
(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 29 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
(pow
(-
(* (cos (* 0.5 phi2)) (sin (* phi1 0.5)))
(* (cos (* phi1 0.5)) (sin (* 0.5 phi2))))
2.0))
(t_1 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_0 (* (* (cos phi1) (cos phi2)) (* t_1 t_1))))
(sqrt
(+
(- 1.0 t_0)
(-
1.0
(exp
(log1p
(*
(cos phi1)
(*
(cos phi2)
(pow
(-
(* (sin (/ lambda1 2.0)) (cos (/ lambda2 2.0)))
(* (cos (/ lambda1 2.0)) (sin (/ lambda2 2.0))))
2.0)))))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((0.5 * phi2)))), 2.0);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((t_0 + ((cos(phi1) * cos(phi2)) * (t_1 * t_1)))), sqrt(((1.0 - t_0) + (1.0 - exp(log1p((cos(phi1) * (cos(phi2) * pow(((sin((lambda1 / 2.0)) * cos((lambda2 / 2.0))) - (cos((lambda1 / 2.0)) * sin((lambda2 / 2.0)))), 2.0))))))))));
}
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(((Math.cos((0.5 * phi2)) * Math.sin((phi1 * 0.5))) - (Math.cos((phi1 * 0.5)) * Math.sin((0.5 * phi2)))), 2.0);
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((t_0 + ((Math.cos(phi1) * Math.cos(phi2)) * (t_1 * t_1)))), Math.sqrt(((1.0 - t_0) + (1.0 - Math.exp(Math.log1p((Math.cos(phi1) * (Math.cos(phi2) * Math.pow(((Math.sin((lambda1 / 2.0)) * Math.cos((lambda2 / 2.0))) - (Math.cos((lambda1 / 2.0)) * Math.sin((lambda2 / 2.0)))), 2.0))))))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(((math.cos((0.5 * phi2)) * math.sin((phi1 * 0.5))) - (math.cos((phi1 * 0.5)) * math.sin((0.5 * phi2)))), 2.0) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) return R * (2.0 * math.atan2(math.sqrt((t_0 + ((math.cos(phi1) * math.cos(phi2)) * (t_1 * t_1)))), math.sqrt(((1.0 - t_0) + (1.0 - math.exp(math.log1p((math.cos(phi1) * (math.cos(phi2) * math.pow(((math.sin((lambda1 / 2.0)) * math.cos((lambda2 / 2.0))) - (math.cos((lambda1 / 2.0)) * math.sin((lambda2 / 2.0)))), 2.0))))))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(Float64(cos(Float64(0.5 * phi2)) * sin(Float64(phi1 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(0.5 * phi2)))) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_0 + Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_1 * t_1)))), sqrt(Float64(Float64(1.0 - t_0) + Float64(1.0 - exp(log1p(Float64(cos(phi1) * Float64(cos(phi2) * (Float64(Float64(sin(Float64(lambda1 / 2.0)) * cos(Float64(lambda2 / 2.0))) - Float64(cos(Float64(lambda1 / 2.0)) * sin(Float64(lambda2 / 2.0)))) ^ 2.0))))))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 + N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$1 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - t$95$0), $MachinePrecision] + N[(1.0 - N[Exp[N[Log[1 + N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[(N[(N[Sin[N[(lambda1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(lambda2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(lambda1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(lambda2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\left(\cos \left(0.5 \cdot \phi_2\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(0.5 \cdot \phi_2\right)\right)}^{2}\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 + \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_1 \cdot t\_1\right)}}{\sqrt{\left(1 - t\_0\right) + \left(1 - e^{\mathsf{log1p}\left(\cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\left(\sin \left(\frac{\lambda_1}{2}\right) \cdot \cos \left(\frac{\lambda_2}{2}\right) - \cos \left(\frac{\lambda_1}{2}\right) \cdot \sin \left(\frac{\lambda_2}{2}\right)\right)}^{2}\right)\right)}\right)}}\right)
\end{array}
\end{array}
Initial program 63.0%
associate-*l*63.0%
Simplified63.0%
div-sub63.0%
sin-diff64.0%
div-inv64.0%
metadata-eval64.0%
div-inv64.0%
metadata-eval64.0%
div-inv64.0%
metadata-eval64.0%
div-inv64.0%
metadata-eval64.0%
Applied egg-rr64.0%
div-sub63.0%
sin-diff64.0%
div-inv64.0%
metadata-eval64.0%
div-inv64.0%
metadata-eval64.0%
div-inv64.0%
metadata-eval64.0%
div-inv64.0%
metadata-eval64.0%
Applied egg-rr78.7%
expm1-log1p-u78.7%
expm1-undefine78.8%
pow278.8%
div-inv78.8%
metadata-eval78.8%
*-commutative78.8%
associate-*r*78.8%
Applied egg-rr78.8%
*-commutative78.8%
metadata-eval78.8%
div-inv78.8%
div-sub78.8%
sin-diff79.3%
Applied egg-rr79.3%
Final simplification79.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(pow
(-
(* (cos (* 0.5 phi2)) (sin (* phi1 0.5)))
(* (cos (* phi1 0.5)) (sin (* 0.5 phi2))))
2.0))
(t_1 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_0 (* (* (cos phi1) (cos phi2)) (* t_1 t_1))))
(sqrt
(+
(- 1.0 t_0)
(-
1.0
(exp
(log1p
(*
(cos phi1)
(*
(cos phi2)
(pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((0.5 * phi2)))), 2.0);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((t_0 + ((cos(phi1) * cos(phi2)) * (t_1 * t_1)))), sqrt(((1.0 - t_0) + (1.0 - exp(log1p((cos(phi1) * (cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0))))))))));
}
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(((Math.cos((0.5 * phi2)) * Math.sin((phi1 * 0.5))) - (Math.cos((phi1 * 0.5)) * Math.sin((0.5 * phi2)))), 2.0);
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((t_0 + ((Math.cos(phi1) * Math.cos(phi2)) * (t_1 * t_1)))), Math.sqrt(((1.0 - t_0) + (1.0 - Math.exp(Math.log1p((Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0))))))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(((math.cos((0.5 * phi2)) * math.sin((phi1 * 0.5))) - (math.cos((phi1 * 0.5)) * math.sin((0.5 * phi2)))), 2.0) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) return R * (2.0 * math.atan2(math.sqrt((t_0 + ((math.cos(phi1) * math.cos(phi2)) * (t_1 * t_1)))), math.sqrt(((1.0 - t_0) + (1.0 - math.exp(math.log1p((math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0))))))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(Float64(cos(Float64(0.5 * phi2)) * sin(Float64(phi1 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(0.5 * phi2)))) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_0 + Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_1 * t_1)))), sqrt(Float64(Float64(1.0 - t_0) + Float64(1.0 - exp(log1p(Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0))))))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 + N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$1 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - t$95$0), $MachinePrecision] + N[(1.0 - N[Exp[N[Log[1 + N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\left(\cos \left(0.5 \cdot \phi_2\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(0.5 \cdot \phi_2\right)\right)}^{2}\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 + \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_1 \cdot t\_1\right)}}{\sqrt{\left(1 - t\_0\right) + \left(1 - e^{\mathsf{log1p}\left(\cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\right)\right)}\right)}}\right)
\end{array}
\end{array}
Initial program 63.0%
associate-*l*63.0%
Simplified63.0%
div-sub63.0%
sin-diff64.0%
div-inv64.0%
metadata-eval64.0%
div-inv64.0%
metadata-eval64.0%
div-inv64.0%
metadata-eval64.0%
div-inv64.0%
metadata-eval64.0%
Applied egg-rr64.0%
div-sub63.0%
sin-diff64.0%
div-inv64.0%
metadata-eval64.0%
div-inv64.0%
metadata-eval64.0%
div-inv64.0%
metadata-eval64.0%
div-inv64.0%
metadata-eval64.0%
Applied egg-rr78.7%
expm1-log1p-u78.7%
expm1-undefine78.8%
pow278.8%
div-inv78.8%
metadata-eval78.8%
*-commutative78.8%
associate-*r*78.8%
Applied egg-rr78.8%
Final simplification78.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1
(pow
(-
(* (cos (* 0.5 phi2)) (sin (* phi1 0.5)))
(* (cos (* phi1 0.5)) (sin (* 0.5 phi2))))
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)
(+
-1.0
(- 1.0 (* t_0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = pow(((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((0.5 * phi2)))), 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) + (-1.0 + (1.0 - (t_0 * pow(sin((0.5 * (lambda1 - lambda2))), 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
real(8) :: t_1
real(8) :: t_2
t_0 = cos(phi1) * cos(phi2)
t_1 = ((cos((0.5d0 * phi2)) * sin((phi1 * 0.5d0))) - (cos((phi1 * 0.5d0)) * sin((0.5d0 * phi2)))) ** 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) + ((-1.0d0) + (1.0d0 - (t_0 * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0))))))))
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.cos((0.5 * phi2)) * Math.sin((phi1 * 0.5))) - (Math.cos((phi1 * 0.5)) * Math.sin((0.5 * phi2)))), 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) + (-1.0 + (1.0 - (t_0 * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0))))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi1) * math.cos(phi2) t_1 = math.pow(((math.cos((0.5 * phi2)) * math.sin((phi1 * 0.5))) - (math.cos((phi1 * 0.5)) * math.sin((0.5 * phi2)))), 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) + (-1.0 + (1.0 - (t_0 * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0))))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = Float64(Float64(cos(Float64(0.5 * phi2)) * sin(Float64(phi1 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(0.5 * phi2)))) ^ 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(-1.0 + Float64(1.0 - Float64(t_0 * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0))))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi1) * cos(phi2); t_1 = ((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((0.5 * phi2)))) ^ 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) + (-1.0 + (1.0 - (t_0 * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0)))))))); 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[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * phi2), $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[(-1.0 + N[(1.0 - N[(t$95$0 * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $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(\cos \left(0.5 \cdot \phi_2\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(0.5 \cdot \phi_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) + \left(-1 + \left(1 - t\_0 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\right)\right)}}\right)
\end{array}
\end{array}
Initial program 63.0%
associate-*l*63.0%
Simplified63.0%
div-sub63.0%
sin-diff64.0%
div-inv64.0%
metadata-eval64.0%
div-inv64.0%
metadata-eval64.0%
div-inv64.0%
metadata-eval64.0%
div-inv64.0%
metadata-eval64.0%
Applied egg-rr64.0%
div-sub63.0%
sin-diff64.0%
div-inv64.0%
metadata-eval64.0%
div-inv64.0%
metadata-eval64.0%
div-inv64.0%
metadata-eval64.0%
div-inv64.0%
metadata-eval64.0%
Applied egg-rr78.7%
expm1-log1p-u78.7%
expm1-undefine78.8%
pow278.8%
div-inv78.8%
metadata-eval78.8%
*-commutative78.8%
associate-*r*78.8%
Applied egg-rr78.8%
sub-neg78.8%
log1p-undefine78.7%
rem-exp-log78.7%
metadata-eval78.7%
Applied egg-rr78.7%
associate-+l+78.7%
associate-*r*78.7%
*-commutative78.7%
*-commutative78.7%
Simplified78.7%
Final simplification78.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(pow
(-
(* (cos (* 0.5 phi2)) (sin (* phi1 0.5)))
(* (cos (* phi1 0.5)) (sin (* 0.5 phi2))))
2.0))
(t_1 (* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
(t_2 (sin (/ (- lambda1 lambda2) 2.0))))
(if (<= phi2 -1.15e+16)
(*
R
(*
2.0
(atan2
(sqrt (+ t_0 t_1))
(sqrt (- (- 1.0 t_0) (* (* (cos phi1) (cos phi2)) (* t_2 t_2)))))))
(*
R
(*
2.0
(atan2
(sqrt (+ (* (cos phi1) t_1) (pow (sin (* 0.5 (- phi1 phi2))) 2.0)))
(sqrt
(-
1.0
(+
t_0
(*
(cos phi1)
(*
(cos phi2)
(pow
(-
(* (sin (/ lambda1 2.0)) (cos (/ lambda2 2.0)))
(* (cos (/ lambda1 2.0)) (sin (/ lambda2 2.0))))
2.0))))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((0.5 * phi2)))), 2.0);
double t_1 = cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if (phi2 <= -1.15e+16) {
tmp = R * (2.0 * atan2(sqrt((t_0 + t_1)), sqrt(((1.0 - t_0) - ((cos(phi1) * cos(phi2)) * (t_2 * t_2))))));
} else {
tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * t_1) + pow(sin((0.5 * (phi1 - phi2))), 2.0))), sqrt((1.0 - (t_0 + (cos(phi1) * (cos(phi2) * pow(((sin((lambda1 / 2.0)) * cos((lambda2 / 2.0))) - (cos((lambda1 / 2.0)) * sin((lambda2 / 2.0)))), 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) :: t_1
real(8) :: t_2
real(8) :: tmp
t_0 = ((cos((0.5d0 * phi2)) * sin((phi1 * 0.5d0))) - (cos((phi1 * 0.5d0)) * sin((0.5d0 * phi2)))) ** 2.0d0
t_1 = cos(phi2) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)
t_2 = sin(((lambda1 - lambda2) / 2.0d0))
if (phi2 <= (-1.15d+16)) then
tmp = r * (2.0d0 * atan2(sqrt((t_0 + t_1)), sqrt(((1.0d0 - t_0) - ((cos(phi1) * cos(phi2)) * (t_2 * t_2))))))
else
tmp = r * (2.0d0 * atan2(sqrt(((cos(phi1) * t_1) + (sin((0.5d0 * (phi1 - phi2))) ** 2.0d0))), sqrt((1.0d0 - (t_0 + (cos(phi1) * (cos(phi2) * (((sin((lambda1 / 2.0d0)) * cos((lambda2 / 2.0d0))) - (cos((lambda1 / 2.0d0)) * sin((lambda2 / 2.0d0)))) ** 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.pow(((Math.cos((0.5 * phi2)) * Math.sin((phi1 * 0.5))) - (Math.cos((phi1 * 0.5)) * Math.sin((0.5 * phi2)))), 2.0);
double t_1 = Math.cos(phi2) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_2 = Math.sin(((lambda1 - lambda2) / 2.0));
double tmp;
