
(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 27 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_0) t_0))))
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0);
return R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0)
code = r * (2.0d0 * atan2(sqrt(t_1), sqrt((1.0d0 - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((Math.cos(phi1) * Math.cos(phi2)) * t_0) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt(t_1), Math.sqrt((1.0 - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((math.cos(phi1) * math.cos(phi2)) * t_0) * t_0) return R * (2.0 * math.atan2(math.sqrt(t_1), math.sqrt((1.0 - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0); tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$1], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) \cdot t\_0\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)
\end{array}
\end{array}
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 phi1)))
(t_1 (cos (* 0.5 phi1)))
(t_2 (* (cos phi1) (cos phi2)))
(t_3 (cos (* 0.5 phi2)))
(t_4 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (fma t_3 t_0 (* (sin (* phi2 -0.5)) t_1)) 2.0)
(* t_2 (* t_4 t_4))))
(sqrt
(+
(- 1.0 (pow (- (* t_3 t_0) (* t_1 (sin (* 0.5 phi2)))) 2.0))
(*
t_2
(-
(/
(+ (* (cos lambda1) (cos lambda2)) (* (sin lambda1) (sin lambda2)))
2.0)
0.5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * phi1));
double t_1 = cos((0.5 * phi1));
double t_2 = cos(phi1) * cos(phi2);
double t_3 = cos((0.5 * phi2));
double t_4 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((pow(fma(t_3, t_0, (sin((phi2 * -0.5)) * t_1)), 2.0) + (t_2 * (t_4 * t_4)))), sqrt(((1.0 - pow(((t_3 * t_0) - (t_1 * sin((0.5 * phi2)))), 2.0)) + (t_2 * ((((cos(lambda1) * cos(lambda2)) + (sin(lambda1) * sin(lambda2))) / 2.0) - 0.5))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * phi1)) t_1 = cos(Float64(0.5 * phi1)) t_2 = Float64(cos(phi1) * cos(phi2)) t_3 = cos(Float64(0.5 * phi2)) t_4 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((fma(t_3, t_0, Float64(sin(Float64(phi2 * -0.5)) * t_1)) ^ 2.0) + Float64(t_2 * Float64(t_4 * t_4)))), sqrt(Float64(Float64(1.0 - (Float64(Float64(t_3 * t_0) - Float64(t_1 * sin(Float64(0.5 * phi2)))) ^ 2.0)) + Float64(t_2 * Float64(Float64(Float64(Float64(cos(lambda1) * cos(lambda2)) + Float64(sin(lambda1) * sin(lambda2))) / 2.0) - 0.5))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(t$95$3 * t$95$0 + N[(N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$2 * N[(t$95$4 * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[(N[(t$95$3 * t$95$0), $MachinePrecision] - N[(t$95$1 * N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[(t$95$2 * N[(N[(N[(N[(N[Cos[lambda1], $MachinePrecision] * N[Cos[lambda2], $MachinePrecision]), $MachinePrecision] + N[(N[Sin[lambda1], $MachinePrecision] * N[Sin[lambda2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \phi_1\right)\\
t_1 := \cos \left(0.5 \cdot \phi_1\right)\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
t_3 := \cos \left(0.5 \cdot \phi_2\right)\\
t_4 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(t\_3, t\_0, \sin \left(\phi_2 \cdot -0.5\right) \cdot t\_1\right)\right)}^{2} + t\_2 \cdot \left(t\_4 \cdot t\_4\right)}}{\sqrt{\left(1 - {\left(t\_3 \cdot t\_0 - t\_1 \cdot \sin \left(0.5 \cdot \phi_2\right)\right)}^{2}\right) + t\_2 \cdot \left(\frac{\cos \lambda_1 \cdot \cos \lambda_2 + \sin \lambda_1 \cdot \sin \lambda_2}{2} - 0.5\right)}}\right)
\end{array}
\end{array}
Initial program 63.7%
associate-*l*63.7%
Simplified63.7%
div-sub63.7%
sin-diff64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
Applied egg-rr64.8%
div-sub63.7%
sin-diff64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
Applied egg-rr76.5%
*-commutative76.5%
*-commutative76.5%
fma-neg76.5%
*-commutative76.5%
*-commutative76.5%
*-commutative76.5%
distribute-lft-neg-in76.5%
sin-neg76.5%
distribute-rgt-neg-in76.5%
metadata-eval76.5%
*-commutative76.5%
Simplified76.5%
sin-mult76.6%
cos-sum76.5%
cos-276.6%
div-sub76.6%
+-inverses76.6%
Applied egg-rr76.6%
cos-076.6%
metadata-eval76.6%
Simplified76.6%
cos-diff77.2%
Applied egg-rr77.2%
Final simplification77.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 phi1)))
(t_1 (cos (* 0.5 phi1)))
(t_2 (* (cos phi1) (cos phi2)))
(t_3 (cos (* 0.5 phi2)))
(t_4 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (fma t_3 t_0 (* (sin (* phi2 -0.5)) t_1)) 2.0)
(* t_2 (* t_4 t_4))))
(sqrt
(+
(- 1.0 (pow (- (* t_3 t_0) (* t_1 (sin (* 0.5 phi2)))) 2.0))
(* t_2 (- (/ (cos (- lambda1 lambda2)) 2.0) 0.5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * phi1));
double t_1 = cos((0.5 * phi1));
double t_2 = cos(phi1) * cos(phi2);
double t_3 = cos((0.5 * phi2));
double t_4 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((pow(fma(t_3, t_0, (sin((phi2 * -0.5)) * t_1)), 2.0) + (t_2 * (t_4 * t_4)))), sqrt(((1.0 - pow(((t_3 * t_0) - (t_1 * sin((0.5 * phi2)))), 2.0)) + (t_2 * ((cos((lambda1 - lambda2)) / 2.0) - 0.5))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * phi1)) t_1 = cos(Float64(0.5 * phi1)) t_2 = Float64(cos(phi1) * cos(phi2)) t_3 = cos(Float64(0.5 * phi2)) t_4 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((fma(t_3, t_0, Float64(sin(Float64(phi2 * -0.5)) * t_1)) ^ 2.0) + Float64(t_2 * Float64(t_4 * t_4)))), sqrt(Float64(Float64(1.0 - (Float64(Float64(t_3 * t_0) - Float64(t_1 * sin(Float64(0.5 * phi2)))) ^ 2.0)) + Float64(t_2 * Float64(Float64(cos(Float64(lambda1 - lambda2)) / 2.0) - 0.5))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(t$95$3 * t$95$0 + N[(N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$2 * N[(t$95$4 * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[(N[(t$95$3 * t$95$0), $MachinePrecision] - N[(t$95$1 * N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[(t$95$2 * N[(N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \phi_1\right)\\
t_1 := \cos \left(0.5 \cdot \phi_1\right)\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
t_3 := \cos \left(0.5 \cdot \phi_2\right)\\
t_4 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(t\_3, t\_0, \sin \left(\phi_2 \cdot -0.5\right) \cdot t\_1\right)\right)}^{2} + t\_2 \cdot \left(t\_4 \cdot t\_4\right)}}{\sqrt{\left(1 - {\left(t\_3 \cdot t\_0 - t\_1 \cdot \sin \left(0.5 \cdot \phi_2\right)\right)}^{2}\right) + t\_2 \cdot \left(\frac{\cos \left(\lambda_1 - \lambda_2\right)}{2} - 0.5\right)}}\right)
\end{array}
\end{array}
Initial program 63.7%
associate-*l*63.7%
Simplified63.7%
div-sub63.7%
sin-diff64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
Applied egg-rr64.8%
div-sub63.7%
sin-diff64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
Applied egg-rr76.5%
*-commutative76.5%
*-commutative76.5%
fma-neg76.5%
*-commutative76.5%
*-commutative76.5%
*-commutative76.5%
distribute-lft-neg-in76.5%
sin-neg76.5%
distribute-rgt-neg-in76.5%
metadata-eval76.5%
*-commutative76.5%
Simplified76.5%
sin-mult76.6%
cos-sum76.5%
cos-276.6%
div-sub76.6%
+-inverses76.6%
Applied egg-rr76.6%
cos-076.6%
metadata-eval76.6%
Simplified76.6%
Final simplification76.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos (* 0.5 phi2)) (sin (* 0.5 phi1))))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (* (cos phi1) (cos phi2)))
(t_3 (cos (* 0.5 phi1))))
(*
R
(*
2.0
(atan2
(sqrt
(+ (* t_2 (* t_1 t_1)) (pow (+ (* (sin (* phi2 -0.5)) t_3) t_0) 2.0)))
(sqrt
(+
(- 1.0 (pow (- t_0 (* t_3 (sin (* 0.5 phi2)))) 2.0))
(* t_2 (- (/ (cos (- lambda1 lambda2)) 2.0) 0.5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((0.5 * phi2)) * sin((0.5 * phi1));
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = cos(phi1) * cos(phi2);
double t_3 = cos((0.5 * phi1));
return R * (2.0 * atan2(sqrt(((t_2 * (t_1 * t_1)) + pow(((sin((phi2 * -0.5)) * t_3) + t_0), 2.0))), sqrt(((1.0 - pow((t_0 - (t_3 * sin((0.5 * phi2)))), 2.0)) + (t_2 * ((cos((lambda1 - lambda2)) / 2.0) - 0.5))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: t_3
t_0 = cos((0.5d0 * phi2)) * sin((0.5d0 * phi1))
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
t_2 = cos(phi1) * cos(phi2)
t_3 = cos((0.5d0 * phi1))
code = r * (2.0d0 * atan2(sqrt(((t_2 * (t_1 * t_1)) + (((sin((phi2 * (-0.5d0))) * t_3) + t_0) ** 2.0d0))), sqrt(((1.0d0 - ((t_0 - (t_3 * sin((0.5d0 * phi2)))) ** 2.0d0)) + (t_2 * ((cos((lambda1 - lambda2)) / 2.0d0) - 0.5d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.cos((0.5 * phi2)) * Math.sin((0.5 * phi1));
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_2 = Math.cos(phi1) * Math.cos(phi2);
double t_3 = Math.cos((0.5 * phi1));
return R * (2.0 * Math.atan2(Math.sqrt(((t_2 * (t_1 * t_1)) + Math.pow(((Math.sin((phi2 * -0.5)) * t_3) + t_0), 2.0))), Math.sqrt(((1.0 - Math.pow((t_0 - (t_3 * Math.sin((0.5 * phi2)))), 2.0)) + (t_2 * ((Math.cos((lambda1 - lambda2)) / 2.0) - 0.5))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos((0.5 * phi2)) * math.sin((0.5 * phi1)) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) t_2 = math.cos(phi1) * math.cos(phi2) t_3 = math.cos((0.5 * phi1)) return R * (2.0 * math.atan2(math.sqrt(((t_2 * (t_1 * t_1)) + math.pow(((math.sin((phi2 * -0.5)) * t_3) + t_0), 2.0))), math.sqrt(((1.0 - math.pow((t_0 - (t_3 * math.sin((0.5 * phi2)))), 2.0)) + (t_2 * ((math.cos((lambda1 - lambda2)) / 2.0) - 0.5))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(Float64(0.5 * phi2)) * sin(Float64(0.5 * phi1))) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(cos(phi1) * cos(phi2)) t_3 = cos(Float64(0.5 * phi1)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_2 * Float64(t_1 * t_1)) + (Float64(Float64(sin(Float64(phi2 * -0.5)) * t_3) + t_0) ^ 2.0))), sqrt(Float64(Float64(1.0 - (Float64(t_0 - Float64(t_3 * sin(Float64(0.5 * phi2)))) ^ 2.0)) + Float64(t_2 * Float64(Float64(cos(Float64(lambda1 - lambda2)) / 2.0) - 0.5))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos((0.5 * phi2)) * sin((0.5 * phi1)); t_1 = sin(((lambda1 - lambda2) / 2.0)); t_2 = cos(phi1) * cos(phi2); t_3 = cos((0.5 * phi1)); tmp = R * (2.0 * atan2(sqrt(((t_2 * (t_1 * t_1)) + (((sin((phi2 * -0.5)) * t_3) + t_0) ^ 2.0))), sqrt(((1.0 - ((t_0 - (t_3 * sin((0.5 * phi2)))) ^ 2.0)) + (t_2 * ((cos((lambda1 - lambda2)) / 2.0) - 0.5)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$2 * N[(t$95$1 * t$95$1), $MachinePrecision]), $MachinePrecision] + N[Power[N[(N[(N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * t$95$3), $MachinePrecision] + t$95$0), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[(t$95$0 - N[(t$95$3 * N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[(t$95$2 * N[(N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(0.5 \cdot \phi_2\right) \cdot \sin \left(0.5 \cdot \phi_1\right)\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
t_3 := \cos \left(0.5 \cdot \phi_1\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 \cdot \left(t\_1 \cdot t\_1\right) + {\left(\sin \left(\phi_2 \cdot -0.5\right) \cdot t\_3 + t\_0\right)}^{2}}}{\sqrt{\left(1 - {\left(t\_0 - t\_3 \cdot \sin \left(0.5 \cdot \phi_2\right)\right)}^{2}\right) + t\_2 \cdot \left(\frac{\cos \left(\lambda_1 - \lambda_2\right)}{2} - 0.5\right)}}\right)
\end{array}
\end{array}
Initial program 63.7%
associate-*l*63.7%
Simplified63.7%
div-sub63.7%
sin-diff64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
Applied egg-rr64.8%
div-sub63.7%
sin-diff64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
Applied egg-rr76.5%
*-commutative76.5%
*-commutative76.5%
fma-neg76.5%
*-commutative76.5%
*-commutative76.5%
*-commutative76.5%
distribute-lft-neg-in76.5%
sin-neg76.5%
distribute-rgt-neg-in76.5%
metadata-eval76.5%
*-commutative76.5%
Simplified76.5%
sin-mult76.6%
cos-sum76.5%
cos-276.6%
div-sub76.6%
+-inverses76.6%
Applied egg-rr76.6%
cos-076.6%
metadata-eval76.6%
Simplified76.6%
fma-undefine76.5%
*-commutative76.5%
*-commutative76.5%
*-commutative76.5%
*-commutative76.5%
*-commutative76.5%
*-commutative76.5%
*-commutative76.5%
Applied egg-rr76.5%
Final simplification76.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (* 0.5 phi1)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (sin (* 0.5 phi1)))
