
(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 25 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 (sin (* phi1 0.5)))
(t_1 (cos (* phi1 0.5)))
(t_2 (sin (/ (- lambda1 lambda2) 2.0)))
(t_3 (* t_2 (* (* (cos phi1) (cos phi2)) t_2))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (fma (cos (* -0.5 phi2)) t_0 (* (sin (* -0.5 phi2)) t_1)) 2.0)
t_3))
(sqrt
(-
1.0
(+
t_3
(pow
(- (* (cos (* phi2 0.5)) t_0) (* t_1 (sin (* phi2 0.5))))
2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((phi1 * 0.5));
double t_1 = cos((phi1 * 0.5));
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double t_3 = t_2 * ((cos(phi1) * cos(phi2)) * t_2);
return R * (2.0 * atan2(sqrt((pow(fma(cos((-0.5 * phi2)), t_0, (sin((-0.5 * phi2)) * t_1)), 2.0) + t_3)), sqrt((1.0 - (t_3 + pow(((cos((phi2 * 0.5)) * t_0) - (t_1 * sin((phi2 * 0.5)))), 2.0))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi1 * 0.5)) t_1 = cos(Float64(phi1 * 0.5)) t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_3 = Float64(t_2 * Float64(Float64(cos(phi1) * cos(phi2)) * t_2)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((fma(cos(Float64(-0.5 * phi2)), t_0, Float64(sin(Float64(-0.5 * phi2)) * t_1)) ^ 2.0) + t_3)), sqrt(Float64(1.0 - Float64(t_3 + (Float64(Float64(cos(Float64(phi2 * 0.5)) * t_0) - Float64(t_1 * sin(Float64(phi2 * 0.5)))) ^ 2.0))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(phi1 * 0.5), $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 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$0 + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$3), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$3 + N[Power[N[(N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision] - N[(t$95$1 * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_1 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_3 := t\_2 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_2\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(\cos \left(-0.5 \cdot \phi_2\right), t\_0, \sin \left(-0.5 \cdot \phi_2\right) \cdot t\_1\right)\right)}^{2} + t\_3}}{\sqrt{1 - \left(t\_3 + {\left(\cos \left(\phi_2 \cdot 0.5\right) \cdot t\_0 - t\_1 \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 62.0%
div-sub62.0%
sin-diff62.8%
div-inv62.8%
metadata-eval62.8%
div-inv62.8%
metadata-eval62.8%
div-inv62.8%
metadata-eval62.8%
div-inv62.8%
metadata-eval62.8%
Applied egg-rr62.8%
div-sub62.0%
sin-diff62.8%
div-inv62.8%
metadata-eval62.8%
div-inv62.8%
metadata-eval62.8%
div-inv62.8%
metadata-eval62.8%
div-inv62.8%
metadata-eval62.8%
Applied egg-rr75.8%
*-commutative75.8%
*-commutative75.8%
fmm-def75.8%
cos-neg75.8%
distribute-rgt-neg-in75.8%
metadata-eval75.8%
*-commutative75.8%
*-commutative75.8%
*-commutative75.8%
*-commutative75.8%
distribute-lft-neg-in75.8%
sin-neg75.8%
distribute-rgt-neg-in75.8%
metadata-eval75.8%
*-commutative75.8%
*-commutative75.8%
Simplified75.8%
Final simplification75.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (/ phi1 2.0)))
(t_2 (cos (/ phi2 2.0)))
(t_3 (sin (/ phi2 2.0)))
(t_4 (sin (/ (- lambda1 lambda2) 2.0)))
(t_5 (* t_4 (* t_0 t_4)))
(t_6 (+ t_5 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(t_7 (cos (/ phi1 2.0))))
(if (<= t_6 1.0)
(*
R
(*
2.0
(atan2
(sqrt
(+
t_5
(pow
(-
(* (cos (* phi2 0.5)) (sin (* phi1 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0)))
(sqrt (- 1.0 t_6)))))
(*
(atan2
(hypot
(fma t_1 t_2 (* t_3 (- t_7)))
(* (sin (* 0.5 (- lambda1 lambda2))) (sqrt t_0)))
(sqrt
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (+ 0.5 (* -0.5 (cos (- lambda1 lambda2)))))
(pow (- (* t_1 t_2) (* t_3 t_7)) 2.0)))))
(* R 2.0)))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = sin((phi1 / 2.0));
double t_2 = cos((phi2 / 2.0));
double t_3 = sin((phi2 / 2.0));
double t_4 = sin(((lambda1 - lambda2) / 2.0));
double t_5 = t_4 * (t_0 * t_4);
double t_6 = t_5 + pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double t_7 = cos((phi1 / 2.0));
double tmp;
if (t_6 <= 1.0) {
tmp = R * (2.0 * atan2(sqrt((t_5 + pow(((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0))), sqrt((1.0 - t_6))));
} else {
tmp = atan2(hypot(fma(t_1, t_2, (t_3 * -t_7)), (sin((0.5 * (lambda1 - lambda2))) * sqrt(t_0))), sqrt((1.0 - fma(cos(phi1), (cos(phi2) * (0.5 + (-0.5 * cos((lambda1 - lambda2))))), pow(((t_1 * t_2) - (t_3 * t_7)), 2.0))))) * (R * 2.0);
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(phi1 / 2.0)) t_2 = cos(Float64(phi2 / 2.0)) t_3 = sin(Float64(phi2 / 2.0)) t_4 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_5 = Float64(t_4 * Float64(t_0 * t_4)) t_6 = Float64(t_5 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0)) t_7 = cos(Float64(phi1 / 2.0)) tmp = 0.0 if (t_6 <= 1.0) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(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))), sqrt(Float64(1.0 - t_6))))); else tmp = Float64(atan(hypot(fma(t_1, t_2, Float64(t_3 * Float64(-t_7))), Float64(sin(Float64(0.5 * Float64(lambda1 - lambda2))) * sqrt(t_0))), sqrt(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2))))), (Float64(Float64(t_1 * t_2) - Float64(t_3 * t_7)) ^ 2.0))))) * Float64(R * 2.0)); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$5 = N[(t$95$4 * N[(t$95$0 * t$95$4), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$6 = N[(t$95$5 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$7 = N[Cos[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[t$95$6, 1.0], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(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]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$6), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[ArcTan[N[Sqrt[N[(t$95$1 * t$95$2 + N[(t$95$3 * (-t$95$7)), $MachinePrecision]), $MachinePrecision] ^ 2 + N[(N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[Sqrt[t$95$0], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[(N[(t$95$1 * t$95$2), $MachinePrecision] - N[(t$95$3 * t$95$7), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(R * 2.0), $MachinePrecision]), $MachinePrecision]]]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \sin \left(\frac{\phi_1}{2}\right)\\
t_2 := \cos \left(\frac{\phi_2}{2}\right)\\
t_3 := \sin \left(\frac{\phi_2}{2}\right)\\
t_4 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_5 := t\_4 \cdot \left(t\_0 \cdot t\_4\right)\\
t_6 := t\_5 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
t_7 := \cos \left(\frac{\phi_1}{2}\right)\\
\mathbf{if}\;t\_6 \leq 1:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{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}}}{\sqrt{1 - t\_6}}\right)\\
\mathbf{else}:\\
\;\;\;\;\tan^{-1}_* \frac{\mathsf{hypot}\left(\mathsf{fma}\left(t\_1, t\_2, t\_3 \cdot \left(-t\_7\right)\right), \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right) \cdot \sqrt{t\_0}\right)}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \left(0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right), {\left(t\_1 \cdot t\_2 - t\_3 \cdot t\_7\right)}^{2}\right)}} \cdot \left(R \cdot 2\right)\\
\end{array}
\end{array}
if (+.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))))) < 1Initial program 63.5%
div-sub63.5%
sin-diff63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
Applied egg-rr64.3%
if 1 < (+.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 0.0%
associate-*r*0.0%
*-commutative0.0%
Simplified0.0%
Applied egg-rr0.0%
*-lft-identity0.0%
*-commutative0.0%
*-commutative0.0%
*-commutative0.0%
Simplified0.0%
metadata-eval0.0%
associate-/r/0.0%
clear-num0.0%
div-sub0.0%
sin-diff0.0%
Applied egg-rr0.0%
fmm-def0.0%
*-commutative0.0%
distribute-rgt-neg-in0.0%
Simplified0.0%
metadata-eval0.0%
associate-/r/0.0%
clear-num0.0%
div-sub0.0%
sin-diff0.0%
Applied egg-rr99.0%
Final simplification65.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* phi1 0.5)))
(t_1 (cos (* phi1 0.5)))
(t_2
(pow (- (* (cos (* phi2 0.5)) t_0) (* t_1 (sin (* phi2 0.5)))) 2.0))
(t_3 (sin (/ (- lambda1 lambda2) 2.0)))
(t_4 (+ (* t_3 (* (* (cos phi1) (cos phi2)) t_3)) t_2)))
(if (or (<= lambda2 -0.0115) (not (<= lambda2 7.4e-6)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (cos phi1) (* (cos phi2) (pow (sin (* -0.5 lambda2)) 2.0)))
(pow
(+ (* (cos (* -0.5 phi2)) t_0) (* (sin (* -0.5 phi2)) t_1))
2.0)))
(sqrt (- 1.0 t_4)))))
(*
R
(*
2.0
(atan2
(sqrt t_4)
(sqrt
(-
1.0
(+
t_2
(*
(cos phi1)
(* (cos phi2) (pow (sin (* 0.5 lambda1)) 2.0))))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((phi1 * 0.5));
double t_1 = cos((phi1 * 0.5));
double t_2 = pow(((cos((phi2 * 0.5)) * t_0) - (t_1 * sin((phi2 * 0.5)))), 2.0);
double t_3 = sin(((lambda1 - lambda2) / 2.0));
double t_4 = (t_3 * ((cos(phi1) * cos(phi2)) * t_3)) + t_2;
double tmp;
if ((lambda2 <= -0.0115) || !(lambda2 <= 7.4e-6)) {
tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * (cos(phi2) * pow(sin((-0.5 * lambda2)), 2.0))) + pow(((cos((-0.5 * phi2)) * t_0) + (sin((-0.5 * phi2)) * t_1)), 2.0))), sqrt((1.0 - t_4))));
} else {
tmp = R * (2.0 * atan2(sqrt(t_4), sqrt((1.0 - (t_2 + (cos(phi1) * (cos(phi2) * pow(sin((0.5 * lambda1)), 2.0))))))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: t_3
real(8) :: t_4
real(8) :: tmp
t_0 = sin((phi1 * 0.5d0))
t_1 = cos((phi1 * 0.5d0))
t_2 = ((cos((phi2 * 0.5d0)) * t_0) - (t_1 * sin((phi2 * 0.5d0)))) ** 2.0d0
t_3 = sin(((lambda1 - lambda2) / 2.0d0))
t_4 = (t_3 * ((cos(phi1) * cos(phi2)) * t_3)) + t_2
if ((lambda2 <= (-0.0115d0)) .or. (.not. (lambda2 <= 7.4d-6))) then
tmp = r * (2.0d0 * atan2(sqrt(((cos(phi1) * (cos(phi2) * (sin(((-0.5d0) * lambda2)) ** 2.0d0))) + (((cos(((-0.5d0) * phi2)) * t_0) + (sin(((-0.5d0) * phi2)) * t_1)) ** 2.0d0))), sqrt((1.0d0 - t_4))))
else
tmp = r * (2.0d0 * atan2(sqrt(t_4), sqrt((1.0d0 - (t_2 + (cos(phi1) * (cos(phi2) * (sin((0.5d0 * lambda1)) ** 2.0d0))))))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin((phi1 * 0.5));
double t_1 = Math.cos((phi1 * 0.5));
double t_2 = Math.pow(((Math.cos((phi2 * 0.5)) * t_0) - (t_1 * Math.sin((phi2 * 0.5)))), 2.0);
double t_3 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_4 = (t_3 * ((Math.cos(phi1) * Math.cos(phi2)) * t_3)) + t_2;
double tmp;
