
(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 18 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_0) t_0))))
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0);
return R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0)
code = r * (2.0d0 * atan2(sqrt(t_1), sqrt((1.0d0 - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((Math.cos(phi1) * Math.cos(phi2)) * t_0) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt(t_1), Math.sqrt((1.0 - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((math.cos(phi1) * math.cos(phi2)) * t_0) * t_0) return R * (2.0 * math.atan2(math.sqrt(t_1), math.sqrt((1.0 - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0); tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$1], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) \cdot t\_0\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)
\end{array}
\end{array}
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2
(pow
(-
(* (cos (* phi2 0.5)) (sin (* phi1 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0))
(t_3
(-
(* (sin (* lambda1 0.5)) (cos (* lambda2 0.5)))
(* (cos (* lambda1 0.5)) (sin (* lambda2 0.5))))))
(*
(atan2
(sqrt (fma t_0 (* t_1 t_1) t_2))
(sqrt (- 1.0 (fma t_0 (* t_3 t_3) t_2))))
(* 2.0 R))))
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 t_2 = pow(((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0);
double t_3 = (sin((lambda1 * 0.5)) * cos((lambda2 * 0.5))) - (cos((lambda1 * 0.5)) * sin((lambda2 * 0.5)));
return atan2(sqrt(fma(t_0, (t_1 * t_1), t_2)), sqrt((1.0 - fma(t_0, (t_3 * t_3), t_2)))) * (2.0 * R);
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(Float64(cos(Float64(phi2 * 0.5)) * sin(Float64(phi1 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0 t_3 = Float64(Float64(sin(Float64(lambda1 * 0.5)) * cos(Float64(lambda2 * 0.5))) - Float64(cos(Float64(lambda1 * 0.5)) * sin(Float64(lambda2 * 0.5)))) return Float64(atan(sqrt(fma(t_0, Float64(t_1 * t_1), t_2)), sqrt(Float64(1.0 - fma(t_0, Float64(t_3 * t_3), t_2)))) * Float64(2.0 * R)) 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]}, Block[{t$95$2 = N[Power[N[(N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$3 = N[(N[(N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(lambda2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(lambda2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, N[(N[ArcTan[N[Sqrt[N[(t$95$0 * N[(t$95$1 * t$95$1), $MachinePrecision] + t$95$2), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 * N[(t$95$3 * t$95$3), $MachinePrecision] + t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(2.0 * R), $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)\\
t_2 := {\left(\cos \left(\phi_2 \cdot 0.5\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\\
t_3 := \sin \left(\lambda_1 \cdot 0.5\right) \cdot \cos \left(\lambda_2 \cdot 0.5\right) - \cos \left(\lambda_1 \cdot 0.5\right) \cdot \sin \left(\lambda_2 \cdot 0.5\right)\\
\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, t\_1 \cdot t\_1, t\_2\right)}}{\sqrt{1 - \mathsf{fma}\left(t\_0, t\_3 \cdot t\_3, t\_2\right)}} \cdot \left(2 \cdot R\right)
\end{array}
\end{array}
Initial program 63.9%
associate-*r*63.9%
*-commutative63.9%
Simplified63.9%
div-sub63.9%
sin-diff64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
Applied egg-rr64.8%
div-sub64.8%
sin-diff77.8%
div-inv77.8%
metadata-eval77.8%
div-inv77.8%
metadata-eval77.8%
div-inv77.8%
metadata-eval77.8%
div-inv77.8%
metadata-eval77.8%
Applied egg-rr77.8%
div-sub77.8%
sin-diff77.7%
div-inv77.7%
metadata-eval77.7%
div-inv77.7%
metadata-eval77.7%
div-inv77.7%
metadata-eval77.7%
div-inv77.7%
metadata-eval77.7%
Applied egg-rr77.7%
div-sub77.7%
sin-diff78.3%
div-inv78.3%
metadata-eval78.3%
div-inv78.3%
metadata-eval78.3%
div-inv78.3%
metadata-eval78.3%
div-inv78.3%
metadata-eval78.3%
Applied egg-rr78.3%
Final simplification78.3%
(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 (/ (- phi1 phi2) 2.0)) 2.0) (* t_0 (* t_1 t_0))))
(t_3 (sqrt (- 1.0 t_2)))
(t_4
(pow
(-
(* (cos (* phi2 0.5)) (sin (* phi1 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0)))
(if (<= (atan2 (sqrt t_2) t_3) 0.01)
(*
R
(*
2.0
(atan2
(pow
(sqrt
(hypot
(sin (* 0.5 (- phi1 phi2)))
(*
(sqrt t_1)
(-
(* (sin (/ lambda1 2.0)) (cos (/ lambda2 2.0)))
(* (cos (/ lambda1 2.0)) (sin (/ lambda2 2.0)))))))
2.0)
t_3)))
(*
(* 2.0 R)
(atan2
(sqrt (fma t_1 (- 0.5 (/ (cos (- lambda1 lambda2)) 2.0)) t_4))
(sqrt (- 1.0 (fma t_1 (* t_0 t_0) t_4))))))))
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(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * (t_1 * t_0));
double t_3 = sqrt((1.0 - t_2));
double t_4 = pow(((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0);
double tmp;
if (atan2(sqrt(t_2), t_3) <= 0.01) {
tmp = R * (2.0 * atan2(pow(sqrt(hypot(sin((0.5 * (phi1 - phi2))), (sqrt(t_1) * ((sin((lambda1 / 2.0)) * cos((lambda2 / 2.0))) - (cos((lambda1 / 2.0)) * sin((lambda2 / 2.0))))))), 2.0), t_3));
} else {
tmp = (2.0 * R) * atan2(sqrt(fma(t_1, (0.5 - (cos((lambda1 - lambda2)) / 2.0)), t_4)), sqrt((1.0 - fma(t_1, (t_0 * t_0), t_4))));
}
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 = Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_0 * Float64(t_1 * t_0))) t_3 = sqrt(Float64(1.0 - t_2)) t_4 = Float64(Float64(cos(Float64(phi2 * 0.5)) * sin(Float64(phi1 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0 tmp = 0.0 if (atan(sqrt(t_2), t_3) <= 0.01) tmp = Float64(R * Float64(2.0 * atan((sqrt(hypot(sin(Float64(0.5 * Float64(phi1 - phi2))), Float64(sqrt(t_1) * 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), t_3))); else tmp = Float64(Float64(2.0 * R) * atan(sqrt(fma(t_1, Float64(0.5 - Float64(cos(Float64(lambda1 - lambda2)) / 2.0)), t_4)), sqrt(Float64(1.0 - fma(t_1, Float64(t_0 * t_0), t_4))))); 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[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = 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]}, Block[{t$95$3 = N[Sqrt[N[(1.0 - t$95$2), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[Power[N[(N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, If[LessEqual[N[ArcTan[N[Sqrt[t$95$2], $MachinePrecision] / t$95$3], $MachinePrecision], 0.01], N[(R * N[(2.0 * N[ArcTan[N[Power[N[Sqrt[N[Sqrt[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] ^ 2 + N[(N[Sqrt[t$95$1], $MachinePrecision] * 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]), $MachinePrecision] ^ 2], $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] / t$95$3], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(2.0 * R), $MachinePrecision] * N[ArcTan[N[Sqrt[N[(t$95$1 * N[(0.5 - N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision] + t$95$4), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$1 * N[(t$95$0 * t$95$0), $MachinePrecision] + t$95$4), $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(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_0 \cdot \left(t\_1 \cdot t\_0\right)\\
t_3 := \sqrt{1 - t\_2}\\
t_4 := {\left(\cos \left(\phi_2 \cdot 0.5\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\\
