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

Percentage Accurate: 78.7% → 88.2%

Time: 22.7s

Alternatives: 18

Speedup: 0.8×

• 37.5% of points produce a very large (infinite) output. You may want to add a precondition.

Specification

Math

\[\begin{array}{l} \\ \frac{\left(\left(x \cdot 9\right) \cdot y - \left(\left(z \cdot 4\right) \cdot t\right) \cdot a\right) + b}{z \cdot c} \end{array} \]

FPCore

(FPCore (x y z t a b c)
 :precision binary64
 (/ (+ (- (* (* x 9.0) y) (* (* (* z 4.0) t) a)) b) (* z c)))

C

double code(double x, double y, double z, double t, double a, double b, double c) {
	return ((((x * 9.0) * y) - (((z * 4.0) * t) * a)) + b) / (z * c);
}

Fortran

real(8) function code(x, y, z, t, a, b, c)
    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
    code = ((((x * 9.0d0) * y) - (((z * 4.0d0) * t) * a)) + b) / (z * c)
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c) {
	return ((((x * 9.0) * y) - (((z * 4.0) * t) * a)) + b) / (z * c);
}

Python

def code(x, y, z, t, a, b, c):
	return ((((x * 9.0) * y) - (((z * 4.0) * t) * a)) + b) / (z * c)

Julia

function code(x, y, z, t, a, b, c)
	return Float64(Float64(Float64(Float64(Float64(x * 9.0) * y) - Float64(Float64(Float64(z * 4.0) * t) * a)) + b) / Float64(z * c))
end

MATLAB

function tmp = code(x, y, z, t, a, b, c)
	tmp = ((((x * 9.0) * y) - (((z * 4.0) * t) * a)) + b) / (z * c);
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_] := N[(N[(N[(N[(N[(x * 9.0), $MachinePrecision] * y), $MachinePrecision] - N[(N[(N[(z * 4.0), $MachinePrecision] * t), $MachinePrecision] * a), $MachinePrecision]), $MachinePrecision] + b), $MachinePrecision] / N[(z * c), $MachinePrecision]), $MachinePrecision]

Initial Program: 78.7% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ \frac{\left(\left(x \cdot 9\right) \cdot y - \left(\left(z \cdot 4\right) \cdot t\right) \cdot a\right) + b}{z \cdot c} \end{array} \]

FPCore

(FPCore (x y z t a b c)
 :precision binary64
 (/ (+ (- (* (* x 9.0) y) (* (* (* z 4.0) t) a)) b) (* z c)))

C

double code(double x, double y, double z, double t, double a, double b, double c) {
	return ((((x * 9.0) * y) - (((z * 4.0) * t) * a)) + b) / (z * c);
}

Fortran

real(8) function code(x, y, z, t, a, b, c)
    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
    code = ((((x * 9.0d0) * y) - (((z * 4.0d0) * t) * a)) + b) / (z * c)
end function

Java

public static double code(double x, double y, double z, double t, double a, double b, double c) {
	return ((((x * 9.0) * y) - (((z * 4.0) * t) * a)) + b) / (z * c);
}

Python

def code(x, y, z, t, a, b, c):
	return ((((x * 9.0) * y) - (((z * 4.0) * t) * a)) + b) / (z * c)

Julia

function code(x, y, z, t, a, b, c)
	return Float64(Float64(Float64(Float64(Float64(x * 9.0) * y) - Float64(Float64(Float64(z * 4.0) * t) * a)) + b) / Float64(z * c))
end

MATLAB

function tmp = code(x, y, z, t, a, b, c)
	tmp = ((((x * 9.0) * y) - (((z * 4.0) * t) * a)) + b) / (z * c);
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_] := N[(N[(N[(N[(N[(x * 9.0), $MachinePrecision] * y), $MachinePrecision] - N[(N[(N[(z * 4.0), $MachinePrecision] * t), $MachinePrecision] * a), $MachinePrecision]), $MachinePrecision] + b), $MachinePrecision] / N[(z * c), $MachinePrecision]), $MachinePrecision]

Alternative 1: 88.2% accurate, 0.1× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c] = \mathsf{sort}([x, y, z, t, a, b, c])\\ \\ \begin{array}{l} \mathbf{if}\;z \leq -1.08 \cdot 10^{+29} \lor \neg \left(z \leq 3.5 \cdot 10^{-94}\right):\\ \;\;\;\;\mathsf{fma}\left(-4, \frac{a}{\frac{c}{t}}, \mathsf{fma}\left(9, \frac{x}{c} \cdot \frac{y}{z}, \frac{b}{z \cdot c}\right)\right)\\ \mathbf{else}:\\ \;\;\;\;\frac{b + \left(y \cdot \left(9 \cdot x\right) - a \cdot \left(t \cdot \left(z \cdot 4\right)\right)\right)}{z \cdot c}\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c)
 :precision binary64
 (if (or (<= z -1.08e+29) (not (<= z 3.5e-94)))
   (fma -4.0 (/ a (/ c t)) (fma 9.0 (* (/ x c) (/ y z)) (/ b (* z c))))
   (/ (+ b (- (* y (* 9.0 x)) (* a (* t (* z 4.0))))) (* z c))))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c);
double code(double x, double y, double z, double t, double a, double b, double c) {
	double tmp;
	if ((z <= -1.08e+29) || !(z <= 3.5e-94)) {
		tmp = fma(-4.0, (a / (c / t)), fma(9.0, ((x / c) * (y / z)), (b / (z * c))));
	} else {
		tmp = (b + ((y * (9.0 * x)) - (a * (t * (z * 4.0))))) / (z * c);
	}
	return tmp;
}

Julia

x, y, z, t, a, b, c = sort([x, y, z, t, a, b, c])
function code(x, y, z, t, a, b, c)
	tmp = 0.0
	if ((z <= -1.08e+29) || !(z <= 3.5e-94))
		tmp = fma(-4.0, Float64(a / Float64(c / t)), fma(9.0, Float64(Float64(x / c) * Float64(y / z)), Float64(b / Float64(z * c))));
	else
		tmp = Float64(Float64(b + Float64(Float64(y * Float64(9.0 * x)) - Float64(a * Float64(t * Float64(z * 4.0))))) / Float64(z * c));
	end
	return tmp
end

Wolfram

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_] := If[Or[LessEqual[z, -1.08e+29], N[Not[LessEqual[z, 3.5e-94]], $MachinePrecision]], N[(-4.0 * N[(a / N[(c / t), $MachinePrecision]), $MachinePrecision] + N[(9.0 * N[(N[(x / c), $MachinePrecision] * N[(y / z), $MachinePrecision]), $MachinePrecision] + N[(b / N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(b + N[(N[(y * N[(9.0 * x), $MachinePrecision]), $MachinePrecision] - N[(a * N[(t * N[(z * 4.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(z * c), $MachinePrecision]), $MachinePrecision]]

Derivation

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

Alternative 2: 88.7% accurate, 0.1× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c] = \mathsf{sort}([x, y, z, t, a, b, c])\\ \\ \begin{array}{l} t_1 := \frac{b + \left(y \cdot \left(9 \cdot x\right) - a \cdot \left(t \cdot \left(z \cdot 4\right)\right)\right)}{z \cdot c}\\ \mathbf{if}\;t_1 \leq -2 \cdot 10^{+14}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t_1 \leq 5 \cdot 10^{-242}:\\ \;\;\;\;\frac{b + \mathsf{fma}\left(x, 9 \cdot y, a \cdot \left(z \cdot \left(-4 \cdot t\right)\right)\right)}{z} \cdot \frac{1}{c}\\ \mathbf{elif}\;t_1 \leq \infty:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;\frac{9}{z} \cdot \frac{x}{\frac{c}{y}} - \frac{a}{\frac{c}{t}} \cdot 4\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c)
 :precision binary64
 (let* ((t_1 (/ (+ b (- (* y (* 9.0 x)) (* a (* t (* z 4.0))))) (* z c))))
   (if (<= t_1 -2e+14)
     t_1
     (if (<= t_1 5e-242)
       (* (/ (+ b (fma x (* 9.0 y) (* a (* z (* -4.0 t))))) z) (/ 1.0 c))
       (if (<= t_1 INFINITY)
         t_1
         (- (* (/ 9.0 z) (/ x (/ c y))) (* (/ a (/ c t)) 4.0)))))))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c);
double code(double x, double y, double z, double t, double a, double b, double c) {
	double t_1 = (b + ((y * (9.0 * x)) - (a * (t * (z * 4.0))))) / (z * c);
	double tmp;
	if (t_1 <= -2e+14) {
		tmp = t_1;
	} else if (t_1 <= 5e-242) {
		tmp = ((b + fma(x, (9.0 * y), (a * (z * (-4.0 * t))))) / z) * (1.0 / c);
	} else if (t_1 <= ((double) INFINITY)) {
		tmp = t_1;
	} else {
		tmp = ((9.0 / z) * (x / (c / y))) - ((a / (c / t)) * 4.0);
	}
	return tmp;
}

Julia

x, y, z, t, a, b, c = sort([x, y, z, t, a, b, c])
function code(x, y, z, t, a, b, c)
	t_1 = Float64(Float64(b + Float64(Float64(y * Float64(9.0 * x)) - Float64(a * Float64(t * Float64(z * 4.0))))) / Float64(z * c))
	tmp = 0.0
	if (t_1 <= -2e+14)
		tmp = t_1;
	elseif (t_1 <= 5e-242)
		tmp = Float64(Float64(Float64(b + fma(x, Float64(9.0 * y), Float64(a * Float64(z * Float64(-4.0 * t))))) / z) * Float64(1.0 / c));
	elseif (t_1 <= Inf)
		tmp = t_1;
	else
		tmp = Float64(Float64(Float64(9.0 / z) * Float64(x / Float64(c / y))) - Float64(Float64(a / Float64(c / t)) * 4.0));
	end
	return tmp
end

Wolfram

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_] := Block[{t$95$1 = N[(N[(b + N[(N[(y * N[(9.0 * x), $MachinePrecision]), $MachinePrecision] - N[(a * N[(t * N[(z * 4.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(z * c), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$1, -2e+14], t$95$1, If[LessEqual[t$95$1, 5e-242], N[(N[(N[(b + N[(x * N[(9.0 * y), $MachinePrecision] + N[(a * N[(z * N[(-4.0 * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / z), $MachinePrecision] * N[(1.0 / c), $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$1, Infinity], t$95$1, N[(N[(N[(9.0 / z), $MachinePrecision] * N[(x / N[(c / y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(a / N[(c / t), $MachinePrecision]), $MachinePrecision] * 4.0), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

