
(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 15 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_0) t_0))))
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0);
return R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0)
code = r * (2.0d0 * atan2(sqrt(t_1), sqrt((1.0d0 - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((Math.cos(phi1) * Math.cos(phi2)) * t_0) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt(t_1), Math.sqrt((1.0 - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((math.cos(phi1) * math.cos(phi2)) * t_0) * t_0) return R * (2.0 * math.atan2(math.sqrt(t_1), math.sqrt((1.0 - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0); tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$1], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) \cdot t\_0\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)
\end{array}
\end{array}
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow
(-
(* (sin (/ phi1 2.0)) (cos (/ phi2 2.0)))
(* (cos (/ phi1 2.0)) (sin (/ phi2 2.0))))
2.0)
(*
(cos phi2)
(*
(cos phi1)
(pow
(-
(* (sin (/ lambda1 2.0)) (cos (/ lambda2 2.0)))
(* (cos (/ lambda1 2.0)) (sin (/ lambda2 2.0))))
2.0)))))
(sqrt
(-
1.0
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_0) t_0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((pow(((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))), 2.0) + (cos(phi2) * (cos(phi1) * pow(((sin((lambda1 / 2.0)) * cos((lambda2 / 2.0))) - (cos((lambda1 / 2.0)) * sin((lambda2 / 2.0)))), 2.0))))), sqrt((1.0 - (pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi1) * cos(phi2)) * t_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 = sin(((lambda1 - lambda2) / 2.0d0))
code = r * (2.0d0 * atan2(sqrt(((((sin((phi1 / 2.0d0)) * cos((phi2 / 2.0d0))) - (cos((phi1 / 2.0d0)) * sin((phi2 / 2.0d0)))) ** 2.0d0) + (cos(phi2) * (cos(phi1) * (((sin((lambda1 / 2.0d0)) * cos((lambda2 / 2.0d0))) - (cos((lambda1 / 2.0d0)) * sin((lambda2 / 2.0d0)))) ** 2.0d0))))), sqrt((1.0d0 - ((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0))))))
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 / 2.0)) * Math.cos((phi2 / 2.0))) - (Math.cos((phi1 / 2.0)) * Math.sin((phi2 / 2.0)))), 2.0) + (Math.cos(phi2) * (Math.cos(phi1) * Math.pow(((Math.sin((lambda1 / 2.0)) * Math.cos((lambda2 / 2.0))) - (Math.cos((lambda1 / 2.0)) * Math.sin((lambda2 / 2.0)))), 2.0))))), Math.sqrt((1.0 - (Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((Math.cos(phi1) * Math.cos(phi2)) * t_0) * t_0))))));
}
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 / 2.0)) * math.cos((phi2 / 2.0))) - (math.cos((phi1 / 2.0)) * math.sin((phi2 / 2.0)))), 2.0) + (math.cos(phi2) * (math.cos(phi1) * math.pow(((math.sin((lambda1 / 2.0)) * math.cos((lambda2 / 2.0))) - (math.cos((lambda1 / 2.0)) * math.sin((lambda2 / 2.0)))), 2.0))))), math.sqrt((1.0 - (math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((math.cos(phi1) * math.cos(phi2)) * t_0) * t_0))))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((Float64(Float64(sin(Float64(phi1 / 2.0)) * cos(Float64(phi2 / 2.0))) - Float64(cos(Float64(phi1 / 2.0)) * sin(Float64(phi2 / 2.0)))) ^ 2.0) + Float64(cos(phi2) * Float64(cos(phi1) * (Float64(Float64(sin(Float64(lambda1 / 2.0)) * cos(Float64(lambda2 / 2.0))) - Float64(cos(Float64(lambda1 / 2.0)) * sin(Float64(lambda2 / 2.0)))) ^ 2.0))))), sqrt(Float64(1.0 - Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); tmp = R * (2.0 * atan2(sqrt(((((sin((phi1 / 2.0)) * cos((phi2 / 2.0))) - (cos((phi1 / 2.0)) * sin((phi2 / 2.0)))) ^ 2.0) + (cos(phi2) * (cos(phi1) * (((sin((lambda1 / 2.0)) * cos((lambda2 / 2.0))) - (cos((lambda1 / 2.0)) * sin((lambda2 / 2.0)))) ^ 2.0))))), sqrt((1.0 - ((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[(N[Sin[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Cos[phi2], $MachinePrecision] * N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[(N[(N[Sin[N[(lambda1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(lambda2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(lambda1 / 2.0), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(lambda2 / 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - 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]), $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(\frac{\phi_1}{2}\right) \cdot \cos \left(\frac{\phi_2}{2}\right) - \cos \left(\frac{\phi_1}{2}\right) \cdot \sin \left(\frac{\phi_2}{2}\right)\right)}^{2} + \cos \phi_2 \cdot \left(\cos \phi_1 \cdot {\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}\right)}}{\sqrt{1 - \left({\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\right)}}\right)
\end{array}
\end{array}
Initial program 63.8%
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
lower-/.f64N/A
lower-cos.f64N/A
lower-/.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
lower-/.f64N/A
lower-sin.f64N/A
lower-/.f6464.9
Applied rewrites64.9%
lift-*.f64N/A
lift-*.f64N/A
associate-*l*N/A
lift-*.f64N/A
*-commutativeN/A
unpow2N/A
lift-pow.f64N/A
associate-*l*N/A
lower-*.f64N/A
lower-*.f6464.9
Applied rewrites64.9%
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
lower-/.f64N/A
lower-cos.f64N/A
lower-/.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
lower-/.f64N/A
lower-sin.f64N/A
lower-/.f6465.5
Applied rewrites65.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda2 lambda1) -0.5)) 2.0)))
(*
R
(*
(atan2
(sqrt
(fma
(* t_0 (cos phi2))
(cos phi1)
(pow
(fma
(cos (* -0.5 phi2))
(sin (* 0.5 phi1))
(* (sin (* -0.5 phi2)) (cos (* -0.5 phi1))))
2.0)))
(sqrt
(-
1.0
(fma
(* (cos phi2) (cos phi1))
t_0
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)))))
