Linear.Matrix:det44 from linear-1.19.1.3

Percentage Accurate: 29.9% → 41.3%

Time: 1.6min

Alternatives: 39

Speedup: 5.5×

• 89.1% of points produce a very large (infinite) output. You may want to add a precondition.

Specification

Math

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

FPCore

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

C

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

Fortran

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

Java

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

Python

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

Julia

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

MATLAB

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

Wolfram

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

Initial Program: 29.9% accurate, 1.0× speedup

Math

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

FPCore

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

C

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

Fortran

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

Java

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

Python

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

Julia

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

MATLAB

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

Wolfram

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

Alternative 1: 41.3% accurate, 1.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := t \cdot j - y \cdot k\\ t_2 := y1 \cdot y4 - y0 \cdot y5\\ t_3 := i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right) + \left(c \cdot \left(z \cdot t - x \cdot y\right) - y5 \cdot t_1\right)\right)\\ t_4 := j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot t_2\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ t_5 := c \cdot y0 - a \cdot y1\\ t_6 := y0 \cdot y5 - y1 \cdot y4\\ \mathbf{if}\;j \leq -1.05 \cdot 10^{+198}:\\ \;\;\;\;t_4\\ \mathbf{elif}\;j \leq -8.5 \cdot 10^{+31}:\\ \;\;\;\;y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) - \left(z \cdot t_5 - j \cdot t_6\right)\right)\\ \mathbf{elif}\;j \leq -2.15 \cdot 10^{-13}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;j \leq -4.8 \cdot 10^{-257}:\\ \;\;\;\;y4 \cdot \left(\left(b \cdot t_1 + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq -2.9 \cdot 10^{-303}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;j \leq 1.05 \cdot 10^{-283}:\\ \;\;\;\;y2 \cdot \left(\left(k \cdot t_2 + x \cdot t_5\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq 7.8 \cdot 10^{-197}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;j \leq 2.6 \cdot 10^{-158}:\\ \;\;\;\;j \cdot \left(y3 \cdot t_6\right)\\ \mathbf{elif}\;j \leq 1.12 \cdot 10^{-24}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot t_1\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;j \leq 2.2 \cdot 10^{+62}:\\ \;\;\;\;x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot t_5\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_4\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* t j) (* y k)))
        (t_2 (- (* y1 y4) (* y0 y5)))
        (t_3
         (*
          i
          (+
           (* y1 (- (* x j) (* z k)))
           (- (* c (- (* z t) (* x y))) (* y5 t_1)))))
        (t_4
         (*
          j
          (-
           (- (* t (- (* b y4) (* i y5))) (* y3 t_2))
           (* x (- (* b y0) (* i y1))))))
        (t_5 (- (* c y0) (* a y1)))
        (t_6 (- (* y0 y5) (* y1 y4))))
   (if (<= j -1.05e+198)
     t_4
     (if (<= j -8.5e+31)
       (* y3 (- (* y (- (* c y4) (* a y5))) (- (* z t_5) (* j t_6))))
       (if (<= j -2.15e-13)
         t_3
         (if (<= j -4.8e-257)
           (*
            y4
            (+
             (+ (* b t_1) (* y1 (- (* k y2) (* j y3))))
             (* c (- (* y y3) (* t y2)))))
           (if (<= j -2.9e-303)
             t_3
             (if (<= j 1.05e-283)
               (* y2 (+ (+ (* k t_2) (* x t_5)) (* t (- (* a y5) (* c y4)))))
               (if (<= j 7.8e-197)
                 t_3
                 (if (<= j 2.6e-158)
                   (* j (* y3 t_6))
                   (if (<= j 1.12e-24)
                     (*
                      b
                      (+
                       (+ (* a (- (* x y) (* z t))) (* y4 t_1))
                       (* y0 (- (* z k) (* x j)))))
                     (if (<= j 2.2e+62)
                       (*
                        x
                        (+
                         (+ (* y (- (* a b) (* c i))) (* y2 t_5))
                         (* j (- (* i y1) (* b y0)))))
                       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 = (t * j) - (y * k);
	double t_2 = (y1 * y4) - (y0 * y5);
	double t_3 = i * ((y1 * ((x * j) - (z * k))) + ((c * ((z * t) - (x * y))) - (y5 * t_1)));
	double t_4 = j * (((t * ((b * y4) - (i * y5))) - (y3 * t_2)) - (x * ((b * y0) - (i * y1))));
	double t_5 = (c * y0) - (a * y1);
	double t_6 = (y0 * y5) - (y1 * y4);
	double tmp;
	if (j <= -1.05e+198) {
		tmp = t_4;
	} else if (j <= -8.5e+31) {
		tmp = y3 * ((y * ((c * y4) - (a * y5))) - ((z * t_5) - (j * t_6)));
	} else if (j <= -2.15e-13) {
		tmp = t_3;
	} else if (j <= -4.8e-257) {
		tmp = y4 * (((b * t_1) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	} else if (j <= -2.9e-303) {
		tmp = t_3;
	} else if (j <= 1.05e-283) {
		tmp = y2 * (((k * t_2) + (x * t_5)) + (t * ((a * y5) - (c * y4))));
	} else if (j <= 7.8e-197) {
		tmp = t_3;
	} else if (j <= 2.6e-158) {
		tmp = j * (y3 * t_6);
	} else if (j <= 1.12e-24) {
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * t_1)) + (y0 * ((z * k) - (x * j))));
	} else if (j <= 2.2e+62) {
		tmp = x * (((y * ((a * b) - (c * i))) + (y2 * t_5)) + (j * ((i * y1) - (b * y0))));
	} 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 = (t * j) - (y * k)
    t_2 = (y1 * y4) - (y0 * y5)
    t_3 = i * ((y1 * ((x * j) - (z * k))) + ((c * ((z * t) - (x * y))) - (y5 * t_1)))
    t_4 = j * (((t * ((b * y4) - (i * y5))) - (y3 * t_2)) - (x * ((b * y0) - (i * y1))))
    t_5 = (c * y0) - (a * y1)
    t_6 = (y0 * y5) - (y1 * y4)
    if (j <= (-1.05d+198)) then
        tmp = t_4
    else if (j <= (-8.5d+31)) then
        tmp = y3 * ((y * ((c * y4) - (a * y5))) - ((z * t_5) - (j * t_6)))
    else if (j <= (-2.15d-13)) then
        tmp = t_3
    else if (j <= (-4.8d-257)) then
        tmp = y4 * (((b * t_1) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))))
    else if (j <= (-2.9d-303)) then
        tmp = t_3
    else if (j <= 1.05d-283) then
        tmp = y2 * (((k * t_2) + (x * t_5)) + (t * ((a * y5) - (c * y4))))
    else if (j <= 7.8d-197) then
        tmp = t_3
    else if (j <= 2.6d-158) then
        tmp = j * (y3 * t_6)
    else if (j <= 1.12d-24) then
        tmp = b * (((a * ((x * y) - (z * t))) + (y4 * t_1)) + (y0 * ((z * k) - (x * j))))
    else if (j <= 2.2d+62) then
        tmp = x * (((y * ((a * b) - (c * i))) + (y2 * t_5)) + (j * ((i * y1) - (b * y0))))
    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 = (t * j) - (y * k);
	double t_2 = (y1 * y4) - (y0 * y5);
	double t_3 = i * ((y1 * ((x * j) - (z * k))) + ((c * ((z * t) - (x * y))) - (y5 * t_1)));
	double t_4 = j * (((t * ((b * y4) - (i * y5))) - (y3 * t_2)) - (x * ((b * y0) - (i * y1))));
	double t_5 = (c * y0) - (a * y1);
	double t_6 = (y0 * y5) - (y1 * y4);
	double tmp;
	if (j <= -1.05e+198) {
		tmp = t_4;
	} else if (j <= -8.5e+31) {
		tmp = y3 * ((y * ((c * y4) - (a * y5))) - ((z * t_5) - (j * t_6)));
	} else if (j <= -2.15e-13) {
		tmp = t_3;
	} else if (j <= -4.8e-257) {
		tmp = y4 * (((b * t_1) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	} else if (j <= -2.9e-303) {
		tmp = t_3;
	} else if (j <= 1.05e-283) {
		tmp = y2 * (((k * t_2) + (x * t_5)) + (t * ((a * y5) - (c * y4))));
	} else if (j <= 7.8e-197) {
		tmp = t_3;
	} else if (j <= 2.6e-158) {
		tmp = j * (y3 * t_6);
	} else if (j <= 1.12e-24) {
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * t_1)) + (y0 * ((z * k) - (x * j))));
	} else if (j <= 2.2e+62) {
		tmp = x * (((y * ((a * b) - (c * i))) + (y2 * t_5)) + (j * ((i * y1) - (b * y0))));
	} 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 = (t * j) - (y * k)
	t_2 = (y1 * y4) - (y0 * y5)
	t_3 = i * ((y1 * ((x * j) - (z * k))) + ((c * ((z * t) - (x * y))) - (y5 * t_1)))
	t_4 = j * (((t * ((b * y4) - (i * y5))) - (y3 * t_2)) - (x * ((b * y0) - (i * y1))))
	t_5 = (c * y0) - (a * y1)
	t_6 = (y0 * y5) - (y1 * y4)
	tmp = 0
	if j <= -1.05e+198:
		tmp = t_4
	elif j <= -8.5e+31:
		tmp = y3 * ((y * ((c * y4) - (a * y5))) - ((z * t_5) - (j * t_6)))
	elif j <= -2.15e-13:
		tmp = t_3
	elif j <= -4.8e-257:
		tmp = y4 * (((b * t_1) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))))
	elif j <= -2.9e-303:
		tmp = t_3
	elif j <= 1.05e-283:
		tmp = y2 * (((k * t_2) + (x * t_5)) + (t * ((a * y5) - (c * y4))))
	elif j <= 7.8e-197:
		tmp = t_3
	elif j <= 2.6e-158:
		tmp = j * (y3 * t_6)
	elif j <= 1.12e-24:
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * t_1)) + (y0 * ((z * k) - (x * j))))
	elif j <= 2.2e+62:
		tmp = x * (((y * ((a * b) - (c * i))) + (y2 * t_5)) + (j * ((i * y1) - (b * y0))))
	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(t * j) - Float64(y * k))
	t_2 = Float64(Float64(y1 * y4) - Float64(y0 * y5))
	t_3 = Float64(i * Float64(Float64(y1 * Float64(Float64(x * j) - Float64(z * k))) + Float64(Float64(c * Float64(Float64(z * t) - Float64(x * y))) - Float64(y5 * t_1))))
	t_4 = Float64(j * Float64(Float64(Float64(t * Float64(Float64(b * y4) - Float64(i * y5))) - Float64(y3 * t_2)) - Float64(x * Float64(Float64(b * y0) - Float64(i * y1)))))
	t_5 = Float64(Float64(c * y0) - Float64(a * y1))
	t_6 = Float64(Float64(y0 * y5) - Float64(y1 * y4))
	tmp = 0.0
	if (j <= -1.05e+198)
		tmp = t_4;
	elseif (j <= -8.5e+31)
		tmp = Float64(y3 * Float64(Float64(y * Float64(Float64(c * y4) - Float64(a * y5))) - Float64(Float64(z * t_5) - Float64(j * t_6))));
	elseif (j <= -2.15e-13)
		tmp = t_3;
	elseif (j <= -4.8e-257)
		tmp = Float64(y4 * Float64(Float64(Float64(b * t_1) + Float64(y1 * Float64(Float64(k * y2) - Float64(j * y3)))) + Float64(c * Float64(Float64(y * y3) - Float64(t * y2)))));
	elseif (j <= -2.9e-303)
		tmp = t_3;
	elseif (j <= 1.05e-283)
		tmp = Float64(y2 * Float64(Float64(Float64(k * t_2) + Float64(x * t_5)) + Float64(t * Float64(Float64(a * y5) - Float64(c * y4)))));
	elseif (j <= 7.8e-197)
		tmp = t_3;
	elseif (j <= 2.6e-158)
		tmp = Float64(j * Float64(y3 * t_6));
	elseif (j <= 1.12e-24)
		tmp = Float64(b * Float64(Float64(Float64(a * Float64(Float64(x * y) - Float64(z * t))) + Float64(y4 * t_1)) + Float64(y0 * Float64(Float64(z * k) - Float64(x * j)))));
	elseif (j <= 2.2e+62)
		tmp = Float64(x * Float64(Float64(Float64(y * Float64(Float64(a * b) - Float64(c * i))) + Float64(y2 * t_5)) + Float64(j * Float64(Float64(i * y1) - Float64(b * y0)))));
	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 = (t * j) - (y * k);
	t_2 = (y1 * y4) - (y0 * y5);
	t_3 = i * ((y1 * ((x * j) - (z * k))) + ((c * ((z * t) - (x * y))) - (y5 * t_1)));
	t_4 = j * (((t * ((b * y4) - (i * y5))) - (y3 * t_2)) - (x * ((b * y0) - (i * y1))));
	t_5 = (c * y0) - (a * y1);
	t_6 = (y0 * y5) - (y1 * y4);
	tmp = 0.0;
	if (j <= -1.05e+198)
		tmp = t_4;
	elseif (j <= -8.5e+31)
		tmp = y3 * ((y * ((c * y4) - (a * y5))) - ((z * t_5) - (j * t_6)));
	elseif (j <= -2.15e-13)
		tmp = t_3;
	elseif (j <= -4.8e-257)
		tmp = y4 * (((b * t_1) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	elseif (j <= -2.9e-303)
		tmp = t_3;
	elseif (j <= 1.05e-283)
		tmp = y2 * (((k * t_2) + (x * t_5)) + (t * ((a * y5) - (c * y4))));
	elseif (j <= 7.8e-197)
		tmp = t_3;
	elseif (j <= 2.6e-158)
		tmp = j * (y3 * t_6);
	elseif (j <= 1.12e-24)
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * t_1)) + (y0 * ((z * k) - (x * j))));
	elseif (j <= 2.2e+62)
		tmp = x * (((y * ((a * b) - (c * i))) + (y2 * t_5)) + (j * ((i * y1) - (b * y0))));
	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[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(i * N[(N[(y1 * N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(c * N[(N[(z * t), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y5 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(j * N[(N[(N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y3 * t$95$2), $MachinePrecision]), $MachinePrecision] - N[(x * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$6 = N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -1.05e+198], t$95$4, If[LessEqual[j, -8.5e+31], N[(y3 * N[(N[(y * N[(N[(c * y4), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(z * t$95$5), $MachinePrecision] - N[(j * t$95$6), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -2.15e-13], t$95$3, If[LessEqual[j, -4.8e-257], N[(y4 * N[(N[(N[(b * t$95$1), $MachinePrecision] + N[(y1 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(c * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, -2.9e-303], t$95$3, If[LessEqual[j, 1.05e-283], N[(y2 * N[(N[(N[(k * t$95$2), $MachinePrecision] + N[(x * t$95$5), $MachinePrecision]), $MachinePrecision] + N[(t * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 7.8e-197], t$95$3, If[LessEqual[j, 2.6e-158], N[(j * N[(y3 * t$95$6), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 1.12e-24], N[(b * N[(N[(N[(a * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y4 * t$95$1), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 2.2e+62], N[(x * N[(N[(N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y2 * t$95$5), $MachinePrecision]), $MachinePrecision] + N[(j * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$4]]]]]]]]]]]]]]]]

Derivation

1. Split input into 8 regimes

2. if j < -1.05000000000000006e198 or 2.20000000000000015e62 < j

   1. Initial program 29.8%

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

   2. Taylor expanded in j around inf 67.8%

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

      1. +-commutative 67.8%

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

      2. mul-1-neg 67.8%

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

      3. unsub-neg 67.8%

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

      4. *-commutative 67.8%

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

   4. Simplified 67.8%

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

   if -1.05000000000000006e198 < j < -8.49999999999999947e31

   1. Initial program 21.7%

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

   2. Taylor expanded in y3 around -inf 57.0%

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

   if -8.49999999999999947e31 < j < -2.1499999999999999e-13 or -4.80000000000000033e-257 < j < -2.90000000000000014e-303 or 1.04999999999999999e-283 < j < 7.7999999999999998e-197

   1. Initial program 36.0%

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

   2. Taylor expanded in i around -inf 65.0%

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

   if -2.1499999999999999e-13 < j < -4.80000000000000033e-257

   1. Initial program 35.5%

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

   2. Taylor expanded in y4 around inf 53.0%

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

   if -2.90000000000000014e-303 < j < 1.04999999999999999e-283

   1. Initial program 18.2%

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

   2. Taylor expanded in y2 around inf 84.8%

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

   if 7.7999999999999998e-197 < j < 2.6e-158

   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. Taylor expanded in j around inf 50.2%

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

      1. +-commutative 50.2%

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

      2. mul-1-neg 50.2%

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

      3. unsub-neg 50.2%

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

      4. *-commutative 50.2%

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

   4. Simplified 50.2%

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

   5. Taylor expanded in y3 around inf 87.7%

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

      1. *-commutative 87.7%

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

      2. *-commutative 87.7%

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

   7. Simplified 87.7%

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

   if 2.6e-158 < j < 1.11999999999999995e-24

   1. Initial program 33.8%

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

   2. Taylor expanded in b around inf 60.8%

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

   if 1.11999999999999995e-24 < j < 2.20000000000000015e62

   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. Taylor expanded in x around inf 62.4%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
3. Recombined 8 regimes into one program.

4. Final simplification 62.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;j \leq -1.05 \cdot 10^{+198}:\\ \;\;\;\;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) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;j \leq -8.5 \cdot 10^{+31}:\\ \;\;\;\;y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) - \left(z \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\right)\\ \mathbf{elif}\;j \leq -2.15 \cdot 10^{-13}:\\ \;\;\;\;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(t \cdot j - y \cdot k\right)\right)\right)\\ \mathbf{elif}\;j \leq -4.8 \cdot 10^{-257}:\\ \;\;\;\;y4 \cdot \left(\left(b \cdot \left(t \cdot j - y \cdot k\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq -2.9 \cdot 10^{-303}:\\ \;\;\;\;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(t \cdot j - y \cdot k\right)\right)\right)\\ \mathbf{elif}\;j \leq 1.05 \cdot 10^{-283}:\\ \;\;\;\;y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq 7.8 \cdot 10^{-197}:\\ \;\;\;\;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(t \cdot j - y \cdot k\right)\right)\right)\\ \mathbf{elif}\;j \leq 2.6 \cdot 10^{-158}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;j \leq 1.12 \cdot 10^{-24}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;j \leq 2.2 \cdot 10^{+62}:\\ \;\;\;\;x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;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) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \end{array} \]

Alternative 2: 53.6% accurate, 0.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot y5 - c \cdot y4\\ t_2 := y1 \cdot y4 - y0 \cdot y5\\ t_3 := c \cdot y0 - a \cdot y1\\ t_4 := \left(\left(\left(\left(\left(a \cdot b - c \cdot i\right) \cdot \left(x \cdot y - z \cdot t\right) + \left(b \cdot y0 - i \cdot y1\right) \cdot \left(z \cdot k - x \cdot j\right)\right) + t_3 \cdot \left(x \cdot y2 - z \cdot y3\right)\right) + \left(b \cdot y4 - i \cdot y5\right) \cdot \left(t \cdot j - y \cdot k\right)\right) + \left(t \cdot y2 - y \cdot y3\right) \cdot t_1\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot t_2\\ \mathbf{if}\;t_4 \leq \infty:\\ \;\;\;\;t_4\\ \mathbf{else}:\\ \;\;\;\;y2 \cdot \left(\left(k \cdot t_2 + x \cdot t_3\right) + t \cdot t_1\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* a y5) (* c y4)))
        (t_2 (- (* y1 y4) (* y0 y5)))
        (t_3 (- (* c y0) (* a y1)))
        (t_4
         (+
          (+
           (+
            (+
             (+
              (* (- (* a b) (* c i)) (- (* x y) (* z t)))
              (* (- (* b y0) (* i y1)) (- (* z k) (* x j))))
             (* t_3 (- (* x y2) (* z y3))))
            (* (- (* b y4) (* i y5)) (- (* t j) (* y k))))
           (* (- (* t y2) (* y y3)) t_1))
          (* (- (* k y2) (* j y3)) t_2))))
   (if (<= t_4 INFINITY) t_4 (* y2 (+ (+ (* k t_2) (* x t_3)) (* t 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 = (a * y5) - (c * y4);
	double t_2 = (y1 * y4) - (y0 * y5);
	double t_3 = (c * y0) - (a * y1);
	double t_4 = (((((((a * b) - (c * i)) * ((x * y) - (z * t))) + (((b * y0) - (i * y1)) * ((z * k) - (x * j)))) + (t_3 * ((x * y2) - (z * y3)))) + (((b * y4) - (i * y5)) * ((t * j) - (y * k)))) + (((t * y2) - (y * y3)) * t_1)) + (((k * y2) - (j * y3)) * t_2);
	double tmp;
	if (t_4 <= ((double) INFINITY)) {
		tmp = t_4;
	} else {
		tmp = y2 * (((k * t_2) + (x * t_3)) + (t * t_1));
	}
	return tmp;
}

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (a * y5) - (c * y4);
	double t_2 = (y1 * y4) - (y0 * y5);
	double t_3 = (c * y0) - (a * y1);
	double t_4 = (((((((a * b) - (c * i)) * ((x * y) - (z * t))) + (((b * y0) - (i * y1)) * ((z * k) - (x * j)))) + (t_3 * ((x * y2) - (z * y3)))) + (((b * y4) - (i * y5)) * ((t * j) - (y * k)))) + (((t * y2) - (y * y3)) * t_1)) + (((k * y2) - (j * y3)) * t_2);
	double tmp;
	if (t_4 <= Double.POSITIVE_INFINITY) {
		tmp = t_4;
	} else {
		tmp = y2 * (((k * t_2) + (x * t_3)) + (t * 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 = (a * y5) - (c * y4)
	t_2 = (y1 * y4) - (y0 * y5)
	t_3 = (c * y0) - (a * y1)
	t_4 = (((((((a * b) - (c * i)) * ((x * y) - (z * t))) + (((b * y0) - (i * y1)) * ((z * k) - (x * j)))) + (t_3 * ((x * y2) - (z * y3)))) + (((b * y4) - (i * y5)) * ((t * j) - (y * k)))) + (((t * y2) - (y * y3)) * t_1)) + (((k * y2) - (j * y3)) * t_2)
	tmp = 0
	if t_4 <= math.inf:
		tmp = t_4
	else:
		tmp = y2 * (((k * t_2) + (x * t_3)) + (t * t_1))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(a * y5) - Float64(c * y4))
	t_2 = Float64(Float64(y1 * y4) - Float64(y0 * y5))
	t_3 = Float64(Float64(c * y0) - Float64(a * y1))
	t_4 = Float64(Float64(Float64(Float64(Float64(Float64(Float64(Float64(a * b) - Float64(c * i)) * Float64(Float64(x * y) - Float64(z * t))) + Float64(Float64(Float64(b * y0) - Float64(i * y1)) * Float64(Float64(z * k) - Float64(x * j)))) + Float64(t_3 * Float64(Float64(x * y2) - Float64(z * y3)))) + Float64(Float64(Float64(b * y4) - Float64(i * y5)) * Float64(Float64(t * j) - Float64(y * k)))) + Float64(Float64(Float64(t * y2) - Float64(y * y3)) * t_1)) + Float64(Float64(Float64(k * y2) - Float64(j * y3)) * t_2))
	tmp = 0.0
	if (t_4 <= Inf)
		tmp = t_4;
	else
		tmp = Float64(y2 * Float64(Float64(Float64(k * t_2) + Float64(x * t_3)) + Float64(t * 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 = (a * y5) - (c * y4);
	t_2 = (y1 * y4) - (y0 * y5);
	t_3 = (c * y0) - (a * y1);
	t_4 = (((((((a * b) - (c * i)) * ((x * y) - (z * t))) + (((b * y0) - (i * y1)) * ((z * k) - (x * j)))) + (t_3 * ((x * y2) - (z * y3)))) + (((b * y4) - (i * y5)) * ((t * j) - (y * k)))) + (((t * y2) - (y * y3)) * t_1)) + (((k * y2) - (j * y3)) * t_2);
	tmp = 0.0;
	if (t_4 <= Inf)
		tmp = t_4;
	else
		tmp = y2 * (((k * t_2) + (x * t_3)) + (t * t_1));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = 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[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision] * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(t$95$3 * N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision] * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$4, Infinity], t$95$4, N[(y2 * N[(N[(N[(k * t$95$2), $MachinePrecision] + N[(x * t$95$3), $MachinePrecision]), $MachinePrecision] + N[(t * t$95$1), $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 90.9%

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

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

   1. Initial program 0.0%

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

   2. Taylor expanded in y2 around inf 40.5%

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

4. Final simplification 56.6%

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

Alternative 3: 36.7% accurate, 1.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ t_2 := j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{if}\;y0 \leq -1.4 \cdot 10^{+152}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y0 \leq -5.5 \cdot 10^{-131}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y0 \leq 1.75 \cdot 10^{-268}:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;y0 \leq 1.12 \cdot 10^{-250}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y0 \leq 8 \cdot 10^{-182}:\\ \;\;\;\;c \cdot \left(i \cdot \left(z \cdot t - x \cdot y\right)\right)\\ \mathbf{elif}\;y0 \leq 2 \cdot 10^{-86}:\\ \;\;\;\;x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y0 \leq 4.1 \cdot 10^{-57}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(z \cdot y1 - y \cdot y5\right)\right)\\ \mathbf{elif}\;y0 \leq 5.5 \cdot 10^{-15}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;y0 \leq 1.2 \cdot 10^{+112}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y0 \leq 1.2 \cdot 10^{+223}:\\ \;\;\;\;y2 \cdot \left(y0 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1
         (*
          j
          (-
           (- (* t (- (* b y4) (* i y5))) (* y3 (- (* y1 y4) (* y0 y5))))
           (* x (- (* b y0) (* i y1))))))
        (t_2 (* j (* y0 (- (* y3 y5) (* x b))))))
   (if (<= y0 -1.4e+152)
     t_2
     (if (<= y0 -5.5e-131)
       t_1
       (if (<= y0 1.75e-268)
         (* t (* y2 (- (* a y5) (* c y4))))
         (if (<= y0 1.12e-250)
           t_1
           (if (<= y0 8e-182)
             (* c (* i (- (* z t) (* x y))))
             (if (<= y0 2e-86)
               (*
                x
                (+
                 (+ (* y (- (* a b) (* c i))) (* y2 (- (* c y0) (* a y1))))
                 (* j (- (* i y1) (* b y0)))))
               (if (<= y0 4.1e-57)
                 (* a (* y3 (- (* z y1) (* y y5))))
                 (if (<= y0 5.5e-15)
                   (*
                    b
                    (+
                     (+ (* a (- (* x y) (* z t))) (* y4 (- (* t j) (* y k))))
                     (* y0 (- (* z k) (* x j)))))
                   (if (<= y0 1.2e+112)
                     t_1
                     (if (<= y0 1.2e+223)
                       (* y2 (* y0 (- (* x c) (* k y5))))
                       t_2))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = j * (((t * ((b * y4) - (i * y5))) - (y3 * ((y1 * y4) - (y0 * y5)))) - (x * ((b * y0) - (i * y1))));
	double t_2 = j * (y0 * ((y3 * y5) - (x * b)));
	double tmp;
	if (y0 <= -1.4e+152) {
		tmp = t_2;
	} else if (y0 <= -5.5e-131) {
		tmp = t_1;
	} else if (y0 <= 1.75e-268) {
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	} else if (y0 <= 1.12e-250) {
		tmp = t_1;
	} else if (y0 <= 8e-182) {
		tmp = c * (i * ((z * t) - (x * y)));
	} else if (y0 <= 2e-86) {
		tmp = x * (((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1)))) + (j * ((i * y1) - (b * y0))));
	} else if (y0 <= 4.1e-57) {
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	} else if (y0 <= 5.5e-15) {
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))));
	} else if (y0 <= 1.2e+112) {
		tmp = t_1;
	} else if (y0 <= 1.2e+223) {
		tmp = y2 * (y0 * ((x * c) - (k * y5)));
	} else {
		tmp = t_2;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = j * (((t * ((b * y4) - (i * y5))) - (y3 * ((y1 * y4) - (y0 * y5)))) - (x * ((b * y0) - (i * y1))))
    t_2 = j * (y0 * ((y3 * y5) - (x * b)))
    if (y0 <= (-1.4d+152)) then
        tmp = t_2
    else if (y0 <= (-5.5d-131)) then
        tmp = t_1
    else if (y0 <= 1.75d-268) then
        tmp = t * (y2 * ((a * y5) - (c * y4)))
    else if (y0 <= 1.12d-250) then
        tmp = t_1
    else if (y0 <= 8d-182) then
        tmp = c * (i * ((z * t) - (x * y)))
    else if (y0 <= 2d-86) then
        tmp = x * (((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1)))) + (j * ((i * y1) - (b * y0))))
    else if (y0 <= 4.1d-57) then
        tmp = a * (y3 * ((z * y1) - (y * y5)))
    else if (y0 <= 5.5d-15) then
        tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))))
    else if (y0 <= 1.2d+112) then
        tmp = t_1
    else if (y0 <= 1.2d+223) then
        tmp = y2 * (y0 * ((x * c) - (k * y5)))
    else
        tmp = t_2
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = j * (((t * ((b * y4) - (i * y5))) - (y3 * ((y1 * y4) - (y0 * y5)))) - (x * ((b * y0) - (i * y1))));
	double t_2 = j * (y0 * ((y3 * y5) - (x * b)));
	double tmp;
	if (y0 <= -1.4e+152) {
		tmp = t_2;
	} else if (y0 <= -5.5e-131) {
		tmp = t_1;
	} else if (y0 <= 1.75e-268) {
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	} else if (y0 <= 1.12e-250) {
		tmp = t_1;
	} else if (y0 <= 8e-182) {
		tmp = c * (i * ((z * t) - (x * y)));
	} else if (y0 <= 2e-86) {
		tmp = x * (((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1)))) + (j * ((i * y1) - (b * y0))));
	} else if (y0 <= 4.1e-57) {
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	} else if (y0 <= 5.5e-15) {
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))));
	} else if (y0 <= 1.2e+112) {
		tmp = t_1;
	} else if (y0 <= 1.2e+223) {
		tmp = y2 * (y0 * ((x * c) - (k * y5)));
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = j * (((t * ((b * y4) - (i * y5))) - (y3 * ((y1 * y4) - (y0 * y5)))) - (x * ((b * y0) - (i * y1))))
	t_2 = j * (y0 * ((y3 * y5) - (x * b)))
	tmp = 0
	if y0 <= -1.4e+152:
		tmp = t_2
	elif y0 <= -5.5e-131:
		tmp = t_1
	elif y0 <= 1.75e-268:
		tmp = t * (y2 * ((a * y5) - (c * y4)))
	elif y0 <= 1.12e-250:
		tmp = t_1
	elif y0 <= 8e-182:
		tmp = c * (i * ((z * t) - (x * y)))
	elif y0 <= 2e-86:
		tmp = x * (((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1)))) + (j * ((i * y1) - (b * y0))))
	elif y0 <= 4.1e-57:
		tmp = a * (y3 * ((z * y1) - (y * y5)))
	elif y0 <= 5.5e-15:
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))))
	elif y0 <= 1.2e+112:
		tmp = t_1
	elif y0 <= 1.2e+223:
		tmp = y2 * (y0 * ((x * c) - (k * y5)))
	else:
		tmp = t_2
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(j * Float64(Float64(Float64(t * Float64(Float64(b * y4) - Float64(i * y5))) - Float64(y3 * Float64(Float64(y1 * y4) - Float64(y0 * y5)))) - Float64(x * Float64(Float64(b * y0) - Float64(i * y1)))))
	t_2 = Float64(j * Float64(y0 * Float64(Float64(y3 * y5) - Float64(x * b))))
	tmp = 0.0
	if (y0 <= -1.4e+152)
		tmp = t_2;
	elseif (y0 <= -5.5e-131)
		tmp = t_1;
	elseif (y0 <= 1.75e-268)
		tmp = Float64(t * Float64(y2 * Float64(Float64(a * y5) - Float64(c * y4))));
	elseif (y0 <= 1.12e-250)
		tmp = t_1;
	elseif (y0 <= 8e-182)
		tmp = Float64(c * Float64(i * Float64(Float64(z * t) - Float64(x * y))));
	elseif (y0 <= 2e-86)
		tmp = Float64(x * Float64(Float64(Float64(y * Float64(Float64(a * b) - Float64(c * i))) + Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1)))) + Float64(j * Float64(Float64(i * y1) - Float64(b * y0)))));
	elseif (y0 <= 4.1e-57)
		tmp = Float64(a * Float64(y3 * Float64(Float64(z * y1) - Float64(y * y5))));
	elseif (y0 <= 5.5e-15)
		tmp = Float64(b * Float64(Float64(Float64(a * Float64(Float64(x * y) - Float64(z * t))) + Float64(y4 * Float64(Float64(t * j) - Float64(y * k)))) + Float64(y0 * Float64(Float64(z * k) - Float64(x * j)))));
	elseif (y0 <= 1.2e+112)
		tmp = t_1;
	elseif (y0 <= 1.2e+223)
		tmp = Float64(y2 * Float64(y0 * Float64(Float64(x * c) - Float64(k * y5))));
	else
		tmp = t_2;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = j * (((t * ((b * y4) - (i * y5))) - (y3 * ((y1 * y4) - (y0 * y5)))) - (x * ((b * y0) - (i * y1))));
	t_2 = j * (y0 * ((y3 * y5) - (x * b)));
	tmp = 0.0;
	if (y0 <= -1.4e+152)
		tmp = t_2;
	elseif (y0 <= -5.5e-131)
		tmp = t_1;
	elseif (y0 <= 1.75e-268)
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	elseif (y0 <= 1.12e-250)
		tmp = t_1;
	elseif (y0 <= 8e-182)
		tmp = c * (i * ((z * t) - (x * y)));
	elseif (y0 <= 2e-86)
		tmp = x * (((y * ((a * b) - (c * i))) + (y2 * ((c * y0) - (a * y1)))) + (j * ((i * y1) - (b * y0))));
	elseif (y0 <= 4.1e-57)
		tmp = a * (y3 * ((z * y1) - (y * y5)));
	elseif (y0 <= 5.5e-15)
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))));
	elseif (y0 <= 1.2e+112)
		tmp = t_1;
	elseif (y0 <= 1.2e+223)
		tmp = y2 * (y0 * ((x * c) - (k * y5)));
	else
		tmp = t_2;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(j * N[(N[(N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y3 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(x * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(j * N[(y0 * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y0, -1.4e+152], t$95$2, If[LessEqual[y0, -5.5e-131], t$95$1, If[LessEqual[y0, 1.75e-268], N[(t * N[(y2 * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 1.12e-250], t$95$1, If[LessEqual[y0, 8e-182], N[(c * N[(i * N[(N[(z * t), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 2e-86], N[(x * N[(N[(N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(j * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 4.1e-57], N[(a * N[(y3 * N[(N[(z * y1), $MachinePrecision] - N[(y * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 5.5e-15], N[(b * N[(N[(N[(a * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y4 * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 1.2e+112], t$95$1, If[LessEqual[y0, 1.2e+223], N[(y2 * N[(y0 * N[(N[(x * c), $MachinePrecision] - N[(k * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$2]]]]]]]]]]]]

Derivation

1. Split input into 8 regimes

2. if y0 < -1.4000000000000001e152 or 1.20000000000000006e223 < y0

   1. Initial program 24.5%

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

   2. Taylor expanded in j around inf 46.0%

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

      1. +-commutative 46.0%

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

      2. mul-1-neg 46.0%

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

      3. unsub-neg 46.0%

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

      4. *-commutative 46.0%

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

   4. Simplified 46.0%

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

   5. Taylor expanded in y0 around -inf 70.5%

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

      1. +-commutative 70.5%

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

      2. mul-1-neg 70.5%

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

      3. unsub-neg 70.5%

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

      4. *-commutative 70.5%

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

   7. Simplified 70.5%

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

   if -1.4000000000000001e152 < y0 < -5.4999999999999997e-131 or 1.75000000000000003e-268 < y0 < 1.11999999999999996e-250 or 5.5000000000000002e-15 < y0 < 1.2e112

   1. Initial program 32.8%

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

   2. Taylor expanded in j around inf 53.9%

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

      1. +-commutative 53.9%

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

      2. mul-1-neg 53.9%

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

      3. unsub-neg 53.9%

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

      4. *-commutative 53.9%

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

   4. Simplified 53.9%

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

   if -5.4999999999999997e-131 < y0 < 1.75000000000000003e-268

   1. Initial program 27.9%

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

   2. Taylor expanded in y2 around inf 38.0%

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

   3. Taylor expanded in t around inf 47.4%

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

   if 1.11999999999999996e-250 < y0 < 8.0000000000000004e-182

   1. Initial program 36.4%

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

   2. Taylor expanded in c around inf 46.8%

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

   3. Taylor expanded in i around inf 74.1%

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

      1. neg-mul-1 74.1%

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

      2. distribute-rgt-neg-in 74.1%

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

   5. Simplified 74.1%

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

   if 8.0000000000000004e-182 < y0 < 2.00000000000000017e-86

   1. Initial program 32.2%

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

   2. Taylor expanded in x around inf 68.3%

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

   if 2.00000000000000017e-86 < y0 < 4.1000000000000001e-57

   1. Initial program 49.8%

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

   2. Taylor expanded in y3 around -inf 40.0%

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

   3. Taylor expanded in a around inf 64.3%

      \[\leadsto -1 \cdot \color{blue}{\left(a \cdot \left(y3 \cdot \left(-1 \cdot \left(y1 \cdot z\right) - -1 \cdot \left(y \cdot y5\right)\right)\right)\right)} \]
   4. Step-by-step derivation

      1. distribute-lft-out-- 64.3%

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

      2. *-commutative 64.3%

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

   5. Simplified 64.3%

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

   if 4.1000000000000001e-57 < y0 < 5.5000000000000002e-15

   1. Initial program 27.3%

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

   2. Taylor expanded in b around inf 45.7%

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

   if 1.2e112 < y0 < 1.20000000000000006e223

   1. Initial program 13.0%

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

   2. Taylor expanded in y2 around inf 52.5%

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

   3. Taylor expanded in y0 around inf 61.3%

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

      1. +-commutative 61.3%

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

      2. mul-1-neg 61.3%

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

      3. unsub-neg 61.3%

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

      4. *-commutative 61.3%

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

      5. *-commutative 61.3%

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

   5. Simplified 61.3%

      \[\leadsto y2 \cdot \color{blue}{\left(y0 \cdot \left(x \cdot c - y5 \cdot k\right)\right)} \]
3. Recombined 8 regimes into one program.

4. Final simplification 58.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y0 \leq -1.4 \cdot 10^{+152}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;y0 \leq -5.5 \cdot 10^{-131}:\\ \;\;\;\;j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;y0 \leq 1.75 \cdot 10^{-268}:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;y0 \leq 1.12 \cdot 10^{-250}:\\ \;\;\;\;j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;y0 \leq 8 \cdot 10^{-182}:\\ \;\;\;\;c \cdot \left(i \cdot \left(z \cdot t - x \cdot y\right)\right)\\ \mathbf{elif}\;y0 \leq 2 \cdot 10^{-86}:\\ \;\;\;\;x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y0 \leq 4.1 \cdot 10^{-57}:\\ \;\;\;\;a \cdot \left(y3 \cdot \left(z \cdot y1 - y \cdot y5\right)\right)\\ \mathbf{elif}\;y0 \leq 5.5 \cdot 10^{-15}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;y0 \leq 1.2 \cdot 10^{+112}:\\ \;\;\;\;j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;y0 \leq 1.2 \cdot 10^{+223}:\\ \;\;\;\;y2 \cdot \left(y0 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \end{array} \]

Alternative 4: 42.1% accurate, 1.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := t \cdot j - y \cdot k\\ t_2 := b \cdot y0 - i \cdot y1\\ t_3 := j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - x \cdot t_2\right)\\ t_4 := c \cdot y0 - a \cdot y1\\ t_5 := y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) - \left(z \cdot t_4 - j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\right)\\ t_6 := i \cdot \left(y1 \cdot \left(x \cdot j - z \cdot k\right) + \left(c \cdot \left(z \cdot t - x \cdot y\right) - y5 \cdot t_1\right)\right)\\ t_7 := a \cdot b - c \cdot i\\ \mathbf{if}\;j \leq -1.05 \cdot 10^{+198}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;j \leq -9 \cdot 10^{+31}:\\ \;\;\;\;t_5\\ \mathbf{elif}\;j \leq -2.5 \cdot 10^{-11}:\\ \;\;\;\;t_6\\ \mathbf{elif}\;j \leq -1.45 \cdot 10^{-258}:\\ \;\;\;\;y4 \cdot \left(\left(b \cdot t_1 + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq 1.3 \cdot 10^{-198}:\\ \;\;\;\;t_6\\ \mathbf{elif}\;j \leq 1.6 \cdot 10^{-155}:\\ \;\;\;\;t_5\\ \mathbf{elif}\;j \leq 4 \cdot 10^{-110}:\\ \;\;\;\;z \cdot \left(k \cdot t_2 + \left(y3 \cdot \left(a \cdot y1 - c \cdot y0\right) - t \cdot t_7\right)\right)\\ \mathbf{elif}\;j \leq 1.3 \cdot 10^{-24}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot t_1\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;j \leq 1.7 \cdot 10^{+62}:\\ \;\;\;\;x \cdot \left(\left(y \cdot t_7 + y2 \cdot t_4\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_3\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* t j) (* y k)))
        (t_2 (- (* b y0) (* i y1)))
        (t_3
         (*
          j
          (-
           (- (* t (- (* b y4) (* i y5))) (* y3 (- (* y1 y4) (* y0 y5))))
           (* x t_2))))
        (t_4 (- (* c y0) (* a y1)))
        (t_5
         (*
          y3
          (-
           (* y (- (* c y4) (* a y5)))
           (- (* z t_4) (* j (- (* y0 y5) (* y1 y4)))))))
        (t_6
         (*
          i
          (+
           (* y1 (- (* x j) (* z k)))
           (- (* c (- (* z t) (* x y))) (* y5 t_1)))))
        (t_7 (- (* a b) (* c i))))
   (if (<= j -1.05e+198)
     t_3
     (if (<= j -9e+31)
       t_5
       (if (<= j -2.5e-11)
         t_6
         (if (<= j -1.45e-258)
           (*
            y4
            (+
             (+ (* b t_1) (* y1 (- (* k y2) (* j y3))))
             (* c (- (* y y3) (* t y2)))))
           (if (<= j 1.3e-198)
             t_6
             (if (<= j 1.6e-155)
               t_5
               (if (<= j 4e-110)
                 (* z (+ (* k t_2) (- (* y3 (- (* a y1) (* c y0))) (* t t_7))))
                 (if (<= j 1.3e-24)
                   (*
                    b
                    (+
                     (+ (* a (- (* x y) (* z t))) (* y4 t_1))
                     (* y0 (- (* z k) (* x j)))))
                   (if (<= j 1.7e+62)
                     (*
                      x
                      (+ (+ (* y t_7) (* y2 t_4)) (* j (- (* i y1) (* b y0)))))
                     t_3)))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (t * j) - (y * k);
	double t_2 = (b * y0) - (i * y1);
	double t_3 = j * (((t * ((b * y4) - (i * y5))) - (y3 * ((y1 * y4) - (y0 * y5)))) - (x * t_2));
	double t_4 = (c * y0) - (a * y1);
	double t_5 = y3 * ((y * ((c * y4) - (a * y5))) - ((z * t_4) - (j * ((y0 * y5) - (y1 * y4)))));
	double t_6 = i * ((y1 * ((x * j) - (z * k))) + ((c * ((z * t) - (x * y))) - (y5 * t_1)));
	double t_7 = (a * b) - (c * i);
	double tmp;
	if (j <= -1.05e+198) {
		tmp = t_3;
	} else if (j <= -9e+31) {
		tmp = t_5;
	} else if (j <= -2.5e-11) {
		tmp = t_6;
	} else if (j <= -1.45e-258) {
		tmp = y4 * (((b * t_1) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	} else if (j <= 1.3e-198) {
		tmp = t_6;
	} else if (j <= 1.6e-155) {
		tmp = t_5;
	} else if (j <= 4e-110) {
		tmp = z * ((k * t_2) + ((y3 * ((a * y1) - (c * y0))) - (t * t_7)));
	} else if (j <= 1.3e-24) {
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * t_1)) + (y0 * ((z * k) - (x * j))));
	} else if (j <= 1.7e+62) {
		tmp = x * (((y * t_7) + (y2 * t_4)) + (j * ((i * y1) - (b * y0))));
	} else {
		tmp = t_3;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: t_5
    real(8) :: t_6
    real(8) :: t_7
    real(8) :: tmp
    t_1 = (t * j) - (y * k)
    t_2 = (b * y0) - (i * y1)
    t_3 = j * (((t * ((b * y4) - (i * y5))) - (y3 * ((y1 * y4) - (y0 * y5)))) - (x * t_2))
    t_4 = (c * y0) - (a * y1)
    t_5 = y3 * ((y * ((c * y4) - (a * y5))) - ((z * t_4) - (j * ((y0 * y5) - (y1 * y4)))))
    t_6 = i * ((y1 * ((x * j) - (z * k))) + ((c * ((z * t) - (x * y))) - (y5 * t_1)))
    t_7 = (a * b) - (c * i)
    if (j <= (-1.05d+198)) then
        tmp = t_3
    else if (j <= (-9d+31)) then
        tmp = t_5
    else if (j <= (-2.5d-11)) then
        tmp = t_6
    else if (j <= (-1.45d-258)) then
        tmp = y4 * (((b * t_1) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))))
    else if (j <= 1.3d-198) then
        tmp = t_6
    else if (j <= 1.6d-155) then
        tmp = t_5
    else if (j <= 4d-110) then
        tmp = z * ((k * t_2) + ((y3 * ((a * y1) - (c * y0))) - (t * t_7)))
    else if (j <= 1.3d-24) then
        tmp = b * (((a * ((x * y) - (z * t))) + (y4 * t_1)) + (y0 * ((z * k) - (x * j))))
    else if (j <= 1.7d+62) then
        tmp = x * (((y * t_7) + (y2 * t_4)) + (j * ((i * y1) - (b * y0))))
    else
        tmp = t_3
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (t * j) - (y * k);
	double t_2 = (b * y0) - (i * y1);
	double t_3 = j * (((t * ((b * y4) - (i * y5))) - (y3 * ((y1 * y4) - (y0 * y5)))) - (x * t_2));
	double t_4 = (c * y0) - (a * y1);
	double t_5 = y3 * ((y * ((c * y4) - (a * y5))) - ((z * t_4) - (j * ((y0 * y5) - (y1 * y4)))));
	double t_6 = i * ((y1 * ((x * j) - (z * k))) + ((c * ((z * t) - (x * y))) - (y5 * t_1)));
	double t_7 = (a * b) - (c * i);
	double tmp;
	if (j <= -1.05e+198) {
		tmp = t_3;
	} else if (j <= -9e+31) {
		tmp = t_5;
	} else if (j <= -2.5e-11) {
		tmp = t_6;
	} else if (j <= -1.45e-258) {
		tmp = y4 * (((b * t_1) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	} else if (j <= 1.3e-198) {
		tmp = t_6;
	} else if (j <= 1.6e-155) {
		tmp = t_5;
	} else if (j <= 4e-110) {
		tmp = z * ((k * t_2) + ((y3 * ((a * y1) - (c * y0))) - (t * t_7)));
	} else if (j <= 1.3e-24) {
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * t_1)) + (y0 * ((z * k) - (x * j))));
	} else if (j <= 1.7e+62) {
		tmp = x * (((y * t_7) + (y2 * t_4)) + (j * ((i * y1) - (b * y0))));
	} else {
		tmp = t_3;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (t * j) - (y * k)
	t_2 = (b * y0) - (i * y1)
	t_3 = j * (((t * ((b * y4) - (i * y5))) - (y3 * ((y1 * y4) - (y0 * y5)))) - (x * t_2))
	t_4 = (c * y0) - (a * y1)
	t_5 = y3 * ((y * ((c * y4) - (a * y5))) - ((z * t_4) - (j * ((y0 * y5) - (y1 * y4)))))
	t_6 = i * ((y1 * ((x * j) - (z * k))) + ((c * ((z * t) - (x * y))) - (y5 * t_1)))
	t_7 = (a * b) - (c * i)
	tmp = 0
	if j <= -1.05e+198:
		tmp = t_3
	elif j <= -9e+31:
		tmp = t_5
	elif j <= -2.5e-11:
		tmp = t_6
	elif j <= -1.45e-258:
		tmp = y4 * (((b * t_1) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))))
	elif j <= 1.3e-198:
		tmp = t_6
	elif j <= 1.6e-155:
		tmp = t_5
	elif j <= 4e-110:
		tmp = z * ((k * t_2) + ((y3 * ((a * y1) - (c * y0))) - (t * t_7)))
	elif j <= 1.3e-24:
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * t_1)) + (y0 * ((z * k) - (x * j))))
	elif j <= 1.7e+62:
		tmp = x * (((y * t_7) + (y2 * t_4)) + (j * ((i * y1) - (b * y0))))
	else:
		tmp = t_3
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(t * j) - Float64(y * k))
	t_2 = Float64(Float64(b * y0) - Float64(i * y1))
	t_3 = Float64(j * Float64(Float64(Float64(t * Float64(Float64(b * y4) - Float64(i * y5))) - Float64(y3 * Float64(Float64(y1 * y4) - Float64(y0 * y5)))) - Float64(x * t_2)))
	t_4 = Float64(Float64(c * y0) - Float64(a * y1))
	t_5 = Float64(y3 * Float64(Float64(y * Float64(Float64(c * y4) - Float64(a * y5))) - Float64(Float64(z * t_4) - Float64(j * Float64(Float64(y0 * y5) - Float64(y1 * y4))))))
	t_6 = Float64(i * Float64(Float64(y1 * Float64(Float64(x * j) - Float64(z * k))) + Float64(Float64(c * Float64(Float64(z * t) - Float64(x * y))) - Float64(y5 * t_1))))
	t_7 = Float64(Float64(a * b) - Float64(c * i))
	tmp = 0.0
	if (j <= -1.05e+198)
		tmp = t_3;
	elseif (j <= -9e+31)
		tmp = t_5;
	elseif (j <= -2.5e-11)
		tmp = t_6;
	elseif (j <= -1.45e-258)
		tmp = Float64(y4 * Float64(Float64(Float64(b * t_1) + Float64(y1 * Float64(Float64(k * y2) - Float64(j * y3)))) + Float64(c * Float64(Float64(y * y3) - Float64(t * y2)))));
	elseif (j <= 1.3e-198)
		tmp = t_6;
	elseif (j <= 1.6e-155)
		tmp = t_5;
	elseif (j <= 4e-110)
		tmp = Float64(z * Float64(Float64(k * t_2) + Float64(Float64(y3 * Float64(Float64(a * y1) - Float64(c * y0))) - Float64(t * t_7))));
	elseif (j <= 1.3e-24)
		tmp = Float64(b * Float64(Float64(Float64(a * Float64(Float64(x * y) - Float64(z * t))) + Float64(y4 * t_1)) + Float64(y0 * Float64(Float64(z * k) - Float64(x * j)))));
	elseif (j <= 1.7e+62)
		tmp = Float64(x * Float64(Float64(Float64(y * t_7) + Float64(y2 * t_4)) + Float64(j * Float64(Float64(i * y1) - Float64(b * y0)))));
	else
		tmp = t_3;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = (t * j) - (y * k);
	t_2 = (b * y0) - (i * y1);
	t_3 = j * (((t * ((b * y4) - (i * y5))) - (y3 * ((y1 * y4) - (y0 * y5)))) - (x * t_2));
	t_4 = (c * y0) - (a * y1);
	t_5 = y3 * ((y * ((c * y4) - (a * y5))) - ((z * t_4) - (j * ((y0 * y5) - (y1 * y4)))));
	t_6 = i * ((y1 * ((x * j) - (z * k))) + ((c * ((z * t) - (x * y))) - (y5 * t_1)));
	t_7 = (a * b) - (c * i);
	tmp = 0.0;
	if (j <= -1.05e+198)
		tmp = t_3;
	elseif (j <= -9e+31)
		tmp = t_5;
	elseif (j <= -2.5e-11)
		tmp = t_6;
	elseif (j <= -1.45e-258)
		tmp = y4 * (((b * t_1) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	elseif (j <= 1.3e-198)
		tmp = t_6;
	elseif (j <= 1.6e-155)
		tmp = t_5;
	elseif (j <= 4e-110)
		tmp = z * ((k * t_2) + ((y3 * ((a * y1) - (c * y0))) - (t * t_7)));
	elseif (j <= 1.3e-24)
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * t_1)) + (y0 * ((z * k) - (x * j))));
	elseif (j <= 1.7e+62)
		tmp = x * (((y * t_7) + (y2 * t_4)) + (j * ((i * y1) - (b * y0))));
	else
		tmp = t_3;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(j * N[(N[(N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y3 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(x * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(y3 * N[(N[(y * N[(N[(c * y4), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(z * t$95$4), $MachinePrecision] - N[(j * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$6 = N[(i * N[(N[(y1 * N[(N[(x * j), $MachinePrecision] - N[(z * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(c * N[(N[(z * t), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y5 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$7 = N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[j, -1.05e+198], t$95$3, If[LessEqual[j, -9e+31], t$95$5, If[LessEqual[j, -2.5e-11], t$95$6, If[LessEqual[j, -1.45e-258], N[(y4 * N[(N[(N[(b * t$95$1), $MachinePrecision] + N[(y1 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(c * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 1.3e-198], t$95$6, If[LessEqual[j, 1.6e-155], t$95$5, If[LessEqual[j, 4e-110], N[(z * N[(N[(k * t$95$2), $MachinePrecision] + N[(N[(y3 * N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(t * t$95$7), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 1.3e-24], N[(b * N[(N[(N[(a * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y4 * t$95$1), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[j, 1.7e+62], N[(x * N[(N[(N[(y * t$95$7), $MachinePrecision] + N[(y2 * t$95$4), $MachinePrecision]), $MachinePrecision] + N[(j * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$3]]]]]]]]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if j < -1.05000000000000006e198 or 1.70000000000000007e62 < j

   1. Initial program 29.8%

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

   2. Taylor expanded in j around inf 67.8%

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

      1. +-commutative 67.8%

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

      2. mul-1-neg 67.8%

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

      3. unsub-neg 67.8%

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

      4. *-commutative 67.8%

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

   4. Simplified 67.8%

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

   if -1.05000000000000006e198 < j < -8.9999999999999992e31 or 1.30000000000000003e-198 < j < 1.60000000000000006e-155

   1. Initial program 21.8%

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

   2. Taylor expanded in y3 around -inf 61.2%

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

   if -8.9999999999999992e31 < j < -2.50000000000000009e-11 or -1.45e-258 < j < 1.30000000000000003e-198

   1. Initial program 33.8%

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

   2. Taylor expanded in i around -inf 59.0%

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

   if -2.50000000000000009e-11 < j < -1.45e-258

   1. Initial program 35.5%

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

   2. Taylor expanded in y4 around inf 53.0%

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

   if 1.60000000000000006e-155 < j < 4.0000000000000002e-110

   1. Initial program 10.9%

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

   2. Taylor expanded in z around -inf 80.0%

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

   if 4.0000000000000002e-110 < j < 1.3e-24

   1. Initial program 42.4%

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

   2. Taylor expanded in b around inf 64.1%

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

   if 1.3e-24 < j < 1.70000000000000007e62

   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. Taylor expanded in x around inf 62.4%

      \[\leadsto \color{blue}{x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - j \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 62.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;j \leq -1.05 \cdot 10^{+198}:\\ \;\;\;\;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) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;j \leq -9 \cdot 10^{+31}:\\ \;\;\;\;y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) - \left(z \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\right)\\ \mathbf{elif}\;j \leq -2.5 \cdot 10^{-11}:\\ \;\;\;\;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(t \cdot j - y \cdot k\right)\right)\right)\\ \mathbf{elif}\;j \leq -1.45 \cdot 10^{-258}:\\ \;\;\;\;y4 \cdot \left(\left(b \cdot \left(t \cdot j - y \cdot k\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;j \leq 1.3 \cdot 10^{-198}:\\ \;\;\;\;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(t \cdot j - y \cdot k\right)\right)\right)\\ \mathbf{elif}\;j \leq 1.6 \cdot 10^{-155}:\\ \;\;\;\;y3 \cdot \left(y \cdot \left(c \cdot y4 - a \cdot y5\right) - \left(z \cdot \left(c \cdot y0 - a \cdot y1\right) - j \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\right)\\ \mathbf{elif}\;j \leq 4 \cdot 10^{-110}:\\ \;\;\;\;z \cdot \left(k \cdot \left(b \cdot y0 - i \cdot y1\right) + \left(y3 \cdot \left(a \cdot y1 - c \cdot y0\right) - t \cdot \left(a \cdot b - c \cdot i\right)\right)\right)\\ \mathbf{elif}\;j \leq 1.3 \cdot 10^{-24}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;j \leq 1.7 \cdot 10^{+62}:\\ \;\;\;\;x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;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) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \end{array} \]