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

Alternative 3: 87.5% accurate, 0.1× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c] = \mathsf{sort}([x, y, z, t, a, b, c])\\ \\ \begin{array}{l} t_1 := y \cdot \left(9 \cdot x\right)\\ t_2 := \frac{b + \left(t_1 - a \cdot \left(t \cdot \left(z \cdot 4\right)\right)\right)}{z \cdot c}\\ \mathbf{if}\;t_2 \leq -2 \cdot 10^{-290}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t_2 \leq 0:\\ \;\;\;\;\frac{1}{\frac{z}{\frac{\mathsf{fma}\left(-4, a \cdot \left(z \cdot t\right), t_1\right)}{c}}}\\ \mathbf{elif}\;t_2 \leq \infty:\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;\frac{9}{z} \cdot \frac{x}{\frac{c}{y}} - \frac{a}{\frac{c}{t}} \cdot 4\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c)
 :precision binary64
 (let* ((t_1 (* y (* 9.0 x)))
        (t_2 (/ (+ b (- t_1 (* a (* t (* z 4.0))))) (* z c))))
   (if (<= t_2 -2e-290)
     t_2
     (if (<= t_2 0.0)
       (/ 1.0 (/ z (/ (fma -4.0 (* a (* z t)) t_1) c)))
       (if (<= t_2 INFINITY)
         t_2
         (- (* (/ 9.0 z) (/ x (/ c y))) (* (/ a (/ c t)) 4.0)))))))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c);
double code(double x, double y, double z, double t, double a, double b, double c) {
	double t_1 = y * (9.0 * x);
	double t_2 = (b + (t_1 - (a * (t * (z * 4.0))))) / (z * c);
	double tmp;
	if (t_2 <= -2e-290) {
		tmp = t_2;
	} else if (t_2 <= 0.0) {
		tmp = 1.0 / (z / (fma(-4.0, (a * (z * t)), t_1) / c));
	} else if (t_2 <= ((double) INFINITY)) {
		tmp = t_2;
	} else {
		tmp = ((9.0 / z) * (x / (c / y))) - ((a / (c / t)) * 4.0);
	}
	return tmp;
}

Julia

x, y, z, t, a, b, c = sort([x, y, z, t, a, b, c])
function code(x, y, z, t, a, b, c)
	t_1 = Float64(y * Float64(9.0 * x))
	t_2 = Float64(Float64(b + Float64(t_1 - Float64(a * Float64(t * Float64(z * 4.0))))) / Float64(z * c))
	tmp = 0.0
	if (t_2 <= -2e-290)
		tmp = t_2;
	elseif (t_2 <= 0.0)
		tmp = Float64(1.0 / Float64(z / Float64(fma(-4.0, Float64(a * Float64(z * t)), t_1) / c)));
	elseif (t_2 <= Inf)
		tmp = t_2;
	else
		tmp = Float64(Float64(Float64(9.0 / z) * Float64(x / Float64(c / y))) - Float64(Float64(a / Float64(c / t)) * 4.0));
	end
	return tmp
end

Wolfram

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_] := Block[{t$95$1 = N[(y * N[(9.0 * x), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(b + N[(t$95$1 - N[(a * N[(t * N[(z * 4.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(z * c), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$2, -2e-290], t$95$2, If[LessEqual[t$95$2, 0.0], N[(1.0 / N[(z / N[(N[(-4.0 * N[(a * N[(z * t), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision] / c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$2, Infinity], t$95$2, N[(N[(N[(9.0 / z), $MachinePrecision] * N[(x / N[(c / y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(a / N[(c / t), $MachinePrecision]), $MachinePrecision] * 4.0), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

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

Alternative 4: 85.4% accurate, 0.1× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c] = \mathsf{sort}([x, y, z, t, a, b, c])\\ \\ \begin{array}{l} \mathbf{if}\;\frac{b + \left(y \cdot \left(9 \cdot x\right) - a \cdot \left(t \cdot \left(z \cdot 4\right)\right)\right)}{z \cdot c} \leq \infty:\\ \;\;\;\;\frac{1}{z} \cdot \frac{b + \mathsf{fma}\left(x, 9 \cdot y, a \cdot \left(z \cdot \left(-4 \cdot t\right)\right)\right)}{c}\\ \mathbf{else}:\\ \;\;\;\;\frac{9}{z} \cdot \frac{x}{\frac{c}{y}} - \frac{a}{\frac{c}{t}} \cdot 4\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c)
 :precision binary64
 (if (<= (/ (+ b (- (* y (* 9.0 x)) (* a (* t (* z 4.0))))) (* z c)) INFINITY)
   (* (/ 1.0 z) (/ (+ b (fma x (* 9.0 y) (* a (* z (* -4.0 t))))) c))
   (- (* (/ 9.0 z) (/ x (/ c y))) (* (/ a (/ c t)) 4.0))))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c);
double code(double x, double y, double z, double t, double a, double b, double c) {
	double tmp;
	if (((b + ((y * (9.0 * x)) - (a * (t * (z * 4.0))))) / (z * c)) <= ((double) INFINITY)) {
		tmp = (1.0 / z) * ((b + fma(x, (9.0 * y), (a * (z * (-4.0 * t))))) / c);
	} else {
		tmp = ((9.0 / z) * (x / (c / y))) - ((a / (c / t)) * 4.0);
	}
	return tmp;
}

Julia

x, y, z, t, a, b, c = sort([x, y, z, t, a, b, c])
function code(x, y, z, t, a, b, c)
	tmp = 0.0
	if (Float64(Float64(b + Float64(Float64(y * Float64(9.0 * x)) - Float64(a * Float64(t * Float64(z * 4.0))))) / Float64(z * c)) <= Inf)
		tmp = Float64(Float64(1.0 / z) * Float64(Float64(b + fma(x, Float64(9.0 * y), Float64(a * Float64(z * Float64(-4.0 * t))))) / c));
	else
		tmp = Float64(Float64(Float64(9.0 / z) * Float64(x / Float64(c / y))) - Float64(Float64(a / Float64(c / t)) * 4.0));
	end
	return tmp
end

Wolfram

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_] := If[LessEqual[N[(N[(b + N[(N[(y * N[(9.0 * x), $MachinePrecision]), $MachinePrecision] - N[(a * N[(t * N[(z * 4.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(z * c), $MachinePrecision]), $MachinePrecision], Infinity], N[(N[(1.0 / z), $MachinePrecision] * N[(N[(b + N[(x * N[(9.0 * y), $MachinePrecision] + N[(a * N[(z * N[(-4.0 * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / c), $MachinePrecision]), $MachinePrecision], N[(N[(N[(9.0 / z), $MachinePrecision] * N[(x / N[(c / y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(a / N[(c / t), $MachinePrecision]), $MachinePrecision] * 4.0), $MachinePrecision]), $MachinePrecision]]

Derivation

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

Alternative 5: 80.9% accurate, 0.2× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c] = \mathsf{sort}([x, y, z, t, a, b, c])\\ \\ \begin{array}{l} \mathbf{if}\;c \leq 6.4 \cdot 10^{-87}:\\ \;\;\;\;\left(b + \mathsf{fma}\left(x, 9 \cdot y, a \cdot \left(z \cdot \left(-4 \cdot t\right)\right)\right)\right) \cdot \frac{1}{z \cdot c}\\ \mathbf{elif}\;c \leq 4.1 \cdot 10^{+139} \lor \neg \left(c \leq 2.55 \cdot 10^{+250}\right):\\ \;\;\;\;\left(\frac{b}{z \cdot c} + 9 \cdot \frac{x \cdot y}{z \cdot c}\right) - 4 \cdot \frac{a \cdot t}{c}\\ \mathbf{else}:\\ \;\;\;\;\frac{9}{z} \cdot \frac{x}{\frac{c}{y}} - \frac{a}{\frac{c}{t}} \cdot 4\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c)
 :precision binary64
 (if (<= c 6.4e-87)
   (* (+ b (fma x (* 9.0 y) (* a (* z (* -4.0 t))))) (/ 1.0 (* z c)))
   (if (or (<= c 4.1e+139) (not (<= c 2.55e+250)))
     (- (+ (/ b (* z c)) (* 9.0 (/ (* x y) (* z c)))) (* 4.0 (/ (* a t) c)))
     (- (* (/ 9.0 z) (/ x (/ c y))) (* (/ a (/ c t)) 4.0)))))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c);
double code(double x, double y, double z, double t, double a, double b, double c) {
	double tmp;
	if (c <= 6.4e-87) {
		tmp = (b + fma(x, (9.0 * y), (a * (z * (-4.0 * t))))) * (1.0 / (z * c));
	} else if ((c <= 4.1e+139) || !(c <= 2.55e+250)) {
		tmp = ((b / (z * c)) + (9.0 * ((x * y) / (z * c)))) - (4.0 * ((a * t) / c));
	} else {
		tmp = ((9.0 / z) * (x / (c / y))) - ((a / (c / t)) * 4.0);
	}
	return tmp;
}

Julia

x, y, z, t, a, b, c = sort([x, y, z, t, a, b, c])
function code(x, y, z, t, a, b, c)
	tmp = 0.0
	if (c <= 6.4e-87)
		tmp = Float64(Float64(b + fma(x, Float64(9.0 * y), Float64(a * Float64(z * Float64(-4.0 * t))))) * Float64(1.0 / Float64(z * c)));
	elseif ((c <= 4.1e+139) || !(c <= 2.55e+250))
		tmp = Float64(Float64(Float64(b / Float64(z * c)) + Float64(9.0 * Float64(Float64(x * y) / Float64(z * c)))) - Float64(4.0 * Float64(Float64(a * t) / c)));
	else
		tmp = Float64(Float64(Float64(9.0 / z) * Float64(x / Float64(c / y))) - Float64(Float64(a / Float64(c / t)) * 4.0));
	end
	return tmp
end

Wolfram

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_] := If[LessEqual[c, 6.4e-87], N[(N[(b + N[(x * N[(9.0 * y), $MachinePrecision] + N[(a * N[(z * N[(-4.0 * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * N[(1.0 / N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[Or[LessEqual[c, 4.1e+139], N[Not[LessEqual[c, 2.55e+250]], $MachinePrecision]], N[(N[(N[(b / N[(z * c), $MachinePrecision]), $MachinePrecision] + N[(9.0 * N[(N[(x * y), $MachinePrecision] / N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(4.0 * N[(N[(a * t), $MachinePrecision] / c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(N[(9.0 / z), $MachinePrecision] * N[(x / N[(c / y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(a / N[(c / t), $MachinePrecision]), $MachinePrecision] * 4.0), $MachinePrecision]), $MachinePrecision]]]

Derivation

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

Alternative 6: 87.5% accurate, 0.2× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c] = \mathsf{sort}([x, y, z, t, a, b, c])\\ \\ \begin{array}{l} t_1 := \frac{b + \left(y \cdot \left(9 \cdot x\right) - a \cdot \left(t \cdot \left(z \cdot 4\right)\right)\right)}{z \cdot c}\\ \mathbf{if}\;t_1 \leq -5 \cdot 10^{-196}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t_1 \leq 0:\\ \;\;\;\;\frac{\frac{b + \left(z \cdot t\right) \cdot \left(-4 \cdot a\right)}{c}}{z}\\ \mathbf{elif}\;t_1 \leq \infty:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;\frac{9}{z} \cdot \frac{x}{\frac{c}{y}} - \frac{a}{\frac{c}{t}} \cdot 4\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c)
 :precision binary64
 (let* ((t_1 (/ (+ b (- (* y (* 9.0 x)) (* a (* t (* z 4.0))))) (* z c))))
   (if (<= t_1 -5e-196)
     t_1
     (if (<= t_1 0.0)
       (/ (/ (+ b (* (* z t) (* -4.0 a))) c) z)
       (if (<= t_1 INFINITY)
         t_1
         (- (* (/ 9.0 z) (/ x (/ c y))) (* (/ a (/ c t)) 4.0)))))))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c);
double code(double x, double y, double z, double t, double a, double b, double c) {
	double t_1 = (b + ((y * (9.0 * x)) - (a * (t * (z * 4.0))))) / (z * c);
	double tmp;
	if (t_1 <= -5e-196) {
		tmp = t_1;
	} else if (t_1 <= 0.0) {
		tmp = ((b + ((z * t) * (-4.0 * a))) / c) / z;
	} else if (t_1 <= ((double) INFINITY)) {
		tmp = t_1;
	} else {
		tmp = ((9.0 / z) * (x / (c / y))) - ((a / (c / t)) * 4.0);
	}
	return tmp;
}

