Linear.Matrix:det33 from linear-1.19.1.3

Percentage Accurate: 73.8% → 82.4%

Time: 31.6s

Alternatives: 28

Speedup: 0.5×

• 57.9% of points produce a very large (infinite) output. You may want to add a precondition.

Specification

Math

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

FPCore

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

C

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

Fortran

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

Java

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

Python

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

Julia

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

MATLAB

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

Wolfram

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

Initial Program: 73.8% accurate, 1.0× speedup

Math

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

FPCore

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

C

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

Fortran

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

Java

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

Python

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

Julia

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

MATLAB

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

Wolfram

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

Alternative 1: 82.4% accurate, 0.1× speedup

Math

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

FPCore

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

C

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

Julia

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

Wolfram

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

Derivation

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

Alternative 2: 82.4% accurate, 0.5× speedup

Math

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

FPCore

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

C

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

Python

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

Julia

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

MATLAB

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

Wolfram

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

Derivation

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

Alternative 3: 68.9% accurate, 0.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(t \cdot a - y \cdot z\right)\\ t_2 := b \cdot \left(a \cdot i - z \cdot c\right)\\ t_3 := j \cdot \left(t \cdot c - y \cdot i\right) - \left(c \cdot \left(z \cdot b\right) + t_1\right)\\ \mathbf{if}\;b \leq -9.5 \cdot 10^{+73}:\\ \;\;\;\;y \cdot \left(x \cdot z\right) - b \cdot \left(z \cdot c - a \cdot i\right)\\ \mathbf{elif}\;b \leq -9.2 \cdot 10^{-222}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;b \leq 4.2 \cdot 10^{-262}:\\ \;\;\;\;c \cdot \left(t \cdot j - z \cdot b\right) - t_1\\ \mathbf{elif}\;b \leq 2:\\ \;\;\;\;t_3\\ \mathbf{elif}\;b \leq 3.7 \cdot 10^{+108}:\\ \;\;\;\;x \cdot \left(y \cdot z - t \cdot a\right) + t_2\\ \mathbf{elif}\;b \leq 1.05 \cdot 10^{+209}:\\ \;\;\;\;t_3\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* x (- (* t a) (* y z))))
        (t_2 (* b (- (* a i) (* z c))))
        (t_3 (- (* j (- (* t c) (* y i))) (+ (* c (* z b)) t_1))))
   (if (<= b -9.5e+73)
     (- (* y (* x z)) (* b (- (* z c) (* a i))))
     (if (<= b -9.2e-222)
       t_3
       (if (<= b 4.2e-262)
         (- (* c (- (* t j) (* z b))) t_1)
         (if (<= b 2.0)
           t_3
           (if (<= b 3.7e+108)
             (+ (* x (- (* y z) (* t a))) t_2)
             (if (<= b 1.05e+209) 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 * ((t * a) - (y * z));
	double t_2 = b * ((a * i) - (z * c));
	double t_3 = (j * ((t * c) - (y * i))) - ((c * (z * b)) + t_1);
	double tmp;
	if (b <= -9.5e+73) {
		tmp = (y * (x * z)) - (b * ((z * c) - (a * i)));
	} else if (b <= -9.2e-222) {
		tmp = t_3;
	} else if (b <= 4.2e-262) {
		tmp = (c * ((t * j) - (z * b))) - t_1;
	} else if (b <= 2.0) {
		tmp = t_3;
	} else if (b <= 3.7e+108) {
		tmp = (x * ((y * z) - (t * a))) + t_2;
	} else if (b <= 1.05e+209) {
		tmp = 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) :: tmp
    t_1 = x * ((t * a) - (y * z))
    t_2 = b * ((a * i) - (z * c))
    t_3 = (j * ((t * c) - (y * i))) - ((c * (z * b)) + t_1)
    if (b <= (-9.5d+73)) then
        tmp = (y * (x * z)) - (b * ((z * c) - (a * i)))
    else if (b <= (-9.2d-222)) then
        tmp = t_3
    else if (b <= 4.2d-262) then
        tmp = (c * ((t * j) - (z * b))) - t_1
    else if (b <= 2.0d0) then
        tmp = t_3
    else if (b <= 3.7d+108) then
        tmp = (x * ((y * z) - (t * a))) + t_2
    else if (b <= 1.05d+209) then
        tmp = 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 = x * ((t * a) - (y * z));
	double t_2 = b * ((a * i) - (z * c));
	double t_3 = (j * ((t * c) - (y * i))) - ((c * (z * b)) + t_1);
	double tmp;
	if (b <= -9.5e+73) {
		tmp = (y * (x * z)) - (b * ((z * c) - (a * i)));
	} else if (b <= -9.2e-222) {
		tmp = t_3;
	} else if (b <= 4.2e-262) {
		tmp = (c * ((t * j) - (z * b))) - t_1;
	} else if (b <= 2.0) {
		tmp = t_3;
	} else if (b <= 3.7e+108) {
		tmp = (x * ((y * z) - (t * a))) + t_2;
	} else if (b <= 1.05e+209) {
		tmp = t_3;
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = x * ((t * a) - (y * z))
	t_2 = b * ((a * i) - (z * c))
	t_3 = (j * ((t * c) - (y * i))) - ((c * (z * b)) + t_1)
	tmp = 0
	if b <= -9.5e+73:
		tmp = (y * (x * z)) - (b * ((z * c) - (a * i)))
	elif b <= -9.2e-222:
		tmp = t_3
	elif b <= 4.2e-262:
		tmp = (c * ((t * j) - (z * b))) - t_1
	elif b <= 2.0:
		tmp = t_3
	elif b <= 3.7e+108:
		tmp = (x * ((y * z) - (t * a))) + t_2
	elif b <= 1.05e+209:
		tmp = t_3
	else:
		tmp = t_2
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(x * Float64(Float64(t * a) - Float64(y * z)))
	t_2 = Float64(b * Float64(Float64(a * i) - Float64(z * c)))
	t_3 = Float64(Float64(j * Float64(Float64(t * c) - Float64(y * i))) - Float64(Float64(c * Float64(z * b)) + t_1))
	tmp = 0.0
	if (b <= -9.5e+73)
		tmp = Float64(Float64(y * Float64(x * z)) - Float64(b * Float64(Float64(z * c) - Float64(a * i))));
	elseif (b <= -9.2e-222)
		tmp = t_3;
	elseif (b <= 4.2e-262)
		tmp = Float64(Float64(c * Float64(Float64(t * j) - Float64(z * b))) - t_1);
	elseif (b <= 2.0)
		tmp = t_3;
	elseif (b <= 3.7e+108)
		tmp = Float64(Float64(x * Float64(Float64(y * z) - Float64(t * a))) + t_2);
	elseif (b <= 1.05e+209)
		tmp = 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 = x * ((t * a) - (y * z));
	t_2 = b * ((a * i) - (z * c));
	t_3 = (j * ((t * c) - (y * i))) - ((c * (z * b)) + t_1);
	tmp = 0.0;
	if (b <= -9.5e+73)
		tmp = (y * (x * z)) - (b * ((z * c) - (a * i)));
	elseif (b <= -9.2e-222)
		tmp = t_3;
	elseif (b <= 4.2e-262)
		tmp = (c * ((t * j) - (z * b))) - t_1;
	elseif (b <= 2.0)
		tmp = t_3;
	elseif (b <= 3.7e+108)
		tmp = (x * ((y * z) - (t * a))) + t_2;
	elseif (b <= 1.05e+209)
		tmp = 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[(x * N[(N[(t * a), $MachinePrecision] - N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(b * N[(N[(a * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(j * N[(N[(t * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(c * N[(z * b), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[b, -9.5e+73], N[(N[(y * N[(x * z), $MachinePrecision]), $MachinePrecision] - N[(b * N[(N[(z * c), $MachinePrecision] - N[(a * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[b, -9.2e-222], t$95$3, If[LessEqual[b, 4.2e-262], N[(N[(c * N[(N[(t * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$1), $MachinePrecision], If[LessEqual[b, 2.0], t$95$3, If[LessEqual[b, 3.7e+108], N[(N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$2), $MachinePrecision], If[LessEqual[b, 1.05e+209], t$95$3, t$95$2]]]]]]]]]

Derivation

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

Alternative 4: 69.7% accurate, 0.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \left(y \cdot \left(x \cdot z - i \cdot j\right) - t \cdot \left(x \cdot a\right)\right) + c \cdot \left(t \cdot j - z \cdot b\right)\\ \mathbf{if}\;a \leq -1.2 \cdot 10^{+48}:\\ \;\;\;\;a \cdot \left(b \cdot i\right) - \left(i \cdot \left(y \cdot j\right) + x \cdot \left(t \cdot a - y \cdot z\right)\right)\\ \mathbf{elif}\;a \leq 24000000000000:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 1.22 \cdot 10^{+247}:\\ \;\;\;\;x \cdot \left(y \cdot z - t \cdot a\right) + b \cdot \left(a \cdot i - z \cdot c\right)\\ \mathbf{elif}\;a \leq 2.7 \cdot 10^{+297}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(b \cdot i - x \cdot t\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1
         (+
          (- (* y (- (* x z) (* i j))) (* t (* x a)))
          (* c (- (* t j) (* z b))))))
   (if (<= a -1.2e+48)
     (- (* a (* b i)) (+ (* i (* y j)) (* x (- (* t a) (* y z)))))
     (if (<= a 24000000000000.0)
       t_1
       (if (<= a 1.22e+247)
         (+ (* x (- (* y z) (* t a))) (* b (- (* a i) (* z c))))
         (if (<= a 2.7e+297) t_1 (* a (- (* b i) (* x t)))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = ((y * ((x * z) - (i * j))) - (t * (x * a))) + (c * ((t * j) - (z * b)));
	double tmp;
	if (a <= -1.2e+48) {
		tmp = (a * (b * i)) - ((i * (y * j)) + (x * ((t * a) - (y * z))));
	} else if (a <= 24000000000000.0) {
		tmp = t_1;
	} else if (a <= 1.22e+247) {
		tmp = (x * ((y * z) - (t * a))) + (b * ((a * i) - (z * c)));
	} else if (a <= 2.7e+297) {
		tmp = t_1;
	} else {
		tmp = a * ((b * i) - (x * t));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: tmp
    t_1 = ((y * ((x * z) - (i * j))) - (t * (x * a))) + (c * ((t * j) - (z * b)))
    if (a <= (-1.2d+48)) then
        tmp = (a * (b * i)) - ((i * (y * j)) + (x * ((t * a) - (y * z))))
    else if (a <= 24000000000000.0d0) then
        tmp = t_1
    else if (a <= 1.22d+247) then
        tmp = (x * ((y * z) - (t * a))) + (b * ((a * i) - (z * c)))
    else if (a <= 2.7d+297) then
        tmp = t_1
    else
        tmp = a * ((b * i) - (x * t))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = ((y * ((x * z) - (i * j))) - (t * (x * a))) + (c * ((t * j) - (z * b)));
	double tmp;
	if (a <= -1.2e+48) {
		tmp = (a * (b * i)) - ((i * (y * j)) + (x * ((t * a) - (y * z))));
	} else if (a <= 24000000000000.0) {
		tmp = t_1;
	} else if (a <= 1.22e+247) {
		tmp = (x * ((y * z) - (t * a))) + (b * ((a * i) - (z * c)));
	} else if (a <= 2.7e+297) {
		tmp = t_1;
	} else {
		tmp = a * ((b * i) - (x * t));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = ((y * ((x * z) - (i * j))) - (t * (x * a))) + (c * ((t * j) - (z * b)))
	tmp = 0
	if a <= -1.2e+48:
		tmp = (a * (b * i)) - ((i * (y * j)) + (x * ((t * a) - (y * z))))
	elif a <= 24000000000000.0:
		tmp = t_1
	elif a <= 1.22e+247:
		tmp = (x * ((y * z) - (t * a))) + (b * ((a * i) - (z * c)))
	elif a <= 2.7e+297:
		tmp = t_1
	else:
		tmp = a * ((b * i) - (x * t))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(Float64(Float64(y * Float64(Float64(x * z) - Float64(i * j))) - Float64(t * Float64(x * a))) + Float64(c * Float64(Float64(t * j) - Float64(z * b))))
	tmp = 0.0
	if (a <= -1.2e+48)
		tmp = Float64(Float64(a * Float64(b * i)) - Float64(Float64(i * Float64(y * j)) + Float64(x * Float64(Float64(t * a) - Float64(y * z)))));
	elseif (a <= 24000000000000.0)
		tmp = t_1;
	elseif (a <= 1.22e+247)
		tmp = Float64(Float64(x * Float64(Float64(y * z) - Float64(t * a))) + Float64(b * Float64(Float64(a * i) - Float64(z * c))));
	elseif (a <= 2.7e+297)
		tmp = t_1;
	else
		tmp = Float64(a * Float64(Float64(b * i) - Float64(x * t)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = ((y * ((x * z) - (i * j))) - (t * (x * a))) + (c * ((t * j) - (z * b)));
	tmp = 0.0;
	if (a <= -1.2e+48)
		tmp = (a * (b * i)) - ((i * (y * j)) + (x * ((t * a) - (y * z))));
	elseif (a <= 24000000000000.0)
		tmp = t_1;
	elseif (a <= 1.22e+247)
		tmp = (x * ((y * z) - (t * a))) + (b * ((a * i) - (z * c)));
	elseif (a <= 2.7e+297)
		tmp = t_1;
	else
		tmp = a * ((b * i) - (x * t));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(N[(N[(y * N[(N[(x * z), $MachinePrecision] - N[(i * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(t * N[(x * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(c * N[(N[(t * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -1.2e+48], N[(N[(a * N[(b * i), $MachinePrecision]), $MachinePrecision] - N[(N[(i * N[(y * j), $MachinePrecision]), $MachinePrecision] + N[(x * N[(N[(t * a), $MachinePrecision] - N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 24000000000000.0], t$95$1, If[LessEqual[a, 1.22e+247], N[(N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(b * N[(N[(a * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 2.7e+297], t$95$1, N[(a * N[(N[(b * i), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

