Graphics.Rendering.Chart.Axis.Types:linMap from Chart-1.5.3

Percentage Accurate: 68.1% → 90.1%

Time: 25.7s

Alternatives: 27

Speedup: 0.8×

Specification

Math

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

FPCore

(FPCore (x y z t a) :precision binary64 (+ x (/ (* (- y x) (- z t)) (- a t))))

C

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

Fortran

real(8) function code(x, y, z, t, a)
    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
    code = x + (((y - x) * (z - t)) / (a - t))
end function

Java

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

Python

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

Julia

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

MATLAB

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

Wolfram

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

Initial Program: 68.1% accurate, 1.0× speedup

Math

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

FPCore

(FPCore (x y z t a) :precision binary64 (+ x (/ (* (- y x) (- z t)) (- a t))))

C

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

Fortran

real(8) function code(x, y, z, t, a)
    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
    code = x + (((y - x) * (z - t)) / (a - t))
end function

Java

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

Python

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

Julia

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

MATLAB

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

Wolfram

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

Alternative 1: 90.1% accurate, 0.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x + \frac{\left(y - x\right) \cdot \left(z - t\right)}{a - t}\\ \mathbf{if}\;t_1 \leq -2 \cdot 10^{-213} \lor \neg \left(t_1 \leq 0\right):\\ \;\;\;\;x + \left(y - x\right) \cdot \frac{z - t}{a - t}\\ \mathbf{else}:\\ \;\;\;\;y + \frac{\left(y - x\right) \cdot \left(a - z\right)}{t}\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (let* ((t_1 (+ x (/ (* (- y x) (- z t)) (- a t)))))
   (if (or (<= t_1 -2e-213) (not (<= t_1 0.0)))
     (+ x (* (- y x) (/ (- z t) (- a t))))
     (+ y (/ (* (- y x) (- a z)) t)))))

C

double code(double x, double y, double z, double t, double a) {
	double t_1 = x + (((y - x) * (z - t)) / (a - t));
	double tmp;
	if ((t_1 <= -2e-213) || !(t_1 <= 0.0)) {
		tmp = x + ((y - x) * ((z - t) / (a - t)));
	} else {
		tmp = y + (((y - x) * (a - z)) / t);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a)
    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) :: t_1
    real(8) :: tmp
    t_1 = x + (((y - x) * (z - t)) / (a - t))
    if ((t_1 <= (-2d-213)) .or. (.not. (t_1 <= 0.0d0))) then
        tmp = x + ((y - x) * ((z - t) / (a - t)))
    else
        tmp = y + (((y - x) * (a - z)) / t)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a) {
	double t_1 = x + (((y - x) * (z - t)) / (a - t));
	double tmp;
	if ((t_1 <= -2e-213) || !(t_1 <= 0.0)) {
		tmp = x + ((y - x) * ((z - t) / (a - t)));
	} else {
		tmp = y + (((y - x) * (a - z)) / t);
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	t_1 = x + (((y - x) * (z - t)) / (a - t))
	tmp = 0
	if (t_1 <= -2e-213) or not (t_1 <= 0.0):
		tmp = x + ((y - x) * ((z - t) / (a - t)))
	else:
		tmp = y + (((y - x) * (a - z)) / t)
	return tmp

Julia

function code(x, y, z, t, a)
	t_1 = Float64(x + Float64(Float64(Float64(y - x) * Float64(z - t)) / Float64(a - t)))
	tmp = 0.0
	if ((t_1 <= -2e-213) || !(t_1 <= 0.0))
		tmp = Float64(x + Float64(Float64(y - x) * Float64(Float64(z - t) / Float64(a - t))));
	else
		tmp = Float64(y + Float64(Float64(Float64(y - x) * Float64(a - z)) / t));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	t_1 = x + (((y - x) * (z - t)) / (a - t));
	tmp = 0.0;
	if ((t_1 <= -2e-213) || ~((t_1 <= 0.0)))
		tmp = x + ((y - x) * ((z - t) / (a - t)));
	else
		tmp = y + (((y - x) * (a - z)) / t);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := Block[{t$95$1 = N[(x + N[(N[(N[(y - x), $MachinePrecision] * N[(z - t), $MachinePrecision]), $MachinePrecision] / N[(a - t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[t$95$1, -2e-213], N[Not[LessEqual[t$95$1, 0.0]], $MachinePrecision]], N[(x + N[(N[(y - x), $MachinePrecision] * N[(N[(z - t), $MachinePrecision] / N[(a - t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(y + N[(N[(N[(y - x), $MachinePrecision] * N[(a - z), $MachinePrecision]), $MachinePrecision] / t), $MachinePrecision]), $MachinePrecision]]]

Derivation

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

Alternative 2: 88.6% accurate, 0.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x + \left(z - t\right) \cdot \frac{y - x}{a - t}\\ t_2 := x + \frac{\left(y - x\right) \cdot \left(z - t\right)}{a - t}\\ \mathbf{if}\;t_2 \leq -\infty:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t_2 \leq -2 \cdot 10^{-213}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;t_2 \leq 0:\\ \;\;\;\;y + \frac{\left(y - x\right) \cdot \left(a - z\right)}{t}\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (let* ((t_1 (+ x (* (- z t) (/ (- y x) (- a t)))))
        (t_2 (+ x (/ (* (- y x) (- z t)) (- a t)))))
   (if (<= t_2 (- INFINITY))
     t_1
     (if (<= t_2 -2e-213)
       t_2
       (if (<= t_2 0.0) (+ y (/ (* (- y x) (- a z)) t)) t_1)))))

C

double code(double x, double y, double z, double t, double a) {
	double t_1 = x + ((z - t) * ((y - x) / (a - t)));
	double t_2 = x + (((y - x) * (z - t)) / (a - t));
	double tmp;
	if (t_2 <= -((double) INFINITY)) {
		tmp = t_1;
	} else if (t_2 <= -2e-213) {
		tmp = t_2;
	} else if (t_2 <= 0.0) {
		tmp = y + (((y - x) * (a - z)) / t);
	} else {
		tmp = t_1;
	}
	return tmp;
}

Java

public static double code(double x, double y, double z, double t, double a) {
	double t_1 = x + ((z - t) * ((y - x) / (a - t)));
	double t_2 = x + (((y - x) * (z - t)) / (a - t));
	double tmp;
	if (t_2 <= -Double.POSITIVE_INFINITY) {
		tmp = t_1;
	} else if (t_2 <= -2e-213) {
		tmp = t_2;
	} else if (t_2 <= 0.0) {
		tmp = y + (((y - x) * (a - z)) / t);
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	t_1 = x + ((z - t) * ((y - x) / (a - t)))
	t_2 = x + (((y - x) * (z - t)) / (a - t))
	tmp = 0
	if t_2 <= -math.inf:
		tmp = t_1
	elif t_2 <= -2e-213:
		tmp = t_2
	elif t_2 <= 0.0:
		tmp = y + (((y - x) * (a - z)) / t)
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a)
	t_1 = Float64(x + Float64(Float64(z - t) * Float64(Float64(y - x) / Float64(a - t))))
	t_2 = Float64(x + Float64(Float64(Float64(y - x) * Float64(z - t)) / Float64(a - t)))
	tmp = 0.0
	if (t_2 <= Float64(-Inf))
		tmp = t_1;
	elseif (t_2 <= -2e-213)
		tmp = t_2;
	elseif (t_2 <= 0.0)
		tmp = Float64(y + Float64(Float64(Float64(y - x) * Float64(a - z)) / t));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	t_1 = x + ((z - t) * ((y - x) / (a - t)));
	t_2 = x + (((y - x) * (z - t)) / (a - t));
	tmp = 0.0;
	if (t_2 <= -Inf)
		tmp = t_1;
	elseif (t_2 <= -2e-213)
		tmp = t_2;
	elseif (t_2 <= 0.0)
		tmp = y + (((y - x) * (a - z)) / t);
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := Block[{t$95$1 = N[(x + N[(N[(z - t), $MachinePrecision] * N[(N[(y - x), $MachinePrecision] / N[(a - t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(x + N[(N[(N[(y - x), $MachinePrecision] * N[(z - t), $MachinePrecision]), $MachinePrecision] / N[(a - t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$2, (-Infinity)], t$95$1, If[LessEqual[t$95$2, -2e-213], t$95$2, If[LessEqual[t$95$2, 0.0], N[(y + N[(N[(N[(y - x), $MachinePrecision] * N[(a - z), $MachinePrecision]), $MachinePrecision] / t), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]

Derivation

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

Alternative 3: 88.6% accurate, 0.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x + \frac{\left(y - x\right) \cdot \left(z - t\right)}{a - t}\\ \mathbf{if}\;t_1 \leq -\infty:\\ \;\;\;\;x - \frac{t - z}{\frac{a - t}{y - x}}\\ \mathbf{elif}\;t_1 \leq -2 \cdot 10^{-213}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;t_1 \leq 0:\\ \;\;\;\;y + \frac{\left(y - x\right) \cdot \left(a - z\right)}{t}\\ \mathbf{else}:\\ \;\;\;\;x + \left(z - t\right) \cdot \frac{y - x}{a - t}\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (let* ((t_1 (+ x (/ (* (- y x) (- z t)) (- a t)))))
   (if (<= t_1 (- INFINITY))
     (- x (/ (- t z) (/ (- a t) (- y x))))
     (if (<= t_1 -2e-213)
       t_1
       (if (<= t_1 0.0)
         (+ y (/ (* (- y x) (- a z)) t))
         (+ x (* (- z t) (/ (- y x) (- a t)))))))))

C

double code(double x, double y, double z, double t, double a) {
	double t_1 = x + (((y - x) * (z - t)) / (a - t));
	double tmp;
	if (t_1 <= -((double) INFINITY)) {
		tmp = x - ((t - z) / ((a - t) / (y - x)));
	} else if (t_1 <= -2e-213) {
		tmp = t_1;
	} else if (t_1 <= 0.0) {
		tmp = y + (((y - x) * (a - z)) / t);
	} else {
		tmp = x + ((z - t) * ((y - x) / (a - t)));
	}
	return tmp;
}

Java

public static double code(double x, double y, double z, double t, double a) {
	double t_1 = x + (((y - x) * (z - t)) / (a - t));
	double tmp;
	if (t_1 <= -Double.POSITIVE_INFINITY) {
		tmp = x - ((t - z) / ((a - t) / (y - x)));
	} else if (t_1 <= -2e-213) {
		tmp = t_1;
	} else if (t_1 <= 0.0) {
		tmp = y + (((y - x) * (a - z)) / t);
	} else {
		tmp = x + ((z - t) * ((y - x) / (a - t)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	t_1 = x + (((y - x) * (z - t)) / (a - t))
	tmp = 0
	if t_1 <= -math.inf:
		tmp = x - ((t - z) / ((a - t) / (y - x)))
	elif t_1 <= -2e-213:
		tmp = t_1
	elif t_1 <= 0.0:
		tmp = y + (((y - x) * (a - z)) / t)
	else:
		tmp = x + ((z - t) * ((y - x) / (a - t)))
	return tmp

Julia

function code(x, y, z, t, a)
	t_1 = Float64(x + Float64(Float64(Float64(y - x) * Float64(z - t)) / Float64(a - t)))
	tmp = 0.0
	if (t_1 <= Float64(-Inf))
		tmp = Float64(x - Float64(Float64(t - z) / Float64(Float64(a - t) / Float64(y - x))));
	elseif (t_1 <= -2e-213)
		tmp = t_1;
	elseif (t_1 <= 0.0)
		tmp = Float64(y + Float64(Float64(Float64(y - x) * Float64(a - z)) / t));
	else
		tmp = Float64(x + Float64(Float64(z - t) * Float64(Float64(y - x) / Float64(a - t))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	t_1 = x + (((y - x) * (z - t)) / (a - t));
	tmp = 0.0;
	if (t_1 <= -Inf)
		tmp = x - ((t - z) / ((a - t) / (y - x)));
	elseif (t_1 <= -2e-213)
		tmp = t_1;
	elseif (t_1 <= 0.0)
		tmp = y + (((y - x) * (a - z)) / t);
	else
		tmp = x + ((z - t) * ((y - x) / (a - t)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := Block[{t$95$1 = N[(x + N[(N[(N[(y - x), $MachinePrecision] * N[(z - t), $MachinePrecision]), $MachinePrecision] / N[(a - t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$1, (-Infinity)], N[(x - N[(N[(t - z), $MachinePrecision] / N[(N[(a - t), $MachinePrecision] / N[(y - x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$1, -2e-213], t$95$1, If[LessEqual[t$95$1, 0.0], N[(y + N[(N[(N[(y - x), $MachinePrecision] * N[(a - z), $MachinePrecision]), $MachinePrecision] / t), $MachinePrecision]), $MachinePrecision], N[(x + N[(N[(z - t), $MachinePrecision] * N[(N[(y - x), $MachinePrecision] / N[(a - t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

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

Alternative 4: 58.2% accurate, 0.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y \cdot \frac{z - t}{a - t}\\ t_2 := x + y \cdot \frac{z}{a}\\ \mathbf{if}\;a \leq -1.6 \cdot 10^{+146}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq -2.25 \cdot 10^{-144}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -5.8 \cdot 10^{-226}:\\ \;\;\;\;\frac{z \cdot \left(x - y\right)}{t}\\ \mathbf{elif}\;a \leq 2.25 \cdot 10^{-188}:\\ \;\;\;\;y + \frac{x}{\frac{t}{z}}\\ \mathbf{elif}\;a \leq 6.2 \cdot 10^{-53}:\\ \;\;\;\;y - \frac{a}{\frac{t}{x}}\\ \mathbf{elif}\;a \leq 6 \cdot 10^{-15}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq 6.6 \cdot 10^{+20}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;x + \frac{z}{\frac{a}{y}}\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (let* ((t_1 (* y (/ (- z t) (- a t)))) (t_2 (+ x (* y (/ z a)))))
   (if (<= a -1.6e+146)
     t_2
     (if (<= a -2.25e-144)
       t_1
       (if (<= a -5.8e-226)
         (/ (* z (- x y)) t)
         (if (<= a 2.25e-188)
           (+ y (/ x (/ t z)))
           (if (<= a 6.2e-53)
             (- y (/ a (/ t x)))
             (if (<= a 6e-15)
               t_2
               (if (<= a 6.6e+20) t_1 (+ x (/ z (/ a y))))))))))))