Java

assert x < y && y < z && z < t && t < a && a < b && b < c;
public static double code(double x, double y, double z, double t, double a, double b, double c) {
	double t_1 = (b + ((y * (9.0 * x)) - (a * (t * (z * 4.0))))) / (z * c);
	double tmp;
	if (t_1 <= -5e-196) {
		tmp = t_1;
	} else if (t_1 <= 0.0) {
		tmp = ((b + ((z * t) * (-4.0 * a))) / c) / z;
	} else if (t_1 <= Double.POSITIVE_INFINITY) {
		tmp = t_1;
	} else {
		tmp = ((9.0 / z) * (x / (c / y))) - ((a / (c / t)) * 4.0);
	}
	return tmp;
}

Python

[x, y, z, t, a, b, c] = sort([x, y, z, t, a, b, c])
def code(x, y, z, t, a, b, c):
	t_1 = (b + ((y * (9.0 * x)) - (a * (t * (z * 4.0))))) / (z * c)
	tmp = 0
	if t_1 <= -5e-196:
		tmp = t_1
	elif t_1 <= 0.0:
		tmp = ((b + ((z * t) * (-4.0 * a))) / c) / z
	elif t_1 <= math.inf:
		tmp = t_1
	else:
		tmp = ((9.0 / z) * (x / (c / y))) - ((a / (c / t)) * 4.0)
	return tmp

Julia

x, y, z, t, a, b, c = sort([x, y, z, t, a, b, c])
function code(x, y, z, t, a, b, c)
	t_1 = Float64(Float64(b + Float64(Float64(y * Float64(9.0 * x)) - Float64(a * Float64(t * Float64(z * 4.0))))) / Float64(z * c))
	tmp = 0.0
	if (t_1 <= -5e-196)
		tmp = t_1;
	elseif (t_1 <= 0.0)
		tmp = Float64(Float64(Float64(b + Float64(Float64(z * t) * Float64(-4.0 * a))) / c) / z);
	elseif (t_1 <= Inf)
		tmp = t_1;
	else
		tmp = Float64(Float64(Float64(9.0 / z) * Float64(x / Float64(c / y))) - Float64(Float64(a / Float64(c / t)) * 4.0));
	end
	return tmp
end

MATLAB

x, y, z, t, a, b, c = num2cell(sort([x, y, z, t, a, b, c])){:}
function tmp_2 = code(x, y, z, t, a, b, c)
	t_1 = (b + ((y * (9.0 * x)) - (a * (t * (z * 4.0))))) / (z * c);
	tmp = 0.0;
	if (t_1 <= -5e-196)
		tmp = t_1;
	elseif (t_1 <= 0.0)
		tmp = ((b + ((z * t) * (-4.0 * a))) / c) / z;
	elseif (t_1 <= Inf)
		tmp = t_1;
	else
		tmp = ((9.0 / z) * (x / (c / y))) - ((a / (c / t)) * 4.0);
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_] := Block[{t$95$1 = N[(N[(b + N[(N[(y * N[(9.0 * x), $MachinePrecision]), $MachinePrecision] - N[(a * N[(t * N[(z * 4.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(z * c), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$1, -5e-196], t$95$1, If[LessEqual[t$95$1, 0.0], N[(N[(N[(b + N[(N[(z * t), $MachinePrecision] * N[(-4.0 * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / c), $MachinePrecision] / z), $MachinePrecision], If[LessEqual[t$95$1, Infinity], t$95$1, N[(N[(N[(9.0 / z), $MachinePrecision] * N[(x / N[(c / y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(a / N[(c / t), $MachinePrecision]), $MachinePrecision] * 4.0), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

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

Alternative 7: 73.9% accurate, 0.5× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c] = \mathsf{sort}([x, y, z, t, a, b, c])\\ \\ \begin{array}{l} t_1 := y \cdot \left(9 \cdot x\right)\\ \mathbf{if}\;t_1 \leq -1 \cdot 10^{+297}:\\ \;\;\;\;\frac{9}{\frac{c}{y} \cdot \frac{z}{x}}\\ \mathbf{elif}\;t_1 \leq -2 \cdot 10^{+24}:\\ \;\;\;\;\frac{\frac{b + 9 \cdot \left(x \cdot y\right)}{c}}{z}\\ \mathbf{elif}\;t_1 \leq 10^{-115}:\\ \;\;\;\;\frac{\frac{b + \left(z \cdot t\right) \cdot \left(-4 \cdot a\right)}{c}}{z}\\ \mathbf{elif}\;t_1 \leq 10^{+256}:\\ \;\;\;\;9 \cdot \frac{x \cdot y}{z \cdot c} + -4 \cdot \frac{a \cdot t}{c}\\ \mathbf{else}:\\ \;\;\;\;\frac{x \cdot \frac{9}{z}}{\frac{c}{y}}\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c)
 :precision binary64
 (let* ((t_1 (* y (* 9.0 x))))
   (if (<= t_1 -1e+297)
     (/ 9.0 (* (/ c y) (/ z x)))
     (if (<= t_1 -2e+24)
       (/ (/ (+ b (* 9.0 (* x y))) c) z)
       (if (<= t_1 1e-115)
         (/ (/ (+ b (* (* z t) (* -4.0 a))) c) z)
         (if (<= t_1 1e+256)
           (+ (* 9.0 (/ (* x y) (* z c))) (* -4.0 (/ (* a t) c)))
           (/ (* x (/ 9.0 z)) (/ c y))))))))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c);
double code(double x, double y, double z, double t, double a, double b, double c) {
	double t_1 = y * (9.0 * x);
	double tmp;
	if (t_1 <= -1e+297) {
		tmp = 9.0 / ((c / y) * (z / x));
	} else if (t_1 <= -2e+24) {
		tmp = ((b + (9.0 * (x * y))) / c) / z;
	} else if (t_1 <= 1e-115) {
		tmp = ((b + ((z * t) * (-4.0 * a))) / c) / z;
	} else if (t_1 <= 1e+256) {
		tmp = (9.0 * ((x * y) / (z * c))) + (-4.0 * ((a * t) / c));
	} else {
		tmp = (x * (9.0 / z)) / (c / y);
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b, c)
    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) :: t_1
    real(8) :: tmp
    t_1 = y * (9.0d0 * x)
    if (t_1 <= (-1d+297)) then
        tmp = 9.0d0 / ((c / y) * (z / x))
    else if (t_1 <= (-2d+24)) then
        tmp = ((b + (9.0d0 * (x * y))) / c) / z
    else if (t_1 <= 1d-115) then
        tmp = ((b + ((z * t) * ((-4.0d0) * a))) / c) / z
    else if (t_1 <= 1d+256) then
        tmp = (9.0d0 * ((x * y) / (z * c))) + ((-4.0d0) * ((a * t) / c))
    else
        tmp = (x * (9.0d0 / z)) / (c / y)
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b && b < c;
public static double code(double x, double y, double z, double t, double a, double b, double c) {
	double t_1 = y * (9.0 * x);
	double tmp;
	if (t_1 <= -1e+297) {
		tmp = 9.0 / ((c / y) * (z / x));
	} else if (t_1 <= -2e+24) {
		tmp = ((b + (9.0 * (x * y))) / c) / z;
	} else if (t_1 <= 1e-115) {
		tmp = ((b + ((z * t) * (-4.0 * a))) / c) / z;
	} else if (t_1 <= 1e+256) {
		tmp = (9.0 * ((x * y) / (z * c))) + (-4.0 * ((a * t) / c));
	} else {
		tmp = (x * (9.0 / z)) / (c / y);
	}
	return tmp;
}

Python

[x, y, z, t, a, b, c] = sort([x, y, z, t, a, b, c])
def code(x, y, z, t, a, b, c):
	t_1 = y * (9.0 * x)
	tmp = 0
	if t_1 <= -1e+297:
		tmp = 9.0 / ((c / y) * (z / x))
	elif t_1 <= -2e+24:
		tmp = ((b + (9.0 * (x * y))) / c) / z
	elif t_1 <= 1e-115:
		tmp = ((b + ((z * t) * (-4.0 * a))) / c) / z
	elif t_1 <= 1e+256:
		tmp = (9.0 * ((x * y) / (z * c))) + (-4.0 * ((a * t) / c))
	else:
		tmp = (x * (9.0 / z)) / (c / y)
	return tmp

Julia

x, y, z, t, a, b, c = sort([x, y, z, t, a, b, c])
function code(x, y, z, t, a, b, c)
	t_1 = Float64(y * Float64(9.0 * x))
	tmp = 0.0
	if (t_1 <= -1e+297)
		tmp = Float64(9.0 / Float64(Float64(c / y) * Float64(z / x)));
	elseif (t_1 <= -2e+24)
		tmp = Float64(Float64(Float64(b + Float64(9.0 * Float64(x * y))) / c) / z);
	elseif (t_1 <= 1e-115)
		tmp = Float64(Float64(Float64(b + Float64(Float64(z * t) * Float64(-4.0 * a))) / c) / z);
	elseif (t_1 <= 1e+256)
		tmp = Float64(Float64(9.0 * Float64(Float64(x * y) / Float64(z * c))) + Float64(-4.0 * Float64(Float64(a * t) / c)));
	else
		tmp = Float64(Float64(x * Float64(9.0 / z)) / Float64(c / y));
	end
	return tmp
end

MATLAB

x, y, z, t, a, b, c = num2cell(sort([x, y, z, t, a, b, c])){:}
function tmp_2 = code(x, y, z, t, a, b, c)
	t_1 = y * (9.0 * x);
	tmp = 0.0;
	if (t_1 <= -1e+297)
		tmp = 9.0 / ((c / y) * (z / x));
	elseif (t_1 <= -2e+24)
		tmp = ((b + (9.0 * (x * y))) / c) / z;
	elseif (t_1 <= 1e-115)
		tmp = ((b + ((z * t) * (-4.0 * a))) / c) / z;
	elseif (t_1 <= 1e+256)
		tmp = (9.0 * ((x * y) / (z * c))) + (-4.0 * ((a * t) / c));
	else
		tmp = (x * (9.0 / z)) / (c / y);
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_] := Block[{t$95$1 = N[(y * N[(9.0 * x), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$1, -1e+297], N[(9.0 / N[(N[(c / y), $MachinePrecision] * N[(z / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$1, -2e+24], N[(N[(N[(b + N[(9.0 * N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / c), $MachinePrecision] / z), $MachinePrecision], If[LessEqual[t$95$1, 1e-115], N[(N[(N[(b + N[(N[(z * t), $MachinePrecision] * N[(-4.0 * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / c), $MachinePrecision] / z), $MachinePrecision], If[LessEqual[t$95$1, 1e+256], N[(N[(9.0 * N[(N[(x * y), $MachinePrecision] / N[(z * c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(-4.0 * N[(N[(a * t), $MachinePrecision] / c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(x * N[(9.0 / z), $MachinePrecision]), $MachinePrecision] / N[(c / y), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

