Linear.Matrix:det44 from linear-1.19.1.3

Percentage Accurate: 30.1% → 42.5%

Time: 1.8min

Alternatives: 31

Speedup: 2.3×

• 89.0% of points produce a very large (infinite) output. You may want to add a precondition.

Specification

Math

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

FPCore

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

C

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

Fortran

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

Java

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

Python

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

Julia

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

MATLAB

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

Wolfram

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

Initial Program: 30.1% accurate, 1.0× speedup

Math

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

FPCore

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

C

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

Fortran

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

Java

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

Python

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

Julia

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

MATLAB

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

Wolfram

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

Alternative 1: 42.5% accurate, 1.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot y2 - z \cdot y3\\ t_2 := x \cdot j - z \cdot k\\ t_3 := y \cdot y3 - t \cdot y2\\ t_4 := y1 \cdot y4 - y0 \cdot y5\\ t_5 := j \cdot y3 - k \cdot y2\\ t_6 := z \cdot t - x \cdot y\\ t_7 := k \cdot y2 - j \cdot y3\\ t_8 := y \cdot k - t \cdot j\\ t_9 := i \cdot \left(y1 \cdot t\_2 + \left(c \cdot t\_6 + y5 \cdot t\_8\right)\right)\\ t_10 := b \cdot y0 - i \cdot y1\\ \mathbf{if}\;i \leq -6.8 \cdot 10^{+190}:\\ \;\;\;\;t\_9\\ \mathbf{elif}\;i \leq -4.5 \cdot 10^{+58}:\\ \;\;\;\;c \cdot \left(\left(i \cdot t\_6 + y0 \cdot t\_1\right) + y4 \cdot t\_3\right)\\ \mathbf{elif}\;i \leq -2.8 \cdot 10^{+39}:\\ \;\;\;\;\left(t \cdot b\right) \cdot \left(j \cdot y4 - z \cdot a\right)\\ \mathbf{elif}\;i \leq -4.2 \cdot 10^{-54}:\\ \;\;\;\;y1 \cdot \left(\left(a \cdot \left(z \cdot y3 - x \cdot y2\right) + y4 \cdot t\_7\right) + i \cdot t\_2\right)\\ \mathbf{elif}\;i \leq 5.5 \cdot 10^{-209}:\\ \;\;\;\;y2 \cdot \left(\left(k \cdot t\_4 + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;i \leq 2.5 \cdot 10^{-127}:\\ \;\;\;\;y0 \cdot \left(\left(y5 \cdot t\_5 + c \cdot t\_1\right) + b \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;i \leq 7.8 \cdot 10^{-59}:\\ \;\;\;\;k \cdot \left(z \cdot t\_10 + \left(y2 \cdot t\_4 + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\right)\\ \mathbf{elif}\;i \leq 6.9 \cdot 10^{+59}:\\ \;\;\;\;t\_7 \cdot t\_4 + j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - x \cdot t\_10\right)\\ \mathbf{elif}\;i \leq 2.45 \cdot 10^{+98}:\\ \;\;\;\;y5 \cdot \left(a \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(i \cdot t\_8 + y0 \cdot t\_5\right)\right)\\ \mathbf{elif}\;i \leq 2.55 \cdot 10^{+160}:\\ \;\;\;\;y4 \cdot \left(c \cdot t\_3 - \left(b \cdot t\_8 + y1 \cdot t\_5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_9\\ \end{array} \end{array} \]

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 (- (* x j) (* z k)))
        (t_3 (- (* y y3) (* t y2)))
        (t_4 (- (* y1 y4) (* y0 y5)))
        (t_5 (- (* j y3) (* k y2)))
        (t_6 (- (* z t) (* x y)))
        (t_7 (- (* k y2) (* j y3)))
        (t_8 (- (* y k) (* t j)))
        (t_9 (* i (+ (* y1 t_2) (+ (* c t_6) (* y5 t_8)))))
        (t_10 (- (* b y0) (* i y1))))
   (if (<= i -6.8e+190)
     t_9
     (if (<= i -4.5e+58)
       (* c (+ (+ (* i t_6) (* y0 t_1)) (* y4 t_3)))
       (if (<= i -2.8e+39)
         (* (* t b) (- (* j y4) (* z a)))
         (if (<= i -4.2e-54)
           (* y1 (+ (+ (* a (- (* z y3) (* x y2))) (* y4 t_7)) (* i t_2)))
           (if (<= i 5.5e-209)
             (*
              y2
              (+
               (+ (* k t_4) (* x (- (* c y0) (* a y1))))
               (* t (- (* a y5) (* c y4)))))
             (if (<= i 2.5e-127)
               (* y0 (+ (+ (* y5 t_5) (* c t_1)) (* b (- (* z k) (* x j)))))
               (if (<= i 7.8e-59)
                 (*
                  k
                  (+ (* z t_10) (+ (* y2 t_4) (* y (- (* i y5) (* b y4))))))
                 (if (<= i 6.9e+59)
                   (+
                    (* t_7 t_4)
                    (* j (- (* t (- (* b y4) (* i y5))) (* x t_10))))
                   (if (<= i 2.45e+98)
                     (*
                      y5
                      (+ (* a (- (* t y2) (* y y3))) (+ (* i t_8) (* y0 t_5))))
                     (if (<= i 2.55e+160)
                       (* y4 (- (* c t_3) (+ (* b t_8) (* y1 t_5))))
                       t_9))))))))))))

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 = (x * j) - (z * k);
	double t_3 = (y * y3) - (t * y2);
	double t_4 = (y1 * y4) - (y0 * y5);
	double t_5 = (j * y3) - (k * y2);
	double t_6 = (z * t) - (x * y);
	double t_7 = (k * y2) - (j * y3);
	double t_8 = (y * k) - (t * j);
	double t_9 = i * ((y1 * t_2) + ((c * t_6) + (y5 * t_8)));
	double t_10 = (b * y0) - (i * y1);
	double tmp;
	if (i <= -6.8e+190) {
		tmp = t_9;
	} else if (i <= -4.5e+58) {
		tmp = c * (((i * t_6) + (y0 * t_1)) + (y4 * t_3));
	} else if (i <= -2.8e+39) {
		tmp = (t * b) * ((j * y4) - (z * a));
	} else if (i <= -4.2e-54) {
		tmp = y1 * (((a * ((z * y3) - (x * y2))) + (y4 * t_7)) + (i * t_2));
	} else if (i <= 5.5e-209) {
		tmp = y2 * (((k * t_4) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))));
	} else if (i <= 2.5e-127) {
		tmp = y0 * (((y5 * t_5) + (c * t_1)) + (b * ((z * k) - (x * j))));
	} else if (i <= 7.8e-59) {
		tmp = k * ((z * t_10) + ((y2 * t_4) + (y * ((i * y5) - (b * y4)))));
	} else if (i <= 6.9e+59) {
		tmp = (t_7 * t_4) + (j * ((t * ((b * y4) - (i * y5))) - (x * t_10)));
	} else if (i <= 2.45e+98) {
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((i * t_8) + (y0 * t_5)));
	} else if (i <= 2.55e+160) {
		tmp = y4 * ((c * t_3) - ((b * t_8) + (y1 * t_5)));
	} else {
		tmp = t_9;
	}
	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_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 = (x * y2) - (z * y3)
    t_2 = (x * j) - (z * k)
    t_3 = (y * y3) - (t * y2)
    t_4 = (y1 * y4) - (y0 * y5)
    t_5 = (j * y3) - (k * y2)
    t_6 = (z * t) - (x * y)
    t_7 = (k * y2) - (j * y3)
    t_8 = (y * k) - (t * j)
    t_9 = i * ((y1 * t_2) + ((c * t_6) + (y5 * t_8)))
    t_10 = (b * y0) - (i * y1)
    if (i <= (-6.8d+190)) then
        tmp = t_9
    else if (i <= (-4.5d+58)) then
        tmp = c * (((i * t_6) + (y0 * t_1)) + (y4 * t_3))
    else if (i <= (-2.8d+39)) then
        tmp = (t * b) * ((j * y4) - (z * a))
    else if (i <= (-4.2d-54)) then
        tmp = y1 * (((a * ((z * y3) - (x * y2))) + (y4 * t_7)) + (i * t_2))
    else if (i <= 5.5d-209) then
        tmp = y2 * (((k * t_4) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))))
    else if (i <= 2.5d-127) then
        tmp = y0 * (((y5 * t_5) + (c * t_1)) + (b * ((z * k) - (x * j))))
    else if (i <= 7.8d-59) then
        tmp = k * ((z * t_10) + ((y2 * t_4) + (y * ((i * y5) - (b * y4)))))
    else if (i <= 6.9d+59) then
        tmp = (t_7 * t_4) + (j * ((t * ((b * y4) - (i * y5))) - (x * t_10)))
    else if (i <= 2.45d+98) then
        tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((i * t_8) + (y0 * t_5)))
    else if (i <= 2.55d+160) then
        tmp = y4 * ((c * t_3) - ((b * t_8) + (y1 * t_5)))
    else
        tmp = t_9
    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 = (x * j) - (z * k);
	double t_3 = (y * y3) - (t * y2);
	double t_4 = (y1 * y4) - (y0 * y5);
	double t_5 = (j * y3) - (k * y2);
	double t_6 = (z * t) - (x * y);
	double t_7 = (k * y2) - (j * y3);
	double t_8 = (y * k) - (t * j);
	double t_9 = i * ((y1 * t_2) + ((c * t_6) + (y5 * t_8)));
	double t_10 = (b * y0) - (i * y1);
	double tmp;
	if (i <= -6.8e+190) {
		tmp = t_9;
	} else if (i <= -4.5e+58) {
		tmp = c * (((i * t_6) + (y0 * t_1)) + (y4 * t_3));
	} else if (i <= -2.8e+39) {
		tmp = (t * b) * ((j * y4) - (z * a));
	} else if (i <= -4.2e-54) {
		tmp = y1 * (((a * ((z * y3) - (x * y2))) + (y4 * t_7)) + (i * t_2));
	} else if (i <= 5.5e-209) {
		tmp = y2 * (((k * t_4) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))));
	} else if (i <= 2.5e-127) {
		tmp = y0 * (((y5 * t_5) + (c * t_1)) + (b * ((z * k) - (x * j))));
	} else if (i <= 7.8e-59) {
		tmp = k * ((z * t_10) + ((y2 * t_4) + (y * ((i * y5) - (b * y4)))));
	} else if (i <= 6.9e+59) {
		tmp = (t_7 * t_4) + (j * ((t * ((b * y4) - (i * y5))) - (x * t_10)));
	} else if (i <= 2.45e+98) {
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((i * t_8) + (y0 * t_5)));
	} else if (i <= 2.55e+160) {
		tmp = y4 * ((c * t_3) - ((b * t_8) + (y1 * t_5)));
	} else {
		tmp = t_9;
	}
	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 = (x * j) - (z * k)
	t_3 = (y * y3) - (t * y2)
	t_4 = (y1 * y4) - (y0 * y5)
	t_5 = (j * y3) - (k * y2)
	t_6 = (z * t) - (x * y)
	t_7 = (k * y2) - (j * y3)
	t_8 = (y * k) - (t * j)
	t_9 = i * ((y1 * t_2) + ((c * t_6) + (y5 * t_8)))
	t_10 = (b * y0) - (i * y1)
	tmp = 0
	if i <= -6.8e+190:
		tmp = t_9
	elif i <= -4.5e+58:
		tmp = c * (((i * t_6) + (y0 * t_1)) + (y4 * t_3))
	elif i <= -2.8e+39:
		tmp = (t * b) * ((j * y4) - (z * a))
	elif i <= -4.2e-54:
		tmp = y1 * (((a * ((z * y3) - (x * y2))) + (y4 * t_7)) + (i * t_2))
	elif i <= 5.5e-209:
		tmp = y2 * (((k * t_4) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))))
	elif i <= 2.5e-127:
		tmp = y0 * (((y5 * t_5) + (c * t_1)) + (b * ((z * k) - (x * j))))
	elif i <= 7.8e-59:
		tmp = k * ((z * t_10) + ((y2 * t_4) + (y * ((i * y5) - (b * y4)))))
	elif i <= 6.9e+59:
		tmp = (t_7 * t_4) + (j * ((t * ((b * y4) - (i * y5))) - (x * t_10)))
	elif i <= 2.45e+98:
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((i * t_8) + (y0 * t_5)))
	elif i <= 2.55e+160:
		tmp = y4 * ((c * t_3) - ((b * t_8) + (y1 * t_5)))
	else:
		tmp = t_9
	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(x * j) - Float64(z * k))
	t_3 = Float64(Float64(y * y3) - Float64(t * y2))
	t_4 = Float64(Float64(y1 * y4) - Float64(y0 * y5))
	t_5 = Float64(Float64(j * y3) - Float64(k * y2))
	t_6 = Float64(Float64(z * t) - Float64(x * y))
	t_7 = Float64(Float64(k * y2) - Float64(j * y3))
	t_8 = Float64(Float64(y * k) - Float64(t * j))
	t_9 = Float64(i * Float64(Float64(y1 * t_2) + Float64(Float64(c * t_6) + Float64(y5 * t_8))))
	t_10 = Float64(Float64(b * y0) - Float64(i * y1))
	tmp = 0.0
	if (i <= -6.8e+190)
		tmp = t_9;
	elseif (i <= -4.5e+58)
		tmp = Float64(c * Float64(Float64(Float64(i * t_6) + Float64(y0 * t_1)) + Float64(y4 * t_3)));
	elseif (i <= -2.8e+39)
		tmp = Float64(Float64(t * b) * Float64(Float64(j * y4) - Float64(z * a)));
	elseif (i <= -4.2e-54)
		tmp = Float64(y1 * Float64(Float64(Float64(a * Float64(Float64(z * y3) - Float64(x * y2))) + Float64(y4 * t_7)) + Float64(i * t_2)));
	elseif (i <= 5.5e-209)
		tmp = Float64(y2 * Float64(Float64(Float64(k * t_4) + Float64(x * Float64(Float64(c * y0) - Float64(a * y1)))) + Float64(t * Float64(Float64(a * y5) - Float64(c * y4)))));
	elseif (i <= 2.5e-127)
		tmp = Float64(y0 * Float64(Float64(Float64(y5 * t_5) + Float64(c * t_1)) + Float64(b * Float64(Float64(z * k) - Float64(x * j)))));
	elseif (i <= 7.8e-59)
		tmp = Float64(k * Float64(Float64(z * t_10) + Float64(Float64(y2 * t_4) + Float64(y * Float64(Float64(i * y5) - Float64(b * y4))))));
	elseif (i <= 6.9e+59)
		tmp = Float64(Float64(t_7 * t_4) + Float64(j * Float64(Float64(t * Float64(Float64(b * y4) - Float64(i * y5))) - Float64(x * t_10))));
	elseif (i <= 2.45e+98)
		tmp = Float64(y5 * Float64(Float64(a * Float64(Float64(t * y2) - Float64(y * y3))) + Float64(Float64(i * t_8) + Float64(y0 * t_5))));
	elseif (i <= 2.55e+160)
		tmp = Float64(y4 * Float64(Float64(c * t_3) - Float64(Float64(b * t_8) + Float64(y1 * t_5))));
	else
		tmp = t_9;
	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 = (x * j) - (z * k);
	t_3 = (y * y3) - (t * y2);
	t_4 = (y1 * y4) - (y0 * y5);
	t_5 = (j * y3) - (k * y2);
	t_6 = (z * t) - (x * y);
	t_7 = (k * y2) - (j * y3);
	t_8 = (y * k) - (t * j);
	t_9 = i * ((y1 * t_2) + ((c * t_6) + (y5 * t_8)));
	t_10 = (b * y0) - (i * y1);
	tmp = 0.0;
	if (i <= -6.8e+190)
		tmp = t_9;
	elseif (i <= -4.5e+58)
		tmp = c * (((i * t_6) + (y0 * t_1)) + (y4 * t_3));
	elseif (i <= -2.8e+39)
		tmp = (t * b) * ((j * y4) - (z * a));
	elseif (i <= -4.2e-54)
		tmp = y1 * (((a * ((z * y3) - (x * y2))) + (y4 * t_7)) + (i * t_2));
	elseif (i <= 5.5e-209)
		tmp = y2 * (((k * t_4) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))));
	elseif (i <= 2.5e-127)
		tmp = y0 * (((y5 * t_5) + (c * t_1)) + (b * ((z * k) - (x * j))));
	elseif (i <= 7.8e-59)
		tmp = k * ((z * t_10) + ((y2 * t_4) + (y * ((i * y5) - (b * y4)))));
	elseif (i <= 6.9e+59)
		tmp = (t_7 * t_4) + (j * ((t * ((b * y4) - (i * y5))) - (x * t_10)));
	elseif (i <= 2.45e+98)
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((i * t_8) + (y0 * t_5)));
	elseif (i <= 2.55e+160)
		tmp = y4 * ((c * t_3) - ((b * t_8) + (y1 * t_5)));
	else
		tmp = t_9;
	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[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(N[(j * y3), $MachinePrecision] - N[(k * y2), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$6 = N[(N[(z * t), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$7 = N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$8 = N[(N[(y * k), $MachinePrecision] - N[(t * j), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$9 = N[(i * N[(N[(y1 * t$95$2), $MachinePrecision] + N[(N[(c * t$95$6), $MachinePrecision] + N[(y5 * t$95$8), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$10 = N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[i, -6.8e+190], t$95$9, If[LessEqual[i, -4.5e+58], N[(c * N[(N[(N[(i * t$95$6), $MachinePrecision] + N[(y0 * t$95$1), $MachinePrecision]), $MachinePrecision] + N[(y4 * t$95$3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, -2.8e+39], N[(N[(t * b), $MachinePrecision] * N[(N[(j * y4), $MachinePrecision] - N[(z * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, -4.2e-54], N[(y1 * N[(N[(N[(a * N[(N[(z * y3), $MachinePrecision] - N[(x * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y4 * t$95$7), $MachinePrecision]), $MachinePrecision] + N[(i * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 5.5e-209], N[(y2 * N[(N[(N[(k * t$95$4), $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[i, 2.5e-127], N[(y0 * N[(N[(N[(y5 * t$95$5), $MachinePrecision] + N[(c * t$95$1), $MachinePrecision]), $MachinePrecision] + N[(b * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 7.8e-59], N[(k * N[(N[(z * t$95$10), $MachinePrecision] + N[(N[(y2 * t$95$4), $MachinePrecision] + N[(y * N[(N[(i * y5), $MachinePrecision] - N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 6.9e+59], N[(N[(t$95$7 * t$95$4), $MachinePrecision] + N[(j * N[(N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(x * t$95$10), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 2.45e+98], N[(y5 * N[(N[(a * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(i * t$95$8), $MachinePrecision] + N[(y0 * t$95$5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[i, 2.55e+160], N[(y4 * N[(N[(c * t$95$3), $MachinePrecision] - N[(N[(b * t$95$8), $MachinePrecision] + N[(y1 * t$95$5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$9]]]]]]]]]]]]]]]]]]]]

Derivation

1. Split input into 10 regimes

2. if i < -6.7999999999999999e190 or 2.5500000000000001e160 < i

   1. Initial program 34.4%

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

   3. Taylor expanded in i around -inf 69.0%

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

   if -6.7999999999999999e190 < i < -4.4999999999999998e58

   1. Initial program 27.0%

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

   3. Taylor expanded in c around inf 70.0%

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

   if -4.4999999999999998e58 < i < -2.80000000000000001e39

   1. Initial program 25.0%

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

   3. Taylor expanded in b around inf 50.0%

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

   4. Taylor expanded in t around inf 100.0%

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

      1. associate-*r* 100.0%

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

      2. *-commutative 100.0%

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

      3. +-commutative 100.0%

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

      4. mul-1-neg 100.0%

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

      5. unsub-neg 100.0%

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

      6. *-commutative 100.0%

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

      7. *-commutative 100.0%

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

   6. Simplified 100.0%

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

   if -2.80000000000000001e39 < i < -4.2e-54

   1. Initial program 27.3%

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

   3. Taylor expanded in y1 around inf 64.8%

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

   if -4.2e-54 < i < 5.5000000000000001e-209

   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. Add Preprocessing

   3. Taylor expanded in y2 around inf 58.7%

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

   if 5.5000000000000001e-209 < i < 2.4999999999999999e-127

   1. Initial program 25.0%

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

   3. Taylor expanded in y0 around inf 80.1%

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

   if 2.4999999999999999e-127 < i < 7.80000000000000038e-59

   1. Initial program 33.9%

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

   3. Taylor expanded in k around -inf 71.5%

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

      1. mul-1-neg 71.5%

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

      2. distribute-rgt-neg-in 71.5%

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

      3. +-commutative 71.5%

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

      4. mul-1-neg 71.5%

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

      5. unsub-neg 71.5%

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

      6. *-commutative 71.5%

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

   5. Simplified 71.5%

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

   if 7.80000000000000038e-59 < i < 6.8999999999999998e59

   1. Initial program 42.7%

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

   3. Taylor expanded in j around inf 67.0%

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

      1. *-commutative 67.0%

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

   5. Simplified 67.0%

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

   if 6.8999999999999998e59 < i < 2.4499999999999999e98

   1. Initial program 13.3%

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

   3. Taylor expanded in y5 around -inf 76.2%

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

   if 2.4499999999999999e98 < i < 2.5500000000000001e160

   1. Initial program 9.3%

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

   3. Taylor expanded in y4 around inf 59.1%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
3. Recombined 10 regimes into one program.

4. Final simplification 67.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;i \leq -6.8 \cdot 10^{+190}:\\ \;\;\;\;i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right) + \left(c \cdot \left(z \cdot t - x \cdot y\right) + y5 \cdot \left(y \cdot k - t \cdot j\right)\right)\right)\\ \mathbf{elif}\;i \leq -4.5 \cdot 10^{+58}:\\ \;\;\;\;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}\;i \leq -2.8 \cdot 10^{+39}:\\ \;\;\;\;\left(t \cdot b\right) \cdot \left(j \cdot y4 - z \cdot a\right)\\ \mathbf{elif}\;i \leq -4.2 \cdot 10^{-54}:\\ \;\;\;\;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}\;i \leq 5.5 \cdot 10^{-209}:\\ \;\;\;\;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}\;i \leq 2.5 \cdot 10^{-127}:\\ \;\;\;\;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}\;i \leq 7.8 \cdot 10^{-59}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right) + \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\right)\\ \mathbf{elif}\;i \leq 6.9 \cdot 10^{+59}:\\ \;\;\;\;\left(k \cdot y2 - j \cdot y3\right) \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;i \leq 2.45 \cdot 10^{+98}:\\ \;\;\;\;y5 \cdot \left(a \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(i \cdot \left(y \cdot k - t \cdot j\right) + y0 \cdot \left(j \cdot y3 - k \cdot y2\right)\right)\right)\\ \mathbf{elif}\;i \leq 2.55 \cdot 10^{+160}:\\ \;\;\;\;y4 \cdot \left(c \cdot \left(y \cdot y3 - t \cdot y2\right) - \left(b \cdot \left(y \cdot k - t \cdot j\right) + y1 \cdot \left(j \cdot y3 - k \cdot y2\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right) + \left(c \cdot \left(z \cdot t - x \cdot y\right) + y5 \cdot \left(y \cdot k - t \cdot j\right)\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 2: 53.6% accurate, 0.5× speedup

Math

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

FPCore

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

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

Python

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

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 87.8%

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

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

   1. Initial program 0.0%

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

   3. Taylor expanded in y5 around -inf 43.5%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
3. Recombined 2 regimes into one program.

4. Final simplification 59.4%

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

Alternative 3: 40.2% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y1 \cdot y4 - y0 \cdot y5\\ t_2 := z \cdot \left(t \cdot i - y0 \cdot y3\right)\\ t_3 := b \cdot y0 - i \cdot y1\\ t_4 := k \cdot \left(z \cdot t\_3 + \left(y2 \cdot t\_1 + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\right)\\ t_5 := j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) - x \cdot t\_3\right)\\ t_6 := y \cdot y3 - t \cdot y2\\ \mathbf{if}\;k \leq -7.8 \cdot 10^{+104}:\\ \;\;\;\;t\_4\\ \mathbf{elif}\;k \leq -5.2 \cdot 10^{+40}:\\ \;\;\;\;y4 \cdot \left(y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;k \leq -1.9 \cdot 10^{+35}:\\ \;\;\;\;t\_4\\ \mathbf{elif}\;k \leq -0.00021:\\ \;\;\;\;b \cdot \left(\left(t \cdot j\right) \cdot y4 + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;k \leq 2.22 \cdot 10^{-302}:\\ \;\;\;\;c \cdot \left(y4 \cdot t\_6 - \left(x \cdot \left(y \cdot i - y0 \cdot y2\right) - t\_2\right)\right)\\ \mathbf{elif}\;k \leq 1.3 \cdot 10^{-250}:\\ \;\;\;\;t\_5\\ \mathbf{elif}\;k \leq 6.2 \cdot 10^{-32}:\\ \;\;\;\;c \cdot \left(t\_2 + x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{elif}\;k \leq 240000:\\ \;\;\;\;y2 \cdot \left(\left(k \cdot t\_1 + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;k \leq 2.85 \cdot 10^{+35}:\\ \;\;\;\;t\_5\\ \mathbf{elif}\;k \leq 5 \cdot 10^{+90}:\\ \;\;\;\;y5 \cdot \left(y2 \cdot \left(t \cdot a - k \cdot y0\right)\right)\\ \mathbf{elif}\;k \leq 7.2 \cdot 10^{+142}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;k \leq 3.2 \cdot 10^{+208}:\\ \;\;\;\;y4 \cdot \left(c \cdot t\_6 - \left(b \cdot \left(y \cdot k - t \cdot j\right) + y1 \cdot \left(j \cdot y3 - k \cdot y2\right)\right)\right)\\ \mathbf{elif}\;k \leq 7 \cdot 10^{+244}:\\ \;\;\;\;y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)\\ \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 (- (* y1 y4) (* y0 y5)))
        (t_2 (* z (- (* t i) (* y0 y3))))
        (t_3 (- (* b y0) (* i y1)))
        (t_4 (* k (+ (* z t_3) (+ (* y2 t_1) (* y (- (* i y5) (* b y4)))))))
        (t_5
         (*
          j
          (-
           (+ (* t (- (* b y4) (* i y5))) (* y3 (- (* y0 y5) (* y1 y4))))
           (* x t_3))))
        (t_6 (- (* y y3) (* t y2))))
   (if (<= k -7.8e+104)
     t_4
     (if (<= k -5.2e+40)
       (* y4 (* y1 (- (* k y2) (* j y3))))
       (if (<= k -1.9e+35)
         t_4
         (if (<= k -0.00021)
           (* b (+ (* (* t j) y4) (* y0 (- (* z k) (* x j)))))
           (if (<= k 2.22e-302)
             (* c (- (* y4 t_6) (- (* x (- (* y i) (* y0 y2))) t_2)))
             (if (<= k 1.3e-250)
               t_5
               (if (<= k 6.2e-32)
                 (* c (+ t_2 (* x (- (* y0 y2) (* y i)))))
                 (if (<= k 240000.0)
                   (*
                    y2
                    (+
                     (+ (* k t_1) (* x (- (* c y0) (* a y1))))
                     (* t (- (* a y5) (* c y4)))))
                   (if (<= k 2.85e+35)
                     t_5
                     (if (<= k 5e+90)
                       (* y5 (* y2 (- (* t a) (* k y0))))
                       (if (<= k 7.2e+142)
                         (* i (* k (- (* y y5) (* z y1))))
                         (if (<= k 3.2e+208)
                           (*
                            y4
                            (-
                             (* c t_6)
                             (+
                              (* b (- (* y k) (* t j)))
                              (* y1 (- (* j y3) (* k y2))))))
                           (if (<= k 7e+244)
                             (* y (* y5 (- (* i k) (* a y3))))
                             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 = (y1 * y4) - (y0 * y5);
	double t_2 = z * ((t * i) - (y0 * y3));
	double t_3 = (b * y0) - (i * y1);
	double t_4 = k * ((z * t_3) + ((y2 * t_1) + (y * ((i * y5) - (b * y4)))));
	double t_5 = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) - (x * t_3));
	double t_6 = (y * y3) - (t * y2);
	double tmp;
	if (k <= -7.8e+104) {
		tmp = t_4;
	} else if (k <= -5.2e+40) {
		tmp = y4 * (y1 * ((k * y2) - (j * y3)));
	} else if (k <= -1.9e+35) {
		tmp = t_4;
	} else if (k <= -0.00021) {
		tmp = b * (((t * j) * y4) + (y0 * ((z * k) - (x * j))));
	} else if (k <= 2.22e-302) {
		tmp = c * ((y4 * t_6) - ((x * ((y * i) - (y0 * y2))) - t_2));
	} else if (k <= 1.3e-250) {
		tmp = t_5;
	} else if (k <= 6.2e-32) {
		tmp = c * (t_2 + (x * ((y0 * y2) - (y * i))));
	} else if (k <= 240000.0) {
		tmp = y2 * (((k * t_1) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))));
	} else if (k <= 2.85e+35) {
		tmp = t_5;
	} else if (k <= 5e+90) {
		tmp = y5 * (y2 * ((t * a) - (k * y0)));
	} else if (k <= 7.2e+142) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (k <= 3.2e+208) {
		tmp = y4 * ((c * t_6) - ((b * ((y * k) - (t * j))) + (y1 * ((j * y3) - (k * y2)))));
	} else if (k <= 7e+244) {
		tmp = y * (y5 * ((i * k) - (a * y3)));
	} 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) :: t_5
    real(8) :: t_6
    real(8) :: tmp
    t_1 = (y1 * y4) - (y0 * y5)
    t_2 = z * ((t * i) - (y0 * y3))
    t_3 = (b * y0) - (i * y1)
    t_4 = k * ((z * t_3) + ((y2 * t_1) + (y * ((i * y5) - (b * y4)))))
    t_5 = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) - (x * t_3))
    t_6 = (y * y3) - (t * y2)
    if (k <= (-7.8d+104)) then
        tmp = t_4
    else if (k <= (-5.2d+40)) then
        tmp = y4 * (y1 * ((k * y2) - (j * y3)))
    else if (k <= (-1.9d+35)) then
        tmp = t_4
    else if (k <= (-0.00021d0)) then
        tmp = b * (((t * j) * y4) + (y0 * ((z * k) - (x * j))))
    else if (k <= 2.22d-302) then
        tmp = c * ((y4 * t_6) - ((x * ((y * i) - (y0 * y2))) - t_2))
    else if (k <= 1.3d-250) then
        tmp = t_5
    else if (k <= 6.2d-32) then
        tmp = c * (t_2 + (x * ((y0 * y2) - (y * i))))
    else if (k <= 240000.0d0) then
        tmp = y2 * (((k * t_1) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))))
    else if (k <= 2.85d+35) then
        tmp = t_5
    else if (k <= 5d+90) then
        tmp = y5 * (y2 * ((t * a) - (k * y0)))
    else if (k <= 7.2d+142) then
        tmp = i * (k * ((y * y5) - (z * y1)))
    else if (k <= 3.2d+208) then
        tmp = y4 * ((c * t_6) - ((b * ((y * k) - (t * j))) + (y1 * ((j * y3) - (k * y2)))))
    else if (k <= 7d+244) then
        tmp = y * (y5 * ((i * k) - (a * y3)))
    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 = (y1 * y4) - (y0 * y5);
	double t_2 = z * ((t * i) - (y0 * y3));
	double t_3 = (b * y0) - (i * y1);
	double t_4 = k * ((z * t_3) + ((y2 * t_1) + (y * ((i * y5) - (b * y4)))));
	double t_5 = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) - (x * t_3));
	double t_6 = (y * y3) - (t * y2);
	double tmp;
	if (k <= -7.8e+104) {
		tmp = t_4;
	} else if (k <= -5.2e+40) {
		tmp = y4 * (y1 * ((k * y2) - (j * y3)));
	} else if (k <= -1.9e+35) {
		tmp = t_4;
	} else if (k <= -0.00021) {
		tmp = b * (((t * j) * y4) + (y0 * ((z * k) - (x * j))));
	} else if (k <= 2.22e-302) {
		tmp = c * ((y4 * t_6) - ((x * ((y * i) - (y0 * y2))) - t_2));
	} else if (k <= 1.3e-250) {
		tmp = t_5;
	} else if (k <= 6.2e-32) {
		tmp = c * (t_2 + (x * ((y0 * y2) - (y * i))));
	} else if (k <= 240000.0) {
		tmp = y2 * (((k * t_1) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))));
	} else if (k <= 2.85e+35) {
		tmp = t_5;
	} else if (k <= 5e+90) {
		tmp = y5 * (y2 * ((t * a) - (k * y0)));
	} else if (k <= 7.2e+142) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (k <= 3.2e+208) {
		tmp = y4 * ((c * t_6) - ((b * ((y * k) - (t * j))) + (y1 * ((j * y3) - (k * y2)))));
	} else if (k <= 7e+244) {
		tmp = y * (y5 * ((i * k) - (a * y3)));
	} 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 = (y1 * y4) - (y0 * y5)
	t_2 = z * ((t * i) - (y0 * y3))
	t_3 = (b * y0) - (i * y1)
	t_4 = k * ((z * t_3) + ((y2 * t_1) + (y * ((i * y5) - (b * y4)))))
	t_5 = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) - (x * t_3))
	t_6 = (y * y3) - (t * y2)
	tmp = 0
	if k <= -7.8e+104:
		tmp = t_4
	elif k <= -5.2e+40:
		tmp = y4 * (y1 * ((k * y2) - (j * y3)))
	elif k <= -1.9e+35:
		tmp = t_4
	elif k <= -0.00021:
		tmp = b * (((t * j) * y4) + (y0 * ((z * k) - (x * j))))
	elif k <= 2.22e-302:
		tmp = c * ((y4 * t_6) - ((x * ((y * i) - (y0 * y2))) - t_2))
	elif k <= 1.3e-250:
		tmp = t_5
	elif k <= 6.2e-32:
		tmp = c * (t_2 + (x * ((y0 * y2) - (y * i))))
	elif k <= 240000.0:
		tmp = y2 * (((k * t_1) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))))
	elif k <= 2.85e+35:
		tmp = t_5
	elif k <= 5e+90:
		tmp = y5 * (y2 * ((t * a) - (k * y0)))
	elif k <= 7.2e+142:
		tmp = i * (k * ((y * y5) - (z * y1)))
	elif k <= 3.2e+208:
		tmp = y4 * ((c * t_6) - ((b * ((y * k) - (t * j))) + (y1 * ((j * y3) - (k * y2)))))
	elif k <= 7e+244:
		tmp = y * (y5 * ((i * k) - (a * y3)))
	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(Float64(y1 * y4) - Float64(y0 * y5))
	t_2 = Float64(z * Float64(Float64(t * i) - Float64(y0 * y3)))
	t_3 = Float64(Float64(b * y0) - Float64(i * y1))
	t_4 = Float64(k * Float64(Float64(z * t_3) + Float64(Float64(y2 * t_1) + Float64(y * Float64(Float64(i * y5) - Float64(b * y4))))))
	t_5 = Float64(j * Float64(Float64(Float64(t * Float64(Float64(b * y4) - Float64(i * y5))) + Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4)))) - Float64(x * t_3)))
	t_6 = Float64(Float64(y * y3) - Float64(t * y2))
	tmp = 0.0
	if (k <= -7.8e+104)
		tmp = t_4;
	elseif (k <= -5.2e+40)
		tmp = Float64(y4 * Float64(y1 * Float64(Float64(k * y2) - Float64(j * y3))));
	elseif (k <= -1.9e+35)
		tmp = t_4;
	elseif (k <= -0.00021)
		tmp = Float64(b * Float64(Float64(Float64(t * j) * y4) + Float64(y0 * Float64(Float64(z * k) - Float64(x * j)))));
	elseif (k <= 2.22e-302)
		tmp = Float64(c * Float64(Float64(y4 * t_6) - Float64(Float64(x * Float64(Float64(y * i) - Float64(y0 * y2))) - t_2)));
	elseif (k <= 1.3e-250)
		tmp = t_5;
	elseif (k <= 6.2e-32)
		tmp = Float64(c * Float64(t_2 + Float64(x * Float64(Float64(y0 * y2) - Float64(y * i)))));
	elseif (k <= 240000.0)
		tmp = Float64(y2 * Float64(Float64(Float64(k * t_1) + Float64(x * Float64(Float64(c * y0) - Float64(a * y1)))) + Float64(t * Float64(Float64(a * y5) - Float64(c * y4)))));
	elseif (k <= 2.85e+35)
		tmp = t_5;
	elseif (k <= 5e+90)
		tmp = Float64(y5 * Float64(y2 * Float64(Float64(t * a) - Float64(k * y0))));
	elseif (k <= 7.2e+142)
		tmp = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))));
	elseif (k <= 3.2e+208)
		tmp = Float64(y4 * Float64(Float64(c * t_6) - Float64(Float64(b * Float64(Float64(y * k) - Float64(t * j))) + Float64(y1 * Float64(Float64(j * y3) - Float64(k * y2))))));
	elseif (k <= 7e+244)
		tmp = Float64(y * Float64(y5 * Float64(Float64(i * k) - Float64(a * y3))));
	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 = (y1 * y4) - (y0 * y5);
	t_2 = z * ((t * i) - (y0 * y3));
	t_3 = (b * y0) - (i * y1);
	t_4 = k * ((z * t_3) + ((y2 * t_1) + (y * ((i * y5) - (b * y4)))));
	t_5 = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) - (x * t_3));
	t_6 = (y * y3) - (t * y2);
	tmp = 0.0;
	if (k <= -7.8e+104)
		tmp = t_4;
	elseif (k <= -5.2e+40)
		tmp = y4 * (y1 * ((k * y2) - (j * y3)));
	elseif (k <= -1.9e+35)
		tmp = t_4;
	elseif (k <= -0.00021)
		tmp = b * (((t * j) * y4) + (y0 * ((z * k) - (x * j))));
	elseif (k <= 2.22e-302)
		tmp = c * ((y4 * t_6) - ((x * ((y * i) - (y0 * y2))) - t_2));
	elseif (k <= 1.3e-250)
		tmp = t_5;
	elseif (k <= 6.2e-32)
		tmp = c * (t_2 + (x * ((y0 * y2) - (y * i))));
	elseif (k <= 240000.0)
		tmp = y2 * (((k * t_1) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))));
	elseif (k <= 2.85e+35)
		tmp = t_5;
	elseif (k <= 5e+90)
		tmp = y5 * (y2 * ((t * a) - (k * y0)));
	elseif (k <= 7.2e+142)
		tmp = i * (k * ((y * y5) - (z * y1)));
	elseif (k <= 3.2e+208)
		tmp = y4 * ((c * t_6) - ((b * ((y * k) - (t * j))) + (y1 * ((j * y3) - (k * y2)))));
	elseif (k <= 7e+244)
		tmp = y * (y5 * ((i * k) - (a * y3)));
	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[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(z * N[(N[(t * i), $MachinePrecision] - N[(y0 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(k * N[(N[(z * t$95$3), $MachinePrecision] + N[(N[(y2 * t$95$1), $MachinePrecision] + N[(y * N[(N[(i * y5), $MachinePrecision] - N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(j * N[(N[(N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(x * t$95$3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$6 = N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[k, -7.8e+104], t$95$4, If[LessEqual[k, -5.2e+40], N[(y4 * N[(y1 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, -1.9e+35], t$95$4, If[LessEqual[k, -0.00021], N[(b * N[(N[(N[(t * j), $MachinePrecision] * y4), $MachinePrecision] + N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 2.22e-302], N[(c * N[(N[(y4 * t$95$6), $MachinePrecision] - N[(N[(x * N[(N[(y * i), $MachinePrecision] - N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 1.3e-250], t$95$5, If[LessEqual[k, 6.2e-32], N[(c * N[(t$95$2 + N[(x * N[(N[(y0 * y2), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 240000.0], N[(y2 * N[(N[(N[(k * t$95$1), $MachinePrecision] + N[(x * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(t * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 2.85e+35], t$95$5, If[LessEqual[k, 5e+90], N[(y5 * N[(y2 * N[(N[(t * a), $MachinePrecision] - N[(k * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 7.2e+142], N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 3.2e+208], N[(y4 * N[(N[(c * t$95$6), $MachinePrecision] - N[(N[(b * N[(N[(y * k), $MachinePrecision] - N[(t * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y1 * N[(N[(j * y3), $MachinePrecision] - N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 7e+244], N[(y * N[(y5 * N[(N[(i * k), $MachinePrecision] - N[(a * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$4]]]]]]]]]]]]]]]]]]]

Derivation

1. Split input into 11 regimes

2. if k < -7.80000000000000033e104 or -5.2000000000000001e40 < k < -1.9e35 or 6.99999999999999946e244 < k

   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. Add Preprocessing

   3. Taylor expanded in k around -inf 71.9%

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

      1. mul-1-neg 71.9%

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

      2. distribute-rgt-neg-in 71.9%

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

      3. +-commutative 71.9%

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

      4. mul-1-neg 71.9%

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

      5. unsub-neg 71.9%

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

      6. *-commutative 71.9%

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

   5. Simplified 71.9%

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

   if -7.80000000000000033e104 < k < -5.2000000000000001e40

   1. Initial program 16.7%

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

   3. Taylor expanded in y4 around inf 41.7%

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

   4. Taylor expanded in y1 around inf 75.1%

      \[\leadsto y4 \cdot \color{blue}{\left(y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 75.1%

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

      2. *-commutative 75.1%

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

   6. Simplified 75.1%

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

   if -1.9e35 < k < -2.1000000000000001e-4

   1. Initial program 25.0%

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

   3. Taylor expanded in b around inf 42.6%

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

   4. Taylor expanded in a around 0 50.9%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 50.9%

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

      2. *-commutative 50.9%

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

      3. *-commutative 50.9%

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

      4. *-commutative 50.9%

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

   6. Simplified 50.9%

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

   7. Taylor expanded in t around inf 67.7%

      \[\leadsto b \cdot \left(\color{blue}{j \cdot \left(t \cdot y4\right)} - y0 \cdot \left(x \cdot j - z \cdot k\right)\right) \]
   8. Step-by-step derivation

      1. associate-*r* 67.6%

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

      2. *-commutative 67.6%

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

   9. Simplified 67.6%

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

   if -2.1000000000000001e-4 < k < 2.2199999999999999e-302

   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. Add Preprocessing

   3. Taylor expanded in c around inf 57.1%

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

   4. Taylor expanded in x around -inf 57.0%

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

   6. Simplified 60.0%

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

   if 2.2199999999999999e-302 < k < 1.30000000000000004e-250 or 2.4e5 < k < 2.84999999999999997e35

   1. Initial program 50.7%

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

   3. Taylor expanded in j around inf 71.7%

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

      1. +-commutative 71.7%

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

      2. mul-1-neg 71.7%

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

      3. unsub-neg 71.7%

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

      4. *-commutative 71.7%

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

   5. Simplified 71.7%

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

   if 1.30000000000000004e-250 < k < 6.20000000000000021e-32

   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. Add Preprocessing

   3. Taylor expanded in c around inf 52.3%

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

   4. Taylor expanded in x around -inf 55.3%

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

   6. Simplified 58.1%

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

   7. Taylor expanded in y4 around 0 61.2%

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

   if 6.20000000000000021e-32 < k < 2.4e5

   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. Add Preprocessing

   3. Taylor expanded in y2 around inf 75.2%

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

   if 2.84999999999999997e35 < k < 5.0000000000000004e90

   1. Initial program 23.9%

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

   3. Taylor expanded in y5 around -inf 76.9%

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

   4. Taylor expanded in y2 around inf 63.4%

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

      1. *-commutative 63.4%

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

      2. *-commutative 63.4%

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

   6. Simplified 63.4%

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

   if 5.0000000000000004e90 < k < 7.2000000000000003e142

   1. Initial program 0.0%

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

   3. Taylor expanded in k around -inf 42.9%

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

      1. mul-1-neg 42.9%

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

      2. distribute-rgt-neg-in 42.9%

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

      3. +-commutative 42.9%

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

      4. mul-1-neg 42.9%

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

      5. unsub-neg 42.9%

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

      6. *-commutative 42.9%

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

   5. Simplified 42.9%

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

   6. Taylor expanded in i around inf 85.7%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(-1 \cdot \left(y1 \cdot z\right) - -1 \cdot \left(y \cdot y5\right)\right)\right)} \]
   7. Step-by-step derivation

      1. distribute-lft-out-- 85.7%

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

      2. *-commutative 85.7%

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

   8. Simplified 85.7%

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

   if 7.2000000000000003e142 < k < 3.2000000000000001e208

   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. Add Preprocessing

   3. Taylor expanded in y4 around inf 73.4%

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

   if 3.2000000000000001e208 < k < 6.99999999999999946e244

   1. Initial program 16.7%

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

   3. Taylor expanded in y around inf 41.9%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y5 around inf 75.3%

      \[\leadsto \color{blue}{y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)} \]
3. Recombined 11 regimes into one program.

