
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_0) t_0))))
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0);
return R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0)
code = r * (2.0d0 * atan2(sqrt(t_1), sqrt((1.0d0 - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((Math.cos(phi1) * Math.cos(phi2)) * t_0) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt(t_1), Math.sqrt((1.0 - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((math.cos(phi1) * math.cos(phi2)) * t_0) * t_0) return R * (2.0 * math.atan2(math.sqrt(t_1), math.sqrt((1.0 - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0); tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$1], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) \cdot t\_0\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)
\end{array}
\end{array}
Sampling outcomes in binary64 precision:
Herbie found 27 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_0) t_0))))
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0);
return R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0)
code = r * (2.0d0 * atan2(sqrt(t_1), sqrt((1.0d0 - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((Math.cos(phi1) * Math.cos(phi2)) * t_0) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt(t_1), Math.sqrt((1.0 - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((math.cos(phi1) * math.cos(phi2)) * t_0) * t_0) return R * (2.0 * math.atan2(math.sqrt(t_1), math.sqrt((1.0 - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0); tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$1], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) \cdot t\_0\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)
\end{array}
\end{array}
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2
(pow
(fma
(cos (* -0.5 phi2))
(sin (* 0.5 phi1))
(* (sin (* -0.5 phi2)) (cos (* 0.5 phi1))))
2.0)))
(*
R
(*
2.0
(atan2
(sqrt (+ t_2 (* t_1 (* t_0 t_1))))
(sqrt
(exp
(log1p
(-
(fma
t_0
(pow
(-
(* (sin (/ lambda1 2.0)) (cos (/ lambda2 2.0)))
(* (cos (/ lambda1 2.0)) (sin (/ lambda2 2.0))))
2.0)
t_2))))))))))
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(fma(cos((-0.5 * phi2)), sin((0.5 * phi1)), (sin((-0.5 * phi2)) * cos((0.5 * phi1)))), 2.0);
return R * (2.0 * atan2(sqrt((t_2 + (t_1 * (t_0 * t_1)))), sqrt(exp(log1p(-fma(t_0, pow(((sin((lambda1 / 2.0)) * cos((lambda2 / 2.0))) - (cos((lambda1 / 2.0)) * sin((lambda2 / 2.0)))), 2.0), t_2))))));
}
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 = fma(cos(Float64(-0.5 * phi2)), sin(Float64(0.5 * phi1)), Float64(sin(Float64(-0.5 * phi2)) * cos(Float64(0.5 * phi1)))) ^ 2.0 return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_2 + Float64(t_1 * Float64(t_0 * t_1)))), sqrt(exp(log1p(Float64(-fma(t_0, (Float64(Float64(sin(Float64(lambda1 / 2.0)) * cos(Float64(lambda2 / 2.0))) - Float64(cos(Float64(lambda1 / 2.0)) * sin(Float64(lambda2 / 2.0)))) ^ 2.0), t_2)))))))) 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[(N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$2 + N[(t$95$1 * N[(t$95$0 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[Exp[N[Log[1 + (-N[(t$95$0 * N[Power[N[(N[(N[Sin[N[(lambda1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(lambda2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(lambda1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(lambda2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$2), $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 := {\left(\mathsf{fma}\left(\cos \left(-0.5 \cdot \phi_2\right), \sin \left(0.5 \cdot \phi_1\right), \sin \left(-0.5 \cdot \phi_2\right) \cdot \cos \left(0.5 \cdot \phi_1\right)\right)\right)}^{2}\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 + t\_1 \cdot \left(t\_0 \cdot t\_1\right)}}{\sqrt{e^{\mathsf{log1p}\left(-\mathsf{fma}\left(t\_0, {\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\_2\right)\right)}}}\right)
\end{array}
\end{array}
Initial program 64.4%
div-sub64.4%
sin-diff65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
Applied egg-rr65.4%
*-commutative65.4%
*-commutative65.4%
fma-neg65.4%
cos-neg65.4%
distribute-rgt-neg-in65.4%
metadata-eval65.4%
*-commutative65.4%
*-commutative65.4%
*-commutative65.4%
distribute-lft-neg-in65.4%
sin-neg65.4%
distribute-rgt-neg-in65.4%
metadata-eval65.4%
*-commutative65.4%
Simplified65.4%
div-sub64.4%
sin-diff65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
Applied egg-rr80.5%
*-commutative65.4%
*-commutative65.4%
fma-neg65.4%
cos-neg65.4%
distribute-rgt-neg-in65.4%
metadata-eval65.4%
*-commutative65.4%
*-commutative65.4%
*-commutative65.4%
distribute-lft-neg-in65.4%
sin-neg65.4%
distribute-rgt-neg-in65.4%
metadata-eval65.4%
*-commutative65.4%
Simplified80.5%
add-exp-log80.5%
sub-neg80.5%
log1p-define80.5%
Applied egg-rr80.5%
metadata-eval80.5%
div-inv80.5%
div-sub80.5%
sin-diff81.0%
Applied egg-rr81.0%
Final simplification81.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2
(pow
(fma
(cos (* -0.5 phi2))
(sin (* 0.5 phi1))
(* (sin (* -0.5 phi2)) (cos (* 0.5 phi1))))
2.0)))
(*
R
(*
2.0
(atan2
(sqrt (+ t_2 (* t_1 (* t_0 t_1))))
(log1p
(expm1
(sqrt
(-
1.0
(fma t_0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0) t_2))))))))))
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(fma(cos((-0.5 * phi2)), sin((0.5 * phi1)), (sin((-0.5 * phi2)) * cos((0.5 * phi1)))), 2.0);
return R * (2.0 * atan2(sqrt((t_2 + (t_1 * (t_0 * t_1)))), log1p(expm1(sqrt((1.0 - fma(t_0, pow(sin((0.5 * (lambda1 - lambda2))), 2.0), t_2)))))));
}
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 = fma(cos(Float64(-0.5 * phi2)), sin(Float64(0.5 * phi1)), Float64(sin(Float64(-0.5 * phi2)) * cos(Float64(0.5 * phi1)))) ^ 2.0 return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_2 + Float64(t_1 * Float64(t_0 * t_1)))), log1p(expm1(sqrt(Float64(1.0 - fma(t_0, (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0), t_2)))))))) 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[(N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$2 + N[(t$95$1 * N[(t$95$0 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Log[1 + N[(Exp[N[Sqrt[N[(1.0 - N[(t$95$0 * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]] - 1), $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 := {\left(\mathsf{fma}\left(\cos \left(-0.5 \cdot \phi_2\right), \sin \left(0.5 \cdot \phi_1\right), \sin \left(-0.5 \cdot \phi_2\right) \cdot \cos \left(0.5 \cdot \phi_1\right)\right)\right)}^{2}\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 + t\_1 \cdot \left(t\_0 \cdot t\_1\right)}}{\mathsf{log1p}\left(\mathsf{expm1}\left(\sqrt{1 - \mathsf{fma}\left(t\_0, {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}, t\_2\right)}\right)\right)}\right)
\end{array}
\end{array}
Initial program 64.4%
div-sub64.4%
sin-diff65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
Applied egg-rr65.4%
*-commutative65.4%
*-commutative65.4%
fma-neg65.4%
cos-neg65.4%
distribute-rgt-neg-in65.4%
metadata-eval65.4%
*-commutative65.4%
*-commutative65.4%
*-commutative65.4%
distribute-lft-neg-in65.4%
sin-neg65.4%
distribute-rgt-neg-in65.4%
metadata-eval65.4%
*-commutative65.4%
Simplified65.4%
div-sub64.4%
sin-diff65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
Applied egg-rr80.5%
*-commutative65.4%
*-commutative65.4%
fma-neg65.4%
cos-neg65.4%
distribute-rgt-neg-in65.4%
metadata-eval65.4%
*-commutative65.4%
*-commutative65.4%
*-commutative65.4%
distribute-lft-neg-in65.4%
sin-neg65.4%
distribute-rgt-neg-in65.4%
metadata-eval65.4%
*-commutative65.4%
Simplified80.5%
add-exp-log80.5%
sub-neg80.5%
log1p-define80.5%
Applied egg-rr80.5%
Applied egg-rr80.5%
Final simplification80.5%
(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
(fma
(cos (* -0.5 phi2))
(sin (* 0.5 phi1))
(* (sin (* -0.5 phi2)) (cos (* 0.5 phi1))))
2.0)))
(*
R
(*
2.0
(atan2
(sqrt (+ t_2 (* t_1 (* t_0 t_1))))
(pow
(pow
(- 1.0 (fma t_0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0) t_2))
1.5)
0.3333333333333333))))))
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(fma(cos((-0.5 * phi2)), sin((0.5 * phi1)), (sin((-0.5 * phi2)) * cos((0.5 * phi1)))), 2.0);
return R * (2.0 * atan2(sqrt((t_2 + (t_1 * (t_0 * t_1)))), pow(pow((1.0 - fma(t_0, pow(sin((0.5 * (lambda1 - lambda2))), 2.0), t_2)), 1.5), 0.3333333333333333)));
}
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 = fma(cos(Float64(-0.5 * phi2)), sin(Float64(0.5 * phi1)), Float64(sin(Float64(-0.5 * phi2)) * cos(Float64(0.5 * phi1)))) ^ 2.0 return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_2 + Float64(t_1 * Float64(t_0 * t_1)))), ((Float64(1.0 - fma(t_0, (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0), t_2)) ^ 1.5) ^ 0.3333333333333333)))) 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[(N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$2 + N[(t$95$1 * N[(t$95$0 * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Power[N[Power[N[(1.0 - N[(t$95$0 * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$2), $MachinePrecision]), $MachinePrecision], 1.5], $MachinePrecision], 0.3333333333333333], $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 := {\left(\mathsf{fma}\left(\cos \left(-0.5 \cdot \phi_2\right), \sin \left(0.5 \cdot \phi_1\right), \sin \left(-0.5 \cdot \phi_2\right) \cdot \cos \left(0.5 \cdot \phi_1\right)\right)\right)}^{2}\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2 + t\_1 \cdot \left(t\_0 \cdot t\_1\right)}}{{\left({\left(1 - \mathsf{fma}\left(t\_0, {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}, t\_2\right)\right)}^{1.5}\right)}^{0.3333333333333333}}\right)
\end{array}
\end{array}
Initial program 64.4%
div-sub64.4%
sin-diff65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
Applied egg-rr65.4%
*-commutative65.4%
*-commutative65.4%
fma-neg65.4%
cos-neg65.4%
distribute-rgt-neg-in65.4%
metadata-eval65.4%
*-commutative65.4%
*-commutative65.4%
*-commutative65.4%
distribute-lft-neg-in65.4%
sin-neg65.4%
distribute-rgt-neg-in65.4%
metadata-eval65.4%
*-commutative65.4%
Simplified65.4%
div-sub64.4%
sin-diff65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
Applied egg-rr80.5%
*-commutative65.4%
*-commutative65.4%
fma-neg65.4%
cos-neg65.4%
distribute-rgt-neg-in65.4%
metadata-eval65.4%
*-commutative65.4%
*-commutative65.4%
*-commutative65.4%
distribute-lft-neg-in65.4%
sin-neg65.4%
distribute-rgt-neg-in65.4%
metadata-eval65.4%
*-commutative65.4%
Simplified80.5%
add-exp-log80.5%
sub-neg80.5%
log1p-define80.5%
Applied egg-rr80.5%
Applied egg-rr80.5%
Final simplification80.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(+
(pow
(fma
(cos (* -0.5 phi2))
(sin (* 0.5 phi1))
(* (sin (* -0.5 phi2)) (cos (* 0.5 phi1))))
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(fma(cos((-0.5 * phi2)), sin((0.5 * phi1)), (sin((-0.5 * phi2)) * cos((0.5 * phi1)))), 2.0) + (t_0 * ((cos(phi1) * cos(phi2)) * t_0));
return R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64((fma(cos(Float64(-0.5 * phi2)), sin(Float64(0.5 * phi1)), Float64(sin(Float64(-0.5 * phi2)) * cos(Float64(0.5 * phi1)))) ^ 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
