
(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 (* phi2 0.5)))
(t_2 (sin (/ (- lambda1 lambda2) 2.0)))
(t_3 (* (cos phi1) (cos phi2)))
(t_4 (sin (* phi1 0.5))))
(*
(*
(atan2
(sqrt
(fma
(pow
(-
(* (cos (* lambda2 0.5)) (sin (* 0.5 lambda1)))
(* (sin (* lambda2 0.5)) (cos (* 0.5 lambda1))))
2.0)
t_3
(pow (fma (- t_0) t_1 (* (cos (* -0.5 phi2)) t_4)) 2.0)))
(sqrt
(-
1.0
(+
(* (* t_2 t_3) t_2)
(pow (- (* t_4 (cos (* phi2 0.5))) (* t_1 t_0)) 2.0)))))
2.0)
R)))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((phi1 * 0.5));
double t_1 = sin((phi2 * 0.5));
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double t_3 = cos(phi1) * cos(phi2);
double t_4 = sin((phi1 * 0.5));
return (atan2(sqrt(fma(pow(((cos((lambda2 * 0.5)) * sin((0.5 * lambda1))) - (sin((lambda2 * 0.5)) * cos((0.5 * lambda1)))), 2.0), t_3, pow(fma(-t_0, t_1, (cos((-0.5 * phi2)) * t_4)), 2.0))), sqrt((1.0 - (((t_2 * t_3) * t_2) + pow(((t_4 * cos((phi2 * 0.5))) - (t_1 * t_0)), 2.0))))) * 2.0) * R;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(phi1 * 0.5)) t_1 = sin(Float64(phi2 * 0.5)) t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_3 = Float64(cos(phi1) * cos(phi2)) t_4 = sin(Float64(phi1 * 0.5)) return Float64(Float64(atan(sqrt(fma((Float64(Float64(cos(Float64(lambda2 * 0.5)) * sin(Float64(0.5 * lambda1))) - Float64(sin(Float64(lambda2 * 0.5)) * cos(Float64(0.5 * lambda1)))) ^ 2.0), t_3, (fma(Float64(-t_0), t_1, Float64(cos(Float64(-0.5 * phi2)) * t_4)) ^ 2.0))), sqrt(Float64(1.0 - Float64(Float64(Float64(t_2 * t_3) * t_2) + (Float64(Float64(t_4 * cos(Float64(phi2 * 0.5))) - Float64(t_1 * t_0)) ^ 2.0))))) * 2.0) * R) 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[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, N[(N[(N[ArcTan[N[Sqrt[N[(N[Power[N[(N[(N[Cos[N[(lambda2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Sin[N[(lambda2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] * t$95$3 + N[Power[N[((-t$95$0) * t$95$1 + N[(N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$4), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[(t$95$2 * t$95$3), $MachinePrecision] * t$95$2), $MachinePrecision] + N[Power[N[(N[(t$95$4 * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(t$95$1 * t$95$0), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_1 := \sin \left(\phi_2 \cdot 0.5\right)\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_3 := \cos \phi_1 \cdot \cos \phi_2\\
t_4 := \sin \left(\phi_1 \cdot 0.5\right)\\
\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left({\left(\cos \left(\lambda_2 \cdot 0.5\right) \cdot \sin \left(0.5 \cdot \lambda_1\right) - \sin \left(\lambda_2 \cdot 0.5\right) \cdot \cos \left(0.5 \cdot \lambda_1\right)\right)}^{2}, t\_3, {\left(\mathsf{fma}\left(-t\_0, t\_1, \cos \left(-0.5 \cdot \phi_2\right) \cdot t\_4\right)\right)}^{2}\right)}}{\sqrt{1 - \left(\left(t\_2 \cdot t\_3\right) \cdot t\_2 + {\left(t\_4 \cdot \cos \left(\phi_2 \cdot 0.5\right) - t\_1 \cdot t\_0\right)}^{2}\right)}} \cdot 2\right) \cdot R
\end{array}
\end{array}
Initial program 67.1%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f6467.8
Applied rewrites67.8%
lift-sin.f64N/A
lift-/.f64N/A
clear-numN/A
associate-/r/N/A
metadata-evalN/A
lift--.f64N/A
distribute-rgt-out--N/A
lift-*.f64N/A
lift-*.f64N/A
sin-diffN/A
lift-sin.f64N/A
lift-cos.f64N/A
lift-*.f64N/A
lift-cos.f64N/A
lift-sin.f64N/A
lift-*.f64N/A
lift--.f6481.0
Applied rewrites81.0%
Applied rewrites81.0%
lift-sin.f64N/A
lift-*.f64N/A
metadata-evalN/A
div-invN/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lift-*.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
lift-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
Applied rewrites81.5%
Final simplification81.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (cos (* phi1 0.5)))
(t_2 (sin (* phi2 0.5)))
(t_3 (* (cos phi1) (cos phi2)))
(t_4 (sin (* phi1 0.5))))
(*
(*
(atan2
(sqrt
(fma
(pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)
t_3
(pow (fma (- t_1) t_2 (* (cos (* -0.5 phi2)) t_4)) 2.0)))
(sqrt
(-
1.0
(+
(* (* t_0 t_3) t_0)
(pow (- (* t_4 (cos (* phi2 0.5))) (* t_2 t_1)) 2.0)))))
2.0)
R)))
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 * 0.5));
double t_2 = sin((phi2 * 0.5));
double t_3 = cos(phi1) * cos(phi2);
double t_4 = sin((phi1 * 0.5));
return (atan2(sqrt(fma(pow(sin(((lambda1 - lambda2) * 0.5)), 2.0), t_3, pow(fma(-t_1, t_2, (cos((-0.5 * phi2)) * t_4)), 2.0))), sqrt((1.0 - (((t_0 * t_3) * t_0) + pow(((t_4 * cos((phi2 * 0.5))) - (t_2 * t_1)), 2.0))))) * 2.0) * R;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = cos(Float64(phi1 * 0.5)) t_2 = sin(Float64(phi2 * 0.5)) t_3 = Float64(cos(phi1) * cos(phi2)) t_4 = sin(Float64(phi1 * 0.5)) return Float64(Float64(atan(sqrt(fma((sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0), t_3, (fma(Float64(-t_1), t_2, Float64(cos(Float64(-0.5 * phi2)) * t_4)) ^ 2.0))), sqrt(Float64(1.0 - Float64(Float64(Float64(t_0 * t_3) * t_0) + (Float64(Float64(t_4 * cos(Float64(phi2 * 0.5))) - Float64(t_2 * t_1)) ^ 2.0))))) * 2.0) * R) 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[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, N[(N[(N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * t$95$3 + N[Power[N[((-t$95$1) * t$95$2 + N[(N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$4), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[(t$95$0 * t$95$3), $MachinePrecision] * t$95$0), $MachinePrecision] + N[Power[N[(N[(t$95$4 * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(t$95$2 * t$95$1), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_2 := \sin \left(\phi_2 \cdot 0.5\right)\\
t_3 := \cos \phi_1 \cdot \cos \phi_2\\
t_4 := \sin \left(\phi_1 \cdot 0.5\right)\\
\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left({\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}, t\_3, {\left(\mathsf{fma}\left(-t\_1, t\_2, \cos \left(-0.5 \cdot \phi_2\right) \cdot t\_4\right)\right)}^{2}\right)}}{\sqrt{1 - \left(\left(t\_0 \cdot t\_3\right) \cdot t\_0 + {\left(t\_4 \cdot \cos \left(\phi_2 \cdot 0.5\right) - t\_2 \cdot t\_1\right)}^{2}\right)}} \cdot 2\right) \cdot R
\end{array}
\end{array}
Initial program 67.1%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f6467.8
Applied rewrites67.8%
lift-sin.f64N/A
lift-/.f64N/A
clear-numN/A
associate-/r/N/A
metadata-evalN/A
lift--.f64N/A
distribute-rgt-out--N/A
lift-*.f64N/A
lift-*.f64N/A
sin-diffN/A
lift-sin.f64N/A
lift-cos.f64N/A
lift-*.f64N/A
lift-cos.f64N/A
lift-sin.f64N/A
lift-*.f64N/A
lift--.f6481.0
Applied rewrites81.0%
Applied rewrites81.0%
Final simplification81.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* phi1 0.5)))
(t_1 (cos (* phi1 0.5)))
(t_2 (sin (* phi2 0.5)))
(t_3
(sqrt
(fma
(pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)
(* (cos phi1) (cos phi2))
(pow (fma (- t_1) t_2 (* (cos (* -0.5 phi2)) t_0)) 2.0))))
(t_4 (pow (fma (- t_2) t_1 (* t_0 (cos (* phi2 0.5)))) 2.0))
(t_5
(*
(*
(atan2