4. Final simplification 67.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;k \leq -7.8 \cdot 10^{+104}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right) + \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\right)\\ \mathbf{elif}\;k \leq -5.2 \cdot 10^{+40}:\\ \;\;\;\;y4 \cdot \left(y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;k \leq -1.9 \cdot 10^{+35}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right) + \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\right)\\ \mathbf{elif}\;k \leq -0.00021:\\ \;\;\;\;b \cdot \left(\left(t \cdot j\right) \cdot y4 + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;k \leq 2.22 \cdot 10^{-302}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right) - \left(x \cdot \left(y \cdot i - y0 \cdot y2\right) - z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)\right)\\ \mathbf{elif}\;k \leq 1.3 \cdot 10^{-250}:\\ \;\;\;\;j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;k \leq 6.2 \cdot 10^{-32}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right) + x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{elif}\;k \leq 240000:\\ \;\;\;\;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}\;k \leq 2.85 \cdot 10^{+35}:\\ \;\;\;\;j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;k \leq 5 \cdot 10^{+90}:\\ \;\;\;\;y5 \cdot \left(y2 \cdot \left(t \cdot a - k \cdot y0\right)\right)\\ \mathbf{elif}\;k \leq 7.2 \cdot 10^{+142}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;k \leq 3.2 \cdot 10^{+208}:\\ \;\;\;\;y4 \cdot \left(c \cdot \left(y \cdot y3 - t \cdot y2\right) - \left(b \cdot \left(y \cdot k - t \cdot j\right) + y1 \cdot \left(j \cdot y3 - k \cdot y2\right)\right)\right)\\ \mathbf{elif}\;k \leq 7 \cdot 10^{+244}:\\ \;\;\;\;y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right) + \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 4: 37.6% accurate, 1.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y1 \cdot y4 - y0 \cdot y5\\ t_2 := j \cdot y3 - k \cdot y2\\ t_3 := y \cdot y3 - t \cdot y2\\ t_4 := z \cdot \left(t \cdot i - y0 \cdot y3\right)\\ t_5 := y \cdot k - t \cdot j\\ t_6 := y5 \cdot \left(a \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(i \cdot t\_5 + y0 \cdot t\_2\right)\right)\\ t_7 := b \cdot y0 - i \cdot y1\\ t_8 := j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) - x \cdot t\_7\right)\\ \mathbf{if}\;k \leq -1.8 \cdot 10^{+263}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;k \leq -2.35 \cdot 10^{+76}:\\ \;\;\;\;t\_6\\ \mathbf{elif}\;k \leq -4.2 \cdot 10^{-14}:\\ \;\;\;\;y4 \cdot \left(y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;k \leq 2.22 \cdot 10^{-302}:\\ \;\;\;\;c \cdot \left(y4 \cdot t\_3 - \left(x \cdot \left(y \cdot i - y0 \cdot y2\right) - t\_4\right)\right)\\ \mathbf{elif}\;k \leq 2 \cdot 10^{-250}:\\ \;\;\;\;t\_8\\ \mathbf{elif}\;k \leq 1.8 \cdot 10^{-29}:\\ \;\;\;\;c \cdot \left(t\_4 + x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{elif}\;k \leq 90000000:\\ \;\;\;\;y2 \cdot \left(\left(k \cdot t\_1 + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;k \leq 4.6 \cdot 10^{+34}:\\ \;\;\;\;t\_8\\ \mathbf{elif}\;k \leq 5.8 \cdot 10^{+118}:\\ \;\;\;\;t\_6\\ \mathbf{elif}\;k \leq 1.1 \cdot 10^{+205}:\\ \;\;\;\;y4 \cdot \left(c \cdot t\_3 - \left(b \cdot t\_5 + y1 \cdot t\_2\right)\right)\\ \mathbf{elif}\;k \leq 2.1 \cdot 10^{+260}:\\ \;\;\;\;i \cdot \left(y \cdot \left(k \cdot y5 - x \cdot c\right)\right)\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(z \cdot t\_7 + \left(y2 \cdot t\_1 + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* y1 y4) (* y0 y5)))
        (t_2 (- (* j y3) (* k y2)))
        (t_3 (- (* y y3) (* t y2)))
        (t_4 (* z (- (* t i) (* y0 y3))))
        (t_5 (- (* y k) (* t j)))
        (t_6 (* y5 (+ (* a (- (* t y2) (* y y3))) (+ (* i t_5) (* y0 t_2)))))
        (t_7 (- (* b y0) (* i y1)))
        (t_8
         (*
          j
          (-
           (+ (* t (- (* b y4) (* i y5))) (* y3 (- (* y0 y5) (* y1 y4))))
           (* x t_7)))))
   (if (<= k -1.8e+263)
     (* i (* k (- (* y y5) (* z y1))))
     (if (<= k -2.35e+76)
       t_6
       (if (<= k -4.2e-14)
         (* y4 (* y1 (- (* k y2) (* j y3))))
         (if (<= k 2.22e-302)
           (* c (- (* y4 t_3) (- (* x (- (* y i) (* y0 y2))) t_4)))
           (if (<= k 2e-250)
             t_8
             (if (<= k 1.8e-29)
               (* c (+ t_4 (* x (- (* y0 y2) (* y i)))))
               (if (<= k 90000000.0)
                 (*
                  y2
                  (+
                   (+ (* k t_1) (* x (- (* c y0) (* a y1))))
                   (* t (- (* a y5) (* c y4)))))
                 (if (<= k 4.6e+34)
                   t_8
                   (if (<= k 5.8e+118)
                     t_6
                     (if (<= k 1.1e+205)
                       (* y4 (- (* c t_3) (+ (* b t_5) (* y1 t_2))))
                       (if (<= k 2.1e+260)
                         (* i (* y (- (* k y5) (* x c))))
                         (*
                          k
                          (+
                           (* z t_7)
                           (+
                            (* y2 t_1)
                            (* y (- (* i y5) (* b 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 = (y1 * y4) - (y0 * y5);
	double t_2 = (j * y3) - (k * y2);
	double t_3 = (y * y3) - (t * y2);
	double t_4 = z * ((t * i) - (y0 * y3));
	double t_5 = (y * k) - (t * j);
	double t_6 = y5 * ((a * ((t * y2) - (y * y3))) + ((i * t_5) + (y0 * t_2)));
	double t_7 = (b * y0) - (i * y1);
	double t_8 = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) - (x * t_7));
	double tmp;
	if (k <= -1.8e+263) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (k <= -2.35e+76) {
		tmp = t_6;
	} else if (k <= -4.2e-14) {
		tmp = y4 * (y1 * ((k * y2) - (j * y3)));
	} else if (k <= 2.22e-302) {
		tmp = c * ((y4 * t_3) - ((x * ((y * i) - (y0 * y2))) - t_4));
	} else if (k <= 2e-250) {
		tmp = t_8;
	} else if (k <= 1.8e-29) {
		tmp = c * (t_4 + (x * ((y0 * y2) - (y * i))));
	} else if (k <= 90000000.0) {
		tmp = y2 * (((k * t_1) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))));
	} else if (k <= 4.6e+34) {
		tmp = t_8;
	} else if (k <= 5.8e+118) {
		tmp = t_6;
	} else if (k <= 1.1e+205) {
		tmp = y4 * ((c * t_3) - ((b * t_5) + (y1 * t_2)));
	} else if (k <= 2.1e+260) {
		tmp = i * (y * ((k * y5) - (x * c)));
	} else {
		tmp = k * ((z * t_7) + ((y2 * t_1) + (y * ((i * y5) - (b * 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) :: t_4
    real(8) :: t_5
    real(8) :: t_6
    real(8) :: t_7
    real(8) :: t_8
    real(8) :: tmp
    t_1 = (y1 * y4) - (y0 * y5)
    t_2 = (j * y3) - (k * y2)
    t_3 = (y * y3) - (t * y2)
    t_4 = z * ((t * i) - (y0 * y3))
    t_5 = (y * k) - (t * j)
    t_6 = y5 * ((a * ((t * y2) - (y * y3))) + ((i * t_5) + (y0 * t_2)))
    t_7 = (b * y0) - (i * y1)
    t_8 = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) - (x * t_7))
    if (k <= (-1.8d+263)) then
        tmp = i * (k * ((y * y5) - (z * y1)))
    else if (k <= (-2.35d+76)) then
        tmp = t_6
    else if (k <= (-4.2d-14)) then
        tmp = y4 * (y1 * ((k * y2) - (j * y3)))
    else if (k <= 2.22d-302) then
        tmp = c * ((y4 * t_3) - ((x * ((y * i) - (y0 * y2))) - t_4))
    else if (k <= 2d-250) then
        tmp = t_8
    else if (k <= 1.8d-29) then
        tmp = c * (t_4 + (x * ((y0 * y2) - (y * i))))
    else if (k <= 90000000.0d0) then
        tmp = y2 * (((k * t_1) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))))
    else if (k <= 4.6d+34) then
        tmp = t_8
    else if (k <= 5.8d+118) then
        tmp = t_6
    else if (k <= 1.1d+205) then
        tmp = y4 * ((c * t_3) - ((b * t_5) + (y1 * t_2)))
    else if (k <= 2.1d+260) then
        tmp = i * (y * ((k * y5) - (x * c)))
    else
        tmp = k * ((z * t_7) + ((y2 * t_1) + (y * ((i * y5) - (b * 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 = (y1 * y4) - (y0 * y5);
	double t_2 = (j * y3) - (k * y2);
	double t_3 = (y * y3) - (t * y2);
	double t_4 = z * ((t * i) - (y0 * y3));
	double t_5 = (y * k) - (t * j);
	double t_6 = y5 * ((a * ((t * y2) - (y * y3))) + ((i * t_5) + (y0 * t_2)));
	double t_7 = (b * y0) - (i * y1);
	double t_8 = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) - (x * t_7));
	double tmp;
	if (k <= -1.8e+263) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (k <= -2.35e+76) {
		tmp = t_6;
	} else if (k <= -4.2e-14) {
		tmp = y4 * (y1 * ((k * y2) - (j * y3)));
	} else if (k <= 2.22e-302) {
		tmp = c * ((y4 * t_3) - ((x * ((y * i) - (y0 * y2))) - t_4));
	} else if (k <= 2e-250) {
		tmp = t_8;
	} else if (k <= 1.8e-29) {
		tmp = c * (t_4 + (x * ((y0 * y2) - (y * i))));
	} else if (k <= 90000000.0) {
		tmp = y2 * (((k * t_1) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))));
	} else if (k <= 4.6e+34) {
		tmp = t_8;
	} else if (k <= 5.8e+118) {
		tmp = t_6;
	} else if (k <= 1.1e+205) {
		tmp = y4 * ((c * t_3) - ((b * t_5) + (y1 * t_2)));
	} else if (k <= 2.1e+260) {
		tmp = i * (y * ((k * y5) - (x * c)));
	} else {
		tmp = k * ((z * t_7) + ((y2 * t_1) + (y * ((i * y5) - (b * y4)))));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (y1 * y4) - (y0 * y5)
	t_2 = (j * y3) - (k * y2)
	t_3 = (y * y3) - (t * y2)
	t_4 = z * ((t * i) - (y0 * y3))
	t_5 = (y * k) - (t * j)
	t_6 = y5 * ((a * ((t * y2) - (y * y3))) + ((i * t_5) + (y0 * t_2)))
	t_7 = (b * y0) - (i * y1)
	t_8 = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) - (x * t_7))
	tmp = 0
	if k <= -1.8e+263:
		tmp = i * (k * ((y * y5) - (z * y1)))
	elif k <= -2.35e+76:
		tmp = t_6
	elif k <= -4.2e-14:
		tmp = y4 * (y1 * ((k * y2) - (j * y3)))
	elif k <= 2.22e-302:
		tmp = c * ((y4 * t_3) - ((x * ((y * i) - (y0 * y2))) - t_4))
	elif k <= 2e-250:
		tmp = t_8
	elif k <= 1.8e-29:
		tmp = c * (t_4 + (x * ((y0 * y2) - (y * i))))
	elif k <= 90000000.0:
		tmp = y2 * (((k * t_1) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))))
	elif k <= 4.6e+34:
		tmp = t_8
	elif k <= 5.8e+118:
		tmp = t_6
	elif k <= 1.1e+205:
		tmp = y4 * ((c * t_3) - ((b * t_5) + (y1 * t_2)))
	elif k <= 2.1e+260:
		tmp = i * (y * ((k * y5) - (x * c)))
	else:
		tmp = k * ((z * t_7) + ((y2 * t_1) + (y * ((i * y5) - (b * 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(Float64(y1 * y4) - Float64(y0 * y5))
	t_2 = Float64(Float64(j * y3) - Float64(k * y2))
	t_3 = Float64(Float64(y * y3) - Float64(t * y2))
	t_4 = Float64(z * Float64(Float64(t * i) - Float64(y0 * y3)))
	t_5 = Float64(Float64(y * k) - Float64(t * j))
	t_6 = Float64(y5 * Float64(Float64(a * Float64(Float64(t * y2) - Float64(y * y3))) + Float64(Float64(i * t_5) + Float64(y0 * t_2))))
	t_7 = Float64(Float64(b * y0) - Float64(i * y1))
	t_8 = Float64(j * Float64(Float64(Float64(t * Float64(Float64(b * y4) - Float64(i * y5))) + Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4)))) - Float64(x * t_7)))
	tmp = 0.0
	if (k <= -1.8e+263)
		tmp = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))));
	elseif (k <= -2.35e+76)
		tmp = t_6;
	elseif (k <= -4.2e-14)
		tmp = Float64(y4 * Float64(y1 * Float64(Float64(k * y2) - Float64(j * y3))));
	elseif (k <= 2.22e-302)
		tmp = Float64(c * Float64(Float64(y4 * t_3) - Float64(Float64(x * Float64(Float64(y * i) - Float64(y0 * y2))) - t_4)));
	elseif (k <= 2e-250)
		tmp = t_8;
	elseif (k <= 1.8e-29)
		tmp = Float64(c * Float64(t_4 + Float64(x * Float64(Float64(y0 * y2) - Float64(y * i)))));
	elseif (k <= 90000000.0)
		tmp = Float64(y2 * Float64(Float64(Float64(k * t_1) + Float64(x * Float64(Float64(c * y0) - Float64(a * y1)))) + Float64(t * Float64(Float64(a * y5) - Float64(c * y4)))));
	elseif (k <= 4.6e+34)
		tmp = t_8;
	elseif (k <= 5.8e+118)
		tmp = t_6;
	elseif (k <= 1.1e+205)
		tmp = Float64(y4 * Float64(Float64(c * t_3) - Float64(Float64(b * t_5) + Float64(y1 * t_2))));
	elseif (k <= 2.1e+260)
		tmp = Float64(i * Float64(y * Float64(Float64(k * y5) - Float64(x * c))));
	else
		tmp = Float64(k * Float64(Float64(z * t_7) + Float64(Float64(y2 * t_1) + Float64(y * Float64(Float64(i * y5) - Float64(b * 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 = (y1 * y4) - (y0 * y5);
	t_2 = (j * y3) - (k * y2);
	t_3 = (y * y3) - (t * y2);
	t_4 = z * ((t * i) - (y0 * y3));
	t_5 = (y * k) - (t * j);
	t_6 = y5 * ((a * ((t * y2) - (y * y3))) + ((i * t_5) + (y0 * t_2)));
	t_7 = (b * y0) - (i * y1);
	t_8 = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) - (x * t_7));
	tmp = 0.0;
	if (k <= -1.8e+263)
		tmp = i * (k * ((y * y5) - (z * y1)));
	elseif (k <= -2.35e+76)
		tmp = t_6;
	elseif (k <= -4.2e-14)
		tmp = y4 * (y1 * ((k * y2) - (j * y3)));
	elseif (k <= 2.22e-302)
		tmp = c * ((y4 * t_3) - ((x * ((y * i) - (y0 * y2))) - t_4));
	elseif (k <= 2e-250)
		tmp = t_8;
	elseif (k <= 1.8e-29)
		tmp = c * (t_4 + (x * ((y0 * y2) - (y * i))));
	elseif (k <= 90000000.0)
		tmp = y2 * (((k * t_1) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))));
	elseif (k <= 4.6e+34)
		tmp = t_8;
	elseif (k <= 5.8e+118)
		tmp = t_6;
	elseif (k <= 1.1e+205)
		tmp = y4 * ((c * t_3) - ((b * t_5) + (y1 * t_2)));
	elseif (k <= 2.1e+260)
		tmp = i * (y * ((k * y5) - (x * c)));
	else
		tmp = k * ((z * t_7) + ((y2 * t_1) + (y * ((i * y5) - (b * 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[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(j * y3), $MachinePrecision] - N[(k * y2), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(z * N[(N[(t * i), $MachinePrecision] - N[(y0 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(N[(y * k), $MachinePrecision] - N[(t * j), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$6 = N[(y5 * N[(N[(a * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(i * t$95$5), $MachinePrecision] + N[(y0 * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$7 = N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$8 = N[(j * N[(N[(N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(x * t$95$7), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[k, -1.8e+263], N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, -2.35e+76], t$95$6, If[LessEqual[k, -4.2e-14], N[(y4 * N[(y1 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 2.22e-302], N[(c * N[(N[(y4 * t$95$3), $MachinePrecision] - N[(N[(x * N[(N[(y * i), $MachinePrecision] - N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 2e-250], t$95$8, If[LessEqual[k, 1.8e-29], N[(c * N[(t$95$4 + N[(x * N[(N[(y0 * y2), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 90000000.0], N[(y2 * N[(N[(N[(k * t$95$1), $MachinePrecision] + N[(x * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(t * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 4.6e+34], t$95$8, If[LessEqual[k, 5.8e+118], t$95$6, If[LessEqual[k, 1.1e+205], N[(y4 * N[(N[(c * t$95$3), $MachinePrecision] - N[(N[(b * t$95$5), $MachinePrecision] + N[(y1 * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 2.1e+260], N[(i * N[(y * N[(N[(k * y5), $MachinePrecision] - N[(x * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(k * N[(N[(z * t$95$7), $MachinePrecision] + N[(N[(y2 * t$95$1), $MachinePrecision] + N[(y * N[(N[(i * y5), $MachinePrecision] - N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]]]]]]]]

Derivation

1. Split input into 10 regimes

2. if k < -1.79999999999999989e263

   1. Initial program 0.0%

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

   3. Taylor expanded in k around -inf 70.0%

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

      1. mul-1-neg 70.0%

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

      2. distribute-rgt-neg-in 70.0%

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

      3. +-commutative 70.0%

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

      4. mul-1-neg 70.0%

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

      5. unsub-neg 70.0%

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

      6. *-commutative 70.0%

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

   5. Simplified 70.0%

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

   6. Taylor expanded in i around inf 70.1%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(-1 \cdot \left(y1 \cdot z\right) - -1 \cdot \left(y \cdot y5\right)\right)\right)} \]
   7. Step-by-step derivation

      1. distribute-lft-out-- 70.1%

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

      2. *-commutative 70.1%

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

   8. Simplified 70.1%

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

   if -1.79999999999999989e263 < k < -2.3500000000000002e76 or 4.5999999999999996e34 < k < 5.80000000000000032e118

   1. Initial program 21.1%

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

   3. Taylor expanded in y5 around -inf 77.1%

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

   if -2.3500000000000002e76 < k < -4.1999999999999998e-14

   1. Initial program 24.2%

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

   3. Taylor expanded in y4 around inf 40.9%

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

   4. Taylor expanded in y1 around inf 53.1%

      \[\leadsto y4 \cdot \color{blue}{\left(y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 53.1%

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

      2. *-commutative 53.1%

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

   6. Simplified 53.1%

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

   if -4.1999999999999998e-14 < k < 2.2199999999999999e-302

   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. Add Preprocessing

   3. Taylor expanded in c around inf 58.8%

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

   4. Taylor expanded in x around -inf 58.6%

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

   6. Simplified 61.7%

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

   if 2.2199999999999999e-302 < k < 2.0000000000000001e-250 or 9e7 < k < 4.5999999999999996e34

   1. Initial program 50.7%

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

   3. Taylor expanded in j around inf 71.7%

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

      1. +-commutative 71.7%

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

      2. mul-1-neg 71.7%

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

      3. unsub-neg 71.7%

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

      4. *-commutative 71.7%

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

   5. Simplified 71.7%

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

   if 2.0000000000000001e-250 < k < 1.79999999999999987e-29

   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. Add Preprocessing

   3. Taylor expanded in c around inf 52.3%

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

   4. Taylor expanded in x around -inf 55.3%

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

   6. Simplified 58.1%

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

   7. Taylor expanded in y4 around 0 61.2%

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

   if 1.79999999999999987e-29 < k < 9e7

   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. Add Preprocessing

   3. Taylor expanded in y2 around inf 75.2%

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

   if 5.80000000000000032e118 < k < 1.0999999999999999e205

   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. Add Preprocessing

   3. Taylor expanded in y4 around inf 64.8%

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

   if 1.0999999999999999e205 < k < 2.10000000000000012e260

   1. Initial program 27.1%

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

   3. Taylor expanded in y around inf 40.5%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in i around inf 60.7%

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

   if 2.10000000000000012e260 < k

   1. Initial program 30.0%

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

   3. Taylor expanded in k around -inf 100.0%

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

      1. mul-1-neg 100.0%

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

      2. distribute-rgt-neg-in 100.0%

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

      3. +-commutative 100.0%

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

      4. mul-1-neg 100.0%

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

      5. unsub-neg 100.0%

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

      6. *-commutative 100.0%

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

   5. Simplified 100.0%

      \[\leadsto \color{blue}{k \cdot \left(-\left(\left(\left(b \cdot y4 - i \cdot y5\right) \cdot y - y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - z \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\right)} \]
3. Recombined 10 regimes into one program.

4. Final simplification 67.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;k \leq -1.8 \cdot 10^{+263}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;k \leq -2.35 \cdot 10^{+76}:\\ \;\;\;\;y5 \cdot \left(a \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(i \cdot \left(y \cdot k - t \cdot j\right) + y0 \cdot \left(j \cdot y3 - k \cdot y2\right)\right)\right)\\ \mathbf{elif}\;k \leq -4.2 \cdot 10^{-14}:\\ \;\;\;\;y4 \cdot \left(y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;k \leq 2.22 \cdot 10^{-302}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right) - \left(x \cdot \left(y \cdot i - y0 \cdot y2\right) - z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)\right)\\ \mathbf{elif}\;k \leq 2 \cdot 10^{-250}:\\ \;\;\;\;j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;k \leq 1.8 \cdot 10^{-29}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right) + x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{elif}\;k \leq 90000000:\\ \;\;\;\;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}\;k \leq 4.6 \cdot 10^{+34}:\\ \;\;\;\;j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;k \leq 5.8 \cdot 10^{+118}:\\ \;\;\;\;y5 \cdot \left(a \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(i \cdot \left(y \cdot k - t \cdot j\right) + y0 \cdot \left(j \cdot y3 - k \cdot y2\right)\right)\right)\\ \mathbf{elif}\;k \leq 1.1 \cdot 10^{+205}:\\ \;\;\;\;y4 \cdot \left(c \cdot \left(y \cdot y3 - t \cdot y2\right) - \left(b \cdot \left(y \cdot k - t \cdot j\right) + y1 \cdot \left(j \cdot y3 - k \cdot y2\right)\right)\right)\\ \mathbf{elif}\;k \leq 2.1 \cdot 10^{+260}:\\ \;\;\;\;i \cdot \left(y \cdot \left(k \cdot y5 - x \cdot c\right)\right)\\ \mathbf{else}:\\ \;\;\;\;k \cdot \left(z \cdot \left(b \cdot y0 - i \cdot y1\right) + \left(y2 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + y \cdot \left(i \cdot y5 - b \cdot y4\right)\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 5: 38.7% accurate, 1.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)\\ t_2 := c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right) - \left(x \cdot \left(y \cdot i - y0 \cdot y2\right) - z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)\right)\\ t_3 := y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{if}\;y \leq -1.8 \cdot 10^{+225}:\\ \;\;\;\;\left(x \cdot y\right) \cdot \left(a \cdot b - c \cdot i\right)\\ \mathbf{elif}\;y \leq -8 \cdot 10^{+192}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;y \leq -1.44 \cdot 10^{+107}:\\ \;\;\;\;t\_3\\ \mathbf{elif}\;y \leq -7.2 \cdot 10^{-103}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;y \leq 9 \cdot 10^{-233}:\\ \;\;\;\;t\_3\\ \mathbf{elif}\;y \leq 8.5 \cdot 10^{+99}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;y \leq 1.46 \cdot 10^{+177}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;y \leq 2 \cdot 10^{+216}:\\ \;\;\;\;t\_2\\ \mathbf{else}:\\ \;\;\;\;i \cdot \left(y \cdot \left(k \cdot y5 - x \cdot c\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* y (* y5 (- (* i k) (* a y3)))))
        (t_2
         (*
          c
          (-
           (* y4 (- (* y y3) (* t y2)))
           (- (* x (- (* y i) (* y0 y2))) (* z (- (* t i) (* y0 y3)))))))
        (t_3
         (*
          y2
          (+
           (+ (* k (- (* y1 y4) (* y0 y5))) (* x (- (* c y0) (* a y1))))
           (* t (- (* a y5) (* c y4)))))))
   (if (<= y -1.8e+225)
     (* (* x y) (- (* a b) (* c i)))
     (if (<= y -8e+192)
       t_1
       (if (<= y -1.44e+107)
         t_3
         (if (<= y -7.2e-103)
           t_2
           (if (<= y 9e-233)
             t_3
             (if (<= y 8.5e+99)
               t_2
               (if (<= y 1.46e+177)
                 t_1
                 (if (<= y 2e+216)
                   t_2
                   (* i (* y (- (* k y5) (* x c))))))))))))))

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 = y * (y5 * ((i * k) - (a * y3)));
	double t_2 = c * ((y4 * ((y * y3) - (t * y2))) - ((x * ((y * i) - (y0 * y2))) - (z * ((t * i) - (y0 * y3)))));
	double t_3 = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))));
	double tmp;
	if (y <= -1.8e+225) {
		tmp = (x * y) * ((a * b) - (c * i));
	} else if (y <= -8e+192) {
		tmp = t_1;
	} else if (y <= -1.44e+107) {
		tmp = t_3;
	} else if (y <= -7.2e-103) {
		tmp = t_2;
	} else if (y <= 9e-233) {
		tmp = t_3;
	} else if (y <= 8.5e+99) {
		tmp = t_2;
	} else if (y <= 1.46e+177) {
		tmp = t_1;
	} else if (y <= 2e+216) {
		tmp = t_2;
	} else {
		tmp = i * (y * ((k * y5) - (x * c)));
	}
	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 = y * (y5 * ((i * k) - (a * y3)))
    t_2 = c * ((y4 * ((y * y3) - (t * y2))) - ((x * ((y * i) - (y0 * y2))) - (z * ((t * i) - (y0 * y3)))))
    t_3 = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))))
    if (y <= (-1.8d+225)) then
        tmp = (x * y) * ((a * b) - (c * i))
    else if (y <= (-8d+192)) then
        tmp = t_1
    else if (y <= (-1.44d+107)) then
        tmp = t_3
    else if (y <= (-7.2d-103)) then
        tmp = t_2
    else if (y <= 9d-233) then
        tmp = t_3
    else if (y <= 8.5d+99) then
        tmp = t_2
    else if (y <= 1.46d+177) then
        tmp = t_1
    else if (y <= 2d+216) then
        tmp = t_2
    else
        tmp = i * (y * ((k * y5) - (x * c)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y * (y5 * ((i * k) - (a * y3)));
	double t_2 = c * ((y4 * ((y * y3) - (t * y2))) - ((x * ((y * i) - (y0 * y2))) - (z * ((t * i) - (y0 * y3)))));
	double t_3 = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))));
	double tmp;
	if (y <= -1.8e+225) {
		tmp = (x * y) * ((a * b) - (c * i));
	} else if (y <= -8e+192) {
		tmp = t_1;
	} else if (y <= -1.44e+107) {
		tmp = t_3;
	} else if (y <= -7.2e-103) {
		tmp = t_2;
	} else if (y <= 9e-233) {
		tmp = t_3;
	} else if (y <= 8.5e+99) {
		tmp = t_2;
	} else if (y <= 1.46e+177) {
		tmp = t_1;
	} else if (y <= 2e+216) {
		tmp = t_2;
	} else {
		tmp = i * (y * ((k * y5) - (x * c)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = y * (y5 * ((i * k) - (a * y3)))
	t_2 = c * ((y4 * ((y * y3) - (t * y2))) - ((x * ((y * i) - (y0 * y2))) - (z * ((t * i) - (y0 * y3)))))
	t_3 = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))))
	tmp = 0
	if y <= -1.8e+225:
		tmp = (x * y) * ((a * b) - (c * i))
	elif y <= -8e+192:
		tmp = t_1
	elif y <= -1.44e+107:
		tmp = t_3
	elif y <= -7.2e-103:
		tmp = t_2
	elif y <= 9e-233:
		tmp = t_3
	elif y <= 8.5e+99:
		tmp = t_2
	elif y <= 1.46e+177:
		tmp = t_1
	elif y <= 2e+216:
		tmp = t_2
	else:
		tmp = i * (y * ((k * y5) - (x * c)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(y * Float64(y5 * Float64(Float64(i * k) - Float64(a * y3))))
	t_2 = Float64(c * Float64(Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2))) - Float64(Float64(x * Float64(Float64(y * i) - Float64(y0 * y2))) - Float64(z * Float64(Float64(t * i) - Float64(y0 * y3))))))
	t_3 = 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)))))
	tmp = 0.0
	if (y <= -1.8e+225)
		tmp = Float64(Float64(x * y) * Float64(Float64(a * b) - Float64(c * i)));
	elseif (y <= -8e+192)
		tmp = t_1;
	elseif (y <= -1.44e+107)
		tmp = t_3;
	elseif (y <= -7.2e-103)
		tmp = t_2;
	elseif (y <= 9e-233)
		tmp = t_3;
	elseif (y <= 8.5e+99)
		tmp = t_2;
	elseif (y <= 1.46e+177)
		tmp = t_1;
	elseif (y <= 2e+216)
		tmp = t_2;
	else
		tmp = Float64(i * Float64(y * Float64(Float64(k * y5) - Float64(x * c))));
	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 = y * (y5 * ((i * k) - (a * y3)));
	t_2 = c * ((y4 * ((y * y3) - (t * y2))) - ((x * ((y * i) - (y0 * y2))) - (z * ((t * i) - (y0 * y3)))));
	t_3 = y2 * (((k * ((y1 * y4) - (y0 * y5))) + (x * ((c * y0) - (a * y1)))) + (t * ((a * y5) - (c * y4))));
	tmp = 0.0;
	if (y <= -1.8e+225)
		tmp = (x * y) * ((a * b) - (c * i));
	elseif (y <= -8e+192)
		tmp = t_1;
	elseif (y <= -1.44e+107)
		tmp = t_3;
	elseif (y <= -7.2e-103)
		tmp = t_2;
	elseif (y <= 9e-233)
		tmp = t_3;
	elseif (y <= 8.5e+99)
		tmp = t_2;
	elseif (y <= 1.46e+177)
		tmp = t_1;
	elseif (y <= 2e+216)
		tmp = t_2;
	else
		tmp = i * (y * ((k * y5) - (x * c)));
	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[(y * N[(y5 * N[(N[(i * k), $MachinePrecision] - N[(a * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(c * N[(N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(x * N[(N[(y * i), $MachinePrecision] - N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(z * N[(N[(t * i), $MachinePrecision] - N[(y0 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = 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[y, -1.8e+225], N[(N[(x * y), $MachinePrecision] * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -8e+192], t$95$1, If[LessEqual[y, -1.44e+107], t$95$3, If[LessEqual[y, -7.2e-103], t$95$2, If[LessEqual[y, 9e-233], t$95$3, If[LessEqual[y, 8.5e+99], t$95$2, If[LessEqual[y, 1.46e+177], t$95$1, If[LessEqual[y, 2e+216], t$95$2, N[(i * N[(y * N[(N[(k * y5), $MachinePrecision] - N[(x * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]

Derivation

1. Split input into 5 regimes

2. if y < -1.7999999999999999e225

   1. Initial program 18.8%

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

   3. Taylor expanded in y around inf 56.3%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in x around inf 63.2%

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

      1. associate-*r* 63.4%

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

      2. *-commutative 63.4%

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

   6. Simplified 63.4%

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

   if -1.7999999999999999e225 < y < -8.00000000000000033e192 or 8.49999999999999984e99 < y < 1.4599999999999999e177

   1. Initial program 22.0%

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

   3. Taylor expanded in y around inf 48.2%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y5 around inf 78.8%

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

   if -8.00000000000000033e192 < y < -1.44e107 or -7.1999999999999996e-103 < y < 9.0000000000000004e-233

   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. Add Preprocessing

   3. Taylor expanded in y2 around inf 57.2%

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

   if -1.44e107 < y < -7.1999999999999996e-103 or 9.0000000000000004e-233 < y < 8.49999999999999984e99 or 1.4599999999999999e177 < y < 2e216

   1. Initial program 30.1%

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

   3. Taylor expanded in c around inf 48.4%

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

   4. Taylor expanded in x around -inf 49.1%

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

   6. Simplified 53.1%

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

   if 2e216 < y

   1. Initial program 23.5%

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

   3. Taylor expanded in y around inf 41.5%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in i around inf 82.4%

      \[\leadsto \color{blue}{i \cdot \left(y \cdot \left(-1 \cdot \left(c \cdot x\right) + k \cdot y5\right)\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 59.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y \leq -1.8 \cdot 10^{+225}:\\ \;\;\;\;\left(x \cdot y\right) \cdot \left(a \cdot b - c \cdot i\right)\\ \mathbf{elif}\;y \leq -8 \cdot 10^{+192}:\\ \;\;\;\;y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)\\ \mathbf{elif}\;y \leq -1.44 \cdot 10^{+107}:\\ \;\;\;\;y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq -7.2 \cdot 10^{-103}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right) - \left(x \cdot \left(y \cdot i - y0 \cdot y2\right) - z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)\right)\\ \mathbf{elif}\;y \leq 9 \cdot 10^{-233}:\\ \;\;\;\;y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq 8.5 \cdot 10^{+99}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right) - \left(x \cdot \left(y \cdot i - y0 \cdot y2\right) - z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)\right)\\ \mathbf{elif}\;y \leq 1.46 \cdot 10^{+177}:\\ \;\;\;\;y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)\\ \mathbf{elif}\;y \leq 2 \cdot 10^{+216}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right) - \left(x \cdot \left(y \cdot i - y0 \cdot y2\right) - z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;i \cdot \left(y \cdot \left(k \cdot y5 - x \cdot c\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 6: 33.8% accurate, 1.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right) + x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{if}\;k \leq -8.4 \cdot 10^{+101}:\\ \;\;\;\;i \cdot \left(y \cdot \left(k \cdot y5 - x \cdot c\right)\right)\\ \mathbf{elif}\;k \leq -8 \cdot 10^{-15}:\\ \;\;\;\;y4 \cdot \left(y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;k \leq -1.22 \cdot 10^{-152}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;k \leq -4.1 \cdot 10^{-181}:\\ \;\;\;\;t \cdot \left(y4 \cdot \left(b \cdot j - c \cdot y2\right)\right)\\ \mathbf{elif}\;k \leq 6.2 \cdot 10^{-10}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;k \leq 5.7 \cdot 10^{+88}:\\ \;\;\;\;y5 \cdot \left(y2 \cdot \left(t \cdot a - k \cdot y0\right)\right)\\ \mathbf{elif}\;k \leq 4.5 \cdot 10^{+146}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;k \leq 10^{+195}:\\ \;\;\;\;y2 \cdot \left(y4 \cdot \left(k \cdot y1 - t \cdot c\right)\right)\\ \mathbf{elif}\;k \leq 6.5 \cdot 10^{+248}:\\ \;\;\;\;y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(\left(t \cdot j - y \cdot k\right) \cdot y4 + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1
         (* c (+ (* z (- (* t i) (* y0 y3))) (* x (- (* y0 y2) (* y i)))))))
   (if (<= k -8.4e+101)
     (* i (* y (- (* k y5) (* x c))))
     (if (<= k -8e-15)
       (* y4 (* y1 (- (* k y2) (* j y3))))
       (if (<= k -1.22e-152)
         t_1
         (if (<= k -4.1e-181)
           (* t (* y4 (- (* b j) (* c y2))))
           (if (<= k 6.2e-10)
             t_1
             (if (<= k 5.7e+88)
               (* y5 (* y2 (- (* t a) (* k y0))))
               (if (<= k 4.5e+146)
                 (* i (* k (- (* y y5) (* z y1))))
                 (if (<= k 1e+195)
                   (* y2 (* y4 (- (* k y1) (* t c))))
                   (if (<= k 6.5e+248)
                     (* y (* y5 (- (* i k) (* a y3))))
                     (*
                      b
                      (+
                       (* (- (* t j) (* y k)) y4)
                       (* y0 (- (* 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 = c * ((z * ((t * i) - (y0 * y3))) + (x * ((y0 * y2) - (y * i))));
	double tmp;
	if (k <= -8.4e+101) {
		tmp = i * (y * ((k * y5) - (x * c)));
	} else if (k <= -8e-15) {
		tmp = y4 * (y1 * ((k * y2) - (j * y3)));
	} else if (k <= -1.22e-152) {
		tmp = t_1;
	} else if (k <= -4.1e-181) {
		tmp = t * (y4 * ((b * j) - (c * y2)));
	} else if (k <= 6.2e-10) {
		tmp = t_1;
	} else if (k <= 5.7e+88) {
		tmp = y5 * (y2 * ((t * a) - (k * y0)));
	} else if (k <= 4.5e+146) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (k <= 1e+195) {
		tmp = y2 * (y4 * ((k * y1) - (t * c)));
	} else if (k <= 6.5e+248) {
		tmp = y * (y5 * ((i * k) - (a * y3)));
	} else {
		tmp = b * ((((t * j) - (y * k)) * y4) + (y0 * ((z * k) - (x * j))));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = c * ((z * ((t * i) - (y0 * y3))) + (x * ((y0 * y2) - (y * i))))
    if (k <= (-8.4d+101)) then
        tmp = i * (y * ((k * y5) - (x * c)))
    else if (k <= (-8d-15)) then
        tmp = y4 * (y1 * ((k * y2) - (j * y3)))
    else if (k <= (-1.22d-152)) then
        tmp = t_1
    else if (k <= (-4.1d-181)) then
        tmp = t * (y4 * ((b * j) - (c * y2)))
    else if (k <= 6.2d-10) then
        tmp = t_1
    else if (k <= 5.7d+88) then
        tmp = y5 * (y2 * ((t * a) - (k * y0)))
    else if (k <= 4.5d+146) then
        tmp = i * (k * ((y * y5) - (z * y1)))
    else if (k <= 1d+195) then
        tmp = y2 * (y4 * ((k * y1) - (t * c)))
    else if (k <= 6.5d+248) then
        tmp = y * (y5 * ((i * k) - (a * y3)))
    else
        tmp = b * ((((t * j) - (y * k)) * y4) + (y0 * ((z * k) - (x * j))))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = c * ((z * ((t * i) - (y0 * y3))) + (x * ((y0 * y2) - (y * i))));
	double tmp;
	if (k <= -8.4e+101) {
		tmp = i * (y * ((k * y5) - (x * c)));
	} else if (k <= -8e-15) {
		tmp = y4 * (y1 * ((k * y2) - (j * y3)));
	} else if (k <= -1.22e-152) {
		tmp = t_1;
	} else if (k <= -4.1e-181) {
		tmp = t * (y4 * ((b * j) - (c * y2)));
	} else if (k <= 6.2e-10) {
		tmp = t_1;
	} else if (k <= 5.7e+88) {
		tmp = y5 * (y2 * ((t * a) - (k * y0)));
	} else if (k <= 4.5e+146) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (k <= 1e+195) {
		tmp = y2 * (y4 * ((k * y1) - (t * c)));
	} else if (k <= 6.5e+248) {
		tmp = y * (y5 * ((i * k) - (a * y3)));
	} else {
		tmp = b * ((((t * j) - (y * k)) * y4) + (y0 * ((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 = c * ((z * ((t * i) - (y0 * y3))) + (x * ((y0 * y2) - (y * i))))
	tmp = 0
	if k <= -8.4e+101:
		tmp = i * (y * ((k * y5) - (x * c)))
	elif k <= -8e-15:
		tmp = y4 * (y1 * ((k * y2) - (j * y3)))
	elif k <= -1.22e-152:
		tmp = t_1
	elif k <= -4.1e-181:
		tmp = t * (y4 * ((b * j) - (c * y2)))
	elif k <= 6.2e-10:
		tmp = t_1
	elif k <= 5.7e+88:
		tmp = y5 * (y2 * ((t * a) - (k * y0)))
	elif k <= 4.5e+146:
		tmp = i * (k * ((y * y5) - (z * y1)))
	elif k <= 1e+195:
		tmp = y2 * (y4 * ((k * y1) - (t * c)))
	elif k <= 6.5e+248:
		tmp = y * (y5 * ((i * k) - (a * y3)))
	else:
		tmp = b * ((((t * j) - (y * k)) * y4) + (y0 * ((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(c * Float64(Float64(z * Float64(Float64(t * i) - Float64(y0 * y3))) + Float64(x * Float64(Float64(y0 * y2) - Float64(y * i)))))
	tmp = 0.0
	if (k <= -8.4e+101)
		tmp = Float64(i * Float64(y * Float64(Float64(k * y5) - Float64(x * c))));
	elseif (k <= -8e-15)
		tmp = Float64(y4 * Float64(y1 * Float64(Float64(k * y2) - Float64(j * y3))));
	elseif (k <= -1.22e-152)
		tmp = t_1;
	elseif (k <= -4.1e-181)
		tmp = Float64(t * Float64(y4 * Float64(Float64(b * j) - Float64(c * y2))));
	elseif (k <= 6.2e-10)
		tmp = t_1;
	elseif (k <= 5.7e+88)
		tmp = Float64(y5 * Float64(y2 * Float64(Float64(t * a) - Float64(k * y0))));
	elseif (k <= 4.5e+146)
		tmp = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))));
	elseif (k <= 1e+195)
		tmp = Float64(y2 * Float64(y4 * Float64(Float64(k * y1) - Float64(t * c))));
	elseif (k <= 6.5e+248)
		tmp = Float64(y * Float64(y5 * Float64(Float64(i * k) - Float64(a * y3))));
	else
		tmp = Float64(b * Float64(Float64(Float64(Float64(t * j) - Float64(y * k)) * y4) + Float64(y0 * 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 = c * ((z * ((t * i) - (y0 * y3))) + (x * ((y0 * y2) - (y * i))));
	tmp = 0.0;
	if (k <= -8.4e+101)
		tmp = i * (y * ((k * y5) - (x * c)));
	elseif (k <= -8e-15)
		tmp = y4 * (y1 * ((k * y2) - (j * y3)));
	elseif (k <= -1.22e-152)
		tmp = t_1;
	elseif (k <= -4.1e-181)
		tmp = t * (y4 * ((b * j) - (c * y2)));
	elseif (k <= 6.2e-10)
		tmp = t_1;
	elseif (k <= 5.7e+88)
		tmp = y5 * (y2 * ((t * a) - (k * y0)));
	elseif (k <= 4.5e+146)
		tmp = i * (k * ((y * y5) - (z * y1)));
	elseif (k <= 1e+195)
		tmp = y2 * (y4 * ((k * y1) - (t * c)));
	elseif (k <= 6.5e+248)
		tmp = y * (y5 * ((i * k) - (a * y3)));
	else
		tmp = b * ((((t * j) - (y * k)) * y4) + (y0 * ((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[(c * N[(N[(z * N[(N[(t * i), $MachinePrecision] - N[(y0 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(x * N[(N[(y0 * y2), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[k, -8.4e+101], N[(i * N[(y * N[(N[(k * y5), $MachinePrecision] - N[(x * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, -8e-15], N[(y4 * N[(y1 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, -1.22e-152], t$95$1, If[LessEqual[k, -4.1e-181], N[(t * N[(y4 * N[(N[(b * j), $MachinePrecision] - N[(c * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 6.2e-10], t$95$1, If[LessEqual[k, 5.7e+88], N[(y5 * N[(y2 * N[(N[(t * a), $MachinePrecision] - N[(k * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 4.5e+146], N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 1e+195], N[(y2 * N[(y4 * N[(N[(k * y1), $MachinePrecision] - N[(t * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 6.5e+248], N[(y * N[(y5 * N[(N[(i * k), $MachinePrecision] - N[(a * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(N[(N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision] * y4), $MachinePrecision] + N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]

Derivation

1. Split input into 9 regimes

2. if k < -8.4000000000000001e101

   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. Add Preprocessing

   3. Taylor expanded in y around inf 34.1%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in i around inf 57.3%

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

   if -8.4000000000000001e101 < k < -8.0000000000000006e-15

   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. Add Preprocessing

   3. Taylor expanded in y4 around inf 41.6%

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

   4. Taylor expanded in y1 around inf 52.8%

      \[\leadsto y4 \cdot \color{blue}{\left(y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 52.8%

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

      2. *-commutative 52.8%

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

   6. Simplified 52.8%

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

   if -8.0000000000000006e-15 < k < -1.22000000000000009e-152 or -4.1000000000000001e-181 < k < 6.2000000000000003e-10

   1. Initial program 41.8%

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

   3. Taylor expanded in c around inf 53.1%

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

   4. Taylor expanded in x around -inf 54.7%

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

   6. Simplified 57.5%

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

   7. Taylor expanded in y4 around 0 56.6%

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

   if -1.22000000000000009e-152 < k < -4.1000000000000001e-181

   1. Initial program 33.3%

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

   3. Taylor expanded in y4 around inf 56.3%

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

   4. Taylor expanded in t around inf 57.3%

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

   if 6.2000000000000003e-10 < k < 5.70000000000000021e88

   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. Add Preprocessing

   3. Taylor expanded in y5 around -inf 56.3%

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

   4. Taylor expanded in y2 around inf 57.3%

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

      1. *-commutative 57.3%

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

      2. *-commutative 57.3%

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

   6. Simplified 57.3%

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

   if 5.70000000000000021e88 < k < 4.50000000000000026e146

   1. Initial program 12.5%

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

   3. Taylor expanded in k around -inf 50.0%

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

      1. mul-1-neg 50.0%

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

      2. distribute-rgt-neg-in 50.0%

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

      3. +-commutative 50.0%

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

      4. mul-1-neg 50.0%

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

      5. unsub-neg 50.0%

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

      6. *-commutative 50.0%

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

   5. Simplified 50.0%

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

   6. Taylor expanded in i around inf 75.2%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(-1 \cdot \left(y1 \cdot z\right) - -1 \cdot \left(y \cdot y5\right)\right)\right)} \]
   7. Step-by-step derivation

      1. distribute-lft-out-- 75.2%

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

      2. *-commutative 75.2%

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

   8. Simplified 75.2%

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

   if 4.50000000000000026e146 < k < 9.99999999999999977e194

   1. Initial program 34.0%

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

   3. Taylor expanded in y4 around inf 78.4%

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

   4. Taylor expanded in y2 around inf 67.3%

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

   if 9.99999999999999977e194 < k < 6.50000000000000048e248

   1. Initial program 15.9%

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

   3. Taylor expanded in y around inf 39.2%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y5 around inf 70.0%

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

   if 6.50000000000000048e248 < k

   1. Initial program 39.0%

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

   3. Taylor expanded in b around inf 54.4%

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

   4. Taylor expanded in a around 0 70.0%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 70.0%

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

      2. *-commutative 70.0%

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

      3. *-commutative 70.0%

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

      4. *-commutative 70.0%

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

   6. Simplified 70.0%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - z \cdot k\right)\right)} \]
3. Recombined 9 regimes into one program.