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

Alternative 5: 65.3% accurate, 0.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(t \cdot a - y \cdot z\right)\\ t_2 := c \cdot \left(t \cdot j - z \cdot b\right) - t_1\\ t_3 := i \cdot \left(a \cdot b - y \cdot j\right)\\ \mathbf{if}\;i \leq -4.8 \cdot 10^{+101}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;i \leq -1 \cdot 10^{+62}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;i \leq -6 \cdot 10^{-32}:\\ \;\;\;\;a \cdot \left(b \cdot i - x \cdot t\right)\\ \mathbf{elif}\;i \leq 1.1 \cdot 10^{-113}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;i \leq 1.08 \cdot 10^{+46}:\\ \;\;\;\;j \cdot \left(t \cdot c - y \cdot i\right) - t_1\\ \mathbf{elif}\;i \leq 7.3 \cdot 10^{+133}:\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;t_3\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* x (- (* t a) (* y z))))
        (t_2 (- (* c (- (* t j) (* z b))) t_1))
        (t_3 (* i (- (* a b) (* y j)))))
   (if (<= i -4.8e+101)
     t_3
     (if (<= i -1e+62)
       t_2
       (if (<= i -6e-32)
         (* a (- (* b i) (* x t)))
         (if (<= i 1.1e-113)
           t_2
           (if (<= i 1.08e+46)
             (- (* j (- (* t c) (* y i))) t_1)
             (if (<= i 7.3e+133) t_2 t_3))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = x * ((t * a) - (y * z));
	double t_2 = (c * ((t * j) - (z * b))) - t_1;
	double t_3 = i * ((a * b) - (y * j));
	double tmp;
	if (i <= -4.8e+101) {
		tmp = t_3;
	} else if (i <= -1e+62) {
		tmp = t_2;
	} else if (i <= -6e-32) {
		tmp = a * ((b * i) - (x * t));
	} else if (i <= 1.1e-113) {
		tmp = t_2;
	} else if (i <= 1.08e+46) {
		tmp = (j * ((t * c) - (y * i))) - t_1;
	} else if (i <= 7.3e+133) {
		tmp = t_2;
	} else {
		tmp = t_3;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: tmp
    t_1 = x * ((t * a) - (y * z))
    t_2 = (c * ((t * j) - (z * b))) - t_1
    t_3 = i * ((a * b) - (y * j))
    if (i <= (-4.8d+101)) then
        tmp = t_3
    else if (i <= (-1d+62)) then
        tmp = t_2
    else if (i <= (-6d-32)) then
        tmp = a * ((b * i) - (x * t))
    else if (i <= 1.1d-113) then
        tmp = t_2
    else if (i <= 1.08d+46) then
        tmp = (j * ((t * c) - (y * i))) - t_1
    else if (i <= 7.3d+133) then
        tmp = t_2
    else
        tmp = t_3
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = x * ((t * a) - (y * z));
	double t_2 = (c * ((t * j) - (z * b))) - t_1;
	double t_3 = i * ((a * b) - (y * j));
	double tmp;
	if (i <= -4.8e+101) {
		tmp = t_3;
	} else if (i <= -1e+62) {
		tmp = t_2;
	} else if (i <= -6e-32) {
		tmp = a * ((b * i) - (x * t));
	} else if (i <= 1.1e-113) {
		tmp = t_2;
	} else if (i <= 1.08e+46) {
		tmp = (j * ((t * c) - (y * i))) - t_1;
	} else if (i <= 7.3e+133) {
		tmp = t_2;
	} else {
		tmp = t_3;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = x * ((t * a) - (y * z))
	t_2 = (c * ((t * j) - (z * b))) - t_1
	t_3 = i * ((a * b) - (y * j))
	tmp = 0
	if i <= -4.8e+101:
		tmp = t_3
	elif i <= -1e+62:
		tmp = t_2
	elif i <= -6e-32:
		tmp = a * ((b * i) - (x * t))
	elif i <= 1.1e-113:
		tmp = t_2
	elif i <= 1.08e+46:
		tmp = (j * ((t * c) - (y * i))) - t_1
	elif i <= 7.3e+133:
		tmp = t_2
	else:
		tmp = t_3
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(x * Float64(Float64(t * a) - Float64(y * z)))
	t_2 = Float64(Float64(c * Float64(Float64(t * j) - Float64(z * b))) - t_1)
	t_3 = Float64(i * Float64(Float64(a * b) - Float64(y * j)))
	tmp = 0.0
	if (i <= -4.8e+101)
		tmp = t_3;
	elseif (i <= -1e+62)
		tmp = t_2;
	elseif (i <= -6e-32)
		tmp = Float64(a * Float64(Float64(b * i) - Float64(x * t)));
	elseif (i <= 1.1e-113)
		tmp = t_2;
	elseif (i <= 1.08e+46)
		tmp = Float64(Float64(j * Float64(Float64(t * c) - Float64(y * i))) - t_1);
	elseif (i <= 7.3e+133)
		tmp = t_2;
	else
		tmp = t_3;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = x * ((t * a) - (y * z));
	t_2 = (c * ((t * j) - (z * b))) - t_1;
	t_3 = i * ((a * b) - (y * j));
	tmp = 0.0;
	if (i <= -4.8e+101)
		tmp = t_3;
	elseif (i <= -1e+62)
		tmp = t_2;
	elseif (i <= -6e-32)
		tmp = a * ((b * i) - (x * t));
	elseif (i <= 1.1e-113)
		tmp = t_2;
	elseif (i <= 1.08e+46)
		tmp = (j * ((t * c) - (y * i))) - t_1;
	elseif (i <= 7.3e+133)
		tmp = t_2;
	else
		tmp = t_3;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(x * N[(N[(t * a), $MachinePrecision] - N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(c * N[(N[(t * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$1), $MachinePrecision]}, Block[{t$95$3 = N[(i * N[(N[(a * b), $MachinePrecision] - N[(y * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[i, -4.8e+101], t$95$3, If[LessEqual[i, -1e+62], t$95$2, If[LessEqual[i, -6e-32], N[(a * N[(N[(b * i), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 1.1e-113], t$95$2, If[LessEqual[i, 1.08e+46], N[(N[(j * N[(N[(t * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$1), $MachinePrecision], If[LessEqual[i, 7.3e+133], t$95$2, t$95$3]]]]]]]]]

Derivation

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

Alternative 6: 68.1% accurate, 0.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := c \cdot \left(t \cdot j - z \cdot b\right) - y \cdot \left(i \cdot j - x \cdot z\right)\\ t_2 := x \cdot \left(t \cdot a - y \cdot z\right)\\ \mathbf{if}\;a \leq -1.1 \cdot 10^{-45}:\\ \;\;\;\;a \cdot \left(b \cdot i\right) - \left(i \cdot \left(y \cdot j\right) + t_2\right)\\ \mathbf{elif}\;a \leq 2.6 \cdot 10^{-303}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 5.5 \cdot 10^{-39}:\\ \;\;\;\;j \cdot \left(t \cdot c - y \cdot i\right) - \left(c \cdot \left(z \cdot b\right) + t_2\right)\\ \mathbf{elif}\;a \leq 1.12 \cdot 10^{+14}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;x \cdot \left(y \cdot z - t \cdot a\right) + b \cdot \left(a \cdot i - z \cdot c\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (- (* c (- (* t j) (* z b))) (* y (- (* i j) (* x z)))))
        (t_2 (* x (- (* t a) (* y z)))))
   (if (<= a -1.1e-45)
     (- (* a (* b i)) (+ (* i (* y j)) t_2))
     (if (<= a 2.6e-303)
       t_1
       (if (<= a 5.5e-39)
         (- (* j (- (* t c) (* y i))) (+ (* c (* z b)) t_2))
         (if (<= a 1.12e+14)
           t_1
           (+ (* x (- (* y z) (* t a))) (* b (- (* a i) (* z c))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = (c * ((t * j) - (z * b))) - (y * ((i * j) - (x * z)));
	double t_2 = x * ((t * a) - (y * z));
	double tmp;
	if (a <= -1.1e-45) {
		tmp = (a * (b * i)) - ((i * (y * j)) + t_2);
	} else if (a <= 2.6e-303) {
		tmp = t_1;
	} else if (a <= 5.5e-39) {
		tmp = (j * ((t * c) - (y * i))) - ((c * (z * b)) + t_2);
	} else if (a <= 1.12e+14) {
		tmp = t_1;
	} else {
		tmp = (x * ((y * z) - (t * a))) + (b * ((a * i) - (z * c)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = (c * ((t * j) - (z * b))) - (y * ((i * j) - (x * z)))
    t_2 = x * ((t * a) - (y * z))
    if (a <= (-1.1d-45)) then
        tmp = (a * (b * i)) - ((i * (y * j)) + t_2)
    else if (a <= 2.6d-303) then
        tmp = t_1
    else if (a <= 5.5d-39) then
        tmp = (j * ((t * c) - (y * i))) - ((c * (z * b)) + t_2)
    else if (a <= 1.12d+14) then
        tmp = t_1
    else
        tmp = (x * ((y * z) - (t * a))) + (b * ((a * i) - (z * c)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = (c * ((t * j) - (z * b))) - (y * ((i * j) - (x * z)));
	double t_2 = x * ((t * a) - (y * z));
	double tmp;
	if (a <= -1.1e-45) {
		tmp = (a * (b * i)) - ((i * (y * j)) + t_2);
	} else if (a <= 2.6e-303) {
		tmp = t_1;
	} else if (a <= 5.5e-39) {
		tmp = (j * ((t * c) - (y * i))) - ((c * (z * b)) + t_2);
	} else if (a <= 1.12e+14) {
		tmp = t_1;
	} else {
		tmp = (x * ((y * z) - (t * a))) + (b * ((a * i) - (z * c)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = (c * ((t * j) - (z * b))) - (y * ((i * j) - (x * z)))
	t_2 = x * ((t * a) - (y * z))
	tmp = 0
	if a <= -1.1e-45:
		tmp = (a * (b * i)) - ((i * (y * j)) + t_2)
	elif a <= 2.6e-303:
		tmp = t_1
	elif a <= 5.5e-39:
		tmp = (j * ((t * c) - (y * i))) - ((c * (z * b)) + t_2)
	elif a <= 1.12e+14:
		tmp = t_1
	else:
		tmp = (x * ((y * z) - (t * a))) + (b * ((a * i) - (z * c)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(Float64(c * Float64(Float64(t * j) - Float64(z * b))) - Float64(y * Float64(Float64(i * j) - Float64(x * z))))
	t_2 = Float64(x * Float64(Float64(t * a) - Float64(y * z)))
	tmp = 0.0
	if (a <= -1.1e-45)
		tmp = Float64(Float64(a * Float64(b * i)) - Float64(Float64(i * Float64(y * j)) + t_2));
	elseif (a <= 2.6e-303)
		tmp = t_1;
	elseif (a <= 5.5e-39)
		tmp = Float64(Float64(j * Float64(Float64(t * c) - Float64(y * i))) - Float64(Float64(c * Float64(z * b)) + t_2));
	elseif (a <= 1.12e+14)
		tmp = t_1;
	else
		tmp = Float64(Float64(x * Float64(Float64(y * z) - Float64(t * a))) + Float64(b * Float64(Float64(a * i) - Float64(z * c))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = (c * ((t * j) - (z * b))) - (y * ((i * j) - (x * z)));
	t_2 = x * ((t * a) - (y * z));
	tmp = 0.0;
	if (a <= -1.1e-45)
		tmp = (a * (b * i)) - ((i * (y * j)) + t_2);
	elseif (a <= 2.6e-303)
		tmp = t_1;
	elseif (a <= 5.5e-39)
		tmp = (j * ((t * c) - (y * i))) - ((c * (z * b)) + t_2);
	elseif (a <= 1.12e+14)
		tmp = t_1;
	else
		tmp = (x * ((y * z) - (t * a))) + (b * ((a * i) - (z * c)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(N[(c * N[(N[(t * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y * N[(N[(i * j), $MachinePrecision] - N[(x * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(x * N[(N[(t * a), $MachinePrecision] - N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -1.1e-45], N[(N[(a * N[(b * i), $MachinePrecision]), $MachinePrecision] - N[(N[(i * N[(y * j), $MachinePrecision]), $MachinePrecision] + t$95$2), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 2.6e-303], t$95$1, If[LessEqual[a, 5.5e-39], N[(N[(j * N[(N[(t * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(c * N[(z * b), $MachinePrecision]), $MachinePrecision] + t$95$2), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 1.12e+14], t$95$1, N[(N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(b * N[(N[(a * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]

