
(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 24 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_0) t_0))))
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0);
return R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0)
code = r * (2.0d0 * atan2(sqrt(t_1), sqrt((1.0d0 - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((Math.cos(phi1) * Math.cos(phi2)) * t_0) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt(t_1), Math.sqrt((1.0 - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((math.cos(phi1) * math.cos(phi2)) * t_0) * t_0) return R * (2.0 * math.atan2(math.sqrt(t_1), math.sqrt((1.0 - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0); tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$1], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) \cdot t\_0\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)
\end{array}
\end{array}
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (* phi1 0.5)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (sin (* phi1 0.5))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (fma t_2 (cos (* -0.5 phi2)) (* (sin (* -0.5 phi2)) t_0)) 2.0)
(* t_1 (* (* (cos phi1) (cos phi2)) t_1))))
(sqrt
(+
1.0
(-
(*
(cos phi2)
(*
(cos phi1)
(-
(*
0.5
(fma (cos lambda1) (cos lambda2) (* (sin lambda1) (sin lambda2))))
0.5)))
(pow
(- (* (cos (* 0.5 phi2)) t_2) (* (sin (* 0.5 phi2)) t_0))
2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((phi1 * 0.5));
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = sin((phi1 * 0.5));
return R * (2.0 * atan2(sqrt((pow(fma(t_2, cos((-0.5 * phi2)), (sin((-0.5 * phi2)) * t_0)), 2.0) + (t_1 * ((cos(phi1) * cos(phi2)) * t_1)))), sqrt((1.0 + ((cos(phi2) * (cos(phi1) * ((0.5 * fma(cos(lambda1), cos(lambda2), (sin(lambda1) * sin(lambda2)))) - 0.5))) - pow(((cos((0.5 * phi2)) * t_2) - (sin((0.5 * phi2)) * t_0)), 2.0))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(phi1 * 0.5)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = sin(Float64(phi1 * 0.5)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((fma(t_2, cos(Float64(-0.5 * phi2)), Float64(sin(Float64(-0.5 * phi2)) * t_0)) ^ 2.0) + Float64(t_1 * Float64(Float64(cos(phi1) * cos(phi2)) * t_1)))), sqrt(Float64(1.0 + Float64(Float64(cos(phi2) * Float64(cos(phi1) * Float64(Float64(0.5 * fma(cos(lambda1), cos(lambda2), Float64(sin(lambda1) * sin(lambda2)))) - 0.5))) - (Float64(Float64(cos(Float64(0.5 * phi2)) * t_2) - Float64(sin(Float64(0.5 * phi2)) * t_0)) ^ 2.0))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(t$95$2 * N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$1 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 + N[(N[(N[Cos[phi2], $MachinePrecision] * N[(N[Cos[phi1], $MachinePrecision] * N[(N[(0.5 * N[(N[Cos[lambda1], $MachinePrecision] * N[Cos[lambda2], $MachinePrecision] + N[(N[Sin[lambda1], $MachinePrecision] * N[Sin[lambda2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[Power[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$2), $MachinePrecision] - N[(N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \sin \left(\phi_1 \cdot 0.5\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(t\_2, \cos \left(-0.5 \cdot \phi_2\right), \sin \left(-0.5 \cdot \phi_2\right) \cdot t\_0\right)\right)}^{2} + t\_1 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_1\right)}}{\sqrt{1 + \left(\cos \phi_2 \cdot \left(\cos \phi_1 \cdot \left(0.5 \cdot \mathsf{fma}\left(\cos \lambda_1, \cos \lambda_2, \sin \lambda_1 \cdot \sin \lambda_2\right) - 0.5\right)\right) - {\left(\cos \left(0.5 \cdot \phi_2\right) \cdot t\_2 - \sin \left(0.5 \cdot \phi_2\right) \cdot t\_0\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 61.4%
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-*.f6462.5
Applied egg-rr62.5%
div-subN/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
sin-sumN/A
lift-sin.f64N/A
lower-fma.f64N/A
lower-cos.f64N/A
metadata-evalN/A
lower-*.f64N/A
lift-cos.f64N/A
lower-*.f64N/A
Applied egg-rr76.6%
lift-cos.f64N/A
lift-cos.f64N/A
lift-*.f64N/A
lift--.f64N/A
lift-/.f64N/A
lift-sin.f64N/A
lift--.f64N/A
lift-/.f64N/A
lift-sin.f64N/A
associate-*l*N/A
lift-*.f64N/A
*-commutativeN/A
associate-*l*N/A
lower-*.f64N/A
lower-*.f64N/A
Applied egg-rr76.7%
lift--.f64N/A
*-rgt-identityN/A
lift--.f64N/A
cos-diffN/A
lower-fma.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
lower-sin.f6477.3
Applied egg-rr77.3%
Final simplification77.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (+ (* t_1 (* t_0 t_1)) (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(t_3 (sqrt t_2))
(t_4
(* t_0 (- (* 0.5 (cos (* 2.0 (* 0.5 (- lambda1 lambda2))))) 0.5))))
(if (<= (atan2 t_3 (sqrt (- 1.0 t_2))) 0.045)
(* R (* 2.0 (atan2 t_3 (sqrt (+ (+ 0.5 (* 0.5 (cos phi2))) t_4)))))
(*
R
(*
2.0
(atan2
(pow
(pow
(fma
t_0
(fma (cos (- lambda1 lambda2)) -0.5 0.5)
(- 0.5 (* 0.5 (cos (- phi1 phi2)))))
2.0)
0.25)
(sqrt
(+ (+ 0.5 (* 0.5 (cos (* 2.0 (* 0.5 (- phi1 phi2)))))) t_4))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = (t_1 * (t_0 * t_1)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double t_3 = sqrt(t_2);
double t_4 = t_0 * ((0.5 * cos((2.0 * (0.5 * (lambda1 - lambda2))))) - 0.5);
double tmp;
if (atan2(t_3, sqrt((1.0 - t_2))) <= 0.045) {
tmp = R * (2.0 * atan2(t_3, sqrt(((0.5 + (0.5 * cos(phi2))) + t_4))));
} else {
tmp = R * (2.0 * atan2(pow(pow(fma(t_0, fma(cos((lambda1 - lambda2)), -0.5, 0.5), (0.5 - (0.5 * cos((phi1 - phi2))))), 2.0), 0.25), sqrt(((0.5 + (0.5 * cos((2.0 * (0.5 * (phi1 - phi2)))))) + t_4))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(Float64(t_1 * Float64(t_0 * t_1)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0)) t_3 = sqrt(t_2) t_4 = Float64(t_0 * Float64(Float64(0.5 * cos(Float64(2.0 * Float64(0.5 * Float64(lambda1 - lambda2))))) - 0.5)) tmp = 0.0 if (atan(t_3, sqrt(Float64(1.0 - t_2))) <= 0.045) tmp = Float64(R * Float64(2.0 * atan(t_3, sqrt(Float64(Float64(0.5 + Float64(0.5 * cos(phi2))) + t_4))))); else tmp = Float64(R * Float64(2.0 * atan(((fma(t_0, fma(cos(Float64(lambda1 - lambda2)), -0.5, 0.5), Float64(0.5 - Float64(0.5 * cos(Float64(phi1 - phi2))))) ^ 2.0) ^ 0.25), sqrt(Float64(Float64(0.5 + Float64(0.5 * cos(Float64(2.0 * Float64(0.5 * Float64(phi1 - phi2)))))) + t_4))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[(t$95$1 * N[(t$95$0 * t$95$1), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[Sqrt[t$95$2], $MachinePrecision]}, Block[{t$95$4 = N[(t$95$0 * N[(N[(0.5 * N[Cos[N[(2.0 * N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[N[ArcTan[t$95$3 / N[Sqrt[N[(1.0 - t$95$2), $MachinePrecision]], $MachinePrecision]], $MachinePrecision], 0.045], N[(R * N[(2.0 * N[ArcTan[t$95$3 / N[Sqrt[N[(N[(0.5 + N[(0.5 * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$4), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Power[N[Power[N[(t$95$0 * N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] * -0.5 + 0.5), $MachinePrecision] + N[(0.5 - N[(0.5 * N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision], 0.25], $MachinePrecision] / 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$4), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := t\_1 \cdot \left(t\_0 \cdot t\_1\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
t_3 := \sqrt{t\_2}\\
t_4 := t\_0 \cdot \left(0.5 \cdot \cos \left(2 \cdot \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\right) - 0.5\right)\\
\mathbf{if}\;\tan^{-1}_* \frac{t\_3}{\sqrt{1 - t\_2}} \leq 0.045:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_3}{\sqrt{\left(0.5 + 0.5 \cdot \cos \phi_2\right) + t\_4}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{{\left({\left(\mathsf{fma}\left(t\_0, \mathsf{fma}\left(\cos \left(\lambda_1 - \lambda_2\right), -0.5, 0.5\right), 0.5 - 0.5 \cdot \cos \left(\phi_1 - \phi_2\right)\right)\right)}^{2}\right)}^{0.25}}{\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\_4}}\right)\\
\end{array}
\end{array}
if (atan2.f64 (sqrt.f64 (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))))) (sqrt.f64 (-.f64 #s(literal 1 binary64) (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))))))) < 0.044999999999999998Initial program 85.5%
Applied egg-rr85.5%
Taylor expanded in phi1 around 0
cos-negN/A
lower-cos.f6485.5
Simplified85.5%
if 0.044999999999999998 < (atan2.f64 (sqrt.f64 (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))))) (sqrt.f64 (-.f64 #s(literal 1 binary64) (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))))))) Initial program 58.9%
Applied egg-rr59.0%
Applied egg-rr59.2%
Final simplification61.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (+ 0.5 (* 0.5 (cos (* 2.0 (* 0.5 (- phi1 phi2)))))))
(t_2 (sin (/ (- lambda1 lambda2) 2.0)))
(t_3 (+ (* t_2 (* t_0 t_2)) (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(t_4 (sqrt t_3)))
(if (<= (atan2 t_4 (sqrt (- 1.0 t_3))) 0.085)
(*
R
(* 2.0 (atan2 t_4 (sqrt (- t_1 (* t_0 (fma -0.5 (cos lambda1) 0.5)))))))
(*
R
(*
2.0
(atan2
(pow
(pow
(fma
t_0
(fma (cos (- lambda1 lambda2)) -0.5 0.5)
(- 0.5 (* 0.5 (cos (- phi1 phi2)))))
2.0)
0.25)
(sqrt
(+
t_1
(*
t_0
(- (* 0.5 (cos (* 2.0 (* 0.5 (- lambda1 lambda2))))) 0.5))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = 0.5 + (0.5 * cos((2.0 * (0.5 * (phi1 - phi2)))));
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double t_3 = (t_2 * (t_0 * t_2)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double t_4 = sqrt(t_3);
double tmp;
if (atan2(t_4, sqrt((1.0 - t_3))) <= 0.085) {
tmp = R * (2.0 * atan2(t_4, sqrt((t_1 - (t_0 * fma(-0.5, cos(lambda1), 0.5))))));
} else {
tmp = R * (2.0 * atan2(pow(pow(fma(t_0, fma(cos((lambda1 - lambda2)), -0.5, 0.5), (0.5 - (0.5 * cos((phi1 - phi2))))), 2.0), 0.25), sqrt((t_1 + (t_0 * ((0.5 * cos((2.0 * (0.5 * (lambda1 - lambda2))))) - 0.5))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = Float64(0.5 + Float64(0.5 * cos(Float64(2.0 * Float64(0.5 * Float64(phi1 - phi2)))))) t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_3 = Float64(Float64(t_2 * Float64(t_0 * t_2)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0)) t_4 = sqrt(t_3) tmp = 0.0 if (atan(t_4, sqrt(Float64(1.0 - t_3))) <= 0.085) tmp = Float64(R * Float64(2.0 * atan(t_4, sqrt(Float64(t_1 - Float64(t_0 * fma(-0.5, cos(lambda1), 0.5))))))); else tmp = Float64(R * Float64(2.0 * atan(((fma(t_0, fma(cos(Float64(lambda1 - lambda2)), -0.5, 0.5), Float64(0.5 - Float64(0.5 * cos(Float64(phi1 - phi2))))) ^ 2.0) ^ 0.25), sqrt(Float64(t_1 + Float64(t_0 * Float64(Float64(0.5 * cos(Float64(2.0 * Float64(0.5 * Float64(lambda1 - lambda2))))) - 0.5))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[(0.5 + N[(0.5 * N[Cos[N[(2.0 * N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[(N[(t$95$2 * N[(t$95$0 * t$95$2), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[Sqrt[t$95$3], $MachinePrecision]}, If[LessEqual[N[ArcTan[t$95$4 / N[Sqrt[N[(1.0 - t$95$3), $MachinePrecision]], $MachinePrecision]], $MachinePrecision], 0.085], N[(R * N[(2.0 * N[ArcTan[t$95$4 / N[Sqrt[N[(t$95$1 - N[(t$95$0 * N[(-0.5 * N[Cos[lambda1], $MachinePrecision] + 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Power[N[Power[N[(t$95$0 * N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] * -0.5 + 0.5), $MachinePrecision] + N[(0.5 - N[(0.5 * N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision], 0.25], $MachinePrecision] / N[Sqrt[N[(t$95$1 + N[(t$95$0 * N[(N[(0.5 * N[Cos[N[(2.0 * N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := 0.5 + 0.5 \cdot \cos \left(2 \cdot \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\right)\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_3 := t\_2 \cdot \left(t\_0 \cdot t\_2\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
t_4 := \sqrt{t\_3}\\
