
(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 17 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_0) t_0))))
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0);
return R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0)
code = r * (2.0d0 * atan2(sqrt(t_1), sqrt((1.0d0 - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((Math.cos(phi1) * Math.cos(phi2)) * t_0) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt(t_1), Math.sqrt((1.0 - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((math.cos(phi1) * math.cos(phi2)) * t_0) * t_0) return R * (2.0 * math.atan2(math.sqrt(t_1), math.sqrt((1.0 - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0); tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$1], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t_0\right) \cdot t_0\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t_1}}{\sqrt{1 - t_1}}\right)
\end{array}
\end{array}
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (/ phi2 2.0)))
(t_1 (cos (/ phi1 2.0)))
(t_2 (sin (/ phi2 2.0)))
(t_3 (* (cos phi1) (cos phi2)))
(t_4 (sin (/ (- lambda1 lambda2) 2.0)))
(t_5 (sin (/ phi1 2.0))))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (fma t_5 t_0 (* t_1 (- t_2))) 2.0) (* t_3 (* t_4 t_4))))
(sqrt
(-
(- 1.0 (pow (- (* t_5 t_0) (* t_1 t_2)) 2.0))
(* t_3 (/ (- 1.0 (cos (- lambda1 lambda2))) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((phi2 / 2.0));
double t_1 = cos((phi1 / 2.0));
double t_2 = sin((phi2 / 2.0));
double t_3 = cos(phi1) * cos(phi2);
double t_4 = sin(((lambda1 - lambda2) / 2.0));
double t_5 = sin((phi1 / 2.0));
return R * (2.0 * atan2(sqrt((pow(fma(t_5, t_0, (t_1 * -t_2)), 2.0) + (t_3 * (t_4 * t_4)))), sqrt(((1.0 - pow(((t_5 * t_0) - (t_1 * t_2)), 2.0)) - (t_3 * ((1.0 - cos((lambda1 - lambda2))) / 2.0))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(phi2 / 2.0)) t_1 = cos(Float64(phi1 / 2.0)) t_2 = sin(Float64(phi2 / 2.0)) t_3 = Float64(cos(phi1) * cos(phi2)) t_4 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_5 = sin(Float64(phi1 / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((fma(t_5, t_0, Float64(t_1 * Float64(-t_2))) ^ 2.0) + Float64(t_3 * Float64(t_4 * t_4)))), sqrt(Float64(Float64(1.0 - (Float64(Float64(t_5 * t_0) - Float64(t_1 * t_2)) ^ 2.0)) - Float64(t_3 * Float64(Float64(1.0 - cos(Float64(lambda1 - lambda2))) / 2.0))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$5 = N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(t$95$5 * t$95$0 + N[(t$95$1 * (-t$95$2)), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$3 * N[(t$95$4 * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[(N[(t$95$5 * t$95$0), $MachinePrecision] - N[(t$95$1 * t$95$2), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] - N[(t$95$3 * N[(N[(1.0 - N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(\frac{\phi_2}{2}\right)\\
t_1 := \cos \left(\frac{\phi_1}{2}\right)\\
t_2 := \sin \left(\frac{\phi_2}{2}\right)\\
t_3 := \cos \phi_1 \cdot \cos \phi_2\\
t_4 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_5 := \sin \left(\frac{\phi_1}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(t_5, t_0, t_1 \cdot \left(-t_2\right)\right)\right)}^{2} + t_3 \cdot \left(t_4 \cdot t_4\right)}}{\sqrt{\left(1 - {\left(t_5 \cdot t_0 - t_1 \cdot t_2\right)}^{2}\right) - t_3 \cdot \frac{1 - \cos \left(\lambda_1 - \lambda_2\right)}{2}}}\right)
\end{array}
\end{array}
Initial program 60.7%
associate-*l*60.7%
Simplified60.7%
div-sub60.7%
sin-diff62.0%
Applied egg-rr62.0%
div-sub60.7%
sin-diff62.0%
Applied egg-rr77.8%
fma-neg77.8%
distribute-rgt-neg-in77.8%
Simplified77.8%
sin-mult77.9%
Applied egg-rr77.9%
div077.9%
cos-077.9%
Simplified77.9%
Final simplification77.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(+
(*
(cos phi1)
(* (cos phi2) (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
(pow
(-
(* (cos (* phi2 0.5)) (sin (* phi1 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0))))
(* R (* 2.0 (atan2 (sqrt t_0) (sqrt (- 1.0 t_0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = (cos(phi1) * (cos(phi2) * pow(sin(((lambda1 - lambda2) * 0.5)), 2.0))) + pow(((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0);
return R * (2.0 * atan2(sqrt(t_0), sqrt((1.0 - t_0))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = (cos(phi1) * (cos(phi2) * (sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0))) + (((cos((phi2 * 0.5d0)) * sin((phi1 * 0.5d0))) - (cos((phi1 * 0.5d0)) * sin((phi2 * 0.5d0)))) ** 2.0d0)
code = r * (2.0d0 * atan2(sqrt(t_0), sqrt((1.0d0 - t_0))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = (Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0))) + Math.pow(((Math.cos((phi2 * 0.5)) * Math.sin((phi1 * 0.5))) - (Math.cos((phi1 * 0.5)) * Math.sin((phi2 * 0.5)))), 2.0);
return R * (2.0 * Math.atan2(Math.sqrt(t_0), Math.sqrt((1.0 - t_0))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = (math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0))) + math.pow(((math.cos((phi2 * 0.5)) * math.sin((phi1 * 0.5))) - (math.cos((phi1 * 0.5)) * math.sin((phi2 * 0.5)))), 2.0) return R * (2.0 * math.atan2(math.sqrt(t_0), math.sqrt((1.0 - t_0))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0))) + (Float64(Float64(cos(Float64(phi2 * 0.5)) * sin(Float64(phi1 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(t_0), sqrt(Float64(1.0 - t_0))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = (cos(phi1) * (cos(phi2) * (sin(((lambda1 - lambda2) * 0.5)) ^ 2.0))) + (((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))) ^ 2.0); tmp = R * (2.0 * atan2(sqrt(t_0), sqrt((1.0 - t_0)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[(N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$0], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\right) + {\left(\cos \left(\phi_2 \cdot 0.5\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t_0}}{\sqrt{1 - t_0}}\right)
\end{array}
\end{array}
Initial program 60.7%
associate-*l*60.7%
Simplified60.7%
div-sub60.7%
sin-diff62.0%
Applied egg-rr62.0%
div-sub60.7%
sin-diff62.0%
Applied egg-rr77.8%
Taylor expanded in phi1 around 0 77.8%
Final simplification77.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt
(-
(-
1.0
(pow
(-
(* (sin (/ phi1 2.0)) (cos (/ phi2 2.0)))
(* (cos (/ phi1 2.0)) (sin (/ phi2 2.0))))
2.0))
t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0);
return R * (2.0 * atan2(sqrt((t_1 + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt(((1.0 - pow(((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))), 2.0)) - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (cos(phi1) * cos(phi2)) * (t_0 * t_0)