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[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(0.5 * phi1), $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(\mathsf{fma}\left(\cos \left(-0.5 \cdot \phi_2\right), \sin \left(0.5 \cdot \phi_1\right), \sin \left(-0.5 \cdot \phi_2\right) \cdot \cos \left(0.5 \cdot \phi_1\right)\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 64.4%
div-sub64.4%
sin-diff65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
Applied egg-rr65.4%
*-commutative65.4%
*-commutative65.4%
fma-neg65.4%
cos-neg65.4%
distribute-rgt-neg-in65.4%
metadata-eval65.4%
*-commutative65.4%
*-commutative65.4%
*-commutative65.4%
distribute-lft-neg-in65.4%
sin-neg65.4%
distribute-rgt-neg-in65.4%
metadata-eval65.4%
*-commutative65.4%
Simplified65.4%
div-sub64.4%
sin-diff65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
Applied egg-rr80.5%
*-commutative65.4%
*-commutative65.4%
fma-neg65.4%
cos-neg65.4%
distribute-rgt-neg-in65.4%
metadata-eval65.4%
*-commutative65.4%
*-commutative65.4%
*-commutative65.4%
distribute-lft-neg-in65.4%
sin-neg65.4%
distribute-rgt-neg-in65.4%
metadata-eval65.4%
*-commutative65.4%
Simplified80.5%
Final simplification80.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (* 0.5 phi1)))
(t_1 (sin (* 0.5 phi1)))
(t_2 (sin (/ (- lambda1 lambda2) 2.0)))
(t_3 (* t_2 (* (* (cos phi1) (cos phi2)) t_2))))
(*
R
(*
2.0
(atan2
(sqrt
(+
t_3
(pow (- (* t_1 (cos (* phi2 0.5))) (* t_0 (sin (* phi2 0.5)))) 2.0)))
(sqrt
(-
1.0
(+
(pow (fma (cos (* -0.5 phi2)) t_1 (* (sin (* -0.5 phi2)) t_0)) 2.0)
t_3))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((0.5 * phi1));
double t_1 = sin((0.5 * phi1));
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double t_3 = t_2 * ((cos(phi1) * cos(phi2)) * t_2);
return R * (2.0 * atan2(sqrt((t_3 + pow(((t_1 * cos((phi2 * 0.5))) - (t_0 * sin((phi2 * 0.5)))), 2.0))), sqrt((1.0 - (pow(fma(cos((-0.5 * phi2)), t_1, (sin((-0.5 * phi2)) * t_0)), 2.0) + t_3)))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(0.5 * phi1)) t_1 = sin(Float64(0.5 * phi1)) t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_3 = Float64(t_2 * Float64(Float64(cos(phi1) * cos(phi2)) * t_2)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_3 + (Float64(Float64(t_1 * cos(Float64(phi2 * 0.5))) - Float64(t_0 * sin(Float64(phi2 * 0.5)))) ^ 2.0))), sqrt(Float64(1.0 - Float64((fma(cos(Float64(-0.5 * phi2)), t_1, Float64(sin(Float64(-0.5 * phi2)) * t_0)) ^ 2.0) + t_3)))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[(t$95$2 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$3 + N[Power[N[(N[(t$95$1 * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(t$95$0 * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[(N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$1 + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$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(0.5 \cdot \phi_1\right)\\
t_1 := \sin \left(0.5 \cdot \phi_1\right)\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_3 := t\_2 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_2\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_3 + {\left(t\_1 \cdot \cos \left(\phi_2 \cdot 0.5\right) - t\_0 \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}}}{\sqrt{1 - \left({\left(\mathsf{fma}\left(\cos \left(-0.5 \cdot \phi_2\right), t\_1, \sin \left(-0.5 \cdot \phi_2\right) \cdot t\_0\right)\right)}^{2} + t\_3\right)}}\right)
\end{array}
\end{array}
Initial program 64.4%
div-sub64.4%
sin-diff65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
Applied egg-rr65.4%
*-commutative65.4%
*-commutative65.4%
fma-neg65.4%
cos-neg65.4%
distribute-rgt-neg-in65.4%
metadata-eval65.4%
*-commutative65.4%
*-commutative65.4%
*-commutative65.4%
distribute-lft-neg-in65.4%
sin-neg65.4%
distribute-rgt-neg-in65.4%
metadata-eval65.4%
*-commutative65.4%
Simplified65.4%
div-sub64.4%
sin-diff65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
Applied egg-rr80.5%
Final simplification80.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(+
(*
(cos phi1)
(* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
(pow
(+
(* (cos (* -0.5 phi2)) (sin (* 0.5 phi1)))
(* (sin (* -0.5 phi2)) (cos (* 0.5 phi1))))
2.0))))
(* R (* 2.0 (atan2 (sqrt t_0) (sqrt (- 1.0 t_0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = (cos(phi1) * (cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0))) + pow(((cos((-0.5 * phi2)) * sin((0.5 * phi1))) + (sin((-0.5 * phi2)) * cos((0.5 * phi1)))), 2.0);
return R * (2.0 * atan2(sqrt(t_0), sqrt((1.0 - t_0))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = (cos(phi1) * (cos(phi2) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0))) + (((cos(((-0.5d0) * phi2)) * sin((0.5d0 * phi1))) + (sin(((-0.5d0) * phi2)) * cos((0.5d0 * phi1)))) ** 2.0d0)
code = r * (2.0d0 * atan2(sqrt(t_0), sqrt((1.0d0 - t_0))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = (Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0))) + Math.pow(((Math.cos((-0.5 * phi2)) * Math.sin((0.5 * phi1))) + (Math.sin((-0.5 * phi2)) * Math.cos((0.5 * phi1)))), 2.0);
return R * (2.0 * Math.atan2(Math.sqrt(t_0), Math.sqrt((1.0 - t_0))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = (math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0))) + math.pow(((math.cos((-0.5 * phi2)) * math.sin((0.5 * phi1))) + (math.sin((-0.5 * phi2)) * math.cos((0.5 * phi1)))), 2.0) return R * (2.0 * math.atan2(math.sqrt(t_0), math.sqrt((1.0 - t_0))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0))) + (Float64(Float64(cos(Float64(-0.5 * phi2)) * sin(Float64(0.5 * phi1))) + Float64(sin(Float64(-0.5 * phi2)) * cos(Float64(0.5 * phi1)))) ^ 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(t_0), sqrt(Float64(1.0 - t_0))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = (cos(phi1) * (cos(phi2) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0))) + (((cos((-0.5 * phi2)) * sin((0.5 * phi1))) + (sin((-0.5 * phi2)) * cos((0.5 * phi1)))) ^ 2.0); tmp = R * (2.0 * atan2(sqrt(t_0), sqrt((1.0 - t_0)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[(N[(N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$0], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\right) + {\left(\cos \left(-0.5 \cdot \phi_2\right) \cdot \sin \left(0.5 \cdot \phi_1\right) + \sin \left(-0.5 \cdot \phi_2\right) \cdot \cos \left(0.5 \cdot \phi_1\right)\right)}^{2}\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0}}{\sqrt{1 - t\_0}}\right)
\end{array}
\end{array}
Initial program 64.4%
div-sub64.4%
sin-diff65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
Applied egg-rr65.4%
*-commutative65.4%
*-commutative65.4%
fma-neg65.4%
cos-neg65.4%
distribute-rgt-neg-in65.4%
metadata-eval65.4%
*-commutative65.4%
*-commutative65.4%
*-commutative65.4%
distribute-lft-neg-in65.4%
sin-neg65.4%
distribute-rgt-neg-in65.4%
metadata-eval65.4%
*-commutative65.4%
Simplified65.4%
div-sub64.4%
sin-diff65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
Applied egg-rr80.5%
*-commutative65.4%
*-commutative65.4%
fma-neg65.4%
cos-neg65.4%
distribute-rgt-neg-in65.4%
metadata-eval65.4%
*-commutative65.4%
*-commutative65.4%
*-commutative65.4%
distribute-lft-neg-in65.4%
sin-neg65.4%
distribute-rgt-neg-in65.4%
metadata-eval65.4%
*-commutative65.4%
Simplified80.5%
Taylor expanded in phi2 around 0 80.4%
Final simplification80.4%
(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))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt
(-
1.0
(+
(pow
(fma
(cos (* -0.5 phi2))
(sin (* 0.5 phi1))
(* (sin (* -0.5 phi2)) (cos (* 0.5 phi1))))
2.0)
t_1))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = t_0 * ((cos(phi1) * cos(phi2)) * t_0);
return R * (2.0 * atan2(sqrt((t_1 + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 - (pow(fma(cos((-0.5 * phi2)), sin((0.5 * phi1)), (sin((-0.5 * phi2)) * cos((0.5 * phi1)))), 2.0) + t_1)))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - Float64((fma(cos(Float64(-0.5 * phi2)), sin(Float64(0.5 * phi1)), Float64(sin(Float64(-0.5 * phi2)) * cos(Float64(0.5 * phi1)))) ^ 2.0) + t_1)))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[(N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{1 - \left({\left(\mathsf{fma}\left(\cos \left(-0.5 \cdot \phi_2\right), \sin \left(0.5 \cdot \phi_1\right), \sin \left(-0.5 \cdot \phi_2\right) \cdot \cos \left(0.5 \cdot \phi_1\right)\right)\right)}^{2} + t\_1\right)}}\right)
\end{array}
\end{array}
Initial program 64.4%
div-sub64.4%
sin-diff65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
Applied egg-rr65.4%
*-commutative65.4%
*-commutative65.4%
fma-neg65.4%
cos-neg65.4%
distribute-rgt-neg-in65.4%
metadata-eval65.4%
*-commutative65.4%
*-commutative65.4%
*-commutative65.4%
distribute-lft-neg-in65.4%
sin-neg65.4%
distribute-rgt-neg-in65.4%
metadata-eval65.4%
*-commutative65.4%
Simplified65.4%
Final simplification65.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(*
(cos phi1)
(* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0)))
(sqrt
(-
1.0
(+
t_0
(pow
(+
(* (cos (* -0.5 phi2)) (sin (* 0.5 phi1)))
(* (sin (* -0.5 phi2)) (cos (* 0.5 phi1))))
2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * (cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0));
return R * (2.0 * atan2(sqrt((t_0 + pow(sin((0.5 * (phi1 - phi2))), 2.0))), sqrt((1.0 - (t_0 + pow(((cos((-0.5 * phi2)) * sin((0.5 * phi1))) + (sin((-0.5 * phi2)) * cos((0.5 * phi1)))), 2.0))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = cos(phi1) * (cos(phi2) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0))
code = r * (2.0d0 * atan2(sqrt((t_0 + (sin((0.5d0 * (phi1 - phi2))) ** 2.0d0))), sqrt((1.0d0 - (t_0 + (((cos(((-0.5d0) * phi2)) * sin((0.5d0 * phi1))) + (sin(((-0.5d0) * phi2)) * cos((0.5d0 * phi1)))) ** 2.0d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((t_0 + Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0))), Math.sqrt((1.0 - (t_0 + Math.pow(((Math.cos((-0.5 * phi2)) * Math.sin((0.5 * phi1))) + (Math.sin((-0.5 * phi2)) * Math.cos((0.5 * phi1)))), 2.0))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0)) return R * (2.0 * math.atan2(math.sqrt((t_0 + math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0))), math.sqrt((1.0 - (t_0 + math.pow(((math.cos((-0.5 * phi2)) * math.sin((0.5 * phi1))) + (math.sin((-0.5 * phi2)) * math.cos((0.5 * phi1)))), 2.0))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0))) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_0 + (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0))), sqrt(Float64(1.0 - Float64(t_0 + (Float64(Float64(cos(Float64(-0.5 * phi2)) * sin(Float64(0.5 * phi1))) + Float64(sin(Float64(-0.5 * phi2)) * cos(Float64(0.5 * phi1)))) ^ 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi1) * (cos(phi2) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0)); tmp = R * (2.0 * atan2(sqrt((t_0 + (sin((0.5 * (phi1 - phi2))) ^ 2.0))), sqrt((1.0 - (t_0 + (((cos((-0.5 * phi2)) * sin((0.5 * phi1))) + (sin((-0.5 * phi2)) * cos((0.5 * phi1)))) ^ 2.0)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 + N[Power[N[(N[(N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 + {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}}}{\sqrt{1 - \left(t\_0 + {\left(\cos \left(-0.5 \cdot \phi_2\right) \cdot \sin \left(0.5 \cdot \phi_1\right) + \sin \left(-0.5 \cdot \phi_2\right) \cdot \cos \left(0.5 \cdot \phi_1\right)\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 64.4%
