= a -5.5e+59)
     t_2
     (if (<= a -3.8e-35)
       t_1
       (if (<= a -1.6e-138)
         (* c (* z (- b)))
         (if (<= a -1e-201)
           (* (* y i) (- j))
           (if (<= a 1.3e-187)
             t_1
             (if (<= a 1.6e-15)
               (* b (* t i))
               (if (<= a 7.8e+43)
                 t_1
                 (if (<= a 2.5e+194) (* x (* t (- a))) 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);
	double t_2 = j * (a * c);
	double tmp;
	if (a <= -5.5e+59) {
		tmp = t_2;
	} else if (a <= -3.8e-35) {
		tmp = t_1;
	} else if (a <= -1.6e-138) {
		tmp = c * (z * -b);
	} else if (a <= -1e-201) {
		tmp = (y * i) * -j;
	} else if (a <= 1.3e-187) {
		tmp = t_1;
	} else if (a <= 1.6e-15) {
		tmp = b * (t * i);
	} else if (a <= 7.8e+43) {
		tmp = t_1;
	} else if (a <= 2.5e+194) {
		tmp = x * (t * -a);
	} 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_2 = j * (a * c)
    if (a <= (-5.5d+59)) then
        tmp = t_2
    else if (a <= (-3.8d-35)) then
        tmp = t_1
    else if (a <= (-1.6d-138)) then
        tmp = c * (z * -b)
    else if (a <= (-1d-201)) then
        tmp = (y * i) * -j
    else if (a <= 1.3d-187) then
        tmp = t_1
    else if (a <= 1.6d-15) then
        tmp = b * (t * i)
    else if (a <= 7.8d+43) then
        tmp = t_1
    else if (a <= 2.5d+194) then
        tmp = x * (t * -a)
    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);
	double t_2 = j * (a * c);
	double tmp;
	if (a <= -5.5e+59) {
		tmp = t_2;
	} else if (a <= -3.8e-35) {
		tmp = t_1;
	} else if (a <= -1.6e-138) {
		tmp = c * (z * -b);
	} else if (a <= -1e-201) {
		tmp = (y * i) * -j;
	} else if (a <= 1.3e-187) {
		tmp = t_1;
	} else if (a <= 1.6e-15) {
		tmp = b * (t * i);
	} else if (a <= 7.8e+43) {
		tmp = t_1;
	} else if (a <= 2.5e+194) {
		tmp = x * (t * -a);
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = x * (y * z)
	t_2 = j * (a * c)
	tmp = 0
	if a <= -5.5e+59:
		tmp = t_2
	elif a <= -3.8e-35:
		tmp = t_1
	elif a <= -1.6e-138:
		tmp = c * (z * -b)
	elif a <= -1e-201:
		tmp = (y * i) * -j
	elif a <= 1.3e-187:
		tmp = t_1
	elif a <= 1.6e-15:
		tmp = b * (t * i)
	elif a <= 7.8e+43:
		tmp = t_1
	elif a <= 2.5e+194:
		tmp = x * (t * -a)
	else:
		tmp = t_2
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(x * Float64(y * z))
	t_2 = Float64(j * Float64(a * c))
	tmp = 0.0
	if (a <= -5.5e+59)
		tmp = t_2;
	elseif (a <= -3.8e-35)
		tmp = t_1;
	elseif (a <= -1.6e-138)
		tmp = Float64(c * Float64(z * Float64(-b)));
	elseif (a <= -1e-201)
		tmp = Float64(Float64(y * i) * Float64(-j));
	elseif (a <= 1.3e-187)
		tmp = t_1;
	elseif (a <= 1.6e-15)
		tmp = Float64(b * Float64(t * i));
	elseif (a <= 7.8e+43)
		tmp = t_1;
	elseif (a <= 2.5e+194)
		tmp = Float64(x * Float64(t * Float64(-a)));
	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_2 = j * (a * c);
	tmp = 0.0;
	if (a <= -5.5e+59)
		tmp = t_2;
	elseif (a <= -3.8e-35)
		tmp = t_1;
	elseif (a <= -1.6e-138)
		tmp = c * (z * -b);
	elseif (a <= -1e-201)
		tmp = (y * i) * -j;
	elseif (a <= 1.3e-187)
		tmp = t_1;
	elseif (a <= 1.6e-15)
		tmp = b * (t * i);
	elseif (a <= 7.8e+43)
		tmp = t_1;
	elseif (a <= 2.5e+194)
		tmp = x * (t * -a);
	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[(y * z), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(j * N[(a * c), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -5.5e+59], t$95$2, If[LessEqual[a, -3.8e-35], t$95$1, If[LessEqual[a, -1.6e-138], N[(c * N[(z * (-b)), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -1e-201], N[(N[(y * i), $MachinePrecision] * (-j)), $MachinePrecision], If[LessEqual[a, 1.3e-187], t$95$1, If[LessEqual[a, 1.6e-15], N[(b * N[(t * i), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 7.8e+43], t$95$1, If[LessEqual[a, 2.5e+194], N[(x * N[(t * (-a)), $MachinePrecision]), $MachinePrecision], t$95$2]]]]]]]]]]