code = r * (2.0d0 * atan2(sqrt((t_1 + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt(((1.0d0 - (((sin((phi1 / 2.0d0)) * cos((phi2 / 2.0d0))) - (cos((phi1 / 2.0d0)) * sin((phi2 / 2.0d0)))) ** 2.0d0)) - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = (Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0);
return R * (2.0 * Math.atan2(Math.sqrt((t_1 + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt(((1.0 - Math.pow(((Math.sin((phi1 / 2.0)) * Math.cos((phi2 / 2.0))) - (Math.cos((phi1 / 2.0)) * Math.sin((phi2 / 2.0)))), 2.0)) - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = (math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0) return R * (2.0 * math.atan2(math.sqrt((t_1 + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt(((1.0 - math.pow(((math.sin((phi1 / 2.0)) * math.cos((phi2 / 2.0))) - (math.cos((phi1 / 2.0)) * math.sin((phi2 / 2.0)))), 2.0)) - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(Float64(1.0 - (Float64(Float64(sin(Float64(phi1 / 2.0)) * cos(Float64(phi2 / 2.0))) - Float64(cos(Float64(phi1 / 2.0)) * sin(Float64(phi2 / 2.0)))) ^ 2.0)) - t_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 - (((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))) ^ 2.0)) - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[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[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 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(\sin \left(\frac{\phi_1}{2}\right) \cdot \cos \left(\frac{\phi_2}{2}\right) - \cos \left(\frac{\phi_1}{2}\right) \cdot \sin \left(\frac{\phi_2}{2}\right)\right)}^{2}\right) - t_1}}\right)
\end{array}
\end{array}
Initial program 60.7%
associate-*l*60.7%
Simplified60.7%
div-sub60.7%
sin-diff62.0%
Applied egg-rr62.0%
Final simplification62.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* t_0 (* (* (cos phi1) (cos phi2)) t_0))))
(sqrt
(fabs
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (+ 0.5 (* (cos (- lambda1 lambda2)) -0.5)))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * ((cos(phi1) * cos(phi2)) * t_0)))), sqrt(fabs((1.0 - fma(cos(phi1), (cos(phi2) * (0.5 + (cos((lambda1 - lambda2)) * -0.5))), pow(sin((0.5 * (phi1 - phi2))), 2.0)))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)))), sqrt(abs(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * Float64(0.5 + Float64(cos(Float64(lambda1 - lambda2)) * -0.5))), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[Abs[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 + N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] * -0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t_0\right)}}{\sqrt{\left|1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \left(0.5 + \cos \left(\lambda_1 - \lambda_2\right) \cdot -0.5\right), {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)\right|}}\right)
\end{array}
\end{array}
Initial program 60.7%
add-sqr-sqrt60.7%
sqrt-unprod61.5%
pow261.5%
Applied egg-rr61.5%
unpow261.5%
rem-sqrt-square61.5%
fma-udef61.5%
associate-*l*61.5%
*-commutative61.5%
fma-udef61.5%
Simplified61.5%
Final simplification61.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (pow (sin (* phi1 0.5)) 2.0))
(t_2 (* (cos phi1) (cos phi2)))
(t_3 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_4 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(if (<= phi1 -0.00095)
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)
(* (cos phi1) (* (cos phi2) (pow (sin (* lambda1 0.5)) 2.0)))))
(sqrt (- 1.0 (+ (* (cos phi1) t_3) t_1))))))
(if (<= phi1 0.00075)
(*
R
(*
2.0
(atan2
(sqrt (+ t_4 (* t_0 (* t_2 t_0))))
(sqrt (- (pow (cos (* phi2 -0.5)) 2.0) (* (cos phi2) t_3))))))
(*
R
(*
2.0
(atan2
(sqrt (fma t_3 (cos phi1) t_1))
(sqrt (- (- 1.0 t_4) (* t_2 (+ 0.5 (* -0.5 (cos lambda2)))))))))))))
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 * 0.5)), 2.0);
double t_2 = cos(phi1) * cos(phi2);
double t_3 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_4 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double tmp;
if (phi1 <= -0.00095) {
tmp = R * (2.0 * atan2(sqrt((pow(sin((0.5 * (phi1 - phi2))), 2.0) + (cos(phi1) * (cos(phi2) * pow(sin((lambda1 * 0.5)), 2.0))))), sqrt((1.0 - ((cos(phi1) * t_3) + t_1)))));
} else if (phi1 <= 0.00075) {
tmp = R * (2.0 * atan2(sqrt((t_4 + (t_0 * (t_2 * t_0)))), sqrt((pow(cos((phi2 * -0.5)), 2.0) - (cos(phi2) * t_3)))));
} else {
tmp = R * (2.0 * atan2(sqrt(fma(t_3, cos(phi1), t_1)), sqrt(((1.0 - t_4) - (t_2 * (0.5 + (-0.5 * cos(lambda2))))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sin(Float64(phi1 * 0.5)) ^ 2.0 t_2 = Float64(cos(phi1) * cos(phi2)) t_3 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_4 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 tmp = 0.0 if (phi1 <= -0.00095) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0) + Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(lambda1 * 0.5)) ^ 2.0))))), sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * t_3) + t_1)))))); elseif (phi1 <= 0.00075) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_4 + Float64(t_0 * Float64(t_2 * t_0)))), sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) - Float64(cos(phi2) * t_3)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_3, cos(phi1), t_1)), sqrt(Float64(Float64(1.0 - t_4) - Float64(t_2 * Float64(0.5 + Float64(-0.5 * cos(lambda2))))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$4 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[LessEqual[phi1, -0.00095], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * t$95$3), $MachinePrecision] + t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[phi1, 0.00075], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$4 + N[(t$95$0 * N[(t$95$2 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi2], $MachinePrecision] * t$95$3), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$3 * N[Cos[phi1], $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - t$95$4), $MachinePrecision] - N[(t$95$2 * N[(0.5 + N[(-0.5 * N[Cos[lambda2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
t_3 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_4 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
\mathbf{if}\;\phi_1 \leq -0.00095:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2} + \cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(\lambda_1 \cdot 0.5\right)}^{2}\right)}}{\sqrt{1 - \left(\cos \phi_1 \cdot t_3 + t_1\right)}}\right)\\