if (phi2 <= -1.15e+16) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_0 + t_1)), Math.sqrt(((1.0 - t_0) - ((Math.cos(phi1) * Math.cos(phi2)) * (t_2 * t_2))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi1) * t_1) + Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0))), Math.sqrt((1.0 - (t_0 + (Math.cos(phi1) * (Math.cos(phi2) * Math.pow(((Math.sin((lambda1 / 2.0)) * Math.cos((lambda2 / 2.0))) - (Math.cos((lambda1 / 2.0)) * Math.sin((lambda2 / 2.0)))), 2.0))))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(((math.cos((0.5 * phi2)) * math.sin((phi1 * 0.5))) - (math.cos((phi1 * 0.5)) * math.sin((0.5 * phi2)))), 2.0) t_1 = math.cos(phi2) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0) t_2 = math.sin(((lambda1 - lambda2) / 2.0)) tmp = 0 if phi2 <= -1.15e+16: tmp = R * (2.0 * math.atan2(math.sqrt((t_0 + t_1)), math.sqrt(((1.0 - t_0) - ((math.cos(phi1) * math.cos(phi2)) * (t_2 * t_2)))))) else: tmp = R * (2.0 * math.atan2(math.sqrt(((math.cos(phi1) * t_1) + math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0))), math.sqrt((1.0 - (t_0 + (math.cos(phi1) * (math.cos(phi2) * math.pow(((math.sin((lambda1 / 2.0)) * math.cos((lambda2 / 2.0))) - (math.cos((lambda1 / 2.0)) * math.sin((lambda2 / 2.0)))), 2.0)))))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(Float64(cos(Float64(0.5 * phi2)) * sin(Float64(phi1 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(0.5 * phi2)))) ^ 2.0 t_1 = Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)) t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if (phi2 <= -1.15e+16) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_0 + t_1)), sqrt(Float64(Float64(1.0 - t_0) - Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_2 * t_2))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi1) * t_1) + (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0))), sqrt(Float64(1.0 - Float64(t_0 + Float64(cos(phi1) * Float64(cos(phi2) * (Float64(Float64(sin(Float64(lambda1 / 2.0)) * cos(Float64(lambda2 / 2.0))) - Float64(cos(Float64(lambda1 / 2.0)) * sin(Float64(lambda2 / 2.0)))) ^ 2.0))))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = ((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((0.5 * phi2)))) ^ 2.0; t_1 = cos(phi2) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0); t_2 = sin(((lambda1 - lambda2) / 2.0)); tmp = 0.0; if (phi2 <= -1.15e+16) tmp = R * (2.0 * atan2(sqrt((t_0 + t_1)), sqrt(((1.0 - t_0) - ((cos(phi1) * cos(phi2)) * (t_2 * t_2)))))); else tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * t_1) + (sin((0.5 * (phi1 - phi2))) ^ 2.0))), sqrt((1.0 - (t_0 + (cos(phi1) * (cos(phi2) * (((sin((lambda1 / 2.0)) * cos((lambda2 / 2.0))) - (cos((lambda1 / 2.0)) * sin((lambda2 / 2.0)))) ^ 2.0)))))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi2, -1.15e+16], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - t$95$0), $MachinePrecision] - N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$2 * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * t$95$1), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 + N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[(N[(N[Sin[N[(lambda1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(lambda2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(lambda1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(lambda2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\left(\cos \left(0.5 \cdot \phi_2\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(0.5 \cdot \phi_2\right)\right)}^{2}\\
t_1 := \cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\phi_2 \leq -1.15 \cdot 10^{+16}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 + t\_1}}{\sqrt{\left(1 - t\_0\right) - \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_2 \cdot t\_2\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_1 \cdot t\_1 + {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}}}{\sqrt{1 - \left(t\_0 + \cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\left(\sin \left(\frac{\lambda_1}{2}\right) \cdot \cos \left(\frac{\lambda_2}{2}\right) - \cos \left(\frac{\lambda_1}{2}\right) \cdot \sin \left(\frac{\lambda_2}{2}\right)\right)}^{2}\right)\right)}}\right)\\
\end{array}
\end{array}
if phi2 < -1.15e16Initial program 45.5%
associate-*l*45.5%
Simplified45.5%
div-sub45.5%
sin-diff47.7%
div-inv47.7%
metadata-eval47.7%
div-inv47.7%
metadata-eval47.7%
div-inv47.7%
metadata-eval47.7%
div-inv47.7%
metadata-eval47.7%
Applied egg-rr47.7%
div-sub45.5%
sin-diff47.7%
div-inv47.7%
metadata-eval47.7%
div-inv47.7%
metadata-eval47.7%
div-inv47.7%
metadata-eval47.7%
div-inv47.7%
metadata-eval47.7%
Applied egg-rr82.4%
Taylor expanded in phi1 around 0 57.5%
if -1.15e16 < phi2 Initial program 68.3%
associate-*l*68.3%
Simplified68.3%
div-sub68.3%
sin-diff69.1%
div-inv69.1%
metadata-eval69.1%
div-inv69.1%
metadata-eval69.1%
div-inv69.1%
metadata-eval69.1%
div-inv69.1%
metadata-eval69.1%
Applied egg-rr69.1%
Taylor expanded in phi1 around 0 69.0%
*-commutative77.7%
metadata-eval77.7%
div-inv77.7%
div-sub77.7%
sin-diff78.3%
Applied egg-rr69.5%
Final simplification66.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(*
(cos phi1)
(* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))))
(*
R
(*
2.0
(atan2
(sqrt
(+
t_0
(pow
(-
(* (sin (/ phi1 2.0)) (cos (/ phi2 2.0)))
(* (cos (/ phi1 2.0)) (sin (/ phi2 2.0))))
2.0)))
(sqrt
(-
1.0
(+
(pow
(-
(* (cos (* 0.5 phi2)) (sin (* phi1 0.5)))
(* (cos (* phi1 0.5)) (sin (* 0.5 phi2))))
2.0)
t_0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * (cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0));
return R * (2.0 * atan2(sqrt((t_0 + pow(((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))), 2.0))), sqrt((1.0 - (pow(((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((0.5 * phi2)))), 2.0) + 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) * (cos(phi2) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0))
code = r * (2.0d0 * atan2(sqrt((t_0 + (((sin((phi1 / 2.0d0)) * cos((phi2 / 2.0d0))) - (cos((phi1 / 2.0d0)) * sin((phi2 / 2.0d0)))) ** 2.0d0))), sqrt((1.0d0 - ((((cos((0.5d0 * phi2)) * sin((phi1 * 0.5d0))) - (cos((phi1 * 0.5d0)) * sin((0.5d0 * phi2)))) ** 2.0d0) + 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.cos(phi2) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((t_0 + 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.sqrt((1.0 - (Math.pow(((Math.cos((0.5 * phi2)) * Math.sin((phi1 * 0.5))) - (Math.cos((phi1 * 0.5)) * Math.sin((0.5 * phi2)))), 2.0) + t_0)))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0)) return R * (2.0 * math.atan2(math.sqrt((t_0 + 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.sqrt((1.0 - (math.pow(((math.cos((0.5 * phi2)) * math.sin((phi1 * 0.5))) - (math.cos((phi1 * 0.5)) * math.sin((0.5 * phi2)))), 2.0) + t_0)))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0))) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_0 + (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))), sqrt(Float64(1.0 - Float64((Float64(Float64(cos(Float64(0.5 * phi2)) * sin(Float64(phi1 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(0.5 * phi2)))) ^ 2.0) + t_0)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi1) * (cos(phi2) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0)); tmp = R * (2.0 * atan2(sqrt((t_0 + (((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))) ^ 2.0))), sqrt((1.0 - ((((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((0.5 * phi2)))) ^ 2.0) + t_0))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 + 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]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 + {\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}}}{\sqrt{1 - \left({\left(\cos \left(0.5 \cdot \phi_2\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(0.5 \cdot \phi_2\right)\right)}^{2} + t\_0\right)}}\right)
\end{array}
\end{array}
Initial program 63.0%
associate-*l*63.0%
Simplified63.0%
div-sub63.0%
sin-diff64.0%
div-inv64.0%
metadata-eval64.0%
div-inv64.0%
metadata-eval64.0%
div-inv64.0%
metadata-eval64.0%
div-inv64.0%
metadata-eval64.0%
Applied egg-rr64.0%
Taylor expanded in phi1 around 0 64.0%
*-commutative64.0%
metadata-eval64.0%
div-inv64.0%
div-sub64.0%
sin-diff78.7%
Applied egg-rr78.7%
Final simplification78.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(pow
(-
(* (cos (* 0.5 phi2)) (sin (* phi1 0.5)))
(* (cos (* phi1 0.5)) (sin (* 0.5 phi2))))
2.0))
(t_2 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))
(t_3 (* (cos phi1) (cos phi2)))
(t_4 (* t_3 (* t_0 t_0))))
(if (or (<= phi1 -10000000000.0) (not (<= phi1 0.02)))
(*
R
(*
2.0
(atan2
(sqrt
(+ t_1 (* (cos phi1) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))))
(sqrt (- (- 1.0 t_1) t_4)))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_4 t_2))
(sqrt
(-
(- 1.0 t_2)
(*
t_3
(cbrt
(pow
(-
0.5
(*
0.5
(+
(* (cos lambda1) (cos lambda2))
(* (sin lambda1) (sin lambda2)))))
3.0)))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((0.5 * phi2)))), 2.0);
double t_2 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double t_3 = cos(phi1) * cos(phi2);
double t_4 = t_3 * (t_0 * t_0);
double tmp;
if ((phi1 <= -10000000000.0) || !(phi1 <= 0.02)) {
tmp = R * (2.0 * atan2(sqrt((t_1 + (cos(phi1) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0)))), sqrt(((1.0 - t_1) - t_4))));
} else {
tmp = R * (2.0 * atan2(sqrt((t_4 + t_2)), sqrt(((1.0 - t_2) - (t_3 * cbrt(pow((0.5 - (0.5 * ((cos(lambda1) * cos(lambda2)) + (sin(lambda1) * sin(lambda2))))), 3.0)))))));
}
return tmp;
}
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.cos((0.5 * phi2)) * Math.sin((phi1 * 0.5))) - (Math.cos((phi1 * 0.5)) * Math.sin((0.5 * phi2)))), 2.0);
double t_2 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0);
double t_3 = Math.cos(phi1) * Math.cos(phi2);
double t_4 = t_3 * (t_0 * t_0);
double tmp;
if ((phi1 <= -10000000000.0) || !(phi1 <= 0.02)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_1 + (Math.cos(phi1) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)))), Math.sqrt(((1.0 - t_1) - t_4))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_4 + t_2)), Math.sqrt(((1.0 - t_2) - (t_3 * Math.cbrt(Math.pow((0.5 - (0.5 * ((Math.cos(lambda1) * Math.cos(lambda2)) + (Math.sin(lambda1) * Math.sin(lambda2))))), 3.0)))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(cos(Float64(0.5 * phi2)) * sin(Float64(phi1 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(0.5 * phi2)))) ^ 2.0 t_2 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 t_3 = Float64(cos(phi1) * cos(phi2)) t_4 = Float64(t_3 * Float64(t_0 * t_0)) tmp = 0.0 if ((phi1 <= -10000000000.0) || !(phi1 <= 0.02)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + Float64(cos(phi1) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)))), sqrt(Float64(Float64(1.0 - t_1) - t_4))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_4 + t_2)), sqrt(Float64(Float64(1.0 - t_2) - Float64(t_3 * cbrt((Float64(0.5 - Float64(0.5 * Float64(Float64(cos(lambda1) * cos(lambda2)) + Float64(sin(lambda1) * sin(lambda2))))) ^ 3.0)))))))); end return tmp 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[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$3 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(t$95$3 * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[phi1, -10000000000.0], N[Not[LessEqual[phi1, 0.02]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - t$95$1), $MachinePrecision] - t$95$4), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$4 + t$95$2), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - t$95$2), $MachinePrecision] - N[(t$95$3 * N[Power[N[Power[N[(0.5 - N[(0.5 * N[(N[(N[Cos[lambda1], $MachinePrecision] * N[Cos[lambda2], $MachinePrecision]), $MachinePrecision] + N[(N[Sin[lambda1], $MachinePrecision] * N[Sin[lambda2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 3.0], $MachinePrecision], 1/3], $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 := {\left(\cos \left(0.5 \cdot \phi_2\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(0.5 \cdot \phi_2\right)\right)}^{2}\\
t_2 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
t_3 := \cos \phi_1 \cdot \cos \phi_2\\
t_4 := t\_3 \cdot \left(t\_0 \cdot t\_0\right)\\
\mathbf{if}\;\phi_1 \leq -10000000000 \lor \neg \left(\phi_1 \leq 0.02\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + \cos \phi_1 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}{\sqrt{\left(1 - t\_1\right) - t\_4}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_4 + t\_2}}{\sqrt{\left(1 - t\_2\right) - t\_3 \cdot \sqrt[3]{{\left(0.5 - 0.5 \cdot \left(\cos \lambda_1 \cdot \cos \lambda_2 + \sin \lambda_1 \cdot \sin \lambda_2\right)\right)}^{3}}}}\right)\\
\end{array}
\end{array}
if phi1 < -1e10 or 0.0200000000000000004 < phi1 Initial program 48.4%
associate-*l*48.5%
Simplified48.5%
div-sub48.5%
sin-diff50.7%
div-inv50.7%
metadata-eval50.7%
div-inv50.7%
metadata-eval50.7%
div-inv50.7%
metadata-eval50.7%
div-inv50.7%
metadata-eval50.7%
Applied egg-rr50.7%
div-sub48.5%
sin-diff50.7%
div-inv50.7%
metadata-eval50.7%
div-inv50.7%
metadata-eval50.7%
div-inv50.7%
metadata-eval50.7%
div-inv50.7%
metadata-eval50.7%
Applied egg-rr80.6%
Taylor expanded in phi2 around 0 57.7%
if -1e10 < phi1 < 0.0200000000000000004Initial program 76.4%
associate-*l*76.4%
Simplified76.4%
add-cbrt-cube76.5%
pow376.5%
Applied egg-rr76.5%
cos-diff77.1%
Applied egg-rr77.1%
Final simplification67.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(pow
(-
(* (cos (* 0.5 phi2)) (sin (* phi1 0.5)))
(* (cos (* phi1 0.5)) (sin (* 0.5 phi2))))
2.0))
(t_1 (* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
(t_2 (sin (/ (- lambda1 lambda2) 2.0)))
(t_3 (* (* (cos phi1) (cos phi2)) (* t_2 t_2))))
(if (<= phi2 -1e+17)
(* R (* 2.0 (atan2 (sqrt (+ t_0 t_1)) (sqrt (- (- 1.0 t_0) t_3)))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_0 t_3))
(sqrt
(fabs
(+
-1.0