Derivation

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

Alternative 8: 29.8% accurate, 1.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(y \cdot z\right)\\ t_2 := j \cdot \left(a \cdot c\right)\\ \mathbf{if}\;a \leq -2.7 \cdot 10^{+70}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq -1.1 \cdot 10^{-35}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -1.2 \cdot 10^{-138}:\\ \;\;\;\;b \cdot \left(z \cdot \left(-c\right)\right)\\ \mathbf{elif}\;a \leq 7.5 \cdot 10^{-188}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 6.5 \cdot 10^{-14}:\\ \;\;\;\;b \cdot \left(t \cdot i\right)\\ \mathbf{elif}\;a \leq 1.45 \cdot 10^{+44}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 2.4 \cdot 10^{+194}:\\ \;\;\;\;a \cdot \left(x \cdot \left(-t\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* x (* y z))) (t_2 (* j (* a c))))
   (if (<= a -2.7e+70)
     t_2
     (if (<= a -1.1e-35)
       t_1
       (if (<= a -1.2e-138)
         (* b (* z (- c)))
         (if (<= a 7.5e-188)
           t_1
           (if (<= a 6.5e-14)
             (* b (* t i))
             (if (<= a 1.45e+44)
               t_1
               (if (<= a 2.4e+194) (* a (* x (- t))) t_2)))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = x * (y * z);
	double t_2 = j * (a * c);
	double tmp;
	if (a <= -2.7e+70) {
		tmp = t_2;
	} else if (a <= -1.1e-35) {
		tmp = t_1;
	} else if (a <= -1.2e-138) {
		tmp = b * (z * -c);
	} else if (a <= 7.5e-188) {
		tmp = t_1;
	} else if (a <= 6.5e-14) {
		tmp = b * (t * i);
	} else if (a <= 1.45e+44) {
		tmp = t_1;
	} else if (a <= 2.4e+194) {
		tmp = a * (x * -t);
	} else {
		tmp = t_2;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = x * (y * z)
    t_2 = j * (a * c)
    if (a <= (-2.7d+70)) then
        tmp = t_2
    else if (a <= (-1.1d-35)) then
        tmp = t_1
    else if (a <= (-1.2d-138)) then
        tmp = b * (z * -c)
    else if (a <= 7.5d-188) then
        tmp = t_1
    else if (a <= 6.5d-14) then
        tmp = b * (t * i)
    else if (a <= 1.45d+44) then
        tmp = t_1
    else if (a <= 2.4d+194) then
        tmp = a * (x * -t)
    else
        tmp = t_2
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = x * (y * z);
	double t_2 = j * (a * c);
	double tmp;
	if (a <= -2.7e+70) {
		tmp = t_2;
	} else if (a <= -1.1e-35) {
		tmp = t_1;
	} else if (a <= -1.2e-138) {
		tmp = b * (z * -c);
	} else if (a <= 7.5e-188) {
		tmp = t_1;
	} else if (a <= 6.5e-14) {
		tmp = b * (t * i);
	} else if (a <= 1.45e+44) {
		tmp = t_1;
	} else if (a <= 2.4e+194) {
		tmp = a * (x * -t);
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = x * (y * z)
	t_2 = j * (a * c)
	tmp = 0
	if a <= -2.7e+70:
		tmp = t_2
	elif a <= -1.1e-35:
		tmp = t_1
	elif a <= -1.2e-138:
		tmp = b * (z * -c)
	elif a <= 7.5e-188:
		tmp = t_1
	elif a <= 6.5e-14:
		tmp = b * (t * i)
	elif a <= 1.45e+44:
		tmp = t_1
	elif a <= 2.4e+194:
		tmp = a * (x * -t)
	else:
		tmp = t_2
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(x * Float64(y * z))
	t_2 = Float64(j * Float64(a * c))
	tmp = 0.0
	if (a <= -2.7e+70)
		tmp = t_2;
	elseif (a <= -1.1e-35)
		tmp = t_1;
	elseif (a <= -1.2e-138)
		tmp = Float64(b * Float64(z * Float64(-c)));
	elseif (a <= 7.5e-188)
		tmp = t_1;
	elseif (a <= 6.5e-14)
		tmp = Float64(b * Float64(t * i));
	elseif (a <= 1.45e+44)
		tmp = t_1;
	elseif (a <= 2.4e+194)
		tmp = Float64(a * Float64(x * Float64(-t)));
	else
		tmp = t_2;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = x * (y * z);
	t_2 = j * (a * c);
	tmp = 0.0;
	if (a <= -2.7e+70)
		tmp = t_2;
	elseif (a <= -1.1e-35)
		tmp = t_1;
	elseif (a <= -1.2e-138)
		tmp = b * (z * -c);
	elseif (a <= 7.5e-188)
		tmp = t_1;
	elseif (a <= 6.5e-14)
		tmp = b * (t * i);
	elseif (a <= 1.45e+44)
		tmp = t_1;
	elseif (a <= 2.4e+194)
		tmp = a * (x * -t);
	else
		tmp = t_2;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(j * N[(a * c), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -2.7e+70], t$95$2, If[LessEqual[a, -1.1e-35], t$95$1, If[LessEqual[a, -1.2e-138], N[(b * N[(z * (-c)), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 7.5e-188], t$95$1, If[LessEqual[a, 6.5e-14], N[(b * N[(t * i), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 1.45e+44], t$95$1, If[LessEqual[a, 2.4e+194], N[(a * N[(x * (-t)), $MachinePrecision]), $MachinePrecision], t$95$2]]]]]]]]]