2.0))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda2 - lambda1) * -0.5)), 2.0);
return R * (atan2(sqrt(fma((t_0 * cos(phi2)), cos(phi1), pow(fma(cos((-0.5 * phi2)), sin((0.5 * phi1)), (sin((-0.5 * phi2)) * cos((-0.5 * phi1)))), 2.0))), sqrt((1.0 - fma((cos(phi2) * cos(phi1)), t_0, pow(sin((0.5 * (phi1 - phi2))), 2.0))))) * 2.0);
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda2 - lambda1) * -0.5)) ^ 2.0 return Float64(R * Float64(atan(sqrt(fma(Float64(t_0 * cos(phi2)), cos(phi1), (fma(cos(Float64(-0.5 * phi2)), sin(Float64(0.5 * phi1)), Float64(sin(Float64(-0.5 * phi2)) * cos(Float64(-0.5 * phi1)))) ^ 2.0))), sqrt(Float64(1.0 - fma(Float64(cos(phi2) * cos(phi1)), t_0, (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0))))) * 2.0)) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda2 - lambda1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(R * N[(N[ArcTan[N[Sqrt[N[(N[(t$95$0 * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[Cos[phi1], $MachinePrecision] + 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]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] * t$95$0 + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_2 - \lambda_1\right) \cdot -0.5\right)}^{2}\\
R \cdot \left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0 \cdot \cos \phi_2, \cos \phi_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}\right)}}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_2 \cdot \cos \phi_1, t\_0, {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}} \cdot 2\right)
\end{array}
\end{array}
Initial program 63.8%
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
lower-/.f64N/A
lower-cos.f64N/A
lower-/.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
lower-/.f64N/A
lower-sin.f64N/A
lower-/.f6464.9
Applied rewrites64.9%
lift-*.f64N/A
lift-*.f64N/A
associate-*l*N/A
lift-*.f64N/A
*-commutativeN/A
unpow2N/A
lift-pow.f64N/A
associate-*l*N/A
lower-*.f64N/A
lower-*.f6464.9
Applied rewrites64.9%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-*.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
lower--.f64N/A
lower-cos.f6452.1
Applied rewrites52.1%
Taylor expanded in lambda1 around -inf
Applied rewrites64.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi2) (cos phi1)))
(t_1 (pow (sin (/ (- lambda1 lambda2) 2.0)) 2.0)))
(*
(atan2
(sqrt (fma t_1 t_0 (pow (sin (/ (- phi1 phi2) 2.0)) 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(((lambda1 - lambda2) / 2.0)), 2.0);
return atan2(sqrt(fma(t_1, t_0, pow(sin(((phi1 - phi2) / 2.0)), 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(Float64(lambda1 - lambda2) / 2.0)) ^ 2.0 return Float64(atan(sqrt(fma(t_1, t_0, (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 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[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(N[ArcTan[N[Sqrt[N[(t$95$1 * t$95$0 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $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(\frac{\lambda_1 - \lambda_2}{2}\right)}^{2}\\
\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_1, t\_0, {\sin \left(\frac{\phi_1 - \phi_2}{2}\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 63.8%
Applied rewrites63.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(fma
(* (cos phi2) (cos phi1))
(pow (sin (* (- lambda2 lambda1) -0.5)) 2.0)
(pow (sin (* (- phi2 phi1) -0.5)) 2.0))))
(* R (* 2.0 (atan2 (sqrt t_0) (sqrt (- 1.0 t_0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = fma((cos(phi2) * cos(phi1)), pow(sin(((lambda2 - lambda1) * -0.5)), 2.0), pow(sin(((phi2 - phi1) * -0.5)), 2.0));
return R * (2.0 * atan2(sqrt(t_0), sqrt((1.0 - t_0))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = fma(Float64(cos(phi2) * cos(phi1)), (sin(Float64(Float64(lambda2 - lambda1) * -0.5)) ^ 2.0), (sin(Float64(Float64(phi2 - phi1) * -0.5)) ^ 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(t_0), sqrt(Float64(1.0 - t_0))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda2 - lambda1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[Sin[N[(N[(phi2 - phi1), $MachinePrecision] * -0.5), $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 := \mathsf{fma}\left(\cos \phi_2 \cdot \cos \phi_1, {\sin \left(\left(\lambda_2 - \lambda_1\right) \cdot -0.5\right)}^{2}, {\sin \left(\left(\phi_2 - \phi_1\right) \cdot -0.5\right)}^{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0}}{\sqrt{1 - t\_0}}\right)
\end{array}
\end{array}
Initial program 63.8%
Taylor expanded in lambda1 around 0
Applied rewrites63.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda2 lambda1) -0.5)) 2.0))
(t_1 (sin (/ (- lambda1 lambda2) 2.0))))
(if (or (<= phi1 -8.5e-5) (not (<= phi1 2.75e-12)))
(*
R
(*
2.0
(atan2
(sqrt
(fma
(pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)
(cos phi1)
(pow (sin (* 0.5 phi1)) 2.0)))
(sqrt (- (pow (cos (* -0.5 phi1)) 2.0) (* t_0 (cos phi1)))))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_1) t_1)))
(sqrt (- (pow (cos (* 0.5 phi2)) 2.0) (* t_0 (cos phi2))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda2 - lambda1) * -0.5)), 2.0);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((phi1 <= -8.5e-5) || !(phi1 <= 2.75e-12)) {
