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

Percentage Accurate: 85.4% → 89.0%

Time: 24.8s

Alternatives: 20

Speedup: 0.5×

• 49.6% of points produce a very large (infinite) output. You may want to add a precondition.

Specification

Math

\[\begin{array}{l} \\ \left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \end{array} \]

FPCore

(FPCore (x y z t a b c i j k)
 :precision binary64
 (-
  (-
   (+ (- (* (* (* (* x 18.0) y) z) t) (* (* a 4.0) t)) (* b c))
   (* (* x 4.0) i))
  (* (* j 27.0) k)))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	return (((((((x * 18.0) * y) * z) * t) - ((a * 4.0) * t)) + (b * c)) - ((x * 4.0) * i)) - ((j * 27.0) * k);
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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
    code = (((((((x * 18.0d0) * y) * z) * t) - ((a * 4.0d0) * t)) + (b * c)) - ((x * 4.0d0) * i)) - ((j * 27.0d0) * k)
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) {
	return (((((((x * 18.0) * y) * z) * t) - ((a * 4.0) * t)) + (b * c)) - ((x * 4.0) * i)) - ((j * 27.0) * k);
}

Python

def code(x, y, z, t, a, b, c, i, j, k):
	return (((((((x * 18.0) * y) * z) * t) - ((a * 4.0) * t)) + (b * c)) - ((x * 4.0) * i)) - ((j * 27.0) * k)

Julia

function code(x, y, z, t, a, b, c, i, j, k)
	return Float64(Float64(Float64(Float64(Float64(Float64(Float64(Float64(x * 18.0) * y) * z) * t) - Float64(Float64(a * 4.0) * t)) + Float64(b * c)) - Float64(Float64(x * 4.0) * i)) - Float64(Float64(j * 27.0) * k))
end

MATLAB

function tmp = code(x, y, z, t, a, b, c, i, j, k)
	tmp = (((((((x * 18.0) * y) * z) * t) - ((a * 4.0) * t)) + (b * c)) - ((x * 4.0) * i)) - ((j * 27.0) * k);
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := N[(N[(N[(N[(N[(N[(N[(N[(x * 18.0), $MachinePrecision] * y), $MachinePrecision] * z), $MachinePrecision] * t), $MachinePrecision] - N[(N[(a * 4.0), $MachinePrecision] * t), $MachinePrecision]), $MachinePrecision] + N[(b * c), $MachinePrecision]), $MachinePrecision] - N[(N[(x * 4.0), $MachinePrecision] * i), $MachinePrecision]), $MachinePrecision] - N[(N[(j * 27.0), $MachinePrecision] * k), $MachinePrecision]), $MachinePrecision]

Initial Program: 85.4% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ \left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - \left(a \cdot 4\right) \cdot t\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \end{array} \]

FPCore

(FPCore (x y z t a b c i j k)
 :precision binary64
 (-
  (-
   (+ (- (* (* (* (* x 18.0) y) z) t) (* (* a 4.0) t)) (* b c))
   (* (* x 4.0) i))
  (* (* j 27.0) k)))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	return (((((((x * 18.0) * y) * z) * t) - ((a * 4.0) * t)) + (b * c)) - ((x * 4.0) * i)) - ((j * 27.0) * k);
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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
    code = (((((((x * 18.0d0) * y) * z) * t) - ((a * 4.0d0) * t)) + (b * c)) - ((x * 4.0d0) * i)) - ((j * 27.0d0) * k)
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) {
	return (((((((x * 18.0) * y) * z) * t) - ((a * 4.0) * t)) + (b * c)) - ((x * 4.0) * i)) - ((j * 27.0) * k);
}

Python

def code(x, y, z, t, a, b, c, i, j, k):
	return (((((((x * 18.0) * y) * z) * t) - ((a * 4.0) * t)) + (b * c)) - ((x * 4.0) * i)) - ((j * 27.0) * k)

Julia

function code(x, y, z, t, a, b, c, i, j, k)
	return Float64(Float64(Float64(Float64(Float64(Float64(Float64(Float64(x * 18.0) * y) * z) * t) - Float64(Float64(a * 4.0) * t)) + Float64(b * c)) - Float64(Float64(x * 4.0) * i)) - Float64(Float64(j * 27.0) * k))
end

MATLAB

function tmp = code(x, y, z, t, a, b, c, i, j, k)
	tmp = (((((((x * 18.0) * y) * z) * t) - ((a * 4.0) * t)) + (b * c)) - ((x * 4.0) * i)) - ((j * 27.0) * k);
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := N[(N[(N[(N[(N[(N[(N[(N[(x * 18.0), $MachinePrecision] * y), $MachinePrecision] * z), $MachinePrecision] * t), $MachinePrecision] - N[(N[(a * 4.0), $MachinePrecision] * t), $MachinePrecision]), $MachinePrecision] + N[(b * c), $MachinePrecision]), $MachinePrecision] - N[(N[(x * 4.0), $MachinePrecision] * i), $MachinePrecision]), $MachinePrecision] - N[(N[(j * 27.0), $MachinePrecision] * k), $MachinePrecision]), $MachinePrecision]

Alternative 1: 89.0% accurate, 0.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;\left(\left(\left(\left(\left(\left(x \cdot 18\right) \cdot y\right) \cdot z\right) \cdot t - t \cdot \left(a \cdot 4\right)\right) + b \cdot c\right) - \left(x \cdot 4\right) \cdot i\right) - \left(j \cdot 27\right) \cdot k \leq \infty:\\ \;\;\;\;\left(b \cdot c + x \cdot \left(18 \cdot \left(t \cdot \left(y \cdot z\right)\right) - 4 \cdot i\right)\right) - \left(4 \cdot \left(t \cdot a\right) + 27 \cdot \left(j \cdot k\right)\right)\\ \mathbf{else}:\\ \;\;\;\;18 \cdot \left(\left(y \cdot z\right) \cdot \left(x \cdot t\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k)
 :precision binary64
 (if (<=
      (-
       (-
        (+ (- (* (* (* (* x 18.0) y) z) t) (* t (* a 4.0))) (* b c))
        (* (* x 4.0) i))
       (* (* j 27.0) k))
      INFINITY)
   (-
    (+ (* b c) (* x (- (* 18.0 (* t (* y z))) (* 4.0 i))))
    (+ (* 4.0 (* t a)) (* 27.0 (* j k))))
   (* 18.0 (* (* y z) (* x t)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double tmp;
	if (((((((((x * 18.0) * y) * z) * t) - (t * (a * 4.0))) + (b * c)) - ((x * 4.0) * i)) - ((j * 27.0) * k)) <= ((double) INFINITY)) {
		tmp = ((b * c) + (x * ((18.0 * (t * (y * z))) - (4.0 * i)))) - ((4.0 * (t * a)) + (27.0 * (j * k)));
	} else {
		tmp = 18.0 * ((y * z) * (x * t));
	}
	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 tmp;
	if (((((((((x * 18.0) * y) * z) * t) - (t * (a * 4.0))) + (b * c)) - ((x * 4.0) * i)) - ((j * 27.0) * k)) <= Double.POSITIVE_INFINITY) {
		tmp = ((b * c) + (x * ((18.0 * (t * (y * z))) - (4.0 * i)))) - ((4.0 * (t * a)) + (27.0 * (j * k)));
	} else {
		tmp = 18.0 * ((y * z) * (x * t));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k):
	tmp = 0
	if ((((((((x * 18.0) * y) * z) * t) - (t * (a * 4.0))) + (b * c)) - ((x * 4.0) * i)) - ((j * 27.0) * k)) <= math.inf:
		tmp = ((b * c) + (x * ((18.0 * (t * (y * z))) - (4.0 * i)))) - ((4.0 * (t * a)) + (27.0 * (j * k)))
	else:
		tmp = 18.0 * ((y * z) * (x * t))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k)
	tmp = 0.0
	if (Float64(Float64(Float64(Float64(Float64(Float64(Float64(Float64(x * 18.0) * y) * z) * t) - Float64(t * Float64(a * 4.0))) + Float64(b * c)) - Float64(Float64(x * 4.0) * i)) - Float64(Float64(j * 27.0) * k)) <= Inf)
		tmp = Float64(Float64(Float64(b * c) + Float64(x * Float64(Float64(18.0 * Float64(t * Float64(y * z))) - Float64(4.0 * i)))) - Float64(Float64(4.0 * Float64(t * a)) + Float64(27.0 * Float64(j * k))));
	else
		tmp = Float64(18.0 * Float64(Float64(y * z) * Float64(x * t)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	tmp = 0.0;
	if (((((((((x * 18.0) * y) * z) * t) - (t * (a * 4.0))) + (b * c)) - ((x * 4.0) * i)) - ((j * 27.0) * k)) <= Inf)
		tmp = ((b * c) + (x * ((18.0 * (t * (y * z))) - (4.0 * i)))) - ((4.0 * (t * a)) + (27.0 * (j * k)));
	else
		tmp = 18.0 * ((y * z) * (x * t));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := If[LessEqual[N[(N[(N[(N[(N[(N[(N[(N[(x * 18.0), $MachinePrecision] * y), $MachinePrecision] * z), $MachinePrecision] * t), $MachinePrecision] - N[(t * N[(a * 4.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(b * c), $MachinePrecision]), $MachinePrecision] - N[(N[(x * 4.0), $MachinePrecision] * i), $MachinePrecision]), $MachinePrecision] - N[(N[(j * 27.0), $MachinePrecision] * k), $MachinePrecision]), $MachinePrecision], Infinity], N[(N[(N[(b * c), $MachinePrecision] + N[(x * N[(N[(18.0 * N[(t * N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(4.0 * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(4.0 * N[(t * a), $MachinePrecision]), $MachinePrecision] + N[(27.0 * N[(j * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(18.0 * N[(N[(y * z), $MachinePrecision] * N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

