
(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 30 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_0) t_0))))
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0);
return R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0)
code = r * (2.0d0 * atan2(sqrt(t_1), sqrt((1.0d0 - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((Math.cos(phi1) * Math.cos(phi2)) * t_0) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt(t_1), Math.sqrt((1.0 - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((math.cos(phi1) * math.cos(phi2)) * t_0) * t_0) return R * (2.0 * math.atan2(math.sqrt(t_1), math.sqrt((1.0 - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0); tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$1], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) \cdot t\_0\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)
\end{array}
\end{array}
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (* phi1 0.5)))
(t_2 (cos (* phi1 0.5)))
(t_3 (sin (/ (- lambda1 lambda2) 2.0)))
(t_4 (cos (* 0.5 phi2))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (- (* t_4 t_1) (* (sin (* 0.5 phi2)) t_2)) 2.0)
(* t_3 (* (log (exp t_0)) t_3))))
(sqrt
(-
1.0
(+
(pow (fma t_4 t_1 (* (sin (* phi2 -0.5)) t_2)) 2.0)
(* t_3 (* t_0 t_3))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = sin((phi1 * 0.5));
double t_2 = cos((phi1 * 0.5));
double t_3 = sin(((lambda1 - lambda2) / 2.0));
double t_4 = cos((0.5 * phi2));
return R * (2.0 * atan2(sqrt((pow(((t_4 * t_1) - (sin((0.5 * phi2)) * t_2)), 2.0) + (t_3 * (log(exp(t_0)) * t_3)))), sqrt((1.0 - (pow(fma(t_4, t_1, (sin((phi2 * -0.5)) * t_2)), 2.0) + (t_3 * (t_0 * t_3)))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(phi1 * 0.5)) t_2 = cos(Float64(phi1 * 0.5)) t_3 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_4 = cos(Float64(0.5 * phi2)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((Float64(Float64(t_4 * t_1) - Float64(sin(Float64(0.5 * phi2)) * t_2)) ^ 2.0) + Float64(t_3 * Float64(log(exp(t_0)) * t_3)))), sqrt(Float64(1.0 - Float64((fma(t_4, t_1, Float64(sin(Float64(phi2 * -0.5)) * t_2)) ^ 2.0) + Float64(t_3 * Float64(t_0 * t_3)))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, 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$1), $MachinePrecision] - N[(N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$3 * N[(N[Log[N[Exp[t$95$0], $MachinePrecision]], $MachinePrecision] * t$95$3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[(t$95$4 * t$95$1 + N[(N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$3 * N[(t$95$0 * t$95$3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_2 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_3 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_4 := \cos \left(0.5 \cdot \phi_2\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(t\_4 \cdot t\_1 - \sin \left(0.5 \cdot \phi_2\right) \cdot t\_2\right)}^{2} + t\_3 \cdot \left(\log \left(e^{t\_0}\right) \cdot t\_3\right)}}{\sqrt{1 - \left({\left(\mathsf{fma}\left(t\_4, t\_1, \sin \left(\phi_2 \cdot -0.5\right) \cdot t\_2\right)\right)}^{2} + t\_3 \cdot \left(t\_0 \cdot t\_3\right)\right)}}\right)
\end{array}
\end{array}
Initial program 57.8%
div-sub57.8%
sin-diff59.2%
div-inv59.2%
metadata-eval59.2%
div-inv59.2%
metadata-eval59.2%
div-inv59.2%
metadata-eval59.2%
div-inv59.2%
metadata-eval59.2%
Applied egg-rr59.2%
div-sub57.8%
sin-diff59.2%
div-inv59.2%
metadata-eval59.2%
div-inv59.2%
metadata-eval59.2%
div-inv59.2%
metadata-eval59.2%
div-inv59.2%
metadata-eval59.2%
Applied egg-rr76.9%
*-commutative76.9%
*-commutative76.9%
fmm-def76.9%
*-commutative76.9%
*-commutative76.9%
*-commutative76.9%
distribute-lft-neg-in76.9%
sin-neg76.9%
distribute-rgt-neg-in76.9%
metadata-eval76.9%
*-commutative76.9%
*-commutative76.9%
Simplified76.9%
add-log-exp77.0%
Applied egg-rr77.0%
Final simplification77.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* phi1 0.5)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (* t_1 (* (* (cos phi1) (cos phi2)) t_1)))
(t_3 (+ t_2 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(t_4 (sqrt t_3)))
(if (<= (* R (* 2.0 (atan2 t_4 (sqrt (- 1.0 t_3))))) 5e+304)
(*
R
(*
2.0
(atan2
t_4
(sqrt (- 1.0 (+ t_2 (cbrt (pow (sin (* 0.5 (- phi1 phi2))) 6.0))))))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow
(-
(* (cos (* 0.5 phi2)) t_0)
(* (sin (* 0.5 phi2)) (cos (* phi1 0.5))))
2.0)
t_2))
(sqrt
(-
1.0
(+
(pow t_0 2.0)
(* (cos phi1) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((phi1 * 0.5));
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = t_1 * ((cos(phi1) * cos(phi2)) * t_1);
double t_3 = t_2 + pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double t_4 = sqrt(t_3);
double tmp;
if ((R * (2.0 * atan2(t_4, sqrt((1.0 - t_3))))) <= 5e+304) {
tmp = R * (2.0 * atan2(t_4, sqrt((1.0 - (t_2 + cbrt(pow(sin((0.5 * (phi1 - phi2))), 6.0)))))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(((cos((0.5 * phi2)) * t_0) - (sin((0.5 * phi2)) * cos((phi1 * 0.5)))), 2.0) + t_2)), sqrt((1.0 - (pow(t_0, 2.0) + (cos(phi1) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0)))))));
}
return tmp;
}
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin((phi1 * 0.5));
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_2 = t_1 * ((Math.cos(phi1) * Math.cos(phi2)) * t_1);
double t_3 = t_2 + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0);
double t_4 = Math.sqrt(t_3);
double tmp;
if ((R * (2.0 * Math.atan2(t_4, Math.sqrt((1.0 - t_3))))) <= 5e+304) {
tmp = R * (2.0 * Math.atan2(t_4, Math.sqrt((1.0 - (t_2 + Math.cbrt(Math.pow(Math.sin((0.5 * (phi1 - phi2))), 6.0)))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((Math.pow(((Math.cos((0.5 * phi2)) * t_0) - (Math.sin((0.5 * phi2)) * Math.cos((phi1 * 0.5)))), 2.0) + t_2)), Math.sqrt((1.0 - (Math.pow(t_0, 2.0) + (Math.cos(phi1) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi1 * 0.5)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(t_1 * Float64(Float64(cos(phi1) * cos(phi2)) * t_1)) t_3 = Float64(t_2 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0)) t_4 = sqrt(t_3) tmp = 0.0 if (Float64(R * Float64(2.0 * atan(t_4, sqrt(Float64(1.0 - t_3))))) <= 5e+304) tmp = Float64(R * Float64(2.0 * atan(t_4, sqrt(Float64(1.0 - Float64(t_2 + cbrt((sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 6.0)))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((Float64(Float64(cos(Float64(0.5 * phi2)) * t_0) - Float64(sin(Float64(0.5 * phi2)) * cos(Float64(phi1 * 0.5)))) ^ 2.0) + t_2)), sqrt(Float64(1.0 - Float64((t_0 ^ 2.0) + Float64(cos(phi1) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(t$95$1 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(t$95$2 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[Sqrt[t$95$3], $MachinePrecision]}, If[LessEqual[N[(R * N[(2.0 * N[ArcTan[t$95$4 / N[Sqrt[N[(1.0 - t$95$3), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 5e+304], N[(R * N[(2.0 * N[ArcTan[t$95$4 / N[Sqrt[N[(1.0 - N[(t$95$2 + N[Power[N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 6.0], $MachinePrecision], 1/3], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision] - N[(N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$2), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[t$95$0, 2.0], $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := t\_1 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_1\right)\\
t_3 := t\_2 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
t_4 := \sqrt{t\_3}\\
\mathbf{if}\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_4}{\sqrt{1 - t\_3}}\right) \leq 5 \cdot 10^{+304}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_4}{\sqrt{1 - \left(t\_2 + \sqrt[3]{{\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{6}}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\cos \left(0.5 \cdot \phi_2\right) \cdot t\_0 - \sin \left(0.5 \cdot \phi_2\right) \cdot \cos \left(\phi_1 \cdot 0.5\right)\right)}^{2} + t\_2}}{\sqrt{1 - \left({t\_0}^{2} + \cos \phi_1 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\right)}}\right)\\
\end{array}
\end{array}
if (*.f64 R (*.f64 #s(literal 2 binary64) (atan2.f64 (sqrt.f64 (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))))) (sqrt.f64 (-.f64 #s(literal 1 binary64) (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))))))))) < 4.9999999999999997e304Initial program 62.7%
add-cbrt-cube62.7%
pow362.7%
pow-pow62.7%
div-inv62.7%
metadata-eval62.7%
metadata-eval62.7%
Applied egg-rr62.7%
if 4.9999999999999997e304 < (*.f64 R (*.f64 #s(literal 2 binary64) (atan2.f64 (sqrt.f64 (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))))) (sqrt.f64 (-.f64 #s(literal 1 binary64) (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))))))))) Initial program 3.0%
div-sub3.0%
sin-diff13.6%
div-inv13.6%
metadata-eval13.6%
div-inv13.6%
metadata-eval13.6%
div-inv13.6%
metadata-eval13.6%
div-inv13.6%
metadata-eval13.6%
Applied egg-rr13.6%
Taylor expanded in phi2 around 0 22.8%
Final simplification59.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* t_0 (* (* (cos phi1) (cos phi2)) t_0)))
(t_2 (+ t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(t_3 (sqrt t_2)))
(if (<= (atan2 t_3 (sqrt (- 1.0 t_2))) 1.5)
(*
R
(*
2.0
(atan2
t_3
(sqrt (- 1.0 (+ t_1 (cbrt (pow (sin (* 0.5 (- phi1 phi2))) 6.0))))))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow
(-
(* (cos (* 0.5 phi2)) (sin (* phi1 0.5)))
(* (sin (* 0.5 phi2)) (cos (* phi1 0.5))))
2.0)
t_1))
(sqrt
(-
1.0
(+
(* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(pow (sin (* phi2 -0.5)) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = t_0 * ((cos(phi1) * cos(phi2)) * t_0);
double t_2 = t_1 + pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double t_3 = sqrt(t_2);
double tmp;
if (atan2(t_3, sqrt((1.0 - t_2))) <= 1.5) {
tmp = R * (2.0 * atan2(t_3, sqrt((1.0 - (t_1 + cbrt(pow(sin((0.5 * (phi1 - phi2))), 6.0)))))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (sin((0.5 * phi2)) * cos((phi1 * 0.5)))), 2.0) + t_1)), sqrt((1.0 - ((cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0)) + pow(sin((phi2 * -0.5)), 2.0))))));
}
return tmp;
}
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0);
double t_2 = t_1 + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0);
double t_3 = Math.sqrt(t_2);
double tmp;
if (Math.atan2(t_3, Math.sqrt((1.0 - t_2))) <= 1.5) {
tmp = R * (2.0 * Math.atan2(t_3, Math.sqrt((1.0 - (t_1 + Math.cbrt(Math.pow(Math.sin((0.5 * (phi1 - phi2))), 6.0)))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((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)), Math.sqrt((1.0 - ((Math.cos(phi2) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)) + Math.pow(Math.sin((phi2 * -0.5)), 2.0))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)) t_2 = Float64(t_1 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0)) t_3 = sqrt(t_2) tmp = 0.0 if (atan(t_3, sqrt(Float64(1.0 - t_2))) <= 1.5) tmp = Float64(R * Float64(2.0 * atan(t_3, sqrt(Float64(1.0 - Float64(t_1 + cbrt((sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 6.0)))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((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)), sqrt(Float64(1.0 - Float64(Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)) + (sin(Float64(phi2 * -0.5)) ^ 2.0))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(t$95$1 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[Sqrt[t$95$2], $MachinePrecision]}, If[LessEqual[N[ArcTan[t$95$3 / N[Sqrt[N[(1.0 - t$95$2), $MachinePrecision]], $MachinePrecision]], $MachinePrecision], 1.5], N[(R * N[(2.0 * N[ArcTan[t$95$3 / N[Sqrt[N[(1.0 - N[(t$95$1 + N[Power[N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 6.0], $MachinePrecision], 1/3], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(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] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right)\\
t_2 := t\_1 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
t_3 := \sqrt{t\_2}\\
\mathbf{if}\;\tan^{-1}_* \frac{t\_3}{\sqrt{1 - t\_2}} \leq 1.5:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_3}{\sqrt{1 - \left(t\_1 + \sqrt[3]{{\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{6}}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\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\_1}}{\sqrt{1 - \left(\cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2} + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}}\right)\\
\end{array}
\end{array}
if (atan2.f64 (sqrt.f64 (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))))) (sqrt.f64 (-.f64 #s(literal 1 binary64) (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))))))) < 1.5Initial program 61.9%
add-cbrt-cube61.9%
pow361.9%
pow-pow61.9%
div-inv61.9%
metadata-eval61.9%
metadata-eval61.9%
Applied egg-rr61.9%
if 1.5 < (atan2.f64 (sqrt.f64 (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))))) (sqrt.f64 (-.f64 #s(literal 1 binary64) (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))))))) Initial program 13.9%
div-sub13.9%
sin-diff23.9%
div-inv23.9%
metadata-eval23.9%
div-inv23.9%
metadata-eval23.9%
div-inv23.9%
metadata-eval23.9%
div-inv23.9%
metadata-eval23.9%
Applied egg-rr23.9%
Taylor expanded in phi1 around 0 33.5%
Final simplification59.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* t_0 (* (* (cos phi1) (cos phi2)) t_0)))
(t_2 (+ t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(t_3 (sqrt t_2)))
(if (<= (atan2 t_3 (sqrt (- 1.0 t_2))) 1.5)
(*
R
(*
2.0
(atan2
t_3
(sqrt (- 1.0 (+ t_1 (cbrt (pow (sin (* 0.5 (- phi1 phi2))) 6.0))))))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow
(-
(* (cos (* 0.5 phi2)) (sin (* phi1 0.5)))
(* (sin (* 0.5 phi2)) (cos (* phi1 0.5))))
2.0)
t_1))
(sqrt (- 1.0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = t_0 * ((cos(phi1) * cos(phi2)) * t_0);