t_3
(sqrt
(-
1.0
(fma
(* (pow (sin (* 0.5 lambda1)) 2.0) (cos phi2))
(cos phi1)
t_4))))
2.0)
R)))
(if (<= lambda1 -1.15e-5)
t_5
(if (<= lambda1 5.6e-6)
(*
(*
(atan2
t_3
(sqrt
(-
1.0
(fma
(* (pow (sin (* -0.5 lambda2)) 2.0) (cos phi2))
(cos phi1)
t_4))))
2.0)
R)
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 = sin((phi2 * 0.5));
double t_3 = sqrt(fma(pow(sin(((lambda1 - lambda2) * 0.5)), 2.0), (cos(phi1) * cos(phi2)), pow(fma(-t_1, t_2, (cos((-0.5 * phi2)) * t_0)), 2.0)));
double t_4 = pow(fma(-t_2, t_1, (t_0 * cos((phi2 * 0.5)))), 2.0);
double t_5 = (atan2(t_3, sqrt((1.0 - fma((pow(sin((0.5 * lambda1)), 2.0) * cos(phi2)), cos(phi1), t_4)))) * 2.0) * R;
double tmp;
if (lambda1 <= -1.15e-5) {
tmp = t_5;
} else if (lambda1 <= 5.6e-6) {
tmp = (atan2(t_3, sqrt((1.0 - fma((pow(sin((-0.5 * lambda2)), 2.0) * cos(phi2)), cos(phi1), t_4)))) * 2.0) * R;
} 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 = sin(Float64(phi2 * 0.5)) t_3 = sqrt(fma((sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0), Float64(cos(phi1) * cos(phi2)), (fma(Float64(-t_1), t_2, Float64(cos(Float64(-0.5 * phi2)) * t_0)) ^ 2.0))) t_4 = fma(Float64(-t_2), t_1, Float64(t_0 * cos(Float64(phi2 * 0.5)))) ^ 2.0 t_5 = Float64(Float64(atan(t_3, sqrt(Float64(1.0 - fma(Float64((sin(Float64(0.5 * lambda1)) ^ 2.0) * cos(phi2)), cos(phi1), t_4)))) * 2.0) * R) tmp = 0.0 if (lambda1 <= -1.15e-5) tmp = t_5; elseif (lambda1 <= 5.6e-6) tmp = Float64(Float64(atan(t_3, sqrt(Float64(1.0 - fma(Float64((sin(Float64(-0.5 * lambda2)) ^ 2.0) * cos(phi2)), cos(phi1), t_4)))) * 2.0) * R); 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[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Sqrt[N[(N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] + N[Power[N[((-t$95$1) * t$95$2 + N[(N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[Power[N[((-t$95$2) * t$95$1 + N[(t$95$0 * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$5 = N[(N[(N[ArcTan[t$95$3 / N[Sqrt[N[(1.0 - N[(N[(N[Power[N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[Cos[phi1], $MachinePrecision] + t$95$4), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]}, If[LessEqual[lambda1, -1.15e-5], t$95$5, If[LessEqual[lambda1, 5.6e-6], N[(N[(N[ArcTan[t$95$3 / N[Sqrt[N[(1.0 - N[(N[(N[Power[N[Sin[N[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[Cos[phi1], $MachinePrecision] + t$95$4), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $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 := \sin \left(\phi_2 \cdot 0.5\right)\\
t_3 := \sqrt{\mathsf{fma}\left({\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}, \cos \phi_1 \cdot \cos \phi_2, {\left(\mathsf{fma}\left(-t\_1, t\_2, \cos \left(-0.5 \cdot \phi_2\right) \cdot t\_0\right)\right)}^{2}\right)}\\
t_4 := {\left(\mathsf{fma}\left(-t\_2, t\_1, t\_0 \cdot \cos \left(\phi_2 \cdot 0.5\right)\right)\right)}^{2}\\
t_5 := \left(\tan^{-1}_* \frac{t\_3}{\sqrt{1 - \mathsf{fma}\left({\sin \left(0.5 \cdot \lambda_1\right)}^{2} \cdot \cos \phi_2, \cos \phi_1, t\_4\right)}} \cdot 2\right) \cdot R\\
\mathbf{if}\;\lambda_1 \leq -1.15 \cdot 10^{-5}:\\
\;\;\;\;t\_5\\
\mathbf{elif}\;\lambda_1 \leq 5.6 \cdot 10^{-6}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{t\_3}{\sqrt{1 - \mathsf{fma}\left({\sin \left(-0.5 \cdot \lambda_2\right)}^{2} \cdot \cos \phi_2, \cos \phi_1, t\_4\right)}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;t\_5\\
\end{array}
\end{array}
if lambda1 < -1.15e-5 or 5.59999999999999975e-6 < lambda1 Initial program 54.2%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f6455.0
Applied rewrites55.0%
lift-sin.f64N/A
lift-/.f64N/A
clear-numN/A
associate-/r/N/A
metadata-evalN/A
lift--.f64N/A
distribute-rgt-out--N/A
lift-*.f64N/A
lift-*.f64N/A
sin-diffN/A
lift-sin.f64N/A
lift-cos.f64N/A
lift-*.f64N/A
lift-cos.f64N/A
lift-sin.f64N/A
lift-*.f64N/A
lift--.f6464.0
Applied rewrites64.0%
Applied rewrites64.0%
Taylor expanded in lambda2 around 0
*-commutativeN/A
lower-fma.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
Applied rewrites63.9%
if -1.15e-5 < lambda1 < 5.59999999999999975e-6Initial program 80.3%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f6480.8
Applied rewrites80.8%
lift-sin.f64N/A
lift-/.f64N/A
clear-numN/A
associate-/r/N/A
metadata-evalN/A
lift--.f64N/A
distribute-rgt-out--N/A
lift-*.f64N/A
lift-*.f64N/A
sin-diffN/A
lift-sin.f64N/A
lift-cos.f64N/A
lift-*.f64N/A
lift-cos.f64N/A
lift-sin.f64N/A
lift-*.f64N/A
lift--.f6498.2
Applied rewrites98.2%
Applied rewrites98.2%
Taylor expanded in lambda1 around 0
*-commutativeN/A
lower-fma.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
Applied rewrites98.2%
Final simplification80.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (* (- 0.5) phi2))
(t_2 (cos (* phi1 0.5)))
(t_3 (sin (/ (- lambda1 lambda2) 2.0)))
(t_4 (* (* t_3 t_0) t_3))
(t_5 (sin (* phi1 0.5)))
(t_6 (* t_5 (cos (* phi2 0.5))))
(t_7 (sin (* phi2 0.5))))
(if (<= lambda2 -2.05e+22)
(*
(*
(atan2
(sqrt (+ (pow (fma t_5 (cos t_1) (* (sin t_1) t_2)) 2.0) t_4))
(sqrt
(-
1.0
(fma
t_0
(pow (sin (* -0.5 lambda2)) 2.0)
(pow (sin (* (- phi1 phi2) 0.5)) 2.0)))))
2.0)
R)
(if (<= lambda2 3.9e-19)
(*
(*
(atan2
(sqrt
(fma
(pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)
t_0
(pow (fma (- t_2) t_7 (* (cos (* -0.5 phi2)) t_5)) 2.0)))
(sqrt
(-
1.0
(fma
(* (pow (sin (* 0.5 lambda1)) 2.0) (cos phi2))
(cos phi1)
(pow (fma (- t_7) t_2 t_6) 2.0)))))
2.0)
R)
(*
(*
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) t_4))
(sqrt (- 1.0 (+ t_4 (pow (- t_6 (* t_7 t_2)) 2.0)))))
2.0)
R)))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = -0.5 * phi2;
double t_2 = cos((phi1 * 0.5));
double t_3 = sin(((lambda1 - lambda2) / 2.0));
double t_4 = (t_3 * t_0) * t_3;
double t_5 = sin((phi1 * 0.5));
double t_6 = t_5 * cos((phi2 * 0.5));
double t_7 = sin((phi2 * 0.5));
double tmp;
if (lambda2 <= -2.05e+22) {
tmp = (atan2(sqrt((pow(fma(t_5, cos(t_1), (sin(t_1) * t_2)), 2.0) + t_4)), sqrt((1.0 - fma(t_0, pow(sin((-0.5 * lambda2)), 2.0), pow(sin(((phi1 - phi2) * 0.5)), 2.0))))) * 2.0) * R;
} else if (lambda2 <= 3.9e-19) {
tmp = (atan2(sqrt(fma(pow(sin(((lambda1 - lambda2) * 0.5)), 2.0), t_0, pow(fma(-t_2, t_7, (cos((-0.5 * phi2)) * t_5)), 2.0))), sqrt((1.0 - fma((pow(sin((0.5 * lambda1)), 2.0) * cos(phi2)), cos(phi1), pow(fma(-t_7, t_2, t_6), 2.0))))) * 2.0) * R;
} else {
