
(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 23 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 lambda1) (sin lambda2)))
(t_1 (* (cos phi1) (cos phi2)))
(t_2
(pow
(-
(* (cos (* 0.5 phi2)) (sin (* phi1 0.5)))
(* (sin (* 0.5 phi2)) (cos (* phi1 0.5))))
2.0))
(t_3 (* (cos lambda2) (cos lambda1)))
(t_4 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_2 (* t_1 (* t_4 t_4))))
(sqrt
(+
(- 1.0 t_2)
(*
t_1
(-
(/
(/
(+ (pow t_3 3.0) (pow t_0 3.0))
(fma t_3 t_3 (* t_0 (- t_0 t_3))))
2.0)
0.5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(lambda1) * sin(lambda2);
double t_1 = cos(phi1) * cos(phi2);
double t_2 = pow(((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (sin((0.5 * phi2)) * cos((phi1 * 0.5)))), 2.0);
double t_3 = cos(lambda2) * cos(lambda1);
double t_4 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((t_2 + (t_1 * (t_4 * t_4)))), sqrt(((1.0 - t_2) + (t_1 * ((((pow(t_3, 3.0) + pow(t_0, 3.0)) / fma(t_3, t_3, (t_0 * (t_0 - t_3)))) / 2.0) - 0.5))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(sin(lambda1) * sin(lambda2)) t_1 = Float64(cos(phi1) * cos(phi2)) t_2 = Float64(Float64(cos(Float64(0.5 * phi2)) * sin(Float64(phi1 * 0.5))) - Float64(sin(Float64(0.5 * phi2)) * cos(Float64(phi1 * 0.5)))) ^ 2.0 t_3 = Float64(cos(lambda2) * cos(lambda1)) t_4 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_2 + Float64(t_1 * Float64(t_4 * t_4)))), sqrt(Float64(Float64(1.0 - t_2) + Float64(t_1 * Float64(Float64(Float64(Float64((t_3 ^ 3.0) + (t_0 ^ 3.0)) / fma(t_3, t_3, Float64(t_0 * Float64(t_0 - t_3)))) / 2.0) - 0.5))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Sin[lambda1], $MachinePrecision] * N[Sin[lambda2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Power[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$3 = N[(N[Cos[lambda2], $MachinePrecision] * N[Cos[lambda1], $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[(t$95$2 + N[(t$95$1 * N[(t$95$4 * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - t$95$2), $MachinePrecision] + N[(t$95$1 * N[(N[(N[(N[(N[Power[t$95$3, 3.0], $MachinePrecision] + N[Power[t$95$0, 3.0], $MachinePrecision]), $MachinePrecision] / N[(t$95$3 * t$95$3 + N[(t$95$0 * N[(t$95$0 - t$95$3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \lambda_1 \cdot \sin \lambda_2\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
t_2 := {\left(\cos \left(0.5 \cdot \phi_2\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \sin \left(0.5 \cdot \phi_2\right) \cdot \cos \left(\phi_1 \cdot 0.5\right)\right)}^{2}\\
t_3 := \cos \lambda_2 \cdot \cos \lambda_1\\
t_4 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 + t\_1 \cdot \left(t\_4 \cdot t\_4\right)}}{\sqrt{\left(1 - t\_2\right) + t\_1 \cdot \left(\frac{\frac{{t\_3}^{3} + {t\_0}^{3}}{\mathsf{fma}\left(t\_3, t\_3, t\_0 \cdot \left(t\_0 - t\_3\right)\right)}}{2} - 0.5\right)}}\right)
\end{array}
\end{array}
Initial program 66.8%
associate-*l*66.8%
Simplified66.8%
div-sub66.8%
sin-diff67.8%
div-inv67.8%
metadata-eval67.8%
div-inv67.8%
metadata-eval67.8%
div-inv67.8%
metadata-eval67.8%
div-inv67.8%
metadata-eval67.8%
Applied egg-rr67.8%
div-sub66.8%
sin-diff67.8%
div-inv67.8%
metadata-eval67.8%
div-inv67.8%
metadata-eval67.8%
div-inv67.8%
metadata-eval67.8%
div-inv67.8%
metadata-eval67.8%
Applied egg-rr80.6%
sin-mult80.6%
cos-sum80.6%
cos-280.6%
div-sub80.6%
+-inverses80.6%
Applied egg-rr80.6%
cos-080.6%
metadata-eval80.6%
Simplified80.6%
cos-diff81.1%
flip3-+81.1%
Applied egg-rr81.1%
cos-neg81.1%
*-commutative81.1%
cos-neg81.1%
fma-define81.1%
Simplified81.1%
Final simplification81.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1
(pow
(-
(* (cos (* 0.5 phi2)) (sin (* phi1 0.5)))
(* (sin (* 0.5 phi2)) (cos (* phi1 0.5))))
2.0))
(t_2 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (* t_0 (* t_2 t_2))))
(sqrt
(+
(- 1.0 t_1)
(*
t_0
(-
(/
(+ (* (cos lambda2) (cos lambda1)) (* (sin lambda1) (sin lambda2)))
2.0)
0.5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = pow(((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (sin((0.5 * phi2)) * cos((phi1 * 0.5)))), 2.0);
double t_2 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((t_1 + (t_0 * (t_2 * t_2)))), sqrt(((1.0 - t_1) + (t_0 * ((((cos(lambda2) * cos(lambda1)) + (sin(lambda1) * sin(lambda2))) / 2.0) - 0.5))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
t_0 = cos(phi1) * cos(phi2)
t_1 = ((cos((0.5d0 * phi2)) * sin((phi1 * 0.5d0))) - (sin((0.5d0 * phi2)) * cos((phi1 * 0.5d0)))) ** 2.0d0
t_2 = sin(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2(sqrt((t_1 + (t_0 * (t_2 * t_2)))), sqrt(((1.0d0 - t_1) + (t_0 * ((((cos(lambda2) * cos(lambda1)) + (sin(lambda1) * sin(lambda2))) / 2.0d0) - 0.5d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.cos(phi1) * Math.cos(phi2);
double t_1 = Math.pow(((Math.cos((0.5 * phi2)) * Math.sin((phi1 * 0.5))) - (Math.sin((0.5 * phi2)) * Math.cos((phi1 * 0.5)))), 2.0);
double t_2 = Math.sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((t_1 + (t_0 * (t_2 * t_2)))), Math.sqrt(((1.0 - t_1) + (t_0 * ((((Math.cos(lambda2) * Math.cos(lambda1)) + (Math.sin(lambda1) * Math.sin(lambda2))) / 2.0) - 0.5))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi1) * math.cos(phi2) t_1 = math.pow(((math.cos((0.5 * phi2)) * math.sin((phi1 * 0.5))) - (math.sin((0.5 * phi2)) * math.cos((phi1 * 0.5)))), 2.0) t_2 = math.sin(((lambda1 - lambda2) / 2.0)) return R * (2.0 * math.atan2(math.sqrt((t_1 + (t_0 * (t_2 * t_2)))), math.sqrt(((1.0 - t_1) + (t_0 * ((((math.cos(lambda2) * math.cos(lambda1)) + (math.sin(lambda1) * math.sin(lambda2))) / 2.0) - 0.5))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = Float64(Float64(cos(Float64(0.5 * phi2)) * sin(Float64(phi1 * 0.5))) - Float64(sin(Float64(0.5 * phi2)) * cos(Float64(phi1 * 0.5)))) ^ 2.0 t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + Float64(t_0 * Float64(t_2 * t_2)))), sqrt(Float64(Float64(1.0 - t_1) + Float64(t_0 * Float64(Float64(Float64(Float64(cos(lambda2) * cos(lambda1)) + Float64(sin(lambda1) * sin(lambda2))) / 2.0) - 0.5))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi1) * cos(phi2); t_1 = ((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (sin((0.5 * phi2)) * cos((phi1 * 0.5)))) ^ 2.0; t_2 = sin(((lambda1 - lambda2) / 2.0)); tmp = R * (2.0 * atan2(sqrt((t_1 + (t_0 * (t_2 * t_2)))), sqrt(((1.0 - t_1) + (t_0 * ((((cos(lambda2) * cos(lambda1)) + (sin(lambda1) * sin(lambda2))) / 2.0) - 0.5)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Power[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[(t$95$0 * N[(t$95$2 * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - t$95$1), $MachinePrecision] + N[(t$95$0 * N[(N[(N[(N[(N[Cos[lambda2], $MachinePrecision] * N[Cos[lambda1], $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 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := {\left(\cos \left(0.5 \cdot \phi_2\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \sin \left(0.5 \cdot \phi_2\right) \cdot \cos \left(\phi_1 \cdot 0.5\right)\right)}^{2}\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + t\_0 \cdot \left(t\_2 \cdot t\_2\right)}}{\sqrt{\left(1 - t\_1\right) + t\_0 \cdot \left(\frac{\cos \lambda_2 \cdot \cos \lambda_1 + \sin \lambda_1 \cdot \sin \lambda_2}{2} - 0.5\right)}}\right)
\end{array}
\end{array}
Initial program 66.8%
associate-*l*66.8%
Simplified66.8%
div-sub66.8%
sin-diff67.8%
div-inv67.8%
metadata-eval67.8%
div-inv67.8%
metadata-eval67.8%
div-inv67.8%
metadata-eval67.8%
div-inv67.8%
metadata-eval67.8%
Applied egg-rr67.8%
div-sub66.8%
sin-diff67.8%
div-inv67.8%
metadata-eval67.8%
div-inv67.8%
metadata-eval67.8%
div-inv67.8%
metadata-eval67.8%
div-inv67.8%
metadata-eval67.8%
Applied egg-rr80.6%
sin-mult80.6%
cos-sum80.6%
cos-280.6%
div-sub80.6%
+-inverses80.6%
Applied egg-rr80.6%
cos-080.6%
metadata-eval80.6%
Simplified80.6%
cos-diff81.1%
+-commutative81.1%
Applied egg-rr81.1%
Final simplification81.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* phi1 0.5)))
(t_1 (cos (* phi1 0.5)))
(t_2 (* (cos phi1) (cos phi2)))
(t_3 (sin (/ (- lambda1 lambda2) 2.0)))
(t_4 (cos (* 0.5 phi2))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (- (* t_4 t_0) (* (sin (* 0.5 phi2)) t_1)) 2.0)
(* t_2 (* t_3 t_3))))
(sqrt
(+
(- 1.0 (pow (fma t_0 t_4 (* t_1 (sin (* phi2 -0.5)))) 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((phi1 * 0.5));
double t_1 = cos((phi1 * 0.5));
double t_2 = cos(phi1) * cos(phi2);
double t_3 = sin(((lambda1 - lambda2) / 2.0));
double t_4 = cos((0.5 * phi2));
return R * (2.0 * atan2(sqrt((pow(((t_4 * t_0) - (sin((0.5 * phi2)) * t_1)), 2.0) + (t_2 * (t_3 * t_3)))), sqrt(((1.0 - pow(fma(t_0, t_4, (t_1 * sin((phi2 * -0.5)))), 2.0)) + (t_2 * ((cos((lambda1 - lambda2)) / 2.0) - 0.5))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi1 * 0.5)) t_1 = cos(Float64(phi1 * 0.5)) t_2 = Float64(cos(phi1) * cos(phi2)) t_3 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_4 = cos(Float64(0.5 * phi2)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((Float64(Float64(t_4 * t_0) - Float64(sin(Float64(0.5 * phi2)) * t_1)) ^ 2.0) + Float64(t_2 * Float64(t_3 * t_3)))), sqrt(Float64(Float64(1.0 - (fma(t_0, t_4, Float64(t_1 * sin(Float64(phi2 * -0.5)))) ^ 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[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[(t$95$4 * t$95$0), $MachinePrecision] - N[(N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$2 * N[(t$95$3 * t$95$3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[(t$95$0 * t$95$4 + N[(t$95$1 * N[Sin[N[(phi2 * -0.5), $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(\phi_1 \cdot 0.5\right)\\
t_1 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
t_3 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_4 := \cos \left(0.5 \cdot \phi_2\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(t\_4 \cdot t\_0 - \sin \left(0.5 \cdot \phi_2\right) \cdot t\_1\right)}^{2} + t\_2 \cdot \left(t\_3 \cdot t\_3\right)}}{\sqrt{\left(1 - {\left(\mathsf{fma}\left(t\_0, t\_4, t\_1 \cdot \sin \left(\phi_2 \cdot -0.5\right)\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 66.8%
associate-*l*66.8%
Simplified66.8%
div-sub66.8%
sin-diff67.8%
div-inv67.8%
metadata-eval67.8%
div-inv67.8%
metadata-eval67.8%
div-inv67.8%
metadata-eval67.8%
div-inv67.8%
metadata-eval67.8%
Applied egg-rr67.8%
div-sub66.8%
sin-diff67.8%
div-inv67.8%
metadata-eval67.8%
div-inv67.8%
metadata-eval67.8%
div-inv67.8%
metadata-eval67.8%
div-inv67.8%
metadata-eval67.8%
Applied egg-rr80.6%
sin-mult80.6%
cos-sum80.6%
