Linear.Matrix:det44 from linear-1.19.1.3

Percentage Accurate: 30.3% → 42.3%

Time: 50.4s

Alternatives: 37

Speedup: 3.6×

• 89.2% of points produce a very large (infinite) output. You may want to add a precondition.

Specification

Math

\[\begin{array}{l} \\ \left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (+
  (-
   (+
    (+
     (-
      (* (- (* x y) (* z t)) (- (* a b) (* c i)))
      (* (- (* x j) (* z k)) (- (* y0 b) (* y1 i))))
     (* (- (* x y2) (* z y3)) (- (* y0 c) (* y1 a))))
    (* (- (* t j) (* y k)) (- (* y4 b) (* y5 i))))
   (* (- (* t y2) (* y y3)) (- (* y4 c) (* y5 a))))
  (* (- (* k y2) (* j y3)) (- (* y4 y1) (* y5 y0)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	return (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - (((x * j) - (z * k)) * ((y0 * b) - (y1 * i)))) + (((x * y2) - (z * y3)) * ((y0 * c) - (y1 * a)))) + (((t * j) - (y * k)) * ((y4 * b) - (y5 * i)))) - (((t * y2) - (y * y3)) * ((y4 * c) - (y5 * a)))) + (((k * y2) - (j * y3)) * ((y4 * y1) - (y5 * y0)));
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    code = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - (((x * j) - (z * k)) * ((y0 * b) - (y1 * i)))) + (((x * y2) - (z * y3)) * ((y0 * c) - (y1 * a)))) + (((t * j) - (y * k)) * ((y4 * b) - (y5 * i)))) - (((t * y2) - (y * y3)) * ((y4 * c) - (y5 * a)))) + (((k * y2) - (j * y3)) * ((y4 * y1) - (y5 * y0)))
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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	return (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - (((x * j) - (z * k)) * ((y0 * b) - (y1 * i)))) + (((x * y2) - (z * y3)) * ((y0 * c) - (y1 * a)))) + (((t * j) - (y * k)) * ((y4 * b) - (y5 * i)))) - (((t * y2) - (y * y3)) * ((y4 * c) - (y5 * a)))) + (((k * y2) - (j * y3)) * ((y4 * y1) - (y5 * y0)));
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	return (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - (((x * j) - (z * k)) * ((y0 * b) - (y1 * i)))) + (((x * y2) - (z * y3)) * ((y0 * c) - (y1 * a)))) + (((t * j) - (y * k)) * ((y4 * b) - (y5 * i)))) - (((t * y2) - (y * y3)) * ((y4 * c) - (y5 * a)))) + (((k * y2) - (j * y3)) * ((y4 * y1) - (y5 * y0)))

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	return Float64(Float64(Float64(Float64(Float64(Float64(Float64(Float64(x * y) - Float64(z * t)) * Float64(Float64(a * b) - Float64(c * i))) - Float64(Float64(Float64(x * j) - Float64(z * k)) * Float64(Float64(y0 * b) - Float64(y1 * i)))) + Float64(Float64(Float64(x * y2) - Float64(z * y3)) * Float64(Float64(y0 * c) - Float64(y1 * a)))) + Float64(Float64(Float64(t * j) - Float64(y * k)) * Float64(Float64(y4 * b) - Float64(y5 * i)))) - Float64(Float64(Float64(t * y2) - Float64(y * y3)) * Float64(Float64(y4 * c) - Float64(y5 * a)))) + Float64(Float64(Float64(k * y2) - Float64(j * y3)) * Float64(Float64(y4 * y1) - Float64(y5 * y0))))
end

MATLAB

function tmp = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - (((x * j) - (z * k)) * ((y0 * b) - (y1 * i)))) + (((x * y2) - (z * y3)) * ((y0 * c) - (y1 * a)))) + (((t * j) - (y * k)) * ((y4 * b) - (y5 * i)))) - (((t * y2) - (y * y3)) * ((y4 * c) - (y5 * a)))) + (((k * y2) - (j * y3)) * ((y4 * y1) - (y5 * y0)));
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := N[(N[(N[(N[(N[(N[(N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision] * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision] * N[(N[(y0 * b), $MachinePrecision] - N[(y1 * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision] * N[(N[(y0 * c), $MachinePrecision] - N[(y1 * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision] * N[(N[(y4 * b), $MachinePrecision] - N[(y5 * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision] * N[(N[(y4 * c), $MachinePrecision] - N[(y5 * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision] * N[(N[(y4 * y1), $MachinePrecision] - N[(y5 * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Initial Program: 30.3% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ \left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (+
  (-
   (+
    (+
     (-
      (* (- (* x y) (* z t)) (- (* a b) (* c i)))
      (* (- (* x j) (* z k)) (- (* y0 b) (* y1 i))))
     (* (- (* x y2) (* z y3)) (- (* y0 c) (* y1 a))))
    (* (- (* t j) (* y k)) (- (* y4 b) (* y5 i))))
   (* (- (* t y2) (* y y3)) (- (* y4 c) (* y5 a))))
  (* (- (* k y2) (* j y3)) (- (* y4 y1) (* y5 y0)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	return (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - (((x * j) - (z * k)) * ((y0 * b) - (y1 * i)))) + (((x * y2) - (z * y3)) * ((y0 * c) - (y1 * a)))) + (((t * j) - (y * k)) * ((y4 * b) - (y5 * i)))) - (((t * y2) - (y * y3)) * ((y4 * c) - (y5 * a)))) + (((k * y2) - (j * y3)) * ((y4 * y1) - (y5 * y0)));
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    code = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - (((x * j) - (z * k)) * ((y0 * b) - (y1 * i)))) + (((x * y2) - (z * y3)) * ((y0 * c) - (y1 * a)))) + (((t * j) - (y * k)) * ((y4 * b) - (y5 * i)))) - (((t * y2) - (y * y3)) * ((y4 * c) - (y5 * a)))) + (((k * y2) - (j * y3)) * ((y4 * y1) - (y5 * y0)))
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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	return (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - (((x * j) - (z * k)) * ((y0 * b) - (y1 * i)))) + (((x * y2) - (z * y3)) * ((y0 * c) - (y1 * a)))) + (((t * j) - (y * k)) * ((y4 * b) - (y5 * i)))) - (((t * y2) - (y * y3)) * ((y4 * c) - (y5 * a)))) + (((k * y2) - (j * y3)) * ((y4 * y1) - (y5 * y0)));
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	return (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - (((x * j) - (z * k)) * ((y0 * b) - (y1 * i)))) + (((x * y2) - (z * y3)) * ((y0 * c) - (y1 * a)))) + (((t * j) - (y * k)) * ((y4 * b) - (y5 * i)))) - (((t * y2) - (y * y3)) * ((y4 * c) - (y5 * a)))) + (((k * y2) - (j * y3)) * ((y4 * y1) - (y5 * y0)))

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	return Float64(Float64(Float64(Float64(Float64(Float64(Float64(Float64(x * y) - Float64(z * t)) * Float64(Float64(a * b) - Float64(c * i))) - Float64(Float64(Float64(x * j) - Float64(z * k)) * Float64(Float64(y0 * b) - Float64(y1 * i)))) + Float64(Float64(Float64(x * y2) - Float64(z * y3)) * Float64(Float64(y0 * c) - Float64(y1 * a)))) + Float64(Float64(Float64(t * j) - Float64(y * k)) * Float64(Float64(y4 * b) - Float64(y5 * i)))) - Float64(Float64(Float64(t * y2) - Float64(y * y3)) * Float64(Float64(y4 * c) - Float64(y5 * a)))) + Float64(Float64(Float64(k * y2) - Float64(j * y3)) * Float64(Float64(y4 * y1) - Float64(y5 * y0))))
end

MATLAB

function tmp = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - (((x * j) - (z * k)) * ((y0 * b) - (y1 * i)))) + (((x * y2) - (z * y3)) * ((y0 * c) - (y1 * a)))) + (((t * j) - (y * k)) * ((y4 * b) - (y5 * i)))) - (((t * y2) - (y * y3)) * ((y4 * c) - (y5 * a)))) + (((k * y2) - (j * y3)) * ((y4 * y1) - (y5 * y0)));
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := N[(N[(N[(N[(N[(N[(N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision] * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision] * N[(N[(y0 * b), $MachinePrecision] - N[(y1 * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision] * N[(N[(y0 * c), $MachinePrecision] - N[(y1 * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision] * N[(N[(y4 * b), $MachinePrecision] - N[(y5 * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision] * N[(N[(y4 * c), $MachinePrecision] - N[(y5 * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision] * N[(N[(y4 * y1), $MachinePrecision] - N[(y5 * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Alternative 1: 42.3% accurate, 1.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := k \cdot y2 - j \cdot y3\\ t_2 := b \cdot y4 - i \cdot y5\\ t_3 := y1 \cdot y4 - y0 \cdot y5\\ t_4 := t\_1 \cdot t\_3\\ t_5 := i \cdot y1 - b \cdot y0\\ t_6 := j \cdot \left(\left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + t \cdot t\_2\right) + x \cdot t\_5\right)\\ t_7 := a \cdot y5 - c \cdot y4\\ t_8 := y2 \cdot \left(\left(k \cdot t\_3 + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + t \cdot t\_7\right)\\ t_9 := x \cdot j - z \cdot k\\ \mathbf{if}\;j \leq -1.05 \cdot 10^{+104}:\\ \;\;\;\;t\_6\\ \mathbf{elif}\;j \leq -2.7 \cdot 10^{+51}:\\ \;\;\;\;t\_4\\ \mathbf{elif}\;j \leq -6.5 \cdot 10^{-8}:\\ \;\;\;\;\left(x \cdot j\right) \cdot t\_5\\ \mathbf{elif}\;j \leq -1.15 \cdot 10^{-90}:\\ \;\;\;\;t\_8\\ \mathbf{elif}\;j \leq -1.7 \cdot 10^{-203}:\\ \;\;\;\;y1 \cdot \left(\left(a \cdot \left(z \cdot y3 - x \cdot y2\right) + y4 \cdot t\_1\right) + i \cdot t\_9\right)\\ \mathbf{elif}\;j \leq 3.8 \cdot 10^{-102}:\\ \;\;\;\;t\_4 + \left(\left(t\_2 \cdot \left(t \cdot j - y \cdot k\right) + \left(b \cdot y0 - i \cdot y1\right) \cdot \left(z \cdot k\right)\right) + \left(t \cdot y2 - y \cdot y3\right) \cdot t\_7\right)\\ \mathbf{elif}\;j \leq 8.2 \cdot 10^{+80}:\\ \;\;\;\;t\_8\\ \mathbf{elif}\;j \leq 1.55 \cdot 10^{+150}:\\ \;\;\;\;t\_4 + i \cdot \left(y1 \cdot t\_9 + \left(c \cdot \left(z \cdot t - x \cdot y\right) + y5 \cdot \left(y \cdot k - t \cdot j\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_6\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* k y2) (* j y3)))
        (t_2 (- (* b y4) (* i y5)))
        (t_3 (- (* y1 y4) (* y0 y5)))
        (t_4 (* t_1 t_3))
        (t_5 (- (* i y1) (* b y0)))
        (t_6 (* j (+ (+ (* y3 (- (* y0 y5) (* y1 y4))) (* t t_2)) (* x t_5))))
        (t_7 (- (* a y5) (* c y4)))
        (t_8 (* y2 (+ (+ (* k t_3) (* x (- (* c y0) (* a y1)))) (* t t_7))))
        (t_9 (- (* x j) (* z k))))
   (if (<= j -1.05e+104)
     t_6
     (if (<= j -2.7e+51)
       t_4
       (if (<= j -6.5e-8)
         (* (* x j) t_5)
         (if (<= j -1.15e-90)
           t_8
           (if (<= j -1.7e-203)
             (* y1 (+ (+ (* a (- (* z y3) (* x y2))) (* y4 t_1)) (* i t_9)))
             (if (<= j 3.8e-102)
               (+
                t_4
                (+
                 (+
                  (* t_2 (- (* t j) (* y k)))
                  (* (- (* b y0) (* i y1)) (* z k)))
                 (* (- (* t y2) (* y y3)) t_7)))
               (if (<= j 8.2e+80)
                 t_8
                 (if (<= j 1.55e+150)
                   (+
                    t_4
                    (*
                     i
                     (+
                      (* y1 t_9)
                      (+
                       (* c (- (* z t) (* x y)))
                       (* y5 (- (* y k) (* t j)))))))
                   t_6))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (k * y2) - (j * y3);
	double t_2 = (b * y4) - (i * y5);
	double t_3 = (y1 * y4) - (y0 * y5);
	double t_4 = t_1 * t_3;
	double t_5 = (i * y1) - (b * y0);
	double t_6 = j * (((y3 * ((y0 * y5) - (y1 * y4))) + (t * t_2)) + (x * t_5));
	double t_7 = (a * y5) - (c * y4);
	double t_8 = y2 * (((k * t_3) + (x * ((c * y0) - (a * y1)))) + (t * t_7));
	double t_9 = (x * j) - (z * k);
	double tmp;
	if (j <= -1.05e+104) {
		tmp = t_6;
	} else if (j <= -2.7e+51) {
		tmp = t_4;
	} else if (j <= -6.5e-8) {
		tmp = (x * j) * t_5;
	} else if (j <= -1.15e-90) {
		tmp = t_8;
	} else if (j <= -1.7e-203) {
		tmp = y1 * (((a * ((z * y3) - (x * y2))) + (y4 * t_1)) + (i * t_9));
	} else if (j <= 3.8e-102) {
		tmp = t_4 + (((t_2 * ((t * j) - (y * k))) + (((b * y0) - (i * y1)) * (z * k))) + (((t * y2) - (y * y3)) * t_7));
	} else if (j <= 8.2e+80) {
		tmp = t_8;
	} else if (j <= 1.55e+150) {
		tmp = t_4 + (i * ((y1 * t_9) + ((c * ((z * t) - (x * y))) + (y5 * ((y * k) - (t * j))))));
	} else {
		tmp = t_6;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: t_5
    real(8) :: t_6
    real(8) :: t_7
    real(8) :: t_8
    real(8) :: t_9
    real(8) :: tmp
    t_1 = (k * y2) - (j * y3)
    t_2 = (b * y4) - (i * y5)
    t_3 = (y1 * y4) - (y0 * y5)
    t_4 = t_1 * t_3
    t_5 = (i * y1) - (b * y0)
    t_6 = j * (((y3 * ((y0 * y5) - (y1 * y4))) + (t * t_2)) + (x * t_5))
    t_7 = (a * y5) - (c * y4)
    t_8 = y2 * (((k * t_3) + (x * ((c * y0) - (a * y1)))) + (t * t_7))
    t_9 = (x * j) - (z * k)
    if (j <= (-1.05d+104)) then
        tmp = t_6
    else if (j <= (-2.7d+51)) then
        tmp = t_4
    else if (j <= (-6.5d-8)) then
        tmp = (x * j) * t_5
    else if (j <= (-1.15d-90)) then
        tmp = t_8
    else if (j <= (-1.7d-203)) then
        tmp = y1 * (((a * ((z * y3) - (x * y2))) + (y4 * t_1)) + (i * t_9))
    else if (j <= 3.8d-102) then
        tmp = t_4 + (((t_2 * ((t * j) - (y * k))) + (((b * y0) - (i * y1)) * (z * k))) + (((t * y2) - (y * y3)) * t_7))
    else if (j <= 8.2d+80) then
        tmp = t_8
    else if (j <= 1.55d+150) then
        tmp = t_4 + (i * ((y1 * t_9) + ((c * ((z * t) - (x * y))) + (y5 * ((y * k) - (t * j))))))
    else
        tmp = t_6
    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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (k * y2) - (j * y3);
	double t_2 = (b * y4) - (i * y5);
	double t_3 = (y1 * y4) - (y0 * y5);
	double t_4 = t_1 * t_3;
	double t_5 = (i * y1) - (b * y0);
	double t_6 = j * (((y3 * ((y0 * y5) - (y1 * y4))) + (t * t_2)) + (x * t_5));
	double t_7 = (a * y5) - (c * y4);
	double t_8 = y2 * (((k * t_3) + (x * ((c * y0) - (a * y1)))) + (t * t_7));
	double t_9 = (x * j) - (z * k);
	double tmp;
	if (j <= -1.05e+104) {
		tmp = t_6;
	} else if (j <= -2.7e+51) {
		tmp = t_4;
	} else if (j <= -6.5e-8) {
		tmp = (x * j) * t_5;
	} else if (j <= -1.15e-90) {
		tmp = t_8;
	} else if (j <= -1.7e-203) {
		tmp = y1 * (((a * ((z * y3) - (x * y2))) + (y4 * t_1)) + (i * t_9));
	} else if (j <= 3.8e-102) {
		tmp = t_4 + (((t_2 * ((t * j) - (y * k))) + (((b * y0) - (i * y1)) * (z * k))) + (((t * y2) - (y * y3)) * t_7));
	} else if (j <= 8.2e+80) {
		tmp = t_8;
	} else if (j <= 1.55e+150) {
		tmp = t_4 + (i * ((y1 * t_9) + ((c * ((z * t) - (x * y))) + (y5 * ((y * k) - (t * j))))));
	} else {
		tmp = t_6;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (k * y2) - (j * y3)
	t_2 = (b * y4) - (i * y5)
	t_3 = (y1 * y4) - (y0 * y5)
	t_4 = t_1 * t_3
	t_5 = (i * y1) - (b * y0)
	t_6 = j * (((y3 * ((y0 * y5) - (y1 * y4))) + (t * t_2)) + (x * t_5))
	t_7 = (a * y5) - (c * y4)
	t_8 = y2 * (((k * t_3) + (x * ((c * y0) - (a * y1)))) + (t * t_7))
	t_9 = (x * j) - (z * k)
	tmp = 0
	if j <= -1.05e+104:
		tmp = t_6
	elif j <= -2.7e+51:
		tmp = t_4
	elif j <= -6.5e-8:
		tmp = (x * j) * t_5
	elif j <= -1.15e-90:
		tmp = t_8
	elif j <= -1.7e-203:
		tmp = y1 * (((a * ((z * y3) - (x * y2))) + (y4 * t_1)) + (i * t_9))
	elif j <= 3.8e-102:
		tmp = t_4 + (((t_2 * ((t * j) - (y * k))) + (((b * y0) - (i * y1)) * (z * k))) + (((t * y2) - (y * y3)) * t_7))
	elif j <= 8.2e+80:
		tmp = t_8
	elif j <= 1.55e+150:
		tmp = t_4 + (i * ((y1 * t_9) + ((c * ((z * t) - (x * y))) + (y5 * ((y * k) - (t * j))))))
	else:
		tmp = t_6
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(k * y2) - Float64(j * y3))
	t_2 = Float64(Float64(b * y4) - Float64(i * y5))
	t_3 = Float64(Float64(y1 * y4) - Float64(y0 * y5))
	t_4 = Float64(t_1 * t_3)
	t_5 = Float64(Float64(i * y1) - Float64(b * y0))
	t_6 = Float64(j * Float64(Float64(Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4))) + Float64(t * t_2)) + Float64(x * t_5)))
	t_7 = Float64(Float64(a * y5) - Float64(c * y4))
	t_8 = Float64(y2 * Float64(Float64(Float64(k * t_3) + Float64(x * Float64(Float64(c * y0) - Float64(a * y1)))) + Float64(t * t_7)))
	t_9 = Float64(Float64(x * j) - Float64(z * k))
	tmp = 0.0
	if (j <= -1.05e+104)
		tmp = t_6;
	elseif (j <= -2.7e+51)
		tmp = t_4;
	elseif (j <= -6.5e-8)
		tmp = Float64(Float64(x * j) * t_5);
	elseif (j <= -1.15e-90)
		tmp = t_8;
	elseif (j <= -1.7e-203)
		tmp = Float64(y1 * Float64(Float64(Float64(a * Float64(Float64(z * y3) - Float64(x * y2))) + Float64(y4 * t_1)) + Float64(i * t_9)));
	elseif (j <= 3.8e-102)
		tmp = Float64(t_4 + Float64(Float64(Float64(t_2 * Float64(Float64(t * j) - Float64(y * k))) + Float64(Float64(Float64(b * y0) - Float64(i * y1)) * Float64(z * k))) + Float64(Float64(Float64(t * y2) - Float64(y * y3)) * t_7)));
	elseif (j <= 8.2e+80)
		tmp = t_8;
	elseif (j <= 1.55e+150)
		tmp = Float64(t_4 + Float64(i * Float64(Float64(y1 * t_9) + Float64(Float64(c * Float64(Float64(z * t) - Float64(x * y))) + Float64(y5 * Float64(Float64(y * k) - Float64(t * j)))))));
	else
		tmp = t_6;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = (k * y2) - (j * y3);
	t_2 = (b * y4) - (i * y5);
	t_3 = (y1 * y4) - (y0 * y5);
	t_4 = t_1 * t_3;
	t_5 = (i * y1) - (b * y0);
	t_6 = j * (((y3 * ((y0 * y5) - (y1 * y4))) + (t * t_2)) + (x * t_5));
	t_7 = (a * y5) - (c * y4);
	t_8 = y2 * (((k * t_3) + (x * ((c * y0) - (a * y1)))) + (t * t_7));
	t_9 = (x * j) - (z * k);
	tmp = 0.0;
	if (j <= -1.05e+104)
		tmp = t_6;
	elseif (j <= -2.7e+51)
		tmp = t_4;
	elseif (j <= -6.5e-8)
		tmp = (x * j) * t_5;
	elseif (j <= -1.15e-90)
		tmp = t_8;
	elseif (j <= -1.7e-203)
		tmp = y1 * (((a * ((z * y3) - (x * y2))) + (y4 * t_1)) + (i * t_9));
	elseif (j <= 3.8e-102)
		tmp = t_4 + (((t_2 * ((t * j) - (y * k))) + (((b * y0) - (i * y1)) * (z * k))) + (((t * y2) - (y * y3)) * t_7));
	elseif (j <= 8.2e+80)
		tmp = t_8;
	elseif (j <= 1.55e+150)
		tmp = t_4 + (i * ((y1 * t_9) + ((c * ((z * t) - (x * y))) + (y5 * ((y * k) - (t * j))))));
	else
		tmp = t_6;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(t$95$1 * t$95$3), $MachinePrecision]}, Block[{t$95$5 = N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$6 = N[(j * N[(N[(N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(t * t$95$2), $MachinePrecision]), $MachinePrecision] + N[(x * t$95$5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$7 = N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$8 = N[(y2 * N[(N[(N[(k * t$95$3), $MachinePrecision] + N[(x * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(t * t$95$7), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$9 = N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -1.05e+104], t$95$6, If[LessEqual[j, -2.7e+51], t$95$4, If[LessEqual[j, -6.5e-8], N[(N[(x * j), $MachinePrecision] * t$95$5), $MachinePrecision], If[LessEqual[j, -1.15e-90], t$95$8, If[LessEqual[j, -1.7e-203], N[(y1 * N[(N[(N[(a * N[(N[(z * y3), $MachinePrecision] - N[(x * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y4 * t$95$1), $MachinePrecision]), $MachinePrecision] + N[(i * t$95$9), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 3.8e-102], N[(t$95$4 + N[(N[(N[(t$95$2 * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision] * N[(z * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision] * t$95$7), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 8.2e+80], t$95$8, If[LessEqual[j, 1.55e+150], N[(t$95$4 + N[(i * N[(N[(y1 * t$95$9), $MachinePrecision] + N[(N[(c * N[(N[(z * t), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y5 * N[(N[(y * k), $MachinePrecision] - N[(t * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$6]]]]]]]]]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if j < -1.0499999999999999e104 or 1.55000000000000007e150 < j

   1. Initial program 23.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 67.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   if -1.0499999999999999e104 < j < -2.69999999999999992e51

   1. Initial program 18.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 18.9%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in i around 0 69.1%

      \[\leadsto \color{blue}{\left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)} \]

   if -2.69999999999999992e51 < j < -6.49999999999999997e-8

   1. Initial program 22.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 55.6%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in x around inf 78.1%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 78.1%

         \[\leadsto \color{blue}{\left(j \cdot x\right) \cdot \left(i \cdot y1 - b \cdot y0\right)} \]

   6. Simplified 78.1%

      \[\leadsto \color{blue}{\left(j \cdot x\right) \cdot \left(i \cdot y1 - b \cdot y0\right)} \]

   if -6.49999999999999997e-8 < j < -1.1499999999999999e-90 or 3.80000000000000026e-102 < j < 8.20000000000000003e80

   1. Initial program 36.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 56.2%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   if -1.1499999999999999e-90 < j < -1.6999999999999999e-203

   1. Initial program 37.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y1 around inf 58.5%

      \[\leadsto \color{blue}{y1 \cdot \left(\left(-1 \cdot \left(a \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - -1 \cdot \left(i \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} \]

   if -1.6999999999999999e-203 < j < 3.80000000000000026e-102

   1. Initial program 49.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 57.5%

      \[\leadsto \left(\left(\color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. associate-*r* 57.5%

         \[\leadsto \left(\left(\color{blue}{\left(k \cdot z\right) \cdot \left(b \cdot y0 - i \cdot y1\right)} + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 57.5%

         \[\leadsto \left(\left(\color{blue}{\left(z \cdot k\right)} \cdot \left(b \cdot y0 - i \cdot y1\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 57.5%

      \[\leadsto \left(\left(\color{blue}{\left(z \cdot k\right) \cdot \left(b \cdot y0 - i \cdot y1\right)} + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   if 8.20000000000000003e80 < j < 1.55000000000000007e150

   1. Initial program 9.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 73.3%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
3. Recombined 7 regimes into one program.

4. Final simplification 62.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;j \leq -1.05 \cdot 10^{+104}:\\ \;\;\;\;j \cdot \left(\left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;j \leq -2.7 \cdot 10^{+51}:\\ \;\;\;\;\left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\\ \mathbf{elif}\;j \leq -6.5 \cdot 10^{-8}:\\ \;\;\;\;\left(x \cdot j\right) \cdot \left(i \cdot y1 - b \cdot y0\right)\\ \mathbf{elif}\;j \leq -1.15 \cdot 10^{-90}:\\ \;\;\;\;y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq -1.7 \cdot 10^{-203}:\\ \;\;\;\;y1 \cdot \left(\left(a \cdot \left(z \cdot y3 - x \cdot y2\right) + y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + i \cdot \left(x \cdot j - z \cdot k\right)\right)\\ \mathbf{elif}\;j \leq 3.8 \cdot 10^{-102}:\\ \;\;\;\;\left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + \left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot \left(t \cdot j - y \cdot k\right) + \left(b \cdot y0 - i \cdot y1\right) \cdot \left(z \cdot k\right)\right) + \left(t \cdot y2 - y \cdot y3\right) \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq 8.2 \cdot 10^{+80}:\\ \;\;\;\;y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq 1.55 \cdot 10^{+150}:\\ \;\;\;\;\left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right) + \left(c \cdot \left(z \cdot t - x \cdot y\right) + y5 \cdot \left(y \cdot k - t \cdot j\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(\left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 2: 55.6% accurate, 0.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\\ t_2 := \left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot \left(t \cdot j - y \cdot k\right) - \left(\left(x \cdot y2 - z \cdot y3\right) \cdot \left(a \cdot y1 - c \cdot y0\right) + \left(\left(b \cdot y0 - i \cdot y1\right) \cdot \left(x \cdot j - z \cdot k\right) + \left(a \cdot b - c \cdot i\right) \cdot \left(z \cdot t - x \cdot y\right)\right)\right)\right) + \left(t \cdot y2 - y \cdot y3\right) \cdot \left(a \cdot y5 - c \cdot y4\right)\right) + t\_1\\ \mathbf{if}\;t\_2 \leq \infty:\\ \;\;\;\;t\_2\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* (- (* k y2) (* j y3)) (- (* y1 y4) (* y0 y5))))
        (t_2
         (+
          (+
           (-
            (* (- (* b y4) (* i y5)) (- (* t j) (* y k)))
            (+
             (* (- (* x y2) (* z y3)) (- (* a y1) (* c y0)))
             (+
              (* (- (* b y0) (* i y1)) (- (* x j) (* z k)))
              (* (- (* a b) (* c i)) (- (* z t) (* x y))))))
           (* (- (* t y2) (* y y3)) (- (* a y5) (* c y4))))
          t_1)))
   (if (<= t_2 INFINITY) t_2 t_1)))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = ((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5));
	double t_2 = (((((b * y4) - (i * y5)) * ((t * j) - (y * k))) - ((((x * y2) - (z * y3)) * ((a * y1) - (c * y0))) + ((((b * y0) - (i * y1)) * ((x * j) - (z * k))) + (((a * b) - (c * i)) * ((z * t) - (x * y)))))) + (((t * y2) - (y * y3)) * ((a * y5) - (c * y4)))) + t_1;
	double tmp;
	if (t_2 <= ((double) INFINITY)) {
		tmp = t_2;
	} else {
		tmp = t_1;
	}
	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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = ((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5));
	double t_2 = (((((b * y4) - (i * y5)) * ((t * j) - (y * k))) - ((((x * y2) - (z * y3)) * ((a * y1) - (c * y0))) + ((((b * y0) - (i * y1)) * ((x * j) - (z * k))) + (((a * b) - (c * i)) * ((z * t) - (x * y)))))) + (((t * y2) - (y * y3)) * ((a * y5) - (c * y4)))) + t_1;
	double tmp;
	if (t_2 <= Double.POSITIVE_INFINITY) {
		tmp = t_2;
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = ((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5))
	t_2 = (((((b * y4) - (i * y5)) * ((t * j) - (y * k))) - ((((x * y2) - (z * y3)) * ((a * y1) - (c * y0))) + ((((b * y0) - (i * y1)) * ((x * j) - (z * k))) + (((a * b) - (c * i)) * ((z * t) - (x * y)))))) + (((t * y2) - (y * y3)) * ((a * y5) - (c * y4)))) + t_1
	tmp = 0
	if t_2 <= math.inf:
		tmp = t_2
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(Float64(k * y2) - Float64(j * y3)) * Float64(Float64(y1 * y4) - Float64(y0 * y5)))
	t_2 = Float64(Float64(Float64(Float64(Float64(Float64(b * y4) - Float64(i * y5)) * Float64(Float64(t * j) - Float64(y * k))) - Float64(Float64(Float64(Float64(x * y2) - Float64(z * y3)) * Float64(Float64(a * y1) - Float64(c * y0))) + Float64(Float64(Float64(Float64(b * y0) - Float64(i * y1)) * Float64(Float64(x * j) - Float64(z * k))) + Float64(Float64(Float64(a * b) - Float64(c * i)) * Float64(Float64(z * t) - Float64(x * y)))))) + Float64(Float64(Float64(t * y2) - Float64(y * y3)) * Float64(Float64(a * y5) - Float64(c * y4)))) + t_1)
	tmp = 0.0
	if (t_2 <= Inf)
		tmp = t_2;
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = ((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5));
	t_2 = (((((b * y4) - (i * y5)) * ((t * j) - (y * k))) - ((((x * y2) - (z * y3)) * ((a * y1) - (c * y0))) + ((((b * y0) - (i * y1)) * ((x * j) - (z * k))) + (((a * b) - (c * i)) * ((z * t) - (x * y)))))) + (((t * y2) - (y * y3)) * ((a * y5) - (c * y4)))) + t_1;
	tmp = 0.0;
	if (t_2 <= Inf)
		tmp = t_2;
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision] * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(N[(N[(N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision] * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision] * N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision] * N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision] * N[(N[(z * t), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision] * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision]}, If[LessEqual[t$95$2, Infinity], t$95$2, t$95$1]]]

Derivation

1. Split input into 2 regimes

2. if (+.f64 (-.f64 (+.f64 (+.f64 (-.f64 (*.f64 (-.f64 (*.f64 x y) (*.f64 z t)) (-.f64 (*.f64 a b) (*.f64 c i))) (*.f64 (-.f64 (*.f64 x j) (*.f64 z k)) (-.f64 (*.f64 y0 b) (*.f64 y1 i)))) (*.f64 (-.f64 (*.f64 x y2) (*.f64 z y3)) (-.f64 (*.f64 y0 c) (*.f64 y1 a)))) (*.f64 (-.f64 (*.f64 t j) (*.f64 y k)) (-.f64 (*.f64 y4 b) (*.f64 y5 i)))) (*.f64 (-.f64 (*.f64 t y2) (*.f64 y y3)) (-.f64 (*.f64 y4 c) (*.f64 y5 a)))) (*.f64 (-.f64 (*.f64 k y2) (*.f64 j y3)) (-.f64 (*.f64 y4 y1) (*.f64 y5 y0)))) < +inf.0

   1. Initial program 93.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   if +inf.0 < (+.f64 (-.f64 (+.f64 (+.f64 (-.f64 (*.f64 (-.f64 (*.f64 x y) (*.f64 z t)) (-.f64 (*.f64 a b) (*.f64 c i))) (*.f64 (-.f64 (*.f64 x j) (*.f64 z k)) (-.f64 (*.f64 y0 b) (*.f64 y1 i)))) (*.f64 (-.f64 (*.f64 x y2) (*.f64 z y3)) (-.f64 (*.f64 y0 c) (*.f64 y1 a)))) (*.f64 (-.f64 (*.f64 t j) (*.f64 y k)) (-.f64 (*.f64 y4 b) (*.f64 y5 i)))) (*.f64 (-.f64 (*.f64 t y2) (*.f64 y y3)) (-.f64 (*.f64 y4 c) (*.f64 y5 a)))) (*.f64 (-.f64 (*.f64 k y2) (*.f64 j y3)) (-.f64 (*.f64 y4 y1) (*.f64 y5 y0))))

   1. Initial program 0.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 25.4%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in i around 0 37.4%

      \[\leadsto \color{blue}{\left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)} \]
3. Recombined 2 regimes into one program.