C

double code(double x, double y, double z, double t, double a) {
	double t_1 = y * ((z - t) / (a - t));
	double t_2 = x + (y * (z / a));
	double tmp;
	if (a <= -1.6e+146) {
		tmp = t_2;
	} else if (a <= -2.25e-144) {
		tmp = t_1;
	} else if (a <= -5.8e-226) {
		tmp = (z * (x - y)) / t;
	} else if (a <= 2.25e-188) {
		tmp = y + (x / (t / z));
	} else if (a <= 6.2e-53) {
		tmp = y - (a / (t / x));
	} else if (a <= 6e-15) {
		tmp = t_2;
	} else if (a <= 6.6e+20) {
		tmp = t_1;
	} else {
		tmp = x + (z / (a / y));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a)
    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) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = y * ((z - t) / (a - t))
    t_2 = x + (y * (z / a))
    if (a <= (-1.6d+146)) then
        tmp = t_2
    else if (a <= (-2.25d-144)) then
        tmp = t_1
    else if (a <= (-5.8d-226)) then
        tmp = (z * (x - y)) / t
    else if (a <= 2.25d-188) then
        tmp = y + (x / (t / z))
    else if (a <= 6.2d-53) then
        tmp = y - (a / (t / x))
    else if (a <= 6d-15) then
        tmp = t_2
    else if (a <= 6.6d+20) then
        tmp = t_1
    else
        tmp = x + (z / (a / y))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a) {
	double t_1 = y * ((z - t) / (a - t));
	double t_2 = x + (y * (z / a));
	double tmp;
	if (a <= -1.6e+146) {
		tmp = t_2;
	} else if (a <= -2.25e-144) {
		tmp = t_1;
	} else if (a <= -5.8e-226) {
		tmp = (z * (x - y)) / t;
	} else if (a <= 2.25e-188) {
		tmp = y + (x / (t / z));
	} else if (a <= 6.2e-53) {
		tmp = y - (a / (t / x));
	} else if (a <= 6e-15) {
		tmp = t_2;
	} else if (a <= 6.6e+20) {
		tmp = t_1;
	} else {
		tmp = x + (z / (a / y));
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	t_1 = y * ((z - t) / (a - t))
	t_2 = x + (y * (z / a))
	tmp = 0
	if a <= -1.6e+146:
		tmp = t_2
	elif a <= -2.25e-144:
		tmp = t_1
	elif a <= -5.8e-226:
		tmp = (z * (x - y)) / t
	elif a <= 2.25e-188:
		tmp = y + (x / (t / z))
	elif a <= 6.2e-53:
		tmp = y - (a / (t / x))
	elif a <= 6e-15:
		tmp = t_2
	elif a <= 6.6e+20:
		tmp = t_1
	else:
		tmp = x + (z / (a / y))
	return tmp

Julia

function code(x, y, z, t, a)
	t_1 = Float64(y * Float64(Float64(z - t) / Float64(a - t)))
	t_2 = Float64(x + Float64(y * Float64(z / a)))
	tmp = 0.0
	if (a <= -1.6e+146)
		tmp = t_2;
	elseif (a <= -2.25e-144)
		tmp = t_1;
	elseif (a <= -5.8e-226)
		tmp = Float64(Float64(z * Float64(x - y)) / t);
	elseif (a <= 2.25e-188)
		tmp = Float64(y + Float64(x / Float64(t / z)));
	elseif (a <= 6.2e-53)
		tmp = Float64(y - Float64(a / Float64(t / x)));
	elseif (a <= 6e-15)
		tmp = t_2;
	elseif (a <= 6.6e+20)
		tmp = t_1;
	else
		tmp = Float64(x + Float64(z / Float64(a / y)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	t_1 = y * ((z - t) / (a - t));
	t_2 = x + (y * (z / a));
	tmp = 0.0;
	if (a <= -1.6e+146)
		tmp = t_2;
	elseif (a <= -2.25e-144)
		tmp = t_1;
	elseif (a <= -5.8e-226)
		tmp = (z * (x - y)) / t;
	elseif (a <= 2.25e-188)
		tmp = y + (x / (t / z));
	elseif (a <= 6.2e-53)
		tmp = y - (a / (t / x));
	elseif (a <= 6e-15)
		tmp = t_2;
	elseif (a <= 6.6e+20)
		tmp = t_1;
	else
		tmp = x + (z / (a / y));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := Block[{t$95$1 = N[(y * N[(N[(z - t), $MachinePrecision] / N[(a - t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(x + N[(y * N[(z / a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -1.6e+146], t$95$2, If[LessEqual[a, -2.25e-144], t$95$1, If[LessEqual[a, -5.8e-226], N[(N[(z * N[(x - y), $MachinePrecision]), $MachinePrecision] / t), $MachinePrecision], If[LessEqual[a, 2.25e-188], N[(y + N[(x / N[(t / z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 6.2e-53], N[(y - N[(a / N[(t / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 6e-15], t$95$2, If[LessEqual[a, 6.6e+20], t$95$1, N[(x + N[(z / N[(a / y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]

Derivation

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

Alternative 5: 66.9% accurate, 0.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y + \left(z - a\right) \cdot \frac{x}{t}\\ t_2 := x + \left(y - x\right) \cdot \frac{z}{a}\\ \mathbf{if}\;a \leq -8.8 \cdot 10^{-43}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq -2.15 \cdot 10^{-66}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -1.12 \cdot 10^{-100}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq 1.8 \cdot 10^{-161}:\\ \;\;\;\;y + \frac{z \cdot \left(x - y\right)}{t}\\ \mathbf{elif}\;a \leq 8 \cdot 10^{-53}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 2.4 \cdot 10^{-18}:\\ \;\;\;\;x + y \cdot \frac{z}{a}\\ \mathbf{elif}\;a \leq 6.5 \cdot 10^{+20}:\\ \;\;\;\;y \cdot \frac{z - t}{a - t}\\ \mathbf{else}:\\ \;\;\;\;x + \frac{z}{\frac{a}{y - x}}\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (let* ((t_1 (+ y (* (- z a) (/ x t)))) (t_2 (+ x (* (- y x) (/ z a)))))
   (if (<= a -8.8e-43)
     t_2
     (if (<= a -2.15e-66)
       t_1
       (if (<= a -1.12e-100)
         t_2
         (if (<= a 1.8e-161)
           (+ y (/ (* z (- x y)) t))
           (if (<= a 8e-53)
             t_1
             (if (<= a 2.4e-18)
               (+ x (* y (/ z a)))
               (if (<= a 6.5e+20)
                 (* y (/ (- z t) (- a t)))
                 (+ x (/ z (/ a (- y x)))))))))))))

C

double code(double x, double y, double z, double t, double a) {
	double t_1 = y + ((z - a) * (x / t));
	double t_2 = x + ((y - x) * (z / a));
	double tmp;
	if (a <= -8.8e-43) {
		tmp = t_2;
	} else if (a <= -2.15e-66) {
		tmp = t_1;
	} else if (a <= -1.12e-100) {
		tmp = t_2;
	} else if (a <= 1.8e-161) {
		tmp = y + ((z * (x - y)) / t);
	} else if (a <= 8e-53) {
		tmp = t_1;
	} else if (a <= 2.4e-18) {
		tmp = x + (y * (z / a));
	} else if (a <= 6.5e+20) {
		tmp = y * ((z - t) / (a - t));
	} else {
		tmp = x + (z / (a / (y - x)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a)
    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) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = y + ((z - a) * (x / t))
    t_2 = x + ((y - x) * (z / a))
    if (a <= (-8.8d-43)) then
        tmp = t_2
    else if (a <= (-2.15d-66)) then
        tmp = t_1
    else if (a <= (-1.12d-100)) then
        tmp = t_2
    else if (a <= 1.8d-161) then
        tmp = y + ((z * (x - y)) / t)
    else if (a <= 8d-53) then
        tmp = t_1
    else if (a <= 2.4d-18) then
        tmp = x + (y * (z / a))
    else if (a <= 6.5d+20) then
        tmp = y * ((z - t) / (a - t))
    else
        tmp = x + (z / (a / (y - x)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a) {
	double t_1 = y + ((z - a) * (x / t));
	double t_2 = x + ((y - x) * (z / a));
	double tmp;
	if (a <= -8.8e-43) {
		tmp = t_2;
	} else if (a <= -2.15e-66) {
		tmp = t_1;
	} else if (a <= -1.12e-100) {
		tmp = t_2;
	} else if (a <= 1.8e-161) {
		tmp = y + ((z * (x - y)) / t);
	} else if (a <= 8e-53) {
		tmp = t_1;
	} else if (a <= 2.4e-18) {
		tmp = x + (y * (z / a));
	} else if (a <= 6.5e+20) {
		tmp = y * ((z - t) / (a - t));
	} else {
		tmp = x + (z / (a / (y - x)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	t_1 = y + ((z - a) * (x / t))
	t_2 = x + ((y - x) * (z / a))
	tmp = 0
	if a <= -8.8e-43:
		tmp = t_2
	elif a <= -2.15e-66:
		tmp = t_1
	elif a <= -1.12e-100:
		tmp = t_2
	elif a <= 1.8e-161:
		tmp = y + ((z * (x - y)) / t)
	elif a <= 8e-53:
		tmp = t_1
	elif a <= 2.4e-18:
		tmp = x + (y * (z / a))
	elif a <= 6.5e+20:
		tmp = y * ((z - t) / (a - t))
	else:
		tmp = x + (z / (a / (y - x)))
	return tmp

Julia

function code(x, y, z, t, a)
	t_1 = Float64(y + Float64(Float64(z - a) * Float64(x / t)))
	t_2 = Float64(x + Float64(Float64(y - x) * Float64(z / a)))
	tmp = 0.0
	if (a <= -8.8e-43)
		tmp = t_2;
	elseif (a <= -2.15e-66)
		tmp = t_1;
	elseif (a <= -1.12e-100)
		tmp = t_2;
	elseif (a <= 1.8e-161)
		tmp = Float64(y + Float64(Float64(z * Float64(x - y)) / t));
	elseif (a <= 8e-53)
		tmp = t_1;
	elseif (a <= 2.4e-18)
		tmp = Float64(x + Float64(y * Float64(z / a)));
	elseif (a <= 6.5e+20)
		tmp = Float64(y * Float64(Float64(z - t) / Float64(a - t)));
	else
		tmp = Float64(x + Float64(z / Float64(a / Float64(y - x))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	t_1 = y + ((z - a) * (x / t));
	t_2 = x + ((y - x) * (z / a));
	tmp = 0.0;
	if (a <= -8.8e-43)
		tmp = t_2;
	elseif (a <= -2.15e-66)
		tmp = t_1;
	elseif (a <= -1.12e-100)
		tmp = t_2;
	elseif (a <= 1.8e-161)
		tmp = y + ((z * (x - y)) / t);
	elseif (a <= 8e-53)
		tmp = t_1;
	elseif (a <= 2.4e-18)
		tmp = x + (y * (z / a));
	elseif (a <= 6.5e+20)
		tmp = y * ((z - t) / (a - t));
	else
		tmp = x + (z / (a / (y - x)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := Block[{t$95$1 = N[(y + N[(N[(z - a), $MachinePrecision] * N[(x / t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(x + N[(N[(y - x), $MachinePrecision] * N[(z / a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -8.8e-43], t$95$2, If[LessEqual[a, -2.15e-66], t$95$1, If[LessEqual[a, -1.12e-100], t$95$2, If[LessEqual[a, 1.8e-161], N[(y + N[(N[(z * N[(x - y), $MachinePrecision]), $MachinePrecision] / t), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 8e-53], t$95$1, If[LessEqual[a, 2.4e-18], N[(x + N[(y * N[(z / a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 6.5e+20], N[(y * N[(N[(z - t), $MachinePrecision] / N[(a - t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(x + N[(z / N[(a / N[(y - x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]

Derivation

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

Alternative 6: 39.6% accurate, 0.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \left(z - t\right) \cdot \frac{y}{a}\\ t_2 := x \cdot \left(1 - \frac{z}{a}\right)\\ t_3 := \left(z - a\right) \cdot \frac{x}{t}\\ \mathbf{if}\;a \leq -3.7 \cdot 10^{+65}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq -5 \cdot 10^{-22}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -3.2 \cdot 10^{-271}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;a \leq 2.6 \cdot 10^{-228}:\\ \;\;\;\;y\\ \mathbf{elif}\;a \leq 6.4 \cdot 10^{-53}:\\ \;\;\;\;t_3\\ \mathbf{elif}\;a \leq 2.9 \cdot 10^{+184} \lor \neg \left(a \leq 2.2 \cdot 10^{+232}\right):\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (let* ((t_1 (* (- z t) (/ y a)))
        (t_2 (* x (- 1.0 (/ z a))))
        (t_3 (* (- z a) (/ x t))))
   (if (<= a -3.7e+65)
     t_2
     (if (<= a -5e-22)
       t_1
       (if (<= a -3.2e-271)
         t_3
         (if (<= a 2.6e-228)
           y
           (if (<= a 6.4e-53)
             t_3
             (if (or (<= a 2.9e+184) (not (<= a 2.2e+232))) t_2 t_1))))))))

