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

Percentage Accurate: 68.5% → 90.8%

Time: 24.1s

Alternatives: 26

Speedup: 1.0×

Specification

Math

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

FPCore

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

C

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

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 - z) * (t - x)) / (a - z))
end function

Java

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

Python

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

Julia

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

MATLAB

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

Wolfram

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

Initial Program: 68.5% accurate, 1.0× speedup

Math

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

FPCore

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

C

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

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 - z) * (t - x)) / (a - z))
end function

Java

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

Python

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

Julia

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

MATLAB

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

Wolfram

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

Alternative 1: 90.8% accurate, 0.3× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x + \frac{\left(y - z\right) \cdot \left(t - x\right)}{a - z}\\ \mathbf{if}\;t_1 \leq -1 \cdot 10^{-305} \lor \neg \left(t_1 \leq 0\right):\\ \;\;\;\;x + \left(x - t\right) \cdot \frac{z - y}{a - z}\\ \mathbf{else}:\\ \;\;\;\;t + \frac{\left(t - x\right) \cdot \left(a - y\right)}{z}\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (let* ((t_1 (+ x (/ (* (- y z) (- t x)) (- a z)))))
   (if (or (<= t_1 -1e-305) (not (<= t_1 0.0)))
     (+ x (* (- x t) (/ (- z y) (- a z))))
     (+ t (/ (* (- t x) (- a y)) z)))))

C

double code(double x, double y, double z, double t, double a) {
	double t_1 = x + (((y - z) * (t - x)) / (a - z));
	double tmp;
	if ((t_1 <= -1e-305) || !(t_1 <= 0.0)) {
		tmp = x + ((x - t) * ((z - y) / (a - z)));
	} else {
		tmp = t + (((t - x) * (a - y)) / z);
	}
	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) * (t - x)) / (a - z))
    if ((t_1 <= (-1d-305)) .or. (.not. (t_1 <= 0.0d0))) then
        tmp = x + ((x - t) * ((z - y) / (a - z)))
    else
        tmp = t + (((t - x) * (a - y)) / z)
    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) * (t - x)) / (a - z));
	double tmp;
	if ((t_1 <= -1e-305) || !(t_1 <= 0.0)) {
		tmp = x + ((x - t) * ((z - y) / (a - z)));
	} else {
		tmp = t + (((t - x) * (a - y)) / z);
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	t_1 = x + (((y - z) * (t - x)) / (a - z))
	tmp = 0
	if (t_1 <= -1e-305) or not (t_1 <= 0.0):
		tmp = x + ((x - t) * ((z - y) / (a - z)))
	else:
		tmp = t + (((t - x) * (a - y)) / z)
	return tmp

Julia

function code(x, y, z, t, a)
	t_1 = Float64(x + Float64(Float64(Float64(y - z) * Float64(t - x)) / Float64(a - z)))
	tmp = 0.0
	if ((t_1 <= -1e-305) || !(t_1 <= 0.0))
		tmp = Float64(x + Float64(Float64(x - t) * Float64(Float64(z - y) / Float64(a - z))));
	else
		tmp = Float64(t + Float64(Float64(Float64(t - x) * Float64(a - y)) / z));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	t_1 = x + (((y - z) * (t - x)) / (a - z));
	tmp = 0.0;
	if ((t_1 <= -1e-305) || ~((t_1 <= 0.0)))
		tmp = x + ((x - t) * ((z - y) / (a - z)));
	else
		tmp = t + (((t - x) * (a - y)) / z);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := Block[{t$95$1 = N[(x + N[(N[(N[(y - z), $MachinePrecision] * N[(t - x), $MachinePrecision]), $MachinePrecision] / N[(a - z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[t$95$1, -1e-305], N[Not[LessEqual[t$95$1, 0.0]], $MachinePrecision]], N[(x + N[(N[(x - t), $MachinePrecision] * N[(N[(z - y), $MachinePrecision] / N[(a - z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(t + N[(N[(N[(t - x), $MachinePrecision] * N[(a - y), $MachinePrecision]), $MachinePrecision] / z), $MachinePrecision]), $MachinePrecision]]]

Derivation

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

Alternative 2: 39.3% accurate, 0.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(\frac{z}{a} + 1\right)\\ t_2 := t \cdot \frac{y - z}{a}\\ \mathbf{if}\;z \leq -1.7 \cdot 10^{-13}:\\ \;\;\;\;t\\ \mathbf{elif}\;z \leq -5.5 \cdot 10^{-106}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;z \leq -1.75 \cdot 10^{-298}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq 2.2 \cdot 10^{-219}:\\ \;\;\;\;\frac{t}{\frac{a}{y}}\\ \mathbf{elif}\;z \leq 5.1 \cdot 10^{-114}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq 1.85 \cdot 10^{-28}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;z \leq 9.4 \cdot 10^{+82}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;t\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (let* ((t_1 (* x (+ (/ z a) 1.0))) (t_2 (* t (/ (- y z) a))))
   (if (<= z -1.7e-13)
     t
     (if (<= z -5.5e-106)
       t_2
       (if (<= z -1.75e-298)
         t_1
         (if (<= z 2.2e-219)
           (/ t (/ a y))
           (if (<= z 5.1e-114)
             t_1
             (if (<= z 1.85e-28) t_2 (if (<= z 9.4e+82) t_1 t)))))))))

C

double code(double x, double y, double z, double t, double a) {
	double t_1 = x * ((z / a) + 1.0);
	double t_2 = t * ((y - z) / a);
	double tmp;
	if (z <= -1.7e-13) {
		tmp = t;
	} else if (z <= -5.5e-106) {
		tmp = t_2;
	} else if (z <= -1.75e-298) {
		tmp = t_1;
	} else if (z <= 2.2e-219) {
		tmp = t / (a / y);
	} else if (z <= 5.1e-114) {
		tmp = t_1;
	} else if (z <= 1.85e-28) {
		tmp = t_2;
	} else if (z <= 9.4e+82) {
		tmp = t_1;
	} else {
		tmp = 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) :: t_2
    real(8) :: tmp
    t_1 = x * ((z / a) + 1.0d0)
    t_2 = t * ((y - z) / a)
    if (z <= (-1.7d-13)) then
        tmp = t
    else if (z <= (-5.5d-106)) then
        tmp = t_2
    else if (z <= (-1.75d-298)) then
        tmp = t_1
    else if (z <= 2.2d-219) then
        tmp = t / (a / y)
    else if (z <= 5.1d-114) then
        tmp = t_1
    else if (z <= 1.85d-28) then
        tmp = t_2
    else if (z <= 9.4d+82) then
        tmp = t_1
    else
        tmp = 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 * ((z / a) + 1.0);
	double t_2 = t * ((y - z) / a);
	double tmp;
	if (z <= -1.7e-13) {
		tmp = t;
	} else if (z <= -5.5e-106) {
		tmp = t_2;
	} else if (z <= -1.75e-298) {
		tmp = t_1;
	} else if (z <= 2.2e-219) {
		tmp = t / (a / y);
	} else if (z <= 5.1e-114) {
		tmp = t_1;
	} else if (z <= 1.85e-28) {
		tmp = t_2;
	} else if (z <= 9.4e+82) {
		tmp = t_1;
	} else {
		tmp = t;
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	t_1 = x * ((z / a) + 1.0)
	t_2 = t * ((y - z) / a)
	tmp = 0
	if z <= -1.7e-13:
		tmp = t
	elif z <= -5.5e-106:
		tmp = t_2
	elif z <= -1.75e-298:
		tmp = t_1
	elif z <= 2.2e-219:
		tmp = t / (a / y)
	elif z <= 5.1e-114:
		tmp = t_1
	elif z <= 1.85e-28:
		tmp = t_2
	elif z <= 9.4e+82:
		tmp = t_1
	else:
		tmp = t
	return tmp

Julia

function code(x, y, z, t, a)
	t_1 = Float64(x * Float64(Float64(z / a) + 1.0))
	t_2 = Float64(t * Float64(Float64(y - z) / a))
	tmp = 0.0
	if (z <= -1.7e-13)
		tmp = t;
	elseif (z <= -5.5e-106)
		tmp = t_2;
	elseif (z <= -1.75e-298)
		tmp = t_1;
	elseif (z <= 2.2e-219)
		tmp = Float64(t / Float64(a / y));
	elseif (z <= 5.1e-114)
		tmp = t_1;
	elseif (z <= 1.85e-28)
		tmp = t_2;
	elseif (z <= 9.4e+82)
		tmp = t_1;
	else
		tmp = t;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	t_1 = x * ((z / a) + 1.0);
	t_2 = t * ((y - z) / a);
	tmp = 0.0;
	if (z <= -1.7e-13)
		tmp = t;
	elseif (z <= -5.5e-106)
		tmp = t_2;
	elseif (z <= -1.75e-298)
		tmp = t_1;
	elseif (z <= 2.2e-219)
		tmp = t / (a / y);
	elseif (z <= 5.1e-114)
		tmp = t_1;
	elseif (z <= 1.85e-28)
		tmp = t_2;
	elseif (z <= 9.4e+82)
		tmp = t_1;
	else
		tmp = t;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := Block[{t$95$1 = N[(x * N[(N[(z / a), $MachinePrecision] + 1.0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(t * N[(N[(y - z), $MachinePrecision] / a), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -1.7e-13], t, If[LessEqual[z, -5.5e-106], t$95$2, If[LessEqual[z, -1.75e-298], t$95$1, If[LessEqual[z, 2.2e-219], N[(t / N[(a / y), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 5.1e-114], t$95$1, If[LessEqual[z, 1.85e-28], t$95$2, If[LessEqual[z, 9.4e+82], t$95$1, t]]]]]]]]]

Derivation

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

Alternative 3: 45.2% accurate, 0.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(1 - \frac{y}{a}\right)\\ t_2 := t \cdot \frac{y - z}{a}\\ \mathbf{if}\;z \leq -4.5 \cdot 10^{-15}:\\ \;\;\;\;t\\ \mathbf{elif}\;z \leq -2.55 \cdot 10^{-105}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;z \leq -1.85 \cdot 10^{-301}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq 2.4 \cdot 10^{-216}:\\ \;\;\;\;\frac{t}{\frac{a}{y}}\\ \mathbf{elif}\;z \leq 9.2 \cdot 10^{-112}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq 8 \cdot 10^{-75}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;z \leq 8.2 \cdot 10^{+132}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;t\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (let* ((t_1 (* x (- 1.0 (/ y a)))) (t_2 (* t (/ (- y z) a))))
   (if (<= z -4.5e-15)
     t
     (if (<= z -2.55e-105)
       t_2
       (if (<= z -1.85e-301)
         t_1
         (if (<= z 2.4e-216)
           (/ t (/ a y))
           (if (<= z 9.2e-112)
             t_1
             (if (<= z 8e-75) t_2 (if (<= z 8.2e+132) t_1 t)))))))))

C

double code(double x, double y, double z, double t, double a) {
	double t_1 = x * (1.0 - (y / a));
	double t_2 = t * ((y - z) / a);
	double tmp;
	if (z <= -4.5e-15) {
		tmp = t;
	} else if (z <= -2.55e-105) {
		tmp = t_2;
	} else if (z <= -1.85e-301) {
		tmp = t_1;
	} else if (z <= 2.4e-216) {
		tmp = t / (a / y);
	} else if (z <= 9.2e-112) {
		tmp = t_1;
	} else if (z <= 8e-75) {
		tmp = t_2;
	} else if (z <= 8.2e+132) {
		tmp = t_1;
	} else {
		tmp = 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) :: t_2
    real(8) :: tmp
    t_1 = x * (1.0d0 - (y / a))
    t_2 = t * ((y - z) / a)
    if (z <= (-4.5d-15)) then
        tmp = t
    else if (z <= (-2.55d-105)) then
        tmp = t_2
    else if (z <= (-1.85d-301)) then
        tmp = t_1
    else if (z <= 2.4d-216) then
        tmp = t / (a / y)
    else if (z <= 9.2d-112) then
        tmp = t_1
    else if (z <= 8d-75) then
        tmp = t_2
    else if (z <= 8.2d+132) then
        tmp = t_1
    else
        tmp = 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 * (1.0 - (y / a));
	double t_2 = t * ((y - z) / a);
	double tmp;
	if (z <= -4.5e-15) {
		tmp = t;
	} else if (z <= -2.55e-105) {
		tmp = t_2;
	} else if (z <= -1.85e-301) {
		tmp = t_1;
	} else if (z <= 2.4e-216) {
		tmp = t / (a / y);
	} else if (z <= 9.2e-112) {
		tmp = t_1;
	} else if (z <= 8e-75) {
		tmp = t_2;
	} else if (z <= 8.2e+132) {
		tmp = t_1;
	} else {
		tmp = t;
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	t_1 = x * (1.0 - (y / a))
	t_2 = t * ((y - z) / a)
	tmp = 0
	if z <= -4.5e-15:
		tmp = t
	elif z <= -2.55e-105:
		tmp = t_2
	elif z <= -1.85e-301:
		tmp = t_1
	elif z <= 2.4e-216:
		tmp = t / (a / y)
	elif z <= 9.2e-112:
		tmp = t_1
	elif z <= 8e-75:
		tmp = t_2
	elif z <= 8.2e+132:
		tmp = t_1
	else:
		tmp = t
	return tmp