if ((lambda2 <= -0.0115) || !(lambda2 <= 7.4e-6)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((-0.5 * lambda2)), 2.0))) + Math.pow(((Math.cos((-0.5 * phi2)) * t_0) + (Math.sin((-0.5 * phi2)) * t_1)), 2.0))), Math.sqrt((1.0 - t_4))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt(t_4), Math.sqrt((1.0 - (t_2 + (Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((0.5 * lambda1)), 2.0))))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin((phi1 * 0.5)) t_1 = math.cos((phi1 * 0.5)) t_2 = math.pow(((math.cos((phi2 * 0.5)) * t_0) - (t_1 * math.sin((phi2 * 0.5)))), 2.0) t_3 = math.sin(((lambda1 - lambda2) / 2.0)) t_4 = (t_3 * ((math.cos(phi1) * math.cos(phi2)) * t_3)) + t_2 tmp = 0 if (lambda2 <= -0.0115) or not (lambda2 <= 7.4e-6): tmp = R * (2.0 * math.atan2(math.sqrt(((math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((-0.5 * lambda2)), 2.0))) + math.pow(((math.cos((-0.5 * phi2)) * t_0) + (math.sin((-0.5 * phi2)) * t_1)), 2.0))), math.sqrt((1.0 - t_4)))) else: tmp = R * (2.0 * math.atan2(math.sqrt(t_4), math.sqrt((1.0 - (t_2 + (math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((0.5 * lambda1)), 2.0)))))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi1 * 0.5)) t_1 = cos(Float64(phi1 * 0.5)) t_2 = Float64(Float64(cos(Float64(phi2 * 0.5)) * t_0) - Float64(t_1 * sin(Float64(phi2 * 0.5)))) ^ 2.0 t_3 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_4 = Float64(Float64(t_3 * Float64(Float64(cos(phi1) * cos(phi2)) * t_3)) + t_2) tmp = 0.0 if ((lambda2 <= -0.0115) || !(lambda2 <= 7.4e-6)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(-0.5 * lambda2)) ^ 2.0))) + (Float64(Float64(cos(Float64(-0.5 * phi2)) * t_0) + Float64(sin(Float64(-0.5 * phi2)) * t_1)) ^ 2.0))), sqrt(Float64(1.0 - t_4))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(t_4), sqrt(Float64(1.0 - Float64(t_2 + Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(0.5 * lambda1)) ^ 2.0))))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin((phi1 * 0.5)); t_1 = cos((phi1 * 0.5)); t_2 = ((cos((phi2 * 0.5)) * t_0) - (t_1 * sin((phi2 * 0.5)))) ^ 2.0; t_3 = sin(((lambda1 - lambda2) / 2.0)); t_4 = (t_3 * ((cos(phi1) * cos(phi2)) * t_3)) + t_2; tmp = 0.0; if ((lambda2 <= -0.0115) || ~((lambda2 <= 7.4e-6))) tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * (cos(phi2) * (sin((-0.5 * lambda2)) ^ 2.0))) + (((cos((-0.5 * phi2)) * t_0) + (sin((-0.5 * phi2)) * t_1)) ^ 2.0))), sqrt((1.0 - t_4)))); else tmp = R * (2.0 * atan2(sqrt(t_4), sqrt((1.0 - (t_2 + (cos(phi1) * (cos(phi2) * (sin((0.5 * lambda1)) ^ 2.0)))))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[(N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision] - N[(t$95$1 * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[(N[(t$95$3 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$3), $MachinePrecision]), $MachinePrecision] + t$95$2), $MachinePrecision]}, If[Or[LessEqual[lambda2, -0.0115], N[Not[LessEqual[lambda2, 7.4e-6]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[(N[(N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision] + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$4), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$4], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$2 + N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_1 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_2 := {\left(\cos \left(\phi_2 \cdot 0.5\right) \cdot t\_0 - t\_1 \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\\
t_3 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_4 := t\_3 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_3\right) + t\_2\\
\mathbf{if}\;\lambda_2 \leq -0.0115 \lor \neg \left(\lambda_2 \leq 7.4 \cdot 10^{-6}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(-0.5 \cdot \lambda_2\right)}^{2}\right) + {\left(\cos \left(-0.5 \cdot \phi_2\right) \cdot t\_0 + \sin \left(-0.5 \cdot \phi_2\right) \cdot t\_1\right)}^{2}}}{\sqrt{1 - t\_4}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_4}}{\sqrt{1 - \left(t\_2 + \cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(0.5 \cdot \lambda_1\right)}^{2}\right)\right)}}\right)\\
\end{array}
\end{array}
if lambda2 < -0.0115 or 7.4000000000000003e-6 < lambda2 Initial program 46.4%
div-sub46.4%
sin-diff47.1%
div-inv47.1%
metadata-eval47.1%
div-inv47.1%
metadata-eval47.1%
div-inv47.1%
metadata-eval47.1%
div-inv47.1%
metadata-eval47.1%
Applied egg-rr47.1%
div-sub46.4%
sin-diff47.1%
div-inv47.1%
metadata-eval47.1%
div-inv47.1%
metadata-eval47.1%
div-inv47.1%
metadata-eval47.1%
div-inv47.1%
metadata-eval47.1%
Applied egg-rr57.9%
*-commutative57.9%
*-commutative57.9%
fmm-def57.9%
cos-neg57.9%
distribute-rgt-neg-in57.9%
metadata-eval57.9%
*-commutative57.9%
*-commutative57.9%
*-commutative57.9%
*-commutative57.9%
distribute-lft-neg-in57.9%
sin-neg57.9%
distribute-rgt-neg-in57.9%
metadata-eval57.9%
*-commutative57.9%
*-commutative57.9%
Simplified57.9%
Taylor expanded in lambda1 around 0 57.0%
if -0.0115 < lambda2 < 7.4000000000000003e-6Initial program 80.7%
div-sub80.7%
sin-diff81.8%
div-inv81.8%
metadata-eval81.8%
div-inv81.8%
metadata-eval81.8%
div-inv81.8%
metadata-eval81.8%
div-inv81.8%
metadata-eval81.8%
Applied egg-rr81.8%
Taylor expanded in lambda2 around 0 81.8%
div-sub80.7%
sin-diff81.8%
div-inv81.8%
metadata-eval81.8%
div-inv81.8%
metadata-eval81.8%
div-inv81.8%
metadata-eval81.8%
div-inv81.8%
metadata-eval81.8%
Applied egg-rr97.4%
Final simplification75.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (* phi1 0.5)))
(t_1 (sin (* phi1 0.5)))
(t_2
(pow (+ (* (cos (* -0.5 phi2)) t_1) (* (sin (* -0.5 phi2)) t_0)) 2.0))
(t_3 (sin (/ (- lambda1 lambda2) 2.0)))
(t_4
(sqrt
(-
1.0
(+
(* t_3 (* (* (cos phi1) (cos phi2)) t_3))
(pow
(- (* (cos (* phi2 0.5)) t_1) (* t_0 (sin (* phi2 0.5))))
2.0))))))
(if (or (<= lambda1 -2.25e-7) (not (<= lambda1 6.8e-39)))
(*
R
(*
2.0
(atan2
(sqrt
(+ t_2 (* (cos phi1) (* (cos phi2) (pow (sin (* 0.5 lambda1)) 2.0)))))
t_4)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (cos phi1) (* (cos phi2) (pow (sin (* -0.5 lambda2)) 2.0)))
t_2))
t_4))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((phi1 * 0.5));
double t_1 = sin((phi1 * 0.5));
double t_2 = pow(((cos((-0.5 * phi2)) * t_1) + (sin((-0.5 * phi2)) * t_0)), 2.0);
double t_3 = sin(((lambda1 - lambda2) / 2.0));
double t_4 = sqrt((1.0 - ((t_3 * ((cos(phi1) * cos(phi2)) * t_3)) + pow(((cos((phi2 * 0.5)) * t_1) - (t_0 * sin((phi2 * 0.5)))), 2.0))));
double tmp;
if ((lambda1 <= -2.25e-7) || !(lambda1 <= 6.8e-39)) {
tmp = R * (2.0 * atan2(sqrt((t_2 + (cos(phi1) * (cos(phi2) * pow(sin((0.5 * lambda1)), 2.0))))), t_4));
} else {
tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * (cos(phi2) * pow(sin((-0.5 * lambda2)), 2.0))) + t_2)), t_4));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: t_3
real(8) :: t_4
real(8) :: tmp
t_0 = cos((phi1 * 0.5d0))
t_1 = sin((phi1 * 0.5d0))
t_2 = ((cos(((-0.5d0) * phi2)) * t_1) + (sin(((-0.5d0) * phi2)) * t_0)) ** 2.0d0
t_3 = sin(((lambda1 - lambda2) / 2.0d0))
t_4 = sqrt((1.0d0 - ((t_3 * ((cos(phi1) * cos(phi2)) * t_3)) + (((cos((phi2 * 0.5d0)) * t_1) - (t_0 * sin((phi2 * 0.5d0)))) ** 2.0d0))))
if ((lambda1 <= (-2.25d-7)) .or. (.not. (lambda1 <= 6.8d-39))) then
tmp = r * (2.0d0 * atan2(sqrt((t_2 + (cos(phi1) * (cos(phi2) * (sin((0.5d0 * lambda1)) ** 2.0d0))))), t_4))
else
tmp = r * (2.0d0 * atan2(sqrt(((cos(phi1) * (cos(phi2) * (sin(((-0.5d0) * lambda2)) ** 2.0d0))) + t_2)), t_4))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.cos((phi1 * 0.5));
double t_1 = Math.sin((phi1 * 0.5));
double t_2 = Math.pow(((Math.cos((-0.5 * phi2)) * t_1) + (Math.sin((-0.5 * phi2)) * t_0)), 2.0);
double t_3 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_4 = Math.sqrt((1.0 - ((t_3 * ((Math.cos(phi1) * Math.cos(phi2)) * t_3)) + Math.pow(((Math.cos((phi2 * 0.5)) * t_1) - (t_0 * Math.sin((phi2 * 0.5)))), 2.0))));
double tmp;
if ((lambda1 <= -2.25e-7) || !(lambda1 <= 6.8e-39)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_2 + (Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((0.5 * lambda1)), 2.0))))), t_4));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((-0.5 * lambda2)), 2.0))) + t_2)), t_4));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos((phi1 * 0.5)) t_1 = math.sin((phi1 * 0.5)) t_2 = math.pow(((math.cos((-0.5 * phi2)) * t_1) + (math.sin((-0.5 * phi2)) * t_0)), 2.0) t_3 = math.sin(((lambda1 - lambda2) / 2.0)) t_4 = math.sqrt((1.0 - ((t_3 * ((math.cos(phi1) * math.cos(phi2)) * t_3)) + math.pow(((math.cos((phi2 * 0.5)) * t_1) - (t_0 * math.sin((phi2 * 0.5)))), 2.0)))) tmp = 0 if (lambda1 <= -2.25e-7) or not (lambda1 <= 6.8e-39): tmp = R * (2.0 * math.atan2(math.sqrt((t_2 + (math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((0.5 * lambda1)), 2.0))))), t_4)) else: tmp = R * (2.0 * math.atan2(math.sqrt(((math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((-0.5 * lambda2)), 2.0))) + t_2)), t_4)) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(phi1 * 0.5)) t_1 = sin(Float64(phi1 * 0.5)) t_2 = Float64(Float64(cos(Float64(-0.5 * phi2)) * t_1) + Float64(sin(Float64(-0.5 * phi2)) * t_0)) ^ 2.0 t_3 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_4 = sqrt(Float64(1.0 - Float64(Float64(t_3 * Float64(Float64(cos(phi1) * cos(phi2)) * t_3)) + (Float64(Float64(cos(Float64(phi2 * 0.5)) * t_1) - Float64(t_0 * sin(Float64(phi2 * 0.5)))) ^ 2.0)))) tmp = 0.0 if ((lambda1 <= -2.25e-7) || !(lambda1 <= 6.8e-39)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_2 + Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(0.5 * lambda1)) ^ 2.0))))), t_4))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(-0.5 * lambda2)) ^ 2.0))) + t_2)), t_4))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos((phi1 * 0.5)); t_1 = sin((phi1 * 0.5)); t_2 = ((cos((-0.5 * phi2)) * t_1) + (sin((-0.5 * phi2)) * t_0)) ^ 2.0; t_3 = sin(((lambda1 - lambda2) / 2.0)); t_4 = sqrt((1.0 - ((t_3 * ((cos(phi1) * cos(phi2)) * t_3)) + (((cos((phi2 * 0.5)) * t_1) - (t_0 * sin((phi2 * 0.5)))) ^ 2.0)))); tmp = 0.0; if ((lambda1 <= -2.25e-7) || ~((lambda1 <= 6.8e-39))) tmp = R * (2.0 * atan2(sqrt((t_2 + (cos(phi1) * (cos(phi2) * (sin((0.5 * lambda1)) ^ 2.0))))), t_4)); else tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * (cos(phi2) * (sin((-0.5 * lambda2)) ^ 2.0))) + t_2)), t_4)); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[(N[(N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$1), $MachinePrecision] + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[Sqrt[N[(1.0 - N[(N[(t$95$3 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$3), $MachinePrecision]), $MachinePrecision] + N[Power[N[(N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * t$95$1), $MachinePrecision] - N[(t$95$0 * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[lambda1, -2.25e-7], N[Not[LessEqual[lambda1, 6.8e-39]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$2 + N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$4], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$2), $MachinePrecision]], $MachinePrecision] / t$95$4], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_1 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_2 := {\left(\cos \left(-0.5 \cdot \phi_2\right) \cdot t\_1 + \sin \left(-0.5 \cdot \phi_2\right) \cdot t\_0\right)}^{2}\\
t_3 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_4 := \sqrt{1 - \left(t\_3 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_3\right) + {\left(\cos \left(\phi_2 \cdot 0.5\right) \cdot t\_1 - t\_0 \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\right)}\\
\mathbf{if}\;\lambda_1 \leq -2.25 \cdot 10^{-7} \lor \neg \left(\lambda_1 \leq 6.8 \cdot 10^{-39}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 + \cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(0.5 \cdot \lambda_1\right)}^{2}\right)}}{t\_4}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(-0.5 \cdot \lambda_2\right)}^{2}\right) + t\_2}}{t\_4}\right)\\
\end{array}
\end{array}
if lambda1 < -2.2499999999999999e-7 or 6.7999999999999998e-39 < lambda1 Initial program 47.3%
div-sub47.3%
sin-diff48.0%
div-inv48.0%
metadata-eval48.0%
div-inv48.0%
metadata-eval48.0%
div-inv48.0%
metadata-eval48.0%
div-inv48.0%
metadata-eval48.0%
Applied egg-rr48.0%
div-sub47.3%
sin-diff48.0%
div-inv48.0%
metadata-eval48.0%
div-inv48.0%
metadata-eval48.0%
div-inv48.0%
metadata-eval48.0%
div-inv48.0%
metadata-eval48.0%
Applied egg-rr56.5%
*-commutative56.5%
*-commutative56.5%
fmm-def56.5%
cos-neg56.5%
distribute-rgt-neg-in56.5%
metadata-eval56.5%
*-commutative56.5%
*-commutative56.5%