Derivation

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

Alternative 9: 29.9% accurate, 1.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(y \cdot z\right)\\ t_2 := j \cdot \left(a \cdot c\right)\\ \mathbf{if}\;a \leq -6.6 \cdot 10^{+57}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq -1.55 \cdot 10^{-36}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -2.2 \cdot 10^{-138}:\\ \;\;\;\;c \cdot \left(z \cdot \left(-b\right)\right)\\ \mathbf{elif}\;a \leq 3.8 \cdot 10^{-188}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 5.5 \cdot 10^{-13}:\\ \;\;\;\;b \cdot \left(t \cdot i\right)\\ \mathbf{elif}\;a \leq 8 \cdot 10^{+43}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 3.2 \cdot 10^{+194}:\\ \;\;\;\;a \cdot \left(x \cdot \left(-t\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* x (* y z))) (t_2 (* j (* a c))))
   (if (<= a -6.6e+57)
     t_2
     (if (<= a -1.55e-36)
       t_1
       (if (<= a -2.2e-138)
         (* c (* z (- b)))
         (if (<= a 3.8e-188)
           t_1
           (if (<= a 5.5e-13)
             (* b (* t i))
             (if (<= a 8e+43)
               t_1
               (if (<= a 3.2e+194) (* a (* x (- t))) t_2)))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = x * (y * z);
	double t_2 = j * (a * c);
	double tmp;
	if (a <= -6.6e+57) {
		tmp = t_2;
	} else if (a <= -1.55e-36) {
		tmp = t_1;
	} else if (a <= -2.2e-138) {
		tmp = c * (z * -b);
	} else if (a <= 3.8e-188) {
		tmp = t_1;
	} else if (a <= 5.5e-13) {
		tmp = b * (t * i);
	} else if (a <= 8e+43) {
		tmp = t_1;
	} else if (a <= 3.2e+194) {
		tmp = a * (x * -t);
	} else {
		tmp = t_2;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = x * (y * z)
    t_2 = j * (a * c)
    if (a <= (-6.6d+57)) then
        tmp = t_2
    else if (a <= (-1.55d-36)) then
        tmp = t_1
    else if (a <= (-2.2d-138)) then
        tmp = c * (z * -b)
    else if (a <= 3.8d-188) then
        tmp = t_1
    else if (a <= 5.5d-13) then
        tmp = b * (t * i)
    else if (a <= 8d+43) then
        tmp = t_1
    else if (a <= 3.2d+194) then
        tmp = a * (x * -t)
    else
        tmp = t_2
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = x * (y * z);
	double t_2 = j * (a * c);
	double tmp;
	if (a <= -6.6e+57) {
		tmp = t_2;
	} else if (a <= -1.55e-36) {
		tmp = t_1;
	} else if (a <= -2.2e-138) {
		tmp = c * (z * -b);
	} else if (a <= 3.8e-188) {
		tmp = t_1;
	} else if (a <= 5.5e-13) {
		tmp = b * (t * i);
	} else if (a <= 8e+43) {
		tmp = t_1;
	} else if (a <= 3.2e+194) {
		tmp = a * (x * -t);
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = x * (y * z)
	t_2 = j * (a * c)
	tmp = 0
	if a <= -6.6e+57:
		tmp = t_2
	elif a <= -1.55e-36:
		tmp = t_1
	elif a <= -2.2e-138:
		tmp = c * (z * -b)
	elif a <= 3.8e-188:
		tmp = t_1
	elif a <= 5.5e-13:
		tmp = b * (t * i)
	elif a <= 8e+43:
		tmp = t_1
	elif a <= 3.2e+194:
		tmp = a * (x * -t)
	else:
		tmp = t_2
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(x * Float64(y * z))
	t_2 = Float64(j * Float64(a * c))
	tmp = 0.0
	if (a <= -6.6e+57)
		tmp = t_2;
	elseif (a <= -1.55e-36)
		tmp = t_1;
	elseif (a <= -2.2e-138)
		tmp = Float64(c * Float64(z * Float64(-b)));
	elseif (a <= 3.8e-188)
		tmp = t_1;
	elseif (a <= 5.5e-13)
		tmp = Float64(b * Float64(t * i));
	elseif (a <= 8e+43)
		tmp = t_1;
	elseif (a <= 3.2e+194)
		tmp = Float64(a * Float64(x * Float64(-t)));
	else
		tmp = t_2;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = x * (y * z);
	t_2 = j * (a * c);
	tmp = 0.0;
	if (a <= -6.6e+57)
		tmp = t_2;
	elseif (a <= -1.55e-36)
		tmp = t_1;
	elseif (a <= -2.2e-138)
		tmp = c * (z * -b);
	elseif (a <= 3.8e-188)
		tmp = t_1;
	elseif (a <= 5.5e-13)
		tmp = b * (t * i);
	elseif (a <= 8e+43)
		tmp = t_1;
	elseif (a <= 3.2e+194)
		tmp = a * (x * -t);
	else
		tmp = t_2;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(j * N[(a * c), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -6.6e+57], t$95$2, If[LessEqual[a, -1.55e-36], t$95$1, If[LessEqual[a, -2.2e-138], N[(c * N[(z * (-b)), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 3.8e-188], t$95$1, If[LessEqual[a, 5.5e-13], N[(b * N[(t * i), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 8e+43], t$95$1, If[LessEqual[a, 3.2e+194], N[(a * N[(x * (-t)), $MachinePrecision]), $MachinePrecision], t$95$2]]]]]]]]]