\mathbf{if}\;\tan^{-1}_* \frac{\sqrt{t\_2}}{t\_3} \leq 0.01:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{{\left(\sqrt{\mathsf{hypot}\left(\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right), \sqrt{t\_1} \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)\right)}\right)}^{2}}{t\_3}\right)\\
\mathbf{else}:\\
\;\;\;\;\left(2 \cdot R\right) \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_1, 0.5 - \frac{\cos \left(\lambda_1 - \lambda_2\right)}{2}, t\_4\right)}}{\sqrt{1 - \mathsf{fma}\left(t\_1, t\_0 \cdot t\_0, t\_4\right)}}\\
\end{array}
\end{array}
if (atan2.f64 (sqrt.f64 (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))))) (sqrt.f64 (-.f64 #s(literal 1 binary64) (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))))))) < 0.0100000000000000002Initial program 93.1%
add-sqr-sqrt92.6%
pow292.6%
Applied egg-rr97.3%
metadata-eval97.3%
div-inv97.3%
div-sub97.3%
sin-diff98.6%
Applied egg-rr98.6%
if 0.0100000000000000002 < (atan2.f64 (sqrt.f64 (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))))) (sqrt.f64 (-.f64 #s(literal 1 binary64) (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))))))) Initial program 61.7%
associate-*r*61.7%
*-commutative61.7%
Simplified61.7%
div-sub61.7%
sin-diff62.7%
div-inv62.7%
metadata-eval62.7%
div-inv62.7%
metadata-eval62.7%
div-inv62.7%
metadata-eval62.7%
div-inv62.7%
metadata-eval62.7%
Applied egg-rr62.7%
div-sub62.7%
sin-diff76.6%
div-inv76.6%
metadata-eval76.6%
div-inv76.6%
metadata-eval76.6%
div-inv76.6%
metadata-eval76.6%
div-inv76.6%
metadata-eval76.6%
Applied egg-rr76.6%
sin-mult76.6%
cos-sum76.5%
cos-276.6%
div-sub76.6%
+-inverses76.6%
Applied egg-rr76.6%
cos-076.6%
metadata-eval76.6%
Simplified76.6%
Final simplification78.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(fma
(* (cos phi1) (cos phi2))
(* t_0 t_0)
(pow
(-
(* (cos (* phi2 0.5)) (sin (* phi1 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0))))
(* (* 2.0 R) (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 = fma((cos(phi1) * cos(phi2)), (t_0 * t_0), pow(((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0));
return (2.0 * R) * atan2(sqrt(t_1), sqrt((1.0 - t_1)));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = fma(Float64(cos(phi1) * cos(phi2)), Float64(t_0 * t_0), (Float64(Float64(cos(Float64(phi2 * 0.5)) * sin(Float64(phi1 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0)) return Float64(Float64(2.0 * R) * atan(sqrt(t_1), sqrt(Float64(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[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision] + N[Power[N[(N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, N[(N[(2.0 * R), $MachinePrecision] * N[ArcTan[N[Sqrt[t$95$1], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \mathsf{fma}\left(\cos \phi_1 \cdot \cos \phi_2, t\_0 \cdot t\_0, {\left(\cos \left(\phi_2 \cdot 0.5\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\right)\\
\left(2 \cdot R\right) \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}
\end{array}
\end{array}
Initial program 63.9%
associate-*r*63.9%
*-commutative63.9%
Simplified63.9%
div-sub63.9%
sin-diff64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
Applied egg-rr64.8%
div-sub64.8%
sin-diff77.8%
div-inv77.8%
metadata-eval77.8%
div-inv77.8%
metadata-eval77.8%
div-inv77.8%
metadata-eval77.8%
div-inv77.8%
metadata-eval77.8%
Applied egg-rr77.8%
Final simplification77.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(pow
(-
(* (cos (* phi2 0.5)) (sin (* phi1 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0))
(t_1 (* (cos phi1) (cos phi2)))
(t_2 (sin (/ (- lambda1 lambda2) 2.0)))
(t_3 (* t_2 t_2)))
(if (or (<= lambda1 -1e-5) (not (<= lambda1 32.0)))
(*
(* 2.0 R)
(atan2
(sqrt
(+ t_0 (* (cos phi1) (* (cos phi2) (pow (sin (* lambda1 0.5)) 2.0)))))
(sqrt (- 1.0 (fma t_1 t_3 t_0)))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_0 (* t_1 t_3)))
(sqrt (- (- 1.0 t_0) (* t_1 (* t_2 (sin (* lambda2 -0.5))))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0);
double t_1 = cos(phi1) * cos(phi2);
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double t_3 = t_2 * t_2;
double tmp;
if ((lambda1 <= -1e-5) || !(lambda1 <= 32.0)) {
tmp = (2.0 * R) * atan2(sqrt((t_0 + (cos(phi1) * (cos(phi2) * pow(sin((lambda1 * 0.5)), 2.0))))), sqrt((1.0 - fma(t_1, t_3, t_0))));
} else {
tmp = R * (2.0 * atan2(sqrt((t_0 + (t_1 * t_3))), sqrt(((1.0 - t_0) - (t_1 * (t_2 * sin((lambda2 * -0.5))))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(Float64(cos(Float64(phi2 * 0.5)) * sin(Float64(phi1 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0 t_1 = Float64(cos(phi1) * cos(phi2)) t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_3 = Float64(t_2 * t_2) tmp = 0.0 if ((lambda1 <= -1e-5) || !(lambda1 <= 32.0)) tmp = Float64(Float64(2.0 * R) * atan(sqrt(Float64(t_0 + Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(lambda1 * 0.5)) ^ 2.0))))), sqrt(Float64(1.0 - fma(t_1, t_3, t_0))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_0 + Float64(t_1 * t_3))), sqrt(Float64(Float64(1.0 - t_0) - Float64(t_1 * Float64(t_2 * sin(Float64(lambda2 * -0.5))))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[(N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[(t$95$2 * t$95$2), $MachinePrecision]}, If[Or[LessEqual[lambda1, -1e-5], N[Not[LessEqual[lambda1, 32.0]], $MachinePrecision]], N[(N[(2.0 * R), $MachinePrecision] * N[ArcTan[N[Sqrt[N[(t$95$0 + N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$1 * t$95$3 + t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 + N[(t$95$1 * t$95$3), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - t$95$0), $MachinePrecision] - N[(t$95$1 * N[(t$95$2 * N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\left(\cos \left(\phi_2 \cdot 0.5\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_3 := t\_2 \cdot t\_2\\
\mathbf{if}\;\lambda_1 \leq -1 \cdot 10^{-5} \lor \neg \left(\lambda_1 \leq 32\right):\\
\;\;\;\;\left(2 \cdot R\right) \cdot \tan^{-1}_* \frac{\sqrt{t\_0 + \cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(\lambda_1 \cdot 0.5\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left(t\_1, t\_3, t\_0\right)}}\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 + t\_1 \cdot t\_3}}{\sqrt{\left(1 - t\_0\right) - t\_1 \cdot \left(t\_2 \cdot \sin \left(\lambda_2 \cdot -0.5\right)\right)}}\right)\\
\end{array}
\end{array}
if lambda1 < -1.00000000000000008e-5 or 32 < lambda1 Initial program 48.4%
associate-*r*48.4%
*-commutative48.4%
Simplified48.4%
div-sub48.4%
sin-diff49.6%
div-inv49.6%
metadata-eval49.6%
div-inv49.6%
metadata-eval49.6%
div-inv49.6%
metadata-eval49.6%
div-inv49.6%
metadata-eval49.6%
Applied egg-rr49.6%
div-sub49.6%
sin-diff59.9%
div-inv59.9%
metadata-eval59.9%
div-inv59.9%
metadata-eval59.9%
div-inv59.9%
metadata-eval59.9%
div-inv59.9%
metadata-eval59.9%
Applied egg-rr59.9%
Taylor expanded in lambda2 around 0 60.4%
if -1.00000000000000008e-5 < lambda1 < 32Initial program 80.4%
associate-*l*80.4%
Simplified80.5%
Taylor expanded in lambda1 around 0 80.3%
div-sub80.3%
sin-diff80.9%
div-inv80.9%
metadata-eval80.9%
div-inv80.9%
metadata-eval80.9%
div-inv80.9%
metadata-eval80.9%
