
(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 16 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_0) t_0))))
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0);
return R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0)
code = r * (2.0d0 * atan2(sqrt(t_1), sqrt((1.0d0 - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((Math.cos(phi1) * Math.cos(phi2)) * t_0) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt(t_1), Math.sqrt((1.0 - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((math.cos(phi1) * math.cos(phi2)) * t_0) * t_0) return R * (2.0 * math.atan2(math.sqrt(t_1), math.sqrt((1.0 - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0); tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$1], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) \cdot t\_0\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)
\end{array}
\end{array}
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* -0.5 phi2)))
(t_1 (cos (* 0.5 phi1)))
(t_2 (sin (* 0.5 phi1)))
(t_3 (sin (/ (- lambda1 lambda2) 2.0)))
(t_4 (* (* (* (cos phi1) (cos phi2)) t_3) t_3)))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (fma t_2 (cos (* phi2 0.5)) (* t_0 t_1)) 2.0) t_4))
(sqrt
(-
1.0
(+ (pow (fma t_2 (cos (* -0.5 phi2)) (* t_1 t_0)) 2.0) t_4))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((-0.5 * phi2));
double t_1 = cos((0.5 * phi1));
double t_2 = sin((0.5 * phi1));
double t_3 = sin(((lambda1 - lambda2) / 2.0));
double t_4 = ((cos(phi1) * cos(phi2)) * t_3) * t_3;
return R * (2.0 * atan2(sqrt((pow(fma(t_2, cos((phi2 * 0.5)), (t_0 * t_1)), 2.0) + t_4)), sqrt((1.0 - (pow(fma(t_2, cos((-0.5 * phi2)), (t_1 * t_0)), 2.0) + t_4)))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(-0.5 * phi2)) t_1 = cos(Float64(0.5 * phi1)) t_2 = sin(Float64(0.5 * phi1)) t_3 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_4 = Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_3) * t_3) return Float64(R * Float64(2.0 * atan(sqrt(Float64((fma(t_2, cos(Float64(phi2 * 0.5)), Float64(t_0 * t_1)) ^ 2.0) + t_4)), sqrt(Float64(1.0 - Float64((fma(t_2, cos(Float64(-0.5 * phi2)), Float64(t_1 * t_0)) ^ 2.0) + t_4)))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$3), $MachinePrecision] * t$95$3), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(t$95$2 * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] + N[(t$95$0 * t$95$1), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$4), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[(t$95$2 * N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] + N[(t$95$1 * t$95$0), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$4), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(-0.5 \cdot \phi_2\right)\\
t_1 := \cos \left(0.5 \cdot \phi_1\right)\\
t_2 := \sin \left(0.5 \cdot \phi_1\right)\\
t_3 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_4 := \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_3\right) \cdot t\_3\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(t\_2, \cos \left(\phi_2 \cdot 0.5\right), t\_0 \cdot t\_1\right)\right)}^{2} + t\_4}}{\sqrt{1 - \left({\left(\mathsf{fma}\left(t\_2, \cos \left(-0.5 \cdot \phi_2\right), t\_1 \cdot t\_0\right)\right)}^{2} + t\_4\right)}}\right)
\end{array}
\end{array}
Initial program 60.3%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f6461.3
Applied rewrites61.3%
lift-sin.f64N/A
lift-/.f64N/A
clear-numN/A
associate-/r/N/A
metadata-evalN/A
lift--.f64N/A
distribute-rgt-out--N/A
lift-*.f64N/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
metadata-evalN/A
lift-*.f64N/A
sin-sumN/A
lift-*.f64N/A
*-commutativeN/A
lift-*.f64N/A
lift-sin.f64N/A
lower-fma.f64N/A
lower-cos.f64N/A
Applied rewrites76.6%
Applied rewrites76.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(fma
(* (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0) (cos phi1))
(cos phi2)
(pow
(fma
(- (sin (* 0.5 phi2)))
(cos (* 0.5 phi1))
(* (cos (* 0.5 phi2)) (sin (* 0.5 phi1))))
2.0))))
(* R (* (atan2 (sqrt t_0) (sqrt (- 1.0 t_0))) 2.0))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = fma((pow(sin(((lambda1 - lambda2) * 0.5)), 2.0) * cos(phi1)), cos(phi2), pow(fma(-sin((0.5 * phi2)), cos((0.5 * phi1)), (cos((0.5 * phi2)) * sin((0.5 * phi1)))), 2.0));
return R * (atan2(sqrt(t_0), sqrt((1.0 - t_0))) * 2.0);
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = fma(Float64((sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0) * cos(phi1)), cos(phi2), (fma(Float64(-sin(Float64(0.5 * phi2))), cos(Float64(0.5 * phi1)), Float64(cos(Float64(0.5 * phi2)) * sin(Float64(0.5 * phi1)))) ^ 2.0)) return Float64(R * Float64(atan(sqrt(t_0), sqrt(Float64(1.0 - t_0))) * 2.0)) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[(N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] * N[Cos[phi2], $MachinePrecision] + N[Power[N[((-N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]) * N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] + N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, N[(R * N[(N[ArcTan[N[Sqrt[t$95$0], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \mathsf{fma}\left({\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2} \cdot \cos \phi_1, \cos \phi_2, {\left(\mathsf{fma}\left(-\sin \left(0.5 \cdot \phi_2\right), \cos \left(0.5 \cdot \phi_1\right), \cos \left(0.5 \cdot \phi_2\right) \cdot \sin \left(0.5 \cdot \phi_1\right)\right)\right)}^{2}\right)\\
R \cdot \left(\tan^{-1}_* \frac{\sqrt{t\_0}}{\sqrt{1 - t\_0}} \cdot 2\right)