(fma (cos phi1) t_1 (pow (sin (* 0.5 (- phi1 phi2))) 2.0)))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((0.5 * phi2)))), 2.0);
double t_1 = cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double t_3 = (cos(phi1) * cos(phi2)) * (t_2 * t_2);
double tmp;
if (phi2 <= -1e+17) {
tmp = R * (2.0 * atan2(sqrt((t_0 + t_1)), sqrt(((1.0 - t_0) - t_3))));
} else {
tmp = R * (2.0 * atan2(sqrt((t_0 + t_3)), sqrt(fabs((-1.0 + fma(cos(phi1), t_1, pow(sin((0.5 * (phi1 - phi2))), 2.0)))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(Float64(cos(Float64(0.5 * phi2)) * sin(Float64(phi1 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(0.5 * phi2)))) ^ 2.0 t_1 = Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)) t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_3 = Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_2 * t_2)) tmp = 0.0 if (phi2 <= -1e+17) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_0 + t_1)), sqrt(Float64(Float64(1.0 - t_0) - t_3))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_0 + t_3)), sqrt(abs(Float64(-1.0 + fma(cos(phi1), t_1, (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $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] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$2 * t$95$2), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[phi2, -1e+17], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - t$95$0), $MachinePrecision] - t$95$3), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 + t$95$3), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[Abs[N[(-1.0 + N[(N[Cos[phi1], $MachinePrecision] * t$95$1 + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\left(\cos \left(0.5 \cdot \phi_2\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(0.5 \cdot \phi_2\right)\right)}^{2}\\
t_1 := \cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_3 := \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_2 \cdot t\_2\right)\\
\mathbf{if}\;\phi_2 \leq -1 \cdot 10^{+17}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 + t\_1}}{\sqrt{\left(1 - t\_0\right) - t\_3}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 + t\_3}}{\sqrt{\left|-1 + \mathsf{fma}\left(\cos \phi_1, t\_1, {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)\right|}}\right)\\
\end{array}
\end{array}
if phi2 < -1e17Initial program 45.5%
associate-*l*45.5%
Simplified45.5%
div-sub45.5%
sin-diff47.7%
div-inv47.7%
metadata-eval47.7%
div-inv47.7%
metadata-eval47.7%
div-inv47.7%
metadata-eval47.7%
div-inv47.7%
metadata-eval47.7%
Applied egg-rr47.7%
div-sub45.5%
sin-diff47.7%
div-inv47.7%
metadata-eval47.7%
div-inv47.7%
metadata-eval47.7%
div-inv47.7%
metadata-eval47.7%
div-inv47.7%
metadata-eval47.7%
Applied egg-rr82.4%
Taylor expanded in phi1 around 0 57.5%
if -1e17 < phi2 Initial program 68.3%
associate-*l*68.3%
Simplified68.3%
div-sub68.3%
sin-diff69.1%
div-inv69.1%
metadata-eval69.1%
div-inv69.1%
metadata-eval69.1%
div-inv69.1%
metadata-eval69.1%
div-inv69.1%
metadata-eval69.1%
Applied egg-rr69.1%
div-sub68.3%
sin-diff69.1%
div-inv69.1%
metadata-eval69.1%
div-inv69.1%
metadata-eval69.1%
div-inv69.1%
metadata-eval69.1%
div-inv69.1%
metadata-eval69.1%
Applied egg-rr77.6%
expm1-log1p-u77.6%
expm1-undefine77.7%
pow277.7%
div-inv77.7%
metadata-eval77.7%
*-commutative77.7%
associate-*r*77.7%
Applied egg-rr77.7%
Applied egg-rr69.3%
unpow1/269.3%
unpow269.3%
rem-sqrt-square69.3%
Simplified69.3%
Final simplification66.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow
(-
(* (cos (* 0.5 phi2)) (sin (* phi1 0.5)))
(* (cos (* phi1 0.5)) (sin (* 0.5 phi2))))
2.0)
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(sqrt
(fabs
(+
-1.0
(fma
(cos phi1)
(* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(pow (sin (* 0.5 (- phi1 phi2))) 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(((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((0.5 * phi2)))), 2.0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))), sqrt(fabs((-1.0 + fma(cos(phi1), (cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0)), pow(sin((0.5 * (phi1 - phi2))), 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(Float64(0.5 * phi2)) * sin(Float64(phi1 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(0.5 * phi2)))) ^ 2.0) + Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)))), sqrt(abs(Float64(-1.0 + fma(cos(phi1), Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 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[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * phi2), $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[Abs[N[(-1.0 + N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $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(\cos \left(0.5 \cdot \phi_2\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(0.5 \cdot \phi_2\right)\right)}^{2} + \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right)}}{\sqrt{\left|-1 + \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}, {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)\right|}}\right)
\end{array}
\end{array}
Initial program 63.0%
associate-*l*63.0%
Simplified63.0%
div-sub63.0%
sin-diff64.0%
div-inv64.0%
metadata-eval64.0%
div-inv64.0%
metadata-eval64.0%
div-inv64.0%
metadata-eval64.0%
div-inv64.0%
metadata-eval64.0%
Applied egg-rr64.0%
div-sub63.0%
sin-diff64.0%
div-inv64.0%
metadata-eval64.0%
div-inv64.0%
metadata-eval64.0%
div-inv64.0%
metadata-eval64.0%
div-inv64.0%
metadata-eval64.0%
Applied egg-rr78.7%
expm1-log1p-u78.7%
expm1-undefine78.8%
pow278.8%
div-inv78.8%
metadata-eval78.8%
*-commutative78.8%
associate-*r*78.8%
Applied egg-rr78.8%
Applied egg-rr64.6%
unpow1/264.6%
unpow264.6%
rem-sqrt-square64.6%
Simplified64.6%
Final simplification64.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (cos phi1) (cos phi2))))
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_1 (* t_0 t_0)) (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt
(+
(-
1.0
(pow
(-
(* (cos (* 0.5 phi2)) (sin (* phi1 0.5)))
(* (cos (* phi1 0.5)) (sin (* 0.5 phi2))))
2.0))
(* t_1 (- 1.0 (+ 1.5 (* -0.5 (cos (- lambda1 lambda2)))))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = cos(phi1) * cos(phi2);
return R * (2.0 * atan2(sqrt(((t_1 * (t_0 * t_0)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt(((1.0 - pow(((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((0.5 * phi2)))), 2.0)) + (t_1 * (1.0 - (1.5 + (-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
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = cos(phi1) * cos(phi2)
code = r * (2.0d0 * atan2(sqrt(((t_1 * (t_0 * t_0)) + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt(((1.0d0 - (((cos((0.5d0 * phi2)) * sin((phi1 * 0.5d0))) - (cos((phi1 * 0.5d0)) * sin((0.5d0 * phi2)))) ** 2.0d0)) + (t_1 * (1.0d0 - (1.5d0 + ((-0.5d0) * cos((lambda1 - lambda2))))))))))
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.cos(phi1) * Math.cos(phi2);
return R * (2.0 * Math.atan2(Math.sqrt(((t_1 * (t_0 * t_0)) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt(((1.0 - Math.pow(((Math.cos((0.5 * phi2)) * Math.sin((phi1 * 0.5))) - (Math.cos((phi1 * 0.5)) * Math.sin((0.5 * phi2)))), 2.0)) + (t_1 * (1.0 - (1.5 + (-0.5 * Math.cos((lambda1 - lambda2))))))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.cos(phi1) * math.cos(phi2) return R * (2.0 * math.atan2(math.sqrt(((t_1 * (t_0 * t_0)) + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt(((1.0 - math.pow(((math.cos((0.5 * phi2)) * math.sin((phi1 * 0.5))) - (math.cos((phi1 * 0.5)) * math.sin((0.5 * phi2)))), 2.0)) + (t_1 * (1.0 - (1.5 + (-0.5 * math.cos((lambda1 - lambda2))))))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(cos(phi1) * cos(phi2)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_1 * Float64(t_0 * t_0)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(Float64(1.0 - (Float64(Float64(cos(Float64(0.5 * phi2)) * sin(Float64(phi1 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(0.5 * phi2)))) ^ 2.0)) + Float64(t_1 * Float64(1.0 - Float64(1.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2))))))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = cos(phi1) * cos(phi2); tmp = R * (2.0 * atan2(sqrt(((t_1 * (t_0 * t_0)) + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(((1.0 - (((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((0.5 * phi2)))) ^ 2.0)) + (t_1 * (1.0 - (1.5 + (-0.5 * cos((lambda1 - lambda2)))))))))); 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[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$1 * 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[(N[(1.0 - N[Power[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[(t$95$1 * N[(1.0 - N[(1.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $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)\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 \cdot \left(t\_0 \cdot t\_0\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{\left(1 - {\left(\cos \left(0.5 \cdot \phi_2\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(0.5 \cdot \phi_2\right)\right)}^{2}\right) + t\_1 \cdot \left(1 - \left(1.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right)\right)}}\right)
\end{array}
\end{array}
Initial program 63.0%
associate-*l*63.0%
Simplified63.0%
div-sub63.0%
sin-diff64.0%
div-inv64.0%
metadata-eval64.0%
div-inv64.0%
metadata-eval64.0%
div-inv64.0%
metadata-eval64.0%
div-inv64.0%
metadata-eval64.0%
Applied egg-rr64.0%
expm1-log1p-u64.0%
expm1-undefine64.1%
Applied egg-rr64.1%
sub-neg64.1%
log1p-undefine64.1%
rem-exp-log64.1%
sub-neg64.1%
associate-+r+64.1%
metadata-eval64.1%
distribute-lft-neg-in64.1%
metadata-eval64.1%
metadata-eval64.1%
Simplified64.1%
Final simplification64.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (cos phi1) (cos phi2))))
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_1 (* t_0 t_0)) (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt
(+
(-
1.0
(pow
(-
(* (cos (* 0.5 phi2)) (sin (* phi1 0.5)))
(* (cos (* phi1 0.5)) (sin (* 0.5 phi2))))
2.0))
(* t_1 (/ (+ -1.0 (cos (- lambda1 lambda2))) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = cos(phi1) * cos(phi2);
return R * (2.0 * atan2(sqrt(((t_1 * (t_0 * t_0)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt(((1.0 - pow(((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((0.5 * phi2)))), 2.0)) + (t_1 * ((-1.0 + cos((lambda1 - lambda2))) / 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
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = cos(phi1) * cos(phi2)
code = r * (2.0d0 * atan2(sqrt(((t_1 * (t_0 * t_0)) + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt(((1.0d0 - (((cos((0.5d0 * phi2)) * sin((phi1 * 0.5d0))) - (cos((phi1 * 0.5d0)) * sin((0.5d0 * phi2)))) ** 2.0d0)) + (t_1 * (((-1.0d0) + cos((lambda1 - lambda2))) / 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));
double t_1 = Math.cos(phi1) * Math.cos(phi2);
return R * (2.0 * Math.atan2(Math.sqrt(((t_1 * (t_0 * t_0)) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt(((1.0 - Math.pow(((Math.cos((0.5 * phi2)) * Math.sin((phi1 * 0.5))) - (Math.cos((phi1 * 0.5)) * Math.sin((0.5 * phi2)))), 2.0)) + (t_1 * ((-1.0 + Math.cos((lambda1 - lambda2))) / 2.0))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.cos(phi1) * math.cos(phi2) return R * (2.0 * math.atan2(math.sqrt(((t_1 * (t_0 * t_0)) + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt(((1.0 - math.pow(((math.cos((0.5 * phi2)) * math.sin((phi1 * 0.5))) - (math.cos((phi1 * 0.5)) * math.sin((0.5 * phi2)))), 2.0)) + (t_1 * ((-1.0 + math.cos((lambda1 - lambda2))) / 2.0))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(cos(phi1) * cos(phi2)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_1 * Float64(t_0 * t_0)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(Float64(1.0 - (Float64(Float64(cos(Float64(0.5 * phi2)) * sin(Float64(phi1 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(0.5 * phi2)))) ^ 2.0)) + Float64(t_1 * Float64(Float64(-1.0 + cos(Float64(lambda1 - lambda2))) / 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = cos(phi1) * cos(phi2); tmp = R * (2.0 * atan2(sqrt(((t_1 * (t_0 * t_0)) + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(((1.0 - (((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((0.5 * phi2)))) ^ 2.0)) + (t_1 * ((-1.0 + cos((lambda1 - lambda2))) / 2.0)))))); 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[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$1 * 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[(N[(1.0 - N[Power[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[(t$95$1 * N[(N[(-1.0 + N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $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)\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 \cdot \left(t\_0 \cdot t\_0\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{\left(1 - {\left(\cos \left(0.5 \cdot \phi_2\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(0.5 \cdot \phi_2\right)\right)}^{2}\right) + t\_1 \cdot \frac{-1 + \cos \left(\lambda_1 - \lambda_2\right)}{2}}}\right)
\end{array}
\end{array}
Initial program 63.0%
associate-*l*63.0%
Simplified63.0%
div-sub63.0%
sin-diff64.0%
div-inv64.0%
metadata-eval64.0%
div-inv64.0%
metadata-eval64.0%
div-inv64.0%
metadata-eval64.0%
div-inv64.0%
metadata-eval64.0%
Applied egg-rr64.0%
sin-mult64.1%
cos-sum64.1%
cos-264.1%
div-sub64.1%
+-inverses64.1%
Applied egg-rr64.1%
cos-064.1%
div-sub64.1%
Simplified64.1%
Final simplification64.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (cos phi1) (cos phi2))))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* t_0 (* t_1 t_0))))