tmp = (atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + t_4)), sqrt((1.0 - (t_4 + pow((t_6 - (t_7 * t_2)), 2.0))))) * 2.0) * R;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = Float64(Float64(-0.5) * phi2) t_2 = cos(Float64(phi1 * 0.5)) t_3 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_4 = Float64(Float64(t_3 * t_0) * t_3) t_5 = sin(Float64(phi1 * 0.5)) t_6 = Float64(t_5 * cos(Float64(phi2 * 0.5))) t_7 = sin(Float64(phi2 * 0.5)) tmp = 0.0 if (lambda2 <= -2.05e+22) tmp = Float64(Float64(atan(sqrt(Float64((fma(t_5, cos(t_1), Float64(sin(t_1) * t_2)) ^ 2.0) + t_4)), sqrt(Float64(1.0 - fma(t_0, (sin(Float64(-0.5 * lambda2)) ^ 2.0), (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0))))) * 2.0) * R); elseif (lambda2 <= 3.9e-19) tmp = Float64(Float64(atan(sqrt(fma((sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0), t_0, (fma(Float64(-t_2), t_7, Float64(cos(Float64(-0.5 * phi2)) * t_5)) ^ 2.0))), sqrt(Float64(1.0 - fma(Float64((sin(Float64(0.5 * lambda1)) ^ 2.0) * cos(phi2)), cos(phi1), (fma(Float64(-t_7), t_2, t_6) ^ 2.0))))) * 2.0) * R); else tmp = Float64(Float64(atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + t_4)), sqrt(Float64(1.0 - Float64(t_4 + (Float64(t_6 - Float64(t_7 * t_2)) ^ 2.0))))) * 2.0) * R); 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) * phi2), $MachinePrecision]}, Block[{t$95$2 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[(N[(t$95$3 * t$95$0), $MachinePrecision] * t$95$3), $MachinePrecision]}, Block[{t$95$5 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$6 = N[(t$95$5 * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$7 = N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[lambda2, -2.05e+22], N[(N[(N[ArcTan[N[Sqrt[N[(N[Power[N[(t$95$5 * N[Cos[t$95$1], $MachinePrecision] + N[(N[Sin[t$95$1], $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$4), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 * N[Power[N[Sin[N[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], If[LessEqual[lambda2, 3.9e-19], N[(N[(N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * t$95$0 + N[Power[N[((-t$95$2) * t$95$7 + N[(N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$5), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Power[N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[Cos[phi1], $MachinePrecision] + N[Power[N[((-t$95$7) * t$95$2 + t$95$6), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], N[(N[(N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$4), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$4 + N[Power[N[(t$95$6 - N[(t$95$7 * t$95$2), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]]]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := \left(-0.5\right) \cdot \phi_2\\
t_2 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_3 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_4 := \left(t\_3 \cdot t\_0\right) \cdot t\_3\\
t_5 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_6 := t\_5 \cdot \cos \left(\phi_2 \cdot 0.5\right)\\
t_7 := \sin \left(\phi_2 \cdot 0.5\right)\\
\mathbf{if}\;\lambda_2 \leq -2.05 \cdot 10^{+22}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(t\_5, \cos t\_1, \sin t\_1 \cdot t\_2\right)\right)}^{2} + t\_4}}{\sqrt{1 - \mathsf{fma}\left(t\_0, {\sin \left(-0.5 \cdot \lambda_2\right)}^{2}, {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\right)}} \cdot 2\right) \cdot R\\
\mathbf{elif}\;\lambda_2 \leq 3.9 \cdot 10^{-19}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left({\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}, t\_0, {\left(\mathsf{fma}\left(-t\_2, t\_7, \cos \left(-0.5 \cdot \phi_2\right) \cdot t\_5\right)\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left({\sin \left(0.5 \cdot \lambda_1\right)}^{2} \cdot \cos \phi_2, \cos \phi_1, {\left(\mathsf{fma}\left(-t\_7, t\_2, t\_6\right)\right)}^{2}\right)}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_4}}{\sqrt{1 - \left(t\_4 + {\left(t\_6 - t\_7 \cdot t\_2\right)}^{2}\right)}} \cdot 2\right) \cdot R\\
\end{array}
\end{array}
if lambda2 < -2.0499999999999999e22Initial program 49.8%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sub-negN/A
sin-sumN/A
lower-fma.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-neg.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
lower-neg.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f6450.5
Applied rewrites50.5%
Taylor expanded in lambda1 around 0
associate-*r*N/A
lower-fma.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f6450.7
Applied rewrites50.7%
if -2.0499999999999999e22 < lambda2 < 3.89999999999999995e-19Initial program 78.1%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f6478.7
Applied rewrites78.7%
lift-sin.f64N/A
lift-/.f64N/A
clear-numN/A
associate-/r/N/A
metadata-evalN/A
lift--.f64N/A
distribute-rgt-out--N/A
lift-*.f64N/A
lift-*.f64N/A
sin-diffN/A
lift-sin.f64N/A
lift-cos.f64N/A
lift-*.f64N/A
lift-cos.f64N/A
lift-sin.f64N/A
lift-*.f64N/A
lift--.f6496.1
Applied rewrites96.1%
Applied rewrites96.1%
Taylor expanded in lambda2 around 0
*-commutativeN/A
lower-fma.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
Applied rewrites95.5%
if 3.89999999999999995e-19 < lambda2 Initial program 57.3%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f6458.0
Applied rewrites58.0%
Final simplification77.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0) (cos phi1)))
(t_1 (sin (* phi1 0.5)))
(t_2 (* (sin (* phi2 0.5)) (cos (* phi1 0.5)))))
(*
(*
(atan2
(sqrt (fma t_0 (cos phi2) (pow (- (* (cos (* -0.5 phi2)) t_1) t_2) 2.0)))
(sqrt
(-
1.0
(fma t_0 (cos phi2) (pow (- (* t_1 (cos (* phi2 0.5))) t_2) 2.0)))))
2.0)
R)))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0) * cos(phi1);
double t_1 = sin((phi1 * 0.5));
double t_2 = sin((phi2 * 0.5)) * cos((phi1 * 0.5));
return (atan2(sqrt(fma(t_0, cos(phi2), pow(((cos((-0.5 * phi2)) * t_1) - t_2), 2.0))), sqrt((1.0 - fma(t_0, cos(phi2), pow(((t_1 * cos((phi2 * 0.5))) - t_2), 2.0))))) * 2.0) * R;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64((sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0) * cos(phi1)) t_1 = sin(Float64(phi1 * 0.5)) t_2 = Float64(sin(Float64(phi2 * 0.5)) * cos(Float64(phi1 * 0.5))) return Float64(Float64(atan(sqrt(fma(t_0, cos(phi2), (Float64(Float64(cos(Float64(-0.5 * phi2)) * t_1) - t_2) ^ 2.0))), sqrt(Float64(1.0 - fma(t_0, cos(phi2), (Float64(Float64(t_1 * cos(Float64(phi2 * 0.5))) - t_2) ^ 2.0))))) * 2.0) * R) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]}, N[(N[(N[ArcTan[N[Sqrt[N[(t$95$0 * N[Cos[phi2], $MachinePrecision] + N[Power[N[(N[(N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$1), $MachinePrecision] - t$95$2), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 * N[Cos[phi2], $MachinePrecision] + N[Power[N[(N[(t$95$1 * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - t$95$2), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2} \cdot \cos \phi_1\\
t_1 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_2 := \sin \left(\phi_2 \cdot 0.5\right) \cdot \cos \left(\phi_1 \cdot 0.5\right)\\
\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \cos \phi_2, {\left(\cos \left(-0.5 \cdot \phi_2\right) \cdot t\_1 - t\_2\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left(t\_0, \cos \phi_2, {\left(t\_1 \cdot \cos \left(\phi_2 \cdot 0.5\right) - t\_2\right)}^{2}\right)}} \cdot 2\right) \cdot R
\end{array}
\end{array}
Initial program 67.1%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f6467.8
Applied rewrites67.8%
lift-sin.f64N/A
lift-/.f64N/A
clear-numN/A
