Diagrams.Solve.Polynomial:cubForm from diagrams-solve-0.1, A

Percentage Accurate: 95.8% → 98.4%

Time: 14.6s

Alternatives: 17

Speedup: 0.9×

• 27.9% of points produce a very large (infinite) output. You may want to add a precondition.

Specification

Math

\[\begin{array}{l} \\ \left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \end{array} \]

FPCore

(FPCore (x y z t a b)
 :precision binary64
 (+ (- (* x 2.0) (* (* (* y 9.0) z) t)) (* (* a 27.0) b)))

C

double code(double x, double y, double z, double t, double a, double b) {
	return ((x * 2.0) - (((y * 9.0) * z) * t)) + ((a * 27.0) * b);
}

Fortran

real(8) function code(x, y, z, t, a, b)
    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
    code = ((x * 2.0d0) - (((y * 9.0d0) * z) * t)) + ((a * 27.0d0) * b)
end function

Java

public static double code(double x, double y, double z, double t, double a, double b) {
	return ((x * 2.0) - (((y * 9.0) * z) * t)) + ((a * 27.0) * b);
}

Python

def code(x, y, z, t, a, b):
	return ((x * 2.0) - (((y * 9.0) * z) * t)) + ((a * 27.0) * b)

Julia

function code(x, y, z, t, a, b)
	return Float64(Float64(Float64(x * 2.0) - Float64(Float64(Float64(y * 9.0) * z) * t)) + Float64(Float64(a * 27.0) * b))
end

MATLAB

function tmp = code(x, y, z, t, a, b)
	tmp = ((x * 2.0) - (((y * 9.0) * z) * t)) + ((a * 27.0) * b);
end

Wolfram

code[x_, y_, z_, t_, a_, b_] := N[(N[(N[(x * 2.0), $MachinePrecision] - N[(N[(N[(y * 9.0), $MachinePrecision] * z), $MachinePrecision] * t), $MachinePrecision]), $MachinePrecision] + N[(N[(a * 27.0), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision]

Initial Program: 95.8% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ \left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + \left(a \cdot 27\right) \cdot b \end{array} \]

FPCore

(FPCore (x y z t a b)
 :precision binary64
 (+ (- (* x 2.0) (* (* (* y 9.0) z) t)) (* (* a 27.0) b)))

C

double code(double x, double y, double z, double t, double a, double b) {
	return ((x * 2.0) - (((y * 9.0) * z) * t)) + ((a * 27.0) * b);
}

Fortran

real(8) function code(x, y, z, t, a, b)
    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
    code = ((x * 2.0d0) - (((y * 9.0d0) * z) * t)) + ((a * 27.0d0) * b)
end function

Java

public static double code(double x, double y, double z, double t, double a, double b) {
	return ((x * 2.0) - (((y * 9.0) * z) * t)) + ((a * 27.0) * b);
}

Python

def code(x, y, z, t, a, b):
	return ((x * 2.0) - (((y * 9.0) * z) * t)) + ((a * 27.0) * b)

Julia

function code(x, y, z, t, a, b)
	return Float64(Float64(Float64(x * 2.0) - Float64(Float64(Float64(y * 9.0) * z) * t)) + Float64(Float64(a * 27.0) * b))
end

MATLAB

function tmp = code(x, y, z, t, a, b)
	tmp = ((x * 2.0) - (((y * 9.0) * z) * t)) + ((a * 27.0) * b);
end

Wolfram

code[x_, y_, z_, t_, a_, b_] := N[(N[(N[(x * 2.0), $MachinePrecision] - N[(N[(N[(y * 9.0), $MachinePrecision] * z), $MachinePrecision] * t), $MachinePrecision]), $MachinePrecision] + N[(N[(a * 27.0), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision]

Alternative 1: 98.4% accurate, 0.1× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} \mathbf{if}\;y \cdot 9 \leq -1 \cdot 10^{+178}:\\ \;\;\;\;\mathsf{fma}\left(a, 27 \cdot b, \mathsf{fma}\left(x, 2, y \cdot \left(z \cdot \left(t \cdot -9\right)\right)\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(x \cdot 2 - t \cdot \left(\left(y \cdot 9\right) \cdot z\right)\right) + b \cdot \left(a \cdot 27\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (if (<= (* y 9.0) -1e+178)
   (fma a (* 27.0 b) (fma x 2.0 (* y (* z (* t -9.0)))))
   (+ (- (* x 2.0) (* t (* (* y 9.0) z))) (* b (* a 27.0)))))

C

assert(x < y && y < z && z < t && t < a && a < b);
double code(double x, double y, double z, double t, double a, double b) {
	double tmp;
	if ((y * 9.0) <= -1e+178) {
		tmp = fma(a, (27.0 * b), fma(x, 2.0, (y * (z * (t * -9.0)))));
	} else {
		tmp = ((x * 2.0) - (t * ((y * 9.0) * z))) + (b * (a * 27.0));
	}
	return tmp;
}

Julia

x, y, z, t, a, b = sort([x, y, z, t, a, b])
function code(x, y, z, t, a, b)
	tmp = 0.0
	if (Float64(y * 9.0) <= -1e+178)
		tmp = fma(a, Float64(27.0 * b), fma(x, 2.0, Float64(y * Float64(z * Float64(t * -9.0)))));
	else
		tmp = Float64(Float64(Float64(x * 2.0) - Float64(t * Float64(Float64(y * 9.0) * z))) + Float64(b * Float64(a * 27.0)));
	end
	return tmp
end

Wolfram

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_] := If[LessEqual[N[(y * 9.0), $MachinePrecision], -1e+178], N[(a * N[(27.0 * b), $MachinePrecision] + N[(x * 2.0 + N[(y * N[(z * N[(t * -9.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(N[(x * 2.0), $MachinePrecision] - N[(t * N[(N[(y * 9.0), $MachinePrecision] * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(b * N[(a * 27.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

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

Alternative 2: 49.3% accurate, 0.7× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} t_1 := 27 \cdot \left(a \cdot b\right)\\ t_2 := a \cdot \left(27 \cdot b\right)\\ \mathbf{if}\;z \leq -7 \cdot 10^{+42}:\\ \;\;\;\;z \cdot \left(y \cdot \left(t \cdot -9\right)\right)\\ \mathbf{elif}\;z \leq -8.5 \cdot 10^{-65}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq -3.3 \cdot 10^{-89}:\\ \;\;\;\;\left(t \cdot -9\right) \cdot \left(y \cdot z\right)\\ \mathbf{elif}\;z \leq -7.6 \cdot 10^{-180}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq 1.56 \cdot 10^{-292}:\\ \;\;\;\;x \cdot 2\\ \mathbf{elif}\;z \leq 9.5 \cdot 10^{-180}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;z \leq 5.2 \cdot 10^{-163}:\\ \;\;\;\;x \cdot 2\\ \mathbf{elif}\;z \leq 1.8 \cdot 10^{+38}:\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;-9 \cdot \left(t \cdot \left(y \cdot z\right)\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (let* ((t_1 (* 27.0 (* a b))) (t_2 (* a (* 27.0 b))))
   (if (<= z -7e+42)
     (* z (* y (* t -9.0)))
     (if (<= z -8.5e-65)
       t_1
       (if (<= z -3.3e-89)
         (* (* t -9.0) (* y z))
         (if (<= z -7.6e-180)
           t_1
           (if (<= z 1.56e-292)
             (* x 2.0)
             (if (<= z 9.5e-180)
               t_2
               (if (<= z 5.2e-163)
                 (* x 2.0)
                 (if (<= z 1.8e+38) t_2 (* -9.0 (* t (* y z)))))))))))))

C

assert(x < y && y < z && z < t && t < a && a < b);
double code(double x, double y, double z, double t, double a, double b) {
	double t_1 = 27.0 * (a * b);
	double t_2 = a * (27.0 * b);
	double tmp;
	if (z <= -7e+42) {
		tmp = z * (y * (t * -9.0));
	} else if (z <= -8.5e-65) {
		tmp = t_1;
	} else if (z <= -3.3e-89) {
		tmp = (t * -9.0) * (y * z);
	} else if (z <= -7.6e-180) {
		tmp = t_1;
	} else if (z <= 1.56e-292) {
		tmp = x * 2.0;
	} else if (z <= 9.5e-180) {
		tmp = t_2;
	} else if (z <= 5.2e-163) {
		tmp = x * 2.0;
	} else if (z <= 1.8e+38) {
		tmp = t_2;
	} else {
		tmp = -9.0 * (t * (y * z));
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b)
    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) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = 27.0d0 * (a * b)
    t_2 = a * (27.0d0 * b)
    if (z <= (-7d+42)) then
        tmp = z * (y * (t * (-9.0d0)))
    else if (z <= (-8.5d-65)) then
        tmp = t_1
    else if (z <= (-3.3d-89)) then
        tmp = (t * (-9.0d0)) * (y * z)
    else if (z <= (-7.6d-180)) then
        tmp = t_1
    else if (z <= 1.56d-292) then
        tmp = x * 2.0d0
    else if (z <= 9.5d-180) then
        tmp = t_2
    else if (z <= 5.2d-163) then
        tmp = x * 2.0d0
    else if (z <= 1.8d+38) then
        tmp = t_2
    else
        tmp = (-9.0d0) * (t * (y * z))
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b;
public static double code(double x, double y, double z, double t, double a, double b) {
	double t_1 = 27.0 * (a * b);
	double t_2 = a * (27.0 * b);
	double tmp;
	if (z <= -7e+42) {
		tmp = z * (y * (t * -9.0));
	} else if (z <= -8.5e-65) {
		tmp = t_1;
	} else if (z <= -3.3e-89) {
		tmp = (t * -9.0) * (y * z);
	} else if (z <= -7.6e-180) {
		tmp = t_1;
	} else if (z <= 1.56e-292) {
		tmp = x * 2.0;
	} else if (z <= 9.5e-180) {
		tmp = t_2;
	} else if (z <= 5.2e-163) {
		tmp = x * 2.0;
	} else if (z <= 1.8e+38) {
		tmp = t_2;
	} else {
		tmp = -9.0 * (t * (y * z));
	}
	return tmp;
}