4. Final simplification 58.7%

   \[\leadsto \begin{array}{l} \mathbf{if}\;k \leq -8.4 \cdot 10^{+101}:\\ \;\;\;\;i \cdot \left(y \cdot \left(k \cdot y5 - x \cdot c\right)\right)\\ \mathbf{elif}\;k \leq -8 \cdot 10^{-15}:\\ \;\;\;\;y4 \cdot \left(y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;k \leq -1.22 \cdot 10^{-152}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right) + x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{elif}\;k \leq -4.1 \cdot 10^{-181}:\\ \;\;\;\;t \cdot \left(y4 \cdot \left(b \cdot j - c \cdot y2\right)\right)\\ \mathbf{elif}\;k \leq 6.2 \cdot 10^{-10}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right) + x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{elif}\;k \leq 5.7 \cdot 10^{+88}:\\ \;\;\;\;y5 \cdot \left(y2 \cdot \left(t \cdot a - k \cdot y0\right)\right)\\ \mathbf{elif}\;k \leq 4.5 \cdot 10^{+146}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;k \leq 10^{+195}:\\ \;\;\;\;y2 \cdot \left(y4 \cdot \left(k \cdot y1 - t \cdot c\right)\right)\\ \mathbf{elif}\;k \leq 6.5 \cdot 10^{+248}:\\ \;\;\;\;y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(\left(t \cdot j - y \cdot k\right) \cdot y4 + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 7: 30.2% accurate, 1.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;k \leq -6.5 \cdot 10^{+99}:\\ \;\;\;\;i \cdot \left(y \cdot \left(k \cdot y5 - x \cdot c\right)\right)\\ \mathbf{elif}\;k \leq -3.8 \cdot 10^{+25}:\\ \;\;\;\;y4 \cdot \left(y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;k \leq 1.95 \cdot 10^{-159}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)\\ \mathbf{elif}\;k \leq 9 \cdot 10^{-14}:\\ \;\;\;\;c \cdot \left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right)\right)\\ \mathbf{elif}\;k \leq 4.8 \cdot 10^{+90}:\\ \;\;\;\;y5 \cdot \left(y2 \cdot \left(t \cdot a - k \cdot y0\right)\right)\\ \mathbf{elif}\;k \leq 4.8 \cdot 10^{+146}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;k \leq 3 \cdot 10^{+199}:\\ \;\;\;\;y2 \cdot \left(y4 \cdot \left(k \cdot y1 - t \cdot c\right)\right)\\ \mathbf{elif}\;k \leq 1.65 \cdot 10^{+246}:\\ \;\;\;\;y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(\left(t \cdot j - y \cdot k\right) \cdot y4 + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= k -6.5e+99)
   (* i (* y (- (* k y5) (* x c))))
   (if (<= k -3.8e+25)
     (* y4 (* y1 (- (* k y2) (* j y3))))
     (if (<= k 1.95e-159)
       (* c (* z (- (* t i) (* y0 y3))))
       (if (<= k 9e-14)
         (* c (* y0 (- (* x y2) (* z y3))))
         (if (<= k 4.8e+90)
           (* y5 (* y2 (- (* t a) (* k y0))))
           (if (<= k 4.8e+146)
             (* i (* k (- (* y y5) (* z y1))))
             (if (<= k 3e+199)
               (* y2 (* y4 (- (* k y1) (* t c))))
               (if (<= k 1.65e+246)
                 (* y (* y5 (- (* i k) (* a y3))))
                 (*
                  b
                  (+
                   (* (- (* t j) (* y k)) y4)
                   (* y0 (- (* 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 tmp;
	if (k <= -6.5e+99) {
		tmp = i * (y * ((k * y5) - (x * c)));
	} else if (k <= -3.8e+25) {
		tmp = y4 * (y1 * ((k * y2) - (j * y3)));
	} else if (k <= 1.95e-159) {
		tmp = c * (z * ((t * i) - (y0 * y3)));
	} else if (k <= 9e-14) {
		tmp = c * (y0 * ((x * y2) - (z * y3)));
	} else if (k <= 4.8e+90) {
		tmp = y5 * (y2 * ((t * a) - (k * y0)));
	} else if (k <= 4.8e+146) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (k <= 3e+199) {
		tmp = y2 * (y4 * ((k * y1) - (t * c)));
	} else if (k <= 1.65e+246) {
		tmp = y * (y5 * ((i * k) - (a * y3)));
	} else {
		tmp = b * ((((t * j) - (y * k)) * y4) + (y0 * ((z * k) - (x * j))));
	}
	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 (k <= (-6.5d+99)) then
        tmp = i * (y * ((k * y5) - (x * c)))
    else if (k <= (-3.8d+25)) then
        tmp = y4 * (y1 * ((k * y2) - (j * y3)))
    else if (k <= 1.95d-159) then
        tmp = c * (z * ((t * i) - (y0 * y3)))
    else if (k <= 9d-14) then
        tmp = c * (y0 * ((x * y2) - (z * y3)))
    else if (k <= 4.8d+90) then
        tmp = y5 * (y2 * ((t * a) - (k * y0)))
    else if (k <= 4.8d+146) then
        tmp = i * (k * ((y * y5) - (z * y1)))
    else if (k <= 3d+199) then
        tmp = y2 * (y4 * ((k * y1) - (t * c)))
    else if (k <= 1.65d+246) then
        tmp = y * (y5 * ((i * k) - (a * y3)))
    else
        tmp = b * ((((t * j) - (y * k)) * y4) + (y0 * ((z * k) - (x * j))))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (k <= -6.5e+99) {
		tmp = i * (y * ((k * y5) - (x * c)));
	} else if (k <= -3.8e+25) {
		tmp = y4 * (y1 * ((k * y2) - (j * y3)));
	} else if (k <= 1.95e-159) {
		tmp = c * (z * ((t * i) - (y0 * y3)));
	} else if (k <= 9e-14) {
		tmp = c * (y0 * ((x * y2) - (z * y3)));
	} else if (k <= 4.8e+90) {
		tmp = y5 * (y2 * ((t * a) - (k * y0)));
	} else if (k <= 4.8e+146) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (k <= 3e+199) {
		tmp = y2 * (y4 * ((k * y1) - (t * c)));
	} else if (k <= 1.65e+246) {
		tmp = y * (y5 * ((i * k) - (a * y3)));
	} else {
		tmp = b * ((((t * j) - (y * k)) * y4) + (y0 * ((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):
	tmp = 0
	if k <= -6.5e+99:
		tmp = i * (y * ((k * y5) - (x * c)))
	elif k <= -3.8e+25:
		tmp = y4 * (y1 * ((k * y2) - (j * y3)))
	elif k <= 1.95e-159:
		tmp = c * (z * ((t * i) - (y0 * y3)))
	elif k <= 9e-14:
		tmp = c * (y0 * ((x * y2) - (z * y3)))
	elif k <= 4.8e+90:
		tmp = y5 * (y2 * ((t * a) - (k * y0)))
	elif k <= 4.8e+146:
		tmp = i * (k * ((y * y5) - (z * y1)))
	elif k <= 3e+199:
		tmp = y2 * (y4 * ((k * y1) - (t * c)))
	elif k <= 1.65e+246:
		tmp = y * (y5 * ((i * k) - (a * y3)))
	else:
		tmp = b * ((((t * j) - (y * k)) * y4) + (y0 * ((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)
	tmp = 0.0
	if (k <= -6.5e+99)
		tmp = Float64(i * Float64(y * Float64(Float64(k * y5) - Float64(x * c))));
	elseif (k <= -3.8e+25)
		tmp = Float64(y4 * Float64(y1 * Float64(Float64(k * y2) - Float64(j * y3))));
	elseif (k <= 1.95e-159)
		tmp = Float64(c * Float64(z * Float64(Float64(t * i) - Float64(y0 * y3))));
	elseif (k <= 9e-14)
		tmp = Float64(c * Float64(y0 * Float64(Float64(x * y2) - Float64(z * y3))));
	elseif (k <= 4.8e+90)
		tmp = Float64(y5 * Float64(y2 * Float64(Float64(t * a) - Float64(k * y0))));
	elseif (k <= 4.8e+146)
		tmp = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))));
	elseif (k <= 3e+199)
		tmp = Float64(y2 * Float64(y4 * Float64(Float64(k * y1) - Float64(t * c))));
	elseif (k <= 1.65e+246)
		tmp = Float64(y * Float64(y5 * Float64(Float64(i * k) - Float64(a * y3))));
	else
		tmp = Float64(b * Float64(Float64(Float64(Float64(t * j) - Float64(y * k)) * y4) + Float64(y0 * 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)
	tmp = 0.0;
	if (k <= -6.5e+99)
		tmp = i * (y * ((k * y5) - (x * c)));
	elseif (k <= -3.8e+25)
		tmp = y4 * (y1 * ((k * y2) - (j * y3)));
	elseif (k <= 1.95e-159)
		tmp = c * (z * ((t * i) - (y0 * y3)));
	elseif (k <= 9e-14)
		tmp = c * (y0 * ((x * y2) - (z * y3)));
	elseif (k <= 4.8e+90)
		tmp = y5 * (y2 * ((t * a) - (k * y0)));
	elseif (k <= 4.8e+146)
		tmp = i * (k * ((y * y5) - (z * y1)));
	elseif (k <= 3e+199)
		tmp = y2 * (y4 * ((k * y1) - (t * c)));
	elseif (k <= 1.65e+246)
		tmp = y * (y5 * ((i * k) - (a * y3)));
	else
		tmp = b * ((((t * j) - (y * k)) * y4) + (y0 * ((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_] := If[LessEqual[k, -6.5e+99], N[(i * N[(y * N[(N[(k * y5), $MachinePrecision] - N[(x * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, -3.8e+25], N[(y4 * N[(y1 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 1.95e-159], N[(c * N[(z * N[(N[(t * i), $MachinePrecision] - N[(y0 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 9e-14], N[(c * N[(y0 * N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 4.8e+90], N[(y5 * N[(y2 * N[(N[(t * a), $MachinePrecision] - N[(k * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 4.8e+146], N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 3e+199], N[(y2 * N[(y4 * N[(N[(k * y1), $MachinePrecision] - N[(t * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 1.65e+246], N[(y * N[(y5 * N[(N[(i * k), $MachinePrecision] - N[(a * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(N[(N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision] * y4), $MachinePrecision] + N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]

Derivation

1. Split input into 9 regimes

2. if k < -6.5000000000000004e99

   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. Add Preprocessing

   3. Taylor expanded in y around inf 34.1%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in i around inf 57.3%

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

   if -6.5000000000000004e99 < k < -3.8e25

   1. Initial program 33.2%

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

   3. Taylor expanded in y4 around inf 40.7%

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

   4. Taylor expanded in y1 around inf 67.1%

      \[\leadsto y4 \cdot \color{blue}{\left(y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 67.1%

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

      2. *-commutative 67.1%

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

   6. Simplified 67.1%

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

   if -3.8e25 < k < 1.94999999999999988e-159

   1. Initial program 36.8%

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

   3. Taylor expanded in c around inf 48.3%

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

   4. Taylor expanded in z around inf 40.1%

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

      1. +-commutative 40.1%

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

      2. mul-1-neg 40.1%

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

      3. unsub-neg 40.1%

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

      4. *-commutative 40.1%

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

   6. Simplified 40.1%

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

   if 1.94999999999999988e-159 < k < 8.9999999999999995e-14

   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. Add Preprocessing

   3. Taylor expanded in c around inf 54.7%

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

   4. Taylor expanded in y0 around inf 59.7%

      \[\leadsto \color{blue}{c \cdot \left(y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right)} \]

   if 8.9999999999999995e-14 < k < 4.8000000000000002e90

   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. Add Preprocessing

   3. Taylor expanded in y5 around -inf 56.3%

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

   4. Taylor expanded in y2 around inf 57.3%

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

      1. *-commutative 57.3%

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

      2. *-commutative 57.3%

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

   6. Simplified 57.3%

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

   if 4.8000000000000002e90 < k < 4.8000000000000004e146

   1. Initial program 12.5%

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

   3. Taylor expanded in k around -inf 50.0%

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

      1. mul-1-neg 50.0%

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

      2. distribute-rgt-neg-in 50.0%

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

      3. +-commutative 50.0%

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

      4. mul-1-neg 50.0%

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

      5. unsub-neg 50.0%

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

      6. *-commutative 50.0%

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

   5. Simplified 50.0%

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

   6. Taylor expanded in i around inf 75.2%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(-1 \cdot \left(y1 \cdot z\right) - -1 \cdot \left(y \cdot y5\right)\right)\right)} \]
   7. Step-by-step derivation

      1. distribute-lft-out-- 75.2%

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

      2. *-commutative 75.2%

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

   8. Simplified 75.2%

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

   if 4.8000000000000004e146 < k < 3.0000000000000001e199

   1. Initial program 34.0%

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

   3. Taylor expanded in y4 around inf 78.4%

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

   4. Taylor expanded in y2 around inf 67.3%

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

   if 3.0000000000000001e199 < k < 1.65e246

   1. Initial program 15.9%

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

   3. Taylor expanded in y around inf 39.2%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y5 around inf 70.0%

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

   if 1.65e246 < k

   1. Initial program 39.0%

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

   3. Taylor expanded in b around inf 54.4%

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

   4. Taylor expanded in a around 0 70.0%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 70.0%

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

      2. *-commutative 70.0%

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

      3. *-commutative 70.0%

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

      4. *-commutative 70.0%

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

   6. Simplified 70.0%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - z \cdot k\right)\right)} \]
3. Recombined 9 regimes into one program.

4. Final simplification 52.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;k \leq -6.5 \cdot 10^{+99}:\\ \;\;\;\;i \cdot \left(y \cdot \left(k \cdot y5 - x \cdot c\right)\right)\\ \mathbf{elif}\;k \leq -3.8 \cdot 10^{+25}:\\ \;\;\;\;y4 \cdot \left(y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;k \leq 1.95 \cdot 10^{-159}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)\\ \mathbf{elif}\;k \leq 9 \cdot 10^{-14}:\\ \;\;\;\;c \cdot \left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right)\right)\\ \mathbf{elif}\;k \leq 4.8 \cdot 10^{+90}:\\ \;\;\;\;y5 \cdot \left(y2 \cdot \left(t \cdot a - k \cdot y0\right)\right)\\ \mathbf{elif}\;k \leq 4.8 \cdot 10^{+146}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;k \leq 3 \cdot 10^{+199}:\\ \;\;\;\;y2 \cdot \left(y4 \cdot \left(k \cdot y1 - t \cdot c\right)\right)\\ \mathbf{elif}\;k \leq 1.65 \cdot 10^{+246}:\\ \;\;\;\;y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(\left(t \cdot j - y \cdot k\right) \cdot y4 + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 8: 34.5% accurate, 1.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y5 \cdot \left(y2 \cdot \left(t \cdot a - k \cdot y0\right)\right)\\ t_2 := c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right) + x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{if}\;k \leq -2.4 \cdot 10^{+102}:\\ \;\;\;\;i \cdot \left(y \cdot \left(k \cdot y5 - x \cdot c\right)\right)\\ \mathbf{elif}\;k \leq -2.4 \cdot 10^{-14}:\\ \;\;\;\;y4 \cdot \left(y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;k \leq -1 \cdot 10^{-152}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;k \leq -1.5 \cdot 10^{-182}:\\ \;\;\;\;t \cdot \left(y4 \cdot \left(b \cdot j - c \cdot y2\right)\right)\\ \mathbf{elif}\;k \leq 1.7 \cdot 10^{-13}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;k \leq 1.25 \cdot 10^{+89}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;k \leq 2.3 \cdot 10^{+220}:\\ \;\;\;\;k \cdot \left(\left(z \cdot \left(b \cdot y0 - i \cdot y1\right) - y0 \cdot \left(y2 \cdot y5\right)\right) + i \cdot \left(y \cdot y5\right)\right)\\ \mathbf{elif}\;k \leq 4.6 \cdot 10^{+244}:\\ \;\;\;\;t\_1\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(\left(t \cdot j - y \cdot k\right) \cdot y4 + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* y5 (* y2 (- (* t a) (* k y0)))))
        (t_2
         (* c (+ (* z (- (* t i) (* y0 y3))) (* x (- (* y0 y2) (* y i)))))))
   (if (<= k -2.4e+102)
     (* i (* y (- (* k y5) (* x c))))
     (if (<= k -2.4e-14)
       (* y4 (* y1 (- (* k y2) (* j y3))))
       (if (<= k -1e-152)
         t_2
         (if (<= k -1.5e-182)
           (* t (* y4 (- (* b j) (* c y2))))
           (if (<= k 1.7e-13)
             t_2
             (if (<= k 1.25e+89)
               t_1
               (if (<= k 2.3e+220)
                 (*
                  k
                  (+
                   (- (* z (- (* b y0) (* i y1))) (* y0 (* y2 y5)))
                   (* i (* y y5))))
                 (if (<= k 4.6e+244)
                   t_1
                   (*
                    b
                    (+
                     (* (- (* t j) (* y k)) y4)
                     (* y0 (- (* 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 = y5 * (y2 * ((t * a) - (k * y0)));
	double t_2 = c * ((z * ((t * i) - (y0 * y3))) + (x * ((y0 * y2) - (y * i))));
	double tmp;
	if (k <= -2.4e+102) {
		tmp = i * (y * ((k * y5) - (x * c)));
	} else if (k <= -2.4e-14) {
		tmp = y4 * (y1 * ((k * y2) - (j * y3)));
	} else if (k <= -1e-152) {
		tmp = t_2;
	} else if (k <= -1.5e-182) {
		tmp = t * (y4 * ((b * j) - (c * y2)));
	} else if (k <= 1.7e-13) {
		tmp = t_2;
	} else if (k <= 1.25e+89) {
		tmp = t_1;
	} else if (k <= 2.3e+220) {
		tmp = k * (((z * ((b * y0) - (i * y1))) - (y0 * (y2 * y5))) + (i * (y * y5)));
	} else if (k <= 4.6e+244) {
		tmp = t_1;
	} else {
		tmp = b * ((((t * j) - (y * k)) * y4) + (y0 * ((z * k) - (x * j))));
	}
	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 = y5 * (y2 * ((t * a) - (k * y0)))
    t_2 = c * ((z * ((t * i) - (y0 * y3))) + (x * ((y0 * y2) - (y * i))))
    if (k <= (-2.4d+102)) then
        tmp = i * (y * ((k * y5) - (x * c)))
    else if (k <= (-2.4d-14)) then
        tmp = y4 * (y1 * ((k * y2) - (j * y3)))
    else if (k <= (-1d-152)) then
        tmp = t_2
    else if (k <= (-1.5d-182)) then
        tmp = t * (y4 * ((b * j) - (c * y2)))
    else if (k <= 1.7d-13) then
        tmp = t_2
    else if (k <= 1.25d+89) then
        tmp = t_1
    else if (k <= 2.3d+220) then
        tmp = k * (((z * ((b * y0) - (i * y1))) - (y0 * (y2 * y5))) + (i * (y * y5)))
    else if (k <= 4.6d+244) then
        tmp = t_1
    else
        tmp = b * ((((t * j) - (y * k)) * y4) + (y0 * ((z * k) - (x * j))))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y5 * (y2 * ((t * a) - (k * y0)));
	double t_2 = c * ((z * ((t * i) - (y0 * y3))) + (x * ((y0 * y2) - (y * i))));
	double tmp;
	if (k <= -2.4e+102) {
		tmp = i * (y * ((k * y5) - (x * c)));
	} else if (k <= -2.4e-14) {
		tmp = y4 * (y1 * ((k * y2) - (j * y3)));
	} else if (k <= -1e-152) {
		tmp = t_2;
	} else if (k <= -1.5e-182) {
		tmp = t * (y4 * ((b * j) - (c * y2)));
	} else if (k <= 1.7e-13) {
		tmp = t_2;
	} else if (k <= 1.25e+89) {
		tmp = t_1;
	} else if (k <= 2.3e+220) {
		tmp = k * (((z * ((b * y0) - (i * y1))) - (y0 * (y2 * y5))) + (i * (y * y5)));
	} else if (k <= 4.6e+244) {
		tmp = t_1;
	} else {
		tmp = b * ((((t * j) - (y * k)) * y4) + (y0 * ((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 = y5 * (y2 * ((t * a) - (k * y0)))
	t_2 = c * ((z * ((t * i) - (y0 * y3))) + (x * ((y0 * y2) - (y * i))))
	tmp = 0
	if k <= -2.4e+102:
		tmp = i * (y * ((k * y5) - (x * c)))
	elif k <= -2.4e-14:
		tmp = y4 * (y1 * ((k * y2) - (j * y3)))
	elif k <= -1e-152:
		tmp = t_2
	elif k <= -1.5e-182:
		tmp = t * (y4 * ((b * j) - (c * y2)))
	elif k <= 1.7e-13:
		tmp = t_2
	elif k <= 1.25e+89:
		tmp = t_1
	elif k <= 2.3e+220:
		tmp = k * (((z * ((b * y0) - (i * y1))) - (y0 * (y2 * y5))) + (i * (y * y5)))
	elif k <= 4.6e+244:
		tmp = t_1
	else:
		tmp = b * ((((t * j) - (y * k)) * y4) + (y0 * ((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(y5 * Float64(y2 * Float64(Float64(t * a) - Float64(k * y0))))
	t_2 = Float64(c * Float64(Float64(z * Float64(Float64(t * i) - Float64(y0 * y3))) + Float64(x * Float64(Float64(y0 * y2) - Float64(y * i)))))
	tmp = 0.0
	if (k <= -2.4e+102)
		tmp = Float64(i * Float64(y * Float64(Float64(k * y5) - Float64(x * c))));
	elseif (k <= -2.4e-14)
		tmp = Float64(y4 * Float64(y1 * Float64(Float64(k * y2) - Float64(j * y3))));
	elseif (k <= -1e-152)
		tmp = t_2;
	elseif (k <= -1.5e-182)
		tmp = Float64(t * Float64(y4 * Float64(Float64(b * j) - Float64(c * y2))));
	elseif (k <= 1.7e-13)
		tmp = t_2;
	elseif (k <= 1.25e+89)
		tmp = t_1;
	elseif (k <= 2.3e+220)
		tmp = Float64(k * Float64(Float64(Float64(z * Float64(Float64(b * y0) - Float64(i * y1))) - Float64(y0 * Float64(y2 * y5))) + Float64(i * Float64(y * y5))));
	elseif (k <= 4.6e+244)
		tmp = t_1;
	else
		tmp = Float64(b * Float64(Float64(Float64(Float64(t * j) - Float64(y * k)) * y4) + Float64(y0 * 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 = y5 * (y2 * ((t * a) - (k * y0)));
	t_2 = c * ((z * ((t * i) - (y0 * y3))) + (x * ((y0 * y2) - (y * i))));
	tmp = 0.0;
	if (k <= -2.4e+102)
		tmp = i * (y * ((k * y5) - (x * c)));
	elseif (k <= -2.4e-14)
		tmp = y4 * (y1 * ((k * y2) - (j * y3)));
	elseif (k <= -1e-152)
		tmp = t_2;
	elseif (k <= -1.5e-182)
		tmp = t * (y4 * ((b * j) - (c * y2)));
	elseif (k <= 1.7e-13)
		tmp = t_2;
	elseif (k <= 1.25e+89)
		tmp = t_1;
	elseif (k <= 2.3e+220)
		tmp = k * (((z * ((b * y0) - (i * y1))) - (y0 * (y2 * y5))) + (i * (y * y5)));
	elseif (k <= 4.6e+244)
		tmp = t_1;
	else
		tmp = b * ((((t * j) - (y * k)) * y4) + (y0 * ((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[(y5 * N[(y2 * N[(N[(t * a), $MachinePrecision] - N[(k * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(c * N[(N[(z * N[(N[(t * i), $MachinePrecision] - N[(y0 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(x * N[(N[(y0 * y2), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[k, -2.4e+102], N[(i * N[(y * N[(N[(k * y5), $MachinePrecision] - N[(x * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, -2.4e-14], N[(y4 * N[(y1 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, -1e-152], t$95$2, If[LessEqual[k, -1.5e-182], N[(t * N[(y4 * N[(N[(b * j), $MachinePrecision] - N[(c * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 1.7e-13], t$95$2, If[LessEqual[k, 1.25e+89], t$95$1, If[LessEqual[k, 2.3e+220], N[(k * N[(N[(N[(z * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y0 * N[(y2 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(i * N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 4.6e+244], t$95$1, N[(b * N[(N[(N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision] * y4), $MachinePrecision] + N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if k < -2.39999999999999994e102

   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. Add Preprocessing

   3. Taylor expanded in y around inf 34.1%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in i around inf 57.3%

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

   if -2.39999999999999994e102 < k < -2.4e-14

   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. Add Preprocessing

   3. Taylor expanded in y4 around inf 41.6%

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

   4. Taylor expanded in y1 around inf 52.8%

      \[\leadsto y4 \cdot \color{blue}{\left(y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 52.8%

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

      2. *-commutative 52.8%

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

   6. Simplified 52.8%

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

   if -2.4e-14 < k < -1.00000000000000007e-152 or -1.5000000000000001e-182 < k < 1.70000000000000008e-13

   1. Initial program 41.8%

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

   3. Taylor expanded in c around inf 53.1%

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

   4. Taylor expanded in x around -inf 54.7%

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

   6. Simplified 57.5%

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

   7. Taylor expanded in y4 around 0 56.6%

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

   if -1.00000000000000007e-152 < k < -1.5000000000000001e-182

   1. Initial program 33.3%

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

   3. Taylor expanded in y4 around inf 56.3%

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

   4. Taylor expanded in t around inf 57.3%

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

   if 1.70000000000000008e-13 < k < 1.24999999999999996e89 or 2.29999999999999997e220 < k < 4.5999999999999999e244

   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. Add Preprocessing

   3. Taylor expanded in y5 around -inf 54.9%

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

   4. Taylor expanded in y2 around inf 61.3%

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

      1. *-commutative 61.3%

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

      2. *-commutative 61.3%

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

   6. Simplified 61.3%

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

   if 1.24999999999999996e89 < k < 2.29999999999999997e220

   1. Initial program 19.6%

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

   3. Taylor expanded in k around -inf 57.6%

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

      1. mul-1-neg 57.6%

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

      2. distribute-rgt-neg-in 57.6%

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

      3. +-commutative 57.6%

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

      4. mul-1-neg 57.6%

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

      5. unsub-neg 57.6%

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

      6. *-commutative 57.6%

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

   5. Simplified 57.6%

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

   6. Taylor expanded in y4 around 0 63.0%

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

   if 4.5999999999999999e244 < k

   1. Initial program 36.2%

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

   3. Taylor expanded in b around inf 50.5%

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

   4. Taylor expanded in a around 0 65.0%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 65.0%

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

      2. *-commutative 65.0%

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

      3. *-commutative 65.0%

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

      4. *-commutative 65.0%

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

   6. Simplified 65.0%

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

4. Final simplification 58.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;k \leq -2.4 \cdot 10^{+102}:\\ \;\;\;\;i \cdot \left(y \cdot \left(k \cdot y5 - x \cdot c\right)\right)\\ \mathbf{elif}\;k \leq -2.4 \cdot 10^{-14}:\\ \;\;\;\;y4 \cdot \left(y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;k \leq -1 \cdot 10^{-152}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right) + x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{elif}\;k \leq -1.5 \cdot 10^{-182}:\\ \;\;\;\;t \cdot \left(y4 \cdot \left(b \cdot j - c \cdot y2\right)\right)\\ \mathbf{elif}\;k \leq 1.7 \cdot 10^{-13}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right) + x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{elif}\;k \leq 1.25 \cdot 10^{+89}:\\ \;\;\;\;y5 \cdot \left(y2 \cdot \left(t \cdot a - k \cdot y0\right)\right)\\ \mathbf{elif}\;k \leq 2.3 \cdot 10^{+220}:\\ \;\;\;\;k \cdot \left(\left(z \cdot \left(b \cdot y0 - i \cdot y1\right) - y0 \cdot \left(y2 \cdot y5\right)\right) + i \cdot \left(y \cdot y5\right)\right)\\ \mathbf{elif}\;k \leq 4.6 \cdot 10^{+244}:\\ \;\;\;\;y5 \cdot \left(y2 \cdot \left(t \cdot a - k \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(\left(t \cdot j - y \cdot k\right) \cdot y4 + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 9: 35.8% accurate, 1.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot y0 - i \cdot y1\\ t_2 := z \cdot \left(t \cdot i - y0 \cdot y3\right)\\ t_3 := y5 \cdot \left(y2 \cdot \left(t \cdot a - k \cdot y0\right)\right)\\ \mathbf{if}\;k \leq -1.15 \cdot 10^{+99}:\\ \;\;\;\;i \cdot \left(y \cdot \left(k \cdot y5 - x \cdot c\right)\right)\\ \mathbf{elif}\;k \leq -1.06 \cdot 10^{-14}:\\ \;\;\;\;y4 \cdot \left(y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;k \leq 5.6 \cdot 10^{-302}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right) - \left(x \cdot \left(y \cdot i - y0 \cdot y2\right) - t\_2\right)\right)\\ \mathbf{elif}\;k \leq 6.8 \cdot 10^{-251}:\\ \;\;\;\;j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) - x \cdot t\_1\right)\\ \mathbf{elif}\;k \leq 3.4 \cdot 10^{-13}:\\ \;\;\;\;c \cdot \left(t\_2 + x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{elif}\;k \leq 1.05 \cdot 10^{+91}:\\ \;\;\;\;t\_3\\ \mathbf{elif}\;k \leq 4.2 \cdot 10^{+220}:\\ \;\;\;\;k \cdot \left(\left(z \cdot t\_1 - y0 \cdot \left(y2 \cdot y5\right)\right) + i \cdot \left(y \cdot y5\right)\right)\\ \mathbf{elif}\;k \leq 10^{+261}:\\ \;\;\;\;t\_3\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(\left(t \cdot j - y \cdot k\right) \cdot y4 + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* b y0) (* i y1)))
        (t_2 (* z (- (* t i) (* y0 y3))))
        (t_3 (* y5 (* y2 (- (* t a) (* k y0))))))
   (if (<= k -1.15e+99)
     (* i (* y (- (* k y5) (* x c))))
     (if (<= k -1.06e-14)
       (* y4 (* y1 (- (* k y2) (* j y3))))
       (if (<= k 5.6e-302)
         (*
          c
          (- (* y4 (- (* y y3) (* t y2))) (- (* x (- (* y i) (* y0 y2))) t_2)))
         (if (<= k 6.8e-251)
           (*
            j
            (-
             (+ (* t (- (* b y4) (* i y5))) (* y3 (- (* y0 y5) (* y1 y4))))
             (* x t_1)))
           (if (<= k 3.4e-13)
             (* c (+ t_2 (* x (- (* y0 y2) (* y i)))))
             (if (<= k 1.05e+91)
               t_3
               (if (<= k 4.2e+220)
                 (* k (+ (- (* z t_1) (* y0 (* y2 y5))) (* i (* y y5))))
                 (if (<= k 1e+261)
                   t_3
                   (*
                    b
                    (+
                     (* (- (* t j) (* y k)) y4)
                     (* y0 (- (* 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 = (b * y0) - (i * y1);
	double t_2 = z * ((t * i) - (y0 * y3));
	double t_3 = y5 * (y2 * ((t * a) - (k * y0)));
	double tmp;
	if (k <= -1.15e+99) {
		tmp = i * (y * ((k * y5) - (x * c)));
	} else if (k <= -1.06e-14) {
		tmp = y4 * (y1 * ((k * y2) - (j * y3)));
	} else if (k <= 5.6e-302) {
		tmp = c * ((y4 * ((y * y3) - (t * y2))) - ((x * ((y * i) - (y0 * y2))) - t_2));
	} else if (k <= 6.8e-251) {
		tmp = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) - (x * t_1));
	} else if (k <= 3.4e-13) {
		tmp = c * (t_2 + (x * ((y0 * y2) - (y * i))));
	} else if (k <= 1.05e+91) {
		tmp = t_3;
	} else if (k <= 4.2e+220) {
		tmp = k * (((z * t_1) - (y0 * (y2 * y5))) + (i * (y * y5)));
	} else if (k <= 1e+261) {
		tmp = t_3;
	} else {
		tmp = b * ((((t * j) - (y * k)) * y4) + (y0 * ((z * k) - (x * j))));
	}
	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 * y0) - (i * y1)
    t_2 = z * ((t * i) - (y0 * y3))
    t_3 = y5 * (y2 * ((t * a) - (k * y0)))
    if (k <= (-1.15d+99)) then
        tmp = i * (y * ((k * y5) - (x * c)))
    else if (k <= (-1.06d-14)) then
        tmp = y4 * (y1 * ((k * y2) - (j * y3)))
    else if (k <= 5.6d-302) then
        tmp = c * ((y4 * ((y * y3) - (t * y2))) - ((x * ((y * i) - (y0 * y2))) - t_2))
    else if (k <= 6.8d-251) then
        tmp = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) - (x * t_1))
    else if (k <= 3.4d-13) then
        tmp = c * (t_2 + (x * ((y0 * y2) - (y * i))))
    else if (k <= 1.05d+91) then
        tmp = t_3
    else if (k <= 4.2d+220) then
        tmp = k * (((z * t_1) - (y0 * (y2 * y5))) + (i * (y * y5)))
    else if (k <= 1d+261) then
        tmp = t_3
    else
        tmp = b * ((((t * j) - (y * k)) * y4) + (y0 * ((z * k) - (x * j))))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (b * y0) - (i * y1);
	double t_2 = z * ((t * i) - (y0 * y3));
	double t_3 = y5 * (y2 * ((t * a) - (k * y0)));
	double tmp;
	if (k <= -1.15e+99) {
		tmp = i * (y * ((k * y5) - (x * c)));
	} else if (k <= -1.06e-14) {
		tmp = y4 * (y1 * ((k * y2) - (j * y3)));
	} else if (k <= 5.6e-302) {
		tmp = c * ((y4 * ((y * y3) - (t * y2))) - ((x * ((y * i) - (y0 * y2))) - t_2));
	} else if (k <= 6.8e-251) {
		tmp = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) - (x * t_1));
	} else if (k <= 3.4e-13) {
		tmp = c * (t_2 + (x * ((y0 * y2) - (y * i))));
	} else if (k <= 1.05e+91) {
		tmp = t_3;
	} else if (k <= 4.2e+220) {
		tmp = k * (((z * t_1) - (y0 * (y2 * y5))) + (i * (y * y5)));
	} else if (k <= 1e+261) {
		tmp = t_3;
	} else {
		tmp = b * ((((t * j) - (y * k)) * y4) + (y0 * ((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 = (b * y0) - (i * y1)
	t_2 = z * ((t * i) - (y0 * y3))
	t_3 = y5 * (y2 * ((t * a) - (k * y0)))
	tmp = 0
	if k <= -1.15e+99:
		tmp = i * (y * ((k * y5) - (x * c)))
	elif k <= -1.06e-14:
		tmp = y4 * (y1 * ((k * y2) - (j * y3)))
	elif k <= 5.6e-302:
		tmp = c * ((y4 * ((y * y3) - (t * y2))) - ((x * ((y * i) - (y0 * y2))) - t_2))
	elif k <= 6.8e-251:
		tmp = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) - (x * t_1))
	elif k <= 3.4e-13:
		tmp = c * (t_2 + (x * ((y0 * y2) - (y * i))))
	elif k <= 1.05e+91:
		tmp = t_3
	elif k <= 4.2e+220:
		tmp = k * (((z * t_1) - (y0 * (y2 * y5))) + (i * (y * y5)))
	elif k <= 1e+261:
		tmp = t_3
	else:
		tmp = b * ((((t * j) - (y * k)) * y4) + (y0 * ((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(b * y0) - Float64(i * y1))
	t_2 = Float64(z * Float64(Float64(t * i) - Float64(y0 * y3)))
	t_3 = Float64(y5 * Float64(y2 * Float64(Float64(t * a) - Float64(k * y0))))
	tmp = 0.0
	if (k <= -1.15e+99)
		tmp = Float64(i * Float64(y * Float64(Float64(k * y5) - Float64(x * c))));
	elseif (k <= -1.06e-14)
		tmp = Float64(y4 * Float64(y1 * Float64(Float64(k * y2) - Float64(j * y3))));
	elseif (k <= 5.6e-302)
		tmp = Float64(c * Float64(Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2))) - Float64(Float64(x * Float64(Float64(y * i) - Float64(y0 * y2))) - t_2)));
	elseif (k <= 6.8e-251)
		tmp = Float64(j * Float64(Float64(Float64(t * Float64(Float64(b * y4) - Float64(i * y5))) + Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4)))) - Float64(x * t_1)));
	elseif (k <= 3.4e-13)
		tmp = Float64(c * Float64(t_2 + Float64(x * Float64(Float64(y0 * y2) - Float64(y * i)))));
	elseif (k <= 1.05e+91)
		tmp = t_3;
	elseif (k <= 4.2e+220)
		tmp = Float64(k * Float64(Float64(Float64(z * t_1) - Float64(y0 * Float64(y2 * y5))) + Float64(i * Float64(y * y5))));
	elseif (k <= 1e+261)
		tmp = t_3;
	else
		tmp = Float64(b * Float64(Float64(Float64(Float64(t * j) - Float64(y * k)) * y4) + Float64(y0 * 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 = (b * y0) - (i * y1);
	t_2 = z * ((t * i) - (y0 * y3));
	t_3 = y5 * (y2 * ((t * a) - (k * y0)));
	tmp = 0.0;
	if (k <= -1.15e+99)
		tmp = i * (y * ((k * y5) - (x * c)));
	elseif (k <= -1.06e-14)
		tmp = y4 * (y1 * ((k * y2) - (j * y3)));
	elseif (k <= 5.6e-302)
		tmp = c * ((y4 * ((y * y3) - (t * y2))) - ((x * ((y * i) - (y0 * y2))) - t_2));
	elseif (k <= 6.8e-251)
		tmp = j * (((t * ((b * y4) - (i * y5))) + (y3 * ((y0 * y5) - (y1 * y4)))) - (x * t_1));
	elseif (k <= 3.4e-13)
		tmp = c * (t_2 + (x * ((y0 * y2) - (y * i))));
	elseif (k <= 1.05e+91)
		tmp = t_3;
	elseif (k <= 4.2e+220)
		tmp = k * (((z * t_1) - (y0 * (y2 * y5))) + (i * (y * y5)));
	elseif (k <= 1e+261)
		tmp = t_3;
	else
		tmp = b * ((((t * j) - (y * k)) * y4) + (y0 * ((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[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(z * N[(N[(t * i), $MachinePrecision] - N[(y0 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(y5 * N[(y2 * N[(N[(t * a), $MachinePrecision] - N[(k * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[k, -1.15e+99], N[(i * N[(y * N[(N[(k * y5), $MachinePrecision] - N[(x * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, -1.06e-14], N[(y4 * N[(y1 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 5.6e-302], N[(c * N[(N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(x * N[(N[(y * i), $MachinePrecision] - N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 6.8e-251], N[(j * N[(N[(N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(x * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 3.4e-13], N[(c * N[(t$95$2 + N[(x * N[(N[(y0 * y2), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 1.05e+91], t$95$3, If[LessEqual[k, 4.2e+220], N[(k * N[(N[(N[(z * t$95$1), $MachinePrecision] - N[(y0 * N[(y2 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(i * N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 1e+261], t$95$3, N[(b * N[(N[(N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision] * y4), $MachinePrecision] + N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]

Derivation

1. Split input into 8 regimes

2. if k < -1.1500000000000001e99

   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. Add Preprocessing

   3. Taylor expanded in y around inf 34.1%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in i around inf 57.3%

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

   if -1.1500000000000001e99 < k < -1.06e-14

   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. Add Preprocessing

   3. Taylor expanded in y4 around inf 41.6%

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

   4. Taylor expanded in y1 around inf 52.8%

      \[\leadsto y4 \cdot \color{blue}{\left(y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 52.8%

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

      2. *-commutative 52.8%

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

   6. Simplified 52.8%

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

   if -1.06e-14 < k < 5.6e-302

   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. Add Preprocessing

   3. Taylor expanded in c around inf 58.8%

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

   4. Taylor expanded in x around -inf 58.6%

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

   6. Simplified 61.7%

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

   if 5.6e-302 < k < 6.80000000000000034e-251

   1. Initial program 69.8%

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

   3. Taylor expanded in j around inf 71.0%

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

      1. +-commutative 71.0%

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

      2. mul-1-neg 71.0%

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

      3. unsub-neg 71.0%

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

      4. *-commutative 71.0%

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

   5. Simplified 71.0%

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

   if 6.80000000000000034e-251 < k < 3.40000000000000015e-13

   1. Initial program 47.4%

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

   3. Taylor expanded in c around inf 50.7%

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

   4. Taylor expanded in x around -inf 53.3%

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

   6. Simplified 55.7%

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

   7. Taylor expanded in y4 around 0 58.5%

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

   if 3.40000000000000015e-13 < k < 1.05000000000000004e91 or 4.20000000000000014e220 < k < 9.9999999999999993e260

   1. Initial program 28.8%

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

   3. Taylor expanded in y5 around -inf 52.1%

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

   4. Taylor expanded in y2 around inf 57.8%

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

      1. *-commutative 57.8%

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

      2. *-commutative 57.8%

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

   6. Simplified 57.8%

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

   if 1.05000000000000004e91 < k < 4.20000000000000014e220

   1. Initial program 19.6%

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

   3. Taylor expanded in k around -inf 57.6%

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

      1. mul-1-neg 57.6%

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

      2. distribute-rgt-neg-in 57.6%

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

      3. +-commutative 57.6%

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

      4. mul-1-neg 57.6%

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

      5. unsub-neg 57.6%

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

      6. *-commutative 57.6%

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

   5. Simplified 57.6%

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

   6. Taylor expanded in y4 around 0 63.0%

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

   if 9.9999999999999993e260 < k

   1. Initial program 30.0%

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

   3. Taylor expanded in b around inf 60.1%

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

   4. Taylor expanded in a around 0 80.1%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 80.1%

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

      2. *-commutative 80.1%

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

      3. *-commutative 80.1%

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

      4. *-commutative 80.1%

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

   6. Simplified 80.1%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - z \cdot k\right)\right)} \]
3. Recombined 8 regimes into one program.