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

Alternative 8: 70.4% accurate, 0.5× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c] = \mathsf{sort}([x, y, z, t, a, b, c])\\ \\ \begin{array}{l} t_1 := y \cdot \left(9 \cdot x\right)\\ \mathbf{if}\;t_1 \leq -1 \cdot 10^{+297}:\\ \;\;\;\;\frac{9}{\frac{c}{y} \cdot \frac{z}{x}}\\ \mathbf{elif}\;t_1 \leq -2 \cdot 10^{+24}:\\ \;\;\;\;\frac{\frac{b + 9 \cdot \left(x \cdot y\right)}{c}}{z}\\ \mathbf{elif}\;t_1 \leq 10^{-172}:\\ \;\;\;\;\frac{b - 4 \cdot \left(a \cdot \left(z \cdot t\right)\right)}{z \cdot c}\\ \mathbf{elif}\;t_1 \leq 2 \cdot 10^{+105}:\\ \;\;\;\;\frac{b + x \cdot \left(9 \cdot y\right)}{z \cdot c}\\ \mathbf{elif}\;t_1 \leq 10^{+158}:\\ \;\;\;\;-4 \cdot \left(a \cdot \frac{t}{c}\right)\\ \mathbf{else}:\\ \;\;\;\;\frac{x \cdot \frac{9}{z}}{\frac{c}{y}}\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c)
 :precision binary64
 (let* ((t_1 (* y (* 9.0 x))))
   (if (<= t_1 -1e+297)
     (/ 9.0 (* (/ c y) (/ z x)))
     (if (<= t_1 -2e+24)
       (/ (/ (+ b (* 9.0 (* x y))) c) z)
       (if (<= t_1 1e-172)
         (/ (- b (* 4.0 (* a (* z t)))) (* z c))
         (if (<= t_1 2e+105)
           (/ (+ b (* x (* 9.0 y))) (* z c))
           (if (<= t_1 1e+158)
             (* -4.0 (* a (/ t c)))
             (/ (* x (/ 9.0 z)) (/ c y)))))))))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c);
double code(double x, double y, double z, double t, double a, double b, double c) {
	double t_1 = y * (9.0 * x);
	double tmp;
	if (t_1 <= -1e+297) {
		tmp = 9.0 / ((c / y) * (z / x));
	} else if (t_1 <= -2e+24) {
		tmp = ((b + (9.0 * (x * y))) / c) / z;
	} else if (t_1 <= 1e-172) {
		tmp = (b - (4.0 * (a * (z * t)))) / (z * c);
	} else if (t_1 <= 2e+105) {
		tmp = (b + (x * (9.0 * y))) / (z * c);
	} else if (t_1 <= 1e+158) {
		tmp = -4.0 * (a * (t / c));
	} else {
		tmp = (x * (9.0 / z)) / (c / y);
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b, c)
    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) :: t_1
    real(8) :: tmp
    t_1 = y * (9.0d0 * x)
    if (t_1 <= (-1d+297)) then
        tmp = 9.0d0 / ((c / y) * (z / x))
    else if (t_1 <= (-2d+24)) then
        tmp = ((b + (9.0d0 * (x * y))) / c) / z
    else if (t_1 <= 1d-172) then
        tmp = (b - (4.0d0 * (a * (z * t)))) / (z * c)
    else if (t_1 <= 2d+105) then
        tmp = (b + (x * (9.0d0 * y))) / (z * c)
    else if (t_1 <= 1d+158) then
        tmp = (-4.0d0) * (a * (t / c))
    else
        tmp = (x * (9.0d0 / z)) / (c / y)
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b && b < c;
public static double code(double x, double y, double z, double t, double a, double b, double c) {
	double t_1 = y * (9.0 * x);
	double tmp;
	if (t_1 <= -1e+297) {
		tmp = 9.0 / ((c / y) * (z / x));
	} else if (t_1 <= -2e+24) {
		tmp = ((b + (9.0 * (x * y))) / c) / z;
	} else if (t_1 <= 1e-172) {
		tmp = (b - (4.0 * (a * (z * t)))) / (z * c);
	} else if (t_1 <= 2e+105) {
		tmp = (b + (x * (9.0 * y))) / (z * c);
	} else if (t_1 <= 1e+158) {
		tmp = -4.0 * (a * (t / c));
	} else {
		tmp = (x * (9.0 / z)) / (c / y);
	}
	return tmp;
}

Python

[x, y, z, t, a, b, c] = sort([x, y, z, t, a, b, c])
def code(x, y, z, t, a, b, c):
	t_1 = y * (9.0 * x)
	tmp = 0
	if t_1 <= -1e+297:
		tmp = 9.0 / ((c / y) * (z / x))
	elif t_1 <= -2e+24:
		tmp = ((b + (9.0 * (x * y))) / c) / z
	elif t_1 <= 1e-172:
		tmp = (b - (4.0 * (a * (z * t)))) / (z * c)
	elif t_1 <= 2e+105:
		tmp = (b + (x * (9.0 * y))) / (z * c)
	elif t_1 <= 1e+158:
		tmp = -4.0 * (a * (t / c))
	else:
		tmp = (x * (9.0 / z)) / (c / y)
	return tmp

Julia

x, y, z, t, a, b, c = sort([x, y, z, t, a, b, c])
function code(x, y, z, t, a, b, c)
	t_1 = Float64(y * Float64(9.0 * x))
	tmp = 0.0
	if (t_1 <= -1e+297)
		tmp = Float64(9.0 / Float64(Float64(c / y) * Float64(z / x)));
	elseif (t_1 <= -2e+24)
		tmp = Float64(Float64(Float64(b + Float64(9.0 * Float64(x * y))) / c) / z);
	elseif (t_1 <= 1e-172)
		tmp = Float64(Float64(b - Float64(4.0 * Float64(a * Float64(z * t)))) / Float64(z * c));
	elseif (t_1 <= 2e+105)
		tmp = Float64(Float64(b + Float64(x * Float64(9.0 * y))) / Float64(z * c));
	elseif (t_1 <= 1e+158)
		tmp = Float64(-4.0 * Float64(a * Float64(t / c)));
	else
		tmp = Float64(Float64(x * Float64(9.0 / z)) / Float64(c / y));
	end
	return tmp
end

MATLAB

x, y, z, t, a, b, c = num2cell(sort([x, y, z, t, a, b, c])){:}
function tmp_2 = code(x, y, z, t, a, b, c)
	t_1 = y * (9.0 * x);
	tmp = 0.0;
	if (t_1 <= -1e+297)
		tmp = 9.0 / ((c / y) * (z / x));
	elseif (t_1 <= -2e+24)
		tmp = ((b + (9.0 * (x * y))) / c) / z;
	elseif (t_1 <= 1e-172)
		tmp = (b - (4.0 * (a * (z * t)))) / (z * c);
	elseif (t_1 <= 2e+105)
		tmp = (b + (x * (9.0 * y))) / (z * c);
	elseif (t_1 <= 1e+158)
		tmp = -4.0 * (a * (t / c));
	else
		tmp = (x * (9.0 / z)) / (c / y);
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_] := Block[{t$95$1 = N[(y * N[(9.0 * x), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$1, -1e+297], N[(9.0 / N[(N[(c / y), $MachinePrecision] * N[(z / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$1, -2e+24], N[(N[(N[(b + N[(9.0 * N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / c), $MachinePrecision] / z), $MachinePrecision], If[LessEqual[t$95$1, 1e-172], N[(N[(b - N[(4.0 * N[(a * N[(z * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(z * c), $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$1, 2e+105], N[(N[(b + N[(x * N[(9.0 * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(z * c), $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$1, 1e+158], N[(-4.0 * N[(a * N[(t / c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(x * N[(9.0 / z), $MachinePrecision]), $MachinePrecision] / N[(c / y), $MachinePrecision]), $MachinePrecision]]]]]]]

Derivation

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

Alternative 9: 70.6% accurate, 0.5× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c] = \mathsf{sort}([x, y, z, t, a, b, c])\\ \\ \begin{array}{l} t_1 := y \cdot \left(9 \cdot x\right)\\ \mathbf{if}\;t_1 \leq -1 \cdot 10^{+297}:\\ \;\;\;\;\frac{9}{\frac{c}{y} \cdot \frac{z}{x}}\\ \mathbf{elif}\;t_1 \leq -2 \cdot 10^{+24}:\\ \;\;\;\;\frac{\frac{b + 9 \cdot \left(x \cdot y\right)}{c}}{z}\\ \mathbf{elif}\;t_1 \leq 10^{-172}:\\ \;\;\;\;\frac{\frac{b + \left(z \cdot t\right) \cdot \left(-4 \cdot a\right)}{c}}{z}\\ \mathbf{elif}\;t_1 \leq 2 \cdot 10^{+105}:\\ \;\;\;\;\frac{b + x \cdot \left(9 \cdot y\right)}{z \cdot c}\\ \mathbf{elif}\;t_1 \leq 10^{+158}:\\ \;\;\;\;-4 \cdot \left(a \cdot \frac{t}{c}\right)\\ \mathbf{else}:\\ \;\;\;\;\frac{x \cdot \frac{9}{z}}{\frac{c}{y}}\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c)
 :precision binary64
 (let* ((t_1 (* y (* 9.0 x))))
   (if (<= t_1 -1e+297)
     (/ 9.0 (* (/ c y) (/ z x)))
     (if (<= t_1 -2e+24)
       (/ (/ (+ b (* 9.0 (* x y))) c) z)
       (if (<= t_1 1e-172)
         (/ (/ (+ b (* (* z t) (* -4.0 a))) c) z)
         (if (<= t_1 2e+105)
           (/ (+ b (* x (* 9.0 y))) (* z c))
           (if (<= t_1 1e+158)
             (* -4.0 (* a (/ t c)))
             (/ (* x (/ 9.0 z)) (/ c y)))))))))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c);
double code(double x, double y, double z, double t, double a, double b, double c) {
	double t_1 = y * (9.0 * x);
	double tmp;
	if (t_1 <= -1e+297) {
		tmp = 9.0 / ((c / y) * (z / x));
	} else if (t_1 <= -2e+24) {
		tmp = ((b + (9.0 * (x * y))) / c) / z;
	} else if (t_1 <= 1e-172) {
		tmp = ((b + ((z * t) * (-4.0 * a))) / c) / z;
	} else if (t_1 <= 2e+105) {
		tmp = (b + (x * (9.0 * y))) / (z * c);
	} else if (t_1 <= 1e+158) {
		tmp = -4.0 * (a * (t / c));
	} else {
		tmp = (x * (9.0 / z)) / (c / y);
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b, c)
    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) :: t_1
    real(8) :: tmp
    t_1 = y * (9.0d0 * x)
    if (t_1 <= (-1d+297)) then
        tmp = 9.0d0 / ((c / y) * (z / x))
    else if (t_1 <= (-2d+24)) then
        tmp = ((b + (9.0d0 * (x * y))) / c) / z
    else if (t_1 <= 1d-172) then
        tmp = ((b + ((z * t) * ((-4.0d0) * a))) / c) / z
    else if (t_1 <= 2d+105) then
        tmp = (b + (x * (9.0d0 * y))) / (z * c)
    else if (t_1 <= 1d+158) then
        tmp = (-4.0d0) * (a * (t / c))
    else
        tmp = (x * (9.0d0 / z)) / (c / y)
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b && b < c;
public static double code(double x, double y, double z, double t, double a, double b, double c) {
	double t_1 = y * (9.0 * x);
	double tmp;
	if (t_1 <= -1e+297) {
		tmp = 9.0 / ((c / y) * (z / x));
	} else if (t_1 <= -2e+24) {
		tmp = ((b + (9.0 * (x * y))) / c) / z;
	} else if (t_1 <= 1e-172) {
		tmp = ((b + ((z * t) * (-4.0 * a))) / c) / z;
	} else if (t_1 <= 2e+105) {
		tmp = (b + (x * (9.0 * y))) / (z * c);
	} else if (t_1 <= 1e+158) {
		tmp = -4.0 * (a * (t / c));
	} else {
		tmp = (x * (9.0 / z)) / (c / y);
	}
	return tmp;
}

