Linear.Matrix:det44 from linear-1.19.1.3

Percentage Accurate: 29.9% → 39.3%

Time: 1.7min

Alternatives: 37

Speedup: 3.7×

• 89.1% 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: 29.9% 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: 39.3% accurate, 1.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot y2 - z \cdot y3\\ t_2 := k \cdot \left(b \cdot y0 - i \cdot y1\right)\\ t_3 := x \cdot y - z \cdot t\\ t_4 := y0 \cdot \left(\left(y5 \cdot \left(j \cdot y3 - k \cdot y2\right) + c \cdot t_1\right) + b \cdot \left(z \cdot k - x \cdot j\right)\right)\\ t_5 := z \cdot y3 - x \cdot y2\\ t_6 := a \cdot \left(\left(y1 \cdot t_5 + b \cdot t_3\right) + y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{if}\;a \leq -3.4 \cdot 10^{+174}:\\ \;\;\;\;b \cdot \left(a \cdot t_3\right)\\ \mathbf{elif}\;a \leq -1.9 \cdot 10^{+110}:\\ \;\;\;\;z \cdot \left(t_2 - c \cdot \left(y0 \cdot y3\right)\right)\\ \mathbf{elif}\;a \leq -5.8 \cdot 10^{+91}:\\ \;\;\;\;\left(y3 \cdot y5\right) \cdot \left(j \cdot y0 - y \cdot a\right)\\ \mathbf{elif}\;a \leq -760000000:\\ \;\;\;\;y1 \cdot \left(\left(a \cdot t_5 + y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + i \cdot \left(x \cdot j - z \cdot k\right)\right)\\ \mathbf{elif}\;a \leq -6.6 \cdot 10^{-15}:\\ \;\;\;\;t_6\\ \mathbf{elif}\;a \leq -1.6 \cdot 10^{-144}:\\ \;\;\;\;c \cdot \left(\left(i \cdot \left(z \cdot t - x \cdot y\right) + y0 \cdot t_1\right) + y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;a \leq 2.5 \cdot 10^{-160}:\\ \;\;\;\;t_4\\ \mathbf{elif}\;a \leq 5.8 \cdot 10^{-57}:\\ \;\;\;\;z \cdot \left(\left(y3 \cdot \left(a \cdot y1 - c \cdot y0\right) + t \cdot \left(c \cdot i - a \cdot b\right)\right) + t_2\right)\\ \mathbf{elif}\;a \leq 4.2 \cdot 10^{+125}:\\ \;\;\;\;t_4\\ \mathbf{elif}\;a \leq 6.2 \cdot 10^{+165}:\\ \;\;\;\;t \cdot \left(\left(j \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(a \cdot b - c \cdot i\right)\right) + y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_6\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* x y2) (* z y3)))
        (t_2 (* k (- (* b y0) (* i y1))))
        (t_3 (- (* x y) (* z t)))
        (t_4
         (*
          y0
          (+
           (+ (* y5 (- (* j y3) (* k y2))) (* c t_1))
           (* b (- (* z k) (* x j))))))
        (t_5 (- (* z y3) (* x y2)))
        (t_6 (* a (+ (+ (* y1 t_5) (* b t_3)) (* y5 (- (* t y2) (* y y3)))))))
   (if (<= a -3.4e+174)
     (* b (* a t_3))
     (if (<= a -1.9e+110)
       (* z (- t_2 (* c (* y0 y3))))
       (if (<= a -5.8e+91)
         (* (* y3 y5) (- (* j y0) (* y a)))
         (if (<= a -760000000.0)
           (*
            y1
            (+
             (+ (* a t_5) (* y4 (- (* k y2) (* j y3))))
             (* i (- (* x j) (* z k)))))
           (if (<= a -6.6e-15)
             t_6
             (if (<= a -1.6e-144)
               (*
                c
                (+
                 (+ (* i (- (* z t) (* x y))) (* y0 t_1))
                 (* y4 (- (* y y3) (* t y2)))))
               (if (<= a 2.5e-160)
                 t_4
                 (if (<= a 5.8e-57)
                   (*
                    z
                    (+
                     (+ (* y3 (- (* a y1) (* c y0))) (* t (- (* c i) (* a b))))
                     t_2))
                   (if (<= a 4.2e+125)
                     t_4
                     (if (<= a 6.2e+165)
                       (*
                        t
                        (+
                         (-
                          (* j (- (* b y4) (* i y5)))
                          (* z (- (* a b) (* c i))))
                         (* y2 (- (* a y5) (* c y4)))))
                       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 = (x * y2) - (z * y3);
	double t_2 = k * ((b * y0) - (i * y1));
	double t_3 = (x * y) - (z * t);
	double t_4 = y0 * (((y5 * ((j * y3) - (k * y2))) + (c * t_1)) + (b * ((z * k) - (x * j))));
	double t_5 = (z * y3) - (x * y2);
	double t_6 = a * (((y1 * t_5) + (b * t_3)) + (y5 * ((t * y2) - (y * y3))));
	double tmp;
	if (a <= -3.4e+174) {
		tmp = b * (a * t_3);
	} else if (a <= -1.9e+110) {
		tmp = z * (t_2 - (c * (y0 * y3)));
	} else if (a <= -5.8e+91) {
		tmp = (y3 * y5) * ((j * y0) - (y * a));
	} else if (a <= -760000000.0) {
		tmp = y1 * (((a * t_5) + (y4 * ((k * y2) - (j * y3)))) + (i * ((x * j) - (z * k))));
	} else if (a <= -6.6e-15) {
		tmp = t_6;
	} else if (a <= -1.6e-144) {
		tmp = c * (((i * ((z * t) - (x * y))) + (y0 * t_1)) + (y4 * ((y * y3) - (t * y2))));
	} else if (a <= 2.5e-160) {
		tmp = t_4;
	} else if (a <= 5.8e-57) {
		tmp = z * (((y3 * ((a * y1) - (c * y0))) + (t * ((c * i) - (a * b)))) + t_2);
	} else if (a <= 4.2e+125) {
		tmp = t_4;
	} else if (a <= 6.2e+165) {
		tmp = t * (((j * ((b * y4) - (i * y5))) - (z * ((a * b) - (c * i)))) + (y2 * ((a * y5) - (c * y4))));
	} 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 = (x * y2) - (z * y3)
    t_2 = k * ((b * y0) - (i * y1))
    t_3 = (x * y) - (z * t)
    t_4 = y0 * (((y5 * ((j * y3) - (k * y2))) + (c * t_1)) + (b * ((z * k) - (x * j))))
    t_5 = (z * y3) - (x * y2)
    t_6 = a * (((y1 * t_5) + (b * t_3)) + (y5 * ((t * y2) - (y * y3))))
    if (a <= (-3.4d+174)) then
        tmp = b * (a * t_3)
    else if (a <= (-1.9d+110)) then
        tmp = z * (t_2 - (c * (y0 * y3)))
    else if (a <= (-5.8d+91)) then
        tmp = (y3 * y5) * ((j * y0) - (y * a))
    else if (a <= (-760000000.0d0)) then
        tmp = y1 * (((a * t_5) + (y4 * ((k * y2) - (j * y3)))) + (i * ((x * j) - (z * k))))
    else if (a <= (-6.6d-15)) then
        tmp = t_6
    else if (a <= (-1.6d-144)) then
        tmp = c * (((i * ((z * t) - (x * y))) + (y0 * t_1)) + (y4 * ((y * y3) - (t * y2))))
    else if (a <= 2.5d-160) then
        tmp = t_4
    else if (a <= 5.8d-57) then
        tmp = z * (((y3 * ((a * y1) - (c * y0))) + (t * ((c * i) - (a * b)))) + t_2)
    else if (a <= 4.2d+125) then
        tmp = t_4
    else if (a <= 6.2d+165) then
        tmp = t * (((j * ((b * y4) - (i * y5))) - (z * ((a * b) - (c * i)))) + (y2 * ((a * y5) - (c * y4))))
    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 = (x * y2) - (z * y3);
	double t_2 = k * ((b * y0) - (i * y1));
	double t_3 = (x * y) - (z * t);
	double t_4 = y0 * (((y5 * ((j * y3) - (k * y2))) + (c * t_1)) + (b * ((z * k) - (x * j))));
	double t_5 = (z * y3) - (x * y2);
	double t_6 = a * (((y1 * t_5) + (b * t_3)) + (y5 * ((t * y2) - (y * y3))));
	double tmp;
	if (a <= -3.4e+174) {
		tmp = b * (a * t_3);
	} else if (a <= -1.9e+110) {
		tmp = z * (t_2 - (c * (y0 * y3)));
	} else if (a <= -5.8e+91) {
		tmp = (y3 * y5) * ((j * y0) - (y * a));
	} else if (a <= -760000000.0) {
		tmp = y1 * (((a * t_5) + (y4 * ((k * y2) - (j * y3)))) + (i * ((x * j) - (z * k))));
	} else if (a <= -6.6e-15) {
		tmp = t_6;
	} else if (a <= -1.6e-144) {
		tmp = c * (((i * ((z * t) - (x * y))) + (y0 * t_1)) + (y4 * ((y * y3) - (t * y2))));
	} else if (a <= 2.5e-160) {
		tmp = t_4;
	} else if (a <= 5.8e-57) {
		tmp = z * (((y3 * ((a * y1) - (c * y0))) + (t * ((c * i) - (a * b)))) + t_2);
	} else if (a <= 4.2e+125) {
		tmp = t_4;
	} else if (a <= 6.2e+165) {
		tmp = t * (((j * ((b * y4) - (i * y5))) - (z * ((a * b) - (c * i)))) + (y2 * ((a * y5) - (c * y4))));
	} 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 = (x * y2) - (z * y3)
	t_2 = k * ((b * y0) - (i * y1))
	t_3 = (x * y) - (z * t)
	t_4 = y0 * (((y5 * ((j * y3) - (k * y2))) + (c * t_1)) + (b * ((z * k) - (x * j))))
	t_5 = (z * y3) - (x * y2)
	t_6 = a * (((y1 * t_5) + (b * t_3)) + (y5 * ((t * y2) - (y * y3))))
	tmp = 0
	if a <= -3.4e+174:
		tmp = b * (a * t_3)
	elif a <= -1.9e+110:
		tmp = z * (t_2 - (c * (y0 * y3)))
	elif a <= -5.8e+91:
		tmp = (y3 * y5) * ((j * y0) - (y * a))
	elif a <= -760000000.0:
		tmp = y1 * (((a * t_5) + (y4 * ((k * y2) - (j * y3)))) + (i * ((x * j) - (z * k))))
	elif a <= -6.6e-15:
		tmp = t_6
	elif a <= -1.6e-144:
		tmp = c * (((i * ((z * t) - (x * y))) + (y0 * t_1)) + (y4 * ((y * y3) - (t * y2))))
	elif a <= 2.5e-160:
		tmp = t_4
	elif a <= 5.8e-57:
		tmp = z * (((y3 * ((a * y1) - (c * y0))) + (t * ((c * i) - (a * b)))) + t_2)
	elif a <= 4.2e+125:
		tmp = t_4
	elif a <= 6.2e+165:
		tmp = t * (((j * ((b * y4) - (i * y5))) - (z * ((a * b) - (c * i)))) + (y2 * ((a * y5) - (c * y4))))
	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(x * y2) - Float64(z * y3))
	t_2 = Float64(k * Float64(Float64(b * y0) - Float64(i * y1)))
	t_3 = Float64(Float64(x * y) - Float64(z * t))
	t_4 = Float64(y0 * Float64(Float64(Float64(y5 * Float64(Float64(j * y3) - Float64(k * y2))) + Float64(c * t_1)) + Float64(b * Float64(Float64(z * k) - Float64(x * j)))))
	t_5 = Float64(Float64(z * y3) - Float64(x * y2))
	t_6 = Float64(a * Float64(Float64(Float64(y1 * t_5) + Float64(b * t_3)) + Float64(y5 * Float64(Float64(t * y2) - Float64(y * y3)))))
	tmp = 0.0
	if (a <= -3.4e+174)
		tmp = Float64(b * Float64(a * t_3));
	elseif (a <= -1.9e+110)
		tmp = Float64(z * Float64(t_2 - Float64(c * Float64(y0 * y3))));
	elseif (a <= -5.8e+91)
		tmp = Float64(Float64(y3 * y5) * Float64(Float64(j * y0) - Float64(y * a)));
	elseif (a <= -760000000.0)
		tmp = Float64(y1 * Float64(Float64(Float64(a * t_5) + Float64(y4 * Float64(Float64(k * y2) - Float64(j * y3)))) + Float64(i * Float64(Float64(x * j) - Float64(z * k)))));
	elseif (a <= -6.6e-15)
		tmp = t_6;
	elseif (a <= -1.6e-144)
		tmp = Float64(c * Float64(Float64(Float64(i * Float64(Float64(z * t) - Float64(x * y))) + Float64(y0 * t_1)) + Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2)))));
	elseif (a <= 2.5e-160)
		tmp = t_4;
	elseif (a <= 5.8e-57)
		tmp = Float64(z * Float64(Float64(Float64(y3 * Float64(Float64(a * y1) - Float64(c * y0))) + Float64(t * Float64(Float64(c * i) - Float64(a * b)))) + t_2));
	elseif (a <= 4.2e+125)
		tmp = t_4;
	elseif (a <= 6.2e+165)
		tmp = Float64(t * Float64(Float64(Float64(j * Float64(Float64(b * y4) - Float64(i * y5))) - Float64(z * Float64(Float64(a * b) - Float64(c * i)))) + Float64(y2 * Float64(Float64(a * y5) - Float64(c * y4)))));
	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 = (x * y2) - (z * y3);
	t_2 = k * ((b * y0) - (i * y1));
	t_3 = (x * y) - (z * t);
	t_4 = y0 * (((y5 * ((j * y3) - (k * y2))) + (c * t_1)) + (b * ((z * k) - (x * j))));
	t_5 = (z * y3) - (x * y2);
	t_6 = a * (((y1 * t_5) + (b * t_3)) + (y5 * ((t * y2) - (y * y3))));
	tmp = 0.0;
	if (a <= -3.4e+174)
		tmp = b * (a * t_3);
	elseif (a <= -1.9e+110)
		tmp = z * (t_2 - (c * (y0 * y3)));
	elseif (a <= -5.8e+91)
		tmp = (y3 * y5) * ((j * y0) - (y * a));
	elseif (a <= -760000000.0)
		tmp = y1 * (((a * t_5) + (y4 * ((k * y2) - (j * y3)))) + (i * ((x * j) - (z * k))));
	elseif (a <= -6.6e-15)
		tmp = t_6;
	elseif (a <= -1.6e-144)
		tmp = c * (((i * ((z * t) - (x * y))) + (y0 * t_1)) + (y4 * ((y * y3) - (t * y2))));
	elseif (a <= 2.5e-160)
		tmp = t_4;
	elseif (a <= 5.8e-57)
		tmp = z * (((y3 * ((a * y1) - (c * y0))) + (t * ((c * i) - (a * b)))) + t_2);
	elseif (a <= 4.2e+125)
		tmp = t_4;
	elseif (a <= 6.2e+165)
		tmp = t * (((j * ((b * y4) - (i * y5))) - (z * ((a * b) - (c * i)))) + (y2 * ((a * y5) - (c * y4))));
	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[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(k * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(y0 * N[(N[(N[(y5 * N[(N[(j * y3), $MachinePrecision] - N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(c * t$95$1), $MachinePrecision]), $MachinePrecision] + N[(b * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(N[(z * y3), $MachinePrecision] - N[(x * y2), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$6 = N[(a * N[(N[(N[(y1 * t$95$5), $MachinePrecision] + N[(b * t$95$3), $MachinePrecision]), $MachinePrecision] + N[(y5 * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -3.4e+174], N[(b * N[(a * t$95$3), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -1.9e+110], N[(z * N[(t$95$2 - N[(c * N[(y0 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -5.8e+91], N[(N[(y3 * y5), $MachinePrecision] * N[(N[(j * y0), $MachinePrecision] - N[(y * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -760000000.0], N[(y1 * N[(N[(N[(a * t$95$5), $MachinePrecision] + N[(y4 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(i * N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -6.6e-15], t$95$6, If[LessEqual[a, -1.6e-144], N[(c * N[(N[(N[(i * N[(N[(z * t), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * t$95$1), $MachinePrecision]), $MachinePrecision] + N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 2.5e-160], t$95$4, If[LessEqual[a, 5.8e-57], N[(z * N[(N[(N[(y3 * N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(t * N[(N[(c * i), $MachinePrecision] - N[(a * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$2), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 4.2e+125], t$95$4, If[LessEqual[a, 6.2e+165], N[(t * N[(N[(N[(j * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(z * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y2 * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$6]]]]]]]]]]]]]]]]

Derivation

1. Split input into 9 regimes

2. if a < -3.4000000000000001e174

   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. Taylor expanded in b around inf 44.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 69.0%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 69.0%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 69.0%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 69.0%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 69.0%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 69.0%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   if -3.4000000000000001e174 < a < -1.89999999999999994e110

   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. Taylor expanded in z around -inf 63.9%

      \[\leadsto \color{blue}{-1 \cdot \left(z \cdot \left(\left(t \cdot \left(a \cdot b - c \cdot i\right) + y3 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   3. Taylor expanded in y0 around inf 73.2%

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

      1. *-commutative 73.2%

         \[\leadsto -1 \cdot \left(z \cdot \left(c \cdot \color{blue}{\left(y3 \cdot y0\right)} - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) \]

   5. Simplified 73.2%

      \[\leadsto -1 \cdot \left(z \cdot \left(\color{blue}{c \cdot \left(y3 \cdot y0\right)} - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) \]

   if -1.89999999999999994e110 < a < -5.80000000000000028e91

   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. Taylor expanded in y3 around -inf 50.0%

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

   3. Taylor expanded in y5 around inf 75.0%

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

      1. associate-*r* 75.0%

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

      2. distribute-lft-out-- 75.0%

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

      3. *-commutative 75.0%

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

   5. Simplified 75.0%

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

   if -5.80000000000000028e91 < a < -7.6e8

   1. Initial program 52.5%

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

   2. Taylor expanded in y1 around inf 73.8%

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

   if -7.6e8 < a < -6.6e-15 or 6.2000000000000003e165 < a

   1. Initial program 33.5%

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

   2. Taylor expanded in a around inf 74.7%

      \[\leadsto \color{blue}{a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   if -6.6e-15 < a < -1.59999999999999986e-144

   1. Initial program 45.5%

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

   2. Taylor expanded in c around inf 77.7%

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

   if -1.59999999999999986e-144 < a < 2.49999999999999997e-160 or 5.8000000000000005e-57 < a < 4.2000000000000001e125

   1. Initial program 33.5%

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

   2. Taylor expanded in y0 around inf 56.1%

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

   if 2.49999999999999997e-160 < a < 5.8000000000000005e-57

   1. Initial program 18.0%

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

   2. Taylor expanded in z around -inf 71.2%

      \[\leadsto \color{blue}{-1 \cdot \left(z \cdot \left(\left(t \cdot \left(a \cdot b - c \cdot i\right) + y3 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   if 4.2000000000000001e125 < a < 6.2000000000000003e165

   1. Initial program 1.4%

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

   2. Taylor expanded in t around inf 85.7%

      \[\leadsto \color{blue}{t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]
3. Recombined 9 regimes into one program.

4. Final simplification 66.6%

   \[\leadsto \begin{array}{l} \mathbf{if}\;a \leq -3.4 \cdot 10^{+174}:\\ \;\;\;\;b \cdot \left(a \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;a \leq -1.9 \cdot 10^{+110}:\\ \;\;\;\;z \cdot \left(k \cdot \left(b \cdot y0 - i \cdot y1\right) - c \cdot \left(y0 \cdot y3\right)\right)\\ \mathbf{elif}\;a \leq -5.8 \cdot 10^{+91}:\\ \;\;\;\;\left(y3 \cdot y5\right) \cdot \left(j \cdot y0 - y \cdot a\right)\\ \mathbf{elif}\;a \leq -760000000:\\ \;\;\;\;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}\;a \leq -6.6 \cdot 10^{-15}:\\ \;\;\;\;a \cdot \left(\left(y1 \cdot \left(z \cdot y3 - x \cdot y2\right) + b \cdot \left(x \cdot y - z \cdot t\right)\right) + y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \mathbf{elif}\;a \leq -1.6 \cdot 10^{-144}:\\ \;\;\;\;c \cdot \left(\left(i \cdot \left(z \cdot t - x \cdot y\right) + y0 \cdot \left(x \cdot y2 - z \cdot y3\right)\right) + y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;a \leq 2.5 \cdot 10^{-160}:\\ \;\;\;\;y0 \cdot \left(\left(y5 \cdot \left(j \cdot y3 - k \cdot y2\right) + c \cdot \left(x \cdot y2 - z \cdot y3\right)\right) + b \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;a \leq 5.8 \cdot 10^{-57}:\\ \;\;\;\;z \cdot \left(\left(y3 \cdot \left(a \cdot y1 - c \cdot y0\right) + t \cdot \left(c \cdot i - a \cdot b\right)\right) + k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;a \leq 4.2 \cdot 10^{+125}:\\ \;\;\;\;y0 \cdot \left(\left(y5 \cdot \left(j \cdot y3 - k \cdot y2\right) + c \cdot \left(x \cdot y2 - z \cdot y3\right)\right) + b \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;a \leq 6.2 \cdot 10^{+165}:\\ \;\;\;\;t \cdot \left(\left(j \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(a \cdot b - c \cdot i\right)\right) + y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(\left(y1 \cdot \left(z \cdot y3 - x \cdot y2\right) + b \cdot \left(x \cdot y - z \cdot t\right)\right) + y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \end{array} \]

Alternative 2: 53.1% accurate, 0.5× speedup

Math

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

FPCore

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

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

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (x * y2) - (z * y3)
	t_2 = (((((((a * b) - (c * i)) * ((x * y) - (z * t))) + (((x * j) - (z * k)) * ((i * y1) - (b * y0)))) + (t_1 * ((c * y0) - (a * y1)))) + (((b * y4) - (i * y5)) * ((t * j) - (y * k)))) + (((t * y2) - (y * y3)) * ((a * y5) - (c * y4)))) + (((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5)))
	tmp = 0
	if t_2 <= math.inf:
		tmp = t_2
	else:
		tmp = y0 * (((y5 * ((j * y3) - (k * y2))) + (c * t_1)) + (b * ((z * k) - (x * j))))
	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(x * y2) - Float64(z * y3))
	t_2 = Float64(Float64(Float64(Float64(Float64(Float64(Float64(Float64(a * b) - Float64(c * i)) * Float64(Float64(x * y) - Float64(z * t))) + Float64(Float64(Float64(x * j) - Float64(z * k)) * Float64(Float64(i * y1) - Float64(b * y0)))) + Float64(t_1 * Float64(Float64(c * y0) - Float64(a * y1)))) + Float64(Float64(Float64(b * y4) - Float64(i * y5)) * Float64(Float64(t * j) - Float64(y * k)))) + Float64(Float64(Float64(t * y2) - Float64(y * y3)) * Float64(Float64(a * y5) - Float64(c * y4)))) + Float64(Float64(Float64(k * y2) - Float64(j * y3)) * Float64(Float64(y1 * y4) - Float64(y0 * y5))))
	tmp = 0.0
	if (t_2 <= Inf)
		tmp = t_2;
	else
		tmp = Float64(y0 * Float64(Float64(Float64(y5 * Float64(Float64(j * y3) - Float64(k * y2))) + Float64(c * t_1)) + Float64(b * Float64(Float64(z * k) - Float64(x * j)))));
	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 = (x * y2) - (z * y3);
	t_2 = (((((((a * b) - (c * i)) * ((x * y) - (z * t))) + (((x * j) - (z * k)) * ((i * y1) - (b * y0)))) + (t_1 * ((c * y0) - (a * y1)))) + (((b * y4) - (i * y5)) * ((t * j) - (y * k)))) + (((t * y2) - (y * y3)) * ((a * y5) - (c * y4)))) + (((k * y2) - (j * y3)) * ((y1 * y4) - (y0 * y5)));
	tmp = 0.0;
	if (t_2 <= Inf)
		tmp = t_2;
	else
		tmp = y0 * (((y5 * ((j * y3) - (k * y2))) + (c * t_1)) + (b * ((z * k) - (x * j))));
	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[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(N[(N[(N[(N[(N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision] * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision] * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(t$95$1 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision] * N[(N[(t * j), $MachinePrecision] - N[(y * k), $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] + N[(N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision] * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$2, Infinity], t$95$2, N[(y0 * N[(N[(N[(y5 * N[(N[(j * y3), $MachinePrecision] - N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(c * t$95$1), $MachinePrecision]), $MachinePrecision] + N[(b * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]

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 91.9%

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

   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. Taylor expanded in y0 around inf 40.6%

      \[\leadsto \color{blue}{y0 \cdot \left(\left(-1 \cdot \left(y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - b \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
3. Recombined 2 regimes into one program.

4. Final simplification 59.4%

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

Alternative 3: 30.9% accurate, 1.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := z \cdot \left(k \cdot \left(b \cdot y0 - i \cdot y1\right) - c \cdot \left(y0 \cdot y3\right)\right)\\ t_2 := a \cdot \left(x \cdot y - z \cdot t\right)\\ \mathbf{if}\;a \leq -2.5 \cdot 10^{+170}:\\ \;\;\;\;b \cdot t_2\\ \mathbf{elif}\;a \leq -7.5 \cdot 10^{+110}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -1.85 \cdot 10^{+90}:\\ \;\;\;\;\left(y3 \cdot y5\right) \cdot \left(j \cdot y0 - y \cdot a\right)\\ \mathbf{elif}\;a \leq -1.5 \cdot 10^{+57}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;a \leq -1.9 \cdot 10^{+32}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;a \leq -4.85 \cdot 10^{-29}:\\ \;\;\;\;k \cdot \left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \mathbf{elif}\;a \leq -9.5 \cdot 10^{-148}:\\ \;\;\;\;y0 \cdot \left(x \cdot \left(c \cdot y2 - b \cdot j\right)\right)\\ \mathbf{elif}\;a \leq -3.8 \cdot 10^{-224}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \mathbf{elif}\;a \leq -1.1 \cdot 10^{-235}:\\ \;\;\;\;b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ \mathbf{elif}\;a \leq 7.5 \cdot 10^{-158}:\\ \;\;\;\;\left(k \cdot y0\right) \cdot \left(z \cdot b - y2 \cdot y5\right)\\ \mathbf{elif}\;a \leq 1.36 \cdot 10^{-34}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 8 \cdot 10^{+53}:\\ \;\;\;\;b \cdot \left(\left(t_2 + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{else}:\\ \;\;\;\;z \cdot \left(y3 \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* z (- (* k (- (* b y0) (* i y1))) (* c (* y0 y3)))))
        (t_2 (* a (- (* x y) (* z t)))))
   (if (<= a -2.5e+170)
     (* b t_2)
     (if (<= a -7.5e+110)
       t_1
       (if (<= a -1.85e+90)
         (* (* y3 y5) (- (* j y0) (* y a)))
         (if (<= a -1.5e+57)
           (* i (* k (- (* y y5) (* z y1))))
           (if (<= a -1.9e+32)
             (* j (* x (- (* i y1) (* b y0))))
             (if (<= a -4.85e-29)
               (* k (* y4 (- (* y1 y2) (* y b))))
               (if (<= a -9.5e-148)
                 (* y0 (* x (- (* c y2) (* b j))))
                 (if (<= a -3.8e-224)
                   (* k (* y1 (- (* y2 y4) (* z i))))
                   (if (<= a -1.1e-235)
                     (* b (* t (- (* j y4) (* z a))))
                     (if (<= a 7.5e-158)
                       (* (* k y0) (- (* z b) (* y2 y5)))
                       (if (<= a 1.36e-34)
                         t_1
                         (if (<= a 8e+53)
                           (*
                            b
                            (+
                             (+ t_2 (* y4 (- (* t j) (* y k))))
                             (* y0 (- (* z k) (* x j)))))
                           (* z (* y3 (- (* 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 = z * ((k * ((b * y0) - (i * y1))) - (c * (y0 * y3)));
	double t_2 = a * ((x * y) - (z * t));
	double tmp;
	if (a <= -2.5e+170) {
		tmp = b * t_2;
	} else if (a <= -7.5e+110) {
		tmp = t_1;
	} else if (a <= -1.85e+90) {
		tmp = (y3 * y5) * ((j * y0) - (y * a));
	} else if (a <= -1.5e+57) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (a <= -1.9e+32) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (a <= -4.85e-29) {
		tmp = k * (y4 * ((y1 * y2) - (y * b)));
	} else if (a <= -9.5e-148) {
		tmp = y0 * (x * ((c * y2) - (b * j)));
	} else if (a <= -3.8e-224) {
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	} else if (a <= -1.1e-235) {
		tmp = b * (t * ((j * y4) - (z * a)));
	} else if (a <= 7.5e-158) {
		tmp = (k * y0) * ((z * b) - (y2 * y5));
	} else if (a <= 1.36e-34) {
		tmp = t_1;
	} else if (a <= 8e+53) {
		tmp = b * ((t_2 + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))));
	} else {
		tmp = z * (y3 * ((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 = z * ((k * ((b * y0) - (i * y1))) - (c * (y0 * y3)))
    t_2 = a * ((x * y) - (z * t))
    if (a <= (-2.5d+170)) then
        tmp = b * t_2
    else if (a <= (-7.5d+110)) then
        tmp = t_1
    else if (a <= (-1.85d+90)) then
        tmp = (y3 * y5) * ((j * y0) - (y * a))
    else if (a <= (-1.5d+57)) then
        tmp = i * (k * ((y * y5) - (z * y1)))
    else if (a <= (-1.9d+32)) then
        tmp = j * (x * ((i * y1) - (b * y0)))
    else if (a <= (-4.85d-29)) then
        tmp = k * (y4 * ((y1 * y2) - (y * b)))
    else if (a <= (-9.5d-148)) then
        tmp = y0 * (x * ((c * y2) - (b * j)))
    else if (a <= (-3.8d-224)) then
        tmp = k * (y1 * ((y2 * y4) - (z * i)))
    else if (a <= (-1.1d-235)) then
        tmp = b * (t * ((j * y4) - (z * a)))
    else if (a <= 7.5d-158) then
        tmp = (k * y0) * ((z * b) - (y2 * y5))
    else if (a <= 1.36d-34) then
        tmp = t_1
    else if (a <= 8d+53) then
        tmp = b * ((t_2 + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))))
    else
        tmp = z * (y3 * ((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 = z * ((k * ((b * y0) - (i * y1))) - (c * (y0 * y3)));
	double t_2 = a * ((x * y) - (z * t));
	double tmp;
	if (a <= -2.5e+170) {
		tmp = b * t_2;
	} else if (a <= -7.5e+110) {
		tmp = t_1;
	} else if (a <= -1.85e+90) {
		tmp = (y3 * y5) * ((j * y0) - (y * a));
	} else if (a <= -1.5e+57) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (a <= -1.9e+32) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (a <= -4.85e-29) {
		tmp = k * (y4 * ((y1 * y2) - (y * b)));
	} else if (a <= -9.5e-148) {
		tmp = y0 * (x * ((c * y2) - (b * j)));
	} else if (a <= -3.8e-224) {
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	} else if (a <= -1.1e-235) {
		tmp = b * (t * ((j * y4) - (z * a)));
	} else if (a <= 7.5e-158) {
		tmp = (k * y0) * ((z * b) - (y2 * y5));
	} else if (a <= 1.36e-34) {
		tmp = t_1;
	} else if (a <= 8e+53) {
		tmp = b * ((t_2 + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))));
	} else {
		tmp = z * (y3 * ((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 = z * ((k * ((b * y0) - (i * y1))) - (c * (y0 * y3)))
	t_2 = a * ((x * y) - (z * t))
	tmp = 0
	if a <= -2.5e+170:
		tmp = b * t_2
	elif a <= -7.5e+110:
		tmp = t_1
	elif a <= -1.85e+90:
		tmp = (y3 * y5) * ((j * y0) - (y * a))
	elif a <= -1.5e+57:
		tmp = i * (k * ((y * y5) - (z * y1)))
	elif a <= -1.9e+32:
		tmp = j * (x * ((i * y1) - (b * y0)))
	elif a <= -4.85e-29:
		tmp = k * (y4 * ((y1 * y2) - (y * b)))
	elif a <= -9.5e-148:
		tmp = y0 * (x * ((c * y2) - (b * j)))
	elif a <= -3.8e-224:
		tmp = k * (y1 * ((y2 * y4) - (z * i)))
	elif a <= -1.1e-235:
		tmp = b * (t * ((j * y4) - (z * a)))
	elif a <= 7.5e-158:
		tmp = (k * y0) * ((z * b) - (y2 * y5))
	elif a <= 1.36e-34:
		tmp = t_1
	elif a <= 8e+53:
		tmp = b * ((t_2 + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))))
	else:
		tmp = z * (y3 * ((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(z * Float64(Float64(k * Float64(Float64(b * y0) - Float64(i * y1))) - Float64(c * Float64(y0 * y3))))
	t_2 = Float64(a * Float64(Float64(x * y) - Float64(z * t)))
	tmp = 0.0
	if (a <= -2.5e+170)
		tmp = Float64(b * t_2);
	elseif (a <= -7.5e+110)
		tmp = t_1;
	elseif (a <= -1.85e+90)
		tmp = Float64(Float64(y3 * y5) * Float64(Float64(j * y0) - Float64(y * a)));
	elseif (a <= -1.5e+57)
		tmp = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))));
	elseif (a <= -1.9e+32)
		tmp = Float64(j * Float64(x * Float64(Float64(i * y1) - Float64(b * y0))));
	elseif (a <= -4.85e-29)
		tmp = Float64(k * Float64(y4 * Float64(Float64(y1 * y2) - Float64(y * b))));
	elseif (a <= -9.5e-148)
		tmp = Float64(y0 * Float64(x * Float64(Float64(c * y2) - Float64(b * j))));
	elseif (a <= -3.8e-224)
		tmp = Float64(k * Float64(y1 * Float64(Float64(y2 * y4) - Float64(z * i))));
	elseif (a <= -1.1e-235)
		tmp = Float64(b * Float64(t * Float64(Float64(j * y4) - Float64(z * a))));
	elseif (a <= 7.5e-158)
		tmp = Float64(Float64(k * y0) * Float64(Float64(z * b) - Float64(y2 * y5)));
	elseif (a <= 1.36e-34)
		tmp = t_1;
	elseif (a <= 8e+53)
		tmp = Float64(b * Float64(Float64(t_2 + Float64(y4 * Float64(Float64(t * j) - Float64(y * k)))) + Float64(y0 * Float64(Float64(z * k) - Float64(x * j)))));
	else
		tmp = Float64(z * Float64(y3 * 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 = z * ((k * ((b * y0) - (i * y1))) - (c * (y0 * y3)));
	t_2 = a * ((x * y) - (z * t));
	tmp = 0.0;
	if (a <= -2.5e+170)
		tmp = b * t_2;
	elseif (a <= -7.5e+110)
		tmp = t_1;
	elseif (a <= -1.85e+90)
		tmp = (y3 * y5) * ((j * y0) - (y * a));
	elseif (a <= -1.5e+57)
		tmp = i * (k * ((y * y5) - (z * y1)));
	elseif (a <= -1.9e+32)
		tmp = j * (x * ((i * y1) - (b * y0)));
	elseif (a <= -4.85e-29)
		tmp = k * (y4 * ((y1 * y2) - (y * b)));
	elseif (a <= -9.5e-148)
		tmp = y0 * (x * ((c * y2) - (b * j)));
	elseif (a <= -3.8e-224)
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	elseif (a <= -1.1e-235)
		tmp = b * (t * ((j * y4) - (z * a)));
	elseif (a <= 7.5e-158)
		tmp = (k * y0) * ((z * b) - (y2 * y5));
	elseif (a <= 1.36e-34)
		tmp = t_1;
	elseif (a <= 8e+53)
		tmp = b * ((t_2 + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))));
	else
		tmp = z * (y3 * ((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[(z * N[(N[(k * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(c * N[(y0 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(a * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -2.5e+170], N[(b * t$95$2), $MachinePrecision], If[LessEqual[a, -7.5e+110], t$95$1, If[LessEqual[a, -1.85e+90], N[(N[(y3 * y5), $MachinePrecision] * N[(N[(j * y0), $MachinePrecision] - N[(y * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -1.5e+57], N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -1.9e+32], N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -4.85e-29], N[(k * N[(y4 * N[(N[(y1 * y2), $MachinePrecision] - N[(y * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -9.5e-148], N[(y0 * N[(x * N[(N[(c * y2), $MachinePrecision] - N[(b * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -3.8e-224], N[(k * N[(y1 * N[(N[(y2 * y4), $MachinePrecision] - N[(z * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -1.1e-235], N[(b * N[(t * N[(N[(j * y4), $MachinePrecision] - N[(z * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 7.5e-158], N[(N[(k * y0), $MachinePrecision] * N[(N[(z * b), $MachinePrecision] - N[(y2 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 1.36e-34], t$95$1, If[LessEqual[a, 8e+53], N[(b * N[(N[(t$95$2 + N[(y4 * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(z * N[(y3 * N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]]]

Derivation

1. Split input into 12 regimes

2. if a < -2.49999999999999988e170

   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. Taylor expanded in b around inf 44.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 69.0%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 69.0%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 69.0%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 69.0%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 69.0%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 69.0%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   if -2.49999999999999988e170 < a < -7.5e110 or 7.5e-158 < a < 1.3600000000000001e-34

   1. Initial program 15.4%

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

   2. Taylor expanded in z around -inf 69.7%

      \[\leadsto \color{blue}{-1 \cdot \left(z \cdot \left(\left(t \cdot \left(a \cdot b - c \cdot i\right) + y3 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   3. Taylor expanded in y0 around inf 66.0%

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

      1. *-commutative 66.0%

         \[\leadsto -1 \cdot \left(z \cdot \left(c \cdot \color{blue}{\left(y3 \cdot y0\right)} - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) \]

   5. Simplified 66.0%

      \[\leadsto -1 \cdot \left(z \cdot \left(\color{blue}{c \cdot \left(y3 \cdot y0\right)} - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) \]

   if -7.5e110 < a < -1.85e90

   1. Initial program 40.0%

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

   2. Taylor expanded in y3 around -inf 60.0%

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

   3. Taylor expanded in y5 around inf 80.0%

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

      1. associate-*r* 80.0%

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

      2. distribute-lft-out-- 80.0%

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

      3. *-commutative 80.0%

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

   5. Simplified 80.0%

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

   if -1.85e90 < a < -1.5e57

   1. Initial program 42.6%

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

   2. Taylor expanded in k around inf 50.8%

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

   3. Taylor expanded in i around inf 86.2%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - y1 \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 86.2%

         \[\leadsto i \cdot \left(k \cdot \left(y \cdot y5 - \color{blue}{z \cdot y1}\right)\right) \]

   5. Simplified 86.2%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)} \]

   if -1.5e57 < a < -1.9000000000000002e32

   1. Initial program 50.0%

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

   2. Taylor expanded in j around inf 83.3%

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

   3. Taylor expanded in x around inf 100.0%

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

      1. *-commutative 100.0%

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

      2. *-commutative 100.0%

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

      3. *-commutative 100.0%

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

   5. Simplified 100.0%

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

   if -1.9000000000000002e32 < a < -4.8500000000000001e-29

   1. Initial program 49.9%

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

   2. Taylor expanded in k around inf 50.7%

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

   3. Taylor expanded in y4 around inf 52.2%

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

      1. +-commutative 52.2%

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

      2. mul-1-neg 52.2%

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

      3. unsub-neg 52.2%

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

   5. Simplified 52.2%

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

   if -4.8500000000000001e-29 < a < -9.50000000000000069e-148

   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. Taylor expanded in y0 around inf 31.5%

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

   3. Taylor expanded in x around inf 50.8%

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

   if -9.50000000000000069e-148 < a < -3.80000000000000002e-224

   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. Taylor expanded in k around inf 41.5%

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

   3. Taylor expanded in y1 around inf 65.4%

      \[\leadsto \color{blue}{k \cdot \left(y1 \cdot \left(y2 \cdot y4 - i \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 65.4%

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

      2. *-commutative 65.4%

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

   5. Simplified 65.4%

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

   if -3.80000000000000002e-224 < a < -1.09999999999999992e-235

   1. Initial program 26.2%

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

   2. Taylor expanded in b around inf 52.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in t around inf 65.5%

      \[\leadsto b \cdot \color{blue}{\left(t \cdot \left(-1 \cdot \left(a \cdot z\right) + j \cdot y4\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 65.5%

         \[\leadsto b \cdot \left(t \cdot \color{blue}{\left(j \cdot y4 + -1 \cdot \left(a \cdot z\right)\right)}\right) \]

      2. mul-1-neg 65.5%

         \[\leadsto b \cdot \left(t \cdot \left(j \cdot y4 + \color{blue}{\left(-a \cdot z\right)}\right)\right) \]

      3. unsub-neg 65.5%

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

      4. *-commutative 65.5%

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

      5. *-commutative 65.5%

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

   5. Simplified 65.5%

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

   if -1.09999999999999992e-235 < a < 7.5e-158

   1. Initial program 37.8%

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

   2. Taylor expanded in y0 around inf 51.2%

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

   3. Taylor expanded in k around inf 45.3%

      \[\leadsto \color{blue}{k \cdot \left(y0 \cdot \left(-1 \cdot \left(y2 \cdot y5\right) - -1 \cdot \left(b \cdot z\right)\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 49.1%

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

      2. distribute-lft-out-- 49.1%

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

      3. *-commutative 49.1%

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

   5. Simplified 49.1%

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

   if 1.3600000000000001e-34 < a < 7.9999999999999999e53

   1. Initial program 26.9%

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

   2. Taylor expanded in b around inf 50.6%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   if 7.9999999999999999e53 < a

   1. Initial program 32.4%

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

   2. Taylor expanded in y3 around -inf 47.2%

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

   3. Taylor expanded in z around inf 55.2%

      \[\leadsto -1 \cdot \color{blue}{\left(y3 \cdot \left(z \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 55.2%

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

      2. associate-*l* 57.0%

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

   5. Simplified 57.0%

      \[\leadsto -1 \cdot \color{blue}{\left(z \cdot \left(\left(c \cdot y0 - a \cdot y1\right) \cdot y3\right)\right)} \]
3. Recombined 12 regimes into one program.

4. Final simplification 59.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;a \leq -2.5 \cdot 10^{+170}:\\ \;\;\;\;b \cdot \left(a \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;a \leq -7.5 \cdot 10^{+110}:\\ \;\;\;\;z \cdot \left(k \cdot \left(b \cdot y0 - i \cdot y1\right) - c \cdot \left(y0 \cdot y3\right)\right)\\ \mathbf{elif}\;a \leq -1.85 \cdot 10^{+90}:\\ \;\;\;\;\left(y3 \cdot y5\right) \cdot \left(j \cdot y0 - y \cdot a\right)\\ \mathbf{elif}\;a \leq -1.5 \cdot 10^{+57}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;a \leq -1.9 \cdot 10^{+32}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;a \leq -4.85 \cdot 10^{-29}:\\ \;\;\;\;k \cdot \left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \mathbf{elif}\;a \leq -9.5 \cdot 10^{-148}:\\ \;\;\;\;y0 \cdot \left(x \cdot \left(c \cdot y2 - b \cdot j\right)\right)\\ \mathbf{elif}\;a \leq -3.8 \cdot 10^{-224}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \mathbf{elif}\;a \leq -1.1 \cdot 10^{-235}:\\ \;\;\;\;b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ \mathbf{elif}\;a \leq 7.5 \cdot 10^{-158}:\\ \;\;\;\;\left(k \cdot y0\right) \cdot \left(z \cdot b - y2 \cdot y5\right)\\ \mathbf{elif}\;a \leq 1.36 \cdot 10^{-34}:\\ \;\;\;\;z \cdot \left(k \cdot \left(b \cdot y0 - i \cdot y1\right) - c \cdot \left(y0 \cdot y3\right)\right)\\ \mathbf{elif}\;a \leq 8 \cdot 10^{+53}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{else}:\\ \;\;\;\;z \cdot \left(y3 \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\\ \end{array} \]

Alternative 4: 36.5% accurate, 1.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) + \left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\right)\\ t_2 := t \cdot j - y \cdot k\\ t_3 := c \cdot y0 - a \cdot y1\\ \mathbf{if}\;t \leq -1.02 \cdot 10^{+216}:\\ \;\;\;\;t \cdot \left(z \cdot \left(c \cdot i - a \cdot b\right)\right)\\ \mathbf{elif}\;t \leq -5.8 \cdot 10^{+104}:\\ \;\;\;\;j \cdot \left(y4 \cdot \left(t \cdot b - y1 \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq -3.5 \cdot 10^{+29}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq -0.023:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;t \leq -4.8 \cdot 10^{-152}:\\ \;\;\;\;x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot t_3\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 3.8 \cdot 10^{-292}:\\ \;\;\;\;y4 \cdot \left(\left(b \cdot t_2 + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq 1.05 \cdot 10^{-213}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq 3.7 \cdot 10^{-171}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot t_2\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;t \leq 1.52 \cdot 10^{+60}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq 1.8 \cdot 10^{+105} \lor \neg \left(t \leq 8.8 \cdot 10^{+171}\right):\\ \;\;\;\;b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot t_3\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1
         (*
          y3
          (+
           (* y (- (* c y4) (* a y5)))
           (+ (* j (- (* y0 y5) (* y1 y4))) (* z (- (* a y1) (* c y0)))))))
        (t_2 (- (* t j) (* y k)))
        (t_3 (- (* c y0) (* a y1))))
   (if (<= t -1.02e+216)
     (* t (* z (- (* c i) (* a b))))
     (if (<= t -5.8e+104)
       (* j (* y4 (- (* t b) (* y1 y3))))
       (if (<= t -3.5e+29)
         (* i (* k (- (* y y5) (* z y1))))
         (if (<= t -0.023)
           (* j (* y0 (- (* y3 y5) (* x b))))
           (if (<= t -4.8e-152)
             (*
              x
              (+
               (+ (* y (- (* a b) (* c i))) (* y2 t_3))
               (* j (- (* i y1) (* b y0)))))
             (if (<= t 3.8e-292)
               (*
                y4
                (+
                 (+ (* b t_2) (* y1 (- (* k y2) (* j y3))))
                 (* c (- (* y y3) (* t y2)))))
               (if (<= t 1.05e-213)
                 t_1
                 (if (<= t 3.7e-171)
                   (*
                    b
                    (+
                     (+ (* a (- (* x y) (* z t))) (* y4 t_2))
                     (* y0 (- (* z k) (* x j)))))
                   (if (<= t 1.52e+60)
                     t_1
                     (if (or (<= t 1.8e+105) (not (<= t 8.8e+171)))
                       (* b (* t (- (* j y4) (* z a))))
                       (*
                        y2
                        (+
                         (+ (* k (- (* y1 y4) (* y0 y5))) (* x t_3))
                         (* t (- (* a y5) (* c y4)))))))))))))))))

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 = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))));
	double t_2 = (t * j) - (y * k);
	double t_3 = (c * y0) - (a * y1);
	double tmp;
	if (t <= -1.02e+216) {
		tmp = t * (z * ((c * i) - (a * b)));
	} else if (t <= -5.8e+104) {
		tmp = j * (y4 * ((t * b) - (y1 * y3)));
	} else if (t <= -3.5e+29) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (t <= -0.023) {
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	} else if (t <= -4.8e-152) {
		tmp = x * (((y * ((a * b) - (c * i))) + (y2 * t_3)) + (j * ((i * y1) - (b * y0))));
	} else if (t <= 3.8e-292) {
		tmp = y4 * (((b * t_2) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	} else if (t <= 1.05e-213) {
		tmp = t_1;
	} else if (t <= 3.7e-171) {
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * t_2)) + (y0 * ((z * k) - (x * j))));
	} else if (t <= 1.52e+60) {
		tmp = t_1;
	} else if ((t <= 1.8e+105) || !(t <= 8.8e+171)) {
		tmp = b * (t * ((j * y4) - (z * a)));
	} else {
		tmp = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * t_3)) + (t * ((a * y5) - (c * y4))));
	}
	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 = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))))
    t_2 = (t * j) - (y * k)
    t_3 = (c * y0) - (a * y1)
    if (t <= (-1.02d+216)) then
        tmp = t * (z * ((c * i) - (a * b)))
    else if (t <= (-5.8d+104)) then
        tmp = j * (y4 * ((t * b) - (y1 * y3)))
    else if (t <= (-3.5d+29)) then
        tmp = i * (k * ((y * y5) - (z * y1)))
    else if (t <= (-0.023d0)) then
        tmp = j * (y0 * ((y3 * y5) - (x * b)))
    else if (t <= (-4.8d-152)) then
        tmp = x * (((y * ((a * b) - (c * i))) + (y2 * t_3)) + (j * ((i * y1) - (b * y0))))
    else if (t <= 3.8d-292) then
        tmp = y4 * (((b * t_2) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))))
    else if (t <= 1.05d-213) then
        tmp = t_1
    else if (t <= 3.7d-171) then
        tmp = b * (((a * ((x * y) - (z * t))) + (y4 * t_2)) + (y0 * ((z * k) - (x * j))))
    else if (t <= 1.52d+60) then
        tmp = t_1
    else if ((t <= 1.8d+105) .or. (.not. (t <= 8.8d+171))) then
        tmp = b * (t * ((j * y4) - (z * a)))
    else
        tmp = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * t_3)) + (t * ((a * y5) - (c * y4))))
    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 = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))));
	double t_2 = (t * j) - (y * k);
	double t_3 = (c * y0) - (a * y1);
	double tmp;
	if (t <= -1.02e+216) {
		tmp = t * (z * ((c * i) - (a * b)));
	} else if (t <= -5.8e+104) {
		tmp = j * (y4 * ((t * b) - (y1 * y3)));
	} else if (t <= -3.5e+29) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (t <= -0.023) {
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	} else if (t <= -4.8e-152) {
		tmp = x * (((y * ((a * b) - (c * i))) + (y2 * t_3)) + (j * ((i * y1) - (b * y0))));
	} else if (t <= 3.8e-292) {
		tmp = y4 * (((b * t_2) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	} else if (t <= 1.05e-213) {
		tmp = t_1;
	} else if (t <= 3.7e-171) {
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * t_2)) + (y0 * ((z * k) - (x * j))));
	} else if (t <= 1.52e+60) {
		tmp = t_1;
	} else if ((t <= 1.8e+105) || !(t <= 8.8e+171)) {
		tmp = b * (t * ((j * y4) - (z * a)));
	} else {
		tmp = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * t_3)) + (t * ((a * y5) - (c * y4))));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))))
	t_2 = (t * j) - (y * k)
	t_3 = (c * y0) - (a * y1)
	tmp = 0
	if t <= -1.02e+216:
		tmp = t * (z * ((c * i) - (a * b)))
	elif t <= -5.8e+104:
		tmp = j * (y4 * ((t * b) - (y1 * y3)))
	elif t <= -3.5e+29:
		tmp = i * (k * ((y * y5) - (z * y1)))
	elif t <= -0.023:
		tmp = j * (y0 * ((y3 * y5) - (x * b)))
	elif t <= -4.8e-152:
		tmp = x * (((y * ((a * b) - (c * i))) + (y2 * t_3)) + (j * ((i * y1) - (b * y0))))
	elif t <= 3.8e-292:
		tmp = y4 * (((b * t_2) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))))
	elif t <= 1.05e-213:
		tmp = t_1
	elif t <= 3.7e-171:
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * t_2)) + (y0 * ((z * k) - (x * j))))
	elif t <= 1.52e+60:
		tmp = t_1
	elif (t <= 1.8e+105) or not (t <= 8.8e+171):
		tmp = b * (t * ((j * y4) - (z * a)))
	else:
		tmp = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * t_3)) + (t * ((a * y5) - (c * y4))))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(y3 * Float64(Float64(y * Float64(Float64(c * y4) - Float64(a * y5))) + Float64(Float64(j * Float64(Float64(y0 * y5) - Float64(y1 * y4))) + Float64(z * Float64(Float64(a * y1) - Float64(c * y0))))))
	t_2 = Float64(Float64(t * j) - Float64(y * k))
	t_3 = Float64(Float64(c * y0) - Float64(a * y1))
	tmp = 0.0
	if (t <= -1.02e+216)
		tmp = Float64(t * Float64(z * Float64(Float64(c * i) - Float64(a * b))));
	elseif (t <= -5.8e+104)
		tmp = Float64(j * Float64(y4 * Float64(Float64(t * b) - Float64(y1 * y3))));
	elseif (t <= -3.5e+29)
		tmp = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))));
	elseif (t <= -0.023)
		tmp = Float64(j * Float64(y0 * Float64(Float64(y3 * y5) - Float64(x * b))));
	elseif (t <= -4.8e-152)
		tmp = Float64(x * Float64(Float64(Float64(y * Float64(Float64(a * b) - Float64(c * i))) + Float64(y2 * t_3)) + Float64(j * Float64(Float64(i * y1) - Float64(b * y0)))));
	elseif (t <= 3.8e-292)
		tmp = Float64(y4 * Float64(Float64(Float64(b * t_2) + Float64(y1 * Float64(Float64(k * y2) - Float64(j * y3)))) + Float64(c * Float64(Float64(y * y3) - Float64(t * y2)))));
	elseif (t <= 1.05e-213)
		tmp = t_1;
	elseif (t <= 3.7e-171)
		tmp = Float64(b * Float64(Float64(Float64(a * Float64(Float64(x * y) - Float64(z * t))) + Float64(y4 * t_2)) + Float64(y0 * Float64(Float64(z * k) - Float64(x * j)))));
	elseif (t <= 1.52e+60)
		tmp = t_1;
	elseif ((t <= 1.8e+105) || !(t <= 8.8e+171))
		tmp = Float64(b * Float64(t * Float64(Float64(j * y4) - Float64(z * a))));
	else
		tmp = Float64(y2 * Float64(Float64(Float64(k * Float64(Float64(y1 * y4) - Float64(y0 * y5))) + Float64(x * t_3)) + Float64(t * Float64(Float64(a * y5) - Float64(c * y4)))));
	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 = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))));
	t_2 = (t * j) - (y * k);
	t_3 = (c * y0) - (a * y1);
	tmp = 0.0;
	if (t <= -1.02e+216)
		tmp = t * (z * ((c * i) - (a * b)));
	elseif (t <= -5.8e+104)
		tmp = j * (y4 * ((t * b) - (y1 * y3)));
	elseif (t <= -3.5e+29)
		tmp = i * (k * ((y * y5) - (z * y1)));
	elseif (t <= -0.023)
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	elseif (t <= -4.8e-152)
		tmp = x * (((y * ((a * b) - (c * i))) + (y2 * t_3)) + (j * ((i * y1) - (b * y0))));
	elseif (t <= 3.8e-292)
		tmp = y4 * (((b * t_2) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	elseif (t <= 1.05e-213)
		tmp = t_1;
	elseif (t <= 3.7e-171)
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * t_2)) + (y0 * ((z * k) - (x * j))));
	elseif (t <= 1.52e+60)
		tmp = t_1;
	elseif ((t <= 1.8e+105) || ~((t <= 8.8e+171)))
		tmp = b * (t * ((j * y4) - (z * a)));
	else
		tmp = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * t_3)) + (t * ((a * y5) - (c * y4))));
	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[(y3 * N[(N[(y * N[(N[(c * y4), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + 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]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -1.02e+216], N[(t * N[(z * N[(N[(c * i), $MachinePrecision] - N[(a * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -5.8e+104], N[(j * N[(y4 * N[(N[(t * b), $MachinePrecision] - N[(y1 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -3.5e+29], N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -0.023], N[(j * N[(y0 * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -4.8e-152], N[(x * N[(N[(N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y2 * t$95$3), $MachinePrecision]), $MachinePrecision] + N[(j * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 3.8e-292], N[(y4 * N[(N[(N[(b * t$95$2), $MachinePrecision] + N[(y1 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(c * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.05e-213], t$95$1, If[LessEqual[t, 3.7e-171], N[(b * N[(N[(N[(a * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y4 * t$95$2), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.52e+60], t$95$1, If[Or[LessEqual[t, 1.8e+105], N[Not[LessEqual[t, 8.8e+171]], $MachinePrecision]], N[(b * N[(t * N[(N[(j * y4), $MachinePrecision] - N[(z * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(y2 * N[(N[(N[(k * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(x * t$95$3), $MachinePrecision]), $MachinePrecision] + N[(t * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]]

Derivation

1. Split input into 10 regimes

2. if t < -1.02e216

   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. Taylor expanded in z around -inf 70.4%

      \[\leadsto \color{blue}{-1 \cdot \left(z \cdot \left(\left(t \cdot \left(a \cdot b - c \cdot i\right) + y3 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   3. Taylor expanded in t around inf 61.6%

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

   if -1.02e216 < t < -5.7999999999999997e104

   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. Taylor expanded in j around inf 40.4%

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

   3. Taylor expanded in y4 around inf 65.2%

      \[\leadsto \color{blue}{j \cdot \left(y4 \cdot \left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 65.2%

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

      2. +-commutative 65.2%

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

      3. mul-1-neg 65.2%

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

      4. unsub-neg 65.2%

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

      5. *-commutative 65.2%

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

   5. Simplified 65.2%

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

   if -5.7999999999999997e104 < t < -3.49999999999999979e29

   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. Taylor expanded in k around inf 37.1%

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

   3. Taylor expanded in i around inf 73.1%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - y1 \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 73.1%

         \[\leadsto i \cdot \left(k \cdot \left(y \cdot y5 - \color{blue}{z \cdot y1}\right)\right) \]

   5. Simplified 73.1%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)} \]

   if -3.49999999999999979e29 < t < -0.023

   1. Initial program 10.0%

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

   2. Taylor expanded in j around inf 50.0%

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

   3. Taylor expanded in y0 around inf 70.6%

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

   if -0.023 < t < -4.8e-152

   1. Initial program 46.7%

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

   2. Taylor expanded in x around inf 54.4%

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

   if -4.8e-152 < t < 3.8000000000000002e-292

   1. Initial program 23.3%

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

   2. Taylor expanded in y4 around inf 59.1%

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

   if 3.8000000000000002e-292 < t < 1.0499999999999999e-213 or 3.70000000000000012e-171 < t < 1.52e60

   1. Initial program 41.9%

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

   2. Taylor expanded in y3 around -inf 58.8%

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

   if 1.0499999999999999e-213 < t < 3.70000000000000012e-171

   1. Initial program 31.5%

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

   2. Taylor expanded in b around inf 56.4%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   if 1.52e60 < t < 1.7999999999999999e105 or 8.7999999999999998e171 < t

   1. Initial program 30.8%

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

   2. Taylor expanded in b around inf 37.1%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in t around inf 64.8%

      \[\leadsto b \cdot \color{blue}{\left(t \cdot \left(-1 \cdot \left(a \cdot z\right) + j \cdot y4\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 64.8%

         \[\leadsto b \cdot \left(t \cdot \color{blue}{\left(j \cdot y4 + -1 \cdot \left(a \cdot z\right)\right)}\right) \]

      2. mul-1-neg 64.8%

         \[\leadsto b \cdot \left(t \cdot \left(j \cdot y4 + \color{blue}{\left(-a \cdot z\right)}\right)\right) \]

      3. unsub-neg 64.8%

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

      4. *-commutative 64.8%

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

      5. *-commutative 64.8%

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

   5. Simplified 64.8%

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

   if 1.7999999999999999e105 < t < 8.7999999999999998e171

   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. Taylor expanded in y2 around inf 47.1%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]
3. Recombined 10 regimes into one program.