*-commutative56.5%
*-commutative56.5%
distribute-lft-neg-in56.5%
sin-neg56.5%
distribute-rgt-neg-in56.5%
metadata-eval56.5%
*-commutative56.5%
*-commutative56.5%
Simplified56.5%
Taylor expanded in lambda2 around 0 55.0%
if -2.2499999999999999e-7 < lambda1 < 6.7999999999999998e-39Initial program 79.2%
div-sub79.2%
sin-diff80.1%
div-inv80.1%
metadata-eval80.1%
div-inv80.1%
metadata-eval80.1%
div-inv80.1%
metadata-eval80.1%
div-inv80.1%
metadata-eval80.1%
Applied egg-rr80.1%
div-sub79.2%
sin-diff80.1%
div-inv80.1%
metadata-eval80.1%
div-inv80.1%
metadata-eval80.1%
div-inv80.1%
metadata-eval80.1%
div-inv80.1%
metadata-eval80.1%
Applied egg-rr98.3%
*-commutative98.3%
*-commutative98.3%
fmm-def98.4%
cos-neg98.4%
distribute-rgt-neg-in98.4%
metadata-eval98.4%
*-commutative98.4%
*-commutative98.4%
*-commutative98.4%
*-commutative98.4%
distribute-lft-neg-in98.4%
sin-neg98.4%
distribute-rgt-neg-in98.4%
metadata-eval98.4%
*-commutative98.4%
*-commutative98.4%
Simplified98.4%
Taylor expanded in lambda1 around 0 98.4%
Final simplification75.0%
(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)))
(t_2 (sin (* phi1 0.5)))
(t_3 (cos (* phi1 0.5)))
(t_4
(sqrt
(-
1.0
(+
t_1
(pow
(- (* (cos (* phi2 0.5)) t_2) (* t_3 (sin (* phi2 0.5))))
2.0))))))
(if (<= lambda1 -4e-12)
(*
R
(* 2.0 (atan2 (sqrt (+ t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))) t_4)))
(if (<= lambda1 6.4e-18)
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (cos phi1) (* (cos phi2) (pow (sin (* -0.5 lambda2)) 2.0)))
(pow
(+ (* (cos (* -0.5 phi2)) t_2) (* (sin (* -0.5 phi2)) t_3))
2.0)))
t_4)))
(*
R
(*
2.0
(atan2 (sqrt (+ t_1 (- 0.5 (/ (cos (- phi1 phi2)) 2.0)))) 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 = t_0 * ((cos(phi1) * cos(phi2)) * t_0);
double t_2 = sin((phi1 * 0.5));
double t_3 = cos((phi1 * 0.5));
double t_4 = sqrt((1.0 - (t_1 + pow(((cos((phi2 * 0.5)) * t_2) - (t_3 * sin((phi2 * 0.5)))), 2.0))));
double tmp;
if (lambda1 <= -4e-12) {
tmp = R * (2.0 * atan2(sqrt((t_1 + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), t_4));
} else if (lambda1 <= 6.4e-18) {
tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * (cos(phi2) * pow(sin((-0.5 * lambda2)), 2.0))) + pow(((cos((-0.5 * phi2)) * t_2) + (sin((-0.5 * phi2)) * t_3)), 2.0))), t_4));
} else {
tmp = R * (2.0 * atan2(sqrt((t_1 + (0.5 - (cos((phi1 - phi2)) / 2.0)))), t_4));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: t_3
real(8) :: t_4
real(8) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = t_0 * ((cos(phi1) * cos(phi2)) * t_0)
t_2 = sin((phi1 * 0.5d0))
t_3 = cos((phi1 * 0.5d0))
t_4 = sqrt((1.0d0 - (t_1 + (((cos((phi2 * 0.5d0)) * t_2) - (t_3 * sin((phi2 * 0.5d0)))) ** 2.0d0))))
if (lambda1 <= (-4d-12)) then
tmp = r * (2.0d0 * atan2(sqrt((t_1 + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), t_4))
else if (lambda1 <= 6.4d-18) then
tmp = r * (2.0d0 * atan2(sqrt(((cos(phi1) * (cos(phi2) * (sin(((-0.5d0) * lambda2)) ** 2.0d0))) + (((cos(((-0.5d0) * phi2)) * t_2) + (sin(((-0.5d0) * phi2)) * t_3)) ** 2.0d0))), t_4))
else
tmp = r * (2.0d0 * atan2(sqrt((t_1 + (0.5d0 - (cos((phi1 - phi2)) / 2.0d0)))), t_4))
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 = t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0);
double t_2 = Math.sin((phi1 * 0.5));
double t_3 = Math.cos((phi1 * 0.5));
double t_4 = Math.sqrt((1.0 - (t_1 + Math.pow(((Math.cos((phi2 * 0.5)) * t_2) - (t_3 * Math.sin((phi2 * 0.5)))), 2.0))));
double tmp;
if (lambda1 <= -4e-12) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_1 + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), t_4));
} else if (lambda1 <= 6.4e-18) {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((-0.5 * lambda2)), 2.0))) + Math.pow(((Math.cos((-0.5 * phi2)) * t_2) + (Math.sin((-0.5 * phi2)) * t_3)), 2.0))), t_4));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_1 + (0.5 - (Math.cos((phi1 - phi2)) / 2.0)))), t_4));
}
return tmp;
}
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) t_2 = math.sin((phi1 * 0.5)) t_3 = math.cos((phi1 * 0.5)) t_4 = math.sqrt((1.0 - (t_1 + math.pow(((math.cos((phi2 * 0.5)) * t_2) - (t_3 * math.sin((phi2 * 0.5)))), 2.0)))) tmp = 0 if lambda1 <= -4e-12: tmp = R * (2.0 * math.atan2(math.sqrt((t_1 + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), t_4)) elif lambda1 <= 6.4e-18: tmp = R * (2.0 * math.atan2(math.sqrt(((math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((-0.5 * lambda2)), 2.0))) + math.pow(((math.cos((-0.5 * phi2)) * t_2) + (math.sin((-0.5 * phi2)) * t_3)), 2.0))), t_4)) else: tmp = R * (2.0 * math.atan2(math.sqrt((t_1 + (0.5 - (math.cos((phi1 - phi2)) / 2.0)))), t_4)) return tmp
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)) t_2 = sin(Float64(phi1 * 0.5)) t_3 = cos(Float64(phi1 * 0.5)) t_4 = sqrt(Float64(1.0 - Float64(t_1 + (Float64(Float64(cos(Float64(phi2 * 0.5)) * t_2) - Float64(t_3 * sin(Float64(phi2 * 0.5)))) ^ 2.0)))) tmp = 0.0 if (lambda1 <= -4e-12) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), t_4))); elseif (lambda1 <= 6.4e-18) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(-0.5 * lambda2)) ^ 2.0))) + (Float64(Float64(cos(Float64(-0.5 * phi2)) * t_2) + Float64(sin(Float64(-0.5 * phi2)) * t_3)) ^ 2.0))), t_4))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + Float64(0.5 - Float64(cos(Float64(phi1 - phi2)) / 2.0)))), t_4))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = t_0 * ((cos(phi1) * cos(phi2)) * t_0); t_2 = sin((phi1 * 0.5)); t_3 = cos((phi1 * 0.5)); t_4 = sqrt((1.0 - (t_1 + (((cos((phi2 * 0.5)) * t_2) - (t_3 * sin((phi2 * 0.5)))) ^ 2.0)))); tmp = 0.0; if (lambda1 <= -4e-12) tmp = R * (2.0 * atan2(sqrt((t_1 + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), t_4)); elseif (lambda1 <= 6.4e-18) tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * (cos(phi2) * (sin((-0.5 * lambda2)) ^ 2.0))) + (((cos((-0.5 * phi2)) * t_2) + (sin((-0.5 * phi2)) * t_3)) ^ 2.0))), t_4)); else tmp = R * (2.0 * atan2(sqrt((t_1 + (0.5 - (cos((phi1 - phi2)) / 2.0)))), t_4)); 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[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[Sqrt[N[(1.0 - N[(t$95$1 + N[Power[N[(N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * t$95$2), $MachinePrecision] - N[(t$95$3 * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[lambda1, -4e-12], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$4], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[lambda1, 6.4e-18], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[(N[(N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$2), $MachinePrecision] + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$3), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$4], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[(0.5 - N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$4], $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)\\
t_2 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_3 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_4 := \sqrt{1 - \left(t\_1 + {\left(\cos \left(\phi_2 \cdot 0.5\right) \cdot t\_2 - t\_3 \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\right)}\\
\mathbf{if}\;\lambda_1 \leq -4 \cdot 10^{-12}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{t\_4}\right)\\
\mathbf{elif}\;\lambda_1 \leq 6.4 \cdot 10^{-18}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(-0.5 \cdot \lambda_2\right)}^{2}\right) + {\left(\cos \left(-0.5 \cdot \phi_2\right) \cdot t\_2 + \sin \left(-0.5 \cdot \phi_2\right) \cdot t\_3\right)}^{2}}}{t\_4}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + \left(0.5 - \frac{\cos \left(\phi_1 - \phi_2\right)}{2}\right)}}{t\_4}\right)\\
\end{array}
\end{array}
if lambda1 < -3.99999999999999992e-12Initial program 40.8%
div-sub40.8%
sin-diff41.9%
div-inv41.9%
metadata-eval41.9%
div-inv41.9%
metadata-eval41.9%
div-inv41.9%
metadata-eval41.9%
div-inv41.9%
metadata-eval41.9%
Applied egg-rr41.9%
if -3.99999999999999992e-12 < lambda1 < 6.3999999999999998e-18Initial program 78.4%
div-sub78.4%
sin-diff79.4%
div-inv79.4%
metadata-eval79.4%
div-inv79.4%
metadata-eval79.4%
div-inv79.4%
metadata-eval79.4%
div-inv79.4%
metadata-eval79.4%
Applied egg-rr79.4%
div-sub78.4%
sin-diff79.4%
div-inv79.4%
metadata-eval79.4%
div-inv79.4%
metadata-eval79.4%
div-inv79.4%
metadata-eval79.4%
div-inv79.4%
metadata-eval79.4%
Applied egg-rr98.4%
*-commutative98.4%
*-commutative98.4%
fmm-def98.4%
cos-neg98.4%
distribute-rgt-neg-in98.4%
metadata-eval98.4%
*-commutative98.4%
*-commutative98.4%
*-commutative98.4%
*-commutative98.4%
distribute-lft-neg-in98.4%
sin-neg98.4%
distribute-rgt-neg-in98.4%
metadata-eval98.4%
*-commutative98.4%
*-commutative98.4%
Simplified98.4%
Taylor expanded in lambda1 around 0 97.9%
if 6.3999999999999998e-18 < lambda1 Initial program 52.9%
div-sub52.9%
sin-diff53.3%
div-inv53.3%
metadata-eval53.3%
div-inv53.3%
metadata-eval53.3%
div-inv53.3%
metadata-eval53.3%
div-inv53.3%
metadata-eval53.3%
Applied egg-rr53.3%
unpow253.3%
sin-mult53.3%
div-inv53.3%
metadata-eval53.3%
div-inv53.3%
metadata-eval53.3%
div-inv53.3%
metadata-eval53.3%
div-inv53.3%
metadata-eval53.3%
Applied egg-rr53.3%
div-sub53.3%
+-inverses53.3%
cos-053.3%
metadata-eval53.3%
distribute-lft-out53.3%
metadata-eval53.3%
*-rgt-identity53.3%
Simplified53.3%
Final simplification71.6%
(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))
(pow
(-
(* (cos (* phi2 0.5)) (sin (* phi1 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0))))
(* 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 = (t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + pow(((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0);
return R * (2.0 * atan2(sqrt(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 = (t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + (((cos((phi2 * 0.5d0)) * sin((phi1 * 0.5d0))) - (cos((phi1 * 0.5d0)) * sin((phi2 * 0.5d0)))) ** 2.0d0)
code = r * (2.0d0 * atan2(sqrt(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 = (t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0)) + Math.pow(((Math.cos((phi2 * 0.5)) * Math.sin((phi1 * 0.5))) - (Math.cos((phi1 * 0.5)) * Math.sin((phi2 * 0.5)))), 2.0);
return R * (2.0 * Math.atan2(Math.sqrt(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 = (t_0 * ((math.cos(phi1) * math.cos(phi2)) * t_0)) + math.pow(((math.cos((phi2 * 0.5)) * math.sin((phi1 * 0.5))) - (math.cos((phi1 * 0.5)) * math.sin((phi2 * 0.5)))), 2.0) return R * (2.0 * math.atan2(math.sqrt(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(Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)) + (Float64(Float64(cos(Float64(phi2 * 0.5)) * sin(Float64(phi1 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(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 = (t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + (((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))) ^ 2.0); tmp = R * (2.0 * atan2(sqrt(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[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $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[(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 := t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) + {\left(\cos \left(\phi_2 \cdot 0.5\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)
\end{array}
\end{array}
Initial program 62.0%
div-sub62.0%
sin-diff62.8%
div-inv62.8%
