
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_0) t_0))))
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0);
return R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0)
code = r * (2.0d0 * atan2(sqrt(t_1), sqrt((1.0d0 - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((Math.cos(phi1) * Math.cos(phi2)) * t_0) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt(t_1), Math.sqrt((1.0 - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((math.cos(phi1) * math.cos(phi2)) * t_0) * t_0) return R * (2.0 * math.atan2(math.sqrt(t_1), math.sqrt((1.0 - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0); tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$1], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) \cdot t\_0\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)
\end{array}
\end{array}
Sampling outcomes in binary64 precision:
Herbie found 19 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_0) t_0))))
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0);
return R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0)
code = r * (2.0d0 * atan2(sqrt(t_1), sqrt((1.0d0 - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((Math.cos(phi1) * Math.cos(phi2)) * t_0) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt(t_1), Math.sqrt((1.0 - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((math.cos(phi1) * math.cos(phi2)) * t_0) * t_0) return R * (2.0 * math.atan2(math.sqrt(t_1), math.sqrt((1.0 - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0); tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$1], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) \cdot t\_0\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)
\end{array}
\end{array}
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1
(pow
(-
(* (sin (/ phi1 2.0)) (cos (/ phi2 2.0)))
(* (cos (/ phi1 2.0)) (sin (/ phi2 2.0))))
2.0))
(t_2 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (* t_0 (* t_2 t_2))))
(sqrt
(+
(- 1.0 t_1)
(*
t_0
(-
(/
(+ (* (cos lambda1) (cos lambda2)) (* (sin lambda1) (sin lambda2)))
2.0)
0.5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = pow(((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))), 2.0);
double t_2 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((t_1 + (t_0 * (t_2 * t_2)))), sqrt(((1.0 - t_1) + (t_0 * ((((cos(lambda1) * cos(lambda2)) + (sin(lambda1) * sin(lambda2))) / 2.0) - 0.5))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
t_0 = cos(phi1) * cos(phi2)
t_1 = ((sin((phi1 / 2.0d0)) * cos((phi2 / 2.0d0))) - (cos((phi1 / 2.0d0)) * sin((phi2 / 2.0d0)))) ** 2.0d0
t_2 = sin(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2(sqrt((t_1 + (t_0 * (t_2 * t_2)))), sqrt(((1.0d0 - t_1) + (t_0 * ((((cos(lambda1) * cos(lambda2)) + (sin(lambda1) * sin(lambda2))) / 2.0d0) - 0.5d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.cos(phi1) * Math.cos(phi2);
double t_1 = Math.pow(((Math.sin((phi1 / 2.0)) * Math.cos((phi2 / 2.0))) - (Math.cos((phi1 / 2.0)) * Math.sin((phi2 / 2.0)))), 2.0);
double t_2 = Math.sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((t_1 + (t_0 * (t_2 * t_2)))), Math.sqrt(((1.0 - t_1) + (t_0 * ((((Math.cos(lambda1) * Math.cos(lambda2)) + (Math.sin(lambda1) * Math.sin(lambda2))) / 2.0) - 0.5))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi1) * math.cos(phi2) t_1 = math.pow(((math.sin((phi1 / 2.0)) * math.cos((phi2 / 2.0))) - (math.cos((phi1 / 2.0)) * math.sin((phi2 / 2.0)))), 2.0) t_2 = math.sin(((lambda1 - lambda2) / 2.0)) return R * (2.0 * math.atan2(math.sqrt((t_1 + (t_0 * (t_2 * t_2)))), math.sqrt(((1.0 - t_1) + (t_0 * ((((math.cos(lambda1) * math.cos(lambda2)) + (math.sin(lambda1) * math.sin(lambda2))) / 2.0) - 0.5))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = Float64(Float64(sin(Float64(phi1 / 2.0)) * cos(Float64(phi2 / 2.0))) - Float64(cos(Float64(phi1 / 2.0)) * sin(Float64(phi2 / 2.0)))) ^ 2.0 t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + Float64(t_0 * Float64(t_2 * t_2)))), sqrt(Float64(Float64(1.0 - t_1) + Float64(t_0 * Float64(Float64(Float64(Float64(cos(lambda1) * cos(lambda2)) + Float64(sin(lambda1) * sin(lambda2))) / 2.0) - 0.5))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi1) * cos(phi2); t_1 = ((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))) ^ 2.0; t_2 = sin(((lambda1 - lambda2) / 2.0)); tmp = R * (2.0 * atan2(sqrt((t_1 + (t_0 * (t_2 * t_2)))), sqrt(((1.0 - t_1) + (t_0 * ((((cos(lambda1) * cos(lambda2)) + (sin(lambda1) * sin(lambda2))) / 2.0) - 0.5)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Power[N[(N[(N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[(t$95$0 * N[(t$95$2 * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - t$95$1), $MachinePrecision] + N[(t$95$0 * N[(N[(N[(N[(N[Cos[lambda1], $MachinePrecision] * N[Cos[lambda2], $MachinePrecision]), $MachinePrecision] + N[(N[Sin[lambda1], $MachinePrecision] * N[Sin[lambda2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := {\left(\sin \left(\frac{\phi_1}{2}\right) \cdot \cos \left(\frac{\phi_2}{2}\right) - \cos \left(\frac{\phi_1}{2}\right) \cdot \sin \left(\frac{\phi_2}{2}\right)\right)}^{2}\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + t\_0 \cdot \left(t\_2 \cdot t\_2\right)}}{\sqrt{\left(1 - t\_1\right) + t\_0 \cdot \left(\frac{\cos \lambda_1 \cdot \cos \lambda_2 + \sin \lambda_1 \cdot \sin \lambda_2}{2} - 0.5\right)}}\right)
\end{array}
\end{array}
Initial program 61.7%
associate-*l*61.7%
Simplified61.7%
div-sub61.7%
sin-diff62.5%
Applied egg-rr62.5%
div-sub61.7%
sin-diff62.5%
Applied egg-rr77.2%
sin-mult77.2%
div-inv77.2%
metadata-eval77.2%
div-inv77.2%
metadata-eval77.2%
cos-sum77.2%
cos-277.2%
div-inv77.2%
metadata-eval77.2%
Applied egg-rr77.2%
div-sub77.2%
+-inverses77.2%
cos-077.2%
metadata-eval77.2%
*-commutative77.2%
Simplified77.2%
associate-*r*77.2%
metadata-eval77.2%
*-un-lft-identity77.2%
cos-diff77.9%
Applied egg-rr77.9%
Final simplification77.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (- lambda1 lambda2) 0.5))
(t_1 (* (cos phi1) (cos phi2)))
(t_2
(pow
(-
(* (sin (/ phi1 2.0)) (cos (/ phi2 2.0)))
(* (cos (/ phi1 2.0)) (sin (/ phi2 2.0))))
2.0)))
(*
R
(*
2.0
(atan2
(sqrt
(+
t_2
(*
t_1
(* (sin (/ (- lambda1 lambda2) 2.0)) (expm1 (log1p (sin t_0)))))))
(sqrt (+ (- 1.0 t_2) (* t_1 (- (/ (cos (* 2.0 t_0)) 2.0) 0.5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = (lambda1 - lambda2) * 0.5;
double t_1 = cos(phi1) * cos(phi2);
double t_2 = pow(((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))), 2.0);
return R * (2.0 * atan2(sqrt((t_2 + (t_1 * (sin(((lambda1 - lambda2) / 2.0)) * expm1(log1p(sin(t_0))))))), sqrt(((1.0 - t_2) + (t_1 * ((cos((2.0 * t_0)) / 2.0) - 0.5))))));
}
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = (lambda1 - lambda2) * 0.5;
double t_1 = Math.cos(phi1) * Math.cos(phi2);
double t_2 = Math.pow(((Math.sin((phi1 / 2.0)) * Math.cos((phi2 / 2.0))) - (Math.cos((phi1 / 2.0)) * Math.sin((phi2 / 2.0)))), 2.0);
