
(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 (* (cos phi1) (cos phi2)))
(t_1 (sin (* phi1 0.5)))
(t_2 (cos (* phi1 0.5)))
(t_3 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (fma (cos (* -0.5 phi2)) t_1 (* (sin (* -0.5 phi2)) t_2)) 2.0)
(* t_3 (* t_0 t_3))))
(sqrt
(-
1.0
(+
(pow (- (* (cos (* phi2 0.5)) t_1) (* t_2 (sin (* phi2 0.5)))) 2.0)
(log
(+
1.0
(expm1
(*
t_0
(pow
(-
(* (sin (/ lambda1 2.0)) (cos (/ lambda2 2.0)))
(* (cos (/ lambda1 2.0)) (sin (/ lambda2 2.0))))
2.0)))))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = sin((phi1 * 0.5));
double t_2 = cos((phi1 * 0.5));
double t_3 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((pow(fma(cos((-0.5 * phi2)), t_1, (sin((-0.5 * phi2)) * t_2)), 2.0) + (t_3 * (t_0 * t_3)))), sqrt((1.0 - (pow(((cos((phi2 * 0.5)) * t_1) - (t_2 * sin((phi2 * 0.5)))), 2.0) + log((1.0 + expm1((t_0 * pow(((sin((lambda1 / 2.0)) * cos((lambda2 / 2.0))) - (cos((lambda1 / 2.0)) * sin((lambda2 / 2.0)))), 2.0))))))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(phi1 * 0.5)) t_2 = cos(Float64(phi1 * 0.5)) t_3 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((fma(cos(Float64(-0.5 * phi2)), t_1, Float64(sin(Float64(-0.5 * phi2)) * t_2)) ^ 2.0) + Float64(t_3 * Float64(t_0 * t_3)))), sqrt(Float64(1.0 - Float64((Float64(Float64(cos(Float64(phi2 * 0.5)) * t_1) - Float64(t_2 * sin(Float64(phi2 * 0.5)))) ^ 2.0) + log(Float64(1.0 + expm1(Float64(t_0 * (Float64(Float64(sin(Float64(lambda1 / 2.0)) * cos(Float64(lambda2 / 2.0))) - Float64(cos(Float64(lambda1 / 2.0)) * sin(Float64(lambda2 / 2.0)))) ^ 2.0))))))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$1 + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$3 * N[(t$95$0 * t$95$3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[(N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * t$95$1), $MachinePrecision] - N[(t$95$2 * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[Log[N[(1.0 + N[(Exp[N[(t$95$0 * N[Power[N[(N[(N[Sin[N[(lambda1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(lambda2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(lambda1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(lambda2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]] - 1), $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(\phi_1 \cdot 0.5\right)\\
t_2 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_3 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(\cos \left(-0.5 \cdot \phi_2\right), t\_1, \sin \left(-0.5 \cdot \phi_2\right) \cdot t\_2\right)\right)}^{2} + t\_3 \cdot \left(t\_0 \cdot t\_3\right)}}{\sqrt{1 - \left({\left(\cos \left(\phi_2 \cdot 0.5\right) \cdot t\_1 - t\_2 \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2} + \log \left(1 + \mathsf{expm1}\left(t\_0 \cdot {\left(\sin \left(\frac{\lambda_1}{2}\right) \cdot \cos \left(\frac{\lambda_2}{2}\right) - \cos \left(\frac{\lambda_1}{2}\right) \cdot \sin \left(\frac{\lambda_2}{2}\right)\right)}^{2}\right)\right)\right)}}\right)
\end{array}
\end{array}
Initial program 63.1%
div-sub63.1%
sin-diff63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
Applied egg-rr63.9%
*-commutative63.9%
*-commutative63.9%
fmm-def63.9%
cos-neg63.9%
distribute-rgt-neg-in63.9%
metadata-eval63.9%
*-commutative63.9%
*-commutative63.9%
*-commutative63.9%
*-commutative63.9%
distribute-lft-neg-in63.9%
sin-neg63.9%
distribute-rgt-neg-in63.9%
metadata-eval63.9%
*-commutative63.9%
*-commutative63.9%
Simplified63.9%
div-sub63.1%
sin-diff63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
Applied egg-rr77.7%
log1p-expm1-u77.7%
log1p-undefine77.8%
associate-*l*77.8%
pow277.8%
div-inv77.8%
metadata-eval77.8%
*-commutative77.8%
Applied egg-rr77.8%
*-commutative77.8%
metadata-eval77.8%
div-inv77.8%
div-sub77.8%
sin-diff78.3%
Applied egg-rr78.3%
Final simplification78.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (* phi1 0.5)))
(t_2 (cos (* phi1 0.5)))
(t_3 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (fma (cos (* -0.5 phi2)) t_1 (* (sin (* -0.5 phi2)) t_2)) 2.0)
(* t_3 (* t_0 t_3))))
(sqrt
(-
1.0
(+
(pow (- (* (cos (* phi2 0.5)) t_1) (* t_2 (sin (* phi2 0.5)))) 2.0)
(log
(+
1.0
(expm1
(* t_0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = sin((phi1 * 0.5));
double t_2 = cos((phi1 * 0.5));
double t_3 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((pow(fma(cos((-0.5 * phi2)), t_1, (sin((-0.5 * phi2)) * t_2)), 2.0) + (t_3 * (t_0 * t_3)))), sqrt((1.0 - (pow(((cos((phi2 * 0.5)) * t_1) - (t_2 * sin((phi2 * 0.5)))), 2.0) + log((1.0 + expm1((t_0 * pow(sin((0.5 * (lambda1 - lambda2))), 2.0))))))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(phi1 * 0.5)) t_2 = cos(Float64(phi1 * 0.5)) t_3 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((fma(cos(Float64(-0.5 * phi2)), t_1, Float64(sin(Float64(-0.5 * phi2)) * t_2)) ^ 2.0) + Float64(t_3 * Float64(t_0 * t_3)))), sqrt(Float64(1.0 - Float64((Float64(Float64(cos(Float64(phi2 * 0.5)) * t_1) - Float64(t_2 * sin(Float64(phi2 * 0.5)))) ^ 2.0) + log(Float64(1.0 + expm1(Float64(t_0 * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0))))))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$1 + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$3 * N[(t$95$0 * t$95$3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[(N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * t$95$1), $MachinePrecision] - N[(t$95$2 * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[Log[N[(1.0 + N[(Exp[N[(t$95$0 * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]] - 1), $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(\phi_1 \cdot 0.5\right)\\
t_2 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_3 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(\cos \left(-0.5 \cdot \phi_2\right), t\_1, \sin \left(-0.5 \cdot \phi_2\right) \cdot t\_2\right)\right)}^{2} + t\_3 \cdot \left(t\_0 \cdot t\_3\right)}}{\sqrt{1 - \left({\left(\cos \left(\phi_2 \cdot 0.5\right) \cdot t\_1 - t\_2 \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2} + \log \left(1 + \mathsf{expm1}\left(t\_0 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\right)\right)\right)}}\right)
\end{array}
\end{array}
Initial program 63.1%
div-sub63.1%
sin-diff63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
Applied egg-rr63.9%
*-commutative63.9%
*-commutative63.9%
fmm-def63.9%
cos-neg63.9%
distribute-rgt-neg-in63.9%
metadata-eval63.9%
*-commutative63.9%
*-commutative63.9%
*-commutative63.9%
*-commutative63.9%
distribute-lft-neg-in63.9%
sin-neg63.9%
distribute-rgt-neg-in63.9%
metadata-eval63.9%
*-commutative63.9%
*-commutative63.9%
Simplified63.9%
div-sub63.1%
sin-diff63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
Applied egg-rr77.7%
log1p-expm1-u77.7%
log1p-undefine77.8%
associate-*l*77.8%
pow277.8%
div-inv77.8%
metadata-eval77.8%
*-commutative77.8%
Applied egg-rr77.8%
Final simplification77.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_1 (cos (* phi1 0.5)))
(t_2 (sin (* phi1 0.5)))
(t_3 (sin (/ (- lambda1 lambda2) 2.0)))
(t_4 (* t_3 (* (* (cos phi1) (cos phi2)) t_3)))
(t_5
(pow (fma (cos (* -0.5 phi2)) t_2 (* (sin (* -0.5 phi2)) t_1)) 2.0)))
(if (or (<= t_3 -0.005) (not (<= t_3 0.2)))
(*
R
(*
2.0
(atan2
(sqrt (+ t_5 t_4))
(sqrt
(fabs
(-
1.0
(fma
(cos phi1)
(* (cos phi2) t_0)
(pow (sin (* 0.5 (- phi1 phi2))) 2.0))))))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_5 (* (cos phi1) t_0)))
(sqrt
(-
1.0
(+
t_4
(pow
(- (* (cos (* phi2 0.5)) t_2) (* t_1 (sin (* phi2 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 = cos((phi1 * 0.5));
double t_2 = sin((phi1 * 0.5));
double t_3 = sin(((lambda1 - lambda2) / 2.0));
double t_4 = t_3 * ((cos(phi1) * cos(phi2)) * t_3);
double t_5 = pow(fma(cos((-0.5 * phi2)), t_2, (sin((-0.5 * phi2)) * t_1)), 2.0);
double tmp;
if ((t_3 <= -0.005) || !(t_3 <= 0.2)) {
tmp = R * (2.0 * atan2(sqrt((t_5 + t_4)), sqrt(fabs((1.0 - fma(cos(phi1), (cos(phi2) * t_0), pow(sin((0.5 * (phi1 - phi2))), 2.0)))))));
} else {
tmp = R * (2.0 * atan2(sqrt((t_5 + (cos(phi1) * t_0))), sqrt((1.0 - (t_4 + pow(((cos((phi2 * 0.5)) * t_2) - (t_1 * sin((phi2 * 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 = cos(Float64(phi1 * 0.5)) t_2 = sin(Float64(phi1 * 0.5)) t_3 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_4 = Float64(t_3 * Float64(Float64(cos(phi1) * cos(phi2)) * t_3)) t_5 = fma(cos(Float64(-0.5 * phi2)), t_2, Float64(sin(Float64(-0.5 * phi2)) * t_1)) ^ 2.0 tmp = 0.0 if ((t_3 <= -0.005) || !(t_3 <= 0.2)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_5 + t_4)), sqrt(abs(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * t_0), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_5 + Float64(cos(phi1) * t_0))), sqrt(Float64(1.0 - Float64(t_4 + (Float64(Float64(cos(Float64(phi2 * 0.5)) * t_2) - Float64(t_1 * sin(Float64(phi2 * 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[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[(t$95$3 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$3), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[Power[N[(N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$2 + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[t$95$3, -0.005], N[Not[LessEqual[t$95$3, 0.2]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$5 + t$95$4), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[Abs[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$5 + N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$4 + N[Power[N[(N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * t$95$2), $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(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_1 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_2 := \sin \left(\phi_1 \cdot 0.5\right)\\
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_5 := {\left(\mathsf{fma}\left(\cos \left(-0.5 \cdot \phi_2\right), t\_2, \sin \left(-0.5 \cdot \phi_2\right) \cdot t\_1\right)\right)}^{2}\\
\mathbf{if}\;t\_3 \leq -0.005 \lor \neg \left(t\_3 \leq 0.2\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_5 + t\_4}}{\sqrt{\left|1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot t\_0, {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)\right|}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_5 + \cos \phi_1 \cdot t\_0}}{\sqrt{1 - \left(t\_4 + {\left(\cos \left(\phi_2 \cdot 0.5\right) \cdot t\_2 - t\_1 \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\right)}}\right)\\