\end{array}
\end{array}
Initial program 60.3%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f6461.3
Applied rewrites61.3%
lift-sin.f64N/A
lift-/.f64N/A
clear-numN/A
associate-/r/N/A
metadata-evalN/A
lift--.f64N/A
distribute-rgt-out--N/A
lift-*.f64N/A
lift-*.f64N/A
sin-diffN/A
lift-sin.f64N/A
lift-cos.f64N/A
lift-*.f64N/A
lift-cos.f64N/A
lift-sin.f64N/A
lift-*.f64N/A
sub-negN/A
+-commutativeN/A
Applied rewrites76.6%
Taylor expanded in lambda1 around 0
Applied rewrites76.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* 0.5 phi1)))
(t_1 (cos (* 0.5 phi1)))
(t_2 (pow (sin (* (- lambda2 lambda1) -0.5)) 2.0)))
(*
(* 2.0 R)
(atan2
(sqrt
(fma
(* t_2 (cos phi2))
(cos phi1)
(pow (fma (- t_1) (sin (* 0.5 phi2)) (* (cos (* 0.5 phi2)) t_0)) 2.0)))
(sqrt
(-
1.0
(fma
(* (cos phi1) (cos phi2))
t_2
(pow
(fma (sin (* -0.5 phi2)) t_1 (* (cos (* -0.5 phi2)) t_0))
2.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((0.5 * phi1));
double t_1 = cos((0.5 * phi1));
double t_2 = pow(sin(((lambda2 - lambda1) * -0.5)), 2.0);
return (2.0 * R) * atan2(sqrt(fma((t_2 * cos(phi2)), cos(phi1), pow(fma(-t_1, sin((0.5 * phi2)), (cos((0.5 * phi2)) * t_0)), 2.0))), sqrt((1.0 - fma((cos(phi1) * cos(phi2)), t_2, pow(fma(sin((-0.5 * phi2)), t_1, (cos((-0.5 * phi2)) * t_0)), 2.0)))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * phi1)) t_1 = cos(Float64(0.5 * phi1)) t_2 = sin(Float64(Float64(lambda2 - lambda1) * -0.5)) ^ 2.0 return Float64(Float64(2.0 * R) * atan(sqrt(fma(Float64(t_2 * cos(phi2)), cos(phi1), (fma(Float64(-t_1), sin(Float64(0.5 * phi2)), Float64(cos(Float64(0.5 * phi2)) * t_0)) ^ 2.0))), sqrt(Float64(1.0 - fma(Float64(cos(phi1) * cos(phi2)), t_2, (fma(sin(Float64(-0.5 * phi2)), t_1, Float64(cos(Float64(-0.5 * phi2)) * t_0)) ^ 2.0)))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(N[(lambda2 - lambda1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(N[(2.0 * R), $MachinePrecision] * N[ArcTan[N[Sqrt[N[(N[(t$95$2 * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[Cos[phi1], $MachinePrecision] + N[Power[N[((-t$95$1) * N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] + N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$2 + N[Power[N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$1 + N[(N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(0.5 \cdot \phi_1\right)\\
t_1 := \cos \left(0.5 \cdot \phi_1\right)\\
t_2 := {\sin \left(\left(\lambda_2 - \lambda_1\right) \cdot -0.5\right)}^{2}\\
\left(2 \cdot R\right) \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_2 \cdot \cos \phi_2, \cos \phi_1, {\left(\mathsf{fma}\left(-t\_1, \sin \left(0.5 \cdot \phi_2\right), \cos \left(0.5 \cdot \phi_2\right) \cdot t\_0\right)\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1 \cdot \cos \phi_2, t\_2, {\left(\mathsf{fma}\left(\sin \left(-0.5 \cdot \phi_2\right), t\_1, \cos \left(-0.5 \cdot \phi_2\right) \cdot t\_0\right)\right)}^{2}\right)}}
\end{array}
\end{array}
Initial program 60.3%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f6461.3
Applied rewrites61.3%
lift-sin.f64N/A
lift-/.f64N/A
clear-numN/A
associate-/r/N/A
metadata-evalN/A
lift--.f64N/A
distribute-rgt-out--N/A
lift-*.f64N/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
metadata-evalN/A
lift-*.f64N/A
sin-sumN/A
lift-*.f64N/A
*-commutativeN/A
lift-*.f64N/A
lift-sin.f64N/A
lower-fma.f64N/A
lower-cos.f64N/A
Applied rewrites76.6%
Taylor expanded in lambda1 around -inf
Applied rewrites76.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (* (* (cos phi1) (cos phi2)) t_0) t_0))
(t_2 (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) t_1)))
(if (<= t_2 5e-9)
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow
(fma
(sin (* 0.5 phi1))
(cos (* -0.5 phi2))
(* (cos (* 0.5 phi1)) (sin (* -0.5 phi2))))
2.0)
t_1))
(sqrt (- 1.0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))))))
(*
R
(*
2.0
(atan2
(sqrt (+ (- 0.5 (* 0.5 (cos (* 2.0 (* 0.5 (- phi1 phi2)))))) t_1))
(sqrt (- 1.0 t_2))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = ((cos(phi1) * cos(phi2)) * t_0) * t_0;
double t_2 = pow(sin(((phi1 - phi2) / 2.0)), 2.0) + t_1;
double tmp;
if (t_2 <= 5e-9) {
tmp = R * (2.0 * atan2(sqrt((pow(fma(sin((0.5 * phi1)), cos((-0.5 * phi2)), (cos((0.5 * phi1)) * sin((-0.5 * phi2)))), 2.0) + t_1)), sqrt((1.0 - pow(sin(((lambda1 - lambda2) * 0.5)), 2.0)))));
} else {
tmp = R * (2.0 * atan2(sqrt(((0.5 - (0.5 * cos((2.0 * (0.5 * (phi1 - phi2)))))) + t_1)), sqrt((1.0 - t_2))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0) t_2 = Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + t_1) tmp = 0.0 if (t_2 <= 5e-9) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((fma(sin(Float64(0.5 * phi1)), cos(Float64(-0.5 * phi2)), Float64(cos(Float64(0.5 * phi1)) * sin(Float64(-0.5 * phi2)))) ^ 2.0) + t_1)), sqrt(Float64(1.0 - (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(0.5 - Float64(0.5 * cos(Float64(2.0 * Float64(0.5 * Float64(phi1 - phi2)))))) + t_1)), sqrt(Float64(1.0 - t_2))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]}, Block[{t$95$2 = N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$1), $MachinePrecision]}, If[LessEqual[t$95$2, 5e-9], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] + N[(N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(0.5 - N[(0.5 * N[Cos[N[(2.0 * N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$2), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) \cdot t\_0\\