4. Final simplification 60.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;k \leq -1.15 \cdot 10^{+99}:\\ \;\;\;\;i \cdot \left(y \cdot \left(k \cdot y5 - x \cdot c\right)\right)\\ \mathbf{elif}\;k \leq -1.06 \cdot 10^{-14}:\\ \;\;\;\;y4 \cdot \left(y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;k \leq 5.6 \cdot 10^{-302}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right) - \left(x \cdot \left(y \cdot i - y0 \cdot y2\right) - z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)\right)\\ \mathbf{elif}\;k \leq 6.8 \cdot 10^{-251}:\\ \;\;\;\;j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;k \leq 3.4 \cdot 10^{-13}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right) + x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{elif}\;k \leq 1.05 \cdot 10^{+91}:\\ \;\;\;\;y5 \cdot \left(y2 \cdot \left(t \cdot a - k \cdot y0\right)\right)\\ \mathbf{elif}\;k \leq 4.2 \cdot 10^{+220}:\\ \;\;\;\;k \cdot \left(\left(z \cdot \left(b \cdot y0 - i \cdot y1\right) - y0 \cdot \left(y2 \cdot y5\right)\right) + i \cdot \left(y \cdot y5\right)\right)\\ \mathbf{elif}\;k \leq 10^{+261}:\\ \;\;\;\;y5 \cdot \left(y2 \cdot \left(t \cdot a - k \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(\left(t \cdot j - y \cdot k\right) \cdot y4 + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 10: 36.4% accurate, 1.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y4 \cdot \left(y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{if}\;k \leq -4.2 \cdot 10^{+101}:\\ \;\;\;\;i \cdot \left(y \cdot \left(k \cdot y5 - x \cdot c\right)\right)\\ \mathbf{elif}\;k \leq -4.2 \cdot 10^{-14}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;k \leq 3.8 \cdot 10^{+25}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right) - \left(x \cdot \left(y \cdot i - y0 \cdot y2\right) - z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)\right)\\ \mathbf{elif}\;k \leq 5 \cdot 10^{+146}:\\ \;\;\;\;\left(i \cdot y5\right) \cdot \left(y \cdot k - t \cdot j\right)\\ \mathbf{elif}\;k \leq 3.5 \cdot 10^{+171}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;k \leq 1.12 \cdot 10^{+229}:\\ \;\;\;\;k \cdot \left(\left(z \cdot \left(b \cdot y0 - i \cdot y1\right) - y0 \cdot \left(y2 \cdot y5\right)\right) + i \cdot \left(y \cdot y5\right)\right)\\ \mathbf{elif}\;k \leq 9.5 \cdot 10^{+245}:\\ \;\;\;\;y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(\left(t \cdot j - y \cdot k\right) \cdot y4 + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* y4 (* y1 (- (* k y2) (* j y3))))))
   (if (<= k -4.2e+101)
     (* i (* y (- (* k y5) (* x c))))
     (if (<= k -4.2e-14)
       t_1
       (if (<= k 3.8e+25)
         (*
          c
          (-
           (* y4 (- (* y y3) (* t y2)))
           (- (* x (- (* y i) (* y0 y2))) (* z (- (* t i) (* y0 y3))))))
         (if (<= k 5e+146)
           (* (* i y5) (- (* y k) (* t j)))
           (if (<= k 3.5e+171)
             t_1
             (if (<= k 1.12e+229)
               (*
                k
                (+
                 (- (* z (- (* b y0) (* i y1))) (* y0 (* y2 y5)))
                 (* i (* y y5))))
               (if (<= k 9.5e+245)
                 (* y (* y5 (- (* i k) (* a y3))))
                 (*
                  b
                  (+
                   (* (- (* t j) (* y k)) y4)
                   (* y0 (- (* 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 = y4 * (y1 * ((k * y2) - (j * y3)));
	double tmp;
	if (k <= -4.2e+101) {
		tmp = i * (y * ((k * y5) - (x * c)));
	} else if (k <= -4.2e-14) {
		tmp = t_1;
	} else if (k <= 3.8e+25) {
		tmp = c * ((y4 * ((y * y3) - (t * y2))) - ((x * ((y * i) - (y0 * y2))) - (z * ((t * i) - (y0 * y3)))));
	} else if (k <= 5e+146) {
		tmp = (i * y5) * ((y * k) - (t * j));
	} else if (k <= 3.5e+171) {
		tmp = t_1;
	} else if (k <= 1.12e+229) {
		tmp = k * (((z * ((b * y0) - (i * y1))) - (y0 * (y2 * y5))) + (i * (y * y5)));
	} else if (k <= 9.5e+245) {
		tmp = y * (y5 * ((i * k) - (a * y3)));
	} else {
		tmp = b * ((((t * j) - (y * k)) * y4) + (y0 * ((z * k) - (x * j))));
	}
	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 = y4 * (y1 * ((k * y2) - (j * y3)))
    if (k <= (-4.2d+101)) then
        tmp = i * (y * ((k * y5) - (x * c)))
    else if (k <= (-4.2d-14)) then
        tmp = t_1
    else if (k <= 3.8d+25) then
        tmp = c * ((y4 * ((y * y3) - (t * y2))) - ((x * ((y * i) - (y0 * y2))) - (z * ((t * i) - (y0 * y3)))))
    else if (k <= 5d+146) then
        tmp = (i * y5) * ((y * k) - (t * j))
    else if (k <= 3.5d+171) then
        tmp = t_1
    else if (k <= 1.12d+229) then
        tmp = k * (((z * ((b * y0) - (i * y1))) - (y0 * (y2 * y5))) + (i * (y * y5)))
    else if (k <= 9.5d+245) then
        tmp = y * (y5 * ((i * k) - (a * y3)))
    else
        tmp = b * ((((t * j) - (y * k)) * y4) + (y0 * ((z * k) - (x * j))))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = y4 * (y1 * ((k * y2) - (j * y3)));
	double tmp;
	if (k <= -4.2e+101) {
		tmp = i * (y * ((k * y5) - (x * c)));
	} else if (k <= -4.2e-14) {
		tmp = t_1;
	} else if (k <= 3.8e+25) {
		tmp = c * ((y4 * ((y * y3) - (t * y2))) - ((x * ((y * i) - (y0 * y2))) - (z * ((t * i) - (y0 * y3)))));
	} else if (k <= 5e+146) {
		tmp = (i * y5) * ((y * k) - (t * j));
	} else if (k <= 3.5e+171) {
		tmp = t_1;
	} else if (k <= 1.12e+229) {
		tmp = k * (((z * ((b * y0) - (i * y1))) - (y0 * (y2 * y5))) + (i * (y * y5)));
	} else if (k <= 9.5e+245) {
		tmp = y * (y5 * ((i * k) - (a * y3)));
	} else {
		tmp = b * ((((t * j) - (y * k)) * y4) + (y0 * ((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 = y4 * (y1 * ((k * y2) - (j * y3)))
	tmp = 0
	if k <= -4.2e+101:
		tmp = i * (y * ((k * y5) - (x * c)))
	elif k <= -4.2e-14:
		tmp = t_1
	elif k <= 3.8e+25:
		tmp = c * ((y4 * ((y * y3) - (t * y2))) - ((x * ((y * i) - (y0 * y2))) - (z * ((t * i) - (y0 * y3)))))
	elif k <= 5e+146:
		tmp = (i * y5) * ((y * k) - (t * j))
	elif k <= 3.5e+171:
		tmp = t_1
	elif k <= 1.12e+229:
		tmp = k * (((z * ((b * y0) - (i * y1))) - (y0 * (y2 * y5))) + (i * (y * y5)))
	elif k <= 9.5e+245:
		tmp = y * (y5 * ((i * k) - (a * y3)))
	else:
		tmp = b * ((((t * j) - (y * k)) * y4) + (y0 * ((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(y4 * Float64(y1 * Float64(Float64(k * y2) - Float64(j * y3))))
	tmp = 0.0
	if (k <= -4.2e+101)
		tmp = Float64(i * Float64(y * Float64(Float64(k * y5) - Float64(x * c))));
	elseif (k <= -4.2e-14)
		tmp = t_1;
	elseif (k <= 3.8e+25)
		tmp = Float64(c * Float64(Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2))) - Float64(Float64(x * Float64(Float64(y * i) - Float64(y0 * y2))) - Float64(z * Float64(Float64(t * i) - Float64(y0 * y3))))));
	elseif (k <= 5e+146)
		tmp = Float64(Float64(i * y5) * Float64(Float64(y * k) - Float64(t * j)));
	elseif (k <= 3.5e+171)
		tmp = t_1;
	elseif (k <= 1.12e+229)
		tmp = Float64(k * Float64(Float64(Float64(z * Float64(Float64(b * y0) - Float64(i * y1))) - Float64(y0 * Float64(y2 * y5))) + Float64(i * Float64(y * y5))));
	elseif (k <= 9.5e+245)
		tmp = Float64(y * Float64(y5 * Float64(Float64(i * k) - Float64(a * y3))));
	else
		tmp = Float64(b * Float64(Float64(Float64(Float64(t * j) - Float64(y * k)) * y4) + Float64(y0 * 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 = y4 * (y1 * ((k * y2) - (j * y3)));
	tmp = 0.0;
	if (k <= -4.2e+101)
		tmp = i * (y * ((k * y5) - (x * c)));
	elseif (k <= -4.2e-14)
		tmp = t_1;
	elseif (k <= 3.8e+25)
		tmp = c * ((y4 * ((y * y3) - (t * y2))) - ((x * ((y * i) - (y0 * y2))) - (z * ((t * i) - (y0 * y3)))));
	elseif (k <= 5e+146)
		tmp = (i * y5) * ((y * k) - (t * j));
	elseif (k <= 3.5e+171)
		tmp = t_1;
	elseif (k <= 1.12e+229)
		tmp = k * (((z * ((b * y0) - (i * y1))) - (y0 * (y2 * y5))) + (i * (y * y5)));
	elseif (k <= 9.5e+245)
		tmp = y * (y5 * ((i * k) - (a * y3)));
	else
		tmp = b * ((((t * j) - (y * k)) * y4) + (y0 * ((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[(y4 * N[(y1 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[k, -4.2e+101], N[(i * N[(y * N[(N[(k * y5), $MachinePrecision] - N[(x * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, -4.2e-14], t$95$1, If[LessEqual[k, 3.8e+25], N[(c * N[(N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(x * N[(N[(y * i), $MachinePrecision] - N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(z * N[(N[(t * i), $MachinePrecision] - N[(y0 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 5e+146], N[(N[(i * y5), $MachinePrecision] * N[(N[(y * k), $MachinePrecision] - N[(t * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 3.5e+171], t$95$1, If[LessEqual[k, 1.12e+229], N[(k * N[(N[(N[(z * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y0 * N[(y2 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(i * N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 9.5e+245], N[(y * N[(y5 * N[(N[(i * k), $MachinePrecision] - N[(a * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(N[(N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision] * y4), $MachinePrecision] + N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if k < -4.2e101

   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. Add Preprocessing

   3. Taylor expanded in y around inf 34.1%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in i around inf 57.3%

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

   if -4.2e101 < k < -4.1999999999999998e-14 or 4.9999999999999999e146 < k < 3.4999999999999999e171

   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. Add Preprocessing

   3. Taylor expanded in y4 around inf 49.2%

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

   4. Taylor expanded in y1 around inf 58.4%

      \[\leadsto y4 \cdot \color{blue}{\left(y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 58.4%

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

      2. *-commutative 58.4%

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

   6. Simplified 58.4%

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

   if -4.1999999999999998e-14 < k < 3.8e25

   1. Initial program 41.0%

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

   3. Taylor expanded in c around inf 52.4%

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

   4. Taylor expanded in x around -inf 53.8%

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

   6. Simplified 57.6%

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

   if 3.8e25 < k < 4.9999999999999999e146

   1. Initial program 16.7%

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

   3. Taylor expanded in y5 around -inf 56.3%

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

   4. Taylor expanded in i around inf 52.6%

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

      1. associate-*r* 52.6%

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

      2. *-commutative 52.6%

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

      3. *-commutative 52.6%

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

   6. Simplified 52.6%

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

   if 3.4999999999999999e171 < k < 1.12e229

   1. Initial program 12.5%

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

   3. Taylor expanded in k around -inf 78.3%

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

      1. mul-1-neg 78.3%

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

      2. distribute-rgt-neg-in 78.3%

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

      3. +-commutative 78.3%

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

      4. mul-1-neg 78.3%

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

      5. unsub-neg 78.3%

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

      6. *-commutative 78.3%

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

   5. Simplified 78.3%

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

   6. Taylor expanded in y4 around 0 78.2%

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

   if 1.12e229 < k < 9.49999999999999939e245

   1. Initial program 14.3%

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

   3. Taylor expanded in y around inf 57.1%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y5 around inf 85.7%

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

   if 9.49999999999999939e245 < k

   1. Initial program 39.0%

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

   3. Taylor expanded in b around inf 54.4%

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

   4. Taylor expanded in a around 0 70.0%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 70.0%

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

      2. *-commutative 70.0%

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

      3. *-commutative 70.0%

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

      4. *-commutative 70.0%

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

   6. Simplified 70.0%

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

4. Final simplification 59.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;k \leq -4.2 \cdot 10^{+101}:\\ \;\;\;\;i \cdot \left(y \cdot \left(k \cdot y5 - x \cdot c\right)\right)\\ \mathbf{elif}\;k \leq -4.2 \cdot 10^{-14}:\\ \;\;\;\;y4 \cdot \left(y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;k \leq 3.8 \cdot 10^{+25}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right) - \left(x \cdot \left(y \cdot i - y0 \cdot y2\right) - z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)\right)\\ \mathbf{elif}\;k \leq 5 \cdot 10^{+146}:\\ \;\;\;\;\left(i \cdot y5\right) \cdot \left(y \cdot k - t \cdot j\right)\\ \mathbf{elif}\;k \leq 3.5 \cdot 10^{+171}:\\ \;\;\;\;y4 \cdot \left(y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;k \leq 1.12 \cdot 10^{+229}:\\ \;\;\;\;k \cdot \left(\left(z \cdot \left(b \cdot y0 - i \cdot y1\right) - y0 \cdot \left(y2 \cdot y5\right)\right) + i \cdot \left(y \cdot y5\right)\right)\\ \mathbf{elif}\;k \leq 9.5 \cdot 10^{+245}:\\ \;\;\;\;y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(\left(t \cdot j - y \cdot k\right) \cdot y4 + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 11: 30.3% accurate, 1.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;k \leq -1.35 \cdot 10^{+99}:\\ \;\;\;\;i \cdot \left(y \cdot \left(k \cdot y5 - x \cdot c\right)\right)\\ \mathbf{elif}\;k \leq -6.9 \cdot 10^{+25}:\\ \;\;\;\;y4 \cdot \left(y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;k \leq 7.8 \cdot 10^{-159}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)\\ \mathbf{elif}\;k \leq 2.1 \cdot 10^{-12}:\\ \;\;\;\;c \cdot \left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right)\right)\\ \mathbf{elif}\;k \leq 1.98 \cdot 10^{+90}:\\ \;\;\;\;y5 \cdot \left(y2 \cdot \left(t \cdot a - k \cdot y0\right)\right)\\ \mathbf{elif}\;k \leq 4.4 \cdot 10^{+146}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;k \leq 3.6 \cdot 10^{+196}:\\ \;\;\;\;y2 \cdot \left(y4 \cdot \left(k \cdot y1 - t \cdot c\right)\right)\\ \mathbf{elif}\;k \leq 8.5 \cdot 10^{+246}:\\ \;\;\;\;y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(k \cdot y1\right) \cdot \left(y2 \cdot y4 - z \cdot i\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= k -1.35e+99)
   (* i (* y (- (* k y5) (* x c))))
   (if (<= k -6.9e+25)
     (* y4 (* y1 (- (* k y2) (* j y3))))
     (if (<= k 7.8e-159)
       (* c (* z (- (* t i) (* y0 y3))))
       (if (<= k 2.1e-12)
         (* c (* y0 (- (* x y2) (* z y3))))
         (if (<= k 1.98e+90)
           (* y5 (* y2 (- (* t a) (* k y0))))
           (if (<= k 4.4e+146)
             (* i (* k (- (* y y5) (* z y1))))
             (if (<= k 3.6e+196)
               (* y2 (* y4 (- (* k y1) (* t c))))
               (if (<= k 8.5e+246)
                 (* y (* y5 (- (* i k) (* a y3))))
                 (* (* k y1) (- (* y2 y4) (* z i))))))))))))

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 (k <= -1.35e+99) {
		tmp = i * (y * ((k * y5) - (x * c)));
	} else if (k <= -6.9e+25) {
		tmp = y4 * (y1 * ((k * y2) - (j * y3)));
	} else if (k <= 7.8e-159) {
		tmp = c * (z * ((t * i) - (y0 * y3)));
	} else if (k <= 2.1e-12) {
		tmp = c * (y0 * ((x * y2) - (z * y3)));
	} else if (k <= 1.98e+90) {
		tmp = y5 * (y2 * ((t * a) - (k * y0)));
	} else if (k <= 4.4e+146) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (k <= 3.6e+196) {
		tmp = y2 * (y4 * ((k * y1) - (t * c)));
	} else if (k <= 8.5e+246) {
		tmp = y * (y5 * ((i * k) - (a * y3)));
	} else {
		tmp = (k * y1) * ((y2 * y4) - (z * i));
	}
	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 (k <= (-1.35d+99)) then
        tmp = i * (y * ((k * y5) - (x * c)))
    else if (k <= (-6.9d+25)) then
        tmp = y4 * (y1 * ((k * y2) - (j * y3)))
    else if (k <= 7.8d-159) then
        tmp = c * (z * ((t * i) - (y0 * y3)))
    else if (k <= 2.1d-12) then
        tmp = c * (y0 * ((x * y2) - (z * y3)))
    else if (k <= 1.98d+90) then
        tmp = y5 * (y2 * ((t * a) - (k * y0)))
    else if (k <= 4.4d+146) then
        tmp = i * (k * ((y * y5) - (z * y1)))
    else if (k <= 3.6d+196) then
        tmp = y2 * (y4 * ((k * y1) - (t * c)))
    else if (k <= 8.5d+246) then
        tmp = y * (y5 * ((i * k) - (a * y3)))
    else
        tmp = (k * y1) * ((y2 * y4) - (z * i))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (k <= -1.35e+99) {
		tmp = i * (y * ((k * y5) - (x * c)));
	} else if (k <= -6.9e+25) {
		tmp = y4 * (y1 * ((k * y2) - (j * y3)));
	} else if (k <= 7.8e-159) {
		tmp = c * (z * ((t * i) - (y0 * y3)));
	} else if (k <= 2.1e-12) {
		tmp = c * (y0 * ((x * y2) - (z * y3)));
	} else if (k <= 1.98e+90) {
		tmp = y5 * (y2 * ((t * a) - (k * y0)));
	} else if (k <= 4.4e+146) {
		tmp = i * (k * ((y * y5) - (z * y1)));
	} else if (k <= 3.6e+196) {
		tmp = y2 * (y4 * ((k * y1) - (t * c)));
	} else if (k <= 8.5e+246) {
		tmp = y * (y5 * ((i * k) - (a * y3)));
	} else {
		tmp = (k * y1) * ((y2 * y4) - (z * i));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if k <= -1.35e+99:
		tmp = i * (y * ((k * y5) - (x * c)))
	elif k <= -6.9e+25:
		tmp = y4 * (y1 * ((k * y2) - (j * y3)))
	elif k <= 7.8e-159:
		tmp = c * (z * ((t * i) - (y0 * y3)))
	elif k <= 2.1e-12:
		tmp = c * (y0 * ((x * y2) - (z * y3)))
	elif k <= 1.98e+90:
		tmp = y5 * (y2 * ((t * a) - (k * y0)))
	elif k <= 4.4e+146:
		tmp = i * (k * ((y * y5) - (z * y1)))
	elif k <= 3.6e+196:
		tmp = y2 * (y4 * ((k * y1) - (t * c)))
	elif k <= 8.5e+246:
		tmp = y * (y5 * ((i * k) - (a * y3)))
	else:
		tmp = (k * y1) * ((y2 * y4) - (z * i))
	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 (k <= -1.35e+99)
		tmp = Float64(i * Float64(y * Float64(Float64(k * y5) - Float64(x * c))));
	elseif (k <= -6.9e+25)
		tmp = Float64(y4 * Float64(y1 * Float64(Float64(k * y2) - Float64(j * y3))));
	elseif (k <= 7.8e-159)
		tmp = Float64(c * Float64(z * Float64(Float64(t * i) - Float64(y0 * y3))));
	elseif (k <= 2.1e-12)
		tmp = Float64(c * Float64(y0 * Float64(Float64(x * y2) - Float64(z * y3))));
	elseif (k <= 1.98e+90)
		tmp = Float64(y5 * Float64(y2 * Float64(Float64(t * a) - Float64(k * y0))));
	elseif (k <= 4.4e+146)
		tmp = Float64(i * Float64(k * Float64(Float64(y * y5) - Float64(z * y1))));
	elseif (k <= 3.6e+196)
		tmp = Float64(y2 * Float64(y4 * Float64(Float64(k * y1) - Float64(t * c))));
	elseif (k <= 8.5e+246)
		tmp = Float64(y * Float64(y5 * Float64(Float64(i * k) - Float64(a * y3))));
	else
		tmp = Float64(Float64(k * y1) * Float64(Float64(y2 * y4) - Float64(z * i)));
	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 (k <= -1.35e+99)
		tmp = i * (y * ((k * y5) - (x * c)));
	elseif (k <= -6.9e+25)
		tmp = y4 * (y1 * ((k * y2) - (j * y3)));
	elseif (k <= 7.8e-159)
		tmp = c * (z * ((t * i) - (y0 * y3)));
	elseif (k <= 2.1e-12)
		tmp = c * (y0 * ((x * y2) - (z * y3)));
	elseif (k <= 1.98e+90)
		tmp = y5 * (y2 * ((t * a) - (k * y0)));
	elseif (k <= 4.4e+146)
		tmp = i * (k * ((y * y5) - (z * y1)));
	elseif (k <= 3.6e+196)
		tmp = y2 * (y4 * ((k * y1) - (t * c)));
	elseif (k <= 8.5e+246)
		tmp = y * (y5 * ((i * k) - (a * y3)));
	else
		tmp = (k * y1) * ((y2 * y4) - (z * i));
	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[k, -1.35e+99], N[(i * N[(y * N[(N[(k * y5), $MachinePrecision] - N[(x * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, -6.9e+25], N[(y4 * N[(y1 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 7.8e-159], N[(c * N[(z * N[(N[(t * i), $MachinePrecision] - N[(y0 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 2.1e-12], N[(c * N[(y0 * N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 1.98e+90], N[(y5 * N[(y2 * N[(N[(t * a), $MachinePrecision] - N[(k * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 4.4e+146], N[(i * N[(k * N[(N[(y * y5), $MachinePrecision] - N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 3.6e+196], N[(y2 * N[(y4 * N[(N[(k * y1), $MachinePrecision] - N[(t * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 8.5e+246], N[(y * N[(y5 * N[(N[(i * k), $MachinePrecision] - N[(a * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(k * y1), $MachinePrecision] * N[(N[(y2 * y4), $MachinePrecision] - N[(z * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]

Derivation

1. Split input into 9 regimes

2. if k < -1.34999999999999994e99

   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. Add Preprocessing

   3. Taylor expanded in y around inf 34.1%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in i around inf 57.3%

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

   if -1.34999999999999994e99 < k < -6.8999999999999998e25

   1. Initial program 33.2%

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

   3. Taylor expanded in y4 around inf 40.7%

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

   4. Taylor expanded in y1 around inf 67.1%

      \[\leadsto y4 \cdot \color{blue}{\left(y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 67.1%

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

      2. *-commutative 67.1%

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

   6. Simplified 67.1%

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

   if -6.8999999999999998e25 < k < 7.79999999999999953e-159

   1. Initial program 36.8%

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

   3. Taylor expanded in c around inf 48.3%

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

   4. Taylor expanded in z around inf 40.1%

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

      1. +-commutative 40.1%

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

      2. mul-1-neg 40.1%

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

      3. unsub-neg 40.1%

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

      4. *-commutative 40.1%

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

   6. Simplified 40.1%

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

   if 7.79999999999999953e-159 < k < 2.09999999999999994e-12

   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. Add Preprocessing

   3. Taylor expanded in c around inf 54.7%

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

   4. Taylor expanded in y0 around inf 59.7%

      \[\leadsto \color{blue}{c \cdot \left(y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right)} \]

   if 2.09999999999999994e-12 < k < 1.98e90

   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. Add Preprocessing

   3. Taylor expanded in y5 around -inf 56.3%

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

   4. Taylor expanded in y2 around inf 57.3%

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

      1. *-commutative 57.3%

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

      2. *-commutative 57.3%

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

   6. Simplified 57.3%

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

   if 1.98e90 < k < 4.3999999999999996e146

   1. Initial program 12.5%

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

   3. Taylor expanded in k around -inf 50.0%

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

      1. mul-1-neg 50.0%

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

      2. distribute-rgt-neg-in 50.0%

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

      3. +-commutative 50.0%

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

      4. mul-1-neg 50.0%

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

      5. unsub-neg 50.0%

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

      6. *-commutative 50.0%

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

   5. Simplified 50.0%

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

   6. Taylor expanded in i around inf 75.2%

      \[\leadsto \color{blue}{i \cdot \left(k \cdot \left(-1 \cdot \left(y1 \cdot z\right) - -1 \cdot \left(y \cdot y5\right)\right)\right)} \]
   7. Step-by-step derivation

      1. distribute-lft-out-- 75.2%

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

      2. *-commutative 75.2%

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

   8. Simplified 75.2%

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

   if 4.3999999999999996e146 < k < 3.60000000000000007e196

   1. Initial program 34.0%

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

   3. Taylor expanded in y4 around inf 78.4%

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

   4. Taylor expanded in y2 around inf 67.3%

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

   if 3.60000000000000007e196 < k < 8.49999999999999952e246

   1. Initial program 15.9%

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

   3. Taylor expanded in y around inf 39.2%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y5 around inf 70.0%

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

   if 8.49999999999999952e246 < k

   1. Initial program 39.0%

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

   3. Taylor expanded in k around -inf 85.1%

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

      1. mul-1-neg 85.1%

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

      2. distribute-rgt-neg-in 85.1%

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

      3. +-commutative 85.1%

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

      4. mul-1-neg 85.1%

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

      5. unsub-neg 85.1%

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

      6. *-commutative 85.1%

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

   5. Simplified 85.1%

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

   6. Taylor expanded in y1 around inf 62.6%

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

      1. *-commutative 62.6%

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

      2. *-commutative 62.6%

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

      3. associate-*l* 69.9%

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

      4. +-commutative 69.9%

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

      5. mul-1-neg 69.9%

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

      6. unsub-neg 69.9%

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

      7. *-commutative 69.9%

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

   8. Simplified 69.9%

      \[\leadsto \color{blue}{\left(y2 \cdot y4 - z \cdot i\right) \cdot \left(y1 \cdot k\right)} \]
3. Recombined 9 regimes into one program.

4. Final simplification 52.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;k \leq -1.35 \cdot 10^{+99}:\\ \;\;\;\;i \cdot \left(y \cdot \left(k \cdot y5 - x \cdot c\right)\right)\\ \mathbf{elif}\;k \leq -6.9 \cdot 10^{+25}:\\ \;\;\;\;y4 \cdot \left(y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;k \leq 7.8 \cdot 10^{-159}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)\\ \mathbf{elif}\;k \leq 2.1 \cdot 10^{-12}:\\ \;\;\;\;c \cdot \left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right)\right)\\ \mathbf{elif}\;k \leq 1.98 \cdot 10^{+90}:\\ \;\;\;\;y5 \cdot \left(y2 \cdot \left(t \cdot a - k \cdot y0\right)\right)\\ \mathbf{elif}\;k \leq 4.4 \cdot 10^{+146}:\\ \;\;\;\;i \cdot \left(k \cdot \left(y \cdot y5 - z \cdot y1\right)\right)\\ \mathbf{elif}\;k \leq 3.6 \cdot 10^{+196}:\\ \;\;\;\;y2 \cdot \left(y4 \cdot \left(k \cdot y1 - t \cdot c\right)\right)\\ \mathbf{elif}\;k \leq 8.5 \cdot 10^{+246}:\\ \;\;\;\;y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(k \cdot y1\right) \cdot \left(y2 \cdot y4 - z \cdot i\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 12: 22.5% accurate, 2.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;t \leq -3.2 \cdot 10^{+83}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i\right)\right)\\ \mathbf{elif}\;t \leq -2.15 \cdot 10^{-270}:\\ \;\;\;\;c \cdot \left(y \cdot \left(x \cdot \left(-i\right)\right)\right)\\ \mathbf{elif}\;t \leq 1.05 \cdot 10^{-244}:\\ \;\;\;\;y \cdot \left(a \cdot \left(y3 \cdot \left(-y5\right)\right)\right)\\ \mathbf{elif}\;t \leq 4.3 \cdot 10^{-238}:\\ \;\;\;\;c \cdot \left(\left(y0 \cdot y3\right) \cdot \left(-z\right)\right)\\ \mathbf{elif}\;t \leq 2.5 \cdot 10^{-110}:\\ \;\;\;\;\left(i \cdot k\right) \cdot \left(y \cdot y5\right)\\ \mathbf{elif}\;t \leq 1.02 \cdot 10^{-109}:\\ \;\;\;\;a \cdot \left(\left(y3 \cdot y5\right) \cdot \left(-y\right)\right)\\ \mathbf{elif}\;t \leq 5.2 \cdot 10^{+23}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;t \leq 2.8 \cdot 10^{+211}:\\ \;\;\;\;b \cdot \left(\left(t \cdot j\right) \cdot y4\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(t \cdot \left(y2 \cdot \left(-y4\right)\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= t -3.2e+83)
   (* c (* z (* t i)))
   (if (<= t -2.15e-270)
     (* c (* y (* x (- i))))
     (if (<= t 1.05e-244)
       (* y (* a (* y3 (- y5))))
       (if (<= t 4.3e-238)
         (* c (* (* y0 y3) (- z)))
         (if (<= t 2.5e-110)
           (* (* i k) (* y y5))
           (if (<= t 1.02e-109)
             (* a (* (* y3 y5) (- y)))
             (if (<= t 5.2e+23)
               (* b (* y0 (- (* z k) (* x j))))
               (if (<= t 2.8e+211)
                 (* b (* (* t j) y4))
                 (* c (* t (* y2 (- 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 (t <= -3.2e+83) {
		tmp = c * (z * (t * i));
	} else if (t <= -2.15e-270) {
		tmp = c * (y * (x * -i));
	} else if (t <= 1.05e-244) {
		tmp = y * (a * (y3 * -y5));
	} else if (t <= 4.3e-238) {
		tmp = c * ((y0 * y3) * -z);
	} else if (t <= 2.5e-110) {
		tmp = (i * k) * (y * y5);
	} else if (t <= 1.02e-109) {
		tmp = a * ((y3 * y5) * -y);
	} else if (t <= 5.2e+23) {
		tmp = b * (y0 * ((z * k) - (x * j)));
	} else if (t <= 2.8e+211) {
		tmp = b * ((t * j) * y4);
	} else {
		tmp = c * (t * (y2 * -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 (t <= (-3.2d+83)) then
        tmp = c * (z * (t * i))
    else if (t <= (-2.15d-270)) then
        tmp = c * (y * (x * -i))
    else if (t <= 1.05d-244) then
        tmp = y * (a * (y3 * -y5))
    else if (t <= 4.3d-238) then
        tmp = c * ((y0 * y3) * -z)
    else if (t <= 2.5d-110) then
        tmp = (i * k) * (y * y5)
    else if (t <= 1.02d-109) then
        tmp = a * ((y3 * y5) * -y)
    else if (t <= 5.2d+23) then
        tmp = b * (y0 * ((z * k) - (x * j)))
    else if (t <= 2.8d+211) then
        tmp = b * ((t * j) * y4)
    else
        tmp = c * (t * (y2 * -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 (t <= -3.2e+83) {
		tmp = c * (z * (t * i));
	} else if (t <= -2.15e-270) {
		tmp = c * (y * (x * -i));
	} else if (t <= 1.05e-244) {
		tmp = y * (a * (y3 * -y5));
	} else if (t <= 4.3e-238) {
		tmp = c * ((y0 * y3) * -z);
	} else if (t <= 2.5e-110) {
		tmp = (i * k) * (y * y5);
	} else if (t <= 1.02e-109) {
		tmp = a * ((y3 * y5) * -y);
	} else if (t <= 5.2e+23) {
		tmp = b * (y0 * ((z * k) - (x * j)));
	} else if (t <= 2.8e+211) {
		tmp = b * ((t * j) * y4);
	} else {
		tmp = c * (t * (y2 * -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 t <= -3.2e+83:
		tmp = c * (z * (t * i))
	elif t <= -2.15e-270:
		tmp = c * (y * (x * -i))
	elif t <= 1.05e-244:
		tmp = y * (a * (y3 * -y5))
	elif t <= 4.3e-238:
		tmp = c * ((y0 * y3) * -z)
	elif t <= 2.5e-110:
		tmp = (i * k) * (y * y5)
	elif t <= 1.02e-109:
		tmp = a * ((y3 * y5) * -y)
	elif t <= 5.2e+23:
		tmp = b * (y0 * ((z * k) - (x * j)))
	elif t <= 2.8e+211:
		tmp = b * ((t * j) * y4)
	else:
		tmp = c * (t * (y2 * -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 (t <= -3.2e+83)
		tmp = Float64(c * Float64(z * Float64(t * i)));
	elseif (t <= -2.15e-270)
		tmp = Float64(c * Float64(y * Float64(x * Float64(-i))));
	elseif (t <= 1.05e-244)
		tmp = Float64(y * Float64(a * Float64(y3 * Float64(-y5))));
	elseif (t <= 4.3e-238)
		tmp = Float64(c * Float64(Float64(y0 * y3) * Float64(-z)));
	elseif (t <= 2.5e-110)
		tmp = Float64(Float64(i * k) * Float64(y * y5));
	elseif (t <= 1.02e-109)
		tmp = Float64(a * Float64(Float64(y3 * y5) * Float64(-y)));
	elseif (t <= 5.2e+23)
		tmp = Float64(b * Float64(y0 * Float64(Float64(z * k) - Float64(x * j))));
	elseif (t <= 2.8e+211)
		tmp = Float64(b * Float64(Float64(t * j) * y4));
	else
		tmp = Float64(c * Float64(t * Float64(y2 * 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 (t <= -3.2e+83)
		tmp = c * (z * (t * i));
	elseif (t <= -2.15e-270)
		tmp = c * (y * (x * -i));
	elseif (t <= 1.05e-244)
		tmp = y * (a * (y3 * -y5));
	elseif (t <= 4.3e-238)
		tmp = c * ((y0 * y3) * -z);
	elseif (t <= 2.5e-110)
		tmp = (i * k) * (y * y5);
	elseif (t <= 1.02e-109)
		tmp = a * ((y3 * y5) * -y);
	elseif (t <= 5.2e+23)
		tmp = b * (y0 * ((z * k) - (x * j)));
	elseif (t <= 2.8e+211)
		tmp = b * ((t * j) * y4);
	else
		tmp = c * (t * (y2 * -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[t, -3.2e+83], N[(c * N[(z * N[(t * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -2.15e-270], N[(c * N[(y * N[(x * (-i)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.05e-244], N[(y * N[(a * N[(y3 * (-y5)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 4.3e-238], N[(c * N[(N[(y0 * y3), $MachinePrecision] * (-z)), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 2.5e-110], N[(N[(i * k), $MachinePrecision] * N[(y * y5), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.02e-109], N[(a * N[(N[(y3 * y5), $MachinePrecision] * (-y)), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 5.2e+23], N[(b * N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 2.8e+211], N[(b * N[(N[(t * j), $MachinePrecision] * y4), $MachinePrecision]), $MachinePrecision], N[(c * N[(t * N[(y2 * (-y4)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]

Derivation

1. Split input into 9 regimes

2. if t < -3.1999999999999999e83

   1. Initial program 20.4%

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

   3. Taylor expanded in c around inf 39.0%

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

   4. Taylor expanded in z around inf 49.4%

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

      1. +-commutative 49.4%

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

      2. mul-1-neg 49.4%

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

      3. unsub-neg 49.4%

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

      4. *-commutative 49.4%

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

   6. Simplified 49.4%

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

   7. Taylor expanded in t around inf 45.5%

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

   if -3.1999999999999999e83 < t < -2.1500000000000001e-270

   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. Add Preprocessing

   3. Taylor expanded in y around inf 32.6%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in x around inf 33.5%

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

      1. associate-*r* 26.4%

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

      2. *-commutative 26.4%

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

   6. Simplified 26.4%

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

   7. Taylor expanded in b around 0 26.4%

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

      1. mul-1-neg 26.4%

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

      2. distribute-rgt-neg-in 26.4%

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

      3. associate-*r* 27.8%

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

      4. distribute-lft-neg-out 27.8%

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

      5. *-commutative 27.8%

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

      6. distribute-rgt-neg-in 27.8%

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

   9. Simplified 27.8%

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

   if -2.1500000000000001e-270 < t < 1.05000000000000001e-244

   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. Add Preprocessing

   3. Taylor expanded in y around inf 34.5%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in a around inf 27.7%

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

   5. Taylor expanded in b around 0 23.8%

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

      1. mul-1-neg 23.8%

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

      2. distribute-rgt-neg-in 23.8%

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

      3. distribute-lft-neg-in 23.8%

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

      4. *-commutative 23.8%

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

   7. Simplified 23.8%

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

   8. Taylor expanded in a around 0 23.8%

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

      1. mul-1-neg 23.8%

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

      2. *-commutative 23.8%

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

      3. *-commutative 23.8%

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

      4. associate-*r* 23.8%

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

      5. distribute-lft-neg-out 23.8%

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

      6. distribute-rgt-neg-out 23.8%

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

      7. associate-*l* 23.8%

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

      8. associate-*l* 30.8%

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

   10. Simplified 30.8%

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

   if 1.05000000000000001e-244 < t < 4.29999999999999969e-238

   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. Add Preprocessing

   3. Taylor expanded in c around inf 39.3%

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

   4. Taylor expanded in z around inf 99.0%

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

      1. +-commutative 99.0%

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

      2. mul-1-neg 99.0%

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

      3. unsub-neg 99.0%

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

      4. *-commutative 99.0%

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

   6. Simplified 99.0%

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

   7. Taylor expanded in t around 0 66.7%

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

      1. neg-mul-1 66.7%

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

      2. distribute-rgt-neg-in 66.7%

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

   9. Simplified 66.7%

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

   if 4.29999999999999969e-238 < t < 2.5e-110

   1. Initial program 50.6%

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

   3. Taylor expanded in y5 around -inf 42.0%

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

   4. Taylor expanded in i around inf 40.9%

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

      1. associate-*r* 41.0%

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

      2. *-commutative 41.0%

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

      3. *-commutative 41.0%

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

   6. Simplified 41.0%

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

   7. Taylor expanded in t around 0 36.1%

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

      1. mul-1-neg 36.1%

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

      2. associate-*r* 45.6%

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

      3. distribute-rgt-neg-in 45.6%

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

      4. distribute-rgt-neg-in 45.6%

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

   9. Simplified 45.6%

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

   if 2.5e-110 < t < 1.02e-109

   1. Initial program 0.0%

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

   3. Taylor expanded in y around inf 0.0%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in a around inf 100.0%

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

   5. Taylor expanded in b around 0 100.0%

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

      1. mul-1-neg 100.0%

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

      2. distribute-rgt-neg-in 100.0%

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

      3. distribute-lft-neg-in 100.0%

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

      4. *-commutative 100.0%

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

   7. Simplified 100.0%

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

   if 1.02e-109 < t < 5.19999999999999983e23

   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. Add Preprocessing

   3. Taylor expanded in b around inf 42.2%

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

   4. Taylor expanded in y0 around inf 63.1%

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

   if 5.19999999999999983e23 < t < 2.8e211

   1. Initial program 43.7%

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

   3. Taylor expanded in b around inf 46.4%

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

   4. Taylor expanded in a around 0 41.3%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 41.3%

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

      2. *-commutative 41.3%

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

      3. *-commutative 41.3%

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

      4. *-commutative 41.3%

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

   6. Simplified 41.3%

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

   7. Taylor expanded in t around inf 38.8%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]
   8. Step-by-step derivation

      1. associate-*r* 41.5%

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

      2. *-commutative 41.5%

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

   9. Simplified 41.5%

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

   if 2.8e211 < t

   1. Initial program 22.0%

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

   3. Taylor expanded in y4 around inf 34.9%

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

   4. Taylor expanded in c around inf 53.0%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 53.0%

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

      2. *-commutative 53.0%

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

   6. Simplified 53.0%

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

   7. Taylor expanded in y3 around 0 52.8%

      \[\leadsto \color{blue}{-1 \cdot \left(c \cdot \left(t \cdot \left(y2 \cdot y4\right)\right)\right)} \]
   8. Step-by-step derivation

      1. mul-1-neg 52.8%

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

      2. distribute-rgt-neg-in 52.8%

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

   9. Simplified 52.8%

      \[\leadsto \color{blue}{c \cdot \left(-t \cdot \left(y2 \cdot y4\right)\right)} \]
3. Recombined 9 regimes into one program.