return R * (2.0 * Math.atan2(Math.sqrt((t_2 + (t_1 * (Math.sin(((lambda1 - lambda2) / 2.0)) * Math.expm1(Math.log1p(Math.sin(t_0))))))), Math.sqrt(((1.0 - t_2) + (t_1 * ((Math.cos((2.0 * t_0)) / 2.0) - 0.5))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = (lambda1 - lambda2) * 0.5 t_1 = math.cos(phi1) * math.cos(phi2) t_2 = math.pow(((math.sin((phi1 / 2.0)) * math.cos((phi2 / 2.0))) - (math.cos((phi1 / 2.0)) * math.sin((phi2 / 2.0)))), 2.0) return R * (2.0 * math.atan2(math.sqrt((t_2 + (t_1 * (math.sin(((lambda1 - lambda2) / 2.0)) * math.expm1(math.log1p(math.sin(t_0))))))), math.sqrt(((1.0 - t_2) + (t_1 * ((math.cos((2.0 * t_0)) / 2.0) - 0.5))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(Float64(lambda1 - lambda2) * 0.5) t_1 = Float64(cos(phi1) * cos(phi2)) t_2 = Float64(Float64(sin(Float64(phi1 / 2.0)) * cos(Float64(phi2 / 2.0))) - Float64(cos(Float64(phi1 / 2.0)) * sin(Float64(phi2 / 2.0)))) ^ 2.0 return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_2 + Float64(t_1 * Float64(sin(Float64(Float64(lambda1 - lambda2) / 2.0)) * expm1(log1p(sin(t_0))))))), sqrt(Float64(Float64(1.0 - t_2) + Float64(t_1 * Float64(Float64(cos(Float64(2.0 * t_0)) / 2.0) - 0.5))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Power[N[(N[(N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$2 + N[(t$95$1 * N[(N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision] * N[(Exp[N[Log[1 + N[Sin[t$95$0], $MachinePrecision]], $MachinePrecision]] - 1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - t$95$2), $MachinePrecision] + N[(t$95$1 * N[(N[(N[Cos[N[(2.0 * t$95$0), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \left(\lambda_1 - \lambda_2\right) \cdot 0.5\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
t_2 := {\left(\sin \left(\frac{\phi_1}{2}\right) \cdot \cos \left(\frac{\phi_2}{2}\right) - \cos \left(\frac{\phi_1}{2}\right) \cdot \sin \left(\frac{\phi_2}{2}\right)\right)}^{2}\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 + t\_1 \cdot \left(\sin \left(\frac{\lambda_1 - \lambda_2}{2}\right) \cdot \mathsf{expm1}\left(\mathsf{log1p}\left(\sin t\_0\right)\right)\right)}}{\sqrt{\left(1 - t\_2\right) + t\_1 \cdot \left(\frac{\cos \left(2 \cdot t\_0\right)}{2} - 0.5\right)}}\right)
\end{array}
\end{array}
Initial program 61.7%
associate-*l*61.7%
Simplified61.7%
div-sub61.7%
sin-diff62.5%
Applied egg-rr62.5%
div-sub61.7%
sin-diff62.5%
Applied egg-rr77.2%
sin-mult77.2%
div-inv77.2%
metadata-eval77.2%
div-inv77.2%
metadata-eval77.2%
cos-sum77.2%
cos-277.2%
div-inv77.2%
metadata-eval77.2%
Applied egg-rr77.2%
div-sub77.2%
+-inverses77.2%
cos-077.2%
metadata-eval77.2%
*-commutative77.2%
Simplified77.2%
expm1-log1p-u77.2%
div-inv77.2%
metadata-eval77.2%
Applied egg-rr77.2%
Final simplification77.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1
(pow
(-
(* (sin (/ phi1 2.0)) (cos (/ phi2 2.0)))
(* (cos (/ phi1 2.0)) (sin (/ phi2 2.0))))
2.0))
(t_2 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (* t_0 (* t_2 t_2))))
(sqrt
(+
(- 1.0 t_1)
(* t_0 (- (/ (log (exp (cos (- lambda1 lambda2)))) 2.0) 0.5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = pow(((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))), 2.0);
double t_2 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((t_1 + (t_0 * (t_2 * t_2)))), sqrt(((1.0 - t_1) + (t_0 * ((log(exp(cos((lambda1 - lambda2)))) / 2.0) - 0.5))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
t_0 = cos(phi1) * cos(phi2)
t_1 = ((sin((phi1 / 2.0d0)) * cos((phi2 / 2.0d0))) - (cos((phi1 / 2.0d0)) * sin((phi2 / 2.0d0)))) ** 2.0d0
t_2 = sin(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2(sqrt((t_1 + (t_0 * (t_2 * t_2)))), sqrt(((1.0d0 - t_1) + (t_0 * ((log(exp(cos((lambda1 - lambda2)))) / 2.0d0) - 0.5d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.cos(phi1) * Math.cos(phi2);
double t_1 = Math.pow(((Math.sin((phi1 / 2.0)) * Math.cos((phi2 / 2.0))) - (Math.cos((phi1 / 2.0)) * Math.sin((phi2 / 2.0)))), 2.0);
double t_2 = Math.sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((t_1 + (t_0 * (t_2 * t_2)))), Math.sqrt(((1.0 - t_1) + (t_0 * ((Math.log(Math.exp(Math.cos((lambda1 - lambda2)))) / 2.0) - 0.5))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi1) * math.cos(phi2) t_1 = math.pow(((math.sin((phi1 / 2.0)) * math.cos((phi2 / 2.0))) - (math.cos((phi1 / 2.0)) * math.sin((phi2 / 2.0)))), 2.0) t_2 = math.sin(((lambda1 - lambda2) / 2.0)) return R * (2.0 * math.atan2(math.sqrt((t_1 + (t_0 * (t_2 * t_2)))), math.sqrt(((1.0 - t_1) + (t_0 * ((math.log(math.exp(math.cos((lambda1 - lambda2)))) / 2.0) - 0.5))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = Float64(Float64(sin(Float64(phi1 / 2.0)) * cos(Float64(phi2 / 2.0))) - Float64(cos(Float64(phi1 / 2.0)) * sin(Float64(phi2 / 2.0)))) ^ 2.0 t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + Float64(t_0 * Float64(t_2 * t_2)))), sqrt(Float64(Float64(1.0 - t_1) + Float64(t_0 * Float64(Float64(log(exp(cos(Float64(lambda1 - lambda2)))) / 2.0) - 0.5))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi1) * cos(phi2); t_1 = ((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))) ^ 2.0; t_2 = sin(((lambda1 - lambda2) / 2.0)); tmp = R * (2.0 * atan2(sqrt((t_1 + (t_0 * (t_2 * t_2)))), sqrt(((1.0 - t_1) + (t_0 * ((log(exp(cos((lambda1 - lambda2)))) / 2.0) - 0.5)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Power[N[(N[(N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[(t$95$0 * N[(t$95$2 * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - t$95$1), $MachinePrecision] + N[(t$95$0 * N[(N[(N[Log[N[Exp[N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := {\left(\sin \left(\frac{\phi_1}{2}\right) \cdot \cos \left(\frac{\phi_2}{2}\right) - \cos \left(\frac{\phi_1}{2}\right) \cdot \sin \left(\frac{\phi_2}{2}\right)\right)}^{2}\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + t\_0 \cdot \left(t\_2 \cdot t\_2\right)}}{\sqrt{\left(1 - t\_1\right) + t\_0 \cdot \left(\frac{\log \left(e^{\cos \left(\lambda_1 - \lambda_2\right)}\right)}{2} - 0.5\right)}}\right)
\end{array}
\end{array}
Initial program 61.7%
associate-*l*61.7%
Simplified61.7%
div-sub61.7%
sin-diff62.5%
Applied egg-rr62.5%
div-sub61.7%
sin-diff62.5%
Applied egg-rr77.2%
sin-mult77.2%
div-inv77.2%
metadata-eval77.2%
div-inv77.2%
metadata-eval77.2%
cos-sum77.2%
cos-277.2%
div-inv77.2%
metadata-eval77.2%
Applied egg-rr77.2%
div-sub77.2%
+-inverses77.2%
cos-077.2%
metadata-eval77.2%
*-commutative77.2%
Simplified77.2%
add-log-exp77.2%
associate-*r*77.2%
metadata-eval77.2%
*-un-lft-identity77.2%
Applied egg-rr77.2%
Final simplification77.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1
(pow
(-
(* (sin (/ phi1 2.0)) (cos (/ phi2 2.0)))
(* (cos (/ phi1 2.0)) (sin (/ phi2 2.0))))
2.0))
(t_2 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (* t_0 (* t_2 t_2))))
(sqrt
(+
(- 1.0 t_1)
(*
t_0
(- (/ (cos (* 2.0 (* (- lambda1 lambda2) 0.5))) 2.0) 0.5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = pow(((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))), 2.0);
double t_2 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((t_1 + (t_0 * (t_2 * t_2)))), sqrt(((1.0 - t_1) + (t_0 * ((cos((2.0 * ((lambda1 - lambda2) * 0.5))) / 2.0) - 0.5))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
t_0 = cos(phi1) * cos(phi2)
t_1 = ((sin((phi1 / 2.0d0)) * cos((phi2 / 2.0d0))) - (cos((phi1 / 2.0d0)) * sin((phi2 / 2.0d0)))) ** 2.0d0
t_2 = sin(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2(sqrt((t_1 + (t_0 * (t_2 * t_2)))), sqrt(((1.0d0 - t_1) + (t_0 * ((cos((2.0d0 * ((lambda1 - lambda2) * 0.5d0))) / 2.0d0) - 0.5d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.cos(phi1) * Math.cos(phi2);
double t_1 = Math.pow(((Math.sin((phi1 / 2.0)) * Math.cos((phi2 / 2.0))) - (Math.cos((phi1 / 2.0)) * Math.sin((phi2 / 2.0)))), 2.0);