t_2 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_1\\
\mathbf{if}\;t\_2 \leq 5 \cdot 10^{-9}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(\sin \left(0.5 \cdot \phi_1\right), \cos \left(-0.5 \cdot \phi_2\right), \cos \left(0.5 \cdot \phi_1\right) \cdot \sin \left(-0.5 \cdot \phi_2\right)\right)\right)}^{2} + t\_1}}{\sqrt{1 - {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\left(0.5 - 0.5 \cdot \cos \left(2 \cdot \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\right)\right) + t\_1}}{\sqrt{1 - t\_2}}\right)\\
\end{array}
\end{array}
if (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))))) < 5.0000000000000001e-9Initial program 69.9%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--l+N/A
*-commutativeN/A
associate-*r*N/A
lower-fma.f64N/A
Applied rewrites68.3%
Taylor expanded in phi1 around 0
Applied rewrites68.3%
lift-sin.f64N/A
lift-/.f64N/A
clear-numN/A
associate-/r/N/A
metadata-evalN/A
lift--.f64N/A
distribute-rgt-out--N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
metadata-evalN/A
lift-*.f64N/A
sin-sumN/A
lift-*.f64N/A
*-commutativeN/A
lift-*.f64N/A
lift-sin.f64N/A
lower-fma.f64N/A
lower-cos.f64N/A
lift-cos.f64N/A
lift-sin.f64N/A
Applied rewrites73.5%
if 5.0000000000000001e-9 < (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))))) Initial program 59.4%
lift-pow.f64N/A
unpow2N/A
lift-sin.f64N/A
lift-sin.f64N/A
sqr-sin-aN/A
lower--.f64N/A
cos-2N/A
cos-sumN/A
lower-*.f64N/A
cos-sumN/A
cos-2N/A
lower-cos.f64N/A
lower-*.f6459.4
lift-/.f64N/A
clear-numN/A
associate-/r/N/A
metadata-evalN/A
lower-*.f6459.4
Applied rewrites59.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_2 (* (* (* (cos phi1) (cos phi2)) t_0) t_0)))
(if (<= (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) t_2) 5e-9)
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (fma (* -0.5 phi2) (cos (* 0.5 phi1)) (sin (* 0.5 phi1))) 2.0)
t_2))
(sqrt (- 1.0 t_1)))))
(*
R
(*
2.0
(atan2
(sqrt (+ (- 0.5 (* 0.5 (cos (* 2.0 (* 0.5 (- phi1 phi2)))))) t_2))
(sqrt (- (pow (cos (* -0.5 phi1)) 2.0) (* t_1 (cos phi1))))))))))
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(((lambda1 - lambda2) * 0.5)), 2.0);
double t_2 = ((cos(phi1) * cos(phi2)) * t_0) * t_0;
double tmp;
if ((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + t_2) <= 5e-9) {
tmp = R * (2.0 * atan2(sqrt((pow(fma((-0.5 * phi2), cos((0.5 * phi1)), sin((0.5 * phi1))), 2.0) + t_2)), sqrt((1.0 - t_1))));
} else {
tmp = R * (2.0 * atan2(sqrt(((0.5 - (0.5 * cos((2.0 * (0.5 * (phi1 - phi2)))))) + t_2)), sqrt((pow(cos((-0.5 * phi1)), 2.0) - (t_1 * cos(phi1))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_2 = Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0) tmp = 0.0 if (Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + t_2) <= 5e-9) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((fma(Float64(-0.5 * phi2), cos(Float64(0.5 * phi1)), sin(Float64(0.5 * phi1))) ^ 2.0) + t_2)), sqrt(Float64(1.0 - t_1))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(0.5 - Float64(0.5 * cos(Float64(2.0 * Float64(0.5 * Float64(phi1 - phi2)))))) + t_2)), sqrt(Float64((cos(Float64(-0.5 * phi1)) ^ 2.0) - Float64(t_1 * cos(phi1))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]}, If[LessEqual[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$2), $MachinePrecision], 5e-9], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[(-0.5 * phi2), $MachinePrecision] * N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] + N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$2), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(0.5 - N[(0.5 * N[Cos[N[(2.0 * N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$2), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(t$95$1 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_2 := \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) \cdot t\_0\\
\mathbf{if}\;{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_2 \leq 5 \cdot 10^{-9}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(-0.5 \cdot \phi_2, \cos \left(0.5 \cdot \phi_1\right), \sin \left(0.5 \cdot \phi_1\right)\right)\right)}^{2} + t\_2}}{\sqrt{1 - t\_1}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\left(0.5 - 0.5 \cdot \cos \left(2 \cdot \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\right)\right) + t\_2}}{\sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - t\_1 \cdot \cos \phi_1}}\right)\\
\end{array}
\end{array}
if (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))))) < 5.0000000000000001e-9Initial program 69.9%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--l+N/A
*-commutativeN/A
associate-*r*N/A
lower-fma.f64N/A
Applied rewrites68.3%
Taylor expanded in phi1 around 0
Applied rewrites68.3%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate-*r*N/A
lower-fma.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
lower-*.f6473.3
Applied rewrites73.3%
if 5.0000000000000001e-9 < (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))))) Initial program 59.4%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites46.0%
lift-pow.f64N/A
unpow2N/A
lift-sin.f64N/A
lift-sin.f64N/A
sqr-sin-aN/A
lower--.f64N/A
cos-2N/A
cos-sumN/A
lower-*.f64N/A
cos-sumN/A
cos-2N/A
lower-cos.f64N/A
lower-*.f6445.9
lift-/.f64N/A
clear-numN/A
associate-/r/N/A
metadata-evalN/A
lower-*.f6445.9
Applied rewrites45.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow
(-