4. Final simplification 60.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -1.02 \cdot 10^{+216}:\\ \;\;\;\;t \cdot \left(z \cdot \left(c \cdot i - a \cdot b\right)\right)\\ \mathbf{elif}\;t \leq -5.8 \cdot 10^{+104}:\\ \;\;\;\;j \cdot \left(y4 \cdot \left(t \cdot b - y1 \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq -3.5 \cdot 10^{+29}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq -0.023:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;t \leq -4.8 \cdot 10^{-152}:\\ \;\;\;\;x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 3.8 \cdot 10^{-292}:\\ \;\;\;\;y4 \cdot \left(\left(b \cdot \left(t \cdot j - y \cdot k\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq 1.05 \cdot 10^{-213}:\\ \;\;\;\;y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) + \left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\right)\\ \mathbf{elif}\;t \leq 3.7 \cdot 10^{-171}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;t \leq 1.52 \cdot 10^{+60}:\\ \;\;\;\;y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) + \left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\right)\\ \mathbf{elif}\;t \leq 1.8 \cdot 10^{+105} \lor \neg \left(t \leq 8.8 \cdot 10^{+171}\right):\\ \;\;\;\;b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ \mathbf{else}:\\ \;\;\;\;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)\\ \end{array} \]

Alternative 5: 36.6% accurate, 1.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := t \cdot j - y \cdot k\\ t_2 := y4 \cdot \left(\left(b \cdot t_1 + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ t_3 := c \cdot y0 - a \cdot y1\\ t_4 := x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot t_3\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ t_5 := y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot t_3\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{if}\;t \leq -1.2 \cdot 10^{+219}:\\ \;\;\;\;t \cdot \left(z \cdot \left(c \cdot i - a \cdot b\right)\right)\\ \mathbf{elif}\;t \leq -5.3 \cdot 10^{+104}:\\ \;\;\;\;j \cdot \left(y4 \cdot \left(t \cdot b - y1 \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq -3.9 \cdot 10^{+29}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq -0.025:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;t \leq -1.6 \cdot 10^{-152}:\\ \;\;\;\;t_4\\ \mathbf{elif}\;t \leq 3 \cdot 10^{-259}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t \leq 3 \cdot 10^{-238}:\\ \;\;\;\;t_4\\ \mathbf{elif}\;t \leq 8.5 \cdot 10^{-149}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t \leq 10^{-27}:\\ \;\;\;\;t_5\\ \mathbf{elif}\;t \leq 6.5 \cdot 10^{+111}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot t_1\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;t \leq 1.6 \cdot 10^{+206}:\\ \;\;\;\;t_5\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* t j) (* y k)))
        (t_2
         (*
          y4
          (+
           (+ (* b t_1) (* y1 (- (* k y2) (* j y3))))
           (* c (- (* y y3) (* t y2))))))
        (t_3 (- (* c y0) (* a y1)))
        (t_4
         (*
          x
          (+
           (+ (* y (- (* a b) (* c i))) (* y2 t_3))
           (* j (- (* i y1) (* b y0))))))
        (t_5
         (*
          y2
          (+
           (+ (* k (- (* y1 y4) (* y0 y5))) (* x t_3))
           (* t (- (* a y5) (* c y4)))))))
   (if (<= t -1.2e+219)
     (* t (* z (- (* c i) (* a b))))
     (if (<= t -5.3e+104)
       (* j (* y4 (- (* t b) (* y1 y3))))
       (if (<= t -3.9e+29)
         (* i (* k (- (* y y5) (* z y1))))
         (if (<= t -0.025)
           (* j (* y0 (- (* y3 y5) (* x b))))
           (if (<= t -1.6e-152)
             t_4
             (if (<= t 3e-259)
               t_2
               (if (<= t 3e-238)
                 t_4
                 (if (<= t 8.5e-149)
                   t_2
                   (if (<= t 1e-27)
                     t_5
                     (if (<= t 6.5e+111)
                       (*
                        b
                        (+
                         (+ (* a (- (* x y) (* z t))) (* y4 t_1))
                         (* y0 (- (* z k) (* x j)))))
                       (if (<= t 1.6e+206)
                         t_5
                         (* b (* t (- (* j y4) (* z a)))))))))))))))))

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 = (t * j) - (y * k);
	double t_2 = y4 * (((b * t_1) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	double t_3 = (c * y0) - (a * y1);
	double t_4 = x * (((y * ((a * b) - (c * i))) + (y2 * t_3)) + (j * ((i * y1) - (b * y0))));
	double t_5 = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * t_3)) + (t * ((a * y5) - (c * y4))));
	double tmp;
	if (t <= -1.2e+219) {
		tmp = t * (z * ((c * i) - (a * b)));
	} else if (t <= -5.3e+104) {
		tmp = j * (y4 * ((t * b) - (y1 * y3)));
	} else if (t <= -3.9e+29) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (t <= -0.025) {
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	} else if (t <= -1.6e-152) {
		tmp = t_4;
	} else if (t <= 3e-259) {
		tmp = t_2;
	} else if (t <= 3e-238) {
		tmp = t_4;
	} else if (t <= 8.5e-149) {
		tmp = t_2;
	} else if (t <= 1e-27) {
		tmp = t_5;
	} else if (t <= 6.5e+111) {
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * t_1)) + (y0 * ((z * k) - (x * j))));
	} else if (t <= 1.6e+206) {
		tmp = t_5;
	} else {
		tmp = b * (t * ((j * y4) - (z * a)));
	}
	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 = (t * j) - (y * k)
    t_2 = y4 * (((b * t_1) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))))
    t_3 = (c * y0) - (a * y1)
    t_4 = x * (((y * ((a * b) - (c * i))) + (y2 * t_3)) + (j * ((i * y1) - (b * y0))))
    t_5 = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * t_3)) + (t * ((a * y5) - (c * y4))))
    if (t <= (-1.2d+219)) then
        tmp = t * (z * ((c * i) - (a * b)))
    else if (t <= (-5.3d+104)) then
        tmp = j * (y4 * ((t * b) - (y1 * y3)))
    else if (t <= (-3.9d+29)) then
        tmp = i * (k * ((y * y5) - (z * y1)))
    else if (t <= (-0.025d0)) then
        tmp = j * (y0 * ((y3 * y5) - (x * b)))
    else if (t <= (-1.6d-152)) then
        tmp = t_4
    else if (t <= 3d-259) then
        tmp = t_2
    else if (t <= 3d-238) then
        tmp = t_4
    else if (t <= 8.5d-149) then
        tmp = t_2
    else if (t <= 1d-27) then
        tmp = t_5
    else if (t <= 6.5d+111) then
        tmp = b * (((a * ((x * y) - (z * t))) + (y4 * t_1)) + (y0 * ((z * k) - (x * j))))
    else if (t <= 1.6d+206) then
        tmp = t_5
    else
        tmp = b * (t * ((j * y4) - (z * a)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (t * j) - (y * k);
	double t_2 = y4 * (((b * t_1) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	double t_3 = (c * y0) - (a * y1);
	double t_4 = x * (((y * ((a * b) - (c * i))) + (y2 * t_3)) + (j * ((i * y1) - (b * y0))));
	double t_5 = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * t_3)) + (t * ((a * y5) - (c * y4))));
	double tmp;
	if (t <= -1.2e+219) {
		tmp = t * (z * ((c * i) - (a * b)));
	} else if (t <= -5.3e+104) {
		tmp = j * (y4 * ((t * b) - (y1 * y3)));
	} else if (t <= -3.9e+29) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (t <= -0.025) {
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	} else if (t <= -1.6e-152) {
		tmp = t_4;
	} else if (t <= 3e-259) {
		tmp = t_2;
	} else if (t <= 3e-238) {
		tmp = t_4;
	} else if (t <= 8.5e-149) {
		tmp = t_2;
	} else if (t <= 1e-27) {
		tmp = t_5;
	} else if (t <= 6.5e+111) {
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * t_1)) + (y0 * ((z * k) - (x * j))));
	} else if (t <= 1.6e+206) {
		tmp = t_5;
	} else {
		tmp = b * (t * ((j * y4) - (z * a)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (t * j) - (y * k)
	t_2 = y4 * (((b * t_1) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))))
	t_3 = (c * y0) - (a * y1)
	t_4 = x * (((y * ((a * b) - (c * i))) + (y2 * t_3)) + (j * ((i * y1) - (b * y0))))
	t_5 = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * t_3)) + (t * ((a * y5) - (c * y4))))
	tmp = 0
	if t <= -1.2e+219:
		tmp = t * (z * ((c * i) - (a * b)))
	elif t <= -5.3e+104:
		tmp = j * (y4 * ((t * b) - (y1 * y3)))
	elif t <= -3.9e+29:
		tmp = i * (k * ((y * y5) - (z * y1)))
	elif t <= -0.025:
		tmp = j * (y0 * ((y3 * y5) - (x * b)))
	elif t <= -1.6e-152:
		tmp = t_4
	elif t <= 3e-259:
		tmp = t_2
	elif t <= 3e-238:
		tmp = t_4
	elif t <= 8.5e-149:
		tmp = t_2
	elif t <= 1e-27:
		tmp = t_5
	elif t <= 6.5e+111:
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * t_1)) + (y0 * ((z * k) - (x * j))))
	elif t <= 1.6e+206:
		tmp = t_5
	else:
		tmp = b * (t * ((j * y4) - (z * a)))
	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(t * j) - Float64(y * k))
	t_2 = Float64(y4 * Float64(Float64(Float64(b * t_1) + Float64(y1 * Float64(Float64(k * y2) - Float64(j * y3)))) + Float64(c * Float64(Float64(y * y3) - Float64(t * y2)))))
	t_3 = Float64(Float64(c * y0) - Float64(a * y1))
	t_4 = Float64(x * Float64(Float64(Float64(y * Float64(Float64(a * b) - Float64(c * i))) + Float64(y2 * t_3)) + Float64(j * Float64(Float64(i * y1) - Float64(b * y0)))))
	t_5 = Float64(y2 * Float64(Float64(Float64(k * Float64(Float64(y1 * y4) - Float64(y0 * y5))) + Float64(x * t_3)) + Float64(t * Float64(Float64(a * y5) - Float64(c * y4)))))
	tmp = 0.0
	if (t <= -1.2e+219)
		tmp = Float64(t * Float64(z * Float64(Float64(c * i) - Float64(a * b))));
	elseif (t <= -5.3e+104)
		tmp = Float64(j * Float64(y4 * Float64(Float64(t * b) - Float64(y1 * y3))));
	elseif (t <= -3.9e+29)
		tmp = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))));
	elseif (t <= -0.025)
		tmp = Float64(j * Float64(y0 * Float64(Float64(y3 * y5) - Float64(x * b))));
	elseif (t <= -1.6e-152)
		tmp = t_4;
	elseif (t <= 3e-259)
		tmp = t_2;
	elseif (t <= 3e-238)
		tmp = t_4;
	elseif (t <= 8.5e-149)
		tmp = t_2;
	elseif (t <= 1e-27)
		tmp = t_5;
	elseif (t <= 6.5e+111)
		tmp = Float64(b * Float64(Float64(Float64(a * Float64(Float64(x * y) - Float64(z * t))) + Float64(y4 * t_1)) + Float64(y0 * Float64(Float64(z * k) - Float64(x * j)))));
	elseif (t <= 1.6e+206)
		tmp = t_5;
	else
		tmp = Float64(b * Float64(t * Float64(Float64(j * y4) - Float64(z * a))));
	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 = (t * j) - (y * k);
	t_2 = y4 * (((b * t_1) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	t_3 = (c * y0) - (a * y1);
	t_4 = x * (((y * ((a * b) - (c * i))) + (y2 * t_3)) + (j * ((i * y1) - (b * y0))));
	t_5 = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * t_3)) + (t * ((a * y5) - (c * y4))));
	tmp = 0.0;
	if (t <= -1.2e+219)
		tmp = t * (z * ((c * i) - (a * b)));
	elseif (t <= -5.3e+104)
		tmp = j * (y4 * ((t * b) - (y1 * y3)));
	elseif (t <= -3.9e+29)
		tmp = i * (k * ((y * y5) - (z * y1)));
	elseif (t <= -0.025)
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	elseif (t <= -1.6e-152)
		tmp = t_4;
	elseif (t <= 3e-259)
		tmp = t_2;
	elseif (t <= 3e-238)
		tmp = t_4;
	elseif (t <= 8.5e-149)
		tmp = t_2;
	elseif (t <= 1e-27)
		tmp = t_5;
	elseif (t <= 6.5e+111)
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * t_1)) + (y0 * ((z * k) - (x * j))));
	elseif (t <= 1.6e+206)
		tmp = t_5;
	else
		tmp = b * (t * ((j * y4) - (z * a)));
	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[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(y4 * N[(N[(N[(b * t$95$1), $MachinePrecision] + N[(y1 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(c * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(x * N[(N[(N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y2 * t$95$3), $MachinePrecision]), $MachinePrecision] + N[(j * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(y2 * N[(N[(N[(k * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $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[t, -1.2e+219], N[(t * N[(z * N[(N[(c * i), $MachinePrecision] - N[(a * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -5.3e+104], N[(j * N[(y4 * N[(N[(t * b), $MachinePrecision] - N[(y1 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -3.9e+29], N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -0.025], N[(j * N[(y0 * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -1.6e-152], t$95$4, If[LessEqual[t, 3e-259], t$95$2, If[LessEqual[t, 3e-238], t$95$4, If[LessEqual[t, 8.5e-149], t$95$2, If[LessEqual[t, 1e-27], t$95$5, If[LessEqual[t, 6.5e+111], N[(b * N[(N[(N[(a * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y4 * t$95$1), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.6e+206], t$95$5, N[(b * N[(t * N[(N[(j * y4), $MachinePrecision] - N[(z * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]]]]]

Derivation

1. Split input into 9 regimes

2. if t < -1.2e219

   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. Taylor expanded in z around -inf 70.4%

      \[\leadsto \color{blue}{-1 \cdot \left(z \cdot \left(\left(t \cdot \left(a \cdot b - c \cdot i\right) + y3 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   3. Taylor expanded in t around inf 61.6%

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

   if -1.2e219 < t < -5.2999999999999999e104

   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. Taylor expanded in j around inf 40.4%

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

   3. Taylor expanded in y4 around inf 65.2%

      \[\leadsto \color{blue}{j \cdot \left(y4 \cdot \left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 65.2%

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

      2. +-commutative 65.2%

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

      3. mul-1-neg 65.2%

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

      4. unsub-neg 65.2%

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

      5. *-commutative 65.2%

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

   5. Simplified 65.2%

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

   if -5.2999999999999999e104 < t < -3.89999999999999968e29

   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. Taylor expanded in k around inf 37.1%

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

   3. Taylor expanded in i around inf 73.1%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - y1 \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 73.1%

         \[\leadsto i \cdot \left(k \cdot \left(y \cdot y5 - \color{blue}{z \cdot y1}\right)\right) \]

   5. Simplified 73.1%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)} \]

   if -3.89999999999999968e29 < t < -0.025000000000000001

   1. Initial program 10.0%

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

   2. Taylor expanded in j around inf 50.0%

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

   3. Taylor expanded in y0 around inf 70.6%

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

   if -0.025000000000000001 < t < -1.60000000000000006e-152 or 3.0000000000000002e-259 < t < 3e-238

   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. Taylor expanded in x around inf 59.3%

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

   if -1.60000000000000006e-152 < t < 3.0000000000000002e-259 or 3e-238 < t < 8.5000000000000006e-149

   1. Initial program 35.5%

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

   2. Taylor expanded in y4 around inf 53.3%

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

   if 8.5000000000000006e-149 < t < 1e-27 or 6.5000000000000002e111 < t < 1.60000000000000003e206

   1. Initial program 37.5%

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

   2. Taylor expanded in y2 around inf 57.7%

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

   if 1e-27 < t < 6.5000000000000002e111

   1. Initial program 26.2%

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

   2. Taylor expanded in b around inf 55.4%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   if 1.60000000000000003e206 < t

   1. Initial program 29.3%

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

   2. Taylor expanded in b around inf 32.3%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in t around inf 62.0%

      \[\leadsto b \cdot \color{blue}{\left(t \cdot \left(-1 \cdot \left(a \cdot z\right) + j \cdot y4\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 62.0%

         \[\leadsto b \cdot \left(t \cdot \color{blue}{\left(j \cdot y4 + -1 \cdot \left(a \cdot z\right)\right)}\right) \]

      2. mul-1-neg 62.0%

         \[\leadsto b \cdot \left(t \cdot \left(j \cdot y4 + \color{blue}{\left(-a \cdot z\right)}\right)\right) \]

      3. unsub-neg 62.0%

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

      4. *-commutative 62.0%

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

      5. *-commutative 62.0%

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

   5. Simplified 62.0%

      \[\leadsto b \cdot \color{blue}{\left(t \cdot \left(y4 \cdot j - z \cdot a\right)\right)} \]
3. Recombined 9 regimes into one program.

4. Final simplification 59.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -1.2 \cdot 10^{+219}:\\ \;\;\;\;t \cdot \left(z \cdot \left(c \cdot i - a \cdot b\right)\right)\\ \mathbf{elif}\;t \leq -5.3 \cdot 10^{+104}:\\ \;\;\;\;j \cdot \left(y4 \cdot \left(t \cdot b - y1 \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq -3.9 \cdot 10^{+29}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq -0.025:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;t \leq -1.6 \cdot 10^{-152}:\\ \;\;\;\;x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 3 \cdot 10^{-259}:\\ \;\;\;\;y4 \cdot \left(\left(b \cdot \left(t \cdot j - y \cdot k\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq 3 \cdot 10^{-238}:\\ \;\;\;\;x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 8.5 \cdot 10^{-149}:\\ \;\;\;\;y4 \cdot \left(\left(b \cdot \left(t \cdot j - y \cdot k\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq 10^{-27}:\\ \;\;\;\;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}\;t \leq 6.5 \cdot 10^{+111}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;t \leq 1.6 \cdot 10^{+206}:\\ \;\;\;\;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}:\\ \;\;\;\;b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ \end{array} \]

Alternative 6: 34.7% accurate, 1.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := z \cdot \left(k \cdot \left(b \cdot y0 - i \cdot y1\right) - c \cdot \left(y0 \cdot y3\right)\right)\\ t_2 := y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ t_3 := a \cdot \left(x \cdot y - z \cdot t\right)\\ \mathbf{if}\;a \leq -3.8 \cdot 10^{+170}:\\ \;\;\;\;b \cdot t_3\\ \mathbf{elif}\;a \leq -1.3 \cdot 10^{+115}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -1.1 \cdot 10^{+90}:\\ \;\;\;\;\left(y3 \cdot y5\right) \cdot \left(j \cdot y0 - y \cdot a\right)\\ \mathbf{elif}\;a \leq -1.22 \cdot 10^{+59}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;a \leq -4.5 \cdot 10^{-79}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq -7.5 \cdot 10^{-262}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 2.5 \cdot 10^{-157}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq 1.4 \cdot 10^{-59}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 3.3 \cdot 10^{-47}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq 3.8 \cdot 10^{+53}:\\ \;\;\;\;b \cdot \left(\left(t_3 + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{else}:\\ \;\;\;\;z \cdot \left(y3 \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* z (- (* k (- (* b y0) (* i y1))) (* c (* y0 y3)))))
        (t_2
         (*
          y2
          (+
           (+ (* k (- (* y1 y4) (* y0 y5))) (* x (- (* c y0) (* a y1))))
           (* t (- (* a y5) (* c y4))))))
        (t_3 (* a (- (* x y) (* z t)))))
   (if (<= a -3.8e+170)
     (* b t_3)
     (if (<= a -1.3e+115)
       t_1
       (if (<= a -1.1e+90)
         (* (* y3 y5) (- (* j y0) (* y a)))
         (if (<= a -1.22e+59)
           (* i (* k (- (* y y5) (* z y1))))
           (if (<= a -4.5e-79)
             t_2
             (if (<= a -7.5e-262)
               t_1
               (if (<= a 2.5e-157)
                 t_2
                 (if (<= a 1.4e-59)
                   t_1
                   (if (<= a 3.3e-47)
                     t_2
                     (if (<= a 3.8e+53)
                       (*
                        b
                        (+
                         (+ t_3 (* y4 (- (* t j) (* y k))))
                         (* y0 (- (* z k) (* x j)))))
                       (* z (* y3 (- (* 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 = z * ((k * ((b * y0) - (i * y1))) - (c * (y0 * y3)));
	double t_2 = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))));
	double t_3 = a * ((x * y) - (z * t));
	double tmp;
	if (a <= -3.8e+170) {
		tmp = b * t_3;
	} else if (a <= -1.3e+115) {
		tmp = t_1;
	} else if (a <= -1.1e+90) {
		tmp = (y3 * y5) * ((j * y0) - (y * a));
	} else if (a <= -1.22e+59) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (a <= -4.5e-79) {
		tmp = t_2;
	} else if (a <= -7.5e-262) {
		tmp = t_1;
	} else if (a <= 2.5e-157) {
		tmp = t_2;
	} else if (a <= 1.4e-59) {
		tmp = t_1;
	} else if (a <= 3.3e-47) {
		tmp = t_2;
	} else if (a <= 3.8e+53) {
		tmp = b * ((t_3 + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))));
	} else {
		tmp = z * (y3 * ((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 = z * ((k * ((b * y0) - (i * y1))) - (c * (y0 * y3)))
    t_2 = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))))
    t_3 = a * ((x * y) - (z * t))
    if (a <= (-3.8d+170)) then
        tmp = b * t_3
    else if (a <= (-1.3d+115)) then
        tmp = t_1
    else if (a <= (-1.1d+90)) then
        tmp = (y3 * y5) * ((j * y0) - (y * a))
    else if (a <= (-1.22d+59)) then
        tmp = i * (k * ((y * y5) - (z * y1)))
    else if (a <= (-4.5d-79)) then
        tmp = t_2
    else if (a <= (-7.5d-262)) then
        tmp = t_1
    else if (a <= 2.5d-157) then
        tmp = t_2
    else if (a <= 1.4d-59) then
        tmp = t_1
    else if (a <= 3.3d-47) then
        tmp = t_2
    else if (a <= 3.8d+53) then
        tmp = b * ((t_3 + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))))
    else
        tmp = z * (y3 * ((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 = z * ((k * ((b * y0) - (i * y1))) - (c * (y0 * y3)));
	double t_2 = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))));
	double t_3 = a * ((x * y) - (z * t));
	double tmp;
	if (a <= -3.8e+170) {
		tmp = b * t_3;
	} else if (a <= -1.3e+115) {
		tmp = t_1;
	} else if (a <= -1.1e+90) {
		tmp = (y3 * y5) * ((j * y0) - (y * a));
	} else if (a <= -1.22e+59) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (a <= -4.5e-79) {
		tmp = t_2;
	} else if (a <= -7.5e-262) {
		tmp = t_1;
	} else if (a <= 2.5e-157) {
		tmp = t_2;
	} else if (a <= 1.4e-59) {
		tmp = t_1;
	} else if (a <= 3.3e-47) {
		tmp = t_2;
	} else if (a <= 3.8e+53) {
		tmp = b * ((t_3 + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))));
	} else {
		tmp = z * (y3 * ((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 = z * ((k * ((b * y0) - (i * y1))) - (c * (y0 * y3)))
	t_2 = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))))
	t_3 = a * ((x * y) - (z * t))
	tmp = 0
	if a <= -3.8e+170:
		tmp = b * t_3
	elif a <= -1.3e+115:
		tmp = t_1
	elif a <= -1.1e+90:
		tmp = (y3 * y5) * ((j * y0) - (y * a))
	elif a <= -1.22e+59:
		tmp = i * (k * ((y * y5) - (z * y1)))
	elif a <= -4.5e-79:
		tmp = t_2
	elif a <= -7.5e-262:
		tmp = t_1
	elif a <= 2.5e-157:
		tmp = t_2
	elif a <= 1.4e-59:
		tmp = t_1
	elif a <= 3.3e-47:
		tmp = t_2
	elif a <= 3.8e+53:
		tmp = b * ((t_3 + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))))
	else:
		tmp = z * (y3 * ((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(z * Float64(Float64(k * Float64(Float64(b * y0) - Float64(i * y1))) - Float64(c * Float64(y0 * y3))))
	t_2 = 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)))))
	t_3 = Float64(a * Float64(Float64(x * y) - Float64(z * t)))
	tmp = 0.0
	if (a <= -3.8e+170)
		tmp = Float64(b * t_3);
	elseif (a <= -1.3e+115)
		tmp = t_1;
	elseif (a <= -1.1e+90)
		tmp = Float64(Float64(y3 * y5) * Float64(Float64(j * y0) - Float64(y * a)));
	elseif (a <= -1.22e+59)
		tmp = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))));
	elseif (a <= -4.5e-79)
		tmp = t_2;
	elseif (a <= -7.5e-262)
		tmp = t_1;
	elseif (a <= 2.5e-157)
		tmp = t_2;
	elseif (a <= 1.4e-59)
		tmp = t_1;
	elseif (a <= 3.3e-47)
		tmp = t_2;
	elseif (a <= 3.8e+53)
		tmp = Float64(b * Float64(Float64(t_3 + Float64(y4 * Float64(Float64(t * j) - Float64(y * k)))) + Float64(y0 * Float64(Float64(z * k) - Float64(x * j)))));
	else
		tmp = Float64(z * Float64(y3 * 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 = z * ((k * ((b * y0) - (i * y1))) - (c * (y0 * y3)));
	t_2 = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))));
	t_3 = a * ((x * y) - (z * t));
	tmp = 0.0;
	if (a <= -3.8e+170)
		tmp = b * t_3;
	elseif (a <= -1.3e+115)
		tmp = t_1;
	elseif (a <= -1.1e+90)
		tmp = (y3 * y5) * ((j * y0) - (y * a));
	elseif (a <= -1.22e+59)
		tmp = i * (k * ((y * y5) - (z * y1)));
	elseif (a <= -4.5e-79)
		tmp = t_2;
	elseif (a <= -7.5e-262)
		tmp = t_1;
	elseif (a <= 2.5e-157)
		tmp = t_2;
	elseif (a <= 1.4e-59)
		tmp = t_1;
	elseif (a <= 3.3e-47)
		tmp = t_2;
	elseif (a <= 3.8e+53)
		tmp = b * ((t_3 + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))));
	else
		tmp = z * (y3 * ((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[(z * N[(N[(k * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(c * N[(y0 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = 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]}, Block[{t$95$3 = N[(a * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -3.8e+170], N[(b * t$95$3), $MachinePrecision], If[LessEqual[a, -1.3e+115], t$95$1, If[LessEqual[a, -1.1e+90], N[(N[(y3 * y5), $MachinePrecision] * N[(N[(j * y0), $MachinePrecision] - N[(y * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -1.22e+59], N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -4.5e-79], t$95$2, If[LessEqual[a, -7.5e-262], t$95$1, If[LessEqual[a, 2.5e-157], t$95$2, If[LessEqual[a, 1.4e-59], t$95$1, If[LessEqual[a, 3.3e-47], t$95$2, If[LessEqual[a, 3.8e+53], N[(b * N[(N[(t$95$3 + N[(y4 * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(z * N[(y3 * N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if a < -3.7999999999999998e170

   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. Taylor expanded in b around inf 44.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 69.0%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 69.0%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 69.0%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 69.0%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 69.0%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 69.0%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   if -3.7999999999999998e170 < a < -1.3e115 or -4.5000000000000003e-79 < a < -7.5000000000000002e-262 or 2.5000000000000001e-157 < a < 1.3999999999999999e-59

   1. Initial program 26.0%

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

   2. Taylor expanded in z around -inf 62.0%

      \[\leadsto \color{blue}{-1 \cdot \left(z \cdot \left(\left(t \cdot \left(a \cdot b - c \cdot i\right) + y3 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   3. Taylor expanded in y0 around inf 59.1%

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

      1. *-commutative 59.1%

         \[\leadsto -1 \cdot \left(z \cdot \left(c \cdot \color{blue}{\left(y3 \cdot y0\right)} - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) \]

   5. Simplified 59.1%

      \[\leadsto -1 \cdot \left(z \cdot \left(\color{blue}{c \cdot \left(y3 \cdot y0\right)} - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) \]

   if -1.3e115 < a < -1.09999999999999995e90

   1. Initial program 40.0%

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

   2. Taylor expanded in y3 around -inf 60.0%

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

   3. Taylor expanded in y5 around inf 80.0%

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

      1. associate-*r* 80.0%

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

      2. distribute-lft-out-- 80.0%

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

      3. *-commutative 80.0%

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

   5. Simplified 80.0%

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

   if -1.09999999999999995e90 < a < -1.22e59

   1. Initial program 42.6%

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

   2. Taylor expanded in k around inf 50.8%

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

   3. Taylor expanded in i around inf 86.2%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - y1 \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 86.2%

         \[\leadsto i \cdot \left(k \cdot \left(y \cdot y5 - \color{blue}{z \cdot y1}\right)\right) \]

   5. Simplified 86.2%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)} \]

   if -1.22e59 < a < -4.5000000000000003e-79 or -7.5000000000000002e-262 < a < 2.5000000000000001e-157 or 1.3999999999999999e-59 < a < 3.30000000000000004e-47

   1. Initial program 39.6%

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

   2. Taylor expanded in y2 around inf 57.3%

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

   if 3.30000000000000004e-47 < a < 3.79999999999999997e53

   1. Initial program 26.9%

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

   2. Taylor expanded in b around inf 50.6%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   if 3.79999999999999997e53 < a

   1. Initial program 32.4%

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

   2. Taylor expanded in y3 around -inf 47.2%

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

   3. Taylor expanded in z around inf 55.2%

      \[\leadsto -1 \cdot \color{blue}{\left(y3 \cdot \left(z \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 55.2%

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

      2. associate-*l* 57.0%

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

   5. Simplified 57.0%

      \[\leadsto -1 \cdot \color{blue}{\left(z \cdot \left(\left(c \cdot y0 - a \cdot y1\right) \cdot y3\right)\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 59.7%

   \[\leadsto \begin{array}{l} \mathbf{if}\;a \leq -3.8 \cdot 10^{+170}:\\ \;\;\;\;b \cdot \left(a \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;a \leq -1.3 \cdot 10^{+115}:\\ \;\;\;\;z \cdot \left(k \cdot \left(b \cdot y0 - i \cdot y1\right) - c \cdot \left(y0 \cdot y3\right)\right)\\ \mathbf{elif}\;a \leq -1.1 \cdot 10^{+90}:\\ \;\;\;\;\left(y3 \cdot y5\right) \cdot \left(j \cdot y0 - y \cdot a\right)\\ \mathbf{elif}\;a \leq -1.22 \cdot 10^{+59}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;a \leq -4.5 \cdot 10^{-79}:\\ \;\;\;\;y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;a \leq -7.5 \cdot 10^{-262}:\\ \;\;\;\;z \cdot \left(k \cdot \left(b \cdot y0 - i \cdot y1\right) - c \cdot \left(y0 \cdot y3\right)\right)\\ \mathbf{elif}\;a \leq 2.5 \cdot 10^{-157}:\\ \;\;\;\;y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;a \leq 1.4 \cdot 10^{-59}:\\ \;\;\;\;z \cdot \left(k \cdot \left(b \cdot y0 - i \cdot y1\right) - c \cdot \left(y0 \cdot y3\right)\right)\\ \mathbf{elif}\;a \leq 3.3 \cdot 10^{-47}:\\ \;\;\;\;y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;a \leq 3.8 \cdot 10^{+53}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{else}:\\ \;\;\;\;z \cdot \left(y3 \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\\ \end{array} \]

Alternative 7: 38.8% accurate, 1.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := k \cdot \left(b \cdot y0 - i \cdot y1\right)\\ t_2 := x \cdot y - z \cdot t\\ t_3 := x \cdot y2 - z \cdot y3\\ t_4 := y0 \cdot \left(\left(y5 \cdot \left(j \cdot y3 - k \cdot y2\right) + c \cdot t_3\right) + b \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{if}\;a \leq -1.9 \cdot 10^{+172}:\\ \;\;\;\;b \cdot \left(a \cdot t_2\right)\\ \mathbf{elif}\;a \leq -2.5 \cdot 10^{+111}:\\ \;\;\;\;z \cdot \left(t_1 - c \cdot \left(y0 \cdot y3\right)\right)\\ \mathbf{elif}\;a \leq -4.7 \cdot 10^{+86}:\\ \;\;\;\;\left(y3 \cdot y5\right) \cdot \left(j \cdot y0 - y \cdot a\right)\\ \mathbf{elif}\;a \leq -1.08 \cdot 10^{+64}:\\ \;\;\;\;i \cdot \left(k \cdot \left(z \cdot \left(-y1\right)\right)\right)\\ \mathbf{elif}\;a \leq -2.1 \cdot 10^{+31}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;a \leq -6 \cdot 10^{-143}:\\ \;\;\;\;c \cdot \left(\left(i \cdot \left(z \cdot t - x \cdot y\right) + y0 \cdot t_3\right) + y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;a \leq 5 \cdot 10^{-161}:\\ \;\;\;\;t_4\\ \mathbf{elif}\;a \leq 1.88 \cdot 10^{-56}:\\ \;\;\;\;z \cdot \left(\left(y3 \cdot \left(a \cdot y1 - c \cdot y0\right) + t \cdot \left(c \cdot i - a \cdot b\right)\right) + t_1\right)\\ \mathbf{elif}\;a \leq 2.35 \cdot 10^{+126}:\\ \;\;\;\;t_4\\ \mathbf{elif}\;a \leq 5.4 \cdot 10^{+160}:\\ \;\;\;\;t \cdot \left(\left(j \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(a \cdot b - c \cdot i\right)\right) + y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(\left(y1 \cdot \left(z \cdot y3 - x \cdot y2\right) + b \cdot t_2\right) + y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* k (- (* b y0) (* i y1))))
        (t_2 (- (* x y) (* z t)))
        (t_3 (- (* x y2) (* z y3)))
        (t_4
         (*
          y0
          (+
           (+ (* y5 (- (* j y3) (* k y2))) (* c t_3))
           (* b (- (* z k) (* x j)))))))
   (if (<= a -1.9e+172)
     (* b (* a t_2))
     (if (<= a -2.5e+111)
       (* z (- t_1 (* c (* y0 y3))))
       (if (<= a -4.7e+86)
         (* (* y3 y5) (- (* j y0) (* y a)))
         (if (<= a -1.08e+64)
           (* i (* k (* z (- y1))))
           (if (<= a -2.1e+31)
             (* j (* x (- (* i y1) (* b y0))))
             (if (<= a -6e-143)
               (*
                c
                (+
                 (+ (* i (- (* z t) (* x y))) (* y0 t_3))
                 (* y4 (- (* y y3) (* t y2)))))
               (if (<= a 5e-161)
                 t_4
                 (if (<= a 1.88e-56)
                   (*
                    z
                    (+
                     (+ (* y3 (- (* a y1) (* c y0))) (* t (- (* c i) (* a b))))
                     t_1))
                   (if (<= a 2.35e+126)
                     t_4
                     (if (<= a 5.4e+160)
                       (*
                        t
                        (+
                         (-
                          (* j (- (* b y4) (* i y5)))
                          (* z (- (* a b) (* c i))))
                         (* y2 (- (* a y5) (* c y4)))))
                       (*
                        a
                        (+
                         (+ (* y1 (- (* z y3) (* x y2))) (* b t_2))
                         (* y5 (- (* t y2) (* 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 t_1 = k * ((b * y0) - (i * y1));
	double t_2 = (x * y) - (z * t);
	double t_3 = (x * y2) - (z * y3);
	double t_4 = y0 * (((y5 * ((j * y3) - (k * y2))) + (c * t_3)) + (b * ((z * k) - (x * j))));
	double tmp;
	if (a <= -1.9e+172) {
		tmp = b * (a * t_2);
	} else if (a <= -2.5e+111) {
		tmp = z * (t_1 - (c * (y0 * y3)));
	} else if (a <= -4.7e+86) {
		tmp = (y3 * y5) * ((j * y0) - (y * a));
	} else if (a <= -1.08e+64) {
		tmp = i * (k * (z * -y1));
	} else if (a <= -2.1e+31) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (a <= -6e-143) {
		tmp = c * (((i * ((z * t) - (x * y))) + (y0 * t_3)) + (y4 * ((y * y3) - (t * y2))));
	} else if (a <= 5e-161) {
		tmp = t_4;
	} else if (a <= 1.88e-56) {
		tmp = z * (((y3 * ((a * y1) - (c * y0))) + (t * ((c * i) - (a * b)))) + t_1);
	} else if (a <= 2.35e+126) {
		tmp = t_4;
	} else if (a <= 5.4e+160) {
		tmp = t * (((j * ((b * y4) - (i * y5))) - (z * ((a * b) - (c * i)))) + (y2 * ((a * y5) - (c * y4))));
	} else {
		tmp = a * (((y1 * ((z * y3) - (x * y2))) + (b * t_2)) + (y5 * ((t * y2) - (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) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: tmp
    t_1 = k * ((b * y0) - (i * y1))
    t_2 = (x * y) - (z * t)
    t_3 = (x * y2) - (z * y3)
    t_4 = y0 * (((y5 * ((j * y3) - (k * y2))) + (c * t_3)) + (b * ((z * k) - (x * j))))
    if (a <= (-1.9d+172)) then
        tmp = b * (a * t_2)
    else if (a <= (-2.5d+111)) then
        tmp = z * (t_1 - (c * (y0 * y3)))
    else if (a <= (-4.7d+86)) then
        tmp = (y3 * y5) * ((j * y0) - (y * a))
    else if (a <= (-1.08d+64)) then
        tmp = i * (k * (z * -y1))
    else if (a <= (-2.1d+31)) then
        tmp = j * (x * ((i * y1) - (b * y0)))
    else if (a <= (-6d-143)) then
        tmp = c * (((i * ((z * t) - (x * y))) + (y0 * t_3)) + (y4 * ((y * y3) - (t * y2))))
    else if (a <= 5d-161) then
        tmp = t_4
    else if (a <= 1.88d-56) then
        tmp = z * (((y3 * ((a * y1) - (c * y0))) + (t * ((c * i) - (a * b)))) + t_1)
    else if (a <= 2.35d+126) then
        tmp = t_4
    else if (a <= 5.4d+160) then
        tmp = t * (((j * ((b * y4) - (i * y5))) - (z * ((a * b) - (c * i)))) + (y2 * ((a * y5) - (c * y4))))
    else
        tmp = a * (((y1 * ((z * y3) - (x * y2))) + (b * t_2)) + (y5 * ((t * y2) - (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 t_1 = k * ((b * y0) - (i * y1));
	double t_2 = (x * y) - (z * t);
	double t_3 = (x * y2) - (z * y3);
	double t_4 = y0 * (((y5 * ((j * y3) - (k * y2))) + (c * t_3)) + (b * ((z * k) - (x * j))));
	double tmp;
	if (a <= -1.9e+172) {
		tmp = b * (a * t_2);
	} else if (a <= -2.5e+111) {
		tmp = z * (t_1 - (c * (y0 * y3)));
	} else if (a <= -4.7e+86) {
		tmp = (y3 * y5) * ((j * y0) - (y * a));
	} else if (a <= -1.08e+64) {
		tmp = i * (k * (z * -y1));
	} else if (a <= -2.1e+31) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (a <= -6e-143) {
		tmp = c * (((i * ((z * t) - (x * y))) + (y0 * t_3)) + (y4 * ((y * y3) - (t * y2))));
	} else if (a <= 5e-161) {
		tmp = t_4;
	} else if (a <= 1.88e-56) {
		tmp = z * (((y3 * ((a * y1) - (c * y0))) + (t * ((c * i) - (a * b)))) + t_1);
	} else if (a <= 2.35e+126) {
		tmp = t_4;
	} else if (a <= 5.4e+160) {
		tmp = t * (((j * ((b * y4) - (i * y5))) - (z * ((a * b) - (c * i)))) + (y2 * ((a * y5) - (c * y4))));
	} else {
		tmp = a * (((y1 * ((z * y3) - (x * y2))) + (b * t_2)) + (y5 * ((t * y2) - (y * y3))));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = k * ((b * y0) - (i * y1))
	t_2 = (x * y) - (z * t)
	t_3 = (x * y2) - (z * y3)
	t_4 = y0 * (((y5 * ((j * y3) - (k * y2))) + (c * t_3)) + (b * ((z * k) - (x * j))))
	tmp = 0
	if a <= -1.9e+172:
		tmp = b * (a * t_2)
	elif a <= -2.5e+111:
		tmp = z * (t_1 - (c * (y0 * y3)))
	elif a <= -4.7e+86:
		tmp = (y3 * y5) * ((j * y0) - (y * a))
	elif a <= -1.08e+64:
		tmp = i * (k * (z * -y1))
	elif a <= -2.1e+31:
		tmp = j * (x * ((i * y1) - (b * y0)))
	elif a <= -6e-143:
		tmp = c * (((i * ((z * t) - (x * y))) + (y0 * t_3)) + (y4 * ((y * y3) - (t * y2))))
	elif a <= 5e-161:
		tmp = t_4
	elif a <= 1.88e-56:
		tmp = z * (((y3 * ((a * y1) - (c * y0))) + (t * ((c * i) - (a * b)))) + t_1)
	elif a <= 2.35e+126:
		tmp = t_4
	elif a <= 5.4e+160:
		tmp = t * (((j * ((b * y4) - (i * y5))) - (z * ((a * b) - (c * i)))) + (y2 * ((a * y5) - (c * y4))))
	else:
		tmp = a * (((y1 * ((z * y3) - (x * y2))) + (b * t_2)) + (y5 * ((t * y2) - (y * y3))))
	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(Float64(b * y0) - Float64(i * y1)))
	t_2 = Float64(Float64(x * y) - Float64(z * t))
	t_3 = Float64(Float64(x * y2) - Float64(z * y3))
	t_4 = Float64(y0 * Float64(Float64(Float64(y5 * Float64(Float64(j * y3) - Float64(k * y2))) + Float64(c * t_3)) + Float64(b * Float64(Float64(z * k) - Float64(x * j)))))
	tmp = 0.0
	if (a <= -1.9e+172)
		tmp = Float64(b * Float64(a * t_2));
	elseif (a <= -2.5e+111)
		tmp = Float64(z * Float64(t_1 - Float64(c * Float64(y0 * y3))));
	elseif (a <= -4.7e+86)
		tmp = Float64(Float64(y3 * y5) * Float64(Float64(j * y0) - Float64(y * a)));
	elseif (a <= -1.08e+64)
		tmp = Float64(i * Float64(k * Float64(z * Float64(-y1))));
	elseif (a <= -2.1e+31)
		tmp = Float64(j * Float64(x * Float64(Float64(i * y1) - Float64(b * y0))));
	elseif (a <= -6e-143)
		tmp = Float64(c * Float64(Float64(Float64(i * Float64(Float64(z * t) - Float64(x * y))) + Float64(y0 * t_3)) + Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2)))));
	elseif (a <= 5e-161)
		tmp = t_4;
	elseif (a <= 1.88e-56)
		tmp = Float64(z * Float64(Float64(Float64(y3 * Float64(Float64(a * y1) - Float64(c * y0))) + Float64(t * Float64(Float64(c * i) - Float64(a * b)))) + t_1));
	elseif (a <= 2.35e+126)
		tmp = t_4;
	elseif (a <= 5.4e+160)
		tmp = Float64(t * Float64(Float64(Float64(j * Float64(Float64(b * y4) - Float64(i * y5))) - Float64(z * Float64(Float64(a * b) - Float64(c * i)))) + Float64(y2 * Float64(Float64(a * y5) - Float64(c * y4)))));
	else
		tmp = Float64(a * Float64(Float64(Float64(y1 * Float64(Float64(z * y3) - Float64(x * y2))) + Float64(b * t_2)) + Float64(y5 * Float64(Float64(t * y2) - 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)
	t_1 = k * ((b * y0) - (i * y1));
	t_2 = (x * y) - (z * t);
	t_3 = (x * y2) - (z * y3);
	t_4 = y0 * (((y5 * ((j * y3) - (k * y2))) + (c * t_3)) + (b * ((z * k) - (x * j))));
	tmp = 0.0;
	if (a <= -1.9e+172)
		tmp = b * (a * t_2);
	elseif (a <= -2.5e+111)
		tmp = z * (t_1 - (c * (y0 * y3)));
	elseif (a <= -4.7e+86)
		tmp = (y3 * y5) * ((j * y0) - (y * a));
	elseif (a <= -1.08e+64)
		tmp = i * (k * (z * -y1));
	elseif (a <= -2.1e+31)
		tmp = j * (x * ((i * y1) - (b * y0)));
	elseif (a <= -6e-143)
		tmp = c * (((i * ((z * t) - (x * y))) + (y0 * t_3)) + (y4 * ((y * y3) - (t * y2))));
	elseif (a <= 5e-161)
		tmp = t_4;
	elseif (a <= 1.88e-56)
		tmp = z * (((y3 * ((a * y1) - (c * y0))) + (t * ((c * i) - (a * b)))) + t_1);
	elseif (a <= 2.35e+126)
		tmp = t_4;
	elseif (a <= 5.4e+160)
		tmp = t * (((j * ((b * y4) - (i * y5))) - (z * ((a * b) - (c * i)))) + (y2 * ((a * y5) - (c * y4))));
	else
		tmp = a * (((y1 * ((z * y3) - (x * y2))) + (b * t_2)) + (y5 * ((t * y2) - (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_] := Block[{t$95$1 = N[(k * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(y0 * N[(N[(N[(y5 * N[(N[(j * y3), $MachinePrecision] - N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(c * t$95$3), $MachinePrecision]), $MachinePrecision] + N[(b * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -1.9e+172], N[(b * N[(a * t$95$2), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -2.5e+111], N[(z * N[(t$95$1 - N[(c * N[(y0 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -4.7e+86], N[(N[(y3 * y5), $MachinePrecision] * N[(N[(j * y0), $MachinePrecision] - N[(y * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -1.08e+64], N[(i * N[(k * N[(z * (-y1)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -2.1e+31], N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -6e-143], N[(c * N[(N[(N[(i * N[(N[(z * t), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * t$95$3), $MachinePrecision]), $MachinePrecision] + N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 5e-161], t$95$4, If[LessEqual[a, 1.88e-56], N[(z * N[(N[(N[(y3 * N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(t * N[(N[(c * i), $MachinePrecision] - N[(a * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 2.35e+126], t$95$4, If[LessEqual[a, 5.4e+160], N[(t * N[(N[(N[(j * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(z * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y2 * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(a * N[(N[(N[(y1 * N[(N[(z * y3), $MachinePrecision] - N[(x * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(b * t$95$2), $MachinePrecision]), $MachinePrecision] + N[(y5 * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]]]

Derivation

1. Split input into 10 regimes

2. if a < -1.89999999999999985e172

   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. Taylor expanded in b around inf 44.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 69.0%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 69.0%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 69.0%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 69.0%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 69.0%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 69.0%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   if -1.89999999999999985e172 < a < -2.4999999999999998e111

   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. Taylor expanded in z around -inf 63.9%

      \[\leadsto \color{blue}{-1 \cdot \left(z \cdot \left(\left(t \cdot \left(a \cdot b - c \cdot i\right) + y3 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   3. Taylor expanded in y0 around inf 73.2%

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

      1. *-commutative 73.2%

         \[\leadsto -1 \cdot \left(z \cdot \left(c \cdot \color{blue}{\left(y3 \cdot y0\right)} - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) \]

   5. Simplified 73.2%

      \[\leadsto -1 \cdot \left(z \cdot \left(\color{blue}{c \cdot \left(y3 \cdot y0\right)} - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) \]

   if -2.4999999999999998e111 < a < -4.7000000000000002e86

   1. Initial program 40.0%

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

   2. Taylor expanded in y3 around -inf 60.0%

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

   3. Taylor expanded in y5 around inf 80.0%

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

      1. associate-*r* 80.0%

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

      2. distribute-lft-out-- 80.0%

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

      3. *-commutative 80.0%

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

   5. Simplified 80.0%

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

   if -4.7000000000000002e86 < a < -1.08000000000000007e64

   1. Initial program 59.7%

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

   2. Taylor expanded in k around inf 51.1%

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

   3. Taylor expanded in y1 around inf 71.1%

      \[\leadsto \color{blue}{k \cdot \left(y1 \cdot \left(y2 \cdot y4 - i \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 71.1%

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

      2. *-commutative 71.1%

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

      3. *-commutative 71.1%

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

      4. *-commutative 71.1%

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

   5. Simplified 71.1%

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

   6. Taylor expanded in y4 around 0 80.6%

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

      1. mul-1-neg 80.6%

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

      2. *-commutative 80.6%

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

      3. distribute-rgt-neg-in 80.6%

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

      4. *-commutative 80.6%

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

   8. Simplified 80.6%

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

   if -1.08000000000000007e64 < a < -2.09999999999999979e31

   1. Initial program 44.3%

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

   2. Taylor expanded in j around inf 55.7%

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

   3. Taylor expanded in x around inf 78.0%

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

      1. *-commutative 78.0%

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

      2. *-commutative 78.0%

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

      3. *-commutative 78.0%

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

   5. Simplified 78.0%

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

   if -2.09999999999999979e31 < a < -5.9999999999999997e-143

   1. Initial program 43.3%

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

   2. Taylor expanded in c around inf 70.4%

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

   if -5.9999999999999997e-143 < a < 4.9999999999999999e-161 or 1.8799999999999999e-56 < a < 2.3499999999999999e126

   1. Initial program 33.5%

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

   2. Taylor expanded in y0 around inf 56.1%

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

   if 4.9999999999999999e-161 < a < 1.8799999999999999e-56

   1. Initial program 18.0%

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

   2. Taylor expanded in z around -inf 71.2%

      \[\leadsto \color{blue}{-1 \cdot \left(z \cdot \left(\left(t \cdot \left(a \cdot b - c \cdot i\right) + y3 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   if 2.3499999999999999e126 < a < 5.4e160

   1. Initial program 1.4%

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

   2. Taylor expanded in t around inf 85.7%

      \[\leadsto \color{blue}{t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   if 5.4e160 < a

   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. Taylor expanded in a around inf 71.9%

      \[\leadsto \color{blue}{a \cdot \left(\left(-1 \cdot \left(y1 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) + b \cdot \left(x \cdot y - t \cdot z\right)\right) - -1 \cdot \left(y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
3. Recombined 10 regimes into one program.