Derivation

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

Alternative 7: 65.4% accurate, 1.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(t \cdot c - y \cdot i\right)\\ t_2 := y \cdot \left(x \cdot z\right) - b \cdot \left(z \cdot c - a \cdot i\right)\\ t_3 := t_1 - x \cdot \left(t \cdot a - y \cdot z\right)\\ \mathbf{if}\;b \leq -1.02 \cdot 10^{+67}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;b \leq -2.05 \cdot 10^{-50}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;b \leq -2.4 \cdot 10^{-73}:\\ \;\;\;\;c \cdot \left(t \cdot j - z \cdot b\right) + z \cdot \left(x \cdot y\right)\\ \mathbf{elif}\;b \leq 4.8:\\ \;\;\;\;t_3\\ \mathbf{elif}\;b \leq 8.5 \cdot 10^{+108}:\\ \;\;\;\;a \cdot \left(b \cdot i - x \cdot t\right)\\ \mathbf{elif}\;b \leq 1.35 \cdot 10^{+135}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* j (- (* t c) (* y i))))
        (t_2 (- (* y (* x z)) (* b (- (* z c) (* a i)))))
        (t_3 (- t_1 (* x (- (* t a) (* y z))))))
   (if (<= b -1.02e+67)
     t_2
     (if (<= b -2.05e-50)
       t_3
       (if (<= b -2.4e-73)
         (+ (* c (- (* t j) (* z b))) (* z (* x y)))
         (if (<= b 4.8)
           t_3
           (if (<= b 8.5e+108)
             (* a (- (* b i) (* x t)))
             (if (<= b 1.35e+135) 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 * ((t * c) - (y * i));
	double t_2 = (y * (x * z)) - (b * ((z * c) - (a * i)));
	double t_3 = t_1 - (x * ((t * a) - (y * z)));
	double tmp;
	if (b <= -1.02e+67) {
		tmp = t_2;
	} else if (b <= -2.05e-50) {
		tmp = t_3;
	} else if (b <= -2.4e-73) {
		tmp = (c * ((t * j) - (z * b))) + (z * (x * y));
	} else if (b <= 4.8) {
		tmp = t_3;
	} else if (b <= 8.5e+108) {
		tmp = a * ((b * i) - (x * t));
	} else if (b <= 1.35e+135) {
		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) :: t_3
    real(8) :: tmp
    t_1 = j * ((t * c) - (y * i))
    t_2 = (y * (x * z)) - (b * ((z * c) - (a * i)))
    t_3 = t_1 - (x * ((t * a) - (y * z)))
    if (b <= (-1.02d+67)) then
        tmp = t_2
    else if (b <= (-2.05d-50)) then
        tmp = t_3
    else if (b <= (-2.4d-73)) then
        tmp = (c * ((t * j) - (z * b))) + (z * (x * y))
    else if (b <= 4.8d0) then
        tmp = t_3
    else if (b <= 8.5d+108) then
        tmp = a * ((b * i) - (x * t))
    else if (b <= 1.35d+135) 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 = j * ((t * c) - (y * i));
	double t_2 = (y * (x * z)) - (b * ((z * c) - (a * i)));
	double t_3 = t_1 - (x * ((t * a) - (y * z)));
	double tmp;
	if (b <= -1.02e+67) {
		tmp = t_2;
	} else if (b <= -2.05e-50) {
		tmp = t_3;
	} else if (b <= -2.4e-73) {
		tmp = (c * ((t * j) - (z * b))) + (z * (x * y));
	} else if (b <= 4.8) {
		tmp = t_3;
	} else if (b <= 8.5e+108) {
		tmp = a * ((b * i) - (x * t));
	} else if (b <= 1.35e+135) {
		tmp = t_1;
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = j * ((t * c) - (y * i))
	t_2 = (y * (x * z)) - (b * ((z * c) - (a * i)))
	t_3 = t_1 - (x * ((t * a) - (y * z)))
	tmp = 0
	if b <= -1.02e+67:
		tmp = t_2
	elif b <= -2.05e-50:
		tmp = t_3
	elif b <= -2.4e-73:
		tmp = (c * ((t * j) - (z * b))) + (z * (x * y))
	elif b <= 4.8:
		tmp = t_3
	elif b <= 8.5e+108:
		tmp = a * ((b * i) - (x * t))
	elif b <= 1.35e+135:
		tmp = 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(t * c) - Float64(y * i)))
	t_2 = Float64(Float64(y * Float64(x * z)) - Float64(b * Float64(Float64(z * c) - Float64(a * i))))
	t_3 = Float64(t_1 - Float64(x * Float64(Float64(t * a) - Float64(y * z))))
	tmp = 0.0
	if (b <= -1.02e+67)
		tmp = t_2;
	elseif (b <= -2.05e-50)
		tmp = t_3;
	elseif (b <= -2.4e-73)
		tmp = Float64(Float64(c * Float64(Float64(t * j) - Float64(z * b))) + Float64(z * Float64(x * y)));
	elseif (b <= 4.8)
		tmp = t_3;
	elseif (b <= 8.5e+108)
		tmp = Float64(a * Float64(Float64(b * i) - Float64(x * t)));
	elseif (b <= 1.35e+135)
		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 = j * ((t * c) - (y * i));
	t_2 = (y * (x * z)) - (b * ((z * c) - (a * i)));
	t_3 = t_1 - (x * ((t * a) - (y * z)));
	tmp = 0.0;
	if (b <= -1.02e+67)
		tmp = t_2;
	elseif (b <= -2.05e-50)
		tmp = t_3;
	elseif (b <= -2.4e-73)
		tmp = (c * ((t * j) - (z * b))) + (z * (x * y));
	elseif (b <= 4.8)
		tmp = t_3;
	elseif (b <= 8.5e+108)
		tmp = a * ((b * i) - (x * t));
	elseif (b <= 1.35e+135)
		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[(j * N[(N[(t * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(y * N[(x * z), $MachinePrecision]), $MachinePrecision] - N[(b * N[(N[(z * c), $MachinePrecision] - N[(a * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(t$95$1 - N[(x * N[(N[(t * a), $MachinePrecision] - N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[b, -1.02e+67], t$95$2, If[LessEqual[b, -2.05e-50], t$95$3, If[LessEqual[b, -2.4e-73], N[(N[(c * N[(N[(t * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(z * N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[b, 4.8], t$95$3, If[LessEqual[b, 8.5e+108], N[(a * N[(N[(b * i), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[b, 1.35e+135], t$95$1, t$95$2]]]]]]]]]

Derivation

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

Alternative 8: 66.7% accurate, 1.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;a \leq -3.9 \cdot 10^{+89} \lor \neg \left(a \leq -0.000235 \lor \neg \left(a \leq -8.5 \cdot 10^{-46}\right) \land a \leq 850000000\right):\\ \;\;\;\;x \cdot \left(y \cdot z - t \cdot a\right) + b \cdot \left(a \cdot i - z \cdot c\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(t \cdot j - z \cdot b\right) - y \cdot \left(i \cdot j - x \cdot z\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (or (<= a -3.9e+89)
         (not
          (or (<= a -0.000235)
              (and (not (<= a -8.5e-46)) (<= a 850000000.0)))))
   (+ (* x (- (* y z) (* t a))) (* b (- (* a i) (* z c))))
   (- (* c (- (* t j) (* z b))) (* y (- (* i j) (* x z))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if ((a <= -3.9e+89) || !((a <= -0.000235) || (!(a <= -8.5e-46) && (a <= 850000000.0)))) {
		tmp = (x * ((y * z) - (t * a))) + (b * ((a * i) - (z * c)));
	} else {
		tmp = (c * ((t * j) - (z * b))) - (y * ((i * j) - (x * z)));
	}
	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 ((a <= (-3.9d+89)) .or. (.not. (a <= (-0.000235d0)) .or. (.not. (a <= (-8.5d-46))) .and. (a <= 850000000.0d0))) then
        tmp = (x * ((y * z) - (t * a))) + (b * ((a * i) - (z * c)))
    else
        tmp = (c * ((t * j) - (z * b))) - (y * ((i * j) - (x * z)))
    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 ((a <= -3.9e+89) || !((a <= -0.000235) || (!(a <= -8.5e-46) && (a <= 850000000.0)))) {
		tmp = (x * ((y * z) - (t * a))) + (b * ((a * i) - (z * c)));
	} else {
		tmp = (c * ((t * j) - (z * b))) - (y * ((i * j) - (x * z)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if (a <= -3.9e+89) or not ((a <= -0.000235) or (not (a <= -8.5e-46) and (a <= 850000000.0))):
		tmp = (x * ((y * z) - (t * a))) + (b * ((a * i) - (z * c)))
	else:
		tmp = (c * ((t * j) - (z * b))) - (y * ((i * j) - (x * z)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if ((a <= -3.9e+89) || !((a <= -0.000235) || (!(a <= -8.5e-46) && (a <= 850000000.0))))
		tmp = Float64(Float64(x * Float64(Float64(y * z) - Float64(t * a))) + Float64(b * Float64(Float64(a * i) - Float64(z * c))));
	else
		tmp = Float64(Float64(c * Float64(Float64(t * j) - Float64(z * b))) - Float64(y * Float64(Float64(i * j) - Float64(x * z))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0;
	if ((a <= -3.9e+89) || ~(((a <= -0.000235) || (~((a <= -8.5e-46)) && (a <= 850000000.0)))))
		tmp = (x * ((y * z) - (t * a))) + (b * ((a * i) - (z * c)));
	else
		tmp = (c * ((t * j) - (z * b))) - (y * ((i * j) - (x * z)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[Or[LessEqual[a, -3.9e+89], N[Not[Or[LessEqual[a, -0.000235], And[N[Not[LessEqual[a, -8.5e-46]], $MachinePrecision], LessEqual[a, 850000000.0]]]], $MachinePrecision]], N[(N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(b * N[(N[(a * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(c * N[(N[(t * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y * N[(N[(i * j), $MachinePrecision] - N[(x * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