Python

[x, y, z, t, a, b] = sort([x, y, z, t, a, b])
def code(x, y, z, t, a, b):
	t_1 = 27.0 * (a * b)
	t_2 = a * (27.0 * b)
	tmp = 0
	if z <= -7e+42:
		tmp = z * (y * (t * -9.0))
	elif z <= -8.5e-65:
		tmp = t_1
	elif z <= -3.3e-89:
		tmp = (t * -9.0) * (y * z)
	elif z <= -7.6e-180:
		tmp = t_1
	elif z <= 1.56e-292:
		tmp = x * 2.0
	elif z <= 9.5e-180:
		tmp = t_2
	elif z <= 5.2e-163:
		tmp = x * 2.0
	elif z <= 1.8e+38:
		tmp = t_2
	else:
		tmp = -9.0 * (t * (y * z))
	return tmp

Julia

x, y, z, t, a, b = sort([x, y, z, t, a, b])
function code(x, y, z, t, a, b)
	t_1 = Float64(27.0 * Float64(a * b))
	t_2 = Float64(a * Float64(27.0 * b))
	tmp = 0.0
	if (z <= -7e+42)
		tmp = Float64(z * Float64(y * Float64(t * -9.0)));
	elseif (z <= -8.5e-65)
		tmp = t_1;
	elseif (z <= -3.3e-89)
		tmp = Float64(Float64(t * -9.0) * Float64(y * z));
	elseif (z <= -7.6e-180)
		tmp = t_1;
	elseif (z <= 1.56e-292)
		tmp = Float64(x * 2.0);
	elseif (z <= 9.5e-180)
		tmp = t_2;
	elseif (z <= 5.2e-163)
		tmp = Float64(x * 2.0);
	elseif (z <= 1.8e+38)
		tmp = t_2;
	else
		tmp = Float64(-9.0 * Float64(t * Float64(y * z)));
	end
	return tmp
end

MATLAB

x, y, z, t, a, b = num2cell(sort([x, y, z, t, a, b])){:}
function tmp_2 = code(x, y, z, t, a, b)
	t_1 = 27.0 * (a * b);
	t_2 = a * (27.0 * b);
	tmp = 0.0;
	if (z <= -7e+42)
		tmp = z * (y * (t * -9.0));
	elseif (z <= -8.5e-65)
		tmp = t_1;
	elseif (z <= -3.3e-89)
		tmp = (t * -9.0) * (y * z);
	elseif (z <= -7.6e-180)
		tmp = t_1;
	elseif (z <= 1.56e-292)
		tmp = x * 2.0;
	elseif (z <= 9.5e-180)
		tmp = t_2;
	elseif (z <= 5.2e-163)
		tmp = x * 2.0;
	elseif (z <= 1.8e+38)
		tmp = t_2;
	else
		tmp = -9.0 * (t * (y * z));
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_] := Block[{t$95$1 = N[(27.0 * N[(a * b), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(a * N[(27.0 * b), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -7e+42], N[(z * N[(y * N[(t * -9.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -8.5e-65], t$95$1, If[LessEqual[z, -3.3e-89], N[(N[(t * -9.0), $MachinePrecision] * N[(y * z), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -7.6e-180], t$95$1, If[LessEqual[z, 1.56e-292], N[(x * 2.0), $MachinePrecision], If[LessEqual[z, 9.5e-180], t$95$2, If[LessEqual[z, 5.2e-163], N[(x * 2.0), $MachinePrecision], If[LessEqual[z, 1.8e+38], t$95$2, N[(-9.0 * N[(t * N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]

Derivation

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

Alternative 3: 97.9% accurate, 0.7× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} t_1 := \left(y \cdot 9\right) \cdot z\\ \mathbf{if}\;t_1 \leq 5 \cdot 10^{+283}:\\ \;\;\;\;\left(x \cdot 2 - t \cdot t_1\right) + b \cdot \left(a \cdot 27\right)\\ \mathbf{else}:\\ \;\;\;\;x \cdot 2 - 9 \cdot \left(y \cdot \left(z \cdot t\right)\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (let* ((t_1 (* (* y 9.0) z)))
   (if (<= t_1 5e+283)
     (+ (- (* x 2.0) (* t t_1)) (* b (* a 27.0)))
     (- (* x 2.0) (* 9.0 (* y (* z t)))))))

C

assert(x < y && y < z && z < t && t < a && a < b);
double code(double x, double y, double z, double t, double a, double b) {
	double t_1 = (y * 9.0) * z;
	double tmp;
	if (t_1 <= 5e+283) {
		tmp = ((x * 2.0) - (t * t_1)) + (b * (a * 27.0));
	} else {
		tmp = (x * 2.0) - (9.0 * (y * (z * t)));
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b)
    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) :: t_1
    real(8) :: tmp
    t_1 = (y * 9.0d0) * z
    if (t_1 <= 5d+283) then
        tmp = ((x * 2.0d0) - (t * t_1)) + (b * (a * 27.0d0))
    else
        tmp = (x * 2.0d0) - (9.0d0 * (y * (z * t)))
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b;
public static double code(double x, double y, double z, double t, double a, double b) {
	double t_1 = (y * 9.0) * z;
	double tmp;
	if (t_1 <= 5e+283) {
		tmp = ((x * 2.0) - (t * t_1)) + (b * (a * 27.0));
	} else {
		tmp = (x * 2.0) - (9.0 * (y * (z * t)));
	}
	return tmp;
}

Python

[x, y, z, t, a, b] = sort([x, y, z, t, a, b])
def code(x, y, z, t, a, b):
	t_1 = (y * 9.0) * z
	tmp = 0
	if t_1 <= 5e+283:
		tmp = ((x * 2.0) - (t * t_1)) + (b * (a * 27.0))
	else:
		tmp = (x * 2.0) - (9.0 * (y * (z * t)))
	return tmp

Julia

x, y, z, t, a, b = sort([x, y, z, t, a, b])
function code(x, y, z, t, a, b)
	t_1 = Float64(Float64(y * 9.0) * z)
	tmp = 0.0
	if (t_1 <= 5e+283)
		tmp = Float64(Float64(Float64(x * 2.0) - Float64(t * t_1)) + Float64(b * Float64(a * 27.0)));
	else
		tmp = Float64(Float64(x * 2.0) - Float64(9.0 * Float64(y * Float64(z * t))));
	end
	return tmp
end

MATLAB

x, y, z, t, a, b = num2cell(sort([x, y, z, t, a, b])){:}
function tmp_2 = code(x, y, z, t, a, b)
	t_1 = (y * 9.0) * z;
	tmp = 0.0;
	if (t_1 <= 5e+283)
		tmp = ((x * 2.0) - (t * t_1)) + (b * (a * 27.0));
	else
		tmp = (x * 2.0) - (9.0 * (y * (z * t)));
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_] := Block[{t$95$1 = N[(N[(y * 9.0), $MachinePrecision] * z), $MachinePrecision]}, If[LessEqual[t$95$1, 5e+283], N[(N[(N[(x * 2.0), $MachinePrecision] - N[(t * t$95$1), $MachinePrecision]), $MachinePrecision] + N[(b * N[(a * 27.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(x * 2.0), $MachinePrecision] - N[(9.0 * N[(y * N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]

Derivation

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

Alternative 4: 49.0% accurate, 0.9× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} t_1 := a \cdot \left(27 \cdot b\right)\\ t_2 := -9 \cdot \left(t \cdot \left(y \cdot z\right)\right)\\ \mathbf{if}\;z \leq -1.8 \cdot 10^{-89}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;z \leq -9.4 \cdot 10^{-181}:\\ \;\;\;\;27 \cdot \left(a \cdot b\right)\\ \mathbf{elif}\;z \leq 7.2 \cdot 10^{-288}:\\ \;\;\;\;x \cdot 2\\ \mathbf{elif}\;z \leq 4.8 \cdot 10^{-182}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq 4.8 \cdot 10^{-162}:\\ \;\;\;\;x \cdot 2\\ \mathbf{elif}\;z \leq 3.1 \cdot 10^{+46}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (let* ((t_1 (* a (* 27.0 b))) (t_2 (* -9.0 (* t (* y z)))))
   (if (<= z -1.8e-89)
     t_2
     (if (<= z -9.4e-181)
       (* 27.0 (* a b))
       (if (<= z 7.2e-288)
         (* x 2.0)
         (if (<= z 4.8e-182)
           t_1
           (if (<= z 4.8e-162) (* x 2.0) (if (<= z 3.1e+46) t_1 t_2))))))))

C

assert(x < y && y < z && z < t && t < a && a < b);
double code(double x, double y, double z, double t, double a, double b) {
	double t_1 = a * (27.0 * b);
	double t_2 = -9.0 * (t * (y * z));
	double tmp;
	if (z <= -1.8e-89) {
		tmp = t_2;
	} else if (z <= -9.4e-181) {
		tmp = 27.0 * (a * b);
	} else if (z <= 7.2e-288) {
		tmp = x * 2.0;
	} else if (z <= 4.8e-182) {
		tmp = t_1;
	} else if (z <= 4.8e-162) {
		tmp = x * 2.0;
	} else if (z <= 3.1e+46) {
		tmp = t_1;
	} else {
		tmp = t_2;
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b)
    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) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = a * (27.0d0 * b)
    t_2 = (-9.0d0) * (t * (y * z))
    if (z <= (-1.8d-89)) then
        tmp = t_2
    else if (z <= (-9.4d-181)) then
        tmp = 27.0d0 * (a * b)
    else if (z <= 7.2d-288) then
        tmp = x * 2.0d0
    else if (z <= 4.8d-182) then
        tmp = t_1
    else if (z <= 4.8d-162) then
        tmp = x * 2.0d0
    else if (z <= 3.1d+46) then
        tmp = t_1
    else
        tmp = t_2
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b;
public static double code(double x, double y, double z, double t, double a, double b) {
	double t_1 = a * (27.0 * b);
	double t_2 = -9.0 * (t * (y * z));
	double tmp;
	if (z <= -1.8e-89) {
		tmp = t_2;
	} else if (z <= -9.4e-181) {
		tmp = 27.0 * (a * b);
	} else if (z <= 7.2e-288) {
		tmp = x * 2.0;
	} else if (z <= 4.8e-182) {
		tmp = t_1;
	} else if (z <= 4.8e-162) {
		tmp = x * 2.0;
	} else if (z <= 3.1e+46) {
		tmp = t_1;
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