4. Final simplification 41.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -3.2 \cdot 10^{+83}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i\right)\right)\\ \mathbf{elif}\;t \leq -2.15 \cdot 10^{-270}:\\ \;\;\;\;c \cdot \left(y \cdot \left(x \cdot \left(-i\right)\right)\right)\\ \mathbf{elif}\;t \leq 1.05 \cdot 10^{-244}:\\ \;\;\;\;y \cdot \left(a \cdot \left(y3 \cdot \left(-y5\right)\right)\right)\\ \mathbf{elif}\;t \leq 4.3 \cdot 10^{-238}:\\ \;\;\;\;c \cdot \left(\left(y0 \cdot y3\right) \cdot \left(-z\right)\right)\\ \mathbf{elif}\;t \leq 2.5 \cdot 10^{-110}:\\ \;\;\;\;\left(i \cdot k\right) \cdot \left(y \cdot y5\right)\\ \mathbf{elif}\;t \leq 1.02 \cdot 10^{-109}:\\ \;\;\;\;a \cdot \left(\left(y3 \cdot y5\right) \cdot \left(-y\right)\right)\\ \mathbf{elif}\;t \leq 5.2 \cdot 10^{+23}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;t \leq 2.8 \cdot 10^{+211}:\\ \;\;\;\;b \cdot \left(\left(t \cdot j\right) \cdot y4\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(t \cdot \left(y2 \cdot \left(-y4\right)\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 13: 30.1% accurate, 2.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := c \cdot \left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right)\right)\\ \mathbf{if}\;y \leq -1060000:\\ \;\;\;\;a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)\\ \mathbf{elif}\;y \leq -1.15 \cdot 10^{-37}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;y \leq -1.4 \cdot 10^{-121}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;y \leq -3.35 \cdot 10^{-181}:\\ \;\;\;\;y4 \cdot \left(c \cdot \left(t \cdot \left(-y2\right)\right)\right)\\ \mathbf{elif}\;y \leq -1.3 \cdot 10^{-249}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;y \leq 5 \cdot 10^{+105}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(i \cdot k\right) \cdot \left(y \cdot y5\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* c (* y0 (- (* x y2) (* z y3))))))
   (if (<= y -1060000.0)
     (* a (* y (- (* x b) (* y3 y5))))
     (if (<= y -1.15e-37)
       t_1
       (if (<= y -1.4e-121)
         (* b (* y0 (- (* z k) (* x j))))
         (if (<= y -3.35e-181)
           (* y4 (* c (* t (- y2))))
           (if (<= y -1.3e-249)
             t_1
             (if (<= y 5e+105)
               (* c (* z (- (* t i) (* y0 y3))))
               (* (* i k) (* y y5))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = c * (y0 * ((x * y2) - (z * y3)));
	double tmp;
	if (y <= -1060000.0) {
		tmp = a * (y * ((x * b) - (y3 * y5)));
	} else if (y <= -1.15e-37) {
		tmp = t_1;
	} else if (y <= -1.4e-121) {
		tmp = b * (y0 * ((z * k) - (x * j)));
	} else if (y <= -3.35e-181) {
		tmp = y4 * (c * (t * -y2));
	} else if (y <= -1.3e-249) {
		tmp = t_1;
	} else if (y <= 5e+105) {
		tmp = c * (z * ((t * i) - (y0 * y3)));
	} else {
		tmp = (i * k) * (y * y5);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = c * (y0 * ((x * y2) - (z * y3)))
    if (y <= (-1060000.0d0)) then
        tmp = a * (y * ((x * b) - (y3 * y5)))
    else if (y <= (-1.15d-37)) then
        tmp = t_1
    else if (y <= (-1.4d-121)) then
        tmp = b * (y0 * ((z * k) - (x * j)))
    else if (y <= (-3.35d-181)) then
        tmp = y4 * (c * (t * -y2))
    else if (y <= (-1.3d-249)) then
        tmp = t_1
    else if (y <= 5d+105) then
        tmp = c * (z * ((t * i) - (y0 * y3)))
    else
        tmp = (i * k) * (y * y5)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = c * (y0 * ((x * y2) - (z * y3)));
	double tmp;
	if (y <= -1060000.0) {
		tmp = a * (y * ((x * b) - (y3 * y5)));
	} else if (y <= -1.15e-37) {
		tmp = t_1;
	} else if (y <= -1.4e-121) {
		tmp = b * (y0 * ((z * k) - (x * j)));
	} else if (y <= -3.35e-181) {
		tmp = y4 * (c * (t * -y2));
	} else if (y <= -1.3e-249) {
		tmp = t_1;
	} else if (y <= 5e+105) {
		tmp = c * (z * ((t * i) - (y0 * y3)));
	} else {
		tmp = (i * k) * (y * y5);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = c * (y0 * ((x * y2) - (z * y3)))
	tmp = 0
	if y <= -1060000.0:
		tmp = a * (y * ((x * b) - (y3 * y5)))
	elif y <= -1.15e-37:
		tmp = t_1
	elif y <= -1.4e-121:
		tmp = b * (y0 * ((z * k) - (x * j)))
	elif y <= -3.35e-181:
		tmp = y4 * (c * (t * -y2))
	elif y <= -1.3e-249:
		tmp = t_1
	elif y <= 5e+105:
		tmp = c * (z * ((t * i) - (y0 * y3)))
	else:
		tmp = (i * k) * (y * y5)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(c * Float64(y0 * Float64(Float64(x * y2) - Float64(z * y3))))
	tmp = 0.0
	if (y <= -1060000.0)
		tmp = Float64(a * Float64(y * Float64(Float64(x * b) - Float64(y3 * y5))));
	elseif (y <= -1.15e-37)
		tmp = t_1;
	elseif (y <= -1.4e-121)
		tmp = Float64(b * Float64(y0 * Float64(Float64(z * k) - Float64(x * j))));
	elseif (y <= -3.35e-181)
		tmp = Float64(y4 * Float64(c * Float64(t * Float64(-y2))));
	elseif (y <= -1.3e-249)
		tmp = t_1;
	elseif (y <= 5e+105)
		tmp = Float64(c * Float64(z * Float64(Float64(t * i) - Float64(y0 * y3))));
	else
		tmp = Float64(Float64(i * k) * Float64(y * y5));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = c * (y0 * ((x * y2) - (z * y3)));
	tmp = 0.0;
	if (y <= -1060000.0)
		tmp = a * (y * ((x * b) - (y3 * y5)));
	elseif (y <= -1.15e-37)
		tmp = t_1;
	elseif (y <= -1.4e-121)
		tmp = b * (y0 * ((z * k) - (x * j)));
	elseif (y <= -3.35e-181)
		tmp = y4 * (c * (t * -y2));
	elseif (y <= -1.3e-249)
		tmp = t_1;
	elseif (y <= 5e+105)
		tmp = c * (z * ((t * i) - (y0 * y3)));
	else
		tmp = (i * k) * (y * y5);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(c * N[(y0 * N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y, -1060000.0], N[(a * N[(y * N[(N[(x * b), $MachinePrecision] - N[(y3 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -1.15e-37], t$95$1, If[LessEqual[y, -1.4e-121], N[(b * N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -3.35e-181], N[(y4 * N[(c * N[(t * (-y2)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -1.3e-249], t$95$1, If[LessEqual[y, 5e+105], N[(c * N[(z * N[(N[(t * i), $MachinePrecision] - N[(y0 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(i * k), $MachinePrecision] * N[(y * y5), $MachinePrecision]), $MachinePrecision]]]]]]]]

Derivation

1. Split input into 6 regimes

2. if y < -1.06e6

   1. Initial program 22.2%

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

   3. Taylor expanded in y around inf 37.1%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in a around inf 39.2%

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

   if -1.06e6 < y < -1.15e-37 or -3.34999999999999979e-181 < y < -1.29999999999999988e-249

   1. Initial program 40.1%

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

   3. Taylor expanded in c around inf 41.1%

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

   4. Taylor expanded in y0 around inf 47.0%

      \[\leadsto \color{blue}{c \cdot \left(y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right)} \]

   if -1.15e-37 < y < -1.4000000000000001e-121

   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. Add Preprocessing

   3. Taylor expanded in b around inf 36.5%

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

   4. Taylor expanded in y0 around inf 42.8%

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

   if -1.4000000000000001e-121 < y < -3.34999999999999979e-181

   1. Initial program 66.5%

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

   3. Taylor expanded in y4 around inf 45.0%

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

   4. Taylor expanded in c around inf 56.4%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 56.4%

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

      2. *-commutative 56.4%

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

   6. Simplified 56.4%

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

   7. Taylor expanded in y3 around 0 45.5%

      \[\leadsto y4 \cdot \color{blue}{\left(-1 \cdot \left(c \cdot \left(t \cdot y2\right)\right)\right)} \]
   8. Step-by-step derivation

      1. mul-1-neg 45.5%

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

      2. *-commutative 45.5%

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

      3. distribute-rgt-neg-in 45.5%

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

   9. Simplified 45.5%

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

   if -1.29999999999999988e-249 < y < 5.00000000000000046e105

   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. Add Preprocessing

   3. Taylor expanded in c around inf 43.9%

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

   4. Taylor expanded in z around inf 44.1%

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

      1. +-commutative 44.1%

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

      2. mul-1-neg 44.1%

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

      3. unsub-neg 44.1%

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

      4. *-commutative 44.1%

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

   6. Simplified 44.1%

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

   if 5.00000000000000046e105 < y

   1. Initial program 28.5%

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

   3. Taylor expanded in y5 around -inf 38.7%

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

   4. Taylor expanded in i around inf 45.7%

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

      1. associate-*r* 43.3%

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

      2. *-commutative 43.3%

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

      3. *-commutative 43.3%

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

   6. Simplified 43.3%

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

   7. Taylor expanded in t around 0 46.1%

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

      1. mul-1-neg 46.1%

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

      2. associate-*r* 48.3%

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

      3. distribute-rgt-neg-in 48.3%

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

      4. distribute-rgt-neg-in 48.3%

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

   9. Simplified 48.3%

      \[\leadsto -1 \cdot \color{blue}{\left(\left(i \cdot k\right) \cdot \left(y \cdot \left(-y5\right)\right)\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 44.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y \leq -1060000:\\ \;\;\;\;a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)\\ \mathbf{elif}\;y \leq -1.15 \cdot 10^{-37}:\\ \;\;\;\;c \cdot \left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right)\right)\\ \mathbf{elif}\;y \leq -1.4 \cdot 10^{-121}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;y \leq -3.35 \cdot 10^{-181}:\\ \;\;\;\;y4 \cdot \left(c \cdot \left(t \cdot \left(-y2\right)\right)\right)\\ \mathbf{elif}\;y \leq -1.3 \cdot 10^{-249}:\\ \;\;\;\;c \cdot \left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right)\right)\\ \mathbf{elif}\;y \leq 5 \cdot 10^{+105}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(i \cdot k\right) \cdot \left(y \cdot y5\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 14: 30.3% accurate, 2.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)\\ t_2 := y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)\\ \mathbf{if}\;t \leq -5 \cdot 10^{+17}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;t \leq -5 \cdot 10^{-271}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{elif}\;t \leq 1.35 \cdot 10^{-259}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;t \leq 2.8 \cdot 10^{-238}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;t \leq 1.3 \cdot 10^{-109}:\\ \;\;\;\;t\_2\\ \mathbf{elif}\;t \leq 1050000:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t \cdot \left(y4 \cdot \left(b \cdot j - c \cdot y2\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* c (* z (- (* t i) (* y0 y3)))))
        (t_2 (* y (* y5 (- (* i k) (* a y3))))))
   (if (<= t -5e+17)
     t_1
     (if (<= t -5e-271)
       (* c (* x (- (* y0 y2) (* y i))))
       (if (<= t 1.35e-259)
         t_2
         (if (<= t 2.8e-238)
           t_1
           (if (<= t 1.3e-109)
             t_2
             (if (<= t 1050000.0)
               (* b (* y0 (- (* z k) (* x j))))
               (* t (* y4 (- (* b j) (* c y2))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = c * (z * ((t * i) - (y0 * y3)));
	double t_2 = y * (y5 * ((i * k) - (a * y3)));
	double tmp;
	if (t <= -5e+17) {
		tmp = t_1;
	} else if (t <= -5e-271) {
		tmp = c * (x * ((y0 * y2) - (y * i)));
	} else if (t <= 1.35e-259) {
		tmp = t_2;
	} else if (t <= 2.8e-238) {
		tmp = t_1;
	} else if (t <= 1.3e-109) {
		tmp = t_2;
	} else if (t <= 1050000.0) {
		tmp = b * (y0 * ((z * k) - (x * j)));
	} else {
		tmp = t * (y4 * ((b * j) - (c * y2)));
	}
	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 = c * (z * ((t * i) - (y0 * y3)))
    t_2 = y * (y5 * ((i * k) - (a * y3)))
    if (t <= (-5d+17)) then
        tmp = t_1
    else if (t <= (-5d-271)) then
        tmp = c * (x * ((y0 * y2) - (y * i)))
    else if (t <= 1.35d-259) then
        tmp = t_2
    else if (t <= 2.8d-238) then
        tmp = t_1
    else if (t <= 1.3d-109) then
        tmp = t_2
    else if (t <= 1050000.0d0) then
        tmp = b * (y0 * ((z * k) - (x * j)))
    else
        tmp = t * (y4 * ((b * j) - (c * y2)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = c * (z * ((t * i) - (y0 * y3)));
	double t_2 = y * (y5 * ((i * k) - (a * y3)));
	double tmp;
	if (t <= -5e+17) {
		tmp = t_1;
	} else if (t <= -5e-271) {
		tmp = c * (x * ((y0 * y2) - (y * i)));
	} else if (t <= 1.35e-259) {
		tmp = t_2;
	} else if (t <= 2.8e-238) {
		tmp = t_1;
	} else if (t <= 1.3e-109) {
		tmp = t_2;
	} else if (t <= 1050000.0) {
		tmp = b * (y0 * ((z * k) - (x * j)));
	} else {
		tmp = t * (y4 * ((b * j) - (c * y2)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = c * (z * ((t * i) - (y0 * y3)))
	t_2 = y * (y5 * ((i * k) - (a * y3)))
	tmp = 0
	if t <= -5e+17:
		tmp = t_1
	elif t <= -5e-271:
		tmp = c * (x * ((y0 * y2) - (y * i)))
	elif t <= 1.35e-259:
		tmp = t_2
	elif t <= 2.8e-238:
		tmp = t_1
	elif t <= 1.3e-109:
		tmp = t_2
	elif t <= 1050000.0:
		tmp = b * (y0 * ((z * k) - (x * j)))
	else:
		tmp = t * (y4 * ((b * j) - (c * y2)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(c * Float64(z * Float64(Float64(t * i) - Float64(y0 * y3))))
	t_2 = Float64(y * Float64(y5 * Float64(Float64(i * k) - Float64(a * y3))))
	tmp = 0.0
	if (t <= -5e+17)
		tmp = t_1;
	elseif (t <= -5e-271)
		tmp = Float64(c * Float64(x * Float64(Float64(y0 * y2) - Float64(y * i))));
	elseif (t <= 1.35e-259)
		tmp = t_2;
	elseif (t <= 2.8e-238)
		tmp = t_1;
	elseif (t <= 1.3e-109)
		tmp = t_2;
	elseif (t <= 1050000.0)
		tmp = Float64(b * Float64(y0 * Float64(Float64(z * k) - Float64(x * j))));
	else
		tmp = Float64(t * Float64(y4 * Float64(Float64(b * j) - Float64(c * y2))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = c * (z * ((t * i) - (y0 * y3)));
	t_2 = y * (y5 * ((i * k) - (a * y3)));
	tmp = 0.0;
	if (t <= -5e+17)
		tmp = t_1;
	elseif (t <= -5e-271)
		tmp = c * (x * ((y0 * y2) - (y * i)));
	elseif (t <= 1.35e-259)
		tmp = t_2;
	elseif (t <= 2.8e-238)
		tmp = t_1;
	elseif (t <= 1.3e-109)
		tmp = t_2;
	elseif (t <= 1050000.0)
		tmp = b * (y0 * ((z * k) - (x * j)));
	else
		tmp = t * (y4 * ((b * j) - (c * y2)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(c * N[(z * N[(N[(t * i), $MachinePrecision] - N[(y0 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(y * N[(y5 * N[(N[(i * k), $MachinePrecision] - N[(a * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -5e+17], t$95$1, If[LessEqual[t, -5e-271], N[(c * N[(x * N[(N[(y0 * y2), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.35e-259], t$95$2, If[LessEqual[t, 2.8e-238], t$95$1, If[LessEqual[t, 1.3e-109], t$95$2, If[LessEqual[t, 1050000.0], N[(b * N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(t * N[(y4 * N[(N[(b * j), $MachinePrecision] - N[(c * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]

Derivation

1. Split input into 5 regimes

2. if t < -5e17 or 1.34999999999999992e-259 < t < 2.80000000000000004e-238

   1. Initial program 22.9%

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

   3. Taylor expanded in c around inf 41.4%

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

   4. Taylor expanded in z around inf 46.0%

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

      1. +-commutative 46.0%

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

      2. mul-1-neg 46.0%

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

      3. unsub-neg 46.0%

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

      4. *-commutative 46.0%

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

   6. Simplified 46.0%

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

   if -5e17 < t < -5.0000000000000002e-271

   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. Add Preprocessing

   3. Taylor expanded in c around inf 47.2%

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

   4. Taylor expanded in x around -inf 47.3%

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

   6. Simplified 48.9%

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

   7. Taylor expanded in x around inf 42.3%

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

   if -5.0000000000000002e-271 < t < 1.34999999999999992e-259 or 2.80000000000000004e-238 < t < 1.2999999999999999e-109

   1. Initial program 44.5%

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

   3. Taylor expanded in y around inf 35.6%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y5 around inf 47.5%

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

   if 1.2999999999999999e-109 < t < 1.05e6

   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. Add Preprocessing

   3. Taylor expanded in b around inf 41.5%

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

   4. Taylor expanded in y0 around inf 64.3%

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

   if 1.05e6 < t

   1. Initial program 34.2%

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

   3. Taylor expanded in y4 around inf 40.8%

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

   4. Taylor expanded in t around inf 47.5%

      \[\leadsto \color{blue}{t \cdot \left(y4 \cdot \left(b \cdot j - c \cdot y2\right)\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 47.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -5 \cdot 10^{+17}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq -5 \cdot 10^{-271}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{elif}\;t \leq 1.35 \cdot 10^{-259}:\\ \;\;\;\;y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq 2.8 \cdot 10^{-238}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq 1.3 \cdot 10^{-109}:\\ \;\;\;\;y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq 1050000:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t \cdot \left(y4 \cdot \left(b \cdot j - c \cdot y2\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 15: 30.3% accurate, 2.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;t \leq -9.2 \cdot 10^{+85}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq -3.8 \cdot 10^{-53}:\\ \;\;\;\;\left(t \cdot b\right) \cdot \left(j \cdot y4 - z \cdot a\right)\\ \mathbf{elif}\;t \leq -1.72 \cdot 10^{-87}:\\ \;\;\;\;y4 \cdot \left(k \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \mathbf{elif}\;t \leq -2.5 \cdot 10^{-268}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{elif}\;t \leq 1.8 \cdot 10^{-109}:\\ \;\;\;\;y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq 1.1:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t \cdot \left(y4 \cdot \left(b \cdot j - c \cdot y2\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= t -9.2e+85)
   (* c (* z (- (* t i) (* y0 y3))))
   (if (<= t -3.8e-53)
     (* (* t b) (- (* j y4) (* z a)))
     (if (<= t -1.72e-87)
       (* y4 (* k (- (* y1 y2) (* y b))))
       (if (<= t -2.5e-268)
         (* c (* x (- (* y0 y2) (* y i))))
         (if (<= t 1.8e-109)
           (* y (* y5 (- (* i k) (* a y3))))
           (if (<= t 1.1)
             (* b (* y0 (- (* z k) (* x j))))
             (* t (* y4 (- (* b j) (* c y2)))))))))))

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 <= -9.2e+85) {
		tmp = c * (z * ((t * i) - (y0 * y3)));
	} else if (t <= -3.8e-53) {
		tmp = (t * b) * ((j * y4) - (z * a));
	} else if (t <= -1.72e-87) {
		tmp = y4 * (k * ((y1 * y2) - (y * b)));
	} else if (t <= -2.5e-268) {
		tmp = c * (x * ((y0 * y2) - (y * i)));
	} else if (t <= 1.8e-109) {
		tmp = y * (y5 * ((i * k) - (a * y3)));
	} else if (t <= 1.1) {
		tmp = b * (y0 * ((z * k) - (x * j)));
	} else {
		tmp = t * (y4 * ((b * j) - (c * y2)));
	}
	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 <= (-9.2d+85)) then
        tmp = c * (z * ((t * i) - (y0 * y3)))
    else if (t <= (-3.8d-53)) then
        tmp = (t * b) * ((j * y4) - (z * a))
    else if (t <= (-1.72d-87)) then
        tmp = y4 * (k * ((y1 * y2) - (y * b)))
    else if (t <= (-2.5d-268)) then
        tmp = c * (x * ((y0 * y2) - (y * i)))
    else if (t <= 1.8d-109) then
        tmp = y * (y5 * ((i * k) - (a * y3)))
    else if (t <= 1.1d0) then
        tmp = b * (y0 * ((z * k) - (x * j)))
    else
        tmp = t * (y4 * ((b * j) - (c * y2)))
    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 <= -9.2e+85) {
		tmp = c * (z * ((t * i) - (y0 * y3)));
	} else if (t <= -3.8e-53) {
		tmp = (t * b) * ((j * y4) - (z * a));
	} else if (t <= -1.72e-87) {
		tmp = y4 * (k * ((y1 * y2) - (y * b)));
	} else if (t <= -2.5e-268) {
		tmp = c * (x * ((y0 * y2) - (y * i)));
	} else if (t <= 1.8e-109) {
		tmp = y * (y5 * ((i * k) - (a * y3)));
	} else if (t <= 1.1) {
		tmp = b * (y0 * ((z * k) - (x * j)));
	} else {
		tmp = t * (y4 * ((b * j) - (c * y2)));
	}
	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 <= -9.2e+85:
		tmp = c * (z * ((t * i) - (y0 * y3)))
	elif t <= -3.8e-53:
		tmp = (t * b) * ((j * y4) - (z * a))
	elif t <= -1.72e-87:
		tmp = y4 * (k * ((y1 * y2) - (y * b)))
	elif t <= -2.5e-268:
		tmp = c * (x * ((y0 * y2) - (y * i)))
	elif t <= 1.8e-109:
		tmp = y * (y5 * ((i * k) - (a * y3)))
	elif t <= 1.1:
		tmp = b * (y0 * ((z * k) - (x * j)))
	else:
		tmp = t * (y4 * ((b * j) - (c * y2)))
	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 <= -9.2e+85)
		tmp = Float64(c * Float64(z * Float64(Float64(t * i) - Float64(y0 * y3))));
	elseif (t <= -3.8e-53)
		tmp = Float64(Float64(t * b) * Float64(Float64(j * y4) - Float64(z * a)));
	elseif (t <= -1.72e-87)
		tmp = Float64(y4 * Float64(k * Float64(Float64(y1 * y2) - Float64(y * b))));
	elseif (t <= -2.5e-268)
		tmp = Float64(c * Float64(x * Float64(Float64(y0 * y2) - Float64(y * i))));
	elseif (t <= 1.8e-109)
		tmp = Float64(y * Float64(y5 * Float64(Float64(i * k) - Float64(a * y3))));
	elseif (t <= 1.1)
		tmp = Float64(b * Float64(y0 * Float64(Float64(z * k) - Float64(x * j))));
	else
		tmp = Float64(t * Float64(y4 * Float64(Float64(b * j) - Float64(c * y2))));
	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 <= -9.2e+85)
		tmp = c * (z * ((t * i) - (y0 * y3)));
	elseif (t <= -3.8e-53)
		tmp = (t * b) * ((j * y4) - (z * a));
	elseif (t <= -1.72e-87)
		tmp = y4 * (k * ((y1 * y2) - (y * b)));
	elseif (t <= -2.5e-268)
		tmp = c * (x * ((y0 * y2) - (y * i)));
	elseif (t <= 1.8e-109)
		tmp = y * (y5 * ((i * k) - (a * y3)));
	elseif (t <= 1.1)
		tmp = b * (y0 * ((z * k) - (x * j)));
	else
		tmp = t * (y4 * ((b * j) - (c * y2)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[t, -9.2e+85], N[(c * N[(z * N[(N[(t * i), $MachinePrecision] - N[(y0 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -3.8e-53], N[(N[(t * b), $MachinePrecision] * N[(N[(j * y4), $MachinePrecision] - N[(z * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -1.72e-87], N[(y4 * N[(k * N[(N[(y1 * y2), $MachinePrecision] - N[(y * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -2.5e-268], N[(c * N[(x * N[(N[(y0 * y2), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.8e-109], N[(y * N[(y5 * N[(N[(i * k), $MachinePrecision] - N[(a * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.1], N[(b * N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(t * N[(y4 * N[(N[(b * j), $MachinePrecision] - N[(c * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]

Derivation

1. Split input into 7 regimes

2. if t < -9.1999999999999996e85

   1. Initial program 20.4%

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

   3. Taylor expanded in c around inf 39.0%

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

   4. Taylor expanded in z around inf 49.4%

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

      1. +-commutative 49.4%

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

      2. mul-1-neg 49.4%

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

      3. unsub-neg 49.4%

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

      4. *-commutative 49.4%

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

   6. Simplified 49.4%

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

   if -9.1999999999999996e85 < t < -3.7999999999999998e-53

   1. Initial program 43.9%

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

   3. Taylor expanded in b around inf 44.8%

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

   4. Taylor expanded in t around inf 53.3%

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

      1. associate-*r* 57.0%

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

      2. *-commutative 57.0%

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

      3. +-commutative 57.0%

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

      4. mul-1-neg 57.0%

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

      5. unsub-neg 57.0%

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

      6. *-commutative 57.0%

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

      7. *-commutative 57.0%

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

   6. Simplified 57.0%

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

   if -3.7999999999999998e-53 < t < -1.7199999999999999e-87

   1. Initial program 21.9%

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

   3. Taylor expanded in y4 around inf 56.0%

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

   4. Taylor expanded in k around inf 67.2%

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

      1. +-commutative 67.2%

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

      2. mul-1-neg 67.2%

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

      3. unsub-neg 67.2%

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

      4. *-commutative 67.2%

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

      5. *-commutative 67.2%

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

   6. Simplified 67.2%

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

   if -1.7199999999999999e-87 < t < -2.5e-268

   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. Add Preprocessing

   3. Taylor expanded in c around inf 50.5%

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

   4. Taylor expanded in x around -inf 50.5%

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

   6. Simplified 53.1%

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

   7. Taylor expanded in x around inf 50.7%

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

   if -2.5e-268 < t < 1.8e-109

   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. Add Preprocessing

   3. Taylor expanded in y around inf 32.3%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in y5 around inf 42.1%

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

   if 1.8e-109 < t < 1.1000000000000001

   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. Add Preprocessing

   3. Taylor expanded in b around inf 41.5%

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

   4. Taylor expanded in y0 around inf 64.3%

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

   if 1.1000000000000001 < t

   1. Initial program 34.2%

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

   3. Taylor expanded in y4 around inf 40.8%

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

   4. Taylor expanded in t around inf 47.5%

      \[\leadsto \color{blue}{t \cdot \left(y4 \cdot \left(b \cdot j - c \cdot y2\right)\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 50.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -9.2 \cdot 10^{+85}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq -3.8 \cdot 10^{-53}:\\ \;\;\;\;\left(t \cdot b\right) \cdot \left(j \cdot y4 - z \cdot a\right)\\ \mathbf{elif}\;t \leq -1.72 \cdot 10^{-87}:\\ \;\;\;\;y4 \cdot \left(k \cdot \left(y1 \cdot y2 - y \cdot b\right)\right)\\ \mathbf{elif}\;t \leq -2.5 \cdot 10^{-268}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{elif}\;t \leq 1.8 \cdot 10^{-109}:\\ \;\;\;\;y \cdot \left(y5 \cdot \left(i \cdot k - a \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq 1.1:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t \cdot \left(y4 \cdot \left(b \cdot j - c \cdot y2\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 16: 21.8% accurate, 2.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(\left(t \cdot j\right) \cdot y4\right)\\ \mathbf{if}\;t \leq -7.8 \cdot 10^{+83}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i\right)\right)\\ \mathbf{elif}\;t \leq -3.4 \cdot 10^{-59}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;t \leq -1.9 \cdot 10^{-87}:\\ \;\;\;\;\left(z \cdot t\right) \cdot \left(c \cdot i\right)\\ \mathbf{elif}\;t \leq -5.1 \cdot 10^{-256}:\\ \;\;\;\;\left(b \cdot k\right) \cdot \left(z \cdot y0\right)\\ \mathbf{elif}\;t \leq 2.3 \cdot 10^{-277}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{elif}\;t \leq 0.0305:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* (* t j) y4))))
   (if (<= t -7.8e+83)
     (* c (* z (* t i)))
     (if (<= t -3.4e-59)
       t_1
       (if (<= t -1.9e-87)
         (* (* z t) (* c i))
         (if (<= t -5.1e-256)
           (* (* b k) (* z y0))
           (if (<= t 2.3e-277)
             (* a (* (* x y) b))
             (if (<= t 0.0305) (* b (* z (* k 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 = b * ((t * j) * y4);
	double tmp;
	if (t <= -7.8e+83) {
		tmp = c * (z * (t * i));
	} else if (t <= -3.4e-59) {
		tmp = t_1;
	} else if (t <= -1.9e-87) {
		tmp = (z * t) * (c * i);
	} else if (t <= -5.1e-256) {
		tmp = (b * k) * (z * y0);
	} else if (t <= 2.3e-277) {
		tmp = a * ((x * y) * b);
	} else if (t <= 0.0305) {
		tmp = b * (z * (k * y0));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = b * ((t * j) * y4)
    if (t <= (-7.8d+83)) then
        tmp = c * (z * (t * i))
    else if (t <= (-3.4d-59)) then
        tmp = t_1
    else if (t <= (-1.9d-87)) then
        tmp = (z * t) * (c * i)
    else if (t <= (-5.1d-256)) then
        tmp = (b * k) * (z * y0)
    else if (t <= 2.3d-277) then
        tmp = a * ((x * y) * b)
    else if (t <= 0.0305d0) then
        tmp = b * (z * (k * 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 = b * ((t * j) * y4);
	double tmp;
	if (t <= -7.8e+83) {
		tmp = c * (z * (t * i));
	} else if (t <= -3.4e-59) {
		tmp = t_1;
	} else if (t <= -1.9e-87) {
		tmp = (z * t) * (c * i);
	} else if (t <= -5.1e-256) {
		tmp = (b * k) * (z * y0);
	} else if (t <= 2.3e-277) {
		tmp = a * ((x * y) * b);
	} else if (t <= 0.0305) {
		tmp = b * (z * (k * 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 = b * ((t * j) * y4)
	tmp = 0
	if t <= -7.8e+83:
		tmp = c * (z * (t * i))
	elif t <= -3.4e-59:
		tmp = t_1
	elif t <= -1.9e-87:
		tmp = (z * t) * (c * i)
	elif t <= -5.1e-256:
		tmp = (b * k) * (z * y0)
	elif t <= 2.3e-277:
		tmp = a * ((x * y) * b)
	elif t <= 0.0305:
		tmp = b * (z * (k * 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(b * Float64(Float64(t * j) * y4))
	tmp = 0.0
	if (t <= -7.8e+83)
		tmp = Float64(c * Float64(z * Float64(t * i)));
	elseif (t <= -3.4e-59)
		tmp = t_1;
	elseif (t <= -1.9e-87)
		tmp = Float64(Float64(z * t) * Float64(c * i));
	elseif (t <= -5.1e-256)
		tmp = Float64(Float64(b * k) * Float64(z * y0));
	elseif (t <= 2.3e-277)
		tmp = Float64(a * Float64(Float64(x * y) * b));
	elseif (t <= 0.0305)
		tmp = Float64(b * Float64(z * Float64(k * 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 = b * ((t * j) * y4);
	tmp = 0.0;
	if (t <= -7.8e+83)
		tmp = c * (z * (t * i));
	elseif (t <= -3.4e-59)
		tmp = t_1;
	elseif (t <= -1.9e-87)
		tmp = (z * t) * (c * i);
	elseif (t <= -5.1e-256)
		tmp = (b * k) * (z * y0);
	elseif (t <= 2.3e-277)
		tmp = a * ((x * y) * b);
	elseif (t <= 0.0305)
		tmp = b * (z * (k * 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[(b * N[(N[(t * j), $MachinePrecision] * y4), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -7.8e+83], N[(c * N[(z * N[(t * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -3.4e-59], t$95$1, If[LessEqual[t, -1.9e-87], N[(N[(z * t), $MachinePrecision] * N[(c * i), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -5.1e-256], N[(N[(b * k), $MachinePrecision] * N[(z * y0), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 2.3e-277], N[(a * N[(N[(x * y), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 0.0305], N[(b * N[(z * N[(k * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]]

Derivation

1. Split input into 6 regimes

2. if t < -7.8000000000000003e83

   1. Initial program 20.4%

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

   3. Taylor expanded in c around inf 39.0%

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

   4. Taylor expanded in z around inf 49.4%

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

      1. +-commutative 49.4%

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

      2. mul-1-neg 49.4%

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

      3. unsub-neg 49.4%

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

      4. *-commutative 49.4%

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

   6. Simplified 49.4%

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

   7. Taylor expanded in t around inf 45.5%

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

   if -7.8000000000000003e83 < t < -3.40000000000000018e-59 or 0.030499999999999999 < t

   1. Initial program 37.3%

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

   3. Taylor expanded in b around inf 40.9%

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

   4. Taylor expanded in a around 0 37.9%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 37.9%

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

      2. *-commutative 37.9%

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

      3. *-commutative 37.9%

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

      4. *-commutative 37.9%

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

   6. Simplified 37.9%

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

   7. Taylor expanded in t around inf 30.3%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]
   8. Step-by-step derivation

      1. associate-*r* 31.4%

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

      2. *-commutative 31.4%

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

   9. Simplified 31.4%

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

   if -3.40000000000000018e-59 < t < -1.9e-87

   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. Add Preprocessing

   3. Taylor expanded in c around inf 38.8%

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

   4. Taylor expanded in z around inf 27.3%

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

      1. +-commutative 27.3%

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

      2. mul-1-neg 27.3%

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

      3. unsub-neg 27.3%

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

      4. *-commutative 27.3%

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

   6. Simplified 27.3%

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

   7. Taylor expanded in t around inf 15.0%

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

      1. associate-*r* 38.4%

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

      2. *-commutative 38.4%

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

   9. Simplified 38.4%

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

   if -1.9e-87 < t < -5.10000000000000011e-256

   1. Initial program 17.4%

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

   3. Taylor expanded in b around inf 21.5%

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

   4. Taylor expanded in a around 0 21.9%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 21.9%

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

      2. *-commutative 21.9%

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

      3. *-commutative 21.9%

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

      4. *-commutative 21.9%

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

   6. Simplified 21.9%

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

   7. Taylor expanded in z around inf 24.6%

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

      1. associate-*r* 27.2%

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

      2. *-commutative 27.2%

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

   9. Simplified 27.2%

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

   if -5.10000000000000011e-256 < t < 2.3e-277

   1. Initial program 43.6%

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

   3. Taylor expanded in y around inf 40.1%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in a around inf 23.6%

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

   5. Taylor expanded in b around inf 27.7%

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

      1. *-commutative 27.7%

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

   7. Simplified 27.7%

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

   if 2.3e-277 < t < 0.030499999999999999

   1. Initial program 37.4%

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

   3. Taylor expanded in b around inf 26.5%

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

   4. Taylor expanded in a around 0 32.2%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 32.2%

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

      2. *-commutative 32.2%

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

      3. *-commutative 32.2%

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

      4. *-commutative 32.2%

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

   6. Simplified 32.2%

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

   7. Taylor expanded in z around inf 31.8%

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

      1. associate-*r* 33.8%

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

   9. Simplified 33.8%

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

4. Final simplification 33.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -7.8 \cdot 10^{+83}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i\right)\right)\\ \mathbf{elif}\;t \leq -3.4 \cdot 10^{-59}:\\ \;\;\;\;b \cdot \left(\left(t \cdot j\right) \cdot y4\right)\\ \mathbf{elif}\;t \leq -1.9 \cdot 10^{-87}:\\ \;\;\;\;\left(z \cdot t\right) \cdot \left(c \cdot i\right)\\ \mathbf{elif}\;t \leq -5.1 \cdot 10^{-256}:\\ \;\;\;\;\left(b \cdot k\right) \cdot \left(z \cdot y0\right)\\ \mathbf{elif}\;t \leq 2.3 \cdot 10^{-277}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{elif}\;t \leq 0.0305:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(\left(t \cdot j\right) \cdot y4\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 17: 22.0% accurate, 2.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(\left(t \cdot j\right) \cdot y4\right)\\ \mathbf{if}\;t \leq -1.45 \cdot 10^{+84}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i\right)\right)\\ \mathbf{elif}\;t \leq -4.7 \cdot 10^{-61}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;t \leq -1.7 \cdot 10^{-87}:\\ \;\;\;\;\left(z \cdot t\right) \cdot \left(c \cdot i\right)\\ \mathbf{elif}\;t \leq -1.4 \cdot 10^{-272}:\\ \;\;\;\;\left(b \cdot k\right) \cdot \left(z \cdot y0\right)\\ \mathbf{elif}\;t \leq 5.1 \cdot 10^{-142}:\\ \;\;\;\;a \cdot \left(\left(y3 \cdot y5\right) \cdot \left(-y\right)\right)\\ \mathbf{elif}\;t \leq 0.145:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* (* t j) y4))))
   (if (<= t -1.45e+84)
     (* c (* z (* t i)))
     (if (<= t -4.7e-61)
       t_1
       (if (<= t -1.7e-87)
         (* (* z t) (* c i))
         (if (<= t -1.4e-272)
           (* (* b k) (* z y0))
           (if (<= t 5.1e-142)
             (* a (* (* y3 y5) (- y)))
             (if (<= t 0.145) (* b (* z (* k 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 = b * ((t * j) * y4);
	double tmp;
	if (t <= -1.45e+84) {
		tmp = c * (z * (t * i));
	} else if (t <= -4.7e-61) {
		tmp = t_1;
	} else if (t <= -1.7e-87) {
		tmp = (z * t) * (c * i);
	} else if (t <= -1.4e-272) {
		tmp = (b * k) * (z * y0);
	} else if (t <= 5.1e-142) {
		tmp = a * ((y3 * y5) * -y);
	} else if (t <= 0.145) {
		tmp = b * (z * (k * y0));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = b * ((t * j) * y4)
    if (t <= (-1.45d+84)) then
        tmp = c * (z * (t * i))
    else if (t <= (-4.7d-61)) then
        tmp = t_1
    else if (t <= (-1.7d-87)) then
        tmp = (z * t) * (c * i)
    else if (t <= (-1.4d-272)) then
        tmp = (b * k) * (z * y0)
    else if (t <= 5.1d-142) then
        tmp = a * ((y3 * y5) * -y)
    else if (t <= 0.145d0) then
        tmp = b * (z * (k * 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 = b * ((t * j) * y4);
	double tmp;
	if (t <= -1.45e+84) {
		tmp = c * (z * (t * i));
	} else if (t <= -4.7e-61) {
		tmp = t_1;
	} else if (t <= -1.7e-87) {
		tmp = (z * t) * (c * i);
	} else if (t <= -1.4e-272) {
		tmp = (b * k) * (z * y0);
	} else if (t <= 5.1e-142) {
		tmp = a * ((y3 * y5) * -y);
	} else if (t <= 0.145) {
		tmp = b * (z * (k * 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 = b * ((t * j) * y4)
	tmp = 0
	if t <= -1.45e+84:
		tmp = c * (z * (t * i))
	elif t <= -4.7e-61:
		tmp = t_1
	elif t <= -1.7e-87:
		tmp = (z * t) * (c * i)
	elif t <= -1.4e-272:
		tmp = (b * k) * (z * y0)
	elif t <= 5.1e-142:
		tmp = a * ((y3 * y5) * -y)
	elif t <= 0.145:
		tmp = b * (z * (k * 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(b * Float64(Float64(t * j) * y4))
	tmp = 0.0
	if (t <= -1.45e+84)
		tmp = Float64(c * Float64(z * Float64(t * i)));
	elseif (t <= -4.7e-61)
		tmp = t_1;
	elseif (t <= -1.7e-87)
		tmp = Float64(Float64(z * t) * Float64(c * i));
	elseif (t <= -1.4e-272)
		tmp = Float64(Float64(b * k) * Float64(z * y0));
	elseif (t <= 5.1e-142)
		tmp = Float64(a * Float64(Float64(y3 * y5) * Float64(-y)));
	elseif (t <= 0.145)
		tmp = Float64(b * Float64(z * Float64(k * 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 = b * ((t * j) * y4);
	tmp = 0.0;
	if (t <= -1.45e+84)
		tmp = c * (z * (t * i));
	elseif (t <= -4.7e-61)
		tmp = t_1;
	elseif (t <= -1.7e-87)
		tmp = (z * t) * (c * i);
	elseif (t <= -1.4e-272)
		tmp = (b * k) * (z * y0);
	elseif (t <= 5.1e-142)
		tmp = a * ((y3 * y5) * -y);
	elseif (t <= 0.145)
		tmp = b * (z * (k * 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[(b * N[(N[(t * j), $MachinePrecision] * y4), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -1.45e+84], N[(c * N[(z * N[(t * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -4.7e-61], t$95$1, If[LessEqual[t, -1.7e-87], N[(N[(z * t), $MachinePrecision] * N[(c * i), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -1.4e-272], N[(N[(b * k), $MachinePrecision] * N[(z * y0), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 5.1e-142], N[(a * N[(N[(y3 * y5), $MachinePrecision] * (-y)), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 0.145], N[(b * N[(z * N[(k * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]]

Derivation

1. Split input into 6 regimes

2. if t < -1.44999999999999994e84

   1. Initial program 20.4%

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

   3. Taylor expanded in c around inf 39.0%

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

   4. Taylor expanded in z around inf 49.4%

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

      1. +-commutative 49.4%

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

      2. mul-1-neg 49.4%

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

      3. unsub-neg 49.4%

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

      4. *-commutative 49.4%

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

   6. Simplified 49.4%

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

   7. Taylor expanded in t around inf 45.5%

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

   if -1.44999999999999994e84 < t < -4.6999999999999997e-61 or 0.14499999999999999 < t

   1. Initial program 37.3%

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

   3. Taylor expanded in b around inf 40.9%

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

   4. Taylor expanded in a around 0 37.9%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 37.9%

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

      2. *-commutative 37.9%

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

      3. *-commutative 37.9%

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

      4. *-commutative 37.9%

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

   6. Simplified 37.9%

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

   7. Taylor expanded in t around inf 30.3%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]
   8. Step-by-step derivation

      1. associate-*r* 31.4%

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

      2. *-commutative 31.4%

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

   9. Simplified 31.4%

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

   if -4.6999999999999997e-61 < t < -1.6999999999999999e-87

   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. Add Preprocessing

   3. Taylor expanded in c around inf 38.8%

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

   4. Taylor expanded in z around inf 27.3%

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

      1. +-commutative 27.3%

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

      2. mul-1-neg 27.3%

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

      3. unsub-neg 27.3%

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

      4. *-commutative 27.3%

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

   6. Simplified 27.3%

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

   7. Taylor expanded in t around inf 15.0%

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

      1. associate-*r* 38.4%

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

      2. *-commutative 38.4%

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

   9. Simplified 38.4%

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

   if -1.6999999999999999e-87 < t < -1.39999999999999997e-272

   1. Initial program 17.8%

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

   3. Taylor expanded in b around inf 24.0%

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

   4. Taylor expanded in a around 0 21.8%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 21.8%

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

      2. *-commutative 21.8%

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

      3. *-commutative 21.8%

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

      4. *-commutative 21.8%

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

   6. Simplified 21.8%

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

   7. Taylor expanded in z around inf 24.2%

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

      1. associate-*r* 26.5%

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

      2. *-commutative 26.5%

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

   9. Simplified 26.5%

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

   if -1.39999999999999997e-272 < t < 5.1000000000000001e-142

   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. Add Preprocessing

   3. Taylor expanded in y around inf 37.7%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in a around inf 30.9%

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

   5. Taylor expanded in b around 0 23.4%

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

      1. mul-1-neg 23.4%

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

      2. distribute-rgt-neg-in 23.4%

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

      3. distribute-lft-neg-in 23.4%

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

      4. *-commutative 23.4%

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

   7. Simplified 23.4%

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

   if 5.1000000000000001e-142 < t < 0.14499999999999999

   1. Initial program 41.6%

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

   3. Taylor expanded in b around inf 35.0%

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

   4. Taylor expanded in a around 0 41.9%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 41.9%

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

      2. *-commutative 41.9%

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

      3. *-commutative 41.9%

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

      4. *-commutative 41.9%

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

   6. Simplified 41.9%

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

   7. Taylor expanded in z around inf 45.7%

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

      1. associate-*r* 49.1%

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

   9. Simplified 49.1%

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

4. Final simplification 34.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -1.45 \cdot 10^{+84}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i\right)\right)\\ \mathbf{elif}\;t \leq -4.7 \cdot 10^{-61}:\\ \;\;\;\;b \cdot \left(\left(t \cdot j\right) \cdot y4\right)\\ \mathbf{elif}\;t \leq -1.7 \cdot 10^{-87}:\\ \;\;\;\;\left(z \cdot t\right) \cdot \left(c \cdot i\right)\\ \mathbf{elif}\;t \leq -1.4 \cdot 10^{-272}:\\ \;\;\;\;\left(b \cdot k\right) \cdot \left(z \cdot y0\right)\\ \mathbf{elif}\;t \leq 5.1 \cdot 10^{-142}:\\ \;\;\;\;a \cdot \left(\left(y3 \cdot y5\right) \cdot \left(-y\right)\right)\\ \mathbf{elif}\;t \leq 0.145:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(\left(t \cdot j\right) \cdot y4\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 18: 28.2% accurate, 2.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := c \cdot \left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right)\right)\\ \mathbf{if}\;y \leq -8200000:\\ \;\;\;\;a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)\\ \mathbf{elif}\;y \leq -3.4 \cdot 10^{-37}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;y \leq -1.95 \cdot 10^{-126}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;y \leq -1.55 \cdot 10^{-180}:\\ \;\;\;\;y4 \cdot \left(c \cdot \left(t \cdot \left(-y2\right)\right)\right)\\ \mathbf{elif}\;y \leq 7.5 \cdot 10^{-117}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;y \leq 3.8 \cdot 10^{+107}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(i \cdot k\right) \cdot \left(y \cdot y5\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* c (* y0 (- (* x y2) (* z y3))))))
   (if (<= y -8200000.0)
     (* a (* y (- (* x b) (* y3 y5))))
     (if (<= y -3.4e-37)
       t_1
       (if (<= y -1.95e-126)
         (* b (* y0 (- (* z k) (* x j))))
         (if (<= y -1.55e-180)
           (* y4 (* c (* t (- y2))))
           (if (<= y 7.5e-117)
             t_1
             (if (<= y 3.8e+107)
               (* c (* z (* t i)))
               (* (* i k) (* y y5))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = c * (y0 * ((x * y2) - (z * y3)));
	double tmp;
	if (y <= -8200000.0) {
		tmp = a * (y * ((x * b) - (y3 * y5)));
	} else if (y <= -3.4e-37) {
		tmp = t_1;
	} else if (y <= -1.95e-126) {
		tmp = b * (y0 * ((z * k) - (x * j)));
	} else if (y <= -1.55e-180) {
		tmp = y4 * (c * (t * -y2));
	} else if (y <= 7.5e-117) {
		tmp = t_1;
	} else if (y <= 3.8e+107) {
		tmp = c * (z * (t * i));
	} else {
		tmp = (i * k) * (y * y5);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = c * (y0 * ((x * y2) - (z * y3)))
    if (y <= (-8200000.0d0)) then
        tmp = a * (y * ((x * b) - (y3 * y5)))
    else if (y <= (-3.4d-37)) then
        tmp = t_1
    else if (y <= (-1.95d-126)) then
        tmp = b * (y0 * ((z * k) - (x * j)))
    else if (y <= (-1.55d-180)) then
        tmp = y4 * (c * (t * -y2))
    else if (y <= 7.5d-117) then
        tmp = t_1
    else if (y <= 3.8d+107) then
        tmp = c * (z * (t * i))
    else
        tmp = (i * k) * (y * y5)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = c * (y0 * ((x * y2) - (z * y3)));
	double tmp;
	if (y <= -8200000.0) {
		tmp = a * (y * ((x * b) - (y3 * y5)));
	} else if (y <= -3.4e-37) {
		tmp = t_1;
	} else if (y <= -1.95e-126) {
		tmp = b * (y0 * ((z * k) - (x * j)));
	} else if (y <= -1.55e-180) {
		tmp = y4 * (c * (t * -y2));
	} else if (y <= 7.5e-117) {
		tmp = t_1;
	} else if (y <= 3.8e+107) {
		tmp = c * (z * (t * i));
	} else {
		tmp = (i * k) * (y * y5);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = c * (y0 * ((x * y2) - (z * y3)))
	tmp = 0
	if y <= -8200000.0:
		tmp = a * (y * ((x * b) - (y3 * y5)))
	elif y <= -3.4e-37:
		tmp = t_1
	elif y <= -1.95e-126:
		tmp = b * (y0 * ((z * k) - (x * j)))
	elif y <= -1.55e-180:
		tmp = y4 * (c * (t * -y2))
	elif y <= 7.5e-117:
		tmp = t_1
	elif y <= 3.8e+107:
		tmp = c * (z * (t * i))
	else:
		tmp = (i * k) * (y * y5)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(c * Float64(y0 * Float64(Float64(x * y2) - Float64(z * y3))))
	tmp = 0.0
	if (y <= -8200000.0)
		tmp = Float64(a * Float64(y * Float64(Float64(x * b) - Float64(y3 * y5))));
	elseif (y <= -3.4e-37)
		tmp = t_1;
	elseif (y <= -1.95e-126)
		tmp = Float64(b * Float64(y0 * Float64(Float64(z * k) - Float64(x * j))));
	elseif (y <= -1.55e-180)
		tmp = Float64(y4 * Float64(c * Float64(t * Float64(-y2))));
	elseif (y <= 7.5e-117)
		tmp = t_1;
	elseif (y <= 3.8e+107)
		tmp = Float64(c * Float64(z * Float64(t * i)));
	else
		tmp = Float64(Float64(i * k) * Float64(y * y5));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = c * (y0 * ((x * y2) - (z * y3)));
	tmp = 0.0;
	if (y <= -8200000.0)
		tmp = a * (y * ((x * b) - (y3 * y5)));
	elseif (y <= -3.4e-37)
		tmp = t_1;
	elseif (y <= -1.95e-126)
		tmp = b * (y0 * ((z * k) - (x * j)));
	elseif (y <= -1.55e-180)
		tmp = y4 * (c * (t * -y2));
	elseif (y <= 7.5e-117)
		tmp = t_1;
	elseif (y <= 3.8e+107)
		tmp = c * (z * (t * i));
	else
		tmp = (i * k) * (y * y5);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(c * N[(y0 * N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y, -8200000.0], N[(a * N[(y * N[(N[(x * b), $MachinePrecision] - N[(y3 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -3.4e-37], t$95$1, If[LessEqual[y, -1.95e-126], N[(b * N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -1.55e-180], N[(y4 * N[(c * N[(t * (-y2)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 7.5e-117], t$95$1, If[LessEqual[y, 3.8e+107], N[(c * N[(z * N[(t * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(i * k), $MachinePrecision] * N[(y * y5), $MachinePrecision]), $MachinePrecision]]]]]]]]