double t_2 = Math.sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((t_1 + (t_0 * (t_2 * t_2)))), Math.sqrt(((1.0 - t_1) + (t_0 * ((Math.cos((2.0 * ((lambda1 - lambda2) * 0.5))) / 2.0) - 0.5))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi1) * math.cos(phi2) t_1 = math.pow(((math.sin((phi1 / 2.0)) * math.cos((phi2 / 2.0))) - (math.cos((phi1 / 2.0)) * math.sin((phi2 / 2.0)))), 2.0) t_2 = math.sin(((lambda1 - lambda2) / 2.0)) return R * (2.0 * math.atan2(math.sqrt((t_1 + (t_0 * (t_2 * t_2)))), math.sqrt(((1.0 - t_1) + (t_0 * ((math.cos((2.0 * ((lambda1 - lambda2) * 0.5))) / 2.0) - 0.5))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = Float64(Float64(sin(Float64(phi1 / 2.0)) * cos(Float64(phi2 / 2.0))) - Float64(cos(Float64(phi1 / 2.0)) * sin(Float64(phi2 / 2.0)))) ^ 2.0 t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + Float64(t_0 * Float64(t_2 * t_2)))), sqrt(Float64(Float64(1.0 - t_1) + Float64(t_0 * Float64(Float64(cos(Float64(2.0 * Float64(Float64(lambda1 - lambda2) * 0.5))) / 2.0) - 0.5))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi1) * cos(phi2); t_1 = ((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))) ^ 2.0; t_2 = sin(((lambda1 - lambda2) / 2.0)); tmp = R * (2.0 * atan2(sqrt((t_1 + (t_0 * (t_2 * t_2)))), sqrt(((1.0 - t_1) + (t_0 * ((cos((2.0 * ((lambda1 - lambda2) * 0.5))) / 2.0) - 0.5)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Power[N[(N[(N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[(t$95$0 * N[(t$95$2 * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - t$95$1), $MachinePrecision] + N[(t$95$0 * N[(N[(N[Cos[N[(2.0 * N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := {\left(\sin \left(\frac{\phi_1}{2}\right) \cdot \cos \left(\frac{\phi_2}{2}\right) - \cos \left(\frac{\phi_1}{2}\right) \cdot \sin \left(\frac{\phi_2}{2}\right)\right)}^{2}\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + t\_0 \cdot \left(t\_2 \cdot t\_2\right)}}{\sqrt{\left(1 - t\_1\right) + t\_0 \cdot \left(\frac{\cos \left(2 \cdot \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)\right)}{2} - 0.5\right)}}\right)
\end{array}
\end{array}
Initial program 61.7%
associate-*l*61.7%
Simplified61.7%
div-sub61.7%
sin-diff62.5%
Applied egg-rr62.5%
div-sub61.7%
sin-diff62.5%
Applied egg-rr77.2%
sin-mult77.2%
div-inv77.2%
metadata-eval77.2%
div-inv77.2%
metadata-eval77.2%
cos-sum77.2%
cos-277.2%
div-inv77.2%
metadata-eval77.2%
Applied egg-rr77.2%
div-sub77.2%
+-inverses77.2%
cos-077.2%
metadata-eval77.2%
*-commutative77.2%
Simplified77.2%
Final simplification77.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(pow
(-
(* (cos (* phi2 0.5)) (sin (* phi1 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(*
(cos phi1)
(* (cos phi2) (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
t_0))
(sqrt
(+
1.0
(-
(*
(cos phi1)
(* (cos phi2) (- (* 0.5 (cos (- lambda1 lambda2))) 0.5)))
t_0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0);
return R * (2.0 * atan2(sqrt(((cos(phi1) * (cos(phi2) * pow(sin(((lambda1 - lambda2) * 0.5)), 2.0))) + t_0)), sqrt((1.0 + ((cos(phi1) * (cos(phi2) * ((0.5 * cos((lambda1 - lambda2))) - 0.5))) - t_0)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = ((cos((phi2 * 0.5d0)) * sin((phi1 * 0.5d0))) - (cos((phi1 * 0.5d0)) * sin((phi2 * 0.5d0)))) ** 2.0d0
code = r * (2.0d0 * atan2(sqrt(((cos(phi1) * (cos(phi2) * (sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0))) + t_0)), sqrt((1.0d0 + ((cos(phi1) * (cos(phi2) * ((0.5d0 * cos((lambda1 - lambda2))) - 0.5d0))) - t_0)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(((Math.cos((phi2 * 0.5)) * Math.sin((phi1 * 0.5))) - (Math.cos((phi1 * 0.5)) * Math.sin((phi2 * 0.5)))), 2.0);
return R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0))) + t_0)), Math.sqrt((1.0 + ((Math.cos(phi1) * (Math.cos(phi2) * ((0.5 * Math.cos((lambda1 - lambda2))) - 0.5))) - t_0)))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(((math.cos((phi2 * 0.5)) * math.sin((phi1 * 0.5))) - (math.cos((phi1 * 0.5)) * math.sin((phi2 * 0.5)))), 2.0) return R * (2.0 * math.atan2(math.sqrt(((math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0))) + t_0)), math.sqrt((1.0 + ((math.cos(phi1) * (math.cos(phi2) * ((0.5 * math.cos((lambda1 - lambda2))) - 0.5))) - t_0)))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(Float64(cos(Float64(phi2 * 0.5)) * sin(Float64(phi1 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0 return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0))) + t_0)), sqrt(Float64(1.0 + Float64(Float64(cos(phi1) * Float64(cos(phi2) * Float64(Float64(0.5 * cos(Float64(lambda1 - lambda2))) - 0.5))) - t_0)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = ((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))) ^ 2.0; tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * (cos(phi2) * (sin(((lambda1 - lambda2) * 0.5)) ^ 2.0))) + t_0)), sqrt((1.0 + ((cos(phi1) * (cos(phi2) * ((0.5 * cos((lambda1 - lambda2))) - 0.5))) - t_0))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[(N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$0), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 + N[(N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\left(\cos \left(\phi_2 \cdot 0.5\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\right) + t\_0}}{\sqrt{1 + \left(\cos \phi_1 \cdot \left(\cos \phi_2 \cdot \left(0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right) - 0.5\right)\right) - t\_0\right)}}\right)
\end{array}
\end{array}
Initial program 61.7%
associate-*l*61.7%
Simplified61.7%
div-sub61.7%
sin-diff62.5%
Applied egg-rr62.5%
div-sub61.7%
sin-diff62.5%
Applied egg-rr77.2%
sin-mult77.2%
div-inv77.2%
metadata-eval77.2%
div-inv77.2%
metadata-eval77.2%
cos-sum77.2%
cos-277.2%
div-inv77.2%
metadata-eval77.2%
Applied egg-rr77.2%
div-sub77.2%
+-inverses77.2%
cos-077.2%
metadata-eval77.2%
*-commutative77.2%
Simplified77.2%
Taylor expanded in phi1 around 0 77.2%
Final simplification77.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow
(-
(* (sin (/ phi1 2.0)) (cos (/ phi2 2.0)))
(* (cos (/ phi1 2.0)) (sin (/ phi2 2.0))))
2.0)
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(sqrt
(-
1.0
(+
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)
(*
(cos phi1)
(* (cos phi2) (+ 0.5 (* (cos (- lambda1 lambda2)) -0.5))))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((pow(((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))), 2.0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))), sqrt((1.0 - (pow(sin((0.5 * (phi1 - phi2))), 2.0) + (cos(phi1) * (cos(phi2) * (0.5 + (cos((lambda1 - lambda2)) * -0.5)))))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2(sqrt(((((sin((phi1 / 2.0d0)) * cos((phi2 / 2.0d0))) - (cos((phi1 / 2.0d0)) * sin((phi2 / 2.0d0)))) ** 2.0d0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))), sqrt((1.0d0 - ((sin((0.5d0 * (phi1 - phi2))) ** 2.0d0) + (cos(phi1) * (cos(phi2) * (0.5d0 + (cos((lambda1 - lambda2)) * (-0.5d0))))))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(((Math.sin((phi1 / 2.0)) * Math.cos((phi2 / 2.0))) - (Math.cos((phi1 / 2.0)) * Math.sin((phi2 / 2.0)))), 2.0) + ((Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0)))), Math.sqrt((1.0 - (Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0) + (Math.cos(phi1) * (Math.cos(phi2) * (0.5 + (Math.cos((lambda1 - lambda2)) * -0.5)))))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) return R * (2.0 * math.atan2(math.sqrt((math.pow(((math.sin((phi1 / 2.0)) * math.cos((phi2 / 2.0))) - (math.cos((phi1 / 2.0)) * math.sin((phi2 / 2.0)))), 2.0) + ((math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0)))), math.sqrt((1.0 - (math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0) + (math.cos(phi1) * (math.cos(phi2) * (0.5 + (math.cos((lambda1 - lambda2)) * -0.5)))))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((Float64(Float64(sin(Float64(phi1 / 2.0)) * cos(Float64(phi2 / 2.0))) - Float64(cos(Float64(phi1 / 2.0)) * sin(Float64(phi2 / 2.0)))) ^ 2.0) + Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)))), sqrt(Float64(1.0 - Float64((sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0) + Float64(cos(phi1) * Float64(cos(phi2) * Float64(0.5 + Float64(cos(Float64(lambda1 - lambda2)) * -0.5)))))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); tmp = R * (2.0 * atan2(sqrt(((((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))) ^ 2.0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))), sqrt((1.0 - ((sin((0.5 * (phi1 - phi2))) ^ 2.0) + (cos(phi1) * (cos(phi2) * (0.5 + (cos((lambda1 - lambda2)) * -0.5))))))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[(N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 + N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] * -0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\sin \left(\frac{\phi_1}{2}\right) \cdot \cos \left(\frac{\phi_2}{2}\right) - \cos \left(\frac{\phi_1}{2}\right) \cdot \sin \left(\frac{\phi_2}{2}\right)\right)}^{2} + \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right)}}{\sqrt{1 - \left({\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2} + \cos \phi_1 \cdot \left(\cos \phi_2 \cdot \left(0.5 + \cos \left(\lambda_1 - \lambda_2\right) \cdot -0.5\right)\right)\right)}}\right)