\end{array}
\end{array}
if (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < -0.0050000000000000001 or 0.20000000000000001 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) Initial program 58.2%
div-sub58.2%
sin-diff59.0%
div-inv59.0%
metadata-eval59.0%
div-inv59.0%
metadata-eval59.0%
div-inv59.0%
metadata-eval59.0%
div-inv59.0%
metadata-eval59.0%
Applied egg-rr59.0%
*-commutative59.0%
*-commutative59.0%
fmm-def59.0%
cos-neg59.0%
distribute-rgt-neg-in59.0%
metadata-eval59.0%
*-commutative59.0%
*-commutative59.0%
*-commutative59.0%
*-commutative59.0%
distribute-lft-neg-in59.0%
sin-neg59.0%
distribute-rgt-neg-in59.0%
metadata-eval59.0%
*-commutative59.0%
*-commutative59.0%
Simplified59.0%
add-sqr-sqrt59.0%
pow1/259.0%
pow1/259.0%
pow-prod-down59.5%
Applied egg-rr59.5%
Simplified59.5%
if -0.0050000000000000001 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < 0.20000000000000001Initial program 75.9%
div-sub75.9%
sin-diff76.6%
div-inv76.6%
metadata-eval76.6%
div-inv76.6%
metadata-eval76.6%
div-inv76.6%
metadata-eval76.6%
div-inv76.6%
metadata-eval76.6%
Applied egg-rr76.6%
*-commutative76.6%
*-commutative76.6%
fmm-def76.6%
cos-neg76.6%
distribute-rgt-neg-in76.6%
metadata-eval76.6%
*-commutative76.6%
*-commutative76.6%
*-commutative76.6%
*-commutative76.6%
distribute-lft-neg-in76.6%
sin-neg76.6%
distribute-rgt-neg-in76.6%
metadata-eval76.6%
*-commutative76.6%
*-commutative76.6%
Simplified76.6%
div-sub75.9%
sin-diff76.6%
div-inv76.6%
metadata-eval76.6%
div-inv76.6%
metadata-eval76.6%
div-inv76.6%
metadata-eval76.6%
div-inv76.6%
metadata-eval76.6%
Applied egg-rr97.4%
Taylor expanded in phi2 around 0 94.0%
Final simplification69.1%
(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 63.1%
div-sub63.1%
sin-diff63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
Applied egg-rr63.9%
*-commutative63.9%
*-commutative63.9%
fmm-def63.9%
cos-neg63.9%
distribute-rgt-neg-in63.9%
metadata-eval63.9%
*-commutative63.9%
*-commutative63.9%
*-commutative63.9%
*-commutative63.9%
distribute-lft-neg-in63.9%
sin-neg63.9%
distribute-rgt-neg-in63.9%
metadata-eval63.9%
*-commutative63.9%
*-commutative63.9%
Simplified63.9%
div-sub63.1%
sin-diff63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
Applied egg-rr77.7%
Final simplification77.7%
(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 -0.000225) (not (<= lambda1 2.5e+14)))
(*
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
(+
t_2
(* (cos phi1) (* (cos phi2) (pow (sin (* -0.5 lambda2)) 2.0)))))
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 <= -0.000225) || !(lambda1 <= 2.5e+14)) {
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((t_2 + (cos(phi1) * (cos(phi2) * pow(sin((-0.5 * lambda2)), 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 = 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 <= (-0.000225d0)) .or. (.not. (lambda1 <= 2.5d+14))) 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((t_2 + (cos(phi1) * (cos(phi2) * (sin(((-0.5d0) * lambda2)) ** 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.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 <= -0.000225) || !(lambda1 <= 2.5e+14)) {
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((t_2 + (Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((-0.5 * lambda2)), 2.0))))), 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 <= -0.000225) or not (lambda1 <= 2.5e+14): 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((t_2 + (math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((-0.5 * lambda2)), 2.0))))), 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 <= -0.000225) || !(lambda1 <= 2.5e+14)) 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(t_2 + Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(-0.5 * lambda2)) ^ 2.0))))), 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 <= -0.000225) || ~((lambda1 <= 2.5e+14))) 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((t_2 + (cos(phi1) * (cos(phi2) * (sin((-0.5 * lambda2)) ^ 2.0))))), 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, -0.000225], N[Not[LessEqual[lambda1, 2.5e+14]], $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[(t$95$2 + 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]), $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 -0.000225 \lor \neg \left(\lambda_1 \leq 2.5 \cdot 10^{+14}\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{t\_2 + \cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(-0.5 \cdot \lambda_2\right)}^{2}\right)}}{t\_4}\right)\\
\end{array}
\end{array}
if lambda1 < -2.2499999999999999e-4 or 2.5e14 < lambda1 Initial program 47.9%
div-sub47.9%
sin-diff48.7%
div-inv48.7%
metadata-eval48.7%
div-inv48.7%
metadata-eval48.7%
div-inv48.7%
metadata-eval48.7%
div-inv48.7%
metadata-eval48.7%
Applied egg-rr48.7%
*-commutative48.7%
*-commutative48.7%
fmm-def48.7%
cos-neg48.7%
distribute-rgt-neg-in48.7%
metadata-eval48.7%
*-commutative48.7%
*-commutative48.7%
*-commutative48.7%
*-commutative48.7%
distribute-lft-neg-in48.7%
sin-neg48.7%
distribute-rgt-neg-in48.7%
metadata-eval48.7%
*-commutative48.7%
*-commutative48.7%
Simplified48.7%
div-sub47.9%
sin-diff48.7%
div-inv48.7%
metadata-eval48.7%
div-inv48.7%
metadata-eval48.7%
div-inv48.7%
metadata-eval48.7%
div-inv48.7%
metadata-eval48.7%
Applied egg-rr61.7%
Taylor expanded in lambda2 around 0 61.5%
if -2.2499999999999999e-4 < lambda1 < 2.5e14Initial program 79.8%
div-sub79.8%
sin-diff80.5%
div-inv80.5%
metadata-eval80.5%
div-inv80.5%
metadata-eval80.5%
div-inv80.5%
metadata-eval80.5%
div-inv80.5%
metadata-eval80.5%
Applied egg-rr80.5%
*-commutative80.5%
*-commutative80.5%
fmm-def80.5%
cos-neg80.5%
distribute-rgt-neg-in80.5%
metadata-eval80.5%
*-commutative80.5%
*-commutative80.5%
*-commutative80.5%
*-commutative80.5%
distribute-lft-neg-in80.5%
sin-neg80.5%
distribute-rgt-neg-in80.5%
metadata-eval80.5%
*-commutative80.5%
*-commutative80.5%
Simplified80.5%
div-sub79.8%
sin-diff80.5%
div-inv80.5%
metadata-eval80.5%
div-inv80.5%
metadata-eval80.5%
div-inv80.5%
metadata-eval80.5%
div-inv80.5%
metadata-eval80.5%
Applied egg-rr95.3%
Taylor expanded in lambda1 around 0 94.5%
Final simplification77.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (* phi1 0.5)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (* t_1 (* (* (cos phi1) (cos phi2)) t_1)))
(t_3 (cos (* -0.5 phi2)))
(t_4 (sin (* phi1 0.5)))
(t_5 (* (sin (* -0.5 phi2)) t_0)))
(if (or (<= lambda1 -11000.0) (not (<= lambda1 1.8e-55)))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (fma t_3 t_4 t_5) 2.0) t_2))
(sqrt
(fabs
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0))))))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (+ (* t_3 t_4) t_5) 2.0)
(* (cos phi1) (* (cos phi2) (pow (sin (* -0.5 lambda2)) 2.0)))))
(sqrt
(-
1.0
(+
t_2
(pow
(- (* (cos (* phi2 0.5)) t_4) (* t_0 (sin (* phi2 0.5))))
2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((phi1 * 0.5));
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = t_1 * ((cos(phi1) * cos(phi2)) * t_1);
double t_3 = cos((-0.5 * phi2));
double t_4 = sin((phi1 * 0.5));
double t_5 = sin((-0.5 * phi2)) * t_0;
double tmp;
if ((lambda1 <= -11000.0) || !(lambda1 <= 1.8e-55)) {
tmp = R * (2.0 * atan2(sqrt((pow(fma(t_3, t_4, t_5), 2.0) + t_2)), sqrt(fabs((1.0 - fma(cos(phi1), (cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0)), pow(sin((0.5 * (phi1 - phi2))), 2.0)))))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(((t_3 * t_4) + t_5), 2.0) + (cos(phi1) * (cos(phi2) * pow(sin((-0.5 * lambda2)), 2.0))))), sqrt((1.0 - (t_2 + pow(((cos((phi2 * 0.5)) * t_4) - (t_0 * sin((phi2 * 0.5)))), 2.0))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(phi1 * 0.5)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(t_1 * Float64(Float64(cos(phi1) * cos(phi2)) * t_1)) t_3 = cos(Float64(-0.5 * phi2)) t_4 = sin(Float64(phi1 * 0.5)) t_5 = Float64(sin(Float64(-0.5 * phi2)) * t_0) tmp = 0.0 if ((lambda1 <= -11000.0) || !(lambda1 <= 1.8e-55)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((fma(t_3, t_4, t_5) ^ 2.0) + t_2)), sqrt(abs(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((Float64(Float64(t_3 * t_4) + t_5) ^ 2.0) + Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(-0.5 * lambda2)) ^ 2.0))))), sqrt(Float64(1.0 - Float64(t_2 + (Float64(Float64(cos(Float64(phi2 * 0.5)) * t_4) - Float64(t_0 * sin(Float64(phi2 * 0.5)))) ^ 2.0))))))); end return 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[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(t$95$1 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$5 = N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision]}, If[Or[LessEqual[lambda1, -11000.0], N[Not[LessEqual[lambda1, 1.8e-55]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(t$95$3 * t$95$4 + t$95$5), $MachinePrecision], 2.0], $MachinePrecision] + t$95$2), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[Abs[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[(t$95$3 * t$95$4), $MachinePrecision] + t$95$5), $MachinePrecision], 2.0], $MachinePrecision] + 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]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$2 + N[Power[N[(N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * t$95$4), $MachinePrecision] - N[(t$95$0 * 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 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := t\_1 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_1\right)\\
t_3 := \cos \left(-0.5 \cdot \phi_2\right)\\
t_4 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_5 := \sin \left(-0.5 \cdot \phi_2\right) \cdot t\_0\\
\mathbf{if}\;\lambda_1 \leq -11000 \lor \neg \left(\lambda_1 \leq 1.8 \cdot 10^{-55}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(t\_3, t\_4, t\_5\right)\right)}^{2} + t\_2}}{\sqrt{\left|1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}, {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)\right|}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(t\_3 \cdot t\_4 + t\_5\right)}^{2} + \cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(-0.5 \cdot \lambda_2\right)}^{2}\right)}}{\sqrt{1 - \left(t\_2 + {\left(\cos \left(\phi_2 \cdot 0.5\right) \cdot t\_4 - t\_0 \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\right)}}\right)\\
\end{array}