tmp = R * (2.0 * atan2(sqrt(fma(pow(sin((0.5 * (lambda1 - lambda2))), 2.0), cos(phi1), pow(sin((0.5 * phi1)), 2.0))), sqrt((pow(cos((-0.5 * phi1)), 2.0) - (t_0 * cos(phi1))))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi1) * cos(phi2)) * t_1) * t_1))), sqrt((pow(cos((0.5 * phi2)), 2.0) - (t_0 * cos(phi2))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda2 - lambda1) * -0.5)) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if ((phi1 <= -8.5e-5) || !(phi1 <= 2.75e-12)) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma((sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0), cos(phi1), (sin(Float64(0.5 * phi1)) ^ 2.0))), sqrt(Float64((cos(Float64(-0.5 * phi1)) ^ 2.0) - Float64(t_0 * cos(phi1))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 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))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda2 - lambda1), $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[phi1, -8.5e-5], N[Not[LessEqual[phi1, 2.75e-12]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(t$95$0 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(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]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_2 - \lambda_1\right) \cdot -0.5\right)}^{2}\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\phi_1 \leq -8.5 \cdot 10^{-5} \lor \neg \left(\phi_1 \leq 2.75 \cdot 10^{-12}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left({\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}, \cos \phi_1, {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)}}{\sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - t\_0 \cdot \cos \phi_1}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{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)\\
\end{array}
\end{array}
if phi1 < -8.500000000000001e-5 or 2.7500000000000002e-12 < phi1 Initial program 46.3%
Taylor expanded in phi2 around 0
Applied rewrites46.6%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6419.7
Applied rewrites19.7%
Taylor expanded in phi2 around 0
lower-sqrt.f64N/A
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6448.1
Applied rewrites48.1%
if -8.500000000000001e-5 < phi1 < 2.7500000000000002e-12Initial program 79.5%
Taylor expanded in phi1 around 0
Applied rewrites79.6%
Final simplification64.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))
(t_1 (cos (* -0.5 phi1)))
(t_2 (* t_0 (cos phi1))))
(if (or (<= phi2 -4400.0) (not (<= phi2 1.32e-5)))
(*
R
(*
2.0
(atan2
(sqrt (fma t_0 (cos phi2) (pow (sin (* -0.5 phi2)) 2.0)))
(sqrt
(-
(-
1.0
(*
(pow (sin (/ (- lambda1 lambda2) 2.0)) 2.0)
(* (cos phi2) (cos phi1))))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0))))))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (fma t_1 (* -0.5 phi2) (sin (* 0.5 phi1))) 2.0) t_2))
(sqrt (- (pow t_1 2.0) t_2))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double t_1 = cos((-0.5 * phi1));
double t_2 = t_0 * cos(phi1);
double tmp;
if ((phi2 <= -4400.0) || !(phi2 <= 1.32e-5)) {
tmp = R * (2.0 * atan2(sqrt(fma(t_0, cos(phi2), pow(sin((-0.5 * phi2)), 2.0))), sqrt(((1.0 - (pow(sin(((lambda1 - lambda2) / 2.0)), 2.0) * (cos(phi2) * cos(phi1)))) - pow(sin(((phi1 - phi2) / 2.0)), 2.0)))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(fma(t_1, (-0.5 * phi2), sin((0.5 * phi1))), 2.0) + t_2)), sqrt((pow(t_1, 2.0) - t_2))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 t_1 = cos(Float64(-0.5 * phi1)) t_2 = Float64(t_0 * cos(phi1)) tmp = 0.0 if ((phi2 <= -4400.0) || !(phi2 <= 1.32e-5)) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_0, cos(phi2), (sin(Float64(-0.5 * phi2)) ^ 2.0))), sqrt(Float64(Float64(1.0 - Float64((sin(Float64(Float64(lambda1 - lambda2) / 2.0)) ^ 2.0) * Float64(cos(phi2) * cos(phi1)))) - (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((fma(t_1, Float64(-0.5 * phi2), sin(Float64(0.5 * phi1))) ^ 2.0) + t_2)), sqrt(Float64((t_1 ^ 2.0) - t_2))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(t$95$0 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[phi2, -4400.0], N[Not[LessEqual[phi2, 1.32e-5]], $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[(N[(1.0 - N[(N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(t$95$1 * N[(-0.5 * phi2), $MachinePrecision] + N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$2), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[t$95$1, 2.0], $MachinePrecision] - t$95$2), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
t_1 := \cos \left(-0.5 \cdot \phi_1\right)\\
t_2 := t\_0 \cdot \cos \phi_1\\
\mathbf{if}\;\phi_2 \leq -4400 \lor \neg \left(\phi_2 \leq 1.32 \cdot 10^{-5}\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{\left(1 - {\sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)}^{2} \cdot \left(\cos \phi_2 \cdot \cos \phi_1\right)\right) - {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(t\_1, -0.5 \cdot \phi_2, \sin \left(0.5 \cdot \phi_1\right)\right)\right)}^{2} + t\_2}}{\sqrt{{t\_1}^{2} - t\_2}}\right)\\
\end{array}
\end{array}
if phi2 < -4400 or 1.32000000000000007e-5 < phi2 Initial program 50.5%
Taylor expanded in phi2 around 0
lower-sin.f64N/A
lower-*.f6414.1
Applied rewrites14.1%
lift--.f64N/A
lift-+.f64N/A
+-commutativeN/A
associate--r+N/A
lower--.f64N/A
Applied rewrites14.1%
Taylor expanded in phi1 around 0
lower-sqrt.f64N/A
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6451.6
Applied rewrites51.6%
if -4400 < phi2 < 1.32000000000000007e-5Initial program 78.0%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate-*r*N/A
*-commutativeN/A
lower-fma.f64N/A
cos-neg-revN/A
lower-cos.f64N/A
distribute-lft-neg-inN/A
metadata-evalN/A
lower-*.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
lower-*.f6477.9
Applied rewrites77.9%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sin-revN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
cos-neg-revN/A
lower-cos.f64N/A
distribute-lft-neg-inN/A
metadata-evalN/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites77.9%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-*.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