Derivation

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

Alternative 10: 50.9% accurate, 1.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(t \cdot i - z \cdot c\right)\\ t_2 := x \cdot \left(y \cdot z - t \cdot a\right)\\ t_3 := c \cdot \left(a \cdot j - z \cdot b\right)\\ \mathbf{if}\;c \leq -9.2 \cdot 10^{+66}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;c \leq -1.9 \cdot 10^{-258}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;c \leq 3.1 \cdot 10^{-287}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;c \leq 3.1 \cdot 10^{-93}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;c \leq 4.8 \cdot 10^{+67}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;t_3\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* b (- (* t i) (* z c))))
        (t_2 (* x (- (* y z) (* t a))))
        (t_3 (* c (- (* a j) (* z b)))))
   (if (<= c -9.2e+66)
     t_3
     (if (<= c -1.9e-258)
       t_2
       (if (<= c 3.1e-287)
         t_1
         (if (<= c 3.1e-93) t_2 (if (<= c 4.8e+67) t_1 t_3)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = b * ((t * i) - (z * c));
	double t_2 = x * ((y * z) - (t * a));
	double t_3 = c * ((a * j) - (z * b));
	double tmp;
	if (c <= -9.2e+66) {
		tmp = t_3;
	} else if (c <= -1.9e-258) {
		tmp = t_2;
	} else if (c <= 3.1e-287) {
		tmp = t_1;
	} else if (c <= 3.1e-93) {
		tmp = t_2;
	} else if (c <= 4.8e+67) {
		tmp = t_1;
	} else {
		tmp = t_3;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: tmp
    t_1 = b * ((t * i) - (z * c))
    t_2 = x * ((y * z) - (t * a))
    t_3 = c * ((a * j) - (z * b))
    if (c <= (-9.2d+66)) then
        tmp = t_3
    else if (c <= (-1.9d-258)) then
        tmp = t_2
    else if (c <= 3.1d-287) then
        tmp = t_1
    else if (c <= 3.1d-93) then
        tmp = t_2
    else if (c <= 4.8d+67) then
        tmp = t_1
    else
        tmp = t_3
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = b * ((t * i) - (z * c));
	double t_2 = x * ((y * z) - (t * a));
	double t_3 = c * ((a * j) - (z * b));
	double tmp;
	if (c <= -9.2e+66) {
		tmp = t_3;
	} else if (c <= -1.9e-258) {
		tmp = t_2;
	} else if (c <= 3.1e-287) {
		tmp = t_1;
	} else if (c <= 3.1e-93) {
		tmp = t_2;
	} else if (c <= 4.8e+67) {
		tmp = t_1;
	} else {
		tmp = t_3;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = b * ((t * i) - (z * c))
	t_2 = x * ((y * z) - (t * a))
	t_3 = c * ((a * j) - (z * b))
	tmp = 0
	if c <= -9.2e+66:
		tmp = t_3
	elif c <= -1.9e-258:
		tmp = t_2
	elif c <= 3.1e-287:
		tmp = t_1
	elif c <= 3.1e-93:
		tmp = t_2
	elif c <= 4.8e+67:
		tmp = t_1
	else:
		tmp = t_3
	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(x * Float64(Float64(y * z) - Float64(t * a)))
	t_3 = Float64(c * Float64(Float64(a * j) - Float64(z * b)))
	tmp = 0.0
	if (c <= -9.2e+66)
		tmp = t_3;
	elseif (c <= -1.9e-258)
		tmp = t_2;
	elseif (c <= 3.1e-287)
		tmp = t_1;
	elseif (c <= 3.1e-93)
		tmp = t_2;
	elseif (c <= 4.8e+67)
		tmp = t_1;
	else
		tmp = t_3;
	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 = x * ((y * z) - (t * a));
	t_3 = c * ((a * j) - (z * b));
	tmp = 0.0;
	if (c <= -9.2e+66)
		tmp = t_3;
	elseif (c <= -1.9e-258)
		tmp = t_2;
	elseif (c <= 3.1e-287)
		tmp = t_1;
	elseif (c <= 3.1e-93)
		tmp = t_2;
	elseif (c <= 4.8e+67)
		tmp = t_1;
	else
		tmp = t_3;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(b * N[(N[(t * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(c * N[(N[(a * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[c, -9.2e+66], t$95$3, If[LessEqual[c, -1.9e-258], t$95$2, If[LessEqual[c, 3.1e-287], t$95$1, If[LessEqual[c, 3.1e-93], t$95$2, If[LessEqual[c, 4.8e+67], t$95$1, t$95$3]]]]]]]]

Derivation

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

Alternative 11: 52.6% accurate, 1.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(y \cdot z - t \cdot a\right)\\ t_2 := c \cdot \left(a \cdot j - z \cdot b\right)\\ \mathbf{if}\;c \leq -1.85 \cdot 10^{+67}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;c \leq -3.2 \cdot 10^{-178}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;c \leq 1.55 \cdot 10^{-165}:\\ \;\;\;\;y \cdot \left(x \cdot z - i \cdot j\right)\\ \mathbf{elif}\;c \leq 3 \cdot 10^{-91}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;c \leq 8 \cdot 10^{+67}:\\ \;\;\;\;b \cdot \left(t \cdot i - z \cdot c\right)\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* x (- (* y z) (* t a)))) (t_2 (* c (- (* a j) (* z b)))))
   (if (<= c -1.85e+67)
     t_2
     (if (<= c -3.2e-178)
       t_1
       (if (<= c 1.55e-165)
         (* y (- (* x z) (* i j)))
         (if (<= c 3e-91)
           t_1
           (if (<= c 8e+67) (* b (- (* t i) (* z c))) t_2)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = x * ((y * z) - (t * a));
	double t_2 = c * ((a * j) - (z * b));
	double tmp;
	if (c <= -1.85e+67) {
		tmp = t_2;
	} else if (c <= -3.2e-178) {
		tmp = t_1;
	} else if (c <= 1.55e-165) {
		tmp = y * ((x * z) - (i * j));
	} else if (c <= 3e-91) {
		tmp = t_1;
	} else if (c <= 8e+67) {
		tmp = b * ((t * i) - (z * c));
	} else {
		tmp = t_2;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = x * ((y * z) - (t * a))
    t_2 = c * ((a * j) - (z * b))
    if (c <= (-1.85d+67)) then
        tmp = t_2
    else if (c <= (-3.2d-178)) then
        tmp = t_1
    else if (c <= 1.55d-165) then
        tmp = y * ((x * z) - (i * j))
    else if (c <= 3d-91) then
        tmp = t_1
    else if (c <= 8d+67) then
        tmp = b * ((t * i) - (z * c))
    else
        tmp = t_2
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = x * ((y * z) - (t * a));
	double t_2 = c * ((a * j) - (z * b));
	double tmp;
	if (c <= -1.85e+67) {
		tmp = t_2;
	} else if (c <= -3.2e-178) {
		tmp = t_1;
	} else if (c <= 1.55e-165) {
		tmp = y * ((x * z) - (i * j));
	} else if (c <= 3e-91) {
		tmp = t_1;
	} else if (c <= 8e+67) {
		tmp = b * ((t * i) - (z * c));
	} 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 = c * ((a * j) - (z * b))
	tmp = 0
	if c <= -1.85e+67:
		tmp = t_2
	elif c <= -3.2e-178:
		tmp = t_1
	elif c <= 1.55e-165:
		tmp = y * ((x * z) - (i * j))
	elif c <= 3e-91:
		tmp = t_1
	elif c <= 8e+67:
		tmp = b * ((t * i) - (z * c))
	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(c * Float64(Float64(a * j) - Float64(z * b)))
	tmp = 0.0
	if (c <= -1.85e+67)
		tmp = t_2;
	elseif (c <= -3.2e-178)
		tmp = t_1;
	elseif (c <= 1.55e-165)
		tmp = Float64(y * Float64(Float64(x * z) - Float64(i * j)));
	elseif (c <= 3e-91)
		tmp = t_1;
	elseif (c <= 8e+67)
		tmp = Float64(b * Float64(Float64(t * i) - Float64(z * c)));
	else
		tmp = t_2;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = x * ((y * z) - (t * a));
	t_2 = c * ((a * j) - (z * b));
	tmp = 0.0;
	if (c <= -1.85e+67)
		tmp = t_2;
	elseif (c <= -3.2e-178)
		tmp = t_1;
	elseif (c <= 1.55e-165)
		tmp = y * ((x * z) - (i * j));
	elseif (c <= 3e-91)
		tmp = t_1;
	elseif (c <= 8e+67)
		tmp = b * ((t * i) - (z * c));
	else
		tmp = t_2;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(c * N[(N[(a * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[c, -1.85e+67], t$95$2, If[LessEqual[c, -3.2e-178], t$95$1, If[LessEqual[c, 1.55e-165], N[(y * N[(N[(x * z), $MachinePrecision] - N[(i * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[c, 3e-91], t$95$1, If[LessEqual[c, 8e+67], N[(b * N[(N[(t * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$2]]]]]]]