\mathbf{if}\;\tan^{-1}_* \frac{t\_4}{\sqrt{1 - t\_3}} \leq 0.085:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_4}{\sqrt{t\_1 - t\_0 \cdot \mathsf{fma}\left(-0.5, \cos \lambda_1, 0.5\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{{\left({\left(\mathsf{fma}\left(t\_0, \mathsf{fma}\left(\cos \left(\lambda_1 - \lambda_2\right), -0.5, 0.5\right), 0.5 - 0.5 \cdot \cos \left(\phi_1 - \phi_2\right)\right)\right)}^{2}\right)}^{0.25}}{\sqrt{t\_1 + t\_0 \cdot \left(0.5 \cdot \cos \left(2 \cdot \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\right) - 0.5\right)}}\right)\\
\end{array}
\end{array}
if (atan2.f64 (sqrt.f64 (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))))) (sqrt.f64 (-.f64 #s(literal 1 binary64) (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))))))) < 0.0850000000000000061Initial program 80.8%
Applied egg-rr80.8%
Taylor expanded in lambda2 around 0
cancel-sign-sub-invN/A
metadata-evalN/A
+-commutativeN/A
lower-fma.f64N/A
lower-cos.f6480.4
Simplified80.4%
if 0.0850000000000000061 < (atan2.f64 (sqrt.f64 (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))))) (sqrt.f64 (-.f64 #s(literal 1 binary64) (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))))))) Initial program 59.1%
Applied egg-rr59.2%
Applied egg-rr59.4%
Final simplification61.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (* phi1 0.5)))
(t_1 (* (cos phi1) (cos phi2)))
(t_2 (cos (- lambda1 lambda2)))
(t_3 (sin (* phi1 0.5)))
(t_4 (cos (- phi1 phi2)))
(t_5 (sin (/ (- lambda1 lambda2) 2.0)))
(t_6 (* t_5 (* t_1 t_5)))
(t_7
(pow (- (* (cos (* 0.5 phi2)) t_3) (* (sin (* 0.5 phi2)) t_0)) 2.0))
(t_8
(sqrt
(+
(pow (fma t_3 (cos (* -0.5 phi2)) (* (sin (* -0.5 phi2)) t_0)) 2.0)
t_6))))
(if (<= t_5 -0.32)
(*
R
(*
2.0
(atan2
(sqrt (fma t_1 (fma t_2 -0.5 0.5) (- 0.5 (* 0.5 t_4))))
(sqrt (- 1.0 (+ t_6 t_7))))))
(if (<= t_5 0.01)
(*
R
(*
2.0
(atan2
t_8
(sqrt
(-
1.0
(+
t_7
(* (cos phi1) (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0))))))))
(*
R
(*
2.0
(atan2
t_8
(sqrt
(/
(+ (+ 1.0 t_4) (* (+ (cos (+ phi1 phi2)) t_4) (- (* 0.5 t_2) 0.5)))
2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((phi1 * 0.5));
double t_1 = cos(phi1) * cos(phi2);
double t_2 = cos((lambda1 - lambda2));
double t_3 = sin((phi1 * 0.5));
double t_4 = cos((phi1 - phi2));
double t_5 = sin(((lambda1 - lambda2) / 2.0));
double t_6 = t_5 * (t_1 * t_5);
double t_7 = pow(((cos((0.5 * phi2)) * t_3) - (sin((0.5 * phi2)) * t_0)), 2.0);
double t_8 = sqrt((pow(fma(t_3, cos((-0.5 * phi2)), (sin((-0.5 * phi2)) * t_0)), 2.0) + t_6));
double tmp;
if (t_5 <= -0.32) {
tmp = R * (2.0 * atan2(sqrt(fma(t_1, fma(t_2, -0.5, 0.5), (0.5 - (0.5 * t_4)))), sqrt((1.0 - (t_6 + t_7)))));
} else if (t_5 <= 0.01) {
tmp = R * (2.0 * atan2(t_8, sqrt((1.0 - (t_7 + (cos(phi1) * pow(sin((-0.5 * (lambda2 - lambda1))), 2.0)))))));
} else {
tmp = R * (2.0 * atan2(t_8, sqrt((((1.0 + t_4) + ((cos((phi1 + phi2)) + t_4) * ((0.5 * t_2) - 0.5))) / 2.0))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(phi1 * 0.5)) t_1 = Float64(cos(phi1) * cos(phi2)) t_2 = cos(Float64(lambda1 - lambda2)) t_3 = sin(Float64(phi1 * 0.5)) t_4 = cos(Float64(phi1 - phi2)) t_5 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_6 = Float64(t_5 * Float64(t_1 * t_5)) t_7 = Float64(Float64(cos(Float64(0.5 * phi2)) * t_3) - Float64(sin(Float64(0.5 * phi2)) * t_0)) ^ 2.0 t_8 = sqrt(Float64((fma(t_3, cos(Float64(-0.5 * phi2)), Float64(sin(Float64(-0.5 * phi2)) * t_0)) ^ 2.0) + t_6)) tmp = 0.0 if (t_5 <= -0.32) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_1, fma(t_2, -0.5, 0.5), Float64(0.5 - Float64(0.5 * t_4)))), sqrt(Float64(1.0 - Float64(t_6 + t_7)))))); elseif (t_5 <= 0.01) tmp = Float64(R * Float64(2.0 * atan(t_8, sqrt(Float64(1.0 - Float64(t_7 + Float64(cos(phi1) * (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0)))))))); else tmp = Float64(R * Float64(2.0 * atan(t_8, sqrt(Float64(Float64(Float64(1.0 + t_4) + Float64(Float64(cos(Float64(phi1 + phi2)) + t_4) * Float64(Float64(0.5 * t_2) - 0.5))) / 2.0))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$5 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$6 = N[(t$95$5 * N[(t$95$1 * t$95$5), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$7 = N[Power[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$3), $MachinePrecision] - N[(N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$8 = N[Sqrt[N[(N[Power[N[(t$95$3 * N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$6), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[t$95$5, -0.32], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 * N[(t$95$2 * -0.5 + 0.5), $MachinePrecision] + N[(0.5 - N[(0.5 * t$95$4), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$6 + t$95$7), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$5, 0.01], N[(R * N[(2.0 * N[ArcTan[t$95$8 / N[Sqrt[N[(1.0 - N[(t$95$7 + N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$8 / N[Sqrt[N[(N[(N[(1.0 + t$95$4), $MachinePrecision] + N[(N[(N[Cos[N[(phi1 + phi2), $MachinePrecision]], $MachinePrecision] + t$95$4), $MachinePrecision] * N[(N[(0.5 * t$95$2), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
t_2 := \cos \left(\lambda_1 - \lambda_2\right)\\
t_3 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_4 := \cos \left(\phi_1 - \phi_2\right)\\
t_5 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_6 := t\_5 \cdot \left(t\_1 \cdot t\_5\right)\\
t_7 := {\left(\cos \left(0.5 \cdot \phi_2\right) \cdot t\_3 - \sin \left(0.5 \cdot \phi_2\right) \cdot t\_0\right)}^{2}\\
t_8 := \sqrt{{\left(\mathsf{fma}\left(t\_3, \cos \left(-0.5 \cdot \phi_2\right), \sin \left(-0.5 \cdot \phi_2\right) \cdot t\_0\right)\right)}^{2} + t\_6}\\
\mathbf{if}\;t\_5 \leq -0.32:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_1, \mathsf{fma}\left(t\_2, -0.5, 0.5\right), 0.5 - 0.5 \cdot t\_4\right)}}{\sqrt{1 - \left(t\_6 + t\_7\right)}}\right)\\
\mathbf{elif}\;t\_5 \leq 0.01:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_8}{\sqrt{1 - \left(t\_7 + \cos \phi_1 \cdot {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_8}{\sqrt{\frac{\left(1 + t\_4\right) + \left(\cos \left(\phi_1 + \phi_2\right) + t\_4\right) \cdot \left(0.5 \cdot t\_2 - 0.5\right)}{2}}}\right)\\
\end{array}
\end{array}
if (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < -0.320000000000000007Initial program 51.5%
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-*.f6452.9
Applied egg-rr52.9%
Applied egg-rr52.9%
if -0.320000000000000007 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < 0.0100000000000000002Initial program 71.4%
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-*.f6472.0
Applied egg-rr72.0%
div-subN/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
sin-sumN/A
lift-sin.f64N/A
lower-fma.f64N/A
lower-cos.f64N/A
metadata-evalN/A
lower-*.f64N/A
lift-cos.f64N/A
lower-*.f64N/A
Applied egg-rr87.3%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-*.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
sub-negN/A
distribute-lft-inN/A
+-commutativeN/A
distribute-rgt-neg-outN/A
distribute-lft-neg-inN/A
metadata-evalN/A
metadata-evalN/A
distribute-lft-neg-inN/A
distribute-rgt-neg-outN/A
mul-1-negN/A
distribute-lft-inN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f6484.5
Simplified84.5%
if 0.0100000000000000002 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) Initial program 59.6%
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-*.f6460.8
Applied egg-rr60.8%
div-subN/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
sin-sumN/A
lift-sin.f64N/A
lower-fma.f64N/A
lower-cos.f64N/A
metadata-evalN/A
lower-*.f64N/A
lift-cos.f64N/A
lower-*.f64N/A
Applied egg-rr71.8%
Applied egg-rr61.7%
Final simplification67.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (* phi1 0.5)))
(t_1 (* (cos phi1) (cos phi2)))
(t_2 (sin (/ (- lambda1 lambda2) 2.0)))
(t_3 (* t_2 (* t_1 t_2)))
(t_4 (cos (- lambda1 lambda2)))
(t_5 (sin (* phi1 0.5)))
(t_6
(sqrt
(-
1.0
(+
t_3
(pow
(- (* (cos (* 0.5 phi2)) t_5) (* (sin (* 0.5 phi2)) t_0))
2.0)))))
(t_7
(pow (fma t_5 (cos (* -0.5 phi2)) (* (sin (* -0.5 phi2)) t_0)) 2.0))
(t_8 (cos (- phi1 phi2))))
(if (<= t_2 -0.055)
(*
R
(*
2.0
(atan2 (sqrt (fma t_1 (fma t_4 -0.5 0.5) (- 0.5 (* 0.5 t_8)))) t_6)))
(if (<= t_2 0.002)
(*
R
(*
2.0
(atan2
(sqrt
(+ t_7 (* (cos phi2) (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0))))
t_6)))
(*
R
(*
2.0
(atan2
(sqrt (+ t_7 t_3))
(sqrt
(/
(+ (+ 1.0 t_8) (* (+ (cos (+ phi1 phi2)) t_8) (- (* 0.5 t_4) 0.5)))
2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((phi1 * 0.5));
double t_1 = cos(phi1) * cos(phi2);
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double t_3 = t_2 * (t_1 * t_2);
double t_4 = cos((lambda1 - lambda2));
double t_5 = sin((phi1 * 0.5));
double t_6 = sqrt((1.0 - (t_3 + pow(((cos((0.5 * phi2)) * t_5) - (sin((0.5 * phi2)) * t_0)), 2.0))));
double t_7 = pow(fma(t_5, cos((-0.5 * phi2)), (sin((-0.5 * phi2)) * t_0)), 2.0);
double t_8 = cos((phi1 - phi2));
double tmp;
if (t_2 <= -0.055) {
tmp = R * (2.0 * atan2(sqrt(fma(t_1, fma(t_4, -0.5, 0.5), (0.5 - (0.5 * t_8)))), t_6));
} else if (t_2 <= 0.002) {
tmp = R * (2.0 * atan2(sqrt((t_7 + (cos(phi2) * pow(sin((-0.5 * (lambda2 - lambda1))), 2.0)))), t_6));
} else {
tmp = R * (2.0 * atan2(sqrt((t_7 + t_3)), sqrt((((1.0 + t_8) + ((cos((phi1 + phi2)) + t_8) * ((0.5 * t_4) - 0.5))) / 2.0))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(phi1 * 0.5)) t_1 = Float64(cos(phi1) * cos(phi2)) t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_3 = Float64(t_2 * Float64(t_1 * t_2)) t_4 = cos(Float64(lambda1 - lambda2)) t_5 = sin(Float64(phi1 * 0.5)) t_6 = sqrt(Float64(1.0 - Float64(t_3 + (Float64(Float64(cos(Float64(0.5 * phi2)) * t_5) - Float64(sin(Float64(0.5 * phi2)) * t_0)) ^ 2.0)))) t_7 = fma(t_5, cos(Float64(-0.5 * phi2)), Float64(sin(Float64(-0.5 * phi2)) * t_0)) ^ 2.0 t_8 = cos(Float64(phi1 - phi2)) tmp = 0.0 if (t_2 <= -0.055) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_1, fma(t_4, -0.5, 0.5), Float64(0.5 - Float64(0.5 * t_8)))), t_6))); elseif (t_2 <= 0.002) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_7 + Float64(cos(phi2) * (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0)))), t_6))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_7 + t_3)), sqrt(Float64(Float64(Float64(1.0 + t_8) + Float64(Float64(cos(Float64(phi1 + phi2)) + t_8) * Float64(Float64(0.5 * t_4) - 0.5))) / 2.0))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[(t$95$2 * N[(t$95$1 * t$95$2), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$5 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$6 = N[Sqrt[N[(1.0 - N[(t$95$3 + N[Power[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$5), $MachinePrecision] - N[(N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$7 = N[Power[N[(t$95$5 * N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$8 = N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[t$95$2, -0.055], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 * N[(t$95$4 * -0.5 + 0.5), $MachinePrecision] + N[(0.5 - N[(0.5 * t$95$8), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$6], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[t$95$2, 0.002], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$7 + N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$6], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$7 + t$95$3), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(N[(1.0 + t$95$8), $MachinePrecision] + N[(N[(N[Cos[N[(phi1 + phi2), $MachinePrecision]], $MachinePrecision] + t$95$8), $MachinePrecision] * N[(N[(0.5 * t$95$4), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_3 := t\_2 \cdot \left(t\_1 \cdot t\_2\right)\\
t_4 := \cos \left(\lambda_1 - \lambda_2\right)\\