4. Final simplification 65.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;a \leq -1.9 \cdot 10^{+172}:\\ \;\;\;\;b \cdot \left(a \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;a \leq -2.5 \cdot 10^{+111}:\\ \;\;\;\;z \cdot \left(k \cdot \left(b \cdot y0 - i \cdot y1\right) - c \cdot \left(y0 \cdot y3\right)\right)\\ \mathbf{elif}\;a \leq -4.7 \cdot 10^{+86}:\\ \;\;\;\;\left(y3 \cdot y5\right) \cdot \left(j \cdot y0 - y \cdot a\right)\\ \mathbf{elif}\;a \leq -1.08 \cdot 10^{+64}:\\ \;\;\;\;i \cdot \left(k \cdot \left(z \cdot \left(-y1\right)\right)\right)\\ \mathbf{elif}\;a \leq -2.1 \cdot 10^{+31}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;a \leq -6 \cdot 10^{-143}:\\ \;\;\;\;c \cdot \left(\left(i \cdot \left(z \cdot t - x \cdot y\right) + y0 \cdot \left(x \cdot y2 - z \cdot y3\right)\right) + y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;a \leq 5 \cdot 10^{-161}:\\ \;\;\;\;y0 \cdot \left(\left(y5 \cdot \left(j \cdot y3 - k \cdot y2\right) + c \cdot \left(x \cdot y2 - z \cdot y3\right)\right) + b \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;a \leq 1.88 \cdot 10^{-56}:\\ \;\;\;\;z \cdot \left(\left(y3 \cdot \left(a \cdot y1 - c \cdot y0\right) + t \cdot \left(c \cdot i - a \cdot b\right)\right) + k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;a \leq 2.35 \cdot 10^{+126}:\\ \;\;\;\;y0 \cdot \left(\left(y5 \cdot \left(j \cdot y3 - k \cdot y2\right) + c \cdot \left(x \cdot y2 - z \cdot y3\right)\right) + b \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;a \leq 5.4 \cdot 10^{+160}:\\ \;\;\;\;t \cdot \left(\left(j \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(a \cdot b - c \cdot i\right)\right) + y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(\left(y1 \cdot \left(z \cdot y3 - x \cdot y2\right) + b \cdot \left(x \cdot y - z \cdot t\right)\right) + y5 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\\ \end{array} \]

Alternative 8: 32.9% accurate, 1.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := z \cdot \left(k \cdot \left(b \cdot y0 - i \cdot y1\right) - c \cdot \left(y0 \cdot y3\right)\right)\\ t_2 := a \cdot \left(x \cdot y - z \cdot t\right)\\ \mathbf{if}\;a \leq -2.2 \cdot 10^{+170}:\\ \;\;\;\;b \cdot t_2\\ \mathbf{elif}\;a \leq -2 \cdot 10^{+111}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -1.05 \cdot 10^{+89}:\\ \;\;\;\;\left(y3 \cdot y5\right) \cdot \left(j \cdot y0 - y \cdot a\right)\\ \mathbf{elif}\;a \leq -3.2 \cdot 10^{+71}:\\ \;\;\;\;y0 \cdot \left(y3 \cdot \left(j \cdot y5 - z \cdot c\right)\right)\\ \mathbf{elif}\;a \leq -5.2 \cdot 10^{-136}:\\ \;\;\;\;x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;a \leq -2.5 \cdot 10^{-248}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 1.42 \cdot 10^{-157}:\\ \;\;\;\;\left(k \cdot y0\right) \cdot \left(z \cdot b - y2 \cdot y5\right)\\ \mathbf{elif}\;a \leq 9.6 \cdot 10^{-57}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 2.4 \cdot 10^{+54}:\\ \;\;\;\;b \cdot \left(\left(t_2 + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;a \leq 7 \cdot 10^{+157}:\\ \;\;\;\;z \cdot \left(y3 \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\\ \mathbf{elif}\;a \leq 6.5 \cdot 10^{+194}:\\ \;\;\;\;k \cdot \left(y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{elif}\;a \leq 9.6 \cdot 10^{+209}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(z \cdot a\right) \cdot \left(y1 \cdot y3 - t \cdot b\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* z (- (* k (- (* b y0) (* i y1))) (* c (* y0 y3)))))
        (t_2 (* a (- (* x y) (* z t)))))
   (if (<= a -2.2e+170)
     (* b t_2)
     (if (<= a -2e+111)
       t_1
       (if (<= a -1.05e+89)
         (* (* y3 y5) (- (* j y0) (* y a)))
         (if (<= a -3.2e+71)
           (* y0 (* y3 (- (* j y5) (* z c))))
           (if (<= a -5.2e-136)
             (*
              x
              (+
               (+ (* y (- (* a b) (* c i))) (* y2 (- (* c y0) (* a y1))))
               (* j (- (* i y1) (* b y0)))))
             (if (<= a -2.5e-248)
               t_1
               (if (<= a 1.42e-157)
                 (* (* k y0) (- (* z b) (* y2 y5)))
                 (if (<= a 9.6e-57)
                   t_1
                   (if (<= a 2.4e+54)
                     (*
                      b
                      (+
                       (+ t_2 (* y4 (- (* t j) (* y k))))
                       (* y0 (- (* z k) (* x j)))))
                     (if (<= a 7e+157)
                       (* z (* y3 (- (* a y1) (* c y0))))
                       (if (<= a 6.5e+194)
                         (* k (* y (- (* i y5) (* b y4))))
                         (if (<= a 9.6e+209)
                           (* j (* y0 (- (* y3 y5) (* x b))))
                           (* (* z a) (- (* y1 y3) (* t b)))))))))))))))))

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 = z * ((k * ((b * y0) - (i * y1))) - (c * (y0 * y3)));
	double t_2 = a * ((x * y) - (z * t));
	double tmp;
	if (a <= -2.2e+170) {
		tmp = b * t_2;
	} else if (a <= -2e+111) {
		tmp = t_1;
	} else if (a <= -1.05e+89) {
		tmp = (y3 * y5) * ((j * y0) - (y * a));
	} else if (a <= -3.2e+71) {
		tmp = y0 * (y3 * ((j * y5) - (z * c)));
	} else if (a <= -5.2e-136) {
		tmp = x * (((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1)))) + (j * ((i * y1) - (b * y0))));
	} else if (a <= -2.5e-248) {
		tmp = t_1;
	} else if (a <= 1.42e-157) {
		tmp = (k * y0) * ((z * b) - (y2 * y5));
	} else if (a <= 9.6e-57) {
		tmp = t_1;
	} else if (a <= 2.4e+54) {
		tmp = b * ((t_2 + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))));
	} else if (a <= 7e+157) {
		tmp = z * (y3 * ((a * y1) - (c * y0)));
	} else if (a <= 6.5e+194) {
		tmp = k * (y * ((i * y5) - (b * y4)));
	} else if (a <= 9.6e+209) {
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	} else {
		tmp = (z * a) * ((y1 * y3) - (t * b));
	}
	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 = z * ((k * ((b * y0) - (i * y1))) - (c * (y0 * y3)))
    t_2 = a * ((x * y) - (z * t))
    if (a <= (-2.2d+170)) then
        tmp = b * t_2
    else if (a <= (-2d+111)) then
        tmp = t_1
    else if (a <= (-1.05d+89)) then
        tmp = (y3 * y5) * ((j * y0) - (y * a))
    else if (a <= (-3.2d+71)) then
        tmp = y0 * (y3 * ((j * y5) - (z * c)))
    else if (a <= (-5.2d-136)) then
        tmp = x * (((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1)))) + (j * ((i * y1) - (b * y0))))
    else if (a <= (-2.5d-248)) then
        tmp = t_1
    else if (a <= 1.42d-157) then
        tmp = (k * y0) * ((z * b) - (y2 * y5))
    else if (a <= 9.6d-57) then
        tmp = t_1
    else if (a <= 2.4d+54) then
        tmp = b * ((t_2 + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))))
    else if (a <= 7d+157) then
        tmp = z * (y3 * ((a * y1) - (c * y0)))
    else if (a <= 6.5d+194) then
        tmp = k * (y * ((i * y5) - (b * y4)))
    else if (a <= 9.6d+209) then
        tmp = j * (y0 * ((y3 * y5) - (x * b)))
    else
        tmp = (z * a) * ((y1 * y3) - (t * b))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = z * ((k * ((b * y0) - (i * y1))) - (c * (y0 * y3)));
	double t_2 = a * ((x * y) - (z * t));
	double tmp;
	if (a <= -2.2e+170) {
		tmp = b * t_2;
	} else if (a <= -2e+111) {
		tmp = t_1;
	} else if (a <= -1.05e+89) {
		tmp = (y3 * y5) * ((j * y0) - (y * a));
	} else if (a <= -3.2e+71) {
		tmp = y0 * (y3 * ((j * y5) - (z * c)));
	} else if (a <= -5.2e-136) {
		tmp = x * (((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1)))) + (j * ((i * y1) - (b * y0))));
	} else if (a <= -2.5e-248) {
		tmp = t_1;
	} else if (a <= 1.42e-157) {
		tmp = (k * y0) * ((z * b) - (y2 * y5));
	} else if (a <= 9.6e-57) {
		tmp = t_1;
	} else if (a <= 2.4e+54) {
		tmp = b * ((t_2 + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))));
	} else if (a <= 7e+157) {
		tmp = z * (y3 * ((a * y1) - (c * y0)));
	} else if (a <= 6.5e+194) {
		tmp = k * (y * ((i * y5) - (b * y4)));
	} else if (a <= 9.6e+209) {
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	} else {
		tmp = (z * a) * ((y1 * y3) - (t * b));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = z * ((k * ((b * y0) - (i * y1))) - (c * (y0 * y3)))
	t_2 = a * ((x * y) - (z * t))
	tmp = 0
	if a <= -2.2e+170:
		tmp = b * t_2
	elif a <= -2e+111:
		tmp = t_1
	elif a <= -1.05e+89:
		tmp = (y3 * y5) * ((j * y0) - (y * a))
	elif a <= -3.2e+71:
		tmp = y0 * (y3 * ((j * y5) - (z * c)))
	elif a <= -5.2e-136:
		tmp = x * (((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1)))) + (j * ((i * y1) - (b * y0))))
	elif a <= -2.5e-248:
		tmp = t_1
	elif a <= 1.42e-157:
		tmp = (k * y0) * ((z * b) - (y2 * y5))
	elif a <= 9.6e-57:
		tmp = t_1
	elif a <= 2.4e+54:
		tmp = b * ((t_2 + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))))
	elif a <= 7e+157:
		tmp = z * (y3 * ((a * y1) - (c * y0)))
	elif a <= 6.5e+194:
		tmp = k * (y * ((i * y5) - (b * y4)))
	elif a <= 9.6e+209:
		tmp = j * (y0 * ((y3 * y5) - (x * b)))
	else:
		tmp = (z * a) * ((y1 * y3) - (t * b))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(z * Float64(Float64(k * Float64(Float64(b * y0) - Float64(i * y1))) - Float64(c * Float64(y0 * y3))))
	t_2 = Float64(a * Float64(Float64(x * y) - Float64(z * t)))
	tmp = 0.0
	if (a <= -2.2e+170)
		tmp = Float64(b * t_2);
	elseif (a <= -2e+111)
		tmp = t_1;
	elseif (a <= -1.05e+89)
		tmp = Float64(Float64(y3 * y5) * Float64(Float64(j * y0) - Float64(y * a)));
	elseif (a <= -3.2e+71)
		tmp = Float64(y0 * Float64(y3 * Float64(Float64(j * y5) - Float64(z * c))));
	elseif (a <= -5.2e-136)
		tmp = Float64(x * Float64(Float64(Float64(y * Float64(Float64(a * b) - Float64(c * i))) + Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1)))) + Float64(j * Float64(Float64(i * y1) - Float64(b * y0)))));
	elseif (a <= -2.5e-248)
		tmp = t_1;
	elseif (a <= 1.42e-157)
		tmp = Float64(Float64(k * y0) * Float64(Float64(z * b) - Float64(y2 * y5)));
	elseif (a <= 9.6e-57)
		tmp = t_1;
	elseif (a <= 2.4e+54)
		tmp = Float64(b * Float64(Float64(t_2 + Float64(y4 * Float64(Float64(t * j) - Float64(y * k)))) + Float64(y0 * Float64(Float64(z * k) - Float64(x * j)))));
	elseif (a <= 7e+157)
		tmp = Float64(z * Float64(y3 * Float64(Float64(a * y1) - Float64(c * y0))));
	elseif (a <= 6.5e+194)
		tmp = Float64(k * Float64(y * Float64(Float64(i * y5) - Float64(b * y4))));
	elseif (a <= 9.6e+209)
		tmp = Float64(j * Float64(y0 * Float64(Float64(y3 * y5) - Float64(x * b))));
	else
		tmp = Float64(Float64(z * a) * Float64(Float64(y1 * y3) - Float64(t * b)));
	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 = z * ((k * ((b * y0) - (i * y1))) - (c * (y0 * y3)));
	t_2 = a * ((x * y) - (z * t));
	tmp = 0.0;
	if (a <= -2.2e+170)
		tmp = b * t_2;
	elseif (a <= -2e+111)
		tmp = t_1;
	elseif (a <= -1.05e+89)
		tmp = (y3 * y5) * ((j * y0) - (y * a));
	elseif (a <= -3.2e+71)
		tmp = y0 * (y3 * ((j * y5) - (z * c)));
	elseif (a <= -5.2e-136)
		tmp = x * (((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1)))) + (j * ((i * y1) - (b * y0))));
	elseif (a <= -2.5e-248)
		tmp = t_1;
	elseif (a <= 1.42e-157)
		tmp = (k * y0) * ((z * b) - (y2 * y5));
	elseif (a <= 9.6e-57)
		tmp = t_1;
	elseif (a <= 2.4e+54)
		tmp = b * ((t_2 + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))));
	elseif (a <= 7e+157)
		tmp = z * (y3 * ((a * y1) - (c * y0)));
	elseif (a <= 6.5e+194)
		tmp = k * (y * ((i * y5) - (b * y4)));
	elseif (a <= 9.6e+209)
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	else
		tmp = (z * a) * ((y1 * y3) - (t * b));
	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[(z * N[(N[(k * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(c * N[(y0 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(a * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -2.2e+170], N[(b * t$95$2), $MachinePrecision], If[LessEqual[a, -2e+111], t$95$1, If[LessEqual[a, -1.05e+89], N[(N[(y3 * y5), $MachinePrecision] * N[(N[(j * y0), $MachinePrecision] - N[(y * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -3.2e+71], N[(y0 * N[(y3 * N[(N[(j * y5), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -5.2e-136], N[(x * N[(N[(N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(j * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -2.5e-248], t$95$1, If[LessEqual[a, 1.42e-157], N[(N[(k * y0), $MachinePrecision] * N[(N[(z * b), $MachinePrecision] - N[(y2 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 9.6e-57], t$95$1, If[LessEqual[a, 2.4e+54], N[(b * N[(N[(t$95$2 + N[(y4 * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 7e+157], N[(z * N[(y3 * N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 6.5e+194], N[(k * N[(y * N[(N[(i * y5), $MachinePrecision] - N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 9.6e+209], N[(j * N[(y0 * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(z * a), $MachinePrecision] * N[(N[(y1 * y3), $MachinePrecision] - N[(t * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]]]

Derivation

1. Split input into 11 regimes

2. if a < -2.19999999999999989e170

   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. Taylor expanded in b around inf 44.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 69.0%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 69.0%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 69.0%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 69.0%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 69.0%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 69.0%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   if -2.19999999999999989e170 < a < -1.99999999999999991e111 or -5.19999999999999993e-136 < a < -2.5e-248 or 1.42000000000000001e-157 < a < 9.60000000000000025e-57

   1. Initial program 21.0%

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

   2. Taylor expanded in z around -inf 64.8%

      \[\leadsto \color{blue}{-1 \cdot \left(z \cdot \left(\left(t \cdot \left(a \cdot b - c \cdot i\right) + y3 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   3. Taylor expanded in y0 around inf 59.4%

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

      1. *-commutative 59.4%

         \[\leadsto -1 \cdot \left(z \cdot \left(c \cdot \color{blue}{\left(y3 \cdot y0\right)} - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) \]

   5. Simplified 59.4%

      \[\leadsto -1 \cdot \left(z \cdot \left(\color{blue}{c \cdot \left(y3 \cdot y0\right)} - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) \]

   if -1.99999999999999991e111 < a < -1.04999999999999993e89

   1. Initial program 40.0%

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

   2. Taylor expanded in y3 around -inf 60.0%

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

   3. Taylor expanded in y5 around inf 80.0%

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

      1. associate-*r* 80.0%

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

      2. distribute-lft-out-- 80.0%

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

      3. *-commutative 80.0%

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

   5. Simplified 80.0%

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

   if -1.04999999999999993e89 < a < -3.20000000000000023e71

   1. Initial program 49.6%

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

   2. Taylor expanded in y0 around inf 51.5%

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

   3. Taylor expanded in y3 around -inf 75.9%

      \[\leadsto \color{blue}{-1 \cdot \left(y0 \cdot \left(y3 \cdot \left(-1 \cdot \left(j \cdot y5\right) + c \cdot z\right)\right)\right)} \]
   4. Step-by-step derivation

      1. mul-1-neg 75.9%

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

      2. distribute-rgt-neg-in 75.9%

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

      3. distribute-rgt-neg-in 75.9%

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

      4. +-commutative 75.9%

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

      5. mul-1-neg 75.9%

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

      6. unsub-neg 75.9%

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

   5. Simplified 75.9%

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

   if -3.20000000000000023e71 < a < -5.19999999999999993e-136

   1. Initial program 47.3%

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

   2. Taylor expanded in x around inf 59.0%

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

   if -2.5e-248 < a < 1.42000000000000001e-157

   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. Taylor expanded in y0 around inf 48.9%

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

   3. Taylor expanded in k around inf 44.8%

      \[\leadsto \color{blue}{k \cdot \left(y0 \cdot \left(-1 \cdot \left(y2 \cdot y5\right) - -1 \cdot \left(b \cdot z\right)\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 49.0%

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

      2. distribute-lft-out-- 49.0%

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

      3. *-commutative 49.0%

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

   5. Simplified 49.0%

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

   if 9.60000000000000025e-57 < a < 2.39999999999999998e54

   1. Initial program 25.9%

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

   2. Taylor expanded in b around inf 48.7%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   if 2.39999999999999998e54 < a < 7.00000000000000004e157

   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. Taylor expanded in y3 around -inf 53.2%

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

   3. Taylor expanded in z around inf 59.7%

      \[\leadsto -1 \cdot \color{blue}{\left(y3 \cdot \left(z \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 59.7%

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

      2. associate-*l* 59.7%

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

   5. Simplified 59.7%

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

   if 7.00000000000000004e157 < a < 6.50000000000000005e194

   1. Initial program 18.7%

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

   2. Taylor expanded in k around inf 54.7%

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

   3. Taylor expanded in y around inf 82.0%

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

   if 6.50000000000000005e194 < a < 9.59999999999999983e209

   1. Initial program 100.0%

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

   2. Taylor expanded in j around inf 100.0%

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

   3. Taylor expanded in y0 around inf 100.0%

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

   if 9.59999999999999983e209 < a

   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. Taylor expanded in z around -inf 77.5%

      \[\leadsto \color{blue}{-1 \cdot \left(z \cdot \left(\left(t \cdot \left(a \cdot b - c \cdot i\right) + y3 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   3. Taylor expanded in a around inf 61.3%

      \[\leadsto -1 \cdot \color{blue}{\left(a \cdot \left(z \cdot \left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right)\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 62.4%

         \[\leadsto -1 \cdot \color{blue}{\left(\left(a \cdot z\right) \cdot \left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right)\right)} \]

      2. *-commutative 62.4%

         \[\leadsto -1 \cdot \left(\color{blue}{\left(z \cdot a\right)} \cdot \left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right)\right) \]

      3. +-commutative 62.4%

         \[\leadsto -1 \cdot \left(\left(z \cdot a\right) \cdot \color{blue}{\left(b \cdot t + -1 \cdot \left(y1 \cdot y3\right)\right)}\right) \]

      4. mul-1-neg 62.4%

         \[\leadsto -1 \cdot \left(\left(z \cdot a\right) \cdot \left(b \cdot t + \color{blue}{\left(-y1 \cdot y3\right)}\right)\right) \]

      5. unsub-neg 62.4%

         \[\leadsto -1 \cdot \left(\left(z \cdot a\right) \cdot \color{blue}{\left(b \cdot t - y1 \cdot y3\right)}\right) \]

      6. *-commutative 62.4%

         \[\leadsto -1 \cdot \left(\left(z \cdot a\right) \cdot \left(b \cdot t - \color{blue}{y3 \cdot y1}\right)\right) \]

   5. Simplified 62.4%

      \[\leadsto -1 \cdot \color{blue}{\left(\left(z \cdot a\right) \cdot \left(b \cdot t - y3 \cdot y1\right)\right)} \]
3. Recombined 11 regimes into one program.

4. Final simplification 59.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;a \leq -2.2 \cdot 10^{+170}:\\ \;\;\;\;b \cdot \left(a \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;a \leq -2 \cdot 10^{+111}:\\ \;\;\;\;z \cdot \left(k \cdot \left(b \cdot y0 - i \cdot y1\right) - c \cdot \left(y0 \cdot y3\right)\right)\\ \mathbf{elif}\;a \leq -1.05 \cdot 10^{+89}:\\ \;\;\;\;\left(y3 \cdot y5\right) \cdot \left(j \cdot y0 - y \cdot a\right)\\ \mathbf{elif}\;a \leq -3.2 \cdot 10^{+71}:\\ \;\;\;\;y0 \cdot \left(y3 \cdot \left(j \cdot y5 - z \cdot c\right)\right)\\ \mathbf{elif}\;a \leq -5.2 \cdot 10^{-136}:\\ \;\;\;\;x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;a \leq -2.5 \cdot 10^{-248}:\\ \;\;\;\;z \cdot \left(k \cdot \left(b \cdot y0 - i \cdot y1\right) - c \cdot \left(y0 \cdot y3\right)\right)\\ \mathbf{elif}\;a \leq 1.42 \cdot 10^{-157}:\\ \;\;\;\;\left(k \cdot y0\right) \cdot \left(z \cdot b - y2 \cdot y5\right)\\ \mathbf{elif}\;a \leq 9.6 \cdot 10^{-57}:\\ \;\;\;\;z \cdot \left(k \cdot \left(b \cdot y0 - i \cdot y1\right) - c \cdot \left(y0 \cdot y3\right)\right)\\ \mathbf{elif}\;a \leq 2.4 \cdot 10^{+54}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;a \leq 7 \cdot 10^{+157}:\\ \;\;\;\;z \cdot \left(y3 \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\\ \mathbf{elif}\;a \leq 6.5 \cdot 10^{+194}:\\ \;\;\;\;k \cdot \left(y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{elif}\;a \leq 9.6 \cdot 10^{+209}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(z \cdot a\right) \cdot \left(y1 \cdot y3 - t \cdot b\right)\\ \end{array} \]

Alternative 9: 42.2% accurate, 2.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot b - c \cdot i\\ t_2 := t \cdot \left(\left(j \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot t_1\right) + y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ t_3 := x \cdot \left(\left(y \cdot t_1 + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ t_4 := y \cdot y3 - t \cdot y2\\ t_5 := t \cdot j - y \cdot k\\ \mathbf{if}\;t \leq -7.8 \cdot 10^{+115}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t \leq -290000000000:\\ \;\;\;\;y5 \cdot \left(a \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(y0 \cdot \left(j \cdot y3 - k \cdot y2\right) - i \cdot t_5\right)\right)\\ \mathbf{elif}\;t \leq -1.75 \cdot 10^{-152}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;t \leq 7.2 \cdot 10^{-293}:\\ \;\;\;\;y4 \cdot \left(\left(b \cdot t_5 + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot t_4\right)\\ \mathbf{elif}\;t \leq 7 \cdot 10^{-257}:\\ \;\;\;\;y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) + \left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\right)\\ \mathbf{elif}\;t \leq 1.7 \cdot 10^{-227}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;t \leq 7.2 \cdot 10^{-27}:\\ \;\;\;\;c \cdot \left(\left(i \cdot \left(z \cdot t - x \cdot y\right) + y0 \cdot \left(x \cdot y2 - z \cdot y3\right)\right) + y4 \cdot t_4\right)\\ \mathbf{elif}\;t \leq 4.4 \cdot 10^{+95}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot t_5\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* a b) (* c i)))
        (t_2
         (*
          t
          (+
           (- (* j (- (* b y4) (* i y5))) (* z t_1))
           (* y2 (- (* a y5) (* c y4))))))
        (t_3
         (*
          x
          (+
           (+ (* y t_1) (* y2 (- (* c y0) (* a y1))))
           (* j (- (* i y1) (* b y0))))))
        (t_4 (- (* y y3) (* t y2)))
        (t_5 (- (* t j) (* y k))))
   (if (<= t -7.8e+115)
     t_2
     (if (<= t -290000000000.0)
       (*
        y5
        (+
         (* a (- (* t y2) (* y y3)))
         (- (* y0 (- (* j y3) (* k y2))) (* i t_5))))
       (if (<= t -1.75e-152)
         t_3
         (if (<= t 7.2e-293)
           (* y4 (+ (+ (* b t_5) (* y1 (- (* k y2) (* j y3)))) (* c t_4)))
           (if (<= t 7e-257)
             (*
              y3
              (+
               (* y (- (* c y4) (* a y5)))
               (+ (* j (- (* y0 y5) (* y1 y4))) (* z (- (* a y1) (* c y0))))))
             (if (<= t 1.7e-227)
               t_3
               (if (<= t 7.2e-27)
                 (*
                  c
                  (+
                   (+ (* i (- (* z t) (* x y))) (* y0 (- (* x y2) (* z y3))))
                   (* y4 t_4)))
                 (if (<= t 4.4e+95)
                   (*
                    b
                    (+
                     (+ (* a (- (* x y) (* z t))) (* y4 t_5))
                     (* y0 (- (* z k) (* x j)))))
                   t_2))))))))))

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 = (a * b) - (c * i);
	double t_2 = t * (((j * ((b * y4) - (i * y5))) - (z * t_1)) + (y2 * ((a * y5) - (c * y4))));
	double t_3 = x * (((y * t_1) + (y2 * ((c * y0) - (a * y1)))) + (j * ((i * y1) - (b * y0))));
	double t_4 = (y * y3) - (t * y2);
	double t_5 = (t * j) - (y * k);
	double tmp;
	if (t <= -7.8e+115) {
		tmp = t_2;
	} else if (t <= -290000000000.0) {
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * t_5)));
	} else if (t <= -1.75e-152) {
		tmp = t_3;
	} else if (t <= 7.2e-293) {
		tmp = y4 * (((b * t_5) + (y1 * ((k * y2) - (j * y3)))) + (c * t_4));
	} else if (t <= 7e-257) {
		tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))));
	} else if (t <= 1.7e-227) {
		tmp = t_3;
	} else if (t <= 7.2e-27) {
		tmp = c * (((i * ((z * t) - (x * y))) + (y0 * ((x * y2) - (z * y3)))) + (y4 * t_4));
	} else if (t <= 4.4e+95) {
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * t_5)) + (y0 * ((z * k) - (x * j))));
	} else {
		tmp = t_2;
	}
	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 = (a * b) - (c * i)
    t_2 = t * (((j * ((b * y4) - (i * y5))) - (z * t_1)) + (y2 * ((a * y5) - (c * y4))))
    t_3 = x * (((y * t_1) + (y2 * ((c * y0) - (a * y1)))) + (j * ((i * y1) - (b * y0))))
    t_4 = (y * y3) - (t * y2)
    t_5 = (t * j) - (y * k)
    if (t <= (-7.8d+115)) then
        tmp = t_2
    else if (t <= (-290000000000.0d0)) then
        tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * t_5)))
    else if (t <= (-1.75d-152)) then
        tmp = t_3
    else if (t <= 7.2d-293) then
        tmp = y4 * (((b * t_5) + (y1 * ((k * y2) - (j * y3)))) + (c * t_4))
    else if (t <= 7d-257) then
        tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))))
    else if (t <= 1.7d-227) then
        tmp = t_3
    else if (t <= 7.2d-27) then
        tmp = c * (((i * ((z * t) - (x * y))) + (y0 * ((x * y2) - (z * y3)))) + (y4 * t_4))
    else if (t <= 4.4d+95) then
        tmp = b * (((a * ((x * y) - (z * t))) + (y4 * t_5)) + (y0 * ((z * k) - (x * j))))
    else
        tmp = t_2
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (a * b) - (c * i);
	double t_2 = t * (((j * ((b * y4) - (i * y5))) - (z * t_1)) + (y2 * ((a * y5) - (c * y4))));
	double t_3 = x * (((y * t_1) + (y2 * ((c * y0) - (a * y1)))) + (j * ((i * y1) - (b * y0))));
	double t_4 = (y * y3) - (t * y2);
	double t_5 = (t * j) - (y * k);
	double tmp;
	if (t <= -7.8e+115) {
		tmp = t_2;
	} else if (t <= -290000000000.0) {
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * t_5)));
	} else if (t <= -1.75e-152) {
		tmp = t_3;
	} else if (t <= 7.2e-293) {
		tmp = y4 * (((b * t_5) + (y1 * ((k * y2) - (j * y3)))) + (c * t_4));
	} else if (t <= 7e-257) {
		tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))));
	} else if (t <= 1.7e-227) {
		tmp = t_3;
	} else if (t <= 7.2e-27) {
		tmp = c * (((i * ((z * t) - (x * y))) + (y0 * ((x * y2) - (z * y3)))) + (y4 * t_4));
	} else if (t <= 4.4e+95) {
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * t_5)) + (y0 * ((z * k) - (x * j))));
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (a * b) - (c * i)
	t_2 = t * (((j * ((b * y4) - (i * y5))) - (z * t_1)) + (y2 * ((a * y5) - (c * y4))))
	t_3 = x * (((y * t_1) + (y2 * ((c * y0) - (a * y1)))) + (j * ((i * y1) - (b * y0))))
	t_4 = (y * y3) - (t * y2)
	t_5 = (t * j) - (y * k)
	tmp = 0
	if t <= -7.8e+115:
		tmp = t_2
	elif t <= -290000000000.0:
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * t_5)))
	elif t <= -1.75e-152:
		tmp = t_3
	elif t <= 7.2e-293:
		tmp = y4 * (((b * t_5) + (y1 * ((k * y2) - (j * y3)))) + (c * t_4))
	elif t <= 7e-257:
		tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))))
	elif t <= 1.7e-227:
		tmp = t_3
	elif t <= 7.2e-27:
		tmp = c * (((i * ((z * t) - (x * y))) + (y0 * ((x * y2) - (z * y3)))) + (y4 * t_4))
	elif t <= 4.4e+95:
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * t_5)) + (y0 * ((z * k) - (x * j))))
	else:
		tmp = t_2
	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(a * b) - Float64(c * i))
	t_2 = Float64(t * Float64(Float64(Float64(j * Float64(Float64(b * y4) - Float64(i * y5))) - Float64(z * t_1)) + Float64(y2 * Float64(Float64(a * y5) - Float64(c * y4)))))
	t_3 = Float64(x * Float64(Float64(Float64(y * t_1) + Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1)))) + Float64(j * Float64(Float64(i * y1) - Float64(b * y0)))))
	t_4 = Float64(Float64(y * y3) - Float64(t * y2))
	t_5 = Float64(Float64(t * j) - Float64(y * k))
	tmp = 0.0
	if (t <= -7.8e+115)
		tmp = t_2;
	elseif (t <= -290000000000.0)
		tmp = Float64(y5 * Float64(Float64(a * Float64(Float64(t * y2) - Float64(y * y3))) + Float64(Float64(y0 * Float64(Float64(j * y3) - Float64(k * y2))) - Float64(i * t_5))));
	elseif (t <= -1.75e-152)
		tmp = t_3;
	elseif (t <= 7.2e-293)
		tmp = Float64(y4 * Float64(Float64(Float64(b * t_5) + Float64(y1 * Float64(Float64(k * y2) - Float64(j * y3)))) + Float64(c * t_4)));
	elseif (t <= 7e-257)
		tmp = Float64(y3 * Float64(Float64(y * Float64(Float64(c * y4) - Float64(a * y5))) + Float64(Float64(j * Float64(Float64(y0 * y5) - Float64(y1 * y4))) + Float64(z * Float64(Float64(a * y1) - Float64(c * y0))))));
	elseif (t <= 1.7e-227)
		tmp = t_3;
	elseif (t <= 7.2e-27)
		tmp = Float64(c * Float64(Float64(Float64(i * Float64(Float64(z * t) - Float64(x * y))) + Float64(y0 * Float64(Float64(x * y2) - Float64(z * y3)))) + Float64(y4 * t_4)));
	elseif (t <= 4.4e+95)
		tmp = Float64(b * Float64(Float64(Float64(a * Float64(Float64(x * y) - Float64(z * t))) + Float64(y4 * t_5)) + Float64(y0 * Float64(Float64(z * k) - Float64(x * j)))));
	else
		tmp = t_2;
	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 = (a * b) - (c * i);
	t_2 = t * (((j * ((b * y4) - (i * y5))) - (z * t_1)) + (y2 * ((a * y5) - (c * y4))));
	t_3 = x * (((y * t_1) + (y2 * ((c * y0) - (a * y1)))) + (j * ((i * y1) - (b * y0))));
	t_4 = (y * y3) - (t * y2);
	t_5 = (t * j) - (y * k);
	tmp = 0.0;
	if (t <= -7.8e+115)
		tmp = t_2;
	elseif (t <= -290000000000.0)
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * t_5)));
	elseif (t <= -1.75e-152)
		tmp = t_3;
	elseif (t <= 7.2e-293)
		tmp = y4 * (((b * t_5) + (y1 * ((k * y2) - (j * y3)))) + (c * t_4));
	elseif (t <= 7e-257)
		tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * ((a * y1) - (c * y0)))));
	elseif (t <= 1.7e-227)
		tmp = t_3;
	elseif (t <= 7.2e-27)
		tmp = c * (((i * ((z * t) - (x * y))) + (y0 * ((x * y2) - (z * y3)))) + (y4 * t_4));
	elseif (t <= 4.4e+95)
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * t_5)) + (y0 * ((z * k) - (x * j))));
	else
		tmp = t_2;
	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[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(t * N[(N[(N[(j * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(z * t$95$1), $MachinePrecision]), $MachinePrecision] + N[(y2 * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(x * N[(N[(N[(y * t$95$1), $MachinePrecision] + N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(j * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -7.8e+115], t$95$2, If[LessEqual[t, -290000000000.0], N[(y5 * N[(N[(a * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(y0 * N[(N[(j * y3), $MachinePrecision] - N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(i * t$95$5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -1.75e-152], t$95$3, If[LessEqual[t, 7.2e-293], N[(y4 * N[(N[(N[(b * t$95$5), $MachinePrecision] + N[(y1 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(c * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 7e-257], N[(y3 * N[(N[(y * N[(N[(c * y4), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + 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]), $MachinePrecision], If[LessEqual[t, 1.7e-227], t$95$3, If[LessEqual[t, 7.2e-27], N[(c * N[(N[(N[(i * N[(N[(z * t), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y4 * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 4.4e+95], N[(b * N[(N[(N[(a * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y4 * t$95$5), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$2]]]]]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if t < -7.80000000000000012e115 or 4.3999999999999998e95 < t

   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. Taylor expanded in t around inf 64.5%

      \[\leadsto \color{blue}{t \cdot \left(\left(-1 \cdot \left(z \cdot \left(a \cdot b - c \cdot i\right)\right) + j \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   if -7.80000000000000012e115 < t < -2.9e11

   1. Initial program 26.1%

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

   2. Taylor expanded in y5 around -inf 83.0%

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

   if -2.9e11 < t < -1.7500000000000001e-152 or 7.00000000000000058e-257 < t < 1.69999999999999989e-227

   1. Initial program 42.1%

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

   2. Taylor expanded in x around inf 61.3%

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

   if -1.7500000000000001e-152 < t < 7.1999999999999997e-293

   1. Initial program 23.3%

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

   2. Taylor expanded in y4 around inf 59.1%

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

   if 7.1999999999999997e-293 < t < 7.00000000000000058e-257

   1. Initial program 83.3%

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

   2. Taylor expanded in y3 around -inf 83.8%

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

   if 1.69999999999999989e-227 < t < 7.1999999999999997e-27

   1. Initial program 40.3%

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

   2. Taylor expanded in c around inf 56.0%

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

   if 7.1999999999999997e-27 < t < 4.3999999999999998e95

   1. Initial program 24.5%

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

   2. Taylor expanded in b around inf 56.7%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 63.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -7.8 \cdot 10^{+115}:\\ \;\;\;\;t \cdot \left(\left(j \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(a \cdot b - c \cdot i\right)\right) + y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;t \leq -290000000000:\\ \;\;\;\;y5 \cdot \left(a \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(y0 \cdot \left(j \cdot y3 - k \cdot y2\right) - i \cdot \left(t \cdot j - y \cdot k\right)\right)\right)\\ \mathbf{elif}\;t \leq -1.75 \cdot 10^{-152}:\\ \;\;\;\;x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 7.2 \cdot 10^{-293}:\\ \;\;\;\;y4 \cdot \left(\left(b \cdot \left(t \cdot j - y \cdot k\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq 7 \cdot 10^{-257}:\\ \;\;\;\;y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) + \left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\right)\\ \mathbf{elif}\;t \leq 1.7 \cdot 10^{-227}:\\ \;\;\;\;x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 7.2 \cdot 10^{-27}:\\ \;\;\;\;c \cdot \left(\left(i \cdot \left(z \cdot t - x \cdot y\right) + y0 \cdot \left(x \cdot y2 - z \cdot y3\right)\right) + y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq 4.4 \cdot 10^{+95}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t \cdot \left(\left(j \cdot \left(b \cdot y4 - i \cdot y5\right) - z \cdot \left(a \cdot b - c \cdot i\right)\right) + y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \end{array} \]

Alternative 10: 42.1% accurate, 2.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot y1 - c \cdot y0\\ t_2 := z \cdot \left(\left(y3 \cdot t_1 + t \cdot \left(c \cdot i - a \cdot b\right)\right) + k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{if}\;z \leq -128000:\\ \;\;\;\;t_2\\ \mathbf{elif}\;z \leq -2.2 \cdot 10^{-102}:\\ \;\;\;\;y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) + \left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot t_1\right)\right)\\ \mathbf{elif}\;z \leq 6.2 \cdot 10^{-166} \lor \neg \left(z \leq 680000000000\right) \land z \leq 5.6 \cdot 10^{+49}:\\ \;\;\;\;y5 \cdot \left(a \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(y0 \cdot \left(j \cdot y3 - k \cdot y2\right) - i \cdot \left(t \cdot j - y \cdot k\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* a y1) (* c y0)))
        (t_2
         (*
          z
          (+
           (+ (* y3 t_1) (* t (- (* c i) (* a b))))
           (* k (- (* b y0) (* i y1)))))))
   (if (<= z -128000.0)
     t_2
     (if (<= z -2.2e-102)
       (*
        y3
        (+
         (* y (- (* c y4) (* a y5)))
         (+ (* j (- (* y0 y5) (* y1 y4))) (* z t_1))))
       (if (or (<= z 6.2e-166)
               (and (not (<= z 680000000000.0)) (<= z 5.6e+49)))
         (*
          y5
          (+
           (* a (- (* t y2) (* y y3)))
           (- (* y0 (- (* j y3) (* k y2))) (* i (- (* t j) (* y k))))))
         t_2)))))

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 = (a * y1) - (c * y0);
	double t_2 = z * (((y3 * t_1) + (t * ((c * i) - (a * b)))) + (k * ((b * y0) - (i * y1))));
	double tmp;
	if (z <= -128000.0) {
		tmp = t_2;
	} else if (z <= -2.2e-102) {
		tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * t_1)));
	} else if ((z <= 6.2e-166) || (!(z <= 680000000000.0) && (z <= 5.6e+49))) {
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * ((t * j) - (y * k)))));
	} else {
		tmp = t_2;
	}
	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 = (a * y1) - (c * y0)
    t_2 = z * (((y3 * t_1) + (t * ((c * i) - (a * b)))) + (k * ((b * y0) - (i * y1))))
    if (z <= (-128000.0d0)) then
        tmp = t_2
    else if (z <= (-2.2d-102)) then
        tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * t_1)))
    else if ((z <= 6.2d-166) .or. (.not. (z <= 680000000000.0d0)) .and. (z <= 5.6d+49)) then
        tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * ((t * j) - (y * k)))))
    else
        tmp = t_2
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (a * y1) - (c * y0);
	double t_2 = z * (((y3 * t_1) + (t * ((c * i) - (a * b)))) + (k * ((b * y0) - (i * y1))));
	double tmp;
	if (z <= -128000.0) {
		tmp = t_2;
	} else if (z <= -2.2e-102) {
		tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * t_1)));
	} else if ((z <= 6.2e-166) || (!(z <= 680000000000.0) && (z <= 5.6e+49))) {
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * ((t * j) - (y * k)))));
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (a * y1) - (c * y0)
	t_2 = z * (((y3 * t_1) + (t * ((c * i) - (a * b)))) + (k * ((b * y0) - (i * y1))))
	tmp = 0
	if z <= -128000.0:
		tmp = t_2
	elif z <= -2.2e-102:
		tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * t_1)))
	elif (z <= 6.2e-166) or (not (z <= 680000000000.0) and (z <= 5.6e+49)):
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * ((t * j) - (y * k)))))
	else:
		tmp = t_2
	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(a * y1) - Float64(c * y0))
	t_2 = Float64(z * Float64(Float64(Float64(y3 * t_1) + Float64(t * Float64(Float64(c * i) - Float64(a * b)))) + Float64(k * Float64(Float64(b * y0) - Float64(i * y1)))))
	tmp = 0.0
	if (z <= -128000.0)
		tmp = t_2;
	elseif (z <= -2.2e-102)
		tmp = Float64(y3 * Float64(Float64(y * Float64(Float64(c * y4) - Float64(a * y5))) + Float64(Float64(j * Float64(Float64(y0 * y5) - Float64(y1 * y4))) + Float64(z * t_1))));
	elseif ((z <= 6.2e-166) || (!(z <= 680000000000.0) && (z <= 5.6e+49)))
		tmp = Float64(y5 * Float64(Float64(a * Float64(Float64(t * y2) - Float64(y * y3))) + Float64(Float64(y0 * Float64(Float64(j * y3) - Float64(k * y2))) - Float64(i * Float64(Float64(t * j) - Float64(y * k))))));
	else
		tmp = t_2;
	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 = (a * y1) - (c * y0);
	t_2 = z * (((y3 * t_1) + (t * ((c * i) - (a * b)))) + (k * ((b * y0) - (i * y1))));
	tmp = 0.0;
	if (z <= -128000.0)
		tmp = t_2;
	elseif (z <= -2.2e-102)
		tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * t_1)));
	elseif ((z <= 6.2e-166) || (~((z <= 680000000000.0)) && (z <= 5.6e+49)))
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * ((t * j) - (y * k)))));
	else
		tmp = t_2;
	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[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(z * N[(N[(N[(y3 * t$95$1), $MachinePrecision] + N[(t * N[(N[(c * i), $MachinePrecision] - N[(a * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(k * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -128000.0], t$95$2, If[LessEqual[z, -2.2e-102], N[(y3 * N[(N[(y * N[(N[(c * y4), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(j * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(z * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[Or[LessEqual[z, 6.2e-166], And[N[Not[LessEqual[z, 680000000000.0]], $MachinePrecision], LessEqual[z, 5.6e+49]]], N[(y5 * N[(N[(a * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(y0 * N[(N[(j * y3), $MachinePrecision] - N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(i * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$2]]]]]

Derivation

1. Split input into 3 regimes

2. if z < -128000 or 6.19999999999999968e-166 < z < 6.8e11 or 5.5999999999999996e49 < z

   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. Taylor expanded in z around -inf 57.0%

      \[\leadsto \color{blue}{-1 \cdot \left(z \cdot \left(\left(t \cdot \left(a \cdot b - c \cdot i\right) + y3 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   if -128000 < z < -2.20000000000000013e-102

   1. Initial program 49.9%

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

   2. Taylor expanded in y3 around -inf 58.2%

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

   if -2.20000000000000013e-102 < z < 6.19999999999999968e-166 or 6.8e11 < z < 5.5999999999999996e49

   1. Initial program 30.5%

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

   2. Taylor expanded in y5 around -inf 60.3%

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

4. Final simplification 58.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -128000:\\ \;\;\;\;z \cdot \left(\left(y3 \cdot \left(a \cdot y1 - c \cdot y0\right) + t \cdot \left(c \cdot i - a \cdot b\right)\right) + k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq -2.2 \cdot 10^{-102}:\\ \;\;\;\;y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) + \left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\right)\\ \mathbf{elif}\;z \leq 6.2 \cdot 10^{-166} \lor \neg \left(z \leq 680000000000\right) \land z \leq 5.6 \cdot 10^{+49}:\\ \;\;\;\;y5 \cdot \left(a \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(y0 \cdot \left(j \cdot y3 - k \cdot y2\right) - i \cdot \left(t \cdot j - y \cdot k\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;z \cdot \left(\left(y3 \cdot \left(a \cdot y1 - c \cdot y0\right) + t \cdot \left(c \cdot i - a \cdot b\right)\right) + k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \end{array} \]

Alternative 11: 38.4% accurate, 2.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := t \cdot j - y \cdot k\\ t_2 := a \cdot y1 - c \cdot y0\\ \mathbf{if}\;z \leq -2.7 \cdot 10^{-19}:\\ \;\;\;\;\left(z \cdot y3\right) \cdot t_2\\ \mathbf{elif}\;z \leq -9.2 \cdot 10^{-104}:\\ \;\;\;\;y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) + \left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot t_2\right)\right)\\ \mathbf{elif}\;z \leq 1.75 \cdot 10^{-147}:\\ \;\;\;\;y5 \cdot \left(a \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(y0 \cdot \left(j \cdot y3 - k \cdot y2\right) - i \cdot t_1\right)\right)\\ \mathbf{elif}\;z \leq 7.5 \cdot 10^{+49}:\\ \;\;\;\;y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 9.6 \cdot 10^{+186}:\\ \;\;\;\;y4 \cdot \left(\left(b \cdot t_1 + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0 - t \cdot a\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* t j) (* y k))) (t_2 (- (* a y1) (* c y0))))
   (if (<= z -2.7e-19)
     (* (* z y3) t_2)
     (if (<= z -9.2e-104)
       (*
        y3
        (+
         (* y (- (* c y4) (* a y5)))
         (+ (* j (- (* y0 y5) (* y1 y4))) (* z t_2))))
       (if (<= z 1.75e-147)
         (*
          y5
          (+
           (* a (- (* t y2) (* y y3)))
           (- (* y0 (- (* j y3) (* k y2))) (* i t_1))))
         (if (<= z 7.5e+49)
           (*
            y2
            (+
             (+ (* k (- (* y1 y4) (* y0 y5))) (* x (- (* c y0) (* a y1))))
             (* t (- (* a y5) (* c y4)))))
           (if (<= z 9.6e+186)
             (*
              y4
              (+
               (+ (* b t_1) (* y1 (- (* k y2) (* j y3))))
               (* c (- (* y y3) (* t y2)))))
             (* b (* z (- (* k y0) (* t a)))))))))))

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 = (t * j) - (y * k);
	double t_2 = (a * y1) - (c * y0);
	double tmp;
	if (z <= -2.7e-19) {
		tmp = (z * y3) * t_2;
	} else if (z <= -9.2e-104) {
		tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * t_2)));
	} else if (z <= 1.75e-147) {
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * t_1)));
	} else if (z <= 7.5e+49) {
		tmp = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))));
	} else if (z <= 9.6e+186) {
		tmp = y4 * (((b * t_1) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	} else {
		tmp = b * (z * ((k * y0) - (t * a)));
	}
	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 = (t * j) - (y * k)
    t_2 = (a * y1) - (c * y0)
    if (z <= (-2.7d-19)) then
        tmp = (z * y3) * t_2
    else if (z <= (-9.2d-104)) then
        tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * t_2)))
    else if (z <= 1.75d-147) then
        tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * t_1)))
    else if (z <= 7.5d+49) then
        tmp = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))))
    else if (z <= 9.6d+186) then
        tmp = y4 * (((b * t_1) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))))
    else
        tmp = b * (z * ((k * y0) - (t * a)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (t * j) - (y * k);
	double t_2 = (a * y1) - (c * y0);
	double tmp;
	if (z <= -2.7e-19) {
		tmp = (z * y3) * t_2;
	} else if (z <= -9.2e-104) {
		tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * t_2)));
	} else if (z <= 1.75e-147) {
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * t_1)));
	} else if (z <= 7.5e+49) {
		tmp = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))));
	} else if (z <= 9.6e+186) {
		tmp = y4 * (((b * t_1) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	} else {
		tmp = b * (z * ((k * y0) - (t * a)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (t * j) - (y * k)
	t_2 = (a * y1) - (c * y0)
	tmp = 0
	if z <= -2.7e-19:
		tmp = (z * y3) * t_2
	elif z <= -9.2e-104:
		tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * t_2)))
	elif z <= 1.75e-147:
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * t_1)))
	elif z <= 7.5e+49:
		tmp = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))))
	elif z <= 9.6e+186:
		tmp = y4 * (((b * t_1) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))))
	else:
		tmp = b * (z * ((k * y0) - (t * a)))
	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(t * j) - Float64(y * k))
	t_2 = Float64(Float64(a * y1) - Float64(c * y0))
	tmp = 0.0
	if (z <= -2.7e-19)
		tmp = Float64(Float64(z * y3) * t_2);
	elseif (z <= -9.2e-104)
		tmp = Float64(y3 * Float64(Float64(y * Float64(Float64(c * y4) - Float64(a * y5))) + Float64(Float64(j * Float64(Float64(y0 * y5) - Float64(y1 * y4))) + Float64(z * t_2))));
	elseif (z <= 1.75e-147)
		tmp = Float64(y5 * Float64(Float64(a * Float64(Float64(t * y2) - Float64(y * y3))) + Float64(Float64(y0 * Float64(Float64(j * y3) - Float64(k * y2))) - Float64(i * t_1))));
	elseif (z <= 7.5e+49)
		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 <= 9.6e+186)
		tmp = Float64(y4 * Float64(Float64(Float64(b * t_1) + Float64(y1 * Float64(Float64(k * y2) - Float64(j * y3)))) + Float64(c * Float64(Float64(y * y3) - Float64(t * y2)))));
	else
		tmp = Float64(b * Float64(z * Float64(Float64(k * y0) - Float64(t * a))));
	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 = (t * j) - (y * k);
	t_2 = (a * y1) - (c * y0);
	tmp = 0.0;
	if (z <= -2.7e-19)
		tmp = (z * y3) * t_2;
	elseif (z <= -9.2e-104)
		tmp = y3 * ((y * ((c * y4) - (a * y5))) + ((j * ((y0 * y5) - (y1 * y4))) + (z * t_2)));
	elseif (z <= 1.75e-147)
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * t_1)));
	elseif (z <= 7.5e+49)
		tmp = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))));
	elseif (z <= 9.6e+186)
		tmp = y4 * (((b * t_1) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	else
		tmp = b * (z * ((k * y0) - (t * a)));
	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[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -2.7e-19], N[(N[(z * y3), $MachinePrecision] * t$95$2), $MachinePrecision], If[LessEqual[z, -9.2e-104], N[(y3 * N[(N[(y * N[(N[(c * y4), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(j * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(z * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.75e-147], N[(y5 * N[(N[(a * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(y0 * N[(N[(j * y3), $MachinePrecision] - N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(i * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 7.5e+49], 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, 9.6e+186], N[(y4 * N[(N[(N[(b * t$95$1), $MachinePrecision] + N[(y1 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(c * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(z * N[(N[(k * y0), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]

Derivation

1. Split input into 6 regimes

2. if z < -2.7000000000000001e-19

   1. Initial program 20.0%

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

   2. Taylor expanded in z around -inf 54.3%

      \[\leadsto \color{blue}{-1 \cdot \left(z \cdot \left(\left(t \cdot \left(a \cdot b - c \cdot i\right) + y3 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   3. Taylor expanded in y3 around inf 56.1%

      \[\leadsto -1 \cdot \color{blue}{\left(y3 \cdot \left(z \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 49.9%

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

   5. Simplified 49.9%

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

   if -2.7000000000000001e-19 < z < -9.1999999999999998e-104

   1. Initial program 52.3%

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

   2. Taylor expanded in y3 around -inf 57.8%

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

   if -9.1999999999999998e-104 < z < 1.75000000000000002e-147

   1. Initial program 29.5%

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

   2. Taylor expanded in y5 around -inf 57.0%

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

   if 1.75000000000000002e-147 < z < 7.4999999999999995e49

   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. Taylor expanded in y2 around inf 47.8%

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

   if 7.4999999999999995e49 < z < 9.5999999999999998e186

   1. Initial program 39.3%

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

   2. Taylor expanded in y4 around inf 57.4%

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

   if 9.5999999999999998e186 < z

   1. Initial program 41.3%

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

   2. Taylor expanded in b around inf 38.7%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in z around inf 64.9%

      \[\leadsto \color{blue}{b \cdot \left(z \cdot \left(-1 \cdot \left(a \cdot t\right) - -1 \cdot \left(k \cdot y0\right)\right)\right)} \]
   4. Step-by-step derivation

      1. distribute-lft-out-- 64.9%

         \[\leadsto b \cdot \left(z \cdot \color{blue}{\left(-1 \cdot \left(a \cdot t - k \cdot y0\right)\right)}\right) \]

      2. *-commutative 64.9%

         \[\leadsto b \cdot \left(z \cdot \left(-1 \cdot \left(a \cdot t - \color{blue}{y0 \cdot k}\right)\right)\right) \]

   5. Simplified 64.9%

      \[\leadsto \color{blue}{b \cdot \left(z \cdot \left(-1 \cdot \left(a \cdot t - y0 \cdot k\right)\right)\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 55.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -2.7 \cdot 10^{-19}:\\ \;\;\;\;\left(z \cdot y3\right) \cdot \left(a \cdot y1 - c \cdot y0\right)\\ \mathbf{elif}\;z \leq -9.2 \cdot 10^{-104}:\\ \;\;\;\;y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) + \left(j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right) + z \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\right)\\ \mathbf{elif}\;z \leq 1.75 \cdot 10^{-147}:\\ \;\;\;\;y5 \cdot \left(a \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(y0 \cdot \left(j \cdot y3 - k \cdot y2\right) - i \cdot \left(t \cdot j - y \cdot k\right)\right)\right)\\ \mathbf{elif}\;z \leq 7.5 \cdot 10^{+49}:\\ \;\;\;\;y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 9.6 \cdot 10^{+186}:\\ \;\;\;\;y4 \cdot \left(\left(b \cdot \left(t \cdot j - y \cdot k\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0 - t \cdot a\right)\right)\\ \end{array} \]