C

double code(double x, double y, double z, double t, double a) {
	double t_1 = (z - t) * (y / a);
	double t_2 = x * (1.0 - (z / a));
	double t_3 = (z - a) * (x / t);
	double tmp;
	if (a <= -3.7e+65) {
		tmp = t_2;
	} else if (a <= -5e-22) {
		tmp = t_1;
	} else if (a <= -3.2e-271) {
		tmp = t_3;
	} else if (a <= 2.6e-228) {
		tmp = y;
	} else if (a <= 6.4e-53) {
		tmp = t_3;
	} else if ((a <= 2.9e+184) || !(a <= 2.2e+232)) {
		tmp = t_2;
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a)
    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) :: t_1
    real(8) :: t_2
    real(8) :: t_3
    real(8) :: tmp
    t_1 = (z - t) * (y / a)
    t_2 = x * (1.0d0 - (z / a))
    t_3 = (z - a) * (x / t)
    if (a <= (-3.7d+65)) then
        tmp = t_2
    else if (a <= (-5d-22)) then
        tmp = t_1
    else if (a <= (-3.2d-271)) then
        tmp = t_3
    else if (a <= 2.6d-228) then
        tmp = y
    else if (a <= 6.4d-53) then
        tmp = t_3
    else if ((a <= 2.9d+184) .or. (.not. (a <= 2.2d+232))) then
        tmp = t_2
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a) {
	double t_1 = (z - t) * (y / a);
	double t_2 = x * (1.0 - (z / a));
	double t_3 = (z - a) * (x / t);
	double tmp;
	if (a <= -3.7e+65) {
		tmp = t_2;
	} else if (a <= -5e-22) {
		tmp = t_1;
	} else if (a <= -3.2e-271) {
		tmp = t_3;
	} else if (a <= 2.6e-228) {
		tmp = y;
	} else if (a <= 6.4e-53) {
		tmp = t_3;
	} else if ((a <= 2.9e+184) || !(a <= 2.2e+232)) {
		tmp = t_2;
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	t_1 = (z - t) * (y / a)
	t_2 = x * (1.0 - (z / a))
	t_3 = (z - a) * (x / t)
	tmp = 0
	if a <= -3.7e+65:
		tmp = t_2
	elif a <= -5e-22:
		tmp = t_1
	elif a <= -3.2e-271:
		tmp = t_3
	elif a <= 2.6e-228:
		tmp = y
	elif a <= 6.4e-53:
		tmp = t_3
	elif (a <= 2.9e+184) or not (a <= 2.2e+232):
		tmp = t_2
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a)
	t_1 = Float64(Float64(z - t) * Float64(y / a))
	t_2 = Float64(x * Float64(1.0 - Float64(z / a)))
	t_3 = Float64(Float64(z - a) * Float64(x / t))
	tmp = 0.0
	if (a <= -3.7e+65)
		tmp = t_2;
	elseif (a <= -5e-22)
		tmp = t_1;
	elseif (a <= -3.2e-271)
		tmp = t_3;
	elseif (a <= 2.6e-228)
		tmp = y;
	elseif (a <= 6.4e-53)
		tmp = t_3;
	elseif ((a <= 2.9e+184) || !(a <= 2.2e+232))
		tmp = t_2;
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	t_1 = (z - t) * (y / a);
	t_2 = x * (1.0 - (z / a));
	t_3 = (z - a) * (x / t);
	tmp = 0.0;
	if (a <= -3.7e+65)
		tmp = t_2;
	elseif (a <= -5e-22)
		tmp = t_1;
	elseif (a <= -3.2e-271)
		tmp = t_3;
	elseif (a <= 2.6e-228)
		tmp = y;
	elseif (a <= 6.4e-53)
		tmp = t_3;
	elseif ((a <= 2.9e+184) || ~((a <= 2.2e+232)))
		tmp = t_2;
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := Block[{t$95$1 = N[(N[(z - t), $MachinePrecision] * N[(y / a), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(x * N[(1.0 - N[(z / a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(z - a), $MachinePrecision] * N[(x / t), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -3.7e+65], t$95$2, If[LessEqual[a, -5e-22], t$95$1, If[LessEqual[a, -3.2e-271], t$95$3, If[LessEqual[a, 2.6e-228], y, If[LessEqual[a, 6.4e-53], t$95$3, If[Or[LessEqual[a, 2.9e+184], N[Not[LessEqual[a, 2.2e+232]], $MachinePrecision]], t$95$2, t$95$1]]]]]]]]]

Derivation

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

Alternative 7: 58.1% accurate, 0.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x + y \cdot \frac{z}{a}\\ \mathbf{if}\;a \leq -1.26 \cdot 10^{+78}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -3.5 \cdot 10^{-224}:\\ \;\;\;\;z \cdot \frac{y - x}{a - t}\\ \mathbf{elif}\;a \leq 2.25 \cdot 10^{-188}:\\ \;\;\;\;y + \frac{x}{\frac{t}{z}}\\ \mathbf{elif}\;a \leq 6.2 \cdot 10^{-53}:\\ \;\;\;\;y - \frac{a}{\frac{t}{x}}\\ \mathbf{elif}\;a \leq 7.2 \cdot 10^{-19}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 7.5 \cdot 10^{+20}:\\ \;\;\;\;y \cdot \frac{z - t}{a - t}\\ \mathbf{else}:\\ \;\;\;\;x + \frac{z}{\frac{a}{y}}\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (let* ((t_1 (+ x (* y (/ z a)))))
   (if (<= a -1.26e+78)
     t_1
     (if (<= a -3.5e-224)
       (* z (/ (- y x) (- a t)))
       (if (<= a 2.25e-188)
         (+ y (/ x (/ t z)))
         (if (<= a 6.2e-53)
           (- y (/ a (/ t x)))
           (if (<= a 7.2e-19)
             t_1
             (if (<= a 7.5e+20)
               (* y (/ (- z t) (- a t)))
               (+ x (/ z (/ a y)))))))))))

C

double code(double x, double y, double z, double t, double a) {
	double t_1 = x + (y * (z / a));
	double tmp;
	if (a <= -1.26e+78) {
		tmp = t_1;
	} else if (a <= -3.5e-224) {
		tmp = z * ((y - x) / (a - t));
	} else if (a <= 2.25e-188) {
		tmp = y + (x / (t / z));
	} else if (a <= 6.2e-53) {
		tmp = y - (a / (t / x));
	} else if (a <= 7.2e-19) {
		tmp = t_1;
	} else if (a <= 7.5e+20) {
		tmp = y * ((z - t) / (a - t));
	} else {
		tmp = x + (z / (a / y));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a)
    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) :: t_1
    real(8) :: tmp
    t_1 = x + (y * (z / a))
    if (a <= (-1.26d+78)) then
        tmp = t_1
    else if (a <= (-3.5d-224)) then
        tmp = z * ((y - x) / (a - t))
    else if (a <= 2.25d-188) then
        tmp = y + (x / (t / z))
    else if (a <= 6.2d-53) then
        tmp = y - (a / (t / x))
    else if (a <= 7.2d-19) then
        tmp = t_1
    else if (a <= 7.5d+20) then
        tmp = y * ((z - t) / (a - t))
    else
        tmp = x + (z / (a / y))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a) {
	double t_1 = x + (y * (z / a));
	double tmp;
	if (a <= -1.26e+78) {
		tmp = t_1;
	} else if (a <= -3.5e-224) {
		tmp = z * ((y - x) / (a - t));
	} else if (a <= 2.25e-188) {
		tmp = y + (x / (t / z));
	} else if (a <= 6.2e-53) {
		tmp = y - (a / (t / x));
	} else if (a <= 7.2e-19) {
		tmp = t_1;
	} else if (a <= 7.5e+20) {
		tmp = y * ((z - t) / (a - t));
	} else {
		tmp = x + (z / (a / y));
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	t_1 = x + (y * (z / a))
	tmp = 0
	if a <= -1.26e+78:
		tmp = t_1
	elif a <= -3.5e-224:
		tmp = z * ((y - x) / (a - t))
	elif a <= 2.25e-188:
		tmp = y + (x / (t / z))
	elif a <= 6.2e-53:
		tmp = y - (a / (t / x))
	elif a <= 7.2e-19:
		tmp = t_1
	elif a <= 7.5e+20:
		tmp = y * ((z - t) / (a - t))
	else:
		tmp = x + (z / (a / y))
	return tmp

Julia

function code(x, y, z, t, a)
	t_1 = Float64(x + Float64(y * Float64(z / a)))
	tmp = 0.0
	if (a <= -1.26e+78)
		tmp = t_1;
	elseif (a <= -3.5e-224)
		tmp = Float64(z * Float64(Float64(y - x) / Float64(a - t)));
	elseif (a <= 2.25e-188)
		tmp = Float64(y + Float64(x / Float64(t / z)));
	elseif (a <= 6.2e-53)
		tmp = Float64(y - Float64(a / Float64(t / x)));
	elseif (a <= 7.2e-19)
		tmp = t_1;
	elseif (a <= 7.5e+20)
		tmp = Float64(y * Float64(Float64(z - t) / Float64(a - t)));
	else
		tmp = Float64(x + Float64(z / Float64(a / y)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	t_1 = x + (y * (z / a));
	tmp = 0.0;
	if (a <= -1.26e+78)
		tmp = t_1;
	elseif (a <= -3.5e-224)
		tmp = z * ((y - x) / (a - t));
	elseif (a <= 2.25e-188)
		tmp = y + (x / (t / z));
	elseif (a <= 6.2e-53)
		tmp = y - (a / (t / x));
	elseif (a <= 7.2e-19)
		tmp = t_1;
	elseif (a <= 7.5e+20)
		tmp = y * ((z - t) / (a - t));
	else
		tmp = x + (z / (a / y));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := Block[{t$95$1 = N[(x + N[(y * N[(z / a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -1.26e+78], t$95$1, If[LessEqual[a, -3.5e-224], N[(z * N[(N[(y - x), $MachinePrecision] / N[(a - t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 2.25e-188], N[(y + N[(x / N[(t / z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 6.2e-53], N[(y - N[(a / N[(t / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 7.2e-19], t$95$1, If[LessEqual[a, 7.5e+20], N[(y * N[(N[(z - t), $MachinePrecision] / N[(a - t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(x + N[(z / N[(a / y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]

Derivation

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

Alternative 8: 61.4% accurate, 0.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x + \left(y - x\right) \cdot \frac{z}{a}\\ \mathbf{if}\;a \leq -1.25 \cdot 10^{+78}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -7.6 \cdot 10^{-224}:\\ \;\;\;\;z \cdot \frac{y - x}{a - t}\\ \mathbf{elif}\;a \leq 2.25 \cdot 10^{-188}:\\ \;\;\;\;y + \frac{x}{\frac{t}{z}}\\ \mathbf{elif}\;a \leq 4.8 \cdot 10^{-53}:\\ \;\;\;\;y - \frac{a}{\frac{t}{x}}\\ \mathbf{elif}\;a \leq 3.9 \cdot 10^{-19}:\\ \;\;\;\;x + y \cdot \frac{z}{a}\\ \mathbf{elif}\;a \leq 5.8 \cdot 10^{+20}:\\ \;\;\;\;y \cdot \frac{z - t}{a - t}\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (let* ((t_1 (+ x (* (- y x) (/ z a)))))
   (if (<= a -1.25e+78)
     t_1
     (if (<= a -7.6e-224)
       (* z (/ (- y x) (- a t)))
       (if (<= a 2.25e-188)
         (+ y (/ x (/ t z)))
         (if (<= a 4.8e-53)
           (- y (/ a (/ t x)))
           (if (<= a 3.9e-19)
             (+ x (* y (/ z a)))
             (if (<= a 5.8e+20) (* y (/ (- z t) (- a t))) t_1))))))))

C

double code(double x, double y, double z, double t, double a) {
	double t_1 = x + ((y - x) * (z / a));
	double tmp;
	if (a <= -1.25e+78) {
		tmp = t_1;
	} else if (a <= -7.6e-224) {
		tmp = z * ((y - x) / (a - t));
	} else if (a <= 2.25e-188) {
		tmp = y + (x / (t / z));
	} else if (a <= 4.8e-53) {
		tmp = y - (a / (t / x));
	} else if (a <= 3.9e-19) {
		tmp = x + (y * (z / a));
	} else if (a <= 5.8e+20) {
		tmp = y * ((z - t) / (a - t));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a)
    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) :: t_1
    real(8) :: tmp
    t_1 = x + ((y - x) * (z / a))
    if (a <= (-1.25d+78)) then
        tmp = t_1
    else if (a <= (-7.6d-224)) then
        tmp = z * ((y - x) / (a - t))
    else if (a <= 2.25d-188) then
        tmp = y + (x / (t / z))
    else if (a <= 4.8d-53) then
        tmp = y - (a / (t / x))
    else if (a <= 3.9d-19) then
        tmp = x + (y * (z / a))
    else if (a <= 5.8d+20) then
        tmp = y * ((z - t) / (a - t))
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a) {
	double t_1 = x + ((y - x) * (z / a));
	double tmp;
	if (a <= -1.25e+78) {
		tmp = t_1;
	} else if (a <= -7.6e-224) {
		tmp = z * ((y - x) / (a - t));
	} else if (a <= 2.25e-188) {
		tmp = y + (x / (t / z));
	} else if (a <= 4.8e-53) {
		tmp = y - (a / (t / x));
	} else if (a <= 3.9e-19) {
		tmp = x + (y * (z / a));
	} else if (a <= 5.8e+20) {
		tmp = y * ((z - t) / (a - t));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	t_1 = x + ((y - x) * (z / a))
	tmp = 0
	if a <= -1.25e+78:
		tmp = t_1
	elif a <= -7.6e-224:
		tmp = z * ((y - x) / (a - t))
	elif a <= 2.25e-188:
		tmp = y + (x / (t / z))
	elif a <= 4.8e-53:
		tmp = y - (a / (t / x))
	elif a <= 3.9e-19:
		tmp = x + (y * (z / a))
	elif a <= 5.8e+20:
		tmp = y * ((z - t) / (a - t))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a)
	t_1 = Float64(x + Float64(Float64(y - x) * Float64(z / a)))
	tmp = 0.0
	if (a <= -1.25e+78)
		tmp = t_1;
	elseif (a <= -7.6e-224)
		tmp = Float64(z * Float64(Float64(y - x) / Float64(a - t)));
	elseif (a <= 2.25e-188)
		tmp = Float64(y + Float64(x / Float64(t / z)));
	elseif (a <= 4.8e-53)
		tmp = Float64(y - Float64(a / Float64(t / x)));
	elseif (a <= 3.9e-19)
		tmp = Float64(x + Float64(y * Float64(z / a)));
	elseif (a <= 5.8e+20)
		tmp = Float64(y * Float64(Float64(z - t) / Float64(a - t)));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	t_1 = x + ((y - x) * (z / a));
	tmp = 0.0;
	if (a <= -1.25e+78)
		tmp = t_1;
	elseif (a <= -7.6e-224)
		tmp = z * ((y - x) / (a - t));
	elseif (a <= 2.25e-188)
		tmp = y + (x / (t / z));
	elseif (a <= 4.8e-53)
		tmp = y - (a / (t / x));
	elseif (a <= 3.9e-19)
		tmp = x + (y * (z / a));
	elseif (a <= 5.8e+20)
		tmp = y * ((z - t) / (a - t));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := Block[{t$95$1 = N[(x + N[(N[(y - x), $MachinePrecision] * N[(z / a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -1.25e+78], t$95$1, If[LessEqual[a, -7.6e-224], N[(z * N[(N[(y - x), $MachinePrecision] / N[(a - t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 2.25e-188], N[(y + N[(x / N[(t / z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 4.8e-53], N[(y - N[(a / N[(t / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 3.9e-19], N[(x + N[(y * N[(z / a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 5.8e+20], N[(y * N[(N[(z - t), $MachinePrecision] / N[(a - t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]]