4. Final simplification 56.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot \left(t \cdot j - y \cdot k\right) - \left(\left(x \cdot y2 - z \cdot y3\right) \cdot \left(a \cdot y1 - c \cdot y0\right) + \left(\left(b \cdot y0 - i \cdot y1\right) \cdot \left(x \cdot j - z \cdot k\right) + \left(a \cdot b - c \cdot i\right) \cdot \left(z \cdot t - x \cdot y\right)\right)\right)\right) + \left(t \cdot y2 - y \cdot y3\right) \cdot \left(a \cdot y5 - c \cdot y4\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) \leq \infty:\\ \;\;\;\;\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot \left(t \cdot j - y \cdot k\right) - \left(\left(x \cdot y2 - z \cdot y3\right) \cdot \left(a \cdot y1 - c \cdot y0\right) + \left(\left(b \cdot y0 - i \cdot y1\right) \cdot \left(x \cdot j - z \cdot k\right) + \left(a \cdot b - c \cdot i\right) \cdot \left(z \cdot t - x \cdot y\right)\right)\right)\right) + \left(t \cdot y2 - y \cdot y3\right) \cdot \left(a \cdot y5 - c \cdot y4\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\\ \mathbf{else}:\\ \;\;\;\;\left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 3: 43.6% accurate, 1.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y1 \cdot y4 - y0 \cdot y5\\ t_2 := y2 \cdot \left(\left(k \cdot t\_1 + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ t_3 := \left(k \cdot y2 - j \cdot y3\right) \cdot t\_1\\ t_4 := y0 \cdot y5 - y1 \cdot y4\\ t_5 := i \cdot y1 - b \cdot y0\\ t_6 := j \cdot \left(\left(y3 \cdot t\_4 + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot t\_5\right)\\ \mathbf{if}\;j \leq -2.66 \cdot 10^{+107}:\\ \;\;\;\;t\_6\\ \mathbf{elif}\;j \leq -2.3 \cdot 10^{+51}:\\ \;\;\;\;t\_3\\ \mathbf{elif}\;j \leq -6.8 \cdot 10^{-7}:\\ \;\;\;\;\left(x \cdot j\right) \cdot t\_5\\ \mathbf{elif}\;j \leq -2.45 \cdot 10^{-90}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;j \leq 3.2 \cdot 10^{-65}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right) - \left(y2 \cdot t\_4 - y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\right)\\ \mathbf{elif}\;j \leq 1.9 \cdot 10^{+83}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;j \leq 1.7 \cdot 10^{+150}:\\ \;\;\;\;t\_3 + i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right) + \left(c \cdot \left(z \cdot t - x \cdot y\right) + y5 \cdot \left(y \cdot k - t \cdot j\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_6\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* y1 y4) (* y0 y5)))
        (t_2
         (*
          y2
          (+
           (+ (* k t_1) (* x (- (* c y0) (* a y1))))
           (* t (- (* a y5) (* c y4))))))
        (t_3 (* (- (* k y2) (* j y3)) t_1))
        (t_4 (- (* y0 y5) (* y1 y4)))
        (t_5 (- (* i y1) (* b y0)))
        (t_6 (* j (+ (+ (* y3 t_4) (* t (- (* b y4) (* i y5)))) (* x t_5)))))
   (if (<= j -2.66e+107)
     t_6
     (if (<= j -2.3e+51)
       t_3
       (if (<= j -6.8e-7)
         (* (* x j) t_5)
         (if (<= j -2.45e-90)
           t_2
           (if (<= j 3.2e-65)
             (*
              k
              (-
               (* z (- (* b y0) (* i y1)))
               (- (* y2 t_4) (* y (- (* i y5) (* b y4))))))
             (if (<= j 1.9e+83)
               t_2
               (if (<= j 1.7e+150)
                 (+
                  t_3
                  (*
                   i
                   (+
                    (* y1 (- (* x j) (* z k)))
                    (+ (* c (- (* z t) (* x y))) (* y5 (- (* y k) (* t j)))))))
                 t_6)))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (y1 * y4) - (y0 * y5);
	double t_2 = y2 * (((k * t_1) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))));
	double t_3 = ((k * y2) - (j * y3)) * t_1;
	double t_4 = (y0 * y5) - (y1 * y4);
	double t_5 = (i * y1) - (b * y0);
	double t_6 = j * (((y3 * t_4) + (t * ((b * y4) - (i * y5)))) + (x * t_5));
	double tmp;
	if (j <= -2.66e+107) {
		tmp = t_6;
	} else if (j <= -2.3e+51) {
		tmp = t_3;
	} else if (j <= -6.8e-7) {
		tmp = (x * j) * t_5;
	} else if (j <= -2.45e-90) {
		tmp = t_2;
	} else if (j <= 3.2e-65) {
		tmp = k * ((z * ((b * y0) - (i * y1))) - ((y2 * t_4) - (y * ((i * y5) - (b * y4)))));
	} else if (j <= 1.9e+83) {
		tmp = t_2;
	} else if (j <= 1.7e+150) {
		tmp = t_3 + (i * ((y1 * ((x * j) - (z * k))) + ((c * ((z * t) - (x * y))) + (y5 * ((y * k) - (t * j))))));
	} else {
		tmp = t_6;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: t_5
    real(8) :: t_6
    real(8) :: tmp
    t_1 = (y1 * y4) - (y0 * y5)
    t_2 = y2 * (((k * t_1) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))))
    t_3 = ((k * y2) - (j * y3)) * t_1
    t_4 = (y0 * y5) - (y1 * y4)
    t_5 = (i * y1) - (b * y0)
    t_6 = j * (((y3 * t_4) + (t * ((b * y4) - (i * y5)))) + (x * t_5))
    if (j <= (-2.66d+107)) then
        tmp = t_6
    else if (j <= (-2.3d+51)) then
        tmp = t_3
    else if (j <= (-6.8d-7)) then
        tmp = (x * j) * t_5
    else if (j <= (-2.45d-90)) then
        tmp = t_2
    else if (j <= 3.2d-65) then
        tmp = k * ((z * ((b * y0) - (i * y1))) - ((y2 * t_4) - (y * ((i * y5) - (b * y4)))))
    else if (j <= 1.9d+83) then
        tmp = t_2
    else if (j <= 1.7d+150) then
        tmp = t_3 + (i * ((y1 * ((x * j) - (z * k))) + ((c * ((z * t) - (x * y))) + (y5 * ((y * k) - (t * j))))))
    else
        tmp = t_6
    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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (y1 * y4) - (y0 * y5);
	double t_2 = y2 * (((k * t_1) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))));
	double t_3 = ((k * y2) - (j * y3)) * t_1;
	double t_4 = (y0 * y5) - (y1 * y4);
	double t_5 = (i * y1) - (b * y0);
	double t_6 = j * (((y3 * t_4) + (t * ((b * y4) - (i * y5)))) + (x * t_5));
	double tmp;
	if (j <= -2.66e+107) {
		tmp = t_6;
	} else if (j <= -2.3e+51) {
		tmp = t_3;
	} else if (j <= -6.8e-7) {
		tmp = (x * j) * t_5;
	} else if (j <= -2.45e-90) {
		tmp = t_2;
	} else if (j <= 3.2e-65) {
		tmp = k * ((z * ((b * y0) - (i * y1))) - ((y2 * t_4) - (y * ((i * y5) - (b * y4)))));
	} else if (j <= 1.9e+83) {
		tmp = t_2;
	} else if (j <= 1.7e+150) {
		tmp = t_3 + (i * ((y1 * ((x * j) - (z * k))) + ((c * ((z * t) - (x * y))) + (y5 * ((y * k) - (t * j))))));
	} else {
		tmp = t_6;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (y1 * y4) - (y0 * y5)
	t_2 = y2 * (((k * t_1) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))))
	t_3 = ((k * y2) - (j * y3)) * t_1
	t_4 = (y0 * y5) - (y1 * y4)
	t_5 = (i * y1) - (b * y0)
	t_6 = j * (((y3 * t_4) + (t * ((b * y4) - (i * y5)))) + (x * t_5))
	tmp = 0
	if j <= -2.66e+107:
		tmp = t_6
	elif j <= -2.3e+51:
		tmp = t_3
	elif j <= -6.8e-7:
		tmp = (x * j) * t_5
	elif j <= -2.45e-90:
		tmp = t_2
	elif j <= 3.2e-65:
		tmp = k * ((z * ((b * y0) - (i * y1))) - ((y2 * t_4) - (y * ((i * y5) - (b * y4)))))
	elif j <= 1.9e+83:
		tmp = t_2
	elif j <= 1.7e+150:
		tmp = t_3 + (i * ((y1 * ((x * j) - (z * k))) + ((c * ((z * t) - (x * y))) + (y5 * ((y * k) - (t * j))))))
	else:
		tmp = t_6
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(y1 * y4) - Float64(y0 * y5))
	t_2 = Float64(y2 * Float64(Float64(Float64(k * t_1) + Float64(x * Float64(Float64(c * y0) - Float64(a * y1)))) + Float64(t * Float64(Float64(a * y5) - Float64(c * y4)))))
	t_3 = Float64(Float64(Float64(k * y2) - Float64(j * y3)) * t_1)
	t_4 = Float64(Float64(y0 * y5) - Float64(y1 * y4))
	t_5 = Float64(Float64(i * y1) - Float64(b * y0))
	t_6 = Float64(j * Float64(Float64(Float64(y3 * t_4) + Float64(t * Float64(Float64(b * y4) - Float64(i * y5)))) + Float64(x * t_5)))
	tmp = 0.0
	if (j <= -2.66e+107)
		tmp = t_6;
	elseif (j <= -2.3e+51)
		tmp = t_3;
	elseif (j <= -6.8e-7)
		tmp = Float64(Float64(x * j) * t_5);
	elseif (j <= -2.45e-90)
		tmp = t_2;
	elseif (j <= 3.2e-65)
		tmp = Float64(k * Float64(Float64(z * Float64(Float64(b * y0) - Float64(i * y1))) - Float64(Float64(y2 * t_4) - Float64(y * Float64(Float64(i * y5) - Float64(b * y4))))));
	elseif (j <= 1.9e+83)
		tmp = t_2;
	elseif (j <= 1.7e+150)
		tmp = Float64(t_3 + Float64(i * Float64(Float64(y1 * Float64(Float64(x * j) - Float64(z * k))) + Float64(Float64(c * Float64(Float64(z * t) - Float64(x * y))) + Float64(y5 * Float64(Float64(y * k) - Float64(t * j)))))));
	else
		tmp = t_6;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = (y1 * y4) - (y0 * y5);
	t_2 = y2 * (((k * t_1) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))));
	t_3 = ((k * y2) - (j * y3)) * t_1;
	t_4 = (y0 * y5) - (y1 * y4);
	t_5 = (i * y1) - (b * y0);
	t_6 = j * (((y3 * t_4) + (t * ((b * y4) - (i * y5)))) + (x * t_5));
	tmp = 0.0;
	if (j <= -2.66e+107)
		tmp = t_6;
	elseif (j <= -2.3e+51)
		tmp = t_3;
	elseif (j <= -6.8e-7)
		tmp = (x * j) * t_5;
	elseif (j <= -2.45e-90)
		tmp = t_2;
	elseif (j <= 3.2e-65)
		tmp = k * ((z * ((b * y0) - (i * y1))) - ((y2 * t_4) - (y * ((i * y5) - (b * y4)))));
	elseif (j <= 1.9e+83)
		tmp = t_2;
	elseif (j <= 1.7e+150)
		tmp = t_3 + (i * ((y1 * ((x * j) - (z * k))) + ((c * ((z * t) - (x * y))) + (y5 * ((y * k) - (t * j))))));
	else
		tmp = t_6;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(y2 * N[(N[(N[(k * t$95$1), $MachinePrecision] + N[(x * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(t * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision] * t$95$1), $MachinePrecision]}, Block[{t$95$4 = N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$6 = N[(j * N[(N[(N[(y3 * t$95$4), $MachinePrecision] + N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(x * t$95$5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -2.66e+107], t$95$6, If[LessEqual[j, -2.3e+51], t$95$3, If[LessEqual[j, -6.8e-7], N[(N[(x * j), $MachinePrecision] * t$95$5), $MachinePrecision], If[LessEqual[j, -2.45e-90], t$95$2, If[LessEqual[j, 3.2e-65], N[(k * N[(N[(z * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(y2 * t$95$4), $MachinePrecision] - N[(y * N[(N[(i * y5), $MachinePrecision] - N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 1.9e+83], t$95$2, If[LessEqual[j, 1.7e+150], N[(t$95$3 + N[(i * N[(N[(y1 * N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(c * N[(N[(z * t), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y5 * N[(N[(y * k), $MachinePrecision] - N[(t * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$6]]]]]]]]]]]]]

Derivation

1. Split input into 6 regimes

2. if j < -2.6599999999999999e107 or 1.69999999999999991e150 < j

   1. Initial program 23.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 67.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   if -2.6599999999999999e107 < j < -2.30000000000000005e51

   1. Initial program 18.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 18.9%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in i around 0 69.1%

      \[\leadsto \color{blue}{\left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)} \]

   if -2.30000000000000005e51 < j < -6.79999999999999948e-7

   1. Initial program 22.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 55.6%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in x around inf 78.1%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 78.1%

         \[\leadsto \color{blue}{\left(j \cdot x\right) \cdot \left(i \cdot y1 - b \cdot y0\right)} \]

   6. Simplified 78.1%

      \[\leadsto \color{blue}{\left(j \cdot x\right) \cdot \left(i \cdot y1 - b \cdot y0\right)} \]

   if -6.79999999999999948e-7 < j < -2.44999999999999991e-90 or 3.1999999999999999e-65 < j < 1.9000000000000001e83

   1. Initial program 34.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 57.2%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   if -2.44999999999999991e-90 < j < 3.1999999999999999e-65

   1. Initial program 45.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 50.2%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   if 1.9000000000000001e83 < j < 1.69999999999999991e150

   1. Initial program 9.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 73.3%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
3. Recombined 6 regimes into one program.

4. Final simplification 59.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;j \leq -2.66 \cdot 10^{+107}:\\ \;\;\;\;j \cdot \left(\left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;j \leq -2.3 \cdot 10^{+51}:\\ \;\;\;\;\left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\\ \mathbf{elif}\;j \leq -6.8 \cdot 10^{-7}:\\ \;\;\;\;\left(x \cdot j\right) \cdot \left(i \cdot y1 - b \cdot y0\right)\\ \mathbf{elif}\;j \leq -2.45 \cdot 10^{-90}:\\ \;\;\;\;y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq 3.2 \cdot 10^{-65}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right) - \left(y2 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) - y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\right)\\ \mathbf{elif}\;j \leq 1.9 \cdot 10^{+83}:\\ \;\;\;\;y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq 1.7 \cdot 10^{+150}:\\ \;\;\;\;\left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right) + \left(c \cdot \left(z \cdot t - x \cdot y\right) + y5 \cdot \left(y \cdot k - t \cdot j\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(\left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 4: 43.4% accurate, 1.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y1 \cdot y4 - y0 \cdot y5\\ t_2 := y2 \cdot \left(\left(k \cdot t\_1 + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ t_3 := y0 \cdot y5 - y1 \cdot y4\\ t_4 := i \cdot y1 - b \cdot y0\\ t_5 := j \cdot \left(\left(y3 \cdot t\_3 + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot t\_4\right)\\ \mathbf{if}\;j \leq -8 \cdot 10^{+109}:\\ \;\;\;\;t\_5\\ \mathbf{elif}\;j \leq -2.65 \cdot 10^{+51}:\\ \;\;\;\;\left(k \cdot y2 - j \cdot y3\right) \cdot t\_1\\ \mathbf{elif}\;j \leq -6.4 \cdot 10^{-7}:\\ \;\;\;\;\left(x \cdot j\right) \cdot t\_4\\ \mathbf{elif}\;j \leq -2.9 \cdot 10^{-90}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;j \leq 1.9 \cdot 10^{-67}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right) - \left(y2 \cdot t\_3 - y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\right)\\ \mathbf{elif}\;j \leq 1.4 \cdot 10^{+167}:\\ \;\;\;\;t\_2\\ \mathbf{else}:\\ \;\;\;\;t\_5\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* y1 y4) (* y0 y5)))
        (t_2
         (*
          y2
          (+
           (+ (* k t_1) (* x (- (* c y0) (* a y1))))
           (* t (- (* a y5) (* c y4))))))
        (t_3 (- (* y0 y5) (* y1 y4)))
        (t_4 (- (* i y1) (* b y0)))
        (t_5 (* j (+ (+ (* y3 t_3) (* t (- (* b y4) (* i y5)))) (* x t_4)))))
   (if (<= j -8e+109)
     t_5
     (if (<= j -2.65e+51)
       (* (- (* k y2) (* j y3)) t_1)
       (if (<= j -6.4e-7)
         (* (* x j) t_4)
         (if (<= j -2.9e-90)
           t_2
           (if (<= j 1.9e-67)
             (*
              k
              (-
               (* z (- (* b y0) (* i y1)))
               (- (* y2 t_3) (* y (- (* i y5) (* b y4))))))
             (if (<= j 1.4e+167) t_2 t_5))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (y1 * y4) - (y0 * y5);
	double t_2 = y2 * (((k * t_1) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))));
	double t_3 = (y0 * y5) - (y1 * y4);
	double t_4 = (i * y1) - (b * y0);
	double t_5 = j * (((y3 * t_3) + (t * ((b * y4) - (i * y5)))) + (x * t_4));
	double tmp;
	if (j <= -8e+109) {
		tmp = t_5;
	} else if (j <= -2.65e+51) {
		tmp = ((k * y2) - (j * y3)) * t_1;
	} else if (j <= -6.4e-7) {
		tmp = (x * j) * t_4;
	} else if (j <= -2.9e-90) {
		tmp = t_2;
	} else if (j <= 1.9e-67) {
		tmp = k * ((z * ((b * y0) - (i * y1))) - ((y2 * t_3) - (y * ((i * y5) - (b * y4)))));
	} else if (j <= 1.4e+167) {
		tmp = t_2;
	} else {
		tmp = t_5;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: t_5
    real(8) :: tmp
    t_1 = (y1 * y4) - (y0 * y5)
    t_2 = y2 * (((k * t_1) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))))
    t_3 = (y0 * y5) - (y1 * y4)
    t_4 = (i * y1) - (b * y0)
    t_5 = j * (((y3 * t_3) + (t * ((b * y4) - (i * y5)))) + (x * t_4))
    if (j <= (-8d+109)) then
        tmp = t_5
    else if (j <= (-2.65d+51)) then
        tmp = ((k * y2) - (j * y3)) * t_1
    else if (j <= (-6.4d-7)) then
        tmp = (x * j) * t_4
    else if (j <= (-2.9d-90)) then
        tmp = t_2
    else if (j <= 1.9d-67) then
        tmp = k * ((z * ((b * y0) - (i * y1))) - ((y2 * t_3) - (y * ((i * y5) - (b * y4)))))
    else if (j <= 1.4d+167) then
        tmp = t_2
    else
        tmp = t_5
    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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (y1 * y4) - (y0 * y5);
	double t_2 = y2 * (((k * t_1) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))));
	double t_3 = (y0 * y5) - (y1 * y4);
	double t_4 = (i * y1) - (b * y0);
	double t_5 = j * (((y3 * t_3) + (t * ((b * y4) - (i * y5)))) + (x * t_4));
	double tmp;
	if (j <= -8e+109) {
		tmp = t_5;
	} else if (j <= -2.65e+51) {
		tmp = ((k * y2) - (j * y3)) * t_1;
	} else if (j <= -6.4e-7) {
		tmp = (x * j) * t_4;
	} else if (j <= -2.9e-90) {
		tmp = t_2;
	} else if (j <= 1.9e-67) {
		tmp = k * ((z * ((b * y0) - (i * y1))) - ((y2 * t_3) - (y * ((i * y5) - (b * y4)))));
	} else if (j <= 1.4e+167) {
		tmp = t_2;
	} else {
		tmp = t_5;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (y1 * y4) - (y0 * y5)
	t_2 = y2 * (((k * t_1) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))))
	t_3 = (y0 * y5) - (y1 * y4)
	t_4 = (i * y1) - (b * y0)
	t_5 = j * (((y3 * t_3) + (t * ((b * y4) - (i * y5)))) + (x * t_4))
	tmp = 0
	if j <= -8e+109:
		tmp = t_5
	elif j <= -2.65e+51:
		tmp = ((k * y2) - (j * y3)) * t_1
	elif j <= -6.4e-7:
		tmp = (x * j) * t_4
	elif j <= -2.9e-90:
		tmp = t_2
	elif j <= 1.9e-67:
		tmp = k * ((z * ((b * y0) - (i * y1))) - ((y2 * t_3) - (y * ((i * y5) - (b * y4)))))
	elif j <= 1.4e+167:
		tmp = t_2
	else:
		tmp = t_5
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(y1 * y4) - Float64(y0 * y5))
	t_2 = Float64(y2 * Float64(Float64(Float64(k * t_1) + Float64(x * Float64(Float64(c * y0) - Float64(a * y1)))) + Float64(t * Float64(Float64(a * y5) - Float64(c * y4)))))
	t_3 = Float64(Float64(y0 * y5) - Float64(y1 * y4))
	t_4 = Float64(Float64(i * y1) - Float64(b * y0))
	t_5 = Float64(j * Float64(Float64(Float64(y3 * t_3) + Float64(t * Float64(Float64(b * y4) - Float64(i * y5)))) + Float64(x * t_4)))
	tmp = 0.0
	if (j <= -8e+109)
		tmp = t_5;
	elseif (j <= -2.65e+51)
		tmp = Float64(Float64(Float64(k * y2) - Float64(j * y3)) * t_1);
	elseif (j <= -6.4e-7)
		tmp = Float64(Float64(x * j) * t_4);
	elseif (j <= -2.9e-90)
		tmp = t_2;
	elseif (j <= 1.9e-67)
		tmp = Float64(k * Float64(Float64(z * Float64(Float64(b * y0) - Float64(i * y1))) - Float64(Float64(y2 * t_3) - Float64(y * Float64(Float64(i * y5) - Float64(b * y4))))));
	elseif (j <= 1.4e+167)
		tmp = t_2;
	else
		tmp = t_5;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = (y1 * y4) - (y0 * y5);
	t_2 = y2 * (((k * t_1) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))));
	t_3 = (y0 * y5) - (y1 * y4);
	t_4 = (i * y1) - (b * y0);
	t_5 = j * (((y3 * t_3) + (t * ((b * y4) - (i * y5)))) + (x * t_4));
	tmp = 0.0;
	if (j <= -8e+109)
		tmp = t_5;
	elseif (j <= -2.65e+51)
		tmp = ((k * y2) - (j * y3)) * t_1;
	elseif (j <= -6.4e-7)
		tmp = (x * j) * t_4;
	elseif (j <= -2.9e-90)
		tmp = t_2;
	elseif (j <= 1.9e-67)
		tmp = k * ((z * ((b * y0) - (i * y1))) - ((y2 * t_3) - (y * ((i * y5) - (b * y4)))));
	elseif (j <= 1.4e+167)
		tmp = t_2;
	else
		tmp = t_5;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(y2 * N[(N[(N[(k * t$95$1), $MachinePrecision] + N[(x * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(t * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(j * N[(N[(N[(y3 * t$95$3), $MachinePrecision] + N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(x * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -8e+109], t$95$5, If[LessEqual[j, -2.65e+51], N[(N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision] * t$95$1), $MachinePrecision], If[LessEqual[j, -6.4e-7], N[(N[(x * j), $MachinePrecision] * t$95$4), $MachinePrecision], If[LessEqual[j, -2.9e-90], t$95$2, If[LessEqual[j, 1.9e-67], N[(k * N[(N[(z * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(y2 * t$95$3), $MachinePrecision] - N[(y * N[(N[(i * y5), $MachinePrecision] - N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 1.4e+167], t$95$2, t$95$5]]]]]]]]]]]

Derivation

1. Split input into 5 regimes

2. if j < -7.99999999999999985e109 or 1.3999999999999999e167 < j

   1. Initial program 23.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 69.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   if -7.99999999999999985e109 < j < -2.6499999999999998e51

   1. Initial program 18.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 18.9%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in i around 0 69.1%

      \[\leadsto \color{blue}{\left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)} \]

   if -2.6499999999999998e51 < j < -6.4000000000000001e-7

   1. Initial program 22.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 55.6%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in x around inf 78.1%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 78.1%

         \[\leadsto \color{blue}{\left(j \cdot x\right) \cdot \left(i \cdot y1 - b \cdot y0\right)} \]

   6. Simplified 78.1%

      \[\leadsto \color{blue}{\left(j \cdot x\right) \cdot \left(i \cdot y1 - b \cdot y0\right)} \]

   if -6.4000000000000001e-7 < j < -2.89999999999999983e-90 or 1.89999999999999994e-67 < j < 1.3999999999999999e167

   1. Initial program 30.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 52.4%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   if -2.89999999999999983e-90 < j < 1.89999999999999994e-67

   1. Initial program 45.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around inf 50.2%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 58.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;j \leq -8 \cdot 10^{+109}:\\ \;\;\;\;j \cdot \left(\left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;j \leq -2.65 \cdot 10^{+51}:\\ \;\;\;\;\left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\\ \mathbf{elif}\;j \leq -6.4 \cdot 10^{-7}:\\ \;\;\;\;\left(x \cdot j\right) \cdot \left(i \cdot y1 - b \cdot y0\right)\\ \mathbf{elif}\;j \leq -2.9 \cdot 10^{-90}:\\ \;\;\;\;y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq 1.9 \cdot 10^{-67}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right) - \left(y2 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) - y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\right)\\ \mathbf{elif}\;j \leq 1.4 \cdot 10^{+167}:\\ \;\;\;\;y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(\left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 5: 40.7% accurate, 1.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y1 \cdot y4 - y0 \cdot y5\\ t_2 := y0 \cdot y5 - y1 \cdot y4\\ t_3 := c \cdot y0 - a \cdot y1\\ \mathbf{if}\;y3 \leq -2 \cdot 10^{+81}:\\ \;\;\;\;y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) - \left(j \cdot t\_1 + z \cdot t\_3\right)\right)\\ \mathbf{elif}\;y3 \leq -9 \cdot 10^{-222}:\\ \;\;\;\;j \cdot \left(\left(y3 \cdot t\_2 + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y3 \leq 4.2 \cdot 10^{-172}:\\ \;\;\;\;y5 \cdot \left(a \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(i \cdot \left(y \cdot k - t \cdot j\right) + y0 \cdot \left(j \cdot y3 - k \cdot y2\right)\right)\right)\\ \mathbf{elif}\;y3 \leq 5.7 \cdot 10^{-21}:\\ \;\;\;\;y2 \cdot \left(\left(k \cdot t\_1 + x \cdot t\_3\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;y3 \leq 3.9 \cdot 10^{+83}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i - y3 \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y3 \cdot \left(j \cdot t\_2 + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* y1 y4) (* y0 y5)))
        (t_2 (- (* y0 y5) (* y1 y4)))
        (t_3 (- (* c y0) (* a y1))))
   (if (<= y3 -2e+81)
     (* y3 (- (* y (- (* c y4) (* a y5))) (+ (* j t_1) (* z t_3))))
     (if (<= y3 -9e-222)
       (*
        j
        (+
         (+ (* y3 t_2) (* t (- (* b y4) (* i y5))))
         (* x (- (* i y1) (* b y0)))))
       (if (<= y3 4.2e-172)
         (*
          y5
          (+
           (* a (- (* t y2) (* y y3)))
           (+ (* i (- (* y k) (* t j))) (* y0 (- (* j y3) (* k y2))))))
         (if (<= y3 5.7e-21)
           (* y2 (+ (+ (* k t_1) (* x t_3)) (* t (- (* a y5) (* c y4)))))
           (if (<= y3 3.9e+83)
             (* j (* y1 (- (* x i) (* y3 y4))))
             (* y3 (+ (* j t_2) (* z (- (* a y1) (* c y0))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (y1 * y4) - (y0 * y5);
	double t_2 = (y0 * y5) - (y1 * y4);
	double t_3 = (c * y0) - (a * y1);
	double tmp;
	if (y3 <= -2e+81) {
		tmp = y3 * ((y * ((c * y4) - (a * y5))) - ((j * t_1) + (z * t_3)));
	} else if (y3 <= -9e-222) {
		tmp = j * (((y3 * t_2) + (t * ((b * y4) - (i * y5)))) + (x * ((i * y1) - (b * y0))));
	} else if (y3 <= 4.2e-172) {
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2)))));
	} else if (y3 <= 5.7e-21) {
		tmp = y2 * (((k * t_1) + (x * t_3)) + (t * ((a * y5) - (c * y4))));
	} else if (y3 <= 3.9e+83) {
		tmp = j * (y1 * ((x * i) - (y3 * y4)));
	} else {
		tmp = y3 * ((j * t_2) + (z * ((a * y1) - (c * y0))));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: tmp
    t_1 = (y1 * y4) - (y0 * y5)
    t_2 = (y0 * y5) - (y1 * y4)
    t_3 = (c * y0) - (a * y1)
    if (y3 <= (-2d+81)) then
        tmp = y3 * ((y * ((c * y4) - (a * y5))) - ((j * t_1) + (z * t_3)))
    else if (y3 <= (-9d-222)) then
        tmp = j * (((y3 * t_2) + (t * ((b * y4) - (i * y5)))) + (x * ((i * y1) - (b * y0))))
    else if (y3 <= 4.2d-172) then
        tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2)))))
    else if (y3 <= 5.7d-21) then
        tmp = y2 * (((k * t_1) + (x * t_3)) + (t * ((a * y5) - (c * y4))))
    else if (y3 <= 3.9d+83) then
        tmp = j * (y1 * ((x * i) - (y3 * y4)))
    else
        tmp = y3 * ((j * t_2) + (z * ((a * y1) - (c * y0))))
    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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (y1 * y4) - (y0 * y5);
	double t_2 = (y0 * y5) - (y1 * y4);
	double t_3 = (c * y0) - (a * y1);
	double tmp;
	if (y3 <= -2e+81) {
		tmp = y3 * ((y * ((c * y4) - (a * y5))) - ((j * t_1) + (z * t_3)));
	} else if (y3 <= -9e-222) {
		tmp = j * (((y3 * t_2) + (t * ((b * y4) - (i * y5)))) + (x * ((i * y1) - (b * y0))));
	} else if (y3 <= 4.2e-172) {
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2)))));
	} else if (y3 <= 5.7e-21) {
		tmp = y2 * (((k * t_1) + (x * t_3)) + (t * ((a * y5) - (c * y4))));
	} else if (y3 <= 3.9e+83) {
		tmp = j * (y1 * ((x * i) - (y3 * y4)));
	} else {
		tmp = y3 * ((j * t_2) + (z * ((a * y1) - (c * y0))));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (y1 * y4) - (y0 * y5)
	t_2 = (y0 * y5) - (y1 * y4)
	t_3 = (c * y0) - (a * y1)
	tmp = 0
	if y3 <= -2e+81:
		tmp = y3 * ((y * ((c * y4) - (a * y5))) - ((j * t_1) + (z * t_3)))
	elif y3 <= -9e-222:
		tmp = j * (((y3 * t_2) + (t * ((b * y4) - (i * y5)))) + (x * ((i * y1) - (b * y0))))
	elif y3 <= 4.2e-172:
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2)))))
	elif y3 <= 5.7e-21:
		tmp = y2 * (((k * t_1) + (x * t_3)) + (t * ((a * y5) - (c * y4))))
	elif y3 <= 3.9e+83:
		tmp = j * (y1 * ((x * i) - (y3 * y4)))
	else:
		tmp = y3 * ((j * t_2) + (z * ((a * y1) - (c * y0))))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(y1 * y4) - Float64(y0 * y5))
	t_2 = Float64(Float64(y0 * y5) - Float64(y1 * y4))
	t_3 = Float64(Float64(c * y0) - Float64(a * y1))
	tmp = 0.0
	if (y3 <= -2e+81)
		tmp = Float64(y3 * Float64(Float64(y * Float64(Float64(c * y4) - Float64(a * y5))) - Float64(Float64(j * t_1) + Float64(z * t_3))));
	elseif (y3 <= -9e-222)
		tmp = Float64(j * Float64(Float64(Float64(y3 * t_2) + Float64(t * Float64(Float64(b * y4) - Float64(i * y5)))) + Float64(x * Float64(Float64(i * y1) - Float64(b * y0)))));
	elseif (y3 <= 4.2e-172)
		tmp = Float64(y5 * Float64(Float64(a * Float64(Float64(t * y2) - Float64(y * y3))) + Float64(Float64(i * Float64(Float64(y * k) - Float64(t * j))) + Float64(y0 * Float64(Float64(j * y3) - Float64(k * y2))))));
	elseif (y3 <= 5.7e-21)
		tmp = Float64(y2 * Float64(Float64(Float64(k * t_1) + Float64(x * t_3)) + Float64(t * Float64(Float64(a * y5) - Float64(c * y4)))));
	elseif (y3 <= 3.9e+83)
		tmp = Float64(j * Float64(y1 * Float64(Float64(x * i) - Float64(y3 * y4))));
	else
		tmp = Float64(y3 * Float64(Float64(j * t_2) + Float64(z * Float64(Float64(a * y1) - Float64(c * y0)))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = (y1 * y4) - (y0 * y5);
	t_2 = (y0 * y5) - (y1 * y4);
	t_3 = (c * y0) - (a * y1);
	tmp = 0.0;
	if (y3 <= -2e+81)
		tmp = y3 * ((y * ((c * y4) - (a * y5))) - ((j * t_1) + (z * t_3)));
	elseif (y3 <= -9e-222)
		tmp = j * (((y3 * t_2) + (t * ((b * y4) - (i * y5)))) + (x * ((i * y1) - (b * y0))));
	elseif (y3 <= 4.2e-172)
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((i * ((y * k) - (t * j))) + (y0 * ((j * y3) - (k * y2)))));
	elseif (y3 <= 5.7e-21)
		tmp = y2 * (((k * t_1) + (x * t_3)) + (t * ((a * y5) - (c * y4))));
	elseif (y3 <= 3.9e+83)
		tmp = j * (y1 * ((x * i) - (y3 * y4)));
	else
		tmp = y3 * ((j * t_2) + (z * ((a * y1) - (c * y0))));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y3, -2e+81], N[(y3 * N[(N[(y * N[(N[(c * y4), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(j * t$95$1), $MachinePrecision] + N[(z * t$95$3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, -9e-222], N[(j * N[(N[(N[(y3 * t$95$2), $MachinePrecision] + N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, 4.2e-172], N[(y5 * N[(N[(a * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(i * N[(N[(y * k), $MachinePrecision] - N[(t * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(N[(j * y3), $MachinePrecision] - N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, 5.7e-21], N[(y2 * N[(N[(N[(k * t$95$1), $MachinePrecision] + N[(x * t$95$3), $MachinePrecision]), $MachinePrecision] + N[(t * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, 3.9e+83], N[(j * N[(y1 * N[(N[(x * i), $MachinePrecision] - N[(y3 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(y3 * N[(N[(j * t$95$2), $MachinePrecision] + N[(z * N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]

Derivation

1. Split input into 6 regimes

2. if y3 < -1.99999999999999984e81

   1. Initial program 25.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y3 around -inf 71.9%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   if -1.99999999999999984e81 < y3 < -9.00000000000000028e-222

   1. Initial program 33.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 47.2%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   if -9.00000000000000028e-222 < y3 < 4.1999999999999999e-172

   1. Initial program 40.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around -inf 47.2%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   if 4.1999999999999999e-172 < y3 < 5.6999999999999996e-21

   1. Initial program 36.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 63.6%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   if 5.6999999999999996e-21 < y3 < 3.9000000000000002e83

   1. Initial program 14.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 29.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y1 around -inf 58.0%

      \[\leadsto \color{blue}{-1 \cdot \left(j \cdot \left(y1 \cdot \left(y3 \cdot y4 - i \cdot x\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 58.0%

         \[\leadsto \color{blue}{\left(-1 \cdot j\right) \cdot \left(y1 \cdot \left(y3 \cdot y4 - i \cdot x\right)\right)} \]

      2. mul-1-neg 58.0%

         \[\leadsto \color{blue}{\left(-j\right)} \cdot \left(y1 \cdot \left(y3 \cdot y4 - i \cdot x\right)\right) \]

   6. Simplified 58.0%

      \[\leadsto \color{blue}{\left(-j\right) \cdot \left(y1 \cdot \left(y3 \cdot y4 - i \cdot x\right)\right)} \]

   if 3.9000000000000002e83 < y3

   1. Initial program 33.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y3 around -inf 54.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y around 0 54.2%

      \[\leadsto -1 \cdot \color{blue}{\left(y3 \cdot \left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 55.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y3 \leq -2 \cdot 10^{+81}:\\ \;\;\;\;y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) - \left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\right)\\ \mathbf{elif}\;y3 \leq -9 \cdot 10^{-222}:\\ \;\;\;\;j \cdot \left(\left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y3 \leq 4.2 \cdot 10^{-172}:\\ \;\;\;\;y5 \cdot \left(a \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(i \cdot \left(y \cdot k - t \cdot j\right) + y0 \cdot \left(j \cdot y3 - k \cdot y2\right)\right)\right)\\ \mathbf{elif}\;y3 \leq 5.7 \cdot 10^{-21}:\\ \;\;\;\;y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;y3 \leq 3.9 \cdot 10^{+83}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i - y3 \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y3 \cdot \left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 6: 39.6% accurate, 1.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := k \cdot \left(y1 \cdot \left(z \cdot \left(\frac{b \cdot y0}{y1} - i\right)\right)\right)\\ \mathbf{if}\;z \leq -4.8 \cdot 10^{-7}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;z \leq 1.95 \cdot 10^{-218}:\\ \;\;\;\;y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 1.45 \cdot 10^{-77}:\\ \;\;\;\;i \cdot \left(x \cdot \left(j \cdot y1 - y \cdot c\right)\right)\\ \mathbf{elif}\;z \leq 6 \cdot 10^{+70}:\\ \;\;\;\;y4 \cdot \left(c \cdot \left(y \cdot y3 - t \cdot y2\right) - \left(y1 \cdot \left(j \cdot y3 - k \cdot y2\right) + b \cdot \left(y \cdot k - t \cdot j\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* k (* y1 (* z (- (/ (* b y0) y1) i))))))
   (if (<= z -4.8e-7)
     t_1
     (if (<= z 1.95e-218)
       (*
        y2
        (+
         (+ (* k (- (* y1 y4) (* y0 y5))) (* x (- (* c y0) (* a y1))))
         (* t (- (* a y5) (* c y4)))))
       (if (<= z 1.45e-77)
         (* i (* x (- (* j y1) (* y c))))
         (if (<= z 6e+70)
           (*
            y4
            (-
             (* c (- (* y y3) (* t y2)))
             (+ (* y1 (- (* j y3) (* k y2))) (* b (- (* y k) (* t 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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = k * (y1 * (z * (((b * y0) / y1) - i)));
	double tmp;
	if (z <= -4.8e-7) {
		tmp = t_1;
	} else if (z <= 1.95e-218) {
		tmp = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))));
	} else if (z <= 1.45e-77) {
		tmp = i * (x * ((j * y1) - (y * c)));
	} else if (z <= 6e+70) {
		tmp = y4 * ((c * ((y * y3) - (t * y2))) - ((y1 * ((j * y3) - (k * y2))) + (b * ((y * k) - (t * j)))));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = k * (y1 * (z * (((b * y0) / y1) - i)))
    if (z <= (-4.8d-7)) then
        tmp = t_1
    else if (z <= 1.95d-218) then
        tmp = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))))
    else if (z <= 1.45d-77) then
        tmp = i * (x * ((j * y1) - (y * c)))
    else if (z <= 6d+70) then
        tmp = y4 * ((c * ((y * y3) - (t * y2))) - ((y1 * ((j * y3) - (k * y2))) + (b * ((y * k) - (t * 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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = k * (y1 * (z * (((b * y0) / y1) - i)));
	double tmp;
	if (z <= -4.8e-7) {
		tmp = t_1;
	} else if (z <= 1.95e-218) {
		tmp = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))));
	} else if (z <= 1.45e-77) {
		tmp = i * (x * ((j * y1) - (y * c)));
	} else if (z <= 6e+70) {
		tmp = y4 * ((c * ((y * y3) - (t * y2))) - ((y1 * ((j * y3) - (k * y2))) + (b * ((y * k) - (t * j)))));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = k * (y1 * (z * (((b * y0) / y1) - i)))
	tmp = 0
	if z <= -4.8e-7:
		tmp = t_1
	elif z <= 1.95e-218:
		tmp = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))))
	elif z <= 1.45e-77:
		tmp = i * (x * ((j * y1) - (y * c)))
	elif z <= 6e+70:
		tmp = y4 * ((c * ((y * y3) - (t * y2))) - ((y1 * ((j * y3) - (k * y2))) + (b * ((y * k) - (t * j)))))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(k * Float64(y1 * Float64(z * Float64(Float64(Float64(b * y0) / y1) - i))))
	tmp = 0.0
	if (z <= -4.8e-7)
		tmp = t_1;
	elseif (z <= 1.95e-218)
		tmp = Float64(y2 * Float64(Float64(Float64(k * Float64(Float64(y1 * y4) - Float64(y0 * y5))) + Float64(x * Float64(Float64(c * y0) - Float64(a * y1)))) + Float64(t * Float64(Float64(a * y5) - Float64(c * y4)))));
	elseif (z <= 1.45e-77)
		tmp = Float64(i * Float64(x * Float64(Float64(j * y1) - Float64(y * c))));
	elseif (z <= 6e+70)
		tmp = Float64(y4 * Float64(Float64(c * Float64(Float64(y * y3) - Float64(t * y2))) - Float64(Float64(y1 * Float64(Float64(j * y3) - Float64(k * y2))) + Float64(b * Float64(Float64(y * k) - Float64(t * j))))));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = k * (y1 * (z * (((b * y0) / y1) - i)));
	tmp = 0.0;
	if (z <= -4.8e-7)
		tmp = t_1;
	elseif (z <= 1.95e-218)
		tmp = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))));
	elseif (z <= 1.45e-77)
		tmp = i * (x * ((j * y1) - (y * c)));
	elseif (z <= 6e+70)
		tmp = y4 * ((c * ((y * y3) - (t * y2))) - ((y1 * ((j * y3) - (k * y2))) + (b * ((y * k) - (t * j)))));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(k * N[(y1 * N[(z * N[(N[(N[(b * y0), $MachinePrecision] / y1), $MachinePrecision] - i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -4.8e-7], t$95$1, If[LessEqual[z, 1.95e-218], N[(y2 * N[(N[(N[(k * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(x * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(t * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.45e-77], N[(i * N[(x * N[(N[(j * y1), $MachinePrecision] - N[(y * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 6e+70], N[(y4 * N[(N[(c * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(y1 * N[(N[(j * y3), $MachinePrecision] - N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(b * N[(N[(y * k), $MachinePrecision] - N[(t * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]