div-inv80.9%
metadata-eval80.9%
Applied egg-rr80.9%
div-sub80.9%
sin-diff96.6%
div-inv96.6%
metadata-eval96.6%
div-inv96.6%
metadata-eval96.6%
div-inv96.6%
metadata-eval96.6%
div-inv96.6%
metadata-eval96.6%
Applied egg-rr96.6%
Final simplification77.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (* t_1 t_1))
(t_3 (* (cos phi1) (cos phi2)))
(t_4 (* t_3 t_2))
(t_5
(pow
(-
(* (cos (* phi2 0.5)) (sin (* phi1 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0)))
(if (<= lambda1 -850000000.0)
(*
R
(*
2.0
(atan2
(sqrt (+ t_0 t_4))
(sqrt
(-
(-
1.0
(pow
(log
(exp
(-
(* (sin (/ phi1 2.0)) (cos (/ phi2 2.0)))
(* (cos (/ phi1 2.0)) (sin (/ phi2 2.0))))))
2.0))
t_4)))))
(if (<= lambda1 8e-20)
(*
R
(*
2.0
(atan2
(sqrt (+ t_5 t_4))
(sqrt (- (- 1.0 t_5) (* t_3 (* t_1 (sin (* lambda2 -0.5)))))))))
(*
(* 2.0 R)
(atan2 (sqrt (fma t_3 t_2 t_5)) (sqrt (- 1.0 (fma t_3 t_2 t_0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = t_1 * t_1;
double t_3 = cos(phi1) * cos(phi2);
double t_4 = t_3 * t_2;
double t_5 = pow(((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0);
double tmp;
if (lambda1 <= -850000000.0) {
tmp = R * (2.0 * atan2(sqrt((t_0 + t_4)), sqrt(((1.0 - pow(log(exp(((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))))), 2.0)) - t_4))));
} else if (lambda1 <= 8e-20) {
tmp = R * (2.0 * atan2(sqrt((t_5 + t_4)), sqrt(((1.0 - t_5) - (t_3 * (t_1 * sin((lambda2 * -0.5))))))));
} else {
tmp = (2.0 * R) * atan2(sqrt(fma(t_3, t_2, t_5)), sqrt((1.0 - fma(t_3, t_2, t_0))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(t_1 * t_1) t_3 = Float64(cos(phi1) * cos(phi2)) t_4 = Float64(t_3 * t_2) t_5 = Float64(Float64(cos(Float64(phi2 * 0.5)) * sin(Float64(phi1 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0 tmp = 0.0 if (lambda1 <= -850000000.0) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_0 + t_4)), sqrt(Float64(Float64(1.0 - (log(exp(Float64(Float64(sin(Float64(phi1 / 2.0)) * cos(Float64(phi2 / 2.0))) - Float64(cos(Float64(phi1 / 2.0)) * sin(Float64(phi2 / 2.0)))))) ^ 2.0)) - t_4))))); elseif (lambda1 <= 8e-20) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_5 + t_4)), sqrt(Float64(Float64(1.0 - t_5) - Float64(t_3 * Float64(t_1 * sin(Float64(lambda2 * -0.5))))))))); else tmp = Float64(Float64(2.0 * R) * atan(sqrt(fma(t_3, t_2, t_5)), sqrt(Float64(1.0 - fma(t_3, t_2, t_0))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(t$95$1 * t$95$1), $MachinePrecision]}, Block[{t$95$3 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(t$95$3 * t$95$2), $MachinePrecision]}, Block[{t$95$5 = N[Power[N[(N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, If[LessEqual[lambda1, -850000000.0], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 + t$95$4), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[Log[N[Exp[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]], $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] - t$95$4), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[lambda1, 8e-20], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$5 + t$95$4), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - t$95$5), $MachinePrecision] - N[(t$95$3 * N[(t$95$1 * N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(2.0 * R), $MachinePrecision] * N[ArcTan[N[Sqrt[N[(t$95$3 * t$95$2 + t$95$5), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$3 * t$95$2 + t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := t\_1 \cdot t\_1\\
t_3 := \cos \phi_1 \cdot \cos \phi_2\\
t_4 := t\_3 \cdot t\_2\\
t_5 := {\left(\cos \left(\phi_2 \cdot 0.5\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\\
\mathbf{if}\;\lambda_1 \leq -850000000:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 + t\_4}}{\sqrt{\left(1 - {\log \left(e^{\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}\right) - t\_4}}\right)\\
\mathbf{elif}\;\lambda_1 \leq 8 \cdot 10^{-20}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_5 + t\_4}}{\sqrt{\left(1 - t\_5\right) - t\_3 \cdot \left(t\_1 \cdot \sin \left(\lambda_2 \cdot -0.5\right)\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;\left(2 \cdot R\right) \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_3, t\_2, t\_5\right)}}{\sqrt{1 - \mathsf{fma}\left(t\_3, t\_2, t\_0\right)}}\\
\end{array}
\end{array}
if lambda1 < -8.5e8Initial program 51.6%
associate-*l*51.6%
Simplified51.6%
pow151.6%
metadata-eval51.6%
sqrt-pow151.6%
add-log-exp51.6%
sqrt-pow151.6%
metadata-eval51.6%
pow151.6%
div-inv51.6%
metadata-eval51.6%
Applied egg-rr51.6%
metadata-eval51.6%
div-inv51.6%
div-sub51.6%
sin-diff52.2%
Applied egg-rr52.2%
if -8.5e8 < lambda1 < 7.99999999999999956e-20Initial program 79.6%
associate-*l*79.6%
Simplified79.6%
Taylor expanded in lambda1 around 0 79.6%
div-sub79.6%
sin-diff80.2%
div-inv80.2%
metadata-eval80.2%
div-inv80.2%
metadata-eval80.2%
div-inv80.2%
metadata-eval80.2%
div-inv80.2%
metadata-eval80.2%
Applied egg-rr80.2%
div-sub80.2%
sin-diff96.1%
div-inv96.1%
metadata-eval96.1%
div-inv96.1%
metadata-eval96.1%
div-inv96.1%
metadata-eval96.1%
div-inv96.1%
metadata-eval96.1%
Applied egg-rr96.1%
if 7.99999999999999956e-20 < lambda1 Initial program 48.8%
associate-*r*48.8%
*-commutative48.8%
Simplified48.8%
div-sub48.8%
sin-diff50.3%
div-inv50.3%
metadata-eval50.3%
div-inv50.3%
metadata-eval50.3%
div-inv50.3%
metadata-eval50.3%
div-inv50.3%
metadata-eval50.3%
Applied egg-rr50.3%
Final simplification72.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* t_0 t_0))
(t_2 (* (cos phi1) (cos phi2))))
(*
(* 2.0 R)
(atan2
(sqrt
(fma
t_2
t_1
(pow
(-
(* (cos (* phi2 0.5)) (sin (* phi1 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0)))
(sqrt (- 1.0 (fma t_2 t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 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 = t_0 * t_0;
double t_2 = cos(phi1) * cos(phi2);
return (2.0 * R) * atan2(sqrt(fma(t_2, t_1, pow(((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0))), sqrt((1.0 - fma(t_2, t_1, pow(sin(((phi1 - phi2) / 2.0)), 2.0)))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(t_0 * t_0) t_2 = Float64(cos(phi1) * cos(phi2)) return Float64(Float64(2.0 * R) * atan(sqrt(fma(t_2, t_1, (Float64(Float64(cos(Float64(phi2 * 0.5)) * sin(Float64(phi1 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0))), sqrt(Float64(1.0 - fma(t_2, t_1, (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 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[(t$95$0 * t$95$0), $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, N[(N[(2.0 * R), $MachinePrecision] * N[ArcTan[N[Sqrt[N[(t$95$2 * t$95$1 + N[Power[N[(N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$2 * t$95$1 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := t\_0 \cdot t\_0\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
\left(2 \cdot R\right) \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_2, t\_1, {\left(\cos \left(\phi_2 \cdot 0.5\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left(t\_2, t\_1, {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right)}}
\end{array}
\end{array}
Initial program 63.9%
associate-*r*63.9%
*-commutative63.9%
Simplified63.9%