Derivation

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

Alternative 12: 30.0% accurate, 1.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(y \cdot z\right)\\ t_2 := j \cdot \left(a \cdot c\right)\\ \mathbf{if}\;a \leq -2.1 \cdot 10^{+61}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq 2.6 \cdot 10^{-187}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 8.5 \cdot 10^{-19}:\\ \;\;\;\;b \cdot \left(t \cdot i\right)\\ \mathbf{elif}\;a \leq 7 \cdot 10^{+43}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 9 \cdot 10^{+194}:\\ \;\;\;\;a \cdot \left(x \cdot \left(-t\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* x (* y z))) (t_2 (* j (* a c))))
   (if (<= a -2.1e+61)
     t_2
     (if (<= a 2.6e-187)
       t_1
       (if (<= a 8.5e-19)
         (* b (* t i))
         (if (<= a 7e+43) t_1 (if (<= a 9e+194) (* a (* x (- t))) t_2)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = x * (y * z);
	double t_2 = j * (a * c);
	double tmp;
	if (a <= -2.1e+61) {
		tmp = t_2;
	} else if (a <= 2.6e-187) {
		tmp = t_1;
	} else if (a <= 8.5e-19) {
		tmp = b * (t * i);
	} else if (a <= 7e+43) {
		tmp = t_1;
	} else if (a <= 9e+194) {
		tmp = a * (x * -t);
	} else {
		tmp = t_2;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = x * (y * z)
    t_2 = j * (a * c)
    if (a <= (-2.1d+61)) then
        tmp = t_2
    else if (a <= 2.6d-187) then
        tmp = t_1
    else if (a <= 8.5d-19) then
        tmp = b * (t * i)
    else if (a <= 7d+43) then
        tmp = t_1
    else if (a <= 9d+194) then
        tmp = a * (x * -t)
    else
        tmp = t_2
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = x * (y * z);
	double t_2 = j * (a * c);
	double tmp;
	if (a <= -2.1e+61) {
		tmp = t_2;
	} else if (a <= 2.6e-187) {
		tmp = t_1;
	} else if (a <= 8.5e-19) {
		tmp = b * (t * i);
	} else if (a <= 7e+43) {
		tmp = t_1;
	} else if (a <= 9e+194) {
		tmp = a * (x * -t);
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = x * (y * z)
	t_2 = j * (a * c)
	tmp = 0
	if a <= -2.1e+61:
		tmp = t_2
	elif a <= 2.6e-187:
		tmp = t_1
	elif a <= 8.5e-19:
		tmp = b * (t * i)
	elif a <= 7e+43:
		tmp = t_1
	elif a <= 9e+194:
		tmp = a * (x * -t)
	else:
		tmp = t_2
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(x * Float64(y * z))
	t_2 = Float64(j * Float64(a * c))
	tmp = 0.0
	if (a <= -2.1e+61)
		tmp = t_2;
	elseif (a <= 2.6e-187)
		tmp = t_1;
	elseif (a <= 8.5e-19)
		tmp = Float64(b * Float64(t * i));
	elseif (a <= 7e+43)
		tmp = t_1;
	elseif (a <= 9e+194)
		tmp = Float64(a * Float64(x * Float64(-t)));
	else
		tmp = t_2;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = x * (y * z);
	t_2 = j * (a * c);
	tmp = 0.0;
	if (a <= -2.1e+61)
		tmp = t_2;
	elseif (a <= 2.6e-187)
		tmp = t_1;
	elseif (a <= 8.5e-19)
		tmp = b * (t * i);
	elseif (a <= 7e+43)
		tmp = t_1;
	elseif (a <= 9e+194)
		tmp = a * (x * -t);
	else
		tmp = t_2;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(j * N[(a * c), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -2.1e+61], t$95$2, If[LessEqual[a, 2.6e-187], t$95$1, If[LessEqual[a, 8.5e-19], N[(b * N[(t * i), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 7e+43], t$95$1, If[LessEqual[a, 9e+194], N[(a * N[(x * (-t)), $MachinePrecision]), $MachinePrecision], t$95$2]]]]]]]