associate-/r/N/A
metadata-evalN/A
lift--.f64N/A
distribute-rgt-out--N/A
lift-*.f64N/A
lift-*.f64N/A
sin-diffN/A
lift-sin.f64N/A
lift-cos.f64N/A
lift-*.f64N/A
lift-cos.f64N/A
lift-sin.f64N/A
lift-*.f64N/A
lift--.f6481.0
Applied rewrites81.0%
Taylor expanded in lambda1 around 0
Applied rewrites80.9%
Final simplification80.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (* t_0 (* (cos phi1) (cos phi2))) t_0)))
(*
(*
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) t_1))
(sqrt
(-
1.0
(+
t_1
(pow
(-
(* (sin (* phi1 0.5)) (cos (* phi2 0.5)))
(* (sin (* phi2 0.5)) (cos (* phi1 0.5))))
2.0)))))
2.0)
R)))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = (t_0 * (cos(phi1) * cos(phi2))) * t_0;
return (atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), sqrt((1.0 - (t_1 + pow(((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (sin((phi2 * 0.5)) * cos((phi1 * 0.5)))), 2.0))))) * 2.0) * R;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (t_0 * (cos(phi1) * cos(phi2))) * t_0
code = (atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + t_1)), sqrt((1.0d0 - (t_1 + (((sin((phi1 * 0.5d0)) * cos((phi2 * 0.5d0))) - (sin((phi2 * 0.5d0)) * cos((phi1 * 0.5d0)))) ** 2.0d0))))) * 2.0d0) * r
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = (t_0 * (Math.cos(phi1) * Math.cos(phi2))) * t_0;
return (Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), Math.sqrt((1.0 - (t_1 + Math.pow(((Math.sin((phi1 * 0.5)) * Math.cos((phi2 * 0.5))) - (Math.sin((phi2 * 0.5)) * Math.cos((phi1 * 0.5)))), 2.0))))) * 2.0) * R;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = (t_0 * (math.cos(phi1) * math.cos(phi2))) * t_0 return (math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), math.sqrt((1.0 - (t_1 + math.pow(((math.sin((phi1 * 0.5)) * math.cos((phi2 * 0.5))) - (math.sin((phi2 * 0.5)) * math.cos((phi1 * 0.5)))), 2.0))))) * 2.0) * R
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(t_0 * Float64(cos(phi1) * cos(phi2))) * t_0) return Float64(Float64(atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + t_1)), sqrt(Float64(1.0 - Float64(t_1 + (Float64(Float64(sin(Float64(phi1 * 0.5)) * cos(Float64(phi2 * 0.5))) - Float64(sin(Float64(phi2 * 0.5)) * cos(Float64(phi1 * 0.5)))) ^ 2.0))))) * 2.0) * R) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (t_0 * (cos(phi1) * cos(phi2))) * t_0; tmp = (atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + t_1)), sqrt((1.0 - (t_1 + (((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (sin((phi2 * 0.5)) * cos((phi1 * 0.5)))) ^ 2.0))))) * 2.0) * R; 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[(t$95$0 * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]}, N[(N[(N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$1 + N[Power[N[(N[(N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \left(t\_0 \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)\right) \cdot t\_0\\
\left(\tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_1}}{\sqrt{1 - \left(t\_1 + {\left(\sin \left(\phi_1 \cdot 0.5\right) \cdot \cos \left(\phi_2 \cdot 0.5\right) - \sin \left(\phi_2 \cdot 0.5\right) \cdot \cos \left(\phi_1 \cdot 0.5\right)\right)}^{2}\right)}} \cdot 2\right) \cdot R
\end{array}
\end{array}
Initial program 67.1%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f6467.8
Applied rewrites67.8%
Final simplification67.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_1 (* (cos phi1) (cos phi2))))
(*
(* 2.0 R)
(atan2
(sqrt (fma t_1 t_0 (pow (sin (* (- phi1 phi2) 0.5)) 2.0)))
(sqrt
(-
1.0
(fma
t_1
t_0
(pow
(fma
(sin (* -0.5 phi2))
(cos (* -0.5 phi1))
(* (cos (* -0.5 phi2)) (sin (* phi1 0.5))))
2.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_1 = cos(phi1) * cos(phi2);
return (2.0 * R) * atan2(sqrt(fma(t_1, t_0, pow(sin(((phi1 - phi2) * 0.5)), 2.0))), sqrt((1.0 - fma(t_1, t_0, pow(fma(sin((-0.5 * phi2)), cos((-0.5 * phi1)), (cos((-0.5 * phi2)) * sin((phi1 * 0.5)))), 2.0)))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_1 = Float64(cos(phi1) * cos(phi2)) return Float64(Float64(2.0 * R) * atan(sqrt(fma(t_1, t_0, (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0))), sqrt(Float64(1.0 - fma(t_1, t_0, (fma(sin(Float64(-0.5 * phi2)), cos(Float64(-0.5 * phi1)), Float64(cos(Float64(-0.5 * phi2)) * sin(Float64(phi1 * 0.5)))) ^ 2.0)))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, N[(N[(2.0 * R), $MachinePrecision] * N[ArcTan[N[Sqrt[N[(t$95$1 * t$95$0 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$1 * t$95$0 + N[Power[N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision] + N[(N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
\left(2 \cdot R\right) \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_1, t\_0, {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left(t\_1, t\_0, {\left(\mathsf{fma}\left(\sin \left(-0.5 \cdot \phi_2\right), \cos \left(-0.5 \cdot \phi_1\right), \cos \left(-0.5 \cdot \phi_2\right) \cdot \sin \left(\phi_1 \cdot 0.5\right)\right)\right)}^{2}\right)}}
\end{array}
\end{array}
Initial program 67.1%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f6467.8
Applied rewrites67.8%
Taylor expanded in lambda1 around 0
Applied rewrites67.8%
Final simplification67.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
(*
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* t_0 (* (cos phi1) (cos phi2))) t_0)))
(sqrt
(-
1.0
(/
(fma
(-
(cos (/ 0.0 (/ 2.0 (- phi1 phi2))))
(cos (* (* (- phi1 phi2) 0.5) 2.0)))
2.0
(*
(*
(+ (cos (+ phi1 phi2)) (cos (- phi1 phi2)))
(pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
2.0))
4.0))))
2.0)
R)))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
return (atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((t_0 * (cos(phi1) * cos(phi2))) * t_0))), sqrt((1.0 - (fma((cos((0.0 / (2.0 / (phi1 - phi2)))) - cos((((phi1 - phi2) * 0.5) * 2.0))), 2.0, (((cos((phi1 + phi2)) + cos((phi1 - phi2))) * pow(sin(((lambda1 - lambda2) * 0.5)), 2.0)) * 2.0)) / 4.0)))) * 2.0) * R;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(Float64(atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(t_0 * Float64(cos(phi1) * cos(phi2))) * t_0))), sqrt(Float64(1.0 - Float64(fma(Float64(cos(Float64(0.0 / Float64(2.0 / Float64(phi1 - phi2)))) - cos(Float64(Float64(Float64(phi1 - phi2) * 0.5) * 2.0))), 2.0, Float64(Float64(Float64(cos(Float64(phi1 + phi2)) + cos(Float64(phi1 - phi2))) * (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0)) * 2.0)) / 4.0)))) * 2.0) * R) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(N[(N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(t$95$0 * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[(N[Cos[N[(0.0 / N[(2.0 / N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] - N[Cos[N[(N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision] * 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * 2.0 + N[(N[(N[(N[Cos[N[(phi1 + phi2), $MachinePrecision]], $MachinePrecision] + N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] * 2.0), $MachinePrecision]), $MachinePrecision] / 4.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\left(\tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(t\_0 \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)\right) \cdot t\_0}}{\sqrt{1 - \frac{\mathsf{fma}\left(\cos \left(\frac{0}{\frac{2}{\phi_1 - \phi_2}}\right) - \cos \left(\left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right) \cdot 2\right), 2, \left(\left(\cos \left(\phi_1 + \phi_2\right) + \cos \left(\phi_1 - \phi_2\right)\right) \cdot {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\right) \cdot 2\right)}{4}}} \cdot 2\right) \cdot R