metadata-eval62.8%
div-inv62.8%
metadata-eval62.8%
div-inv62.8%
metadata-eval62.8%
div-inv62.8%
metadata-eval62.8%
Applied egg-rr62.8%
div-sub62.0%
sin-diff62.8%
div-inv62.8%
metadata-eval62.8%
div-inv62.8%
metadata-eval62.8%
div-inv62.8%
metadata-eval62.8%
div-inv62.8%
metadata-eval62.8%
Applied egg-rr75.8%
Final simplification75.8%
(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 (+ t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt
(-
1.0
(+
t_1
(pow
(-
(* (cos (* phi2 0.5)) (sin (* phi1 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = t_0 * ((cos(phi1) * cos(phi2)) * t_0);
return R * (2.0 * atan2(sqrt((t_1 + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 - (t_1 + pow(((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
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((t_1 + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt((1.0d0 - (t_1 + (((cos((phi2 * 0.5d0)) * sin((phi1 * 0.5d0))) - (cos((phi1 * 0.5d0)) * sin((phi2 * 0.5d0)))) ** 2.0d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt((t_1 + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt((1.0 - (t_1 + Math.pow(((Math.cos((phi2 * 0.5)) * Math.sin((phi1 * 0.5))) - (Math.cos((phi1 * 0.5)) * Math.sin((phi2 * 0.5)))), 2.0))))));
}
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((t_1 + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt((1.0 - (t_1 + math.pow(((math.cos((phi2 * 0.5)) * math.sin((phi1 * 0.5))) - (math.cos((phi1 * 0.5)) * math.sin((phi2 * 0.5)))), 2.0))))))
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(t_1 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - Float64(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))))))) 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((t_1 + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt((1.0 - (t_1 + (((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))) ^ 2.0)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, 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[(t$95$1 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(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]], $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{t\_1 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{1 - \left(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)}}\right)
\end{array}
\end{array}
Initial program 62.0%
div-sub62.0%
sin-diff62.8%
div-inv62.8%
metadata-eval62.8%
div-inv62.8%
metadata-eval62.8%
div-inv62.8%
metadata-eval62.8%
div-inv62.8%
metadata-eval62.8%
Applied egg-rr62.8%
Final simplification62.8%
(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 62.0%
associate-*l*62.0%
Simplified62.0%
div-sub62.0%
sin-diff62.8%
div-inv62.8%
metadata-eval62.8%
div-inv62.8%
metadata-eval62.8%
div-inv62.8%
metadata-eval62.8%
div-inv62.8%
metadata-eval62.8%
Applied egg-rr62.8%
Final simplification62.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(sqrt
(exp
(log1p
(-
(fma
(cos phi1)
(* (cos phi2) (+ 0.5 (* -0.5 (cos (- lambda1 lambda2)))))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))), sqrt(exp(log1p(-fma(cos(phi1), (cos(phi2) * (0.5 + (-0.5 * cos((lambda1 - lambda2))))), pow(sin((0.5 * (phi1 - phi2))), 2.0)))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)))), sqrt(exp(log1p(Float64(-fma(cos(phi1), Float64(cos(phi2) * Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2))))), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0))))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[Exp[N[Log[1 + (-N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision])], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right)}}{\sqrt{e^{\mathsf{log1p}\left(-\mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \left(0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right), {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)\right)}}}\right)
\end{array}
\end{array}
Initial program 62.0%
associate-*l*62.0%
Simplified62.0%
Applied egg-rr62.0%
Final simplification62.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_1 (sin (/ (- lambda1 lambda2) 2.0))))
(if (or (<= phi2 -8.8e-5) (not (<= phi2 1.26e-5)))
(*
(* R 2.0)
(atan2
(sqrt (+ (* (cos phi2) t_0) (pow (sin (* phi2 0.5)) 2.0)))
(sqrt
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (+ 0.5 (* -0.5 (cos (- lambda1 lambda2)))))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0))))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (cos phi1) (cos phi2)) (* t_1 t_1))))
(sqrt
(- 1.0 (+ (* (cos phi1) t_0) (pow (sin (* phi1 0.5)) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((phi2 <= -8.8e-5) || !(phi2 <= 1.26e-5)) {
tmp = (R * 2.0) * atan2(sqrt(((cos(phi2) * t_0) + pow(sin((phi2 * 0.5)), 2.0))), sqrt((1.0 - fma(cos(phi1), (cos(phi2) * (0.5 + (-0.5 * cos((lambda1 - lambda2))))), pow(sin((0.5 * (phi1 - phi2))), 2.0)))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((cos(phi1) * cos(phi2)) * (t_1 * t_1)))), sqrt((1.0 - ((cos(phi1) * t_0) + pow(sin((phi1 * 0.5)), 2.0))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if ((phi2 <= -8.8e-5) || !(phi2 <= 1.26e-5)) tmp = Float64(Float64(R * 2.0) * atan(sqrt(Float64(Float64(cos(phi2) * t_0) + (sin(Float64(phi2 * 0.5)) ^ 2.0))), sqrt(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2))))), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_1 * t_1)))), sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * t_0) + (sin(Float64(phi1 * 0.5)) ^ 2.0))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[phi2, -8.8e-5], N[Not[LessEqual[phi2, 1.26e-5]], $MachinePrecision]], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $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[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$1 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\phi_2 \leq -8.8 \cdot 10^{-5} \lor \neg \left(\phi_2 \leq 1.26 \cdot 10^{-5}\right):\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot t\_0 + {\sin \left(\phi_2 \cdot 0.5\right)}^{2}}}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \left(0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right), {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}}\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_1 \cdot t\_1\right)}}{\sqrt{1 - \left(\cos \phi_1 \cdot t\_0 + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}\right)\\
\end{array}
\end{array}
if phi2 < -8.7999999999999998e-5 or 1.25999999999999996e-5 < phi2 Initial program 49.0%
associate-*r*49.0%
*-commutative49.0%
Simplified49.0%
Applied egg-rr25.3%
*-lft-identity25.3%
*-commutative25.3%
*-commutative25.3%
*-commutative25.3%
Simplified25.3%
metadata-eval25.3%
associate-/r/24.1%
clear-num25.3%
div-sub25.3%
sin-diff25.7%
Applied egg-rr25.7%
fmm-def25.7%
*-commutative25.7%
distribute-rgt-neg-in25.7%
Simplified25.7%
Taylor expanded in phi1 around 0 49.8%
if -8.7999999999999998e-5 < phi2 < 1.25999999999999996e-5Initial program 76.2%
associate-*l*76.2%
Simplified76.2%
Taylor expanded in phi2 around 0 76.2%
Final simplification62.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_2 (+ (* (cos phi2) t_1) (pow (sin (* phi2 0.5)) 2.0)))
(t_3 (* (cos phi1) (cos phi2)))
(t_4 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(if (<= phi2 -2.05e-5)
(*
R
(* 2.0 (atan2 (sqrt (+ (* t_0 (* t_3 t_0)) t_4)) (sqrt (- 1.0 t_2)))))
(if (<= phi2 9.5e-5)
(*
R
(*
2.0
(atan2
(sqrt (+ t_4 (* t_3 (* t_0 t_0))))
(sqrt (- 1.0 (+ (* (cos phi1) t_1) (pow (sin (* phi1 0.5)) 2.0)))))))
(*
(* R 2.0)
(atan2
(sqrt t_2)
(sqrt
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (+ 0.5 (* -0.5 (cos (- lambda1 lambda2)))))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_2 = (cos(phi2) * t_1) + pow(sin((phi2 * 0.5)), 2.0);
double t_3 = cos(phi1) * cos(phi2);
double t_4 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double tmp;
if (phi2 <= -2.05e-5) {
tmp = R * (2.0 * atan2(sqrt(((t_0 * (t_3 * t_0)) + t_4)), sqrt((1.0 - t_2))));
} else if (phi2 <= 9.5e-5) {
tmp = R * (2.0 * atan2(sqrt((t_4 + (t_3 * (t_0 * t_0)))), sqrt((1.0 - ((cos(phi1) * t_1) + pow(sin((phi1 * 0.5)), 2.0))))));
} else {
tmp = (R * 2.0) * atan2(sqrt(t_2), sqrt((1.0 - fma(cos(phi1), (cos(phi2) * (0.5 + (-0.5 * cos((lambda1 - lambda2))))), pow(sin((0.5 * (phi1 - phi2))), 2.0)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_2 = Float64(Float64(cos(phi2) * t_1) + (sin(Float64(phi2 * 0.5)) ^ 2.0)) t_3 = Float64(cos(phi1) * cos(phi2)) t_4 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 tmp = 0.0 if (phi2 <= -2.05e-5) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_0 * Float64(t_3 * t_0)) + t_4)), sqrt(Float64(1.0 - t_2))))); elseif (phi2 <= 9.5e-5) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_4 + Float64(t_3 * Float64(t_0 * t_0)))), sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * t_1) + (sin(Float64(phi1 * 0.5)) ^ 2.0))))))); else tmp = Float64(Float64(R * 2.0) * atan(sqrt(t_2), sqrt(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2))))), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$1), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[LessEqual[phi2, -2.05e-5], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$0 * N[(t$95$3 * t$95$0), $MachinePrecision]), $MachinePrecision] + t$95$4), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$2), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[phi2, 9.5e-5], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$4 + N[(t$95$3 * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * t$95$1), $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[t$95$2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_2 := \cos \phi_2 \cdot t\_1 + {\sin \left(\phi_2 \cdot 0.5\right)}^{2}\\
t_3 := \cos \phi_1 \cdot \cos \phi_2\\
t_4 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
\mathbf{if}\;\phi_2 \leq -2.05 \cdot 10^{-5}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 \cdot \left(t\_3 \cdot t\_0\right) + t\_4}}{\sqrt{1 - t\_2}}\right)\\
\mathbf{elif}\;\phi_2 \leq 9.5 \cdot 10^{-5}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_4 + t\_3 \cdot \left(t\_0 \cdot t\_0\right)}}{\sqrt{1 - \left(\cos \phi_1 \cdot t\_1 + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\sqrt{t\_2}}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \left(0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right), {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}}\\
\end{array}
\end{array}
if phi2 < -2.05000000000000002e-5Initial program 47.5%
div-sub47.5%
sin-diff49.7%
div-inv49.7%
metadata-eval49.7%
div-inv49.7%
metadata-eval49.7%
div-inv49.7%
metadata-eval49.7%
div-inv49.7%
metadata-eval49.7%
Applied egg-rr49.7%
Taylor expanded in phi1 around 0 48.7%
if -2.05000000000000002e-5 < phi2 < 9.5000000000000005e-5Initial program 76.2%
associate-*l*76.2%
Simplified76.2%
Taylor expanded in phi2 around 0 76.2%
if 9.5000000000000005e-5 < phi2 Initial program 50.7%
associate-*r*50.7%
*-commutative50.7%
Simplified50.6%
Applied egg-rr25.6%
*-lft-identity25.6%
*-commutative25.6%
*-commutative25.6%
*-commutative25.6%
Simplified25.6%
metadata-eval25.6%
associate-/r/24.3%
clear-num25.6%
div-sub25.6%
sin-diff25.9%
Applied egg-rr25.9%
fmm-def25.9%
*-commutative25.9%
distribute-rgt-neg-in25.9%
Simplified25.9%
Taylor expanded in phi1 around 0 51.8%
Final simplification62.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_1 (* (cos phi2) t_0))
(t_2 (sin (/ (- lambda1 lambda2) 2.0)))
(t_3