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

Alternative 2: 36.0% accurate, 0.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(k \cdot -27\right)\\ t_2 := 18 \cdot \left(t \cdot \left(y \cdot \left(x \cdot z\right)\right)\right)\\ \mathbf{if}\;b \cdot c \leq -1.65 \cdot 10^{+189}:\\ \;\;\;\;b \cdot c\\ \mathbf{elif}\;b \cdot c \leq -9.5 \cdot 10^{+43}:\\ \;\;\;\;k \cdot \left(j \cdot -27\right)\\ \mathbf{elif}\;b \cdot c \leq -1.35 \cdot 10^{-84}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;b \cdot c \leq -8.5 \cdot 10^{-208}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;b \cdot c \leq 6 \cdot 10^{-181}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;b \cdot c \leq 2.2 \cdot 10^{-32}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;b \cdot c \leq 3.8 \cdot 10^{+38}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;b \cdot c \leq 2.5 \cdot 10^{+77}:\\ \;\;\;\;\left(j \cdot k\right) \cdot -27\\ \mathbf{else}:\\ \;\;\;\;b \cdot c\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k)
 :precision binary64
 (let* ((t_1 (* j (* k -27.0))) (t_2 (* 18.0 (* t (* y (* x z))))))
   (if (<= (* b c) -1.65e+189)
     (* b c)
     (if (<= (* b c) -9.5e+43)
       (* k (* j -27.0))
       (if (<= (* b c) -1.35e-84)
         t_2
         (if (<= (* b c) -8.5e-208)
           t_1
           (if (<= (* b c) 6e-181)
             t_2
             (if (<= (* b c) 2.2e-32)
               t_1
               (if (<= (* b c) 3.8e+38)
                 t_2
                 (if (<= (* b c) 2.5e+77) (* (* j k) -27.0) (* b c)))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double t_1 = j * (k * -27.0);
	double t_2 = 18.0 * (t * (y * (x * z)));
	double tmp;
	if ((b * c) <= -1.65e+189) {
		tmp = b * c;
	} else if ((b * c) <= -9.5e+43) {
		tmp = k * (j * -27.0);
	} else if ((b * c) <= -1.35e-84) {
		tmp = t_2;
	} else if ((b * c) <= -8.5e-208) {
		tmp = t_1;
	} else if ((b * c) <= 6e-181) {
		tmp = t_2;
	} else if ((b * c) <= 2.2e-32) {
		tmp = t_1;
	} else if ((b * c) <= 3.8e+38) {
		tmp = t_2;
	} else if ((b * c) <= 2.5e+77) {
		tmp = (j * k) * -27.0;
	} else {
		tmp = b * c;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = j * (k * (-27.0d0))
    t_2 = 18.0d0 * (t * (y * (x * z)))
    if ((b * c) <= (-1.65d+189)) then
        tmp = b * c
    else if ((b * c) <= (-9.5d+43)) then
        tmp = k * (j * (-27.0d0))
    else if ((b * c) <= (-1.35d-84)) then
        tmp = t_2
    else if ((b * c) <= (-8.5d-208)) then
        tmp = t_1
    else if ((b * c) <= 6d-181) then
        tmp = t_2
    else if ((b * c) <= 2.2d-32) then
        tmp = t_1
    else if ((b * c) <= 3.8d+38) then
        tmp = t_2
    else if ((b * c) <= 2.5d+77) then
        tmp = (j * k) * (-27.0d0)
    else
        tmp = b * c
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double t_1 = j * (k * -27.0);
	double t_2 = 18.0 * (t * (y * (x * z)));
	double tmp;
	if ((b * c) <= -1.65e+189) {
		tmp = b * c;
	} else if ((b * c) <= -9.5e+43) {
		tmp = k * (j * -27.0);
	} else if ((b * c) <= -1.35e-84) {
		tmp = t_2;
	} else if ((b * c) <= -8.5e-208) {
		tmp = t_1;
	} else if ((b * c) <= 6e-181) {
		tmp = t_2;
	} else if ((b * c) <= 2.2e-32) {
		tmp = t_1;
	} else if ((b * c) <= 3.8e+38) {
		tmp = t_2;
	} else if ((b * c) <= 2.5e+77) {
		tmp = (j * k) * -27.0;
	} else {
		tmp = b * c;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k):
	t_1 = j * (k * -27.0)
	t_2 = 18.0 * (t * (y * (x * z)))
	tmp = 0
	if (b * c) <= -1.65e+189:
		tmp = b * c
	elif (b * c) <= -9.5e+43:
		tmp = k * (j * -27.0)
	elif (b * c) <= -1.35e-84:
		tmp = t_2
	elif (b * c) <= -8.5e-208:
		tmp = t_1
	elif (b * c) <= 6e-181:
		tmp = t_2
	elif (b * c) <= 2.2e-32:
		tmp = t_1
	elif (b * c) <= 3.8e+38:
		tmp = t_2
	elif (b * c) <= 2.5e+77:
		tmp = (j * k) * -27.0
	else:
		tmp = b * c
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k)
	t_1 = Float64(j * Float64(k * -27.0))
	t_2 = Float64(18.0 * Float64(t * Float64(y * Float64(x * z))))
	tmp = 0.0
	if (Float64(b * c) <= -1.65e+189)
		tmp = Float64(b * c);
	elseif (Float64(b * c) <= -9.5e+43)
		tmp = Float64(k * Float64(j * -27.0));
	elseif (Float64(b * c) <= -1.35e-84)
		tmp = t_2;
	elseif (Float64(b * c) <= -8.5e-208)
		tmp = t_1;
	elseif (Float64(b * c) <= 6e-181)
		tmp = t_2;
	elseif (Float64(b * c) <= 2.2e-32)
		tmp = t_1;
	elseif (Float64(b * c) <= 3.8e+38)
		tmp = t_2;
	elseif (Float64(b * c) <= 2.5e+77)
		tmp = Float64(Float64(j * k) * -27.0);
	else
		tmp = Float64(b * c);
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	t_1 = j * (k * -27.0);
	t_2 = 18.0 * (t * (y * (x * z)));
	tmp = 0.0;
	if ((b * c) <= -1.65e+189)
		tmp = b * c;
	elseif ((b * c) <= -9.5e+43)
		tmp = k * (j * -27.0);
	elseif ((b * c) <= -1.35e-84)
		tmp = t_2;
	elseif ((b * c) <= -8.5e-208)
		tmp = t_1;
	elseif ((b * c) <= 6e-181)
		tmp = t_2;
	elseif ((b * c) <= 2.2e-32)
		tmp = t_1;
	elseif ((b * c) <= 3.8e+38)
		tmp = t_2;
	elseif ((b * c) <= 2.5e+77)
		tmp = (j * k) * -27.0;
	else
		tmp = b * c;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := Block[{t$95$1 = N[(j * N[(k * -27.0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(18.0 * N[(t * N[(y * N[(x * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[(b * c), $MachinePrecision], -1.65e+189], N[(b * c), $MachinePrecision], If[LessEqual[N[(b * c), $MachinePrecision], -9.5e+43], N[(k * N[(j * -27.0), $MachinePrecision]), $MachinePrecision], If[LessEqual[N[(b * c), $MachinePrecision], -1.35e-84], t$95$2, If[LessEqual[N[(b * c), $MachinePrecision], -8.5e-208], t$95$1, If[LessEqual[N[(b * c), $MachinePrecision], 6e-181], t$95$2, If[LessEqual[N[(b * c), $MachinePrecision], 2.2e-32], t$95$1, If[LessEqual[N[(b * c), $MachinePrecision], 3.8e+38], t$95$2, If[LessEqual[N[(b * c), $MachinePrecision], 2.5e+77], N[(N[(j * k), $MachinePrecision] * -27.0), $MachinePrecision], N[(b * c), $MachinePrecision]]]]]]]]]]]

Derivation

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

Alternative 3: 36.0% accurate, 0.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(k \cdot -27\right)\\ t_2 := 18 \cdot \left(\left(y \cdot z\right) \cdot \left(x \cdot t\right)\right)\\ \mathbf{if}\;b \cdot c \leq -4.9 \cdot 10^{+182}:\\ \;\;\;\;b \cdot c\\ \mathbf{elif}\;b \cdot c \leq -1.7 \cdot 10^{+44}:\\ \;\;\;\;k \cdot \left(j \cdot -27\right)\\ \mathbf{elif}\;b \cdot c \leq -7.6 \cdot 10^{-85}:\\ \;\;\;\;18 \cdot \left(t \cdot \left(y \cdot \left(x \cdot z\right)\right)\right)\\ \mathbf{elif}\;b \cdot c \leq -1.85 \cdot 10^{-193}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;b \cdot c \leq 3.4 \cdot 10^{-180}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;b \cdot c \leq 2.4 \cdot 10^{-32}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;b \cdot c \leq 1.6 \cdot 10^{+103}:\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;b \cdot c\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k)
 :precision binary64
 (let* ((t_1 (* j (* k -27.0))) (t_2 (* 18.0 (* (* y z) (* x t)))))
   (if (<= (* b c) -4.9e+182)
     (* b c)
     (if (<= (* b c) -1.7e+44)
       (* k (* j -27.0))
       (if (<= (* b c) -7.6e-85)
         (* 18.0 (* t (* y (* x z))))
         (if (<= (* b c) -1.85e-193)
           t_1
           (if (<= (* b c) 3.4e-180)
             t_2
             (if (<= (* b c) 2.4e-32)
               t_1
               (if (<= (* b c) 1.6e+103) t_2 (* b c))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double t_1 = j * (k * -27.0);
	double t_2 = 18.0 * ((y * z) * (x * t));
	double tmp;
	if ((b * c) <= -4.9e+182) {
		tmp = b * c;
	} else if ((b * c) <= -1.7e+44) {
		tmp = k * (j * -27.0);
	} else if ((b * c) <= -7.6e-85) {
		tmp = 18.0 * (t * (y * (x * z)));
	} else if ((b * c) <= -1.85e-193) {
		tmp = t_1;
	} else if ((b * c) <= 3.4e-180) {
		tmp = t_2;
	} else if ((b * c) <= 2.4e-32) {
		tmp = t_1;
	} else if ((b * c) <= 1.6e+103) {
		tmp = t_2;
	} else {
		tmp = b * c;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = j * (k * (-27.0d0))
    t_2 = 18.0d0 * ((y * z) * (x * t))
    if ((b * c) <= (-4.9d+182)) then
        tmp = b * c
    else if ((b * c) <= (-1.7d+44)) then
        tmp = k * (j * (-27.0d0))
    else if ((b * c) <= (-7.6d-85)) then
        tmp = 18.0d0 * (t * (y * (x * z)))
    else if ((b * c) <= (-1.85d-193)) then
        tmp = t_1
    else if ((b * c) <= 3.4d-180) then
        tmp = t_2
    else if ((b * c) <= 2.4d-32) then
        tmp = t_1
    else if ((b * c) <= 1.6d+103) then
        tmp = t_2
    else
        tmp = b * c
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double t_1 = j * (k * -27.0);
	double t_2 = 18.0 * ((y * z) * (x * t));
	double tmp;
	if ((b * c) <= -4.9e+182) {
		tmp = b * c;
	} else if ((b * c) <= -1.7e+44) {
		tmp = k * (j * -27.0);
	} else if ((b * c) <= -7.6e-85) {
		tmp = 18.0 * (t * (y * (x * z)));
	} else if ((b * c) <= -1.85e-193) {
		tmp = t_1;
	} else if ((b * c) <= 3.4e-180) {
		tmp = t_2;
	} else if ((b * c) <= 2.4e-32) {
		tmp = t_1;
	} else if ((b * c) <= 1.6e+103) {
		tmp = t_2;
	} else {
		tmp = b * c;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k):
	t_1 = j * (k * -27.0)
	t_2 = 18.0 * ((y * z) * (x * t))
	tmp = 0
	if (b * c) <= -4.9e+182:
		tmp = b * c
	elif (b * c) <= -1.7e+44:
		tmp = k * (j * -27.0)
	elif (b * c) <= -7.6e-85:
		tmp = 18.0 * (t * (y * (x * z)))
	elif (b * c) <= -1.85e-193:
		tmp = t_1
	elif (b * c) <= 3.4e-180:
		tmp = t_2
	elif (b * c) <= 2.4e-32:
		tmp = t_1
	elif (b * c) <= 1.6e+103:
		tmp = t_2
	else:
		tmp = b * c
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k)
	t_1 = Float64(j * Float64(k * -27.0))
	t_2 = Float64(18.0 * Float64(Float64(y * z) * Float64(x * t)))
	tmp = 0.0
	if (Float64(b * c) <= -4.9e+182)
		tmp = Float64(b * c);
	elseif (Float64(b * c) <= -1.7e+44)
		tmp = Float64(k * Float64(j * -27.0));
	elseif (Float64(b * c) <= -7.6e-85)
		tmp = Float64(18.0 * Float64(t * Float64(y * Float64(x * z))));
	elseif (Float64(b * c) <= -1.85e-193)
		tmp = t_1;
	elseif (Float64(b * c) <= 3.4e-180)
		tmp = t_2;
	elseif (Float64(b * c) <= 2.4e-32)
		tmp = t_1;
	elseif (Float64(b * c) <= 1.6e+103)
		tmp = t_2;
	else
		tmp = Float64(b * c);
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	t_1 = j * (k * -27.0);
	t_2 = 18.0 * ((y * z) * (x * t));
	tmp = 0.0;
	if ((b * c) <= -4.9e+182)
		tmp = b * c;
	elseif ((b * c) <= -1.7e+44)
		tmp = k * (j * -27.0);
	elseif ((b * c) <= -7.6e-85)
		tmp = 18.0 * (t * (y * (x * z)));
	elseif ((b * c) <= -1.85e-193)
		tmp = t_1;
	elseif ((b * c) <= 3.4e-180)
		tmp = t_2;
	elseif ((b * c) <= 2.4e-32)
		tmp = t_1;
	elseif ((b * c) <= 1.6e+103)
		tmp = t_2;
	else
		tmp = b * c;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := Block[{t$95$1 = N[(j * N[(k * -27.0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(18.0 * N[(N[(y * z), $MachinePrecision] * N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[(b * c), $MachinePrecision], -4.9e+182], N[(b * c), $MachinePrecision], If[LessEqual[N[(b * c), $MachinePrecision], -1.7e+44], N[(k * N[(j * -27.0), $MachinePrecision]), $MachinePrecision], If[LessEqual[N[(b * c), $MachinePrecision], -7.6e-85], N[(18.0 * N[(t * N[(y * N[(x * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[N[(b * c), $MachinePrecision], -1.85e-193], t$95$1, If[LessEqual[N[(b * c), $MachinePrecision], 3.4e-180], t$95$2, If[LessEqual[N[(b * c), $MachinePrecision], 2.4e-32], t$95$1, If[LessEqual[N[(b * c), $MachinePrecision], 1.6e+103], t$95$2, N[(b * c), $MachinePrecision]]]]]]]]]]