lower--.f64N/A
lower-cos.f6477.9
Applied rewrites77.9%
Final simplification64.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (* -0.5 phi1)))
(t_1 (* (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0) (cos phi1))))
(if (or (<= phi2 -4400.0) (not (<= phi2 7.2e+45)))
(*
R
(*
2.0
(atan2
(sqrt (pow (sin (* (- phi2 phi1) -0.5)) 2.0))
(sqrt
(-
1.0
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(/
(*
(pow (sin (/ (- lambda1 lambda2) 2.0)) 2.0)
(+ (cos (+ phi2 phi1)) (cos (- phi2 phi1))))
2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (fma t_0 (* -0.5 phi2) (sin (* 0.5 phi1))) 2.0) t_1))
(sqrt (- (pow t_0 2.0) t_1))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((-0.5 * phi1));
double t_1 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0) * cos(phi1);
double tmp;
if ((phi2 <= -4400.0) || !(phi2 <= 7.2e+45)) {
tmp = R * (2.0 * atan2(sqrt(pow(sin(((phi2 - phi1) * -0.5)), 2.0)), sqrt((1.0 - (pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((pow(sin(((lambda1 - lambda2) / 2.0)), 2.0) * (cos((phi2 + phi1)) + cos((phi2 - phi1)))) / 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(fma(t_0, (-0.5 * phi2), sin((0.5 * phi1))), 2.0) + t_1)), sqrt((pow(t_0, 2.0) - t_1))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(-0.5 * phi1)) t_1 = Float64((sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0) * cos(phi1)) tmp = 0.0 if ((phi2 <= -4400.0) || !(phi2 <= 7.2e+45)) tmp = Float64(R * Float64(2.0 * atan(sqrt((sin(Float64(Float64(phi2 - phi1) * -0.5)) ^ 2.0)), sqrt(Float64(1.0 - Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64((sin(Float64(Float64(lambda1 - lambda2) / 2.0)) ^ 2.0) * Float64(cos(Float64(phi2 + phi1)) + cos(Float64(phi2 - phi1)))) / 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((fma(t_0, Float64(-0.5 * phi2), sin(Float64(0.5 * phi1))) ^ 2.0) + t_1)), sqrt(Float64((t_0 ^ 2.0) - t_1))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[phi2, -4400.0], N[Not[LessEqual[phi2, 7.2e+45]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[Power[N[Sin[N[(N[(phi2 - phi1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[(N[Cos[N[(phi2 + phi1), $MachinePrecision]], $MachinePrecision] + N[Cos[N[(phi2 - phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(t$95$0 * N[(-0.5 * phi2), $MachinePrecision] + N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[t$95$0, 2.0], $MachinePrecision] - t$95$1), $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 \left(\lambda_1 - \lambda_2\right)\right)}^{2} \cdot \cos \phi_1\\
\mathbf{if}\;\phi_2 \leq -4400 \lor \neg \left(\phi_2 \leq 7.2 \cdot 10^{+45}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\left(\phi_2 - \phi_1\right) \cdot -0.5\right)}^{2}}}{\sqrt{1 - \left({\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \frac{{\sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)}^{2} \cdot \left(\cos \left(\phi_2 + \phi_1\right) + \cos \left(\phi_2 - \phi_1\right)\right)}{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(t\_0, -0.5 \cdot \phi_2, \sin \left(0.5 \cdot \phi_1\right)\right)\right)}^{2} + t\_1}}{\sqrt{{t\_0}^{2} - t\_1}}\right)\\
\end{array}
\end{array}
if phi2 < -4400 or 7.2e45 < phi2 Initial program 50.7%
Taylor expanded in lambda2 around 0
Applied rewrites36.0%
Taylor expanded in lambda1 around 0
Applied rewrites31.4%
lift-*.f64N/A
lift-*.f64N/A
associate-*l*N/A
lift-*.f64N/A
unpow2N/A
lift-pow.f64N/A
*-commutativeN/A
lift-*.f64N/A
*-commutativeN/A
lift-*.f64N/A
*-commutativeN/A
lift-cos.f64N/A
lift-cos.f64N/A
cos-multN/A
Applied rewrites31.9%
if -4400 < phi2 < 7.2e45Initial program 74.9%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate-*r*N/A
*-commutativeN/A
lower-fma.f64N/A
cos-neg-revN/A
lower-cos.f64N/A
distribute-lft-neg-inN/A
metadata-evalN/A
lower-*.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
lower-*.f6473.2
Applied rewrites73.2%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sin-revN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
cos-neg-revN/A
lower-cos.f64N/A
distribute-lft-neg-inN/A
metadata-evalN/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites72.7%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-*.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
lower--.f64N/A
lower-cos.f6472.7
Applied rewrites72.7%
Final simplification53.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(if (or (<= phi2 -0.135) (not (<= phi2 7.8e+50)))
(*
R
(*
2.0
(atan2
(sqrt (pow (sin (* (- phi2 phi1) -0.5)) 2.0))
(sqrt
(-
1.0
(+
t_0
(/
(*
(pow (sin (/ (- lambda1 lambda2) 2.0)) 2.0)
(+ (cos (+ phi2 phi1)) (cos (- phi2 phi1))))
2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt
(+ t_0 (* (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0) (cos phi1))))
(sqrt
(-
(pow (cos (* -0.5 phi1)) 2.0)
(* (pow (sin (* (- lambda2 lambda1) -0.5)) 2.0) (cos phi1))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double tmp;
if ((phi2 <= -0.135) || !(phi2 <= 7.8e+50)) {
tmp = R * (2.0 * atan2(sqrt(pow(sin(((phi2 - phi1) * -0.5)), 2.0)), sqrt((1.0 - (t_0 + ((pow(sin(((lambda1 - lambda2) / 2.0)), 2.0) * (cos((phi2 + phi1)) + cos((phi2 - phi1)))) / 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt((t_0 + (pow(sin((0.5 * (lambda1 - lambda2))), 2.0) * cos(phi1)))), sqrt((pow(cos((-0.5 * phi1)), 2.0) - (pow(sin(((lambda2 - lambda1) * -0.5)), 2.0) * cos(phi1))))));
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: tmp
t_0 = sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0
if ((phi2 <= (-0.135d0)) .or. (.not. (phi2 <= 7.8d+50))) then
tmp = r * (2.0d0 * atan2(sqrt((sin(((phi2 - phi1) * (-0.5d0))) ** 2.0d0)), sqrt((1.0d0 - (t_0 + (((sin(((lambda1 - lambda2) / 2.0d0)) ** 2.0d0) * (cos((phi2 + phi1)) + cos((phi2 - phi1)))) / 2.0d0))))))