Python

[x, y, z, t, a, b, c] = sort([x, y, z, t, a, b, c])
def code(x, y, z, t, a, b, c):
	t_1 = y * (9.0 * x)
	tmp = 0
	if t_1 <= -1e+297:
		tmp = 9.0 / ((c / y) * (z / x))
	elif t_1 <= -2e+24:
		tmp = ((b + (9.0 * (x * y))) / c) / z
	elif t_1 <= 1e-172:
		tmp = ((b + ((z * t) * (-4.0 * a))) / c) / z
	elif t_1 <= 2e+105:
		tmp = (b + (x * (9.0 * y))) / (z * c)
	elif t_1 <= 1e+158:
		tmp = -4.0 * (a * (t / c))
	else:
		tmp = (x * (9.0 / z)) / (c / y)
	return tmp

Julia

x, y, z, t, a, b, c = sort([x, y, z, t, a, b, c])
function code(x, y, z, t, a, b, c)
	t_1 = Float64(y * Float64(9.0 * x))
	tmp = 0.0
	if (t_1 <= -1e+297)
		tmp = Float64(9.0 / Float64(Float64(c / y) * Float64(z / x)));
	elseif (t_1 <= -2e+24)
		tmp = Float64(Float64(Float64(b + Float64(9.0 * Float64(x * y))) / c) / z);
	elseif (t_1 <= 1e-172)
		tmp = Float64(Float64(Float64(b + Float64(Float64(z * t) * Float64(-4.0 * a))) / c) / z);
	elseif (t_1 <= 2e+105)
		tmp = Float64(Float64(b + Float64(x * Float64(9.0 * y))) / Float64(z * c));
	elseif (t_1 <= 1e+158)
		tmp = Float64(-4.0 * Float64(a * Float64(t / c)));
	else
		tmp = Float64(Float64(x * Float64(9.0 / z)) / Float64(c / y));
	end
	return tmp
end

MATLAB

x, y, z, t, a, b, c = num2cell(sort([x, y, z, t, a, b, c])){:}
function tmp_2 = code(x, y, z, t, a, b, c)
	t_1 = y * (9.0 * x);
	tmp = 0.0;
	if (t_1 <= -1e+297)
		tmp = 9.0 / ((c / y) * (z / x));
	elseif (t_1 <= -2e+24)
		tmp = ((b + (9.0 * (x * y))) / c) / z;
	elseif (t_1 <= 1e-172)
		tmp = ((b + ((z * t) * (-4.0 * a))) / c) / z;
	elseif (t_1 <= 2e+105)
		tmp = (b + (x * (9.0 * y))) / (z * c);
	elseif (t_1 <= 1e+158)
		tmp = -4.0 * (a * (t / c));
	else
		tmp = (x * (9.0 / z)) / (c / y);
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_] := Block[{t$95$1 = N[(y * N[(9.0 * x), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$1, -1e+297], N[(9.0 / N[(N[(c / y), $MachinePrecision] * N[(z / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$1, -2e+24], N[(N[(N[(b + N[(9.0 * N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / c), $MachinePrecision] / z), $MachinePrecision], If[LessEqual[t$95$1, 1e-172], N[(N[(N[(b + N[(N[(z * t), $MachinePrecision] * N[(-4.0 * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / c), $MachinePrecision] / z), $MachinePrecision], If[LessEqual[t$95$1, 2e+105], N[(N[(b + N[(x * N[(9.0 * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(z * c), $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$1, 1e+158], N[(-4.0 * N[(a * N[(t / c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(x * N[(9.0 / z), $MachinePrecision]), $MachinePrecision] / N[(c / y), $MachinePrecision]), $MachinePrecision]]]]]]]

Derivation

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

Alternative 10: 72.7% accurate, 0.5× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c] = \mathsf{sort}([x, y, z, t, a, b, c])\\ \\ \begin{array}{l} t_1 := y \cdot \left(9 \cdot x\right)\\ \mathbf{if}\;t_1 \leq -1 \cdot 10^{+297}:\\ \;\;\;\;\frac{9}{\frac{c}{y} \cdot \frac{z}{x}}\\ \mathbf{elif}\;t_1 \leq -2 \cdot 10^{+24}:\\ \;\;\;\;\frac{\frac{b + 9 \cdot \left(x \cdot y\right)}{c}}{z}\\ \mathbf{elif}\;t_1 \leq 10^{-115}:\\ \;\;\;\;\frac{\frac{b + \left(z \cdot t\right) \cdot \left(-4 \cdot a\right)}{c}}{z}\\ \mathbf{else}:\\ \;\;\;\;\frac{9}{z} \cdot \frac{x}{\frac{c}{y}} - \frac{a}{\frac{c}{t}} \cdot 4\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c)
 :precision binary64
 (let* ((t_1 (* y (* 9.0 x))))
   (if (<= t_1 -1e+297)
     (/ 9.0 (* (/ c y) (/ z x)))
     (if (<= t_1 -2e+24)
       (/ (/ (+ b (* 9.0 (* x y))) c) z)
       (if (<= t_1 1e-115)
         (/ (/ (+ b (* (* z t) (* -4.0 a))) c) z)
         (- (* (/ 9.0 z) (/ x (/ c y))) (* (/ a (/ c t)) 4.0)))))))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c);
double code(double x, double y, double z, double t, double a, double b, double c) {
	double t_1 = y * (9.0 * x);
	double tmp;
	if (t_1 <= -1e+297) {
		tmp = 9.0 / ((c / y) * (z / x));
	} else if (t_1 <= -2e+24) {
		tmp = ((b + (9.0 * (x * y))) / c) / z;
	} else if (t_1 <= 1e-115) {
		tmp = ((b + ((z * t) * (-4.0 * a))) / c) / z;
	} else {
		tmp = ((9.0 / z) * (x / (c / y))) - ((a / (c / t)) * 4.0);
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b, c)
    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) :: t_1
    real(8) :: tmp
    t_1 = y * (9.0d0 * x)
    if (t_1 <= (-1d+297)) then
        tmp = 9.0d0 / ((c / y) * (z / x))
    else if (t_1 <= (-2d+24)) then
        tmp = ((b + (9.0d0 * (x * y))) / c) / z
    else if (t_1 <= 1d-115) then
        tmp = ((b + ((z * t) * ((-4.0d0) * a))) / c) / z
    else
        tmp = ((9.0d0 / z) * (x / (c / y))) - ((a / (c / t)) * 4.0d0)
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b && b < c;
public static double code(double x, double y, double z, double t, double a, double b, double c) {
	double t_1 = y * (9.0 * x);
	double tmp;
	if (t_1 <= -1e+297) {
		tmp = 9.0 / ((c / y) * (z / x));
	} else if (t_1 <= -2e+24) {
		tmp = ((b + (9.0 * (x * y))) / c) / z;
	} else if (t_1 <= 1e-115) {
		tmp = ((b + ((z * t) * (-4.0 * a))) / c) / z;
	} else {
		tmp = ((9.0 / z) * (x / (c / y))) - ((a / (c / t)) * 4.0);
	}
	return tmp;
}

Python

[x, y, z, t, a, b, c] = sort([x, y, z, t, a, b, c])
def code(x, y, z, t, a, b, c):
	t_1 = y * (9.0 * x)
	tmp = 0
	if t_1 <= -1e+297:
		tmp = 9.0 / ((c / y) * (z / x))
	elif t_1 <= -2e+24:
		tmp = ((b + (9.0 * (x * y))) / c) / z
	elif t_1 <= 1e-115:
		tmp = ((b + ((z * t) * (-4.0 * a))) / c) / z
	else:
		tmp = ((9.0 / z) * (x / (c / y))) - ((a / (c / t)) * 4.0)
	return tmp

Julia

x, y, z, t, a, b, c = sort([x, y, z, t, a, b, c])
function code(x, y, z, t, a, b, c)
	t_1 = Float64(y * Float64(9.0 * x))
	tmp = 0.0
	if (t_1 <= -1e+297)
		tmp = Float64(9.0 / Float64(Float64(c / y) * Float64(z / x)));
	elseif (t_1 <= -2e+24)
		tmp = Float64(Float64(Float64(b + Float64(9.0 * Float64(x * y))) / c) / z);
	elseif (t_1 <= 1e-115)
		tmp = Float64(Float64(Float64(b + Float64(Float64(z * t) * Float64(-4.0 * a))) / c) / z);
	else
		tmp = Float64(Float64(Float64(9.0 / z) * Float64(x / Float64(c / y))) - Float64(Float64(a / Float64(c / t)) * 4.0));
	end
	return tmp
end

MATLAB

x, y, z, t, a, b, c = num2cell(sort([x, y, z, t, a, b, c])){:}
function tmp_2 = code(x, y, z, t, a, b, c)
	t_1 = y * (9.0 * x);
	tmp = 0.0;
	if (t_1 <= -1e+297)
		tmp = 9.0 / ((c / y) * (z / x));
	elseif (t_1 <= -2e+24)
		tmp = ((b + (9.0 * (x * y))) / c) / z;
	elseif (t_1 <= 1e-115)
		tmp = ((b + ((z * t) * (-4.0 * a))) / c) / z;
	else
		tmp = ((9.0 / z) * (x / (c / y))) - ((a / (c / t)) * 4.0);
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_] := Block[{t$95$1 = N[(y * N[(9.0 * x), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$1, -1e+297], N[(9.0 / N[(N[(c / y), $MachinePrecision] * N[(z / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$1, -2e+24], N[(N[(N[(b + N[(9.0 * N[(x * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / c), $MachinePrecision] / z), $MachinePrecision], If[LessEqual[t$95$1, 1e-115], N[(N[(N[(b + N[(N[(z * t), $MachinePrecision] * N[(-4.0 * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / c), $MachinePrecision] / z), $MachinePrecision], N[(N[(N[(9.0 / z), $MachinePrecision] * N[(x / N[(c / y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(a / N[(c / t), $MachinePrecision]), $MachinePrecision] * 4.0), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

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

Alternative 11: 82.6% accurate, 0.8× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c] = \mathsf{sort}([x, y, z, t, a, b, c])\\ \\ \begin{array}{l} \mathbf{if}\;z \leq -1.02 \cdot 10^{+132} \lor \neg \left(z \leq 4.2 \cdot 10^{+36}\right):\\ \;\;\;\;\frac{9}{z} \cdot \frac{x}{\frac{c}{y}} - \frac{a}{\frac{c}{t}} \cdot 4\\ \mathbf{else}:\\ \;\;\;\;\frac{b + \left(x \cdot \left(9 \cdot y\right) - \left(z \cdot 4\right) \cdot \left(a \cdot t\right)\right)}{z \cdot c}\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c)
 :precision binary64
 (if (or (<= z -1.02e+132) (not (<= z 4.2e+36)))
   (- (* (/ 9.0 z) (/ x (/ c y))) (* (/ a (/ c t)) 4.0))
   (/ (+ b (- (* x (* 9.0 y)) (* (* z 4.0) (* a t)))) (* z c))))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c);
double code(double x, double y, double z, double t, double a, double b, double c) {
	double tmp;
	if ((z <= -1.02e+132) || !(z <= 4.2e+36)) {
		tmp = ((9.0 / z) * (x / (c / y))) - ((a / (c / t)) * 4.0);
	} else {
		tmp = (b + ((x * (9.0 * y)) - ((z * 4.0) * (a * t)))) / (z * c);
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b, c)
    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) :: tmp
    if ((z <= (-1.02d+132)) .or. (.not. (z <= 4.2d+36))) then
        tmp = ((9.0d0 / z) * (x / (c / y))) - ((a / (c / t)) * 4.0d0)
    else
        tmp = (b + ((x * (9.0d0 * y)) - ((z * 4.0d0) * (a * t)))) / (z * c)
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b && b < c;
public static double code(double x, double y, double z, double t, double a, double b, double c) {
	double tmp;
	if ((z <= -1.02e+132) || !(z <= 4.2e+36)) {
		tmp = ((9.0 / z) * (x / (c / y))) - ((a / (c / t)) * 4.0);
	} else {
		tmp = (b + ((x * (9.0 * y)) - ((z * 4.0) * (a * t)))) / (z * c);
	}
	return tmp;
}