Alternative 5: 37.8% accurate, 2.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y1 \cdot y4 - y0 \cdot y5\\ t_2 := j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot t_1\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ t_3 := c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ t_4 := c \cdot y0 - a \cdot y1\\ \mathbf{if}\;z \leq -2.95 \cdot 10^{+100}:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0 - t \cdot a\right)\right)\\ \mathbf{elif}\;z \leq -1.8 \cdot 10^{-162}:\\ \;\;\;\;y2 \cdot \left(\left(k \cdot t_1 + x \cdot t_4\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 6 \cdot 10^{-167}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;z \leq 1.5 \cdot 10^{-77}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;z \leq 5.8 \cdot 10^{+58}:\\ \;\;\;\;x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot t_4\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;z \leq 8.2 \cdot 10^{+135}:\\ \;\;\;\;y4 \cdot \left(\left(b \cdot \left(t \cdot j - y \cdot k\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;z \leq 6 \cdot 10^{+175}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;z \leq 6.2 \cdot 10^{+257}:\\ \;\;\;\;c \cdot \left(i \cdot \left(z \cdot t - x \cdot y\right)\right)\\ \mathbf{elif}\;z \leq 2.8 \cdot 10^{+270}:\\ \;\;\;\;t_3\\ \mathbf{else}:\\ \;\;\;\;\left(z \cdot y3\right) \cdot \left(a \cdot y1 - c \cdot y0\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* y1 y4) (* y0 y5)))
        (t_2
         (*
          j
          (-
           (- (* t (- (* b y4) (* i y5))) (* y3 t_1))
           (* x (- (* b y0) (* i y1))))))
        (t_3 (* c (* y2 (- (* x y0) (* t y4)))))
        (t_4 (- (* c y0) (* a y1))))
   (if (<= z -2.95e+100)
     (* b (* z (- (* k y0) (* t a))))
     (if (<= z -1.8e-162)
       (* y2 (+ (+ (* k t_1) (* x t_4)) (* t (- (* a y5) (* c y4)))))
       (if (<= z 6e-167)
         t_2
         (if (<= z 1.5e-77)
           t_3
           (if (<= z 5.8e+58)
             (*
              x
              (+
               (+ (* y (- (* a b) (* c i))) (* y2 t_4))
               (* j (- (* i y1) (* b y0)))))
             (if (<= z 8.2e+135)
               (*
                y4
                (+
                 (+ (* b (- (* t j) (* y k))) (* y1 (- (* k y2) (* j y3))))
                 (* c (- (* y y3) (* t y2)))))
               (if (<= z 6e+175)
                 t_2
                 (if (<= z 6.2e+257)
                   (* c (* i (- (* z t) (* x y))))
                   (if (<= z 2.8e+270)
                     t_3
                     (* (* z y3) (- (* a y1) (* c y0))))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (y1 * y4) - (y0 * y5);
	double t_2 = j * (((t * ((b * y4) - (i * y5))) - (y3 * t_1)) - (x * ((b * y0) - (i * y1))));
	double t_3 = c * (y2 * ((x * y0) - (t * y4)));
	double t_4 = (c * y0) - (a * y1);
	double tmp;
	if (z <= -2.95e+100) {
		tmp = b * (z * ((k * y0) - (t * a)));
	} else if (z <= -1.8e-162) {
		tmp = y2 * (((k * t_1) + (x * t_4)) + (t * ((a * y5) - (c * y4))));
	} else if (z <= 6e-167) {
		tmp = t_2;
	} else if (z <= 1.5e-77) {
		tmp = t_3;
	} else if (z <= 5.8e+58) {
		tmp = x * (((y * ((a * b) - (c * i))) + (y2 * t_4)) + (j * ((i * y1) - (b * y0))));
	} else if (z <= 8.2e+135) {
		tmp = y4 * (((b * ((t * j) - (y * k))) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	} else if (z <= 6e+175) {
		tmp = t_2;
	} else if (z <= 6.2e+257) {
		tmp = c * (i * ((z * t) - (x * y)));
	} else if (z <= 2.8e+270) {
		tmp = t_3;
	} else {
		tmp = (z * y3) * ((a * y1) - (c * y0));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: tmp
    t_1 = (y1 * y4) - (y0 * y5)
    t_2 = j * (((t * ((b * y4) - (i * y5))) - (y3 * t_1)) - (x * ((b * y0) - (i * y1))))
    t_3 = c * (y2 * ((x * y0) - (t * y4)))
    t_4 = (c * y0) - (a * y1)
    if (z <= (-2.95d+100)) then
        tmp = b * (z * ((k * y0) - (t * a)))
    else if (z <= (-1.8d-162)) then
        tmp = y2 * (((k * t_1) + (x * t_4)) + (t * ((a * y5) - (c * y4))))
    else if (z <= 6d-167) then
        tmp = t_2
    else if (z <= 1.5d-77) then
        tmp = t_3
    else if (z <= 5.8d+58) then
        tmp = x * (((y * ((a * b) - (c * i))) + (y2 * t_4)) + (j * ((i * y1) - (b * y0))))
    else if (z <= 8.2d+135) then
        tmp = y4 * (((b * ((t * j) - (y * k))) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))))
    else if (z <= 6d+175) then
        tmp = t_2
    else if (z <= 6.2d+257) then
        tmp = c * (i * ((z * t) - (x * y)))
    else if (z <= 2.8d+270) then
        tmp = t_3
    else
        tmp = (z * y3) * ((a * y1) - (c * y0))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (y1 * y4) - (y0 * y5);
	double t_2 = j * (((t * ((b * y4) - (i * y5))) - (y3 * t_1)) - (x * ((b * y0) - (i * y1))));
	double t_3 = c * (y2 * ((x * y0) - (t * y4)));
	double t_4 = (c * y0) - (a * y1);
	double tmp;
	if (z <= -2.95e+100) {
		tmp = b * (z * ((k * y0) - (t * a)));
	} else if (z <= -1.8e-162) {
		tmp = y2 * (((k * t_1) + (x * t_4)) + (t * ((a * y5) - (c * y4))));
	} else if (z <= 6e-167) {
		tmp = t_2;
	} else if (z <= 1.5e-77) {
		tmp = t_3;
	} else if (z <= 5.8e+58) {
		tmp = x * (((y * ((a * b) - (c * i))) + (y2 * t_4)) + (j * ((i * y1) - (b * y0))));
	} else if (z <= 8.2e+135) {
		tmp = y4 * (((b * ((t * j) - (y * k))) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	} else if (z <= 6e+175) {
		tmp = t_2;
	} else if (z <= 6.2e+257) {
		tmp = c * (i * ((z * t) - (x * y)));
	} else if (z <= 2.8e+270) {
		tmp = t_3;
	} else {
		tmp = (z * y3) * ((a * y1) - (c * y0));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (y1 * y4) - (y0 * y5)
	t_2 = j * (((t * ((b * y4) - (i * y5))) - (y3 * t_1)) - (x * ((b * y0) - (i * y1))))
	t_3 = c * (y2 * ((x * y0) - (t * y4)))
	t_4 = (c * y0) - (a * y1)
	tmp = 0
	if z <= -2.95e+100:
		tmp = b * (z * ((k * y0) - (t * a)))
	elif z <= -1.8e-162:
		tmp = y2 * (((k * t_1) + (x * t_4)) + (t * ((a * y5) - (c * y4))))
	elif z <= 6e-167:
		tmp = t_2
	elif z <= 1.5e-77:
		tmp = t_3
	elif z <= 5.8e+58:
		tmp = x * (((y * ((a * b) - (c * i))) + (y2 * t_4)) + (j * ((i * y1) - (b * y0))))
	elif z <= 8.2e+135:
		tmp = y4 * (((b * ((t * j) - (y * k))) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))))
	elif z <= 6e+175:
		tmp = t_2
	elif z <= 6.2e+257:
		tmp = c * (i * ((z * t) - (x * y)))
	elif z <= 2.8e+270:
		tmp = t_3
	else:
		tmp = (z * y3) * ((a * y1) - (c * y0))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(y1 * y4) - Float64(y0 * y5))
	t_2 = Float64(j * Float64(Float64(Float64(t * Float64(Float64(b * y4) - Float64(i * y5))) - Float64(y3 * t_1)) - Float64(x * Float64(Float64(b * y0) - Float64(i * y1)))))
	t_3 = Float64(c * Float64(y2 * Float64(Float64(x * y0) - Float64(t * y4))))
	t_4 = Float64(Float64(c * y0) - Float64(a * y1))
	tmp = 0.0
	if (z <= -2.95e+100)
		tmp = Float64(b * Float64(z * Float64(Float64(k * y0) - Float64(t * a))));
	elseif (z <= -1.8e-162)
		tmp = Float64(y2 * Float64(Float64(Float64(k * t_1) + Float64(x * t_4)) + Float64(t * Float64(Float64(a * y5) - Float64(c * y4)))));
	elseif (z <= 6e-167)
		tmp = t_2;
	elseif (z <= 1.5e-77)
		tmp = t_3;
	elseif (z <= 5.8e+58)
		tmp = Float64(x * Float64(Float64(Float64(y * Float64(Float64(a * b) - Float64(c * i))) + Float64(y2 * t_4)) + Float64(j * Float64(Float64(i * y1) - Float64(b * y0)))));
	elseif (z <= 8.2e+135)
		tmp = Float64(y4 * Float64(Float64(Float64(b * Float64(Float64(t * j) - Float64(y * k))) + Float64(y1 * Float64(Float64(k * y2) - Float64(j * y3)))) + Float64(c * Float64(Float64(y * y3) - Float64(t * y2)))));
	elseif (z <= 6e+175)
		tmp = t_2;
	elseif (z <= 6.2e+257)
		tmp = Float64(c * Float64(i * Float64(Float64(z * t) - Float64(x * y))));
	elseif (z <= 2.8e+270)
		tmp = t_3;
	else
		tmp = Float64(Float64(z * y3) * Float64(Float64(a * y1) - Float64(c * y0)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = (y1 * y4) - (y0 * y5);
	t_2 = j * (((t * ((b * y4) - (i * y5))) - (y3 * t_1)) - (x * ((b * y0) - (i * y1))));
	t_3 = c * (y2 * ((x * y0) - (t * y4)));
	t_4 = (c * y0) - (a * y1);
	tmp = 0.0;
	if (z <= -2.95e+100)
		tmp = b * (z * ((k * y0) - (t * a)));
	elseif (z <= -1.8e-162)
		tmp = y2 * (((k * t_1) + (x * t_4)) + (t * ((a * y5) - (c * y4))));
	elseif (z <= 6e-167)
		tmp = t_2;
	elseif (z <= 1.5e-77)
		tmp = t_3;
	elseif (z <= 5.8e+58)
		tmp = x * (((y * ((a * b) - (c * i))) + (y2 * t_4)) + (j * ((i * y1) - (b * y0))));
	elseif (z <= 8.2e+135)
		tmp = y4 * (((b * ((t * j) - (y * k))) + (y1 * ((k * y2) - (j * y3)))) + (c * ((y * y3) - (t * y2))));
	elseif (z <= 6e+175)
		tmp = t_2;
	elseif (z <= 6.2e+257)
		tmp = c * (i * ((z * t) - (x * y)));
	elseif (z <= 2.8e+270)
		tmp = t_3;
	else
		tmp = (z * y3) * ((a * y1) - (c * y0));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(j * N[(N[(N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y3 * t$95$1), $MachinePrecision]), $MachinePrecision] - N[(x * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(c * N[(y2 * N[(N[(x * y0), $MachinePrecision] - N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -2.95e+100], N[(b * N[(z * N[(N[(k * y0), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -1.8e-162], N[(y2 * N[(N[(N[(k * t$95$1), $MachinePrecision] + N[(x * t$95$4), $MachinePrecision]), $MachinePrecision] + N[(t * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 6e-167], t$95$2, If[LessEqual[z, 1.5e-77], t$95$3, If[LessEqual[z, 5.8e+58], N[(x * N[(N[(N[(y * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y2 * t$95$4), $MachinePrecision]), $MachinePrecision] + N[(j * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 8.2e+135], N[(y4 * N[(N[(N[(b * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y1 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(c * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 6e+175], t$95$2, If[LessEqual[z, 6.2e+257], N[(c * N[(i * N[(N[(z * t), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 2.8e+270], t$95$3, N[(N[(z * y3), $MachinePrecision] * N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]]

Derivation

1. Split input into 8 regimes

2. if z < -2.95000000000000013e100

   1. Initial program 28.4%

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

   2. Taylor expanded in b around inf 41.1%

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

   3. Taylor expanded in z around inf 54.9%

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

      1. distribute-lft-out-- 54.9%

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

      2. *-commutative 54.9%

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

      3. *-commutative 54.9%

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

   5. Simplified 54.9%

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

   if -2.95000000000000013e100 < z < -1.7999999999999999e-162

   1. Initial program 30.7%

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

   2. Taylor expanded in y2 around inf 54.8%

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

   if -1.7999999999999999e-162 < z < 5.9999999999999996e-167 or 8.2e135 < z < 6.0000000000000003e175

   1. Initial program 34.1%

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

   2. Taylor expanded in j around inf 57.8%

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

      1. +-commutative 57.8%

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

      2. mul-1-neg 57.8%

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

      3. unsub-neg 57.8%

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

      4. *-commutative 57.8%

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

   4. Simplified 57.8%

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

   if 5.9999999999999996e-167 < z < 1.50000000000000008e-77 or 6.2000000000000001e257 < z < 2.8000000000000001e270

   1. Initial program 21.0%

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

   2. Taylor expanded in c around inf 52.0%

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

   3. Taylor expanded in y2 around inf 56.1%

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

   if 1.50000000000000008e-77 < z < 5.80000000000000004e58

   1. Initial program 34.8%

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

   2. Taylor expanded in x around inf 61.2%

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

   if 5.80000000000000004e58 < z < 8.2e135

   1. Initial program 23.7%

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

   2. Taylor expanded in y4 around inf 54.9%

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

   if 6.0000000000000003e175 < z < 6.2000000000000001e257

   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. Taylor expanded in c around inf 55.6%

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

   3. Taylor expanded in i around inf 66.8%

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

      1. neg-mul-1 66.8%

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

      2. distribute-rgt-neg-in 66.8%

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

   5. Simplified 66.8%

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

   if 2.8000000000000001e270 < z

   1. Initial program 30.0%

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

   2. Taylor expanded in y3 around -inf 40.0%

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

   3. Taylor expanded in z around inf 80.3%

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

      1. associate-*r* 80.3%

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

      2. *-commutative 80.3%

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

      3. *-commutative 80.3%

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

   5. Simplified 80.3%

      \[\leadsto -1 \cdot \color{blue}{\left(\left(y3 \cdot z\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right)} \]
3. Recombined 8 regimes into one program.

4. Final simplification 58.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -2.95 \cdot 10^{+100}:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0 - t \cdot a\right)\right)\\ \mathbf{elif}\;z \leq -1.8 \cdot 10^{-162}:\\ \;\;\;\;y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 6 \cdot 10^{-167}:\\ \;\;\;\;j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq 1.5 \cdot 10^{-77}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 5.8 \cdot 10^{+58}:\\ \;\;\;\;x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;z \leq 8.2 \cdot 10^{+135}:\\ \;\;\;\;y4 \cdot \left(\left(b \cdot \left(t \cdot j - y \cdot k\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) + c \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;z \leq 6 \cdot 10^{+175}:\\ \;\;\;\;j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq 6.2 \cdot 10^{+257}:\\ \;\;\;\;c \cdot \left(i \cdot \left(z \cdot t - x \cdot y\right)\right)\\ \mathbf{elif}\;z \leq 2.8 \cdot 10^{+270}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(z \cdot y3\right) \cdot \left(a \cdot y1 - c \cdot y0\right)\\ \end{array} \]

Alternative 6: 41.2% accurate, 2.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot b - c \cdot i\\ t_2 := b \cdot y0 - i \cdot y1\\ t_3 := y1 \cdot y4 - y0 \cdot y5\\ t_4 := c \cdot y0 - a \cdot y1\\ \mathbf{if}\;z \leq -7.8 \cdot 10^{+100}:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0 - t \cdot a\right)\right)\\ \mathbf{elif}\;z \leq -1.12 \cdot 10^{-161}:\\ \;\;\;\;y2 \cdot \left(\left(k \cdot t_3 + x \cdot t_4\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 5.1 \cdot 10^{-237}:\\ \;\;\;\;j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot t_3\right) - x \cdot t_2\right)\\ \mathbf{elif}\;z \leq 8.8 \cdot 10^{-104}:\\ \;\;\;\;c \cdot \left(\left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right) + i \cdot \left(z \cdot t - x \cdot y\right)\right) + y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;z \leq 1.35 \cdot 10^{-77}:\\ \;\;\;\;y5 \cdot \left(a \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(y0 \cdot \left(j \cdot y3 - k \cdot y2\right) - i \cdot \left(t \cdot j - y \cdot k\right)\right)\right)\\ \mathbf{elif}\;z \leq 4.4 \cdot 10^{+62}:\\ \;\;\;\;x \cdot \left(\left(y \cdot t_1 + y2 \cdot t_4\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;z \cdot \left(k \cdot t_2 + \left(y3 \cdot \left(a \cdot y1 - c \cdot y0\right) - t \cdot t_1\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* a b) (* c i)))
        (t_2 (- (* b y0) (* i y1)))
        (t_3 (- (* y1 y4) (* y0 y5)))
        (t_4 (- (* c y0) (* a y1))))
   (if (<= z -7.8e+100)
     (* b (* z (- (* k y0) (* t a))))
     (if (<= z -1.12e-161)
       (* y2 (+ (+ (* k t_3) (* x t_4)) (* t (- (* a y5) (* c y4)))))
       (if (<= z 5.1e-237)
         (* j (- (- (* t (- (* b y4) (* i y5))) (* y3 t_3)) (* x t_2)))
         (if (<= z 8.8e-104)
           (*
            c
            (+
             (+ (* y0 (- (* x y2) (* z y3))) (* i (- (* z t) (* x y))))
             (* y4 (- (* y y3) (* t y2)))))
           (if (<= z 1.35e-77)
             (*
              y5
              (+
               (* a (- (* t y2) (* y y3)))
               (- (* y0 (- (* j y3) (* k y2))) (* i (- (* t j) (* y k))))))
             (if (<= z 4.4e+62)
               (* x (+ (+ (* y t_1) (* y2 t_4)) (* j (- (* i y1) (* b y0)))))
               (*
                z
                (+
                 (* k t_2)
                 (- (* y3 (- (* a y1) (* c y0))) (* t 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 = (a * b) - (c * i);
	double t_2 = (b * y0) - (i * y1);
	double t_3 = (y1 * y4) - (y0 * y5);
	double t_4 = (c * y0) - (a * y1);
	double tmp;
	if (z <= -7.8e+100) {
		tmp = b * (z * ((k * y0) - (t * a)));
	} else if (z <= -1.12e-161) {
		tmp = y2 * (((k * t_3) + (x * t_4)) + (t * ((a * y5) - (c * y4))));
	} else if (z <= 5.1e-237) {
		tmp = j * (((t * ((b * y4) - (i * y5))) - (y3 * t_3)) - (x * t_2));
	} else if (z <= 8.8e-104) {
		tmp = c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) + (y4 * ((y * y3) - (t * y2))));
	} else if (z <= 1.35e-77) {
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * ((t * j) - (y * k)))));
	} else if (z <= 4.4e+62) {
		tmp = x * (((y * t_1) + (y2 * t_4)) + (j * ((i * y1) - (b * y0))));
	} else {
		tmp = z * ((k * t_2) + ((y3 * ((a * y1) - (c * y0))) - (t * t_1)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: tmp
    t_1 = (a * b) - (c * i)
    t_2 = (b * y0) - (i * y1)
    t_3 = (y1 * y4) - (y0 * y5)
    t_4 = (c * y0) - (a * y1)
    if (z <= (-7.8d+100)) then
        tmp = b * (z * ((k * y0) - (t * a)))
    else if (z <= (-1.12d-161)) then
        tmp = y2 * (((k * t_3) + (x * t_4)) + (t * ((a * y5) - (c * y4))))
    else if (z <= 5.1d-237) then
        tmp = j * (((t * ((b * y4) - (i * y5))) - (y3 * t_3)) - (x * t_2))
    else if (z <= 8.8d-104) then
        tmp = c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) + (y4 * ((y * y3) - (t * y2))))
    else if (z <= 1.35d-77) then
        tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * ((t * j) - (y * k)))))
    else if (z <= 4.4d+62) then
        tmp = x * (((y * t_1) + (y2 * t_4)) + (j * ((i * y1) - (b * y0))))
    else
        tmp = z * ((k * t_2) + ((y3 * ((a * y1) - (c * y0))) - (t * 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 = (a * b) - (c * i);
	double t_2 = (b * y0) - (i * y1);
	double t_3 = (y1 * y4) - (y0 * y5);
	double t_4 = (c * y0) - (a * y1);
	double tmp;
	if (z <= -7.8e+100) {
		tmp = b * (z * ((k * y0) - (t * a)));
	} else if (z <= -1.12e-161) {
		tmp = y2 * (((k * t_3) + (x * t_4)) + (t * ((a * y5) - (c * y4))));
	} else if (z <= 5.1e-237) {
		tmp = j * (((t * ((b * y4) - (i * y5))) - (y3 * t_3)) - (x * t_2));
	} else if (z <= 8.8e-104) {
		tmp = c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) + (y4 * ((y * y3) - (t * y2))));
	} else if (z <= 1.35e-77) {
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * ((t * j) - (y * k)))));
	} else if (z <= 4.4e+62) {
		tmp = x * (((y * t_1) + (y2 * t_4)) + (j * ((i * y1) - (b * y0))));
	} else {
		tmp = z * ((k * t_2) + ((y3 * ((a * y1) - (c * y0))) - (t * 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 = (a * b) - (c * i)
	t_2 = (b * y0) - (i * y1)
	t_3 = (y1 * y4) - (y0 * y5)
	t_4 = (c * y0) - (a * y1)
	tmp = 0
	if z <= -7.8e+100:
		tmp = b * (z * ((k * y0) - (t * a)))
	elif z <= -1.12e-161:
		tmp = y2 * (((k * t_3) + (x * t_4)) + (t * ((a * y5) - (c * y4))))
	elif z <= 5.1e-237:
		tmp = j * (((t * ((b * y4) - (i * y5))) - (y3 * t_3)) - (x * t_2))
	elif z <= 8.8e-104:
		tmp = c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) + (y4 * ((y * y3) - (t * y2))))
	elif z <= 1.35e-77:
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * ((t * j) - (y * k)))))
	elif z <= 4.4e+62:
		tmp = x * (((y * t_1) + (y2 * t_4)) + (j * ((i * y1) - (b * y0))))
	else:
		tmp = z * ((k * t_2) + ((y3 * ((a * y1) - (c * y0))) - (t * t_1)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(a * b) - Float64(c * i))
	t_2 = Float64(Float64(b * y0) - Float64(i * y1))
	t_3 = Float64(Float64(y1 * y4) - Float64(y0 * y5))
	t_4 = Float64(Float64(c * y0) - Float64(a * y1))
	tmp = 0.0
	if (z <= -7.8e+100)
		tmp = Float64(b * Float64(z * Float64(Float64(k * y0) - Float64(t * a))));
	elseif (z <= -1.12e-161)
		tmp = Float64(y2 * Float64(Float64(Float64(k * t_3) + Float64(x * t_4)) + Float64(t * Float64(Float64(a * y5) - Float64(c * y4)))));
	elseif (z <= 5.1e-237)
		tmp = Float64(j * Float64(Float64(Float64(t * Float64(Float64(b * y4) - Float64(i * y5))) - Float64(y3 * t_3)) - Float64(x * t_2)));
	elseif (z <= 8.8e-104)
		tmp = Float64(c * Float64(Float64(Float64(y0 * Float64(Float64(x * y2) - Float64(z * y3))) + Float64(i * Float64(Float64(z * t) - Float64(x * y)))) + Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2)))));
	elseif (z <= 1.35e-77)
		tmp = Float64(y5 * Float64(Float64(a * Float64(Float64(t * y2) - Float64(y * y3))) + Float64(Float64(y0 * Float64(Float64(j * y3) - Float64(k * y2))) - Float64(i * Float64(Float64(t * j) - Float64(y * k))))));
	elseif (z <= 4.4e+62)
		tmp = Float64(x * Float64(Float64(Float64(y * t_1) + Float64(y2 * t_4)) + Float64(j * Float64(Float64(i * y1) - Float64(b * y0)))));
	else
		tmp = Float64(z * Float64(Float64(k * t_2) + Float64(Float64(y3 * Float64(Float64(a * y1) - Float64(c * y0))) - Float64(t * 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 = (a * b) - (c * i);
	t_2 = (b * y0) - (i * y1);
	t_3 = (y1 * y4) - (y0 * y5);
	t_4 = (c * y0) - (a * y1);
	tmp = 0.0;
	if (z <= -7.8e+100)
		tmp = b * (z * ((k * y0) - (t * a)));
	elseif (z <= -1.12e-161)
		tmp = y2 * (((k * t_3) + (x * t_4)) + (t * ((a * y5) - (c * y4))));
	elseif (z <= 5.1e-237)
		tmp = j * (((t * ((b * y4) - (i * y5))) - (y3 * t_3)) - (x * t_2));
	elseif (z <= 8.8e-104)
		tmp = c * (((y0 * ((x * y2) - (z * y3))) + (i * ((z * t) - (x * y)))) + (y4 * ((y * y3) - (t * y2))));
	elseif (z <= 1.35e-77)
		tmp = y5 * ((a * ((t * y2) - (y * y3))) + ((y0 * ((j * y3) - (k * y2))) - (i * ((t * j) - (y * k)))));
	elseif (z <= 4.4e+62)
		tmp = x * (((y * t_1) + (y2 * t_4)) + (j * ((i * y1) - (b * y0))));
	else
		tmp = z * ((k * t_2) + ((y3 * ((a * y1) - (c * y0))) - (t * t_1)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -7.8e+100], N[(b * N[(z * N[(N[(k * y0), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -1.12e-161], N[(y2 * N[(N[(N[(k * t$95$3), $MachinePrecision] + N[(x * t$95$4), $MachinePrecision]), $MachinePrecision] + N[(t * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 5.1e-237], N[(j * N[(N[(N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y3 * t$95$3), $MachinePrecision]), $MachinePrecision] - N[(x * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 8.8e-104], N[(c * N[(N[(N[(y0 * N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(i * N[(N[(z * t), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.35e-77], N[(y5 * N[(N[(a * N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(y0 * N[(N[(j * y3), $MachinePrecision] - N[(k * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(i * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 4.4e+62], N[(x * N[(N[(N[(y * t$95$1), $MachinePrecision] + N[(y2 * t$95$4), $MachinePrecision]), $MachinePrecision] + N[(j * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(z * N[(N[(k * t$95$2), $MachinePrecision] + N[(N[(y3 * N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(t * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]

Derivation

1. Split input into 7 regimes

2. if z < -7.8e100

   1. Initial program 28.4%

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

   2. Taylor expanded in b around inf 41.1%

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

   3. Taylor expanded in z around inf 54.9%

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

      1. distribute-lft-out-- 54.9%

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

      2. *-commutative 54.9%

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

      3. *-commutative 54.9%

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

   5. Simplified 54.9%

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

   if -7.8e100 < z < -1.12000000000000009e-161

   1. Initial program 30.7%

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

   2. Taylor expanded in y2 around inf 54.8%

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

   if -1.12000000000000009e-161 < z < 5.1000000000000004e-237

   1. Initial program 45.0%

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

   2. Taylor expanded in j around inf 59.2%

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

      1. +-commutative 59.2%

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

      2. mul-1-neg 59.2%

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

      3. unsub-neg 59.2%

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

      4. *-commutative 59.2%

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

   4. Simplified 59.2%

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

   if 5.1000000000000004e-237 < z < 8.80000000000000047e-104

   1. Initial program 28.1%

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

   2. Taylor expanded in c around inf 59.0%

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

   if 8.80000000000000047e-104 < z < 1.35e-77

   1. Initial program 0.0%

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

   2. Taylor expanded in y5 around -inf 90.9%

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

   if 1.35e-77 < z < 4.40000000000000029e62

   1. Initial program 37.5%

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

   2. Taylor expanded in x around inf 62.8%

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

   if 4.40000000000000029e62 < z

   1. Initial program 19.8%

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

   2. Taylor expanded in z around -inf 55.4%

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

4. Final simplification 58.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -7.8 \cdot 10^{+100}:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0 - t \cdot a\right)\right)\\ \mathbf{elif}\;z \leq -1.12 \cdot 10^{-161}:\\ \;\;\;\;y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + t \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 5.1 \cdot 10^{-237}:\\ \;\;\;\;j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq 8.8 \cdot 10^{-104}:\\ \;\;\;\;c \cdot \left(\left(y0 \cdot \left(x \cdot y2 - z \cdot y3\right) + i \cdot \left(z \cdot t - x \cdot y\right)\right) + y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;z \leq 1.35 \cdot 10^{-77}:\\ \;\;\;\;y5 \cdot \left(a \cdot \left(t \cdot y2 - y \cdot y3\right) + \left(y0 \cdot \left(j \cdot y3 - k \cdot y2\right) - i \cdot \left(t \cdot j - y \cdot k\right)\right)\right)\\ \mathbf{elif}\;z \leq 4.4 \cdot 10^{+62}:\\ \;\;\;\;x \cdot \left(\left(y \cdot \left(a \cdot b - c \cdot i\right) + y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right) + j \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;z \cdot \left(k \cdot \left(b \cdot y0 - i \cdot y1\right) + \left(y3 \cdot \left(a \cdot y1 - c \cdot y0\right) - t \cdot \left(a \cdot b - c \cdot i\right)\right)\right)\\ \end{array} \]

Alternative 7: 29.7% accurate, 2.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \left(z \cdot y3\right) \cdot \left(a \cdot y1 - c \cdot y0\right)\\ \mathbf{if}\;y4 \leq -4.4 \cdot 10^{+179}:\\ \;\;\;\;\left(c \cdot y4\right) \cdot \left(y \cdot y3 - t \cdot y2\right)\\ \mathbf{elif}\;y4 \leq -1.55 \cdot 10^{+139}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;y4 \leq -1.7 \cdot 10^{-44}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y4 \leq -1.24 \cdot 10^{-219}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y4 \leq 1.8 \cdot 10^{-274}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;y4 \leq 10^{-196}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y4 \leq 2.1 \cdot 10^{-25}:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y0 \cdot y2 - y \cdot i\right)\\ \mathbf{elif}\;y4 \leq 7 \cdot 10^{+66}:\\ \;\;\;\;y2 \cdot \left(k \cdot \left(y1 \cdot y4\right) - a \cdot \left(x \cdot y1\right)\right) - t \cdot \left(y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* (* z y3) (- (* a y1) (* c y0)))))
   (if (<= y4 -4.4e+179)
     (* (* c y4) (- (* y y3) (* t y2)))
     (if (<= y4 -1.55e+139)
       (* y1 (* y4 (- (* k y2) (* j y3))))
       (if (<= y4 -1.7e-44)
         t_1
         (if (<= y4 -1.24e-219)
           (* j (* x (- (* i y1) (* b y0))))
           (if (<= y4 1.8e-274)
             (* j (* y0 (- (* y3 y5) (* x b))))
             (if (<= y4 1e-196)
               t_1
               (if (<= y4 2.1e-25)
                 (* (* x c) (- (* y0 y2) (* y i)))
                 (if (<= y4 7e+66)
                   (-
                    (* y2 (- (* k (* y1 y4)) (* a (* x y1))))
                    (* t (* y2 (- (* c y4) (* a y5)))))
                   (* j (* t (- (* b y4) (* i 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 = (z * y3) * ((a * y1) - (c * y0));
	double tmp;
	if (y4 <= -4.4e+179) {
		tmp = (c * y4) * ((y * y3) - (t * y2));
	} else if (y4 <= -1.55e+139) {
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	} else if (y4 <= -1.7e-44) {
		tmp = t_1;
	} else if (y4 <= -1.24e-219) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (y4 <= 1.8e-274) {
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	} else if (y4 <= 1e-196) {
		tmp = t_1;
	} else if (y4 <= 2.1e-25) {
		tmp = (x * c) * ((y0 * y2) - (y * i));
	} else if (y4 <= 7e+66) {
		tmp = (y2 * ((k * (y1 * y4)) - (a * (x * y1)))) - (t * (y2 * ((c * y4) - (a * y5))));
	} else {
		tmp = j * (t * ((b * y4) - (i * 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 = (z * y3) * ((a * y1) - (c * y0))
    if (y4 <= (-4.4d+179)) then
        tmp = (c * y4) * ((y * y3) - (t * y2))
    else if (y4 <= (-1.55d+139)) then
        tmp = y1 * (y4 * ((k * y2) - (j * y3)))
    else if (y4 <= (-1.7d-44)) then
        tmp = t_1
    else if (y4 <= (-1.24d-219)) then
        tmp = j * (x * ((i * y1) - (b * y0)))
    else if (y4 <= 1.8d-274) then
        tmp = j * (y0 * ((y3 * y5) - (x * b)))
    else if (y4 <= 1d-196) then
        tmp = t_1
    else if (y4 <= 2.1d-25) then
        tmp = (x * c) * ((y0 * y2) - (y * i))
    else if (y4 <= 7d+66) then
        tmp = (y2 * ((k * (y1 * y4)) - (a * (x * y1)))) - (t * (y2 * ((c * y4) - (a * y5))))
    else
        tmp = j * (t * ((b * y4) - (i * 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 = (z * y3) * ((a * y1) - (c * y0));
	double tmp;
	if (y4 <= -4.4e+179) {
		tmp = (c * y4) * ((y * y3) - (t * y2));
	} else if (y4 <= -1.55e+139) {
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	} else if (y4 <= -1.7e-44) {
		tmp = t_1;
	} else if (y4 <= -1.24e-219) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (y4 <= 1.8e-274) {
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	} else if (y4 <= 1e-196) {
		tmp = t_1;
	} else if (y4 <= 2.1e-25) {
		tmp = (x * c) * ((y0 * y2) - (y * i));
	} else if (y4 <= 7e+66) {
		tmp = (y2 * ((k * (y1 * y4)) - (a * (x * y1)))) - (t * (y2 * ((c * y4) - (a * y5))));
	} else {
		tmp = j * (t * ((b * y4) - (i * y5)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (z * y3) * ((a * y1) - (c * y0))
	tmp = 0
	if y4 <= -4.4e+179:
		tmp = (c * y4) * ((y * y3) - (t * y2))
	elif y4 <= -1.55e+139:
		tmp = y1 * (y4 * ((k * y2) - (j * y3)))
	elif y4 <= -1.7e-44:
		tmp = t_1
	elif y4 <= -1.24e-219:
		tmp = j * (x * ((i * y1) - (b * y0)))
	elif y4 <= 1.8e-274:
		tmp = j * (y0 * ((y3 * y5) - (x * b)))
	elif y4 <= 1e-196:
		tmp = t_1
	elif y4 <= 2.1e-25:
		tmp = (x * c) * ((y0 * y2) - (y * i))
	elif y4 <= 7e+66:
		tmp = (y2 * ((k * (y1 * y4)) - (a * (x * y1)))) - (t * (y2 * ((c * y4) - (a * y5))))
	else:
		tmp = j * (t * ((b * y4) - (i * 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(Float64(z * y3) * Float64(Float64(a * y1) - Float64(c * y0)))
	tmp = 0.0
	if (y4 <= -4.4e+179)
		tmp = Float64(Float64(c * y4) * Float64(Float64(y * y3) - Float64(t * y2)));
	elseif (y4 <= -1.55e+139)
		tmp = Float64(y1 * Float64(y4 * Float64(Float64(k * y2) - Float64(j * y3))));
	elseif (y4 <= -1.7e-44)
		tmp = t_1;
	elseif (y4 <= -1.24e-219)
		tmp = Float64(j * Float64(x * Float64(Float64(i * y1) - Float64(b * y0))));
	elseif (y4 <= 1.8e-274)
		tmp = Float64(j * Float64(y0 * Float64(Float64(y3 * y5) - Float64(x * b))));
	elseif (y4 <= 1e-196)
		tmp = t_1;
	elseif (y4 <= 2.1e-25)
		tmp = Float64(Float64(x * c) * Float64(Float64(y0 * y2) - Float64(y * i)));
	elseif (y4 <= 7e+66)
		tmp = Float64(Float64(y2 * Float64(Float64(k * Float64(y1 * y4)) - Float64(a * Float64(x * y1)))) - Float64(t * Float64(y2 * Float64(Float64(c * y4) - Float64(a * y5)))));
	else
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * 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 = (z * y3) * ((a * y1) - (c * y0));
	tmp = 0.0;
	if (y4 <= -4.4e+179)
		tmp = (c * y4) * ((y * y3) - (t * y2));
	elseif (y4 <= -1.55e+139)
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	elseif (y4 <= -1.7e-44)
		tmp = t_1;
	elseif (y4 <= -1.24e-219)
		tmp = j * (x * ((i * y1) - (b * y0)));
	elseif (y4 <= 1.8e-274)
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	elseif (y4 <= 1e-196)
		tmp = t_1;
	elseif (y4 <= 2.1e-25)
		tmp = (x * c) * ((y0 * y2) - (y * i));
	elseif (y4 <= 7e+66)
		tmp = (y2 * ((k * (y1 * y4)) - (a * (x * y1)))) - (t * (y2 * ((c * y4) - (a * y5))));
	else
		tmp = j * (t * ((b * y4) - (i * 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[(N[(z * y3), $MachinePrecision] * N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y4, -4.4e+179], N[(N[(c * y4), $MachinePrecision] * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, -1.55e+139], N[(y1 * N[(y4 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, -1.7e-44], t$95$1, If[LessEqual[y4, -1.24e-219], N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, 1.8e-274], N[(j * N[(y0 * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, 1e-196], t$95$1, If[LessEqual[y4, 2.1e-25], N[(N[(x * c), $MachinePrecision] * N[(N[(y0 * y2), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, 7e+66], N[(N[(y2 * N[(N[(k * N[(y1 * y4), $MachinePrecision]), $MachinePrecision] - N[(a * N[(x * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(t * N[(y2 * N[(N[(c * y4), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]

Derivation

1. Split input into 8 regimes

2. if y4 < -4.4000000000000001e179

   1. Initial program 19.2%

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

   2. Taylor expanded in y4 around inf 73.4%

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

   3. Taylor expanded in c around -inf 70.1%

      \[\leadsto \color{blue}{-1 \cdot \left(c \cdot \left(y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)\right)} \]
   4. Step-by-step derivation

      1. mul-1-neg 70.1%

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

      2. associate-*r* 73.5%

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

      3. *-commutative 73.5%

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

      4. distribute-rgt-neg-in 73.5%

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

      5. *-commutative 73.5%

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

   5. Simplified 73.5%

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

   if -4.4000000000000001e179 < y4 < -1.55e139

   1. Initial program 30.0%

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

   2. Taylor expanded in y4 around inf 40.6%

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

   3. Taylor expanded in y1 around inf 80.5%

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

   if -1.55e139 < y4 < -1.70000000000000008e-44 or 1.79999999999999991e-274 < y4 < 1e-196

   1. Initial program 32.8%

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

   2. Taylor expanded in y3 around -inf 54.2%

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

   3. Taylor expanded in z around inf 53.0%

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

      1. associate-*r* 54.9%

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

      2. *-commutative 54.9%

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

      3. *-commutative 54.9%

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

   5. Simplified 54.9%

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

   if -1.70000000000000008e-44 < y4 < -1.24000000000000005e-219

   1. Initial program 29.0%

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

   2. Taylor expanded in j around inf 49.1%

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

      1. +-commutative 49.1%

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

      2. mul-1-neg 49.1%

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

      3. unsub-neg 49.1%

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

      4. *-commutative 49.1%

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

   4. Simplified 49.1%

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

   5. Taylor expanded in x around inf 46.4%

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

   if -1.24000000000000005e-219 < y4 < 1.79999999999999991e-274

   1. Initial program 29.8%

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

   2. Taylor expanded in j around inf 55.3%

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

      1. +-commutative 55.3%

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

      2. mul-1-neg 55.3%

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

      3. unsub-neg 55.3%

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

      4. *-commutative 55.3%

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

   4. Simplified 55.3%

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

   5. Taylor expanded in y0 around -inf 58.9%

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

      1. +-commutative 58.9%

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

      2. mul-1-neg 58.9%

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

      3. unsub-neg 58.9%

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

      4. *-commutative 58.9%

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

   7. Simplified 58.9%

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

   if 1e-196 < y4 < 2.10000000000000002e-25

   1. Initial program 31.2%

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

   2. Taylor expanded in c around inf 45.2%

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

   3. Taylor expanded in x around inf 49.1%

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

      1. associate-*r* 45.6%

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

      2. +-commutative 45.6%

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

      3. mul-1-neg 45.6%

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

      4. unsub-neg 45.6%

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

   5. Simplified 45.6%

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

   if 2.10000000000000002e-25 < y4 < 6.9999999999999994e66

   1. Initial program 41.4%

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

   2. Taylor expanded in y2 around inf 59.4%

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

   3. Taylor expanded in t around 0 63.9%

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

   4. Taylor expanded in y0 around 0 59.4%

      \[\leadsto \color{blue}{t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right) + y2 \cdot \left(-1 \cdot \left(a \cdot \left(x \cdot y1\right)\right) + k \cdot \left(y1 \cdot y4\right)\right)} \]

   if 6.9999999999999994e66 < y4

   1. Initial program 23.7%

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

   2. Taylor expanded in j around inf 42.3%

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

      1. +-commutative 42.3%

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

      2. mul-1-neg 42.3%

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

      3. unsub-neg 42.3%

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

      4. *-commutative 42.3%

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

   4. Simplified 42.3%

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

   5. Taylor expanded in t around inf 48.0%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]
3. Recombined 8 regimes into one program.

4. Final simplification 55.1%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y4 \leq -4.4 \cdot 10^{+179}:\\ \;\;\;\;\left(c \cdot y4\right) \cdot \left(y \cdot y3 - t \cdot y2\right)\\ \mathbf{elif}\;y4 \leq -1.55 \cdot 10^{+139}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;y4 \leq -1.7 \cdot 10^{-44}:\\ \;\;\;\;\left(z \cdot y3\right) \cdot \left(a \cdot y1 - c \cdot y0\right)\\ \mathbf{elif}\;y4 \leq -1.24 \cdot 10^{-219}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y4 \leq 1.8 \cdot 10^{-274}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;y4 \leq 10^{-196}:\\ \;\;\;\;\left(z \cdot y3\right) \cdot \left(a \cdot y1 - c \cdot y0\right)\\ \mathbf{elif}\;y4 \leq 2.1 \cdot 10^{-25}:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y0 \cdot y2 - y \cdot i\right)\\ \mathbf{elif}\;y4 \leq 7 \cdot 10^{+66}:\\ \;\;\;\;y2 \cdot \left(k \cdot \left(y1 \cdot y4\right) - a \cdot \left(x \cdot y1\right)\right) - t \cdot \left(y2 \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \end{array} \]

Alternative 8: 38.5% accurate, 2.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ t_2 := c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \mathbf{if}\;z \leq -1.05 \cdot 10^{+100}:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0 - t \cdot a\right)\right)\\ \mathbf{elif}\;z \leq 1.35 \cdot 10^{-165}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq 1.15 \cdot 10^{-99}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;z \leq 2.9 \cdot 10^{+175}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq 2.1 \cdot 10^{+260}:\\ \;\;\;\;c \cdot \left(i \cdot \left(z \cdot t - x \cdot y\right)\right)\\ \mathbf{elif}\;z \leq 3 \cdot 10^{+270}:\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;\left(z \cdot y3\right) \cdot \left(a \cdot y1 - c \cdot y0\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1
         (*
          j
          (-
           (- (* t (- (* b y4) (* i y5))) (* y3 (- (* y1 y4) (* y0 y5))))
           (* x (- (* b y0) (* i y1))))))
        (t_2 (* c (* y2 (- (* x y0) (* t y4))))))
   (if (<= z -1.05e+100)
     (* b (* z (- (* k y0) (* t a))))
     (if (<= z 1.35e-165)
       t_1
       (if (<= z 1.15e-99)
         t_2
         (if (<= z 2.9e+175)
           t_1
           (if (<= z 2.1e+260)
             (* c (* i (- (* z t) (* x y))))
             (if (<= z 3e+270) t_2 (* (* z y3) (- (* a y1) (* c y0)))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = j * (((t * ((b * y4) - (i * y5))) - (y3 * ((y1 * y4) - (y0 * y5)))) - (x * ((b * y0) - (i * y1))));
	double t_2 = c * (y2 * ((x * y0) - (t * y4)));
	double tmp;
	if (z <= -1.05e+100) {
		tmp = b * (z * ((k * y0) - (t * a)));
	} else if (z <= 1.35e-165) {
		tmp = t_1;
	} else if (z <= 1.15e-99) {
		tmp = t_2;
	} else if (z <= 2.9e+175) {
		tmp = t_1;
	} else if (z <= 2.1e+260) {
		tmp = c * (i * ((z * t) - (x * y)));
	} else if (z <= 3e+270) {
		tmp = t_2;
	} else {
		tmp = (z * y3) * ((a * y1) - (c * y0));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = j * (((t * ((b * y4) - (i * y5))) - (y3 * ((y1 * y4) - (y0 * y5)))) - (x * ((b * y0) - (i * y1))))
    t_2 = c * (y2 * ((x * y0) - (t * y4)))
    if (z <= (-1.05d+100)) then
        tmp = b * (z * ((k * y0) - (t * a)))
    else if (z <= 1.35d-165) then
        tmp = t_1
    else if (z <= 1.15d-99) then
        tmp = t_2
    else if (z <= 2.9d+175) then
        tmp = t_1
    else if (z <= 2.1d+260) then
        tmp = c * (i * ((z * t) - (x * y)))
    else if (z <= 3d+270) then
        tmp = t_2
    else
        tmp = (z * y3) * ((a * y1) - (c * y0))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = j * (((t * ((b * y4) - (i * y5))) - (y3 * ((y1 * y4) - (y0 * y5)))) - (x * ((b * y0) - (i * y1))));
	double t_2 = c * (y2 * ((x * y0) - (t * y4)));
	double tmp;
	if (z <= -1.05e+100) {
		tmp = b * (z * ((k * y0) - (t * a)));
	} else if (z <= 1.35e-165) {
		tmp = t_1;
	} else if (z <= 1.15e-99) {
		tmp = t_2;
	} else if (z <= 2.9e+175) {
		tmp = t_1;
	} else if (z <= 2.1e+260) {
		tmp = c * (i * ((z * t) - (x * y)));
	} else if (z <= 3e+270) {
		tmp = t_2;
	} else {
		tmp = (z * y3) * ((a * y1) - (c * y0));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = j * (((t * ((b * y4) - (i * y5))) - (y3 * ((y1 * y4) - (y0 * y5)))) - (x * ((b * y0) - (i * y1))))
	t_2 = c * (y2 * ((x * y0) - (t * y4)))
	tmp = 0
	if z <= -1.05e+100:
		tmp = b * (z * ((k * y0) - (t * a)))
	elif z <= 1.35e-165:
		tmp = t_1
	elif z <= 1.15e-99:
		tmp = t_2
	elif z <= 2.9e+175:
		tmp = t_1
	elif z <= 2.1e+260:
		tmp = c * (i * ((z * t) - (x * y)))
	elif z <= 3e+270:
		tmp = t_2
	else:
		tmp = (z * y3) * ((a * y1) - (c * y0))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(j * Float64(Float64(Float64(t * Float64(Float64(b * y4) - Float64(i * y5))) - Float64(y3 * Float64(Float64(y1 * y4) - Float64(y0 * y5)))) - Float64(x * Float64(Float64(b * y0) - Float64(i * y1)))))
	t_2 = Float64(c * Float64(y2 * Float64(Float64(x * y0) - Float64(t * y4))))
	tmp = 0.0
	if (z <= -1.05e+100)
		tmp = Float64(b * Float64(z * Float64(Float64(k * y0) - Float64(t * a))));
	elseif (z <= 1.35e-165)
		tmp = t_1;
	elseif (z <= 1.15e-99)
		tmp = t_2;
	elseif (z <= 2.9e+175)
		tmp = t_1;
	elseif (z <= 2.1e+260)
		tmp = Float64(c * Float64(i * Float64(Float64(z * t) - Float64(x * y))));
	elseif (z <= 3e+270)
		tmp = t_2;
	else
		tmp = Float64(Float64(z * y3) * Float64(Float64(a * y1) - Float64(c * y0)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = j * (((t * ((b * y4) - (i * y5))) - (y3 * ((y1 * y4) - (y0 * y5)))) - (x * ((b * y0) - (i * y1))));
	t_2 = c * (y2 * ((x * y0) - (t * y4)));
	tmp = 0.0;
	if (z <= -1.05e+100)
		tmp = b * (z * ((k * y0) - (t * a)));
	elseif (z <= 1.35e-165)
		tmp = t_1;
	elseif (z <= 1.15e-99)
		tmp = t_2;
	elseif (z <= 2.9e+175)
		tmp = t_1;
	elseif (z <= 2.1e+260)
		tmp = c * (i * ((z * t) - (x * y)));
	elseif (z <= 3e+270)
		tmp = t_2;
	else
		tmp = (z * y3) * ((a * y1) - (c * y0));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(j * N[(N[(N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(y3 * N[(N[(y1 * y4), $MachinePrecision] - N[(y0 * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(x * N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(c * N[(y2 * N[(N[(x * y0), $MachinePrecision] - N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -1.05e+100], N[(b * N[(z * N[(N[(k * y0), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.35e-165], t$95$1, If[LessEqual[z, 1.15e-99], t$95$2, If[LessEqual[z, 2.9e+175], t$95$1, If[LessEqual[z, 2.1e+260], N[(c * N[(i * N[(N[(z * t), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 3e+270], t$95$2, N[(N[(z * y3), $MachinePrecision] * N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]

Derivation

1. Split input into 5 regimes

2. if z < -1.0499999999999999e100

   1. Initial program 27.7%

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

   2. Taylor expanded in b around inf 40.1%

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

   3. Taylor expanded in z around inf 56.0%

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

      1. distribute-lft-out-- 56.0%

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

      2. *-commutative 56.0%

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

      3. *-commutative 56.0%

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

   5. Simplified 56.0%

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

   if -1.0499999999999999e100 < z < 1.3499999999999999e-165 or 1.1499999999999999e-99 < z < 2.9e175

   1. Initial program 30.9%

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

   2. Taylor expanded in j around inf 48.9%

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

      1. +-commutative 48.9%

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

      2. mul-1-neg 48.9%

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

      3. unsub-neg 48.9%

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

      4. *-commutative 48.9%

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

   4. Simplified 48.9%

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

   if 1.3499999999999999e-165 < z < 1.1499999999999999e-99 or 2.10000000000000012e260 < z < 3.00000000000000014e270

   1. Initial program 27.7%

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

   2. Taylor expanded in c around inf 50.4%

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

   3. Taylor expanded in y2 around inf 59.7%

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

   if 2.9e175 < z < 2.10000000000000012e260

   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. Taylor expanded in c around inf 55.6%

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

   3. Taylor expanded in i around inf 66.8%

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

      1. neg-mul-1 66.8%

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

      2. distribute-rgt-neg-in 66.8%

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

   5. Simplified 66.8%

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

   if 3.00000000000000014e270 < z

   1. Initial program 30.0%

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

   2. Taylor expanded in y3 around -inf 40.0%

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

   3. Taylor expanded in z around inf 80.3%

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

      1. associate-*r* 80.3%

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

      2. *-commutative 80.3%

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

      3. *-commutative 80.3%

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

   5. Simplified 80.3%

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

4. Final simplification 53.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -1.05 \cdot 10^{+100}:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0 - t \cdot a\right)\right)\\ \mathbf{elif}\;z \leq 1.35 \cdot 10^{-165}:\\ \;\;\;\;j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq 1.15 \cdot 10^{-99}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 2.9 \cdot 10^{+175}:\\ \;\;\;\;j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq 2.1 \cdot 10^{+260}:\\ \;\;\;\;c \cdot \left(i \cdot \left(z \cdot t - x \cdot y\right)\right)\\ \mathbf{elif}\;z \leq 3 \cdot 10^{+270}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(z \cdot y3\right) \cdot \left(a \cdot y1 - c \cdot y0\right)\\ \end{array} \]