double t_2 = t_1 + pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double t_3 = sqrt(t_2);
double tmp;
if (atan2(t_3, sqrt((1.0 - t_2))) <= 1.5) {
tmp = R * (2.0 * atan2(t_3, sqrt((1.0 - (t_1 + cbrt(pow(sin((0.5 * (phi1 - phi2))), 6.0)))))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (sin((0.5 * phi2)) * cos((phi1 * 0.5)))), 2.0) + t_1)), sqrt((1.0 - pow(sin((0.5 * (lambda1 - lambda2))), 2.0)))));
}
return tmp;
}
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0);
double t_2 = t_1 + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0);
double t_3 = Math.sqrt(t_2);
double tmp;
if (Math.atan2(t_3, Math.sqrt((1.0 - t_2))) <= 1.5) {
tmp = R * (2.0 * Math.atan2(t_3, Math.sqrt((1.0 - (t_1 + Math.cbrt(Math.pow(Math.sin((0.5 * (phi1 - phi2))), 6.0)))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((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)), Math.sqrt((1.0 - Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)) t_2 = Float64(t_1 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0)) t_3 = sqrt(t_2) tmp = 0.0 if (atan(t_3, sqrt(Float64(1.0 - t_2))) <= 1.5) tmp = Float64(R * Float64(2.0 * atan(t_3, sqrt(Float64(1.0 - Float64(t_1 + cbrt((sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 6.0)))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((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)), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(t$95$1 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[Sqrt[t$95$2], $MachinePrecision]}, If[LessEqual[N[ArcTan[t$95$3 / N[Sqrt[N[(1.0 - t$95$2), $MachinePrecision]], $MachinePrecision]], $MachinePrecision], 1.5], N[(R * N[(2.0 * N[ArcTan[t$95$3 / N[Sqrt[N[(1.0 - N[(t$95$1 + N[Power[N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 6.0], $MachinePrecision], 1/3], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(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] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right)\\
t_2 := t\_1 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
t_3 := \sqrt{t\_2}\\
\mathbf{if}\;\tan^{-1}_* \frac{t\_3}{\sqrt{1 - t\_2}} \leq 1.5:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_3}{\sqrt{1 - \left(t\_1 + \sqrt[3]{{\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{6}}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\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\_1}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}\right)\\
\end{array}
\end{array}
if (atan2.f64 (sqrt.f64 (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))))) (sqrt.f64 (-.f64 #s(literal 1 binary64) (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))))))) < 1.5Initial program 61.9%
add-cbrt-cube61.9%
pow361.9%
pow-pow61.9%
div-inv61.9%
metadata-eval61.9%
metadata-eval61.9%
Applied egg-rr61.9%
if 1.5 < (atan2.f64 (sqrt.f64 (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))))) (sqrt.f64 (-.f64 #s(literal 1 binary64) (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))))))) Initial program 13.9%
div-sub13.9%
sin-diff23.9%
div-inv23.9%
metadata-eval23.9%
div-inv23.9%
metadata-eval23.9%
div-inv23.9%
metadata-eval23.9%
div-inv23.9%
metadata-eval23.9%
Applied egg-rr23.9%
Taylor expanded in phi2 around 0 32.7%
fma-define32.7%
Simplified32.7%
Taylor expanded in phi1 around 0 32.6%
Final simplification59.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* t_0 (* (* (cos phi1) (cos phi2)) t_0)))
(t_2 (+ t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(t_3 (sqrt t_2)))
(if (<= (atan2 t_3 (sqrt (- 1.0 t_2))) 1.52)
(*
R
(*
2.0
(atan2 t_3 (sqrt (+ 1.0 (- (- (/ (cos (- phi1 phi2)) 2.0) 0.5) t_1))))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow
(-
(* (cos (* 0.5 phi2)) (sin (* phi1 0.5)))
(* (sin (* 0.5 phi2)) (cos (* phi1 0.5))))
2.0)
t_1))
(sqrt (- 1.0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = t_0 * ((cos(phi1) * cos(phi2)) * t_0);
double t_2 = t_1 + pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double t_3 = sqrt(t_2);
double tmp;
if (atan2(t_3, sqrt((1.0 - t_2))) <= 1.52) {
tmp = R * (2.0 * atan2(t_3, sqrt((1.0 + (((cos((phi1 - phi2)) / 2.0) - 0.5) - t_1)))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (sin((0.5 * phi2)) * cos((phi1 * 0.5)))), 2.0) + t_1)), sqrt((1.0 - pow(sin((0.5 * (lambda1 - lambda2))), 2.0)))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: t_3
real(8) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = t_0 * ((cos(phi1) * cos(phi2)) * t_0)
t_2 = t_1 + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0)
t_3 = sqrt(t_2)
if (atan2(t_3, sqrt((1.0d0 - t_2))) <= 1.52d0) then
tmp = r * (2.0d0 * atan2(t_3, sqrt((1.0d0 + (((cos((phi1 - phi2)) / 2.0d0) - 0.5d0) - t_1)))))
else
tmp = r * (2.0d0 * atan2(sqrt(((((cos((0.5d0 * phi2)) * sin((phi1 * 0.5d0))) - (sin((0.5d0 * phi2)) * cos((phi1 * 0.5d0)))) ** 2.0d0) + t_1)), sqrt((1.0d0 - (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0);
double t_2 = t_1 + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0);
double t_3 = Math.sqrt(t_2);
double tmp;
if (Math.atan2(t_3, Math.sqrt((1.0 - t_2))) <= 1.52) {
tmp = R * (2.0 * Math.atan2(t_3, Math.sqrt((1.0 + (((Math.cos((phi1 - phi2)) / 2.0) - 0.5) - t_1)))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((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)), Math.sqrt((1.0 - Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = t_0 * ((math.cos(phi1) * math.cos(phi2)) * t_0) t_2 = t_1 + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) t_3 = math.sqrt(t_2) tmp = 0 if math.atan2(t_3, math.sqrt((1.0 - t_2))) <= 1.52: tmp = R * (2.0 * math.atan2(t_3, math.sqrt((1.0 + (((math.cos((phi1 - phi2)) / 2.0) - 0.5) - t_1))))) else: tmp = R * (2.0 * math.atan2(math.sqrt((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)), math.sqrt((1.0 - math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)) t_2 = Float64(t_1 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0)) t_3 = sqrt(t_2) tmp = 0.0 if (atan(t_3, sqrt(Float64(1.0 - t_2))) <= 1.52) tmp = Float64(R * Float64(2.0 * atan(t_3, sqrt(Float64(1.0 + Float64(Float64(Float64(cos(Float64(phi1 - phi2)) / 2.0) - 0.5) - t_1)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((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)), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = t_0 * ((cos(phi1) * cos(phi2)) * t_0); t_2 = t_1 + (sin(((phi1 - phi2) / 2.0)) ^ 2.0); t_3 = sqrt(t_2); tmp = 0.0; if (atan2(t_3, sqrt((1.0 - t_2))) <= 1.52) tmp = R * (2.0 * atan2(t_3, sqrt((1.0 + (((cos((phi1 - phi2)) / 2.0) - 0.5) - t_1))))); else tmp = R * (2.0 * atan2(sqrt(((((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (sin((0.5 * phi2)) * cos((phi1 * 0.5)))) ^ 2.0) + t_1)), sqrt((1.0 - (sin((0.5 * (lambda1 - lambda2))) ^ 2.0))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(t$95$1 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[Sqrt[t$95$2], $MachinePrecision]}, If[LessEqual[N[ArcTan[t$95$3 / N[Sqrt[N[(1.0 - t$95$2), $MachinePrecision]], $MachinePrecision]], $MachinePrecision], 1.52], N[(R * N[(2.0 * N[ArcTan[t$95$3 / N[Sqrt[N[(1.0 + N[(N[(N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision] - t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(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] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right)\\
t_2 := t\_1 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
t_3 := \sqrt{t\_2}\\
\mathbf{if}\;\tan^{-1}_* \frac{t\_3}{\sqrt{1 - t\_2}} \leq 1.52:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_3}{\sqrt{1 + \left(\left(\frac{\cos \left(\phi_1 - \phi_2\right)}{2} - 0.5\right) - t\_1\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\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\_1}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}\right)\\
\end{array}
\end{array}
if (atan2.f64 (sqrt.f64 (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))))) (sqrt.f64 (-.f64 #s(literal 1 binary64) (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))))))) < 1.52Initial program 62.2%
unpow262.2%
sin-mult62.2%
div-inv62.2%
metadata-eval62.2%
div-inv62.2%
metadata-eval62.2%
div-inv62.2%
metadata-eval62.2%
div-inv62.2%
metadata-eval62.2%
Applied egg-rr62.2%
div-sub62.2%
+-inverses62.2%
cos-062.2%
metadata-eval62.2%
distribute-lft-out62.2%
metadata-eval62.2%
*-rgt-identity62.2%
Simplified62.2%
if 1.52 < (atan2.f64 (sqrt.f64 (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))))) (sqrt.f64 (-.f64 #s(literal 1 binary64) (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))))))) Initial program 5.7%
div-sub5.7%
sin-diff16.7%
div-inv16.7%
metadata-eval16.7%
div-inv16.7%
metadata-eval16.7%
div-inv16.7%
metadata-eval16.7%
div-inv16.7%
metadata-eval16.7%
Applied egg-rr16.7%
Taylor expanded in phi2 around 0 26.4%
fma-define26.4%
Simplified26.4%
Taylor expanded in phi1 around 0 26.3%
Final simplification59.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (* phi1 0.5)))
(t_1 (cos (* 0.5 phi2)))
(t_2 (sin (/ (- lambda1 lambda2) 2.0)))
(t_3 (* t_2 (* (* (cos phi1) (cos phi2)) t_2)))
(t_4 (sin (* phi1 0.5))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_3 (pow (fma t_1 t_4 (* t_0 (- (sin (* 0.5 phi2))))) 2.0)))
(sqrt
(-
1.0
(+ (pow (fma t_1 t_4 (* (sin (* phi2 -0.5)) t_0)) 2.0) t_3))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((phi1 * 0.5));
double t_1 = cos((0.5 * phi2));
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double t_3 = t_2 * ((cos(phi1) * cos(phi2)) * t_2);
double t_4 = sin((phi1 * 0.5));
return R * (2.0 * atan2(sqrt((t_3 + pow(fma(t_1, t_4, (t_0 * -sin((0.5 * phi2)))), 2.0))), sqrt((1.0 - (pow(fma(t_1, t_4, (sin((phi2 * -0.5)) * t_0)), 2.0) + t_3)))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(phi1 * 0.5)) t_1 = cos(Float64(0.5 * phi2)) t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_3 = Float64(t_2 * Float64(Float64(cos(phi1) * cos(phi2)) * t_2)) t_4 = sin(Float64(phi1 * 0.5)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_3 + (fma(t_1, t_4, Float64(t_0 * Float64(-sin(Float64(0.5 * phi2))))) ^ 2.0))), sqrt(Float64(1.0 - Float64((fma(t_1, t_4, Float64(sin(Float64(phi2 * -0.5)) * t_0)) ^ 2.0) + t_3)))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[(t$95$2 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$3 + N[Power[N[(t$95$1 * t$95$4 + N[(t$95$0 * (-N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision])), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[(t$95$1 * t$95$4 + N[(N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$3), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_1 := \cos \left(0.5 \cdot \phi_2\right)\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_3 := t\_2 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_2\right)\\
t_4 := \sin \left(\phi_1 \cdot 0.5\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_3 + {\left(\mathsf{fma}\left(t\_1, t\_4, t\_0 \cdot \left(-\sin \left(0.5 \cdot \phi_2\right)\right)\right)\right)}^{2}}}{\sqrt{1 - \left({\left(\mathsf{fma}\left(t\_1, t\_4, \sin \left(\phi_2 \cdot -0.5\right) \cdot t\_0\right)\right)}^{2} + t\_3\right)}}\right)
\end{array}
\end{array}
Initial program 57.8%
div-sub57.8%
sin-diff59.2%
div-inv59.2%
metadata-eval59.2%
div-inv59.2%
metadata-eval59.2%
div-inv59.2%
metadata-eval59.2%
div-inv59.2%
metadata-eval59.2%
Applied egg-rr59.2%
div-sub57.8%
sin-diff59.2%
div-inv59.2%
metadata-eval59.2%
div-inv59.2%
metadata-eval59.2%
div-inv59.2%
metadata-eval59.2%
div-inv59.2%
metadata-eval59.2%
Applied egg-rr76.9%
*-commutative76.9%
*-commutative76.9%
fmm-def76.9%
*-commutative76.9%
*-commutative76.9%
*-commutative76.9%
distribute-lft-neg-in76.9%
sin-neg76.9%
distribute-rgt-neg-in76.9%
metadata-eval76.9%
*-commutative76.9%
*-commutative76.9%
Simplified76.9%
Taylor expanded in phi1 around inf 76.9%
fmm-def77.0%
*-commutative77.0%
*-commutative77.0%
distribute-rgt-neg-in77.0%
*-commutative77.0%
Simplified77.0%
Final simplification77.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* phi1 0.5)))
(t_1 (cos (* phi1 0.5)))
(t_2 (sin (/ (- lambda1 lambda2) 2.0)))
(t_3 (* t_2 (* (* (cos phi1) (cos phi2)) t_2)))
(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_3))
(sqrt
(-
1.0
(+ (pow (fma t_4 t_0 (* (sin (* phi2 -0.5)) t_1)) 2.0) t_3))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((phi1 * 0.5));
double t_1 = cos((phi1 * 0.5));
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double t_3 = t_2 * ((cos(phi1) * cos(phi2)) * t_2);
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_3)), sqrt((1.0 - (pow(fma(t_4, t_0, (sin((phi2 * -0.5)) * t_1)), 2.0) + t_3)))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi1 * 0.5)) t_1 = cos(Float64(phi1 * 0.5)) t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_3 = Float64(t_2 * Float64(Float64(cos(phi1) * cos(phi2)) * t_2)) 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) + t_3)), sqrt(Float64(1.0 - Float64((fma(t_4, t_0, Float64(sin(Float64(phi2 * -0.5)) * t_1)) ^ 2.0) + t_3)))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[(t$95$2 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision]}, 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] + t$95$3), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[(t$95$4 * t$95$0 + N[(N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$3), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_1 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_3 := t\_2 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_2\right)\\
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\_3}}{\sqrt{1 - \left({\left(\mathsf{fma}\left(t\_4, t\_0, \sin \left(\phi_2 \cdot -0.5\right) \cdot t\_1\right)\right)}^{2} + t\_3\right)}}\right)
\end{array}
\end{array}
Initial program 57.8%
div-sub57.8%
sin-diff59.2%
div-inv59.2%
metadata-eval59.2%
div-inv59.2%
metadata-eval59.2%
div-inv59.2%
metadata-eval59.2%
div-inv59.2%
metadata-eval59.2%
Applied egg-rr59.2%
