Timeout for forward-xlam

Specification

Math

\[\frac{one\_es \cdot \left(tanphi \cdot sa\right) + \sin lamt \cdot ca}{\cos lamt} \]

FPCore

(FPCore (lamt one_es tanphi sa ca)
  :precision binary64
  :pre TRUE
  (/ (+ (* one_es (* tanphi sa)) (* (sin lamt) ca)) (cos lamt)))

C

double code(double lamt, double one_es, double tanphi, double sa, double ca) {
	return ((one_es * (tanphi * sa)) + (sin(lamt) * ca)) / cos(lamt);
}

Fortran

real(8) function code(lamt, one_es, tanphi, sa, ca)
use fmin_fmax_functions
    real(8), intent (in) :: lamt
    real(8), intent (in) :: one_es
    real(8), intent (in) :: tanphi
    real(8), intent (in) :: sa
    real(8), intent (in) :: ca
    code = ((one_es * (tanphi * sa)) + (sin(lamt) * ca)) / cos(lamt)
end function

Java

public static double code(double lamt, double one_es, double tanphi, double sa, double ca) {
	return ((one_es * (tanphi * sa)) + (Math.sin(lamt) * ca)) / Math.cos(lamt);
}

Python

def code(lamt, one_es, tanphi, sa, ca):
	return ((one_es * (tanphi * sa)) + (math.sin(lamt) * ca)) / math.cos(lamt)

Julia

function code(lamt, one_es, tanphi, sa, ca)
	return Float64(Float64(Float64(one_es * Float64(tanphi * sa)) + Float64(sin(lamt) * ca)) / cos(lamt))
end

MATLAB

function tmp = code(lamt, one_es, tanphi, sa, ca)
	tmp = ((one_es * (tanphi * sa)) + (sin(lamt) * ca)) / cos(lamt);
end

Wolfram

code[lamt_, one$95$es_, tanphi_, sa_, ca_] := N[(N[(N[(one$95$es * N[(tanphi * sa), $MachinePrecision]), $MachinePrecision] + N[(N[Sin[lamt], $MachinePrecision] * ca), $MachinePrecision]), $MachinePrecision] / N[Cos[lamt], $MachinePrecision]), $MachinePrecision]

ReFlow

f(lamt, one_es, tanphi, sa, ca):
	lamt in [-inf, +inf],
	one_es in [-inf, +inf],
	tanphi in [-inf, +inf],
	sa in [-inf, +inf],
	ca in [-inf, +inf]
code: THEORY
BEGIN
f(lamt, one_es, tanphi, sa, ca: real): real =
	((one_es * (tanphi * sa)) + ((sin(lamt)) * ca)) / (cos(lamt))
END code