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (cos phi1) (cos phi2)) (* t_2 t_2))))))
(if (<= phi2 -7.4e-7)
(*
R
(* 2.0 (atan2 t_3 (sqrt (- 1.0 (+ t_1 (pow (sin (* -0.5 phi2)) 2.0)))))))
(if (<= phi2 2.2e-5)
(*
R
(*
2.0
(atan2
t_3
(sqrt (- 1.0 (+ (* (cos phi1) t_0) (pow (sin (* phi1 0.5)) 2.0)))))))
(*
(* R 2.0)
(atan2
(sqrt (+ t_1 (pow (sin (* phi2 0.5)) 2.0)))
(sqrt
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (+ 0.5 (* -0.5 (cos (- lambda1 lambda2)))))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = cos(phi2) * t_0;
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double t_3 = sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((cos(phi1) * cos(phi2)) * (t_2 * t_2))));
double tmp;
if (phi2 <= -7.4e-7) {
tmp = R * (2.0 * atan2(t_3, sqrt((1.0 - (t_1 + pow(sin((-0.5 * phi2)), 2.0))))));
} else if (phi2 <= 2.2e-5) {
tmp = R * (2.0 * atan2(t_3, sqrt((1.0 - ((cos(phi1) * t_0) + pow(sin((phi1 * 0.5)), 2.0))))));
} else {
tmp = (R * 2.0) * atan2(sqrt((t_1 + pow(sin((phi2 * 0.5)), 2.0))), sqrt((1.0 - fma(cos(phi1), (cos(phi2) * (0.5 + (-0.5 * cos((lambda1 - lambda2))))), pow(sin((0.5 * (phi1 - phi2))), 2.0)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_1 = Float64(cos(phi2) * t_0) t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_3 = sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_2 * t_2)))) tmp = 0.0 if (phi2 <= -7.4e-7) tmp = Float64(R * Float64(2.0 * atan(t_3, sqrt(Float64(1.0 - Float64(t_1 + (sin(Float64(-0.5 * phi2)) ^ 2.0))))))); elseif (phi2 <= 2.2e-5) tmp = Float64(R * Float64(2.0 * atan(t_3, sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * t_0) + (sin(Float64(phi1 * 0.5)) ^ 2.0))))))); else tmp = Float64(Float64(R * 2.0) * atan(sqrt(Float64(t_1 + (sin(Float64(phi2 * 0.5)) ^ 2.0))), sqrt(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2))))), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$2 * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi2, -7.4e-7], N[(R * N[(2.0 * N[ArcTan[t$95$3 / N[Sqrt[N[(1.0 - N[(t$95$1 + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[phi2, 2.2e-5], N[(R * N[(2.0 * N[ArcTan[t$95$3 / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[N[(t$95$1 + N[Power[N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_1 := \cos \phi_2 \cdot t\_0\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_3 := \sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_2 \cdot t\_2\right)}\\
\mathbf{if}\;\phi_2 \leq -7.4 \cdot 10^{-7}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_3}{\sqrt{1 - \left(t\_1 + {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)}}\right)\\
\mathbf{elif}\;\phi_2 \leq 2.2 \cdot 10^{-5}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_3}{\sqrt{1 - \left(\cos \phi_1 \cdot t\_0 + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + {\sin \left(\phi_2 \cdot 0.5\right)}^{2}}}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \left(0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right), {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}}\\
\end{array}
\end{array}
if phi2 < -7.40000000000000009e-7Initial program 47.5%
associate-*l*47.5%
Simplified47.5%
Taylor expanded in phi1 around 0 48.7%
if -7.40000000000000009e-7 < phi2 < 2.1999999999999999e-5Initial program 76.2%
associate-*l*76.2%
Simplified76.2%
Taylor expanded in phi2 around 0 76.2%
if 2.1999999999999999e-5 < phi2 Initial program 50.7%
associate-*r*50.7%
*-commutative50.7%
Simplified50.6%
Applied egg-rr25.6%
*-lft-identity25.6%
*-commutative25.6%
*-commutative25.6%
*-commutative25.6%
Simplified25.6%
metadata-eval25.6%
associate-/r/24.3%
clear-num25.6%
div-sub25.6%
sin-diff25.9%
Applied egg-rr25.9%
fmm-def25.9%
*-commutative25.9%
distribute-rgt-neg-in25.9%
Simplified25.9%
Taylor expanded in phi1 around 0 51.8%
Final simplification62.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
(t_1 (pow (sin (* 0.5 (- phi1 phi2))) 2.0)))
(if (or (<= phi2 -5.9e-21) (not (<= phi2 3.7e-13)))
(*
(* R 2.0)
(atan2
(sqrt (+ t_0 (pow (sin (* phi2 0.5)) 2.0)))
(sqrt
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (+ 0.5 (* -0.5 (cos (- lambda1 lambda2)))))
t_1)))))
(*
(* R 2.0)
(atan2
(sqrt (+ (pow (sin (* phi1 0.5)) 2.0) (* (cos phi1) t_0)))
(sqrt
(-
1.0
(+
t_1
(*
(cos phi1)
(* (cos phi2) (+ 0.5 (* -0.5 (cos (- lambda2 lambda1))))))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = pow(sin((0.5 * (phi1 - phi2))), 2.0);
double tmp;
if ((phi2 <= -5.9e-21) || !(phi2 <= 3.7e-13)) {
tmp = (R * 2.0) * atan2(sqrt((t_0 + pow(sin((phi2 * 0.5)), 2.0))), sqrt((1.0 - fma(cos(phi1), (cos(phi2) * (0.5 + (-0.5 * cos((lambda1 - lambda2))))), t_1))));
} else {
tmp = (R * 2.0) * atan2(sqrt((pow(sin((phi1 * 0.5)), 2.0) + (cos(phi1) * t_0))), sqrt((1.0 - (t_1 + (cos(phi1) * (cos(phi2) * (0.5 + (-0.5 * cos((lambda2 - lambda1))))))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)) t_1 = sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0 tmp = 0.0 if ((phi2 <= -5.9e-21) || !(phi2 <= 3.7e-13)) tmp = Float64(Float64(R * 2.0) * atan(sqrt(Float64(t_0 + (sin(Float64(phi2 * 0.5)) ^ 2.0))), sqrt(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2))))), t_1))))); else tmp = Float64(Float64(R * 2.0) * atan(sqrt(Float64((sin(Float64(phi1 * 0.5)) ^ 2.0) + Float64(cos(phi1) * t_0))), sqrt(Float64(1.0 - Float64(t_1 + Float64(cos(phi1) * Float64(cos(phi2) * Float64(0.5 + Float64(-0.5 * cos(Float64(lambda2 - lambda1))))))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[phi2, -5.9e-21], N[Not[LessEqual[phi2, 3.7e-13]], $MachinePrecision]], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[N[(t$95$0 + N[Power[N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$1 + N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda2 - lambda1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_1 := {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\\
\mathbf{if}\;\phi_2 \leq -5.9 \cdot 10^{-21} \lor \neg \left(\phi_2 \leq 3.7 \cdot 10^{-13}\right):\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\sqrt{t\_0 + {\sin \left(\phi_2 \cdot 0.5\right)}^{2}}}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \left(0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right), t\_1\right)}}\\
\mathbf{else}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\phi_1 \cdot 0.5\right)}^{2} + \cos \phi_1 \cdot t\_0}}{\sqrt{1 - \left(t\_1 + \cos \phi_1 \cdot \left(\cos \phi_2 \cdot \left(0.5 + -0.5 \cdot \cos \left(\lambda_2 - \lambda_1\right)\right)\right)\right)}}\\
\end{array}
\end{array}
if phi2 < -5.9000000000000003e-21 or 3.69999999999999989e-13 < phi2 Initial program 50.4%
associate-*r*50.4%
*-commutative50.4%
Simplified50.4%
Applied egg-rr27.2%
*-lft-identity27.2%
*-commutative27.2%
*-commutative27.2%
*-commutative27.2%
Simplified27.2%
metadata-eval27.2%
associate-/r/26.1%
clear-num27.2%
div-sub27.2%
sin-diff27.6%
Applied egg-rr27.6%
fmm-def27.6%
*-commutative27.6%
distribute-rgt-neg-in27.6%
Simplified27.6%
Taylor expanded in phi1 around 0 50.9%
if -5.9000000000000003e-21 < phi2 < 3.69999999999999989e-13Initial program 75.9%
associate-*r*75.9%
*-commutative75.9%
Simplified75.9%
Applied egg-rr53.1%
*-lft-identity53.1%
*-commutative53.1%
*-commutative53.1%
*-commutative53.1%
Simplified53.1%
Taylor expanded in phi2 around 0 51.4%
expm1-log1p-u51.4%
expm1-undefine51.4%
+-commutative51.4%
fma-define51.4%
Applied egg-rr51.4%
expm1-define51.4%
sub-neg51.4%
remove-double-neg51.4%
mul-1-neg51.4%
distribute-neg-in51.4%
+-commutative51.4%
cos-neg51.4%
mul-1-neg51.4%
unsub-neg51.4%
Simplified51.4%
Taylor expanded in phi1 around 0 74.4%
Final simplification61.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(if (or (<= phi1 -4.4e-11) (not (<= phi1 1.85e-51)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* t_0 (* (* (cos phi1) (cos phi2)) t_0))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt
(-
1.0
(+
(pow (sin (* phi1 0.5)) 2.0)
(* (cos phi1) (pow (sin (* 0.5 lambda1)) 2.0))))))))
(*
(* R 2.0)
(atan2
(sqrt
(+
(* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(pow (sin (* phi2 0.5)) 2.0)))
(sqrt
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (+ 0.5 (* -0.5 (cos (- lambda1 lambda2)))))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((phi1 <= -4.4e-11) || !(phi1 <= 1.85e-51)) {
tmp = R * (2.0 * atan2(sqrt(((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 - (pow(sin((phi1 * 0.5)), 2.0) + (cos(phi1) * pow(sin((0.5 * lambda1)), 2.0)))))));
} else {
tmp = (R * 2.0) * atan2(sqrt(((cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0)) + pow(sin((phi2 * 0.5)), 2.0))), sqrt((1.0 - fma(cos(phi1), (cos(phi2) * (0.5 + (-0.5 * cos((lambda1 - lambda2))))), pow(sin((0.5 * (phi1 - phi2))), 2.0)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if ((phi1 <= -4.4e-11) || !(phi1 <= 1.85e-51)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - Float64((sin(Float64(phi1 * 0.5)) ^ 2.0) + Float64(cos(phi1) * (sin(Float64(0.5 * lambda1)) ^ 2.0)))))))); else tmp = Float64(Float64(R * 2.0) * atan(sqrt(Float64(Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)) + (sin(Float64(phi2 * 0.5)) ^ 2.0))), sqrt(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2))))), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[phi1, -4.4e-11], N[Not[LessEqual[phi1, 1.85e-51]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\phi_1 \leq -4.4 \cdot 10^{-11} \lor \neg \left(\phi_1 \leq 1.85 \cdot 10^{-51}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{1 - \left({\sin \left(\phi_1 \cdot 0.5\right)}^{2} + \cos \phi_1 \cdot {\sin \left(0.5 \cdot \lambda_1\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2} + {\sin \left(\phi_2 \cdot 0.5\right)}^{2}}}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \left(0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right), {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}}\\
\end{array}
\end{array}
if phi1 < -4.4000000000000003e-11 or 1.84999999999999987e-51 < phi1 Initial program 47.7%
div-sub47.7%
sin-diff49.3%
div-inv49.3%
metadata-eval49.3%
div-inv49.3%
metadata-eval49.3%
div-inv49.3%
metadata-eval49.3%
div-inv49.3%
metadata-eval49.3%
Applied egg-rr49.3%
Taylor expanded in lambda2 around 0 39.1%
Taylor expanded in phi2 around 0 38.5%
if -4.4000000000000003e-11 < phi1 < 1.84999999999999987e-51Initial program 78.4%
associate-*r*78.4%
*-commutative78.4%
Simplified78.4%
Applied egg-rr58.1%
*-lft-identity58.1%
*-commutative58.1%
*-commutative58.1%
*-commutative58.1%
Simplified58.1%
metadata-eval58.1%
associate-/r/56.7%
clear-num58.1%
div-sub58.1%
sin-diff58.1%
Applied egg-rr58.1%
fmm-def58.1%
*-commutative58.1%
distribute-rgt-neg-in58.1%
Simplified58.1%
Taylor expanded in phi1 around 0 77.7%
Final simplification56.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* t_0 (* t_1 t_1))))
(sqrt
(-
(- 1.0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0))
(* t_0 (+ 0.5 (* -0.5 (cos (- lambda1 lambda2))))))))))))
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));
return R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * (t_1 * t_1)))), sqrt(((1.0 - pow(sin((0.5 * (phi1 - phi2))), 2.0)) - (t_0 * (0.5 + (-0.5 * cos((lambda1 - lambda2)))))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = cos(phi1) * cos(phi2)
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (t_0 * (t_1 * t_1)))), sqrt(((1.0d0 - (sin((0.5d0 * (phi1 - phi2))) ** 2.0d0)) - (t_0 * (0.5d0 + ((-0.5d0) * cos((lambda1 - lambda2)))))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.cos(phi1) * Math.cos(phi2);