\mathbf{elif}\;\phi_1 \leq 0.00075:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t_4 + t_0 \cdot \left(t_2 \cdot t_0\right)}}{\sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} - \cos \phi_2 \cdot t_3}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t_3, \cos \phi_1, t_1\right)}}{\sqrt{\left(1 - t_4\right) - t_2 \cdot \left(0.5 + -0.5 \cdot \cos \lambda_2\right)}}\right)\\
\end{array}
\end{array}
if phi1 < -9.49999999999999998e-4Initial program 49.4%
associate-*l*49.5%
Simplified49.5%
div-sub49.5%
sin-diff51.7%
Applied egg-rr51.7%
Taylor expanded in lambda2 around 0 45.1%
Taylor expanded in phi2 around 0 44.3%
if -9.49999999999999998e-4 < phi1 < 7.5000000000000002e-4Initial program 79.1%
Taylor expanded in phi1 around 0 79.1%
+-commutative79.1%
associate--r+79.1%
unpow279.1%
1-sub-sin79.1%
unpow279.1%
*-commutative79.1%
Simplified79.1%
if 7.5000000000000002e-4 < phi1 Initial program 38.9%
associate-*l*38.9%
Simplified39.0%
add-log-exp39.0%
sqr-sin-a39.0%
cos-239.0%
cos-sum39.0%
add-log-exp16.5%
add-log-exp16.5%
sum-log16.5%
exp-sqrt16.5%
exp-sqrt16.5%
add-sqr-sqrt16.5%
add-log-exp39.0%
Applied egg-rr39.0%
Taylor expanded in lambda1 around 0 36.2%
cancel-sign-sub-inv36.2%
metadata-eval36.2%
cos-neg36.2%
Simplified36.2%
Taylor expanded in phi2 around 0 37.1%
*-commutative37.1%
fma-def37.1%
Simplified37.1%
Final simplification59.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* phi2 -0.5)) 2.0))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_3 (* (cos phi2) t_2))
(t_4 (sqrt (- (pow (cos (* phi2 -0.5)) 2.0) t_3))))
(if (<= phi2 -2.3e-5)
(* R (* 2.0 (atan2 (sqrt (fma t_2 (cos phi2) t_0)) t_4)))
(if (<= phi2 2300.0)
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* t_1 (* (* (cos phi1) (cos phi2)) t_1))))
(sqrt (- (pow (cos (* phi1 0.5)) 2.0) (* (cos phi1) t_2))))))
(* R (* 2.0 (atan2 (sqrt (+ t_3 t_0)) t_4)))))))
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 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_3 = cos(phi2) * t_2;
double t_4 = sqrt((pow(cos((phi2 * -0.5)), 2.0) - t_3));
double tmp;
if (phi2 <= -2.3e-5) {
tmp = R * (2.0 * atan2(sqrt(fma(t_2, cos(phi2), t_0)), t_4));
} else if (phi2 <= 2300.0) {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_1 * ((cos(phi1) * cos(phi2)) * t_1)))), sqrt((pow(cos((phi1 * 0.5)), 2.0) - (cos(phi1) * t_2)))));
} else {
tmp = R * (2.0 * atan2(sqrt((t_3 + t_0)), t_4));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi2 * -0.5)) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_3 = Float64(cos(phi2) * t_2) t_4 = sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) - t_3)) tmp = 0.0 if (phi2 <= -2.3e-5) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_2, cos(phi2), t_0)), t_4))); elseif (phi2 <= 2300.0) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_1 * Float64(Float64(cos(phi1) * cos(phi2)) * t_1)))), sqrt(Float64((cos(Float64(phi1 * 0.5)) ^ 2.0) - Float64(cos(phi1) * t_2)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_3 + t_0)), t_4))); end return 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[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$3 = N[(N[Cos[phi2], $MachinePrecision] * t$95$2), $MachinePrecision]}, Block[{t$95$4 = N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - t$95$3), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi2, -2.3e-5], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$2 * N[Cos[phi2], $MachinePrecision] + t$95$0), $MachinePrecision]], $MachinePrecision] / t$95$4], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[phi2, 2300.0], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$1 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$1), $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$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$3 + t$95$0), $MachinePrecision]], $MachinePrecision] / t$95$4], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_3 := \cos \phi_2 \cdot t_2\\
t_4 := \sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} - t_3}\\
\mathbf{if}\;\phi_2 \leq -2.3 \cdot 10^{-5}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t_2, \cos \phi_2, t_0\right)}}{t_4}\right)\\
\mathbf{elif}\;\phi_2 \leq 2300:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t_1 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t_1\right)}}{\sqrt{{\cos \left(\phi_1 \cdot 0.5\right)}^{2} - \cos \phi_1 \cdot t_2}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t_3 + t_0}}{t_4}\right)\\
\end{array}
\end{array}
if phi2 < -2.3e-5Initial program 46.3%
Taylor expanded in phi1 around 0 47.6%
+-commutative47.6%
associate--r+47.6%
unpow247.6%
1-sub-sin47.6%
unpow247.6%
*-commutative47.6%
Simplified47.6%
Taylor expanded in phi1 around 0 47.8%
*-commutative47.8%
fma-def47.8%
Simplified47.8%
if -2.3e-5 < phi2 < 2300Initial program 77.3%
Taylor expanded in phi2 around 0 77.4%
+-commutative77.4%
associate--r+77.4%
unpow277.4%
1-sub-sin77.4%
unpow277.4%
*-commutative77.4%
Simplified77.4%
if 2300 < phi2 Initial program 44.1%
Taylor expanded in phi1 around 0 45.8%
+-commutative45.8%
associate--r+45.8%
unpow245.8%
1-sub-sin45.9%
unpow245.9%
*-commutative45.9%
Simplified45.9%
Taylor expanded in phi1 around 0 46.8%
Final simplification61.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (* (cos phi1) (cos phi2)))
(t_3 (pow (sin (* phi1 0.5)) 2.0)))
(if (<= phi1 -1.4e-5)
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)
(* (cos phi1) (* (cos phi2) (pow (sin (* lambda1 0.5)) 2.0)))))
(sqrt (- 1.0 (+ (* (cos phi1) t_0) t_3))))))
(if (<= phi1 1.7e-16)
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_1 (* t_2 t_1)) (pow (sin (* phi2 -0.5)) 2.0)))
(sqrt (- (pow (cos (* phi2 -0.5)) 2.0) (* (cos phi2) t_0))))))
(*
R
(*
2.0
(atan2
(sqrt (fma t_0 (cos phi1) t_3))
(sqrt
(-
(- 1.0 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))
(* t_2 (+ 0.5 (* -0.5 (cos lambda2)))))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = cos(phi1) * cos(phi2);
double t_3 = pow(sin((phi1 * 0.5)), 2.0);
double tmp;
if (phi1 <= -1.4e-5) {
tmp = R * (2.0 * atan2(sqrt((pow(sin((0.5 * (phi1 - phi2))), 2.0) + (cos(phi1) * (cos(phi2) * pow(sin((lambda1 * 0.5)), 2.0))))), sqrt((1.0 - ((cos(phi1) * t_0) + t_3)))));
} else if (phi1 <= 1.7e-16) {
tmp = R * (2.0 * atan2(sqrt(((t_1 * (t_2 * t_1)) + pow(sin((phi2 * -0.5)), 2.0))), sqrt((pow(cos((phi2 * -0.5)), 2.0) - (cos(phi2) * t_0)))));
} else {