Derivation

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

Alternative 4: 36.2% accurate, 0.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(k \cdot -27\right)\\ \mathbf{if}\;b \cdot c \leq -4.3 \cdot 10^{+170}:\\ \;\;\;\;b \cdot c\\ \mathbf{elif}\;b \cdot c \leq -9 \cdot 10^{+43}:\\ \;\;\;\;k \cdot \left(j \cdot -27\right)\\ \mathbf{elif}\;b \cdot c \leq -7.2 \cdot 10^{-85}:\\ \;\;\;\;18 \cdot \left(t \cdot \left(y \cdot \left(x \cdot z\right)\right)\right)\\ \mathbf{elif}\;b \cdot c \leq -4 \cdot 10^{-203}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;b \cdot c \leq 1.6 \cdot 10^{-182}:\\ \;\;\;\;x \cdot \left(\left(y \cdot z\right) \cdot \left(18 \cdot t\right)\right)\\ \mathbf{elif}\;b \cdot c \leq 2.1 \cdot 10^{-32}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;b \cdot c \leq 1.66 \cdot 10^{+103}:\\ \;\;\;\;18 \cdot \left(\left(y \cdot z\right) \cdot \left(x \cdot t\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot c\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k)
 :precision binary64
 (let* ((t_1 (* j (* k -27.0))))
   (if (<= (* b c) -4.3e+170)
     (* b c)
     (if (<= (* b c) -9e+43)
       (* k (* j -27.0))
       (if (<= (* b c) -7.2e-85)
         (* 18.0 (* t (* y (* x z))))
         (if (<= (* b c) -4e-203)
           t_1
           (if (<= (* b c) 1.6e-182)
             (* x (* (* y z) (* 18.0 t)))
             (if (<= (* b c) 2.1e-32)
               t_1
               (if (<= (* b c) 1.66e+103)
                 (* 18.0 (* (* y z) (* x t)))
                 (* b c))))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double t_1 = j * (k * -27.0);
	double tmp;
	if ((b * c) <= -4.3e+170) {
		tmp = b * c;
	} else if ((b * c) <= -9e+43) {
		tmp = k * (j * -27.0);
	} else if ((b * c) <= -7.2e-85) {
		tmp = 18.0 * (t * (y * (x * z)));
	} else if ((b * c) <= -4e-203) {
		tmp = t_1;
	} else if ((b * c) <= 1.6e-182) {
		tmp = x * ((y * z) * (18.0 * t));
	} else if ((b * c) <= 2.1e-32) {
		tmp = t_1;
	} else if ((b * c) <= 1.66e+103) {
		tmp = 18.0 * ((y * z) * (x * t));
	} else {
		tmp = b * c;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: t_1
    real(8) :: tmp
    t_1 = j * (k * (-27.0d0))
    if ((b * c) <= (-4.3d+170)) then
        tmp = b * c
    else if ((b * c) <= (-9d+43)) then
        tmp = k * (j * (-27.0d0))
    else if ((b * c) <= (-7.2d-85)) then
        tmp = 18.0d0 * (t * (y * (x * z)))
    else if ((b * c) <= (-4d-203)) then
        tmp = t_1
    else if ((b * c) <= 1.6d-182) then
        tmp = x * ((y * z) * (18.0d0 * t))
    else if ((b * c) <= 2.1d-32) then
        tmp = t_1
    else if ((b * c) <= 1.66d+103) then
        tmp = 18.0d0 * ((y * z) * (x * t))
    else
        tmp = b * c
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double t_1 = j * (k * -27.0);
	double tmp;
	if ((b * c) <= -4.3e+170) {
		tmp = b * c;
	} else if ((b * c) <= -9e+43) {
		tmp = k * (j * -27.0);
	} else if ((b * c) <= -7.2e-85) {
		tmp = 18.0 * (t * (y * (x * z)));
	} else if ((b * c) <= -4e-203) {
		tmp = t_1;
	} else if ((b * c) <= 1.6e-182) {
		tmp = x * ((y * z) * (18.0 * t));
	} else if ((b * c) <= 2.1e-32) {
		tmp = t_1;
	} else if ((b * c) <= 1.66e+103) {
		tmp = 18.0 * ((y * z) * (x * t));
	} else {
		tmp = b * c;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k):
	t_1 = j * (k * -27.0)
	tmp = 0
	if (b * c) <= -4.3e+170:
		tmp = b * c
	elif (b * c) <= -9e+43:
		tmp = k * (j * -27.0)
	elif (b * c) <= -7.2e-85:
		tmp = 18.0 * (t * (y * (x * z)))
	elif (b * c) <= -4e-203:
		tmp = t_1
	elif (b * c) <= 1.6e-182:
		tmp = x * ((y * z) * (18.0 * t))
	elif (b * c) <= 2.1e-32:
		tmp = t_1
	elif (b * c) <= 1.66e+103:
		tmp = 18.0 * ((y * z) * (x * t))
	else:
		tmp = b * c
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k)
	t_1 = Float64(j * Float64(k * -27.0))
	tmp = 0.0
	if (Float64(b * c) <= -4.3e+170)
		tmp = Float64(b * c);
	elseif (Float64(b * c) <= -9e+43)
		tmp = Float64(k * Float64(j * -27.0));
	elseif (Float64(b * c) <= -7.2e-85)
		tmp = Float64(18.0 * Float64(t * Float64(y * Float64(x * z))));
	elseif (Float64(b * c) <= -4e-203)
		tmp = t_1;
	elseif (Float64(b * c) <= 1.6e-182)
		tmp = Float64(x * Float64(Float64(y * z) * Float64(18.0 * t)));
	elseif (Float64(b * c) <= 2.1e-32)
		tmp = t_1;
	elseif (Float64(b * c) <= 1.66e+103)
		tmp = Float64(18.0 * Float64(Float64(y * z) * Float64(x * t)));
	else
		tmp = Float64(b * c);
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	t_1 = j * (k * -27.0);
	tmp = 0.0;
	if ((b * c) <= -4.3e+170)
		tmp = b * c;
	elseif ((b * c) <= -9e+43)
		tmp = k * (j * -27.0);
	elseif ((b * c) <= -7.2e-85)
		tmp = 18.0 * (t * (y * (x * z)));
	elseif ((b * c) <= -4e-203)
		tmp = t_1;
	elseif ((b * c) <= 1.6e-182)
		tmp = x * ((y * z) * (18.0 * t));
	elseif ((b * c) <= 2.1e-32)
		tmp = t_1;
	elseif ((b * c) <= 1.66e+103)
		tmp = 18.0 * ((y * z) * (x * t));
	else
		tmp = b * c;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := Block[{t$95$1 = N[(j * N[(k * -27.0), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[(b * c), $MachinePrecision], -4.3e+170], N[(b * c), $MachinePrecision], If[LessEqual[N[(b * c), $MachinePrecision], -9e+43], N[(k * N[(j * -27.0), $MachinePrecision]), $MachinePrecision], If[LessEqual[N[(b * c), $MachinePrecision], -7.2e-85], N[(18.0 * N[(t * N[(y * N[(x * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[N[(b * c), $MachinePrecision], -4e-203], t$95$1, If[LessEqual[N[(b * c), $MachinePrecision], 1.6e-182], N[(x * N[(N[(y * z), $MachinePrecision] * N[(18.0 * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[N[(b * c), $MachinePrecision], 2.1e-32], t$95$1, If[LessEqual[N[(b * c), $MachinePrecision], 1.66e+103], N[(18.0 * N[(N[(y * z), $MachinePrecision] * N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(b * c), $MachinePrecision]]]]]]]]]

Derivation

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

Alternative 5: 52.8% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(k \cdot -27\right)\\ t_2 := -4 \cdot \left(t \cdot a\right) + t_1\\ t_3 := b \cdot c + \left(x \cdot i\right) \cdot -4\\ \mathbf{if}\;b \cdot c \leq -6.5 \cdot 10^{+43}:\\ \;\;\;\;b \cdot c + t_1\\ \mathbf{elif}\;b \cdot c \leq -6.8 \cdot 10^{+16}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;b \cdot c \leq 1.1 \cdot 10^{-237}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;b \cdot c \leq 4.4 \cdot 10^{-180}:\\ \;\;\;\;x \cdot \left(\left(y \cdot z\right) \cdot \left(18 \cdot t\right)\right)\\ \mathbf{elif}\;b \cdot c \leq 7.2 \cdot 10^{+74}:\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;t_3\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k)
 :precision binary64
 (let* ((t_1 (* j (* k -27.0)))
        (t_2 (+ (* -4.0 (* t a)) t_1))
        (t_3 (+ (* b c) (* (* x i) -4.0))))
   (if (<= (* b c) -6.5e+43)
     (+ (* b c) t_1)
     (if (<= (* b c) -6.8e+16)
       t_3
       (if (<= (* b c) 1.1e-237)
         t_2
         (if (<= (* b c) 4.4e-180)
           (* x (* (* y z) (* 18.0 t)))
           (if (<= (* b c) 7.2e+74) t_2 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 t_1 = j * (k * -27.0);
	double t_2 = (-4.0 * (t * a)) + t_1;
	double t_3 = (b * c) + ((x * i) * -4.0);
	double tmp;
	if ((b * c) <= -6.5e+43) {
		tmp = (b * c) + t_1;
	} else if ((b * c) <= -6.8e+16) {
		tmp = t_3;
	} else if ((b * c) <= 1.1e-237) {
		tmp = t_2;
	} else if ((b * c) <= 4.4e-180) {
		tmp = x * ((y * z) * (18.0 * t));
	} else if ((b * c) <= 7.2e+74) {
		tmp = t_2;
	} else {
		tmp = t_3;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: tmp
    t_1 = j * (k * (-27.0d0))
    t_2 = ((-4.0d0) * (t * a)) + t_1
    t_3 = (b * c) + ((x * i) * (-4.0d0))
    if ((b * c) <= (-6.5d+43)) then
        tmp = (b * c) + t_1
    else if ((b * c) <= (-6.8d+16)) then
        tmp = t_3
    else if ((b * c) <= 1.1d-237) then
        tmp = t_2
    else if ((b * c) <= 4.4d-180) then
        tmp = x * ((y * z) * (18.0d0 * t))
    else if ((b * c) <= 7.2d+74) then
        tmp = t_2
    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 t_1 = j * (k * -27.0);
	double t_2 = (-4.0 * (t * a)) + t_1;
	double t_3 = (b * c) + ((x * i) * -4.0);
	double tmp;
	if ((b * c) <= -6.5e+43) {
		tmp = (b * c) + t_1;
	} else if ((b * c) <= -6.8e+16) {
		tmp = t_3;
	} else if ((b * c) <= 1.1e-237) {
		tmp = t_2;
	} else if ((b * c) <= 4.4e-180) {
		tmp = x * ((y * z) * (18.0 * t));
	} else if ((b * c) <= 7.2e+74) {
		tmp = t_2;
	} else {
		tmp = t_3;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k):
	t_1 = j * (k * -27.0)
	t_2 = (-4.0 * (t * a)) + t_1
	t_3 = (b * c) + ((x * i) * -4.0)
	tmp = 0
	if (b * c) <= -6.5e+43:
		tmp = (b * c) + t_1
	elif (b * c) <= -6.8e+16:
		tmp = t_3
	elif (b * c) <= 1.1e-237:
		tmp = t_2
	elif (b * c) <= 4.4e-180:
		tmp = x * ((y * z) * (18.0 * t))
	elif (b * c) <= 7.2e+74:
		tmp = t_2
	else:
		tmp = t_3
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k)
	t_1 = Float64(j * Float64(k * -27.0))
	t_2 = Float64(Float64(-4.0 * Float64(t * a)) + t_1)
	t_3 = Float64(Float64(b * c) + Float64(Float64(x * i) * -4.0))
	tmp = 0.0
	if (Float64(b * c) <= -6.5e+43)
		tmp = Float64(Float64(b * c) + t_1);
	elseif (Float64(b * c) <= -6.8e+16)
		tmp = t_3;
	elseif (Float64(b * c) <= 1.1e-237)
		tmp = t_2;
	elseif (Float64(b * c) <= 4.4e-180)
		tmp = Float64(x * Float64(Float64(y * z) * Float64(18.0 * t)));
	elseif (Float64(b * c) <= 7.2e+74)
		tmp = t_2;
	else
		tmp = t_3;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	t_1 = j * (k * -27.0);
	t_2 = (-4.0 * (t * a)) + t_1;
	t_3 = (b * c) + ((x * i) * -4.0);
	tmp = 0.0;
	if ((b * c) <= -6.5e+43)
		tmp = (b * c) + t_1;
	elseif ((b * c) <= -6.8e+16)
		tmp = t_3;
	elseif ((b * c) <= 1.1e-237)
		tmp = t_2;
	elseif ((b * c) <= 4.4e-180)
		tmp = x * ((y * z) * (18.0 * t));
	elseif ((b * c) <= 7.2e+74)
		tmp = t_2;
	else
		tmp = t_3;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := Block[{t$95$1 = N[(j * N[(k * -27.0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(-4.0 * N[(t * a), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision]}, Block[{t$95$3 = N[(N[(b * c), $MachinePrecision] + N[(N[(x * i), $MachinePrecision] * -4.0), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[(b * c), $MachinePrecision], -6.5e+43], N[(N[(b * c), $MachinePrecision] + t$95$1), $MachinePrecision], If[LessEqual[N[(b * c), $MachinePrecision], -6.8e+16], t$95$3, If[LessEqual[N[(b * c), $MachinePrecision], 1.1e-237], t$95$2, If[LessEqual[N[(b * c), $MachinePrecision], 4.4e-180], N[(x * N[(N[(y * z), $MachinePrecision] * N[(18.0 * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[N[(b * c), $MachinePrecision], 7.2e+74], t$95$2, t$95$3]]]]]]]]