Derivation

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

Alternative 9: 61.1% accurate, 0.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;a \leq -1.26 \cdot 10^{+78}:\\ \;\;\;\;x + \left(y - x\right) \cdot \frac{z}{a}\\ \mathbf{elif}\;a \leq -3.8 \cdot 10^{-224}:\\ \;\;\;\;z \cdot \frac{y - x}{a - t}\\ \mathbf{elif}\;a \leq 2.25 \cdot 10^{-188}:\\ \;\;\;\;y + \frac{x}{\frac{t}{z}}\\ \mathbf{elif}\;a \leq 6.2 \cdot 10^{-53}:\\ \;\;\;\;y - \frac{a}{\frac{t}{x}}\\ \mathbf{elif}\;a \leq 7.6 \cdot 10^{-17}:\\ \;\;\;\;x + y \cdot \frac{z}{a}\\ \mathbf{elif}\;a \leq 5.6 \cdot 10^{+20}:\\ \;\;\;\;y \cdot \frac{z - t}{a - t}\\ \mathbf{else}:\\ \;\;\;\;x + \frac{z}{\frac{a}{y - x}}\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (if (<= a -1.26e+78)
   (+ x (* (- y x) (/ z a)))
   (if (<= a -3.8e-224)
     (* z (/ (- y x) (- a t)))
     (if (<= a 2.25e-188)
       (+ y (/ x (/ t z)))
       (if (<= a 6.2e-53)
         (- y (/ a (/ t x)))
         (if (<= a 7.6e-17)
           (+ x (* y (/ z a)))
           (if (<= a 5.6e+20)
             (* y (/ (- z t) (- a t)))
             (+ x (/ z (/ a (- y x)))))))))))

C

double code(double x, double y, double z, double t, double a) {
	double tmp;
	if (a <= -1.26e+78) {
		tmp = x + ((y - x) * (z / a));
	} else if (a <= -3.8e-224) {
		tmp = z * ((y - x) / (a - t));
	} else if (a <= 2.25e-188) {
		tmp = y + (x / (t / z));
	} else if (a <= 6.2e-53) {
		tmp = y - (a / (t / x));
	} else if (a <= 7.6e-17) {
		tmp = x + (y * (z / a));
	} else if (a <= 5.6e+20) {
		tmp = y * ((z - t) / (a - t));
	} else {
		tmp = x + (z / (a / (y - x)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a)
    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) :: tmp
    if (a <= (-1.26d+78)) then
        tmp = x + ((y - x) * (z / a))
    else if (a <= (-3.8d-224)) then
        tmp = z * ((y - x) / (a - t))
    else if (a <= 2.25d-188) then
        tmp = y + (x / (t / z))
    else if (a <= 6.2d-53) then
        tmp = y - (a / (t / x))
    else if (a <= 7.6d-17) then
        tmp = x + (y * (z / a))
    else if (a <= 5.6d+20) then
        tmp = y * ((z - t) / (a - t))
    else
        tmp = x + (z / (a / (y - x)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a) {
	double tmp;
	if (a <= -1.26e+78) {
		tmp = x + ((y - x) * (z / a));
	} else if (a <= -3.8e-224) {
		tmp = z * ((y - x) / (a - t));
	} else if (a <= 2.25e-188) {
		tmp = y + (x / (t / z));
	} else if (a <= 6.2e-53) {
		tmp = y - (a / (t / x));
	} else if (a <= 7.6e-17) {
		tmp = x + (y * (z / a));
	} else if (a <= 5.6e+20) {
		tmp = y * ((z - t) / (a - t));
	} else {
		tmp = x + (z / (a / (y - x)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	tmp = 0
	if a <= -1.26e+78:
		tmp = x + ((y - x) * (z / a))
	elif a <= -3.8e-224:
		tmp = z * ((y - x) / (a - t))
	elif a <= 2.25e-188:
		tmp = y + (x / (t / z))
	elif a <= 6.2e-53:
		tmp = y - (a / (t / x))
	elif a <= 7.6e-17:
		tmp = x + (y * (z / a))
	elif a <= 5.6e+20:
		tmp = y * ((z - t) / (a - t))
	else:
		tmp = x + (z / (a / (y - x)))
	return tmp

Julia

function code(x, y, z, t, a)
	tmp = 0.0
	if (a <= -1.26e+78)
		tmp = Float64(x + Float64(Float64(y - x) * Float64(z / a)));
	elseif (a <= -3.8e-224)
		tmp = Float64(z * Float64(Float64(y - x) / Float64(a - t)));
	elseif (a <= 2.25e-188)
		tmp = Float64(y + Float64(x / Float64(t / z)));
	elseif (a <= 6.2e-53)
		tmp = Float64(y - Float64(a / Float64(t / x)));
	elseif (a <= 7.6e-17)
		tmp = Float64(x + Float64(y * Float64(z / a)));
	elseif (a <= 5.6e+20)
		tmp = Float64(y * Float64(Float64(z - t) / Float64(a - t)));
	else
		tmp = Float64(x + Float64(z / Float64(a / Float64(y - x))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	tmp = 0.0;
	if (a <= -1.26e+78)
		tmp = x + ((y - x) * (z / a));
	elseif (a <= -3.8e-224)
		tmp = z * ((y - x) / (a - t));
	elseif (a <= 2.25e-188)
		tmp = y + (x / (t / z));
	elseif (a <= 6.2e-53)
		tmp = y - (a / (t / x));
	elseif (a <= 7.6e-17)
		tmp = x + (y * (z / a));
	elseif (a <= 5.6e+20)
		tmp = y * ((z - t) / (a - t));
	else
		tmp = x + (z / (a / (y - x)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := If[LessEqual[a, -1.26e+78], N[(x + N[(N[(y - x), $MachinePrecision] * N[(z / a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -3.8e-224], N[(z * N[(N[(y - x), $MachinePrecision] / N[(a - t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 2.25e-188], N[(y + N[(x / N[(t / z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 6.2e-53], N[(y - N[(a / N[(t / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 7.6e-17], N[(x + N[(y * N[(z / a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 5.6e+20], N[(y * N[(N[(z - t), $MachinePrecision] / N[(a - t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(x + N[(z / N[(a / N[(y - x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]

Derivation

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

Alternative 10: 71.2% accurate, 0.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y + \left(z - a\right) \cdot \frac{x}{t}\\ t_2 := x + \left(z - t\right) \cdot \frac{y - x}{a}\\ \mathbf{if}\;a \leq -3.6:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq -1.7 \cdot 10^{-93}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -1.75 \cdot 10^{-105}:\\ \;\;\;\;z \cdot \frac{y - x}{a - t}\\ \mathbf{elif}\;a \leq 5.2 \cdot 10^{-161}:\\ \;\;\;\;y + \frac{z \cdot \left(x - y\right)}{t}\\ \mathbf{elif}\;a \leq 8 \cdot 10^{-53}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (let* ((t_1 (+ y (* (- z a) (/ x t)))) (t_2 (+ x (* (- z t) (/ (- y x) a)))))
   (if (<= a -3.6)
     t_2
     (if (<= a -1.7e-93)
       t_1
       (if (<= a -1.75e-105)
         (* z (/ (- y x) (- a t)))
         (if (<= a 5.2e-161)
           (+ y (/ (* z (- x y)) t))
           (if (<= a 8e-53) t_1 t_2)))))))

C

double code(double x, double y, double z, double t, double a) {
	double t_1 = y + ((z - a) * (x / t));
	double t_2 = x + ((z - t) * ((y - x) / a));
	double tmp;
	if (a <= -3.6) {
		tmp = t_2;
	} else if (a <= -1.7e-93) {
		tmp = t_1;
	} else if (a <= -1.75e-105) {
		tmp = z * ((y - x) / (a - t));
	} else if (a <= 5.2e-161) {
		tmp = y + ((z * (x - y)) / t);
	} else if (a <= 8e-53) {
		tmp = t_1;
	} else {
		tmp = t_2;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a)
    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) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = y + ((z - a) * (x / t))
    t_2 = x + ((z - t) * ((y - x) / a))
    if (a <= (-3.6d0)) then
        tmp = t_2
    else if (a <= (-1.7d-93)) then
        tmp = t_1
    else if (a <= (-1.75d-105)) then
        tmp = z * ((y - x) / (a - t))
    else if (a <= 5.2d-161) then
        tmp = y + ((z * (x - y)) / t)
    else if (a <= 8d-53) then
        tmp = t_1
    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 t_1 = y + ((z - a) * (x / t));
	double t_2 = x + ((z - t) * ((y - x) / a));
	double tmp;
	if (a <= -3.6) {
		tmp = t_2;
	} else if (a <= -1.7e-93) {
		tmp = t_1;
	} else if (a <= -1.75e-105) {
		tmp = z * ((y - x) / (a - t));
	} else if (a <= 5.2e-161) {
		tmp = y + ((z * (x - y)) / t);
	} else if (a <= 8e-53) {
		tmp = t_1;
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	t_1 = y + ((z - a) * (x / t))
	t_2 = x + ((z - t) * ((y - x) / a))
	tmp = 0
	if a <= -3.6:
		tmp = t_2
	elif a <= -1.7e-93:
		tmp = t_1
	elif a <= -1.75e-105:
		tmp = z * ((y - x) / (a - t))
	elif a <= 5.2e-161:
		tmp = y + ((z * (x - y)) / t)
	elif a <= 8e-53:
		tmp = t_1
	else:
		tmp = t_2
	return tmp

Julia

function code(x, y, z, t, a)
	t_1 = Float64(y + Float64(Float64(z - a) * Float64(x / t)))
	t_2 = Float64(x + Float64(Float64(z - t) * Float64(Float64(y - x) / a)))
	tmp = 0.0
	if (a <= -3.6)
		tmp = t_2;
	elseif (a <= -1.7e-93)
		tmp = t_1;
	elseif (a <= -1.75e-105)
		tmp = Float64(z * Float64(Float64(y - x) / Float64(a - t)));
	elseif (a <= 5.2e-161)
		tmp = Float64(y + Float64(Float64(z * Float64(x - y)) / t));
	elseif (a <= 8e-53)
		tmp = t_1;
	else
		tmp = t_2;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	t_1 = y + ((z - a) * (x / t));
	t_2 = x + ((z - t) * ((y - x) / a));
	tmp = 0.0;
	if (a <= -3.6)
		tmp = t_2;
	elseif (a <= -1.7e-93)
		tmp = t_1;
	elseif (a <= -1.75e-105)
		tmp = z * ((y - x) / (a - t));
	elseif (a <= 5.2e-161)
		tmp = y + ((z * (x - y)) / t);
	elseif (a <= 8e-53)
		tmp = t_1;
	else
		tmp = t_2;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := Block[{t$95$1 = N[(y + N[(N[(z - a), $MachinePrecision] * N[(x / t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(x + N[(N[(z - t), $MachinePrecision] * N[(N[(y - x), $MachinePrecision] / a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -3.6], t$95$2, If[LessEqual[a, -1.7e-93], t$95$1, If[LessEqual[a, -1.75e-105], N[(z * N[(N[(y - x), $MachinePrecision] / N[(a - t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 5.2e-161], N[(y + N[(N[(z * N[(x - y), $MachinePrecision]), $MachinePrecision] / t), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 8e-53], t$95$1, t$95$2]]]]]]]

Derivation

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

Alternative 11: 71.3% accurate, 0.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y + \left(z - a\right) \cdot \frac{x}{t}\\ \mathbf{if}\;a \leq -3.7 \cdot 10^{-6}:\\ \;\;\;\;x + \left(z - t\right) \cdot \frac{y - x}{a}\\ \mathbf{elif}\;a \leq -2.2 \cdot 10^{-92}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -1.6 \cdot 10^{-113}:\\ \;\;\;\;z \cdot \frac{y - x}{a - t}\\ \mathbf{elif}\;a \leq 1.05 \cdot 10^{-160}:\\ \;\;\;\;y + \frac{z \cdot \left(x - y\right)}{t}\\ \mathbf{elif}\;a \leq 8 \cdot 10^{-53}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;x - \frac{t - z}{\frac{a}{y - x}}\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (let* ((t_1 (+ y (* (- z a) (/ x t)))))
   (if (<= a -3.7e-6)
     (+ x (* (- z t) (/ (- y x) a)))
     (if (<= a -2.2e-92)
       t_1
       (if (<= a -1.6e-113)
         (* z (/ (- y x) (- a t)))
         (if (<= a 1.05e-160)
           (+ y (/ (* z (- x y)) t))
           (if (<= a 8e-53) t_1 (- x (/ (- t z) (/ a (- y x)))))))))))

C

double code(double x, double y, double z, double t, double a) {
	double t_1 = y + ((z - a) * (x / t));
	double tmp;
	if (a <= -3.7e-6) {
		tmp = x + ((z - t) * ((y - x) / a));
	} else if (a <= -2.2e-92) {
		tmp = t_1;
	} else if (a <= -1.6e-113) {
		tmp = z * ((y - x) / (a - t));
	} else if (a <= 1.05e-160) {
		tmp = y + ((z * (x - y)) / t);
	} else if (a <= 8e-53) {
		tmp = t_1;
	} else {
		tmp = x - ((t - z) / (a / (y - x)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a)
    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) :: t_1
    real(8) :: tmp
    t_1 = y + ((z - a) * (x / t))
    if (a <= (-3.7d-6)) then
        tmp = x + ((z - t) * ((y - x) / a))
    else if (a <= (-2.2d-92)) then
        tmp = t_1
    else if (a <= (-1.6d-113)) then
        tmp = z * ((y - x) / (a - t))
    else if (a <= 1.05d-160) then
        tmp = y + ((z * (x - y)) / t)
    else if (a <= 8d-53) then
        tmp = t_1
    else
        tmp = x - ((t - z) / (a / (y - x)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a) {
	double t_1 = y + ((z - a) * (x / t));
	double tmp;
	if (a <= -3.7e-6) {
		tmp = x + ((z - t) * ((y - x) / a));
	} else if (a <= -2.2e-92) {
		tmp = t_1;
	} else if (a <= -1.6e-113) {
		tmp = z * ((y - x) / (a - t));
	} else if (a <= 1.05e-160) {
		tmp = y + ((z * (x - y)) / t);
	} else if (a <= 8e-53) {
		tmp = t_1;
	} else {
		tmp = x - ((t - z) / (a / (y - x)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	t_1 = y + ((z - a) * (x / t))
	tmp = 0
	if a <= -3.7e-6:
		tmp = x + ((z - t) * ((y - x) / a))
	elif a <= -2.2e-92:
		tmp = t_1
	elif a <= -1.6e-113:
		tmp = z * ((y - x) / (a - t))
	elif a <= 1.05e-160:
		tmp = y + ((z * (x - y)) / t)
	elif a <= 8e-53:
		tmp = t_1
	else:
		tmp = x - ((t - z) / (a / (y - x)))
	return tmp