Python

[x, y, z, t, a, b, c] = sort([x, y, z, t, a, b, c])
def code(x, y, z, t, a, b, c):
	tmp = 0
	if (z <= -1.02e+132) or not (z <= 4.2e+36):
		tmp = ((9.0 / z) * (x / (c / y))) - ((a / (c / t)) * 4.0)
	else:
		tmp = (b + ((x * (9.0 * y)) - ((z * 4.0) * (a * t)))) / (z * c)
	return tmp

Julia

x, y, z, t, a, b, c = sort([x, y, z, t, a, b, c])
function code(x, y, z, t, a, b, c)
	tmp = 0.0
	if ((z <= -1.02e+132) || !(z <= 4.2e+36))
		tmp = Float64(Float64(Float64(9.0 / z) * Float64(x / Float64(c / y))) - Float64(Float64(a / Float64(c / t)) * 4.0));
	else
		tmp = Float64(Float64(b + Float64(Float64(x * Float64(9.0 * y)) - Float64(Float64(z * 4.0) * Float64(a * t)))) / Float64(z * c));
	end
	return tmp
end

MATLAB

x, y, z, t, a, b, c = num2cell(sort([x, y, z, t, a, b, c])){:}
function tmp_2 = code(x, y, z, t, a, b, c)
	tmp = 0.0;
	if ((z <= -1.02e+132) || ~((z <= 4.2e+36)))
		tmp = ((9.0 / z) * (x / (c / y))) - ((a / (c / t)) * 4.0);
	else
		tmp = (b + ((x * (9.0 * y)) - ((z * 4.0) * (a * t)))) / (z * c);
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_] := If[Or[LessEqual[z, -1.02e+132], N[Not[LessEqual[z, 4.2e+36]], $MachinePrecision]], N[(N[(N[(9.0 / z), $MachinePrecision] * N[(x / N[(c / y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(N[(a / N[(c / t), $MachinePrecision]), $MachinePrecision] * 4.0), $MachinePrecision]), $MachinePrecision], N[(N[(b + N[(N[(x * N[(9.0 * y), $MachinePrecision]), $MachinePrecision] - N[(N[(z * 4.0), $MachinePrecision] * N[(a * t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(z * c), $MachinePrecision]), $MachinePrecision]]

Derivation

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

Alternative 12: 47.3% accurate, 1.3× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c] = \mathsf{sort}([x, y, z, t, a, b, c])\\ \\ \begin{array}{l} t_1 := 9 \cdot \left(\frac{x}{c} \cdot \frac{y}{z}\right)\\ \mathbf{if}\;a \leq -2 \cdot 10^{-251}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 6.5 \cdot 10^{-103}:\\ \;\;\;\;\frac{\frac{b}{z}}{c}\\ \mathbf{elif}\;a \leq 8.5 \cdot 10^{+69}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;-4 \cdot \left(t \cdot \frac{a}{c}\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c)
 :precision binary64
 (let* ((t_1 (* 9.0 (* (/ x c) (/ y z)))))
   (if (<= a -2e-251)
     t_1
     (if (<= a 6.5e-103)
       (/ (/ b z) c)
       (if (<= a 8.5e+69) t_1 (* -4.0 (* t (/ a c))))))))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c);
double code(double x, double y, double z, double t, double a, double b, double c) {
	double t_1 = 9.0 * ((x / c) * (y / z));
	double tmp;
	if (a <= -2e-251) {
		tmp = t_1;
	} else if (a <= 6.5e-103) {
		tmp = (b / z) / c;
	} else if (a <= 8.5e+69) {
		tmp = t_1;
	} else {
		tmp = -4.0 * (t * (a / c));
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b, c)
    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) :: t_1
    real(8) :: tmp
    t_1 = 9.0d0 * ((x / c) * (y / z))
    if (a <= (-2d-251)) then
        tmp = t_1
    else if (a <= 6.5d-103) then
        tmp = (b / z) / c
    else if (a <= 8.5d+69) then
        tmp = t_1
    else
        tmp = (-4.0d0) * (t * (a / c))
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b && b < c;
public static double code(double x, double y, double z, double t, double a, double b, double c) {
	double t_1 = 9.0 * ((x / c) * (y / z));
	double tmp;
	if (a <= -2e-251) {
		tmp = t_1;
	} else if (a <= 6.5e-103) {
		tmp = (b / z) / c;
	} else if (a <= 8.5e+69) {
		tmp = t_1;
	} else {
		tmp = -4.0 * (t * (a / c));
	}
	return tmp;
}

Python

[x, y, z, t, a, b, c] = sort([x, y, z, t, a, b, c])
def code(x, y, z, t, a, b, c):
	t_1 = 9.0 * ((x / c) * (y / z))
	tmp = 0
	if a <= -2e-251:
		tmp = t_1
	elif a <= 6.5e-103:
		tmp = (b / z) / c
	elif a <= 8.5e+69:
		tmp = t_1
	else:
		tmp = -4.0 * (t * (a / c))
	return tmp

Julia

x, y, z, t, a, b, c = sort([x, y, z, t, a, b, c])
function code(x, y, z, t, a, b, c)
	t_1 = Float64(9.0 * Float64(Float64(x / c) * Float64(y / z)))
	tmp = 0.0
	if (a <= -2e-251)
		tmp = t_1;
	elseif (a <= 6.5e-103)
		tmp = Float64(Float64(b / z) / c);
	elseif (a <= 8.5e+69)
		tmp = t_1;
	else
		tmp = Float64(-4.0 * Float64(t * Float64(a / c)));
	end
	return tmp
end

MATLAB

x, y, z, t, a, b, c = num2cell(sort([x, y, z, t, a, b, c])){:}
function tmp_2 = code(x, y, z, t, a, b, c)
	t_1 = 9.0 * ((x / c) * (y / z));
	tmp = 0.0;
	if (a <= -2e-251)
		tmp = t_1;
	elseif (a <= 6.5e-103)
		tmp = (b / z) / c;
	elseif (a <= 8.5e+69)
		tmp = t_1;
	else
		tmp = -4.0 * (t * (a / c));
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_] := Block[{t$95$1 = N[(9.0 * N[(N[(x / c), $MachinePrecision] * N[(y / z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -2e-251], t$95$1, If[LessEqual[a, 6.5e-103], N[(N[(b / z), $MachinePrecision] / c), $MachinePrecision], If[LessEqual[a, 8.5e+69], t$95$1, N[(-4.0 * N[(t * N[(a / c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

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1. Add Preprocessing

Alternative 13: 47.4% accurate, 1.3× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c] = \mathsf{sort}([x, y, z, t, a, b, c])\\ \\ \begin{array}{l} \mathbf{if}\;a \leq -2.8 \cdot 10^{-251}:\\ \;\;\;\;9 \cdot \left(\frac{x}{c} \cdot \frac{y}{z}\right)\\ \mathbf{elif}\;a \leq 1.75 \cdot 10^{-167}:\\ \;\;\;\;\frac{b}{z \cdot c}\\ \mathbf{elif}\;a \leq 2.6 \cdot 10^{+69}:\\ \;\;\;\;9 \cdot \left(\frac{x}{z} \cdot \frac{y}{c}\right)\\ \mathbf{else}:\\ \;\;\;\;-4 \cdot \left(t \cdot \frac{a}{c}\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c)
 :precision binary64
 (if (<= a -2.8e-251)
   (* 9.0 (* (/ x c) (/ y z)))
   (if (<= a 1.75e-167)
     (/ b (* z c))
     (if (<= a 2.6e+69) (* 9.0 (* (/ x z) (/ y c))) (* -4.0 (* t (/ a c)))))))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c);
double code(double x, double y, double z, double t, double a, double b, double c) {
	double tmp;
	if (a <= -2.8e-251) {
		tmp = 9.0 * ((x / c) * (y / z));
	} else if (a <= 1.75e-167) {
		tmp = b / (z * c);
	} else if (a <= 2.6e+69) {
		tmp = 9.0 * ((x / z) * (y / c));
	} else {
		tmp = -4.0 * (t * (a / c));
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b, c)
    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) :: tmp
    if (a <= (-2.8d-251)) then
        tmp = 9.0d0 * ((x / c) * (y / z))
    else if (a <= 1.75d-167) then
        tmp = b / (z * c)
    else if (a <= 2.6d+69) then
        tmp = 9.0d0 * ((x / z) * (y / c))
    else
        tmp = (-4.0d0) * (t * (a / c))
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b && b < c;
public static double code(double x, double y, double z, double t, double a, double b, double c) {
	double tmp;
	if (a <= -2.8e-251) {
		tmp = 9.0 * ((x / c) * (y / z));
	} else if (a <= 1.75e-167) {
		tmp = b / (z * c);
	} else if (a <= 2.6e+69) {
		tmp = 9.0 * ((x / z) * (y / c));
	} else {
		tmp = -4.0 * (t * (a / c));
	}
	return tmp;
}

Python

[x, y, z, t, a, b, c] = sort([x, y, z, t, a, b, c])
def code(x, y, z, t, a, b, c):
	tmp = 0
	if a <= -2.8e-251:
		tmp = 9.0 * ((x / c) * (y / z))
	elif a <= 1.75e-167:
		tmp = b / (z * c)
	elif a <= 2.6e+69:
		tmp = 9.0 * ((x / z) * (y / c))
	else:
		tmp = -4.0 * (t * (a / c))
	return tmp

Julia

x, y, z, t, a, b, c = sort([x, y, z, t, a, b, c])
function code(x, y, z, t, a, b, c)
	tmp = 0.0
	if (a <= -2.8e-251)
		tmp = Float64(9.0 * Float64(Float64(x / c) * Float64(y / z)));
	elseif (a <= 1.75e-167)
		tmp = Float64(b / Float64(z * c));
	elseif (a <= 2.6e+69)
		tmp = Float64(9.0 * Float64(Float64(x / z) * Float64(y / c)));
	else
		tmp = Float64(-4.0 * Float64(t * Float64(a / c)));
	end
	return tmp
end

MATLAB

x, y, z, t, a, b, c = num2cell(sort([x, y, z, t, a, b, c])){:}
function tmp_2 = code(x, y, z, t, a, b, c)
	tmp = 0.0;
	if (a <= -2.8e-251)
		tmp = 9.0 * ((x / c) * (y / z));
	elseif (a <= 1.75e-167)
		tmp = b / (z * c);
	elseif (a <= 2.6e+69)
		tmp = 9.0 * ((x / z) * (y / c));
	else
		tmp = -4.0 * (t * (a / c));
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_] := If[LessEqual[a, -2.8e-251], N[(9.0 * N[(N[(x / c), $MachinePrecision] * N[(y / z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 1.75e-167], N[(b / N[(z * c), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 2.6e+69], N[(9.0 * N[(N[(x / z), $MachinePrecision] * N[(y / c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(-4.0 * N[(t * N[(a / c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]