Derivation

1. Split input into 6 regimes

2. if y < -8.2e6

   1. Initial program 22.2%

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

   3. Taylor expanded in y around inf 37.1%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in a around inf 39.2%

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

   if -8.2e6 < y < -3.40000000000000018e-37 or -1.5499999999999999e-180 < y < 7.50000000000000066e-117

   1. Initial program 36.4%

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

   3. Taylor expanded in c around inf 40.6%

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

   4. Taylor expanded in y0 around inf 38.4%

      \[\leadsto \color{blue}{c \cdot \left(y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right)} \]

   if -3.40000000000000018e-37 < y < -1.9499999999999999e-126

   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. Add Preprocessing

   3. Taylor expanded in b around inf 36.5%

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

   4. Taylor expanded in y0 around inf 42.8%

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

   if -1.9499999999999999e-126 < y < -1.5499999999999999e-180

   1. Initial program 66.5%

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

   3. Taylor expanded in y4 around inf 45.0%

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

   4. Taylor expanded in c around inf 56.4%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 56.4%

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

      2. *-commutative 56.4%

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

   6. Simplified 56.4%

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

   7. Taylor expanded in y3 around 0 45.5%

      \[\leadsto y4 \cdot \color{blue}{\left(-1 \cdot \left(c \cdot \left(t \cdot y2\right)\right)\right)} \]
   8. Step-by-step derivation

      1. mul-1-neg 45.5%

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

      2. *-commutative 45.5%

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

      3. distribute-rgt-neg-in 45.5%

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

   9. Simplified 45.5%

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

   if 7.50000000000000066e-117 < y < 3.7999999999999998e107

   1. Initial program 27.6%

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

   3. Taylor expanded in c around inf 47.4%

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

   4. Taylor expanded in z around inf 50.1%

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

      1. +-commutative 50.1%

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

      2. mul-1-neg 50.1%

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

      3. unsub-neg 50.1%

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

      4. *-commutative 50.1%

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

   6. Simplified 50.1%

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

   7. Taylor expanded in t around inf 37.4%

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

   if 3.7999999999999998e107 < y

   1. Initial program 28.5%

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

   3. Taylor expanded in y5 around -inf 38.7%

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

   4. Taylor expanded in i around inf 45.7%

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

      1. associate-*r* 43.3%

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

      2. *-commutative 43.3%

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

      3. *-commutative 43.3%

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

   6. Simplified 43.3%

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

   7. Taylor expanded in t around 0 46.1%

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

      1. mul-1-neg 46.1%

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

      2. associate-*r* 48.3%

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

      3. distribute-rgt-neg-in 48.3%

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

      4. distribute-rgt-neg-in 48.3%

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

   9. Simplified 48.3%

      \[\leadsto -1 \cdot \color{blue}{\left(\left(i \cdot k\right) \cdot \left(y \cdot \left(-y5\right)\right)\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 40.6%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y \leq -8200000:\\ \;\;\;\;a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)\\ \mathbf{elif}\;y \leq -3.4 \cdot 10^{-37}:\\ \;\;\;\;c \cdot \left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right)\right)\\ \mathbf{elif}\;y \leq -1.95 \cdot 10^{-126}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;y \leq -1.55 \cdot 10^{-180}:\\ \;\;\;\;y4 \cdot \left(c \cdot \left(t \cdot \left(-y2\right)\right)\right)\\ \mathbf{elif}\;y \leq 7.5 \cdot 10^{-117}:\\ \;\;\;\;c \cdot \left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right)\right)\\ \mathbf{elif}\;y \leq 3.8 \cdot 10^{+107}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(i \cdot k\right) \cdot \left(y \cdot y5\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 19: 30.0% accurate, 2.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;t \leq -3.1 \cdot 10^{+18}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq 3.5 \cdot 10^{-303}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{elif}\;t \leq 4.8 \cdot 10^{-201}:\\ \;\;\;\;a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq 1.65 \cdot 10^{-135}:\\ \;\;\;\;c \cdot \left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq 3450000:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t \cdot \left(y4 \cdot \left(b \cdot j - c \cdot y2\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= t -3.1e+18)
   (* c (* z (- (* t i) (* y0 y3))))
   (if (<= t 3.5e-303)
     (* c (* x (- (* y0 y2) (* y i))))
     (if (<= t 4.8e-201)
       (* a (* y (- (* x b) (* y3 y5))))
       (if (<= t 1.65e-135)
         (* c (* y0 (- (* x y2) (* z y3))))
         (if (<= t 3450000.0)
           (* b (* y0 (- (* z k) (* x j))))
           (* t (* y4 (- (* b j) (* c y2))))))))))

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 <= -3.1e+18) {
		tmp = c * (z * ((t * i) - (y0 * y3)));
	} else if (t <= 3.5e-303) {
		tmp = c * (x * ((y0 * y2) - (y * i)));
	} else if (t <= 4.8e-201) {
		tmp = a * (y * ((x * b) - (y3 * y5)));
	} else if (t <= 1.65e-135) {
		tmp = c * (y0 * ((x * y2) - (z * y3)));
	} else if (t <= 3450000.0) {
		tmp = b * (y0 * ((z * k) - (x * j)));
	} else {
		tmp = t * (y4 * ((b * j) - (c * y2)));
	}
	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 <= (-3.1d+18)) then
        tmp = c * (z * ((t * i) - (y0 * y3)))
    else if (t <= 3.5d-303) then
        tmp = c * (x * ((y0 * y2) - (y * i)))
    else if (t <= 4.8d-201) then
        tmp = a * (y * ((x * b) - (y3 * y5)))
    else if (t <= 1.65d-135) then
        tmp = c * (y0 * ((x * y2) - (z * y3)))
    else if (t <= 3450000.0d0) then
        tmp = b * (y0 * ((z * k) - (x * j)))
    else
        tmp = t * (y4 * ((b * j) - (c * y2)))
    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 <= -3.1e+18) {
		tmp = c * (z * ((t * i) - (y0 * y3)));
	} else if (t <= 3.5e-303) {
		tmp = c * (x * ((y0 * y2) - (y * i)));
	} else if (t <= 4.8e-201) {
		tmp = a * (y * ((x * b) - (y3 * y5)));
	} else if (t <= 1.65e-135) {
		tmp = c * (y0 * ((x * y2) - (z * y3)));
	} else if (t <= 3450000.0) {
		tmp = b * (y0 * ((z * k) - (x * j)));
	} else {
		tmp = t * (y4 * ((b * j) - (c * y2)));
	}
	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 <= -3.1e+18:
		tmp = c * (z * ((t * i) - (y0 * y3)))
	elif t <= 3.5e-303:
		tmp = c * (x * ((y0 * y2) - (y * i)))
	elif t <= 4.8e-201:
		tmp = a * (y * ((x * b) - (y3 * y5)))
	elif t <= 1.65e-135:
		tmp = c * (y0 * ((x * y2) - (z * y3)))
	elif t <= 3450000.0:
		tmp = b * (y0 * ((z * k) - (x * j)))
	else:
		tmp = t * (y4 * ((b * j) - (c * y2)))
	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 <= -3.1e+18)
		tmp = Float64(c * Float64(z * Float64(Float64(t * i) - Float64(y0 * y3))));
	elseif (t <= 3.5e-303)
		tmp = Float64(c * Float64(x * Float64(Float64(y0 * y2) - Float64(y * i))));
	elseif (t <= 4.8e-201)
		tmp = Float64(a * Float64(y * Float64(Float64(x * b) - Float64(y3 * y5))));
	elseif (t <= 1.65e-135)
		tmp = Float64(c * Float64(y0 * Float64(Float64(x * y2) - Float64(z * y3))));
	elseif (t <= 3450000.0)
		tmp = Float64(b * Float64(y0 * Float64(Float64(z * k) - Float64(x * j))));
	else
		tmp = Float64(t * Float64(y4 * Float64(Float64(b * j) - Float64(c * y2))));
	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 <= -3.1e+18)
		tmp = c * (z * ((t * i) - (y0 * y3)));
	elseif (t <= 3.5e-303)
		tmp = c * (x * ((y0 * y2) - (y * i)));
	elseif (t <= 4.8e-201)
		tmp = a * (y * ((x * b) - (y3 * y5)));
	elseif (t <= 1.65e-135)
		tmp = c * (y0 * ((x * y2) - (z * y3)));
	elseif (t <= 3450000.0)
		tmp = b * (y0 * ((z * k) - (x * j)));
	else
		tmp = t * (y4 * ((b * j) - (c * y2)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[t, -3.1e+18], N[(c * N[(z * N[(N[(t * i), $MachinePrecision] - N[(y0 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 3.5e-303], N[(c * N[(x * N[(N[(y0 * y2), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 4.8e-201], N[(a * N[(y * N[(N[(x * b), $MachinePrecision] - N[(y3 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.65e-135], N[(c * N[(y0 * N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 3450000.0], N[(b * N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(t * N[(y4 * N[(N[(b * j), $MachinePrecision] - N[(c * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

1. Split input into 6 regimes

2. if t < -3.1e18

   1. Initial program 23.8%

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

   3. Taylor expanded in c around inf 41.5%

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

   4. Taylor expanded in z around inf 43.6%

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

      1. +-commutative 43.6%

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

      2. mul-1-neg 43.6%

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

      3. unsub-neg 43.6%

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

      4. *-commutative 43.6%

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

   6. Simplified 43.6%

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

   if -3.1e18 < t < 3.5e-303

   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. Add Preprocessing

   3. Taylor expanded in c around inf 48.3%

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

   4. Taylor expanded in x around -inf 48.3%

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

   6. Simplified 49.8%

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

   7. Taylor expanded in x around inf 39.4%

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

   if 3.5e-303 < t < 4.80000000000000018e-201

   1. Initial program 33.4%

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

   3. Taylor expanded in y around inf 33.2%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in a around inf 37.2%

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

   if 4.80000000000000018e-201 < t < 1.65e-135

   1. Initial program 60.7%

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

   3. Taylor expanded in c around inf 52.1%

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

   4. Taylor expanded in y0 around inf 41.4%

      \[\leadsto \color{blue}{c \cdot \left(y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right)} \]

   if 1.65e-135 < t < 3.45e6

   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. Add Preprocessing

   3. Taylor expanded in b around inf 39.7%

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

   4. Taylor expanded in y0 around inf 61.2%

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

   if 3.45e6 < t

   1. Initial program 34.2%

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

   3. Taylor expanded in y4 around inf 40.8%

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

   4. Taylor expanded in t around inf 47.5%

      \[\leadsto \color{blue}{t \cdot \left(y4 \cdot \left(b \cdot j - c \cdot y2\right)\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 44.6%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -3.1 \cdot 10^{+18}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq 3.5 \cdot 10^{-303}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{elif}\;t \leq 4.8 \cdot 10^{-201}:\\ \;\;\;\;a \cdot \left(y \cdot \left(x \cdot b - y3 \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq 1.65 \cdot 10^{-135}:\\ \;\;\;\;c \cdot \left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq 3450000:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t \cdot \left(y4 \cdot \left(b \cdot j - c \cdot y2\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 20: 21.9% accurate, 2.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;t \leq -5.5 \cdot 10^{+83}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i\right)\right)\\ \mathbf{elif}\;t \leq -9.5 \cdot 10^{-271}:\\ \;\;\;\;c \cdot \left(y \cdot \left(x \cdot \left(-i\right)\right)\right)\\ \mathbf{elif}\;t \leq 2.75 \cdot 10^{-146}:\\ \;\;\;\;y \cdot \left(a \cdot \left(y3 \cdot \left(-y5\right)\right)\right)\\ \mathbf{elif}\;t \leq 0.0072:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 1.7 \cdot 10^{+211}:\\ \;\;\;\;b \cdot \left(\left(t \cdot j\right) \cdot y4\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(t \cdot \left(y2 \cdot \left(-y4\right)\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= t -5.5e+83)
   (* c (* z (* t i)))
   (if (<= t -9.5e-271)
     (* c (* y (* x (- i))))
     (if (<= t 2.75e-146)
       (* y (* a (* y3 (- y5))))
       (if (<= t 0.0072)
         (* b (* z (* k y0)))
         (if (<= t 1.7e+211)
           (* b (* (* t j) y4))
           (* c (* t (* y2 (- 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 (t <= -5.5e+83) {
		tmp = c * (z * (t * i));
	} else if (t <= -9.5e-271) {
		tmp = c * (y * (x * -i));
	} else if (t <= 2.75e-146) {
		tmp = y * (a * (y3 * -y5));
	} else if (t <= 0.0072) {
		tmp = b * (z * (k * y0));
	} else if (t <= 1.7e+211) {
		tmp = b * ((t * j) * y4);
	} else {
		tmp = c * (t * (y2 * -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 (t <= (-5.5d+83)) then
        tmp = c * (z * (t * i))
    else if (t <= (-9.5d-271)) then
        tmp = c * (y * (x * -i))
    else if (t <= 2.75d-146) then
        tmp = y * (a * (y3 * -y5))
    else if (t <= 0.0072d0) then
        tmp = b * (z * (k * y0))
    else if (t <= 1.7d+211) then
        tmp = b * ((t * j) * y4)
    else
        tmp = c * (t * (y2 * -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 (t <= -5.5e+83) {
		tmp = c * (z * (t * i));
	} else if (t <= -9.5e-271) {
		tmp = c * (y * (x * -i));
	} else if (t <= 2.75e-146) {
		tmp = y * (a * (y3 * -y5));
	} else if (t <= 0.0072) {
		tmp = b * (z * (k * y0));
	} else if (t <= 1.7e+211) {
		tmp = b * ((t * j) * y4);
	} else {
		tmp = c * (t * (y2 * -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 t <= -5.5e+83:
		tmp = c * (z * (t * i))
	elif t <= -9.5e-271:
		tmp = c * (y * (x * -i))
	elif t <= 2.75e-146:
		tmp = y * (a * (y3 * -y5))
	elif t <= 0.0072:
		tmp = b * (z * (k * y0))
	elif t <= 1.7e+211:
		tmp = b * ((t * j) * y4)
	else:
		tmp = c * (t * (y2 * -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 (t <= -5.5e+83)
		tmp = Float64(c * Float64(z * Float64(t * i)));
	elseif (t <= -9.5e-271)
		tmp = Float64(c * Float64(y * Float64(x * Float64(-i))));
	elseif (t <= 2.75e-146)
		tmp = Float64(y * Float64(a * Float64(y3 * Float64(-y5))));
	elseif (t <= 0.0072)
		tmp = Float64(b * Float64(z * Float64(k * y0)));
	elseif (t <= 1.7e+211)
		tmp = Float64(b * Float64(Float64(t * j) * y4));
	else
		tmp = Float64(c * Float64(t * Float64(y2 * 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 (t <= -5.5e+83)
		tmp = c * (z * (t * i));
	elseif (t <= -9.5e-271)
		tmp = c * (y * (x * -i));
	elseif (t <= 2.75e-146)
		tmp = y * (a * (y3 * -y5));
	elseif (t <= 0.0072)
		tmp = b * (z * (k * y0));
	elseif (t <= 1.7e+211)
		tmp = b * ((t * j) * y4);
	else
		tmp = c * (t * (y2 * -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[t, -5.5e+83], N[(c * N[(z * N[(t * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -9.5e-271], N[(c * N[(y * N[(x * (-i)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 2.75e-146], N[(y * N[(a * N[(y3 * (-y5)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 0.0072], N[(b * N[(z * N[(k * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.7e+211], N[(b * N[(N[(t * j), $MachinePrecision] * y4), $MachinePrecision]), $MachinePrecision], N[(c * N[(t * N[(y2 * (-y4)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

1. Split input into 6 regimes

2. if t < -5.4999999999999996e83

   1. Initial program 20.4%

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

   3. Taylor expanded in c around inf 39.0%

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

   4. Taylor expanded in z around inf 49.4%

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

      1. +-commutative 49.4%

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

      2. mul-1-neg 49.4%

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

      3. unsub-neg 49.4%

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

      4. *-commutative 49.4%

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

   6. Simplified 49.4%

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

   7. Taylor expanded in t around inf 45.5%

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

   if -5.4999999999999996e83 < t < -9.50000000000000103e-271

   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. Add Preprocessing

   3. Taylor expanded in y around inf 32.6%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in x around inf 33.5%

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

      1. associate-*r* 26.4%

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

      2. *-commutative 26.4%

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

   6. Simplified 26.4%

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

   7. Taylor expanded in b around 0 26.4%

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

      1. mul-1-neg 26.4%

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

      2. distribute-rgt-neg-in 26.4%

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

      3. associate-*r* 27.8%

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

      4. distribute-lft-neg-out 27.8%

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

      5. *-commutative 27.8%

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

      6. distribute-rgt-neg-in 27.8%

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

   9. Simplified 27.8%

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

   if -9.50000000000000103e-271 < t < 2.74999999999999999e-146

   1. Initial program 38.2%

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

   3. Taylor expanded in y around inf 35.9%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in a around inf 29.5%

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

   5. Taylor expanded in b around 0 22.4%

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

      1. mul-1-neg 22.4%

         \[\leadsto a \cdot \color{blue}{\left(-y \cdot \left(y3 \cdot y5\right)\right)} \]

      2. distribute-rgt-neg-in 22.4%

         \[\leadsto a \cdot \color{blue}{\left(y \cdot \left(-y3 \cdot y5\right)\right)} \]

      3. distribute-lft-neg-in 22.4%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(\left(-y3\right) \cdot y5\right)}\right) \]

      4. *-commutative 22.4%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(y5 \cdot \left(-y3\right)\right)}\right) \]

   7. Simplified 22.4%

      \[\leadsto a \cdot \color{blue}{\left(y \cdot \left(y5 \cdot \left(-y3\right)\right)\right)} \]

   8. Taylor expanded in a around 0 22.4%

      \[\leadsto \color{blue}{-1 \cdot \left(a \cdot \left(y \cdot \left(y3 \cdot y5\right)\right)\right)} \]
   9. Step-by-step derivation

      1. mul-1-neg 22.4%

         \[\leadsto \color{blue}{-a \cdot \left(y \cdot \left(y3 \cdot y5\right)\right)} \]

      2. *-commutative 22.4%

         \[\leadsto -\color{blue}{\left(y \cdot \left(y3 \cdot y5\right)\right) \cdot a} \]

      3. *-commutative 22.4%

         \[\leadsto -\left(y \cdot \color{blue}{\left(y5 \cdot y3\right)}\right) \cdot a \]

      4. associate-*r* 20.1%

         \[\leadsto -\color{blue}{\left(\left(y \cdot y5\right) \cdot y3\right)} \cdot a \]

      5. distribute-lft-neg-out 20.1%

         \[\leadsto \color{blue}{\left(-\left(y \cdot y5\right) \cdot y3\right) \cdot a} \]

      6. distribute-rgt-neg-out 20.1%

         \[\leadsto \color{blue}{\left(\left(y \cdot y5\right) \cdot \left(-y3\right)\right)} \cdot a \]

      7. associate-*l* 22.4%

         \[\leadsto \color{blue}{\left(y \cdot \left(y5 \cdot \left(-y3\right)\right)\right)} \cdot a \]

      8. associate-*l* 26.8%

         \[\leadsto \color{blue}{y \cdot \left(\left(y5 \cdot \left(-y3\right)\right) \cdot a\right)} \]

   10. Simplified 26.8%

       \[\leadsto \color{blue}{y \cdot \left(\left(y5 \cdot \left(-y3\right)\right) \cdot a\right)} \]

   if 2.74999999999999999e-146 < t < 0.0071999999999999998

   1. Initial program 41.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 35.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around 0 41.9%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 41.9%

         \[\leadsto b \cdot \left(y4 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. *-commutative 41.9%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - \color{blue}{y \cdot k}\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. *-commutative 41.9%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(\color{blue}{x \cdot j} - k \cdot z\right)\right) \]

      4. *-commutative 41.9%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - \color{blue}{z \cdot k}\right)\right) \]

   6. Simplified 41.9%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - z \cdot k\right)\right)} \]

   7. Taylor expanded in z around inf 45.7%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]
   8. Step-by-step derivation

      1. associate-*r* 49.1%

         \[\leadsto b \cdot \color{blue}{\left(\left(k \cdot y0\right) \cdot z\right)} \]

   9. Simplified 49.1%

      \[\leadsto \color{blue}{b \cdot \left(\left(k \cdot y0\right) \cdot z\right)} \]

   if 0.0071999999999999998 < t < 1.69999999999999995e211

   1. Initial program 42.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 47.9%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around 0 43.2%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 43.2%

         \[\leadsto b \cdot \left(y4 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. *-commutative 43.2%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - \color{blue}{y \cdot k}\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. *-commutative 43.2%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(\color{blue}{x \cdot j} - k \cdot z\right)\right) \]

      4. *-commutative 43.2%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - \color{blue}{z \cdot k}\right)\right) \]

   6. Simplified 43.2%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - z \cdot k\right)\right)} \]

   7. Taylor expanded in t around inf 36.0%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]
   8. Step-by-step derivation

      1. associate-*r* 38.5%

         \[\leadsto b \cdot \color{blue}{\left(\left(j \cdot t\right) \cdot y4\right)} \]

      2. *-commutative 38.5%

         \[\leadsto b \cdot \left(\color{blue}{\left(t \cdot j\right)} \cdot y4\right) \]

   9. Simplified 38.5%

      \[\leadsto \color{blue}{b \cdot \left(\left(t \cdot j\right) \cdot y4\right)} \]

   if 1.69999999999999995e211 < t

   1. Initial program 22.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 34.9%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   4. Taylor expanded in c around inf 53.0%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 53.0%

         \[\leadsto y4 \cdot \left(c \cdot \left(\color{blue}{y3 \cdot y} - t \cdot y2\right)\right) \]

      2. *-commutative 53.0%

         \[\leadsto y4 \cdot \left(c \cdot \left(y3 \cdot y - \color{blue}{y2 \cdot t}\right)\right) \]

   6. Simplified 53.0%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y3 \cdot y - y2 \cdot t\right)\right)} \]

   7. Taylor expanded in y3 around 0 52.8%

      \[\leadsto \color{blue}{-1 \cdot \left(c \cdot \left(t \cdot \left(y2 \cdot y4\right)\right)\right)} \]
   8. Step-by-step derivation

      1. mul-1-neg 52.8%

         \[\leadsto \color{blue}{-c \cdot \left(t \cdot \left(y2 \cdot y4\right)\right)} \]

      2. distribute-rgt-neg-in 52.8%

         \[\leadsto \color{blue}{c \cdot \left(-t \cdot \left(y2 \cdot y4\right)\right)} \]

   9. Simplified 52.8%

      \[\leadsto \color{blue}{c \cdot \left(-t \cdot \left(y2 \cdot y4\right)\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 37.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -5.5 \cdot 10^{+83}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i\right)\right)\\ \mathbf{elif}\;t \leq -9.5 \cdot 10^{-271}:\\ \;\;\;\;c \cdot \left(y \cdot \left(x \cdot \left(-i\right)\right)\right)\\ \mathbf{elif}\;t \leq 2.75 \cdot 10^{-146}:\\ \;\;\;\;y \cdot \left(a \cdot \left(y3 \cdot \left(-y5\right)\right)\right)\\ \mathbf{elif}\;t \leq 0.0072:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 1.7 \cdot 10^{+211}:\\ \;\;\;\;b \cdot \left(\left(t \cdot j\right) \cdot y4\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(t \cdot \left(y2 \cdot \left(-y4\right)\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 21: 20.6% accurate, 3.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;b \leq -6.4 \cdot 10^{+209}:\\ \;\;\;\;y \cdot \left(a \cdot \left(x \cdot b\right)\right)\\ \mathbf{elif}\;b \leq -5 \cdot 10^{-39}:\\ \;\;\;\;y4 \cdot \left(c \cdot \left(y \cdot y3\right)\right)\\ \mathbf{elif}\;b \leq 4.9 \cdot 10^{-145}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i\right)\right)\\ \mathbf{elif}\;b \leq 7.8 \cdot 10^{+139}:\\ \;\;\;\;c \cdot \left(t \cdot \left(y2 \cdot \left(-y4\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot k\right) \cdot \left(z \cdot y0\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= b -6.4e+209)
   (* y (* a (* x b)))
   (if (<= b -5e-39)
     (* y4 (* c (* y y3)))
     (if (<= b 4.9e-145)
       (* c (* z (* t i)))
       (if (<= b 7.8e+139) (* c (* t (* y2 (- y4)))) (* (* b k) (* z y0)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (b <= -6.4e+209) {
		tmp = y * (a * (x * b));
	} else if (b <= -5e-39) {
		tmp = y4 * (c * (y * y3));
	} else if (b <= 4.9e-145) {
		tmp = c * (z * (t * i));
	} else if (b <= 7.8e+139) {
		tmp = c * (t * (y2 * -y4));
	} else {
		tmp = (b * k) * (z * y0);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (b <= (-6.4d+209)) then
        tmp = y * (a * (x * b))
    else if (b <= (-5d-39)) then
        tmp = y4 * (c * (y * y3))
    else if (b <= 4.9d-145) then
        tmp = c * (z * (t * i))
    else if (b <= 7.8d+139) then
        tmp = c * (t * (y2 * -y4))
    else
        tmp = (b * k) * (z * y0)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (b <= -6.4e+209) {
		tmp = y * (a * (x * b));
	} else if (b <= -5e-39) {
		tmp = y4 * (c * (y * y3));
	} else if (b <= 4.9e-145) {
		tmp = c * (z * (t * i));
	} else if (b <= 7.8e+139) {
		tmp = c * (t * (y2 * -y4));
	} else {
		tmp = (b * k) * (z * y0);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if b <= -6.4e+209:
		tmp = y * (a * (x * b))
	elif b <= -5e-39:
		tmp = y4 * (c * (y * y3))
	elif b <= 4.9e-145:
		tmp = c * (z * (t * i))
	elif b <= 7.8e+139:
		tmp = c * (t * (y2 * -y4))
	else:
		tmp = (b * k) * (z * y0)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (b <= -6.4e+209)
		tmp = Float64(y * Float64(a * Float64(x * b)));
	elseif (b <= -5e-39)
		tmp = Float64(y4 * Float64(c * Float64(y * y3)));
	elseif (b <= 4.9e-145)
		tmp = Float64(c * Float64(z * Float64(t * i)));
	elseif (b <= 7.8e+139)
		tmp = Float64(c * Float64(t * Float64(y2 * Float64(-y4))));
	else
		tmp = Float64(Float64(b * k) * Float64(z * y0));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (b <= -6.4e+209)
		tmp = y * (a * (x * b));
	elseif (b <= -5e-39)
		tmp = y4 * (c * (y * y3));
	elseif (b <= 4.9e-145)
		tmp = c * (z * (t * i));
	elseif (b <= 7.8e+139)
		tmp = c * (t * (y2 * -y4));
	else
		tmp = (b * k) * (z * y0);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[b, -6.4e+209], N[(y * N[(a * N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[b, -5e-39], N[(y4 * N[(c * N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[b, 4.9e-145], N[(c * N[(z * N[(t * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[b, 7.8e+139], N[(c * N[(t * N[(y2 * (-y4)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(b * k), $MachinePrecision] * N[(z * y0), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

1. Split input into 5 regimes

2. if b < -6.3999999999999999e209

   1. Initial program 33.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 39.4%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in a around inf 45.6%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(b \cdot x - y3 \cdot y5\right)\right)} \]

   5. Taylor expanded in b around inf 51.1%

      \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x\right)}\right) \]
   6. Step-by-step derivation

      1. *-commutative 51.1%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(x \cdot b\right)}\right) \]

   7. Simplified 51.1%

      \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(x \cdot b\right)}\right) \]

   8. Taylor expanded in a around 0 50.8%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y\right)\right)} \]
   9. Step-by-step derivation

      1. *-commutative 50.8%

         \[\leadsto \color{blue}{\left(b \cdot \left(x \cdot y\right)\right) \cdot a} \]

      2. associate-*r* 51.1%

         \[\leadsto \color{blue}{\left(\left(b \cdot x\right) \cdot y\right)} \cdot a \]

      3. *-commutative 51.1%

         \[\leadsto \color{blue}{\left(y \cdot \left(b \cdot x\right)\right)} \cdot a \]

      4. associate-*l* 61.7%

         \[\leadsto \color{blue}{y \cdot \left(\left(b \cdot x\right) \cdot a\right)} \]

   10. Simplified 61.7%

       \[\leadsto \color{blue}{y \cdot \left(\left(b \cdot x\right) \cdot a\right)} \]

   if -6.3999999999999999e209 < b < -4.9999999999999998e-39

   1. Initial program 23.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 33.9%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   4. Taylor expanded in c around inf 40.4%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 40.4%

         \[\leadsto y4 \cdot \left(c \cdot \left(\color{blue}{y3 \cdot y} - t \cdot y2\right)\right) \]

      2. *-commutative 40.4%

         \[\leadsto y4 \cdot \left(c \cdot \left(y3 \cdot y - \color{blue}{y2 \cdot t}\right)\right) \]

   6. Simplified 40.4%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y3 \cdot y - y2 \cdot t\right)\right)} \]

   7. Taylor expanded in y3 around inf 34.6%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y \cdot y3\right)\right)} \]
   8. Step-by-step derivation

      1. *-commutative 34.6%

         \[\leadsto y4 \cdot \left(c \cdot \color{blue}{\left(y3 \cdot y\right)}\right) \]

   9. Simplified 34.6%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y3 \cdot y\right)\right)} \]

   if -4.9999999999999998e-39 < b < 4.89999999999999967e-145

   1. Initial program 33.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in c around inf 39.7%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   4. Taylor expanded in z around inf 33.9%

      \[\leadsto \color{blue}{c \cdot \left(z \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 33.9%

         \[\leadsto c \cdot \left(z \cdot \color{blue}{\left(i \cdot t + -1 \cdot \left(y0 \cdot y3\right)\right)}\right) \]

      2. mul-1-neg 33.9%

         \[\leadsto c \cdot \left(z \cdot \left(i \cdot t + \color{blue}{\left(-y0 \cdot y3\right)}\right)\right) \]

      3. unsub-neg 33.9%

         \[\leadsto c \cdot \left(z \cdot \color{blue}{\left(i \cdot t - y0 \cdot y3\right)}\right) \]

      4. *-commutative 33.9%

         \[\leadsto c \cdot \left(z \cdot \left(\color{blue}{t \cdot i} - y0 \cdot y3\right)\right) \]

   6. Simplified 33.9%

      \[\leadsto \color{blue}{c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)} \]

   7. Taylor expanded in t around inf 27.7%

      \[\leadsto c \cdot \left(z \cdot \color{blue}{\left(i \cdot t\right)}\right) \]

   if 4.89999999999999967e-145 < b < 7.80000000000000012e139

   1. Initial program 34.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 44.7%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   4. Taylor expanded in c around inf 35.5%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 35.5%

         \[\leadsto y4 \cdot \left(c \cdot \left(\color{blue}{y3 \cdot y} - t \cdot y2\right)\right) \]

      2. *-commutative 35.5%

         \[\leadsto y4 \cdot \left(c \cdot \left(y3 \cdot y - \color{blue}{y2 \cdot t}\right)\right) \]

   6. Simplified 35.5%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y3 \cdot y - y2 \cdot t\right)\right)} \]

   7. Taylor expanded in y3 around 0 35.2%

      \[\leadsto \color{blue}{-1 \cdot \left(c \cdot \left(t \cdot \left(y2 \cdot y4\right)\right)\right)} \]
   8. Step-by-step derivation

      1. mul-1-neg 35.2%

         \[\leadsto \color{blue}{-c \cdot \left(t \cdot \left(y2 \cdot y4\right)\right)} \]

      2. distribute-rgt-neg-in 35.2%

         \[\leadsto \color{blue}{c \cdot \left(-t \cdot \left(y2 \cdot y4\right)\right)} \]

   9. Simplified 35.2%

      \[\leadsto \color{blue}{c \cdot \left(-t \cdot \left(y2 \cdot y4\right)\right)} \]

   if 7.80000000000000012e139 < b

   1. Initial program 33.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 42.9%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around 0 40.7%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 40.7%

         \[\leadsto b \cdot \left(y4 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. *-commutative 40.7%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - \color{blue}{y \cdot k}\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. *-commutative 40.7%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(\color{blue}{x \cdot j} - k \cdot z\right)\right) \]

      4. *-commutative 40.7%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - \color{blue}{z \cdot k}\right)\right) \]

   6. Simplified 40.7%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - z \cdot k\right)\right)} \]

   7. Taylor expanded in z around inf 32.1%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]
   8. Step-by-step derivation

      1. associate-*r* 37.3%

         \[\leadsto \color{blue}{\left(b \cdot k\right) \cdot \left(y0 \cdot z\right)} \]

      2. *-commutative 37.3%

         \[\leadsto \left(b \cdot k\right) \cdot \color{blue}{\left(z \cdot y0\right)} \]

   9. Simplified 37.3%

      \[\leadsto \color{blue}{\left(b \cdot k\right) \cdot \left(z \cdot y0\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 34.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;b \leq -6.4 \cdot 10^{+209}:\\ \;\;\;\;y \cdot \left(a \cdot \left(x \cdot b\right)\right)\\ \mathbf{elif}\;b \leq -5 \cdot 10^{-39}:\\ \;\;\;\;y4 \cdot \left(c \cdot \left(y \cdot y3\right)\right)\\ \mathbf{elif}\;b \leq 4.9 \cdot 10^{-145}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i\right)\right)\\ \mathbf{elif}\;b \leq 7.8 \cdot 10^{+139}:\\ \;\;\;\;c \cdot \left(t \cdot \left(y2 \cdot \left(-y4\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot k\right) \cdot \left(z \cdot y0\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 22: 21.8% accurate, 3.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;t \leq -1.25 \cdot 10^{+84}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i\right)\right)\\ \mathbf{elif}\;t \leq 8 \cdot 10^{-179}:\\ \;\;\;\;c \cdot \left(\left(y0 \cdot y3\right) \cdot \left(-z\right)\right)\\ \mathbf{elif}\;t \leq 0.142:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 6.2 \cdot 10^{+210}:\\ \;\;\;\;b \cdot \left(\left(t \cdot j\right) \cdot y4\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(t \cdot \left(y2 \cdot \left(-y4\right)\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= t -1.25e+84)
   (* c (* z (* t i)))
   (if (<= t 8e-179)
     (* c (* (* y0 y3) (- z)))
     (if (<= t 0.142)
       (* b (* z (* k y0)))
       (if (<= t 6.2e+210) (* b (* (* t j) y4)) (* c (* t (* y2 (- 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 (t <= -1.25e+84) {
		tmp = c * (z * (t * i));
	} else if (t <= 8e-179) {
		tmp = c * ((y0 * y3) * -z);
	} else if (t <= 0.142) {
		tmp = b * (z * (k * y0));
	} else if (t <= 6.2e+210) {
		tmp = b * ((t * j) * y4);
	} else {
		tmp = c * (t * (y2 * -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 (t <= (-1.25d+84)) then
        tmp = c * (z * (t * i))
    else if (t <= 8d-179) then
        tmp = c * ((y0 * y3) * -z)
    else if (t <= 0.142d0) then
        tmp = b * (z * (k * y0))
    else if (t <= 6.2d+210) then
        tmp = b * ((t * j) * y4)
    else
        tmp = c * (t * (y2 * -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 (t <= -1.25e+84) {
		tmp = c * (z * (t * i));
	} else if (t <= 8e-179) {
		tmp = c * ((y0 * y3) * -z);
	} else if (t <= 0.142) {
		tmp = b * (z * (k * y0));
	} else if (t <= 6.2e+210) {
		tmp = b * ((t * j) * y4);
	} else {
		tmp = c * (t * (y2 * -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 t <= -1.25e+84:
		tmp = c * (z * (t * i))
	elif t <= 8e-179:
		tmp = c * ((y0 * y3) * -z)
	elif t <= 0.142:
		tmp = b * (z * (k * y0))
	elif t <= 6.2e+210:
		tmp = b * ((t * j) * y4)
	else:
		tmp = c * (t * (y2 * -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 (t <= -1.25e+84)
		tmp = Float64(c * Float64(z * Float64(t * i)));
	elseif (t <= 8e-179)
		tmp = Float64(c * Float64(Float64(y0 * y3) * Float64(-z)));
	elseif (t <= 0.142)
		tmp = Float64(b * Float64(z * Float64(k * y0)));
	elseif (t <= 6.2e+210)
		tmp = Float64(b * Float64(Float64(t * j) * y4));
	else
		tmp = Float64(c * Float64(t * Float64(y2 * 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 (t <= -1.25e+84)
		tmp = c * (z * (t * i));
	elseif (t <= 8e-179)
		tmp = c * ((y0 * y3) * -z);
	elseif (t <= 0.142)
		tmp = b * (z * (k * y0));
	elseif (t <= 6.2e+210)
		tmp = b * ((t * j) * y4);
	else
		tmp = c * (t * (y2 * -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[t, -1.25e+84], N[(c * N[(z * N[(t * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 8e-179], N[(c * N[(N[(y0 * y3), $MachinePrecision] * (-z)), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 0.142], N[(b * N[(z * N[(k * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 6.2e+210], N[(b * N[(N[(t * j), $MachinePrecision] * y4), $MachinePrecision]), $MachinePrecision], N[(c * N[(t * N[(y2 * (-y4)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

1. Split input into 5 regimes

2. if t < -1.25e84

   1. Initial program 20.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in c around inf 39.0%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   4. Taylor expanded in z around inf 49.4%

      \[\leadsto \color{blue}{c \cdot \left(z \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 49.4%

         \[\leadsto c \cdot \left(z \cdot \color{blue}{\left(i \cdot t + -1 \cdot \left(y0 \cdot y3\right)\right)}\right) \]

      2. mul-1-neg 49.4%

         \[\leadsto c \cdot \left(z \cdot \left(i \cdot t + \color{blue}{\left(-y0 \cdot y3\right)}\right)\right) \]

      3. unsub-neg 49.4%

         \[\leadsto c \cdot \left(z \cdot \color{blue}{\left(i \cdot t - y0 \cdot y3\right)}\right) \]

      4. *-commutative 49.4%

         \[\leadsto c \cdot \left(z \cdot \left(\color{blue}{t \cdot i} - y0 \cdot y3\right)\right) \]

   6. Simplified 49.4%

      \[\leadsto \color{blue}{c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)} \]

   7. Taylor expanded in t around inf 45.5%

      \[\leadsto c \cdot \left(z \cdot \color{blue}{\left(i \cdot t\right)}\right) \]

   if -1.25e84 < t < 8.0000000000000002e-179

   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. Add Preprocessing

   3. Taylor expanded in c around inf 44.9%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   4. Taylor expanded in z around inf 26.1%

      \[\leadsto \color{blue}{c \cdot \left(z \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 26.1%

         \[\leadsto c \cdot \left(z \cdot \color{blue}{\left(i \cdot t + -1 \cdot \left(y0 \cdot y3\right)\right)}\right) \]

      2. mul-1-neg 26.1%

         \[\leadsto c \cdot \left(z \cdot \left(i \cdot t + \color{blue}{\left(-y0 \cdot y3\right)}\right)\right) \]

      3. unsub-neg 26.1%

         \[\leadsto c \cdot \left(z \cdot \color{blue}{\left(i \cdot t - y0 \cdot y3\right)}\right) \]

      4. *-commutative 26.1%

         \[\leadsto c \cdot \left(z \cdot \left(\color{blue}{t \cdot i} - y0 \cdot y3\right)\right) \]

   6. Simplified 26.1%

      \[\leadsto \color{blue}{c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)} \]

   7. Taylor expanded in t around 0 24.5%

      \[\leadsto c \cdot \left(z \cdot \color{blue}{\left(-1 \cdot \left(y0 \cdot y3\right)\right)}\right) \]
   8. Step-by-step derivation

      1. neg-mul-1 24.5%

         \[\leadsto c \cdot \left(z \cdot \color{blue}{\left(-y0 \cdot y3\right)}\right) \]

      2. distribute-rgt-neg-in 24.5%

         \[\leadsto c \cdot \left(z \cdot \color{blue}{\left(y0 \cdot \left(-y3\right)\right)}\right) \]

   9. Simplified 24.5%

      \[\leadsto c \cdot \left(z \cdot \color{blue}{\left(y0 \cdot \left(-y3\right)\right)}\right) \]

   if 8.0000000000000002e-179 < t < 0.141999999999999987

   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. Add Preprocessing

   3. Taylor expanded in b around inf 32.5%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around 0 38.2%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 38.2%

         \[\leadsto b \cdot \left(y4 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. *-commutative 38.2%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - \color{blue}{y \cdot k}\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. *-commutative 38.2%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(\color{blue}{x \cdot j} - k \cdot z\right)\right) \]

      4. *-commutative 38.2%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - \color{blue}{z \cdot k}\right)\right) \]

   6. Simplified 38.2%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - z \cdot k\right)\right)} \]

   7. Taylor expanded in z around inf 38.2%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]
   8. Step-by-step derivation