tmp = R * (2.0 * atan2(sqrt(fma(t_0, cos(phi1), t_3)), sqrt(((1.0 - pow(sin(((phi1 - phi2) / 2.0)), 2.0)) - (t_2 * (0.5 + (-0.5 * cos(lambda2))))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(cos(phi1) * cos(phi2)) t_3 = sin(Float64(phi1 * 0.5)) ^ 2.0 tmp = 0.0 if (phi1 <= -1.4e-5) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0) + Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(lambda1 * 0.5)) ^ 2.0))))), sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * t_0) + t_3)))))); elseif (phi1 <= 1.7e-16) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_1 * Float64(t_2 * t_1)) + (sin(Float64(phi2 * -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(t_0, cos(phi1), t_3)), sqrt(Float64(Float64(1.0 - (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0)) - Float64(t_2 * Float64(0.5 + Float64(-0.5 * cos(lambda2))))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[LessEqual[phi1, -1.4e-5], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision] + t$95$3), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[phi1, 1.7e-16], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$1 * N[(t$95$2 * t$95$1), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 * N[Cos[phi1], $MachinePrecision] + t$95$3), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] - N[(t$95$2 * N[(0.5 + N[(-0.5 * N[Cos[lambda2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
t_3 := {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\\
\mathbf{if}\;\phi_1 \leq -1.4 \cdot 10^{-5}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2} + \cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(\lambda_1 \cdot 0.5\right)}^{2}\right)}}{\sqrt{1 - \left(\cos \phi_1 \cdot t_0 + t_3\right)}}\right)\\
\mathbf{elif}\;\phi_1 \leq 1.7 \cdot 10^{-16}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t_1 \cdot \left(t_2 \cdot t_1\right) + {\sin \left(\phi_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(t_0, \cos \phi_1, t_3\right)}}{\sqrt{\left(1 - {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right) - t_2 \cdot \left(0.5 + -0.5 \cdot \cos \lambda_2\right)}}\right)\\
\end{array}
\end{array}
if phi1 < -1.39999999999999998e-5Initial program 49.4%
associate-*l*49.5%
Simplified49.5%
div-sub49.5%
sin-diff51.7%
Applied egg-rr51.7%
Taylor expanded in lambda2 around 0 45.1%
Taylor expanded in phi2 around 0 44.3%
if -1.39999999999999998e-5 < phi1 < 1.7e-16Initial program 79.2%
Taylor expanded in phi1 around 0 79.2%
+-commutative79.2%
associate--r+79.2%
unpow279.2%
1-sub-sin79.3%
unpow279.3%
*-commutative79.3%
Simplified79.3%
Taylor expanded in phi1 around 0 77.7%
if 1.7e-16 < phi1 Initial program 40.8%
associate-*l*40.8%
Simplified40.8%
add-log-exp40.8%
sqr-sin-a40.8%
cos-240.8%
cos-sum40.8%
add-log-exp18.2%
add-log-exp18.2%
sum-log18.2%
exp-sqrt18.2%
exp-sqrt18.2%
add-sqr-sqrt18.2%
add-log-exp40.8%
Applied egg-rr40.8%
Taylor expanded in lambda1 around 0 38.2%
cancel-sign-sub-inv38.2%
metadata-eval38.2%
cos-neg38.2%
Simplified38.2%
Taylor expanded in phi2 around 0 38.3%
*-commutative38.3%
fma-def38.3%
Simplified38.3%
Final simplification58.1%
(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
(+
(- 1.0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0))
(* t_1 (- -0.5 (* (cos (- lambda1 lambda2)) -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 = 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(((1.0 - pow(sin((0.5 * (phi1 - phi2))), 2.0)) + (t_1 * (-0.5 - (cos((lambda1 - lambda2)) * -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
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = cos(phi1) * cos(phi2)
code = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (t_0 * (t_1 * t_0)))), sqrt(((1.0d0 - (sin((0.5d0 * (phi1 - phi2))) ** 2.0d0)) + (t_1 * ((-0.5d0) - (cos((lambda1 - lambda2)) * (-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.cos(phi1) * Math.cos(phi2);
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * (t_1 * t_0)))), Math.sqrt(((1.0 - Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0)) + (t_1 * (-0.5 - (Math.cos((lambda1 - lambda2)) * -0.5)))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.cos(phi1) * math.cos(phi2) return R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (t_0 * (t_1 * t_0)))), math.sqrt(((1.0 - math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0)) + (t_1 * (-0.5 - (math.cos((lambda1 - lambda2)) * -0.5)))))))
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(Float64(Float64(1.0 - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)) + Float64(t_1 * Float64(-0.5 - Float64(cos(Float64(lambda1 - lambda2)) * -0.5)))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = cos(phi1) * cos(phi2); tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (t_0 * (t_1 * t_0)))), sqrt(((1.0 - (sin((0.5 * (phi1 - phi2))) ^ 2.0)) + (t_1 * (-0.5 - (cos((lambda1 - lambda2)) * -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[(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[(N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[(t$95$1 * N[(-0.5 - N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] * -0.5), $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 - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right) + t_1 \cdot \left(-0.5 - \cos \left(\lambda_1 - \lambda_2\right) \cdot -0.5\right)}}\right)
\end{array}
\end{array}
Initial program 60.7%
associate--r+60.7%
*-un-lft-identity60.7%
fma-neg60.7%
div-inv60.7%
metadata-eval60.7%
associate-*l*60.7%
sqr-sin-a60.7%
cos-260.7%
Applied egg-rr60.7%
fma-udef60.7%
*-lft-identity60.7%
*-commutative60.7%
distribute-rgt-neg-in60.7%
*-commutative60.7%
neg-sub060.7%
sub-neg60.7%
associate--r+60.7%
metadata-eval60.7%
distribute-lft-neg-in60.7%
metadata-eval60.7%
Simplified60.7%
Final simplification60.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
(if (or (<= phi1 -0.225) (not (<= phi1 9e-16)))
(*
R
(*
2.0
(atan2
(sqrt (fma t_0 (cos phi1) (pow (sin (* phi1 0.5)) 2.0)))
(sqrt
(-
(- 1.0 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))
(* (* (cos phi1) (cos phi2)) (+ 0.5 (* -0.5 (cos lambda2)))))))))
(*
R
(*
2.0
(atan2
(sqrt (fma t_0 (cos phi2) (pow (sin (* phi2 -0.5)) 2.0)))
(sqrt (- (pow (cos (* phi2 -0.5)) 2.0) (* (cos phi2) t_0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double tmp;
if ((phi1 <= -0.225) || !(phi1 <= 9e-16)) {
tmp = R * (2.0 * atan2(sqrt(fma(t_0, cos(phi1), pow(sin((phi1 * 0.5)), 2.0))), sqrt(((1.0 - pow(sin(((phi1 - phi2) / 2.0)), 2.0)) - ((cos(phi1) * cos(phi2)) * (0.5 + (-0.5 * cos(lambda2))))))));
} else {