cos-280.6%
div-sub80.6%
+-inverses80.6%
Applied egg-rr80.6%
cos-080.6%
metadata-eval80.6%
Simplified80.6%
Taylor expanded in phi1 around inf 80.6%
*-commutative80.6%
fma-neg80.6%
distribute-rgt-neg-in80.6%
sin-neg80.6%
distribute-lft-neg-in80.6%
metadata-eval80.6%
*-commutative80.6%
Simplified80.6%
Final simplification80.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1
(pow
(-
(* (cos (* 0.5 phi2)) (sin (* phi1 0.5)))
(* (sin (* 0.5 phi2)) (cos (* phi1 0.5))))
2.0))
(t_2 (sin (/ (- lambda1 lambda2) 2.0)))
(t_3
(sqrt
(+ (- 1.0 t_1) (* t_0 (- (/ (cos (- lambda1 lambda2)) 2.0) 0.5))))))
(if (or (<= lambda2 -0.0015) (not (<= lambda2 0.0045)))
(*
R
(*
2.0
(atan2 (sqrt (+ t_1 (* t_0 (* t_2 (sin (* lambda2 -0.5)))))) t_3)))
(*
R
(*
2.0
(atan2 (sqrt (+ t_1 (* t_0 (* t_2 (sin (* 0.5 lambda1)))))) t_3))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = pow(((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (sin((0.5 * phi2)) * cos((phi1 * 0.5)))), 2.0);
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double t_3 = sqrt(((1.0 - t_1) + (t_0 * ((cos((lambda1 - lambda2)) / 2.0) - 0.5))));
double tmp;
if ((lambda2 <= -0.0015) || !(lambda2 <= 0.0045)) {
tmp = R * (2.0 * atan2(sqrt((t_1 + (t_0 * (t_2 * sin((lambda2 * -0.5)))))), t_3));
} else {
tmp = R * (2.0 * atan2(sqrt((t_1 + (t_0 * (t_2 * sin((0.5 * lambda1)))))), 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 = cos(phi1) * cos(phi2)
t_1 = ((cos((0.5d0 * phi2)) * sin((phi1 * 0.5d0))) - (sin((0.5d0 * phi2)) * cos((phi1 * 0.5d0)))) ** 2.0d0
t_2 = sin(((lambda1 - lambda2) / 2.0d0))
t_3 = sqrt(((1.0d0 - t_1) + (t_0 * ((cos((lambda1 - lambda2)) / 2.0d0) - 0.5d0))))
if ((lambda2 <= (-0.0015d0)) .or. (.not. (lambda2 <= 0.0045d0))) then
tmp = r * (2.0d0 * atan2(sqrt((t_1 + (t_0 * (t_2 * sin((lambda2 * (-0.5d0))))))), t_3))
else
tmp = r * (2.0d0 * atan2(sqrt((t_1 + (t_0 * (t_2 * sin((0.5d0 * lambda1)))))), 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.cos(phi1) * Math.cos(phi2);
double t_1 = Math.pow(((Math.cos((0.5 * phi2)) * Math.sin((phi1 * 0.5))) - (Math.sin((0.5 * phi2)) * Math.cos((phi1 * 0.5)))), 2.0);
double t_2 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_3 = Math.sqrt(((1.0 - t_1) + (t_0 * ((Math.cos((lambda1 - lambda2)) / 2.0) - 0.5))));
double tmp;
if ((lambda2 <= -0.0015) || !(lambda2 <= 0.0045)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_1 + (t_0 * (t_2 * Math.sin((lambda2 * -0.5)))))), t_3));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_1 + (t_0 * (t_2 * Math.sin((0.5 * lambda1)))))), t_3));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi1) * math.cos(phi2) t_1 = math.pow(((math.cos((0.5 * phi2)) * math.sin((phi1 * 0.5))) - (math.sin((0.5 * phi2)) * math.cos((phi1 * 0.5)))), 2.0) t_2 = math.sin(((lambda1 - lambda2) / 2.0)) t_3 = math.sqrt(((1.0 - t_1) + (t_0 * ((math.cos((lambda1 - lambda2)) / 2.0) - 0.5)))) tmp = 0 if (lambda2 <= -0.0015) or not (lambda2 <= 0.0045): tmp = R * (2.0 * math.atan2(math.sqrt((t_1 + (t_0 * (t_2 * math.sin((lambda2 * -0.5)))))), t_3)) else: tmp = R * (2.0 * math.atan2(math.sqrt((t_1 + (t_0 * (t_2 * math.sin((0.5 * lambda1)))))), t_3)) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = Float64(Float64(cos(Float64(0.5 * phi2)) * sin(Float64(phi1 * 0.5))) - Float64(sin(Float64(0.5 * phi2)) * cos(Float64(phi1 * 0.5)))) ^ 2.0 t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_3 = sqrt(Float64(Float64(1.0 - t_1) + Float64(t_0 * Float64(Float64(cos(Float64(lambda1 - lambda2)) / 2.0) - 0.5)))) tmp = 0.0 if ((lambda2 <= -0.0015) || !(lambda2 <= 0.0045)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + Float64(t_0 * Float64(t_2 * sin(Float64(lambda2 * -0.5)))))), t_3))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + Float64(t_0 * Float64(t_2 * sin(Float64(0.5 * lambda1)))))), t_3))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi1) * cos(phi2); t_1 = ((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (sin((0.5 * phi2)) * cos((phi1 * 0.5)))) ^ 2.0; t_2 = sin(((lambda1 - lambda2) / 2.0)); t_3 = sqrt(((1.0 - t_1) + (t_0 * ((cos((lambda1 - lambda2)) / 2.0) - 0.5)))); tmp = 0.0; if ((lambda2 <= -0.0015) || ~((lambda2 <= 0.0045))) tmp = R * (2.0 * atan2(sqrt((t_1 + (t_0 * (t_2 * sin((lambda2 * -0.5)))))), t_3)); else tmp = R * (2.0 * atan2(sqrt((t_1 + (t_0 * (t_2 * sin((0.5 * lambda1)))))), t_3)); 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[Power[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Sqrt[N[(N[(1.0 - t$95$1), $MachinePrecision] + N[(t$95$0 * N[(N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[lambda2, -0.0015], N[Not[LessEqual[lambda2, 0.0045]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[(t$95$0 * N[(t$95$2 * N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$3], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[(t$95$0 * N[(t$95$2 * N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$3], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := {\left(\cos \left(0.5 \cdot \phi_2\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \sin \left(0.5 \cdot \phi_2\right) \cdot \cos \left(\phi_1 \cdot 0.5\right)\right)}^{2}\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_3 := \sqrt{\left(1 - t\_1\right) + t\_0 \cdot \left(\frac{\cos \left(\lambda_1 - \lambda_2\right)}{2} - 0.5\right)}\\
\mathbf{if}\;\lambda_2 \leq -0.0015 \lor \neg \left(\lambda_2 \leq 0.0045\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + t\_0 \cdot \left(t\_2 \cdot \sin \left(\lambda_2 \cdot -0.5\right)\right)}}{t\_3}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + t\_0 \cdot \left(t\_2 \cdot \sin \left(0.5 \cdot \lambda_1\right)\right)}}{t\_3}\right)\\
\end{array}
\end{array}
if lambda2 < -0.0015 or 0.00449999999999999966 < lambda2 Initial program 53.4%
associate-*l*53.4%
Simplified53.4%
div-sub53.4%
sin-diff54.3%
div-inv54.3%
metadata-eval54.3%
div-inv54.3%
metadata-eval54.3%
div-inv54.3%
metadata-eval54.3%
div-inv54.3%
metadata-eval54.3%
Applied egg-rr54.3%
div-sub53.4%
sin-diff54.3%
div-inv54.3%
metadata-eval54.3%
div-inv54.3%
metadata-eval54.3%
div-inv54.3%
metadata-eval54.3%
div-inv54.3%
metadata-eval54.3%
Applied egg-rr62.4%
sin-mult62.4%
cos-sum62.4%
cos-262.4%
div-sub62.4%
+-inverses62.4%
Applied egg-rr62.4%
cos-062.4%
metadata-eval62.4%
Simplified62.4%
Taylor expanded in lambda1 around 0 60.4%
if -0.0015 < lambda2 < 0.00449999999999999966Initial program 79.5%
associate-*l*79.6%
Simplified79.6%
div-sub79.6%
sin-diff80.8%
div-inv80.8%
metadata-eval80.8%
div-inv80.8%
metadata-eval80.8%
div-inv80.8%
metadata-eval80.8%
div-inv80.8%
metadata-eval80.8%
Applied egg-rr80.8%
div-sub79.6%
sin-diff80.8%
div-inv80.8%
metadata-eval80.8%
div-inv80.8%
metadata-eval80.8%
div-inv80.8%
metadata-eval80.8%
div-inv80.8%
metadata-eval80.8%
Applied egg-rr97.9%
sin-mult98.0%
cos-sum98.0%
cos-298.0%
div-sub98.0%
+-inverses98.0%
Applied egg-rr98.0%
cos-098.0%
metadata-eval98.0%
Simplified98.0%
Taylor expanded in lambda2 around 0 95.2%
Final simplification78.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1
(pow
(-
(* (cos (* 0.5 phi2)) (sin (* phi1 0.5)))
(* (sin (* 0.5 phi2)) (cos (* phi1 0.5))))
2.0))
(t_2 (sin (/ (- lambda1 lambda2) 2.0)))
(t_3 (- 1.0 t_1)))
(if (or (<= lambda2 -0.0015) (not (<= lambda2 0.0045)))
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (* t_0 (* t_2 (sin (* lambda2 -0.5))))))
(sqrt (+ t_3 (* t_0 (- (/ (cos (- lambda1 lambda2)) 2.0) 0.5)))))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (* t_0 (* t_2 t_2))))
(sqrt (+ t_3 (* t_0 (- (/ (cos lambda1) 2.0) 0.5))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = pow(((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (sin((0.5 * phi2)) * cos((phi1 * 0.5)))), 2.0);
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double t_3 = 1.0 - t_1;
double tmp;
if ((lambda2 <= -0.0015) || !(lambda2 <= 0.0045)) {
tmp = R * (2.0 * atan2(sqrt((t_1 + (t_0 * (t_2 * sin((lambda2 * -0.5)))))), sqrt((t_3 + (t_0 * ((cos((lambda1 - lambda2)) / 2.0) - 0.5))))));
} else {
tmp = R * (2.0 * atan2(sqrt((t_1 + (t_0 * (t_2 * t_2)))), sqrt((t_3 + (t_0 * ((cos(lambda1) / 2.0) - 0.5))))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: t_3
real(8) :: tmp
t_0 = cos(phi1) * cos(phi2)
t_1 = ((cos((0.5d0 * phi2)) * sin((phi1 * 0.5d0))) - (sin((0.5d0 * phi2)) * cos((phi1 * 0.5d0)))) ** 2.0d0
t_2 = sin(((lambda1 - lambda2) / 2.0d0))
t_3 = 1.0d0 - t_1
if ((lambda2 <= (-0.0015d0)) .or. (.not. (lambda2 <= 0.0045d0))) then
tmp = r * (2.0d0 * atan2(sqrt((t_1 + (t_0 * (t_2 * sin((lambda2 * (-0.5d0))))))), sqrt((t_3 + (t_0 * ((cos((lambda1 - lambda2)) / 2.0d0) - 0.5d0))))))
else
tmp = r * (2.0d0 * atan2(sqrt((t_1 + (t_0 * (t_2 * t_2)))), sqrt((t_3 + (t_0 * ((cos(lambda1) / 2.0d0) - 0.5d0))))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.cos(phi1) * Math.cos(phi2);
double t_1 = Math.pow(((Math.cos((0.5 * phi2)) * Math.sin((phi1 * 0.5))) - (Math.sin((0.5 * phi2)) * Math.cos((phi1 * 0.5)))), 2.0);
double t_2 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_3 = 1.0 - t_1;
double tmp;