\end{array}
\end{array}
Initial program 61.7%
associate-*l*61.7%
Simplified61.7%
div-sub61.7%
sin-diff62.5%
Applied egg-rr62.5%
div-sub61.7%
sin-diff62.5%
Applied egg-rr77.2%
sin-mult77.2%
div-inv77.2%
metadata-eval77.2%
div-inv77.2%
metadata-eval77.2%
cos-sum77.2%
cos-277.2%
div-inv77.2%
metadata-eval77.2%
Applied egg-rr77.2%
div-sub77.2%
+-inverses77.2%
cos-077.2%
metadata-eval77.2%
*-commutative77.2%
Simplified77.2%
sub-neg77.2%
sin-diff62.5%
div-inv62.5%
metadata-eval62.5%
fma-neg62.5%
div-inv62.5%
metadata-eval62.5%
Applied egg-rr62.5%
Simplified62.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_1 (pow (sin (* phi1 0.5)) 2.0))
(t_2 (sin (/ (- lambda1 lambda2) 2.0)))
(t_3 (+ (* (cos phi1) t_0) t_1))
(t_4 (sqrt (- 1.0 t_3))))
(if (<= phi1 -2.6e-5)
(* R (* 2.0 (atan2 (sqrt (fma (cos phi1) t_0 t_1)) t_4)))
(if (<= phi1 3.15e-12)
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (* (cos phi1) (cos phi2)) (* t_2 t_2))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt
(- 1.0 (+ (* (cos phi2) t_0) (pow (sin (* phi2 -0.5)) 2.0)))))))
(* R (* 2.0 (atan2 (sqrt t_3) t_4)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_1 = pow(sin((phi1 * 0.5)), 2.0);
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double t_3 = (cos(phi1) * t_0) + t_1;
double t_4 = sqrt((1.0 - t_3));
double tmp;
if (phi1 <= -2.6e-5) {
tmp = R * (2.0 * atan2(sqrt(fma(cos(phi1), t_0, t_1)), t_4));
} else if (phi1 <= 3.15e-12) {
tmp = R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_2 * t_2)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 - ((cos(phi2) * t_0) + pow(sin((phi2 * -0.5)), 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt(t_3), t_4));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_1 = sin(Float64(phi1 * 0.5)) ^ 2.0 t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_3 = Float64(Float64(cos(phi1) * t_0) + t_1) t_4 = sqrt(Float64(1.0 - t_3)) tmp = 0.0 if (phi1 <= -2.6e-5) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(cos(phi1), t_0, t_1)), t_4))); elseif (phi1 <= 3.15e-12) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_2 * t_2)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * t_0) + (sin(Float64(phi2 * -0.5)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(t_3), t_4))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[(N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision] + t$95$1), $MachinePrecision]}, Block[{t$95$4 = N[Sqrt[N[(1.0 - t$95$3), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi1, -2.6e-5], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Cos[phi1], $MachinePrecision] * t$95$0 + t$95$1), $MachinePrecision]], $MachinePrecision] / t$95$4], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[phi1, 3.15e-12], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$2 * t$95$2), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$3], $MachinePrecision] / t$95$4], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_1 := {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_3 := \cos \phi_1 \cdot t\_0 + t\_1\\
t_4 := \sqrt{1 - t\_3}\\
\mathbf{if}\;\phi_1 \leq -2.6 \cdot 10^{-5}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_1, t\_0, t\_1\right)}}{t\_4}\right)\\
\mathbf{elif}\;\phi_1 \leq 3.15 \cdot 10^{-12}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_2 \cdot t\_2\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{1 - \left(\cos \phi_2 \cdot t\_0 + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_3}}{t\_4}\right)\\
\end{array}
\end{array}
if phi1 < -2.59999999999999984e-5Initial program 43.7%
associate-*l*43.7%
Simplified43.7%
Taylor expanded in phi2 around 0 44.1%
Taylor expanded in phi2 around 0 45.1%
*-commutative45.1%
fma-undefine45.1%
Simplified45.1%
if -2.59999999999999984e-5 < phi1 < 3.1500000000000001e-12Initial program 79.1%
associate-*l*79.1%
Simplified79.1%
Taylor expanded in phi1 around 0 79.1%
if 3.1500000000000001e-12 < phi1 Initial program 42.4%
associate-*l*42.5%
Simplified42.5%
Taylor expanded in phi2 around 0 43.4%
Taylor expanded in phi2 around 0 43.6%
Final simplification62.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))
(t_1 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_2 (sin (/ (- lambda1 lambda2) 2.0)))
(t_3 (pow (sin (* phi2 -0.5)) 2.0))
(t_4 (* (cos phi1) (cos phi2)))
(t_5 (* t_2 (* t_4 t_2)))
(t_6 (+ (* (cos phi2) t_1) t_3)))
(if (<= phi2 -0.00013)
(* R (* 2.0 (atan2 (sqrt t_6) (sqrt (- 1.0 (+ t_0 t_5))))))
(if (<= phi2 2.6)
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_4 (* t_2 t_2)) t_0))
(sqrt (- 1.0 (+ (* (cos phi1) t_1) (pow (sin (* phi1 0.5)) 2.0)))))))
(* R (* 2.0 (atan2 (sqrt (+ t_3 t_5)) (sqrt (- 1.0 t_6)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double t_1 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double t_3 = pow(sin((phi2 * -0.5)), 2.0);
double t_4 = cos(phi1) * cos(phi2);
double t_5 = t_2 * (t_4 * t_2);
double t_6 = (cos(phi2) * t_1) + t_3;
double tmp;
if (phi2 <= -0.00013) {
tmp = R * (2.0 * atan2(sqrt(t_6), sqrt((1.0 - (t_0 + t_5)))));
} else if (phi2 <= 2.6) {
tmp = R * (2.0 * atan2(sqrt(((t_4 * (t_2 * t_2)) + t_0)), sqrt((1.0 - ((cos(phi1) * t_1) + pow(sin((phi1 * 0.5)), 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt((t_3 + t_5)), sqrt((1.0 - t_6))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: t_3
real(8) :: t_4
real(8) :: t_5
real(8) :: t_6
real(8) :: tmp
t_0 = sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0
t_1 = sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0
t_2 = sin(((lambda1 - lambda2) / 2.0d0))
t_3 = sin((phi2 * (-0.5d0))) ** 2.0d0
t_4 = cos(phi1) * cos(phi2)
t_5 = t_2 * (t_4 * t_2)
t_6 = (cos(phi2) * t_1) + t_3
if (phi2 <= (-0.00013d0)) then
tmp = r * (2.0d0 * atan2(sqrt(t_6), sqrt((1.0d0 - (t_0 + t_5)))))
else if (phi2 <= 2.6d0) then
tmp = r * (2.0d0 * atan2(sqrt(((t_4 * (t_2 * t_2)) + t_0)), sqrt((1.0d0 - ((cos(phi1) * t_1) + (sin((phi1 * 0.5d0)) ** 2.0d0))))))
else
tmp = r * (2.0d0 * atan2(sqrt((t_3 + t_5)), sqrt((1.0d0 - t_6))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0);
double t_1 = Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_2 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_3 = Math.pow(Math.sin((phi2 * -0.5)), 2.0);
double t_4 = Math.cos(phi1) * Math.cos(phi2);
double t_5 = t_2 * (t_4 * t_2);
double t_6 = (Math.cos(phi2) * t_1) + t_3;
double tmp;
if (phi2 <= -0.00013) {
tmp = R * (2.0 * Math.atan2(Math.sqrt(t_6), Math.sqrt((1.0 - (t_0 + t_5)))));