Alternative 12: 29.9% accurate, 2.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;a \leq -7.5 \cdot 10^{+169}:\\ \;\;\;\;b \cdot \left(a \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;a \leq -5.8 \cdot 10^{+122}:\\ \;\;\;\;z \cdot \left(k \cdot \left(b \cdot y0 - i \cdot y1\right) - c \cdot \left(y0 \cdot y3\right)\right)\\ \mathbf{elif}\;a \leq -5.5 \cdot 10^{+89}:\\ \;\;\;\;\left(y3 \cdot y5\right) \cdot \left(j \cdot y0 - y \cdot a\right)\\ \mathbf{elif}\;a \leq -1 \cdot 10^{+57}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;a \leq -6.5 \cdot 10^{+33}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;a \leq -1.35 \cdot 10^{-29}:\\ \;\;\;\;k \cdot \left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \mathbf{elif}\;a \leq -3.2 \cdot 10^{-145}:\\ \;\;\;\;y0 \cdot \left(x \cdot \left(c \cdot y2 - b \cdot j\right)\right)\\ \mathbf{elif}\;a \leq -3.1 \cdot 10^{-224}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \mathbf{elif}\;a \leq -4.8 \cdot 10^{-235}:\\ \;\;\;\;b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ \mathbf{elif}\;a \leq 1.82 \cdot 10^{-155}:\\ \;\;\;\;\left(k \cdot y0\right) \cdot \left(z \cdot b - y2 \cdot y5\right)\\ \mathbf{elif}\;a \leq 1.82 \cdot 10^{-25}:\\ \;\;\;\;\left(y3 \cdot y4\right) \cdot \left(y \cdot c - j \cdot y1\right)\\ \mathbf{elif}\;a \leq 42000000:\\ \;\;\;\;\left(k \cdot y5\right) \cdot \left(y \cdot i - y0 \cdot y2\right)\\ \mathbf{elif}\;a \leq 6 \cdot 10^{+33}:\\ \;\;\;\;y0 \cdot \left(y5 \cdot \left(j \cdot y3 - k \cdot y2\right)\right)\\ \mathbf{elif}\;a \leq 1.65 \cdot 10^{+59}:\\ \;\;\;\;t \cdot \left(z \cdot \left(c \cdot i - a \cdot b\right)\right)\\ \mathbf{else}:\\ \;\;\;\;z \cdot \left(y3 \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= a -7.5e+169)
   (* b (* a (- (* x y) (* z t))))
   (if (<= a -5.8e+122)
     (* z (- (* k (- (* b y0) (* i y1))) (* c (* y0 y3))))
     (if (<= a -5.5e+89)
       (* (* y3 y5) (- (* j y0) (* y a)))
       (if (<= a -1e+57)
         (* i (* k (- (* y y5) (* z y1))))
         (if (<= a -6.5e+33)
           (* j (* x (- (* i y1) (* b y0))))
           (if (<= a -1.35e-29)
             (* k (* y4 (- (* y1 y2) (* y b))))
             (if (<= a -3.2e-145)
               (* y0 (* x (- (* c y2) (* b j))))
               (if (<= a -3.1e-224)
                 (* k (* y1 (- (* y2 y4) (* z i))))
                 (if (<= a -4.8e-235)
                   (* b (* t (- (* j y4) (* z a))))
                   (if (<= a 1.82e-155)
                     (* (* k y0) (- (* z b) (* y2 y5)))
                     (if (<= a 1.82e-25)
                       (* (* y3 y4) (- (* y c) (* j y1)))
                       (if (<= a 42000000.0)
                         (* (* k y5) (- (* y i) (* y0 y2)))
                         (if (<= a 6e+33)
                           (* y0 (* y5 (- (* j y3) (* k y2))))
                           (if (<= a 1.65e+59)
                             (* t (* z (- (* c i) (* a b))))
                             (* z (* y3 (- (* 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 tmp;
	if (a <= -7.5e+169) {
		tmp = b * (a * ((x * y) - (z * t)));
	} else if (a <= -5.8e+122) {
		tmp = z * ((k * ((b * y0) - (i * y1))) - (c * (y0 * y3)));
	} else if (a <= -5.5e+89) {
		tmp = (y3 * y5) * ((j * y0) - (y * a));
	} else if (a <= -1e+57) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (a <= -6.5e+33) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (a <= -1.35e-29) {
		tmp = k * (y4 * ((y1 * y2) - (y * b)));
	} else if (a <= -3.2e-145) {
		tmp = y0 * (x * ((c * y2) - (b * j)));
	} else if (a <= -3.1e-224) {
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	} else if (a <= -4.8e-235) {
		tmp = b * (t * ((j * y4) - (z * a)));
	} else if (a <= 1.82e-155) {
		tmp = (k * y0) * ((z * b) - (y2 * y5));
	} else if (a <= 1.82e-25) {
		tmp = (y3 * y4) * ((y * c) - (j * y1));
	} else if (a <= 42000000.0) {
		tmp = (k * y5) * ((y * i) - (y0 * y2));
	} else if (a <= 6e+33) {
		tmp = y0 * (y5 * ((j * y3) - (k * y2)));
	} else if (a <= 1.65e+59) {
		tmp = t * (z * ((c * i) - (a * b)));
	} else {
		tmp = z * (y3 * ((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) :: tmp
    if (a <= (-7.5d+169)) then
        tmp = b * (a * ((x * y) - (z * t)))
    else if (a <= (-5.8d+122)) then
        tmp = z * ((k * ((b * y0) - (i * y1))) - (c * (y0 * y3)))
    else if (a <= (-5.5d+89)) then
        tmp = (y3 * y5) * ((j * y0) - (y * a))
    else if (a <= (-1d+57)) then
        tmp = i * (k * ((y * y5) - (z * y1)))
    else if (a <= (-6.5d+33)) then
        tmp = j * (x * ((i * y1) - (b * y0)))
    else if (a <= (-1.35d-29)) then
        tmp = k * (y4 * ((y1 * y2) - (y * b)))
    else if (a <= (-3.2d-145)) then
        tmp = y0 * (x * ((c * y2) - (b * j)))
    else if (a <= (-3.1d-224)) then
        tmp = k * (y1 * ((y2 * y4) - (z * i)))
    else if (a <= (-4.8d-235)) then
        tmp = b * (t * ((j * y4) - (z * a)))
    else if (a <= 1.82d-155) then
        tmp = (k * y0) * ((z * b) - (y2 * y5))
    else if (a <= 1.82d-25) then
        tmp = (y3 * y4) * ((y * c) - (j * y1))
    else if (a <= 42000000.0d0) then
        tmp = (k * y5) * ((y * i) - (y0 * y2))
    else if (a <= 6d+33) then
        tmp = y0 * (y5 * ((j * y3) - (k * y2)))
    else if (a <= 1.65d+59) then
        tmp = t * (z * ((c * i) - (a * b)))
    else
        tmp = z * (y3 * ((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 tmp;
	if (a <= -7.5e+169) {
		tmp = b * (a * ((x * y) - (z * t)));
	} else if (a <= -5.8e+122) {
		tmp = z * ((k * ((b * y0) - (i * y1))) - (c * (y0 * y3)));
	} else if (a <= -5.5e+89) {
		tmp = (y3 * y5) * ((j * y0) - (y * a));
	} else if (a <= -1e+57) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (a <= -6.5e+33) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (a <= -1.35e-29) {
		tmp = k * (y4 * ((y1 * y2) - (y * b)));
	} else if (a <= -3.2e-145) {
		tmp = y0 * (x * ((c * y2) - (b * j)));
	} else if (a <= -3.1e-224) {
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	} else if (a <= -4.8e-235) {
		tmp = b * (t * ((j * y4) - (z * a)));
	} else if (a <= 1.82e-155) {
		tmp = (k * y0) * ((z * b) - (y2 * y5));
	} else if (a <= 1.82e-25) {
		tmp = (y3 * y4) * ((y * c) - (j * y1));
	} else if (a <= 42000000.0) {
		tmp = (k * y5) * ((y * i) - (y0 * y2));
	} else if (a <= 6e+33) {
		tmp = y0 * (y5 * ((j * y3) - (k * y2)));
	} else if (a <= 1.65e+59) {
		tmp = t * (z * ((c * i) - (a * b)));
	} else {
		tmp = z * (y3 * ((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):
	tmp = 0
	if a <= -7.5e+169:
		tmp = b * (a * ((x * y) - (z * t)))
	elif a <= -5.8e+122:
		tmp = z * ((k * ((b * y0) - (i * y1))) - (c * (y0 * y3)))
	elif a <= -5.5e+89:
		tmp = (y3 * y5) * ((j * y0) - (y * a))
	elif a <= -1e+57:
		tmp = i * (k * ((y * y5) - (z * y1)))
	elif a <= -6.5e+33:
		tmp = j * (x * ((i * y1) - (b * y0)))
	elif a <= -1.35e-29:
		tmp = k * (y4 * ((y1 * y2) - (y * b)))
	elif a <= -3.2e-145:
		tmp = y0 * (x * ((c * y2) - (b * j)))
	elif a <= -3.1e-224:
		tmp = k * (y1 * ((y2 * y4) - (z * i)))
	elif a <= -4.8e-235:
		tmp = b * (t * ((j * y4) - (z * a)))
	elif a <= 1.82e-155:
		tmp = (k * y0) * ((z * b) - (y2 * y5))
	elif a <= 1.82e-25:
		tmp = (y3 * y4) * ((y * c) - (j * y1))
	elif a <= 42000000.0:
		tmp = (k * y5) * ((y * i) - (y0 * y2))
	elif a <= 6e+33:
		tmp = y0 * (y5 * ((j * y3) - (k * y2)))
	elif a <= 1.65e+59:
		tmp = t * (z * ((c * i) - (a * b)))
	else:
		tmp = z * (y3 * ((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)
	tmp = 0.0
	if (a <= -7.5e+169)
		tmp = Float64(b * Float64(a * Float64(Float64(x * y) - Float64(z * t))));
	elseif (a <= -5.8e+122)
		tmp = Float64(z * Float64(Float64(k * Float64(Float64(b * y0) - Float64(i * y1))) - Float64(c * Float64(y0 * y3))));
	elseif (a <= -5.5e+89)
		tmp = Float64(Float64(y3 * y5) * Float64(Float64(j * y0) - Float64(y * a)));
	elseif (a <= -1e+57)
		tmp = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))));
	elseif (a <= -6.5e+33)
		tmp = Float64(j * Float64(x * Float64(Float64(i * y1) - Float64(b * y0))));
	elseif (a <= -1.35e-29)
		tmp = Float64(k * Float64(y4 * Float64(Float64(y1 * y2) - Float64(y * b))));
	elseif (a <= -3.2e-145)
		tmp = Float64(y0 * Float64(x * Float64(Float64(c * y2) - Float64(b * j))));
	elseif (a <= -3.1e-224)
		tmp = Float64(k * Float64(y1 * Float64(Float64(y2 * y4) - Float64(z * i))));
	elseif (a <= -4.8e-235)
		tmp = Float64(b * Float64(t * Float64(Float64(j * y4) - Float64(z * a))));
	elseif (a <= 1.82e-155)
		tmp = Float64(Float64(k * y0) * Float64(Float64(z * b) - Float64(y2 * y5)));
	elseif (a <= 1.82e-25)
		tmp = Float64(Float64(y3 * y4) * Float64(Float64(y * c) - Float64(j * y1)));
	elseif (a <= 42000000.0)
		tmp = Float64(Float64(k * y5) * Float64(Float64(y * i) - Float64(y0 * y2)));
	elseif (a <= 6e+33)
		tmp = Float64(y0 * Float64(y5 * Float64(Float64(j * y3) - Float64(k * y2))));
	elseif (a <= 1.65e+59)
		tmp = Float64(t * Float64(z * Float64(Float64(c * i) - Float64(a * b))));
	else
		tmp = Float64(z * Float64(y3 * 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)
	tmp = 0.0;
	if (a <= -7.5e+169)
		tmp = b * (a * ((x * y) - (z * t)));
	elseif (a <= -5.8e+122)
		tmp = z * ((k * ((b * y0) - (i * y1))) - (c * (y0 * y3)));
	elseif (a <= -5.5e+89)
		tmp = (y3 * y5) * ((j * y0) - (y * a));
	elseif (a <= -1e+57)
		tmp = i * (k * ((y * y5) - (z * y1)));
	elseif (a <= -6.5e+33)
		tmp = j * (x * ((i * y1) - (b * y0)));
	elseif (a <= -1.35e-29)
		tmp = k * (y4 * ((y1 * y2) - (y * b)));
	elseif (a <= -3.2e-145)
		tmp = y0 * (x * ((c * y2) - (b * j)));
	elseif (a <= -3.1e-224)
		tmp = k * (y1 * ((y2 * y4) - (z * i)));
	elseif (a <= -4.8e-235)
		tmp = b * (t * ((j * y4) - (z * a)));
	elseif (a <= 1.82e-155)
		tmp = (k * y0) * ((z * b) - (y2 * y5));
	elseif (a <= 1.82e-25)
		tmp = (y3 * y4) * ((y * c) - (j * y1));
	elseif (a <= 42000000.0)
		tmp = (k * y5) * ((y * i) - (y0 * y2));
	elseif (a <= 6e+33)
		tmp = y0 * (y5 * ((j * y3) - (k * y2)));
	elseif (a <= 1.65e+59)
		tmp = t * (z * ((c * i) - (a * b)));
	else
		tmp = z * (y3 * ((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_] := If[LessEqual[a, -7.5e+169], N[(b * N[(a * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -5.8e+122], N[(z * N[(N[(k * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(c * N[(y0 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -5.5e+89], N[(N[(y3 * y5), $MachinePrecision] * N[(N[(j * y0), $MachinePrecision] - N[(y * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -1e+57], N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -6.5e+33], N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -1.35e-29], N[(k * N[(y4 * N[(N[(y1 * y2), $MachinePrecision] - N[(y * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -3.2e-145], N[(y0 * N[(x * N[(N[(c * y2), $MachinePrecision] - N[(b * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -3.1e-224], N[(k * N[(y1 * N[(N[(y2 * y4), $MachinePrecision] - N[(z * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -4.8e-235], N[(b * N[(t * N[(N[(j * y4), $MachinePrecision] - N[(z * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 1.82e-155], N[(N[(k * y0), $MachinePrecision] * N[(N[(z * b), $MachinePrecision] - N[(y2 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 1.82e-25], N[(N[(y3 * y4), $MachinePrecision] * N[(N[(y * c), $MachinePrecision] - N[(j * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 42000000.0], N[(N[(k * y5), $MachinePrecision] * N[(N[(y * i), $MachinePrecision] - N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 6e+33], N[(y0 * N[(y5 * N[(N[(j * y3), $MachinePrecision] - N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 1.65e+59], N[(t * N[(z * N[(N[(c * i), $MachinePrecision] - N[(a * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(z * N[(y3 * N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]]]

Derivation

1. Split input into 15 regimes

2. if a < -7.49999999999999992e169

   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. Taylor expanded in b around inf 44.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 69.0%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 69.0%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 69.0%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 69.0%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 69.0%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 69.0%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   if -7.49999999999999992e169 < a < -5.8000000000000002e122

   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. Taylor expanded in z around -inf 63.9%

      \[\leadsto \color{blue}{-1 \cdot \left(z \cdot \left(\left(t \cdot \left(a \cdot b - c \cdot i\right) + y3 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   3. Taylor expanded in y0 around inf 73.2%

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

      1. *-commutative 73.2%

         \[\leadsto -1 \cdot \left(z \cdot \left(c \cdot \color{blue}{\left(y3 \cdot y0\right)} - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) \]

   5. Simplified 73.2%

      \[\leadsto -1 \cdot \left(z \cdot \left(\color{blue}{c \cdot \left(y3 \cdot y0\right)} - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right) \]

   if -5.8000000000000002e122 < a < -5.49999999999999976e89

   1. Initial program 40.0%

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

   2. Taylor expanded in y3 around -inf 60.0%

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

   3. Taylor expanded in y5 around inf 80.0%

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

      1. associate-*r* 80.0%

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

      2. distribute-lft-out-- 80.0%

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

      3. *-commutative 80.0%

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

   5. Simplified 80.0%

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

   if -5.49999999999999976e89 < a < -1.00000000000000005e57

   1. Initial program 42.6%

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

   2. Taylor expanded in k around inf 50.8%

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

   3. Taylor expanded in i around inf 86.2%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - y1 \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 86.2%

         \[\leadsto i \cdot \left(k \cdot \left(y \cdot y5 - \color{blue}{z \cdot y1}\right)\right) \]

   5. Simplified 86.2%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)} \]

   if -1.00000000000000005e57 < a < -6.49999999999999993e33

   1. Initial program 50.0%

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

   2. Taylor expanded in j around inf 83.3%

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

   3. Taylor expanded in x around inf 100.0%

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

      1. *-commutative 100.0%

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

      2. *-commutative 100.0%

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

      3. *-commutative 100.0%

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

   5. Simplified 100.0%

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

   if -6.49999999999999993e33 < a < -1.35000000000000011e-29

   1. Initial program 49.9%

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

   2. Taylor expanded in k around inf 50.7%

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

   3. Taylor expanded in y4 around inf 52.2%

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

      1. +-commutative 52.2%

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

      2. mul-1-neg 52.2%

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

      3. unsub-neg 52.2%

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

   5. Simplified 52.2%

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

   if -1.35000000000000011e-29 < a < -3.20000000000000008e-145

   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. Taylor expanded in y0 around inf 31.5%

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

   3. Taylor expanded in x around inf 50.8%

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

   if -3.20000000000000008e-145 < a < -3.10000000000000008e-224

   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. Taylor expanded in k around inf 41.5%

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

   3. Taylor expanded in y1 around inf 65.4%

      \[\leadsto \color{blue}{k \cdot \left(y1 \cdot \left(y2 \cdot y4 - i \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 65.4%

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

      2. *-commutative 65.4%

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

   5. Simplified 65.4%

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

   if -3.10000000000000008e-224 < a < -4.80000000000000022e-235

   1. Initial program 26.2%

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

   2. Taylor expanded in b around inf 52.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in t around inf 65.5%

      \[\leadsto b \cdot \color{blue}{\left(t \cdot \left(-1 \cdot \left(a \cdot z\right) + j \cdot y4\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 65.5%

         \[\leadsto b \cdot \left(t \cdot \color{blue}{\left(j \cdot y4 + -1 \cdot \left(a \cdot z\right)\right)}\right) \]

      2. mul-1-neg 65.5%

         \[\leadsto b \cdot \left(t \cdot \left(j \cdot y4 + \color{blue}{\left(-a \cdot z\right)}\right)\right) \]

      3. unsub-neg 65.5%

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

      4. *-commutative 65.5%

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

      5. *-commutative 65.5%

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

   5. Simplified 65.5%

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

   if -4.80000000000000022e-235 < a < 1.82000000000000006e-155

   1. Initial program 37.0%

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

   2. Taylor expanded in y0 around inf 50.1%

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

   3. Taylor expanded in k around inf 46.4%

      \[\leadsto \color{blue}{k \cdot \left(y0 \cdot \left(-1 \cdot \left(y2 \cdot y5\right) - -1 \cdot \left(b \cdot z\right)\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 50.1%

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

      2. distribute-lft-out-- 50.1%

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

      3. *-commutative 50.1%

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

   5. Simplified 50.1%

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

   if 1.82000000000000006e-155 < a < 1.8199999999999999e-25

   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. Taylor expanded in y3 around -inf 44.1%

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

   3. Taylor expanded in y4 around inf 56.8%

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

      1. associate-*r* 51.2%

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

      2. *-commutative 51.2%

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

   5. Simplified 51.2%

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

   if 1.8199999999999999e-25 < a < 4.2e7

   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. Taylor expanded in k around inf 33.6%

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

   3. Taylor expanded in y5 around inf 78.0%

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

      1. associate-*r* 66.9%

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

      2. +-commutative 66.9%

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

      3. mul-1-neg 66.9%

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

      4. unsub-neg 66.9%

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

   5. Simplified 66.9%

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

   if 4.2e7 < a < 5.99999999999999967e33

   1. Initial program 18.2%

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

   2. Taylor expanded in y0 around inf 64.8%

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

   3. Taylor expanded in y5 around inf 56.4%

      \[\leadsto y0 \cdot \color{blue}{\left(-1 \cdot \left(y5 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 56.4%

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

      2. neg-mul-1 56.4%

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

      3. *-commutative 56.4%

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

      4. *-commutative 56.4%

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

   5. Simplified 56.4%

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

   if 5.99999999999999967e33 < a < 1.65e59

   1. Initial program 40.0%

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

   2. Taylor expanded in z around -inf 60.0%

      \[\leadsto \color{blue}{-1 \cdot \left(z \cdot \left(\left(t \cdot \left(a \cdot b - c \cdot i\right) + y3 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   3. Taylor expanded in t around inf 80.2%

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

   if 1.65e59 < a

   1. Initial program 33.0%

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

   2. Taylor expanded in y3 around -inf 46.2%

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

   3. Taylor expanded in z around inf 56.3%

      \[\leadsto -1 \cdot \color{blue}{\left(y3 \cdot \left(z \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 56.3%

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

      2. associate-*l* 58.1%

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

   5. Simplified 58.1%

      \[\leadsto -1 \cdot \color{blue}{\left(z \cdot \left(\left(c \cdot y0 - a \cdot y1\right) \cdot y3\right)\right)} \]
3. Recombined 15 regimes into one program.

4. Final simplification 60.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;a \leq -7.5 \cdot 10^{+169}:\\ \;\;\;\;b \cdot \left(a \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;a \leq -5.8 \cdot 10^{+122}:\\ \;\;\;\;z \cdot \left(k \cdot \left(b \cdot y0 - i \cdot y1\right) - c \cdot \left(y0 \cdot y3\right)\right)\\ \mathbf{elif}\;a \leq -5.5 \cdot 10^{+89}:\\ \;\;\;\;\left(y3 \cdot y5\right) \cdot \left(j \cdot y0 - y \cdot a\right)\\ \mathbf{elif}\;a \leq -1 \cdot 10^{+57}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;a \leq -6.5 \cdot 10^{+33}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;a \leq -1.35 \cdot 10^{-29}:\\ \;\;\;\;k \cdot \left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \mathbf{elif}\;a \leq -3.2 \cdot 10^{-145}:\\ \;\;\;\;y0 \cdot \left(x \cdot \left(c \cdot y2 - b \cdot j\right)\right)\\ \mathbf{elif}\;a \leq -3.1 \cdot 10^{-224}:\\ \;\;\;\;k \cdot \left(y1 \cdot \left(y2 \cdot y4 - z \cdot i\right)\right)\\ \mathbf{elif}\;a \leq -4.8 \cdot 10^{-235}:\\ \;\;\;\;b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ \mathbf{elif}\;a \leq 1.82 \cdot 10^{-155}:\\ \;\;\;\;\left(k \cdot y0\right) \cdot \left(z \cdot b - y2 \cdot y5\right)\\ \mathbf{elif}\;a \leq 1.82 \cdot 10^{-25}:\\ \;\;\;\;\left(y3 \cdot y4\right) \cdot \left(y \cdot c - j \cdot y1\right)\\ \mathbf{elif}\;a \leq 42000000:\\ \;\;\;\;\left(k \cdot y5\right) \cdot \left(y \cdot i - y0 \cdot y2\right)\\ \mathbf{elif}\;a \leq 6 \cdot 10^{+33}:\\ \;\;\;\;y0 \cdot \left(y5 \cdot \left(j \cdot y3 - k \cdot y2\right)\right)\\ \mathbf{elif}\;a \leq 1.65 \cdot 10^{+59}:\\ \;\;\;\;t \cdot \left(z \cdot \left(c \cdot i - a \cdot b\right)\right)\\ \mathbf{else}:\\ \;\;\;\;z \cdot \left(y3 \cdot \left(a \cdot y1 - c \cdot y0\right)\right)\\ \end{array} \]

Alternative 13: 28.6% accurate, 2.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(a \cdot \left(x \cdot y - z \cdot t\right)\right)\\ t_2 := \left(j \cdot \left(-y5\right)\right) \cdot \left(t \cdot i\right)\\ t_3 := b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ t_4 := b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ \mathbf{if}\;t \leq -2.9 \cdot 10^{+221}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t \leq -6 \cdot 10^{+104}:\\ \;\;\;\;j \cdot \left(y4 \cdot \left(t \cdot b - y1 \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq -1.5 \cdot 10^{+72}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq -1.55 \cdot 10^{-149}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;t \leq 4.5 \cdot 10^{-194}:\\ \;\;\;\;k \cdot \left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \mathbf{elif}\;t \leq 1.1 \cdot 10^{-151}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;t \leq 5.8 \cdot 10^{-59}:\\ \;\;\;\;z \cdot \left(c \cdot \left(y0 \cdot \left(-y3\right)\right)\right)\\ \mathbf{elif}\;t \leq 2.75 \cdot 10^{+38}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq 2.55 \cdot 10^{+105}:\\ \;\;\;\;t_4\\ \mathbf{elif}\;t \leq 5.2 \cdot 10^{+111}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq 2.1 \cdot 10^{+218}:\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;t_4\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* a (- (* x y) (* z t)))))
        (t_2 (* (* j (- y5)) (* t i)))
        (t_3 (* b (* y0 (- (* z k) (* x j)))))
        (t_4 (* b (* t (- (* j y4) (* z a))))))
   (if (<= t -2.9e+221)
     t_2
     (if (<= t -6e+104)
       (* j (* y4 (- (* t b) (* y1 y3))))
       (if (<= t -1.5e+72)
         (* i (* k (- (* y y5) (* z y1))))
         (if (<= t -1.55e-149)
           t_3
           (if (<= t 4.5e-194)
             (* k (* y4 (- (* y1 y2) (* y b))))
             (if (<= t 1.1e-151)
               t_3
               (if (<= t 5.8e-59)
                 (* z (* c (* y0 (- y3))))
                 (if (<= t 2.75e+38)
                   t_1
                   (if (<= t 2.55e+105)
                     t_4
                     (if (<= t 5.2e+111)
                       t_1
                       (if (<= t 2.1e+218) t_2 t_4)))))))))))))

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 * (a * ((x * y) - (z * t)));
	double t_2 = (j * -y5) * (t * i);
	double t_3 = b * (y0 * ((z * k) - (x * j)));
	double t_4 = b * (t * ((j * y4) - (z * a)));
	double tmp;
	if (t <= -2.9e+221) {
		tmp = t_2;
	} else if (t <= -6e+104) {
		tmp = j * (y4 * ((t * b) - (y1 * y3)));
	} else if (t <= -1.5e+72) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (t <= -1.55e-149) {
		tmp = t_3;
	} else if (t <= 4.5e-194) {
		tmp = k * (y4 * ((y1 * y2) - (y * b)));
	} else if (t <= 1.1e-151) {
		tmp = t_3;
	} else if (t <= 5.8e-59) {
		tmp = z * (c * (y0 * -y3));
	} else if (t <= 2.75e+38) {
		tmp = t_1;
	} else if (t <= 2.55e+105) {
		tmp = t_4;
	} else if (t <= 5.2e+111) {
		tmp = t_1;
	} else if (t <= 2.1e+218) {
		tmp = t_2;
	} else {
		tmp = t_4;
	}
	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) :: tmp
    t_1 = b * (a * ((x * y) - (z * t)))
    t_2 = (j * -y5) * (t * i)
    t_3 = b * (y0 * ((z * k) - (x * j)))
    t_4 = b * (t * ((j * y4) - (z * a)))
    if (t <= (-2.9d+221)) then
        tmp = t_2
    else if (t <= (-6d+104)) then
        tmp = j * (y4 * ((t * b) - (y1 * y3)))
    else if (t <= (-1.5d+72)) then
        tmp = i * (k * ((y * y5) - (z * y1)))
    else if (t <= (-1.55d-149)) then
        tmp = t_3
    else if (t <= 4.5d-194) then
        tmp = k * (y4 * ((y1 * y2) - (y * b)))
    else if (t <= 1.1d-151) then
        tmp = t_3
    else if (t <= 5.8d-59) then
        tmp = z * (c * (y0 * -y3))
    else if (t <= 2.75d+38) then
        tmp = t_1
    else if (t <= 2.55d+105) then
        tmp = t_4
    else if (t <= 5.2d+111) then
        tmp = t_1
    else if (t <= 2.1d+218) then
        tmp = t_2
    else
        tmp = t_4
    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 * (a * ((x * y) - (z * t)));
	double t_2 = (j * -y5) * (t * i);
	double t_3 = b * (y0 * ((z * k) - (x * j)));
	double t_4 = b * (t * ((j * y4) - (z * a)));
	double tmp;
	if (t <= -2.9e+221) {
		tmp = t_2;
	} else if (t <= -6e+104) {
		tmp = j * (y4 * ((t * b) - (y1 * y3)));
	} else if (t <= -1.5e+72) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (t <= -1.55e-149) {
		tmp = t_3;
	} else if (t <= 4.5e-194) {
		tmp = k * (y4 * ((y1 * y2) - (y * b)));
	} else if (t <= 1.1e-151) {
		tmp = t_3;
	} else if (t <= 5.8e-59) {
		tmp = z * (c * (y0 * -y3));
	} else if (t <= 2.75e+38) {
		tmp = t_1;
	} else if (t <= 2.55e+105) {
		tmp = t_4;
	} else if (t <= 5.2e+111) {
		tmp = t_1;
	} else if (t <= 2.1e+218) {
		tmp = t_2;
	} else {
		tmp = t_4;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = b * (a * ((x * y) - (z * t)))
	t_2 = (j * -y5) * (t * i)
	t_3 = b * (y0 * ((z * k) - (x * j)))
	t_4 = b * (t * ((j * y4) - (z * a)))
	tmp = 0
	if t <= -2.9e+221:
		tmp = t_2
	elif t <= -6e+104:
		tmp = j * (y4 * ((t * b) - (y1 * y3)))
	elif t <= -1.5e+72:
		tmp = i * (k * ((y * y5) - (z * y1)))
	elif t <= -1.55e-149:
		tmp = t_3
	elif t <= 4.5e-194:
		tmp = k * (y4 * ((y1 * y2) - (y * b)))
	elif t <= 1.1e-151:
		tmp = t_3
	elif t <= 5.8e-59:
		tmp = z * (c * (y0 * -y3))
	elif t <= 2.75e+38:
		tmp = t_1
	elif t <= 2.55e+105:
		tmp = t_4
	elif t <= 5.2e+111:
		tmp = t_1
	elif t <= 2.1e+218:
		tmp = t_2
	else:
		tmp = t_4
	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(a * Float64(Float64(x * y) - Float64(z * t))))
	t_2 = Float64(Float64(j * Float64(-y5)) * Float64(t * i))
	t_3 = Float64(b * Float64(y0 * Float64(Float64(z * k) - Float64(x * j))))
	t_4 = Float64(b * Float64(t * Float64(Float64(j * y4) - Float64(z * a))))
	tmp = 0.0
	if (t <= -2.9e+221)
		tmp = t_2;
	elseif (t <= -6e+104)
		tmp = Float64(j * Float64(y4 * Float64(Float64(t * b) - Float64(y1 * y3))));
	elseif (t <= -1.5e+72)
		tmp = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))));
	elseif (t <= -1.55e-149)
		tmp = t_3;
	elseif (t <= 4.5e-194)
		tmp = Float64(k * Float64(y4 * Float64(Float64(y1 * y2) - Float64(y * b))));
	elseif (t <= 1.1e-151)
		tmp = t_3;
	elseif (t <= 5.8e-59)
		tmp = Float64(z * Float64(c * Float64(y0 * Float64(-y3))));
	elseif (t <= 2.75e+38)
		tmp = t_1;
	elseif (t <= 2.55e+105)
		tmp = t_4;
	elseif (t <= 5.2e+111)
		tmp = t_1;
	elseif (t <= 2.1e+218)
		tmp = t_2;
	else
		tmp = t_4;
	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 * (a * ((x * y) - (z * t)));
	t_2 = (j * -y5) * (t * i);
	t_3 = b * (y0 * ((z * k) - (x * j)));
	t_4 = b * (t * ((j * y4) - (z * a)));
	tmp = 0.0;
	if (t <= -2.9e+221)
		tmp = t_2;
	elseif (t <= -6e+104)
		tmp = j * (y4 * ((t * b) - (y1 * y3)));
	elseif (t <= -1.5e+72)
		tmp = i * (k * ((y * y5) - (z * y1)));
	elseif (t <= -1.55e-149)
		tmp = t_3;
	elseif (t <= 4.5e-194)
		tmp = k * (y4 * ((y1 * y2) - (y * b)));
	elseif (t <= 1.1e-151)
		tmp = t_3;
	elseif (t <= 5.8e-59)
		tmp = z * (c * (y0 * -y3));
	elseif (t <= 2.75e+38)
		tmp = t_1;
	elseif (t <= 2.55e+105)
		tmp = t_4;
	elseif (t <= 5.2e+111)
		tmp = t_1;
	elseif (t <= 2.1e+218)
		tmp = t_2;
	else
		tmp = t_4;
	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[(a * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(j * (-y5)), $MachinePrecision] * N[(t * i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(b * N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(b * N[(t * N[(N[(j * y4), $MachinePrecision] - N[(z * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -2.9e+221], t$95$2, If[LessEqual[t, -6e+104], N[(j * N[(y4 * N[(N[(t * b), $MachinePrecision] - N[(y1 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -1.5e+72], N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -1.55e-149], t$95$3, If[LessEqual[t, 4.5e-194], N[(k * N[(y4 * N[(N[(y1 * y2), $MachinePrecision] - N[(y * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.1e-151], t$95$3, If[LessEqual[t, 5.8e-59], N[(z * N[(c * N[(y0 * (-y3)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 2.75e+38], t$95$1, If[LessEqual[t, 2.55e+105], t$95$4, If[LessEqual[t, 5.2e+111], t$95$1, If[LessEqual[t, 2.1e+218], t$95$2, t$95$4]]]]]]]]]]]]]]]

Derivation

1. Split input into 8 regimes

2. if t < -2.8999999999999998e221 or 5.1999999999999997e111 < t < 2.0999999999999999e218

   1. Initial program 30.9%

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

   2. Taylor expanded in j around inf 41.2%

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

   3. Taylor expanded in y5 around -inf 54.6%

      \[\leadsto \color{blue}{-1 \cdot \left(j \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)\right)\right)} \]
   4. Step-by-step derivation

      1. mul-1-neg 54.6%

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

      2. associate-*r* 54.6%

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

      3. distribute-lft-neg-in 54.6%

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

      4. distribute-rgt-neg-in 54.6%

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

      5. +-commutative 54.6%

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

      6. mul-1-neg 54.6%

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

      7. unsub-neg 54.6%

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

      8. *-commutative 54.6%

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

   5. Simplified 54.6%

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

   6. Taylor expanded in i around inf 54.7%

      \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \color{blue}{\left(i \cdot t\right)} \]
   7. Step-by-step derivation

      1. *-commutative 54.7%

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

   8. Simplified 54.7%

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

   if -2.8999999999999998e221 < t < -5.99999999999999937e104

   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. Taylor expanded in j around inf 38.5%

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

   3. Taylor expanded in y4 around inf 62.2%

      \[\leadsto \color{blue}{j \cdot \left(y4 \cdot \left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 62.2%

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

      2. +-commutative 62.2%

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

      3. mul-1-neg 62.2%

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

      4. unsub-neg 62.2%

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

      5. *-commutative 62.2%

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

   5. Simplified 62.2%

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

   if -5.99999999999999937e104 < t < -1.50000000000000001e72

   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. Taylor expanded in k around inf 38.4%

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

   3. Taylor expanded in i around inf 75.3%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - y1 \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 75.3%

         \[\leadsto i \cdot \left(k \cdot \left(y \cdot y5 - \color{blue}{z \cdot y1}\right)\right) \]

   5. Simplified 75.3%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)} \]

   if -1.50000000000000001e72 < t < -1.54999999999999994e-149 or 4.4999999999999999e-194 < t < 1.1e-151

   1. Initial program 38.3%

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

   2. Taylor expanded in b around inf 36.8%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in y0 around inf 51.8%

      \[\leadsto b \cdot \color{blue}{\left(y0 \cdot \left(k \cdot z - j \cdot x\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 51.8%

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

   5. Simplified 51.8%

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

   if -1.54999999999999994e-149 < t < 4.4999999999999999e-194

   1. Initial program 34.5%

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

   2. Taylor expanded in k around inf 37.9%

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

   3. Taylor expanded in y4 around inf 38.4%

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

      1. +-commutative 38.4%

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

      2. mul-1-neg 38.4%

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

      3. unsub-neg 38.4%

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

   5. Simplified 38.4%

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

   if 1.1e-151 < t < 5.80000000000000033e-59

   1. Initial program 54.4%

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

   2. Taylor expanded in z around -inf 54.6%

      \[\leadsto \color{blue}{-1 \cdot \left(z \cdot \left(\left(t \cdot \left(a \cdot b - c \cdot i\right) + y3 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   3. Taylor expanded in y0 around inf 33.2%

      \[\leadsto -1 \cdot \color{blue}{\left(y0 \cdot \left(z \cdot \left(c \cdot y3 - b \cdot k\right)\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 33.2%

         \[\leadsto -1 \cdot \color{blue}{\left(\left(y0 \cdot z\right) \cdot \left(c \cdot y3 - b \cdot k\right)\right)} \]

      2. *-commutative 33.2%

         \[\leadsto -1 \cdot \left(\color{blue}{\left(z \cdot y0\right)} \cdot \left(c \cdot y3 - b \cdot k\right)\right) \]

      3. *-commutative 33.2%

         \[\leadsto -1 \cdot \left(\left(z \cdot y0\right) \cdot \left(\color{blue}{y3 \cdot c} - b \cdot k\right)\right) \]

      4. *-commutative 33.2%

         \[\leadsto -1 \cdot \left(\left(z \cdot y0\right) \cdot \left(y3 \cdot c - \color{blue}{k \cdot b}\right)\right) \]

   5. Simplified 33.2%

      \[\leadsto -1 \cdot \color{blue}{\left(\left(z \cdot y0\right) \cdot \left(y3 \cdot c - k \cdot b\right)\right)} \]

   6. Taylor expanded in y3 around inf 47.5%

      \[\leadsto -1 \cdot \color{blue}{\left(c \cdot \left(y0 \cdot \left(y3 \cdot z\right)\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 62.2%

         \[\leadsto -1 \cdot \left(c \cdot \color{blue}{\left(\left(y0 \cdot y3\right) \cdot z\right)}\right) \]

      2. associate-*r* 62.2%

         \[\leadsto -1 \cdot \color{blue}{\left(\left(c \cdot \left(y0 \cdot y3\right)\right) \cdot z\right)} \]

   8. Simplified 62.2%

      \[\leadsto -1 \cdot \color{blue}{\left(\left(c \cdot \left(y0 \cdot y3\right)\right) \cdot z\right)} \]

   if 5.80000000000000033e-59 < t < 2.7500000000000002e38 or 2.54999999999999996e105 < t < 5.1999999999999997e111

   1. Initial program 30.8%

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

   2. Taylor expanded in b around inf 52.6%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 53.0%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 53.0%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 53.0%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 53.0%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 53.0%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 53.0%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   if 2.7500000000000002e38 < t < 2.54999999999999996e105 or 2.0999999999999999e218 < t

   1. Initial program 26.5%

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

   2. Taylor expanded in b around inf 33.5%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in t around inf 61.5%

      \[\leadsto b \cdot \color{blue}{\left(t \cdot \left(-1 \cdot \left(a \cdot z\right) + j \cdot y4\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 61.5%

         \[\leadsto b \cdot \left(t \cdot \color{blue}{\left(j \cdot y4 + -1 \cdot \left(a \cdot z\right)\right)}\right) \]

      2. mul-1-neg 61.5%

         \[\leadsto b \cdot \left(t \cdot \left(j \cdot y4 + \color{blue}{\left(-a \cdot z\right)}\right)\right) \]

      3. unsub-neg 61.5%

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

      4. *-commutative 61.5%

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

      5. *-commutative 61.5%

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

   5. Simplified 61.5%

      \[\leadsto b \cdot \color{blue}{\left(t \cdot \left(y4 \cdot j - z \cdot a\right)\right)} \]
3. Recombined 8 regimes into one program.

4. Final simplification 53.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -2.9 \cdot 10^{+221}:\\ \;\;\;\;\left(j \cdot \left(-y5\right)\right) \cdot \left(t \cdot i\right)\\ \mathbf{elif}\;t \leq -6 \cdot 10^{+104}:\\ \;\;\;\;j \cdot \left(y4 \cdot \left(t \cdot b - y1 \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq -1.5 \cdot 10^{+72}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq -1.55 \cdot 10^{-149}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;t \leq 4.5 \cdot 10^{-194}:\\ \;\;\;\;k \cdot \left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \mathbf{elif}\;t \leq 1.1 \cdot 10^{-151}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;t \leq 5.8 \cdot 10^{-59}:\\ \;\;\;\;z \cdot \left(c \cdot \left(y0 \cdot \left(-y3\right)\right)\right)\\ \mathbf{elif}\;t \leq 2.75 \cdot 10^{+38}:\\ \;\;\;\;b \cdot \left(a \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;t \leq 2.55 \cdot 10^{+105}:\\ \;\;\;\;b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ \mathbf{elif}\;t \leq 5.2 \cdot 10^{+111}:\\ \;\;\;\;b \cdot \left(a \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;t \leq 2.1 \cdot 10^{+218}:\\ \;\;\;\;\left(j \cdot \left(-y5\right)\right) \cdot \left(t \cdot i\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ \end{array} \]

Alternative 14: 28.6% accurate, 3.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ t_2 := \left(j \cdot \left(-y5\right)\right) \cdot \left(t \cdot i\right)\\ t_3 := b \cdot \left(a \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{if}\;t \leq -8.5 \cdot 10^{+221}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t \leq -6 \cdot 10^{+104}:\\ \;\;\;\;j \cdot \left(y4 \cdot \left(t \cdot b - y1 \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq -6.6 \cdot 10^{+66}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq 6 \cdot 10^{-150}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;t \leq 1.9 \cdot 10^{-58}:\\ \;\;\;\;z \cdot \left(c \cdot \left(y0 \cdot \left(-y3\right)\right)\right)\\ \mathbf{elif}\;t \leq 1.65 \cdot 10^{+35}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;t \leq 2.75 \cdot 10^{+107}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq 2.35 \cdot 10^{+111}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;t \leq 2.1 \cdot 10^{+216}:\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* t (- (* j y4) (* z a)))))
        (t_2 (* (* j (- y5)) (* t i)))
        (t_3 (* b (* a (- (* x y) (* z t))))))
   (if (<= t -8.5e+221)
     t_2
     (if (<= t -6e+104)
       (* j (* y4 (- (* t b) (* y1 y3))))
       (if (<= t -6.6e+66)
         (* i (* k (- (* y y5) (* z y1))))
         (if (<= t 6e-150)
           (* b (* y0 (- (* z k) (* x j))))
           (if (<= t 1.9e-58)
             (* z (* c (* y0 (- y3))))
             (if (<= t 1.65e+35)
               t_3
               (if (<= t 2.75e+107)
                 t_1
                 (if (<= t 2.35e+111)
                   t_3
                   (if (<= t 2.1e+216) 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 = b * (t * ((j * y4) - (z * a)));
	double t_2 = (j * -y5) * (t * i);
	double t_3 = b * (a * ((x * y) - (z * t)));
	double tmp;
	if (t <= -8.5e+221) {
		tmp = t_2;
	} else if (t <= -6e+104) {
		tmp = j * (y4 * ((t * b) - (y1 * y3)));
	} else if (t <= -6.6e+66) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (t <= 6e-150) {
		tmp = b * (y0 * ((z * k) - (x * j)));
	} else if (t <= 1.9e-58) {
		tmp = z * (c * (y0 * -y3));
	} else if (t <= 1.65e+35) {
		tmp = t_3;
	} else if (t <= 2.75e+107) {
		tmp = t_1;
	} else if (t <= 2.35e+111) {
		tmp = t_3;
	} else if (t <= 2.1e+216) {
		tmp = t_2;
	} 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) :: t_3
    real(8) :: tmp
    t_1 = b * (t * ((j * y4) - (z * a)))
    t_2 = (j * -y5) * (t * i)
    t_3 = b * (a * ((x * y) - (z * t)))
    if (t <= (-8.5d+221)) then
        tmp = t_2
    else if (t <= (-6d+104)) then
        tmp = j * (y4 * ((t * b) - (y1 * y3)))
    else if (t <= (-6.6d+66)) then
        tmp = i * (k * ((y * y5) - (z * y1)))
    else if (t <= 6d-150) then
        tmp = b * (y0 * ((z * k) - (x * j)))
    else if (t <= 1.9d-58) then
        tmp = z * (c * (y0 * -y3))
    else if (t <= 1.65d+35) then
        tmp = t_3
    else if (t <= 2.75d+107) then
        tmp = t_1
    else if (t <= 2.35d+111) then
        tmp = t_3
    else if (t <= 2.1d+216) then
        tmp = t_2
    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 = b * (t * ((j * y4) - (z * a)));
	double t_2 = (j * -y5) * (t * i);
	double t_3 = b * (a * ((x * y) - (z * t)));
	double tmp;
	if (t <= -8.5e+221) {
		tmp = t_2;
	} else if (t <= -6e+104) {
		tmp = j * (y4 * ((t * b) - (y1 * y3)));
	} else if (t <= -6.6e+66) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (t <= 6e-150) {
		tmp = b * (y0 * ((z * k) - (x * j)));
	} else if (t <= 1.9e-58) {
		tmp = z * (c * (y0 * -y3));
	} else if (t <= 1.65e+35) {
		tmp = t_3;
	} else if (t <= 2.75e+107) {
		tmp = t_1;
	} else if (t <= 2.35e+111) {
		tmp = t_3;
	} else if (t <= 2.1e+216) {
		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 = b * (t * ((j * y4) - (z * a)))
	t_2 = (j * -y5) * (t * i)
	t_3 = b * (a * ((x * y) - (z * t)))
	tmp = 0
	if t <= -8.5e+221:
		tmp = t_2
	elif t <= -6e+104:
		tmp = j * (y4 * ((t * b) - (y1 * y3)))
	elif t <= -6.6e+66:
		tmp = i * (k * ((y * y5) - (z * y1)))
	elif t <= 6e-150:
		tmp = b * (y0 * ((z * k) - (x * j)))
	elif t <= 1.9e-58:
		tmp = z * (c * (y0 * -y3))
	elif t <= 1.65e+35:
		tmp = t_3
	elif t <= 2.75e+107:
		tmp = t_1
	elif t <= 2.35e+111:
		tmp = t_3
	elif t <= 2.1e+216:
		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(b * Float64(t * Float64(Float64(j * y4) - Float64(z * a))))
	t_2 = Float64(Float64(j * Float64(-y5)) * Float64(t * i))
	t_3 = Float64(b * Float64(a * Float64(Float64(x * y) - Float64(z * t))))
	tmp = 0.0
	if (t <= -8.5e+221)
		tmp = t_2;
	elseif (t <= -6e+104)
		tmp = Float64(j * Float64(y4 * Float64(Float64(t * b) - Float64(y1 * y3))));
	elseif (t <= -6.6e+66)
		tmp = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))));
	elseif (t <= 6e-150)
		tmp = Float64(b * Float64(y0 * Float64(Float64(z * k) - Float64(x * j))));
	elseif (t <= 1.9e-58)
		tmp = Float64(z * Float64(c * Float64(y0 * Float64(-y3))));
	elseif (t <= 1.65e+35)
		tmp = t_3;
	elseif (t <= 2.75e+107)
		tmp = t_1;
	elseif (t <= 2.35e+111)
		tmp = t_3;
	elseif (t <= 2.1e+216)
		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 = b * (t * ((j * y4) - (z * a)));
	t_2 = (j * -y5) * (t * i);
	t_3 = b * (a * ((x * y) - (z * t)));
	tmp = 0.0;
	if (t <= -8.5e+221)
		tmp = t_2;
	elseif (t <= -6e+104)
		tmp = j * (y4 * ((t * b) - (y1 * y3)));
	elseif (t <= -6.6e+66)
		tmp = i * (k * ((y * y5) - (z * y1)));
	elseif (t <= 6e-150)
		tmp = b * (y0 * ((z * k) - (x * j)));
	elseif (t <= 1.9e-58)
		tmp = z * (c * (y0 * -y3));
	elseif (t <= 1.65e+35)
		tmp = t_3;
	elseif (t <= 2.75e+107)
		tmp = t_1;
	elseif (t <= 2.35e+111)
		tmp = t_3;
	elseif (t <= 2.1e+216)
		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[(b * N[(t * N[(N[(j * y4), $MachinePrecision] - N[(z * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(j * (-y5)), $MachinePrecision] * N[(t * i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(b * N[(a * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -8.5e+221], t$95$2, If[LessEqual[t, -6e+104], N[(j * N[(y4 * N[(N[(t * b), $MachinePrecision] - N[(y1 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -6.6e+66], N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 6e-150], N[(b * N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.9e-58], N[(z * N[(c * N[(y0 * (-y3)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.65e+35], t$95$3, If[LessEqual[t, 2.75e+107], t$95$1, If[LessEqual[t, 2.35e+111], t$95$3, If[LessEqual[t, 2.1e+216], t$95$2, t$95$1]]]]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if t < -8.5000000000000004e221 or 2.35000000000000004e111 < t < 2.10000000000000001e216

   1. Initial program 30.9%

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

   2. Taylor expanded in j around inf 41.2%

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

   3. Taylor expanded in y5 around -inf 54.6%

      \[\leadsto \color{blue}{-1 \cdot \left(j \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)\right)\right)} \]
   4. Step-by-step derivation

      1. mul-1-neg 54.6%

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

      2. associate-*r* 54.6%

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

      3. distribute-lft-neg-in 54.6%

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

      4. distribute-rgt-neg-in 54.6%

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

      5. +-commutative 54.6%

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

      6. mul-1-neg 54.6%

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

      7. unsub-neg 54.6%

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

      8. *-commutative 54.6%

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

   5. Simplified 54.6%

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

   6. Taylor expanded in i around inf 54.7%

      \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \color{blue}{\left(i \cdot t\right)} \]
   7. Step-by-step derivation

      1. *-commutative 54.7%

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

   8. Simplified 54.7%

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

   if -8.5000000000000004e221 < t < -5.99999999999999937e104

   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. Taylor expanded in j around inf 38.5%

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

   3. Taylor expanded in y4 around inf 62.2%

      \[\leadsto \color{blue}{j \cdot \left(y4 \cdot \left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 62.2%

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

      2. +-commutative 62.2%

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

      3. mul-1-neg 62.2%

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

      4. unsub-neg 62.2%

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

      5. *-commutative 62.2%

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

   5. Simplified 62.2%

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

   if -5.99999999999999937e104 < t < -6.6000000000000003e66

   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. Taylor expanded in k around inf 38.4%

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

   3. Taylor expanded in i around inf 75.3%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - y1 \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 75.3%

         \[\leadsto i \cdot \left(k \cdot \left(y \cdot y5 - \color{blue}{z \cdot y1}\right)\right) \]

   5. Simplified 75.3%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)} \]

   if -6.6000000000000003e66 < t < 6.0000000000000003e-150

   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. Taylor expanded in b around inf 38.8%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in y0 around inf 41.1%

      \[\leadsto b \cdot \color{blue}{\left(y0 \cdot \left(k \cdot z - j \cdot x\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 41.1%

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

   5. Simplified 41.1%

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

   if 6.0000000000000003e-150 < t < 1.8999999999999999e-58

   1. Initial program 54.4%

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

   2. Taylor expanded in z around -inf 54.6%

      \[\leadsto \color{blue}{-1 \cdot \left(z \cdot \left(\left(t \cdot \left(a \cdot b - c \cdot i\right) + y3 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   3. Taylor expanded in y0 around inf 33.2%

      \[\leadsto -1 \cdot \color{blue}{\left(y0 \cdot \left(z \cdot \left(c \cdot y3 - b \cdot k\right)\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 33.2%

         \[\leadsto -1 \cdot \color{blue}{\left(\left(y0 \cdot z\right) \cdot \left(c \cdot y3 - b \cdot k\right)\right)} \]

      2. *-commutative 33.2%

         \[\leadsto -1 \cdot \left(\color{blue}{\left(z \cdot y0\right)} \cdot \left(c \cdot y3 - b \cdot k\right)\right) \]

      3. *-commutative 33.2%

         \[\leadsto -1 \cdot \left(\left(z \cdot y0\right) \cdot \left(\color{blue}{y3 \cdot c} - b \cdot k\right)\right) \]

      4. *-commutative 33.2%

         \[\leadsto -1 \cdot \left(\left(z \cdot y0\right) \cdot \left(y3 \cdot c - \color{blue}{k \cdot b}\right)\right) \]

   5. Simplified 33.2%

      \[\leadsto -1 \cdot \color{blue}{\left(\left(z \cdot y0\right) \cdot \left(y3 \cdot c - k \cdot b\right)\right)} \]

   6. Taylor expanded in y3 around inf 47.5%

      \[\leadsto -1 \cdot \color{blue}{\left(c \cdot \left(y0 \cdot \left(y3 \cdot z\right)\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 62.2%

         \[\leadsto -1 \cdot \left(c \cdot \color{blue}{\left(\left(y0 \cdot y3\right) \cdot z\right)}\right) \]

      2. associate-*r* 62.2%

         \[\leadsto -1 \cdot \color{blue}{\left(\left(c \cdot \left(y0 \cdot y3\right)\right) \cdot z\right)} \]

   8. Simplified 62.2%

      \[\leadsto -1 \cdot \color{blue}{\left(\left(c \cdot \left(y0 \cdot y3\right)\right) \cdot z\right)} \]

   if 1.8999999999999999e-58 < t < 1.6500000000000001e35 or 2.7500000000000002e107 < t < 2.35000000000000004e111

   1. Initial program 30.8%

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

   2. Taylor expanded in b around inf 52.6%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 53.0%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 53.0%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 53.0%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 53.0%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 53.0%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 53.0%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   if 1.6500000000000001e35 < t < 2.7500000000000002e107 or 2.10000000000000001e216 < t

   1. Initial program 26.5%

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

   2. Taylor expanded in b around inf 33.5%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in t around inf 61.5%

      \[\leadsto b \cdot \color{blue}{\left(t \cdot \left(-1 \cdot \left(a \cdot z\right) + j \cdot y4\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 61.5%

         \[\leadsto b \cdot \left(t \cdot \color{blue}{\left(j \cdot y4 + -1 \cdot \left(a \cdot z\right)\right)}\right) \]

      2. mul-1-neg 61.5%

         \[\leadsto b \cdot \left(t \cdot \left(j \cdot y4 + \color{blue}{\left(-a \cdot z\right)}\right)\right) \]

      3. unsub-neg 61.5%

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

      4. *-commutative 61.5%

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

      5. *-commutative 61.5%

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

   5. Simplified 61.5%

      \[\leadsto b \cdot \color{blue}{\left(t \cdot \left(y4 \cdot j - z \cdot a\right)\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 51.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -8.5 \cdot 10^{+221}:\\ \;\;\;\;\left(j \cdot \left(-y5\right)\right) \cdot \left(t \cdot i\right)\\ \mathbf{elif}\;t \leq -6 \cdot 10^{+104}:\\ \;\;\;\;j \cdot \left(y4 \cdot \left(t \cdot b - y1 \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq -6.6 \cdot 10^{+66}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq 6 \cdot 10^{-150}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;t \leq 1.9 \cdot 10^{-58}:\\ \;\;\;\;z \cdot \left(c \cdot \left(y0 \cdot \left(-y3\right)\right)\right)\\ \mathbf{elif}\;t \leq 1.65 \cdot 10^{+35}:\\ \;\;\;\;b \cdot \left(a \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;t \leq 2.75 \cdot 10^{+107}:\\ \;\;\;\;b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ \mathbf{elif}\;t \leq 2.35 \cdot 10^{+111}:\\ \;\;\;\;b \cdot \left(a \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;t \leq 2.1 \cdot 10^{+216}:\\ \;\;\;\;\left(j \cdot \left(-y5\right)\right) \cdot \left(t \cdot i\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ \end{array} \]

Alternative 15: 29.4% accurate, 3.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \left(j \cdot \left(-y5\right)\right) \cdot \left(t \cdot i\right)\\ t_2 := b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{if}\;t \leq -5.6 \cdot 10^{+221}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq -5.3 \cdot 10^{+104}:\\ \;\;\;\;j \cdot \left(y4 \cdot \left(t \cdot b - y1 \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq -2.1 \cdot 10^{+74}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq -6.8 \cdot 10^{-147}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t \leq 7.5 \cdot 10^{-193}:\\ \;\;\;\;k \cdot \left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \mathbf{elif}\;t \leq 4.5 \cdot 10^{-151}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t \leq 5.8 \cdot 10^{-41}:\\ \;\;\;\;y0 \cdot \left(y3 \cdot \left(j \cdot y5 - z \cdot c\right)\right)\\ \mathbf{elif}\;t \leq 5.2 \cdot 10^{+111}:\\ \;\;\;\;b \cdot \left(a \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;t \leq 7.2 \cdot 10^{+216}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* (* j (- y5)) (* t i))) (t_2 (* b (* y0 (- (* z k) (* x j))))))
   (if (<= t -5.6e+221)
     t_1
     (if (<= t -5.3e+104)
       (* j (* y4 (- (* t b) (* y1 y3))))
       (if (<= t -2.1e+74)
         (* i (* k (- (* y y5) (* z y1))))
         (if (<= t -6.8e-147)
           t_2
           (if (<= t 7.5e-193)
             (* k (* y4 (- (* y1 y2) (* y b))))
             (if (<= t 4.5e-151)
               t_2
               (if (<= t 5.8e-41)
                 (* y0 (* y3 (- (* j y5) (* z c))))
                 (if (<= t 5.2e+111)
                   (* b (* a (- (* x y) (* z t))))
                   (if (<= t 7.2e+216)
                     t_1
                     (* b (* t (- (* j y4) (* z a)))))))))))))))

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 * -y5) * (t * i);
	double t_2 = b * (y0 * ((z * k) - (x * j)));
	double tmp;
	if (t <= -5.6e+221) {
		tmp = t_1;
	} else if (t <= -5.3e+104) {
		tmp = j * (y4 * ((t * b) - (y1 * y3)));
	} else if (t <= -2.1e+74) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (t <= -6.8e-147) {
		tmp = t_2;
	} else if (t <= 7.5e-193) {
		tmp = k * (y4 * ((y1 * y2) - (y * b)));
	} else if (t <= 4.5e-151) {
		tmp = t_2;
	} else if (t <= 5.8e-41) {
		tmp = y0 * (y3 * ((j * y5) - (z * c)));
	} else if (t <= 5.2e+111) {
		tmp = b * (a * ((x * y) - (z * t)));
	} else if (t <= 7.2e+216) {
		tmp = t_1;
	} else {
		tmp = b * (t * ((j * y4) - (z * a)));
	}
	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 = (j * -y5) * (t * i)
    t_2 = b * (y0 * ((z * k) - (x * j)))
    if (t <= (-5.6d+221)) then
        tmp = t_1
    else if (t <= (-5.3d+104)) then
        tmp = j * (y4 * ((t * b) - (y1 * y3)))
    else if (t <= (-2.1d+74)) then
        tmp = i * (k * ((y * y5) - (z * y1)))
    else if (t <= (-6.8d-147)) then
        tmp = t_2
    else if (t <= 7.5d-193) then
        tmp = k * (y4 * ((y1 * y2) - (y * b)))
    else if (t <= 4.5d-151) then
        tmp = t_2
    else if (t <= 5.8d-41) then
        tmp = y0 * (y3 * ((j * y5) - (z * c)))
    else if (t <= 5.2d+111) then
        tmp = b * (a * ((x * y) - (z * t)))
    else if (t <= 7.2d+216) then
        tmp = t_1
    else
        tmp = b * (t * ((j * y4) - (z * a)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (j * -y5) * (t * i);
	double t_2 = b * (y0 * ((z * k) - (x * j)));
	double tmp;
	if (t <= -5.6e+221) {
		tmp = t_1;
	} else if (t <= -5.3e+104) {
		tmp = j * (y4 * ((t * b) - (y1 * y3)));
	} else if (t <= -2.1e+74) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (t <= -6.8e-147) {
		tmp = t_2;
	} else if (t <= 7.5e-193) {
		tmp = k * (y4 * ((y1 * y2) - (y * b)));
	} else if (t <= 4.5e-151) {
		tmp = t_2;
	} else if (t <= 5.8e-41) {
		tmp = y0 * (y3 * ((j * y5) - (z * c)));
	} else if (t <= 5.2e+111) {
		tmp = b * (a * ((x * y) - (z * t)));
	} else if (t <= 7.2e+216) {
		tmp = t_1;
	} else {
		tmp = b * (t * ((j * y4) - (z * a)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (j * -y5) * (t * i)
	t_2 = b * (y0 * ((z * k) - (x * j)))
	tmp = 0
	if t <= -5.6e+221:
		tmp = t_1
	elif t <= -5.3e+104:
		tmp = j * (y4 * ((t * b) - (y1 * y3)))
	elif t <= -2.1e+74:
		tmp = i * (k * ((y * y5) - (z * y1)))
	elif t <= -6.8e-147:
		tmp = t_2
	elif t <= 7.5e-193:
		tmp = k * (y4 * ((y1 * y2) - (y * b)))
	elif t <= 4.5e-151:
		tmp = t_2
	elif t <= 5.8e-41:
		tmp = y0 * (y3 * ((j * y5) - (z * c)))
	elif t <= 5.2e+111:
		tmp = b * (a * ((x * y) - (z * t)))
	elif t <= 7.2e+216:
		tmp = t_1
	else:
		tmp = b * (t * ((j * y4) - (z * a)))
	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(j * Float64(-y5)) * Float64(t * i))
	t_2 = Float64(b * Float64(y0 * Float64(Float64(z * k) - Float64(x * j))))
	tmp = 0.0
	if (t <= -5.6e+221)
		tmp = t_1;
	elseif (t <= -5.3e+104)
		tmp = Float64(j * Float64(y4 * Float64(Float64(t * b) - Float64(y1 * y3))));
	elseif (t <= -2.1e+74)
		tmp = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))));
	elseif (t <= -6.8e-147)
		tmp = t_2;
	elseif (t <= 7.5e-193)
		tmp = Float64(k * Float64(y4 * Float64(Float64(y1 * y2) - Float64(y * b))));
	elseif (t <= 4.5e-151)
		tmp = t_2;
	elseif (t <= 5.8e-41)
		tmp = Float64(y0 * Float64(y3 * Float64(Float64(j * y5) - Float64(z * c))));
	elseif (t <= 5.2e+111)
		tmp = Float64(b * Float64(a * Float64(Float64(x * y) - Float64(z * t))));
	elseif (t <= 7.2e+216)
		tmp = t_1;
	else
		tmp = Float64(b * Float64(t * Float64(Float64(j * y4) - Float64(z * a))));
	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 * -y5) * (t * i);
	t_2 = b * (y0 * ((z * k) - (x * j)));
	tmp = 0.0;
	if (t <= -5.6e+221)
		tmp = t_1;
	elseif (t <= -5.3e+104)
		tmp = j * (y4 * ((t * b) - (y1 * y3)));
	elseif (t <= -2.1e+74)
		tmp = i * (k * ((y * y5) - (z * y1)));
	elseif (t <= -6.8e-147)
		tmp = t_2;
	elseif (t <= 7.5e-193)
		tmp = k * (y4 * ((y1 * y2) - (y * b)));
	elseif (t <= 4.5e-151)
		tmp = t_2;
	elseif (t <= 5.8e-41)
		tmp = y0 * (y3 * ((j * y5) - (z * c)));
	elseif (t <= 5.2e+111)
		tmp = b * (a * ((x * y) - (z * t)));
	elseif (t <= 7.2e+216)
		tmp = t_1;
	else
		tmp = b * (t * ((j * y4) - (z * a)));
	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[(j * (-y5)), $MachinePrecision] * N[(t * i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(b * N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -5.6e+221], t$95$1, If[LessEqual[t, -5.3e+104], N[(j * N[(y4 * N[(N[(t * b), $MachinePrecision] - N[(y1 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -2.1e+74], N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -6.8e-147], t$95$2, If[LessEqual[t, 7.5e-193], N[(k * N[(y4 * N[(N[(y1 * y2), $MachinePrecision] - N[(y * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 4.5e-151], t$95$2, If[LessEqual[t, 5.8e-41], N[(y0 * N[(y3 * N[(N[(j * y5), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 5.2e+111], N[(b * N[(a * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 7.2e+216], t$95$1, N[(b * N[(t * N[(N[(j * y4), $MachinePrecision] - N[(z * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]

Derivation

1. Split input into 8 regimes

2. if t < -5.59999999999999978e221 or 5.1999999999999997e111 < t < 7.2000000000000004e216

   1. Initial program 30.9%

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

   2. Taylor expanded in j around inf 41.2%

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

   3. Taylor expanded in y5 around -inf 54.6%

      \[\leadsto \color{blue}{-1 \cdot \left(j \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)\right)\right)} \]
   4. Step-by-step derivation

      1. mul-1-neg 54.6%

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

      2. associate-*r* 54.6%

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

      3. distribute-lft-neg-in 54.6%

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

      4. distribute-rgt-neg-in 54.6%

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

      5. +-commutative 54.6%

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

      6. mul-1-neg 54.6%

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

      7. unsub-neg 54.6%

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

      8. *-commutative 54.6%

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

   5. Simplified 54.6%

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

   6. Taylor expanded in i around inf 54.7%

      \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \color{blue}{\left(i \cdot t\right)} \]
   7. Step-by-step derivation

      1. *-commutative 54.7%

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

   8. Simplified 54.7%

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

   if -5.59999999999999978e221 < t < -5.2999999999999999e104

   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. Taylor expanded in j around inf 38.5%

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

   3. Taylor expanded in y4 around inf 62.2%

      \[\leadsto \color{blue}{j \cdot \left(y4 \cdot \left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 62.2%

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

      2. +-commutative 62.2%

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

      3. mul-1-neg 62.2%

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

      4. unsub-neg 62.2%

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

      5. *-commutative 62.2%

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

   5. Simplified 62.2%

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

   if -5.2999999999999999e104 < t < -2.0999999999999999e74

   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. Taylor expanded in k around inf 38.4%

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

   3. Taylor expanded in i around inf 75.3%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - y1 \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 75.3%

         \[\leadsto i \cdot \left(k \cdot \left(y \cdot y5 - \color{blue}{z \cdot y1}\right)\right) \]

   5. Simplified 75.3%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)} \]

   if -2.0999999999999999e74 < t < -6.79999999999999991e-147 or 7.4999999999999998e-193 < t < 4.5000000000000002e-151

   1. Initial program 38.3%

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

   2. Taylor expanded in b around inf 36.8%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in y0 around inf 51.8%

      \[\leadsto b \cdot \color{blue}{\left(y0 \cdot \left(k \cdot z - j \cdot x\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 51.8%

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

   5. Simplified 51.8%

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

   if -6.79999999999999991e-147 < t < 7.4999999999999998e-193

   1. Initial program 34.5%

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

   2. Taylor expanded in k around inf 37.9%

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

   3. Taylor expanded in y4 around inf 38.4%

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

      1. +-commutative 38.4%

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

      2. mul-1-neg 38.4%

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

      3. unsub-neg 38.4%

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

   5. Simplified 38.4%

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

   if 4.5000000000000002e-151 < t < 5.79999999999999955e-41

   1. Initial program 53.4%

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

   2. Taylor expanded in y0 around inf 65.5%

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

   3. Taylor expanded in y3 around -inf 71.2%

      \[\leadsto \color{blue}{-1 \cdot \left(y0 \cdot \left(y3 \cdot \left(-1 \cdot \left(j \cdot y5\right) + c \cdot z\right)\right)\right)} \]
   4. Step-by-step derivation

      1. mul-1-neg 71.2%

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

      2. distribute-rgt-neg-in 71.2%

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

      3. distribute-rgt-neg-in 71.2%

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

      4. +-commutative 71.2%

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

      5. mul-1-neg 71.2%

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

      6. unsub-neg 71.2%

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

   5. Simplified 71.2%

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

   if 5.79999999999999955e-41 < t < 5.1999999999999997e111

   1. Initial program 24.6%

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

   2. Taylor expanded in b around inf 52.1%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 46.5%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 46.5%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 46.5%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 46.5%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 46.5%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 46.5%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   if 7.2000000000000004e216 < t

   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. Taylor expanded in b around inf 28.6%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in t around inf 61.5%

      \[\leadsto b \cdot \color{blue}{\left(t \cdot \left(-1 \cdot \left(a \cdot z\right) + j \cdot y4\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 61.5%

         \[\leadsto b \cdot \left(t \cdot \color{blue}{\left(j \cdot y4 + -1 \cdot \left(a \cdot z\right)\right)}\right) \]

      2. mul-1-neg 61.5%

         \[\leadsto b \cdot \left(t \cdot \left(j \cdot y4 + \color{blue}{\left(-a \cdot z\right)}\right)\right) \]

      3. unsub-neg 61.5%

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

      4. *-commutative 61.5%

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

      5. *-commutative 61.5%

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

   5. Simplified 61.5%

      \[\leadsto b \cdot \color{blue}{\left(t \cdot \left(y4 \cdot j - z \cdot a\right)\right)} \]
3. Recombined 8 regimes into one program.