tmp = R * (2.0 * atan2(sqrt(fma(t_0, cos(phi2), pow(sin((phi2 * -0.5)), 2.0))), sqrt((pow(cos((phi2 * -0.5)), 2.0) - (cos(phi2) * t_0)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 tmp = 0.0 if ((phi1 <= -0.225) || !(phi1 <= 9e-16)) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_0, cos(phi1), (sin(Float64(phi1 * 0.5)) ^ 2.0))), sqrt(Float64(Float64(1.0 - (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0)) - Float64(Float64(cos(phi1) * cos(phi2)) * Float64(0.5 + Float64(-0.5 * cos(lambda2))))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_0, cos(phi2), (sin(Float64(phi2 * -0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) - Float64(cos(phi2) * t_0)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[phi1, -0.225], N[Not[LessEqual[phi1, 9e-16]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] - N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(0.5 + N[(-0.5 * N[Cos[lambda2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
\mathbf{if}\;\phi_1 \leq -0.225 \lor \neg \left(\phi_1 \leq 9 \cdot 10^{-16}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t_0, \cos \phi_1, {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}{\sqrt{\left(1 - {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right) - \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(0.5 + -0.5 \cdot \cos \lambda_2\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t_0, \cos \phi_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 t_0}}\right)\\
\end{array}
\end{array}
if phi1 < -0.225000000000000006 or 9.0000000000000003e-16 < phi1 Initial program 44.5%
associate-*l*44.5%
Simplified44.5%
add-log-exp44.5%
sqr-sin-a44.6%
cos-244.5%
cos-sum44.6%
add-log-exp20.4%
add-log-exp20.4%
sum-log20.4%
exp-sqrt20.4%
exp-sqrt20.4%
add-sqr-sqrt20.4%
add-log-exp44.6%
Applied egg-rr44.6%
Taylor expanded in lambda1 around 0 40.5%
cancel-sign-sub-inv40.5%
metadata-eval40.5%
cos-neg40.5%
Simplified40.5%
Taylor expanded in phi2 around 0 40.9%
*-commutative40.9%
fma-def40.9%
Simplified40.9%
if -0.225000000000000006 < phi1 < 9.0000000000000003e-16Initial program 78.7%
Taylor expanded in phi1 around 0 78.7%
+-commutative78.7%
associate--r+78.7%
unpow278.7%
1-sub-sin78.8%
unpow278.8%
*-commutative78.8%
Simplified78.8%
Taylor expanded in phi1 around 0 77.2%
*-commutative77.2%
fma-def77.2%
Simplified77.2%
Final simplification58.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_1 (pow (sin (* phi1 0.5)) 2.0)))
(if (<= phi1 -2.7e-5)
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)
(* (cos phi1) (* (cos phi2) (pow (sin (* lambda1 0.5)) 2.0)))))
(sqrt (- 1.0 (+ (* (cos phi1) t_0) t_1))))))
(if (<= phi1 6.2e-16)
(*
R
(*
2.0
(atan2
(sqrt (fma t_0 (cos phi2) (pow (sin (* phi2 -0.5)) 2.0)))
(sqrt (- (pow (cos (* phi2 -0.5)) 2.0) (* (cos phi2) t_0))))))
(*
R
(*
2.0
(atan2
(sqrt (fma t_0 (cos phi1) t_1))
(sqrt
(-
(- 1.0 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))
(*
(* (cos phi1) (cos phi2))
(+ 0.5 (* -0.5 (cos lambda2)))))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_1 = pow(sin((phi1 * 0.5)), 2.0);
double tmp;
if (phi1 <= -2.7e-5) {
tmp = R * (2.0 * atan2(sqrt((pow(sin((0.5 * (phi1 - phi2))), 2.0) + (cos(phi1) * (cos(phi2) * pow(sin((lambda1 * 0.5)), 2.0))))), sqrt((1.0 - ((cos(phi1) * t_0) + t_1)))));
} else if (phi1 <= 6.2e-16) {
tmp = R * (2.0 * atan2(sqrt(fma(t_0, cos(phi2), pow(sin((phi2 * -0.5)), 2.0))), sqrt((pow(cos((phi2 * -0.5)), 2.0) - (cos(phi2) * t_0)))));
} else {
tmp = R * (2.0 * atan2(sqrt(fma(t_0, cos(phi1), t_1)), sqrt(((1.0 - pow(sin(((phi1 - phi2) / 2.0)), 2.0)) - ((cos(phi1) * cos(phi2)) * (0.5 + (-0.5 * cos(lambda2))))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_1 = sin(Float64(phi1 * 0.5)) ^ 2.0 tmp = 0.0 if (phi1 <= -2.7e-5) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0) + Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(lambda1 * 0.5)) ^ 2.0))))), sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * t_0) + t_1)))))); elseif (phi1 <= 6.2e-16) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_0, cos(phi2), (sin(Float64(phi2 * -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(t_0, cos(phi1), t_1)), sqrt(Float64(Float64(1.0 - (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0)) - Float64(Float64(cos(phi1) * cos(phi2)) * Float64(0.5 + Float64(-0.5 * cos(lambda2))))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[LessEqual[phi1, -2.7e-5], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision] + t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[phi1, 6.2e-16], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 * N[Cos[phi1], $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] - N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(0.5 + N[(-0.5 * N[Cos[lambda2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_1 := {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\\
\mathbf{if}\;\phi_1 \leq -2.7 \cdot 10^{-5}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2} + \cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(\lambda_1 \cdot 0.5\right)}^{2}\right)}}{\sqrt{1 - \left(\cos \phi_1 \cdot t_0 + t_1\right)}}\right)\\
\mathbf{elif}\;\phi_1 \leq 6.2 \cdot 10^{-16}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t_0, \cos \phi_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 t_0}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t_0, \cos \phi_1, t_1\right)}}{\sqrt{\left(1 - {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right) - \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(0.5 + -0.5 \cdot \cos \lambda_2\right)}}\right)\\
\end{array}
\end{array}
if phi1 < -2.6999999999999999e-5Initial program 49.4%
associate-*l*49.5%
Simplified49.5%
div-sub49.5%
sin-diff51.7%
Applied egg-rr51.7%
Taylor expanded in lambda2 around 0 45.1%
Taylor expanded in phi2 around 0 44.3%
if -2.6999999999999999e-5 < phi1 < 6.2000000000000002e-16Initial program 79.2%
Taylor expanded in phi1 around 0 79.2%
+-commutative79.2%
associate--r+79.2%
unpow279.2%
1-sub-sin79.3%
unpow279.3%
*-commutative79.3%
Simplified79.3%
Taylor expanded in phi1 around 0 77.7%
*-commutative77.7%
fma-def77.7%
Simplified77.7%
if 6.2000000000000002e-16 < phi1 Initial program 40.8%
associate-*l*40.8%
Simplified40.8%
add-log-exp40.8%
sqr-sin-a40.8%
cos-240.8%
cos-sum40.8%
add-log-exp18.2%
add-log-exp18.2%
sum-log18.2%
exp-sqrt18.2%
exp-sqrt18.2%
add-sqr-sqrt18.2%
add-log-exp40.8%
Applied egg-rr40.8%
Taylor expanded in lambda1 around 0 38.2%
cancel-sign-sub-inv38.2%
metadata-eval38.2%
cos-neg38.2%
Simplified38.2%
Taylor expanded in phi2 around 0 38.3%
*-commutative38.3%
fma-def38.3%
Simplified38.3%
Final simplification58.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
(if (or (<= phi1 -0.225) (not (<= phi1 9e-16)))
(*
R
(*
2.0
(atan2
(sqrt (+ (* (cos phi1) t_0) (pow (sin (* phi1 0.5)) 2.0)))