} else if (phi2 <= 2.6) {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((t_4 * (t_2 * t_2)) + t_0)), Math.sqrt((1.0 - ((Math.cos(phi1) * t_1) + Math.pow(Math.sin((phi1 * 0.5)), 2.0))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_3 + t_5)), Math.sqrt((1.0 - t_6))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) t_1 = math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0) t_2 = math.sin(((lambda1 - lambda2) / 2.0)) t_3 = math.pow(math.sin((phi2 * -0.5)), 2.0) t_4 = math.cos(phi1) * math.cos(phi2) t_5 = t_2 * (t_4 * t_2) t_6 = (math.cos(phi2) * t_1) + t_3 tmp = 0 if phi2 <= -0.00013: tmp = R * (2.0 * math.atan2(math.sqrt(t_6), math.sqrt((1.0 - (t_0 + t_5))))) elif phi2 <= 2.6: tmp = R * (2.0 * math.atan2(math.sqrt(((t_4 * (t_2 * t_2)) + t_0)), math.sqrt((1.0 - ((math.cos(phi1) * t_1) + math.pow(math.sin((phi1 * 0.5)), 2.0)))))) else: tmp = R * (2.0 * math.atan2(math.sqrt((t_3 + t_5)), math.sqrt((1.0 - t_6)))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_3 = sin(Float64(phi2 * -0.5)) ^ 2.0 t_4 = Float64(cos(phi1) * cos(phi2)) t_5 = Float64(t_2 * Float64(t_4 * t_2)) t_6 = Float64(Float64(cos(phi2) * t_1) + t_3) tmp = 0.0 if (phi2 <= -0.00013) tmp = Float64(R * Float64(2.0 * atan(sqrt(t_6), sqrt(Float64(1.0 - Float64(t_0 + t_5)))))); elseif (phi2 <= 2.6) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_4 * Float64(t_2 * t_2)) + t_0)), sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * t_1) + (sin(Float64(phi1 * 0.5)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_3 + t_5)), sqrt(Float64(1.0 - t_6))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((phi1 - phi2) / 2.0)) ^ 2.0; t_1 = sin(((lambda1 - lambda2) * 0.5)) ^ 2.0; t_2 = sin(((lambda1 - lambda2) / 2.0)); t_3 = sin((phi2 * -0.5)) ^ 2.0; t_4 = cos(phi1) * cos(phi2); t_5 = t_2 * (t_4 * t_2); t_6 = (cos(phi2) * t_1) + t_3; tmp = 0.0; if (phi2 <= -0.00013) tmp = R * (2.0 * atan2(sqrt(t_6), sqrt((1.0 - (t_0 + t_5))))); elseif (phi2 <= 2.6) tmp = R * (2.0 * atan2(sqrt(((t_4 * (t_2 * t_2)) + t_0)), sqrt((1.0 - ((cos(phi1) * t_1) + (sin((phi1 * 0.5)) ^ 2.0)))))); else tmp = R * (2.0 * atan2(sqrt((t_3 + t_5)), sqrt((1.0 - t_6)))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$4 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(t$95$2 * N[(t$95$4 * t$95$2), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$6 = N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$1), $MachinePrecision] + t$95$3), $MachinePrecision]}, If[LessEqual[phi2, -0.00013], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$6], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 + t$95$5), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[phi2, 2.6], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$4 * N[(t$95$2 * t$95$2), $MachinePrecision]), $MachinePrecision] + t$95$0), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * t$95$1), $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$3 + t$95$5), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$6), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
t_1 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_3 := {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\\
t_4 := \cos \phi_1 \cdot \cos \phi_2\\
t_5 := t\_2 \cdot \left(t\_4 \cdot t\_2\right)\\
t_6 := \cos \phi_2 \cdot t\_1 + t\_3\\
\mathbf{if}\;\phi_2 \leq -0.00013:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_6}}{\sqrt{1 - \left(t\_0 + t\_5\right)}}\right)\\
\mathbf{elif}\;\phi_2 \leq 2.6:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_4 \cdot \left(t\_2 \cdot t\_2\right) + t\_0}}{\sqrt{1 - \left(\cos \phi_1 \cdot t\_1 + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_3 + t\_5}}{\sqrt{1 - t\_6}}\right)\\
\end{array}
\end{array}
if phi2 < -1.29999999999999989e-4Initial program 44.2%
Taylor expanded in phi1 around 0 43.4%
Taylor expanded in phi1 around 0 44.4%
if -1.29999999999999989e-4 < phi2 < 2.60000000000000009Initial program 75.9%
associate-*l*75.9%
Simplified75.9%
Taylor expanded in phi2 around 0 75.5%
if 2.60000000000000009 < phi2 Initial program 47.9%
Taylor expanded in phi1 around 0 47.4%
Taylor expanded in phi1 around 0 49.0%
Final simplification61.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))
(t_2 (* (cos phi1) (cos phi2))))
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_2 (* t_0 t_0)) t_1))
(sqrt
(+
(- 1.0 t_1)
(*
t_2
(- (/ (cos (* 2.0 (* (- lambda1 lambda2) 0.5))) 2.0) 0.5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double t_2 = cos(phi1) * cos(phi2);
return R * (2.0 * atan2(sqrt(((t_2 * (t_0 * t_0)) + t_1)), sqrt(((1.0 - t_1) + (t_2 * ((cos((2.0 * ((lambda1 - lambda2) * 0.5))) / 2.0) - 0.5))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0
t_2 = cos(phi1) * cos(phi2)
code = r * (2.0d0 * atan2(sqrt(((t_2 * (t_0 * t_0)) + t_1)), sqrt(((1.0d0 - t_1) + (t_2 * ((cos((2.0d0 * ((lambda1 - lambda2) * 0.5d0))) / 2.0d0) - 0.5d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0);
double t_2 = Math.cos(phi1) * Math.cos(phi2);
return R * (2.0 * Math.atan2(Math.sqrt(((t_2 * (t_0 * t_0)) + t_1)), Math.sqrt(((1.0 - t_1) + (t_2 * ((Math.cos((2.0 * ((lambda1 - lambda2) * 0.5))) / 2.0) - 0.5))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) t_2 = math.cos(phi1) * math.cos(phi2) return R * (2.0 * math.atan2(math.sqrt(((t_2 * (t_0 * t_0)) + t_1)), math.sqrt(((1.0 - t_1) + (t_2 * ((math.cos((2.0 * ((lambda1 - lambda2) * 0.5))) / 2.0) - 0.5))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 t_2 = Float64(cos(phi1) * cos(phi2)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_2 * Float64(t_0 * t_0)) + t_1)), sqrt(Float64(Float64(1.0 - t_1) + Float64(t_2 * Float64(Float64(cos(Float64(2.0 * Float64(Float64(lambda1 - lambda2) * 0.5))) / 2.0) - 0.5))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = sin(((phi1 - phi2) / 2.0)) ^ 2.0; t_2 = cos(phi1) * cos(phi2); tmp = R * (2.0 * atan2(sqrt(((t_2 * (t_0 * t_0)) + t_1)), sqrt(((1.0 - t_1) + (t_2 * ((cos((2.0 * ((lambda1 - lambda2) * 0.5))) / 2.0) - 0.5)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$2 * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - t$95$1), $MachinePrecision] + N[(t$95$2 * N[(N[(N[Cos[N[(2.0 * N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 \cdot \left(t\_0 \cdot t\_0\right) + t\_1}}{\sqrt{\left(1 - t\_1\right) + t\_2 \cdot \left(\frac{\cos \left(2 \cdot \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)\right)}{2} - 0.5\right)}}\right)
\end{array}
\end{array}
Initial program 61.7%
associate-*l*61.7%
Simplified61.7%
sin-mult77.2%
div-inv77.2%
metadata-eval77.2%
div-inv77.2%
metadata-eval77.2%
cos-sum77.2%
cos-277.2%
div-inv77.2%
metadata-eval77.2%
Applied egg-rr61.7%
div-sub77.2%
+-inverses77.2%
cos-077.2%
metadata-eval77.2%
*-commutative77.2%
Simplified61.7%
Final simplification61.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_1 (pow (sin (* phi1 0.5)) 2.0))
(t_2 (pow (sin (* phi2 -0.5)) 2.0))
(t_3 (+ (* (cos phi1) t_0) t_1))
(t_4 (sqrt (- 1.0 t_3)))
(t_5 (sin (/ (- lambda1 lambda2) 2.0))))
(if (<= phi1 -7.2e-34)
(* R (* 2.0 (atan2 (sqrt (fma (cos phi1) t_0 t_1)) t_4)))
(if (<= phi1 5.8e-14)
(*
R
(*
2.0
(atan2
(sqrt (+ t_2 (* t_5 (* (* (cos phi1) (cos phi2)) t_5))))
(sqrt (- 1.0 (+ (* (cos phi2) t_0) t_2))))))
(* R (* 2.0 (atan2 (sqrt t_3) t_4)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_1 = pow(sin((phi1 * 0.5)), 2.0);
double t_2 = pow(sin((phi2 * -0.5)), 2.0);
double t_3 = (cos(phi1) * t_0) + t_1;
double t_4 = sqrt((1.0 - t_3));
double t_5 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if (phi1 <= -7.2e-34) {
tmp = R * (2.0 * atan2(sqrt(fma(cos(phi1), t_0, t_1)), t_4));
} else if (phi1 <= 5.8e-14) {
tmp = R * (2.0 * atan2(sqrt((t_2 + (t_5 * ((cos(phi1) * cos(phi2)) * t_5)))), sqrt((1.0 - ((cos(phi2) * t_0) + t_2)))));
} else {