Derivation

1. Split input into 4 regimes

2. if z < -4.79999999999999957e-7 or 5.99999999999999952e70 < z

   1. Initial program 28.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around -inf 38.4%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 38.4%

         \[\leadsto \color{blue}{\left(-k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 38.4%

         \[\leadsto \left(-k \cdot \left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 38.4%

      \[\leadsto \color{blue}{\left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in y1 around inf 40.1%

      \[\leadsto \left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - \color{blue}{y1 \cdot \left(-1 \cdot \left(i \cdot z\right) + \frac{b \cdot \left(y0 \cdot z\right)}{y1}\right)}\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   7. Taylor expanded in z around inf 52.0%

      \[\leadsto \color{blue}{k \cdot \left(y1 \cdot \left(z \cdot \left(-1 \cdot i + \frac{b \cdot y0}{y1}\right)\right)\right)} \]

   if -4.79999999999999957e-7 < z < 1.95e-218

   1. Initial program 36.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 48.7%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   if 1.95e-218 < z < 1.4499999999999999e-77

   1. Initial program 38.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 39.5%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in x around inf 51.0%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 51.0%

         \[\leadsto \color{blue}{\left(-1 \cdot i\right) \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right)} \]

      2. neg-mul-1 51.0%

         \[\leadsto \color{blue}{\left(-i\right)} \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right) \]

   6. Simplified 51.0%

      \[\leadsto \color{blue}{\left(-i\right) \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right)} \]

   if 1.4499999999999999e-77 < z < 5.99999999999999952e70

   1. Initial program 33.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 63.9%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 52.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -4.8 \cdot 10^{-7}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(z \cdot \left(\frac{b \cdot y0}{y1} - i\right)\right)\right)\\ \mathbf{elif}\;z \leq 1.95 \cdot 10^{-218}:\\ \;\;\;\;y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 1.45 \cdot 10^{-77}:\\ \;\;\;\;i \cdot \left(x \cdot \left(j \cdot y1 - y \cdot c\right)\right)\\ \mathbf{elif}\;z \leq 6 \cdot 10^{+70}:\\ \;\;\;\;y4 \cdot \left(c \cdot \left(y \cdot y3 - t \cdot y2\right) - \left(y1 \cdot \left(j \cdot y3 - k \cdot y2\right) + b \cdot \left(y \cdot k - t \cdot j\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(z \cdot \left(\frac{b \cdot y0}{y1} - i\right)\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 7: 31.7% accurate, 2.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -2.75 \cdot 10^{+135}:\\ \;\;\;\;i \cdot \left(z \cdot \left(t \cdot c - k \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq -2.3 \cdot 10^{+22}:\\ \;\;\;\;k \cdot \left(y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq -8.5 \cdot 10^{-18}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq 1.9 \cdot 10^{-218}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 10^{-91}:\\ \;\;\;\;i \cdot \left(x \cdot \left(j \cdot y1 - y \cdot c\right)\right)\\ \mathbf{elif}\;z \leq 3.1 \cdot 10^{+19}:\\ \;\;\;\;y2 \cdot \left(y1 \cdot \left(k \cdot y4 - x \cdot a\right)\right)\\ \mathbf{elif}\;z \leq 2.2 \cdot 10^{+70}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot y0 - i \cdot y1\right) \cdot \left(z \cdot k\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= z -2.75e+135)
   (* i (* z (- (* t c) (* k y1))))
   (if (<= z -2.3e+22)
     (* k (* y (- (* i y5) (* b y4))))
     (if (<= z -8.5e-18)
       (* j (* t (- (* b y4) (* i y5))))
       (if (<= z 1.9e-218)
         (* c (* y2 (- (* x y0) (* t y4))))
         (if (<= z 1e-91)
           (* i (* x (- (* j y1) (* y c))))
           (if (<= z 3.1e+19)
             (* y2 (* y1 (- (* k y4) (* x a))))
             (if (<= z 2.2e+70)
               (* b (* y4 (- (* t j) (* y k))))
               (* (- (* b y0) (* i y1)) (* z k))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -2.75e+135) {
		tmp = i * (z * ((t * c) - (k * y1)));
	} else if (z <= -2.3e+22) {
		tmp = k * (y * ((i * y5) - (b * y4)));
	} else if (z <= -8.5e-18) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (z <= 1.9e-218) {
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	} else if (z <= 1e-91) {
		tmp = i * (x * ((j * y1) - (y * c)));
	} else if (z <= 3.1e+19) {
		tmp = y2 * (y1 * ((k * y4) - (x * a)));
	} else if (z <= 2.2e+70) {
		tmp = b * (y4 * ((t * j) - (y * k)));
	} else {
		tmp = ((b * y0) - (i * y1)) * (z * k);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (z <= (-2.75d+135)) then
        tmp = i * (z * ((t * c) - (k * y1)))
    else if (z <= (-2.3d+22)) then
        tmp = k * (y * ((i * y5) - (b * y4)))
    else if (z <= (-8.5d-18)) then
        tmp = j * (t * ((b * y4) - (i * y5)))
    else if (z <= 1.9d-218) then
        tmp = c * (y2 * ((x * y0) - (t * y4)))
    else if (z <= 1d-91) then
        tmp = i * (x * ((j * y1) - (y * c)))
    else if (z <= 3.1d+19) then
        tmp = y2 * (y1 * ((k * y4) - (x * a)))
    else if (z <= 2.2d+70) then
        tmp = b * (y4 * ((t * j) - (y * k)))
    else
        tmp = ((b * y0) - (i * y1)) * (z * k)
    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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -2.75e+135) {
		tmp = i * (z * ((t * c) - (k * y1)));
	} else if (z <= -2.3e+22) {
		tmp = k * (y * ((i * y5) - (b * y4)));
	} else if (z <= -8.5e-18) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (z <= 1.9e-218) {
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	} else if (z <= 1e-91) {
		tmp = i * (x * ((j * y1) - (y * c)));
	} else if (z <= 3.1e+19) {
		tmp = y2 * (y1 * ((k * y4) - (x * a)));
	} else if (z <= 2.2e+70) {
		tmp = b * (y4 * ((t * j) - (y * k)));
	} else {
		tmp = ((b * y0) - (i * y1)) * (z * k);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if z <= -2.75e+135:
		tmp = i * (z * ((t * c) - (k * y1)))
	elif z <= -2.3e+22:
		tmp = k * (y * ((i * y5) - (b * y4)))
	elif z <= -8.5e-18:
		tmp = j * (t * ((b * y4) - (i * y5)))
	elif z <= 1.9e-218:
		tmp = c * (y2 * ((x * y0) - (t * y4)))
	elif z <= 1e-91:
		tmp = i * (x * ((j * y1) - (y * c)))
	elif z <= 3.1e+19:
		tmp = y2 * (y1 * ((k * y4) - (x * a)))
	elif z <= 2.2e+70:
		tmp = b * (y4 * ((t * j) - (y * k)))
	else:
		tmp = ((b * y0) - (i * y1)) * (z * k)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (z <= -2.75e+135)
		tmp = Float64(i * Float64(z * Float64(Float64(t * c) - Float64(k * y1))));
	elseif (z <= -2.3e+22)
		tmp = Float64(k * Float64(y * Float64(Float64(i * y5) - Float64(b * y4))));
	elseif (z <= -8.5e-18)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))));
	elseif (z <= 1.9e-218)
		tmp = Float64(c * Float64(y2 * Float64(Float64(x * y0) - Float64(t * y4))));
	elseif (z <= 1e-91)
		tmp = Float64(i * Float64(x * Float64(Float64(j * y1) - Float64(y * c))));
	elseif (z <= 3.1e+19)
		tmp = Float64(y2 * Float64(y1 * Float64(Float64(k * y4) - Float64(x * a))));
	elseif (z <= 2.2e+70)
		tmp = Float64(b * Float64(y4 * Float64(Float64(t * j) - Float64(y * k))));
	else
		tmp = Float64(Float64(Float64(b * y0) - Float64(i * y1)) * Float64(z * k));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (z <= -2.75e+135)
		tmp = i * (z * ((t * c) - (k * y1)));
	elseif (z <= -2.3e+22)
		tmp = k * (y * ((i * y5) - (b * y4)));
	elseif (z <= -8.5e-18)
		tmp = j * (t * ((b * y4) - (i * y5)));
	elseif (z <= 1.9e-218)
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	elseif (z <= 1e-91)
		tmp = i * (x * ((j * y1) - (y * c)));
	elseif (z <= 3.1e+19)
		tmp = y2 * (y1 * ((k * y4) - (x * a)));
	elseif (z <= 2.2e+70)
		tmp = b * (y4 * ((t * j) - (y * k)));
	else
		tmp = ((b * y0) - (i * y1)) * (z * k);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[z, -2.75e+135], N[(i * N[(z * N[(N[(t * c), $MachinePrecision] - N[(k * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -2.3e+22], N[(k * N[(y * N[(N[(i * y5), $MachinePrecision] - N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -8.5e-18], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.9e-218], N[(c * N[(y2 * N[(N[(x * y0), $MachinePrecision] - N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1e-91], N[(i * N[(x * N[(N[(j * y1), $MachinePrecision] - N[(y * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 3.1e+19], N[(y2 * N[(y1 * N[(N[(k * y4), $MachinePrecision] - N[(x * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 2.2e+70], N[(b * N[(y4 * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision] * N[(z * k), $MachinePrecision]), $MachinePrecision]]]]]]]]

Derivation

1. Split input into 8 regimes

2. if z < -2.7499999999999999e135

   1. Initial program 26.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 39.6%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in z around -inf 50.6%

      \[\leadsto \color{blue}{i \cdot \left(z \cdot \left(c \cdot t - k \cdot y1\right)\right)} \]

   if -2.7499999999999999e135 < z < -2.3000000000000002e22

   1. Initial program 44.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around -inf 61.8%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 61.8%

         \[\leadsto \color{blue}{\left(-k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 61.8%

         \[\leadsto \left(-k \cdot \left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 61.8%

      \[\leadsto \color{blue}{\left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in y around inf 61.6%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 61.6%

         \[\leadsto \color{blue}{\left(-1 \cdot k\right) \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

      2. neg-mul-1 61.6%

         \[\leadsto \color{blue}{\left(-k\right)} \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) \]

   8. Simplified 61.6%

      \[\leadsto \color{blue}{\left(-k\right) \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   if -2.3000000000000002e22 < z < -8.4999999999999995e-18

   1. Initial program 27.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 63.6%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in t around inf 65.0%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   if -8.4999999999999995e-18 < z < 1.8999999999999999e-218

   1. Initial program 36.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 48.7%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in c around inf 38.7%

      \[\leadsto \color{blue}{c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)} \]

   if 1.8999999999999999e-218 < z < 1.00000000000000002e-91

   1. Initial program 35.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 35.7%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in x around inf 48.9%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 48.9%

         \[\leadsto \color{blue}{\left(-1 \cdot i\right) \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right)} \]

      2. neg-mul-1 48.9%

         \[\leadsto \color{blue}{\left(-i\right)} \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right) \]

   6. Simplified 48.9%

      \[\leadsto \color{blue}{\left(-i\right) \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right)} \]

   if 1.00000000000000002e-91 < z < 3.1e19

   1. Initial program 22.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 41.4%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in y1 around inf 52.9%

      \[\leadsto y2 \cdot \color{blue}{\left(y1 \cdot \left(-1 \cdot \left(a \cdot x\right) + k \cdot y4\right)\right)} \]

   if 3.1e19 < z < 2.20000000000000001e70

   1. Initial program 66.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 58.4%

      \[\leadsto \left(\color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in b around inf 75.2%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} \]

   if 2.20000000000000001e70 < z

   1. Initial program 22.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around -inf 41.3%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 41.3%

         \[\leadsto \color{blue}{\left(-k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 41.3%

         \[\leadsto \left(-k \cdot \left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 41.3%

      \[\leadsto \color{blue}{\left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in z around -inf 53.1%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 59.6%

         \[\leadsto \color{blue}{\left(k \cdot z\right) \cdot \left(b \cdot y0 - i \cdot y1\right)} \]

   8. Simplified 59.6%

      \[\leadsto \color{blue}{\left(k \cdot z\right) \cdot \left(b \cdot y0 - i \cdot y1\right)} \]
3. Recombined 8 regimes into one program.

4. Final simplification 50.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -2.75 \cdot 10^{+135}:\\ \;\;\;\;i \cdot \left(z \cdot \left(t \cdot c - k \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq -2.3 \cdot 10^{+22}:\\ \;\;\;\;k \cdot \left(y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq -8.5 \cdot 10^{-18}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq 1.9 \cdot 10^{-218}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 10^{-91}:\\ \;\;\;\;i \cdot \left(x \cdot \left(j \cdot y1 - y \cdot c\right)\right)\\ \mathbf{elif}\;z \leq 3.1 \cdot 10^{+19}:\\ \;\;\;\;y2 \cdot \left(y1 \cdot \left(k \cdot y4 - x \cdot a\right)\right)\\ \mathbf{elif}\;z \leq 2.2 \cdot 10^{+70}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot y0 - i \cdot y1\right) \cdot \left(z \cdot k\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 8: 31.8% accurate, 2.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -5.5 \cdot 10^{+134}:\\ \;\;\;\;i \cdot \left(z \cdot \left(t \cdot c - k \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq -5.5 \cdot 10^{+22}:\\ \;\;\;\;k \cdot \left(y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq -7 \cdot 10^{-17}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq 8.5 \cdot 10^{-219}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 5.4 \cdot 10^{-73}:\\ \;\;\;\;i \cdot \left(x \cdot \left(j \cdot y1 - y \cdot c\right)\right)\\ \mathbf{elif}\;z \leq 3.6 \cdot 10^{+19}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 3.5 \cdot 10^{+70}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot y0 - i \cdot y1\right) \cdot \left(z \cdot k\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= z -5.5e+134)
   (* i (* z (- (* t c) (* k y1))))
   (if (<= z -5.5e+22)
     (* k (* y (- (* i y5) (* b y4))))
     (if (<= z -7e-17)
       (* j (* t (- (* b y4) (* i y5))))
       (if (<= z 8.5e-219)
         (* c (* y2 (- (* x y0) (* t y4))))
         (if (<= z 5.4e-73)
           (* i (* x (- (* j y1) (* y c))))
           (if (<= z 3.6e+19)
             (* j (* y3 (- (* y0 y5) (* y1 y4))))
             (if (<= z 3.5e+70)
               (* b (* y4 (- (* t j) (* y k))))
               (* (- (* b y0) (* i y1)) (* z k))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -5.5e+134) {
		tmp = i * (z * ((t * c) - (k * y1)));
	} else if (z <= -5.5e+22) {
		tmp = k * (y * ((i * y5) - (b * y4)));
	} else if (z <= -7e-17) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (z <= 8.5e-219) {
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	} else if (z <= 5.4e-73) {
		tmp = i * (x * ((j * y1) - (y * c)));
	} else if (z <= 3.6e+19) {
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	} else if (z <= 3.5e+70) {
		tmp = b * (y4 * ((t * j) - (y * k)));
	} else {
		tmp = ((b * y0) - (i * y1)) * (z * k);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (z <= (-5.5d+134)) then
        tmp = i * (z * ((t * c) - (k * y1)))
    else if (z <= (-5.5d+22)) then
        tmp = k * (y * ((i * y5) - (b * y4)))
    else if (z <= (-7d-17)) then
        tmp = j * (t * ((b * y4) - (i * y5)))
    else if (z <= 8.5d-219) then
        tmp = c * (y2 * ((x * y0) - (t * y4)))
    else if (z <= 5.4d-73) then
        tmp = i * (x * ((j * y1) - (y * c)))
    else if (z <= 3.6d+19) then
        tmp = j * (y3 * ((y0 * y5) - (y1 * y4)))
    else if (z <= 3.5d+70) then
        tmp = b * (y4 * ((t * j) - (y * k)))
    else
        tmp = ((b * y0) - (i * y1)) * (z * k)
    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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -5.5e+134) {
		tmp = i * (z * ((t * c) - (k * y1)));
	} else if (z <= -5.5e+22) {
		tmp = k * (y * ((i * y5) - (b * y4)));
	} else if (z <= -7e-17) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (z <= 8.5e-219) {
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	} else if (z <= 5.4e-73) {
		tmp = i * (x * ((j * y1) - (y * c)));
	} else if (z <= 3.6e+19) {
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	} else if (z <= 3.5e+70) {
		tmp = b * (y4 * ((t * j) - (y * k)));
	} else {
		tmp = ((b * y0) - (i * y1)) * (z * k);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if z <= -5.5e+134:
		tmp = i * (z * ((t * c) - (k * y1)))
	elif z <= -5.5e+22:
		tmp = k * (y * ((i * y5) - (b * y4)))
	elif z <= -7e-17:
		tmp = j * (t * ((b * y4) - (i * y5)))
	elif z <= 8.5e-219:
		tmp = c * (y2 * ((x * y0) - (t * y4)))
	elif z <= 5.4e-73:
		tmp = i * (x * ((j * y1) - (y * c)))
	elif z <= 3.6e+19:
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)))
	elif z <= 3.5e+70:
		tmp = b * (y4 * ((t * j) - (y * k)))
	else:
		tmp = ((b * y0) - (i * y1)) * (z * k)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (z <= -5.5e+134)
		tmp = Float64(i * Float64(z * Float64(Float64(t * c) - Float64(k * y1))));
	elseif (z <= -5.5e+22)
		tmp = Float64(k * Float64(y * Float64(Float64(i * y5) - Float64(b * y4))));
	elseif (z <= -7e-17)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))));
	elseif (z <= 8.5e-219)
		tmp = Float64(c * Float64(y2 * Float64(Float64(x * y0) - Float64(t * y4))));
	elseif (z <= 5.4e-73)
		tmp = Float64(i * Float64(x * Float64(Float64(j * y1) - Float64(y * c))));
	elseif (z <= 3.6e+19)
		tmp = Float64(j * Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4))));
	elseif (z <= 3.5e+70)
		tmp = Float64(b * Float64(y4 * Float64(Float64(t * j) - Float64(y * k))));
	else
		tmp = Float64(Float64(Float64(b * y0) - Float64(i * y1)) * Float64(z * k));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (z <= -5.5e+134)
		tmp = i * (z * ((t * c) - (k * y1)));
	elseif (z <= -5.5e+22)
		tmp = k * (y * ((i * y5) - (b * y4)));
	elseif (z <= -7e-17)
		tmp = j * (t * ((b * y4) - (i * y5)));
	elseif (z <= 8.5e-219)
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	elseif (z <= 5.4e-73)
		tmp = i * (x * ((j * y1) - (y * c)));
	elseif (z <= 3.6e+19)
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	elseif (z <= 3.5e+70)
		tmp = b * (y4 * ((t * j) - (y * k)));
	else
		tmp = ((b * y0) - (i * y1)) * (z * k);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[z, -5.5e+134], N[(i * N[(z * N[(N[(t * c), $MachinePrecision] - N[(k * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -5.5e+22], N[(k * N[(y * N[(N[(i * y5), $MachinePrecision] - N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -7e-17], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 8.5e-219], N[(c * N[(y2 * N[(N[(x * y0), $MachinePrecision] - N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 5.4e-73], N[(i * N[(x * N[(N[(j * y1), $MachinePrecision] - N[(y * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 3.6e+19], N[(j * N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 3.5e+70], N[(b * N[(y4 * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision] * N[(z * k), $MachinePrecision]), $MachinePrecision]]]]]]]]

Derivation

1. Split input into 8 regimes

2. if z < -5.4999999999999999e134

   1. Initial program 26.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 39.6%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in z around -inf 50.6%

      \[\leadsto \color{blue}{i \cdot \left(z \cdot \left(c \cdot t - k \cdot y1\right)\right)} \]

   if -5.4999999999999999e134 < z < -5.50000000000000021e22

   1. Initial program 44.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around -inf 61.8%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 61.8%

         \[\leadsto \color{blue}{\left(-k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 61.8%

         \[\leadsto \left(-k \cdot \left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 61.8%

      \[\leadsto \color{blue}{\left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in y around inf 61.6%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 61.6%

         \[\leadsto \color{blue}{\left(-1 \cdot k\right) \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

      2. neg-mul-1 61.6%

         \[\leadsto \color{blue}{\left(-k\right)} \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) \]

   8. Simplified 61.6%

      \[\leadsto \color{blue}{\left(-k\right) \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   if -5.50000000000000021e22 < z < -7.0000000000000003e-17

   1. Initial program 27.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 63.6%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in t around inf 65.0%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   if -7.0000000000000003e-17 < z < 8.49999999999999964e-219

   1. Initial program 36.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 48.7%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in c around inf 38.7%

      \[\leadsto \color{blue}{c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)} \]

   if 8.49999999999999964e-219 < z < 5.39999999999999989e-73

   1. Initial program 38.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 45.7%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in x around inf 49.2%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 49.2%

         \[\leadsto \color{blue}{\left(-1 \cdot i\right) \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right)} \]

      2. neg-mul-1 49.2%

         \[\leadsto \color{blue}{\left(-i\right)} \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right) \]

   6. Simplified 49.2%

      \[\leadsto \color{blue}{\left(-i\right) \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right)} \]

   if 5.39999999999999989e-73 < z < 3.6e19

   1. Initial program 14.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around -inf 42.9%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 42.9%

         \[\leadsto \color{blue}{\left(-k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 42.9%

         \[\leadsto \left(-k \cdot \left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 42.9%

      \[\leadsto \color{blue}{\left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in k around 0 53.1%

      \[\leadsto \color{blue}{-1 \cdot \left(j \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 53.1%

         \[\leadsto \color{blue}{\left(-1 \cdot j\right) \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \]

      2. mul-1-neg 53.1%

         \[\leadsto \color{blue}{\left(-j\right)} \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) \]

   8. Simplified 53.1%

      \[\leadsto \color{blue}{\left(-j\right) \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \]

   if 3.6e19 < z < 3.50000000000000002e70

   1. Initial program 66.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 58.4%

      \[\leadsto \left(\color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in b around inf 75.2%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} \]

   if 3.50000000000000002e70 < z

   1. Initial program 22.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around -inf 41.3%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 41.3%

         \[\leadsto \color{blue}{\left(-k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 41.3%

         \[\leadsto \left(-k \cdot \left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 41.3%

      \[\leadsto \color{blue}{\left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in z around -inf 53.1%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 59.6%

         \[\leadsto \color{blue}{\left(k \cdot z\right) \cdot \left(b \cdot y0 - i \cdot y1\right)} \]

   8. Simplified 59.6%

      \[\leadsto \color{blue}{\left(k \cdot z\right) \cdot \left(b \cdot y0 - i \cdot y1\right)} \]
3. Recombined 8 regimes into one program.

4. Final simplification 50.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -5.5 \cdot 10^{+134}:\\ \;\;\;\;i \cdot \left(z \cdot \left(t \cdot c - k \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq -5.5 \cdot 10^{+22}:\\ \;\;\;\;k \cdot \left(y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq -7 \cdot 10^{-17}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;z \leq 8.5 \cdot 10^{-219}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 5.4 \cdot 10^{-73}:\\ \;\;\;\;i \cdot \left(x \cdot \left(j \cdot y1 - y \cdot c\right)\right)\\ \mathbf{elif}\;z \leq 3.6 \cdot 10^{+19}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 3.5 \cdot 10^{+70}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot y0 - i \cdot y1\right) \cdot \left(z \cdot k\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 9: 41.8% accurate, 2.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y1 \cdot y4 - y0 \cdot y5\\ t_2 := c \cdot y0 - a \cdot y1\\ \mathbf{if}\;y3 \leq -5.3 \cdot 10^{+50}:\\ \;\;\;\;y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) - \left(j \cdot t\_1 + z \cdot t\_2\right)\right)\\ \mathbf{elif}\;y3 \leq 6.4 \cdot 10^{-182}:\\ \;\;\;\;y4 \cdot \left(c \cdot \left(y \cdot y3 - t \cdot y2\right) - \left(y1 \cdot \left(j \cdot y3 - k \cdot y2\right) + b \cdot \left(y \cdot k - t \cdot j\right)\right)\right)\\ \mathbf{elif}\;y3 \leq 2.45 \cdot 10^{-21}:\\ \;\;\;\;y2 \cdot \left(\left(k \cdot t\_1 + x \cdot t\_2\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;y3 \leq 7 \cdot 10^{+82}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i - y3 \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y3 \cdot \left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* y1 y4) (* y0 y5))) (t_2 (- (* c y0) (* a y1))))
   (if (<= y3 -5.3e+50)
     (* y3 (- (* y (- (* c y4) (* a y5))) (+ (* j t_1) (* z t_2))))
     (if (<= y3 6.4e-182)
       (*
        y4
        (-
         (* c (- (* y y3) (* t y2)))
         (+ (* y1 (- (* j y3) (* k y2))) (* b (- (* y k) (* t j))))))
       (if (<= y3 2.45e-21)
         (* y2 (+ (+ (* k t_1) (* x t_2)) (* t (- (* a y5) (* c y4)))))
         (if (<= y3 7e+82)
           (* j (* y1 (- (* x i) (* y3 y4))))
           (*
            y3
            (+
             (* j (- (* y0 y5) (* y1 y4)))
             (* z (- (* a y1) (* c y0)))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (y1 * y4) - (y0 * y5);
	double t_2 = (c * y0) - (a * y1);
	double tmp;
	if (y3 <= -5.3e+50) {
		tmp = y3 * ((y * ((c * y4) - (a * y5))) - ((j * t_1) + (z * t_2)));
	} else if (y3 <= 6.4e-182) {
		tmp = y4 * ((c * ((y * y3) - (t * y2))) - ((y1 * ((j * y3) - (k * y2))) + (b * ((y * k) - (t * j)))));
	} else if (y3 <= 2.45e-21) {
		tmp = y2 * (((k * t_1) + (x * t_2)) + (t * ((a * y5) - (c * y4))));
	} else if (y3 <= 7e+82) {
		tmp = j * (y1 * ((x * i) - (y3 * y4)));
	} else {
		tmp = y3 * ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0))));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = (y1 * y4) - (y0 * y5)
    t_2 = (c * y0) - (a * y1)
    if (y3 <= (-5.3d+50)) then
        tmp = y3 * ((y * ((c * y4) - (a * y5))) - ((j * t_1) + (z * t_2)))
    else if (y3 <= 6.4d-182) then
        tmp = y4 * ((c * ((y * y3) - (t * y2))) - ((y1 * ((j * y3) - (k * y2))) + (b * ((y * k) - (t * j)))))
    else if (y3 <= 2.45d-21) then
        tmp = y2 * (((k * t_1) + (x * t_2)) + (t * ((a * y5) - (c * y4))))
    else if (y3 <= 7d+82) then
        tmp = j * (y1 * ((x * i) - (y3 * y4)))
    else
        tmp = y3 * ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0))))
    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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (y1 * y4) - (y0 * y5);
	double t_2 = (c * y0) - (a * y1);
	double tmp;
	if (y3 <= -5.3e+50) {
		tmp = y3 * ((y * ((c * y4) - (a * y5))) - ((j * t_1) + (z * t_2)));
	} else if (y3 <= 6.4e-182) {
		tmp = y4 * ((c * ((y * y3) - (t * y2))) - ((y1 * ((j * y3) - (k * y2))) + (b * ((y * k) - (t * j)))));
	} else if (y3 <= 2.45e-21) {
		tmp = y2 * (((k * t_1) + (x * t_2)) + (t * ((a * y5) - (c * y4))));
	} else if (y3 <= 7e+82) {
		tmp = j * (y1 * ((x * i) - (y3 * y4)));
	} else {
		tmp = y3 * ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0))));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (y1 * y4) - (y0 * y5)
	t_2 = (c * y0) - (a * y1)
	tmp = 0
	if y3 <= -5.3e+50:
		tmp = y3 * ((y * ((c * y4) - (a * y5))) - ((j * t_1) + (z * t_2)))
	elif y3 <= 6.4e-182:
		tmp = y4 * ((c * ((y * y3) - (t * y2))) - ((y1 * ((j * y3) - (k * y2))) + (b * ((y * k) - (t * j)))))
	elif y3 <= 2.45e-21:
		tmp = y2 * (((k * t_1) + (x * t_2)) + (t * ((a * y5) - (c * y4))))
	elif y3 <= 7e+82:
		tmp = j * (y1 * ((x * i) - (y3 * y4)))
	else:
		tmp = y3 * ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0))))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(y1 * y4) - Float64(y0 * y5))
	t_2 = Float64(Float64(c * y0) - Float64(a * y1))
	tmp = 0.0
	if (y3 <= -5.3e+50)
		tmp = Float64(y3 * Float64(Float64(y * Float64(Float64(c * y4) - Float64(a * y5))) - Float64(Float64(j * t_1) + Float64(z * t_2))));
	elseif (y3 <= 6.4e-182)
		tmp = Float64(y4 * Float64(Float64(c * Float64(Float64(y * y3) - Float64(t * y2))) - Float64(Float64(y1 * Float64(Float64(j * y3) - Float64(k * y2))) + Float64(b * Float64(Float64(y * k) - Float64(t * j))))));
	elseif (y3 <= 2.45e-21)
		tmp = Float64(y2 * Float64(Float64(Float64(k * t_1) + Float64(x * t_2)) + Float64(t * Float64(Float64(a * y5) - Float64(c * y4)))));
	elseif (y3 <= 7e+82)
		tmp = Float64(j * Float64(y1 * Float64(Float64(x * i) - Float64(y3 * y4))));
	else
		tmp = Float64(y3 * Float64(Float64(j * Float64(Float64(y0 * y5) - Float64(y1 * y4))) + Float64(z * Float64(Float64(a * y1) - Float64(c * y0)))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = (y1 * y4) - (y0 * y5);
	t_2 = (c * y0) - (a * y1);
	tmp = 0.0;
	if (y3 <= -5.3e+50)
		tmp = y3 * ((y * ((c * y4) - (a * y5))) - ((j * t_1) + (z * t_2)));
	elseif (y3 <= 6.4e-182)
		tmp = y4 * ((c * ((y * y3) - (t * y2))) - ((y1 * ((j * y3) - (k * y2))) + (b * ((y * k) - (t * j)))));
	elseif (y3 <= 2.45e-21)
		tmp = y2 * (((k * t_1) + (x * t_2)) + (t * ((a * y5) - (c * y4))));
	elseif (y3 <= 7e+82)
		tmp = j * (y1 * ((x * i) - (y3 * y4)));
	else
		tmp = y3 * ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0))));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y3, -5.3e+50], N[(y3 * N[(N[(y * N[(N[(c * y4), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(j * t$95$1), $MachinePrecision] + N[(z * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, 6.4e-182], N[(y4 * N[(N[(c * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(y1 * N[(N[(j * y3), $MachinePrecision] - N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(b * N[(N[(y * k), $MachinePrecision] - N[(t * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, 2.45e-21], N[(y2 * N[(N[(N[(k * t$95$1), $MachinePrecision] + N[(x * t$95$2), $MachinePrecision]), $MachinePrecision] + N[(t * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, 7e+82], N[(j * N[(y1 * N[(N[(x * i), $MachinePrecision] - N[(y3 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(y3 * N[(N[(j * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(z * N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]

Derivation

1. Split input into 5 regimes

2. if y3 < -5.3000000000000002e50

   1. Initial program 20.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y3 around -inf 62.2%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   if -5.3000000000000002e50 < y3 < 6.40000000000000004e-182

   1. Initial program 40.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 44.9%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   if 6.40000000000000004e-182 < y3 < 2.4500000000000001e-21

   1. Initial program 36.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 60.8%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   if 2.4500000000000001e-21 < y3 < 7.0000000000000001e82

   1. Initial program 14.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 29.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y1 around -inf 58.0%

      \[\leadsto \color{blue}{-1 \cdot \left(j \cdot \left(y1 \cdot \left(y3 \cdot y4 - i \cdot x\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 58.0%

         \[\leadsto \color{blue}{\left(-1 \cdot j\right) \cdot \left(y1 \cdot \left(y3 \cdot y4 - i \cdot x\right)\right)} \]

      2. mul-1-neg 58.0%

         \[\leadsto \color{blue}{\left(-j\right)} \cdot \left(y1 \cdot \left(y3 \cdot y4 - i \cdot x\right)\right) \]

   6. Simplified 58.0%

      \[\leadsto \color{blue}{\left(-j\right) \cdot \left(y1 \cdot \left(y3 \cdot y4 - i \cdot x\right)\right)} \]

   if 7.0000000000000001e82 < y3

   1. Initial program 33.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y3 around -inf 54.1%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y around 0 54.2%

      \[\leadsto -1 \cdot \color{blue}{\left(y3 \cdot \left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 53.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y3 \leq -5.3 \cdot 10^{+50}:\\ \;\;\;\;y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) - \left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\right)\\ \mathbf{elif}\;y3 \leq 6.4 \cdot 10^{-182}:\\ \;\;\;\;y4 \cdot \left(c \cdot \left(y \cdot y3 - t \cdot y2\right) - \left(y1 \cdot \left(j \cdot y3 - k \cdot y2\right) + b \cdot \left(y \cdot k - t \cdot j\right)\right)\right)\\ \mathbf{elif}\;y3 \leq 2.45 \cdot 10^{-21}:\\ \;\;\;\;y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;y3 \leq 7 \cdot 10^{+82}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i - y3 \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y3 \cdot \left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 10: 31.7% accurate, 2.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right)\right)\\ \mathbf{if}\;z \leq -3.6 \cdot 10^{+134}:\\ \;\;\;\;i \cdot \left(z \cdot \left(t \cdot c - k \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq -1.05 \cdot 10^{-6}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;z \leq 1.7 \cdot 10^{-217}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 6.2 \cdot 10^{-73}:\\ \;\;\;\;i \cdot \left(x \cdot \left(j \cdot y1 - y \cdot c\right)\right)\\ \mathbf{elif}\;z \leq 2.8 \cdot 10^{+19}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 9.2 \cdot 10^{+70}:\\ \;\;\;\;t\_1\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot y0 - i \cdot y1\right) \cdot \left(z \cdot k\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* y4 (- (* t j) (* y k))))))
   (if (<= z -3.6e+134)
     (* i (* z (- (* t c) (* k y1))))
     (if (<= z -1.05e-6)
       t_1
       (if (<= z 1.7e-217)
         (* c (* y2 (- (* x y0) (* t y4))))
         (if (<= z 6.2e-73)
           (* i (* x (- (* j y1) (* y c))))
           (if (<= z 2.8e+19)
             (* j (* y3 (- (* y0 y5) (* y1 y4))))
             (if (<= z 9.2e+70) t_1 (* (- (* b y0) (* i y1)) (* z k))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (y4 * ((t * j) - (y * k)));
	double tmp;
	if (z <= -3.6e+134) {
		tmp = i * (z * ((t * c) - (k * y1)));
	} else if (z <= -1.05e-6) {
		tmp = t_1;
	} else if (z <= 1.7e-217) {
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	} else if (z <= 6.2e-73) {
		tmp = i * (x * ((j * y1) - (y * c)));
	} else if (z <= 2.8e+19) {
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	} else if (z <= 9.2e+70) {
		tmp = t_1;
	} else {
		tmp = ((b * y0) - (i * y1)) * (z * k);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = b * (y4 * ((t * j) - (y * k)))
    if (z <= (-3.6d+134)) then
        tmp = i * (z * ((t * c) - (k * y1)))
    else if (z <= (-1.05d-6)) then
        tmp = t_1
    else if (z <= 1.7d-217) then
        tmp = c * (y2 * ((x * y0) - (t * y4)))
    else if (z <= 6.2d-73) then
        tmp = i * (x * ((j * y1) - (y * c)))
    else if (z <= 2.8d+19) then
        tmp = j * (y3 * ((y0 * y5) - (y1 * y4)))
    else if (z <= 9.2d+70) then
        tmp = t_1
    else
        tmp = ((b * y0) - (i * y1)) * (z * k)
    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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (y4 * ((t * j) - (y * k)));
	double tmp;
	if (z <= -3.6e+134) {
		tmp = i * (z * ((t * c) - (k * y1)));
	} else if (z <= -1.05e-6) {
		tmp = t_1;
	} else if (z <= 1.7e-217) {
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	} else if (z <= 6.2e-73) {
		tmp = i * (x * ((j * y1) - (y * c)));
	} else if (z <= 2.8e+19) {
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	} else if (z <= 9.2e+70) {
		tmp = t_1;
	} else {
		tmp = ((b * y0) - (i * y1)) * (z * k);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = b * (y4 * ((t * j) - (y * k)))
	tmp = 0
	if z <= -3.6e+134:
		tmp = i * (z * ((t * c) - (k * y1)))
	elif z <= -1.05e-6:
		tmp = t_1
	elif z <= 1.7e-217:
		tmp = c * (y2 * ((x * y0) - (t * y4)))
	elif z <= 6.2e-73:
		tmp = i * (x * ((j * y1) - (y * c)))
	elif z <= 2.8e+19:
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)))
	elif z <= 9.2e+70:
		tmp = t_1
	else:
		tmp = ((b * y0) - (i * y1)) * (z * k)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(b * Float64(y4 * Float64(Float64(t * j) - Float64(y * k))))
	tmp = 0.0
	if (z <= -3.6e+134)
		tmp = Float64(i * Float64(z * Float64(Float64(t * c) - Float64(k * y1))));
	elseif (z <= -1.05e-6)
		tmp = t_1;
	elseif (z <= 1.7e-217)
		tmp = Float64(c * Float64(y2 * Float64(Float64(x * y0) - Float64(t * y4))));
	elseif (z <= 6.2e-73)
		tmp = Float64(i * Float64(x * Float64(Float64(j * y1) - Float64(y * c))));
	elseif (z <= 2.8e+19)
		tmp = Float64(j * Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4))));
	elseif (z <= 9.2e+70)
		tmp = t_1;
	else
		tmp = Float64(Float64(Float64(b * y0) - Float64(i * y1)) * Float64(z * k));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = b * (y4 * ((t * j) - (y * k)));
	tmp = 0.0;
	if (z <= -3.6e+134)
		tmp = i * (z * ((t * c) - (k * y1)));
	elseif (z <= -1.05e-6)
		tmp = t_1;
	elseif (z <= 1.7e-217)
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	elseif (z <= 6.2e-73)
		tmp = i * (x * ((j * y1) - (y * c)));
	elseif (z <= 2.8e+19)
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	elseif (z <= 9.2e+70)
		tmp = t_1;
	else
		tmp = ((b * y0) - (i * y1)) * (z * k);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(b * N[(y4 * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -3.6e+134], N[(i * N[(z * N[(N[(t * c), $MachinePrecision] - N[(k * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -1.05e-6], t$95$1, If[LessEqual[z, 1.7e-217], N[(c * N[(y2 * N[(N[(x * y0), $MachinePrecision] - N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 6.2e-73], N[(i * N[(x * N[(N[(j * y1), $MachinePrecision] - N[(y * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 2.8e+19], N[(j * N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 9.2e+70], t$95$1, N[(N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision] * N[(z * k), $MachinePrecision]), $MachinePrecision]]]]]]]]