(sqrt
(-
(- 1.0 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))
(* (* (cos phi1) (cos phi2)) (+ 0.5 (* -0.5 (cos lambda2)))))))))
(*
R
(*
2.0
(atan2
(sqrt (fma t_0 (cos phi2) (pow (sin (* phi2 -0.5)) 2.0)))
(sqrt (- (pow (cos (* phi2 -0.5)) 2.0) (* (cos phi2) t_0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double tmp;
if ((phi1 <= -0.225) || !(phi1 <= 9e-16)) {
tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * t_0) + pow(sin((phi1 * 0.5)), 2.0))), sqrt(((1.0 - pow(sin(((phi1 - phi2) / 2.0)), 2.0)) - ((cos(phi1) * cos(phi2)) * (0.5 + (-0.5 * cos(lambda2))))))));
} else {
tmp = R * (2.0 * atan2(sqrt(fma(t_0, cos(phi2), pow(sin((phi2 * -0.5)), 2.0))), sqrt((pow(cos((phi2 * -0.5)), 2.0) - (cos(phi2) * t_0)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 tmp = 0.0 if ((phi1 <= -0.225) || !(phi1 <= 9e-16)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi1) * t_0) + (sin(Float64(phi1 * 0.5)) ^ 2.0))), sqrt(Float64(Float64(1.0 - (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0)) - Float64(Float64(cos(phi1) * cos(phi2)) * Float64(0.5 + Float64(-0.5 * cos(lambda2))))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_0, cos(phi2), (sin(Float64(phi2 * -0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) - Float64(cos(phi2) * t_0)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[phi1, -0.225], N[Not[LessEqual[phi1, 9e-16]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] - N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(0.5 + N[(-0.5 * N[Cos[lambda2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
\mathbf{if}\;\phi_1 \leq -0.225 \lor \neg \left(\phi_1 \leq 9 \cdot 10^{-16}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_1 \cdot t_0 + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}}}{\sqrt{\left(1 - {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right) - \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(0.5 + -0.5 \cdot \cos \lambda_2\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t_0, \cos \phi_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 t_0}}\right)\\
\end{array}
\end{array}
if phi1 < -0.225000000000000006 or 9.0000000000000003e-16 < phi1 Initial program 44.5%
associate-*l*44.5%
Simplified44.5%
add-log-exp44.5%
sqr-sin-a44.6%
cos-244.5%
cos-sum44.6%
add-log-exp20.4%
add-log-exp20.4%
sum-log20.4%
exp-sqrt20.4%
exp-sqrt20.4%
add-sqr-sqrt20.4%
add-log-exp44.6%
Applied egg-rr44.6%
Taylor expanded in lambda1 around 0 40.5%
cancel-sign-sub-inv40.5%
metadata-eval40.5%
cos-neg40.5%
Simplified40.5%
Taylor expanded in phi2 around 0 40.9%
if -0.225000000000000006 < phi1 < 9.0000000000000003e-16Initial program 78.7%
Taylor expanded in phi1 around 0 78.7%
+-commutative78.7%
associate--r+78.7%
unpow278.7%
1-sub-sin78.8%
unpow278.8%
*-commutative78.8%
Simplified78.8%
Taylor expanded in phi1 around 0 77.2%
*-commutative77.2%
fma-def77.2%
Simplified77.2%
Final simplification58.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_1 (* (cos phi2) t_0)))
(if (or (<= phi1 -0.225) (not (<= phi1 9e-16)))
(*
R
(*
2.0
(atan2
(sqrt (+ (* (cos phi1) t_0) (pow (sin (* phi1 0.5)) 2.0)))
(sqrt
(-
(- 1.0 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))
(* (* (cos phi1) (cos phi2)) (+ 0.5 (* -0.5 (cos lambda2)))))))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (pow (sin (* phi2 -0.5)) 2.0)))
(sqrt (- (pow (cos (* phi2 -0.5)) 2.0) t_1))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_1 = cos(phi2) * t_0;
double tmp;
if ((phi1 <= -0.225) || !(phi1 <= 9e-16)) {
tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * t_0) + pow(sin((phi1 * 0.5)), 2.0))), sqrt(((1.0 - pow(sin(((phi1 - phi2) / 2.0)), 2.0)) - ((cos(phi1) * cos(phi2)) * (0.5 + (-0.5 * cos(lambda2))))))));
} else {
tmp = R * (2.0 * atan2(sqrt((t_1 + pow(sin((phi2 * -0.5)), 2.0))), sqrt((pow(cos((phi2 * -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(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0
t_1 = cos(phi2) * t_0
if ((phi1 <= (-0.225d0)) .or. (.not. (phi1 <= 9d-16))) then
tmp = r * (2.0d0 * atan2(sqrt(((cos(phi1) * t_0) + (sin((phi1 * 0.5d0)) ** 2.0d0))), sqrt(((1.0d0 - (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0)) - ((cos(phi1) * cos(phi2)) * (0.5d0 + ((-0.5d0) * cos(lambda2))))))))
else
tmp = r * (2.0d0 * atan2(sqrt((t_1 + (sin((phi2 * (-0.5d0))) ** 2.0d0))), sqrt(((cos((phi2 * (-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(((lambda1 - lambda2) * 0.5)), 2.0);
double t_1 = Math.cos(phi2) * t_0;
double tmp;
if ((phi1 <= -0.225) || !(phi1 <= 9e-16)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi1) * t_0) + Math.pow(Math.sin((phi1 * 0.5)), 2.0))), Math.sqrt(((1.0 - Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0)) - ((Math.cos(phi1) * Math.cos(phi2)) * (0.5 + (-0.5 * Math.cos(lambda2))))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_1 + Math.pow(Math.sin((phi2 * -0.5)), 2.0))), Math.sqrt((Math.pow(Math.cos((phi2 * -0.5)), 2.0) - t_1))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0) t_1 = math.cos(phi2) * t_0 tmp = 0 if (phi1 <= -0.225) or not (phi1 <= 9e-16): tmp = R * (2.0 * math.atan2(math.sqrt(((math.cos(phi1) * t_0) + math.pow(math.sin((phi1 * 0.5)), 2.0))), math.sqrt(((1.0 - math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0)) - ((math.cos(phi1) * math.cos(phi2)) * (0.5 + (-0.5 * math.cos(lambda2)))))))) else: tmp = R * (2.0 * math.atan2(math.sqrt((t_1 + math.pow(math.sin((phi2 * -0.5)), 2.0))), math.sqrt((math.pow(math.cos((phi2 * -0.5)), 2.0) - t_1)))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_1 = Float64(cos(phi2) * t_0) tmp = 0.0 if ((phi1 <= -0.225) || !(phi1 <= 9e-16)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi1) * t_0) + (sin(Float64(phi1 * 0.5)) ^ 2.0))), sqrt(Float64(Float64(1.0 - (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0)) - Float64(Float64(cos(phi1) * cos(phi2)) * Float64(0.5 + Float64(-0.5 * cos(lambda2))))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + (sin(Float64(phi2 * -0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) - t_1))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) * 0.5)) ^ 2.0; t_1 = cos(phi2) * t_0; tmp = 0.0; if ((phi1 <= -0.225) || ~((phi1 <= 9e-16))) tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * t_0) + (sin((phi1 * 0.5)) ^ 2.0))), sqrt(((1.0 - (sin(((phi1 - phi2) / 2.0)) ^ 2.0)) - ((cos(phi1) * cos(phi2)) * (0.5 + (-0.5 * cos(lambda2)))))))); else tmp = R * (2.0 * atan2(sqrt((t_1 + (sin((phi2 * -0.5)) ^ 2.0))), sqrt(((cos((phi2 * -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[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision]}, If[Or[LessEqual[phi1, -0.225], N[Not[LessEqual[phi1, 9e-16]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] - N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(0.5 + N[(-0.5 * N[Cos[lambda2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -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(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_1 := \cos \phi_2 \cdot t_0\\