div-sub64.4%
sin-diff65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
Applied egg-rr65.4%
*-commutative65.4%
*-commutative65.4%
fma-neg65.4%
cos-neg65.4%
distribute-rgt-neg-in65.4%
metadata-eval65.4%
*-commutative65.4%
*-commutative65.4%
*-commutative65.4%
distribute-lft-neg-in65.4%
sin-neg65.4%
distribute-rgt-neg-in65.4%
metadata-eval65.4%
*-commutative65.4%
Simplified65.4%
Taylor expanded in phi1 around 0 65.4%
Final simplification65.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_1 (* t_0 t_1)) (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt
(fabs
(-
1.0
(fma
t_0
(+ 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 = cos(phi1) * cos(phi2);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt(((t_1 * (t_0 * t_1)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt(fabs((1.0 - fma(t_0, (0.5 + (-0.5 * cos((lambda1 - lambda2)))), pow(sin((0.5 * (phi1 - phi2))), 2.0)))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_1 * Float64(t_0 * t_1)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(abs(Float64(1.0 - fma(t_0, Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2)))), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$1 * N[(t$95$0 * t$95$1), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[Abs[N[(1.0 - N[(t$95$0 * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $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]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 \cdot \left(t\_0 \cdot t\_1\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{\left|1 - \mathsf{fma}\left(t\_0, 0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)\right|}}\right)
\end{array}
\end{array}
Initial program 64.4%
Applied egg-rr65.0%
unpow1/265.0%
unpow265.0%
rem-sqrt-square65.0%
*-commutative65.0%
cancel-sign-sub-inv65.0%
metadata-eval65.0%
*-commutative65.0%
Simplified65.0%
Final simplification65.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- lambda1 lambda2))))
(t_1 (pow t_0 2.0))
(t_2 (* (cos phi1) (cos phi2)))
(t_3
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(*
(* t_2 (sin (/ (- lambda1 lambda2) 2.0)))
(sin (* 0.5 lambda1))))))
(t_4 (* (cos phi1) t_1)))
(if (<= phi1 -2.5e+15)
(* R (* 2.0 (atan2 t_3 (sqrt (- (pow (cos (* 0.5 phi1)) 2.0) t_4)))))
(if (<= phi1 -2.25e-187)
(*
R
(*
2.0
(atan2
t_3
(sqrt (- (pow (cos (* -0.5 phi2)) 2.0) (* (cos phi2) t_1))))))
(if (<= phi1 1.56)
(*
(atan2
(hypot (sin (* 0.5 (- phi1 phi2))) (* t_0 (sqrt t_2)))
(sqrt
(-
1.0
(fma
t_2
(+ 0.5 (* -0.5 (cos (- lambda1 lambda2))))
(- 0.5 (/ (cos (- phi1 phi2)) 2.0))))))
(* R 2.0))
(*
R
(*
2.0
(atan2
t_3
(sqrt (- 1.0 (+ t_4 (pow (sin (* 0.5 phi1)) 2.0))))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (lambda1 - lambda2)));
double t_1 = pow(t_0, 2.0);
double t_2 = cos(phi1) * cos(phi2);
double t_3 = sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((t_2 * sin(((lambda1 - lambda2) / 2.0))) * sin((0.5 * lambda1)))));
double t_4 = cos(phi1) * t_1;
double tmp;
if (phi1 <= -2.5e+15) {
tmp = R * (2.0 * atan2(t_3, sqrt((pow(cos((0.5 * phi1)), 2.0) - t_4))));
} else if (phi1 <= -2.25e-187) {
tmp = R * (2.0 * atan2(t_3, sqrt((pow(cos((-0.5 * phi2)), 2.0) - (cos(phi2) * t_1)))));
} else if (phi1 <= 1.56) {
tmp = atan2(hypot(sin((0.5 * (phi1 - phi2))), (t_0 * sqrt(t_2))), sqrt((1.0 - fma(t_2, (0.5 + (-0.5 * cos((lambda1 - lambda2)))), (0.5 - (cos((phi1 - phi2)) / 2.0)))))) * (R * 2.0);
} else {
tmp = R * (2.0 * atan2(t_3, sqrt((1.0 - (t_4 + pow(sin((0.5 * phi1)), 2.0))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) t_1 = t_0 ^ 2.0 t_2 = Float64(cos(phi1) * cos(phi2)) t_3 = sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(t_2 * sin(Float64(Float64(lambda1 - lambda2) / 2.0))) * sin(Float64(0.5 * lambda1))))) t_4 = Float64(cos(phi1) * t_1) tmp = 0.0 if (phi1 <= -2.5e+15) tmp = Float64(R * Float64(2.0 * atan(t_3, sqrt(Float64((cos(Float64(0.5 * phi1)) ^ 2.0) - t_4))))); elseif (phi1 <= -2.25e-187) tmp = Float64(R * Float64(2.0 * atan(t_3, sqrt(Float64((cos(Float64(-0.5 * phi2)) ^ 2.0) - Float64(cos(phi2) * t_1)))))); elseif (phi1 <= 1.56) tmp = Float64(atan(hypot(sin(Float64(0.5 * Float64(phi1 - phi2))), Float64(t_0 * sqrt(t_2))), sqrt(Float64(1.0 - fma(t_2, Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2)))), Float64(0.5 - Float64(cos(Float64(phi1 - phi2)) / 2.0)))))) * Float64(R * 2.0)); else tmp = Float64(R * Float64(2.0 * atan(t_3, sqrt(Float64(1.0 - Float64(t_4 + (sin(Float64(0.5 * phi1)) ^ 2.0))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[t$95$0, 2.0], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(t$95$2 * N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[(N[Cos[phi1], $MachinePrecision] * t$95$1), $MachinePrecision]}, If[LessEqual[phi1, -2.5e+15], N[(R * N[(2.0 * N[ArcTan[t$95$3 / N[Sqrt[N[(N[Power[N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - t$95$4), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[phi1, -2.25e-187], N[(R * N[(2.0 * N[ArcTan[t$95$3 / N[Sqrt[N[(N[Power[N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi2], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[phi1, 1.56], N[(N[ArcTan[N[Sqrt[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] ^ 2 + N[(t$95$0 * N[Sqrt[t$95$2], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$2 * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(0.5 - N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(R * 2.0), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$3 / N[Sqrt[N[(1.0 - N[(t$95$4 + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\\
t_1 := {t\_0}^{2}\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
t_3 := \sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(t\_2 \cdot \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\right) \cdot \sin \left(0.5 \cdot \lambda_1\right)}\\
t_4 := \cos \phi_1 \cdot t\_1\\
\mathbf{if}\;\phi_1 \leq -2.5 \cdot 10^{+15}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_3}{\sqrt{{\cos \left(0.5 \cdot \phi_1\right)}^{2} - t\_4}}\right)\\
\mathbf{elif}\;\phi_1 \leq -2.25 \cdot 10^{-187}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_3}{\sqrt{{\cos \left(-0.5 \cdot \phi_2\right)}^{2} - \cos \phi_2 \cdot t\_1}}\right)\\
\mathbf{elif}\;\phi_1 \leq 1.56:\\
\;\;\;\;\tan^{-1}_* \frac{\mathsf{hypot}\left(\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right), t\_0 \cdot \sqrt{t\_2}\right)}{\sqrt{1 - \mathsf{fma}\left(t\_2, 0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), 0.5 - \frac{\cos \left(\phi_1 - \phi_2\right)}{2}\right)}} \cdot \left(R \cdot 2\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_3}{\sqrt{1 - \left(t\_4 + {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)}}\right)\\
\end{array}
\end{array}
if phi1 < -2.5e15Initial program 51.1%
Taylor expanded in lambda2 around 0 47.2%
Taylor expanded in phi2 around 0 48.8%
+-commutative52.8%
associate--r+52.8%
unpow252.8%
1-sub-sin52.9%
unpow252.9%
*-commutative52.9%
Simplified49.0%
if -2.5e15 < phi1 < -2.2499999999999999e-187Initial program 84.8%
Taylor expanded in lambda2 around 0 61.5%
Taylor expanded in phi1 around 0 61.7%
+-commutative85.0%
associate--r+85.0%
unpow285.0%
1-sub-sin85.0%
unpow285.0%
Simplified61.8%
if -2.2499999999999999e-187 < phi1 < 1.5600000000000001Initial program 80.2%
associate-*r*80.2%
*-commutative80.2%
Simplified80.3%
Applied egg-rr66.2%
*-lft-identity66.2%
*-commutative66.2%
*-commutative66.2%
*-commutative66.2%
*-commutative66.2%
Simplified66.2%
flip--55.6%
div-inv54.3%
pow254.3%
pow254.3%
Applied egg-rr54.3%
+-commutative54.3%
Simplified54.3%
*-commutative54.3%
un-div-inv55.6%
unpow255.6%
unpow255.6%
+-commutative55.6%
flip--66.2%
metadata-eval66.2%
div-inv66.2%
unpow266.2%
sin-mult66.2%
Applied egg-rr66.2%
div-sub66.2%
+-inverses66.2%
cos-066.2%
metadata-eval66.2%
distribute-rgt-out66.2%
metadata-eval66.2%
*-rgt-identity66.2%
Simplified66.2%
if 1.5600000000000001 < phi1 Initial program 46.3%
Taylor expanded in lambda2 around 0 34.2%
Taylor expanded in phi2 around 0 34.7%
Final simplification52.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(*
(* t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(sin (* 0.5 lambda1))))))
(t_2 (sin (* 0.5 (- lambda1 lambda2))))
(t_3 (pow t_2 2.0))
(t_4
(*
R
(*
2.0
(atan2
t_1
(sqrt (- (pow (cos (* 0.5 phi1)) 2.0) (* (cos phi1) t_3))))))))
(if (<= phi1 -2.5e+15)
t_4
(if (<= phi1 -1.02e-182)
(*
R
(*
2.0
(atan2
t_1
(sqrt (- (pow (cos (* -0.5 phi2)) 2.0) (* (cos phi2) t_3))))))
(if (<= phi1 0.7)
(*
(atan2
(hypot (sin (* 0.5 (- phi1 phi2))) (* t_2 (sqrt t_0)))
(sqrt
(-
1.0
(fma
t_0
(+ 0.5 (* -0.5 (cos (- lambda1 lambda2))))
(- 0.5 (/ (cos (- phi1 phi2)) 2.0))))))
(* R 2.0))
t_4)))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((t_0 * sin(((lambda1 - lambda2) / 2.0))) * sin((0.5 * lambda1)))));
double t_2 = sin((0.5 * (lambda1 - lambda2)));
double t_3 = pow(t_2, 2.0);
double t_4 = R * (2.0 * atan2(t_1, sqrt((pow(cos((0.5 * phi1)), 2.0) - (cos(phi1) * t_3)))));
double tmp;
if (phi1 <= -2.5e+15) {
tmp = t_4;
} else if (phi1 <= -1.02e-182) {
tmp = R * (2.0 * atan2(t_1, sqrt((pow(cos((-0.5 * phi2)), 2.0) - (cos(phi2) * t_3)))));
} else if (phi1 <= 0.7) {
tmp = atan2(hypot(sin((0.5 * (phi1 - phi2))), (t_2 * sqrt(t_0))), sqrt((1.0 - fma(t_0, (0.5 + (-0.5 * cos((lambda1 - lambda2)))), (0.5 - (cos((phi1 - phi2)) / 2.0)))))) * (R * 2.0);
} else {
tmp = t_4;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(t_0 * sin(Float64(Float64(lambda1 - lambda2) / 2.0))) * sin(Float64(0.5 * lambda1))))) t_2 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) t_3 = t_2 ^ 2.0 t_4 = Float64(R * Float64(2.0 * atan(t_1, sqrt(Float64((cos(Float64(0.5 * phi1)) ^ 2.0) - Float64(cos(phi1) * t_3)))))) tmp = 0.0 if (phi1 <= -2.5e+15) tmp = t_4; elseif (phi1 <= -1.02e-182) tmp = Float64(R * Float64(2.0 * atan(t_1, sqrt(Float64((cos(Float64(-0.5 * phi2)) ^ 2.0) - Float64(cos(phi2) * t_3)))))); elseif (phi1 <= 0.7) tmp = Float64(atan(hypot(sin(Float64(0.5 * Float64(phi1 - phi2))), Float64(t_2 * sqrt(t_0))), sqrt(Float64(1.0 - fma(t_0, Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2)))), Float64(0.5 - Float64(cos(Float64(phi1 - phi2)) / 2.0)))))) * Float64(R * 2.0)); else tmp = t_4; end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(t$95$0 * N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Power[t$95$2, 2.0], $MachinePrecision]}, Block[{t$95$4 = N[(R * N[(2.0 * N[ArcTan[t$95$1 / N[Sqrt[N[(N[Power[N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi1], $MachinePrecision] * t$95$3), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[phi1, -2.5e+15], t$95$4, If[LessEqual[phi1, -1.02e-182], N[(R * N[(2.0 * N[ArcTan[t$95$1 / N[Sqrt[N[(N[Power[N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi2], $MachinePrecision] * t$95$3), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[phi1, 0.7], N[(N[ArcTan[N[Sqrt[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] ^ 2 + N[(t$95$2 * N[Sqrt[t$95$0], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(0.5 - N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(R * 2.0), $MachinePrecision]), $MachinePrecision], t$95$4]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(t\_0 \cdot \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\right) \cdot \sin \left(0.5 \cdot \lambda_1\right)}\\