Derivation

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

Alternative 6: 35.7% accurate, 1.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;b \cdot c \leq -1.1 \cdot 10^{+173}:\\ \;\;\;\;b \cdot c\\ \mathbf{elif}\;b \cdot c \leq -3 \cdot 10^{+40}:\\ \;\;\;\;k \cdot \left(j \cdot -27\right)\\ \mathbf{elif}\;b \cdot c \leq -1.75 \cdot 10^{-59}:\\ \;\;\;\;x \cdot \left(i \cdot -4\right)\\ \mathbf{elif}\;b \cdot c \leq -1.5 \cdot 10^{-308}:\\ \;\;\;\;\left(j \cdot k\right) \cdot -27\\ \mathbf{elif}\;b \cdot c \leq 4.6 \cdot 10^{-249}:\\ \;\;\;\;-4 \cdot \left(t \cdot a\right)\\ \mathbf{elif}\;b \cdot c \leq 3 \cdot 10^{+77}:\\ \;\;\;\;j \cdot \left(k \cdot -27\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot c\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k)
 :precision binary64
 (if (<= (* b c) -1.1e+173)
   (* b c)
   (if (<= (* b c) -3e+40)
     (* k (* j -27.0))
     (if (<= (* b c) -1.75e-59)
       (* x (* i -4.0))
       (if (<= (* b c) -1.5e-308)
         (* (* j k) -27.0)
         (if (<= (* b c) 4.6e-249)
           (* -4.0 (* t a))
           (if (<= (* b c) 3e+77) (* j (* k -27.0)) (* b c))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double tmp;
	if ((b * c) <= -1.1e+173) {
		tmp = b * c;
	} else if ((b * c) <= -3e+40) {
		tmp = k * (j * -27.0);
	} else if ((b * c) <= -1.75e-59) {
		tmp = x * (i * -4.0);
	} else if ((b * c) <= -1.5e-308) {
		tmp = (j * k) * -27.0;
	} else if ((b * c) <= 4.6e-249) {
		tmp = -4.0 * (t * a);
	} else if ((b * c) <= 3e+77) {
		tmp = j * (k * -27.0);
	} else {
		tmp = b * c;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: tmp
    if ((b * c) <= (-1.1d+173)) then
        tmp = b * c
    else if ((b * c) <= (-3d+40)) then
        tmp = k * (j * (-27.0d0))
    else if ((b * c) <= (-1.75d-59)) then
        tmp = x * (i * (-4.0d0))
    else if ((b * c) <= (-1.5d-308)) then
        tmp = (j * k) * (-27.0d0)
    else if ((b * c) <= 4.6d-249) then
        tmp = (-4.0d0) * (t * a)
    else if ((b * c) <= 3d+77) then
        tmp = j * (k * (-27.0d0))
    else
        tmp = b * c
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double tmp;
	if ((b * c) <= -1.1e+173) {
		tmp = b * c;
	} else if ((b * c) <= -3e+40) {
		tmp = k * (j * -27.0);
	} else if ((b * c) <= -1.75e-59) {
		tmp = x * (i * -4.0);
	} else if ((b * c) <= -1.5e-308) {
		tmp = (j * k) * -27.0;
	} else if ((b * c) <= 4.6e-249) {
		tmp = -4.0 * (t * a);
	} else if ((b * c) <= 3e+77) {
		tmp = j * (k * -27.0);
	} else {
		tmp = b * c;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k):
	tmp = 0
	if (b * c) <= -1.1e+173:
		tmp = b * c
	elif (b * c) <= -3e+40:
		tmp = k * (j * -27.0)
	elif (b * c) <= -1.75e-59:
		tmp = x * (i * -4.0)
	elif (b * c) <= -1.5e-308:
		tmp = (j * k) * -27.0
	elif (b * c) <= 4.6e-249:
		tmp = -4.0 * (t * a)
	elif (b * c) <= 3e+77:
		tmp = j * (k * -27.0)
	else:
		tmp = b * c
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k)
	tmp = 0.0
	if (Float64(b * c) <= -1.1e+173)
		tmp = Float64(b * c);
	elseif (Float64(b * c) <= -3e+40)
		tmp = Float64(k * Float64(j * -27.0));
	elseif (Float64(b * c) <= -1.75e-59)
		tmp = Float64(x * Float64(i * -4.0));
	elseif (Float64(b * c) <= -1.5e-308)
		tmp = Float64(Float64(j * k) * -27.0);
	elseif (Float64(b * c) <= 4.6e-249)
		tmp = Float64(-4.0 * Float64(t * a));
	elseif (Float64(b * c) <= 3e+77)
		tmp = Float64(j * Float64(k * -27.0));
	else
		tmp = Float64(b * c);
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	tmp = 0.0;
	if ((b * c) <= -1.1e+173)
		tmp = b * c;
	elseif ((b * c) <= -3e+40)
		tmp = k * (j * -27.0);
	elseif ((b * c) <= -1.75e-59)
		tmp = x * (i * -4.0);
	elseif ((b * c) <= -1.5e-308)
		tmp = (j * k) * -27.0;
	elseif ((b * c) <= 4.6e-249)
		tmp = -4.0 * (t * a);
	elseif ((b * c) <= 3e+77)
		tmp = j * (k * -27.0);
	else
		tmp = b * c;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := If[LessEqual[N[(b * c), $MachinePrecision], -1.1e+173], N[(b * c), $MachinePrecision], If[LessEqual[N[(b * c), $MachinePrecision], -3e+40], N[(k * N[(j * -27.0), $MachinePrecision]), $MachinePrecision], If[LessEqual[N[(b * c), $MachinePrecision], -1.75e-59], N[(x * N[(i * -4.0), $MachinePrecision]), $MachinePrecision], If[LessEqual[N[(b * c), $MachinePrecision], -1.5e-308], N[(N[(j * k), $MachinePrecision] * -27.0), $MachinePrecision], If[LessEqual[N[(b * c), $MachinePrecision], 4.6e-249], N[(-4.0 * N[(t * a), $MachinePrecision]), $MachinePrecision], If[LessEqual[N[(b * c), $MachinePrecision], 3e+77], N[(j * N[(k * -27.0), $MachinePrecision]), $MachinePrecision], N[(b * c), $MachinePrecision]]]]]]]

Derivation

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

Alternative 7: 70.4% accurate, 1.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;t \leq -3.4 \cdot 10^{+204} \lor \neg \left(t \leq -4.9 \cdot 10^{+166}\right) \land \left(t \leq -3.2 \cdot 10^{+119} \lor \neg \left(t \leq 5.2 \cdot 10^{+115} \lor \neg \left(t \leq 1.95 \cdot 10^{+139}\right) \land t \leq 4.8 \cdot 10^{+169}\right)\right):\\ \;\;\;\;\left(-t\right) \cdot \left(a \cdot 4 + \left(y \cdot z\right) \cdot \left(x \cdot -18\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot c - \left(27 \cdot \left(j \cdot k\right) + 4 \cdot \left(x \cdot i\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k)
 :precision binary64
 (if (or (<= t -3.4e+204)
         (and (not (<= t -4.9e+166))
              (or (<= t -3.2e+119)
                  (not
                   (or (<= t 5.2e+115)
                       (and (not (<= t 1.95e+139)) (<= t 4.8e+169)))))))
   (* (- t) (+ (* a 4.0) (* (* y z) (* x -18.0))))
   (- (* b c) (+ (* 27.0 (* j k)) (* 4.0 (* x i))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double tmp;
	if ((t <= -3.4e+204) || (!(t <= -4.9e+166) && ((t <= -3.2e+119) || !((t <= 5.2e+115) || (!(t <= 1.95e+139) && (t <= 4.8e+169)))))) {
		tmp = -t * ((a * 4.0) + ((y * z) * (x * -18.0)));
	} else {
		tmp = (b * c) - ((27.0 * (j * k)) + (4.0 * (x * i)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: tmp
    if ((t <= (-3.4d+204)) .or. (.not. (t <= (-4.9d+166))) .and. (t <= (-3.2d+119)) .or. (.not. (t <= 5.2d+115) .or. (.not. (t <= 1.95d+139)) .and. (t <= 4.8d+169))) then
        tmp = -t * ((a * 4.0d0) + ((y * z) * (x * (-18.0d0))))
    else
        tmp = (b * c) - ((27.0d0 * (j * k)) + (4.0d0 * (x * i)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double tmp;
	if ((t <= -3.4e+204) || (!(t <= -4.9e+166) && ((t <= -3.2e+119) || !((t <= 5.2e+115) || (!(t <= 1.95e+139) && (t <= 4.8e+169)))))) {
		tmp = -t * ((a * 4.0) + ((y * z) * (x * -18.0)));
	} else {
		tmp = (b * c) - ((27.0 * (j * k)) + (4.0 * (x * i)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k):
	tmp = 0
	if (t <= -3.4e+204) or (not (t <= -4.9e+166) and ((t <= -3.2e+119) or not ((t <= 5.2e+115) or (not (t <= 1.95e+139) and (t <= 4.8e+169))))):
		tmp = -t * ((a * 4.0) + ((y * z) * (x * -18.0)))
	else:
		tmp = (b * c) - ((27.0 * (j * k)) + (4.0 * (x * i)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k)
	tmp = 0.0
	if ((t <= -3.4e+204) || (!(t <= -4.9e+166) && ((t <= -3.2e+119) || !((t <= 5.2e+115) || (!(t <= 1.95e+139) && (t <= 4.8e+169))))))
		tmp = Float64(Float64(-t) * Float64(Float64(a * 4.0) + Float64(Float64(y * z) * Float64(x * -18.0))));
	else
		tmp = Float64(Float64(b * c) - Float64(Float64(27.0 * Float64(j * k)) + Float64(4.0 * Float64(x * i))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	tmp = 0.0;
	if ((t <= -3.4e+204) || (~((t <= -4.9e+166)) && ((t <= -3.2e+119) || ~(((t <= 5.2e+115) || (~((t <= 1.95e+139)) && (t <= 4.8e+169)))))))
		tmp = -t * ((a * 4.0) + ((y * z) * (x * -18.0)));
	else
		tmp = (b * c) - ((27.0 * (j * k)) + (4.0 * (x * i)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := If[Or[LessEqual[t, -3.4e+204], And[N[Not[LessEqual[t, -4.9e+166]], $MachinePrecision], Or[LessEqual[t, -3.2e+119], N[Not[Or[LessEqual[t, 5.2e+115], And[N[Not[LessEqual[t, 1.95e+139]], $MachinePrecision], LessEqual[t, 4.8e+169]]]], $MachinePrecision]]]], N[((-t) * N[(N[(a * 4.0), $MachinePrecision] + N[(N[(y * z), $MachinePrecision] * N[(x * -18.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(b * c), $MachinePrecision] - N[(N[(27.0 * N[(j * k), $MachinePrecision]), $MachinePrecision] + N[(4.0 * N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