\end{array}
if lambda1 < -11000 or 1.8e-55 < lambda1 Initial program 51.9%
div-sub51.9%
sin-diff52.6%
div-inv52.6%
metadata-eval52.6%
div-inv52.6%
metadata-eval52.6%
div-inv52.6%
metadata-eval52.6%
div-inv52.6%
metadata-eval52.6%
Applied egg-rr52.6%
*-commutative52.6%
*-commutative52.6%
fmm-def52.6%
cos-neg52.6%
distribute-rgt-neg-in52.6%
metadata-eval52.6%
*-commutative52.6%
*-commutative52.6%
*-commutative52.6%
*-commutative52.6%
distribute-lft-neg-in52.6%
sin-neg52.6%
distribute-rgt-neg-in52.6%
metadata-eval52.6%
*-commutative52.6%
*-commutative52.6%
Simplified52.6%
add-sqr-sqrt52.6%
pow1/252.6%
pow1/252.6%
pow-prod-down53.0%
Applied egg-rr53.0%
Simplified53.0%
if -11000 < lambda1 < 1.8e-55Initial program 77.7%
div-sub77.7%
sin-diff78.7%
div-inv78.7%
metadata-eval78.7%
div-inv78.7%
metadata-eval78.7%
div-inv78.7%
metadata-eval78.7%
div-inv78.7%
metadata-eval78.7%
Applied egg-rr78.7%
*-commutative78.7%
*-commutative78.7%
fmm-def78.7%
cos-neg78.7%
distribute-rgt-neg-in78.7%
metadata-eval78.7%
*-commutative78.7%
*-commutative78.7%
*-commutative78.7%
*-commutative78.7%
distribute-lft-neg-in78.7%
sin-neg78.7%
distribute-rgt-neg-in78.7%
metadata-eval78.7%
*-commutative78.7%
*-commutative78.7%
Simplified78.7%
div-sub77.7%
sin-diff78.7%
div-inv78.7%
metadata-eval78.7%
div-inv78.7%
metadata-eval78.7%
div-inv78.7%
metadata-eval78.7%
div-inv78.7%
metadata-eval78.7%
Applied egg-rr95.0%
Taylor expanded in lambda1 around 0 94.3%
Final simplification70.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_1 (* (cos phi1) t_0))
(t_2 (sin (* phi1 0.5)))
(t_3 (cos (* phi1 0.5)))
(t_4
(pow (fma (cos (* -0.5 phi2)) t_2 (* (sin (* -0.5 phi2)) t_3)) 2.0))
(t_5
(pow (- (* (cos (* phi2 0.5)) t_2) (* t_3 (sin (* phi2 0.5)))) 2.0))
(t_6 (sin (/ (- lambda1 lambda2) 2.0)))
(t_7 (* t_6 (* (* (cos phi1) (cos phi2)) t_6)))
(t_8 (sqrt (- 1.0 (+ t_7 t_5)))))
(if (<= phi1 -450.0)
(* R (* 2.0 (atan2 (sqrt (+ t_4 t_7)) (sqrt (- 1.0 (+ t_5 t_1))))))
(if (<= phi1 1.3e-15)
(* R (* 2.0 (atan2 (sqrt (+ t_4 (* (cos phi2) t_0))) t_8)))
(* R (* 2.0 (atan2 (sqrt (+ t_4 t_1)) t_8)))))))
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(phi1) * t_0;
double t_2 = sin((phi1 * 0.5));
double t_3 = cos((phi1 * 0.5));
double t_4 = pow(fma(cos((-0.5 * phi2)), t_2, (sin((-0.5 * phi2)) * t_3)), 2.0);
double t_5 = pow(((cos((phi2 * 0.5)) * t_2) - (t_3 * sin((phi2 * 0.5)))), 2.0);
double t_6 = sin(((lambda1 - lambda2) / 2.0));
double t_7 = t_6 * ((cos(phi1) * cos(phi2)) * t_6);
double t_8 = sqrt((1.0 - (t_7 + t_5)));
double tmp;
if (phi1 <= -450.0) {
tmp = R * (2.0 * atan2(sqrt((t_4 + t_7)), sqrt((1.0 - (t_5 + t_1)))));
} else if (phi1 <= 1.3e-15) {
tmp = R * (2.0 * atan2(sqrt((t_4 + (cos(phi2) * t_0))), t_8));
} else {
tmp = R * (2.0 * atan2(sqrt((t_4 + t_1)), t_8));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_1 = Float64(cos(phi1) * t_0) t_2 = sin(Float64(phi1 * 0.5)) t_3 = cos(Float64(phi1 * 0.5)) t_4 = fma(cos(Float64(-0.5 * phi2)), t_2, Float64(sin(Float64(-0.5 * phi2)) * t_3)) ^ 2.0 t_5 = Float64(Float64(cos(Float64(phi2 * 0.5)) * t_2) - Float64(t_3 * sin(Float64(phi2 * 0.5)))) ^ 2.0 t_6 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_7 = Float64(t_6 * Float64(Float64(cos(phi1) * cos(phi2)) * t_6)) t_8 = sqrt(Float64(1.0 - Float64(t_7 + t_5))) tmp = 0.0 if (phi1 <= -450.0) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_4 + t_7)), sqrt(Float64(1.0 - Float64(t_5 + t_1)))))); elseif (phi1 <= 1.3e-15) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_4 + Float64(cos(phi2) * t_0))), t_8))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_4 + t_1)), t_8))); 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[phi1], $MachinePrecision] * t$95$0), $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[Power[N[(N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$2 + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$3), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$5 = 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]}, Block[{t$95$6 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$7 = N[(t$95$6 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$6), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$8 = N[Sqrt[N[(1.0 - N[(t$95$7 + t$95$5), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi1, -450.0], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$4 + t$95$7), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$5 + t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[phi1, 1.3e-15], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$4 + N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$8], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$4 + t$95$1), $MachinePrecision]], $MachinePrecision] / t$95$8], $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_1 \cdot t\_0\\
t_2 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_3 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_4 := {\left(\mathsf{fma}\left(\cos \left(-0.5 \cdot \phi_2\right), t\_2, \sin \left(-0.5 \cdot \phi_2\right) \cdot t\_3\right)\right)}^{2}\\
t_5 := {\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}\\
t_6 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_7 := t\_6 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_6\right)\\
t_8 := \sqrt{1 - \left(t\_7 + t\_5\right)}\\
\mathbf{if}\;\phi_1 \leq -450:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_4 + t\_7}}{\sqrt{1 - \left(t\_5 + t\_1\right)}}\right)\\
\mathbf{elif}\;\phi_1 \leq 1.3 \cdot 10^{-15}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_4 + \cos \phi_2 \cdot t\_0}}{t\_8}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_4 + t\_1}}{t\_8}\right)\\
\end{array}
\end{array}
if phi1 < -450Initial program 44.0%
div-sub44.0%
sin-diff45.7%
div-inv45.7%
metadata-eval45.7%
div-inv45.7%
metadata-eval45.7%
div-inv45.7%
metadata-eval45.7%
div-inv45.7%
metadata-eval45.7%
Applied egg-rr45.7%
*-commutative45.7%
*-commutative45.7%
fmm-def45.7%
cos-neg45.7%
distribute-rgt-neg-in45.7%
metadata-eval45.7%
*-commutative45.7%
*-commutative45.7%
*-commutative45.7%
*-commutative45.7%
distribute-lft-neg-in45.7%
sin-neg45.7%
distribute-rgt-neg-in45.7%
metadata-eval45.7%
*-commutative45.7%
*-commutative45.7%
Simplified45.7%
div-sub44.0%
sin-diff45.7%
div-inv45.7%
metadata-eval45.7%
div-inv45.7%
metadata-eval45.7%
div-inv45.7%
metadata-eval45.7%
div-inv45.7%
metadata-eval45.7%
Applied egg-rr71.0%
Taylor expanded in phi2 around 0 56.8%
if -450 < phi1 < 1.30000000000000002e-15Initial program 79.0%
div-sub79.0%
sin-diff79.1%
div-inv79.1%
metadata-eval79.1%
div-inv79.1%
metadata-eval79.1%
div-inv79.1%
metadata-eval79.1%
div-inv79.1%
metadata-eval79.1%
Applied egg-rr79.1%
*-commutative79.1%
*-commutative79.1%
fmm-def79.1%
cos-neg79.1%
distribute-rgt-neg-in79.1%
metadata-eval79.1%
*-commutative79.1%
*-commutative79.1%
*-commutative79.1%
*-commutative79.1%
distribute-lft-neg-in79.1%
sin-neg79.1%
distribute-rgt-neg-in79.1%
metadata-eval79.1%
*-commutative79.1%
*-commutative79.1%
Simplified79.1%
div-sub79.0%
sin-diff79.1%
div-inv79.1%
metadata-eval79.1%
div-inv79.1%
metadata-eval79.1%
div-inv79.1%
metadata-eval79.1%
div-inv79.1%
metadata-eval79.1%
Applied egg-rr79.9%
Taylor expanded in phi1 around 0 79.5%
*-commutative79.5%
Simplified79.5%
if 1.30000000000000002e-15 < phi1 Initial program 49.9%
div-sub49.9%
sin-diff51.4%
div-inv51.4%
metadata-eval51.4%
div-inv51.4%
metadata-eval51.4%
div-inv51.4%
metadata-eval51.4%
div-inv51.4%
metadata-eval51.4%
Applied egg-rr51.4%
*-commutative51.4%
*-commutative51.4%
fmm-def51.4%
cos-neg51.4%
distribute-rgt-neg-in51.4%
metadata-eval51.4%
*-commutative51.4%
*-commutative51.4%
*-commutative51.4%
*-commutative51.4%
distribute-lft-neg-in51.4%
sin-neg51.4%
distribute-rgt-neg-in51.4%
metadata-eval51.4%
*-commutative51.4%
*-commutative51.4%
Simplified51.4%
div-sub49.9%
sin-diff51.4%
div-inv51.4%
metadata-eval51.4%
div-inv51.4%
metadata-eval51.4%
div-inv51.4%
metadata-eval51.4%
div-inv51.4%
metadata-eval51.4%
Applied egg-rr79.7%
Taylor expanded in phi2 around 0 61.0%
Final simplification69.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
(t_1 (cos (* -0.5 phi2)))
(t_2 (sin (* phi1 0.5)))
(t_3 (cos (* phi1 0.5)))
(t_4 (sin (/ (- lambda1 lambda2) 2.0)))
(t_5 (* t_4 (* (* (cos phi1) (cos phi2)) t_4)))
(t_6 (sin (* -0.5 phi2)))
(t_7 (pow (fma t_1 t_2 (* t_6 t_3)) 2.0))
(t_8
(pow (- (* (cos (* phi2 0.5)) t_2) (* t_3 (sin (* phi2 0.5)))) 2.0))
(t_9 (sqrt (- 1.0 (+ t_5 t_8)))))
(if (<= phi1 -440.0)
(* R (* 2.0 (atan2 (sqrt (+ t_7 t_5)) (sqrt (- 1.0 (+ t_8 t_0))))))
(if (<= phi1 0.00245)
(*
R
(*
2.0
(atan2
(sqrt
(+
t_5
(pow
(+ t_6 (* phi1 (+ (* -0.125 (* phi1 t_6)) (* t_1 0.5))))
2.0)))
t_9)))
(* R (* 2.0 (atan2 (sqrt (+ t_7 t_0)) t_9)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = cos((-0.5 * phi2));
double t_2 = sin((phi1 * 0.5));
double t_3 = cos((phi1 * 0.5));
double t_4 = sin(((lambda1 - lambda2) / 2.0));
double t_5 = t_4 * ((cos(phi1) * cos(phi2)) * t_4);
double t_6 = sin((-0.5 * phi2));
double t_7 = pow(fma(t_1, t_2, (t_6 * t_3)), 2.0);
double t_8 = pow(((cos((phi2 * 0.5)) * t_2) - (t_3 * sin((phi2 * 0.5)))), 2.0);
double t_9 = sqrt((1.0 - (t_5 + t_8)));
double tmp;
if (phi1 <= -440.0) {
tmp = R * (2.0 * atan2(sqrt((t_7 + t_5)), sqrt((1.0 - (t_8 + t_0)))));
} else if (phi1 <= 0.00245) {
tmp = R * (2.0 * atan2(sqrt((t_5 + pow((t_6 + (phi1 * ((-0.125 * (phi1 * t_6)) + (t_1 * 0.5)))), 2.0))), t_9));
} else {