(t_3 (* (cos phi1) (cos phi2))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* t_3 (* t_1 t_1))
(pow (fma 1.0 t_2 (* (sin (* phi2 -0.5)) t_0)) 2.0)))
(sqrt
(+
(-
1.0
(pow (- (* (cos (* 0.5 phi2)) t_2) (* t_0 (sin (* 0.5 phi2)))) 2.0))
(* t_3 (- (/ (cos (- lambda1 lambda2)) 2.0) 0.5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((0.5 * phi1));
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = sin((0.5 * phi1));
double t_3 = cos(phi1) * cos(phi2);
return R * (2.0 * atan2(sqrt(((t_3 * (t_1 * t_1)) + pow(fma(1.0, t_2, (sin((phi2 * -0.5)) * t_0)), 2.0))), sqrt(((1.0 - pow(((cos((0.5 * phi2)) * t_2) - (t_0 * sin((0.5 * phi2)))), 2.0)) + (t_3 * ((cos((lambda1 - lambda2)) / 2.0) - 0.5))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(0.5 * phi1)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = sin(Float64(0.5 * phi1)) t_3 = Float64(cos(phi1) * cos(phi2)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_3 * Float64(t_1 * t_1)) + (fma(1.0, t_2, Float64(sin(Float64(phi2 * -0.5)) * t_0)) ^ 2.0))), sqrt(Float64(Float64(1.0 - (Float64(Float64(cos(Float64(0.5 * phi2)) * t_2) - Float64(t_0 * sin(Float64(0.5 * phi2)))) ^ 2.0)) + Float64(t_3 * Float64(Float64(cos(Float64(lambda1 - lambda2)) / 2.0) - 0.5))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$3 * N[(t$95$1 * t$95$1), $MachinePrecision]), $MachinePrecision] + N[Power[N[(1.0 * t$95$2 + N[(N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$2), $MachinePrecision] - N[(t$95$0 * N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[(t$95$3 * N[(N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(0.5 \cdot \phi_1\right)\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \sin \left(0.5 \cdot \phi_1\right)\\
t_3 := \cos \phi_1 \cdot \cos \phi_2\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_3 \cdot \left(t\_1 \cdot t\_1\right) + {\left(\mathsf{fma}\left(1, t\_2, \sin \left(\phi_2 \cdot -0.5\right) \cdot t\_0\right)\right)}^{2}}}{\sqrt{\left(1 - {\left(\cos \left(0.5 \cdot \phi_2\right) \cdot t\_2 - t\_0 \cdot \sin \left(0.5 \cdot \phi_2\right)\right)}^{2}\right) + t\_3 \cdot \left(\frac{\cos \left(\lambda_1 - \lambda_2\right)}{2} - 0.5\right)}}\right)
\end{array}
\end{array}
Initial program 63.7%
associate-*l*63.7%
Simplified63.7%
div-sub63.7%
sin-diff64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
Applied egg-rr64.8%
div-sub63.7%
sin-diff64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
Applied egg-rr76.5%
*-commutative76.5%
*-commutative76.5%
fma-neg76.5%
*-commutative76.5%
*-commutative76.5%
*-commutative76.5%
distribute-lft-neg-in76.5%
sin-neg76.5%
distribute-rgt-neg-in76.5%
metadata-eval76.5%
*-commutative76.5%
Simplified76.5%
sin-mult76.6%
cos-sum76.5%
cos-276.6%
div-sub76.6%
+-inverses76.6%
Applied egg-rr76.6%
cos-076.6%
metadata-eval76.6%
Simplified76.6%
Taylor expanded in phi2 around 0 65.4%
Final simplification65.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt
(-
(-
1.0
(pow
(-
(* (cos (* 0.5 phi2)) (sin (* 0.5 phi1)))
(* (cos (* 0.5 phi1)) (sin (* 0.5 phi2))))
2.0))
t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0);
return R * (2.0 * atan2(sqrt((t_1 + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt(((1.0 - pow(((cos((0.5 * phi2)) * sin((0.5 * phi1))) - (cos((0.5 * phi1)) * sin((0.5 * phi2)))), 2.0)) - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0)
code = r * (2.0d0 * atan2(sqrt((t_1 + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt(((1.0d0 - (((cos((0.5d0 * phi2)) * sin((0.5d0 * phi1))) - (cos((0.5d0 * phi1)) * sin((0.5d0 * phi2)))) ** 2.0d0)) - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = (Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0);
return R * (2.0 * Math.atan2(Math.sqrt((t_1 + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt(((1.0 - Math.pow(((Math.cos((0.5 * phi2)) * Math.sin((0.5 * phi1))) - (Math.cos((0.5 * phi1)) * Math.sin((0.5 * phi2)))), 2.0)) - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = (math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0) return R * (2.0 * math.atan2(math.sqrt((t_1 + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt(((1.0 - math.pow(((math.cos((0.5 * phi2)) * math.sin((0.5 * phi1))) - (math.cos((0.5 * phi1)) * math.sin((0.5 * phi2)))), 2.0)) - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(Float64(1.0 - (Float64(Float64(cos(Float64(0.5 * phi2)) * sin(Float64(0.5 * phi1))) - Float64(cos(Float64(0.5 * phi1)) * sin(Float64(0.5 * phi2)))) ^ 2.0)) - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0); tmp = R * (2.0 * atan2(sqrt((t_1 + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(((1.0 - (((cos((0.5 * phi2)) * sin((0.5 * phi1))) - (cos((0.5 * phi1)) * sin((0.5 * phi2)))) ^ 2.0)) - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{\left(1 - {\left(\cos \left(0.5 \cdot \phi_2\right) \cdot \sin \left(0.5 \cdot \phi_1\right) - \cos \left(0.5 \cdot \phi_1\right) \cdot \sin \left(0.5 \cdot \phi_2\right)\right)}^{2}\right) - t\_1}}\right)
\end{array}
\end{array}
Initial program 63.7%
associate-*l*63.7%
Simplified63.7%
div-sub63.7%
sin-diff64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
Applied egg-rr64.8%
Final simplification64.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow
(fma
(cos (* 0.5 phi2))
(sin (* 0.5 phi1))
(* (sin (* phi2 -0.5)) (cos (* 0.5 phi1))))
2.0)
(* t_0 (* t_1 t_1))))
(sqrt
(-
(- 1.0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0))
(* t_0 (- 0.5 (/ (cos (- 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(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((pow(fma(cos((0.5 * phi2)), sin((0.5 * phi1)), (sin((phi2 * -0.5)) * cos((0.5 * phi1)))), 2.0) + (t_0 * (t_1 * t_1)))), sqrt(((1.0 - pow(sin((0.5 * (phi1 - phi2))), 2.0)) - (t_0 * (0.5 - (cos((lambda1 - lambda2)) / 2.0)))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((fma(cos(Float64(0.5 * phi2)), sin(Float64(0.5 * phi1)), Float64(sin(Float64(phi2 * -0.5)) * cos(Float64(0.5 * phi1)))) ^ 2.0) + Float64(t_0 * Float64(t_1 * t_1)))), sqrt(Float64(Float64(1.0 - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)) - Float64(t_0 * Float64(0.5 - Float64(cos(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[(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[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] + N[(N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$0 * N[(t$95$1 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] - N[(t$95$0 * N[(0.5 - N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(\cos \left(0.5 \cdot \phi_2\right), \sin \left(0.5 \cdot \phi_1\right), \sin \left(\phi_2 \cdot -0.5\right) \cdot \cos \left(0.5 \cdot \phi_1\right)\right)\right)}^{2} + t\_0 \cdot \left(t\_1 \cdot t\_1\right)}}{\sqrt{\left(1 - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right) - t\_0 \cdot \left(0.5 - \frac{\cos \left(\lambda_1 - \lambda_2\right)}{2}\right)}}\right)
\end{array}
\end{array}
Initial program 63.7%
associate-*l*63.7%
Simplified63.7%
div-sub63.7%
sin-diff64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
Applied egg-rr64.8%
div-sub63.7%
sin-diff64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
div-inv64.8%
metadata-eval64.8%
Applied egg-rr76.5%
*-commutative76.5%
*-commutative76.5%
fma-neg76.5%
*-commutative76.5%
*-commutative76.5%
*-commutative76.5%
distribute-lft-neg-in76.5%
sin-neg76.5%
distribute-rgt-neg-in76.5%
metadata-eval76.5%
*-commutative76.5%
Simplified76.5%
sin-mult76.6%
cos-sum76.5%
cos-276.6%
div-sub76.6%
+-inverses76.6%
Applied egg-rr76.6%
cos-076.6%
metadata-eval76.6%
Simplified76.6%
sub-neg76.6%
*-commutative76.6%
*-commutative76.6%
sin-diff64.5%
*-commutative64.5%
*-commutative64.5%
Applied egg-rr64.5%
sub-neg64.5%
sub-neg64.5%
*-commutative64.5%
distribute-rgt-neg-in64.5%
distribute-lft-in64.5%
sub-neg64.5%
sub-neg64.5%
neg-mul-164.5%
neg-mul-164.5%
sub-neg64.5%
Simplified64.5%
Final simplification64.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (cos phi1) (cos phi2))))
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_1 (* t_0 t_0)) (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt
(fabs
(+
(fma
t_1
(- 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));
double t_1 = cos(phi1) * cos(phi2);
return R * (2.0 * atan2(sqrt(((t_1 * (t_0 * t_0)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt(fabs((fma(t_1, (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)) t_1 = Float64(cos(phi1) * cos(phi2)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_1 * Float64(t_0 * t_0)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(abs(Float64(fma(t_1, 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]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$1 * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[Abs[N[(N[(t$95$1 * N[(0.5 - N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * N[(phi2 - phi1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + -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)\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 \cdot \left(t\_0 \cdot t\_0\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{\left|\mathsf{fma}\left(t\_1, 0.5 - 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), {\sin \left(-0.5 \cdot \left(\phi_2 - \phi_1\right)\right)}^{2}\right) + -1\right|}}\right)
\end{array}
\end{array}
Initial program 63.7%
associate-*l*63.7%
Simplified63.7%
Applied egg-rr64.4%
Simplified64.4%
Final simplification64.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0))))
(if (or (<= t_1 -0.066) (not (<= t_1 0.03)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow
(-
(* (cos (* 0.5 phi2)) (sin (* 0.5 phi1)))
(* (cos (* 0.5 phi1)) (sin (* 0.5 phi2))))
2.0)
(* t_0 (- 0.5 (/ (cos (- lambda1 lambda2)) 2.0)))))
(sqrt (- 1.0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))))))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* t_1 (* t_0 t_1))))
(sqrt (- 1.0 (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);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((t_1 <= -0.066) || !(t_1 <= 0.03)) {
tmp = R * (2.0 * atan2(sqrt((pow(((cos((0.5 * phi2)) * sin((0.5 * phi1))) - (cos((0.5 * phi1)) * sin((0.5 * phi2)))), 2.0) + (t_0 * (0.5 - (cos((lambda1 - lambda2)) / 2.0))))), sqrt((1.0 - pow(sin((0.5 * (lambda1 - lambda2))), 2.0)))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_1 * (t_0 * t_1)))), sqrt((1.0 - pow(sin((0.5 * (phi1 - phi2))), 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) :: tmp
t_0 = cos(phi1) * cos(phi2)
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
if ((t_1 <= (-0.066d0)) .or. (.not. (t_1 <= 0.03d0))) then
tmp = r * (2.0d0 * atan2(sqrt(((((cos((0.5d0 * phi2)) * sin((0.5d0 * phi1))) - (cos((0.5d0 * phi1)) * sin((0.5d0 * phi2)))) ** 2.0d0) + (t_0 * (0.5d0 - (cos((lambda1 - lambda2)) / 2.0d0))))), sqrt((1.0d0 - (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)))))
else