div-sub63.9%
sin-diff64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
Applied egg-rr64.8%
Final simplification64.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* t_0 (* (* (cos phi1) (cos phi2)) t_0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow
(-
(* (cos (* phi2 0.5)) (sin (* phi1 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0)
t_1))
(sqrt (- 1.0 (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) 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 = t_0 * ((cos(phi1) * cos(phi2)) * t_0);
return R * (2.0 * atan2(sqrt((pow(((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0) + t_1)), sqrt((1.0 - (pow(sin(((phi1 - phi2) / 2.0)), 2.0) + 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 = t_0 * ((cos(phi1) * cos(phi2)) * t_0)
code = r * (2.0d0 * atan2(sqrt(((((cos((phi2 * 0.5d0)) * sin((phi1 * 0.5d0))) - (cos((phi1 * 0.5d0)) * sin((phi2 * 0.5d0)))) ** 2.0d0) + t_1)), sqrt((1.0d0 - ((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + 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 = t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(((Math.cos((phi2 * 0.5)) * Math.sin((phi1 * 0.5))) - (Math.cos((phi1 * 0.5)) * Math.sin((phi2 * 0.5)))), 2.0) + t_1)), Math.sqrt((1.0 - (Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = t_0 * ((math.cos(phi1) * math.cos(phi2)) * t_0) return R * (2.0 * math.atan2(math.sqrt((math.pow(((math.cos((phi2 * 0.5)) * math.sin((phi1 * 0.5))) - (math.cos((phi1 * 0.5)) * math.sin((phi2 * 0.5)))), 2.0) + t_1)), math.sqrt((1.0 - (math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((Float64(Float64(cos(Float64(phi2 * 0.5)) * sin(Float64(phi1 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0) + t_1)), sqrt(Float64(1.0 - Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + t_1)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = t_0 * ((cos(phi1) * cos(phi2)) * t_0); tmp = R * (2.0 * atan2(sqrt(((((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))) ^ 2.0) + t_1)), sqrt((1.0 - ((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + 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[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$1), $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 := t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\cos \left(\phi_2 \cdot 0.5\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2} + t\_1}}{\sqrt{1 - \left({\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_1\right)}}\right)
\end{array}
\end{array}
Initial program 63.9%
div-sub63.9%
sin-diff64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
Applied egg-rr64.8%
Final simplification64.8%
(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 (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) t_1))
(sqrt
(-
(-
1.0
(pow
(-
(* (cos (* phi2 0.5)) (sin (* phi1 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0))
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 = (cos(phi1) * cos(phi2)) * (t_0 * t_0);
return R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), sqrt(((1.0 - pow(((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0)) - 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 = (cos(phi1) * cos(phi2)) * (t_0 * t_0)
code = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + t_1)), sqrt(((1.0d0 - (((cos((phi2 * 0.5d0)) * sin((phi1 * 0.5d0))) - (cos((phi1 * 0.5d0)) * sin((phi2 * 0.5d0)))) ** 2.0d0)) - 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.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0);
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), Math.sqrt(((1.0 - Math.pow(((Math.cos((phi2 * 0.5)) * Math.sin((phi1 * 0.5))) - (Math.cos((phi1 * 0.5)) * Math.sin((phi2 * 0.5)))), 2.0)) - 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((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), math.sqrt(((1.0 - math.pow(((math.cos((phi2 * 0.5)) * math.sin((phi1 * 0.5))) - (math.cos((phi1 * 0.5)) * math.sin((phi2 * 0.5)))), 2.0)) - 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((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + t_1)), sqrt(Float64(Float64(1.0 - (Float64(Float64(cos(Float64(phi2 * 0.5)) * sin(Float64(phi1 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0)) - 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(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + t_1)), sqrt(((1.0 - (((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))) ^ 2.0)) - 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[(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[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[(N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $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{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_1}}{\sqrt{\left(1 - {\left(\cos \left(\phi_2 \cdot 0.5\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\right) - t\_1}}\right)
\end{array}
\end{array}
Initial program 63.9%
associate-*l*63.9%
Simplified63.9%
div-sub63.9%
sin-diff64.6%
div-inv64.6%
metadata-eval64.6%
div-inv64.6%
metadata-eval64.6%
div-inv64.6%
metadata-eval64.6%
div-inv64.6%
metadata-eval64.6%
Applied egg-rr64.6%
Final simplification64.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* t_0 (* (* (cos phi1) (cos phi2)) t_0))))
(sqrt
(fabs
(-
1.0
(fma
(* (cos phi2) (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0))
(cos phi1)
(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));
return R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * ((cos(phi1) * cos(phi2)) * t_0)))), sqrt(fabs((1.0 - fma((cos(phi2) * pow(sin((-0.5 * (lambda2 - lambda1))), 2.0)), cos(phi1), pow(sin((-0.5 * (phi2 - phi1))), 2.0)))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)))), sqrt(abs(Float64(1.0 - fma(Float64(cos(phi2) * (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0)), cos(phi1), (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]}, 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[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[Abs[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] * N[Cos[phi1], $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)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\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)}}{\sqrt{\left|1 - \mathsf{fma}\left(\cos \phi_2 \cdot {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}, \cos \phi_1, {\sin \left(-0.5 \cdot \left(\phi_2 - \phi_1\right)\right)}^{2}\right)\right|}}\right)
\end{array}
\end{array}
Initial program 63.9%
add-sqr-sqrt63.9%
sqrt-unprod64.2%
pow264.2%
Applied egg-rr64.3%
Simplified64.3%
Final simplification64.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0)))
(if (or (<= phi2 -6.7e-6) (not (<= phi2 6.5e-5)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (cos phi2) (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(pow (sin (* phi2 -0.5)) 2.0)))
(sqrt (- (pow (cos (* phi2 -0.5)) 2.0) (* (cos phi2) t_1))))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* t_0 (* (* (cos phi1) (cos phi2)) t_0))))
(sqrt (- (pow (cos (* phi1 0.5)) 2.0) (* (cos phi1) 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((-0.5 * (lambda2 - lambda1))), 2.0);