(sqrt
(fabs
(-
1.0
(fma
t_1
(+ 0.5 (* -0.5 (cos (- lambda1 lambda2))))
(pow (sin (* -0.5 (- phi2 phi1))) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = cos(phi1) * cos(phi2);
return R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * (t_1 * t_0)))), sqrt(fabs((1.0 - fma(t_1, (0.5 + (-0.5 * cos((lambda1 - lambda2)))), pow(sin((-0.5 * (phi2 - phi1))), 2.0)))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(cos(phi1) * cos(phi2)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_0 * Float64(t_1 * t_0)))), sqrt(abs(Float64(1.0 - fma(t_1, Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2)))), (sin(Float64(-0.5 * Float64(phi2 - phi1))) ^ 2.0)))))))) 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[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $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[(t$95$0 * N[(t$95$1 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[Abs[N[(1.0 - N[(t$95$1 * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * N[(phi2 - phi1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $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)\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_0 \cdot \left(t\_1 \cdot t\_0\right)}}{\sqrt{\left|1 - \mathsf{fma}\left(t\_1, 0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), {\sin \left(-0.5 \cdot \left(\phi_2 - \phi_1\right)\right)}^{2}\right)\right|}}\right)
\end{array}
\end{array}
Initial program 63.0%
Applied egg-rr63.6%
Simplified63.6%
Final simplification63.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (- (+ 1.0 (- (/ (cos (- phi1 phi2)) 2.0) 0.5)) 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 = (cos(phi1) * cos(phi2)) * (t_0 * t_0);
return R * (2.0 * atan2(sqrt((t_1 + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt(((1.0 + ((cos((phi1 - phi2)) / 2.0) - 0.5)) - 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 = (cos(phi1) * cos(phi2)) * (t_0 * t_0)
code = r * (2.0d0 * atan2(sqrt((t_1 + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt(((1.0d0 + ((cos((phi1 - phi2)) / 2.0d0) - 0.5d0)) - 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.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0);
return R * (2.0 * Math.atan2(Math.sqrt((t_1 + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt(((1.0 + ((Math.cos((phi1 - phi2)) / 2.0) - 0.5)) - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = (math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0) return R * (2.0 * math.atan2(math.sqrt((t_1 + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt(((1.0 + ((math.cos((phi1 - phi2)) / 2.0) - 0.5)) - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(Float64(1.0 + Float64(Float64(cos(Float64(phi1 - phi2)) / 2.0) - 0.5)) - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0); tmp = R * (2.0 * atan2(sqrt((t_1 + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(((1.0 + ((cos((phi1 - phi2)) / 2.0) - 0.5)) - 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[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 + N[(N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision] - 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 := \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{\left(1 + \left(\frac{\cos \left(\phi_1 - \phi_2\right)}{2} - 0.5\right)\right) - t\_1}}\right)
\end{array}
\end{array}
Initial program 63.0%
associate-*l*63.0%
Simplified63.0%
unpow263.0%
sin-mult63.1%
div-inv63.1%
metadata-eval63.1%
div-inv63.1%
metadata-eval63.1%
div-inv63.1%
metadata-eval63.1%
div-inv63.1%
metadata-eval63.1%
Applied egg-rr63.1%
div-sub63.1%
+-inverses63.1%
cos-063.1%
metadata-eval63.1%
distribute-lft-out63.1%
metadata-eval63.1%
*-rgt-identity63.1%
Simplified63.1%
Final simplification63.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (cos phi1) (cos phi2)))
(t_2 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
(if (or (<= phi2 -9.2e-10) (not (<= phi2 3.2e-61)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* t_1 t_0) (sin (* lambda2 -0.5)))))
(sqrt (- 1.0 (+ (* (cos phi2) t_2) (pow (sin (* phi2 -0.5)) 2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt (+ (* (cos phi1) t_2) (pow (sin (/ phi1 2.0)) 2.0)))
(sqrt (- (pow (cos (* phi1 0.5)) 2.0) (* t_1 (* t_0 t_0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = cos(phi1) * cos(phi2);
double t_2 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double tmp;
if ((phi2 <= -9.2e-10) || !(phi2 <= 3.2e-61)) {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((t_1 * t_0) * sin((lambda2 * -0.5))))), sqrt((1.0 - ((cos(phi2) * t_2) + pow(sin((phi2 * -0.5)), 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * t_2) + pow(sin((phi1 / 2.0)), 2.0))), sqrt((pow(cos((phi1 * 0.5)), 2.0) - (t_1 * (t_0 * t_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) :: t_1
real(8) :: t_2
real(8) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = cos(phi1) * cos(phi2)
t_2 = sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0
if ((phi2 <= (-9.2d-10)) .or. (.not. (phi2 <= 3.2d-61))) then
tmp = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + ((t_1 * t_0) * sin((lambda2 * (-0.5d0)))))), sqrt((1.0d0 - ((cos(phi2) * t_2) + (sin((phi2 * (-0.5d0))) ** 2.0d0))))))
else
tmp = r * (2.0d0 * atan2(sqrt(((cos(phi1) * t_2) + (sin((phi1 / 2.0d0)) ** 2.0d0))), sqrt(((cos((phi1 * 0.5d0)) ** 2.0d0) - (t_1 * (t_0 * t_0))))))
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 t_1 = Math.cos(phi1) * Math.cos(phi2);
double t_2 = Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0);
double tmp;
if ((phi2 <= -9.2e-10) || !(phi2 <= 3.2e-61)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((t_1 * t_0) * Math.sin((lambda2 * -0.5))))), Math.sqrt((1.0 - ((Math.cos(phi2) * t_2) + Math.pow(Math.sin((phi2 * -0.5)), 2.0))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi1) * t_2) + Math.pow(Math.sin((phi1 / 2.0)), 2.0))), Math.sqrt((Math.pow(Math.cos((phi1 * 0.5)), 2.0) - (t_1 * (t_0 * t_0))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.cos(phi1) * math.cos(phi2) t_2 = math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0) tmp = 0 if (phi2 <= -9.2e-10) or not (phi2 <= 3.2e-61): tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((t_1 * t_0) * math.sin((lambda2 * -0.5))))), math.sqrt((1.0 - ((math.cos(phi2) * t_2) + math.pow(math.sin((phi2 * -0.5)), 2.0)))))) else: tmp = R * (2.0 * math.atan2(math.sqrt(((math.cos(phi1) * t_2) + math.pow(math.sin((phi1 / 2.0)), 2.0))), math.sqrt((math.pow(math.cos((phi1 * 0.5)), 2.0) - (t_1 * (t_0 * t_0)))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(cos(phi1) * cos(phi2)) t_2 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 tmp = 0.0 if ((phi2 <= -9.2e-10) || !(phi2 <= 3.2e-61)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(t_1 * t_0) * sin(Float64(lambda2 * -0.5))))), sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * t_2) + (sin(Float64(phi2 * -0.5)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi1) * t_2) + (sin(Float64(phi1 / 2.0)) ^ 2.0))), sqrt(Float64((cos(Float64(phi1 * 0.5)) ^ 2.0) - Float64(t_1 * Float64(t_0 * t_0))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = cos(phi1) * cos(phi2); t_2 = sin((0.5 * (lambda1 - lambda2))) ^ 2.0; tmp = 0.0; if ((phi2 <= -9.2e-10) || ~((phi2 <= 3.2e-61))) tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + ((t_1 * t_0) * sin((lambda2 * -0.5))))), sqrt((1.0 - ((cos(phi2) * t_2) + (sin((phi2 * -0.5)) ^ 2.0)))))); else tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * t_2) + (sin((phi1 / 2.0)) ^ 2.0))), sqrt(((cos((phi1 * 0.5)) ^ 2.0) - (t_1 * (t_0 * t_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]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[phi2, -9.2e-10], N[Not[LessEqual[phi2, 3.2e-61]], $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[(t$95$1 * t$95$0), $MachinePrecision] * N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$2), $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[Cos[phi1], $MachinePrecision] * t$95$2), $MachinePrecision] + N[Power[N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(t$95$1 * N[(t$95$0 * t$95$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)\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
t_2 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
\mathbf{if}\;\phi_2 \leq -9.2 \cdot 10^{-10} \lor \neg \left(\phi_2 \leq 3.2 \cdot 10^{-61}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(t\_1 \cdot t\_0\right) \cdot \sin \left(\lambda_2 \cdot -0.5\right)}}{\sqrt{1 - \left(\cos \phi_2 \cdot t\_2 + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_1 \cdot t\_2 + {\sin \left(\frac{\phi_1}{2}\right)}^{2}}}{\sqrt{{\cos \left(\phi_1 \cdot 0.5\right)}^{2} - t\_1 \cdot \left(t\_0 \cdot t\_0\right)}}\right)\\
\end{array}
\end{array}
if phi2 < -9.20000000000000028e-10 or 3.2000000000000001e-61 < phi2 Initial program 49.9%
Taylor expanded in lambda1 around 0 40.7%
Taylor expanded in phi1 around 0 41.3%
if -9.20000000000000028e-10 < phi2 < 3.2000000000000001e-61Initial program 79.5%
associate-*l*79.6%
Simplified79.6%
Taylor expanded in phi1 around inf 77.9%
Taylor expanded in phi2 around 0 77.9%
unpow277.9%
1-sub-sin78.0%
unpow278.0%
*-commutative78.0%
Simplified78.0%
Taylor expanded in phi2 around 0 78.0%
Final simplification57.5%
(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 (- 1.0 (+ 1.5 (* -0.5 (cos (- lambda1 lambda2)))))))))))))
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 * (1.0 - (1.5 + (-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
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 * (1.0d0 - (1.5d0 + ((-0.5d0) * cos((lambda1 - lambda2))))))))))
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 * (1.0 - (1.5 + (-0.5 * Math.cos((lambda1 - lambda2))))))))));
}
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 * (1.0 - (1.5 + (-0.5 * math.cos((lambda1 - lambda2))))))))))
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(1.0 - Float64(1.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2))))))))))) 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 * (1.0 - (1.5 + (-0.5 * cos((lambda1 - lambda2)))))))))); 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[(1.0 - N[(1.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $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)\\
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(1 - \left(1.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right)\right)}}\right)
\end{array}
\end{array}
Initial program 63.0%
associate-*l*63.0%
Simplified63.0%
expm1-log1p-u64.0%
expm1-undefine64.1%
Applied egg-rr63.0%
sub-neg64.1%
log1p-undefine64.1%
rem-exp-log64.1%
sub-neg64.1%
associate-+r+64.1%
metadata-eval64.1%
distribute-lft-neg-in64.1%
metadata-eval64.1%
metadata-eval64.1%
Simplified63.0%
Final simplification63.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (* 0.5 (- lambda1 lambda2))))
(t_2 (sin (/ (- lambda1 lambda2) 2.0))))
(if (or (<= phi1 -1.95e-30) (not (<= phi1 3.4e-9)))
(*
R
(*
2.0
(atan2
(sqrt (+ (* (cos phi1) (pow t_1 2.0)) (pow (sin (/ phi1 2.0)) 2.0)))
(sqrt (- (pow (cos (* phi1 0.5)) 2.0) (* t_0 (* t_2 t_2)))))))
(*
(atan2
(hypot (sin (* 0.5 (- phi1 phi2))) (* t_1 (sqrt t_0)))
(sqrt
(-
1.0
(fma
t_0
(+ 0.5 (* -0.5 (cos (- lambda1 lambda2))))
(pow (sin (* phi2 -0.5)) 2.0)))))
(* R 2.0)))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = sin((0.5 * (lambda1 - lambda2)));
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((phi1 <= -1.95e-30) || !(phi1 <= 3.4e-9)) {
tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * pow(t_1, 2.0)) + pow(sin((phi1 / 2.0)), 2.0))), sqrt((pow(cos((phi1 * 0.5)), 2.0) - (t_0 * (t_2 * t_2))))));
} else {
tmp = atan2(hypot(sin((0.5 * (phi1 - phi2))), (t_1 * sqrt(t_0))), sqrt((1.0 - fma(t_0, (0.5 + (-0.5 * cos((lambda1 - lambda2)))), pow(sin((phi2 * -0.5)), 2.0))))) * (R * 2.0);
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if ((phi1 <= -1.95e-30) || !(phi1 <= 3.4e-9)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi1) * (t_1 ^ 2.0)) + (sin(Float64(phi1 / 2.0)) ^ 2.0))), sqrt(Float64((cos(Float64(phi1 * 0.5)) ^ 2.0) - Float64(t_0 * Float64(t_2 * t_2))))))); else tmp = Float64(atan(hypot(sin(Float64(0.5 * Float64(phi1 - phi2))), Float64(t_1 * sqrt(t_0))), sqrt(Float64(1.0 - fma(t_0, Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2)))), (sin(Float64(phi2 * -0.5)) ^ 2.0))))) * Float64(R * 2.0)); end return tmp 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[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[phi1, -1.95e-30], N[Not[LessEqual[phi1, 3.4e-9]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * N[Power[t$95$1, 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(t$95$0 * N[(t$95$2 * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[ArcTan[N[Sqrt[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] ^ 2 + N[(t$95$1 * N[Sqrt[t$95$0], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(R * 2.0), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\phi_1 \leq -1.95 \cdot 10^{-30} \lor \neg \left(\phi_1 \leq 3.4 \cdot 10^{-9}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_1 \cdot {t\_1}^{2} + {\sin \left(\frac{\phi_1}{2}\right)}^{2}}}{\sqrt{{\cos \left(\phi_1 \cdot 0.5\right)}^{2} - t\_0 \cdot \left(t\_2 \cdot t\_2\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;\tan^{-1}_* \frac{\mathsf{hypot}\left(\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right), t\_1 \cdot \sqrt{t\_0}\right)}{\sqrt{1 - \mathsf{fma}\left(t\_0, 0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}} \cdot \left(R \cdot 2\right)\\