Alternative 9: 33.0% accurate, 2.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -1.5 \cdot 10^{+100}:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0 - t \cdot a\right)\right)\\ \mathbf{elif}\;z \leq -1.54 \cdot 10^{-105}:\\ \;\;\;\;y2 \cdot \left(x \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq 2.6 \cdot 10^{-177}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;z \leq 2.5 \cdot 10^{-92}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 8.5 \cdot 10^{+57}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;z \leq 1.06 \cdot 10^{+150}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i - y3 \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 2.25 \cdot 10^{+176}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3 - t \cdot i\right)\right)\\ \mathbf{elif}\;z \leq 1.8 \cdot 10^{+256}:\\ \;\;\;\;c \cdot \left(i \cdot \left(z \cdot t - x \cdot y\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(z \cdot y3\right) \cdot \left(a \cdot y1 - c \cdot y0\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= z -1.5e+100)
   (* b (* z (- (* k y0) (* t a))))
   (if (<= z -1.54e-105)
     (* y2 (* x (- (* c y0) (* a y1))))
     (if (<= z 2.6e-177)
       (*
        b
        (+
         (+ (* a (- (* x y) (* z t))) (* y4 (- (* t j) (* y k))))
         (* y0 (- (* z k) (* x j)))))
       (if (<= z 2.5e-92)
         (* c (* y2 (- (* x y0) (* t y4))))
         (if (<= z 8.5e+57)
           (* j (* y0 (- (* y3 y5) (* x b))))
           (if (<= z 1.06e+150)
             (* j (* y1 (- (* x i) (* y3 y4))))
             (if (<= z 2.25e+176)
               (* j (* y5 (- (* y0 y3) (* t i))))
               (if (<= z 1.8e+256)
                 (* c (* i (- (* z t) (* x y))))
                 (* (* z y3) (- (* a y1) (* c y0))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -1.5e+100) {
		tmp = b * (z * ((k * y0) - (t * a)));
	} else if (z <= -1.54e-105) {
		tmp = y2 * (x * ((c * y0) - (a * y1)));
	} else if (z <= 2.6e-177) {
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))));
	} else if (z <= 2.5e-92) {
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	} else if (z <= 8.5e+57) {
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	} else if (z <= 1.06e+150) {
		tmp = j * (y1 * ((x * i) - (y3 * y4)));
	} else if (z <= 2.25e+176) {
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	} else if (z <= 1.8e+256) {
		tmp = c * (i * ((z * t) - (x * y)));
	} else {
		tmp = (z * y3) * ((a * y1) - (c * y0));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (z <= (-1.5d+100)) then
        tmp = b * (z * ((k * y0) - (t * a)))
    else if (z <= (-1.54d-105)) then
        tmp = y2 * (x * ((c * y0) - (a * y1)))
    else if (z <= 2.6d-177) then
        tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))))
    else if (z <= 2.5d-92) then
        tmp = c * (y2 * ((x * y0) - (t * y4)))
    else if (z <= 8.5d+57) then
        tmp = j * (y0 * ((y3 * y5) - (x * b)))
    else if (z <= 1.06d+150) then
        tmp = j * (y1 * ((x * i) - (y3 * y4)))
    else if (z <= 2.25d+176) then
        tmp = j * (y5 * ((y0 * y3) - (t * i)))
    else if (z <= 1.8d+256) then
        tmp = c * (i * ((z * t) - (x * y)))
    else
        tmp = (z * y3) * ((a * y1) - (c * y0))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (z <= -1.5e+100) {
		tmp = b * (z * ((k * y0) - (t * a)));
	} else if (z <= -1.54e-105) {
		tmp = y2 * (x * ((c * y0) - (a * y1)));
	} else if (z <= 2.6e-177) {
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))));
	} else if (z <= 2.5e-92) {
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	} else if (z <= 8.5e+57) {
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	} else if (z <= 1.06e+150) {
		tmp = j * (y1 * ((x * i) - (y3 * y4)));
	} else if (z <= 2.25e+176) {
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	} else if (z <= 1.8e+256) {
		tmp = c * (i * ((z * t) - (x * y)));
	} else {
		tmp = (z * y3) * ((a * y1) - (c * y0));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if z <= -1.5e+100:
		tmp = b * (z * ((k * y0) - (t * a)))
	elif z <= -1.54e-105:
		tmp = y2 * (x * ((c * y0) - (a * y1)))
	elif z <= 2.6e-177:
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))))
	elif z <= 2.5e-92:
		tmp = c * (y2 * ((x * y0) - (t * y4)))
	elif z <= 8.5e+57:
		tmp = j * (y0 * ((y3 * y5) - (x * b)))
	elif z <= 1.06e+150:
		tmp = j * (y1 * ((x * i) - (y3 * y4)))
	elif z <= 2.25e+176:
		tmp = j * (y5 * ((y0 * y3) - (t * i)))
	elif z <= 1.8e+256:
		tmp = c * (i * ((z * t) - (x * y)))
	else:
		tmp = (z * y3) * ((a * y1) - (c * y0))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (z <= -1.5e+100)
		tmp = Float64(b * Float64(z * Float64(Float64(k * y0) - Float64(t * a))));
	elseif (z <= -1.54e-105)
		tmp = Float64(y2 * Float64(x * Float64(Float64(c * y0) - Float64(a * y1))));
	elseif (z <= 2.6e-177)
		tmp = Float64(b * Float64(Float64(Float64(a * Float64(Float64(x * y) - Float64(z * t))) + Float64(y4 * Float64(Float64(t * j) - Float64(y * k)))) + Float64(y0 * Float64(Float64(z * k) - Float64(x * j)))));
	elseif (z <= 2.5e-92)
		tmp = Float64(c * Float64(y2 * Float64(Float64(x * y0) - Float64(t * y4))));
	elseif (z <= 8.5e+57)
		tmp = Float64(j * Float64(y0 * Float64(Float64(y3 * y5) - Float64(x * b))));
	elseif (z <= 1.06e+150)
		tmp = Float64(j * Float64(y1 * Float64(Float64(x * i) - Float64(y3 * y4))));
	elseif (z <= 2.25e+176)
		tmp = Float64(j * Float64(y5 * Float64(Float64(y0 * y3) - Float64(t * i))));
	elseif (z <= 1.8e+256)
		tmp = Float64(c * Float64(i * Float64(Float64(z * t) - Float64(x * y))));
	else
		tmp = Float64(Float64(z * y3) * Float64(Float64(a * y1) - Float64(c * y0)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (z <= -1.5e+100)
		tmp = b * (z * ((k * y0) - (t * a)));
	elseif (z <= -1.54e-105)
		tmp = y2 * (x * ((c * y0) - (a * y1)));
	elseif (z <= 2.6e-177)
		tmp = b * (((a * ((x * y) - (z * t))) + (y4 * ((t * j) - (y * k)))) + (y0 * ((z * k) - (x * j))));
	elseif (z <= 2.5e-92)
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	elseif (z <= 8.5e+57)
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	elseif (z <= 1.06e+150)
		tmp = j * (y1 * ((x * i) - (y3 * y4)));
	elseif (z <= 2.25e+176)
		tmp = j * (y5 * ((y0 * y3) - (t * i)));
	elseif (z <= 1.8e+256)
		tmp = c * (i * ((z * t) - (x * y)));
	else
		tmp = (z * y3) * ((a * y1) - (c * y0));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[z, -1.5e+100], N[(b * N[(z * N[(N[(k * y0), $MachinePrecision] - N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -1.54e-105], N[(y2 * N[(x * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 2.6e-177], N[(b * N[(N[(N[(a * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y4 * N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(N[(z * k), $MachinePrecision] - N[(x * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 2.5e-92], N[(c * N[(y2 * N[(N[(x * y0), $MachinePrecision] - N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 8.5e+57], N[(j * N[(y0 * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.06e+150], N[(j * N[(y1 * N[(N[(x * i), $MachinePrecision] - N[(y3 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 2.25e+176], N[(j * N[(y5 * N[(N[(y0 * y3), $MachinePrecision] - N[(t * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.8e+256], N[(c * N[(i * N[(N[(z * t), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(z * y3), $MachinePrecision] * N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]

Derivation

1. Split input into 9 regimes

2. if z < -1.49999999999999993e100

   1. Initial program 28.4%

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

   2. Taylor expanded in b around inf 41.1%

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

   3. Taylor expanded in z around inf 54.9%

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

      1. distribute-lft-out-- 54.9%

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

      2. *-commutative 54.9%

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

      3. *-commutative 54.9%

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

   5. Simplified 54.9%

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

   if -1.49999999999999993e100 < z < -1.5399999999999999e-105

   1. Initial program 28.1%

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

   2. Taylor expanded in y2 around inf 54.1%

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

   3. Taylor expanded in x around inf 45.2%

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

   if -1.5399999999999999e-105 < z < 2.6000000000000001e-177

   1. Initial program 41.2%

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

   2. Taylor expanded in b around inf 50.7%

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

   if 2.6000000000000001e-177 < z < 2.50000000000000006e-92

   1. Initial program 16.4%

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

   2. Taylor expanded in c around inf 44.3%

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

   3. Taylor expanded in y2 around inf 56.6%

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

   if 2.50000000000000006e-92 < z < 8.5000000000000001e57

   1. Initial program 30.8%

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

   2. Taylor expanded in j around inf 57.8%

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

      1. +-commutative 57.8%

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

      2. mul-1-neg 57.8%

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

      3. unsub-neg 57.8%

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

      4. *-commutative 57.8%

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

   4. Simplified 57.8%

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

   5. Taylor expanded in y0 around -inf 55.0%

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

      1. +-commutative 55.0%

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

      2. mul-1-neg 55.0%

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

      3. unsub-neg 55.0%

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

      4. *-commutative 55.0%

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

   7. Simplified 55.0%

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

   if 8.5000000000000001e57 < z < 1.06000000000000006e150

   1. Initial program 19.2%

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

   2. Taylor expanded in j around inf 32.5%

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

      1. +-commutative 32.5%

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

      2. mul-1-neg 32.5%

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

      3. unsub-neg 32.5%

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

      4. *-commutative 32.5%

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

   4. Simplified 32.5%

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

   5. Taylor expanded in y1 around -inf 44.7%

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

      1. +-commutative 44.7%

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

      2. mul-1-neg 44.7%

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

      3. sub-neg 44.7%

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

      4. *-commutative 44.7%

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

   7. Simplified 44.7%

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

   if 1.06000000000000006e150 < z < 2.25000000000000002e176

   1. Initial program 10.0%

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

   2. Taylor expanded in j around inf 70.1%

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

      1. +-commutative 70.1%

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

      2. mul-1-neg 70.1%

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

      3. unsub-neg 70.1%

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

      4. *-commutative 70.1%

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

   4. Simplified 70.1%

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

   5. Taylor expanded in y5 around inf 60.9%

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

      1. distribute-lft-out-- 60.9%

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

      2. *-commutative 60.9%

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

   7. Simplified 60.9%

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

   if 2.25000000000000002e176 < z < 1.79999999999999985e256

   1. Initial program 17.6%

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

   2. Taylor expanded in c around inf 58.8%

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

   3. Taylor expanded in i around inf 70.7%

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

      1. neg-mul-1 70.7%

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

      2. distribute-rgt-neg-in 70.7%

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

   5. Simplified 70.7%

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

   if 1.79999999999999985e256 < z

   1. Initial program 35.7%

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

   2. Taylor expanded in y3 around -inf 42.9%

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

   3. Taylor expanded in z around inf 64.7%

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

      1. associate-*r* 64.7%

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

      2. *-commutative 64.7%

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

      3. *-commutative 64.7%

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

   5. Simplified 64.7%

      \[\leadsto -1 \cdot \color{blue}{\left(\left(y3 \cdot z\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right)} \]
3. Recombined 9 regimes into one program.

4. Final simplification 53.6%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -1.5 \cdot 10^{+100}:\\ \;\;\;\;b \cdot \left(z \cdot \left(k \cdot y0 - t \cdot a\right)\right)\\ \mathbf{elif}\;z \leq -1.54 \cdot 10^{-105}:\\ \;\;\;\;y2 \cdot \left(x \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;z \leq 2.6 \cdot 10^{-177}:\\ \;\;\;\;b \cdot \left(\left(a \cdot \left(x \cdot y - z \cdot t\right) + y4 \cdot \left(t \cdot j - y \cdot k\right)\right) + y0 \cdot \left(z \cdot k - x \cdot j\right)\right)\\ \mathbf{elif}\;z \leq 2.5 \cdot 10^{-92}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 8.5 \cdot 10^{+57}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;z \leq 1.06 \cdot 10^{+150}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i - y3 \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 2.25 \cdot 10^{+176}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(y0 \cdot y3 - t \cdot i\right)\right)\\ \mathbf{elif}\;z \leq 1.8 \cdot 10^{+256}:\\ \;\;\;\;c \cdot \left(i \cdot \left(z \cdot t - x \cdot y\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(z \cdot y3\right) \cdot \left(a \cdot y1 - c \cdot y0\right)\\ \end{array} \]

Alternative 10: 32.5% accurate, 2.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{if}\;y0 \leq -1.55 \cdot 10^{+127}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y0 \leq -1.65 \cdot 10^{-8}:\\ \;\;\;\;y2 \cdot \left(x \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;y0 \leq -5.5 \cdot 10^{-68}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;y0 \leq -1.4 \cdot 10^{-104}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i - y3 \cdot y4\right)\right)\\ \mathbf{elif}\;y0 \leq -4.4 \cdot 10^{-142}:\\ \;\;\;\;i \cdot \left(-t \cdot \left(j \cdot y5\right)\right)\\ \mathbf{elif}\;y0 \leq 1.15 \cdot 10^{-279}:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;y0 \leq 4.1 \cdot 10^{-160}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;y0 \leq 10^{-78}:\\ \;\;\;\;c \cdot \left(y \cdot \left(y3 \cdot y4 - x \cdot i\right)\right)\\ \mathbf{elif}\;y0 \leq 5.5 \cdot 10^{-5}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;y0 \leq 2.2 \cdot 10^{+111}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y0 \leq 3 \cdot 10^{+224}:\\ \;\;\;\;y2 \cdot \left(y0 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* j (* y0 (- (* y3 y5) (* x b))))))
   (if (<= y0 -1.55e+127)
     t_1
     (if (<= y0 -1.65e-8)
       (* y2 (* x (- (* c y0) (* a y1))))
       (if (<= y0 -5.5e-68)
         (* j (* t (- (* b y4) (* i y5))))
         (if (<= y0 -1.4e-104)
           (* j (* y1 (- (* x i) (* y3 y4))))
           (if (<= y0 -4.4e-142)
             (* i (- (* t (* j y5))))
             (if (<= y0 1.15e-279)
               (* t (* y2 (- (* a y5) (* c y4))))
               (if (<= y0 4.1e-160)
                 (* a (* b (- (* x y) (* z t))))
                 (if (<= y0 1e-78)
                   (* c (* y (- (* y3 y4) (* x i))))
                   (if (<= y0 5.5e-5)
                     (* y1 (* y4 (- (* k y2) (* j y3))))
                     (if (<= y0 2.2e+111)
                       (* j (* x (- (* i y1) (* b y0))))
                       (if (<= y0 3e+224)
                         (* y2 (* y0 (- (* x c) (* k y5))))
                         t_1)))))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = j * (y0 * ((y3 * y5) - (x * b)));
	double tmp;
	if (y0 <= -1.55e+127) {
		tmp = t_1;
	} else if (y0 <= -1.65e-8) {
		tmp = y2 * (x * ((c * y0) - (a * y1)));
	} else if (y0 <= -5.5e-68) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (y0 <= -1.4e-104) {
		tmp = j * (y1 * ((x * i) - (y3 * y4)));
	} else if (y0 <= -4.4e-142) {
		tmp = i * -(t * (j * y5));
	} else if (y0 <= 1.15e-279) {
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	} else if (y0 <= 4.1e-160) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (y0 <= 1e-78) {
		tmp = c * (y * ((y3 * y4) - (x * i)));
	} else if (y0 <= 5.5e-5) {
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	} else if (y0 <= 2.2e+111) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (y0 <= 3e+224) {
		tmp = y2 * (y0 * ((x * c) - (k * y5)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = j * (y0 * ((y3 * y5) - (x * b)))
    if (y0 <= (-1.55d+127)) then
        tmp = t_1
    else if (y0 <= (-1.65d-8)) then
        tmp = y2 * (x * ((c * y0) - (a * y1)))
    else if (y0 <= (-5.5d-68)) then
        tmp = j * (t * ((b * y4) - (i * y5)))
    else if (y0 <= (-1.4d-104)) then
        tmp = j * (y1 * ((x * i) - (y3 * y4)))
    else if (y0 <= (-4.4d-142)) then
        tmp = i * -(t * (j * y5))
    else if (y0 <= 1.15d-279) then
        tmp = t * (y2 * ((a * y5) - (c * y4)))
    else if (y0 <= 4.1d-160) then
        tmp = a * (b * ((x * y) - (z * t)))
    else if (y0 <= 1d-78) then
        tmp = c * (y * ((y3 * y4) - (x * i)))
    else if (y0 <= 5.5d-5) then
        tmp = y1 * (y4 * ((k * y2) - (j * y3)))
    else if (y0 <= 2.2d+111) then
        tmp = j * (x * ((i * y1) - (b * y0)))
    else if (y0 <= 3d+224) then
        tmp = y2 * (y0 * ((x * c) - (k * y5)))
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = j * (y0 * ((y3 * y5) - (x * b)));
	double tmp;
	if (y0 <= -1.55e+127) {
		tmp = t_1;
	} else if (y0 <= -1.65e-8) {
		tmp = y2 * (x * ((c * y0) - (a * y1)));
	} else if (y0 <= -5.5e-68) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (y0 <= -1.4e-104) {
		tmp = j * (y1 * ((x * i) - (y3 * y4)));
	} else if (y0 <= -4.4e-142) {
		tmp = i * -(t * (j * y5));
	} else if (y0 <= 1.15e-279) {
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	} else if (y0 <= 4.1e-160) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (y0 <= 1e-78) {
		tmp = c * (y * ((y3 * y4) - (x * i)));
	} else if (y0 <= 5.5e-5) {
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	} else if (y0 <= 2.2e+111) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (y0 <= 3e+224) {
		tmp = y2 * (y0 * ((x * c) - (k * y5)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = j * (y0 * ((y3 * y5) - (x * b)))
	tmp = 0
	if y0 <= -1.55e+127:
		tmp = t_1
	elif y0 <= -1.65e-8:
		tmp = y2 * (x * ((c * y0) - (a * y1)))
	elif y0 <= -5.5e-68:
		tmp = j * (t * ((b * y4) - (i * y5)))
	elif y0 <= -1.4e-104:
		tmp = j * (y1 * ((x * i) - (y3 * y4)))
	elif y0 <= -4.4e-142:
		tmp = i * -(t * (j * y5))
	elif y0 <= 1.15e-279:
		tmp = t * (y2 * ((a * y5) - (c * y4)))
	elif y0 <= 4.1e-160:
		tmp = a * (b * ((x * y) - (z * t)))
	elif y0 <= 1e-78:
		tmp = c * (y * ((y3 * y4) - (x * i)))
	elif y0 <= 5.5e-5:
		tmp = y1 * (y4 * ((k * y2) - (j * y3)))
	elif y0 <= 2.2e+111:
		tmp = j * (x * ((i * y1) - (b * y0)))
	elif y0 <= 3e+224:
		tmp = y2 * (y0 * ((x * c) - (k * y5)))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(j * Float64(y0 * Float64(Float64(y3 * y5) - Float64(x * b))))
	tmp = 0.0
	if (y0 <= -1.55e+127)
		tmp = t_1;
	elseif (y0 <= -1.65e-8)
		tmp = Float64(y2 * Float64(x * Float64(Float64(c * y0) - Float64(a * y1))));
	elseif (y0 <= -5.5e-68)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))));
	elseif (y0 <= -1.4e-104)
		tmp = Float64(j * Float64(y1 * Float64(Float64(x * i) - Float64(y3 * y4))));
	elseif (y0 <= -4.4e-142)
		tmp = Float64(i * Float64(-Float64(t * Float64(j * y5))));
	elseif (y0 <= 1.15e-279)
		tmp = Float64(t * Float64(y2 * Float64(Float64(a * y5) - Float64(c * y4))));
	elseif (y0 <= 4.1e-160)
		tmp = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))));
	elseif (y0 <= 1e-78)
		tmp = Float64(c * Float64(y * Float64(Float64(y3 * y4) - Float64(x * i))));
	elseif (y0 <= 5.5e-5)
		tmp = Float64(y1 * Float64(y4 * Float64(Float64(k * y2) - Float64(j * y3))));
	elseif (y0 <= 2.2e+111)
		tmp = Float64(j * Float64(x * Float64(Float64(i * y1) - Float64(b * y0))));
	elseif (y0 <= 3e+224)
		tmp = Float64(y2 * Float64(y0 * Float64(Float64(x * c) - Float64(k * y5))));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = j * (y0 * ((y3 * y5) - (x * b)));
	tmp = 0.0;
	if (y0 <= -1.55e+127)
		tmp = t_1;
	elseif (y0 <= -1.65e-8)
		tmp = y2 * (x * ((c * y0) - (a * y1)));
	elseif (y0 <= -5.5e-68)
		tmp = j * (t * ((b * y4) - (i * y5)));
	elseif (y0 <= -1.4e-104)
		tmp = j * (y1 * ((x * i) - (y3 * y4)));
	elseif (y0 <= -4.4e-142)
		tmp = i * -(t * (j * y5));
	elseif (y0 <= 1.15e-279)
		tmp = t * (y2 * ((a * y5) - (c * y4)));
	elseif (y0 <= 4.1e-160)
		tmp = a * (b * ((x * y) - (z * t)));
	elseif (y0 <= 1e-78)
		tmp = c * (y * ((y3 * y4) - (x * i)));
	elseif (y0 <= 5.5e-5)
		tmp = y1 * (y4 * ((k * y2) - (j * y3)));
	elseif (y0 <= 2.2e+111)
		tmp = j * (x * ((i * y1) - (b * y0)));
	elseif (y0 <= 3e+224)
		tmp = y2 * (y0 * ((x * c) - (k * y5)));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(j * N[(y0 * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y0, -1.55e+127], t$95$1, If[LessEqual[y0, -1.65e-8], N[(y2 * N[(x * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, -5.5e-68], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, -1.4e-104], N[(j * N[(y1 * N[(N[(x * i), $MachinePrecision] - N[(y3 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, -4.4e-142], N[(i * (-N[(t * N[(j * y5), $MachinePrecision]), $MachinePrecision])), $MachinePrecision], If[LessEqual[y0, 1.15e-279], N[(t * N[(y2 * N[(N[(a * y5), $MachinePrecision] - N[(c * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 4.1e-160], N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 1e-78], N[(c * N[(y * N[(N[(y3 * y4), $MachinePrecision] - N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 5.5e-5], N[(y1 * N[(y4 * N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 2.2e+111], N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, 3e+224], N[(y2 * N[(y0 * N[(N[(x * c), $MachinePrecision] - N[(k * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]]]]]]]

Derivation

1. Split input into 11 regimes

2. if y0 < -1.5500000000000001e127 or 3.0000000000000001e224 < y0

   1. Initial program 25.0%

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

   2. Taylor expanded in j around inf 47.5%

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

      1. +-commutative 47.5%

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

      2. mul-1-neg 47.5%

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

      3. unsub-neg 47.5%

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

      4. *-commutative 47.5%

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

   4. Simplified 47.5%

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

   5. Taylor expanded in y0 around -inf 65.1%

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

      1. +-commutative 65.1%

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

      2. mul-1-neg 65.1%

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

      3. unsub-neg 65.1%

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

      4. *-commutative 65.1%

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

   7. Simplified 65.1%

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

   if -1.5500000000000001e127 < y0 < -1.64999999999999989e-8

   1. Initial program 35.0%

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

   2. Taylor expanded in y2 around inf 50.5%

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

   3. Taylor expanded in x around inf 54.9%

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

   if -1.64999999999999989e-8 < y0 < -5.5000000000000003e-68

   1. Initial program 31.3%

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

   2. Taylor expanded in j around inf 56.7%

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

      1. +-commutative 56.7%

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

      2. mul-1-neg 56.7%

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

      3. unsub-neg 56.7%

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

      4. *-commutative 56.7%

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

   4. Simplified 56.7%

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

   5. Taylor expanded in t around inf 51.3%

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

   if -5.5000000000000003e-68 < y0 < -1.4e-104

   1. Initial program 20.0%

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

   2. Taylor expanded in j around inf 60.0%

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

      1. +-commutative 60.0%

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

      2. mul-1-neg 60.0%

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

      3. unsub-neg 60.0%

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

      4. *-commutative 60.0%

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

   4. Simplified 60.0%

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

   5. Taylor expanded in y1 around -inf 100.0%

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

      1. +-commutative 100.0%

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

      2. mul-1-neg 100.0%

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

      3. sub-neg 100.0%

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

      4. *-commutative 100.0%

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

   7. Simplified 100.0%

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

   if -1.4e-104 < y0 < -4.40000000000000033e-142

   1. Initial program 20.0%

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

   2. Taylor expanded in j around inf 60.0%

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

      1. +-commutative 60.0%

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

      2. mul-1-neg 60.0%

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

      3. unsub-neg 60.0%

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

      4. *-commutative 60.0%

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

   4. Simplified 60.0%

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

   5. Taylor expanded in t around inf 50.6%

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

   6. Taylor expanded in b around 0 51.0%

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

      1. associate-*r* 51.0%

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

      2. neg-mul-1 51.0%

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

   8. Simplified 51.0%

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

   9. Taylor expanded in j around 0 51.0%

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

       1. mul-1-neg 51.0%

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

       2. distribute-rgt-neg-in 51.0%

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

       3. *-commutative 51.0%

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

       4. associate-*l* 70.4%

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

   11. Simplified 70.4%

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

   if -4.40000000000000033e-142 < y0 < 1.14999999999999998e-279

   1. Initial program 29.0%

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

   2. Taylor expanded in y2 around inf 37.7%

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

   3. Taylor expanded in t around inf 48.3%

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

   if 1.14999999999999998e-279 < y0 < 4.10000000000000002e-160

   1. Initial program 29.0%

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

   2. Taylor expanded in b around inf 24.7%

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

   3. Taylor expanded in a around inf 39.3%

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

   if 4.10000000000000002e-160 < y0 < 9.99999999999999999e-79

   1. Initial program 37.2%

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

   2. Taylor expanded in c around inf 32.5%

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

   3. Taylor expanded in y around inf 38.2%

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

      1. *-commutative 38.2%

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

      2. cancel-sign-sub-inv 38.2%

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

      3. metadata-eval 38.2%

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

      4. *-lft-identity 38.2%

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

      5. +-commutative 38.2%

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

      6. mul-1-neg 38.2%

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

      7. unsub-neg 38.2%

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

      8. *-commutative 38.2%

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

   5. Simplified 38.2%

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

   if 9.99999999999999999e-79 < y0 < 5.5000000000000002e-5

   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. Taylor expanded in y4 around inf 39.3%

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

   3. Taylor expanded in y1 around inf 39.7%

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

   if 5.5000000000000002e-5 < y0 < 2.19999999999999999e111

   1. Initial program 45.8%

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

   2. Taylor expanded in j around inf 59.1%

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

      1. +-commutative 59.1%

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

      2. mul-1-neg 59.1%

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

      3. unsub-neg 59.1%

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

      4. *-commutative 59.1%

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

   4. Simplified 59.1%

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

   5. Taylor expanded in x around inf 59.1%

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

   if 2.19999999999999999e111 < y0 < 3.0000000000000001e224

   1. Initial program 13.0%

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

   2. Taylor expanded in y2 around inf 52.5%

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

   3. Taylor expanded in y0 around inf 61.3%

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

      1. +-commutative 61.3%

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

      2. mul-1-neg 61.3%

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

      3. unsub-neg 61.3%

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

      4. *-commutative 61.3%

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

      5. *-commutative 61.3%

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

   5. Simplified 61.3%

      \[\leadsto y2 \cdot \color{blue}{\left(y0 \cdot \left(x \cdot c - y5 \cdot k\right)\right)} \]
3. Recombined 11 regimes into one program.

4. Final simplification 54.5%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y0 \leq -1.55 \cdot 10^{+127}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;y0 \leq -1.65 \cdot 10^{-8}:\\ \;\;\;\;y2 \cdot \left(x \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;y0 \leq -5.5 \cdot 10^{-68}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;y0 \leq -1.4 \cdot 10^{-104}:\\ \;\;\;\;j \cdot \left(y1 \cdot \left(x \cdot i - y3 \cdot y4\right)\right)\\ \mathbf{elif}\;y0 \leq -4.4 \cdot 10^{-142}:\\ \;\;\;\;i \cdot \left(-t \cdot \left(j \cdot y5\right)\right)\\ \mathbf{elif}\;y0 \leq 1.15 \cdot 10^{-279}:\\ \;\;\;\;t \cdot \left(y2 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\\ \mathbf{elif}\;y0 \leq 4.1 \cdot 10^{-160}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;y0 \leq 10^{-78}:\\ \;\;\;\;c \cdot \left(y \cdot \left(y3 \cdot y4 - x \cdot i\right)\right)\\ \mathbf{elif}\;y0 \leq 5.5 \cdot 10^{-5}:\\ \;\;\;\;y1 \cdot \left(y4 \cdot \left(k \cdot y2 - j \cdot y3\right)\right)\\ \mathbf{elif}\;y0 \leq 2.2 \cdot 10^{+111}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;y0 \leq 3 \cdot 10^{+224}:\\ \;\;\;\;y2 \cdot \left(y0 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \end{array} \]

Alternative 11: 29.5% accurate, 3.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{if}\;y \leq -8.5 \cdot 10^{+169}:\\ \;\;\;\;c \cdot \left(y \cdot \left(y3 \cdot y4 - x \cdot i\right)\right)\\ \mathbf{elif}\;y \leq -1.75 \cdot 10^{+82}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y \leq -7.6 \cdot 10^{+66}:\\ \;\;\;\;c \cdot \left(t \cdot \left(z \cdot i - y2 \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq -1.65 \cdot 10^{-131}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y \leq -1.7 \cdot 10^{-305}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)\\ \mathbf{elif}\;y \leq 1.8 \cdot 10^{-167}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq 1.02 \cdot 10^{-119}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;y \leq 8 \cdot 10^{-91}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y \leq 1.45 \cdot 10^{-35}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;y \leq 1.55 \cdot 10^{+161}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* j (* y0 (- (* y3 y5) (* x b))))))
   (if (<= y -8.5e+169)
     (* c (* y (- (* y3 y4) (* x i))))
     (if (<= y -1.75e+82)
       t_1
       (if (<= y -7.6e+66)
         (* c (* t (- (* z i) (* y2 y4))))
         (if (<= y -1.65e-131)
           (* b (* x (- (* y a) (* j y0))))
           (if (<= y -1.7e-305)
             (* c (* z (- (* t i) (* y0 y3))))
             (if (<= y 1.8e-167)
               (* c (* y2 (- (* x y0) (* t y4))))
               (if (<= y 1.02e-119)
                 (* j (* t (- (* b y4) (* i y5))))
                 (if (<= y 8e-91)
                   t_1
                   (if (<= y 1.45e-35)
                     (* a (* b (- (* x y) (* z t))))
                     (if (<= y 1.55e+161)
                       t_1
                       (* c (* y4 (- (* y y3) (* t 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 = j * (y0 * ((y3 * y5) - (x * b)));
	double tmp;
	if (y <= -8.5e+169) {
		tmp = c * (y * ((y3 * y4) - (x * i)));
	} else if (y <= -1.75e+82) {
		tmp = t_1;
	} else if (y <= -7.6e+66) {
		tmp = c * (t * ((z * i) - (y2 * y4)));
	} else if (y <= -1.65e-131) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (y <= -1.7e-305) {
		tmp = c * (z * ((t * i) - (y0 * y3)));
	} else if (y <= 1.8e-167) {
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	} else if (y <= 1.02e-119) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (y <= 8e-91) {
		tmp = t_1;
	} else if (y <= 1.45e-35) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (y <= 1.55e+161) {
		tmp = t_1;
	} else {
		tmp = c * (y4 * ((y * y3) - (t * 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) :: tmp
    t_1 = j * (y0 * ((y3 * y5) - (x * b)))
    if (y <= (-8.5d+169)) then
        tmp = c * (y * ((y3 * y4) - (x * i)))
    else if (y <= (-1.75d+82)) then
        tmp = t_1
    else if (y <= (-7.6d+66)) then
        tmp = c * (t * ((z * i) - (y2 * y4)))
    else if (y <= (-1.65d-131)) then
        tmp = b * (x * ((y * a) - (j * y0)))
    else if (y <= (-1.7d-305)) then
        tmp = c * (z * ((t * i) - (y0 * y3)))
    else if (y <= 1.8d-167) then
        tmp = c * (y2 * ((x * y0) - (t * y4)))
    else if (y <= 1.02d-119) then
        tmp = j * (t * ((b * y4) - (i * y5)))
    else if (y <= 8d-91) then
        tmp = t_1
    else if (y <= 1.45d-35) then
        tmp = a * (b * ((x * y) - (z * t)))
    else if (y <= 1.55d+161) then
        tmp = t_1
    else
        tmp = c * (y4 * ((y * y3) - (t * 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 = j * (y0 * ((y3 * y5) - (x * b)));
	double tmp;
	if (y <= -8.5e+169) {
		tmp = c * (y * ((y3 * y4) - (x * i)));
	} else if (y <= -1.75e+82) {
		tmp = t_1;
	} else if (y <= -7.6e+66) {
		tmp = c * (t * ((z * i) - (y2 * y4)));
	} else if (y <= -1.65e-131) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (y <= -1.7e-305) {
		tmp = c * (z * ((t * i) - (y0 * y3)));
	} else if (y <= 1.8e-167) {
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	} else if (y <= 1.02e-119) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (y <= 8e-91) {
		tmp = t_1;
	} else if (y <= 1.45e-35) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (y <= 1.55e+161) {
		tmp = t_1;
	} else {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = j * (y0 * ((y3 * y5) - (x * b)))
	tmp = 0
	if y <= -8.5e+169:
		tmp = c * (y * ((y3 * y4) - (x * i)))
	elif y <= -1.75e+82:
		tmp = t_1
	elif y <= -7.6e+66:
		tmp = c * (t * ((z * i) - (y2 * y4)))
	elif y <= -1.65e-131:
		tmp = b * (x * ((y * a) - (j * y0)))
	elif y <= -1.7e-305:
		tmp = c * (z * ((t * i) - (y0 * y3)))
	elif y <= 1.8e-167:
		tmp = c * (y2 * ((x * y0) - (t * y4)))
	elif y <= 1.02e-119:
		tmp = j * (t * ((b * y4) - (i * y5)))
	elif y <= 8e-91:
		tmp = t_1
	elif y <= 1.45e-35:
		tmp = a * (b * ((x * y) - (z * t)))
	elif y <= 1.55e+161:
		tmp = t_1
	else:
		tmp = c * (y4 * ((y * y3) - (t * 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(j * Float64(y0 * Float64(Float64(y3 * y5) - Float64(x * b))))
	tmp = 0.0
	if (y <= -8.5e+169)
		tmp = Float64(c * Float64(y * Float64(Float64(y3 * y4) - Float64(x * i))));
	elseif (y <= -1.75e+82)
		tmp = t_1;
	elseif (y <= -7.6e+66)
		tmp = Float64(c * Float64(t * Float64(Float64(z * i) - Float64(y2 * y4))));
	elseif (y <= -1.65e-131)
		tmp = Float64(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))));
	elseif (y <= -1.7e-305)
		tmp = Float64(c * Float64(z * Float64(Float64(t * i) - Float64(y0 * y3))));
	elseif (y <= 1.8e-167)
		tmp = Float64(c * Float64(y2 * Float64(Float64(x * y0) - Float64(t * y4))));
	elseif (y <= 1.02e-119)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))));
	elseif (y <= 8e-91)
		tmp = t_1;
	elseif (y <= 1.45e-35)
		tmp = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))));
	elseif (y <= 1.55e+161)
		tmp = t_1;
	else
		tmp = Float64(c * Float64(y4 * Float64(Float64(y * y3) - Float64(t * 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 = j * (y0 * ((y3 * y5) - (x * b)));
	tmp = 0.0;
	if (y <= -8.5e+169)
		tmp = c * (y * ((y3 * y4) - (x * i)));
	elseif (y <= -1.75e+82)
		tmp = t_1;
	elseif (y <= -7.6e+66)
		tmp = c * (t * ((z * i) - (y2 * y4)));
	elseif (y <= -1.65e-131)
		tmp = b * (x * ((y * a) - (j * y0)));
	elseif (y <= -1.7e-305)
		tmp = c * (z * ((t * i) - (y0 * y3)));
	elseif (y <= 1.8e-167)
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	elseif (y <= 1.02e-119)
		tmp = j * (t * ((b * y4) - (i * y5)));
	elseif (y <= 8e-91)
		tmp = t_1;
	elseif (y <= 1.45e-35)
		tmp = a * (b * ((x * y) - (z * t)));
	elseif (y <= 1.55e+161)
		tmp = t_1;
	else
		tmp = c * (y4 * ((y * y3) - (t * 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[(j * N[(y0 * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y, -8.5e+169], N[(c * N[(y * N[(N[(y3 * y4), $MachinePrecision] - N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -1.75e+82], t$95$1, If[LessEqual[y, -7.6e+66], N[(c * N[(t * N[(N[(z * i), $MachinePrecision] - N[(y2 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -1.65e-131], N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -1.7e-305], N[(c * N[(z * N[(N[(t * i), $MachinePrecision] - N[(y0 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 1.8e-167], N[(c * N[(y2 * N[(N[(x * y0), $MachinePrecision] - N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 1.02e-119], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 8e-91], t$95$1, If[LessEqual[y, 1.45e-35], N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 1.55e+161], t$95$1, N[(c * N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]

Derivation

1. Split input into 9 regimes

2. if y < -8.5000000000000004e169

   1. Initial program 26.7%

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

   2. Taylor expanded in c around inf 47.3%

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

   3. Taylor expanded in y around inf 62.3%

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

      1. *-commutative 62.3%

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

      2. cancel-sign-sub-inv 62.3%

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

      3. metadata-eval 62.3%

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

      4. *-lft-identity 62.3%

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

      5. +-commutative 62.3%

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

      6. mul-1-neg 62.3%

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

      7. unsub-neg 62.3%

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

      8. *-commutative 62.3%

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

   5. Simplified 62.3%

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

   if -8.5000000000000004e169 < y < -1.75e82 or 1.02e-119 < y < 8.00000000000000018e-91 or 1.4500000000000001e-35 < y < 1.55000000000000003e161

   1. Initial program 25.9%

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

   2. Taylor expanded in j around inf 41.5%

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

      1. +-commutative 41.5%

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

      2. mul-1-neg 41.5%

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

      3. unsub-neg 41.5%

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

      4. *-commutative 41.5%

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

   4. Simplified 41.5%

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

   5. Taylor expanded in y0 around -inf 56.1%

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

      1. +-commutative 56.1%

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

      2. mul-1-neg 56.1%

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

      3. unsub-neg 56.1%

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

      4. *-commutative 56.1%

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

   7. Simplified 56.1%

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

   if -1.75e82 < y < -7.6000000000000004e66

   1. Initial program 50.0%

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

   2. Taylor expanded in c around inf 76.0%

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

   3. Taylor expanded in t around inf 100.0%

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

      1. *-commutative 100.0%

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

   5. Simplified 100.0%

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

   if -7.6000000000000004e66 < y < -1.6500000000000001e-131

   1. Initial program 37.6%

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

   2. Taylor expanded in b around inf 34.9%

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

   3. Taylor expanded in x around inf 35.8%

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

      1. *-commutative 35.8%

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

   5. Simplified 35.8%

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

   if -1.6500000000000001e-131 < y < -1.7e-305

   1. Initial program 32.2%

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

   2. Taylor expanded in c around inf 37.4%

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

   3. Taylor expanded in z around inf 33.2%

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

      1. *-commutative 33.2%

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

      2. +-commutative 33.2%

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

      3. mul-1-neg 33.2%

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

      4. sub-neg 33.2%

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

      5. *-commutative 33.2%

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

   5. Simplified 33.2%

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

   if -1.7e-305 < y < 1.8e-167

   1. Initial program 28.6%

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

   2. Taylor expanded in c around inf 50.6%

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

   3. Taylor expanded in y2 around inf 58.3%

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

   if 1.8e-167 < y < 1.02e-119

   1. Initial program 36.4%

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

   2. Taylor expanded in j around inf 82.0%

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

      1. +-commutative 82.0%

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

      2. mul-1-neg 82.0%

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

      3. unsub-neg 82.0%

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

      4. *-commutative 82.0%

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

   4. Simplified 82.0%

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

   5. Taylor expanded in t around inf 73.1%

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

   if 8.00000000000000018e-91 < y < 1.4500000000000001e-35

   1. Initial program 35.7%

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

   2. Taylor expanded in b around inf 43.8%

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

   3. Taylor expanded in a around inf 45.0%

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

   if 1.55000000000000003e161 < y

   1. Initial program 11.5%

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

   2. Taylor expanded in y4 around inf 50.1%

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

   3. Taylor expanded in c around inf 66.2%

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

      1. *-commutative 66.2%

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

   5. Simplified 66.2%

      \[\leadsto \color{blue}{c \cdot \left(y4 \cdot \left(y3 \cdot y - t \cdot y2\right)\right)} \]
3. Recombined 9 regimes into one program.

4. Final simplification 51.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y \leq -8.5 \cdot 10^{+169}:\\ \;\;\;\;c \cdot \left(y \cdot \left(y3 \cdot y4 - x \cdot i\right)\right)\\ \mathbf{elif}\;y \leq -1.75 \cdot 10^{+82}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;y \leq -7.6 \cdot 10^{+66}:\\ \;\;\;\;c \cdot \left(t \cdot \left(z \cdot i - y2 \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq -1.65 \cdot 10^{-131}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y \leq -1.7 \cdot 10^{-305}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)\\ \mathbf{elif}\;y \leq 1.8 \cdot 10^{-167}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq 1.02 \cdot 10^{-119}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;y \leq 8 \cdot 10^{-91}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;y \leq 1.45 \cdot 10^{-35}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;y \leq 1.55 \cdot 10^{+161}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \end{array} \]

Alternative 12: 29.5% accurate, 3.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{if}\;y \leq -8.5 \cdot 10^{+169}:\\ \;\;\;\;c \cdot \left(y \cdot \left(y3 \cdot y4 - x \cdot i\right)\right)\\ \mathbf{elif}\;y \leq -9.2 \cdot 10^{+78}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y \leq -1.45 \cdot 10^{+66}:\\ \;\;\;\;c \cdot \left(t \cdot \left(z \cdot i - y2 \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq -4.6 \cdot 10^{-148}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y \leq 7.5 \cdot 10^{-294}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq 6.6 \cdot 10^{-168}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq 9.2 \cdot 10^{-118}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;y \leq 2.3 \cdot 10^{-92}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y \leq 2.2 \cdot 10^{-36}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;y \leq 1.52 \cdot 10^{+159}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* j (* y0 (- (* y3 y5) (* x b))))))
   (if (<= y -8.5e+169)
     (* c (* y (- (* y3 y4) (* x i))))
     (if (<= y -9.2e+78)
       t_1
       (if (<= y -1.45e+66)
         (* c (* t (- (* z i) (* y2 y4))))
         (if (<= y -4.6e-148)
           (* b (* x (- (* y a) (* j y0))))
           (if (<= y 7.5e-294)
             (* j (* y3 (- (* y0 y5) (* y1 y4))))
             (if (<= y 6.6e-168)
               (* c (* y2 (- (* x y0) (* t y4))))
               (if (<= y 9.2e-118)
                 (* j (* t (- (* b y4) (* i y5))))
                 (if (<= y 2.3e-92)
                   t_1
                   (if (<= y 2.2e-36)
                     (* a (* b (- (* x y) (* z t))))
                     (if (<= y 1.52e+159)
                       t_1
                       (* c (* y4 (- (* y y3) (* t 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 = j * (y0 * ((y3 * y5) - (x * b)));
	double tmp;
	if (y <= -8.5e+169) {
		tmp = c * (y * ((y3 * y4) - (x * i)));
	} else if (y <= -9.2e+78) {
		tmp = t_1;
	} else if (y <= -1.45e+66) {
		tmp = c * (t * ((z * i) - (y2 * y4)));
	} else if (y <= -4.6e-148) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (y <= 7.5e-294) {
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	} else if (y <= 6.6e-168) {
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	} else if (y <= 9.2e-118) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (y <= 2.3e-92) {
		tmp = t_1;
	} else if (y <= 2.2e-36) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (y <= 1.52e+159) {
		tmp = t_1;
	} else {
		tmp = c * (y4 * ((y * y3) - (t * 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) :: tmp
    t_1 = j * (y0 * ((y3 * y5) - (x * b)))
    if (y <= (-8.5d+169)) then
        tmp = c * (y * ((y3 * y4) - (x * i)))
    else if (y <= (-9.2d+78)) then
        tmp = t_1
    else if (y <= (-1.45d+66)) then
        tmp = c * (t * ((z * i) - (y2 * y4)))
    else if (y <= (-4.6d-148)) then
        tmp = b * (x * ((y * a) - (j * y0)))
    else if (y <= 7.5d-294) then
        tmp = j * (y3 * ((y0 * y5) - (y1 * y4)))
    else if (y <= 6.6d-168) then
        tmp = c * (y2 * ((x * y0) - (t * y4)))
    else if (y <= 9.2d-118) then
        tmp = j * (t * ((b * y4) - (i * y5)))
    else if (y <= 2.3d-92) then
        tmp = t_1
    else if (y <= 2.2d-36) then
        tmp = a * (b * ((x * y) - (z * t)))
    else if (y <= 1.52d+159) then
        tmp = t_1
    else
        tmp = c * (y4 * ((y * y3) - (t * 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 = j * (y0 * ((y3 * y5) - (x * b)));
	double tmp;
	if (y <= -8.5e+169) {
		tmp = c * (y * ((y3 * y4) - (x * i)));
	} else if (y <= -9.2e+78) {
		tmp = t_1;
	} else if (y <= -1.45e+66) {
		tmp = c * (t * ((z * i) - (y2 * y4)));
	} else if (y <= -4.6e-148) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (y <= 7.5e-294) {
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	} else if (y <= 6.6e-168) {
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	} else if (y <= 9.2e-118) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (y <= 2.3e-92) {
		tmp = t_1;
	} else if (y <= 2.2e-36) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else if (y <= 1.52e+159) {
		tmp = t_1;
	} else {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = j * (y0 * ((y3 * y5) - (x * b)))
	tmp = 0
	if y <= -8.5e+169:
		tmp = c * (y * ((y3 * y4) - (x * i)))
	elif y <= -9.2e+78:
		tmp = t_1
	elif y <= -1.45e+66:
		tmp = c * (t * ((z * i) - (y2 * y4)))
	elif y <= -4.6e-148:
		tmp = b * (x * ((y * a) - (j * y0)))
	elif y <= 7.5e-294:
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)))
	elif y <= 6.6e-168:
		tmp = c * (y2 * ((x * y0) - (t * y4)))
	elif y <= 9.2e-118:
		tmp = j * (t * ((b * y4) - (i * y5)))
	elif y <= 2.3e-92:
		tmp = t_1
	elif y <= 2.2e-36:
		tmp = a * (b * ((x * y) - (z * t)))
	elif y <= 1.52e+159:
		tmp = t_1
	else:
		tmp = c * (y4 * ((y * y3) - (t * 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(j * Float64(y0 * Float64(Float64(y3 * y5) - Float64(x * b))))
	tmp = 0.0
	if (y <= -8.5e+169)
		tmp = Float64(c * Float64(y * Float64(Float64(y3 * y4) - Float64(x * i))));
	elseif (y <= -9.2e+78)
		tmp = t_1;
	elseif (y <= -1.45e+66)
		tmp = Float64(c * Float64(t * Float64(Float64(z * i) - Float64(y2 * y4))));
	elseif (y <= -4.6e-148)
		tmp = Float64(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))));
	elseif (y <= 7.5e-294)
		tmp = Float64(j * Float64(y3 * Float64(Float64(y0 * y5) - Float64(y1 * y4))));
	elseif (y <= 6.6e-168)
		tmp = Float64(c * Float64(y2 * Float64(Float64(x * y0) - Float64(t * y4))));
	elseif (y <= 9.2e-118)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))));
	elseif (y <= 2.3e-92)
		tmp = t_1;
	elseif (y <= 2.2e-36)
		tmp = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))));
	elseif (y <= 1.52e+159)
		tmp = t_1;
	else
		tmp = Float64(c * Float64(y4 * Float64(Float64(y * y3) - Float64(t * 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 = j * (y0 * ((y3 * y5) - (x * b)));
	tmp = 0.0;
	if (y <= -8.5e+169)
		tmp = c * (y * ((y3 * y4) - (x * i)));
	elseif (y <= -9.2e+78)
		tmp = t_1;
	elseif (y <= -1.45e+66)
		tmp = c * (t * ((z * i) - (y2 * y4)));
	elseif (y <= -4.6e-148)
		tmp = b * (x * ((y * a) - (j * y0)));
	elseif (y <= 7.5e-294)
		tmp = j * (y3 * ((y0 * y5) - (y1 * y4)));
	elseif (y <= 6.6e-168)
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	elseif (y <= 9.2e-118)
		tmp = j * (t * ((b * y4) - (i * y5)));
	elseif (y <= 2.3e-92)
		tmp = t_1;
	elseif (y <= 2.2e-36)
		tmp = a * (b * ((x * y) - (z * t)));
	elseif (y <= 1.52e+159)
		tmp = t_1;
	else
		tmp = c * (y4 * ((y * y3) - (t * 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[(j * N[(y0 * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y, -8.5e+169], N[(c * N[(y * N[(N[(y3 * y4), $MachinePrecision] - N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -9.2e+78], t$95$1, If[LessEqual[y, -1.45e+66], N[(c * N[(t * N[(N[(z * i), $MachinePrecision] - N[(y2 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -4.6e-148], N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 7.5e-294], N[(j * N[(y3 * N[(N[(y0 * y5), $MachinePrecision] - N[(y1 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 6.6e-168], N[(c * N[(y2 * N[(N[(x * y0), $MachinePrecision] - N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 9.2e-118], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 2.3e-92], t$95$1, If[LessEqual[y, 2.2e-36], N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 1.52e+159], t$95$1, N[(c * N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]

Derivation

1. Split input into 9 regimes

2. if y < -8.5000000000000004e169

   1. Initial program 26.7%

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

   2. Taylor expanded in c around inf 47.3%

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

   3. Taylor expanded in y around inf 62.3%

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

      1. *-commutative 62.3%

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

      2. cancel-sign-sub-inv 62.3%

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

      3. metadata-eval 62.3%

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

      4. *-lft-identity 62.3%

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

      5. +-commutative 62.3%

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

      6. mul-1-neg 62.3%

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

      7. unsub-neg 62.3%

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

      8. *-commutative 62.3%

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

   5. Simplified 62.3%

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

   if -8.5000000000000004e169 < y < -9.2000000000000008e78 or 9.20000000000000084e-118 < y < 2.30000000000000016e-92 or 2.1999999999999999e-36 < y < 1.5199999999999999e159

   1. Initial program 25.9%

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

   2. Taylor expanded in j around inf 41.5%

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

      1. +-commutative 41.5%

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

      2. mul-1-neg 41.5%

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

      3. unsub-neg 41.5%

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

      4. *-commutative 41.5%

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

   4. Simplified 41.5%

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

   5. Taylor expanded in y0 around -inf 56.1%

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

      1. +-commutative 56.1%

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

      2. mul-1-neg 56.1%

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

      3. unsub-neg 56.1%

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

      4. *-commutative 56.1%

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

   7. Simplified 56.1%

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

   if -9.2000000000000008e78 < y < -1.44999999999999993e66

   1. Initial program 50.0%

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

   2. Taylor expanded in c around inf 76.0%

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

   3. Taylor expanded in t around inf 100.0%

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

      1. *-commutative 100.0%

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

   5. Simplified 100.0%

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

   if -1.44999999999999993e66 < y < -4.59999999999999995e-148

   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. Taylor expanded in b around inf 37.2%

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

   3. Taylor expanded in x around inf 35.6%

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

      1. *-commutative 35.6%

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

   5. Simplified 35.6%

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

   if -4.59999999999999995e-148 < y < 7.5000000000000004e-294

   1. Initial program 28.9%

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

   2. Taylor expanded in j around inf 51.8%

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

      1. +-commutative 51.8%

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

      2. mul-1-neg 51.8%

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

      3. unsub-neg 51.8%

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

      4. *-commutative 51.8%

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

   4. Simplified 51.8%

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

   5. Taylor expanded in y3 around inf 36.0%

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

      1. *-commutative 36.0%

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

      2. *-commutative 36.0%

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

   7. Simplified 36.0%

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

   if 7.5000000000000004e-294 < y < 6.6000000000000003e-168

   1. Initial program 34.8%

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

   2. Taylor expanded in c around inf 48.4%

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

   3. Taylor expanded in y2 around inf 57.8%

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

   if 6.6000000000000003e-168 < y < 9.20000000000000084e-118

   1. Initial program 36.4%

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

   2. Taylor expanded in j around inf 82.0%

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

      1. +-commutative 82.0%

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

      2. mul-1-neg 82.0%

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

      3. unsub-neg 82.0%

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

      4. *-commutative 82.0%

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

   4. Simplified 82.0%

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

   5. Taylor expanded in t around inf 73.1%

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

   if 2.30000000000000016e-92 < y < 2.1999999999999999e-36

   1. Initial program 35.7%

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

   2. Taylor expanded in b around inf 43.8%

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

   3. Taylor expanded in a around inf 45.0%

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

   if 1.5199999999999999e159 < y

   1. Initial program 11.5%

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

   2. Taylor expanded in y4 around inf 50.1%

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

   3. Taylor expanded in c around inf 66.2%

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

      1. *-commutative 66.2%

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

   5. Simplified 66.2%

      \[\leadsto \color{blue}{c \cdot \left(y4 \cdot \left(y3 \cdot y - t \cdot y2\right)\right)} \]
3. Recombined 9 regimes into one program.