Derivation

1. Split input into 6 regimes

2. if z < -3.59999999999999988e134

   1. Initial program 26.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 39.6%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in z around -inf 50.6%

      \[\leadsto \color{blue}{i \cdot \left(z \cdot \left(c \cdot t - k \cdot y1\right)\right)} \]

   if -3.59999999999999988e134 < z < -1.0499999999999999e-6 or 2.8e19 < z < 9.19999999999999975e70

   1. Initial program 47.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 48.0%

      \[\leadsto \left(\color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in b around inf 55.6%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} \]

   if -1.0499999999999999e-6 < z < 1.70000000000000008e-217

   1. Initial program 35.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 48.1%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in c around inf 38.2%

      \[\leadsto \color{blue}{c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)} \]

   if 1.70000000000000008e-217 < z < 6.19999999999999938e-73

   1. Initial program 38.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 45.7%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in x around inf 49.2%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 49.2%

         \[\leadsto \color{blue}{\left(-1 \cdot i\right) \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right)} \]

      2. neg-mul-1 49.2%

         \[\leadsto \color{blue}{\left(-i\right)} \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right) \]

   6. Simplified 49.2%

      \[\leadsto \color{blue}{\left(-i\right) \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right)} \]

   if 6.19999999999999938e-73 < z < 2.8e19

   1. Initial program 14.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around -inf 42.9%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 42.9%

         \[\leadsto \color{blue}{\left(-k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 42.9%

         \[\leadsto \left(-k \cdot \left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 42.9%

      \[\leadsto \color{blue}{\left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in k around 0 53.1%

      \[\leadsto \color{blue}{-1 \cdot \left(j \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 53.1%

         \[\leadsto \color{blue}{\left(-1 \cdot j\right) \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \]

      2. mul-1-neg 53.1%

         \[\leadsto \color{blue}{\left(-j\right)} \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) \]

   8. Simplified 53.1%

      \[\leadsto \color{blue}{\left(-j\right) \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \]

   if 9.19999999999999975e70 < z

   1. Initial program 22.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around -inf 41.3%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 41.3%

         \[\leadsto \color{blue}{\left(-k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 41.3%

         \[\leadsto \left(-k \cdot \left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 41.3%

      \[\leadsto \color{blue}{\left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in z around -inf 53.1%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 59.6%

         \[\leadsto \color{blue}{\left(k \cdot z\right) \cdot \left(b \cdot y0 - i \cdot y1\right)} \]

   8. Simplified 59.6%

      \[\leadsto \color{blue}{\left(k \cdot z\right) \cdot \left(b \cdot y0 - i \cdot y1\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 48.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -3.6 \cdot 10^{+134}:\\ \;\;\;\;i \cdot \left(z \cdot \left(t \cdot c - k \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq -1.05 \cdot 10^{-6}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right)\right)\\ \mathbf{elif}\;z \leq 1.7 \cdot 10^{-217}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 6.2 \cdot 10^{-73}:\\ \;\;\;\;i \cdot \left(x \cdot \left(j \cdot y1 - y \cdot c\right)\right)\\ \mathbf{elif}\;z \leq 2.8 \cdot 10^{+19}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 9.2 \cdot 10^{+70}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot y0 - i \cdot y1\right) \cdot \left(z \cdot k\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 11: 31.5% accurate, 2.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right)\right)\\ \mathbf{if}\;z \leq -1.65 \cdot 10^{+134}:\\ \;\;\;\;i \cdot \left(z \cdot \left(t \cdot c - k \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq -5.8 \cdot 10^{-6}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;z \leq 6.5 \cdot 10^{-219}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 2 \cdot 10^{-72}:\\ \;\;\;\;i \cdot \left(x \cdot \left(j \cdot y1 - y \cdot c\right)\right)\\ \mathbf{elif}\;z \leq 9 \cdot 10^{+18}:\\ \;\;\;\;\left(j \cdot y3\right) \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\\ \mathbf{elif}\;z \leq 1.35 \cdot 10^{+70}:\\ \;\;\;\;t\_1\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot y0 - i \cdot y1\right) \cdot \left(z \cdot k\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* y4 (- (* t j) (* y k))))))
   (if (<= z -1.65e+134)
     (* i (* z (- (* t c) (* k y1))))
     (if (<= z -5.8e-6)
       t_1
       (if (<= z 6.5e-219)
         (* c (* y2 (- (* x y0) (* t y4))))
         (if (<= z 2e-72)
           (* i (* x (- (* j y1) (* y c))))
           (if (<= z 9e+18)
             (* (* j y3) (- (* y0 y5) (* y1 y4)))
             (if (<= z 1.35e+70) t_1 (* (- (* b y0) (* i y1)) (* z k))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (y4 * ((t * j) - (y * k)));
	double tmp;
	if (z <= -1.65e+134) {
		tmp = i * (z * ((t * c) - (k * y1)));
	} else if (z <= -5.8e-6) {
		tmp = t_1;
	} else if (z <= 6.5e-219) {
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	} else if (z <= 2e-72) {
		tmp = i * (x * ((j * y1) - (y * c)));
	} else if (z <= 9e+18) {
		tmp = (j * y3) * ((y0 * y5) - (y1 * y4));
	} else if (z <= 1.35e+70) {
		tmp = t_1;
	} else {
		tmp = ((b * y0) - (i * y1)) * (z * k);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = b * (y4 * ((t * j) - (y * k)))
    if (z <= (-1.65d+134)) then
        tmp = i * (z * ((t * c) - (k * y1)))
    else if (z <= (-5.8d-6)) then
        tmp = t_1
    else if (z <= 6.5d-219) then
        tmp = c * (y2 * ((x * y0) - (t * y4)))
    else if (z <= 2d-72) then
        tmp = i * (x * ((j * y1) - (y * c)))
    else if (z <= 9d+18) then
        tmp = (j * y3) * ((y0 * y5) - (y1 * y4))
    else if (z <= 1.35d+70) then
        tmp = t_1
    else
        tmp = ((b * y0) - (i * y1)) * (z * k)
    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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (y4 * ((t * j) - (y * k)));
	double tmp;
	if (z <= -1.65e+134) {
		tmp = i * (z * ((t * c) - (k * y1)));
	} else if (z <= -5.8e-6) {
		tmp = t_1;
	} else if (z <= 6.5e-219) {
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	} else if (z <= 2e-72) {
		tmp = i * (x * ((j * y1) - (y * c)));
	} else if (z <= 9e+18) {
		tmp = (j * y3) * ((y0 * y5) - (y1 * y4));
	} else if (z <= 1.35e+70) {
		tmp = t_1;
	} else {
		tmp = ((b * y0) - (i * y1)) * (z * k);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = b * (y4 * ((t * j) - (y * k)))
	tmp = 0
	if z <= -1.65e+134:
		tmp = i * (z * ((t * c) - (k * y1)))
	elif z <= -5.8e-6:
		tmp = t_1
	elif z <= 6.5e-219:
		tmp = c * (y2 * ((x * y0) - (t * y4)))
	elif z <= 2e-72:
		tmp = i * (x * ((j * y1) - (y * c)))
	elif z <= 9e+18:
		tmp = (j * y3) * ((y0 * y5) - (y1 * y4))
	elif z <= 1.35e+70:
		tmp = t_1
	else:
		tmp = ((b * y0) - (i * y1)) * (z * k)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(b * Float64(y4 * Float64(Float64(t * j) - Float64(y * k))))
	tmp = 0.0
	if (z <= -1.65e+134)
		tmp = Float64(i * Float64(z * Float64(Float64(t * c) - Float64(k * y1))));
	elseif (z <= -5.8e-6)
		tmp = t_1;
	elseif (z <= 6.5e-219)
		tmp = Float64(c * Float64(y2 * Float64(Float64(x * y0) - Float64(t * y4))));
	elseif (z <= 2e-72)
		tmp = Float64(i * Float64(x * Float64(Float64(j * y1) - Float64(y * c))));
	elseif (z <= 9e+18)
		tmp = Float64(Float64(j * y3) * Float64(Float64(y0 * y5) - Float64(y1 * y4)));
	elseif (z <= 1.35e+70)
		tmp = t_1;
	else
		tmp = Float64(Float64(Float64(b * y0) - Float64(i * y1)) * Float64(z * k));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = b * (y4 * ((t * j) - (y * k)));
	tmp = 0.0;
	if (z <= -1.65e+134)
		tmp = i * (z * ((t * c) - (k * y1)));
	elseif (z <= -5.8e-6)
		tmp = t_1;
	elseif (z <= 6.5e-219)
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	elseif (z <= 2e-72)
		tmp = i * (x * ((j * y1) - (y * c)));
	elseif (z <= 9e+18)
		tmp = (j * y3) * ((y0 * y5) - (y1 * y4));
	elseif (z <= 1.35e+70)
		tmp = t_1;
	else
		tmp = ((b * y0) - (i * y1)) * (z * k);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(b * N[(y4 * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -1.65e+134], N[(i * N[(z * N[(N[(t * c), $MachinePrecision] - N[(k * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -5.8e-6], t$95$1, If[LessEqual[z, 6.5e-219], N[(c * N[(y2 * N[(N[(x * y0), $MachinePrecision] - N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 2e-72], N[(i * N[(x * N[(N[(j * y1), $MachinePrecision] - N[(y * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 9e+18], N[(N[(j * y3), $MachinePrecision] * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.35e+70], t$95$1, N[(N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision] * N[(z * k), $MachinePrecision]), $MachinePrecision]]]]]]]]

Derivation

1. Split input into 6 regimes

2. if z < -1.65e134

   1. Initial program 26.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 39.6%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in z around -inf 50.6%

      \[\leadsto \color{blue}{i \cdot \left(z \cdot \left(c \cdot t - k \cdot y1\right)\right)} \]

   if -1.65e134 < z < -5.8000000000000004e-6 or 9e18 < z < 1.35e70

   1. Initial program 47.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 48.0%

      \[\leadsto \left(\color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in b around inf 55.6%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} \]

   if -5.8000000000000004e-6 < z < 6.49999999999999958e-219

   1. Initial program 35.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 48.1%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in c around inf 38.2%

      \[\leadsto \color{blue}{c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)} \]

   if 6.49999999999999958e-219 < z < 1.9999999999999999e-72

   1. Initial program 38.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 45.7%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in x around inf 49.2%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 49.2%

         \[\leadsto \color{blue}{\left(-1 \cdot i\right) \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right)} \]

      2. neg-mul-1 49.2%

         \[\leadsto \color{blue}{\left(-i\right)} \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right) \]

   6. Simplified 49.2%

      \[\leadsto \color{blue}{\left(-i\right) \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right)} \]

   if 1.9999999999999999e-72 < z < 9e18

   1. Initial program 14.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around -inf 42.9%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 42.9%

         \[\leadsto \color{blue}{\left(-k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 42.9%

         \[\leadsto \left(-k \cdot \left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 42.9%

      \[\leadsto \color{blue}{\left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in y1 around inf 47.7%

      \[\leadsto \left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - \color{blue}{y1 \cdot \left(-1 \cdot \left(i \cdot z\right) + \frac{b \cdot \left(y0 \cdot z\right)}{y1}\right)}\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   7. Taylor expanded in k around 0 53.1%

      \[\leadsto \color{blue}{-1 \cdot \left(j \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} \]
   8. Step-by-step derivation

      1. mul-1-neg 53.1%

         \[\leadsto \color{blue}{-j \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \]

      2. associate-*r* 48.2%

         \[\leadsto -\color{blue}{\left(j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)} \]

      3. *-commutative 48.2%

         \[\leadsto -\color{blue}{\left(y3 \cdot j\right)} \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) \]

   9. Simplified 48.2%

      \[\leadsto \color{blue}{-\left(y3 \cdot j\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)} \]

   if 1.35e70 < z

   1. Initial program 22.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around -inf 41.3%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 41.3%

         \[\leadsto \color{blue}{\left(-k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 41.3%

         \[\leadsto \left(-k \cdot \left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 41.3%

      \[\leadsto \color{blue}{\left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in z around -inf 53.1%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 59.6%

         \[\leadsto \color{blue}{\left(k \cdot z\right) \cdot \left(b \cdot y0 - i \cdot y1\right)} \]

   8. Simplified 59.6%

      \[\leadsto \color{blue}{\left(k \cdot z\right) \cdot \left(b \cdot y0 - i \cdot y1\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 48.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -1.65 \cdot 10^{+134}:\\ \;\;\;\;i \cdot \left(z \cdot \left(t \cdot c - k \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq -5.8 \cdot 10^{-6}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right)\right)\\ \mathbf{elif}\;z \leq 6.5 \cdot 10^{-219}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 2 \cdot 10^{-72}:\\ \;\;\;\;i \cdot \left(x \cdot \left(j \cdot y1 - y \cdot c\right)\right)\\ \mathbf{elif}\;z \leq 9 \cdot 10^{+18}:\\ \;\;\;\;\left(j \cdot y3\right) \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\\ \mathbf{elif}\;z \leq 1.35 \cdot 10^{+70}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot y0 - i \cdot y1\right) \cdot \left(z \cdot k\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 12: 39.0% accurate, 2.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := k \cdot \left(y1 \cdot \left(z \cdot \left(\frac{b \cdot y0}{y1} - i\right)\right)\right)\\ t_2 := y1 \cdot y4 - y0 \cdot y5\\ \mathbf{if}\;z \leq -2.6 \cdot 10^{-7}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;z \leq 2.75 \cdot 10^{-217}:\\ \;\;\;\;y2 \cdot \left(\left(k \cdot t\_2 + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 6.2 \cdot 10^{-79}:\\ \;\;\;\;i \cdot \left(x \cdot \left(j \cdot y1 - y \cdot c\right)\right)\\ \mathbf{elif}\;z \leq 2.3 \cdot 10^{+19}:\\ \;\;\;\;\left(k \cdot y2 - j \cdot y3\right) \cdot t\_2\\ \mathbf{elif}\;z \leq 5 \cdot 10^{+70}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* k (* y1 (* z (- (/ (* b y0) y1) i)))))
        (t_2 (- (* y1 y4) (* y0 y5))))
   (if (<= z -2.6e-7)
     t_1
     (if (<= z 2.75e-217)
       (*
        y2
        (+
         (+ (* k t_2) (* x (- (* c y0) (* a y1))))
         (* t (- (* a y5) (* c y4)))))
       (if (<= z 6.2e-79)
         (* i (* x (- (* j y1) (* y c))))
         (if (<= z 2.3e+19)
           (* (- (* k y2) (* j y3)) t_2)
           (if (<= z 5e+70) (* b (* y4 (- (* t j) (* y k)))) t_1)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = k * (y1 * (z * (((b * y0) / y1) - i)));
	double t_2 = (y1 * y4) - (y0 * y5);
	double tmp;
	if (z <= -2.6e-7) {
		tmp = t_1;
	} else if (z <= 2.75e-217) {
		tmp = y2 * (((k * t_2) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))));
	} else if (z <= 6.2e-79) {
		tmp = i * (x * ((j * y1) - (y * c)));
	} else if (z <= 2.3e+19) {
		tmp = ((k * y2) - (j * y3)) * t_2;
	} else if (z <= 5e+70) {
		tmp = b * (y4 * ((t * j) - (y * k)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = k * (y1 * (z * (((b * y0) / y1) - i)))
    t_2 = (y1 * y4) - (y0 * y5)
    if (z <= (-2.6d-7)) then
        tmp = t_1
    else if (z <= 2.75d-217) then
        tmp = y2 * (((k * t_2) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))))
    else if (z <= 6.2d-79) then
        tmp = i * (x * ((j * y1) - (y * c)))
    else if (z <= 2.3d+19) then
        tmp = ((k * y2) - (j * y3)) * t_2
    else if (z <= 5d+70) then
        tmp = b * (y4 * ((t * j) - (y * k)))
    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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = k * (y1 * (z * (((b * y0) / y1) - i)));
	double t_2 = (y1 * y4) - (y0 * y5);
	double tmp;
	if (z <= -2.6e-7) {
		tmp = t_1;
	} else if (z <= 2.75e-217) {
		tmp = y2 * (((k * t_2) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))));
	} else if (z <= 6.2e-79) {
		tmp = i * (x * ((j * y1) - (y * c)));
	} else if (z <= 2.3e+19) {
		tmp = ((k * y2) - (j * y3)) * t_2;
	} else if (z <= 5e+70) {
		tmp = b * (y4 * ((t * j) - (y * k)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = k * (y1 * (z * (((b * y0) / y1) - i)))
	t_2 = (y1 * y4) - (y0 * y5)
	tmp = 0
	if z <= -2.6e-7:
		tmp = t_1
	elif z <= 2.75e-217:
		tmp = y2 * (((k * t_2) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))))
	elif z <= 6.2e-79:
		tmp = i * (x * ((j * y1) - (y * c)))
	elif z <= 2.3e+19:
		tmp = ((k * y2) - (j * y3)) * t_2
	elif z <= 5e+70:
		tmp = b * (y4 * ((t * j) - (y * k)))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(k * Float64(y1 * Float64(z * Float64(Float64(Float64(b * y0) / y1) - i))))
	t_2 = Float64(Float64(y1 * y4) - Float64(y0 * y5))
	tmp = 0.0
	if (z <= -2.6e-7)
		tmp = t_1;
	elseif (z <= 2.75e-217)
		tmp = Float64(y2 * Float64(Float64(Float64(k * t_2) + Float64(x * Float64(Float64(c * y0) - Float64(a * y1)))) + Float64(t * Float64(Float64(a * y5) - Float64(c * y4)))));
	elseif (z <= 6.2e-79)
		tmp = Float64(i * Float64(x * Float64(Float64(j * y1) - Float64(y * c))));
	elseif (z <= 2.3e+19)
		tmp = Float64(Float64(Float64(k * y2) - Float64(j * y3)) * t_2);
	elseif (z <= 5e+70)
		tmp = Float64(b * Float64(y4 * Float64(Float64(t * j) - Float64(y * k))));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = k * (y1 * (z * (((b * y0) / y1) - i)));
	t_2 = (y1 * y4) - (y0 * y5);
	tmp = 0.0;
	if (z <= -2.6e-7)
		tmp = t_1;
	elseif (z <= 2.75e-217)
		tmp = y2 * (((k * t_2) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))));
	elseif (z <= 6.2e-79)
		tmp = i * (x * ((j * y1) - (y * c)));
	elseif (z <= 2.3e+19)
		tmp = ((k * y2) - (j * y3)) * t_2;
	elseif (z <= 5e+70)
		tmp = b * (y4 * ((t * j) - (y * k)));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(k * N[(y1 * N[(z * N[(N[(N[(b * y0), $MachinePrecision] / y1), $MachinePrecision] - i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -2.6e-7], t$95$1, If[LessEqual[z, 2.75e-217], N[(y2 * N[(N[(N[(k * t$95$2), $MachinePrecision] + N[(x * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(t * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 6.2e-79], N[(i * N[(x * N[(N[(j * y1), $MachinePrecision] - N[(y * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 2.3e+19], N[(N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision] * t$95$2), $MachinePrecision], If[LessEqual[z, 5e+70], N[(b * N[(y4 * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]]

Derivation

1. Split input into 5 regimes

2. if z < -2.59999999999999999e-7 or 5.0000000000000002e70 < z

   1. Initial program 28.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around -inf 38.4%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 38.4%

         \[\leadsto \color{blue}{\left(-k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 38.4%

         \[\leadsto \left(-k \cdot \left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 38.4%

      \[\leadsto \color{blue}{\left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in y1 around inf 40.1%

      \[\leadsto \left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - \color{blue}{y1 \cdot \left(-1 \cdot \left(i \cdot z\right) + \frac{b \cdot \left(y0 \cdot z\right)}{y1}\right)}\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   7. Taylor expanded in z around inf 52.0%

      \[\leadsto \color{blue}{k \cdot \left(y1 \cdot \left(z \cdot \left(-1 \cdot i + \frac{b \cdot y0}{y1}\right)\right)\right)} \]

   if -2.59999999999999999e-7 < z < 2.74999999999999987e-217

   1. Initial program 36.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 48.7%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   if 2.74999999999999987e-217 < z < 6.1999999999999999e-79

   1. Initial program 38.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 39.5%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in x around inf 51.0%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 51.0%

         \[\leadsto \color{blue}{\left(-1 \cdot i\right) \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right)} \]

      2. neg-mul-1 51.0%

         \[\leadsto \color{blue}{\left(-i\right)} \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right) \]

   6. Simplified 51.0%

      \[\leadsto \color{blue}{\left(-i\right) \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right)} \]

   if 6.1999999999999999e-79 < z < 2.3e19

   1. Initial program 16.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 45.8%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in i around 0 59.0%

      \[\leadsto \color{blue}{\left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)} \]

   if 2.3e19 < z < 5.0000000000000002e70

   1. Initial program 66.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 58.4%

      \[\leadsto \left(\color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in b around inf 75.2%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 52.6%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -2.6 \cdot 10^{-7}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(z \cdot \left(\frac{b \cdot y0}{y1} - i\right)\right)\right)\\ \mathbf{elif}\;z \leq 2.75 \cdot 10^{-217}:\\ \;\;\;\;y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 6.2 \cdot 10^{-79}:\\ \;\;\;\;i \cdot \left(x \cdot \left(j \cdot y1 - y \cdot c\right)\right)\\ \mathbf{elif}\;z \leq 2.3 \cdot 10^{+19}:\\ \;\;\;\;\left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\\ \mathbf{elif}\;z \leq 5 \cdot 10^{+70}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right)\right)\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(z \cdot \left(\frac{b \cdot y0}{y1} - i\right)\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 13: 34.3% accurate, 2.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := k \cdot \left(y1 \cdot \left(z \cdot \left(\frac{b \cdot y0}{y1} - i\right)\right)\right)\\ \mathbf{if}\;z \leq -2.1 \cdot 10^{-7}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;z \leq 7 \cdot 10^{-218}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 1.3 \cdot 10^{-92}:\\ \;\;\;\;i \cdot \left(x \cdot \left(j \cdot y1 - y \cdot c\right)\right)\\ \mathbf{elif}\;z \leq 3.7 \cdot 10^{+18}:\\ \;\;\;\;y2 \cdot \left(y1 \cdot \left(k \cdot y4 - x \cdot a\right)\right)\\ \mathbf{elif}\;z \leq 4.7 \cdot 10^{+70}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* k (* y1 (* z (- (/ (* b y0) y1) i))))))
   (if (<= z -2.1e-7)
     t_1
     (if (<= z 7e-218)
       (* c (* y2 (- (* x y0) (* t y4))))
       (if (<= z 1.3e-92)
         (* i (* x (- (* j y1) (* y c))))
         (if (<= z 3.7e+18)
           (* y2 (* y1 (- (* k y4) (* x a))))
           (if (<= z 4.7e+70) (* b (* y4 (- (* t j) (* y k)))) t_1)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = k * (y1 * (z * (((b * y0) / y1) - i)));
	double tmp;
	if (z <= -2.1e-7) {
		tmp = t_1;
	} else if (z <= 7e-218) {
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	} else if (z <= 1.3e-92) {
		tmp = i * (x * ((j * y1) - (y * c)));
	} else if (z <= 3.7e+18) {
		tmp = y2 * (y1 * ((k * y4) - (x * a)));
	} else if (z <= 4.7e+70) {
		tmp = b * (y4 * ((t * j) - (y * k)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = k * (y1 * (z * (((b * y0) / y1) - i)))
    if (z <= (-2.1d-7)) then
        tmp = t_1
    else if (z <= 7d-218) then
        tmp = c * (y2 * ((x * y0) - (t * y4)))
    else if (z <= 1.3d-92) then
        tmp = i * (x * ((j * y1) - (y * c)))
    else if (z <= 3.7d+18) then
        tmp = y2 * (y1 * ((k * y4) - (x * a)))
    else if (z <= 4.7d+70) then
        tmp = b * (y4 * ((t * j) - (y * k)))
    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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = k * (y1 * (z * (((b * y0) / y1) - i)));
	double tmp;
	if (z <= -2.1e-7) {
		tmp = t_1;
	} else if (z <= 7e-218) {
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	} else if (z <= 1.3e-92) {
		tmp = i * (x * ((j * y1) - (y * c)));
	} else if (z <= 3.7e+18) {
		tmp = y2 * (y1 * ((k * y4) - (x * a)));
	} else if (z <= 4.7e+70) {
		tmp = b * (y4 * ((t * j) - (y * k)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = k * (y1 * (z * (((b * y0) / y1) - i)))
	tmp = 0
	if z <= -2.1e-7:
		tmp = t_1
	elif z <= 7e-218:
		tmp = c * (y2 * ((x * y0) - (t * y4)))
	elif z <= 1.3e-92:
		tmp = i * (x * ((j * y1) - (y * c)))
	elif z <= 3.7e+18:
		tmp = y2 * (y1 * ((k * y4) - (x * a)))
	elif z <= 4.7e+70:
		tmp = b * (y4 * ((t * j) - (y * k)))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(k * Float64(y1 * Float64(z * Float64(Float64(Float64(b * y0) / y1) - i))))
	tmp = 0.0
	if (z <= -2.1e-7)
		tmp = t_1;
	elseif (z <= 7e-218)
		tmp = Float64(c * Float64(y2 * Float64(Float64(x * y0) - Float64(t * y4))));
	elseif (z <= 1.3e-92)
		tmp = Float64(i * Float64(x * Float64(Float64(j * y1) - Float64(y * c))));
	elseif (z <= 3.7e+18)
		tmp = Float64(y2 * Float64(y1 * Float64(Float64(k * y4) - Float64(x * a))));
	elseif (z <= 4.7e+70)
		tmp = Float64(b * Float64(y4 * Float64(Float64(t * j) - Float64(y * k))));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = k * (y1 * (z * (((b * y0) / y1) - i)));
	tmp = 0.0;
	if (z <= -2.1e-7)
		tmp = t_1;
	elseif (z <= 7e-218)
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	elseif (z <= 1.3e-92)
		tmp = i * (x * ((j * y1) - (y * c)));
	elseif (z <= 3.7e+18)
		tmp = y2 * (y1 * ((k * y4) - (x * a)));
	elseif (z <= 4.7e+70)
		tmp = b * (y4 * ((t * j) - (y * k)));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(k * N[(y1 * N[(z * N[(N[(N[(b * y0), $MachinePrecision] / y1), $MachinePrecision] - i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -2.1e-7], t$95$1, If[LessEqual[z, 7e-218], N[(c * N[(y2 * N[(N[(x * y0), $MachinePrecision] - N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.3e-92], N[(i * N[(x * N[(N[(j * y1), $MachinePrecision] - N[(y * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 3.7e+18], N[(y2 * N[(y1 * N[(N[(k * y4), $MachinePrecision] - N[(x * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 4.7e+70], N[(b * N[(y4 * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]

Derivation

1. Split input into 5 regimes

2. if z < -2.1e-7 or 4.6999999999999998e70 < z

   1. Initial program 28.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around -inf 38.4%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 38.4%

         \[\leadsto \color{blue}{\left(-k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 38.4%

         \[\leadsto \left(-k \cdot \left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 38.4%

      \[\leadsto \color{blue}{\left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in y1 around inf 40.1%

      \[\leadsto \left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - \color{blue}{y1 \cdot \left(-1 \cdot \left(i \cdot z\right) + \frac{b \cdot \left(y0 \cdot z\right)}{y1}\right)}\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   7. Taylor expanded in z around inf 52.0%

      \[\leadsto \color{blue}{k \cdot \left(y1 \cdot \left(z \cdot \left(-1 \cdot i + \frac{b \cdot y0}{y1}\right)\right)\right)} \]

   if -2.1e-7 < z < 7e-218

   1. Initial program 36.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 48.7%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in c around inf 38.7%

      \[\leadsto \color{blue}{c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)} \]

   if 7e-218 < z < 1.3e-92

   1. Initial program 35.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 35.7%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in x around inf 48.9%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 48.9%

         \[\leadsto \color{blue}{\left(-1 \cdot i\right) \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right)} \]

      2. neg-mul-1 48.9%

         \[\leadsto \color{blue}{\left(-i\right)} \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right) \]

   6. Simplified 48.9%

      \[\leadsto \color{blue}{\left(-i\right) \cdot \left(x \cdot \left(c \cdot y - j \cdot y1\right)\right)} \]

   if 1.3e-92 < z < 3.7e18

   1. Initial program 22.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 41.4%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in y1 around inf 52.9%

      \[\leadsto y2 \cdot \color{blue}{\left(y1 \cdot \left(-1 \cdot \left(a \cdot x\right) + k \cdot y4\right)\right)} \]

   if 3.7e18 < z < 4.6999999999999998e70

   1. Initial program 66.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 58.4%

      \[\leadsto \left(\color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in b around inf 75.2%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 48.6%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -2.1 \cdot 10^{-7}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(z \cdot \left(\frac{b \cdot y0}{y1} - i\right)\right)\right)\\ \mathbf{elif}\;z \leq 7 \cdot 10^{-218}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 1.3 \cdot 10^{-92}:\\ \;\;\;\;i \cdot \left(x \cdot \left(j \cdot y1 - y \cdot c\right)\right)\\ \mathbf{elif}\;z \leq 3.7 \cdot 10^{+18}:\\ \;\;\;\;y2 \cdot \left(y1 \cdot \left(k \cdot y4 - x \cdot a\right)\right)\\ \mathbf{elif}\;z \leq 4.7 \cdot 10^{+70}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right)\right)\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(z \cdot \left(\frac{b \cdot y0}{y1} - i\right)\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 14: 31.5% accurate, 2.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right)\right)\\ \mathbf{if}\;z \leq -2.65 \cdot 10^{+135}:\\ \;\;\;\;i \cdot \left(z \cdot \left(t \cdot c - k \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq -56000000000000:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;z \leq -1.4 \cdot 10^{-217}:\\ \;\;\;\;\left(x \cdot j\right) \cdot \left(i \cdot y1 - b \cdot y0\right)\\ \mathbf{elif}\;z \leq 5 \cdot 10^{+20}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq 8 \cdot 10^{+70}:\\ \;\;\;\;t\_1\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot y0 - i \cdot y1\right) \cdot \left(z \cdot k\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* y4 (- (* t j) (* y k))))))
   (if (<= z -2.65e+135)
     (* i (* z (- (* t c) (* k y1))))
     (if (<= z -56000000000000.0)
       t_1
       (if (<= z -1.4e-217)
         (* (* x j) (- (* i y1) (* b y0)))
         (if (<= z 5e+20)
           (* x (* y2 (- (* c y0) (* a y1))))
           (if (<= z 8e+70) t_1 (* (- (* b y0) (* i y1)) (* z k)))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (y4 * ((t * j) - (y * k)));
	double tmp;
	if (z <= -2.65e+135) {
		tmp = i * (z * ((t * c) - (k * y1)));
	} else if (z <= -56000000000000.0) {
		tmp = t_1;
	} else if (z <= -1.4e-217) {
		tmp = (x * j) * ((i * y1) - (b * y0));
	} else if (z <= 5e+20) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (z <= 8e+70) {
		tmp = t_1;
	} else {
		tmp = ((b * y0) - (i * y1)) * (z * k);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = b * (y4 * ((t * j) - (y * k)))
    if (z <= (-2.65d+135)) then
        tmp = i * (z * ((t * c) - (k * y1)))
    else if (z <= (-56000000000000.0d0)) then
        tmp = t_1
    else if (z <= (-1.4d-217)) then
        tmp = (x * j) * ((i * y1) - (b * y0))
    else if (z <= 5d+20) then
        tmp = x * (y2 * ((c * y0) - (a * y1)))
    else if (z <= 8d+70) then
        tmp = t_1
    else
        tmp = ((b * y0) - (i * y1)) * (z * k)
    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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (y4 * ((t * j) - (y * k)));
	double tmp;
	if (z <= -2.65e+135) {
		tmp = i * (z * ((t * c) - (k * y1)));
	} else if (z <= -56000000000000.0) {
		tmp = t_1;
	} else if (z <= -1.4e-217) {
		tmp = (x * j) * ((i * y1) - (b * y0));
	} else if (z <= 5e+20) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (z <= 8e+70) {
		tmp = t_1;
	} else {
		tmp = ((b * y0) - (i * y1)) * (z * k);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = b * (y4 * ((t * j) - (y * k)))
	tmp = 0
	if z <= -2.65e+135:
		tmp = i * (z * ((t * c) - (k * y1)))
	elif z <= -56000000000000.0:
		tmp = t_1
	elif z <= -1.4e-217:
		tmp = (x * j) * ((i * y1) - (b * y0))
	elif z <= 5e+20:
		tmp = x * (y2 * ((c * y0) - (a * y1)))
	elif z <= 8e+70:
		tmp = t_1
	else:
		tmp = ((b * y0) - (i * y1)) * (z * k)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(b * Float64(y4 * Float64(Float64(t * j) - Float64(y * k))))
	tmp = 0.0
	if (z <= -2.65e+135)
		tmp = Float64(i * Float64(z * Float64(Float64(t * c) - Float64(k * y1))));
	elseif (z <= -56000000000000.0)
		tmp = t_1;
	elseif (z <= -1.4e-217)
		tmp = Float64(Float64(x * j) * Float64(Float64(i * y1) - Float64(b * y0)));
	elseif (z <= 5e+20)
		tmp = Float64(x * Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))));
	elseif (z <= 8e+70)
		tmp = t_1;
	else
		tmp = Float64(Float64(Float64(b * y0) - Float64(i * y1)) * Float64(z * k));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = b * (y4 * ((t * j) - (y * k)));
	tmp = 0.0;
	if (z <= -2.65e+135)
		tmp = i * (z * ((t * c) - (k * y1)));
	elseif (z <= -56000000000000.0)
		tmp = t_1;
	elseif (z <= -1.4e-217)
		tmp = (x * j) * ((i * y1) - (b * y0));
	elseif (z <= 5e+20)
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	elseif (z <= 8e+70)
		tmp = t_1;
	else
		tmp = ((b * y0) - (i * y1)) * (z * k);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(b * N[(y4 * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -2.65e+135], N[(i * N[(z * N[(N[(t * c), $MachinePrecision] - N[(k * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -56000000000000.0], t$95$1, If[LessEqual[z, -1.4e-217], N[(N[(x * j), $MachinePrecision] * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 5e+20], N[(x * N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 8e+70], t$95$1, N[(N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision] * N[(z * k), $MachinePrecision]), $MachinePrecision]]]]]]]