Julia

function code(x, y, z, t, a)
	t_1 = Float64(y + Float64(Float64(z - a) * Float64(x / t)))
	tmp = 0.0
	if (a <= -3.7e-6)
		tmp = Float64(x + Float64(Float64(z - t) * Float64(Float64(y - x) / a)));
	elseif (a <= -2.2e-92)
		tmp = t_1;
	elseif (a <= -1.6e-113)
		tmp = Float64(z * Float64(Float64(y - x) / Float64(a - t)));
	elseif (a <= 1.05e-160)
		tmp = Float64(y + Float64(Float64(z * Float64(x - y)) / t));
	elseif (a <= 8e-53)
		tmp = t_1;
	else
		tmp = Float64(x - Float64(Float64(t - z) / Float64(a / Float64(y - x))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	t_1 = y + ((z - a) * (x / t));
	tmp = 0.0;
	if (a <= -3.7e-6)
		tmp = x + ((z - t) * ((y - x) / a));
	elseif (a <= -2.2e-92)
		tmp = t_1;
	elseif (a <= -1.6e-113)
		tmp = z * ((y - x) / (a - t));
	elseif (a <= 1.05e-160)
		tmp = y + ((z * (x - y)) / t);
	elseif (a <= 8e-53)
		tmp = t_1;
	else
		tmp = x - ((t - z) / (a / (y - x)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := Block[{t$95$1 = N[(y + N[(N[(z - a), $MachinePrecision] * N[(x / t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -3.7e-6], N[(x + N[(N[(z - t), $MachinePrecision] * N[(N[(y - x), $MachinePrecision] / a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -2.2e-92], t$95$1, If[LessEqual[a, -1.6e-113], N[(z * N[(N[(y - x), $MachinePrecision] / N[(a - t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 1.05e-160], N[(y + N[(N[(z * N[(x - y), $MachinePrecision]), $MachinePrecision] / t), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 8e-53], t$95$1, N[(x - N[(N[(t - z), $MachinePrecision] / N[(a / N[(y - x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]

Derivation

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

Alternative 12: 71.8% accurate, 0.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x + \left(z - t\right) \cdot \frac{y - x}{a}\\ \mathbf{if}\;a \leq -1.8 \cdot 10^{-42}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 8 \cdot 10^{-53}:\\ \;\;\;\;y + \frac{\left(y - x\right) \cdot \left(a - z\right)}{t}\\ \mathbf{elif}\;a \leq 1.5 \cdot 10^{-18}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 14200000:\\ \;\;\;\;y \cdot \frac{z - t}{a - t}\\ \mathbf{elif}\;a \leq 3.1 \cdot 10^{+99}:\\ \;\;\;\;x - \frac{t}{\frac{a - t}{y - x}}\\ \mathbf{else}:\\ \;\;\;\;x - \frac{t - z}{\frac{a}{y - x}}\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (let* ((t_1 (+ x (* (- z t) (/ (- y x) a)))))
   (if (<= a -1.8e-42)
     t_1
     (if (<= a 8e-53)
       (+ y (/ (* (- y x) (- a z)) t))
       (if (<= a 1.5e-18)
         t_1
         (if (<= a 14200000.0)
           (* y (/ (- z t) (- a t)))
           (if (<= a 3.1e+99)
             (- x (/ t (/ (- a t) (- y x))))
             (- x (/ (- t z) (/ a (- y x)))))))))))

C

double code(double x, double y, double z, double t, double a) {
	double t_1 = x + ((z - t) * ((y - x) / a));
	double tmp;
	if (a <= -1.8e-42) {
		tmp = t_1;
	} else if (a <= 8e-53) {
		tmp = y + (((y - x) * (a - z)) / t);
	} else if (a <= 1.5e-18) {
		tmp = t_1;
	} else if (a <= 14200000.0) {
		tmp = y * ((z - t) / (a - t));
	} else if (a <= 3.1e+99) {
		tmp = x - (t / ((a - t) / (y - x)));
	} else {
		tmp = x - ((t - z) / (a / (y - x)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a)
    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) :: t_1
    real(8) :: tmp
    t_1 = x + ((z - t) * ((y - x) / a))
    if (a <= (-1.8d-42)) then
        tmp = t_1
    else if (a <= 8d-53) then
        tmp = y + (((y - x) * (a - z)) / t)
    else if (a <= 1.5d-18) then
        tmp = t_1
    else if (a <= 14200000.0d0) then
        tmp = y * ((z - t) / (a - t))
    else if (a <= 3.1d+99) then
        tmp = x - (t / ((a - t) / (y - x)))
    else
        tmp = x - ((t - z) / (a / (y - x)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a) {
	double t_1 = x + ((z - t) * ((y - x) / a));
	double tmp;
	if (a <= -1.8e-42) {
		tmp = t_1;
	} else if (a <= 8e-53) {
		tmp = y + (((y - x) * (a - z)) / t);
	} else if (a <= 1.5e-18) {
		tmp = t_1;
	} else if (a <= 14200000.0) {
		tmp = y * ((z - t) / (a - t));
	} else if (a <= 3.1e+99) {
		tmp = x - (t / ((a - t) / (y - x)));
	} else {
		tmp = x - ((t - z) / (a / (y - x)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	t_1 = x + ((z - t) * ((y - x) / a))
	tmp = 0
	if a <= -1.8e-42:
		tmp = t_1
	elif a <= 8e-53:
		tmp = y + (((y - x) * (a - z)) / t)
	elif a <= 1.5e-18:
		tmp = t_1
	elif a <= 14200000.0:
		tmp = y * ((z - t) / (a - t))
	elif a <= 3.1e+99:
		tmp = x - (t / ((a - t) / (y - x)))
	else:
		tmp = x - ((t - z) / (a / (y - x)))
	return tmp

Julia

function code(x, y, z, t, a)
	t_1 = Float64(x + Float64(Float64(z - t) * Float64(Float64(y - x) / a)))
	tmp = 0.0
	if (a <= -1.8e-42)
		tmp = t_1;
	elseif (a <= 8e-53)
		tmp = Float64(y + Float64(Float64(Float64(y - x) * Float64(a - z)) / t));
	elseif (a <= 1.5e-18)
		tmp = t_1;
	elseif (a <= 14200000.0)
		tmp = Float64(y * Float64(Float64(z - t) / Float64(a - t)));
	elseif (a <= 3.1e+99)
		tmp = Float64(x - Float64(t / Float64(Float64(a - t) / Float64(y - x))));
	else
		tmp = Float64(x - Float64(Float64(t - z) / Float64(a / Float64(y - x))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	t_1 = x + ((z - t) * ((y - x) / a));
	tmp = 0.0;
	if (a <= -1.8e-42)
		tmp = t_1;
	elseif (a <= 8e-53)
		tmp = y + (((y - x) * (a - z)) / t);
	elseif (a <= 1.5e-18)
		tmp = t_1;
	elseif (a <= 14200000.0)
		tmp = y * ((z - t) / (a - t));
	elseif (a <= 3.1e+99)
		tmp = x - (t / ((a - t) / (y - x)));
	else
		tmp = x - ((t - z) / (a / (y - x)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := Block[{t$95$1 = N[(x + N[(N[(z - t), $MachinePrecision] * N[(N[(y - x), $MachinePrecision] / a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -1.8e-42], t$95$1, If[LessEqual[a, 8e-53], N[(y + N[(N[(N[(y - x), $MachinePrecision] * N[(a - z), $MachinePrecision]), $MachinePrecision] / t), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 1.5e-18], t$95$1, If[LessEqual[a, 14200000.0], N[(y * N[(N[(z - t), $MachinePrecision] / N[(a - t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 3.1e+99], N[(x - N[(t / N[(N[(a - t), $MachinePrecision] / N[(y - x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(x - N[(N[(t - z), $MachinePrecision] / N[(a / N[(y - x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]

Derivation

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

Alternative 13: 40.1% accurate, 0.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(1 - \frac{z}{a}\right)\\ t_2 := \left(z - a\right) \cdot \frac{x}{t}\\ \mathbf{if}\;a \leq -4 \cdot 10^{+62}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -8.2 \cdot 10^{-41}:\\ \;\;\;\;z \cdot \frac{y}{a}\\ \mathbf{elif}\;a \leq -1.38 \cdot 10^{-115}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -9.5 \cdot 10^{-273}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq 1.15 \cdot 10^{-228}:\\ \;\;\;\;y\\ \mathbf{elif}\;a \leq 5.5 \cdot 10^{-53}:\\ \;\;\;\;t_2\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (let* ((t_1 (* x (- 1.0 (/ z a)))) (t_2 (* (- z a) (/ x t))))
   (if (<= a -4e+62)
     t_1
     (if (<= a -8.2e-41)
       (* z (/ y a))
       (if (<= a -1.38e-115)
         t_1
         (if (<= a -9.5e-273)
           t_2
           (if (<= a 1.15e-228) y (if (<= a 5.5e-53) t_2 t_1))))))))

C

double code(double x, double y, double z, double t, double a) {
	double t_1 = x * (1.0 - (z / a));
	double t_2 = (z - a) * (x / t);
	double tmp;
	if (a <= -4e+62) {
		tmp = t_1;
	} else if (a <= -8.2e-41) {
		tmp = z * (y / a);
	} else if (a <= -1.38e-115) {
		tmp = t_1;
	} else if (a <= -9.5e-273) {
		tmp = t_2;
	} else if (a <= 1.15e-228) {
		tmp = y;
	} else if (a <= 5.5e-53) {
		tmp = t_2;
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a)
    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) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = x * (1.0d0 - (z / a))
    t_2 = (z - a) * (x / t)
    if (a <= (-4d+62)) then
        tmp = t_1
    else if (a <= (-8.2d-41)) then
        tmp = z * (y / a)
    else if (a <= (-1.38d-115)) then
        tmp = t_1
    else if (a <= (-9.5d-273)) then
        tmp = t_2
    else if (a <= 1.15d-228) then
        tmp = y
    else if (a <= 5.5d-53) then
        tmp = t_2
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a) {
	double t_1 = x * (1.0 - (z / a));
	double t_2 = (z - a) * (x / t);
	double tmp;
	if (a <= -4e+62) {
		tmp = t_1;
	} else if (a <= -8.2e-41) {
		tmp = z * (y / a);
	} else if (a <= -1.38e-115) {
		tmp = t_1;
	} else if (a <= -9.5e-273) {
		tmp = t_2;
	} else if (a <= 1.15e-228) {
		tmp = y;
	} else if (a <= 5.5e-53) {
		tmp = t_2;
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	t_1 = x * (1.0 - (z / a))
	t_2 = (z - a) * (x / t)
	tmp = 0
	if a <= -4e+62:
		tmp = t_1
	elif a <= -8.2e-41:
		tmp = z * (y / a)
	elif a <= -1.38e-115:
		tmp = t_1
	elif a <= -9.5e-273:
		tmp = t_2
	elif a <= 1.15e-228:
		tmp = y
	elif a <= 5.5e-53:
		tmp = t_2
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a)
	t_1 = Float64(x * Float64(1.0 - Float64(z / a)))
	t_2 = Float64(Float64(z - a) * Float64(x / t))
	tmp = 0.0
	if (a <= -4e+62)
		tmp = t_1;
	elseif (a <= -8.2e-41)
		tmp = Float64(z * Float64(y / a));
	elseif (a <= -1.38e-115)
		tmp = t_1;
	elseif (a <= -9.5e-273)
		tmp = t_2;
	elseif (a <= 1.15e-228)
		tmp = y;
	elseif (a <= 5.5e-53)
		tmp = t_2;
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	t_1 = x * (1.0 - (z / a));
	t_2 = (z - a) * (x / t);
	tmp = 0.0;
	if (a <= -4e+62)
		tmp = t_1;
	elseif (a <= -8.2e-41)
		tmp = z * (y / a);
	elseif (a <= -1.38e-115)
		tmp = t_1;
	elseif (a <= -9.5e-273)
		tmp = t_2;
	elseif (a <= 1.15e-228)
		tmp = y;
	elseif (a <= 5.5e-53)
		tmp = t_2;
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := Block[{t$95$1 = N[(x * N[(1.0 - N[(z / a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(z - a), $MachinePrecision] * N[(x / t), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -4e+62], t$95$1, If[LessEqual[a, -8.2e-41], N[(z * N[(y / a), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -1.38e-115], t$95$1, If[LessEqual[a, -9.5e-273], t$95$2, If[LessEqual[a, 1.15e-228], y, If[LessEqual[a, 5.5e-53], t$95$2, t$95$1]]]]]]]]

Derivation

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

Alternative 14: 62.9% accurate, 0.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;a \leq -1.25 \cdot 10^{+78}:\\ \;\;\;\;x + \left(y - x\right) \cdot \frac{z}{a}\\ \mathbf{elif}\;a \leq -1.65 \cdot 10^{-230}:\\ \;\;\;\;z \cdot \frac{y - x}{a - t}\\ \mathbf{elif}\;a \leq 8 \cdot 10^{-53}:\\ \;\;\;\;y + \left(z - a\right) \cdot \frac{x}{t}\\ \mathbf{elif}\;a \leq 3.9 \cdot 10^{-19}:\\ \;\;\;\;x + y \cdot \frac{z}{a}\\ \mathbf{elif}\;a \leq 5.5 \cdot 10^{+20}:\\ \;\;\;\;y \cdot \frac{z - t}{a - t}\\ \mathbf{else}:\\ \;\;\;\;x + \frac{z}{\frac{a}{y - x}}\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (if (<= a -1.25e+78)
   (+ x (* (- y x) (/ z a)))
   (if (<= a -1.65e-230)
     (* z (/ (- y x) (- a t)))
     (if (<= a 8e-53)
       (+ y (* (- z a) (/ x t)))
       (if (<= a 3.9e-19)
         (+ x (* y (/ z a)))
         (if (<= a 5.5e+20)
           (* y (/ (- z t) (- a t)))
           (+ x (/ z (/ a (- y x))))))))))

C

double code(double x, double y, double z, double t, double a) {
	double tmp;
	if (a <= -1.25e+78) {
		tmp = x + ((y - x) * (z / a));
	} else if (a <= -1.65e-230) {
		tmp = z * ((y - x) / (a - t));
	} else if (a <= 8e-53) {
		tmp = y + ((z - a) * (x / t));
	} else if (a <= 3.9e-19) {
		tmp = x + (y * (z / a));
	} else if (a <= 5.5e+20) {
		tmp = y * ((z - t) / (a - t));
	} else {
		tmp = x + (z / (a / (y - x)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a)
    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) :: tmp
    if (a <= (-1.25d+78)) then
        tmp = x + ((y - x) * (z / a))
    else if (a <= (-1.65d-230)) then
        tmp = z * ((y - x) / (a - t))
    else if (a <= 8d-53) then
        tmp = y + ((z - a) * (x / t))
    else if (a <= 3.9d-19) then
        tmp = x + (y * (z / a))
    else if (a <= 5.5d+20) then
        tmp = y * ((z - t) / (a - t))
    else
        tmp = x + (z / (a / (y - x)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a) {
	double tmp;
	if (a <= -1.25e+78) {
		tmp = x + ((y - x) * (z / a));
	} else if (a <= -1.65e-230) {
		tmp = z * ((y - x) / (a - t));
	} else if (a <= 8e-53) {
		tmp = y + ((z - a) * (x / t));
	} else if (a <= 3.9e-19) {
		tmp = x + (y * (z / a));
	} else if (a <= 5.5e+20) {
		tmp = y * ((z - t) / (a - t));
	} else {
		tmp = x + (z / (a / (y - x)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	tmp = 0
	if a <= -1.25e+78:
		tmp = x + ((y - x) * (z / a))
	elif a <= -1.65e-230:
		tmp = z * ((y - x) / (a - t))
	elif a <= 8e-53:
		tmp = y + ((z - a) * (x / t))
	elif a <= 3.9e-19:
		tmp = x + (y * (z / a))
	elif a <= 5.5e+20:
		tmp = y * ((z - t) / (a - t))
	else:
		tmp = x + (z / (a / (y - x)))
	return tmp