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

Alternative 9: 65.7% accurate, 1.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := c \cdot \left(t \cdot j - z \cdot b\right)\\ t_2 := a \cdot \left(b \cdot i - x \cdot t\right)\\ \mathbf{if}\;a \leq -1.75 \cdot 10^{+89}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq 8200000000:\\ \;\;\;\;t_1 - y \cdot \left(i \cdot j - x \cdot z\right)\\ \mathbf{elif}\;a \leq 1.7 \cdot 10^{+106}:\\ \;\;\;\;b \cdot \left(a \cdot i - z \cdot c\right)\\ \mathbf{elif}\;a \leq 6 \cdot 10^{+142}:\\ \;\;\;\;t_1 - x \cdot \left(t \cdot a - y \cdot z\right)\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* c (- (* t j) (* z b)))) (t_2 (* a (- (* b i) (* x t)))))
   (if (<= a -1.75e+89)
     t_2
     (if (<= a 8200000000.0)
       (- t_1 (* y (- (* i j) (* x z))))
       (if (<= a 1.7e+106)
         (* b (- (* a i) (* z c)))
         (if (<= a 6e+142) (- t_1 (* x (- (* t a) (* y z)))) t_2))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = c * ((t * j) - (z * b));
	double t_2 = a * ((b * i) - (x * t));
	double tmp;
	if (a <= -1.75e+89) {
		tmp = t_2;
	} else if (a <= 8200000000.0) {
		tmp = t_1 - (y * ((i * j) - (x * z)));
	} else if (a <= 1.7e+106) {
		tmp = b * ((a * i) - (z * c));
	} else if (a <= 6e+142) {
		tmp = t_1 - (x * ((t * a) - (y * z)));
	} else {
		tmp = t_2;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = c * ((t * j) - (z * b))
    t_2 = a * ((b * i) - (x * t))
    if (a <= (-1.75d+89)) then
        tmp = t_2
    else if (a <= 8200000000.0d0) then
        tmp = t_1 - (y * ((i * j) - (x * z)))
    else if (a <= 1.7d+106) then
        tmp = b * ((a * i) - (z * c))
    else if (a <= 6d+142) then
        tmp = t_1 - (x * ((t * a) - (y * z)))
    else
        tmp = t_2
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = c * ((t * j) - (z * b));
	double t_2 = a * ((b * i) - (x * t));
	double tmp;
	if (a <= -1.75e+89) {
		tmp = t_2;
	} else if (a <= 8200000000.0) {
		tmp = t_1 - (y * ((i * j) - (x * z)));
	} else if (a <= 1.7e+106) {
		tmp = b * ((a * i) - (z * c));
	} else if (a <= 6e+142) {
		tmp = t_1 - (x * ((t * a) - (y * z)));
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = c * ((t * j) - (z * b))
	t_2 = a * ((b * i) - (x * t))
	tmp = 0
	if a <= -1.75e+89:
		tmp = t_2
	elif a <= 8200000000.0:
		tmp = t_1 - (y * ((i * j) - (x * z)))
	elif a <= 1.7e+106:
		tmp = b * ((a * i) - (z * c))
	elif a <= 6e+142:
		tmp = t_1 - (x * ((t * a) - (y * z)))
	else:
		tmp = t_2
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(c * Float64(Float64(t * j) - Float64(z * b)))
	t_2 = Float64(a * Float64(Float64(b * i) - Float64(x * t)))
	tmp = 0.0
	if (a <= -1.75e+89)
		tmp = t_2;
	elseif (a <= 8200000000.0)
		tmp = Float64(t_1 - Float64(y * Float64(Float64(i * j) - Float64(x * z))));
	elseif (a <= 1.7e+106)
		tmp = Float64(b * Float64(Float64(a * i) - Float64(z * c)));
	elseif (a <= 6e+142)
		tmp = Float64(t_1 - Float64(x * Float64(Float64(t * a) - Float64(y * z))));
	else
		tmp = t_2;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = c * ((t * j) - (z * b));
	t_2 = a * ((b * i) - (x * t));
	tmp = 0.0;
	if (a <= -1.75e+89)
		tmp = t_2;
	elseif (a <= 8200000000.0)
		tmp = t_1 - (y * ((i * j) - (x * z)));
	elseif (a <= 1.7e+106)
		tmp = b * ((a * i) - (z * c));
	elseif (a <= 6e+142)
		tmp = t_1 - (x * ((t * a) - (y * z)));
	else
		tmp = t_2;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(c * N[(N[(t * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(a * N[(N[(b * i), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -1.75e+89], t$95$2, If[LessEqual[a, 8200000000.0], N[(t$95$1 - N[(y * N[(N[(i * j), $MachinePrecision] - N[(x * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 1.7e+106], N[(b * N[(N[(a * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 6e+142], N[(t$95$1 - N[(x * N[(N[(t * a), $MachinePrecision] - N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$2]]]]]]

Derivation

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

Alternative 10: 58.5% accurate, 1.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot \left(b \cdot i - x \cdot t\right)\\ \mathbf{if}\;a \leq -1.2 \cdot 10^{+77}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -2.45 \cdot 10^{-45}:\\ \;\;\;\;y \cdot \left(x \cdot z\right) - b \cdot \left(z \cdot c - a \cdot i\right)\\ \mathbf{elif}\;a \leq 16600000000:\\ \;\;\;\;c \cdot \left(t \cdot j - z \cdot b\right) + z \cdot \left(x \cdot y\right)\\ \mathbf{elif}\;a \leq 9.2 \cdot 10^{+108}:\\ \;\;\;\;b \cdot \left(a \cdot i - z \cdot c\right)\\ \mathbf{elif}\;a \leq 7.6 \cdot 10^{+142}:\\ \;\;\;\;x \cdot \left(y \cdot z - t \cdot a\right) - c \cdot \left(z \cdot b\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* a (- (* b i) (* x t)))))
   (if (<= a -1.2e+77)
     t_1
     (if (<= a -2.45e-45)
       (- (* y (* x z)) (* b (- (* z c) (* a i))))
       (if (<= a 16600000000.0)
         (+ (* c (- (* t j) (* z b))) (* z (* x y)))
         (if (<= a 9.2e+108)
           (* b (- (* a i) (* z c)))
           (if (<= a 7.6e+142)
             (- (* x (- (* y z) (* t a))) (* c (* z b)))
             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 * ((b * i) - (x * t));
	double tmp;
	if (a <= -1.2e+77) {
		tmp = t_1;
	} else if (a <= -2.45e-45) {
		tmp = (y * (x * z)) - (b * ((z * c) - (a * i)));
	} else if (a <= 16600000000.0) {
		tmp = (c * ((t * j) - (z * b))) + (z * (x * y));
	} else if (a <= 9.2e+108) {
		tmp = b * ((a * i) - (z * c));
	} else if (a <= 7.6e+142) {
		tmp = (x * ((y * z) - (t * a))) - (c * (z * b));
	} 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 * ((b * i) - (x * t))
    if (a <= (-1.2d+77)) then
        tmp = t_1
    else if (a <= (-2.45d-45)) then
        tmp = (y * (x * z)) - (b * ((z * c) - (a * i)))
    else if (a <= 16600000000.0d0) then
        tmp = (c * ((t * j) - (z * b))) + (z * (x * y))
    else if (a <= 9.2d+108) then
        tmp = b * ((a * i) - (z * c))
    else if (a <= 7.6d+142) then
        tmp = (x * ((y * z) - (t * a))) - (c * (z * b))
    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 * ((b * i) - (x * t));
	double tmp;
	if (a <= -1.2e+77) {
		tmp = t_1;
	} else if (a <= -2.45e-45) {
		tmp = (y * (x * z)) - (b * ((z * c) - (a * i)));
	} else if (a <= 16600000000.0) {
		tmp = (c * ((t * j) - (z * b))) + (z * (x * y));
	} else if (a <= 9.2e+108) {
		tmp = b * ((a * i) - (z * c));
	} else if (a <= 7.6e+142) {
		tmp = (x * ((y * z) - (t * a))) - (c * (z * b));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = a * ((b * i) - (x * t))
	tmp = 0
	if a <= -1.2e+77:
		tmp = t_1
	elif a <= -2.45e-45:
		tmp = (y * (x * z)) - (b * ((z * c) - (a * i)))
	elif a <= 16600000000.0:
		tmp = (c * ((t * j) - (z * b))) + (z * (x * y))
	elif a <= 9.2e+108:
		tmp = b * ((a * i) - (z * c))
	elif a <= 7.6e+142:
		tmp = (x * ((y * z) - (t * a))) - (c * (z * b))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(a * Float64(Float64(b * i) - Float64(x * t)))
	tmp = 0.0
	if (a <= -1.2e+77)
		tmp = t_1;
	elseif (a <= -2.45e-45)
		tmp = Float64(Float64(y * Float64(x * z)) - Float64(b * Float64(Float64(z * c) - Float64(a * i))));
	elseif (a <= 16600000000.0)
		tmp = Float64(Float64(c * Float64(Float64(t * j) - Float64(z * b))) + Float64(z * Float64(x * y)));
	elseif (a <= 9.2e+108)
		tmp = Float64(b * Float64(Float64(a * i) - Float64(z * c)));
	elseif (a <= 7.6e+142)
		tmp = Float64(Float64(x * Float64(Float64(y * z) - Float64(t * a))) - Float64(c * Float64(z * b)));
	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 * ((b * i) - (x * t));
	tmp = 0.0;
	if (a <= -1.2e+77)
		tmp = t_1;
	elseif (a <= -2.45e-45)
		tmp = (y * (x * z)) - (b * ((z * c) - (a * i)));
	elseif (a <= 16600000000.0)
		tmp = (c * ((t * j) - (z * b))) + (z * (x * y));
	elseif (a <= 9.2e+108)
		tmp = b * ((a * i) - (z * c));
	elseif (a <= 7.6e+142)
		tmp = (x * ((y * z) - (t * a))) - (c * (z * b));
	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[(b * i), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -1.2e+77], t$95$1, If[LessEqual[a, -2.45e-45], N[(N[(y * N[(x * z), $MachinePrecision]), $MachinePrecision] - N[(b * N[(N[(z * c), $MachinePrecision] - N[(a * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 16600000000.0], N[(N[(c * N[(N[(t * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(z * N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 9.2e+108], N[(b * N[(N[(a * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 7.6e+142], N[(N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(c * N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]