if ((lambda2 <= -0.0015) || !(lambda2 <= 0.0045)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_1 + (t_0 * (t_2 * Math.sin((lambda2 * -0.5)))))), Math.sqrt((t_3 + (t_0 * ((Math.cos((lambda1 - lambda2)) / 2.0) - 0.5))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_1 + (t_0 * (t_2 * t_2)))), Math.sqrt((t_3 + (t_0 * ((Math.cos(lambda1) / 2.0) - 0.5))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi1) * math.cos(phi2) t_1 = math.pow(((math.cos((0.5 * phi2)) * math.sin((phi1 * 0.5))) - (math.sin((0.5 * phi2)) * math.cos((phi1 * 0.5)))), 2.0) t_2 = math.sin(((lambda1 - lambda2) / 2.0)) t_3 = 1.0 - t_1 tmp = 0 if (lambda2 <= -0.0015) or not (lambda2 <= 0.0045): tmp = R * (2.0 * math.atan2(math.sqrt((t_1 + (t_0 * (t_2 * math.sin((lambda2 * -0.5)))))), math.sqrt((t_3 + (t_0 * ((math.cos((lambda1 - lambda2)) / 2.0) - 0.5)))))) else: tmp = R * (2.0 * math.atan2(math.sqrt((t_1 + (t_0 * (t_2 * t_2)))), math.sqrt((t_3 + (t_0 * ((math.cos(lambda1) / 2.0) - 0.5)))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = Float64(Float64(cos(Float64(0.5 * phi2)) * sin(Float64(phi1 * 0.5))) - Float64(sin(Float64(0.5 * phi2)) * cos(Float64(phi1 * 0.5)))) ^ 2.0 t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_3 = Float64(1.0 - t_1) tmp = 0.0 if ((lambda2 <= -0.0015) || !(lambda2 <= 0.0045)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + Float64(t_0 * Float64(t_2 * sin(Float64(lambda2 * -0.5)))))), sqrt(Float64(t_3 + Float64(t_0 * Float64(Float64(cos(Float64(lambda1 - lambda2)) / 2.0) - 0.5))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + Float64(t_0 * Float64(t_2 * t_2)))), sqrt(Float64(t_3 + Float64(t_0 * Float64(Float64(cos(lambda1) / 2.0) - 0.5))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi1) * cos(phi2); t_1 = ((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (sin((0.5 * phi2)) * cos((phi1 * 0.5)))) ^ 2.0; t_2 = sin(((lambda1 - lambda2) / 2.0)); t_3 = 1.0 - t_1; tmp = 0.0; if ((lambda2 <= -0.0015) || ~((lambda2 <= 0.0045))) tmp = R * (2.0 * atan2(sqrt((t_1 + (t_0 * (t_2 * sin((lambda2 * -0.5)))))), sqrt((t_3 + (t_0 * ((cos((lambda1 - lambda2)) / 2.0) - 0.5)))))); else tmp = R * (2.0 * atan2(sqrt((t_1 + (t_0 * (t_2 * t_2)))), sqrt((t_3 + (t_0 * ((cos(lambda1) / 2.0) - 0.5)))))); 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[Power[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[(1.0 - t$95$1), $MachinePrecision]}, If[Or[LessEqual[lambda2, -0.0015], N[Not[LessEqual[lambda2, 0.0045]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[(t$95$0 * N[(t$95$2 * N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(t$95$3 + N[(t$95$0 * N[(N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[(t$95$0 * N[(t$95$2 * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(t$95$3 + N[(t$95$0 * N[(N[(N[Cos[lambda1], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := {\left(\cos \left(0.5 \cdot \phi_2\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \sin \left(0.5 \cdot \phi_2\right) \cdot \cos \left(\phi_1 \cdot 0.5\right)\right)}^{2}\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_3 := 1 - t\_1\\
\mathbf{if}\;\lambda_2 \leq -0.0015 \lor \neg \left(\lambda_2 \leq 0.0045\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + t\_0 \cdot \left(t\_2 \cdot \sin \left(\lambda_2 \cdot -0.5\right)\right)}}{\sqrt{t\_3 + t\_0 \cdot \left(\frac{\cos \left(\lambda_1 - \lambda_2\right)}{2} - 0.5\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + t\_0 \cdot \left(t\_2 \cdot t\_2\right)}}{\sqrt{t\_3 + t\_0 \cdot \left(\frac{\cos \lambda_1}{2} - 0.5\right)}}\right)\\
\end{array}
\end{array}
if lambda2 < -0.0015 or 0.00449999999999999966 < lambda2 Initial program 53.4%
associate-*l*53.4%
Simplified53.4%
div-sub53.4%
sin-diff54.3%
div-inv54.3%
metadata-eval54.3%
div-inv54.3%
metadata-eval54.3%
div-inv54.3%
metadata-eval54.3%
div-inv54.3%
metadata-eval54.3%
Applied egg-rr54.3%
div-sub53.4%
sin-diff54.3%
div-inv54.3%
metadata-eval54.3%
div-inv54.3%
metadata-eval54.3%
div-inv54.3%
metadata-eval54.3%
div-inv54.3%
metadata-eval54.3%
Applied egg-rr62.4%
sin-mult62.4%
cos-sum62.4%
cos-262.4%
div-sub62.4%
+-inverses62.4%
Applied egg-rr62.4%
cos-062.4%
metadata-eval62.4%
Simplified62.4%
Taylor expanded in lambda1 around 0 60.4%
if -0.0015 < lambda2 < 0.00449999999999999966Initial program 79.5%
associate-*l*79.6%
Simplified79.6%
div-sub79.6%
sin-diff80.8%
div-inv80.8%
metadata-eval80.8%
div-inv80.8%
metadata-eval80.8%
div-inv80.8%
metadata-eval80.8%
div-inv80.8%
metadata-eval80.8%
Applied egg-rr80.8%
div-sub79.6%
sin-diff80.8%
div-inv80.8%
metadata-eval80.8%
div-inv80.8%
metadata-eval80.8%
div-inv80.8%
metadata-eval80.8%
div-inv80.8%
metadata-eval80.8%
Applied egg-rr97.9%
sin-mult98.0%
cos-sum98.0%
cos-298.0%
div-sub98.0%
+-inverses98.0%
Applied egg-rr98.0%
cos-098.0%
metadata-eval98.0%
Simplified98.0%
Taylor expanded in lambda2 around 0 98.0%
Final simplification79.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))
(t_1
(pow
(-
(* (cos (* 0.5 phi2)) (sin (* phi1 0.5)))
(* (sin (* 0.5 phi2)) (cos (* phi1 0.5))))
2.0))
(t_2 (- 1.0 t_1))
(t_3 (sin (/ (- lambda1 lambda2) 2.0)))
(t_4 (* (cos phi1) (cos phi2)))
(t_5 (* t_4 (* t_3 t_3))))
(if (<= lambda1 -4e-6)
(*
R
(*
2.0
(atan2
(sqrt (+ t_0 (* t_3 (* t_4 t_3))))
(sqrt
(fabs
(-
1.0
(fma
(pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)
t_4
(pow (sin (* 0.5 (- phi1 phi2))) 2.0))))))))
(if (<= lambda1 95000.0)
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (* t_4 (* t_3 (sin (* lambda2 -0.5))))))
(sqrt (+ t_2 (* t_4 (- (/ (cos (- lambda1 lambda2)) 2.0) 0.5)))))))
(* R (* 2.0 (atan2 (sqrt (+ t_5 t_0)) (sqrt (- t_2 t_5)))))))))
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 = pow(((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (sin((0.5 * phi2)) * cos((phi1 * 0.5)))), 2.0);
double t_2 = 1.0 - t_1;
double t_3 = sin(((lambda1 - lambda2) / 2.0));
double t_4 = cos(phi1) * cos(phi2);
double t_5 = t_4 * (t_3 * t_3);
double tmp;
if (lambda1 <= -4e-6) {
tmp = R * (2.0 * atan2(sqrt((t_0 + (t_3 * (t_4 * t_3)))), sqrt(fabs((1.0 - fma(pow(sin((0.5 * (lambda1 - lambda2))), 2.0), t_4, pow(sin((0.5 * (phi1 - phi2))), 2.0)))))));
} else if (lambda1 <= 95000.0) {
tmp = R * (2.0 * atan2(sqrt((t_1 + (t_4 * (t_3 * sin((lambda2 * -0.5)))))), sqrt((t_2 + (t_4 * ((cos((lambda1 - lambda2)) / 2.0) - 0.5))))));
} else {
tmp = R * (2.0 * atan2(sqrt((t_5 + t_0)), sqrt((t_2 - t_5))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 t_1 = Float64(Float64(cos(Float64(0.5 * phi2)) * sin(Float64(phi1 * 0.5))) - Float64(sin(Float64(0.5 * phi2)) * cos(Float64(phi1 * 0.5)))) ^ 2.0 t_2 = Float64(1.0 - t_1) t_3 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_4 = Float64(cos(phi1) * cos(phi2)) t_5 = Float64(t_4 * Float64(t_3 * t_3)) tmp = 0.0 if (lambda1 <= -4e-6) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_0 + Float64(t_3 * Float64(t_4 * t_3)))), sqrt(abs(Float64(1.0 - fma((sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0), t_4, (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))))); elseif (lambda1 <= 95000.0) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + Float64(t_4 * Float64(t_3 * sin(Float64(lambda2 * -0.5)))))), sqrt(Float64(t_2 + Float64(t_4 * Float64(Float64(cos(Float64(lambda1 - lambda2)) / 2.0) - 0.5))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_5 + t_0)), sqrt(Float64(t_2 - t_5))))); 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[Power[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[(1.0 - t$95$1), $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(t$95$4 * N[(t$95$3 * t$95$3), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[lambda1, -4e-6], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 + N[(t$95$3 * N[(t$95$4 * t$95$3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[Abs[N[(1.0 - N[(N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * t$95$4 + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[lambda1, 95000.0], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[(t$95$4 * N[(t$95$3 * N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(t$95$2 + N[(t$95$4 * N[(N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$5 + t$95$0), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(t$95$2 - t$95$5), $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 := {\left(\cos \left(0.5 \cdot \phi_2\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \sin \left(0.5 \cdot \phi_2\right) \cdot \cos \left(\phi_1 \cdot 0.5\right)\right)}^{2}\\
t_2 := 1 - t\_1\\
t_3 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_4 := \cos \phi_1 \cdot \cos \phi_2\\
t_5 := t\_4 \cdot \left(t\_3 \cdot t\_3\right)\\
\mathbf{if}\;\lambda_1 \leq -4 \cdot 10^{-6}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 + t\_3 \cdot \left(t\_4 \cdot t\_3\right)}}{\sqrt{\left|1 - \mathsf{fma}\left({\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}, t\_4, {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)\right|}}\right)\\
\mathbf{elif}\;\lambda_1 \leq 95000:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + t\_4 \cdot \left(t\_3 \cdot \sin \left(\lambda_2 \cdot -0.5\right)\right)}}{\sqrt{t\_2 + t\_4 \cdot \left(\frac{\cos \left(\lambda_1 - \lambda_2\right)}{2} - 0.5\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_5 + t\_0}}{\sqrt{t\_2 - t\_5}}\right)\\
\end{array}
\end{array}
if lambda1 < -3.99999999999999982e-6Initial program 55.1%
add-sqr-sqrt55.1%
sqrt-unprod56.5%
pow256.5%
Applied egg-rr56.5%
unpow256.5%
rem-sqrt-square56.5%
fma-undefine56.5%
*-commutative56.5%
fma-define56.5%
*-commutative56.5%
*-commutative56.5%
Simplified56.5%
if -3.99999999999999982e-6 < lambda1 < 95000Initial program 79.3%
associate-*l*79.3%
Simplified79.3%
div-sub79.3%
sin-diff80.1%
div-inv80.1%
metadata-eval80.1%
div-inv80.1%
metadata-eval80.1%
div-inv80.1%
metadata-eval80.1%
div-inv80.1%
metadata-eval80.1%
Applied egg-rr80.1%
div-sub79.3%
sin-diff80.1%
div-inv80.1%
metadata-eval80.1%
div-inv80.1%
metadata-eval80.1%
div-inv80.1%
metadata-eval80.1%
div-inv80.1%
metadata-eval80.1%
Applied egg-rr97.2%
sin-mult97.3%
cos-sum97.2%
cos-297.3%
div-sub97.3%
+-inverses97.3%
Applied egg-rr97.3%
cos-097.3%
metadata-eval97.3%
Simplified97.3%
Taylor expanded in lambda1 around 0 93.8%
if 95000 < lambda1 Initial program 54.0%
associate-*l*54.0%
Simplified54.0%
div-sub54.0%
sin-diff55.5%
div-inv55.5%
metadata-eval55.5%
div-inv55.5%
metadata-eval55.5%
div-inv55.5%
metadata-eval55.5%
div-inv55.5%
metadata-eval55.5%
Applied egg-rr55.5%
Final simplification74.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1
(pow
(-
(* (cos (* 0.5 phi2)) (sin (* phi1 0.5)))
(* (sin (* 0.5 phi2)) (cos (* phi1 0.5))))
2.0))
(t_2 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (* t_0 (* t_2 t_2))))
(sqrt
(+ (- 1.0 t_1) (* t_0 (- (/ (cos (- lambda1 lambda2)) 2.0) 0.5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = pow(((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (sin((0.5 * phi2)) * cos((phi1 * 0.5)))), 2.0);
double t_2 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((t_1 + (t_0 * (t_2 * t_2)))), sqrt(((1.0 - t_1) + (t_0 * ((cos((lambda1 - lambda2)) / 2.0) - 0.5))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
t_0 = cos(phi1) * cos(phi2)
t_1 = ((cos((0.5d0 * phi2)) * sin((phi1 * 0.5d0))) - (sin((0.5d0 * phi2)) * cos((phi1 * 0.5d0)))) ** 2.0d0
t_2 = sin(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2(sqrt((t_1 + (t_0 * (t_2 * t_2)))), sqrt(((1.0d0 - t_1) + (t_0 * ((cos((lambda1 - lambda2)) / 2.0d0) - 0.5d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.cos(phi1) * Math.cos(phi2);
double t_1 = Math.pow(((Math.cos((0.5 * phi2)) * Math.sin((phi1 * 0.5))) - (Math.sin((0.5 * phi2)) * Math.cos((phi1 * 0.5)))), 2.0);