\end{array}
\end{array}
Initial program 67.1%
Applied rewrites67.5%
Final simplification67.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
(*
(* 2.0 R)
(atan2
(sqrt (fma t_1 t_0 (pow (sin (* (- phi1 phi2) 0.5)) 2.0)))
(sqrt (- (pow (cos (/ (- phi1 phi2) -2.0)) 2.0) (* t_1 t_0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
return (2.0 * R) * atan2(sqrt(fma(t_1, t_0, pow(sin(((phi1 - phi2) * 0.5)), 2.0))), sqrt((pow(cos(((phi1 - phi2) / -2.0)), 2.0) - (t_1 * t_0))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 return Float64(Float64(2.0 * R) * atan(sqrt(fma(t_1, t_0, (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(Float64(phi1 - phi2) / -2.0)) ^ 2.0) - Float64(t_1 * t_0))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(N[(2.0 * R), $MachinePrecision] * N[ArcTan[N[Sqrt[N[(t$95$1 * t$95$0 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(N[(phi1 - phi2), $MachinePrecision] / -2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(t$95$1 * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
\left(2 \cdot R\right) \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_1, t\_0, {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\right)}}{\sqrt{{\cos \left(\frac{\phi_1 - \phi_2}{-2}\right)}^{2} - t\_1 \cdot t\_0}}
\end{array}
\end{array}
Initial program 67.1%
Applied rewrites67.3%
Final simplification67.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(fma
(* (cos phi1) (cos phi2))
(pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)
(pow (sin (* (- phi1 phi2) 0.5)) 2.0))))
(* (atan2 (sqrt t_0) (sqrt (- 1.0 t_0))) (* 2.0 R))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = fma((cos(phi1) * cos(phi2)), pow(sin(((lambda1 - lambda2) * 0.5)), 2.0), pow(sin(((phi1 - phi2) * 0.5)), 2.0));
return atan2(sqrt(t_0), sqrt((1.0 - t_0))) * (2.0 * R);
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = fma(Float64(cos(phi1) * cos(phi2)), (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0), (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0)) return Float64(atan(sqrt(t_0), sqrt(Float64(1.0 - t_0))) * Float64(2.0 * R)) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, N[(N[ArcTan[N[Sqrt[t$95$0], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(2.0 * R), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \mathsf{fma}\left(\cos \phi_1 \cdot \cos \phi_2, {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}, {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\right)\\
\tan^{-1}_* \frac{\sqrt{t\_0}}{\sqrt{1 - t\_0}} \cdot \left(2 \cdot R\right)
\end{array}
\end{array}
Initial program 67.1%
Taylor expanded in lambda1 around 0
Applied rewrites67.1%
Final simplification67.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (* t_0 (* (cos phi1) (cos phi2))) t_0))
(t_2 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_3 (pow (sin (* phi1 0.5)) 2.0))
(t_4 (sqrt (- (pow (cos (* -0.5 phi1)) 2.0) (* t_2 (cos phi1))))))
(if (<= phi1 -4.9e-5)
(* (* (atan2 (sqrt (+ t_3 t_1)) t_4) 2.0) R)
(if (<= phi1 0.00053)
(*
(*
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) t_1))
(sqrt (- (pow (cos (* phi2 0.5)) 2.0) (* t_2 (cos phi2)))))
2.0)
R)
(* (* (atan2 (sqrt (fma t_2 (cos phi1) t_3)) t_4) 2.0) R)))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = (t_0 * (cos(phi1) * cos(phi2))) * t_0;
double t_2 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_3 = pow(sin((phi1 * 0.5)), 2.0);
double t_4 = sqrt((pow(cos((-0.5 * phi1)), 2.0) - (t_2 * cos(phi1))));
double tmp;
if (phi1 <= -4.9e-5) {
tmp = (atan2(sqrt((t_3 + t_1)), t_4) * 2.0) * R;
} else if (phi1 <= 0.00053) {
tmp = (atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), sqrt((pow(cos((phi2 * 0.5)), 2.0) - (t_2 * cos(phi2))))) * 2.0) * R;
} else {
tmp = (atan2(sqrt(fma(t_2, cos(phi1), t_3)), t_4) * 2.0) * R;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(t_0 * Float64(cos(phi1) * cos(phi2))) * t_0) t_2 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_3 = sin(Float64(phi1 * 0.5)) ^ 2.0 t_4 = sqrt(Float64((cos(Float64(-0.5 * phi1)) ^ 2.0) - Float64(t_2 * cos(phi1)))) tmp = 0.0 if (phi1 <= -4.9e-5) tmp = Float64(Float64(atan(sqrt(Float64(t_3 + t_1)), t_4) * 2.0) * R); elseif (phi1 <= 0.00053) tmp = Float64(Float64(atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + t_1)), sqrt(Float64((cos(Float64(phi2 * 0.5)) ^ 2.0) - Float64(t_2 * cos(phi2))))) * 2.0) * R); else tmp = Float64(Float64(atan(sqrt(fma(t_2, cos(phi1), t_3)), t_4) * 2.0) * R); 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[(t$95$0 * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$3 = N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$4 = N[Sqrt[N[(N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(t$95$2 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi1, -4.9e-5], N[(N[(N[ArcTan[N[Sqrt[N[(t$95$3 + t$95$1), $MachinePrecision]], $MachinePrecision] / t$95$4], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], If[LessEqual[phi1, 0.00053], N[(N[(N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(t$95$2 * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], N[(N[(N[ArcTan[N[Sqrt[N[(t$95$2 * N[Cos[phi1], $MachinePrecision] + t$95$3), $MachinePrecision]], $MachinePrecision] / t$95$4], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \left(t\_0 \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)\right) \cdot t\_0\\
t_2 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_3 := {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\\
t_4 := \sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - t\_2 \cdot \cos \phi_1}\\
\mathbf{if}\;\phi_1 \leq -4.9 \cdot 10^{-5}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{t\_3 + t\_1}}{t\_4} \cdot 2\right) \cdot R\\
\mathbf{elif}\;\phi_1 \leq 0.00053:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_1}}{\sqrt{{\cos \left(\phi_2 \cdot 0.5\right)}^{2} - t\_2 \cdot \cos \phi_2}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_2, \cos \phi_1, t\_3\right)}}{t\_4} \cdot 2\right) \cdot R\\
\end{array}
\end{array}
if phi1 < -4.9e-5Initial program 59.4%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
*-commutativeN/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites60.8%
Taylor expanded in phi2 around 0
lower-sin.f64N/A
lower-*.f6460.9
Applied rewrites60.9%