Julia

function code(x, y, z, t, a)
	t_1 = Float64(x * Float64(1.0 - Float64(y / a)))
	t_2 = Float64(t * Float64(Float64(y - z) / a))
	tmp = 0.0
	if (z <= -4.5e-15)
		tmp = t;
	elseif (z <= -2.55e-105)
		tmp = t_2;
	elseif (z <= -1.85e-301)
		tmp = t_1;
	elseif (z <= 2.4e-216)
		tmp = Float64(t / Float64(a / y));
	elseif (z <= 9.2e-112)
		tmp = t_1;
	elseif (z <= 8e-75)
		tmp = t_2;
	elseif (z <= 8.2e+132)
		tmp = t_1;
	else
		tmp = t;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	t_1 = x * (1.0 - (y / a));
	t_2 = t * ((y - z) / a);
	tmp = 0.0;
	if (z <= -4.5e-15)
		tmp = t;
	elseif (z <= -2.55e-105)
		tmp = t_2;
	elseif (z <= -1.85e-301)
		tmp = t_1;
	elseif (z <= 2.4e-216)
		tmp = t / (a / y);
	elseif (z <= 9.2e-112)
		tmp = t_1;
	elseif (z <= 8e-75)
		tmp = t_2;
	elseif (z <= 8.2e+132)
		tmp = t_1;
	else
		tmp = t;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := Block[{t$95$1 = N[(x * N[(1.0 - N[(y / a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(t * N[(N[(y - z), $MachinePrecision] / a), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -4.5e-15], t, If[LessEqual[z, -2.55e-105], t$95$2, If[LessEqual[z, -1.85e-301], t$95$1, If[LessEqual[z, 2.4e-216], N[(t / N[(a / y), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 9.2e-112], t$95$1, If[LessEqual[z, 8e-75], t$95$2, If[LessEqual[z, 8.2e+132], t$95$1, t]]]]]]]]]

Derivation

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

Alternative 4: 45.4% accurate, 0.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x \cdot \left(1 - \frac{y}{a}\right)\\ t_2 := t \cdot \frac{y - z}{a}\\ \mathbf{if}\;z \leq -1.08 \cdot 10^{-13}:\\ \;\;\;\;t\\ \mathbf{elif}\;z \leq -2.55 \cdot 10^{-105}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;z \leq -8.5 \cdot 10^{-205}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq 1.55 \cdot 10^{-218}:\\ \;\;\;\;y \cdot \frac{t - x}{a}\\ \mathbf{elif}\;z \leq 9.6 \cdot 10^{-113}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq 2.9 \cdot 10^{-75}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;z \leq 2.8 \cdot 10^{+134}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;t\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (let* ((t_1 (* x (- 1.0 (/ y a)))) (t_2 (* t (/ (- y z) a))))
   (if (<= z -1.08e-13)
     t
     (if (<= z -2.55e-105)
       t_2
       (if (<= z -8.5e-205)
         t_1
         (if (<= z 1.55e-218)
           (* y (/ (- t x) a))
           (if (<= z 9.6e-113)
             t_1
             (if (<= z 2.9e-75) t_2 (if (<= z 2.8e+134) t_1 t)))))))))

C

double code(double x, double y, double z, double t, double a) {
	double t_1 = x * (1.0 - (y / a));
	double t_2 = t * ((y - z) / a);
	double tmp;
	if (z <= -1.08e-13) {
		tmp = t;
	} else if (z <= -2.55e-105) {
		tmp = t_2;
	} else if (z <= -8.5e-205) {
		tmp = t_1;
	} else if (z <= 1.55e-218) {
		tmp = y * ((t - x) / a);
	} else if (z <= 9.6e-113) {
		tmp = t_1;
	} else if (z <= 2.9e-75) {
		tmp = t_2;
	} else if (z <= 2.8e+134) {
		tmp = t_1;
	} else {
		tmp = 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) :: t_2
    real(8) :: tmp
    t_1 = x * (1.0d0 - (y / a))
    t_2 = t * ((y - z) / a)
    if (z <= (-1.08d-13)) then
        tmp = t
    else if (z <= (-2.55d-105)) then
        tmp = t_2
    else if (z <= (-8.5d-205)) then
        tmp = t_1
    else if (z <= 1.55d-218) then
        tmp = y * ((t - x) / a)
    else if (z <= 9.6d-113) then
        tmp = t_1
    else if (z <= 2.9d-75) then
        tmp = t_2
    else if (z <= 2.8d+134) then
        tmp = t_1
    else
        tmp = 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 * (1.0 - (y / a));
	double t_2 = t * ((y - z) / a);
	double tmp;
	if (z <= -1.08e-13) {
		tmp = t;
	} else if (z <= -2.55e-105) {
		tmp = t_2;
	} else if (z <= -8.5e-205) {
		tmp = t_1;
	} else if (z <= 1.55e-218) {
		tmp = y * ((t - x) / a);
	} else if (z <= 9.6e-113) {
		tmp = t_1;
	} else if (z <= 2.9e-75) {
		tmp = t_2;
	} else if (z <= 2.8e+134) {
		tmp = t_1;
	} else {
		tmp = t;
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	t_1 = x * (1.0 - (y / a))
	t_2 = t * ((y - z) / a)
	tmp = 0
	if z <= -1.08e-13:
		tmp = t
	elif z <= -2.55e-105:
		tmp = t_2
	elif z <= -8.5e-205:
		tmp = t_1
	elif z <= 1.55e-218:
		tmp = y * ((t - x) / a)
	elif z <= 9.6e-113:
		tmp = t_1
	elif z <= 2.9e-75:
		tmp = t_2
	elif z <= 2.8e+134:
		tmp = t_1
	else:
		tmp = t
	return tmp

Julia

function code(x, y, z, t, a)
	t_1 = Float64(x * Float64(1.0 - Float64(y / a)))
	t_2 = Float64(t * Float64(Float64(y - z) / a))
	tmp = 0.0
	if (z <= -1.08e-13)
		tmp = t;
	elseif (z <= -2.55e-105)
		tmp = t_2;
	elseif (z <= -8.5e-205)
		tmp = t_1;
	elseif (z <= 1.55e-218)
		tmp = Float64(y * Float64(Float64(t - x) / a));
	elseif (z <= 9.6e-113)
		tmp = t_1;
	elseif (z <= 2.9e-75)
		tmp = t_2;
	elseif (z <= 2.8e+134)
		tmp = t_1;
	else
		tmp = t;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	t_1 = x * (1.0 - (y / a));
	t_2 = t * ((y - z) / a);
	tmp = 0.0;
	if (z <= -1.08e-13)
		tmp = t;
	elseif (z <= -2.55e-105)
		tmp = t_2;
	elseif (z <= -8.5e-205)
		tmp = t_1;
	elseif (z <= 1.55e-218)
		tmp = y * ((t - x) / a);
	elseif (z <= 9.6e-113)
		tmp = t_1;
	elseif (z <= 2.9e-75)
		tmp = t_2;
	elseif (z <= 2.8e+134)
		tmp = t_1;
	else
		tmp = t;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := Block[{t$95$1 = N[(x * N[(1.0 - N[(y / a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(t * N[(N[(y - z), $MachinePrecision] / a), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -1.08e-13], t, If[LessEqual[z, -2.55e-105], t$95$2, If[LessEqual[z, -8.5e-205], t$95$1, If[LessEqual[z, 1.55e-218], N[(y * N[(N[(t - x), $MachinePrecision] / a), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 9.6e-113], t$95$1, If[LessEqual[z, 2.9e-75], t$95$2, If[LessEqual[z, 2.8e+134], t$95$1, t]]]]]]]]]

Derivation

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

Alternative 5: 54.3% accurate, 0.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y \cdot \frac{t - x}{a - z}\\ t_2 := \frac{t}{\frac{z - a}{z}}\\ \mathbf{if}\;z \leq -9.6 \cdot 10^{+89}:\\ \;\;\;\;\frac{-t}{\frac{z}{y - z}}\\ \mathbf{elif}\;z \leq -2 \cdot 10^{+34}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq -1.65 \cdot 10^{-15}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;z \leq -8.5 \cdot 10^{-40}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq 2.7 \cdot 10^{-73}:\\ \;\;\;\;x + \frac{y \cdot t}{a}\\ \mathbf{elif}\;z \leq 9.6 \cdot 10^{+162}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (let* ((t_1 (* y (/ (- t x) (- a z)))) (t_2 (/ t (/ (- z a) z))))
   (if (<= z -9.6e+89)
     (/ (- t) (/ z (- y z)))
     (if (<= z -2e+34)
       t_1
       (if (<= z -1.65e-15)
         t_2
         (if (<= z -8.5e-40)
           t_1
           (if (<= z 2.7e-73)
             (+ x (/ (* y t) a))
             (if (<= z 9.6e+162) t_1 t_2))))))))

C

double code(double x, double y, double z, double t, double a) {
	double t_1 = y * ((t - x) / (a - z));
	double t_2 = t / ((z - a) / z);
	double tmp;
	if (z <= -9.6e+89) {
		tmp = -t / (z / (y - z));
	} else if (z <= -2e+34) {
		tmp = t_1;
	} else if (z <= -1.65e-15) {
		tmp = t_2;
	} else if (z <= -8.5e-40) {
		tmp = t_1;
	} else if (z <= 2.7e-73) {
		tmp = x + ((y * t) / a);
	} else if (z <= 9.6e+162) {
		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 * ((t - x) / (a - z))
    t_2 = t / ((z - a) / z)
    if (z <= (-9.6d+89)) then
        tmp = -t / (z / (y - z))
    else if (z <= (-2d+34)) then
        tmp = t_1
    else if (z <= (-1.65d-15)) then
        tmp = t_2
    else if (z <= (-8.5d-40)) then
        tmp = t_1
    else if (z <= 2.7d-73) then
        tmp = x + ((y * t) / a)
    else if (z <= 9.6d+162) 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 * ((t - x) / (a - z));
	double t_2 = t / ((z - a) / z);
	double tmp;
	if (z <= -9.6e+89) {
		tmp = -t / (z / (y - z));
	} else if (z <= -2e+34) {
		tmp = t_1;
	} else if (z <= -1.65e-15) {
		tmp = t_2;
	} else if (z <= -8.5e-40) {
		tmp = t_1;
	} else if (z <= 2.7e-73) {
		tmp = x + ((y * t) / a);
	} else if (z <= 9.6e+162) {
		tmp = t_1;
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	t_1 = y * ((t - x) / (a - z))
	t_2 = t / ((z - a) / z)
	tmp = 0
	if z <= -9.6e+89:
		tmp = -t / (z / (y - z))
	elif z <= -2e+34:
		tmp = t_1
	elif z <= -1.65e-15:
		tmp = t_2
	elif z <= -8.5e-40:
		tmp = t_1
	elif z <= 2.7e-73:
		tmp = x + ((y * t) / a)
	elif z <= 9.6e+162:
		tmp = t_1
	else:
		tmp = t_2
	return tmp

Julia

function code(x, y, z, t, a)
	t_1 = Float64(y * Float64(Float64(t - x) / Float64(a - z)))
	t_2 = Float64(t / Float64(Float64(z - a) / z))
	tmp = 0.0
	if (z <= -9.6e+89)
		tmp = Float64(Float64(-t) / Float64(z / Float64(y - z)));
	elseif (z <= -2e+34)
		tmp = t_1;
	elseif (z <= -1.65e-15)
		tmp = t_2;
	elseif (z <= -8.5e-40)
		tmp = t_1;
	elseif (z <= 2.7e-73)
		tmp = Float64(x + Float64(Float64(y * t) / a));
	elseif (z <= 9.6e+162)
		tmp = t_1;
	else
		tmp = t_2;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	t_1 = y * ((t - x) / (a - z));
	t_2 = t / ((z - a) / z);
	tmp = 0.0;
	if (z <= -9.6e+89)
		tmp = -t / (z / (y - z));
	elseif (z <= -2e+34)
		tmp = t_1;
	elseif (z <= -1.65e-15)
		tmp = t_2;
	elseif (z <= -8.5e-40)
		tmp = t_1;
	elseif (z <= 2.7e-73)
		tmp = x + ((y * t) / a);
	elseif (z <= 9.6e+162)
		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[(t - x), $MachinePrecision] / N[(a - z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(t / N[(N[(z - a), $MachinePrecision] / z), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -9.6e+89], N[((-t) / N[(z / N[(y - z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -2e+34], t$95$1, If[LessEqual[z, -1.65e-15], t$95$2, If[LessEqual[z, -8.5e-40], t$95$1, If[LessEqual[z, 2.7e-73], N[(x + N[(N[(y * t), $MachinePrecision] / a), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 9.6e+162], t$95$1, t$95$2]]]]]]]]