double t_2 = Math.sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((t_1 + (t_0 * (t_2 * t_2)))), Math.sqrt(((1.0 - t_1) + (t_0 * ((Math.cos((lambda1 - lambda2)) / 2.0) - 0.5))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi1) * math.cos(phi2) t_1 = math.pow(((math.cos((0.5 * phi2)) * math.sin((phi1 * 0.5))) - (math.sin((0.5 * phi2)) * math.cos((phi1 * 0.5)))), 2.0) t_2 = math.sin(((lambda1 - lambda2) / 2.0)) return R * (2.0 * math.atan2(math.sqrt((t_1 + (t_0 * (t_2 * t_2)))), math.sqrt(((1.0 - t_1) + (t_0 * ((math.cos((lambda1 - lambda2)) / 2.0) - 0.5))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = Float64(Float64(cos(Float64(0.5 * phi2)) * sin(Float64(phi1 * 0.5))) - Float64(sin(Float64(0.5 * phi2)) * cos(Float64(phi1 * 0.5)))) ^ 2.0 t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + Float64(t_0 * Float64(t_2 * t_2)))), sqrt(Float64(Float64(1.0 - t_1) + Float64(t_0 * Float64(Float64(cos(Float64(lambda1 - lambda2)) / 2.0) - 0.5))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi1) * cos(phi2); t_1 = ((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (sin((0.5 * phi2)) * cos((phi1 * 0.5)))) ^ 2.0; t_2 = sin(((lambda1 - lambda2) / 2.0)); tmp = R * (2.0 * atan2(sqrt((t_1 + (t_0 * (t_2 * t_2)))), sqrt(((1.0 - t_1) + (t_0 * ((cos((lambda1 - lambda2)) / 2.0) - 0.5)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Power[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[(t$95$0 * N[(t$95$2 * t$95$2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - t$95$1), $MachinePrecision] + N[(t$95$0 * N[(N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := {\left(\cos \left(0.5 \cdot \phi_2\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \sin \left(0.5 \cdot \phi_2\right) \cdot \cos \left(\phi_1 \cdot 0.5\right)\right)}^{2}\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + t\_0 \cdot \left(t\_2 \cdot t\_2\right)}}{\sqrt{\left(1 - t\_1\right) + t\_0 \cdot \left(\frac{\cos \left(\lambda_1 - \lambda_2\right)}{2} - 0.5\right)}}\right)
\end{array}
\end{array}
Initial program 66.8%
associate-*l*66.8%
Simplified66.8%
div-sub66.8%
sin-diff67.8%
div-inv67.8%
metadata-eval67.8%
div-inv67.8%
metadata-eval67.8%
div-inv67.8%
metadata-eval67.8%
div-inv67.8%
metadata-eval67.8%
Applied egg-rr67.8%
div-sub66.8%
sin-diff67.8%
div-inv67.8%
metadata-eval67.8%
div-inv67.8%
metadata-eval67.8%
div-inv67.8%
metadata-eval67.8%
div-inv67.8%
metadata-eval67.8%
Applied egg-rr80.6%
sin-mult80.6%
cos-sum80.6%
cos-280.6%
div-sub80.6%
+-inverses80.6%
Applied egg-rr80.6%
cos-080.6%
metadata-eval80.6%
Simplified80.6%
Final simplification80.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt
(-
(-
1.0
(pow
(-
(* (cos (* 0.5 phi2)) (sin (* phi1 0.5)))
(* (sin (* 0.5 phi2)) (cos (* phi1 0.5))))
2.0))
t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0);
return R * (2.0 * atan2(sqrt((t_1 + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt(((1.0 - pow(((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (sin((0.5 * phi2)) * cos((phi1 * 0.5)))), 2.0)) - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0)
code = r * (2.0d0 * atan2(sqrt((t_1 + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt(((1.0d0 - (((cos((0.5d0 * phi2)) * sin((phi1 * 0.5d0))) - (sin((0.5d0 * phi2)) * cos((phi1 * 0.5d0)))) ** 2.0d0)) - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = (Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0);
return R * (2.0 * Math.atan2(Math.sqrt((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((phi1 * 0.5))) - (Math.sin((0.5 * phi2)) * Math.cos((phi1 * 0.5)))), 2.0)) - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = (math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0) return R * (2.0 * math.atan2(math.sqrt((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((phi1 * 0.5))) - (math.sin((0.5 * phi2)) * math.cos((phi1 * 0.5)))), 2.0)) - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(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(phi1 * 0.5))) - Float64(sin(Float64(0.5 * phi2)) * cos(Float64(phi1 * 0.5)))) ^ 2.0)) - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0); tmp = R * (2.0 * atan2(sqrt((t_1 + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(((1.0 - (((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (sin((0.5 * phi2)) * cos((phi1 * 0.5)))) ^ 2.0)) - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(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[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] - 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(\phi_1 \cdot 0.5\right) - \sin \left(0.5 \cdot \phi_2\right) \cdot \cos \left(\phi_1 \cdot 0.5\right)\right)}^{2}\right) - t\_1}}\right)
\end{array}
\end{array}
Initial program 66.8%
associate-*l*66.8%
Simplified66.8%
div-sub66.8%
sin-diff67.8%
div-inv67.8%
metadata-eval67.8%
div-inv67.8%
metadata-eval67.8%
div-inv67.8%
metadata-eval67.8%
div-inv67.8%
metadata-eval67.8%
Applied egg-rr67.8%
Final simplification67.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (cos phi1) (cos phi2))))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* t_0 (* t_1 t_0))))
(sqrt
(fabs
(-
1.0
(fma
(pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)
t_1
(pow (sin (* 0.5 (- phi1 phi2))) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = cos(phi1) * cos(phi2);
return R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * (t_1 * t_0)))), sqrt(fabs((1.0 - fma(pow(sin((0.5 * (lambda1 - lambda2))), 2.0), t_1, pow(sin((0.5 * (phi1 - phi2))), 2.0)))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(cos(phi1) * cos(phi2)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_0 * Float64(t_1 * t_0)))), sqrt(abs(Float64(1.0 - fma((sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0), t_1, (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$0 * N[(t$95$1 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[Abs[N[(1.0 - N[(N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * t$95$1 + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_0 \cdot \left(t\_1 \cdot t\_0\right)}}{\sqrt{\left|1 - \mathsf{fma}\left({\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}, t\_1, {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)\right|}}\right)
\end{array}
\end{array}
Initial program 66.8%
add-sqr-sqrt66.8%
sqrt-unprod67.6%
pow267.6%
Applied egg-rr67.6%
unpow267.6%
rem-sqrt-square67.6%
fma-undefine67.6%
*-commutative67.6%
fma-define67.6%
*-commutative67.6%
*-commutative67.6%
Simplified67.6%
Final simplification67.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))
(t_1 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_2 (* (cos phi1) t_1))
(t_3 (sin (/ (- lambda1 lambda2) 2.0)))
(t_4 (* (* (cos phi1) (cos phi2)) t_3))
(t_5 (sqrt (+ t_0 (* (sin (* lambda2 -0.5)) t_4)))))
(if (<= phi1 -7800000000.0)
(*
R
(* 2.0 (atan2 t_5 (sqrt (- 1.0 (+ t_2 (pow (sin (* phi1 0.5)) 2.0)))))))
(if (<= phi1 260000.0)
(*
R
(*
2.0
(atan2
(sqrt (+ t_0 (* t_3 t_4)))
(sqrt (- (pow (cos (* phi2 -0.5)) 2.0) (* (cos phi2) t_1))))))
(*
R
(* 2.0 (atan2 t_5 (sqrt (- (pow (cos (* phi1 0.5)) 2.0) t_2)))))))))
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 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_2 = cos(phi1) * t_1;
double t_3 = sin(((lambda1 - lambda2) / 2.0));
double t_4 = (cos(phi1) * cos(phi2)) * t_3;
double t_5 = sqrt((t_0 + (sin((lambda2 * -0.5)) * t_4)));
double tmp;
if (phi1 <= -7800000000.0) {
tmp = R * (2.0 * atan2(t_5, sqrt((1.0 - (t_2 + pow(sin((phi1 * 0.5)), 2.0))))));
} else if (phi1 <= 260000.0) {
tmp = R * (2.0 * atan2(sqrt((t_0 + (t_3 * t_4))), sqrt((pow(cos((phi2 * -0.5)), 2.0) - (cos(phi2) * t_1)))));
} else {
tmp = R * (2.0 * atan2(t_5, sqrt((pow(cos((phi1 * 0.5)), 2.0) - t_2))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: t_3
real(8) :: t_4
real(8) :: t_5
real(8) :: tmp
t_0 = sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0
t_1 = sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0
t_2 = cos(phi1) * t_1
t_3 = sin(((lambda1 - lambda2) / 2.0d0))
t_4 = (cos(phi1) * cos(phi2)) * t_3
t_5 = sqrt((t_0 + (sin((lambda2 * (-0.5d0))) * t_4)))
if (phi1 <= (-7800000000.0d0)) then
tmp = r * (2.0d0 * atan2(t_5, sqrt((1.0d0 - (t_2 + (sin((phi1 * 0.5d0)) ** 2.0d0))))))
else if (phi1 <= 260000.0d0) then
tmp = r * (2.0d0 * atan2(sqrt((t_0 + (t_3 * t_4))), sqrt(((cos((phi2 * (-0.5d0))) ** 2.0d0) - (cos(phi2) * t_1)))))
else
tmp = r * (2.0d0 * atan2(t_5, sqrt(((cos((phi1 * 0.5d0)) ** 2.0d0) - t_2))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0);
double t_1 = Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_2 = Math.cos(phi1) * t_1;
double t_3 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_4 = (Math.cos(phi1) * Math.cos(phi2)) * t_3;
double t_5 = Math.sqrt((t_0 + (Math.sin((lambda2 * -0.5)) * t_4)));
double tmp;
if (phi1 <= -7800000000.0) {
tmp = R * (2.0 * Math.atan2(t_5, Math.sqrt((1.0 - (t_2 + Math.pow(Math.sin((phi1 * 0.5)), 2.0))))));
} else if (phi1 <= 260000.0) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_0 + (t_3 * t_4))), Math.sqrt((Math.pow(Math.cos((phi2 * -0.5)), 2.0) - (Math.cos(phi2) * t_1)))));
} else {
tmp = R * (2.0 * Math.atan2(t_5, Math.sqrt((Math.pow(Math.cos((phi1 * 0.5)), 2.0) - t_2))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) t_1 = math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0) t_2 = math.cos(phi1) * t_1 t_3 = math.sin(((lambda1 - lambda2) / 2.0)) t_4 = (math.cos(phi1) * math.cos(phi2)) * t_3 t_5 = math.sqrt((t_0 + (math.sin((lambda2 * -0.5)) * t_4))) tmp = 0 if phi1 <= -7800000000.0: tmp = R * (2.0 * math.atan2(t_5, math.sqrt((1.0 - (t_2 + math.pow(math.sin((phi1 * 0.5)), 2.0)))))) elif phi1 <= 260000.0: tmp = R * (2.0 * math.atan2(math.sqrt((t_0 + (t_3 * t_4))), math.sqrt((math.pow(math.cos((phi2 * -0.5)), 2.0) - (math.cos(phi2) * t_1))))) else: tmp = R * (2.0 * math.atan2(t_5, math.sqrt((math.pow(math.cos((phi1 * 0.5)), 2.0) - t_2)))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 t_1 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_2 = Float64(cos(phi1) * t_1) t_3 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_4 = Float64(Float64(cos(phi1) * cos(phi2)) * t_3) t_5 = sqrt(Float64(t_0 + Float64(sin(Float64(lambda2 * -0.5)) * t_4))) tmp = 0.0 if (phi1 <= -7800000000.0) tmp = Float64(R * Float64(2.0 * atan(t_5, sqrt(Float64(1.0 - Float64(t_2 + (sin(Float64(phi1 * 0.5)) ^ 2.0))))))); elseif (phi1 <= 260000.0) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_0 + Float64(t_3 * t_4))), sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) - Float64(cos(phi2) * t_1)))))); else tmp = Float64(R * Float64(2.0 * atan(t_5, sqrt(Float64((cos(Float64(phi1 * 0.5)) ^ 2.0) - t_2))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((phi1 - phi2) / 2.0)) ^ 2.0; t_1 = sin((0.5 * (lambda1 - lambda2))) ^ 2.0; t_2 = cos(phi1) * t_1; t_3 = sin(((lambda1 - lambda2) / 2.0)); t_4 = (cos(phi1) * cos(phi2)) * t_3; t_5 = sqrt((t_0 + (sin((lambda2 * -0.5)) * t_4))); tmp = 0.0; if (phi1 <= -7800000000.0) tmp = R * (2.0 * atan2(t_5, sqrt((1.0 - (t_2 + (sin((phi1 * 0.5)) ^ 2.0)))))); elseif (phi1 <= 260000.0) tmp = R * (2.0 * atan2(sqrt((t_0 + (t_3 * t_4))), sqrt(((cos((phi2 * -0.5)) ^ 2.0) - (cos(phi2) * t_1))))); else tmp = R * (2.0 * atan2(t_5, sqrt(((cos((phi1 * 0.5)) ^ 2.0) - t_2)))); end tmp_2 = 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[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * t$95$1), $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$3), $MachinePrecision]}, Block[{t$95$5 = N[Sqrt[N[(t$95$0 + N[(N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision] * t$95$4), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi1, -7800000000.0], N[(R * N[(2.0 * N[ArcTan[t$95$5 / N[Sqrt[N[(1.0 - N[(t$95$2 + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[phi1, 260000.0], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 + N[(t$95$3 * t$95$4), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi2], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$5 / N[Sqrt[N[(N[Power[N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - t$95$2), $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(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_2 := \cos \phi_1 \cdot t\_1\\