tmp = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (t_1 * (t_0 * t_1)))), sqrt((1.0d0 - (sin((0.5d0 * (phi1 - phi2))) ** 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.sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((t_1 <= -0.066) || !(t_1 <= 0.03)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(((Math.cos((0.5 * phi2)) * Math.sin((0.5 * phi1))) - (Math.cos((0.5 * phi1)) * Math.sin((0.5 * phi2)))), 2.0) + (t_0 * (0.5 - (Math.cos((lambda1 - lambda2)) / 2.0))))), Math.sqrt((1.0 - Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_1 * (t_0 * t_1)))), Math.sqrt((1.0 - Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0)))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi1) * math.cos(phi2) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) tmp = 0 if (t_1 <= -0.066) or not (t_1 <= 0.03): tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(((math.cos((0.5 * phi2)) * math.sin((0.5 * phi1))) - (math.cos((0.5 * phi1)) * math.sin((0.5 * phi2)))), 2.0) + (t_0 * (0.5 - (math.cos((lambda1 - lambda2)) / 2.0))))), math.sqrt((1.0 - math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0))))) else: tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_1 * (t_0 * t_1)))), math.sqrt((1.0 - math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if ((t_1 <= -0.066) || !(t_1 <= 0.03)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((Float64(Float64(cos(Float64(0.5 * phi2)) * sin(Float64(0.5 * phi1))) - Float64(cos(Float64(0.5 * phi1)) * sin(Float64(0.5 * phi2)))) ^ 2.0) + Float64(t_0 * Float64(0.5 - Float64(cos(Float64(lambda1 - lambda2)) / 2.0))))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_1 * Float64(t_0 * t_1)))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi1) * cos(phi2); t_1 = sin(((lambda1 - lambda2) / 2.0)); tmp = 0.0; if ((t_1 <= -0.066) || ~((t_1 <= 0.03))) tmp = R * (2.0 * atan2(sqrt(((((cos((0.5 * phi2)) * sin((0.5 * phi1))) - (cos((0.5 * phi1)) * sin((0.5 * phi2)))) ^ 2.0) + (t_0 * (0.5 - (cos((lambda1 - lambda2)) / 2.0))))), sqrt((1.0 - (sin((0.5 * (lambda1 - lambda2))) ^ 2.0))))); else tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (t_1 * (t_0 * t_1)))), sqrt((1.0 - (sin((0.5 * (phi1 - phi2))) ^ 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[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[t$95$1, -0.066], N[Not[LessEqual[t$95$1, 0.03]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$0 * N[(0.5 - N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$1 * N[(t$95$0 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;t\_1 \leq -0.066 \lor \neg \left(t\_1 \leq 0.03\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\cos \left(0.5 \cdot \phi_2\right) \cdot \sin \left(0.5 \cdot \phi_1\right) - \cos \left(0.5 \cdot \phi_1\right) \cdot \sin \left(0.5 \cdot \phi_2\right)\right)}^{2} + t\_0 \cdot \left(0.5 - \frac{\cos \left(\lambda_1 - \lambda_2\right)}{2}\right)}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_1 \cdot \left(t\_0 \cdot t\_1\right)}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}}}\right)\\
\end{array}
\end{array}
if (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < -0.066000000000000003 or 0.029999999999999999 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) Initial program 59.1%
associate-*l*59.1%
Simplified59.1%
Taylor expanded in phi2 around 0 42.7%
Taylor expanded in phi1 around 0 35.0%
sin-mult70.6%
cos-sum70.6%
cos-270.6%
div-sub70.6%
+-inverses70.6%
Applied egg-rr34.9%
cos-070.6%
metadata-eval70.6%
Simplified34.9%
div-sub59.1%
sin-diff60.3%
div-inv60.3%
metadata-eval60.3%
div-inv60.3%
metadata-eval60.3%
div-inv60.3%
metadata-eval60.3%
div-inv60.3%
metadata-eval60.3%
Applied egg-rr35.8%
if -0.066000000000000003 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < 0.029999999999999999Initial program 80.5%
Taylor expanded in lambda2 around 0 78.5%
Taylor expanded in lambda1 around 0 75.8%
Final simplification44.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(if (or (<= t_1 -0.066) (not (<= t_1 0.03)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(*
t_0
(-
0.5
(/
(+
(* (cos lambda1) (cos lambda2))
(* (sin lambda1) (sin lambda2)))
2.0)))
t_2))
(sqrt (- 1.0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_2 (* t_1 (* t_0 t_1))))
(sqrt (- 1.0 (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);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double tmp;
if ((t_1 <= -0.066) || !(t_1 <= 0.03)) {
tmp = R * (2.0 * atan2(sqrt(((t_0 * (0.5 - (((cos(lambda1) * cos(lambda2)) + (sin(lambda1) * sin(lambda2))) / 2.0))) + t_2)), sqrt((1.0 - pow(sin((0.5 * (lambda1 - lambda2))), 2.0)))));
} else {
tmp = R * (2.0 * atan2(sqrt((t_2 + (t_1 * (t_0 * t_1)))), sqrt((1.0 - pow(sin((0.5 * (phi1 - phi2))), 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 = sin(((lambda1 - lambda2) / 2.0d0))
t_2 = sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0
if ((t_1 <= (-0.066d0)) .or. (.not. (t_1 <= 0.03d0))) then
tmp = r * (2.0d0 * atan2(sqrt(((t_0 * (0.5d0 - (((cos(lambda1) * cos(lambda2)) + (sin(lambda1) * sin(lambda2))) / 2.0d0))) + t_2)), sqrt((1.0d0 - (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)))))
else
tmp = r * (2.0d0 * atan2(sqrt((t_2 + (t_1 * (t_0 * t_1)))), sqrt((1.0d0 - (sin((0.5d0 * (phi1 - phi2))) ** 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.sin(((lambda1 - lambda2) / 2.0));
double t_2 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0);
double tmp;
if ((t_1 <= -0.066) || !(t_1 <= 0.03)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((t_0 * (0.5 - (((Math.cos(lambda1) * Math.cos(lambda2)) + (Math.sin(lambda1) * Math.sin(lambda2))) / 2.0))) + t_2)), Math.sqrt((1.0 - Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_2 + (t_1 * (t_0 * t_1)))), Math.sqrt((1.0 - Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0)))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi1) * math.cos(phi2) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) t_2 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) tmp = 0 if (t_1 <= -0.066) or not (t_1 <= 0.03): tmp = R * (2.0 * math.atan2(math.sqrt(((t_0 * (0.5 - (((math.cos(lambda1) * math.cos(lambda2)) + (math.sin(lambda1) * math.sin(lambda2))) / 2.0))) + t_2)), math.sqrt((1.0 - math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0))))) else: tmp = R * (2.0 * math.atan2(math.sqrt((t_2 + (t_1 * (t_0 * t_1)))), math.sqrt((1.0 - math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 tmp = 0.0 if ((t_1 <= -0.066) || !(t_1 <= 0.03)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_0 * Float64(0.5 - Float64(Float64(Float64(cos(lambda1) * cos(lambda2)) + Float64(sin(lambda1) * sin(lambda2))) / 2.0))) + t_2)), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_2 + Float64(t_1 * Float64(t_0 * t_1)))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi1) * cos(phi2); t_1 = sin(((lambda1 - lambda2) / 2.0)); t_2 = sin(((phi1 - phi2) / 2.0)) ^ 2.0; tmp = 0.0; if ((t_1 <= -0.066) || ~((t_1 <= 0.03))) tmp = R * (2.0 * atan2(sqrt(((t_0 * (0.5 - (((cos(lambda1) * cos(lambda2)) + (sin(lambda1) * sin(lambda2))) / 2.0))) + t_2)), sqrt((1.0 - (sin((0.5 * (lambda1 - lambda2))) ^ 2.0))))); else tmp = R * (2.0 * atan2(sqrt((t_2 + (t_1 * (t_0 * t_1)))), sqrt((1.0 - (sin((0.5 * (phi1 - phi2))) ^ 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[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[t$95$1, -0.066], N[Not[LessEqual[t$95$1, 0.03]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$0 * N[(0.5 - N[(N[(N[(N[Cos[lambda1], $MachinePrecision] * N[Cos[lambda2], $MachinePrecision]), $MachinePrecision] + N[(N[Sin[lambda1], $MachinePrecision] * N[Sin[lambda2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$2), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$2 + N[(t$95$1 * N[(t$95$0 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
\mathbf{if}\;t\_1 \leq -0.066 \lor \neg \left(t\_1 \leq 0.03\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 \cdot \left(0.5 - \frac{\cos \lambda_1 \cdot \cos \lambda_2 + \sin \lambda_1 \cdot \sin \lambda_2}{2}\right) + t\_2}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 + t\_1 \cdot \left(t\_0 \cdot t\_1\right)}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}}}\right)\\
\end{array}
\end{array}
if (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < -0.066000000000000003 or 0.029999999999999999 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) Initial program 59.1%
associate-*l*59.1%
Simplified59.1%
Taylor expanded in phi2 around 0 42.7%
Taylor expanded in phi1 around 0 35.0%
sin-mult70.6%
cos-sum70.6%
cos-270.6%
div-sub70.6%
+-inverses70.6%
Applied egg-rr34.9%
cos-070.6%
metadata-eval70.6%
Simplified34.9%
cos-diff71.4%
Applied egg-rr35.3%
if -0.066000000000000003 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < 0.029999999999999999Initial program 80.5%
Taylor expanded in lambda2 around 0 78.5%
Taylor expanded in lambda1 around 0 75.8%
Final simplification44.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (* t_1 t_1))
(t_3 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_4 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(if (or (<= phi2 -3700000.0) (not (<= phi2 0.000115)))
(*
(* R 2.0)
(atan2
(sqrt (+ 0.5 (- (* (cos phi2) t_3) (* 0.5 (cos phi2)))))
(sqrt (- 1.0 (fma t_0 t_2 t_4)))))
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_0 t_2) t_4))
(sqrt
(- 1.0 (+ (* (cos phi1) t_3) (pow (sin (* 0.5 phi1)) 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(((lambda1 - lambda2) / 2.0));
double t_2 = t_1 * t_1;
double t_3 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_4 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double tmp;
if ((phi2 <= -3700000.0) || !(phi2 <= 0.000115)) {
tmp = (R * 2.0) * atan2(sqrt((0.5 + ((cos(phi2) * t_3) - (0.5 * cos(phi2))))), sqrt((1.0 - fma(t_0, t_2, t_4))));
} else {
tmp = R * (2.0 * atan2(sqrt(((t_0 * t_2) + t_4)), sqrt((1.0 - ((cos(phi1) * t_3) + pow(sin((0.5 * phi1)), 2.0))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(t_1 * t_1) t_3 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_4 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 tmp = 0.0 if ((phi2 <= -3700000.0) || !(phi2 <= 0.000115)) tmp = Float64(Float64(R * 2.0) * atan(sqrt(Float64(0.5 + Float64(Float64(cos(phi2) * t_3) - Float64(0.5 * cos(phi2))))), sqrt(Float64(1.0 - fma(t_0, t_2, t_4))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_0 * t_2) + t_4)), sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * t_3) + (sin(Float64(0.5 * phi1)) ^ 2.0))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(t$95$1 * t$95$1), $MachinePrecision]}, Block[{t$95$3 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$4 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[phi2, -3700000.0], N[Not[LessEqual[phi2, 0.000115]], $MachinePrecision]], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[N[(0.5 + N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$3), $MachinePrecision] - N[(0.5 * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 * t$95$2 + t$95$4), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$0 * t$95$2), $MachinePrecision] + t$95$4), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * t$95$3), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi1), $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 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := t\_1 \cdot t\_1\\
t_3 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_4 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
\mathbf{if}\;\phi_2 \leq -3700000 \lor \neg \left(\phi_2 \leq 0.000115\right):\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\sqrt{0.5 + \left(\cos \phi_2 \cdot t\_3 - 0.5 \cdot \cos \phi_2\right)}}{\sqrt{1 - \mathsf{fma}\left(t\_0, t\_2, t\_4\right)}}\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 \cdot t\_2 + t\_4}}{\sqrt{1 - \left(\cos \phi_1 \cdot t\_3 + {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)}}\right)\\
\end{array}
\end{array}
if phi2 < -3.7e6 or 1.15e-4 < phi2 Initial program 48.5%
associate-*r*48.5%
*-commutative48.5%
Simplified48.6%
unpow248.5%
sin-mult48.7%
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-rr48.4%
div-sub48.7%
+-inverses48.7%
cos-048.7%
metadata-eval48.7%
distribute-lft-out48.7%
metadata-eval48.7%
*-rgt-identity48.7%
Simplified48.4%
Taylor expanded in phi1 around 0 49.2%
associate--l+49.2%
cos-neg49.2%
Simplified49.2%
if -3.7e6 < phi2 < 1.15e-4Initial program 77.9%
associate-*l*77.9%
Simplified78.0%
Taylor expanded in phi2 around 0 78.0%
Final simplification64.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))
(t_1 (* (cos phi1) (cos phi2)))
(t_2 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_3 (* (cos phi1) t_2))
(t_4 (sin (/ (- lambda1 lambda2) 2.0)))
(t_5 (* t_4 t_4)))
(if (<= phi1 -4.2e-5)
(*
(atan2
(sqrt (- (+ 0.5 t_3) (* 0.5 (cos phi1))))
(sqrt (- 1.0 (fma t_1 t_5 t_0))))
(* R 2.0))
(if (<= phi1 4.3e-32)
(*
R
(*
2.0
(atan2
(sqrt (+ t_0 (* t_4 (* t_1 t_4))))
(sqrt
(- 1.0 (+ (* (cos phi2) t_2) (pow (sin (* phi2 -0.5)) 2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_1 t_5) t_0))
(sqrt (- 1.0 (+ t_3 (pow (sin (* 0.5 phi1)) 2.0)))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double t_1 = cos(phi1) * cos(phi2);