(* (sin (* phi1 0.5)) (cos (* phi2 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0)
(* (* (* (cos phi1) (cos phi2)) t_0) t_0)))
(sqrt
(-
(pow (cos (/ (- phi1 phi2) -2.0)) 2.0)
(*
(pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)
(* (cos phi2) (cos phi1))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((pow(((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0))), sqrt((pow(cos(((phi1 - phi2) / -2.0)), 2.0) - (pow(sin(((lambda1 - lambda2) * 0.5)), 2.0) * (cos(phi2) * cos(phi1)))))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2(sqrt(((((sin((phi1 * 0.5d0)) * cos((phi2 * 0.5d0))) - (cos((phi1 * 0.5d0)) * sin((phi2 * 0.5d0)))) ** 2.0d0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0))), sqrt(((cos(((phi1 - phi2) / (-2.0d0))) ** 2.0d0) - ((sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0) * (cos(phi2) * cos(phi1)))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(((Math.sin((phi1 * 0.5)) * Math.cos((phi2 * 0.5))) - (Math.cos((phi1 * 0.5)) * Math.sin((phi2 * 0.5)))), 2.0) + (((Math.cos(phi1) * Math.cos(phi2)) * t_0) * t_0))), Math.sqrt((Math.pow(Math.cos(((phi1 - phi2) / -2.0)), 2.0) - (Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0) * (Math.cos(phi2) * Math.cos(phi1)))))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) return R * (2.0 * math.atan2(math.sqrt((math.pow(((math.sin((phi1 * 0.5)) * math.cos((phi2 * 0.5))) - (math.cos((phi1 * 0.5)) * math.sin((phi2 * 0.5)))), 2.0) + (((math.cos(phi1) * math.cos(phi2)) * t_0) * t_0))), math.sqrt((math.pow(math.cos(((phi1 - phi2) / -2.0)), 2.0) - (math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0) * (math.cos(phi2) * math.cos(phi1)))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((Float64(Float64(sin(Float64(phi1 * 0.5)) * cos(Float64(phi2 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0))), sqrt(Float64((cos(Float64(Float64(phi1 - phi2) / -2.0)) ^ 2.0) - Float64((sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0) * Float64(cos(phi2) * cos(phi1)))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); tmp = R * (2.0 * atan2(sqrt(((((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))) ^ 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0))), sqrt(((cos(((phi1 - phi2) / -2.0)) ^ 2.0) - ((sin(((lambda1 - lambda2) * 0.5)) ^ 2.0) * (cos(phi2) * cos(phi1))))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[(N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(N[(phi1 - phi2), $MachinePrecision] / -2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\sin \left(\phi_1 \cdot 0.5\right) \cdot \cos \left(\phi_2 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) \cdot t\_0}}{\sqrt{{\cos \left(\frac{\phi_1 - \phi_2}{-2}\right)}^{2} - {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2} \cdot \left(\cos \phi_2 \cdot \cos \phi_1\right)}}\right)
\end{array}
\end{array}
Initial program 60.3%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f6461.3
Applied rewrites61.3%
lift--.f64N/A
lift-+.f64N/A
associate--r+N/A
lower--.f64N/A
Applied rewrites61.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (* (* (cos phi1) (cos phi2)) t_0) t_0)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow
(-
(* (sin (* phi1 0.5)) (cos (* phi2 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0)
t_1))
(sqrt
(-
1.0
(+ (- 0.5 (* 0.5 (cos (* 2.0 (* 0.5 (- phi1 phi2)))))) t_1))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = ((cos(phi1) * cos(phi2)) * t_0) * t_0;
return R * (2.0 * atan2(sqrt((pow(((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0) + t_1)), sqrt((1.0 - ((0.5 - (0.5 * cos((2.0 * (0.5 * (phi1 - phi2)))))) + t_1)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = ((cos(phi1) * cos(phi2)) * t_0) * t_0
code = r * (2.0d0 * atan2(sqrt(((((sin((phi1 * 0.5d0)) * cos((phi2 * 0.5d0))) - (cos((phi1 * 0.5d0)) * sin((phi2 * 0.5d0)))) ** 2.0d0) + t_1)), sqrt((1.0d0 - ((0.5d0 - (0.5d0 * cos((2.0d0 * (0.5d0 * (phi1 - phi2)))))) + t_1)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = ((Math.cos(phi1) * Math.cos(phi2)) * t_0) * t_0;
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(((Math.sin((phi1 * 0.5)) * Math.cos((phi2 * 0.5))) - (Math.cos((phi1 * 0.5)) * Math.sin((phi2 * 0.5)))), 2.0) + t_1)), Math.sqrt((1.0 - ((0.5 - (0.5 * Math.cos((2.0 * (0.5 * (phi1 - phi2)))))) + t_1)))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = ((math.cos(phi1) * math.cos(phi2)) * t_0) * t_0 return R * (2.0 * math.atan2(math.sqrt((math.pow(((math.sin((phi1 * 0.5)) * math.cos((phi2 * 0.5))) - (math.cos((phi1 * 0.5)) * math.sin((phi2 * 0.5)))), 2.0) + t_1)), math.sqrt((1.0 - ((0.5 - (0.5 * math.cos((2.0 * (0.5 * (phi1 - phi2)))))) + t_1)))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0) return Float64(R * Float64(2.0 * atan(sqrt(Float64((Float64(Float64(sin(Float64(phi1 * 0.5)) * cos(Float64(phi2 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0) + t_1)), sqrt(Float64(1.0 - Float64(Float64(0.5 - Float64(0.5 * cos(Float64(2.0 * Float64(0.5 * Float64(phi1 - phi2)))))) + t_1)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = ((cos(phi1) * cos(phi2)) * t_0) * t_0; tmp = R * (2.0 * atan2(sqrt(((((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))) ^ 2.0) + t_1)), sqrt((1.0 - ((0.5 - (0.5 * cos((2.0 * (0.5 * (phi1 - phi2)))))) + t_1))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[(N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(0.5 - N[(0.5 * N[Cos[N[(2.0 * N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $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 := \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{{\left(\sin \left(\phi_1 \cdot 0.5\right) \cdot \cos \left(\phi_2 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2} + t\_1}}{\sqrt{1 - \left(\left(0.5 - 0.5 \cdot \cos \left(2 \cdot \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\right)\right) + t\_1\right)}}\right)