Derivation

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

Alternative 6: 54.7% accurate, 0.6× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := \left(t - x\right) \cdot \frac{y}{a - z}\\ t_2 := \frac{t}{\frac{z - a}{z}}\\ \mathbf{if}\;z \leq -2.2 \cdot 10^{+87}:\\ \;\;\;\;\frac{-t}{\frac{z}{y - z}}\\ \mathbf{elif}\;z \leq -5.8 \cdot 10^{+37}:\\ \;\;\;\;y \cdot \frac{t - x}{a - z}\\ \mathbf{elif}\;z \leq -2.3 \cdot 10^{-15}:\\ \;\;\;\;t_2\\ \mathbf{elif}\;z \leq -1.95 \cdot 10^{-121}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq 1.7 \cdot 10^{-71}:\\ \;\;\;\;x + \frac{y \cdot t}{a}\\ \mathbf{elif}\;z \leq 1.12 \cdot 10^{+163}:\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;t_2\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (let* ((t_1 (* (- t x) (/ y (- a z)))) (t_2 (/ t (/ (- z a) z))))
   (if (<= z -2.2e+87)
     (/ (- t) (/ z (- y z)))
     (if (<= z -5.8e+37)
       (* y (/ (- t x) (- a z)))
       (if (<= z -2.3e-15)
         t_2
         (if (<= z -1.95e-121)
           t_1
           (if (<= z 1.7e-71)
             (+ x (/ (* y t) a))
             (if (<= z 1.12e+163) t_1 t_2))))))))

C

double code(double x, double y, double z, double t, double a) {
	double t_1 = (t - x) * (y / (a - z));
	double t_2 = t / ((z - a) / z);
	double tmp;
	if (z <= -2.2e+87) {
		tmp = -t / (z / (y - z));
	} else if (z <= -5.8e+37) {
		tmp = y * ((t - x) / (a - z));
	} else if (z <= -2.3e-15) {
		tmp = t_2;
	} else if (z <= -1.95e-121) {
		tmp = t_1;
	} else if (z <= 1.7e-71) {
		tmp = x + ((y * t) / a);
	} else if (z <= 1.12e+163) {
		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 = (t - x) * (y / (a - z))
    t_2 = t / ((z - a) / z)
    if (z <= (-2.2d+87)) then
        tmp = -t / (z / (y - z))
    else if (z <= (-5.8d+37)) then
        tmp = y * ((t - x) / (a - z))
    else if (z <= (-2.3d-15)) then
        tmp = t_2
    else if (z <= (-1.95d-121)) then
        tmp = t_1
    else if (z <= 1.7d-71) then
        tmp = x + ((y * t) / a)
    else if (z <= 1.12d+163) 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 = (t - x) * (y / (a - z));
	double t_2 = t / ((z - a) / z);
	double tmp;
	if (z <= -2.2e+87) {
		tmp = -t / (z / (y - z));
	} else if (z <= -5.8e+37) {
		tmp = y * ((t - x) / (a - z));
	} else if (z <= -2.3e-15) {
		tmp = t_2;
	} else if (z <= -1.95e-121) {
		tmp = t_1;
	} else if (z <= 1.7e-71) {
		tmp = x + ((y * t) / a);
	} else if (z <= 1.12e+163) {
		tmp = t_1;
	} else {
		tmp = t_2;
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	t_1 = (t - x) * (y / (a - z))
	t_2 = t / ((z - a) / z)
	tmp = 0
	if z <= -2.2e+87:
		tmp = -t / (z / (y - z))
	elif z <= -5.8e+37:
		tmp = y * ((t - x) / (a - z))
	elif z <= -2.3e-15:
		tmp = t_2
	elif z <= -1.95e-121:
		tmp = t_1
	elif z <= 1.7e-71:
		tmp = x + ((y * t) / a)
	elif z <= 1.12e+163:
		tmp = t_1
	else:
		tmp = t_2
	return tmp

Julia

function code(x, y, z, t, a)
	t_1 = Float64(Float64(t - x) * Float64(y / Float64(a - z)))
	t_2 = Float64(t / Float64(Float64(z - a) / z))
	tmp = 0.0
	if (z <= -2.2e+87)
		tmp = Float64(Float64(-t) / Float64(z / Float64(y - z)));
	elseif (z <= -5.8e+37)
		tmp = Float64(y * Float64(Float64(t - x) / Float64(a - z)));
	elseif (z <= -2.3e-15)
		tmp = t_2;
	elseif (z <= -1.95e-121)
		tmp = t_1;
	elseif (z <= 1.7e-71)
		tmp = Float64(x + Float64(Float64(y * t) / a));
	elseif (z <= 1.12e+163)
		tmp = t_1;
	else
		tmp = t_2;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	t_1 = (t - x) * (y / (a - z));
	t_2 = t / ((z - a) / z);
	tmp = 0.0;
	if (z <= -2.2e+87)
		tmp = -t / (z / (y - z));
	elseif (z <= -5.8e+37)
		tmp = y * ((t - x) / (a - z));
	elseif (z <= -2.3e-15)
		tmp = t_2;
	elseif (z <= -1.95e-121)
		tmp = t_1;
	elseif (z <= 1.7e-71)
		tmp = x + ((y * t) / a);
	elseif (z <= 1.12e+163)
		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[(t - x), $MachinePrecision] * N[(y / N[(a - z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(t / N[(N[(z - a), $MachinePrecision] / z), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -2.2e+87], N[((-t) / N[(z / N[(y - z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -5.8e+37], N[(y * N[(N[(t - x), $MachinePrecision] / N[(a - z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -2.3e-15], t$95$2, If[LessEqual[z, -1.95e-121], t$95$1, If[LessEqual[z, 1.7e-71], N[(x + N[(N[(y * t), $MachinePrecision] / a), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.12e+163], t$95$1, t$95$2]]]]]]]]

Derivation

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

Alternative 7: 38.6% accurate, 0.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := t \cdot \frac{y - z}{a}\\ \mathbf{if}\;z \leq -1.35 \cdot 10^{-13}:\\ \;\;\;\;t\\ \mathbf{elif}\;z \leq -5.5 \cdot 10^{-106}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq -2.3 \cdot 10^{-300}:\\ \;\;\;\;x\\ \mathbf{elif}\;z \leq 3.6 \cdot 10^{-217}:\\ \;\;\;\;\frac{t}{\frac{a}{y}}\\ \mathbf{elif}\;z \leq 3.7 \cdot 10^{-116}:\\ \;\;\;\;x\\ \mathbf{elif}\;z \leq 2.8 \cdot 10^{-28}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq 2 \cdot 10^{+31}:\\ \;\;\;\;x\\ \mathbf{else}:\\ \;\;\;\;t\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (let* ((t_1 (* t (/ (- y z) a))))
   (if (<= z -1.35e-13)
     t
     (if (<= z -5.5e-106)
       t_1
       (if (<= z -2.3e-300)
         x
         (if (<= z 3.6e-217)
           (/ t (/ a y))
           (if (<= z 3.7e-116)
             x
             (if (<= z 2.8e-28) t_1 (if (<= z 2e+31) x t)))))))))

C

double code(double x, double y, double z, double t, double a) {
	double t_1 = t * ((y - z) / a);
	double tmp;
	if (z <= -1.35e-13) {
		tmp = t;
	} else if (z <= -5.5e-106) {
		tmp = t_1;
	} else if (z <= -2.3e-300) {
		tmp = x;
	} else if (z <= 3.6e-217) {
		tmp = t / (a / y);
	} else if (z <= 3.7e-116) {
		tmp = x;
	} else if (z <= 2.8e-28) {
		tmp = t_1;
	} else if (z <= 2e+31) {
		tmp = x;
	} else {
		tmp = 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 = t * ((y - z) / a)
    if (z <= (-1.35d-13)) then
        tmp = t
    else if (z <= (-5.5d-106)) then
        tmp = t_1
    else if (z <= (-2.3d-300)) then
        tmp = x
    else if (z <= 3.6d-217) then
        tmp = t / (a / y)
    else if (z <= 3.7d-116) then
        tmp = x
    else if (z <= 2.8d-28) then
        tmp = t_1
    else if (z <= 2d+31) then
        tmp = x
    else
        tmp = 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 = t * ((y - z) / a);
	double tmp;
	if (z <= -1.35e-13) {
		tmp = t;
	} else if (z <= -5.5e-106) {
		tmp = t_1;
	} else if (z <= -2.3e-300) {
		tmp = x;
	} else if (z <= 3.6e-217) {
		tmp = t / (a / y);
	} else if (z <= 3.7e-116) {
		tmp = x;
	} else if (z <= 2.8e-28) {
		tmp = t_1;
	} else if (z <= 2e+31) {
		tmp = x;
	} else {
		tmp = t;
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	t_1 = t * ((y - z) / a)
	tmp = 0
	if z <= -1.35e-13:
		tmp = t
	elif z <= -5.5e-106:
		tmp = t_1
	elif z <= -2.3e-300:
		tmp = x
	elif z <= 3.6e-217:
		tmp = t / (a / y)
	elif z <= 3.7e-116:
		tmp = x
	elif z <= 2.8e-28:
		tmp = t_1
	elif z <= 2e+31:
		tmp = x
	else:
		tmp = t
	return tmp

Julia

function code(x, y, z, t, a)
	t_1 = Float64(t * Float64(Float64(y - z) / a))
	tmp = 0.0
	if (z <= -1.35e-13)
		tmp = t;
	elseif (z <= -5.5e-106)
		tmp = t_1;
	elseif (z <= -2.3e-300)
		tmp = x;
	elseif (z <= 3.6e-217)
		tmp = Float64(t / Float64(a / y));
	elseif (z <= 3.7e-116)
		tmp = x;
	elseif (z <= 2.8e-28)
		tmp = t_1;
	elseif (z <= 2e+31)
		tmp = x;
	else
		tmp = t;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	t_1 = t * ((y - z) / a);
	tmp = 0.0;
	if (z <= -1.35e-13)
		tmp = t;
	elseif (z <= -5.5e-106)
		tmp = t_1;
	elseif (z <= -2.3e-300)
		tmp = x;
	elseif (z <= 3.6e-217)
		tmp = t / (a / y);
	elseif (z <= 3.7e-116)
		tmp = x;
	elseif (z <= 2.8e-28)
		tmp = t_1;
	elseif (z <= 2e+31)
		tmp = x;
	else
		tmp = t;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := Block[{t$95$1 = N[(t * N[(N[(y - z), $MachinePrecision] / a), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -1.35e-13], t, If[LessEqual[z, -5.5e-106], t$95$1, If[LessEqual[z, -2.3e-300], x, If[LessEqual[z, 3.6e-217], N[(t / N[(a / y), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 3.7e-116], x, If[LessEqual[z, 2.8e-28], t$95$1, If[LessEqual[z, 2e+31], x, t]]]]]]]]

Derivation

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

Alternative 8: 60.5% accurate, 0.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := x + \left(t - x\right) \cdot \frac{y}{a}\\ \mathbf{if}\;a \leq -4.5 \cdot 10^{-52}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;a \leq -1.2 \cdot 10^{-273}:\\ \;\;\;\;y \cdot \frac{t - x}{a - z}\\ \mathbf{elif}\;a \leq 7 \cdot 10^{-287}:\\ \;\;\;\;\frac{-t}{\frac{z}{y - z}}\\ \mathbf{elif}\;a \leq 1.22 \cdot 10^{-170}:\\ \;\;\;\;\left(t - x\right) \cdot \frac{y}{a - z}\\ \mathbf{elif}\;a \leq 2.55 \cdot 10^{+33}:\\ \;\;\;\;t - y \cdot \frac{t}{z}\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (let* ((t_1 (+ x (* (- t x) (/ y a)))))
   (if (<= a -4.5e-52)
     t_1
     (if (<= a -1.2e-273)
       (* y (/ (- t x) (- a z)))
       (if (<= a 7e-287)
         (/ (- t) (/ z (- y z)))
         (if (<= a 1.22e-170)
           (* (- t x) (/ y (- a z)))
           (if (<= a 2.55e+33) (- t (* y (/ t z))) t_1)))))))