\end{array}
\end{array}
if phi1 < -1.9500000000000002e-30 or 3.3999999999999998e-9 < phi1 Initial program 48.2%
associate-*l*48.2%
Simplified48.2%
Taylor expanded in phi1 around inf 47.0%
Taylor expanded in phi2 around 0 47.3%
unpow247.3%
1-sub-sin47.4%
unpow247.4%
*-commutative47.4%
Simplified47.4%
Taylor expanded in phi2 around 0 49.1%
if -1.9500000000000002e-30 < phi1 < 3.3999999999999998e-9Initial program 78.9%
associate-*r*78.9%
*-commutative78.9%
Simplified79.0%
Applied egg-rr62.3%
*-lft-identity62.3%
*-commutative62.3%
*-commutative62.3%
cancel-sign-sub-inv62.3%
metadata-eval62.3%
Simplified62.3%
Taylor expanded in phi1 around 0 62.3%
*-commutative62.3%
Simplified62.3%
Final simplification55.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (* 0.5 (- lambda1 lambda2))))
(t_2 (* (cos phi1) (pow t_1 2.0)))
(t_3 (sin (/ (- lambda1 lambda2) 2.0)))
(t_4 (* t_0 (* t_3 t_3)))
(t_5 (pow (sin (/ phi1 2.0)) 2.0))
(t_6 (pow (cos (* phi1 0.5)) 2.0)))
(if (<= phi1 -1.95e-30)
(* R (* 2.0 (atan2 (sqrt (+ t_2 t_5)) (sqrt (- t_6 t_4)))))
(if (<= phi1 6.8e-9)
(*
(atan2
(hypot (sin (* 0.5 (- phi1 phi2))) (* t_1 (sqrt t_0)))
(sqrt
(-
1.0
(fma
t_0
(+ 0.5 (* -0.5 (cos (- lambda1 lambda2))))
(pow (sin (* phi2 -0.5)) 2.0)))))
(* R 2.0))
(* R (* 2.0 (atan2 (sqrt (+ t_4 t_5)) (sqrt (- t_6 t_2)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = sin((0.5 * (lambda1 - lambda2)));
double t_2 = cos(phi1) * pow(t_1, 2.0);
double t_3 = sin(((lambda1 - lambda2) / 2.0));
double t_4 = t_0 * (t_3 * t_3);
double t_5 = pow(sin((phi1 / 2.0)), 2.0);
double t_6 = pow(cos((phi1 * 0.5)), 2.0);
double tmp;
if (phi1 <= -1.95e-30) {
tmp = R * (2.0 * atan2(sqrt((t_2 + t_5)), sqrt((t_6 - t_4))));
} else if (phi1 <= 6.8e-9) {
tmp = atan2(hypot(sin((0.5 * (phi1 - phi2))), (t_1 * sqrt(t_0))), sqrt((1.0 - fma(t_0, (0.5 + (-0.5 * cos((lambda1 - lambda2)))), pow(sin((phi2 * -0.5)), 2.0))))) * (R * 2.0);
} else {
tmp = R * (2.0 * atan2(sqrt((t_4 + t_5)), sqrt((t_6 - t_2))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) t_2 = Float64(cos(phi1) * (t_1 ^ 2.0)) t_3 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_4 = Float64(t_0 * Float64(t_3 * t_3)) t_5 = sin(Float64(phi1 / 2.0)) ^ 2.0 t_6 = cos(Float64(phi1 * 0.5)) ^ 2.0 tmp = 0.0 if (phi1 <= -1.95e-30) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_2 + t_5)), sqrt(Float64(t_6 - t_4))))); elseif (phi1 <= 6.8e-9) tmp = Float64(atan(hypot(sin(Float64(0.5 * Float64(phi1 - phi2))), Float64(t_1 * sqrt(t_0))), sqrt(Float64(1.0 - fma(t_0, Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2)))), (sin(Float64(phi2 * -0.5)) ^ 2.0))))) * Float64(R * 2.0)); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_4 + t_5)), sqrt(Float64(t_6 - t_2))))); end return tmp 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[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Power[t$95$1, 2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[(t$95$0 * N[(t$95$3 * t$95$3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[Power[N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$6 = N[Power[N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[LessEqual[phi1, -1.95e-30], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$2 + t$95$5), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(t$95$6 - t$95$4), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[phi1, 6.8e-9], N[(N[ArcTan[N[Sqrt[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] ^ 2 + N[(t$95$1 * N[Sqrt[t$95$0], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(R * 2.0), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$4 + t$95$5), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(t$95$6 - t$95$2), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\\
t_2 := \cos \phi_1 \cdot {t\_1}^{2}\\
t_3 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_4 := t\_0 \cdot \left(t\_3 \cdot t\_3\right)\\
t_5 := {\sin \left(\frac{\phi_1}{2}\right)}^{2}\\
t_6 := {\cos \left(\phi_1 \cdot 0.5\right)}^{2}\\
\mathbf{if}\;\phi_1 \leq -1.95 \cdot 10^{-30}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 + t\_5}}{\sqrt{t\_6 - t\_4}}\right)\\
\mathbf{elif}\;\phi_1 \leq 6.8 \cdot 10^{-9}:\\
\;\;\;\;\tan^{-1}_* \frac{\mathsf{hypot}\left(\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right), t\_1 \cdot \sqrt{t\_0}\right)}{\sqrt{1 - \mathsf{fma}\left(t\_0, 0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}} \cdot \left(R \cdot 2\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_4 + t\_5}}{\sqrt{t\_6 - t\_2}}\right)\\
\end{array}
\end{array}
if phi1 < -1.9500000000000002e-30Initial program 45.1%
associate-*l*45.1%
Simplified45.1%
Taylor expanded in phi1 around inf 43.0%
Taylor expanded in phi2 around 0 43.3%
unpow243.3%
1-sub-sin43.3%
unpow243.3%
*-commutative43.3%
Simplified43.3%
Taylor expanded in phi2 around 0 45.7%
if -1.9500000000000002e-30 < phi1 < 6.7999999999999997e-9Initial program 78.9%
associate-*r*78.9%
*-commutative78.9%
Simplified79.0%
Applied egg-rr62.3%
*-lft-identity62.3%
*-commutative62.3%
*-commutative62.3%
cancel-sign-sub-inv62.3%
metadata-eval62.3%
Simplified62.3%
Taylor expanded in phi1 around 0 62.3%
*-commutative62.3%
Simplified62.3%
if 6.7999999999999997e-9 < phi1 Initial program 52.4%
associate-*l*52.4%
Simplified52.4%
Taylor expanded in phi1 around inf 52.3%
Taylor expanded in phi2 around 0 52.6%
unpow252.6%
1-sub-sin52.8%
unpow252.8%
*-commutative52.8%
Simplified52.8%
Taylor expanded in phi2 around 0 54.0%
Final simplification55.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- lambda1 lambda2))))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (* (cos phi1) (cos phi2))))
(if (or (<= phi2 -4e-37) (not (<= phi2 6.8e-53)))
(*
R
(*
2.0
(atan2
(sqrt (+ (* (cos phi2) (pow t_0 2.0)) (* 0.25 (pow phi2 2.0))))
(sqrt
(-
1.0
(+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* t_1 (* t_2 t_1))))))))
(*
(* R 2.0)
(atan2
(hypot (sin (* phi1 0.5)) (* t_0 (sqrt t_2)))
(sqrt
(-
1.0
(fma
t_2
(+ 0.5 (* -0.5 (cos (- lambda1 lambda2))))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (lambda1 - lambda2)));
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = cos(phi1) * cos(phi2);
double tmp;
if ((phi2 <= -4e-37) || !(phi2 <= 6.8e-53)) {
tmp = R * (2.0 * atan2(sqrt(((cos(phi2) * pow(t_0, 2.0)) + (0.25 * pow(phi2, 2.0)))), sqrt((1.0 - (pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_1 * (t_2 * t_1)))))));
} else {
tmp = (R * 2.0) * atan2(hypot(sin((phi1 * 0.5)), (t_0 * sqrt(t_2))), sqrt((1.0 - fma(t_2, (0.5 + (-0.5 * cos((lambda1 - lambda2)))), pow(sin((0.5 * (phi1 - phi2))), 2.0)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(cos(phi1) * cos(phi2)) tmp = 0.0 if ((phi2 <= -4e-37) || !(phi2 <= 6.8e-53)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi2) * (t_0 ^ 2.0)) + Float64(0.25 * (phi2 ^ 2.0)))), sqrt(Float64(1.0 - Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_1 * Float64(t_2 * t_1)))))))); else tmp = Float64(Float64(R * 2.0) * atan(hypot(sin(Float64(phi1 * 0.5)), Float64(t_0 * sqrt(t_2))), sqrt(Float64(1.0 - fma(t_2, Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2)))), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[phi2, -4e-37], N[Not[LessEqual[phi2, 6.8e-53]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[t$95$0, 2.0], $MachinePrecision]), $MachinePrecision] + N[(0.25 * N[Power[phi2, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$1 * N[(t$95$2 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] ^ 2 + N[(t$95$0 * N[Sqrt[t$95$2], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$2 * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
\mathbf{if}\;\phi_2 \leq -4 \cdot 10^{-37} \lor \neg \left(\phi_2 \leq 6.8 \cdot 10^{-53}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot {t\_0}^{2} + 0.25 \cdot {\phi_2}^{2}}}{\sqrt{1 - \left({\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_1 \cdot \left(t\_2 \cdot t\_1\right)\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(\sin \left(\phi_1 \cdot 0.5\right), t\_0 \cdot \sqrt{t\_2}\right)}{\sqrt{1 - \mathsf{fma}\left(t\_2, 0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}}\\
\end{array}
\end{array}
if phi2 < -4.00000000000000027e-37 or 6.8e-53 < phi2 Initial program 50.8%
Taylor expanded in phi2 around 0 22.6%
*-commutative22.6%
associate-*r*22.6%
*-commutative22.6%
Simplified22.6%
Taylor expanded in phi1 around 0 21.2%
if -4.00000000000000027e-37 < phi2 < 6.8e-53Initial program 79.4%
associate-*r*79.4%
*-commutative79.4%
Simplified79.3%
Applied egg-rr57.8%
*-lft-identity57.8%
*-commutative57.8%
*-commutative57.8%
cancel-sign-sub-inv57.8%
metadata-eval57.8%
Simplified57.8%
Taylor expanded in phi2 around 0 56.4%
Final simplification36.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- lambda1 lambda2))))
(t_1 (sin (* 0.5 (- phi1 phi2))))
(t_2 (pow t_1 2.0))
(t_3 (* (cos phi1) (cos phi2)))
(t_4 (sqrt t_3))
(t_5 (sin (/ (- lambda1 lambda2) 2.0))))
(if (<= lambda1 -4.8e+16)
(*
(* R 2.0)
(atan2
(hypot t_1 (* t_4 (sin (* 0.5 lambda1))))
(sqrt
(- 1.0 (fma t_3 (+ 0.5 (* -0.5 (cos (- lambda1 lambda2)))) t_2)))))
(if (<= lambda1 8.8e-16)
(*
(* R 2.0)
(atan2
(hypot t_1 (* t_0 t_4))
(sqrt (- 1.0 (fma t_3 (+ 0.5 (* (cos lambda2) -0.5)) t_2)))))
(*
R
(*
2.0
(atan2
(sqrt (+ (* (cos phi2) (pow t_0 2.0)) (* 0.25 (pow phi2 2.0))))
(sqrt
(-
1.0
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* t_5 (* t_3 t_5))))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (lambda1 - lambda2)));
double t_1 = sin((0.5 * (phi1 - phi2)));
double t_2 = pow(t_1, 2.0);
double t_3 = cos(phi1) * cos(phi2);
double t_4 = sqrt(t_3);
double t_5 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if (lambda1 <= -4.8e+16) {
tmp = (R * 2.0) * atan2(hypot(t_1, (t_4 * sin((0.5 * lambda1)))), sqrt((1.0 - fma(t_3, (0.5 + (-0.5 * cos((lambda1 - lambda2)))), t_2))));
} else if (lambda1 <= 8.8e-16) {
tmp = (R * 2.0) * atan2(hypot(t_1, (t_0 * t_4)), sqrt((1.0 - fma(t_3, (0.5 + (cos(lambda2) * -0.5)), t_2))));
} else {
tmp = R * (2.0 * atan2(sqrt(((cos(phi2) * pow(t_0, 2.0)) + (0.25 * pow(phi2, 2.0)))), sqrt((1.0 - (pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_5 * (t_3 * t_5)))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) t_1 = sin(Float64(0.5 * Float64(phi1 - phi2))) t_2 = t_1 ^ 2.0 t_3 = Float64(cos(phi1) * cos(phi2)) t_4 = sqrt(t_3) t_5 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if (lambda1 <= -4.8e+16) tmp = Float64(Float64(R * 2.0) * atan(hypot(t_1, Float64(t_4 * sin(Float64(0.5 * lambda1)))), sqrt(Float64(1.0 - fma(t_3, Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2)))), t_2))))); elseif (lambda1 <= 8.8e-16) tmp = Float64(Float64(R * 2.0) * atan(hypot(t_1, Float64(t_0 * t_4)), sqrt(Float64(1.0 - fma(t_3, Float64(0.5 + Float64(cos(lambda2) * -0.5)), t_2))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi2) * (t_0 ^ 2.0)) + Float64(0.25 * (phi2 ^ 2.0)))), sqrt(Float64(1.0 - Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_5 * Float64(t_3 * t_5)))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Power[t$95$1, 2.0], $MachinePrecision]}, Block[{t$95$3 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[Sqrt[t$95$3], $MachinePrecision]}, Block[{t$95$5 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[lambda1, -4.8e+16], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[t$95$1 ^ 2 + N[(t$95$4 * N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$3 * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision], If[LessEqual[lambda1, 8.8e-16], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[t$95$1 ^ 2 + N[(t$95$0 * t$95$4), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$3 * N[(0.5 + N[(N[Cos[lambda2], $MachinePrecision] * -0.5), $MachinePrecision]), $MachinePrecision] + t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[t$95$0, 2.0], $MachinePrecision]), $MachinePrecision] + N[(0.25 * N[Power[phi2, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$5 * N[(t$95$3 * t$95$5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\\
t_1 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
t_2 := {t\_1}^{2}\\
t_3 := \cos \phi_1 \cdot \cos \phi_2\\
t_4 := \sqrt{t\_3}\\
t_5 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\lambda_1 \leq -4.8 \cdot 10^{+16}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(t\_1, t\_4 \cdot \sin \left(0.5 \cdot \lambda_1\right)\right)}{\sqrt{1 - \mathsf{fma}\left(t\_3, 0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), t\_2\right)}}\\
\mathbf{elif}\;\lambda_1 \leq 8.8 \cdot 10^{-16}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(t\_1, t\_0 \cdot t\_4\right)}{\sqrt{1 - \mathsf{fma}\left(t\_3, 0.5 + \cos \lambda_2 \cdot -0.5, t\_2\right)}}\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot {t\_0}^{2} + 0.25 \cdot {\phi_2}^{2}}}{\sqrt{1 - \left({\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_5 \cdot \left(t\_3 \cdot t\_5\right)\right)}}\right)\\
\end{array}
\end{array}
if lambda1 < -4.8e16Initial program 49.8%
associate-*r*49.8%
*-commutative49.8%
Simplified49.7%
Applied egg-rr32.0%
*-lft-identity32.0%
*-commutative32.0%
*-commutative32.0%
cancel-sign-sub-inv32.0%
metadata-eval32.0%
Simplified32.0%
Taylor expanded in lambda2 around 0 31.8%
if -4.8e16 < lambda1 < 8.80000000000000001e-16Initial program 79.4%
associate-*r*79.4%
*-commutative79.4%
Simplified79.4%
Applied egg-rr60.2%
*-lft-identity60.2%
*-commutative60.2%
*-commutative60.2%
cancel-sign-sub-inv60.2%
metadata-eval60.2%
Simplified60.2%
Taylor expanded in lambda1 around 0 60.2%