Derivation

1. Split input into 5 regimes

2. if z < -2.65000000000000008e135

   1. Initial program 26.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 39.6%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in z around -inf 50.6%

      \[\leadsto \color{blue}{i \cdot \left(z \cdot \left(c \cdot t - k \cdot y1\right)\right)} \]

   if -2.65000000000000008e135 < z < -5.6e13 or 5e20 < z < 8.00000000000000058e70

   1. Initial program 48.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 54.6%

      \[\leadsto \left(\color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in b around inf 60.5%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} \]

   if -5.6e13 < z < -1.4e-217

   1. Initial program 34.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 44.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in x around inf 47.0%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 43.3%

         \[\leadsto \color{blue}{\left(j \cdot x\right) \cdot \left(i \cdot y1 - b \cdot y0\right)} \]

   6. Simplified 43.3%

      \[\leadsto \color{blue}{\left(j \cdot x\right) \cdot \left(i \cdot y1 - b \cdot y0\right)} \]

   if -1.4e-217 < z < 5e20

   1. Initial program 32.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 41.1%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in x around inf 33.8%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   if 8.00000000000000058e70 < z

   1. Initial program 22.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around -inf 41.3%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 41.3%

         \[\leadsto \color{blue}{\left(-k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 41.3%

         \[\leadsto \left(-k \cdot \left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 41.3%

      \[\leadsto \color{blue}{\left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in z around -inf 53.1%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 59.6%

         \[\leadsto \color{blue}{\left(k \cdot z\right) \cdot \left(b \cdot y0 - i \cdot y1\right)} \]

   8. Simplified 59.6%

      \[\leadsto \color{blue}{\left(k \cdot z\right) \cdot \left(b \cdot y0 - i \cdot y1\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 46.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -2.65 \cdot 10^{+135}:\\ \;\;\;\;i \cdot \left(z \cdot \left(t \cdot c - k \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq -56000000000000:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right)\right)\\ \mathbf{elif}\;z \leq -1.4 \cdot 10^{-217}:\\ \;\;\;\;\left(x \cdot j\right) \cdot \left(i \cdot y1 - b \cdot y0\right)\\ \mathbf{elif}\;z \leq 5 \cdot 10^{+20}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq 8 \cdot 10^{+70}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot y0 - i \cdot y1\right) \cdot \left(z \cdot k\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 15: 31.4% accurate, 2.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{if}\;y0 \leq -3 \cdot 10^{+179}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;y0 \leq -20000000000:\\ \;\;\;\;y2 \cdot \left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;y0 \leq 1.04 \cdot 10^{-116}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right)\right)\\ \mathbf{elif}\;y0 \leq 1.1 \cdot 10^{+91}:\\ \;\;\;\;y2 \cdot \left(t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;y0 \leq 3.9 \cdot 10^{+227}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* j (* y0 (- (* y3 y5) (* x b))))))
   (if (<= y0 -3e+179)
     t_1
     (if (<= y0 -20000000000.0)
       (* y2 (* k (- (* y1 y4) (* y0 y5))))
       (if (<= y0 1.04e-116)
         (* b (* y4 (- (* t j) (* y k))))
         (if (<= y0 1.1e+91)
           (* y2 (* t (- (* a y5) (* c y4))))
           (if (<= y0 3.9e+227) (* x (* y2 (- (* c y0) (* a y1)))) t_1)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = j * (y0 * ((y3 * y5) - (x * b)));
	double tmp;
	if (y0 <= -3e+179) {
		tmp = t_1;
	} else if (y0 <= -20000000000.0) {
		tmp = y2 * (k * ((y1 * y4) - (y0 * y5)));
	} else if (y0 <= 1.04e-116) {
		tmp = b * (y4 * ((t * j) - (y * k)));
	} else if (y0 <= 1.1e+91) {
		tmp = y2 * (t * ((a * y5) - (c * y4)));
	} else if (y0 <= 3.9e+227) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = j * (y0 * ((y3 * y5) - (x * b)))
    if (y0 <= (-3d+179)) then
        tmp = t_1
    else if (y0 <= (-20000000000.0d0)) then
        tmp = y2 * (k * ((y1 * y4) - (y0 * y5)))
    else if (y0 <= 1.04d-116) then
        tmp = b * (y4 * ((t * j) - (y * k)))
    else if (y0 <= 1.1d+91) then
        tmp = y2 * (t * ((a * y5) - (c * y4)))
    else if (y0 <= 3.9d+227) then
        tmp = x * (y2 * ((c * y0) - (a * y1)))
    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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = j * (y0 * ((y3 * y5) - (x * b)));
	double tmp;
	if (y0 <= -3e+179) {
		tmp = t_1;
	} else if (y0 <= -20000000000.0) {
		tmp = y2 * (k * ((y1 * y4) - (y0 * y5)));
	} else if (y0 <= 1.04e-116) {
		tmp = b * (y4 * ((t * j) - (y * k)));
	} else if (y0 <= 1.1e+91) {
		tmp = y2 * (t * ((a * y5) - (c * y4)));
	} else if (y0 <= 3.9e+227) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = j * (y0 * ((y3 * y5) - (x * b)))
	tmp = 0
	if y0 <= -3e+179:
		tmp = t_1
	elif y0 <= -20000000000.0:
		tmp = y2 * (k * ((y1 * y4) - (y0 * y5)))
	elif y0 <= 1.04e-116:
		tmp = b * (y4 * ((t * j) - (y * k)))
	elif y0 <= 1.1e+91:
		tmp = y2 * (t * ((a * y5) - (c * y4)))
	elif y0 <= 3.9e+227:
		tmp = x * (y2 * ((c * y0) - (a * y1)))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(j * Float64(y0 * Float64(Float64(y3 * y5) - Float64(x * b))))
	tmp = 0.0
	if (y0 <= -3e+179)
		tmp = t_1;
	elseif (y0 <= -20000000000.0)
		tmp = Float64(y2 * Float64(k * Float64(Float64(y1 * y4) - Float64(y0 * y5))));
	elseif (y0 <= 1.04e-116)
		tmp = Float64(b * Float64(y4 * Float64(Float64(t * j) - Float64(y * k))));
	elseif (y0 <= 1.1e+91)
		tmp = Float64(y2 * Float64(t * Float64(Float64(a * y5) - Float64(c * y4))));
	elseif (y0 <= 3.9e+227)
		tmp = Float64(x * Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = j * (y0 * ((y3 * y5) - (x * b)));
	tmp = 0.0;
	if (y0 <= -3e+179)
		tmp = t_1;
	elseif (y0 <= -20000000000.0)
		tmp = y2 * (k * ((y1 * y4) - (y0 * y5)));
	elseif (y0 <= 1.04e-116)
		tmp = b * (y4 * ((t * j) - (y * k)));
	elseif (y0 <= 1.1e+91)
		tmp = y2 * (t * ((a * y5) - (c * y4)));
	elseif (y0 <= 3.9e+227)
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(j * N[(y0 * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y0, -3e+179], t$95$1, If[LessEqual[y0, -20000000000.0], N[(y2 * N[(k * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 1.04e-116], N[(b * N[(y4 * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 1.1e+91], N[(y2 * N[(t * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 3.9e+227], N[(x * N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]

Derivation

1. Split input into 5 regimes

2. if y0 < -2.9999999999999998e179 or 3.8999999999999999e227 < y0

   1. Initial program 24.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 53.3%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y0 around inf 66.3%

      \[\leadsto \color{blue}{j \cdot \left(y0 \cdot \left(y3 \cdot y5 - b \cdot x\right)\right)} \]

   if -2.9999999999999998e179 < y0 < -2e10

   1. Initial program 30.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 44.2%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in k around inf 48.7%

      \[\leadsto y2 \cdot \color{blue}{\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \]

   if -2e10 < y0 < 1.03999999999999993e-116

   1. Initial program 37.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 39.5%

      \[\leadsto \left(\color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in b around inf 36.7%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} \]

   if 1.03999999999999993e-116 < y0 < 1.1e91

   1. Initial program 23.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 37.9%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in t around inf 44.3%

      \[\leadsto y2 \cdot \color{blue}{\left(t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)} \]

   if 1.1e91 < y0 < 3.8999999999999999e227

   1. Initial program 40.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 50.6%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in x around inf 51.3%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 45.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y0 \leq -3 \cdot 10^{+179}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;y0 \leq -20000000000:\\ \;\;\;\;y2 \cdot \left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;y0 \leq 1.04 \cdot 10^{-116}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right)\right)\\ \mathbf{elif}\;y0 \leq 1.1 \cdot 10^{+91}:\\ \;\;\;\;y2 \cdot \left(t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;y0 \leq 3.9 \cdot 10^{+227}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 16: 31.2% accurate, 3.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{if}\;y0 \leq -8.8 \cdot 10^{+176}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;y0 \leq -17000000000000:\\ \;\;\;\;y2 \cdot \left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;y0 \leq 3.3 \cdot 10^{+77}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right)\right)\\ \mathbf{elif}\;y0 \leq 1.05 \cdot 10^{+249}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* j (* y0 (- (* y3 y5) (* x b))))))
   (if (<= y0 -8.8e+176)
     t_1
     (if (<= y0 -17000000000000.0)
       (* y2 (* k (- (* y1 y4) (* y0 y5))))
       (if (<= y0 3.3e+77)
         (* b (* y4 (- (* t j) (* y k))))
         (if (<= y0 1.05e+249) (* c (* y2 (- (* x y0) (* t y4)))) t_1))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = j * (y0 * ((y3 * y5) - (x * b)));
	double tmp;
	if (y0 <= -8.8e+176) {
		tmp = t_1;
	} else if (y0 <= -17000000000000.0) {
		tmp = y2 * (k * ((y1 * y4) - (y0 * y5)));
	} else if (y0 <= 3.3e+77) {
		tmp = b * (y4 * ((t * j) - (y * k)));
	} else if (y0 <= 1.05e+249) {
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = j * (y0 * ((y3 * y5) - (x * b)))
    if (y0 <= (-8.8d+176)) then
        tmp = t_1
    else if (y0 <= (-17000000000000.0d0)) then
        tmp = y2 * (k * ((y1 * y4) - (y0 * y5)))
    else if (y0 <= 3.3d+77) then
        tmp = b * (y4 * ((t * j) - (y * k)))
    else if (y0 <= 1.05d+249) then
        tmp = c * (y2 * ((x * y0) - (t * y4)))
    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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = j * (y0 * ((y3 * y5) - (x * b)));
	double tmp;
	if (y0 <= -8.8e+176) {
		tmp = t_1;
	} else if (y0 <= -17000000000000.0) {
		tmp = y2 * (k * ((y1 * y4) - (y0 * y5)));
	} else if (y0 <= 3.3e+77) {
		tmp = b * (y4 * ((t * j) - (y * k)));
	} else if (y0 <= 1.05e+249) {
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = j * (y0 * ((y3 * y5) - (x * b)))
	tmp = 0
	if y0 <= -8.8e+176:
		tmp = t_1
	elif y0 <= -17000000000000.0:
		tmp = y2 * (k * ((y1 * y4) - (y0 * y5)))
	elif y0 <= 3.3e+77:
		tmp = b * (y4 * ((t * j) - (y * k)))
	elif y0 <= 1.05e+249:
		tmp = c * (y2 * ((x * y0) - (t * y4)))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(j * Float64(y0 * Float64(Float64(y3 * y5) - Float64(x * b))))
	tmp = 0.0
	if (y0 <= -8.8e+176)
		tmp = t_1;
	elseif (y0 <= -17000000000000.0)
		tmp = Float64(y2 * Float64(k * Float64(Float64(y1 * y4) - Float64(y0 * y5))));
	elseif (y0 <= 3.3e+77)
		tmp = Float64(b * Float64(y4 * Float64(Float64(t * j) - Float64(y * k))));
	elseif (y0 <= 1.05e+249)
		tmp = Float64(c * Float64(y2 * Float64(Float64(x * y0) - Float64(t * y4))));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = j * (y0 * ((y3 * y5) - (x * b)));
	tmp = 0.0;
	if (y0 <= -8.8e+176)
		tmp = t_1;
	elseif (y0 <= -17000000000000.0)
		tmp = y2 * (k * ((y1 * y4) - (y0 * y5)));
	elseif (y0 <= 3.3e+77)
		tmp = b * (y4 * ((t * j) - (y * k)));
	elseif (y0 <= 1.05e+249)
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(j * N[(y0 * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y0, -8.8e+176], t$95$1, If[LessEqual[y0, -17000000000000.0], N[(y2 * N[(k * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 3.3e+77], N[(b * N[(y4 * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 1.05e+249], N[(c * N[(y2 * N[(N[(x * y0), $MachinePrecision] - N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]

Derivation

1. Split input into 4 regimes

2. if y0 < -8.80000000000000029e176 or 1.0499999999999999e249 < y0

   1. Initial program 22.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 53.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y0 around inf 67.2%

      \[\leadsto \color{blue}{j \cdot \left(y0 \cdot \left(y3 \cdot y5 - b \cdot x\right)\right)} \]

   if -8.80000000000000029e176 < y0 < -1.7e13

   1. Initial program 30.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 44.2%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in k around inf 48.7%

      \[\leadsto y2 \cdot \color{blue}{\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} \]

   if -1.7e13 < y0 < 3.2999999999999998e77

   1. Initial program 34.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 37.4%

      \[\leadsto \left(\color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in b around inf 35.4%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} \]

   if 3.2999999999999998e77 < y0 < 1.0499999999999999e249

   1. Initial program 35.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 50.5%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in c around inf 50.8%

      \[\leadsto \color{blue}{c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 43.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y0 \leq -8.8 \cdot 10^{+176}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;y0 \leq -17000000000000:\\ \;\;\;\;y2 \cdot \left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\\ \mathbf{elif}\;y0 \leq 3.3 \cdot 10^{+77}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right)\right)\\ \mathbf{elif}\;y0 \leq 1.05 \cdot 10^{+249}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 17: 30.2% accurate, 3.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{if}\;y0 \leq -3.4 \cdot 10^{+178}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;y0 \leq -1.04 \cdot 10^{+73}:\\ \;\;\;\;c \cdot \left(y \cdot \left(x \cdot \left(-i\right)\right)\right)\\ \mathbf{elif}\;y0 \leq 2.1 \cdot 10^{+77}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right)\right)\\ \mathbf{elif}\;y0 \leq 2.3 \cdot 10^{+247}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* j (* y0 (- (* y3 y5) (* x b))))))
   (if (<= y0 -3.4e+178)
     t_1
     (if (<= y0 -1.04e+73)
       (* c (* y (* x (- i))))
       (if (<= y0 2.1e+77)
         (* b (* y4 (- (* t j) (* y k))))
         (if (<= y0 2.3e+247) (* c (* y2 (- (* x y0) (* t y4)))) t_1))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = j * (y0 * ((y3 * y5) - (x * b)));
	double tmp;
	if (y0 <= -3.4e+178) {
		tmp = t_1;
	} else if (y0 <= -1.04e+73) {
		tmp = c * (y * (x * -i));
	} else if (y0 <= 2.1e+77) {
		tmp = b * (y4 * ((t * j) - (y * k)));
	} else if (y0 <= 2.3e+247) {
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = j * (y0 * ((y3 * y5) - (x * b)))
    if (y0 <= (-3.4d+178)) then
        tmp = t_1
    else if (y0 <= (-1.04d+73)) then
        tmp = c * (y * (x * -i))
    else if (y0 <= 2.1d+77) then
        tmp = b * (y4 * ((t * j) - (y * k)))
    else if (y0 <= 2.3d+247) then
        tmp = c * (y2 * ((x * y0) - (t * y4)))
    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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = j * (y0 * ((y3 * y5) - (x * b)));
	double tmp;
	if (y0 <= -3.4e+178) {
		tmp = t_1;
	} else if (y0 <= -1.04e+73) {
		tmp = c * (y * (x * -i));
	} else if (y0 <= 2.1e+77) {
		tmp = b * (y4 * ((t * j) - (y * k)));
	} else if (y0 <= 2.3e+247) {
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = j * (y0 * ((y3 * y5) - (x * b)))
	tmp = 0
	if y0 <= -3.4e+178:
		tmp = t_1
	elif y0 <= -1.04e+73:
		tmp = c * (y * (x * -i))
	elif y0 <= 2.1e+77:
		tmp = b * (y4 * ((t * j) - (y * k)))
	elif y0 <= 2.3e+247:
		tmp = c * (y2 * ((x * y0) - (t * y4)))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(j * Float64(y0 * Float64(Float64(y3 * y5) - Float64(x * b))))
	tmp = 0.0
	if (y0 <= -3.4e+178)
		tmp = t_1;
	elseif (y0 <= -1.04e+73)
		tmp = Float64(c * Float64(y * Float64(x * Float64(-i))));
	elseif (y0 <= 2.1e+77)
		tmp = Float64(b * Float64(y4 * Float64(Float64(t * j) - Float64(y * k))));
	elseif (y0 <= 2.3e+247)
		tmp = Float64(c * Float64(y2 * Float64(Float64(x * y0) - Float64(t * y4))));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = j * (y0 * ((y3 * y5) - (x * b)));
	tmp = 0.0;
	if (y0 <= -3.4e+178)
		tmp = t_1;
	elseif (y0 <= -1.04e+73)
		tmp = c * (y * (x * -i));
	elseif (y0 <= 2.1e+77)
		tmp = b * (y4 * ((t * j) - (y * k)));
	elseif (y0 <= 2.3e+247)
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(j * N[(y0 * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y0, -3.4e+178], t$95$1, If[LessEqual[y0, -1.04e+73], N[(c * N[(y * N[(x * (-i)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 2.1e+77], N[(b * N[(y4 * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 2.3e+247], N[(c * N[(y2 * N[(N[(x * y0), $MachinePrecision] - N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]

Derivation

1. Split input into 4 regimes

2. if y0 < -3.4000000000000003e178 or 2.29999999999999991e247 < y0

   1. Initial program 22.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in j around inf 53.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   4. Taylor expanded in y0 around inf 67.2%

      \[\leadsto \color{blue}{j \cdot \left(y0 \cdot \left(y3 \cdot y5 - b \cdot x\right)\right)} \]

   if -3.4000000000000003e178 < y0 < -1.03999999999999993e73

   1. Initial program 21.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 22.2%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in c around inf 44.1%

      \[\leadsto \color{blue}{-1 \cdot \left(c \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right)\right)} \]

   5. Taylor expanded in x around inf 44.0%

      \[\leadsto \color{blue}{-1 \cdot \left(c \cdot \left(i \cdot \left(x \cdot y\right)\right)\right)} \]
   6. Step-by-step derivation

      1. mul-1-neg 44.0%

         \[\leadsto \color{blue}{-c \cdot \left(i \cdot \left(x \cdot y\right)\right)} \]

      2. distribute-rgt-neg-in 44.0%

         \[\leadsto \color{blue}{c \cdot \left(-i \cdot \left(x \cdot y\right)\right)} \]

      3. associate-*r* 50.8%

         \[\leadsto c \cdot \left(-\color{blue}{\left(i \cdot x\right) \cdot y}\right) \]

      4. distribute-lft-neg-out 50.8%

         \[\leadsto c \cdot \color{blue}{\left(\left(-i \cdot x\right) \cdot y\right)} \]

      5. distribute-rgt-neg-in 50.8%

         \[\leadsto c \cdot \left(\color{blue}{\left(i \cdot \left(-x\right)\right)} \cdot y\right) \]

   7. Simplified 50.8%

      \[\leadsto \color{blue}{c \cdot \left(\left(i \cdot \left(-x\right)\right) \cdot y\right)} \]

   if -1.03999999999999993e73 < y0 < 2.0999999999999999e77

   1. Initial program 35.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 39.5%

      \[\leadsto \left(\color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in b around inf 35.4%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} \]

   if 2.0999999999999999e77 < y0 < 2.29999999999999991e247

   1. Initial program 35.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 50.5%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in c around inf 50.8%

      \[\leadsto \color{blue}{c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 43.1%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y0 \leq -3.4 \cdot 10^{+178}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;y0 \leq -1.04 \cdot 10^{+73}:\\ \;\;\;\;c \cdot \left(y \cdot \left(x \cdot \left(-i\right)\right)\right)\\ \mathbf{elif}\;y0 \leq 2.1 \cdot 10^{+77}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right)\right)\\ \mathbf{elif}\;y0 \leq 2.3 \cdot 10^{+247}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 18: 30.3% accurate, 3.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right)\right)\\ \mathbf{if}\;z \leq -2.85 \cdot 10^{+134}:\\ \;\;\;\;i \cdot \left(z \cdot \left(t \cdot c - k \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq -1.15 \cdot 10^{-5}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;z \leq 9.2 \cdot 10^{-127}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 8 \cdot 10^{+84}:\\ \;\;\;\;t\_1\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* y4 (- (* t j) (* y k))))))
   (if (<= z -2.85e+134)
     (* i (* z (- (* t c) (* k y1))))
     (if (<= z -1.15e-5)
       t_1
       (if (<= z 9.2e-127)
         (* c (* y2 (- (* x y0) (* t y4))))
         (if (<= z 8e+84) t_1 (* b (* k (* z y0)))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (y4 * ((t * j) - (y * k)));
	double tmp;
	if (z <= -2.85e+134) {
		tmp = i * (z * ((t * c) - (k * y1)));
	} else if (z <= -1.15e-5) {
		tmp = t_1;
	} else if (z <= 9.2e-127) {
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	} else if (z <= 8e+84) {
		tmp = t_1;
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = b * (y4 * ((t * j) - (y * k)))
    if (z <= (-2.85d+134)) then
        tmp = i * (z * ((t * c) - (k * y1)))
    else if (z <= (-1.15d-5)) then
        tmp = t_1
    else if (z <= 9.2d-127) then
        tmp = c * (y2 * ((x * y0) - (t * y4)))
    else if (z <= 8d+84) then
        tmp = t_1
    else
        tmp = b * (k * (z * y0))
    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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (y4 * ((t * j) - (y * k)));
	double tmp;
	if (z <= -2.85e+134) {
		tmp = i * (z * ((t * c) - (k * y1)));
	} else if (z <= -1.15e-5) {
		tmp = t_1;
	} else if (z <= 9.2e-127) {
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	} else if (z <= 8e+84) {
		tmp = t_1;
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = b * (y4 * ((t * j) - (y * k)))
	tmp = 0
	if z <= -2.85e+134:
		tmp = i * (z * ((t * c) - (k * y1)))
	elif z <= -1.15e-5:
		tmp = t_1
	elif z <= 9.2e-127:
		tmp = c * (y2 * ((x * y0) - (t * y4)))
	elif z <= 8e+84:
		tmp = t_1
	else:
		tmp = b * (k * (z * y0))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(b * Float64(y4 * Float64(Float64(t * j) - Float64(y * k))))
	tmp = 0.0
	if (z <= -2.85e+134)
		tmp = Float64(i * Float64(z * Float64(Float64(t * c) - Float64(k * y1))));
	elseif (z <= -1.15e-5)
		tmp = t_1;
	elseif (z <= 9.2e-127)
		tmp = Float64(c * Float64(y2 * Float64(Float64(x * y0) - Float64(t * y4))));
	elseif (z <= 8e+84)
		tmp = t_1;
	else
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = b * (y4 * ((t * j) - (y * k)));
	tmp = 0.0;
	if (z <= -2.85e+134)
		tmp = i * (z * ((t * c) - (k * y1)));
	elseif (z <= -1.15e-5)
		tmp = t_1;
	elseif (z <= 9.2e-127)
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	elseif (z <= 8e+84)
		tmp = t_1;
	else
		tmp = b * (k * (z * y0));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(b * N[(y4 * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -2.85e+134], N[(i * N[(z * N[(N[(t * c), $MachinePrecision] - N[(k * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -1.15e-5], t$95$1, If[LessEqual[z, 9.2e-127], N[(c * N[(y2 * N[(N[(x * y0), $MachinePrecision] - N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 8e+84], t$95$1, N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

1. Split input into 4 regimes

2. if z < -2.85000000000000019e134

   1. Initial program 26.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 39.6%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in z around -inf 50.6%

      \[\leadsto \color{blue}{i \cdot \left(z \cdot \left(c \cdot t - k \cdot y1\right)\right)} \]

   if -2.85000000000000019e134 < z < -1.15e-5 or 9.20000000000000075e-127 < z < 8.00000000000000046e84

   1. Initial program 36.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 44.9%

      \[\leadsto \left(\color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in b around inf 41.1%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} \]

   if -1.15e-5 < z < 9.20000000000000075e-127

   1. Initial program 36.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 44.4%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in c around inf 36.6%

      \[\leadsto \color{blue}{c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)} \]

   if 8.00000000000000046e84 < z

   1. Initial program 22.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around -inf 39.4%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 39.4%

         \[\leadsto \color{blue}{\left(-k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 39.4%

         \[\leadsto \left(-k \cdot \left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 39.4%

      \[\leadsto \color{blue}{\left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in z around -inf 49.7%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   7. Taylor expanded in b around inf 49.6%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 42.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -2.85 \cdot 10^{+134}:\\ \;\;\;\;i \cdot \left(z \cdot \left(t \cdot c - k \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq -1.15 \cdot 10^{-5}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right)\right)\\ \mathbf{elif}\;z \leq 9.2 \cdot 10^{-127}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 8 \cdot 10^{+84}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 19: 28.3% accurate, 3.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := c \cdot \left(y \cdot \left(x \cdot \left(-i\right)\right)\right)\\ \mathbf{if}\;x \leq -4 \cdot 10^{+129}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;x \leq -6.8 \cdot 10^{-17}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;x \leq 1.12 \cdot 10^{+17}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right)\right)\\ \mathbf{elif}\;x \leq 1.1 \cdot 10^{+129}:\\ \;\;\;\;i \cdot \left(k \cdot \left(z \cdot \left(-y1\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* c (* y (* x (- i))))))
   (if (<= x -4e+129)
     t_1
     (if (<= x -6.8e-17)
       (* a (* y5 (- (* t y2) (* y y3))))
       (if (<= x 1.12e+17)
         (* b (* y4 (- (* t j) (* y k))))
         (if (<= x 1.1e+129) (* i (* k (* z (- y1)))) t_1))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = c * (y * (x * -i));
	double tmp;
	if (x <= -4e+129) {
		tmp = t_1;
	} else if (x <= -6.8e-17) {
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	} else if (x <= 1.12e+17) {
		tmp = b * (y4 * ((t * j) - (y * k)));
	} else if (x <= 1.1e+129) {
		tmp = i * (k * (z * -y1));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = c * (y * (x * -i))
    if (x <= (-4d+129)) then
        tmp = t_1
    else if (x <= (-6.8d-17)) then
        tmp = a * (y5 * ((t * y2) - (y * y3)))
    else if (x <= 1.12d+17) then
        tmp = b * (y4 * ((t * j) - (y * k)))
    else if (x <= 1.1d+129) then
        tmp = i * (k * (z * -y1))
    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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = c * (y * (x * -i));
	double tmp;
	if (x <= -4e+129) {
		tmp = t_1;
	} else if (x <= -6.8e-17) {
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	} else if (x <= 1.12e+17) {
		tmp = b * (y4 * ((t * j) - (y * k)));
	} else if (x <= 1.1e+129) {
		tmp = i * (k * (z * -y1));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = c * (y * (x * -i))
	tmp = 0
	if x <= -4e+129:
		tmp = t_1
	elif x <= -6.8e-17:
		tmp = a * (y5 * ((t * y2) - (y * y3)))
	elif x <= 1.12e+17:
		tmp = b * (y4 * ((t * j) - (y * k)))
	elif x <= 1.1e+129:
		tmp = i * (k * (z * -y1))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(c * Float64(y * Float64(x * Float64(-i))))
	tmp = 0.0
	if (x <= -4e+129)
		tmp = t_1;
	elseif (x <= -6.8e-17)
		tmp = Float64(a * Float64(y5 * Float64(Float64(t * y2) - Float64(y * y3))));
	elseif (x <= 1.12e+17)
		tmp = Float64(b * Float64(y4 * Float64(Float64(t * j) - Float64(y * k))));
	elseif (x <= 1.1e+129)
		tmp = Float64(i * Float64(k * Float64(z * Float64(-y1))));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = c * (y * (x * -i));
	tmp = 0.0;
	if (x <= -4e+129)
		tmp = t_1;
	elseif (x <= -6.8e-17)
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	elseif (x <= 1.12e+17)
		tmp = b * (y4 * ((t * j) - (y * k)));
	elseif (x <= 1.1e+129)
		tmp = i * (k * (z * -y1));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(c * N[(y * N[(x * (-i)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[x, -4e+129], t$95$1, If[LessEqual[x, -6.8e-17], N[(a * N[(y5 * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 1.12e+17], N[(b * N[(y4 * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 1.1e+129], N[(i * N[(k * N[(z * (-y1)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]

Derivation

1. Split input into 4 regimes

2. if x < -4e129 or 1.1e129 < x

   1. Initial program 30.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 32.8%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in c around inf 40.0%

      \[\leadsto \color{blue}{-1 \cdot \left(c \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right)\right)} \]

   5. Taylor expanded in x around inf 41.4%

      \[\leadsto \color{blue}{-1 \cdot \left(c \cdot \left(i \cdot \left(x \cdot y\right)\right)\right)} \]
   6. Step-by-step derivation

      1. mul-1-neg 41.4%

         \[\leadsto \color{blue}{-c \cdot \left(i \cdot \left(x \cdot y\right)\right)} \]

      2. distribute-rgt-neg-in 41.4%

         \[\leadsto \color{blue}{c \cdot \left(-i \cdot \left(x \cdot y\right)\right)} \]

      3. associate-*r* 41.4%

         \[\leadsto c \cdot \left(-\color{blue}{\left(i \cdot x\right) \cdot y}\right) \]

      4. distribute-lft-neg-out 41.4%

         \[\leadsto c \cdot \color{blue}{\left(\left(-i \cdot x\right) \cdot y\right)} \]

      5. distribute-rgt-neg-in 41.4%

         \[\leadsto c \cdot \left(\color{blue}{\left(i \cdot \left(-x\right)\right)} \cdot y\right) \]

   7. Simplified 41.4%

      \[\leadsto \color{blue}{c \cdot \left(\left(i \cdot \left(-x\right)\right) \cdot y\right)} \]

   if -4e129 < x < -6.7999999999999996e-17

   1. Initial program 24.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 39.8%

      \[\leadsto \left(\color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in a around inf 40.5%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   if -6.7999999999999996e-17 < x < 1.12e17

   1. Initial program 38.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 44.7%

      \[\leadsto \left(\color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in b around inf 38.8%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} \]

   if 1.12e17 < x < 1.1e129

   1. Initial program 22.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around -inf 45.5%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 45.5%

         \[\leadsto \color{blue}{\left(-k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 45.5%

         \[\leadsto \left(-k \cdot \left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 45.5%

      \[\leadsto \color{blue}{\left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in z around -inf 31.0%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   7. Taylor expanded in b around 0 31.2%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(k \cdot \left(y1 \cdot z\right)\right)\right)} \]
   8. Step-by-step derivation

      1. associate-*r* 31.2%

         \[\leadsto \color{blue}{\left(-1 \cdot i\right) \cdot \left(k \cdot \left(y1 \cdot z\right)\right)} \]

      2. neg-mul-1 31.2%

         \[\leadsto \color{blue}{\left(-i\right)} \cdot \left(k \cdot \left(y1 \cdot z\right)\right) \]

      3. *-commutative 31.2%

         \[\leadsto \left(-i\right) \cdot \color{blue}{\left(\left(y1 \cdot z\right) \cdot k\right)} \]

      4. *-commutative 31.2%

         \[\leadsto \left(-i\right) \cdot \left(\color{blue}{\left(z \cdot y1\right)} \cdot k\right) \]

   9. Simplified 31.2%

      \[\leadsto \color{blue}{\left(-i\right) \cdot \left(\left(z \cdot y1\right) \cdot k\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 39.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -4 \cdot 10^{+129}:\\ \;\;\;\;c \cdot \left(y \cdot \left(x \cdot \left(-i\right)\right)\right)\\ \mathbf{elif}\;x \leq -6.8 \cdot 10^{-17}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;x \leq 1.12 \cdot 10^{+17}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right)\right)\\ \mathbf{elif}\;x \leq 1.1 \cdot 10^{+129}:\\ \;\;\;\;i \cdot \left(k \cdot \left(z \cdot \left(-y1\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(y \cdot \left(x \cdot \left(-i\right)\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 20: 40.2% accurate, 3.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := k \cdot \left(y1 \cdot \left(z \cdot \left(\frac{b \cdot y0}{y1} - i\right)\right)\right)\\ \mathbf{if}\;z \leq -2.4 \cdot 10^{+45}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;z \leq 3.6 \cdot 10^{+18}:\\ \;\;\;\;\left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\\ \mathbf{elif}\;z \leq 3.6 \cdot 10^{+70}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* k (* y1 (* z (- (/ (* b y0) y1) i))))))
   (if (<= z -2.4e+45)
     t_1
     (if (<= z 3.6e+18)
       (* (- (* k y2) (* j y3)) (- (* y1 y4) (* y0 y5)))
       (if (<= z 3.6e+70) (* b (* y4 (- (* t j) (* y k)))) t_1)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = k * (y1 * (z * (((b * y0) / y1) - i)));
	double tmp;
	if (z <= -2.4e+45) {
		tmp = t_1;
	} else if (z <= 3.6e+18) {
		tmp = ((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5));
	} else if (z <= 3.6e+70) {
		tmp = b * (y4 * ((t * j) - (y * k)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = k * (y1 * (z * (((b * y0) / y1) - i)))
    if (z <= (-2.4d+45)) then
        tmp = t_1
    else if (z <= 3.6d+18) then
        tmp = ((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5))
    else if (z <= 3.6d+70) then
        tmp = b * (y4 * ((t * j) - (y * k)))
    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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = k * (y1 * (z * (((b * y0) / y1) - i)));
	double tmp;
	if (z <= -2.4e+45) {
		tmp = t_1;
	} else if (z <= 3.6e+18) {
		tmp = ((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5));
	} else if (z <= 3.6e+70) {
		tmp = b * (y4 * ((t * j) - (y * k)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = k * (y1 * (z * (((b * y0) / y1) - i)))
	tmp = 0
	if z <= -2.4e+45:
		tmp = t_1
	elif z <= 3.6e+18:
		tmp = ((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5))
	elif z <= 3.6e+70:
		tmp = b * (y4 * ((t * j) - (y * k)))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(k * Float64(y1 * Float64(z * Float64(Float64(Float64(b * y0) / y1) - i))))
	tmp = 0.0
	if (z <= -2.4e+45)
		tmp = t_1;
	elseif (z <= 3.6e+18)
		tmp = Float64(Float64(Float64(k * y2) - Float64(j * y3)) * Float64(Float64(y1 * y4) - Float64(y0 * y5)));
	elseif (z <= 3.6e+70)
		tmp = Float64(b * Float64(y4 * Float64(Float64(t * j) - Float64(y * k))));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = k * (y1 * (z * (((b * y0) / y1) - i)));
	tmp = 0.0;
	if (z <= -2.4e+45)
		tmp = t_1;
	elseif (z <= 3.6e+18)
		tmp = ((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5));
	elseif (z <= 3.6e+70)
		tmp = b * (y4 * ((t * j) - (y * k)));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(k * N[(y1 * N[(z * N[(N[(N[(b * y0), $MachinePrecision] / y1), $MachinePrecision] - i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -2.4e+45], t$95$1, If[LessEqual[z, 3.6e+18], N[(N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision] * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 3.6e+70], N[(b * N[(y4 * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]

Derivation

1. Split input into 3 regimes

2. if z < -2.39999999999999989e45 or 3.6e70 < z

   1. Initial program 28.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around -inf 41.7%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 41.7%

         \[\leadsto \color{blue}{\left(-k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 41.7%

         \[\leadsto \left(-k \cdot \left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 41.7%

      \[\leadsto \color{blue}{\left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in y1 around inf 43.7%

      \[\leadsto \left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - \color{blue}{y1 \cdot \left(-1 \cdot \left(i \cdot z\right) + \frac{b \cdot \left(y0 \cdot z\right)}{y1}\right)}\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   7. Taylor expanded in z around inf 55.2%

      \[\leadsto \color{blue}{k \cdot \left(y1 \cdot \left(z \cdot \left(-1 \cdot i + \frac{b \cdot y0}{y1}\right)\right)\right)} \]

   if -2.39999999999999989e45 < z < 3.6e18

   1. Initial program 32.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 35.3%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in i around 0 41.3%

      \[\leadsto \color{blue}{\left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)} \]

   if 3.6e18 < z < 3.6e70

   1. Initial program 66.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 58.4%

      \[\leadsto \left(\color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in b around inf 75.2%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} \]
3. Recombined 3 regimes into one program.