tmp = R * (2.0 * atan2(sqrt((t_7 + t_0)), t_9));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)) t_1 = cos(Float64(-0.5 * phi2)) t_2 = sin(Float64(phi1 * 0.5)) t_3 = cos(Float64(phi1 * 0.5)) t_4 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_5 = Float64(t_4 * Float64(Float64(cos(phi1) * cos(phi2)) * t_4)) t_6 = sin(Float64(-0.5 * phi2)) t_7 = fma(t_1, t_2, Float64(t_6 * t_3)) ^ 2.0 t_8 = Float64(Float64(cos(Float64(phi2 * 0.5)) * t_2) - Float64(t_3 * sin(Float64(phi2 * 0.5)))) ^ 2.0 t_9 = sqrt(Float64(1.0 - Float64(t_5 + t_8))) tmp = 0.0 if (phi1 <= -440.0) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_7 + t_5)), sqrt(Float64(1.0 - Float64(t_8 + t_0)))))); elseif (phi1 <= 0.00245) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_5 + (Float64(t_6 + Float64(phi1 * Float64(Float64(-0.125 * Float64(phi1 * t_6)) + Float64(t_1 * 0.5)))) ^ 2.0))), t_9))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_7 + t_0)), t_9))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(-0.5 * phi2), $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[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$5 = N[(t$95$4 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$4), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$6 = N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$7 = N[Power[N[(t$95$1 * t$95$2 + N[(t$95$6 * t$95$3), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$8 = 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]}, Block[{t$95$9 = N[Sqrt[N[(1.0 - N[(t$95$5 + t$95$8), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi1, -440.0], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$7 + t$95$5), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$8 + t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[phi1, 0.00245], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$5 + N[Power[N[(t$95$6 + N[(phi1 * N[(N[(-0.125 * N[(phi1 * t$95$6), $MachinePrecision]), $MachinePrecision] + N[(t$95$1 * 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$9], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$7 + t$95$0), $MachinePrecision]], $MachinePrecision] / t$95$9], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_1 := \cos \left(-0.5 \cdot \phi_2\right)\\
t_2 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_3 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_4 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_5 := t\_4 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_4\right)\\
t_6 := \sin \left(-0.5 \cdot \phi_2\right)\\
t_7 := {\left(\mathsf{fma}\left(t\_1, t\_2, t\_6 \cdot t\_3\right)\right)}^{2}\\
t_8 := {\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}\\
t_9 := \sqrt{1 - \left(t\_5 + t\_8\right)}\\
\mathbf{if}\;\phi_1 \leq -440:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_7 + t\_5}}{\sqrt{1 - \left(t\_8 + t\_0\right)}}\right)\\
\mathbf{elif}\;\phi_1 \leq 0.00245:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_5 + {\left(t\_6 + \phi_1 \cdot \left(-0.125 \cdot \left(\phi_1 \cdot t\_6\right) + t\_1 \cdot 0.5\right)\right)}^{2}}}{t\_9}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_7 + t\_0}}{t\_9}\right)\\
\end{array}
\end{array}
if phi1 < -440Initial program 44.0%
div-sub44.0%
sin-diff45.7%
div-inv45.7%
metadata-eval45.7%
div-inv45.7%
metadata-eval45.7%
div-inv45.7%
metadata-eval45.7%
div-inv45.7%
metadata-eval45.7%
Applied egg-rr45.7%
*-commutative45.7%
*-commutative45.7%
fmm-def45.7%
cos-neg45.7%
distribute-rgt-neg-in45.7%
metadata-eval45.7%
*-commutative45.7%
*-commutative45.7%
*-commutative45.7%
*-commutative45.7%
distribute-lft-neg-in45.7%
sin-neg45.7%
distribute-rgt-neg-in45.7%
metadata-eval45.7%
*-commutative45.7%
*-commutative45.7%
Simplified45.7%
div-sub44.0%
sin-diff45.7%
div-inv45.7%
metadata-eval45.7%
div-inv45.7%
metadata-eval45.7%
div-inv45.7%
metadata-eval45.7%
div-inv45.7%
metadata-eval45.7%
Applied egg-rr71.0%
Taylor expanded in phi2 around 0 56.8%
if -440 < phi1 < 0.0024499999999999999Initial program 78.9%
div-sub78.9%
sin-diff78.9%
div-inv78.9%
metadata-eval78.9%
div-inv78.9%
metadata-eval78.9%
div-inv78.9%
metadata-eval78.9%
div-inv78.9%
metadata-eval78.9%
Applied egg-rr78.9%
*-commutative78.9%
*-commutative78.9%
fmm-def78.9%
cos-neg78.9%
distribute-rgt-neg-in78.9%
metadata-eval78.9%
*-commutative78.9%
*-commutative78.9%
*-commutative78.9%
*-commutative78.9%
distribute-lft-neg-in78.9%
sin-neg78.9%
distribute-rgt-neg-in78.9%
metadata-eval78.9%
*-commutative78.9%
*-commutative78.9%
Simplified78.9%
div-sub78.9%
sin-diff78.9%
div-inv78.9%
metadata-eval78.9%
div-inv78.9%
metadata-eval78.9%
div-inv78.9%
metadata-eval78.9%
div-inv78.9%
metadata-eval78.9%
Applied egg-rr79.7%
Taylor expanded in phi1 around 0 79.3%
if 0.0024499999999999999 < phi1 Initial program 48.9%
div-sub48.9%
sin-diff50.5%
div-inv50.5%
metadata-eval50.5%
div-inv50.5%
metadata-eval50.5%
div-inv50.5%
metadata-eval50.5%
div-inv50.5%
metadata-eval50.5%
Applied egg-rr50.5%
*-commutative50.5%
*-commutative50.5%
fmm-def50.5%
cos-neg50.5%
distribute-rgt-neg-in50.5%
metadata-eval50.5%
*-commutative50.5%
*-commutative50.5%
*-commutative50.5%
*-commutative50.5%
distribute-lft-neg-in50.5%
sin-neg50.5%
distribute-rgt-neg-in50.5%
metadata-eval50.5%
*-commutative50.5%
*-commutative50.5%
Simplified50.5%
div-sub48.9%
sin-diff50.5%
div-inv50.5%
metadata-eval50.5%
div-inv50.5%
metadata-eval50.5%
div-inv50.5%
metadata-eval50.5%
div-inv50.5%
metadata-eval50.5%
Applied egg-rr80.1%
Taylor expanded in phi2 around 0 60.5%
Final simplification69.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (* phi1 0.5)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (sin (* phi1 0.5))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(*
(cos phi1)
(* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
(pow (+ (* (cos (* -0.5 phi2)) t_2) (* (sin (* -0.5 phi2)) t_0)) 2.0)))
(sqrt
(-
1.0
(+
(* t_1 (* (* (cos phi1) (cos phi2)) t_1))
(pow
(- (* (cos (* phi2 0.5)) t_2) (* t_0 (sin (* phi2 0.5))))
2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((phi1 * 0.5));
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = sin((phi1 * 0.5));
return R * (2.0 * atan2(sqrt(((cos(phi1) * (cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0))) + pow(((cos((-0.5 * phi2)) * t_2) + (sin((-0.5 * phi2)) * t_0)), 2.0))), sqrt((1.0 - ((t_1 * ((cos(phi1) * cos(phi2)) * t_1)) + pow(((cos((phi2 * 0.5)) * t_2) - (t_0 * 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
real(8) :: t_2
t_0 = cos((phi1 * 0.5d0))
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
t_2 = sin((phi1 * 0.5d0))
code = r * (2.0d0 * atan2(sqrt(((cos(phi1) * (cos(phi2) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0))) + (((cos(((-0.5d0) * phi2)) * t_2) + (sin(((-0.5d0) * phi2)) * t_0)) ** 2.0d0))), sqrt((1.0d0 - ((t_1 * ((cos(phi1) * cos(phi2)) * t_1)) + (((cos((phi2 * 0.5d0)) * t_2) - (t_0 * 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.cos((phi1 * 0.5));
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_2 = Math.sin((phi1 * 0.5));
return R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0))) + Math.pow(((Math.cos((-0.5 * phi2)) * t_2) + (Math.sin((-0.5 * phi2)) * t_0)), 2.0))), Math.sqrt((1.0 - ((t_1 * ((Math.cos(phi1) * Math.cos(phi2)) * t_1)) + Math.pow(((Math.cos((phi2 * 0.5)) * t_2) - (t_0 * Math.sin((phi2 * 0.5)))), 2.0))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos((phi1 * 0.5)) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) t_2 = math.sin((phi1 * 0.5)) return R * (2.0 * math.atan2(math.sqrt(((math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0))) + math.pow(((math.cos((-0.5 * phi2)) * t_2) + (math.sin((-0.5 * phi2)) * t_0)), 2.0))), math.sqrt((1.0 - ((t_1 * ((math.cos(phi1) * math.cos(phi2)) * t_1)) + math.pow(((math.cos((phi2 * 0.5)) * t_2) - (t_0 * math.sin((phi2 * 0.5)))), 2.0))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(phi1 * 0.5)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = sin(Float64(phi1 * 0.5)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0))) + (Float64(Float64(cos(Float64(-0.5 * phi2)) * t_2) + Float64(sin(Float64(-0.5 * phi2)) * t_0)) ^ 2.0))), sqrt(Float64(1.0 - Float64(Float64(t_1 * Float64(Float64(cos(phi1) * cos(phi2)) * t_1)) + (Float64(Float64(cos(Float64(phi2 * 0.5)) * t_2) - Float64(t_0 * sin(Float64(phi2 * 0.5)))) ^ 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos((phi1 * 0.5)); t_1 = sin(((lambda1 - lambda2) / 2.0)); t_2 = sin((phi1 * 0.5)); tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * (cos(phi2) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0))) + (((cos((-0.5 * phi2)) * t_2) + (sin((-0.5 * phi2)) * t_0)) ^ 2.0))), sqrt((1.0 - ((t_1 * ((cos(phi1) * cos(phi2)) * t_1)) + (((cos((phi2 * 0.5)) * t_2) - (t_0 * sin((phi2 * 0.5)))) ^ 2.0)))))); 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[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(phi1 * 0.5), $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 * N[(lambda1 - lambda2), $MachinePrecision]), $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$0), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(t$95$1 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision] + N[Power[N[(N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * t$95$2), $MachinePrecision] - N[(t$95$0 * 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 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \sin \left(\phi_1 \cdot 0.5\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\right) + {\left(\cos \left(-0.5 \cdot \phi_2\right) \cdot t\_2 + \sin \left(-0.5 \cdot \phi_2\right) \cdot t\_0\right)}^{2}}}{\sqrt{1 - \left(t\_1 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_1\right) + {\left(\cos \left(\phi_2 \cdot 0.5\right) \cdot t\_2 - t\_0 \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 63.1%
div-sub63.1%
sin-diff63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
Applied egg-rr63.9%
*-commutative63.9%
*-commutative63.9%
fmm-def63.9%
cos-neg63.9%
distribute-rgt-neg-in63.9%
metadata-eval63.9%
*-commutative63.9%
*-commutative63.9%
*-commutative63.9%
*-commutative63.9%
distribute-lft-neg-in63.9%
sin-neg63.9%
distribute-rgt-neg-in63.9%
metadata-eval63.9%
*-commutative63.9%
*-commutative63.9%
Simplified63.9%
div-sub63.1%
sin-diff63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
Applied egg-rr77.7%
Taylor expanded in phi2 around inf 77.7%
Final simplification77.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow
(fma
(cos (* -0.5 phi2))
(sin (* phi1 0.5))
(* (sin (* -0.5 phi2)) (cos (* phi1 0.5))))
2.0)
(* t_0 (* (* (cos phi1) (cos phi2)) t_0))))
(sqrt
(fabs
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((pow(fma(cos((-0.5 * phi2)), sin((phi1 * 0.5)), (sin((-0.5 * phi2)) * cos((phi1 * 0.5)))), 2.0) + (t_0 * ((cos(phi1) * cos(phi2)) * t_0)))), sqrt(fabs((1.0 - fma(cos(phi1), (cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0)), pow(sin((0.5 * (phi1 - phi2))), 2.0)))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((fma(cos(Float64(-0.5 * phi2)), sin(Float64(phi1 * 0.5)), Float64(sin(Float64(-0.5 * phi2)) * cos(Float64(phi1 * 0.5)))) ^ 2.0) + Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)))), sqrt(abs(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[Abs[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(\cos \left(-0.5 \cdot \phi_2\right), \sin \left(\phi_1 \cdot 0.5\right), \sin \left(-0.5 \cdot \phi_2\right) \cdot \cos \left(\phi_1 \cdot 0.5\right)\right)\right)}^{2} + t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right)}}{\sqrt{\left|1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}, {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)\right|}}\right)