else
tmp = r * (2.0d0 * atan2(sqrt((t_0 + ((sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0) * cos(phi1)))), sqrt(((cos(((-0.5d0) * phi1)) ** 2.0d0) - ((sin(((lambda2 - lambda1) * (-0.5d0))) ** 2.0d0) * cos(phi1))))))
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 tmp;
if ((phi2 <= -0.135) || !(phi2 <= 7.8e+50)) {
tmp = R * (2.0 * Math.atan2(Math.sqrt(Math.pow(Math.sin(((phi2 - phi1) * -0.5)), 2.0)), Math.sqrt((1.0 - (t_0 + ((Math.pow(Math.sin(((lambda1 - lambda2) / 2.0)), 2.0) * (Math.cos((phi2 + phi1)) + Math.cos((phi2 - phi1)))) / 2.0))))));
} else {
tmp = R * (2.0 * Math.atan2(Math.sqrt((t_0 + (Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0) * Math.cos(phi1)))), Math.sqrt((Math.pow(Math.cos((-0.5 * phi1)), 2.0) - (Math.pow(Math.sin(((lambda2 - lambda1) * -0.5)), 2.0) * Math.cos(phi1))))));
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) tmp = 0 if (phi2 <= -0.135) or not (phi2 <= 7.8e+50): tmp = R * (2.0 * math.atan2(math.sqrt(math.pow(math.sin(((phi2 - phi1) * -0.5)), 2.0)), math.sqrt((1.0 - (t_0 + ((math.pow(math.sin(((lambda1 - lambda2) / 2.0)), 2.0) * (math.cos((phi2 + phi1)) + math.cos((phi2 - phi1)))) / 2.0)))))) else: tmp = R * (2.0 * math.atan2(math.sqrt((t_0 + (math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0) * math.cos(phi1)))), math.sqrt((math.pow(math.cos((-0.5 * phi1)), 2.0) - (math.pow(math.sin(((lambda2 - lambda1) * -0.5)), 2.0) * math.cos(phi1)))))) return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 tmp = 0.0 if ((phi2 <= -0.135) || !(phi2 <= 7.8e+50)) tmp = Float64(R * Float64(2.0 * atan(sqrt((sin(Float64(Float64(phi2 - phi1) * -0.5)) ^ 2.0)), sqrt(Float64(1.0 - Float64(t_0 + Float64(Float64((sin(Float64(Float64(lambda1 - lambda2) / 2.0)) ^ 2.0) * Float64(cos(Float64(phi2 + phi1)) + cos(Float64(phi2 - phi1)))) / 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_0 + Float64((sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0) * cos(phi1)))), sqrt(Float64((cos(Float64(-0.5 * phi1)) ^ 2.0) - Float64((sin(Float64(Float64(lambda2 - lambda1) * -0.5)) ^ 2.0) * cos(phi1))))))); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((phi1 - phi2) / 2.0)) ^ 2.0; tmp = 0.0; if ((phi2 <= -0.135) || ~((phi2 <= 7.8e+50))) tmp = R * (2.0 * atan2(sqrt((sin(((phi2 - phi1) * -0.5)) ^ 2.0)), sqrt((1.0 - (t_0 + (((sin(((lambda1 - lambda2) / 2.0)) ^ 2.0) * (cos((phi2 + phi1)) + cos((phi2 - phi1)))) / 2.0)))))); else tmp = R * (2.0 * atan2(sqrt((t_0 + ((sin((0.5 * (lambda1 - lambda2))) ^ 2.0) * cos(phi1)))), sqrt(((cos((-0.5 * phi1)) ^ 2.0) - ((sin(((lambda2 - lambda1) * -0.5)) ^ 2.0) * cos(phi1)))))); 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]}, If[Or[LessEqual[phi2, -0.135], N[Not[LessEqual[phi2, 7.8e+50]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[Power[N[Sin[N[(N[(phi2 - phi1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 + N[(N[(N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[(N[Cos[N[(phi2 + phi1), $MachinePrecision]], $MachinePrecision] + N[Cos[N[(phi2 - phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 + N[(N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Power[N[Sin[N[(N[(lambda2 - lambda1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $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}\\
\mathbf{if}\;\phi_2 \leq -0.135 \lor \neg \left(\phi_2 \leq 7.8 \cdot 10^{+50}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\left(\phi_2 - \phi_1\right) \cdot -0.5\right)}^{2}}}{\sqrt{1 - \left(t\_0 + \frac{{\sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)}^{2} \cdot \left(\cos \left(\phi_2 + \phi_1\right) + \cos \left(\phi_2 - \phi_1\right)\right)}{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 + {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2} \cdot \cos \phi_1}}{\sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - {\sin \left(\left(\lambda_2 - \lambda_1\right) \cdot -0.5\right)}^{2} \cdot \cos \phi_1}}\right)\\
\end{array}
\end{array}
if phi2 < -0.13500000000000001 or 7.79999999999999935e50 < phi2 Initial program 50.1%
Taylor expanded in lambda2 around 0
Applied rewrites36.0%
Taylor expanded in lambda1 around 0
Applied rewrites31.4%
lift-*.f64N/A
lift-*.f64N/A
associate-*l*N/A
lift-*.f64N/A
unpow2N/A
lift-pow.f64N/A
*-commutativeN/A
lift-*.f64N/A
*-commutativeN/A
lift-*.f64N/A
*-commutativeN/A
lift-cos.f64N/A
lift-cos.f64N/A
cos-multN/A
Applied rewrites31.9%
if -0.13500000000000001 < phi2 < 7.79999999999999935e50Initial program 75.5%
Taylor expanded in phi2 around 0
Applied rewrites72.6%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-*.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
lower--.f64N/A
lower-cos.f6472.6
Applied rewrites72.6%
Final simplification53.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(if (or (<= phi2 -1.55e-7) (not (<= phi2 3e+46)))
(*
R
(*
2.0
(atan2
(sqrt (pow (sin (* (- phi2 phi1) -0.5)) 2.0))
(sqrt
(-
1.0
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(/
(*
(pow (sin (/ (- lambda1 lambda2) 2.0)) 2.0)
(+ (cos (+ phi2 phi1)) (cos (- phi2 phi1))))
2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt
(fma
(pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)
(cos phi1)
(pow (sin (* 0.5 phi1)) 2.0)))
(sqrt
(-
(pow (cos (* -0.5 phi1)) 2.0)
(* (pow (sin (* (- lambda2 lambda1) -0.5)) 2.0) (cos phi1)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double tmp;
if ((phi2 <= -1.55e-7) || !(phi2 <= 3e+46)) {