div-sub57.8%
sin-diff59.2%
div-inv59.2%
metadata-eval59.2%
div-inv59.2%
metadata-eval59.2%
div-inv59.2%
metadata-eval59.2%
div-inv59.2%
metadata-eval59.2%
Applied egg-rr76.9%
*-commutative76.9%
*-commutative76.9%
fmm-def76.9%
*-commutative76.9%
*-commutative76.9%
*-commutative76.9%
distribute-lft-neg-in76.9%
sin-neg76.9%
distribute-rgt-neg-in76.9%
metadata-eval76.9%
*-commutative76.9%
*-commutative76.9%
Simplified76.9%
Final simplification76.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (* phi1 0.5)))
(t_1 (* (cos (* 0.5 phi2)) (sin (* phi1 0.5))))
(t_2 (pow (+ (* (sin (* phi2 -0.5)) t_0) t_1) 2.0))
(t_3 (sin (/ (- lambda1 lambda2) 2.0)))
(t_4
(sqrt
(+
(pow (- t_1 (* (sin (* 0.5 phi2)) t_0)) 2.0)
(* t_3 (* (* (cos phi1) (cos phi2)) t_3))))))
(if (or (<= lambda1 -1.6e-5) (not (<= lambda1 6.8e-6)))
(*
R
(*
2.0
(atan2
t_4
(sqrt
(-
1.0
(+
(* (cos phi1) (* (cos phi2) (pow (sin (* 0.5 lambda1)) 2.0)))
t_2))))))
(*
R
(*
2.0
(atan2
t_4
(sqrt
(-
1.0
(+
t_2
(*
(cos phi1)
(* (cos phi2) (pow (sin (* lambda2 -0.5)) 2.0))))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((phi1 * 0.5));
double t_1 = cos((0.5 * phi2)) * sin((phi1 * 0.5));
double t_2 = pow(((sin((phi2 * -0.5)) * t_0) + t_1), 2.0);
double t_3 = sin(((lambda1 - lambda2) / 2.0));
double t_4 = sqrt((pow((t_1 - (sin((0.5 * phi2)) * t_0)), 2.0) + (t_3 * ((cos(phi1) * cos(phi2)) * t_3))));
double tmp;
if ((lambda1 <= -1.6e-5) || !(lambda1 <= 6.8e-6)) {
tmp = R * (2.0 * atan2(t_4, sqrt((1.0 - ((cos(phi1) * (cos(phi2) * pow(sin((0.5 * lambda1)), 2.0))) + t_2)))));
} else {
tmp = R * (2.0 * atan2(t_4, sqrt((1.0 - (t_2 + (cos(phi1) * (cos(phi2) * pow(sin((lambda2 * -0.5)), 2.0))))))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: t_3
real(8) :: t_4
real(8) :: tmp
t_0 = cos((phi1 * 0.5d0))
t_1 = cos((0.5d0 * phi2)) * sin((phi1 * 0.5d0))
t_2 = ((sin((phi2 * (-0.5d0))) * t_0) + t_1) ** 2.0d0
t_3 = sin(((lambda1 - lambda2) / 2.0d0))
t_4 = sqrt((((t_1 - (sin((0.5d0 * phi2)) * t_0)) ** 2.0d0) + (t_3 * ((cos(phi1) * cos(phi2)) * t_3))))
if ((lambda1 <= (-1.6d-5)) .or. (.not. (lambda1 <= 6.8d-6))) then
tmp = r * (2.0d0 * atan2(t_4, sqrt((1.0d0 - ((cos(phi1) * (cos(phi2) * (sin((0.5d0 * lambda1)) ** 2.0d0))) + t_2)))))
else
tmp = r * (2.0d0 * atan2(t_4, sqrt((1.0d0 - (t_2 + (cos(phi1) * (cos(phi2) * (sin((lambda2 * (-0.5d0))) ** 2.0d0))))))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.cos((phi1 * 0.5));
double t_1 = Math.cos((0.5 * phi2)) * Math.sin((phi1 * 0.5));
double t_2 = Math.pow(((Math.sin((phi2 * -0.5)) * t_0) + t_1), 2.0);
double t_3 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_4 = Math.sqrt((Math.pow((t_1 - (Math.sin((0.5 * phi2)) * t_0)), 2.0) + (t_3 * ((Math.cos(phi1) * Math.cos(phi2)) * t_3))));
double tmp;
if ((lambda1 <= -1.6e-5) || !(lambda1 <= 6.8e-6)) {
tmp = R * (2.0 * Math.atan2(t_4, Math.sqrt((1.0 - ((Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((0.5 * lambda1)), 2.0))) + t_2)))));
} else {
tmp = R * (2.0 * Math.atan2(t_4, Math.sqrt((1.0 - (t_2 + (Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((lambda2 * -0.5)), 2.0))))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos((phi1 * 0.5)) t_1 = math.cos((0.5 * phi2)) * math.sin((phi1 * 0.5)) t_2 = math.pow(((math.sin((phi2 * -0.5)) * t_0) + t_1), 2.0) t_3 = math.sin(((lambda1 - lambda2) / 2.0)) t_4 = math.sqrt((math.pow((t_1 - (math.sin((0.5 * phi2)) * t_0)), 2.0) + (t_3 * ((math.cos(phi1) * math.cos(phi2)) * t_3)))) tmp = 0 if (lambda1 <= -1.6e-5) or not (lambda1 <= 6.8e-6): tmp = R * (2.0 * math.atan2(t_4, math.sqrt((1.0 - ((math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((0.5 * lambda1)), 2.0))) + t_2))))) else: tmp = R * (2.0 * math.atan2(t_4, math.sqrt((1.0 - (t_2 + (math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((lambda2 * -0.5)), 2.0)))))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(phi1 * 0.5)) t_1 = Float64(cos(Float64(0.5 * phi2)) * sin(Float64(phi1 * 0.5))) t_2 = Float64(Float64(sin(Float64(phi2 * -0.5)) * t_0) + t_1) ^ 2.0 t_3 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_4 = sqrt(Float64((Float64(t_1 - Float64(sin(Float64(0.5 * phi2)) * t_0)) ^ 2.0) + Float64(t_3 * Float64(Float64(cos(phi1) * cos(phi2)) * t_3)))) tmp = 0.0 if ((lambda1 <= -1.6e-5) || !(lambda1 <= 6.8e-6)) tmp = Float64(R * Float64(2.0 * atan(t_4, sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(0.5 * lambda1)) ^ 2.0))) + t_2)))))); else tmp = Float64(R * Float64(2.0 * atan(t_4, sqrt(Float64(1.0 - Float64(t_2 + Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(lambda2 * -0.5)) ^ 2.0))))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos((phi1 * 0.5)); t_1 = cos((0.5 * phi2)) * sin((phi1 * 0.5)); t_2 = ((sin((phi2 * -0.5)) * t_0) + t_1) ^ 2.0; t_3 = sin(((lambda1 - lambda2) / 2.0)); t_4 = sqrt((((t_1 - (sin((0.5 * phi2)) * t_0)) ^ 2.0) + (t_3 * ((cos(phi1) * cos(phi2)) * t_3)))); tmp = 0.0; if ((lambda1 <= -1.6e-5) || ~((lambda1 <= 6.8e-6))) tmp = R * (2.0 * atan2(t_4, sqrt((1.0 - ((cos(phi1) * (cos(phi2) * (sin((0.5 * lambda1)) ^ 2.0))) + t_2))))); else tmp = R * (2.0 * atan2(t_4, sqrt((1.0 - (t_2 + (cos(phi1) * (cos(phi2) * (sin((lambda2 * -0.5)) ^ 2.0)))))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Power[N[(N[(N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision] + t$95$1), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[Sqrt[N[(N[Power[N[(t$95$1 - N[(N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$3 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[lambda1, -1.6e-5], N[Not[LessEqual[lambda1, 6.8e-6]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[t$95$4 / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$4 / N[Sqrt[N[(1.0 - N[(t$95$2 + 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]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_1 := \cos \left(0.5 \cdot \phi_2\right) \cdot \sin \left(\phi_1 \cdot 0.5\right)\\
t_2 := {\left(\sin \left(\phi_2 \cdot -0.5\right) \cdot t\_0 + t\_1\right)}^{2}\\
t_3 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_4 := \sqrt{{\left(t\_1 - \sin \left(0.5 \cdot \phi_2\right) \cdot t\_0\right)}^{2} + t\_3 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_3\right)}\\
\mathbf{if}\;\lambda_1 \leq -1.6 \cdot 10^{-5} \lor \neg \left(\lambda_1 \leq 6.8 \cdot 10^{-6}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_4}{\sqrt{1 - \left(\cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(0.5 \cdot \lambda_1\right)}^{2}\right) + t\_2\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_4}{\sqrt{1 - \left(t\_2 + \cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(\lambda_2 \cdot -0.5\right)}^{2}\right)\right)}}\right)\\
\end{array}
\end{array}
if lambda1 < -1.59999999999999993e-5 or 6.80000000000000012e-6 < lambda1 Initial program 41.6%
div-sub41.6%
sin-diff43.7%
div-inv43.7%
metadata-eval43.7%
div-inv43.7%
metadata-eval43.7%
div-inv43.7%
metadata-eval43.7%
div-inv43.7%
metadata-eval43.7%
Applied egg-rr43.7%
div-sub41.6%
sin-diff43.7%
div-inv43.7%
metadata-eval43.7%
div-inv43.7%
metadata-eval43.7%
div-inv43.7%
metadata-eval43.7%
div-inv43.7%
metadata-eval43.7%
Applied egg-rr57.3%
*-commutative57.3%
*-commutative57.3%
fmm-def57.3%
*-commutative57.3%
*-commutative57.3%
*-commutative57.3%
distribute-lft-neg-in57.3%
sin-neg57.3%
distribute-rgt-neg-in57.3%
metadata-eval57.3%
*-commutative57.3%
*-commutative57.3%
Simplified57.3%
Taylor expanded in lambda2 around 0 57.4%
if -1.59999999999999993e-5 < lambda1 < 6.80000000000000012e-6Initial program 74.4%
div-sub74.4%
sin-diff75.1%
div-inv75.1%
metadata-eval75.1%
div-inv75.1%
metadata-eval75.1%
div-inv75.1%
metadata-eval75.1%
div-inv75.1%
metadata-eval75.1%
Applied egg-rr75.1%
div-sub74.4%
sin-diff75.1%
div-inv75.1%
metadata-eval75.1%
div-inv75.1%
metadata-eval75.1%
div-inv75.1%
metadata-eval75.1%
div-inv75.1%
metadata-eval75.1%
Applied egg-rr97.2%
*-commutative97.2%
*-commutative97.2%
fmm-def97.2%
*-commutative97.2%
*-commutative97.2%
*-commutative97.2%
distribute-lft-neg-in97.2%
sin-neg97.2%
distribute-rgt-neg-in97.2%
metadata-eval97.2%
*-commutative97.2%
*-commutative97.2%
Simplified97.2%
Taylor expanded in lambda1 around 0 97.1%
Final simplification77.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos (* 0.5 phi2)) (sin (* phi1 0.5))))
(t_1 (* (cos phi1) (cos phi2)))
(t_2 (cos (* phi1 0.5)))
(t_3 (pow (- t_0 (* (sin (* 0.5 phi2)) t_2)) 2.0))
(t_4 (sin (/ (- lambda1 lambda2) 2.0)))
(t_5 (* t_4 t_4))
(t_6 (sqrt (+ t_3 (* t_4 (* t_1 t_4))))))
(if (<= lambda1 -0.015)
(*
R
(*
2.0
(atan2
t_6
(sqrt
(-
1.0
(+
(* (cos phi1) (* (cos phi2) (pow (sin (* 0.5 lambda1)) 2.0)))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)))))))
(if (<= lambda1 9e-23)
(*
R
(*
2.0
(atan2
t_6
(sqrt
(-
1.0
(+
(pow (+ (* (sin (* phi2 -0.5)) t_2) t_0) 2.0)
(*
(cos phi1)
(* (cos phi2) (pow (sin (* lambda2 -0.5)) 2.0)))))))))
(*
(atan2
(sqrt (fma t_1 t_5 t_3))
(sqrt (- 1.0 (fma t_1 t_5 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))))
(* R 2.0))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((0.5 * phi2)) * sin((phi1 * 0.5));
double t_1 = cos(phi1) * cos(phi2);
double t_2 = cos((phi1 * 0.5));
double t_3 = pow((t_0 - (sin((0.5 * phi2)) * t_2)), 2.0);
double t_4 = sin(((lambda1 - lambda2) / 2.0));
double t_5 = t_4 * t_4;
double t_6 = sqrt((t_3 + (t_4 * (t_1 * t_4))));
double tmp;
if (lambda1 <= -0.015) {
tmp = R * (2.0 * atan2(t_6, sqrt((1.0 - ((cos(phi1) * (cos(phi2) * pow(sin((0.5 * lambda1)), 2.0))) + pow(sin((0.5 * (phi1 - phi2))), 2.0))))));
} else if (lambda1 <= 9e-23) {
tmp = R * (2.0 * atan2(t_6, sqrt((1.0 - (pow(((sin((phi2 * -0.5)) * t_2) + t_0), 2.0) + (cos(phi1) * (cos(phi2) * pow(sin((lambda2 * -0.5)), 2.0))))))));
} else {
tmp = atan2(sqrt(fma(t_1, t_5, t_3)), sqrt((1.0 - fma(t_1, t_5, pow(sin(((phi1 - phi2) / 2.0)), 2.0))))) * (R * 2.0);
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(Float64(0.5 * phi2)) * sin(Float64(phi1 * 0.5))) t_1 = Float64(cos(phi1) * cos(phi2)) t_2 = cos(Float64(phi1 * 0.5)) t_3 = Float64(t_0 - Float64(sin(Float64(0.5 * phi2)) * t_2)) ^ 2.0 t_4 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_5 = Float64(t_4 * t_4) t_6 = sqrt(Float64(t_3 + Float64(t_4 * Float64(t_1 * t_4)))) tmp = 0.0 if (lambda1 <= -0.015) tmp = Float64(R * Float64(2.0 * atan(t_6, sqrt(Float64(1.0 - Float64(Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(0.5 * lambda1)) ^ 2.0))) + (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0))))))); elseif (lambda1 <= 9e-23) tmp = Float64(R * Float64(2.0 * atan(t_6, sqrt(Float64(1.0 - Float64((Float64(Float64(sin(Float64(phi2 * -0.5)) * t_2) + t_0) ^ 2.0) + Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(lambda2 * -0.5)) ^ 2.0))))))))); else tmp = Float64(atan(sqrt(fma(t_1, t_5, t_3)), sqrt(Float64(1.0 - fma(t_1, t_5, (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))))) * Float64(R * 2.0)); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Power[N[(t$95$0 - N[(N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$4 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$5 = N[(t$95$4 * t$95$4), $MachinePrecision]}, Block[{t$95$6 = N[Sqrt[N[(t$95$3 + N[(t$95$4 * N[(t$95$1 * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[lambda1, -0.015], N[(R * N[(2.0 * N[ArcTan[t$95$6 / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[lambda1, 9e-23], N[(R * N[(2.0 * N[ArcTan[t$95$6 / N[Sqrt[N[(1.0 - N[(N[Power[N[(N[(N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * t$95$2), $MachinePrecision] + t$95$0), $MachinePrecision], 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[(N[ArcTan[N[Sqrt[N[(t$95$1 * t$95$5 + t$95$3), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$1 * t$95$5 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(R * 2.0), $MachinePrecision]), $MachinePrecision]]]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(0.5 \cdot \phi_2\right) \cdot \sin \left(\phi_1 \cdot 0.5\right)\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
t_2 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_3 := {\left(t\_0 - \sin \left(0.5 \cdot \phi_2\right) \cdot t\_2\right)}^{2}\\
t_4 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_5 := t\_4 \cdot t\_4\\
t_6 := \sqrt{t\_3 + t\_4 \cdot \left(t\_1 \cdot t\_4\right)}\\
\mathbf{if}\;\lambda_1 \leq -0.015:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_6}{\sqrt{1 - \left(\cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(0.5 \cdot \lambda_1\right)}^{2}\right) + {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}}\right)\\
\mathbf{elif}\;\lambda_1 \leq 9 \cdot 10^{-23}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_6}{\sqrt{1 - \left({\left(\sin \left(\phi_2 \cdot -0.5\right) \cdot t\_2 + t\_0\right)}^{2} + \cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(\lambda_2 \cdot -0.5\right)}^{2}\right)\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_1, t\_5, t\_3\right)}}{\sqrt{1 - \mathsf{fma}\left(t\_1, t\_5, {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right)}} \cdot \left(R \cdot 2\right)\\
\end{array}
\end{array}
if lambda1 < -0.014999999999999999Initial program 39.3%
div-sub39.3%
sin-diff41.0%
div-inv41.0%
metadata-eval41.0%
div-inv41.0%
metadata-eval41.0%
div-inv41.0%
metadata-eval41.0%
div-inv41.0%
metadata-eval41.0%
Applied egg-rr41.0%
Taylor expanded in lambda2 around 0 41.1%
if -0.014999999999999999 < lambda1 < 8.9999999999999995e-23Initial program 72.9%
div-sub72.9%
sin-diff73.7%
div-inv73.7%
metadata-eval73.7%
div-inv73.7%
metadata-eval73.7%
div-inv73.7%
metadata-eval73.7%
div-inv73.7%
metadata-eval73.7%
Applied egg-rr73.7%
div-sub72.9%
sin-diff73.7%
div-inv73.7%
metadata-eval73.7%
div-inv73.7%
metadata-eval73.7%
div-inv73.7%
metadata-eval73.7%
div-inv73.7%
metadata-eval73.7%
Applied egg-rr97.5%
*-commutative97.5%
*-commutative97.5%
fmm-def97.5%
*-commutative97.5%
*-commutative97.5%
*-commutative97.5%
distribute-lft-neg-in97.5%