\end{array}
\end{array}
Initial program 60.3%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f6461.3
Applied rewrites61.3%
lift-pow.f64N/A
unpow2N/A
lift-sin.f64N/A
lift-sin.f64N/A
sqr-sin-aN/A
lower--.f64N/A
cos-2N/A
cos-sumN/A
lower-*.f64N/A
cos-sumN/A
cos-2N/A
lower-cos.f64N/A
lower-*.f6461.3
lift-/.f64N/A
clear-numN/A
associate-/r/N/A
metadata-evalN/A
lower-*.f6461.3
Applied rewrites61.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi2) (cos phi1)))
(t_1 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
(*
(atan2
(sqrt (fma t_1 t_0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0)))
(sqrt (- (pow (cos (/ (- phi1 phi2) -2.0)) 2.0) (* t_1 t_0))))
(* R 2.0))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi2) * cos(phi1);
double t_1 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
return atan2(sqrt(fma(t_1, t_0, pow(sin((0.5 * (phi1 - phi2))), 2.0))), sqrt((pow(cos(((phi1 - phi2) / -2.0)), 2.0) - (t_1 * t_0)))) * (R * 2.0);
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi2) * cos(phi1)) t_1 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 return Float64(atan(sqrt(fma(t_1, t_0, (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0))), sqrt(Float64((cos(Float64(Float64(phi1 - phi2) / -2.0)) ^ 2.0) - Float64(t_1 * t_0)))) * Float64(R * 2.0)) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(N[ArcTan[N[Sqrt[N[(t$95$1 * t$95$0 + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(N[(phi1 - phi2), $MachinePrecision] / -2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(t$95$1 * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(R * 2.0), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_2 \cdot \cos \phi_1\\
t_1 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_1, t\_0, {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}}{\sqrt{{\cos \left(\frac{\phi_1 - \phi_2}{-2}\right)}^{2} - t\_1 \cdot t\_0}} \cdot \left(R \cdot 2\right)
\end{array}
\end{array}
Initial program 60.3%
Applied rewrites60.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (* (* (cos phi1) (cos phi2)) t_0) t_0)))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) t_1))
(sqrt
(-
1.0
(+ (- 0.5 (* 0.5 (cos (* 2.0 (* 0.5 (- phi1 phi2)))))) t_1))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = ((cos(phi1) * cos(phi2)) * t_0) * t_0;
return R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), sqrt((1.0 - ((0.5 - (0.5 * cos((2.0 * (0.5 * (phi1 - phi2)))))) + t_1)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = ((cos(phi1) * cos(phi2)) * t_0) * t_0
code = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + t_1)), sqrt((1.0d0 - ((0.5d0 - (0.5d0 * cos((2.0d0 * (0.5d0 * (phi1 - phi2)))))) + t_1)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = ((Math.cos(phi1) * Math.cos(phi2)) * t_0) * t_0;
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), Math.sqrt((1.0 - ((0.5 - (0.5 * Math.cos((2.0 * (0.5 * (phi1 - phi2)))))) + t_1)))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = ((math.cos(phi1) * math.cos(phi2)) * t_0) * t_0 return R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), math.sqrt((1.0 - ((0.5 - (0.5 * math.cos((2.0 * (0.5 * (phi1 - phi2)))))) + t_1)))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0) return Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + t_1)), sqrt(Float64(1.0 - Float64(Float64(0.5 - Float64(0.5 * cos(Float64(2.0 * Float64(0.5 * Float64(phi1 - phi2)))))) + t_1)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = ((cos(phi1) * cos(phi2)) * t_0) * t_0; tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + t_1)), sqrt((1.0 - ((0.5 - (0.5 * cos((2.0 * (0.5 * (phi1 - phi2)))))) + t_1))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(0.5 - N[(0.5 * N[Cos[N[(2.0 * N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $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 := \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{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_1}}{\sqrt{1 - \left(\left(0.5 - 0.5 \cdot \cos \left(2 \cdot \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\right)\right) + t\_1\right)}}\right)
\end{array}
\end{array}
Initial program 60.3%
lift-pow.f64N/A
unpow2N/A
lift-sin.f64N/A
lift-sin.f64N/A
sqr-sin-aN/A
lower--.f64N/A
cos-2N/A
cos-sumN/A
lower-*.f64N/A
cos-sumN/A
cos-2N/A
lower-cos.f64N/A
lower-*.f6460.4
lift-/.f64N/A
clear-numN/A
associate-/r/N/A
metadata-evalN/A
lower-*.f6460.4
Applied rewrites60.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_1 (sin (/ (- lambda1 lambda2) 2.0))))
(if (or (<= phi2 -9.5e-5) (not (<= phi2 0.001)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (* -0.5 phi2)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_1) t_1)))
(sqrt (- (pow (cos (* -0.5 phi2)) 2.0) (* t_0 (cos phi2)))))))
(*
(atan2
(sqrt
(fma
t_0
(* (cos phi2) (cos phi1))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)))
(sqrt (fma (- (cos phi1)) t_0 (pow (cos (* -0.5 phi1)) 2.0))))
(* R 2.0)))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((phi2 <= -9.5e-5) || !(phi2 <= 0.001)) {