[x, y, z, t, a, b] = sort([x, y, z, t, a, b])
def code(x, y, z, t, a, b):
	t_1 = a * (27.0 * b)
	t_2 = -9.0 * (t * (y * z))
	tmp = 0
	if z <= -1.8e-89:
		tmp = t_2
	elif z <= -9.4e-181:
		tmp = 27.0 * (a * b)
	elif z <= 7.2e-288:
		tmp = x * 2.0
	elif z <= 4.8e-182:
		tmp = t_1
	elif z <= 4.8e-162:
		tmp = x * 2.0
	elif z <= 3.1e+46:
		tmp = t_1
	else:
		tmp = t_2
	return tmp

Julia

x, y, z, t, a, b = sort([x, y, z, t, a, b])
function code(x, y, z, t, a, b)
	t_1 = Float64(a * Float64(27.0 * b))
	t_2 = Float64(-9.0 * Float64(t * Float64(y * z)))
	tmp = 0.0
	if (z <= -1.8e-89)
		tmp = t_2;
	elseif (z <= -9.4e-181)
		tmp = Float64(27.0 * Float64(a * b));
	elseif (z <= 7.2e-288)
		tmp = Float64(x * 2.0);
	elseif (z <= 4.8e-182)
		tmp = t_1;
	elseif (z <= 4.8e-162)
		tmp = Float64(x * 2.0);
	elseif (z <= 3.1e+46)
		tmp = t_1;
	else
		tmp = t_2;
	end
	return tmp
end

MATLAB

x, y, z, t, a, b = num2cell(sort([x, y, z, t, a, b])){:}
function tmp_2 = code(x, y, z, t, a, b)
	t_1 = a * (27.0 * b);
	t_2 = -9.0 * (t * (y * z));
	tmp = 0.0;
	if (z <= -1.8e-89)
		tmp = t_2;
	elseif (z <= -9.4e-181)
		tmp = 27.0 * (a * b);
	elseif (z <= 7.2e-288)
		tmp = x * 2.0;
	elseif (z <= 4.8e-182)
		tmp = t_1;
	elseif (z <= 4.8e-162)
		tmp = x * 2.0;
	elseif (z <= 3.1e+46)
		tmp = t_1;
	else
		tmp = t_2;
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_] := Block[{t$95$1 = N[(a * N[(27.0 * b), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(-9.0 * N[(t * N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -1.8e-89], t$95$2, If[LessEqual[z, -9.4e-181], N[(27.0 * N[(a * b), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 7.2e-288], N[(x * 2.0), $MachinePrecision], If[LessEqual[z, 4.8e-182], t$95$1, If[LessEqual[z, 4.8e-162], N[(x * 2.0), $MachinePrecision], If[LessEqual[z, 3.1e+46], t$95$1, t$95$2]]]]]]]]

Derivation

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

Alternative 5: 49.0% accurate, 0.9× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} t_1 := a \cdot \left(27 \cdot b\right)\\ \mathbf{if}\;z \leq -3.2 \cdot 10^{-89}:\\ \;\;\;\;t \cdot \left(-9 \cdot \left(y \cdot z\right)\right)\\ \mathbf{elif}\;z \leq -2.6 \cdot 10^{-179}:\\ \;\;\;\;27 \cdot \left(a \cdot b\right)\\ \mathbf{elif}\;z \leq 1.85 \cdot 10^{-291}:\\ \;\;\;\;x \cdot 2\\ \mathbf{elif}\;z \leq 7.4 \cdot 10^{-180}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq 6.1 \cdot 10^{-163}:\\ \;\;\;\;x \cdot 2\\ \mathbf{elif}\;z \leq 5.4 \cdot 10^{+42}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;-9 \cdot \left(t \cdot \left(y \cdot z\right)\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (let* ((t_1 (* a (* 27.0 b))))
   (if (<= z -3.2e-89)
     (* t (* -9.0 (* y z)))
     (if (<= z -2.6e-179)
       (* 27.0 (* a b))
       (if (<= z 1.85e-291)
         (* x 2.0)
         (if (<= z 7.4e-180)
           t_1
           (if (<= z 6.1e-163)
             (* x 2.0)
             (if (<= z 5.4e+42) t_1 (* -9.0 (* t (* y z)))))))))))

C

assert(x < y && y < z && z < t && t < a && a < b);
double code(double x, double y, double z, double t, double a, double b) {
	double t_1 = a * (27.0 * b);
	double tmp;
	if (z <= -3.2e-89) {
		tmp = t * (-9.0 * (y * z));
	} else if (z <= -2.6e-179) {
		tmp = 27.0 * (a * b);
	} else if (z <= 1.85e-291) {
		tmp = x * 2.0;
	} else if (z <= 7.4e-180) {
		tmp = t_1;
	} else if (z <= 6.1e-163) {
		tmp = x * 2.0;
	} else if (z <= 5.4e+42) {
		tmp = t_1;
	} else {
		tmp = -9.0 * (t * (y * z));
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b)
    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) :: t_1
    real(8) :: tmp
    t_1 = a * (27.0d0 * b)
    if (z <= (-3.2d-89)) then
        tmp = t * ((-9.0d0) * (y * z))
    else if (z <= (-2.6d-179)) then
        tmp = 27.0d0 * (a * b)
    else if (z <= 1.85d-291) then
        tmp = x * 2.0d0
    else if (z <= 7.4d-180) then
        tmp = t_1
    else if (z <= 6.1d-163) then
        tmp = x * 2.0d0
    else if (z <= 5.4d+42) then
        tmp = t_1
    else
        tmp = (-9.0d0) * (t * (y * z))
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b;
public static double code(double x, double y, double z, double t, double a, double b) {
	double t_1 = a * (27.0 * b);
	double tmp;
	if (z <= -3.2e-89) {
		tmp = t * (-9.0 * (y * z));
	} else if (z <= -2.6e-179) {
		tmp = 27.0 * (a * b);
	} else if (z <= 1.85e-291) {
		tmp = x * 2.0;
	} else if (z <= 7.4e-180) {
		tmp = t_1;
	} else if (z <= 6.1e-163) {
		tmp = x * 2.0;
	} else if (z <= 5.4e+42) {
		tmp = t_1;
	} else {
		tmp = -9.0 * (t * (y * z));
	}
	return tmp;
}

Python

[x, y, z, t, a, b] = sort([x, y, z, t, a, b])
def code(x, y, z, t, a, b):
	t_1 = a * (27.0 * b)
	tmp = 0
	if z <= -3.2e-89:
		tmp = t * (-9.0 * (y * z))
	elif z <= -2.6e-179:
		tmp = 27.0 * (a * b)
	elif z <= 1.85e-291:
		tmp = x * 2.0
	elif z <= 7.4e-180:
		tmp = t_1
	elif z <= 6.1e-163:
		tmp = x * 2.0
	elif z <= 5.4e+42:
		tmp = t_1
	else:
		tmp = -9.0 * (t * (y * z))
	return tmp

Julia

x, y, z, t, a, b = sort([x, y, z, t, a, b])
function code(x, y, z, t, a, b)
	t_1 = Float64(a * Float64(27.0 * b))
	tmp = 0.0
	if (z <= -3.2e-89)
		tmp = Float64(t * Float64(-9.0 * Float64(y * z)));
	elseif (z <= -2.6e-179)
		tmp = Float64(27.0 * Float64(a * b));
	elseif (z <= 1.85e-291)
		tmp = Float64(x * 2.0);
	elseif (z <= 7.4e-180)
		tmp = t_1;
	elseif (z <= 6.1e-163)
		tmp = Float64(x * 2.0);
	elseif (z <= 5.4e+42)
		tmp = t_1;
	else
		tmp = Float64(-9.0 * Float64(t * Float64(y * z)));
	end
	return tmp
end

MATLAB

x, y, z, t, a, b = num2cell(sort([x, y, z, t, a, b])){:}
function tmp_2 = code(x, y, z, t, a, b)
	t_1 = a * (27.0 * b);
	tmp = 0.0;
	if (z <= -3.2e-89)
		tmp = t * (-9.0 * (y * z));
	elseif (z <= -2.6e-179)
		tmp = 27.0 * (a * b);
	elseif (z <= 1.85e-291)
		tmp = x * 2.0;
	elseif (z <= 7.4e-180)
		tmp = t_1;
	elseif (z <= 6.1e-163)
		tmp = x * 2.0;
	elseif (z <= 5.4e+42)
		tmp = t_1;
	else
		tmp = -9.0 * (t * (y * z));
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_] := Block[{t$95$1 = N[(a * N[(27.0 * b), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -3.2e-89], N[(t * N[(-9.0 * N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -2.6e-179], N[(27.0 * N[(a * b), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.85e-291], N[(x * 2.0), $MachinePrecision], If[LessEqual[z, 7.4e-180], t$95$1, If[LessEqual[z, 6.1e-163], N[(x * 2.0), $MachinePrecision], If[LessEqual[z, 5.4e+42], t$95$1, N[(-9.0 * N[(t * N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]