t_2 := \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\\
t_3 := {t\_2}^{2}\\
t_4 := R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_1}{\sqrt{{\cos \left(0.5 \cdot \phi_1\right)}^{2} - \cos \phi_1 \cdot t\_3}}\right)\\
\mathbf{if}\;\phi_1 \leq -2.5 \cdot 10^{+15}:\\
\;\;\;\;t\_4\\
\mathbf{elif}\;\phi_1 \leq -1.02 \cdot 10^{-182}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_1}{\sqrt{{\cos \left(-0.5 \cdot \phi_2\right)}^{2} - \cos \phi_2 \cdot t\_3}}\right)\\
\mathbf{elif}\;\phi_1 \leq 0.7:\\
\;\;\;\;\tan^{-1}_* \frac{\mathsf{hypot}\left(\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right), t\_2 \cdot \sqrt{t\_0}\right)}{\sqrt{1 - \mathsf{fma}\left(t\_0, 0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), 0.5 - \frac{\cos \left(\phi_1 - \phi_2\right)}{2}\right)}} \cdot \left(R \cdot 2\right)\\
\mathbf{else}:\\
\;\;\;\;t\_4\\
\end{array}
\end{array}
if phi1 < -2.5e15 or 0.69999999999999996 < phi1 Initial program 48.5%
Taylor expanded in lambda2 around 0 40.1%
Taylor expanded in phi2 around 0 41.2%
+-commutative49.5%
associate--r+49.5%
unpow249.5%
1-sub-sin49.6%
unpow249.6%
*-commutative49.6%
Simplified41.2%
if -2.5e15 < phi1 < -1.02e-182Initial program 84.8%
Taylor expanded in lambda2 around 0 61.5%
Taylor expanded in phi1 around 0 61.7%
+-commutative85.0%
associate--r+85.0%
unpow285.0%
1-sub-sin85.0%
unpow285.0%
Simplified61.8%
if -1.02e-182 < phi1 < 0.69999999999999996Initial program 80.2%
associate-*r*80.2%
*-commutative80.2%
Simplified80.3%
Applied egg-rr66.2%
*-lft-identity66.2%
*-commutative66.2%
*-commutative66.2%
*-commutative66.2%
*-commutative66.2%
Simplified66.2%
flip--55.6%
div-inv54.3%
pow254.3%
pow254.3%
Applied egg-rr54.3%
+-commutative54.3%
Simplified54.3%
*-commutative54.3%
un-div-inv55.6%
unpow255.6%
unpow255.6%
+-commutative55.6%
flip--66.2%
metadata-eval66.2%
div-inv66.2%
unpow266.2%
sin-mult66.2%
Applied egg-rr66.2%
div-sub66.2%
+-inverses66.2%
cos-066.2%
metadata-eval66.2%
distribute-rgt-out66.2%
metadata-eval66.2%
*-rgt-identity66.2%
Simplified66.2%
Final simplification52.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* t_0 (* (* (cos phi1) (cos phi2)) t_0))))
(*
R
(*
2.0
(atan2
(sqrt (+ t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (+ 1.0 (- (- (/ (cos (- phi1 phi2)) 2.0) 0.5) t_1))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = t_0 * ((cos(phi1) * cos(phi2)) * t_0);
return R * (2.0 * atan2(sqrt((t_1 + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 + (((cos((phi1 - phi2)) / 2.0) - 0.5) - t_1)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = t_0 * ((cos(phi1) * cos(phi2)) * t_0)
code = r * (2.0d0 * atan2(sqrt((t_1 + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt((1.0d0 + (((cos((phi1 - phi2)) / 2.0d0) - 0.5d0) - t_1)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt((t_1 + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt((1.0 + (((Math.cos((phi1 - phi2)) / 2.0) - 0.5) - t_1)))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = t_0 * ((math.cos(phi1) * math.cos(phi2)) * t_0) return R * (2.0 * math.atan2(math.sqrt((t_1 + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt((1.0 + (((math.cos((phi1 - phi2)) / 2.0) - 0.5) - t_1)))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(t_1 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 + Float64(Float64(Float64(cos(Float64(phi1 - phi2)) / 2.0) - 0.5) - t_1)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = t_0 * ((cos(phi1) * cos(phi2)) * t_0); tmp = R * (2.0 * atan2(sqrt((t_1 + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt((1.0 + (((cos((phi1 - phi2)) / 2.0) - 0.5) - t_1))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 + N[(N[(N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision] - 0.5), $MachinePrecision] - t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{1 + \left(\left(\frac{\cos \left(\phi_1 - \phi_2\right)}{2} - 0.5\right) - t\_1\right)}}\right)
\end{array}
\end{array}
Initial program 64.4%
unpow264.4%
sin-mult64.5%
div-inv64.5%
metadata-eval64.5%
div-inv64.5%
metadata-eval64.5%
div-inv64.5%
metadata-eval64.5%
div-inv64.5%
metadata-eval64.5%
Applied egg-rr64.5%
div-sub64.5%
+-inverses64.5%
cos-064.5%
metadata-eval64.5%
distribute-lft-out64.5%
metadata-eval64.5%
*-rgt-identity64.5%
Simplified64.5%
Final simplification64.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(sqrt
(+
(* t_0 (* (* (cos phi1) (cos phi2)) t_0))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0))))
(t_2 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
(if (or (<= phi1 -2.5e+15) (not (<= phi1 8e-12)))
(*
R
(*
2.0
(atan2 t_1 (sqrt (- (pow (cos (* 0.5 phi1)) 2.0) (* (cos phi1) t_2))))))
(*
R
(*
2.0
(atan2
t_1
(sqrt (- (pow (cos (* -0.5 phi2)) 2.0) (* (cos phi2) t_2)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = sqrt(((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0)));
double t_2 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double tmp;
if ((phi1 <= -2.5e+15) || !(phi1 <= 8e-12)) {
tmp = R * (2.0 * atan2(t_1, sqrt((pow(cos((0.5 * phi1)), 2.0) - (cos(phi1) * t_2)))));
} else {
tmp = R * (2.0 * atan2(t_1, sqrt((pow(cos((-0.5 * phi2)), 2.0) - (cos(phi2) * t_2)))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = sqrt(((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0)))
t_2 = sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0
if ((phi1 <= (-2.5d+15)) .or. (.not. (phi1 <= 8d-12))) then
tmp = r * (2.0d0 * atan2(t_1, sqrt(((cos((0.5d0 * phi1)) ** 2.0d0) - (cos(phi1) * t_2)))))
else
tmp = r * (2.0d0 * atan2(t_1, sqrt(((cos(((-0.5d0) * phi2)) ** 2.0d0) - (cos(phi2) * t_2)))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.sqrt(((t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0)) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0)));
double t_2 = Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0);
double tmp;
if ((phi1 <= -2.5e+15) || !(phi1 <= 8e-12)) {
tmp = R * (2.0 * Math.atan2(t_1, Math.sqrt((Math.pow(Math.cos((0.5 * phi1)), 2.0) - (Math.cos(phi1) * t_2)))));
} else {
tmp = R * (2.0 * Math.atan2(t_1, Math.sqrt((Math.pow(Math.cos((-0.5 * phi2)), 2.0) - (Math.cos(phi2) * t_2)))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.sqrt(((t_0 * ((math.cos(phi1) * math.cos(phi2)) * t_0)) + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))) t_2 = math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0) tmp = 0 if (phi1 <= -2.5e+15) or not (phi1 <= 8e-12): tmp = R * (2.0 * math.atan2(t_1, math.sqrt((math.pow(math.cos((0.5 * phi1)), 2.0) - (math.cos(phi1) * t_2))))) else: tmp = R * (2.0 * math.atan2(t_1, math.sqrt((math.pow(math.cos((-0.5 * phi2)), 2.0) - (math.cos(phi2) * t_2))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sqrt(Float64(Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))) t_2 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 tmp = 0.0 if ((phi1 <= -2.5e+15) || !(phi1 <= 8e-12)) tmp = Float64(R * Float64(2.0 * atan(t_1, sqrt(Float64((cos(Float64(0.5 * phi1)) ^ 2.0) - Float64(cos(phi1) * t_2)))))); else tmp = Float64(R * Float64(2.0 * atan(t_1, sqrt(Float64((cos(Float64(-0.5 * phi2)) ^ 2.0) - Float64(cos(phi2) * t_2)))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = sqrt(((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))); t_2 = sin((0.5 * (lambda1 - lambda2))) ^ 2.0; tmp = 0.0; if ((phi1 <= -2.5e+15) || ~((phi1 <= 8e-12))) tmp = R * (2.0 * atan2(t_1, sqrt(((cos((0.5 * phi1)) ^ 2.0) - (cos(phi1) * t_2))))); else tmp = R * (2.0 * atan2(t_1, sqrt(((cos((-0.5 * phi2)) ^ 2.0) - (cos(phi2) * t_2))))); 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[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $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, -2.5e+15], N[Not[LessEqual[phi1, 8e-12]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[t$95$1 / N[Sqrt[N[(N[Power[N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi1], $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$1 / N[Sqrt[N[(N[Power[N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi2], $MachinePrecision] * t$95$2), $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 := \sqrt{t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}\\
t_2 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
\mathbf{if}\;\phi_1 \leq -2.5 \cdot 10^{+15} \lor \neg \left(\phi_1 \leq 8 \cdot 10^{-12}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_1}{\sqrt{{\cos \left(0.5 \cdot \phi_1\right)}^{2} - \cos \phi_1 \cdot t\_2}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_1}{\sqrt{{\cos \left(-0.5 \cdot \phi_2\right)}^{2} - \cos \phi_2 \cdot t\_2}}\right)\\
\end{array}
\end{array}
if phi1 < -2.5e15 or 7.99999999999999984e-12 < phi1 Initial program 48.3%
Taylor expanded in phi2 around 0 49.3%
+-commutative49.3%
associate--r+49.3%
unpow249.3%
1-sub-sin49.4%
unpow249.4%
*-commutative49.4%
Simplified49.4%
if -2.5e15 < phi1 < 7.99999999999999984e-12Initial program 82.2%
Taylor expanded in phi1 around 0 82.3%
+-commutative82.3%
associate--r+82.3%
unpow282.3%
1-sub-sin82.3%
unpow282.3%
Simplified82.3%
Final simplification65.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))
(t_1 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_2 (* (cos phi1) t_1))
(t_3 (sin (/ (- lambda1 lambda2) 2.0)))
(t_4 (* (* (cos phi1) (cos phi2)) t_3))
(t_5 (sqrt (+ t_0 (* t_4 (sin (* 0.5 lambda1)))))))
(if (<= phi1 -2.5e+15)
(* R (* 2.0 (atan2 t_5 (sqrt (- (pow (cos (* 0.5 phi1)) 2.0) t_2)))))
(if (<= phi1 0.000145)
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_3 t_4) t_0))
(sqrt (- (pow (cos (* -0.5 phi2)) 2.0) (* (cos phi2) t_1))))))
(*
R
(*
2.0
(atan2 t_5 (sqrt (- 1.0 (+ t_2 (pow (sin (* 0.5 phi1)) 2.0)))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double t_1 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_2 = cos(phi1) * t_1;
double t_3 = sin(((lambda1 - lambda2) / 2.0));
double t_4 = (cos(phi1) * cos(phi2)) * t_3;
double t_5 = sqrt((t_0 + (t_4 * sin((0.5 * lambda1)))));
double tmp;
if (phi1 <= -2.5e+15) {
tmp = R * (2.0 * atan2(t_5, sqrt((pow(cos((0.5 * phi1)), 2.0) - t_2))));
} else if (phi1 <= 0.000145) {
tmp = R * (2.0 * atan2(sqrt(((t_3 * t_4) + t_0)), sqrt((pow(cos((-0.5 * phi2)), 2.0) - (cos(phi2) * t_1)))));
} else {
tmp = R * (2.0 * atan2(t_5, sqrt((1.0 - (t_2 + pow(sin((0.5 * phi1)), 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) :: t_5