tmp = R * (2.0 * atan2(sqrt((pow(sin((-0.5 * phi2)), 2.0) + (((cos(phi1) * cos(phi2)) * t_1) * t_1))), sqrt((pow(cos((-0.5 * phi2)), 2.0) - (t_0 * cos(phi2))))));
} else {
tmp = atan2(sqrt(fma(t_0, (cos(phi2) * cos(phi1)), pow(sin((0.5 * (phi1 - phi2))), 2.0))), sqrt(fma(-cos(phi1), t_0, pow(cos((-0.5 * phi1)), 2.0)))) * (R * 2.0);
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if ((phi2 <= -9.5e-5) || !(phi2 <= 0.001)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(-0.5 * phi2)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_1) * t_1))), sqrt(Float64((cos(Float64(-0.5 * phi2)) ^ 2.0) - Float64(t_0 * cos(phi2))))))); else tmp = Float64(atan(sqrt(fma(t_0, Float64(cos(phi2) * cos(phi1)), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0))), sqrt(fma(Float64(-cos(phi1)), t_0, (cos(Float64(-0.5 * phi1)) ^ 2.0)))) * Float64(R * 2.0)); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[phi2, -9.5e-5], N[Not[LessEqual[phi2, 0.001]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$1), $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(t$95$0 * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[ArcTan[N[Sqrt[N[(t$95$0 * N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[((-N[Cos[phi1], $MachinePrecision]) * t$95$0 + N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(R * 2.0), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\phi_2 \leq -9.5 \cdot 10^{-5} \lor \neg \left(\phi_2 \leq 0.001\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(-0.5 \cdot \phi_2\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_1\right) \cdot t\_1}}{\sqrt{{\cos \left(-0.5 \cdot \phi_2\right)}^{2} - t\_0 \cdot \cos \phi_2}}\right)\\
\mathbf{else}:\\
\;\;\;\;\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \cos \phi_2 \cdot \cos \phi_1, {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}}{\sqrt{\mathsf{fma}\left(-\cos \phi_1, t\_0, {\cos \left(-0.5 \cdot \phi_1\right)}^{2}\right)}} \cdot \left(R \cdot 2\right)\\
\end{array}
\end{array}
if phi2 < -9.5000000000000005e-5 or 1e-3 < phi2 Initial program 45.9%
Taylor expanded in phi1 around 0
lower-*.f6446.1
Applied rewrites46.1%
Taylor expanded in phi1 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites47.0%
if -9.5000000000000005e-5 < phi2 < 1e-3Initial program 74.5%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites74.6%
Applied rewrites74.6%
Final simplification60.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
(if (or (<= phi2 -1.35e-5) (not (<= phi2 0.000145)))
(*
R
(*
2.0
(atan2
(sqrt (fma t_0 (cos phi2) (pow (sin (* -0.5 phi2)) 2.0)))
(sqrt
(-
1.0
(fma
(* (cos phi1) (cos phi2))
(pow (sin (* (- lambda2 lambda1) -0.5)) 2.0)
(pow (sin (* (- phi1 phi2) 0.5)) 2.0)))))))
(*
(atan2
(sqrt
(fma
t_0
(* (cos phi2) (cos phi1))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)))
(sqrt (fma (- (cos phi1)) t_0 (pow (cos (* -0.5 phi1)) 2.0))))
(* R 2.0)))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double tmp;
if ((phi2 <= -1.35e-5) || !(phi2 <= 0.000145)) {
tmp = R * (2.0 * atan2(sqrt(fma(t_0, cos(phi2), pow(sin((-0.5 * phi2)), 2.0))), sqrt((1.0 - fma((cos(phi1) * cos(phi2)), pow(sin(((lambda2 - lambda1) * -0.5)), 2.0), pow(sin(((phi1 - phi2) * 0.5)), 2.0))))));
} else {
tmp = atan2(sqrt(fma(t_0, (cos(phi2) * cos(phi1)), pow(sin((0.5 * (phi1 - phi2))), 2.0))), sqrt(fma(-cos(phi1), t_0, pow(cos((-0.5 * phi1)), 2.0)))) * (R * 2.0);
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 tmp = 0.0 if ((phi2 <= -1.35e-5) || !(phi2 <= 0.000145)) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_0, cos(phi2), (sin(Float64(-0.5 * phi2)) ^ 2.0))), sqrt(Float64(1.0 - fma(Float64(cos(phi1) * cos(phi2)), (sin(Float64(Float64(lambda2 - lambda1) * -0.5)) ^ 2.0), (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0))))))); else tmp = Float64(atan(sqrt(fma(t_0, Float64(cos(phi2) * cos(phi1)), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0))), sqrt(fma(Float64(-cos(phi1)), t_0, (cos(Float64(-0.5 * phi1)) ^ 2.0)))) * Float64(R * 2.0)); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[phi2, -1.35e-5], N[Not[LessEqual[phi2, 0.000145]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda2 - lambda1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[ArcTan[N[Sqrt[N[(t$95$0 * N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[((-N[Cos[phi1], $MachinePrecision]) * t$95$0 + N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(R * 2.0), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
\mathbf{if}\;\phi_2 \leq -1.35 \cdot 10^{-5} \lor \neg \left(\phi_2 \leq 0.000145\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \cos \phi_2, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1 \cdot \cos \phi_2, {\sin \left(\left(\lambda_2 - \lambda_1\right) \cdot -0.5\right)}^{2}, {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \cos \phi_2 \cdot \cos \phi_1, {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}}{\sqrt{\mathsf{fma}\left(-\cos \phi_1, t\_0, {\cos \left(-0.5 \cdot \phi_1\right)}^{2}\right)}} \cdot \left(R \cdot 2\right)\\
\end{array}
\end{array}
if phi2 < -1.3499999999999999e-5 or 1.45e-4 < phi2 Initial program 45.9%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--l+N/A
*-commutativeN/A
associate-*r*N/A
lower-fma.f64N/A
Applied rewrites9.3%
Taylor expanded in phi1 around 0
Applied rewrites20.9%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6422.0
Applied rewrites22.0%