4. Final simplification 51.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y \leq -8.5 \cdot 10^{+169}:\\ \;\;\;\;c \cdot \left(y \cdot \left(y3 \cdot y4 - x \cdot i\right)\right)\\ \mathbf{elif}\;y \leq -9.2 \cdot 10^{+78}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;y \leq -1.45 \cdot 10^{+66}:\\ \;\;\;\;c \cdot \left(t \cdot \left(z \cdot i - y2 \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq -4.6 \cdot 10^{-148}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y \leq 7.5 \cdot 10^{-294}:\\ \;\;\;\;j \cdot \left(y3 \cdot \left(y0 \cdot y5 - y1 \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq 6.6 \cdot 10^{-168}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq 9.2 \cdot 10^{-118}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;y \leq 2.3 \cdot 10^{-92}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;y \leq 2.2 \cdot 10^{-36}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;y \leq 1.52 \cdot 10^{+159}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \end{array} \]

Alternative 13: 30.1% accurate, 3.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{if}\;y \leq -8.5 \cdot 10^{+169}:\\ \;\;\;\;c \cdot \left(y \cdot \left(y3 \cdot y4 - x \cdot i\right)\right)\\ \mathbf{elif}\;y \leq -1 \cdot 10^{+83}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y \leq -2.15 \cdot 10^{+67}:\\ \;\;\;\;c \cdot \left(t \cdot \left(z \cdot i - y2 \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq -5.3 \cdot 10^{-141}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y \leq 2.7 \cdot 10^{-167}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;y \leq 6 \cdot 10^{-119}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;y \leq 6 \cdot 10^{-74}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y \leq 0.00042:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)\\ \mathbf{elif}\;y \leq 1.1 \cdot 10^{+159}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* j (* y0 (- (* y3 y5) (* x b))))))
   (if (<= y -8.5e+169)
     (* c (* y (- (* y3 y4) (* x i))))
     (if (<= y -1e+83)
       t_1
       (if (<= y -2.15e+67)
         (* c (* t (- (* z i) (* y2 y4))))
         (if (<= y -5.3e-141)
           (* b (* x (- (* y a) (* j y0))))
           (if (<= y 2.7e-167)
             (* x (* y2 (- (* c y0) (* a y1))))
             (if (<= y 6e-119)
               (* j (* t (- (* b y4) (* i y5))))
               (if (<= y 6e-74)
                 t_1
                 (if (<= y 0.00042)
                   (* c (* z (- (* t i) (* y0 y3))))
                   (if (<= y 1.1e+159)
                     t_1
                     (* c (* y4 (- (* y y3) (* t 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 = j * (y0 * ((y3 * y5) - (x * b)));
	double tmp;
	if (y <= -8.5e+169) {
		tmp = c * (y * ((y3 * y4) - (x * i)));
	} else if (y <= -1e+83) {
		tmp = t_1;
	} else if (y <= -2.15e+67) {
		tmp = c * (t * ((z * i) - (y2 * y4)));
	} else if (y <= -5.3e-141) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (y <= 2.7e-167) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (y <= 6e-119) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (y <= 6e-74) {
		tmp = t_1;
	} else if (y <= 0.00042) {
		tmp = c * (z * ((t * i) - (y0 * y3)));
	} else if (y <= 1.1e+159) {
		tmp = t_1;
	} else {
		tmp = c * (y4 * ((y * y3) - (t * 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) :: tmp
    t_1 = j * (y0 * ((y3 * y5) - (x * b)))
    if (y <= (-8.5d+169)) then
        tmp = c * (y * ((y3 * y4) - (x * i)))
    else if (y <= (-1d+83)) then
        tmp = t_1
    else if (y <= (-2.15d+67)) then
        tmp = c * (t * ((z * i) - (y2 * y4)))
    else if (y <= (-5.3d-141)) then
        tmp = b * (x * ((y * a) - (j * y0)))
    else if (y <= 2.7d-167) then
        tmp = x * (y2 * ((c * y0) - (a * y1)))
    else if (y <= 6d-119) then
        tmp = j * (t * ((b * y4) - (i * y5)))
    else if (y <= 6d-74) then
        tmp = t_1
    else if (y <= 0.00042d0) then
        tmp = c * (z * ((t * i) - (y0 * y3)))
    else if (y <= 1.1d+159) then
        tmp = t_1
    else
        tmp = c * (y4 * ((y * y3) - (t * 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 = j * (y0 * ((y3 * y5) - (x * b)));
	double tmp;
	if (y <= -8.5e+169) {
		tmp = c * (y * ((y3 * y4) - (x * i)));
	} else if (y <= -1e+83) {
		tmp = t_1;
	} else if (y <= -2.15e+67) {
		tmp = c * (t * ((z * i) - (y2 * y4)));
	} else if (y <= -5.3e-141) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (y <= 2.7e-167) {
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	} else if (y <= 6e-119) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (y <= 6e-74) {
		tmp = t_1;
	} else if (y <= 0.00042) {
		tmp = c * (z * ((t * i) - (y0 * y3)));
	} else if (y <= 1.1e+159) {
		tmp = t_1;
	} else {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = j * (y0 * ((y3 * y5) - (x * b)))
	tmp = 0
	if y <= -8.5e+169:
		tmp = c * (y * ((y3 * y4) - (x * i)))
	elif y <= -1e+83:
		tmp = t_1
	elif y <= -2.15e+67:
		tmp = c * (t * ((z * i) - (y2 * y4)))
	elif y <= -5.3e-141:
		tmp = b * (x * ((y * a) - (j * y0)))
	elif y <= 2.7e-167:
		tmp = x * (y2 * ((c * y0) - (a * y1)))
	elif y <= 6e-119:
		tmp = j * (t * ((b * y4) - (i * y5)))
	elif y <= 6e-74:
		tmp = t_1
	elif y <= 0.00042:
		tmp = c * (z * ((t * i) - (y0 * y3)))
	elif y <= 1.1e+159:
		tmp = t_1
	else:
		tmp = c * (y4 * ((y * y3) - (t * 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(j * Float64(y0 * Float64(Float64(y3 * y5) - Float64(x * b))))
	tmp = 0.0
	if (y <= -8.5e+169)
		tmp = Float64(c * Float64(y * Float64(Float64(y3 * y4) - Float64(x * i))));
	elseif (y <= -1e+83)
		tmp = t_1;
	elseif (y <= -2.15e+67)
		tmp = Float64(c * Float64(t * Float64(Float64(z * i) - Float64(y2 * y4))));
	elseif (y <= -5.3e-141)
		tmp = Float64(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))));
	elseif (y <= 2.7e-167)
		tmp = Float64(x * Float64(y2 * Float64(Float64(c * y0) - Float64(a * y1))));
	elseif (y <= 6e-119)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))));
	elseif (y <= 6e-74)
		tmp = t_1;
	elseif (y <= 0.00042)
		tmp = Float64(c * Float64(z * Float64(Float64(t * i) - Float64(y0 * y3))));
	elseif (y <= 1.1e+159)
		tmp = t_1;
	else
		tmp = Float64(c * Float64(y4 * Float64(Float64(y * y3) - Float64(t * 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 = j * (y0 * ((y3 * y5) - (x * b)));
	tmp = 0.0;
	if (y <= -8.5e+169)
		tmp = c * (y * ((y3 * y4) - (x * i)));
	elseif (y <= -1e+83)
		tmp = t_1;
	elseif (y <= -2.15e+67)
		tmp = c * (t * ((z * i) - (y2 * y4)));
	elseif (y <= -5.3e-141)
		tmp = b * (x * ((y * a) - (j * y0)));
	elseif (y <= 2.7e-167)
		tmp = x * (y2 * ((c * y0) - (a * y1)));
	elseif (y <= 6e-119)
		tmp = j * (t * ((b * y4) - (i * y5)));
	elseif (y <= 6e-74)
		tmp = t_1;
	elseif (y <= 0.00042)
		tmp = c * (z * ((t * i) - (y0 * y3)));
	elseif (y <= 1.1e+159)
		tmp = t_1;
	else
		tmp = c * (y4 * ((y * y3) - (t * 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[(j * N[(y0 * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y, -8.5e+169], N[(c * N[(y * N[(N[(y3 * y4), $MachinePrecision] - N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -1e+83], t$95$1, If[LessEqual[y, -2.15e+67], N[(c * N[(t * N[(N[(z * i), $MachinePrecision] - N[(y2 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -5.3e-141], N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 2.7e-167], N[(x * N[(y2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 6e-119], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 6e-74], t$95$1, If[LessEqual[y, 0.00042], N[(c * N[(z * N[(N[(t * i), $MachinePrecision] - N[(y0 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 1.1e+159], t$95$1, N[(c * N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]

Derivation

1. Split input into 8 regimes

2. if y < -8.5000000000000004e169

   1. Initial program 26.7%

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

   2. Taylor expanded in c around inf 47.3%

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

   3. Taylor expanded in y around inf 62.3%

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

      1. *-commutative 62.3%

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

      2. cancel-sign-sub-inv 62.3%

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

      3. metadata-eval 62.3%

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

      4. *-lft-identity 62.3%

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

      5. +-commutative 62.3%

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

      6. mul-1-neg 62.3%

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

      7. unsub-neg 62.3%

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

      8. *-commutative 62.3%

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

   5. Simplified 62.3%

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

   if -8.5000000000000004e169 < y < -1.00000000000000003e83 or 6.0000000000000004e-119 < y < 6.00000000000000014e-74 or 4.2000000000000002e-4 < y < 1.1e159

   1. Initial program 27.3%

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

   2. Taylor expanded in j around inf 38.8%

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

      1. +-commutative 38.8%

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

      2. mul-1-neg 38.8%

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

      3. unsub-neg 38.8%

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

      4. *-commutative 38.8%

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

   4. Simplified 38.8%

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

   5. Taylor expanded in y0 around -inf 55.2%

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

      1. +-commutative 55.2%

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

      2. mul-1-neg 55.2%

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

      3. unsub-neg 55.2%

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

      4. *-commutative 55.2%

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

   7. Simplified 55.2%

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

   if -1.00000000000000003e83 < y < -2.1500000000000001e67

   1. Initial program 50.0%

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

   2. Taylor expanded in c around inf 76.0%

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

   3. Taylor expanded in t around inf 100.0%

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

      1. *-commutative 100.0%

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

   5. Simplified 100.0%

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

   if -2.1500000000000001e67 < y < -5.30000000000000007e-141

   1. Initial program 35.8%

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

   2. Taylor expanded in b around inf 35.7%

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

   3. Taylor expanded in x around inf 36.5%

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

      1. *-commutative 36.5%

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

   5. Simplified 36.5%

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

   if -5.30000000000000007e-141 < y < 2.7000000000000001e-167

   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. Taylor expanded in y2 around inf 45.9%

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

   3. Taylor expanded in x around inf 39.8%

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

   if 2.7000000000000001e-167 < y < 6.0000000000000004e-119

   1. Initial program 36.4%

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

   2. Taylor expanded in j around inf 82.0%

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

      1. +-commutative 82.0%

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

      2. mul-1-neg 82.0%

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

      3. unsub-neg 82.0%

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

      4. *-commutative 82.0%

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

   4. Simplified 82.0%

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

   5. Taylor expanded in t around inf 73.1%

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

   if 6.00000000000000014e-74 < y < 4.2000000000000002e-4

   1. Initial program 30.8%

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

   2. Taylor expanded in c around inf 46.5%

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

   3. Taylor expanded in z around inf 47.2%

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

      1. *-commutative 47.2%

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

      2. +-commutative 47.2%

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

      3. mul-1-neg 47.2%

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

      4. sub-neg 47.2%

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

      5. *-commutative 47.2%

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

   5. Simplified 47.2%

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

   if 1.1e159 < y

   1. Initial program 11.5%

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

   2. Taylor expanded in y4 around inf 50.1%

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

   3. Taylor expanded in c around inf 66.2%

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

      1. *-commutative 66.2%

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

   5. Simplified 66.2%

      \[\leadsto \color{blue}{c \cdot \left(y4 \cdot \left(y3 \cdot y - t \cdot y2\right)\right)} \]
3. Recombined 8 regimes into one program.

4. Final simplification 51.0%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y \leq -8.5 \cdot 10^{+169}:\\ \;\;\;\;c \cdot \left(y \cdot \left(y3 \cdot y4 - x \cdot i\right)\right)\\ \mathbf{elif}\;y \leq -1 \cdot 10^{+83}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;y \leq -2.15 \cdot 10^{+67}:\\ \;\;\;\;c \cdot \left(t \cdot \left(z \cdot i - y2 \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq -5.3 \cdot 10^{-141}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y \leq 2.7 \cdot 10^{-167}:\\ \;\;\;\;x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;y \leq 6 \cdot 10^{-119}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;y \leq 6 \cdot 10^{-74}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{elif}\;y \leq 0.00042:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)\\ \mathbf{elif}\;y \leq 1.1 \cdot 10^{+159}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \end{array} \]

Alternative 14: 31.2% accurate, 3.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;t \leq -2.2 \cdot 10^{+138}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq -1.35 \cdot 10^{-62}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq 3.8 \cdot 10^{-266}:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y0 \cdot y2 - y \cdot i\right)\\ \mathbf{elif}\;t \leq 4.8 \cdot 10^{-227}:\\ \;\;\;\;\left(k \cdot y4\right) \cdot \left(y1 \cdot y2 - y \cdot b\right)\\ \mathbf{elif}\;t \leq 9.2 \cdot 10^{-142}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 1.25 \cdot 10^{-104}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq 7.5 \cdot 10^{-96}:\\ \;\;\;\;\left(x \cdot y2\right) \cdot \left(c \cdot y0 - a \cdot y1\right)\\ \mathbf{elif}\;t \leq 1.75 \cdot 10^{+45}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 4.6 \cdot 10^{+151}:\\ \;\;\;\;y2 \cdot \left(y0 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(t \cdot \left(z \cdot i - y2 \cdot y4\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= t -2.2e+138)
   (* j (* t (- (* b y4) (* i y5))))
   (if (<= t -1.35e-62)
     (* c (* y4 (- (* y y3) (* t y2))))
     (if (<= t 3.8e-266)
       (* (* x c) (- (* y0 y2) (* y i)))
       (if (<= t 4.8e-227)
         (* (* k y4) (- (* y1 y2) (* y b)))
         (if (<= t 9.2e-142)
           (* b (* x (- (* y a) (* j y0))))
           (if (<= t 1.25e-104)
             (* c (* z (- (* t i) (* y0 y3))))
             (if (<= t 7.5e-96)
               (* (* x y2) (- (* c y0) (* a y1)))
               (if (<= t 1.75e+45)
                 (* j (* x (- (* i y1) (* b y0))))
                 (if (<= t 4.6e+151)
                   (* y2 (* y0 (- (* x c) (* k y5))))
                   (* c (* t (- (* z i) (* 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 <= -2.2e+138) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (t <= -1.35e-62) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (t <= 3.8e-266) {
		tmp = (x * c) * ((y0 * y2) - (y * i));
	} else if (t <= 4.8e-227) {
		tmp = (k * y4) * ((y1 * y2) - (y * b));
	} else if (t <= 9.2e-142) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (t <= 1.25e-104) {
		tmp = c * (z * ((t * i) - (y0 * y3)));
	} else if (t <= 7.5e-96) {
		tmp = (x * y2) * ((c * y0) - (a * y1));
	} else if (t <= 1.75e+45) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (t <= 4.6e+151) {
		tmp = y2 * (y0 * ((x * c) - (k * y5)));
	} else {
		tmp = c * (t * ((z * i) - (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 <= (-2.2d+138)) then
        tmp = j * (t * ((b * y4) - (i * y5)))
    else if (t <= (-1.35d-62)) then
        tmp = c * (y4 * ((y * y3) - (t * y2)))
    else if (t <= 3.8d-266) then
        tmp = (x * c) * ((y0 * y2) - (y * i))
    else if (t <= 4.8d-227) then
        tmp = (k * y4) * ((y1 * y2) - (y * b))
    else if (t <= 9.2d-142) then
        tmp = b * (x * ((y * a) - (j * y0)))
    else if (t <= 1.25d-104) then
        tmp = c * (z * ((t * i) - (y0 * y3)))
    else if (t <= 7.5d-96) then
        tmp = (x * y2) * ((c * y0) - (a * y1))
    else if (t <= 1.75d+45) then
        tmp = j * (x * ((i * y1) - (b * y0)))
    else if (t <= 4.6d+151) then
        tmp = y2 * (y0 * ((x * c) - (k * y5)))
    else
        tmp = c * (t * ((z * i) - (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 <= -2.2e+138) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (t <= -1.35e-62) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (t <= 3.8e-266) {
		tmp = (x * c) * ((y0 * y2) - (y * i));
	} else if (t <= 4.8e-227) {
		tmp = (k * y4) * ((y1 * y2) - (y * b));
	} else if (t <= 9.2e-142) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (t <= 1.25e-104) {
		tmp = c * (z * ((t * i) - (y0 * y3)));
	} else if (t <= 7.5e-96) {
		tmp = (x * y2) * ((c * y0) - (a * y1));
	} else if (t <= 1.75e+45) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (t <= 4.6e+151) {
		tmp = y2 * (y0 * ((x * c) - (k * y5)));
	} else {
		tmp = c * (t * ((z * i) - (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 <= -2.2e+138:
		tmp = j * (t * ((b * y4) - (i * y5)))
	elif t <= -1.35e-62:
		tmp = c * (y4 * ((y * y3) - (t * y2)))
	elif t <= 3.8e-266:
		tmp = (x * c) * ((y0 * y2) - (y * i))
	elif t <= 4.8e-227:
		tmp = (k * y4) * ((y1 * y2) - (y * b))
	elif t <= 9.2e-142:
		tmp = b * (x * ((y * a) - (j * y0)))
	elif t <= 1.25e-104:
		tmp = c * (z * ((t * i) - (y0 * y3)))
	elif t <= 7.5e-96:
		tmp = (x * y2) * ((c * y0) - (a * y1))
	elif t <= 1.75e+45:
		tmp = j * (x * ((i * y1) - (b * y0)))
	elif t <= 4.6e+151:
		tmp = y2 * (y0 * ((x * c) - (k * y5)))
	else:
		tmp = c * (t * ((z * i) - (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 <= -2.2e+138)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))));
	elseif (t <= -1.35e-62)
		tmp = Float64(c * Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2))));
	elseif (t <= 3.8e-266)
		tmp = Float64(Float64(x * c) * Float64(Float64(y0 * y2) - Float64(y * i)));
	elseif (t <= 4.8e-227)
		tmp = Float64(Float64(k * y4) * Float64(Float64(y1 * y2) - Float64(y * b)));
	elseif (t <= 9.2e-142)
		tmp = Float64(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))));
	elseif (t <= 1.25e-104)
		tmp = Float64(c * Float64(z * Float64(Float64(t * i) - Float64(y0 * y3))));
	elseif (t <= 7.5e-96)
		tmp = Float64(Float64(x * y2) * Float64(Float64(c * y0) - Float64(a * y1)));
	elseif (t <= 1.75e+45)
		tmp = Float64(j * Float64(x * Float64(Float64(i * y1) - Float64(b * y0))));
	elseif (t <= 4.6e+151)
		tmp = Float64(y2 * Float64(y0 * Float64(Float64(x * c) - Float64(k * y5))));
	else
		tmp = Float64(c * Float64(t * Float64(Float64(z * i) - Float64(y2 * 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 <= -2.2e+138)
		tmp = j * (t * ((b * y4) - (i * y5)));
	elseif (t <= -1.35e-62)
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	elseif (t <= 3.8e-266)
		tmp = (x * c) * ((y0 * y2) - (y * i));
	elseif (t <= 4.8e-227)
		tmp = (k * y4) * ((y1 * y2) - (y * b));
	elseif (t <= 9.2e-142)
		tmp = b * (x * ((y * a) - (j * y0)));
	elseif (t <= 1.25e-104)
		tmp = c * (z * ((t * i) - (y0 * y3)));
	elseif (t <= 7.5e-96)
		tmp = (x * y2) * ((c * y0) - (a * y1));
	elseif (t <= 1.75e+45)
		tmp = j * (x * ((i * y1) - (b * y0)));
	elseif (t <= 4.6e+151)
		tmp = y2 * (y0 * ((x * c) - (k * y5)));
	else
		tmp = c * (t * ((z * i) - (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, -2.2e+138], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -1.35e-62], N[(c * N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 3.8e-266], N[(N[(x * c), $MachinePrecision] * N[(N[(y0 * y2), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 4.8e-227], N[(N[(k * y4), $MachinePrecision] * N[(N[(y1 * y2), $MachinePrecision] - N[(y * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 9.2e-142], N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.25e-104], N[(c * N[(z * N[(N[(t * i), $MachinePrecision] - N[(y0 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 7.5e-96], N[(N[(x * y2), $MachinePrecision] * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.75e+45], N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 4.6e+151], N[(y2 * N[(y0 * N[(N[(x * c), $MachinePrecision] - N[(k * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(c * N[(t * N[(N[(z * i), $MachinePrecision] - N[(y2 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]

Derivation

1. Split input into 10 regimes

2. if t < -2.2000000000000001e138

   1. Initial program 18.6%

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

   2. Taylor expanded in j around inf 39.9%

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

      1. +-commutative 39.9%

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

      2. mul-1-neg 39.9%

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

      3. unsub-neg 39.9%

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

      4. *-commutative 39.9%

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

   4. Simplified 39.9%

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

   5. Taylor expanded in t around inf 50.4%

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

   if -2.2000000000000001e138 < t < -1.3500000000000001e-62

   1. Initial program 23.5%

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

   2. Taylor expanded in y4 around inf 47.3%

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

   3. Taylor expanded in c around inf 52.3%

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

      1. *-commutative 52.3%

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

   5. Simplified 52.3%

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

   if -1.3500000000000001e-62 < t < 3.79999999999999994e-266

   1. Initial program 40.0%

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

   2. Taylor expanded in c around inf 50.8%

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

   3. Taylor expanded in x around inf 49.3%

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

      1. associate-*r* 49.3%

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

      2. +-commutative 49.3%

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

      3. mul-1-neg 49.3%

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

      4. unsub-neg 49.3%

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

   5. Simplified 49.3%

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

   if 3.79999999999999994e-266 < t < 4.7999999999999999e-227

   1. Initial program 28.6%

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

   2. Taylor expanded in y4 around inf 50.4%

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

   3. Taylor expanded in k around inf 65.1%

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

      1. associate-*r* 58.2%

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

      2. *-commutative 58.2%

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

      3. +-commutative 58.2%

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

      4. mul-1-neg 58.2%

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

      5. unsub-neg 58.2%

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

   5. Simplified 58.2%

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

   if 4.7999999999999999e-227 < t < 9.20000000000000009e-142

   1. Initial program 21.5%

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

   2. Taylor expanded in b around inf 42.6%

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

   3. Taylor expanded in x around inf 54.2%

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

      1. *-commutative 54.2%

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

   5. Simplified 54.2%

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

   if 9.20000000000000009e-142 < t < 1.24999999999999995e-104

   1. Initial program 51.0%

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

   2. Taylor expanded in c around inf 39.3%

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

   3. Taylor expanded in z around inf 51.2%

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

      1. *-commutative 51.2%

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

      2. +-commutative 51.2%

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

      3. mul-1-neg 51.2%

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

      4. sub-neg 51.2%

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

      5. *-commutative 51.2%

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

   5. Simplified 51.2%

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

   if 1.24999999999999995e-104 < t < 7.5e-96

   1. Initial program 40.0%

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

   2. Taylor expanded in y2 around inf 79.7%

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

   3. Taylor expanded in t around 0 80.0%

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

   4. Taylor expanded in x around inf 81.2%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 96.9%

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

      2. *-commutative 96.9%

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

      3. *-commutative 96.9%

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

      4. *-lft-identity 96.9%

         \[\leadsto \color{blue}{\left(1 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \cdot \left(y2 \cdot x\right) \]

      5. *-lft-identity 96.9%

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

      6. *-commutative 96.9%

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

      7. *-commutative 96.9%

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

   6. Simplified 96.9%

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

   if 7.5e-96 < t < 1.75000000000000011e45

   1. Initial program 32.8%

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

   2. Taylor expanded in j around inf 52.7%

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

      1. +-commutative 52.7%

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

      2. mul-1-neg 52.7%

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

      3. unsub-neg 52.7%

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

      4. *-commutative 52.7%

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

   4. Simplified 52.7%

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

   5. Taylor expanded in x around inf 40.4%

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

   if 1.75000000000000011e45 < t < 4.6000000000000002e151

   1. Initial program 30.0%

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

   2. Taylor expanded in y2 around inf 35.6%

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

   3. Taylor expanded in y0 around inf 61.0%

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

      1. +-commutative 61.0%

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

      2. mul-1-neg 61.0%

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

      3. unsub-neg 61.0%

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

      4. *-commutative 61.0%

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

      5. *-commutative 61.0%

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

   5. Simplified 61.0%

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

   if 4.6000000000000002e151 < t

   1. Initial program 25.0%

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

   2. Taylor expanded in c around inf 46.4%

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

   3. Taylor expanded in t around inf 54.0%

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

      1. *-commutative 54.0%

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

   5. Simplified 54.0%

      \[\leadsto \color{blue}{c \cdot \left(t \cdot \left(i \cdot z - y4 \cdot y2\right)\right)} \]
3. Recombined 10 regimes into one program.

4. Final simplification 52.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -2.2 \cdot 10^{+138}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq -1.35 \cdot 10^{-62}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq 3.8 \cdot 10^{-266}:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y0 \cdot y2 - y \cdot i\right)\\ \mathbf{elif}\;t \leq 4.8 \cdot 10^{-227}:\\ \;\;\;\;\left(k \cdot y4\right) \cdot \left(y1 \cdot y2 - y \cdot b\right)\\ \mathbf{elif}\;t \leq 9.2 \cdot 10^{-142}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 1.25 \cdot 10^{-104}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq 7.5 \cdot 10^{-96}:\\ \;\;\;\;\left(x \cdot y2\right) \cdot \left(c \cdot y0 - a \cdot y1\right)\\ \mathbf{elif}\;t \leq 1.75 \cdot 10^{+45}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 4.6 \cdot 10^{+151}:\\ \;\;\;\;y2 \cdot \left(y0 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(t \cdot \left(z \cdot i - y2 \cdot y4\right)\right)\\ \end{array} \]

Alternative 15: 30.3% accurate, 3.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;t \leq -3.1 \cdot 10^{+140}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq -4.5 \cdot 10^{-65}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq 3.8 \cdot 10^{-266}:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y0 \cdot y2 - y \cdot i\right)\\ \mathbf{elif}\;t \leq 1.25 \cdot 10^{-227}:\\ \;\;\;\;\left(k \cdot y4\right) \cdot \left(y1 \cdot y2 - y \cdot b\right)\\ \mathbf{elif}\;t \leq 1.14 \cdot 10^{-144}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 1.36 \cdot 10^{-104}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq 6.8 \cdot 10^{-96}:\\ \;\;\;\;\left(x \cdot y2\right) \cdot \left(c \cdot y0 - a \cdot y1\right)\\ \mathbf{elif}\;t \leq 1.7 \cdot 10^{+45}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 1.3 \cdot 10^{+150}:\\ \;\;\;\;y2 \cdot \left(y0 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(i \cdot \left(z \cdot t - x \cdot y\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= t -3.1e+140)
   (* j (* t (- (* b y4) (* i y5))))
   (if (<= t -4.5e-65)
     (* c (* y4 (- (* y y3) (* t y2))))
     (if (<= t 3.8e-266)
       (* (* x c) (- (* y0 y2) (* y i)))
       (if (<= t 1.25e-227)
         (* (* k y4) (- (* y1 y2) (* y b)))
         (if (<= t 1.14e-144)
           (* b (* x (- (* y a) (* j y0))))
           (if (<= t 1.36e-104)
             (* c (* z (- (* t i) (* y0 y3))))
             (if (<= t 6.8e-96)
               (* (* x y2) (- (* c y0) (* a y1)))
               (if (<= t 1.7e+45)
                 (* j (* x (- (* i y1) (* b y0))))
                 (if (<= t 1.3e+150)
                   (* y2 (* y0 (- (* x c) (* k y5))))
                   (* c (* i (- (* z t) (* x y))))))))))))))

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+140) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (t <= -4.5e-65) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (t <= 3.8e-266) {
		tmp = (x * c) * ((y0 * y2) - (y * i));
	} else if (t <= 1.25e-227) {
		tmp = (k * y4) * ((y1 * y2) - (y * b));
	} else if (t <= 1.14e-144) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (t <= 1.36e-104) {
		tmp = c * (z * ((t * i) - (y0 * y3)));
	} else if (t <= 6.8e-96) {
		tmp = (x * y2) * ((c * y0) - (a * y1));
	} else if (t <= 1.7e+45) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (t <= 1.3e+150) {
		tmp = y2 * (y0 * ((x * c) - (k * y5)));
	} else {
		tmp = c * (i * ((z * t) - (x * y)));
	}
	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+140)) then
        tmp = j * (t * ((b * y4) - (i * y5)))
    else if (t <= (-4.5d-65)) then
        tmp = c * (y4 * ((y * y3) - (t * y2)))
    else if (t <= 3.8d-266) then
        tmp = (x * c) * ((y0 * y2) - (y * i))
    else if (t <= 1.25d-227) then
        tmp = (k * y4) * ((y1 * y2) - (y * b))
    else if (t <= 1.14d-144) then
        tmp = b * (x * ((y * a) - (j * y0)))
    else if (t <= 1.36d-104) then
        tmp = c * (z * ((t * i) - (y0 * y3)))
    else if (t <= 6.8d-96) then
        tmp = (x * y2) * ((c * y0) - (a * y1))
    else if (t <= 1.7d+45) then
        tmp = j * (x * ((i * y1) - (b * y0)))
    else if (t <= 1.3d+150) then
        tmp = y2 * (y0 * ((x * c) - (k * y5)))
    else
        tmp = c * (i * ((z * t) - (x * y)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (t <= -3.1e+140) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (t <= -4.5e-65) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (t <= 3.8e-266) {
		tmp = (x * c) * ((y0 * y2) - (y * i));
	} else if (t <= 1.25e-227) {
		tmp = (k * y4) * ((y1 * y2) - (y * b));
	} else if (t <= 1.14e-144) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (t <= 1.36e-104) {
		tmp = c * (z * ((t * i) - (y0 * y3)));
	} else if (t <= 6.8e-96) {
		tmp = (x * y2) * ((c * y0) - (a * y1));
	} else if (t <= 1.7e+45) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (t <= 1.3e+150) {
		tmp = y2 * (y0 * ((x * c) - (k * y5)));
	} else {
		tmp = c * (i * ((z * t) - (x * y)));
	}
	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+140:
		tmp = j * (t * ((b * y4) - (i * y5)))
	elif t <= -4.5e-65:
		tmp = c * (y4 * ((y * y3) - (t * y2)))
	elif t <= 3.8e-266:
		tmp = (x * c) * ((y0 * y2) - (y * i))
	elif t <= 1.25e-227:
		tmp = (k * y4) * ((y1 * y2) - (y * b))
	elif t <= 1.14e-144:
		tmp = b * (x * ((y * a) - (j * y0)))
	elif t <= 1.36e-104:
		tmp = c * (z * ((t * i) - (y0 * y3)))
	elif t <= 6.8e-96:
		tmp = (x * y2) * ((c * y0) - (a * y1))
	elif t <= 1.7e+45:
		tmp = j * (x * ((i * y1) - (b * y0)))
	elif t <= 1.3e+150:
		tmp = y2 * (y0 * ((x * c) - (k * y5)))
	else:
		tmp = c * (i * ((z * t) - (x * y)))
	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+140)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))));
	elseif (t <= -4.5e-65)
		tmp = Float64(c * Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2))));
	elseif (t <= 3.8e-266)
		tmp = Float64(Float64(x * c) * Float64(Float64(y0 * y2) - Float64(y * i)));
	elseif (t <= 1.25e-227)
		tmp = Float64(Float64(k * y4) * Float64(Float64(y1 * y2) - Float64(y * b)));
	elseif (t <= 1.14e-144)
		tmp = Float64(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))));
	elseif (t <= 1.36e-104)
		tmp = Float64(c * Float64(z * Float64(Float64(t * i) - Float64(y0 * y3))));
	elseif (t <= 6.8e-96)
		tmp = Float64(Float64(x * y2) * Float64(Float64(c * y0) - Float64(a * y1)));
	elseif (t <= 1.7e+45)
		tmp = Float64(j * Float64(x * Float64(Float64(i * y1) - Float64(b * y0))));
	elseif (t <= 1.3e+150)
		tmp = Float64(y2 * Float64(y0 * Float64(Float64(x * c) - Float64(k * y5))));
	else
		tmp = Float64(c * Float64(i * Float64(Float64(z * t) - Float64(x * y))));
	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+140)
		tmp = j * (t * ((b * y4) - (i * y5)));
	elseif (t <= -4.5e-65)
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	elseif (t <= 3.8e-266)
		tmp = (x * c) * ((y0 * y2) - (y * i));
	elseif (t <= 1.25e-227)
		tmp = (k * y4) * ((y1 * y2) - (y * b));
	elseif (t <= 1.14e-144)
		tmp = b * (x * ((y * a) - (j * y0)));
	elseif (t <= 1.36e-104)
		tmp = c * (z * ((t * i) - (y0 * y3)));
	elseif (t <= 6.8e-96)
		tmp = (x * y2) * ((c * y0) - (a * y1));
	elseif (t <= 1.7e+45)
		tmp = j * (x * ((i * y1) - (b * y0)));
	elseif (t <= 1.3e+150)
		tmp = y2 * (y0 * ((x * c) - (k * y5)));
	else
		tmp = c * (i * ((z * t) - (x * y)));
	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+140], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -4.5e-65], N[(c * N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 3.8e-266], N[(N[(x * c), $MachinePrecision] * N[(N[(y0 * y2), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.25e-227], N[(N[(k * y4), $MachinePrecision] * N[(N[(y1 * y2), $MachinePrecision] - N[(y * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.14e-144], N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.36e-104], N[(c * N[(z * N[(N[(t * i), $MachinePrecision] - N[(y0 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 6.8e-96], N[(N[(x * y2), $MachinePrecision] * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.7e+45], N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.3e+150], N[(y2 * N[(y0 * N[(N[(x * c), $MachinePrecision] - N[(k * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(c * N[(i * N[(N[(z * t), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]

Derivation

1. Split input into 10 regimes

2. if t < -3.1e140

   1. Initial program 18.6%

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

   2. Taylor expanded in j around inf 39.9%

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

      1. +-commutative 39.9%

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

      2. mul-1-neg 39.9%

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

      3. unsub-neg 39.9%

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

      4. *-commutative 39.9%

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

   4. Simplified 39.9%

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

   5. Taylor expanded in t around inf 50.4%

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

   if -3.1e140 < t < -4.4999999999999998e-65

   1. Initial program 23.5%

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

   2. Taylor expanded in y4 around inf 47.3%

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

   3. Taylor expanded in c around inf 52.3%

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

      1. *-commutative 52.3%

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

   5. Simplified 52.3%

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

   if -4.4999999999999998e-65 < t < 3.79999999999999994e-266

   1. Initial program 40.0%

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

   2. Taylor expanded in c around inf 50.8%

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

   3. Taylor expanded in x around inf 49.3%

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

      1. associate-*r* 49.3%

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

      2. +-commutative 49.3%

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

      3. mul-1-neg 49.3%

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

      4. unsub-neg 49.3%

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

   5. Simplified 49.3%

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

   if 3.79999999999999994e-266 < t < 1.2499999999999999e-227

   1. Initial program 28.6%

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

   2. Taylor expanded in y4 around inf 50.4%

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

   3. Taylor expanded in k around inf 65.1%

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

      1. associate-*r* 58.2%

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

      2. *-commutative 58.2%

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

      3. +-commutative 58.2%

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

      4. mul-1-neg 58.2%

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

      5. unsub-neg 58.2%

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

   5. Simplified 58.2%

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

   if 1.2499999999999999e-227 < t < 1.14000000000000006e-144

   1. Initial program 21.5%

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

   2. Taylor expanded in b around inf 42.6%

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

   3. Taylor expanded in x around inf 54.2%

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

      1. *-commutative 54.2%

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

   5. Simplified 54.2%

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

   if 1.14000000000000006e-144 < t < 1.35999999999999997e-104

   1. Initial program 51.0%

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

   2. Taylor expanded in c around inf 39.3%

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

   3. Taylor expanded in z around inf 51.2%

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

      1. *-commutative 51.2%

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

      2. +-commutative 51.2%

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

      3. mul-1-neg 51.2%

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

      4. sub-neg 51.2%

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

      5. *-commutative 51.2%

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

   5. Simplified 51.2%

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

   if 1.35999999999999997e-104 < t < 6.8000000000000002e-96

   1. Initial program 40.0%

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

   2. Taylor expanded in y2 around inf 79.7%

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

   3. Taylor expanded in t around 0 80.0%

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

   4. Taylor expanded in x around inf 81.2%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 96.9%

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

      2. *-commutative 96.9%

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

      3. *-commutative 96.9%

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

      4. *-lft-identity 96.9%

         \[\leadsto \color{blue}{\left(1 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \cdot \left(y2 \cdot x\right) \]

      5. *-lft-identity 96.9%

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

      6. *-commutative 96.9%

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

      7. *-commutative 96.9%

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

   6. Simplified 96.9%

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

   if 6.8000000000000002e-96 < t < 1.7e45

   1. Initial program 32.8%

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

   2. Taylor expanded in j around inf 52.7%

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

      1. +-commutative 52.7%

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

      2. mul-1-neg 52.7%

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

      3. unsub-neg 52.7%

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

      4. *-commutative 52.7%

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

   4. Simplified 52.7%

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

   5. Taylor expanded in x around inf 40.4%

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

   if 1.7e45 < t < 1.30000000000000003e150

   1. Initial program 26.3%

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

   2. Taylor expanded in y2 around inf 32.3%

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

   3. Taylor expanded in y0 around inf 64.1%

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

      1. +-commutative 64.1%

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

      2. mul-1-neg 64.1%

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

      3. unsub-neg 64.1%

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

      4. *-commutative 64.1%

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

      5. *-commutative 64.1%

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

   5. Simplified 64.1%

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

   if 1.30000000000000003e150 < t

   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. Taylor expanded in c around inf 44.8%

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

   3. Taylor expanded in i around inf 59.0%

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

      1. neg-mul-1 59.0%

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

      2. distribute-rgt-neg-in 59.0%

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

   5. Simplified 59.0%

      \[\leadsto c \cdot \color{blue}{\left(i \cdot \left(-\left(x \cdot y - t \cdot z\right)\right)\right)} \]
3. Recombined 10 regimes into one program.

4. Final simplification 52.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -3.1 \cdot 10^{+140}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq -4.5 \cdot 10^{-65}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq 3.8 \cdot 10^{-266}:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y0 \cdot y2 - y \cdot i\right)\\ \mathbf{elif}\;t \leq 1.25 \cdot 10^{-227}:\\ \;\;\;\;\left(k \cdot y4\right) \cdot \left(y1 \cdot y2 - y \cdot b\right)\\ \mathbf{elif}\;t \leq 1.14 \cdot 10^{-144}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 1.36 \cdot 10^{-104}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)\\ \mathbf{elif}\;t \leq 6.8 \cdot 10^{-96}:\\ \;\;\;\;\left(x \cdot y2\right) \cdot \left(c \cdot y0 - a \cdot y1\right)\\ \mathbf{elif}\;t \leq 1.7 \cdot 10^{+45}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 1.3 \cdot 10^{+150}:\\ \;\;\;\;y2 \cdot \left(y0 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(i \cdot \left(z \cdot t - x \cdot y\right)\right)\\ \end{array} \]

Alternative 16: 30.7% accurate, 3.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;t \leq -2.1 \cdot 10^{+142}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq -6 \cdot 10^{-63}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq 3.8 \cdot 10^{-266}:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y0 \cdot y2 - y \cdot i\right)\\ \mathbf{elif}\;t \leq 1.35 \cdot 10^{-226}:\\ \;\;\;\;\left(k \cdot y4\right) \cdot \left(y1 \cdot y2 - y \cdot b\right)\\ \mathbf{elif}\;t \leq 1.4 \cdot 10^{-164}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 1.12 \cdot 10^{-104}:\\ \;\;\;\;y1 \cdot \left(y3 \cdot \left(z \cdot a - j \cdot y4\right)\right)\\ \mathbf{elif}\;t \leq 9.5 \cdot 10^{-96}:\\ \;\;\;\;\left(x \cdot y2\right) \cdot \left(c \cdot y0 - a \cdot y1\right)\\ \mathbf{elif}\;t \leq 1.7 \cdot 10^{+45}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 6.7 \cdot 10^{+149}:\\ \;\;\;\;y2 \cdot \left(y0 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(i \cdot \left(z \cdot t - x \cdot y\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= t -2.1e+142)
   (* j (* t (- (* b y4) (* i y5))))
   (if (<= t -6e-63)
     (* c (* y4 (- (* y y3) (* t y2))))
     (if (<= t 3.8e-266)
       (* (* x c) (- (* y0 y2) (* y i)))
       (if (<= t 1.35e-226)
         (* (* k y4) (- (* y1 y2) (* y b)))
         (if (<= t 1.4e-164)
           (* b (* x (- (* y a) (* j y0))))
           (if (<= t 1.12e-104)
             (* y1 (* y3 (- (* z a) (* j y4))))
             (if (<= t 9.5e-96)
               (* (* x y2) (- (* c y0) (* a y1)))
               (if (<= t 1.7e+45)
                 (* j (* x (- (* i y1) (* b y0))))
                 (if (<= t 6.7e+149)
                   (* y2 (* y0 (- (* x c) (* k y5))))
                   (* c (* i (- (* z t) (* x y))))))))))))))

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 <= -2.1e+142) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (t <= -6e-63) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (t <= 3.8e-266) {
		tmp = (x * c) * ((y0 * y2) - (y * i));
	} else if (t <= 1.35e-226) {
		tmp = (k * y4) * ((y1 * y2) - (y * b));
	} else if (t <= 1.4e-164) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (t <= 1.12e-104) {
		tmp = y1 * (y3 * ((z * a) - (j * y4)));
	} else if (t <= 9.5e-96) {
		tmp = (x * y2) * ((c * y0) - (a * y1));
	} else if (t <= 1.7e+45) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (t <= 6.7e+149) {
		tmp = y2 * (y0 * ((x * c) - (k * y5)));
	} else {
		tmp = c * (i * ((z * t) - (x * y)));
	}
	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 <= (-2.1d+142)) then
        tmp = j * (t * ((b * y4) - (i * y5)))
    else if (t <= (-6d-63)) then
        tmp = c * (y4 * ((y * y3) - (t * y2)))
    else if (t <= 3.8d-266) then
        tmp = (x * c) * ((y0 * y2) - (y * i))
    else if (t <= 1.35d-226) then
        tmp = (k * y4) * ((y1 * y2) - (y * b))
    else if (t <= 1.4d-164) then
        tmp = b * (x * ((y * a) - (j * y0)))
    else if (t <= 1.12d-104) then
        tmp = y1 * (y3 * ((z * a) - (j * y4)))
    else if (t <= 9.5d-96) then
        tmp = (x * y2) * ((c * y0) - (a * y1))
    else if (t <= 1.7d+45) then
        tmp = j * (x * ((i * y1) - (b * y0)))
    else if (t <= 6.7d+149) then
        tmp = y2 * (y0 * ((x * c) - (k * y5)))
    else
        tmp = c * (i * ((z * t) - (x * y)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (t <= -2.1e+142) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (t <= -6e-63) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (t <= 3.8e-266) {
		tmp = (x * c) * ((y0 * y2) - (y * i));
	} else if (t <= 1.35e-226) {
		tmp = (k * y4) * ((y1 * y2) - (y * b));
	} else if (t <= 1.4e-164) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (t <= 1.12e-104) {
		tmp = y1 * (y3 * ((z * a) - (j * y4)));
	} else if (t <= 9.5e-96) {
		tmp = (x * y2) * ((c * y0) - (a * y1));
	} else if (t <= 1.7e+45) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (t <= 6.7e+149) {
		tmp = y2 * (y0 * ((x * c) - (k * y5)));
	} else {
		tmp = c * (i * ((z * t) - (x * y)));
	}
	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 <= -2.1e+142:
		tmp = j * (t * ((b * y4) - (i * y5)))
	elif t <= -6e-63:
		tmp = c * (y4 * ((y * y3) - (t * y2)))
	elif t <= 3.8e-266:
		tmp = (x * c) * ((y0 * y2) - (y * i))
	elif t <= 1.35e-226:
		tmp = (k * y4) * ((y1 * y2) - (y * b))
	elif t <= 1.4e-164:
		tmp = b * (x * ((y * a) - (j * y0)))
	elif t <= 1.12e-104:
		tmp = y1 * (y3 * ((z * a) - (j * y4)))
	elif t <= 9.5e-96:
		tmp = (x * y2) * ((c * y0) - (a * y1))
	elif t <= 1.7e+45:
		tmp = j * (x * ((i * y1) - (b * y0)))
	elif t <= 6.7e+149:
		tmp = y2 * (y0 * ((x * c) - (k * y5)))
	else:
		tmp = c * (i * ((z * t) - (x * y)))
	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 <= -2.1e+142)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))));
	elseif (t <= -6e-63)
		tmp = Float64(c * Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2))));
	elseif (t <= 3.8e-266)
		tmp = Float64(Float64(x * c) * Float64(Float64(y0 * y2) - Float64(y * i)));
	elseif (t <= 1.35e-226)
		tmp = Float64(Float64(k * y4) * Float64(Float64(y1 * y2) - Float64(y * b)));
	elseif (t <= 1.4e-164)
		tmp = Float64(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))));
	elseif (t <= 1.12e-104)
		tmp = Float64(y1 * Float64(y3 * Float64(Float64(z * a) - Float64(j * y4))));
	elseif (t <= 9.5e-96)
		tmp = Float64(Float64(x * y2) * Float64(Float64(c * y0) - Float64(a * y1)));
	elseif (t <= 1.7e+45)
		tmp = Float64(j * Float64(x * Float64(Float64(i * y1) - Float64(b * y0))));
	elseif (t <= 6.7e+149)
		tmp = Float64(y2 * Float64(y0 * Float64(Float64(x * c) - Float64(k * y5))));
	else
		tmp = Float64(c * Float64(i * Float64(Float64(z * t) - Float64(x * y))));
	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 <= -2.1e+142)
		tmp = j * (t * ((b * y4) - (i * y5)));
	elseif (t <= -6e-63)
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	elseif (t <= 3.8e-266)
		tmp = (x * c) * ((y0 * y2) - (y * i));
	elseif (t <= 1.35e-226)
		tmp = (k * y4) * ((y1 * y2) - (y * b));
	elseif (t <= 1.4e-164)
		tmp = b * (x * ((y * a) - (j * y0)));
	elseif (t <= 1.12e-104)
		tmp = y1 * (y3 * ((z * a) - (j * y4)));
	elseif (t <= 9.5e-96)
		tmp = (x * y2) * ((c * y0) - (a * y1));
	elseif (t <= 1.7e+45)
		tmp = j * (x * ((i * y1) - (b * y0)));
	elseif (t <= 6.7e+149)
		tmp = y2 * (y0 * ((x * c) - (k * y5)));
	else
		tmp = c * (i * ((z * t) - (x * y)));
	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, -2.1e+142], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -6e-63], N[(c * N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 3.8e-266], N[(N[(x * c), $MachinePrecision] * N[(N[(y0 * y2), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.35e-226], N[(N[(k * y4), $MachinePrecision] * N[(N[(y1 * y2), $MachinePrecision] - N[(y * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.4e-164], N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.12e-104], N[(y1 * N[(y3 * N[(N[(z * a), $MachinePrecision] - N[(j * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 9.5e-96], N[(N[(x * y2), $MachinePrecision] * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.7e+45], N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 6.7e+149], N[(y2 * N[(y0 * N[(N[(x * c), $MachinePrecision] - N[(k * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(c * N[(i * N[(N[(z * t), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]

Derivation

1. Split input into 10 regimes

2. if t < -2.1e142

   1. Initial program 18.6%

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

   2. Taylor expanded in j around inf 39.9%

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

      1. +-commutative 39.9%

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

      2. mul-1-neg 39.9%

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

      3. unsub-neg 39.9%

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

      4. *-commutative 39.9%

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

   4. Simplified 39.9%

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

   5. Taylor expanded in t around inf 50.4%

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

   if -2.1e142 < t < -5.99999999999999959e-63

   1. Initial program 23.5%

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

   2. Taylor expanded in y4 around inf 47.3%

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

   3. Taylor expanded in c around inf 52.3%

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

      1. *-commutative 52.3%

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

   5. Simplified 52.3%

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

   if -5.99999999999999959e-63 < t < 3.79999999999999994e-266

   1. Initial program 40.0%

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

   2. Taylor expanded in c around inf 50.8%

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

   3. Taylor expanded in x around inf 49.3%

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

      1. associate-*r* 49.3%

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

      2. +-commutative 49.3%

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

      3. mul-1-neg 49.3%

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

      4. unsub-neg 49.3%

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

   5. Simplified 49.3%

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

   if 3.79999999999999994e-266 < t < 1.35000000000000007e-226

   1. Initial program 28.6%

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

   2. Taylor expanded in y4 around inf 50.4%

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

   3. Taylor expanded in k around inf 65.1%

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

      1. associate-*r* 58.2%

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

      2. *-commutative 58.2%

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

      3. +-commutative 58.2%

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

      4. mul-1-neg 58.2%

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

      5. unsub-neg 58.2%

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

   5. Simplified 58.2%

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

   if 1.35000000000000007e-226 < t < 1.4000000000000001e-164

   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. Taylor expanded in b around inf 44.3%

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

   3. Taylor expanded in x around inf 57.2%

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

      1. *-commutative 57.2%

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

   5. Simplified 57.2%

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

   if 1.4000000000000001e-164 < t < 1.12e-104

   1. Initial program 37.1%

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

   2. Taylor expanded in y3 around -inf 73.4%

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

   3. Taylor expanded in y1 around inf 56.0%

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

      1. +-commutative 56.0%

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

      2. mul-1-neg 56.0%

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

      3. unsub-neg 56.0%

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

      4. *-commutative 56.0%

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

   5. Simplified 56.0%

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

   if 1.12e-104 < t < 9.4999999999999993e-96

   1. Initial program 40.0%

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

   2. Taylor expanded in y2 around inf 79.7%

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

   3. Taylor expanded in t around 0 80.0%

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

   4. Taylor expanded in x around inf 81.2%

      \[\leadsto \color{blue}{x \cdot \left(y2 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]
   5. Step-by-step derivation

      1. associate-*r* 96.9%

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

      2. *-commutative 96.9%

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

      3. *-commutative 96.9%

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

      4. *-lft-identity 96.9%

         \[\leadsto \color{blue}{\left(1 \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \cdot \left(y2 \cdot x\right) \]

      5. *-lft-identity 96.9%

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

      6. *-commutative 96.9%

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

      7. *-commutative 96.9%

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

   6. Simplified 96.9%

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

   if 9.4999999999999993e-96 < t < 1.7e45

   1. Initial program 32.8%

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

   2. Taylor expanded in j around inf 52.7%

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

      1. +-commutative 52.7%

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

      2. mul-1-neg 52.7%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 52.7%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 52.7%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 52.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in x around inf 40.4%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   if 1.7e45 < t < 6.69999999999999982e149

   1. Initial program 26.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y2 around inf 32.3%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   3. Taylor expanded in y0 around inf 64.1%

      \[\leadsto y2 \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(k \cdot y5\right) + c \cdot x\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 64.1%

         \[\leadsto y2 \cdot \left(y0 \cdot \color{blue}{\left(c \cdot x + -1 \cdot \left(k \cdot y5\right)\right)}\right) \]

      2. mul-1-neg 64.1%

         \[\leadsto y2 \cdot \left(y0 \cdot \left(c \cdot x + \color{blue}{\left(-k \cdot y5\right)}\right)\right) \]

      3. unsub-neg 64.1%

         \[\leadsto y2 \cdot \left(y0 \cdot \color{blue}{\left(c \cdot x - k \cdot y5\right)}\right) \]

      4. *-commutative 64.1%

         \[\leadsto y2 \cdot \left(y0 \cdot \left(\color{blue}{x \cdot c} - k \cdot y5\right)\right) \]

      5. *-commutative 64.1%

         \[\leadsto y2 \cdot \left(y0 \cdot \left(x \cdot c - \color{blue}{y5 \cdot k}\right)\right) \]

   5. Simplified 64.1%

      \[\leadsto y2 \cdot \color{blue}{\left(y0 \cdot \left(x \cdot c - y5 \cdot k\right)\right)} \]

   if 6.69999999999999982e149 < t

   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. Taylor expanded in c around inf 44.8%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in i around inf 59.0%

      \[\leadsto c \cdot \color{blue}{\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right)\right)} \]
   4. Step-by-step derivation

      1. neg-mul-1 59.0%

         \[\leadsto c \cdot \color{blue}{\left(-i \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

      2. distribute-rgt-neg-in 59.0%

         \[\leadsto c \cdot \color{blue}{\left(i \cdot \left(-\left(x \cdot y - t \cdot z\right)\right)\right)} \]

   5. Simplified 59.0%

      \[\leadsto c \cdot \color{blue}{\left(i \cdot \left(-\left(x \cdot y - t \cdot z\right)\right)\right)} \]
3. Recombined 10 regimes into one program.