sin-neg97.5%
distribute-rgt-neg-in97.5%
metadata-eval97.5%
*-commutative97.5%
*-commutative97.5%
Simplified97.5%
Taylor expanded in lambda1 around 0 97.3%
if 8.9999999999999995e-23 < lambda1 Initial program 48.9%
associate-*r*48.9%
*-commutative48.9%
Simplified48.9%
div-sub48.9%
sin-diff51.1%
div-inv51.1%
metadata-eval51.1%
div-inv51.1%
metadata-eval51.1%
div-inv51.1%
metadata-eval51.1%
div-inv51.1%
metadata-eval51.1%
Applied egg-rr51.2%
Final simplification70.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* t_0 (* (* (cos phi1) (cos phi2)) t_0)))
(t_2 (cos (* 0.5 phi2)))
(t_3 (sin (* phi1 0.5)))
(t_4 (cos (* phi1 0.5)))
(t_5 (pow (- (* t_2 t_3) (* (sin (* 0.5 phi2)) t_4)) 2.0)))
(if (or (<= phi2 -0.17) (not (<= phi2 7000000000000.0)))
(*
R
(*
2.0
(atan2
(sqrt
(+ t_5 (* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))))
(sqrt
(-
1.0
(+ (pow (fma t_2 t_3 (* (sin (* phi2 -0.5)) t_4)) 2.0) t_1))))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_5 t_1))
(sqrt
(-
1.0
(fma
(cos phi1)
(pow
(-
(* (sin (/ lambda1 2.0)) (cos (/ lambda2 2.0)))
(* (cos (/ lambda1 2.0)) (sin (/ lambda2 2.0))))
2.0)
(pow t_3 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = t_0 * ((cos(phi1) * cos(phi2)) * t_0);
double t_2 = cos((0.5 * phi2));
double t_3 = sin((phi1 * 0.5));
double t_4 = cos((phi1 * 0.5));
double t_5 = pow(((t_2 * t_3) - (sin((0.5 * phi2)) * t_4)), 2.0);
double tmp;
if ((phi2 <= -0.17) || !(phi2 <= 7000000000000.0)) {
tmp = R * (2.0 * atan2(sqrt((t_5 + (cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0)))), sqrt((1.0 - (pow(fma(t_2, t_3, (sin((phi2 * -0.5)) * t_4)), 2.0) + t_1)))));
} else {
tmp = R * (2.0 * atan2(sqrt((t_5 + t_1)), sqrt((1.0 - fma(cos(phi1), pow(((sin((lambda1 / 2.0)) * cos((lambda2 / 2.0))) - (cos((lambda1 / 2.0)) * sin((lambda2 / 2.0)))), 2.0), pow(t_3, 2.0))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)) t_2 = cos(Float64(0.5 * phi2)) t_3 = sin(Float64(phi1 * 0.5)) t_4 = cos(Float64(phi1 * 0.5)) t_5 = Float64(Float64(t_2 * t_3) - Float64(sin(Float64(0.5 * phi2)) * t_4)) ^ 2.0 tmp = 0.0 if ((phi2 <= -0.17) || !(phi2 <= 7000000000000.0)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_5 + Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)))), sqrt(Float64(1.0 - Float64((fma(t_2, t_3, Float64(sin(Float64(phi2 * -0.5)) * t_4)) ^ 2.0) + t_1)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_5 + t_1)), sqrt(Float64(1.0 - fma(cos(phi1), (Float64(Float64(sin(Float64(lambda1 / 2.0)) * cos(Float64(lambda2 / 2.0))) - Float64(cos(Float64(lambda1 / 2.0)) * sin(Float64(lambda2 / 2.0)))) ^ 2.0), (t_3 ^ 2.0))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$5 = N[Power[N[(N[(t$95$2 * t$95$3), $MachinePrecision] - N[(N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$4), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[phi2, -0.17], N[Not[LessEqual[phi2, 7000000000000.0]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$5 + N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[(t$95$2 * t$95$3 + N[(N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * t$95$4), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$5 + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[(N[(N[Sin[N[(lambda1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(lambda2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(lambda1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(lambda2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[Power[t$95$3, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right)\\
t_2 := \cos \left(0.5 \cdot \phi_2\right)\\
t_3 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_4 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_5 := {\left(t\_2 \cdot t\_3 - \sin \left(0.5 \cdot \phi_2\right) \cdot t\_4\right)}^{2}\\
\mathbf{if}\;\phi_2 \leq -0.17 \lor \neg \left(\phi_2 \leq 7000000000000\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_5 + \cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}{\sqrt{1 - \left({\left(\mathsf{fma}\left(t\_2, t\_3, \sin \left(\phi_2 \cdot -0.5\right) \cdot t\_4\right)\right)}^{2} + t\_1\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_5 + t\_1}}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, {\left(\sin \left(\frac{\lambda_1}{2}\right) \cdot \cos \left(\frac{\lambda_2}{2}\right) - \cos \left(\frac{\lambda_1}{2}\right) \cdot \sin \left(\frac{\lambda_2}{2}\right)\right)}^{2}, {t\_3}^{2}\right)}}\right)\\
\end{array}
\end{array}
if phi2 < -0.170000000000000012 or 7e12 < phi2 Initial program 46.5%
div-sub46.5%
sin-diff49.0%
div-inv49.0%
metadata-eval49.0%
div-inv49.0%
metadata-eval49.0%
div-inv49.0%
metadata-eval49.0%
div-inv49.0%
metadata-eval49.0%
Applied egg-rr49.0%
div-sub46.5%
sin-diff49.0%
div-inv49.0%
metadata-eval49.0%
div-inv49.0%
metadata-eval49.0%
div-inv49.0%
metadata-eval49.0%
div-inv49.0%
metadata-eval49.0%
Applied egg-rr79.3%
*-commutative79.3%
*-commutative79.3%
fmm-def79.3%
*-commutative79.3%
*-commutative79.3%
*-commutative79.3%
distribute-lft-neg-in79.3%
sin-neg79.3%
distribute-rgt-neg-in79.3%
metadata-eval79.3%
*-commutative79.3%
*-commutative79.3%
Simplified79.3%
add-log-exp79.4%
Applied egg-rr79.4%
Taylor expanded in phi1 around 0 57.7%
if -0.170000000000000012 < phi2 < 7e12Initial program 70.3%
div-sub70.3%
sin-diff70.5%
div-inv70.5%
metadata-eval70.5%
div-inv70.5%
metadata-eval70.5%
div-inv70.5%
metadata-eval70.5%
div-inv70.5%
metadata-eval70.5%
Applied egg-rr70.5%
Taylor expanded in phi2 around 0 70.8%
fma-define70.8%
Simplified70.8%
*-commutative70.8%
metadata-eval70.8%
div-inv70.8%
div-sub70.8%
sin-diff71.6%
Applied egg-rr71.6%
Final simplification64.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(+
(pow
(-
(* (cos (* 0.5 phi2)) (sin (* phi1 0.5)))
(* (sin (* 0.5 phi2)) (cos (* phi1 0.5))))
2.0)
(* t_0 (* (* (cos phi1) (cos phi2)) t_0)))))
(* 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(((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (sin((0.5 * phi2)) * cos((phi1 * 0.5)))), 2.0) + (t_0 * ((cos(phi1) * cos(phi2)) * t_0));
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 = (((cos((0.5d0 * phi2)) * sin((phi1 * 0.5d0))) - (sin((0.5d0 * phi2)) * cos((phi1 * 0.5d0)))) ** 2.0d0) + (t_0 * ((cos(phi1) * cos(phi2)) * 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.cos((0.5 * phi2)) * Math.sin((phi1 * 0.5))) - (Math.sin((0.5 * phi2)) * Math.cos((phi1 * 0.5)))), 2.0) + (t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * 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.cos((0.5 * phi2)) * math.sin((phi1 * 0.5))) - (math.sin((0.5 * phi2)) * math.cos((phi1 * 0.5)))), 2.0) + (t_0 * ((math.cos(phi1) * math.cos(phi2)) * 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((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) + Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * 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 = (((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (sin((0.5 * phi2)) * cos((phi1 * 0.5)))) ^ 2.0) + (t_0 * ((cos(phi1) * cos(phi2)) * t_0)); 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[(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] + N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $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 := {\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\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)
\end{array}
\end{array}
Initial program 57.8%
div-sub57.8%
sin-diff59.2%
div-inv59.2%
metadata-eval59.2%
div-inv59.2%
metadata-eval59.2%
div-inv59.2%
metadata-eval59.2%
div-inv59.2%
metadata-eval59.2%
Applied egg-rr59.2%
div-sub57.8%
sin-diff59.2%
div-inv59.2%
metadata-eval59.2%
div-inv59.2%
metadata-eval59.2%
div-inv59.2%
metadata-eval59.2%
div-inv59.2%
metadata-eval59.2%
Applied egg-rr76.9%
Final simplification76.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* t_0 (* (* (cos phi1) (cos phi2)) t_0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow
(-
(* (cos (* 0.5 phi2)) (sin (* phi1 0.5)))
(* (sin (* 0.5 phi2)) (cos (* phi1 0.5))))
2.0)
t_1))
(sqrt (- 1.0 (+ t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = t_0 * ((cos(phi1) * cos(phi2)) * t_0);
return R * (2.0 * atan2(sqrt((pow(((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (sin((0.5 * phi2)) * cos((phi1 * 0.5)))), 2.0) + t_1)), sqrt((1.0 - (t_1 + pow(sin(((phi1 - phi2) / 2.0)), 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
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = t_0 * ((cos(phi1) * cos(phi2)) * t_0)
code = r * (2.0d0 * atan2(sqrt(((((cos((0.5d0 * phi2)) * sin((phi1 * 0.5d0))) - (sin((0.5d0 * phi2)) * cos((phi1 * 0.5d0)))) ** 2.0d0) + t_1)), sqrt((1.0d0 - (t_1 + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt((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)), Math.sqrt((1.0 - (t_1 + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = t_0 * ((math.cos(phi1) * math.cos(phi2)) * t_0) return R * (2.0 * math.atan2(math.sqrt((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)), math.sqrt((1.0 - (t_1 + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((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)), sqrt(Float64(1.0 - Float64(t_1 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = t_0 * ((cos(phi1) * cos(phi2)) * t_0); tmp = R * (2.0 * atan2(sqrt(((((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (sin((0.5 * phi2)) * cos((phi1 * 0.5)))) ^ 2.0) + t_1)), sqrt((1.0 - (t_1 + (sin(((phi1 - phi2) / 2.0)) ^ 2.0)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(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] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$1 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\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\_1}}{\sqrt{1 - \left(t\_1 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 57.8%
div-sub57.8%
sin-diff59.2%
div-inv59.2%
metadata-eval59.2%
div-inv59.2%
metadata-eval59.2%
div-inv59.2%
metadata-eval59.2%
div-inv59.2%
metadata-eval59.2%
Applied egg-rr59.2%
Final simplification59.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(*
(cos phi1)
(* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow
(-
(* (cos (* 0.5 phi2)) (sin (* phi1 0.5)))
(* (sin (* 0.5 phi2)) (cos (* phi1 0.5))))
2.0)
t_0))
(sqrt (- 1.0 (+ (pow (sin (* 0.5 (- phi1 phi2))) 2.0) t_0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * (cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0));
return R * (2.0 * atan2(sqrt((pow(((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (sin((0.5 * phi2)) * cos((phi1 * 0.5)))), 2.0) + t_0)), sqrt((1.0 - (pow(sin((0.5 * (phi1 - phi2))), 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(phi1) * (cos(phi2) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0))
code = r * (2.0d0 * atan2(sqrt(((((cos((0.5d0 * phi2)) * sin((phi1 * 0.5d0))) - (sin((0.5d0 * phi2)) * cos((phi1 * 0.5d0)))) ** 2.0d0) + t_0)), sqrt((1.0d0 - ((sin((0.5d0 * (phi1 - phi2))) ** 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(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((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_0)), Math.sqrt((1.0 - (Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0) + t_0)))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0)) return R * (2.0 * math.atan2(math.sqrt((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_0)), math.sqrt((1.0 - (math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0) + t_0)))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0))) return Float64(R * Float64(2.0 * atan(sqrt(Float64((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_0)), sqrt(Float64(1.0 - Float64((sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0) + t_0)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi1) * (cos(phi2) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0)); tmp = R * (2.0 * atan2(sqrt(((((cos((0.5 * phi2)) * sin((phi1 * 0.5))) - (sin((0.5 * phi2)) * cos((phi1 * 0.5)))) ^ 2.0) + t_0)), sqrt((1.0 - ((sin((0.5 * (phi1 - phi2))) ^ 2.0) + t_0))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(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] + t$95$0), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\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\_0}}{\sqrt{1 - \left({\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2} + t\_0\right)}}\right)
\end{array}
\end{array}
Initial program 57.8%
div-sub57.8%
sin-diff59.2%
div-inv59.2%
metadata-eval59.2%
div-inv59.2%
metadata-eval59.2%
div-inv59.2%
metadata-eval59.2%
div-inv59.2%
metadata-eval59.2%
Applied egg-rr59.2%
Taylor expanded in phi1 around 0 59.1%
Final simplification59.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_2 (pow (sin (* phi2 -0.5)) 2.0)))
(if (or (<= phi2 -3.65e-6) (not (<= phi2 7000000000000.0)))
(*
R
(*
2.0
(atan2
(sqrt (+ (* (cos phi2) t_1) t_2))
(sqrt (- 1.0 (fma (cos phi2) t_1 t_2))))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(sqrt
(- 1.0 (+ (pow (sin (* phi1 0.5)) 2.0) (* (cos phi1) 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((0.5 * (lambda1 - lambda2))), 2.0);
double t_2 = pow(sin((phi2 * -0.5)), 2.0);
double tmp;
if ((phi2 <= -3.65e-6) || !(phi2 <= 7000000000000.0)) {
tmp = R * (2.0 * atan2(sqrt(((cos(phi2) * t_1) + t_2)), sqrt((1.0 - fma(cos(phi2), t_1, t_2)))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))), sqrt((1.0 - (pow(sin((phi1 * 0.5)), 2.0) + (cos(phi1) * t_1))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_2 = sin(Float64(phi2 * -0.5)) ^ 2.0 tmp = 0.0 if ((phi2 <= -3.65e-6) || !(phi2 <= 7000000000000.0)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi2) * t_1) + t_2)), sqrt(Float64(1.0 - fma(cos(phi2), t_1, t_2)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)))), sqrt(Float64(1.0 - Float64((sin(Float64(phi1 * 0.5)) ^ 2.0) + Float64(cos(phi1) * t_1))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[phi2, -3.65e-6], N[Not[LessEqual[phi2, 7000000000000.0]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$1), $MachinePrecision] + t$95$2), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi2], $MachinePrecision] * t$95$1 + t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * t$95$1), $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(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_2 := {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\\