C

double code(double x, double y, double z, double t, double a) {
	double t_1 = x + ((t - x) * (y / a));
	double tmp;
	if (a <= -4.5e-52) {
		tmp = t_1;
	} else if (a <= -1.2e-273) {
		tmp = y * ((t - x) / (a - z));
	} else if (a <= 7e-287) {
		tmp = -t / (z / (y - z));
	} else if (a <= 1.22e-170) {
		tmp = (t - x) * (y / (a - z));
	} else if (a <= 2.55e+33) {
		tmp = t - (y * (t / z));
	} 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 + ((t - x) * (y / a))
    if (a <= (-4.5d-52)) then
        tmp = t_1
    else if (a <= (-1.2d-273)) then
        tmp = y * ((t - x) / (a - z))
    else if (a <= 7d-287) then
        tmp = -t / (z / (y - z))
    else if (a <= 1.22d-170) then
        tmp = (t - x) * (y / (a - z))
    else if (a <= 2.55d+33) then
        tmp = t - (y * (t / z))
    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 + ((t - x) * (y / a));
	double tmp;
	if (a <= -4.5e-52) {
		tmp = t_1;
	} else if (a <= -1.2e-273) {
		tmp = y * ((t - x) / (a - z));
	} else if (a <= 7e-287) {
		tmp = -t / (z / (y - z));
	} else if (a <= 1.22e-170) {
		tmp = (t - x) * (y / (a - z));
	} else if (a <= 2.55e+33) {
		tmp = t - (y * (t / z));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	t_1 = x + ((t - x) * (y / a))
	tmp = 0
	if a <= -4.5e-52:
		tmp = t_1
	elif a <= -1.2e-273:
		tmp = y * ((t - x) / (a - z))
	elif a <= 7e-287:
		tmp = -t / (z / (y - z))
	elif a <= 1.22e-170:
		tmp = (t - x) * (y / (a - z))
	elif a <= 2.55e+33:
		tmp = t - (y * (t / z))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a)
	t_1 = Float64(x + Float64(Float64(t - x) * Float64(y / a)))
	tmp = 0.0
	if (a <= -4.5e-52)
		tmp = t_1;
	elseif (a <= -1.2e-273)
		tmp = Float64(y * Float64(Float64(t - x) / Float64(a - z)));
	elseif (a <= 7e-287)
		tmp = Float64(Float64(-t) / Float64(z / Float64(y - z)));
	elseif (a <= 1.22e-170)
		tmp = Float64(Float64(t - x) * Float64(y / Float64(a - z)));
	elseif (a <= 2.55e+33)
		tmp = Float64(t - Float64(y * Float64(t / z)));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	t_1 = x + ((t - x) * (y / a));
	tmp = 0.0;
	if (a <= -4.5e-52)
		tmp = t_1;
	elseif (a <= -1.2e-273)
		tmp = y * ((t - x) / (a - z));
	elseif (a <= 7e-287)
		tmp = -t / (z / (y - z));
	elseif (a <= 1.22e-170)
		tmp = (t - x) * (y / (a - z));
	elseif (a <= 2.55e+33)
		tmp = t - (y * (t / z));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := Block[{t$95$1 = N[(x + N[(N[(t - x), $MachinePrecision] * N[(y / a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[a, -4.5e-52], t$95$1, If[LessEqual[a, -1.2e-273], N[(y * N[(N[(t - x), $MachinePrecision] / N[(a - z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 7e-287], N[((-t) / N[(z / N[(y - z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 1.22e-170], N[(N[(t - x), $MachinePrecision] * N[(y / N[(a - z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[a, 2.55e+33], N[(t - N[(y * N[(t / z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]]

Derivation

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

Alternative 9: 38.4% accurate, 0.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := t \cdot \frac{y}{a}\\ \mathbf{if}\;z \leq -6.5 \cdot 10^{-33}:\\ \;\;\;\;t\\ \mathbf{elif}\;z \leq -1.02 \cdot 10^{-105}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq -1.65 \cdot 10^{-304}:\\ \;\;\;\;x\\ \mathbf{elif}\;z \leq 2.9 \cdot 10^{-219}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq 1.2 \cdot 10^{-105}:\\ \;\;\;\;x\\ \mathbf{elif}\;z \leq 4.5 \cdot 10^{-75}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq 4.3 \cdot 10^{+30}:\\ \;\;\;\;x\\ \mathbf{else}:\\ \;\;\;\;t\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (let* ((t_1 (* t (/ y a))))
   (if (<= z -6.5e-33)
     t
     (if (<= z -1.02e-105)
       t_1
       (if (<= z -1.65e-304)
         x
         (if (<= z 2.9e-219)
           t_1
           (if (<= z 1.2e-105)
             x
             (if (<= z 4.5e-75) t_1 (if (<= z 4.3e+30) x t)))))))))

C

double code(double x, double y, double z, double t, double a) {
	double t_1 = t * (y / a);
	double tmp;
	if (z <= -6.5e-33) {
		tmp = t;
	} else if (z <= -1.02e-105) {
		tmp = t_1;
	} else if (z <= -1.65e-304) {
		tmp = x;
	} else if (z <= 2.9e-219) {
		tmp = t_1;
	} else if (z <= 1.2e-105) {
		tmp = x;
	} else if (z <= 4.5e-75) {
		tmp = t_1;
	} else if (z <= 4.3e+30) {
		tmp = x;
	} else {
		tmp = 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 = t * (y / a)
    if (z <= (-6.5d-33)) then
        tmp = t
    else if (z <= (-1.02d-105)) then
        tmp = t_1
    else if (z <= (-1.65d-304)) then
        tmp = x
    else if (z <= 2.9d-219) then
        tmp = t_1
    else if (z <= 1.2d-105) then
        tmp = x
    else if (z <= 4.5d-75) then
        tmp = t_1
    else if (z <= 4.3d+30) then
        tmp = x
    else
        tmp = 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 = t * (y / a);
	double tmp;
	if (z <= -6.5e-33) {
		tmp = t;
	} else if (z <= -1.02e-105) {
		tmp = t_1;
	} else if (z <= -1.65e-304) {
		tmp = x;
	} else if (z <= 2.9e-219) {
		tmp = t_1;
	} else if (z <= 1.2e-105) {
		tmp = x;
	} else if (z <= 4.5e-75) {
		tmp = t_1;
	} else if (z <= 4.3e+30) {
		tmp = x;
	} else {
		tmp = t;
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	t_1 = t * (y / a)
	tmp = 0
	if z <= -6.5e-33:
		tmp = t
	elif z <= -1.02e-105:
		tmp = t_1
	elif z <= -1.65e-304:
		tmp = x
	elif z <= 2.9e-219:
		tmp = t_1
	elif z <= 1.2e-105:
		tmp = x
	elif z <= 4.5e-75:
		tmp = t_1
	elif z <= 4.3e+30:
		tmp = x
	else:
		tmp = t
	return tmp

Julia

function code(x, y, z, t, a)
	t_1 = Float64(t * Float64(y / a))
	tmp = 0.0
	if (z <= -6.5e-33)
		tmp = t;
	elseif (z <= -1.02e-105)
		tmp = t_1;
	elseif (z <= -1.65e-304)
		tmp = x;
	elseif (z <= 2.9e-219)
		tmp = t_1;
	elseif (z <= 1.2e-105)
		tmp = x;
	elseif (z <= 4.5e-75)
		tmp = t_1;
	elseif (z <= 4.3e+30)
		tmp = x;
	else
		tmp = t;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	t_1 = t * (y / a);
	tmp = 0.0;
	if (z <= -6.5e-33)
		tmp = t;
	elseif (z <= -1.02e-105)
		tmp = t_1;
	elseif (z <= -1.65e-304)
		tmp = x;
	elseif (z <= 2.9e-219)
		tmp = t_1;
	elseif (z <= 1.2e-105)
		tmp = x;
	elseif (z <= 4.5e-75)
		tmp = t_1;
	elseif (z <= 4.3e+30)
		tmp = x;
	else
		tmp = t;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := Block[{t$95$1 = N[(t * N[(y / a), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -6.5e-33], t, If[LessEqual[z, -1.02e-105], t$95$1, If[LessEqual[z, -1.65e-304], x, If[LessEqual[z, 2.9e-219], t$95$1, If[LessEqual[z, 1.2e-105], x, If[LessEqual[z, 4.5e-75], t$95$1, If[LessEqual[z, 4.3e+30], x, t]]]]]]]]

Derivation

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

Alternative 10: 38.3% accurate, 0.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := y \cdot \frac{t}{a}\\ \mathbf{if}\;z \leq -3 \cdot 10^{-33}:\\ \;\;\;\;t\\ \mathbf{elif}\;z \leq -8.8 \cdot 10^{-106}:\\ \;\;\;\;t \cdot \frac{y}{a}\\ \mathbf{elif}\;z \leq -2.9 \cdot 10^{-302}:\\ \;\;\;\;x\\ \mathbf{elif}\;z \leq 2.1 \cdot 10^{-218}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq 5.3 \cdot 10^{-98}:\\ \;\;\;\;x\\ \mathbf{elif}\;z \leq 8.8 \cdot 10^{-75}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq 5.2 \cdot 10^{+29}:\\ \;\;\;\;x\\ \mathbf{else}:\\ \;\;\;\;t\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (let* ((t_1 (* y (/ t a))))
   (if (<= z -3e-33)
     t
     (if (<= z -8.8e-106)
       (* t (/ y a))
       (if (<= z -2.9e-302)
         x
         (if (<= z 2.1e-218)
           t_1
           (if (<= z 5.3e-98)
             x
             (if (<= z 8.8e-75) t_1 (if (<= z 5.2e+29) x t)))))))))

C

double code(double x, double y, double z, double t, double a) {
	double t_1 = y * (t / a);
	double tmp;
	if (z <= -3e-33) {
		tmp = t;
	} else if (z <= -8.8e-106) {
		tmp = t * (y / a);
	} else if (z <= -2.9e-302) {
		tmp = x;
	} else if (z <= 2.1e-218) {
		tmp = t_1;
	} else if (z <= 5.3e-98) {
		tmp = x;
	} else if (z <= 8.8e-75) {
		tmp = t_1;
	} else if (z <= 5.2e+29) {
		tmp = x;
	} else {
		tmp = 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 = y * (t / a)
    if (z <= (-3d-33)) then
        tmp = t
    else if (z <= (-8.8d-106)) then
        tmp = t * (y / a)
    else if (z <= (-2.9d-302)) then
        tmp = x
    else if (z <= 2.1d-218) then
        tmp = t_1
    else if (z <= 5.3d-98) then
        tmp = x
    else if (z <= 8.8d-75) then
        tmp = t_1
    else if (z <= 5.2d+29) then
        tmp = x
    else
        tmp = 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 = y * (t / a);
	double tmp;
	if (z <= -3e-33) {
		tmp = t;
	} else if (z <= -8.8e-106) {
		tmp = t * (y / a);
	} else if (z <= -2.9e-302) {
		tmp = x;
	} else if (z <= 2.1e-218) {
		tmp = t_1;
	} else if (z <= 5.3e-98) {
		tmp = x;
	} else if (z <= 8.8e-75) {
		tmp = t_1;
	} else if (z <= 5.2e+29) {
		tmp = x;
	} else {
		tmp = t;
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	t_1 = y * (t / a)
	tmp = 0
	if z <= -3e-33:
		tmp = t
	elif z <= -8.8e-106:
		tmp = t * (y / a)
	elif z <= -2.9e-302:
		tmp = x
	elif z <= 2.1e-218:
		tmp = t_1
	elif z <= 5.3e-98:
		tmp = x
	elif z <= 8.8e-75:
		tmp = t_1
	elif z <= 5.2e+29:
		tmp = x
	else:
		tmp = t
	return tmp

Julia

function code(x, y, z, t, a)
	t_1 = Float64(y * Float64(t / a))
	tmp = 0.0
	if (z <= -3e-33)
		tmp = t;
	elseif (z <= -8.8e-106)
		tmp = Float64(t * Float64(y / a));
	elseif (z <= -2.9e-302)
		tmp = x;
	elseif (z <= 2.1e-218)
		tmp = t_1;
	elseif (z <= 5.3e-98)
		tmp = x;
	elseif (z <= 8.8e-75)
		tmp = t_1;
	elseif (z <= 5.2e+29)
		tmp = x;
	else
		tmp = t;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	t_1 = y * (t / a);
	tmp = 0.0;
	if (z <= -3e-33)
		tmp = t;
	elseif (z <= -8.8e-106)
		tmp = t * (y / a);
	elseif (z <= -2.9e-302)
		tmp = x;
	elseif (z <= 2.1e-218)
		tmp = t_1;
	elseif (z <= 5.3e-98)
		tmp = x;
	elseif (z <= 8.8e-75)
		tmp = t_1;
	elseif (z <= 5.2e+29)
		tmp = x;
	else
		tmp = t;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := Block[{t$95$1 = N[(y * N[(t / a), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -3e-33], t, If[LessEqual[z, -8.8e-106], N[(t * N[(y / a), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -2.9e-302], x, If[LessEqual[z, 2.1e-218], t$95$1, If[LessEqual[z, 5.3e-98], x, If[LessEqual[z, 8.8e-75], t$95$1, If[LessEqual[z, 5.2e+29], x, t]]]]]]]]