Derivation

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

Alternative 6: 49.0% accurate, 0.9× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} t_1 := a \cdot \left(27 \cdot b\right)\\ \mathbf{if}\;z \leq -3.2 \cdot 10^{-89}:\\ \;\;\;\;t \cdot \left(z \cdot \left(y \cdot -9\right)\right)\\ \mathbf{elif}\;z \leq -9.2 \cdot 10^{-183}:\\ \;\;\;\;27 \cdot \left(a \cdot b\right)\\ \mathbf{elif}\;z \leq 3.15 \cdot 10^{-291}:\\ \;\;\;\;x \cdot 2\\ \mathbf{elif}\;z \leq 4.5 \cdot 10^{-181}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq 1.12 \cdot 10^{-162}:\\ \;\;\;\;x \cdot 2\\ \mathbf{elif}\;z \leq 6.2 \cdot 10^{+46}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;-9 \cdot \left(t \cdot \left(y \cdot z\right)\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (let* ((t_1 (* a (* 27.0 b))))
   (if (<= z -3.2e-89)
     (* t (* z (* y -9.0)))
     (if (<= z -9.2e-183)
       (* 27.0 (* a b))
       (if (<= z 3.15e-291)
         (* x 2.0)
         (if (<= z 4.5e-181)
           t_1
           (if (<= z 1.12e-162)
             (* x 2.0)
             (if (<= z 6.2e+46) t_1 (* -9.0 (* t (* y z)))))))))))

C

assert(x < y && y < z && z < t && t < a && a < b);
double code(double x, double y, double z, double t, double a, double b) {
	double t_1 = a * (27.0 * b);
	double tmp;
	if (z <= -3.2e-89) {
		tmp = t * (z * (y * -9.0));
	} else if (z <= -9.2e-183) {
		tmp = 27.0 * (a * b);
	} else if (z <= 3.15e-291) {
		tmp = x * 2.0;
	} else if (z <= 4.5e-181) {
		tmp = t_1;
	} else if (z <= 1.12e-162) {
		tmp = x * 2.0;
	} else if (z <= 6.2e+46) {
		tmp = t_1;
	} else {
		tmp = -9.0 * (t * (y * z));
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b)
    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) :: t_1
    real(8) :: tmp
    t_1 = a * (27.0d0 * b)
    if (z <= (-3.2d-89)) then
        tmp = t * (z * (y * (-9.0d0)))
    else if (z <= (-9.2d-183)) then
        tmp = 27.0d0 * (a * b)
    else if (z <= 3.15d-291) then
        tmp = x * 2.0d0
    else if (z <= 4.5d-181) then
        tmp = t_1
    else if (z <= 1.12d-162) then
        tmp = x * 2.0d0
    else if (z <= 6.2d+46) then
        tmp = t_1
    else
        tmp = (-9.0d0) * (t * (y * z))
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b;
public static double code(double x, double y, double z, double t, double a, double b) {
	double t_1 = a * (27.0 * b);
	double tmp;
	if (z <= -3.2e-89) {
		tmp = t * (z * (y * -9.0));
	} else if (z <= -9.2e-183) {
		tmp = 27.0 * (a * b);
	} else if (z <= 3.15e-291) {
		tmp = x * 2.0;
	} else if (z <= 4.5e-181) {
		tmp = t_1;
	} else if (z <= 1.12e-162) {
		tmp = x * 2.0;
	} else if (z <= 6.2e+46) {
		tmp = t_1;
	} else {
		tmp = -9.0 * (t * (y * z));
	}
	return tmp;
}

Python

[x, y, z, t, a, b] = sort([x, y, z, t, a, b])
def code(x, y, z, t, a, b):
	t_1 = a * (27.0 * b)
	tmp = 0
	if z <= -3.2e-89:
		tmp = t * (z * (y * -9.0))
	elif z <= -9.2e-183:
		tmp = 27.0 * (a * b)
	elif z <= 3.15e-291:
		tmp = x * 2.0
	elif z <= 4.5e-181:
		tmp = t_1
	elif z <= 1.12e-162:
		tmp = x * 2.0
	elif z <= 6.2e+46:
		tmp = t_1
	else:
		tmp = -9.0 * (t * (y * z))
	return tmp

Julia

x, y, z, t, a, b = sort([x, y, z, t, a, b])
function code(x, y, z, t, a, b)
	t_1 = Float64(a * Float64(27.0 * b))
	tmp = 0.0
	if (z <= -3.2e-89)
		tmp = Float64(t * Float64(z * Float64(y * -9.0)));
	elseif (z <= -9.2e-183)
		tmp = Float64(27.0 * Float64(a * b));
	elseif (z <= 3.15e-291)
		tmp = Float64(x * 2.0);
	elseif (z <= 4.5e-181)
		tmp = t_1;
	elseif (z <= 1.12e-162)
		tmp = Float64(x * 2.0);
	elseif (z <= 6.2e+46)
		tmp = t_1;
	else
		tmp = Float64(-9.0 * Float64(t * Float64(y * z)));
	end
	return tmp
end

MATLAB

x, y, z, t, a, b = num2cell(sort([x, y, z, t, a, b])){:}
function tmp_2 = code(x, y, z, t, a, b)
	t_1 = a * (27.0 * b);
	tmp = 0.0;
	if (z <= -3.2e-89)
		tmp = t * (z * (y * -9.0));
	elseif (z <= -9.2e-183)
		tmp = 27.0 * (a * b);
	elseif (z <= 3.15e-291)
		tmp = x * 2.0;
	elseif (z <= 4.5e-181)
		tmp = t_1;
	elseif (z <= 1.12e-162)
		tmp = x * 2.0;
	elseif (z <= 6.2e+46)
		tmp = t_1;
	else
		tmp = -9.0 * (t * (y * z));
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_] := Block[{t$95$1 = N[(a * N[(27.0 * b), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -3.2e-89], N[(t * N[(z * N[(y * -9.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -9.2e-183], N[(27.0 * N[(a * b), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 3.15e-291], N[(x * 2.0), $MachinePrecision], If[LessEqual[z, 4.5e-181], t$95$1, If[LessEqual[z, 1.12e-162], N[(x * 2.0), $MachinePrecision], If[LessEqual[z, 6.2e+46], t$95$1, N[(-9.0 * N[(t * N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]

Derivation

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

Alternative 7: 80.4% accurate, 0.9× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} t_1 := 27 \cdot \left(a \cdot b\right)\\ \mathbf{if}\;z \leq -2.35 \cdot 10^{-89}:\\ \;\;\;\;x \cdot 2 - 9 \cdot \left(y \cdot \left(z \cdot t\right)\right)\\ \mathbf{elif}\;z \leq 1.7 \cdot 10^{-110}:\\ \;\;\;\;x \cdot 2 + t_1\\ \mathbf{elif}\;z \leq 1.72 \cdot 10^{+44}:\\ \;\;\;\;t_1 - 9 \cdot \left(t \cdot \left(y \cdot z\right)\right)\\ \mathbf{else}:\\ \;\;\;\;x \cdot 2 + \left(t \cdot -9\right) \cdot \left(y \cdot z\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (let* ((t_1 (* 27.0 (* a b))))
   (if (<= z -2.35e-89)
     (- (* x 2.0) (* 9.0 (* y (* z t))))
     (if (<= z 1.7e-110)
       (+ (* x 2.0) t_1)
       (if (<= z 1.72e+44)
         (- t_1 (* 9.0 (* t (* y z))))
         (+ (* x 2.0) (* (* t -9.0) (* y z))))))))

C

assert(x < y && y < z && z < t && t < a && a < b);
double code(double x, double y, double z, double t, double a, double b) {
	double t_1 = 27.0 * (a * b);
	double tmp;
	if (z <= -2.35e-89) {
		tmp = (x * 2.0) - (9.0 * (y * (z * t)));
	} else if (z <= 1.7e-110) {
		tmp = (x * 2.0) + t_1;
	} else if (z <= 1.72e+44) {
		tmp = t_1 - (9.0 * (t * (y * z)));
	} else {
		tmp = (x * 2.0) + ((t * -9.0) * (y * z));
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b)
    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) :: t_1
    real(8) :: tmp
    t_1 = 27.0d0 * (a * b)
    if (z <= (-2.35d-89)) then
        tmp = (x * 2.0d0) - (9.0d0 * (y * (z * t)))
    else if (z <= 1.7d-110) then
        tmp = (x * 2.0d0) + t_1
    else if (z <= 1.72d+44) then
        tmp = t_1 - (9.0d0 * (t * (y * z)))
    else
        tmp = (x * 2.0d0) + ((t * (-9.0d0)) * (y * z))
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b;
public static double code(double x, double y, double z, double t, double a, double b) {
	double t_1 = 27.0 * (a * b);
	double tmp;
	if (z <= -2.35e-89) {
		tmp = (x * 2.0) - (9.0 * (y * (z * t)));
	} else if (z <= 1.7e-110) {
		tmp = (x * 2.0) + t_1;
	} else if (z <= 1.72e+44) {
		tmp = t_1 - (9.0 * (t * (y * z)));
	} else {
		tmp = (x * 2.0) + ((t * -9.0) * (y * z));
	}
	return tmp;
}

Python

[x, y, z, t, a, b] = sort([x, y, z, t, a, b])
def code(x, y, z, t, a, b):
	t_1 = 27.0 * (a * b)
	tmp = 0
	if z <= -2.35e-89:
		tmp = (x * 2.0) - (9.0 * (y * (z * t)))
	elif z <= 1.7e-110:
		tmp = (x * 2.0) + t_1
	elif z <= 1.72e+44:
		tmp = t_1 - (9.0 * (t * (y * z)))
	else:
		tmp = (x * 2.0) + ((t * -9.0) * (y * z))
	return tmp

Julia

x, y, z, t, a, b = sort([x, y, z, t, a, b])
function code(x, y, z, t, a, b)
	t_1 = Float64(27.0 * Float64(a * b))
	tmp = 0.0
	if (z <= -2.35e-89)
		tmp = Float64(Float64(x * 2.0) - Float64(9.0 * Float64(y * Float64(z * t))));
	elseif (z <= 1.7e-110)
		tmp = Float64(Float64(x * 2.0) + t_1);
	elseif (z <= 1.72e+44)
		tmp = Float64(t_1 - Float64(9.0 * Float64(t * Float64(y * z))));
	else
		tmp = Float64(Float64(x * 2.0) + Float64(Float64(t * -9.0) * Float64(y * z)));
	end
	return tmp
end