double tmp;
if ((phi2 <= -6.7e-6) || !(phi2 <= 6.5e-5)) {
tmp = R * (2.0 * atan2(sqrt(((cos(phi2) * pow(sin(((lambda1 - lambda2) * 0.5)), 2.0)) + pow(sin((phi2 * -0.5)), 2.0))), sqrt((pow(cos((phi2 * -0.5)), 2.0) - (cos(phi2) * t_1)))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * ((cos(phi1) * cos(phi2)) * t_0)))), sqrt((pow(cos((phi1 * 0.5)), 2.0) - (cos(phi1) * 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 = sin(((-0.5d0) * (lambda2 - lambda1))) ** 2.0d0
if ((phi2 <= (-6.7d-6)) .or. (.not. (phi2 <= 6.5d-5))) then
tmp = r * (2.0d0 * atan2(sqrt(((cos(phi2) * (sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0)) + (sin((phi2 * (-0.5d0))) ** 2.0d0))), sqrt(((cos((phi2 * (-0.5d0))) ** 2.0d0) - (cos(phi2) * t_1)))))
else
tmp = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (t_0 * ((cos(phi1) * cos(phi2)) * t_0)))), sqrt(((cos((phi1 * 0.5d0)) ** 2.0d0) - (cos(phi1) * 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.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0);
double tmp;
if ((phi2 <= -6.7e-6) || !(phi2 <= 6.5e-5)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi2) * Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0)) + Math.pow(Math.sin((phi2 * -0.5)), 2.0))), Math.sqrt((Math.pow(Math.cos((phi2 * -0.5)), 2.0) - (Math.cos(phi2) * t_1)))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0)))), Math.sqrt((Math.pow(Math.cos((phi1 * 0.5)), 2.0) - (Math.cos(phi1) * t_1)))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin((-0.5 * (lambda2 - lambda1))), 2.0) tmp = 0 if (phi2 <= -6.7e-6) or not (phi2 <= 6.5e-5): tmp = R * (2.0 * math.atan2(math.sqrt(((math.cos(phi2) * math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0)) + math.pow(math.sin((phi2 * -0.5)), 2.0))), math.sqrt((math.pow(math.cos((phi2 * -0.5)), 2.0) - (math.cos(phi2) * t_1))))) else: tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * ((math.cos(phi1) * math.cos(phi2)) * t_0)))), math.sqrt((math.pow(math.cos((phi1 * 0.5)), 2.0) - (math.cos(phi1) * t_1))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0 tmp = 0.0 if ((phi2 <= -6.7e-6) || !(phi2 <= 6.5e-5)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi2) * (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0)) + (sin(Float64(phi2 * -0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) - Float64(cos(phi2) * t_1)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)))), sqrt(Float64((cos(Float64(phi1 * 0.5)) ^ 2.0) - Float64(cos(phi1) * t_1)))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = sin((-0.5 * (lambda2 - lambda1))) ^ 2.0; tmp = 0.0; if ((phi2 <= -6.7e-6) || ~((phi2 <= 6.5e-5))) tmp = R * (2.0 * atan2(sqrt(((cos(phi2) * (sin(((lambda1 - lambda2) * 0.5)) ^ 2.0)) + (sin((phi2 * -0.5)) ^ 2.0))), sqrt(((cos((phi2 * -0.5)) ^ 2.0) - (cos(phi2) * t_1))))); else tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (t_0 * ((cos(phi1) * cos(phi2)) * t_0)))), sqrt(((cos((phi1 * 0.5)) ^ 2.0) - (cos(phi1) * 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[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[phi2, -6.7e-6], N[Not[LessEqual[phi2, 6.5e-5]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi2], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $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[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi1], $MachinePrecision] * t$95$1), $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(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}\\
\mathbf{if}\;\phi_2 \leq -6.7 \cdot 10^{-6} \lor \neg \left(\phi_2 \leq 6.5 \cdot 10^{-5}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2} + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}}}{\sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} - \cos \phi_2 \cdot t\_1}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\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)}}{\sqrt{{\cos \left(\phi_1 \cdot 0.5\right)}^{2} - \cos \phi_1 \cdot t\_1}}\right)\\
\end{array}
\end{array}
if phi2 < -6.7e-6 or 6.49999999999999943e-5 < phi2 Initial program 49.3%
Taylor expanded in phi1 around 0 49.8%
+-commutative49.8%
associate--r+49.8%
unpow249.8%
1-sub-sin49.9%
unpow249.9%
*-commutative49.9%
Simplified49.9%
Taylor expanded in phi1 around 0 50.9%
if -6.7e-6 < phi2 < 6.49999999999999943e-5Initial program 79.5%
Taylor expanded in phi2 around 0 79.5%
Simplified79.6%
Final simplification64.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(*
R
(*
2.0
(atan2
(sqrt (+ t_2 (* t_0 (* t_1 t_1))))
(sqrt
(+ (- 1.0 t_2) (* t_0 (- (/ (cos (- lambda1 lambda2)) 2.0) 0.5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
return R * (2.0 * atan2(sqrt((t_2 + (t_0 * (t_1 * t_1)))), sqrt(((1.0 - t_2) + (t_0 * ((cos((lambda1 - lambda2)) / 2.0) - 0.5))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
t_0 = cos(phi1) * cos(phi2)
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
t_2 = sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0
code = r * (2.0d0 * atan2(sqrt((t_2 + (t_0 * (t_1 * t_1)))), sqrt(((1.0d0 - t_2) + (t_0 * ((cos((lambda1 - lambda2)) / 2.0d0) - 0.5d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.cos(phi1) * Math.cos(phi2);
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_2 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0);
return R * (2.0 * Math.atan2(Math.sqrt((t_2 + (t_0 * (t_1 * t_1)))), Math.sqrt(((1.0 - t_2) + (t_0 * ((Math.cos((lambda1 - lambda2)) / 2.0) - 0.5))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi1) * math.cos(phi2) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) t_2 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) return R * (2.0 * math.atan2(math.sqrt((t_2 + (t_0 * (t_1 * t_1)))), math.sqrt(((1.0 - t_2) + (t_0 * ((math.cos((lambda1 - lambda2)) / 2.0) - 0.5))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_2 + Float64(t_0 * Float64(t_1 * t_1)))), sqrt(Float64(Float64(1.0 - t_2) + Float64(t_0 * Float64(Float64(cos(Float64(lambda1 - lambda2)) / 2.0) - 0.5))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi1) * cos(phi2); t_1 = sin(((lambda1 - lambda2) / 2.0)); t_2 = sin(((phi1 - phi2) / 2.0)) ^ 2.0; tmp = R * (2.0 * atan2(sqrt((t_2 + (t_0 * (t_1 * t_1)))), sqrt(((1.0 - t_2) + (t_0 * ((cos((lambda1 - lambda2)) / 2.0) - 0.5)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$2 + N[(t$95$0 * N[(t$95$1 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - t$95$2), $MachinePrecision] + N[(t$95$0 * N[(N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 + t\_0 \cdot \left(t\_1 \cdot t\_1\right)}}{\sqrt{\left(1 - t\_2\right) + t\_0 \cdot \left(\frac{\cos \left(\lambda_1 - \lambda_2\right)}{2} - 0.5\right)}}\right)
\end{array}
\end{array}
Initial program 63.9%
associate-*l*63.9%
Simplified63.9%
sin-mult64.0%
cos-sum63.9%
cos-264.0%
div-sub64.0%
+-inverses64.0%
Applied egg-rr64.0%
cos-064.0%
metadata-eval64.0%
Simplified64.0%
Final simplification64.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* t_0 (* (* (cos phi1) (cos phi2)) t_0))))
(sqrt
(-
(pow (cos (* phi2 -0.5)) 2.0)