real(8) :: tmp
t_0 = sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0
t_1 = sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0
t_2 = cos(phi1) * t_1
t_3 = sin(((lambda1 - lambda2) / 2.0d0))
t_4 = (cos(phi1) * cos(phi2)) * t_3
t_5 = sqrt((t_0 + (t_4 * sin((0.5d0 * lambda1)))))
if (phi1 <= (-2.5d+15)) then
tmp = r * (2.0d0 * atan2(t_5, sqrt(((cos((0.5d0 * phi1)) ** 2.0d0) - t_2))))
else if (phi1 <= 0.000145d0) then
tmp = r * (2.0d0 * atan2(sqrt(((t_3 * t_4) + t_0)), sqrt(((cos(((-0.5d0) * phi2)) ** 2.0d0) - (cos(phi2) * t_1)))))
else
tmp = r * (2.0d0 * atan2(t_5, sqrt((1.0d0 - (t_2 + (sin((0.5d0 * phi1)) ** 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.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0);
double t_1 = Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_2 = Math.cos(phi1) * t_1;
double t_3 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_4 = (Math.cos(phi1) * Math.cos(phi2)) * t_3;
double t_5 = Math.sqrt((t_0 + (t_4 * Math.sin((0.5 * lambda1)))));
double tmp;
if (phi1 <= -2.5e+15) {
tmp = R * (2.0 * Math.atan2(t_5, Math.sqrt((Math.pow(Math.cos((0.5 * phi1)), 2.0) - t_2))));
} else if (phi1 <= 0.000145) {
tmp = R * (2.0 * Math.atan2(Math.sqrt(((t_3 * t_4) + t_0)), Math.sqrt((Math.pow(Math.cos((-0.5 * phi2)), 2.0) - (Math.cos(phi2) * t_1)))));
} else {
tmp = R * (2.0 * Math.atan2(t_5, Math.sqrt((1.0 - (t_2 + Math.pow(Math.sin((0.5 * phi1)), 2.0))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) t_1 = math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0) t_2 = math.cos(phi1) * t_1 t_3 = math.sin(((lambda1 - lambda2) / 2.0)) t_4 = (math.cos(phi1) * math.cos(phi2)) * t_3 t_5 = math.sqrt((t_0 + (t_4 * math.sin((0.5 * lambda1))))) tmp = 0 if phi1 <= -2.5e+15: tmp = R * (2.0 * math.atan2(t_5, math.sqrt((math.pow(math.cos((0.5 * phi1)), 2.0) - t_2)))) elif phi1 <= 0.000145: tmp = R * (2.0 * math.atan2(math.sqrt(((t_3 * t_4) + t_0)), math.sqrt((math.pow(math.cos((-0.5 * phi2)), 2.0) - (math.cos(phi2) * t_1))))) else: tmp = R * (2.0 * math.atan2(t_5, math.sqrt((1.0 - (t_2 + math.pow(math.sin((0.5 * phi1)), 2.0)))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 t_1 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_2 = Float64(cos(phi1) * t_1) t_3 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_4 = Float64(Float64(cos(phi1) * cos(phi2)) * t_3) t_5 = sqrt(Float64(t_0 + Float64(t_4 * sin(Float64(0.5 * lambda1))))) tmp = 0.0 if (phi1 <= -2.5e+15) tmp = Float64(R * Float64(2.0 * atan(t_5, sqrt(Float64((cos(Float64(0.5 * phi1)) ^ 2.0) - t_2))))); elseif (phi1 <= 0.000145) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_3 * t_4) + t_0)), sqrt(Float64((cos(Float64(-0.5 * phi2)) ^ 2.0) - Float64(cos(phi2) * t_1)))))); else tmp = Float64(R * Float64(2.0 * atan(t_5, sqrt(Float64(1.0 - Float64(t_2 + (sin(Float64(0.5 * phi1)) ^ 2.0))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((phi1 - phi2) / 2.0)) ^ 2.0; t_1 = sin((0.5 * (lambda1 - lambda2))) ^ 2.0; t_2 = cos(phi1) * t_1; t_3 = sin(((lambda1 - lambda2) / 2.0)); t_4 = (cos(phi1) * cos(phi2)) * t_3; t_5 = sqrt((t_0 + (t_4 * sin((0.5 * lambda1))))); tmp = 0.0; if (phi1 <= -2.5e+15) tmp = R * (2.0 * atan2(t_5, sqrt(((cos((0.5 * phi1)) ^ 2.0) - t_2)))); elseif (phi1 <= 0.000145) tmp = R * (2.0 * atan2(sqrt(((t_3 * t_4) + t_0)), sqrt(((cos((-0.5 * phi2)) ^ 2.0) - (cos(phi2) * t_1))))); else tmp = R * (2.0 * atan2(t_5, sqrt((1.0 - (t_2 + (sin((0.5 * phi1)) ^ 2.0)))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * t$95$1), $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$3), $MachinePrecision]}, Block[{t$95$5 = N[Sqrt[N[(t$95$0 + N[(t$95$4 * N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi1, -2.5e+15], N[(R * N[(2.0 * N[ArcTan[t$95$5 / N[Sqrt[N[(N[Power[N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - t$95$2), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[phi1, 0.000145], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$3 * t$95$4), $MachinePrecision] + t$95$0), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi2], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$5 / N[Sqrt[N[(1.0 - N[(t$95$2 + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
t_1 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_2 := \cos \phi_1 \cdot t\_1\\
t_3 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_4 := \left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_3\\
t_5 := \sqrt{t\_0 + t\_4 \cdot \sin \left(0.5 \cdot \lambda_1\right)}\\
\mathbf{if}\;\phi_1 \leq -2.5 \cdot 10^{+15}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_5}{\sqrt{{\cos \left(0.5 \cdot \phi_1\right)}^{2} - t\_2}}\right)\\
\mathbf{elif}\;\phi_1 \leq 0.000145:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_3 \cdot t\_4 + t\_0}}{\sqrt{{\cos \left(-0.5 \cdot \phi_2\right)}^{2} - \cos \phi_2 \cdot t\_1}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_5}{\sqrt{1 - \left(t\_2 + {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)}}\right)\\
\end{array}
\end{array}
if phi1 < -2.5e15Initial program 51.1%
Taylor expanded in lambda2 around 0 47.2%
Taylor expanded in phi2 around 0 48.8%
+-commutative52.8%
associate--r+52.8%
unpow252.8%
1-sub-sin52.9%
unpow252.9%
*-commutative52.9%
Simplified49.0%
if -2.5e15 < phi1 < 1.45e-4Initial program 81.7%
Taylor expanded in phi1 around 0 81.8%
+-commutative81.8%
associate--r+81.8%
unpow281.8%
1-sub-sin81.7%
unpow281.7%
Simplified81.7%
if 1.45e-4 < phi1 Initial program 46.3%
Taylor expanded in lambda2 around 0 34.2%
Taylor expanded in phi2 around 0 34.7%
Final simplification60.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (* 0.5 (- lambda1 lambda2)))))
(if (or (<= phi2 -15000000000000.0) (not (<= phi2 1.55e+34)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* t_0 (sin (/ (- lambda1 lambda2) 2.0))) (sin (* 0.5 lambda1)))))
(sqrt
(- (pow (cos (* -0.5 phi2)) 2.0) (* (cos phi2) (pow t_1 2.0)))))))
(*
(atan2
(hypot (sin (* 0.5 (- phi1 phi2))) (* t_1 (sqrt t_0)))
(sqrt
(-
1.0
(fma
t_0
(+ 0.5 (* -0.5 (cos (- lambda1 lambda2))))
(- 0.5 (/ (cos (- phi1 phi2)) 2.0))))))
(* R 2.0)))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = sin((0.5 * (lambda1 - lambda2)));
double tmp;
if ((phi2 <= -15000000000000.0) || !(phi2 <= 1.55e+34)) {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((t_0 * sin(((lambda1 - lambda2) / 2.0))) * sin((0.5 * lambda1))))), sqrt((pow(cos((-0.5 * phi2)), 2.0) - (cos(phi2) * pow(t_1, 2.0))))));
} else {
tmp = atan2(hypot(sin((0.5 * (phi1 - phi2))), (t_1 * sqrt(t_0))), sqrt((1.0 - fma(t_0, (0.5 + (-0.5 * cos((lambda1 - lambda2)))), (0.5 - (cos((phi1 - phi2)) / 2.0)))))) * (R * 2.0);
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) tmp = 0.0 if ((phi2 <= -15000000000000.0) || !(phi2 <= 1.55e+34)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(t_0 * sin(Float64(Float64(lambda1 - lambda2) / 2.0))) * sin(Float64(0.5 * lambda1))))), sqrt(Float64((cos(Float64(-0.5 * phi2)) ^ 2.0) - Float64(cos(phi2) * (t_1 ^ 2.0))))))); else tmp = Float64(atan(hypot(sin(Float64(0.5 * Float64(phi1 - phi2))), Float64(t_1 * sqrt(t_0))), sqrt(Float64(1.0 - fma(t_0, Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2)))), Float64(0.5 - Float64(cos(Float64(phi1 - phi2)) / 2.0)))))) * Float64(R * 2.0)); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[phi2, -15000000000000.0], N[Not[LessEqual[phi2, 1.55e+34]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(t$95$0 * N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi2], $MachinePrecision] * N[Power[t$95$1, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[ArcTan[N[Sqrt[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] ^ 2 + N[(t$95$1 * N[Sqrt[t$95$0], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(0.5 - N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(R * 2.0), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\\
\mathbf{if}\;\phi_2 \leq -15000000000000 \lor \neg \left(\phi_2 \leq 1.55 \cdot 10^{+34}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(t\_0 \cdot \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\right) \cdot \sin \left(0.5 \cdot \lambda_1\right)}}{\sqrt{{\cos \left(-0.5 \cdot \phi_2\right)}^{2} - \cos \phi_2 \cdot {t\_1}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;\tan^{-1}_* \frac{\mathsf{hypot}\left(\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right), t\_1 \cdot \sqrt{t\_0}\right)}{\sqrt{1 - \mathsf{fma}\left(t\_0, 0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), 0.5 - \frac{\cos \left(\phi_1 - \phi_2\right)}{2}\right)}} \cdot \left(R \cdot 2\right)\\
\end{array}
\end{array}
if phi2 < -1.5e13 or 1.54999999999999989e34 < phi2 Initial program 49.7%
Taylor expanded in lambda2 around 0 39.5%
Taylor expanded in phi1 around 0 40.7%
+-commutative50.7%
associate--r+50.7%
unpow250.7%
1-sub-sin50.7%
unpow250.7%
Simplified40.7%
if -1.5e13 < phi2 < 1.54999999999999989e34Initial program 77.9%
associate-*r*77.9%
*-commutative77.9%
Simplified77.9%
Applied egg-rr55.1%
*-lft-identity55.1%
*-commutative55.1%
*-commutative55.1%
*-commutative55.1%
*-commutative55.1%
Simplified55.1%
flip--45.4%
div-inv44.5%
pow244.5%
pow244.5%
Applied egg-rr44.5%
+-commutative44.5%
Simplified44.5%
*-commutative44.5%
un-div-inv45.4%
unpow245.4%
unpow245.4%
+-commutative45.4%
flip--55.1%
metadata-eval55.1%
div-inv55.1%
unpow255.1%
sin-mult55.1%
Applied egg-rr55.1%
div-sub55.1%
+-inverses55.1%
cos-055.1%
metadata-eval55.1%
distribute-rgt-out55.1%
metadata-eval55.1%
*-rgt-identity55.1%
Simplified55.1%
Final simplification48.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_1 (* t_0 t_1)) (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt
(+
(- 1.0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0))
(* t_0 (- (* 0.5 (cos (- lambda1 lambda2))) 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));
return R * (2.0 * atan2(sqrt(((t_1 * (t_0 * t_1)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt(((1.0 - pow(sin((0.5 * (phi1 - phi2))), 2.0)) + (t_0 * ((0.5 * cos((lambda1 - lambda2))) - 0.5))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = cos(phi1) * cos(phi2)
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2(sqrt(((t_1 * (t_0 * t_1)) + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt(((1.0d0 - (sin((0.5d0 * (phi1 - phi2))) ** 2.0d0)) + (t_0 * ((0.5d0 * cos((lambda1 - lambda2))) - 0.5d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.cos(phi1) * Math.cos(phi2);