\mathbf{if}\;\phi_2 \leq -3.65 \cdot 10^{-6} \lor \neg \left(\phi_2 \leq 7000000000000\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot t\_1 + t\_2}}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_2, t\_1, t\_2\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right)}}{\sqrt{1 - \left({\sin \left(\phi_1 \cdot 0.5\right)}^{2} + \cos \phi_1 \cdot t\_1\right)}}\right)\\
\end{array}
\end{array}
if phi2 < -3.65000000000000021e-6 or 7e12 < phi2 Initial program 46.3%
associate-*l*46.3%
Simplified46.3%
Taylor expanded in phi1 around 0 47.2%
fma-define47.2%
Simplified47.2%
Taylor expanded in phi1 around 0 49.0%
if -3.65000000000000021e-6 < phi2 < 7e12Initial program 70.7%
associate-*l*70.7%
Simplified70.7%
Taylor expanded in phi2 around 0 71.0%
Final simplification59.3%
(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 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
(if (or (<= phi1 -1.2e-5) (not (<= phi1 0.24)))
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (* (cos phi1) t_2)))
(sqrt (- 1.0 (fma (cos phi1) t_2 t_1))))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))))
(sqrt
(-
1.0
(fma
(cos phi2)
(- 0.5 (/ (cos (- lambda2 lambda1)) 2.0))
(pow (sin (* phi2 -0.5)) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin((phi1 * 0.5)), 2.0);
double t_2 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double tmp;
if ((phi1 <= -1.2e-5) || !(phi1 <= 0.24)) {
tmp = R * (2.0 * atan2(sqrt((t_1 + (cos(phi1) * t_2))), sqrt((1.0 - fma(cos(phi1), t_2, t_1)))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))), sqrt((1.0 - fma(cos(phi2), (0.5 - (cos((lambda2 - lambda1)) / 2.0)), pow(sin((phi2 * -0.5)), 2.0))))));
}
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 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 tmp = 0.0 if ((phi1 <= -1.2e-5) || !(phi1 <= 0.24)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + Float64(cos(phi1) * t_2))), sqrt(Float64(1.0 - fma(cos(phi1), t_2, t_1)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)))), sqrt(Float64(1.0 - fma(cos(phi2), Float64(0.5 - Float64(cos(Float64(lambda2 - lambda1)) / 2.0)), (sin(Float64(phi2 * -0.5)) ^ 2.0))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[phi1, -1.2e-5], N[Not[LessEqual[phi1, 0.24]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[(N[Cos[phi1], $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * t$95$2 + t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - 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]], $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 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
\mathbf{if}\;\phi_1 \leq -1.2 \cdot 10^{-5} \lor \neg \left(\phi_1 \leq 0.24\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + \cos \phi_1 \cdot t\_2}}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, t\_2, t\_1\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(t\_0 \cdot t\_0\right)}}{\sqrt{1 - \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)}}\right)\\
\end{array}
\end{array}
if phi1 < -1.2e-5 or 0.23999999999999999 < phi1 Initial program 42.7%
div-sub42.7%
sin-diff45.1%
div-inv45.1%
metadata-eval45.1%
div-inv45.1%
metadata-eval45.1%
div-inv45.1%
metadata-eval45.1%
div-inv45.1%
metadata-eval45.1%
Applied egg-rr45.1%
Taylor expanded in phi2 around 0 46.2%
fma-define46.2%
Simplified46.2%
Taylor expanded in phi2 around 0 45.0%
if -1.2e-5 < phi1 < 0.23999999999999999Initial program 78.1%
associate-*l*78.0%
Simplified78.0%
Taylor expanded in phi1 around 0 78.0%
fma-define78.0%
Simplified78.0%
*-commutative78.0%
metadata-eval78.0%
div-inv78.0%
pow278.0%
sin-mult78.1%
Applied egg-rr78.1%
div-sub78.1%
+-inverses78.1%
cos-078.1%
metadata-eval78.1%
associate-*r*78.1%
metadata-eval78.1%
*-lft-identity78.1%
sub-neg78.1%
remove-double-neg78.1%
mul-1-neg78.1%
distribute-neg-in78.1%
+-commutative78.1%
cos-neg78.1%
mul-1-neg78.1%
unsub-neg78.1%
Simplified78.1%
Final simplification59.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* phi1 0.5)) 2.0))
(t_1 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_2 (* (cos phi2) t_1)))
(if (or (<= phi1 -2.7e-5) (not (<= phi1 0.24)))
(*
R
(*
2.0
(atan2
(sqrt (+ t_0 (* (cos phi1) t_1)))
(sqrt (- 1.0 (fma (cos phi1) t_1 t_0))))))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (* 0.5 (- phi1 phi2))) 2.0) (* (cos phi1) t_2)))
(sqrt (- 1.0 (+ t_2 (pow (sin (* phi2 -0.5)) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((phi1 * 0.5)), 2.0);
double t_1 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_2 = cos(phi2) * t_1;
double tmp;
if ((phi1 <= -2.7e-5) || !(phi1 <= 0.24)) {
tmp = R * (2.0 * atan2(sqrt((t_0 + (cos(phi1) * t_1))), sqrt((1.0 - fma(cos(phi1), t_1, t_0)))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(sin((0.5 * (phi1 - phi2))), 2.0) + (cos(phi1) * t_2))), sqrt((1.0 - (t_2 + pow(sin((phi2 * -0.5)), 2.0))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi1 * 0.5)) ^ 2.0 t_1 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_2 = Float64(cos(phi2) * t_1) tmp = 0.0 if ((phi1 <= -2.7e-5) || !(phi1 <= 0.24)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_0 + Float64(cos(phi1) * t_1))), sqrt(Float64(1.0 - fma(cos(phi1), t_1, t_0)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0) + Float64(cos(phi1) * t_2))), sqrt(Float64(1.0 - Float64(t_2 + (sin(Float64(phi2 * -0.5)) ^ 2.0))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(phi1 * 0.5), $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[phi2], $MachinePrecision] * t$95$1), $MachinePrecision]}, If[Or[LessEqual[phi1, -2.7e-5], N[Not[LessEqual[phi1, 0.24]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 + N[(N[Cos[phi1], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * t$95$1 + t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$2 + 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 := {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\\
t_1 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_2 := \cos \phi_2 \cdot t\_1\\
\mathbf{if}\;\phi_1 \leq -2.7 \cdot 10^{-5} \lor \neg \left(\phi_1 \leq 0.24\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 + \cos \phi_1 \cdot t\_1}}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, t\_1, t\_0\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2} + \cos \phi_1 \cdot t\_2}}{\sqrt{1 - \left(t\_2 + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}}\right)\\
\end{array}
\end{array}
if phi1 < -2.6999999999999999e-5 or 0.23999999999999999 < phi1 Initial program 42.7%
div-sub42.7%
sin-diff45.1%
div-inv45.1%
metadata-eval45.1%
div-inv45.1%
metadata-eval45.1%
div-inv45.1%
metadata-eval45.1%
div-inv45.1%
metadata-eval45.1%
Applied egg-rr45.1%
Taylor expanded in phi2 around 0 46.2%
fma-define46.2%
Simplified46.2%
Taylor expanded in phi2 around 0 45.0%
if -2.6999999999999999e-5 < phi1 < 0.23999999999999999Initial program 78.1%
associate-*l*78.0%
Simplified78.0%
Taylor expanded in phi1 around 0 78.0%
fma-define78.0%
Simplified78.0%
Taylor expanded in phi1 around 0 78.0%
Final simplification59.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(*
R
(*
2.0
(atan2
(sqrt (+ t_2 (* t_0 (* t_1 t_1))))
(sqrt
(+ (- 1.0 t_2) (* 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 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
return R * (2.0 * atan2(sqrt((t_2 + (t_0 * (t_1 * t_1)))), sqrt(((1.0 - t_2) + (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 = sin(((lambda1 - lambda2) / 2.0d0))
t_2 = sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0
code = r * (2.0d0 * atan2(sqrt((t_2 + (t_0 * (t_1 * t_1)))), sqrt(((1.0d0 - t_2) + (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.sin(((lambda1 - lambda2) / 2.0));
double t_2 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0);
return R * (2.0 * Math.atan2(Math.sqrt((t_2 + (t_0 * (t_1 * t_1)))), Math.sqrt(((1.0 - t_2) + (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.sin(((lambda1 - lambda2) / 2.0)) t_2 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) return R * (2.0 * math.atan2(math.sqrt((t_2 + (t_0 * (t_1 * t_1)))), math.sqrt(((1.0 - t_2) + (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 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_2 + Float64(t_0 * Float64(t_1 * t_1)))), sqrt(Float64(Float64(1.0 - t_2) + 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 = sin(((lambda1 - lambda2) / 2.0)); t_2 = sin(((phi1 - phi2) / 2.0)) ^ 2.0; tmp = R * (2.0 * atan2(sqrt((t_2 + (t_0 * (t_1 * t_1)))), sqrt(((1.0 - t_2) + (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[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$2 + N[(t$95$0 * N[(t$95$1 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - t$95$2), $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 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 + t\_0 \cdot \left(t\_1 \cdot t\_1\right)}}{\sqrt{\left(1 - t\_2\right) + t\_0 \cdot \left(\frac{\cos \left(\lambda_1 - \lambda_2\right)}{2} - 0.5\right)}}\right)
\end{array}
\end{array}
Initial program 57.8%
associate-*l*57.8%
Simplified57.7%
sin-mult57.7%
cos-sum57.7%
cos-257.7%
div-sub57.7%
+-inverses57.7%
Applied egg-rr57.7%
cos-057.7%
metadata-eval57.7%
Simplified57.7%
Final simplification57.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* phi1 0.5)) 2.0))
(t_1 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
(if (or (<= phi1 -1.1e-6) (not (<= phi1 0.24)))
(*
R
(*
2.0
(atan2
(sqrt (+ t_0 (* (cos phi1) t_1)))
(sqrt (- 1.0 (fma (cos phi1) t_1 t_0))))))
(*
(* R 2.0)
(atan2
(sqrt (+ (* (cos phi2) t_1) (pow (sin (* phi2 -0.5)) 2.0)))
(sqrt
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (- 0.5 (* 0.5 (cos (- lambda1 lambda2)))))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((phi1 * 0.5)), 2.0);
double t_1 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double tmp;
if ((phi1 <= -1.1e-6) || !(phi1 <= 0.24)) {
tmp = R * (2.0 * atan2(sqrt((t_0 + (cos(phi1) * t_1))), sqrt((1.0 - fma(cos(phi1), t_1, t_0)))));
} else {
tmp = (R * 2.0) * atan2(sqrt(((cos(phi2) * t_1) + pow(sin((phi2 * -0.5)), 2.0))), sqrt((1.0 - fma(cos(phi1), (cos(phi2) * (0.5 - (0.5 * cos((lambda1 - lambda2))))), pow(sin((0.5 * (phi1 - phi2))), 2.0)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi1 * 0.5)) ^ 2.0 t_1 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 tmp = 0.0 if ((phi1 <= -1.1e-6) || !(phi1 <= 0.24)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_0 + Float64(cos(phi1) * t_1))), sqrt(Float64(1.0 - fma(cos(phi1), t_1, t_0)))))); else tmp = Float64(Float64(R * 2.0) * atan(sqrt(Float64(Float64(cos(phi2) * t_1) + (sin(Float64(phi2 * -0.5)) ^ 2.0))), sqrt(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * Float64(0.5 - Float64(0.5 * cos(Float64(lambda1 - lambda2))))), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(phi1 * 0.5), $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]}, If[Or[LessEqual[phi1, -1.1e-6], N[Not[LessEqual[phi1, 0.24]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 + N[(N[Cos[phi1], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * t$95$1 + t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$1), $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 - N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\\
t_1 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
\mathbf{if}\;\phi_1 \leq -1.1 \cdot 10^{-6} \lor \neg \left(\phi_1 \leq 0.24\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 + \cos \phi_1 \cdot t\_1}}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, t\_1, t\_0\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot t\_1 + {\sin \left(\phi_2 \cdot -0.5\right)}^{2}}}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \left(0.5 - 0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right), {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}}\\
\end{array}
\end{array}
if phi1 < -1.1000000000000001e-6 or 0.23999999999999999 < phi1 Initial program 42.7%
div-sub42.7%
sin-diff45.1%
div-inv45.1%
metadata-eval45.1%
div-inv45.1%
metadata-eval45.1%
div-inv45.1%
metadata-eval45.1%
div-inv45.1%
metadata-eval45.1%
Applied egg-rr45.1%
Taylor expanded in phi2 around 0 46.2%
fma-define46.2%
Simplified46.2%
Taylor expanded in phi2 around 0 45.0%
if -1.1000000000000001e-6 < phi1 < 0.23999999999999999Initial program 78.1%
associate-*r*78.1%
*-commutative78.1%
Simplified78.0%
Applied egg-rr62.8%
*-lft-identity62.8%
*-commutative62.8%
*-commutative62.8%
metadata-eval62.8%
cancel-sign-sub-inv62.8%
Simplified62.8%
Taylor expanded in phi1 around 0 76.4%
Final simplification58.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi2) (+ 0.5 (* -0.5 (cos (- lambda1 lambda2))))))
(t_1 (pow (sin (* 0.5 (- phi1 phi2))) 2.0)))
(*
(* R 2.0)
(atan2
(sqrt (+ t_1 (* (cos phi1) t_0)))
(sqrt (+ 1.0 (+ 1.0 (- -1.0 (fma (cos phi1) t_0 t_1)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi2) * (0.5 + (-0.5 * cos((lambda1 - lambda2))));
double t_1 = pow(sin((0.5 * (phi1 - phi2))), 2.0);
return (R * 2.0) * atan2(sqrt((t_1 + (cos(phi1) * t_0))), sqrt((1.0 + (1.0 + (-1.0 - fma(cos(phi1), t_0, t_1))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi2) * Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2))))) t_1 = sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0 return Float64(Float64(R * 2.0) * atan(sqrt(Float64(t_1 + Float64(cos(phi1) * t_0))), sqrt(Float64(1.0 + Float64(1.0 + Float64(-1.0 - fma(cos(phi1), t_0, t_1))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi2], $MachinePrecision] * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(N[(R * 2.0), $MachinePrecision] * N[ArcTan[N[Sqrt[N[(t$95$1 + N[(N[Cos[phi1], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 + N[(1.0 + N[(-1.0 - N[(N[Cos[phi1], $MachinePrecision] * t$95$0 + t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_2 \cdot \left(0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right)\right)\\