MATLAB

x, y, z, t, a, b = num2cell(sort([x, y, z, t, a, b])){:}
function tmp_2 = code(x, y, z, t, a, b)
	t_1 = 27.0 * (a * b);
	tmp = 0.0;
	if (z <= -2.35e-89)
		tmp = (x * 2.0) - (9.0 * (y * (z * t)));
	elseif (z <= 1.7e-110)
		tmp = (x * 2.0) + t_1;
	elseif (z <= 1.72e+44)
		tmp = t_1 - (9.0 * (t * (y * z)));
	else
		tmp = (x * 2.0) + ((t * -9.0) * (y * z));
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_] := Block[{t$95$1 = N[(27.0 * N[(a * b), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -2.35e-89], N[(N[(x * 2.0), $MachinePrecision] - N[(9.0 * N[(y * N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.7e-110], N[(N[(x * 2.0), $MachinePrecision] + t$95$1), $MachinePrecision], If[LessEqual[z, 1.72e+44], N[(t$95$1 - N[(9.0 * N[(t * N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(x * 2.0), $MachinePrecision] + N[(N[(t * -9.0), $MachinePrecision] * N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

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

Alternative 8: 80.4% accurate, 0.9× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} t_1 := 27 \cdot \left(a \cdot b\right)\\ \mathbf{if}\;z \leq -1.7 \cdot 10^{-89}:\\ \;\;\;\;x \cdot 2 - 9 \cdot \left(y \cdot \left(z \cdot t\right)\right)\\ \mathbf{elif}\;z \leq 1.8 \cdot 10^{-110}:\\ \;\;\;\;x \cdot 2 + t_1\\ \mathbf{elif}\;z \leq 2.2 \cdot 10^{+53}:\\ \;\;\;\;t_1 - t \cdot \left(9 \cdot \left(y \cdot z\right)\right)\\ \mathbf{else}:\\ \;\;\;\;x \cdot 2 + \left(t \cdot -9\right) \cdot \left(y \cdot z\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (let* ((t_1 (* 27.0 (* a b))))
   (if (<= z -1.7e-89)
     (- (* x 2.0) (* 9.0 (* y (* z t))))
     (if (<= z 1.8e-110)
       (+ (* x 2.0) t_1)
       (if (<= z 2.2e+53)
         (- t_1 (* t (* 9.0 (* y z))))
         (+ (* x 2.0) (* (* t -9.0) (* y z))))))))

C

assert(x < y && y < z && z < t && t < a && a < b);
double code(double x, double y, double z, double t, double a, double b) {
	double t_1 = 27.0 * (a * b);
	double tmp;
	if (z <= -1.7e-89) {
		tmp = (x * 2.0) - (9.0 * (y * (z * t)));
	} else if (z <= 1.8e-110) {
		tmp = (x * 2.0) + t_1;
	} else if (z <= 2.2e+53) {
		tmp = t_1 - (t * (9.0 * (y * z)));
	} else {
		tmp = (x * 2.0) + ((t * -9.0) * (y * z));
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b)
    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) :: t_1
    real(8) :: tmp
    t_1 = 27.0d0 * (a * b)
    if (z <= (-1.7d-89)) then
        tmp = (x * 2.0d0) - (9.0d0 * (y * (z * t)))
    else if (z <= 1.8d-110) then
        tmp = (x * 2.0d0) + t_1
    else if (z <= 2.2d+53) then
        tmp = t_1 - (t * (9.0d0 * (y * z)))
    else
        tmp = (x * 2.0d0) + ((t * (-9.0d0)) * (y * z))
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b;
public static double code(double x, double y, double z, double t, double a, double b) {
	double t_1 = 27.0 * (a * b);
	double tmp;
	if (z <= -1.7e-89) {
		tmp = (x * 2.0) - (9.0 * (y * (z * t)));
	} else if (z <= 1.8e-110) {
		tmp = (x * 2.0) + t_1;
	} else if (z <= 2.2e+53) {
		tmp = t_1 - (t * (9.0 * (y * z)));
	} else {
		tmp = (x * 2.0) + ((t * -9.0) * (y * z));
	}
	return tmp;
}

Python

[x, y, z, t, a, b] = sort([x, y, z, t, a, b])
def code(x, y, z, t, a, b):
	t_1 = 27.0 * (a * b)
	tmp = 0
	if z <= -1.7e-89:
		tmp = (x * 2.0) - (9.0 * (y * (z * t)))
	elif z <= 1.8e-110:
		tmp = (x * 2.0) + t_1
	elif z <= 2.2e+53:
		tmp = t_1 - (t * (9.0 * (y * z)))
	else:
		tmp = (x * 2.0) + ((t * -9.0) * (y * z))
	return tmp

Julia

x, y, z, t, a, b = sort([x, y, z, t, a, b])
function code(x, y, z, t, a, b)
	t_1 = Float64(27.0 * Float64(a * b))
	tmp = 0.0
	if (z <= -1.7e-89)
		tmp = Float64(Float64(x * 2.0) - Float64(9.0 * Float64(y * Float64(z * t))));
	elseif (z <= 1.8e-110)
		tmp = Float64(Float64(x * 2.0) + t_1);
	elseif (z <= 2.2e+53)
		tmp = Float64(t_1 - Float64(t * Float64(9.0 * Float64(y * z))));
	else
		tmp = Float64(Float64(x * 2.0) + Float64(Float64(t * -9.0) * Float64(y * z)));
	end
	return tmp
end

MATLAB

x, y, z, t, a, b = num2cell(sort([x, y, z, t, a, b])){:}
function tmp_2 = code(x, y, z, t, a, b)
	t_1 = 27.0 * (a * b);
	tmp = 0.0;
	if (z <= -1.7e-89)
		tmp = (x * 2.0) - (9.0 * (y * (z * t)));
	elseif (z <= 1.8e-110)
		tmp = (x * 2.0) + t_1;
	elseif (z <= 2.2e+53)
		tmp = t_1 - (t * (9.0 * (y * z)));
	else
		tmp = (x * 2.0) + ((t * -9.0) * (y * z));
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_] := Block[{t$95$1 = N[(27.0 * N[(a * b), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -1.7e-89], N[(N[(x * 2.0), $MachinePrecision] - N[(9.0 * N[(y * N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.8e-110], N[(N[(x * 2.0), $MachinePrecision] + t$95$1), $MachinePrecision], If[LessEqual[z, 2.2e+53], N[(t$95$1 - N[(t * N[(9.0 * N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(x * 2.0), $MachinePrecision] + N[(N[(t * -9.0), $MachinePrecision] * N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

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

Alternative 9: 97.2% accurate, 0.9× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} \mathbf{if}\;z \leq -4.4 \cdot 10^{+62}:\\ \;\;\;\;x \cdot 2 - 9 \cdot \left(y \cdot \left(z \cdot t\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(a \cdot 27\right) + \left(x \cdot 2 - t \cdot \left(9 \cdot \left(y \cdot z\right)\right)\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (if (<= z -4.4e+62)
   (- (* x 2.0) (* 9.0 (* y (* z t))))
   (+ (* b (* a 27.0)) (- (* x 2.0) (* t (* 9.0 (* y z)))))))

C

assert(x < y && y < z && z < t && t < a && a < b);
double code(double x, double y, double z, double t, double a, double b) {
	double tmp;
	if (z <= -4.4e+62) {
		tmp = (x * 2.0) - (9.0 * (y * (z * t)));
	} else {
		tmp = (b * (a * 27.0)) + ((x * 2.0) - (t * (9.0 * (y * z))));
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b)
    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) :: tmp
    if (z <= (-4.4d+62)) then
        tmp = (x * 2.0d0) - (9.0d0 * (y * (z * t)))
    else
        tmp = (b * (a * 27.0d0)) + ((x * 2.0d0) - (t * (9.0d0 * (y * z))))
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b;
public static double code(double x, double y, double z, double t, double a, double b) {
	double tmp;
	if (z <= -4.4e+62) {
		tmp = (x * 2.0) - (9.0 * (y * (z * t)));
	} else {
		tmp = (b * (a * 27.0)) + ((x * 2.0) - (t * (9.0 * (y * z))));
	}
	return tmp;
}

Python

[x, y, z, t, a, b] = sort([x, y, z, t, a, b])
def code(x, y, z, t, a, b):
	tmp = 0
	if z <= -4.4e+62:
		tmp = (x * 2.0) - (9.0 * (y * (z * t)))
	else:
		tmp = (b * (a * 27.0)) + ((x * 2.0) - (t * (9.0 * (y * z))))
	return tmp

Julia

x, y, z, t, a, b = sort([x, y, z, t, a, b])
function code(x, y, z, t, a, b)
	tmp = 0.0
	if (z <= -4.4e+62)
		tmp = Float64(Float64(x * 2.0) - Float64(9.0 * Float64(y * Float64(z * t))));
	else
		tmp = Float64(Float64(b * Float64(a * 27.0)) + Float64(Float64(x * 2.0) - Float64(t * Float64(9.0 * Float64(y * z)))));
	end
	return tmp
end

MATLAB

x, y, z, t, a, b = num2cell(sort([x, y, z, t, a, b])){:}
function tmp_2 = code(x, y, z, t, a, b)
	tmp = 0.0;
	if (z <= -4.4e+62)
		tmp = (x * 2.0) - (9.0 * (y * (z * t)));
	else
		tmp = (b * (a * 27.0)) + ((x * 2.0) - (t * (9.0 * (y * z))));
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_] := If[LessEqual[z, -4.4e+62], N[(N[(x * 2.0), $MachinePrecision] - N[(9.0 * N[(y * N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(b * N[(a * 27.0), $MachinePrecision]), $MachinePrecision] + N[(N[(x * 2.0), $MachinePrecision] - N[(t * N[(9.0 * N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

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

Alternative 10: 98.1% accurate, 0.9× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} \mathbf{if}\;z \leq 2.25 \cdot 10^{-60}:\\ \;\;\;\;\left(x \cdot 2 - \left(y \cdot 9\right) \cdot \left(z \cdot t\right)\right) + a \cdot \left(27 \cdot b\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot \left(a \cdot 27\right) + \left(x \cdot 2 - t \cdot \left(9 \cdot \left(y \cdot z\right)\right)\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (if (<= z 2.25e-60)
   (+ (- (* x 2.0) (* (* y 9.0) (* z t))) (* a (* 27.0 b)))
   (+ (* b (* a 27.0)) (- (* x 2.0) (* t (* 9.0 (* y z)))))))