t_3 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_4 := \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_3\\
t_5 := \sqrt{t\_0 + \sin \left(\lambda_2 \cdot -0.5\right) \cdot t\_4}\\
\mathbf{if}\;\phi_1 \leq -7800000000:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_5}{\sqrt{1 - \left(t\_2 + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}\right)\\
\mathbf{elif}\;\phi_1 \leq 260000:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 + t\_3 \cdot t\_4}}{\sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} - \cos \phi_2 \cdot t\_1}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_5}{\sqrt{{\cos \left(\phi_1 \cdot 0.5\right)}^{2} - t\_2}}\right)\\
\end{array}
\end{array}
if phi1 < -7.8e9Initial program 45.2%
Taylor expanded in lambda1 around 0 38.6%
Taylor expanded in phi2 around 0 39.5%
if -7.8e9 < phi1 < 2.6e5Initial program 77.9%
Taylor expanded in phi1 around 0 77.2%
+-commutative16.5%
associate--r+16.5%
unpow216.5%
1-sub-sin16.5%
unpow216.5%
Simplified77.3%
if 2.6e5 < phi1 Initial program 61.0%
Taylor expanded in lambda1 around 0 45.1%
Taylor expanded in phi2 around 0 47.5%
+-commutative47.5%
associate--r+47.5%
unpow247.5%
1-sub-sin47.5%
unpow247.5%
Simplified47.5%
Final simplification61.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_1 (* (cos phi2) t_0))
(t_2 (pow (sin (* phi2 -0.5)) 2.0))
(t_3 (pow (cos (* phi2 -0.5)) 2.0))
(t_4 (sin (/ (- lambda1 lambda2) 2.0))))
(if (<= phi2 -900000.0)
(* R (* 2.0 (atan2 (sqrt (+ t_1 t_2)) (sqrt (- t_3 t_1)))))
(if (<= phi2 3.2e-25)
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* t_4 (* (* (cos phi1) (cos phi2)) t_4))))
(sqrt (- (pow (cos (* phi1 0.5)) 2.0) (* (cos phi1) t_0))))))
(*
R
(*
2.0
(atan2
(sqrt (fma (cos phi2) t_0 t_2))
(sqrt
(+
t_3
(* (cos phi2) (- (/ (cos (- lambda2 lambda1)) 2.0) 0.5)))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = cos(phi2) * t_0;
double t_2 = pow(sin((phi2 * -0.5)), 2.0);
double t_3 = pow(cos((phi2 * -0.5)), 2.0);
double t_4 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if (phi2 <= -900000.0) {
tmp = R * (2.0 * atan2(sqrt((t_1 + t_2)), sqrt((t_3 - t_1))));
} else if (phi2 <= 3.2e-25) {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_4 * ((cos(phi1) * cos(phi2)) * t_4)))), sqrt((pow(cos((phi1 * 0.5)), 2.0) - (cos(phi1) * t_0)))));
} else {
tmp = R * (2.0 * atan2(sqrt(fma(cos(phi2), t_0, t_2)), sqrt((t_3 + (cos(phi2) * ((cos((lambda2 - lambda1)) / 2.0) - 0.5))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_1 = Float64(cos(phi2) * t_0) t_2 = sin(Float64(phi2 * -0.5)) ^ 2.0 t_3 = cos(Float64(phi2 * -0.5)) ^ 2.0 t_4 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if (phi2 <= -900000.0) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + t_2)), sqrt(Float64(t_3 - t_1))))); elseif (phi2 <= 3.2e-25) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_4 * Float64(Float64(cos(phi1) * cos(phi2)) * t_4)))), sqrt(Float64((cos(Float64(phi1 * 0.5)) ^ 2.0) - Float64(cos(phi1) * t_0)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(cos(phi2), t_0, t_2)), sqrt(Float64(t_3 + Float64(cos(phi2) * Float64(Float64(cos(Float64(lambda2 - lambda1)) / 2.0) - 0.5))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$3 = N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$4 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi2, -900000.0], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + t$95$2), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(t$95$3 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[phi2, 3.2e-25], 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$4 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Cos[phi2], $MachinePrecision] * t$95$0 + t$95$2), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(t$95$3 + N[(N[Cos[phi2], $MachinePrecision] * N[(N[(N[Cos[N[(lambda2 - lambda1), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_1 := \cos \phi_2 \cdot t\_0\\
t_2 := {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\\
t_3 := {\cos \left(\phi_2 \cdot -0.5\right)}^{2}\\
t_4 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\phi_2 \leq -900000:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + t\_2}}{\sqrt{t\_3 - t\_1}}\right)\\
\mathbf{elif}\;\phi_2 \leq 3.2 \cdot 10^{-25}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_4 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_4\right)}}{\sqrt{{\cos \left(\phi_1 \cdot 0.5\right)}^{2} - \cos \phi_1 \cdot t\_0}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_2, t\_0, t\_2\right)}}{\sqrt{t\_3 + \cos \phi_2 \cdot \left(\frac{\cos \left(\lambda_2 - \lambda_1\right)}{2} - 0.5\right)}}\right)\\
\end{array}
\end{array}
if phi2 < -9e5Initial program 53.3%
Taylor expanded in phi1 around 0 54.2%
+-commutative20.4%
associate--r+20.4%
unpow220.4%
1-sub-sin20.4%
unpow220.4%
Simplified54.3%
Taylor expanded in phi1 around 0 54.7%
if -9e5 < phi2 < 3.2000000000000001e-25Initial program 77.9%
Taylor expanded in phi2 around 0 78.0%
+-commutative50.5%
associate--r+50.6%
unpow250.6%
1-sub-sin50.6%
unpow250.6%
Simplified78.0%
if 3.2000000000000001e-25 < phi2 Initial program 59.2%
Taylor expanded in phi1 around 0 61.6%
+-commutative13.6%
associate--r+13.6%
unpow213.6%
1-sub-sin13.6%
unpow213.6%
Simplified61.6%
add-cbrt-cube61.4%
pow361.4%
Applied egg-rr45.6%
Taylor expanded in phi1 around 0 61.9%
fma-define61.9%
*-commutative61.9%
Simplified61.9%
unpow213.6%
sin-mult13.6%
*-commutative13.6%
*-commutative13.6%
*-commutative13.6%
*-commutative13.6%
Applied egg-rr62.0%
div-sub13.6%
+-inverses13.6%
cos-013.6%
metadata-eval13.6%
distribute-lft-out13.6%
metadata-eval13.6%
*-rgt-identity13.6%
sub-neg13.6%
remove-double-neg13.6%
mul-1-neg13.6%
distribute-neg-in13.6%
+-commutative13.6%
cos-neg13.6%
mul-1-neg13.6%
unsub-neg13.6%
Simplified62.0%
Final simplification67.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
(if (or (<= phi1 -1.15e-29) (not (<= phi1 260000.0)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(*
(sin (* lambda2 -0.5))
(* (* (cos phi1) (cos phi2)) (sin (/ (- lambda1 lambda2) 2.0))))))
(sqrt (- (pow (cos (* phi1 0.5)) 2.0) (* (cos phi1) t_0))))))
(*
R
(*
2.0
(atan2
(sqrt (fma (cos phi2) t_0 (pow (sin (* phi2 -0.5)) 2.0)))
(sqrt
(+
(pow (cos (* phi2 -0.5)) 2.0)
(* (cos phi2) (- (/ (cos (- lambda2 lambda1)) 2.0) 0.5))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double tmp;
if ((phi1 <= -1.15e-29) || !(phi1 <= 260000.0)) {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (sin((lambda2 * -0.5)) * ((cos(phi1) * cos(phi2)) * sin(((lambda1 - lambda2) / 2.0)))))), sqrt((pow(cos((phi1 * 0.5)), 2.0) - (cos(phi1) * t_0)))));
} else {
tmp = R * (2.0 * atan2(sqrt(fma(cos(phi2), t_0, pow(sin((phi2 * -0.5)), 2.0))), sqrt((pow(cos((phi2 * -0.5)), 2.0) + (cos(phi2) * ((cos((lambda2 - lambda1)) / 2.0) - 0.5))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 tmp = 0.0 if ((phi1 <= -1.15e-29) || !(phi1 <= 260000.0)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(sin(Float64(lambda2 * -0.5)) * Float64(Float64(cos(phi1) * cos(phi2)) * sin(Float64(Float64(lambda1 - lambda2) / 2.0)))))), sqrt(Float64((cos(Float64(phi1 * 0.5)) ^ 2.0) - Float64(cos(phi1) * t_0)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(cos(phi2), t_0, (sin(Float64(phi2 * -0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) + Float64(cos(phi2) * Float64(Float64(cos(Float64(lambda2 - lambda1)) / 2.0) - 0.5))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[phi1, -1.15e-29], N[Not[LessEqual[phi1, 260000.0]], $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[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision] * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Cos[phi2], $MachinePrecision] * t$95$0 + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi2], $MachinePrecision] * N[(N[(N[Cos[N[(lambda2 - lambda1), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
\mathbf{if}\;\phi_1 \leq -1.15 \cdot 10^{-29} \lor \neg \left(\phi_1 \leq 260000\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \sin \left(\lambda_2 \cdot -0.5\right) \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\right)}}{\sqrt{{\cos \left(\phi_1 \cdot 0.5\right)}^{2} - \cos \phi_1 \cdot t\_0}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_2, t\_0, {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}}{\sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} + \cos \phi_2 \cdot \left(\frac{\cos \left(\lambda_2 - \lambda_1\right)}{2} - 0.5\right)}}\right)\\
\end{array}
\end{array}
if phi1 < -1.14999999999999996e-29 or 2.6e5 < phi1 Initial program 53.0%
Taylor expanded in lambda1 around 0 41.7%
Taylor expanded in phi2 around 0 43.4%
+-commutative43.4%
associate--r+43.5%
unpow243.5%
1-sub-sin43.5%
unpow243.5%
Simplified43.5%
if -1.14999999999999996e-29 < phi1 < 2.6e5Initial program 79.9%
Taylor expanded in phi1 around 0 79.2%
+-commutative16.9%
associate--r+16.9%
unpow216.9%
1-sub-sin16.9%
unpow216.9%
Simplified79.2%
add-cbrt-cube78.2%
pow378.2%
Applied egg-rr58.8%
Taylor expanded in phi1 around 0 78.8%
fma-define78.8%
*-commutative78.8%
Simplified78.8%
unpow216.9%
sin-mult16.9%
*-commutative16.9%
*-commutative16.9%
*-commutative16.9%
*-commutative16.9%