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

Alternative 8: 53.9% accurate, 1.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(k \cdot -27\right)\\ t_2 := x \cdot \left(i \cdot -4\right) + t_1\\ \mathbf{if}\;b \cdot c \leq -1.25 \cdot 10^{+41}:\\ \;\;\;\;b \cdot c + t_1\\ \mathbf{elif}\;b \cdot c \leq -5.7 \cdot 10^{-43}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;b \cdot c \leq 6.6 \cdot 10^{-249}:\\ \;\;\;\;-4 \cdot \left(t \cdot a\right) + t_1\\ \mathbf{elif}\;b \cdot c \leq 1.35 \cdot 10^{+76}:\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;b \cdot c + \left(x \cdot i\right) \cdot -4\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k)
 :precision binary64
 (let* ((t_1 (* j (* k -27.0))) (t_2 (+ (* x (* i -4.0)) t_1)))
   (if (<= (* b c) -1.25e+41)
     (+ (* b c) t_1)
     (if (<= (* b c) -5.7e-43)
       t_2
       (if (<= (* b c) 6.6e-249)
         (+ (* -4.0 (* t a)) t_1)
         (if (<= (* b c) 1.35e+76) t_2 (+ (* b c) (* (* x i) -4.0))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double t_1 = j * (k * -27.0);
	double t_2 = (x * (i * -4.0)) + t_1;
	double tmp;
	if ((b * c) <= -1.25e+41) {
		tmp = (b * c) + t_1;
	} else if ((b * c) <= -5.7e-43) {
		tmp = t_2;
	} else if ((b * c) <= 6.6e-249) {
		tmp = (-4.0 * (t * a)) + t_1;
	} else if ((b * c) <= 1.35e+76) {
		tmp = t_2;
	} else {
		tmp = (b * c) + ((x * i) * -4.0);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = j * (k * (-27.0d0))
    t_2 = (x * (i * (-4.0d0))) + t_1
    if ((b * c) <= (-1.25d+41)) then
        tmp = (b * c) + t_1
    else if ((b * c) <= (-5.7d-43)) then
        tmp = t_2
    else if ((b * c) <= 6.6d-249) then
        tmp = ((-4.0d0) * (t * a)) + t_1
    else if ((b * c) <= 1.35d+76) then
        tmp = t_2
    else
        tmp = (b * c) + ((x * i) * (-4.0d0))
    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 t_1 = j * (k * -27.0);
	double t_2 = (x * (i * -4.0)) + t_1;
	double tmp;
	if ((b * c) <= -1.25e+41) {
		tmp = (b * c) + t_1;
	} else if ((b * c) <= -5.7e-43) {
		tmp = t_2;
	} else if ((b * c) <= 6.6e-249) {
		tmp = (-4.0 * (t * a)) + t_1;
	} else if ((b * c) <= 1.35e+76) {
		tmp = t_2;
	} else {
		tmp = (b * c) + ((x * i) * -4.0);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k):
	t_1 = j * (k * -27.0)
	t_2 = (x * (i * -4.0)) + t_1
	tmp = 0
	if (b * c) <= -1.25e+41:
		tmp = (b * c) + t_1
	elif (b * c) <= -5.7e-43:
		tmp = t_2
	elif (b * c) <= 6.6e-249:
		tmp = (-4.0 * (t * a)) + t_1
	elif (b * c) <= 1.35e+76:
		tmp = t_2
	else:
		tmp = (b * c) + ((x * i) * -4.0)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k)
	t_1 = Float64(j * Float64(k * -27.0))
	t_2 = Float64(Float64(x * Float64(i * -4.0)) + t_1)
	tmp = 0.0
	if (Float64(b * c) <= -1.25e+41)
		tmp = Float64(Float64(b * c) + t_1);
	elseif (Float64(b * c) <= -5.7e-43)
		tmp = t_2;
	elseif (Float64(b * c) <= 6.6e-249)
		tmp = Float64(Float64(-4.0 * Float64(t * a)) + t_1);
	elseif (Float64(b * c) <= 1.35e+76)
		tmp = t_2;
	else
		tmp = Float64(Float64(b * c) + Float64(Float64(x * i) * -4.0));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	t_1 = j * (k * -27.0);
	t_2 = (x * (i * -4.0)) + t_1;
	tmp = 0.0;
	if ((b * c) <= -1.25e+41)
		tmp = (b * c) + t_1;
	elseif ((b * c) <= -5.7e-43)
		tmp = t_2;
	elseif ((b * c) <= 6.6e-249)
		tmp = (-4.0 * (t * a)) + t_1;
	elseif ((b * c) <= 1.35e+76)
		tmp = t_2;
	else
		tmp = (b * c) + ((x * i) * -4.0);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := Block[{t$95$1 = N[(j * N[(k * -27.0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(x * N[(i * -4.0), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision]}, If[LessEqual[N[(b * c), $MachinePrecision], -1.25e+41], N[(N[(b * c), $MachinePrecision] + t$95$1), $MachinePrecision], If[LessEqual[N[(b * c), $MachinePrecision], -5.7e-43], t$95$2, If[LessEqual[N[(b * c), $MachinePrecision], 6.6e-249], N[(N[(-4.0 * N[(t * a), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision], If[LessEqual[N[(b * c), $MachinePrecision], 1.35e+76], t$95$2, N[(N[(b * c), $MachinePrecision] + N[(N[(x * i), $MachinePrecision] * -4.0), $MachinePrecision]), $MachinePrecision]]]]]]]

Derivation

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

Alternative 9: 78.5% accurate, 1.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := 27 \cdot \left(j \cdot k\right)\\ \mathbf{if}\;i \leq -9.5 \cdot 10^{+183} \lor \neg \left(i \leq 3.4 \cdot 10^{+163}\right):\\ \;\;\;\;b \cdot c - \left(t_1 + 4 \cdot \left(x \cdot i\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot c + t \cdot \left(18 \cdot \left(x \cdot \left(y \cdot z\right)\right) - a \cdot 4\right)\right) - t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k)
 :precision binary64
 (let* ((t_1 (* 27.0 (* j k))))
   (if (or (<= i -9.5e+183) (not (<= i 3.4e+163)))
     (- (* b c) (+ t_1 (* 4.0 (* x i))))
     (- (+ (* b c) (* t (- (* 18.0 (* x (* y z))) (* a 4.0)))) 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 t_1 = 27.0 * (j * k);
	double tmp;
	if ((i <= -9.5e+183) || !(i <= 3.4e+163)) {
		tmp = (b * c) - (t_1 + (4.0 * (x * i)));
	} else {
		tmp = ((b * c) + (t * ((18.0 * (x * (y * z))) - (a * 4.0)))) - t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: t_1
    real(8) :: tmp
    t_1 = 27.0d0 * (j * k)
    if ((i <= (-9.5d+183)) .or. (.not. (i <= 3.4d+163))) then
        tmp = (b * c) - (t_1 + (4.0d0 * (x * i)))
    else
        tmp = ((b * c) + (t * ((18.0d0 * (x * (y * z))) - (a * 4.0d0)))) - 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 t_1 = 27.0 * (j * k);
	double tmp;
	if ((i <= -9.5e+183) || !(i <= 3.4e+163)) {
		tmp = (b * c) - (t_1 + (4.0 * (x * i)));
	} else {
		tmp = ((b * c) + (t * ((18.0 * (x * (y * z))) - (a * 4.0)))) - t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k):
	t_1 = 27.0 * (j * k)
	tmp = 0
	if (i <= -9.5e+183) or not (i <= 3.4e+163):
		tmp = (b * c) - (t_1 + (4.0 * (x * i)))
	else:
		tmp = ((b * c) + (t * ((18.0 * (x * (y * z))) - (a * 4.0)))) - t_1
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k)
	t_1 = Float64(27.0 * Float64(j * k))
	tmp = 0.0
	if ((i <= -9.5e+183) || !(i <= 3.4e+163))
		tmp = Float64(Float64(b * c) - Float64(t_1 + Float64(4.0 * Float64(x * i))));
	else
		tmp = Float64(Float64(Float64(b * c) + Float64(t * Float64(Float64(18.0 * Float64(x * Float64(y * z))) - Float64(a * 4.0)))) - t_1);
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	t_1 = 27.0 * (j * k);
	tmp = 0.0;
	if ((i <= -9.5e+183) || ~((i <= 3.4e+163)))
		tmp = (b * c) - (t_1 + (4.0 * (x * i)));
	else
		tmp = ((b * c) + (t * ((18.0 * (x * (y * z))) - (a * 4.0)))) - t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := Block[{t$95$1 = N[(27.0 * N[(j * k), $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[i, -9.5e+183], N[Not[LessEqual[i, 3.4e+163]], $MachinePrecision]], N[(N[(b * c), $MachinePrecision] - N[(t$95$1 + N[(4.0 * N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(N[(b * c), $MachinePrecision] + N[(t * N[(N[(18.0 * N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(a * 4.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$1), $MachinePrecision]]]

Derivation

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

Alternative 10: 79.7% accurate, 1.1× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;i \leq -4.3 \cdot 10^{+82} \lor \neg \left(i \leq 8 \cdot 10^{+166}\right):\\ \;\;\;\;\left(b \cdot c + x \cdot \left(18 \cdot \left(t \cdot \left(y \cdot z\right)\right) - 4 \cdot i\right)\right) - t \cdot \left(a \cdot 4\right)\\ \mathbf{else}:\\ \;\;\;\;\left(b \cdot c + t \cdot \left(18 \cdot \left(x \cdot \left(y \cdot z\right)\right) - a \cdot 4\right)\right) - 27 \cdot \left(j \cdot k\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k)
 :precision binary64
 (if (or (<= i -4.3e+82) (not (<= i 8e+166)))
   (- (+ (* b c) (* x (- (* 18.0 (* t (* y z))) (* 4.0 i)))) (* t (* a 4.0)))
   (-
    (+ (* b c) (* t (- (* 18.0 (* x (* y z))) (* a 4.0))))
    (* 27.0 (* j k)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double tmp;
	if ((i <= -4.3e+82) || !(i <= 8e+166)) {
		tmp = ((b * c) + (x * ((18.0 * (t * (y * z))) - (4.0 * i)))) - (t * (a * 4.0));
	} else {
		tmp = ((b * c) + (t * ((18.0 * (x * (y * z))) - (a * 4.0)))) - (27.0 * (j * k));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: tmp
    if ((i <= (-4.3d+82)) .or. (.not. (i <= 8d+166))) then
        tmp = ((b * c) + (x * ((18.0d0 * (t * (y * z))) - (4.0d0 * i)))) - (t * (a * 4.0d0))
    else
        tmp = ((b * c) + (t * ((18.0d0 * (x * (y * z))) - (a * 4.0d0)))) - (27.0d0 * (j * k))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double tmp;
	if ((i <= -4.3e+82) || !(i <= 8e+166)) {
		tmp = ((b * c) + (x * ((18.0 * (t * (y * z))) - (4.0 * i)))) - (t * (a * 4.0));
	} else {
		tmp = ((b * c) + (t * ((18.0 * (x * (y * z))) - (a * 4.0)))) - (27.0 * (j * k));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k):
	tmp = 0
	if (i <= -4.3e+82) or not (i <= 8e+166):
		tmp = ((b * c) + (x * ((18.0 * (t * (y * z))) - (4.0 * i)))) - (t * (a * 4.0))
	else:
		tmp = ((b * c) + (t * ((18.0 * (x * (y * z))) - (a * 4.0)))) - (27.0 * (j * k))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k)
	tmp = 0.0
	if ((i <= -4.3e+82) || !(i <= 8e+166))
		tmp = Float64(Float64(Float64(b * c) + Float64(x * Float64(Float64(18.0 * Float64(t * Float64(y * z))) - Float64(4.0 * i)))) - Float64(t * Float64(a * 4.0)));
	else
		tmp = Float64(Float64(Float64(b * c) + Float64(t * Float64(Float64(18.0 * Float64(x * Float64(y * z))) - Float64(a * 4.0)))) - Float64(27.0 * Float64(j * k)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	tmp = 0.0;
	if ((i <= -4.3e+82) || ~((i <= 8e+166)))
		tmp = ((b * c) + (x * ((18.0 * (t * (y * z))) - (4.0 * i)))) - (t * (a * 4.0));
	else
		tmp = ((b * c) + (t * ((18.0 * (x * (y * z))) - (a * 4.0)))) - (27.0 * (j * k));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := If[Or[LessEqual[i, -4.3e+82], N[Not[LessEqual[i, 8e+166]], $MachinePrecision]], N[(N[(N[(b * c), $MachinePrecision] + N[(x * N[(N[(18.0 * N[(t * N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(4.0 * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(t * N[(a * 4.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(N[(b * c), $MachinePrecision] + N[(t * N[(N[(18.0 * N[(x * N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(a * 4.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(27.0 * N[(j * k), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