Julia

function code(x, y, z, t, a)
	tmp = 0.0
	if (a <= -1.25e+78)
		tmp = Float64(x + Float64(Float64(y - x) * Float64(z / a)));
	elseif (a <= -1.65e-230)
		tmp = Float64(z * Float64(Float64(y - x) / Float64(a - t)));
	elseif (a <= 8e-53)
		tmp = Float64(y + Float64(Float64(z - a) * Float64(x / t)));
	elseif (a <= 3.9e-19)
		tmp = Float64(x + Float64(y * Float64(z / a)));
	elseif (a <= 5.5e+20)
		tmp = Float64(y * Float64(Float64(z - t) / Float64(a - t)));
	else
		tmp = Float64(x + Float64(z / Float64(a / Float64(y - x))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	tmp = 0.0;
	if (a <= -1.25e+78)
		tmp = x + ((y - x) * (z / a));
	elseif (a <= -1.65e-230)
		tmp = z * ((y - x) / (a - t));
	elseif (a <= 8e-53)
		tmp = y + ((z - a) * (x / t));
	elseif (a <= 3.9e-19)
		tmp = x + (y * (z / a));
	elseif (a <= 5.5e+20)
		tmp = y * ((z - t) / (a - t));
	else
		tmp = x + (z / (a / (y - x)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := If[LessEqual[a, -1.25e+78], N[(x + N[(N[(y - x), $MachinePrecision] * N[(z / a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -1.65e-230], N[(z * N[(N[(y - x), $MachinePrecision] / N[(a - t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 8e-53], N[(y + N[(N[(z - a), $MachinePrecision] * N[(x / t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 3.9e-19], N[(x + N[(y * N[(z / a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 5.5e+20], N[(y * N[(N[(z - t), $MachinePrecision] / N[(a - t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(x + N[(z / N[(a / N[(y - x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

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

Alternative 15: 69.1% accurate, 0.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;a \leq -1.42 \cdot 10^{-42}:\\ \;\;\;\;x + \left(y - x\right) \cdot \frac{z}{a}\\ \mathbf{elif}\;a \leq 8.5 \cdot 10^{-163}:\\ \;\;\;\;y - \frac{z}{\frac{t}{y - x}}\\ \mathbf{elif}\;a \leq 8 \cdot 10^{-53}:\\ \;\;\;\;y + \left(z - a\right) \cdot \frac{x}{t}\\ \mathbf{elif}\;a \leq 7.2 \cdot 10^{-19}:\\ \;\;\;\;x + y \cdot \frac{z}{a}\\ \mathbf{elif}\;a \leq 7.5 \cdot 10^{+20}:\\ \;\;\;\;y \cdot \frac{z - t}{a - t}\\ \mathbf{else}:\\ \;\;\;\;x + \frac{z}{\frac{a}{y - x}}\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (if (<= a -1.42e-42)
   (+ x (* (- y x) (/ z a)))
   (if (<= a 8.5e-163)
     (- y (/ z (/ t (- y x))))
     (if (<= a 8e-53)
       (+ y (* (- z a) (/ x t)))
       (if (<= a 7.2e-19)
         (+ x (* y (/ z a)))
         (if (<= a 7.5e+20)
           (* y (/ (- z t) (- a t)))
           (+ x (/ z (/ a (- y x))))))))))

C

double code(double x, double y, double z, double t, double a) {
	double tmp;
	if (a <= -1.42e-42) {
		tmp = x + ((y - x) * (z / a));
	} else if (a <= 8.5e-163) {
		tmp = y - (z / (t / (y - x)));
	} else if (a <= 8e-53) {
		tmp = y + ((z - a) * (x / t));
	} else if (a <= 7.2e-19) {
		tmp = x + (y * (z / a));
	} else if (a <= 7.5e+20) {
		tmp = y * ((z - t) / (a - t));
	} else {
		tmp = x + (z / (a / (y - x)));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a)
    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) :: tmp
    if (a <= (-1.42d-42)) then
        tmp = x + ((y - x) * (z / a))
    else if (a <= 8.5d-163) then
        tmp = y - (z / (t / (y - x)))
    else if (a <= 8d-53) then
        tmp = y + ((z - a) * (x / t))
    else if (a <= 7.2d-19) then
        tmp = x + (y * (z / a))
    else if (a <= 7.5d+20) then
        tmp = y * ((z - t) / (a - t))
    else
        tmp = x + (z / (a / (y - x)))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a) {
	double tmp;
	if (a <= -1.42e-42) {
		tmp = x + ((y - x) * (z / a));
	} else if (a <= 8.5e-163) {
		tmp = y - (z / (t / (y - x)));
	} else if (a <= 8e-53) {
		tmp = y + ((z - a) * (x / t));
	} else if (a <= 7.2e-19) {
		tmp = x + (y * (z / a));
	} else if (a <= 7.5e+20) {
		tmp = y * ((z - t) / (a - t));
	} else {
		tmp = x + (z / (a / (y - x)));
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	tmp = 0
	if a <= -1.42e-42:
		tmp = x + ((y - x) * (z / a))
	elif a <= 8.5e-163:
		tmp = y - (z / (t / (y - x)))
	elif a <= 8e-53:
		tmp = y + ((z - a) * (x / t))
	elif a <= 7.2e-19:
		tmp = x + (y * (z / a))
	elif a <= 7.5e+20:
		tmp = y * ((z - t) / (a - t))
	else:
		tmp = x + (z / (a / (y - x)))
	return tmp

Julia

function code(x, y, z, t, a)
	tmp = 0.0
	if (a <= -1.42e-42)
		tmp = Float64(x + Float64(Float64(y - x) * Float64(z / a)));
	elseif (a <= 8.5e-163)
		tmp = Float64(y - Float64(z / Float64(t / Float64(y - x))));
	elseif (a <= 8e-53)
		tmp = Float64(y + Float64(Float64(z - a) * Float64(x / t)));
	elseif (a <= 7.2e-19)
		tmp = Float64(x + Float64(y * Float64(z / a)));
	elseif (a <= 7.5e+20)
		tmp = Float64(y * Float64(Float64(z - t) / Float64(a - t)));
	else
		tmp = Float64(x + Float64(z / Float64(a / Float64(y - x))));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	tmp = 0.0;
	if (a <= -1.42e-42)
		tmp = x + ((y - x) * (z / a));
	elseif (a <= 8.5e-163)
		tmp = y - (z / (t / (y - x)));
	elseif (a <= 8e-53)
		tmp = y + ((z - a) * (x / t));
	elseif (a <= 7.2e-19)
		tmp = x + (y * (z / a));
	elseif (a <= 7.5e+20)
		tmp = y * ((z - t) / (a - t));
	else
		tmp = x + (z / (a / (y - x)));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := If[LessEqual[a, -1.42e-42], N[(x + N[(N[(y - x), $MachinePrecision] * N[(z / a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 8.5e-163], N[(y - N[(z / N[(t / N[(y - x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 8e-53], N[(y + N[(N[(z - a), $MachinePrecision] * N[(x / t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 7.2e-19], N[(x + N[(y * N[(z / a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 7.5e+20], N[(y * N[(N[(z - t), $MachinePrecision] / N[(a - t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(x + N[(z / N[(a / N[(y - x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

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

Alternative 16: 82.4% accurate, 0.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;a \leq -1.4 \cdot 10^{-111} \lor \neg \left(a \leq 5 \cdot 10^{-53}\right):\\ \;\;\;\;x + \left(z - t\right) \cdot \frac{y - x}{a - t}\\ \mathbf{else}:\\ \;\;\;\;y + \frac{\left(y - x\right) \cdot \left(a - z\right)}{t}\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (if (or (<= a -1.4e-111) (not (<= a 5e-53)))
   (+ x (* (- z t) (/ (- y x) (- a t))))
   (+ y (/ (* (- y x) (- a z)) t))))

C

double code(double x, double y, double z, double t, double a) {
	double tmp;
	if ((a <= -1.4e-111) || !(a <= 5e-53)) {
		tmp = x + ((z - t) * ((y - x) / (a - t)));
	} else {
		tmp = y + (((y - x) * (a - z)) / t);
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a)
    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) :: tmp
    if ((a <= (-1.4d-111)) .or. (.not. (a <= 5d-53))) then
        tmp = x + ((z - t) * ((y - x) / (a - t)))
    else
        tmp = y + (((y - x) * (a - z)) / t)
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a) {
	double tmp;
	if ((a <= -1.4e-111) || !(a <= 5e-53)) {
		tmp = x + ((z - t) * ((y - x) / (a - t)));
	} else {
		tmp = y + (((y - x) * (a - z)) / t);
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	tmp = 0
	if (a <= -1.4e-111) or not (a <= 5e-53):
		tmp = x + ((z - t) * ((y - x) / (a - t)))
	else:
		tmp = y + (((y - x) * (a - z)) / t)
	return tmp

Julia

function code(x, y, z, t, a)
	tmp = 0.0
	if ((a <= -1.4e-111) || !(a <= 5e-53))
		tmp = Float64(x + Float64(Float64(z - t) * Float64(Float64(y - x) / Float64(a - t))));
	else
		tmp = Float64(y + Float64(Float64(Float64(y - x) * Float64(a - z)) / t));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	tmp = 0.0;
	if ((a <= -1.4e-111) || ~((a <= 5e-53)))
		tmp = x + ((z - t) * ((y - x) / (a - t)));
	else
		tmp = y + (((y - x) * (a - z)) / t);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := If[Or[LessEqual[a, -1.4e-111], N[Not[LessEqual[a, 5e-53]], $MachinePrecision]], N[(x + N[(N[(z - t), $MachinePrecision] * N[(N[(y - x), $MachinePrecision] / N[(a - t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(y + N[(N[(N[(y - x), $MachinePrecision] * N[(a - z), $MachinePrecision]), $MachinePrecision] / t), $MachinePrecision]), $MachinePrecision]]

Derivation

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

Alternative 17: 37.8% accurate, 0.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := z \cdot \frac{y}{a}\\ \mathbf{if}\;a \leq -4.3 \cdot 10^{+74}:\\ \;\;\;\;x\\ \mathbf{elif}\;a \leq -2.2 \cdot 10^{-18}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 6.2 \cdot 10^{-53}:\\ \;\;\;\;y\\ \mathbf{elif}\;a \leq 2.9 \cdot 10^{+184}:\\ \;\;\;\;x\\ \mathbf{elif}\;a \leq 2.95 \cdot 10^{+212}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;x\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (let* ((t_1 (* z (/ y a))))
   (if (<= a -4.3e+74)
     x
     (if (<= a -2.2e-18)
       t_1
       (if (<= a 6.2e-53)
         y
         (if (<= a 2.9e+184) x (if (<= a 2.95e+212) t_1 x)))))))

C

double code(double x, double y, double z, double t, double a) {
	double t_1 = z * (y / a);
	double tmp;
	if (a <= -4.3e+74) {
		tmp = x;
	} else if (a <= -2.2e-18) {
		tmp = t_1;
	} else if (a <= 6.2e-53) {
		tmp = y;
	} else if (a <= 2.9e+184) {
		tmp = x;
	} else if (a <= 2.95e+212) {
		tmp = t_1;
	} else {
		tmp = x;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a)
    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) :: t_1
    real(8) :: tmp
    t_1 = z * (y / a)
    if (a <= (-4.3d+74)) then
        tmp = x
    else if (a <= (-2.2d-18)) then
        tmp = t_1
    else if (a <= 6.2d-53) then
        tmp = y
    else if (a <= 2.9d+184) then
        tmp = x
    else if (a <= 2.95d+212) then
        tmp = t_1
    else
        tmp = x
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a) {
	double t_1 = z * (y / a);
	double tmp;
	if (a <= -4.3e+74) {
		tmp = x;
	} else if (a <= -2.2e-18) {
		tmp = t_1;
	} else if (a <= 6.2e-53) {
		tmp = y;
	} else if (a <= 2.9e+184) {
		tmp = x;
	} else if (a <= 2.95e+212) {
		tmp = t_1;
	} else {
		tmp = x;
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	t_1 = z * (y / a)
	tmp = 0
	if a <= -4.3e+74:
		tmp = x
	elif a <= -2.2e-18:
		tmp = t_1
	elif a <= 6.2e-53:
		tmp = y
	elif a <= 2.9e+184:
		tmp = x
	elif a <= 2.95e+212:
		tmp = t_1
	else:
		tmp = x
	return tmp

Julia

function code(x, y, z, t, a)
	t_1 = Float64(z * Float64(y / a))
	tmp = 0.0
	if (a <= -4.3e+74)
		tmp = x;
	elseif (a <= -2.2e-18)
		tmp = t_1;
	elseif (a <= 6.2e-53)
		tmp = y;
	elseif (a <= 2.9e+184)
		tmp = x;
	elseif (a <= 2.95e+212)
		tmp = t_1;
	else
		tmp = x;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	t_1 = z * (y / a);
	tmp = 0.0;
	if (a <= -4.3e+74)
		tmp = x;
	elseif (a <= -2.2e-18)
		tmp = t_1;
	elseif (a <= 6.2e-53)
		tmp = y;
	elseif (a <= 2.9e+184)
		tmp = x;
	elseif (a <= 2.95e+212)
		tmp = t_1;
	else
		tmp = x;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := Block[{t$95$1 = N[(z * N[(y / a), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -4.3e+74], x, If[LessEqual[a, -2.2e-18], t$95$1, If[LessEqual[a, 6.2e-53], y, If[LessEqual[a, 2.9e+184], x, If[LessEqual[a, 2.95e+212], t$95$1, x]]]]]]