      1. associate-*r* 41.1%

         \[\leadsto b \cdot \color{blue}{\left(\left(k \cdot y0\right) \cdot z\right)} \]

   9. Simplified 41.1%

      \[\leadsto \color{blue}{b \cdot \left(\left(k \cdot y0\right) \cdot z\right)} \]

   if 0.141999999999999987 < t < 6.1999999999999999e210

   1. Initial program 42.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 47.9%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around 0 43.2%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 43.2%

         \[\leadsto b \cdot \left(y4 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. *-commutative 43.2%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - \color{blue}{y \cdot k}\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. *-commutative 43.2%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(\color{blue}{x \cdot j} - k \cdot z\right)\right) \]

      4. *-commutative 43.2%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - \color{blue}{z \cdot k}\right)\right) \]

   6. Simplified 43.2%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - z \cdot k\right)\right)} \]

   7. Taylor expanded in t around inf 36.0%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]
   8. Step-by-step derivation

      1. associate-*r* 38.5%

         \[\leadsto b \cdot \color{blue}{\left(\left(j \cdot t\right) \cdot y4\right)} \]

      2. *-commutative 38.5%

         \[\leadsto b \cdot \left(\color{blue}{\left(t \cdot j\right)} \cdot y4\right) \]

   9. Simplified 38.5%

      \[\leadsto \color{blue}{b \cdot \left(\left(t \cdot j\right) \cdot y4\right)} \]

   if 6.1999999999999999e210 < t

   1. Initial program 22.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 34.9%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   4. Taylor expanded in c around inf 53.0%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 53.0%

         \[\leadsto y4 \cdot \left(c \cdot \left(\color{blue}{y3 \cdot y} - t \cdot y2\right)\right) \]

      2. *-commutative 53.0%

         \[\leadsto y4 \cdot \left(c \cdot \left(y3 \cdot y - \color{blue}{y2 \cdot t}\right)\right) \]

   6. Simplified 53.0%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y3 \cdot y - y2 \cdot t\right)\right)} \]

   7. Taylor expanded in y3 around 0 52.8%

      \[\leadsto \color{blue}{-1 \cdot \left(c \cdot \left(t \cdot \left(y2 \cdot y4\right)\right)\right)} \]
   8. Step-by-step derivation

      1. mul-1-neg 52.8%

         \[\leadsto \color{blue}{-c \cdot \left(t \cdot \left(y2 \cdot y4\right)\right)} \]

      2. distribute-rgt-neg-in 52.8%

         \[\leadsto \color{blue}{c \cdot \left(-t \cdot \left(y2 \cdot y4\right)\right)} \]

   9. Simplified 52.8%

      \[\leadsto \color{blue}{c \cdot \left(-t \cdot \left(y2 \cdot y4\right)\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 35.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -1.25 \cdot 10^{+84}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i\right)\right)\\ \mathbf{elif}\;t \leq 8 \cdot 10^{-179}:\\ \;\;\;\;c \cdot \left(\left(y0 \cdot y3\right) \cdot \left(-z\right)\right)\\ \mathbf{elif}\;t \leq 0.142:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 6.2 \cdot 10^{+210}:\\ \;\;\;\;b \cdot \left(\left(t \cdot j\right) \cdot y4\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(t \cdot \left(y2 \cdot \left(-y4\right)\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 23: 18.5% accurate, 3.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;k \leq -2.45 \cdot 10^{+42}:\\ \;\;\;\;c \cdot \left(t \cdot \left(y2 \cdot \left(-y4\right)\right)\right)\\ \mathbf{elif}\;k \leq -1.1 \cdot 10^{-239}:\\ \;\;\;\;c \cdot \left(y0 \cdot \left(z \cdot \left(-y3\right)\right)\right)\\ \mathbf{elif}\;k \leq 2.9 \cdot 10^{-6}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i\right)\right)\\ \mathbf{elif}\;k \leq 2.7 \cdot 10^{+239}:\\ \;\;\;\;\left(i \cdot k\right) \cdot \left(y \cdot y5\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(y \cdot \left(-y4\right)\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= k -2.45e+42)
   (* c (* t (* y2 (- y4))))
   (if (<= k -1.1e-239)
     (* c (* y0 (* z (- y3))))
     (if (<= k 2.9e-6)
       (* c (* z (* t i)))
       (if (<= k 2.7e+239) (* (* i k) (* y y5)) (* b (* k (* y (- 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 (k <= -2.45e+42) {
		tmp = c * (t * (y2 * -y4));
	} else if (k <= -1.1e-239) {
		tmp = c * (y0 * (z * -y3));
	} else if (k <= 2.9e-6) {
		tmp = c * (z * (t * i));
	} else if (k <= 2.7e+239) {
		tmp = (i * k) * (y * y5);
	} else {
		tmp = b * (k * (y * -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 (k <= (-2.45d+42)) then
        tmp = c * (t * (y2 * -y4))
    else if (k <= (-1.1d-239)) then
        tmp = c * (y0 * (z * -y3))
    else if (k <= 2.9d-6) then
        tmp = c * (z * (t * i))
    else if (k <= 2.7d+239) then
        tmp = (i * k) * (y * y5)
    else
        tmp = b * (k * (y * -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 (k <= -2.45e+42) {
		tmp = c * (t * (y2 * -y4));
	} else if (k <= -1.1e-239) {
		tmp = c * (y0 * (z * -y3));
	} else if (k <= 2.9e-6) {
		tmp = c * (z * (t * i));
	} else if (k <= 2.7e+239) {
		tmp = (i * k) * (y * y5);
	} else {
		tmp = b * (k * (y * -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 k <= -2.45e+42:
		tmp = c * (t * (y2 * -y4))
	elif k <= -1.1e-239:
		tmp = c * (y0 * (z * -y3))
	elif k <= 2.9e-6:
		tmp = c * (z * (t * i))
	elif k <= 2.7e+239:
		tmp = (i * k) * (y * y5)
	else:
		tmp = b * (k * (y * -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 (k <= -2.45e+42)
		tmp = Float64(c * Float64(t * Float64(y2 * Float64(-y4))));
	elseif (k <= -1.1e-239)
		tmp = Float64(c * Float64(y0 * Float64(z * Float64(-y3))));
	elseif (k <= 2.9e-6)
		tmp = Float64(c * Float64(z * Float64(t * i)));
	elseif (k <= 2.7e+239)
		tmp = Float64(Float64(i * k) * Float64(y * y5));
	else
		tmp = Float64(b * Float64(k * Float64(y * 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 (k <= -2.45e+42)
		tmp = c * (t * (y2 * -y4));
	elseif (k <= -1.1e-239)
		tmp = c * (y0 * (z * -y3));
	elseif (k <= 2.9e-6)
		tmp = c * (z * (t * i));
	elseif (k <= 2.7e+239)
		tmp = (i * k) * (y * y5);
	else
		tmp = b * (k * (y * -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[k, -2.45e+42], N[(c * N[(t * N[(y2 * (-y4)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, -1.1e-239], N[(c * N[(y0 * N[(z * (-y3)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 2.9e-6], N[(c * N[(z * N[(t * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[k, 2.7e+239], N[(N[(i * k), $MachinePrecision] * N[(y * y5), $MachinePrecision]), $MachinePrecision], N[(b * N[(k * N[(y * (-y4)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

1. Split input into 5 regimes

2. if k < -2.4500000000000001e42

   1. Initial program 16.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 37.0%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   4. Taylor expanded in c around inf 32.3%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 32.3%

         \[\leadsto y4 \cdot \left(c \cdot \left(\color{blue}{y3 \cdot y} - t \cdot y2\right)\right) \]

      2. *-commutative 32.3%

         \[\leadsto y4 \cdot \left(c \cdot \left(y3 \cdot y - \color{blue}{y2 \cdot t}\right)\right) \]

   6. Simplified 32.3%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y3 \cdot y - y2 \cdot t\right)\right)} \]

   7. Taylor expanded in y3 around 0 37.9%

      \[\leadsto \color{blue}{-1 \cdot \left(c \cdot \left(t \cdot \left(y2 \cdot y4\right)\right)\right)} \]
   8. Step-by-step derivation

      1. mul-1-neg 37.9%

         \[\leadsto \color{blue}{-c \cdot \left(t \cdot \left(y2 \cdot y4\right)\right)} \]

      2. distribute-rgt-neg-in 37.9%

         \[\leadsto \color{blue}{c \cdot \left(-t \cdot \left(y2 \cdot y4\right)\right)} \]

   9. Simplified 37.9%

      \[\leadsto \color{blue}{c \cdot \left(-t \cdot \left(y2 \cdot y4\right)\right)} \]

   if -2.4500000000000001e42 < k < -1.09999999999999991e-239

   1. Initial program 36.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in c around inf 50.0%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   4. Taylor expanded in z around inf 35.5%

      \[\leadsto \color{blue}{c \cdot \left(z \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 35.5%

         \[\leadsto c \cdot \left(z \cdot \color{blue}{\left(i \cdot t + -1 \cdot \left(y0 \cdot y3\right)\right)}\right) \]

      2. mul-1-neg 35.5%

         \[\leadsto c \cdot \left(z \cdot \left(i \cdot t + \color{blue}{\left(-y0 \cdot y3\right)}\right)\right) \]

      3. unsub-neg 35.5%

         \[\leadsto c \cdot \left(z \cdot \color{blue}{\left(i \cdot t - y0 \cdot y3\right)}\right) \]

      4. *-commutative 35.5%

         \[\leadsto c \cdot \left(z \cdot \left(\color{blue}{t \cdot i} - y0 \cdot y3\right)\right) \]

   6. Simplified 35.5%

      \[\leadsto \color{blue}{c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)} \]

   7. Taylor expanded in t around 0 26.9%

      \[\leadsto c \cdot \color{blue}{\left(-1 \cdot \left(y0 \cdot \left(y3 \cdot z\right)\right)\right)} \]
   8. Step-by-step derivation

      1. associate-*r* 26.9%

         \[\leadsto c \cdot \color{blue}{\left(\left(-1 \cdot y0\right) \cdot \left(y3 \cdot z\right)\right)} \]

      2. neg-mul-1 26.9%

         \[\leadsto c \cdot \left(\color{blue}{\left(-y0\right)} \cdot \left(y3 \cdot z\right)\right) \]

      3. *-commutative 26.9%

         \[\leadsto c \cdot \left(\left(-y0\right) \cdot \color{blue}{\left(z \cdot y3\right)}\right) \]

   9. Simplified 26.9%

      \[\leadsto c \cdot \color{blue}{\left(\left(-y0\right) \cdot \left(z \cdot y3\right)\right)} \]

   if -1.09999999999999991e-239 < k < 2.9000000000000002e-6

   1. Initial program 42.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in c around inf 47.6%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   4. Taylor expanded in z around inf 40.8%

      \[\leadsto \color{blue}{c \cdot \left(z \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 40.8%

         \[\leadsto c \cdot \left(z \cdot \color{blue}{\left(i \cdot t + -1 \cdot \left(y0 \cdot y3\right)\right)}\right) \]

      2. mul-1-neg 40.8%

         \[\leadsto c \cdot \left(z \cdot \left(i \cdot t + \color{blue}{\left(-y0 \cdot y3\right)}\right)\right) \]

      3. unsub-neg 40.8%

         \[\leadsto c \cdot \left(z \cdot \color{blue}{\left(i \cdot t - y0 \cdot y3\right)}\right) \]

      4. *-commutative 40.8%

         \[\leadsto c \cdot \left(z \cdot \left(\color{blue}{t \cdot i} - y0 \cdot y3\right)\right) \]

   6. Simplified 40.8%

      \[\leadsto \color{blue}{c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)} \]

   7. Taylor expanded in t around inf 31.2%

      \[\leadsto c \cdot \left(z \cdot \color{blue}{\left(i \cdot t\right)}\right) \]

   if 2.9000000000000002e-6 < k < 2.6999999999999999e239

   1. Initial program 24.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y5 around -inf 49.7%

      \[\leadsto \color{blue}{-1 \cdot \left(y5 \cdot \left(\left(i \cdot \left(j \cdot t - k \cdot y\right) + y0 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - a \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]

   4. Taylor expanded in i around inf 43.9%

      \[\leadsto -1 \cdot \color{blue}{\left(i \cdot \left(y5 \cdot \left(j \cdot t - k \cdot y\right)\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 38.3%

         \[\leadsto -1 \cdot \color{blue}{\left(\left(i \cdot y5\right) \cdot \left(j \cdot t - k \cdot y\right)\right)} \]

      2. *-commutative 38.3%

         \[\leadsto -1 \cdot \left(\left(i \cdot y5\right) \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right)\right) \]

      3. *-commutative 38.3%

         \[\leadsto -1 \cdot \left(\left(i \cdot y5\right) \cdot \left(t \cdot j - \color{blue}{y \cdot k}\right)\right) \]

   6. Simplified 38.3%

      \[\leadsto -1 \cdot \color{blue}{\left(\left(i \cdot y5\right) \cdot \left(t \cdot j - y \cdot k\right)\right)} \]

   7. Taylor expanded in t around 0 32.5%

      \[\leadsto -1 \cdot \color{blue}{\left(-1 \cdot \left(i \cdot \left(k \cdot \left(y \cdot y5\right)\right)\right)\right)} \]
   8. Step-by-step derivation

      1. mul-1-neg 32.5%

         \[\leadsto -1 \cdot \color{blue}{\left(-i \cdot \left(k \cdot \left(y \cdot y5\right)\right)\right)} \]

      2. associate-*r* 34.3%

         \[\leadsto -1 \cdot \left(-\color{blue}{\left(i \cdot k\right) \cdot \left(y \cdot y5\right)}\right) \]

      3. distribute-rgt-neg-in 34.3%

         \[\leadsto -1 \cdot \color{blue}{\left(\left(i \cdot k\right) \cdot \left(-y \cdot y5\right)\right)} \]

      4. distribute-rgt-neg-in 34.3%

         \[\leadsto -1 \cdot \left(\left(i \cdot k\right) \cdot \color{blue}{\left(y \cdot \left(-y5\right)\right)}\right) \]

   9. Simplified 34.3%

      \[\leadsto -1 \cdot \color{blue}{\left(\left(i \cdot k\right) \cdot \left(y \cdot \left(-y5\right)\right)\right)} \]

   if 2.6999999999999999e239 < k

   1. Initial program 31.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 44.2%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around 0 56.9%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 56.9%

         \[\leadsto b \cdot \left(y4 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. *-commutative 56.9%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - \color{blue}{y \cdot k}\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. *-commutative 56.9%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(\color{blue}{x \cdot j} - k \cdot z\right)\right) \]

      4. *-commutative 56.9%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - \color{blue}{z \cdot k}\right)\right) \]

   6. Simplified 56.9%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - z \cdot k\right)\right)} \]

   7. Taylor expanded in y around inf 56.8%

      \[\leadsto \color{blue}{-1 \cdot \left(b \cdot \left(k \cdot \left(y \cdot y4\right)\right)\right)} \]
   8. Step-by-step derivation

      1. mul-1-neg 56.8%

         \[\leadsto \color{blue}{-b \cdot \left(k \cdot \left(y \cdot y4\right)\right)} \]

      2. distribute-rgt-neg-in 56.8%

         \[\leadsto \color{blue}{b \cdot \left(-k \cdot \left(y \cdot y4\right)\right)} \]

      3. *-commutative 56.8%

         \[\leadsto b \cdot \left(-\color{blue}{\left(y \cdot y4\right) \cdot k}\right) \]

      4. distribute-lft-neg-in 56.8%

         \[\leadsto b \cdot \color{blue}{\left(\left(-y \cdot y4\right) \cdot k\right)} \]

      5. distribute-rgt-neg-in 56.8%

         \[\leadsto b \cdot \left(\color{blue}{\left(y \cdot \left(-y4\right)\right)} \cdot k\right) \]

   9. Simplified 56.8%

      \[\leadsto \color{blue}{b \cdot \left(\left(y \cdot \left(-y4\right)\right) \cdot k\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 33.6%

   \[\leadsto \begin{array}{l} \mathbf{if}\;k \leq -2.45 \cdot 10^{+42}:\\ \;\;\;\;c \cdot \left(t \cdot \left(y2 \cdot \left(-y4\right)\right)\right)\\ \mathbf{elif}\;k \leq -1.1 \cdot 10^{-239}:\\ \;\;\;\;c \cdot \left(y0 \cdot \left(z \cdot \left(-y3\right)\right)\right)\\ \mathbf{elif}\;k \leq 2.9 \cdot 10^{-6}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i\right)\right)\\ \mathbf{elif}\;k \leq 2.7 \cdot 10^{+239}:\\ \;\;\;\;\left(i \cdot k\right) \cdot \left(y \cdot y5\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(k \cdot \left(y \cdot \left(-y4\right)\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 24: 27.1% accurate, 3.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;t \leq -6.4 \cdot 10^{+38}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i\right)\right)\\ \mathbf{elif}\;t \leq 5.1 \cdot 10^{-300}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{elif}\;t \leq 3.7 \cdot 10^{+21}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;t \leq 9.5 \cdot 10^{+210}:\\ \;\;\;\;b \cdot \left(\left(t \cdot j\right) \cdot y4\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(t \cdot \left(y2 \cdot \left(-y4\right)\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= t -6.4e+38)
   (* c (* z (* t i)))
   (if (<= t 5.1e-300)
     (* c (* x (- (* y0 y2) (* y i))))
     (if (<= t 3.7e+21)
       (* b (* y0 (- (* z k) (* x j))))
       (if (<= t 9.5e+210) (* b (* (* t j) y4)) (* c (* t (* y2 (- 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 (t <= -6.4e+38) {
		tmp = c * (z * (t * i));
	} else if (t <= 5.1e-300) {
		tmp = c * (x * ((y0 * y2) - (y * i)));
	} else if (t <= 3.7e+21) {
		tmp = b * (y0 * ((z * k) - (x * j)));
	} else if (t <= 9.5e+210) {
		tmp = b * ((t * j) * y4);
	} else {
		tmp = c * (t * (y2 * -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 (t <= (-6.4d+38)) then
        tmp = c * (z * (t * i))
    else if (t <= 5.1d-300) then
        tmp = c * (x * ((y0 * y2) - (y * i)))
    else if (t <= 3.7d+21) then
        tmp = b * (y0 * ((z * k) - (x * j)))
    else if (t <= 9.5d+210) then
        tmp = b * ((t * j) * y4)
    else
        tmp = c * (t * (y2 * -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 (t <= -6.4e+38) {
		tmp = c * (z * (t * i));
	} else if (t <= 5.1e-300) {
		tmp = c * (x * ((y0 * y2) - (y * i)));
	} else if (t <= 3.7e+21) {
		tmp = b * (y0 * ((z * k) - (x * j)));
	} else if (t <= 9.5e+210) {
		tmp = b * ((t * j) * y4);
	} else {
		tmp = c * (t * (y2 * -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 t <= -6.4e+38:
		tmp = c * (z * (t * i))
	elif t <= 5.1e-300:
		tmp = c * (x * ((y0 * y2) - (y * i)))
	elif t <= 3.7e+21:
		tmp = b * (y0 * ((z * k) - (x * j)))
	elif t <= 9.5e+210:
		tmp = b * ((t * j) * y4)
	else:
		tmp = c * (t * (y2 * -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 (t <= -6.4e+38)
		tmp = Float64(c * Float64(z * Float64(t * i)));
	elseif (t <= 5.1e-300)
		tmp = Float64(c * Float64(x * Float64(Float64(y0 * y2) - Float64(y * i))));
	elseif (t <= 3.7e+21)
		tmp = Float64(b * Float64(y0 * Float64(Float64(z * k) - Float64(x * j))));
	elseif (t <= 9.5e+210)
		tmp = Float64(b * Float64(Float64(t * j) * y4));
	else
		tmp = Float64(c * Float64(t * Float64(y2 * 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 (t <= -6.4e+38)
		tmp = c * (z * (t * i));
	elseif (t <= 5.1e-300)
		tmp = c * (x * ((y0 * y2) - (y * i)));
	elseif (t <= 3.7e+21)
		tmp = b * (y0 * ((z * k) - (x * j)));
	elseif (t <= 9.5e+210)
		tmp = b * ((t * j) * y4);
	else
		tmp = c * (t * (y2 * -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[t, -6.4e+38], N[(c * N[(z * N[(t * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 5.1e-300], N[(c * N[(x * N[(N[(y0 * y2), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 3.7e+21], N[(b * N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 9.5e+210], N[(b * N[(N[(t * j), $MachinePrecision] * y4), $MachinePrecision]), $MachinePrecision], N[(c * N[(t * N[(y2 * (-y4)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

1. Split input into 5 regimes

2. if t < -6.3999999999999997e38

   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. Add Preprocessing

   3. Taylor expanded in c around inf 40.6%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   4. Taylor expanded in z around inf 44.4%

      \[\leadsto \color{blue}{c \cdot \left(z \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 44.4%

         \[\leadsto c \cdot \left(z \cdot \color{blue}{\left(i \cdot t + -1 \cdot \left(y0 \cdot y3\right)\right)}\right) \]

      2. mul-1-neg 44.4%

         \[\leadsto c \cdot \left(z \cdot \left(i \cdot t + \color{blue}{\left(-y0 \cdot y3\right)}\right)\right) \]

      3. unsub-neg 44.4%

         \[\leadsto c \cdot \left(z \cdot \color{blue}{\left(i \cdot t - y0 \cdot y3\right)}\right) \]

      4. *-commutative 44.4%

         \[\leadsto c \cdot \left(z \cdot \left(\color{blue}{t \cdot i} - y0 \cdot y3\right)\right) \]

   6. Simplified 44.4%

      \[\leadsto \color{blue}{c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)} \]

   7. Taylor expanded in t around inf 41.0%

      \[\leadsto c \cdot \left(z \cdot \color{blue}{\left(i \cdot t\right)}\right) \]

   if -6.3999999999999997e38 < t < 5.0999999999999999e-300

   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. Add Preprocessing

   3. Taylor expanded in c around inf 49.1%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   4. Taylor expanded in x around -inf 47.8%

      \[\leadsto c \cdot \color{blue}{\left(\left(-1 \cdot \left(x \cdot \left(-1 \cdot \left(y0 \cdot y2\right) + i \cdot y\right)\right) + \left(-1 \cdot \left(y0 \cdot \left(y3 \cdot z\right)\right) + i \cdot \left(t \cdot z\right)\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]
   5. Step-by-step derivation

   6. Simplified 49.2%

      \[\leadsto c \cdot \color{blue}{\left(\left(z \cdot \left(t \cdot i - y0 \cdot y3\right) - x \cdot \left(y \cdot i - y0 \cdot y2\right)\right) - y4 \cdot \left(y2 \cdot t - y3 \cdot y\right)\right)} \]

   7. Taylor expanded in x around inf 39.8%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y0 \cdot y2 - i \cdot y\right)\right)} \]

   if 5.0999999999999999e-300 < t < 3.7e21

   1. Initial program 39.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 31.2%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in y0 around inf 38.4%

      \[\leadsto \color{blue}{b \cdot \left(y0 \cdot \left(k \cdot z - j \cdot x\right)\right)} \]

   if 3.7e21 < t < 9.5000000000000004e210

   1. Initial program 43.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 46.4%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around 0 41.3%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 41.3%

         \[\leadsto b \cdot \left(y4 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. *-commutative 41.3%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - \color{blue}{y \cdot k}\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. *-commutative 41.3%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(\color{blue}{x \cdot j} - k \cdot z\right)\right) \]

      4. *-commutative 41.3%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - \color{blue}{z \cdot k}\right)\right) \]

   6. Simplified 41.3%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - z \cdot k\right)\right)} \]

   7. Taylor expanded in t around inf 38.8%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]
   8. Step-by-step derivation

      1. associate-*r* 41.5%

         \[\leadsto b \cdot \color{blue}{\left(\left(j \cdot t\right) \cdot y4\right)} \]

      2. *-commutative 41.5%

         \[\leadsto b \cdot \left(\color{blue}{\left(t \cdot j\right)} \cdot y4\right) \]

   9. Simplified 41.5%

      \[\leadsto \color{blue}{b \cdot \left(\left(t \cdot j\right) \cdot y4\right)} \]

   if 9.5000000000000004e210 < t

   1. Initial program 22.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y4 around inf 34.9%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   4. Taylor expanded in c around inf 53.0%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 53.0%

         \[\leadsto y4 \cdot \left(c \cdot \left(\color{blue}{y3 \cdot y} - t \cdot y2\right)\right) \]

      2. *-commutative 53.0%

         \[\leadsto y4 \cdot \left(c \cdot \left(y3 \cdot y - \color{blue}{y2 \cdot t}\right)\right) \]

   6. Simplified 53.0%

      \[\leadsto y4 \cdot \color{blue}{\left(c \cdot \left(y3 \cdot y - y2 \cdot t\right)\right)} \]

   7. Taylor expanded in y3 around 0 52.8%

      \[\leadsto \color{blue}{-1 \cdot \left(c \cdot \left(t \cdot \left(y2 \cdot y4\right)\right)\right)} \]
   8. Step-by-step derivation

      1. mul-1-neg 52.8%

         \[\leadsto \color{blue}{-c \cdot \left(t \cdot \left(y2 \cdot y4\right)\right)} \]

      2. distribute-rgt-neg-in 52.8%

         \[\leadsto \color{blue}{c \cdot \left(-t \cdot \left(y2 \cdot y4\right)\right)} \]

   9. Simplified 52.8%

      \[\leadsto \color{blue}{c \cdot \left(-t \cdot \left(y2 \cdot y4\right)\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 41.1%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -6.4 \cdot 10^{+38}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i\right)\right)\\ \mathbf{elif}\;t \leq 5.1 \cdot 10^{-300}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2 - y \cdot i\right)\right)\\ \mathbf{elif}\;t \leq 3.7 \cdot 10^{+21}:\\ \;\;\;\;b \cdot \left(y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;t \leq 9.5 \cdot 10^{+210}:\\ \;\;\;\;b \cdot \left(\left(t \cdot j\right) \cdot y4\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(t \cdot \left(y2 \cdot \left(-y4\right)\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 25: 22.6% accurate, 3.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;t \leq -9.6 \cdot 10^{+17}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{elif}\;t \leq -3.7 \cdot 10^{-254}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 7.8 \cdot 10^{-276}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{elif}\;t \leq 0.033:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(\left(t \cdot j\right) \cdot y4\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= t -9.6e+17)
   (* b (* j (* t y4)))
   (if (<= t -3.7e-254)
     (* b (* k (* z y0)))
     (if (<= t 7.8e-276)
       (* a (* (* x y) b))
       (if (<= t 0.033) (* b (* z (* k y0))) (* b (* (* t j) 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 (t <= -9.6e+17) {
		tmp = b * (j * (t * y4));
	} else if (t <= -3.7e-254) {
		tmp = b * (k * (z * y0));
	} else if (t <= 7.8e-276) {
		tmp = a * ((x * y) * b);
	} else if (t <= 0.033) {
		tmp = b * (z * (k * y0));
	} else {
		tmp = b * ((t * j) * 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 (t <= (-9.6d+17)) then
        tmp = b * (j * (t * y4))
    else if (t <= (-3.7d-254)) then
        tmp = b * (k * (z * y0))
    else if (t <= 7.8d-276) then
        tmp = a * ((x * y) * b)
    else if (t <= 0.033d0) then
        tmp = b * (z * (k * y0))
    else
        tmp = b * ((t * j) * 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 (t <= -9.6e+17) {
		tmp = b * (j * (t * y4));
	} else if (t <= -3.7e-254) {
		tmp = b * (k * (z * y0));
	} else if (t <= 7.8e-276) {
		tmp = a * ((x * y) * b);
	} else if (t <= 0.033) {
		tmp = b * (z * (k * y0));
	} else {
		tmp = b * ((t * j) * 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 t <= -9.6e+17:
		tmp = b * (j * (t * y4))
	elif t <= -3.7e-254:
		tmp = b * (k * (z * y0))
	elif t <= 7.8e-276:
		tmp = a * ((x * y) * b)
	elif t <= 0.033:
		tmp = b * (z * (k * y0))
	else:
		tmp = b * ((t * j) * 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 (t <= -9.6e+17)
		tmp = Float64(b * Float64(j * Float64(t * y4)));
	elseif (t <= -3.7e-254)
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	elseif (t <= 7.8e-276)
		tmp = Float64(a * Float64(Float64(x * y) * b));
	elseif (t <= 0.033)
		tmp = Float64(b * Float64(z * Float64(k * y0)));
	else
		tmp = Float64(b * Float64(Float64(t * j) * 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 (t <= -9.6e+17)
		tmp = b * (j * (t * y4));
	elseif (t <= -3.7e-254)
		tmp = b * (k * (z * y0));
	elseif (t <= 7.8e-276)
		tmp = a * ((x * y) * b);
	elseif (t <= 0.033)
		tmp = b * (z * (k * y0));
	else
		tmp = b * ((t * j) * 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[t, -9.6e+17], N[(b * N[(j * N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -3.7e-254], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 7.8e-276], N[(a * N[(N[(x * y), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 0.033], N[(b * N[(z * N[(k * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(N[(t * j), $MachinePrecision] * y4), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

1. Split input into 5 regimes

2. if t < -9.6e17

   1. Initial program 23.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 27.6%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around 0 31.3%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 31.3%

         \[\leadsto b \cdot \left(y4 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. *-commutative 31.3%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - \color{blue}{y \cdot k}\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. *-commutative 31.3%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(\color{blue}{x \cdot j} - k \cdot z\right)\right) \]

      4. *-commutative 31.3%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - \color{blue}{z \cdot k}\right)\right) \]

   6. Simplified 31.3%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - z \cdot k\right)\right)} \]

   7. Taylor expanded in t around inf 23.7%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]
   8. Step-by-step derivation

      1. *-commutative 23.7%

         \[\leadsto b \cdot \color{blue}{\left(\left(t \cdot y4\right) \cdot j\right)} \]

   9. Simplified 23.7%

      \[\leadsto \color{blue}{b \cdot \left(\left(t \cdot y4\right) \cdot j\right)} \]

   if -9.6e17 < t < -3.7000000000000004e-254

   1. Initial program 25.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 23.2%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around 0 25.5%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 25.5%

         \[\leadsto b \cdot \left(y4 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. *-commutative 25.5%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - \color{blue}{y \cdot k}\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. *-commutative 25.5%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(\color{blue}{x \cdot j} - k \cdot z\right)\right) \]

      4. *-commutative 25.5%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - \color{blue}{z \cdot k}\right)\right) \]

   6. Simplified 25.5%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - z \cdot k\right)\right)} \]

   7. Taylor expanded in z around inf 25.3%

      \[\leadsto b \cdot \color{blue}{\left(k \cdot \left(y0 \cdot z\right)\right)} \]
   8. Step-by-step derivation

      1. *-commutative 25.3%

         \[\leadsto b \cdot \color{blue}{\left(\left(y0 \cdot z\right) \cdot k\right)} \]

      2. *-commutative 25.3%

         \[\leadsto b \cdot \left(\color{blue}{\left(z \cdot y0\right)} \cdot k\right) \]

   9. Simplified 25.3%

      \[\leadsto b \cdot \color{blue}{\left(\left(z \cdot y0\right) \cdot k\right)} \]

   if -3.7000000000000004e-254 < t < 7.8e-276

   1. Initial program 43.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 40.1%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in a around inf 23.6%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(b \cdot x - y3 \cdot y5\right)\right)} \]

   5. Taylor expanded in b around inf 27.7%

      \[\leadsto a \cdot \color{blue}{\left(b \cdot \left(x \cdot y\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 27.7%

         \[\leadsto a \cdot \color{blue}{\left(\left(x \cdot y\right) \cdot b\right)} \]

   7. Simplified 27.7%

      \[\leadsto a \cdot \color{blue}{\left(\left(x \cdot y\right) \cdot b\right)} \]

   if 7.8e-276 < t < 0.033000000000000002

   1. Initial program 37.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 26.5%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around 0 32.2%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 32.2%

         \[\leadsto b \cdot \left(y4 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. *-commutative 32.2%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - \color{blue}{y \cdot k}\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. *-commutative 32.2%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(\color{blue}{x \cdot j} - k \cdot z\right)\right) \]

      4. *-commutative 32.2%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - \color{blue}{z \cdot k}\right)\right) \]

   6. Simplified 32.2%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - z \cdot k\right)\right)} \]

   7. Taylor expanded in z around inf 31.8%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]
   8. Step-by-step derivation

      1. associate-*r* 33.8%

         \[\leadsto b \cdot \color{blue}{\left(\left(k \cdot y0\right) \cdot z\right)} \]

   9. Simplified 33.8%

      \[\leadsto \color{blue}{b \cdot \left(\left(k \cdot y0\right) \cdot z\right)} \]

   if 0.033000000000000002 < t

   1. Initial program 35.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 38.4%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around 0 34.0%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 34.0%

         \[\leadsto b \cdot \left(y4 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. *-commutative 34.0%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - \color{blue}{y \cdot k}\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. *-commutative 34.0%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(\color{blue}{x \cdot j} - k \cdot z\right)\right) \]

      4. *-commutative 34.0%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - \color{blue}{z \cdot k}\right)\right) \]

   6. Simplified 34.0%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - z \cdot k\right)\right)} \]

   7. Taylor expanded in t around inf 30.9%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]
   8. Step-by-step derivation

      1. associate-*r* 32.5%

         \[\leadsto b \cdot \color{blue}{\left(\left(j \cdot t\right) \cdot y4\right)} \]

      2. *-commutative 32.5%

         \[\leadsto b \cdot \left(\color{blue}{\left(t \cdot j\right)} \cdot y4\right) \]

   9. Simplified 32.5%

      \[\leadsto \color{blue}{b \cdot \left(\left(t \cdot j\right) \cdot y4\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 28.6%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -9.6 \cdot 10^{+17}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{elif}\;t \leq -3.7 \cdot 10^{-254}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 7.8 \cdot 10^{-276}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{elif}\;t \leq 0.033:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(\left(t \cdot j\right) \cdot y4\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 26: 22.5% accurate, 3.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;t \leq -3.2 \cdot 10^{+15}:\\ \;\;\;\;c \cdot \left(\left(z \cdot t\right) \cdot i\right)\\ \mathbf{elif}\;t \leq -3.2 \cdot 10^{-256}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 8 \cdot 10^{-279}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{elif}\;t \leq 0.118:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(\left(t \cdot j\right) \cdot y4\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= t -3.2e+15)
   (* c (* (* z t) i))
   (if (<= t -3.2e-256)
     (* b (* k (* z y0)))
     (if (<= t 8e-279)
       (* a (* (* x y) b))
       (if (<= t 0.118) (* b (* z (* k y0))) (* b (* (* t j) 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 (t <= -3.2e+15) {
		tmp = c * ((z * t) * i);
	} else if (t <= -3.2e-256) {
		tmp = b * (k * (z * y0));
	} else if (t <= 8e-279) {
		tmp = a * ((x * y) * b);
	} else if (t <= 0.118) {
		tmp = b * (z * (k * y0));
	} else {
		tmp = b * ((t * j) * 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 (t <= (-3.2d+15)) then
        tmp = c * ((z * t) * i)
    else if (t <= (-3.2d-256)) then
        tmp = b * (k * (z * y0))
    else if (t <= 8d-279) then
        tmp = a * ((x * y) * b)
    else if (t <= 0.118d0) then
        tmp = b * (z * (k * y0))
    else
        tmp = b * ((t * j) * 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 (t <= -3.2e+15) {
		tmp = c * ((z * t) * i);
	} else if (t <= -3.2e-256) {
		tmp = b * (k * (z * y0));
	} else if (t <= 8e-279) {
		tmp = a * ((x * y) * b);
	} else if (t <= 0.118) {
		tmp = b * (z * (k * y0));
	} else {
		tmp = b * ((t * j) * 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 t <= -3.2e+15:
		tmp = c * ((z * t) * i)
	elif t <= -3.2e-256:
		tmp = b * (k * (z * y0))
	elif t <= 8e-279:
		tmp = a * ((x * y) * b)
	elif t <= 0.118:
		tmp = b * (z * (k * y0))
	else:
		tmp = b * ((t * j) * 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 (t <= -3.2e+15)
		tmp = Float64(c * Float64(Float64(z * t) * i));
	elseif (t <= -3.2e-256)
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	elseif (t <= 8e-279)
		tmp = Float64(a * Float64(Float64(x * y) * b));
	elseif (t <= 0.118)
		tmp = Float64(b * Float64(z * Float64(k * y0)));
	else
		tmp = Float64(b * Float64(Float64(t * j) * 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 (t <= -3.2e+15)
		tmp = c * ((z * t) * i);
	elseif (t <= -3.2e-256)
		tmp = b * (k * (z * y0));
	elseif (t <= 8e-279)
		tmp = a * ((x * y) * b);
	elseif (t <= 0.118)
		tmp = b * (z * (k * y0));
	else
		tmp = b * ((t * j) * 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[t, -3.2e+15], N[(c * N[(N[(z * t), $MachinePrecision] * i), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -3.2e-256], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 8e-279], N[(a * N[(N[(x * y), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 0.118], N[(b * N[(z * N[(k * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(N[(t * j), $MachinePrecision] * y4), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

1. Split input into 5 regimes

2. if t < -3.2e15

   1. Initial program 23.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in c around inf 41.5%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   4. Taylor expanded in z around inf 43.6%

      \[\leadsto \color{blue}{c \cdot \left(z \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 43.6%

         \[\leadsto c \cdot \left(z \cdot \color{blue}{\left(i \cdot t + -1 \cdot \left(y0 \cdot y3\right)\right)}\right) \]

      2. mul-1-neg 43.6%

         \[\leadsto c \cdot \left(z \cdot \left(i \cdot t + \color{blue}{\left(-y0 \cdot y3\right)}\right)\right) \]

      3. unsub-neg 43.6%

         \[\leadsto c \cdot \left(z \cdot \color{blue}{\left(i \cdot t - y0 \cdot y3\right)}\right) \]

      4. *-commutative 43.6%

         \[\leadsto c \cdot \left(z \cdot \left(\color{blue}{t \cdot i} - y0 \cdot y3\right)\right) \]

   6. Simplified 43.6%

      \[\leadsto \color{blue}{c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)} \]

   7. Taylor expanded in t around inf 36.1%

      \[\leadsto \color{blue}{c \cdot \left(i \cdot \left(t \cdot z\right)\right)} \]
   8. Step-by-step derivation

      1. *-commutative 36.1%

         \[\leadsto c \cdot \left(i \cdot \color{blue}{\left(z \cdot t\right)}\right) \]

   9. Simplified 36.1%

      \[\leadsto \color{blue}{c \cdot \left(i \cdot \left(z \cdot t\right)\right)} \]

   if -3.2e15 < t < -3.1999999999999999e-256

   1. Initial program 25.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 23.2%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around 0 25.5%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 25.5%

         \[\leadsto b \cdot \left(y4 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. *-commutative 25.5%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - \color{blue}{y \cdot k}\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. *-commutative 25.5%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(\color{blue}{x \cdot j} - k \cdot z\right)\right) \]

      4. *-commutative 25.5%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - \color{blue}{z \cdot k}\right)\right) \]

   6. Simplified 25.5%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - z \cdot k\right)\right)} \]

   7. Taylor expanded in z around inf 25.3%

      \[\leadsto b \cdot \color{blue}{\left(k \cdot \left(y0 \cdot z\right)\right)} \]
   8. Step-by-step derivation

      1. *-commutative 25.3%

         \[\leadsto b \cdot \color{blue}{\left(\left(y0 \cdot z\right) \cdot k\right)} \]

      2. *-commutative 25.3%

         \[\leadsto b \cdot \left(\color{blue}{\left(z \cdot y0\right)} \cdot k\right) \]

   9. Simplified 25.3%

      \[\leadsto b \cdot \color{blue}{\left(\left(z \cdot y0\right) \cdot k\right)} \]

   if -3.1999999999999999e-256 < t < 8.00000000000000044e-279

   1. Initial program 43.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 40.1%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in a around inf 23.6%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(b \cdot x - y3 \cdot y5\right)\right)} \]

   5. Taylor expanded in b around inf 27.7%

      \[\leadsto a \cdot \color{blue}{\left(b \cdot \left(x \cdot y\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 27.7%

         \[\leadsto a \cdot \color{blue}{\left(\left(x \cdot y\right) \cdot b\right)} \]

   7. Simplified 27.7%

      \[\leadsto a \cdot \color{blue}{\left(\left(x \cdot y\right) \cdot b\right)} \]

   if 8.00000000000000044e-279 < t < 0.11799999999999999

   1. Initial program 37.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 26.5%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around 0 32.2%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 32.2%

         \[\leadsto b \cdot \left(y4 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. *-commutative 32.2%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - \color{blue}{y \cdot k}\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. *-commutative 32.2%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(\color{blue}{x \cdot j} - k \cdot z\right)\right) \]

      4. *-commutative 32.2%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - \color{blue}{z \cdot k}\right)\right) \]

   6. Simplified 32.2%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - z \cdot k\right)\right)} \]

   7. Taylor expanded in z around inf 31.8%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]
   8. Step-by-step derivation

      1. associate-*r* 33.8%

         \[\leadsto b \cdot \color{blue}{\left(\left(k \cdot y0\right) \cdot z\right)} \]

   9. Simplified 33.8%

      \[\leadsto \color{blue}{b \cdot \left(\left(k \cdot y0\right) \cdot z\right)} \]

   if 0.11799999999999999 < t

   1. Initial program 35.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 38.4%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around 0 34.0%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 34.0%

         \[\leadsto b \cdot \left(y4 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. *-commutative 34.0%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - \color{blue}{y \cdot k}\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. *-commutative 34.0%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(\color{blue}{x \cdot j} - k \cdot z\right)\right) \]

      4. *-commutative 34.0%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - \color{blue}{z \cdot k}\right)\right) \]

   6. Simplified 34.0%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - z \cdot k\right)\right)} \]

   7. Taylor expanded in t around inf 30.9%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]
   8. Step-by-step derivation

      1. associate-*r* 32.5%

         \[\leadsto b \cdot \color{blue}{\left(\left(j \cdot t\right) \cdot y4\right)} \]

      2. *-commutative 32.5%

         \[\leadsto b \cdot \left(\color{blue}{\left(t \cdot j\right)} \cdot y4\right) \]

   9. Simplified 32.5%

      \[\leadsto \color{blue}{b \cdot \left(\left(t \cdot j\right) \cdot y4\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 31.7%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -3.2 \cdot 10^{+15}:\\ \;\;\;\;c \cdot \left(\left(z \cdot t\right) \cdot i\right)\\ \mathbf{elif}\;t \leq -3.2 \cdot 10^{-256}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 8 \cdot 10^{-279}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{elif}\;t \leq 0.118:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(\left(t \cdot j\right) \cdot y4\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 27: 22.4% accurate, 3.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;t \leq -6 \cdot 10^{+17}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i\right)\right)\\ \mathbf{elif}\;t \leq -3.95 \cdot 10^{-252}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 3.6 \cdot 10^{-276}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{elif}\;t \leq 0.047:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(\left(t \cdot j\right) \cdot y4\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= t -6e+17)
   (* c (* z (* t i)))
   (if (<= t -3.95e-252)
     (* b (* k (* z y0)))
     (if (<= t 3.6e-276)
       (* a (* (* x y) b))
       (if (<= t 0.047) (* b (* z (* k y0))) (* b (* (* t j) 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 (t <= -6e+17) {
		tmp = c * (z * (t * i));
	} else if (t <= -3.95e-252) {
		tmp = b * (k * (z * y0));
	} else if (t <= 3.6e-276) {
		tmp = a * ((x * y) * b);
	} else if (t <= 0.047) {
		tmp = b * (z * (k * y0));
	} else {
		tmp = b * ((t * j) * 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 (t <= (-6d+17)) then
        tmp = c * (z * (t * i))
    else if (t <= (-3.95d-252)) then
        tmp = b * (k * (z * y0))
    else if (t <= 3.6d-276) then
        tmp = a * ((x * y) * b)
    else if (t <= 0.047d0) then
        tmp = b * (z * (k * y0))
    else
        tmp = b * ((t * j) * 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 (t <= -6e+17) {
		tmp = c * (z * (t * i));
	} else if (t <= -3.95e-252) {
		tmp = b * (k * (z * y0));
	} else if (t <= 3.6e-276) {
		tmp = a * ((x * y) * b);
	} else if (t <= 0.047) {
		tmp = b * (z * (k * y0));
	} else {
		tmp = b * ((t * j) * 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 t <= -6e+17:
		tmp = c * (z * (t * i))
	elif t <= -3.95e-252:
		tmp = b * (k * (z * y0))
	elif t <= 3.6e-276:
		tmp = a * ((x * y) * b)
	elif t <= 0.047:
		tmp = b * (z * (k * y0))
	else:
		tmp = b * ((t * j) * 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 (t <= -6e+17)
		tmp = Float64(c * Float64(z * Float64(t * i)));
	elseif (t <= -3.95e-252)
		tmp = Float64(b * Float64(k * Float64(z * y0)));
	elseif (t <= 3.6e-276)
		tmp = Float64(a * Float64(Float64(x * y) * b));
	elseif (t <= 0.047)
		tmp = Float64(b * Float64(z * Float64(k * y0)));
	else
		tmp = Float64(b * Float64(Float64(t * j) * 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 (t <= -6e+17)
		tmp = c * (z * (t * i));
	elseif (t <= -3.95e-252)
		tmp = b * (k * (z * y0));
	elseif (t <= 3.6e-276)
		tmp = a * ((x * y) * b);
	elseif (t <= 0.047)
		tmp = b * (z * (k * y0));
	else
		tmp = b * ((t * j) * 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[t, -6e+17], N[(c * N[(z * N[(t * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -3.95e-252], N[(b * N[(k * N[(z * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 3.6e-276], N[(a * N[(N[(x * y), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 0.047], N[(b * N[(z * N[(k * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * N[(N[(t * j), $MachinePrecision] * y4), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