t_1 := {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\\
\left(R \cdot 2\right) \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + \cos \phi_1 \cdot t\_0}}{\sqrt{1 + \left(1 + \left(-1 - \mathsf{fma}\left(\cos \phi_1, t\_0, t\_1\right)\right)\right)}}
\end{array}
\end{array}
Initial program 57.8%
associate-*r*57.8%
*-commutative57.8%
Simplified57.7%
Applied egg-rr57.7%
fma-undefine57.7%
+-commutative57.7%
div-inv57.7%
metadata-eval57.7%
associate-*l*57.7%
sqr-sin-a56.5%
cancel-sign-sub-inv56.5%
metadata-eval56.5%
cos-256.4%
cos-sum56.5%
add-log-exp15.9%
add-log-exp15.9%
Applied egg-rr56.5%
Final simplification56.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* phi1 0.5)) 2.0))
(t_1 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_2 (pow (sin (* phi2 -0.5)) 2.0)))
(if (or (<= phi1 -1.45e-8) (not (<= phi1 0.24)))
(*
R
(*
2.0
(atan2
(sqrt (+ t_0 (* (cos phi1) t_1)))
(sqrt (- 1.0 (fma (cos phi1) t_1 t_0))))))
(*
R
(*
2.0
(atan2
(sqrt (+ (* (cos phi2) t_1) t_2))
(sqrt (- 1.0 (fma (cos phi2) t_1 t_2)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((phi1 * 0.5)), 2.0);
double t_1 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_2 = pow(sin((phi2 * -0.5)), 2.0);
double tmp;
if ((phi1 <= -1.45e-8) || !(phi1 <= 0.24)) {
tmp = R * (2.0 * atan2(sqrt((t_0 + (cos(phi1) * t_1))), sqrt((1.0 - fma(cos(phi1), t_1, t_0)))));
} else {
tmp = R * (2.0 * atan2(sqrt(((cos(phi2) * t_1) + t_2)), sqrt((1.0 - fma(cos(phi2), t_1, t_2)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi1 * 0.5)) ^ 2.0 t_1 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_2 = sin(Float64(phi2 * -0.5)) ^ 2.0 tmp = 0.0 if ((phi1 <= -1.45e-8) || !(phi1 <= 0.24)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_0 + Float64(cos(phi1) * t_1))), sqrt(Float64(1.0 - fma(cos(phi1), t_1, t_0)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi2) * t_1) + t_2)), sqrt(Float64(1.0 - fma(cos(phi2), t_1, t_2)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(phi1 * 0.5), $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[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[phi1, -1.45e-8], N[Not[LessEqual[phi1, 0.24]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 + N[(N[Cos[phi1], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * t$95$1 + t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * t$95$1), $MachinePrecision] + t$95$2), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi2], $MachinePrecision] * t$95$1 + t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\\
t_1 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_2 := {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\\
\mathbf{if}\;\phi_1 \leq -1.45 \cdot 10^{-8} \lor \neg \left(\phi_1 \leq 0.24\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 + \cos \phi_1 \cdot t\_1}}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, t\_1, t\_0\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot t\_1 + t\_2}}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_2, t\_1, t\_2\right)}}\right)\\
\end{array}
\end{array}
if phi1 < -1.4500000000000001e-8 or 0.23999999999999999 < phi1 Initial program 42.7%
div-sub42.7%
sin-diff45.1%
div-inv45.1%
metadata-eval45.1%
div-inv45.1%
metadata-eval45.1%
div-inv45.1%
metadata-eval45.1%
div-inv45.1%
metadata-eval45.1%
Applied egg-rr45.1%
Taylor expanded in phi2 around 0 46.2%
fma-define46.2%
Simplified46.2%
Taylor expanded in phi2 around 0 45.0%
if -1.4500000000000001e-8 < phi1 < 0.23999999999999999Initial program 78.1%
associate-*l*78.0%
Simplified78.0%
Taylor expanded in phi1 around 0 78.0%
fma-define78.0%
Simplified78.0%
Taylor expanded in phi1 around 0 76.3%
Final simplification58.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* phi1 0.5)) 2.0))
(t_1 (sin (* phi2 -0.5)))
(t_2 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
(if (or (<= phi1 -1.6e-22) (not (<= phi1 0.24)))
(*
R
(*
2.0
(atan2
(sqrt (+ t_0 (* (cos phi1) t_2)))
(sqrt (- 1.0 (fma (cos phi1) t_2 t_0))))))
(*
R
(*
2.0
(atan2
(hypot t_1 (sqrt (* (cos phi2) t_2)))
(sqrt (- 1.0 (fma (cos phi2) t_2 (pow t_1 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((phi1 * 0.5)), 2.0);
double t_1 = sin((phi2 * -0.5));
double t_2 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double tmp;
if ((phi1 <= -1.6e-22) || !(phi1 <= 0.24)) {
tmp = R * (2.0 * atan2(sqrt((t_0 + (cos(phi1) * t_2))), sqrt((1.0 - fma(cos(phi1), t_2, t_0)))));
} else {
tmp = R * (2.0 * atan2(hypot(t_1, sqrt((cos(phi2) * t_2))), sqrt((1.0 - fma(cos(phi2), t_2, pow(t_1, 2.0))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi1 * 0.5)) ^ 2.0 t_1 = sin(Float64(phi2 * -0.5)) t_2 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 tmp = 0.0 if ((phi1 <= -1.6e-22) || !(phi1 <= 0.24)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_0 + Float64(cos(phi1) * t_2))), sqrt(Float64(1.0 - fma(cos(phi1), t_2, t_0)))))); else tmp = Float64(R * Float64(2.0 * atan(hypot(t_1, sqrt(Float64(cos(phi2) * t_2))), sqrt(Float64(1.0 - fma(cos(phi2), t_2, (t_1 ^ 2.0))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[phi1, -1.6e-22], N[Not[LessEqual[phi1, 0.24]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 + N[(N[Cos[phi1], $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * t$95$2 + t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$1 ^ 2 + N[Sqrt[N[(N[Cos[phi2], $MachinePrecision] * t$95$2), $MachinePrecision]], $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi2], $MachinePrecision] * t$95$2 + N[Power[t$95$1, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\\
t_1 := \sin \left(\phi_2 \cdot -0.5\right)\\
t_2 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
\mathbf{if}\;\phi_1 \leq -1.6 \cdot 10^{-22} \lor \neg \left(\phi_1 \leq 0.24\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 + \cos \phi_1 \cdot t\_2}}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, t\_2, t\_0\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(t\_1, \sqrt{\cos \phi_2 \cdot t\_2}\right)}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_2, t\_2, {t\_1}^{2}\right)}}\right)\\
\end{array}
\end{array}
if phi1 < -1.59999999999999994e-22 or 0.23999999999999999 < phi1 Initial program 42.8%
div-sub42.8%
sin-diff45.2%
div-inv45.2%
metadata-eval45.2%
div-inv45.2%
metadata-eval45.2%
div-inv45.2%
metadata-eval45.2%
div-inv45.2%
metadata-eval45.2%
Applied egg-rr45.2%
Taylor expanded in phi2 around 0 46.2%
fma-define46.2%
Simplified46.2%
Taylor expanded in phi2 around 0 45.0%
if -1.59999999999999994e-22 < phi1 < 0.23999999999999999Initial program 79.0%
associate-*l*78.9%
Simplified78.9%
Taylor expanded in phi1 around 0 78.9%
fma-define78.9%
Simplified78.9%
Taylor expanded in phi1 around 0 77.2%
+-commutative77.2%
*-commutative77.2%
unpow277.2%
rem-square-sqrt60.8%
hypot-undefine61.6%
Simplified61.6%
Final simplification51.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_1 (sin (* phi2 -0.5))))
(*
R
(*
2.0
(atan2
(hypot t_1 (sqrt (* (cos phi2) t_0)))
(sqrt (- 1.0 (fma (cos phi2) t_0 (pow t_1 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = sin((phi2 * -0.5));
return R * (2.0 * atan2(hypot(t_1, sqrt((cos(phi2) * t_0))), sqrt((1.0 - fma(cos(phi2), t_0, pow(t_1, 2.0))))));
}
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)) return Float64(R * Float64(2.0 * atan(hypot(t_1, sqrt(Float64(cos(phi2) * t_0))), sqrt(Float64(1.0 - fma(cos(phi2), t_0, (t_1 ^ 2.0))))))) 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]}, Block[{t$95$1 = N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$1 ^ 2 + N[Sqrt[N[(N[Cos[phi2], $MachinePrecision] * t$95$0), $MachinePrecision]], $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi2], $MachinePrecision] * t$95$0 + 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(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_1 := \sin \left(\phi_2 \cdot -0.5\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\mathsf{hypot}\left(t\_1, \sqrt{\cos \phi_2 \cdot t\_0}\right)}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_2, t\_0, {t\_1}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 57.8%
associate-*l*57.8%
Simplified57.7%
Taylor expanded in phi1 around 0 44.8%
fma-define44.8%
Simplified44.8%
Taylor expanded in phi1 around 0 43.9%
+-commutative43.9%
*-commutative43.9%
unpow243.9%
rem-square-sqrt33.7%
hypot-undefine34.0%
Simplified34.0%
Final simplification34.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(sqrt
(-
(- 1.0 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))))))
(if (or (<= (- lambda1 lambda2) -5e-47)
(not (<= (- lambda1 lambda2) 0.0002)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(* 0.25 (pow phi2 2.0))))
t_1)))
(*
R
(*
2.0
(atan2
(* phi2 (- (* 0.5 (cos (* phi1 0.5))) (/ (sin (* phi1 0.5)) phi2)))
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 = sqrt(((1.0 - pow(sin(((phi1 - phi2) / 2.0)), 2.0)) - ((cos(phi1) * cos(phi2)) * (t_0 * t_0))));
double tmp;
if (((lambda1 - lambda2) <= -5e-47) || !((lambda1 - lambda2) <= 0.0002)) {
tmp = R * (2.0 * atan2(sqrt(((cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0)) + (0.25 * pow(phi2, 2.0)))), t_1));
} else {
tmp = R * (2.0 * atan2((phi2 * ((0.5 * cos((phi1 * 0.5))) - (sin((phi1 * 0.5)) / phi2))), 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) / 2.0d0))
t_1 = sqrt(((1.0d0 - (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0)) - ((cos(phi1) * cos(phi2)) * (t_0 * t_0))))
if (((lambda1 - lambda2) <= (-5d-47)) .or. (.not. ((lambda1 - lambda2) <= 0.0002d0))) then
tmp = r * (2.0d0 * atan2(sqrt(((cos(phi2) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)) + (0.25d0 * (phi2 ** 2.0d0)))), t_1))
else
tmp = r * (2.0d0 * atan2((phi2 * ((0.5d0 * cos((phi1 * 0.5d0))) - (sin((phi1 * 0.5d0)) / phi2))), 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(((lambda1 - lambda2) / 2.0));
double t_1 = Math.sqrt(((1.0 - Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0)) - ((Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0))));
double tmp;
if (((lambda1 - lambda2) <= -5e-47) || !((lambda1 - lambda2) <= 0.0002)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi2) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)) + (0.25 * Math.pow(phi2, 2.0)))), t_1));
} else {
tmp = R * (2.0 * Math.atan2((phi2 * ((0.5 * Math.cos((phi1 * 0.5))) - (Math.sin((phi1 * 0.5)) / phi2))), t_1));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.sqrt(((1.0 - math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0)) - ((math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0)))) tmp = 0 if ((lambda1 - lambda2) <= -5e-47) or not ((lambda1 - lambda2) <= 0.0002): tmp = R * (2.0 * math.atan2(math.sqrt(((math.cos(phi2) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0)) + (0.25 * math.pow(phi2, 2.0)))), t_1)) else: tmp = R * (2.0 * math.atan2((phi2 * ((0.5 * math.cos((phi1 * 0.5))) - (math.sin((phi1 * 0.5)) / phi2))), t_1)) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sqrt(Float64(Float64(1.0 - (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0)) - Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)))) tmp = 0.0 if ((Float64(lambda1 - lambda2) <= -5e-47) || !(Float64(lambda1 - lambda2) <= 0.0002)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)) + Float64(0.25 * (phi2 ^ 2.0)))), t_1))); else tmp = Float64(R * Float64(2.0 * atan(Float64(phi2 * Float64(Float64(0.5 * cos(Float64(phi1 * 0.5))) - Float64(sin(Float64(phi1 * 0.5)) / phi2))), t_1))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = sqrt(((1.0 - (sin(((phi1 - phi2) / 2.0)) ^ 2.0)) - ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))); tmp = 0.0; if (((lambda1 - lambda2) <= -5e-47) || ~(((lambda1 - lambda2) <= 0.0002))) tmp = R * (2.0 * atan2(sqrt(((cos(phi2) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0)) + (0.25 * (phi2 ^ 2.0)))), t_1)); else tmp = R * (2.0 * atan2((phi2 * ((0.5 * cos((phi1 * 0.5))) - (sin((phi1 * 0.5)) / phi2))), t_1)); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[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[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[N[(lambda1 - lambda2), $MachinePrecision], -5e-47], N[Not[LessEqual[N[(lambda1 - lambda2), $MachinePrecision], 0.0002]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[(0.25 * N[Power[phi2, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[(phi2 * N[(N[(0.5 * N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] / phi2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / t$95$1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \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(t\_0 \cdot t\_0\right)}\\
\mathbf{if}\;\lambda_1 - \lambda_2 \leq -5 \cdot 10^{-47} \lor \neg \left(\lambda_1 - \lambda_2 \leq 0.0002\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2} + 0.25 \cdot {\phi_2}^{2}}}{t\_1}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\phi_2 \cdot \left(0.5 \cdot \cos \left(\phi_1 \cdot 0.5\right) - \frac{\sin \left(\phi_1 \cdot 0.5\right)}{\phi_2}\right)}{t\_1}\right)\\
\end{array}
\end{array}
if (-.f64 lambda1 lambda2) < -5.00000000000000011e-47 or 2.0000000000000001e-4 < (-.f64 lambda1 lambda2) Initial program 53.2%
associate-*l*53.2%
Simplified53.1%
Taylor expanded in phi2 around 0 39.4%
*-commutative39.4%
associate-*r*39.4%
*-commutative39.4%
Simplified39.4%
Taylor expanded in phi1 around 0 28.7%
if -5.00000000000000011e-47 < (-.f64 lambda1 lambda2) < 2.0000000000000001e-4Initial program 79.3%