4. Final simplification 48.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -2.4 \cdot 10^{+45}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(z \cdot \left(\frac{b \cdot y0}{y1} - i\right)\right)\right)\\ \mathbf{elif}\;z \leq 3.6 \cdot 10^{+18}:\\ \;\;\;\;\left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\\ \mathbf{elif}\;z \leq 3.6 \cdot 10^{+70}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right)\right)\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(z \cdot \left(\frac{b \cdot y0}{y1} - i\right)\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 21: 32.7% accurate, 3.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{if}\;z \leq -1.38 \cdot 10^{-18}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;z \leq 6.6 \cdot 10^{+19}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq 2.6 \cdot 10^{+70}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* k (* z (- (* b y0) (* i y1))))))
   (if (<= z -1.38e-18)
     t_1
     (if (<= z 6.6e+19)
       (* x (* y2 (- (* c y0) (* a y1))))
       (if (<= z 2.6e+70) (* b (* y4 (- (* t j) (* y k)))) t_1)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = k * (z * ((b * y0) - (i * y1)));
	double tmp;
	if (z <= -1.38e-18) {
		tmp = t_1;
	} else if (z <= 6.6e+19) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (z <= 2.6e+70) {
		tmp = b * (y4 * ((t * j) - (y * k)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = k * (z * ((b * y0) - (i * y1)))
    if (z <= (-1.38d-18)) then
        tmp = t_1
    else if (z <= 6.6d+19) then
        tmp = x * (y2 * ((c * y0) - (a * y1)))
    else if (z <= 2.6d+70) then
        tmp = b * (y4 * ((t * j) - (y * k)))
    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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = k * (z * ((b * y0) - (i * y1)));
	double tmp;
	if (z <= -1.38e-18) {
		tmp = t_1;
	} else if (z <= 6.6e+19) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (z <= 2.6e+70) {
		tmp = b * (y4 * ((t * j) - (y * k)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = k * (z * ((b * y0) - (i * y1)))
	tmp = 0
	if z <= -1.38e-18:
		tmp = t_1
	elif z <= 6.6e+19:
		tmp = x * (y2 * ((c * y0) - (a * y1)))
	elif z <= 2.6e+70:
		tmp = b * (y4 * ((t * j) - (y * k)))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(k * Float64(z * Float64(Float64(b * y0) - Float64(i * y1))))
	tmp = 0.0
	if (z <= -1.38e-18)
		tmp = t_1;
	elseif (z <= 6.6e+19)
		tmp = Float64(x * Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))));
	elseif (z <= 2.6e+70)
		tmp = Float64(b * Float64(y4 * Float64(Float64(t * j) - Float64(y * k))));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = k * (z * ((b * y0) - (i * y1)));
	tmp = 0.0;
	if (z <= -1.38e-18)
		tmp = t_1;
	elseif (z <= 6.6e+19)
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	elseif (z <= 2.6e+70)
		tmp = b * (y4 * ((t * j) - (y * k)));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(k * N[(z * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -1.38e-18], t$95$1, If[LessEqual[z, 6.6e+19], N[(x * N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 2.6e+70], N[(b * N[(y4 * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]

Derivation

1. Split input into 3 regimes

2. if z < -1.38e-18 or 2.6e70 < z

   1. Initial program 27.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around -inf 38.9%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 38.9%

         \[\leadsto \color{blue}{\left(-k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 38.9%

         \[\leadsto \left(-k \cdot \left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 38.9%

      \[\leadsto \color{blue}{\left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in z around -inf 46.5%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   if -1.38e-18 < z < 6.6e19

   1. Initial program 33.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 43.1%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in x around inf 34.6%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   if 6.6e19 < z < 2.6e70

   1. Initial program 66.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 58.4%

      \[\leadsto \left(\color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in b around inf 75.2%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} \]
3. Recombined 3 regimes into one program.

4. Final simplification 41.7%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -1.38 \cdot 10^{-18}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq 6.6 \cdot 10^{+19}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq 2.6 \cdot 10^{+70}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right)\right)\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 22: 29.1% accurate, 3.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y \leq -4.1 \cdot 10^{+221}:\\ \;\;\;\;c \cdot \left(y \cdot \left(x \cdot \left(-i\right)\right)\right)\\ \mathbf{elif}\;y \leq -1.8 \cdot 10^{-137}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right)\right)\\ \mathbf{elif}\;y \leq 4.6 \cdot 10^{+62}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(-a\right) \cdot \left(y5 \cdot \left(y \cdot y3\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= y -4.1e+221)
   (* c (* y (* x (- i))))
   (if (<= y -1.8e-137)
     (* b (* y4 (- (* t j) (* y k))))
     (if (<= y 4.6e+62)
       (* c (* y2 (- (* x y0) (* t y4))))
       (* (- a) (* y5 (* y y3)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y <= -4.1e+221) {
		tmp = c * (y * (x * -i));
	} else if (y <= -1.8e-137) {
		tmp = b * (y4 * ((t * j) - (y * k)));
	} else if (y <= 4.6e+62) {
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	} else {
		tmp = -a * (y5 * (y * y3));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (y <= (-4.1d+221)) then
        tmp = c * (y * (x * -i))
    else if (y <= (-1.8d-137)) then
        tmp = b * (y4 * ((t * j) - (y * k)))
    else if (y <= 4.6d+62) then
        tmp = c * (y2 * ((x * y0) - (t * y4)))
    else
        tmp = -a * (y5 * (y * y3))
    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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y <= -4.1e+221) {
		tmp = c * (y * (x * -i));
	} else if (y <= -1.8e-137) {
		tmp = b * (y4 * ((t * j) - (y * k)));
	} else if (y <= 4.6e+62) {
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	} else {
		tmp = -a * (y5 * (y * y3));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if y <= -4.1e+221:
		tmp = c * (y * (x * -i))
	elif y <= -1.8e-137:
		tmp = b * (y4 * ((t * j) - (y * k)))
	elif y <= 4.6e+62:
		tmp = c * (y2 * ((x * y0) - (t * y4)))
	else:
		tmp = -a * (y5 * (y * y3))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (y <= -4.1e+221)
		tmp = Float64(c * Float64(y * Float64(x * Float64(-i))));
	elseif (y <= -1.8e-137)
		tmp = Float64(b * Float64(y4 * Float64(Float64(t * j) - Float64(y * k))));
	elseif (y <= 4.6e+62)
		tmp = Float64(c * Float64(y2 * Float64(Float64(x * y0) - Float64(t * y4))));
	else
		tmp = Float64(Float64(-a) * Float64(y5 * Float64(y * y3)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (y <= -4.1e+221)
		tmp = c * (y * (x * -i));
	elseif (y <= -1.8e-137)
		tmp = b * (y4 * ((t * j) - (y * k)));
	elseif (y <= 4.6e+62)
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	else
		tmp = -a * (y5 * (y * y3));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[y, -4.1e+221], N[(c * N[(y * N[(x * (-i)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -1.8e-137], N[(b * N[(y4 * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 4.6e+62], N[(c * N[(y2 * N[(N[(x * y0), $MachinePrecision] - N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[((-a) * N[(y5 * N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]

Derivation

1. Split input into 4 regimes

2. if y < -4.09999999999999971e221

   1. Initial program 25.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 50.0%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in c around inf 75.1%

      \[\leadsto \color{blue}{-1 \cdot \left(c \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right)\right)} \]

   5. Taylor expanded in x around inf 75.1%

      \[\leadsto \color{blue}{-1 \cdot \left(c \cdot \left(i \cdot \left(x \cdot y\right)\right)\right)} \]
   6. Step-by-step derivation

      1. mul-1-neg 75.1%

         \[\leadsto \color{blue}{-c \cdot \left(i \cdot \left(x \cdot y\right)\right)} \]

      2. distribute-rgt-neg-in 75.1%

         \[\leadsto \color{blue}{c \cdot \left(-i \cdot \left(x \cdot y\right)\right)} \]

      3. associate-*r* 63.2%

         \[\leadsto c \cdot \left(-\color{blue}{\left(i \cdot x\right) \cdot y}\right) \]

      4. distribute-lft-neg-out 63.2%

         \[\leadsto c \cdot \color{blue}{\left(\left(-i \cdot x\right) \cdot y\right)} \]

      5. distribute-rgt-neg-in 63.2%

         \[\leadsto c \cdot \left(\color{blue}{\left(i \cdot \left(-x\right)\right)} \cdot y\right) \]

   7. Simplified 63.2%

      \[\leadsto \color{blue}{c \cdot \left(\left(i \cdot \left(-x\right)\right) \cdot y\right)} \]

   if -4.09999999999999971e221 < y < -1.80000000000000003e-137

   1. Initial program 39.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 43.5%

      \[\leadsto \left(\color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in b around inf 38.6%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} \]

   if -1.80000000000000003e-137 < y < 4.59999999999999968e62

   1. Initial program 36.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 44.4%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in c around inf 35.3%

      \[\leadsto \color{blue}{c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)} \]

   if 4.59999999999999968e62 < y

   1. Initial program 16.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 32.9%

      \[\leadsto \left(\color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in a around inf 47.5%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   5. Taylor expanded in t around 0 39.9%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(y \cdot \left(y3 \cdot y5\right)\right)\right)} \]
   6. Step-by-step derivation

      1. associate-*r* 39.9%

         \[\leadsto \color{blue}{\left(-1 \cdot a\right) \cdot \left(y \cdot \left(y3 \cdot y5\right)\right)} \]

      2. mul-1-neg 39.9%

         \[\leadsto \color{blue}{\left(-a\right)} \cdot \left(y \cdot \left(y3 \cdot y5\right)\right) \]

      3. associate-*r* 47.7%

         \[\leadsto \left(-a\right) \cdot \color{blue}{\left(\left(y \cdot y3\right) \cdot y5\right)} \]

   7. Simplified 47.7%

      \[\leadsto \color{blue}{\left(-a\right) \cdot \left(\left(y \cdot y3\right) \cdot y5\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 40.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y \leq -4.1 \cdot 10^{+221}:\\ \;\;\;\;c \cdot \left(y \cdot \left(x \cdot \left(-i\right)\right)\right)\\ \mathbf{elif}\;y \leq -1.8 \cdot 10^{-137}:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right)\right)\\ \mathbf{elif}\;y \leq 4.6 \cdot 10^{+62}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(-a\right) \cdot \left(y5 \cdot \left(y \cdot y3\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 23: 27.5% accurate, 4.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := c \cdot \left(y \cdot \left(x \cdot \left(-i\right)\right)\right)\\ \mathbf{if}\;x \leq -1.95 \cdot 10^{+129}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;x \leq 1.55 \cdot 10^{-43}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;x \leq 5.8 \cdot 10^{+128}:\\ \;\;\;\;k \cdot \left(z \cdot \left(i \cdot \left(-y1\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* c (* y (* x (- i))))))
   (if (<= x -1.95e+129)
     t_1
     (if (<= x 1.55e-43)
       (* a (* y5 (- (* t y2) (* y y3))))
       (if (<= x 5.8e+128) (* k (* z (* i (- y1)))) t_1)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = c * (y * (x * -i));
	double tmp;
	if (x <= -1.95e+129) {
		tmp = t_1;
	} else if (x <= 1.55e-43) {
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	} else if (x <= 5.8e+128) {
		tmp = k * (z * (i * -y1));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = c * (y * (x * -i))
    if (x <= (-1.95d+129)) then
        tmp = t_1
    else if (x <= 1.55d-43) then
        tmp = a * (y5 * ((t * y2) - (y * y3)))
    else if (x <= 5.8d+128) then
        tmp = k * (z * (i * -y1))
    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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = c * (y * (x * -i));
	double tmp;
	if (x <= -1.95e+129) {
		tmp = t_1;
	} else if (x <= 1.55e-43) {
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	} else if (x <= 5.8e+128) {
		tmp = k * (z * (i * -y1));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = c * (y * (x * -i))
	tmp = 0
	if x <= -1.95e+129:
		tmp = t_1
	elif x <= 1.55e-43:
		tmp = a * (y5 * ((t * y2) - (y * y3)))
	elif x <= 5.8e+128:
		tmp = k * (z * (i * -y1))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(c * Float64(y * Float64(x * Float64(-i))))
	tmp = 0.0
	if (x <= -1.95e+129)
		tmp = t_1;
	elseif (x <= 1.55e-43)
		tmp = Float64(a * Float64(y5 * Float64(Float64(t * y2) - Float64(y * y3))));
	elseif (x <= 5.8e+128)
		tmp = Float64(k * Float64(z * Float64(i * Float64(-y1))));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = c * (y * (x * -i));
	tmp = 0.0;
	if (x <= -1.95e+129)
		tmp = t_1;
	elseif (x <= 1.55e-43)
		tmp = a * (y5 * ((t * y2) - (y * y3)));
	elseif (x <= 5.8e+128)
		tmp = k * (z * (i * -y1));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(c * N[(y * N[(x * (-i)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[x, -1.95e+129], t$95$1, If[LessEqual[x, 1.55e-43], N[(a * N[(y5 * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 5.8e+128], N[(k * N[(z * N[(i * (-y1)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]

Derivation

1. Split input into 3 regimes

2. if x < -1.9499999999999999e129 or 5.8000000000000001e128 < x

   1. Initial program 30.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 32.8%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in c around inf 40.0%

      \[\leadsto \color{blue}{-1 \cdot \left(c \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right)\right)} \]

   5. Taylor expanded in x around inf 41.4%

      \[\leadsto \color{blue}{-1 \cdot \left(c \cdot \left(i \cdot \left(x \cdot y\right)\right)\right)} \]
   6. Step-by-step derivation

      1. mul-1-neg 41.4%

         \[\leadsto \color{blue}{-c \cdot \left(i \cdot \left(x \cdot y\right)\right)} \]

      2. distribute-rgt-neg-in 41.4%

         \[\leadsto \color{blue}{c \cdot \left(-i \cdot \left(x \cdot y\right)\right)} \]

      3. associate-*r* 41.4%

         \[\leadsto c \cdot \left(-\color{blue}{\left(i \cdot x\right) \cdot y}\right) \]

      4. distribute-lft-neg-out 41.4%

         \[\leadsto c \cdot \color{blue}{\left(\left(-i \cdot x\right) \cdot y\right)} \]

      5. distribute-rgt-neg-in 41.4%

         \[\leadsto c \cdot \left(\color{blue}{\left(i \cdot \left(-x\right)\right)} \cdot y\right) \]

   7. Simplified 41.4%

      \[\leadsto \color{blue}{c \cdot \left(\left(i \cdot \left(-x\right)\right) \cdot y\right)} \]

   if -1.9499999999999999e129 < x < 1.55e-43

   1. Initial program 34.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 42.8%

      \[\leadsto \left(\color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in a around inf 33.2%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   if 1.55e-43 < x < 5.8000000000000001e128

   1. Initial program 31.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around -inf 48.2%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 48.2%

         \[\leadsto \color{blue}{\left(-k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 48.2%

         \[\leadsto \left(-k \cdot \left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 48.2%

      \[\leadsto \color{blue}{\left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in z around -inf 30.1%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   7. Taylor expanded in b around 0 27.9%

      \[\leadsto k \cdot \left(z \cdot \color{blue}{\left(-1 \cdot \left(i \cdot y1\right)\right)}\right) \]
   8. Step-by-step derivation

      1. *-commutative 27.9%

         \[\leadsto k \cdot \left(z \cdot \left(-1 \cdot \color{blue}{\left(y1 \cdot i\right)}\right)\right) \]

      2. neg-mul-1 27.9%

         \[\leadsto k \cdot \left(z \cdot \color{blue}{\left(-y1 \cdot i\right)}\right) \]

      3. distribute-lft-neg-in 27.9%

         \[\leadsto k \cdot \left(z \cdot \color{blue}{\left(\left(-y1\right) \cdot i\right)}\right) \]

   9. Simplified 27.9%

      \[\leadsto k \cdot \left(z \cdot \color{blue}{\left(\left(-y1\right) \cdot i\right)}\right) \]
3. Recombined 3 regimes into one program.

4. Final simplification 34.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;x \leq -1.95 \cdot 10^{+129}:\\ \;\;\;\;c \cdot \left(y \cdot \left(x \cdot \left(-i\right)\right)\right)\\ \mathbf{elif}\;x \leq 1.55 \cdot 10^{-43}:\\ \;\;\;\;a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;x \leq 5.8 \cdot 10^{+128}:\\ \;\;\;\;k \cdot \left(z \cdot \left(i \cdot \left(-y1\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(y \cdot \left(x \cdot \left(-i\right)\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 24: 22.1% accurate, 4.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -6.2 \cdot 10^{-45}:\\ \;\;\;\;k \cdot \left(z \cdot \left(i \cdot \left(-y1\right)\right)\right)\\ \mathbf{elif}\;z \leq 1.65 \cdot 10^{-202}:\\ \;\;\;\;\left(-a\right) \cdot \left(y5 \cdot \left(y \cdot y3\right)\right)\\ \mathbf{elif}\;z \leq 5.6 \cdot 10^{+132}:\\ \;\;\;\;c \cdot \left(y \cdot \left(x \cdot \left(-i\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= z -6.2e-45)
   (* k (* z (* i (- y1))))
   (if (<= z 1.65e-202)
     (* (- a) (* y5 (* y y3)))
     (if (<= z 5.6e+132) (* c (* y (* x (- i)))) (* b (* k (* z y0)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -6.2e-45) {
		tmp = k * (z * (i * -y1));
	} else if (z <= 1.65e-202) {
		tmp = -a * (y5 * (y * y3));
	} else if (z <= 5.6e+132) {
		tmp = c * (y * (x * -i));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (z <= (-6.2d-45)) then
        tmp = k * (z * (i * -y1))
    else if (z <= 1.65d-202) then
        tmp = -a * (y5 * (y * y3))
    else if (z <= 5.6d+132) then
        tmp = c * (y * (x * -i))
    else
        tmp = b * (k * (z * y0))
    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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -6.2e-45) {
		tmp = k * (z * (i * -y1));
	} else if (z <= 1.65e-202) {
		tmp = -a * (y5 * (y * y3));
	} else if (z <= 5.6e+132) {
		tmp = c * (y * (x * -i));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if z <= -6.2e-45:
		tmp = k * (z * (i * -y1))
	elif z <= 1.65e-202:
		tmp = -a * (y5 * (y * y3))
	elif z <= 5.6e+132:
		tmp = c * (y * (x * -i))
	else:
		tmp = b * (k * (z * y0))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (z <= -6.2e-45)
		tmp = Float64(k * Float64(z * Float64(i * Float64(-y1))));
	elseif (z <= 1.65e-202)
		tmp = Float64(Float64(-a) * Float64(y5 * Float64(y * y3)));
	elseif (z <= 5.6e+132)
		tmp = Float64(c * Float64(y * Float64(x * Float64(-i))));
	else
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (z <= -6.2e-45)
		tmp = k * (z * (i * -y1));
	elseif (z <= 1.65e-202)
		tmp = -a * (y5 * (y * y3));
	elseif (z <= 5.6e+132)
		tmp = c * (y * (x * -i));
	else
		tmp = b * (k * (z * y0));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[z, -6.2e-45], N[(k * N[(z * N[(i * (-y1)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.65e-202], N[((-a) * N[(y5 * N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 5.6e+132], N[(c * N[(y * N[(x * (-i)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]

Derivation

1. Split input into 4 regimes

2. if z < -6.2000000000000002e-45

   1. Initial program 30.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around -inf 39.3%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 39.3%

         \[\leadsto \color{blue}{\left(-k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 39.3%

         \[\leadsto \left(-k \cdot \left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 39.3%

      \[\leadsto \color{blue}{\left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in z around -inf 38.4%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   7. Taylor expanded in b around 0 30.6%

      \[\leadsto k \cdot \left(z \cdot \color{blue}{\left(-1 \cdot \left(i \cdot y1\right)\right)}\right) \]
   8. Step-by-step derivation

      1. *-commutative 30.6%

         \[\leadsto k \cdot \left(z \cdot \left(-1 \cdot \color{blue}{\left(y1 \cdot i\right)}\right)\right) \]

      2. neg-mul-1 30.6%

         \[\leadsto k \cdot \left(z \cdot \color{blue}{\left(-y1 \cdot i\right)}\right) \]

      3. distribute-lft-neg-in 30.6%

         \[\leadsto k \cdot \left(z \cdot \color{blue}{\left(\left(-y1\right) \cdot i\right)}\right) \]

   9. Simplified 30.6%

      \[\leadsto k \cdot \left(z \cdot \color{blue}{\left(\left(-y1\right) \cdot i\right)}\right) \]

   if -6.2000000000000002e-45 < z < 1.64999999999999995e-202

   1. Initial program 36.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 43.8%

      \[\leadsto \left(\color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in a around inf 29.6%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   5. Taylor expanded in t around 0 27.3%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(y \cdot \left(y3 \cdot y5\right)\right)\right)} \]
   6. Step-by-step derivation

      1. associate-*r* 27.3%

         \[\leadsto \color{blue}{\left(-1 \cdot a\right) \cdot \left(y \cdot \left(y3 \cdot y5\right)\right)} \]

      2. mul-1-neg 27.3%

         \[\leadsto \color{blue}{\left(-a\right)} \cdot \left(y \cdot \left(y3 \cdot y5\right)\right) \]

      3. associate-*r* 29.8%

         \[\leadsto \left(-a\right) \cdot \color{blue}{\left(\left(y \cdot y3\right) \cdot y5\right)} \]

   7. Simplified 29.8%

      \[\leadsto \color{blue}{\left(-a\right) \cdot \left(\left(y \cdot y3\right) \cdot y5\right)} \]

   if 1.64999999999999995e-202 < z < 5.5999999999999998e132

   1. Initial program 34.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 41.6%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in c around inf 31.5%

      \[\leadsto \color{blue}{-1 \cdot \left(c \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right)\right)} \]

   5. Taylor expanded in x around inf 28.8%

      \[\leadsto \color{blue}{-1 \cdot \left(c \cdot \left(i \cdot \left(x \cdot y\right)\right)\right)} \]
   6. Step-by-step derivation

      1. mul-1-neg 28.8%

         \[\leadsto \color{blue}{-c \cdot \left(i \cdot \left(x \cdot y\right)\right)} \]

      2. distribute-rgt-neg-in 28.8%

         \[\leadsto \color{blue}{c \cdot \left(-i \cdot \left(x \cdot y\right)\right)} \]

      3. associate-*r* 28.8%

         \[\leadsto c \cdot \left(-\color{blue}{\left(i \cdot x\right) \cdot y}\right) \]

      4. distribute-lft-neg-out 28.8%

         \[\leadsto c \cdot \color{blue}{\left(\left(-i \cdot x\right) \cdot y\right)} \]

      5. distribute-rgt-neg-in 28.8%

         \[\leadsto c \cdot \left(\color{blue}{\left(i \cdot \left(-x\right)\right)} \cdot y\right) \]

   7. Simplified 28.8%

      \[\leadsto \color{blue}{c \cdot \left(\left(i \cdot \left(-x\right)\right) \cdot y\right)} \]

   if 5.5999999999999998e132 < z

   1. Initial program 22.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around -inf 37.8%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 37.8%

         \[\leadsto \color{blue}{\left(-k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 37.8%

         \[\leadsto \left(-k \cdot \left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 37.8%

      \[\leadsto \color{blue}{\left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in z around -inf 54.1%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   7. Taylor expanded in b around inf 56.7%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 33.1%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -6.2 \cdot 10^{-45}:\\ \;\;\;\;k \cdot \left(z \cdot \left(i \cdot \left(-y1\right)\right)\right)\\ \mathbf{elif}\;z \leq 1.65 \cdot 10^{-202}:\\ \;\;\;\;\left(-a\right) \cdot \left(y5 \cdot \left(y \cdot y3\right)\right)\\ \mathbf{elif}\;z \leq 5.6 \cdot 10^{+132}:\\ \;\;\;\;c \cdot \left(y \cdot \left(x \cdot \left(-i\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 25: 21.7% accurate, 4.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -7.4 \cdot 10^{-109}:\\ \;\;\;\;k \cdot \left(z \cdot \left(i \cdot \left(-y1\right)\right)\right)\\ \mathbf{elif}\;z \leq 3.7 \cdot 10^{-183}:\\ \;\;\;\;a \cdot \left(x \cdot \left(y2 \cdot \left(-y1\right)\right)\right)\\ \mathbf{elif}\;z \leq 1.1 \cdot 10^{+137}:\\ \;\;\;\;c \cdot \left(y \cdot \left(x \cdot \left(-i\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= z -7.4e-109)
   (* k (* z (* i (- y1))))
   (if (<= z 3.7e-183)
     (* a (* x (* y2 (- y1))))
     (if (<= z 1.1e+137) (* c (* y (* x (- i)))) (* b (* k (* z y0)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -7.4e-109) {
		tmp = k * (z * (i * -y1));
	} else if (z <= 3.7e-183) {
		tmp = a * (x * (y2 * -y1));
	} else if (z <= 1.1e+137) {
		tmp = c * (y * (x * -i));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (z <= (-7.4d-109)) then
        tmp = k * (z * (i * -y1))
    else if (z <= 3.7d-183) then
        tmp = a * (x * (y2 * -y1))
    else if (z <= 1.1d+137) then
        tmp = c * (y * (x * -i))
    else
        tmp = b * (k * (z * y0))
    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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -7.4e-109) {
		tmp = k * (z * (i * -y1));
	} else if (z <= 3.7e-183) {
		tmp = a * (x * (y2 * -y1));
	} else if (z <= 1.1e+137) {
		tmp = c * (y * (x * -i));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if z <= -7.4e-109:
		tmp = k * (z * (i * -y1))
	elif z <= 3.7e-183:
		tmp = a * (x * (y2 * -y1))
	elif z <= 1.1e+137:
		tmp = c * (y * (x * -i))
	else:
		tmp = b * (k * (z * y0))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (z <= -7.4e-109)
		tmp = Float64(k * Float64(z * Float64(i * Float64(-y1))));
	elseif (z <= 3.7e-183)
		tmp = Float64(a * Float64(x * Float64(y2 * Float64(-y1))));
	elseif (z <= 1.1e+137)
		tmp = Float64(c * Float64(y * Float64(x * Float64(-i))));
	else
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (z <= -7.4e-109)
		tmp = k * (z * (i * -y1));
	elseif (z <= 3.7e-183)
		tmp = a * (x * (y2 * -y1));
	elseif (z <= 1.1e+137)
		tmp = c * (y * (x * -i));
	else
		tmp = b * (k * (z * y0));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[z, -7.4e-109], N[(k * N[(z * N[(i * (-y1)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 3.7e-183], N[(a * N[(x * N[(y2 * (-y1)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.1e+137], N[(c * N[(y * N[(x * (-i)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]

Derivation

1. Split input into 4 regimes

2. if z < -7.39999999999999961e-109

   1. Initial program 30.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around -inf 39.0%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 39.0%

         \[\leadsto \color{blue}{\left(-k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 39.0%

         \[\leadsto \left(-k \cdot \left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 39.0%

      \[\leadsto \color{blue}{\left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in z around -inf 36.3%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   7. Taylor expanded in b around 0 28.3%

      \[\leadsto k \cdot \left(z \cdot \color{blue}{\left(-1 \cdot \left(i \cdot y1\right)\right)}\right) \]
   8. Step-by-step derivation

      1. *-commutative 28.3%

         \[\leadsto k \cdot \left(z \cdot \left(-1 \cdot \color{blue}{\left(y1 \cdot i\right)}\right)\right) \]

      2. neg-mul-1 28.3%

         \[\leadsto k \cdot \left(z \cdot \color{blue}{\left(-y1 \cdot i\right)}\right) \]

      3. distribute-lft-neg-in 28.3%

         \[\leadsto k \cdot \left(z \cdot \color{blue}{\left(\left(-y1\right) \cdot i\right)}\right) \]

   9. Simplified 28.3%

      \[\leadsto k \cdot \left(z \cdot \color{blue}{\left(\left(-y1\right) \cdot i\right)}\right) \]

   if -7.39999999999999961e-109 < z < 3.6999999999999999e-183

   1. Initial program 37.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 45.3%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in y1 around inf 31.1%

      \[\leadsto y2 \cdot \color{blue}{\left(y1 \cdot \left(-1 \cdot \left(a \cdot x\right) + k \cdot y4\right)\right)} \]

   5. Taylor expanded in a around inf 29.5%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(x \cdot \left(y1 \cdot y2\right)\right)\right)} \]
   6. Step-by-step derivation

      1. associate-*r* 29.5%

         \[\leadsto \color{blue}{\left(-1 \cdot a\right) \cdot \left(x \cdot \left(y1 \cdot y2\right)\right)} \]

      2. mul-1-neg 29.5%

         \[\leadsto \color{blue}{\left(-a\right)} \cdot \left(x \cdot \left(y1 \cdot y2\right)\right) \]

   7. Simplified 29.5%

      \[\leadsto \color{blue}{\left(-a\right) \cdot \left(x \cdot \left(y1 \cdot y2\right)\right)} \]

   if 3.6999999999999999e-183 < z < 1.10000000000000008e137

   1. Initial program 35.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 42.2%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in c around inf 31.9%

      \[\leadsto \color{blue}{-1 \cdot \left(c \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right)\right)} \]

   5. Taylor expanded in x around inf 29.2%

      \[\leadsto \color{blue}{-1 \cdot \left(c \cdot \left(i \cdot \left(x \cdot y\right)\right)\right)} \]
   6. Step-by-step derivation

      1. mul-1-neg 29.2%

         \[\leadsto \color{blue}{-c \cdot \left(i \cdot \left(x \cdot y\right)\right)} \]

      2. distribute-rgt-neg-in 29.2%

         \[\leadsto \color{blue}{c \cdot \left(-i \cdot \left(x \cdot y\right)\right)} \]

      3. associate-*r* 29.2%

         \[\leadsto c \cdot \left(-\color{blue}{\left(i \cdot x\right) \cdot y}\right) \]

      4. distribute-lft-neg-out 29.2%

         \[\leadsto c \cdot \color{blue}{\left(\left(-i \cdot x\right) \cdot y\right)} \]

      5. distribute-rgt-neg-in 29.2%

         \[\leadsto c \cdot \left(\color{blue}{\left(i \cdot \left(-x\right)\right)} \cdot y\right) \]

   7. Simplified 29.2%

      \[\leadsto \color{blue}{c \cdot \left(\left(i \cdot \left(-x\right)\right) \cdot y\right)} \]

   if 1.10000000000000008e137 < z

   1. Initial program 22.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around -inf 37.8%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 37.8%

         \[\leadsto \color{blue}{\left(-k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 37.8%

         \[\leadsto \left(-k \cdot \left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 37.8%

      \[\leadsto \color{blue}{\left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in z around -inf 54.1%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   7. Taylor expanded in b around inf 56.7%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 32.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -7.4 \cdot 10^{-109}:\\ \;\;\;\;k \cdot \left(z \cdot \left(i \cdot \left(-y1\right)\right)\right)\\ \mathbf{elif}\;z \leq 3.7 \cdot 10^{-183}:\\ \;\;\;\;a \cdot \left(x \cdot \left(y2 \cdot \left(-y1\right)\right)\right)\\ \mathbf{elif}\;z \leq 1.1 \cdot 10^{+137}:\\ \;\;\;\;c \cdot \left(y \cdot \left(x \cdot \left(-i\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 26: 21.8% accurate, 4.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -1.05 \cdot 10^{-45}:\\ \;\;\;\;k \cdot \left(z \cdot \left(i \cdot \left(-y1\right)\right)\right)\\ \mathbf{elif}\;z \leq 2.2 \cdot 10^{-194}:\\ \;\;\;\;a \cdot \left(y \cdot \left(y3 \cdot \left(-y5\right)\right)\right)\\ \mathbf{elif}\;z \leq 7 \cdot 10^{+144}:\\ \;\;\;\;c \cdot \left(y \cdot \left(x \cdot \left(-i\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= z -1.05e-45)
   (* k (* z (* i (- y1))))
   (if (<= z 2.2e-194)
     (* a (* y (* y3 (- y5))))
     (if (<= z 7e+144) (* c (* y (* x (- i)))) (* b (* k (* z y0)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -1.05e-45) {
		tmp = k * (z * (i * -y1));
	} else if (z <= 2.2e-194) {
		tmp = a * (y * (y3 * -y5));
	} else if (z <= 7e+144) {
		tmp = c * (y * (x * -i));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (z <= (-1.05d-45)) then
        tmp = k * (z * (i * -y1))
    else if (z <= 2.2d-194) then
        tmp = a * (y * (y3 * -y5))
    else if (z <= 7d+144) then
        tmp = c * (y * (x * -i))
    else
        tmp = b * (k * (z * y0))
    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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -1.05e-45) {
		tmp = k * (z * (i * -y1));
	} else if (z <= 2.2e-194) {
		tmp = a * (y * (y3 * -y5));
	} else if (z <= 7e+144) {
		tmp = c * (y * (x * -i));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if z <= -1.05e-45:
		tmp = k * (z * (i * -y1))
	elif z <= 2.2e-194:
		tmp = a * (y * (y3 * -y5))
	elif z <= 7e+144:
		tmp = c * (y * (x * -i))
	else:
		tmp = b * (k * (z * y0))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (z <= -1.05e-45)
		tmp = Float64(k * Float64(z * Float64(i * Float64(-y1))));
	elseif (z <= 2.2e-194)
		tmp = Float64(a * Float64(y * Float64(y3 * Float64(-y5))));
	elseif (z <= 7e+144)
		tmp = Float64(c * Float64(y * Float64(x * Float64(-i))));
	else
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (z <= -1.05e-45)
		tmp = k * (z * (i * -y1));
	elseif (z <= 2.2e-194)
		tmp = a * (y * (y3 * -y5));
	elseif (z <= 7e+144)
		tmp = c * (y * (x * -i));
	else
		tmp = b * (k * (z * y0));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[z, -1.05e-45], N[(k * N[(z * N[(i * (-y1)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 2.2e-194], N[(a * N[(y * N[(y3 * (-y5)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 7e+144], N[(c * N[(y * N[(x * (-i)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]

Derivation

1. Split input into 4 regimes

2. if z < -1.04999999999999998e-45

   1. Initial program 30.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around -inf 39.3%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 39.3%

         \[\leadsto \color{blue}{\left(-k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 39.3%

         \[\leadsto \left(-k \cdot \left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 39.3%

      \[\leadsto \color{blue}{\left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in z around -inf 38.4%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   7. Taylor expanded in b around 0 30.6%

      \[\leadsto k \cdot \left(z \cdot \color{blue}{\left(-1 \cdot \left(i \cdot y1\right)\right)}\right) \]
   8. Step-by-step derivation

      1. *-commutative 30.6%

         \[\leadsto k \cdot \left(z \cdot \left(-1 \cdot \color{blue}{\left(y1 \cdot i\right)}\right)\right) \]

      2. neg-mul-1 30.6%

         \[\leadsto k \cdot \left(z \cdot \color{blue}{\left(-y1 \cdot i\right)}\right) \]

      3. distribute-lft-neg-in 30.6%

         \[\leadsto k \cdot \left(z \cdot \color{blue}{\left(\left(-y1\right) \cdot i\right)}\right) \]

   9. Simplified 30.6%

      \[\leadsto k \cdot \left(z \cdot \color{blue}{\left(\left(-y1\right) \cdot i\right)}\right) \]

   if -1.04999999999999998e-45 < z < 2.2000000000000001e-194

   1. Initial program 36.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 43.8%

      \[\leadsto \left(\color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in a around inf 29.6%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   5. Taylor expanded in t around 0 27.3%

      \[\leadsto a \cdot \color{blue}{\left(-1 \cdot \left(y \cdot \left(y3 \cdot y5\right)\right)\right)} \]
   6. Step-by-step derivation

      1. associate-*r* 27.3%

         \[\leadsto a \cdot \color{blue}{\left(\left(-1 \cdot y\right) \cdot \left(y3 \cdot y5\right)\right)} \]

      2. neg-mul-1 27.3%

         \[\leadsto a \cdot \left(\color{blue}{\left(-y\right)} \cdot \left(y3 \cdot y5\right)\right) \]

   7. Simplified 27.3%

      \[\leadsto a \cdot \color{blue}{\left(\left(-y\right) \cdot \left(y3 \cdot y5\right)\right)} \]

   if 2.2000000000000001e-194 < z < 6.9999999999999996e144

   1. Initial program 34.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 41.6%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in c around inf 31.5%

      \[\leadsto \color{blue}{-1 \cdot \left(c \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right)\right)} \]

   5. Taylor expanded in x around inf 28.8%

      \[\leadsto \color{blue}{-1 \cdot \left(c \cdot \left(i \cdot \left(x \cdot y\right)\right)\right)} \]
   6. Step-by-step derivation

      1. mul-1-neg 28.8%

         \[\leadsto \color{blue}{-c \cdot \left(i \cdot \left(x \cdot y\right)\right)} \]

      2. distribute-rgt-neg-in 28.8%

         \[\leadsto \color{blue}{c \cdot \left(-i \cdot \left(x \cdot y\right)\right)} \]

      3. associate-*r* 28.8%

         \[\leadsto c \cdot \left(-\color{blue}{\left(i \cdot x\right) \cdot y}\right) \]

      4. distribute-lft-neg-out 28.8%

         \[\leadsto c \cdot \color{blue}{\left(\left(-i \cdot x\right) \cdot y\right)} \]

      5. distribute-rgt-neg-in 28.8%

         \[\leadsto c \cdot \left(\color{blue}{\left(i \cdot \left(-x\right)\right)} \cdot y\right) \]