4. Final simplification 53.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -2.1 \cdot 10^{+142}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq -6 \cdot 10^{-63}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq 3.8 \cdot 10^{-266}:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y0 \cdot y2 - y \cdot i\right)\\ \mathbf{elif}\;t \leq 1.35 \cdot 10^{-226}:\\ \;\;\;\;\left(k \cdot y4\right) \cdot \left(y1 \cdot y2 - y \cdot b\right)\\ \mathbf{elif}\;t \leq 1.4 \cdot 10^{-164}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 1.12 \cdot 10^{-104}:\\ \;\;\;\;y1 \cdot \left(y3 \cdot \left(z \cdot a - j \cdot y4\right)\right)\\ \mathbf{elif}\;t \leq 9.5 \cdot 10^{-96}:\\ \;\;\;\;\left(x \cdot y2\right) \cdot \left(c \cdot y0 - a \cdot y1\right)\\ \mathbf{elif}\;t \leq 1.7 \cdot 10^{+45}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 6.7 \cdot 10^{+149}:\\ \;\;\;\;y2 \cdot \left(y0 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(i \cdot \left(z \cdot t - x \cdot y\right)\right)\\ \end{array} \]

Alternative 17: 30.5% accurate, 3.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;t \leq -1.45 \cdot 10^{+144}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq -1.1 \cdot 10^{-61}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq 3.8 \cdot 10^{-266}:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y0 \cdot y2 - y \cdot i\right)\\ \mathbf{elif}\;t \leq 1.45 \cdot 10^{-225}:\\ \;\;\;\;\left(k \cdot y4\right) \cdot \left(y1 \cdot y2 - y \cdot b\right)\\ \mathbf{elif}\;t \leq 1.7 \cdot 10^{-144}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 8 \cdot 10^{-96}:\\ \;\;\;\;\left(z \cdot y3\right) \cdot \left(a \cdot y1 - c \cdot y0\right)\\ \mathbf{elif}\;t \leq 1.75 \cdot 10^{+45}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 1.05 \cdot 10^{+151}:\\ \;\;\;\;y2 \cdot \left(y0 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(i \cdot \left(z \cdot t - x \cdot y\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= t -1.45e+144)
   (* j (* t (- (* b y4) (* i y5))))
   (if (<= t -1.1e-61)
     (* c (* y4 (- (* y y3) (* t y2))))
     (if (<= t 3.8e-266)
       (* (* x c) (- (* y0 y2) (* y i)))
       (if (<= t 1.45e-225)
         (* (* k y4) (- (* y1 y2) (* y b)))
         (if (<= t 1.7e-144)
           (* b (* x (- (* y a) (* j y0))))
           (if (<= t 8e-96)
             (* (* z y3) (- (* a y1) (* c y0)))
             (if (<= t 1.75e+45)
               (* j (* x (- (* i y1) (* b y0))))
               (if (<= t 1.05e+151)
                 (* y2 (* y0 (- (* x c) (* k y5))))
                 (* c (* i (- (* z t) (* x y)))))))))))))

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 <= -1.45e+144) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (t <= -1.1e-61) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (t <= 3.8e-266) {
		tmp = (x * c) * ((y0 * y2) - (y * i));
	} else if (t <= 1.45e-225) {
		tmp = (k * y4) * ((y1 * y2) - (y * b));
	} else if (t <= 1.7e-144) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (t <= 8e-96) {
		tmp = (z * y3) * ((a * y1) - (c * y0));
	} else if (t <= 1.75e+45) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (t <= 1.05e+151) {
		tmp = y2 * (y0 * ((x * c) - (k * y5)));
	} else {
		tmp = c * (i * ((z * t) - (x * y)));
	}
	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 <= (-1.45d+144)) then
        tmp = j * (t * ((b * y4) - (i * y5)))
    else if (t <= (-1.1d-61)) then
        tmp = c * (y4 * ((y * y3) - (t * y2)))
    else if (t <= 3.8d-266) then
        tmp = (x * c) * ((y0 * y2) - (y * i))
    else if (t <= 1.45d-225) then
        tmp = (k * y4) * ((y1 * y2) - (y * b))
    else if (t <= 1.7d-144) then
        tmp = b * (x * ((y * a) - (j * y0)))
    else if (t <= 8d-96) then
        tmp = (z * y3) * ((a * y1) - (c * y0))
    else if (t <= 1.75d+45) then
        tmp = j * (x * ((i * y1) - (b * y0)))
    else if (t <= 1.05d+151) then
        tmp = y2 * (y0 * ((x * c) - (k * y5)))
    else
        tmp = c * (i * ((z * t) - (x * y)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (t <= -1.45e+144) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (t <= -1.1e-61) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (t <= 3.8e-266) {
		tmp = (x * c) * ((y0 * y2) - (y * i));
	} else if (t <= 1.45e-225) {
		tmp = (k * y4) * ((y1 * y2) - (y * b));
	} else if (t <= 1.7e-144) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (t <= 8e-96) {
		tmp = (z * y3) * ((a * y1) - (c * y0));
	} else if (t <= 1.75e+45) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (t <= 1.05e+151) {
		tmp = y2 * (y0 * ((x * c) - (k * y5)));
	} else {
		tmp = c * (i * ((z * t) - (x * y)));
	}
	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 <= -1.45e+144:
		tmp = j * (t * ((b * y4) - (i * y5)))
	elif t <= -1.1e-61:
		tmp = c * (y4 * ((y * y3) - (t * y2)))
	elif t <= 3.8e-266:
		tmp = (x * c) * ((y0 * y2) - (y * i))
	elif t <= 1.45e-225:
		tmp = (k * y4) * ((y1 * y2) - (y * b))
	elif t <= 1.7e-144:
		tmp = b * (x * ((y * a) - (j * y0)))
	elif t <= 8e-96:
		tmp = (z * y3) * ((a * y1) - (c * y0))
	elif t <= 1.75e+45:
		tmp = j * (x * ((i * y1) - (b * y0)))
	elif t <= 1.05e+151:
		tmp = y2 * (y0 * ((x * c) - (k * y5)))
	else:
		tmp = c * (i * ((z * t) - (x * y)))
	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 <= -1.45e+144)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))));
	elseif (t <= -1.1e-61)
		tmp = Float64(c * Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2))));
	elseif (t <= 3.8e-266)
		tmp = Float64(Float64(x * c) * Float64(Float64(y0 * y2) - Float64(y * i)));
	elseif (t <= 1.45e-225)
		tmp = Float64(Float64(k * y4) * Float64(Float64(y1 * y2) - Float64(y * b)));
	elseif (t <= 1.7e-144)
		tmp = Float64(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))));
	elseif (t <= 8e-96)
		tmp = Float64(Float64(z * y3) * Float64(Float64(a * y1) - Float64(c * y0)));
	elseif (t <= 1.75e+45)
		tmp = Float64(j * Float64(x * Float64(Float64(i * y1) - Float64(b * y0))));
	elseif (t <= 1.05e+151)
		tmp = Float64(y2 * Float64(y0 * Float64(Float64(x * c) - Float64(k * y5))));
	else
		tmp = Float64(c * Float64(i * Float64(Float64(z * t) - Float64(x * y))));
	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 <= -1.45e+144)
		tmp = j * (t * ((b * y4) - (i * y5)));
	elseif (t <= -1.1e-61)
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	elseif (t <= 3.8e-266)
		tmp = (x * c) * ((y0 * y2) - (y * i));
	elseif (t <= 1.45e-225)
		tmp = (k * y4) * ((y1 * y2) - (y * b));
	elseif (t <= 1.7e-144)
		tmp = b * (x * ((y * a) - (j * y0)));
	elseif (t <= 8e-96)
		tmp = (z * y3) * ((a * y1) - (c * y0));
	elseif (t <= 1.75e+45)
		tmp = j * (x * ((i * y1) - (b * y0)));
	elseif (t <= 1.05e+151)
		tmp = y2 * (y0 * ((x * c) - (k * y5)));
	else
		tmp = c * (i * ((z * t) - (x * y)));
	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, -1.45e+144], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -1.1e-61], N[(c * N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 3.8e-266], N[(N[(x * c), $MachinePrecision] * N[(N[(y0 * y2), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.45e-225], N[(N[(k * y4), $MachinePrecision] * N[(N[(y1 * y2), $MachinePrecision] - N[(y * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.7e-144], N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 8e-96], N[(N[(z * y3), $MachinePrecision] * N[(N[(a * y1), $MachinePrecision] - N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.75e+45], N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.05e+151], N[(y2 * N[(y0 * N[(N[(x * c), $MachinePrecision] - N[(k * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(c * N[(i * N[(N[(z * t), $MachinePrecision] - N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]

Derivation

1. Split input into 9 regimes

2. if t < -1.44999999999999999e144

   1. Initial program 18.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 39.9%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 39.9%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 39.9%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 39.9%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 39.9%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 39.9%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in t around inf 50.4%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   if -1.44999999999999999e144 < t < -1.10000000000000004e-61

   1. Initial program 23.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf 47.3%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in c around inf 52.3%

      \[\leadsto \color{blue}{c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 52.3%

         \[\leadsto c \cdot \left(y4 \cdot \left(\color{blue}{y3 \cdot y} - t \cdot y2\right)\right) \]

   5. Simplified 52.3%

      \[\leadsto \color{blue}{c \cdot \left(y4 \cdot \left(y3 \cdot y - t \cdot y2\right)\right)} \]

   if -1.10000000000000004e-61 < t < 3.79999999999999994e-266

   1. Initial program 40.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in c around inf 50.8%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in x around inf 49.3%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 49.3%

         \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)} \]

      2. +-commutative 49.3%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 + -1 \cdot \left(i \cdot y\right)\right)} \]

      3. mul-1-neg 49.3%

         \[\leadsto \left(c \cdot x\right) \cdot \left(y0 \cdot y2 + \color{blue}{\left(-i \cdot y\right)}\right) \]

      4. unsub-neg 49.3%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 - i \cdot y\right)} \]

   5. Simplified 49.3%

      \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(y0 \cdot y2 - i \cdot y\right)} \]

   if 3.79999999999999994e-266 < t < 1.4499999999999999e-225

   1. Initial program 28.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf 50.4%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in k around inf 65.1%

      \[\leadsto \color{blue}{k \cdot \left(y4 \cdot \left(-1 \cdot \left(b \cdot y\right) + y1 \cdot y2\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 58.2%

         \[\leadsto \color{blue}{\left(k \cdot y4\right) \cdot \left(-1 \cdot \left(b \cdot y\right) + y1 \cdot y2\right)} \]

      2. *-commutative 58.2%

         \[\leadsto \color{blue}{\left(y4 \cdot k\right)} \cdot \left(-1 \cdot \left(b \cdot y\right) + y1 \cdot y2\right) \]

      3. +-commutative 58.2%

         \[\leadsto \left(y4 \cdot k\right) \cdot \color{blue}{\left(y1 \cdot y2 + -1 \cdot \left(b \cdot y\right)\right)} \]

      4. mul-1-neg 58.2%

         \[\leadsto \left(y4 \cdot k\right) \cdot \left(y1 \cdot y2 + \color{blue}{\left(-b \cdot y\right)}\right) \]

      5. unsub-neg 58.2%

         \[\leadsto \left(y4 \cdot k\right) \cdot \color{blue}{\left(y1 \cdot y2 - b \cdot y\right)} \]

   5. Simplified 58.2%

      \[\leadsto \color{blue}{\left(y4 \cdot k\right) \cdot \left(y1 \cdot y2 - b \cdot y\right)} \]

   if 1.4499999999999999e-225 < t < 1.70000000000000009e-144

   1. Initial program 21.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 42.6%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in x around inf 54.2%

      \[\leadsto \color{blue}{b \cdot \left(x \cdot \left(a \cdot y - j \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 54.2%

         \[\leadsto b \cdot \left(x \cdot \left(\color{blue}{y \cdot a} - j \cdot y0\right)\right) \]

   5. Simplified 54.2%

      \[\leadsto \color{blue}{b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)} \]

   if 1.70000000000000009e-144 < t < 7.9999999999999993e-96

   1. Initial program 46.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y3 around -inf 54.7%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   3. Taylor expanded in z around inf 63.1%

      \[\leadsto -1 \cdot \color{blue}{\left(y3 \cdot \left(z \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 56.3%

         \[\leadsto -1 \cdot \color{blue}{\left(\left(y3 \cdot z\right) \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

      2. *-commutative 56.3%

         \[\leadsto -1 \cdot \left(\left(y3 \cdot z\right) \cdot \left(\color{blue}{y0 \cdot c} - a \cdot y1\right)\right) \]

      3. *-commutative 56.3%

         \[\leadsto -1 \cdot \left(\left(y3 \cdot z\right) \cdot \left(y0 \cdot c - \color{blue}{y1 \cdot a}\right)\right) \]

   5. Simplified 56.3%

      \[\leadsto -1 \cdot \color{blue}{\left(\left(y3 \cdot z\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right)} \]

   if 7.9999999999999993e-96 < t < 1.75000000000000011e45

   1. Initial program 32.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 52.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 52.7%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 52.7%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 52.7%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 52.7%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 52.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in x around inf 40.4%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   if 1.75000000000000011e45 < t < 1.05e151

   1. Initial program 26.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y2 around inf 32.3%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   3. Taylor expanded in y0 around inf 64.1%

      \[\leadsto y2 \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(k \cdot y5\right) + c \cdot x\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 64.1%

         \[\leadsto y2 \cdot \left(y0 \cdot \color{blue}{\left(c \cdot x + -1 \cdot \left(k \cdot y5\right)\right)}\right) \]

      2. mul-1-neg 64.1%

         \[\leadsto y2 \cdot \left(y0 \cdot \left(c \cdot x + \color{blue}{\left(-k \cdot y5\right)}\right)\right) \]

      3. unsub-neg 64.1%

         \[\leadsto y2 \cdot \left(y0 \cdot \color{blue}{\left(c \cdot x - k \cdot y5\right)}\right) \]

      4. *-commutative 64.1%

         \[\leadsto y2 \cdot \left(y0 \cdot \left(\color{blue}{x \cdot c} - k \cdot y5\right)\right) \]

      5. *-commutative 64.1%

         \[\leadsto y2 \cdot \left(y0 \cdot \left(x \cdot c - \color{blue}{y5 \cdot k}\right)\right) \]

   5. Simplified 64.1%

      \[\leadsto y2 \cdot \color{blue}{\left(y0 \cdot \left(x \cdot c - y5 \cdot k\right)\right)} \]

   if 1.05e151 < t

   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. Taylor expanded in c around inf 44.8%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in i around inf 59.0%

      \[\leadsto c \cdot \color{blue}{\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right)\right)} \]
   4. Step-by-step derivation

      1. neg-mul-1 59.0%

         \[\leadsto c \cdot \color{blue}{\left(-i \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

      2. distribute-rgt-neg-in 59.0%

         \[\leadsto c \cdot \color{blue}{\left(i \cdot \left(-\left(x \cdot y - t \cdot z\right)\right)\right)} \]

   5. Simplified 59.0%

      \[\leadsto c \cdot \color{blue}{\left(i \cdot \left(-\left(x \cdot y - t \cdot z\right)\right)\right)} \]
3. Recombined 9 regimes into one program.

4. Final simplification 52.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -1.45 \cdot 10^{+144}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq -1.1 \cdot 10^{-61}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq 3.8 \cdot 10^{-266}:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y0 \cdot y2 - y \cdot i\right)\\ \mathbf{elif}\;t \leq 1.45 \cdot 10^{-225}:\\ \;\;\;\;\left(k \cdot y4\right) \cdot \left(y1 \cdot y2 - y \cdot b\right)\\ \mathbf{elif}\;t \leq 1.7 \cdot 10^{-144}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 8 \cdot 10^{-96}:\\ \;\;\;\;\left(z \cdot y3\right) \cdot \left(a \cdot y1 - c \cdot y0\right)\\ \mathbf{elif}\;t \leq 1.75 \cdot 10^{+45}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 1.05 \cdot 10^{+151}:\\ \;\;\;\;y2 \cdot \left(y0 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(i \cdot \left(z \cdot t - x \cdot y\right)\right)\\ \end{array} \]

Alternative 18: 31.6% accurate, 3.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;t \leq -6.6 \cdot 10^{+137}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq -1.85 \cdot 10^{-65}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq 3.8 \cdot 10^{-266}:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y0 \cdot y2 - y \cdot i\right)\\ \mathbf{elif}\;t \leq 2.1 \cdot 10^{-221}:\\ \;\;\;\;\left(k \cdot y4\right) \cdot \left(y1 \cdot y2 - y \cdot b\right)\\ \mathbf{elif}\;t \leq 6.8 \cdot 10^{-96}:\\ \;\;\;\;y2 \cdot \left(x \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq 1.65 \cdot 10^{+45}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 6.2 \cdot 10^{+151}:\\ \;\;\;\;y2 \cdot \left(y0 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(t \cdot \left(z \cdot i - y2 \cdot y4\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= t -6.6e+137)
   (* j (* t (- (* b y4) (* i y5))))
   (if (<= t -1.85e-65)
     (* c (* y4 (- (* y y3) (* t y2))))
     (if (<= t 3.8e-266)
       (* (* x c) (- (* y0 y2) (* y i)))
       (if (<= t 2.1e-221)
         (* (* k y4) (- (* y1 y2) (* y b)))
         (if (<= t 6.8e-96)
           (* y2 (* x (- (* c y0) (* a y1))))
           (if (<= t 1.65e+45)
             (* j (* x (- (* i y1) (* b y0))))
             (if (<= t 6.2e+151)
               (* y2 (* y0 (- (* x c) (* k y5))))
               (* c (* t (- (* z i) (* 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 <= -6.6e+137) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (t <= -1.85e-65) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (t <= 3.8e-266) {
		tmp = (x * c) * ((y0 * y2) - (y * i));
	} else if (t <= 2.1e-221) {
		tmp = (k * y4) * ((y1 * y2) - (y * b));
	} else if (t <= 6.8e-96) {
		tmp = y2 * (x * ((c * y0) - (a * y1)));
	} else if (t <= 1.65e+45) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (t <= 6.2e+151) {
		tmp = y2 * (y0 * ((x * c) - (k * y5)));
	} else {
		tmp = c * (t * ((z * i) - (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 <= (-6.6d+137)) then
        tmp = j * (t * ((b * y4) - (i * y5)))
    else if (t <= (-1.85d-65)) then
        tmp = c * (y4 * ((y * y3) - (t * y2)))
    else if (t <= 3.8d-266) then
        tmp = (x * c) * ((y0 * y2) - (y * i))
    else if (t <= 2.1d-221) then
        tmp = (k * y4) * ((y1 * y2) - (y * b))
    else if (t <= 6.8d-96) then
        tmp = y2 * (x * ((c * y0) - (a * y1)))
    else if (t <= 1.65d+45) then
        tmp = j * (x * ((i * y1) - (b * y0)))
    else if (t <= 6.2d+151) then
        tmp = y2 * (y0 * ((x * c) - (k * y5)))
    else
        tmp = c * (t * ((z * i) - (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 <= -6.6e+137) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (t <= -1.85e-65) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (t <= 3.8e-266) {
		tmp = (x * c) * ((y0 * y2) - (y * i));
	} else if (t <= 2.1e-221) {
		tmp = (k * y4) * ((y1 * y2) - (y * b));
	} else if (t <= 6.8e-96) {
		tmp = y2 * (x * ((c * y0) - (a * y1)));
	} else if (t <= 1.65e+45) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else if (t <= 6.2e+151) {
		tmp = y2 * (y0 * ((x * c) - (k * y5)));
	} else {
		tmp = c * (t * ((z * i) - (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 <= -6.6e+137:
		tmp = j * (t * ((b * y4) - (i * y5)))
	elif t <= -1.85e-65:
		tmp = c * (y4 * ((y * y3) - (t * y2)))
	elif t <= 3.8e-266:
		tmp = (x * c) * ((y0 * y2) - (y * i))
	elif t <= 2.1e-221:
		tmp = (k * y4) * ((y1 * y2) - (y * b))
	elif t <= 6.8e-96:
		tmp = y2 * (x * ((c * y0) - (a * y1)))
	elif t <= 1.65e+45:
		tmp = j * (x * ((i * y1) - (b * y0)))
	elif t <= 6.2e+151:
		tmp = y2 * (y0 * ((x * c) - (k * y5)))
	else:
		tmp = c * (t * ((z * i) - (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 <= -6.6e+137)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))));
	elseif (t <= -1.85e-65)
		tmp = Float64(c * Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2))));
	elseif (t <= 3.8e-266)
		tmp = Float64(Float64(x * c) * Float64(Float64(y0 * y2) - Float64(y * i)));
	elseif (t <= 2.1e-221)
		tmp = Float64(Float64(k * y4) * Float64(Float64(y1 * y2) - Float64(y * b)));
	elseif (t <= 6.8e-96)
		tmp = Float64(y2 * Float64(x * Float64(Float64(c * y0) - Float64(a * y1))));
	elseif (t <= 1.65e+45)
		tmp = Float64(j * Float64(x * Float64(Float64(i * y1) - Float64(b * y0))));
	elseif (t <= 6.2e+151)
		tmp = Float64(y2 * Float64(y0 * Float64(Float64(x * c) - Float64(k * y5))));
	else
		tmp = Float64(c * Float64(t * Float64(Float64(z * i) - Float64(y2 * 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 <= -6.6e+137)
		tmp = j * (t * ((b * y4) - (i * y5)));
	elseif (t <= -1.85e-65)
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	elseif (t <= 3.8e-266)
		tmp = (x * c) * ((y0 * y2) - (y * i));
	elseif (t <= 2.1e-221)
		tmp = (k * y4) * ((y1 * y2) - (y * b));
	elseif (t <= 6.8e-96)
		tmp = y2 * (x * ((c * y0) - (a * y1)));
	elseif (t <= 1.65e+45)
		tmp = j * (x * ((i * y1) - (b * y0)));
	elseif (t <= 6.2e+151)
		tmp = y2 * (y0 * ((x * c) - (k * y5)));
	else
		tmp = c * (t * ((z * i) - (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, -6.6e+137], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -1.85e-65], N[(c * N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 3.8e-266], N[(N[(x * c), $MachinePrecision] * N[(N[(y0 * y2), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 2.1e-221], N[(N[(k * y4), $MachinePrecision] * N[(N[(y1 * y2), $MachinePrecision] - N[(y * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 6.8e-96], N[(y2 * N[(x * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.65e+45], N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 6.2e+151], N[(y2 * N[(y0 * N[(N[(x * c), $MachinePrecision] - N[(k * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(c * N[(t * N[(N[(z * i), $MachinePrecision] - N[(y2 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]

Derivation

1. Split input into 8 regimes

2. if t < -6.60000000000000005e137

   1. Initial program 18.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 39.9%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 39.9%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 39.9%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 39.9%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 39.9%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 39.9%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in t around inf 50.4%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   if -6.60000000000000005e137 < t < -1.85e-65

   1. Initial program 23.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf 47.3%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in c around inf 52.3%

      \[\leadsto \color{blue}{c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 52.3%

         \[\leadsto c \cdot \left(y4 \cdot \left(\color{blue}{y3 \cdot y} - t \cdot y2\right)\right) \]

   5. Simplified 52.3%

      \[\leadsto \color{blue}{c \cdot \left(y4 \cdot \left(y3 \cdot y - t \cdot y2\right)\right)} \]

   if -1.85e-65 < t < 3.79999999999999994e-266

   1. Initial program 40.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in c around inf 50.8%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in x around inf 49.3%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 49.3%

         \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)} \]

      2. +-commutative 49.3%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 + -1 \cdot \left(i \cdot y\right)\right)} \]

      3. mul-1-neg 49.3%

         \[\leadsto \left(c \cdot x\right) \cdot \left(y0 \cdot y2 + \color{blue}{\left(-i \cdot y\right)}\right) \]

      4. unsub-neg 49.3%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 - i \cdot y\right)} \]

   5. Simplified 49.3%

      \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(y0 \cdot y2 - i \cdot y\right)} \]

   if 3.79999999999999994e-266 < t < 2.1e-221

   1. Initial program 37.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf 50.5%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in k around inf 57.4%

      \[\leadsto \color{blue}{k \cdot \left(y4 \cdot \left(-1 \cdot \left(b \cdot y\right) + y1 \cdot y2\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 51.3%

         \[\leadsto \color{blue}{\left(k \cdot y4\right) \cdot \left(-1 \cdot \left(b \cdot y\right) + y1 \cdot y2\right)} \]

      2. *-commutative 51.3%

         \[\leadsto \color{blue}{\left(y4 \cdot k\right)} \cdot \left(-1 \cdot \left(b \cdot y\right) + y1 \cdot y2\right) \]

      3. +-commutative 51.3%

         \[\leadsto \left(y4 \cdot k\right) \cdot \color{blue}{\left(y1 \cdot y2 + -1 \cdot \left(b \cdot y\right)\right)} \]

      4. mul-1-neg 51.3%

         \[\leadsto \left(y4 \cdot k\right) \cdot \left(y1 \cdot y2 + \color{blue}{\left(-b \cdot y\right)}\right) \]

      5. unsub-neg 51.3%

         \[\leadsto \left(y4 \cdot k\right) \cdot \color{blue}{\left(y1 \cdot y2 - b \cdot y\right)} \]

   5. Simplified 51.3%

      \[\leadsto \color{blue}{\left(y4 \cdot k\right) \cdot \left(y1 \cdot y2 - b \cdot y\right)} \]

   if 2.1e-221 < t < 6.8000000000000002e-96

   1. Initial program 27.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y2 around inf 50.6%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   3. Taylor expanded in x around inf 47.0%

      \[\leadsto y2 \cdot \color{blue}{\left(x \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   if 6.8000000000000002e-96 < t < 1.65e45

   1. Initial program 32.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 52.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 52.7%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 52.7%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 52.7%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 52.7%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 52.7%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in x around inf 40.4%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   if 1.65e45 < t < 6.2000000000000004e151

   1. Initial program 30.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y2 around inf 35.6%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   3. Taylor expanded in y0 around inf 61.0%

      \[\leadsto y2 \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(k \cdot y5\right) + c \cdot x\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 61.0%

         \[\leadsto y2 \cdot \left(y0 \cdot \color{blue}{\left(c \cdot x + -1 \cdot \left(k \cdot y5\right)\right)}\right) \]

      2. mul-1-neg 61.0%

         \[\leadsto y2 \cdot \left(y0 \cdot \left(c \cdot x + \color{blue}{\left(-k \cdot y5\right)}\right)\right) \]

      3. unsub-neg 61.0%

         \[\leadsto y2 \cdot \left(y0 \cdot \color{blue}{\left(c \cdot x - k \cdot y5\right)}\right) \]

      4. *-commutative 61.0%

         \[\leadsto y2 \cdot \left(y0 \cdot \left(\color{blue}{x \cdot c} - k \cdot y5\right)\right) \]

      5. *-commutative 61.0%

         \[\leadsto y2 \cdot \left(y0 \cdot \left(x \cdot c - \color{blue}{y5 \cdot k}\right)\right) \]

   5. Simplified 61.0%

      \[\leadsto y2 \cdot \color{blue}{\left(y0 \cdot \left(x \cdot c - y5 \cdot k\right)\right)} \]

   if 6.2000000000000004e151 < t

   1. Initial program 25.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in c around inf 46.4%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in t around inf 54.0%

      \[\leadsto \color{blue}{c \cdot \left(t \cdot \left(i \cdot z - y2 \cdot y4\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 54.0%

         \[\leadsto c \cdot \left(t \cdot \left(i \cdot z - \color{blue}{y4 \cdot y2}\right)\right) \]

   5. Simplified 54.0%

      \[\leadsto \color{blue}{c \cdot \left(t \cdot \left(i \cdot z - y4 \cdot y2\right)\right)} \]
3. Recombined 8 regimes into one program.

4. Final simplification 50.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -6.6 \cdot 10^{+137}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq -1.85 \cdot 10^{-65}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq 3.8 \cdot 10^{-266}:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y0 \cdot y2 - y \cdot i\right)\\ \mathbf{elif}\;t \leq 2.1 \cdot 10^{-221}:\\ \;\;\;\;\left(k \cdot y4\right) \cdot \left(y1 \cdot y2 - y \cdot b\right)\\ \mathbf{elif}\;t \leq 6.8 \cdot 10^{-96}:\\ \;\;\;\;y2 \cdot \left(x \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq 1.65 \cdot 10^{+45}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 6.2 \cdot 10^{+151}:\\ \;\;\;\;y2 \cdot \left(y0 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(t \cdot \left(z \cdot i - y2 \cdot y4\right)\right)\\ \end{array} \]

Alternative 19: 21.2% accurate, 3.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot \left(b \cdot \left(t \cdot \left(-z\right)\right)\right)\\ t_2 := y2 \cdot \left(x \cdot \left(c \cdot y0\right)\right)\\ t_3 := c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{if}\;z \leq -7 \cdot 10^{+98}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq -1 \cdot 10^{-147}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;z \leq 2 \cdot 10^{-186}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{elif}\;z \leq 1.8 \cdot 10^{-101}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;z \leq 3.8 \cdot 10^{+121}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 8.2 \cdot 10^{+150}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;z \leq 2.35 \cdot 10^{+176}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(t \cdot \left(-i\right)\right)\right)\\ \mathbf{elif}\;z \leq 1.55 \cdot 10^{+189}:\\ \;\;\;\;t_3\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* a (* b (* t (- z)))))
        (t_2 (* y2 (* x (* c y0))))
        (t_3 (* c (* x (* y0 y2)))))
   (if (<= z -7e+98)
     t_1
     (if (<= z -1e-147)
       t_2
       (if (<= z 2e-186)
         (* a (* (* x y) b))
         (if (<= z 1.8e-101)
           t_3
           (if (<= z 3.8e+121)
             (* b (* j (* t y4)))
             (if (<= z 8.2e+150)
               t_2
               (if (<= z 2.35e+176)
                 (* j (* y5 (* t (- i))))
                 (if (<= z 1.55e+189) t_3 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 = a * (b * (t * -z));
	double t_2 = y2 * (x * (c * y0));
	double t_3 = c * (x * (y0 * y2));
	double tmp;
	if (z <= -7e+98) {
		tmp = t_1;
	} else if (z <= -1e-147) {
		tmp = t_2;
	} else if (z <= 2e-186) {
		tmp = a * ((x * y) * b);
	} else if (z <= 1.8e-101) {
		tmp = t_3;
	} else if (z <= 3.8e+121) {
		tmp = b * (j * (t * y4));
	} else if (z <= 8.2e+150) {
		tmp = t_2;
	} else if (z <= 2.35e+176) {
		tmp = j * (y5 * (t * -i));
	} else if (z <= 1.55e+189) {
		tmp = t_3;
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: tmp
    t_1 = a * (b * (t * -z))
    t_2 = y2 * (x * (c * y0))
    t_3 = c * (x * (y0 * y2))
    if (z <= (-7d+98)) then
        tmp = t_1
    else if (z <= (-1d-147)) then
        tmp = t_2
    else if (z <= 2d-186) then
        tmp = a * ((x * y) * b)
    else if (z <= 1.8d-101) then
        tmp = t_3
    else if (z <= 3.8d+121) then
        tmp = b * (j * (t * y4))
    else if (z <= 8.2d+150) then
        tmp = t_2
    else if (z <= 2.35d+176) then
        tmp = j * (y5 * (t * -i))
    else if (z <= 1.55d+189) then
        tmp = t_3
    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 = a * (b * (t * -z));
	double t_2 = y2 * (x * (c * y0));
	double t_3 = c * (x * (y0 * y2));
	double tmp;
	if (z <= -7e+98) {
		tmp = t_1;
	} else if (z <= -1e-147) {
		tmp = t_2;
	} else if (z <= 2e-186) {
		tmp = a * ((x * y) * b);
	} else if (z <= 1.8e-101) {
		tmp = t_3;
	} else if (z <= 3.8e+121) {
		tmp = b * (j * (t * y4));
	} else if (z <= 8.2e+150) {
		tmp = t_2;
	} else if (z <= 2.35e+176) {
		tmp = j * (y5 * (t * -i));
	} else if (z <= 1.55e+189) {
		tmp = t_3;
	} 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 = a * (b * (t * -z))
	t_2 = y2 * (x * (c * y0))
	t_3 = c * (x * (y0 * y2))
	tmp = 0
	if z <= -7e+98:
		tmp = t_1
	elif z <= -1e-147:
		tmp = t_2
	elif z <= 2e-186:
		tmp = a * ((x * y) * b)
	elif z <= 1.8e-101:
		tmp = t_3
	elif z <= 3.8e+121:
		tmp = b * (j * (t * y4))
	elif z <= 8.2e+150:
		tmp = t_2
	elif z <= 2.35e+176:
		tmp = j * (y5 * (t * -i))
	elif z <= 1.55e+189:
		tmp = t_3
	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(a * Float64(b * Float64(t * Float64(-z))))
	t_2 = Float64(y2 * Float64(x * Float64(c * y0)))
	t_3 = Float64(c * Float64(x * Float64(y0 * y2)))
	tmp = 0.0
	if (z <= -7e+98)
		tmp = t_1;
	elseif (z <= -1e-147)
		tmp = t_2;
	elseif (z <= 2e-186)
		tmp = Float64(a * Float64(Float64(x * y) * b));
	elseif (z <= 1.8e-101)
		tmp = t_3;
	elseif (z <= 3.8e+121)
		tmp = Float64(b * Float64(j * Float64(t * y4)));
	elseif (z <= 8.2e+150)
		tmp = t_2;
	elseif (z <= 2.35e+176)
		tmp = Float64(j * Float64(y5 * Float64(t * Float64(-i))));
	elseif (z <= 1.55e+189)
		tmp = t_3;
	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 = a * (b * (t * -z));
	t_2 = y2 * (x * (c * y0));
	t_3 = c * (x * (y0 * y2));
	tmp = 0.0;
	if (z <= -7e+98)
		tmp = t_1;
	elseif (z <= -1e-147)
		tmp = t_2;
	elseif (z <= 2e-186)
		tmp = a * ((x * y) * b);
	elseif (z <= 1.8e-101)
		tmp = t_3;
	elseif (z <= 3.8e+121)
		tmp = b * (j * (t * y4));
	elseif (z <= 8.2e+150)
		tmp = t_2;
	elseif (z <= 2.35e+176)
		tmp = j * (y5 * (t * -i));
	elseif (z <= 1.55e+189)
		tmp = t_3;
	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[(a * N[(b * N[(t * (-z)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(y2 * N[(x * N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(c * N[(x * N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -7e+98], t$95$1, If[LessEqual[z, -1e-147], t$95$2, If[LessEqual[z, 2e-186], N[(a * N[(N[(x * y), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.8e-101], t$95$3, If[LessEqual[z, 3.8e+121], N[(b * N[(j * N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 8.2e+150], t$95$2, If[LessEqual[z, 2.35e+176], N[(j * N[(y5 * N[(t * (-i)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.55e+189], t$95$3, t$95$1]]]]]]]]]]]

Derivation

1. Split input into 6 regimes

2. if z < -7e98 or 1.55e189 < z

   1. Initial program 28.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 35.4%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 43.6%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   4. Taylor expanded in x around 0 43.9%

      \[\leadsto a \cdot \left(b \cdot \color{blue}{\left(-1 \cdot \left(t \cdot z\right)\right)}\right) \]
   5. Step-by-step derivation

      1. neg-mul-1 43.9%

         \[\leadsto a \cdot \left(b \cdot \color{blue}{\left(-t \cdot z\right)}\right) \]

      2. distribute-lft-neg-in 43.9%

         \[\leadsto a \cdot \left(b \cdot \color{blue}{\left(\left(-t\right) \cdot z\right)}\right) \]

      3. *-commutative 43.9%

         \[\leadsto a \cdot \left(b \cdot \color{blue}{\left(z \cdot \left(-t\right)\right)}\right) \]

   6. Simplified 43.9%

      \[\leadsto a \cdot \left(b \cdot \color{blue}{\left(z \cdot \left(-t\right)\right)}\right) \]

   if -7e98 < z < -9.9999999999999997e-148 or 3.8e121 < z < 8.19999999999999988e150

   1. Initial program 28.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y2 around inf 52.8%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   3. Taylor expanded in x around inf 35.0%

      \[\leadsto y2 \cdot \color{blue}{\left(x \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   4. Taylor expanded in c around inf 30.6%

      \[\leadsto y2 \cdot \left(x \cdot \color{blue}{\left(c \cdot y0\right)}\right) \]
   5. Step-by-step derivation

      1. *-commutative 30.6%

         \[\leadsto y2 \cdot \left(x \cdot \color{blue}{\left(y0 \cdot c\right)}\right) \]

   6. Simplified 30.6%

      \[\leadsto y2 \cdot \left(x \cdot \color{blue}{\left(y0 \cdot c\right)}\right) \]

   if -9.9999999999999997e-148 < z < 1.9999999999999998e-186

   1. Initial program 41.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 50.8%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 30.8%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   4. Taylor expanded in x around inf 28.6%

      \[\leadsto a \cdot \color{blue}{\left(b \cdot \left(x \cdot y\right)\right)} \]

   if 1.9999999999999998e-186 < z < 1.8e-101 or 2.34999999999999991e176 < z < 1.55e189

   1. Initial program 23.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in c around inf 61.8%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in x around inf 50.6%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 43.0%

         \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)} \]

      2. +-commutative 43.0%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 + -1 \cdot \left(i \cdot y\right)\right)} \]

      3. mul-1-neg 43.0%

         \[\leadsto \left(c \cdot x\right) \cdot \left(y0 \cdot y2 + \color{blue}{\left(-i \cdot y\right)}\right) \]

      4. unsub-neg 43.0%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 - i \cdot y\right)} \]

   5. Simplified 43.0%

      \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(y0 \cdot y2 - i \cdot y\right)} \]

   6. Taylor expanded in y0 around inf 43.3%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 43.3%

         \[\leadsto c \cdot \left(x \cdot \color{blue}{\left(y2 \cdot y0\right)}\right) \]

   8. Simplified 43.3%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y2 \cdot y0\right)\right)} \]

   if 1.8e-101 < z < 3.8e121

   1. Initial program 25.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 50.5%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 50.5%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 50.5%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 50.5%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 50.5%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 50.5%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in t around inf 43.3%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   6. Taylor expanded in b around inf 36.0%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 36.0%

         \[\leadsto b \cdot \color{blue}{\left(\left(t \cdot y4\right) \cdot j\right)} \]

   8. Simplified 36.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(t \cdot y4\right) \cdot j\right)} \]

   if 8.19999999999999988e150 < z < 2.34999999999999991e176

   1. Initial program 11.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 66.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 66.8%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 66.8%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 66.8%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 66.8%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 66.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in t around inf 56.5%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   6. Taylor expanded in b around 0 46.0%

      \[\leadsto j \cdot \color{blue}{\left(-1 \cdot \left(i \cdot \left(t \cdot y5\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 46.0%

         \[\leadsto j \cdot \color{blue}{\left(-i \cdot \left(t \cdot y5\right)\right)} \]

      2. associate-*r* 56.6%

         \[\leadsto j \cdot \left(-\color{blue}{\left(i \cdot t\right) \cdot y5}\right) \]

      3. distribute-rgt-neg-in 56.6%

         \[\leadsto j \cdot \color{blue}{\left(\left(i \cdot t\right) \cdot \left(-y5\right)\right)} \]

   8. Simplified 56.6%

      \[\leadsto j \cdot \color{blue}{\left(\left(i \cdot t\right) \cdot \left(-y5\right)\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 36.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;z \leq -7 \cdot 10^{+98}:\\ \;\;\;\;a \cdot \left(b \cdot \left(t \cdot \left(-z\right)\right)\right)\\ \mathbf{elif}\;z \leq -1 \cdot 10^{-147}:\\ \;\;\;\;y2 \cdot \left(x \cdot \left(c \cdot y0\right)\right)\\ \mathbf{elif}\;z \leq 2 \cdot 10^{-186}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{elif}\;z \leq 1.8 \cdot 10^{-101}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{elif}\;z \leq 3.8 \cdot 10^{+121}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{elif}\;z \leq 8.2 \cdot 10^{+150}:\\ \;\;\;\;y2 \cdot \left(x \cdot \left(c \cdot y0\right)\right)\\ \mathbf{elif}\;z \leq 2.35 \cdot 10^{+176}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(t \cdot \left(-i\right)\right)\right)\\ \mathbf{elif}\;z \leq 1.55 \cdot 10^{+189}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(b \cdot \left(t \cdot \left(-z\right)\right)\right)\\ \end{array} \]

Alternative 20: 32.5% accurate, 4.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;t \leq -6.6 \cdot 10^{+139}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq -3.8 \cdot 10^{-61}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq 7.1 \cdot 10^{-240}:\\ \;\;\;\;c \cdot \left(y \cdot \left(y3 \cdot y4 - x \cdot i\right)\right)\\ \mathbf{elif}\;t \leq 1.45 \cdot 10^{-105}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 3.6 \cdot 10^{-90}:\\ \;\;\;\;y2 \cdot \left(x \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq 1.6 \cdot 10^{+152}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(t \cdot \left(z \cdot i - y2 \cdot y4\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= t -6.6e+139)
   (* j (* t (- (* b y4) (* i y5))))
   (if (<= t -3.8e-61)
     (* c (* y4 (- (* y y3) (* t y2))))
     (if (<= t 7.1e-240)
       (* c (* y (- (* y3 y4) (* x i))))
       (if (<= t 1.45e-105)
         (* b (* x (- (* y a) (* j y0))))
         (if (<= t 3.6e-90)
           (* y2 (* x (- (* c y0) (* a y1))))
           (if (<= t 1.6e+152)
             (* j (* y0 (- (* y3 y5) (* x b))))
             (* c (* t (- (* z i) (* 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 <= -6.6e+139) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (t <= -3.8e-61) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (t <= 7.1e-240) {
		tmp = c * (y * ((y3 * y4) - (x * i)));
	} else if (t <= 1.45e-105) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (t <= 3.6e-90) {
		tmp = y2 * (x * ((c * y0) - (a * y1)));
	} else if (t <= 1.6e+152) {
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	} else {
		tmp = c * (t * ((z * i) - (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 <= (-6.6d+139)) then
        tmp = j * (t * ((b * y4) - (i * y5)))
    else if (t <= (-3.8d-61)) then
        tmp = c * (y4 * ((y * y3) - (t * y2)))
    else if (t <= 7.1d-240) then
        tmp = c * (y * ((y3 * y4) - (x * i)))
    else if (t <= 1.45d-105) then
        tmp = b * (x * ((y * a) - (j * y0)))
    else if (t <= 3.6d-90) then
        tmp = y2 * (x * ((c * y0) - (a * y1)))
    else if (t <= 1.6d+152) then
        tmp = j * (y0 * ((y3 * y5) - (x * b)))
    else
        tmp = c * (t * ((z * i) - (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 <= -6.6e+139) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (t <= -3.8e-61) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (t <= 7.1e-240) {
		tmp = c * (y * ((y3 * y4) - (x * i)));
	} else if (t <= 1.45e-105) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (t <= 3.6e-90) {
		tmp = y2 * (x * ((c * y0) - (a * y1)));
	} else if (t <= 1.6e+152) {
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	} else {
		tmp = c * (t * ((z * i) - (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 <= -6.6e+139:
		tmp = j * (t * ((b * y4) - (i * y5)))
	elif t <= -3.8e-61:
		tmp = c * (y4 * ((y * y3) - (t * y2)))
	elif t <= 7.1e-240:
		tmp = c * (y * ((y3 * y4) - (x * i)))
	elif t <= 1.45e-105:
		tmp = b * (x * ((y * a) - (j * y0)))
	elif t <= 3.6e-90:
		tmp = y2 * (x * ((c * y0) - (a * y1)))
	elif t <= 1.6e+152:
		tmp = j * (y0 * ((y3 * y5) - (x * b)))
	else:
		tmp = c * (t * ((z * i) - (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 <= -6.6e+139)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))));
	elseif (t <= -3.8e-61)
		tmp = Float64(c * Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2))));
	elseif (t <= 7.1e-240)
		tmp = Float64(c * Float64(y * Float64(Float64(y3 * y4) - Float64(x * i))));
	elseif (t <= 1.45e-105)
		tmp = Float64(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))));
	elseif (t <= 3.6e-90)
		tmp = Float64(y2 * Float64(x * Float64(Float64(c * y0) - Float64(a * y1))));
	elseif (t <= 1.6e+152)
		tmp = Float64(j * Float64(y0 * Float64(Float64(y3 * y5) - Float64(x * b))));
	else
		tmp = Float64(c * Float64(t * Float64(Float64(z * i) - Float64(y2 * 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 <= -6.6e+139)
		tmp = j * (t * ((b * y4) - (i * y5)));
	elseif (t <= -3.8e-61)
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	elseif (t <= 7.1e-240)
		tmp = c * (y * ((y3 * y4) - (x * i)));
	elseif (t <= 1.45e-105)
		tmp = b * (x * ((y * a) - (j * y0)));
	elseif (t <= 3.6e-90)
		tmp = y2 * (x * ((c * y0) - (a * y1)));
	elseif (t <= 1.6e+152)
		tmp = j * (y0 * ((y3 * y5) - (x * b)));
	else
		tmp = c * (t * ((z * i) - (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, -6.6e+139], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -3.8e-61], N[(c * N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 7.1e-240], N[(c * N[(y * N[(N[(y3 * y4), $MachinePrecision] - N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.45e-105], N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 3.6e-90], N[(y2 * N[(x * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.6e+152], N[(j * N[(y0 * N[(N[(y3 * y5), $MachinePrecision] - N[(x * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(c * N[(t * N[(N[(z * i), $MachinePrecision] - N[(y2 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]

Derivation

1. Split input into 7 regimes

2. if t < -6.6000000000000003e139

   1. Initial program 18.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 39.9%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 39.9%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 39.9%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 39.9%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 39.9%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 39.9%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in t around inf 50.4%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   if -6.6000000000000003e139 < t < -3.7999999999999998e-61

   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. Taylor expanded in y4 around inf 46.0%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in c around inf 51.1%

      \[\leadsto \color{blue}{c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 51.1%

         \[\leadsto c \cdot \left(y4 \cdot \left(\color{blue}{y3 \cdot y} - t \cdot y2\right)\right) \]

   5. Simplified 51.1%

      \[\leadsto \color{blue}{c \cdot \left(y4 \cdot \left(y3 \cdot y - t \cdot y2\right)\right)} \]

   if -3.7999999999999998e-61 < t < 7.09999999999999952e-240

   1. Initial program 40.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in c around inf 47.5%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in y around inf 42.6%

      \[\leadsto c \cdot \color{blue}{\left(y \cdot \left(-1 \cdot \left(i \cdot x\right) - -1 \cdot \left(y3 \cdot y4\right)\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 42.6%

         \[\leadsto c \cdot \color{blue}{\left(\left(-1 \cdot \left(i \cdot x\right) - -1 \cdot \left(y3 \cdot y4\right)\right) \cdot y\right)} \]

      2. cancel-sign-sub-inv 42.6%

         \[\leadsto c \cdot \left(\color{blue}{\left(-1 \cdot \left(i \cdot x\right) + \left(--1\right) \cdot \left(y3 \cdot y4\right)\right)} \cdot y\right) \]

      3. metadata-eval 42.6%

         \[\leadsto c \cdot \left(\left(-1 \cdot \left(i \cdot x\right) + \color{blue}{1} \cdot \left(y3 \cdot y4\right)\right) \cdot y\right) \]

      4. *-lft-identity 42.6%

         \[\leadsto c \cdot \left(\left(-1 \cdot \left(i \cdot x\right) + \color{blue}{y3 \cdot y4}\right) \cdot y\right) \]

      5. +-commutative 42.6%

         \[\leadsto c \cdot \left(\color{blue}{\left(y3 \cdot y4 + -1 \cdot \left(i \cdot x\right)\right)} \cdot y\right) \]

      6. mul-1-neg 42.6%

         \[\leadsto c \cdot \left(\left(y3 \cdot y4 + \color{blue}{\left(-i \cdot x\right)}\right) \cdot y\right) \]

      7. unsub-neg 42.6%

         \[\leadsto c \cdot \left(\color{blue}{\left(y3 \cdot y4 - i \cdot x\right)} \cdot y\right) \]

      8. *-commutative 42.6%

         \[\leadsto c \cdot \left(\left(\color{blue}{y4 \cdot y3} - i \cdot x\right) \cdot y\right) \]

   5. Simplified 42.6%

      \[\leadsto c \cdot \color{blue}{\left(\left(y4 \cdot y3 - i \cdot x\right) \cdot y\right)} \]

   if 7.09999999999999952e-240 < t < 1.45000000000000002e-105

   1. Initial program 26.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 42.5%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in x around inf 40.4%

      \[\leadsto \color{blue}{b \cdot \left(x \cdot \left(a \cdot y - j \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 40.4%

         \[\leadsto b \cdot \left(x \cdot \left(\color{blue}{y \cdot a} - j \cdot y0\right)\right) \]

   5. Simplified 40.4%

      \[\leadsto \color{blue}{b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)} \]

   if 1.45000000000000002e-105 < t < 3.59999999999999981e-90

   1. Initial program 37.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y2 around inf 62.6%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   3. Taylor expanded in x around inf 73.4%

      \[\leadsto y2 \cdot \color{blue}{\left(x \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   if 3.59999999999999981e-90 < t < 1.60000000000000003e152

   1. Initial program 32.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 44.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 44.8%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 44.8%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 44.8%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 44.8%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 44.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in y0 around -inf 37.7%

      \[\leadsto j \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(b \cdot x\right) + y3 \cdot y5\right)\right)} \]
   6. Step-by-step derivation

      1. +-commutative 37.7%

         \[\leadsto j \cdot \left(y0 \cdot \color{blue}{\left(y3 \cdot y5 + -1 \cdot \left(b \cdot x\right)\right)}\right) \]

      2. mul-1-neg 37.7%

         \[\leadsto j \cdot \left(y0 \cdot \left(y3 \cdot y5 + \color{blue}{\left(-b \cdot x\right)}\right)\right) \]

      3. unsub-neg 37.7%

         \[\leadsto j \cdot \left(y0 \cdot \color{blue}{\left(y3 \cdot y5 - b \cdot x\right)}\right) \]

      4. *-commutative 37.7%

         \[\leadsto j \cdot \left(y0 \cdot \left(\color{blue}{y5 \cdot y3} - b \cdot x\right)\right) \]

   7. Simplified 37.7%

      \[\leadsto j \cdot \color{blue}{\left(y0 \cdot \left(y5 \cdot y3 - b \cdot x\right)\right)} \]

   if 1.60000000000000003e152 < t

   1. Initial program 22.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in c around inf 48.1%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in t around inf 56.0%

      \[\leadsto \color{blue}{c \cdot \left(t \cdot \left(i \cdot z - y2 \cdot y4\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 56.0%

         \[\leadsto c \cdot \left(t \cdot \left(i \cdot z - \color{blue}{y4 \cdot y2}\right)\right) \]

   5. Simplified 56.0%

      \[\leadsto \color{blue}{c \cdot \left(t \cdot \left(i \cdot z - y4 \cdot y2\right)\right)} \]
3. Recombined 7 regimes into one program.

4. Final simplification 46.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -6.6 \cdot 10^{+139}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq -3.8 \cdot 10^{-61}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq 7.1 \cdot 10^{-240}:\\ \;\;\;\;c \cdot \left(y \cdot \left(y3 \cdot y4 - x \cdot i\right)\right)\\ \mathbf{elif}\;t \leq 1.45 \cdot 10^{-105}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 3.6 \cdot 10^{-90}:\\ \;\;\;\;y2 \cdot \left(x \cdot \left(c \cdot y0 - a \cdot y1\right)\right)\\ \mathbf{elif}\;t \leq 1.6 \cdot 10^{+152}:\\ \;\;\;\;j \cdot \left(y0 \cdot \left(y3 \cdot y5 - x \cdot b\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(t \cdot \left(z \cdot i - y2 \cdot y4\right)\right)\\ \end{array} \]

Alternative 21: 19.5% accurate, 4.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ t_2 := a \cdot \left(b \cdot \left(t \cdot \left(-z\right)\right)\right)\\ \mathbf{if}\;y2 \leq -2.8 \cdot 10^{+122}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y2 \leq -5.8 \cdot 10^{-181}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y2 \leq -2.1 \cdot 10^{-286}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y2 \leq 4 \cdot 10^{-262}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;y2 \leq 1.4 \cdot 10^{-57}:\\ \;\;\;\;y2 \cdot \left(x \cdot \left(c \cdot y0\right)\right)\\ \mathbf{elif}\;y2 \leq 4.1 \cdot 10^{-14}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y2 \leq 3.4 \cdot 10^{+28}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(b \cdot \left(t \cdot y4\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* j (* t y4)))) (t_2 (* a (* b (* t (- z))))))
   (if (<= y2 -2.8e+122)
     (* c (* x (* y0 y2)))
     (if (<= y2 -5.8e-181)
       t_2
       (if (<= y2 -2.1e-286)
         t_1
         (if (<= y2 4e-262)
           t_2
           (if (<= y2 1.4e-57)
             (* y2 (* x (* c y0)))
             (if (<= y2 4.1e-14)
               t_1
               (if (<= y2 3.4e+28)
                 (* a (* (* x y) b))
                 (* j (* b (* t 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 = b * (j * (t * y4));
	double t_2 = a * (b * (t * -z));
	double tmp;
	if (y2 <= -2.8e+122) {
		tmp = c * (x * (y0 * y2));
	} else if (y2 <= -5.8e-181) {
		tmp = t_2;
	} else if (y2 <= -2.1e-286) {
		tmp = t_1;
	} else if (y2 <= 4e-262) {
		tmp = t_2;
	} else if (y2 <= 1.4e-57) {
		tmp = y2 * (x * (c * y0));
	} else if (y2 <= 4.1e-14) {
		tmp = t_1;
	} else if (y2 <= 3.4e+28) {
		tmp = a * ((x * y) * b);
	} else {
		tmp = j * (b * (t * 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) :: tmp
    t_1 = b * (j * (t * y4))
    t_2 = a * (b * (t * -z))
    if (y2 <= (-2.8d+122)) then
        tmp = c * (x * (y0 * y2))
    else if (y2 <= (-5.8d-181)) then
        tmp = t_2
    else if (y2 <= (-2.1d-286)) then
        tmp = t_1
    else if (y2 <= 4d-262) then
        tmp = t_2
    else if (y2 <= 1.4d-57) then
        tmp = y2 * (x * (c * y0))
    else if (y2 <= 4.1d-14) then
        tmp = t_1
    else if (y2 <= 3.4d+28) then
        tmp = a * ((x * y) * b)
    else
        tmp = j * (b * (t * 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 = b * (j * (t * y4));
	double t_2 = a * (b * (t * -z));
	double tmp;
	if (y2 <= -2.8e+122) {
		tmp = c * (x * (y0 * y2));
	} else if (y2 <= -5.8e-181) {
		tmp = t_2;
	} else if (y2 <= -2.1e-286) {
		tmp = t_1;
	} else if (y2 <= 4e-262) {
		tmp = t_2;
	} else if (y2 <= 1.4e-57) {
		tmp = y2 * (x * (c * y0));
	} else if (y2 <= 4.1e-14) {
		tmp = t_1;
	} else if (y2 <= 3.4e+28) {
		tmp = a * ((x * y) * b);
	} else {
		tmp = j * (b * (t * y4));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = b * (j * (t * y4))
	t_2 = a * (b * (t * -z))
	tmp = 0
	if y2 <= -2.8e+122:
		tmp = c * (x * (y0 * y2))
	elif y2 <= -5.8e-181:
		tmp = t_2
	elif y2 <= -2.1e-286:
		tmp = t_1
	elif y2 <= 4e-262:
		tmp = t_2
	elif y2 <= 1.4e-57:
		tmp = y2 * (x * (c * y0))
	elif y2 <= 4.1e-14:
		tmp = t_1
	elif y2 <= 3.4e+28:
		tmp = a * ((x * y) * b)
	else:
		tmp = j * (b * (t * 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(b * Float64(j * Float64(t * y4)))
	t_2 = Float64(a * Float64(b * Float64(t * Float64(-z))))
	tmp = 0.0
	if (y2 <= -2.8e+122)
		tmp = Float64(c * Float64(x * Float64(y0 * y2)));
	elseif (y2 <= -5.8e-181)
		tmp = t_2;
	elseif (y2 <= -2.1e-286)
		tmp = t_1;
	elseif (y2 <= 4e-262)
		tmp = t_2;
	elseif (y2 <= 1.4e-57)
		tmp = Float64(y2 * Float64(x * Float64(c * y0)));
	elseif (y2 <= 4.1e-14)
		tmp = t_1;
	elseif (y2 <= 3.4e+28)
		tmp = Float64(a * Float64(Float64(x * y) * b));
	else
		tmp = Float64(j * Float64(b * Float64(t * 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 = b * (j * (t * y4));
	t_2 = a * (b * (t * -z));
	tmp = 0.0;
	if (y2 <= -2.8e+122)
		tmp = c * (x * (y0 * y2));
	elseif (y2 <= -5.8e-181)
		tmp = t_2;
	elseif (y2 <= -2.1e-286)
		tmp = t_1;
	elseif (y2 <= 4e-262)
		tmp = t_2;
	elseif (y2 <= 1.4e-57)
		tmp = y2 * (x * (c * y0));
	elseif (y2 <= 4.1e-14)
		tmp = t_1;
	elseif (y2 <= 3.4e+28)
		tmp = a * ((x * y) * b);
	else
		tmp = j * (b * (t * 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[(b * N[(j * N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(a * N[(b * N[(t * (-z)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y2, -2.8e+122], N[(c * N[(x * N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, -5.8e-181], t$95$2, If[LessEqual[y2, -2.1e-286], t$95$1, If[LessEqual[y2, 4e-262], t$95$2, If[LessEqual[y2, 1.4e-57], N[(y2 * N[(x * N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 4.1e-14], t$95$1, If[LessEqual[y2, 3.4e+28], N[(a * N[(N[(x * y), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision], N[(j * N[(b * N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]

Derivation

1. Split input into 6 regimes

2. if y2 < -2.8e122

   1. Initial program 20.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in c around inf 50.0%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in x around inf 50.7%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 40.8%

         \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)} \]

      2. +-commutative 40.8%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 + -1 \cdot \left(i \cdot y\right)\right)} \]

      3. mul-1-neg 40.8%

         \[\leadsto \left(c \cdot x\right) \cdot \left(y0 \cdot y2 + \color{blue}{\left(-i \cdot y\right)}\right) \]

      4. unsub-neg 40.8%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 - i \cdot y\right)} \]

   5. Simplified 40.8%

      \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(y0 \cdot y2 - i \cdot y\right)} \]

   6. Taylor expanded in y0 around inf 53.1%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 53.1%

         \[\leadsto c \cdot \left(x \cdot \color{blue}{\left(y2 \cdot y0\right)}\right) \]

   8. Simplified 53.1%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y2 \cdot y0\right)\right)} \]

   if -2.8e122 < y2 < -5.7999999999999996e-181 or -2.09999999999999988e-286 < y2 < 4.00000000000000005e-262

   1. Initial program 26.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 32.8%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 33.6%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   4. Taylor expanded in x around 0 28.5%

      \[\leadsto a \cdot \left(b \cdot \color{blue}{\left(-1 \cdot \left(t \cdot z\right)\right)}\right) \]
   5. Step-by-step derivation

      1. neg-mul-1 28.5%

         \[\leadsto a \cdot \left(b \cdot \color{blue}{\left(-t \cdot z\right)}\right) \]

      2. distribute-lft-neg-in 28.5%

         \[\leadsto a \cdot \left(b \cdot \color{blue}{\left(\left(-t\right) \cdot z\right)}\right) \]

      3. *-commutative 28.5%

         \[\leadsto a \cdot \left(b \cdot \color{blue}{\left(z \cdot \left(-t\right)\right)}\right) \]

   6. Simplified 28.5%

      \[\leadsto a \cdot \left(b \cdot \color{blue}{\left(z \cdot \left(-t\right)\right)}\right) \]

   if -5.7999999999999996e-181 < y2 < -2.09999999999999988e-286 or 1.4e-57 < y2 < 4.1000000000000002e-14

   1. Initial program 47.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 45.1%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 45.1%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 45.1%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 45.1%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 45.1%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 45.1%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in t around inf 36.9%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   6. Taylor expanded in b around inf 36.8%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 36.8%

         \[\leadsto b \cdot \color{blue}{\left(\left(t \cdot y4\right) \cdot j\right)} \]

   8. Simplified 36.8%

      \[\leadsto \color{blue}{b \cdot \left(\left(t \cdot y4\right) \cdot j\right)} \]

   if 4.00000000000000005e-262 < y2 < 1.4e-57

   1. Initial program 36.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y2 around inf 45.2%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   3. Taylor expanded in x around inf 48.1%

      \[\leadsto y2 \cdot \color{blue}{\left(x \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   4. Taylor expanded in c around inf 30.1%

      \[\leadsto y2 \cdot \left(x \cdot \color{blue}{\left(c \cdot y0\right)}\right) \]
   5. Step-by-step derivation

      1. *-commutative 30.1%

         \[\leadsto y2 \cdot \left(x \cdot \color{blue}{\left(y0 \cdot c\right)}\right) \]

   6. Simplified 30.1%

      \[\leadsto y2 \cdot \left(x \cdot \color{blue}{\left(y0 \cdot c\right)}\right) \]

   if 4.1000000000000002e-14 < y2 < 3.4e28

   1. Initial program 21.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 35.9%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 43.4%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   4. Taylor expanded in x around inf 43.5%

      \[\leadsto a \cdot \color{blue}{\left(b \cdot \left(x \cdot y\right)\right)} \]

   if 3.4e28 < y2

   1. Initial program 25.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 40.1%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 40.1%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 40.1%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 40.1%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 40.1%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 40.1%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in t around inf 26.8%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   6. Taylor expanded in b around inf 28.0%

      \[\leadsto j \cdot \color{blue}{\left(b \cdot \left(t \cdot y4\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 28.0%

         \[\leadsto j \cdot \color{blue}{\left(\left(t \cdot y4\right) \cdot b\right)} \]

   8. Simplified 28.0%

      \[\leadsto j \cdot \color{blue}{\left(\left(t \cdot y4\right) \cdot b\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 34.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y2 \leq -2.8 \cdot 10^{+122}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y2 \leq -5.8 \cdot 10^{-181}:\\ \;\;\;\;a \cdot \left(b \cdot \left(t \cdot \left(-z\right)\right)\right)\\ \mathbf{elif}\;y2 \leq -2.1 \cdot 10^{-286}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{elif}\;y2 \leq 4 \cdot 10^{-262}:\\ \;\;\;\;a \cdot \left(b \cdot \left(t \cdot \left(-z\right)\right)\right)\\ \mathbf{elif}\;y2 \leq 1.4 \cdot 10^{-57}:\\ \;\;\;\;y2 \cdot \left(x \cdot \left(c \cdot y0\right)\right)\\ \mathbf{elif}\;y2 \leq 4.1 \cdot 10^{-14}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{elif}\;y2 \leq 3.4 \cdot 10^{+28}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(b \cdot \left(t \cdot y4\right)\right)\\ \end{array} \]