if -4.9e-5 < phi1 < 5.29999999999999981e-4Initial program 79.4%
Taylor expanded in phi1 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
*-commutativeN/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites79.5%
if 5.29999999999999981e-4 < phi1 Initial program 50.7%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
*-commutativeN/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites51.1%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6451.5
Applied rewrites51.5%
Final simplification67.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_1 (* t_0 (cos phi1)))
(t_2
(*
(*
(atan2
(sqrt (fma t_0 (cos phi2) (pow (sin (* -0.5 phi2)) 2.0)))
(sqrt
(-
1.0
(+
(*
(sin (* 0.5 lambda1))
(*
(sin (/ (- lambda1 lambda2) 2.0))
(* (cos phi1) (cos phi2))))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))))
2.0)
R)))
(if (<= phi2 -115.0)
t_2
(if (<= phi2 0.106)
(*
(*
(atan2
(sqrt (fma (cos phi2) t_1 (pow (sin (* (- phi1 phi2) 0.5)) 2.0)))
(sqrt (- (pow (cos (* -0.5 phi1)) 2.0) t_1)))
2.0)
R)
t_2))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_1 = t_0 * cos(phi1);
double t_2 = (atan2(sqrt(fma(t_0, cos(phi2), pow(sin((-0.5 * phi2)), 2.0))), sqrt((1.0 - ((sin((0.5 * lambda1)) * (sin(((lambda1 - lambda2) / 2.0)) * (cos(phi1) * cos(phi2)))) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))))) * 2.0) * R;
double tmp;
if (phi2 <= -115.0) {
tmp = t_2;
} else if (phi2 <= 0.106) {
tmp = (atan2(sqrt(fma(cos(phi2), t_1, pow(sin(((phi1 - phi2) * 0.5)), 2.0))), sqrt((pow(cos((-0.5 * phi1)), 2.0) - t_1))) * 2.0) * R;
} else {
tmp = t_2;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_1 = Float64(t_0 * cos(phi1)) t_2 = Float64(Float64(atan(sqrt(fma(t_0, cos(phi2), (sin(Float64(-0.5 * phi2)) ^ 2.0))), sqrt(Float64(1.0 - Float64(Float64(sin(Float64(0.5 * lambda1)) * Float64(sin(Float64(Float64(lambda1 - lambda2) / 2.0)) * Float64(cos(phi1) * cos(phi2)))) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))))) * 2.0) * R) tmp = 0.0 if (phi2 <= -115.0) tmp = t_2; elseif (phi2 <= 0.106) tmp = Float64(Float64(atan(sqrt(fma(cos(phi2), t_1, (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(-0.5 * phi1)) ^ 2.0) - t_1))) * 2.0) * R); else tmp = t_2; end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[(t$95$0 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(N[ArcTan[N[Sqrt[N[(t$95$0 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision] * N[(N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision] * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]}, If[LessEqual[phi2, -115.0], t$95$2, If[LessEqual[phi2, 0.106], N[(N[(N[ArcTan[N[Sqrt[N[(N[Cos[phi2], $MachinePrecision] * t$95$1 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], t$95$2]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_1 := t\_0 \cdot \cos \phi_1\\
t_2 := \left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \cos \phi_2, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)}}{\sqrt{1 - \left(\sin \left(0.5 \cdot \lambda_1\right) \cdot \left(\sin \left(\frac{\lambda_1 - \lambda_2}{2}\right) \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right)}} \cdot 2\right) \cdot R\\
\mathbf{if}\;\phi_2 \leq -115:\\
\;\;\;\;t\_2\\
\mathbf{elif}\;\phi_2 \leq 0.106:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_2, t\_1, {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\right)}}{\sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - t\_1}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;t\_2\\
\end{array}
\end{array}
if phi2 < -115 or 0.105999999999999997 < phi2 Initial program 52.3%
Taylor expanded in lambda1 around inf
*-commutativeN/A
lower-*.f6446.2
Applied rewrites46.2%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-fma.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6446.6
Applied rewrites46.6%
if -115 < phi2 < 0.105999999999999997Initial program 79.0%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
*-commutativeN/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites79.0%
lift-+.f64N/A
+-commutativeN/A
lift-*.f64N/A
Applied rewrites79.0%
Final simplification64.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0) (cos phi1)))
(t_1 (pow (sin (* (- phi1 phi2) 0.5)) 2.0))
(t_2
(*
(*
(atan2
(sqrt t_1)
(sqrt
(-
1.0
(+
(*
(sin (* 0.5 lambda1))
(*
(sin (/ (- lambda1 lambda2) 2.0))
(* (cos phi1) (cos phi2))))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))))
2.0)
R)))
(if (<= phi2 -175.0)
t_2
(if (<= phi2 0.27)
(*
(*
(atan2
(sqrt (fma (cos phi2) t_0 t_1))
(sqrt (- (pow (cos (* -0.5 phi1)) 2.0) t_0)))
2.0)
R)
t_2))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0) * cos(phi1);
double t_1 = pow(sin(((phi1 - phi2) * 0.5)), 2.0);
double t_2 = (atan2(sqrt(t_1), sqrt((1.0 - ((sin((0.5 * lambda1)) * (sin(((lambda1 - lambda2) / 2.0)) * (cos(phi1) * cos(phi2)))) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))))) * 2.0) * R;
double tmp;
if (phi2 <= -175.0) {
tmp = t_2;
} else if (phi2 <= 0.27) {
tmp = (atan2(sqrt(fma(cos(phi2), t_0, t_1)), sqrt((pow(cos((-0.5 * phi1)), 2.0) - t_0))) * 2.0) * R;
} else {
tmp = t_2;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64((sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0) * cos(phi1)) t_1 = sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0 t_2 = Float64(Float64(atan(sqrt(t_1), sqrt(Float64(1.0 - Float64(Float64(sin(Float64(0.5 * lambda1)) * Float64(sin(Float64(Float64(lambda1 - lambda2) / 2.0)) * Float64(cos(phi1) * cos(phi2)))) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))))) * 2.0) * R) tmp = 0.0 if (phi2 <= -175.0) tmp = t_2; elseif (phi2 <= 0.27) tmp = Float64(Float64(atan(sqrt(fma(cos(phi2), t_0, t_1)), sqrt(Float64((cos(Float64(-0.5 * phi1)) ^ 2.0) - t_0))) * 2.0) * R); else tmp = t_2; end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[(N[(N[ArcTan[N[Sqrt[t$95$1], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision] * N[(N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision] * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]}, If[LessEqual[phi2, -175.0], t$95$2, If[LessEqual[phi2, 0.27], N[(N[(N[ArcTan[N[Sqrt[N[(N[Cos[phi2], $MachinePrecision] * t$95$0 + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], t$95$2]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2} \cdot \cos \phi_1\\
t_1 := {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\\
t_2 := \left(\tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - \left(\sin \left(0.5 \cdot \lambda_1\right) \cdot \left(\sin \left(\frac{\lambda_1 - \lambda_2}{2}\right) \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right)}} \cdot 2\right) \cdot R\\
\mathbf{if}\;\phi_2 \leq -175:\\
\;\;\;\;t\_2\\
\mathbf{elif}\;\phi_2 \leq 0.27:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_2, t\_0, t\_1\right)}}{\sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - t\_0}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;t\_2\\
\end{array}
\end{array}
if phi2 < -175 or 0.27000000000000002 < phi2 Initial program 51.5%