double t_1 = 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 * (t_1 * t_1)))), Math.sqrt(((1.0 - Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0)) - (t_0 * (0.5 + (-0.5 * Math.cos((lambda1 - lambda2)))))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi1) * math.cos(phi2) t_1 = 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 * (t_1 * t_1)))), math.sqrt(((1.0 - math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0)) - (t_0 * (0.5 + (-0.5 * math.cos((lambda1 - lambda2)))))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = 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(t_1 * t_1)))), sqrt(Float64(Float64(1.0 - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)) - Float64(t_0 * Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2)))))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi1) * cos(phi2); t_1 = sin(((lambda1 - lambda2) / 2.0)); tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (t_0 * (t_1 * t_1)))), sqrt(((1.0 - (sin((0.5 * (phi1 - phi2))) ^ 2.0)) - (t_0 * (0.5 + (-0.5 * cos((lambda1 - lambda2))))))))); 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]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$0 * N[(t$95$1 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] - N[(t$95$0 * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \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(t\_1 \cdot t\_1\right)}}{\sqrt{\left(1 - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right) - t\_0 \cdot \left(0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right)}}\right)
\end{array}
\end{array}
Initial program 62.0%
associate-*l*62.0%
Simplified62.0%
*-commutative62.0%
cancel-sign-sub-inv62.0%
div-inv62.0%
metadata-eval62.0%
Applied egg-rr62.0%
Final simplification62.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi2) (+ 0.5 (* -0.5 (cos (- lambda1 lambda2))))))
(t_1 (sin (* 0.5 (- lambda1 lambda2))))
(t_2 (sin (* 0.5 (- phi1 phi2)))))
(if (or (<= phi2 -1.45e-25) (not (<= phi2 1.5e-42)))
(*
(* R 2.0)
(atan2
(sqrt (+ (* (cos phi2) (pow t_1 2.0)) (pow (sin (* phi2 0.5)) 2.0)))
(sqrt (- 1.0 (fma (cos phi1) t_0 (pow t_2 2.0))))))
(*
(* R 2.0)
(atan2
(hypot t_2 (* t_1 (sqrt (* (cos phi1) (cos phi2)))))
(sqrt (- 1.0 (fma (cos phi1) t_0 (pow (sin (* phi1 0.5)) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi2) * (0.5 + (-0.5 * cos((lambda1 - lambda2))));
double t_1 = sin((0.5 * (lambda1 - lambda2)));
double t_2 = sin((0.5 * (phi1 - phi2)));
double tmp;
if ((phi2 <= -1.45e-25) || !(phi2 <= 1.5e-42)) {
tmp = (R * 2.0) * atan2(sqrt(((cos(phi2) * pow(t_1, 2.0)) + pow(sin((phi2 * 0.5)), 2.0))), sqrt((1.0 - fma(cos(phi1), t_0, pow(t_2, 2.0)))));
} else {
tmp = (R * 2.0) * atan2(hypot(t_2, (t_1 * sqrt((cos(phi1) * cos(phi2))))), sqrt((1.0 - fma(cos(phi1), t_0, pow(sin((phi1 * 0.5)), 2.0)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi2) * Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2))))) t_1 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) t_2 = sin(Float64(0.5 * Float64(phi1 - phi2))) tmp = 0.0 if ((phi2 <= -1.45e-25) || !(phi2 <= 1.5e-42)) tmp = Float64(Float64(R * 2.0) * atan(sqrt(Float64(Float64(cos(phi2) * (t_1 ^ 2.0)) + (sin(Float64(phi2 * 0.5)) ^ 2.0))), sqrt(Float64(1.0 - fma(cos(phi1), t_0, (t_2 ^ 2.0)))))); else tmp = Float64(Float64(R * 2.0) * atan(hypot(t_2, Float64(t_1 * sqrt(Float64(cos(phi1) * cos(phi2))))), sqrt(Float64(1.0 - fma(cos(phi1), t_0, (sin(Float64(phi1 * 0.5)) ^ 2.0)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[phi2, -1.45e-25], N[Not[LessEqual[phi2, 1.5e-42]], $MachinePrecision]], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[t$95$1, 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * t$95$0 + N[Power[t$95$2, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[t$95$2 ^ 2 + N[(t$95$1 * N[Sqrt[N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * t$95$0 + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_2 \cdot \left(0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right)\\
t_1 := \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\\
t_2 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
\mathbf{if}\;\phi_2 \leq -1.45 \cdot 10^{-25} \lor \neg \left(\phi_2 \leq 1.5 \cdot 10^{-42}\right):\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot {t\_1}^{2} + {\sin \left(\phi_2 \cdot 0.5\right)}^{2}}}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, t\_0, {t\_2}^{2}\right)}}\\
\mathbf{else}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(t\_2, t\_1 \cdot \sqrt{\cos \phi_1 \cdot \cos \phi_2}\right)}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, t\_0, {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}\\
\end{array}
\end{array}
if phi2 < -1.45e-25 or 1.50000000000000014e-42 < phi2 Initial program 51.1%
associate-*r*51.1%
*-commutative51.1%
Simplified51.1%
Applied egg-rr26.3%
*-lft-identity26.3%
*-commutative26.3%
*-commutative26.3%
*-commutative26.3%
Simplified26.3%
metadata-eval26.3%
associate-/r/25.2%
clear-num26.3%
div-sub26.3%
sin-diff26.7%
Applied egg-rr26.7%
fmm-def26.7%
*-commutative26.7%
distribute-rgt-neg-in26.7%
Simplified26.7%
Taylor expanded in phi1 around 0 49.6%
if -1.45e-25 < phi2 < 1.50000000000000014e-42Initial program 76.2%
associate-*r*76.2%
*-commutative76.2%
Simplified76.2%
Applied egg-rr55.4%
*-lft-identity55.4%
*-commutative55.4%
*-commutative55.4%
*-commutative55.4%
Simplified55.4%
Taylor expanded in phi2 around 0 55.4%
Final simplification52.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- phi1 phi2))))
(t_1
(hypot
t_0
(*
(sin (* 0.5 (- lambda1 lambda2)))
(sqrt (* (cos phi1) (cos phi2))))))
(t_2 (pow t_0 2.0)))
(if (or (<= lambda2 -1.75e-37) (not (<= lambda2 7.4e-6)))
(*
(* R 2.0)
(atan2
t_1
(sqrt
(-
1.0
(fma (cos phi1) (* (cos phi2) (+ 0.5 (* -0.5 (cos lambda2)))) t_2)))))
(*
(* R 2.0)
(atan2
t_1
(sqrt
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (+ 0.5 (* -0.5 (cos lambda1))))
t_2))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (phi1 - phi2)));
double t_1 = hypot(t_0, (sin((0.5 * (lambda1 - lambda2))) * sqrt((cos(phi1) * cos(phi2)))));
double t_2 = pow(t_0, 2.0);
double tmp;
if ((lambda2 <= -1.75e-37) || !(lambda2 <= 7.4e-6)) {
tmp = (R * 2.0) * atan2(t_1, sqrt((1.0 - fma(cos(phi1), (cos(phi2) * (0.5 + (-0.5 * cos(lambda2)))), t_2))));
} else {
tmp = (R * 2.0) * atan2(t_1, sqrt((1.0 - fma(cos(phi1), (cos(phi2) * (0.5 + (-0.5 * cos(lambda1)))), t_2))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(phi1 - phi2))) t_1 = hypot(t_0, Float64(sin(Float64(0.5 * Float64(lambda1 - lambda2))) * sqrt(Float64(cos(phi1) * cos(phi2))))) t_2 = t_0 ^ 2.0 tmp = 0.0 if ((lambda2 <= -1.75e-37) || !(lambda2 <= 7.4e-6)) tmp = Float64(Float64(R * 2.0) * atan(t_1, sqrt(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * Float64(0.5 + Float64(-0.5 * cos(lambda2)))), t_2))))); else tmp = Float64(Float64(R * 2.0) * atan(t_1, sqrt(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * Float64(0.5 + Float64(-0.5 * cos(lambda1)))), t_2))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sqrt[t$95$0 ^ 2 + N[(N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[Sqrt[N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision]}, Block[{t$95$2 = N[Power[t$95$0, 2.0], $MachinePrecision]}, If[Or[LessEqual[lambda2, -1.75e-37], N[Not[LessEqual[lambda2, 7.4e-6]], $MachinePrecision]], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[t$95$1 / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 + N[(-0.5 * N[Cos[lambda2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[t$95$1 / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 + N[(-0.5 * N[Cos[lambda1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
t_1 := \mathsf{hypot}\left(t\_0, \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right) \cdot \sqrt{\cos \phi_1 \cdot \cos \phi_2}\right)\\
t_2 := {t\_0}^{2}\\
\mathbf{if}\;\lambda_2 \leq -1.75 \cdot 10^{-37} \lor \neg \left(\lambda_2 \leq 7.4 \cdot 10^{-6}\right):\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{t\_1}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \left(0.5 + -0.5 \cdot \cos \lambda_2\right), t\_2\right)}}\\
\mathbf{else}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{t\_1}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \left(0.5 + -0.5 \cdot \cos \lambda_1\right), t\_2\right)}}\\
\end{array}
\end{array}
if lambda2 < -1.7500000000000001e-37 or 7.4000000000000003e-6 < lambda2 Initial program 46.2%
associate-*r*46.2%
*-commutative46.2%
Simplified46.2%
Applied egg-rr27.7%
*-lft-identity27.7%
*-commutative27.7%
*-commutative27.7%
*-commutative27.7%
Simplified27.7%
Taylor expanded in lambda1 around 0 27.4%
cos-neg27.4%
Simplified27.4%
if -1.7500000000000001e-37 < lambda2 < 7.4000000000000003e-6Initial program 82.3%
associate-*r*82.3%
*-commutative82.3%
Simplified82.3%
Applied egg-rr53.4%
*-lft-identity53.4%
*-commutative53.4%
*-commutative53.4%
*-commutative53.4%
Simplified53.4%
Taylor expanded in lambda2 around 0 53.4%
Final simplification38.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- lambda1 lambda2))))
(t_1 (sin (* 0.5 (- phi1 phi2))))
(t_2 (pow t_1 2.0)))
(if (or (<= lambda2 -1.15e-18) (not (<= lambda2 2.35e-5)))
(*
(* R 2.0)
(atan2
(hypot (sin (* phi1 0.5)) (* t_0 (sqrt (cos phi1))))
(sqrt
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (+ 0.5 (* -0.5 (cos (- lambda1 lambda2)))))
t_2)))))
(*
(* R 2.0)
(atan2
(hypot t_1 (* t_0 (sqrt (* (cos phi1) (cos phi2)))))
(sqrt
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (+ 0.5 (* -0.5 (cos lambda1))))
t_2))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (lambda1 - lambda2)));
double t_1 = sin((0.5 * (phi1 - phi2)));
double t_2 = pow(t_1, 2.0);
double tmp;
if ((lambda2 <= -1.15e-18) || !(lambda2 <= 2.35e-5)) {
tmp = (R * 2.0) * atan2(hypot(sin((phi1 * 0.5)), (t_0 * sqrt(cos(phi1)))), sqrt((1.0 - fma(cos(phi1), (cos(phi2) * (0.5 + (-0.5 * cos((lambda1 - lambda2))))), t_2))));
} else {
tmp = (R * 2.0) * atan2(hypot(t_1, (t_0 * sqrt((cos(phi1) * cos(phi2))))), sqrt((1.0 - fma(cos(phi1), (cos(phi2) * (0.5 + (-0.5 * cos(lambda1)))), t_2))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) t_1 = sin(Float64(0.5 * Float64(phi1 - phi2))) t_2 = t_1 ^ 2.0 tmp = 0.0 if ((lambda2 <= -1.15e-18) || !(lambda2 <= 2.35e-5)) tmp = Float64(Float64(R * 2.0) * atan(hypot(sin(Float64(phi1 * 0.5)), Float64(t_0 * sqrt(cos(phi1)))), sqrt(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2))))), t_2))))); else tmp = Float64(Float64(R * 2.0) * atan(hypot(t_1, Float64(t_0 * sqrt(Float64(cos(phi1) * cos(phi2))))), sqrt(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * Float64(0.5 + Float64(-0.5 * cos(lambda1)))), t_2))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Power[t$95$1, 2.0], $MachinePrecision]}, If[Or[LessEqual[lambda2, -1.15e-18], N[Not[LessEqual[lambda2, 2.35e-5]], $MachinePrecision]], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] ^ 2 + N[(t$95$0 * N[Sqrt[N[Cos[phi1], $MachinePrecision]], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[t$95$1 ^ 2 + N[(t$95$0 * N[Sqrt[N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 + N[(-0.5 * N[Cos[lambda1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\\
t_1 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