4. Final simplification 52.6%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -5.6 \cdot 10^{+221}:\\ \;\;\;\;\left(j \cdot \left(-y5\right)\right) \cdot \left(t \cdot i\right)\\ \mathbf{elif}\;t \leq -5.3 \cdot 10^{+104}:\\ \;\;\;\;j \cdot \left(y4 \cdot \left(t \cdot b - y1 \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq -2.1 \cdot 10^{+74}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq -6.8 \cdot 10^{-147}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;t \leq 7.5 \cdot 10^{-193}:\\ \;\;\;\;k \cdot \left(y4 \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \mathbf{elif}\;t \leq 4.5 \cdot 10^{-151}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;t \leq 5.8 \cdot 10^{-41}:\\ \;\;\;\;y0 \cdot \left(y3 \cdot \left(j \cdot y5 - z \cdot c\right)\right)\\ \mathbf{elif}\;t \leq 5.2 \cdot 10^{+111}:\\ \;\;\;\;b \cdot \left(a \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;t \leq 7.2 \cdot 10^{+216}:\\ \;\;\;\;\left(j \cdot \left(-y5\right)\right) \cdot \left(t \cdot i\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ \end{array} \]

Alternative 16: 29.3% accurate, 3.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \left(j \cdot \left(-y5\right)\right) \cdot \left(t \cdot i\right)\\ t_2 := b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{if}\;t \leq -8 \cdot 10^{+221}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq -6.8 \cdot 10^{+104}:\\ \;\;\;\;j \cdot \left(y4 \cdot \left(t \cdot b - y1 \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq -2.7 \cdot 10^{+67}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq -3.8 \cdot 10^{-176}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t \leq 1.55 \cdot 10^{-198}:\\ \;\;\;\;k \cdot \left(y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{elif}\;t \leq 1.9 \cdot 10^{-151}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t \leq 2.15 \cdot 10^{-41}:\\ \;\;\;\;y0 \cdot \left(y3 \cdot \left(j \cdot y5 - z \cdot c\right)\right)\\ \mathbf{elif}\;t \leq 2.4 \cdot 10^{+111}:\\ \;\;\;\;b \cdot \left(a \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;t \leq 1.9 \cdot 10^{+216}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* (* j (- y5)) (* t i))) (t_2 (* b (* y0 (- (* z k) (* x j))))))
   (if (<= t -8e+221)
     t_1
     (if (<= t -6.8e+104)
       (* j (* y4 (- (* t b) (* y1 y3))))
       (if (<= t -2.7e+67)
         (* i (* k (- (* y y5) (* z y1))))
         (if (<= t -3.8e-176)
           t_2
           (if (<= t 1.55e-198)
             (* k (* y (- (* i y5) (* b y4))))
             (if (<= t 1.9e-151)
               t_2
               (if (<= t 2.15e-41)
                 (* y0 (* y3 (- (* j y5) (* z c))))
                 (if (<= t 2.4e+111)
                   (* b (* a (- (* x y) (* z t))))
                   (if (<= t 1.9e+216)
                     t_1
                     (* b (* t (- (* j y4) (* z a)))))))))))))))

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 * -y5) * (t * i);
	double t_2 = b * (y0 * ((z * k) - (x * j)));
	double tmp;
	if (t <= -8e+221) {
		tmp = t_1;
	} else if (t <= -6.8e+104) {
		tmp = j * (y4 * ((t * b) - (y1 * y3)));
	} else if (t <= -2.7e+67) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (t <= -3.8e-176) {
		tmp = t_2;
	} else if (t <= 1.55e-198) {
		tmp = k * (y * ((i * y5) - (b * y4)));
	} else if (t <= 1.9e-151) {
		tmp = t_2;
	} else if (t <= 2.15e-41) {
		tmp = y0 * (y3 * ((j * y5) - (z * c)));
	} else if (t <= 2.4e+111) {
		tmp = b * (a * ((x * y) - (z * t)));
	} else if (t <= 1.9e+216) {
		tmp = t_1;
	} else {
		tmp = b * (t * ((j * y4) - (z * a)));
	}
	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 = (j * -y5) * (t * i)
    t_2 = b * (y0 * ((z * k) - (x * j)))
    if (t <= (-8d+221)) then
        tmp = t_1
    else if (t <= (-6.8d+104)) then
        tmp = j * (y4 * ((t * b) - (y1 * y3)))
    else if (t <= (-2.7d+67)) then
        tmp = i * (k * ((y * y5) - (z * y1)))
    else if (t <= (-3.8d-176)) then
        tmp = t_2
    else if (t <= 1.55d-198) then
        tmp = k * (y * ((i * y5) - (b * y4)))
    else if (t <= 1.9d-151) then
        tmp = t_2
    else if (t <= 2.15d-41) then
        tmp = y0 * (y3 * ((j * y5) - (z * c)))
    else if (t <= 2.4d+111) then
        tmp = b * (a * ((x * y) - (z * t)))
    else if (t <= 1.9d+216) then
        tmp = t_1
    else
        tmp = b * (t * ((j * y4) - (z * a)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (j * -y5) * (t * i);
	double t_2 = b * (y0 * ((z * k) - (x * j)));
	double tmp;
	if (t <= -8e+221) {
		tmp = t_1;
	} else if (t <= -6.8e+104) {
		tmp = j * (y4 * ((t * b) - (y1 * y3)));
	} else if (t <= -2.7e+67) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (t <= -3.8e-176) {
		tmp = t_2;
	} else if (t <= 1.55e-198) {
		tmp = k * (y * ((i * y5) - (b * y4)));
	} else if (t <= 1.9e-151) {
		tmp = t_2;
	} else if (t <= 2.15e-41) {
		tmp = y0 * (y3 * ((j * y5) - (z * c)));
	} else if (t <= 2.4e+111) {
		tmp = b * (a * ((x * y) - (z * t)));
	} else if (t <= 1.9e+216) {
		tmp = t_1;
	} else {
		tmp = b * (t * ((j * y4) - (z * a)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (j * -y5) * (t * i)
	t_2 = b * (y0 * ((z * k) - (x * j)))
	tmp = 0
	if t <= -8e+221:
		tmp = t_1
	elif t <= -6.8e+104:
		tmp = j * (y4 * ((t * b) - (y1 * y3)))
	elif t <= -2.7e+67:
		tmp = i * (k * ((y * y5) - (z * y1)))
	elif t <= -3.8e-176:
		tmp = t_2
	elif t <= 1.55e-198:
		tmp = k * (y * ((i * y5) - (b * y4)))
	elif t <= 1.9e-151:
		tmp = t_2
	elif t <= 2.15e-41:
		tmp = y0 * (y3 * ((j * y5) - (z * c)))
	elif t <= 2.4e+111:
		tmp = b * (a * ((x * y) - (z * t)))
	elif t <= 1.9e+216:
		tmp = t_1
	else:
		tmp = b * (t * ((j * y4) - (z * a)))
	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(j * Float64(-y5)) * Float64(t * i))
	t_2 = Float64(b * Float64(y0 * Float64(Float64(z * k) - Float64(x * j))))
	tmp = 0.0
	if (t <= -8e+221)
		tmp = t_1;
	elseif (t <= -6.8e+104)
		tmp = Float64(j * Float64(y4 * Float64(Float64(t * b) - Float64(y1 * y3))));
	elseif (t <= -2.7e+67)
		tmp = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))));
	elseif (t <= -3.8e-176)
		tmp = t_2;
	elseif (t <= 1.55e-198)
		tmp = Float64(k * Float64(y * Float64(Float64(i * y5) - Float64(b * y4))));
	elseif (t <= 1.9e-151)
		tmp = t_2;
	elseif (t <= 2.15e-41)
		tmp = Float64(y0 * Float64(y3 * Float64(Float64(j * y5) - Float64(z * c))));
	elseif (t <= 2.4e+111)
		tmp = Float64(b * Float64(a * Float64(Float64(x * y) - Float64(z * t))));
	elseif (t <= 1.9e+216)
		tmp = t_1;
	else
		tmp = Float64(b * Float64(t * Float64(Float64(j * y4) - Float64(z * a))));
	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 * -y5) * (t * i);
	t_2 = b * (y0 * ((z * k) - (x * j)));
	tmp = 0.0;
	if (t <= -8e+221)
		tmp = t_1;
	elseif (t <= -6.8e+104)
		tmp = j * (y4 * ((t * b) - (y1 * y3)));
	elseif (t <= -2.7e+67)
		tmp = i * (k * ((y * y5) - (z * y1)));
	elseif (t <= -3.8e-176)
		tmp = t_2;
	elseif (t <= 1.55e-198)
		tmp = k * (y * ((i * y5) - (b * y4)));
	elseif (t <= 1.9e-151)
		tmp = t_2;
	elseif (t <= 2.15e-41)
		tmp = y0 * (y3 * ((j * y5) - (z * c)));
	elseif (t <= 2.4e+111)
		tmp = b * (a * ((x * y) - (z * t)));
	elseif (t <= 1.9e+216)
		tmp = t_1;
	else
		tmp = b * (t * ((j * y4) - (z * a)));
	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[(j * (-y5)), $MachinePrecision] * N[(t * i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(b * N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -8e+221], t$95$1, If[LessEqual[t, -6.8e+104], N[(j * N[(y4 * N[(N[(t * b), $MachinePrecision] - N[(y1 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -2.7e+67], N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -3.8e-176], t$95$2, If[LessEqual[t, 1.55e-198], N[(k * N[(y * N[(N[(i * y5), $MachinePrecision] - N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.9e-151], t$95$2, If[LessEqual[t, 2.15e-41], N[(y0 * N[(y3 * N[(N[(j * y5), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 2.4e+111], N[(b * N[(a * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.9e+216], t$95$1, N[(b * N[(t * N[(N[(j * y4), $MachinePrecision] - N[(z * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]

Derivation

1. Split input into 8 regimes

2. if t < -8.0000000000000004e221 or 2.40000000000000006e111 < t < 1.90000000000000007e216

   1. Initial program 30.9%

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

   2. Taylor expanded in j around inf 41.2%

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

   3. Taylor expanded in y5 around -inf 54.6%

      \[\leadsto \color{blue}{-1 \cdot \left(j \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)\right)\right)} \]
   4. Step-by-step derivation

      1. mul-1-neg 54.6%

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

      2. associate-*r* 54.6%

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

      3. distribute-lft-neg-in 54.6%

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

      4. distribute-rgt-neg-in 54.6%

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

      5. +-commutative 54.6%

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

      6. mul-1-neg 54.6%

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

      7. unsub-neg 54.6%

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

      8. *-commutative 54.6%

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

   5. Simplified 54.6%

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

   6. Taylor expanded in i around inf 54.7%

      \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \color{blue}{\left(i \cdot t\right)} \]
   7. Step-by-step derivation

      1. *-commutative 54.7%

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

   8. Simplified 54.7%

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

   if -8.0000000000000004e221 < t < -6.7999999999999994e104

   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. Taylor expanded in j around inf 38.5%

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

   3. Taylor expanded in y4 around inf 62.2%

      \[\leadsto \color{blue}{j \cdot \left(y4 \cdot \left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 62.2%

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

      2. +-commutative 62.2%

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

      3. mul-1-neg 62.2%

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

      4. unsub-neg 62.2%

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

      5. *-commutative 62.2%

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

   5. Simplified 62.2%

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

   if -6.7999999999999994e104 < t < -2.6999999999999999e67

   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. Taylor expanded in k around inf 38.4%

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

   3. Taylor expanded in i around inf 75.3%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - y1 \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 75.3%

         \[\leadsto i \cdot \left(k \cdot \left(y \cdot y5 - \color{blue}{z \cdot y1}\right)\right) \]

   5. Simplified 75.3%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)} \]

   if -2.6999999999999999e67 < t < -3.80000000000000012e-176 or 1.5499999999999999e-198 < t < 1.89999999999999985e-151

   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. Taylor expanded in b around inf 38.1%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in y0 around inf 50.2%

      \[\leadsto b \cdot \color{blue}{\left(y0 \cdot \left(k \cdot z - j \cdot x\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 50.2%

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

   5. Simplified 50.2%

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

   if -3.80000000000000012e-176 < t < 1.5499999999999999e-198

   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. Taylor expanded in k around inf 38.4%

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

   3. Taylor expanded in y around inf 41.8%

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

   if 1.89999999999999985e-151 < t < 2.1499999999999999e-41

   1. Initial program 53.4%

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

   2. Taylor expanded in y0 around inf 65.5%

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

   3. Taylor expanded in y3 around -inf 71.2%

      \[\leadsto \color{blue}{-1 \cdot \left(y0 \cdot \left(y3 \cdot \left(-1 \cdot \left(j \cdot y5\right) + c \cdot z\right)\right)\right)} \]
   4. Step-by-step derivation

      1. mul-1-neg 71.2%

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

      2. distribute-rgt-neg-in 71.2%

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

      3. distribute-rgt-neg-in 71.2%

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

      4. +-commutative 71.2%

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

      5. mul-1-neg 71.2%

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

      6. unsub-neg 71.2%

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

   5. Simplified 71.2%

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

   if 2.1499999999999999e-41 < t < 2.40000000000000006e111

   1. Initial program 24.6%

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

   2. Taylor expanded in b around inf 52.1%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 46.5%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 46.5%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 46.5%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 46.5%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 46.5%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 46.5%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   if 1.90000000000000007e216 < t

   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. Taylor expanded in b around inf 28.6%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in t around inf 61.5%

      \[\leadsto b \cdot \color{blue}{\left(t \cdot \left(-1 \cdot \left(a \cdot z\right) + j \cdot y4\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 61.5%

         \[\leadsto b \cdot \left(t \cdot \color{blue}{\left(j \cdot y4 + -1 \cdot \left(a \cdot z\right)\right)}\right) \]

      2. mul-1-neg 61.5%

         \[\leadsto b \cdot \left(t \cdot \left(j \cdot y4 + \color{blue}{\left(-a \cdot z\right)}\right)\right) \]

      3. unsub-neg 61.5%

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

      4. *-commutative 61.5%

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

      5. *-commutative 61.5%

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

   5. Simplified 61.5%

      \[\leadsto b \cdot \color{blue}{\left(t \cdot \left(y4 \cdot j - z \cdot a\right)\right)} \]
3. Recombined 8 regimes into one program.

4. Final simplification 53.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -8 \cdot 10^{+221}:\\ \;\;\;\;\left(j \cdot \left(-y5\right)\right) \cdot \left(t \cdot i\right)\\ \mathbf{elif}\;t \leq -6.8 \cdot 10^{+104}:\\ \;\;\;\;j \cdot \left(y4 \cdot \left(t \cdot b - y1 \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq -2.7 \cdot 10^{+67}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq -3.8 \cdot 10^{-176}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;t \leq 1.55 \cdot 10^{-198}:\\ \;\;\;\;k \cdot \left(y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{elif}\;t \leq 1.9 \cdot 10^{-151}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;t \leq 2.15 \cdot 10^{-41}:\\ \;\;\;\;y0 \cdot \left(y3 \cdot \left(j \cdot y5 - z \cdot c\right)\right)\\ \mathbf{elif}\;t \leq 2.4 \cdot 10^{+111}:\\ \;\;\;\;b \cdot \left(a \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;t \leq 1.9 \cdot 10^{+216}:\\ \;\;\;\;\left(j \cdot \left(-y5\right)\right) \cdot \left(t \cdot i\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ \end{array} \]

Alternative 17: 28.0% accurate, 3.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \left(j \cdot \left(-y5\right)\right) \cdot \left(t \cdot i\right)\\ t_2 := b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ t_3 := b \cdot \left(a \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{if}\;t \leq -3.7 \cdot 10^{+214}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq -3 \cdot 10^{+86}:\\ \;\;\;\;j \cdot \left(b \cdot \left(t \cdot y4\right)\right)\\ \mathbf{elif}\;t \leq 1.2 \cdot 10^{-151}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;t \leq 6.8 \cdot 10^{-59}:\\ \;\;\;\;z \cdot \left(c \cdot \left(y0 \cdot \left(-y3\right)\right)\right)\\ \mathbf{elif}\;t \leq 4.1 \cdot 10^{+38}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;t \leq 4.9 \cdot 10^{+103}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t \leq 2.38 \cdot 10^{+111}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;t \leq 3.5 \cdot 10^{+216}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* (* j (- y5)) (* t i)))
        (t_2 (* b (* t (- (* j y4) (* z a)))))
        (t_3 (* b (* a (- (* x y) (* z t))))))
   (if (<= t -3.7e+214)
     t_1
     (if (<= t -3e+86)
       (* j (* b (* t y4)))
       (if (<= t 1.2e-151)
         (* b (* y0 (- (* z k) (* x j))))
         (if (<= t 6.8e-59)
           (* z (* c (* y0 (- y3))))
           (if (<= t 4.1e+38)
             t_3
             (if (<= t 4.9e+103)
               t_2
               (if (<= t 2.38e+111) t_3 (if (<= t 3.5e+216) t_1 t_2))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (j * -y5) * (t * i);
	double t_2 = b * (t * ((j * y4) - (z * a)));
	double t_3 = b * (a * ((x * y) - (z * t)));
	double tmp;
	if (t <= -3.7e+214) {
		tmp = t_1;
	} else if (t <= -3e+86) {
		tmp = j * (b * (t * y4));
	} else if (t <= 1.2e-151) {
		tmp = b * (y0 * ((z * k) - (x * j)));
	} else if (t <= 6.8e-59) {
		tmp = z * (c * (y0 * -y3));
	} else if (t <= 4.1e+38) {
		tmp = t_3;
	} else if (t <= 4.9e+103) {
		tmp = t_2;
	} else if (t <= 2.38e+111) {
		tmp = t_3;
	} else if (t <= 3.5e+216) {
		tmp = t_1;
	} else {
		tmp = t_2;
	}
	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 = (j * -y5) * (t * i)
    t_2 = b * (t * ((j * y4) - (z * a)))
    t_3 = b * (a * ((x * y) - (z * t)))
    if (t <= (-3.7d+214)) then
        tmp = t_1
    else if (t <= (-3d+86)) then
        tmp = j * (b * (t * y4))
    else if (t <= 1.2d-151) then
        tmp = b * (y0 * ((z * k) - (x * j)))
    else if (t <= 6.8d-59) then
        tmp = z * (c * (y0 * -y3))
    else if (t <= 4.1d+38) then
        tmp = t_3
    else if (t <= 4.9d+103) then
        tmp = t_2
    else if (t <= 2.38d+111) then
        tmp = t_3
    else if (t <= 3.5d+216) then
        tmp = t_1
    else
        tmp = t_2
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (j * -y5) * (t * i);
	double t_2 = b * (t * ((j * y4) - (z * a)));
	double t_3 = b * (a * ((x * y) - (z * t)));
	double tmp;
	if (t <= -3.7e+214) {
		tmp = t_1;
	} else if (t <= -3e+86) {
		tmp = j * (b * (t * y4));
	} else if (t <= 1.2e-151) {
		tmp = b * (y0 * ((z * k) - (x * j)));
	} else if (t <= 6.8e-59) {
		tmp = z * (c * (y0 * -y3));
	} else if (t <= 4.1e+38) {
		tmp = t_3;
	} else if (t <= 4.9e+103) {
		tmp = t_2;
	} else if (t <= 2.38e+111) {
		tmp = t_3;
	} else if (t <= 3.5e+216) {
		tmp = t_1;
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (j * -y5) * (t * i)
	t_2 = b * (t * ((j * y4) - (z * a)))
	t_3 = b * (a * ((x * y) - (z * t)))
	tmp = 0
	if t <= -3.7e+214:
		tmp = t_1
	elif t <= -3e+86:
		tmp = j * (b * (t * y4))
	elif t <= 1.2e-151:
		tmp = b * (y0 * ((z * k) - (x * j)))
	elif t <= 6.8e-59:
		tmp = z * (c * (y0 * -y3))
	elif t <= 4.1e+38:
		tmp = t_3
	elif t <= 4.9e+103:
		tmp = t_2
	elif t <= 2.38e+111:
		tmp = t_3
	elif t <= 3.5e+216:
		tmp = t_1
	else:
		tmp = t_2
	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(j * Float64(-y5)) * Float64(t * i))
	t_2 = Float64(b * Float64(t * Float64(Float64(j * y4) - Float64(z * a))))
	t_3 = Float64(b * Float64(a * Float64(Float64(x * y) - Float64(z * t))))
	tmp = 0.0
	if (t <= -3.7e+214)
		tmp = t_1;
	elseif (t <= -3e+86)
		tmp = Float64(j * Float64(b * Float64(t * y4)));
	elseif (t <= 1.2e-151)
		tmp = Float64(b * Float64(y0 * Float64(Float64(z * k) - Float64(x * j))));
	elseif (t <= 6.8e-59)
		tmp = Float64(z * Float64(c * Float64(y0 * Float64(-y3))));
	elseif (t <= 4.1e+38)
		tmp = t_3;
	elseif (t <= 4.9e+103)
		tmp = t_2;
	elseif (t <= 2.38e+111)
		tmp = t_3;
	elseif (t <= 3.5e+216)
		tmp = t_1;
	else
		tmp = t_2;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = (j * -y5) * (t * i);
	t_2 = b * (t * ((j * y4) - (z * a)));
	t_3 = b * (a * ((x * y) - (z * t)));
	tmp = 0.0;
	if (t <= -3.7e+214)
		tmp = t_1;
	elseif (t <= -3e+86)
		tmp = j * (b * (t * y4));
	elseif (t <= 1.2e-151)
		tmp = b * (y0 * ((z * k) - (x * j)));
	elseif (t <= 6.8e-59)
		tmp = z * (c * (y0 * -y3));
	elseif (t <= 4.1e+38)
		tmp = t_3;
	elseif (t <= 4.9e+103)
		tmp = t_2;
	elseif (t <= 2.38e+111)
		tmp = t_3;
	elseif (t <= 3.5e+216)
		tmp = t_1;
	else
		tmp = t_2;
	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[(j * (-y5)), $MachinePrecision] * N[(t * i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(b * N[(t * N[(N[(j * y4), $MachinePrecision] - N[(z * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(b * N[(a * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -3.7e+214], t$95$1, If[LessEqual[t, -3e+86], N[(j * N[(b * N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.2e-151], N[(b * N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 6.8e-59], N[(z * N[(c * N[(y0 * (-y3)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 4.1e+38], t$95$3, If[LessEqual[t, 4.9e+103], t$95$2, If[LessEqual[t, 2.38e+111], t$95$3, If[LessEqual[t, 3.5e+216], t$95$1, t$95$2]]]]]]]]]]]

Derivation

1. Split input into 6 regimes

2. if t < -3.69999999999999981e214 or 2.3800000000000001e111 < t < 3.49999999999999992e216

   1. Initial program 31.8%

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

   2. Taylor expanded in j around inf 39.2%

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

   3. Taylor expanded in y5 around -inf 52.0%

      \[\leadsto \color{blue}{-1 \cdot \left(j \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)\right)\right)} \]
   4. Step-by-step derivation

      1. mul-1-neg 52.0%

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

      2. associate-*r* 52.0%

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

      3. distribute-lft-neg-in 52.0%

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

      4. distribute-rgt-neg-in 52.0%

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

      5. +-commutative 52.0%

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

      6. mul-1-neg 52.0%

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

      7. unsub-neg 52.0%

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

      8. *-commutative 52.0%

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

   5. Simplified 52.0%

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

   6. Taylor expanded in i around inf 52.1%

      \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \color{blue}{\left(i \cdot t\right)} \]
   7. Step-by-step derivation

      1. *-commutative 52.1%

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

   8. Simplified 52.1%

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

   if -3.69999999999999981e214 < t < -2.99999999999999977e86

   1. Initial program 29.2%

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

   2. Taylor expanded in j around inf 42.1%

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

   3. Taylor expanded in y4 around inf 54.7%

      \[\leadsto \color{blue}{j \cdot \left(y4 \cdot \left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 54.7%

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

      2. +-commutative 54.7%

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

      3. mul-1-neg 54.7%

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

      4. unsub-neg 54.7%

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

      5. *-commutative 54.7%

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

   5. Simplified 54.7%

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

   6. Taylor expanded in b around inf 51.0%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 38.9%

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

      2. *-commutative 38.9%

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

      3. associate-*l* 51.2%

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

   8. Simplified 51.2%

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

   if -2.99999999999999977e86 < t < 1.2e-151

   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. Taylor expanded in b around inf 38.7%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in y0 around inf 40.9%

      \[\leadsto b \cdot \color{blue}{\left(y0 \cdot \left(k \cdot z - j \cdot x\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 40.9%

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

   5. Simplified 40.9%

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

   if 1.2e-151 < t < 6.80000000000000035e-59

   1. Initial program 54.4%

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

   2. Taylor expanded in z around -inf 54.6%

      \[\leadsto \color{blue}{-1 \cdot \left(z \cdot \left(\left(t \cdot \left(a \cdot b - c \cdot i\right) + y3 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   3. Taylor expanded in y0 around inf 33.2%

      \[\leadsto -1 \cdot \color{blue}{\left(y0 \cdot \left(z \cdot \left(c \cdot y3 - b \cdot k\right)\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 33.2%

         \[\leadsto -1 \cdot \color{blue}{\left(\left(y0 \cdot z\right) \cdot \left(c \cdot y3 - b \cdot k\right)\right)} \]

      2. *-commutative 33.2%

         \[\leadsto -1 \cdot \left(\color{blue}{\left(z \cdot y0\right)} \cdot \left(c \cdot y3 - b \cdot k\right)\right) \]

      3. *-commutative 33.2%

         \[\leadsto -1 \cdot \left(\left(z \cdot y0\right) \cdot \left(\color{blue}{y3 \cdot c} - b \cdot k\right)\right) \]

      4. *-commutative 33.2%

         \[\leadsto -1 \cdot \left(\left(z \cdot y0\right) \cdot \left(y3 \cdot c - \color{blue}{k \cdot b}\right)\right) \]

   5. Simplified 33.2%

      \[\leadsto -1 \cdot \color{blue}{\left(\left(z \cdot y0\right) \cdot \left(y3 \cdot c - k \cdot b\right)\right)} \]

   6. Taylor expanded in y3 around inf 47.5%

      \[\leadsto -1 \cdot \color{blue}{\left(c \cdot \left(y0 \cdot \left(y3 \cdot z\right)\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 62.2%

         \[\leadsto -1 \cdot \left(c \cdot \color{blue}{\left(\left(y0 \cdot y3\right) \cdot z\right)}\right) \]

      2. associate-*r* 62.2%

         \[\leadsto -1 \cdot \color{blue}{\left(\left(c \cdot \left(y0 \cdot y3\right)\right) \cdot z\right)} \]

   8. Simplified 62.2%

      \[\leadsto -1 \cdot \color{blue}{\left(\left(c \cdot \left(y0 \cdot y3\right)\right) \cdot z\right)} \]

   if 6.80000000000000035e-59 < t < 4.1000000000000003e38 or 4.8999999999999999e103 < t < 2.3800000000000001e111

   1. Initial program 30.8%

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

   2. Taylor expanded in b around inf 52.6%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 53.0%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 53.0%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 53.0%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 53.0%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 53.0%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 53.0%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   if 4.1000000000000003e38 < t < 4.8999999999999999e103 or 3.49999999999999992e216 < t

   1. Initial program 26.5%

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

   2. Taylor expanded in b around inf 33.5%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in t around inf 61.5%

      \[\leadsto b \cdot \color{blue}{\left(t \cdot \left(-1 \cdot \left(a \cdot z\right) + j \cdot y4\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 61.5%

         \[\leadsto b \cdot \left(t \cdot \color{blue}{\left(j \cdot y4 + -1 \cdot \left(a \cdot z\right)\right)}\right) \]

      2. mul-1-neg 61.5%

         \[\leadsto b \cdot \left(t \cdot \left(j \cdot y4 + \color{blue}{\left(-a \cdot z\right)}\right)\right) \]

      3. unsub-neg 61.5%

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

      4. *-commutative 61.5%

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

      5. *-commutative 61.5%

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

   5. Simplified 61.5%

      \[\leadsto b \cdot \color{blue}{\left(t \cdot \left(y4 \cdot j - z \cdot a\right)\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 49.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -3.7 \cdot 10^{+214}:\\ \;\;\;\;\left(j \cdot \left(-y5\right)\right) \cdot \left(t \cdot i\right)\\ \mathbf{elif}\;t \leq -3 \cdot 10^{+86}:\\ \;\;\;\;j \cdot \left(b \cdot \left(t \cdot y4\right)\right)\\ \mathbf{elif}\;t \leq 1.2 \cdot 10^{-151}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;t \leq 6.8 \cdot 10^{-59}:\\ \;\;\;\;z \cdot \left(c \cdot \left(y0 \cdot \left(-y3\right)\right)\right)\\ \mathbf{elif}\;t \leq 4.1 \cdot 10^{+38}:\\ \;\;\;\;b \cdot \left(a \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;t \leq 4.9 \cdot 10^{+103}:\\ \;\;\;\;b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ \mathbf{elif}\;t \leq 2.38 \cdot 10^{+111}:\\ \;\;\;\;b \cdot \left(a \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;t \leq 3.5 \cdot 10^{+216}:\\ \;\;\;\;\left(j \cdot \left(-y5\right)\right) \cdot \left(t \cdot i\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ \end{array} \]

Alternative 18: 28.5% accurate, 3.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \left(j \cdot \left(-y5\right)\right) \cdot \left(t \cdot i\right)\\ t_2 := b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ t_3 := b \cdot \left(a \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{if}\;t \leq -3.8 \cdot 10^{+215}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq -3.2 \cdot 10^{+90}:\\ \;\;\;\;j \cdot \left(b \cdot \left(t \cdot y4 - x \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 1.2 \cdot 10^{-151}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;t \leq 1.25 \cdot 10^{-58}:\\ \;\;\;\;z \cdot \left(c \cdot \left(y0 \cdot \left(-y3\right)\right)\right)\\ \mathbf{elif}\;t \leq 6.6 \cdot 10^{+35}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;t \leq 1.75 \cdot 10^{+104}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t \leq 1.75 \cdot 10^{+111}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;t \leq 2.6 \cdot 10^{+216}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* (* j (- y5)) (* t i)))
        (t_2 (* b (* t (- (* j y4) (* z a)))))
        (t_3 (* b (* a (- (* x y) (* z t))))))
   (if (<= t -3.8e+215)
     t_1
     (if (<= t -3.2e+90)
       (* j (* b (- (* t y4) (* x y0))))
       (if (<= t 1.2e-151)
         (* b (* y0 (- (* z k) (* x j))))
         (if (<= t 1.25e-58)
           (* z (* c (* y0 (- y3))))
           (if (<= t 6.6e+35)
             t_3
             (if (<= t 1.75e+104)
               t_2
               (if (<= t 1.75e+111) t_3 (if (<= t 2.6e+216) t_1 t_2))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (j * -y5) * (t * i);
	double t_2 = b * (t * ((j * y4) - (z * a)));
	double t_3 = b * (a * ((x * y) - (z * t)));
	double tmp;
	if (t <= -3.8e+215) {
		tmp = t_1;
	} else if (t <= -3.2e+90) {
		tmp = j * (b * ((t * y4) - (x * y0)));
	} else if (t <= 1.2e-151) {
		tmp = b * (y0 * ((z * k) - (x * j)));
	} else if (t <= 1.25e-58) {
		tmp = z * (c * (y0 * -y3));
	} else if (t <= 6.6e+35) {
		tmp = t_3;
	} else if (t <= 1.75e+104) {
		tmp = t_2;
	} else if (t <= 1.75e+111) {
		tmp = t_3;
	} else if (t <= 2.6e+216) {
		tmp = t_1;
	} else {
		tmp = t_2;
	}
	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 = (j * -y5) * (t * i)
    t_2 = b * (t * ((j * y4) - (z * a)))
    t_3 = b * (a * ((x * y) - (z * t)))
    if (t <= (-3.8d+215)) then
        tmp = t_1
    else if (t <= (-3.2d+90)) then
        tmp = j * (b * ((t * y4) - (x * y0)))
    else if (t <= 1.2d-151) then
        tmp = b * (y0 * ((z * k) - (x * j)))
    else if (t <= 1.25d-58) then
        tmp = z * (c * (y0 * -y3))
    else if (t <= 6.6d+35) then
        tmp = t_3
    else if (t <= 1.75d+104) then
        tmp = t_2
    else if (t <= 1.75d+111) then
        tmp = t_3
    else if (t <= 2.6d+216) then
        tmp = t_1
    else
        tmp = t_2
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (j * -y5) * (t * i);
	double t_2 = b * (t * ((j * y4) - (z * a)));
	double t_3 = b * (a * ((x * y) - (z * t)));
	double tmp;
	if (t <= -3.8e+215) {
		tmp = t_1;
	} else if (t <= -3.2e+90) {
		tmp = j * (b * ((t * y4) - (x * y0)));
	} else if (t <= 1.2e-151) {
		tmp = b * (y0 * ((z * k) - (x * j)));
	} else if (t <= 1.25e-58) {
		tmp = z * (c * (y0 * -y3));
	} else if (t <= 6.6e+35) {
		tmp = t_3;
	} else if (t <= 1.75e+104) {
		tmp = t_2;
	} else if (t <= 1.75e+111) {
		tmp = t_3;
	} else if (t <= 2.6e+216) {
		tmp = t_1;
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (j * -y5) * (t * i)
	t_2 = b * (t * ((j * y4) - (z * a)))
	t_3 = b * (a * ((x * y) - (z * t)))
	tmp = 0
	if t <= -3.8e+215:
		tmp = t_1
	elif t <= -3.2e+90:
		tmp = j * (b * ((t * y4) - (x * y0)))
	elif t <= 1.2e-151:
		tmp = b * (y0 * ((z * k) - (x * j)))
	elif t <= 1.25e-58:
		tmp = z * (c * (y0 * -y3))
	elif t <= 6.6e+35:
		tmp = t_3
	elif t <= 1.75e+104:
		tmp = t_2
	elif t <= 1.75e+111:
		tmp = t_3
	elif t <= 2.6e+216:
		tmp = t_1
	else:
		tmp = t_2
	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(j * Float64(-y5)) * Float64(t * i))
	t_2 = Float64(b * Float64(t * Float64(Float64(j * y4) - Float64(z * a))))
	t_3 = Float64(b * Float64(a * Float64(Float64(x * y) - Float64(z * t))))
	tmp = 0.0
	if (t <= -3.8e+215)
		tmp = t_1;
	elseif (t <= -3.2e+90)
		tmp = Float64(j * Float64(b * Float64(Float64(t * y4) - Float64(x * y0))));
	elseif (t <= 1.2e-151)
		tmp = Float64(b * Float64(y0 * Float64(Float64(z * k) - Float64(x * j))));
	elseif (t <= 1.25e-58)
		tmp = Float64(z * Float64(c * Float64(y0 * Float64(-y3))));
	elseif (t <= 6.6e+35)
		tmp = t_3;
	elseif (t <= 1.75e+104)
		tmp = t_2;
	elseif (t <= 1.75e+111)
		tmp = t_3;
	elseif (t <= 2.6e+216)
		tmp = t_1;
	else
		tmp = t_2;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = (j * -y5) * (t * i);
	t_2 = b * (t * ((j * y4) - (z * a)));
	t_3 = b * (a * ((x * y) - (z * t)));
	tmp = 0.0;
	if (t <= -3.8e+215)
		tmp = t_1;
	elseif (t <= -3.2e+90)
		tmp = j * (b * ((t * y4) - (x * y0)));
	elseif (t <= 1.2e-151)
		tmp = b * (y0 * ((z * k) - (x * j)));
	elseif (t <= 1.25e-58)
		tmp = z * (c * (y0 * -y3));
	elseif (t <= 6.6e+35)
		tmp = t_3;
	elseif (t <= 1.75e+104)
		tmp = t_2;
	elseif (t <= 1.75e+111)
		tmp = t_3;
	elseif (t <= 2.6e+216)
		tmp = t_1;
	else
		tmp = t_2;
	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[(j * (-y5)), $MachinePrecision] * N[(t * i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(b * N[(t * N[(N[(j * y4), $MachinePrecision] - N[(z * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(b * N[(a * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -3.8e+215], t$95$1, If[LessEqual[t, -3.2e+90], N[(j * N[(b * N[(N[(t * y4), $MachinePrecision] - N[(x * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.2e-151], N[(b * N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.25e-58], N[(z * N[(c * N[(y0 * (-y3)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 6.6e+35], t$95$3, If[LessEqual[t, 1.75e+104], t$95$2, If[LessEqual[t, 1.75e+111], t$95$3, If[LessEqual[t, 2.6e+216], t$95$1, t$95$2]]]]]]]]]]]

Derivation

1. Split input into 6 regimes

2. if t < -3.79999999999999968e215 or 1.7500000000000001e111 < t < 2.5999999999999999e216

   1. Initial program 31.8%

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

   2. Taylor expanded in j around inf 39.2%

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

   3. Taylor expanded in y5 around -inf 52.0%

      \[\leadsto \color{blue}{-1 \cdot \left(j \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)\right)\right)} \]
   4. Step-by-step derivation

      1. mul-1-neg 52.0%

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

      2. associate-*r* 52.0%

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

      3. distribute-lft-neg-in 52.0%

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

      4. distribute-rgt-neg-in 52.0%

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

      5. +-commutative 52.0%

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

      6. mul-1-neg 52.0%

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

      7. unsub-neg 52.0%

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

      8. *-commutative 52.0%

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

   5. Simplified 52.0%

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

   6. Taylor expanded in i around inf 52.1%

      \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \color{blue}{\left(i \cdot t\right)} \]
   7. Step-by-step derivation

      1. *-commutative 52.1%

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

   8. Simplified 52.1%

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

   if -3.79999999999999968e215 < t < -3.19999999999999998e90

   1. Initial program 29.2%

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

   2. Taylor expanded in j around inf 42.1%

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

   3. Taylor expanded in b around inf 55.1%

      \[\leadsto j \cdot \color{blue}{\left(b \cdot \left(t \cdot y4 - x \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 55.1%

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

   5. Simplified 55.1%

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

   if -3.19999999999999998e90 < t < 1.2e-151

   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. Taylor expanded in b around inf 38.7%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in y0 around inf 40.9%

      \[\leadsto b \cdot \color{blue}{\left(y0 \cdot \left(k \cdot z - j \cdot x\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 40.9%

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

   5. Simplified 40.9%

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

   if 1.2e-151 < t < 1.24999999999999994e-58

   1. Initial program 54.4%

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

   2. Taylor expanded in z around -inf 54.6%

      \[\leadsto \color{blue}{-1 \cdot \left(z \cdot \left(\left(t \cdot \left(a \cdot b - c \cdot i\right) + y3 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   3. Taylor expanded in y0 around inf 33.2%

      \[\leadsto -1 \cdot \color{blue}{\left(y0 \cdot \left(z \cdot \left(c \cdot y3 - b \cdot k\right)\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 33.2%

         \[\leadsto -1 \cdot \color{blue}{\left(\left(y0 \cdot z\right) \cdot \left(c \cdot y3 - b \cdot k\right)\right)} \]

      2. *-commutative 33.2%

         \[\leadsto -1 \cdot \left(\color{blue}{\left(z \cdot y0\right)} \cdot \left(c \cdot y3 - b \cdot k\right)\right) \]

      3. *-commutative 33.2%

         \[\leadsto -1 \cdot \left(\left(z \cdot y0\right) \cdot \left(\color{blue}{y3 \cdot c} - b \cdot k\right)\right) \]

      4. *-commutative 33.2%

         \[\leadsto -1 \cdot \left(\left(z \cdot y0\right) \cdot \left(y3 \cdot c - \color{blue}{k \cdot b}\right)\right) \]

   5. Simplified 33.2%

      \[\leadsto -1 \cdot \color{blue}{\left(\left(z \cdot y0\right) \cdot \left(y3 \cdot c - k \cdot b\right)\right)} \]

   6. Taylor expanded in y3 around inf 47.5%

      \[\leadsto -1 \cdot \color{blue}{\left(c \cdot \left(y0 \cdot \left(y3 \cdot z\right)\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 62.2%

         \[\leadsto -1 \cdot \left(c \cdot \color{blue}{\left(\left(y0 \cdot y3\right) \cdot z\right)}\right) \]

      2. associate-*r* 62.2%

         \[\leadsto -1 \cdot \color{blue}{\left(\left(c \cdot \left(y0 \cdot y3\right)\right) \cdot z\right)} \]

   8. Simplified 62.2%

      \[\leadsto -1 \cdot \color{blue}{\left(\left(c \cdot \left(y0 \cdot y3\right)\right) \cdot z\right)} \]

   if 1.24999999999999994e-58 < t < 6.6000000000000003e35 or 1.7500000000000001e104 < t < 1.7500000000000001e111

   1. Initial program 30.8%

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

   2. Taylor expanded in b around inf 52.6%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 53.0%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 53.0%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 53.0%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 53.0%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 53.0%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 53.0%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   if 6.6000000000000003e35 < t < 1.7500000000000001e104 or 2.5999999999999999e216 < t

   1. Initial program 26.5%

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

   2. Taylor expanded in b around inf 33.5%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in t around inf 61.5%

      \[\leadsto b \cdot \color{blue}{\left(t \cdot \left(-1 \cdot \left(a \cdot z\right) + j \cdot y4\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 61.5%

         \[\leadsto b \cdot \left(t \cdot \color{blue}{\left(j \cdot y4 + -1 \cdot \left(a \cdot z\right)\right)}\right) \]

      2. mul-1-neg 61.5%

         \[\leadsto b \cdot \left(t \cdot \left(j \cdot y4 + \color{blue}{\left(-a \cdot z\right)}\right)\right) \]

      3. unsub-neg 61.5%

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

      4. *-commutative 61.5%

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

      5. *-commutative 61.5%

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

   5. Simplified 61.5%

      \[\leadsto b \cdot \color{blue}{\left(t \cdot \left(y4 \cdot j - z \cdot a\right)\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 49.6%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -3.8 \cdot 10^{+215}:\\ \;\;\;\;\left(j \cdot \left(-y5\right)\right) \cdot \left(t \cdot i\right)\\ \mathbf{elif}\;t \leq -3.2 \cdot 10^{+90}:\\ \;\;\;\;j \cdot \left(b \cdot \left(t \cdot y4 - x \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 1.2 \cdot 10^{-151}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;t \leq 1.25 \cdot 10^{-58}:\\ \;\;\;\;z \cdot \left(c \cdot \left(y0 \cdot \left(-y3\right)\right)\right)\\ \mathbf{elif}\;t \leq 6.6 \cdot 10^{+35}:\\ \;\;\;\;b \cdot \left(a \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;t \leq 1.75 \cdot 10^{+104}:\\ \;\;\;\;b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ \mathbf{elif}\;t \leq 1.75 \cdot 10^{+111}:\\ \;\;\;\;b \cdot \left(a \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;t \leq 2.6 \cdot 10^{+216}:\\ \;\;\;\;\left(j \cdot \left(-y5\right)\right) \cdot \left(t \cdot i\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ \end{array} \]

Alternative 19: 31.3% accurate, 3.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{if}\;t \leq -3.3 \cdot 10^{+217}:\\ \;\;\;\;t \cdot \left(z \cdot \left(c \cdot i - a \cdot b\right)\right)\\ \mathbf{elif}\;t \leq -5.5 \cdot 10^{+104}:\\ \;\;\;\;j \cdot \left(y4 \cdot \left(t \cdot b - y1 \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq -3.4 \cdot 10^{+29}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq -0.0039:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;t \leq -4.8 \cdot 10^{-173}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq 4.5 \cdot 10^{-199}:\\ \;\;\;\;k \cdot \left(y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{elif}\;t \leq 4.6 \cdot 10^{-151}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq 3.3 \cdot 10^{-40}:\\ \;\;\;\;y0 \cdot \left(y3 \cdot \left(j \cdot y5 - z \cdot c\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* y0 (- (* z k) (* x j))))))
   (if (<= t -3.3e+217)
     (* t (* z (- (* c i) (* a b))))
     (if (<= t -5.5e+104)
       (* j (* y4 (- (* t b) (* y1 y3))))
       (if (<= t -3.4e+29)
         (* i (* k (- (* y y5) (* z y1))))
         (if (<= t -0.0039)
           (* j (* y0 (- (* y3 y5) (* x b))))
           (if (<= t -4.8e-173)
             t_1
             (if (<= t 4.5e-199)
               (* k (* y (- (* i y5) (* b y4))))
               (if (<= t 4.6e-151)
                 t_1
                 (if (<= t 3.3e-40)
                   (* y0 (* y3 (- (* j y5) (* z c))))
                   (* b (* t (- (* j y4) (* z a))))))))))))))

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 * (y0 * ((z * k) - (x * j)));
	double tmp;
	if (t <= -3.3e+217) {
		tmp = t * (z * ((c * i) - (a * b)));
	} else if (t <= -5.5e+104) {
		tmp = j * (y4 * ((t * b) - (y1 * y3)));
	} else if (t <= -3.4e+29) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (t <= -0.0039) {
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	} else if (t <= -4.8e-173) {
		tmp = t_1;
	} else if (t <= 4.5e-199) {
		tmp = k * (y * ((i * y5) - (b * y4)));
	} else if (t <= 4.6e-151) {
		tmp = t_1;
	} else if (t <= 3.3e-40) {
		tmp = y0 * (y3 * ((j * y5) - (z * c)));
	} else {
		tmp = b * (t * ((j * y4) - (z * a)));
	}
	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 * (y0 * ((z * k) - (x * j)))
    if (t <= (-3.3d+217)) then
        tmp = t * (z * ((c * i) - (a * b)))
    else if (t <= (-5.5d+104)) then
        tmp = j * (y4 * ((t * b) - (y1 * y3)))
    else if (t <= (-3.4d+29)) then
        tmp = i * (k * ((y * y5) - (z * y1)))
    else if (t <= (-0.0039d0)) then
        tmp = j * (y0 * ((y3 * y5) - (x * b)))
    else if (t <= (-4.8d-173)) then
        tmp = t_1
    else if (t <= 4.5d-199) then
        tmp = k * (y * ((i * y5) - (b * y4)))
    else if (t <= 4.6d-151) then
        tmp = t_1
    else if (t <= 3.3d-40) then
        tmp = y0 * (y3 * ((j * y5) - (z * c)))
    else
        tmp = b * (t * ((j * y4) - (z * a)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (y0 * ((z * k) - (x * j)));
	double tmp;
	if (t <= -3.3e+217) {
		tmp = t * (z * ((c * i) - (a * b)));
	} else if (t <= -5.5e+104) {
		tmp = j * (y4 * ((t * b) - (y1 * y3)));
	} else if (t <= -3.4e+29) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (t <= -0.0039) {
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	} else if (t <= -4.8e-173) {
		tmp = t_1;
	} else if (t <= 4.5e-199) {
		tmp = k * (y * ((i * y5) - (b * y4)));
	} else if (t <= 4.6e-151) {
		tmp = t_1;
	} else if (t <= 3.3e-40) {
		tmp = y0 * (y3 * ((j * y5) - (z * c)));
	} else {
		tmp = b * (t * ((j * y4) - (z * a)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = b * (y0 * ((z * k) - (x * j)))
	tmp = 0
	if t <= -3.3e+217:
		tmp = t * (z * ((c * i) - (a * b)))
	elif t <= -5.5e+104:
		tmp = j * (y4 * ((t * b) - (y1 * y3)))
	elif t <= -3.4e+29:
		tmp = i * (k * ((y * y5) - (z * y1)))
	elif t <= -0.0039:
		tmp = j * (y0 * ((y3 * y5) - (x * b)))
	elif t <= -4.8e-173:
		tmp = t_1
	elif t <= 4.5e-199:
		tmp = k * (y * ((i * y5) - (b * y4)))
	elif t <= 4.6e-151:
		tmp = t_1
	elif t <= 3.3e-40:
		tmp = y0 * (y3 * ((j * y5) - (z * c)))
	else:
		tmp = b * (t * ((j * y4) - (z * a)))
	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(y0 * Float64(Float64(z * k) - Float64(x * j))))
	tmp = 0.0
	if (t <= -3.3e+217)
		tmp = Float64(t * Float64(z * Float64(Float64(c * i) - Float64(a * b))));
	elseif (t <= -5.5e+104)
		tmp = Float64(j * Float64(y4 * Float64(Float64(t * b) - Float64(y1 * y3))));
	elseif (t <= -3.4e+29)
		tmp = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))));
	elseif (t <= -0.0039)
		tmp = Float64(j * Float64(y0 * Float64(Float64(y3 * y5) - Float64(x * b))));
	elseif (t <= -4.8e-173)
		tmp = t_1;
	elseif (t <= 4.5e-199)
		tmp = Float64(k * Float64(y * Float64(Float64(i * y5) - Float64(b * y4))));
	elseif (t <= 4.6e-151)
		tmp = t_1;
	elseif (t <= 3.3e-40)
		tmp = Float64(y0 * Float64(y3 * Float64(Float64(j * y5) - Float64(z * c))));
	else
		tmp = Float64(b * Float64(t * Float64(Float64(j * y4) - Float64(z * a))));
	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 * (y0 * ((z * k) - (x * j)));
	tmp = 0.0;
	if (t <= -3.3e+217)
		tmp = t * (z * ((c * i) - (a * b)));
	elseif (t <= -5.5e+104)
		tmp = j * (y4 * ((t * b) - (y1 * y3)));
	elseif (t <= -3.4e+29)
		tmp = i * (k * ((y * y5) - (z * y1)));
	elseif (t <= -0.0039)
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	elseif (t <= -4.8e-173)
		tmp = t_1;
	elseif (t <= 4.5e-199)
		tmp = k * (y * ((i * y5) - (b * y4)));
	elseif (t <= 4.6e-151)
		tmp = t_1;
	elseif (t <= 3.3e-40)
		tmp = y0 * (y3 * ((j * y5) - (z * c)));
	else
		tmp = b * (t * ((j * y4) - (z * a)));
	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[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -3.3e+217], N[(t * N[(z * N[(N[(c * i), $MachinePrecision] - N[(a * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -5.5e+104], N[(j * N[(y4 * N[(N[(t * b), $MachinePrecision] - N[(y1 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -3.4e+29], N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -0.0039], N[(j * N[(y0 * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -4.8e-173], t$95$1, If[LessEqual[t, 4.5e-199], N[(k * N[(y * N[(N[(i * y5), $MachinePrecision] - N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 4.6e-151], t$95$1, If[LessEqual[t, 3.3e-40], N[(y0 * N[(y3 * N[(N[(j * y5), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(t * N[(N[(j * y4), $MachinePrecision] - N[(z * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]

Derivation

1. Split input into 8 regimes

2. if t < -3.3e217

   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. Taylor expanded in z around -inf 70.4%

      \[\leadsto \color{blue}{-1 \cdot \left(z \cdot \left(\left(t \cdot \left(a \cdot b - c \cdot i\right) + y3 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   3. Taylor expanded in t around inf 61.6%

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

   if -3.3e217 < t < -5.50000000000000017e104

   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. Taylor expanded in j around inf 40.4%

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

   3. Taylor expanded in y4 around inf 65.2%

      \[\leadsto \color{blue}{j \cdot \left(y4 \cdot \left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 65.2%

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

      2. +-commutative 65.2%

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

      3. mul-1-neg 65.2%

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

      4. unsub-neg 65.2%

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

      5. *-commutative 65.2%

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

   5. Simplified 65.2%

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

   if -5.50000000000000017e104 < t < -3.39999999999999981e29

   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. Taylor expanded in k around inf 37.1%

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

   3. Taylor expanded in i around inf 73.1%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - y1 \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 73.1%

         \[\leadsto i \cdot \left(k \cdot \left(y \cdot y5 - \color{blue}{z \cdot y1}\right)\right) \]

   5. Simplified 73.1%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)} \]

   if -3.39999999999999981e29 < t < -0.0038999999999999998

   1. Initial program 10.0%

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

   2. Taylor expanded in j around inf 50.0%

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

   3. Taylor expanded in y0 around inf 70.6%

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

   if -0.0038999999999999998 < t < -4.80000000000000034e-173 or 4.49999999999999998e-199 < t < 4.59999999999999992e-151

   1. Initial program 39.7%

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

   2. Taylor expanded in b around inf 40.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in y0 around inf 46.9%

      \[\leadsto b \cdot \color{blue}{\left(y0 \cdot \left(k \cdot z - j \cdot x\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 46.9%

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

   5. Simplified 46.9%

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

   if -4.80000000000000034e-173 < t < 4.49999999999999998e-199

   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. Taylor expanded in k around inf 38.4%

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

   3. Taylor expanded in y around inf 41.8%

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

   if 4.59999999999999992e-151 < t < 3.29999999999999993e-40

   1. Initial program 53.4%

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

   2. Taylor expanded in y0 around inf 65.5%

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

   3. Taylor expanded in y3 around -inf 71.2%

      \[\leadsto \color{blue}{-1 \cdot \left(y0 \cdot \left(y3 \cdot \left(-1 \cdot \left(j \cdot y5\right) + c \cdot z\right)\right)\right)} \]
   4. Step-by-step derivation

      1. mul-1-neg 71.2%

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

      2. distribute-rgt-neg-in 71.2%

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

      3. distribute-rgt-neg-in 71.2%

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

      4. +-commutative 71.2%

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

      5. mul-1-neg 71.2%

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

      6. unsub-neg 71.2%

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

   5. Simplified 71.2%

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

   if 3.29999999999999993e-40 < t

   1. Initial program 27.5%

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

   2. Taylor expanded in b around inf 38.6%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in t around inf 46.1%

      \[\leadsto b \cdot \color{blue}{\left(t \cdot \left(-1 \cdot \left(a \cdot z\right) + j \cdot y4\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 46.1%

         \[\leadsto b \cdot \left(t \cdot \color{blue}{\left(j \cdot y4 + -1 \cdot \left(a \cdot z\right)\right)}\right) \]

      2. mul-1-neg 46.1%

         \[\leadsto b \cdot \left(t \cdot \left(j \cdot y4 + \color{blue}{\left(-a \cdot z\right)}\right)\right) \]

      3. unsub-neg 46.1%

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

      4. *-commutative 46.1%

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

      5. *-commutative 46.1%

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

   5. Simplified 46.1%

      \[\leadsto b \cdot \color{blue}{\left(t \cdot \left(y4 \cdot j - z \cdot a\right)\right)} \]
3. Recombined 8 regimes into one program.