associate-*l*79.3%
Simplified79.3%
Taylor expanded in phi2 around 0 59.4%
*-commutative59.4%
associate-*r*59.4%
*-commutative59.4%
Simplified59.4%
Taylor expanded in phi2 around inf 45.1%
+-commutative45.1%
mul-1-neg45.1%
unsub-neg45.1%
Simplified45.1%
Final simplification31.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(sqrt
(-
(- 1.0 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))))))
(if (<= t_0 0.002)
(*
R
(*
2.0
(atan2
(* phi2 (- (* 0.5 (cos (* phi1 0.5))) (/ (sin (* phi1 0.5)) phi2)))
t_1)))
(*
R
(*
2.0
(atan2 (* (sin (* 0.5 (- lambda1 lambda2))) (sqrt (cos phi1))) 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 = sqrt(((1.0 - pow(sin(((phi1 - phi2) / 2.0)), 2.0)) - ((cos(phi1) * cos(phi2)) * (t_0 * t_0))));
double tmp;
if (t_0 <= 0.002) {
tmp = R * (2.0 * atan2((phi2 * ((0.5 * cos((phi1 * 0.5))) - (sin((phi1 * 0.5)) / phi2))), t_1));
} else {
tmp = R * (2.0 * atan2((sin((0.5 * (lambda1 - lambda2))) * sqrt(cos(phi1))), 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) / 2.0d0))
t_1 = sqrt(((1.0d0 - (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0)) - ((cos(phi1) * cos(phi2)) * (t_0 * t_0))))
if (t_0 <= 0.002d0) then
tmp = r * (2.0d0 * atan2((phi2 * ((0.5d0 * cos((phi1 * 0.5d0))) - (sin((phi1 * 0.5d0)) / phi2))), t_1))
else
tmp = r * (2.0d0 * atan2((sin((0.5d0 * (lambda1 - lambda2))) * sqrt(cos(phi1))), 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(((lambda1 - lambda2) / 2.0));
double t_1 = Math.sqrt(((1.0 - Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0)) - ((Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0))));
double tmp;
if (t_0 <= 0.002) {
tmp = R * (2.0 * Math.atan2((phi2 * ((0.5 * Math.cos((phi1 * 0.5))) - (Math.sin((phi1 * 0.5)) / phi2))), t_1));
} else {
tmp = R * (2.0 * Math.atan2((Math.sin((0.5 * (lambda1 - lambda2))) * Math.sqrt(Math.cos(phi1))), t_1));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.sqrt(((1.0 - math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0)) - ((math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0)))) tmp = 0 if t_0 <= 0.002: tmp = R * (2.0 * math.atan2((phi2 * ((0.5 * math.cos((phi1 * 0.5))) - (math.sin((phi1 * 0.5)) / phi2))), t_1)) else: tmp = R * (2.0 * math.atan2((math.sin((0.5 * (lambda1 - lambda2))) * math.sqrt(math.cos(phi1))), t_1)) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sqrt(Float64(Float64(1.0 - (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0)) - Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0)))) tmp = 0.0 if (t_0 <= 0.002) tmp = Float64(R * Float64(2.0 * atan(Float64(phi2 * Float64(Float64(0.5 * cos(Float64(phi1 * 0.5))) - Float64(sin(Float64(phi1 * 0.5)) / phi2))), t_1))); else tmp = Float64(R * Float64(2.0 * atan(Float64(sin(Float64(0.5 * Float64(lambda1 - lambda2))) * sqrt(cos(phi1))), t_1))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = sqrt(((1.0 - (sin(((phi1 - phi2) / 2.0)) ^ 2.0)) - ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))); tmp = 0.0; if (t_0 <= 0.002) tmp = R * (2.0 * atan2((phi2 * ((0.5 * cos((phi1 * 0.5))) - (sin((phi1 * 0.5)) / phi2))), t_1)); else tmp = R * (2.0 * atan2((sin((0.5 * (lambda1 - lambda2))) * sqrt(cos(phi1))), t_1)); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[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[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[t$95$0, 0.002], N[(R * N[(2.0 * N[ArcTan[N[(phi2 * N[(N[(0.5 * N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] / phi2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / t$95$1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[(N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[Sqrt[N[Cos[phi1], $MachinePrecision]], $MachinePrecision]), $MachinePrecision] / t$95$1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \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(t\_0 \cdot t\_0\right)}\\
\mathbf{if}\;t\_0 \leq 0.002:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\phi_2 \cdot \left(0.5 \cdot \cos \left(\phi_1 \cdot 0.5\right) - \frac{\sin \left(\phi_1 \cdot 0.5\right)}{\phi_2}\right)}{t\_1}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right) \cdot \sqrt{\cos \phi_1}}{t\_1}\right)\\
\end{array}
\end{array}
if (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < 2e-3Initial program 61.4%
associate-*l*61.3%
Simplified61.3%
Taylor expanded in phi2 around 0 45.1%
*-commutative45.1%
associate-*r*45.1%
*-commutative45.1%
Simplified45.1%
Taylor expanded in phi2 around inf 19.5%
+-commutative19.5%
mul-1-neg19.5%
unsub-neg19.5%
Simplified19.5%
if 2e-3 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) Initial program 52.7%
associate-*l*52.7%
Simplified52.7%
Taylor expanded in phi1 around 0 37.5%
Taylor expanded in phi2 around 0 23.4%
Final simplification21.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))) (t_1 (sin (* phi1 0.5))))
(if (<= phi2 -1.9e-185)
(*
R
(*
2.0
(atan2
(*
-0.5
(*
phi2
(+
1.0
(*
(pow phi1 2.0)
(- (* (pow phi1 2.0) 0.0026041666666666665) 0.125)))))
(sqrt
(-
1.0
(+
(pow t_1 2.0)
(* (cos phi1) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))))))))
(*
R
(*
2.0
(atan2
(* phi2 (- (* 0.5 (cos (* phi1 0.5))) (/ t_1 phi2)))
(sqrt
(-
(- 1.0 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = sin((phi1 * 0.5));
double tmp;
if (phi2 <= -1.9e-185) {
tmp = R * (2.0 * atan2((-0.5 * (phi2 * (1.0 + (pow(phi1, 2.0) * ((pow(phi1, 2.0) * 0.0026041666666666665) - 0.125))))), sqrt((1.0 - (pow(t_1, 2.0) + (cos(phi1) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0)))))));
} else {
tmp = R * (2.0 * atan2((phi2 * ((0.5 * cos((phi1 * 0.5))) - (t_1 / phi2))), sqrt(((1.0 - pow(sin(((phi1 - phi2) / 2.0)), 2.0)) - ((cos(phi1) * cos(phi2)) * (t_0 * t_0))))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = sin((phi1 * 0.5d0))
if (phi2 <= (-1.9d-185)) then
tmp = r * (2.0d0 * atan2(((-0.5d0) * (phi2 * (1.0d0 + ((phi1 ** 2.0d0) * (((phi1 ** 2.0d0) * 0.0026041666666666665d0) - 0.125d0))))), sqrt((1.0d0 - ((t_1 ** 2.0d0) + (cos(phi1) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)))))))
else
tmp = r * (2.0d0 * atan2((phi2 * ((0.5d0 * cos((phi1 * 0.5d0))) - (t_1 / phi2))), sqrt(((1.0d0 - (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0)) - ((cos(phi1) * cos(phi2)) * (t_0 * t_0))))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.sin((phi1 * 0.5));
double tmp;
if (phi2 <= -1.9e-185) {
tmp = R * (2.0 * Math.atan2((-0.5 * (phi2 * (1.0 + (Math.pow(phi1, 2.0) * ((Math.pow(phi1, 2.0) * 0.0026041666666666665) - 0.125))))), Math.sqrt((1.0 - (Math.pow(t_1, 2.0) + (Math.cos(phi1) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)))))));
} else {
tmp = R * (2.0 * Math.atan2((phi2 * ((0.5 * Math.cos((phi1 * 0.5))) - (t_1 / phi2))), Math.sqrt(((1.0 - Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0)) - ((Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.sin((phi1 * 0.5)) tmp = 0 if phi2 <= -1.9e-185: tmp = R * (2.0 * math.atan2((-0.5 * (phi2 * (1.0 + (math.pow(phi1, 2.0) * ((math.pow(phi1, 2.0) * 0.0026041666666666665) - 0.125))))), math.sqrt((1.0 - (math.pow(t_1, 2.0) + (math.cos(phi1) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0))))))) else: tmp = R * (2.0 * math.atan2((phi2 * ((0.5 * math.cos((phi1 * 0.5))) - (t_1 / phi2))), math.sqrt(((1.0 - math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0)) - ((math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0)))))) 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)) tmp = 0.0 if (phi2 <= -1.9e-185) tmp = Float64(R * Float64(2.0 * atan(Float64(-0.5 * Float64(phi2 * Float64(1.0 + Float64((phi1 ^ 2.0) * Float64(Float64((phi1 ^ 2.0) * 0.0026041666666666665) - 0.125))))), sqrt(Float64(1.0 - Float64((t_1 ^ 2.0) + Float64(cos(phi1) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)))))))); else tmp = Float64(R * Float64(2.0 * atan(Float64(phi2 * Float64(Float64(0.5 * cos(Float64(phi1 * 0.5))) - Float64(t_1 / phi2))), sqrt(Float64(Float64(1.0 - (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0)) - Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = sin((phi1 * 0.5)); tmp = 0.0; if (phi2 <= -1.9e-185) tmp = R * (2.0 * atan2((-0.5 * (phi2 * (1.0 + ((phi1 ^ 2.0) * (((phi1 ^ 2.0) * 0.0026041666666666665) - 0.125))))), sqrt((1.0 - ((t_1 ^ 2.0) + (cos(phi1) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0))))))); else tmp = R * (2.0 * atan2((phi2 * ((0.5 * cos((phi1 * 0.5))) - (t_1 / phi2))), sqrt(((1.0 - (sin(((phi1 - phi2) / 2.0)) ^ 2.0)) - ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi2, -1.9e-185], N[(R * N[(2.0 * N[ArcTan[N[(-0.5 * N[(phi2 * N[(1.0 + N[(N[Power[phi1, 2.0], $MachinePrecision] * N[(N[(N[Power[phi1, 2.0], $MachinePrecision] * 0.0026041666666666665), $MachinePrecision] - 0.125), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[t$95$1, 2.0], $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[(phi2 * N[(N[(0.5 * N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(t$95$1 / phi2), $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[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \sin \left(\phi_1 \cdot 0.5\right)\\
\mathbf{if}\;\phi_2 \leq -1.9 \cdot 10^{-185}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{-0.5 \cdot \left(\phi_2 \cdot \left(1 + {\phi_1}^{2} \cdot \left({\phi_1}^{2} \cdot 0.0026041666666666665 - 0.125\right)\right)\right)}{\sqrt{1 - \left({t\_1}^{2} + \cos \phi_1 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\phi_2 \cdot \left(0.5 \cdot \cos \left(\phi_1 \cdot 0.5\right) - \frac{t\_1}{\phi_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(t\_0 \cdot t\_0\right)}}\right)\\
\end{array}
\end{array}
if phi2 < -1.9e-185Initial program 49.4%
associate-*l*49.4%
Simplified49.4%
Taylor expanded in phi2 around 0 32.3%
*-commutative32.3%
associate-*r*32.3%
*-commutative32.3%
Simplified32.3%
Taylor expanded in phi2 around -inf 13.5%
Taylor expanded in phi2 around 0 14.0%
Taylor expanded in phi1 around 0 19.8%
if -1.9e-185 < phi2 Initial program 63.7%
associate-*l*63.7%
Simplified63.6%
Taylor expanded in phi2 around 0 50.4%
*-commutative50.4%
associate-*r*50.4%
*-commutative50.4%
Simplified50.4%
Taylor expanded in phi2 around inf 20.1%
+-commutative20.1%
mul-1-neg20.1%
unsub-neg20.1%
Simplified20.1%
Final simplification20.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(if (<= phi2 -5e-310)
(*
R
(*
2.0
(atan2
(*
-0.5
(*
phi2
(+
1.0
(*
(pow phi1 2.0)
(- (* (pow phi1 2.0) 0.0026041666666666665) 0.125)))))
(sqrt
(-
1.0
(+
(pow (sin (* phi1 0.5)) 2.0)
(* (cos phi1) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))))))))
(*
R
(*
2.0
(atan2
(* 0.5 (* phi2 (cos (* phi1 0.5))))
(sqrt
(-
(- 1.0 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))
(* (* (cos phi1) (cos phi2)) (* t_0 t_0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if (phi2 <= -5e-310) {
tmp = R * (2.0 * atan2((-0.5 * (phi2 * (1.0 + (pow(phi1, 2.0) * ((pow(phi1, 2.0) * 0.0026041666666666665) - 0.125))))), sqrt((1.0 - (pow(sin((phi1 * 0.5)), 2.0) + (cos(phi1) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0)))))));
} else {
tmp = R * (2.0 * atan2((0.5 * (phi2 * cos((phi1 * 0.5)))), sqrt(((1.0 - pow(sin(((phi1 - phi2) / 2.0)), 2.0)) - ((cos(phi1) * cos(phi2)) * (t_0 * t_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) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
if (phi2 <= (-5d-310)) then
tmp = r * (2.0d0 * atan2(((-0.5d0) * (phi2 * (1.0d0 + ((phi1 ** 2.0d0) * (((phi1 ** 2.0d0) * 0.0026041666666666665d0) - 0.125d0))))), sqrt((1.0d0 - ((sin((phi1 * 0.5d0)) ** 2.0d0) + (cos(phi1) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)))))))
else
tmp = r * (2.0d0 * atan2((0.5d0 * (phi2 * cos((phi1 * 0.5d0)))), sqrt(((1.0d0 - (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0)) - ((cos(phi1) * cos(phi2)) * (t_0 * t_0))))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double tmp;
if (phi2 <= -5e-310) {
tmp = R * (2.0 * Math.atan2((-0.5 * (phi2 * (1.0 + (Math.pow(phi1, 2.0) * ((Math.pow(phi1, 2.0) * 0.0026041666666666665) - 0.125))))), Math.sqrt((1.0 - (Math.pow(Math.sin((phi1 * 0.5)), 2.0) + (Math.cos(phi1) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)))))));
} else {
tmp = R * (2.0 * Math.atan2((0.5 * (phi2 * Math.cos((phi1 * 0.5)))), Math.sqrt(((1.0 - Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0)) - ((Math.cos(phi1) * Math.cos(phi2)) * (t_0 * t_0))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) tmp = 0 if phi2 <= -5e-310: tmp = R * (2.0 * math.atan2((-0.5 * (phi2 * (1.0 + (math.pow(phi1, 2.0) * ((math.pow(phi1, 2.0) * 0.0026041666666666665) - 0.125))))), math.sqrt((1.0 - (math.pow(math.sin((phi1 * 0.5)), 2.0) + (math.cos(phi1) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0))))))) else: tmp = R * (2.0 * math.atan2((0.5 * (phi2 * math.cos((phi1 * 0.5)))), math.sqrt(((1.0 - math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0)) - ((math.cos(phi1) * math.cos(phi2)) * (t_0 * t_0)))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if (phi2 <= -5e-310) tmp = Float64(R * Float64(2.0 * atan(Float64(-0.5 * Float64(phi2 * Float64(1.0 + Float64((phi1 ^ 2.0) * Float64(Float64((phi1 ^ 2.0) * 0.0026041666666666665) - 0.125))))), sqrt(Float64(1.0 - Float64((sin(Float64(phi1 * 0.5)) ^ 2.0) + Float64(cos(phi1) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)))))))); else tmp = Float64(R * Float64(2.0 * atan(Float64(0.5 * Float64(phi2 * cos(Float64(phi1 * 0.5)))), sqrt(Float64(Float64(1.0 - (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0)) - Float64(Float64(cos(phi1) * cos(phi2)) * Float64(t_0 * t_0))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); tmp = 0.0; if (phi2 <= -5e-310) tmp = R * (2.0 * atan2((-0.5 * (phi2 * (1.0 + ((phi1 ^ 2.0) * (((phi1 ^ 2.0) * 0.0026041666666666665) - 0.125))))), sqrt((1.0 - ((sin((phi1 * 0.5)) ^ 2.0) + (cos(phi1) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0))))))); else tmp = R * (2.0 * atan2((0.5 * (phi2 * cos((phi1 * 0.5)))), sqrt(((1.0 - (sin(((phi1 - phi2) / 2.0)) ^ 2.0)) - ((cos(phi1) * cos(phi2)) * (t_0 * t_0)))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi2, -5e-310], N[(R * N[(2.0 * N[ArcTan[N[(-0.5 * N[(phi2 * N[(1.0 + N[(N[Power[phi1, 2.0], $MachinePrecision] * N[(N[(N[Power[phi1, 2.0], $MachinePrecision] * 0.0026041666666666665), $MachinePrecision] - 0.125), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[(0.5 * N[(phi2 * N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] - N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(t$95$0 * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\phi_2 \leq -5 \cdot 10^{-310}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{-0.5 \cdot \left(\phi_2 \cdot \left(1 + {\phi_1}^{2} \cdot \left({\phi_1}^{2} \cdot 0.0026041666666666665 - 0.125\right)\right)\right)}{\sqrt{1 - \left({\sin \left(\phi_1 \cdot 0.5\right)}^{2} + \cos \phi_1 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{0.5 \cdot \left(\phi_2 \cdot \cos \left(\phi_1 \cdot 0.5\right)\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(t\_0 \cdot t\_0\right)}}\right)\\
