Average Error: 0.3 → 0.0
Time: 3.8s
Precision: binary64
\[\log x - \log \log x \]
\[\log \left(\sqrt{\frac{\log x}{x}}\right) \cdot -2 \]
(FPCore (x) :precision binary64 (- (log x) (log (log x))))
(FPCore (x) :precision binary64 (* (log (sqrt (/ (log x) x))) -2.0))
double code(double x) {
	return log(x) - log(log(x));
}
double code(double x) {
	return log(sqrt((log(x) / x))) * -2.0;
}
real(8) function code(x)
    real(8), intent (in) :: x
    code = log(x) - log(log(x))
end function
real(8) function code(x)
    real(8), intent (in) :: x
    code = log(sqrt((log(x) / x))) * (-2.0d0)
end function
public static double code(double x) {
	return Math.log(x) - Math.log(Math.log(x));
}
public static double code(double x) {
	return Math.log(Math.sqrt((Math.log(x) / x))) * -2.0;
}
def code(x):
	return math.log(x) - math.log(math.log(x))
def code(x):
	return math.log(math.sqrt((math.log(x) / x))) * -2.0
function code(x)
	return Float64(log(x) - log(log(x)))
end
function code(x)
	return Float64(log(sqrt(Float64(log(x) / x))) * -2.0)
end
function tmp = code(x)
	tmp = log(x) - log(log(x));
end
function tmp = code(x)
	tmp = log(sqrt((log(x) / x))) * -2.0;
end
code[x_] := N[(N[Log[x], $MachinePrecision] - N[Log[N[Log[x], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
code[x_] := N[(N[Log[N[Sqrt[N[(N[Log[x], $MachinePrecision] / x), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * -2.0), $MachinePrecision]
\log x - \log \log x
\log \left(\sqrt{\frac{\log x}{x}}\right) \cdot -2

Error

Bits error versus x

Try it out

Your Program's Arguments

Results

Enter valid numbers for all inputs

Derivation

  1. Initial program 0.3

    \[\log x - \log \log x \]
  2. Applied egg-rr0.0

    \[\leadsto \color{blue}{-\log \left(\frac{\log x}{x}\right)} \]
  3. Applied egg-rr0.0

    \[\leadsto -\color{blue}{2 \cdot \log \left(\sqrt{\frac{\log x}{x}}\right)} \]
  4. Final simplification0.0

    \[\leadsto \log \left(\sqrt{\frac{\log x}{x}}\right) \cdot -2 \]

Reproduce

herbie shell --seed 2022151 
(FPCore (x)
  :name "Jmat.Real.lambertw, estimator"
  :precision binary64
  (- (log x) (log (log x))))