tmp = R * (2.0 * atan2(sqrt(pow(sin(((phi2 - phi1) * -0.5)), 2.0)), sqrt((1.0 - (pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((pow(sin(((lambda1 - lambda2) / 2.0)), 2.0) * (cos((phi2 + phi1)) + cos((phi2 - phi1)))) / 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt(fma(pow(sin((0.5 * (lambda1 - lambda2))), 2.0), cos(phi1), pow(sin((0.5 * phi1)), 2.0))), sqrt((pow(cos((-0.5 * phi1)), 2.0) - (pow(sin(((lambda2 - lambda1) * -0.5)), 2.0) * cos(phi1))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) tmp = 0.0 if ((phi2 <= -1.55e-7) || !(phi2 <= 3e+46)) tmp = Float64(R * Float64(2.0 * atan(sqrt((sin(Float64(Float64(phi2 - phi1) * -0.5)) ^ 2.0)), sqrt(Float64(1.0 - Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64((sin(Float64(Float64(lambda1 - lambda2) / 2.0)) ^ 2.0) * Float64(cos(Float64(phi2 + phi1)) + cos(Float64(phi2 - phi1)))) / 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(fma((sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0), cos(phi1), (sin(Float64(0.5 * phi1)) ^ 2.0))), sqrt(Float64((cos(Float64(-0.5 * phi1)) ^ 2.0) - Float64((sin(Float64(Float64(lambda2 - lambda1) * -0.5)) ^ 2.0) * cos(phi1))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := If[Or[LessEqual[phi2, -1.55e-7], N[Not[LessEqual[phi2, 3e+46]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[Power[N[Sin[N[(N[(phi2 - phi1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[(N[Cos[N[(phi2 + phi1), $MachinePrecision]], $MachinePrecision] + N[Cos[N[(phi2 - phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Power[N[Sin[N[(N[(lambda2 - lambda1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
\mathbf{if}\;\phi_2 \leq -1.55 \cdot 10^{-7} \lor \neg \left(\phi_2 \leq 3 \cdot 10^{+46}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\left(\phi_2 - \phi_1\right) \cdot -0.5\right)}^{2}}}{\sqrt{1 - \left({\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \frac{{\sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)}^{2} \cdot \left(\cos \left(\phi_2 + \phi_1\right) + \cos \left(\phi_2 - \phi_1\right)\right)}{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left({\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}, \cos \phi_1, {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)}}{\sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - {\sin \left(\left(\lambda_2 - \lambda_1\right) \cdot -0.5\right)}^{2} \cdot \cos \phi_1}}\right)\\
\end{array}
\end{array}
if phi2 < -1.55e-7 or 3.00000000000000023e46 < phi2 Initial program 50.5%
Taylor expanded in lambda2 around 0
Applied rewrites36.3%
Taylor expanded in lambda1 around 0
Applied rewrites31.8%
lift-*.f64N/A
lift-*.f64N/A
associate-*l*N/A
lift-*.f64N/A
unpow2N/A
lift-pow.f64N/A
*-commutativeN/A
lift-*.f64N/A
*-commutativeN/A
lift-*.f64N/A
*-commutativeN/A
lift-cos.f64N/A
lift-cos.f64N/A
cos-multN/A
Applied rewrites32.3%
if -1.55e-7 < phi2 < 3.00000000000000023e46Initial program 76.1%
Taylor expanded in phi2 around 0
Applied rewrites73.7%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6446.2
Applied rewrites46.2%
Taylor expanded in phi2 around 0
lower-sqrt.f64N/A
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6472.1
Applied rewrites72.1%
Final simplification53.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(sqrt (pow (sin (* (- phi2 phi1) -0.5)) 2.0))
(sqrt
(-
1.0
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(/
(*
(pow (sin (/ (- lambda1 lambda2) 2.0)) 2.0)
(+ (cos (+ phi2 phi1)) (cos (- phi2 phi1))))
2.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2(sqrt(pow(sin(((phi2 - phi1) * -0.5)), 2.0)), sqrt((1.0 - (pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((pow(sin(((lambda1 - lambda2) / 2.0)), 2.0) * (cos((phi2 + phi1)) + cos((phi2 - 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
code = r * (2.0d0 * atan2(sqrt((sin(((phi2 - phi1) * (-0.5d0))) ** 2.0d0)), sqrt((1.0d0 - ((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (((sin(((lambda1 - lambda2) / 2.0d0)) ** 2.0d0) * (cos((phi2 + phi1)) + cos((phi2 - phi1)))) / 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.sqrt(Math.pow(Math.sin(((phi2 - phi1) * -0.5)), 2.0)), Math.sqrt((1.0 - (Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((Math.pow(Math.sin(((lambda1 - lambda2) / 2.0)), 2.0) * (Math.cos((phi2 + phi1)) + Math.cos((phi2 - phi1)))) / 2.0))))));
}
def code(R, lambda1, lambda2, phi1, phi2): return R * (2.0 * math.atan2(math.sqrt(math.pow(math.sin(((phi2 - phi1) * -0.5)), 2.0)), math.sqrt((1.0 - (math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + ((math.pow(math.sin(((lambda1 - lambda2) / 2.0)), 2.0) * (math.cos((phi2 + phi1)) + math.cos((phi2 - phi1)))) / 2.0))))))
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(sqrt((sin(Float64(Float64(phi2 - phi1) * -0.5)) ^ 2.0)), sqrt(Float64(1.0 - Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64((sin(Float64(Float64(lambda1 - lambda2) / 2.0)) ^ 2.0) * Float64(cos(Float64(phi2 + phi1)) + cos(Float64(phi2 - phi1)))) / 2.0))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) tmp = R * (2.0 * atan2(sqrt((sin(((phi2 - phi1) * -0.5)) ^ 2.0)), sqrt((1.0 - ((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (((sin(((lambda1 - lambda2) / 2.0)) ^ 2.0) * (cos((phi2 + phi1)) + cos((phi2 - phi1)))) / 2.0)))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[Power[N[Sin[N[(N[(phi2 - phi1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[(N[Cos[N[(phi2 + phi1), $MachinePrecision]], $MachinePrecision] + N[Cos[N[(phi2 - phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / 2.0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\left(\phi_2 - \phi_1\right) \cdot -0.5\right)}^{2}}}{\sqrt{1 - \left({\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \frac{{\sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)}^{2} \cdot \left(\cos \left(\phi_2 + \phi_1\right) + \cos \left(\phi_2 - \phi_1\right)\right)}{2}\right)}}\right)
