Timeout for exact-forward-two-inv-denom

Specification

Math

\[\frac{2}{\sqrt{\sin Cn \cdot \sin Cn + \cos Cn \cdot \left(\cos Cn \cdot \left(\cos lam \cdot \cos lam\right)\right)}} \]

FPCore

(FPCore (Cn lam)
  :precision binary64
  :pre TRUE
  (/
 2.0
 (sqrt
  (+
   (* (sin Cn) (sin Cn))
   (* (cos Cn) (* (cos Cn) (* (cos lam) (cos lam))))))))

C

double code(double Cn, double lam) {
	return 2.0 / sqrt(((sin(Cn) * sin(Cn)) + (cos(Cn) * (cos(Cn) * (cos(lam) * cos(lam))))));
}

Fortran

real(8) function code(cn, lam)
use fmin_fmax_functions
    real(8), intent (in) :: cn
    real(8), intent (in) :: lam
    code = 2.0d0 / sqrt(((sin(cn) * sin(cn)) + (cos(cn) * (cos(cn) * (cos(lam) * cos(lam))))))
end function

Java

public static double code(double Cn, double lam) {
	return 2.0 / Math.sqrt(((Math.sin(Cn) * Math.sin(Cn)) + (Math.cos(Cn) * (Math.cos(Cn) * (Math.cos(lam) * Math.cos(lam))))));
}

Python

def code(Cn, lam):
	return 2.0 / math.sqrt(((math.sin(Cn) * math.sin(Cn)) + (math.cos(Cn) * (math.cos(Cn) * (math.cos(lam) * math.cos(lam))))))

Julia

function code(Cn, lam)
	return Float64(2.0 / sqrt(Float64(Float64(sin(Cn) * sin(Cn)) + Float64(cos(Cn) * Float64(cos(Cn) * Float64(cos(lam) * cos(lam)))))))
end

MATLAB

function tmp = code(Cn, lam)
	tmp = 2.0 / sqrt(((sin(Cn) * sin(Cn)) + (cos(Cn) * (cos(Cn) * (cos(lam) * cos(lam))))));
end

Wolfram

code[Cn_, lam_] := N[(2.0 / N[Sqrt[N[(N[(N[Sin[Cn], $MachinePrecision] * N[Sin[Cn], $MachinePrecision]), $MachinePrecision] + N[(N[Cos[Cn], $MachinePrecision] * N[(N[Cos[Cn], $MachinePrecision] * N[(N[Cos[lam], $MachinePrecision] * N[Cos[lam], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]

ReFlow

f(Cn, lam):
	Cn in [-inf, +inf],
	lam in [-inf, +inf]
code: THEORY
BEGIN
f(Cn, lam: real): real =
	(2) / (sqrt((((sin(Cn)) * (sin(Cn))) + ((cos(Cn)) * ((cos(Cn)) * ((cos(lam)) * (cos(lam))))))))
END code