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * Math.atan2(Math.sqrt(((t_1 * (t_0 * t_1)) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt(((1.0 - Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0)) + (t_0 * ((0.5 * Math.cos((lambda1 - lambda2))) - 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)) return R * (2.0 * math.atan2(math.sqrt(((t_1 * (t_0 * t_1)) + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt(((1.0 - math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0)) + (t_0 * ((0.5 * math.cos((lambda1 - lambda2))) - 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)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_1 * Float64(t_0 * t_1)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(Float64(1.0 - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)) + Float64(t_0 * Float64(Float64(0.5 * cos(Float64(lambda1 - lambda2))) - 0.5))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi1) * cos(phi2); t_1 = sin(((lambda1 - lambda2) / 2.0)); tmp = R * (2.0 * atan2(sqrt(((t_1 * (t_0 * t_1)) + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(((1.0 - (sin((0.5 * (phi1 - phi2))) ^ 2.0)) + (t_0 * ((0.5 * cos((lambda1 - lambda2))) - 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]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$1 * N[(t$95$0 * t$95$1), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + N[(t$95$0 * N[(N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $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)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 \cdot \left(t\_0 \cdot t\_1\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{\left(1 - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right) + t\_0 \cdot \left(0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right) - 0.5\right)}}\right)
\end{array}
\end{array}
Initial program 64.4%
associate--r+64.4%
associate-*l*64.4%
cancel-sign-sub-inv64.4%
div-inv64.4%
metadata-eval64.4%
sqr-sin-a64.5%
cos-264.5%
cos-sum64.5%
Applied egg-rr64.5%
Final simplification64.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- lambda1 lambda2))))
(t_1 (* (cos phi1) (cos phi2))))
(if (or (<= phi1 -400.0) (not (<= phi1 1.56)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ phi1 2.0)) 2.0)
(* (sin (* 0.5 lambda1)) (* t_1 (sin (* -0.5 lambda2))))))
(sqrt (- (pow (cos (* 0.5 phi1)) 2.0) (* (cos phi1) (pow t_0 2.0)))))))
(*
(atan2
(hypot (sin (* 0.5 (- phi1 phi2))) (* t_0 (sqrt t_1)))
(sqrt
(-
1.0
(fma
t_1
(+ 0.5 (* -0.5 (cos (- lambda1 lambda2))))
(- 0.5 (/ (cos (- phi1 phi2)) 2.0))))))
(* R 2.0)))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (lambda1 - lambda2)));
double t_1 = cos(phi1) * cos(phi2);
double tmp;
if ((phi1 <= -400.0) || !(phi1 <= 1.56)) {
tmp = R * (2.0 * atan2(sqrt((pow(sin((phi1 / 2.0)), 2.0) + (sin((0.5 * lambda1)) * (t_1 * sin((-0.5 * lambda2)))))), sqrt((pow(cos((0.5 * phi1)), 2.0) - (cos(phi1) * pow(t_0, 2.0))))));
} else {
tmp = atan2(hypot(sin((0.5 * (phi1 - phi2))), (t_0 * sqrt(t_1))), sqrt((1.0 - fma(t_1, (0.5 + (-0.5 * cos((lambda1 - lambda2)))), (0.5 - (cos((phi1 - phi2)) / 2.0)))))) * (R * 2.0);
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) t_1 = Float64(cos(phi1) * cos(phi2)) tmp = 0.0 if ((phi1 <= -400.0) || !(phi1 <= 1.56)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(phi1 / 2.0)) ^ 2.0) + Float64(sin(Float64(0.5 * lambda1)) * Float64(t_1 * sin(Float64(-0.5 * lambda2)))))), sqrt(Float64((cos(Float64(0.5 * phi1)) ^ 2.0) - Float64(cos(phi1) * (t_0 ^ 2.0))))))); else tmp = Float64(atan(hypot(sin(Float64(0.5 * Float64(phi1 - phi2))), Float64(t_0 * sqrt(t_1))), sqrt(Float64(1.0 - fma(t_1, Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2)))), Float64(0.5 - Float64(cos(Float64(phi1 - phi2)) / 2.0)))))) * Float64(R * 2.0)); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[phi1, -400.0], N[Not[LessEqual[phi1, 1.56]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision] * N[(t$95$1 * N[Sin[N[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi1], $MachinePrecision] * N[Power[t$95$0, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[ArcTan[N[Sqrt[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] ^ 2 + N[(t$95$0 * N[Sqrt[t$95$1], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$1 * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(0.5 - N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(R * 2.0), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
\mathbf{if}\;\phi_1 \leq -400 \lor \neg \left(\phi_1 \leq 1.56\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1}{2}\right)}^{2} + \sin \left(0.5 \cdot \lambda_1\right) \cdot \left(t\_1 \cdot \sin \left(-0.5 \cdot \lambda_2\right)\right)}}{\sqrt{{\cos \left(0.5 \cdot \phi_1\right)}^{2} - \cos \phi_1 \cdot {t\_0}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;\tan^{-1}_* \frac{\mathsf{hypot}\left(\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right), t\_0 \cdot \sqrt{t\_1}\right)}{\sqrt{1 - \mathsf{fma}\left(t\_1, 0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), 0.5 - \frac{\cos \left(\phi_1 - \phi_2\right)}{2}\right)}} \cdot \left(R \cdot 2\right)\\
\end{array}
\end{array}
if phi1 < -400 or 1.5600000000000001 < phi1 Initial program 48.3%
Taylor expanded in lambda2 around 0 40.0%
Taylor expanded in lambda1 around 0 28.2%
Taylor expanded in phi1 around inf 28.3%
Taylor expanded in phi2 around 0 29.4%
+-commutative49.3%
associate--r+49.3%
unpow249.3%
1-sub-sin49.4%
unpow249.4%
*-commutative49.4%
Simplified29.4%
if -400 < phi1 < 1.5600000000000001Initial program 82.2%
associate-*r*82.2%
*-commutative82.2%
Simplified82.2%
Applied egg-rr61.9%
*-lft-identity61.9%
*-commutative61.9%
*-commutative61.9%
*-commutative61.9%
*-commutative61.9%
Simplified61.9%
flip--52.6%
div-inv51.7%
pow251.7%
pow251.7%
Applied egg-rr51.7%
+-commutative51.7%
Simplified51.7%
*-commutative51.7%
un-div-inv52.6%
unpow252.6%
unpow252.6%
+-commutative52.6%
flip--61.9%
metadata-eval61.9%
div-inv61.9%
unpow261.9%
sin-mult61.9%
Applied egg-rr61.9%
div-sub61.9%
+-inverses61.9%
cos-061.9%
metadata-eval61.9%
distribute-rgt-out61.9%
metadata-eval61.9%
*-rgt-identity61.9%
Simplified61.9%
Final simplification44.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(*
(cos phi1)
(* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
t_0))
(sqrt
(+
1.0
(-
(*
(cos phi1)
(* (cos phi2) (- (* 0.5 (cos (- lambda1 lambda2))) 0.5)))
t_0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (phi1 - phi2))), 2.0);
return R * (2.0 * atan2(sqrt(((cos(phi1) * (cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0))) + t_0)), sqrt((1.0 + ((cos(phi1) * (cos(phi2) * ((0.5 * cos((lambda1 - lambda2))) - 0.5))) - t_0)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin((0.5d0 * (phi1 - phi2))) ** 2.0d0
code = r * (2.0d0 * atan2(sqrt(((cos(phi1) * (cos(phi2) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0))) + t_0)), sqrt((1.0d0 + ((cos(phi1) * (cos(phi2) * ((0.5d0 * cos((lambda1 - lambda2))) - 0.5d0))) - t_0)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(Math.sin((0.5 * (phi1 - phi2))), 2.0);
return R * (2.0 * Math.atan2(Math.sqrt(((Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0))) + t_0)), Math.sqrt((1.0 + ((Math.cos(phi1) * (Math.cos(phi2) * ((0.5 * Math.cos((lambda1 - lambda2))) - 0.5))) - t_0)))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(math.sin((0.5 * (phi1 - phi2))), 2.0) return R * (2.0 * math.atan2(math.sqrt(((math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0))) + t_0)), math.sqrt((1.0 + ((math.cos(phi1) * (math.cos(phi2) * ((0.5 * math.cos((lambda1 - lambda2))) - 0.5))) - t_0)))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0 return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0))) + t_0)), sqrt(Float64(1.0 + Float64(Float64(cos(phi1) * Float64(cos(phi2) * Float64(Float64(0.5 * cos(Float64(lambda1 - lambda2))) - 0.5))) - t_0)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin((0.5 * (phi1 - phi2))) ^ 2.0; tmp = R * (2.0 * atan2(sqrt(((cos(phi1) * (cos(phi2) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0))) + t_0)), sqrt((1.0 + ((cos(phi1) * (cos(phi2) * ((0.5 * cos((lambda1 - lambda2))) - 0.5))) - t_0))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$0), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 + N[(N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\right) + t\_0}}{\sqrt{1 + \left(\cos \phi_1 \cdot \left(\cos \phi_2 \cdot \left(0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right) - 0.5\right)\right) - t\_0\right)}}\right)
\end{array}
\end{array}
Initial program 64.4%
add-cbrt-cube63.3%
pow363.3%
pow-pow63.3%
div-inv63.3%
metadata-eval63.3%
metadata-eval63.3%
Applied egg-rr63.3%
+-commutative63.3%
associate-*l*63.3%
fma-undefine63.3%
add-cube-cbrt63.2%
pow363.2%
Applied egg-rr63.2%
Taylor expanded in phi1 around 0 64.5%
Final simplification64.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2))))
(*
(atan2
(hypot
(sin (* 0.5 (- phi1 phi2)))
(* (sin (* 0.5 (- lambda1 lambda2))) (sqrt t_0)))
(sqrt
(-
1.0
(fma
t_0
(+ 0.5 (* -0.5 (cos (- lambda1 lambda2))))
(- 0.5 (/ (cos (- phi1 phi2)) 2.0))))))
(* R 2.0))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
return atan2(hypot(sin((0.5 * (phi1 - phi2))), (sin((0.5 * (lambda1 - lambda2))) * sqrt(t_0))), sqrt((1.0 - fma(t_0, (0.5 + (-0.5 * cos((lambda1 - lambda2)))), (0.5 - (cos((phi1 - phi2)) / 2.0)))))) * (R * 2.0);
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) return Float64(atan(hypot(sin(Float64(0.5 * Float64(phi1 - phi2))), Float64(sin(Float64(0.5 * Float64(lambda1 - lambda2))) * sqrt(t_0))), sqrt(Float64(1.0 - fma(t_0, Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2)))), Float64(0.5 - Float64(cos(Float64(phi1 - phi2)) / 2.0)))))) * Float64(R * 2.0)) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, N[(N[ArcTan[N[Sqrt[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] ^ 2 + N[(N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] * N[Sqrt[t$95$0], $MachinePrecision]), $MachinePrecision] ^ 2], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(0.5 - N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(R * 2.0), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
\tan^{-1}_* \frac{\mathsf{hypot}\left(\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right), \sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right) \cdot \sqrt{t\_0}\right)}{\sqrt{1 - \mathsf{fma}\left(t\_0, 0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), 0.5 - \frac{\cos \left(\phi_1 - \phi_2\right)}{2}\right)}} \cdot \left(R \cdot 2\right)
\end{array}
\end{array}
Initial program 64.4%
associate-*r*64.4%
*-commutative64.4%
Simplified64.5%
Applied egg-rr39.8%
*-lft-identity39.8%
*-commutative39.8%
*-commutative39.8%
*-commutative39.8%
*-commutative39.8%
Simplified39.8%
flip--29.6%
div-inv28.8%
pow228.8%
pow228.8%
Applied egg-rr28.8%
+-commutative28.8%
Simplified28.8%
*-commutative28.8%
un-div-inv29.6%
unpow229.6%
unpow229.6%
+-commutative29.6%
flip--39.8%
metadata-eval39.8%
div-inv39.8%
unpow239.8%
sin-mult39.8%
Applied egg-rr39.8%
div-sub39.8%
+-inverses39.8%
cos-039.8%
metadata-eval39.8%
distribute-rgt-out39.8%
metadata-eval39.8%
*-rgt-identity39.8%
Simplified39.8%
Final simplification39.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(sqrt
(-
1.0
(+
(* t_0 (* (* (cos phi1) (cos phi2)) t_0))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0))))))
(if (<= R 2.4e-122)
(* R (* 2.0 (atan2 (sin (* 0.5 (fabs (- phi1 phi2)))) t_1)))
(*
R
(*
2.0
(atan2
(+
(sin (* 0.5 (- phi1 phi2)))
(*
0.25
(/
(* (sin (* -0.5 lambda2)) (* (cos phi1) lambda1))