Alternative 22: 31.4% accurate, 4.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;t \leq -4.6 \cdot 10^{+138}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq -4.2 \cdot 10^{-61}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq 4.7 \cdot 10^{-240}:\\ \;\;\;\;c \cdot \left(y \cdot \left(y3 \cdot y4 - x \cdot i\right)\right)\\ \mathbf{elif}\;t \leq 7.6 \cdot 10^{-181}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 1.8 \cdot 10^{+45}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= t -4.6e+138)
   (* j (* t (- (* b y4) (* i y5))))
   (if (<= t -4.2e-61)
     (* c (* y4 (- (* y y3) (* t y2))))
     (if (<= t 4.7e-240)
       (* c (* y (- (* y3 y4) (* x i))))
       (if (<= t 7.6e-181)
         (* b (* x (- (* y a) (* j y0))))
         (if (<= t 1.8e+45)
           (* j (* x (- (* i y1) (* b y0))))
           (* c (* z (- (* t i) (* y0 y3))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (t <= -4.6e+138) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (t <= -4.2e-61) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (t <= 4.7e-240) {
		tmp = c * (y * ((y3 * y4) - (x * i)));
	} else if (t <= 7.6e-181) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (t <= 1.8e+45) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else {
		tmp = c * (z * ((t * i) - (y0 * y3)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (t <= (-4.6d+138)) then
        tmp = j * (t * ((b * y4) - (i * y5)))
    else if (t <= (-4.2d-61)) then
        tmp = c * (y4 * ((y * y3) - (t * y2)))
    else if (t <= 4.7d-240) then
        tmp = c * (y * ((y3 * y4) - (x * i)))
    else if (t <= 7.6d-181) then
        tmp = b * (x * ((y * a) - (j * y0)))
    else if (t <= 1.8d+45) then
        tmp = j * (x * ((i * y1) - (b * y0)))
    else
        tmp = c * (z * ((t * i) - (y0 * y3)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (t <= -4.6e+138) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (t <= -4.2e-61) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (t <= 4.7e-240) {
		tmp = c * (y * ((y3 * y4) - (x * i)));
	} else if (t <= 7.6e-181) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (t <= 1.8e+45) {
		tmp = j * (x * ((i * y1) - (b * y0)));
	} else {
		tmp = c * (z * ((t * i) - (y0 * y3)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if t <= -4.6e+138:
		tmp = j * (t * ((b * y4) - (i * y5)))
	elif t <= -4.2e-61:
		tmp = c * (y4 * ((y * y3) - (t * y2)))
	elif t <= 4.7e-240:
		tmp = c * (y * ((y3 * y4) - (x * i)))
	elif t <= 7.6e-181:
		tmp = b * (x * ((y * a) - (j * y0)))
	elif t <= 1.8e+45:
		tmp = j * (x * ((i * y1) - (b * y0)))
	else:
		tmp = c * (z * ((t * i) - (y0 * y3)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (t <= -4.6e+138)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))));
	elseif (t <= -4.2e-61)
		tmp = Float64(c * Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2))));
	elseif (t <= 4.7e-240)
		tmp = Float64(c * Float64(y * Float64(Float64(y3 * y4) - Float64(x * i))));
	elseif (t <= 7.6e-181)
		tmp = Float64(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))));
	elseif (t <= 1.8e+45)
		tmp = Float64(j * Float64(x * Float64(Float64(i * y1) - Float64(b * y0))));
	else
		tmp = Float64(c * Float64(z * Float64(Float64(t * i) - Float64(y0 * y3))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (t <= -4.6e+138)
		tmp = j * (t * ((b * y4) - (i * y5)));
	elseif (t <= -4.2e-61)
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	elseif (t <= 4.7e-240)
		tmp = c * (y * ((y3 * y4) - (x * i)));
	elseif (t <= 7.6e-181)
		tmp = b * (x * ((y * a) - (j * y0)));
	elseif (t <= 1.8e+45)
		tmp = j * (x * ((i * y1) - (b * y0)));
	else
		tmp = c * (z * ((t * i) - (y0 * y3)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[t, -4.6e+138], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -4.2e-61], N[(c * N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 4.7e-240], N[(c * N[(y * N[(N[(y3 * y4), $MachinePrecision] - N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 7.6e-181], N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.8e+45], N[(j * N[(x * N[(N[(i * y1), $MachinePrecision] - N[(b * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(c * N[(z * N[(N[(t * i), $MachinePrecision] - N[(y0 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

1. Split input into 6 regimes

2. if t < -4.60000000000000015e138

   1. Initial program 18.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 39.9%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 39.9%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 39.9%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 39.9%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 39.9%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 39.9%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in t around inf 50.4%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   if -4.60000000000000015e138 < t < -4.1999999999999998e-61

   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. Taylor expanded in y4 around inf 46.0%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in c around inf 51.1%

      \[\leadsto \color{blue}{c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 51.1%

         \[\leadsto c \cdot \left(y4 \cdot \left(\color{blue}{y3 \cdot y} - t \cdot y2\right)\right) \]

   5. Simplified 51.1%

      \[\leadsto \color{blue}{c \cdot \left(y4 \cdot \left(y3 \cdot y - t \cdot y2\right)\right)} \]

   if -4.1999999999999998e-61 < t < 4.70000000000000012e-240

   1. Initial program 40.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in c around inf 47.5%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in y around inf 42.6%

      \[\leadsto c \cdot \color{blue}{\left(y \cdot \left(-1 \cdot \left(i \cdot x\right) - -1 \cdot \left(y3 \cdot y4\right)\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 42.6%

         \[\leadsto c \cdot \color{blue}{\left(\left(-1 \cdot \left(i \cdot x\right) - -1 \cdot \left(y3 \cdot y4\right)\right) \cdot y\right)} \]

      2. cancel-sign-sub-inv 42.6%

         \[\leadsto c \cdot \left(\color{blue}{\left(-1 \cdot \left(i \cdot x\right) + \left(--1\right) \cdot \left(y3 \cdot y4\right)\right)} \cdot y\right) \]

      3. metadata-eval 42.6%

         \[\leadsto c \cdot \left(\left(-1 \cdot \left(i \cdot x\right) + \color{blue}{1} \cdot \left(y3 \cdot y4\right)\right) \cdot y\right) \]

      4. *-lft-identity 42.6%

         \[\leadsto c \cdot \left(\left(-1 \cdot \left(i \cdot x\right) + \color{blue}{y3 \cdot y4}\right) \cdot y\right) \]

      5. +-commutative 42.6%

         \[\leadsto c \cdot \left(\color{blue}{\left(y3 \cdot y4 + -1 \cdot \left(i \cdot x\right)\right)} \cdot y\right) \]

      6. mul-1-neg 42.6%

         \[\leadsto c \cdot \left(\left(y3 \cdot y4 + \color{blue}{\left(-i \cdot x\right)}\right) \cdot y\right) \]

      7. unsub-neg 42.6%

         \[\leadsto c \cdot \left(\color{blue}{\left(y3 \cdot y4 - i \cdot x\right)} \cdot y\right) \]

      8. *-commutative 42.6%

         \[\leadsto c \cdot \left(\left(\color{blue}{y4 \cdot y3} - i \cdot x\right) \cdot y\right) \]

   5. Simplified 42.6%

      \[\leadsto c \cdot \color{blue}{\left(\left(y4 \cdot y3 - i \cdot x\right) \cdot y\right)} \]

   if 4.70000000000000012e-240 < t < 7.5999999999999996e-181

   1. Initial program 18.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 30.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in x around inf 47.8%

      \[\leadsto \color{blue}{b \cdot \left(x \cdot \left(a \cdot y - j \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 47.8%

         \[\leadsto b \cdot \left(x \cdot \left(\color{blue}{y \cdot a} - j \cdot y0\right)\right) \]

   5. Simplified 47.8%

      \[\leadsto \color{blue}{b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)} \]

   if 7.5999999999999996e-181 < t < 1.8e45

   1. Initial program 33.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 42.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 42.4%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 42.4%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 42.4%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 42.4%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 42.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in x around inf 36.8%

      \[\leadsto \color{blue}{j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)} \]

   if 1.8e45 < t

   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. Taylor expanded in c around inf 35.4%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in z around inf 44.5%

      \[\leadsto c \cdot \color{blue}{\left(z \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 44.5%

         \[\leadsto c \cdot \color{blue}{\left(\left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right) \cdot z\right)} \]

      2. +-commutative 44.5%

         \[\leadsto c \cdot \left(\color{blue}{\left(i \cdot t + -1 \cdot \left(y0 \cdot y3\right)\right)} \cdot z\right) \]

      3. mul-1-neg 44.5%

         \[\leadsto c \cdot \left(\left(i \cdot t + \color{blue}{\left(-y0 \cdot y3\right)}\right) \cdot z\right) \]

      4. sub-neg 44.5%

         \[\leadsto c \cdot \left(\color{blue}{\left(i \cdot t - y0 \cdot y3\right)} \cdot z\right) \]

      5. *-commutative 44.5%

         \[\leadsto c \cdot \left(\left(\color{blue}{t \cdot i} - y0 \cdot y3\right) \cdot z\right) \]

   5. Simplified 44.5%

      \[\leadsto c \cdot \color{blue}{\left(\left(t \cdot i - y0 \cdot y3\right) \cdot z\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 44.7%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -4.6 \cdot 10^{+138}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq -4.2 \cdot 10^{-61}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq 4.7 \cdot 10^{-240}:\\ \;\;\;\;c \cdot \left(y \cdot \left(y3 \cdot y4 - x \cdot i\right)\right)\\ \mathbf{elif}\;t \leq 7.6 \cdot 10^{-181}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 1.8 \cdot 10^{+45}:\\ \;\;\;\;j \cdot \left(x \cdot \left(i \cdot y1 - b \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)\\ \end{array} \]

Alternative 23: 31.3% accurate, 4.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;t \leq -1.05 \cdot 10^{+144}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq -3 \cdot 10^{-63}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq 3.8 \cdot 10^{-266}:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y0 \cdot y2 - y \cdot i\right)\\ \mathbf{elif}\;t \leq 1.5 \cdot 10^{+45}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 2.3 \cdot 10^{+151}:\\ \;\;\;\;y2 \cdot \left(y0 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(t \cdot \left(z \cdot i - y2 \cdot y4\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= t -1.05e+144)
   (* j (* t (- (* b y4) (* i y5))))
   (if (<= t -3e-63)
     (* c (* y4 (- (* y y3) (* t y2))))
     (if (<= t 3.8e-266)
       (* (* x c) (- (* y0 y2) (* y i)))
       (if (<= t 1.5e+45)
         (* b (* x (- (* y a) (* j y0))))
         (if (<= t 2.3e+151)
           (* y2 (* y0 (- (* x c) (* k y5))))
           (* c (* t (- (* z i) (* 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 <= -1.05e+144) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (t <= -3e-63) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (t <= 3.8e-266) {
		tmp = (x * c) * ((y0 * y2) - (y * i));
	} else if (t <= 1.5e+45) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (t <= 2.3e+151) {
		tmp = y2 * (y0 * ((x * c) - (k * y5)));
	} else {
		tmp = c * (t * ((z * i) - (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 <= (-1.05d+144)) then
        tmp = j * (t * ((b * y4) - (i * y5)))
    else if (t <= (-3d-63)) then
        tmp = c * (y4 * ((y * y3) - (t * y2)))
    else if (t <= 3.8d-266) then
        tmp = (x * c) * ((y0 * y2) - (y * i))
    else if (t <= 1.5d+45) then
        tmp = b * (x * ((y * a) - (j * y0)))
    else if (t <= 2.3d+151) then
        tmp = y2 * (y0 * ((x * c) - (k * y5)))
    else
        tmp = c * (t * ((z * i) - (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 <= -1.05e+144) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (t <= -3e-63) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (t <= 3.8e-266) {
		tmp = (x * c) * ((y0 * y2) - (y * i));
	} else if (t <= 1.5e+45) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (t <= 2.3e+151) {
		tmp = y2 * (y0 * ((x * c) - (k * y5)));
	} else {
		tmp = c * (t * ((z * i) - (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 <= -1.05e+144:
		tmp = j * (t * ((b * y4) - (i * y5)))
	elif t <= -3e-63:
		tmp = c * (y4 * ((y * y3) - (t * y2)))
	elif t <= 3.8e-266:
		tmp = (x * c) * ((y0 * y2) - (y * i))
	elif t <= 1.5e+45:
		tmp = b * (x * ((y * a) - (j * y0)))
	elif t <= 2.3e+151:
		tmp = y2 * (y0 * ((x * c) - (k * y5)))
	else:
		tmp = c * (t * ((z * i) - (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 <= -1.05e+144)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))));
	elseif (t <= -3e-63)
		tmp = Float64(c * Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2))));
	elseif (t <= 3.8e-266)
		tmp = Float64(Float64(x * c) * Float64(Float64(y0 * y2) - Float64(y * i)));
	elseif (t <= 1.5e+45)
		tmp = Float64(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))));
	elseif (t <= 2.3e+151)
		tmp = Float64(y2 * Float64(y0 * Float64(Float64(x * c) - Float64(k * y5))));
	else
		tmp = Float64(c * Float64(t * Float64(Float64(z * i) - Float64(y2 * 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 <= -1.05e+144)
		tmp = j * (t * ((b * y4) - (i * y5)));
	elseif (t <= -3e-63)
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	elseif (t <= 3.8e-266)
		tmp = (x * c) * ((y0 * y2) - (y * i));
	elseif (t <= 1.5e+45)
		tmp = b * (x * ((y * a) - (j * y0)));
	elseif (t <= 2.3e+151)
		tmp = y2 * (y0 * ((x * c) - (k * y5)));
	else
		tmp = c * (t * ((z * i) - (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, -1.05e+144], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -3e-63], N[(c * N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 3.8e-266], N[(N[(x * c), $MachinePrecision] * N[(N[(y0 * y2), $MachinePrecision] - N[(y * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 1.5e+45], N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 2.3e+151], N[(y2 * N[(y0 * N[(N[(x * c), $MachinePrecision] - N[(k * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(c * N[(t * N[(N[(z * i), $MachinePrecision] - N[(y2 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

1. Split input into 6 regimes

2. if t < -1.04999999999999998e144

   1. Initial program 18.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 39.9%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 39.9%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 39.9%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 39.9%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 39.9%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 39.9%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in t around inf 50.4%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   if -1.04999999999999998e144 < t < -2.99999999999999979e-63

   1. Initial program 23.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf 47.3%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in c around inf 52.3%

      \[\leadsto \color{blue}{c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 52.3%

         \[\leadsto c \cdot \left(y4 \cdot \left(\color{blue}{y3 \cdot y} - t \cdot y2\right)\right) \]

   5. Simplified 52.3%

      \[\leadsto \color{blue}{c \cdot \left(y4 \cdot \left(y3 \cdot y - t \cdot y2\right)\right)} \]

   if -2.99999999999999979e-63 < t < 3.79999999999999994e-266

   1. Initial program 40.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in c around inf 50.8%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in x around inf 49.3%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 49.3%

         \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)} \]

      2. +-commutative 49.3%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 + -1 \cdot \left(i \cdot y\right)\right)} \]

      3. mul-1-neg 49.3%

         \[\leadsto \left(c \cdot x\right) \cdot \left(y0 \cdot y2 + \color{blue}{\left(-i \cdot y\right)}\right) \]

      4. unsub-neg 49.3%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 - i \cdot y\right)} \]

   5. Simplified 49.3%

      \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(y0 \cdot y2 - i \cdot y\right)} \]

   if 3.79999999999999994e-266 < t < 1.50000000000000005e45

   1. Initial program 31.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 40.7%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in x around inf 34.1%

      \[\leadsto \color{blue}{b \cdot \left(x \cdot \left(a \cdot y - j \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 34.1%

         \[\leadsto b \cdot \left(x \cdot \left(\color{blue}{y \cdot a} - j \cdot y0\right)\right) \]

   5. Simplified 34.1%

      \[\leadsto \color{blue}{b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)} \]

   if 1.50000000000000005e45 < t < 2.3000000000000001e151

   1. Initial program 30.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y2 around inf 35.6%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   3. Taylor expanded in y0 around inf 61.0%

      \[\leadsto y2 \cdot \color{blue}{\left(y0 \cdot \left(-1 \cdot \left(k \cdot y5\right) + c \cdot x\right)\right)} \]
   4. Step-by-step derivation

      1. +-commutative 61.0%

         \[\leadsto y2 \cdot \left(y0 \cdot \color{blue}{\left(c \cdot x + -1 \cdot \left(k \cdot y5\right)\right)}\right) \]

      2. mul-1-neg 61.0%

         \[\leadsto y2 \cdot \left(y0 \cdot \left(c \cdot x + \color{blue}{\left(-k \cdot y5\right)}\right)\right) \]

      3. unsub-neg 61.0%

         \[\leadsto y2 \cdot \left(y0 \cdot \color{blue}{\left(c \cdot x - k \cdot y5\right)}\right) \]

      4. *-commutative 61.0%

         \[\leadsto y2 \cdot \left(y0 \cdot \left(\color{blue}{x \cdot c} - k \cdot y5\right)\right) \]

      5. *-commutative 61.0%

         \[\leadsto y2 \cdot \left(y0 \cdot \left(x \cdot c - \color{blue}{y5 \cdot k}\right)\right) \]

   5. Simplified 61.0%

      \[\leadsto y2 \cdot \color{blue}{\left(y0 \cdot \left(x \cdot c - y5 \cdot k\right)\right)} \]

   if 2.3000000000000001e151 < t

   1. Initial program 25.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in c around inf 46.4%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in t around inf 54.0%

      \[\leadsto \color{blue}{c \cdot \left(t \cdot \left(i \cdot z - y2 \cdot y4\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 54.0%

         \[\leadsto c \cdot \left(t \cdot \left(i \cdot z - \color{blue}{y4 \cdot y2}\right)\right) \]

   5. Simplified 54.0%

      \[\leadsto \color{blue}{c \cdot \left(t \cdot \left(i \cdot z - y4 \cdot y2\right)\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 46.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -1.05 \cdot 10^{+144}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq -3 \cdot 10^{-63}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq 3.8 \cdot 10^{-266}:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y0 \cdot y2 - y \cdot i\right)\\ \mathbf{elif}\;t \leq 1.5 \cdot 10^{+45}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;t \leq 2.3 \cdot 10^{+151}:\\ \;\;\;\;y2 \cdot \left(y0 \cdot \left(x \cdot c - k \cdot y5\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(t \cdot \left(z \cdot i - y2 \cdot y4\right)\right)\\ \end{array} \]

Alternative 24: 22.1% accurate, 4.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := c \cdot \left(i \cdot \left(x \cdot \left(-y\right)\right)\right)\\ \mathbf{if}\;y5 \leq -2.3 \cdot 10^{+139}:\\ \;\;\;\;i \cdot \left(-t \cdot \left(j \cdot y5\right)\right)\\ \mathbf{elif}\;y5 \leq -5.8 \cdot 10^{-106}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y5 \leq -1.75 \cdot 10^{-269}:\\ \;\;\;\;a \cdot \left(b \cdot \left(t \cdot \left(-z\right)\right)\right)\\ \mathbf{elif}\;y5 \leq 1.95 \cdot 10^{-181}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y5 \leq 7.4 \cdot 10^{-9}:\\ \;\;\;\;y2 \cdot \left(x \cdot \left(a \cdot \left(-y1\right)\right)\right)\\ \mathbf{elif}\;y5 \leq 2.8 \cdot 10^{+84}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(t \cdot \left(i \cdot \left(-y5\right)\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* c (* i (* x (- y))))))
   (if (<= y5 -2.3e+139)
     (* i (- (* t (* j y5))))
     (if (<= y5 -5.8e-106)
       t_1
       (if (<= y5 -1.75e-269)
         (* a (* b (* t (- z))))
         (if (<= y5 1.95e-181)
           t_1
           (if (<= y5 7.4e-9)
             (* y2 (* x (* a (- y1))))
             (if (<= y5 2.8e+84)
               (* c (* x (* y0 y2)))
               (* j (* t (* i (- 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 * (i * (x * -y));
	double tmp;
	if (y5 <= -2.3e+139) {
		tmp = i * -(t * (j * y5));
	} else if (y5 <= -5.8e-106) {
		tmp = t_1;
	} else if (y5 <= -1.75e-269) {
		tmp = a * (b * (t * -z));
	} else if (y5 <= 1.95e-181) {
		tmp = t_1;
	} else if (y5 <= 7.4e-9) {
		tmp = y2 * (x * (a * -y1));
	} else if (y5 <= 2.8e+84) {
		tmp = c * (x * (y0 * y2));
	} else {
		tmp = j * (t * (i * -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 * (i * (x * -y))
    if (y5 <= (-2.3d+139)) then
        tmp = i * -(t * (j * y5))
    else if (y5 <= (-5.8d-106)) then
        tmp = t_1
    else if (y5 <= (-1.75d-269)) then
        tmp = a * (b * (t * -z))
    else if (y5 <= 1.95d-181) then
        tmp = t_1
    else if (y5 <= 7.4d-9) then
        tmp = y2 * (x * (a * -y1))
    else if (y5 <= 2.8d+84) then
        tmp = c * (x * (y0 * y2))
    else
        tmp = j * (t * (i * -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 * (i * (x * -y));
	double tmp;
	if (y5 <= -2.3e+139) {
		tmp = i * -(t * (j * y5));
	} else if (y5 <= -5.8e-106) {
		tmp = t_1;
	} else if (y5 <= -1.75e-269) {
		tmp = a * (b * (t * -z));
	} else if (y5 <= 1.95e-181) {
		tmp = t_1;
	} else if (y5 <= 7.4e-9) {
		tmp = y2 * (x * (a * -y1));
	} else if (y5 <= 2.8e+84) {
		tmp = c * (x * (y0 * y2));
	} else {
		tmp = j * (t * (i * -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 * (i * (x * -y))
	tmp = 0
	if y5 <= -2.3e+139:
		tmp = i * -(t * (j * y5))
	elif y5 <= -5.8e-106:
		tmp = t_1
	elif y5 <= -1.75e-269:
		tmp = a * (b * (t * -z))
	elif y5 <= 1.95e-181:
		tmp = t_1
	elif y5 <= 7.4e-9:
		tmp = y2 * (x * (a * -y1))
	elif y5 <= 2.8e+84:
		tmp = c * (x * (y0 * y2))
	else:
		tmp = j * (t * (i * -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(i * Float64(x * Float64(-y))))
	tmp = 0.0
	if (y5 <= -2.3e+139)
		tmp = Float64(i * Float64(-Float64(t * Float64(j * y5))));
	elseif (y5 <= -5.8e-106)
		tmp = t_1;
	elseif (y5 <= -1.75e-269)
		tmp = Float64(a * Float64(b * Float64(t * Float64(-z))));
	elseif (y5 <= 1.95e-181)
		tmp = t_1;
	elseif (y5 <= 7.4e-9)
		tmp = Float64(y2 * Float64(x * Float64(a * Float64(-y1))));
	elseif (y5 <= 2.8e+84)
		tmp = Float64(c * Float64(x * Float64(y0 * y2)));
	else
		tmp = Float64(j * Float64(t * Float64(i * Float64(-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 * (i * (x * -y));
	tmp = 0.0;
	if (y5 <= -2.3e+139)
		tmp = i * -(t * (j * y5));
	elseif (y5 <= -5.8e-106)
		tmp = t_1;
	elseif (y5 <= -1.75e-269)
		tmp = a * (b * (t * -z));
	elseif (y5 <= 1.95e-181)
		tmp = t_1;
	elseif (y5 <= 7.4e-9)
		tmp = y2 * (x * (a * -y1));
	elseif (y5 <= 2.8e+84)
		tmp = c * (x * (y0 * y2));
	else
		tmp = j * (t * (i * -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[(i * N[(x * (-y)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y5, -2.3e+139], N[(i * (-N[(t * N[(j * y5), $MachinePrecision]), $MachinePrecision])), $MachinePrecision], If[LessEqual[y5, -5.8e-106], t$95$1, If[LessEqual[y5, -1.75e-269], N[(a * N[(b * N[(t * (-z)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 1.95e-181], t$95$1, If[LessEqual[y5, 7.4e-9], N[(y2 * N[(x * N[(a * (-y1)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y5, 2.8e+84], N[(c * N[(x * N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(j * N[(t * N[(i * (-y5)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]

Derivation

1. Split input into 6 regimes

2. if y5 < -2.3e139

   1. Initial program 18.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 53.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 53.4%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 53.4%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 53.4%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 53.4%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 53.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in t around inf 43.4%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   6. Taylor expanded in b around 0 43.3%

      \[\leadsto j \cdot \color{blue}{\left(-1 \cdot \left(i \cdot \left(t \cdot y5\right)\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 43.3%

         \[\leadsto j \cdot \color{blue}{\left(\left(-1 \cdot i\right) \cdot \left(t \cdot y5\right)\right)} \]

      2. neg-mul-1 43.3%

         \[\leadsto j \cdot \left(\color{blue}{\left(-i\right)} \cdot \left(t \cdot y5\right)\right) \]

   8. Simplified 43.3%

      \[\leadsto j \cdot \color{blue}{\left(\left(-i\right) \cdot \left(t \cdot y5\right)\right)} \]

   9. Taylor expanded in j around 0 45.4%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(j \cdot \left(t \cdot y5\right)\right)\right)} \]
   10. Step-by-step derivation

       1. mul-1-neg 45.4%

          \[\leadsto \color{blue}{-i \cdot \left(j \cdot \left(t \cdot y5\right)\right)} \]

       2. distribute-rgt-neg-in 45.4%

          \[\leadsto \color{blue}{i \cdot \left(-j \cdot \left(t \cdot y5\right)\right)} \]

       3. *-commutative 45.4%

          \[\leadsto i \cdot \left(-\color{blue}{\left(t \cdot y5\right) \cdot j}\right) \]

       4. associate-*l* 47.5%

          \[\leadsto i \cdot \left(-\color{blue}{t \cdot \left(y5 \cdot j\right)}\right) \]

   11. Simplified 47.5%

       \[\leadsto \color{blue}{i \cdot \left(-t \cdot \left(y5 \cdot j\right)\right)} \]

   if -2.3e139 < y5 < -5.8000000000000001e-106 or -1.75000000000000009e-269 < y5 < 1.95e-181

   1. Initial program 24.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in c around inf 47.0%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in x around inf 40.6%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 36.1%

         \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)} \]

      2. +-commutative 36.1%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 + -1 \cdot \left(i \cdot y\right)\right)} \]

      3. mul-1-neg 36.1%

         \[\leadsto \left(c \cdot x\right) \cdot \left(y0 \cdot y2 + \color{blue}{\left(-i \cdot y\right)}\right) \]

      4. unsub-neg 36.1%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 - i \cdot y\right)} \]

   5. Simplified 36.1%

      \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(y0 \cdot y2 - i \cdot y\right)} \]

   6. Taylor expanded in y0 around 0 30.6%

      \[\leadsto \color{blue}{-1 \cdot \left(c \cdot \left(i \cdot \left(x \cdot y\right)\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 30.6%

         \[\leadsto \color{blue}{\left(-1 \cdot c\right) \cdot \left(i \cdot \left(x \cdot y\right)\right)} \]

      2. neg-mul-1 30.6%

         \[\leadsto \color{blue}{\left(-c\right)} \cdot \left(i \cdot \left(x \cdot y\right)\right) \]

      3. *-commutative 30.6%

         \[\leadsto \left(-c\right) \cdot \color{blue}{\left(\left(x \cdot y\right) \cdot i\right)} \]

   8. Simplified 30.6%

      \[\leadsto \color{blue}{\left(-c\right) \cdot \left(\left(x \cdot y\right) \cdot i\right)} \]

   if -5.8000000000000001e-106 < y5 < -1.75000000000000009e-269

   1. Initial program 46.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 43.2%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 33.7%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   4. Taylor expanded in x around 0 30.0%

      \[\leadsto a \cdot \left(b \cdot \color{blue}{\left(-1 \cdot \left(t \cdot z\right)\right)}\right) \]
   5. Step-by-step derivation

      1. neg-mul-1 30.0%

         \[\leadsto a \cdot \left(b \cdot \color{blue}{\left(-t \cdot z\right)}\right) \]

      2. distribute-lft-neg-in 30.0%

         \[\leadsto a \cdot \left(b \cdot \color{blue}{\left(\left(-t\right) \cdot z\right)}\right) \]

      3. *-commutative 30.0%

         \[\leadsto a \cdot \left(b \cdot \color{blue}{\left(z \cdot \left(-t\right)\right)}\right) \]

   6. Simplified 30.0%

      \[\leadsto a \cdot \left(b \cdot \color{blue}{\left(z \cdot \left(-t\right)\right)}\right) \]

   if 1.95e-181 < y5 < 7.4e-9

   1. Initial program 39.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y2 around inf 40.4%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   3. Taylor expanded in x around inf 40.1%

      \[\leadsto y2 \cdot \color{blue}{\left(x \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   4. Taylor expanded in c around 0 32.3%

      \[\leadsto y2 \cdot \left(x \cdot \color{blue}{\left(-1 \cdot \left(a \cdot y1\right)\right)}\right) \]
   5. Step-by-step derivation

      1. neg-mul-1 32.3%

         \[\leadsto y2 \cdot \left(x \cdot \color{blue}{\left(-a \cdot y1\right)}\right) \]

      2. distribute-lft-neg-in 32.3%

         \[\leadsto y2 \cdot \left(x \cdot \color{blue}{\left(\left(-a\right) \cdot y1\right)}\right) \]

      3. *-commutative 32.3%

         \[\leadsto y2 \cdot \left(x \cdot \color{blue}{\left(y1 \cdot \left(-a\right)\right)}\right) \]

   6. Simplified 32.3%

      \[\leadsto y2 \cdot \left(x \cdot \color{blue}{\left(y1 \cdot \left(-a\right)\right)}\right) \]

   if 7.4e-9 < y5 < 2.79999999999999982e84

   1. Initial program 30.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in c around inf 48.7%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in x around inf 44.6%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 40.2%

         \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)} \]

      2. +-commutative 40.2%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 + -1 \cdot \left(i \cdot y\right)\right)} \]

      3. mul-1-neg 40.2%

         \[\leadsto \left(c \cdot x\right) \cdot \left(y0 \cdot y2 + \color{blue}{\left(-i \cdot y\right)}\right) \]

      4. unsub-neg 40.2%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 - i \cdot y\right)} \]

   5. Simplified 40.2%

      \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(y0 \cdot y2 - i \cdot y\right)} \]

   6. Taylor expanded in y0 around inf 40.4%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 40.4%

         \[\leadsto c \cdot \left(x \cdot \color{blue}{\left(y2 \cdot y0\right)}\right) \]

   8. Simplified 40.4%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y2 \cdot y0\right)\right)} \]

   if 2.79999999999999982e84 < y5

   1. Initial program 27.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 31.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 31.4%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 31.4%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 31.4%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 31.4%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 31.4%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in t around inf 40.3%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   6. Taylor expanded in b around 0 35.1%

      \[\leadsto j \cdot \left(t \cdot \color{blue}{\left(-1 \cdot \left(i \cdot y5\right)\right)}\right) \]
   7. Step-by-step derivation

      1. mul-1-neg 35.1%

         \[\leadsto j \cdot \left(t \cdot \color{blue}{\left(-i \cdot y5\right)}\right) \]

      2. distribute-lft-neg-out 35.1%

         \[\leadsto j \cdot \left(t \cdot \color{blue}{\left(\left(-i\right) \cdot y5\right)}\right) \]

      3. *-commutative 35.1%

         \[\leadsto j \cdot \left(t \cdot \color{blue}{\left(y5 \cdot \left(-i\right)\right)}\right) \]

   8. Simplified 35.1%

      \[\leadsto j \cdot \left(t \cdot \color{blue}{\left(y5 \cdot \left(-i\right)\right)}\right) \]
3. Recombined 6 regimes into one program.

4. Final simplification 35.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y5 \leq -2.3 \cdot 10^{+139}:\\ \;\;\;\;i \cdot \left(-t \cdot \left(j \cdot y5\right)\right)\\ \mathbf{elif}\;y5 \leq -5.8 \cdot 10^{-106}:\\ \;\;\;\;c \cdot \left(i \cdot \left(x \cdot \left(-y\right)\right)\right)\\ \mathbf{elif}\;y5 \leq -1.75 \cdot 10^{-269}:\\ \;\;\;\;a \cdot \left(b \cdot \left(t \cdot \left(-z\right)\right)\right)\\ \mathbf{elif}\;y5 \leq 1.95 \cdot 10^{-181}:\\ \;\;\;\;c \cdot \left(i \cdot \left(x \cdot \left(-y\right)\right)\right)\\ \mathbf{elif}\;y5 \leq 7.4 \cdot 10^{-9}:\\ \;\;\;\;y2 \cdot \left(x \cdot \left(a \cdot \left(-y1\right)\right)\right)\\ \mathbf{elif}\;y5 \leq 2.8 \cdot 10^{+84}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(t \cdot \left(i \cdot \left(-y5\right)\right)\right)\\ \end{array} \]

Alternative 25: 28.1% accurate, 4.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{if}\;y0 \leq -6.8 \cdot 10^{+71}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y0 \leq -7 \cdot 10^{-110}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y0 \leq -2 \cdot 10^{-216}:\\ \;\;\;\;i \cdot \left(-t \cdot \left(j \cdot y5\right)\right)\\ \mathbf{elif}\;y0 \leq 1.5 \cdot 10^{+85}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;y2 \cdot \left(x \cdot \left(c \cdot y0\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* a (* b (- (* x y) (* z t))))))
   (if (<= y0 -6.8e+71)
     (* c (* x (* y0 y2)))
     (if (<= y0 -7e-110)
       t_1
       (if (<= y0 -2e-216)
         (* i (- (* t (* j y5))))
         (if (<= y0 1.5e+85) t_1 (* y2 (* x (* c y0)))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = a * (b * ((x * y) - (z * t)));
	double tmp;
	if (y0 <= -6.8e+71) {
		tmp = c * (x * (y0 * y2));
	} else if (y0 <= -7e-110) {
		tmp = t_1;
	} else if (y0 <= -2e-216) {
		tmp = i * -(t * (j * y5));
	} else if (y0 <= 1.5e+85) {
		tmp = t_1;
	} else {
		tmp = y2 * (x * (c * y0));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = a * (b * ((x * y) - (z * t)))
    if (y0 <= (-6.8d+71)) then
        tmp = c * (x * (y0 * y2))
    else if (y0 <= (-7d-110)) then
        tmp = t_1
    else if (y0 <= (-2d-216)) then
        tmp = i * -(t * (j * y5))
    else if (y0 <= 1.5d+85) then
        tmp = t_1
    else
        tmp = y2 * (x * (c * y0))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = a * (b * ((x * y) - (z * t)));
	double tmp;
	if (y0 <= -6.8e+71) {
		tmp = c * (x * (y0 * y2));
	} else if (y0 <= -7e-110) {
		tmp = t_1;
	} else if (y0 <= -2e-216) {
		tmp = i * -(t * (j * y5));
	} else if (y0 <= 1.5e+85) {
		tmp = t_1;
	} else {
		tmp = y2 * (x * (c * y0));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = a * (b * ((x * y) - (z * t)))
	tmp = 0
	if y0 <= -6.8e+71:
		tmp = c * (x * (y0 * y2))
	elif y0 <= -7e-110:
		tmp = t_1
	elif y0 <= -2e-216:
		tmp = i * -(t * (j * y5))
	elif y0 <= 1.5e+85:
		tmp = t_1
	else:
		tmp = y2 * (x * (c * y0))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))))
	tmp = 0.0
	if (y0 <= -6.8e+71)
		tmp = Float64(c * Float64(x * Float64(y0 * y2)));
	elseif (y0 <= -7e-110)
		tmp = t_1;
	elseif (y0 <= -2e-216)
		tmp = Float64(i * Float64(-Float64(t * Float64(j * y5))));
	elseif (y0 <= 1.5e+85)
		tmp = t_1;
	else
		tmp = Float64(y2 * Float64(x * Float64(c * y0)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = a * (b * ((x * y) - (z * t)));
	tmp = 0.0;
	if (y0 <= -6.8e+71)
		tmp = c * (x * (y0 * y2));
	elseif (y0 <= -7e-110)
		tmp = t_1;
	elseif (y0 <= -2e-216)
		tmp = i * -(t * (j * y5));
	elseif (y0 <= 1.5e+85)
		tmp = t_1;
	else
		tmp = y2 * (x * (c * y0));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y0, -6.8e+71], N[(c * N[(x * N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y0, -7e-110], t$95$1, If[LessEqual[y0, -2e-216], N[(i * (-N[(t * N[(j * y5), $MachinePrecision]), $MachinePrecision])), $MachinePrecision], If[LessEqual[y0, 1.5e+85], t$95$1, N[(y2 * N[(x * N[(c * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

1. Split input into 4 regimes

2. if y0 < -6.7999999999999997e71

   1. Initial program 31.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in c around inf 48.4%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in x around inf 50.6%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 43.1%

         \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)} \]

      2. +-commutative 43.1%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 + -1 \cdot \left(i \cdot y\right)\right)} \]

      3. mul-1-neg 43.1%

         \[\leadsto \left(c \cdot x\right) \cdot \left(y0 \cdot y2 + \color{blue}{\left(-i \cdot y\right)}\right) \]

      4. unsub-neg 43.1%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 - i \cdot y\right)} \]

   5. Simplified 43.1%

      \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(y0 \cdot y2 - i \cdot y\right)} \]

   6. Taylor expanded in y0 around inf 43.5%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 43.5%

         \[\leadsto c \cdot \left(x \cdot \color{blue}{\left(y2 \cdot y0\right)}\right) \]

   8. Simplified 43.5%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y2 \cdot y0\right)\right)} \]

   if -6.7999999999999997e71 < y0 < -6.99999999999999947e-110 or -2.0000000000000001e-216 < y0 < 1.5e85

   1. Initial program 32.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 36.5%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 33.0%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   if -6.99999999999999947e-110 < y0 < -2.0000000000000001e-216

   1. Initial program 21.8%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 53.1%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 53.1%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 53.1%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 53.1%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 53.1%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 53.1%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in t around inf 32.8%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   6. Taylor expanded in b around 0 32.6%

      \[\leadsto j \cdot \color{blue}{\left(-1 \cdot \left(i \cdot \left(t \cdot y5\right)\right)\right)} \]
   7. Step-by-step derivation

      1. associate-*r* 32.6%

         \[\leadsto j \cdot \color{blue}{\left(\left(-1 \cdot i\right) \cdot \left(t \cdot y5\right)\right)} \]

      2. neg-mul-1 32.6%

         \[\leadsto j \cdot \left(\color{blue}{\left(-i\right)} \cdot \left(t \cdot y5\right)\right) \]

   8. Simplified 32.6%

      \[\leadsto j \cdot \color{blue}{\left(\left(-i\right) \cdot \left(t \cdot y5\right)\right)} \]

   9. Taylor expanded in j around 0 32.6%

      \[\leadsto \color{blue}{-1 \cdot \left(i \cdot \left(j \cdot \left(t \cdot y5\right)\right)\right)} \]
   10. Step-by-step derivation

       1. mul-1-neg 32.6%

          \[\leadsto \color{blue}{-i \cdot \left(j \cdot \left(t \cdot y5\right)\right)} \]

       2. distribute-rgt-neg-in 32.6%

          \[\leadsto \color{blue}{i \cdot \left(-j \cdot \left(t \cdot y5\right)\right)} \]

       3. *-commutative 32.6%

          \[\leadsto i \cdot \left(-\color{blue}{\left(t \cdot y5\right) \cdot j}\right) \]

       4. associate-*l* 45.2%

          \[\leadsto i \cdot \left(-\color{blue}{t \cdot \left(y5 \cdot j\right)}\right) \]

   11. Simplified 45.2%

       \[\leadsto \color{blue}{i \cdot \left(-t \cdot \left(y5 \cdot j\right)\right)} \]

   if 1.5e85 < y0

   1. Initial program 19.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y2 around inf 40.8%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   3. Taylor expanded in x around inf 31.6%

      \[\leadsto y2 \cdot \color{blue}{\left(x \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   4. Taylor expanded in c around inf 29.5%

      \[\leadsto y2 \cdot \left(x \cdot \color{blue}{\left(c \cdot y0\right)}\right) \]
   5. Step-by-step derivation

      1. *-commutative 29.5%

         \[\leadsto y2 \cdot \left(x \cdot \color{blue}{\left(y0 \cdot c\right)}\right) \]

   6. Simplified 29.5%

      \[\leadsto y2 \cdot \left(x \cdot \color{blue}{\left(y0 \cdot c\right)}\right) \]
3. Recombined 4 regimes into one program.

4. Final simplification 35.7%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y0 \leq -6.8 \cdot 10^{+71}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y0 \leq -7 \cdot 10^{-110}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{elif}\;y0 \leq -2 \cdot 10^{-216}:\\ \;\;\;\;i \cdot \left(-t \cdot \left(j \cdot y5\right)\right)\\ \mathbf{elif}\;y0 \leq 1.5 \cdot 10^{+85}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{else}:\\ \;\;\;\;y2 \cdot \left(x \cdot \left(c \cdot y0\right)\right)\\ \end{array} \]

Alternative 26: 25.6% accurate, 4.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y \leq -2.1 \cdot 10^{-146}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y \leq 2.3 \cdot 10^{-282}:\\ \;\;\;\;y2 \cdot \left(x \cdot \left(a \cdot \left(-y1\right)\right)\right)\\ \mathbf{elif}\;y \leq 3.05 \cdot 10^{-89}:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y0 \cdot y2\right)\\ \mathbf{elif}\;y \leq 1.32 \cdot 10^{+200}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= y -2.1e-146)
   (* b (* x (- (* y a) (* j y0))))
   (if (<= y 2.3e-282)
     (* y2 (* x (* a (- y1))))
     (if (<= y 3.05e-89)
       (* (* x c) (* y0 y2))
       (if (<= y 1.32e+200)
         (* a (* b (- (* x y) (* z t))))
         (* c (* y4 (* y y3))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y <= -2.1e-146) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (y <= 2.3e-282) {
		tmp = y2 * (x * (a * -y1));
	} else if (y <= 3.05e-89) {
		tmp = (x * c) * (y0 * y2);
	} else if (y <= 1.32e+200) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else {
		tmp = c * (y4 * (y * y3));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (y <= (-2.1d-146)) then
        tmp = b * (x * ((y * a) - (j * y0)))
    else if (y <= 2.3d-282) then
        tmp = y2 * (x * (a * -y1))
    else if (y <= 3.05d-89) then
        tmp = (x * c) * (y0 * y2)
    else if (y <= 1.32d+200) then
        tmp = a * (b * ((x * y) - (z * t)))
    else
        tmp = c * (y4 * (y * y3))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y <= -2.1e-146) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (y <= 2.3e-282) {
		tmp = y2 * (x * (a * -y1));
	} else if (y <= 3.05e-89) {
		tmp = (x * c) * (y0 * y2);
	} else if (y <= 1.32e+200) {
		tmp = a * (b * ((x * y) - (z * t)));
	} else {
		tmp = c * (y4 * (y * y3));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if y <= -2.1e-146:
		tmp = b * (x * ((y * a) - (j * y0)))
	elif y <= 2.3e-282:
		tmp = y2 * (x * (a * -y1))
	elif y <= 3.05e-89:
		tmp = (x * c) * (y0 * y2)
	elif y <= 1.32e+200:
		tmp = a * (b * ((x * y) - (z * t)))
	else:
		tmp = c * (y4 * (y * y3))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (y <= -2.1e-146)
		tmp = Float64(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))));
	elseif (y <= 2.3e-282)
		tmp = Float64(y2 * Float64(x * Float64(a * Float64(-y1))));
	elseif (y <= 3.05e-89)
		tmp = Float64(Float64(x * c) * Float64(y0 * y2));
	elseif (y <= 1.32e+200)
		tmp = Float64(a * Float64(b * Float64(Float64(x * y) - Float64(z * t))));
	else
		tmp = Float64(c * Float64(y4 * Float64(y * y3)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (y <= -2.1e-146)
		tmp = b * (x * ((y * a) - (j * y0)));
	elseif (y <= 2.3e-282)
		tmp = y2 * (x * (a * -y1));
	elseif (y <= 3.05e-89)
		tmp = (x * c) * (y0 * y2);
	elseif (y <= 1.32e+200)
		tmp = a * (b * ((x * y) - (z * t)));
	else
		tmp = c * (y4 * (y * y3));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[y, -2.1e-146], N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 2.3e-282], N[(y2 * N[(x * N[(a * (-y1)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 3.05e-89], N[(N[(x * c), $MachinePrecision] * N[(y0 * y2), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 1.32e+200], N[(a * N[(b * N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(c * N[(y4 * N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

1. Split input into 5 regimes

2. if y < -2.0999999999999999e-146

   1. Initial program 30.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 31.8%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in x around inf 37.7%

      \[\leadsto \color{blue}{b \cdot \left(x \cdot \left(a \cdot y - j \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 37.7%

         \[\leadsto b \cdot \left(x \cdot \left(\color{blue}{y \cdot a} - j \cdot y0\right)\right) \]

   5. Simplified 37.7%

      \[\leadsto \color{blue}{b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)} \]

   if -2.0999999999999999e-146 < y < 2.2999999999999999e-282

   1. Initial program 31.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y2 around inf 41.1%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   3. Taylor expanded in x around inf 32.2%

      \[\leadsto y2 \cdot \color{blue}{\left(x \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   4. Taylor expanded in c around 0 26.3%

      \[\leadsto y2 \cdot \left(x \cdot \color{blue}{\left(-1 \cdot \left(a \cdot y1\right)\right)}\right) \]
   5. Step-by-step derivation

      1. neg-mul-1 26.3%

         \[\leadsto y2 \cdot \left(x \cdot \color{blue}{\left(-a \cdot y1\right)}\right) \]

      2. distribute-lft-neg-in 26.3%

         \[\leadsto y2 \cdot \left(x \cdot \color{blue}{\left(\left(-a\right) \cdot y1\right)}\right) \]

      3. *-commutative 26.3%

         \[\leadsto y2 \cdot \left(x \cdot \color{blue}{\left(y1 \cdot \left(-a\right)\right)}\right) \]

   6. Simplified 26.3%

      \[\leadsto y2 \cdot \left(x \cdot \color{blue}{\left(y1 \cdot \left(-a\right)\right)}\right) \]

   if 2.2999999999999999e-282 < y < 3.0500000000000001e-89

   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. Taylor expanded in c around inf 42.6%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in x around inf 35.9%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 35.8%

         \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)} \]

      2. +-commutative 35.8%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 + -1 \cdot \left(i \cdot y\right)\right)} \]

      3. mul-1-neg 35.8%

         \[\leadsto \left(c \cdot x\right) \cdot \left(y0 \cdot y2 + \color{blue}{\left(-i \cdot y\right)}\right) \]

      4. unsub-neg 35.8%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 - i \cdot y\right)} \]

   5. Simplified 35.8%

      \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(y0 \cdot y2 - i \cdot y\right)} \]

   6. Taylor expanded in y0 around inf 35.8%

      \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2\right)} \]
   7. Step-by-step derivation

      1. *-commutative 35.8%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y2 \cdot y0\right)} \]

   8. Simplified 35.8%

      \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y2 \cdot y0\right)} \]

   if 3.0500000000000001e-89 < y < 1.3199999999999999e200

   1. Initial program 29.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 43.4%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 38.4%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   if 1.3199999999999999e200 < y

   1. Initial program 5.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y3 around -inf 53.3%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   3. Taylor expanded in y around inf 85.1%

      \[\leadsto -1 \cdot \color{blue}{\left(y \cdot \left(y3 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 85.1%

         \[\leadsto -1 \cdot \color{blue}{\left(\left(y \cdot y3\right) \cdot \left(a \cdot y5 - c \cdot y4\right)\right)} \]

      2. *-commutative 85.1%

         \[\leadsto -1 \cdot \left(\color{blue}{\left(y3 \cdot y\right)} \cdot \left(a \cdot y5 - c \cdot y4\right)\right) \]

      3. *-commutative 85.1%

         \[\leadsto -1 \cdot \left(\left(y3 \cdot y\right) \cdot \left(\color{blue}{y5 \cdot a} - c \cdot y4\right)\right) \]

      4. *-commutative 85.1%

         \[\leadsto -1 \cdot \left(\left(y3 \cdot y\right) \cdot \left(y5 \cdot a - \color{blue}{y4 \cdot c}\right)\right) \]

   5. Simplified 85.1%

      \[\leadsto -1 \cdot \color{blue}{\left(\left(y3 \cdot y\right) \cdot \left(y5 \cdot a - y4 \cdot c\right)\right)} \]

   6. Taylor expanded in y5 around 0 53.8%

      \[\leadsto -1 \cdot \left(\left(y3 \cdot y\right) \cdot \color{blue}{\left(-1 \cdot \left(c \cdot y4\right)\right)}\right) \]
   7. Step-by-step derivation

      1. mul-1-neg 53.8%

         \[\leadsto -1 \cdot \left(\left(y3 \cdot y\right) \cdot \color{blue}{\left(-c \cdot y4\right)}\right) \]

      2. distribute-rgt-neg-in 53.8%

         \[\leadsto -1 \cdot \left(\left(y3 \cdot y\right) \cdot \color{blue}{\left(c \cdot \left(-y4\right)\right)}\right) \]

   8. Simplified 53.8%

      \[\leadsto -1 \cdot \left(\left(y3 \cdot y\right) \cdot \color{blue}{\left(c \cdot \left(-y4\right)\right)}\right) \]

   9. Taylor expanded in y3 around 0 59.3%

      \[\leadsto -1 \cdot \color{blue}{\left(-1 \cdot \left(c \cdot \left(y \cdot \left(y3 \cdot y4\right)\right)\right)\right)} \]
   10. Step-by-step derivation

       1. mul-1-neg 59.3%

          \[\leadsto -1 \cdot \color{blue}{\left(-c \cdot \left(y \cdot \left(y3 \cdot y4\right)\right)\right)} \]

       2. *-commutative 59.3%

          \[\leadsto -1 \cdot \left(-\color{blue}{\left(y \cdot \left(y3 \cdot y4\right)\right) \cdot c}\right) \]

       3. distribute-rgt-neg-in 59.3%

          \[\leadsto -1 \cdot \color{blue}{\left(\left(y \cdot \left(y3 \cdot y4\right)\right) \cdot \left(-c\right)\right)} \]

       4. associate-*r* 64.3%

          \[\leadsto -1 \cdot \left(\color{blue}{\left(\left(y \cdot y3\right) \cdot y4\right)} \cdot \left(-c\right)\right) \]

       5. *-commutative 64.3%

          \[\leadsto -1 \cdot \left(\color{blue}{\left(y4 \cdot \left(y \cdot y3\right)\right)} \cdot \left(-c\right)\right) \]

   11. Simplified 64.3%

       \[\leadsto -1 \cdot \color{blue}{\left(\left(y4 \cdot \left(y \cdot y3\right)\right) \cdot \left(-c\right)\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 37.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y \leq -2.1 \cdot 10^{-146}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y \leq 2.3 \cdot 10^{-282}:\\ \;\;\;\;y2 \cdot \left(x \cdot \left(a \cdot \left(-y1\right)\right)\right)\\ \mathbf{elif}\;y \leq 3.05 \cdot 10^{-89}:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y0 \cdot y2\right)\\ \mathbf{elif}\;y \leq 1.32 \cdot 10^{+200}:\\ \;\;\;\;a \cdot \left(b \cdot \left(x \cdot y - z \cdot t\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3\right)\right)\\ \end{array} \]

Alternative 27: 29.3% accurate, 4.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y \leq -1.5 \cdot 10^{-131}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y \leq -5.5 \cdot 10^{-307}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)\\ \mathbf{elif}\;y \leq 5 \cdot 10^{-73}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq 6.5 \cdot 10^{+141}:\\ \;\;\;\;c \cdot \left(t \cdot \left(z \cdot i - y2 \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= y -1.5e-131)
   (* b (* x (- (* y a) (* j y0))))
   (if (<= y -5.5e-307)
     (* c (* z (- (* t i) (* y0 y3))))
     (if (<= y 5e-73)
       (* c (* y2 (- (* x y0) (* t y4))))
       (if (<= y 6.5e+141)
         (* c (* t (- (* z i) (* y2 y4))))
         (* c (* y4 (- (* y y3) (* t 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 (y <= -1.5e-131) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (y <= -5.5e-307) {
		tmp = c * (z * ((t * i) - (y0 * y3)));
	} else if (y <= 5e-73) {
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	} else if (y <= 6.5e+141) {
		tmp = c * (t * ((z * i) - (y2 * y4)));
	} else {
		tmp = c * (y4 * ((y * y3) - (t * 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 (y <= (-1.5d-131)) then
        tmp = b * (x * ((y * a) - (j * y0)))
    else if (y <= (-5.5d-307)) then
        tmp = c * (z * ((t * i) - (y0 * y3)))
    else if (y <= 5d-73) then
        tmp = c * (y2 * ((x * y0) - (t * y4)))
    else if (y <= 6.5d+141) then
        tmp = c * (t * ((z * i) - (y2 * y4)))
    else
        tmp = c * (y4 * ((y * y3) - (t * 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 (y <= -1.5e-131) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (y <= -5.5e-307) {
		tmp = c * (z * ((t * i) - (y0 * y3)));
	} else if (y <= 5e-73) {
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	} else if (y <= 6.5e+141) {
		tmp = c * (t * ((z * i) - (y2 * y4)));
	} else {
		tmp = c * (y4 * ((y * y3) - (t * 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 y <= -1.5e-131:
		tmp = b * (x * ((y * a) - (j * y0)))
	elif y <= -5.5e-307:
		tmp = c * (z * ((t * i) - (y0 * y3)))
	elif y <= 5e-73:
		tmp = c * (y2 * ((x * y0) - (t * y4)))
	elif y <= 6.5e+141:
		tmp = c * (t * ((z * i) - (y2 * y4)))
	else:
		tmp = c * (y4 * ((y * y3) - (t * 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 (y <= -1.5e-131)
		tmp = Float64(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))));
	elseif (y <= -5.5e-307)
		tmp = Float64(c * Float64(z * Float64(Float64(t * i) - Float64(y0 * y3))));
	elseif (y <= 5e-73)
		tmp = Float64(c * Float64(y2 * Float64(Float64(x * y0) - Float64(t * y4))));
	elseif (y <= 6.5e+141)
		tmp = Float64(c * Float64(t * Float64(Float64(z * i) - Float64(y2 * y4))));
	else
		tmp = Float64(c * Float64(y4 * Float64(Float64(y * y3) - Float64(t * 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 (y <= -1.5e-131)
		tmp = b * (x * ((y * a) - (j * y0)));
	elseif (y <= -5.5e-307)
		tmp = c * (z * ((t * i) - (y0 * y3)));
	elseif (y <= 5e-73)
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	elseif (y <= 6.5e+141)
		tmp = c * (t * ((z * i) - (y2 * y4)));
	else
		tmp = c * (y4 * ((y * y3) - (t * 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[y, -1.5e-131], N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, -5.5e-307], N[(c * N[(z * N[(N[(t * i), $MachinePrecision] - N[(y0 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 5e-73], N[(c * N[(y2 * N[(N[(x * y0), $MachinePrecision] - N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 6.5e+141], N[(c * N[(t * N[(N[(z * i), $MachinePrecision] - N[(y2 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(c * N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

1. Split input into 5 regimes

2. if y < -1.49999999999999998e-131

   1. Initial program 31.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 31.4%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in x around inf 37.4%

      \[\leadsto \color{blue}{b \cdot \left(x \cdot \left(a \cdot y - j \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 37.4%

         \[\leadsto b \cdot \left(x \cdot \left(\color{blue}{y \cdot a} - j \cdot y0\right)\right) \]

   5. Simplified 37.4%

      \[\leadsto \color{blue}{b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)} \]

   if -1.49999999999999998e-131 < y < -5.50000000000000039e-307

   1. Initial program 32.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in c around inf 37.4%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in z around inf 33.2%

      \[\leadsto c \cdot \color{blue}{\left(z \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 33.2%

         \[\leadsto c \cdot \color{blue}{\left(\left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right) \cdot z\right)} \]