Derivation

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

Alternative 13: 29.1% accurate, 2.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := i \cdot \left(t \cdot b\right)\\ \mathbf{if}\;t \leq -3.3 \cdot 10^{+42}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq 7 \cdot 10^{-145}:\\ \;\;\;\;a \cdot \left(c \cdot j\right)\\ \mathbf{elif}\;t \leq 7.8 \cdot 10^{-18}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq 2.6 \cdot 10^{+22}:\\ \;\;\;\;c \cdot \left(a \cdot j\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(t \cdot i\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* i (* t b))))
   (if (<= t -3.3e+42)
     t_1
     (if (<= t 7e-145)
       (* a (* c j))
       (if (<= t 7.8e-18)
         t_1
         (if (<= t 2.6e+22) (* c (* a j)) (* b (* t i))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = i * (t * b);
	double tmp;
	if (t <= -3.3e+42) {
		tmp = t_1;
	} else if (t <= 7e-145) {
		tmp = a * (c * j);
	} else if (t <= 7.8e-18) {
		tmp = t_1;
	} else if (t <= 2.6e+22) {
		tmp = c * (a * j);
	} else {
		tmp = b * (t * i);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: tmp
    t_1 = i * (t * b)
    if (t <= (-3.3d+42)) then
        tmp = t_1
    else if (t <= 7d-145) then
        tmp = a * (c * j)
    else if (t <= 7.8d-18) then
        tmp = t_1
    else if (t <= 2.6d+22) then
        tmp = c * (a * j)
    else
        tmp = b * (t * i)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = i * (t * b);
	double tmp;
	if (t <= -3.3e+42) {
		tmp = t_1;
	} else if (t <= 7e-145) {
		tmp = a * (c * j);
	} else if (t <= 7.8e-18) {
		tmp = t_1;
	} else if (t <= 2.6e+22) {
		tmp = c * (a * j);
	} else {
		tmp = b * (t * i);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = i * (t * b)
	tmp = 0
	if t <= -3.3e+42:
		tmp = t_1
	elif t <= 7e-145:
		tmp = a * (c * j)
	elif t <= 7.8e-18:
		tmp = t_1
	elif t <= 2.6e+22:
		tmp = c * (a * j)
	else:
		tmp = b * (t * i)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(i * Float64(t * b))
	tmp = 0.0
	if (t <= -3.3e+42)
		tmp = t_1;
	elseif (t <= 7e-145)
		tmp = Float64(a * Float64(c * j));
	elseif (t <= 7.8e-18)
		tmp = t_1;
	elseif (t <= 2.6e+22)
		tmp = Float64(c * Float64(a * j));
	else
		tmp = Float64(b * Float64(t * i));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = i * (t * b);
	tmp = 0.0;
	if (t <= -3.3e+42)
		tmp = t_1;
	elseif (t <= 7e-145)
		tmp = a * (c * j);
	elseif (t <= 7.8e-18)
		tmp = t_1;
	elseif (t <= 2.6e+22)
		tmp = c * (a * j);
	else
		tmp = b * (t * i);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(i * N[(t * b), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -3.3e+42], t$95$1, If[LessEqual[t, 7e-145], N[(a * N[(c * j), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 7.8e-18], t$95$1, If[LessEqual[t, 2.6e+22], N[(c * N[(a * j), $MachinePrecision]), $MachinePrecision], N[(b * N[(t * i), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

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

Alternative 14: 29.8% accurate, 2.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(y \cdot z\right)\\ t_2 := c \cdot \left(a \cdot j\right)\\ \mathbf{if}\;a \leq -3.9 \cdot 10^{+56}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq 4.8 \cdot 10^{-188}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 1.8 \cdot 10^{-16}:\\ \;\;\;\;b \cdot \left(t \cdot i\right)\\ \mathbf{elif}\;a \leq 2.1 \cdot 10^{+102}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* x (* y z))) (t_2 (* c (* a j))))
   (if (<= a -3.9e+56)
     t_2
     (if (<= a 4.8e-188)
       t_1
       (if (<= a 1.8e-16) (* b (* t i)) (if (<= a 2.1e+102) 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);
	double t_2 = c * (a * j);
	double tmp;
	if (a <= -3.9e+56) {
		tmp = t_2;
	} else if (a <= 4.8e-188) {
		tmp = t_1;
	} else if (a <= 1.8e-16) {
		tmp = b * (t * i);
	} else if (a <= 2.1e+102) {
		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_2 = c * (a * j)
    if (a <= (-3.9d+56)) then
        tmp = t_2
    else if (a <= 4.8d-188) then
        tmp = t_1
    else if (a <= 1.8d-16) then
        tmp = b * (t * i)
    else if (a <= 2.1d+102) 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);
	double t_2 = c * (a * j);
	double tmp;
	if (a <= -3.9e+56) {
		tmp = t_2;
	} else if (a <= 4.8e-188) {
		tmp = t_1;
	} else if (a <= 1.8e-16) {
		tmp = b * (t * i);
	} else if (a <= 2.1e+102) {
		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_2 = c * (a * j)
	tmp = 0
	if a <= -3.9e+56:
		tmp = t_2
	elif a <= 4.8e-188:
		tmp = t_1
	elif a <= 1.8e-16:
		tmp = b * (t * i)
	elif a <= 2.1e+102:
		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(y * z))
	t_2 = Float64(c * Float64(a * j))
	tmp = 0.0
	if (a <= -3.9e+56)
		tmp = t_2;
	elseif (a <= 4.8e-188)
		tmp = t_1;
	elseif (a <= 1.8e-16)
		tmp = Float64(b * Float64(t * i));
	elseif (a <= 2.1e+102)
		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_2 = c * (a * j);
	tmp = 0.0;
	if (a <= -3.9e+56)
		tmp = t_2;
	elseif (a <= 4.8e-188)
		tmp = t_1;
	elseif (a <= 1.8e-16)
		tmp = b * (t * i);
	elseif (a <= 2.1e+102)
		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[(y * z), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(c * N[(a * j), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -3.9e+56], t$95$2, If[LessEqual[a, 4.8e-188], t$95$1, If[LessEqual[a, 1.8e-16], N[(b * N[(t * i), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 2.1e+102], t$95$1, t$95$2]]]]]]