(sin (* 0.5 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 - ((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))));
double tmp;
if (R <= 2.4e-122) {
tmp = R * (2.0 * atan2(sin((0.5 * fabs((phi1 - phi2)))), t_1));
} else {
tmp = R * (2.0 * atan2((sin((0.5 * (phi1 - phi2))) + (0.25 * ((sin((-0.5 * lambda2)) * (cos(phi1) * lambda1)) / sin((0.5 * 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 - ((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))))
if (r <= 2.4d-122) then
tmp = r * (2.0d0 * atan2(sin((0.5d0 * abs((phi1 - phi2)))), t_1))
else
tmp = r * (2.0d0 * atan2((sin((0.5d0 * (phi1 - phi2))) + (0.25d0 * ((sin(((-0.5d0) * lambda2)) * (cos(phi1) * lambda1)) / sin((0.5d0 * 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 - ((t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0)) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))));
double tmp;
if (R <= 2.4e-122) {
tmp = R * (2.0 * Math.atan2(Math.sin((0.5 * Math.abs((phi1 - phi2)))), t_1));
} else {
tmp = R * (2.0 * Math.atan2((Math.sin((0.5 * (phi1 - phi2))) + (0.25 * ((Math.sin((-0.5 * lambda2)) * (Math.cos(phi1) * lambda1)) / Math.sin((0.5 * 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 - ((t_0 * ((math.cos(phi1) * math.cos(phi2)) * t_0)) + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0)))) tmp = 0 if R <= 2.4e-122: tmp = R * (2.0 * math.atan2(math.sin((0.5 * math.fabs((phi1 - phi2)))), t_1)) else: tmp = R * (2.0 * math.atan2((math.sin((0.5 * (phi1 - phi2))) + (0.25 * ((math.sin((-0.5 * lambda2)) * (math.cos(phi1) * lambda1)) / math.sin((0.5 * 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(1.0 - Float64(Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0)))) tmp = 0.0 if (R <= 2.4e-122) tmp = Float64(R * Float64(2.0 * atan(sin(Float64(0.5 * abs(Float64(phi1 - phi2)))), t_1))); else tmp = Float64(R * Float64(2.0 * atan(Float64(sin(Float64(0.5 * Float64(phi1 - phi2))) + Float64(0.25 * Float64(Float64(sin(Float64(-0.5 * lambda2)) * Float64(cos(phi1) * lambda1)) / sin(Float64(0.5 * 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 - ((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + (sin(((phi1 - phi2) / 2.0)) ^ 2.0)))); tmp = 0.0; if (R <= 2.4e-122) tmp = R * (2.0 * atan2(sin((0.5 * abs((phi1 - phi2)))), t_1)); else tmp = R * (2.0 * atan2((sin((0.5 * (phi1 - phi2))) + (0.25 * ((sin((-0.5 * lambda2)) * (cos(phi1) * lambda1)) / sin((0.5 * 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[(1.0 - N[(N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[R, 2.4e-122], N[(R * N[(2.0 * N[ArcTan[N[Sin[N[(0.5 * N[Abs[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[(N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] + N[(0.25 * N[(N[(N[Sin[N[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision] * N[(N[Cos[phi1], $MachinePrecision] * lambda1), $MachinePrecision]), $MachinePrecision] / N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]), $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{1 - \left(t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right)}\\
\mathbf{if}\;R \leq 2.4 \cdot 10^{-122}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sin \left(0.5 \cdot \left|\phi_1 - \phi_2\right|\right)}{t\_1}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right) + 0.25 \cdot \frac{\sin \left(-0.5 \cdot \lambda_2\right) \cdot \left(\cos \phi_1 \cdot \lambda_1\right)}{\sin \left(0.5 \cdot \phi_1\right)}}{t\_1}\right)\\
\end{array}
\end{array}
if R < 2.39999999999999987e-122Initial program 62.4%
Taylor expanded in lambda2 around 0 47.6%
Taylor expanded in lambda1 around 0 31.1%
Taylor expanded in lambda2 around 0 19.2%
add-sqr-sqrt10.5%
sqrt-unprod10.6%
pow210.6%
Applied egg-rr10.6%
unpow210.6%
rem-sqrt-square17.1%
Simplified17.1%
if 2.39999999999999987e-122 < R Initial program 68.5%
Taylor expanded in lambda2 around 0 42.6%
Taylor expanded in lambda1 around 0 16.1%
Taylor expanded in phi2 around 0 16.5%
associate-*r*16.5%
*-commutative16.5%
*-commutative16.5%
*-commutative16.5%
Simplified16.5%
Final simplification16.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sin (* 0.5 (- phi1 phi2)))
(sqrt
(-
1.0
(+
(* t_0 (* (* (cos phi1) (cos phi2)) t_0))
(pow
(-
(* (sin (* 0.5 phi1)) (cos (* phi2 0.5)))
(* (cos (* 0.5 phi1)) (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));
return R * (2.0 * atan2(sin((0.5 * (phi1 - phi2))), sqrt((1.0 - ((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + pow(((sin((0.5 * phi1)) * cos((phi2 * 0.5))) - (cos((0.5 * phi1)) * sin((phi2 * 0.5)))), 2.0))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2(sin((0.5d0 * (phi1 - phi2))), sqrt((1.0d0 - ((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + (((sin((0.5d0 * phi1)) * cos((phi2 * 0.5d0))) - (cos((0.5d0 * phi1)) * sin((phi2 * 0.5d0)))) ** 2.0d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * Math.atan2(Math.sin((0.5 * (phi1 - phi2))), Math.sqrt((1.0 - ((t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0)) + Math.pow(((Math.sin((0.5 * phi1)) * Math.cos((phi2 * 0.5))) - (Math.cos((0.5 * phi1)) * Math.sin((phi2 * 0.5)))), 2.0))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) return R * (2.0 * math.atan2(math.sin((0.5 * (phi1 - phi2))), math.sqrt((1.0 - ((t_0 * ((math.cos(phi1) * math.cos(phi2)) * t_0)) + math.pow(((math.sin((0.5 * phi1)) * math.cos((phi2 * 0.5))) - (math.cos((0.5 * phi1)) * math.sin((phi2 * 0.5)))), 2.0))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sin(Float64(0.5 * Float64(phi1 - phi2))), sqrt(Float64(1.0 - Float64(Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)) + (Float64(Float64(sin(Float64(0.5 * phi1)) * cos(Float64(phi2 * 0.5))) - Float64(cos(Float64(0.5 * phi1)) * sin(Float64(phi2 * 0.5)))) ^ 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); tmp = R * (2.0 * atan2(sin((0.5 * (phi1 - phi2))), sqrt((1.0 - ((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + (((sin((0.5 * phi1)) * cos((phi2 * 0.5))) - (cos((0.5 * phi1)) * sin((phi2 * 0.5)))) ^ 2.0)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[(N[(N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}{\sqrt{1 - \left(t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) + {\left(\sin \left(0.5 \cdot \phi_1\right) \cdot \cos \left(\phi_2 \cdot 0.5\right) - \cos \left(0.5 \cdot \phi_1\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 64.4%
Taylor expanded in lambda2 around 0 45.9%
Taylor expanded in lambda1 around 0 29.7%
Taylor expanded in lambda2 around 0 17.9%
div-sub64.4%
sin-diff65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
div-inv65.4%
metadata-eval65.4%
Applied egg-rr18.4%
Final simplification18.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- phi1 phi2))))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (* (cos phi1) (cos phi2))))
(if (<= R 1.9e-113)
(*
R
(*
2.0
(atan2
(sin (* 0.5 (fabs (- phi1 phi2))))
(sqrt
(-
1.0
(+ (* t_1 (* t_2 t_1)) (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))))))
(*
R
(*
2.0
(atan2
t_0
(sqrt
(expm1
(log1p
(-
1.0
(fma
t_2
(+ 0.5 (* -0.5 (cos (- lambda1 lambda2))))
(pow t_0 2.0))))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (phi1 - phi2)));
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = cos(phi1) * cos(phi2);
double tmp;
if (R <= 1.9e-113) {
tmp = R * (2.0 * atan2(sin((0.5 * fabs((phi1 - phi2)))), sqrt((1.0 - ((t_1 * (t_2 * t_1)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))))));
} else {
tmp = R * (2.0 * atan2(t_0, sqrt(expm1(log1p((1.0 - fma(t_2, (0.5 + (-0.5 * cos((lambda1 - lambda2)))), pow(t_0, 2.0))))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(phi1 - phi2))) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(cos(phi1) * cos(phi2)) tmp = 0.0 if (R <= 1.9e-113) tmp = Float64(R * Float64(2.0 * atan(sin(Float64(0.5 * abs(Float64(phi1 - phi2)))), sqrt(Float64(1.0 - Float64(Float64(t_1 * Float64(t_2 * t_1)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(t_0, sqrt(expm1(log1p(Float64(1.0 - fma(t_2, Float64(0.5 + Float64(-0.5 * cos(Float64(lambda1 - lambda2)))), (t_0 ^ 2.0))))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[R, 1.9e-113], N[(R * N[(2.0 * N[ArcTan[N[Sin[N[(0.5 * N[Abs[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(t$95$1 * N[(t$95$2 * t$95$1), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$0 / N[Sqrt[N[(Exp[N[Log[1 + N[(1.0 - N[(t$95$2 * N[(0.5 + N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[t$95$0, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]] - 1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
\mathbf{if}\;R \leq 1.9 \cdot 10^{-113}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sin \left(0.5 \cdot \left|\phi_1 - \phi_2\right|\right)}{\sqrt{1 - \left(t\_1 \cdot \left(t\_2 \cdot t\_1\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_0}{\sqrt{\mathsf{expm1}\left(\mathsf{log1p}\left(1 - \mathsf{fma}\left(t\_2, 0.5 + -0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right), {t\_0}^{2}\right)\right)\right)}}\right)\\
\end{array}
\end{array}
if R < 1.89999999999999992e-113Initial program 62.0%
Taylor expanded in lambda2 around 0 46.8%
Taylor expanded in lambda1 around 0 30.8%
Taylor expanded in lambda2 around 0 18.9%
add-sqr-sqrt10.3%
sqrt-unprod10.5%
pow210.5%
Applied egg-rr10.5%
unpow210.5%
rem-sqrt-square16.9%
Simplified16.9%
if 1.89999999999999992e-113 < R Initial program 69.6%
Taylor expanded in lambda2 around 0 44.1%
Taylor expanded in lambda1 around 0 27.2%
Taylor expanded in lambda2 around 0 15.7%
+-commutative15.7%
associate-*l*15.7%
fma-undefine15.7%
expm1-log1p-u15.7%
Applied egg-rr15.7%
*-commutative15.7%
cancel-sign-sub-inv15.7%
metadata-eval15.7%
*-commutative15.7%
Simplified15.7%
Final simplification16.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- phi1 phi2))))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (* (cos phi1) (cos phi2))))
(if (<= R 1.35e-115)
(*
R
(*
2.0
(atan2
(sin (* 0.5 (fabs (- phi1 phi2))))
(sqrt
(-
1.0
(+ (* t_1 (* t_2 t_1)) (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))))))
(*
R
(*
2.0
(atan2
t_0
(sqrt
(+
1.0
(-
(* t_2 (- (* 0.5 (cos (- lambda1 lambda2))) 0.5))
(pow t_0 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (phi1 - phi2)));
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = cos(phi1) * cos(phi2);
double tmp;
if (R <= 1.35e-115) {
tmp = R * (2.0 * atan2(sin((0.5 * fabs((phi1 - phi2)))), sqrt((1.0 - ((t_1 * (t_2 * t_1)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))))));
} else {
tmp = R * (2.0 * atan2(t_0, sqrt((1.0 + ((t_2 * ((0.5 * cos((lambda1 - lambda2))) - 0.5)) - pow(t_0, 2.0))))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: tmp
t_0 = sin((0.5d0 * (phi1 - phi2)))
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
t_2 = cos(phi1) * cos(phi2)
if (r <= 1.35d-115) then
tmp = r * (2.0d0 * atan2(sin((0.5d0 * abs((phi1 - phi2)))), sqrt((1.0d0 - ((t_1 * (t_2 * t_1)) + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))))))
else
tmp = r * (2.0d0 * atan2(t_0, sqrt((1.0d0 + ((t_2 * ((0.5d0 * cos((lambda1 - lambda2))) - 0.5d0)) - (t_0 ** 2.0d0))))))