\end{array}
Initial program 63.8%
Taylor expanded in lambda2 around 0
Applied rewrites40.9%
Taylor expanded in lambda1 around 0
Applied rewrites28.6%
lift-*.f64N/A
lift-*.f64N/A
associate-*l*N/A
lift-*.f64N/A
unpow2N/A
lift-pow.f64N/A
*-commutativeN/A
lift-*.f64N/A
*-commutativeN/A
lift-*.f64N/A
*-commutativeN/A
lift-cos.f64N/A
lift-cos.f64N/A
cos-multN/A
Applied rewrites28.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sqrt (pow (sin (* (- phi2 phi1) -0.5)) 2.0)))
(t_1 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
(if (<= (sin (/ (- lambda1 lambda2) 2.0)) 0.4)
(*
R
(*
2.0
(atan2
t_0
(sqrt
(-
1.0
(+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* t_1 (cos phi1))))))))
(*
R
(*
2.0
(atan2
t_0
(sqrt (- 1.0 (fma t_1 (cos phi2) (pow (sin (* -0.5 phi2)) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sqrt(pow(sin(((phi2 - phi1) * -0.5)), 2.0));
double t_1 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double tmp;
if (sin(((lambda1 - lambda2) / 2.0)) <= 0.4) {
tmp = R * (2.0 * atan2(t_0, sqrt((1.0 - (pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (t_1 * cos(phi1)))))));
} else {
tmp = R * (2.0 * atan2(t_0, sqrt((1.0 - fma(t_1, cos(phi2), pow(sin((-0.5 * phi2)), 2.0))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sqrt((sin(Float64(Float64(phi2 - phi1) * -0.5)) ^ 2.0)) t_1 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 tmp = 0.0 if (sin(Float64(Float64(lambda1 - lambda2) / 2.0)) <= 0.4) tmp = Float64(R * Float64(2.0 * atan(t_0, sqrt(Float64(1.0 - Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(t_1 * cos(phi1)))))))); else tmp = Float64(R * Float64(2.0 * atan(t_0, sqrt(Float64(1.0 - fma(t_1, cos(phi2), (sin(Float64(-0.5 * phi2)) ^ 2.0))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sqrt[N[Power[N[Sin[N[(N[(phi2 - phi1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[LessEqual[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 0.4], N[(R * N[(2.0 * N[ArcTan[t$95$0 / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$1 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$0 / N[Sqrt[N[(1.0 - N[(t$95$1 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sqrt{{\sin \left(\left(\phi_2 - \phi_1\right) \cdot -0.5\right)}^{2}}\\
t_1 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
\mathbf{if}\;\sin \left(\frac{\lambda_1 - \lambda_2}{2}\right) \leq 0.4:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_0}{\sqrt{1 - \left({\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_1 \cdot \cos \phi_1\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_0}{\sqrt{1 - \mathsf{fma}\left(t\_1, \cos \phi_2, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)}}\right)\\
\end{array}
\end{array}
if (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < 0.40000000000000002Initial program 68.1%
Taylor expanded in lambda2 around 0
Applied rewrites48.0%
Taylor expanded in lambda1 around 0
Applied rewrites34.5%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-*.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
lower--.f64N/A
lower-cos.f6433.4
Applied rewrites33.4%
if 0.40000000000000002 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) Initial program 54.9%
Taylor expanded in lambda2 around 0
Applied rewrites26.6%
Taylor expanded in lambda1 around 0
Applied rewrites16.4%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6416.7
Applied rewrites16.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(sqrt (pow (sin (* (- phi2 phi1) -0.5)) 2.0))
(sqrt
(-
1.0
(fma
(* (cos phi2) (cos phi1))
(pow (sin (* 0.5 lambda1)) 2.0)
(pow (sin (* 0.5 (- phi1 phi2))) 2.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2(sqrt(pow(sin(((phi2 - phi1) * -0.5)), 2.0)), sqrt((1.0 - fma((cos(phi2) * cos(phi1)), pow(sin((0.5 * lambda1)), 2.0), pow(sin((0.5 * (phi1 - phi2))), 2.0))))));
}
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(sqrt((sin(Float64(Float64(phi2 - phi1) * -0.5)) ^ 2.0)), sqrt(Float64(1.0 - fma(Float64(cos(phi2) * cos(phi1)), (sin(Float64(0.5 * lambda1)) ^ 2.0), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[Power[N[Sin[N[(N[(phi2 - phi1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] * N[Power[N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\left(\phi_2 - \phi_1\right) \cdot -0.5\right)}^{2}}}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_2 \cdot \cos \phi_1, {\sin \left(0.5 \cdot \lambda_1\right)}^{2}, {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}}\right)
\end{array}
Initial program 63.8%
Taylor expanded in lambda2 around 0
Applied rewrites40.9%
Taylor expanded in lambda1 around 0
Applied rewrites28.6%
Taylor expanded in lambda2 around 0
associate-*r*N/A
lower-fma.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
lower--.f6428.5
Applied rewrites28.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sqrt (pow (sin (* (- phi2 phi1) -0.5)) 2.0)))
(t_1 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
(if (or (<= phi1 -7.8e-6) (not (<= phi1 1.32e-30)))
(*
R
(*
2.0
(atan2
t_0
(sqrt (- 1.0 (fma t_1 (cos phi1) (pow (sin (* 0.5 phi1)) 2.0)))))))
(*
R
(*
2.0
(atan2
t_0
(sqrt (- 1.0 (fma t_1 (cos phi2) (pow (sin (* -0.5 phi2)) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sqrt(pow(sin(((phi2 - phi1) * -0.5)), 2.0));
double t_1 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double tmp;
if ((phi1 <= -7.8e-6) || !(phi1 <= 1.32e-30)) {
tmp = R * (2.0 * atan2(t_0, sqrt((1.0 - fma(t_1, cos(phi1), pow(sin((0.5 * phi1)), 2.0))))));
} else {