\end{array}
\end{array}
Initial program 63.1%
div-sub63.1%
sin-diff63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
Applied egg-rr63.9%
*-commutative63.9%
*-commutative63.9%
fmm-def63.9%
cos-neg63.9%
distribute-rgt-neg-in63.9%
metadata-eval63.9%
*-commutative63.9%
*-commutative63.9%
*-commutative63.9%
*-commutative63.9%
distribute-lft-neg-in63.9%
sin-neg63.9%
distribute-rgt-neg-in63.9%
metadata-eval63.9%
*-commutative63.9%
*-commutative63.9%
Simplified63.9%
add-sqr-sqrt63.9%
pow1/263.9%
pow1/263.9%
pow-prod-down64.2%
Applied egg-rr64.2%
Simplified64.2%
Final simplification64.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(*
(cos phi1)
(* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))))
(*
R
(*
2.0
(atan2
(sqrt
(+
t_0
(pow
(+
(* (cos (* -0.5 phi2)) (sin (* phi1 0.5)))
(* (sin (* -0.5 phi2)) (cos (* phi1 0.5))))
2.0)))
(sqrt (- 1.0 (+ t_0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * (cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0));
return R * (2.0 * atan2(sqrt((t_0 + pow(((cos((-0.5 * phi2)) * sin((phi1 * 0.5))) + (sin((-0.5 * phi2)) * cos((phi1 * 0.5)))), 2.0))), sqrt((1.0 - (t_0 + pow(sin((0.5 * (phi1 - phi2))), 2.0))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = cos(phi1) * (cos(phi2) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0))
code = r * (2.0d0 * atan2(sqrt((t_0 + (((cos(((-0.5d0) * phi2)) * sin((phi1 * 0.5d0))) + (sin(((-0.5d0) * phi2)) * cos((phi1 * 0.5d0)))) ** 2.0d0))), sqrt((1.0d0 - (t_0 + (sin((0.5d0 * (phi1 - phi2))) ** 2.0d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((t_0 + Math.pow(((Math.cos((-0.5 * phi2)) * Math.sin((phi1 * 0.5))) + (Math.sin((-0.5 * phi2)) * Math.cos((phi1 * 0.5)))), 2.0))), Math.sqrt((1.0 - (t_0 + Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0)) return R * (2.0 * math.atan2(math.sqrt((t_0 + math.pow(((math.cos((-0.5 * phi2)) * math.sin((phi1 * 0.5))) + (math.sin((-0.5 * phi2)) * math.cos((phi1 * 0.5)))), 2.0))), math.sqrt((1.0 - (t_0 + math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0))) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_0 + (Float64(Float64(cos(Float64(-0.5 * phi2)) * sin(Float64(phi1 * 0.5))) + Float64(sin(Float64(-0.5 * phi2)) * cos(Float64(phi1 * 0.5)))) ^ 2.0))), sqrt(Float64(1.0 - Float64(t_0 + (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi1) * (cos(phi2) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0)); tmp = R * (2.0 * atan2(sqrt((t_0 + (((cos((-0.5 * phi2)) * sin((phi1 * 0.5))) + (sin((-0.5 * phi2)) * cos((phi1 * 0.5)))) ^ 2.0))), sqrt((1.0 - (t_0 + (sin((0.5 * (phi1 - phi2))) ^ 2.0)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 + N[Power[N[(N[(N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 + {\left(\cos \left(-0.5 \cdot \phi_2\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) + \sin \left(-0.5 \cdot \phi_2\right) \cdot \cos \left(\phi_1 \cdot 0.5\right)\right)}^{2}}}{\sqrt{1 - \left(t\_0 + {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 63.1%
div-sub63.1%
sin-diff63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
div-inv63.9%
metadata-eval63.9%
Applied egg-rr63.9%
*-commutative63.9%
*-commutative63.9%
fmm-def63.9%
cos-neg63.9%
distribute-rgt-neg-in63.9%
metadata-eval63.9%
*-commutative63.9%
*-commutative63.9%
*-commutative63.9%
*-commutative63.9%
distribute-lft-neg-in63.9%
sin-neg63.9%
distribute-rgt-neg-in63.9%
metadata-eval63.9%
*-commutative63.9%
*-commutative63.9%
Simplified63.9%
Taylor expanded in phi2 around 0 63.9%
Final simplification63.9%
(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
(fabs
(+
(fma
(cos phi1)
(* (cos phi2) (+ 0.5 (* -0.5 (cos (- lambda1 lambda2)))))
(pow (sin (* -0.5 (- phi2 phi1))) 2.0))
-1.0))))))))
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(fabs((fma(cos(phi1), (cos(phi2) * (0.5 + (-0.5 * cos((lambda1 - lambda2))))), pow(sin((-0.5 * (phi2 - phi1))), 2.0)) + -1.0)))));
}
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(abs(Float64(fma(cos(phi1), Float64(cos(phi2) * Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2))))), (sin(Float64(-0.5 * Float64(phi2 - phi1))) ^ 2.0)) + -1.0)))))) 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[Abs[N[(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[(phi2 - phi1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + -1.0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right)}}{\sqrt{\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_2 - \phi_1\right)\right)}^{2}\right) + -1\right|}}\right)
\end{array}
\end{array}
Initial program 63.1%
associate-*l*63.1%
Simplified63.1%
Applied egg-rr63.5%
unpow1/263.5%
unpow263.5%
rem-sqrt-square63.5%
*-commutative63.5%
Simplified63.5%
Final simplification63.5%
(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 (- (- (/ (cos (- phi1 phi2)) 2.0) 0.5) t_1))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = 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 + (((cos((phi1 - phi2)) / 2.0) - 0.5) - t_1)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = 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 + (((cos((phi1 - phi2)) / 2.0d0) - 0.5d0) - t_1)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = 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 + (((Math.cos((phi1 - phi2)) / 2.0) - 0.5) - t_1)))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = 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 + (((math.cos((phi1 - phi2)) / 2.0) - 0.5) - t_1)))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(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(Float64(Float64(cos(Float64(phi1 - phi2)) / 2.0) - 0.5) - t_1)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = 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 + (((cos((phi1 - phi2)) / 2.0) - 0.5) - t_1))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(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[(N[(N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision] - t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{1 + \left(\left(\frac{\cos \left(\phi_1 - \phi_2\right)}{2} - 0.5\right) - t\_1\right)}}\right)
\end{array}
\end{array}
Initial program 63.1%
unpow263.1%
sin-mult63.2%
div-inv63.2%
metadata-eval63.2%
div-inv63.2%
metadata-eval63.2%
div-inv63.2%
metadata-eval63.2%
div-inv63.2%
metadata-eval63.2%
Applied egg-rr63.2%
div-sub63.2%
+-inverses63.2%
cos-063.2%
metadata-eval63.2%
distribute-lft-out63.2%
metadata-eval63.2%
*-rgt-identity63.2%
Simplified63.2%
Final simplification63.2%
(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 (- (/ (cos (- phi1 phi2)) 2.0) 0.5)) t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0);
return R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), sqrt(((1.0 + ((cos((phi1 - phi2)) / 2.0) - 0.5)) - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0)
code = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + t_1)), sqrt(((1.0d0 + ((cos((phi1 - phi2)) / 2.0d0) - 0.5d0)) - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = (Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0);
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), Math.sqrt(((1.0 + ((Math.cos((phi1 - phi2)) / 2.0) - 0.5)) - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = (math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0) return R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), math.sqrt(((1.0 + ((math.cos((phi1 - phi2)) / 2.0) - 0.5)) - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + t_1)), sqrt(Float64(Float64(1.0 + Float64(Float64(cos(Float64(phi1 - phi2)) / 2.0) - 0.5)) - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0); tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + t_1)), sqrt(((1.0 + ((cos((phi1 - phi2)) / 2.0) - 0.5)) - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(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[(N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision] - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_1}}{\sqrt{\left(1 + \left(\frac{\cos \left(\phi_1 - \phi_2\right)}{2} - 0.5\right)\right) - t\_1}}\right)
\end{array}
\end{array}
Initial program 63.1%
associate-*l*63.1%
Simplified63.1%
unpow263.1%
sin-mult63.2%
div-inv63.2%
metadata-eval63.2%
div-inv63.2%
metadata-eval63.2%
div-inv63.2%
metadata-eval63.2%
div-inv63.2%
metadata-eval63.2%
Applied egg-rr63.2%
div-sub63.2%
+-inverses63.2%
cos-063.2%
metadata-eval63.2%
distribute-lft-out63.2%
metadata-eval63.2%
*-rgt-identity63.2%
Simplified63.2%
Final simplification63.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
(if (or (<= phi1 -440.0) (not (<= phi1 2.7)))
(*
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 (+ (* (cos phi1) t_0) (pow (sin (* phi1 0.5)) 2.0)))))))
(*
(atan2
(sqrt (+ (* (cos phi2) t_0) (pow (sin (* -0.5 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)))))
(* R 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 tmp;
if ((phi1 <= -440.0) || !(phi1 <= 2.7)) {
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 - ((cos(phi1) * t_0) + pow(sin((phi1 * 0.5)), 2.0))))));
} else {
tmp = atan2(sqrt(((cos(phi2) * t_0) + pow(sin((-0.5 * 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))))) * (R * 2.0);
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 tmp = 0.0 if ((phi1 <= -440.0) || !(phi1 <= 2.7)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * sin(Float64(Float64(lambda1 - lambda2) / 2.0))) * sin(Float64(0.5 * lambda1))))), sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * t_0) + (sin(Float64(phi1 * 0.5)) ^ 2.0))))))); else tmp = Float64(atan(sqrt(Float64(Float64(cos(phi2) * t_0) + (sin(Float64(-0.5 * 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))))) * Float64(R * 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]}, If[Or[LessEqual[phi1, -440.0], N[Not[LessEqual[phi1, 2.7]], $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[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $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], N[(N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $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] * N[(R * 2.0), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