t_5 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_6 := \sqrt{1 - \left(t\_3 + {\left(\cos \left(0.5 \cdot \phi_2\right) \cdot t\_5 - \sin \left(0.5 \cdot \phi_2\right) \cdot t\_0\right)}^{2}\right)}\\
t_7 := {\left(\mathsf{fma}\left(t\_5, \cos \left(-0.5 \cdot \phi_2\right), \sin \left(-0.5 \cdot \phi_2\right) \cdot t\_0\right)\right)}^{2}\\
t_8 := \cos \left(\phi_1 - \phi_2\right)\\
\mathbf{if}\;t\_2 \leq -0.055:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_1, \mathsf{fma}\left(t\_4, -0.5, 0.5\right), 0.5 - 0.5 \cdot t\_8\right)}}{t\_6}\right)\\
\mathbf{elif}\;t\_2 \leq 0.002:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_7 + \cos \phi_2 \cdot {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}}}{t\_6}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_7 + t\_3}}{\sqrt{\frac{\left(1 + t\_8\right) + \left(\cos \left(\phi_1 + \phi_2\right) + t\_8\right) \cdot \left(0.5 \cdot t\_4 - 0.5\right)}{2}}}\right)\\
\end{array}
\end{array}
if (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < -0.0550000000000000003Initial program 50.3%
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-*.f6451.5
Applied egg-rr51.5%
Applied egg-rr51.5%
if -0.0550000000000000003 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < 2e-3Initial program 78.2%
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-*.f6478.9
Applied egg-rr78.9%
div-subN/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
sin-sumN/A
lift-sin.f64N/A
lower-fma.f64N/A
lower-cos.f64N/A
metadata-evalN/A
lower-*.f64N/A
lift-cos.f64N/A
lower-*.f64N/A
Applied egg-rr95.9%
Taylor expanded in phi1 around 0
lower-*.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
sub-negN/A
distribute-lft-inN/A
+-commutativeN/A
distribute-rgt-neg-outN/A
distribute-lft-neg-inN/A
metadata-evalN/A
metadata-evalN/A
distribute-lft-neg-inN/A
distribute-rgt-neg-outN/A
mul-1-negN/A
distribute-lft-inN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f6494.0
Simplified94.0%
if 2e-3 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) Initial program 59.1%
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-*.f6460.3
Applied egg-rr60.3%
div-subN/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
sin-sumN/A
lift-sin.f64N/A
lower-fma.f64N/A
lower-cos.f64N/A
metadata-evalN/A
lower-*.f64N/A
lift-cos.f64N/A
lower-*.f64N/A
Applied egg-rr71.2%
Applied egg-rr61.2%
Final simplification67.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (* phi1 0.5)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (cos (* 0.5 (- lambda1 lambda2))))
(t_3 (sin (* phi1 0.5))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (fma t_3 (cos (* -0.5 phi2)) (* (sin (* -0.5 phi2)) t_0)) 2.0)
(* t_1 (* (* (cos phi1) (cos phi2)) t_1))))
(sqrt
(+
1.0
(-
(*
(cos phi2)
(*
(cos phi1)
(-
(* 0.5 (fma t_2 t_2 (- (fma (cos (- lambda1 lambda2)) -0.5 0.5))))
0.5)))
(pow
(- (* (cos (* 0.5 phi2)) t_3) (* (sin (* 0.5 phi2)) t_0))
2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((phi1 * 0.5));
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = cos((0.5 * (lambda1 - lambda2)));
double t_3 = sin((phi1 * 0.5));
return R * (2.0 * atan2(sqrt((pow(fma(t_3, cos((-0.5 * phi2)), (sin((-0.5 * phi2)) * t_0)), 2.0) + (t_1 * ((cos(phi1) * cos(phi2)) * t_1)))), sqrt((1.0 + ((cos(phi2) * (cos(phi1) * ((0.5 * fma(t_2, t_2, -fma(cos((lambda1 - lambda2)), -0.5, 0.5))) - 0.5))) - pow(((cos((0.5 * phi2)) * t_3) - (sin((0.5 * phi2)) * t_0)), 2.0))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(phi1 * 0.5)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = cos(Float64(0.5 * Float64(lambda1 - lambda2))) t_3 = sin(Float64(phi1 * 0.5)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((fma(t_3, cos(Float64(-0.5 * phi2)), Float64(sin(Float64(-0.5 * phi2)) * t_0)) ^ 2.0) + Float64(t_1 * Float64(Float64(cos(phi1) * cos(phi2)) * t_1)))), sqrt(Float64(1.0 + Float64(Float64(cos(phi2) * Float64(cos(phi1) * Float64(Float64(0.5 * fma(t_2, t_2, Float64(-fma(cos(Float64(lambda1 - lambda2)), -0.5, 0.5)))) - 0.5))) - (Float64(Float64(cos(Float64(0.5 * phi2)) * t_3) - Float64(sin(Float64(0.5 * phi2)) * t_0)) ^ 2.0))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Cos[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(t$95$3 * N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$1 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 + N[(N[(N[Cos[phi2], $MachinePrecision] * N[(N[Cos[phi1], $MachinePrecision] * N[(N[(0.5 * N[(t$95$2 * t$95$2 + (-N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] * -0.5 + 0.5), $MachinePrecision])), $MachinePrecision]), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[Power[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$3), $MachinePrecision] - N[(N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \cos \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\\
t_3 := \sin \left(\phi_1 \cdot 0.5\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(t\_3, \cos \left(-0.5 \cdot \phi_2\right), \sin \left(-0.5 \cdot \phi_2\right) \cdot t\_0\right)\right)}^{2} + t\_1 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_1\right)}}{\sqrt{1 + \left(\cos \phi_2 \cdot \left(\cos \phi_1 \cdot \left(0.5 \cdot \mathsf{fma}\left(t\_2, t\_2, -\mathsf{fma}\left(\cos \left(\lambda_1 - \lambda_2\right), -0.5, 0.5\right)\right) - 0.5\right)\right) - {\left(\cos \left(0.5 \cdot \phi_2\right) \cdot t\_3 - \sin \left(0.5 \cdot \phi_2\right) \cdot t\_0\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 61.4%
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-*.f6462.5
Applied egg-rr62.5%
div-subN/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
sin-sumN/A
lift-sin.f64N/A
lower-fma.f64N/A
lower-cos.f64N/A
metadata-evalN/A
lower-*.f64N/A
lift-cos.f64N/A
lower-*.f64N/A
Applied egg-rr76.6%
lift-cos.f64N/A
lift-cos.f64N/A
lift-*.f64N/A
lift--.f64N/A
lift-/.f64N/A
lift-sin.f64N/A
lift--.f64N/A
lift-/.f64N/A
lift-sin.f64N/A
associate-*l*N/A
lift-*.f64N/A
*-commutativeN/A
associate-*l*N/A
lower-*.f64N/A
lower-*.f64N/A
Applied egg-rr76.7%
Applied egg-rr76.7%
Final simplification76.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* phi1 0.5)))
(t_1 (cos (* phi1 0.5)))
(t_2
(pow (- (* (cos (* 0.5 phi2)) t_0) (* (sin (* 0.5 phi2)) t_1)) 2.0))
(t_3 (sin (/ (- lambda1 lambda2) 2.0)))
(t_4
(sqrt
(+
(pow (fma t_0 (cos (* -0.5 phi2)) (* (sin (* -0.5 phi2)) t_1)) 2.0)
(* t_3 (* (* (cos phi1) (cos phi2)) t_3)))))
(t_5
(*
R
(*
2.0
(atan2
t_4
(sqrt
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (fma (cos lambda2) -0.5 0.5))
t_2))))))))
(if (<= lambda2 -0.000125)
t_5
(if (<= lambda2 2.5e-5)
(*
R
(*
2.0
(atan2
t_4
(sqrt
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (fma -0.5 (cos lambda1) 0.5))
t_2))))))
t_5))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((phi1 * 0.5));
double t_1 = cos((phi1 * 0.5));
double t_2 = pow(((cos((0.5 * phi2)) * t_0) - (sin((0.5 * phi2)) * t_1)), 2.0);
double t_3 = sin(((lambda1 - lambda2) / 2.0));
double t_4 = sqrt((pow(fma(t_0, cos((-0.5 * phi2)), (sin((-0.5 * phi2)) * t_1)), 2.0) + (t_3 * ((cos(phi1) * cos(phi2)) * t_3))));
double t_5 = R * (2.0 * atan2(t_4, sqrt((1.0 - fma(cos(phi1), (cos(phi2) * fma(cos(lambda2), -0.5, 0.5)), t_2)))));
double tmp;
if (lambda2 <= -0.000125) {
tmp = t_5;
} else if (lambda2 <= 2.5e-5) {
tmp = R * (2.0 * atan2(t_4, sqrt((1.0 - fma(cos(phi1), (cos(phi2) * fma(-0.5, cos(lambda1), 0.5)), t_2)))));
} else {
tmp = t_5;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi1 * 0.5)) t_1 = cos(Float64(phi1 * 0.5)) t_2 = Float64(Float64(cos(Float64(0.5 * phi2)) * t_0) - Float64(sin(Float64(0.5 * phi2)) * t_1)) ^ 2.0 t_3 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_4 = sqrt(Float64((fma(t_0, cos(Float64(-0.5 * phi2)), Float64(sin(Float64(-0.5 * phi2)) * t_1)) ^ 2.0) + Float64(t_3 * Float64(Float64(cos(phi1) * cos(phi2)) * t_3)))) t_5 = Float64(R * Float64(2.0 * atan(t_4, sqrt(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * fma(cos(lambda2), -0.5, 0.5)), t_2)))))) tmp = 0.0 if (lambda2 <= -0.000125) tmp = t_5; elseif (lambda2 <= 2.5e-5) tmp = Float64(R * Float64(2.0 * atan(t_4, sqrt(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * fma(-0.5, cos(lambda1), 0.5)), t_2)))))); else tmp = t_5; end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision] - N[(N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[Sqrt[N[(N[Power[N[(t$95$0 * N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$3 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$3), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$5 = N[(R * N[(2.0 * N[ArcTan[t$95$4 / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(N[Cos[lambda2], $MachinePrecision] * -0.5 + 0.5), $MachinePrecision]), $MachinePrecision] + t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[lambda2, -0.000125], t$95$5, If[LessEqual[lambda2, 2.5e-5], N[(R * N[(2.0 * N[ArcTan[t$95$4 / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(-0.5 * N[Cos[lambda1], $MachinePrecision] + 0.5), $MachinePrecision]), $MachinePrecision] + t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$5]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_1 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_2 := {\left(\cos \left(0.5 \cdot \phi_2\right) \cdot t\_0 - \sin \left(0.5 \cdot \phi_2\right) \cdot t\_1\right)}^{2}\\
t_3 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_4 := \sqrt{{\left(\mathsf{fma}\left(t\_0, \cos \left(-0.5 \cdot \phi_2\right), \sin \left(-0.5 \cdot \phi_2\right) \cdot t\_1\right)\right)}^{2} + t\_3 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_3\right)}\\
t_5 := R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_4}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \mathsf{fma}\left(\cos \lambda_2, -0.5, 0.5\right), t\_2\right)}}\right)\\
\mathbf{if}\;\lambda_2 \leq -0.000125:\\
\;\;\;\;t\_5\\
\mathbf{elif}\;\lambda_2 \leq 2.5 \cdot 10^{-5}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_4}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \mathsf{fma}\left(-0.5, \cos \lambda_1, 0.5\right), t\_2\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;t\_5\\
\end{array}
\end{array}
if lambda2 < -1.25e-4 or 2.50000000000000012e-5 < lambda2 Initial program 42.4%
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-*.f6443.4
Applied egg-rr43.4%
div-subN/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
sin-sumN/A
lift-sin.f64N/A
lower-fma.f64N/A
lower-cos.f64N/A
metadata-evalN/A
lower-*.f64N/A
lift-cos.f64N/A
lower-*.f64N/A
Applied egg-rr54.8%
lift-cos.f64N/A
lift-cos.f64N/A
lift-*.f64N/A
lift--.f64N/A
lift-/.f64N/A
lift-sin.f64N/A
lift--.f64N/A
lift-/.f64N/A
lift-sin.f64N/A
associate-*l*N/A
lift-*.f64N/A
*-commutativeN/A
associate-*l*N/A
lower-*.f64N/A
lower-*.f64N/A
Applied egg-rr54.9%
Taylor expanded in lambda1 around 0
lower--.f64N/A
lower-fma.f64N/A
Simplified55.1%
if -1.25e-4 < lambda2 < 2.50000000000000012e-5Initial program 80.1%
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-*.f6481.2
Applied egg-rr81.2%
div-subN/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
sin-sumN/A
lift-sin.f64N/A
lower-fma.f64N/A
lower-cos.f64N/A
metadata-evalN/A
lower-*.f64N/A
lift-cos.f64N/A
lower-*.f64N/A
Applied egg-rr98.1%
lift-cos.f64N/A
lift-cos.f64N/A
lift-*.f64N/A
lift--.f64N/A
lift-/.f64N/A
lift-sin.f64N/A
lift--.f64N/A
lift-/.f64N/A
lift-sin.f64N/A
associate-*l*N/A
lift-*.f64N/A
*-commutativeN/A
associate-*l*N/A
lower-*.f64N/A
lower-*.f64N/A
Applied egg-rr98.2%
Taylor expanded in lambda2 around 0
lower--.f64N/A
lower-fma.f64N/A
lower-cos.f64N/A
*-commutativeN/A
lower-*.f64N/A
cancel-sign-sub-invN/A
metadata-evalN/A
+-commutativeN/A
lower-fma.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
Simplified98.1%
Final simplification76.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* 0.5 (- phi1 phi2)))