Derivation

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

Alternative 11: 59.0% accurate, 1.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot \left(b \cdot i - x \cdot t\right)\\ \mathbf{if}\;a \leq -5.5 \cdot 10^{+75}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 940000000000:\\ \;\;\;\;c \cdot \left(t \cdot j - z \cdot b\right) + z \cdot \left(x \cdot y\right)\\ \mathbf{elif}\;a \leq 3.7 \cdot 10^{+106}:\\ \;\;\;\;b \cdot \left(a \cdot i - z \cdot c\right)\\ \mathbf{elif}\;a \leq 4.4 \cdot 10^{+142}:\\ \;\;\;\;x \cdot \left(y \cdot z - t \cdot a\right) - c \cdot \left(z \cdot b\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* a (- (* b i) (* x t)))))
   (if (<= a -5.5e+75)
     t_1
     (if (<= a 940000000000.0)
       (+ (* c (- (* t j) (* z b))) (* z (* x y)))
       (if (<= a 3.7e+106)
         (* b (- (* a i) (* z c)))
         (if (<= a 4.4e+142)
           (- (* x (- (* y z) (* t a))) (* c (* z b)))
           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 * ((b * i) - (x * t));
	double tmp;
	if (a <= -5.5e+75) {
		tmp = t_1;
	} else if (a <= 940000000000.0) {
		tmp = (c * ((t * j) - (z * b))) + (z * (x * y));
	} else if (a <= 3.7e+106) {
		tmp = b * ((a * i) - (z * c));
	} else if (a <= 4.4e+142) {
		tmp = (x * ((y * z) - (t * a))) - (c * (z * b));
	} 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 * ((b * i) - (x * t))
    if (a <= (-5.5d+75)) then
        tmp = t_1
    else if (a <= 940000000000.0d0) then
        tmp = (c * ((t * j) - (z * b))) + (z * (x * y))
    else if (a <= 3.7d+106) then
        tmp = b * ((a * i) - (z * c))
    else if (a <= 4.4d+142) then
        tmp = (x * ((y * z) - (t * a))) - (c * (z * b))
    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 * ((b * i) - (x * t));
	double tmp;
	if (a <= -5.5e+75) {
		tmp = t_1;
	} else if (a <= 940000000000.0) {
		tmp = (c * ((t * j) - (z * b))) + (z * (x * y));
	} else if (a <= 3.7e+106) {
		tmp = b * ((a * i) - (z * c));
	} else if (a <= 4.4e+142) {
		tmp = (x * ((y * z) - (t * a))) - (c * (z * b));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = a * ((b * i) - (x * t))
	tmp = 0
	if a <= -5.5e+75:
		tmp = t_1
	elif a <= 940000000000.0:
		tmp = (c * ((t * j) - (z * b))) + (z * (x * y))
	elif a <= 3.7e+106:
		tmp = b * ((a * i) - (z * c))
	elif a <= 4.4e+142:
		tmp = (x * ((y * z) - (t * a))) - (c * (z * b))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(a * Float64(Float64(b * i) - Float64(x * t)))
	tmp = 0.0
	if (a <= -5.5e+75)
		tmp = t_1;
	elseif (a <= 940000000000.0)
		tmp = Float64(Float64(c * Float64(Float64(t * j) - Float64(z * b))) + Float64(z * Float64(x * y)));
	elseif (a <= 3.7e+106)
		tmp = Float64(b * Float64(Float64(a * i) - Float64(z * c)));
	elseif (a <= 4.4e+142)
		tmp = Float64(Float64(x * Float64(Float64(y * z) - Float64(t * a))) - Float64(c * Float64(z * b)));
	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 * ((b * i) - (x * t));
	tmp = 0.0;
	if (a <= -5.5e+75)
		tmp = t_1;
	elseif (a <= 940000000000.0)
		tmp = (c * ((t * j) - (z * b))) + (z * (x * y));
	elseif (a <= 3.7e+106)
		tmp = b * ((a * i) - (z * c));
	elseif (a <= 4.4e+142)
		tmp = (x * ((y * z) - (t * a))) - (c * (z * b));
	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[(b * i), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -5.5e+75], t$95$1, If[LessEqual[a, 940000000000.0], N[(N[(c * N[(N[(t * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(z * N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 3.7e+106], N[(b * N[(N[(a * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 4.4e+142], N[(N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(c * N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]

Derivation

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

Alternative 12: 52.0% accurate, 1.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(t \cdot c - y \cdot i\right)\\ t_2 := a \cdot \left(b \cdot i - x \cdot t\right)\\ \mathbf{if}\;a \leq -1.45 \cdot 10^{+69}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq -7 \cdot 10^{-83}:\\ \;\;\;\;y \cdot \left(x \cdot z - i \cdot j\right)\\ \mathbf{elif}\;a \leq -4.6 \cdot 10^{-190}:\\ \;\;\;\;z \cdot \left(x \cdot y - b \cdot c\right)\\ \mathbf{elif}\;a \leq -3.9 \cdot 10^{-230}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -1.7 \cdot 10^{-280}:\\ \;\;\;\;c \cdot \left(t \cdot j - z \cdot b\right)\\ \mathbf{elif}\;a \leq 162000:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* j (- (* t c) (* y i)))) (t_2 (* a (- (* b i) (* x t)))))
   (if (<= a -1.45e+69)
     t_2
     (if (<= a -7e-83)
       (* y (- (* x z) (* i j)))
       (if (<= a -4.6e-190)
         (* z (- (* x y) (* b c)))
         (if (<= a -3.9e-230)
           t_1
           (if (<= a -1.7e-280)
             (* c (- (* t j) (* z b)))
             (if (<= a 162000.0) 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 * ((t * c) - (y * i));
	double t_2 = a * ((b * i) - (x * t));
	double tmp;
	if (a <= -1.45e+69) {
		tmp = t_2;
	} else if (a <= -7e-83) {
		tmp = y * ((x * z) - (i * j));
	} else if (a <= -4.6e-190) {
		tmp = z * ((x * y) - (b * c));
	} else if (a <= -3.9e-230) {
		tmp = t_1;
	} else if (a <= -1.7e-280) {
		tmp = c * ((t * j) - (z * b));
	} else if (a <= 162000.0) {
		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 = j * ((t * c) - (y * i))
    t_2 = a * ((b * i) - (x * t))
    if (a <= (-1.45d+69)) then
        tmp = t_2
    else if (a <= (-7d-83)) then
        tmp = y * ((x * z) - (i * j))
    else if (a <= (-4.6d-190)) then
        tmp = z * ((x * y) - (b * c))
    else if (a <= (-3.9d-230)) then
        tmp = t_1
    else if (a <= (-1.7d-280)) then
        tmp = c * ((t * j) - (z * b))
    else if (a <= 162000.0d0) 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 = j * ((t * c) - (y * i));
	double t_2 = a * ((b * i) - (x * t));
	double tmp;
	if (a <= -1.45e+69) {
		tmp = t_2;
	} else if (a <= -7e-83) {
		tmp = y * ((x * z) - (i * j));
	} else if (a <= -4.6e-190) {
		tmp = z * ((x * y) - (b * c));
	} else if (a <= -3.9e-230) {
		tmp = t_1;
	} else if (a <= -1.7e-280) {
		tmp = c * ((t * j) - (z * b));
	} else if (a <= 162000.0) {
		tmp = t_1;
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = j * ((t * c) - (y * i))
	t_2 = a * ((b * i) - (x * t))
	tmp = 0
	if a <= -1.45e+69:
		tmp = t_2
	elif a <= -7e-83:
		tmp = y * ((x * z) - (i * j))
	elif a <= -4.6e-190:
		tmp = z * ((x * y) - (b * c))
	elif a <= -3.9e-230:
		tmp = t_1
	elif a <= -1.7e-280:
		tmp = c * ((t * j) - (z * b))
	elif a <= 162000.0:
		tmp = 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(t * c) - Float64(y * i)))
	t_2 = Float64(a * Float64(Float64(b * i) - Float64(x * t)))
	tmp = 0.0
	if (a <= -1.45e+69)
		tmp = t_2;
	elseif (a <= -7e-83)
		tmp = Float64(y * Float64(Float64(x * z) - Float64(i * j)));
	elseif (a <= -4.6e-190)
		tmp = Float64(z * Float64(Float64(x * y) - Float64(b * c)));
	elseif (a <= -3.9e-230)
		tmp = t_1;
	elseif (a <= -1.7e-280)
		tmp = Float64(c * Float64(Float64(t * j) - Float64(z * b)));
	elseif (a <= 162000.0)
		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 = j * ((t * c) - (y * i));
	t_2 = a * ((b * i) - (x * t));
	tmp = 0.0;
	if (a <= -1.45e+69)
		tmp = t_2;
	elseif (a <= -7e-83)
		tmp = y * ((x * z) - (i * j));
	elseif (a <= -4.6e-190)
		tmp = z * ((x * y) - (b * c));
	elseif (a <= -3.9e-230)
		tmp = t_1;
	elseif (a <= -1.7e-280)
		tmp = c * ((t * j) - (z * b));
	elseif (a <= 162000.0)
		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[(j * N[(N[(t * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(a * N[(N[(b * i), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -1.45e+69], t$95$2, If[LessEqual[a, -7e-83], N[(y * N[(N[(x * z), $MachinePrecision] - N[(i * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -4.6e-190], N[(z * N[(N[(x * y), $MachinePrecision] - N[(b * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -3.9e-230], t$95$1, If[LessEqual[a, -1.7e-280], N[(c * N[(N[(t * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 162000.0], t$95$1, t$95$2]]]]]]]]

Derivation

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

Alternative 13: 59.3% accurate, 1.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;a \leq -4.2 \cdot 10^{+77} \lor \neg \left(a \leq 1.65 \cdot 10^{-10}\right):\\ \;\;\;\;a \cdot \left(b \cdot i - x \cdot t\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(t \cdot j - z \cdot b\right) + z \cdot \left(x \cdot y\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (or (<= a -4.2e+77) (not (<= a 1.65e-10)))
   (* a (- (* b i) (* x t)))
   (+ (* c (- (* t j) (* z b))) (* z (* x y)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if ((a <= -4.2e+77) || !(a <= 1.65e-10)) {
		tmp = a * ((b * i) - (x * t));
	} else {
		tmp = (c * ((t * j) - (z * b))) + (z * (x * 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) :: tmp
    if ((a <= (-4.2d+77)) .or. (.not. (a <= 1.65d-10))) then
        tmp = a * ((b * i) - (x * t))
    else
        tmp = (c * ((t * j) - (z * b))) + (z * (x * 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 tmp;
	if ((a <= -4.2e+77) || !(a <= 1.65e-10)) {
		tmp = a * ((b * i) - (x * t));
	} else {
		tmp = (c * ((t * j) - (z * b))) + (z * (x * y));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if (a <= -4.2e+77) or not (a <= 1.65e-10):
		tmp = a * ((b * i) - (x * t))
	else:
		tmp = (c * ((t * j) - (z * b))) + (z * (x * y))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if ((a <= -4.2e+77) || !(a <= 1.65e-10))
		tmp = Float64(a * Float64(Float64(b * i) - Float64(x * t)));
	else
		tmp = Float64(Float64(c * Float64(Float64(t * j) - Float64(z * b))) + Float64(z * Float64(x * y)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0;
	if ((a <= -4.2e+77) || ~((a <= 1.65e-10)))
		tmp = a * ((b * i) - (x * t));
	else
		tmp = (c * ((t * j) - (z * b))) + (z * (x * y));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[Or[LessEqual[a, -4.2e+77], N[Not[LessEqual[a, 1.65e-10]], $MachinePrecision]], N[(a * N[(N[(b * i), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(c * N[(N[(t * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(z * N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

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

Alternative 14: 50.9% accurate, 1.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := c \cdot \left(t \cdot j - z \cdot b\right)\\ t_2 := a \cdot \left(b \cdot i - x \cdot t\right)\\ \mathbf{if}\;a \leq -1.02 \cdot 10^{-48}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq -2.3 \cdot 10^{-289}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 4.6 \cdot 10^{-294}:\\ \;\;\;\;i \cdot \left(y \cdot \left(-j\right)\right)\\ \mathbf{elif}\;a \leq 8.5 \cdot 10^{-11}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* c (- (* t j) (* z b)))) (t_2 (* a (- (* b i) (* x t)))))
   (if (<= a -1.02e-48)
     t_2
     (if (<= a -2.3e-289)
       t_1
       (if (<= a 4.6e-294) (* i (* y (- j))) (if (<= a 8.5e-11) t_1 t_2))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = c * ((t * j) - (z * b));
	double t_2 = a * ((b * i) - (x * t));
	double tmp;
	if (a <= -1.02e-48) {
		tmp = t_2;
	} else if (a <= -2.3e-289) {
		tmp = t_1;
	} else if (a <= 4.6e-294) {
		tmp = i * (y * -j);
	} else if (a <= 8.5e-11) {
		tmp = t_1;
	} else {
		tmp = t_2;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = c * ((t * j) - (z * b))
    t_2 = a * ((b * i) - (x * t))
    if (a <= (-1.02d-48)) then
        tmp = t_2
    else if (a <= (-2.3d-289)) then
        tmp = t_1
    else if (a <= 4.6d-294) then
        tmp = i * (y * -j)
    else if (a <= 8.5d-11) then
        tmp = t_1
    else
        tmp = t_2
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = c * ((t * j) - (z * b));
	double t_2 = a * ((b * i) - (x * t));
	double tmp;
	if (a <= -1.02e-48) {
		tmp = t_2;
	} else if (a <= -2.3e-289) {
		tmp = t_1;
	} else if (a <= 4.6e-294) {
		tmp = i * (y * -j);
	} else if (a <= 8.5e-11) {
		tmp = t_1;
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = c * ((t * j) - (z * b))
	t_2 = a * ((b * i) - (x * t))
	tmp = 0
	if a <= -1.02e-48:
		tmp = t_2
	elif a <= -2.3e-289:
		tmp = t_1
	elif a <= 4.6e-294:
		tmp = i * (y * -j)
	elif a <= 8.5e-11:
		tmp = t_1
	else:
		tmp = t_2
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(c * Float64(Float64(t * j) - Float64(z * b)))
	t_2 = Float64(a * Float64(Float64(b * i) - Float64(x * t)))
	tmp = 0.0
	if (a <= -1.02e-48)
		tmp = t_2;
	elseif (a <= -2.3e-289)
		tmp = t_1;
	elseif (a <= 4.6e-294)
		tmp = Float64(i * Float64(y * Float64(-j)));
	elseif (a <= 8.5e-11)
		tmp = t_1;
	else
		tmp = t_2;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = c * ((t * j) - (z * b));
	t_2 = a * ((b * i) - (x * t));
	tmp = 0.0;
	if (a <= -1.02e-48)
		tmp = t_2;
	elseif (a <= -2.3e-289)
		tmp = t_1;
	elseif (a <= 4.6e-294)
		tmp = i * (y * -j);
	elseif (a <= 8.5e-11)
		tmp = t_1;
	else
		tmp = t_2;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(c * N[(N[(t * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(a * N[(N[(b * i), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -1.02e-48], t$95$2, If[LessEqual[a, -2.3e-289], t$95$1, If[LessEqual[a, 4.6e-294], N[(i * N[(y * (-j)), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 8.5e-11], t$95$1, t$95$2]]]]]]