\end{array}
\end{array}
if phi2 < -4.999999999999985e-310Initial program 55.5%
associate-*l*55.5%
Simplified55.5%
Taylor expanded in phi2 around 0 41.7%
*-commutative41.7%
associate-*r*41.7%
*-commutative41.7%
Simplified41.7%
Taylor expanded in phi2 around -inf 12.4%
Taylor expanded in phi2 around 0 12.8%
Taylor expanded in phi1 around 0 18.9%
if -4.999999999999985e-310 < phi2 Initial program 60.1%
associate-*l*60.1%
Simplified60.1%
Taylor expanded in phi2 around 0 44.1%
*-commutative44.1%
associate-*r*44.1%
*-commutative44.1%
Simplified44.1%
Taylor expanded in phi2 around inf 12.1%
Final simplification15.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(sqrt
(-
1.0
(+
(pow (sin (* phi1 0.5)) 2.0)
(* (cos phi1) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))))))
(if (<= phi2 -5e-310)
(*
R
(*
2.0
(atan2
(*
-0.5
(*
phi2
(+
1.0
(*
(pow phi1 2.0)
(- (* (pow phi1 2.0) 0.0026041666666666665) 0.125)))))
t_0)))
(* R (* 2.0 (atan2 (* phi2 (+ -0.5 (* (pow phi1 2.0) 0.0625))) t_0))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sqrt((1.0 - (pow(sin((phi1 * 0.5)), 2.0) + (cos(phi1) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0)))));
double tmp;
if (phi2 <= -5e-310) {
tmp = R * (2.0 * atan2((-0.5 * (phi2 * (1.0 + (pow(phi1, 2.0) * ((pow(phi1, 2.0) * 0.0026041666666666665) - 0.125))))), t_0));
} else {
tmp = R * (2.0 * atan2((phi2 * (-0.5 + (pow(phi1, 2.0) * 0.0625))), t_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) :: tmp
t_0 = sqrt((1.0d0 - ((sin((phi1 * 0.5d0)) ** 2.0d0) + (cos(phi1) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)))))
if (phi2 <= (-5d-310)) then
tmp = r * (2.0d0 * atan2(((-0.5d0) * (phi2 * (1.0d0 + ((phi1 ** 2.0d0) * (((phi1 ** 2.0d0) * 0.0026041666666666665d0) - 0.125d0))))), t_0))
else
tmp = r * (2.0d0 * atan2((phi2 * ((-0.5d0) + ((phi1 ** 2.0d0) * 0.0625d0))), t_0))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sqrt((1.0 - (Math.pow(Math.sin((phi1 * 0.5)), 2.0) + (Math.cos(phi1) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)))));
double tmp;
if (phi2 <= -5e-310) {
tmp = R * (2.0 * Math.atan2((-0.5 * (phi2 * (1.0 + (Math.pow(phi1, 2.0) * ((Math.pow(phi1, 2.0) * 0.0026041666666666665) - 0.125))))), t_0));
} else {
tmp = R * (2.0 * Math.atan2((phi2 * (-0.5 + (Math.pow(phi1, 2.0) * 0.0625))), t_0));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sqrt((1.0 - (math.pow(math.sin((phi1 * 0.5)), 2.0) + (math.cos(phi1) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0))))) tmp = 0 if phi2 <= -5e-310: tmp = R * (2.0 * math.atan2((-0.5 * (phi2 * (1.0 + (math.pow(phi1, 2.0) * ((math.pow(phi1, 2.0) * 0.0026041666666666665) - 0.125))))), t_0)) else: tmp = R * (2.0 * math.atan2((phi2 * (-0.5 + (math.pow(phi1, 2.0) * 0.0625))), t_0)) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sqrt(Float64(1.0 - Float64((sin(Float64(phi1 * 0.5)) ^ 2.0) + Float64(cos(phi1) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0))))) tmp = 0.0 if (phi2 <= -5e-310) tmp = Float64(R * Float64(2.0 * atan(Float64(-0.5 * Float64(phi2 * Float64(1.0 + Float64((phi1 ^ 2.0) * Float64(Float64((phi1 ^ 2.0) * 0.0026041666666666665) - 0.125))))), t_0))); else tmp = Float64(R * Float64(2.0 * atan(Float64(phi2 * Float64(-0.5 + Float64((phi1 ^ 2.0) * 0.0625))), t_0))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sqrt((1.0 - ((sin((phi1 * 0.5)) ^ 2.0) + (cos(phi1) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0))))); tmp = 0.0; if (phi2 <= -5e-310) tmp = R * (2.0 * atan2((-0.5 * (phi2 * (1.0 + ((phi1 ^ 2.0) * (((phi1 ^ 2.0) * 0.0026041666666666665) - 0.125))))), t_0)); else tmp = R * (2.0 * atan2((phi2 * (-0.5 + ((phi1 ^ 2.0) * 0.0625))), t_0)); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi2, -5e-310], N[(R * N[(2.0 * N[ArcTan[N[(-0.5 * N[(phi2 * N[(1.0 + N[(N[Power[phi1, 2.0], $MachinePrecision] * N[(N[(N[Power[phi1, 2.0], $MachinePrecision] * 0.0026041666666666665), $MachinePrecision] - 0.125), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / t$95$0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[(phi2 * N[(-0.5 + N[(N[Power[phi1, 2.0], $MachinePrecision] * 0.0625), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / t$95$0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sqrt{1 - \left({\sin \left(\phi_1 \cdot 0.5\right)}^{2} + \cos \phi_1 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\right)}\\
\mathbf{if}\;\phi_2 \leq -5 \cdot 10^{-310}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{-0.5 \cdot \left(\phi_2 \cdot \left(1 + {\phi_1}^{2} \cdot \left({\phi_1}^{2} \cdot 0.0026041666666666665 - 0.125\right)\right)\right)}{t\_0}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\phi_2 \cdot \left(-0.5 + {\phi_1}^{2} \cdot 0.0625\right)}{t\_0}\right)\\
\end{array}
\end{array}
if phi2 < -4.999999999999985e-310Initial program 55.5%
associate-*l*55.5%
Simplified55.5%
Taylor expanded in phi2 around 0 41.7%
*-commutative41.7%
associate-*r*41.7%
*-commutative41.7%
Simplified41.7%
Taylor expanded in phi2 around -inf 12.4%
Taylor expanded in phi2 around 0 12.8%
Taylor expanded in phi1 around 0 18.9%
if -4.999999999999985e-310 < phi2 Initial program 60.1%
associate-*l*60.1%
Simplified60.1%
Taylor expanded in phi2 around 0 44.1%
*-commutative44.1%
associate-*r*44.1%
*-commutative44.1%
Simplified44.1%
Taylor expanded in phi2 around -inf 5.4%
Taylor expanded in phi2 around 0 5.7%
Taylor expanded in phi1 around 0 11.0%
+-commutative11.0%
associate-*r*11.0%
distribute-rgt-out11.0%
Simplified11.0%
Final simplification15.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(sqrt
(-
1.0
(+
(pow (sin (* phi1 0.5)) 2.0)
(* (cos phi1) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))))))
(if (<= phi2 -5e-310)
(* R (* 2.0 (atan2 (* phi2 -0.5) t_0)))
(* R (* 2.0 (atan2 (* phi2 (+ -0.5 (* (pow phi1 2.0) 0.0625))) t_0))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sqrt((1.0 - (pow(sin((phi1 * 0.5)), 2.0) + (cos(phi1) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0)))));
double tmp;
if (phi2 <= -5e-310) {
tmp = R * (2.0 * atan2((phi2 * -0.5), t_0));
} else {
tmp = R * (2.0 * atan2((phi2 * (-0.5 + (pow(phi1, 2.0) * 0.0625))), t_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) :: tmp
t_0 = sqrt((1.0d0 - ((sin((phi1 * 0.5d0)) ** 2.0d0) + (cos(phi1) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0)))))
if (phi2 <= (-5d-310)) then
tmp = r * (2.0d0 * atan2((phi2 * (-0.5d0)), t_0))
else
tmp = r * (2.0d0 * atan2((phi2 * ((-0.5d0) + ((phi1 ** 2.0d0) * 0.0625d0))), t_0))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sqrt((1.0 - (Math.pow(Math.sin((phi1 * 0.5)), 2.0) + (Math.cos(phi1) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)))));
double tmp;
if (phi2 <= -5e-310) {
tmp = R * (2.0 * Math.atan2((phi2 * -0.5), t_0));
} else {
tmp = R * (2.0 * Math.atan2((phi2 * (-0.5 + (Math.pow(phi1, 2.0) * 0.0625))), t_0));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sqrt((1.0 - (math.pow(math.sin((phi1 * 0.5)), 2.0) + (math.cos(phi1) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0))))) tmp = 0 if phi2 <= -5e-310: tmp = R * (2.0 * math.atan2((phi2 * -0.5), t_0)) else: tmp = R * (2.0 * math.atan2((phi2 * (-0.5 + (math.pow(phi1, 2.0) * 0.0625))), t_0)) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sqrt(Float64(1.0 - Float64((sin(Float64(phi1 * 0.5)) ^ 2.0) + Float64(cos(phi1) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0))))) tmp = 0.0 if (phi2 <= -5e-310) tmp = Float64(R * Float64(2.0 * atan(Float64(phi2 * -0.5), t_0))); else tmp = Float64(R * Float64(2.0 * atan(Float64(phi2 * Float64(-0.5 + Float64((phi1 ^ 2.0) * 0.0625))), t_0))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sqrt((1.0 - ((sin((phi1 * 0.5)) ^ 2.0) + (cos(phi1) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0))))); tmp = 0.0; if (phi2 <= -5e-310) tmp = R * (2.0 * atan2((phi2 * -0.5), t_0)); else tmp = R * (2.0 * atan2((phi2 * (-0.5 + ((phi1 ^ 2.0) * 0.0625))), t_0)); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi2, -5e-310], N[(R * N[(2.0 * N[ArcTan[N[(phi2 * -0.5), $MachinePrecision] / t$95$0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[(phi2 * N[(-0.5 + N[(N[Power[phi1, 2.0], $MachinePrecision] * 0.0625), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / t$95$0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sqrt{1 - \left({\sin \left(\phi_1 \cdot 0.5\right)}^{2} + \cos \phi_1 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\right)}\\
\mathbf{if}\;\phi_2 \leq -5 \cdot 10^{-310}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\phi_2 \cdot -0.5}{t\_0}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\phi_2 \cdot \left(-0.5 + {\phi_1}^{2} \cdot 0.0625\right)}{t\_0}\right)\\
\end{array}
\end{array}
if phi2 < -4.999999999999985e-310Initial program 55.5%
associate-*l*55.5%
Simplified55.5%
Taylor expanded in phi2 around 0 41.7%
*-commutative41.7%
associate-*r*41.7%
*-commutative41.7%
Simplified41.7%
Taylor expanded in phi2 around -inf 12.4%
Taylor expanded in phi2 around 0 12.8%
Taylor expanded in phi1 around 0 15.9%
*-commutative15.9%
Simplified15.9%
if -4.999999999999985e-310 < phi2 Initial program 60.1%
associate-*l*60.1%
Simplified60.1%
Taylor expanded in phi2 around 0 44.1%
*-commutative44.1%
associate-*r*44.1%
*-commutative44.1%
Simplified44.1%
Taylor expanded in phi2 around -inf 5.4%
Taylor expanded in phi2 around 0 5.7%
Taylor expanded in phi1 around 0 11.0%
+-commutative11.0%
associate-*r*11.0%
distribute-rgt-out11.0%
Simplified11.0%
Final simplification13.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(* phi2 -0.5)
(sqrt
(-
1.0
(+
(pow (sin (* phi1 0.5)) 2.0)
(* (cos phi1) (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((phi2 * -0.5), sqrt((1.0 - (pow(sin((phi1 * 0.5)), 2.0) + (cos(phi1) * 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((phi2 * (-0.5d0)), sqrt((1.0d0 - ((sin((phi1 * 0.5d0)) ** 2.0d0) + (cos(phi1) * (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((phi2 * -0.5), Math.sqrt((1.0 - (Math.pow(Math.sin((phi1 * 0.5)), 2.0) + (Math.cos(phi1) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0)))))));
}
def code(R, lambda1, lambda2, phi1, phi2): return R * (2.0 * math.atan2((phi2 * -0.5), math.sqrt((1.0 - (math.pow(math.sin((phi1 * 0.5)), 2.0) + (math.cos(phi1) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0)))))))
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(Float64(phi2 * -0.5), sqrt(Float64(1.0 - Float64((sin(Float64(phi1 * 0.5)) ^ 2.0) + Float64(cos(phi1) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) tmp = R * (2.0 * atan2((phi2 * -0.5), sqrt((1.0 - ((sin((phi1 * 0.5)) ^ 2.0) + (cos(phi1) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0))))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[(phi2 * -0.5), $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\phi_2 \cdot -0.5}{\sqrt{1 - \left({\sin \left(\phi_1 \cdot 0.5\right)}^{2} + \cos \phi_1 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\right)}}\right)
\end{array}
Initial program 57.8%
associate-*l*57.8%
Simplified57.7%
Taylor expanded in phi2 around 0 42.9%
*-commutative42.9%
associate-*r*42.9%
*-commutative42.9%
Simplified42.9%
Taylor expanded in phi2 around -inf 9.0%
Taylor expanded in phi2 around 0 9.4%
Taylor expanded in phi1 around 0 9.6%
*-commutative9.6%
Simplified9.6%
Final simplification9.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(* -0.5 (* phi2 (cos (* phi1 0.5))))
(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((-0.5 * (phi2 * cos((phi1 * 0.5)))), 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(((-0.5d0) * (phi2 * cos((phi1 * 0.5d0)))), 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((-0.5 * (phi2 * Math.cos((phi1 * 0.5)))), 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((-0.5 * (phi2 * math.cos((phi1 * 0.5)))), 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(Float64(-0.5 * Float64(phi2 * cos(Float64(phi1 * 0.5)))), 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((-0.5 * (phi2 * cos((phi1 * 0.5)))), 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[(-0.5 * N[(phi2 * N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{-0.5 \cdot \left(\phi_2 \cdot \cos \left(\phi_1 \cdot 0.5\right)\right)}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}\right)
\end{array}
Initial program 57.8%
associate-*l*57.8%
Simplified57.7%
Taylor expanded in phi2 around 0 42.9%
*-commutative42.9%
associate-*r*42.9%
*-commutative42.9%
Simplified42.9%
Taylor expanded in phi2 around -inf 9.0%
Taylor expanded in phi2 around 0 9.4%
Taylor expanded in phi1 around 0 9.4%
Final simplification9.4%
herbie shell --seed 2024181
(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))))))))))