(t_1 (sin (* phi1 0.5)))
(t_2 (+ 1.0 (- 0.5 (* 0.5 (cos (* 2.0 t_0))))))
(t_3 (cos (- phi1 phi2)))
(t_4 (cos (* phi1 0.5)))
(t_5 (sin (/ (- lambda1 lambda2) 2.0)))
(t_6
(sqrt
(+
(pow (fma t_1 (cos (* -0.5 phi2)) (* (sin (* -0.5 phi2)) t_4)) 2.0)
(* t_5 (* (* (cos phi1) (cos phi2)) t_5)))))
(t_7 (+ (cos (+ phi1 phi2)) t_3)))
(if (<= lambda2 -1.55e-6)
(*
R
(*
2.0
(atan2
t_6
(sqrt
(/
(+ (+ 1.0 t_3) (* t_7 (- (* 0.5 (cos (- lambda1 lambda2))) 0.5)))
2.0)))))
(if (<= lambda2 1.35e-12)
(*
R
(*
2.0
(atan2
t_6
(sqrt
(-
1.0
(fma
(cos phi1)
(* (cos phi2) (fma -0.5 (cos lambda1) 0.5))
(pow
(- (* (cos (* 0.5 phi2)) t_1) (* (sin (* 0.5 phi2)) t_4))
2.0)))))))
(*
R
(*
2.0
(atan2
t_6
(sqrt
(/
(+
(* 2.0 (- 1.0 (pow (sin t_0) 4.0)))
(*
t_2
(*
t_7
(- (* 0.5 (cos (* 2.0 (* 0.5 (- lambda1 lambda2))))) 0.5))))
(* 2.0 t_2))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = 0.5 * (phi1 - phi2);
double t_1 = sin((phi1 * 0.5));
double t_2 = 1.0 + (0.5 - (0.5 * cos((2.0 * t_0))));
double t_3 = cos((phi1 - phi2));
double t_4 = cos((phi1 * 0.5));
double t_5 = sin(((lambda1 - lambda2) / 2.0));
double t_6 = sqrt((pow(fma(t_1, cos((-0.5 * phi2)), (sin((-0.5 * phi2)) * t_4)), 2.0) + (t_5 * ((cos(phi1) * cos(phi2)) * t_5))));
double t_7 = cos((phi1 + phi2)) + t_3;
double tmp;
if (lambda2 <= -1.55e-6) {
tmp = R * (2.0 * atan2(t_6, sqrt((((1.0 + t_3) + (t_7 * ((0.5 * cos((lambda1 - lambda2))) - 0.5))) / 2.0))));
} else if (lambda2 <= 1.35e-12) {
tmp = R * (2.0 * atan2(t_6, sqrt((1.0 - fma(cos(phi1), (cos(phi2) * fma(-0.5, cos(lambda1), 0.5)), pow(((cos((0.5 * phi2)) * t_1) - (sin((0.5 * phi2)) * t_4)), 2.0))))));
} else {
tmp = R * (2.0 * atan2(t_6, sqrt((((2.0 * (1.0 - pow(sin(t_0), 4.0))) + (t_2 * (t_7 * ((0.5 * cos((2.0 * (0.5 * (lambda1 - lambda2))))) - 0.5)))) / (2.0 * t_2)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(0.5 * Float64(phi1 - phi2)) t_1 = sin(Float64(phi1 * 0.5)) t_2 = Float64(1.0 + Float64(0.5 - Float64(0.5 * cos(Float64(2.0 * t_0))))) t_3 = cos(Float64(phi1 - phi2)) t_4 = cos(Float64(phi1 * 0.5)) t_5 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_6 = sqrt(Float64((fma(t_1, cos(Float64(-0.5 * phi2)), Float64(sin(Float64(-0.5 * phi2)) * t_4)) ^ 2.0) + Float64(t_5 * Float64(Float64(cos(phi1) * cos(phi2)) * t_5)))) t_7 = Float64(cos(Float64(phi1 + phi2)) + t_3) tmp = 0.0 if (lambda2 <= -1.55e-6) tmp = Float64(R * Float64(2.0 * atan(t_6, sqrt(Float64(Float64(Float64(1.0 + t_3) + Float64(t_7 * Float64(Float64(0.5 * cos(Float64(lambda1 - lambda2))) - 0.5))) / 2.0))))); elseif (lambda2 <= 1.35e-12) tmp = Float64(R * Float64(2.0 * atan(t_6, sqrt(Float64(1.0 - fma(cos(phi1), Float64(cos(phi2) * fma(-0.5, cos(lambda1), 0.5)), (Float64(Float64(cos(Float64(0.5 * phi2)) * t_1) - Float64(sin(Float64(0.5 * phi2)) * t_4)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(t_6, sqrt(Float64(Float64(Float64(2.0 * Float64(1.0 - (sin(t_0) ^ 4.0))) + Float64(t_2 * Float64(t_7 * Float64(Float64(0.5 * cos(Float64(2.0 * Float64(0.5 * Float64(lambda1 - lambda2))))) - 0.5)))) / Float64(2.0 * t_2)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(1.0 + N[(0.5 - N[(0.5 * N[Cos[N[(2.0 * t$95$0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$5 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$6 = N[Sqrt[N[(N[Power[N[(t$95$1 * N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$4), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$5 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$7 = N[(N[Cos[N[(phi1 + phi2), $MachinePrecision]], $MachinePrecision] + t$95$3), $MachinePrecision]}, If[LessEqual[lambda2, -1.55e-6], N[(R * N[(2.0 * N[ArcTan[t$95$6 / N[Sqrt[N[(N[(N[(1.0 + t$95$3), $MachinePrecision] + N[(t$95$7 * N[(N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[lambda2, 1.35e-12], N[(R * N[(2.0 * N[ArcTan[t$95$6 / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(-0.5 * N[Cos[lambda1], $MachinePrecision] + 0.5), $MachinePrecision]), $MachinePrecision] + N[Power[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$1), $MachinePrecision] - N[(N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$4), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$6 / N[Sqrt[N[(N[(N[(2.0 * N[(1.0 - N[Power[N[Sin[t$95$0], $MachinePrecision], 4.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(t$95$2 * N[(t$95$7 * N[(N[(0.5 * N[Cos[N[(2.0 * N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / N[(2.0 * t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := 0.5 \cdot \left(\phi_1 - \phi_2\right)\\
t_1 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_2 := 1 + \left(0.5 - 0.5 \cdot \cos \left(2 \cdot t\_0\right)\right)\\
t_3 := \cos \left(\phi_1 - \phi_2\right)\\
t_4 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_5 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_6 := \sqrt{{\left(\mathsf{fma}\left(t\_1, \cos \left(-0.5 \cdot \phi_2\right), \sin \left(-0.5 \cdot \phi_2\right) \cdot t\_4\right)\right)}^{2} + t\_5 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_5\right)}\\
t_7 := \cos \left(\phi_1 + \phi_2\right) + t\_3\\
\mathbf{if}\;\lambda_2 \leq -1.55 \cdot 10^{-6}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_6}{\sqrt{\frac{\left(1 + t\_3\right) + t\_7 \cdot \left(0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right) - 0.5\right)}{2}}}\right)\\
\mathbf{elif}\;\lambda_2 \leq 1.35 \cdot 10^{-12}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_6}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, \cos \phi_2 \cdot \mathsf{fma}\left(-0.5, \cos \lambda_1, 0.5\right), {\left(\cos \left(0.5 \cdot \phi_2\right) \cdot t\_1 - \sin \left(0.5 \cdot \phi_2\right) \cdot t\_4\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_6}{\sqrt{\frac{2 \cdot \left(1 - {\sin t\_0}^{4}\right) + t\_2 \cdot \left(t\_7 \cdot \left(0.5 \cdot \cos \left(2 \cdot \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\right) - 0.5\right)\right)}{2 \cdot t\_2}}}\right)\\
\end{array}
\end{array}
if lambda2 < -1.55e-6Initial program 44.8%
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-*.f6445.4
Applied egg-rr45.4%
div-subN/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
sin-sumN/A
lift-sin.f64N/A
lower-fma.f64N/A
lower-cos.f64N/A
metadata-evalN/A
lower-*.f64N/A
lift-cos.f64N/A
lower-*.f64N/A
Applied egg-rr57.9%
Applied egg-rr46.3%
if -1.55e-6 < lambda2 < 1.3499999999999999e-12Initial program 79.8%
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-*.f6481.0
Applied egg-rr81.0%
div-subN/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
sin-sumN/A
lift-sin.f64N/A
lower-fma.f64N/A
lower-cos.f64N/A
metadata-evalN/A
lower-*.f64N/A
lift-cos.f64N/A
lower-*.f64N/A
Applied egg-rr98.4%
lift-cos.f64N/A
lift-cos.f64N/A
lift-*.f64N/A
lift--.f64N/A
lift-/.f64N/A
lift-sin.f64N/A
lift--.f64N/A
lift-/.f64N/A
lift-sin.f64N/A
associate-*l*N/A
lift-*.f64N/A
*-commutativeN/A
associate-*l*N/A
lower-*.f64N/A
lower-*.f64N/A
Applied egg-rr98.5%
Taylor expanded in lambda2 around 0
lower--.f64N/A
lower-fma.f64N/A
lower-cos.f64N/A
*-commutativeN/A
lower-*.f64N/A
cancel-sign-sub-invN/A
metadata-evalN/A
+-commutativeN/A
lower-fma.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
Simplified98.5%
if 1.3499999999999999e-12 < lambda2 Initial program 43.1%
Applied egg-rr44.1%
div-subN/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
sin-sumN/A
lift-sin.f64N/A
lower-fma.f64N/A
lower-cos.f64N/A
metadata-evalN/A
lower-*.f64N/A
lift-cos.f64N/A
lower-*.f64N/A
Applied egg-rr44.5%
Final simplification71.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* phi1 0.5)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (* t_1 (* (* (cos phi1) (cos phi2)) t_1)))
(t_3 (cos (* phi1 0.5)))
(t_4
(pow (fma t_0 (cos (* -0.5 phi2)) (* (sin (* -0.5 phi2)) t_3)) 2.0))
(t_5
(pow (- (* (cos (* 0.5 phi2)) t_0) (* (sin (* 0.5 phi2)) t_3)) 2.0))
(t_6 (* (cos phi2) (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0)))
(t_7 (sqrt (+ t_4 t_2))))
(if (<= phi2 -4.4e-54)
(* R (* 2.0 (atan2 (sqrt (+ t_4 t_6)) (sqrt (- 1.0 (+ t_2 t_5))))))
(if (<= phi2 2400000000000.0)
(*
R
(*
2.0
(atan2
t_7
(sqrt
(fma
phi2
(* t_0 t_3)
(-
(pow t_3 2.0)
(* (cos phi1) (fma -0.5 (cos (- lambda1 lambda2)) 0.5))))))))
(* R (* 2.0 (atan2 t_7 (sqrt (- 1.0 (+ t_5 t_6))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((phi1 * 0.5));
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = t_1 * ((cos(phi1) * cos(phi2)) * t_1);
double t_3 = cos((phi1 * 0.5));
double t_4 = pow(fma(t_0, cos((-0.5 * phi2)), (sin((-0.5 * phi2)) * t_3)), 2.0);
double t_5 = pow(((cos((0.5 * phi2)) * t_0) - (sin((0.5 * phi2)) * t_3)), 2.0);
double t_6 = cos(phi2) * pow(sin((-0.5 * (lambda2 - lambda1))), 2.0);
double t_7 = sqrt((t_4 + t_2));
double tmp;
if (phi2 <= -4.4e-54) {
tmp = R * (2.0 * atan2(sqrt((t_4 + t_6)), sqrt((1.0 - (t_2 + t_5)))));
} else if (phi2 <= 2400000000000.0) {
tmp = R * (2.0 * atan2(t_7, sqrt(fma(phi2, (t_0 * t_3), (pow(t_3, 2.0) - (cos(phi1) * fma(-0.5, cos((lambda1 - lambda2)), 0.5)))))));
} else {
tmp = R * (2.0 * atan2(t_7, sqrt((1.0 - (t_5 + t_6)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi1 * 0.5)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(t_1 * Float64(Float64(cos(phi1) * cos(phi2)) * t_1)) t_3 = cos(Float64(phi1 * 0.5)) t_4 = fma(t_0, cos(Float64(-0.5 * phi2)), Float64(sin(Float64(-0.5 * phi2)) * t_3)) ^ 2.0 t_5 = Float64(Float64(cos(Float64(0.5 * phi2)) * t_0) - Float64(sin(Float64(0.5 * phi2)) * t_3)) ^ 2.0 t_6 = Float64(cos(phi2) * (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0)) t_7 = sqrt(Float64(t_4 + t_2)) tmp = 0.0 if (phi2 <= -4.4e-54) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(t_4 + t_6)), sqrt(Float64(1.0 - Float64(t_2 + t_5)))))); elseif (phi2 <= 2400000000000.0) tmp = Float64(R * Float64(2.0 * atan(t_7, sqrt(fma(phi2, Float64(t_0 * t_3), Float64((t_3 ^ 2.0) - Float64(cos(phi1) * fma(-0.5, cos(Float64(lambda1 - lambda2)), 0.5)))))))); else tmp = Float64(R * Float64(2.0 * atan(t_7, sqrt(Float64(1.0 - Float64(t_5 + t_6)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(t$95$1 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[Power[N[(t$95$0 * N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$3), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$5 = N[Power[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision] - N[(N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$3), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$6 = N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$7 = N[Sqrt[N[(t$95$4 + t$95$2), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi2, -4.4e-54], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$4 + t$95$6), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$2 + t$95$5), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[phi2, 2400000000000.0], N[(R * N[(2.0 * N[ArcTan[t$95$7 / N[Sqrt[N[(phi2 * N[(t$95$0 * t$95$3), $MachinePrecision] + N[(N[Power[t$95$3, 2.0], $MachinePrecision] - N[(N[Cos[phi1], $MachinePrecision] * N[(-0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] + 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[t$95$7 / N[Sqrt[N[(1.0 - N[(t$95$5 + t$95$6), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := t\_1 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_1\right)\\
t_3 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_4 := {\left(\mathsf{fma}\left(t\_0, \cos \left(-0.5 \cdot \phi_2\right), \sin \left(-0.5 \cdot \phi_2\right) \cdot t\_3\right)\right)}^{2}\\
t_5 := {\left(\cos \left(0.5 \cdot \phi_2\right) \cdot t\_0 - \sin \left(0.5 \cdot \phi_2\right) \cdot t\_3\right)}^{2}\\
t_6 := \cos \phi_2 \cdot {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2}\\
t_7 := \sqrt{t\_4 + t\_2}\\