4. Final simplification 51.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -3.3 \cdot 10^{+217}:\\ \;\;\;\;t \cdot \left(z \cdot \left(c \cdot i - a \cdot b\right)\right)\\ \mathbf{elif}\;t \leq -5.5 \cdot 10^{+104}:\\ \;\;\;\;j \cdot \left(y4 \cdot \left(t \cdot b - y1 \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq -3.4 \cdot 10^{+29}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq -0.0039:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;t \leq -4.8 \cdot 10^{-173}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;t \leq 4.5 \cdot 10^{-199}:\\ \;\;\;\;k \cdot \left(y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\\ \mathbf{elif}\;t \leq 4.6 \cdot 10^{-151}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;t \leq 3.3 \cdot 10^{-40}:\\ \;\;\;\;y0 \cdot \left(y3 \cdot \left(j \cdot y5 - z \cdot c\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ \end{array} \]

Alternative 20: 31.7% accurate, 3.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{if}\;t \leq -3 \cdot 10^{+217}:\\ \;\;\;\;t \cdot \left(z \cdot \left(c \cdot i - a \cdot b\right)\right)\\ \mathbf{elif}\;t \leq -5.6 \cdot 10^{+104}:\\ \;\;\;\;j \cdot \left(y4 \cdot \left(t \cdot b - y1 \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq -3.5 \cdot 10^{+29}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq -4.8 \cdot 10^{-5}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;t \leq -1.05 \cdot 10^{-281}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq 3 \cdot 10^{-195}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0 - y \cdot y4\right)\right)\\ \mathbf{elif}\;t \leq 2 \cdot 10^{-150}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq 2.22 \cdot 10^{-41}:\\ \;\;\;\;y0 \cdot \left(y3 \cdot \left(j \cdot y5 - z \cdot c\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* y0 (- (* z k) (* x j))))))
   (if (<= t -3e+217)
     (* t (* z (- (* c i) (* a b))))
     (if (<= t -5.6e+104)
       (* j (* y4 (- (* t b) (* y1 y3))))
       (if (<= t -3.5e+29)
         (* i (* k (- (* y y5) (* z y1))))
         (if (<= t -4.8e-5)
           (* j (* y0 (- (* y3 y5) (* x b))))
           (if (<= t -1.05e-281)
             t_1
             (if (<= t 3e-195)
               (* b (* k (- (* z y0) (* y y4))))
               (if (<= t 2e-150)
                 t_1
                 (if (<= t 2.22e-41)
                   (* y0 (* y3 (- (* j y5) (* z c))))
                   (* b (* t (- (* j y4) (* z a))))))))))))))

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 * (y0 * ((z * k) - (x * j)));
	double tmp;
	if (t <= -3e+217) {
		tmp = t * (z * ((c * i) - (a * b)));
	} else if (t <= -5.6e+104) {
		tmp = j * (y4 * ((t * b) - (y1 * y3)));
	} else if (t <= -3.5e+29) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (t <= -4.8e-5) {
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	} else if (t <= -1.05e-281) {
		tmp = t_1;
	} else if (t <= 3e-195) {
		tmp = b * (k * ((z * y0) - (y * y4)));
	} else if (t <= 2e-150) {
		tmp = t_1;
	} else if (t <= 2.22e-41) {
		tmp = y0 * (y3 * ((j * y5) - (z * c)));
	} else {
		tmp = b * (t * ((j * y4) - (z * a)));
	}
	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 * (y0 * ((z * k) - (x * j)))
    if (t <= (-3d+217)) then
        tmp = t * (z * ((c * i) - (a * b)))
    else if (t <= (-5.6d+104)) then
        tmp = j * (y4 * ((t * b) - (y1 * y3)))
    else if (t <= (-3.5d+29)) then
        tmp = i * (k * ((y * y5) - (z * y1)))
    else if (t <= (-4.8d-5)) then
        tmp = j * (y0 * ((y3 * y5) - (x * b)))
    else if (t <= (-1.05d-281)) then
        tmp = t_1
    else if (t <= 3d-195) then
        tmp = b * (k * ((z * y0) - (y * y4)))
    else if (t <= 2d-150) then
        tmp = t_1
    else if (t <= 2.22d-41) then
        tmp = y0 * (y3 * ((j * y5) - (z * c)))
    else
        tmp = b * (t * ((j * y4) - (z * a)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (y0 * ((z * k) - (x * j)));
	double tmp;
	if (t <= -3e+217) {
		tmp = t * (z * ((c * i) - (a * b)));
	} else if (t <= -5.6e+104) {
		tmp = j * (y4 * ((t * b) - (y1 * y3)));
	} else if (t <= -3.5e+29) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (t <= -4.8e-5) {
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	} else if (t <= -1.05e-281) {
		tmp = t_1;
	} else if (t <= 3e-195) {
		tmp = b * (k * ((z * y0) - (y * y4)));
	} else if (t <= 2e-150) {
		tmp = t_1;
	} else if (t <= 2.22e-41) {
		tmp = y0 * (y3 * ((j * y5) - (z * c)));
	} else {
		tmp = b * (t * ((j * y4) - (z * a)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = b * (y0 * ((z * k) - (x * j)))
	tmp = 0
	if t <= -3e+217:
		tmp = t * (z * ((c * i) - (a * b)))
	elif t <= -5.6e+104:
		tmp = j * (y4 * ((t * b) - (y1 * y3)))
	elif t <= -3.5e+29:
		tmp = i * (k * ((y * y5) - (z * y1)))
	elif t <= -4.8e-5:
		tmp = j * (y0 * ((y3 * y5) - (x * b)))
	elif t <= -1.05e-281:
		tmp = t_1
	elif t <= 3e-195:
		tmp = b * (k * ((z * y0) - (y * y4)))
	elif t <= 2e-150:
		tmp = t_1
	elif t <= 2.22e-41:
		tmp = y0 * (y3 * ((j * y5) - (z * c)))
	else:
		tmp = b * (t * ((j * y4) - (z * a)))
	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(y0 * Float64(Float64(z * k) - Float64(x * j))))
	tmp = 0.0
	if (t <= -3e+217)
		tmp = Float64(t * Float64(z * Float64(Float64(c * i) - Float64(a * b))));
	elseif (t <= -5.6e+104)
		tmp = Float64(j * Float64(y4 * Float64(Float64(t * b) - Float64(y1 * y3))));
	elseif (t <= -3.5e+29)
		tmp = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))));
	elseif (t <= -4.8e-5)
		tmp = Float64(j * Float64(y0 * Float64(Float64(y3 * y5) - Float64(x * b))));
	elseif (t <= -1.05e-281)
		tmp = t_1;
	elseif (t <= 3e-195)
		tmp = Float64(b * Float64(k * Float64(Float64(z * y0) - Float64(y * y4))));
	elseif (t <= 2e-150)
		tmp = t_1;
	elseif (t <= 2.22e-41)
		tmp = Float64(y0 * Float64(y3 * Float64(Float64(j * y5) - Float64(z * c))));
	else
		tmp = Float64(b * Float64(t * Float64(Float64(j * y4) - Float64(z * a))));
	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 * (y0 * ((z * k) - (x * j)));
	tmp = 0.0;
	if (t <= -3e+217)
		tmp = t * (z * ((c * i) - (a * b)));
	elseif (t <= -5.6e+104)
		tmp = j * (y4 * ((t * b) - (y1 * y3)));
	elseif (t <= -3.5e+29)
		tmp = i * (k * ((y * y5) - (z * y1)));
	elseif (t <= -4.8e-5)
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	elseif (t <= -1.05e-281)
		tmp = t_1;
	elseif (t <= 3e-195)
		tmp = b * (k * ((z * y0) - (y * y4)));
	elseif (t <= 2e-150)
		tmp = t_1;
	elseif (t <= 2.22e-41)
		tmp = y0 * (y3 * ((j * y5) - (z * c)));
	else
		tmp = b * (t * ((j * y4) - (z * a)));
	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[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -3e+217], N[(t * N[(z * N[(N[(c * i), $MachinePrecision] - N[(a * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -5.6e+104], N[(j * N[(y4 * N[(N[(t * b), $MachinePrecision] - N[(y1 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -3.5e+29], N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -4.8e-5], N[(j * N[(y0 * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -1.05e-281], t$95$1, If[LessEqual[t, 3e-195], N[(b * N[(k * N[(N[(z * y0), $MachinePrecision] - N[(y * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 2e-150], t$95$1, If[LessEqual[t, 2.22e-41], N[(y0 * N[(y3 * N[(N[(j * y5), $MachinePrecision] - N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(t * N[(N[(j * y4), $MachinePrecision] - N[(z * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]

Derivation

1. Split input into 8 regimes

2. if t < -2.99999999999999976e217

   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. Taylor expanded in z around -inf 70.4%

      \[\leadsto \color{blue}{-1 \cdot \left(z \cdot \left(\left(t \cdot \left(a \cdot b - c \cdot i\right) + y3 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   3. Taylor expanded in t around inf 61.6%

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

   if -2.99999999999999976e217 < t < -5.6e104

   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. Taylor expanded in j around inf 40.4%

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

   3. Taylor expanded in y4 around inf 65.2%

      \[\leadsto \color{blue}{j \cdot \left(y4 \cdot \left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 65.2%

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

      2. +-commutative 65.2%

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

      3. mul-1-neg 65.2%

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

      4. unsub-neg 65.2%

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

      5. *-commutative 65.2%

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

   5. Simplified 65.2%

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

   if -5.6e104 < t < -3.49999999999999979e29

   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. Taylor expanded in k around inf 37.1%

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

   3. Taylor expanded in i around inf 73.1%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - y1 \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 73.1%

         \[\leadsto i \cdot \left(k \cdot \left(y \cdot y5 - \color{blue}{z \cdot y1}\right)\right) \]

   5. Simplified 73.1%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)} \]

   if -3.49999999999999979e29 < t < -4.8000000000000001e-5

   1. Initial program 10.0%

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

   2. Taylor expanded in j around inf 50.0%

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

   3. Taylor expanded in y0 around inf 70.6%

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

   if -4.8000000000000001e-5 < t < -1.0499999999999999e-281 or 3e-195 < t < 2.00000000000000001e-150

   1. Initial program 37.6%

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

   2. Taylor expanded in b around inf 37.9%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in y0 around inf 44.8%

      \[\leadsto b \cdot \color{blue}{\left(y0 \cdot \left(k \cdot z - j \cdot x\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 44.8%

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

   5. Simplified 44.8%

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

   if -1.0499999999999999e-281 < t < 3e-195

   1. Initial program 39.3%

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

   2. Taylor expanded in b around inf 43.6%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in k around inf 43.7%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(-1 \cdot \left(y \cdot y4\right) - -1 \cdot \left(y0 \cdot z\right)\right)\right)} \]
   4. Step-by-step derivation

      1. distribute-lft-out-- 43.7%

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

      2. *-commutative 43.7%

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

      3. *-commutative 43.7%

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

   5. Simplified 43.7%

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

   if 2.00000000000000001e-150 < t < 2.2200000000000001e-41

   1. Initial program 53.4%

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

   2. Taylor expanded in y0 around inf 65.5%

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

   3. Taylor expanded in y3 around -inf 71.2%

      \[\leadsto \color{blue}{-1 \cdot \left(y0 \cdot \left(y3 \cdot \left(-1 \cdot \left(j \cdot y5\right) + c \cdot z\right)\right)\right)} \]
   4. Step-by-step derivation

      1. mul-1-neg 71.2%

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

      2. distribute-rgt-neg-in 71.2%

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

      3. distribute-rgt-neg-in 71.2%

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

      4. +-commutative 71.2%

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

      5. mul-1-neg 71.2%

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

      6. unsub-neg 71.2%

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

   5. Simplified 71.2%

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

   if 2.2200000000000001e-41 < t

   1. Initial program 27.5%

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

   2. Taylor expanded in b around inf 38.6%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in t around inf 46.1%

      \[\leadsto b \cdot \color{blue}{\left(t \cdot \left(-1 \cdot \left(a \cdot z\right) + j \cdot y4\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 46.1%

         \[\leadsto b \cdot \left(t \cdot \color{blue}{\left(j \cdot y4 + -1 \cdot \left(a \cdot z\right)\right)}\right) \]

      2. mul-1-neg 46.1%

         \[\leadsto b \cdot \left(t \cdot \left(j \cdot y4 + \color{blue}{\left(-a \cdot z\right)}\right)\right) \]

      3. unsub-neg 46.1%

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

      4. *-commutative 46.1%

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

      5. *-commutative 46.1%

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

   5. Simplified 46.1%

      \[\leadsto b \cdot \color{blue}{\left(t \cdot \left(y4 \cdot j - z \cdot a\right)\right)} \]
3. Recombined 8 regimes into one program.

4. Final simplification 52.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -3 \cdot 10^{+217}:\\ \;\;\;\;t \cdot \left(z \cdot \left(c \cdot i - a \cdot b\right)\right)\\ \mathbf{elif}\;t \leq -5.6 \cdot 10^{+104}:\\ \;\;\;\;j \cdot \left(y4 \cdot \left(t \cdot b - y1 \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq -3.5 \cdot 10^{+29}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq -4.8 \cdot 10^{-5}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;t \leq -1.05 \cdot 10^{-281}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;t \leq 3 \cdot 10^{-195}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0 - y \cdot y4\right)\right)\\ \mathbf{elif}\;t \leq 2 \cdot 10^{-150}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;t \leq 2.22 \cdot 10^{-41}:\\ \;\;\;\;y0 \cdot \left(y3 \cdot \left(j \cdot y5 - z \cdot c\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ \end{array} \]

Alternative 21: 30.4% accurate, 3.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ t_2 := b \cdot \left(a \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{if}\;t \leq -2.05 \cdot 10^{+86}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq 6 \cdot 10^{-150}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;t \leq 2 \cdot 10^{-58}:\\ \;\;\;\;z \cdot \left(c \cdot \left(y0 \cdot \left(-y3\right)\right)\right)\\ \mathbf{elif}\;t \leq 3.5 \cdot 10^{+36}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t \leq 2.55 \cdot 10^{+104}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq 4.6 \cdot 10^{+111}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t \leq 6.2 \cdot 10^{+216}:\\ \;\;\;\;\left(j \cdot \left(-y5\right)\right) \cdot \left(t \cdot i\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* t (- (* j y4) (* z a)))))
        (t_2 (* b (* a (- (* x y) (* z t))))))
   (if (<= t -2.05e+86)
     (* j (* t (- (* b y4) (* i y5))))
     (if (<= t 6e-150)
       (* b (* y0 (- (* z k) (* x j))))
       (if (<= t 2e-58)
         (* z (* c (* y0 (- y3))))
         (if (<= t 3.5e+36)
           t_2
           (if (<= t 2.55e+104)
             t_1
             (if (<= t 4.6e+111)
               t_2
               (if (<= t 6.2e+216) (* (* j (- y5)) (* t i)) t_1)))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (t * ((j * y4) - (z * a)));
	double t_2 = b * (a * ((x * y) - (z * t)));
	double tmp;
	if (t <= -2.05e+86) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (t <= 6e-150) {
		tmp = b * (y0 * ((z * k) - (x * j)));
	} else if (t <= 2e-58) {
		tmp = z * (c * (y0 * -y3));
	} else if (t <= 3.5e+36) {
		tmp = t_2;
	} else if (t <= 2.55e+104) {
		tmp = t_1;
	} else if (t <= 4.6e+111) {
		tmp = t_2;
	} else if (t <= 6.2e+216) {
		tmp = (j * -y5) * (t * i);
	} 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 = b * (t * ((j * y4) - (z * a)))
    t_2 = b * (a * ((x * y) - (z * t)))
    if (t <= (-2.05d+86)) then
        tmp = j * (t * ((b * y4) - (i * y5)))
    else if (t <= 6d-150) then
        tmp = b * (y0 * ((z * k) - (x * j)))
    else if (t <= 2d-58) then
        tmp = z * (c * (y0 * -y3))
    else if (t <= 3.5d+36) then
        tmp = t_2
    else if (t <= 2.55d+104) then
        tmp = t_1
    else if (t <= 4.6d+111) then
        tmp = t_2
    else if (t <= 6.2d+216) then
        tmp = (j * -y5) * (t * i)
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (t * ((j * y4) - (z * a)));
	double t_2 = b * (a * ((x * y) - (z * t)));
	double tmp;
	if (t <= -2.05e+86) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (t <= 6e-150) {
		tmp = b * (y0 * ((z * k) - (x * j)));
	} else if (t <= 2e-58) {
		tmp = z * (c * (y0 * -y3));
	} else if (t <= 3.5e+36) {
		tmp = t_2;
	} else if (t <= 2.55e+104) {
		tmp = t_1;
	} else if (t <= 4.6e+111) {
		tmp = t_2;
	} else if (t <= 6.2e+216) {
		tmp = (j * -y5) * (t * i);
	} 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 = b * (t * ((j * y4) - (z * a)))
	t_2 = b * (a * ((x * y) - (z * t)))
	tmp = 0
	if t <= -2.05e+86:
		tmp = j * (t * ((b * y4) - (i * y5)))
	elif t <= 6e-150:
		tmp = b * (y0 * ((z * k) - (x * j)))
	elif t <= 2e-58:
		tmp = z * (c * (y0 * -y3))
	elif t <= 3.5e+36:
		tmp = t_2
	elif t <= 2.55e+104:
		tmp = t_1
	elif t <= 4.6e+111:
		tmp = t_2
	elif t <= 6.2e+216:
		tmp = (j * -y5) * (t * i)
	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(b * Float64(t * Float64(Float64(j * y4) - Float64(z * a))))
	t_2 = Float64(b * Float64(a * Float64(Float64(x * y) - Float64(z * t))))
	tmp = 0.0
	if (t <= -2.05e+86)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))));
	elseif (t <= 6e-150)
		tmp = Float64(b * Float64(y0 * Float64(Float64(z * k) - Float64(x * j))));
	elseif (t <= 2e-58)
		tmp = Float64(z * Float64(c * Float64(y0 * Float64(-y3))));
	elseif (t <= 3.5e+36)
		tmp = t_2;
	elseif (t <= 2.55e+104)
		tmp = t_1;
	elseif (t <= 4.6e+111)
		tmp = t_2;
	elseif (t <= 6.2e+216)
		tmp = Float64(Float64(j * Float64(-y5)) * Float64(t * i));
	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 = b * (t * ((j * y4) - (z * a)));
	t_2 = b * (a * ((x * y) - (z * t)));
	tmp = 0.0;
	if (t <= -2.05e+86)
		tmp = j * (t * ((b * y4) - (i * y5)));
	elseif (t <= 6e-150)
		tmp = b * (y0 * ((z * k) - (x * j)));
	elseif (t <= 2e-58)
		tmp = z * (c * (y0 * -y3));
	elseif (t <= 3.5e+36)
		tmp = t_2;
	elseif (t <= 2.55e+104)
		tmp = t_1;
	elseif (t <= 4.6e+111)
		tmp = t_2;
	elseif (t <= 6.2e+216)
		tmp = (j * -y5) * (t * i);
	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[(b * N[(t * N[(N[(j * y4), $MachinePrecision] - N[(z * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(b * N[(a * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -2.05e+86], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 6e-150], N[(b * N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 2e-58], N[(z * N[(c * N[(y0 * (-y3)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 3.5e+36], t$95$2, If[LessEqual[t, 2.55e+104], t$95$1, If[LessEqual[t, 4.6e+111], t$95$2, If[LessEqual[t, 6.2e+216], N[(N[(j * (-y5)), $MachinePrecision] * N[(t * i), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]]]]

Derivation

1. Split input into 6 regimes

2. if t < -2.05e86

   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. Taylor expanded in j around inf 38.0%

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

   3. Taylor expanded in t around inf 49.7%

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

   if -2.05e86 < t < 6.0000000000000003e-150

   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. Taylor expanded in b around inf 38.7%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in y0 around inf 40.9%

      \[\leadsto b \cdot \color{blue}{\left(y0 \cdot \left(k \cdot z - j \cdot x\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 40.9%

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

   5. Simplified 40.9%

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

   if 6.0000000000000003e-150 < t < 2.0000000000000001e-58

   1. Initial program 54.4%

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

   2. Taylor expanded in z around -inf 54.6%

      \[\leadsto \color{blue}{-1 \cdot \left(z \cdot \left(\left(t \cdot \left(a \cdot b - c \cdot i\right) + y3 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   3. Taylor expanded in y0 around inf 33.2%

      \[\leadsto -1 \cdot \color{blue}{\left(y0 \cdot \left(z \cdot \left(c \cdot y3 - b \cdot k\right)\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 33.2%

         \[\leadsto -1 \cdot \color{blue}{\left(\left(y0 \cdot z\right) \cdot \left(c \cdot y3 - b \cdot k\right)\right)} \]

      2. *-commutative 33.2%

         \[\leadsto -1 \cdot \left(\color{blue}{\left(z \cdot y0\right)} \cdot \left(c \cdot y3 - b \cdot k\right)\right) \]

      3. *-commutative 33.2%

         \[\leadsto -1 \cdot \left(\left(z \cdot y0\right) \cdot \left(\color{blue}{y3 \cdot c} - b \cdot k\right)\right) \]

      4. *-commutative 33.2%

         \[\leadsto -1 \cdot \left(\left(z \cdot y0\right) \cdot \left(y3 \cdot c - \color{blue}{k \cdot b}\right)\right) \]

   5. Simplified 33.2%

      \[\leadsto -1 \cdot \color{blue}{\left(\left(z \cdot y0\right) \cdot \left(y3 \cdot c - k \cdot b\right)\right)} \]

   6. Taylor expanded in y3 around inf 47.5%

      \[\leadsto -1 \cdot \color{blue}{\left(c \cdot \left(y0 \cdot \left(y3 \cdot z\right)\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 62.2%

         \[\leadsto -1 \cdot \left(c \cdot \color{blue}{\left(\left(y0 \cdot y3\right) \cdot z\right)}\right) \]

      2. associate-*r* 62.2%

         \[\leadsto -1 \cdot \color{blue}{\left(\left(c \cdot \left(y0 \cdot y3\right)\right) \cdot z\right)} \]

   8. Simplified 62.2%

      \[\leadsto -1 \cdot \color{blue}{\left(\left(c \cdot \left(y0 \cdot y3\right)\right) \cdot z\right)} \]

   if 2.0000000000000001e-58 < t < 3.4999999999999998e36 or 2.5500000000000001e104 < t < 4.60000000000000004e111

   1. Initial program 30.8%

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

   2. Taylor expanded in b around inf 52.6%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 53.0%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 53.0%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 53.0%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 53.0%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 53.0%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 53.0%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   if 3.4999999999999998e36 < t < 2.5500000000000001e104 or 6.20000000000000007e216 < t

   1. Initial program 26.5%

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

   2. Taylor expanded in b around inf 33.5%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in t around inf 61.5%

      \[\leadsto b \cdot \color{blue}{\left(t \cdot \left(-1 \cdot \left(a \cdot z\right) + j \cdot y4\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 61.5%

         \[\leadsto b \cdot \left(t \cdot \color{blue}{\left(j \cdot y4 + -1 \cdot \left(a \cdot z\right)\right)}\right) \]

      2. mul-1-neg 61.5%

         \[\leadsto b \cdot \left(t \cdot \left(j \cdot y4 + \color{blue}{\left(-a \cdot z\right)}\right)\right) \]

      3. unsub-neg 61.5%

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

      4. *-commutative 61.5%

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

      5. *-commutative 61.5%

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

   5. Simplified 61.5%

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

   if 4.60000000000000004e111 < t < 6.20000000000000007e216

   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. Taylor expanded in j around inf 45.2%

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

   3. Taylor expanded in y5 around -inf 46.4%

      \[\leadsto \color{blue}{-1 \cdot \left(j \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)\right)\right)} \]
   4. Step-by-step derivation

      1. mul-1-neg 46.4%

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

      2. associate-*r* 46.4%

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

      3. distribute-lft-neg-in 46.4%

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

      4. distribute-rgt-neg-in 46.4%

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

      5. +-commutative 46.4%

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

      6. mul-1-neg 46.4%

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

      7. unsub-neg 46.4%

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

      8. *-commutative 46.4%

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

   5. Simplified 46.4%

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

   6. Taylor expanded in i around inf 46.5%

      \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \color{blue}{\left(i \cdot t\right)} \]
   7. Step-by-step derivation

      1. *-commutative 46.5%

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

   8. Simplified 46.5%

      \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \color{blue}{\left(t \cdot i\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 48.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -2.05 \cdot 10^{+86}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq 6 \cdot 10^{-150}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;t \leq 2 \cdot 10^{-58}:\\ \;\;\;\;z \cdot \left(c \cdot \left(y0 \cdot \left(-y3\right)\right)\right)\\ \mathbf{elif}\;t \leq 3.5 \cdot 10^{+36}:\\ \;\;\;\;b \cdot \left(a \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;t \leq 2.55 \cdot 10^{+104}:\\ \;\;\;\;b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ \mathbf{elif}\;t \leq 4.6 \cdot 10^{+111}:\\ \;\;\;\;b \cdot \left(a \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;t \leq 6.2 \cdot 10^{+216}:\\ \;\;\;\;\left(j \cdot \left(-y5\right)\right) \cdot \left(t \cdot i\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ \end{array} \]

Alternative 22: 26.4% accurate, 4.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(a \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{if}\;j \leq -8 \cdot 10^{+165}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(x \cdot \left(-j\right)\right)\right)\\ \mathbf{elif}\;j \leq -1.95 \cdot 10^{+60}:\\ \;\;\;\;\left(j \cdot \left(-y5\right)\right) \cdot \left(t \cdot i\right)\\ \mathbf{elif}\;j \leq -8.4 \cdot 10^{-42}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;j \leq -1.3 \cdot 10^{-82}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{elif}\;j \leq 4 \cdot 10^{-163}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;j \leq 6.8 \cdot 10^{+64}:\\ \;\;\;\;z \cdot \left(c \cdot \left(y0 \cdot \left(-y3\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* a (- (* x y) (* z t))))))
   (if (<= j -8e+165)
     (* b (* y0 (* x (- j))))
     (if (<= j -1.95e+60)
       (* (* j (- y5)) (* t i))
       (if (<= j -8.4e-42)
         t_1
         (if (<= j -1.3e-82)
           (* b (* k (* z y0)))
           (if (<= j 4e-163)
             t_1
             (if (<= j 6.8e+64)
               (* z (* c (* y0 (- y3))))
               (* b (* t (- (* j y4) (* z a))))))))))))

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 * (a * ((x * y) - (z * t)));
	double tmp;
	if (j <= -8e+165) {
		tmp = b * (y0 * (x * -j));
	} else if (j <= -1.95e+60) {
		tmp = (j * -y5) * (t * i);
	} else if (j <= -8.4e-42) {
		tmp = t_1;
	} else if (j <= -1.3e-82) {
		tmp = b * (k * (z * y0));
	} else if (j <= 4e-163) {
		tmp = t_1;
	} else if (j <= 6.8e+64) {
		tmp = z * (c * (y0 * -y3));
	} else {
		tmp = b * (t * ((j * y4) - (z * a)));
	}
	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 * (a * ((x * y) - (z * t)))
    if (j <= (-8d+165)) then
        tmp = b * (y0 * (x * -j))
    else if (j <= (-1.95d+60)) then
        tmp = (j * -y5) * (t * i)
    else if (j <= (-8.4d-42)) then
        tmp = t_1
    else if (j <= (-1.3d-82)) then
        tmp = b * (k * (z * y0))
    else if (j <= 4d-163) then
        tmp = t_1
    else if (j <= 6.8d+64) then
        tmp = z * (c * (y0 * -y3))
    else
        tmp = b * (t * ((j * y4) - (z * a)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (a * ((x * y) - (z * t)));
	double tmp;
	if (j <= -8e+165) {
		tmp = b * (y0 * (x * -j));
	} else if (j <= -1.95e+60) {
		tmp = (j * -y5) * (t * i);
	} else if (j <= -8.4e-42) {
		tmp = t_1;
	} else if (j <= -1.3e-82) {
		tmp = b * (k * (z * y0));
	} else if (j <= 4e-163) {
		tmp = t_1;
	} else if (j <= 6.8e+64) {
		tmp = z * (c * (y0 * -y3));
	} else {
		tmp = b * (t * ((j * y4) - (z * a)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = b * (a * ((x * y) - (z * t)))
	tmp = 0
	if j <= -8e+165:
		tmp = b * (y0 * (x * -j))
	elif j <= -1.95e+60:
		tmp = (j * -y5) * (t * i)
	elif j <= -8.4e-42:
		tmp = t_1
	elif j <= -1.3e-82:
		tmp = b * (k * (z * y0))
	elif j <= 4e-163:
		tmp = t_1
	elif j <= 6.8e+64:
		tmp = z * (c * (y0 * -y3))
	else:
		tmp = b * (t * ((j * y4) - (z * a)))
	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(a * Float64(Float64(x * y) - Float64(z * t))))
	tmp = 0.0
	if (j <= -8e+165)
		tmp = Float64(b * Float64(y0 * Float64(x * Float64(-j))));
	elseif (j <= -1.95e+60)
		tmp = Float64(Float64(j * Float64(-y5)) * Float64(t * i));
	elseif (j <= -8.4e-42)
		tmp = t_1;
	elseif (j <= -1.3e-82)
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	elseif (j <= 4e-163)
		tmp = t_1;
	elseif (j <= 6.8e+64)
		tmp = Float64(z * Float64(c * Float64(y0 * Float64(-y3))));
	else
		tmp = Float64(b * Float64(t * Float64(Float64(j * y4) - Float64(z * a))));
	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 * (a * ((x * y) - (z * t)));
	tmp = 0.0;
	if (j <= -8e+165)
		tmp = b * (y0 * (x * -j));
	elseif (j <= -1.95e+60)
		tmp = (j * -y5) * (t * i);
	elseif (j <= -8.4e-42)
		tmp = t_1;
	elseif (j <= -1.3e-82)
		tmp = b * (k * (z * y0));
	elseif (j <= 4e-163)
		tmp = t_1;
	elseif (j <= 6.8e+64)
		tmp = z * (c * (y0 * -y3));
	else
		tmp = b * (t * ((j * y4) - (z * a)));
	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[(a * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -8e+165], N[(b * N[(y0 * N[(x * (-j)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -1.95e+60], N[(N[(j * (-y5)), $MachinePrecision] * N[(t * i), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -8.4e-42], t$95$1, If[LessEqual[j, -1.3e-82], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 4e-163], t$95$1, If[LessEqual[j, 6.8e+64], N[(z * N[(c * N[(y0 * (-y3)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(t * N[(N[(j * y4), $MachinePrecision] - N[(z * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]

Derivation

1. Split input into 6 regimes

2. if j < -7.9999999999999992e165

   1. Initial program 26.1%

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

   2. Taylor expanded in j around inf 56.5%

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

   3. Taylor expanded in x around inf 49.0%

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

      1. *-commutative 49.0%

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

      2. *-commutative 49.0%

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

      3. *-commutative 49.0%

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

   5. Simplified 49.0%

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

   6. Taylor expanded in y1 around 0 53.1%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(j \cdot \left(x \cdot y0\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 53.1%

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

      2. distribute-rgt-neg-in 53.1%

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

      3. associate-*r* 61.5%

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

      4. *-commutative 61.5%

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

   8. Simplified 61.5%

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

   if -7.9999999999999992e165 < j < -1.95000000000000015e60

   1. Initial program 27.8%

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

   2. Taylor expanded in j around inf 33.4%

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

   3. Taylor expanded in y5 around -inf 50.6%

      \[\leadsto \color{blue}{-1 \cdot \left(j \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)\right)\right)} \]
   4. Step-by-step derivation

      1. mul-1-neg 50.6%

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

      2. associate-*r* 50.6%

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

      3. distribute-lft-neg-in 50.6%

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

      4. distribute-rgt-neg-in 50.6%

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

      5. +-commutative 50.6%

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

      6. mul-1-neg 50.6%

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

      7. unsub-neg 50.6%

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

      8. *-commutative 50.6%

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

   5. Simplified 50.6%

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

   6. Taylor expanded in i around inf 50.8%

      \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \color{blue}{\left(i \cdot t\right)} \]
   7. Step-by-step derivation

      1. *-commutative 50.8%

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

   8. Simplified 50.8%

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

   if -1.95000000000000015e60 < j < -8.40000000000000025e-42 or -1.3e-82 < j < 3.99999999999999969e-163

   1. Initial program 38.6%

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

   2. Taylor expanded in b around inf 39.3%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 45.4%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 45.4%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 45.4%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 45.4%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 45.4%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 45.4%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   if -8.40000000000000025e-42 < j < -1.3e-82

   1. Initial program 46.7%

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

   2. Taylor expanded in z around -inf 39.3%

      \[\leadsto \color{blue}{-1 \cdot \left(z \cdot \left(\left(t \cdot \left(a \cdot b - c \cdot i\right) + y3 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   3. Taylor expanded in y0 around inf 24.9%

      \[\leadsto -1 \cdot \color{blue}{\left(y0 \cdot \left(z \cdot \left(c \cdot y3 - b \cdot k\right)\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 25.0%

         \[\leadsto -1 \cdot \color{blue}{\left(\left(y0 \cdot z\right) \cdot \left(c \cdot y3 - b \cdot k\right)\right)} \]

      2. *-commutative 25.0%

         \[\leadsto -1 \cdot \left(\color{blue}{\left(z \cdot y0\right)} \cdot \left(c \cdot y3 - b \cdot k\right)\right) \]

      3. *-commutative 25.0%

         \[\leadsto -1 \cdot \left(\left(z \cdot y0\right) \cdot \left(\color{blue}{y3 \cdot c} - b \cdot k\right)\right) \]

      4. *-commutative 25.0%

         \[\leadsto -1 \cdot \left(\left(z \cdot y0\right) \cdot \left(y3 \cdot c - \color{blue}{k \cdot b}\right)\right) \]

   5. Simplified 25.0%

      \[\leadsto -1 \cdot \color{blue}{\left(\left(z \cdot y0\right) \cdot \left(y3 \cdot c - k \cdot b\right)\right)} \]

   6. Taylor expanded in y3 around 0 47.6%

      \[\leadsto -1 \cdot \color{blue}{\left(-1 \cdot \left(b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 47.6%

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

      2. neg-mul-1 47.6%

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

   8. Simplified 47.6%

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

   if 3.99999999999999969e-163 < j < 6.8000000000000003e64

   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. Taylor expanded in z around -inf 43.5%

      \[\leadsto \color{blue}{-1 \cdot \left(z \cdot \left(\left(t \cdot \left(a \cdot b - c \cdot i\right) + y3 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   3. Taylor expanded in y0 around inf 26.9%

      \[\leadsto -1 \cdot \color{blue}{\left(y0 \cdot \left(z \cdot \left(c \cdot y3 - b \cdot k\right)\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 26.7%

         \[\leadsto -1 \cdot \color{blue}{\left(\left(y0 \cdot z\right) \cdot \left(c \cdot y3 - b \cdot k\right)\right)} \]

      2. *-commutative 26.7%

         \[\leadsto -1 \cdot \left(\color{blue}{\left(z \cdot y0\right)} \cdot \left(c \cdot y3 - b \cdot k\right)\right) \]

      3. *-commutative 26.7%

         \[\leadsto -1 \cdot \left(\left(z \cdot y0\right) \cdot \left(\color{blue}{y3 \cdot c} - b \cdot k\right)\right) \]

      4. *-commutative 26.7%

         \[\leadsto -1 \cdot \left(\left(z \cdot y0\right) \cdot \left(y3 \cdot c - \color{blue}{k \cdot b}\right)\right) \]

   5. Simplified 26.7%

      \[\leadsto -1 \cdot \color{blue}{\left(\left(z \cdot y0\right) \cdot \left(y3 \cdot c - k \cdot b\right)\right)} \]

   6. Taylor expanded in y3 around inf 26.5%

      \[\leadsto -1 \cdot \color{blue}{\left(c \cdot \left(y0 \cdot \left(y3 \cdot z\right)\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 26.4%

         \[\leadsto -1 \cdot \left(c \cdot \color{blue}{\left(\left(y0 \cdot y3\right) \cdot z\right)}\right) \]

      2. associate-*r* 28.6%

         \[\leadsto -1 \cdot \color{blue}{\left(\left(c \cdot \left(y0 \cdot y3\right)\right) \cdot z\right)} \]

   8. Simplified 28.6%

      \[\leadsto -1 \cdot \color{blue}{\left(\left(c \cdot \left(y0 \cdot y3\right)\right) \cdot z\right)} \]

   if 6.8000000000000003e64 < j

   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. Taylor expanded in b around inf 44.2%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in t around inf 44.7%

      \[\leadsto b \cdot \color{blue}{\left(t \cdot \left(-1 \cdot \left(a \cdot z\right) + j \cdot y4\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 44.7%

         \[\leadsto b \cdot \left(t \cdot \color{blue}{\left(j \cdot y4 + -1 \cdot \left(a \cdot z\right)\right)}\right) \]

      2. mul-1-neg 44.7%

         \[\leadsto b \cdot \left(t \cdot \left(j \cdot y4 + \color{blue}{\left(-a \cdot z\right)}\right)\right) \]

      3. unsub-neg 44.7%

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

      4. *-commutative 44.7%

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

      5. *-commutative 44.7%

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

   5. Simplified 44.7%

      \[\leadsto b \cdot \color{blue}{\left(t \cdot \left(y4 \cdot j - z \cdot a\right)\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 44.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;j \leq -8 \cdot 10^{+165}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(x \cdot \left(-j\right)\right)\right)\\ \mathbf{elif}\;j \leq -1.95 \cdot 10^{+60}:\\ \;\;\;\;\left(j \cdot \left(-y5\right)\right) \cdot \left(t \cdot i\right)\\ \mathbf{elif}\;j \leq -8.4 \cdot 10^{-42}:\\ \;\;\;\;b \cdot \left(a \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;j \leq -1.3 \cdot 10^{-82}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{elif}\;j \leq 4 \cdot 10^{-163}:\\ \;\;\;\;b \cdot \left(a \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;j \leq 6.8 \cdot 10^{+64}:\\ \;\;\;\;z \cdot \left(c \cdot \left(y0 \cdot \left(-y3\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(t \cdot \left(j \cdot y4 - z \cdot a\right)\right)\\ \end{array} \]

Alternative 23: 21.3% accurate, 4.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y3 \leq -7.2 \cdot 10^{+89}:\\ \;\;\;\;c \cdot \left(y0 \cdot \left(y3 \cdot \left(-z\right)\right)\right)\\ \mathbf{elif}\;y3 \leq -14000000:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{elif}\;y3 \leq -1.4 \cdot 10^{-185}:\\ \;\;\;\;\left(j \cdot \left(-y5\right)\right) \cdot \left(t \cdot i\right)\\ \mathbf{elif}\;y3 \leq -6.8 \cdot 10^{-238}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a\right)\right)\\ \mathbf{elif}\;y3 \leq 3.3 \cdot 10^{-218}:\\ \;\;\;\;i \cdot \left(k \cdot \left(z \cdot \left(-y1\right)\right)\right)\\ \mathbf{elif}\;y3 \leq 9 \cdot 10^{-89}:\\ \;\;\;\;a \cdot \left(\left(z \cdot t\right) \cdot \left(-b\right)\right)\\ \mathbf{elif}\;y3 \leq 1.46 \cdot 10^{+193}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(x \cdot \left(-j\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(y3 \cdot \left(-y4\right)\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= y3 -7.2e+89)
   (* c (* y0 (* y3 (- z))))
   (if (<= y3 -14000000.0)
     (* a (* (* x y) b))
     (if (<= y3 -1.4e-185)
       (* (* j (- y5)) (* t i))
       (if (<= y3 -6.8e-238)
         (* b (* x (* y a)))
         (if (<= y3 3.3e-218)
           (* i (* k (* z (- y1))))
           (if (<= y3 9e-89)
             (* a (* (* z t) (- b)))
             (if (<= y3 1.46e+193)
               (* b (* y0 (* x (- j))))
               (* j (* y1 (* y3 (- y4))))))))))))

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 (y3 <= -7.2e+89) {
		tmp = c * (y0 * (y3 * -z));
	} else if (y3 <= -14000000.0) {
		tmp = a * ((x * y) * b);
	} else if (y3 <= -1.4e-185) {
		tmp = (j * -y5) * (t * i);
	} else if (y3 <= -6.8e-238) {
		tmp = b * (x * (y * a));
	} else if (y3 <= 3.3e-218) {
		tmp = i * (k * (z * -y1));
	} else if (y3 <= 9e-89) {
		tmp = a * ((z * t) * -b);
	} else if (y3 <= 1.46e+193) {
		tmp = b * (y0 * (x * -j));
	} else {
		tmp = j * (y1 * (y3 * -y4));
	}
	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 (y3 <= (-7.2d+89)) then
        tmp = c * (y0 * (y3 * -z))
    else if (y3 <= (-14000000.0d0)) then
        tmp = a * ((x * y) * b)
    else if (y3 <= (-1.4d-185)) then
        tmp = (j * -y5) * (t * i)
    else if (y3 <= (-6.8d-238)) then
        tmp = b * (x * (y * a))
    else if (y3 <= 3.3d-218) then
        tmp = i * (k * (z * -y1))
    else if (y3 <= 9d-89) then
        tmp = a * ((z * t) * -b)
    else if (y3 <= 1.46d+193) then
        tmp = b * (y0 * (x * -j))
    else
        tmp = j * (y1 * (y3 * -y4))
    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 (y3 <= -7.2e+89) {
		tmp = c * (y0 * (y3 * -z));
	} else if (y3 <= -14000000.0) {
		tmp = a * ((x * y) * b);
	} else if (y3 <= -1.4e-185) {
		tmp = (j * -y5) * (t * i);
	} else if (y3 <= -6.8e-238) {
		tmp = b * (x * (y * a));
	} else if (y3 <= 3.3e-218) {
		tmp = i * (k * (z * -y1));
	} else if (y3 <= 9e-89) {
		tmp = a * ((z * t) * -b);
	} else if (y3 <= 1.46e+193) {
		tmp = b * (y0 * (x * -j));
	} else {
		tmp = j * (y1 * (y3 * -y4));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if y3 <= -7.2e+89:
		tmp = c * (y0 * (y3 * -z))
	elif y3 <= -14000000.0:
		tmp = a * ((x * y) * b)
	elif y3 <= -1.4e-185:
		tmp = (j * -y5) * (t * i)
	elif y3 <= -6.8e-238:
		tmp = b * (x * (y * a))
	elif y3 <= 3.3e-218:
		tmp = i * (k * (z * -y1))
	elif y3 <= 9e-89:
		tmp = a * ((z * t) * -b)
	elif y3 <= 1.46e+193:
		tmp = b * (y0 * (x * -j))
	else:
		tmp = j * (y1 * (y3 * -y4))
	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 (y3 <= -7.2e+89)
		tmp = Float64(c * Float64(y0 * Float64(y3 * Float64(-z))));
	elseif (y3 <= -14000000.0)
		tmp = Float64(a * Float64(Float64(x * y) * b));
	elseif (y3 <= -1.4e-185)
		tmp = Float64(Float64(j * Float64(-y5)) * Float64(t * i));
	elseif (y3 <= -6.8e-238)
		tmp = Float64(b * Float64(x * Float64(y * a)));
	elseif (y3 <= 3.3e-218)
		tmp = Float64(i * Float64(k * Float64(z * Float64(-y1))));
	elseif (y3 <= 9e-89)
		tmp = Float64(a * Float64(Float64(z * t) * Float64(-b)));
	elseif (y3 <= 1.46e+193)
		tmp = Float64(b * Float64(y0 * Float64(x * Float64(-j))));
	else
		tmp = Float64(j * Float64(y1 * Float64(y3 * Float64(-y4))));
	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 (y3 <= -7.2e+89)
		tmp = c * (y0 * (y3 * -z));
	elseif (y3 <= -14000000.0)
		tmp = a * ((x * y) * b);
	elseif (y3 <= -1.4e-185)
		tmp = (j * -y5) * (t * i);
	elseif (y3 <= -6.8e-238)
		tmp = b * (x * (y * a));
	elseif (y3 <= 3.3e-218)
		tmp = i * (k * (z * -y1));
	elseif (y3 <= 9e-89)
		tmp = a * ((z * t) * -b);
	elseif (y3 <= 1.46e+193)
		tmp = b * (y0 * (x * -j));
	else
		tmp = j * (y1 * (y3 * -y4));
	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[y3, -7.2e+89], N[(c * N[(y0 * N[(y3 * (-z)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, -14000000.0], N[(a * N[(N[(x * y), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, -1.4e-185], N[(N[(j * (-y5)), $MachinePrecision] * N[(t * i), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, -6.8e-238], N[(b * N[(x * N[(y * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, 3.3e-218], N[(i * N[(k * N[(z * (-y1)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, 9e-89], N[(a * N[(N[(z * t), $MachinePrecision] * (-b)), $MachinePrecision]), $MachinePrecision], If[LessEqual[y3, 1.46e+193], N[(b * N[(y0 * N[(x * (-j)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(j * N[(y1 * N[(y3 * (-y4)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]

Derivation

1. Split input into 8 regimes

2. if y3 < -7.2e89

   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. Taylor expanded in z around -inf 50.3%

      \[\leadsto \color{blue}{-1 \cdot \left(z \cdot \left(\left(t \cdot \left(a \cdot b - c \cdot i\right) + y3 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   3. Taylor expanded in y0 around inf 45.1%

      \[\leadsto -1 \cdot \color{blue}{\left(y0 \cdot \left(z \cdot \left(c \cdot y3 - b \cdot k\right)\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 44.9%

         \[\leadsto -1 \cdot \color{blue}{\left(\left(y0 \cdot z\right) \cdot \left(c \cdot y3 - b \cdot k\right)\right)} \]

      2. *-commutative 44.9%

         \[\leadsto -1 \cdot \left(\color{blue}{\left(z \cdot y0\right)} \cdot \left(c \cdot y3 - b \cdot k\right)\right) \]

      3. *-commutative 44.9%

         \[\leadsto -1 \cdot \left(\left(z \cdot y0\right) \cdot \left(\color{blue}{y3 \cdot c} - b \cdot k\right)\right) \]

      4. *-commutative 44.9%

         \[\leadsto -1 \cdot \left(\left(z \cdot y0\right) \cdot \left(y3 \cdot c - \color{blue}{k \cdot b}\right)\right) \]

   5. Simplified 44.9%

      \[\leadsto -1 \cdot \color{blue}{\left(\left(z \cdot y0\right) \cdot \left(y3 \cdot c - k \cdot b\right)\right)} \]

   6. Taylor expanded in y3 around inf 48.5%

      \[\leadsto -1 \cdot \color{blue}{\left(c \cdot \left(y0 \cdot \left(y3 \cdot z\right)\right)\right)} \]

   if -7.2e89 < y3 < -1.4e7

   1. Initial program 35.7%

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

   2. Taylor expanded in b around inf 57.5%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 65.2%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 65.2%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 65.2%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 65.2%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 65.2%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 65.2%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   6. Taylor expanded in y around inf 58.2%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]

   if -1.4e7 < y3 < -1.39999999999999996e-185

   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. Taylor expanded in j around inf 46.5%

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

   3. Taylor expanded in y5 around -inf 27.2%

      \[\leadsto \color{blue}{-1 \cdot \left(j \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)\right)\right)} \]
   4. Step-by-step derivation

      1. mul-1-neg 27.2%

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

      2. associate-*r* 27.2%

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

      3. distribute-lft-neg-in 27.2%

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

      4. distribute-rgt-neg-in 27.2%

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

      5. +-commutative 27.2%

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

      6. mul-1-neg 27.2%

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

      7. unsub-neg 27.2%

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

      8. *-commutative 27.2%

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

   5. Simplified 27.2%

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

   6. Taylor expanded in i around inf 27.3%

      \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \color{blue}{\left(i \cdot t\right)} \]
   7. Step-by-step derivation

      1. *-commutative 27.3%

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

   8. Simplified 27.3%

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

   if -1.39999999999999996e-185 < y3 < -6.79999999999999966e-238

   1. Initial program 20.6%

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

   2. Taylor expanded in b around inf 60.6%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 60.7%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 60.7%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 60.7%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 60.7%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 60.7%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 60.7%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   6. Taylor expanded in y around inf 41.4%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 41.4%

         \[\leadsto \color{blue}{\left(b \cdot \left(x \cdot y\right)\right) \cdot a} \]

      2. associate-*l* 50.6%

         \[\leadsto \color{blue}{b \cdot \left(\left(x \cdot y\right) \cdot a\right)} \]

      3. associate-*l* 50.7%

         \[\leadsto b \cdot \color{blue}{\left(x \cdot \left(y \cdot a\right)\right)} \]

   8. Simplified 50.7%

      \[\leadsto \color{blue}{b \cdot \left(x \cdot \left(y \cdot a\right)\right)} \]

   if -6.79999999999999966e-238 < y3 < 3.30000000000000023e-218

   1. Initial program 30.9%

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

   2. Taylor expanded in k around inf 31.0%

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

   3. Taylor expanded in y1 around inf 34.5%

      \[\leadsto \color{blue}{k \cdot \left(y1 \cdot \left(y2 \cdot y4 - i \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 31.7%

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

      2. *-commutative 31.7%

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

      3. *-commutative 31.7%

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

      4. *-commutative 31.7%

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

   5. Simplified 31.7%

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

   6. Taylor expanded in y4 around 0 29.5%

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

      1. mul-1-neg 29.5%

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

      2. *-commutative 29.5%

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

      3. distribute-rgt-neg-in 29.5%

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

      4. *-commutative 29.5%

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

   8. Simplified 29.5%

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

   if 3.30000000000000023e-218 < y3 < 8.9999999999999998e-89

   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. Taylor expanded in b around inf 59.6%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 49.4%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 49.4%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 49.4%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 49.4%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 49.4%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 49.4%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   6. Taylor expanded in y around 0 38.7%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(b \cdot \left(t \cdot z\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 38.7%

         \[\leadsto \color{blue}{-a \cdot \left(b \cdot \left(t \cdot z\right)\right)} \]

      2. *-commutative 38.7%

         \[\leadsto -\color{blue}{\left(b \cdot \left(t \cdot z\right)\right) \cdot a} \]

      3. distribute-rgt-neg-in 38.7%

         \[\leadsto \color{blue}{\left(b \cdot \left(t \cdot z\right)\right) \cdot \left(-a\right)} \]

      4. *-commutative 38.7%

         \[\leadsto \left(b \cdot \color{blue}{\left(z \cdot t\right)}\right) \cdot \left(-a\right) \]

   8. Simplified 38.7%

      \[\leadsto \color{blue}{\left(b \cdot \left(z \cdot t\right)\right) \cdot \left(-a\right)} \]

   if 8.9999999999999998e-89 < y3 < 1.4600000000000001e193

   1. Initial program 29.0%

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

   2. Taylor expanded in j around inf 35.9%

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

   3. Taylor expanded in x around inf 33.1%

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

      1. *-commutative 33.1%

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

      2. *-commutative 33.1%

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

      3. *-commutative 33.1%

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

   5. Simplified 33.1%

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

   6. Taylor expanded in y1 around 0 25.2%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(j \cdot \left(x \cdot y0\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 25.2%

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

      2. distribute-rgt-neg-in 25.2%

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

      3. associate-*r* 33.2%

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

      4. *-commutative 33.2%

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

   8. Simplified 33.2%

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

   if 1.4600000000000001e193 < y3

   1. Initial program 32.0%

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

   2. Taylor expanded in j around inf 44.7%

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

   3. Taylor expanded in y4 around inf 40.7%

      \[\leadsto \color{blue}{j \cdot \left(y4 \cdot \left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 40.7%

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

      2. +-commutative 40.7%

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

      3. mul-1-neg 40.7%

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

      4. unsub-neg 40.7%

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

      5. *-commutative 40.7%

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

   5. Simplified 40.7%

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

   6. Taylor expanded in b around 0 48.6%

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

      1. mul-1-neg 48.6%

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

      2. *-commutative 48.6%

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

      3. distribute-rgt-neg-in 48.6%

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

   8. Simplified 48.6%

      \[\leadsto j \cdot \color{blue}{\left(\left(y3 \cdot y4\right) \cdot \left(-y1\right)\right)} \]
3. Recombined 8 regimes into one program.