cos-neg60.2%
Simplified60.2%
if 8.80000000000000001e-16 < lambda1 Initial program 49.4%
Taylor expanded in phi2 around 0 38.8%
*-commutative38.8%
associate-*r*38.8%
*-commutative38.8%
Simplified38.8%
Taylor expanded in phi1 around 0 27.8%
Final simplification43.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- phi1 phi2))))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (* (cos phi1) (cos phi2)))
(t_3 (pow t_0 2.0))
(t_4 (sin (* 0.5 (- lambda1 lambda2))))
(t_5 (* t_4 (sqrt t_2))))
(if (<= lambda2 -2.4e-13)
(*
R
(*
2.0
(atan2
(sqrt (+ (* (cos phi2) (pow t_4 2.0)) (* 0.25 (pow phi2 2.0))))
(sqrt
(-
1.0
(+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* t_1 (* t_2 t_1))))))))
(if (<= lambda2 3.25e+25)
(*
(* R 2.0)
(atan2
(hypot t_0 t_5)
(sqrt (- 1.0 (fma t_2 (+ 0.5 (* (cos lambda1) -0.5)) t_3)))))
(*
(* R 2.0)
(atan2
(hypot (sin (* phi1 0.5)) t_5)
(sqrt
(-
1.0
(fma t_2 (+ 0.5 (* -0.5 (cos (- lambda1 lambda2)))) t_3)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (phi1 - phi2)));
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = cos(phi1) * cos(phi2);
double t_3 = pow(t_0, 2.0);
double t_4 = sin((0.5 * (lambda1 - lambda2)));
double t_5 = t_4 * sqrt(t_2);
double tmp;
if (lambda2 <= -2.4e-13) {
tmp = R * (2.0 * atan2(sqrt(((cos(phi2) * pow(t_4, 2.0)) + (0.25 * pow(phi2, 2.0)))), sqrt((1.0 - (pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_1 * (t_2 * t_1)))))));
} else if (lambda2 <= 3.25e+25) {
tmp = (R * 2.0) * atan2(hypot(t_0, t_5), sqrt((1.0 - fma(t_2, (0.5 + (cos(lambda1) * -0.5)), t_3))));
} else {
tmp = (R * 2.0) * atan2(hypot(sin((phi1 * 0.5)), t_5), sqrt((1.0 - fma(t_2, (0.5 + (-0.5 * cos((lambda1 - lambda2)))), t_3))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(phi1 - phi2))) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(cos(phi1) * cos(phi2)) t_3 = t_0 ^ 2.0 t_4 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) t_5 = Float64(t_4 * sqrt(t_2)) tmp = 0.0 if (lambda2 <= -2.4e-13) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi2) * (t_4 ^ 2.0)) + Float64(0.25 * (phi2 ^ 2.0)))), sqrt(Float64(1.0 - Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_1 * Float64(t_2 * t_1)))))))); elseif (lambda2 <= 3.25e+25) tmp = Float64(Float64(R * 2.0) * atan(hypot(t_0, t_5), sqrt(Float64(1.0 - fma(t_2, Float64(0.5 + Float64(cos(lambda1) * -0.5)), t_3))))); else tmp = Float64(Float64(R * 2.0) * atan(hypot(sin(Float64(phi1 * 0.5)), t_5), sqrt(Float64(1.0 - fma(t_2, Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2)))), t_3))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[Power[t$95$0, 2.0], $MachinePrecision]}, Block[{t$95$4 = N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$5 = N[(t$95$4 * N[Sqrt[t$95$2], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[lambda2, -2.4e-13], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[t$95$4, 2.0], $MachinePrecision]), $MachinePrecision] + N[(0.25 * N[Power[phi2, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$1 * N[(t$95$2 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[lambda2, 3.25e+25], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[t$95$0 ^ 2 + t$95$5 ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$2 * N[(0.5 + N[(N[Cos[lambda1], $MachinePrecision] * -0.5), $MachinePrecision]), $MachinePrecision] + t$95$3), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] ^ 2 + t$95$5 ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$2 * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$3), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
t_3 := {t\_0}^{2}\\
t_4 := \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\\
t_5 := t\_4 \cdot \sqrt{t\_2}\\
\mathbf{if}\;\lambda_2 \leq -2.4 \cdot 10^{-13}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot {t\_4}^{2} + 0.25 \cdot {\phi_2}^{2}}}{\sqrt{1 - \left({\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_1 \cdot \left(t\_2 \cdot t\_1\right)\right)}}\right)\\
\mathbf{elif}\;\lambda_2 \leq 3.25 \cdot 10^{+25}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(t\_0, t\_5\right)}{\sqrt{1 - \mathsf{fma}\left(t\_2, 0.5 + \cos \lambda_1 \cdot -0.5, t\_3\right)}}\\
\mathbf{else}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(\sin \left(\phi_1 \cdot 0.5\right), t\_5\right)}{\sqrt{1 - \mathsf{fma}\left(t\_2, 0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), t\_3\right)}}\\
\end{array}
\end{array}
if lambda2 < -2.3999999999999999e-13Initial program 44.3%
Taylor expanded in phi2 around 0 32.4%
*-commutative32.4%
associate-*r*32.4%
*-commutative32.4%
Simplified32.4%
Taylor expanded in phi1 around 0 25.4%
if -2.3999999999999999e-13 < lambda2 < 3.25000000000000003e25Initial program 77.5%
associate-*r*77.5%
*-commutative77.5%
Simplified77.5%
Applied egg-rr49.9%
*-lft-identity49.9%
*-commutative49.9%
*-commutative49.9%
cancel-sign-sub-inv49.9%
metadata-eval49.9%
Simplified49.9%
Taylor expanded in lambda2 around 0 50.0%
if 3.25000000000000003e25 < lambda2 Initial program 51.4%
associate-*r*51.4%
*-commutative51.4%
Simplified51.4%
Applied egg-rr37.1%
*-lft-identity37.1%
*-commutative37.1%
*-commutative37.1%
cancel-sign-sub-inv37.1%
metadata-eval37.1%
Simplified37.1%
Taylor expanded in phi2 around 0 26.4%
Final simplification38.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- phi1 phi2))))
(t_1 (sin (* 0.5 (- lambda1 lambda2))))
(t_2 (sin (/ (- lambda1 lambda2) 2.0)))
(t_3 (* (cos phi1) (cos phi2)))
(t_4 (sqrt t_3))
(t_5
(sqrt
(-
1.0
(fma
t_3
(+ 0.5 (* -0.5 (cos (- lambda1 lambda2))))
(pow t_0 2.0))))))
(if (<= lambda2 -2.52e-101)
(*
R
(*
2.0
(atan2
(sqrt (+ (* (cos phi2) (pow t_1 2.0)) (* 0.25 (pow phi2 2.0))))
(sqrt
(-
1.0
(+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* t_2 (* t_3 t_2))))))))
(if (<= lambda2 13000000000000.0)
(* (* R 2.0) (atan2 (hypot t_0 (* t_4 (sin (* 0.5 lambda1)))) t_5))
(* (* R 2.0) (atan2 (hypot (sin (* phi1 0.5)) (* t_1 t_4)) t_5))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (phi1 - phi2)));
double t_1 = sin((0.5 * (lambda1 - lambda2)));
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double t_3 = cos(phi1) * cos(phi2);
double t_4 = sqrt(t_3);
double t_5 = sqrt((1.0 - fma(t_3, (0.5 + (-0.5 * cos((lambda1 - lambda2)))), pow(t_0, 2.0))));
double tmp;
if (lambda2 <= -2.52e-101) {
tmp = R * (2.0 * atan2(sqrt(((cos(phi2) * pow(t_1, 2.0)) + (0.25 * pow(phi2, 2.0)))), sqrt((1.0 - (pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_2 * (t_3 * t_2)))))));
} else if (lambda2 <= 13000000000000.0) {
tmp = (R * 2.0) * atan2(hypot(t_0, (t_4 * sin((0.5 * lambda1)))), t_5);
} else {
tmp = (R * 2.0) * atan2(hypot(sin((phi1 * 0.5)), (t_1 * t_4)), t_5);
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(phi1 - phi2))) t_1 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_3 = Float64(cos(phi1) * cos(phi2)) t_4 = sqrt(t_3) t_5 = sqrt(Float64(1.0 - fma(t_3, Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2)))), (t_0 ^ 2.0)))) tmp = 0.0 if (lambda2 <= -2.52e-101) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi2) * (t_1 ^ 2.0)) + Float64(0.25 * (phi2 ^ 2.0)))), sqrt(Float64(1.0 - Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_2 * Float64(t_3 * t_2)))))))); elseif (lambda2 <= 13000000000000.0) tmp = Float64(Float64(R * 2.0) * atan(hypot(t_0, Float64(t_4 * sin(Float64(0.5 * lambda1)))), t_5)); else tmp = Float64(Float64(R * 2.0) * atan(hypot(sin(Float64(phi1 * 0.5)), Float64(t_1 * t_4)), t_5)); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[Sqrt[t$95$3], $MachinePrecision]}, Block[{t$95$5 = N[Sqrt[N[(1.0 - N[(t$95$3 * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[t$95$0, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[lambda2, -2.52e-101], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[t$95$1, 2.0], $MachinePrecision]), $MachinePrecision] + N[(0.25 * N[Power[phi2, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$2 * N[(t$95$3 * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[lambda2, 13000000000000.0], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[t$95$0 ^ 2 + N[(t$95$4 * N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / t$95$5], $MachinePrecision]), $MachinePrecision], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] ^ 2 + N[(t$95$1 * t$95$4), $MachinePrecision] ^ 2], $MachinePrecision] / t$95$5], $MachinePrecision]), $MachinePrecision]]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
t_1 := \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_3 := \cos \phi_1 \cdot \cos \phi_2\\
t_4 := \sqrt{t\_3}\\
t_5 := \sqrt{1 - \mathsf{fma}\left(t\_3, 0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), {t\_0}^{2}\right)}\\
\mathbf{if}\;\lambda_2 \leq -2.52 \cdot 10^{-101}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot {t\_1}^{2} + 0.25 \cdot {\phi_2}^{2}}}{\sqrt{1 - \left({\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_2 \cdot \left(t\_3 \cdot t\_2\right)\right)}}\right)\\
\mathbf{elif}\;\lambda_2 \leq 13000000000000:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(t\_0, t\_4 \cdot \sin \left(0.5 \cdot \lambda_1\right)\right)}{t\_5}\\
\mathbf{else}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(\sin \left(\phi_1 \cdot 0.5\right), t\_1 \cdot t\_4\right)}{t\_5}\\
\end{array}
\end{array}
if lambda2 < -2.52e-101Initial program 48.2%
Taylor expanded in phi2 around 0 37.1%
*-commutative37.1%
associate-*r*37.1%
*-commutative37.1%
Simplified37.1%
Taylor expanded in phi1 around 0 29.7%
if -2.52e-101 < lambda2 < 1.3e13Initial program 80.2%
associate-*r*80.2%
*-commutative80.2%
Simplified80.2%
Applied egg-rr51.2%
*-lft-identity51.2%
*-commutative51.2%
*-commutative51.2%
cancel-sign-sub-inv51.2%
metadata-eval51.2%
Simplified51.2%
Taylor expanded in lambda2 around 0 50.4%
if 1.3e13 < lambda2 Initial program 51.3%
associate-*r*51.3%
*-commutative51.3%
Simplified51.3%
Applied egg-rr35.7%
*-lft-identity35.7%
*-commutative35.7%
*-commutative35.7%
cancel-sign-sub-inv35.7%
metadata-eval35.7%
Simplified35.7%
Taylor expanded in phi2 around 0 25.4%
Final simplification37.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(*
(cos phi1)
(* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
t_0))
(sqrt
(-
1.0
(+
t_0
(*
(cos phi1)
(* (cos phi2) (- 0.5 (* 0.5 (cos (- lambda1 lambda2))))))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (phi1 - phi2))), 2.0);
return R * (2.0 * atan2(sqrt(((cos(phi1) * (cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0))) + t_0)), sqrt((1.0 - (t_0 + (cos(phi1) * (cos(phi2) * (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
real(8) :: t_0
t_0 = sin((0.5d0 * (phi1 - phi2))) ** 2.0d0
code = r * (2.0d0 * atan2(sqrt(((cos(phi1) * (cos(phi2) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0))) + t_0)), sqrt((1.0d0 - (t_0 + (cos(phi1) * (cos(phi2) * (0.5d0 - (0.5d0 * cos((lambda1 - lambda2)))))))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0);
return R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0))) + t_0)), Math.sqrt((1.0 - (t_0 + (Math.cos(phi1) * (Math.cos(phi2) * (0.5 - (0.5 * Math.cos((lambda1 - lambda2)))))))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0) return R * (2.0 * math.atan2(math.sqrt(((math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0))) + t_0)), math.sqrt((1.0 - (t_0 + (math.cos(phi1) * (math.cos(phi2) * (0.5 - (0.5 * math.cos((lambda1 - lambda2)))))))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0 return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0))) + t_0)), sqrt(Float64(1.0 - Float64(t_0 + Float64(cos(phi1) * Float64(cos(phi2) * Float64(0.5 - Float64(0.5 * cos(Float64(lambda1 - lambda2)))))))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin((0.5 * (phi1 - phi2))) ^ 2.0; tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * (cos(phi2) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0))) + t_0)), sqrt((1.0 - (t_0 + (cos(phi1) * (cos(phi2) * (0.5 - (0.5 * cos((lambda1 - lambda2))))))))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $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[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$0), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 + N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 - N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\right) + t\_0}}{\sqrt{1 - \left(t\_0 + \cos \phi_1 \cdot \left(\cos \phi_2 \cdot \left(0.5 - 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right)\right)\right)}}\right)
\end{array}
\end{array}
Initial program 63.0%
associate-*l*63.0%
Simplified63.0%
add-cbrt-cube63.0%
pow363.0%
Applied egg-rr63.1%
Taylor expanded in phi1 around 0 63.0%
Final simplification63.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2))) (t_1 (sin (* 0.5 (- phi1 phi2)))))
(*
(* R 2.0)
(atan2
(hypot t_1 (* (sin (* 0.5 (- lambda1 lambda2))) (sqrt t_0)))
(sqrt
(-
1.0
(fma t_0 (+ 0.5 (* -0.5 (cos (- lambda1 lambda2)))) (pow t_1 2.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = sin((0.5 * (phi1 - phi2)));
return (R * 2.0) * atan2(hypot(t_1, (sin((0.5 * (lambda1 - lambda2))) * sqrt(t_0))), sqrt((1.0 - fma(t_0, (0.5 + (-0.5 * cos((lambda1 - lambda2)))), pow(t_1, 2.0)))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(0.5 * Float64(phi1 - phi2))) return Float64(Float64(R * 2.0) * atan(hypot(t_1, Float64(sin(Float64(0.5 * Float64(lambda1 - lambda2))) * sqrt(t_0))), sqrt(Float64(1.0 - fma(t_0, Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2)))), (t_1 ^ 2.0)))))) 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[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[t$95$1 ^ 2 + N[(N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[Sqrt[t$95$0], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[t$95$1, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(t\_1, \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right) \cdot \sqrt{t\_0}\right)}{\sqrt{1 - \mathsf{fma}\left(t\_0, 0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), {t\_1}^{2}\right)}}