\mathbf{if}\;\phi_2 \leq -4.4 \cdot 10^{-54}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_4 + t\_6}}{\sqrt{1 - \left(t\_2 + t\_5\right)}}\right)\\
\mathbf{elif}\;\phi_2 \leq 2400000000000:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_7}{\sqrt{\mathsf{fma}\left(\phi_2, t\_0 \cdot t\_3, {t\_3}^{2} - \cos \phi_1 \cdot \mathsf{fma}\left(-0.5, \cos \left(\lambda_1 - \lambda_2\right), 0.5\right)\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_7}{\sqrt{1 - \left(t\_5 + t\_6\right)}}\right)\\
\end{array}
\end{array}
if phi2 < -4.3999999999999999e-54Initial program 47.9%
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-*.f6450.1
Applied egg-rr50.1%
div-subN/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
sin-sumN/A
lift-sin.f64N/A
lower-fma.f64N/A
lower-cos.f64N/A
metadata-evalN/A
lower-*.f64N/A
lift-cos.f64N/A
lower-*.f64N/A
Applied egg-rr73.5%
Taylor expanded in phi1 around 0
lower-*.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
sub-negN/A
distribute-lft-inN/A
+-commutativeN/A
distribute-rgt-neg-outN/A
distribute-lft-neg-inN/A
metadata-evalN/A
metadata-evalN/A
distribute-lft-neg-inN/A
distribute-rgt-neg-outN/A
mul-1-negN/A
distribute-lft-inN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f6458.0
Simplified58.0%
if -4.3999999999999999e-54 < phi2 < 2.4e12Initial program 76.8%
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-*.f6476.8
Applied egg-rr76.8%
div-subN/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
sin-sumN/A
lift-sin.f64N/A
lower-fma.f64N/A
lower-cos.f64N/A
metadata-evalN/A
lower-*.f64N/A
lift-cos.f64N/A
lower-*.f64N/A
Applied egg-rr77.1%
lift-cos.f64N/A
lift-cos.f64N/A
lift-*.f64N/A
lift--.f64N/A
lift-/.f64N/A
lift-sin.f64N/A
lift--.f64N/A
lift-/.f64N/A
lift-sin.f64N/A
associate-*l*N/A
lift-*.f64N/A
*-commutativeN/A
associate-*l*N/A
lower-*.f64N/A
lower-*.f64N/A
Applied egg-rr77.2%
Taylor expanded in phi2 around 0
Simplified77.3%
if 2.4e12 < phi2 Initial program 46.2%
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-*.f6447.9
Applied egg-rr47.9%
div-subN/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
sin-sumN/A
lift-sin.f64N/A
lower-fma.f64N/A
lower-cos.f64N/A
metadata-evalN/A
lower-*.f64N/A
lift-cos.f64N/A
lower-*.f64N/A
Applied egg-rr79.9%
Taylor expanded in phi1 around 0
lower-*.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
sub-negN/A
distribute-lft-inN/A
+-commutativeN/A
distribute-rgt-neg-outN/A
distribute-lft-neg-inN/A
metadata-evalN/A
metadata-evalN/A
distribute-lft-neg-inN/A
distribute-rgt-neg-outN/A
mul-1-negN/A
distribute-lft-inN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f6457.6
Simplified57.6%
Final simplification67.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (* phi1 0.5)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (sin (* phi1 0.5))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (fma t_2 (cos (* -0.5 phi2)) (* (sin (* -0.5 phi2)) t_0)) 2.0)
(* t_1 (* (* (cos phi1) (cos phi2)) t_1))))
(sqrt
(+
1.0
(-
(*
(cos phi2)
(* (cos phi1) (- (* 0.5 (cos (- lambda1 lambda2))) 0.5)))
(pow
(- (* (cos (* 0.5 phi2)) t_2) (* (sin (* 0.5 phi2)) t_0))
2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((phi1 * 0.5));
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = sin((phi1 * 0.5));
return R * (2.0 * atan2(sqrt((pow(fma(t_2, cos((-0.5 * phi2)), (sin((-0.5 * phi2)) * t_0)), 2.0) + (t_1 * ((cos(phi1) * cos(phi2)) * t_1)))), sqrt((1.0 + ((cos(phi2) * (cos(phi1) * ((0.5 * cos((lambda1 - lambda2))) - 0.5))) - pow(((cos((0.5 * phi2)) * t_2) - (sin((0.5 * phi2)) * t_0)), 2.0))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(phi1 * 0.5)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = sin(Float64(phi1 * 0.5)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((fma(t_2, cos(Float64(-0.5 * phi2)), Float64(sin(Float64(-0.5 * phi2)) * t_0)) ^ 2.0) + Float64(t_1 * Float64(Float64(cos(phi1) * cos(phi2)) * t_1)))), sqrt(Float64(1.0 + Float64(Float64(cos(phi2) * Float64(cos(phi1) * Float64(Float64(0.5 * cos(Float64(lambda1 - lambda2))) - 0.5))) - (Float64(Float64(cos(Float64(0.5 * phi2)) * t_2) - Float64(sin(Float64(0.5 * phi2)) * t_0)) ^ 2.0))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(t$95$2 * N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$1 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 + N[(N[(N[Cos[phi2], $MachinePrecision] * N[(N[Cos[phi1], $MachinePrecision] * N[(N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[Power[N[(N[(N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$2), $MachinePrecision] - N[(N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \sin \left(\phi_1 \cdot 0.5\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(t\_2, \cos \left(-0.5 \cdot \phi_2\right), \sin \left(-0.5 \cdot \phi_2\right) \cdot t\_0\right)\right)}^{2} + t\_1 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_1\right)}}{\sqrt{1 + \left(\cos \phi_2 \cdot \left(\cos \phi_1 \cdot \left(0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right) - 0.5\right)\right) - {\left(\cos \left(0.5 \cdot \phi_2\right) \cdot t\_2 - \sin \left(0.5 \cdot \phi_2\right) \cdot t\_0\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 61.4%
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-*.f6462.5
Applied egg-rr62.5%
div-subN/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
sin-sumN/A
lift-sin.f64N/A
lower-fma.f64N/A
lower-cos.f64N/A
metadata-evalN/A
lower-*.f64N/A
lift-cos.f64N/A
lower-*.f64N/A
Applied egg-rr76.6%
lift-cos.f64N/A
lift-cos.f64N/A
lift-*.f64N/A
lift--.f64N/A
lift-/.f64N/A
lift-sin.f64N/A
lift--.f64N/A
lift-/.f64N/A
lift-sin.f64N/A
associate-*l*N/A
lift-*.f64N/A
*-commutativeN/A
associate-*l*N/A
lower-*.f64N/A
lower-*.f64N/A
Applied egg-rr76.7%
Final simplification76.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))
(t_2 (sin (/ (- lambda1 lambda2) 2.0))))
(if (<= (+ (* t_2 (* t_0 t_2)) t_1) 0.001)
(*
R
(*
2.0
(atan2
(sqrt
(+ (* (cos phi2) (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0)) t_1))
(sqrt
(-
(pow (cos (* phi1 0.5)) 2.0)
(* (cos phi1) (pow (sin (* 0.5 lambda1)) 2.0)))))))
(*
R
(*
2.0
(atan2
(pow
(pow
(fma
t_0
(fma (cos (- lambda1 lambda2)) -0.5 0.5)
(- 0.5 (* 0.5 (cos (- phi1 phi2)))))
2.0)
0.25)
(sqrt
(+
(+ 0.5 (* 0.5 (cos (* 2.0 (* 0.5 (- phi1 phi2))))))
(*
t_0
(- (* 0.5 (cos (* 2.0 (* 0.5 (- lambda1 lambda2))))) 0.5))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if (((t_2 * (t_0 * t_2)) + t_1) <= 0.001) {
tmp = R * (2.0 * atan2(sqrt(((cos(phi2) * pow(sin((-0.5 * (lambda2 - lambda1))), 2.0)) + t_1)), sqrt((pow(cos((phi1 * 0.5)), 2.0) - (cos(phi1) * pow(sin((0.5 * lambda1)), 2.0))))));
} else {
tmp = R * (2.0 * atan2(pow(pow(fma(t_0, fma(cos((lambda1 - lambda2)), -0.5, 0.5), (0.5 - (0.5 * cos((phi1 - phi2))))), 2.0), 0.25), sqrt(((0.5 + (0.5 * cos((2.0 * (0.5 * (phi1 - phi2)))))) + (t_0 * ((0.5 * cos((2.0 * (0.5 * (lambda1 - lambda2))))) - 0.5))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if (Float64(Float64(t_2 * Float64(t_0 * t_2)) + t_1) <= 0.001) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi2) * (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0)) + t_1)), sqrt(Float64((cos(Float64(phi1 * 0.5)) ^ 2.0) - Float64(cos(phi1) * (sin(Float64(0.5 * lambda1)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(((fma(t_0, fma(cos(Float64(lambda1 - lambda2)), -0.5, 0.5), Float64(0.5 - Float64(0.5 * cos(Float64(phi1 - phi2))))) ^ 2.0) ^ 0.25), sqrt(Float64(Float64(0.5 + Float64(0.5 * cos(Float64(2.0 * Float64(0.5 * Float64(phi1 - phi2)))))) + Float64(t_0 * Float64(Float64(0.5 * cos(Float64(2.0 * Float64(0.5 * Float64(lambda1 - lambda2))))) - 0.5))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[N[(N[(t$95$2 * N[(t$95$0 * t$95$2), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision], 0.001], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Power[N[Power[N[(t$95$0 * N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] * -0.5 + 0.5), $MachinePrecision] + N[(0.5 - N[(0.5 * N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision], 0.25], $MachinePrecision] / 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[(t$95$0 * N[(N[(0.5 * N[Cos[N[(2.0 * N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;t\_2 \cdot \left(t\_0 \cdot t\_2\right) + t\_1 \leq 0.001:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2} + t\_1}}{\sqrt{{\cos \left(\phi_1 \cdot 0.5\right)}^{2} - \cos \phi_1 \cdot {\sin \left(0.5 \cdot \lambda_1\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{{\left({\left(\mathsf{fma}\left(t\_0, \mathsf{fma}\left(\cos \left(\lambda_1 - \lambda_2\right), -0.5, 0.5\right), 0.5 - 0.5 \cdot \cos \left(\phi_1 - \phi_2\right)\right)\right)}^{2}\right)}^{0.25}}{\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\_0 \cdot \left(0.5 \cdot \cos \left(2 \cdot \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\right) - 0.5\right)}}\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))))) < 1e-3Initial program 78.1%
Taylor expanded in lambda2 around 0
lower--.f64N/A
associate-*r*N/A
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
Simplified78.1%
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
lower-cos.f64N/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6478.1
Simplified78.1%
Taylor expanded in phi1 around 0
lower-*.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
sub-negN/A
distribute-lft-inN/A
+-commutativeN/A
distribute-rgt-neg-outN/A
distribute-lft-neg-inN/A
metadata-evalN/A
metadata-evalN/A
distribute-lft-neg-inN/A
distribute-rgt-neg-outN/A
mul-1-negN/A
distribute-lft-inN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f6479.8
Simplified79.8%
if 1e-3 < (+.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 59.6%
Applied egg-rr59.7%
Applied egg-rr59.6%
Final simplification61.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))
(t_2 (sin (/ (- lambda1 lambda2) 2.0))))
(if (<= (+ (* t_2 (* t_0 t_2)) t_1) 0.001)
(*
R
(*
2.0
(atan2
(sqrt
(+ (* (cos phi2) (pow (sin (* -0.5 (- lambda2 lambda1))) 2.0)) t_1))
(sqrt
(-
(pow (cos (* phi1 0.5)) 2.0)
(* (cos phi1) (pow (sin (* 0.5 lambda1)) 2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt
(fma
t_0
(fma (cos (- lambda1 lambda2)) -0.5 0.5)
(- 0.5 (* 0.5 (cos (- phi1 phi2))))))
(sqrt
(+
(+ 0.5 (* 0.5 (cos (* 2.0 (* 0.5 (- phi1 phi2))))))
(*
t_0
(- (* 0.5 (cos (* 2.0 (* 0.5 (- lambda1 lambda2))))) 0.5))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if (((t_2 * (t_0 * t_2)) + t_1) <= 0.001) {