tmp = R * (2.0 * atan2(t_0, sqrt((1.0 - fma(t_1, cos(phi2), pow(sin((-0.5 * phi2)), 2.0))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sqrt((sin(Float64(Float64(phi2 - phi1) * -0.5)) ^ 2.0)) t_1 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 tmp = 0.0 if ((phi1 <= -7.8e-6) || !(phi1 <= 1.32e-30)) tmp = Float64(R * Float64(2.0 * atan(t_0, sqrt(Float64(1.0 - fma(t_1, cos(phi1), (sin(Float64(0.5 * phi1)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(t_0, sqrt(Float64(1.0 - fma(t_1, cos(phi2), (sin(Float64(-0.5 * phi2)) ^ 2.0))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sqrt[N[Power[N[Sin[N[(N[(phi2 - phi1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[phi1, -7.8e-6], N[Not[LessEqual[phi1, 1.32e-30]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[t$95$0 / N[Sqrt[N[(1.0 - N[(t$95$1 * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi1), $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[(t$95$1 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sqrt{{\sin \left(\left(\phi_2 - \phi_1\right) \cdot -0.5\right)}^{2}}\\
t_1 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
\mathbf{if}\;\phi_1 \leq -7.8 \cdot 10^{-6} \lor \neg \left(\phi_1 \leq 1.32 \cdot 10^{-30}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_0}{\sqrt{1 - \mathsf{fma}\left(t\_1, \cos \phi_1, {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_0}{\sqrt{1 - \mathsf{fma}\left(t\_1, \cos \phi_2, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)}}\right)\\
\end{array}
\end{array}
if phi1 < -7.7999999999999999e-6 or 1.32e-30 < phi1 Initial program 48.0%
Taylor expanded in lambda2 around 0
Applied rewrites34.9%
Taylor expanded in lambda1 around 0
Applied rewrites26.9%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6427.4
Applied rewrites27.4%
if -7.7999999999999999e-6 < phi1 < 1.32e-30Initial program 78.8%
Taylor expanded in lambda2 around 0
Applied rewrites46.7%
Taylor expanded in lambda1 around 0
Applied rewrites30.1%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6430.1
Applied rewrites30.1%
Final simplification28.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(sqrt (pow (sin (* (- phi2 phi1) -0.5)) 2.0))
(sqrt
(-
1.0
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0) (cos phi2)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2(sqrt(pow(sin(((phi2 - phi1) * -0.5)), 2.0)), sqrt((1.0 - (pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (pow(sin((0.5 * (lambda1 - lambda2))), 2.0) * cos(phi2)))))));
}
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(sqrt((sin(((phi2 - phi1) * (-0.5d0))) ** 2.0d0)), sqrt((1.0d0 - ((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + ((sin((0.5d0 * (lambda1 - lambda2))) ** 2.0d0) * cos(phi2)))))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * Math.atan2(Math.sqrt(Math.pow(Math.sin(((phi2 - phi1) * -0.5)), 2.0)), Math.sqrt((1.0 - (Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (Math.pow(Math.sin((0.5 * (lambda1 - lambda2))), 2.0) * Math.cos(phi2)))))));
}
def code(R, lambda1, lambda2, phi1, phi2): return R * (2.0 * math.atan2(math.sqrt(math.pow(math.sin(((phi2 - phi1) * -0.5)), 2.0)), math.sqrt((1.0 - (math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (math.pow(math.sin((0.5 * (lambda1 - lambda2))), 2.0) * math.cos(phi2)))))))
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(sqrt((sin(Float64(Float64(phi2 - phi1) * -0.5)) ^ 2.0)), sqrt(Float64(1.0 - Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64((sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0) * cos(phi2)))))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) tmp = R * (2.0 * atan2(sqrt((sin(((phi2 - phi1) * -0.5)) ^ 2.0)), sqrt((1.0 - ((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + ((sin((0.5 * (lambda1 - lambda2))) ^ 2.0) * cos(phi2))))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[Power[N[Sin[N[(N[(phi2 - phi1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\left(\phi_2 - \phi_1\right) \cdot -0.5\right)}^{2}}}{\sqrt{1 - \left({\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2} \cdot \cos \phi_2\right)}}\right)
\end{array}
Initial program 63.8%
Taylor expanded in lambda2 around 0
Applied rewrites40.9%
Taylor expanded in lambda1 around 0
Applied rewrites28.6%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-*.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
lower--.f64N/A
lower-cos.f6426.5
Applied rewrites26.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(sqrt (pow (sin (* (- phi2 phi1) -0.5)) 2.0))
(sqrt
(-
1.0
(fma
(pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)
(cos phi1)
(pow (sin (* 0.5 phi1)) 2.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2(sqrt(pow(sin(((phi2 - phi1) * -0.5)), 2.0)), sqrt((1.0 - fma(pow(sin((0.5 * (lambda1 - lambda2))), 2.0), cos(phi1), pow(sin((0.5 * phi1)), 2.0))))));
}
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(sqrt((sin(Float64(Float64(phi2 - phi1) * -0.5)) ^ 2.0)), sqrt(Float64(1.0 - fma((sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0), cos(phi1), (sin(Float64(0.5 * phi1)) ^ 2.0))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[Power[N[Sin[N[(N[(phi2 - phi1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\left(\phi_2 - \phi_1\right) \cdot -0.5\right)}^{2}}}{\sqrt{1 - \mathsf{fma}\left({\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}, \cos \phi_1, {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)}}\right)
\end{array}
Initial program 63.8%
Taylor expanded in lambda2 around 0
Applied rewrites40.9%
Taylor expanded in lambda1 around 0
Applied rewrites28.6%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6423.3
Applied rewrites23.3%
herbie shell --seed 2024332
(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))))))))))