Derivation

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

Alternative 15: 51.4% accurate, 1.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot \left(b \cdot i - x \cdot t\right)\\ \mathbf{if}\;a \leq -1.36 \cdot 10^{+69}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -9 \cdot 10^{-46}:\\ \;\;\;\;x \cdot \left(y \cdot z - t \cdot a\right)\\ \mathbf{elif}\;a \leq -3.8 \cdot 10^{-281}:\\ \;\;\;\;c \cdot \left(t \cdot j - z \cdot b\right)\\ \mathbf{elif}\;a \leq 360000:\\ \;\;\;\;j \cdot \left(t \cdot c - y \cdot i\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* a (- (* b i) (* x t)))))
   (if (<= a -1.36e+69)
     t_1
     (if (<= a -9e-46)
       (* x (- (* y z) (* t a)))
       (if (<= a -3.8e-281)
         (* c (- (* t j) (* z b)))
         (if (<= a 360000.0) (* j (- (* t c) (* y i))) t_1))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = a * ((b * i) - (x * t));
	double tmp;
	if (a <= -1.36e+69) {
		tmp = t_1;
	} else if (a <= -9e-46) {
		tmp = x * ((y * z) - (t * a));
	} else if (a <= -3.8e-281) {
		tmp = c * ((t * j) - (z * b));
	} else if (a <= 360000.0) {
		tmp = j * ((t * c) - (y * i));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: tmp
    t_1 = a * ((b * i) - (x * t))
    if (a <= (-1.36d+69)) then
        tmp = t_1
    else if (a <= (-9d-46)) then
        tmp = x * ((y * z) - (t * a))
    else if (a <= (-3.8d-281)) then
        tmp = c * ((t * j) - (z * b))
    else if (a <= 360000.0d0) then
        tmp = j * ((t * c) - (y * i))
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = a * ((b * i) - (x * t));
	double tmp;
	if (a <= -1.36e+69) {
		tmp = t_1;
	} else if (a <= -9e-46) {
		tmp = x * ((y * z) - (t * a));
	} else if (a <= -3.8e-281) {
		tmp = c * ((t * j) - (z * b));
	} else if (a <= 360000.0) {
		tmp = j * ((t * c) - (y * i));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = a * ((b * i) - (x * t))
	tmp = 0
	if a <= -1.36e+69:
		tmp = t_1
	elif a <= -9e-46:
		tmp = x * ((y * z) - (t * a))
	elif a <= -3.8e-281:
		tmp = c * ((t * j) - (z * b))
	elif a <= 360000.0:
		tmp = j * ((t * c) - (y * i))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(a * Float64(Float64(b * i) - Float64(x * t)))
	tmp = 0.0
	if (a <= -1.36e+69)
		tmp = t_1;
	elseif (a <= -9e-46)
		tmp = Float64(x * Float64(Float64(y * z) - Float64(t * a)));
	elseif (a <= -3.8e-281)
		tmp = Float64(c * Float64(Float64(t * j) - Float64(z * b)));
	elseif (a <= 360000.0)
		tmp = Float64(j * Float64(Float64(t * c) - Float64(y * i)));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = a * ((b * i) - (x * t));
	tmp = 0.0;
	if (a <= -1.36e+69)
		tmp = t_1;
	elseif (a <= -9e-46)
		tmp = x * ((y * z) - (t * a));
	elseif (a <= -3.8e-281)
		tmp = c * ((t * j) - (z * b));
	elseif (a <= 360000.0)
		tmp = j * ((t * c) - (y * i));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(a * N[(N[(b * i), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -1.36e+69], t$95$1, If[LessEqual[a, -9e-46], N[(x * N[(N[(y * z), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -3.8e-281], N[(c * N[(N[(t * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 360000.0], N[(j * N[(N[(t * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]

Derivation

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

Alternative 16: 52.0% accurate, 1.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot \left(b \cdot i - x \cdot t\right)\\ \mathbf{if}\;a \leq -2.4 \cdot 10^{+69}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -3.7 \cdot 10^{-152}:\\ \;\;\;\;y \cdot \left(x \cdot z - i \cdot j\right)\\ \mathbf{elif}\;a \leq -6.4 \cdot 10^{-282}:\\ \;\;\;\;c \cdot \left(t \cdot j - z \cdot b\right)\\ \mathbf{elif}\;a \leq 240000:\\ \;\;\;\;j \cdot \left(t \cdot c - y \cdot i\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* a (- (* b i) (* x t)))))
   (if (<= a -2.4e+69)
     t_1
     (if (<= a -3.7e-152)
       (* y (- (* x z) (* i j)))
       (if (<= a -6.4e-282)
         (* c (- (* t j) (* z b)))
         (if (<= a 240000.0) (* j (- (* t c) (* y i))) t_1))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = a * ((b * i) - (x * t));
	double tmp;
	if (a <= -2.4e+69) {
		tmp = t_1;
	} else if (a <= -3.7e-152) {
		tmp = y * ((x * z) - (i * j));
	} else if (a <= -6.4e-282) {
		tmp = c * ((t * j) - (z * b));
	} else if (a <= 240000.0) {
		tmp = j * ((t * c) - (y * i));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: tmp
    t_1 = a * ((b * i) - (x * t))
    if (a <= (-2.4d+69)) then
        tmp = t_1
    else if (a <= (-3.7d-152)) then
        tmp = y * ((x * z) - (i * j))
    else if (a <= (-6.4d-282)) then
        tmp = c * ((t * j) - (z * b))
    else if (a <= 240000.0d0) then
        tmp = j * ((t * c) - (y * i))
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = a * ((b * i) - (x * t));
	double tmp;
	if (a <= -2.4e+69) {
		tmp = t_1;
	} else if (a <= -3.7e-152) {
		tmp = y * ((x * z) - (i * j));
	} else if (a <= -6.4e-282) {
		tmp = c * ((t * j) - (z * b));
	} else if (a <= 240000.0) {
		tmp = j * ((t * c) - (y * i));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = a * ((b * i) - (x * t))
	tmp = 0
	if a <= -2.4e+69:
		tmp = t_1
	elif a <= -3.7e-152:
		tmp = y * ((x * z) - (i * j))
	elif a <= -6.4e-282:
		tmp = c * ((t * j) - (z * b))
	elif a <= 240000.0:
		tmp = j * ((t * c) - (y * i))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(a * Float64(Float64(b * i) - Float64(x * t)))
	tmp = 0.0
	if (a <= -2.4e+69)
		tmp = t_1;
	elseif (a <= -3.7e-152)
		tmp = Float64(y * Float64(Float64(x * z) - Float64(i * j)));
	elseif (a <= -6.4e-282)
		tmp = Float64(c * Float64(Float64(t * j) - Float64(z * b)));
	elseif (a <= 240000.0)
		tmp = Float64(j * Float64(Float64(t * c) - Float64(y * i)));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = a * ((b * i) - (x * t));
	tmp = 0.0;
	if (a <= -2.4e+69)
		tmp = t_1;
	elseif (a <= -3.7e-152)
		tmp = y * ((x * z) - (i * j));
	elseif (a <= -6.4e-282)
		tmp = c * ((t * j) - (z * b));
	elseif (a <= 240000.0)
		tmp = j * ((t * c) - (y * i));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(a * N[(N[(b * i), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -2.4e+69], t$95$1, If[LessEqual[a, -3.7e-152], N[(y * N[(N[(x * z), $MachinePrecision] - N[(i * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -6.4e-282], N[(c * N[(N[(t * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 240000.0], N[(j * N[(N[(t * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]

Derivation

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

Alternative 17: 30.0% accurate, 1.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;j \leq -1.4 \cdot 10^{+43}:\\ \;\;\;\;y \cdot \left(i \cdot \left(-j\right)\right)\\ \mathbf{elif}\;j \leq -1.22 \cdot 10^{-186}:\\ \;\;\;\;b \cdot \left(a \cdot i\right)\\ \mathbf{elif}\;j \leq 5 \cdot 10^{-172}:\\ \;\;\;\;\left(b \cdot c\right) \cdot \left(-z\right)\\ \mathbf{elif}\;j \leq 6.5 \cdot 10^{+114}:\\ \;\;\;\;a \cdot \left(b \cdot i\right)\\ \mathbf{elif}\;j \leq 2.15 \cdot 10^{+285}:\\ \;\;\;\;t \cdot \left(c \cdot j\right)\\ \mathbf{else}:\\ \;\;\;\;i \cdot \left(y \cdot \left(-j\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (<= j -1.4e+43)
   (* y (* i (- j)))
   (if (<= j -1.22e-186)
     (* b (* a i))
     (if (<= j 5e-172)
       (* (* b c) (- z))
       (if (<= j 6.5e+114)
         (* a (* b i))
         (if (<= j 2.15e+285) (* t (* c j)) (* 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 (j <= -1.4e+43) {
		tmp = y * (i * -j);
	} else if (j <= -1.22e-186) {
		tmp = b * (a * i);
	} else if (j <= 5e-172) {
		tmp = (b * c) * -z;
	} else if (j <= 6.5e+114) {
		tmp = a * (b * i);
	} else if (j <= 2.15e+285) {
		tmp = t * (c * j);
	} 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 (j <= (-1.4d+43)) then
        tmp = y * (i * -j)
    else if (j <= (-1.22d-186)) then
        tmp = b * (a * i)
    else if (j <= 5d-172) then
        tmp = (b * c) * -z
    else if (j <= 6.5d+114) then
        tmp = a * (b * i)
    else if (j <= 2.15d+285) then
        tmp = t * (c * j)
    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 (j <= -1.4e+43) {
		tmp = y * (i * -j);
	} else if (j <= -1.22e-186) {
		tmp = b * (a * i);
	} else if (j <= 5e-172) {
		tmp = (b * c) * -z;
	} else if (j <= 6.5e+114) {
		tmp = a * (b * i);
	} else if (j <= 2.15e+285) {
		tmp = t * (c * j);
	} else {
		tmp = i * (y * -j);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if j <= -1.4e+43:
		tmp = y * (i * -j)
	elif j <= -1.22e-186:
		tmp = b * (a * i)
	elif j <= 5e-172:
		tmp = (b * c) * -z
	elif j <= 6.5e+114:
		tmp = a * (b * i)
	elif j <= 2.15e+285:
		tmp = t * (c * j)
	else:
		tmp = i * (y * -j)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if (j <= -1.4e+43)
		tmp = Float64(y * Float64(i * Float64(-j)));
	elseif (j <= -1.22e-186)
		tmp = Float64(b * Float64(a * i));
	elseif (j <= 5e-172)
		tmp = Float64(Float64(b * c) * Float64(-z));
	elseif (j <= 6.5e+114)
		tmp = Float64(a * Float64(b * i));
	elseif (j <= 2.15e+285)
		tmp = Float64(t * Float64(c * j));
	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 (j <= -1.4e+43)
		tmp = y * (i * -j);
	elseif (j <= -1.22e-186)
		tmp = b * (a * i);
	elseif (j <= 5e-172)
		tmp = (b * c) * -z;
	elseif (j <= 6.5e+114)
		tmp = a * (b * i);
	elseif (j <= 2.15e+285)
		tmp = t * (c * j);
	else
		tmp = i * (y * -j);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[LessEqual[j, -1.4e+43], N[(y * N[(i * (-j)), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -1.22e-186], N[(b * N[(a * i), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 5e-172], N[(N[(b * c), $MachinePrecision] * (-z)), $MachinePrecision], If[LessEqual[j, 6.5e+114], N[(a * N[(b * i), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 2.15e+285], N[(t * N[(c * j), $MachinePrecision]), $MachinePrecision], N[(i * N[(y * (-j)), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