tmp = R * (2.0 * atan2(sqrt(((cos(phi2) * pow(sin((-0.5 * (lambda2 - lambda1))), 2.0)) + t_1)), sqrt((pow(cos((phi1 * 0.5)), 2.0) - (cos(phi1) * pow(sin((0.5 * lambda1)), 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt(fma(t_0, fma(cos((lambda1 - lambda2)), -0.5, 0.5), (0.5 - (0.5 * cos((phi1 - phi2)))))), sqrt(((0.5 + (0.5 * cos((2.0 * (0.5 * (phi1 - phi2)))))) + (t_0 * ((0.5 * cos((2.0 * (0.5 * (lambda1 - lambda2))))) - 0.5))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if (Float64(Float64(t_2 * Float64(t_0 * t_2)) + t_1) <= 0.001) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(cos(phi2) * (sin(Float64(-0.5 * Float64(lambda2 - lambda1))) ^ 2.0)) + t_1)), sqrt(Float64((cos(Float64(phi1 * 0.5)) ^ 2.0) - Float64(cos(phi1) * (sin(Float64(0.5 * lambda1)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_0, fma(cos(Float64(lambda1 - lambda2)), -0.5, 0.5), Float64(0.5 - Float64(0.5 * cos(Float64(phi1 - phi2)))))), sqrt(Float64(Float64(0.5 + Float64(0.5 * cos(Float64(2.0 * Float64(0.5 * Float64(phi1 - phi2)))))) + Float64(t_0 * Float64(Float64(0.5 * cos(Float64(2.0 * Float64(0.5 * Float64(lambda1 - lambda2))))) - 0.5))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[N[(N[(t$95$2 * N[(t$95$0 * t$95$2), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision], 0.001], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * N[Power[N[Sin[N[(-0.5 * N[(lambda2 - lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Cos[phi1], $MachinePrecision] * N[Power[N[Sin[N[(0.5 * lambda1), $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[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] * -0.5 + 0.5), $MachinePrecision] + N[(0.5 - N[(0.5 * N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / 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[(t$95$0 * N[(N[(0.5 * N[Cos[N[(2.0 * N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;t\_2 \cdot \left(t\_0 \cdot t\_2\right) + t\_1 \leq 0.001:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\cos \phi_2 \cdot {\sin \left(-0.5 \cdot \left(\lambda_2 - \lambda_1\right)\right)}^{2} + t\_1}}{\sqrt{{\cos \left(\phi_1 \cdot 0.5\right)}^{2} - \cos \phi_1 \cdot {\sin \left(0.5 \cdot \lambda_1\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \mathsf{fma}\left(\cos \left(\lambda_1 - \lambda_2\right), -0.5, 0.5\right), 0.5 - 0.5 \cdot \cos \left(\phi_1 - \phi_2\right)\right)}}{\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\_0 \cdot \left(0.5 \cdot \cos \left(2 \cdot \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\right) - 0.5\right)}}\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))))) < 1e-3Initial program 78.1%
Taylor expanded in lambda2 around 0
lower--.f64N/A
associate-*r*N/A
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
Simplified78.1%
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
lower-cos.f64N/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6478.1
Simplified78.1%
Taylor expanded in phi1 around 0
lower-*.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
sub-negN/A
distribute-lft-inN/A
+-commutativeN/A
distribute-rgt-neg-outN/A
distribute-lft-neg-inN/A
metadata-evalN/A
metadata-evalN/A
distribute-lft-neg-inN/A
distribute-rgt-neg-outN/A
mul-1-negN/A
distribute-lft-inN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f6479.8
Simplified79.8%
if 1e-3 < (+.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 59.6%
Applied egg-rr59.7%
Applied egg-rr59.6%
Final simplification61.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (+ (* t_1 (* t_0 t_1)) (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))))
(if (<= t_2 0.001)
(*
R
(*
2.0
(atan2
(sqrt t_2)
(sqrt
(fma
(- 0.5 (* 0.5 (cos (* 2.0 (* 0.5 lambda1)))))
(- (cos phi1))
(+ 0.5 (* 0.5 (cos (* 2.0 (* phi1 0.5))))))))))
(*
R
(*
2.0
(atan2
(sqrt
(fma
t_0
(fma (cos (- lambda1 lambda2)) -0.5 0.5)
(- 0.5 (* 0.5 (cos (- phi1 phi2))))))
(sqrt
(+
(+ 0.5 (* 0.5 (cos (* 2.0 (* 0.5 (- phi1 phi2))))))
(*
t_0
(- (* 0.5 (cos (* 2.0 (* 0.5 (- lambda1 lambda2))))) 0.5))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = (t_1 * (t_0 * t_1)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double tmp;
if (t_2 <= 0.001) {
tmp = R * (2.0 * atan2(sqrt(t_2), sqrt(fma((0.5 - (0.5 * cos((2.0 * (0.5 * lambda1))))), -cos(phi1), (0.5 + (0.5 * cos((2.0 * (phi1 * 0.5)))))))));
} else {
tmp = R * (2.0 * atan2(sqrt(fma(t_0, fma(cos((lambda1 - lambda2)), -0.5, 0.5), (0.5 - (0.5 * cos((phi1 - phi2)))))), sqrt(((0.5 + (0.5 * cos((2.0 * (0.5 * (phi1 - phi2)))))) + (t_0 * ((0.5 * cos((2.0 * (0.5 * (lambda1 - lambda2))))) - 0.5))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(Float64(t_1 * Float64(t_0 * t_1)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0)) tmp = 0.0 if (t_2 <= 0.001) tmp = Float64(R * Float64(2.0 * atan(sqrt(t_2), sqrt(fma(Float64(0.5 - Float64(0.5 * cos(Float64(2.0 * Float64(0.5 * lambda1))))), Float64(-cos(phi1)), Float64(0.5 + Float64(0.5 * cos(Float64(2.0 * Float64(phi1 * 0.5)))))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_0, fma(cos(Float64(lambda1 - lambda2)), -0.5, 0.5), Float64(0.5 - Float64(0.5 * cos(Float64(phi1 - phi2)))))), sqrt(Float64(Float64(0.5 + Float64(0.5 * cos(Float64(2.0 * Float64(0.5 * Float64(phi1 - phi2)))))) + Float64(t_0 * Float64(Float64(0.5 * cos(Float64(2.0 * Float64(0.5 * Float64(lambda1 - lambda2))))) - 0.5))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[(t$95$1 * N[(t$95$0 * t$95$1), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$2, 0.001], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$2], $MachinePrecision] / N[Sqrt[N[(N[(0.5 - N[(0.5 * N[Cos[N[(2.0 * N[(0.5 * lambda1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * (-N[Cos[phi1], $MachinePrecision]) + N[(0.5 + N[(0.5 * N[Cos[N[(2.0 * N[(phi1 * 0.5), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 * N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] * -0.5 + 0.5), $MachinePrecision] + N[(0.5 - N[(0.5 * N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / 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[(t$95$0 * N[(N[(0.5 * N[Cos[N[(2.0 * N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := t\_1 \cdot \left(t\_0 \cdot t\_1\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
\mathbf{if}\;t\_2 \leq 0.001:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2}}{\sqrt{\mathsf{fma}\left(0.5 - 0.5 \cdot \cos \left(2 \cdot \left(0.5 \cdot \lambda_1\right)\right), -\cos \phi_1, 0.5 + 0.5 \cdot \cos \left(2 \cdot \left(\phi_1 \cdot 0.5\right)\right)\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \mathsf{fma}\left(\cos \left(\lambda_1 - \lambda_2\right), -0.5, 0.5\right), 0.5 - 0.5 \cdot \cos \left(\phi_1 - \phi_2\right)\right)}}{\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\_0 \cdot \left(0.5 \cdot \cos \left(2 \cdot \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\right) - 0.5\right)}}\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))))) < 1e-3Initial program 78.1%
Taylor expanded in lambda2 around 0
lower--.f64N/A
associate-*r*N/A
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
Simplified78.1%
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
lower-cos.f64N/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6478.1
Simplified78.1%
Applied egg-rr78.1%
if 1e-3 < (+.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 59.6%
Applied egg-rr59.7%
Applied egg-rr59.6%
Final simplification61.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (+ (* t_1 (* t_0 t_1)) (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))))
(if (<= t_2 0.0005)
(* R (* 2.0 (atan2 (sqrt t_2) (sqrt (pow (cos (* 0.5 lambda1)) 2.0)))))
(*
R
(*
2.0
(atan2
(sqrt
(fma
t_0
(fma (cos (- lambda1 lambda2)) -0.5 0.5)
(- 0.5 (* 0.5 (cos (- phi1 phi2))))))
(sqrt
(+
(+ 0.5 (* 0.5 (cos (* 2.0 (* 0.5 (- phi1 phi2))))))
(*
t_0
(- (* 0.5 (cos (* 2.0 (* 0.5 (- lambda1 lambda2))))) 0.5))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = (t_1 * (t_0 * t_1)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double tmp;
if (t_2 <= 0.0005) {
tmp = R * (2.0 * atan2(sqrt(t_2), sqrt(pow(cos((0.5 * lambda1)), 2.0))));
} else {
tmp = R * (2.0 * atan2(sqrt(fma(t_0, fma(cos((lambda1 - lambda2)), -0.5, 0.5), (0.5 - (0.5 * cos((phi1 - phi2)))))), sqrt(((0.5 + (0.5 * cos((2.0 * (0.5 * (phi1 - phi2)))))) + (t_0 * ((0.5 * cos((2.0 * (0.5 * (lambda1 - lambda2))))) - 0.5))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(Float64(t_1 * Float64(t_0 * t_1)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0)) tmp = 0.0 if (t_2 <= 0.0005) tmp = Float64(R * Float64(2.0 * atan(sqrt(t_2), sqrt((cos(Float64(0.5 * lambda1)) ^ 2.0))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_0, fma(cos(Float64(lambda1 - lambda2)), -0.5, 0.5), Float64(0.5 - Float64(0.5 * cos(Float64(phi1 - phi2)))))), sqrt(Float64(Float64(0.5 + Float64(0.5 * cos(Float64(2.0 * Float64(0.5 * Float64(phi1 - phi2)))))) + Float64(t_0 * Float64(Float64(0.5 * cos(Float64(2.0 * Float64(0.5 * Float64(lambda1 - lambda2))))) - 0.5))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[(t$95$1 * N[(t$95$0 * t$95$1), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, If[LessEqual[t$95$2, 0.0005], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$2], $MachinePrecision] / N[Sqrt[N[Power[N[Cos[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 * N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] * -0.5 + 0.5), $MachinePrecision] + N[(0.5 - N[(0.5 * N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / 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[(t$95$0 * N[(N[(0.5 * N[Cos[N[(2.0 * N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := t\_1 \cdot \left(t\_0 \cdot t\_1\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
\mathbf{if}\;t\_2 \leq 0.0005:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2}}{\sqrt{{\cos \left(0.5 \cdot \lambda_1\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \mathsf{fma}\left(\cos \left(\lambda_1 - \lambda_2\right), -0.5, 0.5\right), 0.5 - 0.5 \cdot \cos \left(\phi_1 - \phi_2\right)\right)}}{\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\_0 \cdot \left(0.5 \cdot \cos \left(2 \cdot \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)\right) - 0.5\right)}}\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-4Initial program 83.5%
Taylor expanded in lambda2 around 0
lower--.f64N/A
associate-*r*N/A
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
Simplified83.5%
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
lower-cos.f64N/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6483.5
Simplified83.5%
Taylor expanded in phi1 around 0
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower-pow.f64N/A
lower-cos.f64N/A
lower-*.f6483.5
Simplified83.5%
if 5.0000000000000001e-4 < (+.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 59.2%
Applied egg-rr59.3%
Applied egg-rr59.3%
Final simplification61.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (- phi1 phi2))) (t_1 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow
(fma
(sin (* phi1 0.5))
(cos (* -0.5 phi2))
(* (sin (* -0.5 phi2)) (cos (* phi1 0.5))))
2.0)
(* t_1 (* (* (cos phi1) (cos phi2)) t_1))))
(sqrt
(/
(+
(+ 1.0 t_0)
(*
(+ (cos (+ phi1 phi2)) t_0)
(- (* 0.5 (cos (- lambda1 lambda2))) 0.5)))
2.0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((phi1 - phi2));
double t_1 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((pow(fma(sin((phi1 * 0.5)), cos((-0.5 * phi2)), (sin((-0.5 * phi2)) * cos((phi1 * 0.5)))), 2.0) + (t_1 * ((cos(phi1) * cos(phi2)) * t_1)))), sqrt((((1.0 + t_0) + ((cos((phi1 + phi2)) + t_0) * ((0.5 * cos((lambda1 - lambda2))) - 0.5))) / 2.0))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(phi1 - phi2)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((fma(sin(Float64(phi1 * 0.5)), cos(Float64(-0.5 * phi2)), Float64(sin(Float64(-0.5 * phi2)) * cos(Float64(phi1 * 0.5)))) ^ 2.0) + Float64(t_1 * Float64(Float64(cos(phi1) * cos(phi2)) * t_1)))), sqrt(Float64(Float64(Float64(1.0 + t_0) + Float64(Float64(cos(Float64(phi1 + phi2)) + t_0) * Float64(Float64(0.5 * cos(Float64(lambda1 - lambda2))) - 0.5))) / 2.0))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(t$95$1 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(N[(1.0 + t$95$0), $MachinePrecision] + N[(N[(N[Cos[N[(phi1 + phi2), $MachinePrecision]], $MachinePrecision] + t$95$0), $MachinePrecision] * N[(N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(\phi_1 - \phi_2\right)\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(\sin \left(\phi_1 \cdot 0.5\right), \cos \left(-0.5 \cdot \phi_2\right), \sin \left(-0.5 \cdot \phi_2\right) \cdot \cos \left(\phi_1 \cdot 0.5\right)\right)\right)}^{2} + t\_1 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_1\right)}}{\sqrt{\frac{\left(1 + t\_0\right) + \left(\cos \left(\phi_1 + \phi_2\right) + t\_0\right) \cdot \left(0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right) - 0.5\right)}{2}}}\right)
\end{array}
\end{array}
Initial program 61.4%
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-*.f6462.5
Applied egg-rr62.5%