Taylor expanded in lambda1 around -inf
lower--.f64N/A
associate-*r*N/A
lower-fma.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
unsub-negN/A
lower--.f64N/A
Applied rewrites46.6%
if -1.3499999999999999e-5 < phi2 < 1.45e-4Initial program 74.5%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites74.6%
Applied rewrites74.6%
Final simplification60.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
(if (or (<= phi2 -0.000104) (not (<= phi2 0.00106)))
(*
R
(*
2.0
(atan2
(sqrt (fma t_0 (cos phi2) (pow (sin (* -0.5 phi2)) 2.0)))
(sqrt
(-
1.0
(fma
(* (cos phi1) (cos phi2))
(pow (sin (* -0.5 lambda2)) 2.0)
(pow (sin (* (- phi1 phi2) 0.5)) 2.0)))))))
(*
(atan2
(sqrt
(fma
t_0
(* (cos phi2) (cos phi1))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)))
(sqrt (fma (- (cos phi1)) t_0 (pow (cos (* -0.5 phi1)) 2.0))))
(* R 2.0)))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double tmp;
if ((phi2 <= -0.000104) || !(phi2 <= 0.00106)) {
tmp = R * (2.0 * atan2(sqrt(fma(t_0, cos(phi2), pow(sin((-0.5 * phi2)), 2.0))), sqrt((1.0 - fma((cos(phi1) * cos(phi2)), pow(sin((-0.5 * lambda2)), 2.0), pow(sin(((phi1 - phi2) * 0.5)), 2.0))))));
} else {
tmp = atan2(sqrt(fma(t_0, (cos(phi2) * cos(phi1)), pow(sin((0.5 * (phi1 - phi2))), 2.0))), sqrt(fma(-cos(phi1), t_0, pow(cos((-0.5 * phi1)), 2.0)))) * (R * 2.0);
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 tmp = 0.0 if ((phi2 <= -0.000104) || !(phi2 <= 0.00106)) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_0, cos(phi2), (sin(Float64(-0.5 * phi2)) ^ 2.0))), sqrt(Float64(1.0 - fma(Float64(cos(phi1) * cos(phi2)), (sin(Float64(-0.5 * lambda2)) ^ 2.0), (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0))))))); else tmp = Float64(atan(sqrt(fma(t_0, Float64(cos(phi2) * cos(phi1)), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0))), sqrt(fma(Float64(-cos(phi1)), t_0, (cos(Float64(-0.5 * phi1)) ^ 2.0)))) * Float64(R * 2.0)); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[phi2, -0.000104], N[Not[LessEqual[phi2, 0.00106]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[Power[N[Sin[N[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[ArcTan[N[Sqrt[N[(t$95$0 * N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[((-N[Cos[phi1], $MachinePrecision]) * t$95$0 + N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(R * 2.0), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
\mathbf{if}\;\phi_2 \leq -0.000104 \lor \neg \left(\phi_2 \leq 0.00106\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \cos \phi_2, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1 \cdot \cos \phi_2, {\sin \left(-0.5 \cdot \lambda_2\right)}^{2}, {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \cos \phi_2 \cdot \cos \phi_1, {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}}{\sqrt{\mathsf{fma}\left(-\cos \phi_1, t\_0, {\cos \left(-0.5 \cdot \phi_1\right)}^{2}\right)}} \cdot \left(R \cdot 2\right)\\
\end{array}
\end{array}
if phi2 < -1.03999999999999994e-4 or 0.00105999999999999996 < phi2 Initial program 45.9%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--l+N/A
*-commutativeN/A
associate-*r*N/A
lower-fma.f64N/A
Applied rewrites9.3%
Taylor expanded in phi1 around 0
Applied rewrites20.9%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6422.0
Applied rewrites22.0%
Taylor expanded in lambda1 around 0
lower--.f64N/A
associate-*r*N/A
lower-fma.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
Applied rewrites39.2%
if -1.03999999999999994e-4 < phi2 < 0.00105999999999999996Initial program 74.5%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites74.6%
Applied rewrites74.6%
Final simplification57.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_2 (* (cos phi1) (cos phi2))))
(if (or (<= phi2 -0.000104) (not (<= phi2 0.00106)))
(*
R
(*
2.0
(atan2
(sqrt (fma t_1 (cos phi2) (pow (sin (* -0.5 phi2)) 2.0)))
(sqrt
(-
1.0
(fma
t_2
(pow (sin (* -0.5 lambda2)) 2.0)
(pow (sin (* (- phi1 phi2) 0.5)) 2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(- 0.5 (* 0.5 (cos (* 2.0 (* 0.5 (- phi1 phi2))))))
(* (* t_2 t_0) t_0)))
(sqrt (- (pow (cos (* -0.5 phi1)) 2.0) (* t_1 (cos phi1))))))))))
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(((lambda1 - lambda2) * 0.5)), 2.0);
double t_2 = cos(phi1) * cos(phi2);
double tmp;
if ((phi2 <= -0.000104) || !(phi2 <= 0.00106)) {
tmp = R * (2.0 * atan2(sqrt(fma(t_1, cos(phi2), pow(sin((-0.5 * phi2)), 2.0))), sqrt((1.0 - fma(t_2, pow(sin((-0.5 * lambda2)), 2.0), pow(sin(((phi1 - phi2) * 0.5)), 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt(((0.5 - (0.5 * cos((2.0 * (0.5 * (phi1 - phi2)))))) + ((t_2 * t_0) * t_0))), sqrt((pow(cos((-0.5 * phi1)), 2.0) - (t_1 * cos(phi1))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_2 = Float64(cos(phi1) * cos(phi2)) tmp = 0.0 if ((phi2 <= -0.000104) || !(phi2 <= 0.00106)) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_1, cos(phi2), (sin(Float64(-0.5 * phi2)) ^ 2.0))), sqrt(Float64(1.0 - fma(t_2, (sin(Float64(-0.5 * lambda2)) ^ 2.0), (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(0.5 - Float64(0.5 * cos(Float64(2.0 * Float64(0.5 * Float64(phi1 - phi2)))))) + Float64(Float64(t_2 * t_0) * t_0))), sqrt(Float64((cos(Float64(-0.5 * phi1)) ^ 2.0) - Float64(t_1 * cos(phi1))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[phi2, -0.000104], N[Not[LessEqual[phi2, 0.00106]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$2 * N[Power[N[Sin[N[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(0.5 - N[(0.5 * N[Cos[N[(2.0 * N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(t$95$2 * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(t$95$1 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