Applied egg-rr78.9%
div-sub16.9%
+-inverses16.9%
cos-016.9%
metadata-eval16.9%
distribute-lft-out16.9%
metadata-eval16.9%
*-rgt-identity16.9%
sub-neg16.9%
remove-double-neg16.9%
mul-1-neg16.9%
distribute-neg-in16.9%
+-commutative16.9%
cos-neg16.9%
mul-1-neg16.9%
unsub-neg16.9%
Simplified78.9%
Final simplification61.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_1 (* (cos phi1) t_0))
(t_2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(*
(sin (* lambda2 -0.5))
(*
(* (cos phi1) (cos phi2))
(sin (/ (- lambda1 lambda2) 2.0))))))))
(if (<= phi1 -3.2e-30)
(*
R
(* 2.0 (atan2 t_2 (sqrt (- 1.0 (+ t_1 (pow (sin (* phi1 0.5)) 2.0)))))))
(if (<= phi1 260000.0)
(*
R
(*
2.0
(atan2
(sqrt (fma (cos phi2) t_0 (pow (sin (* phi2 -0.5)) 2.0)))
(sqrt
(+
(pow (cos (* phi2 -0.5)) 2.0)
(* (cos phi2) (- (/ (cos (- lambda2 lambda1)) 2.0) 0.5)))))))
(*
R
(* 2.0 (atan2 t_2 (sqrt (- (pow (cos (* phi1 0.5)) 2.0) t_1)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = cos(phi1) * t_0;
double t_2 = sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (sin((lambda2 * -0.5)) * ((cos(phi1) * cos(phi2)) * sin(((lambda1 - lambda2) / 2.0))))));
double tmp;
if (phi1 <= -3.2e-30) {
tmp = R * (2.0 * atan2(t_2, sqrt((1.0 - (t_1 + pow(sin((phi1 * 0.5)), 2.0))))));
} else if (phi1 <= 260000.0) {
tmp = R * (2.0 * atan2(sqrt(fma(cos(phi2), t_0, pow(sin((phi2 * -0.5)), 2.0))), sqrt((pow(cos((phi2 * -0.5)), 2.0) + (cos(phi2) * ((cos((lambda2 - lambda1)) / 2.0) - 0.5))))));
} else {
tmp = R * (2.0 * atan2(t_2, sqrt((pow(cos((phi1 * 0.5)), 2.0) - t_1))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_1 = Float64(cos(phi1) * t_0) t_2 = sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(sin(Float64(lambda2 * -0.5)) * Float64(Float64(cos(phi1) * cos(phi2)) * sin(Float64(Float64(lambda1 - lambda2) / 2.0)))))) tmp = 0.0 if (phi1 <= -3.2e-30) tmp = Float64(R * Float64(2.0 * atan(t_2, sqrt(Float64(1.0 - Float64(t_1 + (sin(Float64(phi1 * 0.5)) ^ 2.0))))))); elseif (phi1 <= 260000.0) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(cos(phi2), t_0, (sin(Float64(phi2 * -0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) + Float64(cos(phi2) * Float64(Float64(cos(Float64(lambda2 - lambda1)) / 2.0) - 0.5))))))); else tmp = Float64(R * Float64(2.0 * atan(t_2, sqrt(Float64((cos(Float64(phi1 * 0.5)) ^ 2.0) - t_1))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision]}, Block[{t$95$2 = N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision] * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi1, -3.2e-30], N[(R * N[(2.0 * N[ArcTan[t$95$2 / N[Sqrt[N[(1.0 - N[(t$95$1 + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[phi1, 260000.0], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Cos[phi2], $MachinePrecision] * t$95$0 + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi2], $MachinePrecision] * N[(N[(N[Cos[N[(lambda2 - lambda1), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$2 / N[Sqrt[N[(N[Power[N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_1 := \cos \phi_1 \cdot t\_0\\
t_2 := \sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \sin \left(\lambda_2 \cdot -0.5\right) \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\right)}\\
\mathbf{if}\;\phi_1 \leq -3.2 \cdot 10^{-30}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_2}{\sqrt{1 - \left(t\_1 + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}\right)\\
\mathbf{elif}\;\phi_1 \leq 260000:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_2, t\_0, {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}}{\sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} + \cos \phi_2 \cdot \left(\frac{\cos \left(\lambda_2 - \lambda_1\right)}{2} - 0.5\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_2}{\sqrt{{\cos \left(\phi_1 \cdot 0.5\right)}^{2} - t\_1}}\right)\\
\end{array}
\end{array}
if phi1 < -3.2e-30Initial program 44.0%
Taylor expanded in lambda1 around 0 38.0%
Taylor expanded in phi2 around 0 38.9%
if -3.2e-30 < phi1 < 2.6e5Initial program 79.9%
Taylor expanded in phi1 around 0 79.2%
+-commutative16.9%
associate--r+16.9%
unpow216.9%
1-sub-sin16.9%
unpow216.9%
Simplified79.2%
add-cbrt-cube78.2%
pow378.2%
Applied egg-rr58.8%
Taylor expanded in phi1 around 0 78.8%
fma-define78.8%
*-commutative78.8%
Simplified78.8%
unpow216.9%
sin-mult16.9%
*-commutative16.9%
*-commutative16.9%
*-commutative16.9%
*-commutative16.9%
Applied egg-rr78.9%
div-sub16.9%
+-inverses16.9%
cos-016.9%
metadata-eval16.9%
distribute-lft-out16.9%
metadata-eval16.9%
*-rgt-identity16.9%
sub-neg16.9%
remove-double-neg16.9%
mul-1-neg16.9%
distribute-neg-in16.9%
+-commutative16.9%
cos-neg16.9%
mul-1-neg16.9%
unsub-neg16.9%
Simplified78.9%
if 2.6e5 < phi1 Initial program 61.0%
Taylor expanded in lambda1 around 0 45.1%
Taylor expanded in phi2 around 0 47.5%
+-commutative47.5%
associate--r+47.5%
unpow247.5%
1-sub-sin47.5%
unpow247.5%
Simplified47.5%
Final simplification61.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))
(t_2 (* (cos phi1) (cos phi2))))
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_2 (* t_0 t_0)) t_1))
(sqrt
(+ (- 1.0 t_1) (* t_2 (- (/ (cos (- lambda1 lambda2)) 2.0) 0.5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double t_2 = cos(phi1) * cos(phi2);
return R * (2.0 * atan2(sqrt(((t_2 * (t_0 * t_0)) + t_1)), sqrt(((1.0 - t_1) + (t_2 * ((cos((lambda1 - lambda2)) / 2.0) - 0.5))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0
t_2 = cos(phi1) * cos(phi2)
code = r * (2.0d0 * atan2(sqrt(((t_2 * (t_0 * t_0)) + t_1)), sqrt(((1.0d0 - t_1) + (t_2 * ((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.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0);
double t_2 = Math.cos(phi1) * Math.cos(phi2);
return R * (2.0 * Math.atan2(Math.sqrt(((t_2 * (t_0 * t_0)) + t_1)), Math.sqrt(((1.0 - t_1) + (t_2 * ((Math.cos((lambda1 - lambda2)) / 2.0) - 0.5))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) t_2 = math.cos(phi1) * math.cos(phi2) return R * (2.0 * math.atan2(math.sqrt(((t_2 * (t_0 * t_0)) + t_1)), math.sqrt(((1.0 - t_1) + (t_2 * ((math.cos((lambda1 - lambda2)) / 2.0) - 0.5))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 t_2 = Float64(cos(phi1) * cos(phi2)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_2 * Float64(t_0 * t_0)) + t_1)), sqrt(Float64(Float64(1.0 - t_1) + Float64(t_2 * Float64(Float64(cos(Float64(lambda1 - lambda2)) / 2.0) - 0.5))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = sin(((phi1 - phi2) / 2.0)) ^ 2.0; t_2 = cos(phi1) * cos(phi2); tmp = R * (2.0 * atan2(sqrt(((t_2 * (t_0 * t_0)) + t_1)), sqrt(((1.0 - t_1) + (t_2 * ((cos((lambda1 - lambda2)) / 2.0) - 0.5)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$2 * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - t$95$1), $MachinePrecision] + N[(t$95$2 * N[(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(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 \cdot \left(t\_0 \cdot t\_0\right) + t\_1}}{\sqrt{\left(1 - t\_1\right) + t\_2 \cdot \left(\frac{\cos \left(\lambda_1 - \lambda_2\right)}{2} - 0.5\right)}}\right)
\end{array}
\end{array}
Initial program 66.8%
associate-*l*66.8%
Simplified66.8%
sin-mult80.6%
cos-sum80.6%
cos-280.6%
div-sub80.6%
+-inverses80.6%
Applied egg-rr66.8%
cos-080.6%
metadata-eval80.6%
Simplified66.8%
Final simplification66.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_1 (pow (sin (* phi2 -0.5)) 2.0)))
(if (or (<= phi2 -4.4e-14) (not (<= phi2 1.9e-16)))
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (* (cos phi2) (pow (sin (* lambda2 -0.5)) 2.0))))
(sqrt (- (pow (cos (* phi2 -0.5)) 2.0) (* (cos phi2) t_0))))))
(*
R
(* 2.0 (atan2 (sqrt (fma (cos phi2) t_0 t_1)) (sqrt (- 1.0 t_0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = pow(sin((phi2 * -0.5)), 2.0);
double tmp;
if ((phi2 <= -4.4e-14) || !(phi2 <= 1.9e-16)) {
tmp = R * (2.0 * atan2(sqrt((t_1 + (cos(phi2) * pow(sin((lambda2 * -0.5)), 2.0)))), sqrt((pow(cos((phi2 * -0.5)), 2.0) - (cos(phi2) * t_0)))));
} else {
tmp = R * (2.0 * atan2(sqrt(fma(cos(phi2), t_0, t_1)), sqrt((1.0 - t_0))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_1 = sin(Float64(phi2 * -0.5)) ^ 2.0 tmp = 0.0 if ((phi2 <= -4.4e-14) || !(phi2 <= 1.9e-16)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + Float64(cos(phi2) * (sin(Float64(lambda2 * -0.5)) ^ 2.0)))), sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) - Float64(cos(phi2) * t_0)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(cos(phi2), t_0, t_1)), sqrt(Float64(1.0 - t_0))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[phi2, -4.4e-14], N[Not[LessEqual[phi2, 1.9e-16]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Cos[phi2], $MachinePrecision] * t$95$0 + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_1 := {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\\
\mathbf{if}\;\phi_2 \leq -4.4 \cdot 10^{-14} \lor \neg \left(\phi_2 \leq 1.9 \cdot 10^{-16}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + \cos \phi_2 \cdot {\sin \left(\lambda_2 \cdot -0.5\right)}^{2}}}{\sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} - \cos \phi_2 \cdot t\_0}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_2, t\_0, t\_1\right)}}{\sqrt{1 - t\_0}}\right)\\
\end{array}
\end{array}
if phi2 < -4.4000000000000002e-14 or 1.90000000000000006e-16 < phi2 Initial program 54.9%
Taylor expanded in phi1 around 0 55.9%
+-commutative16.9%
associate--r+16.9%
unpow216.9%
1-sub-sin16.9%
unpow216.9%
Simplified55.9%
add-cbrt-cube55.7%
pow355.8%
Applied egg-rr33.8%
Taylor expanded in phi1 around 0 56.2%
fma-define56.2%
*-commutative56.2%
Simplified56.2%
Taylor expanded in lambda1 around 0 43.9%
if -4.4000000000000002e-14 < phi2 < 1.90000000000000006e-16Initial program 79.9%
Taylor expanded in phi1 around 0 46.5%
+-commutative11.5%
associate--r+11.5%
unpow211.5%
1-sub-sin11.5%
unpow211.5%
Simplified46.5%
add-cbrt-cube45.6%
pow345.5%
Applied egg-rr39.3%
Taylor expanded in phi1 around 0 43.0%
fma-define43.0%
*-commutative43.0%
Simplified43.0%
Taylor expanded in phi2 around 0 43.0%
Final simplification43.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* phi2 -0.5)) 2.0))
(t_1
(sqrt
(-
(pow (cos (* phi2 -0.5)) 2.0)
(* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))))))
(if (or (<= lambda1 -6e-6) (not (<= lambda1 250000000000.0)))
(*
R
(*
2.0
(atan2
(sqrt (+ t_0 (* (cos phi2) (pow (sin (* 0.5 lambda1)) 2.0))))
t_1)))
(*
R
(*
2.0
(atan2
(sqrt (+ t_0 (* (cos phi2) (pow (sin (* lambda2 -0.5)) 2.0))))
t_1))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((phi2 * -0.5)), 2.0);