   7. Simplified 28.8%

      \[\leadsto \color{blue}{c \cdot \left(\left(i \cdot \left(-x\right)\right) \cdot y\right)} \]

   if 6.9999999999999996e144 < z

   1. Initial program 22.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around -inf 37.8%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 37.8%

         \[\leadsto \color{blue}{\left(-k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 37.8%

         \[\leadsto \left(-k \cdot \left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 37.8%

      \[\leadsto \color{blue}{\left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in z around -inf 54.1%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   7. Taylor expanded in b around inf 56.7%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 32.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -1.05 \cdot 10^{-45}:\\ \;\;\;\;k \cdot \left(z \cdot \left(i \cdot \left(-y1\right)\right)\right)\\ \mathbf{elif}\;z \leq 2.2 \cdot 10^{-194}:\\ \;\;\;\;a \cdot \left(y \cdot \left(y3 \cdot \left(-y5\right)\right)\right)\\ \mathbf{elif}\;z \leq 7 \cdot 10^{+144}:\\ \;\;\;\;c \cdot \left(y \cdot \left(x \cdot \left(-i\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 27: 22.0% accurate, 4.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -4.8 \cdot 10^{-48}:\\ \;\;\;\;\left(c \cdot i\right) \cdot \left(z \cdot t\right)\\ \mathbf{elif}\;z \leq 1.8 \cdot 10^{-201}:\\ \;\;\;\;a \cdot \left(y \cdot \left(y3 \cdot \left(-y5\right)\right)\right)\\ \mathbf{elif}\;z \leq 1.1 \cdot 10^{+133}:\\ \;\;\;\;c \cdot \left(y \cdot \left(x \cdot \left(-i\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= z -4.8e-48)
   (* (* c i) (* z t))
   (if (<= z 1.8e-201)
     (* a (* y (* y3 (- y5))))
     (if (<= z 1.1e+133) (* c (* y (* x (- i)))) (* b (* k (* z y0)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -4.8e-48) {
		tmp = (c * i) * (z * t);
	} else if (z <= 1.8e-201) {
		tmp = a * (y * (y3 * -y5));
	} else if (z <= 1.1e+133) {
		tmp = c * (y * (x * -i));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (z <= (-4.8d-48)) then
        tmp = (c * i) * (z * t)
    else if (z <= 1.8d-201) then
        tmp = a * (y * (y3 * -y5))
    else if (z <= 1.1d+133) then
        tmp = c * (y * (x * -i))
    else
        tmp = b * (k * (z * y0))
    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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -4.8e-48) {
		tmp = (c * i) * (z * t);
	} else if (z <= 1.8e-201) {
		tmp = a * (y * (y3 * -y5));
	} else if (z <= 1.1e+133) {
		tmp = c * (y * (x * -i));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if z <= -4.8e-48:
		tmp = (c * i) * (z * t)
	elif z <= 1.8e-201:
		tmp = a * (y * (y3 * -y5))
	elif z <= 1.1e+133:
		tmp = c * (y * (x * -i))
	else:
		tmp = b * (k * (z * y0))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (z <= -4.8e-48)
		tmp = Float64(Float64(c * i) * Float64(z * t));
	elseif (z <= 1.8e-201)
		tmp = Float64(a * Float64(y * Float64(y3 * Float64(-y5))));
	elseif (z <= 1.1e+133)
		tmp = Float64(c * Float64(y * Float64(x * Float64(-i))));
	else
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (z <= -4.8e-48)
		tmp = (c * i) * (z * t);
	elseif (z <= 1.8e-201)
		tmp = a * (y * (y3 * -y5));
	elseif (z <= 1.1e+133)
		tmp = c * (y * (x * -i));
	else
		tmp = b * (k * (z * y0));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[z, -4.8e-48], N[(N[(c * i), $MachinePrecision] * N[(z * t), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.8e-201], N[(a * N[(y * N[(y3 * (-y5)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.1e+133], N[(c * N[(y * N[(x * (-i)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]

Derivation

1. Split input into 4 regimes

2. if z < -4.8e-48

   1. Initial program 31.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 35.9%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in z around -inf 39.1%

      \[\leadsto \color{blue}{i \cdot \left(z \cdot \left(c \cdot t - k \cdot y1\right)\right)} \]

   5. Taylor expanded in c around inf 27.2%

      \[\leadsto \color{blue}{c \cdot \left(i \cdot \left(t \cdot z\right)\right)} \]
   6. Step-by-step derivation

      1. associate-*r* 28.5%

         \[\leadsto \color{blue}{\left(c \cdot i\right) \cdot \left(t \cdot z\right)} \]

      2. *-commutative 28.5%

         \[\leadsto \color{blue}{\left(i \cdot c\right)} \cdot \left(t \cdot z\right) \]

      3. *-commutative 28.5%

         \[\leadsto \left(i \cdot c\right) \cdot \color{blue}{\left(z \cdot t\right)} \]

   7. Simplified 28.5%

      \[\leadsto \color{blue}{\left(i \cdot c\right) \cdot \left(z \cdot t\right)} \]

   if -4.8e-48 < z < 1.80000000000000016e-201

   1. Initial program 35.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 43.1%

      \[\leadsto \left(\color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in a around inf 30.0%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   5. Taylor expanded in t around 0 27.6%

      \[\leadsto a \cdot \color{blue}{\left(-1 \cdot \left(y \cdot \left(y3 \cdot y5\right)\right)\right)} \]
   6. Step-by-step derivation

      1. associate-*r* 27.6%

         \[\leadsto a \cdot \color{blue}{\left(\left(-1 \cdot y\right) \cdot \left(y3 \cdot y5\right)\right)} \]

      2. neg-mul-1 27.6%

         \[\leadsto a \cdot \left(\color{blue}{\left(-y\right)} \cdot \left(y3 \cdot y5\right)\right) \]

   7. Simplified 27.6%

      \[\leadsto a \cdot \color{blue}{\left(\left(-y\right) \cdot \left(y3 \cdot y5\right)\right)} \]

   if 1.80000000000000016e-201 < z < 1.1e133

   1. Initial program 34.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 41.6%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in c around inf 31.5%

      \[\leadsto \color{blue}{-1 \cdot \left(c \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right)\right)} \]

   5. Taylor expanded in x around inf 28.8%

      \[\leadsto \color{blue}{-1 \cdot \left(c \cdot \left(i \cdot \left(x \cdot y\right)\right)\right)} \]
   6. Step-by-step derivation

      1. mul-1-neg 28.8%

         \[\leadsto \color{blue}{-c \cdot \left(i \cdot \left(x \cdot y\right)\right)} \]

      2. distribute-rgt-neg-in 28.8%

         \[\leadsto \color{blue}{c \cdot \left(-i \cdot \left(x \cdot y\right)\right)} \]

      3. associate-*r* 28.8%

         \[\leadsto c \cdot \left(-\color{blue}{\left(i \cdot x\right) \cdot y}\right) \]

      4. distribute-lft-neg-out 28.8%

         \[\leadsto c \cdot \color{blue}{\left(\left(-i \cdot x\right) \cdot y\right)} \]

      5. distribute-rgt-neg-in 28.8%

         \[\leadsto c \cdot \left(\color{blue}{\left(i \cdot \left(-x\right)\right)} \cdot y\right) \]

   7. Simplified 28.8%

      \[\leadsto \color{blue}{c \cdot \left(\left(i \cdot \left(-x\right)\right) \cdot y\right)} \]

   if 1.1e133 < z

   1. Initial program 22.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around -inf 37.8%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 37.8%

         \[\leadsto \color{blue}{\left(-k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 37.8%

         \[\leadsto \left(-k \cdot \left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 37.8%

      \[\leadsto \color{blue}{\left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in z around -inf 54.1%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   7. Taylor expanded in b around inf 56.7%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 31.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -4.8 \cdot 10^{-48}:\\ \;\;\;\;\left(c \cdot i\right) \cdot \left(z \cdot t\right)\\ \mathbf{elif}\;z \leq 1.8 \cdot 10^{-201}:\\ \;\;\;\;a \cdot \left(y \cdot \left(y3 \cdot \left(-y5\right)\right)\right)\\ \mathbf{elif}\;z \leq 1.1 \cdot 10^{+133}:\\ \;\;\;\;c \cdot \left(y \cdot \left(x \cdot \left(-i\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 28: 21.4% accurate, 4.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -4.6 \cdot 10^{-51}:\\ \;\;\;\;\left(c \cdot i\right) \cdot \left(z \cdot t\right)\\ \mathbf{elif}\;z \leq 4.5 \cdot 10^{-271}:\\ \;\;\;\;a \cdot \left(y \cdot \left(y3 \cdot \left(-y5\right)\right)\right)\\ \mathbf{elif}\;z \leq 30500000000000:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= z -4.6e-51)
   (* (* c i) (* z t))
   (if (<= z 4.5e-271)
     (* a (* y (* y3 (- y5))))
     (if (<= z 30500000000000.0)
       (* k (* y1 (* y2 y4)))
       (* b (* k (* z y0)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -4.6e-51) {
		tmp = (c * i) * (z * t);
	} else if (z <= 4.5e-271) {
		tmp = a * (y * (y3 * -y5));
	} else if (z <= 30500000000000.0) {
		tmp = k * (y1 * (y2 * y4));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (z <= (-4.6d-51)) then
        tmp = (c * i) * (z * t)
    else if (z <= 4.5d-271) then
        tmp = a * (y * (y3 * -y5))
    else if (z <= 30500000000000.0d0) then
        tmp = k * (y1 * (y2 * y4))
    else
        tmp = b * (k * (z * y0))
    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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -4.6e-51) {
		tmp = (c * i) * (z * t);
	} else if (z <= 4.5e-271) {
		tmp = a * (y * (y3 * -y5));
	} else if (z <= 30500000000000.0) {
		tmp = k * (y1 * (y2 * y4));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if z <= -4.6e-51:
		tmp = (c * i) * (z * t)
	elif z <= 4.5e-271:
		tmp = a * (y * (y3 * -y5))
	elif z <= 30500000000000.0:
		tmp = k * (y1 * (y2 * y4))
	else:
		tmp = b * (k * (z * y0))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (z <= -4.6e-51)
		tmp = Float64(Float64(c * i) * Float64(z * t));
	elseif (z <= 4.5e-271)
		tmp = Float64(a * Float64(y * Float64(y3 * Float64(-y5))));
	elseif (z <= 30500000000000.0)
		tmp = Float64(k * Float64(y1 * Float64(y2 * y4)));
	else
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (z <= -4.6e-51)
		tmp = (c * i) * (z * t);
	elseif (z <= 4.5e-271)
		tmp = a * (y * (y3 * -y5));
	elseif (z <= 30500000000000.0)
		tmp = k * (y1 * (y2 * y4));
	else
		tmp = b * (k * (z * y0));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[z, -4.6e-51], N[(N[(c * i), $MachinePrecision] * N[(z * t), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 4.5e-271], N[(a * N[(y * N[(y3 * (-y5)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 30500000000000.0], N[(k * N[(y1 * N[(y2 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]

Derivation

1. Split input into 4 regimes

2. if z < -4.60000000000000004e-51

   1. Initial program 31.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 35.9%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in z around -inf 39.1%

      \[\leadsto \color{blue}{i \cdot \left(z \cdot \left(c \cdot t - k \cdot y1\right)\right)} \]

   5. Taylor expanded in c around inf 27.2%

      \[\leadsto \color{blue}{c \cdot \left(i \cdot \left(t \cdot z\right)\right)} \]
   6. Step-by-step derivation

      1. associate-*r* 28.5%

         \[\leadsto \color{blue}{\left(c \cdot i\right) \cdot \left(t \cdot z\right)} \]

      2. *-commutative 28.5%

         \[\leadsto \color{blue}{\left(i \cdot c\right)} \cdot \left(t \cdot z\right) \]

      3. *-commutative 28.5%

         \[\leadsto \left(i \cdot c\right) \cdot \color{blue}{\left(z \cdot t\right)} \]

   7. Simplified 28.5%

      \[\leadsto \color{blue}{\left(i \cdot c\right) \cdot \left(z \cdot t\right)} \]

   if -4.60000000000000004e-51 < z < 4.4999999999999998e-271

   1. Initial program 38.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 40.4%

      \[\leadsto \left(\color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in a around inf 29.8%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   5. Taylor expanded in t around 0 28.6%

      \[\leadsto a \cdot \color{blue}{\left(-1 \cdot \left(y \cdot \left(y3 \cdot y5\right)\right)\right)} \]
   6. Step-by-step derivation

      1. associate-*r* 28.6%

         \[\leadsto a \cdot \color{blue}{\left(\left(-1 \cdot y\right) \cdot \left(y3 \cdot y5\right)\right)} \]

      2. neg-mul-1 28.6%

         \[\leadsto a \cdot \left(\color{blue}{\left(-y\right)} \cdot \left(y3 \cdot y5\right)\right) \]

   7. Simplified 28.6%

      \[\leadsto a \cdot \color{blue}{\left(\left(-y\right) \cdot \left(y3 \cdot y5\right)\right)} \]

   if 4.4999999999999998e-271 < z < 3.05e13

   1. Initial program 28.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 40.0%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in y1 around inf 33.5%

      \[\leadsto y2 \cdot \color{blue}{\left(y1 \cdot \left(-1 \cdot \left(a \cdot x\right) + k \cdot y4\right)\right)} \]

   5. Taylor expanded in a around 0 24.6%

      \[\leadsto \color{blue}{k \cdot \left(y1 \cdot \left(y2 \cdot y4\right)\right)} \]

   if 3.05e13 < z

   1. Initial program 31.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around -inf 38.3%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 38.3%

         \[\leadsto \color{blue}{\left(-k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 38.3%

         \[\leadsto \left(-k \cdot \left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 38.3%

      \[\leadsto \color{blue}{\left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in z around -inf 47.4%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   7. Taylor expanded in b around inf 42.2%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 30.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -4.6 \cdot 10^{-51}:\\ \;\;\;\;\left(c \cdot i\right) \cdot \left(z \cdot t\right)\\ \mathbf{elif}\;z \leq 4.5 \cdot 10^{-271}:\\ \;\;\;\;a \cdot \left(y \cdot \left(y3 \cdot \left(-y5\right)\right)\right)\\ \mathbf{elif}\;z \leq 30500000000000:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 29: 20.7% accurate, 4.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -3.8 \cdot 10^{-191}:\\ \;\;\;\;\left(c \cdot i\right) \cdot \left(z \cdot t\right)\\ \mathbf{elif}\;z \leq 6.5 \cdot 10^{-139}:\\ \;\;\;\;\left(c \cdot y4\right) \cdot \left(t \cdot \left(-y2\right)\right)\\ \mathbf{elif}\;z \leq 1.05 \cdot 10^{+89}:\\ \;\;\;\;y2 \cdot \left(y1 \cdot \left(k \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= z -3.8e-191)
   (* (* c i) (* z t))
   (if (<= z 6.5e-139)
     (* (* c y4) (* t (- y2)))
     (if (<= z 1.05e+89) (* y2 (* y1 (* k y4))) (* b (* k (* z y0)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -3.8e-191) {
		tmp = (c * i) * (z * t);
	} else if (z <= 6.5e-139) {
		tmp = (c * y4) * (t * -y2);
	} else if (z <= 1.05e+89) {
		tmp = y2 * (y1 * (k * y4));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (z <= (-3.8d-191)) then
        tmp = (c * i) * (z * t)
    else if (z <= 6.5d-139) then
        tmp = (c * y4) * (t * -y2)
    else if (z <= 1.05d+89) then
        tmp = y2 * (y1 * (k * y4))
    else
        tmp = b * (k * (z * y0))
    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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -3.8e-191) {
		tmp = (c * i) * (z * t);
	} else if (z <= 6.5e-139) {
		tmp = (c * y4) * (t * -y2);
	} else if (z <= 1.05e+89) {
		tmp = y2 * (y1 * (k * y4));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if z <= -3.8e-191:
		tmp = (c * i) * (z * t)
	elif z <= 6.5e-139:
		tmp = (c * y4) * (t * -y2)
	elif z <= 1.05e+89:
		tmp = y2 * (y1 * (k * y4))
	else:
		tmp = b * (k * (z * y0))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (z <= -3.8e-191)
		tmp = Float64(Float64(c * i) * Float64(z * t));
	elseif (z <= 6.5e-139)
		tmp = Float64(Float64(c * y4) * Float64(t * Float64(-y2)));
	elseif (z <= 1.05e+89)
		tmp = Float64(y2 * Float64(y1 * Float64(k * y4)));
	else
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (z <= -3.8e-191)
		tmp = (c * i) * (z * t);
	elseif (z <= 6.5e-139)
		tmp = (c * y4) * (t * -y2);
	elseif (z <= 1.05e+89)
		tmp = y2 * (y1 * (k * y4));
	else
		tmp = b * (k * (z * y0));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[z, -3.8e-191], N[(N[(c * i), $MachinePrecision] * N[(z * t), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 6.5e-139], N[(N[(c * y4), $MachinePrecision] * N[(t * (-y2)), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.05e+89], N[(y2 * N[(y1 * N[(k * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]

Derivation

1. Split input into 4 regimes

2. if z < -3.7999999999999998e-191

   1. Initial program 33.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 33.8%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in z around -inf 32.6%

      \[\leadsto \color{blue}{i \cdot \left(z \cdot \left(c \cdot t - k \cdot y1\right)\right)} \]

   5. Taylor expanded in c around inf 22.9%

      \[\leadsto \color{blue}{c \cdot \left(i \cdot \left(t \cdot z\right)\right)} \]
   6. Step-by-step derivation

      1. associate-*r* 24.8%

         \[\leadsto \color{blue}{\left(c \cdot i\right) \cdot \left(t \cdot z\right)} \]

      2. *-commutative 24.8%

         \[\leadsto \color{blue}{\left(i \cdot c\right)} \cdot \left(t \cdot z\right) \]

      3. *-commutative 24.8%

         \[\leadsto \left(i \cdot c\right) \cdot \color{blue}{\left(z \cdot t\right)} \]

   7. Simplified 24.8%

      \[\leadsto \color{blue}{\left(i \cdot c\right) \cdot \left(z \cdot t\right)} \]

   if -3.7999999999999998e-191 < z < 6.5e-139

   1. Initial program 35.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 42.4%

      \[\leadsto \left(\color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in c around inf 31.7%

      \[\leadsto \color{blue}{-1 \cdot \left(c \cdot \left(y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   5. Step-by-step derivation

      1. mul-1-neg 31.7%

         \[\leadsto \color{blue}{-c \cdot \left(y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. associate-*r* 31.7%

         \[\leadsto -\color{blue}{\left(c \cdot y4\right) \cdot \left(t \cdot y2 - y \cdot y3\right)} \]

   6. Simplified 31.7%

      \[\leadsto \color{blue}{-\left(c \cdot y4\right) \cdot \left(t \cdot y2 - y \cdot y3\right)} \]

   7. Taylor expanded in t around inf 30.3%

      \[\leadsto -\left(c \cdot y4\right) \cdot \color{blue}{\left(t \cdot y2\right)} \]

   if 6.5e-139 < z < 1.04999999999999993e89

   1. Initial program 34.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 31.5%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in y1 around inf 39.9%

      \[\leadsto y2 \cdot \color{blue}{\left(y1 \cdot \left(-1 \cdot \left(a \cdot x\right) + k \cdot y4\right)\right)} \]

   5. Taylor expanded in a around 0 21.8%

      \[\leadsto y2 \cdot \color{blue}{\left(k \cdot \left(y1 \cdot y4\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 21.8%

         \[\leadsto y2 \cdot \left(k \cdot \color{blue}{\left(y4 \cdot y1\right)}\right) \]

      2. associate-*l* 23.8%

         \[\leadsto y2 \cdot \color{blue}{\left(\left(k \cdot y4\right) \cdot y1\right)} \]

      3. *-commutative 23.8%

         \[\leadsto y2 \cdot \color{blue}{\left(y1 \cdot \left(k \cdot y4\right)\right)} \]

   7. Simplified 23.8%

      \[\leadsto y2 \cdot \color{blue}{\left(y1 \cdot \left(k \cdot y4\right)\right)} \]

   if 1.04999999999999993e89 < z

   1. Initial program 22.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around -inf 37.9%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 37.9%

         \[\leadsto \color{blue}{\left(-k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 37.9%

         \[\leadsto \left(-k \cdot \left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 37.9%

      \[\leadsto \color{blue}{\left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in z around -inf 50.9%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   7. Taylor expanded in b around inf 50.8%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 30.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -3.8 \cdot 10^{-191}:\\ \;\;\;\;\left(c \cdot i\right) \cdot \left(z \cdot t\right)\\ \mathbf{elif}\;z \leq 6.5 \cdot 10^{-139}:\\ \;\;\;\;\left(c \cdot y4\right) \cdot \left(t \cdot \left(-y2\right)\right)\\ \mathbf{elif}\;z \leq 1.05 \cdot 10^{+89}:\\ \;\;\;\;y2 \cdot \left(y1 \cdot \left(k \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 30: 22.1% accurate, 4.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;t \leq -3 \cdot 10^{+47}:\\ \;\;\;\;i \cdot \left(z \cdot \left(t \cdot c\right)\right)\\ \mathbf{elif}\;t \leq -2.3 \cdot 10^{-96}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq 1.15 \cdot 10^{+60}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(i \cdot \left(z \cdot t\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= t -3e+47)
   (* i (* z (* t c)))
   (if (<= t -2.3e-96)
     (* c (* y4 (* y y3)))
     (if (<= t 1.15e+60) (* b (* k (* z y0))) (* c (* i (* z t)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (t <= -3e+47) {
		tmp = i * (z * (t * c));
	} else if (t <= -2.3e-96) {
		tmp = c * (y4 * (y * y3));
	} else if (t <= 1.15e+60) {
		tmp = b * (k * (z * y0));
	} else {
		tmp = c * (i * (z * t));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (t <= (-3d+47)) then
        tmp = i * (z * (t * c))
    else if (t <= (-2.3d-96)) then
        tmp = c * (y4 * (y * y3))
    else if (t <= 1.15d+60) then
        tmp = b * (k * (z * y0))
    else
        tmp = c * (i * (z * 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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (t <= -3e+47) {
		tmp = i * (z * (t * c));
	} else if (t <= -2.3e-96) {
		tmp = c * (y4 * (y * y3));
	} else if (t <= 1.15e+60) {
		tmp = b * (k * (z * y0));
	} else {
		tmp = c * (i * (z * t));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if t <= -3e+47:
		tmp = i * (z * (t * c))
	elif t <= -2.3e-96:
		tmp = c * (y4 * (y * y3))
	elif t <= 1.15e+60:
		tmp = b * (k * (z * y0))
	else:
		tmp = c * (i * (z * t))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (t <= -3e+47)
		tmp = Float64(i * Float64(z * Float64(t * c)));
	elseif (t <= -2.3e-96)
		tmp = Float64(c * Float64(y4 * Float64(y * y3)));
	elseif (t <= 1.15e+60)
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	else
		tmp = Float64(c * Float64(i * Float64(z * t)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (t <= -3e+47)
		tmp = i * (z * (t * c));
	elseif (t <= -2.3e-96)
		tmp = c * (y4 * (y * y3));
	elseif (t <= 1.15e+60)
		tmp = b * (k * (z * y0));
	else
		tmp = c * (i * (z * t));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[t, -3e+47], N[(i * N[(z * N[(t * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -2.3e-96], N[(c * N[(y4 * N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.15e+60], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(c * N[(i * N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]

Derivation

1. Split input into 4 regimes

2. if t < -3.0000000000000001e47

   1. Initial program 20.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 32.9%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in z around -inf 31.8%

      \[\leadsto \color{blue}{i \cdot \left(z \cdot \left(c \cdot t - k \cdot y1\right)\right)} \]

   5. Taylor expanded in c around inf 31.7%

      \[\leadsto i \cdot \left(z \cdot \color{blue}{\left(c \cdot t\right)}\right) \]

   if -3.0000000000000001e47 < t < -2.3e-96

   1. Initial program 33.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 42.7%

      \[\leadsto \left(\color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in c around inf 49.2%

      \[\leadsto \color{blue}{-1 \cdot \left(c \cdot \left(y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   5. Step-by-step derivation

      1. mul-1-neg 49.2%

         \[\leadsto \color{blue}{-c \cdot \left(y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. associate-*r* 29.3%

         \[\leadsto -\color{blue}{\left(c \cdot y4\right) \cdot \left(t \cdot y2 - y \cdot y3\right)} \]

   6. Simplified 29.3%

      \[\leadsto \color{blue}{-\left(c \cdot y4\right) \cdot \left(t \cdot y2 - y \cdot y3\right)} \]

   7. Taylor expanded in t around 0 31.5%

      \[\leadsto \color{blue}{c \cdot \left(y \cdot \left(y3 \cdot y4\right)\right)} \]
   8. Step-by-step derivation

      1. associate-*r* 37.5%

         \[\leadsto c \cdot \color{blue}{\left(\left(y \cdot y3\right) \cdot y4\right)} \]

   9. Simplified 37.5%

      \[\leadsto \color{blue}{c \cdot \left(\left(y \cdot y3\right) \cdot y4\right)} \]

   if -2.3e-96 < t < 1.15000000000000008e60

   1. Initial program 36.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around -inf 43.3%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 43.3%

         \[\leadsto \color{blue}{\left(-k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 43.3%

         \[\leadsto \left(-k \cdot \left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 43.3%

      \[\leadsto \color{blue}{\left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in z around -inf 30.0%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   7. Taylor expanded in b around inf 23.0%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]

   if 1.15000000000000008e60 < t

   1. Initial program 33.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 33.5%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in z around -inf 36.0%

      \[\leadsto \color{blue}{i \cdot \left(z \cdot \left(c \cdot t - k \cdot y1\right)\right)} \]

   5. Taylor expanded in c around inf 31.6%

      \[\leadsto \color{blue}{c \cdot \left(i \cdot \left(t \cdot z\right)\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 28.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -3 \cdot 10^{+47}:\\ \;\;\;\;i \cdot \left(z \cdot \left(t \cdot c\right)\right)\\ \mathbf{elif}\;t \leq -2.3 \cdot 10^{-96}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq 1.15 \cdot 10^{+60}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(i \cdot \left(z \cdot t\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 31: 22.1% accurate, 4.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := c \cdot \left(i \cdot \left(z \cdot t\right)\right)\\ \mathbf{if}\;t \leq -5.6 \cdot 10^{+44}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;t \leq -1.95 \cdot 10^{-95}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq 1.3 \cdot 10^{+60}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* c (* i (* z t)))))
   (if (<= t -5.6e+44)
     t_1
     (if (<= t -1.95e-95)
       (* c (* y4 (* y y3)))
       (if (<= t 1.3e+60) (* b (* k (* z y0))) t_1)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = c * (i * (z * t));
	double tmp;
	if (t <= -5.6e+44) {
		tmp = t_1;
	} else if (t <= -1.95e-95) {
		tmp = c * (y4 * (y * y3));
	} else if (t <= 1.3e+60) {
		tmp = b * (k * (z * y0));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = c * (i * (z * t))
    if (t <= (-5.6d+44)) then
        tmp = t_1
    else if (t <= (-1.95d-95)) then
        tmp = c * (y4 * (y * y3))
    else if (t <= 1.3d+60) then
        tmp = b * (k * (z * y0))
    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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = c * (i * (z * t));
	double tmp;
	if (t <= -5.6e+44) {
		tmp = t_1;
	} else if (t <= -1.95e-95) {
		tmp = c * (y4 * (y * y3));
	} else if (t <= 1.3e+60) {
		tmp = b * (k * (z * y0));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = c * (i * (z * t))
	tmp = 0
	if t <= -5.6e+44:
		tmp = t_1
	elif t <= -1.95e-95:
		tmp = c * (y4 * (y * y3))
	elif t <= 1.3e+60:
		tmp = b * (k * (z * y0))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(c * Float64(i * Float64(z * t)))
	tmp = 0.0
	if (t <= -5.6e+44)
		tmp = t_1;
	elseif (t <= -1.95e-95)
		tmp = Float64(c * Float64(y4 * Float64(y * y3)));
	elseif (t <= 1.3e+60)
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = c * (i * (z * t));
	tmp = 0.0;
	if (t <= -5.6e+44)
		tmp = t_1;
	elseif (t <= -1.95e-95)
		tmp = c * (y4 * (y * y3));
	elseif (t <= 1.3e+60)
		tmp = b * (k * (z * y0));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(c * N[(i * N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -5.6e+44], t$95$1, If[LessEqual[t, -1.95e-95], N[(c * N[(y4 * N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.3e+60], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]

Derivation

1. Split input into 3 regimes

2. if t < -5.6000000000000002e44 or 1.30000000000000004e60 < t

   1. Initial program 26.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 33.2%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in z around -inf 33.8%

      \[\leadsto \color{blue}{i \cdot \left(z \cdot \left(c \cdot t - k \cdot y1\right)\right)} \]

   5. Taylor expanded in c around inf 30.6%

      \[\leadsto \color{blue}{c \cdot \left(i \cdot \left(t \cdot z\right)\right)} \]

   if -5.6000000000000002e44 < t < -1.95e-95

   1. Initial program 33.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 42.7%

      \[\leadsto \left(\color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in c around inf 49.2%

      \[\leadsto \color{blue}{-1 \cdot \left(c \cdot \left(y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   5. Step-by-step derivation

      1. mul-1-neg 49.2%

         \[\leadsto \color{blue}{-c \cdot \left(y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. associate-*r* 29.3%

         \[\leadsto -\color{blue}{\left(c \cdot y4\right) \cdot \left(t \cdot y2 - y \cdot y3\right)} \]

   6. Simplified 29.3%

      \[\leadsto \color{blue}{-\left(c \cdot y4\right) \cdot \left(t \cdot y2 - y \cdot y3\right)} \]

   7. Taylor expanded in t around 0 31.5%

      \[\leadsto \color{blue}{c \cdot \left(y \cdot \left(y3 \cdot y4\right)\right)} \]
   8. Step-by-step derivation

      1. associate-*r* 37.5%

         \[\leadsto c \cdot \color{blue}{\left(\left(y \cdot y3\right) \cdot y4\right)} \]

   9. Simplified 37.5%

      \[\leadsto \color{blue}{c \cdot \left(\left(y \cdot y3\right) \cdot y4\right)} \]

   if -1.95e-95 < t < 1.30000000000000004e60

   1. Initial program 36.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around -inf 43.3%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 43.3%

         \[\leadsto \color{blue}{\left(-k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 43.3%

         \[\leadsto \left(-k \cdot \left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 43.3%

      \[\leadsto \color{blue}{\left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in z around -inf 30.0%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   7. Taylor expanded in b around inf 23.0%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]
3. Recombined 3 regimes into one program.

4. Final simplification 27.6%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -5.6 \cdot 10^{+44}:\\ \;\;\;\;c \cdot \left(i \cdot \left(z \cdot t\right)\right)\\ \mathbf{elif}\;t \leq -1.95 \cdot 10^{-95}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq 1.3 \cdot 10^{+60}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(i \cdot \left(z \cdot t\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 32: 22.0% accurate, 4.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := c \cdot \left(i \cdot \left(z \cdot t\right)\right)\\ \mathbf{if}\;t \leq -6.4 \cdot 10^{+46}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;t \leq -1.8 \cdot 10^{-244}:\\ \;\;\;\;c \cdot \left(y \cdot \left(y3 \cdot y4\right)\right)\\ \mathbf{elif}\;t \leq 1.46 \cdot 10^{+60}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* c (* i (* z t)))))
   (if (<= t -6.4e+46)
     t_1
     (if (<= t -1.8e-244)
       (* c (* y (* y3 y4)))
       (if (<= t 1.46e+60) (* b (* k (* z y0))) t_1)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = c * (i * (z * t));
	double tmp;
	if (t <= -6.4e+46) {
		tmp = t_1;
	} else if (t <= -1.8e-244) {
		tmp = c * (y * (y3 * y4));
	} else if (t <= 1.46e+60) {
		tmp = b * (k * (z * y0));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = c * (i * (z * t))
    if (t <= (-6.4d+46)) then
        tmp = t_1
    else if (t <= (-1.8d-244)) then
        tmp = c * (y * (y3 * y4))
    else if (t <= 1.46d+60) then
        tmp = b * (k * (z * y0))
    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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = c * (i * (z * t));
	double tmp;
	if (t <= -6.4e+46) {
		tmp = t_1;
	} else if (t <= -1.8e-244) {
		tmp = c * (y * (y3 * y4));
	} else if (t <= 1.46e+60) {
		tmp = b * (k * (z * y0));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = c * (i * (z * t))
	tmp = 0
	if t <= -6.4e+46:
		tmp = t_1
	elif t <= -1.8e-244:
		tmp = c * (y * (y3 * y4))
	elif t <= 1.46e+60:
		tmp = b * (k * (z * y0))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(c * Float64(i * Float64(z * t)))
	tmp = 0.0
	if (t <= -6.4e+46)
		tmp = t_1;
	elseif (t <= -1.8e-244)
		tmp = Float64(c * Float64(y * Float64(y3 * y4)));
	elseif (t <= 1.46e+60)
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = c * (i * (z * t));
	tmp = 0.0;
	if (t <= -6.4e+46)
		tmp = t_1;
	elseif (t <= -1.8e-244)
		tmp = c * (y * (y3 * y4));
	elseif (t <= 1.46e+60)
		tmp = b * (k * (z * y0));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(c * N[(i * N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -6.4e+46], t$95$1, If[LessEqual[t, -1.8e-244], N[(c * N[(y * N[(y3 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.46e+60], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]

Derivation

1. Split input into 3 regimes

2. if t < -6.3999999999999996e46 or 1.4600000000000001e60 < t

   1. Initial program 26.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 33.2%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in z around -inf 33.8%

      \[\leadsto \color{blue}{i \cdot \left(z \cdot \left(c \cdot t - k \cdot y1\right)\right)} \]

   5. Taylor expanded in c around inf 30.6%

      \[\leadsto \color{blue}{c \cdot \left(i \cdot \left(t \cdot z\right)\right)} \]

   if -6.3999999999999996e46 < t < -1.79999999999999987e-244

   1. Initial program 28.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 41.9%

      \[\leadsto \left(\color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in c around inf 36.0%

      \[\leadsto \color{blue}{-1 \cdot \left(c \cdot \left(y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   5. Step-by-step derivation

      1. mul-1-neg 36.0%

         \[\leadsto \color{blue}{-c \cdot \left(y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

      2. associate-*r* 25.6%

         \[\leadsto -\color{blue}{\left(c \cdot y4\right) \cdot \left(t \cdot y2 - y \cdot y3\right)} \]

   6. Simplified 25.6%

      \[\leadsto \color{blue}{-\left(c \cdot y4\right) \cdot \left(t \cdot y2 - y \cdot y3\right)} \]

   7. Taylor expanded in t around 0 26.8%

      \[\leadsto \color{blue}{c \cdot \left(y \cdot \left(y3 \cdot y4\right)\right)} \]

   if -1.79999999999999987e-244 < t < 1.4600000000000001e60

   1. Initial program 40.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around -inf 44.0%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 44.0%

         \[\leadsto \color{blue}{\left(-k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 44.0%

         \[\leadsto \left(-k \cdot \left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 44.0%

      \[\leadsto \color{blue}{\left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in z around -inf 29.6%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   7. Taylor expanded in b around inf 23.5%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]
3. Recombined 3 regimes into one program.

4. Final simplification 26.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -6.4 \cdot 10^{+46}:\\ \;\;\;\;c \cdot \left(i \cdot \left(z \cdot t\right)\right)\\ \mathbf{elif}\;t \leq -1.8 \cdot 10^{-244}:\\ \;\;\;\;c \cdot \left(y \cdot \left(y3 \cdot y4\right)\right)\\ \mathbf{elif}\;t \leq 1.46 \cdot 10^{+60}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(i \cdot \left(z \cdot t\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 33: 22.4% accurate, 5.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;t \leq -5 \cdot 10^{+33} \lor \neg \left(t \leq 2.7 \cdot 10^{+59}\right):\\ \;\;\;\;c \cdot \left(i \cdot \left(z \cdot t\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (or (<= t -5e+33) (not (<= t 2.7e+59)))
   (* c (* i (* z t)))
   (* b (* k (* z y0)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if ((t <= -5e+33) || !(t <= 2.7e+59)) {
		tmp = c * (i * (z * t));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if ((t <= (-5d+33)) .or. (.not. (t <= 2.7d+59))) then
        tmp = c * (i * (z * t))
    else
        tmp = b * (k * (z * y0))
    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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if ((t <= -5e+33) || !(t <= 2.7e+59)) {
		tmp = c * (i * (z * t));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if (t <= -5e+33) or not (t <= 2.7e+59):
		tmp = c * (i * (z * t))
	else:
		tmp = b * (k * (z * y0))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if ((t <= -5e+33) || !(t <= 2.7e+59))
		tmp = Float64(c * Float64(i * Float64(z * t)));
	else
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if ((t <= -5e+33) || ~((t <= 2.7e+59)))
		tmp = c * (i * (z * t));
	else
		tmp = b * (k * (z * y0));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[Or[LessEqual[t, -5e+33], N[Not[LessEqual[t, 2.7e+59]], $MachinePrecision]], N[(c * N[(i * N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if t < -4.99999999999999973e33 or 2.7000000000000001e59 < t

   1. Initial program 25.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 32.9%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in z around -inf 33.5%

      \[\leadsto \color{blue}{i \cdot \left(z \cdot \left(c \cdot t - k \cdot y1\right)\right)} \]

   5. Taylor expanded in c around inf 30.4%

      \[\leadsto \color{blue}{c \cdot \left(i \cdot \left(t \cdot z\right)\right)} \]

   if -4.99999999999999973e33 < t < 2.7000000000000001e59

   1. Initial program 36.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around -inf 43.0%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 43.0%

         \[\leadsto \color{blue}{\left(-k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 43.0%

         \[\leadsto \left(-k \cdot \left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 43.0%

      \[\leadsto \color{blue}{\left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in z around -inf 30.4%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   7. Taylor expanded in b around inf 21.6%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]
3. Recombined 2 regimes into one program.