C

assert(x < y && y < z && z < t && t < a && a < b);
double code(double x, double y, double z, double t, double a, double b) {
	double tmp;
	if (z <= 2.25e-60) {
		tmp = ((x * 2.0) - ((y * 9.0) * (z * t))) + (a * (27.0 * b));
	} else {
		tmp = (b * (a * 27.0)) + ((x * 2.0) - (t * (9.0 * (y * z))));
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b)
    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) :: tmp
    if (z <= 2.25d-60) then
        tmp = ((x * 2.0d0) - ((y * 9.0d0) * (z * t))) + (a * (27.0d0 * b))
    else
        tmp = (b * (a * 27.0d0)) + ((x * 2.0d0) - (t * (9.0d0 * (y * z))))
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b;
public static double code(double x, double y, double z, double t, double a, double b) {
	double tmp;
	if (z <= 2.25e-60) {
		tmp = ((x * 2.0) - ((y * 9.0) * (z * t))) + (a * (27.0 * b));
	} else {
		tmp = (b * (a * 27.0)) + ((x * 2.0) - (t * (9.0 * (y * z))));
	}
	return tmp;
}

Python

[x, y, z, t, a, b] = sort([x, y, z, t, a, b])
def code(x, y, z, t, a, b):
	tmp = 0
	if z <= 2.25e-60:
		tmp = ((x * 2.0) - ((y * 9.0) * (z * t))) + (a * (27.0 * b))
	else:
		tmp = (b * (a * 27.0)) + ((x * 2.0) - (t * (9.0 * (y * z))))
	return tmp

Julia

x, y, z, t, a, b = sort([x, y, z, t, a, b])
function code(x, y, z, t, a, b)
	tmp = 0.0
	if (z <= 2.25e-60)
		tmp = Float64(Float64(Float64(x * 2.0) - Float64(Float64(y * 9.0) * Float64(z * t))) + Float64(a * Float64(27.0 * b)));
	else
		tmp = Float64(Float64(b * Float64(a * 27.0)) + Float64(Float64(x * 2.0) - Float64(t * Float64(9.0 * Float64(y * z)))));
	end
	return tmp
end

MATLAB

x, y, z, t, a, b = num2cell(sort([x, y, z, t, a, b])){:}
function tmp_2 = code(x, y, z, t, a, b)
	tmp = 0.0;
	if (z <= 2.25e-60)
		tmp = ((x * 2.0) - ((y * 9.0) * (z * t))) + (a * (27.0 * b));
	else
		tmp = (b * (a * 27.0)) + ((x * 2.0) - (t * (9.0 * (y * z))));
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_] := If[LessEqual[z, 2.25e-60], N[(N[(N[(x * 2.0), $MachinePrecision] - N[(N[(y * 9.0), $MachinePrecision] * N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(a * N[(27.0 * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(b * N[(a * 27.0), $MachinePrecision]), $MachinePrecision] + N[(N[(x * 2.0), $MachinePrecision] - N[(t * N[(9.0 * N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

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

Alternative 11: 75.2% accurate, 1.0× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} t_1 := x \cdot 2 + 27 \cdot \left(a \cdot b\right)\\ \mathbf{if}\;z \leq -8.4 \cdot 10^{+42}:\\ \;\;\;\;z \cdot \left(y \cdot \left(t \cdot -9\right)\right)\\ \mathbf{elif}\;z \leq -4.7 \cdot 10^{-66}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq -3.7 \cdot 10^{-89}:\\ \;\;\;\;\left(t \cdot -9\right) \cdot \left(y \cdot z\right)\\ \mathbf{elif}\;z \leq 4.8 \cdot 10^{+78}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;-9 \cdot \left(t \cdot \left(y \cdot z\right)\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (let* ((t_1 (+ (* x 2.0) (* 27.0 (* a b)))))
   (if (<= z -8.4e+42)
     (* z (* y (* t -9.0)))
     (if (<= z -4.7e-66)
       t_1
       (if (<= z -3.7e-89)
         (* (* t -9.0) (* y z))
         (if (<= z 4.8e+78) t_1 (* -9.0 (* t (* y z)))))))))

C

assert(x < y && y < z && z < t && t < a && a < b);
double code(double x, double y, double z, double t, double a, double b) {
	double t_1 = (x * 2.0) + (27.0 * (a * b));
	double tmp;
	if (z <= -8.4e+42) {
		tmp = z * (y * (t * -9.0));
	} else if (z <= -4.7e-66) {
		tmp = t_1;
	} else if (z <= -3.7e-89) {
		tmp = (t * -9.0) * (y * z);
	} else if (z <= 4.8e+78) {
		tmp = t_1;
	} else {
		tmp = -9.0 * (t * (y * z));
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b)
    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) :: t_1
    real(8) :: tmp
    t_1 = (x * 2.0d0) + (27.0d0 * (a * b))
    if (z <= (-8.4d+42)) then
        tmp = z * (y * (t * (-9.0d0)))
    else if (z <= (-4.7d-66)) then
        tmp = t_1
    else if (z <= (-3.7d-89)) then
        tmp = (t * (-9.0d0)) * (y * z)
    else if (z <= 4.8d+78) then
        tmp = t_1
    else
        tmp = (-9.0d0) * (t * (y * z))
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b;
public static double code(double x, double y, double z, double t, double a, double b) {
	double t_1 = (x * 2.0) + (27.0 * (a * b));
	double tmp;
	if (z <= -8.4e+42) {
		tmp = z * (y * (t * -9.0));
	} else if (z <= -4.7e-66) {
		tmp = t_1;
	} else if (z <= -3.7e-89) {
		tmp = (t * -9.0) * (y * z);
	} else if (z <= 4.8e+78) {
		tmp = t_1;
	} else {
		tmp = -9.0 * (t * (y * z));
	}
	return tmp;
}

Python

[x, y, z, t, a, b] = sort([x, y, z, t, a, b])
def code(x, y, z, t, a, b):
	t_1 = (x * 2.0) + (27.0 * (a * b))
	tmp = 0
	if z <= -8.4e+42:
		tmp = z * (y * (t * -9.0))
	elif z <= -4.7e-66:
		tmp = t_1
	elif z <= -3.7e-89:
		tmp = (t * -9.0) * (y * z)
	elif z <= 4.8e+78:
		tmp = t_1
	else:
		tmp = -9.0 * (t * (y * z))
	return tmp

Julia

x, y, z, t, a, b = sort([x, y, z, t, a, b])
function code(x, y, z, t, a, b)
	t_1 = Float64(Float64(x * 2.0) + Float64(27.0 * Float64(a * b)))
	tmp = 0.0
	if (z <= -8.4e+42)
		tmp = Float64(z * Float64(y * Float64(t * -9.0)));
	elseif (z <= -4.7e-66)
		tmp = t_1;
	elseif (z <= -3.7e-89)
		tmp = Float64(Float64(t * -9.0) * Float64(y * z));
	elseif (z <= 4.8e+78)
		tmp = t_1;
	else
		tmp = Float64(-9.0 * Float64(t * Float64(y * z)));
	end
	return tmp
end

MATLAB

x, y, z, t, a, b = num2cell(sort([x, y, z, t, a, b])){:}
function tmp_2 = code(x, y, z, t, a, b)
	t_1 = (x * 2.0) + (27.0 * (a * b));
	tmp = 0.0;
	if (z <= -8.4e+42)
		tmp = z * (y * (t * -9.0));
	elseif (z <= -4.7e-66)
		tmp = t_1;
	elseif (z <= -3.7e-89)
		tmp = (t * -9.0) * (y * z);
	elseif (z <= 4.8e+78)
		tmp = t_1;
	else
		tmp = -9.0 * (t * (y * z));
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_] := Block[{t$95$1 = N[(N[(x * 2.0), $MachinePrecision] + N[(27.0 * N[(a * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -8.4e+42], N[(z * N[(y * N[(t * -9.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -4.7e-66], t$95$1, If[LessEqual[z, -3.7e-89], N[(N[(t * -9.0), $MachinePrecision] * N[(y * z), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 4.8e+78], t$95$1, N[(-9.0 * N[(t * N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

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

Alternative 12: 78.2% accurate, 1.1× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} \mathbf{if}\;t \leq -8.4 \cdot 10^{-23} \lor \neg \left(t \leq 9 \cdot 10^{+94}\right):\\ \;\;\;\;x \cdot 2 + \left(t \cdot -9\right) \cdot \left(y \cdot z\right)\\ \mathbf{else}:\\ \;\;\;\;x \cdot 2 + 27 \cdot \left(a \cdot b\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (if (or (<= t -8.4e-23) (not (<= t 9e+94)))
   (+ (* x 2.0) (* (* t -9.0) (* y z)))
   (+ (* x 2.0) (* 27.0 (* a b)))))

C

assert(x < y && y < z && z < t && t < a && a < b);
double code(double x, double y, double z, double t, double a, double b) {
	double tmp;
	if ((t <= -8.4e-23) || !(t <= 9e+94)) {
		tmp = (x * 2.0) + ((t * -9.0) * (y * z));
	} else {
		tmp = (x * 2.0) + (27.0 * (a * b));
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b)
    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) :: tmp
    if ((t <= (-8.4d-23)) .or. (.not. (t <= 9d+94))) then
        tmp = (x * 2.0d0) + ((t * (-9.0d0)) * (y * z))
    else
        tmp = (x * 2.0d0) + (27.0d0 * (a * b))
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b;
public static double code(double x, double y, double z, double t, double a, double b) {
	double tmp;
	if ((t <= -8.4e-23) || !(t <= 9e+94)) {
		tmp = (x * 2.0) + ((t * -9.0) * (y * z));
	} else {
		tmp = (x * 2.0) + (27.0 * (a * b));
	}
	return tmp;
}