double t_1 = sqrt((pow(cos((phi2 * -0.5)), 2.0) - (cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0))));
double tmp;
if ((lambda1 <= -6e-6) || !(lambda1 <= 250000000000.0)) {
tmp = R * (2.0 * atan2(sqrt((t_0 + (cos(phi2) * pow(sin((0.5 * lambda1)), 2.0)))), t_1));
} else {
tmp = R * (2.0 * atan2(sqrt((t_0 + (cos(phi2) * pow(sin((lambda2 * -0.5)), 2.0)))), t_1));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: tmp
t_0 = sin((phi2 * (-0.5d0))) ** 2.0d0
t_1 = sqrt(((cos((phi2 * (-0.5d0))) ** 2.0d0) - (cos(phi2) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0))))
if ((lambda1 <= (-6d-6)) .or. (.not. (lambda1 <= 250000000000.0d0))) then
tmp = r * (2.0d0 * atan2(sqrt((t_0 + (cos(phi2) * (sin((0.5d0 * lambda1)) ** 2.0d0)))), t_1))
else
tmp = r * (2.0d0 * atan2(sqrt((t_0 + (cos(phi2) * (sin((lambda2 * (-0.5d0))) ** 2.0d0)))), t_1))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(Math.sin((phi2 * -0.5)), 2.0);
double t_1 = Math.sqrt((Math.pow(Math.cos((phi2 * -0.5)), 2.0) - (Math.cos(phi2) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0))));
double tmp;
if ((lambda1 <= -6e-6) || !(lambda1 <= 250000000000.0)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_0 + (Math.cos(phi2) * Math.pow(Math.sin((0.5 * lambda1)), 2.0)))), t_1));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_0 + (Math.cos(phi2) * Math.pow(Math.sin((lambda2 * -0.5)), 2.0)))), t_1));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(math.sin((phi2 * -0.5)), 2.0) t_1 = math.sqrt((math.pow(math.cos((phi2 * -0.5)), 2.0) - (math.cos(phi2) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0)))) tmp = 0 if (lambda1 <= -6e-6) or not (lambda1 <= 250000000000.0): tmp = R * (2.0 * math.atan2(math.sqrt((t_0 + (math.cos(phi2) * math.pow(math.sin((0.5 * lambda1)), 2.0)))), t_1)) else: tmp = R * (2.0 * math.atan2(math.sqrt((t_0 + (math.cos(phi2) * math.pow(math.sin((lambda2 * -0.5)), 2.0)))), t_1)) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi2 * -0.5)) ^ 2.0 t_1 = sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) - Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)))) tmp = 0.0 if ((lambda1 <= -6e-6) || !(lambda1 <= 250000000000.0)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_0 + Float64(cos(phi2) * (sin(Float64(0.5 * lambda1)) ^ 2.0)))), t_1))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_0 + Float64(cos(phi2) * (sin(Float64(lambda2 * -0.5)) ^ 2.0)))), t_1))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin((phi2 * -0.5)) ^ 2.0; t_1 = sqrt(((cos((phi2 * -0.5)) ^ 2.0) - (cos(phi2) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0)))); tmp = 0.0; if ((lambda1 <= -6e-6) || ~((lambda1 <= 250000000000.0))) tmp = R * (2.0 * atan2(sqrt((t_0 + (cos(phi2) * (sin((0.5 * lambda1)) ^ 2.0)))), t_1)); else tmp = R * (2.0 * atan2(sqrt((t_0 + (cos(phi2) * (sin((lambda2 * -0.5)) ^ 2.0)))), t_1)); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[lambda1, -6e-6], N[Not[LessEqual[lambda1, 250000000000.0]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 + N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 + N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\\
t_1 := \sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} - \cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}\\
\mathbf{if}\;\lambda_1 \leq -6 \cdot 10^{-6} \lor \neg \left(\lambda_1 \leq 250000000000\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 + \cos \phi_2 \cdot {\sin \left(0.5 \cdot \lambda_1\right)}^{2}}}{t\_1}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 + \cos \phi_2 \cdot {\sin \left(\lambda_2 \cdot -0.5\right)}^{2}}}{t\_1}\right)\\
\end{array}
\end{array}
if lambda1 < -6.0000000000000002e-6 or 2.5e11 < lambda1 Initial program 55.2%
Taylor expanded in phi1 around 0 44.4%
+-commutative10.2%
associate--r+10.2%
unpow210.2%
1-sub-sin10.2%
unpow210.2%
Simplified44.4%
add-cbrt-cube44.3%
pow344.3%
Applied egg-rr30.6%
Taylor expanded in phi1 around 0 43.9%
fma-define43.9%
*-commutative43.9%
Simplified43.9%
Taylor expanded in lambda2 around 0 43.2%
if -6.0000000000000002e-6 < lambda1 < 2.5e11Initial program 78.3%
Taylor expanded in phi1 around 0 58.5%
+-commutative18.5%
associate--r+18.5%
unpow218.5%
1-sub-sin18.5%
unpow218.5%
Simplified58.5%
add-cbrt-cube57.6%
pow357.6%
Applied egg-rr42.2%
Taylor expanded in phi1 around 0 56.0%
fma-define56.0%
*-commutative56.0%
Simplified56.0%
Taylor expanded in lambda1 around 0 53.5%
Final simplification48.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(sqrt
(fma
(cos phi2)
(- 0.5 (/ (cos (- lambda2 lambda1)) 2.0))
(pow (sin (* phi2 -0.5)) 2.0)))
(sqrt
(-
(pow (cos (* phi2 -0.5)) 2.0)
(* (cos phi2) (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(fma(cos(phi2), (0.5 - (cos((lambda2 - lambda1)) / 2.0)), pow(sin((phi2 * -0.5)), 2.0))), sqrt((pow(cos((phi2 * -0.5)), 2.0) - (cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0))))));
}
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(sqrt(fma(cos(phi2), Float64(0.5 - Float64(cos(Float64(lambda2 - lambda1)) / 2.0)), (sin(Float64(phi2 * -0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) - Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 - N[(N[Cos[N[(lambda2 - lambda1), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_2, 0.5 - \frac{\cos \left(\lambda_2 - \lambda_1\right)}{2}, {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}}{\sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} - \cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}\right)
\end{array}
Initial program 66.8%
Taylor expanded in phi1 around 0 51.4%
+-commutative14.3%
associate--r+14.3%
unpow214.3%
1-sub-sin14.3%
unpow214.3%
Simplified51.4%
add-cbrt-cube50.9%
pow350.9%
Applied egg-rr36.4%
Taylor expanded in phi1 around 0 49.9%
fma-define49.9%
*-commutative49.9%
Simplified49.9%
unpow214.3%
sin-mult14.3%
*-commutative14.3%
*-commutative14.3%
*-commutative14.3%
*-commutative14.3%
Applied egg-rr47.1%
div-sub14.3%
+-inverses14.3%
cos-014.3%
metadata-eval14.3%
distribute-lft-out14.3%
metadata-eval14.3%
*-rgt-identity14.3%
sub-neg14.3%
remove-double-neg14.3%
mul-1-neg14.3%
distribute-neg-in14.3%
+-commutative14.3%
cos-neg14.3%
mul-1-neg14.3%
unsub-neg14.3%
Simplified47.1%
Final simplification47.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(sqrt
(fma
(cos phi2)
(pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)
(pow (sin (* phi2 -0.5)) 2.0)))
(sqrt
(+
(pow (cos (* phi2 -0.5)) 2.0)
(* (cos phi2) (- (/ (cos (- lambda2 lambda1)) 2.0) 0.5))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2(sqrt(fma(cos(phi2), pow(sin((0.5 * (lambda1 - lambda2))), 2.0), pow(sin((phi2 * -0.5)), 2.0))), sqrt((pow(cos((phi2 * -0.5)), 2.0) + (cos(phi2) * ((cos((lambda2 - lambda1)) / 2.0) - 0.5))))));
}
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(sqrt(fma(cos(phi2), (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0), (sin(Float64(phi2 * -0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) + Float64(cos(phi2) * Float64(Float64(cos(Float64(lambda2 - lambda1)) / 2.0) - 0.5))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi2], $MachinePrecision] * N[(N[(N[Cos[N[(lambda2 - lambda1), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_2, {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}, {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}}{\sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} + \cos \phi_2 \cdot \left(\frac{\cos \left(\lambda_2 - \lambda_1\right)}{2} - 0.5\right)}}\right)
\end{array}
Initial program 66.8%
Taylor expanded in phi1 around 0 51.4%
+-commutative14.3%
associate--r+14.3%
unpow214.3%
1-sub-sin14.3%
unpow214.3%
Simplified51.4%
add-cbrt-cube50.9%
pow350.9%
Applied egg-rr36.4%
Taylor expanded in phi1 around 0 49.9%
fma-define49.9%
*-commutative49.9%
Simplified49.9%
unpow214.3%
sin-mult14.3%
*-commutative14.3%
*-commutative14.3%
*-commutative14.3%
*-commutative14.3%
Applied egg-rr50.0%
div-sub14.3%
+-inverses14.3%
cos-014.3%
metadata-eval14.3%
distribute-lft-out14.3%
metadata-eval14.3%
*-rgt-identity14.3%
sub-neg14.3%
remove-double-neg14.3%
mul-1-neg14.3%
distribute-neg-in14.3%
+-commutative14.3%
cos-neg14.3%
mul-1-neg14.3%
unsub-neg14.3%
Simplified50.0%
Final simplification50.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
(*
R
(*
2.0
(atan2
(sqrt (fma (cos phi2) t_0 (pow (sin (* phi2 -0.5)) 2.0)))
(sqrt (- 1.0 t_0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
return R * (2.0 * atan2(sqrt(fma(cos(phi2), t_0, pow(sin((phi2 * -0.5)), 2.0))), sqrt((1.0 - t_0))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 return Float64(R * Float64(2.0 * atan(sqrt(fma(cos(phi2), t_0, (sin(Float64(phi2 * -0.5)) ^ 2.0))), sqrt(Float64(1.0 - t_0))))) 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]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Cos[phi2], $MachinePrecision] * t$95$0 + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_2, t\_0, {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}}{\sqrt{1 - t\_0}}\right)
\end{array}
\end{array}
Initial program 66.8%
Taylor expanded in phi1 around 0 51.4%
+-commutative14.3%
associate--r+14.3%
unpow214.3%
1-sub-sin14.3%
unpow214.3%
Simplified51.4%
add-cbrt-cube50.9%
pow350.9%
Applied egg-rr36.4%
Taylor expanded in phi1 around 0 49.9%
fma-define49.9%
*-commutative49.9%
Simplified49.9%
Taylor expanded in phi2 around 0 32.3%
Final simplification32.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- phi1 phi2))))
(t_1 (sin (* 0.5 (- lambda1 lambda2)))))
(if (<= (sin (/ (- lambda1 lambda2) 2.0)) 2e-29)
(*
R
(*
2.0
(atan2
t_0
(sqrt
(-
1.0
(+
(pow t_0 2.0)
(* (cos phi1) (* (cos phi2) (pow (sin (* lambda2 -0.5)) 2.0)))))))))
(*
R
(*
2.0
(atan2
t_1
(sqrt
(- (pow (cos (* phi2 -0.5)) 2.0) (* (cos phi2) (pow t_1 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 = sin((0.5 * (lambda1 - lambda2)));
double tmp;
if (sin(((lambda1 - lambda2) / 2.0)) <= 2e-29) {
tmp = R * (2.0 * atan2(t_0, sqrt((1.0 - (pow(t_0, 2.0) + (cos(phi1) * (cos(phi2) * pow(sin((lambda2 * -0.5)), 2.0))))))));
} else {
tmp = R * (2.0 * atan2(t_1, sqrt((pow(cos((phi2 * -0.5)), 2.0) - (cos(phi2) * pow(t_1, 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((0.5d0 * (phi1 - phi2)))
t_1 = sin((0.5d0 * (lambda1 - lambda2)))
if (sin(((lambda1 - lambda2) / 2.0d0)) <= 2d-29) then
tmp = r * (2.0d0 * atan2(t_0, sqrt((1.0d0 - ((t_0 ** 2.0d0) + (cos(phi1) * (cos(phi2) * (sin((lambda2 * (-0.5d0))) ** 2.0d0))))))))
else
tmp = r * (2.0d0 * atan2(t_1, sqrt(((cos((phi2 * (-0.5d0))) ** 2.0d0) - (cos(phi2) * (t_1 ** 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((0.5 * (phi1 - phi2)));