div-subN/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
sin-sumN/A
lift-sin.f64N/A
lower-fma.f64N/A
lower-cos.f64N/A
metadata-evalN/A
lower-*.f64N/A
lift-cos.f64N/A
lower-*.f64N/A
Applied egg-rr76.6%
Applied egg-rr62.7%
Final simplification62.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (- phi1 phi2))) (t_1 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(* t_1 (* (* (cos phi1) (cos phi2)) t_1))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt
(/
(-
(+ 1.0 t_0)
(*
(+ (cos (+ phi1 phi2)) t_0)
(fma (cos (- lambda1 lambda2)) -0.5 0.5)))
2.0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((phi1 - phi2));
double t_1 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt(((t_1 * ((cos(phi1) * cos(phi2)) * t_1)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((((1.0 + t_0) - ((cos((phi1 + phi2)) + t_0) * fma(cos((lambda1 - lambda2)), -0.5, 0.5))) / 2.0))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(phi1 - phi2)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_1 * Float64(Float64(cos(phi1) * cos(phi2)) * t_1)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(Float64(Float64(1.0 + t_0) - Float64(Float64(cos(Float64(phi1 + phi2)) + t_0) * fma(cos(Float64(lambda1 - lambda2)), -0.5, 0.5))) / 2.0))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$1 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(N[(1.0 + t$95$0), $MachinePrecision] - N[(N[(N[Cos[N[(phi1 + phi2), $MachinePrecision]], $MachinePrecision] + t$95$0), $MachinePrecision] * N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] * -0.5 + 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(\phi_1 - \phi_2\right)\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_1\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{\frac{\left(1 + t\_0\right) - \left(\cos \left(\phi_1 + \phi_2\right) + t\_0\right) \cdot \mathsf{fma}\left(\cos \left(\lambda_1 - \lambda_2\right), -0.5, 0.5\right)}{2}}}\right)
\end{array}
\end{array}
Initial program 61.4%
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-*.f6462.5
Applied egg-rr62.5%
Applied egg-rr62.1%
Final simplification62.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt (+ (* t_1 (* t_0 t_1)) (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt
(-
(- 1.0 (* t_0 (fma (cos (- lambda1 lambda2)) -0.5 0.5)))
(- 0.5 (* 0.5 (cos (- phi1 phi2)))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt(((t_1 * (t_0 * t_1)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt(((1.0 - (t_0 * fma(cos((lambda1 - lambda2)), -0.5, 0.5))) - (0.5 - (0.5 * cos((phi1 - phi2))))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_1 * Float64(t_0 * t_1)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(Float64(1.0 - Float64(t_0 * fma(cos(Float64(lambda1 - lambda2)), -0.5, 0.5))) - Float64(0.5 - Float64(0.5 * cos(Float64(phi1 - phi2))))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$1 * N[(t$95$0 * t$95$1), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[(t$95$0 * N[(N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision] * -0.5 + 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[(0.5 - N[(0.5 * N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1 \cdot \left(t\_0 \cdot t\_1\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{\left(1 - t\_0 \cdot \mathsf{fma}\left(\cos \left(\lambda_1 - \lambda_2\right), -0.5, 0.5\right)\right) - \left(0.5 - 0.5 \cdot \cos \left(\phi_1 - \phi_2\right)\right)}}\right)
\end{array}
\end{array}
Initial program 61.4%
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-*.f6462.5
Applied egg-rr62.5%
Applied egg-rr61.5%
Final simplification61.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(sqrt
(+
(* t_0 (* (* (cos phi1) (cos phi2)) t_0))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0))))
(t_2 (* R (* 2.0 (atan2 t_1 (sqrt (pow (cos (* 0.5 lambda1)) 2.0)))))))
(if (<= lambda1 -500000000.0)
t_2
(if (<= lambda1 0.0017)
(*
R
(*
2.0
(atan2 t_1 (sqrt (- 1.0 (pow (sin (* -0.5 (- phi2 phi1))) 2.0))))))
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 = sqrt(((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0)));
double t_2 = R * (2.0 * atan2(t_1, sqrt(pow(cos((0.5 * lambda1)), 2.0))));
double tmp;
if (lambda1 <= -500000000.0) {
tmp = t_2;
} else if (lambda1 <= 0.0017) {
tmp = R * (2.0 * atan2(t_1, sqrt((1.0 - pow(sin((-0.5 * (phi2 - phi1))), 2.0)))));
} else {
tmp = t_2;
}
return tmp;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
real(8) :: t_2
real(8) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = sqrt(((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0)))
t_2 = r * (2.0d0 * atan2(t_1, sqrt((cos((0.5d0 * lambda1)) ** 2.0d0))))
if (lambda1 <= (-500000000.0d0)) then
tmp = t_2
else if (lambda1 <= 0.0017d0) then
tmp = r * (2.0d0 * atan2(t_1, sqrt((1.0d0 - (sin(((-0.5d0) * (phi2 - phi1))) ** 2.0d0)))))
else
tmp = t_2
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.sqrt(((t_0 * ((Math.cos(phi1) * Math.cos(phi2)) * t_0)) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0)));
double t_2 = R * (2.0 * Math.atan2(t_1, Math.sqrt(Math.pow(Math.cos((0.5 * lambda1)), 2.0))));
double tmp;
if (lambda1 <= -500000000.0) {
tmp = t_2;
} else if (lambda1 <= 0.0017) {
tmp = R * (2.0 * Math.atan2(t_1, Math.sqrt((1.0 - Math.pow(Math.sin((-0.5 * (phi2 - phi1))), 2.0)))));
} else {
tmp = t_2;
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.sqrt(((t_0 * ((math.cos(phi1) * math.cos(phi2)) * t_0)) + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))) t_2 = R * (2.0 * math.atan2(t_1, math.sqrt(math.pow(math.cos((0.5 * lambda1)), 2.0)))) tmp = 0 if lambda1 <= -500000000.0: tmp = t_2 elif lambda1 <= 0.0017: tmp = R * (2.0 * math.atan2(t_1, math.sqrt((1.0 - math.pow(math.sin((-0.5 * (phi2 - phi1))), 2.0))))) else: tmp = t_2 return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sqrt(Float64(Float64(t_0 * Float64(Float64(cos(phi1) * cos(phi2)) * t_0)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))) t_2 = Float64(R * Float64(2.0 * atan(t_1, sqrt((cos(Float64(0.5 * lambda1)) ^ 2.0))))) tmp = 0.0 if (lambda1 <= -500000000.0) tmp = t_2; elseif (lambda1 <= 0.0017) tmp = Float64(R * Float64(2.0 * atan(t_1, sqrt(Float64(1.0 - (sin(Float64(-0.5 * Float64(phi2 - phi1))) ^ 2.0)))))); else tmp = t_2; end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = sqrt(((t_0 * ((cos(phi1) * cos(phi2)) * t_0)) + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))); t_2 = R * (2.0 * atan2(t_1, sqrt((cos((0.5 * lambda1)) ^ 2.0)))); tmp = 0.0; if (lambda1 <= -500000000.0) tmp = t_2; elseif (lambda1 <= 0.0017) tmp = R * (2.0 * atan2(t_1, sqrt((1.0 - (sin((-0.5 * (phi2 - phi1))) ^ 2.0))))); else tmp = t_2; end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sqrt[N[(N[(t$95$0 * N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(R * N[(2.0 * N[ArcTan[t$95$1 / N[Sqrt[N[Power[N[Cos[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[lambda1, -500000000.0], t$95$2, If[LessEqual[lambda1, 0.0017], N[(R * N[(2.0 * N[ArcTan[t$95$1 / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(-0.5 * N[(phi2 - phi1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$2]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \sqrt{t\_0 \cdot \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}\\
t_2 := R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_1}{\sqrt{{\cos \left(0.5 \cdot \lambda_1\right)}^{2}}}\right)\\
\mathbf{if}\;\lambda_1 \leq -500000000:\\
\;\;\;\;t\_2\\
\mathbf{elif}\;\lambda_1 \leq 0.0017:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_1}{\sqrt{1 - {\sin \left(-0.5 \cdot \left(\phi_2 - \phi_1\right)\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;t\_2\\
\end{array}
\end{array}
if lambda1 < -5e8 or 0.00169999999999999991 < lambda1 Initial program 46.1%
Taylor expanded in lambda2 around 0
lower--.f64N/A
associate-*r*N/A
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
Simplified46.1%
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
lower-cos.f64N/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6442.8
Simplified42.8%
Taylor expanded in phi1 around 0
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower-pow.f64N/A
lower-cos.f64N/A
lower-*.f6431.3
Simplified31.3%
if -5e8 < lambda1 < 0.00169999999999999991Initial program 76.9%
Taylor expanded in lambda2 around 0
lower--.f64N/A
associate-*r*N/A
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
Simplified54.7%
Taylor expanded in lambda1 around 0
sub-negN/A
mul-1-negN/A
distribute-rgt-inN/A
metadata-evalN/A
associate-*l*N/A
*-commutativeN/A
neg-mul-1N/A
*-commutativeN/A
associate-*l*N/A
metadata-evalN/A
distribute-rgt-inN/A
+-commutativeN/A
sub-negN/A
lower--.f64N/A
lower-pow.f64N/A
Simplified54.1%
Final simplification42.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (cos phi1) (cos phi2)))
(t_2
(*
R
(*
2.0
(atan2
(sqrt
(+ (* t_0 (* t_1 t_0)) (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (pow (cos (* 0.5 lambda1)) 2.0)))))))
(if (<= lambda1 -2.65e-59)
t_2
(if (<= lambda1 2.7e-67)
(*
R
(*
2.0
(atan2
(sqrt
(fma
(pow (sin (* -0.5 lambda2)) 2.0)
t_1
(pow (sin (* -0.5 (- phi2 phi1))) 2.0)))
(sqrt (- 1.0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0))))))
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);
double t_2 = R * (2.0 * atan2(sqrt(((t_0 * (t_1 * t_0)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt(pow(cos((0.5 * lambda1)), 2.0))));
double tmp;
if (lambda1 <= -2.65e-59) {
tmp = t_2;
} else if (lambda1 <= 2.7e-67) {
tmp = R * (2.0 * atan2(sqrt(fma(pow(sin((-0.5 * lambda2)), 2.0), t_1, pow(sin((-0.5 * (phi2 - phi1))), 2.0))), sqrt((1.0 - pow(sin((0.5 * (phi1 - phi2))), 2.0)))));
} else {
tmp = t_2;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(cos(phi1) * cos(phi2)) t_2 = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(t_0 * Float64(t_1 * t_0)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt((cos(Float64(0.5 * lambda1)) ^ 2.0))))) tmp = 0.0 if (lambda1 <= -2.65e-59) tmp = t_2; elseif (lambda1 <= 2.7e-67) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma((sin(Float64(-0.5 * lambda2)) ^ 2.0), t_1, (sin(Float64(-0.5 * Float64(phi2 - phi1))) ^ 2.0))), sqrt(Float64(1.0 - (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0)))))); else tmp = 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[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$0 * N[(t$95$1 * t$95$0), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[Power[N[Cos[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[lambda1, -2.65e-59], t$95$2, If[LessEqual[lambda1, 2.7e-67], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * t$95$1 + N[Power[N[Sin[N[(-0.5 * N[(phi2 - phi1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], t$95$2]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
t_2 := R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0 \cdot \left(t\_1 \cdot t\_0\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{{\cos \left(0.5 \cdot \lambda_1\right)}^{2}}}\right)\\
\mathbf{if}\;\lambda_1 \leq -2.65 \cdot 10^{-59}:\\
\;\;\;\;t\_2\\
\mathbf{elif}\;\lambda_1 \leq 2.7 \cdot 10^{-67}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left({\sin \left(-0.5 \cdot \lambda_2\right)}^{2}, t\_1, {\sin \left(-0.5 \cdot \left(\phi_2 - \phi_1\right)\right)}^{2}\right)}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;t\_2\\
\end{array}
\end{array}
if lambda1 < -2.6500000000000002e-59 or 2.70000000000000016e-67 < lambda1 Initial program 50.0%
Taylor expanded in lambda2 around 0
lower--.f64N/A
associate-*r*N/A
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
Simplified46.6%
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
lower-cos.f64N/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6443.1
Simplified43.1%