\mathbf{if}\;\phi_1 \leq -440 \lor \neg \left(\phi_1 \leq 2.7\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\right) \cdot \sin \left(0.5 \cdot \lambda_1\right)}}{\sqrt{1 - \left(\cos \phi_1 \cdot t\_0 + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;\tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot t\_0 + {\sin \left(-0.5 \cdot \phi_2\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)}} \cdot \left(R \cdot 2\right)\\
\end{array}
\end{array}
if phi1 < -440 or 2.7000000000000002 < phi1 Initial program 46.1%
Taylor expanded in lambda2 around 0 39.9%
Taylor expanded in phi2 around 0 40.4%
if -440 < phi1 < 2.7000000000000002Initial program 79.0%
associate-*r*79.0%
*-commutative79.0%
Simplified79.0%
Applied egg-rr55.3%
*-lft-identity55.3%
*-commutative55.3%
*-commutative55.3%
*-commutative55.3%
Simplified55.3%
Taylor expanded in phi1 around 0 52.3%
Taylor expanded in phi1 around 0 75.4%
Final simplification58.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(+
(* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(pow (sin (* -0.5 phi2)) 2.0)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (pow (sin (* 0.5 (- phi1 phi2))) 2.0))
(t_3 (sqrt t_0))
(t_4 (* (cos phi1) (cos phi2))))
(if (<= (- lambda1 lambda2) -500000.0)
(* R (* 2.0 (atan2 t_3 (sqrt (- 1.0 t_0)))))
(if (<= (- lambda1 lambda2) 5e-8)
(*
R
(*
2.0
(atan2
(sqrt (+ t_2 (* -0.5 (* lambda1 (* t_4 lambda2)))))
(sqrt
(-
1.0
(+ (* t_1 (* t_4 t_1)) (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))))))
(*
(atan2
t_3
(sqrt
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (+ 0.5 (* -0.5 (cos (- lambda1 lambda2)))))
t_2))))
(* R 2.0))))))
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)) + pow(sin((-0.5 * phi2)), 2.0);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = pow(sin((0.5 * (phi1 - phi2))), 2.0);
double t_3 = sqrt(t_0);
double t_4 = cos(phi1) * cos(phi2);
double tmp;
if ((lambda1 - lambda2) <= -500000.0) {
tmp = R * (2.0 * atan2(t_3, sqrt((1.0 - t_0))));
} else if ((lambda1 - lambda2) <= 5e-8) {
tmp = R * (2.0 * atan2(sqrt((t_2 + (-0.5 * (lambda1 * (t_4 * lambda2))))), sqrt((1.0 - ((t_1 * (t_4 * t_1)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))))));
} else {
tmp = atan2(t_3, sqrt((1.0 - fma(cos(phi1), (cos(phi2) * (0.5 + (-0.5 * cos((lambda1 - lambda2))))), t_2)))) * (R * 2.0);
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)) + (sin(Float64(-0.5 * phi2)) ^ 2.0)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0 t_3 = sqrt(t_0) t_4 = Float64(cos(phi1) * cos(phi2)) tmp = 0.0 if (Float64(lambda1 - lambda2) <= -500000.0) tmp = Float64(R * Float64(2.0 * atan(t_3, sqrt(Float64(1.0 - t_0))))); elseif (Float64(lambda1 - lambda2) <= 5e-8) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_2 + Float64(-0.5 * Float64(lambda1 * Float64(t_4 * lambda2))))), sqrt(Float64(1.0 - Float64(Float64(t_1 * Float64(t_4 * t_1)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))))))); else tmp = Float64(atan(t_3, sqrt(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2))))), t_2)))) * Float64(R * 2.0)); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = 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[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$3 = N[Sqrt[t$95$0], $MachinePrecision]}, Block[{t$95$4 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[(lambda1 - lambda2), $MachinePrecision], -500000.0], N[(R * N[(2.0 * N[ArcTan[t$95$3 / N[Sqrt[N[(1.0 - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[N[(lambda1 - lambda2), $MachinePrecision], 5e-8], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$2 + N[(-0.5 * N[(lambda1 * N[(t$95$4 * lambda2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(t$95$1 * N[(t$95$4 * t$95$1), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[ArcTan[t$95$3 / 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] * N[(R * 2.0), $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} + {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\\
t_3 := \sqrt{t\_0}\\
t_4 := \cos \phi_1 \cdot \cos \phi_2\\
\mathbf{if}\;\lambda_1 - \lambda_2 \leq -500000:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_3}{\sqrt{1 - t\_0}}\right)\\
\mathbf{elif}\;\lambda_1 - \lambda_2 \leq 5 \cdot 10^{-8}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 + -0.5 \cdot \left(\lambda_1 \cdot \left(t\_4 \cdot \lambda_2\right)\right)}}{\sqrt{1 - \left(t\_1 \cdot \left(t\_4 \cdot t\_1\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;\tan^{-1}_* \frac{t\_3}{\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)}} \cdot \left(R \cdot 2\right)\\
\end{array}
\end{array}
if (-.f64 lambda1 lambda2) < -5e5Initial program 59.8%
Taylor expanded in phi1 around 0 42.8%
+-commutative42.8%
unpow242.8%
associate-*r*42.8%
distribute-rgt-out42.8%
Simplified42.8%
Taylor expanded in phi1 around 0 43.1%
Taylor expanded in phi1 around 0 48.5%
if -5e5 < (-.f64 lambda1 lambda2) < 4.9999999999999998e-8Initial program 77.9%
expm1-log1p-u77.9%
expm1-undefine67.2%
log1p-undefine67.1%
add-exp-log67.1%
div-inv67.1%
metadata-eval67.1%
Applied egg-rr67.1%
Taylor expanded in lambda1 around 0 65.6%
Taylor expanded in lambda2 around 0 73.6%
if 4.9999999999999998e-8 < (-.f64 lambda1 lambda2) Initial program 56.3%
associate-*r*56.3%
*-commutative56.3%
Simplified56.3%
Applied egg-rr39.8%
*-lft-identity39.8%
*-commutative39.8%
*-commutative39.8%
*-commutative39.8%
Simplified39.8%
Taylor expanded in phi1 around 0 36.0%
Taylor expanded in phi1 around 0 49.0%
Final simplification54.9%
(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
(-
(- 1.0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0))
(*
(cos phi1)
(* (cos phi2) (+ 0.5 (* -0.5 (cos (- lambda1 lambda2)))))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = 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(((1.0 - pow(sin((0.5 * (phi1 - phi2))), 2.0)) - (cos(phi1) * (cos(phi2) * (0.5 + (-0.5 * cos((lambda1 - lambda2))))))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))), sqrt(((1.0d0 - (sin((0.5d0 * (phi1 - phi2))) ** 2.0d0)) - (cos(phi1) * (cos(phi2) * (0.5d0 + ((-0.5d0) * cos((lambda1 - lambda2))))))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0)))), Math.sqrt(((1.0 - Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0)) - (Math.cos(phi1) * (Math.cos(phi2) * (0.5 + (-0.5 * Math.cos((lambda1 - lambda2))))))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) return R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0)))), math.sqrt(((1.0 - math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0)) - (math.cos(phi1) * (math.cos(phi2) * (0.5 + (-0.5 * math.cos((lambda1 - lambda2))))))))))
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(Float64(Float64(1.0 - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)) - Float64(cos(phi1) * Float64(cos(phi2) * Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2))))))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))), sqrt(((1.0 - (sin((0.5 * (phi1 - phi2))) ^ 2.0)) - (cos(phi1) * (cos(phi2) * (0.5 + (-0.5 * cos((lambda1 - lambda2)))))))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, 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[(N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\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{\left(1 - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right) - \cos \phi_1 \cdot \left(\cos \phi_2 \cdot \left(0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right)\right)}}\right)
\end{array}
\end{array}
Initial program 63.1%
associate-*l*63.1%
Simplified63.1%
associate-*l*63.1%
cancel-sign-sub-inv63.1%
div-inv63.1%
metadata-eval63.1%
sqr-sin-a63.1%
cancel-sign-sub-inv63.1%
metadata-eval63.1%
cos-263.1%
cos-sum63.1%
Applied egg-rr63.1%
Final simplification63.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0)))
(*
2.0
(*
R
(atan2
(sqrt
(+
(*
(cos phi1)
(* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
t_0))
(sqrt
(-
1.0
(+
t_0
(*
(cos phi1)
(* (cos phi2) (+ 0.5 (* -0.5 (cos (- lambda1 lambda2))))))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (phi1 - phi2))), 2.0);
return 2.0 * (R * atan2(sqrt(((cos(phi1) * (cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0))) + t_0)), sqrt((1.0 - (t_0 + (cos(phi1) * (cos(phi2) * (0.5 + (-0.5 * cos((lambda1 - lambda2)))))))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin((0.5d0 * (phi1 - phi2))) ** 2.0d0
code = 2.0d0 * (r * atan2(sqrt(((cos(phi1) * (cos(phi2) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0))) + t_0)), sqrt((1.0d0 - (t_0 + (cos(phi1) * (cos(phi2) * (0.5d0 + ((-0.5d0) * cos((lambda1 - lambda2)))))))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0);
return 2.0 * (R * Math.atan2(Math.sqrt(((Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0))) + t_0)), Math.sqrt((1.0 - (t_0 + (Math.cos(phi1) * (Math.cos(phi2) * (0.5 + (-0.5 * Math.cos((lambda1 - lambda2)))))))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0) return 2.0 * (R * math.atan2(math.sqrt(((math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0))) + t_0)), math.sqrt((1.0 - (t_0 + (math.cos(phi1) * (math.cos(phi2) * (0.5 + (-0.5 * math.cos((lambda1 - lambda2)))))))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0 return Float64(2.0 * Float64(R * atan(sqrt(Float64(Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0))) + t_0)), sqrt(Float64(1.0 - Float64(t_0 + Float64(cos(phi1) * Float64(cos(phi2) * Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2)))))))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin((0.5 * (phi1 - phi2))) ^ 2.0; tmp = 2.0 * (R * atan2(sqrt(((cos(phi1) * (cos(phi2) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0))) + t_0)), sqrt((1.0 - (t_0 + (cos(phi1) * (cos(phi2) * (0.5 + (-0.5 * cos((lambda1 - lambda2))))))))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(2.0 * N[(R * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$0), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 + N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\\
2 \cdot \left(R \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\right) + t\_0}}{\sqrt{1 - \left(t\_0 + \cos \phi_1 \cdot \left(\cos \phi_2 \cdot \left(0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right)\right)\right)}}\right)