4. Final simplification 39.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y3 \leq -7.2 \cdot 10^{+89}:\\ \;\;\;\;c \cdot \left(y0 \cdot \left(y3 \cdot \left(-z\right)\right)\right)\\ \mathbf{elif}\;y3 \leq -14000000:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{elif}\;y3 \leq -1.4 \cdot 10^{-185}:\\ \;\;\;\;\left(j \cdot \left(-y5\right)\right) \cdot \left(t \cdot i\right)\\ \mathbf{elif}\;y3 \leq -6.8 \cdot 10^{-238}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a\right)\right)\\ \mathbf{elif}\;y3 \leq 3.3 \cdot 10^{-218}:\\ \;\;\;\;i \cdot \left(k \cdot \left(z \cdot \left(-y1\right)\right)\right)\\ \mathbf{elif}\;y3 \leq 9 \cdot 10^{-89}:\\ \;\;\;\;a \cdot \left(\left(z \cdot t\right) \cdot \left(-b\right)\right)\\ \mathbf{elif}\;y3 \leq 1.46 \cdot 10^{+193}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(x \cdot \left(-j\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(y3 \cdot \left(-y4\right)\right)\right)\\ \end{array} \]

Alternative 24: 21.4% accurate, 4.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(y0 \cdot \left(x \cdot \left(-j\right)\right)\right)\\ \mathbf{if}\;j \leq -1.1 \cdot 10^{+27}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;j \leq -2 \cdot 10^{-114}:\\ \;\;\;\;\left(y2 \cdot y4\right) \cdot \left(k \cdot y1\right)\\ \mathbf{elif}\;j \leq 1.9 \cdot 10^{-301}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a\right)\right)\\ \mathbf{elif}\;j \leq 2.06 \cdot 10^{-252}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq 4.8 \cdot 10^{-216}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{elif}\;j \leq 1.04 \cdot 10^{+73}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* y0 (* x (- j))))))
   (if (<= j -1.1e+27)
     t_1
     (if (<= j -2e-114)
       (* (* y2 y4) (* k y1))
       (if (<= j 1.9e-301)
         (* b (* x (* y a)))
         (if (<= j 2.06e-252)
           (* k (* y2 (* y1 y4)))
           (if (<= j 4.8e-216)
             (* a (* (* x y) b))
             (if (<= j 1.04e+73) (* j (* y0 (* y3 y5))) 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 = b * (y0 * (x * -j));
	double tmp;
	if (j <= -1.1e+27) {
		tmp = t_1;
	} else if (j <= -2e-114) {
		tmp = (y2 * y4) * (k * y1);
	} else if (j <= 1.9e-301) {
		tmp = b * (x * (y * a));
	} else if (j <= 2.06e-252) {
		tmp = k * (y2 * (y1 * y4));
	} else if (j <= 4.8e-216) {
		tmp = a * ((x * y) * b);
	} else if (j <= 1.04e+73) {
		tmp = j * (y0 * (y3 * y5));
	} 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 = b * (y0 * (x * -j))
    if (j <= (-1.1d+27)) then
        tmp = t_1
    else if (j <= (-2d-114)) then
        tmp = (y2 * y4) * (k * y1)
    else if (j <= 1.9d-301) then
        tmp = b * (x * (y * a))
    else if (j <= 2.06d-252) then
        tmp = k * (y2 * (y1 * y4))
    else if (j <= 4.8d-216) then
        tmp = a * ((x * y) * b)
    else if (j <= 1.04d+73) then
        tmp = j * (y0 * (y3 * y5))
    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 = b * (y0 * (x * -j));
	double tmp;
	if (j <= -1.1e+27) {
		tmp = t_1;
	} else if (j <= -2e-114) {
		tmp = (y2 * y4) * (k * y1);
	} else if (j <= 1.9e-301) {
		tmp = b * (x * (y * a));
	} else if (j <= 2.06e-252) {
		tmp = k * (y2 * (y1 * y4));
	} else if (j <= 4.8e-216) {
		tmp = a * ((x * y) * b);
	} else if (j <= 1.04e+73) {
		tmp = j * (y0 * (y3 * y5));
	} 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 = b * (y0 * (x * -j))
	tmp = 0
	if j <= -1.1e+27:
		tmp = t_1
	elif j <= -2e-114:
		tmp = (y2 * y4) * (k * y1)
	elif j <= 1.9e-301:
		tmp = b * (x * (y * a))
	elif j <= 2.06e-252:
		tmp = k * (y2 * (y1 * y4))
	elif j <= 4.8e-216:
		tmp = a * ((x * y) * b)
	elif j <= 1.04e+73:
		tmp = j * (y0 * (y3 * y5))
	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(b * Float64(y0 * Float64(x * Float64(-j))))
	tmp = 0.0
	if (j <= -1.1e+27)
		tmp = t_1;
	elseif (j <= -2e-114)
		tmp = Float64(Float64(y2 * y4) * Float64(k * y1));
	elseif (j <= 1.9e-301)
		tmp = Float64(b * Float64(x * Float64(y * a)));
	elseif (j <= 2.06e-252)
		tmp = Float64(k * Float64(y2 * Float64(y1 * y4)));
	elseif (j <= 4.8e-216)
		tmp = Float64(a * Float64(Float64(x * y) * b));
	elseif (j <= 1.04e+73)
		tmp = Float64(j * Float64(y0 * Float64(y3 * y5)));
	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 = b * (y0 * (x * -j));
	tmp = 0.0;
	if (j <= -1.1e+27)
		tmp = t_1;
	elseif (j <= -2e-114)
		tmp = (y2 * y4) * (k * y1);
	elseif (j <= 1.9e-301)
		tmp = b * (x * (y * a));
	elseif (j <= 2.06e-252)
		tmp = k * (y2 * (y1 * y4));
	elseif (j <= 4.8e-216)
		tmp = a * ((x * y) * b);
	elseif (j <= 1.04e+73)
		tmp = j * (y0 * (y3 * y5));
	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[(b * N[(y0 * N[(x * (-j)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -1.1e+27], t$95$1, If[LessEqual[j, -2e-114], N[(N[(y2 * y4), $MachinePrecision] * N[(k * y1), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 1.9e-301], N[(b * N[(x * N[(y * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 2.06e-252], N[(k * N[(y2 * N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 4.8e-216], N[(a * N[(N[(x * y), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 1.04e+73], N[(j * N[(y0 * N[(y3 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]]

Derivation

1. Split input into 6 regimes

2. if j < -1.0999999999999999e27 or 1.03999999999999993e73 < j

   1. Initial program 30.6%

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

   2. Taylor expanded in j around inf 51.1%

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

   3. Taylor expanded in x around inf 43.7%

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

      1. *-commutative 43.7%

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

      2. *-commutative 43.7%

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

      3. *-commutative 43.7%

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

   5. Simplified 43.7%

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

   6. Taylor expanded in y1 around 0 35.3%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(j \cdot \left(x \cdot y0\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 35.3%

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

      2. distribute-rgt-neg-in 35.3%

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

      3. associate-*r* 43.8%

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

      4. *-commutative 43.8%

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

   8. Simplified 43.8%

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

   if -1.0999999999999999e27 < j < -2.0000000000000001e-114

   1. Initial program 43.1%

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

   2. Taylor expanded in k around inf 45.3%

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

   3. Taylor expanded in y1 around inf 35.4%

      \[\leadsto \color{blue}{k \cdot \left(y1 \cdot \left(y2 \cdot y4 - i \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 38.7%

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

      2. *-commutative 38.7%

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

      3. *-commutative 38.7%

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

      4. *-commutative 38.7%

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

   5. Simplified 38.7%

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

   6. Taylor expanded in y4 around inf 35.3%

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

   if -2.0000000000000001e-114 < j < 1.89999999999999998e-301

   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. Taylor expanded in b around inf 41.7%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 46.4%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 46.4%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 46.4%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 46.4%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 46.4%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 46.4%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   6. Taylor expanded in y around inf 23.4%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 23.4%

         \[\leadsto \color{blue}{\left(b \cdot \left(x \cdot y\right)\right) \cdot a} \]

      2. associate-*l* 25.5%

         \[\leadsto \color{blue}{b \cdot \left(\left(x \cdot y\right) \cdot a\right)} \]

      3. associate-*l* 29.7%

         \[\leadsto b \cdot \color{blue}{\left(x \cdot \left(y \cdot a\right)\right)} \]

   8. Simplified 29.7%

      \[\leadsto \color{blue}{b \cdot \left(x \cdot \left(y \cdot a\right)\right)} \]

   if 1.89999999999999998e-301 < j < 2.06000000000000011e-252

   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. Taylor expanded in k around inf 50.0%

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

   3. Taylor expanded in y1 around inf 67.5%

      \[\leadsto \color{blue}{k \cdot \left(y1 \cdot \left(y2 \cdot y4 - i \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 67.2%

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

      2. *-commutative 67.2%

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

      3. *-commutative 67.2%

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

      4. *-commutative 67.2%

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

   5. Simplified 67.2%

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

   6. Taylor expanded in y4 around inf 67.5%

      \[\leadsto \color{blue}{k \cdot \left(y1 \cdot \left(y2 \cdot y4\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 67.5%

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

      2. associate-*l* 68.0%

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

   8. Simplified 68.0%

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

   if 2.06000000000000011e-252 < j < 4.80000000000000007e-216

   1. Initial program 39.8%

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

   2. Taylor expanded in b around inf 30.1%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 70.3%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 70.3%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 70.3%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 70.3%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 70.3%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 70.3%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   6. Taylor expanded in y around inf 60.5%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]

   if 4.80000000000000007e-216 < j < 1.03999999999999993e73

   1. Initial program 33.5%

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

   2. Taylor expanded in j around inf 26.5%

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

   3. Taylor expanded in y5 around -inf 23.7%

      \[\leadsto \color{blue}{-1 \cdot \left(j \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)\right)\right)} \]
   4. Step-by-step derivation

      1. mul-1-neg 23.7%

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

      2. associate-*r* 20.5%

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

      3. distribute-lft-neg-in 20.5%

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

      4. distribute-rgt-neg-in 20.5%

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

      5. +-commutative 20.5%

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

      6. mul-1-neg 20.5%

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

      7. unsub-neg 20.5%

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

      8. *-commutative 20.5%

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

   5. Simplified 20.5%

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

   6. Taylor expanded in i around 0 23.8%

      \[\leadsto \color{blue}{j \cdot \left(y0 \cdot \left(y3 \cdot y5\right)\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 37.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;j \leq -1.1 \cdot 10^{+27}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(x \cdot \left(-j\right)\right)\right)\\ \mathbf{elif}\;j \leq -2 \cdot 10^{-114}:\\ \;\;\;\;\left(y2 \cdot y4\right) \cdot \left(k \cdot y1\right)\\ \mathbf{elif}\;j \leq 1.9 \cdot 10^{-301}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a\right)\right)\\ \mathbf{elif}\;j \leq 2.06 \cdot 10^{-252}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq 4.8 \cdot 10^{-216}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{elif}\;j \leq 1.04 \cdot 10^{+73}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(x \cdot \left(-j\right)\right)\right)\\ \end{array} \]

Alternative 25: 21.9% accurate, 4.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \mathbf{if}\;y \leq -2.2 \cdot 10^{+32}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a\right)\right)\\ \mathbf{elif}\;y \leq -8.2 \cdot 10^{-181}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y \leq 10^{-170}:\\ \;\;\;\;b \cdot \left(a \cdot \left(z \cdot \left(-t\right)\right)\right)\\ \mathbf{elif}\;y \leq 4.1 \cdot 10^{-75}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y \leq 0.00015:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j\right)\right)\\ \mathbf{elif}\;y \leq 2.75 \cdot 10^{+125}:\\ \;\;\;\;j \cdot \left(x \cdot \left(b \cdot \left(-y0\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* j (* y1 (* x i)))))
   (if (<= y -2.2e+32)
     (* b (* x (* y a)))
     (if (<= y -8.2e-181)
       t_1
       (if (<= y 1e-170)
         (* b (* a (* z (- t))))
         (if (<= y 4.1e-75)
           t_1
           (if (<= y 0.00015)
             (* b (* y4 (* t j)))
             (if (<= y 2.75e+125)
               (* j (* x (* b (- y0))))
               (* a (* (* x y) b))))))))))

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 * (y1 * (x * i));
	double tmp;
	if (y <= -2.2e+32) {
		tmp = b * (x * (y * a));
	} else if (y <= -8.2e-181) {
		tmp = t_1;
	} else if (y <= 1e-170) {
		tmp = b * (a * (z * -t));
	} else if (y <= 4.1e-75) {
		tmp = t_1;
	} else if (y <= 0.00015) {
		tmp = b * (y4 * (t * j));
	} else if (y <= 2.75e+125) {
		tmp = j * (x * (b * -y0));
	} else {
		tmp = a * ((x * y) * b);
	}
	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 * (y1 * (x * i))
    if (y <= (-2.2d+32)) then
        tmp = b * (x * (y * a))
    else if (y <= (-8.2d-181)) then
        tmp = t_1
    else if (y <= 1d-170) then
        tmp = b * (a * (z * -t))
    else if (y <= 4.1d-75) then
        tmp = t_1
    else if (y <= 0.00015d0) then
        tmp = b * (y4 * (t * j))
    else if (y <= 2.75d+125) then
        tmp = j * (x * (b * -y0))
    else
        tmp = a * ((x * y) * b)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = j * (y1 * (x * i));
	double tmp;
	if (y <= -2.2e+32) {
		tmp = b * (x * (y * a));
	} else if (y <= -8.2e-181) {
		tmp = t_1;
	} else if (y <= 1e-170) {
		tmp = b * (a * (z * -t));
	} else if (y <= 4.1e-75) {
		tmp = t_1;
	} else if (y <= 0.00015) {
		tmp = b * (y4 * (t * j));
	} else if (y <= 2.75e+125) {
		tmp = j * (x * (b * -y0));
	} else {
		tmp = a * ((x * y) * b);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = j * (y1 * (x * i))
	tmp = 0
	if y <= -2.2e+32:
		tmp = b * (x * (y * a))
	elif y <= -8.2e-181:
		tmp = t_1
	elif y <= 1e-170:
		tmp = b * (a * (z * -t))
	elif y <= 4.1e-75:
		tmp = t_1
	elif y <= 0.00015:
		tmp = b * (y4 * (t * j))
	elif y <= 2.75e+125:
		tmp = j * (x * (b * -y0))
	else:
		tmp = a * ((x * y) * b)
	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(y1 * Float64(x * i)))
	tmp = 0.0
	if (y <= -2.2e+32)
		tmp = Float64(b * Float64(x * Float64(y * a)));
	elseif (y <= -8.2e-181)
		tmp = t_1;
	elseif (y <= 1e-170)
		tmp = Float64(b * Float64(a * Float64(z * Float64(-t))));
	elseif (y <= 4.1e-75)
		tmp = t_1;
	elseif (y <= 0.00015)
		tmp = Float64(b * Float64(y4 * Float64(t * j)));
	elseif (y <= 2.75e+125)
		tmp = Float64(j * Float64(x * Float64(b * Float64(-y0))));
	else
		tmp = Float64(a * Float64(Float64(x * y) * b));
	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 * (y1 * (x * i));
	tmp = 0.0;
	if (y <= -2.2e+32)
		tmp = b * (x * (y * a));
	elseif (y <= -8.2e-181)
		tmp = t_1;
	elseif (y <= 1e-170)
		tmp = b * (a * (z * -t));
	elseif (y <= 4.1e-75)
		tmp = t_1;
	elseif (y <= 0.00015)
		tmp = b * (y4 * (t * j));
	elseif (y <= 2.75e+125)
		tmp = j * (x * (b * -y0));
	else
		tmp = a * ((x * y) * b);
	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[(y1 * N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y, -2.2e+32], N[(b * N[(x * N[(y * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -8.2e-181], t$95$1, If[LessEqual[y, 1e-170], N[(b * N[(a * N[(z * (-t)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 4.1e-75], t$95$1, If[LessEqual[y, 0.00015], N[(b * N[(y4 * N[(t * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 2.75e+125], N[(j * N[(x * N[(b * (-y0)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(a * N[(N[(x * y), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision]]]]]]]]

Derivation

1. Split input into 6 regimes

2. if y < -2.20000000000000001e32

   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. Taylor expanded in b around inf 36.7%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 37.2%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 37.2%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 37.2%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 37.2%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 37.2%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 37.2%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   6. Taylor expanded in y around inf 27.3%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 27.3%

         \[\leadsto \color{blue}{\left(b \cdot \left(x \cdot y\right)\right) \cdot a} \]

      2. associate-*l* 28.9%

         \[\leadsto \color{blue}{b \cdot \left(\left(x \cdot y\right) \cdot a\right)} \]

      3. associate-*l* 38.8%

         \[\leadsto b \cdot \color{blue}{\left(x \cdot \left(y \cdot a\right)\right)} \]

   8. Simplified 38.8%

      \[\leadsto \color{blue}{b \cdot \left(x \cdot \left(y \cdot a\right)\right)} \]

   if -2.20000000000000001e32 < y < -8.2000000000000003e-181 or 9.99999999999999983e-171 < y < 4.10000000000000002e-75

   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. Taylor expanded in j around inf 49.3%

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

   3. Taylor expanded in x around inf 42.0%

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

      1. *-commutative 42.0%

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

      2. *-commutative 42.0%

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

      3. *-commutative 42.0%

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

   5. Simplified 42.0%

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

   6. Taylor expanded in y1 around inf 34.4%

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

      1. *-commutative 34.4%

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

      2. associate-*l* 32.9%

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

      3. *-commutative 32.9%

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

      4. associate-*l* 36.0%

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

   8. Simplified 36.0%

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

   if -8.2000000000000003e-181 < y < 9.99999999999999983e-171

   1. Initial program 45.0%

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

   2. Taylor expanded in b around inf 45.6%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 30.5%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 30.5%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 30.5%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 30.5%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 30.5%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 30.5%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   6. Taylor expanded in y around 0 28.8%

      \[\leadsto b \cdot \color{blue}{\left(-1 \cdot \left(a \cdot \left(t \cdot z\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 28.8%

         \[\leadsto b \cdot \color{blue}{\left(-a \cdot \left(t \cdot z\right)\right)} \]

      2. *-commutative 28.8%

         \[\leadsto b \cdot \left(-a \cdot \color{blue}{\left(z \cdot t\right)}\right) \]

      3. *-commutative 28.8%

         \[\leadsto b \cdot \left(-\color{blue}{\left(z \cdot t\right) \cdot a}\right) \]

      4. distribute-rgt-neg-in 28.8%

         \[\leadsto b \cdot \color{blue}{\left(\left(z \cdot t\right) \cdot \left(-a\right)\right)} \]

   8. Simplified 28.8%

      \[\leadsto b \cdot \color{blue}{\left(\left(z \cdot t\right) \cdot \left(-a\right)\right)} \]

   if 4.10000000000000002e-75 < y < 1.49999999999999987e-4

   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. Taylor expanded in j around inf 33.8%

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

   3. Taylor expanded in y4 around inf 47.3%

      \[\leadsto \color{blue}{j \cdot \left(y4 \cdot \left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 47.3%

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

      2. +-commutative 47.3%

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

      3. mul-1-neg 47.3%

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

      4. unsub-neg 47.3%

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

      5. *-commutative 47.3%

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

   5. Simplified 47.3%

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

   6. Taylor expanded in b around inf 34.0%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 34.0%

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

   8. Simplified 34.0%

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

   if 1.49999999999999987e-4 < y < 2.74999999999999998e125

   1. Initial program 24.3%

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

   2. Taylor expanded in j around inf 28.2%

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

   3. Taylor expanded in x around inf 37.1%

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

      1. *-commutative 37.1%

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

      2. *-commutative 37.1%

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

      3. *-commutative 37.1%

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

   5. Simplified 37.1%

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

   6. Taylor expanded in y1 around 0 33.4%

      \[\leadsto j \cdot \left(\color{blue}{\left(-1 \cdot \left(b \cdot y0\right)\right)} \cdot x\right) \]
   7. Step-by-step derivation

      1. mul-1-neg 33.4%

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

      2. *-commutative 33.4%

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

      3. distribute-rgt-neg-in 33.4%

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

   8. Simplified 33.4%

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

   if 2.74999999999999998e125 < y

   1. Initial program 24.7%

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

   2. Taylor expanded in b around inf 33.1%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 46.9%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 46.9%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 46.9%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 46.9%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 46.9%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 46.9%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   6. Taylor expanded in y around inf 44.2%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 35.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y \leq -2.2 \cdot 10^{+32}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a\right)\right)\\ \mathbf{elif}\;y \leq -8.2 \cdot 10^{-181}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \mathbf{elif}\;y \leq 10^{-170}:\\ \;\;\;\;b \cdot \left(a \cdot \left(z \cdot \left(-t\right)\right)\right)\\ \mathbf{elif}\;y \leq 4.1 \cdot 10^{-75}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \mathbf{elif}\;y \leq 0.00015:\\ \;\;\;\;b \cdot \left(y4 \cdot \left(t \cdot j\right)\right)\\ \mathbf{elif}\;y \leq 2.75 \cdot 10^{+125}:\\ \;\;\;\;j \cdot \left(x \cdot \left(b \cdot \left(-y0\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \end{array} \]

Alternative 26: 22.0% accurate, 4.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \mathbf{if}\;y \leq -2.2 \cdot 10^{+32}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a\right)\right)\\ \mathbf{elif}\;y \leq -8.2 \cdot 10^{-181}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y \leq 1.36 \cdot 10^{-170}:\\ \;\;\;\;b \cdot \left(a \cdot \left(z \cdot \left(-t\right)\right)\right)\\ \mathbf{elif}\;y \leq 3.2 \cdot 10^{-75}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y \leq 1.55 \cdot 10^{-11}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(y3 \cdot \left(-y4\right)\right)\right)\\ \mathbf{elif}\;y \leq 2.3 \cdot 10^{+125}:\\ \;\;\;\;j \cdot \left(x \cdot \left(b \cdot \left(-y0\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* j (* y1 (* x i)))))
   (if (<= y -2.2e+32)
     (* b (* x (* y a)))
     (if (<= y -8.2e-181)
       t_1
       (if (<= y 1.36e-170)
         (* b (* a (* z (- t))))
         (if (<= y 3.2e-75)
           t_1
           (if (<= y 1.55e-11)
             (* j (* y1 (* y3 (- y4))))
             (if (<= y 2.3e+125)
               (* j (* x (* b (- y0))))
               (* a (* (* x y) b))))))))))

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 * (y1 * (x * i));
	double tmp;
	if (y <= -2.2e+32) {
		tmp = b * (x * (y * a));
	} else if (y <= -8.2e-181) {
		tmp = t_1;
	} else if (y <= 1.36e-170) {
		tmp = b * (a * (z * -t));
	} else if (y <= 3.2e-75) {
		tmp = t_1;
	} else if (y <= 1.55e-11) {
		tmp = j * (y1 * (y3 * -y4));
	} else if (y <= 2.3e+125) {
		tmp = j * (x * (b * -y0));
	} else {
		tmp = a * ((x * y) * b);
	}
	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 * (y1 * (x * i))
    if (y <= (-2.2d+32)) then
        tmp = b * (x * (y * a))
    else if (y <= (-8.2d-181)) then
        tmp = t_1
    else if (y <= 1.36d-170) then
        tmp = b * (a * (z * -t))
    else if (y <= 3.2d-75) then
        tmp = t_1
    else if (y <= 1.55d-11) then
        tmp = j * (y1 * (y3 * -y4))
    else if (y <= 2.3d+125) then
        tmp = j * (x * (b * -y0))
    else
        tmp = a * ((x * y) * b)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = j * (y1 * (x * i));
	double tmp;
	if (y <= -2.2e+32) {
		tmp = b * (x * (y * a));
	} else if (y <= -8.2e-181) {
		tmp = t_1;
	} else if (y <= 1.36e-170) {
		tmp = b * (a * (z * -t));
	} else if (y <= 3.2e-75) {
		tmp = t_1;
	} else if (y <= 1.55e-11) {
		tmp = j * (y1 * (y3 * -y4));
	} else if (y <= 2.3e+125) {
		tmp = j * (x * (b * -y0));
	} else {
		tmp = a * ((x * y) * b);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = j * (y1 * (x * i))
	tmp = 0
	if y <= -2.2e+32:
		tmp = b * (x * (y * a))
	elif y <= -8.2e-181:
		tmp = t_1
	elif y <= 1.36e-170:
		tmp = b * (a * (z * -t))
	elif y <= 3.2e-75:
		tmp = t_1
	elif y <= 1.55e-11:
		tmp = j * (y1 * (y3 * -y4))
	elif y <= 2.3e+125:
		tmp = j * (x * (b * -y0))
	else:
		tmp = a * ((x * y) * b)
	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(y1 * Float64(x * i)))
	tmp = 0.0
	if (y <= -2.2e+32)
		tmp = Float64(b * Float64(x * Float64(y * a)));
	elseif (y <= -8.2e-181)
		tmp = t_1;
	elseif (y <= 1.36e-170)
		tmp = Float64(b * Float64(a * Float64(z * Float64(-t))));
	elseif (y <= 3.2e-75)
		tmp = t_1;
	elseif (y <= 1.55e-11)
		tmp = Float64(j * Float64(y1 * Float64(y3 * Float64(-y4))));
	elseif (y <= 2.3e+125)
		tmp = Float64(j * Float64(x * Float64(b * Float64(-y0))));
	else
		tmp = Float64(a * Float64(Float64(x * y) * b));
	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 * (y1 * (x * i));
	tmp = 0.0;
	if (y <= -2.2e+32)
		tmp = b * (x * (y * a));
	elseif (y <= -8.2e-181)
		tmp = t_1;
	elseif (y <= 1.36e-170)
		tmp = b * (a * (z * -t));
	elseif (y <= 3.2e-75)
		tmp = t_1;
	elseif (y <= 1.55e-11)
		tmp = j * (y1 * (y3 * -y4));
	elseif (y <= 2.3e+125)
		tmp = j * (x * (b * -y0));
	else
		tmp = a * ((x * y) * b);
	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[(y1 * N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y, -2.2e+32], N[(b * N[(x * N[(y * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -8.2e-181], t$95$1, If[LessEqual[y, 1.36e-170], N[(b * N[(a * N[(z * (-t)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 3.2e-75], t$95$1, If[LessEqual[y, 1.55e-11], N[(j * N[(y1 * N[(y3 * (-y4)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 2.3e+125], N[(j * N[(x * N[(b * (-y0)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(a * N[(N[(x * y), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision]]]]]]]]

Derivation

1. Split input into 6 regimes

2. if y < -2.20000000000000001e32

   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. Taylor expanded in b around inf 36.7%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 37.2%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 37.2%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 37.2%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 37.2%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 37.2%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 37.2%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   6. Taylor expanded in y around inf 27.3%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 27.3%

         \[\leadsto \color{blue}{\left(b \cdot \left(x \cdot y\right)\right) \cdot a} \]

      2. associate-*l* 28.9%

         \[\leadsto \color{blue}{b \cdot \left(\left(x \cdot y\right) \cdot a\right)} \]

      3. associate-*l* 38.8%

         \[\leadsto b \cdot \color{blue}{\left(x \cdot \left(y \cdot a\right)\right)} \]

   8. Simplified 38.8%

      \[\leadsto \color{blue}{b \cdot \left(x \cdot \left(y \cdot a\right)\right)} \]

   if -2.20000000000000001e32 < y < -8.2000000000000003e-181 or 1.35999999999999994e-170 < y < 3.19999999999999977e-75

   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. Taylor expanded in j around inf 49.3%

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

   3. Taylor expanded in x around inf 42.0%

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

      1. *-commutative 42.0%

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

      2. *-commutative 42.0%

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

      3. *-commutative 42.0%

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

   5. Simplified 42.0%

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

   6. Taylor expanded in y1 around inf 34.4%

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

      1. *-commutative 34.4%

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

      2. associate-*l* 32.9%

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

      3. *-commutative 32.9%

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

      4. associate-*l* 36.0%

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

   8. Simplified 36.0%

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

   if -8.2000000000000003e-181 < y < 1.35999999999999994e-170

   1. Initial program 45.0%

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

   2. Taylor expanded in b around inf 45.6%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 30.5%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 30.5%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 30.5%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 30.5%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 30.5%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 30.5%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   6. Taylor expanded in y around 0 28.8%

      \[\leadsto b \cdot \color{blue}{\left(-1 \cdot \left(a \cdot \left(t \cdot z\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 28.8%

         \[\leadsto b \cdot \color{blue}{\left(-a \cdot \left(t \cdot z\right)\right)} \]

      2. *-commutative 28.8%

         \[\leadsto b \cdot \left(-a \cdot \color{blue}{\left(z \cdot t\right)}\right) \]

      3. *-commutative 28.8%

         \[\leadsto b \cdot \left(-\color{blue}{\left(z \cdot t\right) \cdot a}\right) \]

      4. distribute-rgt-neg-in 28.8%

         \[\leadsto b \cdot \color{blue}{\left(\left(z \cdot t\right) \cdot \left(-a\right)\right)} \]

   8. Simplified 28.8%

      \[\leadsto b \cdot \color{blue}{\left(\left(z \cdot t\right) \cdot \left(-a\right)\right)} \]

   if 3.19999999999999977e-75 < y < 1.55000000000000014e-11

   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. Taylor expanded in j around inf 33.9%

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

   3. Taylor expanded in y4 around inf 42.4%

      \[\leadsto \color{blue}{j \cdot \left(y4 \cdot \left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 42.4%

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

      2. +-commutative 42.4%

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

      3. mul-1-neg 42.4%

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

      4. unsub-neg 42.4%

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

      5. *-commutative 42.4%

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

   5. Simplified 42.4%

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

   6. Taylor expanded in b around 0 34.3%

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

      1. mul-1-neg 34.3%

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

      2. *-commutative 34.3%

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

      3. distribute-rgt-neg-in 34.3%

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

   8. Simplified 34.3%

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

   if 1.55000000000000014e-11 < y < 2.30000000000000013e125

   1. Initial program 21.7%

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

   2. Taylor expanded in j around inf 28.8%

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

   3. Taylor expanded in x around inf 36.8%

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

      1. *-commutative 36.8%

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

      2. *-commutative 36.8%

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

      3. *-commutative 36.8%

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

   5. Simplified 36.8%

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

   6. Taylor expanded in y1 around 0 33.4%

      \[\leadsto j \cdot \left(\color{blue}{\left(-1 \cdot \left(b \cdot y0\right)\right)} \cdot x\right) \]
   7. Step-by-step derivation

      1. mul-1-neg 33.4%

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

      2. *-commutative 33.4%

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

      3. distribute-rgt-neg-in 33.4%

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

   8. Simplified 33.4%

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

   if 2.30000000000000013e125 < y

   1. Initial program 24.7%

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

   2. Taylor expanded in b around inf 33.1%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 46.9%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 46.9%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 46.9%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 46.9%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 46.9%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 46.9%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   6. Taylor expanded in y around inf 44.2%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 35.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y \leq -2.2 \cdot 10^{+32}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a\right)\right)\\ \mathbf{elif}\;y \leq -8.2 \cdot 10^{-181}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \mathbf{elif}\;y \leq 1.36 \cdot 10^{-170}:\\ \;\;\;\;b \cdot \left(a \cdot \left(z \cdot \left(-t\right)\right)\right)\\ \mathbf{elif}\;y \leq 3.2 \cdot 10^{-75}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \mathbf{elif}\;y \leq 1.55 \cdot 10^{-11}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(y3 \cdot \left(-y4\right)\right)\right)\\ \mathbf{elif}\;y \leq 2.3 \cdot 10^{+125}:\\ \;\;\;\;j \cdot \left(x \cdot \left(b \cdot \left(-y0\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \end{array} \]

Alternative 27: 19.8% accurate, 4.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ t_2 := b \cdot \left(x \cdot \left(y \cdot a\right)\right)\\ t_3 := b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{if}\;t \leq -4.8 \cdot 10^{+215}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq -5.2 \cdot 10^{-12}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;t \leq 10^{-151}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t \leq 2.05 \cdot 10^{-42}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq 3.4 \cdot 10^{+26}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t \leq 2.8 \cdot 10^{+215}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;t_3\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* j (* y1 (* x i))))
        (t_2 (* b (* x (* y a))))
        (t_3 (* b (* j (* t y4)))))
   (if (<= t -4.8e+215)
     t_1
     (if (<= t -5.2e-12)
       t_3
       (if (<= t 1e-151)
         t_2
         (if (<= t 2.05e-42)
           (* j (* y0 (* y3 y5)))
           (if (<= t 3.4e+26) t_2 (if (<= t 2.8e+215) t_1 t_3))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = j * (y1 * (x * i));
	double t_2 = b * (x * (y * a));
	double t_3 = b * (j * (t * y4));
	double tmp;
	if (t <= -4.8e+215) {
		tmp = t_1;
	} else if (t <= -5.2e-12) {
		tmp = t_3;
	} else if (t <= 1e-151) {
		tmp = t_2;
	} else if (t <= 2.05e-42) {
		tmp = j * (y0 * (y3 * y5));
	} else if (t <= 3.4e+26) {
		tmp = t_2;
	} else if (t <= 2.8e+215) {
		tmp = t_1;
	} else {
		tmp = t_3;
	}
	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 = j * (y1 * (x * i))
    t_2 = b * (x * (y * a))
    t_3 = b * (j * (t * y4))
    if (t <= (-4.8d+215)) then
        tmp = t_1
    else if (t <= (-5.2d-12)) then
        tmp = t_3
    else if (t <= 1d-151) then
        tmp = t_2
    else if (t <= 2.05d-42) then
        tmp = j * (y0 * (y3 * y5))
    else if (t <= 3.4d+26) then
        tmp = t_2
    else if (t <= 2.8d+215) then
        tmp = t_1
    else
        tmp = t_3
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = j * (y1 * (x * i));
	double t_2 = b * (x * (y * a));
	double t_3 = b * (j * (t * y4));
	double tmp;
	if (t <= -4.8e+215) {
		tmp = t_1;
	} else if (t <= -5.2e-12) {
		tmp = t_3;
	} else if (t <= 1e-151) {
		tmp = t_2;
	} else if (t <= 2.05e-42) {
		tmp = j * (y0 * (y3 * y5));
	} else if (t <= 3.4e+26) {
		tmp = t_2;
	} else if (t <= 2.8e+215) {
		tmp = t_1;
	} else {
		tmp = t_3;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = j * (y1 * (x * i))
	t_2 = b * (x * (y * a))
	t_3 = b * (j * (t * y4))
	tmp = 0
	if t <= -4.8e+215:
		tmp = t_1
	elif t <= -5.2e-12:
		tmp = t_3
	elif t <= 1e-151:
		tmp = t_2
	elif t <= 2.05e-42:
		tmp = j * (y0 * (y3 * y5))
	elif t <= 3.4e+26:
		tmp = t_2
	elif t <= 2.8e+215:
		tmp = t_1
	else:
		tmp = t_3
	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(y1 * Float64(x * i)))
	t_2 = Float64(b * Float64(x * Float64(y * a)))
	t_3 = Float64(b * Float64(j * Float64(t * y4)))
	tmp = 0.0
	if (t <= -4.8e+215)
		tmp = t_1;
	elseif (t <= -5.2e-12)
		tmp = t_3;
	elseif (t <= 1e-151)
		tmp = t_2;
	elseif (t <= 2.05e-42)
		tmp = Float64(j * Float64(y0 * Float64(y3 * y5)));
	elseif (t <= 3.4e+26)
		tmp = t_2;
	elseif (t <= 2.8e+215)
		tmp = t_1;
	else
		tmp = t_3;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = j * (y1 * (x * i));
	t_2 = b * (x * (y * a));
	t_3 = b * (j * (t * y4));
	tmp = 0.0;
	if (t <= -4.8e+215)
		tmp = t_1;
	elseif (t <= -5.2e-12)
		tmp = t_3;
	elseif (t <= 1e-151)
		tmp = t_2;
	elseif (t <= 2.05e-42)
		tmp = j * (y0 * (y3 * y5));
	elseif (t <= 3.4e+26)
		tmp = t_2;
	elseif (t <= 2.8e+215)
		tmp = t_1;
	else
		tmp = t_3;
	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[(y1 * N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(b * N[(x * N[(y * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(b * N[(j * N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -4.8e+215], t$95$1, If[LessEqual[t, -5.2e-12], t$95$3, If[LessEqual[t, 1e-151], t$95$2, If[LessEqual[t, 2.05e-42], N[(j * N[(y0 * N[(y3 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 3.4e+26], t$95$2, If[LessEqual[t, 2.8e+215], t$95$1, t$95$3]]]]]]]]]

Derivation

1. Split input into 4 regimes

2. if t < -4.8000000000000002e215 or 3.4000000000000003e26 < t < 2.8e215

   1. Initial program 29.5%

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

   2. Taylor expanded in j around inf 36.6%

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

   3. Taylor expanded in x around inf 30.3%

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

      1. *-commutative 30.3%

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

      2. *-commutative 30.3%

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

      3. *-commutative 30.3%

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

   5. Simplified 30.3%

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

   6. Taylor expanded in y1 around inf 25.4%

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

      1. *-commutative 25.4%

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

      2. associate-*l* 25.5%

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

      3. *-commutative 25.5%

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

      4. associate-*l* 30.6%

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

   8. Simplified 30.6%

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

   if -4.8000000000000002e215 < t < -5.19999999999999965e-12 or 2.8e215 < t

   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. Taylor expanded in j around inf 44.1%

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

   3. Taylor expanded in y4 around inf 39.1%

      \[\leadsto \color{blue}{j \cdot \left(y4 \cdot \left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 39.1%

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

      2. +-commutative 39.1%

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

      3. mul-1-neg 39.1%

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

      4. unsub-neg 39.1%

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

      5. *-commutative 39.1%

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

   5. Simplified 39.1%

      \[\leadsto \color{blue}{j \cdot \left(\left(b \cdot t - y3 \cdot y1\right) \cdot y4\right)} \]

   6. Taylor expanded in b around inf 41.8%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]

   if -5.19999999999999965e-12 < t < 9.9999999999999994e-152 or 2.0500000000000001e-42 < t < 3.4000000000000003e26

   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. Taylor expanded in b around inf 42.4%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 28.2%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 28.2%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 28.2%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 28.2%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 28.2%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 28.2%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   6. Taylor expanded in y around inf 22.0%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 22.0%

         \[\leadsto \color{blue}{\left(b \cdot \left(x \cdot y\right)\right) \cdot a} \]

      2. associate-*l* 26.3%

         \[\leadsto \color{blue}{b \cdot \left(\left(x \cdot y\right) \cdot a\right)} \]

      3. associate-*l* 29.0%

         \[\leadsto b \cdot \color{blue}{\left(x \cdot \left(y \cdot a\right)\right)} \]

   8. Simplified 29.0%

      \[\leadsto \color{blue}{b \cdot \left(x \cdot \left(y \cdot a\right)\right)} \]

   if 9.9999999999999994e-152 < t < 2.0500000000000001e-42

   1. Initial program 53.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 35.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in y5 around -inf 53.7%

      \[\leadsto \color{blue}{-1 \cdot \left(j \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)\right)\right)} \]
   4. Step-by-step derivation

      1. mul-1-neg 53.7%

         \[\leadsto \color{blue}{-j \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)\right)} \]

      2. associate-*r* 53.7%

         \[\leadsto -\color{blue}{\left(j \cdot y5\right) \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)} \]

      3. distribute-lft-neg-in 53.7%

         \[\leadsto \color{blue}{\left(-j \cdot y5\right) \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)} \]

      4. distribute-rgt-neg-in 53.7%

         \[\leadsto \color{blue}{\left(j \cdot \left(-y5\right)\right)} \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right) \]

      5. +-commutative 53.7%

         \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \color{blue}{\left(i \cdot t + -1 \cdot \left(y0 \cdot y3\right)\right)} \]

      6. mul-1-neg 53.7%

         \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \left(i \cdot t + \color{blue}{\left(-y0 \cdot y3\right)}\right) \]

      7. unsub-neg 53.7%

         \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \color{blue}{\left(i \cdot t - y0 \cdot y3\right)} \]

      8. *-commutative 53.7%

         \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \left(i \cdot t - \color{blue}{y3 \cdot y0}\right) \]

   5. Simplified 53.7%

      \[\leadsto \color{blue}{\left(j \cdot \left(-y5\right)\right) \cdot \left(i \cdot t - y3 \cdot y0\right)} \]

   6. Taylor expanded in i around 0 43.1%

      \[\leadsto \color{blue}{j \cdot \left(y0 \cdot \left(y3 \cdot y5\right)\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 33.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -4.8 \cdot 10^{+215}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \mathbf{elif}\;t \leq -5.2 \cdot 10^{-12}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{elif}\;t \leq 10^{-151}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a\right)\right)\\ \mathbf{elif}\;t \leq 2.05 \cdot 10^{-42}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq 3.4 \cdot 10^{+26}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a\right)\right)\\ \mathbf{elif}\;t \leq 2.8 \cdot 10^{+215}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \end{array} \]

Alternative 28: 26.7% accurate, 4.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := z \cdot \left(c \cdot \left(y0 \cdot \left(-y3\right)\right)\right)\\ t_2 := b \cdot \left(a \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{if}\;y0 \leq -1.4 \cdot 10^{+155}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y0 \leq -106000000:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y0 \leq -5.2 \cdot 10^{-167}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(y3 \cdot \left(-y4\right)\right)\right)\\ \mathbf{elif}\;y0 \leq 8 \cdot 10^{+57}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y0 \leq 8.8 \cdot 10^{+225}:\\ \;\;\;\;b \cdot \left(j \cdot \left(x \cdot \left(-y0\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* z (* c (* y0 (- y3))))) (t_2 (* b (* a (- (* x y) (* z t))))))
   (if (<= y0 -1.4e+155)
     t_1
     (if (<= y0 -106000000.0)
       t_2
       (if (<= y0 -5.2e-167)
         (* j (* y1 (* y3 (- y4))))
         (if (<= y0 8e+57)
           t_2
           (if (<= y0 8.8e+225) (* b (* j (* x (- 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 = z * (c * (y0 * -y3));
	double t_2 = b * (a * ((x * y) - (z * t)));
	double tmp;
	if (y0 <= -1.4e+155) {
		tmp = t_1;
	} else if (y0 <= -106000000.0) {
		tmp = t_2;
	} else if (y0 <= -5.2e-167) {
		tmp = j * (y1 * (y3 * -y4));
	} else if (y0 <= 8e+57) {
		tmp = t_2;
	} else if (y0 <= 8.8e+225) {
		tmp = b * (j * (x * -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) :: t_2
    real(8) :: tmp
    t_1 = z * (c * (y0 * -y3))
    t_2 = b * (a * ((x * y) - (z * t)))
    if (y0 <= (-1.4d+155)) then
        tmp = t_1
    else if (y0 <= (-106000000.0d0)) then
        tmp = t_2
    else if (y0 <= (-5.2d-167)) then
        tmp = j * (y1 * (y3 * -y4))
    else if (y0 <= 8d+57) then
        tmp = t_2
    else if (y0 <= 8.8d+225) then
        tmp = b * (j * (x * -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 = z * (c * (y0 * -y3));
	double t_2 = b * (a * ((x * y) - (z * t)));
	double tmp;
	if (y0 <= -1.4e+155) {
		tmp = t_1;
	} else if (y0 <= -106000000.0) {
		tmp = t_2;
	} else if (y0 <= -5.2e-167) {
		tmp = j * (y1 * (y3 * -y4));
	} else if (y0 <= 8e+57) {
		tmp = t_2;
	} else if (y0 <= 8.8e+225) {
		tmp = b * (j * (x * -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 = z * (c * (y0 * -y3))
	t_2 = b * (a * ((x * y) - (z * t)))
	tmp = 0
	if y0 <= -1.4e+155:
		tmp = t_1
	elif y0 <= -106000000.0:
		tmp = t_2
	elif y0 <= -5.2e-167:
		tmp = j * (y1 * (y3 * -y4))
	elif y0 <= 8e+57:
		tmp = t_2
	elif y0 <= 8.8e+225:
		tmp = b * (j * (x * -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(z * Float64(c * Float64(y0 * Float64(-y3))))
	t_2 = Float64(b * Float64(a * Float64(Float64(x * y) - Float64(z * t))))
	tmp = 0.0
	if (y0 <= -1.4e+155)
		tmp = t_1;
	elseif (y0 <= -106000000.0)
		tmp = t_2;
	elseif (y0 <= -5.2e-167)
		tmp = Float64(j * Float64(y1 * Float64(y3 * Float64(-y4))));
	elseif (y0 <= 8e+57)
		tmp = t_2;
	elseif (y0 <= 8.8e+225)
		tmp = Float64(b * Float64(j * Float64(x * Float64(-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 = z * (c * (y0 * -y3));
	t_2 = b * (a * ((x * y) - (z * t)));
	tmp = 0.0;
	if (y0 <= -1.4e+155)
		tmp = t_1;
	elseif (y0 <= -106000000.0)
		tmp = t_2;
	elseif (y0 <= -5.2e-167)
		tmp = j * (y1 * (y3 * -y4));
	elseif (y0 <= 8e+57)
		tmp = t_2;
	elseif (y0 <= 8.8e+225)
		tmp = b * (j * (x * -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[(z * N[(c * N[(y0 * (-y3)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(b * N[(a * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y0, -1.4e+155], t$95$1, If[LessEqual[y0, -106000000.0], t$95$2, If[LessEqual[y0, -5.2e-167], N[(j * N[(y1 * N[(y3 * (-y4)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 8e+57], t$95$2, If[LessEqual[y0, 8.8e+225], N[(b * N[(j * N[(x * (-y0)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]]

Derivation

1. Split input into 4 regimes

2. if y0 < -1.40000000000000008e155 or 8.80000000000000055e225 < y0

   1. Initial program 35.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in z around -inf 52.4%

      \[\leadsto \color{blue}{-1 \cdot \left(z \cdot \left(\left(t \cdot \left(a \cdot b - c \cdot i\right) + y3 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   3. Taylor expanded in y0 around inf 38.5%

      \[\leadsto -1 \cdot \color{blue}{\left(y0 \cdot \left(z \cdot \left(c \cdot y3 - b \cdot k\right)\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 40.2%

         \[\leadsto -1 \cdot \color{blue}{\left(\left(y0 \cdot z\right) \cdot \left(c \cdot y3 - b \cdot k\right)\right)} \]

      2. *-commutative 40.2%

         \[\leadsto -1 \cdot \left(\color{blue}{\left(z \cdot y0\right)} \cdot \left(c \cdot y3 - b \cdot k\right)\right) \]

      3. *-commutative 40.2%

         \[\leadsto -1 \cdot \left(\left(z \cdot y0\right) \cdot \left(\color{blue}{y3 \cdot c} - b \cdot k\right)\right) \]

      4. *-commutative 40.2%

         \[\leadsto -1 \cdot \left(\left(z \cdot y0\right) \cdot \left(y3 \cdot c - \color{blue}{k \cdot b}\right)\right) \]

   5. Simplified 40.2%

      \[\leadsto -1 \cdot \color{blue}{\left(\left(z \cdot y0\right) \cdot \left(y3 \cdot c - k \cdot b\right)\right)} \]

   6. Taylor expanded in y3 around inf 38.0%

      \[\leadsto -1 \cdot \color{blue}{\left(c \cdot \left(y0 \cdot \left(y3 \cdot z\right)\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 43.2%

         \[\leadsto -1 \cdot \left(c \cdot \color{blue}{\left(\left(y0 \cdot y3\right) \cdot z\right)}\right) \]

      2. associate-*r* 43.3%

         \[\leadsto -1 \cdot \color{blue}{\left(\left(c \cdot \left(y0 \cdot y3\right)\right) \cdot z\right)} \]

   8. Simplified 43.3%

      \[\leadsto -1 \cdot \color{blue}{\left(\left(c \cdot \left(y0 \cdot y3\right)\right) \cdot z\right)} \]

   if -1.40000000000000008e155 < y0 < -1.06e8 or -5.1999999999999998e-167 < y0 < 8.00000000000000039e57

   1. Initial program 37.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 40.3%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 40.7%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 40.7%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 40.7%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 40.7%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 40.7%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 40.7%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   if -1.06e8 < y0 < -5.1999999999999998e-167

   1. Initial program 21.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 33.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in y4 around inf 40.5%

      \[\leadsto \color{blue}{j \cdot \left(y4 \cdot \left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 40.5%

         \[\leadsto j \cdot \color{blue}{\left(\left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right) \cdot y4\right)} \]

      2. +-commutative 40.5%

         \[\leadsto j \cdot \left(\color{blue}{\left(b \cdot t + -1 \cdot \left(y1 \cdot y3\right)\right)} \cdot y4\right) \]

      3. mul-1-neg 40.5%

         \[\leadsto j \cdot \left(\left(b \cdot t + \color{blue}{\left(-y1 \cdot y3\right)}\right) \cdot y4\right) \]

      4. unsub-neg 40.5%

         \[\leadsto j \cdot \left(\color{blue}{\left(b \cdot t - y1 \cdot y3\right)} \cdot y4\right) \]

      5. *-commutative 40.5%

         \[\leadsto j \cdot \left(\left(b \cdot t - \color{blue}{y3 \cdot y1}\right) \cdot y4\right) \]

   5. Simplified 40.5%

      \[\leadsto \color{blue}{j \cdot \left(\left(b \cdot t - y3 \cdot y1\right) \cdot y4\right)} \]

   6. Taylor expanded in b around 0 29.9%

      \[\leadsto j \cdot \color{blue}{\left(-1 \cdot \left(y1 \cdot \left(y3 \cdot y4\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 29.9%

         \[\leadsto j \cdot \color{blue}{\left(-y1 \cdot \left(y3 \cdot y4\right)\right)} \]

      2. *-commutative 29.9%

         \[\leadsto j \cdot \left(-\color{blue}{\left(y3 \cdot y4\right) \cdot y1}\right) \]

      3. distribute-rgt-neg-in 29.9%

         \[\leadsto j \cdot \color{blue}{\left(\left(y3 \cdot y4\right) \cdot \left(-y1\right)\right)} \]

   8. Simplified 29.9%

      \[\leadsto j \cdot \color{blue}{\left(\left(y3 \cdot y4\right) \cdot \left(-y1\right)\right)} \]

   if 8.00000000000000039e57 < y0 < 8.80000000000000055e225

   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. Taylor expanded in j around inf 44.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in x around inf 42.8%

      \[\leadsto j \cdot \color{blue}{\left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 42.8%

         \[\leadsto j \cdot \color{blue}{\left(\left(i \cdot y1 - b \cdot y0\right) \cdot x\right)} \]

      2. *-commutative 42.8%

         \[\leadsto j \cdot \left(\left(\color{blue}{y1 \cdot i} - b \cdot y0\right) \cdot x\right) \]

      3. *-commutative 42.8%

         \[\leadsto j \cdot \left(\left(y1 \cdot i - \color{blue}{y0 \cdot b}\right) \cdot x\right) \]

   5. Simplified 42.8%

      \[\leadsto j \cdot \color{blue}{\left(\left(y1 \cdot i - y0 \cdot b\right) \cdot x\right)} \]

   6. Taylor expanded in y1 around 0 40.7%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(j \cdot \left(x \cdot y0\right)\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 40.7%

         \[\leadsto \color{blue}{\left(-1 \cdot b\right) \cdot \left(j \cdot \left(x \cdot y0\right)\right)} \]

      2. neg-mul-1 40.7%

         \[\leadsto \color{blue}{\left(-b\right)} \cdot \left(j \cdot \left(x \cdot y0\right)\right) \]

      3. *-commutative 40.7%

         \[\leadsto \left(-b\right) \cdot \left(j \cdot \color{blue}{\left(y0 \cdot x\right)}\right) \]

   8. Simplified 40.7%

      \[\leadsto \color{blue}{\left(-b\right) \cdot \left(j \cdot \left(y0 \cdot x\right)\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 40.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y0 \leq -1.4 \cdot 10^{+155}:\\ \;\;\;\;z \cdot \left(c \cdot \left(y0 \cdot \left(-y3\right)\right)\right)\\ \mathbf{elif}\;y0 \leq -106000000:\\ \;\;\;\;b \cdot \left(a \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;y0 \leq -5.2 \cdot 10^{-167}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(y3 \cdot \left(-y4\right)\right)\right)\\ \mathbf{elif}\;y0 \leq 8 \cdot 10^{+57}:\\ \;\;\;\;b \cdot \left(a \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;y0 \leq 8.8 \cdot 10^{+225}:\\ \;\;\;\;b \cdot \left(j \cdot \left(x \cdot \left(-y0\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;z \cdot \left(c \cdot \left(y0 \cdot \left(-y3\right)\right)\right)\\ \end{array} \]

Alternative 29: 21.8% accurate, 5.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y \leq -2.2 \cdot 10^{+32}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a\right)\right)\\ \mathbf{elif}\;y \leq -4.7 \cdot 10^{-181}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \mathbf{elif}\;y \leq 2.5 \cdot 10^{-278}:\\ \;\;\;\;b \cdot \left(a \cdot \left(z \cdot \left(-t\right)\right)\right)\\ \mathbf{elif}\;y \leq 2.7 \cdot 10^{-11}:\\ \;\;\;\;\left(j \cdot \left(-y5\right)\right) \cdot \left(t \cdot i\right)\\ \mathbf{elif}\;y \leq 2.3 \cdot 10^{+125}:\\ \;\;\;\;j \cdot \left(x \cdot \left(b \cdot \left(-y0\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= y -2.2e+32)
   (* b (* x (* y a)))
   (if (<= y -4.7e-181)
     (* j (* y1 (* x i)))
     (if (<= y 2.5e-278)
       (* b (* a (* z (- t))))
       (if (<= y 2.7e-11)
         (* (* j (- y5)) (* t i))
         (if (<= y 2.3e+125) (* j (* x (* b (- y0)))) (* a (* (* x y) b))))))))

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 <= -2.2e+32) {
		tmp = b * (x * (y * a));
	} else if (y <= -4.7e-181) {
		tmp = j * (y1 * (x * i));
	} else if (y <= 2.5e-278) {
		tmp = b * (a * (z * -t));
	} else if (y <= 2.7e-11) {
		tmp = (j * -y5) * (t * i);
	} else if (y <= 2.3e+125) {
		tmp = j * (x * (b * -y0));
	} else {
		tmp = a * ((x * y) * b);
	}
	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 <= (-2.2d+32)) then
        tmp = b * (x * (y * a))
    else if (y <= (-4.7d-181)) then
        tmp = j * (y1 * (x * i))
    else if (y <= 2.5d-278) then
        tmp = b * (a * (z * -t))
    else if (y <= 2.7d-11) then
        tmp = (j * -y5) * (t * i)
    else if (y <= 2.3d+125) then
        tmp = j * (x * (b * -y0))
    else
        tmp = a * ((x * y) * b)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y <= -2.2e+32) {
		tmp = b * (x * (y * a));
	} else if (y <= -4.7e-181) {
		tmp = j * (y1 * (x * i));
	} else if (y <= 2.5e-278) {
		tmp = b * (a * (z * -t));
	} else if (y <= 2.7e-11) {
		tmp = (j * -y5) * (t * i);
	} else if (y <= 2.3e+125) {
		tmp = j * (x * (b * -y0));
	} else {
		tmp = a * ((x * y) * b);
	}
	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 <= -2.2e+32:
		tmp = b * (x * (y * a))
	elif y <= -4.7e-181:
		tmp = j * (y1 * (x * i))
	elif y <= 2.5e-278:
		tmp = b * (a * (z * -t))
	elif y <= 2.7e-11:
		tmp = (j * -y5) * (t * i)
	elif y <= 2.3e+125:
		tmp = j * (x * (b * -y0))
	else:
		tmp = a * ((x * y) * b)
	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 <= -2.2e+32)
		tmp = Float64(b * Float64(x * Float64(y * a)));
	elseif (y <= -4.7e-181)
		tmp = Float64(j * Float64(y1 * Float64(x * i)));
	elseif (y <= 2.5e-278)
		tmp = Float64(b * Float64(a * Float64(z * Float64(-t))));
	elseif (y <= 2.7e-11)
		tmp = Float64(Float64(j * Float64(-y5)) * Float64(t * i));
	elseif (y <= 2.3e+125)
		tmp = Float64(j * Float64(x * Float64(b * Float64(-y0))));
	else
		tmp = Float64(a * Float64(Float64(x * y) * b));
	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 <= -2.2e+32)
		tmp = b * (x * (y * a));
	elseif (y <= -4.7e-181)
		tmp = j * (y1 * (x * i));
	elseif (y <= 2.5e-278)
		tmp = b * (a * (z * -t));
	elseif (y <= 2.7e-11)
		tmp = (j * -y5) * (t * i);
	elseif (y <= 2.3e+125)
		tmp = j * (x * (b * -y0));
	else
		tmp = a * ((x * y) * b);
	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, -2.2e+32], N[(b * N[(x * N[(y * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -4.7e-181], N[(j * N[(y1 * N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 2.5e-278], N[(b * N[(a * N[(z * (-t)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 2.7e-11], N[(N[(j * (-y5)), $MachinePrecision] * N[(t * i), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 2.3e+125], N[(j * N[(x * N[(b * (-y0)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(a * N[(N[(x * y), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

1. Split input into 6 regimes

2. if y < -2.20000000000000001e32

   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. Taylor expanded in b around inf 36.7%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 37.2%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 37.2%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 37.2%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 37.2%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 37.2%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 37.2%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   6. Taylor expanded in y around inf 27.3%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 27.3%

         \[\leadsto \color{blue}{\left(b \cdot \left(x \cdot y\right)\right) \cdot a} \]

      2. associate-*l* 28.9%

         \[\leadsto \color{blue}{b \cdot \left(\left(x \cdot y\right) \cdot a\right)} \]

      3. associate-*l* 38.8%

         \[\leadsto b \cdot \color{blue}{\left(x \cdot \left(y \cdot a\right)\right)} \]

   8. Simplified 38.8%

      \[\leadsto \color{blue}{b \cdot \left(x \cdot \left(y \cdot a\right)\right)} \]

   if -2.20000000000000001e32 < y < -4.6999999999999998e-181

   1. Initial program 39.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 46.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in x around inf 40.2%

      \[\leadsto j \cdot \color{blue}{\left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 40.2%

         \[\leadsto j \cdot \color{blue}{\left(\left(i \cdot y1 - b \cdot y0\right) \cdot x\right)} \]

      2. *-commutative 40.2%

         \[\leadsto j \cdot \left(\left(\color{blue}{y1 \cdot i} - b \cdot y0\right) \cdot x\right) \]

      3. *-commutative 40.2%

         \[\leadsto j \cdot \left(\left(y1 \cdot i - \color{blue}{y0 \cdot b}\right) \cdot x\right) \]

   5. Simplified 40.2%

      \[\leadsto j \cdot \color{blue}{\left(\left(y1 \cdot i - y0 \cdot b\right) \cdot x\right)} \]

   6. Taylor expanded in y1 around inf 33.5%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(x \cdot y1\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 33.5%

         \[\leadsto \color{blue}{\left(j \cdot \left(x \cdot y1\right)\right) \cdot i} \]

      2. associate-*l* 31.3%

         \[\leadsto \color{blue}{j \cdot \left(\left(x \cdot y1\right) \cdot i\right)} \]

      3. *-commutative 31.3%

         \[\leadsto j \cdot \left(\color{blue}{\left(y1 \cdot x\right)} \cdot i\right) \]