\mathbf{if}\;\phi_1 \leq -0.225 \lor \neg \left(\phi_1 \leq 9 \cdot 10^{-16}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_1 \cdot t_0 + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}}}{\sqrt{\left(1 - {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right) - \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(0.5 + -0.5 \cdot \cos \lambda_2\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t_1 + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}}}{\sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} - t_1}}\right)\\
\end{array}
\end{array}
if phi1 < -0.225000000000000006 or 9.0000000000000003e-16 < phi1 Initial program 44.5%
associate-*l*44.5%
Simplified44.5%
add-log-exp44.5%
sqr-sin-a44.6%
cos-244.5%
cos-sum44.6%
add-log-exp20.4%
add-log-exp20.4%
sum-log20.4%
exp-sqrt20.4%
exp-sqrt20.4%
add-sqr-sqrt20.4%
add-log-exp44.6%
Applied egg-rr44.6%
Taylor expanded in lambda1 around 0 40.5%
cancel-sign-sub-inv40.5%
metadata-eval40.5%
cos-neg40.5%
Simplified40.5%
Taylor expanded in phi2 around 0 40.9%
if -0.225000000000000006 < phi1 < 9.0000000000000003e-16Initial program 78.7%
Taylor expanded in phi1 around 0 78.7%
+-commutative78.7%
associate--r+78.7%
unpow278.7%
1-sub-sin78.8%
unpow278.8%
*-commutative78.8%
Simplified78.8%
Taylor expanded in phi1 around 0 77.2%
Final simplification58.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
(*
R
(*
2.0
(atan2
(sqrt (+ (* (cos phi1) t_0) (pow (sin (* phi1 0.5)) 2.0)))
(sqrt (- (pow (cos (* phi2 -0.5)) 2.0) (* (cos phi2) t_0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
return R * (2.0 * atan2(sqrt(((cos(phi1) * t_0) + pow(sin((phi1 * 0.5)), 2.0))), sqrt((pow(cos((phi2 * -0.5)), 2.0) - (cos(phi2) * t_0)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0
code = r * (2.0d0 * atan2(sqrt(((cos(phi1) * t_0) + (sin((phi1 * 0.5d0)) ** 2.0d0))), sqrt(((cos((phi2 * (-0.5d0))) ** 2.0d0) - (cos(phi2) * t_0)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0);
return R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi1) * t_0) + Math.pow(Math.sin((phi1 * 0.5)), 2.0))), Math.sqrt((Math.pow(Math.cos((phi2 * -0.5)), 2.0) - (Math.cos(phi2) * t_0)))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0) return R * (2.0 * math.atan2(math.sqrt(((math.cos(phi1) * t_0) + math.pow(math.sin((phi1 * 0.5)), 2.0))), math.sqrt((math.pow(math.cos((phi2 * -0.5)), 2.0) - (math.cos(phi2) * t_0)))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi1) * t_0) + (sin(Float64(phi1 * 0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) - Float64(cos(phi2) * t_0)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) * 0.5)) ^ 2.0; tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * t_0) + (sin((phi1 * 0.5)) ^ 2.0))), sqrt(((cos((phi2 * -0.5)) ^ 2.0) - (cos(phi2) * t_0))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / 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]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_1 \cdot t_0 + {\sin \left(\phi_1 \cdot 0.5\right)}^{2}}}{\sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} - \cos \phi_2 \cdot t_0}}\right)
\end{array}
\end{array}
Initial program 60.7%
Taylor expanded in phi1 around 0 49.0%
+-commutative49.0%
associate--r+49.0%
unpow249.0%
1-sub-sin49.0%
unpow249.0%
*-commutative49.0%
Simplified49.0%
Taylor expanded in phi2 around 0 34.1%
Final simplification34.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi2) (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_0 (pow (sin (* phi2 -0.5)) 2.0)))
(sqrt (- (pow (cos (* phi2 -0.5)) 2.0) t_0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi2) * pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
return R * (2.0 * atan2(sqrt((t_0 + pow(sin((phi2 * -0.5)), 2.0))), sqrt((pow(cos((phi2 * -0.5)), 2.0) - t_0))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = cos(phi2) * (sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0)
code = r * (2.0d0 * atan2(sqrt((t_0 + (sin((phi2 * (-0.5d0))) ** 2.0d0))), sqrt(((cos((phi2 * (-0.5d0))) ** 2.0d0) - t_0))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.cos(phi2) * Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0);
return R * (2.0 * Math.atan2(Math.sqrt((t_0 + Math.pow(Math.sin((phi2 * -0.5)), 2.0))), Math.sqrt((Math.pow(Math.cos((phi2 * -0.5)), 2.0) - t_0))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi2) * math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0) return R * (2.0 * math.atan2(math.sqrt((t_0 + math.pow(math.sin((phi2 * -0.5)), 2.0))), math.sqrt((math.pow(math.cos((phi2 * -0.5)), 2.0) - t_0))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi2) * (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_0 + (sin(Float64(phi2 * -0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(phi2 * -0.5)) ^ 2.0) - t_0))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi2) * (sin(((lambda1 - lambda2) * 0.5)) ^ 2.0); tmp = R * (2.0 * atan2(sqrt((t_0 + (sin((phi2 * -0.5)) ^ 2.0))), sqrt(((cos((phi2 * -0.5)) ^ 2.0) - t_0)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_2 \cdot {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t_0 + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}}}{\sqrt{{\cos \left(\phi_2 \cdot -0.5\right)}^{2} - t_0}}\right)
\end{array}
\end{array}
Initial program 60.7%
Taylor expanded in phi1 around 0 49.0%
+-commutative49.0%
associate--r+49.0%
unpow249.0%
1-sub-sin49.0%
unpow249.0%
*-commutative49.0%
Simplified49.0%
Taylor expanded in phi1 around 0 46.3%
Final simplification46.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(sin (* (- lambda1 lambda2) 0.5))
(sqrt
(-
(- 1.0 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))
(*
(* (cos phi1) (cos phi2))
(log (exp (- 0.5 (* (cos (- lambda1 lambda2)) 0.5)))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2(sin(((lambda1 - lambda2) * 0.5)), sqrt(((1.0 - pow(sin(((phi1 - phi2) / 2.0)), 2.0)) - ((cos(phi1) * cos(phi2)) * log(exp((0.5 - (cos((lambda1 - lambda2)) * 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(((lambda1 - lambda2) * 0.5d0)), sqrt(((1.0d0 - (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0)) - ((cos(phi1) * cos(phi2)) * log(exp((0.5d0 - (cos((lambda1 - lambda2)) * 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(((lambda1 - lambda2) * 0.5)), Math.sqrt(((1.0 - Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0)) - ((Math.cos(phi1) * Math.cos(phi2)) * Math.log(Math.exp((0.5 - (Math.cos((lambda1 - lambda2)) * 0.5)))))))));