double t_2 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_3 = cos(phi1) * t_2;
double t_4 = sin(((lambda1 - lambda2) / 2.0));
double t_5 = t_4 * t_4;
double tmp;
if (phi1 <= -4.2e-5) {
tmp = atan2(sqrt(((0.5 + t_3) - (0.5 * cos(phi1)))), sqrt((1.0 - fma(t_1, t_5, t_0)))) * (R * 2.0);
} else if (phi1 <= 4.3e-32) {
tmp = R * (2.0 * atan2(sqrt((t_0 + (t_4 * (t_1 * t_4)))), sqrt((1.0 - ((cos(phi2) * t_2) + pow(sin((phi2 * -0.5)), 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt(((t_1 * t_5) + t_0)), sqrt((1.0 - (t_3 + pow(sin((0.5 * phi1)), 2.0))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 t_1 = Float64(cos(phi1) * cos(phi2)) t_2 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_3 = Float64(cos(phi1) * t_2) t_4 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_5 = Float64(t_4 * t_4) tmp = 0.0 if (phi1 <= -4.2e-5) tmp = Float64(atan(sqrt(Float64(Float64(0.5 + t_3) - Float64(0.5 * cos(phi1)))), sqrt(Float64(1.0 - fma(t_1, t_5, t_0)))) * Float64(R * 2.0)); elseif (phi1 <= 4.3e-32) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_0 + Float64(t_4 * Float64(t_1 * t_4)))), sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * t_2) + (sin(Float64(phi2 * -0.5)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_1 * t_5) + t_0)), sqrt(Float64(1.0 - Float64(t_3 + (sin(Float64(0.5 * phi1)) ^ 2.0))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$3 = N[(N[Cos[phi1], $MachinePrecision] * t$95$2), $MachinePrecision]}, Block[{t$95$4 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$5 = N[(t$95$4 * t$95$4), $MachinePrecision]}, If[LessEqual[phi1, -4.2e-5], N[(N[ArcTan[N[Sqrt[N[(N[(0.5 + t$95$3), $MachinePrecision] - N[(0.5 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$1 * t$95$5 + t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(R * 2.0), $MachinePrecision]), $MachinePrecision], If[LessEqual[phi1, 4.3e-32], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 + N[(t$95$4 * N[(t$95$1 * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$2), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$1 * t$95$5), $MachinePrecision] + t$95$0), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$3 + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
t_2 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_3 := \cos \phi_1 \cdot t\_2\\
t_4 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_5 := t\_4 \cdot t\_4\\
\mathbf{if}\;\phi_1 \leq -4.2 \cdot 10^{-5}:\\
\;\;\;\;\tan^{-1}_* \frac{\sqrt{\left(0.5 + t\_3\right) - 0.5 \cdot \cos \phi_1}}{\sqrt{1 - \mathsf{fma}\left(t\_1, t\_5, t\_0\right)}} \cdot \left(R \cdot 2\right)\\
\mathbf{elif}\;\phi_1 \leq 4.3 \cdot 10^{-32}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 + t\_4 \cdot \left(t\_1 \cdot t\_4\right)}}{\sqrt{1 - \left(\cos \phi_2 \cdot t\_2 + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 \cdot t\_5 + t\_0}}{\sqrt{1 - \left(t\_3 + {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)}}\right)\\
\end{array}
\end{array}
if phi1 < -4.19999999999999977e-5Initial program 50.1%
associate-*r*50.1%
*-commutative50.1%
Simplified50.2%
unpow250.1%
sin-mult50.1%
div-inv50.1%
metadata-eval50.1%
div-inv50.1%
metadata-eval50.1%
div-inv50.1%
metadata-eval50.1%
div-inv50.1%
metadata-eval50.1%
Applied egg-rr50.2%
div-sub50.1%
+-inverses50.1%
cos-050.1%
metadata-eval50.1%
distribute-lft-out50.1%
metadata-eval50.1%
*-rgt-identity50.1%
Simplified50.2%
Taylor expanded in phi2 around 0 52.0%
if -4.19999999999999977e-5 < phi1 < 4.2999999999999999e-32Initial program 76.0%
clear-num71.9%
inv-pow71.9%
Applied egg-rr71.9%
unpow-171.9%
Simplified71.9%
Taylor expanded in phi1 around 0 76.0%
if 4.2999999999999999e-32 < phi1 Initial program 50.2%
associate-*l*50.2%
Simplified50.3%
Taylor expanded in phi2 around 0 51.4%
Final simplification64.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))
(t_1 (* (cos phi1) (cos phi2)))
(t_2 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_3 (sin (/ (- lambda1 lambda2) 2.0)))
(t_4 (* t_3 t_3))
(t_5 (* (cos phi1) t_2))
(t_6 (sqrt (+ (* t_1 t_4) t_0))))
(if (<= phi1 -3e-5)
(*
(atan2
(sqrt (- (+ 0.5 t_5) (* 0.5 (cos phi1))))
(sqrt (- 1.0 (fma t_1 t_4 t_0))))
(* R 2.0))
(if (<= phi1 4.3e-32)
(*
R
(*
2.0
(atan2
t_6
(sqrt
(- 1.0 (+ (* (cos phi2) t_2) (pow (sin (* phi2 -0.5)) 2.0)))))))
(*
R
(*
2.0
(atan2 t_6 (sqrt (- 1.0 (+ t_5 (pow (sin (* 0.5 phi1)) 2.0)))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double t_1 = cos(phi1) * cos(phi2);
double t_2 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_3 = sin(((lambda1 - lambda2) / 2.0));
double t_4 = t_3 * t_3;
double t_5 = cos(phi1) * t_2;
double t_6 = sqrt(((t_1 * t_4) + t_0));
double tmp;
if (phi1 <= -3e-5) {
tmp = atan2(sqrt(((0.5 + t_5) - (0.5 * cos(phi1)))), sqrt((1.0 - fma(t_1, t_4, t_0)))) * (R * 2.0);
} else if (phi1 <= 4.3e-32) {
tmp = R * (2.0 * atan2(t_6, sqrt((1.0 - ((cos(phi2) * t_2) + pow(sin((phi2 * -0.5)), 2.0))))));
} else {
tmp = R * (2.0 * atan2(t_6, sqrt((1.0 - (t_5 + pow(sin((0.5 * phi1)), 2.0))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 t_1 = Float64(cos(phi1) * cos(phi2)) t_2 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_3 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_4 = Float64(t_3 * t_3) t_5 = Float64(cos(phi1) * t_2) t_6 = sqrt(Float64(Float64(t_1 * t_4) + t_0)) tmp = 0.0 if (phi1 <= -3e-5) tmp = Float64(atan(sqrt(Float64(Float64(0.5 + t_5) - Float64(0.5 * cos(phi1)))), sqrt(Float64(1.0 - fma(t_1, t_4, t_0)))) * Float64(R * 2.0)); elseif (phi1 <= 4.3e-32) tmp = Float64(R * Float64(2.0 * atan(t_6, sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * t_2) + (sin(Float64(phi2 * -0.5)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(t_6, sqrt(Float64(1.0 - Float64(t_5 + (sin(Float64(0.5 * phi1)) ^ 2.0))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[(t$95$3 * t$95$3), $MachinePrecision]}, Block[{t$95$5 = N[(N[Cos[phi1], $MachinePrecision] * t$95$2), $MachinePrecision]}, Block[{t$95$6 = N[Sqrt[N[(N[(t$95$1 * t$95$4), $MachinePrecision] + t$95$0), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi1, -3e-5], N[(N[ArcTan[N[Sqrt[N[(N[(0.5 + t$95$5), $MachinePrecision] - N[(0.5 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$1 * t$95$4 + t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(R * 2.0), $MachinePrecision]), $MachinePrecision], If[LessEqual[phi1, 4.3e-32], N[(R * N[(2.0 * N[ArcTan[t$95$6 / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$2), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$6 / N[Sqrt[N[(1.0 - N[(t$95$5 + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
t_2 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_3 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_4 := t\_3 \cdot t\_3\\
t_5 := \cos \phi_1 \cdot t\_2\\
t_6 := \sqrt{t\_1 \cdot t\_4 + t\_0}\\
\mathbf{if}\;\phi_1 \leq -3 \cdot 10^{-5}:\\
\;\;\;\;\tan^{-1}_* \frac{\sqrt{\left(0.5 + t\_5\right) - 0.5 \cdot \cos \phi_1}}{\sqrt{1 - \mathsf{fma}\left(t\_1, t\_4, t\_0\right)}} \cdot \left(R \cdot 2\right)\\
\mathbf{elif}\;\phi_1 \leq 4.3 \cdot 10^{-32}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_6}{\sqrt{1 - \left(\cos \phi_2 \cdot t\_2 + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_6}{\sqrt{1 - \left(t\_5 + {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)}}\right)\\
\end{array}
\end{array}
if phi1 < -3.00000000000000008e-5Initial program 50.1%
associate-*r*50.1%
*-commutative50.1%
Simplified50.2%
unpow250.1%
sin-mult50.1%
div-inv50.1%
metadata-eval50.1%
div-inv50.1%
metadata-eval50.1%
div-inv50.1%
metadata-eval50.1%
div-inv50.1%
metadata-eval50.1%
Applied egg-rr50.2%
div-sub50.1%
+-inverses50.1%
cos-050.1%
metadata-eval50.1%
distribute-lft-out50.1%
metadata-eval50.1%
*-rgt-identity50.1%
Simplified50.2%
Taylor expanded in phi2 around 0 52.0%
if -3.00000000000000008e-5 < phi1 < 4.2999999999999999e-32Initial program 76.0%
associate-*l*76.0%
Simplified76.0%
Taylor expanded in phi1 around 0 76.0%
if 4.2999999999999999e-32 < phi1 Initial program 50.2%
associate-*l*50.2%
Simplified50.3%
Taylor expanded in phi2 around 0 51.4%
Final simplification64.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (- (+ 1.0 (- (/ (cos (- phi1 phi2)) 2.0) 0.5)) t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0);
return R * (2.0 * atan2(sqrt((t_1 + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt(((1.0 + ((cos((phi1 - phi2)) / 2.0) - 0.5)) - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0)
code = r * (2.0d0 * atan2(sqrt((t_1 + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt(((1.0d0 + ((cos((phi1 - phi2)) / 2.0d0) - 0.5d0)) - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = (Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0);
return R * (2.0 * Math.atan2(Math.sqrt((t_1 + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt(((1.0 + ((Math.cos((phi1 - phi2)) / 2.0) - 0.5)) - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = (math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0) return R * (2.0 * math.atan2(math.sqrt((t_1 + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt(((1.0 + ((math.cos((phi1 - phi2)) / 2.0) - 0.5)) - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(Float64(1.0 + Float64(Float64(cos(Float64(phi1 - phi2)) / 2.0) - 0.5)) - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0); tmp = R * (2.0 * atan2(sqrt((t_1 + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(((1.0 + ((cos((phi1 - phi2)) / 2.0) - 0.5)) - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 + N[(N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision] - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{\left(1 + \left(\frac{\cos \left(\phi_1 - \phi_2\right)}{2} - 0.5\right)\right) - t\_1}}\right)
\end{array}
\end{array}
Initial program 63.7%
associate-*l*63.7%
Simplified63.7%
unpow263.7%
sin-mult63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
Applied egg-rr63.8%
div-sub63.8%
+-inverses63.8%
cos-063.8%
metadata-eval63.8%
distribute-lft-out63.8%
metadata-eval63.8%
*-rgt-identity63.8%
Simplified63.8%
Final simplification63.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (- 0.5 (/ (cos (- phi1 phi2)) 2.0))))
(sqrt (- (- 1.0 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)) t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0);
return R * (2.0 * atan2(sqrt((t_1 + (0.5 - (cos((phi1 - phi2)) / 2.0)))), sqrt(((1.0 - pow(sin(((phi1 - phi2) / 2.0)), 2.0)) - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0)
code = r * (2.0d0 * atan2(sqrt((t_1 + (0.5d0 - (cos((phi1 - phi2)) / 2.0d0)))), sqrt(((1.0d0 - (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0)) - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = (Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0);
return R * (2.0 * Math.atan2(Math.sqrt((t_1 + (0.5 - (Math.cos((phi1 - phi2)) / 2.0)))), Math.sqrt(((1.0 - Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0)) - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = (math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0) return R * (2.0 * math.atan2(math.sqrt((t_1 + (0.5 - (math.cos((phi1 - phi2)) / 2.0)))), math.sqrt(((1.0 - math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0)) - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + Float64(0.5 - Float64(cos(Float64(phi1 - phi2)) / 2.0)))), sqrt(Float64(Float64(1.0 - (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0)) - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0); tmp = R * (2.0 * atan2(sqrt((t_1 + (0.5 - (cos((phi1 - phi2)) / 2.0)))), sqrt(((1.0 - (sin(((phi1 - phi2) / 2.0)) ^ 2.0)) - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[(0.5 - N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + \left(0.5 - \frac{\cos \left(\phi_1 - \phi_2\right)}{2}\right)}}{\sqrt{\left(1 - {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right) - t\_1}}\right)
\end{array}
\end{array}
Initial program 63.7%
associate-*l*63.7%
Simplified63.7%
unpow263.7%
sin-mult63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
Applied egg-rr61.8%
div-sub63.8%
+-inverses63.8%
cos-063.8%
metadata-eval63.8%