Derivation

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

Alternative 18: 45.7% accurate, 0.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \left(z - a\right) \cdot \frac{x}{t}\\ t_2 := x + y \cdot \frac{z}{a}\\ \mathbf{if}\;a \leq -1.8 \cdot 10^{-25}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq -2.5 \cdot 10^{-273}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 4.2 \cdot 10^{-229}:\\ \;\;\;\;y\\ \mathbf{elif}\;a \leq 5.2 \cdot 10^{-53}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (let* ((t_1 (* (- z a) (/ x t))) (t_2 (+ x (* y (/ z a)))))
   (if (<= a -1.8e-25)
     t_2
     (if (<= a -2.5e-273)
       t_1
       (if (<= a 4.2e-229) y (if (<= a 5.2e-53) t_1 t_2))))))

C

double code(double x, double y, double z, double t, double a) {
	double t_1 = (z - a) * (x / t);
	double t_2 = x + (y * (z / a));
	double tmp;
	if (a <= -1.8e-25) {
		tmp = t_2;
	} else if (a <= -2.5e-273) {
		tmp = t_1;
	} else if (a <= 4.2e-229) {
		tmp = y;
	} else if (a <= 5.2e-53) {
		tmp = t_1;
	} else {
		tmp = t_2;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a)
    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) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = (z - a) * (x / t)
    t_2 = x + (y * (z / a))
    if (a <= (-1.8d-25)) then
        tmp = t_2
    else if (a <= (-2.5d-273)) then
        tmp = t_1
    else if (a <= 4.2d-229) then
        tmp = y
    else if (a <= 5.2d-53) then
        tmp = t_1
    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 t_1 = (z - a) * (x / t);
	double t_2 = x + (y * (z / a));
	double tmp;
	if (a <= -1.8e-25) {
		tmp = t_2;
	} else if (a <= -2.5e-273) {
		tmp = t_1;
	} else if (a <= 4.2e-229) {
		tmp = y;
	} else if (a <= 5.2e-53) {
		tmp = t_1;
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	t_1 = (z - a) * (x / t)
	t_2 = x + (y * (z / a))
	tmp = 0
	if a <= -1.8e-25:
		tmp = t_2
	elif a <= -2.5e-273:
		tmp = t_1
	elif a <= 4.2e-229:
		tmp = y
	elif a <= 5.2e-53:
		tmp = t_1
	else:
		tmp = t_2
	return tmp

Julia

function code(x, y, z, t, a)
	t_1 = Float64(Float64(z - a) * Float64(x / t))
	t_2 = Float64(x + Float64(y * Float64(z / a)))
	tmp = 0.0
	if (a <= -1.8e-25)
		tmp = t_2;
	elseif (a <= -2.5e-273)
		tmp = t_1;
	elseif (a <= 4.2e-229)
		tmp = y;
	elseif (a <= 5.2e-53)
		tmp = t_1;
	else
		tmp = t_2;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	t_1 = (z - a) * (x / t);
	t_2 = x + (y * (z / a));
	tmp = 0.0;
	if (a <= -1.8e-25)
		tmp = t_2;
	elseif (a <= -2.5e-273)
		tmp = t_1;
	elseif (a <= 4.2e-229)
		tmp = y;
	elseif (a <= 5.2e-53)
		tmp = t_1;
	else
		tmp = t_2;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := Block[{t$95$1 = N[(N[(z - a), $MachinePrecision] * N[(x / t), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(x + N[(y * N[(z / a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -1.8e-25], t$95$2, If[LessEqual[a, -2.5e-273], t$95$1, If[LessEqual[a, 4.2e-229], y, If[LessEqual[a, 5.2e-53], t$95$1, t$95$2]]]]]]

Derivation

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

Alternative 19: 45.8% accurate, 0.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \left(z - a\right) \cdot \frac{x}{t}\\ \mathbf{if}\;a \leq -7 \cdot 10^{-32}:\\ \;\;\;\;x + \frac{y}{\frac{a}{z}}\\ \mathbf{elif}\;a \leq -2.4 \cdot 10^{-272}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 9.6 \cdot 10^{-229}:\\ \;\;\;\;y\\ \mathbf{elif}\;a \leq 5 \cdot 10^{-53}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;x + y \cdot \frac{z}{a}\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (let* ((t_1 (* (- z a) (/ x t))))
   (if (<= a -7e-32)
     (+ x (/ y (/ a z)))
     (if (<= a -2.4e-272)
       t_1
       (if (<= a 9.6e-229) y (if (<= a 5e-53) t_1 (+ x (* y (/ z a)))))))))

C

double code(double x, double y, double z, double t, double a) {
	double t_1 = (z - a) * (x / t);
	double tmp;
	if (a <= -7e-32) {
		tmp = x + (y / (a / z));
	} else if (a <= -2.4e-272) {
		tmp = t_1;
	} else if (a <= 9.6e-229) {
		tmp = y;
	} else if (a <= 5e-53) {
		tmp = t_1;
	} else {
		tmp = x + (y * (z / a));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a)
    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) :: t_1
    real(8) :: tmp
    t_1 = (z - a) * (x / t)
    if (a <= (-7d-32)) then
        tmp = x + (y / (a / z))
    else if (a <= (-2.4d-272)) then
        tmp = t_1
    else if (a <= 9.6d-229) then
        tmp = y
    else if (a <= 5d-53) then
        tmp = t_1
    else
        tmp = x + (y * (z / a))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a) {
	double t_1 = (z - a) * (x / t);
	double tmp;
	if (a <= -7e-32) {
		tmp = x + (y / (a / z));
	} else if (a <= -2.4e-272) {
		tmp = t_1;
	} else if (a <= 9.6e-229) {
		tmp = y;
	} else if (a <= 5e-53) {
		tmp = t_1;
	} else {
		tmp = x + (y * (z / a));
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	t_1 = (z - a) * (x / t)
	tmp = 0
	if a <= -7e-32:
		tmp = x + (y / (a / z))
	elif a <= -2.4e-272:
		tmp = t_1
	elif a <= 9.6e-229:
		tmp = y
	elif a <= 5e-53:
		tmp = t_1
	else:
		tmp = x + (y * (z / a))
	return tmp

Julia

function code(x, y, z, t, a)
	t_1 = Float64(Float64(z - a) * Float64(x / t))
	tmp = 0.0
	if (a <= -7e-32)
		tmp = Float64(x + Float64(y / Float64(a / z)));
	elseif (a <= -2.4e-272)
		tmp = t_1;
	elseif (a <= 9.6e-229)
		tmp = y;
	elseif (a <= 5e-53)
		tmp = t_1;
	else
		tmp = Float64(x + Float64(y * Float64(z / a)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	t_1 = (z - a) * (x / t);
	tmp = 0.0;
	if (a <= -7e-32)
		tmp = x + (y / (a / z));
	elseif (a <= -2.4e-272)
		tmp = t_1;
	elseif (a <= 9.6e-229)
		tmp = y;
	elseif (a <= 5e-53)
		tmp = t_1;
	else
		tmp = x + (y * (z / a));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := Block[{t$95$1 = N[(N[(z - a), $MachinePrecision] * N[(x / t), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -7e-32], N[(x + N[(y / N[(a / z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, -2.4e-272], t$95$1, If[LessEqual[a, 9.6e-229], y, If[LessEqual[a, 5e-53], t$95$1, N[(x + N[(y * N[(z / a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]

Derivation

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

Alternative 20: 45.4% accurate, 0.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \left(z - a\right) \cdot \frac{x}{t}\\ t_2 := x + \frac{z}{\frac{a}{y}}\\ \mathbf{if}\;a \leq -1.6 \cdot 10^{-30}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;a \leq -6.2 \cdot 10^{-271}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq 10^{-229}:\\ \;\;\;\;y\\ \mathbf{elif}\;a \leq 5 \cdot 10^{-53}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (let* ((t_1 (* (- z a) (/ x t))) (t_2 (+ x (/ z (/ a y)))))
   (if (<= a -1.6e-30)
     t_2
     (if (<= a -6.2e-271)
       t_1
       (if (<= a 1e-229) y (if (<= a 5e-53) t_1 t_2))))))

C

double code(double x, double y, double z, double t, double a) {
	double t_1 = (z - a) * (x / t);
	double t_2 = x + (z / (a / y));
	double tmp;
	if (a <= -1.6e-30) {
		tmp = t_2;
	} else if (a <= -6.2e-271) {
		tmp = t_1;
	} else if (a <= 1e-229) {
		tmp = y;
	} else if (a <= 5e-53) {
		tmp = t_1;
	} else {
		tmp = t_2;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a)
    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) :: t_1
    real(8) :: t_2
    real(8) :: tmp
    t_1 = (z - a) * (x / t)
    t_2 = x + (z / (a / y))
    if (a <= (-1.6d-30)) then
        tmp = t_2
    else if (a <= (-6.2d-271)) then
        tmp = t_1
    else if (a <= 1d-229) then
        tmp = y
    else if (a <= 5d-53) then
        tmp = t_1
    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 t_1 = (z - a) * (x / t);
	double t_2 = x + (z / (a / y));
	double tmp;
	if (a <= -1.6e-30) {
		tmp = t_2;
	} else if (a <= -6.2e-271) {
		tmp = t_1;
	} else if (a <= 1e-229) {
		tmp = y;
	} else if (a <= 5e-53) {
		tmp = t_1;
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	t_1 = (z - a) * (x / t)
	t_2 = x + (z / (a / y))
	tmp = 0
	if a <= -1.6e-30:
		tmp = t_2
	elif a <= -6.2e-271:
		tmp = t_1
	elif a <= 1e-229:
		tmp = y
	elif a <= 5e-53:
		tmp = t_1
	else:
		tmp = t_2
	return tmp

Julia

function code(x, y, z, t, a)
	t_1 = Float64(Float64(z - a) * Float64(x / t))
	t_2 = Float64(x + Float64(z / Float64(a / y)))
	tmp = 0.0
	if (a <= -1.6e-30)
		tmp = t_2;
	elseif (a <= -6.2e-271)
		tmp = t_1;
	elseif (a <= 1e-229)
		tmp = y;
	elseif (a <= 5e-53)
		tmp = t_1;
	else
		tmp = t_2;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	t_1 = (z - a) * (x / t);
	t_2 = x + (z / (a / y));
	tmp = 0.0;
	if (a <= -1.6e-30)
		tmp = t_2;
	elseif (a <= -6.2e-271)
		tmp = t_1;
	elseif (a <= 1e-229)
		tmp = y;
	elseif (a <= 5e-53)
		tmp = t_1;
	else
		tmp = t_2;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := Block[{t$95$1 = N[(N[(z - a), $MachinePrecision] * N[(x / t), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(x + N[(z / N[(a / y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -1.6e-30], t$95$2, If[LessEqual[a, -6.2e-271], t$95$1, If[LessEqual[a, 1e-229], y, If[LessEqual[a, 5e-53], t$95$1, t$95$2]]]]]]

Derivation

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

Alternative 21: 57.6% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;a \leq -0.116:\\ \;\;\;\;x + \frac{y}{\frac{a}{z}}\\ \mathbf{elif}\;a \leq 2.25 \cdot 10^{-188}:\\ \;\;\;\;y + \frac{x}{\frac{t}{z}}\\ \mathbf{elif}\;a \leq 7.5 \cdot 10^{-53}:\\ \;\;\;\;y - \frac{a}{\frac{t}{x}}\\ \mathbf{else}:\\ \;\;\;\;x + \frac{z}{\frac{a}{y}}\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (if (<= a -0.116)
   (+ x (/ y (/ a z)))
   (if (<= a 2.25e-188)
     (+ y (/ x (/ t z)))
     (if (<= a 7.5e-53) (- y (/ a (/ t x))) (+ x (/ z (/ a y)))))))

C

double code(double x, double y, double z, double t, double a) {
	double tmp;
	if (a <= -0.116) {
		tmp = x + (y / (a / z));
	} else if (a <= 2.25e-188) {
		tmp = y + (x / (t / z));
	} else if (a <= 7.5e-53) {
		tmp = y - (a / (t / x));
	} else {
		tmp = x + (z / (a / y));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a)
    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) :: tmp
    if (a <= (-0.116d0)) then
        tmp = x + (y / (a / z))
    else if (a <= 2.25d-188) then
        tmp = y + (x / (t / z))
    else if (a <= 7.5d-53) then
        tmp = y - (a / (t / x))
    else
        tmp = x + (z / (a / y))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a) {
	double tmp;
	if (a <= -0.116) {
		tmp = x + (y / (a / z));
	} else if (a <= 2.25e-188) {
		tmp = y + (x / (t / z));
	} else if (a <= 7.5e-53) {
		tmp = y - (a / (t / x));
	} else {
		tmp = x + (z / (a / y));
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	tmp = 0
	if a <= -0.116:
		tmp = x + (y / (a / z))
	elif a <= 2.25e-188:
		tmp = y + (x / (t / z))
	elif a <= 7.5e-53:
		tmp = y - (a / (t / x))
	else:
		tmp = x + (z / (a / y))
	return tmp

Julia

function code(x, y, z, t, a)
	tmp = 0.0
	if (a <= -0.116)
		tmp = Float64(x + Float64(y / Float64(a / z)));
	elseif (a <= 2.25e-188)
		tmp = Float64(y + Float64(x / Float64(t / z)));
	elseif (a <= 7.5e-53)
		tmp = Float64(y - Float64(a / Float64(t / x)));
	else
		tmp = Float64(x + Float64(z / Float64(a / y)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	tmp = 0.0;
	if (a <= -0.116)
		tmp = x + (y / (a / z));
	elseif (a <= 2.25e-188)
		tmp = y + (x / (t / z));
	elseif (a <= 7.5e-53)
		tmp = y - (a / (t / x));
	else
		tmp = x + (z / (a / y));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := If[LessEqual[a, -0.116], N[(x + N[(y / N[(a / z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 2.25e-188], N[(y + N[(x / N[(t / z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 7.5e-53], N[(y - N[(a / N[(t / x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(x + N[(z / N[(a / y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]

Derivation

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

Alternative 22: 41.3% accurate, 1.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;y \leq -1 \cdot 10^{+83} \lor \neg \left(y \leq 5.7 \cdot 10^{+69}\right):\\ \;\;\;\;y \cdot \frac{z}{a - t}\\ \mathbf{else}:\\ \;\;\;\;x \cdot \left(1 - \frac{z}{a}\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (if (or (<= y -1e+83) (not (<= y 5.7e+69)))
   (* y (/ z (- a t)))
   (* x (- 1.0 (/ z a)))))

C

double code(double x, double y, double z, double t, double a) {
	double tmp;
	if ((y <= -1e+83) || !(y <= 5.7e+69)) {
		tmp = y * (z / (a - t));
	} else {
		tmp = x * (1.0 - (z / a));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a)
    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) :: tmp
    if ((y <= (-1d+83)) .or. (.not. (y <= 5.7d+69))) then
        tmp = y * (z / (a - t))
    else
        tmp = x * (1.0d0 - (z / a))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a) {
	double tmp;
	if ((y <= -1e+83) || !(y <= 5.7e+69)) {
		tmp = y * (z / (a - t));
	} else {
		tmp = x * (1.0 - (z / a));
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	tmp = 0
	if (y <= -1e+83) or not (y <= 5.7e+69):
		tmp = y * (z / (a - t))
	else:
		tmp = x * (1.0 - (z / a))
	return tmp