}
def code(R, lambda1, lambda2, phi1, phi2): return R * (2.0 * math.atan2(math.sin(((lambda1 - lambda2) * 0.5)), math.sqrt(((1.0 - math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0)) - ((math.cos(phi1) * math.cos(phi2)) * math.log(math.exp((0.5 - (math.cos((lambda1 - lambda2)) * 0.5)))))))))
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(sin(Float64(Float64(lambda1 - lambda2) * 0.5)), sqrt(Float64(Float64(1.0 - (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0)) - Float64(Float64(cos(phi1) * cos(phi2)) * log(exp(Float64(0.5 - Float64(cos(Float64(lambda1 - lambda2)) * 0.5)))))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) tmp = R * (2.0 * atan2(sin(((lambda1 - lambda2) * 0.5)), sqrt(((1.0 - (sin(((phi1 - phi2) / 2.0)) ^ 2.0)) - ((cos(phi1) * cos(phi2)) * log(exp((0.5 - (cos((lambda1 - lambda2)) * 0.5))))))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] - N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[Log[N[Exp[N[(0.5 - N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] * 0.5), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}{\sqrt{\left(1 - {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right) - \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \log \left(e^{0.5 - \cos \left(\lambda_1 - \lambda_2\right) \cdot 0.5}\right)}}\right)
\end{array}
Initial program 60.7%
associate-*l*60.7%
Simplified60.7%
add-log-exp60.7%
sqr-sin-a60.7%
cos-260.7%
cos-sum60.7%
add-log-exp23.2%
add-log-exp23.2%
sum-log23.2%
exp-sqrt23.2%
exp-sqrt23.2%
add-sqr-sqrt23.2%
add-log-exp60.7%
Applied egg-rr60.7%
Taylor expanded in phi1 around 0 45.9%
Taylor expanded in phi2 around 0 17.1%
Final simplification17.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (- lambda1 lambda2) 0.5)))
(*
R
(*
2.0
(atan2
(* (sin t_0) (sqrt (cos phi1)))
(sqrt
(+
1.0
(-
(* (cos phi2) (- (/ (cos (* 2.0 t_0)) 2.0) 0.5))
(pow (sin (* phi2 -0.5)) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = (lambda1 - lambda2) * 0.5;
return R * (2.0 * atan2((sin(t_0) * sqrt(cos(phi1))), sqrt((1.0 + ((cos(phi2) * ((cos((2.0 * t_0)) / 2.0) - 0.5)) - pow(sin((phi2 * -0.5)), 2.0))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = (lambda1 - lambda2) * 0.5d0
code = r * (2.0d0 * atan2((sin(t_0) * sqrt(cos(phi1))), sqrt((1.0d0 + ((cos(phi2) * ((cos((2.0d0 * t_0)) / 2.0d0) - 0.5d0)) - (sin((phi2 * (-0.5d0))) ** 2.0d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = (lambda1 - lambda2) * 0.5;
return R * (2.0 * Math.atan2((Math.sin(t_0) * Math.sqrt(Math.cos(phi1))), Math.sqrt((1.0 + ((Math.cos(phi2) * ((Math.cos((2.0 * t_0)) / 2.0) - 0.5)) - Math.pow(Math.sin((phi2 * -0.5)), 2.0))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = (lambda1 - lambda2) * 0.5 return R * (2.0 * math.atan2((math.sin(t_0) * math.sqrt(math.cos(phi1))), math.sqrt((1.0 + ((math.cos(phi2) * ((math.cos((2.0 * t_0)) / 2.0) - 0.5)) - math.pow(math.sin((phi2 * -0.5)), 2.0))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(Float64(lambda1 - lambda2) * 0.5) return Float64(R * Float64(2.0 * atan(Float64(sin(t_0) * sqrt(cos(phi1))), sqrt(Float64(1.0 + Float64(Float64(cos(phi2) * Float64(Float64(cos(Float64(2.0 * t_0)) / 2.0) - 0.5)) - (sin(Float64(phi2 * -0.5)) ^ 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = (lambda1 - lambda2) * 0.5; tmp = R * (2.0 * atan2((sin(t_0) * sqrt(cos(phi1))), sqrt((1.0 + ((cos(phi2) * ((cos((2.0 * t_0)) / 2.0) - 0.5)) - (sin((phi2 * -0.5)) ^ 2.0)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[(N[Sin[t$95$0], $MachinePrecision] * N[Sqrt[N[Cos[phi1], $MachinePrecision]], $MachinePrecision]), $MachinePrecision] / N[Sqrt[N[(1.0 + N[(N[(N[Cos[phi2], $MachinePrecision] * N[(N[(N[Cos[N[(2.0 * t$95$0), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision] - N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \left(\lambda_1 - \lambda_2\right) \cdot 0.5\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sin t_0 \cdot \sqrt{\cos \phi_1}}{\sqrt{1 + \left(\cos \phi_2 \cdot \left(\frac{\cos \left(2 \cdot t_0\right)}{2} - 0.5\right) - {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 60.7%
associate-*l*60.7%
Simplified60.7%
Taylor expanded in phi1 around 0 43.6%
Taylor expanded in phi2 around 0 15.2%
Taylor expanded in phi1 around 0 15.2%
*-commutative15.2%
metadata-eval15.2%
div-inv15.2%
pow215.2%
sin-mult15.3%
Applied egg-rr15.3%
div-sub15.3%
+-inverses15.3%
cos-015.3%
metadata-eval15.3%
*-commutative15.3%
Simplified15.3%
Final simplification15.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* (- lambda1 lambda2) 0.5))))
(*
R
(* 2.0 (atan2 (* t_0 (sqrt (cos phi1))) (sqrt (- 1.0 (pow t_0 2.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) * 0.5));
return R * (2.0 * atan2((t_0 * sqrt(cos(phi1))), sqrt((1.0 - pow(t_0, 2.0)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin(((lambda1 - lambda2) * 0.5d0))
code = r * (2.0d0 * atan2((t_0 * sqrt(cos(phi1))), sqrt((1.0d0 - (t_0 ** 2.0d0)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) * 0.5));
return R * (2.0 * Math.atan2((t_0 * Math.sqrt(Math.cos(phi1))), Math.sqrt((1.0 - Math.pow(t_0, 2.0)))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) * 0.5)) return R * (2.0 * math.atan2((t_0 * math.sqrt(math.cos(phi1))), math.sqrt((1.0 - math.pow(t_0, 2.0)))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) return Float64(R * Float64(2.0 * atan(Float64(t_0 * sqrt(cos(phi1))), sqrt(Float64(1.0 - (t_0 ^ 2.0)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) * 0.5)); tmp = R * (2.0 * atan2((t_0 * sqrt(cos(phi1))), sqrt((1.0 - (t_0 ^ 2.0))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[(t$95$0 * N[Sqrt[N[Cos[phi1], $MachinePrecision]], $MachinePrecision]), $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[t$95$0, 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{t_0 \cdot \sqrt{\cos \phi_1}}{\sqrt{1 - {t_0}^{2}}}\right)
\end{array}
\end{array}
Initial program 60.7%
associate-*l*60.7%
Simplified60.7%
Taylor expanded in phi1 around 0 43.6%
Taylor expanded in phi2 around 0 15.2%
Taylor expanded in phi1 around 0 15.2%
Taylor expanded in phi2 around 0 15.1%
Final simplification15.1%
herbie shell --seed 2024020
(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))))))))))