Python

[x, y, z, t, a, b] = sort([x, y, z, t, a, b])
def code(x, y, z, t, a, b):
	tmp = 0
	if (t <= -8.4e-23) or not (t <= 9e+94):
		tmp = (x * 2.0) + ((t * -9.0) * (y * z))
	else:
		tmp = (x * 2.0) + (27.0 * (a * b))
	return tmp

Julia

x, y, z, t, a, b = sort([x, y, z, t, a, b])
function code(x, y, z, t, a, b)
	tmp = 0.0
	if ((t <= -8.4e-23) || !(t <= 9e+94))
		tmp = Float64(Float64(x * 2.0) + Float64(Float64(t * -9.0) * Float64(y * z)));
	else
		tmp = Float64(Float64(x * 2.0) + Float64(27.0 * Float64(a * b)));
	end
	return tmp
end

MATLAB

x, y, z, t, a, b = num2cell(sort([x, y, z, t, a, b])){:}
function tmp_2 = code(x, y, z, t, a, b)
	tmp = 0.0;
	if ((t <= -8.4e-23) || ~((t <= 9e+94)))
		tmp = (x * 2.0) + ((t * -9.0) * (y * z));
	else
		tmp = (x * 2.0) + (27.0 * (a * b));
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_] := If[Or[LessEqual[t, -8.4e-23], N[Not[LessEqual[t, 9e+94]], $MachinePrecision]], N[(N[(x * 2.0), $MachinePrecision] + N[(N[(t * -9.0), $MachinePrecision] * N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(x * 2.0), $MachinePrecision] + N[(27.0 * N[(a * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

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

Alternative 13: 78.2% accurate, 1.1× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} \mathbf{if}\;t \leq -9.6 \cdot 10^{-20}:\\ \;\;\;\;x \cdot 2 - 9 \cdot \left(t \cdot \left(y \cdot z\right)\right)\\ \mathbf{elif}\;t \leq 6.5 \cdot 10^{+94}:\\ \;\;\;\;x \cdot 2 + 27 \cdot \left(a \cdot b\right)\\ \mathbf{else}:\\ \;\;\;\;x \cdot 2 + \left(t \cdot -9\right) \cdot \left(y \cdot z\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (if (<= t -9.6e-20)
   (- (* x 2.0) (* 9.0 (* t (* y z))))
   (if (<= t 6.5e+94)
     (+ (* x 2.0) (* 27.0 (* a b)))
     (+ (* x 2.0) (* (* t -9.0) (* y z))))))

C

assert(x < y && y < z && z < t && t < a && a < b);
double code(double x, double y, double z, double t, double a, double b) {
	double tmp;
	if (t <= -9.6e-20) {
		tmp = (x * 2.0) - (9.0 * (t * (y * z)));
	} else if (t <= 6.5e+94) {
		tmp = (x * 2.0) + (27.0 * (a * b));
	} else {
		tmp = (x * 2.0) + ((t * -9.0) * (y * z));
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b)
    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) :: tmp
    if (t <= (-9.6d-20)) then
        tmp = (x * 2.0d0) - (9.0d0 * (t * (y * z)))
    else if (t <= 6.5d+94) then
        tmp = (x * 2.0d0) + (27.0d0 * (a * b))
    else
        tmp = (x * 2.0d0) + ((t * (-9.0d0)) * (y * z))
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b;
public static double code(double x, double y, double z, double t, double a, double b) {
	double tmp;
	if (t <= -9.6e-20) {
		tmp = (x * 2.0) - (9.0 * (t * (y * z)));
	} else if (t <= 6.5e+94) {
		tmp = (x * 2.0) + (27.0 * (a * b));
	} else {
		tmp = (x * 2.0) + ((t * -9.0) * (y * z));
	}
	return tmp;
}

Python

[x, y, z, t, a, b] = sort([x, y, z, t, a, b])
def code(x, y, z, t, a, b):
	tmp = 0
	if t <= -9.6e-20:
		tmp = (x * 2.0) - (9.0 * (t * (y * z)))
	elif t <= 6.5e+94:
		tmp = (x * 2.0) + (27.0 * (a * b))
	else:
		tmp = (x * 2.0) + ((t * -9.0) * (y * z))
	return tmp

Julia

x, y, z, t, a, b = sort([x, y, z, t, a, b])
function code(x, y, z, t, a, b)
	tmp = 0.0
	if (t <= -9.6e-20)
		tmp = Float64(Float64(x * 2.0) - Float64(9.0 * Float64(t * Float64(y * z))));
	elseif (t <= 6.5e+94)
		tmp = Float64(Float64(x * 2.0) + Float64(27.0 * Float64(a * b)));
	else
		tmp = Float64(Float64(x * 2.0) + Float64(Float64(t * -9.0) * Float64(y * z)));
	end
	return tmp
end

MATLAB

x, y, z, t, a, b = num2cell(sort([x, y, z, t, a, b])){:}
function tmp_2 = code(x, y, z, t, a, b)
	tmp = 0.0;
	if (t <= -9.6e-20)
		tmp = (x * 2.0) - (9.0 * (t * (y * z)));
	elseif (t <= 6.5e+94)
		tmp = (x * 2.0) + (27.0 * (a * b));
	else
		tmp = (x * 2.0) + ((t * -9.0) * (y * z));
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_] := If[LessEqual[t, -9.6e-20], N[(N[(x * 2.0), $MachinePrecision] - N[(9.0 * N[(t * N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 6.5e+94], N[(N[(x * 2.0), $MachinePrecision] + N[(27.0 * N[(a * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(x * 2.0), $MachinePrecision] + N[(N[(t * -9.0), $MachinePrecision] * N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]

Derivation

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

Alternative 14: 79.1% accurate, 1.1× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} \mathbf{if}\;z \leq -3.7 \cdot 10^{-89}:\\ \;\;\;\;x \cdot 2 - 9 \cdot \left(y \cdot \left(z \cdot t\right)\right)\\ \mathbf{elif}\;z \leq 4.8 \cdot 10^{+49}:\\ \;\;\;\;x \cdot 2 + 27 \cdot \left(a \cdot b\right)\\ \mathbf{else}:\\ \;\;\;\;x \cdot 2 + \left(t \cdot -9\right) \cdot \left(y \cdot z\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (if (<= z -3.7e-89)
   (- (* x 2.0) (* 9.0 (* y (* z t))))
   (if (<= z 4.8e+49)
     (+ (* x 2.0) (* 27.0 (* a b)))
     (+ (* x 2.0) (* (* t -9.0) (* y z))))))

C

assert(x < y && y < z && z < t && t < a && a < b);
double code(double x, double y, double z, double t, double a, double b) {
	double tmp;
	if (z <= -3.7e-89) {
		tmp = (x * 2.0) - (9.0 * (y * (z * t)));
	} else if (z <= 4.8e+49) {
		tmp = (x * 2.0) + (27.0 * (a * b));
	} else {
		tmp = (x * 2.0) + ((t * -9.0) * (y * z));
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b)
    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) :: tmp
    if (z <= (-3.7d-89)) then
        tmp = (x * 2.0d0) - (9.0d0 * (y * (z * t)))
    else if (z <= 4.8d+49) then
        tmp = (x * 2.0d0) + (27.0d0 * (a * b))
    else
        tmp = (x * 2.0d0) + ((t * (-9.0d0)) * (y * z))
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b;
public static double code(double x, double y, double z, double t, double a, double b) {
	double tmp;
	if (z <= -3.7e-89) {
		tmp = (x * 2.0) - (9.0 * (y * (z * t)));
	} else if (z <= 4.8e+49) {
		tmp = (x * 2.0) + (27.0 * (a * b));
	} else {
		tmp = (x * 2.0) + ((t * -9.0) * (y * z));
	}
	return tmp;
}

Python

[x, y, z, t, a, b] = sort([x, y, z, t, a, b])
def code(x, y, z, t, a, b):
	tmp = 0
	if z <= -3.7e-89:
		tmp = (x * 2.0) - (9.0 * (y * (z * t)))
	elif z <= 4.8e+49:
		tmp = (x * 2.0) + (27.0 * (a * b))
	else:
		tmp = (x * 2.0) + ((t * -9.0) * (y * z))
	return tmp

Julia

x, y, z, t, a, b = sort([x, y, z, t, a, b])
function code(x, y, z, t, a, b)
	tmp = 0.0
	if (z <= -3.7e-89)
		tmp = Float64(Float64(x * 2.0) - Float64(9.0 * Float64(y * Float64(z * t))));
	elseif (z <= 4.8e+49)
		tmp = Float64(Float64(x * 2.0) + Float64(27.0 * Float64(a * b)));
	else
		tmp = Float64(Float64(x * 2.0) + Float64(Float64(t * -9.0) * Float64(y * z)));
	end
	return tmp
end

MATLAB

x, y, z, t, a, b = num2cell(sort([x, y, z, t, a, b])){:}
function tmp_2 = code(x, y, z, t, a, b)
	tmp = 0.0;
	if (z <= -3.7e-89)
		tmp = (x * 2.0) - (9.0 * (y * (z * t)));
	elseif (z <= 4.8e+49)
		tmp = (x * 2.0) + (27.0 * (a * b));
	else
		tmp = (x * 2.0) + ((t * -9.0) * (y * z));
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_] := If[LessEqual[z, -3.7e-89], N[(N[(x * 2.0), $MachinePrecision] - N[(9.0 * N[(y * N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 4.8e+49], N[(N[(x * 2.0), $MachinePrecision] + N[(27.0 * N[(a * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(x * 2.0), $MachinePrecision] + N[(N[(t * -9.0), $MachinePrecision] * N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]

Derivation

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

Alternative 15: 47.0% accurate, 1.9× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} \mathbf{if}\;a \leq -380 \lor \neg \left(a \leq 1.6 \cdot 10^{-100}\right):\\ \;\;\;\;27 \cdot \left(a \cdot b\right)\\ \mathbf{else}:\\ \;\;\;\;x \cdot 2\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (if (or (<= a -380.0) (not (<= a 1.6e-100))) (* 27.0 (* a b)) (* x 2.0)))