      2. +-commutative 33.2%

         \[\leadsto c \cdot \left(\color{blue}{\left(i \cdot t + -1 \cdot \left(y0 \cdot y3\right)\right)} \cdot z\right) \]

      3. mul-1-neg 33.2%

         \[\leadsto c \cdot \left(\left(i \cdot t + \color{blue}{\left(-y0 \cdot y3\right)}\right) \cdot z\right) \]

      4. sub-neg 33.2%

         \[\leadsto c \cdot \left(\color{blue}{\left(i \cdot t - y0 \cdot y3\right)} \cdot z\right) \]

      5. *-commutative 33.2%

         \[\leadsto c \cdot \left(\left(\color{blue}{t \cdot i} - y0 \cdot y3\right) \cdot z\right) \]

   5. Simplified 33.2%

      \[\leadsto c \cdot \color{blue}{\left(\left(t \cdot i - y0 \cdot y3\right) \cdot z\right)} \]

   if -5.50000000000000039e-307 < y < 4.9999999999999998e-73

   1. Initial program 32.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in c around inf 44.7%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in y2 around inf 47.2%

      \[\leadsto \color{blue}{c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)} \]

   if 4.9999999999999998e-73 < y < 6.50000000000000053e141

   1. Initial program 28.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in c around inf 50.1%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in t around inf 48.1%

      \[\leadsto \color{blue}{c \cdot \left(t \cdot \left(i \cdot z - y2 \cdot y4\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 48.1%

         \[\leadsto c \cdot \left(t \cdot \left(i \cdot z - \color{blue}{y4 \cdot y2}\right)\right) \]

   5. Simplified 48.1%

      \[\leadsto \color{blue}{c \cdot \left(t \cdot \left(i \cdot z - y4 \cdot y2\right)\right)} \]

   if 6.50000000000000053e141 < y

   1. Initial program 10.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf 46.9%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in c around inf 61.5%

      \[\leadsto \color{blue}{c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 61.5%

         \[\leadsto c \cdot \left(y4 \cdot \left(\color{blue}{y3 \cdot y} - t \cdot y2\right)\right) \]

   5. Simplified 61.5%

      \[\leadsto \color{blue}{c \cdot \left(y4 \cdot \left(y3 \cdot y - t \cdot y2\right)\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 42.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y \leq -1.5 \cdot 10^{-131}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y \leq -5.5 \cdot 10^{-307}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)\\ \mathbf{elif}\;y \leq 5 \cdot 10^{-73}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq 6.5 \cdot 10^{+141}:\\ \;\;\;\;c \cdot \left(t \cdot \left(z \cdot i - y2 \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \end{array} \]

Alternative 28: 31.1% accurate, 4.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;t \leq -6 \cdot 10^{+140}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq -2.8 \cdot 10^{-61}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq 3.7 \cdot 10^{-240}:\\ \;\;\;\;c \cdot \left(y \cdot \left(y3 \cdot y4 - x \cdot i\right)\right)\\ \mathbf{elif}\;t \leq 2.7 \cdot 10^{+18}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= t -6e+140)
   (* j (* t (- (* b y4) (* i y5))))
   (if (<= t -2.8e-61)
     (* c (* y4 (- (* y y3) (* t y2))))
     (if (<= t 3.7e-240)
       (* c (* y (- (* y3 y4) (* x i))))
       (if (<= t 2.7e+18)
         (* b (* x (- (* y a) (* j y0))))
         (* c (* z (- (* t i) (* y0 y3)))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (t <= -6e+140) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (t <= -2.8e-61) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (t <= 3.7e-240) {
		tmp = c * (y * ((y3 * y4) - (x * i)));
	} else if (t <= 2.7e+18) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else {
		tmp = c * (z * ((t * i) - (y0 * y3)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (t <= (-6d+140)) then
        tmp = j * (t * ((b * y4) - (i * y5)))
    else if (t <= (-2.8d-61)) then
        tmp = c * (y4 * ((y * y3) - (t * y2)))
    else if (t <= 3.7d-240) then
        tmp = c * (y * ((y3 * y4) - (x * i)))
    else if (t <= 2.7d+18) then
        tmp = b * (x * ((y * a) - (j * y0)))
    else
        tmp = c * (z * ((t * i) - (y0 * y3)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (t <= -6e+140) {
		tmp = j * (t * ((b * y4) - (i * y5)));
	} else if (t <= -2.8e-61) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (t <= 3.7e-240) {
		tmp = c * (y * ((y3 * y4) - (x * i)));
	} else if (t <= 2.7e+18) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else {
		tmp = c * (z * ((t * i) - (y0 * y3)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if t <= -6e+140:
		tmp = j * (t * ((b * y4) - (i * y5)))
	elif t <= -2.8e-61:
		tmp = c * (y4 * ((y * y3) - (t * y2)))
	elif t <= 3.7e-240:
		tmp = c * (y * ((y3 * y4) - (x * i)))
	elif t <= 2.7e+18:
		tmp = b * (x * ((y * a) - (j * y0)))
	else:
		tmp = c * (z * ((t * i) - (y0 * y3)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (t <= -6e+140)
		tmp = Float64(j * Float64(t * Float64(Float64(b * y4) - Float64(i * y5))));
	elseif (t <= -2.8e-61)
		tmp = Float64(c * Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2))));
	elseif (t <= 3.7e-240)
		tmp = Float64(c * Float64(y * Float64(Float64(y3 * y4) - Float64(x * i))));
	elseif (t <= 2.7e+18)
		tmp = Float64(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))));
	else
		tmp = Float64(c * Float64(z * Float64(Float64(t * i) - Float64(y0 * y3))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (t <= -6e+140)
		tmp = j * (t * ((b * y4) - (i * y5)));
	elseif (t <= -2.8e-61)
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	elseif (t <= 3.7e-240)
		tmp = c * (y * ((y3 * y4) - (x * i)));
	elseif (t <= 2.7e+18)
		tmp = b * (x * ((y * a) - (j * y0)));
	else
		tmp = c * (z * ((t * i) - (y0 * y3)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[t, -6e+140], N[(j * N[(t * N[(N[(b * y4), $MachinePrecision] - N[(i * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, -2.8e-61], N[(c * N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 3.7e-240], N[(c * N[(y * N[(N[(y3 * y4), $MachinePrecision] - N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 2.7e+18], N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(c * N[(z * N[(N[(t * i), $MachinePrecision] - N[(y0 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

1. Split input into 5 regimes

2. if t < -5.99999999999999993e140

   1. Initial program 18.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 39.9%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 39.9%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 39.9%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 39.9%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 39.9%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 39.9%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in t around inf 50.4%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   if -5.99999999999999993e140 < t < -2.8000000000000001e-61

   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. Taylor expanded in y4 around inf 46.0%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in c around inf 51.1%

      \[\leadsto \color{blue}{c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 51.1%

         \[\leadsto c \cdot \left(y4 \cdot \left(\color{blue}{y3 \cdot y} - t \cdot y2\right)\right) \]

   5. Simplified 51.1%

      \[\leadsto \color{blue}{c \cdot \left(y4 \cdot \left(y3 \cdot y - t \cdot y2\right)\right)} \]

   if -2.8000000000000001e-61 < t < 3.7000000000000002e-240

   1. Initial program 40.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in c around inf 47.5%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in y around inf 42.6%

      \[\leadsto c \cdot \color{blue}{\left(y \cdot \left(-1 \cdot \left(i \cdot x\right) - -1 \cdot \left(y3 \cdot y4\right)\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 42.6%

         \[\leadsto c \cdot \color{blue}{\left(\left(-1 \cdot \left(i \cdot x\right) - -1 \cdot \left(y3 \cdot y4\right)\right) \cdot y\right)} \]

      2. cancel-sign-sub-inv 42.6%

         \[\leadsto c \cdot \left(\color{blue}{\left(-1 \cdot \left(i \cdot x\right) + \left(--1\right) \cdot \left(y3 \cdot y4\right)\right)} \cdot y\right) \]

      3. metadata-eval 42.6%

         \[\leadsto c \cdot \left(\left(-1 \cdot \left(i \cdot x\right) + \color{blue}{1} \cdot \left(y3 \cdot y4\right)\right) \cdot y\right) \]

      4. *-lft-identity 42.6%

         \[\leadsto c \cdot \left(\left(-1 \cdot \left(i \cdot x\right) + \color{blue}{y3 \cdot y4}\right) \cdot y\right) \]

      5. +-commutative 42.6%

         \[\leadsto c \cdot \left(\color{blue}{\left(y3 \cdot y4 + -1 \cdot \left(i \cdot x\right)\right)} \cdot y\right) \]

      6. mul-1-neg 42.6%

         \[\leadsto c \cdot \left(\left(y3 \cdot y4 + \color{blue}{\left(-i \cdot x\right)}\right) \cdot y\right) \]

      7. unsub-neg 42.6%

         \[\leadsto c \cdot \left(\color{blue}{\left(y3 \cdot y4 - i \cdot x\right)} \cdot y\right) \]

      8. *-commutative 42.6%

         \[\leadsto c \cdot \left(\left(\color{blue}{y4 \cdot y3} - i \cdot x\right) \cdot y\right) \]

   5. Simplified 42.6%

      \[\leadsto c \cdot \color{blue}{\left(\left(y4 \cdot y3 - i \cdot x\right) \cdot y\right)} \]

   if 3.7000000000000002e-240 < t < 2.7e18

   1. Initial program 29.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 38.2%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in x around inf 34.6%

      \[\leadsto \color{blue}{b \cdot \left(x \cdot \left(a \cdot y - j \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 34.6%

         \[\leadsto b \cdot \left(x \cdot \left(\color{blue}{y \cdot a} - j \cdot y0\right)\right) \]

   5. Simplified 34.6%

      \[\leadsto \color{blue}{b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)} \]

   if 2.7e18 < t

   1. Initial program 27.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in c around inf 36.5%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in z around inf 42.7%

      \[\leadsto c \cdot \color{blue}{\left(z \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 42.7%

         \[\leadsto c \cdot \color{blue}{\left(\left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right) \cdot z\right)} \]

      2. +-commutative 42.7%

         \[\leadsto c \cdot \left(\color{blue}{\left(i \cdot t + -1 \cdot \left(y0 \cdot y3\right)\right)} \cdot z\right) \]

      3. mul-1-neg 42.7%

         \[\leadsto c \cdot \left(\left(i \cdot t + \color{blue}{\left(-y0 \cdot y3\right)}\right) \cdot z\right) \]

      4. sub-neg 42.7%

         \[\leadsto c \cdot \left(\color{blue}{\left(i \cdot t - y0 \cdot y3\right)} \cdot z\right) \]

      5. *-commutative 42.7%

         \[\leadsto c \cdot \left(\left(\color{blue}{t \cdot i} - y0 \cdot y3\right) \cdot z\right) \]

   5. Simplified 42.7%

      \[\leadsto c \cdot \color{blue}{\left(\left(t \cdot i - y0 \cdot y3\right) \cdot z\right)} \]
3. Recombined 5 regimes into one program.

4. Final simplification 43.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -6 \cdot 10^{+140}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)\\ \mathbf{elif}\;t \leq -2.8 \cdot 10^{-61}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq 3.7 \cdot 10^{-240}:\\ \;\;\;\;c \cdot \left(y \cdot \left(y3 \cdot y4 - x \cdot i\right)\right)\\ \mathbf{elif}\;t \leq 2.7 \cdot 10^{+18}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)\\ \end{array} \]

Alternative 29: 21.9% accurate, 5.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{if}\;y4 \leq -6 \cdot 10^{+131}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y4 \leq -2500000000000:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y0 \cdot y2\right)\\ \mathbf{elif}\;y4 \leq -1.75 \cdot 10^{-44}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y4 \leq 2.95 \cdot 10^{+41}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y4 \leq 5.5 \cdot 10^{+161}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* j (* t y4)))))
   (if (<= y4 -6e+131)
     t_1
     (if (<= y4 -2500000000000.0)
       (* (* x c) (* y0 y2))
       (if (<= y4 -1.75e-44)
         t_1
         (if (<= y4 2.95e+41)
           (* c (* x (* y0 y2)))
           (if (<= y4 5.5e+161) (* a (* (* x y) b)) t_1)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (j * (t * y4));
	double tmp;
	if (y4 <= -6e+131) {
		tmp = t_1;
	} else if (y4 <= -2500000000000.0) {
		tmp = (x * c) * (y0 * y2);
	} else if (y4 <= -1.75e-44) {
		tmp = t_1;
	} else if (y4 <= 2.95e+41) {
		tmp = c * (x * (y0 * y2));
	} else if (y4 <= 5.5e+161) {
		tmp = a * ((x * y) * b);
	} 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 * (j * (t * y4))
    if (y4 <= (-6d+131)) then
        tmp = t_1
    else if (y4 <= (-2500000000000.0d0)) then
        tmp = (x * c) * (y0 * y2)
    else if (y4 <= (-1.75d-44)) then
        tmp = t_1
    else if (y4 <= 2.95d+41) then
        tmp = c * (x * (y0 * y2))
    else if (y4 <= 5.5d+161) then
        tmp = a * ((x * y) * b)
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (j * (t * y4));
	double tmp;
	if (y4 <= -6e+131) {
		tmp = t_1;
	} else if (y4 <= -2500000000000.0) {
		tmp = (x * c) * (y0 * y2);
	} else if (y4 <= -1.75e-44) {
		tmp = t_1;
	} else if (y4 <= 2.95e+41) {
		tmp = c * (x * (y0 * y2));
	} else if (y4 <= 5.5e+161) {
		tmp = a * ((x * y) * b);
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = b * (j * (t * y4))
	tmp = 0
	if y4 <= -6e+131:
		tmp = t_1
	elif y4 <= -2500000000000.0:
		tmp = (x * c) * (y0 * y2)
	elif y4 <= -1.75e-44:
		tmp = t_1
	elif y4 <= 2.95e+41:
		tmp = c * (x * (y0 * y2))
	elif y4 <= 5.5e+161:
		tmp = a * ((x * y) * b)
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(b * Float64(j * Float64(t * y4)))
	tmp = 0.0
	if (y4 <= -6e+131)
		tmp = t_1;
	elseif (y4 <= -2500000000000.0)
		tmp = Float64(Float64(x * c) * Float64(y0 * y2));
	elseif (y4 <= -1.75e-44)
		tmp = t_1;
	elseif (y4 <= 2.95e+41)
		tmp = Float64(c * Float64(x * Float64(y0 * y2)));
	elseif (y4 <= 5.5e+161)
		tmp = Float64(a * Float64(Float64(x * y) * b));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = b * (j * (t * y4));
	tmp = 0.0;
	if (y4 <= -6e+131)
		tmp = t_1;
	elseif (y4 <= -2500000000000.0)
		tmp = (x * c) * (y0 * y2);
	elseif (y4 <= -1.75e-44)
		tmp = t_1;
	elseif (y4 <= 2.95e+41)
		tmp = c * (x * (y0 * y2));
	elseif (y4 <= 5.5e+161)
		tmp = a * ((x * y) * b);
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(b * N[(j * N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y4, -6e+131], t$95$1, If[LessEqual[y4, -2500000000000.0], N[(N[(x * c), $MachinePrecision] * N[(y0 * y2), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, -1.75e-44], t$95$1, If[LessEqual[y4, 2.95e+41], N[(c * N[(x * N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, 5.5e+161], N[(a * N[(N[(x * y), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]

Derivation

1. Split input into 4 regimes

2. if y4 < -6.0000000000000003e131 or -2.5e12 < y4 < -1.7499999999999999e-44 or 5.5000000000000005e161 < y4

   1. Initial program 21.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 39.2%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 39.2%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 39.2%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 39.2%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 39.2%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 39.2%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in t around inf 41.4%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   6. Taylor expanded in b around inf 38.1%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 38.1%

         \[\leadsto b \cdot \color{blue}{\left(\left(t \cdot y4\right) \cdot j\right)} \]

   8. Simplified 38.1%

      \[\leadsto \color{blue}{b \cdot \left(\left(t \cdot y4\right) \cdot j\right)} \]

   if -6.0000000000000003e131 < y4 < -2.5e12

   1. Initial program 37.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in c around inf 54.8%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in x around inf 34.5%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 38.4%

         \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)} \]

      2. +-commutative 38.4%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 + -1 \cdot \left(i \cdot y\right)\right)} \]

      3. mul-1-neg 38.4%

         \[\leadsto \left(c \cdot x\right) \cdot \left(y0 \cdot y2 + \color{blue}{\left(-i \cdot y\right)}\right) \]

      4. unsub-neg 38.4%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 - i \cdot y\right)} \]

   5. Simplified 38.4%

      \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(y0 \cdot y2 - i \cdot y\right)} \]

   6. Taylor expanded in y0 around inf 30.3%

      \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2\right)} \]
   7. Step-by-step derivation

      1. *-commutative 30.3%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y2 \cdot y0\right)} \]

   8. Simplified 30.3%

      \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y2 \cdot y0\right)} \]

   if -1.7499999999999999e-44 < y4 < 2.95e41

   1. Initial program 31.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in c around inf 39.3%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in x around inf 37.2%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 33.0%

         \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)} \]

      2. +-commutative 33.0%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 + -1 \cdot \left(i \cdot y\right)\right)} \]

      3. mul-1-neg 33.0%

         \[\leadsto \left(c \cdot x\right) \cdot \left(y0 \cdot y2 + \color{blue}{\left(-i \cdot y\right)}\right) \]

      4. unsub-neg 33.0%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 - i \cdot y\right)} \]

   5. Simplified 33.0%

      \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(y0 \cdot y2 - i \cdot y\right)} \]

   6. Taylor expanded in y0 around inf 25.5%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 25.5%

         \[\leadsto c \cdot \left(x \cdot \color{blue}{\left(y2 \cdot y0\right)}\right) \]

   8. Simplified 25.5%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y2 \cdot y0\right)\right)} \]

   if 2.95e41 < y4 < 5.5000000000000005e161

   1. Initial program 36.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 50.3%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 43.4%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   4. Taylor expanded in x around inf 33.4%

      \[\leadsto a \cdot \color{blue}{\left(b \cdot \left(x \cdot y\right)\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 31.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y4 \leq -6 \cdot 10^{+131}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{elif}\;y4 \leq -2500000000000:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y0 \cdot y2\right)\\ \mathbf{elif}\;y4 \leq -1.75 \cdot 10^{-44}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{elif}\;y4 \leq 2.95 \cdot 10^{+41}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y4 \leq 5.5 \cdot 10^{+161}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \end{array} \]

Alternative 30: 19.9% accurate, 5.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y2 \leq -1.15 \cdot 10^{+123}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y2 \leq -5.8 \cdot 10^{-181}:\\ \;\;\;\;a \cdot \left(b \cdot \left(t \cdot \left(-z\right)\right)\right)\\ \mathbf{elif}\;y2 \leq 9.5 \cdot 10^{-56}:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y \cdot \left(-i\right)\right)\\ \mathbf{elif}\;y2 \leq 6.6 \cdot 10^{-14}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{elif}\;y2 \leq 5.8 \cdot 10^{+17}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(b \cdot \left(t \cdot y4\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= y2 -1.15e+123)
   (* c (* x (* y0 y2)))
   (if (<= y2 -5.8e-181)
     (* a (* b (* t (- z))))
     (if (<= y2 9.5e-56)
       (* (* x c) (* y (- i)))
       (if (<= y2 6.6e-14)
         (* b (* j (* t y4)))
         (if (<= y2 5.8e+17) (* a (* (* x y) b)) (* j (* b (* t 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 (y2 <= -1.15e+123) {
		tmp = c * (x * (y0 * y2));
	} else if (y2 <= -5.8e-181) {
		tmp = a * (b * (t * -z));
	} else if (y2 <= 9.5e-56) {
		tmp = (x * c) * (y * -i);
	} else if (y2 <= 6.6e-14) {
		tmp = b * (j * (t * y4));
	} else if (y2 <= 5.8e+17) {
		tmp = a * ((x * y) * b);
	} else {
		tmp = j * (b * (t * 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 (y2 <= (-1.15d+123)) then
        tmp = c * (x * (y0 * y2))
    else if (y2 <= (-5.8d-181)) then
        tmp = a * (b * (t * -z))
    else if (y2 <= 9.5d-56) then
        tmp = (x * c) * (y * -i)
    else if (y2 <= 6.6d-14) then
        tmp = b * (j * (t * y4))
    else if (y2 <= 5.8d+17) then
        tmp = a * ((x * y) * b)
    else
        tmp = j * (b * (t * 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 (y2 <= -1.15e+123) {
		tmp = c * (x * (y0 * y2));
	} else if (y2 <= -5.8e-181) {
		tmp = a * (b * (t * -z));
	} else if (y2 <= 9.5e-56) {
		tmp = (x * c) * (y * -i);
	} else if (y2 <= 6.6e-14) {
		tmp = b * (j * (t * y4));
	} else if (y2 <= 5.8e+17) {
		tmp = a * ((x * y) * b);
	} else {
		tmp = j * (b * (t * 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 y2 <= -1.15e+123:
		tmp = c * (x * (y0 * y2))
	elif y2 <= -5.8e-181:
		tmp = a * (b * (t * -z))
	elif y2 <= 9.5e-56:
		tmp = (x * c) * (y * -i)
	elif y2 <= 6.6e-14:
		tmp = b * (j * (t * y4))
	elif y2 <= 5.8e+17:
		tmp = a * ((x * y) * b)
	else:
		tmp = j * (b * (t * 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 (y2 <= -1.15e+123)
		tmp = Float64(c * Float64(x * Float64(y0 * y2)));
	elseif (y2 <= -5.8e-181)
		tmp = Float64(a * Float64(b * Float64(t * Float64(-z))));
	elseif (y2 <= 9.5e-56)
		tmp = Float64(Float64(x * c) * Float64(y * Float64(-i)));
	elseif (y2 <= 6.6e-14)
		tmp = Float64(b * Float64(j * Float64(t * y4)));
	elseif (y2 <= 5.8e+17)
		tmp = Float64(a * Float64(Float64(x * y) * b));
	else
		tmp = Float64(j * Float64(b * Float64(t * 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 (y2 <= -1.15e+123)
		tmp = c * (x * (y0 * y2));
	elseif (y2 <= -5.8e-181)
		tmp = a * (b * (t * -z));
	elseif (y2 <= 9.5e-56)
		tmp = (x * c) * (y * -i);
	elseif (y2 <= 6.6e-14)
		tmp = b * (j * (t * y4));
	elseif (y2 <= 5.8e+17)
		tmp = a * ((x * y) * b);
	else
		tmp = j * (b * (t * 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[y2, -1.15e+123], N[(c * N[(x * N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, -5.8e-181], N[(a * N[(b * N[(t * (-z)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 9.5e-56], N[(N[(x * c), $MachinePrecision] * N[(y * (-i)), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 6.6e-14], N[(b * N[(j * N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y2, 5.8e+17], N[(a * N[(N[(x * y), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision], N[(j * N[(b * N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

1. Split input into 6 regimes

2. if y2 < -1.14999999999999995e123

   1. Initial program 20.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in c around inf 50.0%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in x around inf 50.7%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 40.8%

         \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)} \]

      2. +-commutative 40.8%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 + -1 \cdot \left(i \cdot y\right)\right)} \]

      3. mul-1-neg 40.8%

         \[\leadsto \left(c \cdot x\right) \cdot \left(y0 \cdot y2 + \color{blue}{\left(-i \cdot y\right)}\right) \]

      4. unsub-neg 40.8%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 - i \cdot y\right)} \]

   5. Simplified 40.8%

      \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(y0 \cdot y2 - i \cdot y\right)} \]

   6. Taylor expanded in y0 around inf 53.1%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 53.1%

         \[\leadsto c \cdot \left(x \cdot \color{blue}{\left(y2 \cdot y0\right)}\right) \]

   8. Simplified 53.1%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y2 \cdot y0\right)\right)} \]

   if -1.14999999999999995e123 < y2 < -5.7999999999999996e-181

   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. Taylor expanded in b around inf 33.2%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 33.8%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   4. Taylor expanded in x around 0 29.0%

      \[\leadsto a \cdot \left(b \cdot \color{blue}{\left(-1 \cdot \left(t \cdot z\right)\right)}\right) \]
   5. Step-by-step derivation

      1. neg-mul-1 29.0%

         \[\leadsto a \cdot \left(b \cdot \color{blue}{\left(-t \cdot z\right)}\right) \]

      2. distribute-lft-neg-in 29.0%

         \[\leadsto a \cdot \left(b \cdot \color{blue}{\left(\left(-t\right) \cdot z\right)}\right) \]

      3. *-commutative 29.0%

         \[\leadsto a \cdot \left(b \cdot \color{blue}{\left(z \cdot \left(-t\right)\right)}\right) \]

   6. Simplified 29.0%

      \[\leadsto a \cdot \left(b \cdot \color{blue}{\left(z \cdot \left(-t\right)\right)}\right) \]

   if -5.7999999999999996e-181 < y2 < 9.4999999999999991e-56

   1. Initial program 39.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in c around inf 42.6%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in x around inf 25.7%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 28.2%

         \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)} \]

      2. +-commutative 28.2%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 + -1 \cdot \left(i \cdot y\right)\right)} \]

      3. mul-1-neg 28.2%

         \[\leadsto \left(c \cdot x\right) \cdot \left(y0 \cdot y2 + \color{blue}{\left(-i \cdot y\right)}\right) \]

      4. unsub-neg 28.2%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 - i \cdot y\right)} \]

   5. Simplified 28.2%

      \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(y0 \cdot y2 - i \cdot y\right)} \]

   6. Taylor expanded in y0 around 0 29.6%

      \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(-1 \cdot \left(i \cdot y\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 29.6%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(-i \cdot y\right)} \]

      2. distribute-lft-neg-out 29.6%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(\left(-i\right) \cdot y\right)} \]

      3. *-commutative 29.6%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y \cdot \left(-i\right)\right)} \]

   8. Simplified 29.6%

      \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y \cdot \left(-i\right)\right)} \]

   if 9.4999999999999991e-56 < y2 < 6.5999999999999996e-14

   1. Initial program 50.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 50.3%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 50.3%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 50.3%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 50.3%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 50.3%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 50.3%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in t around inf 44.4%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   6. Taylor expanded in b around inf 51.0%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 51.0%

         \[\leadsto b \cdot \color{blue}{\left(\left(t \cdot y4\right) \cdot j\right)} \]

   8. Simplified 51.0%

      \[\leadsto \color{blue}{b \cdot \left(\left(t \cdot y4\right) \cdot j\right)} \]

   if 6.5999999999999996e-14 < y2 < 5.8e17

   1. Initial program 10.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 40.1%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 60.4%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   4. Taylor expanded in x around inf 60.5%

      \[\leadsto a \cdot \color{blue}{\left(b \cdot \left(x \cdot y\right)\right)} \]

   if 5.8e17 < y2

   1. Initial program 26.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 40.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 40.8%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 40.8%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 40.8%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 40.8%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 40.8%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in t around inf 26.7%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   6. Taylor expanded in b around inf 27.9%

      \[\leadsto j \cdot \color{blue}{\left(b \cdot \left(t \cdot y4\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 27.9%

         \[\leadsto j \cdot \color{blue}{\left(\left(t \cdot y4\right) \cdot b\right)} \]

   8. Simplified 27.9%

      \[\leadsto j \cdot \color{blue}{\left(\left(t \cdot y4\right) \cdot b\right)} \]
3. Recombined 6 regimes into one program.

4. Final simplification 35.1%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y2 \leq -1.15 \cdot 10^{+123}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y2 \leq -5.8 \cdot 10^{-181}:\\ \;\;\;\;a \cdot \left(b \cdot \left(t \cdot \left(-z\right)\right)\right)\\ \mathbf{elif}\;y2 \leq 9.5 \cdot 10^{-56}:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y \cdot \left(-i\right)\right)\\ \mathbf{elif}\;y2 \leq 6.6 \cdot 10^{-14}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{elif}\;y2 \leq 5.8 \cdot 10^{+17}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{else}:\\ \;\;\;\;j \cdot \left(b \cdot \left(t \cdot y4\right)\right)\\ \end{array} \]

Alternative 31: 30.4% accurate, 5.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := c \cdot \left(t \cdot \left(z \cdot i - y2 \cdot y4\right)\right)\\ \mathbf{if}\;t \leq -2.2 \cdot 10^{-65}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t \leq -2.5 \cdot 10^{-229}:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y \cdot \left(-i\right)\right)\\ \mathbf{elif}\;t \leq 3.6 \cdot 10^{+161}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* c (* t (- (* z i) (* y2 y4))))))
   (if (<= t -2.2e-65)
     t_1
     (if (<= t -2.5e-229)
       (* (* x c) (* y (- i)))
       (if (<= t 3.6e+161) (* b (* x (- (* y a) (* j y0)))) t_1)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = c * (t * ((z * i) - (y2 * y4)));
	double tmp;
	if (t <= -2.2e-65) {
		tmp = t_1;
	} else if (t <= -2.5e-229) {
		tmp = (x * c) * (y * -i);
	} else if (t <= 3.6e+161) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: tmp
    t_1 = c * (t * ((z * i) - (y2 * y4)))
    if (t <= (-2.2d-65)) then
        tmp = t_1
    else if (t <= (-2.5d-229)) then
        tmp = (x * c) * (y * -i)
    else if (t <= 3.6d+161) then
        tmp = b * (x * ((y * a) - (j * y0)))
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = c * (t * ((z * i) - (y2 * y4)));
	double tmp;
	if (t <= -2.2e-65) {
		tmp = t_1;
	} else if (t <= -2.5e-229) {
		tmp = (x * c) * (y * -i);
	} else if (t <= 3.6e+161) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = c * (t * ((z * i) - (y2 * y4)))
	tmp = 0
	if t <= -2.2e-65:
		tmp = t_1
	elif t <= -2.5e-229:
		tmp = (x * c) * (y * -i)
	elif t <= 3.6e+161:
		tmp = b * (x * ((y * a) - (j * y0)))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(c * Float64(t * Float64(Float64(z * i) - Float64(y2 * y4))))
	tmp = 0.0
	if (t <= -2.2e-65)
		tmp = t_1;
	elseif (t <= -2.5e-229)
		tmp = Float64(Float64(x * c) * Float64(y * Float64(-i)));
	elseif (t <= 3.6e+161)
		tmp = Float64(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = c * (t * ((z * i) - (y2 * y4)));
	tmp = 0.0;
	if (t <= -2.2e-65)
		tmp = t_1;
	elseif (t <= -2.5e-229)
		tmp = (x * c) * (y * -i);
	elseif (t <= 3.6e+161)
		tmp = b * (x * ((y * a) - (j * y0)));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(c * N[(t * N[(N[(z * i), $MachinePrecision] - N[(y2 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t, -2.2e-65], t$95$1, If[LessEqual[t, -2.5e-229], N[(N[(x * c), $MachinePrecision] * N[(y * (-i)), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 3.6e+161], N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]

Derivation

1. Split input into 3 regimes

2. if t < -2.20000000000000021e-65 or 3.59999999999999984e161 < t

   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. Taylor expanded in c around inf 38.9%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in t around inf 43.9%

      \[\leadsto \color{blue}{c \cdot \left(t \cdot \left(i \cdot z - y2 \cdot y4\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 43.9%

         \[\leadsto c \cdot \left(t \cdot \left(i \cdot z - \color{blue}{y4 \cdot y2}\right)\right) \]

   5. Simplified 43.9%

      \[\leadsto \color{blue}{c \cdot \left(t \cdot \left(i \cdot z - y4 \cdot y2\right)\right)} \]

   if -2.20000000000000021e-65 < t < -2.50000000000000008e-229

   1. Initial program 40.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in c around inf 50.7%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in x around inf 51.2%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 51.2%

         \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)} \]

      2. +-commutative 51.2%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 + -1 \cdot \left(i \cdot y\right)\right)} \]

      3. mul-1-neg 51.2%

         \[\leadsto \left(c \cdot x\right) \cdot \left(y0 \cdot y2 + \color{blue}{\left(-i \cdot y\right)}\right) \]

      4. unsub-neg 51.2%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 - i \cdot y\right)} \]

   5. Simplified 51.2%

      \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(y0 \cdot y2 - i \cdot y\right)} \]

   6. Taylor expanded in y0 around 0 39.1%

      \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(-1 \cdot \left(i \cdot y\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 39.1%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(-i \cdot y\right)} \]

      2. distribute-lft-neg-out 39.1%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(\left(-i\right) \cdot y\right)} \]

      3. *-commutative 39.1%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y \cdot \left(-i\right)\right)} \]

   8. Simplified 39.1%

      \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y \cdot \left(-i\right)\right)} \]

   if -2.50000000000000008e-229 < t < 3.59999999999999984e161

   1. Initial program 33.6%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 39.5%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in x around inf 34.1%

      \[\leadsto \color{blue}{b \cdot \left(x \cdot \left(a \cdot y - j \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 34.1%

         \[\leadsto b \cdot \left(x \cdot \left(\color{blue}{y \cdot a} - j \cdot y0\right)\right) \]

   5. Simplified 34.1%

      \[\leadsto \color{blue}{b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)} \]
3. Recombined 3 regimes into one program.

4. Final simplification 38.7%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -2.2 \cdot 10^{-65}:\\ \;\;\;\;c \cdot \left(t \cdot \left(z \cdot i - y2 \cdot y4\right)\right)\\ \mathbf{elif}\;t \leq -2.5 \cdot 10^{-229}:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y \cdot \left(-i\right)\right)\\ \mathbf{elif}\;t \leq 3.6 \cdot 10^{+161}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(t \cdot \left(z \cdot i - y2 \cdot y4\right)\right)\\ \end{array} \]

Alternative 32: 28.6% accurate, 5.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y \leq -1.16 \cdot 10^{-121}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y \leq 7.5 \cdot 10^{-73}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq 5.5 \cdot 10^{+164}:\\ \;\;\;\;c \cdot \left(t \cdot \left(z \cdot i - y2 \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= y -1.16e-121)
   (* b (* x (- (* y a) (* j y0))))
   (if (<= y 7.5e-73)
     (* c (* y2 (- (* x y0) (* t y4))))
     (if (<= y 5.5e+164)
       (* c (* t (- (* z i) (* y2 y4))))
       (* c (* y4 (* y y3)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y <= -1.16e-121) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (y <= 7.5e-73) {
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	} else if (y <= 5.5e+164) {
		tmp = c * (t * ((z * i) - (y2 * y4)));
	} else {
		tmp = c * (y4 * (y * y3));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (y <= (-1.16d-121)) then
        tmp = b * (x * ((y * a) - (j * y0)))
    else if (y <= 7.5d-73) then
        tmp = c * (y2 * ((x * y0) - (t * y4)))
    else if (y <= 5.5d+164) then
        tmp = c * (t * ((z * i) - (y2 * y4)))
    else
        tmp = c * (y4 * (y * y3))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (y <= -1.16e-121) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (y <= 7.5e-73) {
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	} else if (y <= 5.5e+164) {
		tmp = c * (t * ((z * i) - (y2 * y4)));
	} else {
		tmp = c * (y4 * (y * y3));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if y <= -1.16e-121:
		tmp = b * (x * ((y * a) - (j * y0)))
	elif y <= 7.5e-73:
		tmp = c * (y2 * ((x * y0) - (t * y4)))
	elif y <= 5.5e+164:
		tmp = c * (t * ((z * i) - (y2 * y4)))
	else:
		tmp = c * (y4 * (y * y3))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (y <= -1.16e-121)
		tmp = Float64(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))));
	elseif (y <= 7.5e-73)
		tmp = Float64(c * Float64(y2 * Float64(Float64(x * y0) - Float64(t * y4))));
	elseif (y <= 5.5e+164)
		tmp = Float64(c * Float64(t * Float64(Float64(z * i) - Float64(y2 * y4))));
	else
		tmp = Float64(c * Float64(y4 * Float64(y * y3)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (y <= -1.16e-121)
		tmp = b * (x * ((y * a) - (j * y0)));
	elseif (y <= 7.5e-73)
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	elseif (y <= 5.5e+164)
		tmp = c * (t * ((z * i) - (y2 * y4)));
	else
		tmp = c * (y4 * (y * y3));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[y, -1.16e-121], N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 7.5e-73], N[(c * N[(y2 * N[(N[(x * y0), $MachinePrecision] - N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 5.5e+164], N[(c * N[(t * N[(N[(z * i), $MachinePrecision] - N[(y2 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(c * N[(y4 * N[(y * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]

Derivation

1. Split input into 4 regimes

2. if y < -1.1600000000000001e-121

   1. Initial program 32.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 29.1%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in x around inf 37.6%

      \[\leadsto \color{blue}{b \cdot \left(x \cdot \left(a \cdot y - j \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 37.6%

         \[\leadsto b \cdot \left(x \cdot \left(\color{blue}{y \cdot a} - j \cdot y0\right)\right) \]

   5. Simplified 37.6%

      \[\leadsto \color{blue}{b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)} \]

   if -1.1600000000000001e-121 < y < 7.5e-73

   1. Initial program 31.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in c around inf 41.0%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in y2 around inf 35.6%

      \[\leadsto \color{blue}{c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)} \]

   if 7.5e-73 < y < 5.4999999999999998e164

   1. Initial program 29.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in c around inf 46.4%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in t around inf 47.0%

      \[\leadsto \color{blue}{c \cdot \left(t \cdot \left(i \cdot z - y2 \cdot y4\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 47.0%

         \[\leadsto c \cdot \left(t \cdot \left(i \cdot z - \color{blue}{y4 \cdot y2}\right)\right) \]

   5. Simplified 47.0%

      \[\leadsto \color{blue}{c \cdot \left(t \cdot \left(i \cdot z - y4 \cdot y2\right)\right)} \]

   if 5.4999999999999998e164 < y

   1. Initial program 8.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y3 around -inf 52.5%

      \[\leadsto \color{blue}{-1 \cdot \left(y3 \cdot \left(\left(j \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + z \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - y \cdot \left(c \cdot y4 - a \cdot y5\right)\right)\right)} \]

   3. Taylor expanded in y around inf 72.8%

      \[\leadsto -1 \cdot \color{blue}{\left(y \cdot \left(y3 \cdot \left(a \cdot y5 - c \cdot y4\right)\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 72.8%

         \[\leadsto -1 \cdot \color{blue}{\left(\left(y \cdot y3\right) \cdot \left(a \cdot y5 - c \cdot y4\right)\right)} \]

      2. *-commutative 72.8%

         \[\leadsto -1 \cdot \left(\color{blue}{\left(y3 \cdot y\right)} \cdot \left(a \cdot y5 - c \cdot y4\right)\right) \]

      3. *-commutative 72.8%

         \[\leadsto -1 \cdot \left(\left(y3 \cdot y\right) \cdot \left(\color{blue}{y5 \cdot a} - c \cdot y4\right)\right) \]

      4. *-commutative 72.8%

         \[\leadsto -1 \cdot \left(\left(y3 \cdot y\right) \cdot \left(y5 \cdot a - \color{blue}{y4 \cdot c}\right)\right) \]

   5. Simplified 72.8%

      \[\leadsto -1 \cdot \color{blue}{\left(\left(y3 \cdot y\right) \cdot \left(y5 \cdot a - y4 \cdot c\right)\right)} \]

   6. Taylor expanded in y5 around 0 49.0%

      \[\leadsto -1 \cdot \left(\left(y3 \cdot y\right) \cdot \color{blue}{\left(-1 \cdot \left(c \cdot y4\right)\right)}\right) \]
   7. Step-by-step derivation

      1. mul-1-neg 49.0%

         \[\leadsto -1 \cdot \left(\left(y3 \cdot y\right) \cdot \color{blue}{\left(-c \cdot y4\right)}\right) \]

      2. distribute-rgt-neg-in 49.0%

         \[\leadsto -1 \cdot \left(\left(y3 \cdot y\right) \cdot \color{blue}{\left(c \cdot \left(-y4\right)\right)}\right) \]

   8. Simplified 49.0%

      \[\leadsto -1 \cdot \left(\left(y3 \cdot y\right) \cdot \color{blue}{\left(c \cdot \left(-y4\right)\right)}\right) \]

   9. Taylor expanded in y3 around 0 53.2%

      \[\leadsto -1 \cdot \color{blue}{\left(-1 \cdot \left(c \cdot \left(y \cdot \left(y3 \cdot y4\right)\right)\right)\right)} \]
   10. Step-by-step derivation

       1. mul-1-neg 53.2%

          \[\leadsto -1 \cdot \color{blue}{\left(-c \cdot \left(y \cdot \left(y3 \cdot y4\right)\right)\right)} \]

       2. *-commutative 53.2%

          \[\leadsto -1 \cdot \left(-\color{blue}{\left(y \cdot \left(y3 \cdot y4\right)\right) \cdot c}\right) \]

       3. distribute-rgt-neg-in 53.2%

          \[\leadsto -1 \cdot \color{blue}{\left(\left(y \cdot \left(y3 \cdot y4\right)\right) \cdot \left(-c\right)\right)} \]

       4. associate-*r* 57.1%

          \[\leadsto -1 \cdot \left(\color{blue}{\left(\left(y \cdot y3\right) \cdot y4\right)} \cdot \left(-c\right)\right) \]

       5. *-commutative 57.1%

          \[\leadsto -1 \cdot \left(\color{blue}{\left(y4 \cdot \left(y \cdot y3\right)\right)} \cdot \left(-c\right)\right) \]

   11. Simplified 57.1%

       \[\leadsto -1 \cdot \color{blue}{\left(\left(y4 \cdot \left(y \cdot y3\right)\right) \cdot \left(-c\right)\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 40.2%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y \leq -1.16 \cdot 10^{-121}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y \leq 7.5 \cdot 10^{-73}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq 5.5 \cdot 10^{+164}:\\ \;\;\;\;c \cdot \left(t \cdot \left(z \cdot i - y2 \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3\right)\right)\\ \end{array} \]

Alternative 33: 29.3% accurate, 5.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y \leq -5.3 \cdot 10^{-121}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y \leq 7 \cdot 10^{-73}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq 1.65 \cdot 10^{+143}:\\ \;\;\;\;c \cdot \left(t \cdot \left(z \cdot i - y2 \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= y -5.3e-121)
   (* b (* x (- (* y a) (* j y0))))
   (if (<= y 7e-73)
     (* c (* y2 (- (* x y0) (* t y4))))
     (if (<= y 1.65e+143)
       (* c (* t (- (* z i) (* y2 y4))))
       (* c (* y4 (- (* y y3) (* t 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 (y <= -5.3e-121) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (y <= 7e-73) {
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	} else if (y <= 1.65e+143) {
		tmp = c * (t * ((z * i) - (y2 * y4)));
	} else {
		tmp = c * (y4 * ((y * y3) - (t * 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 (y <= (-5.3d-121)) then
        tmp = b * (x * ((y * a) - (j * y0)))
    else if (y <= 7d-73) then
        tmp = c * (y2 * ((x * y0) - (t * y4)))
    else if (y <= 1.65d+143) then
        tmp = c * (t * ((z * i) - (y2 * y4)))
    else
        tmp = c * (y4 * ((y * y3) - (t * 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 (y <= -5.3e-121) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else if (y <= 7e-73) {
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	} else if (y <= 1.65e+143) {
		tmp = c * (t * ((z * i) - (y2 * y4)));
	} else {
		tmp = c * (y4 * ((y * y3) - (t * 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 y <= -5.3e-121:
		tmp = b * (x * ((y * a) - (j * y0)))
	elif y <= 7e-73:
		tmp = c * (y2 * ((x * y0) - (t * y4)))
	elif y <= 1.65e+143:
		tmp = c * (t * ((z * i) - (y2 * y4)))
	else:
		tmp = c * (y4 * ((y * y3) - (t * 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 (y <= -5.3e-121)
		tmp = Float64(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))));
	elseif (y <= 7e-73)
		tmp = Float64(c * Float64(y2 * Float64(Float64(x * y0) - Float64(t * y4))));
	elseif (y <= 1.65e+143)
		tmp = Float64(c * Float64(t * Float64(Float64(z * i) - Float64(y2 * y4))));
	else
		tmp = Float64(c * Float64(y4 * Float64(Float64(y * y3) - Float64(t * 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 (y <= -5.3e-121)
		tmp = b * (x * ((y * a) - (j * y0)));
	elseif (y <= 7e-73)
		tmp = c * (y2 * ((x * y0) - (t * y4)));
	elseif (y <= 1.65e+143)
		tmp = c * (t * ((z * i) - (y2 * y4)));
	else
		tmp = c * (y4 * ((y * y3) - (t * 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[y, -5.3e-121], N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 7e-73], N[(c * N[(y2 * N[(N[(x * y0), $MachinePrecision] - N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y, 1.65e+143], N[(c * N[(t * N[(N[(z * i), $MachinePrecision] - N[(y2 * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(c * N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]

Derivation

1. Split input into 4 regimes

2. if y < -5.2999999999999996e-121

   1. Initial program 32.2%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 29.1%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in x around inf 37.6%

      \[\leadsto \color{blue}{b \cdot \left(x \cdot \left(a \cdot y - j \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 37.6%

         \[\leadsto b \cdot \left(x \cdot \left(\color{blue}{y \cdot a} - j \cdot y0\right)\right) \]

   5. Simplified 37.6%

      \[\leadsto \color{blue}{b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)} \]

   if -5.2999999999999996e-121 < y < 6.9999999999999995e-73

   1. Initial program 31.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in c around inf 41.0%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in y2 around inf 35.6%

      \[\leadsto \color{blue}{c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)} \]

   if 6.9999999999999995e-73 < y < 1.65e143

   1. Initial program 28.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in c around inf 50.1%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in t around inf 48.1%

      \[\leadsto \color{blue}{c \cdot \left(t \cdot \left(i \cdot z - y2 \cdot y4\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 48.1%

         \[\leadsto c \cdot \left(t \cdot \left(i \cdot z - \color{blue}{y4 \cdot y2}\right)\right) \]

   5. Simplified 48.1%

      \[\leadsto \color{blue}{c \cdot \left(t \cdot \left(i \cdot z - y4 \cdot y2\right)\right)} \]

   if 1.65e143 < y

   1. Initial program 10.7%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf 46.9%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in c around inf 61.5%

      \[\leadsto \color{blue}{c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 61.5%

         \[\leadsto c \cdot \left(y4 \cdot \left(\color{blue}{y3 \cdot y} - t \cdot y2\right)\right) \]

   5. Simplified 61.5%

      \[\leadsto \color{blue}{c \cdot \left(y4 \cdot \left(y3 \cdot y - t \cdot y2\right)\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 40.9%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y \leq -5.3 \cdot 10^{-121}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{elif}\;y \leq 7 \cdot 10^{-73}:\\ \;\;\;\;c \cdot \left(y2 \cdot \left(x \cdot y0 - t \cdot y4\right)\right)\\ \mathbf{elif}\;y \leq 1.65 \cdot 10^{+143}:\\ \;\;\;\;c \cdot \left(t \cdot \left(z \cdot i - y2 \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \end{array} \]

Alternative 34: 30.2% accurate, 5.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;t \leq -4 \cdot 10^{-61}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq 4.3 \cdot 10^{-240}:\\ \;\;\;\;c \cdot \left(y \cdot \left(y3 \cdot y4 - x \cdot i\right)\right)\\ \mathbf{elif}\;t \leq 6.2 \cdot 10^{+17}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= t -4e-61)
   (* c (* y4 (- (* y y3) (* t y2))))
   (if (<= t 4.3e-240)
     (* c (* y (- (* y3 y4) (* x i))))
     (if (<= t 6.2e+17)
       (* b (* x (- (* y a) (* j y0))))
       (* c (* z (- (* t i) (* y0 y3))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (t <= -4e-61) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (t <= 4.3e-240) {
		tmp = c * (y * ((y3 * y4) - (x * i)));
	} else if (t <= 6.2e+17) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else {
		tmp = c * (z * ((t * i) - (y0 * y3)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if (t <= (-4d-61)) then
        tmp = c * (y4 * ((y * y3) - (t * y2)))
    else if (t <= 4.3d-240) then
        tmp = c * (y * ((y3 * y4) - (x * i)))
    else if (t <= 6.2d+17) then
        tmp = b * (x * ((y * a) - (j * y0)))
    else
        tmp = c * (z * ((t * i) - (y0 * y3)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (t <= -4e-61) {
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	} else if (t <= 4.3e-240) {
		tmp = c * (y * ((y3 * y4) - (x * i)));
	} else if (t <= 6.2e+17) {
		tmp = b * (x * ((y * a) - (j * y0)));
	} else {
		tmp = c * (z * ((t * i) - (y0 * y3)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if t <= -4e-61:
		tmp = c * (y4 * ((y * y3) - (t * y2)))
	elif t <= 4.3e-240:
		tmp = c * (y * ((y3 * y4) - (x * i)))
	elif t <= 6.2e+17:
		tmp = b * (x * ((y * a) - (j * y0)))
	else:
		tmp = c * (z * ((t * i) - (y0 * y3)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if (t <= -4e-61)
		tmp = Float64(c * Float64(y4 * Float64(Float64(y * y3) - Float64(t * y2))));
	elseif (t <= 4.3e-240)
		tmp = Float64(c * Float64(y * Float64(Float64(y3 * y4) - Float64(x * i))));
	elseif (t <= 6.2e+17)
		tmp = Float64(b * Float64(x * Float64(Float64(y * a) - Float64(j * y0))));
	else
		tmp = Float64(c * Float64(z * Float64(Float64(t * i) - Float64(y0 * y3))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if (t <= -4e-61)
		tmp = c * (y4 * ((y * y3) - (t * y2)));
	elseif (t <= 4.3e-240)
		tmp = c * (y * ((y3 * y4) - (x * i)));
	elseif (t <= 6.2e+17)
		tmp = b * (x * ((y * a) - (j * y0)));
	else
		tmp = c * (z * ((t * i) - (y0 * y3)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[LessEqual[t, -4e-61], N[(c * N[(y4 * N[(N[(y * y3), $MachinePrecision] - N[(t * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 4.3e-240], N[(c * N[(y * N[(N[(y3 * y4), $MachinePrecision] - N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 6.2e+17], N[(b * N[(x * N[(N[(y * a), $MachinePrecision] - N[(j * y0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(c * N[(z * N[(N[(t * i), $MachinePrecision] - N[(y0 * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]

Derivation

1. Split input into 4 regimes

2. if t < -4.0000000000000002e-61

   1. Initial program 21.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y4 around inf 43.0%

      \[\leadsto \color{blue}{y4 \cdot \left(\left(b \cdot \left(j \cdot t - k \cdot y\right) + y1 \cdot \left(k \cdot y2 - j \cdot y3\right)\right) - c \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in c around inf 42.4%

      \[\leadsto \color{blue}{c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 42.4%

         \[\leadsto c \cdot \left(y4 \cdot \left(\color{blue}{y3 \cdot y} - t \cdot y2\right)\right) \]

   5. Simplified 42.4%

      \[\leadsto \color{blue}{c \cdot \left(y4 \cdot \left(y3 \cdot y - t \cdot y2\right)\right)} \]

   if -4.0000000000000002e-61 < t < 4.30000000000000013e-240

   1. Initial program 40.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in c around inf 47.5%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in y around inf 42.6%

      \[\leadsto c \cdot \color{blue}{\left(y \cdot \left(-1 \cdot \left(i \cdot x\right) - -1 \cdot \left(y3 \cdot y4\right)\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 42.6%

         \[\leadsto c \cdot \color{blue}{\left(\left(-1 \cdot \left(i \cdot x\right) - -1 \cdot \left(y3 \cdot y4\right)\right) \cdot y\right)} \]

      2. cancel-sign-sub-inv 42.6%

         \[\leadsto c \cdot \left(\color{blue}{\left(-1 \cdot \left(i \cdot x\right) + \left(--1\right) \cdot \left(y3 \cdot y4\right)\right)} \cdot y\right) \]

      3. metadata-eval 42.6%

         \[\leadsto c \cdot \left(\left(-1 \cdot \left(i \cdot x\right) + \color{blue}{1} \cdot \left(y3 \cdot y4\right)\right) \cdot y\right) \]

      4. *-lft-identity 42.6%

         \[\leadsto c \cdot \left(\left(-1 \cdot \left(i \cdot x\right) + \color{blue}{y3 \cdot y4}\right) \cdot y\right) \]

      5. +-commutative 42.6%

         \[\leadsto c \cdot \left(\color{blue}{\left(y3 \cdot y4 + -1 \cdot \left(i \cdot x\right)\right)} \cdot y\right) \]

      6. mul-1-neg 42.6%

         \[\leadsto c \cdot \left(\left(y3 \cdot y4 + \color{blue}{\left(-i \cdot x\right)}\right) \cdot y\right) \]

      7. unsub-neg 42.6%

         \[\leadsto c \cdot \left(\color{blue}{\left(y3 \cdot y4 - i \cdot x\right)} \cdot y\right) \]

      8. *-commutative 42.6%

         \[\leadsto c \cdot \left(\left(\color{blue}{y4 \cdot y3} - i \cdot x\right) \cdot y\right) \]

   5. Simplified 42.6%

      \[\leadsto c \cdot \color{blue}{\left(\left(y4 \cdot y3 - i \cdot x\right) \cdot y\right)} \]

   if 4.30000000000000013e-240 < t < 6.2e17

   1. Initial program 29.9%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 38.2%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in x around inf 34.6%

      \[\leadsto \color{blue}{b \cdot \left(x \cdot \left(a \cdot y - j \cdot y0\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 34.6%

         \[\leadsto b \cdot \left(x \cdot \left(\color{blue}{y \cdot a} - j \cdot y0\right)\right) \]

   5. Simplified 34.6%

      \[\leadsto \color{blue}{b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)} \]

   if 6.2e17 < t

   1. Initial program 27.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in c around inf 36.5%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in z around inf 42.7%

      \[\leadsto c \cdot \color{blue}{\left(z \cdot \left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right)\right)} \]
   4. Step-by-step derivation

      1. *-commutative 42.7%

         \[\leadsto c \cdot \color{blue}{\left(\left(-1 \cdot \left(y0 \cdot y3\right) + i \cdot t\right) \cdot z\right)} \]

      2. +-commutative 42.7%

         \[\leadsto c \cdot \left(\color{blue}{\left(i \cdot t + -1 \cdot \left(y0 \cdot y3\right)\right)} \cdot z\right) \]

      3. mul-1-neg 42.7%

         \[\leadsto c \cdot \left(\left(i \cdot t + \color{blue}{\left(-y0 \cdot y3\right)}\right) \cdot z\right) \]

      4. sub-neg 42.7%

         \[\leadsto c \cdot \left(\color{blue}{\left(i \cdot t - y0 \cdot y3\right)} \cdot z\right) \]

      5. *-commutative 42.7%

         \[\leadsto c \cdot \left(\left(\color{blue}{t \cdot i} - y0 \cdot y3\right) \cdot z\right) \]

   5. Simplified 42.7%

      \[\leadsto c \cdot \color{blue}{\left(\left(t \cdot i - y0 \cdot y3\right) \cdot z\right)} \]
3. Recombined 4 regimes into one program.

