Average Error: 6.3 → 0.8
Time: 5.8s
Precision: binary64
\[x + \frac{e^{y \cdot \log \left(\frac{y}{z + y}\right)}}{y} \]
\[\begin{array}{l} \mathbf{if}\;y \leq 5.736736187083638 \cdot 10^{-6}:\\ \;\;\;\;x + \frac{1}{y}\\ \mathbf{else}:\\ \;\;\;\;x + {\left(y \cdot e^{z}\right)}^{-1}\\ \end{array} \]
(FPCore (x y z)
 :precision binary64
 (+ x (/ (exp (* y (log (/ y (+ z y))))) y)))
(FPCore (x y z)
 :precision binary64
 (if (<= y 5.736736187083638e-6)
   (+ x (/ 1.0 y))
   (+ x (pow (* y (exp z)) -1.0))))
double code(double x, double y, double z) {
	return x + (exp((y * log((y / (z + y))))) / y);
}
double code(double x, double y, double z) {
	double tmp;
	if (y <= 5.736736187083638e-6) {
		tmp = x + (1.0 / y);
	} else {
		tmp = x + pow((y * exp(z)), -1.0);
	}
	return tmp;
}
real(8) function code(x, y, z)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    code = x + (exp((y * log((y / (z + y))))) / y)
end function
real(8) function code(x, y, z)
    real(8), intent (in) :: x
    real(8), intent (in) :: y
    real(8), intent (in) :: z
    real(8) :: tmp
    if (y <= 5.736736187083638d-6) then
        tmp = x + (1.0d0 / y)
    else
        tmp = x + ((y * exp(z)) ** (-1.0d0))
    end if
    code = tmp
end function
public static double code(double x, double y, double z) {
	return x + (Math.exp((y * Math.log((y / (z + y))))) / y);
}
public static double code(double x, double y, double z) {
	double tmp;
	if (y <= 5.736736187083638e-6) {
		tmp = x + (1.0 / y);
	} else {
		tmp = x + Math.pow((y * Math.exp(z)), -1.0);
	}
	return tmp;
}
def code(x, y, z):
	return x + (math.exp((y * math.log((y / (z + y))))) / y)
def code(x, y, z):
	tmp = 0
	if y <= 5.736736187083638e-6:
		tmp = x + (1.0 / y)
	else:
		tmp = x + math.pow((y * math.exp(z)), -1.0)
	return tmp
function code(x, y, z)
	return Float64(x + Float64(exp(Float64(y * log(Float64(y / Float64(z + y))))) / y))
end
function code(x, y, z)
	tmp = 0.0
	if (y <= 5.736736187083638e-6)
		tmp = Float64(x + Float64(1.0 / y));
	else
		tmp = Float64(x + (Float64(y * exp(z)) ^ -1.0));
	end
	return tmp
end
function tmp = code(x, y, z)
	tmp = x + (exp((y * log((y / (z + y))))) / y);
end
function tmp_2 = code(x, y, z)
	tmp = 0.0;
	if (y <= 5.736736187083638e-6)
		tmp = x + (1.0 / y);
	else
		tmp = x + ((y * exp(z)) ^ -1.0);
	end
	tmp_2 = tmp;
end
code[x_, y_, z_] := N[(x + N[(N[Exp[N[(y * N[Log[N[(y / N[(z + y), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / y), $MachinePrecision]), $MachinePrecision]
code[x_, y_, z_] := If[LessEqual[y, 5.736736187083638e-6], N[(x + N[(1.0 / y), $MachinePrecision]), $MachinePrecision], N[(x + N[Power[N[(y * N[Exp[z], $MachinePrecision]), $MachinePrecision], -1.0], $MachinePrecision]), $MachinePrecision]]
x + \frac{e^{y \cdot \log \left(\frac{y}{z + y}\right)}}{y}
\begin{array}{l}
\mathbf{if}\;y \leq 5.736736187083638 \cdot 10^{-6}:\\
\;\;\;\;x + \frac{1}{y}\\

\mathbf{else}:\\
\;\;\;\;x + {\left(y \cdot e^{z}\right)}^{-1}\\


\end{array}

Error

Bits error versus x

Bits error versus y

Bits error versus z

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Target

Original6.3
Target1.2
Herbie0.8
\[\begin{array}{l} \mathbf{if}\;\frac{y}{z + y} < 7.11541576 \cdot 10^{-315}:\\ \;\;\;\;x + \frac{e^{\frac{-1}{z}}}{y}\\ \mathbf{else}:\\ \;\;\;\;x + \frac{e^{\log \left({\left(\frac{y}{y + z}\right)}^{y}\right)}}{y}\\ \end{array} \]

Derivation

  1. Split input into 2 regimes
  2. if y < 5.7367361870836383e-6

    1. Initial program 8.1

      \[x + \frac{e^{y \cdot \log \left(\frac{y}{z + y}\right)}}{y} \]
    2. Simplified8.1

      \[\leadsto \color{blue}{x + \frac{{\left(\frac{y}{y + z}\right)}^{y}}{y}} \]
    3. Taylor expanded in y around 0 1.1

      \[\leadsto x + \frac{\color{blue}{1}}{y} \]

    if 5.7367361870836383e-6 < y

    1. Initial program 2.1

      \[x + \frac{e^{y \cdot \log \left(\frac{y}{z + y}\right)}}{y} \]
    2. Simplified2.1

      \[\leadsto \color{blue}{x + \frac{{\left(\frac{y}{y + z}\right)}^{y}}{y}} \]
    3. Taylor expanded in y around inf 0.2

      \[\leadsto x + \frac{\color{blue}{e^{-z}}}{y} \]
    4. Applied egg-rr0.2

      \[\leadsto x + \color{blue}{{\left(y \cdot e^{z}\right)}^{-1}} \]
  3. Recombined 2 regimes into one program.
  4. Final simplification0.8

    \[\leadsto \begin{array}{l} \mathbf{if}\;y \leq 5.736736187083638 \cdot 10^{-6}:\\ \;\;\;\;x + \frac{1}{y}\\ \mathbf{else}:\\ \;\;\;\;x + {\left(y \cdot e^{z}\right)}^{-1}\\ \end{array} \]

Reproduce

herbie shell --seed 2022133 
(FPCore (x y z)
  :name "Numeric.SpecFunctions:invIncompleteBetaWorker from math-functions-0.1.5.2, G"
  :precision binary64

  :herbie-target
  (if (< (/ y (+ z y)) 7.11541576e-315) (+ x (/ (exp (/ -1.0 z)) y)) (+ x (/ (exp (log (pow (/ y (+ y z)) y))) y)))

  (+ x (/ (exp (* y (log (/ y (+ z y))))) y)))