Derivation

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

Alternative 15: 30.0% accurate, 2.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(y \cdot z\right)\\ \mathbf{if}\;a \leq -9.5 \cdot 10^{+62}:\\ \;\;\;\;j \cdot \left(a \cdot c\right)\\ \mathbf{elif}\;a \leq 3.6 \cdot 10^{-187}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 7.6 \cdot 10^{-12}:\\ \;\;\;\;b \cdot \left(t \cdot i\right)\\ \mathbf{elif}\;a \leq 2.05 \cdot 10^{+102}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(a \cdot j\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* x (* y z))))
   (if (<= a -9.5e+62)
     (* j (* a c))
     (if (<= a 3.6e-187)
       t_1
       (if (<= a 7.6e-12)
         (* b (* t i))
         (if (<= a 2.05e+102) t_1 (* c (* a j))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = x * (y * z);
	double tmp;
	if (a <= -9.5e+62) {
		tmp = j * (a * c);
	} else if (a <= 3.6e-187) {
		tmp = t_1;
	} else if (a <= 7.6e-12) {
		tmp = b * (t * i);
	} else if (a <= 2.05e+102) {
		tmp = t_1;
	} else {
		tmp = c * (a * 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 * (y * z)
    if (a <= (-9.5d+62)) then
        tmp = j * (a * c)
    else if (a <= 3.6d-187) then
        tmp = t_1
    else if (a <= 7.6d-12) then
        tmp = b * (t * i)
    else if (a <= 2.05d+102) then
        tmp = t_1
    else
        tmp = c * (a * 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 * (y * z);
	double tmp;
	if (a <= -9.5e+62) {
		tmp = j * (a * c);
	} else if (a <= 3.6e-187) {
		tmp = t_1;
	} else if (a <= 7.6e-12) {
		tmp = b * (t * i);
	} else if (a <= 2.05e+102) {
		tmp = t_1;
	} else {
		tmp = c * (a * j);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = x * (y * z)
	tmp = 0
	if a <= -9.5e+62:
		tmp = j * (a * c)
	elif a <= 3.6e-187:
		tmp = t_1
	elif a <= 7.6e-12:
		tmp = b * (t * i)
	elif a <= 2.05e+102:
		tmp = t_1
	else:
		tmp = c * (a * j)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(x * Float64(y * z))
	tmp = 0.0
	if (a <= -9.5e+62)
		tmp = Float64(j * Float64(a * c));
	elseif (a <= 3.6e-187)
		tmp = t_1;
	elseif (a <= 7.6e-12)
		tmp = Float64(b * Float64(t * i));
	elseif (a <= 2.05e+102)
		tmp = t_1;
	else
		tmp = Float64(c * Float64(a * j));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = x * (y * z);
	tmp = 0.0;
	if (a <= -9.5e+62)
		tmp = j * (a * c);
	elseif (a <= 3.6e-187)
		tmp = t_1;
	elseif (a <= 7.6e-12)
		tmp = b * (t * i);
	elseif (a <= 2.05e+102)
		tmp = t_1;
	else
		tmp = c * (a * j);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -9.5e+62], N[(j * N[(a * c), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 3.6e-187], t$95$1, If[LessEqual[a, 7.6e-12], N[(b * N[(t * i), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 2.05e+102], t$95$1, N[(c * N[(a * j), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

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

Alternative 16: 51.6% accurate, 2.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;b \leq -6.1 \cdot 10^{-30} \lor \neg \left(b \leq 2.7 \cdot 10^{-20}\right):\\ \;\;\;\;b \cdot \left(t \cdot i - z \cdot c\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(c \cdot j - x \cdot t\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (or (<= b -6.1e-30) (not (<= b 2.7e-20)))
   (* b (- (* t i) (* z c)))
   (* 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 tmp;
	if ((b <= -6.1e-30) || !(b <= 2.7e-20)) {
		tmp = b * ((t * i) - (z * c));
	} else {
		tmp = 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) :: tmp
    if ((b <= (-6.1d-30)) .or. (.not. (b <= 2.7d-20))) then
        tmp = b * ((t * i) - (z * c))
    else
        tmp = 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 tmp;
	if ((b <= -6.1e-30) || !(b <= 2.7e-20)) {
		tmp = b * ((t * i) - (z * c));
	} else {
		tmp = a * ((c * j) - (x * t));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if (b <= -6.1e-30) or not (b <= 2.7e-20):
		tmp = b * ((t * i) - (z * c))
	else:
		tmp = a * ((c * j) - (x * t))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if ((b <= -6.1e-30) || !(b <= 2.7e-20))
		tmp = Float64(b * Float64(Float64(t * i) - Float64(z * c)));
	else
		tmp = 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)
	tmp = 0.0;
	if ((b <= -6.1e-30) || ~((b <= 2.7e-20)))
		tmp = b * ((t * i) - (z * c));
	else
		tmp = a * ((c * j) - (x * t));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[Or[LessEqual[b, -6.1e-30], N[Not[LessEqual[b, 2.7e-20]], $MachinePrecision]], 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]]