Derivation

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1. Add Preprocessing

Alternative 14: 47.3% accurate, 1.3× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c] = \mathsf{sort}([x, y, z, t, a, b, c])\\ \\ \begin{array}{l} \mathbf{if}\;a \leq -3.4 \cdot 10^{-251}:\\ \;\;\;\;9 \cdot \left(\frac{x}{c} \cdot \frac{y}{z}\right)\\ \mathbf{elif}\;a \leq 1.6 \cdot 10^{-174}:\\ \;\;\;\;\frac{b}{z \cdot c}\\ \mathbf{elif}\;a \leq 4.7 \cdot 10^{+67}:\\ \;\;\;\;\frac{x \cdot \frac{9}{z}}{\frac{c}{y}}\\ \mathbf{else}:\\ \;\;\;\;-4 \cdot \left(t \cdot \frac{a}{c}\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c)
 :precision binary64
 (if (<= a -3.4e-251)
   (* 9.0 (* (/ x c) (/ y z)))
   (if (<= a 1.6e-174)
     (/ b (* z c))
     (if (<= a 4.7e+67) (/ (* x (/ 9.0 z)) (/ c y)) (* -4.0 (* t (/ a c)))))))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c);
double code(double x, double y, double z, double t, double a, double b, double c) {
	double tmp;
	if (a <= -3.4e-251) {
		tmp = 9.0 * ((x / c) * (y / z));
	} else if (a <= 1.6e-174) {
		tmp = b / (z * c);
	} else if (a <= 4.7e+67) {
		tmp = (x * (9.0 / z)) / (c / y);
	} else {
		tmp = -4.0 * (t * (a / c));
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b, c)
    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) :: tmp
    if (a <= (-3.4d-251)) then
        tmp = 9.0d0 * ((x / c) * (y / z))
    else if (a <= 1.6d-174) then
        tmp = b / (z * c)
    else if (a <= 4.7d+67) then
        tmp = (x * (9.0d0 / z)) / (c / y)
    else
        tmp = (-4.0d0) * (t * (a / c))
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b && b < c;
public static double code(double x, double y, double z, double t, double a, double b, double c) {
	double tmp;
	if (a <= -3.4e-251) {
		tmp = 9.0 * ((x / c) * (y / z));
	} else if (a <= 1.6e-174) {
		tmp = b / (z * c);
	} else if (a <= 4.7e+67) {
		tmp = (x * (9.0 / z)) / (c / y);
	} else {
		tmp = -4.0 * (t * (a / c));
	}
	return tmp;
}

Python

[x, y, z, t, a, b, c] = sort([x, y, z, t, a, b, c])
def code(x, y, z, t, a, b, c):
	tmp = 0
	if a <= -3.4e-251:
		tmp = 9.0 * ((x / c) * (y / z))
	elif a <= 1.6e-174:
		tmp = b / (z * c)
	elif a <= 4.7e+67:
		tmp = (x * (9.0 / z)) / (c / y)
	else:
		tmp = -4.0 * (t * (a / c))
	return tmp

Julia

x, y, z, t, a, b, c = sort([x, y, z, t, a, b, c])
function code(x, y, z, t, a, b, c)
	tmp = 0.0
	if (a <= -3.4e-251)
		tmp = Float64(9.0 * Float64(Float64(x / c) * Float64(y / z)));
	elseif (a <= 1.6e-174)
		tmp = Float64(b / Float64(z * c));
	elseif (a <= 4.7e+67)
		tmp = Float64(Float64(x * Float64(9.0 / z)) / Float64(c / y));
	else
		tmp = Float64(-4.0 * Float64(t * Float64(a / c)));
	end
	return tmp
end

MATLAB

x, y, z, t, a, b, c = num2cell(sort([x, y, z, t, a, b, c])){:}
function tmp_2 = code(x, y, z, t, a, b, c)
	tmp = 0.0;
	if (a <= -3.4e-251)
		tmp = 9.0 * ((x / c) * (y / z));
	elseif (a <= 1.6e-174)
		tmp = b / (z * c);
	elseif (a <= 4.7e+67)
		tmp = (x * (9.0 / z)) / (c / y);
	else
		tmp = -4.0 * (t * (a / c));
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_] := If[LessEqual[a, -3.4e-251], N[(9.0 * N[(N[(x / c), $MachinePrecision] * N[(y / z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 1.6e-174], N[(b / N[(z * c), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 4.7e+67], N[(N[(x * N[(9.0 / z), $MachinePrecision]), $MachinePrecision] / N[(c / y), $MachinePrecision]), $MachinePrecision], N[(-4.0 * N[(t * N[(a / c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]

Derivation

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1. Add Preprocessing

Alternative 15: 64.2% accurate, 1.5× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c] = \mathsf{sort}([x, y, z, t, a, b, c])\\ \\ \begin{array}{l} \mathbf{if}\;a \leq 6.5 \cdot 10^{+66}:\\ \;\;\;\;\frac{b + x \cdot \left(9 \cdot y\right)}{z \cdot c}\\ \mathbf{else}:\\ \;\;\;\;-4 \cdot \left(t \cdot \frac{a}{c}\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c)
 :precision binary64
 (if (<= a 6.5e+66) (/ (+ b (* x (* 9.0 y))) (* z c)) (* -4.0 (* t (/ a c)))))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c);
double code(double x, double y, double z, double t, double a, double b, double c) {
	double tmp;
	if (a <= 6.5e+66) {
		tmp = (b + (x * (9.0 * y))) / (z * c);
	} else {
		tmp = -4.0 * (t * (a / c));
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b, c)
    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) :: tmp
    if (a <= 6.5d+66) then
        tmp = (b + (x * (9.0d0 * y))) / (z * c)
    else
        tmp = (-4.0d0) * (t * (a / c))
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b && b < c;
public static double code(double x, double y, double z, double t, double a, double b, double c) {
	double tmp;
	if (a <= 6.5e+66) {
		tmp = (b + (x * (9.0 * y))) / (z * c);
	} else {
		tmp = -4.0 * (t * (a / c));
	}
	return tmp;
}

Python

[x, y, z, t, a, b, c] = sort([x, y, z, t, a, b, c])
def code(x, y, z, t, a, b, c):
	tmp = 0
	if a <= 6.5e+66:
		tmp = (b + (x * (9.0 * y))) / (z * c)
	else:
		tmp = -4.0 * (t * (a / c))
	return tmp

Julia

x, y, z, t, a, b, c = sort([x, y, z, t, a, b, c])
function code(x, y, z, t, a, b, c)
	tmp = 0.0
	if (a <= 6.5e+66)
		tmp = Float64(Float64(b + Float64(x * Float64(9.0 * y))) / Float64(z * c));
	else
		tmp = Float64(-4.0 * Float64(t * Float64(a / c)));
	end
	return tmp
end

MATLAB

x, y, z, t, a, b, c = num2cell(sort([x, y, z, t, a, b, c])){:}
function tmp_2 = code(x, y, z, t, a, b, c)
	tmp = 0.0;
	if (a <= 6.5e+66)
		tmp = (b + (x * (9.0 * y))) / (z * c);
	else
		tmp = -4.0 * (t * (a / c));
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_] := If[LessEqual[a, 6.5e+66], N[(N[(b + N[(x * N[(9.0 * y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(z * c), $MachinePrecision]), $MachinePrecision], N[(-4.0 * N[(t * N[(a / c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

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

Alternative 16: 45.4% accurate, 2.1× speedup

Math

\[\begin{array}{l} [x, y, z, t, a, b, c] = \mathsf{sort}([x, y, z, t, a, b, c])\\ \\ \begin{array}{l} \mathbf{if}\;a \leq 2.6 \cdot 10^{+65}:\\ \;\;\;\;\frac{\frac{b}{z}}{c}\\ \mathbf{else}:\\ \;\;\;\;-4 \cdot \left(t \cdot \frac{a}{c}\right)\\ \end{array} \end{array} \]

FPCore

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
(FPCore (x y z t a b c)
 :precision binary64
 (if (<= a 2.6e+65) (/ (/ b z) c) (* -4.0 (* t (/ a c)))))

C

assert(x < y && y < z && z < t && t < a && a < b && b < c);
double code(double x, double y, double z, double t, double a, double b, double c) {
	double tmp;
	if (a <= 2.6e+65) {
		tmp = (b / z) / c;
	} else {
		tmp = -4.0 * (t * (a / c));
	}
	return tmp;
}

Fortran

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
real(8) function code(x, y, z, t, a, b, c)
    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) :: tmp
    if (a <= 2.6d+65) then
        tmp = (b / z) / c
    else
        tmp = (-4.0d0) * (t * (a / c))
    end if
    code = tmp
end function

Java

assert x < y && y < z && z < t && t < a && a < b && b < c;
public static double code(double x, double y, double z, double t, double a, double b, double c) {
	double tmp;
	if (a <= 2.6e+65) {
		tmp = (b / z) / c;
	} else {
		tmp = -4.0 * (t * (a / c));
	}
	return tmp;
}

Python

[x, y, z, t, a, b, c] = sort([x, y, z, t, a, b, c])
def code(x, y, z, t, a, b, c):
	tmp = 0
	if a <= 2.6e+65:
		tmp = (b / z) / c
	else:
		tmp = -4.0 * (t * (a / c))
	return tmp

Julia

x, y, z, t, a, b, c = sort([x, y, z, t, a, b, c])
function code(x, y, z, t, a, b, c)
	tmp = 0.0
	if (a <= 2.6e+65)
		tmp = Float64(Float64(b / z) / c);
	else
		tmp = Float64(-4.0 * Float64(t * Float64(a / c)));
	end
	return tmp
end

MATLAB

x, y, z, t, a, b, c = num2cell(sort([x, y, z, t, a, b, c])){:}
function tmp_2 = code(x, y, z, t, a, b, c)
	tmp = 0.0;
	if (a <= 2.6e+65)
		tmp = (b / z) / c;
	else
		tmp = -4.0 * (t * (a / c));
	end
	tmp_2 = tmp;
end

Wolfram

NOTE: x, y, z, t, a, b, and c should be sorted in increasing order before calling this function.
code[x_, y_, z_, t_, a_, b_, c_] := If[LessEqual[a, 2.6e+65], N[(N[(b / z), $MachinePrecision] / c), $MachinePrecision], N[(-4.0 * N[(t * N[(a / c), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