Julia

function code(x, y, z, t, a)
	tmp = 0.0
	if ((y <= -1e+83) || !(y <= 5.7e+69))
		tmp = Float64(y * Float64(z / Float64(a - t)));
	else
		tmp = Float64(x * Float64(1.0 - Float64(z / a)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	tmp = 0.0;
	if ((y <= -1e+83) || ~((y <= 5.7e+69)))
		tmp = y * (z / (a - t));
	else
		tmp = x * (1.0 - (z / a));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := If[Or[LessEqual[y, -1e+83], N[Not[LessEqual[y, 5.7e+69]], $MachinePrecision]], N[(y * N[(z / N[(a - t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(x * N[(1.0 - N[(z / a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

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

Alternative 23: 47.5% accurate, 1.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;t \leq -9 \cdot 10^{+119}:\\ \;\;\;\;y\\ \mathbf{elif}\;t \leq 3.5 \cdot 10^{-13}:\\ \;\;\;\;x \cdot \left(1 - \frac{z}{a}\right)\\ \mathbf{elif}\;t \leq 6.7 \cdot 10^{+115}:\\ \;\;\;\;y\\ \mathbf{elif}\;t \leq 2.1 \cdot 10^{+140}:\\ \;\;\;\;x\\ \mathbf{else}:\\ \;\;\;\;y\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (if (<= t -9e+119)
   y
   (if (<= t 3.5e-13)
     (* x (- 1.0 (/ z a)))
     (if (<= t 6.7e+115) y (if (<= t 2.1e+140) x y)))))

C

double code(double x, double y, double z, double t, double a) {
	double tmp;
	if (t <= -9e+119) {
		tmp = y;
	} else if (t <= 3.5e-13) {
		tmp = x * (1.0 - (z / a));
	} else if (t <= 6.7e+115) {
		tmp = y;
	} else if (t <= 2.1e+140) {
		tmp = x;
	} else {
		tmp = y;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a)
    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) :: tmp
    if (t <= (-9d+119)) then
        tmp = y
    else if (t <= 3.5d-13) then
        tmp = x * (1.0d0 - (z / a))
    else if (t <= 6.7d+115) then
        tmp = y
    else if (t <= 2.1d+140) then
        tmp = x
    else
        tmp = y
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a) {
	double tmp;
	if (t <= -9e+119) {
		tmp = y;
	} else if (t <= 3.5e-13) {
		tmp = x * (1.0 - (z / a));
	} else if (t <= 6.7e+115) {
		tmp = y;
	} else if (t <= 2.1e+140) {
		tmp = x;
	} else {
		tmp = y;
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	tmp = 0
	if t <= -9e+119:
		tmp = y
	elif t <= 3.5e-13:
		tmp = x * (1.0 - (z / a))
	elif t <= 6.7e+115:
		tmp = y
	elif t <= 2.1e+140:
		tmp = x
	else:
		tmp = y
	return tmp

Julia

function code(x, y, z, t, a)
	tmp = 0.0
	if (t <= -9e+119)
		tmp = y;
	elseif (t <= 3.5e-13)
		tmp = Float64(x * Float64(1.0 - Float64(z / a)));
	elseif (t <= 6.7e+115)
		tmp = y;
	elseif (t <= 2.1e+140)
		tmp = x;
	else
		tmp = y;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	tmp = 0.0;
	if (t <= -9e+119)
		tmp = y;
	elseif (t <= 3.5e-13)
		tmp = x * (1.0 - (z / a));
	elseif (t <= 6.7e+115)
		tmp = y;
	elseif (t <= 2.1e+140)
		tmp = x;
	else
		tmp = y;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := If[LessEqual[t, -9e+119], y, If[LessEqual[t, 3.5e-13], N[(x * N[(1.0 - N[(z / a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t, 6.7e+115], y, If[LessEqual[t, 2.1e+140], x, y]]]]

Derivation

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

Alternative 24: 59.2% accurate, 1.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;a \leq -0.0008:\\ \;\;\;\;x + \frac{y}{\frac{a}{z}}\\ \mathbf{elif}\;a \leq 7.2 \cdot 10^{-53}:\\ \;\;\;\;y + \frac{x}{\frac{t}{z}}\\ \mathbf{else}:\\ \;\;\;\;x + \frac{z}{\frac{a}{y}}\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (if (<= a -0.0008)
   (+ x (/ y (/ a z)))
   (if (<= a 7.2e-53) (+ y (/ x (/ t z))) (+ x (/ z (/ a y))))))

C

double code(double x, double y, double z, double t, double a) {
	double tmp;
	if (a <= -0.0008) {
		tmp = x + (y / (a / z));
	} else if (a <= 7.2e-53) {
		tmp = y + (x / (t / z));
	} else {
		tmp = x + (z / (a / y));
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a)
    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) :: tmp
    if (a <= (-0.0008d0)) then
        tmp = x + (y / (a / z))
    else if (a <= 7.2d-53) then
        tmp = y + (x / (t / z))
    else
        tmp = x + (z / (a / y))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a) {
	double tmp;
	if (a <= -0.0008) {
		tmp = x + (y / (a / z));
	} else if (a <= 7.2e-53) {
		tmp = y + (x / (t / z));
	} else {
		tmp = x + (z / (a / y));
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	tmp = 0
	if a <= -0.0008:
		tmp = x + (y / (a / z))
	elif a <= 7.2e-53:
		tmp = y + (x / (t / z))
	else:
		tmp = x + (z / (a / y))
	return tmp

Julia

function code(x, y, z, t, a)
	tmp = 0.0
	if (a <= -0.0008)
		tmp = Float64(x + Float64(y / Float64(a / z)));
	elseif (a <= 7.2e-53)
		tmp = Float64(y + Float64(x / Float64(t / z)));
	else
		tmp = Float64(x + Float64(z / Float64(a / y)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	tmp = 0.0;
	if (a <= -0.0008)
		tmp = x + (y / (a / z));
	elseif (a <= 7.2e-53)
		tmp = y + (x / (t / z));
	else
		tmp = x + (z / (a / y));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := If[LessEqual[a, -0.0008], N[(x + N[(y / N[(a / z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 7.2e-53], N[(y + N[(x / N[(t / z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(x + N[(z / N[(a / y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]

Derivation

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

Alternative 25: 38.3% accurate, 1.4× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;a \leq -5.8 \cdot 10^{+74}:\\ \;\;\;\;x\\ \mathbf{elif}\;a \leq -7 \cdot 10^{-19}:\\ \;\;\;\;y \cdot \frac{z}{a}\\ \mathbf{elif}\;a \leq 6.2 \cdot 10^{-53}:\\ \;\;\;\;y\\ \mathbf{else}:\\ \;\;\;\;x\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (if (<= a -5.8e+74)
   x
   (if (<= a -7e-19) (* y (/ z a)) (if (<= a 6.2e-53) y x))))

C

double code(double x, double y, double z, double t, double a) {
	double tmp;
	if (a <= -5.8e+74) {
		tmp = x;
	} else if (a <= -7e-19) {
		tmp = y * (z / a);
	} else if (a <= 6.2e-53) {
		tmp = y;
	} else {
		tmp = x;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a)
    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) :: tmp
    if (a <= (-5.8d+74)) then
        tmp = x
    else if (a <= (-7d-19)) then
        tmp = y * (z / a)
    else if (a <= 6.2d-53) then
        tmp = y
    else
        tmp = x
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a) {
	double tmp;
	if (a <= -5.8e+74) {
		tmp = x;
	} else if (a <= -7e-19) {
		tmp = y * (z / a);
	} else if (a <= 6.2e-53) {
		tmp = y;
	} else {
		tmp = x;
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	tmp = 0
	if a <= -5.8e+74:
		tmp = x
	elif a <= -7e-19:
		tmp = y * (z / a)
	elif a <= 6.2e-53:
		tmp = y
	else:
		tmp = x
	return tmp

Julia

function code(x, y, z, t, a)
	tmp = 0.0
	if (a <= -5.8e+74)
		tmp = x;
	elseif (a <= -7e-19)
		tmp = Float64(y * Float64(z / a));
	elseif (a <= 6.2e-53)
		tmp = y;
	else
		tmp = x;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	tmp = 0.0;
	if (a <= -5.8e+74)
		tmp = x;
	elseif (a <= -7e-19)
		tmp = y * (z / a);
	elseif (a <= 6.2e-53)
		tmp = y;
	else
		tmp = x;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := If[LessEqual[a, -5.8e+74], x, If[LessEqual[a, -7e-19], N[(y * N[(z / a), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 6.2e-53], y, x]]]

Derivation

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

Alternative 26: 38.2% accurate, 2.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;a \leq -1.75 \cdot 10^{+123}:\\ \;\;\;\;x\\ \mathbf{elif}\;a \leq 8 \cdot 10^{-53}:\\ \;\;\;\;y\\ \mathbf{else}:\\ \;\;\;\;x\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (if (<= a -1.75e+123) x (if (<= a 8e-53) y x)))

C

double code(double x, double y, double z, double t, double a) {
	double tmp;
	if (a <= -1.75e+123) {
		tmp = x;
	} else if (a <= 8e-53) {
		tmp = y;
	} else {
		tmp = x;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a)
    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) :: tmp
    if (a <= (-1.75d+123)) then
        tmp = x
    else if (a <= 8d-53) then
        tmp = y
    else
        tmp = x
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a) {
	double tmp;
	if (a <= -1.75e+123) {
		tmp = x;
	} else if (a <= 8e-53) {
		tmp = y;
	} else {
		tmp = x;
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	tmp = 0
	if a <= -1.75e+123:
		tmp = x
	elif a <= 8e-53:
		tmp = y
	else:
		tmp = x
	return tmp

Julia

function code(x, y, z, t, a)
	tmp = 0.0
	if (a <= -1.75e+123)
		tmp = x;
	elseif (a <= 8e-53)
		tmp = y;
	else
		tmp = x;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	tmp = 0.0;
	if (a <= -1.75e+123)
		tmp = x;
	elseif (a <= 8e-53)
		tmp = y;
	else
		tmp = x;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := If[LessEqual[a, -1.75e+123], x, If[LessEqual[a, 8e-53], y, x]]

Derivation

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

Alternative 27: 25.1% accurate, 13.0× speedup

Math

\[\begin{array}{l} \\ x \end{array} \]

FPCore

(FPCore (x y z t a) :precision binary64 x)

C

double code(double x, double y, double z, double t, double a) {
	return x;
}

Fortran

real(8) function code(x, y, z, t, a)
    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
    code = x
end function

Java

public static double code(double x, double y, double z, double t, double a) {
	return x;
}

Python

def code(x, y, z, t, a):
	return x

Julia

function code(x, y, z, t, a)
	return x
end

MATLAB

function tmp = code(x, y, z, t, a)
	tmp = x;
end

Wolfram

code[x_, y_, z_, t_, a_] := x

Derivation

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

Developer target: 87.0% accurate, 0.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x + \frac{y - x}{1} \cdot \frac{z - t}{a - t}\\ \mathbf{if}\;a < -1.6153062845442575 \cdot 10^{-142}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a < 3.774403170083174 \cdot 10^{-182}:\\ \;\;\;\;y - \frac{z}{t} \cdot \left(y - x\right)\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (let* ((t_1 (+ x (* (/ (- y x) 1.0) (/ (- z t) (- a t))))))
   (if (< a -1.6153062845442575e-142)
     t_1
     (if (< a 3.774403170083174e-182) (- y (* (/ z t) (- y x))) t_1))))

C

double code(double x, double y, double z, double t, double a) {
	double t_1 = x + (((y - x) / 1.0) * ((z - t) / (a - t)));
	double tmp;
	if (a < -1.6153062845442575e-142) {
		tmp = t_1;
	} else if (a < 3.774403170083174e-182) {
		tmp = y - ((z / t) * (y - x));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Fortran

real(8) function code(x, y, z, t, a)
    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) :: t_1
    real(8) :: tmp
    t_1 = x + (((y - x) / 1.0d0) * ((z - t) / (a - t)))
    if (a < (-1.6153062845442575d-142)) then
        tmp = t_1
    else if (a < 3.774403170083174d-182) then
        tmp = y - ((z / t) * (y - x))
    else
        tmp = t_1
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a) {
	double t_1 = x + (((y - x) / 1.0) * ((z - t) / (a - t)));
	double tmp;
	if (a < -1.6153062845442575e-142) {
		tmp = t_1;
	} else if (a < 3.774403170083174e-182) {
		tmp = y - ((z / t) * (y - x));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	t_1 = x + (((y - x) / 1.0) * ((z - t) / (a - t)))
	tmp = 0
	if a < -1.6153062845442575e-142:
		tmp = t_1
	elif a < 3.774403170083174e-182:
		tmp = y - ((z / t) * (y - x))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a)
	t_1 = Float64(x + Float64(Float64(Float64(y - x) / 1.0) * Float64(Float64(z - t) / Float64(a - t))))
	tmp = 0.0
	if (a < -1.6153062845442575e-142)
		tmp = t_1;
	elseif (a < 3.774403170083174e-182)
		tmp = Float64(y - Float64(Float64(z / t) * Float64(y - x)));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	t_1 = x + (((y - x) / 1.0) * ((z - t) / (a - t)));
	tmp = 0.0;
	if (a < -1.6153062845442575e-142)
		tmp = t_1;
	elseif (a < 3.774403170083174e-182)
		tmp = y - ((z / t) * (y - x));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := Block[{t$95$1 = N[(x + N[(N[(N[(y - x), $MachinePrecision] / 1.0), $MachinePrecision] * N[(N[(z - t), $MachinePrecision] / N[(a - t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[Less[a, -1.6153062845442575e-142], t$95$1, If[Less[a, 3.774403170083174e-182], N[(y - N[(N[(z / t), $MachinePrecision] * N[(y - x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]

Reproduce

herbie shell --seed 2023350 
(FPCore (x y z t a)
  :name "Graphics.Rendering.Chart.Axis.Types:linMap from Chart-1.5.3"
  :precision binary64

  :herbie-target
  (if (< a -1.6153062845442575e-142) (+ x (* (/ (- y x) 1.0) (/ (- z t) (- a t)))) (if (< a 3.774403170083174e-182) (- y (* (/ z t) (- y x))) (+ x (* (/ (- y x) 1.0) (/ (- z t) (- a t))))))

  (+ x (/ (* (- y x) (- z t)) (- a t))))