t_2 := {t\_1}^{2}\\
\mathbf{if}\;\lambda_2 \leq -1.15 \cdot 10^{-18} \lor \neg \left(\lambda_2 \leq 2.35 \cdot 10^{-5}\right):\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(\sin \left(\phi_1 \cdot 0.5\right), t\_0 \cdot \sqrt{\cos \phi_1}\right)}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \left(0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right), t\_2\right)}}\\
\mathbf{else}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(t\_1, t\_0 \cdot \sqrt{\cos \phi_1 \cdot \cos \phi_2}\right)}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \left(0.5 + -0.5 \cdot \cos \lambda_1\right), t\_2\right)}}\\
\end{array}
\end{array}
if lambda2 < -1.15e-18 or 2.34999999999999986e-5 < lambda2 Initial program 46.1%
associate-*r*46.1%
*-commutative46.1%
Simplified46.1%
Applied egg-rr27.4%
*-lft-identity27.4%
*-commutative27.4%
*-commutative27.4%
*-commutative27.4%
Simplified27.4%
Taylor expanded in phi2 around 0 22.9%
Taylor expanded in phi2 around 0 25.7%
if -1.15e-18 < lambda2 < 2.34999999999999986e-5Initial program 81.7%
associate-*r*81.7%
*-commutative81.7%
Simplified81.7%
Applied egg-rr53.3%
*-lft-identity53.3%
*-commutative53.3%
*-commutative53.3%
*-commutative53.3%
Simplified53.3%
Taylor expanded in lambda2 around 0 53.1%
Final simplification37.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- phi1 phi2))))
(t_1
(sqrt
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (+ 0.5 (* -0.5 (cos (- lambda1 lambda2)))))
(pow t_0 2.0))))))
(if (or (<= lambda2 -8e-22) (not (<= lambda2 1.55e-28)))
(*
(* R 2.0)
(atan2
(hypot
(sin (* phi1 0.5))
(* (sin (* 0.5 (- lambda1 lambda2))) (sqrt (cos phi1))))
t_1))
(*
(* R 2.0)
(atan2
(hypot t_0 (* (sin (* 0.5 lambda1)) (sqrt (* (cos phi1) (cos phi2)))))
t_1)))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (phi1 - phi2)));
double t_1 = sqrt((1.0 - fma(cos(phi1), (cos(phi2) * (0.5 + (-0.5 * cos((lambda1 - lambda2))))), pow(t_0, 2.0))));
double tmp;
if ((lambda2 <= -8e-22) || !(lambda2 <= 1.55e-28)) {
tmp = (R * 2.0) * atan2(hypot(sin((phi1 * 0.5)), (sin((0.5 * (lambda1 - lambda2))) * sqrt(cos(phi1)))), t_1);
} else {
tmp = (R * 2.0) * atan2(hypot(t_0, (sin((0.5 * lambda1)) * sqrt((cos(phi1) * cos(phi2))))), t_1);
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(phi1 - phi2))) t_1 = sqrt(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2))))), (t_0 ^ 2.0)))) tmp = 0.0 if ((lambda2 <= -8e-22) || !(lambda2 <= 1.55e-28)) tmp = Float64(Float64(R * 2.0) * atan(hypot(sin(Float64(phi1 * 0.5)), Float64(sin(Float64(0.5 * Float64(lambda1 - lambda2))) * sqrt(cos(phi1)))), t_1)); else tmp = Float64(Float64(R * 2.0) * atan(hypot(t_0, Float64(sin(Float64(0.5 * lambda1)) * sqrt(Float64(cos(phi1) * cos(phi2))))), t_1)); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[t$95$0, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[lambda2, -8e-22], N[Not[LessEqual[lambda2, 1.55e-28]], $MachinePrecision]], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] ^ 2 + N[(N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[Sqrt[N[Cos[phi1], $MachinePrecision]], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / t$95$1], $MachinePrecision]), $MachinePrecision], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[t$95$0 ^ 2 + N[(N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision] * N[Sqrt[N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / t$95$1], $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
t_1 := \sqrt{1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \left(0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right), {t\_0}^{2}\right)}\\
\mathbf{if}\;\lambda_2 \leq -8 \cdot 10^{-22} \lor \neg \left(\lambda_2 \leq 1.55 \cdot 10^{-28}\right):\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(\sin \left(\phi_1 \cdot 0.5\right), \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right) \cdot \sqrt{\cos \phi_1}\right)}{t\_1}\\
\mathbf{else}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(t\_0, \sin \left(0.5 \cdot \lambda_1\right) \cdot \sqrt{\cos \phi_1 \cdot \cos \phi_2}\right)}{t\_1}\\
\end{array}
\end{array}
if lambda2 < -8.0000000000000004e-22 or 1.54999999999999996e-28 < lambda2 Initial program 47.9%
associate-*r*47.9%
*-commutative47.9%
Simplified47.9%
Applied egg-rr29.2%
*-lft-identity29.2%
*-commutative29.2%
*-commutative29.2%
*-commutative29.2%
Simplified29.2%
Taylor expanded in phi2 around 0 24.3%
Taylor expanded in phi2 around 0 27.0%
if -8.0000000000000004e-22 < lambda2 < 1.54999999999999996e-28Initial program 80.9%
associate-*r*80.9%
*-commutative80.9%
Simplified80.9%
Applied egg-rr52.1%
*-lft-identity52.1%
*-commutative52.1%
*-commutative52.1%
*-commutative52.1%
Simplified52.1%
Taylor expanded in lambda2 around 0 49.4%
Final simplification36.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- lambda1 lambda2))))
(t_1 (* (cos phi1) (cos phi2)))
(t_2 (* t_0 (sqrt t_1)))
(t_3 (sin (* phi1 0.5))))
(if (<= phi1 -6.6e-7)
(*
(* R 2.0)
(atan2
(hypot t_3 t_2)
(sqrt
(-
1.0
(+
(pow t_3 2.0)
(* (cos phi1) (+ 0.5 (* -0.5 (cos (- lambda2 lambda1))))))))))
(if (<= phi1 3.75e-25)
(*
(* R 2.0)
(atan2
(hypot (sin (* 0.5 (- phi1 phi2))) t_2)
(sqrt
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (+ 0.5 (* -0.5 (cos (- lambda1 lambda2)))))
(pow (sin (* -0.5 phi2)) 2.0))))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(*
t_1
(* (sin (/ (- lambda1 lambda2) 2.0)) (sin (* 0.5 lambda1))))))
(sqrt (- 1.0 (pow t_0 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (lambda1 - lambda2)));
double t_1 = cos(phi1) * cos(phi2);
double t_2 = t_0 * sqrt(t_1);
double t_3 = sin((phi1 * 0.5));
double tmp;
if (phi1 <= -6.6e-7) {
tmp = (R * 2.0) * atan2(hypot(t_3, t_2), sqrt((1.0 - (pow(t_3, 2.0) + (cos(phi1) * (0.5 + (-0.5 * cos((lambda2 - lambda1)))))))));
} else if (phi1 <= 3.75e-25) {
tmp = (R * 2.0) * atan2(hypot(sin((0.5 * (phi1 - phi2))), t_2), sqrt((1.0 - fma(cos(phi1), (cos(phi2) * (0.5 + (-0.5 * cos((lambda1 - lambda2))))), pow(sin((-0.5 * phi2)), 2.0)))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_1 * (sin(((lambda1 - lambda2) / 2.0)) * sin((0.5 * lambda1)))))), sqrt((1.0 - pow(t_0, 2.0)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) t_1 = Float64(cos(phi1) * cos(phi2)) t_2 = Float64(t_0 * sqrt(t_1)) t_3 = sin(Float64(phi1 * 0.5)) tmp = 0.0 if (phi1 <= -6.6e-7) tmp = Float64(Float64(R * 2.0) * atan(hypot(t_3, t_2), sqrt(Float64(1.0 - Float64((t_3 ^ 2.0) + Float64(cos(phi1) * Float64(0.5 + Float64(-0.5 * cos(Float64(lambda2 - lambda1)))))))))); elseif (phi1 <= 3.75e-25) tmp = Float64(Float64(R * 2.0) * atan(hypot(sin(Float64(0.5 * Float64(phi1 - phi2))), t_2), sqrt(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2))))), (sin(Float64(-0.5 * phi2)) ^ 2.0)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_1 * Float64(sin(Float64(Float64(lambda1 - lambda2) / 2.0)) * sin(Float64(0.5 * lambda1)))))), sqrt(Float64(1.0 - (t_0 ^ 2.0)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(t$95$0 * N[Sqrt[t$95$1], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi1, -6.6e-7], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[t$95$3 ^ 2 + t$95$2 ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[t$95$3, 2.0], $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda2 - lambda1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision], If[LessEqual[phi1, 3.75e-25], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] ^ 2 + t$95$2 ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $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$1 * N[(N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[t$95$0, 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
t_2 := t\_0 \cdot \sqrt{t\_1}\\
t_3 := \sin \left(\phi_1 \cdot 0.5\right)\\
\mathbf{if}\;\phi_1 \leq -6.6 \cdot 10^{-7}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(t\_3, t\_2\right)}{\sqrt{1 - \left({t\_3}^{2} + \cos \phi_1 \cdot \left(0.5 + -0.5 \cdot \cos \left(\lambda_2 - \lambda_1\right)\right)\right)}}\\
\mathbf{elif}\;\phi_1 \leq 3.75 \cdot 10^{-25}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right), t\_2\right)}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \left(0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right), {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)}}\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_1 \cdot \left(\sin \left(\frac{\lambda_1 - \lambda_2}{2}\right) \cdot \sin \left(0.5 \cdot \lambda_1\right)\right)}}{\sqrt{1 - {t\_0}^{2}}}\right)\\
\end{array}
\end{array}
if phi1 < -6.6000000000000003e-7Initial program 49.6%
associate-*r*49.6%
*-commutative49.6%
Simplified49.6%
Applied egg-rr22.2%
*-lft-identity22.2%
*-commutative22.2%
*-commutative22.2%
*-commutative22.2%
Simplified22.2%
Taylor expanded in phi2 around 0 22.3%
expm1-log1p-u22.3%
expm1-undefine22.3%
+-commutative22.3%
fma-define22.3%
Applied egg-rr22.3%
expm1-define22.3%
sub-neg22.3%
remove-double-neg22.3%
mul-1-neg22.3%
distribute-neg-in22.3%
+-commutative22.3%
cos-neg22.3%
mul-1-neg22.3%
unsub-neg22.3%
Simplified22.3%
Taylor expanded in phi2 around 0 23.5%
if -6.6000000000000003e-7 < phi1 < 3.74999999999999994e-25Initial program 76.8%
associate-*r*76.8%
*-commutative76.8%
Simplified76.7%
Applied egg-rr57.3%
*-lft-identity57.3%
*-commutative57.3%
*-commutative57.3%
*-commutative57.3%
Simplified57.3%
Taylor expanded in phi1 around 0 57.3%
*-commutative57.3%
Simplified57.3%
if 3.74999999999999994e-25 < phi1 Initial program 44.2%
associate-*l*44.2%
Simplified44.1%
Taylor expanded in phi1 around 0 6.5%
Taylor expanded in lambda2 around 0 6.7%
Taylor expanded in phi2 around 0 20.1%
Final simplification39.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- lambda1 lambda2)))))
(if (or (<= phi2 -4.5e-65) (not (<= phi2 5.3e-43)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(*
(* (cos phi1) (cos phi2))
(* (sin (/ (- lambda1 lambda2) 2.0)) (sin (* 0.5 lambda1))))))
(sqrt (- 1.0 (pow t_0 2.0))))))
(*
(* R 2.0)
(atan2
(hypot (sin (* phi1 0.5)) (* t_0 (sqrt (cos phi1))))
(sqrt
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (+ 0.5 (* -0.5 (cos (- lambda1 lambda2)))))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (lambda1 - lambda2)));
double tmp;
if ((phi2 <= -4.5e-65) || !(phi2 <= 5.3e-43)) {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((cos(phi1) * cos(phi2)) * (sin(((lambda1 - lambda2) / 2.0)) * sin((0.5 * lambda1)))))), sqrt((1.0 - pow(t_0, 2.0)))));
} else {
tmp = (R * 2.0) * atan2(hypot(sin((phi1 * 0.5)), (t_0 * sqrt(cos(phi1)))), sqrt((1.0 - fma(cos(phi1), (cos(phi2) * (0.5 + (-0.5 * cos((lambda1 - lambda2))))), pow(sin((0.5 * (phi1 - phi2))), 2.0)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) tmp = 0.0 if ((phi2 <= -4.5e-65) || !(phi2 <= 5.3e-43)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(cos(phi1) * cos(phi2)) * Float64(sin(Float64(Float64(lambda1 - lambda2) / 2.0)) * sin(Float64(0.5 * lambda1)))))), sqrt(Float64(1.0 - (t_0 ^ 2.0)))))); else tmp = Float64(Float64(R * 2.0) * atan(hypot(sin(Float64(phi1 * 0.5)), Float64(t_0 * sqrt(cos(phi1)))), sqrt(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2))))), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[phi2, -4.5e-65], N[Not[LessEqual[phi2, 5.3e-43]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[t$95$0, 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] ^ 2 + N[(t$95$0 * N[Sqrt[N[Cos[phi1], $MachinePrecision]], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\\