C

assert(x < y && y < z && z < t && t < a && a < b);
double code(double x, double y, double z, double t, double a, double b) {
	double tmp;
	if ((a <= -380.0) || !(a <= 1.6e-100)) {
		tmp = 27.0 * (a * b);
	} else {
		tmp = x * 2.0;
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b)
    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) :: tmp
    if ((a <= (-380.0d0)) .or. (.not. (a <= 1.6d-100))) then
        tmp = 27.0d0 * (a * b)
    else
        tmp = x * 2.0d0
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b;
public static double code(double x, double y, double z, double t, double a, double b) {
	double tmp;
	if ((a <= -380.0) || !(a <= 1.6e-100)) {
		tmp = 27.0 * (a * b);
	} else {
		tmp = x * 2.0;
	}
	return tmp;
}

Python

[x, y, z, t, a, b] = sort([x, y, z, t, a, b])
def code(x, y, z, t, a, b):
	tmp = 0
	if (a <= -380.0) or not (a <= 1.6e-100):
		tmp = 27.0 * (a * b)
	else:
		tmp = x * 2.0
	return tmp

Julia

x, y, z, t, a, b = sort([x, y, z, t, a, b])
function code(x, y, z, t, a, b)
	tmp = 0.0
	if ((a <= -380.0) || !(a <= 1.6e-100))
		tmp = Float64(27.0 * Float64(a * b));
	else
		tmp = Float64(x * 2.0);
	end
	return tmp
end

MATLAB

x, y, z, t, a, b = num2cell(sort([x, y, z, t, a, b])){:}
function tmp_2 = code(x, y, z, t, a, b)
	tmp = 0.0;
	if ((a <= -380.0) || ~((a <= 1.6e-100)))
		tmp = 27.0 * (a * b);
	else
		tmp = x * 2.0;
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_] := If[Or[LessEqual[a, -380.0], N[Not[LessEqual[a, 1.6e-100]], $MachinePrecision]], N[(27.0 * N[(a * b), $MachinePrecision]), $MachinePrecision], N[(x * 2.0), $MachinePrecision]]

Derivation

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

Alternative 16: 47.1% accurate, 1.9× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ \begin{array}{l} \mathbf{if}\;a \leq -135:\\ \;\;\;\;a \cdot \left(27 \cdot b\right)\\ \mathbf{elif}\;a \leq 1.75 \cdot 10^{-92}:\\ \;\;\;\;x \cdot 2\\ \mathbf{else}:\\ \;\;\;\;27 \cdot \left(a \cdot b\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b)
 :precision binary64
 (if (<= a -135.0)
   (* a (* 27.0 b))
   (if (<= a 1.75e-92) (* x 2.0) (* 27.0 (* a b)))))

C

assert(x < y && y < z && z < t && t < a && a < b);
double code(double x, double y, double z, double t, double a, double b) {
	double tmp;
	if (a <= -135.0) {
		tmp = a * (27.0 * b);
	} else if (a <= 1.75e-92) {
		tmp = x * 2.0;
	} else {
		tmp = 27.0 * (a * b);
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b)
    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) :: tmp
    if (a <= (-135.0d0)) then
        tmp = a * (27.0d0 * b)
    else if (a <= 1.75d-92) then
        tmp = x * 2.0d0
    else
        tmp = 27.0d0 * (a * b)
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b;
public static double code(double x, double y, double z, double t, double a, double b) {
	double tmp;
	if (a <= -135.0) {
		tmp = a * (27.0 * b);
	} else if (a <= 1.75e-92) {
		tmp = x * 2.0;
	} else {
		tmp = 27.0 * (a * b);
	}
	return tmp;
}

Python

[x, y, z, t, a, b] = sort([x, y, z, t, a, b])
def code(x, y, z, t, a, b):
	tmp = 0
	if a <= -135.0:
		tmp = a * (27.0 * b)
	elif a <= 1.75e-92:
		tmp = x * 2.0
	else:
		tmp = 27.0 * (a * b)
	return tmp

Julia

x, y, z, t, a, b = sort([x, y, z, t, a, b])
function code(x, y, z, t, a, b)
	tmp = 0.0
	if (a <= -135.0)
		tmp = Float64(a * Float64(27.0 * b));
	elseif (a <= 1.75e-92)
		tmp = Float64(x * 2.0);
	else
		tmp = Float64(27.0 * Float64(a * b));
	end
	return tmp
end

MATLAB

x, y, z, t, a, b = num2cell(sort([x, y, z, t, a, b])){:}
function tmp_2 = code(x, y, z, t, a, b)
	tmp = 0.0;
	if (a <= -135.0)
		tmp = a * (27.0 * b);
	elseif (a <= 1.75e-92)
		tmp = x * 2.0;
	else
		tmp = 27.0 * (a * b);
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_] := If[LessEqual[a, -135.0], N[(a * N[(27.0 * b), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 1.75e-92], N[(x * 2.0), $MachinePrecision], N[(27.0 * N[(a * b), $MachinePrecision]), $MachinePrecision]]]

Derivation

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

Alternative 17: 30.4% accurate, 5.7× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b] = \mathsf{sort}([x, y, z, t, a, b])\\ \\ x \cdot 2 \end{array} \]

FPCore

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
(FPCore (x y z t a b) :precision binary64 (* x 2.0))

C

assert(x < y && y < z && z < t && t < a && a < b);
double code(double x, double y, double z, double t, double a, double b) {
	return x * 2.0;
}

Fortran

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b)
    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
    code = x * 2.0d0
end function

Java

assert x < y && y < z && z < t && t < a && a < b;
public static double code(double x, double y, double z, double t, double a, double b) {
	return x * 2.0;
}

Python

[x, y, z, t, a, b] = sort([x, y, z, t, a, b])
def code(x, y, z, t, a, b):
	return x * 2.0

Julia

x, y, z, t, a, b = sort([x, y, z, t, a, b])
function code(x, y, z, t, a, b)
	return Float64(x * 2.0)
end

MATLAB

x, y, z, t, a, b = num2cell(sort([x, y, z, t, a, b])){:}
function tmp = code(x, y, z, t, a, b)
	tmp = x * 2.0;
end

Wolfram

NOTE: x, y, z, t, a, and b should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_] := N[(x * 2.0), $MachinePrecision]

Derivation

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

Developer target: 95.3% accurate, 0.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y < 7.590524218811189 \cdot 10^{-161}:\\ \;\;\;\;\left(x \cdot 2 - \left(\left(y \cdot 9\right) \cdot z\right) \cdot t\right) + a \cdot \left(27 \cdot b\right)\\ \mathbf{else}:\\ \;\;\;\;\left(x \cdot 2 - 9 \cdot \left(y \cdot \left(t \cdot z\right)\right)\right) + \left(a \cdot 27\right) \cdot b\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b)
 :precision binary64
 (if (< y 7.590524218811189e-161)
   (+ (- (* x 2.0) (* (* (* y 9.0) z) t)) (* a (* 27.0 b)))
   (+ (- (* x 2.0) (* 9.0 (* y (* t z)))) (* (* a 27.0) b))))

C

double code(double x, double y, double z, double t, double a, double b) {
	double tmp;
	if (y < 7.590524218811189e-161) {
		tmp = ((x * 2.0) - (((y * 9.0) * z) * t)) + (a * (27.0 * b));
	} else {
		tmp = ((x * 2.0) - (9.0 * (y * (t * z)))) + ((a * 27.0) * b);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b)
    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) :: tmp
    if (y < 7.590524218811189d-161) then
        tmp = ((x * 2.0d0) - (((y * 9.0d0) * z) * t)) + (a * (27.0d0 * b))
    else
        tmp = ((x * 2.0d0) - (9.0d0 * (y * (t * z)))) + ((a * 27.0d0) * 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 tmp;
	if (y < 7.590524218811189e-161) {
		tmp = ((x * 2.0) - (((y * 9.0) * z) * t)) + (a * (27.0 * b));
	} else {
		tmp = ((x * 2.0) - (9.0 * (y * (t * z)))) + ((a * 27.0) * b);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b):
	tmp = 0
	if y < 7.590524218811189e-161:
		tmp = ((x * 2.0) - (((y * 9.0) * z) * t)) + (a * (27.0 * b))
	else:
		tmp = ((x * 2.0) - (9.0 * (y * (t * z)))) + ((a * 27.0) * b)
	return tmp

Julia

function code(x, y, z, t, a, b)
	tmp = 0.0
	if (y < 7.590524218811189e-161)
		tmp = Float64(Float64(Float64(x * 2.0) - Float64(Float64(Float64(y * 9.0) * z) * t)) + Float64(a * Float64(27.0 * b)));
	else
		tmp = Float64(Float64(Float64(x * 2.0) - Float64(9.0 * Float64(y * Float64(t * z)))) + Float64(Float64(a * 27.0) * b));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b)
	tmp = 0.0;
	if (y < 7.590524218811189e-161)
		tmp = ((x * 2.0) - (((y * 9.0) * z) * t)) + (a * (27.0 * b));
	else
		tmp = ((x * 2.0) - (9.0 * (y * (t * z)))) + ((a * 27.0) * b);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_] := If[Less[y, 7.590524218811189e-161], N[(N[(N[(x * 2.0), $MachinePrecision] - N[(N[(N[(y * 9.0), $MachinePrecision] * z), $MachinePrecision] * t), $MachinePrecision]), $MachinePrecision] + N[(a * N[(27.0 * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(N[(x * 2.0), $MachinePrecision] - N[(9.0 * N[(y * N[(t * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(a * 27.0), $MachinePrecision] * b), $MachinePrecision]), $MachinePrecision]]

Reproduce

herbie shell --seed 2023364 
(FPCore (x y z t a b)
  :name "Diagrams.Solve.Polynomial:cubForm  from diagrams-solve-0.1, A"
  :precision binary64

  :herbie-target
  (if (< y 7.590524218811189e-161) (+ (- (* x 2.0) (* (* (* y 9.0) z) t)) (* a (* 27.0 b))) (+ (- (* x 2.0) (* 9.0 (* y (* t z)))) (* (* a 27.0) b)))

  (+ (- (* x 2.0) (* (* (* y 9.0) z) t)) (* (* a 27.0) b)))