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

Alternative 11: 36.0% accurate, 1.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \left(j \cdot k\right) \cdot -27\\ \mathbf{if}\;b \cdot c \leq -6.4 \cdot 10^{+170}:\\ \;\;\;\;b \cdot c\\ \mathbf{elif}\;b \cdot c \leq -2.1 \cdot 10^{-302}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;b \cdot c \leq 4 \cdot 10^{-249}:\\ \;\;\;\;-4 \cdot \left(t \cdot a\right)\\ \mathbf{elif}\;b \cdot c \leq 7.5 \cdot 10^{+76}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;b \cdot c\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k)
 :precision binary64
 (let* ((t_1 (* (* j k) -27.0)))
   (if (<= (* b c) -6.4e+170)
     (* b c)
     (if (<= (* b c) -2.1e-302)
       t_1
       (if (<= (* b c) 4e-249)
         (* -4.0 (* t a))
         (if (<= (* b c) 7.5e+76) t_1 (* b c)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double t_1 = (j * k) * -27.0;
	double tmp;
	if ((b * c) <= -6.4e+170) {
		tmp = b * c;
	} else if ((b * c) <= -2.1e-302) {
		tmp = t_1;
	} else if ((b * c) <= 4e-249) {
		tmp = -4.0 * (t * a);
	} else if ((b * c) <= 7.5e+76) {
		tmp = t_1;
	} else {
		tmp = b * c;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: t_1
    real(8) :: tmp
    t_1 = (j * k) * (-27.0d0)
    if ((b * c) <= (-6.4d+170)) then
        tmp = b * c
    else if ((b * c) <= (-2.1d-302)) then
        tmp = t_1
    else if ((b * c) <= 4d-249) then
        tmp = (-4.0d0) * (t * a)
    else if ((b * c) <= 7.5d+76) then
        tmp = t_1
    else
        tmp = b * c
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double t_1 = (j * k) * -27.0;
	double tmp;
	if ((b * c) <= -6.4e+170) {
		tmp = b * c;
	} else if ((b * c) <= -2.1e-302) {
		tmp = t_1;
	} else if ((b * c) <= 4e-249) {
		tmp = -4.0 * (t * a);
	} else if ((b * c) <= 7.5e+76) {
		tmp = t_1;
	} else {
		tmp = b * c;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k):
	t_1 = (j * k) * -27.0
	tmp = 0
	if (b * c) <= -6.4e+170:
		tmp = b * c
	elif (b * c) <= -2.1e-302:
		tmp = t_1
	elif (b * c) <= 4e-249:
		tmp = -4.0 * (t * a)
	elif (b * c) <= 7.5e+76:
		tmp = t_1
	else:
		tmp = b * c
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k)
	t_1 = Float64(Float64(j * k) * -27.0)
	tmp = 0.0
	if (Float64(b * c) <= -6.4e+170)
		tmp = Float64(b * c);
	elseif (Float64(b * c) <= -2.1e-302)
		tmp = t_1;
	elseif (Float64(b * c) <= 4e-249)
		tmp = Float64(-4.0 * Float64(t * a));
	elseif (Float64(b * c) <= 7.5e+76)
		tmp = t_1;
	else
		tmp = Float64(b * c);
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	t_1 = (j * k) * -27.0;
	tmp = 0.0;
	if ((b * c) <= -6.4e+170)
		tmp = b * c;
	elseif ((b * c) <= -2.1e-302)
		tmp = t_1;
	elseif ((b * c) <= 4e-249)
		tmp = -4.0 * (t * a);
	elseif ((b * c) <= 7.5e+76)
		tmp = t_1;
	else
		tmp = b * c;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := Block[{t$95$1 = N[(N[(j * k), $MachinePrecision] * -27.0), $MachinePrecision]}, If[LessEqual[N[(b * c), $MachinePrecision], -6.4e+170], N[(b * c), $MachinePrecision], If[LessEqual[N[(b * c), $MachinePrecision], -2.1e-302], t$95$1, If[LessEqual[N[(b * c), $MachinePrecision], 4e-249], N[(-4.0 * N[(t * a), $MachinePrecision]), $MachinePrecision], If[LessEqual[N[(b * c), $MachinePrecision], 7.5e+76], t$95$1, N[(b * c), $MachinePrecision]]]]]]

Derivation

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

Alternative 12: 35.9% accurate, 1.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := j \cdot \left(k \cdot -27\right)\\ \mathbf{if}\;b \cdot c \leq -3.6 \cdot 10^{+171}:\\ \;\;\;\;b \cdot c\\ \mathbf{elif}\;b \cdot c \leq -2.05 \cdot 10^{-305}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;b \cdot c \leq 6.6 \cdot 10^{-249}:\\ \;\;\;\;-4 \cdot \left(t \cdot a\right)\\ \mathbf{elif}\;b \cdot c \leq 5.5 \cdot 10^{+77}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;b \cdot c\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k)
 :precision binary64
 (let* ((t_1 (* j (* k -27.0))))
   (if (<= (* b c) -3.6e+171)
     (* b c)
     (if (<= (* b c) -2.05e-305)
       t_1
       (if (<= (* b c) 6.6e-249)
         (* -4.0 (* t a))
         (if (<= (* b c) 5.5e+77) t_1 (* b c)))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double t_1 = j * (k * -27.0);
	double tmp;
	if ((b * c) <= -3.6e+171) {
		tmp = b * c;
	} else if ((b * c) <= -2.05e-305) {
		tmp = t_1;
	} else if ((b * c) <= 6.6e-249) {
		tmp = -4.0 * (t * a);
	} else if ((b * c) <= 5.5e+77) {
		tmp = t_1;
	} else {
		tmp = b * c;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: t_1
    real(8) :: tmp
    t_1 = j * (k * (-27.0d0))
    if ((b * c) <= (-3.6d+171)) then
        tmp = b * c
    else if ((b * c) <= (-2.05d-305)) then
        tmp = t_1
    else if ((b * c) <= 6.6d-249) then
        tmp = (-4.0d0) * (t * a)
    else if ((b * c) <= 5.5d+77) then
        tmp = t_1
    else
        tmp = b * c
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double t_1 = j * (k * -27.0);
	double tmp;
	if ((b * c) <= -3.6e+171) {
		tmp = b * c;
	} else if ((b * c) <= -2.05e-305) {
		tmp = t_1;
	} else if ((b * c) <= 6.6e-249) {
		tmp = -4.0 * (t * a);
	} else if ((b * c) <= 5.5e+77) {
		tmp = t_1;
	} else {
		tmp = b * c;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k):
	t_1 = j * (k * -27.0)
	tmp = 0
	if (b * c) <= -3.6e+171:
		tmp = b * c
	elif (b * c) <= -2.05e-305:
		tmp = t_1
	elif (b * c) <= 6.6e-249:
		tmp = -4.0 * (t * a)
	elif (b * c) <= 5.5e+77:
		tmp = t_1
	else:
		tmp = b * c
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k)
	t_1 = Float64(j * Float64(k * -27.0))
	tmp = 0.0
	if (Float64(b * c) <= -3.6e+171)
		tmp = Float64(b * c);
	elseif (Float64(b * c) <= -2.05e-305)
		tmp = t_1;
	elseif (Float64(b * c) <= 6.6e-249)
		tmp = Float64(-4.0 * Float64(t * a));
	elseif (Float64(b * c) <= 5.5e+77)
		tmp = t_1;
	else
		tmp = Float64(b * c);
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	t_1 = j * (k * -27.0);
	tmp = 0.0;
	if ((b * c) <= -3.6e+171)
		tmp = b * c;
	elseif ((b * c) <= -2.05e-305)
		tmp = t_1;
	elseif ((b * c) <= 6.6e-249)
		tmp = -4.0 * (t * a);
	elseif ((b * c) <= 5.5e+77)
		tmp = t_1;
	else
		tmp = b * c;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := Block[{t$95$1 = N[(j * N[(k * -27.0), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[(b * c), $MachinePrecision], -3.6e+171], N[(b * c), $MachinePrecision], If[LessEqual[N[(b * c), $MachinePrecision], -2.05e-305], t$95$1, If[LessEqual[N[(b * c), $MachinePrecision], 6.6e-249], N[(-4.0 * N[(t * a), $MachinePrecision]), $MachinePrecision], If[LessEqual[N[(b * c), $MachinePrecision], 5.5e+77], t$95$1, N[(b * c), $MachinePrecision]]]]]]

Derivation

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

Alternative 13: 35.9% accurate, 1.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;b \cdot c \leq -4.5 \cdot 10^{+171}:\\ \;\;\;\;b \cdot c\\ \mathbf{elif}\;b \cdot c \leq -6.2 \cdot 10^{-299}:\\ \;\;\;\;k \cdot \left(j \cdot -27\right)\\ \mathbf{elif}\;b \cdot c \leq 4.8 \cdot 10^{-249}:\\ \;\;\;\;-4 \cdot \left(t \cdot a\right)\\ \mathbf{elif}\;b \cdot c \leq 7.5 \cdot 10^{+77}:\\ \;\;\;\;j \cdot \left(k \cdot -27\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot c\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k)
 :precision binary64
 (if (<= (* b c) -4.5e+171)
   (* b c)
   (if (<= (* b c) -6.2e-299)
     (* k (* j -27.0))
     (if (<= (* b c) 4.8e-249)
       (* -4.0 (* t a))
       (if (<= (* b c) 7.5e+77) (* j (* k -27.0)) (* b c))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double tmp;
	if ((b * c) <= -4.5e+171) {
		tmp = b * c;
	} else if ((b * c) <= -6.2e-299) {
		tmp = k * (j * -27.0);
	} else if ((b * c) <= 4.8e-249) {
		tmp = -4.0 * (t * a);
	} else if ((b * c) <= 7.5e+77) {
		tmp = j * (k * -27.0);
	} else {
		tmp = b * c;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: tmp
    if ((b * c) <= (-4.5d+171)) then
        tmp = b * c
    else if ((b * c) <= (-6.2d-299)) then
        tmp = k * (j * (-27.0d0))
    else if ((b * c) <= 4.8d-249) then
        tmp = (-4.0d0) * (t * a)
    else if ((b * c) <= 7.5d+77) then
        tmp = j * (k * (-27.0d0))
    else
        tmp = b * c
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double tmp;
	if ((b * c) <= -4.5e+171) {
		tmp = b * c;
	} else if ((b * c) <= -6.2e-299) {
		tmp = k * (j * -27.0);
	} else if ((b * c) <= 4.8e-249) {
		tmp = -4.0 * (t * a);
	} else if ((b * c) <= 7.5e+77) {
		tmp = j * (k * -27.0);
	} else {
		tmp = b * c;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k):
	tmp = 0
	if (b * c) <= -4.5e+171:
		tmp = b * c
	elif (b * c) <= -6.2e-299:
		tmp = k * (j * -27.0)
	elif (b * c) <= 4.8e-249:
		tmp = -4.0 * (t * a)
	elif (b * c) <= 7.5e+77:
		tmp = j * (k * -27.0)
	else:
		tmp = b * c
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k)
	tmp = 0.0
	if (Float64(b * c) <= -4.5e+171)
		tmp = Float64(b * c);
	elseif (Float64(b * c) <= -6.2e-299)
		tmp = Float64(k * Float64(j * -27.0));
	elseif (Float64(b * c) <= 4.8e-249)
		tmp = Float64(-4.0 * Float64(t * a));
	elseif (Float64(b * c) <= 7.5e+77)
		tmp = Float64(j * Float64(k * -27.0));
	else
		tmp = Float64(b * c);
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	tmp = 0.0;
	if ((b * c) <= -4.5e+171)
		tmp = b * c;
	elseif ((b * c) <= -6.2e-299)
		tmp = k * (j * -27.0);
	elseif ((b * c) <= 4.8e-249)
		tmp = -4.0 * (t * a);
	elseif ((b * c) <= 7.5e+77)
		tmp = j * (k * -27.0);
	else
		tmp = b * c;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := If[LessEqual[N[(b * c), $MachinePrecision], -4.5e+171], N[(b * c), $MachinePrecision], If[LessEqual[N[(b * c), $MachinePrecision], -6.2e-299], N[(k * N[(j * -27.0), $MachinePrecision]), $MachinePrecision], If[LessEqual[N[(b * c), $MachinePrecision], 4.8e-249], N[(-4.0 * N[(t * a), $MachinePrecision]), $MachinePrecision], If[LessEqual[N[(b * c), $MachinePrecision], 7.5e+77], N[(j * N[(k * -27.0), $MachinePrecision]), $MachinePrecision], N[(b * c), $MachinePrecision]]]]]

Derivation

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

Alternative 14: 57.1% accurate, 1.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;x \leq -3.7 \cdot 10^{+190}:\\ \;\;\;\;x \cdot \left(\left(y \cdot t\right) \cdot \left(18 \cdot z\right)\right) + j \cdot \left(k \cdot -27\right)\\ \mathbf{elif}\;x \leq -2050 \lor \neg \left(x \leq 6 \cdot 10^{+114}\right):\\ \;\;\;\;x \cdot \left(18 \cdot \left(t \cdot \left(y \cdot z\right)\right) - 4 \cdot i\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot c + \left(j \cdot k\right) \cdot -27\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k)
 :precision binary64
 (if (<= x -3.7e+190)
   (+ (* x (* (* y t) (* 18.0 z))) (* j (* k -27.0)))
   (if (or (<= x -2050.0) (not (<= x 6e+114)))
     (* x (- (* 18.0 (* t (* y z))) (* 4.0 i)))
     (+ (* b c) (* (* j k) -27.0)))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double tmp;
	if (x <= -3.7e+190) {
		tmp = (x * ((y * t) * (18.0 * z))) + (j * (k * -27.0));
	} else if ((x <= -2050.0) || !(x <= 6e+114)) {
		tmp = x * ((18.0 * (t * (y * z))) - (4.0 * i));
	} else {
		tmp = (b * c) + ((j * k) * -27.0);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: tmp
    if (x <= (-3.7d+190)) then
        tmp = (x * ((y * t) * (18.0d0 * z))) + (j * (k * (-27.0d0)))
    else if ((x <= (-2050.0d0)) .or. (.not. (x <= 6d+114))) then
        tmp = x * ((18.0d0 * (t * (y * z))) - (4.0d0 * i))
    else
        tmp = (b * c) + ((j * k) * (-27.0d0))
    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 tmp;
	if (x <= -3.7e+190) {
		tmp = (x * ((y * t) * (18.0 * z))) + (j * (k * -27.0));
	} else if ((x <= -2050.0) || !(x <= 6e+114)) {
		tmp = x * ((18.0 * (t * (y * z))) - (4.0 * i));
	} else {
		tmp = (b * c) + ((j * k) * -27.0);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k):
	tmp = 0
	if x <= -3.7e+190:
		tmp = (x * ((y * t) * (18.0 * z))) + (j * (k * -27.0))
	elif (x <= -2050.0) or not (x <= 6e+114):
		tmp = x * ((18.0 * (t * (y * z))) - (4.0 * i))
	else:
		tmp = (b * c) + ((j * k) * -27.0)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k)
	tmp = 0.0
	if (x <= -3.7e+190)
		tmp = Float64(Float64(x * Float64(Float64(y * t) * Float64(18.0 * z))) + Float64(j * Float64(k * -27.0)));
	elseif ((x <= -2050.0) || !(x <= 6e+114))
		tmp = Float64(x * Float64(Float64(18.0 * Float64(t * Float64(y * z))) - Float64(4.0 * i)));
	else
		tmp = Float64(Float64(b * c) + Float64(Float64(j * k) * -27.0));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	tmp = 0.0;
	if (x <= -3.7e+190)
		tmp = (x * ((y * t) * (18.0 * z))) + (j * (k * -27.0));
	elseif ((x <= -2050.0) || ~((x <= 6e+114)))
		tmp = x * ((18.0 * (t * (y * z))) - (4.0 * i));
	else
		tmp = (b * c) + ((j * k) * -27.0);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := If[LessEqual[x, -3.7e+190], N[(N[(x * N[(N[(y * t), $MachinePrecision] * N[(18.0 * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(j * N[(k * -27.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[Or[LessEqual[x, -2050.0], N[Not[LessEqual[x, 6e+114]], $MachinePrecision]], N[(x * N[(N[(18.0 * N[(t * N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(4.0 * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(b * c), $MachinePrecision] + N[(N[(j * k), $MachinePrecision] * -27.0), $MachinePrecision]), $MachinePrecision]]]