tmp = R * (2.0 * atan2(sqrt(t_3), t_4));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_1 = sin(Float64(phi1 * 0.5)) ^ 2.0 t_2 = sin(Float64(phi2 * -0.5)) ^ 2.0 t_3 = Float64(Float64(cos(phi1) * t_0) + t_1) t_4 = sqrt(Float64(1.0 - t_3)) t_5 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if (phi1 <= -7.2e-34) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(cos(phi1), t_0, t_1)), t_4))); elseif (phi1 <= 5.8e-14) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_2 + Float64(t_5 * Float64(Float64(cos(phi1) * cos(phi2)) * t_5)))), sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * t_0) + t_2)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(t_3), t_4))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$3 = N[(N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision] + t$95$1), $MachinePrecision]}, Block[{t$95$4 = N[Sqrt[N[(1.0 - t$95$3), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$5 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi1, -7.2e-34], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Cos[phi1], $MachinePrecision] * t$95$0 + t$95$1), $MachinePrecision]], $MachinePrecision] / t$95$4], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[phi1, 5.8e-14], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$2 + N[(t$95$5 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision] + t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$3], $MachinePrecision] / t$95$4], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_1 := {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\\
t_2 := {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\\
t_3 := \cos \phi_1 \cdot t\_0 + t\_1\\
t_4 := \sqrt{1 - t\_3}\\
t_5 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\phi_1 \leq -7.2 \cdot 10^{-34}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_1, t\_0, t\_1\right)}}{t\_4}\right)\\
\mathbf{elif}\;\phi_1 \leq 5.8 \cdot 10^{-14}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 + t\_5 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_5\right)}}{\sqrt{1 - \left(\cos \phi_2 \cdot t\_0 + t\_2\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_3}}{t\_4}\right)\\
\end{array}
\end{array}
if phi1 < -7.20000000000000016e-34Initial program 47.1%
associate-*l*47.0%
Simplified47.0%
Taylor expanded in phi2 around 0 46.1%
Taylor expanded in phi2 around 0 47.0%
*-commutative47.0%
fma-undefine47.0%
Simplified47.0%
if -7.20000000000000016e-34 < phi1 < 5.8000000000000005e-14Initial program 80.1%
Taylor expanded in phi1 around 0 76.9%
Taylor expanded in phi1 around 0 77.0%
if 5.8000000000000005e-14 < phi1 Initial program 42.4%
associate-*l*42.5%
Simplified42.5%
Taylor expanded in phi2 around 0 43.4%
Taylor expanded in phi2 around 0 43.6%
Final simplification60.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(if (or (<= phi2 -0.0102) (not (<= phi2 2.6)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)
(* (cos phi1) (* (cos phi2) (pow (sin (* lambda1 0.5)) 2.0)))))
(sqrt
(-
1.0
(+
(* (cos phi2) (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(pow (sin (* phi2 0.5)) 2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))
(pow (sin (/ 1.0 (/ 2.0 (- phi1 phi2)))) 2.0)))
(sqrt
(+
1.0
(-
(* (cos phi1) (- (/ (cos (- lambda1 lambda2)) 2.0) 0.5))
(pow (sin (* phi1 0.5)) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((phi2 <= -0.0102) || !(phi2 <= 2.6)) {
tmp = R * (2.0 * atan2(sqrt((pow(sin((0.5 * (phi1 - phi2))), 2.0) + (cos(phi1) * (cos(phi2) * pow(sin((lambda1 * 0.5)), 2.0))))), sqrt((1.0 - ((cos(phi2) * pow(sin(((lambda1 - lambda2) * 0.5)), 2.0)) + pow(sin((phi2 * 0.5)), 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + pow(sin((1.0 / (2.0 / (phi1 - phi2)))), 2.0))), sqrt((1.0 + ((cos(phi1) * ((cos((lambda1 - lambda2)) / 2.0) - 0.5)) - pow(sin((phi1 * 0.5)), 2.0))))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
if ((phi2 <= (-0.0102d0)) .or. (.not. (phi2 <= 2.6d0))) then
tmp = r * (2.0d0 * atan2(sqrt(((sin((0.5d0 * (phi1 - phi2))) ** 2.0d0) + (cos(phi1) * (cos(phi2) * (sin((lambda1 * 0.5d0)) ** 2.0d0))))), sqrt((1.0d0 - ((cos(phi2) * (sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0)) + (sin((phi2 * 0.5d0)) ** 2.0d0))))))
else
tmp = r * (2.0d0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + (sin((1.0d0 / (2.0d0 / (phi1 - phi2)))) ** 2.0d0))), sqrt((1.0d0 + ((cos(phi1) * ((cos((lambda1 - lambda2)) / 2.0d0) - 0.5d0)) - (sin((phi1 * 0.5d0)) ** 2.0d0))))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((phi2 <= -0.0102) || !(phi2 <= 2.6)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0) + (Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((lambda1 * 0.5)), 2.0))))), Math.sqrt((1.0 - ((Math.cos(phi2) * Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0)) + Math.pow(Math.sin((phi2 * 0.5)), 2.0))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((((Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0)) + Math.pow(Math.sin((1.0 / (2.0 / (phi1 - phi2)))), 2.0))), Math.sqrt((1.0 + ((Math.cos(phi1) * ((Math.cos((lambda1 - lambda2)) / 2.0) - 0.5)) - Math.pow(Math.sin((phi1 * 0.5)), 2.0))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) tmp = 0 if (phi2 <= -0.0102) or not (phi2 <= 2.6): tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0) + (math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((lambda1 * 0.5)), 2.0))))), math.sqrt((1.0 - ((math.cos(phi2) * math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0)) + math.pow(math.sin((phi2 * 0.5)), 2.0)))))) else: tmp = R * (2.0 * math.atan2(math.sqrt((((math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0)) + math.pow(math.sin((1.0 / (2.0 / (phi1 - phi2)))), 2.0))), math.sqrt((1.0 + ((math.cos(phi1) * ((math.cos((lambda1 - lambda2)) / 2.0) - 0.5)) - math.pow(math.sin((phi1 * 0.5)), 2.0)))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if ((phi2 <= -0.0102) || !(phi2 <= 2.6)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0) + Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(lambda1 * 0.5)) ^ 2.0))))), sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0)) + (sin(Float64(phi2 * 0.5)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) + (sin(Float64(1.0 / Float64(2.0 / Float64(phi1 - phi2)))) ^ 2.0))), sqrt(Float64(1.0 + Float64(Float64(cos(phi1) * Float64(Float64(cos(Float64(lambda1 - lambda2)) / 2.0) - 0.5)) - (sin(Float64(phi1 * 0.5)) ^ 2.0))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); tmp = 0.0; if ((phi2 <= -0.0102) || ~((phi2 <= 2.6))) tmp = R * (2.0 * atan2(sqrt(((sin((0.5 * (phi1 - phi2))) ^ 2.0) + (cos(phi1) * (cos(phi2) * (sin((lambda1 * 0.5)) ^ 2.0))))), sqrt((1.0 - ((cos(phi2) * (sin(((lambda1 - lambda2) * 0.5)) ^ 2.0)) + (sin((phi2 * 0.5)) ^ 2.0)))))); else tmp = R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + (sin((1.0 / (2.0 / (phi1 - phi2)))) ^ 2.0))), sqrt((1.0 + ((cos(phi1) * ((cos((lambda1 - lambda2)) / 2.0) - 0.5)) - (sin((phi1 * 0.5)) ^ 2.0)))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[phi2, -0.0102], N[Not[LessEqual[phi2, 2.6]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(1.0 / N[(2.0 / N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 + N[(N[(N[Cos[phi1], $MachinePrecision] * N[(N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision] - N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\phi_2 \leq -0.0102 \lor \neg \left(\phi_2 \leq 2.6\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2} + \cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(\lambda_1 \cdot 0.5\right)}^{2}\right)}}{\sqrt{1 - \left(\cos \phi_2 \cdot {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2} + {\sin \left(\phi_2 \cdot 0.5\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right) + {\sin \left(\frac{1}{\frac{2}{\phi_1 - \phi_2}}\right)}^{2}}}{\sqrt{1 + \left(\cos \phi_1 \cdot \left(\frac{\cos \left(\lambda_1 - \lambda_2\right)}{2} - 0.5\right) - {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}\right)\\
\end{array}
\end{array}
if phi2 < -0.010200000000000001 or 2.60000000000000009 < phi2 Initial program 45.6%
associate-*l*45.6%
Simplified45.6%
div-sub45.6%
sin-diff47.3%
Applied egg-rr47.3%
Taylor expanded in lambda2 around 0 39.5%
Taylor expanded in phi1 around 0 38.6%