Derivation

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

Alternative 11: 38.5% accurate, 0.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -6.8 \cdot 10^{-34}:\\ \;\;\;\;t\\ \mathbf{elif}\;z \leq -8.5 \cdot 10^{-106}:\\ \;\;\;\;t \cdot \frac{y}{a}\\ \mathbf{elif}\;z \leq -7.2 \cdot 10^{-299}:\\ \;\;\;\;x\\ \mathbf{elif}\;z \leq 6 \cdot 10^{-217}:\\ \;\;\;\;\frac{t}{\frac{a}{y}}\\ \mathbf{elif}\;z \leq 4.2 \cdot 10^{-99}:\\ \;\;\;\;x\\ \mathbf{elif}\;z \leq 4.1 \cdot 10^{-75}:\\ \;\;\;\;y \cdot \frac{t}{a}\\ \mathbf{elif}\;z \leq 2.8 \cdot 10^{+31}:\\ \;\;\;\;x\\ \mathbf{else}:\\ \;\;\;\;t\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (if (<= z -6.8e-34)
   t
   (if (<= z -8.5e-106)
     (* t (/ y a))
     (if (<= z -7.2e-299)
       x
       (if (<= z 6e-217)
         (/ t (/ a y))
         (if (<= z 4.2e-99)
           x
           (if (<= z 4.1e-75) (* y (/ t a)) (if (<= z 2.8e+31) x t))))))))

C

double code(double x, double y, double z, double t, double a) {
	double tmp;
	if (z <= -6.8e-34) {
		tmp = t;
	} else if (z <= -8.5e-106) {
		tmp = t * (y / a);
	} else if (z <= -7.2e-299) {
		tmp = x;
	} else if (z <= 6e-217) {
		tmp = t / (a / y);
	} else if (z <= 4.2e-99) {
		tmp = x;
	} else if (z <= 4.1e-75) {
		tmp = y * (t / a);
	} else if (z <= 2.8e+31) {
		tmp = x;
	} else {
		tmp = 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 (z <= (-6.8d-34)) then
        tmp = t
    else if (z <= (-8.5d-106)) then
        tmp = t * (y / a)
    else if (z <= (-7.2d-299)) then
        tmp = x
    else if (z <= 6d-217) then
        tmp = t / (a / y)
    else if (z <= 4.2d-99) then
        tmp = x
    else if (z <= 4.1d-75) then
        tmp = y * (t / a)
    else if (z <= 2.8d+31) then
        tmp = x
    else
        tmp = 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 (z <= -6.8e-34) {
		tmp = t;
	} else if (z <= -8.5e-106) {
		tmp = t * (y / a);
	} else if (z <= -7.2e-299) {
		tmp = x;
	} else if (z <= 6e-217) {
		tmp = t / (a / y);
	} else if (z <= 4.2e-99) {
		tmp = x;
	} else if (z <= 4.1e-75) {
		tmp = y * (t / a);
	} else if (z <= 2.8e+31) {
		tmp = x;
	} else {
		tmp = t;
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	tmp = 0
	if z <= -6.8e-34:
		tmp = t
	elif z <= -8.5e-106:
		tmp = t * (y / a)
	elif z <= -7.2e-299:
		tmp = x
	elif z <= 6e-217:
		tmp = t / (a / y)
	elif z <= 4.2e-99:
		tmp = x
	elif z <= 4.1e-75:
		tmp = y * (t / a)
	elif z <= 2.8e+31:
		tmp = x
	else:
		tmp = t
	return tmp

Julia

function code(x, y, z, t, a)
	tmp = 0.0
	if (z <= -6.8e-34)
		tmp = t;
	elseif (z <= -8.5e-106)
		tmp = Float64(t * Float64(y / a));
	elseif (z <= -7.2e-299)
		tmp = x;
	elseif (z <= 6e-217)
		tmp = Float64(t / Float64(a / y));
	elseif (z <= 4.2e-99)
		tmp = x;
	elseif (z <= 4.1e-75)
		tmp = Float64(y * Float64(t / a));
	elseif (z <= 2.8e+31)
		tmp = x;
	else
		tmp = t;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	tmp = 0.0;
	if (z <= -6.8e-34)
		tmp = t;
	elseif (z <= -8.5e-106)
		tmp = t * (y / a);
	elseif (z <= -7.2e-299)
		tmp = x;
	elseif (z <= 6e-217)
		tmp = t / (a / y);
	elseif (z <= 4.2e-99)
		tmp = x;
	elseif (z <= 4.1e-75)
		tmp = y * (t / a);
	elseif (z <= 2.8e+31)
		tmp = x;
	else
		tmp = t;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := If[LessEqual[z, -6.8e-34], t, If[LessEqual[z, -8.5e-106], N[(t * N[(y / a), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -7.2e-299], x, If[LessEqual[z, 6e-217], N[(t / N[(a / y), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 4.2e-99], x, If[LessEqual[z, 4.1e-75], N[(y * N[(t / a), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 2.8e+31], x, t]]]]]]]

Derivation

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

Alternative 12: 38.4% accurate, 0.7× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -4.2 \cdot 10^{-34}:\\ \;\;\;\;t\\ \mathbf{elif}\;z \leq -1.6 \cdot 10^{-105}:\\ \;\;\;\;t \cdot \frac{y}{a}\\ \mathbf{elif}\;z \leq -2 \cdot 10^{-300}:\\ \;\;\;\;x\\ \mathbf{elif}\;z \leq 3.5 \cdot 10^{-216}:\\ \;\;\;\;\frac{t}{\frac{a}{y}}\\ \mathbf{elif}\;z \leq 2 \cdot 10^{-96}:\\ \;\;\;\;x\\ \mathbf{elif}\;z \leq 1.9 \cdot 10^{-74}:\\ \;\;\;\;\frac{y \cdot t}{a}\\ \mathbf{elif}\;z \leq 1.8 \cdot 10^{+29}:\\ \;\;\;\;x\\ \mathbf{else}:\\ \;\;\;\;t\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (if (<= z -4.2e-34)
   t
   (if (<= z -1.6e-105)
     (* t (/ y a))
     (if (<= z -2e-300)
       x
       (if (<= z 3.5e-216)
         (/ t (/ a y))
         (if (<= z 2e-96)
           x
           (if (<= z 1.9e-74) (/ (* y t) a) (if (<= z 1.8e+29) x t))))))))

C

double code(double x, double y, double z, double t, double a) {
	double tmp;
	if (z <= -4.2e-34) {
		tmp = t;
	} else if (z <= -1.6e-105) {
		tmp = t * (y / a);
	} else if (z <= -2e-300) {
		tmp = x;
	} else if (z <= 3.5e-216) {
		tmp = t / (a / y);
	} else if (z <= 2e-96) {
		tmp = x;
	} else if (z <= 1.9e-74) {
		tmp = (y * t) / a;
	} else if (z <= 1.8e+29) {
		tmp = x;
	} else {
		tmp = 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 (z <= (-4.2d-34)) then
        tmp = t
    else if (z <= (-1.6d-105)) then
        tmp = t * (y / a)
    else if (z <= (-2d-300)) then
        tmp = x
    else if (z <= 3.5d-216) then
        tmp = t / (a / y)
    else if (z <= 2d-96) then
        tmp = x
    else if (z <= 1.9d-74) then
        tmp = (y * t) / a
    else if (z <= 1.8d+29) then
        tmp = x
    else
        tmp = 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 (z <= -4.2e-34) {
		tmp = t;
	} else if (z <= -1.6e-105) {
		tmp = t * (y / a);
	} else if (z <= -2e-300) {
		tmp = x;
	} else if (z <= 3.5e-216) {
		tmp = t / (a / y);
	} else if (z <= 2e-96) {
		tmp = x;
	} else if (z <= 1.9e-74) {
		tmp = (y * t) / a;
	} else if (z <= 1.8e+29) {
		tmp = x;
	} else {
		tmp = t;
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	tmp = 0
	if z <= -4.2e-34:
		tmp = t
	elif z <= -1.6e-105:
		tmp = t * (y / a)
	elif z <= -2e-300:
		tmp = x
	elif z <= 3.5e-216:
		tmp = t / (a / y)
	elif z <= 2e-96:
		tmp = x
	elif z <= 1.9e-74:
		tmp = (y * t) / a
	elif z <= 1.8e+29:
		tmp = x
	else:
		tmp = t
	return tmp

Julia

function code(x, y, z, t, a)
	tmp = 0.0
	if (z <= -4.2e-34)
		tmp = t;
	elseif (z <= -1.6e-105)
		tmp = Float64(t * Float64(y / a));
	elseif (z <= -2e-300)
		tmp = x;
	elseif (z <= 3.5e-216)
		tmp = Float64(t / Float64(a / y));
	elseif (z <= 2e-96)
		tmp = x;
	elseif (z <= 1.9e-74)
		tmp = Float64(Float64(y * t) / a);
	elseif (z <= 1.8e+29)
		tmp = x;
	else
		tmp = t;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	tmp = 0.0;
	if (z <= -4.2e-34)
		tmp = t;
	elseif (z <= -1.6e-105)
		tmp = t * (y / a);
	elseif (z <= -2e-300)
		tmp = x;
	elseif (z <= 3.5e-216)
		tmp = t / (a / y);
	elseif (z <= 2e-96)
		tmp = x;
	elseif (z <= 1.9e-74)
		tmp = (y * t) / a;
	elseif (z <= 1.8e+29)
		tmp = x;
	else
		tmp = t;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := If[LessEqual[z, -4.2e-34], t, If[LessEqual[z, -1.6e-105], N[(t * N[(y / a), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -2e-300], x, If[LessEqual[z, 3.5e-216], N[(t / N[(a / y), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 2e-96], x, If[LessEqual[z, 1.9e-74], N[(N[(y * t), $MachinePrecision] / a), $MachinePrecision], If[LessEqual[z, 1.8e+29], x, t]]]]]]]

Derivation

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

Alternative 13: 62.7% accurate, 0.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := t + \left(a - y\right) \cdot \frac{t}{z}\\ \mathbf{if}\;z \leq -3.6 \cdot 10^{+90}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq -4.4 \cdot 10^{+35}:\\ \;\;\;\;y \cdot \frac{t - x}{a - z}\\ \mathbf{elif}\;z \leq -2.05 \cdot 10^{-19}:\\ \;\;\;\;\frac{t}{\frac{z - a}{z}}\\ \mathbf{elif}\;z \leq 4.1 \cdot 10^{+34}:\\ \;\;\;\;x + \left(t - x\right) \cdot \frac{y}{a}\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (let* ((t_1 (+ t (* (- a y) (/ t z)))))
   (if (<= z -3.6e+90)
     t_1
     (if (<= z -4.4e+35)
       (* y (/ (- t x) (- a z)))
       (if (<= z -2.05e-19)
         (/ t (/ (- z a) z))
         (if (<= z 4.1e+34) (+ x (* (- t x) (/ y a))) t_1))))))

C

double code(double x, double y, double z, double t, double a) {
	double t_1 = t + ((a - y) * (t / z));
	double tmp;
	if (z <= -3.6e+90) {
		tmp = t_1;
	} else if (z <= -4.4e+35) {
		tmp = y * ((t - x) / (a - z));
	} else if (z <= -2.05e-19) {
		tmp = t / ((z - a) / z);
	} else if (z <= 4.1e+34) {
		tmp = x + ((t - x) * (y / a));
	} 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 = t + ((a - y) * (t / z))
    if (z <= (-3.6d+90)) then
        tmp = t_1
    else if (z <= (-4.4d+35)) then
        tmp = y * ((t - x) / (a - z))
    else if (z <= (-2.05d-19)) then
        tmp = t / ((z - a) / z)
    else if (z <= 4.1d+34) then
        tmp = x + ((t - x) * (y / a))
    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 = t + ((a - y) * (t / z));
	double tmp;
	if (z <= -3.6e+90) {
		tmp = t_1;
	} else if (z <= -4.4e+35) {
		tmp = y * ((t - x) / (a - z));
	} else if (z <= -2.05e-19) {
		tmp = t / ((z - a) / z);
	} else if (z <= 4.1e+34) {
		tmp = x + ((t - x) * (y / a));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	t_1 = t + ((a - y) * (t / z))
	tmp = 0
	if z <= -3.6e+90:
		tmp = t_1
	elif z <= -4.4e+35:
		tmp = y * ((t - x) / (a - z))
	elif z <= -2.05e-19:
		tmp = t / ((z - a) / z)
	elif z <= 4.1e+34:
		tmp = x + ((t - x) * (y / a))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a)
	t_1 = Float64(t + Float64(Float64(a - y) * Float64(t / z)))
	tmp = 0.0
	if (z <= -3.6e+90)
		tmp = t_1;
	elseif (z <= -4.4e+35)
		tmp = Float64(y * Float64(Float64(t - x) / Float64(a - z)));
	elseif (z <= -2.05e-19)
		tmp = Float64(t / Float64(Float64(z - a) / z));
	elseif (z <= 4.1e+34)
		tmp = Float64(x + Float64(Float64(t - x) * Float64(y / a)));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	t_1 = t + ((a - y) * (t / z));
	tmp = 0.0;
	if (z <= -3.6e+90)
		tmp = t_1;
	elseif (z <= -4.4e+35)
		tmp = y * ((t - x) / (a - z));
	elseif (z <= -2.05e-19)
		tmp = t / ((z - a) / z);
	elseif (z <= 4.1e+34)
		tmp = x + ((t - x) * (y / a));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := Block[{t$95$1 = N[(t + N[(N[(a - y), $MachinePrecision] * N[(t / z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -3.6e+90], t$95$1, If[LessEqual[z, -4.4e+35], N[(y * N[(N[(t - x), $MachinePrecision] / N[(a - z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -2.05e-19], N[(t / N[(N[(z - a), $MachinePrecision] / z), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 4.1e+34], N[(x + N[(N[(t - x), $MachinePrecision] * N[(y / a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]