1. Split input into 5 regimes

2. if t < -6e17

   1. Initial program 23.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in c around inf 41.5%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   4. Taylor expanded in z around inf 43.6%

      \[\leadsto \color{blue}{c \cdot \left(z \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)\right)} \]
   5. Step-by-step derivation

      1. +-commutative 43.6%

         \[\leadsto c \cdot \left(z \cdot \color{blue}{\left(i \cdot t + -1 \cdot \left(y0 \cdot y3\right)\right)}\right) \]

      2. mul-1-neg 43.6%

         \[\leadsto c \cdot \left(z \cdot \left(i \cdot t + \color{blue}{\left(-y0 \cdot y3\right)}\right)\right) \]

      3. unsub-neg 43.6%

         \[\leadsto c \cdot \left(z \cdot \color{blue}{\left(i \cdot t - y0 \cdot y3\right)}\right) \]

      4. *-commutative 43.6%

         \[\leadsto c \cdot \left(z \cdot \left(\color{blue}{t \cdot i} - y0 \cdot y3\right)\right) \]

   6. Simplified 43.6%

      \[\leadsto \color{blue}{c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)} \]

   7. Taylor expanded in t around inf 37.5%

      \[\leadsto c \cdot \left(z \cdot \color{blue}{\left(i \cdot t\right)}\right) \]

   if -6e17 < t < -3.95000000000000007e-252

   1. Initial program 25.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 23.2%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around 0 25.5%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 25.5%

         \[\leadsto b \cdot \left(y4 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. *-commutative 25.5%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - \color{blue}{y \cdot k}\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. *-commutative 25.5%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(\color{blue}{x \cdot j} - k \cdot z\right)\right) \]

      4. *-commutative 25.5%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - \color{blue}{z \cdot k}\right)\right) \]

   6. Simplified 25.5%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - z \cdot k\right)\right)} \]

   7. Taylor expanded in z around inf 25.3%

      \[\leadsto b \cdot \color{blue}{\left(k \cdot \left(y0 \cdot z\right)\right)} \]
   8. Step-by-step derivation

      1. *-commutative 25.3%

         \[\leadsto b \cdot \color{blue}{\left(\left(y0 \cdot z\right) \cdot k\right)} \]

      2. *-commutative 25.3%

         \[\leadsto b \cdot \left(\color{blue}{\left(z \cdot y0\right)} \cdot k\right) \]

   9. Simplified 25.3%

      \[\leadsto b \cdot \color{blue}{\left(\left(z \cdot y0\right) \cdot k\right)} \]

   if -3.95000000000000007e-252 < t < 3.59999999999999994e-276

   1. Initial program 43.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 40.1%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in a around inf 23.6%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(b \cdot x - y3 \cdot y5\right)\right)} \]

   5. Taylor expanded in b around inf 27.7%

      \[\leadsto a \cdot \color{blue}{\left(b \cdot \left(x \cdot y\right)\right)} \]
   6. Step-by-step derivation

      1. *-commutative 27.7%

         \[\leadsto a \cdot \color{blue}{\left(\left(x \cdot y\right) \cdot b\right)} \]

   7. Simplified 27.7%

      \[\leadsto a \cdot \color{blue}{\left(\left(x \cdot y\right) \cdot b\right)} \]

   if 3.59999999999999994e-276 < t < 0.047

   1. Initial program 37.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 26.5%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around 0 32.2%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 32.2%

         \[\leadsto b \cdot \left(y4 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. *-commutative 32.2%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - \color{blue}{y \cdot k}\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. *-commutative 32.2%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(\color{blue}{x \cdot j} - k \cdot z\right)\right) \]

      4. *-commutative 32.2%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - \color{blue}{z \cdot k}\right)\right) \]

   6. Simplified 32.2%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - z \cdot k\right)\right)} \]

   7. Taylor expanded in z around inf 31.8%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]
   8. Step-by-step derivation

      1. associate-*r* 33.8%

         \[\leadsto b \cdot \color{blue}{\left(\left(k \cdot y0\right) \cdot z\right)} \]

   9. Simplified 33.8%

      \[\leadsto \color{blue}{b \cdot \left(\left(k \cdot y0\right) \cdot z\right)} \]

   if 0.047 < t

   1. Initial program 35.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 38.4%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around 0 34.0%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 34.0%

         \[\leadsto b \cdot \left(y4 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. *-commutative 34.0%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - \color{blue}{y \cdot k}\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. *-commutative 34.0%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(\color{blue}{x \cdot j} - k \cdot z\right)\right) \]

      4. *-commutative 34.0%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - \color{blue}{z \cdot k}\right)\right) \]

   6. Simplified 34.0%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - z \cdot k\right)\right)} \]

   7. Taylor expanded in t around inf 30.9%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]
   8. Step-by-step derivation

      1. associate-*r* 32.5%

         \[\leadsto b \cdot \color{blue}{\left(\left(j \cdot t\right) \cdot y4\right)} \]

      2. *-commutative 32.5%

         \[\leadsto b \cdot \left(\color{blue}{\left(t \cdot j\right)} \cdot y4\right) \]

   9. Simplified 32.5%

      \[\leadsto \color{blue}{b \cdot \left(\left(t \cdot j\right) \cdot y4\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 32.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -6 \cdot 10^{+17}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i\right)\right)\\ \mathbf{elif}\;t \leq -3.95 \cdot 10^{-252}:\\ \;\;\;\;b \cdot \left(k \cdot \left(z \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 3.6 \cdot 10^{-276}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{elif}\;t \leq 0.047:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(\left(t \cdot j\right) \cdot y4\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 28: 22.6% accurate, 4.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(z \cdot \left(k \cdot y0\right)\right)\\ \mathbf{if}\;y0 \leq -3.1 \cdot 10^{+72}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;y0 \leq 2.1 \cdot 10^{-180}:\\ \;\;\;\;a \cdot \left(y \cdot \left(x \cdot b\right)\right)\\ \mathbf{elif}\;y0 \leq 1.3 \cdot 10^{+34}:\\ \;\;\;\;b \cdot \left(\left(t \cdot j\right) \cdot y4\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* z (* k y0)))))
   (if (<= y0 -3.1e+72)
     t_1
     (if (<= y0 2.1e-180)
       (* a (* y (* x b)))
       (if (<= y0 1.3e+34) (* b (* (* t j) y4)) t_1)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (z * (k * y0));
	double tmp;
	if (y0 <= -3.1e+72) {
		tmp = t_1;
	} else if (y0 <= 2.1e-180) {
		tmp = a * (y * (x * b));
	} else if (y0 <= 1.3e+34) {
		tmp = b * ((t * j) * y4);
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = b * (z * (k * y0))
    if (y0 <= (-3.1d+72)) then
        tmp = t_1
    else if (y0 <= 2.1d-180) then
        tmp = a * (y * (x * b))
    else if (y0 <= 1.3d+34) then
        tmp = b * ((t * j) * y4)
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (z * (k * y0));
	double tmp;
	if (y0 <= -3.1e+72) {
		tmp = t_1;
	} else if (y0 <= 2.1e-180) {
		tmp = a * (y * (x * b));
	} else if (y0 <= 1.3e+34) {
		tmp = b * ((t * j) * y4);
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = b * (z * (k * y0))
	tmp = 0
	if y0 <= -3.1e+72:
		tmp = t_1
	elif y0 <= 2.1e-180:
		tmp = a * (y * (x * b))
	elif y0 <= 1.3e+34:
		tmp = b * ((t * j) * y4)
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(b * Float64(z * Float64(k * y0)))
	tmp = 0.0
	if (y0 <= -3.1e+72)
		tmp = t_1;
	elseif (y0 <= 2.1e-180)
		tmp = Float64(a * Float64(y * Float64(x * b)));
	elseif (y0 <= 1.3e+34)
		tmp = Float64(b * Float64(Float64(t * j) * y4));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = b * (z * (k * y0));
	tmp = 0.0;
	if (y0 <= -3.1e+72)
		tmp = t_1;
	elseif (y0 <= 2.1e-180)
		tmp = a * (y * (x * b));
	elseif (y0 <= 1.3e+34)
		tmp = b * ((t * j) * y4);
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(b * N[(z * N[(k * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y0, -3.1e+72], t$95$1, If[LessEqual[y0, 2.1e-180], N[(a * N[(y * N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 1.3e+34], N[(b * N[(N[(t * j), $MachinePrecision] * y4), $MachinePrecision]), $MachinePrecision], t$95$1]]]]

Derivation

1. Split input into 3 regimes

2. if y0 < -3.09999999999999988e72 or 1.29999999999999999e34 < y0

   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. Add Preprocessing

   3. Taylor expanded in b around inf 32.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around 0 38.0%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 38.0%

         \[\leadsto b \cdot \left(y4 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. *-commutative 38.0%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - \color{blue}{y \cdot k}\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. *-commutative 38.0%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(\color{blue}{x \cdot j} - k \cdot z\right)\right) \]

      4. *-commutative 38.0%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - \color{blue}{z \cdot k}\right)\right) \]

   6. Simplified 38.0%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - z \cdot k\right)\right)} \]

   7. Taylor expanded in z around inf 32.9%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]
   8. Step-by-step derivation

      1. associate-*r* 32.1%

         \[\leadsto b \cdot \color{blue}{\left(\left(k \cdot y0\right) \cdot z\right)} \]

   9. Simplified 32.1%

      \[\leadsto \color{blue}{b \cdot \left(\left(k \cdot y0\right) \cdot z\right)} \]

   if -3.09999999999999988e72 < y0 < 2.0999999999999999e-180

   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. Add Preprocessing

   3. Taylor expanded in y around inf 35.4%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in a around inf 28.5%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(b \cdot x - y3 \cdot y5\right)\right)} \]

   5. Taylor expanded in b around inf 20.6%

      \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x\right)}\right) \]
   6. Step-by-step derivation

      1. *-commutative 20.6%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(x \cdot b\right)}\right) \]

   7. Simplified 20.6%

      \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(x \cdot b\right)}\right) \]

   if 2.0999999999999999e-180 < y0 < 1.29999999999999999e34

   1. Initial program 41.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 37.7%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around 0 34.1%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 34.1%

         \[\leadsto b \cdot \left(y4 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. *-commutative 34.1%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - \color{blue}{y \cdot k}\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. *-commutative 34.1%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(\color{blue}{x \cdot j} - k \cdot z\right)\right) \]

      4. *-commutative 34.1%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - \color{blue}{z \cdot k}\right)\right) \]

   6. Simplified 34.1%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - z \cdot k\right)\right)} \]

   7. Taylor expanded in t around inf 25.3%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]
   8. Step-by-step derivation

      1. associate-*r* 25.3%

         \[\leadsto b \cdot \color{blue}{\left(\left(j \cdot t\right) \cdot y4\right)} \]

      2. *-commutative 25.3%

         \[\leadsto b \cdot \left(\color{blue}{\left(t \cdot j\right)} \cdot y4\right) \]

   9. Simplified 25.3%

      \[\leadsto \color{blue}{b \cdot \left(\left(t \cdot j\right) \cdot y4\right)} \]
3. Recombined 3 regimes into one program.

4. Final simplification 25.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y0 \leq -3.1 \cdot 10^{+72}:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0\right)\right)\\ \mathbf{elif}\;y0 \leq 2.1 \cdot 10^{-180}:\\ \;\;\;\;a \cdot \left(y \cdot \left(x \cdot b\right)\right)\\ \mathbf{elif}\;y0 \leq 1.3 \cdot 10^{+34}:\\ \;\;\;\;b \cdot \left(\left(t \cdot j\right) \cdot y4\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 29: 22.3% accurate, 4.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(z \cdot \left(k \cdot y0\right)\right)\\ \mathbf{if}\;y0 \leq -4.2 \cdot 10^{+73}:\\ \;\;\;\;t\_1\\ \mathbf{elif}\;y0 \leq 1.6 \cdot 10^{-179}:\\ \;\;\;\;a \cdot \left(y \cdot \left(x \cdot b\right)\right)\\ \mathbf{elif}\;y0 \leq 1.1 \cdot 10^{+91}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t\_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* z (* k y0)))))
   (if (<= y0 -4.2e+73)
     t_1
     (if (<= y0 1.6e-179)
       (* a (* y (* x b)))
       (if (<= y0 1.1e+91) (* b (* j (* t y4))) t_1)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (z * (k * y0));
	double tmp;
	if (y0 <= -4.2e+73) {
		tmp = t_1;
	} else if (y0 <= 1.6e-179) {
		tmp = a * (y * (x * b));
	} else if (y0 <= 1.1e+91) {
		tmp = b * (j * (t * y4));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = b * (z * (k * y0))
    if (y0 <= (-4.2d+73)) then
        tmp = t_1
    else if (y0 <= 1.6d-179) then
        tmp = a * (y * (x * b))
    else if (y0 <= 1.1d+91) then
        tmp = b * (j * (t * y4))
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (z * (k * y0));
	double tmp;
	if (y0 <= -4.2e+73) {
		tmp = t_1;
	} else if (y0 <= 1.6e-179) {
		tmp = a * (y * (x * b));
	} else if (y0 <= 1.1e+91) {
		tmp = b * (j * (t * y4));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = b * (z * (k * y0))
	tmp = 0
	if y0 <= -4.2e+73:
		tmp = t_1
	elif y0 <= 1.6e-179:
		tmp = a * (y * (x * b))
	elif y0 <= 1.1e+91:
		tmp = b * (j * (t * y4))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(b * Float64(z * Float64(k * y0)))
	tmp = 0.0
	if (y0 <= -4.2e+73)
		tmp = t_1;
	elseif (y0 <= 1.6e-179)
		tmp = Float64(a * Float64(y * Float64(x * b)));
	elseif (y0 <= 1.1e+91)
		tmp = Float64(b * Float64(j * Float64(t * y4)));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = b * (z * (k * y0));
	tmp = 0.0;
	if (y0 <= -4.2e+73)
		tmp = t_1;
	elseif (y0 <= 1.6e-179)
		tmp = a * (y * (x * b));
	elseif (y0 <= 1.1e+91)
		tmp = b * (j * (t * y4));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(b * N[(z * N[(k * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y0, -4.2e+73], t$95$1, If[LessEqual[y0, 1.6e-179], N[(a * N[(y * N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 1.1e+91], N[(b * N[(j * N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]

Derivation

1. Split input into 3 regimes

2. if y0 < -4.2000000000000003e73 or 1.1e91 < y0

   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. Add Preprocessing

   3. Taylor expanded in b around inf 32.1%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around 0 39.9%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 39.9%

         \[\leadsto b \cdot \left(y4 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. *-commutative 39.9%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - \color{blue}{y \cdot k}\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. *-commutative 39.9%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(\color{blue}{x \cdot j} - k \cdot z\right)\right) \]

      4. *-commutative 39.9%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - \color{blue}{z \cdot k}\right)\right) \]

   6. Simplified 39.9%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - z \cdot k\right)\right)} \]

   7. Taylor expanded in z around inf 34.2%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]
   8. Step-by-step derivation

      1. associate-*r* 34.3%

         \[\leadsto b \cdot \color{blue}{\left(\left(k \cdot y0\right) \cdot z\right)} \]

   9. Simplified 34.3%

      \[\leadsto \color{blue}{b \cdot \left(\left(k \cdot y0\right) \cdot z\right)} \]

   if -4.2000000000000003e73 < y0 < 1.6e-179

   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. Add Preprocessing

   3. Taylor expanded in y around inf 35.4%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in a around inf 28.5%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(b \cdot x - y3 \cdot y5\right)\right)} \]

   5. Taylor expanded in b around inf 20.6%

      \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x\right)}\right) \]
   6. Step-by-step derivation

      1. *-commutative 20.6%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(x \cdot b\right)}\right) \]

   7. Simplified 20.6%

      \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(x \cdot b\right)}\right) \]

   if 1.6e-179 < y0 < 1.1e91

   1. Initial program 43.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 36.5%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around 0 31.8%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 31.8%

         \[\leadsto b \cdot \left(y4 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. *-commutative 31.8%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - \color{blue}{y \cdot k}\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. *-commutative 31.8%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(\color{blue}{x \cdot j} - k \cdot z\right)\right) \]

      4. *-commutative 31.8%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - \color{blue}{z \cdot k}\right)\right) \]

   6. Simplified 31.8%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - z \cdot k\right)\right)} \]

   7. Taylor expanded in t around inf 24.6%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]
   8. Step-by-step derivation

      1. *-commutative 24.6%

         \[\leadsto b \cdot \color{blue}{\left(\left(t \cdot y4\right) \cdot j\right)} \]

   9. Simplified 24.6%

      \[\leadsto \color{blue}{b \cdot \left(\left(t \cdot y4\right) \cdot j\right)} \]
3. Recombined 3 regimes into one program.

4. Final simplification 26.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y0 \leq -4.2 \cdot 10^{+73}:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0\right)\right)\\ \mathbf{elif}\;y0 \leq 1.6 \cdot 10^{-179}:\\ \;\;\;\;a \cdot \left(y \cdot \left(x \cdot b\right)\right)\\ \mathbf{elif}\;y0 \leq 1.1 \cdot 10^{+91}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 30: 22.3% accurate, 5.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y0 \leq -9.2 \cdot 10^{+70} \lor \neg \left(y0 \leq 4.7 \cdot 10^{+90}\right):\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(y \cdot \left(x \cdot b\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (or (<= y0 -9.2e+70) (not (<= y0 4.7e+90)))
   (* b (* z (* k y0)))
   (* 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) {
	double tmp;
	if ((y0 <= -9.2e+70) || !(y0 <= 4.7e+90)) {
		tmp = b * (z * (k * y0));
	} else {
		tmp = a * (y * (x * 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 ((y0 <= (-9.2d+70)) .or. (.not. (y0 <= 4.7d+90))) then
        tmp = b * (z * (k * y0))
    else
        tmp = a * (y * (x * 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 ((y0 <= -9.2e+70) || !(y0 <= 4.7e+90)) {
		tmp = b * (z * (k * y0));
	} else {
		tmp = a * (y * (x * 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 (y0 <= -9.2e+70) or not (y0 <= 4.7e+90):
		tmp = b * (z * (k * y0))
	else:
		tmp = a * (y * (x * 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 ((y0 <= -9.2e+70) || !(y0 <= 4.7e+90))
		tmp = Float64(b * Float64(z * Float64(k * y0)));
	else
		tmp = Float64(a * Float64(y * Float64(x * 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 ((y0 <= -9.2e+70) || ~((y0 <= 4.7e+90)))
		tmp = b * (z * (k * y0));
	else
		tmp = a * (y * (x * 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[y0, -9.2e+70], N[Not[LessEqual[y0, 4.7e+90]], $MachinePrecision]], N[(b * N[(z * N[(k * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(a * N[(y * N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if y0 < -9.19999999999999975e70 or 4.7000000000000001e90 < y0

   1. Initial program 26.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in b around inf 32.9%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   4. Taylor expanded in a around 0 40.5%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(j \cdot t - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]
   5. Step-by-step derivation

      1. *-commutative 40.5%

         \[\leadsto b \cdot \left(y4 \cdot \left(\color{blue}{t \cdot j} - k \cdot y\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      2. *-commutative 40.5%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - \color{blue}{y \cdot k}\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right) \]

      3. *-commutative 40.5%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(\color{blue}{x \cdot j} - k \cdot z\right)\right) \]

      4. *-commutative 40.5%

         \[\leadsto b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - \color{blue}{z \cdot k}\right)\right) \]

   6. Simplified 40.5%

      \[\leadsto \color{blue}{b \cdot \left(y4 \cdot \left(t \cdot j - y \cdot k\right) - y0 \cdot \left(x \cdot j - z \cdot k\right)\right)} \]

   7. Taylor expanded in z around inf 33.8%

      \[\leadsto \color{blue}{b \cdot \left(k \cdot \left(y0 \cdot z\right)\right)} \]
   8. Step-by-step derivation

      1. associate-*r* 33.9%

         \[\leadsto b \cdot \color{blue}{\left(\left(k \cdot y0\right) \cdot z\right)} \]

   9. Simplified 33.9%

      \[\leadsto \color{blue}{b \cdot \left(\left(k \cdot y0\right) \cdot z\right)} \]

   if -9.19999999999999975e70 < y0 < 4.7000000000000001e90

   1. Initial program 34.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]
   2. Add Preprocessing

   3. Taylor expanded in y around inf 32.3%

      \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   4. Taylor expanded in a around inf 23.1%

      \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(b \cdot x - y3 \cdot y5\right)\right)} \]

   5. Taylor expanded in b around inf 17.9%

      \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x\right)}\right) \]
   6. Step-by-step derivation

      1. *-commutative 17.9%

         \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(x \cdot b\right)}\right) \]

   7. Simplified 17.9%

      \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(x \cdot b\right)}\right) \]
3. Recombined 2 regimes into one program.

4. Final simplification 23.6%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y0 \leq -9.2 \cdot 10^{+70} \lor \neg \left(y0 \leq 4.7 \cdot 10^{+90}\right):\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(y \cdot \left(x \cdot b\right)\right)\\ \end{array} \]
5. Add Preprocessing

Alternative 31: 17.0% 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 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. Add Preprocessing

3. Taylor expanded in y around inf 30.9%

   \[\leadsto \color{blue}{y \cdot \left(\left(-1 \cdot \left(k \cdot \left(b \cdot y4 - i \cdot y5\right)\right) + x \cdot \left(a \cdot b - c \cdot i\right)\right) - -1 \cdot \left(y3 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

4. Taylor expanded in a around inf 21.6%

   \[\leadsto \color{blue}{a \cdot \left(y \cdot \left(b \cdot x - y3 \cdot y5\right)\right)} \]

5. Taylor expanded in b around inf 14.8%

   \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(b \cdot x\right)}\right) \]
6. Step-by-step derivation

   1. *-commutative 14.8%

      \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(x \cdot b\right)}\right) \]

7. Simplified 14.8%

   \[\leadsto a \cdot \left(y \cdot \color{blue}{\left(x \cdot b\right)}\right) \]

8. Final simplification 14.8%

   \[\leadsto a \cdot \left(y \cdot \left(x \cdot b\right)\right) \]
9. Add Preprocessing

Developer target: 28.1% accurate, 0.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y4 \cdot c - y5 \cdot a\\ t_2 := x \cdot y2 - z \cdot y3\\ t_3 := y2 \cdot t - y3 \cdot y\\ t_4 := k \cdot y2 - j \cdot y3\\ t_5 := y4 \cdot b - y5 \cdot i\\ t_6 := \left(j \cdot t - k \cdot y\right) \cdot t\_5\\ t_7 := b \cdot a - i \cdot c\\ t_8 := t\_7 \cdot \left(y \cdot x - t \cdot z\right)\\ t_9 := j \cdot x - k \cdot z\\ t_10 := \left(b \cdot y0 - i \cdot y1\right) \cdot t\_9\\ t_11 := t\_9 \cdot \left(y0 \cdot b - i \cdot y1\right)\\ t_12 := y4 \cdot y1 - y5 \cdot y0\\ t_13 := t\_4 \cdot t\_12\\ t_14 := \left(y2 \cdot k - y3 \cdot j\right) \cdot t\_12\\ t_15 := \left(\left(\left(\left(k \cdot y\right) \cdot \left(y5 \cdot i\right) - \left(y \cdot b\right) \cdot \left(y4 \cdot k\right)\right) - \left(y5 \cdot t\right) \cdot \left(i \cdot j\right)\right) - \left(t\_3 \cdot t\_1 - t\_14\right)\right) + \left(t\_8 - \left(t\_11 - \left(y2 \cdot x - y3 \cdot z\right) \cdot \left(c \cdot y0 - y1 \cdot a\right)\right)\right)\\ t_16 := \left(\left(t\_6 - \left(y3 \cdot y\right) \cdot \left(y5 \cdot a - y4 \cdot c\right)\right) + \left(\left(y5 \cdot a\right) \cdot \left(t \cdot y2\right) + t\_13\right)\right) + \left(t\_2 \cdot \left(c \cdot y0 - a \cdot y1\right) - \left(t\_10 - \left(y \cdot x - z \cdot t\right) \cdot t\_7\right)\right)\\ t_17 := t \cdot y2 - y \cdot y3\\ \mathbf{if}\;y4 < -7.206256231996481 \cdot 10^{+60}:\\ \;\;\;\;\left(t\_8 - \left(t\_11 - t\_6\right)\right) - \left(\frac{t\_3}{\frac{1}{t\_1}} - t\_14\right)\\ \mathbf{elif}\;y4 < -3.364603505246317 \cdot 10^{-66}:\\ \;\;\;\;\left(\left(\left(\left(t \cdot c\right) \cdot \left(i \cdot z\right) - \left(a \cdot t\right) \cdot \left(b \cdot z\right)\right) - \left(y \cdot c\right) \cdot \left(i \cdot x\right)\right) - t\_10\right) + \left(\left(y0 \cdot c - a \cdot y1\right) \cdot t\_2 - \left(t\_17 \cdot \left(y4 \cdot c - a \cdot y5\right) - \left(y1 \cdot y4 - y5 \cdot y0\right) \cdot t\_4\right)\right)\\ \mathbf{elif}\;y4 < -1.2000065055686116 \cdot 10^{-105}:\\ \;\;\;\;t\_16\\ \mathbf{elif}\;y4 < 6.718963124057495 \cdot 10^{-279}:\\ \;\;\;\;t\_15\\ \mathbf{elif}\;y4 < 4.77962681403792 \cdot 10^{-222}:\\ \;\;\;\;t\_16\\ \mathbf{elif}\;y4 < 2.2852241541266835 \cdot 10^{-175}:\\ \;\;\;\;t\_15\\ \mathbf{else}:\\ \;\;\;\;\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(k \cdot \left(i \cdot \left(z \cdot y1\right)\right) - \left(j \cdot \left(i \cdot \left(x \cdot y1\right)\right) + y0 \cdot \left(k \cdot \left(z \cdot b\right)\right)\right)\right)\right) + \left(z \cdot \left(y3 \cdot \left(a \cdot y1\right)\right) - \left(y2 \cdot \left(x \cdot \left(a \cdot y1\right)\right) + y0 \cdot \left(z \cdot \left(c \cdot y3\right)\right)\right)\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot t\_5\right) - t\_17 \cdot t\_1\right) + t\_13\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* y4 c) (* y5 a)))
        (t_2 (- (* x y2) (* z y3)))
        (t_3 (- (* y2 t) (* y3 y)))
        (t_4 (- (* k y2) (* j y3)))
        (t_5 (- (* y4 b) (* y5 i)))
        (t_6 (* (- (* j t) (* k y)) t_5))
        (t_7 (- (* b a) (* i c)))
        (t_8 (* t_7 (- (* y x) (* t z))))
        (t_9 (- (* j x) (* k z)))
        (t_10 (* (- (* b y0) (* i y1)) t_9))
        (t_11 (* t_9 (- (* y0 b) (* i y1))))
        (t_12 (- (* y4 y1) (* y5 y0)))
        (t_13 (* t_4 t_12))
        (t_14 (* (- (* y2 k) (* y3 j)) t_12))
        (t_15
         (+
          (-
           (-
            (- (* (* k y) (* y5 i)) (* (* y b) (* y4 k)))
            (* (* y5 t) (* i j)))
           (- (* t_3 t_1) t_14))
          (- t_8 (- t_11 (* (- (* y2 x) (* y3 z)) (- (* c y0) (* y1 a)))))))
        (t_16
         (+
          (+
           (- t_6 (* (* y3 y) (- (* y5 a) (* y4 c))))
           (+ (* (* y5 a) (* t y2)) t_13))
          (-
           (* t_2 (- (* c y0) (* a y1)))
           (- t_10 (* (- (* y x) (* z t)) t_7)))))
        (t_17 (- (* t y2) (* y y3))))
   (if (< y4 -7.206256231996481e+60)
     (- (- t_8 (- t_11 t_6)) (- (/ t_3 (/ 1.0 t_1)) t_14))
     (if (< y4 -3.364603505246317e-66)
       (+
        (-
         (- (- (* (* t c) (* i z)) (* (* a t) (* b z))) (* (* y c) (* i x)))
         t_10)
        (-
         (* (- (* y0 c) (* a y1)) t_2)
         (- (* t_17 (- (* y4 c) (* a y5))) (* (- (* y1 y4) (* y5 y0)) t_4))))
       (if (< y4 -1.2000065055686116e-105)
         t_16
         (if (< y4 6.718963124057495e-279)
           t_15
           (if (< y4 4.77962681403792e-222)
             t_16
             (if (< y4 2.2852241541266835e-175)
               t_15
               (+
                (-
                 (+
                  (+
                   (-
                    (* (- (* x y) (* z t)) (- (* a b) (* c i)))
                    (-
                     (* k (* i (* z y1)))
                     (+ (* j (* i (* x y1))) (* y0 (* k (* z b))))))
                   (-
                    (* z (* y3 (* a y1)))
                    (+ (* y2 (* x (* a y1))) (* y0 (* z (* c y3))))))
                  (* (- (* t j) (* y k)) t_5))
                 (* t_17 t_1))
                t_13)))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (y4 * c) - (y5 * a);
	double t_2 = (x * y2) - (z * y3);
	double t_3 = (y2 * t) - (y3 * y);
	double t_4 = (k * y2) - (j * y3);
	double t_5 = (y4 * b) - (y5 * i);
	double t_6 = ((j * t) - (k * y)) * t_5;
	double t_7 = (b * a) - (i * c);
	double t_8 = t_7 * ((y * x) - (t * z));
	double t_9 = (j * x) - (k * z);
	double t_10 = ((b * y0) - (i * y1)) * t_9;
	double t_11 = t_9 * ((y0 * b) - (i * y1));
	double t_12 = (y4 * y1) - (y5 * y0);
	double t_13 = t_4 * t_12;
	double t_14 = ((y2 * k) - (y3 * j)) * t_12;
	double t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))));
	double t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)));
	double t_17 = (t * y2) - (y * y3);
	double tmp;
	if (y4 < -7.206256231996481e+60) {
		tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0 / t_1)) - t_14);
	} else if (y4 < -3.364603505246317e-66) {
		tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)));
	} else if (y4 < -1.2000065055686116e-105) {
		tmp = t_16;
	} else if (y4 < 6.718963124057495e-279) {
		tmp = t_15;
	} else if (y4 < 4.77962681403792e-222) {
		tmp = t_16;
	} else if (y4 < 2.2852241541266835e-175) {
		tmp = t_15;
	} else {
		tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_10
    real(8) :: t_11
    real(8) :: t_12
    real(8) :: t_13
    real(8) :: t_14
    real(8) :: t_15
    real(8) :: t_16
    real(8) :: t_17
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: t_5
    real(8) :: t_6
    real(8) :: t_7
    real(8) :: t_8
    real(8) :: t_9
    real(8) :: tmp
    t_1 = (y4 * c) - (y5 * a)
    t_2 = (x * y2) - (z * y3)
    t_3 = (y2 * t) - (y3 * y)
    t_4 = (k * y2) - (j * y3)
    t_5 = (y4 * b) - (y5 * i)
    t_6 = ((j * t) - (k * y)) * t_5
    t_7 = (b * a) - (i * c)
    t_8 = t_7 * ((y * x) - (t * z))
    t_9 = (j * x) - (k * z)
    t_10 = ((b * y0) - (i * y1)) * t_9
    t_11 = t_9 * ((y0 * b) - (i * y1))
    t_12 = (y4 * y1) - (y5 * y0)
    t_13 = t_4 * t_12
    t_14 = ((y2 * k) - (y3 * j)) * t_12
    t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))))
    t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)))
    t_17 = (t * y2) - (y * y3)
    if (y4 < (-7.206256231996481d+60)) then
        tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0d0 / t_1)) - t_14)
    else if (y4 < (-3.364603505246317d-66)) then
        tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)))
    else if (y4 < (-1.2000065055686116d-105)) then
        tmp = t_16
    else if (y4 < 6.718963124057495d-279) then
        tmp = t_15
    else if (y4 < 4.77962681403792d-222) then
        tmp = t_16
    else if (y4 < 2.2852241541266835d-175) then
        tmp = t_15
    else
        tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (y4 * c) - (y5 * a);
	double t_2 = (x * y2) - (z * y3);
	double t_3 = (y2 * t) - (y3 * y);
	double t_4 = (k * y2) - (j * y3);
	double t_5 = (y4 * b) - (y5 * i);
	double t_6 = ((j * t) - (k * y)) * t_5;
	double t_7 = (b * a) - (i * c);
	double t_8 = t_7 * ((y * x) - (t * z));
	double t_9 = (j * x) - (k * z);
	double t_10 = ((b * y0) - (i * y1)) * t_9;
	double t_11 = t_9 * ((y0 * b) - (i * y1));
	double t_12 = (y4 * y1) - (y5 * y0);
	double t_13 = t_4 * t_12;
	double t_14 = ((y2 * k) - (y3 * j)) * t_12;
	double t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))));
	double t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)));
	double t_17 = (t * y2) - (y * y3);
	double tmp;
	if (y4 < -7.206256231996481e+60) {
		tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0 / t_1)) - t_14);
	} else if (y4 < -3.364603505246317e-66) {
		tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)));
	} else if (y4 < -1.2000065055686116e-105) {
		tmp = t_16;
	} else if (y4 < 6.718963124057495e-279) {
		tmp = t_15;
	} else if (y4 < 4.77962681403792e-222) {
		tmp = t_16;
	} else if (y4 < 2.2852241541266835e-175) {
		tmp = t_15;
	} else {
		tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (y4 * c) - (y5 * a)
	t_2 = (x * y2) - (z * y3)
	t_3 = (y2 * t) - (y3 * y)
	t_4 = (k * y2) - (j * y3)
	t_5 = (y4 * b) - (y5 * i)
	t_6 = ((j * t) - (k * y)) * t_5
	t_7 = (b * a) - (i * c)
	t_8 = t_7 * ((y * x) - (t * z))
	t_9 = (j * x) - (k * z)
	t_10 = ((b * y0) - (i * y1)) * t_9
	t_11 = t_9 * ((y0 * b) - (i * y1))
	t_12 = (y4 * y1) - (y5 * y0)
	t_13 = t_4 * t_12
	t_14 = ((y2 * k) - (y3 * j)) * t_12
	t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))))
	t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)))
	t_17 = (t * y2) - (y * y3)
	tmp = 0
	if y4 < -7.206256231996481e+60:
		tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0 / t_1)) - t_14)
	elif y4 < -3.364603505246317e-66:
		tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)))
	elif y4 < -1.2000065055686116e-105:
		tmp = t_16
	elif y4 < 6.718963124057495e-279:
		tmp = t_15
	elif y4 < 4.77962681403792e-222:
		tmp = t_16
	elif y4 < 2.2852241541266835e-175:
		tmp = t_15
	else:
		tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(y4 * c) - Float64(y5 * a))
	t_2 = Float64(Float64(x * y2) - Float64(z * y3))
	t_3 = Float64(Float64(y2 * t) - Float64(y3 * y))
	t_4 = Float64(Float64(k * y2) - Float64(j * y3))
	t_5 = Float64(Float64(y4 * b) - Float64(y5 * i))
	t_6 = Float64(Float64(Float64(j * t) - Float64(k * y)) * t_5)
	t_7 = Float64(Float64(b * a) - Float64(i * c))
	t_8 = Float64(t_7 * Float64(Float64(y * x) - Float64(t * z)))
	t_9 = Float64(Float64(j * x) - Float64(k * z))
	t_10 = Float64(Float64(Float64(b * y0) - Float64(i * y1)) * t_9)
	t_11 = Float64(t_9 * Float64(Float64(y0 * b) - Float64(i * y1)))
	t_12 = Float64(Float64(y4 * y1) - Float64(y5 * y0))
	t_13 = Float64(t_4 * t_12)
	t_14 = Float64(Float64(Float64(y2 * k) - Float64(y3 * j)) * t_12)
	t_15 = Float64(Float64(Float64(Float64(Float64(Float64(k * y) * Float64(y5 * i)) - Float64(Float64(y * b) * Float64(y4 * k))) - Float64(Float64(y5 * t) * Float64(i * j))) - Float64(Float64(t_3 * t_1) - t_14)) + Float64(t_8 - Float64(t_11 - Float64(Float64(Float64(y2 * x) - Float64(y3 * z)) * Float64(Float64(c * y0) - Float64(y1 * a))))))
	t_16 = Float64(Float64(Float64(t_6 - Float64(Float64(y3 * y) * Float64(Float64(y5 * a) - Float64(y4 * c)))) + Float64(Float64(Float64(y5 * a) * Float64(t * y2)) + t_13)) + Float64(Float64(t_2 * Float64(Float64(c * y0) - Float64(a * y1))) - Float64(t_10 - Float64(Float64(Float64(y * x) - Float64(z * t)) * t_7))))
	t_17 = Float64(Float64(t * y2) - Float64(y * y3))
	tmp = 0.0
	if (y4 < -7.206256231996481e+60)
		tmp = Float64(Float64(t_8 - Float64(t_11 - t_6)) - Float64(Float64(t_3 / Float64(1.0 / t_1)) - t_14));
	elseif (y4 < -3.364603505246317e-66)
		tmp = Float64(Float64(Float64(Float64(Float64(Float64(t * c) * Float64(i * z)) - Float64(Float64(a * t) * Float64(b * z))) - Float64(Float64(y * c) * Float64(i * x))) - t_10) + Float64(Float64(Float64(Float64(y0 * c) - Float64(a * y1)) * t_2) - Float64(Float64(t_17 * Float64(Float64(y4 * c) - Float64(a * y5))) - Float64(Float64(Float64(y1 * y4) - Float64(y5 * y0)) * t_4))));
	elseif (y4 < -1.2000065055686116e-105)
		tmp = t_16;
	elseif (y4 < 6.718963124057495e-279)
		tmp = t_15;
	elseif (y4 < 4.77962681403792e-222)
		tmp = t_16;
	elseif (y4 < 2.2852241541266835e-175)
		tmp = t_15;
	else
		tmp = Float64(Float64(Float64(Float64(Float64(Float64(Float64(Float64(x * y) - Float64(z * t)) * Float64(Float64(a * b) - Float64(c * i))) - Float64(Float64(k * Float64(i * Float64(z * y1))) - Float64(Float64(j * Float64(i * Float64(x * y1))) + Float64(y0 * Float64(k * Float64(z * b)))))) + Float64(Float64(z * Float64(y3 * Float64(a * y1))) - Float64(Float64(y2 * Float64(x * Float64(a * y1))) + Float64(y0 * Float64(z * Float64(c * y3)))))) + Float64(Float64(Float64(t * j) - Float64(y * k)) * t_5)) - Float64(t_17 * t_1)) + t_13);
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = (y4 * c) - (y5 * a);
	t_2 = (x * y2) - (z * y3);
	t_3 = (y2 * t) - (y3 * y);
	t_4 = (k * y2) - (j * y3);
	t_5 = (y4 * b) - (y5 * i);
	t_6 = ((j * t) - (k * y)) * t_5;
	t_7 = (b * a) - (i * c);
	t_8 = t_7 * ((y * x) - (t * z));
	t_9 = (j * x) - (k * z);
	t_10 = ((b * y0) - (i * y1)) * t_9;
	t_11 = t_9 * ((y0 * b) - (i * y1));
	t_12 = (y4 * y1) - (y5 * y0);
	t_13 = t_4 * t_12;
	t_14 = ((y2 * k) - (y3 * j)) * t_12;
	t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))));
	t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)));
	t_17 = (t * y2) - (y * y3);
	tmp = 0.0;
	if (y4 < -7.206256231996481e+60)
		tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0 / t_1)) - t_14);
	elseif (y4 < -3.364603505246317e-66)
		tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)));
	elseif (y4 < -1.2000065055686116e-105)
		tmp = t_16;
	elseif (y4 < 6.718963124057495e-279)
		tmp = t_15;
	elseif (y4 < 4.77962681403792e-222)
		tmp = t_16;
	elseif (y4 < 2.2852241541266835e-175)
		tmp = t_15;
	else
		tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(y4 * c), $MachinePrecision] - N[(y5 * a), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(y2 * t), $MachinePrecision] - N[(y3 * y), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(N[(y4 * b), $MachinePrecision] - N[(y5 * i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$6 = N[(N[(N[(j * t), $MachinePrecision] - N[(k * y), $MachinePrecision]), $MachinePrecision] * t$95$5), $MachinePrecision]}, Block[{t$95$7 = N[(N[(b * a), $MachinePrecision] - N[(i * c), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$8 = N[(t$95$7 * N[(N[(y * x), $MachinePrecision] - N[(t * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$9 = N[(N[(j * x), $MachinePrecision] - N[(k * z), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$10 = N[(N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision] * t$95$9), $MachinePrecision]}, Block[{t$95$11 = N[(t$95$9 * N[(N[(y0 * b), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$12 = N[(N[(y4 * y1), $MachinePrecision] - N[(y5 * y0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$13 = N[(t$95$4 * t$95$12), $MachinePrecision]}, Block[{t$95$14 = N[(N[(N[(y2 * k), $MachinePrecision] - N[(y3 * j), $MachinePrecision]), $MachinePrecision] * t$95$12), $MachinePrecision]}, Block[{t$95$15 = N[(N[(N[(N[(N[(N[(k * y), $MachinePrecision] * N[(y5 * i), $MachinePrecision]), $MachinePrecision] - N[(N[(y * b), $MachinePrecision] * N[(y4 * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(y5 * t), $MachinePrecision] * N[(i * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(t$95$3 * t$95$1), $MachinePrecision] - t$95$14), $MachinePrecision]), $MachinePrecision] + N[(t$95$8 - N[(t$95$11 - N[(N[(N[(y2 * x), $MachinePrecision] - N[(y3 * z), $MachinePrecision]), $MachinePrecision] * N[(N[(c * y0), $MachinePrecision] - N[(y1 * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$16 = N[(N[(N[(t$95$6 - N[(N[(y3 * y), $MachinePrecision] * N[(N[(y5 * a), $MachinePrecision] - N[(y4 * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(y5 * a), $MachinePrecision] * N[(t * y2), $MachinePrecision]), $MachinePrecision] + t$95$13), $MachinePrecision]), $MachinePrecision] + N[(N[(t$95$2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(t$95$10 - N[(N[(N[(y * x), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision] * t$95$7), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$17 = N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]}, If[Less[y4, -7.206256231996481e+60], N[(N[(t$95$8 - N[(t$95$11 - t$95$6), $MachinePrecision]), $MachinePrecision] - N[(N[(t$95$3 / N[(1.0 / t$95$1), $MachinePrecision]), $MachinePrecision] - t$95$14), $MachinePrecision]), $MachinePrecision], If[Less[y4, -3.364603505246317e-66], N[(N[(N[(N[(N[(N[(t * c), $MachinePrecision] * N[(i * z), $MachinePrecision]), $MachinePrecision] - N[(N[(a * t), $MachinePrecision] * N[(b * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(y * c), $MachinePrecision] * N[(i * x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$10), $MachinePrecision] + N[(N[(N[(N[(y0 * c), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision] * t$95$2), $MachinePrecision] - N[(N[(t$95$17 * N[(N[(y4 * c), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(N[(y1 * y4), $MachinePrecision] - N[(y5 * y0), $MachinePrecision]), $MachinePrecision] * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[Less[y4, -1.2000065055686116e-105], t$95$16, If[Less[y4, 6.718963124057495e-279], t$95$15, If[Less[y4, 4.77962681403792e-222], t$95$16, If[Less[y4, 2.2852241541266835e-175], t$95$15, N[(N[(N[(N[(N[(N[(N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision] * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(k * N[(i * N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(j * N[(i * N[(x * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(k * N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(z * N[(y3 * N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(y2 * N[(x * N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(z * N[(c * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision] * t$95$5), $MachinePrecision]), $MachinePrecision] - N[(t$95$17 * t$95$1), $MachinePrecision]), $MachinePrecision] + t$95$13), $MachinePrecision]]]]]]]]]]]]]]]]]]]]]]]]

Reproduce

herbie shell --seed 2024027 
(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)))))