      4. associate-*l* 35.8%

         \[\leadsto j \cdot \color{blue}{\left(y1 \cdot \left(x \cdot i\right)\right)} \]

   8. Simplified 35.8%

      \[\leadsto \color{blue}{j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)} \]

   if -4.6999999999999998e-181 < y < 2.49999999999999992e-278

   1. Initial program 41.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 61.8%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 31.8%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 31.8%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 31.8%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 31.8%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 31.8%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 31.8%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   6. Taylor expanded in y around 0 31.8%

      \[\leadsto b \cdot \color{blue}{\left(-1 \cdot \left(a \cdot \left(t \cdot z\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 31.8%

         \[\leadsto b \cdot \color{blue}{\left(-a \cdot \left(t \cdot z\right)\right)} \]

      2. *-commutative 31.8%

         \[\leadsto b \cdot \left(-a \cdot \color{blue}{\left(z \cdot t\right)}\right) \]

      3. *-commutative 31.8%

         \[\leadsto b \cdot \left(-\color{blue}{\left(z \cdot t\right) \cdot a}\right) \]

      4. distribute-rgt-neg-in 31.8%

         \[\leadsto b \cdot \color{blue}{\left(\left(z \cdot t\right) \cdot \left(-a\right)\right)} \]

   8. Simplified 31.8%

      \[\leadsto b \cdot \color{blue}{\left(\left(z \cdot t\right) \cdot \left(-a\right)\right)} \]

   if 2.49999999999999992e-278 < y < 2.70000000000000005e-11

   1. Initial program 35.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 44.9%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in y5 around -inf 38.3%

      \[\leadsto \color{blue}{-1 \cdot \left(j \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)\right)\right)} \]
   4. Step-by-step derivation

      1. mul-1-neg 38.3%

         \[\leadsto \color{blue}{-j \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)\right)} \]

      2. associate-*r* 38.3%

         \[\leadsto -\color{blue}{\left(j \cdot y5\right) \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)} \]

      3. distribute-lft-neg-in 38.3%

         \[\leadsto \color{blue}{\left(-j \cdot y5\right) \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)} \]

      4. distribute-rgt-neg-in 38.3%

         \[\leadsto \color{blue}{\left(j \cdot \left(-y5\right)\right)} \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right) \]

      5. +-commutative 38.3%

         \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \color{blue}{\left(i \cdot t + -1 \cdot \left(y0 \cdot y3\right)\right)} \]

      6. mul-1-neg 38.3%

         \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \left(i \cdot t + \color{blue}{\left(-y0 \cdot y3\right)}\right) \]

      7. unsub-neg 38.3%

         \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \color{blue}{\left(i \cdot t - y0 \cdot y3\right)} \]

      8. *-commutative 38.3%

         \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \left(i \cdot t - \color{blue}{y3 \cdot y0}\right) \]

   5. Simplified 38.3%

      \[\leadsto \color{blue}{\left(j \cdot \left(-y5\right)\right) \cdot \left(i \cdot t - y3 \cdot y0\right)} \]

   6. Taylor expanded in i around inf 38.4%

      \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \color{blue}{\left(i \cdot t\right)} \]
   7. Step-by-step derivation

      1. *-commutative 38.4%

         \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \color{blue}{\left(t \cdot i\right)} \]

   8. Simplified 38.4%

      \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \color{blue}{\left(t \cdot i\right)} \]

   if 2.70000000000000005e-11 < y < 2.30000000000000013e125

   1. Initial program 21.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 28.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in x around inf 36.8%

      \[\leadsto j \cdot \color{blue}{\left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 36.8%

         \[\leadsto j \cdot \color{blue}{\left(\left(i \cdot y1 - b \cdot y0\right) \cdot x\right)} \]

      2. *-commutative 36.8%

         \[\leadsto j \cdot \left(\left(\color{blue}{y1 \cdot i} - b \cdot y0\right) \cdot x\right) \]

      3. *-commutative 36.8%

         \[\leadsto j \cdot \left(\left(y1 \cdot i - \color{blue}{y0 \cdot b}\right) \cdot x\right) \]

   5. Simplified 36.8%

      \[\leadsto j \cdot \color{blue}{\left(\left(y1 \cdot i - y0 \cdot b\right) \cdot x\right)} \]

   6. Taylor expanded in y1 around 0 33.4%

      \[\leadsto j \cdot \left(\color{blue}{\left(-1 \cdot \left(b \cdot y0\right)\right)} \cdot x\right) \]
   7. Step-by-step derivation

      1. mul-1-neg 33.4%

         \[\leadsto j \cdot \left(\color{blue}{\left(-b \cdot y0\right)} \cdot x\right) \]

      2. *-commutative 33.4%

         \[\leadsto j \cdot \left(\left(-\color{blue}{y0 \cdot b}\right) \cdot x\right) \]

      3. distribute-rgt-neg-in 33.4%

         \[\leadsto j \cdot \left(\color{blue}{\left(y0 \cdot \left(-b\right)\right)} \cdot x\right) \]

   8. Simplified 33.4%

      \[\leadsto j \cdot \left(\color{blue}{\left(y0 \cdot \left(-b\right)\right)} \cdot x\right) \]

   if 2.30000000000000013e125 < y

   1. Initial program 24.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 33.1%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 46.9%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 46.9%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 46.9%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 46.9%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 46.9%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 46.9%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   6. Taylor expanded in y around inf 44.2%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 37.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y \leq -2.2 \cdot 10^{+32}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a\right)\right)\\ \mathbf{elif}\;y \leq -4.7 \cdot 10^{-181}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \mathbf{elif}\;y \leq 2.5 \cdot 10^{-278}:\\ \;\;\;\;b \cdot \left(a \cdot \left(z \cdot \left(-t\right)\right)\right)\\ \mathbf{elif}\;y \leq 2.7 \cdot 10^{-11}:\\ \;\;\;\;\left(j \cdot \left(-y5\right)\right) \cdot \left(t \cdot i\right)\\ \mathbf{elif}\;y \leq 2.3 \cdot 10^{+125}:\\ \;\;\;\;j \cdot \left(x \cdot \left(b \cdot \left(-y0\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \end{array} \]

Alternative 30: 20.8% accurate, 5.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;j \leq -5.7 \cdot 10^{+100}:\\ \;\;\;\;y0 \cdot \left(y3 \cdot \left(j \cdot y5\right)\right)\\ \mathbf{elif}\;j \leq 7 \cdot 10^{-296}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a\right)\right)\\ \mathbf{elif}\;j \leq 1.75 \cdot 10^{-251}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq 4.8 \cdot 10^{-216}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{elif}\;j \leq 6.5 \cdot 10^{+76}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= j -5.7e+100)
   (* y0 (* y3 (* j y5)))
   (if (<= j 7e-296)
     (* b (* x (* y a)))
     (if (<= j 1.75e-251)
       (* k (* y2 (* y1 y4)))
       (if (<= j 4.8e-216)
         (* a (* (* x y) b))
         (if (<= j 6.5e+76) (* j (* y0 (* y3 y5))) (* i (* j (* x y1)))))))))

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 (j <= -5.7e+100) {
		tmp = y0 * (y3 * (j * y5));
	} else if (j <= 7e-296) {
		tmp = b * (x * (y * a));
	} else if (j <= 1.75e-251) {
		tmp = k * (y2 * (y1 * y4));
	} else if (j <= 4.8e-216) {
		tmp = a * ((x * y) * b);
	} else if (j <= 6.5e+76) {
		tmp = j * (y0 * (y3 * y5));
	} else {
		tmp = i * (j * (x * y1));
	}
	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 (j <= (-5.7d+100)) then
        tmp = y0 * (y3 * (j * y5))
    else if (j <= 7d-296) then
        tmp = b * (x * (y * a))
    else if (j <= 1.75d-251) then
        tmp = k * (y2 * (y1 * y4))
    else if (j <= 4.8d-216) then
        tmp = a * ((x * y) * b)
    else if (j <= 6.5d+76) then
        tmp = j * (y0 * (y3 * y5))
    else
        tmp = i * (j * (x * y1))
    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 (j <= -5.7e+100) {
		tmp = y0 * (y3 * (j * y5));
	} else if (j <= 7e-296) {
		tmp = b * (x * (y * a));
	} else if (j <= 1.75e-251) {
		tmp = k * (y2 * (y1 * y4));
	} else if (j <= 4.8e-216) {
		tmp = a * ((x * y) * b);
	} else if (j <= 6.5e+76) {
		tmp = j * (y0 * (y3 * y5));
	} else {
		tmp = i * (j * (x * y1));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if j <= -5.7e+100:
		tmp = y0 * (y3 * (j * y5))
	elif j <= 7e-296:
		tmp = b * (x * (y * a))
	elif j <= 1.75e-251:
		tmp = k * (y2 * (y1 * y4))
	elif j <= 4.8e-216:
		tmp = a * ((x * y) * b)
	elif j <= 6.5e+76:
		tmp = j * (y0 * (y3 * y5))
	else:
		tmp = i * (j * (x * y1))
	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 (j <= -5.7e+100)
		tmp = Float64(y0 * Float64(y3 * Float64(j * y5)));
	elseif (j <= 7e-296)
		tmp = Float64(b * Float64(x * Float64(y * a)));
	elseif (j <= 1.75e-251)
		tmp = Float64(k * Float64(y2 * Float64(y1 * y4)));
	elseif (j <= 4.8e-216)
		tmp = Float64(a * Float64(Float64(x * y) * b));
	elseif (j <= 6.5e+76)
		tmp = Float64(j * Float64(y0 * Float64(y3 * y5)));
	else
		tmp = Float64(i * Float64(j * Float64(x * y1)));
	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 (j <= -5.7e+100)
		tmp = y0 * (y3 * (j * y5));
	elseif (j <= 7e-296)
		tmp = b * (x * (y * a));
	elseif (j <= 1.75e-251)
		tmp = k * (y2 * (y1 * y4));
	elseif (j <= 4.8e-216)
		tmp = a * ((x * y) * b);
	elseif (j <= 6.5e+76)
		tmp = j * (y0 * (y3 * y5));
	else
		tmp = i * (j * (x * y1));
	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[j, -5.7e+100], N[(y0 * N[(y3 * N[(j * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 7e-296], N[(b * N[(x * N[(y * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 1.75e-251], N[(k * N[(y2 * N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 4.8e-216], N[(a * N[(N[(x * y), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 6.5e+76], N[(j * N[(y0 * N[(y3 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(i * N[(j * N[(x * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

1. Split input into 6 regimes

2. if j < -5.69999999999999984e100

   1. Initial program 26.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 50.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in y5 around -inf 50.4%

      \[\leadsto \color{blue}{-1 \cdot \left(j \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)\right)\right)} \]
   4. Step-by-step derivation

      1. mul-1-neg 50.4%

         \[\leadsto \color{blue}{-j \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)\right)} \]

      2. associate-*r* 50.4%

         \[\leadsto -\color{blue}{\left(j \cdot y5\right) \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)} \]

      3. distribute-lft-neg-in 50.4%

         \[\leadsto \color{blue}{\left(-j \cdot y5\right) \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)} \]

      4. distribute-rgt-neg-in 50.4%

         \[\leadsto \color{blue}{\left(j \cdot \left(-y5\right)\right)} \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right) \]

      5. +-commutative 50.4%

         \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \color{blue}{\left(i \cdot t + -1 \cdot \left(y0 \cdot y3\right)\right)} \]

      6. mul-1-neg 50.4%

         \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \left(i \cdot t + \color{blue}{\left(-y0 \cdot y3\right)}\right) \]

      7. unsub-neg 50.4%

         \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \color{blue}{\left(i \cdot t - y0 \cdot y3\right)} \]

      8. *-commutative 50.4%

         \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \left(i \cdot t - \color{blue}{y3 \cdot y0}\right) \]

   5. Simplified 50.4%

      \[\leadsto \color{blue}{\left(j \cdot \left(-y5\right)\right) \cdot \left(i \cdot t - y3 \cdot y0\right)} \]

   6. Taylor expanded in i around 0 25.1%

      \[\leadsto \color{blue}{j \cdot \left(y0 \cdot \left(y3 \cdot y5\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 25.1%

         \[\leadsto \color{blue}{\left(y0 \cdot \left(y3 \cdot y5\right)\right) \cdot j} \]

      2. associate-*l* 27.9%

         \[\leadsto \color{blue}{y0 \cdot \left(\left(y3 \cdot y5\right) \cdot j\right)} \]

      3. associate-*r* 39.1%

         \[\leadsto y0 \cdot \color{blue}{\left(y3 \cdot \left(y5 \cdot j\right)\right)} \]

   8. Simplified 39.1%

      \[\leadsto \color{blue}{y0 \cdot \left(y3 \cdot \left(y5 \cdot j\right)\right)} \]

   if -5.69999999999999984e100 < j < 6.9999999999999998e-296

   1. Initial program 43.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 41.8%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 41.0%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 41.0%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 41.0%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 41.0%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 41.0%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 41.0%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   6. Taylor expanded in y around inf 23.9%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 23.9%

         \[\leadsto \color{blue}{\left(b \cdot \left(x \cdot y\right)\right) \cdot a} \]

      2. associate-*l* 23.9%

         \[\leadsto \color{blue}{b \cdot \left(\left(x \cdot y\right) \cdot a\right)} \]

      3. associate-*l* 25.8%

         \[\leadsto b \cdot \color{blue}{\left(x \cdot \left(y \cdot a\right)\right)} \]

   8. Simplified 25.8%

      \[\leadsto \color{blue}{b \cdot \left(x \cdot \left(y \cdot a\right)\right)} \]

   if 6.9999999999999998e-296 < j < 1.75000000000000017e-251

   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. Taylor expanded in k around inf 50.0%

      \[\leadsto \color{blue}{k \cdot \left(\left(-1 \cdot \left(y \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - -1 \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   3. Taylor expanded in y1 around inf 67.5%

      \[\leadsto \color{blue}{k \cdot \left(y1 \cdot \left(y2 \cdot y4 - i \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 67.2%

         \[\leadsto \color{blue}{\left(k \cdot y1\right) \cdot \left(y2 \cdot y4 - i \cdot z\right)} \]

      2. *-commutative 67.2%

         \[\leadsto \color{blue}{\left(y1 \cdot k\right)} \cdot \left(y2 \cdot y4 - i \cdot z\right) \]

      3. *-commutative 67.2%

         \[\leadsto \left(y1 \cdot k\right) \cdot \left(\color{blue}{y4 \cdot y2} - i \cdot z\right) \]

      4. *-commutative 67.2%

         \[\leadsto \left(y1 \cdot k\right) \cdot \left(y4 \cdot y2 - \color{blue}{z \cdot i}\right) \]

   5. Simplified 67.2%

      \[\leadsto \color{blue}{\left(y1 \cdot k\right) \cdot \left(y4 \cdot y2 - z \cdot i\right)} \]

   6. Taylor expanded in y4 around inf 67.5%

      \[\leadsto \color{blue}{k \cdot \left(y1 \cdot \left(y2 \cdot y4\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 67.5%

         \[\leadsto k \cdot \color{blue}{\left(\left(y2 \cdot y4\right) \cdot y1\right)} \]

      2. associate-*l* 68.0%

         \[\leadsto k \cdot \color{blue}{\left(y2 \cdot \left(y4 \cdot y1\right)\right)} \]

   8. Simplified 68.0%

      \[\leadsto \color{blue}{k \cdot \left(y2 \cdot \left(y4 \cdot y1\right)\right)} \]

   if 1.75000000000000017e-251 < j < 4.80000000000000007e-216

   1. Initial program 39.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 30.1%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 70.3%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 70.3%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 70.3%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 70.3%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 70.3%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 70.3%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   6. Taylor expanded in y around inf 60.5%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]

   if 4.80000000000000007e-216 < j < 6.5000000000000005e76

   1. Initial program 32.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 27.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in y5 around -inf 23.0%

      \[\leadsto \color{blue}{-1 \cdot \left(j \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)\right)\right)} \]
   4. Step-by-step derivation

      1. mul-1-neg 23.0%

         \[\leadsto \color{blue}{-j \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)\right)} \]

      2. associate-*r* 19.8%

         \[\leadsto -\color{blue}{\left(j \cdot y5\right) \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)} \]

      3. distribute-lft-neg-in 19.8%

         \[\leadsto \color{blue}{\left(-j \cdot y5\right) \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)} \]

      4. distribute-rgt-neg-in 19.8%

         \[\leadsto \color{blue}{\left(j \cdot \left(-y5\right)\right)} \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right) \]

      5. +-commutative 19.8%

         \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \color{blue}{\left(i \cdot t + -1 \cdot \left(y0 \cdot y3\right)\right)} \]

      6. mul-1-neg 19.8%

         \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \left(i \cdot t + \color{blue}{\left(-y0 \cdot y3\right)}\right) \]

      7. unsub-neg 19.8%

         \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \color{blue}{\left(i \cdot t - y0 \cdot y3\right)} \]

      8. *-commutative 19.8%

         \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \left(i \cdot t - \color{blue}{y3 \cdot y0}\right) \]

   5. Simplified 19.8%

      \[\leadsto \color{blue}{\left(j \cdot \left(-y5\right)\right) \cdot \left(i \cdot t - y3 \cdot y0\right)} \]

   6. Taylor expanded in i around 0 23.0%

      \[\leadsto \color{blue}{j \cdot \left(y0 \cdot \left(y3 \cdot y5\right)\right)} \]

   if 6.5000000000000005e76 < j

   1. Initial program 25.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 58.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in x around inf 46.0%

      \[\leadsto j \cdot \color{blue}{\left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 46.0%

         \[\leadsto j \cdot \color{blue}{\left(\left(i \cdot y1 - b \cdot y0\right) \cdot x\right)} \]

      2. *-commutative 46.0%

         \[\leadsto j \cdot \left(\left(\color{blue}{y1 \cdot i} - b \cdot y0\right) \cdot x\right) \]

      3. *-commutative 46.0%

         \[\leadsto j \cdot \left(\left(y1 \cdot i - \color{blue}{y0 \cdot b}\right) \cdot x\right) \]

   5. Simplified 46.0%

      \[\leadsto j \cdot \color{blue}{\left(\left(y1 \cdot i - y0 \cdot b\right) \cdot x\right)} \]

   6. Taylor expanded in y1 around inf 37.3%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(x \cdot y1\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 37.3%

         \[\leadsto i \cdot \left(j \cdot \color{blue}{\left(y1 \cdot x\right)}\right) \]

   8. Simplified 37.3%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(y1 \cdot x\right)\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 31.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;j \leq -5.7 \cdot 10^{+100}:\\ \;\;\;\;y0 \cdot \left(y3 \cdot \left(j \cdot y5\right)\right)\\ \mathbf{elif}\;j \leq 7 \cdot 10^{-296}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a\right)\right)\\ \mathbf{elif}\;j \leq 1.75 \cdot 10^{-251}:\\ \;\;\;\;k \cdot \left(y2 \cdot \left(y1 \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq 4.8 \cdot 10^{-216}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{elif}\;j \leq 6.5 \cdot 10^{+76}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \end{array} \]

Alternative 31: 22.0% accurate, 5.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y \leq -1.95 \cdot 10^{+32}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a\right)\right)\\ \mathbf{elif}\;y \leq -6.2 \cdot 10^{-181}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \mathbf{elif}\;y \leq 1.8 \cdot 10^{-206}:\\ \;\;\;\;b \cdot \left(a \cdot \left(z \cdot \left(-t\right)\right)\right)\\ \mathbf{elif}\;y \leq 5.4 \cdot 10^{+126}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(x \cdot \left(-j\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= y -1.95e+32)
   (* b (* x (* y a)))
   (if (<= y -6.2e-181)
     (* j (* y1 (* x i)))
     (if (<= y 1.8e-206)
       (* b (* a (* z (- t))))
       (if (<= y 5.4e+126) (* b (* y0 (* x (- j)))) (* a (* (* x y) b)))))))

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 <= -1.95e+32) {
		tmp = b * (x * (y * a));
	} else if (y <= -6.2e-181) {
		tmp = j * (y1 * (x * i));
	} else if (y <= 1.8e-206) {
		tmp = b * (a * (z * -t));
	} else if (y <= 5.4e+126) {
		tmp = b * (y0 * (x * -j));
	} else {
		tmp = a * ((x * y) * b);
	}
	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 <= (-1.95d+32)) then
        tmp = b * (x * (y * a))
    else if (y <= (-6.2d-181)) then
        tmp = j * (y1 * (x * i))
    else if (y <= 1.8d-206) then
        tmp = b * (a * (z * -t))
    else if (y <= 5.4d+126) then
        tmp = b * (y0 * (x * -j))
    else
        tmp = a * ((x * y) * b)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y <= -1.95e+32) {
		tmp = b * (x * (y * a));
	} else if (y <= -6.2e-181) {
		tmp = j * (y1 * (x * i));
	} else if (y <= 1.8e-206) {
		tmp = b * (a * (z * -t));
	} else if (y <= 5.4e+126) {
		tmp = b * (y0 * (x * -j));
	} else {
		tmp = a * ((x * y) * b);
	}
	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 <= -1.95e+32:
		tmp = b * (x * (y * a))
	elif y <= -6.2e-181:
		tmp = j * (y1 * (x * i))
	elif y <= 1.8e-206:
		tmp = b * (a * (z * -t))
	elif y <= 5.4e+126:
		tmp = b * (y0 * (x * -j))
	else:
		tmp = a * ((x * y) * b)
	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 <= -1.95e+32)
		tmp = Float64(b * Float64(x * Float64(y * a)));
	elseif (y <= -6.2e-181)
		tmp = Float64(j * Float64(y1 * Float64(x * i)));
	elseif (y <= 1.8e-206)
		tmp = Float64(b * Float64(a * Float64(z * Float64(-t))));
	elseif (y <= 5.4e+126)
		tmp = Float64(b * Float64(y0 * Float64(x * Float64(-j))));
	else
		tmp = Float64(a * Float64(Float64(x * y) * b));
	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 <= -1.95e+32)
		tmp = b * (x * (y * a));
	elseif (y <= -6.2e-181)
		tmp = j * (y1 * (x * i));
	elseif (y <= 1.8e-206)
		tmp = b * (a * (z * -t));
	elseif (y <= 5.4e+126)
		tmp = b * (y0 * (x * -j));
	else
		tmp = a * ((x * y) * b);
	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, -1.95e+32], N[(b * N[(x * N[(y * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -6.2e-181], N[(j * N[(y1 * N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 1.8e-206], N[(b * N[(a * N[(z * (-t)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 5.4e+126], N[(b * N[(y0 * N[(x * (-j)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(a * N[(N[(x * y), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

1. Split input into 5 regimes

2. if y < -1.95e32

   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. Taylor expanded in b around inf 36.7%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 37.2%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 37.2%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 37.2%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 37.2%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 37.2%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 37.2%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   6. Taylor expanded in y around inf 27.3%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 27.3%

         \[\leadsto \color{blue}{\left(b \cdot \left(x \cdot y\right)\right) \cdot a} \]

      2. associate-*l* 28.9%

         \[\leadsto \color{blue}{b \cdot \left(\left(x \cdot y\right) \cdot a\right)} \]

      3. associate-*l* 38.8%

         \[\leadsto b \cdot \color{blue}{\left(x \cdot \left(y \cdot a\right)\right)} \]

   8. Simplified 38.8%

      \[\leadsto \color{blue}{b \cdot \left(x \cdot \left(y \cdot a\right)\right)} \]

   if -1.95e32 < y < -6.20000000000000043e-181

   1. Initial program 39.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 46.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in x around inf 40.2%

      \[\leadsto j \cdot \color{blue}{\left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 40.2%

         \[\leadsto j \cdot \color{blue}{\left(\left(i \cdot y1 - b \cdot y0\right) \cdot x\right)} \]

      2. *-commutative 40.2%

         \[\leadsto j \cdot \left(\left(\color{blue}{y1 \cdot i} - b \cdot y0\right) \cdot x\right) \]

      3. *-commutative 40.2%

         \[\leadsto j \cdot \left(\left(y1 \cdot i - \color{blue}{y0 \cdot b}\right) \cdot x\right) \]

   5. Simplified 40.2%

      \[\leadsto j \cdot \color{blue}{\left(\left(y1 \cdot i - y0 \cdot b\right) \cdot x\right)} \]

   6. Taylor expanded in y1 around inf 33.5%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(x \cdot y1\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 33.5%

         \[\leadsto \color{blue}{\left(j \cdot \left(x \cdot y1\right)\right) \cdot i} \]

      2. associate-*l* 31.3%

         \[\leadsto \color{blue}{j \cdot \left(\left(x \cdot y1\right) \cdot i\right)} \]

      3. *-commutative 31.3%

         \[\leadsto j \cdot \left(\color{blue}{\left(y1 \cdot x\right)} \cdot i\right) \]

      4. associate-*l* 35.8%

         \[\leadsto j \cdot \color{blue}{\left(y1 \cdot \left(x \cdot i\right)\right)} \]

   8. Simplified 35.8%

      \[\leadsto \color{blue}{j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)} \]

   if -6.20000000000000043e-181 < y < 1.79999999999999997e-206

   1. Initial program 46.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 46.8%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 30.0%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 30.0%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 30.0%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 30.0%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 30.0%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 30.0%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   6. Taylor expanded in y around 0 30.1%

      \[\leadsto b \cdot \color{blue}{\left(-1 \cdot \left(a \cdot \left(t \cdot z\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 30.1%

         \[\leadsto b \cdot \color{blue}{\left(-a \cdot \left(t \cdot z\right)\right)} \]

      2. *-commutative 30.1%

         \[\leadsto b \cdot \left(-a \cdot \color{blue}{\left(z \cdot t\right)}\right) \]

      3. *-commutative 30.1%

         \[\leadsto b \cdot \left(-\color{blue}{\left(z \cdot t\right) \cdot a}\right) \]

      4. distribute-rgt-neg-in 30.1%

         \[\leadsto b \cdot \color{blue}{\left(\left(z \cdot t\right) \cdot \left(-a\right)\right)} \]

   8. Simplified 30.1%

      \[\leadsto b \cdot \color{blue}{\left(\left(z \cdot t\right) \cdot \left(-a\right)\right)} \]

   if 1.79999999999999997e-206 < y < 5.40000000000000005e126

   1. Initial program 24.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 39.6%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in x around inf 32.7%

      \[\leadsto j \cdot \color{blue}{\left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 32.7%

         \[\leadsto j \cdot \color{blue}{\left(\left(i \cdot y1 - b \cdot y0\right) \cdot x\right)} \]

      2. *-commutative 32.7%

         \[\leadsto j \cdot \left(\left(\color{blue}{y1 \cdot i} - b \cdot y0\right) \cdot x\right) \]

      3. *-commutative 32.7%

         \[\leadsto j \cdot \left(\left(y1 \cdot i - \color{blue}{y0 \cdot b}\right) \cdot x\right) \]

   5. Simplified 32.7%

      \[\leadsto j \cdot \color{blue}{\left(\left(y1 \cdot i - y0 \cdot b\right) \cdot x\right)} \]

   6. Taylor expanded in y1 around 0 22.9%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(j \cdot \left(x \cdot y0\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 22.9%

         \[\leadsto \color{blue}{-b \cdot \left(j \cdot \left(x \cdot y0\right)\right)} \]

      2. distribute-rgt-neg-in 22.9%

         \[\leadsto \color{blue}{b \cdot \left(-j \cdot \left(x \cdot y0\right)\right)} \]

      3. associate-*r* 25.7%

         \[\leadsto b \cdot \left(-\color{blue}{\left(j \cdot x\right) \cdot y0}\right) \]

      4. *-commutative 25.7%

         \[\leadsto b \cdot \left(-\color{blue}{y0 \cdot \left(j \cdot x\right)}\right) \]

   8. Simplified 25.7%

      \[\leadsto \color{blue}{b \cdot \left(-y0 \cdot \left(j \cdot x\right)\right)} \]

   if 5.40000000000000005e126 < y

   1. Initial program 24.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 33.1%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 46.9%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 46.9%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 46.9%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 46.9%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 46.9%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 46.9%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   6. Taylor expanded in y around inf 44.2%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 33.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y \leq -1.95 \cdot 10^{+32}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a\right)\right)\\ \mathbf{elif}\;y \leq -6.2 \cdot 10^{-181}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i\right)\right)\\ \mathbf{elif}\;y \leq 1.8 \cdot 10^{-206}:\\ \;\;\;\;b \cdot \left(a \cdot \left(z \cdot \left(-t\right)\right)\right)\\ \mathbf{elif}\;y \leq 5.4 \cdot 10^{+126}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(x \cdot \left(-j\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \end{array} \]

Alternative 32: 22.2% accurate, 6.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ t_2 := b \cdot \left(x \cdot \left(y \cdot a\right)\right)\\ \mathbf{if}\;t \leq -5.8 \cdot 10^{-14}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq 7.6 \cdot 10^{-151}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t \leq 8.5 \cdot 10^{-43}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq 1.9 \cdot 10^{+37}:\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* j (* t y4)))) (t_2 (* b (* x (* y a)))))
   (if (<= t -5.8e-14)
     t_1
     (if (<= t 7.6e-151)
       t_2
       (if (<= t 8.5e-43)
         (* j (* y0 (* y3 y5)))
         (if (<= t 1.9e+37) 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 = b * (j * (t * y4));
	double t_2 = b * (x * (y * a));
	double tmp;
	if (t <= -5.8e-14) {
		tmp = t_1;
	} else if (t <= 7.6e-151) {
		tmp = t_2;
	} else if (t <= 8.5e-43) {
		tmp = j * (y0 * (y3 * y5));
	} else if (t <= 1.9e+37) {
		tmp = t_2;
	} 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 = b * (j * (t * y4))
    t_2 = b * (x * (y * a))
    if (t <= (-5.8d-14)) then
        tmp = t_1
    else if (t <= 7.6d-151) then
        tmp = t_2
    else if (t <= 8.5d-43) then
        tmp = j * (y0 * (y3 * y5))
    else if (t <= 1.9d+37) then
        tmp = t_2
    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 = b * (j * (t * y4));
	double t_2 = b * (x * (y * a));
	double tmp;
	if (t <= -5.8e-14) {
		tmp = t_1;
	} else if (t <= 7.6e-151) {
		tmp = t_2;
	} else if (t <= 8.5e-43) {
		tmp = j * (y0 * (y3 * y5));
	} else if (t <= 1.9e+37) {
		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 = b * (j * (t * y4))
	t_2 = b * (x * (y * a))
	tmp = 0
	if t <= -5.8e-14:
		tmp = t_1
	elif t <= 7.6e-151:
		tmp = t_2
	elif t <= 8.5e-43:
		tmp = j * (y0 * (y3 * y5))
	elif t <= 1.9e+37:
		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(b * Float64(j * Float64(t * y4)))
	t_2 = Float64(b * Float64(x * Float64(y * a)))
	tmp = 0.0
	if (t <= -5.8e-14)
		tmp = t_1;
	elseif (t <= 7.6e-151)
		tmp = t_2;
	elseif (t <= 8.5e-43)
		tmp = Float64(j * Float64(y0 * Float64(y3 * y5)));
	elseif (t <= 1.9e+37)
		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 = b * (j * (t * y4));
	t_2 = b * (x * (y * a));
	tmp = 0.0;
	if (t <= -5.8e-14)
		tmp = t_1;
	elseif (t <= 7.6e-151)
		tmp = t_2;
	elseif (t <= 8.5e-43)
		tmp = j * (y0 * (y3 * y5));
	elseif (t <= 1.9e+37)
		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[(b * N[(j * N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(b * N[(x * N[(y * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -5.8e-14], t$95$1, If[LessEqual[t, 7.6e-151], t$95$2, If[LessEqual[t, 8.5e-43], N[(j * N[(y0 * N[(y3 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.9e+37], t$95$2, t$95$1]]]]]]

Derivation

1. Split input into 3 regimes

2. if t < -5.8000000000000005e-14 or 1.89999999999999995e37 < t

   1. Initial program 29.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 40.6%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in y4 around inf 32.7%

      \[\leadsto \color{blue}{j \cdot \left(y4 \cdot \left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 32.7%

         \[\leadsto j \cdot \color{blue}{\left(\left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right) \cdot y4\right)} \]

      2. +-commutative 32.7%

         \[\leadsto j \cdot \left(\color{blue}{\left(b \cdot t + -1 \cdot \left(y1 \cdot y3\right)\right)} \cdot y4\right) \]

      3. mul-1-neg 32.7%

         \[\leadsto j \cdot \left(\left(b \cdot t + \color{blue}{\left(-y1 \cdot y3\right)}\right) \cdot y4\right) \]

      4. unsub-neg 32.7%

         \[\leadsto j \cdot \left(\color{blue}{\left(b \cdot t - y1 \cdot y3\right)} \cdot y4\right) \]

      5. *-commutative 32.7%

         \[\leadsto j \cdot \left(\left(b \cdot t - \color{blue}{y3 \cdot y1}\right) \cdot y4\right) \]

   5. Simplified 32.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(b \cdot t - y3 \cdot y1\right) \cdot y4\right)} \]

   6. Taylor expanded in b around inf 29.7%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]

   if -5.8000000000000005e-14 < t < 7.5999999999999994e-151 or 8.50000000000000056e-43 < t < 1.89999999999999995e37

   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. Taylor expanded in b around inf 42.5%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 27.7%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 27.7%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 27.7%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 27.7%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 27.7%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 27.7%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   6. Taylor expanded in y around inf 21.6%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 21.6%

         \[\leadsto \color{blue}{\left(b \cdot \left(x \cdot y\right)\right) \cdot a} \]

      2. associate-*l* 25.9%

         \[\leadsto \color{blue}{b \cdot \left(\left(x \cdot y\right) \cdot a\right)} \]

      3. associate-*l* 28.5%

         \[\leadsto b \cdot \color{blue}{\left(x \cdot \left(y \cdot a\right)\right)} \]

   8. Simplified 28.5%

      \[\leadsto \color{blue}{b \cdot \left(x \cdot \left(y \cdot a\right)\right)} \]

   if 7.5999999999999994e-151 < t < 8.50000000000000056e-43

   1. Initial program 53.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 35.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in y5 around -inf 53.7%

      \[\leadsto \color{blue}{-1 \cdot \left(j \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)\right)\right)} \]
   4. Step-by-step derivation

      1. mul-1-neg 53.7%

         \[\leadsto \color{blue}{-j \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)\right)} \]

      2. associate-*r* 53.7%

         \[\leadsto -\color{blue}{\left(j \cdot y5\right) \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)} \]

      3. distribute-lft-neg-in 53.7%

         \[\leadsto \color{blue}{\left(-j \cdot y5\right) \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)} \]

      4. distribute-rgt-neg-in 53.7%

         \[\leadsto \color{blue}{\left(j \cdot \left(-y5\right)\right)} \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right) \]

      5. +-commutative 53.7%

         \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \color{blue}{\left(i \cdot t + -1 \cdot \left(y0 \cdot y3\right)\right)} \]

      6. mul-1-neg 53.7%

         \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \left(i \cdot t + \color{blue}{\left(-y0 \cdot y3\right)}\right) \]

      7. unsub-neg 53.7%

         \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \color{blue}{\left(i \cdot t - y0 \cdot y3\right)} \]

      8. *-commutative 53.7%

         \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \left(i \cdot t - \color{blue}{y3 \cdot y0}\right) \]

   5. Simplified 53.7%

      \[\leadsto \color{blue}{\left(j \cdot \left(-y5\right)\right) \cdot \left(i \cdot t - y3 \cdot y0\right)} \]

   6. Taylor expanded in i around 0 43.1%

      \[\leadsto \color{blue}{j \cdot \left(y0 \cdot \left(y3 \cdot y5\right)\right)} \]
3. Recombined 3 regimes into one program.

4. Final simplification 30.1%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -5.8 \cdot 10^{-14}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{elif}\;t \leq 7.6 \cdot 10^{-151}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a\right)\right)\\ \mathbf{elif}\;t \leq 8.5 \cdot 10^{-43}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq 1.9 \cdot 10^{+37}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \end{array} \]

Alternative 33: 21.9% accurate, 6.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(x \cdot \left(y \cdot a\right)\right)\\ \mathbf{if}\;a \leq -5 \cdot 10^{+51}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -1.4 \cdot 10^{-133}:\\ \;\;\;\;\left(j \cdot \left(-y5\right)\right) \cdot \left(t \cdot i\right)\\ \mathbf{elif}\;a \leq 2.8 \cdot 10^{-57}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{elif}\;a \leq 1.1 \cdot 10^{+89}:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* x (* y a)))))
   (if (<= a -5e+51)
     t_1
     (if (<= a -1.4e-133)
       (* (* j (- y5)) (* t i))
       (if (<= a 2.8e-57)
         (* b (* k (* z y0)))
         (if (<= a 1.1e+89) (* i (* j (* x 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 = b * (x * (y * a));
	double tmp;
	if (a <= -5e+51) {
		tmp = t_1;
	} else if (a <= -1.4e-133) {
		tmp = (j * -y5) * (t * i);
	} else if (a <= 2.8e-57) {
		tmp = b * (k * (z * y0));
	} else if (a <= 1.1e+89) {
		tmp = i * (j * (x * 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 = b * (x * (y * a))
    if (a <= (-5d+51)) then
        tmp = t_1
    else if (a <= (-1.4d-133)) then
        tmp = (j * -y5) * (t * i)
    else if (a <= 2.8d-57) then
        tmp = b * (k * (z * y0))
    else if (a <= 1.1d+89) then
        tmp = i * (j * (x * 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 = b * (x * (y * a));
	double tmp;
	if (a <= -5e+51) {
		tmp = t_1;
	} else if (a <= -1.4e-133) {
		tmp = (j * -y5) * (t * i);
	} else if (a <= 2.8e-57) {
		tmp = b * (k * (z * y0));
	} else if (a <= 1.1e+89) {
		tmp = i * (j * (x * 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 = b * (x * (y * a))
	tmp = 0
	if a <= -5e+51:
		tmp = t_1
	elif a <= -1.4e-133:
		tmp = (j * -y5) * (t * i)
	elif a <= 2.8e-57:
		tmp = b * (k * (z * y0))
	elif a <= 1.1e+89:
		tmp = i * (j * (x * 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(b * Float64(x * Float64(y * a)))
	tmp = 0.0
	if (a <= -5e+51)
		tmp = t_1;
	elseif (a <= -1.4e-133)
		tmp = Float64(Float64(j * Float64(-y5)) * Float64(t * i));
	elseif (a <= 2.8e-57)
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	elseif (a <= 1.1e+89)
		tmp = Float64(i * Float64(j * Float64(x * 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 = b * (x * (y * a));
	tmp = 0.0;
	if (a <= -5e+51)
		tmp = t_1;
	elseif (a <= -1.4e-133)
		tmp = (j * -y5) * (t * i);
	elseif (a <= 2.8e-57)
		tmp = b * (k * (z * y0));
	elseif (a <= 1.1e+89)
		tmp = i * (j * (x * 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[(b * N[(x * N[(y * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -5e+51], t$95$1, If[LessEqual[a, -1.4e-133], N[(N[(j * (-y5)), $MachinePrecision] * N[(t * i), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 2.8e-57], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 1.1e+89], N[(i * N[(j * N[(x * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]

Derivation

1. Split input into 4 regimes

2. if a < -5e51 or 1.1e89 < a

   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. Taylor expanded in b around inf 38.5%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 49.8%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 49.8%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 49.8%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 49.8%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 49.8%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 49.8%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   6. Taylor expanded in y around inf 27.4%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 27.4%

         \[\leadsto \color{blue}{\left(b \cdot \left(x \cdot y\right)\right) \cdot a} \]

      2. associate-*l* 32.0%

         \[\leadsto \color{blue}{b \cdot \left(\left(x \cdot y\right) \cdot a\right)} \]

      3. associate-*l* 38.5%

         \[\leadsto b \cdot \color{blue}{\left(x \cdot \left(y \cdot a\right)\right)} \]

   8. Simplified 38.5%

      \[\leadsto \color{blue}{b \cdot \left(x \cdot \left(y \cdot a\right)\right)} \]

   if -5e51 < a < -1.3999999999999999e-133

   1. Initial program 47.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 42.2%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in y5 around -inf 39.1%

      \[\leadsto \color{blue}{-1 \cdot \left(j \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)\right)\right)} \]
   4. Step-by-step derivation

      1. mul-1-neg 39.1%

         \[\leadsto \color{blue}{-j \cdot \left(y5 \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)\right)} \]

      2. associate-*r* 36.5%

         \[\leadsto -\color{blue}{\left(j \cdot y5\right) \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)} \]

      3. distribute-lft-neg-in 36.5%

         \[\leadsto \color{blue}{\left(-j \cdot y5\right) \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)} \]

      4. distribute-rgt-neg-in 36.5%

         \[\leadsto \color{blue}{\left(j \cdot \left(-y5\right)\right)} \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right) \]

      5. +-commutative 36.5%

         \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \color{blue}{\left(i \cdot t + -1 \cdot \left(y0 \cdot y3\right)\right)} \]

      6. mul-1-neg 36.5%

         \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \left(i \cdot t + \color{blue}{\left(-y0 \cdot y3\right)}\right) \]

      7. unsub-neg 36.5%

         \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \color{blue}{\left(i \cdot t - y0 \cdot y3\right)} \]

      8. *-commutative 36.5%

         \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \left(i \cdot t - \color{blue}{y3 \cdot y0}\right) \]

   5. Simplified 36.5%

      \[\leadsto \color{blue}{\left(j \cdot \left(-y5\right)\right) \cdot \left(i \cdot t - y3 \cdot y0\right)} \]

   6. Taylor expanded in i around inf 30.7%

      \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \color{blue}{\left(i \cdot t\right)} \]
   7. Step-by-step derivation

      1. *-commutative 30.7%

         \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \color{blue}{\left(t \cdot i\right)} \]

   8. Simplified 30.7%

      \[\leadsto \left(j \cdot \left(-y5\right)\right) \cdot \color{blue}{\left(t \cdot i\right)} \]

   if -1.3999999999999999e-133 < a < 2.7999999999999999e-57

   1. Initial program 30.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in z around -inf 48.9%

      \[\leadsto \color{blue}{-1 \cdot \left(z \cdot \left(\left(t \cdot \left(a \cdot b - c \cdot i\right) + y3 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - k \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]

   3. Taylor expanded in y0 around inf 34.6%

      \[\leadsto -1 \cdot \color{blue}{\left(y0 \cdot \left(z \cdot \left(c \cdot y3 - b \cdot k\right)\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 34.3%

         \[\leadsto -1 \cdot \color{blue}{\left(\left(y0 \cdot z\right) \cdot \left(c \cdot y3 - b \cdot k\right)\right)} \]

      2. *-commutative 34.3%

         \[\leadsto -1 \cdot \left(\color{blue}{\left(z \cdot y0\right)} \cdot \left(c \cdot y3 - b \cdot k\right)\right) \]

      3. *-commutative 34.3%

         \[\leadsto -1 \cdot \left(\left(z \cdot y0\right) \cdot \left(\color{blue}{y3 \cdot c} - b \cdot k\right)\right) \]

      4. *-commutative 34.3%

         \[\leadsto -1 \cdot \left(\left(z \cdot y0\right) \cdot \left(y3 \cdot c - \color{blue}{k \cdot b}\right)\right) \]

   5. Simplified 34.3%

      \[\leadsto -1 \cdot \color{blue}{\left(\left(z \cdot y0\right) \cdot \left(y3 \cdot c - k \cdot b\right)\right)} \]

   6. Taylor expanded in y3 around 0 34.2%

      \[\leadsto -1 \cdot \color{blue}{\left(-1 \cdot \left(b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 34.2%

         \[\leadsto -1 \cdot \color{blue}{\left(\left(-1 \cdot b\right) \cdot \left(k \cdot \left(y0 \cdot z\right)\right)\right)} \]

      2. neg-mul-1 34.2%

         \[\leadsto -1 \cdot \left(\color{blue}{\left(-b\right)} \cdot \left(k \cdot \left(y0 \cdot z\right)\right)\right) \]

   8. Simplified 34.2%

      \[\leadsto -1 \cdot \color{blue}{\left(\left(-b\right) \cdot \left(k \cdot \left(y0 \cdot z\right)\right)\right)} \]

   if 2.7999999999999999e-57 < a < 1.1e89

   1. Initial program 25.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 37.3%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in x around inf 29.8%

      \[\leadsto j \cdot \color{blue}{\left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 29.8%

         \[\leadsto j \cdot \color{blue}{\left(\left(i \cdot y1 - b \cdot y0\right) \cdot x\right)} \]

      2. *-commutative 29.8%

         \[\leadsto j \cdot \left(\left(\color{blue}{y1 \cdot i} - b \cdot y0\right) \cdot x\right) \]

      3. *-commutative 29.8%

         \[\leadsto j \cdot \left(\left(y1 \cdot i - \color{blue}{y0 \cdot b}\right) \cdot x\right) \]

   5. Simplified 29.8%

      \[\leadsto j \cdot \color{blue}{\left(\left(y1 \cdot i - y0 \cdot b\right) \cdot x\right)} \]

   6. Taylor expanded in y1 around inf 29.7%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(x \cdot y1\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 29.7%

         \[\leadsto i \cdot \left(j \cdot \color{blue}{\left(y1 \cdot x\right)}\right) \]

   8. Simplified 29.7%

      \[\leadsto \color{blue}{i \cdot \left(j \cdot \left(y1 \cdot x\right)\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 34.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;a \leq -5 \cdot 10^{+51}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a\right)\right)\\ \mathbf{elif}\;a \leq -1.4 \cdot 10^{-133}:\\ \;\;\;\;\left(j \cdot \left(-y5\right)\right) \cdot \left(t \cdot i\right)\\ \mathbf{elif}\;a \leq 2.8 \cdot 10^{-57}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{elif}\;a \leq 1.1 \cdot 10^{+89}:\\ \;\;\;\;i \cdot \left(j \cdot \left(x \cdot y1\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a\right)\right)\\ \end{array} \]

Alternative 34: 21.2% accurate, 8.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;t \leq -6.1 \cdot 10^{-12} \lor \neg \left(t \leq 2.8 \cdot 10^{+215}\right):\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (or (<= t -6.1e-12) (not (<= t 2.8e+215)))
   (* b (* j (* t y4)))
   (* a (* (* x y) b))))

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 <= -6.1e-12) || !(t <= 2.8e+215)) {
		tmp = b * (j * (t * y4));
	} else {
		tmp = a * ((x * y) * b);
	}
	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 <= (-6.1d-12)) .or. (.not. (t <= 2.8d+215))) then
        tmp = b * (j * (t * y4))
    else
        tmp = a * ((x * y) * b)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if ((t <= -6.1e-12) || !(t <= 2.8e+215)) {
		tmp = b * (j * (t * y4));
	} else {
		tmp = a * ((x * y) * b);
	}
	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 <= -6.1e-12) or not (t <= 2.8e+215):
		tmp = b * (j * (t * y4))
	else:
		tmp = a * ((x * y) * b)
	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 <= -6.1e-12) || !(t <= 2.8e+215))
		tmp = Float64(b * Float64(j * Float64(t * y4)));
	else
		tmp = Float64(a * Float64(Float64(x * y) * b));
	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 <= -6.1e-12) || ~((t <= 2.8e+215)))
		tmp = b * (j * (t * y4));
	else
		tmp = a * ((x * y) * b);
	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, -6.1e-12], N[Not[LessEqual[t, 2.8e+215]], $MachinePrecision]], N[(b * N[(j * N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(a * N[(N[(x * y), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if t < -6.1000000000000003e-12 or 2.8e215 < t

   1. Initial program 29.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 41.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in y4 around inf 36.0%

      \[\leadsto \color{blue}{j \cdot \left(y4 \cdot \left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 36.0%

         \[\leadsto j \cdot \color{blue}{\left(\left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right) \cdot y4\right)} \]

      2. +-commutative 36.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(b \cdot t + -1 \cdot \left(y1 \cdot y3\right)\right)} \cdot y4\right) \]

      3. mul-1-neg 36.0%

         \[\leadsto j \cdot \left(\left(b \cdot t + \color{blue}{\left(-y1 \cdot y3\right)}\right) \cdot y4\right) \]

      4. unsub-neg 36.0%

         \[\leadsto j \cdot \left(\color{blue}{\left(b \cdot t - y1 \cdot y3\right)} \cdot y4\right) \]

      5. *-commutative 36.0%

         \[\leadsto j \cdot \left(\left(b \cdot t - \color{blue}{y3 \cdot y1}\right) \cdot y4\right) \]

   5. Simplified 36.0%

      \[\leadsto \color{blue}{j \cdot \left(\left(b \cdot t - y3 \cdot y1\right) \cdot y4\right)} \]

   6. Taylor expanded in b around inf 36.0%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]

   if -6.1000000000000003e-12 < t < 2.8e215

   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. Taylor expanded in b around inf 39.6%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 27.2%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 27.2%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 27.2%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 27.2%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 27.2%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 27.2%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   6. Taylor expanded in y around inf 18.9%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]
3. Recombined 2 regimes into one program.

4. Final simplification 25.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -6.1 \cdot 10^{-12} \lor \neg \left(t \leq 2.8 \cdot 10^{+215}\right):\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \end{array} \]

Alternative 35: 22.4% accurate, 8.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;t \leq -6.2 \cdot 10^{-14} \lor \neg \left(t \leq 1.1 \cdot 10^{+42}\right):\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (or (<= t -6.2e-14) (not (<= t 1.1e+42)))
   (* b (* j (* t y4)))
   (* b (* x (* y a)))))

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 <= -6.2e-14) || !(t <= 1.1e+42)) {
		tmp = b * (j * (t * y4));
	} else {
		tmp = b * (x * (y * a));
	}
	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 <= (-6.2d-14)) .or. (.not. (t <= 1.1d+42))) then
        tmp = b * (j * (t * y4))
    else
        tmp = b * (x * (y * a))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if ((t <= -6.2e-14) || !(t <= 1.1e+42)) {
		tmp = b * (j * (t * y4));
	} else {
		tmp = b * (x * (y * a));
	}
	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 <= -6.2e-14) or not (t <= 1.1e+42):
		tmp = b * (j * (t * y4))
	else:
		tmp = b * (x * (y * a))
	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 <= -6.2e-14) || !(t <= 1.1e+42))
		tmp = Float64(b * Float64(j * Float64(t * y4)));
	else
		tmp = Float64(b * Float64(x * Float64(y * a)));
	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 <= -6.2e-14) || ~((t <= 1.1e+42)))
		tmp = b * (j * (t * y4));
	else
		tmp = b * (x * (y * a));
	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, -6.2e-14], N[Not[LessEqual[t, 1.1e+42]], $MachinePrecision]], N[(b * N[(j * N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(x * N[(y * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if t < -6.20000000000000009e-14 or 1.1000000000000001e42 < t

   1. Initial program 29.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 40.9%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]

   3. Taylor expanded in y4 around inf 32.9%

      \[\leadsto \color{blue}{j \cdot \left(y4 \cdot \left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 32.9%

         \[\leadsto j \cdot \color{blue}{\left(\left(-1 \cdot \left(y1 \cdot y3\right) + b \cdot t\right) \cdot y4\right)} \]

      2. +-commutative 32.9%

         \[\leadsto j \cdot \left(\color{blue}{\left(b \cdot t + -1 \cdot \left(y1 \cdot y3\right)\right)} \cdot y4\right) \]

      3. mul-1-neg 32.9%

         \[\leadsto j \cdot \left(\left(b \cdot t + \color{blue}{\left(-y1 \cdot y3\right)}\right) \cdot y4\right) \]

      4. unsub-neg 32.9%

         \[\leadsto j \cdot \left(\color{blue}{\left(b \cdot t - y1 \cdot y3\right)} \cdot y4\right) \]

      5. *-commutative 32.9%

         \[\leadsto j \cdot \left(\left(b \cdot t - \color{blue}{y3 \cdot y1}\right) \cdot y4\right) \]

   5. Simplified 32.9%

      \[\leadsto \color{blue}{j \cdot \left(\left(b \cdot t - y3 \cdot y1\right) \cdot y4\right)} \]

   6. Taylor expanded in b around inf 29.9%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]

   if -6.20000000000000009e-14 < t < 1.1000000000000001e42

   1. Initial program 37.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 39.8%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 25.6%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
   4. Step-by-step derivation

      1. sub-neg 25.6%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

      2. *-commutative 25.6%

         \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

      3. sub-neg 25.6%

         \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

      4. *-commutative 25.6%

         \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

   5. Simplified 25.6%

      \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

   6. Taylor expanded in y around inf 20.4%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 20.4%

         \[\leadsto \color{blue}{\left(b \cdot \left(x \cdot y\right)\right) \cdot a} \]

      2. associate-*l* 24.1%

         \[\leadsto \color{blue}{b \cdot \left(\left(x \cdot y\right) \cdot a\right)} \]

      3. associate-*l* 26.3%

         \[\leadsto b \cdot \color{blue}{\left(x \cdot \left(y \cdot a\right)\right)} \]

   8. Simplified 26.3%

      \[\leadsto \color{blue}{b \cdot \left(x \cdot \left(y \cdot a\right)\right)} \]
3. Recombined 2 regimes into one program.

4. Final simplification 28.1%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -6.2 \cdot 10^{-14} \lor \neg \left(t \leq 1.1 \cdot 10^{+42}\right):\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a\right)\right)\\ \end{array} \]

Alternative 36: 17.0% accurate, 13.6× speedup

Math

\[\begin{array}{l} \\ a \cdot \left(\left(x \cdot y\right) \cdot b\right) \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (* a (* (* x y) b)))

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 * ((x * y) * b);
}

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 * ((x * y) * b)
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 * ((x * y) * b);
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	return a * ((x * y) * b)

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	return Float64(a * Float64(Float64(x * y) * b))
end

MATLAB

function tmp = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = a * ((x * y) * b);
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := N[(a * N[(N[(x * y), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 33.7%

   \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

2. Taylor expanded in b around inf 36.9%

   \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

3. Taylor expanded in a around inf 30.1%

   \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
4. Step-by-step derivation

   1. sub-neg 30.1%

      \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

   2. *-commutative 30.1%

      \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

   3. sub-neg 30.1%

      \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

   4. *-commutative 30.1%

      \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

5. Simplified 30.1%

   \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

6. Taylor expanded in y around inf 17.2%

   \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]

7. Final simplification 17.2%

   \[\leadsto a \cdot \left(\left(x \cdot y\right) \cdot b\right) \]

Alternative 37: 17.3% accurate, 13.6× speedup

Math

\[\begin{array}{l} \\ a \cdot \left(y \cdot \left(x \cdot b\right)\right) \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (* a (* y (* x b))))

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 * (y * (x * b));
}

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 * (y * (x * b))
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 * (y * (x * b));
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	return a * (y * (x * b))

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	return Float64(a * Float64(y * Float64(x * b)))
end

MATLAB

function tmp = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = a * (y * (x * b));
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := N[(a * N[(y * N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 33.7%

   \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

2. Taylor expanded in b around inf 36.9%

   \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

3. Taylor expanded in a around inf 30.1%

   \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(x \cdot y - t \cdot z\right)\right)} \]
4. Step-by-step derivation

   1. sub-neg 30.1%

      \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y + \left(-t \cdot z\right)\right)}\right) \]

   2. *-commutative 30.1%

      \[\leadsto b \cdot \left(a \cdot \left(x \cdot y + \left(-\color{blue}{z \cdot t}\right)\right)\right) \]

   3. sub-neg 30.1%

      \[\leadsto b \cdot \left(a \cdot \color{blue}{\left(x \cdot y - z \cdot t\right)}\right) \]

   4. *-commutative 30.1%

      \[\leadsto b \cdot \left(a \cdot \left(\color{blue}{y \cdot x} - z \cdot t\right)\right) \]

5. Simplified 30.1%

   \[\leadsto b \cdot \color{blue}{\left(a \cdot \left(y \cdot x - z \cdot t\right)\right)} \]

6. Taylor expanded in y around inf 17.2%

   \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]
7. Step-by-step derivation

   1. associate-*r* 17.6%

      \[\leadsto a \cdot \color{blue}{\left(\left(b \cdot x\right) \cdot y\right)} \]

   2. *-commutative 17.6%

      \[\leadsto a \cdot \left(\color{blue}{\left(x \cdot b\right)} \cdot y\right) \]

8. Simplified 17.6%

   \[\leadsto \color{blue}{a \cdot \left(\left(x \cdot b\right) \cdot y\right)} \]

9. Final simplification 17.6%

   \[\leadsto a \cdot \left(y \cdot \left(x \cdot b\right)\right) \]

Developer target: 27.4% accurate, 0.8× 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 2023293 
(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

  :herbie-target
  (if (< y4 -7.206256231996481e+60) (- (- (* (- (* 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)) (/ 1.0 (- (* y4 c) (* y5 a)))) (* (- (* y2 k) (* y3 j)) (- (* y4 y1) (* y5 y0))))) (if (< y4 -3.364603505246317e-66) (+ (- (- (- (* (* 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 -1.2000065055686116e-105) (+ (+ (- (* (- (* 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 6.718963124057495e-279) (+ (- (- (- (* (* 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 4.77962681403792e-222) (+ (+ (- (* (- (* 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 2.2852241541266835e-175) (+ (- (- (- (* (* 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)))))