\mathbf{if}\;\phi_2 \leq -0.000104 \lor \neg \left(\phi_2 \leq 0.00106\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_1, \cos \phi_2, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left(t\_2, {\sin \left(-0.5 \cdot \lambda_2\right)}^{2}, {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\left(0.5 - 0.5 \cdot \cos \left(2 \cdot \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\right)\right) + \left(t\_2 \cdot t\_0\right) \cdot t\_0}}{\sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - t\_1 \cdot \cos \phi_1}}\right)\\
\end{array}
\end{array}
if phi2 < -1.03999999999999994e-4 or 0.00105999999999999996 < phi2 Initial program 45.9%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--l+N/A
*-commutativeN/A
associate-*r*N/A
lower-fma.f64N/A
Applied rewrites9.3%
Taylor expanded in phi1 around 0
Applied rewrites20.9%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6422.0
Applied rewrites22.0%
Taylor expanded in lambda1 around 0
lower--.f64N/A
associate-*r*N/A
lower-fma.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
Applied rewrites39.2%
if -1.03999999999999994e-4 < phi2 < 0.00105999999999999996Initial program 74.5%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites74.6%
lift-pow.f64N/A
unpow2N/A
lift-sin.f64N/A
lift-sin.f64N/A
sqr-sin-aN/A
lower--.f64N/A
cos-2N/A
cos-sumN/A
lower-*.f64N/A
cos-sumN/A
cos-2N/A
lower-cos.f64N/A
lower-*.f6471.4
lift-/.f64N/A
clear-numN/A
associate-/r/N/A
metadata-evalN/A
lower-*.f6471.4
Applied rewrites71.4%
Final simplification55.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
(atan2
(sqrt
(fma
(pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)
(* (cos phi2) (cos phi1))
(pow (sin (* (- phi1 phi2) 0.5)) 2.0)))
(sqrt (pow (cos (/ (- lambda1 lambda2) -2.0)) 2.0)))
(* R 2.0)))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return atan2(sqrt(fma(pow(sin(((lambda1 - lambda2) * 0.5)), 2.0), (cos(phi2) * cos(phi1)), pow(sin(((phi1 - phi2) * 0.5)), 2.0))), sqrt(pow(cos(((lambda1 - lambda2) / -2.0)), 2.0))) * (R * 2.0);
}
function code(R, lambda1, lambda2, phi1, phi2) return Float64(atan(sqrt(fma((sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0), Float64(cos(phi2) * cos(phi1)), (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0))), sqrt((cos(Float64(Float64(lambda1 - lambda2) / -2.0)) ^ 2.0))) * Float64(R * 2.0)) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[Power[N[Cos[N[(N[(lambda1 - lambda2), $MachinePrecision] / -2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(R * 2.0), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left({\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}, \cos \phi_2 \cdot \cos \phi_1, {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\right)}}{\sqrt{{\cos \left(\frac{\lambda_1 - \lambda_2}{-2}\right)}^{2}}} \cdot \left(R \cdot 2\right)
\end{array}
Initial program 60.3%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--l+N/A
*-commutativeN/A
associate-*r*N/A
lower-fma.f64N/A
Applied rewrites42.3%
Taylor expanded in phi1 around 0
Applied rewrites35.2%
Applied rewrites35.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
(*
R
(*
2.0
(atan2
(sqrt (fma t_0 (cos phi2) (pow (sin (* -0.5 phi2)) 2.0)))
(sqrt (- 1.0 t_0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
return R * (2.0 * atan2(sqrt(fma(t_0, cos(phi2), pow(sin((-0.5 * phi2)), 2.0))), sqrt((1.0 - t_0))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 return Float64(R * Float64(2.0 * atan(sqrt(fma(t_0, cos(phi2), (sin(Float64(-0.5 * phi2)) ^ 2.0))), sqrt(Float64(1.0 - t_0))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \cos \phi_2, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)}}{\sqrt{1 - t\_0}}\right)
\end{array}
\end{array}
Initial program 60.3%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--l+N/A
*-commutativeN/A
associate-*r*N/A
lower-fma.f64N/A
Applied rewrites42.3%
Taylor expanded in phi1 around 0
Applied rewrites35.2%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6433.8
Applied rewrites33.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
(*
R
(*
2.0
(atan2
(sqrt (fma t_0 (cos phi1) (pow (sin (* 0.5 phi1)) 2.0)))
(sqrt (- 1.0 t_0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
return R * (2.0 * atan2(sqrt(fma(t_0, cos(phi1), pow(sin((0.5 * phi1)), 2.0))), sqrt((1.0 - t_0))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 return Float64(R * Float64(2.0 * atan(sqrt(fma(t_0, cos(phi1), (sin(Float64(0.5 * phi1)) ^ 2.0))), sqrt(Float64(1.0 - t_0))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \cos \phi_1, {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)}}{\sqrt{1 - t\_0}}\right)
\end{array}
\end{array}
Initial program 60.3%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--l+N/A
*-commutativeN/A
associate-*r*N/A
lower-fma.f64N/A
Applied rewrites42.3%
Taylor expanded in phi1 around 0
Applied rewrites35.2%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6433.8
Applied rewrites33.8%
Taylor expanded in phi2 around 0
lower-sqrt.f64N/A
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6433.4
Applied rewrites33.4%
herbie shell --seed 2024313
(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))))))))))