\end{array}
\end{array}
Initial program 63.1%
associate-*r*63.1%
*-commutative63.1%
Simplified63.1%
Applied egg-rr4.6%
Taylor expanded in R around 0 63.1%
Final simplification63.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1
(+
(* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(pow (sin (* -0.5 phi2)) 2.0)))
(t_2 (sin (/ (- lambda1 lambda2) 2.0))))
(if (or (<= (- lambda1 lambda2) -500000.0)
(not (<= (- lambda1 lambda2) 5e-8)))
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1)))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)
(* -0.5 (* lambda1 (* t_0 lambda2)))))
(sqrt
(-
1.0
(+ (* t_2 (* t_0 t_2)) (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = (cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0)) + pow(sin((-0.5 * phi2)), 2.0);
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if (((lambda1 - lambda2) <= -500000.0) || !((lambda1 - lambda2) <= 5e-8)) {
tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(sin((0.5 * (phi1 - phi2))), 2.0) + (-0.5 * (lambda1 * (t_0 * lambda2))))), sqrt((1.0 - ((t_2 * (t_0 * t_2)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: tmp
t_0 = cos(phi1) * cos(phi2)
t_1 = (cos(phi2) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)) + (sin(((-0.5d0) * phi2)) ** 2.0d0)
t_2 = sin(((lambda1 - lambda2) / 2.0d0))
if (((lambda1 - lambda2) <= (-500000.0d0)) .or. (.not. ((lambda1 - lambda2) <= 5d-8))) then
tmp = r * (2.0d0 * atan2(sqrt(t_1), sqrt((1.0d0 - t_1))))
else
tmp = r * (2.0d0 * atan2(sqrt(((sin((0.5d0 * (phi1 - phi2))) ** 2.0d0) + ((-0.5d0) * (lambda1 * (t_0 * lambda2))))), sqrt((1.0d0 - ((t_2 * (t_0 * t_2)) + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.cos(phi1) * Math.cos(phi2);
double t_1 = (Math.cos(phi2) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)) + Math.pow(Math.sin((-0.5 * phi2)), 2.0);
double t_2 = Math.sin(((lambda1 - lambda2) / 2.0));
double tmp;
if (((lambda1 - lambda2) <= -500000.0) || !((lambda1 - lambda2) <= 5e-8)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt(t_1), Math.sqrt((1.0 - t_1))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0) + (-0.5 * (lambda1 * (t_0 * lambda2))))), Math.sqrt((1.0 - ((t_2 * (t_0 * t_2)) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi1) * math.cos(phi2) t_1 = (math.cos(phi2) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0)) + math.pow(math.sin((-0.5 * phi2)), 2.0) t_2 = math.sin(((lambda1 - lambda2) / 2.0)) tmp = 0 if ((lambda1 - lambda2) <= -500000.0) or not ((lambda1 - lambda2) <= 5e-8): tmp = R * (2.0 * math.atan2(math.sqrt(t_1), math.sqrt((1.0 - t_1)))) else: tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0) + (-0.5 * (lambda1 * (t_0 * lambda2))))), math.sqrt((1.0 - ((t_2 * (t_0 * t_2)) + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0)))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = Float64(Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)) + (sin(Float64(-0.5 * phi2)) ^ 2.0)) t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if ((Float64(lambda1 - lambda2) <= -500000.0) || !(Float64(lambda1 - lambda2) <= 5e-8)) tmp = Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0) + Float64(-0.5 * Float64(lambda1 * Float64(t_0 * lambda2))))), sqrt(Float64(1.0 - Float64(Float64(t_2 * Float64(t_0 * t_2)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi1) * cos(phi2); t_1 = (cos(phi2) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0)) + (sin((-0.5 * phi2)) ^ 2.0); t_2 = sin(((lambda1 - lambda2) / 2.0)); tmp = 0.0; if (((lambda1 - lambda2) <= -500000.0) || ~(((lambda1 - lambda2) <= 5e-8))) tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1)))); else tmp = R * (2.0 * atan2(sqrt(((sin((0.5 * (phi1 - phi2))) ^ 2.0) + (-0.5 * (lambda1 * (t_0 * lambda2))))), sqrt((1.0 - ((t_2 * (t_0 * t_2)) + (sin(((phi1 - phi2) / 2.0)) ^ 2.0)))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[N[(lambda1 - lambda2), $MachinePrecision], -500000.0], N[Not[LessEqual[N[(lambda1 - lambda2), $MachinePrecision], 5e-8]], $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], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(-0.5 * N[(lambda1 * N[(t$95$0 * lambda2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(t$95$2 * N[(t$95$0 * t$95$2), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2} + {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\lambda_1 - \lambda_2 \leq -500000 \lor \neg \left(\lambda_1 - \lambda_2 \leq 5 \cdot 10^{-8}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2} + -0.5 \cdot \left(\lambda_1 \cdot \left(t\_0 \cdot \lambda_2\right)\right)}}{\sqrt{1 - \left(t\_2 \cdot \left(t\_0 \cdot t\_2\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right)}}\right)\\
\end{array}
\end{array}
if (-.f64 lambda1 lambda2) < -5e5 or 4.9999999999999998e-8 < (-.f64 lambda1 lambda2) Initial program 58.1%
Taylor expanded in phi1 around 0 43.2%
+-commutative43.2%
unpow243.2%
associate-*r*43.2%
distribute-rgt-out43.2%
Simplified43.2%
Taylor expanded in phi1 around 0 43.3%
Taylor expanded in phi1 around 0 48.5%
if -5e5 < (-.f64 lambda1 lambda2) < 4.9999999999999998e-8Initial program 77.9%
expm1-log1p-u77.9%
expm1-undefine67.2%
log1p-undefine67.1%
add-exp-log67.1%
div-inv67.1%
metadata-eval67.1%
Applied egg-rr67.1%
Taylor expanded in lambda1 around 0 65.6%
Taylor expanded in lambda2 around 0 73.6%
Final simplification54.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- lambda1 lambda2))))
(t_1 (+ (* (cos phi2) (pow t_0 2.0)) (pow (sin (* -0.5 phi2)) 2.0))))
(if (or (<= phi2 -5.5e-9) (not (<= phi2 7.4e-63)))
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1)))))
(*
(* R 2.0)
(atan2
(hypot
(sin (* 0.5 (- phi1 phi2)))
(* t_0 (sqrt (* (cos phi1) (cos phi2)))))
(sqrt
(-
1.0
(+
(pow (sin (* phi1 0.5)) 2.0)
(* (cos phi1) (+ 0.5 (* -0.5 (cos (- lambda1 lambda2)))))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (lambda1 - lambda2)));
double t_1 = (cos(phi2) * pow(t_0, 2.0)) + pow(sin((-0.5 * phi2)), 2.0);
double tmp;
if ((phi2 <= -5.5e-9) || !(phi2 <= 7.4e-63)) {
tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
} else {
tmp = (R * 2.0) * atan2(hypot(sin((0.5 * (phi1 - phi2))), (t_0 * sqrt((cos(phi1) * cos(phi2))))), sqrt((1.0 - (pow(sin((phi1 * 0.5)), 2.0) + (cos(phi1) * (0.5 + (-0.5 * cos((lambda1 - lambda2)))))))));
}
return tmp;
}
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin((0.5 * (lambda1 - lambda2)));
double t_1 = (Math.cos(phi2) * Math.pow(t_0, 2.0)) + Math.pow(Math.sin((-0.5 * phi2)), 2.0);
double tmp;
if ((phi2 <= -5.5e-9) || !(phi2 <= 7.4e-63)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt(t_1), Math.sqrt((1.0 - t_1))));
} else {
tmp = (R * 2.0) * Math.atan2(Math.hypot(Math.sin((0.5 * (phi1 - phi2))), (t_0 * Math.sqrt((Math.cos(phi1) * Math.cos(phi2))))), Math.sqrt((1.0 - (Math.pow(Math.sin((phi1 * 0.5)), 2.0) + (Math.cos(phi1) * (0.5 + (-0.5 * Math.cos((lambda1 - lambda2)))))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin((0.5 * (lambda1 - lambda2))) t_1 = (math.cos(phi2) * math.pow(t_0, 2.0)) + math.pow(math.sin((-0.5 * phi2)), 2.0) tmp = 0 if (phi2 <= -5.5e-9) or not (phi2 <= 7.4e-63): tmp = R * (2.0 * math.atan2(math.sqrt(t_1), math.sqrt((1.0 - t_1)))) else: tmp = (R * 2.0) * math.atan2(math.hypot(math.sin((0.5 * (phi1 - phi2))), (t_0 * math.sqrt((math.cos(phi1) * math.cos(phi2))))), math.sqrt((1.0 - (math.pow(math.sin((phi1 * 0.5)), 2.0) + (math.cos(phi1) * (0.5 + (-0.5 * math.cos((lambda1 - lambda2))))))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) t_1 = Float64(Float64(cos(phi2) * (t_0 ^ 2.0)) + (sin(Float64(-0.5 * phi2)) ^ 2.0)) tmp = 0.0 if ((phi2 <= -5.5e-9) || !(phi2 <= 7.4e-63)) tmp = Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))); else tmp = Float64(Float64(R * 2.0) * atan(hypot(sin(Float64(0.5 * Float64(phi1 - phi2))), Float64(t_0 * sqrt(Float64(cos(phi1) * cos(phi2))))), sqrt(Float64(1.0 - Float64((sin(Float64(phi1 * 0.5)) ^ 2.0) + Float64(cos(phi1) * Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2)))))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin((0.5 * (lambda1 - lambda2))); t_1 = (cos(phi2) * (t_0 ^ 2.0)) + (sin((-0.5 * phi2)) ^ 2.0); tmp = 0.0; if ((phi2 <= -5.5e-9) || ~((phi2 <= 7.4e-63))) tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1)))); else tmp = (R * 2.0) * atan2(hypot(sin((0.5 * (phi1 - phi2))), (t_0 * sqrt((cos(phi1) * cos(phi2))))), sqrt((1.0 - ((sin((phi1 * 0.5)) ^ 2.0) + (cos(phi1) * (0.5 + (-0.5 * cos((lambda1 - lambda2))))))))); end tmp_2 = 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[(N[Cos[phi2], $MachinePrecision] * N[Power[t$95$0, 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[phi2, -5.5e-9], N[Not[LessEqual[phi2, 7.4e-63]], $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], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] ^ 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[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * 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 := \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\\
t_1 := \cos \phi_2 \cdot {t\_0}^{2} + {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\\
\mathbf{if}\;\phi_2 \leq -5.5 \cdot 10^{-9} \lor \neg \left(\phi_2 \leq 7.4 \cdot 10^{-63}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)\\
\mathbf{else}:\\
\;\;\;\;\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\_0 \cdot \sqrt{\cos \phi_1 \cdot \cos \phi_2}\right)}{\sqrt{1 - \left({\sin \left(\phi_1 \cdot 0.5\right)}^{2} + \cos \phi_1 \cdot \left(0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right)\right)}}\\
\end{array}
\end{array}
if phi2 < -5.4999999999999996e-9 or 7.40000000000000025e-63 < phi2 Initial program 51.3%
Taylor expanded in phi1 around 0 45.2%
+-commutative45.2%
unpow245.2%
associate-*r*45.2%
distribute-rgt-out45.2%
Simplified45.2%
Taylor expanded in phi1 around 0 45.4%
Taylor expanded in phi1 around 0 50.1%
if -5.4999999999999996e-9 < phi2 < 7.40000000000000025e-63Initial program 77.9%
associate-*r*77.9%
*-commutative77.9%
Simplified77.9%
Applied egg-rr57.2%
*-lft-identity57.2%
*-commutative57.2%
*-commutative57.2%
*-commutative57.2%
Simplified57.2%
add-cube-cbrt57.0%
pow357.0%
+-commutative57.0%
fma-define57.0%
Applied egg-rr57.0%
Taylor expanded in phi2 around 0 57.2%