(* (cos phi2) (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * ((cos(phi1) * cos(phi2)) * t_0)))), sqrt((pow(cos((phi2 * -0.5)), 2.0) - (cos(phi2) * pow(sin((-0.5 * (lambda2 - lambda1))), 2.0))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (t_0 * ((cos(phi1) * cos(phi2)) * t_0)))), sqrt(((cos((phi2 * (-0.5d0))) ** 2.0d0) - (cos(phi2) * (sin(((-0.5d0) * (lambda2 - lambda1))) ** 2.0d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0)))), Math.sqrt((Math.pow(Math.cos((phi2 * -0.5)), 2.0) - (Math.cos(phi2) * Math.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) return R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * ((math.cos(phi1) * math.cos(phi2)) * t_0)))), math.sqrt((math.pow(math.cos((phi2 * -0.5)), 2.0) - (math.cos(phi2) * math.pow(math.sin((-0.5 * (lambda2 - lambda1))), 2.0))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)))), sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) - Float64(cos(phi2) * (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (t_0 * ((cos(phi1) * cos(phi2)) * t_0)))), sqrt(((cos((phi2 * -0.5)) ^ 2.0) - (cos(phi2) * (sin((-0.5 * (lambda2 - lambda1))) ^ 2.0)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $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{{\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)}}{\sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} - \cos \phi_2 \cdot {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}}}\right)
\end{array}
\end{array}
Initial program 63.9%
Taylor expanded in phi1 around 0 49.7%
+-commutative49.7%
associate--r+49.7%
unpow249.7%
1-sub-sin49.8%
unpow249.8%
*-commutative49.8%
Simplified49.8%
Final simplification49.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (cos phi2) (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(pow (sin (* phi2 -0.5)) 2.0)))
(sqrt
(-
(pow (cos (* phi2 -0.5)) 2.0)
(* (cos phi2) (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2(sqrt(((cos(phi2) * pow(sin(((lambda1 - lambda2) * 0.5)), 2.0)) + pow(sin((phi2 * -0.5)), 2.0))), sqrt((pow(cos((phi2 * -0.5)), 2.0) - (cos(phi2) * pow(sin((-0.5 * (lambda2 - lambda1))), 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(sqrt(((cos(phi2) * (sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0)) + (sin((phi2 * (-0.5d0))) ** 2.0d0))), sqrt(((cos((phi2 * (-0.5d0))) ** 2.0d0) - (cos(phi2) * (sin(((-0.5d0) * (lambda2 - lambda1))) ** 2.0d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi2) * Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0)) + Math.pow(Math.sin((phi2 * -0.5)), 2.0))), Math.sqrt((Math.pow(Math.cos((phi2 * -0.5)), 2.0) - (Math.cos(phi2) * Math.pow(Math.sin((-0.5 * (lambda2 - lambda1))), 2.0))))));
}
def code(R, lambda1, lambda2, phi1, phi2): return R * (2.0 * math.atan2(math.sqrt(((math.cos(phi2) * math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0)) + math.pow(math.sin((phi2 * -0.5)), 2.0))), math.sqrt((math.pow(math.cos((phi2 * -0.5)), 2.0) - (math.cos(phi2) * math.pow(math.sin((-0.5 * (lambda2 - lambda1))), 2.0))))))
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi2) * (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0)) + (sin(Float64(phi2 * -0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) - Float64(cos(phi2) * (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) tmp = R * (2.0 * atan2(sqrt(((cos(phi2) * (sin(((lambda1 - lambda2) * 0.5)) ^ 2.0)) + (sin((phi2 * -0.5)) ^ 2.0))), sqrt(((cos((phi2 * -0.5)) ^ 2.0) - (cos(phi2) * (sin((-0.5 * (lambda2 - lambda1))) ^ 2.0)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2} + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}}}{\sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} - \cos \phi_2 \cdot {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}}}\right)
\end{array}
Initial program 63.9%
Taylor expanded in phi1 around 0 49.7%
+-commutative49.7%
associate--r+49.7%
unpow249.7%
1-sub-sin49.8%
unpow249.8%
*-commutative49.8%
Simplified49.8%
Taylor expanded in phi1 around 0 47.7%
Final simplification47.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (cos (* phi2 -0.5)) 2.0)) (t_1 (pow (sin (* phi1 0.5)) 2.0)))
(if (or (<= lambda1 -82000000000.0) (not (<= lambda1 7.5e+22)))
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (* (cos phi1) (pow (sin (* lambda1 0.5)) 2.0))))
(sqrt
(+ t_0 (* (cos phi2) (- (/ (cos (- lambda2 lambda1)) 2.0) 0.5)))))))
(*
R
(*
2.0
(atan2
(sqrt
(+ (* (cos phi1) (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)) t_1))
(sqrt (+ t_0 (* (cos phi2) (- (/ (cos lambda2) 2.0) 0.5))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(cos((phi2 * -0.5)), 2.0);
double t_1 = pow(sin((phi1 * 0.5)), 2.0);
double tmp;
if ((lambda1 <= -82000000000.0) || !(lambda1 <= 7.5e+22)) {
tmp = R * (2.0 * atan2(sqrt((t_1 + (cos(phi1) * pow(sin((lambda1 * 0.5)), 2.0)))), sqrt((t_0 + (cos(phi2) * ((cos((lambda2 - lambda1)) / 2.0) - 0.5))))));
} else {
tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * pow(sin(((lambda1 - lambda2) * 0.5)), 2.0)) + t_1)), sqrt((t_0 + (cos(phi2) * ((cos(lambda2) / 2.0) - 0.5))))));
}
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((phi2 * (-0.5d0))) ** 2.0d0
t_1 = sin((phi1 * 0.5d0)) ** 2.0d0
if ((lambda1 <= (-82000000000.0d0)) .or. (.not. (lambda1 <= 7.5d+22))) then
tmp = r * (2.0d0 * atan2(sqrt((t_1 + (cos(phi1) * (sin((lambda1 * 0.5d0)) ** 2.0d0)))), sqrt((t_0 + (cos(phi2) * ((cos((lambda2 - lambda1)) / 2.0d0) - 0.5d0))))))
else
tmp = r * (2.0d0 * atan2(sqrt(((cos(phi1) * (sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0)) + t_1)), sqrt((t_0 + (cos(phi2) * ((cos(lambda2) / 2.0d0) - 0.5d0))))))
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((phi2 * -0.5)), 2.0);
double t_1 = Math.pow(Math.sin((phi1 * 0.5)), 2.0);
double tmp;
if ((lambda1 <= -82000000000.0) || !(lambda1 <= 7.5e+22)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_1 + (Math.cos(phi1) * Math.pow(Math.sin((lambda1 * 0.5)), 2.0)))), Math.sqrt((t_0 + (Math.cos(phi2) * ((Math.cos((lambda2 - lambda1)) / 2.0) - 0.5))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi1) * Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0)) + t_1)), Math.sqrt((t_0 + (Math.cos(phi2) * ((Math.cos(lambda2) / 2.0) - 0.5))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(math.cos((phi2 * -0.5)), 2.0) t_1 = math.pow(math.sin((phi1 * 0.5)), 2.0) tmp = 0 if (lambda1 <= -82000000000.0) or not (lambda1 <= 7.5e+22): tmp = R * (2.0 * math.atan2(math.sqrt((t_1 + (math.cos(phi1) * math.pow(math.sin((lambda1 * 0.5)), 2.0)))), math.sqrt((t_0 + (math.cos(phi2) * ((math.cos((lambda2 - lambda1)) / 2.0) - 0.5)))))) else: tmp = R * (2.0 * math.atan2(math.sqrt(((math.cos(phi1) * math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0)) + t_1)), math.sqrt((t_0 + (math.cos(phi2) * ((math.cos(lambda2) / 2.0) - 0.5)))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(phi2 * -0.5)) ^ 2.0 t_1 = sin(Float64(phi1 * 0.5)) ^ 2.0 tmp = 0.0 if ((lambda1 <= -82000000000.0) || !