Taylor expanded in phi1 around 0
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower-pow.f64N/A
lower-cos.f64N/A
lower-*.f6432.0
Simplified32.0%
if -2.6500000000000002e-59 < lambda1 < 2.70000000000000016e-67Initial program 79.5%
Taylor expanded in lambda2 around 0
lower--.f64N/A
associate-*r*N/A
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
Simplified56.4%
Taylor expanded in lambda1 around 0
lower-sqrt.f64N/A
*-commutativeN/A
*-commutativeN/A
associate-*l*N/A
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
Simplified56.4%
Taylor expanded in lambda1 around 0
lower--.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
distribute-lft-inN/A
metadata-evalN/A
distribute-lft-neg-inN/A
distribute-rgt-neg-outN/A
mul-1-negN/A
distribute-rgt-neg-outN/A
distribute-lft-neg-inN/A
metadata-evalN/A
distribute-lft-inN/A
+-commutativeN/A
neg-mul-1N/A
lower-*.f64N/A
neg-mul-1N/A
sub-negN/A
lower--.f6456.4
Simplified56.4%
Final simplification41.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(sqrt
(fma
(pow (sin (* -0.5 lambda2)) 2.0)
(* (cos phi1) (cos phi2))
(pow (sin (* -0.5 (- phi2 phi1))) 2.0)))
(sqrt (- 1.0 (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(fma(pow(sin((-0.5 * lambda2)), 2.0), (cos(phi1) * cos(phi2)), pow(sin((-0.5 * (phi2 - phi1))), 2.0))), sqrt((1.0 - pow(sin((0.5 * (phi1 - phi2))), 2.0)))));
}
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(sqrt(fma((sin(Float64(-0.5 * lambda2)) ^ 2.0), Float64(cos(phi1) * cos(phi2)), (sin(Float64(-0.5 * Float64(phi2 - phi1))) ^ 2.0))), sqrt(Float64(1.0 - (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[(N[Power[N[Sin[N[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * N[(phi2 - phi1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left({\sin \left(-0.5 \cdot \lambda_2\right)}^{2}, \cos \phi_1 \cdot \cos \phi_2, {\sin \left(-0.5 \cdot \left(\phi_2 - \phi_1\right)\right)}^{2}\right)}}{\sqrt{1 - {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}}}\right)
\end{array}
Initial program 61.4%
Taylor expanded in lambda2 around 0
lower--.f64N/A
associate-*r*N/A
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
Simplified50.4%
Taylor expanded in lambda1 around 0
lower-sqrt.f64N/A
*-commutativeN/A
*-commutativeN/A
associate-*l*N/A
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
Simplified34.1%
Taylor expanded in lambda1 around 0
lower--.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
distribute-lft-inN/A
metadata-evalN/A
distribute-lft-neg-inN/A
distribute-rgt-neg-outN/A
mul-1-negN/A
distribute-rgt-neg-outN/A
distribute-lft-neg-inN/A
metadata-evalN/A
distribute-lft-inN/A
+-commutativeN/A
neg-mul-1N/A
lower-*.f64N/A
neg-mul-1N/A
sub-negN/A
lower--.f6434.3
Simplified34.3%
Final simplification34.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(pow (- 0.5 (* 0.5 (cos (* 2.0 (* -0.5 (- phi2 phi1)))))) 0.5)
(sqrt
(+
(fma 0.5 (cos (- phi1 phi2)) 0.5)
(*
(cos phi1)
(* (cos phi2) (- (* 0.5 (cos (- lambda1 lambda2))) 0.5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2(pow((0.5 - (0.5 * cos((2.0 * (-0.5 * (phi2 - phi1)))))), 0.5), sqrt((fma(0.5, cos((phi1 - phi2)), 0.5) + (cos(phi1) * (cos(phi2) * ((0.5 * cos((lambda1 - lambda2))) - 0.5)))))));
}
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan((Float64(0.5 - Float64(0.5 * cos(Float64(2.0 * Float64(-0.5 * Float64(phi2 - phi1)))))) ^ 0.5), sqrt(Float64(fma(0.5, cos(Float64(phi1 - phi2)), 0.5) + Float64(cos(phi1) * Float64(cos(phi2) * Float64(Float64(0.5 * cos(Float64(lambda1 - lambda2))) - 0.5)))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[Power[N[(0.5 - N[(0.5 * N[Cos[N[(2.0 * N[(-0.5 * N[(phi2 - phi1), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 0.5], $MachinePrecision] / N[Sqrt[N[(N[(0.5 * N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] + 0.5), $MachinePrecision] + N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{{\left(0.5 - 0.5 \cdot \cos \left(2 \cdot \left(-0.5 \cdot \left(\phi_2 - \phi_1\right)\right)\right)\right)}^{0.5}}{\sqrt{\mathsf{fma}\left(0.5, \cos \left(\phi_1 - \phi_2\right), 0.5\right) + \cos \phi_1 \cdot \left(\cos \phi_2 \cdot \left(0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right) - 0.5\right)\right)}}\right)
\end{array}
Initial program 61.4%
Taylor expanded in lambda1 around 0
lower-sin.f64N/A
lower-*.f6443.9
Simplified43.9%
Taylor expanded in lambda2 around 0
sub-negN/A
distribute-rgt-inN/A
metadata-evalN/A
associate-*l*N/A
*-commutativeN/A
neg-mul-1N/A
*-commutativeN/A
associate-*l*N/A
metadata-evalN/A
distribute-rgt-inN/A
+-commutativeN/A
lower-sin.f64N/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f6414.6
Simplified14.6%
Applied egg-rr14.6%
lift--.f64N/A
lift-*.f64N/A
lift-sin.f6414.6
unpow1N/A
metadata-evalN/A
pow-prod-upN/A
pow-prod-downN/A
unpow2N/A
lift-pow.f64N/A
lower-pow.f6430.9
lift-pow.f64N/A
unpow2N/A
lift-sin.f64N/A
lift-sin.f64N/A
sqr-sin-aN/A
lower--.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
lower-*.f6427.2
Applied egg-rr27.2%
Final simplification27.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (- phi1 phi2))))
(*
R
(*
2.0
(atan2
(sin (* -0.5 (- phi2 phi1)))
(sqrt
(/
(+
(+ 1.0 t_0)
(*
(+ (cos (+ phi1 phi2)) t_0)
(- (* 0.5 (cos (- lambda1 lambda2))) 0.5)))
2.0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((phi1 - phi2));
return R * (2.0 * atan2(sin((-0.5 * (phi2 - phi1))), sqrt((((1.0 + t_0) + ((cos((phi1 + phi2)) + t_0) * ((0.5 * cos((lambda1 - lambda2))) - 0.5))) / 2.0))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = cos((phi1 - phi2))
code = r * (2.0d0 * atan2(sin(((-0.5d0) * (phi2 - phi1))), sqrt((((1.0d0 + t_0) + ((cos((phi1 + phi2)) + t_0) * ((0.5d0 * cos((lambda1 - lambda2))) - 0.5d0))) / 2.0d0))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.cos((phi1 - phi2));
return R * (2.0 * Math.atan2(Math.sin((-0.5 * (phi2 - phi1))), Math.sqrt((((1.0 + t_0) + ((Math.cos((phi1 + phi2)) + t_0) * ((0.5 * Math.cos((lambda1 - lambda2))) - 0.5))) / 2.0))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos((phi1 - phi2)) return R * (2.0 * math.atan2(math.sin((-0.5 * (phi2 - phi1))), math.sqrt((((1.0 + t_0) + ((math.cos((phi1 + phi2)) + t_0) * ((0.5 * math.cos((lambda1 - lambda2))) - 0.5))) / 2.0))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(phi1 - phi2)) return Float64(R * Float64(2.0 * atan(sin(Float64(-0.5 * Float64(phi2 - phi1))), sqrt(Float64(Float64(Float64(1.0 + t_0) + Float64(Float64(cos(Float64(phi1 + phi2)) + t_0) * Float64(Float64(0.5 * cos(Float64(lambda1 - lambda2))) - 0.5))) / 2.0))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos((phi1 - phi2)); tmp = R * (2.0 * atan2(sin((-0.5 * (phi2 - phi1))), sqrt((((1.0 + t_0) + ((cos((phi1 + phi2)) + t_0) * ((0.5 * cos((lambda1 - lambda2))) - 0.5))) / 2.0)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sin[N[(-0.5 * N[(phi2 - phi1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(N[(1.0 + t$95$0), $MachinePrecision] + N[(N[(N[Cos[N[(phi1 + phi2), $MachinePrecision]], $MachinePrecision] + t$95$0), $MachinePrecision] * N[(N[(0.5 * N[Cos[N[(lambda1 - lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(\phi_1 - \phi_2\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sin \left(-0.5 \cdot \left(\phi_2 - \phi_1\right)\right)}{\sqrt{\frac{\left(1 + t\_0\right) + \left(\cos \left(\phi_1 + \phi_2\right) + t\_0\right) \cdot \left(0.5 \cdot \cos \left(\lambda_1 - \lambda_2\right) - 0.5\right)}{2}}}\right)
\end{array}
\end{array}
Initial program 61.4%
Taylor expanded in lambda1 around 0
lower-sin.f64N/A
lower-*.f6443.9
Simplified43.9%
Taylor expanded in lambda2 around 0
sub-negN/A
distribute-rgt-inN/A
metadata-evalN/A
associate-*l*N/A
*-commutativeN/A
neg-mul-1N/A
*-commutativeN/A
associate-*l*N/A
metadata-evalN/A
distribute-rgt-inN/A
+-commutativeN/A
lower-sin.f64N/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f6414.6
Simplified14.6%
Applied egg-rr15.1%
Final simplification15.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(sin (* -0.5 (- phi2 phi1)))
(sqrt
(-
(fma 0.5 (cos (- phi1 phi2)) 0.5)
(* (cos phi1) (* (cos phi2) (fma (cos lambda2) -0.5 0.5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2(sin((-0.5 * (phi2 - phi1))), sqrt((fma(0.5, cos((phi1 - phi2)), 0.5) - (cos(phi1) * (cos(phi2) * fma(cos(lambda2), -0.5, 0.5)))))));
}
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(sin(Float64(-0.5 * Float64(phi2 - phi1))), sqrt(Float64(fma(0.5, cos(Float64(phi1 - phi2)), 0.5) - Float64(cos(phi1) * Float64(cos(phi2) * fma(cos(lambda2), -0.5, 0.5)))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[Sin[N[(-0.5 * N[(phi2 - phi1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(0.5 * N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] + 0.5), $MachinePrecision] - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(N[Cos[lambda2], $MachinePrecision] * -0.5 + 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sin \left(-0.5 \cdot \left(\phi_2 - \phi_1\right)\right)}{\sqrt{\mathsf{fma}\left(0.5, \cos \left(\phi_1 - \phi_2\right), 0.5\right) - \cos \phi_1 \cdot \left(\cos \phi_2 \cdot \mathsf{fma}\left(\cos \lambda_2, -0.5, 0.5\right)\right)}}\right)
\end{array}
Initial program 61.4%
Taylor expanded in lambda1 around 0
lower-sin.f64N/A
lower-*.f6443.9
Simplified43.9%
Taylor expanded in lambda2 around 0
sub-negN/A
distribute-rgt-inN/A
metadata-evalN/A
associate-*l*N/A
*-commutativeN/A
neg-mul-1N/A
*-commutativeN/A
associate-*l*N/A
metadata-evalN/A
distribute-rgt-inN/A
+-commutativeN/A
lower-sin.f64N/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f6414.6
Simplified14.6%
Applied egg-rr14.6%
Taylor expanded in lambda1 around 0
cancel-sign-sub-invN/A
metadata-evalN/A
+-commutativeN/A
*-commutativeN/A
lower-fma.f64N/A
cos-negN/A
lower-cos.f6414.8
Simplified14.8%
Final simplification14.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(sin (* -0.5 (- phi2 phi1)))
(sqrt
(-
(fma 0.5 (cos (- phi1 phi2)) 0.5)
(* (cos phi1) (* (cos phi2) (fma -0.5 (cos lambda1) 0.5)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2(sin((-0.5 * (phi2 - phi1))), sqrt((fma(0.5, cos((phi1 - phi2)), 0.5) - (cos(phi1) * (cos(phi2) * fma(-0.5, cos(lambda1), 0.5)))))));
}
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(sin(Float64(-0.5 * Float64(phi2 - phi1))), sqrt(Float64(fma(0.5, cos(Float64(phi1 - phi2)), 0.5) - Float64(cos(phi1) * Float64(cos(phi2) * fma(-0.5, cos(lambda1), 0.5)))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[Sin[N[(-0.5 * N[(phi2 - phi1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(0.5 * N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] + 0.5), $MachinePrecision] - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[(-0.5 * N[Cos[lambda1], $MachinePrecision] + 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sin \left(-0.5 \cdot \left(\phi_2 - \phi_1\right)\right)}{\sqrt{\mathsf{fma}\left(0.5, \cos \left(\phi_1 - \phi_2\right), 0.5\right) - \cos \phi_1 \cdot \left(\cos \phi_2 \cdot \mathsf{fma}\left(-0.5, \cos \lambda_1, 0.5\right)\right)}}\right)
\end{array}
Initial program 61.4%
Taylor expanded in lambda1 around 0
lower-sin.f64N/A
lower-*.f6443.9
Simplified43.9%
Taylor expanded in lambda2 around 0
sub-negN/A
distribute-rgt-inN/A
metadata-evalN/A
associate-*l*N/A
*-commutativeN/A
neg-mul-1N/A
*-commutativeN/A
associate-*l*N/A
metadata-evalN/A
distribute-rgt-inN/A
+-commutativeN/A
lower-sin.f64N/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f6414.6
Simplified14.6%
Applied egg-rr14.6%
Taylor expanded in lambda2 around 0
cancel-sign-sub-invN/A
metadata-evalN/A
+-commutativeN/A
lower-fma.f64N/A
lower-cos.f6414.6
Simplified14.6%
Final simplification14.6%
herbie shell --seed 2024219
(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))))))))))