if -0.010200000000000001 < phi2 < 2.60000000000000009Initial program 76.1%
associate-*l*76.1%
Simplified76.1%
Taylor expanded in phi2 around 0 75.3%
clear-num72.4%
inv-pow72.4%
Applied egg-rr72.4%
unpow-172.4%
Simplified72.4%
*-commutative72.4%
metadata-eval72.4%
div-inv72.4%
pow272.4%
sin-mult72.5%
Applied egg-rr72.5%
div-sub72.5%
+-inverses72.5%
cos-072.5%
metadata-eval72.5%
Simplified72.5%
Final simplification56.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))
(pow (sin (/ 1.0 (/ 2.0 (- phi1 phi2)))) 2.0)))
(sqrt
(+
1.0
(-
(* (cos phi1) (- (/ (cos (- lambda1 lambda2)) 2.0) 0.5))
(pow (sin (* phi1 0.5)) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + pow(sin((1.0 / (2.0 / (phi1 - phi2)))), 2.0))), sqrt((1.0 + ((cos(phi1) * ((cos((lambda1 - lambda2)) / 2.0) - 0.5)) - pow(sin((phi1 * 0.5)), 2.0))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + (sin((1.0d0 / (2.0d0 / (phi1 - phi2)))) ** 2.0d0))), sqrt((1.0d0 + ((cos(phi1) * ((cos((lambda1 - lambda2)) / 2.0d0) - 0.5d0)) - (sin((phi1 * 0.5d0)) ** 2.0d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((((Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0)) + Math.pow(Math.sin((1.0 / (2.0 / (phi1 - phi2)))), 2.0))), Math.sqrt((1.0 + ((Math.cos(phi1) * ((Math.cos((lambda1 - lambda2)) / 2.0) - 0.5)) - Math.pow(Math.sin((phi1 * 0.5)), 2.0))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) return R * (2.0 * math.atan2(math.sqrt((((math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0)) + math.pow(math.sin((1.0 / (2.0 / (phi1 - phi2)))), 2.0))), math.sqrt((1.0 + ((math.cos(phi1) * ((math.cos((lambda1 - lambda2)) / 2.0) - 0.5)) - math.pow(math.sin((phi1 * 0.5)), 2.0))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) + (sin(Float64(1.0 / Float64(2.0 / Float64(phi1 - phi2)))) ^ 2.0))), sqrt(Float64(1.0 + Float64(Float64(cos(phi1) * Float64(Float64(cos(Float64(lambda1 - lambda2)) / 2.0) - 0.5)) - (sin(Float64(phi1 * 0.5)) ^ 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); tmp = R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + (sin((1.0 / (2.0 / (phi1 - phi2)))) ^ 2.0))), sqrt((1.0 + ((cos(phi1) * ((cos((lambda1 - lambda2)) / 2.0) - 0.5)) - (sin((phi1 * 0.5)) ^ 2.0)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(1.0 / N[(2.0 / N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 + N[(N[(N[Cos[phi1], $MachinePrecision] * N[(N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision] - N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right) + {\sin \left(\frac{1}{\frac{2}{\phi_1 - \phi_2}}\right)}^{2}}}{\sqrt{1 + \left(\cos \phi_1 \cdot \left(\frac{\cos \left(\lambda_1 - \lambda_2\right)}{2} - 0.5\right) - {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 61.7%
associate-*l*61.7%
Simplified61.7%
Taylor expanded in phi2 around 0 49.4%
clear-num47.8%
inv-pow47.8%
Applied egg-rr47.8%
unpow-147.8%
Simplified47.8%
*-commutative47.8%
metadata-eval47.8%
div-inv47.8%
pow247.8%
sin-mult47.9%
Applied egg-rr47.9%
div-sub47.9%
+-inverses47.9%
cos-047.9%
metadata-eval47.9%
Simplified47.9%
Final simplification47.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(+
(* (cos phi1) (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(pow (sin (* phi1 0.5)) 2.0))))
(* R (* 2.0 (atan2 (sqrt t_0) (sqrt (- 1.0 t_0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = (cos(phi1) * pow(sin(((lambda1 - lambda2) * 0.5)), 2.0)) + pow(sin((phi1 * 0.5)), 2.0);
return R * (2.0 * atan2(sqrt(t_0), sqrt((1.0 - t_0))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = (cos(phi1) * (sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0)) + (sin((phi1 * 0.5d0)) ** 2.0d0)
code = r * (2.0d0 * atan2(sqrt(t_0), sqrt((1.0d0 - t_0))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = (Math.cos(phi1) * Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0)) + Math.pow(Math.sin((phi1 * 0.5)), 2.0);
return R * (2.0 * Math.atan2(Math.sqrt(t_0), Math.sqrt((1.0 - t_0))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = (math.cos(phi1) * math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0)) + math.pow(math.sin((phi1 * 0.5)), 2.0) return R * (2.0 * math.atan2(math.sqrt(t_0), math.sqrt((1.0 - t_0))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(Float64(cos(phi1) * (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0)) + (sin(Float64(phi1 * 0.5)) ^ 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(t_0), sqrt(Float64(1.0 - t_0))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = (cos(phi1) * (sin(((lambda1 - lambda2) * 0.5)) ^ 2.0)) + (sin((phi1 * 0.5)) ^ 2.0); tmp = R * (2.0 * atan2(sqrt(t_0), sqrt((1.0 - t_0)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$0], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2} + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0}}{\sqrt{1 - t\_0}}\right)
\end{array}
\end{array}
Initial program 61.7%
associate-*l*61.7%
Simplified61.7%
Taylor expanded in phi2 around 0 49.4%
Taylor expanded in phi2 around 0 46.7%
Final simplification46.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (- 1.0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 - pow(sin(((lambda1 - lambda2) * 0.5)), 2.0)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt((1.0d0 - (sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((((Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0)) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt((1.0 - Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0)))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) return R * (2.0 * math.atan2(math.sqrt((((math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0)) + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt((1.0 - math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0)))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); tmp = R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt((1.0 - (sin(((lambda1 - lambda2) * 0.5)) ^ 2.0))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{1 - {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}}}\right)
\end{array}
\end{array}
Initial program 61.7%
associate-*l*61.7%
Simplified61.7%
Taylor expanded in phi2 around 0 49.4%
Taylor expanded in phi1 around 0 38.3%
Final simplification38.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* (cos phi2) (* t_0 t_0))))
(sqrt (- 1.0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (cos(phi2) * (t_0 * t_0)))), sqrt((1.0 - pow(sin(((lambda1 - lambda2) * 0.5)), 2.0)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (cos(phi2) * (t_0 * t_0)))), sqrt((1.0d0 - (sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (Math.cos(phi2) * (t_0 * t_0)))), Math.sqrt((1.0 - Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0)))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) return R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (math.cos(phi2) * (t_0 * t_0)))), math.sqrt((1.0 - math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0)))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(cos(phi2) * Float64(t_0 * t_0)))), sqrt(Float64(1.0 - (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (cos(phi2) * (t_0 * t_0)))), sqrt((1.0 - (sin(((lambda1 - lambda2) * 0.5)) ^ 2.0))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi2], $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \cos \phi_2 \cdot \left(t\_0 \cdot t\_0\right)}}{\sqrt{1 - {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}}}\right)
\end{array}
\end{array}
Initial program 61.7%
associate-*l*61.7%
Simplified61.7%
Taylor expanded in phi2 around 0 49.4%
Taylor expanded in phi1 around 0 38.3%
Taylor expanded in phi1 around 0 38.1%
Final simplification38.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
(*
R
(*
2.0
(atan2