Derivation

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

Alternative 17: 52.3% accurate, 2.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;c \leq -1.15 \cdot 10^{+86} \lor \neg \left(c \leq 1.35 \cdot 10^{+66}\right):\\ \;\;\;\;c \cdot \left(a \cdot j - z \cdot b\right)\\ \mathbf{else}:\\ \;\;\;\;i \cdot \left(t \cdot b - y \cdot j\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (or (<= c -1.15e+86) (not (<= c 1.35e+66)))
   (* c (- (* a j) (* z b)))
   (* i (- (* t b) (* 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 ((c <= -1.15e+86) || !(c <= 1.35e+66)) {
		tmp = c * ((a * j) - (z * b));
	} else {
		tmp = i * ((t * b) - (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 ((c <= (-1.15d+86)) .or. (.not. (c <= 1.35d+66))) then
        tmp = c * ((a * j) - (z * b))
    else
        tmp = i * ((t * b) - (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 ((c <= -1.15e+86) || !(c <= 1.35e+66)) {
		tmp = c * ((a * j) - (z * b));
	} else {
		tmp = i * ((t * b) - (y * j));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if (c <= -1.15e+86) or not (c <= 1.35e+66):
		tmp = c * ((a * j) - (z * b))
	else:
		tmp = i * ((t * b) - (y * j))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if ((c <= -1.15e+86) || !(c <= 1.35e+66))
		tmp = Float64(c * Float64(Float64(a * j) - Float64(z * b)));
	else
		tmp = Float64(i * Float64(Float64(t * b) - Float64(y * j)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0;
	if ((c <= -1.15e+86) || ~((c <= 1.35e+66)))
		tmp = c * ((a * j) - (z * b));
	else
		tmp = i * ((t * b) - (y * j));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[Or[LessEqual[c, -1.15e+86], N[Not[LessEqual[c, 1.35e+66]], $MachinePrecision]], N[(c * N[(N[(a * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(i * N[(N[(t * b), $MachinePrecision] - N[(y * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

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

Alternative 18: 30.0% accurate, 3.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;c \leq -1.66 \cdot 10^{+87} \lor \neg \left(c \leq 165000000\right):\\ \;\;\;\;a \cdot \left(c \cdot j\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(t \cdot i\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (or (<= c -1.66e+87) (not (<= c 165000000.0)))
   (* a (* c j))
   (* b (* t i))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if ((c <= -1.66e+87) || !(c <= 165000000.0)) {
		tmp = a * (c * j);
	} else {
		tmp = b * (t * i);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: tmp
    if ((c <= (-1.66d+87)) .or. (.not. (c <= 165000000.0d0))) then
        tmp = a * (c * j)
    else
        tmp = b * (t * i)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if ((c <= -1.66e+87) || !(c <= 165000000.0)) {
		tmp = a * (c * j);
	} else {
		tmp = b * (t * i);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if (c <= -1.66e+87) or not (c <= 165000000.0):
		tmp = a * (c * j)
	else:
		tmp = b * (t * i)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if ((c <= -1.66e+87) || !(c <= 165000000.0))
		tmp = Float64(a * Float64(c * j));
	else
		tmp = Float64(b * Float64(t * i));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0;
	if ((c <= -1.66e+87) || ~((c <= 165000000.0)))
		tmp = a * (c * j);
	else
		tmp = b * (t * i);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[Or[LessEqual[c, -1.66e+87], N[Not[LessEqual[c, 165000000.0]], $MachinePrecision]], N[(a * N[(c * j), $MachinePrecision]), $MachinePrecision], N[(b * N[(t * i), $MachinePrecision]), $MachinePrecision]]

Derivation

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

Alternative 19: 29.6% accurate, 3.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;c \leq -9.6 \cdot 10^{+85} \lor \neg \left(c \leq 8.5 \cdot 10^{+78}\right):\\ \;\;\;\;c \cdot \left(a \cdot j\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(t \cdot i\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (or (<= c -9.6e+85) (not (<= c 8.5e+78))) (* c (* a j)) (* b (* t i))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if ((c <= -9.6e+85) || !(c <= 8.5e+78)) {
		tmp = c * (a * j);
	} else {
		tmp = b * (t * i);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: tmp
    if ((c <= (-9.6d+85)) .or. (.not. (c <= 8.5d+78))) then
        tmp = c * (a * j)
    else
        tmp = b * (t * i)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if ((c <= -9.6e+85) || !(c <= 8.5e+78)) {
		tmp = c * (a * j);
	} else {
		tmp = b * (t * i);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if (c <= -9.6e+85) or not (c <= 8.5e+78):
		tmp = c * (a * j)
	else:
		tmp = b * (t * i)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if ((c <= -9.6e+85) || !(c <= 8.5e+78))
		tmp = Float64(c * Float64(a * j));
	else
		tmp = Float64(b * Float64(t * i));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0;
	if ((c <= -9.6e+85) || ~((c <= 8.5e+78)))
		tmp = c * (a * j);
	else
		tmp = b * (t * i);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[Or[LessEqual[c, -9.6e+85], N[Not[LessEqual[c, 8.5e+78]], $MachinePrecision]], N[(c * N[(a * j), $MachinePrecision]), $MachinePrecision], N[(b * N[(t * i), $MachinePrecision]), $MachinePrecision]]

Derivation

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

Alternative 20: 22.2% 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

Developer target: 59.8% 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 2024008 
(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)))))