\end{array}
\end{array}
Initial program 63.0%
associate-*r*63.0%
*-commutative63.0%
Simplified63.0%
Applied egg-rr42.7%
*-lft-identity42.7%
*-commutative42.7%
*-commutative42.7%
cancel-sign-sub-inv42.7%
metadata-eval42.7%
Simplified42.7%
Final simplification42.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(sqrt
(-
1.0
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* t_0 (* (* (cos phi1) (cos phi2)) t_0)))))))
(if (or (<= (- lambda1 lambda2) -5e-84)
(not (<= (- lambda1 lambda2) 2e-107)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(* 0.25 (pow phi2 2.0))))
t_1)))
(*
R
(*
2.0
(atan2
(+
(sin (/ 1.0 (/ 2.0 (- phi1 phi2))))
(*
-0.25
(/
(* lambda2 (* (cos phi1) (* (cos phi2) (sin (* 0.5 lambda1)))))
(sin (* 0.5 (- phi1 phi2))))))
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 = sqrt((1.0 - (pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * ((cos(phi1) * cos(phi2)) * t_0)))));
double tmp;
if (((lambda1 - lambda2) <= -5e-84) || !((lambda1 - lambda2) <= 2e-107)) {
tmp = R * (2.0 * atan2(sqrt(((cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0)) + (0.25 * pow(phi2, 2.0)))), t_1));
} else {
tmp = R * (2.0 * atan2((sin((1.0 / (2.0 / (phi1 - phi2)))) + (-0.25 * ((lambda2 * (cos(phi1) * (cos(phi2) * sin((0.5 * lambda1))))) / sin((0.5 * (phi1 - phi2)))))), t_1));
}
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) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = sqrt((1.0d0 - ((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (t_0 * ((cos(phi1) * cos(phi2)) * t_0)))))
if (((lambda1 - lambda2) <= (-5d-84)) .or. (.not. ((lambda1 - lambda2) <= 2d-107))) then
tmp = r * (2.0d0 * atan2(sqrt(((cos(phi2) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)) + (0.25d0 * (phi2 ** 2.0d0)))), t_1))
else
tmp = r * (2.0d0 * atan2((sin((1.0d0 / (2.0d0 / (phi1 - phi2)))) + ((-0.25d0) * ((lambda2 * (cos(phi1) * (cos(phi2) * sin((0.5d0 * lambda1))))) / sin((0.5d0 * (phi1 - phi2)))))), t_1))
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 t_1 = Math.sqrt((1.0 - (Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0)))));
double tmp;
if (((lambda1 - lambda2) <= -5e-84) || !((lambda1 - lambda2) <= 2e-107)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi2) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)) + (0.25 * Math.pow(phi2, 2.0)))), t_1));
} else {
tmp = R * (2.0 * Math.atan2((Math.sin((1.0 / (2.0 / (phi1 - phi2)))) + (-0.25 * ((lambda2 * (Math.cos(phi1) * (Math.cos(phi2) * Math.sin((0.5 * lambda1))))) / Math.sin((0.5 * (phi1 - phi2)))))), t_1));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.sqrt((1.0 - (math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * ((math.cos(phi1) * math.cos(phi2)) * t_0))))) tmp = 0 if ((lambda1 - lambda2) <= -5e-84) or not ((lambda1 - lambda2) <= 2e-107): tmp = R * (2.0 * math.atan2(math.sqrt(((math.cos(phi2) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0)) + (0.25 * math.pow(phi2, 2.0)))), t_1)) else: tmp = R * (2.0 * math.atan2((math.sin((1.0 / (2.0 / (phi1 - phi2)))) + (-0.25 * ((lambda2 * (math.cos(phi1) * (math.cos(phi2) * math.sin((0.5 * lambda1))))) / math.sin((0.5 * (phi1 - phi2)))))), t_1)) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sqrt(Float64(1.0 - Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0))))) tmp = 0.0 if ((Float64(lambda1 - lambda2) <= -5e-84) || !(Float64(lambda1 - lambda2) <= 2e-107)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)) + Float64(0.25 * (phi2 ^ 2.0)))), t_1))); else tmp = Float64(R * Float64(2.0 * atan(Float64(sin(Float64(1.0 / Float64(2.0 / Float64(phi1 - phi2)))) + Float64(-0.25 * Float64(Float64(lambda2 * Float64(cos(phi1) * Float64(cos(phi2) * sin(Float64(0.5 * lambda1))))) / sin(Float64(0.5 * Float64(phi1 - phi2)))))), t_1))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = sqrt((1.0 - ((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (t_0 * ((cos(phi1) * cos(phi2)) * t_0))))); tmp = 0.0; if (((lambda1 - lambda2) <= -5e-84) || ~(((lambda1 - lambda2) <= 2e-107))) tmp = R * (2.0 * atan2(sqrt(((cos(phi2) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0)) + (0.25 * (phi2 ^ 2.0)))), t_1)); else tmp = R * (2.0 * atan2((sin((1.0 / (2.0 / (phi1 - phi2)))) + (-0.25 * ((lambda2 * (cos(phi1) * (cos(phi2) * sin((0.5 * lambda1))))) / sin((0.5 * (phi1 - phi2)))))), t_1)); 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]}, Block[{t$95$1 = N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[N[(lambda1 - lambda2), $MachinePrecision], -5e-84], N[Not[LessEqual[N[(lambda1 - lambda2), $MachinePrecision], 2e-107]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[(0.25 * N[Power[phi2, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[(N[Sin[N[(1.0 / N[(2.0 / N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] + N[(-0.25 * N[(N[(lambda2 * N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / t$95$1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \sqrt{1 - \left({\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right)\right)}\\
\mathbf{if}\;\lambda_1 - \lambda_2 \leq -5 \cdot 10^{-84} \lor \neg \left(\lambda_1 - \lambda_2 \leq 2 \cdot 10^{-107}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2} + 0.25 \cdot {\phi_2}^{2}}}{t\_1}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sin \left(\frac{1}{\frac{2}{\phi_1 - \phi_2}}\right) + -0.25 \cdot \frac{\lambda_2 \cdot \left(\cos \phi_1 \cdot \left(\cos \phi_2 \cdot \sin \left(0.5 \cdot \lambda_1\right)\right)\right)}{\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}}{t\_1}\right)\\
\end{array}
\end{array}
if (-.f64 lambda1 lambda2) < -5.0000000000000002e-84 or 2e-107 < (-.f64 lambda1 lambda2) Initial program 60.0%
Taylor expanded in phi2 around 0 44.7%
*-commutative44.7%
associate-*r*44.7%
*-commutative44.7%
Simplified44.7%
Taylor expanded in phi1 around 0 30.8%
if -5.0000000000000002e-84 < (-.f64 lambda1 lambda2) < 2e-107Initial program 87.3%
Taylor expanded in lambda1 around 0 87.3%
Taylor expanded in lambda2 around 0 51.4%
*-commutative51.4%
metadata-eval51.4%
div-inv51.4%
clear-num52.9%
Applied egg-rr52.9%
Final simplification33.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(sqrt
(-
1.0
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* t_0 (* (* (cos phi1) (cos phi2)) t_0)))))))
(if (or (<= (- lambda1 lambda2) -5e-84)
(not (<= (- lambda1 lambda2) 2e-107)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(* 0.25 (pow phi2 2.0))))
t_1)))
(* R (* 2.0 (atan2 (sin (* 0.5 (- phi1 phi2))) 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 = sqrt((1.0 - (pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * ((cos(phi1) * cos(phi2)) * t_0)))));
double tmp;
if (((lambda1 - lambda2) <= -5e-84) || !((lambda1 - lambda2) <= 2e-107)) {
tmp = R * (2.0 * atan2(sqrt(((cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0)) + (0.25 * pow(phi2, 2.0)))), t_1));
} else {
tmp = R * (2.0 * atan2(sin((0.5 * (phi1 - phi2))), t_1));
}
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) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = sqrt((1.0d0 - ((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (t_0 * ((cos(phi1) * cos(phi2)) * t_0)))))
if (((lambda1 - lambda2) <= (-5d-84)) .or. (.not. ((lambda1 - lambda2) <= 2d-107))) then
tmp = r * (2.0d0 * atan2(sqrt(((cos(phi2) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)) + (0.25d0 * (phi2 ** 2.0d0)))), t_1))
else
tmp = r * (2.0d0 * atan2(sin((0.5d0 * (phi1 - phi2))), t_1))
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 t_1 = Math.sqrt((1.0 - (Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0)))));
double tmp;
if (((lambda1 - lambda2) <= -5e-84) || !((lambda1 - lambda2) <= 2e-107)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi2) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)) + (0.25 * Math.pow(phi2, 2.0)))), t_1));
} else {
tmp = R * (2.0 * Math.atan2(Math.sin((0.5 * (phi1 - phi2))), t_1));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.sqrt((1.0 - (math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * ((math.cos(phi1) * math.cos(phi2)) * t_0))))) tmp = 0 if ((lambda1 - lambda2) <= -5e-84) or not ((lambda1 - lambda2) <= 2e-107): tmp = R * (2.0 * math.atan2(math.sqrt(((math.cos(phi2) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0)) + (0.25 * math.pow(phi2, 2.0)))), t_1)) else: tmp = R * (2.0 * math.atan2(math.sin((0.5 * (phi1 - phi2))), t_1)) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sqrt(Float64(1.0 - Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0))))) tmp = 0.0 if ((Float64(lambda1 - lambda2) <= -5e-84) || !(Float64(lambda1 - lambda2) <= 2e-107)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)) + Float64(0.25 * (phi2 ^ 2.0)))), t_1))); else tmp = Float64(R * Float64(2.0 * atan(sin(Float64(0.5 * Float64(phi1 - phi2))), t_1))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = sqrt((1.0 - ((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (t_0 * ((cos(phi1) * cos(phi2)) * t_0))))); tmp = 0.0; if (((lambda1 - lambda2) <= -5e-84) || ~(((lambda1 - lambda2) <= 2e-107))) tmp = R * (2.0 * atan2(sqrt(((cos(phi2) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0)) + (0.25 * (phi2 ^ 2.0)))), t_1)); else tmp = R * (2.0 * atan2(sin((0.5 * (phi1 - phi2))), t_1)); 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]}, Block[{t$95$1 = N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[N[(lambda1 - lambda2), $MachinePrecision], -5e-84], N[Not[LessEqual[N[(lambda1 - lambda2), $MachinePrecision], 2e-107]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[(0.25 * N[Power[phi2, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \sqrt{1 - \left({\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right)\right)}\\
\mathbf{if}\;\lambda_1 - \lambda_2 \leq -5 \cdot 10^{-84} \lor \neg \left(\lambda_1 - \lambda_2 \leq 2 \cdot 10^{-107}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2} + 0.25 \cdot {\phi_2}^{2}}}{t\_1}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}{t\_1}\right)\\
\end{array}
\end{array}
if (-.f64 lambda1 lambda2) < -5.0000000000000002e-84 or 2e-107 < (-.f64 lambda1 lambda2) Initial program 60.0%
Taylor expanded in phi2 around 0 44.7%
*-commutative44.7%
associate-*r*44.7%
*-commutative44.7%
Simplified44.7%
Taylor expanded in phi1 around 0 30.8%
if -5.0000000000000002e-84 < (-.f64 lambda1 lambda2) < 2e-107Initial program 87.3%
Taylor expanded in lambda1 around 0 87.3%
div-sub87.3%
sin-diff87.3%
div-inv87.3%
metadata-eval87.3%
div-inv87.3%
metadata-eval87.3%
div-inv87.3%
metadata-eval87.3%
div-inv87.3%
metadata-eval87.3%
Applied egg-rr87.3%
Taylor expanded in lambda2 around 0 51.4%
Final simplification33.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0))))
(if (<= t_1 1e-79)
(*
R
(*
2.0
(atan2
(sin (* 0.5 (- phi1 phi2)))
(sqrt
(-
1.0
(+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* t_1 (* t_0 t_1))))))))
(*
R
(*
2.0
(atan2
(* (sin (* 0.5 (- lambda1 lambda2))) (sqrt (cos phi2)))
(sqrt (- (pow (cos (* phi1 0.5)) 2.0) (* t_0 (* t_1 t_1))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if (t_1 <= 1e-79) {
tmp = R * (2.0 * atan2(sin((0.5 * (phi1 - phi2))), sqrt((1.0 - (pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_1 * (t_0 * t_1)))))));
} else {
tmp = R * (2.0 * atan2((sin((0.5 * (lambda1 - lambda2))) * sqrt(cos(phi2))), sqrt((pow(cos((phi1 * 0.5)), 2.0) - (t_0 * (t_1 * t_1))))));
}
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) :: tmp
t_0 = cos(phi1) * cos(phi2)
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
if (t_1 <= 1d-79) then
tmp = r * (2.0d0 * atan2(sin((0.5d0 * (phi1 - phi2))), sqrt((1.0d0 - ((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (t_1 * (t_0 * t_1)))))))
else
tmp = r * (2.0d0 * atan2((sin((0.5d0 * (lambda1 - lambda2))) * sqrt(cos(phi2))), sqrt(((cos((phi1 * 0.5d0)) ** 2.0d0) - (t_0 * (t_1 * t_1))))))
end if
code = tmp
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.sin(((lambda1 - lambda2) / 2.0));
double tmp;
if (t_1 <= 1e-79) {
tmp = R * (2.0 * Math.atan2(Math.sin((0.5 * (phi1 - phi2))), Math.sqrt((1.0 - (Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_1 * (t_0 * t_1)))))));
} else {