Derivation

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

Alternative 14: 74.7% accurate, 0.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;a \leq -2.7 \cdot 10^{+16}:\\ \;\;\;\;x - \frac{y - z}{a} \cdot \left(x - t\right)\\ \mathbf{elif}\;a \leq -3.3 \cdot 10^{-96} \lor \neg \left(a \leq 6.4 \cdot 10^{-117}\right):\\ \;\;\;\;x - \frac{z - y}{\frac{a - z}{t}}\\ \mathbf{else}:\\ \;\;\;\;t + \frac{y}{z} \cdot \left(x - t\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (if (<= a -2.7e+16)
   (- x (* (/ (- y z) a) (- x t)))
   (if (or (<= a -3.3e-96) (not (<= a 6.4e-117)))
     (- x (/ (- z y) (/ (- a z) t)))
     (+ t (* (/ y z) (- x t))))))

C

double code(double x, double y, double z, double t, double a) {
	double tmp;
	if (a <= -2.7e+16) {
		tmp = x - (((y - z) / a) * (x - t));
	} else if ((a <= -3.3e-96) || !(a <= 6.4e-117)) {
		tmp = x - ((z - y) / ((a - z) / t));
	} else {
		tmp = t + ((y / z) * (x - 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 <= (-2.7d+16)) then
        tmp = x - (((y - z) / a) * (x - t))
    else if ((a <= (-3.3d-96)) .or. (.not. (a <= 6.4d-117))) then
        tmp = x - ((z - y) / ((a - z) / t))
    else
        tmp = t + ((y / z) * (x - t))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a) {
	double tmp;
	if (a <= -2.7e+16) {
		tmp = x - (((y - z) / a) * (x - t));
	} else if ((a <= -3.3e-96) || !(a <= 6.4e-117)) {
		tmp = x - ((z - y) / ((a - z) / t));
	} else {
		tmp = t + ((y / z) * (x - t));
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	tmp = 0
	if a <= -2.7e+16:
		tmp = x - (((y - z) / a) * (x - t))
	elif (a <= -3.3e-96) or not (a <= 6.4e-117):
		tmp = x - ((z - y) / ((a - z) / t))
	else:
		tmp = t + ((y / z) * (x - t))
	return tmp

Julia

function code(x, y, z, t, a)
	tmp = 0.0
	if (a <= -2.7e+16)
		tmp = Float64(x - Float64(Float64(Float64(y - z) / a) * Float64(x - t)));
	elseif ((a <= -3.3e-96) || !(a <= 6.4e-117))
		tmp = Float64(x - Float64(Float64(z - y) / Float64(Float64(a - z) / t)));
	else
		tmp = Float64(t + Float64(Float64(y / z) * Float64(x - t)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	tmp = 0.0;
	if (a <= -2.7e+16)
		tmp = x - (((y - z) / a) * (x - t));
	elseif ((a <= -3.3e-96) || ~((a <= 6.4e-117)))
		tmp = x - ((z - y) / ((a - z) / t));
	else
		tmp = t + ((y / z) * (x - t));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := If[LessEqual[a, -2.7e+16], N[(x - N[(N[(N[(y - z), $MachinePrecision] / a), $MachinePrecision] * N[(x - t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[Or[LessEqual[a, -3.3e-96], N[Not[LessEqual[a, 6.4e-117]], $MachinePrecision]], N[(x - N[(N[(z - y), $MachinePrecision] / N[(N[(a - z), $MachinePrecision] / t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(t + N[(N[(y / z), $MachinePrecision] * N[(x - t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]

Derivation

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

Alternative 15: 53.0% accurate, 0.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := t - y \cdot \frac{t}{z}\\ \mathbf{if}\;z \leq -4 \cdot 10^{+81}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq -8.5 \cdot 10^{+48}:\\ \;\;\;\;\frac{x \cdot y}{z - a}\\ \mathbf{elif}\;z \leq -1.7 \cdot 10^{-33} \lor \neg \left(z \leq 1.4 \cdot 10^{-26}\right):\\ \;\;\;\;t_1\\ \mathbf{else}:\\ \;\;\;\;x + \frac{y \cdot t}{a}\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (let* ((t_1 (- t (* y (/ t z)))))
   (if (<= z -4e+81)
     t_1
     (if (<= z -8.5e+48)
       (/ (* x y) (- z a))
       (if (or (<= z -1.7e-33) (not (<= z 1.4e-26)))
         t_1
         (+ x (/ (* y t) a)))))))

C

double code(double x, double y, double z, double t, double a) {
	double t_1 = t - (y * (t / z));
	double tmp;
	if (z <= -4e+81) {
		tmp = t_1;
	} else if (z <= -8.5e+48) {
		tmp = (x * y) / (z - a);
	} else if ((z <= -1.7e-33) || !(z <= 1.4e-26)) {
		tmp = t_1;
	} else {
		tmp = x + ((y * t) / 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 = t - (y * (t / z))
    if (z <= (-4d+81)) then
        tmp = t_1
    else if (z <= (-8.5d+48)) then
        tmp = (x * y) / (z - a)
    else if ((z <= (-1.7d-33)) .or. (.not. (z <= 1.4d-26))) then
        tmp = t_1
    else
        tmp = x + ((y * t) / 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 = t - (y * (t / z));
	double tmp;
	if (z <= -4e+81) {
		tmp = t_1;
	} else if (z <= -8.5e+48) {
		tmp = (x * y) / (z - a);
	} else if ((z <= -1.7e-33) || !(z <= 1.4e-26)) {
		tmp = t_1;
	} else {
		tmp = x + ((y * t) / a);
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	t_1 = t - (y * (t / z))
	tmp = 0
	if z <= -4e+81:
		tmp = t_1
	elif z <= -8.5e+48:
		tmp = (x * y) / (z - a)
	elif (z <= -1.7e-33) or not (z <= 1.4e-26):
		tmp = t_1
	else:
		tmp = x + ((y * t) / a)
	return tmp

Julia

function code(x, y, z, t, a)
	t_1 = Float64(t - Float64(y * Float64(t / z)))
	tmp = 0.0
	if (z <= -4e+81)
		tmp = t_1;
	elseif (z <= -8.5e+48)
		tmp = Float64(Float64(x * y) / Float64(z - a));
	elseif ((z <= -1.7e-33) || !(z <= 1.4e-26))
		tmp = t_1;
	else
		tmp = Float64(x + Float64(Float64(y * t) / a));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	t_1 = t - (y * (t / z));
	tmp = 0.0;
	if (z <= -4e+81)
		tmp = t_1;
	elseif (z <= -8.5e+48)
		tmp = (x * y) / (z - a);
	elseif ((z <= -1.7e-33) || ~((z <= 1.4e-26)))
		tmp = t_1;
	else
		tmp = x + ((y * t) / a);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := Block[{t$95$1 = N[(t - N[(y * N[(t / z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -4e+81], t$95$1, If[LessEqual[z, -8.5e+48], N[(N[(x * y), $MachinePrecision] / N[(z - a), $MachinePrecision]), $MachinePrecision], If[Or[LessEqual[z, -1.7e-33], N[Not[LessEqual[z, 1.4e-26]], $MachinePrecision]], t$95$1, N[(x + N[(N[(y * t), $MachinePrecision] / a), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

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

Alternative 16: 52.7% accurate, 0.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := t - y \cdot \frac{t}{z}\\ \mathbf{if}\;z \leq -6 \cdot 10^{+86}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq -3.8 \cdot 10^{+38}:\\ \;\;\;\;\frac{x \cdot y}{z - a}\\ \mathbf{elif}\;z \leq -1.65 \cdot 10^{-21}:\\ \;\;\;\;\frac{t}{\frac{z - a}{z}}\\ \mathbf{elif}\;z \leq 1.6 \cdot 10^{-26}:\\ \;\;\;\;x + \frac{y \cdot t}{a}\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (let* ((t_1 (- t (* y (/ t z)))))
   (if (<= z -6e+86)
     t_1
     (if (<= z -3.8e+38)
       (/ (* x y) (- z a))
       (if (<= z -1.65e-21)
         (/ t (/ (- z a) z))
         (if (<= z 1.6e-26) (+ x (/ (* y t) a)) t_1))))))

C

double code(double x, double y, double z, double t, double a) {
	double t_1 = t - (y * (t / z));
	double tmp;
	if (z <= -6e+86) {
		tmp = t_1;
	} else if (z <= -3.8e+38) {
		tmp = (x * y) / (z - a);
	} else if (z <= -1.65e-21) {
		tmp = t / ((z - a) / z);
	} else if (z <= 1.6e-26) {
		tmp = x + ((y * t) / a);
	} 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 = t - (y * (t / z))
    if (z <= (-6d+86)) then
        tmp = t_1
    else if (z <= (-3.8d+38)) then
        tmp = (x * y) / (z - a)
    else if (z <= (-1.65d-21)) then
        tmp = t / ((z - a) / z)
    else if (z <= 1.6d-26) then
        tmp = x + ((y * t) / a)
    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 = t - (y * (t / z));
	double tmp;
	if (z <= -6e+86) {
		tmp = t_1;
	} else if (z <= -3.8e+38) {
		tmp = (x * y) / (z - a);
	} else if (z <= -1.65e-21) {
		tmp = t / ((z - a) / z);
	} else if (z <= 1.6e-26) {
		tmp = x + ((y * t) / a);
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	t_1 = t - (y * (t / z))
	tmp = 0
	if z <= -6e+86:
		tmp = t_1
	elif z <= -3.8e+38:
		tmp = (x * y) / (z - a)
	elif z <= -1.65e-21:
		tmp = t / ((z - a) / z)
	elif z <= 1.6e-26:
		tmp = x + ((y * t) / a)
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a)
	t_1 = Float64(t - Float64(y * Float64(t / z)))
	tmp = 0.0
	if (z <= -6e+86)
		tmp = t_1;
	elseif (z <= -3.8e+38)
		tmp = Float64(Float64(x * y) / Float64(z - a));
	elseif (z <= -1.65e-21)
		tmp = Float64(t / Float64(Float64(z - a) / z));
	elseif (z <= 1.6e-26)
		tmp = Float64(x + Float64(Float64(y * t) / a));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	t_1 = t - (y * (t / z));
	tmp = 0.0;
	if (z <= -6e+86)
		tmp = t_1;
	elseif (z <= -3.8e+38)
		tmp = (x * y) / (z - a);
	elseif (z <= -1.65e-21)
		tmp = t / ((z - a) / z);
	elseif (z <= 1.6e-26)
		tmp = x + ((y * t) / a);
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := Block[{t$95$1 = N[(t - N[(y * N[(t / z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -6e+86], t$95$1, If[LessEqual[z, -3.8e+38], N[(N[(x * y), $MachinePrecision] / N[(z - a), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -1.65e-21], N[(t / N[(N[(z - a), $MachinePrecision] / z), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.6e-26], N[(x + N[(N[(y * t), $MachinePrecision] / a), $MachinePrecision]), $MachinePrecision], t$95$1]]]]]

Derivation

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

Alternative 17: 52.8% accurate, 0.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -4 \cdot 10^{+81}:\\ \;\;\;\;\frac{-t}{\frac{z}{y - z}}\\ \mathbf{elif}\;z \leq -1.4 \cdot 10^{+38}:\\ \;\;\;\;\frac{x \cdot y}{z - a}\\ \mathbf{elif}\;z \leq -9.6 \cdot 10^{-20}:\\ \;\;\;\;\frac{t}{\frac{z - a}{z}}\\ \mathbf{elif}\;z \leq 7 \cdot 10^{-27}:\\ \;\;\;\;x + \frac{y \cdot t}{a}\\ \mathbf{else}:\\ \;\;\;\;t - y \cdot \frac{t}{z}\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (if (<= z -4e+81)
   (/ (- t) (/ z (- y z)))
   (if (<= z -1.4e+38)
     (/ (* x y) (- z a))
     (if (<= z -9.6e-20)
       (/ t (/ (- z a) z))
       (if (<= z 7e-27) (+ x (/ (* y t) a)) (- t (* y (/ t z))))))))