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

Alternative 17: 34.8% accurate, 3.8× speedup

Math

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

FPCore

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

C

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

Fortran

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

Java

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

Python

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

Julia

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

MATLAB

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

Wolfram

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

Derivation

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

Alternative 18: 34.5% accurate, 3.8× speedup

Math

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

FPCore

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

C

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

Fortran

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

Java

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

Python

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

Julia

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

MATLAB

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

Wolfram

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

Derivation

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

Developer target: 79.9% accurate, 0.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \frac{b}{c \cdot z}\\ t_2 := 4 \cdot \frac{a \cdot t}{c}\\ t_3 := \left(x \cdot 9\right) \cdot y\\ t_4 := \left(t_3 - \left(\left(z \cdot 4\right) \cdot t\right) \cdot a\right) + b\\ t_5 := \frac{t_4}{z \cdot c}\\ t_6 := \frac{\left(t_3 - \left(z \cdot 4\right) \cdot \left(t \cdot a\right)\right) + b}{z \cdot c}\\ \mathbf{if}\;t_5 < -1.100156740804105 \cdot 10^{-171}:\\ \;\;\;\;t_6\\ \mathbf{elif}\;t_5 < 0:\\ \;\;\;\;\frac{\frac{t_4}{z}}{c}\\ \mathbf{elif}\;t_5 < 1.1708877911747488 \cdot 10^{-53}:\\ \;\;\;\;t_6\\ \mathbf{elif}\;t_5 < 2.876823679546137 \cdot 10^{+130}:\\ \;\;\;\;\left(\left(9 \cdot \frac{y}{c}\right) \cdot \frac{x}{z} + t_1\right) - t_2\\ \mathbf{elif}\;t_5 < 1.3838515042456319 \cdot 10^{+158}:\\ \;\;\;\;t_6\\ \mathbf{else}:\\ \;\;\;\;\left(9 \cdot \left(\frac{y}{c \cdot z} \cdot x\right) + t_1\right) - t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a b c)
 :precision binary64
 (let* ((t_1 (/ b (* c z)))
        (t_2 (* 4.0 (/ (* a t) c)))
        (t_3 (* (* x 9.0) y))
        (t_4 (+ (- t_3 (* (* (* z 4.0) t) a)) b))
        (t_5 (/ t_4 (* z c)))
        (t_6 (/ (+ (- t_3 (* (* z 4.0) (* t a))) b) (* z c))))
   (if (< t_5 -1.100156740804105e-171)
     t_6
     (if (< t_5 0.0)
       (/ (/ t_4 z) c)
       (if (< t_5 1.1708877911747488e-53)
         t_6
         (if (< t_5 2.876823679546137e+130)
           (- (+ (* (* 9.0 (/ y c)) (/ x z)) t_1) t_2)
           (if (< t_5 1.3838515042456319e+158)
             t_6
             (- (+ (* 9.0 (* (/ y (* c z)) x)) t_1) t_2))))))))

C

double code(double x, double y, double z, double t, double a, double b, double c) {
	double t_1 = b / (c * z);
	double t_2 = 4.0 * ((a * t) / c);
	double t_3 = (x * 9.0) * y;
	double t_4 = (t_3 - (((z * 4.0) * t) * a)) + b;
	double t_5 = t_4 / (z * c);
	double t_6 = ((t_3 - ((z * 4.0) * (t * a))) + b) / (z * c);
	double tmp;
	if (t_5 < -1.100156740804105e-171) {
		tmp = t_6;
	} else if (t_5 < 0.0) {
		tmp = (t_4 / z) / c;
	} else if (t_5 < 1.1708877911747488e-53) {
		tmp = t_6;
	} else if (t_5 < 2.876823679546137e+130) {
		tmp = (((9.0 * (y / c)) * (x / z)) + t_1) - t_2;
	} else if (t_5 < 1.3838515042456319e+158) {
		tmp = t_6;
	} else {
		tmp = ((9.0 * ((y / (c * z)) * x)) + t_1) - t_2;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a, b, c)
    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) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: t_4
    real(8) :: t_5
    real(8) :: t_6
    real(8) :: tmp
    t_1 = b / (c * z)
    t_2 = 4.0d0 * ((a * t) / c)
    t_3 = (x * 9.0d0) * y
    t_4 = (t_3 - (((z * 4.0d0) * t) * a)) + b
    t_5 = t_4 / (z * c)
    t_6 = ((t_3 - ((z * 4.0d0) * (t * a))) + b) / (z * c)
    if (t_5 < (-1.100156740804105d-171)) then
        tmp = t_6
    else if (t_5 < 0.0d0) then
        tmp = (t_4 / z) / c
    else if (t_5 < 1.1708877911747488d-53) then
        tmp = t_6
    else if (t_5 < 2.876823679546137d+130) then
        tmp = (((9.0d0 * (y / c)) * (x / z)) + t_1) - t_2
    else if (t_5 < 1.3838515042456319d+158) then
        tmp = t_6
    else
        tmp = ((9.0d0 * ((y / (c * z)) * x)) + t_1) - 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 t_1 = b / (c * z);
	double t_2 = 4.0 * ((a * t) / c);
	double t_3 = (x * 9.0) * y;
	double t_4 = (t_3 - (((z * 4.0) * t) * a)) + b;
	double t_5 = t_4 / (z * c);
	double t_6 = ((t_3 - ((z * 4.0) * (t * a))) + b) / (z * c);
	double tmp;
	if (t_5 < -1.100156740804105e-171) {
		tmp = t_6;
	} else if (t_5 < 0.0) {
		tmp = (t_4 / z) / c;
	} else if (t_5 < 1.1708877911747488e-53) {
		tmp = t_6;
	} else if (t_5 < 2.876823679546137e+130) {
		tmp = (((9.0 * (y / c)) * (x / z)) + t_1) - t_2;
	} else if (t_5 < 1.3838515042456319e+158) {
		tmp = t_6;
	} else {
		tmp = ((9.0 * ((y / (c * z)) * x)) + t_1) - t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a, b, c):
	t_1 = b / (c * z)
	t_2 = 4.0 * ((a * t) / c)
	t_3 = (x * 9.0) * y
	t_4 = (t_3 - (((z * 4.0) * t) * a)) + b
	t_5 = t_4 / (z * c)
	t_6 = ((t_3 - ((z * 4.0) * (t * a))) + b) / (z * c)
	tmp = 0
	if t_5 < -1.100156740804105e-171:
		tmp = t_6
	elif t_5 < 0.0:
		tmp = (t_4 / z) / c
	elif t_5 < 1.1708877911747488e-53:
		tmp = t_6
	elif t_5 < 2.876823679546137e+130:
		tmp = (((9.0 * (y / c)) * (x / z)) + t_1) - t_2
	elif t_5 < 1.3838515042456319e+158:
		tmp = t_6
	else:
		tmp = ((9.0 * ((y / (c * z)) * x)) + t_1) - t_2
	return tmp

Julia

function code(x, y, z, t, a, b, c)
	t_1 = Float64(b / Float64(c * z))
	t_2 = Float64(4.0 * Float64(Float64(a * t) / c))
	t_3 = Float64(Float64(x * 9.0) * y)
	t_4 = Float64(Float64(t_3 - Float64(Float64(Float64(z * 4.0) * t) * a)) + b)
	t_5 = Float64(t_4 / Float64(z * c))
	t_6 = Float64(Float64(Float64(t_3 - Float64(Float64(z * 4.0) * Float64(t * a))) + b) / Float64(z * c))
	tmp = 0.0
	if (t_5 < -1.100156740804105e-171)
		tmp = t_6;
	elseif (t_5 < 0.0)
		tmp = Float64(Float64(t_4 / z) / c);
	elseif (t_5 < 1.1708877911747488e-53)
		tmp = t_6;
	elseif (t_5 < 2.876823679546137e+130)
		tmp = Float64(Float64(Float64(Float64(9.0 * Float64(y / c)) * Float64(x / z)) + t_1) - t_2);
	elseif (t_5 < 1.3838515042456319e+158)
		tmp = t_6;
	else
		tmp = Float64(Float64(Float64(9.0 * Float64(Float64(y / Float64(c * z)) * x)) + t_1) - t_2);
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a, b, c)
	t_1 = b / (c * z);
	t_2 = 4.0 * ((a * t) / c);
	t_3 = (x * 9.0) * y;
	t_4 = (t_3 - (((z * 4.0) * t) * a)) + b;
	t_5 = t_4 / (z * c);
	t_6 = ((t_3 - ((z * 4.0) * (t * a))) + b) / (z * c);
	tmp = 0.0;
	if (t_5 < -1.100156740804105e-171)
		tmp = t_6;
	elseif (t_5 < 0.0)
		tmp = (t_4 / z) / c;
	elseif (t_5 < 1.1708877911747488e-53)
		tmp = t_6;
	elseif (t_5 < 2.876823679546137e+130)
		tmp = (((9.0 * (y / c)) * (x / z)) + t_1) - t_2;
	elseif (t_5 < 1.3838515042456319e+158)
		tmp = t_6;
	else
		tmp = ((9.0 * ((y / (c * z)) * x)) + t_1) - t_2;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_, b_, c_] := Block[{t$95$1 = N[(b / N[(c * z), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(4.0 * N[(N[(a * t), $MachinePrecision] / c), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(x * 9.0), $MachinePrecision] * y), $MachinePrecision]}, Block[{t$95$4 = N[(N[(t$95$3 - N[(N[(N[(z * 4.0), $MachinePrecision] * t), $MachinePrecision] * a), $MachinePrecision]), $MachinePrecision] + b), $MachinePrecision]}, Block[{t$95$5 = N[(t$95$4 / N[(z * c), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$6 = N[(N[(N[(t$95$3 - N[(N[(z * 4.0), $MachinePrecision] * N[(t * a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + b), $MachinePrecision] / N[(z * c), $MachinePrecision]), $MachinePrecision]}, If[Less[t$95$5, -1.100156740804105e-171], t$95$6, If[Less[t$95$5, 0.0], N[(N[(t$95$4 / z), $MachinePrecision] / c), $MachinePrecision], If[Less[t$95$5, 1.1708877911747488e-53], t$95$6, If[Less[t$95$5, 2.876823679546137e+130], N[(N[(N[(N[(9.0 * N[(y / c), $MachinePrecision]), $MachinePrecision] * N[(x / z), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision] - t$95$2), $MachinePrecision], If[Less[t$95$5, 1.3838515042456319e+158], t$95$6, N[(N[(N[(9.0 * N[(N[(y / N[(c * z), $MachinePrecision]), $MachinePrecision] * x), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision] - t$95$2), $MachinePrecision]]]]]]]]]]]]

Reproduce

herbie shell --seed 2023343 
(FPCore (x y z t a b c)
  :name "Diagrams.Solve.Polynomial:cubForm  from diagrams-solve-0.1, J"
  :precision binary64

  :herbie-target
  (if (< (/ (+ (- (* (* x 9.0) y) (* (* (* z 4.0) t) a)) b) (* z c)) -1.100156740804105e-171) (/ (+ (- (* (* x 9.0) y) (* (* z 4.0) (* t a))) b) (* z c)) (if (< (/ (+ (- (* (* x 9.0) y) (* (* (* z 4.0) t) a)) b) (* z c)) 0.0) (/ (/ (+ (- (* (* x 9.0) y) (* (* (* z 4.0) t) a)) b) z) c) (if (< (/ (+ (- (* (* x 9.0) y) (* (* (* z 4.0) t) a)) b) (* z c)) 1.1708877911747488e-53) (/ (+ (- (* (* x 9.0) y) (* (* z 4.0) (* t a))) b) (* z c)) (if (< (/ (+ (- (* (* x 9.0) y) (* (* (* z 4.0) t) a)) b) (* z c)) 2.876823679546137e+130) (- (+ (* (* 9.0 (/ y c)) (/ x z)) (/ b (* c z))) (* 4.0 (/ (* a t) c))) (if (< (/ (+ (- (* (* x 9.0) y) (* (* (* z 4.0) t) a)) b) (* z c)) 1.3838515042456319e+158) (/ (+ (- (* (* x 9.0) y) (* (* z 4.0) (* t a))) b) (* z c)) (- (+ (* 9.0 (* (/ y (* c z)) x)) (/ b (* c z))) (* 4.0 (/ (* a t) c))))))))

  (/ (+ (- (* (* x 9.0) y) (* (* (* z 4.0) t) a)) b) (* z c)))