Taylor expanded in lambda1 around inf
*-commutativeN/A
lower-*.f6445.2
Applied rewrites45.2%
Taylor expanded in lambda2 around 0
Applied rewrites42.2%
Taylor expanded in lambda1 around 0
Applied rewrites33.6%
if -175 < phi2 < 0.27000000000000002Initial program 79.3%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
*-commutativeN/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites78.3%
lift-+.f64N/A
+-commutativeN/A
lift-*.f64N/A
Applied rewrites78.3%
Final simplification58.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* (- lambda1 lambda2) 0.5)))
(t_1 (pow t_0 2.0))
(t_2 (sqrt (- 1.0 t_1)))
(t_3 (sin (/ (- lambda1 lambda2) 2.0)))
(t_4 (pow (sin (* (- phi1 phi2) 0.5)) 2.0)))
(if (<= t_3 -0.02)
(*
(*
(atan2 (sqrt (fma (* (* t_0 (cos phi1)) (cos phi2)) t_0 t_4)) t_2)
2.0)
R)
(if (<= t_3 2e-40)
(*
(*
(atan2
(sqrt t_4)
(sqrt
(-
1.0
(+
(* (sin (* 0.5 lambda1)) (* t_3 (* (cos phi1) (cos phi2))))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))))
2.0)
R)
(*
(* (atan2 (sqrt (fma (cos phi1) (* t_1 (cos phi2)) t_4)) t_2) 2.0)
R)))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) * 0.5));
double t_1 = pow(t_0, 2.0);
double t_2 = sqrt((1.0 - t_1));
double t_3 = sin(((lambda1 - lambda2) / 2.0));
double t_4 = pow(sin(((phi1 - phi2) * 0.5)), 2.0);
double tmp;
if (t_3 <= -0.02) {
tmp = (atan2(sqrt(fma(((t_0 * cos(phi1)) * cos(phi2)), t_0, t_4)), t_2) * 2.0) * R;
} else if (t_3 <= 2e-40) {
tmp = (atan2(sqrt(t_4), sqrt((1.0 - ((sin((0.5 * lambda1)) * (t_3 * (cos(phi1) * cos(phi2)))) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))))) * 2.0) * R;
} else {
tmp = (atan2(sqrt(fma(cos(phi1), (t_1 * cos(phi2)), t_4)), t_2) * 2.0) * R;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) t_1 = t_0 ^ 2.0 t_2 = sqrt(Float64(1.0 - t_1)) t_3 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_4 = sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0 tmp = 0.0 if (t_3 <= -0.02) tmp = Float64(Float64(atan(sqrt(fma(Float64(Float64(t_0 * cos(phi1)) * cos(phi2)), t_0, t_4)), t_2) * 2.0) * R); elseif (t_3 <= 2e-40) tmp = Float64(Float64(atan(sqrt(t_4), sqrt(Float64(1.0 - Float64(Float64(sin(Float64(0.5 * lambda1)) * Float64(t_3 * Float64(cos(phi1) * cos(phi2)))) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))))) * 2.0) * R); else tmp = Float64(Float64(atan(sqrt(fma(cos(phi1), Float64(t_1 * cos(phi2)), t_4)), t_2) * 2.0) * R); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[t$95$0, 2.0], $MachinePrecision]}, Block[{t$95$2 = N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[LessEqual[t$95$3, -0.02], N[(N[(N[ArcTan[N[Sqrt[N[(N[(N[(t$95$0 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0 + t$95$4), $MachinePrecision]], $MachinePrecision] / t$95$2], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], If[LessEqual[t$95$3, 2e-40], N[(N[(N[ArcTan[N[Sqrt[t$95$4], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision] * N[(t$95$3 * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], N[(N[(N[ArcTan[N[Sqrt[N[(N[Cos[phi1], $MachinePrecision] * N[(t$95$1 * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] + t$95$4), $MachinePrecision]], $MachinePrecision] / t$95$2], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)\\
t_1 := {t\_0}^{2}\\
t_2 := \sqrt{1 - t\_1}\\
t_3 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_4 := {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\\
\mathbf{if}\;t\_3 \leq -0.02:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\left(t\_0 \cdot \cos \phi_1\right) \cdot \cos \phi_2, t\_0, t\_4\right)}}{t\_2} \cdot 2\right) \cdot R\\
\mathbf{elif}\;t\_3 \leq 2 \cdot 10^{-40}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{t\_4}}{\sqrt{1 - \left(\sin \left(0.5 \cdot \lambda_1\right) \cdot \left(t\_3 \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right)}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_1, t\_1 \cdot \cos \phi_2, t\_4\right)}}{t\_2} \cdot 2\right) \cdot R\\
\end{array}
\end{array}
if (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < -0.0200000000000000004Initial program 67.8%
Taylor expanded in phi2 around 0
mul-1-negN/A
*-commutativeN/A
associate-*r*N/A
distribute-lft-neg-inN/A
lower-fma.f64N/A
Applied rewrites51.2%
Taylor expanded in phi1 around 0
Applied rewrites34.3%
lift-+.f64N/A
+-commutativeN/A
lift-*.f64N/A
lower-fma.f6434.3
Applied rewrites34.3%
if -0.0200000000000000004 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < 1.9999999999999999e-40Initial program 79.1%
Taylor expanded in lambda1 around inf
*-commutativeN/A
lower-*.f6477.5
Applied rewrites77.5%
Taylor expanded in lambda2 around 0
Applied rewrites76.8%
Taylor expanded in lambda1 around 0
Applied rewrites70.5%
if 1.9999999999999999e-40 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) Initial program 58.3%
Taylor expanded in phi2 around 0
mul-1-negN/A
*-commutativeN/A
associate-*r*N/A
distribute-lft-neg-inN/A
lower-fma.f64N/A
Applied rewrites41.8%
Taylor expanded in phi1 around 0
Applied rewrites36.5%
lift-+.f64N/A
+-commutativeN/A
Applied rewrites36.5%
Final simplification44.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_1
(*
(*
(atan2
(sqrt (pow (sin (* (- phi1 phi2) 0.5)) 2.0))
(sqrt
(-
1.0
(+
(*
(sin (* 0.5 lambda1))
(*
(sin (/ (- lambda1 lambda2) 2.0))
(* (cos phi1) (cos phi2))))
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))))
2.0)
R)))
(if (<= phi2 -1.1e-24)
t_1
(if (<= phi2 0.165)
(*
(*
(atan2
(sqrt (fma t_0 (cos phi1) (pow (sin (* phi1 0.5)) 2.0)))
(sqrt (- (pow (cos (* -0.5 phi1)) 2.0) (* t_0 (cos phi1)))))
2.0)
R)
t_1))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_1 = (atan2(sqrt(pow(sin(((phi1 - phi2) * 0.5)), 2.0)), sqrt((1.0 - ((sin((0.5 * lambda1)) * (sin(((lambda1 - lambda2) / 2.0)) * (cos(phi1) * cos(phi2)))) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))))) * 2.0) * R;
double tmp;
if (phi2 <= -1.1e-24) {
tmp = t_1;
} else if (phi2 <= 0.165) {
tmp = (atan2(sqrt(fma(t_0, cos(phi1), pow(sin((phi1 * 0.5)), 2.0))), sqrt((pow(cos((-0.5 * phi1)), 2.0) - (t_0 * cos(phi1))))) * 2.0) * R;
} else {
tmp = t_1;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_1 = Float64(Float64(atan(sqrt((sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0)), sqrt(Float64(1.0 - Float64(Float64(sin(Float64(0.5 * lambda1)) * Float64(sin(Float64(Float64(lambda1 - lambda2) / 2.0)) * Float64(cos(phi1) * cos(phi2)))) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))))) * 2.0) * R) tmp = 0.0 if (phi2 <= -1.1e-24) tmp = t_1; elseif (phi2 <= 0.165) tmp = Float64(Float64(atan(sqrt(fma(t_0, cos(phi1), (sin(Float64(phi1 * 0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(-0.5 * phi1)) ^ 2.0) - Float64(t_0 * cos(phi1))))) * 2.0) * R); else tmp = t_1; end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[ArcTan[N[Sqrt[N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision] * N[(N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision] * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]}, If[LessEqual[phi2, -1.1e-24], t$95$1, If[LessEqual[phi2, 0.165], N[(N[(N[ArcTan[N[Sqrt[N[(t$95$0 * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(t$95$0 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], t$95$1]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_1 := \left(\tan^{-1}_* \frac{\sqrt{{\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}}}{\sqrt{1 - \left(\sin \left(0.5 \cdot \lambda_1\right) \cdot \left(\sin \left(\frac{\lambda_1 - \lambda_2}{2}\right) \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)\right) + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right)}} \cdot 2\right) \cdot R\\