distribute-lft-out63.8%
metadata-eval63.8%
*-rgt-identity63.8%
Simplified61.8%
Final simplification61.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2
(sqrt
(-
1.0
(fma
(* (cos phi1) (cos phi2))
(* t_1 t_1)
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0))))))
(if (or (<= phi1 -1.3e-6) (not (<= phi1 4.3e-32)))
(*
(atan2 (sqrt (- (+ 0.5 (* (cos phi1) t_0)) (* 0.5 (cos phi1)))) t_2)
(* R 2.0))
(*
(* R 2.0)
(atan2 (sqrt (+ 0.5 (- (* (cos phi2) t_0) (* 0.5 (cos phi2))))) t_2)))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = sqrt((1.0 - fma((cos(phi1) * cos(phi2)), (t_1 * t_1), pow(sin(((phi1 - phi2) / 2.0)), 2.0))));
double tmp;
if ((phi1 <= -1.3e-6) || !(phi1 <= 4.3e-32)) {
tmp = atan2(sqrt(((0.5 + (cos(phi1) * t_0)) - (0.5 * cos(phi1)))), t_2) * (R * 2.0);
} else {
tmp = (R * 2.0) * atan2(sqrt((0.5 + ((cos(phi2) * t_0) - (0.5 * cos(phi2))))), t_2);
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = sqrt(Float64(1.0 - fma(Float64(cos(phi1) * cos(phi2)), Float64(t_1 * t_1), (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0)))) tmp = 0.0 if ((phi1 <= -1.3e-6) || !(phi1 <= 4.3e-32)) tmp = Float64(atan(sqrt(Float64(Float64(0.5 + Float64(cos(phi1) * t_0)) - Float64(0.5 * cos(phi1)))), t_2) * Float64(R * 2.0)); else tmp = Float64(Float64(R * 2.0) * atan(sqrt(Float64(0.5 + Float64(Float64(cos(phi2) * t_0) - Float64(0.5 * cos(phi2))))), t_2)); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$1 * t$95$1), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[phi1, -1.3e-6], N[Not[LessEqual[phi1, 4.3e-32]], $MachinePrecision]], N[(N[ArcTan[N[Sqrt[N[(N[(0.5 + N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision] - N[(0.5 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$2], $MachinePrecision] * N[(R * 2.0), $MachinePrecision]), $MachinePrecision], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[N[(0.5 + N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision] - N[(0.5 * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$2], $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \sqrt{1 - \mathsf{fma}\left(\cos \phi_1 \cdot \cos \phi_2, t\_1 \cdot t\_1, {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right)}\\
\mathbf{if}\;\phi_1 \leq -1.3 \cdot 10^{-6} \lor \neg \left(\phi_1 \leq 4.3 \cdot 10^{-32}\right):\\
\;\;\;\;\tan^{-1}_* \frac{\sqrt{\left(0.5 + \cos \phi_1 \cdot t\_0\right) - 0.5 \cdot \cos \phi_1}}{t\_2} \cdot \left(R \cdot 2\right)\\
\mathbf{else}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\sqrt{0.5 + \left(\cos \phi_2 \cdot t\_0 - 0.5 \cdot \cos \phi_2\right)}}{t\_2}\\
\end{array}
\end{array}
if phi1 < -1.30000000000000005e-6 or 4.2999999999999999e-32 < phi1 Initial program 50.1%
associate-*r*50.1%
*-commutative50.1%
Simplified50.2%
unpow250.2%
sin-mult50.2%
div-inv50.2%
metadata-eval50.2%
div-inv50.2%
metadata-eval50.2%
div-inv50.2%
metadata-eval50.2%
div-inv50.2%
metadata-eval50.2%
Applied egg-rr50.0%
div-sub50.2%
+-inverses50.2%
cos-050.2%
metadata-eval50.2%
distribute-lft-out50.2%
metadata-eval50.2%
*-rgt-identity50.2%
Simplified50.0%
Taylor expanded in phi2 around 0 50.7%
if -1.30000000000000005e-6 < phi1 < 4.2999999999999999e-32Initial program 76.0%
associate-*r*76.0%
*-commutative76.0%
Simplified76.0%
unpow276.0%
sin-mult76.1%
div-inv76.1%
metadata-eval76.1%
div-inv76.1%
metadata-eval76.1%
div-inv76.1%
metadata-eval76.1%
div-inv76.1%
metadata-eval76.1%
Applied egg-rr72.6%
div-sub76.1%
+-inverses76.1%
cos-076.1%
metadata-eval76.1%
distribute-lft-out76.1%
metadata-eval76.1%
*-rgt-identity76.1%
Simplified72.6%
Taylor expanded in phi1 around 0 67.1%
associate--l+67.1%
cos-neg67.1%
Simplified67.1%
Final simplification59.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (* (cos phi1) (cos phi2)))
(t_3 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
(if (or (<= phi1 -0.000185) (not (<= phi1 0.00165)))
(*
R
(*
2.0
(atan2
(sqrt (+ t_0 (* (* t_2 t_1) (sin (* 0.5 lambda1)))))
(sqrt (- 1.0 (+ (* (cos phi1) t_3) (pow (sin (* 0.5 phi1)) 2.0)))))))
(*
(* R 2.0)
(atan2
(sqrt (+ 0.5 (- (* (cos phi2) t_3) (* 0.5 (cos phi2)))))
(sqrt (- 1.0 (fma t_2 (* t_1 t_1) t_0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = cos(phi1) * cos(phi2);
double t_3 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double tmp;
if ((phi1 <= -0.000185) || !(phi1 <= 0.00165)) {
tmp = R * (2.0 * atan2(sqrt((t_0 + ((t_2 * t_1) * sin((0.5 * lambda1))))), sqrt((1.0 - ((cos(phi1) * t_3) + pow(sin((0.5 * phi1)), 2.0))))));
} else {
tmp = (R * 2.0) * atan2(sqrt((0.5 + ((cos(phi2) * t_3) - (0.5 * cos(phi2))))), sqrt((1.0 - fma(t_2, (t_1 * t_1), t_0))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(cos(phi1) * cos(phi2)) t_3 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 tmp = 0.0 if ((phi1 <= -0.000185) || !(phi1 <= 0.00165)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_0 + Float64(Float64(t_2 * t_1) * sin(Float64(0.5 * lambda1))))), sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * t_3) + (sin(Float64(0.5 * phi1)) ^ 2.0))))))); else tmp = Float64(Float64(R * 2.0) * atan(sqrt(Float64(0.5 + Float64(Float64(cos(phi2) * t_3) - Float64(0.5 * cos(phi2))))), sqrt(Float64(1.0 - fma(t_2, Float64(t_1 * t_1), t_0))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[phi1, -0.000185], N[Not[LessEqual[phi1, 0.00165]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 + N[(N[(t$95$2 * t$95$1), $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$3), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[N[(0.5 + N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$3), $MachinePrecision] - N[(0.5 * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$2 * N[(t$95$1 * t$95$1), $MachinePrecision] + t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
t_3 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
\mathbf{if}\;\phi_1 \leq -0.000185 \lor \neg \left(\phi_1 \leq 0.00165\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 + \left(t\_2 \cdot t\_1\right) \cdot \sin \left(0.5 \cdot \lambda_1\right)}}{\sqrt{1 - \left(\cos \phi_1 \cdot t\_3 + {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\sqrt{0.5 + \left(\cos \phi_2 \cdot t\_3 - 0.5 \cdot \cos \phi_2\right)}}{\sqrt{1 - \mathsf{fma}\left(t\_2, t\_1 \cdot t\_1, t\_0\right)}}\\
\end{array}
\end{array}
if phi1 < -1.85e-4 or 0.00165 < phi1 Initial program 48.9%
Taylor expanded in lambda2 around 0 35.6%
Taylor expanded in phi2 around 0 37.0%
if -1.85e-4 < phi1 < 0.00165Initial program 76.5%
associate-*r*76.5%
*-commutative76.5%
Simplified76.5%
unpow276.5%
sin-mult76.6%
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-rr73.2%
div-sub76.6%
+-inverses76.6%
cos-076.6%
metadata-eval76.6%
distribute-lft-out76.6%
metadata-eval76.6%
*-rgt-identity76.6%
Simplified73.2%
Taylor expanded in phi1 around 0 67.5%
associate--l+67.6%
cos-neg67.6%
Simplified67.6%
Final simplification53.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (sin (* 0.5 (- phi1 phi2))))
(t_2 (pow t_1 2.0))
(t_3 (* (cos phi1) (cos phi2))))
(if (or (<= (- lambda1 lambda2) -1e+28) (not (<= (- lambda1 lambda2) 1e-6)))
(*
(* R 2.0)
(atan2
(hypot t_1 (* (sin (* 0.5 (- lambda1 lambda2))) (sqrt t_3)))
(sqrt (- 1.0 (fma t_3 (- 0.5 (* 0.5 (cos (- lambda1 lambda2)))) t_2)))))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* t_0 (* t_3 t_0))))
(sqrt (- 1.0 t_2))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = sin((0.5 * (phi1 - phi2)));
double t_2 = pow(t_1, 2.0);
double t_3 = cos(phi1) * cos(phi2);
double tmp;
if (((lambda1 - lambda2) <= -1e+28) || !((lambda1 - lambda2) <= 1e-6)) {
tmp = (R * 2.0) * atan2(hypot(t_1, (sin((0.5 * (lambda1 - lambda2))) * sqrt(t_3))), sqrt((1.0 - fma(t_3, (0.5 - (0.5 * cos((lambda1 - lambda2)))), t_2))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * (t_3 * t_0)))), sqrt((1.0 - t_2))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sin(Float64(0.5 * Float64(phi1 - phi2))) t_2 = t_1 ^ 2.0 t_3 = Float64(cos(phi1) * cos(phi2)) tmp = 0.0 if ((Float64(lambda1 - lambda2) <= -1e+28) || !(Float64(lambda1 - lambda2) <= 1e-6)) tmp = Float64(Float64(R * 2.0) * atan(hypot(t_1, Float64(sin(Float64(0.5 * Float64(lambda1 - lambda2))) * sqrt(t_3))), sqrt(Float64(1.0 - fma(t_3, Float64(0.5 - Float64(0.5 * cos(Float64(lambda1 - lambda2)))), t_2))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_0 * Float64(t_3 * t_0)))), sqrt(Float64(1.0 - t_2))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Power[t$95$1, 2.0], $MachinePrecision]}, Block[{t$95$3 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[N[(lambda1 - lambda2), $MachinePrecision], -1e+28], N[Not[LessEqual[N[(lambda1 - lambda2), $MachinePrecision], 1e-6]], $MachinePrecision]], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[t$95$1 ^ 2 + N[(N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[Sqrt[t$95$3], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$3 * N[(0.5 - N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$0 * N[(t$95$3 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$2), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
t_2 := {t\_1}^{2}\\
t_3 := \cos \phi_1 \cdot \cos \phi_2\\
\mathbf{if}\;\lambda_1 - \lambda_2 \leq -1 \cdot 10^{+28} \lor \neg \left(\lambda_1 - \lambda_2 \leq 10^{-6}\right):\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(t\_1, \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right) \cdot \sqrt{t\_3}\right)}{\sqrt{1 - \mathsf{fma}\left(t\_3, 0.5 - 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), t\_2\right)}}\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_0 \cdot \left(t\_3 \cdot t\_0\right)}}{\sqrt{1 - t\_2}}\right)\\
\end{array}
\end{array}
if (-.f64 lambda1 lambda2) < -9.99999999999999958e27 or 9.99999999999999955e-7 < (-.f64 lambda1 lambda2) Initial program 59.6%
associate-*r*59.6%
*-commutative59.6%
Simplified59.7%
Applied egg-rr37.9%
*-lft-identity37.9%
*-commutative37.9%
*-commutative37.9%
*-commutative37.9%
Simplified37.9%
if -9.99999999999999958e27 < (-.f64 lambda1 lambda2) < 9.99999999999999955e-7Initial program 79.6%
Taylor expanded in lambda2 around 0 77.4%
Taylor expanded in lambda1 around 0 77.2%
Final simplification45.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- phi1 phi2))))
(t_1 (* (cos phi1) (cos phi2)))
(t_2 (sin (* 0.5 (- lambda1 lambda2)))))
(if (or (<= phi2 -1.1e-9) (not (<= phi2 1.55)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* t_1 (sin (/ (- lambda1 lambda2) 2.0))) (sin (* 0.5 lambda1)))))
(sqrt
(-
1.0
(+ (* (cos phi2) (pow t_2 2.0)) (pow (sin (* phi2 -0.5)) 2.0)))))))
(*
(* R 2.0)
(atan2
(hypot t_0 (* t_2 (sqrt t_1)))
(sqrt
(-
1.0
(fma
t_1
(- 0.5 (* 0.5 (cos (- lambda1 lambda2))))
(pow t_0 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (phi1 - phi2)));
double t_1 = cos(phi1) * cos(phi2);
double t_2 = sin((0.5 * (lambda1 - lambda2)));
double tmp;
if ((phi2 <= -1.1e-9) || !(phi2 <= 1.55)) {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((t_1 * sin(((lambda1 - lambda2) / 2.0))) * sin((0.5 * lambda1))))), sqrt((1.0 - ((cos(phi2) * pow(t_2, 2.0)) + pow(sin((phi2 * -0.5)), 2.0))))));
} else {
tmp = (R * 2.0) * atan2(hypot(t_0, (t_2 * sqrt(t_1))), sqrt((1.0 - fma(t_1, (0.5 - (0.5 * cos((lambda1 - lambda2)))), pow(t_0, 2.0)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(phi1 - phi2))) t_1 = Float64(cos(phi1) * cos(phi2)) t_2 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) tmp = 0.0 if ((phi2 <= -1.1e-9) || !(phi2 <= 1.55)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(t_1 * sin(Float64(Float64(lambda1 - lambda2) / 2.0))) * sin(Float64(0.5 * lambda1))))), sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * (t_2 ^ 2.0)) + (sin(Float64(phi2 * -0.5)) ^ 2.0))))))); else tmp = Float64(Float64(R * 2.0) * atan(hypot(t_0, Float64(t_2 * sqrt(t_1))), sqrt(Float64(1.0 - fma(t_1, Float64(0.5 - Float64(0.5 * cos(Float64(lambda1 - lambda2)))), (t_0 ^ 2.0)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[phi2, -1.1e-9], N[Not[LessEqual[phi2, 1.55]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(t$95$1 * 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[phi2], $MachinePrecision] * N[Power[t$95$2, 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[t$95$0 ^ 2 + N[(t$95$2 * N[Sqrt[t$95$1], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$1 * N[(0.5 - N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[t$95$0, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