\mathbf{if}\;\phi_2 \leq -4.5 \cdot 10^{-65} \lor \neg \left(\phi_2 \leq 5.3 \cdot 10^{-43}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(\sin \left(\frac{\lambda_1 - \lambda_2}{2}\right) \cdot \sin \left(0.5 \cdot \lambda_1\right)\right)}}{\sqrt{1 - {t\_0}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(\sin \left(\phi_1 \cdot 0.5\right), t\_0 \cdot \sqrt{\cos \phi_1}\right)}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \left(0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right), {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}}\\
\end{array}
\end{array}
if phi2 < -4.4999999999999998e-65 or 5.3000000000000003e-43 < phi2 Initial program 52.3%
associate-*l*52.3%
Simplified52.3%
Taylor expanded in phi1 around 0 41.8%
Taylor expanded in lambda2 around 0 32.7%
Taylor expanded in phi2 around 0 23.7%
if -4.4999999999999998e-65 < phi2 < 5.3000000000000003e-43Initial program 76.2%
associate-*r*76.2%
*-commutative76.2%
Simplified76.1%
Applied egg-rr55.0%
*-lft-identity55.0%
*-commutative55.0%
*-commutative55.0%
*-commutative55.0%
Simplified55.0%
Taylor expanded in phi2 around 0 54.1%
Taylor expanded in phi2 around 0 54.1%
Final simplification36.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* phi1 0.5)))
(t_1 (* (cos phi1) (cos phi2)))
(t_2 (sin (* 0.5 (- lambda1 lambda2)))))
(if (or (<= phi2 -1.35e-64) (not (<= phi2 6e-45)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* t_1 (* (sin (/ (- lambda1 lambda2) 2.0)) (sin (* 0.5 lambda1))))))
(sqrt (- 1.0 (pow t_2 2.0))))))
(*
(* R 2.0)
(atan2
(hypot t_0 (* t_2 (sqrt t_1)))
(sqrt
(-
1.0
(+
(pow t_0 2.0)
(* (cos phi1) (+ 0.5 (* -0.5 (cos (- lambda2 lambda1)))))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((phi1 * 0.5));
double t_1 = cos(phi1) * cos(phi2);
double t_2 = sin((0.5 * (lambda1 - lambda2)));
double tmp;
if ((phi2 <= -1.35e-64) || !(phi2 <= 6e-45)) {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_1 * (sin(((lambda1 - lambda2) / 2.0)) * sin((0.5 * lambda1)))))), sqrt((1.0 - pow(t_2, 2.0)))));
} else {
tmp = (R * 2.0) * atan2(hypot(t_0, (t_2 * sqrt(t_1))), sqrt((1.0 - (pow(t_0, 2.0) + (cos(phi1) * (0.5 + (-0.5 * cos((lambda2 - lambda1)))))))));
}
return tmp;
}
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin((phi1 * 0.5));
double t_1 = Math.cos(phi1) * Math.cos(phi2);
double t_2 = Math.sin((0.5 * (lambda1 - lambda2)));
double tmp;
if ((phi2 <= -1.35e-64) || !(phi2 <= 6e-45)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_1 * (Math.sin(((lambda1 - lambda2) / 2.0)) * Math.sin((0.5 * lambda1)))))), Math.sqrt((1.0 - Math.pow(t_2, 2.0)))));
} else {
tmp = (R * 2.0) * Math.atan2(Math.hypot(t_0, (t_2 * Math.sqrt(t_1))), Math.sqrt((1.0 - (Math.pow(t_0, 2.0) + (Math.cos(phi1) * (0.5 + (-0.5 * Math.cos((lambda2 - lambda1)))))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin((phi1 * 0.5)) t_1 = math.cos(phi1) * math.cos(phi2) t_2 = math.sin((0.5 * (lambda1 - lambda2))) tmp = 0 if (phi2 <= -1.35e-64) or not (phi2 <= 6e-45): tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_1 * (math.sin(((lambda1 - lambda2) / 2.0)) * math.sin((0.5 * lambda1)))))), math.sqrt((1.0 - math.pow(t_2, 2.0))))) else: tmp = (R * 2.0) * math.atan2(math.hypot(t_0, (t_2 * math.sqrt(t_1))), math.sqrt((1.0 - (math.pow(t_0, 2.0) + (math.cos(phi1) * (0.5 + (-0.5 * math.cos((lambda2 - lambda1))))))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi1 * 0.5)) t_1 = Float64(cos(phi1) * cos(phi2)) t_2 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) tmp = 0.0 if ((phi2 <= -1.35e-64) || !(phi2 <= 6e-45)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_1 * Float64(sin(Float64(Float64(lambda1 - lambda2) / 2.0)) * sin(Float64(0.5 * lambda1)))))), sqrt(Float64(1.0 - (t_2 ^ 2.0)))))); else tmp = Float64(Float64(R * 2.0) * atan(hypot(t_0, Float64(t_2 * sqrt(t_1))), sqrt(Float64(1.0 - Float64((t_0 ^ 2.0) + Float64(cos(phi1) * Float64(0.5 + Float64(-0.5 * cos(Float64(lambda2 - lambda1)))))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin((phi1 * 0.5)); t_1 = cos(phi1) * cos(phi2); t_2 = sin((0.5 * (lambda1 - lambda2))); tmp = 0.0; if ((phi2 <= -1.35e-64) || ~((phi2 <= 6e-45))) tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (t_1 * (sin(((lambda1 - lambda2) / 2.0)) * sin((0.5 * lambda1)))))), sqrt((1.0 - (t_2 ^ 2.0))))); else tmp = (R * 2.0) * atan2(hypot(t_0, (t_2 * sqrt(t_1))), sqrt((1.0 - ((t_0 ^ 2.0) + (cos(phi1) * (0.5 + (-0.5 * cos((lambda2 - lambda1))))))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[phi2, -1.35e-64], N[Not[LessEqual[phi2, 6e-45]], $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$1 * N[(N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[t$95$2, 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[t$95$0 ^ 2 + N[(t$95$2 * N[Sqrt[t$95$1], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[t$95$0, 2.0], $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda2 - lambda1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
t_2 := \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\\
\mathbf{if}\;\phi_2 \leq -1.35 \cdot 10^{-64} \lor \neg \left(\phi_2 \leq 6 \cdot 10^{-45}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_1 \cdot \left(\sin \left(\frac{\lambda_1 - \lambda_2}{2}\right) \cdot \sin \left(0.5 \cdot \lambda_1\right)\right)}}{\sqrt{1 - {t\_2}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(t\_0, t\_2 \cdot \sqrt{t\_1}\right)}{\sqrt{1 - \left({t\_0}^{2} + \cos \phi_1 \cdot \left(0.5 + -0.5 \cdot \cos \left(\lambda_2 - \lambda_1\right)\right)\right)}}\\
\end{array}
\end{array}
if phi2 < -1.34999999999999993e-64 or 6.00000000000000022e-45 < phi2 Initial program 52.3%
associate-*l*52.3%
Simplified52.3%
Taylor expanded in phi1 around 0 41.8%
Taylor expanded in lambda2 around 0 32.7%
Taylor expanded in phi2 around 0 23.7%
if -1.34999999999999993e-64 < phi2 < 6.00000000000000022e-45Initial program 76.2%
associate-*r*76.2%
*-commutative76.2%
Simplified76.1%
Applied egg-rr55.0%
*-lft-identity55.0%
*-commutative55.0%
*-commutative55.0%
*-commutative55.0%
Simplified55.0%
Taylor expanded in phi2 around 0 54.1%
expm1-log1p-u54.0%
expm1-undefine54.0%
+-commutative54.0%
fma-define54.0%
Applied egg-rr54.0%
expm1-define54.0%
sub-neg54.0%
remove-double-neg54.0%
mul-1-neg54.0%
distribute-neg-in54.0%
+-commutative54.0%
cos-neg54.0%
mul-1-neg54.0%
unsub-neg54.0%
Simplified54.0%
Taylor expanded in phi2 around 0 54.1%
Final simplification36.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
: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 (* 0.5 lambda1))))))
(sqrt (- 1.0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((cos(phi1) * cos(phi2)) * (sin(((lambda1 - lambda2) / 2.0)) * sin((0.5 * lambda1)))))), sqrt((1.0 - pow(sin((0.5 * (lambda1 - lambda2))), 2.0)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
code = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + ((cos(phi1) * cos(phi2)) * (sin(((lambda1 - lambda2) / 2.0d0)) * sin((0.5d0 * lambda1)))))), sqrt((1.0d0 - (sin((0.5d0 * (lambda1 - lambda2))) ** 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.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((Math.cos(phi1) * Math.cos(phi2)) * (Math.sin(((lambda1 - lambda2) / 2.0)) * Math.sin((0.5 * lambda1)))))), Math.sqrt((1.0 - Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)))));
}
def code(R, lambda1, lambda2, phi1, phi2): return R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((math.cos(phi1) * math.cos(phi2)) * (math.sin(((lambda1 - lambda2) / 2.0)) * math.sin((0.5 * lambda1)))))), math.sqrt((1.0 - math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0)))))
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(cos(phi1) * cos(phi2)) * Float64(sin(Float64(Float64(lambda1 - lambda2) / 2.0)) * sin(Float64(0.5 * lambda1)))))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + ((cos(phi1) * cos(phi2)) * (sin(((lambda1 - lambda2) / 2.0)) * sin((0.5 * lambda1)))))), sqrt((1.0 - (sin((0.5 * (lambda1 - lambda2))) ^ 2.0))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(\sin \left(\frac{\lambda_1 - \lambda_2}{2}\right) \cdot \sin \left(0.5 \cdot \lambda_1\right)\right)}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}\right)
\end{array}
Initial program 62.0%
associate-*l*62.0%
Simplified62.0%
Taylor expanded in phi1 around 0 42.7%
Taylor expanded in lambda2 around 0 30.8%
Taylor expanded in phi2 around 0 26.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
(* R 2.0)
(atan2
(* (sin (* 0.5 (- lambda1 lambda2))) (+ 1.0 (* -0.25 (pow phi2 2.0))))
(sqrt
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (+ 0.5 (* -0.5 (cos (- lambda1 lambda2)))))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return (R * 2.0) * atan2((sin((0.5 * (lambda1 - lambda2))) * (1.0 + (-0.25 * pow(phi2, 2.0)))), sqrt((1.0 - fma(cos(phi1), (cos(phi2) * (0.5 + (-0.5 * cos((lambda1 - lambda2))))), pow(sin((0.5 * (phi1 - phi2))), 2.0)))));
}
function code(R, lambda1, lambda2, phi1, phi2) return Float64(Float64(R * 2.0) * atan(Float64(sin(Float64(0.5 * Float64(lambda1 - lambda2))) * Float64(1.0 + Float64(-0.25 * (phi2 ^ 2.0)))), sqrt(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2))))), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[(N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[(1.0 + N[(-0.25 * N[Power[phi2, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right) \cdot \left(1 + -0.25 \cdot {\phi_2}^{2}\right)}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \left(0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right), {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}}
\end{array}
Initial program 62.0%
associate-*r*62.0%
*-commutative62.0%
Simplified62.0%
Applied egg-rr38.9%
*-lft-identity38.9%
*-commutative38.9%
*-commutative38.9%
*-commutative38.9%
Simplified38.9%
Taylor expanded in phi2 around 0 28.8%
Taylor expanded in phi1 around 0 13.0%
Taylor expanded in phi2 around 0 16.0%
associate-*r*16.0%
distribute-rgt1-in16.0%
+-commutative16.0%
Simplified16.0%
Final simplification16.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
(* R 2.0)
(atan2
(sin (* 0.5 (- lambda1 lambda2)))
(sqrt
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (+ 0.5 (* -0.5 (cos (- lambda1 lambda2)))))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return (R * 2.0) * atan2(sin((0.5 * (lambda1 - lambda2))), sqrt((1.0 - fma(cos(phi1), (cos(phi2) * (0.5 + (-0.5 * cos((lambda1 - lambda2))))), pow(sin((0.5 * (phi1 - phi2))), 2.0)))));
}
function code(R, lambda1, lambda2, phi1, phi2) return Float64(Float64(R * 2.0) * atan(sin(Float64(0.5 * Float64(lambda1 - lambda2))), sqrt(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2))))), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \left(0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right), {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}}
\end{array}
Initial program 62.0%
associate-*r*62.0%
*-commutative62.0%
Simplified62.0%
Applied egg-rr38.9%
*-lft-identity38.9%
*-commutative38.9%
*-commutative38.9%
*-commutative38.9%
Simplified38.9%
Taylor expanded in phi2 around 0 28.8%
Taylor expanded in phi1 around 0 13.0%
Taylor expanded in phi2 around 0 15.5%
Final simplification15.5%
herbie shell --seed 2024169
(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))))))))))