tmp = R * (2.0 * Math.atan2((Math.sin((0.5 * (lambda1 - lambda2))) * Math.sqrt(Math.cos(phi2))), Math.sqrt((Math.pow(Math.cos((phi1 * 0.5)), 2.0) - (t_0 * (t_1 * t_1))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi1) * math.cos(phi2) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) tmp = 0 if t_1 <= 1e-79: tmp = R * (2.0 * math.atan2(math.sin((0.5 * (phi1 - phi2))), math.sqrt((1.0 - (math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_1 * (t_0 * t_1))))))) else: tmp = R * (2.0 * math.atan2((math.sin((0.5 * (lambda1 - lambda2))) * math.sqrt(math.cos(phi2))), math.sqrt((math.pow(math.cos((phi1 * 0.5)), 2.0) - (t_0 * (t_1 * t_1)))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if (t_1 <= 1e-79) tmp = Float64(R * Float64(2.0 * atan(sin(Float64(0.5 * Float64(phi1 - phi2))), sqrt(Float64(1.0 - Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_1 * Float64(t_0 * t_1)))))))); else tmp = Float64(R * Float64(2.0 * atan(Float64(sin(Float64(0.5 * Float64(lambda1 - lambda2))) * sqrt(cos(phi2))), sqrt(Float64((cos(Float64(phi1 * 0.5)) ^ 2.0) - Float64(t_0 * Float64(t_1 * t_1))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi1) * cos(phi2); t_1 = sin(((lambda1 - lambda2) / 2.0)); tmp = 0.0; if (t_1 <= 1e-79) tmp = R * (2.0 * atan2(sin((0.5 * (phi1 - phi2))), sqrt((1.0 - ((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (t_1 * (t_0 * t_1))))))); else tmp = R * (2.0 * atan2((sin((0.5 * (lambda1 - lambda2))) * sqrt(cos(phi2))), sqrt(((cos((phi1 * 0.5)) ^ 2.0) - (t_0 * (t_1 * t_1)))))); end tmp_2 = tmp; 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[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[t$95$1, 1e-79], N[(R * N[(2.0 * N[ArcTan[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$1 * N[(t$95$0 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[(N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[Sqrt[N[Cos[phi2], $MachinePrecision]], $MachinePrecision]), $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(t$95$0 * N[(t$95$1 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;t\_1 \leq 10^{-79}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}{\sqrt{1 - \left({\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_1 \cdot \left(t\_0 \cdot t\_1\right)\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right) \cdot \sqrt{\cos \phi_2}}{\sqrt{{\cos \left(\phi_1 \cdot 0.5\right)}^{2} - t\_0 \cdot \left(t\_1 \cdot t\_1\right)}}\right)\\
\end{array}
\end{array}
if (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < 1e-79Initial program 69.3%
Taylor expanded in lambda1 around 0 51.9%
div-sub51.9%
sin-diff51.8%
div-inv51.8%
metadata-eval51.8%
div-inv51.8%
metadata-eval51.8%
div-inv51.8%
metadata-eval51.8%
div-inv51.8%
metadata-eval51.8%
Applied egg-rr51.8%
Taylor expanded in lambda2 around 0 19.0%
if 1e-79 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) Initial program 55.1%
associate-*l*55.1%
Simplified55.1%
Taylor expanded in phi1 around inf 38.4%
Taylor expanded in phi2 around 0 38.4%
unpow238.4%
1-sub-sin38.5%
unpow238.5%
*-commutative38.5%
Simplified38.5%
Taylor expanded in phi1 around 0 24.5%
Final simplification21.4%
(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 2.0)) 2.0)))
(sqrt
(- 1.0 (* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 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 / 2.0)), 2.0))), sqrt((1.0 - (cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 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 / 2.0d0)) ** 2.0d0))), sqrt((1.0d0 - (cos(phi2) * (sin((0.5d0 * (lambda1 - lambda2))) ** 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 / 2.0)), 2.0))), Math.sqrt((1.0 - (Math.cos(phi2) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 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 / 2.0)), 2.0))), math.sqrt((1.0 - (math.cos(phi2) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 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(phi1 / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 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 / 2.0)) ^ 2.0))), sqrt((1.0 - (cos(phi2) * (sin((0.5 * (lambda1 - lambda2))) ^ 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[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $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{\phi_1}{2}\right)}^{2}}}{\sqrt{1 - \cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}\right)
\end{array}
\end{array}
Initial program 63.0%
associate-*l*63.0%
Simplified63.0%
Taylor expanded in phi1 around inf 42.5%
Taylor expanded in phi2 around 0 42.5%
unpow242.5%
1-sub-sin42.5%
unpow242.5%
*-commutative42.5%
Simplified42.5%
Taylor expanded in phi1 around 0 28.9%
Final simplification28.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(sqrt
(-
1.0
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* t_0 (* (* (cos phi1) (cos phi2)) t_0)))))))
(if (<= phi2 -6e-193)
(* R (* 2.0 (atan2 (sin (* 0.5 (- phi1 phi2))) t_1)))
(*
R
(*
2.0
(atan2
(* phi2 (- (* 0.5 (cos (* phi1 0.5))) (/ (sin (* phi1 0.5)) phi2)))
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 = sqrt((1.0 - (pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * ((cos(phi1) * cos(phi2)) * t_0)))));
double tmp;
if (phi2 <= -6e-193) {
tmp = R * (2.0 * atan2(sin((0.5 * (phi1 - phi2))), t_1));
} else {
tmp = R * (2.0 * atan2((phi2 * ((0.5 * cos((phi1 * 0.5))) - (sin((phi1 * 0.5)) / phi2))), t_1));
}
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) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = sqrt((1.0d0 - ((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (t_0 * ((cos(phi1) * cos(phi2)) * t_0)))))
if (phi2 <= (-6d-193)) then
tmp = r * (2.0d0 * atan2(sin((0.5d0 * (phi1 - phi2))), t_1))
else
tmp = r * (2.0d0 * atan2((phi2 * ((0.5d0 * cos((phi1 * 0.5d0))) - (sin((phi1 * 0.5d0)) / phi2))), t_1))
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 t_1 = Math.sqrt((1.0 - (Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0)))));
double tmp;
if (phi2 <= -6e-193) {
tmp = R * (2.0 * Math.atan2(Math.sin((0.5 * (phi1 - phi2))), t_1));
} else {
tmp = R * (2.0 * Math.atan2((phi2 * ((0.5 * Math.cos((phi1 * 0.5))) - (Math.sin((phi1 * 0.5)) / phi2))), t_1));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.sqrt((1.0 - (math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * ((math.cos(phi1) * math.cos(phi2)) * t_0))))) tmp = 0 if phi2 <= -6e-193: tmp = R * (2.0 * math.atan2(math.sin((0.5 * (phi1 - phi2))), t_1)) else: tmp = R * (2.0 * math.atan2((phi2 * ((0.5 * math.cos((phi1 * 0.5))) - (math.sin((phi1 * 0.5)) / phi2))), t_1)) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sqrt(Float64(1.0 - Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0))))) tmp = 0.0 if (phi2 <= -6e-193) tmp = Float64(R * Float64(2.0 * atan(sin(Float64(0.5 * Float64(phi1 - phi2))), t_1))); else tmp = Float64(R * Float64(2.0 * atan(Float64(phi2 * Float64(Float64(0.5 * cos(Float64(phi1 * 0.5))) - Float64(sin(Float64(phi1 * 0.5)) / phi2))), t_1))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = sqrt((1.0 - ((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (t_0 * ((cos(phi1) * cos(phi2)) * t_0))))); tmp = 0.0; if (phi2 <= -6e-193) tmp = R * (2.0 * atan2(sin((0.5 * (phi1 - phi2))), t_1)); else tmp = R * (2.0 * atan2((phi2 * ((0.5 * cos((phi1 * 0.5))) - (sin((phi1 * 0.5)) / phi2))), t_1)); 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]}, Block[{t$95$1 = N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi2, -6e-193], N[(R * N[(2.0 * N[ArcTan[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[(phi2 * N[(N[(0.5 * N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] / phi2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / t$95$1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \sqrt{1 - \left({\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right)\right)}\\
\mathbf{if}\;\phi_2 \leq -6 \cdot 10^{-193}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}{t\_1}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\phi_2 \cdot \left(0.5 \cdot \cos \left(\phi_1 \cdot 0.5\right) - \frac{\sin \left(\phi_1 \cdot 0.5\right)}{\phi_2}\right)}{t\_1}\right)\\
\end{array}
\end{array}
if phi2 < -5.9999999999999998e-193Initial program 58.7%
Taylor expanded in lambda1 around 0 46.9%
div-sub46.9%
sin-diff46.8%
div-inv46.8%
metadata-eval46.8%
div-inv46.8%
metadata-eval46.8%
div-inv46.8%
metadata-eval46.8%
div-inv46.8%
metadata-eval46.8%
Applied egg-rr46.8%
Taylor expanded in lambda2 around 0 18.2%
if -5.9999999999999998e-193 < phi2 Initial program 66.0%
Taylor expanded in phi2 around 0 50.0%
*-commutative50.0%
associate-*r*50.0%
*-commutative50.0%
Simplified50.0%
Taylor expanded in phi2 around inf 19.2%
+-commutative19.2%
mul-1-neg19.2%
unsub-neg19.2%
Simplified19.2%
Final simplification18.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(sqrt
(-
1.0
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* t_0 (* (* (cos phi1) (cos phi2)) t_0)))))))
(if (<= phi2 8.5e-70)
(* R (* 2.0 (atan2 (sin (* 0.5 (- phi1 phi2))) t_1)))
(* R (* 2.0 (atan2 (* 0.5 phi2) 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 = sqrt((1.0 - (pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * ((cos(phi1) * cos(phi2)) * t_0)))));
double tmp;
if (phi2 <= 8.5e-70) {
tmp = R * (2.0 * atan2(sin((0.5 * (phi1 - phi2))), t_1));
} else {
tmp = R * (2.0 * atan2((0.5 * phi2), t_1));
}
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) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = sqrt((1.0d0 - ((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (t_0 * ((cos(phi1) * cos(phi2)) * t_0)))))
if (phi2 <= 8.5d-70) then
tmp = r * (2.0d0 * atan2(sin((0.5d0 * (phi1 - phi2))), t_1))
else
tmp = r * (2.0d0 * atan2((0.5d0 * phi2), t_1))
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 t_1 = Math.sqrt((1.0 - (Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0)))));
double tmp;
if (phi2 <= 8.5e-70) {
tmp = R * (2.0 * Math.atan2(Math.sin((0.5 * (phi1 - phi2))), t_1));
} else {
tmp = R * (2.0 * Math.atan2((0.5 * phi2), t_1));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.sqrt((1.0 - (math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * ((math.cos(phi1) * math.cos(phi2)) * t_0))))) tmp = 0 if phi2 <= 8.5e-70: tmp = R * (2.0 * math.atan2(math.sin((0.5 * (phi1 - phi2))), t_1)) else: tmp = R * (2.0 * math.atan2((0.5 * phi2), t_1)) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sqrt(Float64(1.0 - Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0))))) tmp = 0.0 if (phi2 <= 8.5e-70) tmp = Float64(R * Float64(2.0 * atan(sin(Float64(0.5 * Float64(phi1 - phi2))), t_1))); else tmp = Float64(R * Float64(2.0 * atan(Float64(0.5 * phi2), t_1))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = sqrt((1.0 - ((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (t_0 * ((cos(phi1) * cos(phi2)) * t_0))))); tmp = 0.0; if (phi2 <= 8.5e-70) tmp = R * (2.0 * atan2(sin((0.5 * (phi1 - phi2))), t_1)); else tmp = R * (2.0 * atan2((0.5 * phi2), t_1)); 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]}, Block[{t$95$1 = N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi2, 8.5e-70], N[(R * N[(2.0 * N[ArcTan[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[(0.5 * phi2), $MachinePrecision] / t$95$1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \sqrt{1 - \left({\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right)\right)}\\
\mathbf{if}\;\phi_2 \leq 8.5 \cdot 10^{-70}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}{t\_1}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{0.5 \cdot \phi_2}{t\_1}\right)\\
\end{array}
\end{array}
if phi2 < 8.5000000000000002e-70Initial program 67.2%
Taylor expanded in lambda1 around 0 44.9%
div-sub44.9%
sin-diff44.5%
div-inv44.5%
metadata-eval44.5%
div-inv44.5%
metadata-eval44.5%
div-inv44.5%
metadata-eval44.5%
div-inv44.5%
metadata-eval44.5%
Applied egg-rr44.5%
Taylor expanded in lambda2 around 0 16.8%
if 8.5000000000000002e-70 < phi2 Initial program 53.6%
Taylor expanded in phi2 around 0 23.2%
*-commutative23.2%
associate-*r*23.2%
*-commutative23.2%
Simplified23.2%
Taylor expanded in phi2 around inf 16.2%
associate-*r*16.2%
Simplified16.2%
Taylor expanded in phi1 around 0 18.0%
*-commutative18.0%
Simplified18.0%
Final simplification17.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(* (* 0.5 phi2) (cos (* phi1 0.5)))
(sqrt
(-
1.0
(+
(* (cos phi1) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(pow (sin (* phi1 0.5)) 2.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2(((0.5 * phi2) * cos((phi1 * 0.5))), sqrt((1.0 - ((cos(phi1) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0)) + 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
code = r * (2.0d0 * atan2(((0.5d0 * phi2) * cos((phi1 * 0.5d0))), sqrt((1.0d0 - ((cos(phi1) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)) + (sin((phi1 * 0.5d0)) ** 2.0d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * Math.atan2(((0.5 * phi2) * Math.cos((phi1 * 0.5))), Math.sqrt((1.0 - ((Math.cos(phi1) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)) + Math.pow(Math.sin((phi1 * 0.5)), 2.0))))));
}
def code(R, lambda1, lambda2, phi1, phi2): return R * (2.0 * math.atan2(((0.5 * phi2) * math.cos((phi1 * 0.5))), math.sqrt((1.0 - ((math.cos(phi1) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0)) + math.pow(math.sin((phi1 * 0.5)), 2.0))))))
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(Float64(Float64(0.5 * phi2) * cos(Float64(phi1 * 0.5))), sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)) + (sin(Float64(phi1 * 0.5)) ^ 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) tmp = R * (2.0 * atan2(((0.5 * phi2) * cos((phi1 * 0.5))), sqrt((1.0 - ((cos(phi1) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0)) + (sin((phi1 * 0.5)) ^ 2.0)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[(N[(0.5 * phi2), $MachinePrecision] * N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\left(0.5 \cdot \phi_2\right) \cdot \cos \left(\phi_1 \cdot 0.5\right)}{\sqrt{1 - \left(\cos \phi_1 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2} + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}\right)
\end{array}
Initial program 63.0%
Taylor expanded in phi2 around 0 46.8%
*-commutative46.8%
associate-*r*46.8%
*-commutative46.8%
Simplified46.8%
Taylor expanded in phi2 around inf 9.2%
associate-*r*9.2%
Simplified9.2%
Taylor expanded in phi2 around 0 9.5%
Final simplification9.5%
herbie shell --seed 2024151
(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))))))))))