(sqrt (+ (* (cos phi2) t_0) (pow (sin (* phi2 -0.5)) 2.0)))
(sqrt (- 1.0 t_0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
return R * (2.0 * atan2(sqrt(((cos(phi2) * t_0) + pow(sin((phi2 * -0.5)), 2.0))), sqrt((1.0 - t_0))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0
code = r * (2.0d0 * atan2(sqrt(((cos(phi2) * t_0) + (sin((phi2 * (-0.5d0))) ** 2.0d0))), sqrt((1.0d0 - t_0))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0);
return R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi2) * t_0) + Math.pow(Math.sin((phi2 * -0.5)), 2.0))), Math.sqrt((1.0 - t_0))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0) return R * (2.0 * math.atan2(math.sqrt(((math.cos(phi2) * t_0) + math.pow(math.sin((phi2 * -0.5)), 2.0))), math.sqrt((1.0 - t_0))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi2) * t_0) + (sin(Float64(phi2 * -0.5)) ^ 2.0))), sqrt(Float64(1.0 - t_0))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) * 0.5)) ^ 2.0; tmp = R * (2.0 * atan2(sqrt(((cos(phi2) * t_0) + (sin((phi2 * -0.5)) ^ 2.0))), sqrt((1.0 - t_0)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot t\_0 + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}}}{\sqrt{1 - t\_0}}\right)
\end{array}
\end{array}
Initial program 61.7%
associate-*l*61.7%
Simplified61.7%
Taylor expanded in phi2 around 0 49.4%
Taylor expanded in phi1 around 0 38.3%
Taylor expanded in phi1 around 0 35.8%
Final simplification35.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (cos phi1) (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(pow (sin (* phi1 0.5)) 2.0)))
(sqrt (+ 0.5 (* 0.5 (cos (- lambda1 lambda2)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2(sqrt(((cos(phi1) * pow(sin(((lambda1 - lambda2) * 0.5)), 2.0)) + pow(sin((phi1 * 0.5)), 2.0))), sqrt((0.5 + (0.5 * cos((lambda1 - lambda2)))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
code = r * (2.0d0 * atan2(sqrt(((cos(phi1) * (sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0)) + (sin((phi1 * 0.5d0)) ** 2.0d0))), sqrt((0.5d0 + (0.5d0 * cos((lambda1 - lambda2)))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi1) * Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0)) + Math.pow(Math.sin((phi1 * 0.5)), 2.0))), Math.sqrt((0.5 + (0.5 * Math.cos((lambda1 - lambda2)))))));
}
def code(R, lambda1, lambda2, phi1, phi2): return R * (2.0 * math.atan2(math.sqrt(((math.cos(phi1) * math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0)) + math.pow(math.sin((phi1 * 0.5)), 2.0))), math.sqrt((0.5 + (0.5 * math.cos((lambda1 - lambda2)))))))
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi1) * (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0)) + (sin(Float64(phi1 * 0.5)) ^ 2.0))), sqrt(Float64(0.5 + Float64(0.5 * cos(Float64(lambda1 - lambda2)))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * (sin(((lambda1 - lambda2) * 0.5)) ^ 2.0)) + (sin((phi1 * 0.5)) ^ 2.0))), sqrt((0.5 + (0.5 * cos((lambda1 - lambda2))))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(0.5 + N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_1 \cdot {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2} + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}}}{\sqrt{0.5 + 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)}}\right)
\end{array}
Initial program 61.7%
associate-*l*61.7%
Simplified61.7%
Taylor expanded in phi2 around 0 49.4%
Taylor expanded in phi1 around 0 38.3%
Taylor expanded in phi2 around 0 35.7%
*-un-lft-identity35.7%
*-commutative35.7%
metadata-eval35.7%
div-inv35.7%
pow235.7%
1-sub-sin35.7%
sqr-cos-a35.7%
div-inv35.7%
metadata-eval35.7%
*-commutative35.7%
associate-*r*35.7%
metadata-eval35.7%
*-un-lft-identity35.7%
Applied egg-rr35.7%
*-lft-identity35.7%
Simplified35.7%
Final simplification35.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
(* R 2.0)
(atan2
(hypot
(sin (* phi1 0.5))
(sqrt (* (cos phi1) (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))))
(sqrt (+ 0.5 (* 0.5 (cos (- lambda1 lambda2))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return (R * 2.0) * atan2(hypot(sin((phi1 * 0.5)), sqrt((cos(phi1) * pow(sin(((lambda1 - lambda2) * 0.5)), 2.0)))), sqrt((0.5 + (0.5 * cos((lambda1 - lambda2))))));
}
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return (R * 2.0) * Math.atan2(Math.hypot(Math.sin((phi1 * 0.5)), Math.sqrt((Math.cos(phi1) * Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0)))), Math.sqrt((0.5 + (0.5 * Math.cos((lambda1 - lambda2))))));
}
def code(R, lambda1, lambda2, phi1, phi2): return (R * 2.0) * math.atan2(math.hypot(math.sin((phi1 * 0.5)), math.sqrt((math.cos(phi1) * math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0)))), math.sqrt((0.5 + (0.5 * math.cos((lambda1 - lambda2))))))
function code(R, lambda1, lambda2, phi1, phi2) return Float64(Float64(R * 2.0) * atan(hypot(sin(Float64(phi1 * 0.5)), sqrt(Float64(cos(phi1) * (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0)))), sqrt(Float64(0.5 + Float64(0.5 * cos(Float64(lambda1 - lambda2))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) tmp = (R * 2.0) * atan2(hypot(sin((phi1 * 0.5)), sqrt((cos(phi1) * (sin(((lambda1 - lambda2) * 0.5)) ^ 2.0)))), sqrt((0.5 + (0.5 * cos((lambda1 - lambda2)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] ^ 2 + N[Sqrt[N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(0.5 + N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(\sin \left(\phi_1 \cdot 0.5\right), \sqrt{\cos \phi_1 \cdot {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}}\right)}{\sqrt{0.5 + 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)}}
\end{array}
Initial program 61.7%
associate-*l*61.7%
Simplified61.7%
Taylor expanded in phi2 around 0 49.4%
Taylor expanded in phi1 around 0 38.3%
Taylor expanded in phi2 around 0 35.7%
Applied egg-rr31.0%
unpow131.0%
associate-*r*31.0%
*-commutative31.0%
*-commutative31.0%
Simplified31.0%
Final simplification31.0%
(FPCore (R lambda1 lambda2 phi1 phi2) :precision binary64 (let* ((t_0 (sin (* (- lambda1 lambda2) 0.5)))) (* R (* 2.0 (atan2 t_0 (sqrt (- 1.0 (pow t_0 2.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) * 0.5));
return R * (2.0 * atan2(t_0, sqrt((1.0 - pow(t_0, 2.0)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin(((lambda1 - lambda2) * 0.5d0))
code = r * (2.0d0 * atan2(t_0, sqrt((1.0d0 - (t_0 ** 2.0d0)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) * 0.5));
return R * (2.0 * Math.atan2(t_0, Math.sqrt((1.0 - Math.pow(t_0, 2.0)))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) * 0.5)) return R * (2.0 * math.atan2(t_0, math.sqrt((1.0 - math.pow(t_0, 2.0)))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) return Float64(R * Float64(2.0 * atan(t_0, sqrt(Float64(1.0 - (t_0 ^ 2.0)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) * 0.5)); tmp = R * (2.0 * atan2(t_0, sqrt((1.0 - (t_0 ^ 2.0))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[t$95$0 / N[Sqrt[N[(1.0 - N[Power[t$95$0, 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_0}{\sqrt{1 - {t\_0}^{2}}}\right)
\end{array}
\end{array}
Initial program 61.7%
associate-*l*61.7%
Simplified61.7%
Taylor expanded in phi2 around 0 49.4%
Taylor expanded in phi1 around 0 38.3%
Taylor expanded in phi2 around 0 35.7%
Taylor expanded in phi1 around 0 17.9%
Final simplification17.9%
herbie shell --seed 2024150
(FPCore (R lambda1 lambda2 phi1 phi2)
:name "Distance on a great circle"
:precision binary64
(* R (* 2.0 (atan2 (sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* (* (* (cos phi1) (cos phi2)) (sin (/ (- lambda1 lambda2) 2.0))) (sin (/ (- lambda1 lambda2) 2.0))))) (sqrt (- 1.0 (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* (* (* (cos phi1) (cos phi2)) (sin (/ (- lambda1 lambda2) 2.0))) (sin (/ (- lambda1 lambda2) 2.0))))))))))