(lambda1 <= 7.5e+22)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + Float64(cos(phi1) * (sin(Float64(lambda1 * 0.5)) ^ 2.0)))), sqrt(Float64(t_0 + Float64(cos(phi2) * Float64(Float64(cos(Float64(lambda2 - lambda1)) / 2.0) - 0.5))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi1) * (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0)) + t_1)), sqrt(Float64(t_0 + Float64(cos(phi2) * Float64(Float64(cos(lambda2) / 2.0) - 0.5))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos((phi2 * -0.5)) ^ 2.0; t_1 = sin((phi1 * 0.5)) ^ 2.0; tmp = 0.0; if ((lambda1 <= -82000000000.0) || ~((lambda1 <= 7.5e+22))) tmp = R * (2.0 * atan2(sqrt((t_1 + (cos(phi1) * (sin((lambda1 * 0.5)) ^ 2.0)))), sqrt((t_0 + (cos(phi2) * ((cos((lambda2 - lambda1)) / 2.0) - 0.5)))))); else tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * (sin(((lambda1 - lambda2) * 0.5)) ^ 2.0)) + t_1)), sqrt((t_0 + (cos(phi2) * ((cos(lambda2) / 2.0) - 0.5)))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[lambda1, -82000000000.0], N[Not[LessEqual[lambda1, 7.5e+22]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(t$95$0 + N[(N[Cos[phi2], $MachinePrecision] * N[(N[(N[Cos[N[(lambda2 - lambda1), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(t$95$0 + N[(N[Cos[phi2], $MachinePrecision] * N[(N[(N[Cos[lambda2], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\cos \left(\phi_2 \cdot -0.5\right)}^{2}\\
t_1 := {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\\
\mathbf{if}\;\lambda_1 \leq -82000000000 \lor \neg \left(\lambda_1 \leq 7.5 \cdot 10^{+22}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + \cos \phi_1 \cdot {\sin \left(\lambda_1 \cdot 0.5\right)}^{2}}}{\sqrt{t\_0 + \cos \phi_2 \cdot \left(\frac{\cos \left(\lambda_2 - \lambda_1\right)}{2} - 0.5\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_1 \cdot {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2} + t\_1}}{\sqrt{t\_0 + \cos \phi_2 \cdot \left(\frac{\cos \lambda_2}{2} - 0.5\right)}}\right)\\
\end{array}
\end{array}
if lambda1 < -8.2e10 or 7.5000000000000002e22 < lambda1 Initial program 49.1%
Taylor expanded in phi1 around 0 38.8%
+-commutative38.8%
associate--r+38.8%
unpow238.8%
1-sub-sin38.8%
unpow238.8%
*-commutative38.8%
Simplified38.8%
Taylor expanded in phi2 around 0 32.8%
unpow232.8%
sin-mult32.8%
Applied egg-rr32.8%
div-sub32.8%
+-inverses32.8%
cos-032.8%
metadata-eval32.8%
count-232.8%
associate-*r*32.8%
metadata-eval32.8%
mul-1-neg32.8%
cos-neg32.8%
Simplified32.8%
Taylor expanded in lambda2 around 0 33.0%
if -8.2e10 < lambda1 < 7.5000000000000002e22Initial program 77.8%
Taylor expanded in phi1 around 0 60.0%
+-commutative60.0%
associate--r+60.0%
unpow260.0%
1-sub-sin60.0%
unpow260.0%
*-commutative60.0%
Simplified60.0%
Taylor expanded in phi2 around 0 34.0%
unpow234.0%
sin-mult34.0%
Applied egg-rr34.0%
div-sub34.0%
+-inverses34.0%
cos-034.0%
metadata-eval34.0%
count-234.0%
associate-*r*34.0%
metadata-eval34.0%
mul-1-neg34.0%
cos-neg34.0%
Simplified34.0%
Taylor expanded in lambda1 around 0 34.1%
Final simplification33.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (cos phi1) (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(pow (sin (* phi1 0.5)) 2.0)))
(sqrt
(+
(pow (cos (* phi2 -0.5)) 2.0)
(* (cos phi2) (- (/ (cos (- lambda2 lambda1)) 2.0) 0.5))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2(sqrt(((cos(phi1) * pow(sin(((lambda1 - lambda2) * 0.5)), 2.0)) + pow(sin((phi1 * 0.5)), 2.0))), sqrt((pow(cos((phi2 * -0.5)), 2.0) + (cos(phi2) * ((cos((lambda2 - lambda1)) / 2.0) - 0.5))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
code = r * (2.0d0 * atan2(sqrt(((cos(phi1) * (sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0)) + (sin((phi1 * 0.5d0)) ** 2.0d0))), sqrt(((cos((phi2 * (-0.5d0))) ** 2.0d0) + (cos(phi2) * ((cos((lambda2 - lambda1)) / 2.0d0) - 0.5d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi1) * Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0)) + Math.pow(Math.sin((phi1 * 0.5)), 2.0))), Math.sqrt((Math.pow(Math.cos((phi2 * -0.5)), 2.0) + (Math.cos(phi2) * ((Math.cos((lambda2 - lambda1)) / 2.0) - 0.5))))));
}
def code(R, lambda1, lambda2, phi1, phi2): return R * (2.0 * math.atan2(math.sqrt(((math.cos(phi1) * math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0)) + math.pow(math.sin((phi1 * 0.5)), 2.0))), math.sqrt((math.pow(math.cos((phi2 * -0.5)), 2.0) + (math.cos(phi2) * ((math.cos((lambda2 - lambda1)) / 2.0) - 0.5))))))
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi1) * (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0)) + (sin(Float64(phi1 * 0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) + Float64(cos(phi2) * Float64(Float64(cos(Float64(lambda2 - lambda1)) / 2.0) - 0.5))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * (sin(((lambda1 - lambda2) * 0.5)) ^ 2.0)) + (sin((phi1 * 0.5)) ^ 2.0))), sqrt(((cos((phi2 * -0.5)) ^ 2.0) + (cos(phi2) * ((cos((lambda2 - lambda1)) / 2.0) - 0.5)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi2], $MachinePrecision] * N[(N[(N[Cos[N[(lambda2 - lambda1), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_1 \cdot {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2} + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}}}{\sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} + \cos \phi_2 \cdot \left(\frac{\cos \left(\lambda_2 - \lambda_1\right)}{2} - 0.5\right)}}\right)
\end{array}
Initial program 63.9%
Taylor expanded in phi1 around 0 49.7%
+-commutative49.7%
associate--r+49.7%
unpow249.7%
1-sub-sin49.8%
unpow249.8%
*-commutative49.8%
Simplified49.8%
Taylor expanded in phi2 around 0 33.4%
unpow233.4%
sin-mult33.4%
Applied egg-rr33.4%
div-sub33.4%
+-inverses33.4%
cos-033.4%
metadata-eval33.4%
count-233.4%
associate-*r*33.4%
metadata-eval33.4%
mul-1-neg33.4%
cos-neg33.4%
Simplified33.4%
Final simplification33.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (cos phi1) (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(pow (sin (* phi1 0.5)) 2.0)))
(sqrt
(+
(pow (cos (* phi2 -0.5)) 2.0)
(* (cos phi2) (- (/ (cos lambda1) 2.0) 0.5))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2(sqrt(((cos(phi1) * pow(sin(((lambda1 - lambda2) * 0.5)), 2.0)) + pow(sin((phi1 * 0.5)), 2.0))), sqrt((pow(cos((phi2 * -0.5)), 2.0) + (cos(phi2) * ((cos(lambda1) / 2.0) - 0.5))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
code = r * (2.0d0 * atan2(sqrt(((cos(phi1) * (sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0)) + (sin((phi1 * 0.5d0)) ** 2.0d0))), sqrt(((cos((phi2 * (-0.5d0))) ** 2.0d0) + (cos(phi2) * ((cos(lambda1) / 2.0d0) - 0.5d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi1) * Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0)) + Math.pow(Math.sin((phi1 * 0.5)), 2.0))), Math.sqrt((Math.pow(Math.cos((phi2 * -0.5)), 2.0) + (Math.cos(phi2) * ((Math.cos(lambda1) / 2.0) - 0.5))))));
}
def code(R, lambda1, lambda2, phi1, phi2): return R * (2.0 * math.atan2(math.sqrt(((math.cos(phi1) * math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0)) + math.pow(math.sin((phi1 * 0.5)), 2.0))), math.sqrt((math.pow(math.cos((phi2 * -0.5)), 2.0) + (math.cos(phi2) * ((math.cos(lambda1) / 2.0) - 0.5))))))