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin((0.5 * (phi1 - phi2)));
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_2 = Math.cos(phi1) * Math.cos(phi2);
double tmp;
if (R <= 1.35e-115) {
tmp = R * (2.0 * Math.atan2(Math.sin((0.5 * Math.abs((phi1 - phi2)))), Math.sqrt((1.0 - ((t_1 * (t_2 * t_1)) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))))));
} else {
tmp = R * (2.0 * Math.atan2(t_0, Math.sqrt((1.0 + ((t_2 * ((0.5 * Math.cos((lambda1 - lambda2))) - 0.5)) - Math.pow(t_0, 2.0))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin((0.5 * (phi1 - phi2))) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) t_2 = math.cos(phi1) * math.cos(phi2) tmp = 0 if R <= 1.35e-115: tmp = R * (2.0 * math.atan2(math.sin((0.5 * math.fabs((phi1 - phi2)))), math.sqrt((1.0 - ((t_1 * (t_2 * t_1)) + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0)))))) else: tmp = R * (2.0 * math.atan2(t_0, math.sqrt((1.0 + ((t_2 * ((0.5 * math.cos((lambda1 - lambda2))) - 0.5)) - math.pow(t_0, 2.0)))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(phi1 - phi2))) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(cos(phi1) * cos(phi2)) tmp = 0.0 if (R <= 1.35e-115) tmp = Float64(R * Float64(2.0 * atan(sin(Float64(0.5 * abs(Float64(phi1 - phi2)))), sqrt(Float64(1.0 - Float64(Float64(t_1 * Float64(t_2 * t_1)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(t_0, sqrt(Float64(1.0 + Float64(Float64(t_2 * Float64(Float64(0.5 * cos(Float64(lambda1 - lambda2))) - 0.5)) - (t_0 ^ 2.0))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin((0.5 * (phi1 - phi2))); t_1 = sin(((lambda1 - lambda2) / 2.0)); t_2 = cos(phi1) * cos(phi2); tmp = 0.0; if (R <= 1.35e-115) tmp = R * (2.0 * atan2(sin((0.5 * abs((phi1 - phi2)))), sqrt((1.0 - ((t_1 * (t_2 * t_1)) + (sin(((phi1 - phi2) / 2.0)) ^ 2.0)))))); else tmp = R * (2.0 * atan2(t_0, sqrt((1.0 + ((t_2 * ((0.5 * cos((lambda1 - lambda2))) - 0.5)) - (t_0 ^ 2.0)))))); end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[R, 1.35e-115], N[(R * N[(2.0 * N[ArcTan[N[Sin[N[(0.5 * N[Abs[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(t$95$1 * N[(t$95$2 * t$95$1), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$0 / N[Sqrt[N[(1.0 + N[(N[(t$95$2 * N[(N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision] - N[Power[t$95$0, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
\mathbf{if}\;R \leq 1.35 \cdot 10^{-115}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sin \left(0.5 \cdot \left|\phi_1 - \phi_2\right|\right)}{\sqrt{1 - \left(t\_1 \cdot \left(t\_2 \cdot t\_1\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_0}{\sqrt{1 + \left(t\_2 \cdot \left(0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right) - 0.5\right) - {t\_0}^{2}\right)}}\right)\\
\end{array}
\end{array}
if R < 1.35e-115Initial program 62.0%
Taylor expanded in lambda2 around 0 46.8%
Taylor expanded in lambda1 around 0 30.8%
Taylor expanded in lambda2 around 0 18.9%
add-sqr-sqrt10.3%
sqrt-unprod10.5%
pow210.5%
Applied egg-rr10.5%
unpow210.5%
rem-sqrt-square16.9%
Simplified16.9%
if 1.35e-115 < R Initial program 69.6%
Taylor expanded in lambda2 around 0 44.1%
Taylor expanded in lambda1 around 0 27.2%
Taylor expanded in lambda2 around 0 15.7%
associate--r+15.7%
sub-neg15.7%
associate--l+15.7%
div-inv15.7%
metadata-eval15.7%
associate-*l*15.7%
sqr-sin-a15.7%
Applied egg-rr15.7%
Final simplification16.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- phi1 phi2)))))
(*
R
(*
2.0
(atan2
t_0
(sqrt
(-
1.0
(+
(pow t_0 2.0)
(* (cos phi1) (* (cos phi2) (pow (sin (* 0.5 lambda1)) 2.0)))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (phi1 - phi2)));
return R * (2.0 * atan2(t_0, sqrt((1.0 - (pow(t_0, 2.0) + (cos(phi1) * (cos(phi2) * pow(sin((0.5 * lambda1)), 2.0))))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin((0.5d0 * (phi1 - phi2)))
code = r * (2.0d0 * atan2(t_0, sqrt((1.0d0 - ((t_0 ** 2.0d0) + (cos(phi1) * (cos(phi2) * (sin((0.5d0 * lambda1)) ** 2.0d0))))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin((0.5 * (phi1 - phi2)));
return R * (2.0 * Math.atan2(t_0, Math.sqrt((1.0 - (Math.pow(t_0, 2.0) + (Math.cos(phi1) * (Math.cos(phi2) * Math.pow(Math.sin((0.5 * lambda1)), 2.0))))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin((0.5 * (phi1 - phi2))) return R * (2.0 * math.atan2(t_0, math.sqrt((1.0 - (math.pow(t_0, 2.0) + (math.cos(phi1) * (math.cos(phi2) * math.pow(math.sin((0.5 * lambda1)), 2.0))))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(phi1 - phi2))) return Float64(R * Float64(2.0 * atan(t_0, sqrt(Float64(1.0 - Float64((t_0 ^ 2.0) + Float64(cos(phi1) * Float64(cos(phi2) * (sin(Float64(0.5 * lambda1)) ^ 2.0))))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin((0.5 * (phi1 - phi2))); tmp = R * (2.0 * atan2(t_0, sqrt((1.0 - ((t_0 ^ 2.0) + (cos(phi1) * (cos(phi2) * (sin((0.5 * lambda1)) ^ 2.0)))))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[t$95$0 / N[Sqrt[N[(1.0 - N[(N[Power[t$95$0, 2.0], $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_0}{\sqrt{1 - \left({t\_0}^{2} + \cos \phi_1 \cdot \left(\cos \phi_2 \cdot {\sin \left(0.5 \cdot \lambda_1\right)}^{2}\right)\right)}}\right)
\end{array}
\end{array}
Initial program 64.4%
Taylor expanded in lambda2 around 0 45.9%
Taylor expanded in lambda1 around 0 29.7%
Taylor expanded in lambda2 around 0 17.9%
Taylor expanded in lambda2 around 0 17.9%
Final simplification17.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 (- phi1 phi2)))))
(*
R
(*
2.0
(atan2
t_0
(sqrt
(+
1.0
(-
(*
(* (cos phi1) (cos phi2))
(- (* 0.5 (cos (- lambda1 lambda2))) 0.5))
(pow t_0 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * (phi1 - phi2)));
return R * (2.0 * atan2(t_0, sqrt((1.0 + (((cos(phi1) * cos(phi2)) * ((0.5 * cos((lambda1 - lambda2))) - 0.5)) - pow(t_0, 2.0))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin((0.5d0 * (phi1 - phi2)))
code = r * (2.0d0 * atan2(t_0, sqrt((1.0d0 + (((cos(phi1) * cos(phi2)) * ((0.5d0 * cos((lambda1 - lambda2))) - 0.5d0)) - (t_0 ** 2.0d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin((0.5 * (phi1 - phi2)));
return R * (2.0 * Math.atan2(t_0, Math.sqrt((1.0 + (((Math.cos(phi1) * Math.cos(phi2)) * ((0.5 * Math.cos((lambda1 - lambda2))) - 0.5)) - Math.pow(t_0, 2.0))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin((0.5 * (phi1 - phi2))) return R * (2.0 * math.atan2(t_0, math.sqrt((1.0 + (((math.cos(phi1) * math.cos(phi2)) * ((0.5 * math.cos((lambda1 - lambda2))) - 0.5)) - math.pow(t_0, 2.0))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(phi1 - phi2))) return Float64(R * Float64(2.0 * atan(t_0, sqrt(Float64(1.0 + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * Float64(Float64(0.5 * cos(Float64(lambda1 - lambda2))) - 0.5)) - (t_0 ^ 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin((0.5 * (phi1 - phi2))); tmp = R * (2.0 * atan2(t_0, sqrt((1.0 + (((cos(phi1) * cos(phi2)) * ((0.5 * cos((lambda1 - lambda2))) - 0.5)) - (t_0 ^ 2.0)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[t$95$0 / N[Sqrt[N[(1.0 + N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision] - N[Power[t$95$0, 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_0}{\sqrt{1 + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot \left(0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right) - 0.5\right) - {t\_0}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 64.4%
Taylor expanded in lambda2 around 0 45.9%
Taylor expanded in lambda1 around 0 29.7%
Taylor expanded in lambda2 around 0 17.9%
associate--r+17.9%
sub-neg17.9%
associate--l+17.9%
div-inv17.9%
metadata-eval17.9%
associate-*l*17.9%
sqr-sin-a17.9%
Applied egg-rr17.9%
Final simplification17.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(sin (* 0.5 (- phi1 phi2)))
(sqrt
(-
(pow (cos (* 0.5 phi1)) 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(sin((0.5 * (phi1 - phi2))), sqrt((pow(cos((0.5 * phi1)), 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(sin((0.5d0 * (phi1 - phi2))), sqrt(((cos((0.5d0 * phi1)) ** 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(Math.sin((0.5 * (phi1 - phi2))), Math.sqrt((Math.pow(Math.cos((0.5 * phi1)), 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(math.sin((0.5 * (phi1 - phi2))), math.sqrt((math.pow(math.cos((0.5 * phi1)), 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(sin(Float64(0.5 * Float64(phi1 - phi2))), sqrt(Float64((cos(Float64(0.5 * phi1)) ^ 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(sin((0.5 * (phi1 - phi2))), sqrt(((cos((0.5 * phi1)) ^ 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[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(0.5 * phi1), $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]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}{\sqrt{{\cos \left(0.5 \cdot \phi_1\right)}^{2} - \cos \phi_1 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}\right)
\end{array}
Initial program 64.4%
Taylor expanded in lambda2 around 0 45.9%
Taylor expanded in lambda1 around 0 29.7%
Taylor expanded in lambda2 around 0 17.9%
Taylor expanded in phi2 around 0 16.2%
+-commutative49.8%
associate--r+49.8%
unpow249.8%
1-sub-sin49.8%
unpow249.8%
*-commutative49.8%
Simplified16.2%
Final simplification16.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(sin (* 0.5 (- phi1 phi2)))
(sqrt
(-
(pow (cos (* -0.5 phi2)) 2.0)
(* (cos phi2) (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2(sin((0.5 * (phi1 - phi2))), sqrt((pow(cos((-0.5 * phi2)), 2.0) - (cos(phi2) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
code = r * (2.0d0 * atan2(sin((0.5d0 * (phi1 - phi2))), sqrt(((cos(((-0.5d0) * phi2)) ** 2.0d0) - (cos(phi2) * (sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * Math.atan2(Math.sin((0.5 * (phi1 - phi2))), Math.sqrt((Math.pow(Math.cos((-0.5 * phi2)), 2.0) - (Math.cos(phi2) * Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0))))));
}
def code(R, lambda1, lambda2, phi1, phi2): return R * (2.0 * math.atan2(math.sin((0.5 * (phi1 - phi2))), math.sqrt((math.pow(math.cos((-0.5 * phi2)), 2.0) - (math.cos(phi2) * math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0))))))
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(sin(Float64(0.5 * Float64(phi1 - phi2))), sqrt(Float64((cos(Float64(-0.5 * phi2)) ^ 2.0) - Float64(cos(phi2) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) tmp = R * (2.0 * atan2(sin((0.5 * (phi1 - phi2))), sqrt(((cos((-0.5 * phi2)) ^ 2.0) - (cos(phi2) * (sin((0.5 * (lambda1 - lambda2))) ^ 2.0)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}{\sqrt{{\cos \left(-0.5 \cdot \phi_2\right)}^{2} - \cos \phi_2 \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}}}\right)
\end{array}
Initial program 64.4%
Taylor expanded in lambda2 around 0 45.9%
Taylor expanded in lambda1 around 0 29.7%
Taylor expanded in lambda2 around 0 17.9%
Taylor expanded in phi1 around 0 14.7%
+-commutative50.0%
associate--r+50.0%
unpow250.0%
1-sub-sin49.9%
unpow249.9%
Simplified14.7%
herbie shell --seed 2024121
(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))))))))))