Final simplification53.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(hypot
(sin (* 0.5 (- phi1 phi2)))
(*
(sin (* 0.5 (- lambda1 lambda2)))
(sqrt (* (cos phi1) (cos phi2))))))
(t_1 (+ 0.5 (* -0.5 (cos (- lambda1 lambda2))))))
(if (or (<= phi2 -4e-7) (not (<= phi2 8e-63)))
(*
(* R 2.0)
(atan2
t_0
(sqrt (- 1.0 (+ (* (cos phi2) t_1) (pow (sin (* -0.5 phi2)) 2.0))))))
(*
(* R 2.0)
(atan2
t_0
(sqrt (- 1.0 (+ (pow (sin (* phi1 0.5)) 2.0) (* (cos phi1) t_1)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = hypot(sin((0.5 * (phi1 - phi2))), (sin((0.5 * (lambda1 - lambda2))) * sqrt((cos(phi1) * cos(phi2)))));
double t_1 = 0.5 + (-0.5 * cos((lambda1 - lambda2)));
double tmp;
if ((phi2 <= -4e-7) || !(phi2 <= 8e-63)) {
tmp = (R * 2.0) * atan2(t_0, sqrt((1.0 - ((cos(phi2) * t_1) + pow(sin((-0.5 * phi2)), 2.0)))));
} else {
tmp = (R * 2.0) * atan2(t_0, sqrt((1.0 - (pow(sin((phi1 * 0.5)), 2.0) + (cos(phi1) * t_1)))));
}
return tmp;
}
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.hypot(Math.sin((0.5 * (phi1 - phi2))), (Math.sin((0.5 * (lambda1 - lambda2))) * Math.sqrt((Math.cos(phi1) * Math.cos(phi2)))));
double t_1 = 0.5 + (-0.5 * Math.cos((lambda1 - lambda2)));
double tmp;
if ((phi2 <= -4e-7) || !(phi2 <= 8e-63)) {
tmp = (R * 2.0) * Math.atan2(t_0, Math.sqrt((1.0 - ((Math.cos(phi2) * t_1) + Math.pow(Math.sin((-0.5 * phi2)), 2.0)))));
} else {
tmp = (R * 2.0) * Math.atan2(t_0, Math.sqrt((1.0 - (Math.pow(Math.sin((phi1 * 0.5)), 2.0) + (Math.cos(phi1) * t_1)))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.hypot(math.sin((0.5 * (phi1 - phi2))), (math.sin((0.5 * (lambda1 - lambda2))) * math.sqrt((math.cos(phi1) * math.cos(phi2))))) t_1 = 0.5 + (-0.5 * math.cos((lambda1 - lambda2))) tmp = 0 if (phi2 <= -4e-7) or not (phi2 <= 8e-63): tmp = (R * 2.0) * math.atan2(t_0, math.sqrt((1.0 - ((math.cos(phi2) * t_1) + math.pow(math.sin((-0.5 * phi2)), 2.0))))) else: tmp = (R * 2.0) * math.atan2(t_0, math.sqrt((1.0 - (math.pow(math.sin((phi1 * 0.5)), 2.0) + (math.cos(phi1) * t_1))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = hypot(sin(Float64(0.5 * Float64(phi1 - phi2))), Float64(sin(Float64(0.5 * Float64(lambda1 - lambda2))) * sqrt(Float64(cos(phi1) * cos(phi2))))) t_1 = Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2)))) tmp = 0.0 if ((phi2 <= -4e-7) || !(phi2 <= 8e-63)) tmp = Float64(Float64(R * 2.0) * atan(t_0, sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * t_1) + (sin(Float64(-0.5 * phi2)) ^ 2.0)))))); else tmp = Float64(Float64(R * 2.0) * atan(t_0, sqrt(Float64(1.0 - Float64((sin(Float64(phi1 * 0.5)) ^ 2.0) + Float64(cos(phi1) * t_1)))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = hypot(sin((0.5 * (phi1 - phi2))), (sin((0.5 * (lambda1 - lambda2))) * sqrt((cos(phi1) * cos(phi2))))); t_1 = 0.5 + (-0.5 * cos((lambda1 - lambda2))); tmp = 0.0; if ((phi2 <= -4e-7) || ~((phi2 <= 8e-63))) tmp = (R * 2.0) * atan2(t_0, sqrt((1.0 - ((cos(phi2) * t_1) + (sin((-0.5 * phi2)) ^ 2.0))))); else tmp = (R * 2.0) * atan2(t_0, sqrt((1.0 - ((sin((phi1 * 0.5)) ^ 2.0) + (cos(phi1) * t_1))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sqrt[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] ^ 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$1 = N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[phi2, -4e-7], N[Not[LessEqual[phi2, 8e-63]], $MachinePrecision]], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[t$95$0 / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$1), $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[t$95$0 / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \mathsf{hypot}\left(\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right), \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right) \cdot \sqrt{\cos \phi_1 \cdot \cos \phi_2}\right)\\
t_1 := 0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\\
\mathbf{if}\;\phi_2 \leq -4 \cdot 10^{-7} \lor \neg \left(\phi_2 \leq 8 \cdot 10^{-63}\right):\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{t\_0}{\sqrt{1 - \left(\cos \phi_2 \cdot t\_1 + {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)}}\\
\mathbf{else}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{t\_0}{\sqrt{1 - \left({\sin \left(\phi_1 \cdot 0.5\right)}^{2} + \cos \phi_1 \cdot t\_1\right)}}\\
\end{array}
\end{array}
if phi2 < -3.9999999999999998e-7 or 8.00000000000000053e-63 < phi2 Initial program 51.3%
associate-*r*51.3%
*-commutative51.3%
Simplified51.2%
Applied egg-rr23.6%
*-lft-identity23.6%
*-commutative23.6%
*-commutative23.6%
*-commutative23.6%
Simplified23.6%
add-cube-cbrt23.5%
pow323.5%
+-commutative23.5%
fma-define23.5%
Applied egg-rr23.5%
Taylor expanded in phi1 around 0 24.1%
if -3.9999999999999998e-7 < phi2 < 8.00000000000000053e-63Initial program 77.8%
associate-*r*77.8%
*-commutative77.8%
Simplified77.8%
Applied egg-rr56.7%
*-lft-identity56.7%
*-commutative56.7%
*-commutative56.7%
*-commutative56.7%
Simplified56.7%
add-cube-cbrt56.5%
pow356.5%
+-commutative56.5%
fma-define56.5%
Applied egg-rr56.5%
Taylor expanded in phi2 around 0 56.7%
Final simplification38.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
(* R 2.0)
(atan2
(hypot
(sin (* 0.5 (- phi1 phi2)))
(* (sin (* 0.5 (- lambda1 lambda2))) (sqrt (* (cos phi1) (cos phi2)))))
(sqrt
(-
1.0
(+
(pow (sin (* phi1 0.5)) 2.0)
(* (cos phi1) (+ 0.5 (* -0.5 (cos (- lambda1 lambda2)))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return (R * 2.0) * atan2(hypot(sin((0.5 * (phi1 - phi2))), (sin((0.5 * (lambda1 - lambda2))) * sqrt((cos(phi1) * cos(phi2))))), sqrt((1.0 - (pow(sin((phi1 * 0.5)), 2.0) + (cos(phi1) * (0.5 + (-0.5 * cos((lambda1 - lambda2)))))))));
}
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return (R * 2.0) * Math.atan2(Math.hypot(Math.sin((0.5 * (phi1 - phi2))), (Math.sin((0.5 * (lambda1 - lambda2))) * Math.sqrt((Math.cos(phi1) * Math.cos(phi2))))), Math.sqrt((1.0 - (Math.pow(Math.sin((phi1 * 0.5)), 2.0) + (Math.cos(phi1) * (0.5 + (-0.5 * Math.cos((lambda1 - lambda2)))))))));
}
def code(R, lambda1, lambda2, phi1, phi2): return (R * 2.0) * math.atan2(math.hypot(math.sin((0.5 * (phi1 - phi2))), (math.sin((0.5 * (lambda1 - lambda2))) * math.sqrt((math.cos(phi1) * math.cos(phi2))))), math.sqrt((1.0 - (math.pow(math.sin((phi1 * 0.5)), 2.0) + (math.cos(phi1) * (0.5 + (-0.5 * math.cos((lambda1 - lambda2)))))))))
function code(R, lambda1, lambda2, phi1, phi2) return Float64(Float64(R * 2.0) * atan(hypot(sin(Float64(0.5 * Float64(phi1 - phi2))), Float64(sin(Float64(0.5 * Float64(lambda1 - lambda2))) * sqrt(Float64(cos(phi1) * cos(phi2))))), sqrt(Float64(1.0 - Float64((sin(Float64(phi1 * 0.5)) ^ 2.0) + Float64(cos(phi1) * Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2)))))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) tmp = (R * 2.0) * atan2(hypot(sin((0.5 * (phi1 - phi2))), (sin((0.5 * (lambda1 - lambda2))) * sqrt((cos(phi1) * cos(phi2))))), sqrt((1.0 - ((sin((phi1 * 0.5)) ^ 2.0) + (cos(phi1) * (0.5 + (-0.5 * cos((lambda1 - lambda2))))))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] ^ 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] / 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[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right), \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right) \cdot \sqrt{\cos \phi_1 \cdot \cos \phi_2}\right)}{\sqrt{1 - \left({\sin \left(\phi_1 \cdot 0.5\right)}^{2} + \cos \phi_1 \cdot \left(0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right)\right)}}
\end{array}
Initial program 63.1%
associate-*r*63.1%
*-commutative63.1%
Simplified63.1%
Applied egg-rr38.4%
*-lft-identity38.4%
*-commutative38.4%
*-commutative38.4%
*-commutative38.4%
Simplified38.4%
add-cube-cbrt38.2%
pow338.2%
+-commutative38.2%
fma-define38.2%
Applied egg-rr38.2%
Taylor expanded in phi2 around 0 33.0%
Final simplification33.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
(* R 2.0)
(atan2
(*
(sin (* 0.5 (- lambda1 lambda2)))
(+
1.0
(* (pow phi1 2.0) (- (* (pow phi1 2.0) -0.010416666666666666) 0.25))))
(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 + (pow(phi1, 2.0) * ((pow(phi1, 2.0) * -0.010416666666666666) - 0.25)))), 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((phi1 ^ 2.0) * Float64(Float64((phi1 ^ 2.0) * -0.010416666666666666) - 0.25)))), 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[(N[Power[phi1, 2.0], $MachinePrecision] * N[(N[(N[Power[phi1, 2.0], $MachinePrecision] * -0.010416666666666666), $MachinePrecision] - 0.25), $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 + {\phi_1}^{2} \cdot \left({\phi_1}^{2} \cdot -0.010416666666666666 - 0.25\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 63.1%
associate-*r*63.1%
*-commutative63.1%
Simplified63.1%
Applied egg-rr38.4%
*-lft-identity38.4%
*-commutative38.4%
*-commutative38.4%
*-commutative38.4%
Simplified38.4%
Taylor expanded in phi1 around 0 30.8%
Taylor expanded in phi2 around 0 13.2%
Taylor expanded in phi1 around 0 16.3%
Final simplification16.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
(* R 2.0)
(atan2
(* (sin (* 0.5 (- lambda1 lambda2))) (+ 1.0 (* (pow phi1 2.0) -0.25)))
(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 + (pow(phi1, 2.0) * -0.25))), 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((phi1 ^ 2.0) * -0.25))), 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[(N[Power[phi1, 2.0], $MachinePrecision] * -0.25), $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 + {\phi_1}^{2} \cdot -0.25\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 63.1%
associate-*r*63.1%
*-commutative63.1%
Simplified63.1%
Applied egg-rr38.4%
*-lft-identity38.4%
*-commutative38.4%
*-commutative38.4%
*-commutative38.4%
Simplified38.4%
Taylor expanded in phi1 around 0 30.8%
Taylor expanded in phi2 around 0 13.2%
Taylor expanded in phi1 around 0 16.2%
*-commutative16.2%
Simplified16.2%
Final simplification16.2%
(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 63.1%
associate-*r*63.1%
*-commutative63.1%
Simplified63.1%
Applied egg-rr38.4%
*-lft-identity38.4%
*-commutative38.4%
*-commutative38.4%
*-commutative38.4%
Simplified38.4%
Taylor expanded in phi1 around 0 30.8%
Taylor expanded in phi2 around 0 13.2%
Taylor expanded in phi1 around 0 15.5%
Final simplification15.5%
herbie shell --seed 2024165
(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))))))))))