4. Final simplification 24.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -5 \cdot 10^{+33} \lor \neg \left(t \leq 2.7 \cdot 10^{+59}\right):\\ \;\;\;\;c \cdot \left(i \cdot \left(z \cdot t\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 34: 21.4% accurate, 5.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -2.5 \cdot 10^{-110}:\\ \;\;\;\;\left(c \cdot i\right) \cdot \left(z \cdot t\right)\\ \mathbf{elif}\;z \leq 280000000000:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= z -2.5e-110)
   (* (* c i) (* z t))
   (if (<= z 280000000000.0) (* k (* y1 (* y2 y4))) (* b (* k (* z y0))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -2.5e-110) {
		tmp = (c * i) * (z * t);
	} else if (z <= 280000000000.0) {
		tmp = k * (y1 * (y2 * y4));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (z <= (-2.5d-110)) then
        tmp = (c * i) * (z * t)
    else if (z <= 280000000000.0d0) then
        tmp = k * (y1 * (y2 * y4))
    else
        tmp = b * (k * (z * y0))
    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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -2.5e-110) {
		tmp = (c * i) * (z * t);
	} else if (z <= 280000000000.0) {
		tmp = k * (y1 * (y2 * y4));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if z <= -2.5e-110:
		tmp = (c * i) * (z * t)
	elif z <= 280000000000.0:
		tmp = k * (y1 * (y2 * y4))
	else:
		tmp = b * (k * (z * y0))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (z <= -2.5e-110)
		tmp = Float64(Float64(c * i) * Float64(z * t));
	elseif (z <= 280000000000.0)
		tmp = Float64(k * Float64(y1 * Float64(y2 * y4)));
	else
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (z <= -2.5e-110)
		tmp = (c * i) * (z * t);
	elseif (z <= 280000000000.0)
		tmp = k * (y1 * (y2 * y4));
	else
		tmp = b * (k * (z * y0));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[z, -2.5e-110], N[(N[(c * i), $MachinePrecision] * N[(z * t), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 280000000000.0], N[(k * N[(y1 * N[(y2 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]

Derivation

1. Split input into 3 regimes

2. if z < -2.5e-110

   1. Initial program 30.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 33.4%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in z around -inf 36.3%

      \[\leadsto \color{blue}{i \cdot \left(z \cdot \left(c \cdot t - k \cdot y1\right)\right)} \]

   5. Taylor expanded in c around inf 27.0%

      \[\leadsto \color{blue}{c \cdot \left(i \cdot \left(t \cdot z\right)\right)} \]
   6. Step-by-step derivation

      1. associate-*r* 28.1%

         \[\leadsto \color{blue}{\left(c \cdot i\right) \cdot \left(t \cdot z\right)} \]

      2. *-commutative 28.1%

         \[\leadsto \color{blue}{\left(i \cdot c\right)} \cdot \left(t \cdot z\right) \]

      3. *-commutative 28.1%

         \[\leadsto \left(i \cdot c\right) \cdot \color{blue}{\left(z \cdot t\right)} \]

   7. Simplified 28.1%

      \[\leadsto \color{blue}{\left(i \cdot c\right) \cdot \left(z \cdot t\right)} \]

   if -2.5e-110 < z < 2.8e11

   1. Initial program 34.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 40.7%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in y1 around inf 31.3%

      \[\leadsto y2 \cdot \color{blue}{\left(y1 \cdot \left(-1 \cdot \left(a \cdot x\right) + k \cdot y4\right)\right)} \]

   5. Taylor expanded in a around 0 20.5%

      \[\leadsto \color{blue}{k \cdot \left(y1 \cdot \left(y2 \cdot y4\right)\right)} \]

   if 2.8e11 < z

   1. Initial program 31.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around -inf 38.3%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 38.3%

         \[\leadsto \color{blue}{\left(-k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 38.3%

         \[\leadsto \left(-k \cdot \left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 38.3%

      \[\leadsto \color{blue}{\left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in z around -inf 47.4%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   7. Taylor expanded in b around inf 42.2%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]
3. Recombined 3 regimes into one program.

4. Final simplification 28.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -2.5 \cdot 10^{-110}:\\ \;\;\;\;\left(c \cdot i\right) \cdot \left(z \cdot t\right)\\ \mathbf{elif}\;z \leq 280000000000:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 35: 22.2% accurate, 5.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -1.05 \cdot 10^{+55}:\\ \;\;\;\;i \cdot \left(z \cdot \left(t \cdot c\right)\right)\\ \mathbf{elif}\;z \leq 3.4 \cdot 10^{+14}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= z -1.05e+55)
   (* i (* z (* t c)))
   (if (<= z 3.4e+14) (* k (* y1 (* y2 y4))) (* b (* k (* z y0))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -1.05e+55) {
		tmp = i * (z * (t * c));
	} else if (z <= 3.4e+14) {
		tmp = k * (y1 * (y2 * y4));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (z <= (-1.05d+55)) then
        tmp = i * (z * (t * c))
    else if (z <= 3.4d+14) then
        tmp = k * (y1 * (y2 * y4))
    else
        tmp = b * (k * (z * y0))
    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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -1.05e+55) {
		tmp = i * (z * (t * c));
	} else if (z <= 3.4e+14) {
		tmp = k * (y1 * (y2 * y4));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if z <= -1.05e+55:
		tmp = i * (z * (t * c))
	elif z <= 3.4e+14:
		tmp = k * (y1 * (y2 * y4))
	else:
		tmp = b * (k * (z * y0))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (z <= -1.05e+55)
		tmp = Float64(i * Float64(z * Float64(t * c)));
	elseif (z <= 3.4e+14)
		tmp = Float64(k * Float64(y1 * Float64(y2 * y4)));
	else
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (z <= -1.05e+55)
		tmp = i * (z * (t * c));
	elseif (z <= 3.4e+14)
		tmp = k * (y1 * (y2 * y4));
	else
		tmp = b * (k * (z * y0));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[z, -1.05e+55], N[(i * N[(z * N[(t * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 3.4e+14], N[(k * N[(y1 * N[(y2 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]

Derivation

1. Split input into 3 regimes

2. if z < -1.05e55

   1. Initial program 33.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in i around -inf 35.7%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(\left(c \cdot \left(x \cdot y - t \cdot z\right) + y5 \cdot \left(j \cdot t - k \cdot y\right)\right) - y1 \cdot \left(j \cdot x - k \cdot z\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in z around -inf 43.8%

      \[\leadsto \color{blue}{i \cdot \left(z \cdot \left(c \cdot t - k \cdot y1\right)\right)} \]

   5. Taylor expanded in c around inf 30.2%

      \[\leadsto i \cdot \left(z \cdot \color{blue}{\left(c \cdot t\right)}\right) \]

   if -1.05e55 < z < 3.4e14

   1. Initial program 32.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y2 around inf 40.1%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   4. Taylor expanded in y1 around inf 29.3%

      \[\leadsto y2 \cdot \color{blue}{\left(y1 \cdot \left(-1 \cdot \left(a \cdot x\right) + k \cdot y4\right)\right)} \]

   5. Taylor expanded in a around 0 21.1%

      \[\leadsto \color{blue}{k \cdot \left(y1 \cdot \left(y2 \cdot y4\right)\right)} \]

   if 3.4e14 < z

   1. Initial program 31.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around -inf 38.3%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 38.3%

         \[\leadsto \color{blue}{\left(-k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 38.3%

         \[\leadsto \left(-k \cdot \left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 38.3%

      \[\leadsto \color{blue}{\left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in z around -inf 47.4%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   7. Taylor expanded in b around inf 42.2%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]
3. Recombined 3 regimes into one program.

4. Final simplification 27.7%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -1.05 \cdot 10^{+55}:\\ \;\;\;\;i \cdot \left(z \cdot \left(t \cdot c\right)\right)\\ \mathbf{elif}\;z \leq 3.4 \cdot 10^{+14}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 36: 20.0% accurate, 7.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y5 \leq -1.3 \cdot 10^{+65}:\\ \;\;\;\;a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= y5 -1.3e+65) (* a (* t (* y2 y5))) (* b (* k (* z y0)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y5 <= -1.3e+65) {
		tmp = a * (t * (y2 * y5));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (y5 <= (-1.3d+65)) then
        tmp = a * (t * (y2 * y5))
    else
        tmp = b * (k * (z * y0))
    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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y5 <= -1.3e+65) {
		tmp = a * (t * (y2 * y5));
	} else {
		tmp = b * (k * (z * y0));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if y5 <= -1.3e+65:
		tmp = a * (t * (y2 * y5))
	else:
		tmp = b * (k * (z * y0))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (y5 <= -1.3e+65)
		tmp = Float64(a * Float64(t * Float64(y2 * y5)));
	else
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (y5 <= -1.3e+65)
		tmp = a * (t * (y2 * y5));
	else
		tmp = b * (k * (z * y0));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[y5, -1.3e+65], N[(a * N[(t * N[(y2 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if y5 < -1.30000000000000001e65

   1. Initial program 27.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 52.4%

      \[\leadsto \left(\color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   4. Taylor expanded in a around inf 41.6%

      \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   5. Taylor expanded in t around inf 32.7%

      \[\leadsto \color{blue}{a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)} \]

   if -1.30000000000000001e65 < y5

   1. Initial program 33.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in k around -inf 39.4%

      \[\leadsto \color{blue}{-1 \cdot \left(k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   4. Step-by-step derivation

      1. mul-1-neg 39.4%

         \[\leadsto \color{blue}{\left(-k \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

      2. *-commutative 39.4%

         \[\leadsto \left(-k \cdot \left(\color{blue}{\left(b \cdot y4 - i \cdot y5\right) \cdot y} - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   5. Simplified 39.4%

      \[\leadsto \color{blue}{\left(-k \cdot \left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   6. Taylor expanded in z around -inf 27.3%

      \[\leadsto \color{blue}{k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   7. Taylor expanded in b around inf 18.8%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]
3. Recombined 2 regimes into one program.

4. Final simplification 21.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y5 \leq -1.3 \cdot 10^{+65}:\\ \;\;\;\;a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 37: 17.0% accurate, 13.6× speedup

Math

\[\begin{array}{l} \\ a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right) \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (* a (* t (* y2 y5))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	return a * (t * (y2 * y5));
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    code = a * (t * (y2 * y5))
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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	return a * (t * (y2 * y5));
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	return a * (t * (y2 * y5))

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	return Float64(a * Float64(t * Float64(y2 * y5)))
end

MATLAB

function tmp = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = a * (t * (y2 * y5));
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := N[(a * N[(t * N[(y2 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 32.5%

   \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
2. Add Preprocessing

3. Taylor expanded in y4 around inf 36.5%

   \[\leadsto \left(\color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right)\right)} - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

4. Taylor expanded in a around inf 25.1%

   \[\leadsto \color{blue}{a \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

5. Taylor expanded in t around inf 12.8%

   \[\leadsto \color{blue}{a \cdot \left(t \cdot \left(y2 \cdot y5\right)\right)} \]
6. Add Preprocessing

Developer Target 1: 28.2% accurate, 0.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y4 \cdot c - y5 \cdot a\\ t_2 := x \cdot y2 - z \cdot y3\\ t_3 := y2 \cdot t - y3 \cdot y\\ t_4 := k \cdot y2 - j \cdot y3\\ t_5 := y4 \cdot b - y5 \cdot i\\ t_6 := \left(j \cdot t - k \cdot y\right) \cdot t\_5\\ t_7 := b \cdot a - i \cdot c\\ t_8 := t\_7 \cdot \left(y \cdot x - t \cdot z\right)\\ t_9 := j \cdot x - k \cdot z\\ t_10 := \left(b \cdot y0 - i \cdot y1\right) \cdot t\_9\\ t_11 := t\_9 \cdot \left(y0 \cdot b - i \cdot y1\right)\\ t_12 := y4 \cdot y1 - y5 \cdot y0\\ t_13 := t\_4 \cdot t\_12\\ t_14 := \left(y2 \cdot k - y3 \cdot j\right) \cdot t\_12\\ t_15 := \left(\left(\left(\left(k \cdot y\right) \cdot \left(y5 \cdot i\right) - \left(y \cdot b\right) \cdot \left(y4 \cdot k\right)\right) - \left(y5 \cdot t\right) \cdot \left(i \cdot j\right)\right) - \left(t\_3 \cdot t\_1 - t\_14\right)\right) + \left(t\_8 - \left(t\_11 - \left(y2 \cdot x - y3 \cdot z\right) \cdot \left(c \cdot y0 - y1 \cdot a\right)\right)\right)\\ t_16 := \left(\left(t\_6 - \left(y3 \cdot y\right) \cdot \left(y5 \cdot a - y4 \cdot c\right)\right) + \left(\left(y5 \cdot a\right) \cdot \left(t \cdot y2\right) + t\_13\right)\right) + \left(t\_2 \cdot \left(c \cdot y0 - a \cdot y1\right) - \left(t\_10 - \left(y \cdot x - z \cdot t\right) \cdot t\_7\right)\right)\\ t_17 := t \cdot y2 - y \cdot y3\\ \mathbf{if}\;y4 < -7.206256231996481 \cdot 10^{+60}:\\ \;\;\;\;\left(t\_8 - \left(t\_11 - t\_6\right)\right) - \left(\frac{t\_3}{\frac{1}{t\_1}} - t\_14\right)\\ \mathbf{elif}\;y4 < -3.364603505246317 \cdot 10^{-66}:\\ \;\;\;\;\left(\left(\left(\left(t \cdot c\right) \cdot \left(i \cdot z\right) - \left(a \cdot t\right) \cdot \left(b \cdot z\right)\right) - \left(y \cdot c\right) \cdot \left(i \cdot x\right)\right) - t\_10\right) + \left(\left(y0 \cdot c - a \cdot y1\right) \cdot t\_2 - \left(t\_17 \cdot \left(y4 \cdot c - a \cdot y5\right) - \left(y1 \cdot y4 - y5 \cdot y0\right) \cdot t\_4\right)\right)\\ \mathbf{elif}\;y4 < -1.2000065055686116 \cdot 10^{-105}:\\ \;\;\;\;t\_16\\ \mathbf{elif}\;y4 < 6.718963124057495 \cdot 10^{-279}:\\ \;\;\;\;t\_15\\ \mathbf{elif}\;y4 < 4.77962681403792 \cdot 10^{-222}:\\ \;\;\;\;t\_16\\ \mathbf{elif}\;y4 < 2.2852241541266835 \cdot 10^{-175}:\\ \;\;\;\;t\_15\\ \mathbf{else}:\\ \;\;\;\;\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(k \cdot \left(i \cdot \left(z \cdot y1\right)\right) - \left(j \cdot \left(i \cdot \left(x \cdot y1\right)\right) + y0 \cdot \left(k \cdot \left(z \cdot b\right)\right)\right)\right)\right) + \left(z \cdot \left(y3 \cdot \left(a \cdot y1\right)\right) - \left(y2 \cdot \left(x \cdot \left(a \cdot y1\right)\right) + y0 \cdot \left(z \cdot \left(c \cdot y3\right)\right)\right)\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot t\_5\right) - t\_17 \cdot t\_1\right) + t\_13\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* y4 c) (* y5 a)))
        (t_2 (- (* x y2) (* z y3)))
        (t_3 (- (* y2 t) (* y3 y)))
        (t_4 (- (* k y2) (* j y3)))
        (t_5 (- (* y4 b) (* y5 i)))
        (t_6 (* (- (* j t) (* k y)) t_5))
        (t_7 (- (* b a) (* i c)))
        (t_8 (* t_7 (- (* y x) (* t z))))
        (t_9 (- (* j x) (* k z)))
        (t_10 (* (- (* b y0) (* i y1)) t_9))
        (t_11 (* t_9 (- (* y0 b) (* i y1))))
        (t_12 (- (* y4 y1) (* y5 y0)))
        (t_13 (* t_4 t_12))
        (t_14 (* (- (* y2 k) (* y3 j)) t_12))
        (t_15
         (+
          (-
           (-
            (- (* (* k y) (* y5 i)) (* (* y b) (* y4 k)))
            (* (* y5 t) (* i j)))
           (- (* t_3 t_1) t_14))
          (- t_8 (- t_11 (* (- (* y2 x) (* y3 z)) (- (* c y0) (* y1 a)))))))
        (t_16
         (+
          (+
           (- t_6 (* (* y3 y) (- (* y5 a) (* y4 c))))
           (+ (* (* y5 a) (* t y2)) t_13))
          (-
           (* t_2 (- (* c y0) (* a y1)))
           (- t_10 (* (- (* y x) (* z t)) t_7)))))
        (t_17 (- (* t y2) (* y y3))))
   (if (< y4 -7.206256231996481e+60)
     (- (- t_8 (- t_11 t_6)) (- (/ t_3 (/ 1.0 t_1)) t_14))
     (if (< y4 -3.364603505246317e-66)
       (+
        (-
         (- (- (* (* t c) (* i z)) (* (* a t) (* b z))) (* (* y c) (* i x)))
         t_10)
        (-
         (* (- (* y0 c) (* a y1)) t_2)
         (- (* t_17 (- (* y4 c) (* a y5))) (* (- (* y1 y4) (* y5 y0)) t_4))))
       (if (< y4 -1.2000065055686116e-105)
         t_16
         (if (< y4 6.718963124057495e-279)
           t_15
           (if (< y4 4.77962681403792e-222)
             t_16
             (if (< y4 2.2852241541266835e-175)
               t_15
               (+
                (-
                 (+
                  (+
                   (-
                    (* (- (* x y) (* z t)) (- (* a b) (* c i)))
                    (-
                     (* k (* i (* z y1)))
                     (+ (* j (* i (* x y1))) (* y0 (* k (* z b))))))
                   (-
                    (* z (* y3 (* a y1)))
                    (+ (* y2 (* x (* a y1))) (* y0 (* z (* c y3))))))
                  (* (- (* t j) (* y k)) t_5))
                 (* t_17 t_1))
                t_13)))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (y4 * c) - (y5 * a);
	double t_2 = (x * y2) - (z * y3);
	double t_3 = (y2 * t) - (y3 * y);
	double t_4 = (k * y2) - (j * y3);
	double t_5 = (y4 * b) - (y5 * i);
	double t_6 = ((j * t) - (k * y)) * t_5;
	double t_7 = (b * a) - (i * c);
	double t_8 = t_7 * ((y * x) - (t * z));
	double t_9 = (j * x) - (k * z);
	double t_10 = ((b * y0) - (i * y1)) * t_9;
	double t_11 = t_9 * ((y0 * b) - (i * y1));
	double t_12 = (y4 * y1) - (y5 * y0);
	double t_13 = t_4 * t_12;
	double t_14 = ((y2 * k) - (y3 * j)) * t_12;
	double t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))));
	double t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)));
	double t_17 = (t * y2) - (y * y3);
	double tmp;
	if (y4 < -7.206256231996481e+60) {
		tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0 / t_1)) - t_14);
	} else if (y4 < -3.364603505246317e-66) {
		tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)));
	} else if (y4 < -1.2000065055686116e-105) {
		tmp = t_16;
	} else if (y4 < 6.718963124057495e-279) {
		tmp = t_15;
	} else if (y4 < 4.77962681403792e-222) {
		tmp = t_16;
	} else if (y4 < 2.2852241541266835e-175) {
		tmp = t_15;
	} else {
		tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    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), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_10
    real(8) :: t_11
    real(8) :: t_12
    real(8) :: t_13
    real(8) :: t_14
    real(8) :: t_15
    real(8) :: t_16
    real(8) :: t_17
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: t_5
    real(8) :: t_6
    real(8) :: t_7
    real(8) :: t_8
    real(8) :: t_9
    real(8) :: tmp
    t_1 = (y4 * c) - (y5 * a)
    t_2 = (x * y2) - (z * y3)
    t_3 = (y2 * t) - (y3 * y)
    t_4 = (k * y2) - (j * y3)
    t_5 = (y4 * b) - (y5 * i)
    t_6 = ((j * t) - (k * y)) * t_5
    t_7 = (b * a) - (i * c)
    t_8 = t_7 * ((y * x) - (t * z))
    t_9 = (j * x) - (k * z)
    t_10 = ((b * y0) - (i * y1)) * t_9
    t_11 = t_9 * ((y0 * b) - (i * y1))
    t_12 = (y4 * y1) - (y5 * y0)
    t_13 = t_4 * t_12
    t_14 = ((y2 * k) - (y3 * j)) * t_12
    t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))))
    t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)))
    t_17 = (t * y2) - (y * y3)
    if (y4 < (-7.206256231996481d+60)) then
        tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0d0 / t_1)) - t_14)
    else if (y4 < (-3.364603505246317d-66)) then
        tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)))
    else if (y4 < (-1.2000065055686116d-105)) then
        tmp = t_16
    else if (y4 < 6.718963124057495d-279) then
        tmp = t_15
    else if (y4 < 4.77962681403792d-222) then
        tmp = t_16
    else if (y4 < 2.2852241541266835d-175) then
        tmp = t_15
    else
        tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13
    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 k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (y4 * c) - (y5 * a);
	double t_2 = (x * y2) - (z * y3);
	double t_3 = (y2 * t) - (y3 * y);
	double t_4 = (k * y2) - (j * y3);
	double t_5 = (y4 * b) - (y5 * i);
	double t_6 = ((j * t) - (k * y)) * t_5;
	double t_7 = (b * a) - (i * c);
	double t_8 = t_7 * ((y * x) - (t * z));
	double t_9 = (j * x) - (k * z);
	double t_10 = ((b * y0) - (i * y1)) * t_9;
	double t_11 = t_9 * ((y0 * b) - (i * y1));
	double t_12 = (y4 * y1) - (y5 * y0);
	double t_13 = t_4 * t_12;
	double t_14 = ((y2 * k) - (y3 * j)) * t_12;
	double t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))));
	double t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)));
	double t_17 = (t * y2) - (y * y3);
	double tmp;
	if (y4 < -7.206256231996481e+60) {
		tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0 / t_1)) - t_14);
	} else if (y4 < -3.364603505246317e-66) {
		tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)));
	} else if (y4 < -1.2000065055686116e-105) {
		tmp = t_16;
	} else if (y4 < 6.718963124057495e-279) {
		tmp = t_15;
	} else if (y4 < 4.77962681403792e-222) {
		tmp = t_16;
	} else if (y4 < 2.2852241541266835e-175) {
		tmp = t_15;
	} else {
		tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (y4 * c) - (y5 * a)
	t_2 = (x * y2) - (z * y3)
	t_3 = (y2 * t) - (y3 * y)
	t_4 = (k * y2) - (j * y3)
	t_5 = (y4 * b) - (y5 * i)
	t_6 = ((j * t) - (k * y)) * t_5
	t_7 = (b * a) - (i * c)
	t_8 = t_7 * ((y * x) - (t * z))
	t_9 = (j * x) - (k * z)
	t_10 = ((b * y0) - (i * y1)) * t_9
	t_11 = t_9 * ((y0 * b) - (i * y1))
	t_12 = (y4 * y1) - (y5 * y0)
	t_13 = t_4 * t_12
	t_14 = ((y2 * k) - (y3 * j)) * t_12
	t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))))
	t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)))
	t_17 = (t * y2) - (y * y3)
	tmp = 0
	if y4 < -7.206256231996481e+60:
		tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0 / t_1)) - t_14)
	elif y4 < -3.364603505246317e-66:
		tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)))
	elif y4 < -1.2000065055686116e-105:
		tmp = t_16
	elif y4 < 6.718963124057495e-279:
		tmp = t_15
	elif y4 < 4.77962681403792e-222:
		tmp = t_16
	elif y4 < 2.2852241541266835e-175:
		tmp = t_15
	else:
		tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(y4 * c) - Float64(y5 * a))
	t_2 = Float64(Float64(x * y2) - Float64(z * y3))
	t_3 = Float64(Float64(y2 * t) - Float64(y3 * y))
	t_4 = Float64(Float64(k * y2) - Float64(j * y3))
	t_5 = Float64(Float64(y4 * b) - Float64(y5 * i))
	t_6 = Float64(Float64(Float64(j * t) - Float64(k * y)) * t_5)
	t_7 = Float64(Float64(b * a) - Float64(i * c))
	t_8 = Float64(t_7 * Float64(Float64(y * x) - Float64(t * z)))
	t_9 = Float64(Float64(j * x) - Float64(k * z))
	t_10 = Float64(Float64(Float64(b * y0) - Float64(i * y1)) * t_9)
	t_11 = Float64(t_9 * Float64(Float64(y0 * b) - Float64(i * y1)))
	t_12 = Float64(Float64(y4 * y1) - Float64(y5 * y0))
	t_13 = Float64(t_4 * t_12)
	t_14 = Float64(Float64(Float64(y2 * k) - Float64(y3 * j)) * t_12)
	t_15 = Float64(Float64(Float64(Float64(Float64(Float64(k * y) * Float64(y5 * i)) - Float64(Float64(y * b) * Float64(y4 * k))) - Float64(Float64(y5 * t) * Float64(i * j))) - Float64(Float64(t_3 * t_1) - t_14)) + Float64(t_8 - Float64(t_11 - Float64(Float64(Float64(y2 * x) - Float64(y3 * z)) * Float64(Float64(c * y0) - Float64(y1 * a))))))
	t_16 = Float64(Float64(Float64(t_6 - Float64(Float64(y3 * y) * Float64(Float64(y5 * a) - Float64(y4 * c)))) + Float64(Float64(Float64(y5 * a) * Float64(t * y2)) + t_13)) + Float64(Float64(t_2 * Float64(Float64(c * y0) - Float64(a * y1))) - Float64(t_10 - Float64(Float64(Float64(y * x) - Float64(z * t)) * t_7))))
	t_17 = Float64(Float64(t * y2) - Float64(y * y3))
	tmp = 0.0
	if (y4 < -7.206256231996481e+60)
		tmp = Float64(Float64(t_8 - Float64(t_11 - t_6)) - Float64(Float64(t_3 / Float64(1.0 / t_1)) - t_14));
	elseif (y4 < -3.364603505246317e-66)
		tmp = Float64(Float64(Float64(Float64(Float64(Float64(t * c) * Float64(i * z)) - Float64(Float64(a * t) * Float64(b * z))) - Float64(Float64(y * c) * Float64(i * x))) - t_10) + Float64(Float64(Float64(Float64(y0 * c) - Float64(a * y1)) * t_2) - Float64(Float64(t_17 * Float64(Float64(y4 * c) - Float64(a * y5))) - Float64(Float64(Float64(y1 * y4) - Float64(y5 * y0)) * t_4))));
	elseif (y4 < -1.2000065055686116e-105)
		tmp = t_16;
	elseif (y4 < 6.718963124057495e-279)
		tmp = t_15;
	elseif (y4 < 4.77962681403792e-222)
		tmp = t_16;
	elseif (y4 < 2.2852241541266835e-175)
		tmp = t_15;
	else
		tmp = Float64(Float64(Float64(Float64(Float64(Float64(Float64(Float64(x * y) - Float64(z * t)) * Float64(Float64(a * b) - Float64(c * i))) - Float64(Float64(k * Float64(i * Float64(z * y1))) - Float64(Float64(j * Float64(i * Float64(x * y1))) + Float64(y0 * Float64(k * Float64(z * b)))))) + Float64(Float64(z * Float64(y3 * Float64(a * y1))) - Float64(Float64(y2 * Float64(x * Float64(a * y1))) + Float64(y0 * Float64(z * Float64(c * y3)))))) + Float64(Float64(Float64(t * j) - Float64(y * k)) * t_5)) - Float64(t_17 * t_1)) + t_13);
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = (y4 * c) - (y5 * a);
	t_2 = (x * y2) - (z * y3);
	t_3 = (y2 * t) - (y3 * y);
	t_4 = (k * y2) - (j * y3);
	t_5 = (y4 * b) - (y5 * i);
	t_6 = ((j * t) - (k * y)) * t_5;
	t_7 = (b * a) - (i * c);
	t_8 = t_7 * ((y * x) - (t * z));
	t_9 = (j * x) - (k * z);
	t_10 = ((b * y0) - (i * y1)) * t_9;
	t_11 = t_9 * ((y0 * b) - (i * y1));
	t_12 = (y4 * y1) - (y5 * y0);
	t_13 = t_4 * t_12;
	t_14 = ((y2 * k) - (y3 * j)) * t_12;
	t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))));
	t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)));
	t_17 = (t * y2) - (y * y3);
	tmp = 0.0;
	if (y4 < -7.206256231996481e+60)
		tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0 / t_1)) - t_14);
	elseif (y4 < -3.364603505246317e-66)
		tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)));
	elseif (y4 < -1.2000065055686116e-105)
		tmp = t_16;
	elseif (y4 < 6.718963124057495e-279)
		tmp = t_15;
	elseif (y4 < 4.77962681403792e-222)
		tmp = t_16;
	elseif (y4 < 2.2852241541266835e-175)
		tmp = t_15;
	else
		tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(y4 * c), $MachinePrecision] - N[(y5 * a), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(y2 * t), $MachinePrecision] - N[(y3 * y), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(N[(y4 * b), $MachinePrecision] - N[(y5 * i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$6 = N[(N[(N[(j * t), $MachinePrecision] - N[(k * y), $MachinePrecision]), $MachinePrecision] * t$95$5), $MachinePrecision]}, Block[{t$95$7 = N[(N[(b * a), $MachinePrecision] - N[(i * c), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$8 = N[(t$95$7 * N[(N[(y * x), $MachinePrecision] - N[(t * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$9 = N[(N[(j * x), $MachinePrecision] - N[(k * z), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$10 = N[(N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision] * t$95$9), $MachinePrecision]}, Block[{t$95$11 = N[(t$95$9 * N[(N[(y0 * b), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$12 = N[(N[(y4 * y1), $MachinePrecision] - N[(y5 * y0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$13 = N[(t$95$4 * t$95$12), $MachinePrecision]}, Block[{t$95$14 = N[(N[(N[(y2 * k), $MachinePrecision] - N[(y3 * j), $MachinePrecision]), $MachinePrecision] * t$95$12), $MachinePrecision]}, Block[{t$95$15 = N[(N[(N[(N[(N[(N[(k * y), $MachinePrecision] * N[(y5 * i), $MachinePrecision]), $MachinePrecision] - N[(N[(y * b), $MachinePrecision] * N[(y4 * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(y5 * t), $MachinePrecision] * N[(i * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(t$95$3 * t$95$1), $MachinePrecision] - t$95$14), $MachinePrecision]), $MachinePrecision] + N[(t$95$8 - N[(t$95$11 - N[(N[(N[(y2 * x), $MachinePrecision] - N[(y3 * z), $MachinePrecision]), $MachinePrecision] * N[(N[(c * y0), $MachinePrecision] - N[(y1 * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$16 = N[(N[(N[(t$95$6 - N[(N[(y3 * y), $MachinePrecision] * N[(N[(y5 * a), $MachinePrecision] - N[(y4 * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(y5 * a), $MachinePrecision] * N[(t * y2), $MachinePrecision]), $MachinePrecision] + t$95$13), $MachinePrecision]), $MachinePrecision] + N[(N[(t$95$2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(t$95$10 - N[(N[(N[(y * x), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision] * t$95$7), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$17 = N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]}, If[Less[y4, -7.206256231996481e+60], N[(N[(t$95$8 - N[(t$95$11 - t$95$6), $MachinePrecision]), $MachinePrecision] - N[(N[(t$95$3 / N[(1.0 / t$95$1), $MachinePrecision]), $MachinePrecision] - t$95$14), $MachinePrecision]), $MachinePrecision], If[Less[y4, -3.364603505246317e-66], N[(N[(N[(N[(N[(N[(t * c), $MachinePrecision] * N[(i * z), $MachinePrecision]), $MachinePrecision] - N[(N[(a * t), $MachinePrecision] * N[(b * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(y * c), $MachinePrecision] * N[(i * x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$10), $MachinePrecision] + N[(N[(N[(N[(y0 * c), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision] * t$95$2), $MachinePrecision] - N[(N[(t$95$17 * N[(N[(y4 * c), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(N[(y1 * y4), $MachinePrecision] - N[(y5 * y0), $MachinePrecision]), $MachinePrecision] * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[Less[y4, -1.2000065055686116e-105], t$95$16, If[Less[y4, 6.718963124057495e-279], t$95$15, If[Less[y4, 4.77962681403792e-222], t$95$16, If[Less[y4, 2.2852241541266835e-175], t$95$15, N[(N[(N[(N[(N[(N[(N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision] * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(k * N[(i * N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(j * N[(i * N[(x * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(k * N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(z * N[(y3 * N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(y2 * N[(x * N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(z * N[(c * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision] * t$95$5), $MachinePrecision]), $MachinePrecision] - N[(t$95$17 * t$95$1), $MachinePrecision]), $MachinePrecision] + t$95$13), $MachinePrecision]]]]]]]]]]]]]]]]]]]]]]]]

Reproduce

herbie shell --seed 2024170 
(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
  :name "Linear.Matrix:det44 from linear-1.19.1.3"
  :precision binary64

  :alt
  (! :herbie-platform default (if (< y4 -7206256231996481000000000000000000000000000000000000000000000) (- (- (* (- (* b a) (* i c)) (- (* y x) (* t z))) (- (* (- (* j x) (* k z)) (- (* y0 b) (* i y1))) (* (- (* j t) (* k y)) (- (* y4 b) (* y5 i))))) (- (/ (- (* y2 t) (* y3 y)) (/ 1 (- (* y4 c) (* y5 a)))) (* (- (* y2 k) (* y3 j)) (- (* y4 y1) (* y5 y0))))) (if (< y4 -3364603505246317/1000000000000000000000000000000000000000000000000000000000000000000000000000000000) (+ (- (- (- (* (* t c) (* i z)) (* (* a t) (* b z))) (* (* y c) (* i x))) (* (- (* b y0) (* i y1)) (- (* j x) (* k z)))) (- (* (- (* y0 c) (* a y1)) (- (* x y2) (* z y3))) (- (* (- (* t y2) (* y y3)) (- (* y4 c) (* a y5))) (* (- (* y1 y4) (* y5 y0)) (- (* k y2) (* j y3)))))) (if (< y4 -3000016263921529/2500000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000) (+ (+ (- (* (- (* j t) (* k y)) (- (* y4 b) (* y5 i))) (* (* y3 y) (- (* y5 a) (* y4 c)))) (+ (* (* y5 a) (* t y2)) (* (- (* k y2) (* j y3)) (- (* y4 y1) (* y5 y0))))) (- (* (- (* x y2) (* z y3)) (- (* c y0) (* a y1))) (- (* (- (* b y0) (* i y1)) (- (* j x) (* k z))) (* (- (* y x) (* z t)) (- (* b a) (* i c)))))) (if (< y4 1343792624811499/200000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000) (+ (- (- (- (* (* k y) (* y5 i)) (* (* y b) (* y4 k))) (* (* y5 t) (* i j))) (- (* (- (* y2 t) (* y3 y)) (- (* y4 c) (* y5 a))) (* (- (* y2 k) (* y3 j)) (- (* y4 y1) (* y5 y0))))) (- (* (- (* b a) (* i c)) (- (* y x) (* t z))) (- (* (- (* j x) (* k z)) (- (* y0 b) (* i y1))) (* (- (* y2 x) (* y3 z)) (- (* c y0) (* y1 a)))))) (if (< y4 29872667587737/6250000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000) (+ (+ (- (* (- (* j t) (* k y)) (- (* y4 b) (* y5 i))) (* (* y3 y) (- (* y5 a) (* y4 c)))) (+ (* (* y5 a) (* t y2)) (* (- (* k y2) (* j y3)) (- (* y4 y1) (* y5 y0))))) (- (* (- (* x y2) (* z y3)) (- (* c y0) (* a y1))) (- (* (- (* b y0) (* i y1)) (- (* j x) (* k z))) (* (- (* y x) (* z t)) (- (* b a) (* i c)))))) (if (< y4 4570448308253367/20000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000) (+ (- (- (- (* (* k y) (* y5 i)) (* (* y b) (* y4 k))) (* (* y5 t) (* i j))) (- (* (- (* y2 t) (* y3 y)) (- (* y4 c) (* y5 a))) (* (- (* y2 k) (* y3 j)) (- (* y4 y1) (* y5 y0))))) (- (* (- (* b a) (* i c)) (- (* y x) (* t z))) (- (* (- (* j x) (* k z)) (- (* y0 b) (* i y1))) (* (- (* y2 x) (* y3 z)) (- (* c y0) (* y1 a)))))) (+ (- (+ (+ (- (* (- (* x y) (* z t)) (- (* a b) (* c i))) (- (* k (* i (* z y1))) (+ (* j (* i (* x y1))) (* y0 (* k (* z b)))))) (- (* z (* y3 (* a y1))) (+ (* y2 (* x (* a y1))) (* y0 (* z (* c y3)))))) (* (- (* t j) (* y k)) (- (* y4 b) (* y5 i)))) (* (- (* t y2) (* y y3)) (- (* y4 c) (* y5 a)))) (* (- (* k y2) (* j y3)) (- (* y4 y1) (* y5 y0)))))))))))

  (+ (- (+ (+ (- (* (- (* x y) (* z t)) (- (* a b) (* c i))) (* (- (* x j) (* z k)) (- (* y0 b) (* y1 i)))) (* (- (* x y2) (* z y3)) (- (* y0 c) (* y1 a)))) (* (- (* t j) (* y k)) (- (* y4 b) (* y5 i)))) (* (- (* t y2) (* y y3)) (- (* y4 c) (* y5 a)))) (* (- (* k y2) (* j y3)) (- (* y4 y1) (* y5 y0)))))