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

Alternative 18: 42.6% accurate, 1.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot \left(b \cdot i - x \cdot t\right)\\ \mathbf{if}\;a \leq -1.1 \cdot 10^{-154}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -9 \cdot 10^{-246}:\\ \;\;\;\;b \cdot \left(z \cdot \left(-c\right)\right)\\ \mathbf{elif}\;a \leq 5.5 \cdot 10^{-51}:\\ \;\;\;\;t \cdot \left(c \cdot j\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* a (- (* b i) (* x t)))))
   (if (<= a -1.1e-154)
     t_1
     (if (<= a -9e-246)
       (* b (* z (- c)))
       (if (<= a 5.5e-51) (* t (* c 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 * ((b * i) - (x * t));
	double tmp;
	if (a <= -1.1e-154) {
		tmp = t_1;
	} else if (a <= -9e-246) {
		tmp = b * (z * -c);
	} else if (a <= 5.5e-51) {
		tmp = t * (c * 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 * ((b * i) - (x * t))
    if (a <= (-1.1d-154)) then
        tmp = t_1
    else if (a <= (-9d-246)) then
        tmp = b * (z * -c)
    else if (a <= 5.5d-51) then
        tmp = t * (c * 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 * ((b * i) - (x * t));
	double tmp;
	if (a <= -1.1e-154) {
		tmp = t_1;
	} else if (a <= -9e-246) {
		tmp = b * (z * -c);
	} else if (a <= 5.5e-51) {
		tmp = t * (c * j);
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = a * ((b * i) - (x * t))
	tmp = 0
	if a <= -1.1e-154:
		tmp = t_1
	elif a <= -9e-246:
		tmp = b * (z * -c)
	elif a <= 5.5e-51:
		tmp = t * (c * 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(b * i) - Float64(x * t)))
	tmp = 0.0
	if (a <= -1.1e-154)
		tmp = t_1;
	elseif (a <= -9e-246)
		tmp = Float64(b * Float64(z * Float64(-c)));
	elseif (a <= 5.5e-51)
		tmp = Float64(t * Float64(c * 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 * ((b * i) - (x * t));
	tmp = 0.0;
	if (a <= -1.1e-154)
		tmp = t_1;
	elseif (a <= -9e-246)
		tmp = b * (z * -c);
	elseif (a <= 5.5e-51)
		tmp = t * (c * 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[(b * i), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -1.1e-154], t$95$1, If[LessEqual[a, -9e-246], N[(b * N[(z * (-c)), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 5.5e-51], N[(t * N[(c * j), $MachinePrecision]), $MachinePrecision], t$95$1]]]]

Derivation

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

Alternative 19: 44.0% accurate, 1.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot \left(b \cdot i - x \cdot t\right)\\ \mathbf{if}\;a \leq -1.06 \cdot 10^{+77}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -6.6 \cdot 10^{-246}:\\ \;\;\;\;b \cdot \left(a \cdot i - z \cdot c\right)\\ \mathbf{elif}\;a \leq 1.15 \cdot 10^{-50}:\\ \;\;\;\;t \cdot \left(c \cdot j\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* a (- (* b i) (* x t)))))
   (if (<= a -1.06e+77)
     t_1
     (if (<= a -6.6e-246)
       (* b (- (* a i) (* z c)))
       (if (<= a 1.15e-50) (* t (* c 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 * ((b * i) - (x * t));
	double tmp;
	if (a <= -1.06e+77) {
		tmp = t_1;
	} else if (a <= -6.6e-246) {
		tmp = b * ((a * i) - (z * c));
	} else if (a <= 1.15e-50) {
		tmp = t * (c * 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 * ((b * i) - (x * t))
    if (a <= (-1.06d+77)) then
        tmp = t_1
    else if (a <= (-6.6d-246)) then
        tmp = b * ((a * i) - (z * c))
    else if (a <= 1.15d-50) then
        tmp = t * (c * 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 * ((b * i) - (x * t));
	double tmp;
	if (a <= -1.06e+77) {
		tmp = t_1;
	} else if (a <= -6.6e-246) {
		tmp = b * ((a * i) - (z * c));
	} else if (a <= 1.15e-50) {
		tmp = t * (c * j);
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = a * ((b * i) - (x * t))
	tmp = 0
	if a <= -1.06e+77:
		tmp = t_1
	elif a <= -6.6e-246:
		tmp = b * ((a * i) - (z * c))
	elif a <= 1.15e-50:
		tmp = t * (c * 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(b * i) - Float64(x * t)))
	tmp = 0.0
	if (a <= -1.06e+77)
		tmp = t_1;
	elseif (a <= -6.6e-246)
		tmp = Float64(b * Float64(Float64(a * i) - Float64(z * c)));
	elseif (a <= 1.15e-50)
		tmp = Float64(t * Float64(c * 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 * ((b * i) - (x * t));
	tmp = 0.0;
	if (a <= -1.06e+77)
		tmp = t_1;
	elseif (a <= -6.6e-246)
		tmp = b * ((a * i) - (z * c));
	elseif (a <= 1.15e-50)
		tmp = t * (c * 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[(b * i), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -1.06e+77], t$95$1, If[LessEqual[a, -6.6e-246], N[(b * N[(N[(a * i), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 1.15e-50], N[(t * N[(c * j), $MachinePrecision]), $MachinePrecision], t$95$1]]]]

Derivation

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

Alternative 20: 51.4% accurate, 1.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot \left(b \cdot i - x \cdot t\right)\\ \mathbf{if}\;a \leq -2.35 \cdot 10^{-46}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -5.2 \cdot 10^{-282}:\\ \;\;\;\;c \cdot \left(t \cdot j - z \cdot b\right)\\ \mathbf{elif}\;a \leq 200000:\\ \;\;\;\;j \cdot \left(t \cdot c - y \cdot i\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* a (- (* b i) (* x t)))))
   (if (<= a -2.35e-46)
     t_1
     (if (<= a -5.2e-282)
       (* c (- (* t j) (* z b)))
       (if (<= a 200000.0) (* j (- (* t c) (* y i))) t_1)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = a * ((b * i) - (x * t));
	double tmp;
	if (a <= -2.35e-46) {
		tmp = t_1;
	} else if (a <= -5.2e-282) {
		tmp = c * ((t * j) - (z * b));
	} else if (a <= 200000.0) {
		tmp = j * ((t * c) - (y * i));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: t_1
    real(8) :: tmp
    t_1 = a * ((b * i) - (x * t))
    if (a <= (-2.35d-46)) then
        tmp = t_1
    else if (a <= (-5.2d-282)) then
        tmp = c * ((t * j) - (z * b))
    else if (a <= 200000.0d0) then
        tmp = j * ((t * c) - (y * i))
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double t_1 = a * ((b * i) - (x * t));
	double tmp;
	if (a <= -2.35e-46) {
		tmp = t_1;
	} else if (a <= -5.2e-282) {
		tmp = c * ((t * j) - (z * b));
	} else if (a <= 200000.0) {
		tmp = j * ((t * c) - (y * i));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = a * ((b * i) - (x * t))
	tmp = 0
	if a <= -2.35e-46:
		tmp = t_1
	elif a <= -5.2e-282:
		tmp = c * ((t * j) - (z * b))
	elif a <= 200000.0:
		tmp = j * ((t * c) - (y * i))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(a * Float64(Float64(b * i) - Float64(x * t)))
	tmp = 0.0
	if (a <= -2.35e-46)
		tmp = t_1;
	elseif (a <= -5.2e-282)
		tmp = Float64(c * Float64(Float64(t * j) - Float64(z * b)));
	elseif (a <= 200000.0)
		tmp = Float64(j * Float64(Float64(t * c) - Float64(y * i)));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	t_1 = a * ((b * i) - (x * t));
	tmp = 0.0;
	if (a <= -2.35e-46)
		tmp = t_1;
	elseif (a <= -5.2e-282)
		tmp = c * ((t * j) - (z * b));
	elseif (a <= 200000.0)
		tmp = j * ((t * c) - (y * i));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := Block[{t$95$1 = N[(a * N[(N[(b * i), $MachinePrecision] - N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -2.35e-46], t$95$1, If[LessEqual[a, -5.2e-282], N[(c * N[(N[(t * j), $MachinePrecision] - N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 200000.0], N[(j * N[(N[(t * c), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]

Derivation

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

Alternative 21: 29.2% accurate, 2.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;j \leq -1.7 \cdot 10^{-68}:\\ \;\;\;\;y \cdot \left(i \cdot \left(-j\right)\right)\\ \mathbf{elif}\;j \leq 1.55 \cdot 10^{-252}:\\ \;\;\;\;a \cdot \left(x \cdot \left(-t\right)\right)\\ \mathbf{elif}\;j \leq 7.5 \cdot 10^{+112}:\\ \;\;\;\;a \cdot \left(b \cdot i\right)\\ \mathbf{elif}\;j \leq 1.9 \cdot 10^{+283}:\\ \;\;\;\;t \cdot \left(c \cdot j\right)\\ \mathbf{else}:\\ \;\;\;\;i \cdot \left(y \cdot \left(-j\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (<= j -1.7e-68)
   (* y (* i (- j)))
   (if (<= j 1.55e-252)
     (* a (* x (- t)))
     (if (<= j 7.5e+112)
       (* a (* b i))
       (if (<= j 1.9e+283) (* t (* c j)) (* 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 (j <= -1.7e-68) {
		tmp = y * (i * -j);
	} else if (j <= 1.55e-252) {
		tmp = a * (x * -t);
	} else if (j <= 7.5e+112) {
		tmp = a * (b * i);
	} else if (j <= 1.9e+283) {
		tmp = t * (c * j);
	} 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 (j <= (-1.7d-68)) then
        tmp = y * (i * -j)
    else if (j <= 1.55d-252) then
        tmp = a * (x * -t)
    else if (j <= 7.5d+112) then
        tmp = a * (b * i)
    else if (j <= 1.9d+283) then
        tmp = t * (c * j)
    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 (j <= -1.7e-68) {
		tmp = y * (i * -j);
	} else if (j <= 1.55e-252) {
		tmp = a * (x * -t);
	} else if (j <= 7.5e+112) {
		tmp = a * (b * i);
	} else if (j <= 1.9e+283) {
		tmp = t * (c * j);
	} else {
		tmp = i * (y * -j);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if j <= -1.7e-68:
		tmp = y * (i * -j)
	elif j <= 1.55e-252:
		tmp = a * (x * -t)
	elif j <= 7.5e+112:
		tmp = a * (b * i)
	elif j <= 1.9e+283:
		tmp = t * (c * j)
	else:
		tmp = i * (y * -j)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if (j <= -1.7e-68)
		tmp = Float64(y * Float64(i * Float64(-j)));
	elseif (j <= 1.55e-252)
		tmp = Float64(a * Float64(x * Float64(-t)));
	elseif (j <= 7.5e+112)
		tmp = Float64(a * Float64(b * i));
	elseif (j <= 1.9e+283)
		tmp = Float64(t * Float64(c * j));
	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 (j <= -1.7e-68)
		tmp = y * (i * -j);
	elseif (j <= 1.55e-252)
		tmp = a * (x * -t);
	elseif (j <= 7.5e+112)
		tmp = a * (b * i);
	elseif (j <= 1.9e+283)
		tmp = t * (c * j);
	else
		tmp = i * (y * -j);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[LessEqual[j, -1.7e-68], N[(y * N[(i * (-j)), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 1.55e-252], N[(a * N[(x * (-t)), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 7.5e+112], N[(a * N[(b * i), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 1.9e+283], N[(t * N[(c * j), $MachinePrecision]), $MachinePrecision], N[(i * N[(y * (-j)), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