t_2 := \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\\
\mathbf{if}\;\phi_2 \leq -1.1 \cdot 10^{-9} \lor \neg \left(\phi_2 \leq 1.55\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(t\_1 \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_2 \cdot {t\_2}^{2} + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(t\_0, t\_2 \cdot \sqrt{t\_1}\right)}{\sqrt{1 - \mathsf{fma}\left(t\_1, 0.5 - 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), {t\_0}^{2}\right)}}\\
\end{array}
\end{array}
if phi2 < -1.0999999999999999e-9 or 1.55000000000000004 < phi2 Initial program 47.9%
Taylor expanded in lambda2 around 0 40.2%
Taylor expanded in phi1 around 0 41.7%
if -1.0999999999999999e-9 < phi2 < 1.55000000000000004Initial program 79.0%
associate-*r*79.0%
*-commutative79.0%
Simplified79.0%
Applied egg-rr57.3%
*-lft-identity57.3%
*-commutative57.3%
*-commutative57.3%
*-commutative57.3%
Simplified57.3%
Final simplification49.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- phi1 phi2))))
(t_1 (* (cos phi1) (cos phi2)))
(t_2 (sin (* 0.5 (- lambda1 lambda2)))))
(if (or (<= phi1 -1e-15) (not (<= phi1 7.2e+22)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* t_1 (sin (/ (- lambda1 lambda2) 2.0))) (sin (* 0.5 lambda1)))))
(sqrt
(-
1.0
(+ (* (cos phi1) (pow t_2 2.0)) (pow (sin (* 0.5 phi1)) 2.0)))))))
(*
(* R 2.0)
(atan2
(hypot t_0 (* t_2 (sqrt t_1)))
(sqrt
(-
1.0
(fma
t_1
(- 0.5 (* 0.5 (cos (- lambda1 lambda2))))
(pow t_0 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (phi1 - phi2)));
double t_1 = cos(phi1) * cos(phi2);
double t_2 = sin((0.5 * (lambda1 - lambda2)));
double tmp;
if ((phi1 <= -1e-15) || !(phi1 <= 7.2e+22)) {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((t_1 * sin(((lambda1 - lambda2) / 2.0))) * sin((0.5 * lambda1))))), sqrt((1.0 - ((cos(phi1) * pow(t_2, 2.0)) + pow(sin((0.5 * phi1)), 2.0))))));
} else {
tmp = (R * 2.0) * atan2(hypot(t_0, (t_2 * sqrt(t_1))), sqrt((1.0 - fma(t_1, (0.5 - (0.5 * cos((lambda1 - lambda2)))), pow(t_0, 2.0)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(phi1 - phi2))) t_1 = Float64(cos(phi1) * cos(phi2)) t_2 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) tmp = 0.0 if ((phi1 <= -1e-15) || !(phi1 <= 7.2e+22)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(t_1 * sin(Float64(Float64(lambda1 - lambda2) / 2.0))) * sin(Float64(0.5 * lambda1))))), sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * (t_2 ^ 2.0)) + (sin(Float64(0.5 * phi1)) ^ 2.0))))))); else tmp = Float64(Float64(R * 2.0) * atan(hypot(t_0, Float64(t_2 * sqrt(t_1))), sqrt(Float64(1.0 - fma(t_1, Float64(0.5 - Float64(0.5 * cos(Float64(lambda1 - lambda2)))), (t_0 ^ 2.0)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[phi1, -1e-15], N[Not[LessEqual[phi1, 7.2e+22]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(t$95$1 * 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] * N[Power[t$95$2, 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[t$95$0 ^ 2 + N[(t$95$2 * N[Sqrt[t$95$1], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$1 * N[(0.5 - N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[t$95$0, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
t_2 := \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\\
\mathbf{if}\;\phi_1 \leq -1 \cdot 10^{-15} \lor \neg \left(\phi_1 \leq 7.2 \cdot 10^{+22}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(t\_1 \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\_2}^{2} + {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(t\_0, t\_2 \cdot \sqrt{t\_1}\right)}{\sqrt{1 - \mathsf{fma}\left(t\_1, 0.5 - 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), {t\_0}^{2}\right)}}\\
\end{array}
\end{array}
if phi1 < -1.0000000000000001e-15 or 7.2e22 < phi1 Initial program 49.7%
Taylor expanded in lambda2 around 0 35.2%
Taylor expanded in phi2 around 0 36.7%
if -1.0000000000000001e-15 < phi1 < 7.2e22Initial program 74.7%
associate-*r*74.7%
*-commutative74.7%
Simplified74.7%
Applied egg-rr54.9%
*-lft-identity54.9%
*-commutative54.9%
*-commutative54.9%
*-commutative54.9%
Simplified54.9%
Final simplification46.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (cos phi1) (cos phi2))))
(if (or (<= t_0 -0.066) (not (<= t_0 5e-7)))
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_1 (* t_0 t_0)) (- 0.5 (/ (cos (- phi1 phi2)) 2.0))))
(sqrt (- 1.0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))))))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* t_0 (* t_1 t_0))))
(sqrt (- 1.0 (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));
double t_1 = cos(phi1) * cos(phi2);
double tmp;
if ((t_0 <= -0.066) || !(t_0 <= 5e-7)) {
tmp = R * (2.0 * atan2(sqrt(((t_1 * (t_0 * t_0)) + (0.5 - (cos((phi1 - phi2)) / 2.0)))), sqrt((1.0 - pow(sin((0.5 * (lambda1 - lambda2))), 2.0)))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * (t_1 * t_0)))), sqrt((1.0 - pow(sin((0.5 * (phi1 - phi2))), 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) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = cos(phi1) * cos(phi2)
if ((t_0 <= (-0.066d0)) .or. (.not. (t_0 <= 5d-7))) then
tmp = r * (2.0d0 * atan2(sqrt(((t_1 * (t_0 * t_0)) + (0.5d0 - (cos((phi1 - phi2)) / 2.0d0)))), sqrt((1.0d0 - (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)))))
else
tmp = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (t_0 * (t_1 * t_0)))), sqrt((1.0d0 - (sin((0.5d0 * (phi1 - phi2))) ** 2.0d0)))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.cos(phi1) * Math.cos(phi2);
double tmp;
if ((t_0 <= -0.066) || !(t_0 <= 5e-7)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((t_1 * (t_0 * t_0)) + (0.5 - (Math.cos((phi1 - phi2)) / 2.0)))), Math.sqrt((1.0 - Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * (t_1 * t_0)))), Math.sqrt((1.0 - Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0)))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.cos(phi1) * math.cos(phi2) tmp = 0 if (t_0 <= -0.066) or not (t_0 <= 5e-7): tmp = R * (2.0 * math.atan2(math.sqrt(((t_1 * (t_0 * t_0)) + (0.5 - (math.cos((phi1 - phi2)) / 2.0)))), math.sqrt((1.0 - math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0))))) else: tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * (t_1 * t_0)))), math.sqrt((1.0 - math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(cos(phi1) * cos(phi2)) tmp = 0.0 if ((t_0 <= -0.066) || !(t_0 <= 5e-7)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_1 * Float64(t_0 * t_0)) + Float64(0.5 - Float64(cos(Float64(phi1 - phi2)) / 2.0)))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_0 * Float64(t_1 * t_0)))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = cos(phi1) * cos(phi2); tmp = 0.0; if ((t_0 <= -0.066) || ~((t_0 <= 5e-7))) tmp = R * (2.0 * atan2(sqrt(((t_1 * (t_0 * t_0)) + (0.5 - (cos((phi1 - phi2)) / 2.0)))), sqrt((1.0 - (sin((0.5 * (lambda1 - lambda2))) ^ 2.0))))); else tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (t_0 * (t_1 * t_0)))), sqrt((1.0 - (sin((0.5 * (phi1 - phi2))) ^ 2.0))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[t$95$0, -0.066], N[Not[LessEqual[t$95$0, 5e-7]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$1 * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision] + N[(0.5 - N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$0 * N[(t$95$1 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
\mathbf{if}\;t\_0 \leq -0.066 \lor \neg \left(t\_0 \leq 5 \cdot 10^{-7}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 \cdot \left(t\_0 \cdot t\_0\right) + \left(0.5 - \frac{\cos \left(\phi_1 - \phi_2\right)}{2}\right)}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_0 \cdot \left(t\_1 \cdot t\_0\right)}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}}}\right)\\
\end{array}
\end{array}
if (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < -0.066000000000000003 or 4.99999999999999977e-7 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) Initial program 59.4%
associate-*l*59.5%
Simplified59.4%
Taylor expanded in phi2 around 0 43.3%
Taylor expanded in phi1 around 0 35.2%
unpow259.4%
sin-mult59.5%
div-inv59.5%
metadata-eval59.5%
div-inv59.5%
metadata-eval59.5%
div-inv59.5%
metadata-eval59.5%
div-inv59.5%
metadata-eval59.5%
Applied egg-rr35.3%
div-sub59.5%
+-inverses59.5%
cos-059.5%
metadata-eval59.5%
distribute-lft-out59.5%
metadata-eval59.5%
*-rgt-identity59.5%
Simplified35.3%
if -0.066000000000000003 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < 4.99999999999999977e-7Initial program 80.4%
Taylor expanded in lambda2 around 0 80.4%
Taylor expanded in lambda1 around 0 77.6%
Final simplification43.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (cos phi1) (cos phi2)))
(t_2 (* t_1 (* t_0 t_0)))
(t_3 (sqrt (- 1.0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))))
(if (<= t_0 -0.066)
(*
R
(*
2.0
(atan2
(sqrt
(+
t_2
(pow
(+ (sin (* phi2 -0.5)) (* (cos (* 0.5 phi2)) (* 0.5 phi1)))
2.0)))
t_3)))
(if (<= t_0 5e-7)
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* t_0 (* t_1 t_0))))
(sqrt (- 1.0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0))))))
(*
R
(*
2.0
(atan2 (sqrt (+ t_2 (- 0.5 (/ (cos (- phi1 phi2)) 2.0)))) t_3)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = cos(phi1) * cos(phi2);
double t_2 = t_1 * (t_0 * t_0);
double t_3 = sqrt((1.0 - pow(sin((0.5 * (lambda1 - lambda2))), 2.0)));
double tmp;
if (t_0 <= -0.066) {
tmp = R * (2.0 * atan2(sqrt((t_2 + pow((sin((phi2 * -0.5)) + (cos((0.5 * phi2)) * (0.5 * phi1))), 2.0))), t_3));
} else if (t_0 <= 5e-7) {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * (t_1 * t_0)))), sqrt((1.0 - pow(sin((0.5 * (phi1 - phi2))), 2.0)))));
} else {
tmp = R * (2.0 * atan2(sqrt((t_2 + (0.5 - (cos((phi1 - phi2)) / 2.0)))), t_3));
}
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) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = cos(phi1) * cos(phi2)
t_2 = t_1 * (t_0 * t_0)
t_3 = sqrt((1.0d0 - (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)))
if (t_0 <= (-0.066d0)) then
tmp = r * (2.0d0 * atan2(sqrt((t_2 + ((sin((phi2 * (-0.5d0))) + (cos((0.5d0 * phi2)) * (0.5d0 * phi1))) ** 2.0d0))), t_3))
else if (t_0 <= 5d-7) then
tmp = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (t_0 * (t_1 * t_0)))), sqrt((1.0d0 - (sin((0.5d0 * (phi1 - phi2))) ** 2.0d0)))))
else
tmp = r * (2.0d0 * atan2(sqrt((t_2 + (0.5d0 - (cos((phi1 - phi2)) / 2.0d0)))), t_3))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.cos(phi1) * Math.cos(phi2);
double t_2 = t_1 * (t_0 * t_0);
double t_3 = Math.sqrt((1.0 - Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)));
double tmp;
if (t_0 <= -0.066) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_2 + Math.pow((Math.sin((phi2 * -0.5)) + (Math.cos((0.5 * phi2)) * (0.5 * phi1))), 2.0))), t_3));