double t_1 = Math.sin((0.5 * (lambda1 - lambda2)));
double tmp;
if (Math.sin(((lambda1 - lambda2) / 2.0)) <= 2e-29) {
tmp = R * (2.0 * Math.atan2(t_0, Math.sqrt((1.0 - (Math.pow(t_0, 2.0) + (Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((lambda2 * -0.5)), 2.0))))))));
} else {
tmp = R * (2.0 * Math.atan2(t_1, Math.sqrt((Math.pow(Math.cos((phi2 * -0.5)), 2.0) - (Math.cos(phi2) * Math.pow(t_1, 2.0))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin((0.5 * (phi1 - phi2))) t_1 = math.sin((0.5 * (lambda1 - lambda2))) tmp = 0 if math.sin(((lambda1 - lambda2) / 2.0)) <= 2e-29: tmp = R * (2.0 * math.atan2(t_0, math.sqrt((1.0 - (math.pow(t_0, 2.0) + (math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((lambda2 * -0.5)), 2.0)))))))) else: tmp = R * (2.0 * math.atan2(t_1, math.sqrt((math.pow(math.cos((phi2 * -0.5)), 2.0) - (math.cos(phi2) * math.pow(t_1, 2.0)))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(phi1 - phi2))) t_1 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) tmp = 0.0 if (sin(Float64(Float64(lambda1 - lambda2) / 2.0)) <= 2e-29) tmp = Float64(R * Float64(2.0 * atan(t_0, sqrt(Float64(1.0 - Float64((t_0 ^ 2.0) + Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(lambda2 * -0.5)) ^ 2.0))))))))); else tmp = Float64(R * Float64(2.0 * atan(t_1, sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) - Float64(cos(phi2) * (t_1 ^ 2.0))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin((0.5 * (phi1 - phi2))); t_1 = sin((0.5 * (lambda1 - lambda2))); tmp = 0.0; if (sin(((lambda1 - lambda2) / 2.0)) <= 2e-29) tmp = R * (2.0 * atan2(t_0, sqrt((1.0 - ((t_0 ^ 2.0) + (cos(phi1) * (cos(phi2) * (sin((lambda2 * -0.5)) ^ 2.0)))))))); else tmp = R * (2.0 * atan2(t_1, sqrt(((cos((phi2 * -0.5)) ^ 2.0) - (cos(phi2) * (t_1 ^ 2.0)))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2e-29], N[(R * N[(2.0 * N[ArcTan[t$95$0 / N[Sqrt[N[(1.0 - N[(N[Power[t$95$0, 2.0], $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$1 / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi2], $MachinePrecision] * N[Power[t$95$1, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
t_1 := \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\\
\mathbf{if}\;\sin \left(\frac{\lambda_1 - \lambda_2}{2}\right) \leq 2 \cdot 10^{-29}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_0}{\sqrt{1 - \left({t\_0}^{2} + \cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(\lambda_2 \cdot -0.5\right)}^{2}\right)\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_1}{\sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} - \cos \phi_2 \cdot {t\_1}^{2}}}\right)\\
\end{array}
\end{array}
if (sin.f64 (/.f64 (-.f64 lambda1 lambda2) 2)) < 1.99999999999999989e-29Initial program 68.8%
Taylor expanded in lambda1 around 0 50.3%
Taylor expanded in lambda2 around 0 20.6%
Taylor expanded in lambda1 around 0 20.8%
if 1.99999999999999989e-29 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) 2)) Initial program 63.9%
Taylor expanded in phi1 around 0 47.4%
+-commutative8.8%
associate--r+8.8%
unpow28.8%
1-sub-sin8.8%
unpow28.8%
Simplified47.4%
add-cbrt-cube47.3%
pow347.3%
Applied egg-rr35.5%
Taylor expanded in phi1 around 0 47.0%
fma-define47.0%
*-commutative47.0%
Simplified47.0%
Taylor expanded in phi2 around 0 31.8%
Final simplification25.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- lambda1 lambda2))))
(t_1
(sqrt
(- (pow (cos (* phi2 -0.5)) 2.0) (* (cos phi2) (pow t_0 2.0))))))
(if (<= phi2 -1.9e+15)
(* R (* 2.0 (atan2 (sin (* phi2 -0.5)) t_1)))
(* R (* 2.0 (atan2 t_0 t_1))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (lambda1 - lambda2)));
double t_1 = sqrt((pow(cos((phi2 * -0.5)), 2.0) - (cos(phi2) * pow(t_0, 2.0))));
double tmp;
if (phi2 <= -1.9e+15) {
tmp = R * (2.0 * atan2(sin((phi2 * -0.5)), t_1));
} else {
tmp = R * (2.0 * atan2(t_0, t_1));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: tmp
t_0 = sin((0.5d0 * (lambda1 - lambda2)))
t_1 = sqrt(((cos((phi2 * (-0.5d0))) ** 2.0d0) - (cos(phi2) * (t_0 ** 2.0d0))))
if (phi2 <= (-1.9d+15)) then
tmp = r * (2.0d0 * atan2(sin((phi2 * (-0.5d0))), t_1))
else
tmp = r * (2.0d0 * atan2(t_0, t_1))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin((0.5 * (lambda1 - lambda2)));
double t_1 = Math.sqrt((Math.pow(Math.cos((phi2 * -0.5)), 2.0) - (Math.cos(phi2) * Math.pow(t_0, 2.0))));
double tmp;
if (phi2 <= -1.9e+15) {
tmp = R * (2.0 * Math.atan2(Math.sin((phi2 * -0.5)), t_1));
} else {
tmp = R * (2.0 * Math.atan2(t_0, t_1));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin((0.5 * (lambda1 - lambda2))) t_1 = math.sqrt((math.pow(math.cos((phi2 * -0.5)), 2.0) - (math.cos(phi2) * math.pow(t_0, 2.0)))) tmp = 0 if phi2 <= -1.9e+15: tmp = R * (2.0 * math.atan2(math.sin((phi2 * -0.5)), t_1)) else: tmp = R * (2.0 * math.atan2(t_0, t_1)) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) t_1 = sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) - Float64(cos(phi2) * (t_0 ^ 2.0)))) tmp = 0.0 if (phi2 <= -1.9e+15) tmp = Float64(R * Float64(2.0 * atan(sin(Float64(phi2 * -0.5)), t_1))); else tmp = Float64(R * Float64(2.0 * atan(t_0, t_1))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin((0.5 * (lambda1 - lambda2))); t_1 = sqrt(((cos((phi2 * -0.5)) ^ 2.0) - (cos(phi2) * (t_0 ^ 2.0)))); tmp = 0.0; if (phi2 <= -1.9e+15) tmp = R * (2.0 * atan2(sin((phi2 * -0.5)), t_1)); else tmp = R * (2.0 * atan2(t_0, t_1)); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi2], $MachinePrecision] * N[Power[t$95$0, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi2, -1.9e+15], N[(R * N[(2.0 * N[ArcTan[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] / t$95$1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$0 / t$95$1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\\
t_1 := \sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} - \cos \phi_2 \cdot {t\_0}^{2}}\\
\mathbf{if}\;\phi_2 \leq -1.9 \cdot 10^{+15}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sin \left(\phi_2 \cdot -0.5\right)}{t\_1}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_0}{t\_1}\right)\\
\end{array}
\end{array}
if phi2 < -1.9e15Initial program 52.9%
Taylor expanded in lambda1 around 0 46.9%
Taylor expanded in lambda2 around 0 21.1%
Taylor expanded in phi1 around 0 21.9%
+-commutative21.9%
associate--r+21.9%
unpow221.9%
1-sub-sin22.0%
unpow222.0%
Simplified22.0%
Taylor expanded in phi1 around 0 22.5%
*-commutative22.5%
Simplified22.5%
if -1.9e15 < phi2 Initial program 71.1%
Taylor expanded in phi1 around 0 50.6%
+-commutative12.0%
associate--r+12.0%
unpow212.0%
1-sub-sin12.0%
unpow212.0%
Simplified50.5%
add-cbrt-cube49.9%
pow349.9%
Applied egg-rr40.4%
Taylor expanded in phi1 around 0 48.4%
fma-define48.4%
*-commutative48.4%
Simplified48.4%
Taylor expanded in phi2 around 0 19.0%
Final simplification19.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(sin (* 0.5 (- phi1 phi2)))
(sqrt
(+
(pow (cos (* phi2 -0.5)) 2.0)
(* (cos phi2) (- (/ (cos (- lambda2 lambda1)) 2.0) 0.5))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2(sin((0.5 * (phi1 - phi2))), sqrt((pow(cos((phi2 * -0.5)), 2.0) + (cos(phi2) * ((cos((lambda2 - lambda1)) / 2.0) - 0.5))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
code = r * (2.0d0 * atan2(sin((0.5d0 * (phi1 - phi2))), sqrt(((cos((phi2 * (-0.5d0))) ** 2.0d0) + (cos(phi2) * ((cos((lambda2 - lambda1)) / 2.0d0) - 0.5d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * Math.atan2(Math.sin((0.5 * (phi1 - phi2))), Math.sqrt((Math.pow(Math.cos((phi2 * -0.5)), 2.0) + (Math.cos(phi2) * ((Math.cos((lambda2 - lambda1)) / 2.0) - 0.5))))));
}
def code(R, lambda1, lambda2, phi1, phi2): return R * (2.0 * math.atan2(math.sin((0.5 * (phi1 - phi2))), math.sqrt((math.pow(math.cos((phi2 * -0.5)), 2.0) + (math.cos(phi2) * ((math.cos((lambda2 - lambda1)) / 2.0) - 0.5))))))
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(sin(Float64(0.5 * Float64(phi1 - phi2))), sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) + Float64(cos(phi2) * Float64(Float64(cos(Float64(lambda2 - lambda1)) / 2.0) - 0.5))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) tmp = R * (2.0 * atan2(sin((0.5 * (phi1 - phi2))), sqrt(((cos((phi2 * -0.5)) ^ 2.0) + (cos(phi2) * ((cos((lambda2 - lambda1)) / 2.0) - 0.5)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi2], $MachinePrecision] * N[(N[(N[Cos[N[(lambda2 - lambda1), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}{\sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} + \cos \phi_2 \cdot \left(\frac{\cos \left(\lambda_2 - \lambda_1\right)}{2} - 0.5\right)}}\right)
\end{array}
Initial program 66.8%
Taylor expanded in lambda1 around 0 46.3%
Taylor expanded in lambda2 around 0 16.0%
Taylor expanded in phi1 around 0 14.3%
+-commutative14.3%
associate--r+14.3%
unpow214.3%
1-sub-sin14.3%
unpow214.3%
Simplified14.3%
unpow214.3%
sin-mult14.3%
*-commutative14.3%
*-commutative14.3%
*-commutative14.3%
*-commutative14.3%
Applied egg-rr14.3%
div-sub14.3%
+-inverses14.3%
cos-014.3%
metadata-eval14.3%
distribute-lft-out14.3%
metadata-eval14.3%
*-rgt-identity14.3%
sub-neg14.3%
remove-double-neg14.3%
mul-1-neg14.3%
distribute-neg-in14.3%
+-commutative14.3%
cos-neg14.3%
mul-1-neg14.3%
unsub-neg14.3%
Simplified14.3%
Final simplification14.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(sin (* 0.5 (- phi1 phi2)))
(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(sin((0.5 * (phi1 - phi2))), 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(sin((0.5d0 * (phi1 - phi2))), 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.sin((0.5 * (phi1 - phi2))), 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.sin((0.5 * (phi1 - phi2))), 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(sin(Float64(0.5 * Float64(phi1 - phi2))), 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(sin((0.5 * (phi1 - phi2))), 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[Sin[N[(0.5 * N[(phi1 - phi2), $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{\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}\right)
\end{array}
Initial program 66.8%
Taylor expanded in lambda1 around 0 46.3%
Taylor expanded in lambda2 around 0 16.0%
Taylor expanded in phi1 around 0 14.3%
+-commutative14.3%
associate--r+14.3%
unpow214.3%
1-sub-sin14.3%
unpow214.3%
Simplified14.3%
Taylor expanded in phi2 around 0 11.0%
Final simplification11.0%
herbie shell --seed 2024043
(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))))))))))