C

double code(double x, double y, double z, double t, double a) {
	double tmp;
	if (z <= -4e+81) {
		tmp = -t / (z / (y - z));
	} else if (z <= -1.4e+38) {
		tmp = (x * y) / (z - a);
	} else if (z <= -9.6e-20) {
		tmp = t / ((z - a) / z);
	} else if (z <= 7e-27) {
		tmp = x + ((y * t) / a);
	} else {
		tmp = t - (y * (t / z));
	}
	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 (z <= (-4d+81)) then
        tmp = -t / (z / (y - z))
    else if (z <= (-1.4d+38)) then
        tmp = (x * y) / (z - a)
    else if (z <= (-9.6d-20)) then
        tmp = t / ((z - a) / z)
    else if (z <= 7d-27) then
        tmp = x + ((y * t) / a)
    else
        tmp = t - (y * (t / z))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a) {
	double tmp;
	if (z <= -4e+81) {
		tmp = -t / (z / (y - z));
	} else if (z <= -1.4e+38) {
		tmp = (x * y) / (z - a);
	} else if (z <= -9.6e-20) {
		tmp = t / ((z - a) / z);
	} else if (z <= 7e-27) {
		tmp = x + ((y * t) / a);
	} else {
		tmp = t - (y * (t / z));
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	tmp = 0
	if z <= -4e+81:
		tmp = -t / (z / (y - z))
	elif z <= -1.4e+38:
		tmp = (x * y) / (z - a)
	elif z <= -9.6e-20:
		tmp = t / ((z - a) / z)
	elif z <= 7e-27:
		tmp = x + ((y * t) / a)
	else:
		tmp = t - (y * (t / z))
	return tmp

Julia

function code(x, y, z, t, a)
	tmp = 0.0
	if (z <= -4e+81)
		tmp = Float64(Float64(-t) / Float64(z / Float64(y - z)));
	elseif (z <= -1.4e+38)
		tmp = Float64(Float64(x * y) / Float64(z - a));
	elseif (z <= -9.6e-20)
		tmp = Float64(t / Float64(Float64(z - a) / z));
	elseif (z <= 7e-27)
		tmp = Float64(x + Float64(Float64(y * t) / a));
	else
		tmp = Float64(t - Float64(y * Float64(t / z)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	tmp = 0.0;
	if (z <= -4e+81)
		tmp = -t / (z / (y - z));
	elseif (z <= -1.4e+38)
		tmp = (x * y) / (z - a);
	elseif (z <= -9.6e-20)
		tmp = t / ((z - a) / z);
	elseif (z <= 7e-27)
		tmp = x + ((y * t) / a);
	else
		tmp = t - (y * (t / z));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := If[LessEqual[z, -4e+81], N[((-t) / N[(z / N[(y - z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -1.4e+38], N[(N[(x * y), $MachinePrecision] / N[(z - a), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -9.6e-20], N[(t / N[(N[(z - a), $MachinePrecision] / z), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 7e-27], N[(x + N[(N[(y * t), $MachinePrecision] / a), $MachinePrecision]), $MachinePrecision], N[(t - N[(y * N[(t / z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]

Derivation

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

Alternative 18: 69.5% accurate, 0.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := t + \frac{y}{z} \cdot \left(x - t\right)\\ \mathbf{if}\;z \leq -1.4 \cdot 10^{+34}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z \leq -1.7 \cdot 10^{-105}:\\ \;\;\;\;\frac{t}{\frac{a - z}{y - z}}\\ \mathbf{elif}\;z \leq 1.75 \cdot 10^{-26}:\\ \;\;\;\;x + \left(t - x\right) \cdot \frac{y}{a}\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (let* ((t_1 (+ t (* (/ y z) (- x t)))))
   (if (<= z -1.4e+34)
     t_1
     (if (<= z -1.7e-105)
       (/ t (/ (- a z) (- y z)))
       (if (<= z 1.75e-26) (+ x (* (- t x) (/ y a))) t_1)))))

C

double code(double x, double y, double z, double t, double a) {
	double t_1 = t + ((y / z) * (x - t));
	double tmp;
	if (z <= -1.4e+34) {
		tmp = t_1;
	} else if (z <= -1.7e-105) {
		tmp = t / ((a - z) / (y - z));
	} else if (z <= 1.75e-26) {
		tmp = x + ((t - x) * (y / a));
	} 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 = t + ((y / z) * (x - t))
    if (z <= (-1.4d+34)) then
        tmp = t_1
    else if (z <= (-1.7d-105)) then
        tmp = t / ((a - z) / (y - z))
    else if (z <= 1.75d-26) then
        tmp = x + ((t - x) * (y / a))
    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 = t + ((y / z) * (x - t));
	double tmp;
	if (z <= -1.4e+34) {
		tmp = t_1;
	} else if (z <= -1.7e-105) {
		tmp = t / ((a - z) / (y - z));
	} else if (z <= 1.75e-26) {
		tmp = x + ((t - x) * (y / a));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	t_1 = t + ((y / z) * (x - t))
	tmp = 0
	if z <= -1.4e+34:
		tmp = t_1
	elif z <= -1.7e-105:
		tmp = t / ((a - z) / (y - z))
	elif z <= 1.75e-26:
		tmp = x + ((t - x) * (y / a))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a)
	t_1 = Float64(t + Float64(Float64(y / z) * Float64(x - t)))
	tmp = 0.0
	if (z <= -1.4e+34)
		tmp = t_1;
	elseif (z <= -1.7e-105)
		tmp = Float64(t / Float64(Float64(a - z) / Float64(y - z)));
	elseif (z <= 1.75e-26)
		tmp = Float64(x + Float64(Float64(t - x) * Float64(y / a)));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	t_1 = t + ((y / z) * (x - t));
	tmp = 0.0;
	if (z <= -1.4e+34)
		tmp = t_1;
	elseif (z <= -1.7e-105)
		tmp = t / ((a - z) / (y - z));
	elseif (z <= 1.75e-26)
		tmp = x + ((t - x) * (y / a));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := Block[{t$95$1 = N[(t + N[(N[(y / z), $MachinePrecision] * N[(x - t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[z, -1.4e+34], t$95$1, If[LessEqual[z, -1.7e-105], N[(t / N[(N[(a - z), $MachinePrecision] / N[(y - z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.75e-26], N[(x + N[(N[(t - x), $MachinePrecision] * N[(y / a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]]

Derivation

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

Alternative 19: 69.1% accurate, 0.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -1.25 \cdot 10^{-11}:\\ \;\;\;\;t - \frac{x}{z} \cdot \left(a - y\right)\\ \mathbf{elif}\;z \leq -2 \cdot 10^{-105}:\\ \;\;\;\;\frac{t}{\frac{a - z}{y - z}}\\ \mathbf{elif}\;z \leq 1.95 \cdot 10^{-26}:\\ \;\;\;\;x + \left(t - x\right) \cdot \frac{y}{a}\\ \mathbf{else}:\\ \;\;\;\;t + \frac{y}{z} \cdot \left(x - t\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (if (<= z -1.25e-11)
   (- t (* (/ x z) (- a y)))
   (if (<= z -2e-105)
     (/ t (/ (- a z) (- y z)))
     (if (<= z 1.95e-26)
       (+ x (* (- t x) (/ y a)))
       (+ t (* (/ y z) (- x t)))))))

C

double code(double x, double y, double z, double t, double a) {
	double tmp;
	if (z <= -1.25e-11) {
		tmp = t - ((x / z) * (a - y));
	} else if (z <= -2e-105) {
		tmp = t / ((a - z) / (y - z));
	} else if (z <= 1.95e-26) {
		tmp = x + ((t - x) * (y / a));
	} else {
		tmp = t + ((y / z) * (x - 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 (z <= (-1.25d-11)) then
        tmp = t - ((x / z) * (a - y))
    else if (z <= (-2d-105)) then
        tmp = t / ((a - z) / (y - z))
    else if (z <= 1.95d-26) then
        tmp = x + ((t - x) * (y / a))
    else
        tmp = t + ((y / z) * (x - t))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a) {
	double tmp;
	if (z <= -1.25e-11) {
		tmp = t - ((x / z) * (a - y));
	} else if (z <= -2e-105) {
		tmp = t / ((a - z) / (y - z));
	} else if (z <= 1.95e-26) {
		tmp = x + ((t - x) * (y / a));
	} else {
		tmp = t + ((y / z) * (x - t));
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	tmp = 0
	if z <= -1.25e-11:
		tmp = t - ((x / z) * (a - y))
	elif z <= -2e-105:
		tmp = t / ((a - z) / (y - z))
	elif z <= 1.95e-26:
		tmp = x + ((t - x) * (y / a))
	else:
		tmp = t + ((y / z) * (x - t))
	return tmp

Julia

function code(x, y, z, t, a)
	tmp = 0.0
	if (z <= -1.25e-11)
		tmp = Float64(t - Float64(Float64(x / z) * Float64(a - y)));
	elseif (z <= -2e-105)
		tmp = Float64(t / Float64(Float64(a - z) / Float64(y - z)));
	elseif (z <= 1.95e-26)
		tmp = Float64(x + Float64(Float64(t - x) * Float64(y / a)));
	else
		tmp = Float64(t + Float64(Float64(y / z) * Float64(x - t)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	tmp = 0.0;
	if (z <= -1.25e-11)
		tmp = t - ((x / z) * (a - y));
	elseif (z <= -2e-105)
		tmp = t / ((a - z) / (y - z));
	elseif (z <= 1.95e-26)
		tmp = x + ((t - x) * (y / a));
	else
		tmp = t + ((y / z) * (x - t));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := If[LessEqual[z, -1.25e-11], N[(t - N[(N[(x / z), $MachinePrecision] * N[(a - y), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, -2e-105], N[(t / N[(N[(a - z), $MachinePrecision] / N[(y - z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 1.95e-26], N[(x + N[(N[(t - x), $MachinePrecision] * N[(y / a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(t + N[(N[(y / z), $MachinePrecision] * N[(x - t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]

Derivation

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

Alternative 20: 74.8% accurate, 0.9× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;a \leq -5.1 \cdot 10^{-62} \lor \neg \left(a \leq 7 \cdot 10^{-18}\right):\\ \;\;\;\;x - \frac{y - z}{a} \cdot \left(x - t\right)\\ \mathbf{else}:\\ \;\;\;\;t + \frac{y}{z} \cdot \left(x - t\right)\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (if (or (<= a -5.1e-62) (not (<= a 7e-18)))
   (- x (* (/ (- y z) a) (- x t)))
   (+ t (* (/ y z) (- x t)))))

C

double code(double x, double y, double z, double t, double a) {
	double tmp;
	if ((a <= -5.1e-62) || !(a <= 7e-18)) {
		tmp = x - (((y - z) / a) * (x - t));
	} else {
		tmp = t + ((y / z) * (x - 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 <= (-5.1d-62)) .or. (.not. (a <= 7d-18))) then
        tmp = x - (((y - z) / a) * (x - t))
    else
        tmp = t + ((y / z) * (x - t))
    end if
    code = tmp
end function

Java

public static double code(double x, double y, double z, double t, double a) {
	double tmp;
	if ((a <= -5.1e-62) || !(a <= 7e-18)) {
		tmp = x - (((y - z) / a) * (x - t));
	} else {
		tmp = t + ((y / z) * (x - t));
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	tmp = 0
	if (a <= -5.1e-62) or not (a <= 7e-18):
		tmp = x - (((y - z) / a) * (x - t))
	else:
		tmp = t + ((y / z) * (x - t))
	return tmp

Julia

function code(x, y, z, t, a)
	tmp = 0.0
	if ((a <= -5.1e-62) || !(a <= 7e-18))
		tmp = Float64(x - Float64(Float64(Float64(y - z) / a) * Float64(x - t)));
	else
		tmp = Float64(t + Float64(Float64(y / z) * Float64(x - t)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	tmp = 0.0;
	if ((a <= -5.1e-62) || ~((a <= 7e-18)))
		tmp = x - (((y - z) / a) * (x - t));
	else
		tmp = t + ((y / z) * (x - t));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := If[Or[LessEqual[a, -5.1e-62], N[Not[LessEqual[a, 7e-18]], $MachinePrecision]], N[(x - N[(N[(N[(y - z), $MachinePrecision] / a), $MachinePrecision] * N[(x - t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(t + N[(N[(y / z), $MachinePrecision] * N[(x - t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

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

Alternative 21: 50.4% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -2.4 \cdot 10^{-33}:\\ \;\;\;\;t\\ \mathbf{elif}\;z \leq 1.65 \cdot 10^{-74}:\\ \;\;\;\;x + \frac{y \cdot t}{a}\\ \mathbf{elif}\;z \leq 2.7 \cdot 10^{+133}:\\ \;\;\;\;x \cdot \left(1 - \frac{y}{a}\right)\\ \mathbf{else}:\\ \;\;\;\;t\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (if (<= z -2.4e-33)
   t
   (if (<= z 1.65e-74)
     (+ x (/ (* y t) a))
     (if (<= z 2.7e+133) (* x (- 1.0 (/ y a))) t))))