4. Final simplification 40.7%

   \[\leadsto \begin{array}{l} \mathbf{if}\;t \leq -4 \cdot 10^{-61}:\\ \;\;\;\;c \cdot \left(y4 \cdot \left(y \cdot y3 - t \cdot y2\right)\right)\\ \mathbf{elif}\;t \leq 4.3 \cdot 10^{-240}:\\ \;\;\;\;c \cdot \left(y \cdot \left(y3 \cdot y4 - x \cdot i\right)\right)\\ \mathbf{elif}\;t \leq 6.2 \cdot 10^{+17}:\\ \;\;\;\;b \cdot \left(x \cdot \left(y \cdot a - j \cdot y0\right)\right)\\ \mathbf{else}:\\ \;\;\;\;c \cdot \left(z \cdot \left(t \cdot i - y0 \cdot y3\right)\right)\\ \end{array} \]

Alternative 35: 22.0% accurate, 5.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;b \leq -4 \cdot 10^{-28}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4\right)\right)\\ \mathbf{elif}\;b \leq -5.5 \cdot 10^{-279}:\\ \;\;\;\;y2 \cdot \left(a \cdot \left(x \cdot \left(-y1\right)\right)\right)\\ \mathbf{elif}\;b \leq 2.05 \cdot 10^{-10}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(t \cdot \left(-i\right)\right)\right)\\ \mathbf{elif}\;b \leq 1.15 \cdot 10^{+72}:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y0 \cdot y2\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(b \cdot \left(t \cdot \left(-z\right)\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= b -4e-28)
   (* j (* t (* b y4)))
   (if (<= b -5.5e-279)
     (* y2 (* a (* x (- y1))))
     (if (<= b 2.05e-10)
       (* j (* y5 (* t (- i))))
       (if (<= b 1.15e+72) (* (* x c) (* y0 y2)) (* a (* b (* t (- z)))))))))

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 <= -4e-28) {
		tmp = j * (t * (b * y4));
	} else if (b <= -5.5e-279) {
		tmp = y2 * (a * (x * -y1));
	} else if (b <= 2.05e-10) {
		tmp = j * (y5 * (t * -i));
	} else if (b <= 1.15e+72) {
		tmp = (x * c) * (y0 * y2);
	} else {
		tmp = a * (b * (t * -z));
	}
	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 <= (-4d-28)) then
        tmp = j * (t * (b * y4))
    else if (b <= (-5.5d-279)) then
        tmp = y2 * (a * (x * -y1))
    else if (b <= 2.05d-10) then
        tmp = j * (y5 * (t * -i))
    else if (b <= 1.15d+72) then
        tmp = (x * c) * (y0 * y2)
    else
        tmp = a * (b * (t * -z))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (b <= -4e-28) {
		tmp = j * (t * (b * y4));
	} else if (b <= -5.5e-279) {
		tmp = y2 * (a * (x * -y1));
	} else if (b <= 2.05e-10) {
		tmp = j * (y5 * (t * -i));
	} else if (b <= 1.15e+72) {
		tmp = (x * c) * (y0 * y2);
	} else {
		tmp = a * (b * (t * -z));
	}
	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 <= -4e-28:
		tmp = j * (t * (b * y4))
	elif b <= -5.5e-279:
		tmp = y2 * (a * (x * -y1))
	elif b <= 2.05e-10:
		tmp = j * (y5 * (t * -i))
	elif b <= 1.15e+72:
		tmp = (x * c) * (y0 * y2)
	else:
		tmp = a * (b * (t * -z))
	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 <= -4e-28)
		tmp = Float64(j * Float64(t * Float64(b * y4)));
	elseif (b <= -5.5e-279)
		tmp = Float64(y2 * Float64(a * Float64(x * Float64(-y1))));
	elseif (b <= 2.05e-10)
		tmp = Float64(j * Float64(y5 * Float64(t * Float64(-i))));
	elseif (b <= 1.15e+72)
		tmp = Float64(Float64(x * c) * Float64(y0 * y2));
	else
		tmp = Float64(a * Float64(b * Float64(t * Float64(-z))));
	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 <= -4e-28)
		tmp = j * (t * (b * y4));
	elseif (b <= -5.5e-279)
		tmp = y2 * (a * (x * -y1));
	elseif (b <= 2.05e-10)
		tmp = j * (y5 * (t * -i));
	elseif (b <= 1.15e+72)
		tmp = (x * c) * (y0 * y2);
	else
		tmp = a * (b * (t * -z));
	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, -4e-28], N[(j * N[(t * N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[b, -5.5e-279], N[(y2 * N[(a * N[(x * (-y1)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[b, 2.05e-10], N[(j * N[(y5 * N[(t * (-i)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[b, 1.15e+72], N[(N[(x * c), $MachinePrecision] * N[(y0 * y2), $MachinePrecision]), $MachinePrecision], N[(a * N[(b * N[(t * (-z)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

1. Split input into 5 regimes

2. if b < -3.99999999999999988e-28

   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. Taylor expanded in j around inf 40.9%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 40.9%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 40.9%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 40.9%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 40.9%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 40.9%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in t around inf 34.0%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   6. Taylor expanded in b around inf 34.0%

      \[\leadsto j \cdot \left(t \cdot \color{blue}{\left(b \cdot y4\right)}\right) \]
   7. Step-by-step derivation

      1. *-commutative 34.0%

         \[\leadsto j \cdot \left(t \cdot \color{blue}{\left(y4 \cdot b\right)}\right) \]

   8. Simplified 34.0%

      \[\leadsto j \cdot \left(t \cdot \color{blue}{\left(y4 \cdot b\right)}\right) \]

   if -3.99999999999999988e-28 < b < -5.5000000000000002e-279

   1. Initial program 23.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y2 around inf 51.7%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   3. Taylor expanded in x around inf 36.4%

      \[\leadsto y2 \cdot \color{blue}{\left(x \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   4. Taylor expanded in c around 0 26.3%

      \[\leadsto y2 \cdot \color{blue}{\left(-1 \cdot \left(a \cdot \left(x \cdot y1\right)\right)\right)} \]
   5. Step-by-step derivation

      1. mul-1-neg 26.3%

         \[\leadsto y2 \cdot \color{blue}{\left(-a \cdot \left(x \cdot y1\right)\right)} \]

      2. distribute-rgt-neg-in 26.3%

         \[\leadsto y2 \cdot \color{blue}{\left(a \cdot \left(-x \cdot y1\right)\right)} \]

      3. distribute-rgt-neg-in 26.3%

         \[\leadsto y2 \cdot \left(a \cdot \color{blue}{\left(x \cdot \left(-y1\right)\right)}\right) \]

   6. Simplified 26.3%

      \[\leadsto y2 \cdot \color{blue}{\left(a \cdot \left(x \cdot \left(-y1\right)\right)\right)} \]

   if -5.5000000000000002e-279 < b < 2.0499999999999999e-10

   1. Initial program 38.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 45.3%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 45.3%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 45.3%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 45.3%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 45.3%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 45.3%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in t around inf 30.3%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   6. Taylor expanded in b around 0 28.5%

      \[\leadsto j \cdot \color{blue}{\left(-1 \cdot \left(i \cdot \left(t \cdot y5\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 28.5%

         \[\leadsto j \cdot \color{blue}{\left(-i \cdot \left(t \cdot y5\right)\right)} \]

      2. associate-*r* 28.5%

         \[\leadsto j \cdot \left(-\color{blue}{\left(i \cdot t\right) \cdot y5}\right) \]

      3. distribute-rgt-neg-in 28.5%

         \[\leadsto j \cdot \color{blue}{\left(\left(i \cdot t\right) \cdot \left(-y5\right)\right)} \]

   8. Simplified 28.5%

      \[\leadsto j \cdot \color{blue}{\left(\left(i \cdot t\right) \cdot \left(-y5\right)\right)} \]

   if 2.0499999999999999e-10 < b < 1.15e72

   1. Initial program 50.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in c around inf 39.6%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in x around inf 46.1%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 45.7%

         \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)} \]

      2. +-commutative 45.7%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 + -1 \cdot \left(i \cdot y\right)\right)} \]

      3. mul-1-neg 45.7%

         \[\leadsto \left(c \cdot x\right) \cdot \left(y0 \cdot y2 + \color{blue}{\left(-i \cdot y\right)}\right) \]

      4. unsub-neg 45.7%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 - i \cdot y\right)} \]

   5. Simplified 45.7%

      \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(y0 \cdot y2 - i \cdot y\right)} \]

   6. Taylor expanded in y0 around inf 45.7%

      \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2\right)} \]
   7. Step-by-step derivation

      1. *-commutative 45.7%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y2 \cdot y0\right)} \]

   8. Simplified 45.7%

      \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y2 \cdot y0\right)} \]

   if 1.15e72 < b

   1. Initial program 27.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 57.1%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 36.7%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   4. Taylor expanded in x around 0 29.0%

      \[\leadsto a \cdot \left(b \cdot \color{blue}{\left(-1 \cdot \left(t \cdot z\right)\right)}\right) \]
   5. Step-by-step derivation

      1. neg-mul-1 29.0%

         \[\leadsto a \cdot \left(b \cdot \color{blue}{\left(-t \cdot z\right)}\right) \]

      2. distribute-lft-neg-in 29.0%

         \[\leadsto a \cdot \left(b \cdot \color{blue}{\left(\left(-t\right) \cdot z\right)}\right) \]

      3. *-commutative 29.0%

         \[\leadsto a \cdot \left(b \cdot \color{blue}{\left(z \cdot \left(-t\right)\right)}\right) \]

   6. Simplified 29.0%

      \[\leadsto a \cdot \left(b \cdot \color{blue}{\left(z \cdot \left(-t\right)\right)}\right) \]
3. Recombined 5 regimes into one program.

4. Final simplification 30.8%

   \[\leadsto \begin{array}{l} \mathbf{if}\;b \leq -4 \cdot 10^{-28}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4\right)\right)\\ \mathbf{elif}\;b \leq -5.5 \cdot 10^{-279}:\\ \;\;\;\;y2 \cdot \left(a \cdot \left(x \cdot \left(-y1\right)\right)\right)\\ \mathbf{elif}\;b \leq 2.05 \cdot 10^{-10}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(t \cdot \left(-i\right)\right)\right)\\ \mathbf{elif}\;b \leq 1.15 \cdot 10^{+72}:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y0 \cdot y2\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(b \cdot \left(t \cdot \left(-z\right)\right)\right)\\ \end{array} \]

Alternative 36: 22.1% accurate, 5.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;b \leq -5.8 \cdot 10^{-29}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4\right)\right)\\ \mathbf{elif}\;b \leq -8 \cdot 10^{-279}:\\ \;\;\;\;y2 \cdot \left(x \cdot \left(a \cdot \left(-y1\right)\right)\right)\\ \mathbf{elif}\;b \leq 7.5 \cdot 10^{-11}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(t \cdot \left(-i\right)\right)\right)\\ \mathbf{elif}\;b \leq 7.2 \cdot 10^{+74}:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y0 \cdot y2\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(b \cdot \left(t \cdot \left(-z\right)\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (<= b -5.8e-29)
   (* j (* t (* b y4)))
   (if (<= b -8e-279)
     (* y2 (* x (* a (- y1))))
     (if (<= b 7.5e-11)
       (* j (* y5 (* t (- i))))
       (if (<= b 7.2e+74) (* (* x c) (* y0 y2)) (* a (* b (* t (- z)))))))))

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 <= -5.8e-29) {
		tmp = j * (t * (b * y4));
	} else if (b <= -8e-279) {
		tmp = y2 * (x * (a * -y1));
	} else if (b <= 7.5e-11) {
		tmp = j * (y5 * (t * -i));
	} else if (b <= 7.2e+74) {
		tmp = (x * c) * (y0 * y2);
	} else {
		tmp = a * (b * (t * -z));
	}
	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 <= (-5.8d-29)) then
        tmp = j * (t * (b * y4))
    else if (b <= (-8d-279)) then
        tmp = y2 * (x * (a * -y1))
    else if (b <= 7.5d-11) then
        tmp = j * (y5 * (t * -i))
    else if (b <= 7.2d+74) then
        tmp = (x * c) * (y0 * y2)
    else
        tmp = a * (b * (t * -z))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if (b <= -5.8e-29) {
		tmp = j * (t * (b * y4));
	} else if (b <= -8e-279) {
		tmp = y2 * (x * (a * -y1));
	} else if (b <= 7.5e-11) {
		tmp = j * (y5 * (t * -i));
	} else if (b <= 7.2e+74) {
		tmp = (x * c) * (y0 * y2);
	} else {
		tmp = a * (b * (t * -z));
	}
	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 <= -5.8e-29:
		tmp = j * (t * (b * y4))
	elif b <= -8e-279:
		tmp = y2 * (x * (a * -y1))
	elif b <= 7.5e-11:
		tmp = j * (y5 * (t * -i))
	elif b <= 7.2e+74:
		tmp = (x * c) * (y0 * y2)
	else:
		tmp = a * (b * (t * -z))
	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 <= -5.8e-29)
		tmp = Float64(j * Float64(t * Float64(b * y4)));
	elseif (b <= -8e-279)
		tmp = Float64(y2 * Float64(x * Float64(a * Float64(-y1))));
	elseif (b <= 7.5e-11)
		tmp = Float64(j * Float64(y5 * Float64(t * Float64(-i))));
	elseif (b <= 7.2e+74)
		tmp = Float64(Float64(x * c) * Float64(y0 * y2));
	else
		tmp = Float64(a * Float64(b * Float64(t * Float64(-z))));
	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 <= -5.8e-29)
		tmp = j * (t * (b * y4));
	elseif (b <= -8e-279)
		tmp = y2 * (x * (a * -y1));
	elseif (b <= 7.5e-11)
		tmp = j * (y5 * (t * -i));
	elseif (b <= 7.2e+74)
		tmp = (x * c) * (y0 * y2);
	else
		tmp = a * (b * (t * -z));
	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, -5.8e-29], N[(j * N[(t * N[(b * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[b, -8e-279], N[(y2 * N[(x * N[(a * (-y1)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[b, 7.5e-11], N[(j * N[(y5 * N[(t * (-i)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[b, 7.2e+74], N[(N[(x * c), $MachinePrecision] * N[(y0 * y2), $MachinePrecision]), $MachinePrecision], N[(a * N[(b * N[(t * (-z)), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

1. Split input into 5 regimes

2. if b < -5.80000000000000048e-29

   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. Taylor expanded in j around inf 40.9%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 40.9%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 40.9%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 40.9%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 40.9%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 40.9%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in t around inf 34.0%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   6. Taylor expanded in b around inf 34.0%

      \[\leadsto j \cdot \left(t \cdot \color{blue}{\left(b \cdot y4\right)}\right) \]
   7. Step-by-step derivation

      1. *-commutative 34.0%

         \[\leadsto j \cdot \left(t \cdot \color{blue}{\left(y4 \cdot b\right)}\right) \]

   8. Simplified 34.0%

      \[\leadsto j \cdot \left(t \cdot \color{blue}{\left(y4 \cdot b\right)}\right) \]

   if -5.80000000000000048e-29 < b < -8.00000000000000044e-279

   1. Initial program 23.4%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in y2 around inf 51.7%

      \[\leadsto \color{blue}{y2 \cdot \left(\left(k \cdot \left(y1 \cdot y4 - y0 \cdot y5\right) + x \cdot \left(c \cdot y0 - a \cdot y1\right)\right) - t \cdot \left(c \cdot y4 - a \cdot y5\right)\right)} \]

   3. Taylor expanded in x around inf 36.4%

      \[\leadsto y2 \cdot \color{blue}{\left(x \cdot \left(c \cdot y0 - a \cdot y1\right)\right)} \]

   4. Taylor expanded in c around 0 29.4%

      \[\leadsto y2 \cdot \left(x \cdot \color{blue}{\left(-1 \cdot \left(a \cdot y1\right)\right)}\right) \]
   5. Step-by-step derivation

      1. neg-mul-1 29.4%

         \[\leadsto y2 \cdot \left(x \cdot \color{blue}{\left(-a \cdot y1\right)}\right) \]

      2. distribute-lft-neg-in 29.4%

         \[\leadsto y2 \cdot \left(x \cdot \color{blue}{\left(\left(-a\right) \cdot y1\right)}\right) \]

      3. *-commutative 29.4%

         \[\leadsto y2 \cdot \left(x \cdot \color{blue}{\left(y1 \cdot \left(-a\right)\right)}\right) \]

   6. Simplified 29.4%

      \[\leadsto y2 \cdot \left(x \cdot \color{blue}{\left(y1 \cdot \left(-a\right)\right)}\right) \]

   if -8.00000000000000044e-279 < b < 7.5e-11

   1. Initial program 38.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 45.3%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 45.3%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 45.3%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 45.3%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 45.3%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 45.3%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in t around inf 30.3%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   6. Taylor expanded in b around 0 28.5%

      \[\leadsto j \cdot \color{blue}{\left(-1 \cdot \left(i \cdot \left(t \cdot y5\right)\right)\right)} \]
   7. Step-by-step derivation

      1. mul-1-neg 28.5%

         \[\leadsto j \cdot \color{blue}{\left(-i \cdot \left(t \cdot y5\right)\right)} \]

      2. associate-*r* 28.5%

         \[\leadsto j \cdot \left(-\color{blue}{\left(i \cdot t\right) \cdot y5}\right) \]

      3. distribute-rgt-neg-in 28.5%

         \[\leadsto j \cdot \color{blue}{\left(\left(i \cdot t\right) \cdot \left(-y5\right)\right)} \]

   8. Simplified 28.5%

      \[\leadsto j \cdot \color{blue}{\left(\left(i \cdot t\right) \cdot \left(-y5\right)\right)} \]

   if 7.5e-11 < b < 7.19999999999999975e74

   1. Initial program 50.0%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in c around inf 39.6%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in x around inf 46.1%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 45.7%

         \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)} \]

      2. +-commutative 45.7%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 + -1 \cdot \left(i \cdot y\right)\right)} \]

      3. mul-1-neg 45.7%

         \[\leadsto \left(c \cdot x\right) \cdot \left(y0 \cdot y2 + \color{blue}{\left(-i \cdot y\right)}\right) \]

      4. unsub-neg 45.7%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 - i \cdot y\right)} \]

   5. Simplified 45.7%

      \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(y0 \cdot y2 - i \cdot y\right)} \]

   6. Taylor expanded in y0 around inf 45.7%

      \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2\right)} \]
   7. Step-by-step derivation

      1. *-commutative 45.7%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y2 \cdot y0\right)} \]

   8. Simplified 45.7%

      \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y2 \cdot y0\right)} \]

   if 7.19999999999999975e74 < b

   1. Initial program 27.5%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 57.1%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 36.7%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   4. Taylor expanded in x around 0 29.0%

      \[\leadsto a \cdot \left(b \cdot \color{blue}{\left(-1 \cdot \left(t \cdot z\right)\right)}\right) \]
   5. Step-by-step derivation

      1. neg-mul-1 29.0%

         \[\leadsto a \cdot \left(b \cdot \color{blue}{\left(-t \cdot z\right)}\right) \]

      2. distribute-lft-neg-in 29.0%

         \[\leadsto a \cdot \left(b \cdot \color{blue}{\left(\left(-t\right) \cdot z\right)}\right) \]

      3. *-commutative 29.0%

         \[\leadsto a \cdot \left(b \cdot \color{blue}{\left(z \cdot \left(-t\right)\right)}\right) \]

   6. Simplified 29.0%

      \[\leadsto a \cdot \left(b \cdot \color{blue}{\left(z \cdot \left(-t\right)\right)}\right) \]
3. Recombined 5 regimes into one program.

4. Final simplification 31.4%

   \[\leadsto \begin{array}{l} \mathbf{if}\;b \leq -5.8 \cdot 10^{-29}:\\ \;\;\;\;j \cdot \left(t \cdot \left(b \cdot y4\right)\right)\\ \mathbf{elif}\;b \leq -8 \cdot 10^{-279}:\\ \;\;\;\;y2 \cdot \left(x \cdot \left(a \cdot \left(-y1\right)\right)\right)\\ \mathbf{elif}\;b \leq 7.5 \cdot 10^{-11}:\\ \;\;\;\;j \cdot \left(y5 \cdot \left(t \cdot \left(-i\right)\right)\right)\\ \mathbf{elif}\;b \leq 7.2 \cdot 10^{+74}:\\ \;\;\;\;\left(x \cdot c\right) \cdot \left(y0 \cdot y2\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(b \cdot \left(t \cdot \left(-z\right)\right)\right)\\ \end{array} \]

Alternative 37: 22.3% accurate, 7.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{if}\;y4 \leq -1.6 \cdot 10^{-44}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;y4 \leq 1.75 \cdot 10^{+40}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y4 \leq 5.8 \cdot 10^{+163}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (* b (* j (* t y4)))))
   (if (<= y4 -1.6e-44)
     t_1
     (if (<= y4 1.75e+40)
       (* c (* x (* y0 y2)))
       (if (<= y4 5.8e+163) (* a (* (* x y) b)) t_1)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (j * (t * y4));
	double tmp;
	if (y4 <= -1.6e-44) {
		tmp = t_1;
	} else if (y4 <= 1.75e+40) {
		tmp = c * (x * (y0 * y2));
	} else if (y4 <= 5.8e+163) {
		tmp = a * ((x * y) * b);
	} 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 * (j * (t * y4))
    if (y4 <= (-1.6d-44)) then
        tmp = t_1
    else if (y4 <= 1.75d+40) then
        tmp = c * (x * (y0 * y2))
    else if (y4 <= 5.8d+163) then
        tmp = a * ((x * y) * b)
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = b * (j * (t * y4));
	double tmp;
	if (y4 <= -1.6e-44) {
		tmp = t_1;
	} else if (y4 <= 1.75e+40) {
		tmp = c * (x * (y0 * y2));
	} else if (y4 <= 5.8e+163) {
		tmp = a * ((x * y) * b);
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = b * (j * (t * y4))
	tmp = 0
	if y4 <= -1.6e-44:
		tmp = t_1
	elif y4 <= 1.75e+40:
		tmp = c * (x * (y0 * y2))
	elif y4 <= 5.8e+163:
		tmp = a * ((x * y) * b)
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(b * Float64(j * Float64(t * y4)))
	tmp = 0.0
	if (y4 <= -1.6e-44)
		tmp = t_1;
	elseif (y4 <= 1.75e+40)
		tmp = Float64(c * Float64(x * Float64(y0 * y2)));
	elseif (y4 <= 5.8e+163)
		tmp = Float64(a * Float64(Float64(x * y) * b));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = b * (j * (t * y4));
	tmp = 0.0;
	if (y4 <= -1.6e-44)
		tmp = t_1;
	elseif (y4 <= 1.75e+40)
		tmp = c * (x * (y0 * y2));
	elseif (y4 <= 5.8e+163)
		tmp = a * ((x * y) * b);
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(b * N[(j * N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[y4, -1.6e-44], t$95$1, If[LessEqual[y4, 1.75e+40], N[(c * N[(x * N[(y0 * y2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[y4, 5.8e+163], N[(a * N[(N[(x * y), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision], t$95$1]]]]

Derivation

1. Split input into 3 regimes

2. if y4 < -1.59999999999999997e-44 or 5.79999999999999996e163 < y4

   1. Initial program 25.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in j around inf 35.6%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 35.6%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 35.6%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 35.6%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 35.6%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 35.6%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in t around inf 34.8%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   6. Taylor expanded in b around inf 32.2%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 32.2%

         \[\leadsto b \cdot \color{blue}{\left(\left(t \cdot y4\right) \cdot j\right)} \]

   8. Simplified 32.2%

      \[\leadsto \color{blue}{b \cdot \left(\left(t \cdot y4\right) \cdot j\right)} \]

   if -1.59999999999999997e-44 < y4 < 1.75e40

   1. Initial program 31.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in c around inf 39.3%

      \[\leadsto \color{blue}{c \cdot \left(\left(-1 \cdot \left(i \cdot \left(x \cdot y - t \cdot z\right)\right) + y0 \cdot \left(x \cdot y2 - y3 \cdot z\right)\right) - y4 \cdot \left(t \cdot y2 - y \cdot y3\right)\right)} \]

   3. Taylor expanded in x around inf 37.2%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)\right)} \]
   4. Step-by-step derivation

      1. associate-*r* 33.0%

         \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(-1 \cdot \left(i \cdot y\right) + y0 \cdot y2\right)} \]

      2. +-commutative 33.0%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 + -1 \cdot \left(i \cdot y\right)\right)} \]

      3. mul-1-neg 33.0%

         \[\leadsto \left(c \cdot x\right) \cdot \left(y0 \cdot y2 + \color{blue}{\left(-i \cdot y\right)}\right) \]

      4. unsub-neg 33.0%

         \[\leadsto \left(c \cdot x\right) \cdot \color{blue}{\left(y0 \cdot y2 - i \cdot y\right)} \]

   5. Simplified 33.0%

      \[\leadsto \color{blue}{\left(c \cdot x\right) \cdot \left(y0 \cdot y2 - i \cdot y\right)} \]

   6. Taylor expanded in y0 around inf 25.5%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 25.5%

         \[\leadsto c \cdot \left(x \cdot \color{blue}{\left(y2 \cdot y0\right)}\right) \]

   8. Simplified 25.5%

      \[\leadsto \color{blue}{c \cdot \left(x \cdot \left(y2 \cdot y0\right)\right)} \]

   if 1.75e40 < y4 < 5.79999999999999996e163

   1. Initial program 36.1%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 50.3%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 43.4%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   4. Taylor expanded in x around inf 33.4%

      \[\leadsto a \cdot \color{blue}{\left(b \cdot \left(x \cdot y\right)\right)} \]
3. Recombined 3 regimes into one program.

4. Final simplification 29.3%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y4 \leq -1.6 \cdot 10^{-44}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{elif}\;y4 \leq 1.75 \cdot 10^{+40}:\\ \;\;\;\;c \cdot \left(x \cdot \left(y0 \cdot y2\right)\right)\\ \mathbf{elif}\;y4 \leq 5.8 \cdot 10^{+163}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \end{array} \]

Alternative 38: 21.9% accurate, 8.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y4 \leq -1.06 \cdot 10^{-125} \lor \neg \left(y4 \leq 6.2 \cdot 10^{+161}\right):\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (if (or (<= y4 -1.06e-125) (not (<= y4 6.2e+161)))
   (* b (* j (* t y4)))
   (* a (* (* x y) b))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if ((y4 <= -1.06e-125) || !(y4 <= 6.2e+161)) {
		tmp = b * (j * (t * y4));
	} else {
		tmp = a * ((x * y) * b);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: tmp
    if ((y4 <= (-1.06d-125)) .or. (.not. (y4 <= 6.2d+161))) then
        tmp = b * (j * (t * y4))
    else
        tmp = a * ((x * y) * b)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double tmp;
	if ((y4 <= -1.06e-125) || !(y4 <= 6.2e+161)) {
		tmp = b * (j * (t * y4));
	} else {
		tmp = a * ((x * y) * b);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	tmp = 0
	if (y4 <= -1.06e-125) or not (y4 <= 6.2e+161):
		tmp = b * (j * (t * y4))
	else:
		tmp = a * ((x * y) * b)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0
	if ((y4 <= -1.06e-125) || !(y4 <= 6.2e+161))
		tmp = Float64(b * Float64(j * Float64(t * y4)));
	else
		tmp = Float64(a * Float64(Float64(x * y) * b));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = 0.0;
	if ((y4 <= -1.06e-125) || ~((y4 <= 6.2e+161)))
		tmp = b * (j * (t * y4));
	else
		tmp = a * ((x * y) * b);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := If[Or[LessEqual[y4, -1.06e-125], N[Not[LessEqual[y4, 6.2e+161]], $MachinePrecision]], N[(b * N[(j * N[(t * y4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(a * N[(N[(x * y), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision]]

Derivation

1. Split input into 2 regimes

2. if y4 < -1.05999999999999999e-125 or 6.20000000000000013e161 < y4

   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. Taylor expanded in j around inf 38.5%

      \[\leadsto \color{blue}{j \cdot \left(\left(-1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) + t \cdot \left(b \cdot y4 - i \cdot y5\right)\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right)} \]
   3. Step-by-step derivation

      1. +-commutative 38.5%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + -1 \cdot \left(y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      2. mul-1-neg 38.5%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) + \color{blue}{\left(-y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)}\right) - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      3. unsub-neg 38.5%

         \[\leadsto j \cdot \left(\color{blue}{\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right)} - x \cdot \left(b \cdot y0 - i \cdot y1\right)\right) \]

      4. *-commutative 38.5%

         \[\leadsto j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \color{blue}{\left(b \cdot y0 - i \cdot y1\right) \cdot x}\right) \]

   4. Simplified 38.5%

      \[\leadsto \color{blue}{j \cdot \left(\left(t \cdot \left(b \cdot y4 - i \cdot y5\right) - y3 \cdot \left(y1 \cdot y4 - y0 \cdot y5\right)\right) - \left(b \cdot y0 - i \cdot y1\right) \cdot x\right)} \]

   5. Taylor expanded in t around inf 32.5%

      \[\leadsto \color{blue}{j \cdot \left(t \cdot \left(b \cdot y4 - i \cdot y5\right)\right)} \]

   6. Taylor expanded in b around inf 28.8%

      \[\leadsto \color{blue}{b \cdot \left(j \cdot \left(t \cdot y4\right)\right)} \]
   7. Step-by-step derivation

      1. *-commutative 28.8%

         \[\leadsto b \cdot \color{blue}{\left(\left(t \cdot y4\right) \cdot j\right)} \]

   8. Simplified 28.8%

      \[\leadsto \color{blue}{b \cdot \left(\left(t \cdot y4\right) \cdot j\right)} \]

   if -1.05999999999999999e-125 < y4 < 6.20000000000000013e161

   1. Initial program 31.3%

      \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

   2. Taylor expanded in b around inf 39.4%

      \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

   3. Taylor expanded in a around inf 29.8%

      \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

   4. Taylor expanded in x around inf 20.5%

      \[\leadsto a \cdot \color{blue}{\left(b \cdot \left(x \cdot y\right)\right)} \]
3. Recombined 2 regimes into one program.

4. Final simplification 24.7%

   \[\leadsto \begin{array}{l} \mathbf{if}\;y4 \leq -1.06 \cdot 10^{-125} \lor \neg \left(y4 \leq 6.2 \cdot 10^{+161}\right):\\ \;\;\;\;b \cdot \left(j \cdot \left(t \cdot y4\right)\right)\\ \mathbf{else}:\\ \;\;\;\;a \cdot \left(\left(x \cdot y\right) \cdot b\right)\\ \end{array} \]

Alternative 39: 17.0% accurate, 13.6× speedup

Math

\[\begin{array}{l} \\ a \cdot \left(\left(x \cdot y\right) \cdot b\right) \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (* a (* (* x y) b)))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	return a * ((x * y) * b);
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    code = a * ((x * y) * b)
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	return a * ((x * y) * b);
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	return a * ((x * y) * b)

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	return Float64(a * Float64(Float64(x * y) * b))
end

MATLAB

function tmp = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	tmp = a * ((x * y) * b);
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := N[(a * N[(N[(x * y), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision]

Derivation

1. Initial program 29.1%

   \[\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(x \cdot j - z \cdot k\right) \cdot \left(y0 \cdot b - y1 \cdot i\right)\right) + \left(x \cdot y2 - z \cdot y3\right) \cdot \left(y0 \cdot c - y1 \cdot a\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot \left(y4 \cdot b - y5 \cdot i\right)\right) - \left(t \cdot y2 - y \cdot y3\right) \cdot \left(y4 \cdot c - y5 \cdot a\right)\right) + \left(k \cdot y2 - j \cdot y3\right) \cdot \left(y4 \cdot y1 - y5 \cdot y0\right) \]

2. Taylor expanded in b around inf 36.5%

   \[\leadsto \color{blue}{b \cdot \left(\left(a \cdot \left(x \cdot y - t \cdot z\right) + y4 \cdot \left(j \cdot t - k \cdot y\right)\right) - y0 \cdot \left(j \cdot x - k \cdot z\right)\right)} \]

3. Taylor expanded in a around inf 25.2%

   \[\leadsto \color{blue}{a \cdot \left(b \cdot \left(x \cdot y - t \cdot z\right)\right)} \]

4. Taylor expanded in x around inf 15.6%

   \[\leadsto a \cdot \color{blue}{\left(b \cdot \left(x \cdot y\right)\right)} \]

5. Final simplification 15.6%

   \[\leadsto a \cdot \left(\left(x \cdot y\right) \cdot b\right) \]

Developer target: 27.4% accurate, 0.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y4 \cdot c - y5 \cdot a\\ t_2 := x \cdot y2 - z \cdot y3\\ t_3 := y2 \cdot t - y3 \cdot y\\ t_4 := k \cdot y2 - j \cdot y3\\ t_5 := y4 \cdot b - y5 \cdot i\\ t_6 := \left(j \cdot t - k \cdot y\right) \cdot t_5\\ t_7 := b \cdot a - i \cdot c\\ t_8 := t_7 \cdot \left(y \cdot x - t \cdot z\right)\\ t_9 := j \cdot x - k \cdot z\\ t_10 := \left(b \cdot y0 - i \cdot y1\right) \cdot t_9\\ t_11 := t_9 \cdot \left(y0 \cdot b - i \cdot y1\right)\\ t_12 := y4 \cdot y1 - y5 \cdot y0\\ t_13 := t_4 \cdot t_12\\ t_14 := \left(y2 \cdot k - y3 \cdot j\right) \cdot t_12\\ t_15 := \left(\left(\left(\left(k \cdot y\right) \cdot \left(y5 \cdot i\right) - \left(y \cdot b\right) \cdot \left(y4 \cdot k\right)\right) - \left(y5 \cdot t\right) \cdot \left(i \cdot j\right)\right) - \left(t_3 \cdot t_1 - t_14\right)\right) + \left(t_8 - \left(t_11 - \left(y2 \cdot x - y3 \cdot z\right) \cdot \left(c \cdot y0 - y1 \cdot a\right)\right)\right)\\ t_16 := \left(\left(t_6 - \left(y3 \cdot y\right) \cdot \left(y5 \cdot a - y4 \cdot c\right)\right) + \left(\left(y5 \cdot a\right) \cdot \left(t \cdot y2\right) + t_13\right)\right) + \left(t_2 \cdot \left(c \cdot y0 - a \cdot y1\right) - \left(t_10 - \left(y \cdot x - z \cdot t\right) \cdot t_7\right)\right)\\ t_17 := t \cdot y2 - y \cdot y3\\ \mathbf{if}\;y4 < -7.206256231996481 \cdot 10^{+60}:\\ \;\;\;\;\left(t_8 - \left(t_11 - t_6\right)\right) - \left(\frac{t_3}{\frac{1}{t_1}} - t_14\right)\\ \mathbf{elif}\;y4 < -3.364603505246317 \cdot 10^{-66}:\\ \;\;\;\;\left(\left(\left(\left(t \cdot c\right) \cdot \left(i \cdot z\right) - \left(a \cdot t\right) \cdot \left(b \cdot z\right)\right) - \left(y \cdot c\right) \cdot \left(i \cdot x\right)\right) - t_10\right) + \left(\left(y0 \cdot c - a \cdot y1\right) \cdot t_2 - \left(t_17 \cdot \left(y4 \cdot c - a \cdot y5\right) - \left(y1 \cdot y4 - y5 \cdot y0\right) \cdot t_4\right)\right)\\ \mathbf{elif}\;y4 < -1.2000065055686116 \cdot 10^{-105}:\\ \;\;\;\;t_16\\ \mathbf{elif}\;y4 < 6.718963124057495 \cdot 10^{-279}:\\ \;\;\;\;t_15\\ \mathbf{elif}\;y4 < 4.77962681403792 \cdot 10^{-222}:\\ \;\;\;\;t_16\\ \mathbf{elif}\;y4 < 2.2852241541266835 \cdot 10^{-175}:\\ \;\;\;\;t_15\\ \mathbf{else}:\\ \;\;\;\;\left(\left(\left(\left(\left(x \cdot y - z \cdot t\right) \cdot \left(a \cdot b - c \cdot i\right) - \left(k \cdot \left(i \cdot \left(z \cdot y1\right)\right) - \left(j \cdot \left(i \cdot \left(x \cdot y1\right)\right) + y0 \cdot \left(k \cdot \left(z \cdot b\right)\right)\right)\right)\right) + \left(z \cdot \left(y3 \cdot \left(a \cdot y1\right)\right) - \left(y2 \cdot \left(x \cdot \left(a \cdot y1\right)\right) + y0 \cdot \left(z \cdot \left(c \cdot y3\right)\right)\right)\right)\right) + \left(t \cdot j - y \cdot k\right) \cdot t_5\right) - t_17 \cdot t_1\right) + t_13\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k y0 y1 y2 y3 y4 y5)
 :precision binary64
 (let* ((t_1 (- (* y4 c) (* y5 a)))
        (t_2 (- (* x y2) (* z y3)))
        (t_3 (- (* y2 t) (* y3 y)))
        (t_4 (- (* k y2) (* j y3)))
        (t_5 (- (* y4 b) (* y5 i)))
        (t_6 (* (- (* j t) (* k y)) t_5))
        (t_7 (- (* b a) (* i c)))
        (t_8 (* t_7 (- (* y x) (* t z))))
        (t_9 (- (* j x) (* k z)))
        (t_10 (* (- (* b y0) (* i y1)) t_9))
        (t_11 (* t_9 (- (* y0 b) (* i y1))))
        (t_12 (- (* y4 y1) (* y5 y0)))
        (t_13 (* t_4 t_12))
        (t_14 (* (- (* y2 k) (* y3 j)) t_12))
        (t_15
         (+
          (-
           (-
            (- (* (* k y) (* y5 i)) (* (* y b) (* y4 k)))
            (* (* y5 t) (* i j)))
           (- (* t_3 t_1) t_14))
          (- t_8 (- t_11 (* (- (* y2 x) (* y3 z)) (- (* c y0) (* y1 a)))))))
        (t_16
         (+
          (+
           (- t_6 (* (* y3 y) (- (* y5 a) (* y4 c))))
           (+ (* (* y5 a) (* t y2)) t_13))
          (-
           (* t_2 (- (* c y0) (* a y1)))
           (- t_10 (* (- (* y x) (* z t)) t_7)))))
        (t_17 (- (* t y2) (* y y3))))
   (if (< y4 -7.206256231996481e+60)
     (- (- t_8 (- t_11 t_6)) (- (/ t_3 (/ 1.0 t_1)) t_14))
     (if (< y4 -3.364603505246317e-66)
       (+
        (-
         (- (- (* (* t c) (* i z)) (* (* a t) (* b z))) (* (* y c) (* i x)))
         t_10)
        (-
         (* (- (* y0 c) (* a y1)) t_2)
         (- (* t_17 (- (* y4 c) (* a y5))) (* (- (* y1 y4) (* y5 y0)) t_4))))
       (if (< y4 -1.2000065055686116e-105)
         t_16
         (if (< y4 6.718963124057495e-279)
           t_15
           (if (< y4 4.77962681403792e-222)
             t_16
             (if (< y4 2.2852241541266835e-175)
               t_15
               (+
                (-
                 (+
                  (+
                   (-
                    (* (- (* x y) (* z t)) (- (* a b) (* c i)))
                    (-
                     (* k (* i (* z y1)))
                     (+ (* j (* i (* x y1))) (* y0 (* k (* z b))))))
                   (-
                    (* z (* y3 (* a y1)))
                    (+ (* y2 (* x (* a y1))) (* y0 (* z (* c y3))))))
                  (* (- (* t j) (* y k)) t_5))
                 (* t_17 t_1))
                t_13)))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (y4 * c) - (y5 * a);
	double t_2 = (x * y2) - (z * y3);
	double t_3 = (y2 * t) - (y3 * y);
	double t_4 = (k * y2) - (j * y3);
	double t_5 = (y4 * b) - (y5 * i);
	double t_6 = ((j * t) - (k * y)) * t_5;
	double t_7 = (b * a) - (i * c);
	double t_8 = t_7 * ((y * x) - (t * z));
	double t_9 = (j * x) - (k * z);
	double t_10 = ((b * y0) - (i * y1)) * t_9;
	double t_11 = t_9 * ((y0 * b) - (i * y1));
	double t_12 = (y4 * y1) - (y5 * y0);
	double t_13 = t_4 * t_12;
	double t_14 = ((y2 * k) - (y3 * j)) * t_12;
	double t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))));
	double t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)));
	double t_17 = (t * y2) - (y * y3);
	double tmp;
	if (y4 < -7.206256231996481e+60) {
		tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0 / t_1)) - t_14);
	} else if (y4 < -3.364603505246317e-66) {
		tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)));
	} else if (y4 < -1.2000065055686116e-105) {
		tmp = t_16;
	} else if (y4 < 6.718963124057495e-279) {
		tmp = t_15;
	} else if (y4 < 4.77962681403792e-222) {
		tmp = t_16;
	} else if (y4 < 2.2852241541266835e-175) {
		tmp = t_15;
	} else {
		tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8), intent (in) :: t
    real(8), intent (in) :: a
    real(8), intent (in) :: b
    real(8), intent (in) :: c
    real(8), intent (in) :: i
    real(8), intent (in) :: j
    real(8), intent (in) :: k
    real(8), intent (in) :: y0
    real(8), intent (in) :: y1
    real(8), intent (in) :: y2
    real(8), intent (in) :: y3
    real(8), intent (in) :: y4
    real(8), intent (in) :: y5
    real(8) :: t_1
    real(8) :: t_10
    real(8) :: t_11
    real(8) :: t_12
    real(8) :: t_13
    real(8) :: t_14
    real(8) :: t_15
    real(8) :: t_16
    real(8) :: t_17
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: t_5
    real(8) :: t_6
    real(8) :: t_7
    real(8) :: t_8
    real(8) :: t_9
    real(8) :: tmp
    t_1 = (y4 * c) - (y5 * a)
    t_2 = (x * y2) - (z * y3)
    t_3 = (y2 * t) - (y3 * y)
    t_4 = (k * y2) - (j * y3)
    t_5 = (y4 * b) - (y5 * i)
    t_6 = ((j * t) - (k * y)) * t_5
    t_7 = (b * a) - (i * c)
    t_8 = t_7 * ((y * x) - (t * z))
    t_9 = (j * x) - (k * z)
    t_10 = ((b * y0) - (i * y1)) * t_9
    t_11 = t_9 * ((y0 * b) - (i * y1))
    t_12 = (y4 * y1) - (y5 * y0)
    t_13 = t_4 * t_12
    t_14 = ((y2 * k) - (y3 * j)) * t_12
    t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))))
    t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)))
    t_17 = (t * y2) - (y * y3)
    if (y4 < (-7.206256231996481d+60)) then
        tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0d0 / t_1)) - t_14)
    else if (y4 < (-3.364603505246317d-66)) then
        tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)))
    else if (y4 < (-1.2000065055686116d-105)) then
        tmp = t_16
    else if (y4 < 6.718963124057495d-279) then
        tmp = t_15
    else if (y4 < 4.77962681403792d-222) then
        tmp = t_16
    else if (y4 < 2.2852241541266835d-175) then
        tmp = t_15
    else
        tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k, double y0, double y1, double y2, double y3, double y4, double y5) {
	double t_1 = (y4 * c) - (y5 * a);
	double t_2 = (x * y2) - (z * y3);
	double t_3 = (y2 * t) - (y3 * y);
	double t_4 = (k * y2) - (j * y3);
	double t_5 = (y4 * b) - (y5 * i);
	double t_6 = ((j * t) - (k * y)) * t_5;
	double t_7 = (b * a) - (i * c);
	double t_8 = t_7 * ((y * x) - (t * z));
	double t_9 = (j * x) - (k * z);
	double t_10 = ((b * y0) - (i * y1)) * t_9;
	double t_11 = t_9 * ((y0 * b) - (i * y1));
	double t_12 = (y4 * y1) - (y5 * y0);
	double t_13 = t_4 * t_12;
	double t_14 = ((y2 * k) - (y3 * j)) * t_12;
	double t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))));
	double t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)));
	double t_17 = (t * y2) - (y * y3);
	double tmp;
	if (y4 < -7.206256231996481e+60) {
		tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0 / t_1)) - t_14);
	} else if (y4 < -3.364603505246317e-66) {
		tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)));
	} else if (y4 < -1.2000065055686116e-105) {
		tmp = t_16;
	} else if (y4 < 6.718963124057495e-279) {
		tmp = t_15;
	} else if (y4 < 4.77962681403792e-222) {
		tmp = t_16;
	} else if (y4 < 2.2852241541266835e-175) {
		tmp = t_15;
	} else {
		tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5):
	t_1 = (y4 * c) - (y5 * a)
	t_2 = (x * y2) - (z * y3)
	t_3 = (y2 * t) - (y3 * y)
	t_4 = (k * y2) - (j * y3)
	t_5 = (y4 * b) - (y5 * i)
	t_6 = ((j * t) - (k * y)) * t_5
	t_7 = (b * a) - (i * c)
	t_8 = t_7 * ((y * x) - (t * z))
	t_9 = (j * x) - (k * z)
	t_10 = ((b * y0) - (i * y1)) * t_9
	t_11 = t_9 * ((y0 * b) - (i * y1))
	t_12 = (y4 * y1) - (y5 * y0)
	t_13 = t_4 * t_12
	t_14 = ((y2 * k) - (y3 * j)) * t_12
	t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))))
	t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)))
	t_17 = (t * y2) - (y * y3)
	tmp = 0
	if y4 < -7.206256231996481e+60:
		tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0 / t_1)) - t_14)
	elif y4 < -3.364603505246317e-66:
		tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)))
	elif y4 < -1.2000065055686116e-105:
		tmp = t_16
	elif y4 < 6.718963124057495e-279:
		tmp = t_15
	elif y4 < 4.77962681403792e-222:
		tmp = t_16
	elif y4 < 2.2852241541266835e-175:
		tmp = t_15
	else:
		tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = Float64(Float64(y4 * c) - Float64(y5 * a))
	t_2 = Float64(Float64(x * y2) - Float64(z * y3))
	t_3 = Float64(Float64(y2 * t) - Float64(y3 * y))
	t_4 = Float64(Float64(k * y2) - Float64(j * y3))
	t_5 = Float64(Float64(y4 * b) - Float64(y5 * i))
	t_6 = Float64(Float64(Float64(j * t) - Float64(k * y)) * t_5)
	t_7 = Float64(Float64(b * a) - Float64(i * c))
	t_8 = Float64(t_7 * Float64(Float64(y * x) - Float64(t * z)))
	t_9 = Float64(Float64(j * x) - Float64(k * z))
	t_10 = Float64(Float64(Float64(b * y0) - Float64(i * y1)) * t_9)
	t_11 = Float64(t_9 * Float64(Float64(y0 * b) - Float64(i * y1)))
	t_12 = Float64(Float64(y4 * y1) - Float64(y5 * y0))
	t_13 = Float64(t_4 * t_12)
	t_14 = Float64(Float64(Float64(y2 * k) - Float64(y3 * j)) * t_12)
	t_15 = Float64(Float64(Float64(Float64(Float64(Float64(k * y) * Float64(y5 * i)) - Float64(Float64(y * b) * Float64(y4 * k))) - Float64(Float64(y5 * t) * Float64(i * j))) - Float64(Float64(t_3 * t_1) - t_14)) + Float64(t_8 - Float64(t_11 - Float64(Float64(Float64(y2 * x) - Float64(y3 * z)) * Float64(Float64(c * y0) - Float64(y1 * a))))))
	t_16 = Float64(Float64(Float64(t_6 - Float64(Float64(y3 * y) * Float64(Float64(y5 * a) - Float64(y4 * c)))) + Float64(Float64(Float64(y5 * a) * Float64(t * y2)) + t_13)) + Float64(Float64(t_2 * Float64(Float64(c * y0) - Float64(a * y1))) - Float64(t_10 - Float64(Float64(Float64(y * x) - Float64(z * t)) * t_7))))
	t_17 = Float64(Float64(t * y2) - Float64(y * y3))
	tmp = 0.0
	if (y4 < -7.206256231996481e+60)
		tmp = Float64(Float64(t_8 - Float64(t_11 - t_6)) - Float64(Float64(t_3 / Float64(1.0 / t_1)) - t_14));
	elseif (y4 < -3.364603505246317e-66)
		tmp = Float64(Float64(Float64(Float64(Float64(Float64(t * c) * Float64(i * z)) - Float64(Float64(a * t) * Float64(b * z))) - Float64(Float64(y * c) * Float64(i * x))) - t_10) + Float64(Float64(Float64(Float64(y0 * c) - Float64(a * y1)) * t_2) - Float64(Float64(t_17 * Float64(Float64(y4 * c) - Float64(a * y5))) - Float64(Float64(Float64(y1 * y4) - Float64(y5 * y0)) * t_4))));
	elseif (y4 < -1.2000065055686116e-105)
		tmp = t_16;
	elseif (y4 < 6.718963124057495e-279)
		tmp = t_15;
	elseif (y4 < 4.77962681403792e-222)
		tmp = t_16;
	elseif (y4 < 2.2852241541266835e-175)
		tmp = t_15;
	else
		tmp = Float64(Float64(Float64(Float64(Float64(Float64(Float64(Float64(x * y) - Float64(z * t)) * Float64(Float64(a * b) - Float64(c * i))) - Float64(Float64(k * Float64(i * Float64(z * y1))) - Float64(Float64(j * Float64(i * Float64(x * y1))) + Float64(y0 * Float64(k * Float64(z * b)))))) + Float64(Float64(z * Float64(y3 * Float64(a * y1))) - Float64(Float64(y2 * Float64(x * Float64(a * y1))) + Float64(y0 * Float64(z * Float64(c * y3)))))) + Float64(Float64(Float64(t * j) - Float64(y * k)) * t_5)) - Float64(t_17 * t_1)) + t_13);
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k, y0, y1, y2, y3, y4, y5)
	t_1 = (y4 * c) - (y5 * a);
	t_2 = (x * y2) - (z * y3);
	t_3 = (y2 * t) - (y3 * y);
	t_4 = (k * y2) - (j * y3);
	t_5 = (y4 * b) - (y5 * i);
	t_6 = ((j * t) - (k * y)) * t_5;
	t_7 = (b * a) - (i * c);
	t_8 = t_7 * ((y * x) - (t * z));
	t_9 = (j * x) - (k * z);
	t_10 = ((b * y0) - (i * y1)) * t_9;
	t_11 = t_9 * ((y0 * b) - (i * y1));
	t_12 = (y4 * y1) - (y5 * y0);
	t_13 = t_4 * t_12;
	t_14 = ((y2 * k) - (y3 * j)) * t_12;
	t_15 = (((((k * y) * (y5 * i)) - ((y * b) * (y4 * k))) - ((y5 * t) * (i * j))) - ((t_3 * t_1) - t_14)) + (t_8 - (t_11 - (((y2 * x) - (y3 * z)) * ((c * y0) - (y1 * a)))));
	t_16 = ((t_6 - ((y3 * y) * ((y5 * a) - (y4 * c)))) + (((y5 * a) * (t * y2)) + t_13)) + ((t_2 * ((c * y0) - (a * y1))) - (t_10 - (((y * x) - (z * t)) * t_7)));
	t_17 = (t * y2) - (y * y3);
	tmp = 0.0;
	if (y4 < -7.206256231996481e+60)
		tmp = (t_8 - (t_11 - t_6)) - ((t_3 / (1.0 / t_1)) - t_14);
	elseif (y4 < -3.364603505246317e-66)
		tmp = (((((t * c) * (i * z)) - ((a * t) * (b * z))) - ((y * c) * (i * x))) - t_10) + ((((y0 * c) - (a * y1)) * t_2) - ((t_17 * ((y4 * c) - (a * y5))) - (((y1 * y4) - (y5 * y0)) * t_4)));
	elseif (y4 < -1.2000065055686116e-105)
		tmp = t_16;
	elseif (y4 < 6.718963124057495e-279)
		tmp = t_15;
	elseif (y4 < 4.77962681403792e-222)
		tmp = t_16;
	elseif (y4 < 2.2852241541266835e-175)
		tmp = t_15;
	else
		tmp = (((((((x * y) - (z * t)) * ((a * b) - (c * i))) - ((k * (i * (z * y1))) - ((j * (i * (x * y1))) + (y0 * (k * (z * b)))))) + ((z * (y3 * (a * y1))) - ((y2 * (x * (a * y1))) + (y0 * (z * (c * y3)))))) + (((t * j) - (y * k)) * t_5)) - (t_17 * t_1)) + t_13;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_, y0_, y1_, y2_, y3_, y4_, y5_] := Block[{t$95$1 = N[(N[(y4 * c), $MachinePrecision] - N[(y5 * a), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(x * y2), $MachinePrecision] - N[(z * y3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(y2 * t), $MachinePrecision] - N[(y3 * y), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[(k * y2), $MachinePrecision] - N[(j * y3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(N[(y4 * b), $MachinePrecision] - N[(y5 * i), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$6 = N[(N[(N[(j * t), $MachinePrecision] - N[(k * y), $MachinePrecision]), $MachinePrecision] * t$95$5), $MachinePrecision]}, Block[{t$95$7 = N[(N[(b * a), $MachinePrecision] - N[(i * c), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$8 = N[(t$95$7 * N[(N[(y * x), $MachinePrecision] - N[(t * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$9 = N[(N[(j * x), $MachinePrecision] - N[(k * z), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$10 = N[(N[(N[(b * y0), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision] * t$95$9), $MachinePrecision]}, Block[{t$95$11 = N[(t$95$9 * N[(N[(y0 * b), $MachinePrecision] - N[(i * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$12 = N[(N[(y4 * y1), $MachinePrecision] - N[(y5 * y0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$13 = N[(t$95$4 * t$95$12), $MachinePrecision]}, Block[{t$95$14 = N[(N[(N[(y2 * k), $MachinePrecision] - N[(y3 * j), $MachinePrecision]), $MachinePrecision] * t$95$12), $MachinePrecision]}, Block[{t$95$15 = N[(N[(N[(N[(N[(N[(k * y), $MachinePrecision] * N[(y5 * i), $MachinePrecision]), $MachinePrecision] - N[(N[(y * b), $MachinePrecision] * N[(y4 * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(y5 * t), $MachinePrecision] * N[(i * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(t$95$3 * t$95$1), $MachinePrecision] - t$95$14), $MachinePrecision]), $MachinePrecision] + N[(t$95$8 - N[(t$95$11 - N[(N[(N[(y2 * x), $MachinePrecision] - N[(y3 * z), $MachinePrecision]), $MachinePrecision] * N[(N[(c * y0), $MachinePrecision] - N[(y1 * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$16 = N[(N[(N[(t$95$6 - N[(N[(y3 * y), $MachinePrecision] * N[(N[(y5 * a), $MachinePrecision] - N[(y4 * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(y5 * a), $MachinePrecision] * N[(t * y2), $MachinePrecision]), $MachinePrecision] + t$95$13), $MachinePrecision]), $MachinePrecision] + N[(N[(t$95$2 * N[(N[(c * y0), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(t$95$10 - N[(N[(N[(y * x), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision] * t$95$7), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$17 = N[(N[(t * y2), $MachinePrecision] - N[(y * y3), $MachinePrecision]), $MachinePrecision]}, If[Less[y4, -7.206256231996481e+60], N[(N[(t$95$8 - N[(t$95$11 - t$95$6), $MachinePrecision]), $MachinePrecision] - N[(N[(t$95$3 / N[(1.0 / t$95$1), $MachinePrecision]), $MachinePrecision] - t$95$14), $MachinePrecision]), $MachinePrecision], If[Less[y4, -3.364603505246317e-66], N[(N[(N[(N[(N[(N[(t * c), $MachinePrecision] * N[(i * z), $MachinePrecision]), $MachinePrecision] - N[(N[(a * t), $MachinePrecision] * N[(b * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(y * c), $MachinePrecision] * N[(i * x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$10), $MachinePrecision] + N[(N[(N[(N[(y0 * c), $MachinePrecision] - N[(a * y1), $MachinePrecision]), $MachinePrecision] * t$95$2), $MachinePrecision] - N[(N[(t$95$17 * N[(N[(y4 * c), $MachinePrecision] - N[(a * y5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(N[(y1 * y4), $MachinePrecision] - N[(y5 * y0), $MachinePrecision]), $MachinePrecision] * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[Less[y4, -1.2000065055686116e-105], t$95$16, If[Less[y4, 6.718963124057495e-279], t$95$15, If[Less[y4, 4.77962681403792e-222], t$95$16, If[Less[y4, 2.2852241541266835e-175], t$95$15, N[(N[(N[(N[(N[(N[(N[(N[(x * y), $MachinePrecision] - N[(z * t), $MachinePrecision]), $MachinePrecision] * N[(N[(a * b), $MachinePrecision] - N[(c * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(k * N[(i * N[(z * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(j * N[(i * N[(x * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(k * N[(z * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(z * N[(y3 * N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(y2 * N[(x * N[(a * y1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(y0 * N[(z * N[(c * y3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(t * j), $MachinePrecision] - N[(y * k), $MachinePrecision]), $MachinePrecision] * t$95$5), $MachinePrecision]), $MachinePrecision] - N[(t$95$17 * t$95$1), $MachinePrecision]), $MachinePrecision] + t$95$13), $MachinePrecision]]]]]]]]]]]]]]]]]]]]]]]]

Reproduce

herbie shell --seed 2023320 
(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)))))