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi1) * (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0)) + (sin(Float64(phi1 * 0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) + Float64(cos(phi2) * Float64(Float64(cos(lambda1) / 2.0) - 0.5))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * (sin(((lambda1 - lambda2) * 0.5)) ^ 2.0)) + (sin((phi1 * 0.5)) ^ 2.0))), sqrt(((cos((phi2 * -0.5)) ^ 2.0) + (cos(phi2) * ((cos(lambda1) / 2.0) - 0.5)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi2], $MachinePrecision] * N[(N[(N[Cos[lambda1], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_1 \cdot {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2} + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}}}{\sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} + \cos \phi_2 \cdot \left(\frac{\cos \lambda_1}{2} - 0.5\right)}}\right)
\end{array}
Initial program 63.9%
Taylor expanded in phi1 around 0 49.7%
+-commutative49.7%
associate--r+49.7%
unpow249.7%
1-sub-sin49.8%
unpow249.8%
*-commutative49.8%
Simplified49.8%
Taylor expanded in phi2 around 0 33.4%
unpow233.4%
sin-mult33.4%
Applied egg-rr33.4%
div-sub33.4%
+-inverses33.4%
cos-033.4%
metadata-eval33.4%
count-233.4%
associate-*r*33.4%
metadata-eval33.4%
mul-1-neg33.4%
cos-neg33.4%
Simplified33.4%
Taylor expanded in lambda2 around 0 29.7%
cos-neg29.7%
Simplified29.7%
Final simplification29.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (* phi1 0.5)) 2.0)
(* (cos phi1) (pow (sin (* lambda1 0.5)) 2.0))))
(sqrt
(+
(pow (cos (* phi2 -0.5)) 2.0)
(* (cos phi2) (- (/ (cos (- lambda2 lambda1)) 2.0) 0.5))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2(sqrt((pow(sin((phi1 * 0.5)), 2.0) + (cos(phi1) * pow(sin((lambda1 * 0.5)), 2.0)))), sqrt((pow(cos((phi2 * -0.5)), 2.0) + (cos(phi2) * ((cos((lambda2 - lambda1)) / 2.0) - 0.5))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
code = r * (2.0d0 * atan2(sqrt(((sin((phi1 * 0.5d0)) ** 2.0d0) + (cos(phi1) * (sin((lambda1 * 0.5d0)) ** 2.0d0)))), sqrt(((cos((phi2 * (-0.5d0))) ** 2.0d0) + (cos(phi2) * ((cos((lambda2 - lambda1)) / 2.0d0) - 0.5d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin((phi1 * 0.5)), 2.0) + (Math.cos(phi1) * Math.pow(Math.sin((lambda1 * 0.5)), 2.0)))), Math.sqrt((Math.pow(Math.cos((phi2 * -0.5)), 2.0) + (Math.cos(phi2) * ((Math.cos((lambda2 - lambda1)) / 2.0) - 0.5))))));
}
def code(R, lambda1, lambda2, phi1, phi2): return R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin((phi1 * 0.5)), 2.0) + (math.cos(phi1) * math.pow(math.sin((lambda1 * 0.5)), 2.0)))), math.sqrt((math.pow(math.cos((phi2 * -0.5)), 2.0) + (math.cos(phi2) * ((math.cos((lambda2 - lambda1)) / 2.0) - 0.5))))))
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(phi1 * 0.5)) ^ 2.0) + Float64(cos(phi1) * (sin(Float64(lambda1 * 0.5)) ^ 2.0)))), sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) + Float64(cos(phi2) * Float64(Float64(cos(Float64(lambda2 - lambda1)) / 2.0) - 0.5))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) tmp = R * (2.0 * atan2(sqrt(((sin((phi1 * 0.5)) ^ 2.0) + (cos(phi1) * (sin((lambda1 * 0.5)) ^ 2.0)))), sqrt(((cos((phi2 * -0.5)) ^ 2.0) + (cos(phi2) * ((cos((lambda2 - lambda1)) / 2.0) - 0.5)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi2], $MachinePrecision] * N[(N[(N[Cos[N[(lambda2 - lambda1), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\phi_1 \cdot 0.5\right)}^{2} + \cos \phi_1 \cdot {\sin \left(\lambda_1 \cdot 0.5\right)}^{2}}}{\sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} + \cos \phi_2 \cdot \left(\frac{\cos \left(\lambda_2 - \lambda_1\right)}{2} - 0.5\right)}}\right)
\end{array}
Initial program 63.9%
Taylor expanded in phi1 around 0 49.7%
+-commutative49.7%
associate--r+49.7%
unpow249.7%
1-sub-sin49.8%
unpow249.8%
*-commutative49.8%
Simplified49.8%
Taylor expanded in phi2 around 0 33.4%
unpow233.4%
sin-mult33.4%
Applied egg-rr33.4%
div-sub33.4%
+-inverses33.4%
cos-033.4%
metadata-eval33.4%
count-233.4%
associate-*r*33.4%
metadata-eval33.4%
mul-1-neg33.4%
cos-neg33.4%
Simplified33.4%
Taylor expanded in lambda2 around 0 26.6%
Final simplification26.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* (- lambda1 lambda2) 0.5))))
(*
R
(*
2.0
(atan2
(+
t_0
(* 0.5 (/ (* (pow phi1 2.0) (+ 0.25 (* -0.5 (pow t_0 2.0)))) t_0)))
(sqrt
(+
(pow (cos (* phi2 -0.5)) 2.0)
(* (cos phi2) (- (/ (cos (- lambda2 lambda1)) 2.0) 0.5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) * 0.5));
return R * (2.0 * atan2((t_0 + (0.5 * ((pow(phi1, 2.0) * (0.25 + (-0.5 * pow(t_0, 2.0)))) / t_0))), sqrt((pow(cos((phi2 * -0.5)), 2.0) + (cos(phi2) * ((cos((lambda2 - lambda1)) / 2.0) - 0.5))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin(((lambda1 - lambda2) * 0.5d0))
code = r * (2.0d0 * atan2((t_0 + (0.5d0 * (((phi1 ** 2.0d0) * (0.25d0 + ((-0.5d0) * (t_0 ** 2.0d0)))) / t_0))), sqrt(((cos((phi2 * (-0.5d0))) ** 2.0d0) + (cos(phi2) * ((cos((lambda2 - lambda1)) / 2.0d0) - 0.5d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) * 0.5));
return R * (2.0 * Math.atan2((t_0 + (0.5 * ((Math.pow(phi1, 2.0) * (0.25 + (-0.5 * Math.pow(t_0, 2.0)))) / t_0))), Math.sqrt((Math.pow(Math.cos((phi2 * -0.5)), 2.0) + (Math.cos(phi2) * ((Math.cos((lambda2 - lambda1)) / 2.0) - 0.5))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) * 0.5)) return R * (2.0 * math.atan2((t_0 + (0.5 * ((math.pow(phi1, 2.0) * (0.25 + (-0.5 * math.pow(t_0, 2.0)))) / t_0))), math.sqrt((math.pow(math.cos((phi2 * -0.5)), 2.0) + (math.cos(phi2) * ((math.cos((lambda2 - lambda1)) / 2.0) - 0.5))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) return Float64(R * Float64(2.0 * atan(Float64(t_0 + Float64(0.5 * Float64(Float64((phi1 ^ 2.0) * Float64(0.25 + Float64(-0.5 * (t_0 ^ 2.0)))) / t_0))), sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) + Float64(cos(phi2) * Float64(Float64(cos(Float64(lambda2 - lambda1)) / 2.0) - 0.5))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) * 0.5)); tmp = R * (2.0 * atan2((t_0 + (0.5 * (((phi1 ^ 2.0) * (0.25 + (-0.5 * (t_0 ^ 2.0)))) / t_0))), sqrt(((cos((phi2 * -0.5)) ^ 2.0) + (cos(phi2) * ((cos((lambda2 - lambda1)) / 2.0) - 0.5)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[(t$95$0 + N[(0.5 * N[(N[(N[Power[phi1, 2.0], $MachinePrecision] * N[(0.25 + N[(-0.5 * N[Power[t$95$0, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi2], $MachinePrecision] * N[(N[(N[Cos[N[(lambda2 - lambda1), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_0 + 0.5 \cdot \frac{{\phi_1}^{2} \cdot \left(0.25 + -0.5 \cdot {t\_0}^{2}\right)}{t\_0}}{\sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} + \cos \phi_2 \cdot \left(\frac{\cos \left(\lambda_2 - \lambda_1\right)}{2} - 0.5\right)}}\right)
\end{array}
\end{array}
Initial program 63.9%
Taylor expanded in phi1 around 0 49.7%
+-commutative49.7%
associate--r+49.7%
unpow249.7%
1-sub-sin49.8%
unpow249.8%
*-commutative49.8%
Simplified49.8%
Taylor expanded in phi2 around 0 33.4%
unpow233.4%
sin-mult33.4%
Applied egg-rr33.4%
div-sub33.4%
+-inverses33.4%
cos-033.4%
metadata-eval33.4%
count-233.4%
associate-*r*33.4%
metadata-eval33.4%
mul-1-neg33.4%
cos-neg33.4%
Simplified33.4%
Taylor expanded in phi1 around 0 20.1%
Final simplification20.1%
herbie shell --seed 2024101
(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))))))))))