C

double code(double x, double y, double z, double t, double a) {
	double tmp;
	if (z <= -2.4e-33) {
		tmp = t;
	} else if (z <= 1.65e-74) {
		tmp = x + ((y * t) / a);
	} else if (z <= 2.7e+133) {
		tmp = x * (1.0 - (y / a));
	} else {
		tmp = 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 (z <= (-2.4d-33)) then
        tmp = t
    else if (z <= 1.65d-74) then
        tmp = x + ((y * t) / a)
    else if (z <= 2.7d+133) then
        tmp = x * (1.0d0 - (y / a))
    else
        tmp = 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 (z <= -2.4e-33) {
		tmp = t;
	} else if (z <= 1.65e-74) {
		tmp = x + ((y * t) / a);
	} else if (z <= 2.7e+133) {
		tmp = x * (1.0 - (y / a));
	} else {
		tmp = t;
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	tmp = 0
	if z <= -2.4e-33:
		tmp = t
	elif z <= 1.65e-74:
		tmp = x + ((y * t) / a)
	elif z <= 2.7e+133:
		tmp = x * (1.0 - (y / a))
	else:
		tmp = t
	return tmp

Julia

function code(x, y, z, t, a)
	tmp = 0.0
	if (z <= -2.4e-33)
		tmp = t;
	elseif (z <= 1.65e-74)
		tmp = Float64(x + Float64(Float64(y * t) / a));
	elseif (z <= 2.7e+133)
		tmp = Float64(x * Float64(1.0 - Float64(y / a)));
	else
		tmp = t;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	tmp = 0.0;
	if (z <= -2.4e-33)
		tmp = t;
	elseif (z <= 1.65e-74)
		tmp = x + ((y * t) / a);
	elseif (z <= 2.7e+133)
		tmp = x * (1.0 - (y / a));
	else
		tmp = t;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := If[LessEqual[z, -2.4e-33], t, If[LessEqual[z, 1.65e-74], N[(x + N[(N[(y * t), $MachinePrecision] / a), $MachinePrecision]), $MachinePrecision], If[LessEqual[z, 2.7e+133], N[(x * N[(1.0 - N[(y / a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t]]]

Derivation

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

Alternative 22: 70.4% accurate, 1.0× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -3.4 \cdot 10^{-34} \lor \neg \left(z \leq 1.25 \cdot 10^{-26}\right):\\ \;\;\;\;t + \frac{y}{z} \cdot \left(x - t\right)\\ \mathbf{else}:\\ \;\;\;\;x + \left(t - x\right) \cdot \frac{y}{a}\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (if (or (<= z -3.4e-34) (not (<= z 1.25e-26)))
   (+ t (* (/ y z) (- x t)))
   (+ x (* (- t x) (/ y a)))))

C

double code(double x, double y, double z, double t, double a) {
	double tmp;
	if ((z <= -3.4e-34) || !(z <= 1.25e-26)) {
		tmp = t + ((y / z) * (x - t));
	} else {
		tmp = x + ((t - x) * (y / 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 ((z <= (-3.4d-34)) .or. (.not. (z <= 1.25d-26))) then
        tmp = t + ((y / z) * (x - t))
    else
        tmp = x + ((t - x) * (y / 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 ((z <= -3.4e-34) || !(z <= 1.25e-26)) {
		tmp = t + ((y / z) * (x - t));
	} else {
		tmp = x + ((t - x) * (y / a));
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	tmp = 0
	if (z <= -3.4e-34) or not (z <= 1.25e-26):
		tmp = t + ((y / z) * (x - t))
	else:
		tmp = x + ((t - x) * (y / a))
	return tmp

Julia

function code(x, y, z, t, a)
	tmp = 0.0
	if ((z <= -3.4e-34) || !(z <= 1.25e-26))
		tmp = Float64(t + Float64(Float64(y / z) * Float64(x - t)));
	else
		tmp = Float64(x + Float64(Float64(t - x) * Float64(y / a)));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	tmp = 0.0;
	if ((z <= -3.4e-34) || ~((z <= 1.25e-26)))
		tmp = t + ((y / z) * (x - t));
	else
		tmp = x + ((t - x) * (y / a));
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := If[Or[LessEqual[z, -3.4e-34], N[Not[LessEqual[z, 1.25e-26]], $MachinePrecision]], N[(t + N[(N[(y / z), $MachinePrecision] * N[(x - t), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(x + N[(N[(t - x), $MachinePrecision] * N[(y / a), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]

Derivation

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

Alternative 23: 53.6% accurate, 1.2× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -2.8 \cdot 10^{-33} \lor \neg \left(z \leq 1.2 \cdot 10^{-26}\right):\\ \;\;\;\;t - y \cdot \frac{t}{z}\\ \mathbf{else}:\\ \;\;\;\;x + \frac{y \cdot t}{a}\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (if (or (<= z -2.8e-33) (not (<= z 1.2e-26)))
   (- t (* y (/ t z)))
   (+ x (/ (* y t) a))))

C

double code(double x, double y, double z, double t, double a) {
	double tmp;
	if ((z <= -2.8e-33) || !(z <= 1.2e-26)) {
		tmp = t - (y * (t / z));
	} else {
		tmp = x + ((y * t) / 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 ((z <= (-2.8d-33)) .or. (.not. (z <= 1.2d-26))) then
        tmp = t - (y * (t / z))
    else
        tmp = x + ((y * t) / 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 ((z <= -2.8e-33) || !(z <= 1.2e-26)) {
		tmp = t - (y * (t / z));
	} else {
		tmp = x + ((y * t) / a);
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	tmp = 0
	if (z <= -2.8e-33) or not (z <= 1.2e-26):
		tmp = t - (y * (t / z))
	else:
		tmp = x + ((y * t) / a)
	return tmp

Julia

function code(x, y, z, t, a)
	tmp = 0.0
	if ((z <= -2.8e-33) || !(z <= 1.2e-26))
		tmp = Float64(t - Float64(y * Float64(t / z)));
	else
		tmp = Float64(x + Float64(Float64(y * t) / a));
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	tmp = 0.0;
	if ((z <= -2.8e-33) || ~((z <= 1.2e-26)))
		tmp = t - (y * (t / z));
	else
		tmp = x + ((y * t) / a);
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := If[Or[LessEqual[z, -2.8e-33], N[Not[LessEqual[z, 1.2e-26]], $MachinePrecision]], N[(t - N[(y * N[(t / z), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(x + N[(N[(y * t), $MachinePrecision] / a), $MachinePrecision]), $MachinePrecision]]

Derivation

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

Alternative 24: 38.6% accurate, 2.5× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} \mathbf{if}\;z \leq -1.7 \cdot 10^{-82}:\\ \;\;\;\;t\\ \mathbf{elif}\;z \leq 3.1 \cdot 10^{+31}:\\ \;\;\;\;x\\ \mathbf{else}:\\ \;\;\;\;t\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (if (<= z -1.7e-82) t (if (<= z 3.1e+31) x t)))

C

double code(double x, double y, double z, double t, double a) {
	double tmp;
	if (z <= -1.7e-82) {
		tmp = t;
	} else if (z <= 3.1e+31) {
		tmp = x;
	} else {
		tmp = 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 (z <= (-1.7d-82)) then
        tmp = t
    else if (z <= 3.1d+31) then
        tmp = x
    else
        tmp = 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 (z <= -1.7e-82) {
		tmp = t;
	} else if (z <= 3.1e+31) {
		tmp = x;
	} else {
		tmp = t;
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	tmp = 0
	if z <= -1.7e-82:
		tmp = t
	elif z <= 3.1e+31:
		tmp = x
	else:
		tmp = t
	return tmp

Julia

function code(x, y, z, t, a)
	tmp = 0.0
	if (z <= -1.7e-82)
		tmp = t;
	elseif (z <= 3.1e+31)
		tmp = x;
	else
		tmp = t;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	tmp = 0.0;
	if (z <= -1.7e-82)
		tmp = t;
	elseif (z <= 3.1e+31)
		tmp = x;
	else
		tmp = t;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := If[LessEqual[z, -1.7e-82], t, If[LessEqual[z, 3.1e+31], x, t]]

Derivation

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

Alternative 25: 2.8% accurate, 13.0× speedup

Math

\[\begin{array}{l} \\ 0 \end{array} \]

FPCore

(FPCore (x y z t a) :precision binary64 0.0)

C

double code(double x, double y, double z, double t, double a) {
	return 0.0;
}

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 = 0.0d0
end function

Java

public static double code(double x, double y, double z, double t, double a) {
	return 0.0;
}

Python

def code(x, y, z, t, a):
	return 0.0

Julia

function code(x, y, z, t, a)
	return 0.0
end

MATLAB

function tmp = code(x, y, z, t, a)
	tmp = 0.0;
end

Wolfram

code[x_, y_, z_, t_, a_] := 0.0

Derivation

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

Alternative 26: 25.3% accurate, 13.0× speedup

Math

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

FPCore

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

C

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

Java

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

Python

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

Julia

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

MATLAB

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

Wolfram

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

Derivation

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

Developer target: 83.7% accurate, 0.8× speedup

Math

\[\begin{array}{l} \\ \begin{array}{l} t_1 := t - \frac{y}{z} \cdot \left(t - x\right)\\ \mathbf{if}\;z < -1.2536131056095036 \cdot 10^{+188}:\\ \;\;\;\;t_1\\ \mathbf{elif}\;z < 4.446702369113811 \cdot 10^{+64}:\\ \;\;\;\;x + \frac{y - z}{\frac{a - z}{t - x}}\\ \mathbf{else}:\\ \;\;\;\;t_1\\ \end{array} \end{array} \]

FPCore

(FPCore (x y z t a)
 :precision binary64
 (let* ((t_1 (- t (* (/ y z) (- t x)))))
   (if (< z -1.2536131056095036e+188)
     t_1
     (if (< z 4.446702369113811e+64)
       (+ x (/ (- y z) (/ (- a z) (- t x))))
       t_1))))

C

double code(double x, double y, double z, double t, double a) {
	double t_1 = t - ((y / z) * (t - x));
	double tmp;
	if (z < -1.2536131056095036e+188) {
		tmp = t_1;
	} else if (z < 4.446702369113811e+64) {
		tmp = x + ((y - z) / ((a - z) / (t - 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 = t - ((y / z) * (t - x))
    if (z < (-1.2536131056095036d+188)) then
        tmp = t_1
    else if (z < 4.446702369113811d+64) then
        tmp = x + ((y - z) / ((a - z) / (t - 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 = t - ((y / z) * (t - x));
	double tmp;
	if (z < -1.2536131056095036e+188) {
		tmp = t_1;
	} else if (z < 4.446702369113811e+64) {
		tmp = x + ((y - z) / ((a - z) / (t - x)));
	} else {
		tmp = t_1;
	}
	return tmp;
}

Python

def code(x, y, z, t, a):
	t_1 = t - ((y / z) * (t - x))
	tmp = 0
	if z < -1.2536131056095036e+188:
		tmp = t_1
	elif z < 4.446702369113811e+64:
		tmp = x + ((y - z) / ((a - z) / (t - x)))
	else:
		tmp = t_1
	return tmp

Julia

function code(x, y, z, t, a)
	t_1 = Float64(t - Float64(Float64(y / z) * Float64(t - x)))
	tmp = 0.0
	if (z < -1.2536131056095036e+188)
		tmp = t_1;
	elseif (z < 4.446702369113811e+64)
		tmp = Float64(x + Float64(Float64(y - z) / Float64(Float64(a - z) / Float64(t - x))));
	else
		tmp = t_1;
	end
	return tmp
end

MATLAB

function tmp_2 = code(x, y, z, t, a)
	t_1 = t - ((y / z) * (t - x));
	tmp = 0.0;
	if (z < -1.2536131056095036e+188)
		tmp = t_1;
	elseif (z < 4.446702369113811e+64)
		tmp = x + ((y - z) / ((a - z) / (t - x)));
	else
		tmp = t_1;
	end
	tmp_2 = tmp;
end

Wolfram

code[x_, y_, z_, t_, a_] := Block[{t$95$1 = N[(t - N[(N[(y / z), $MachinePrecision] * N[(t - x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[Less[z, -1.2536131056095036e+188], t$95$1, If[Less[z, 4.446702369113811e+64], N[(x + N[(N[(y - z), $MachinePrecision] / N[(N[(a - z), $MachinePrecision] / N[(t - x), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$1]]]

Reproduce

herbie shell --seed 2024008 
(FPCore (x y z t a)
  :name "Graphics.Rendering.Chart.Axis.Types:invLinMap from Chart-1.5.3"
  :precision binary64

  :herbie-target
  (if (< z -1.2536131056095036e+188) (- t (* (/ y z) (- t x))) (if (< z 4.446702369113811e+64) (+ x (/ (- y z) (/ (- a z) (- t x)))) (- t (* (/ y z) (- t x)))))

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