} else if (t_0 <= 5e-7) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * (t_1 * t_0)))), Math.sqrt((1.0 - Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0)))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_2 + (0.5 - (Math.cos((phi1 - phi2)) / 2.0)))), t_3));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.cos(phi1) * math.cos(phi2) t_2 = t_1 * (t_0 * t_0) t_3 = math.sqrt((1.0 - math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0))) tmp = 0 if t_0 <= -0.066: tmp = R * (2.0 * math.atan2(math.sqrt((t_2 + math.pow((math.sin((phi2 * -0.5)) + (math.cos((0.5 * phi2)) * (0.5 * phi1))), 2.0))), t_3)) elif t_0 <= 5e-7: tmp = R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * (t_1 * t_0)))), math.sqrt((1.0 - math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0))))) else: tmp = R * (2.0 * math.atan2(math.sqrt((t_2 + (0.5 - (math.cos((phi1 - phi2)) / 2.0)))), t_3)) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(cos(phi1) * cos(phi2)) t_2 = Float64(t_1 * Float64(t_0 * t_0)) t_3 = sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0))) tmp = 0.0 if (t_0 <= -0.066) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_2 + (Float64(sin(Float64(phi2 * -0.5)) + Float64(cos(Float64(0.5 * phi2)) * Float64(0.5 * phi1))) ^ 2.0))), t_3))); elseif (t_0 <= 5e-7) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_0 * Float64(t_1 * t_0)))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_2 + Float64(0.5 - Float64(cos(Float64(phi1 - phi2)) / 2.0)))), t_3))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = cos(phi1) * cos(phi2); t_2 = t_1 * (t_0 * t_0); t_3 = sqrt((1.0 - (sin((0.5 * (lambda1 - lambda2))) ^ 2.0))); tmp = 0.0; if (t_0 <= -0.066) tmp = R * (2.0 * atan2(sqrt((t_2 + ((sin((phi2 * -0.5)) + (cos((0.5 * phi2)) * (0.5 * phi1))) ^ 2.0))), t_3)); elseif (t_0 <= 5e-7) tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (t_0 * (t_1 * t_0)))), sqrt((1.0 - (sin((0.5 * (phi1 - phi2))) ^ 2.0))))); else tmp = R * (2.0 * atan2(sqrt((t_2 + (0.5 - (cos((phi1 - phi2)) / 2.0)))), t_3)); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(t$95$1 * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[t$95$0, -0.066], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$2 + N[Power[N[(N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] + N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[(0.5 * phi1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$3], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$0, 5e-7], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$0 * N[(t$95$1 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$2 + N[(0.5 - N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$3], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
t_2 := t\_1 \cdot \left(t\_0 \cdot t\_0\right)\\
t_3 := \sqrt{1 - {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}\\
\mathbf{if}\;t\_0 \leq -0.066:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 + {\left(\sin \left(\phi_2 \cdot -0.5\right) + \cos \left(0.5 \cdot \phi_2\right) \cdot \left(0.5 \cdot \phi_1\right)\right)}^{2}}}{t\_3}\right)\\
\mathbf{elif}\;t\_0 \leq 5 \cdot 10^{-7}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_0 \cdot \left(t\_1 \cdot t\_0\right)}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 + \left(0.5 - \frac{\cos \left(\phi_1 - \phi_2\right)}{2}\right)}}{t\_3}\right)\\
\end{array}
\end{array}
if (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < -0.066000000000000003Initial program 57.6%
associate-*l*57.7%
Simplified57.6%
Taylor expanded in phi2 around 0 38.2%
Taylor expanded in phi1 around 0 34.3%
Taylor expanded in phi1 around 0 34.3%
associate-*r*34.3%
*-commutative34.3%
metadata-eval34.3%
distribute-rgt-neg-in34.3%
cos-neg34.3%
*-commutative34.3%
Simplified34.3%
if -0.066000000000000003 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < 4.99999999999999977e-7Initial program 80.4%
Taylor expanded in lambda2 around 0 80.4%
Taylor expanded in lambda1 around 0 77.6%
if 4.99999999999999977e-7 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) Initial program 60.9%
associate-*l*60.9%
Simplified60.9%
Taylor expanded in phi2 around 0 47.3%
Taylor expanded in phi1 around 0 36.0%
unpow260.9%
sin-mult61.0%
div-inv61.0%
metadata-eval61.0%
div-inv61.0%
metadata-eval61.0%
div-inv61.0%
metadata-eval61.0%
div-inv61.0%
metadata-eval61.0%
Applied egg-rr36.0%
div-sub61.0%
+-inverses61.0%
cos-061.0%
metadata-eval61.0%
distribute-lft-out61.0%
metadata-eval61.0%
*-rgt-identity61.0%
Simplified36.0%
Final simplification43.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (- 1.0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
(t_1 (* (cos phi1) (cos phi2)))
(t_2 (sin (/ (- lambda1 lambda2) 2.0)))
(t_3 (* t_1 (* t_2 t_2)))
(t_4 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(if (<= t_2 -0.066)
(* R (* 2.0 (atan2 (sqrt (+ t_3 t_4)) (cbrt (pow t_0 1.5)))))
(if (<= t_2 5e-7)
(*
R
(*
2.0
(atan2
(sqrt (+ t_4 (* t_2 (* t_1 t_2))))
(sqrt (- 1.0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0))))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_3 (- 0.5 (/ (cos (- phi1 phi2)) 2.0))))
(sqrt t_0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = 1.0 - pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = cos(phi1) * cos(phi2);
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double t_3 = t_1 * (t_2 * t_2);
double t_4 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double tmp;
if (t_2 <= -0.066) {
tmp = R * (2.0 * atan2(sqrt((t_3 + t_4)), cbrt(pow(t_0, 1.5))));
} else if (t_2 <= 5e-7) {
tmp = R * (2.0 * atan2(sqrt((t_4 + (t_2 * (t_1 * t_2)))), sqrt((1.0 - pow(sin((0.5 * (phi1 - phi2))), 2.0)))));
} else {
tmp = R * (2.0 * atan2(sqrt((t_3 + (0.5 - (cos((phi1 - phi2)) / 2.0)))), sqrt(t_0)));
}
return tmp;
}
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = 1.0 - Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = Math.cos(phi1) * Math.cos(phi2);
double t_2 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_3 = t_1 * (t_2 * t_2);
double t_4 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0);
double tmp;
if (t_2 <= -0.066) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_3 + t_4)), Math.cbrt(Math.pow(t_0, 1.5))));
} else if (t_2 <= 5e-7) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_4 + (t_2 * (t_1 * t_2)))), Math.sqrt((1.0 - Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0)))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_3 + (0.5 - (Math.cos((phi1 - phi2)) / 2.0)))), Math.sqrt(t_0)));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(1.0 - (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)) t_1 = Float64(cos(phi1) * cos(phi2)) t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_3 = Float64(t_1 * Float64(t_2 * t_2)) t_4 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 tmp = 0.0 if (t_2 <= -0.066) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_3 + t_4)), cbrt((t_0 ^ 1.5))))); elseif (t_2 <= 5e-7) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_4 + Float64(t_2 * Float64(t_1 * t_2)))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_3 + Float64(0.5 - Float64(cos(Float64(phi1 - phi2)) / 2.0)))), sqrt(t_0)))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[(t$95$1 * N[(t$95$2 * t$95$2), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[LessEqual[t$95$2, -0.066], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$3 + t$95$4), $MachinePrecision]], $MachinePrecision] / N[Power[N[Power[t$95$0, 1.5], $MachinePrecision], 1/3], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$2, 5e-7], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$4 + N[(t$95$2 * N[(t$95$1 * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$3 + N[(0.5 - N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[t$95$0], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := 1 - {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_3 := t\_1 \cdot \left(t\_2 \cdot t\_2\right)\\
t_4 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
\mathbf{if}\;t\_2 \leq -0.066:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_3 + t\_4}}{\sqrt[3]{{t\_0}^{1.5}}}\right)\\
\mathbf{elif}\;t\_2 \leq 5 \cdot 10^{-7}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_4 + t\_2 \cdot \left(t\_1 \cdot t\_2\right)}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_3 + \left(0.5 - \frac{\cos \left(\phi_1 - \phi_2\right)}{2}\right)}}{\sqrt{t\_0}}\right)\\
\end{array}
\end{array}
if (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < -0.066000000000000003Initial program 57.6%
associate-*l*57.7%
Simplified57.6%
Taylor expanded in phi2 around 0 38.2%
Taylor expanded in phi1 around 0 34.3%
add-cbrt-cube34.3%
pow1/334.3%
add-sqr-sqrt34.3%
pow134.3%
pow1/234.3%
pow-prod-up34.3%
metadata-eval34.3%
Applied egg-rr34.3%
unpow1/334.3%
Simplified34.3%
if -0.066000000000000003 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < 4.99999999999999977e-7Initial program 80.4%
Taylor expanded in lambda2 around 0 80.4%
Taylor expanded in lambda1 around 0 77.6%
if 4.99999999999999977e-7 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) Initial program 60.9%
associate-*l*60.9%
Simplified60.9%
Taylor expanded in phi2 around 0 47.3%
Taylor expanded in phi1 around 0 36.0%
unpow260.9%
sin-mult61.0%
div-inv61.0%
metadata-eval61.0%
div-inv61.0%
metadata-eval61.0%
div-inv61.0%
metadata-eval61.0%
div-inv61.0%
metadata-eval61.0%
Applied egg-rr36.0%
div-sub61.0%
+-inverses61.0%
cos-061.0%
metadata-eval61.0%
distribute-lft-out61.0%
metadata-eval61.0%
*-rgt-identity61.0%
Simplified36.0%
Final simplification43.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(if (<= (- lambda1 lambda2) -4e+21)
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_0 (- 0.5 (/ (cos (- lambda1 lambda2)) 2.0))) t_2))
(sqrt
(-
1.0
(pow
(-
(* (sin (/ lambda1 2.0)) (cos (/ lambda2 2.0)))
(* (cos (/ lambda1 2.0)) (sin (/ lambda2 2.0))))
2.0))))))
(if (<= (- lambda1 lambda2) 0.02)
(*
R
(*
2.0
(atan2
(sqrt (+ t_2 (* t_1 (* t_0 t_1))))
(sqrt (- 1.0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0))))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(*
t_0
(-
0.5
(/
(+
(* (cos lambda1) (cos lambda2))
(* (sin lambda1) (sin lambda2)))
2.0)))
t_2))
(sqrt (- 1.0 (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(((lambda1 - lambda2) / 2.0));
double t_2 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double tmp;
if ((lambda1 - lambda2) <= -4e+21) {
tmp = R * (2.0 * atan2(sqrt(((t_0 * (0.5 - (cos((lambda1 - lambda2)) / 2.0))) + t_2)), sqrt((1.0 - pow(((sin((lambda1 / 2.0)) * cos((lambda2 / 2.0))) - (cos((lambda1 / 2.0)) * sin((lambda2 / 2.0)))), 2.0)))));
} else if ((lambda1 - lambda2) <= 0.02) {
tmp = R * (2.0 * atan2(sqrt((t_2 + (t_1 * (t_0 * t_1)))), sqrt((1.0 - pow(sin((0.5 * (phi1 - phi2))), 2.0)))));
} else {
tmp = R * (2.0 * atan2(sqrt(((t_0 * (0.5 - (((cos(lambda1) * cos(lambda2)) + (sin(lambda1) * sin(lambda2))) / 2.0))) + t_2)), sqrt((1.0 - pow(sin((0.5 * (lambda1 - lambda2))), 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 = sin(((lambda1 - lambda2) / 2.0d0))
t_2 = sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0
if ((lambda1 - lambda2) <= (-4d+21)) then
tmp = r * (2.0d0 * atan2(sqrt(((t_0 * (0.5d0 - (cos((lambda1 - lambda2)) / 2.0d0))) + t_2)), sqrt((1.0d0 - (((sin((lambda1 / 2.0d0)) * cos((lambda2 / 2.0d0))) - (cos((lambda1 / 2.0d0)) * sin((lambda2 / 2.0d0)))) ** 2.0d0)))))
else if ((lambda1 - lambda2) <= 0.02d0) then
tmp = r * (2.0d0 * atan2(sqrt((t_2 + (t_1 * (t_0 * t_1)))), sqrt((1.0d0 - (sin((0.5d0 * (phi1 - phi2))) ** 2.0d0)))))
else
tmp = r * (2.0d0 * atan2(sqrt(((t_0 * (0.5d0 - (((cos(lambda1) * cos(lambda2)) + (sin(lambda1) * sin(lambda2))) / 2.0d0))) + t_2)), sqrt((1.0d0 - (sin((0.5d0 * (lambda1 - lambda2))) ** 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.sin(((lambda1 - lambda2) / 2.0));
double t_2 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0);
double tmp;
if ((lambda1 - lambda2) <= -4e+21) {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((t_0 * (0.5 - (Math.cos((lambda1 - lambda2)) / 2.0))) + t_2)), Math.sqrt((1.0 - Math.pow(((Math.sin((lambda1 / 2.0)) * Math.cos((lambda2 / 2.0))) - (Math.cos((lambda1 / 2.0)) * Math.sin((lambda2 / 2.0)))), 2.0)))));
