Timeout for forward-phidp

Specification

Math

\[\sin^{-1} \left(\frac{one\_es \cdot \left(ca \cdot \sin \phi\right) - sa \cdot \left(\cos \phi \cdot \sin lamt\right)}{\sqrt{1 - es \cdot \left(\sin \phi \cdot \sin \phi\right)}}\right) \]

FPCore

(FPCore (phi es one_es ca sa lamt)
  :precision binary64
  :pre TRUE
  (asin
 (/
  (- (* one_es (* ca (sin phi))) (* sa (* (cos phi) (sin lamt))))
  (sqrt (- 1.0 (* es (* (sin phi) (sin phi))))))))

C

double code(double phi, double es, double one_es, double ca, double sa, double lamt) {
	return asin((((one_es * (ca * sin(phi))) - (sa * (cos(phi) * sin(lamt)))) / sqrt((1.0 - (es * (sin(phi) * sin(phi)))))));
}

Fortran

real(8) function code(phi, es, one_es, ca, sa, lamt)
use fmin_fmax_functions
    real(8), intent (in) :: phi
    real(8), intent (in) :: es
    real(8), intent (in) :: one_es
    real(8), intent (in) :: ca
    real(8), intent (in) :: sa
    real(8), intent (in) :: lamt
    code = asin((((one_es * (ca * sin(phi))) - (sa * (cos(phi) * sin(lamt)))) / sqrt((1.0d0 - (es * (sin(phi) * sin(phi)))))))
end function

Java

public static double code(double phi, double es, double one_es, double ca, double sa, double lamt) {
	return Math.asin((((one_es * (ca * Math.sin(phi))) - (sa * (Math.cos(phi) * Math.sin(lamt)))) / Math.sqrt((1.0 - (es * (Math.sin(phi) * Math.sin(phi)))))));
}

Python

def code(phi, es, one_es, ca, sa, lamt):
	return math.asin((((one_es * (ca * math.sin(phi))) - (sa * (math.cos(phi) * math.sin(lamt)))) / math.sqrt((1.0 - (es * (math.sin(phi) * math.sin(phi)))))))

Julia

function code(phi, es, one_es, ca, sa, lamt)
	return asin(Float64(Float64(Float64(one_es * Float64(ca * sin(phi))) - Float64(sa * Float64(cos(phi) * sin(lamt)))) / sqrt(Float64(1.0 - Float64(es * Float64(sin(phi) * sin(phi)))))))
end

MATLAB

function tmp = code(phi, es, one_es, ca, sa, lamt)
	tmp = asin((((one_es * (ca * sin(phi))) - (sa * (cos(phi) * sin(lamt)))) / sqrt((1.0 - (es * (sin(phi) * sin(phi)))))));
end

Wolfram

code[phi_, es_, one$95$es_, ca_, sa_, lamt_] := N[ArcSin[N[(N[(N[(one$95$es * N[(ca * N[Sin[phi], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(sa * N[(N[Cos[phi], $MachinePrecision] * N[Sin[lamt], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[Sqrt[N[(1.0 - N[(es * N[(N[Sin[phi], $MachinePrecision] * N[Sin[phi], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]

ReFlow

f(phi, es, one_es, ca, sa, lamt):
	phi in [-inf, +inf],
	es in [-inf, +inf],
	one_es in [-inf, +inf],
	ca in [-inf, +inf],
	sa in [-inf, +inf],
	lamt in [-inf, +inf]
code: THEORY
BEGIN
f(phi, es, one_es, ca, sa, lamt: real): real =
	asin((((one_es * (ca * (sin(phi)))) - (sa * ((cos(phi)) * (sin(lamt))))) / (sqrt(((1) - (es * ((sin(phi)) * (sin(phi)))))))))
END code