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

Alternative 22: 29.9% accurate, 2.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := i \cdot \left(y \cdot \left(-j\right)\right)\\ \mathbf{if}\;j \leq -1.4 \cdot 10^{+49}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;j \leq 1.06 \cdot 10^{+104}:\\ \;\;\;\;b \cdot \left(a \cdot i\right)\\ \mathbf{elif}\;j \leq 1.2 \cdot 10^{+282}:\\ \;\;\;\;t \cdot \left(c \cdot j\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (let* ((t_1 (* i (* y (- j)))))
   (if (<= j -1.4e+49)
     t_1
     (if (<= j 1.06e+104)
       (* b (* a i))
       (if (<= j 1.2e+282) (* t (* c 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 = i * (y * -j);
	double tmp;
	if (j <= -1.4e+49) {
		tmp = t_1;
	} else if (j <= 1.06e+104) {
		tmp = b * (a * i);
	} else if (j <= 1.2e+282) {
		tmp = t * (c * 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 = i * (y * -j)
    if (j <= (-1.4d+49)) then
        tmp = t_1
    else if (j <= 1.06d+104) then
        tmp = b * (a * i)
    else if (j <= 1.2d+282) then
        tmp = t * (c * 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 = i * (y * -j);
	double tmp;
	if (j <= -1.4e+49) {
		tmp = t_1;
	} else if (j <= 1.06e+104) {
		tmp = b * (a * i);
	} else if (j <= 1.2e+282) {
		tmp = t * (c * j);
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	t_1 = i * (y * -j)
	tmp = 0
	if j <= -1.4e+49:
		tmp = t_1
	elif j <= 1.06e+104:
		tmp = b * (a * i)
	elif j <= 1.2e+282:
		tmp = t * (c * j)
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	t_1 = Float64(i * Float64(y * Float64(-j)))
	tmp = 0.0
	if (j <= -1.4e+49)
		tmp = t_1;
	elseif (j <= 1.06e+104)
		tmp = Float64(b * Float64(a * i));
	elseif (j <= 1.2e+282)
		tmp = Float64(t * Float64(c * 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 = i * (y * -j);
	tmp = 0.0;
	if (j <= -1.4e+49)
		tmp = t_1;
	elseif (j <= 1.06e+104)
		tmp = b * (a * i);
	elseif (j <= 1.2e+282)
		tmp = t * (c * 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[(i * N[(y * (-j)), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -1.4e+49], t$95$1, If[LessEqual[j, 1.06e+104], N[(b * N[(a * i), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 1.2e+282], N[(t * N[(c * j), $MachinePrecision]), $MachinePrecision], t$95$1]]]]

Derivation

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

Alternative 23: 30.0% accurate, 2.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;j \leq -2.1 \cdot 10^{+41}:\\ \;\;\;\;y \cdot \left(i \cdot \left(-j\right)\right)\\ \mathbf{elif}\;j \leq 1.75 \cdot 10^{+105}:\\ \;\;\;\;b \cdot \left(a \cdot i\right)\\ \mathbf{elif}\;j \leq 4.4 \cdot 10^{+281}:\\ \;\;\;\;t \cdot \left(c \cdot j\right)\\ \mathbf{else}:\\ \;\;\;\;i \cdot \left(y \cdot \left(-j\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (<= j -2.1e+41)
   (* y (* i (- j)))
   (if (<= j 1.75e+105)
     (* b (* a i))
     (if (<= j 4.4e+281) (* t (* c j)) (* 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 (j <= -2.1e+41) {
		tmp = y * (i * -j);
	} else if (j <= 1.75e+105) {
		tmp = b * (a * i);
	} else if (j <= 4.4e+281) {
		tmp = t * (c * j);
	} 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 (j <= (-2.1d+41)) then
        tmp = y * (i * -j)
    else if (j <= 1.75d+105) then
        tmp = b * (a * i)
    else if (j <= 4.4d+281) then
        tmp = t * (c * j)
    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 (j <= -2.1e+41) {
		tmp = y * (i * -j);
	} else if (j <= 1.75e+105) {
		tmp = b * (a * i);
	} else if (j <= 4.4e+281) {
		tmp = t * (c * j);
	} else {
		tmp = i * (y * -j);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if j <= -2.1e+41:
		tmp = y * (i * -j)
	elif j <= 1.75e+105:
		tmp = b * (a * i)
	elif j <= 4.4e+281:
		tmp = t * (c * j)
	else:
		tmp = i * (y * -j)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if (j <= -2.1e+41)
		tmp = Float64(y * Float64(i * Float64(-j)));
	elseif (j <= 1.75e+105)
		tmp = Float64(b * Float64(a * i));
	elseif (j <= 4.4e+281)
		tmp = Float64(t * Float64(c * j));
	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 (j <= -2.1e+41)
		tmp = y * (i * -j);
	elseif (j <= 1.75e+105)
		tmp = b * (a * i);
	elseif (j <= 4.4e+281)
		tmp = t * (c * j);
	else
		tmp = i * (y * -j);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[LessEqual[j, -2.1e+41], N[(y * N[(i * (-j)), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 1.75e+105], N[(b * N[(a * i), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 4.4e+281], N[(t * N[(c * j), $MachinePrecision]), $MachinePrecision], N[(i * N[(y * (-j)), $MachinePrecision]), $MachinePrecision]]]]

Derivation

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

Alternative 24: 29.8% accurate, 3.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;a \leq -1.2 \cdot 10^{-37} \lor \neg \left(a \leq 4.5 \cdot 10^{-63}\right):\\ \;\;\;\;b \cdot \left(a \cdot i\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(t \cdot c\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (or (<= a -1.2e-37) (not (<= a 4.5e-63))) (* b (* a i)) (* j (* t c))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if ((a <= -1.2e-37) || !(a <= 4.5e-63)) {
		tmp = b * (a * i);
	} else {
		tmp = j * (t * c);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: tmp
    if ((a <= (-1.2d-37)) .or. (.not. (a <= 4.5d-63))) then
        tmp = b * (a * i)
    else
        tmp = j * (t * c)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if ((a <= -1.2e-37) || !(a <= 4.5e-63)) {
		tmp = b * (a * i);
	} else {
		tmp = j * (t * c);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if (a <= -1.2e-37) or not (a <= 4.5e-63):
		tmp = b * (a * i)
	else:
		tmp = j * (t * c)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if ((a <= -1.2e-37) || !(a <= 4.5e-63))
		tmp = Float64(b * Float64(a * i));
	else
		tmp = Float64(j * Float64(t * c));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0;
	if ((a <= -1.2e-37) || ~((a <= 4.5e-63)))
		tmp = b * (a * i);
	else
		tmp = j * (t * c);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[Or[LessEqual[a, -1.2e-37], N[Not[LessEqual[a, 4.5e-63]], $MachinePrecision]], N[(b * N[(a * i), $MachinePrecision]), $MachinePrecision], N[(j * N[(t * c), $MachinePrecision]), $MachinePrecision]]

Derivation

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

Alternative 25: 30.1% accurate, 3.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;a \leq -3.2 \cdot 10^{+25}:\\ \;\;\;\;b \cdot \left(a \cdot i\right)\\ \mathbf{elif}\;a \leq 1.1 \cdot 10^{-38}:\\ \;\;\;\;c \cdot \left(t \cdot j\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(b \cdot i\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (<= a -3.2e+25)
   (* b (* a i))
   (if (<= a 1.1e-38) (* c (* t j)) (* a (* b i)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if (a <= -3.2e+25) {
		tmp = b * (a * i);
	} else if (a <= 1.1e-38) {
		tmp = c * (t * j);
	} else {
		tmp = a * (b * i);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: tmp
    if (a <= (-3.2d+25)) then
        tmp = b * (a * i)
    else if (a <= 1.1d-38) then
        tmp = c * (t * j)
    else
        tmp = a * (b * i)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if (a <= -3.2e+25) {
		tmp = b * (a * i);
	} else if (a <= 1.1e-38) {
		tmp = c * (t * j);
	} else {
		tmp = a * (b * i);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if a <= -3.2e+25:
		tmp = b * (a * i)
	elif a <= 1.1e-38:
		tmp = c * (t * j)
	else:
		tmp = a * (b * i)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if (a <= -3.2e+25)
		tmp = Float64(b * Float64(a * i));
	elseif (a <= 1.1e-38)
		tmp = Float64(c * Float64(t * j));
	else
		tmp = Float64(a * Float64(b * i));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0;
	if (a <= -3.2e+25)
		tmp = b * (a * i);
	elseif (a <= 1.1e-38)
		tmp = c * (t * j);
	else
		tmp = a * (b * i);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[LessEqual[a, -3.2e+25], N[(b * N[(a * i), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 1.1e-38], N[(c * N[(t * j), $MachinePrecision]), $MachinePrecision], N[(a * N[(b * i), $MachinePrecision]), $MachinePrecision]]]

Derivation

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

Alternative 26: 29.8% accurate, 3.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;a \leq -1.18 \cdot 10^{-39}:\\ \;\;\;\;b \cdot \left(a \cdot i\right)\\ \mathbf{elif}\;a \leq 8.2 \cdot 10^{-36}:\\ \;\;\;\;t \cdot \left(c \cdot j\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(b \cdot i\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j)
 :precision binary64
 (if (<= a -1.18e-39)
   (* b (* a i))
   (if (<= a 8.2e-36) (* t (* c j)) (* a (* b i)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if (a <= -1.18e-39) {
		tmp = b * (a * i);
	} else if (a <= 8.2e-36) {
		tmp = t * (c * j);
	} else {
		tmp = a * (b * i);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8) :: tmp
    if (a <= (-1.18d-39)) then
        tmp = b * (a * i)
    else if (a <= 8.2d-36) then
        tmp = t * (c * j)
    else
        tmp = a * (b * i)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j) {
	double tmp;
	if (a <= -1.18e-39) {
		tmp = b * (a * i);
	} else if (a <= 8.2e-36) {
		tmp = t * (c * j);
	} else {
		tmp = a * (b * i);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j):
	tmp = 0
	if a <= -1.18e-39:
		tmp = b * (a * i)
	elif a <= 8.2e-36:
		tmp = t * (c * j)
	else:
		tmp = a * (b * i)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0
	if (a <= -1.18e-39)
		tmp = Float64(b * Float64(a * i));
	elseif (a <= 8.2e-36)
		tmp = Float64(t * Float64(c * j));
	else
		tmp = Float64(a * Float64(b * i));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j)
	tmp = 0.0;
	if (a <= -1.18e-39)
		tmp = b * (a * i);
	elseif (a <= 8.2e-36)
		tmp = t * (c * j);
	else
		tmp = a * (b * i);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_] := If[LessEqual[a, -1.18e-39], N[(b * N[(a * i), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 8.2e-36], N[(t * N[(c * j), $MachinePrecision]), $MachinePrecision], N[(a * N[(b * i), $MachinePrecision]), $MachinePrecision]]]

Derivation

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

Alternative 27: 22.1% accurate, 5.8× speedup

Math

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

FPCore

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

C

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

Fortran

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

Java

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

Python

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

Julia

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

MATLAB

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

Wolfram

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

Derivation

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

Alternative 28: 22.5% accurate, 5.8× speedup

Math

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

FPCore

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

C

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

Fortran

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

Java

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

Python

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

Julia

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

MATLAB

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

Wolfram

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

Derivation

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

Developer target: 69.0% accurate, 0.1× speedup

Math

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

FPCore

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

C

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

Fortran

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

Java

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

Python

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

Julia

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

MATLAB

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

Wolfram

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

Reproduce

herbie shell --seed 2023347 
(FPCore (x y z t a b c i j)
  :name "Linear.Matrix:det33 from linear-1.19.1.3"
  :precision binary64

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

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