Derivation

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

Alternative 15: 62.2% accurate, 1.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;j \leq -5 \cdot 10^{+67}:\\ \;\;\;\;b \cdot c - \left(27 \cdot \left(j \cdot k\right) + 4 \cdot \left(x \cdot i\right)\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot c + x \cdot \left(18 \cdot \left(t \cdot \left(y \cdot z\right)\right) - 4 \cdot i\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k)
 :precision binary64
 (if (<= j -5e+67)
   (- (* b c) (+ (* 27.0 (* j k)) (* 4.0 (* x i))))
   (+ (* b c) (* x (- (* 18.0 (* t (* y z))) (* 4.0 i))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double tmp;
	if (j <= -5e+67) {
		tmp = (b * c) - ((27.0 * (j * k)) + (4.0 * (x * i)));
	} else {
		tmp = (b * c) + (x * ((18.0 * (t * (y * z))) - (4.0 * i)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: tmp
    if (j <= (-5d+67)) then
        tmp = (b * c) - ((27.0d0 * (j * k)) + (4.0d0 * (x * i)))
    else
        tmp = (b * c) + (x * ((18.0d0 * (t * (y * z))) - (4.0d0 * i)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double tmp;
	if (j <= -5e+67) {
		tmp = (b * c) - ((27.0 * (j * k)) + (4.0 * (x * i)));
	} else {
		tmp = (b * c) + (x * ((18.0 * (t * (y * z))) - (4.0 * i)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k):
	tmp = 0
	if j <= -5e+67:
		tmp = (b * c) - ((27.0 * (j * k)) + (4.0 * (x * i)))
	else:
		tmp = (b * c) + (x * ((18.0 * (t * (y * z))) - (4.0 * i)))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k)
	tmp = 0.0
	if (j <= -5e+67)
		tmp = Float64(Float64(b * c) - Float64(Float64(27.0 * Float64(j * k)) + Float64(4.0 * Float64(x * i))));
	else
		tmp = Float64(Float64(b * c) + Float64(x * Float64(Float64(18.0 * Float64(t * Float64(y * z))) - Float64(4.0 * i))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	tmp = 0.0;
	if (j <= -5e+67)
		tmp = (b * c) - ((27.0 * (j * k)) + (4.0 * (x * i)));
	else
		tmp = (b * c) + (x * ((18.0 * (t * (y * z))) - (4.0 * i)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := If[LessEqual[j, -5e+67], N[(N[(b * c), $MachinePrecision] - N[(N[(27.0 * N[(j * k), $MachinePrecision]), $MachinePrecision] + N[(4.0 * N[(x * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(b * c), $MachinePrecision] + N[(x * N[(N[(18.0 * N[(t * N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(4.0 * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

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

Alternative 16: 48.5% accurate, 1.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;x \leq -3.7 \cdot 10^{+145}:\\ \;\;\;\;18 \cdot \left(t \cdot \left(y \cdot \left(x \cdot z\right)\right)\right)\\ \mathbf{elif}\;x \leq -3.55 \cdot 10^{+87}:\\ \;\;\;\;x \cdot \left(i \cdot -4\right)\\ \mathbf{elif}\;x \leq -1250:\\ \;\;\;\;\left(y \cdot t\right) \cdot \left(x \cdot \left(18 \cdot z\right)\right)\\ \mathbf{elif}\;x \leq 6.2 \cdot 10^{+132}:\\ \;\;\;\;b \cdot c + \left(j \cdot k\right) \cdot -27\\ \mathbf{else}:\\ \;\;\;\;18 \cdot \left(\left(y \cdot z\right) \cdot \left(x \cdot t\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k)
 :precision binary64
 (if (<= x -3.7e+145)
   (* 18.0 (* t (* y (* x z))))
   (if (<= x -3.55e+87)
     (* x (* i -4.0))
     (if (<= x -1250.0)
       (* (* y t) (* x (* 18.0 z)))
       (if (<= x 6.2e+132)
         (+ (* b c) (* (* j k) -27.0))
         (* 18.0 (* (* y z) (* x t))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double tmp;
	if (x <= -3.7e+145) {
		tmp = 18.0 * (t * (y * (x * z)));
	} else if (x <= -3.55e+87) {
		tmp = x * (i * -4.0);
	} else if (x <= -1250.0) {
		tmp = (y * t) * (x * (18.0 * z));
	} else if (x <= 6.2e+132) {
		tmp = (b * c) + ((j * k) * -27.0);
	} else {
		tmp = 18.0 * ((y * z) * (x * t));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: tmp
    if (x <= (-3.7d+145)) then
        tmp = 18.0d0 * (t * (y * (x * z)))
    else if (x <= (-3.55d+87)) then
        tmp = x * (i * (-4.0d0))
    else if (x <= (-1250.0d0)) then
        tmp = (y * t) * (x * (18.0d0 * z))
    else if (x <= 6.2d+132) then
        tmp = (b * c) + ((j * k) * (-27.0d0))
    else
        tmp = 18.0d0 * ((y * z) * (x * t))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double tmp;
	if (x <= -3.7e+145) {
		tmp = 18.0 * (t * (y * (x * z)));
	} else if (x <= -3.55e+87) {
		tmp = x * (i * -4.0);
	} else if (x <= -1250.0) {
		tmp = (y * t) * (x * (18.0 * z));
	} else if (x <= 6.2e+132) {
		tmp = (b * c) + ((j * k) * -27.0);
	} else {
		tmp = 18.0 * ((y * z) * (x * t));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k):
	tmp = 0
	if x <= -3.7e+145:
		tmp = 18.0 * (t * (y * (x * z)))
	elif x <= -3.55e+87:
		tmp = x * (i * -4.0)
	elif x <= -1250.0:
		tmp = (y * t) * (x * (18.0 * z))
	elif x <= 6.2e+132:
		tmp = (b * c) + ((j * k) * -27.0)
	else:
		tmp = 18.0 * ((y * z) * (x * t))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k)
	tmp = 0.0
	if (x <= -3.7e+145)
		tmp = Float64(18.0 * Float64(t * Float64(y * Float64(x * z))));
	elseif (x <= -3.55e+87)
		tmp = Float64(x * Float64(i * -4.0));
	elseif (x <= -1250.0)
		tmp = Float64(Float64(y * t) * Float64(x * Float64(18.0 * z)));
	elseif (x <= 6.2e+132)
		tmp = Float64(Float64(b * c) + Float64(Float64(j * k) * -27.0));
	else
		tmp = Float64(18.0 * Float64(Float64(y * z) * Float64(x * t)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	tmp = 0.0;
	if (x <= -3.7e+145)
		tmp = 18.0 * (t * (y * (x * z)));
	elseif (x <= -3.55e+87)
		tmp = x * (i * -4.0);
	elseif (x <= -1250.0)
		tmp = (y * t) * (x * (18.0 * z));
	elseif (x <= 6.2e+132)
		tmp = (b * c) + ((j * k) * -27.0);
	else
		tmp = 18.0 * ((y * z) * (x * t));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := If[LessEqual[x, -3.7e+145], N[(18.0 * N[(t * N[(y * N[(x * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -3.55e+87], N[(x * N[(i * -4.0), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -1250.0], N[(N[(y * t), $MachinePrecision] * N[(x * N[(18.0 * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 6.2e+132], N[(N[(b * c), $MachinePrecision] + N[(N[(j * k), $MachinePrecision] * -27.0), $MachinePrecision]), $MachinePrecision], N[(18.0 * N[(N[(y * z), $MachinePrecision] * N[(x * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

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

Alternative 17: 50.0% accurate, 1.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := b \cdot c + \left(x \cdot i\right) \cdot -4\\ \mathbf{if}\;x \leq -1.45 \cdot 10^{+144}:\\ \;\;\;\;18 \cdot \left(t \cdot \left(y \cdot \left(x \cdot z\right)\right)\right)\\ \mathbf{elif}\;x \leq -8.5 \cdot 10^{-44}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;x \leq 2.2 \cdot 10^{+112}:\\ \;\;\;\;b \cdot c + \left(j \cdot k\right) \cdot -27\\ \mathbf{elif}\;x \leq 1.2 \cdot 10^{+252}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;x \cdot \left(\left(y \cdot z\right) \cdot \left(18 \cdot t\right)\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k)
 :precision binary64
 (let* ((t_1 (+ (* b c) (* (* x i) -4.0))))
   (if (<= x -1.45e+144)
     (* 18.0 (* t (* y (* x z))))
     (if (<= x -8.5e-44)
       t_1
       (if (<= x 2.2e+112)
         (+ (* b c) (* (* j k) -27.0))
         (if (<= x 1.2e+252) t_1 (* x (* (* y z) (* 18.0 t)))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double t_1 = (b * c) + ((x * i) * -4.0);
	double tmp;
	if (x <= -1.45e+144) {
		tmp = 18.0 * (t * (y * (x * z)));
	} else if (x <= -8.5e-44) {
		tmp = t_1;
	} else if (x <= 2.2e+112) {
		tmp = (b * c) + ((j * k) * -27.0);
	} else if (x <= 1.2e+252) {
		tmp = t_1;
	} else {
		tmp = x * ((y * z) * (18.0 * t));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: t_1
    real(8) :: tmp
    t_1 = (b * c) + ((x * i) * (-4.0d0))
    if (x <= (-1.45d+144)) then
        tmp = 18.0d0 * (t * (y * (x * z)))
    else if (x <= (-8.5d-44)) then
        tmp = t_1
    else if (x <= 2.2d+112) then
        tmp = (b * c) + ((j * k) * (-27.0d0))
    else if (x <= 1.2d+252) then
        tmp = t_1
    else
        tmp = x * ((y * z) * (18.0d0 * t))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double t_1 = (b * c) + ((x * i) * -4.0);
	double tmp;
	if (x <= -1.45e+144) {
		tmp = 18.0 * (t * (y * (x * z)));
	} else if (x <= -8.5e-44) {
		tmp = t_1;
	} else if (x <= 2.2e+112) {
		tmp = (b * c) + ((j * k) * -27.0);
	} else if (x <= 1.2e+252) {
		tmp = t_1;
	} else {
		tmp = x * ((y * z) * (18.0 * t));
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k):
	t_1 = (b * c) + ((x * i) * -4.0)
	tmp = 0
	if x <= -1.45e+144:
		tmp = 18.0 * (t * (y * (x * z)))
	elif x <= -8.5e-44:
		tmp = t_1
	elif x <= 2.2e+112:
		tmp = (b * c) + ((j * k) * -27.0)
	elif x <= 1.2e+252:
		tmp = t_1
	else:
		tmp = x * ((y * z) * (18.0 * t))
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k)
	t_1 = Float64(Float64(b * c) + Float64(Float64(x * i) * -4.0))
	tmp = 0.0
	if (x <= -1.45e+144)
		tmp = Float64(18.0 * Float64(t * Float64(y * Float64(x * z))));
	elseif (x <= -8.5e-44)
		tmp = t_1;
	elseif (x <= 2.2e+112)
		tmp = Float64(Float64(b * c) + Float64(Float64(j * k) * -27.0));
	elseif (x <= 1.2e+252)
		tmp = t_1;
	else
		tmp = Float64(x * Float64(Float64(y * z) * Float64(18.0 * t)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	t_1 = (b * c) + ((x * i) * -4.0);
	tmp = 0.0;
	if (x <= -1.45e+144)
		tmp = 18.0 * (t * (y * (x * z)));
	elseif (x <= -8.5e-44)
		tmp = t_1;
	elseif (x <= 2.2e+112)
		tmp = (b * c) + ((j * k) * -27.0);
	elseif (x <= 1.2e+252)
		tmp = t_1;
	else
		tmp = x * ((y * z) * (18.0 * t));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := Block[{t$95$1 = N[(N[(b * c), $MachinePrecision] + N[(N[(x * i), $MachinePrecision] * -4.0), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[x, -1.45e+144], N[(18.0 * N[(t * N[(y * N[(x * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, -8.5e-44], t$95$1, If[LessEqual[x, 2.2e+112], N[(N[(b * c), $MachinePrecision] + N[(N[(j * k), $MachinePrecision] * -27.0), $MachinePrecision]), $MachinePrecision], If[LessEqual[x, 1.2e+252], t$95$1, N[(x * N[(N[(y * z), $MachinePrecision] * N[(18.0 * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