} else if ((lambda1 - lambda2) <= 0.02) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_2 + (t_1 * (t_0 * t_1)))), Math.sqrt((1.0 - Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0)))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((t_0 * (0.5 - (((Math.cos(lambda1) * Math.cos(lambda2)) + (Math.sin(lambda1) * Math.sin(lambda2))) / 2.0))) + t_2)), Math.sqrt((1.0 - Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi1) * math.cos(phi2) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) t_2 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) tmp = 0 if (lambda1 - lambda2) <= -4e+21: tmp = R * (2.0 * math.atan2(math.sqrt(((t_0 * (0.5 - (math.cos((lambda1 - lambda2)) / 2.0))) + t_2)), math.sqrt((1.0 - math.pow(((math.sin((lambda1 / 2.0)) * math.cos((lambda2 / 2.0))) - (math.cos((lambda1 / 2.0)) * math.sin((lambda2 / 2.0)))), 2.0))))) elif (lambda1 - lambda2) <= 0.02: tmp = R * (2.0 * math.atan2(math.sqrt((t_2 + (t_1 * (t_0 * t_1)))), math.sqrt((1.0 - math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0))))) else: tmp = R * (2.0 * math.atan2(math.sqrt(((t_0 * (0.5 - (((math.cos(lambda1) * math.cos(lambda2)) + (math.sin(lambda1) * math.sin(lambda2))) / 2.0))) + t_2)), math.sqrt((1.0 - math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 tmp = 0.0 if (Float64(lambda1 - lambda2) <= -4e+21) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_0 * Float64(0.5 - Float64(cos(Float64(lambda1 - lambda2)) / 2.0))) + t_2)), sqrt(Float64(1.0 - (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)))))); elseif (Float64(lambda1 - lambda2) <= 0.02) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_2 + Float64(t_1 * Float64(t_0 * t_1)))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_0 * Float64(0.5 - Float64(Float64(Float64(cos(lambda1) * cos(lambda2)) + Float64(sin(lambda1) * sin(lambda2))) / 2.0))) + t_2)), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi1) * cos(phi2); t_1 = sin(((lambda1 - lambda2) / 2.0)); t_2 = sin(((phi1 - phi2) / 2.0)) ^ 2.0; tmp = 0.0; if ((lambda1 - lambda2) <= -4e+21) tmp = R * (2.0 * atan2(sqrt(((t_0 * (0.5 - (cos((lambda1 - lambda2)) / 2.0))) + t_2)), sqrt((1.0 - (((sin((lambda1 / 2.0)) * cos((lambda2 / 2.0))) - (cos((lambda1 / 2.0)) * sin((lambda2 / 2.0)))) ^ 2.0))))); elseif ((lambda1 - lambda2) <= 0.02) tmp = R * (2.0 * atan2(sqrt((t_2 + (t_1 * (t_0 * t_1)))), sqrt((1.0 - (sin((0.5 * (phi1 - phi2))) ^ 2.0))))); else tmp = R * (2.0 * atan2(sqrt(((t_0 * (0.5 - (((cos(lambda1) * cos(lambda2)) + (sin(lambda1) * sin(lambda2))) / 2.0))) + t_2)), sqrt((1.0 - (sin((0.5 * (lambda1 - lambda2))) ^ 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[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[LessEqual[N[(lambda1 - lambda2), $MachinePrecision], -4e+21], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$0 * N[(0.5 - N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$2), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - 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]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[N[(lambda1 - lambda2), $MachinePrecision], 0.02], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$2 + N[(t$95$1 * N[(t$95$0 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$0 * N[(0.5 - N[(N[(N[(N[Cos[lambda1], $MachinePrecision] * N[Cos[lambda2], $MachinePrecision]), $MachinePrecision] + N[(N[Sin[lambda1], $MachinePrecision] * N[Sin[lambda2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$2), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
\mathbf{if}\;\lambda_1 - \lambda_2 \leq -4 \cdot 10^{+21}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 \cdot \left(0.5 - \frac{\cos \left(\lambda_1 - \lambda_2\right)}{2}\right) + t\_2}}{\sqrt{1 - {\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)\\
\mathbf{elif}\;\lambda_1 - \lambda_2 \leq 0.02:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 + t\_1 \cdot \left(t\_0 \cdot t\_1\right)}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 \cdot \left(0.5 - \frac{\cos \lambda_1 \cdot \cos \lambda_2 + \sin \lambda_1 \cdot \sin \lambda_2}{2}\right) + t\_2}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}\right)\\
\end{array}
\end{array}
if (-.f64 lambda1 lambda2) < -4e21Initial program 59.4%
associate-*l*59.5%
Simplified59.4%
Taylor expanded in phi2 around 0 40.9%
Taylor expanded in phi1 around 0 37.6%
sin-mult75.5%
cos-sum75.3%
cos-275.5%
div-sub75.5%
+-inverses75.5%
Applied egg-rr37.5%
cos-075.5%
metadata-eval75.5%
Simplified37.5%
*-commutative37.5%
metadata-eval37.5%
div-inv37.5%
div-sub37.5%
sin-diff38.4%
Applied egg-rr38.4%
if -4e21 < (-.f64 lambda1 lambda2) < 0.0200000000000000004Initial program 80.7%
Taylor expanded in lambda2 around 0 77.4%
Taylor expanded in lambda1 around 0 77.2%
if 0.0200000000000000004 < (-.f64 lambda1 lambda2) Initial program 59.1%
associate-*l*59.1%
Simplified59.1%
Taylor expanded in phi2 around 0 43.4%
Taylor expanded in phi1 around 0 32.3%
sin-mult66.0%
cos-sum66.0%
cos-266.0%
div-sub66.0%
+-inverses66.0%
Applied egg-rr32.2%
cos-066.0%
metadata-eval66.0%
Simplified32.2%
cos-diff66.8%
Applied egg-rr32.7%
Final simplification44.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (- 1.0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 - pow(sin((0.5 * (lambda1 - lambda2))), 2.0)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt((1.0d0 - (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((((Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0)) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt((1.0 - Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) return R * (2.0 * math.atan2(math.sqrt((((math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0)) + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt((1.0 - math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0)))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); tmp = R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt((1.0 - (sin((0.5 * (lambda1 - lambda2))) ^ 2.0))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}\right)
\end{array}
\end{array}
Initial program 63.7%
associate-*l*63.7%
Simplified63.7%
Taylor expanded in phi2 around 0 44.4%
Taylor expanded in phi1 around 0 36.1%
Final simplification36.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))
(- 0.5 (/ (cos (- phi1 phi2)) 2.0))))
(sqrt (- 1.0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + (0.5 - (cos((phi1 - phi2)) / 2.0)))), sqrt((1.0 - pow(sin((0.5 * (lambda1 - lambda2))), 2.0)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + (0.5d0 - (cos((phi1 - phi2)) / 2.0d0)))), sqrt((1.0d0 - (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((((Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0)) + (0.5 - (Math.cos((phi1 - phi2)) / 2.0)))), Math.sqrt((1.0 - Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) return R * (2.0 * math.atan2(math.sqrt((((math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0)) + (0.5 - (math.cos((phi1 - phi2)) / 2.0)))), math.sqrt((1.0 - math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0)))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) + Float64(0.5 - Float64(cos(Float64(phi1 - phi2)) / 2.0)))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); tmp = R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (t_0 * t_0)) + (0.5 - (cos((phi1 - phi2)) / 2.0)))), sqrt((1.0 - (sin((0.5 * (lambda1 - lambda2))) ^ 2.0))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision] + N[(0.5 - N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right) + \left(0.5 - \frac{\cos \left(\phi_1 - \phi_2\right)}{2}\right)}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}\right)
\end{array}
\end{array}
Initial program 63.7%
associate-*l*63.7%
Simplified63.7%
Taylor expanded in phi2 around 0 44.4%
Taylor expanded in phi1 around 0 36.1%
unpow263.7%
sin-mult63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
Applied egg-rr34.5%
div-sub63.8%
+-inverses63.8%
cos-063.8%
metadata-eval63.8%
distribute-lft-out63.8%
metadata-eval63.8%
*-rgt-identity63.8%
Simplified34.5%
Final simplification34.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (* (cos phi1) (cos phi2)) (- 0.5 (/ (cos (- lambda1 lambda2)) 2.0)))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (- 1.0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (0.5 - (cos((lambda1 - lambda2)) / 2.0))) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 - pow(sin((0.5 * (lambda1 - lambda2))), 2.0)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
code = r * (2.0d0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (0.5d0 - (cos((lambda1 - lambda2)) / 2.0d0))) + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt((1.0d0 - (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * Math.atan2(Math.sqrt((((Math.cos(phi1) * Math.cos(phi2)) * (0.5 - (Math.cos((lambda1 - lambda2)) / 2.0))) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt((1.0 - Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)))));
}
def code(R, lambda1, lambda2, phi1, phi2): return R * (2.0 * math.atan2(math.sqrt((((math.cos(phi1) * math.cos(phi2)) * (0.5 - (math.cos((lambda1 - lambda2)) / 2.0))) + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt((1.0 - math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0)))))
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(Float64(cos(phi1) * cos(phi2)) * Float64(0.5 - Float64(cos(Float64(lambda1 - lambda2)) / 2.0))) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) tmp = R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (0.5 - (cos((lambda1 - lambda2)) / 2.0))) + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt((1.0 - (sin((0.5 * (lambda1 - lambda2))) ^ 2.0))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(0.5 - N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(0.5 - \frac{\cos \left(\lambda_1 - \lambda_2\right)}{2}\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}\right)
\end{array}
Initial program 63.7%
associate-*l*63.7%
Simplified63.7%
Taylor expanded in phi2 around 0 44.4%
Taylor expanded in phi1 around 0 36.1%
sin-mult76.6%
cos-sum76.5%
cos-276.6%
div-sub76.6%
+-inverses76.6%
Applied egg-rr33.1%
cos-076.6%
metadata-eval76.6%
Simplified33.1%
Final simplification33.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (* (cos phi1) (cos phi2)) (- 0.5 (/ (cos (- lambda1 lambda2)) 2.0)))
(- 0.5 (/ (cos (- phi1 phi2)) 2.0))))
(sqrt (- 1.0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (0.5 - (cos((lambda1 - lambda2)) / 2.0))) + (0.5 - (cos((phi1 - phi2)) / 2.0)))), sqrt((1.0 - pow(sin((0.5 * (lambda1 - lambda2))), 2.0)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
code = r * (2.0d0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (0.5d0 - (cos((lambda1 - lambda2)) / 2.0d0))) + (0.5d0 - (cos((phi1 - phi2)) / 2.0d0)))), sqrt((1.0d0 - (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * Math.atan2(Math.sqrt((((Math.cos(phi1) * Math.cos(phi2)) * (0.5 - (Math.cos((lambda1 - lambda2)) / 2.0))) + (0.5 - (Math.cos((phi1 - phi2)) / 2.0)))), Math.sqrt((1.0 - Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)))));
}
def code(R, lambda1, lambda2, phi1, phi2): return R * (2.0 * math.atan2(math.sqrt((((math.cos(phi1) * math.cos(phi2)) * (0.5 - (math.cos((lambda1 - lambda2)) / 2.0))) + (0.5 - (math.cos((phi1 - phi2)) / 2.0)))), math.sqrt((1.0 - math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0)))))
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(Float64(cos(phi1) * cos(phi2)) * Float64(0.5 - Float64(cos(Float64(lambda1 - lambda2)) / 2.0))) + Float64(0.5 - Float64(cos(Float64(phi1 - phi2)) / 2.0)))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) tmp = R * (2.0 * atan2(sqrt((((cos(phi1) * cos(phi2)) * (0.5 - (cos((lambda1 - lambda2)) / 2.0))) + (0.5 - (cos((phi1 - phi2)) / 2.0)))), sqrt((1.0 - (sin((0.5 * (lambda1 - lambda2))) ^ 2.0))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(0.5 - N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(0.5 - N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(0.5 - \frac{\cos \left(\lambda_1 - \lambda_2\right)}{2}\right) + \left(0.5 - \frac{\cos \left(\phi_1 - \phi_2\right)}{2}\right)}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}\right)
\end{array}
Initial program 63.7%
associate-*l*63.7%
Simplified63.7%
Taylor expanded in phi2 around 0 44.4%
Taylor expanded in phi1 around 0 36.1%
sin-mult76.6%
cos-sum76.5%
cos-276.6%
div-sub76.6%
+-inverses76.6%
Applied egg-rr33.1%
cos-076.6%
metadata-eval76.6%
Simplified33.1%
unpow263.7%
sin-mult63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
div-inv63.8%
metadata-eval63.8%
Applied egg-rr31.5%
div-sub63.8%
+-inverses63.8%
cos-063.8%
metadata-eval63.8%
distribute-lft-out63.8%
metadata-eval63.8%
*-rgt-identity63.8%
Simplified31.5%
Final simplification31.5%
herbie shell --seed 2024123
(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))))))))))