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

Alternative 18: 59.8% accurate, 1.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;x \leq -3200 \lor \neg \left(x \leq 3.6 \cdot 10^{+115}\right):\\ \;\;\;\;x \cdot \left(18 \cdot \left(t \cdot \left(y \cdot z\right)\right) - 4 \cdot i\right)\\ \mathbf{else}:\\ \;\;\;\;b \cdot c + \left(j \cdot k\right) \cdot -27\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k)
 :precision binary64
 (if (or (<= x -3200.0) (not (<= x 3.6e+115)))
   (* x (- (* 18.0 (* t (* y z))) (* 4.0 i)))
   (+ (* b c) (* (* j k) -27.0))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double tmp;
	if ((x <= -3200.0) || !(x <= 3.6e+115)) {
		tmp = x * ((18.0 * (t * (y * z))) - (4.0 * i));
	} else {
		tmp = (b * c) + ((j * k) * -27.0);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: tmp
    if ((x <= (-3200.0d0)) .or. (.not. (x <= 3.6d+115))) then
        tmp = x * ((18.0d0 * (t * (y * z))) - (4.0d0 * i))
    else
        tmp = (b * c) + ((j * k) * (-27.0d0))
    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 tmp;
	if ((x <= -3200.0) || !(x <= 3.6e+115)) {
		tmp = x * ((18.0 * (t * (y * z))) - (4.0 * i));
	} else {
		tmp = (b * c) + ((j * k) * -27.0);
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k):
	tmp = 0
	if (x <= -3200.0) or not (x <= 3.6e+115):
		tmp = x * ((18.0 * (t * (y * z))) - (4.0 * i))
	else:
		tmp = (b * c) + ((j * k) * -27.0)
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k)
	tmp = 0.0
	if ((x <= -3200.0) || !(x <= 3.6e+115))
		tmp = Float64(x * Float64(Float64(18.0 * Float64(t * Float64(y * z))) - Float64(4.0 * i)));
	else
		tmp = Float64(Float64(b * c) + Float64(Float64(j * k) * -27.0));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	tmp = 0.0;
	if ((x <= -3200.0) || ~((x <= 3.6e+115)))
		tmp = x * ((18.0 * (t * (y * z))) - (4.0 * i));
	else
		tmp = (b * c) + ((j * k) * -27.0);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := If[Or[LessEqual[x, -3200.0], N[Not[LessEqual[x, 3.6e+115]], $MachinePrecision]], N[(x * N[(N[(18.0 * N[(t * N[(y * z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(4.0 * i), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(b * c), $MachinePrecision] + N[(N[(j * k), $MachinePrecision] * -27.0), $MachinePrecision]), $MachinePrecision]]

Derivation

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

Alternative 19: 36.3% accurate, 2.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;b \cdot c \leq -8.6 \cdot 10^{+169} \lor \neg \left(b \cdot c \leq 4.2 \cdot 10^{+76}\right):\\ \;\;\;\;b \cdot c\\ \mathbf{else}:\\ \;\;\;\;\left(j \cdot k\right) \cdot -27\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k)
 :precision binary64
 (if (or (<= (* b c) -8.6e+169) (not (<= (* b c) 4.2e+76)))
   (* b c)
   (* (* j k) -27.0)))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double tmp;
	if (((b * c) <= -8.6e+169) || !((b * c) <= 4.2e+76)) {
		tmp = b * c;
	} else {
		tmp = (j * k) * -27.0;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: tmp
    if (((b * c) <= (-8.6d+169)) .or. (.not. ((b * c) <= 4.2d+76))) then
        tmp = b * c
    else
        tmp = (j * k) * (-27.0d0)
    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 tmp;
	if (((b * c) <= -8.6e+169) || !((b * c) <= 4.2e+76)) {
		tmp = b * c;
	} else {
		tmp = (j * k) * -27.0;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k):
	tmp = 0
	if ((b * c) <= -8.6e+169) or not ((b * c) <= 4.2e+76):
		tmp = b * c
	else:
		tmp = (j * k) * -27.0
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k)
	tmp = 0.0
	if ((Float64(b * c) <= -8.6e+169) || !(Float64(b * c) <= 4.2e+76))
		tmp = Float64(b * c);
	else
		tmp = Float64(Float64(j * k) * -27.0);
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	tmp = 0.0;
	if (((b * c) <= -8.6e+169) || ~(((b * c) <= 4.2e+76)))
		tmp = b * c;
	else
		tmp = (j * k) * -27.0;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := If[Or[LessEqual[N[(b * c), $MachinePrecision], -8.6e+169], N[Not[LessEqual[N[(b * c), $MachinePrecision], 4.2e+76]], $MachinePrecision]], N[(b * c), $MachinePrecision], N[(N[(j * k), $MachinePrecision] * -27.0), $MachinePrecision]]

Derivation

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

Alternative 20: 23.8% accurate, 10.3× speedup

Math

\[\begin{array}{l} \\ b \cdot c \end{array} \]

FPCore

(FPCore (x y z t a b c i j k) :precision binary64 (* b c))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	return b * c;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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
    code = b * c
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) {
	return b * c;
}

Python

def code(x, y, z, t, a, b, c, i, j, k):
	return b * c

Julia

function code(x, y, z, t, a, b, c, i, j, k)
	return Float64(b * c)
end

MATLAB

function tmp = code(x, y, z, t, a, b, c, i, j, k)
	tmp = b * c;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := N[(b * c), $MachinePrecision]

Derivation

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

Developer target: 89.3% accurate, 0.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \left(a \cdot t + i \cdot x\right) \cdot 4\\ t_2 := \left(\left(18 \cdot t\right) \cdot \left(\left(x \cdot y\right) \cdot z\right) - t_1\right) - \left(\left(k \cdot j\right) \cdot 27 - c \cdot b\right)\\ \mathbf{if}\;t < -1.6210815397541398 \cdot 10^{-69}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t < 165.68027943805222:\\ \;\;\;\;\left(\left(18 \cdot y\right) \cdot \left(x \cdot \left(z \cdot t\right)\right) - t_1\right) + \left(c \cdot b - 27 \cdot \left(k \cdot j\right)\right)\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c i j k)
 :precision binary64
 (let* ((t_1 (* (+ (* a t) (* i x)) 4.0))
        (t_2
         (-
          (- (* (* 18.0 t) (* (* x y) z)) t_1)
          (- (* (* k j) 27.0) (* c b)))))
   (if (< t -1.6210815397541398e-69)
     t_2
     (if (< t 165.68027943805222)
       (+ (- (* (* 18.0 y) (* x (* z t))) t_1) (- (* c b) (* 27.0 (* k j))))
       t_2))))

C

double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double t_1 = ((a * t) + (i * x)) * 4.0;
	double t_2 = (((18.0 * t) * ((x * y) * z)) - t_1) - (((k * j) * 27.0) - (c * b));
	double tmp;
	if (t < -1.6210815397541398e-69) {
		tmp = t_2;
	} else if (t < 165.68027943805222) {
		tmp = (((18.0 * y) * (x * (z * t))) - t_1) + ((c * b) - (27.0 * (k * j)));
	} else {
		tmp = t_2;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c, i, j, k)
    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) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = ((a * t) + (i * x)) * 4.0d0
    t_2 = (((18.0d0 * t) * ((x * y) * z)) - t_1) - (((k * j) * 27.0d0) - (c * b))
    if (t < (-1.6210815397541398d-69)) then
        tmp = t_2
    else if (t < 165.68027943805222d0) then
        tmp = (((18.0d0 * y) * (x * (z * t))) - t_1) + ((c * b) - (27.0d0 * (k * j)))
    else
        tmp = t_2
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c, double i, double j, double k) {
	double t_1 = ((a * t) + (i * x)) * 4.0;
	double t_2 = (((18.0 * t) * ((x * y) * z)) - t_1) - (((k * j) * 27.0) - (c * b));
	double tmp;
	if (t < -1.6210815397541398e-69) {
		tmp = t_2;
	} else if (t < 165.68027943805222) {
		tmp = (((18.0 * y) * (x * (z * t))) - t_1) + ((c * b) - (27.0 * (k * j)));
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c, i, j, k):
	t_1 = ((a * t) + (i * x)) * 4.0
	t_2 = (((18.0 * t) * ((x * y) * z)) - t_1) - (((k * j) * 27.0) - (c * b))
	tmp = 0
	if t < -1.6210815397541398e-69:
		tmp = t_2
	elif t < 165.68027943805222:
		tmp = (((18.0 * y) * (x * (z * t))) - t_1) + ((c * b) - (27.0 * (k * j)))
	else:
		tmp = t_2
	return tmp

Julia

function code(x, y, z, t, a, b, c, i, j, k)
	t_1 = Float64(Float64(Float64(a * t) + Float64(i * x)) * 4.0)
	t_2 = Float64(Float64(Float64(Float64(18.0 * t) * Float64(Float64(x * y) * z)) - t_1) - Float64(Float64(Float64(k * j) * 27.0) - Float64(c * b)))
	tmp = 0.0
	if (t < -1.6210815397541398e-69)
		tmp = t_2;
	elseif (t < 165.68027943805222)
		tmp = Float64(Float64(Float64(Float64(18.0 * y) * Float64(x * Float64(z * t))) - t_1) + Float64(Float64(c * b) - Float64(27.0 * Float64(k * j))));
	else
		tmp = t_2;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c, i, j, k)
	t_1 = ((a * t) + (i * x)) * 4.0;
	t_2 = (((18.0 * t) * ((x * y) * z)) - t_1) - (((k * j) * 27.0) - (c * b));
	tmp = 0.0;
	if (t < -1.6210815397541398e-69)
		tmp = t_2;
	elseif (t < 165.68027943805222)
		tmp = (((18.0 * y) * (x * (z * t))) - t_1) + ((c * b) - (27.0 * (k * j)));
	else
		tmp = t_2;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_, i_, j_, k_] := Block[{t$95$1 = N[(N[(N[(a * t), $MachinePrecision] + N[(i * x), $MachinePrecision]), $MachinePrecision] * 4.0), $MachinePrecision]}, Block[{t$95$2 = N[(N[(N[(N[(18.0 * t), $MachinePrecision] * N[(N[(x * y), $MachinePrecision] * z), $MachinePrecision]), $MachinePrecision] - t$95$1), $MachinePrecision] - N[(N[(N[(k * j), $MachinePrecision] * 27.0), $MachinePrecision] - N[(c * b), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[Less[t, -1.6210815397541398e-69], t$95$2, If[Less[t, 165.68027943805222], N[(N[(N[(N[(18.0 * y), $MachinePrecision] * N[(x * N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$1), $MachinePrecision] + N[(N[(c * b), $MachinePrecision] - N[(27.0 * N[(k * j), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$2]]]]

Reproduce

herbie shell --seed 2023350 
(FPCore (x y z t a b c i j k)
  :name "Diagrams.Solve.Polynomial:cubForm  from diagrams-solve-0.1, E"
  :precision binary64

  :herbie-target
  (if (< t -1.6210815397541398e-69) (- (- (* (* 18.0 t) (* (* x y) z)) (* (+ (* a t) (* i x)) 4.0)) (- (* (* k j) 27.0) (* c b))) (if (< t 165.68027943805222) (+ (- (* (* 18.0 y) (* x (* z t))) (* (+ (* a t) (* i x)) 4.0)) (- (* c b) (* 27.0 (* k j)))) (- (- (* (* 18.0 t) (* (* x y) z)) (* (+ (* a t) (* i x)) 4.0)) (- (* (* k j) 27.0) (* c b)))))

  (- (- (+ (- (* (* (* (* x 18.0) y) z) t) (* (* a 4.0) t)) (* b c)) (* (* x 4.0) i)) (* (* j 27.0) k)))