\mathbf{if}\;\phi_2 \leq -1.1 \cdot 10^{-24}:\\
\;\;\;\;t\_1\\
\mathbf{elif}\;\phi_2 \leq 0.165:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \cos \phi_1, {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}{\sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - t\_0 \cdot \cos \phi_1}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;t\_1\\
\end{array}
\end{array}
if phi2 < -1.10000000000000001e-24 or 0.165000000000000008 < phi2 Initial program 52.0%
Taylor expanded in lambda1 around inf
*-commutativeN/A
lower-*.f6446.0
Applied rewrites46.0%
Taylor expanded in lambda2 around 0
Applied rewrites42.7%
Taylor expanded in lambda1 around 0
Applied rewrites34.0%
if -1.10000000000000001e-24 < phi2 < 0.165000000000000008Initial program 80.5%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
*-commutativeN/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites80.0%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6479.2
Applied rewrites79.2%
Final simplification58.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* (- lambda1 lambda2) 0.5))))
(*
(*
(atan2
(sqrt
(fma
(* (* t_0 (cos phi1)) (cos phi2))
t_0
(pow (sin (* (- phi1 phi2) 0.5)) 2.0)))
(sqrt (- 1.0 (pow t_0 2.0))))
2.0)
R)))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) * 0.5));
return (atan2(sqrt(fma(((t_0 * cos(phi1)) * cos(phi2)), t_0, pow(sin(((phi1 - phi2) * 0.5)), 2.0))), sqrt((1.0 - pow(t_0, 2.0)))) * 2.0) * R;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) return Float64(Float64(atan(sqrt(fma(Float64(Float64(t_0 * cos(phi1)) * cos(phi2)), t_0, (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0))), sqrt(Float64(1.0 - (t_0 ^ 2.0)))) * 2.0) * R) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision]}, N[(N[(N[ArcTan[N[Sqrt[N[(N[(N[(t$95$0 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[t$95$0, 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)\\
\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\left(t\_0 \cdot \cos \phi_1\right) \cdot \cos \phi_2, t\_0, {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\right)}}{\sqrt{1 - {t\_0}^{2}}} \cdot 2\right) \cdot R
\end{array}
\end{array}
Initial program 67.1%
Taylor expanded in phi2 around 0
mul-1-negN/A
*-commutativeN/A
associate-*r*N/A
distribute-lft-neg-inN/A
lower-fma.f64N/A
Applied rewrites47.7%
Taylor expanded in phi1 around 0
Applied rewrites35.5%
lift-+.f64N/A
+-commutativeN/A
lift-*.f64N/A
lower-fma.f6435.5
Applied rewrites35.5%
Final simplification35.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_1 (sqrt (- 1.0 t_0))))
(if (<= phi2 -1.25e-79)
(*
(*
(atan2
(sqrt
(fma
(* (cos phi1) (cos phi2))
(pow (sin (* -0.5 lambda2)) 2.0)
(pow (sin (* (- phi1 phi2) 0.5)) 2.0)))
t_1)
2.0)
R)
(*
(*
(atan2 (sqrt (fma t_0 (cos phi1) (pow (sin (* phi1 0.5)) 2.0))) t_1)
2.0)
R))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_1 = sqrt((1.0 - t_0));
double tmp;
if (phi2 <= -1.25e-79) {
tmp = (atan2(sqrt(fma((cos(phi1) * cos(phi2)), pow(sin((-0.5 * lambda2)), 2.0), pow(sin(((phi1 - phi2) * 0.5)), 2.0))), t_1) * 2.0) * R;
} else {
tmp = (atan2(sqrt(fma(t_0, cos(phi1), pow(sin((phi1 * 0.5)), 2.0))), t_1) * 2.0) * R;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_1 = sqrt(Float64(1.0 - t_0)) tmp = 0.0 if (phi2 <= -1.25e-79) tmp = Float64(Float64(atan(sqrt(fma(Float64(cos(phi1) * cos(phi2)), (sin(Float64(-0.5 * lambda2)) ^ 2.0), (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0))), t_1) * 2.0) * R); else tmp = Float64(Float64(atan(sqrt(fma(t_0, cos(phi1), (sin(Float64(phi1 * 0.5)) ^ 2.0))), t_1) * 2.0) * R); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sqrt[N[(1.0 - t$95$0), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi2, -1.25e-79], N[(N[(N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[Power[N[Sin[N[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$1], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], N[(N[(N[ArcTan[N[Sqrt[N[(t$95$0 * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$1], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_1 := \sqrt{1 - t\_0}\\
\mathbf{if}\;\phi_2 \leq -1.25 \cdot 10^{-79}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_1 \cdot \cos \phi_2, {\sin \left(-0.5 \cdot \lambda_2\right)}^{2}, {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\right)}}{t\_1} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \cos \phi_1, {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}{t\_1} \cdot 2\right) \cdot R\\
\end{array}
\end{array}
if phi2 < -1.25e-79Initial program 51.6%
Taylor expanded in phi2 around 0
mul-1-negN/A
*-commutativeN/A
associate-*r*N/A
distribute-lft-neg-inN/A
lower-fma.f64N/A
Applied rewrites22.8%
Taylor expanded in phi1 around 0
Applied rewrites27.7%
Taylor expanded in lambda1 around 0
associate-*r*N/A
lower-fma.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
Applied rewrites28.1%
if -1.25e-79 < phi2 Initial program 74.1%
Taylor expanded in phi2 around 0
mul-1-negN/A
*-commutativeN/A
associate-*r*N/A
distribute-lft-neg-inN/A
lower-fma.f64N/A
Applied rewrites58.8%
Taylor expanded in phi1 around 0
Applied rewrites38.9%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6437.8
Applied rewrites37.8%
Final simplification34.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
(*
(*
(atan2
(sqrt
(fma
(cos phi1)
(* t_0 (cos phi2))
(pow (sin (* (- phi1 phi2) 0.5)) 2.0)))
(sqrt (- 1.0 t_0)))
2.0)
R)))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
return (atan2(sqrt(fma(cos(phi1), (t_0 * cos(phi2)), pow(sin(((phi1 - phi2) * 0.5)), 2.0))), sqrt((1.0 - t_0))) * 2.0) * R;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 return Float64(Float64(atan(sqrt(fma(cos(phi1), Float64(t_0 * cos(phi2)), (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0))), sqrt(Float64(1.0 - t_0))) * 2.0) * R) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(N[(N[ArcTan[N[Sqrt[N[(N[Cos[phi1], $MachinePrecision] * N[(t$95$0 * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_1, t\_0 \cdot \cos \phi_2, {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\right)}}{\sqrt{1 - t\_0}} \cdot 2\right) \cdot R
\end{array}
\end{array}
Initial program 67.1%
Taylor expanded in phi2 around 0
mul-1-negN/A
*-commutativeN/A
associate-*r*N/A
distribute-lft-neg-inN/A
lower-fma.f64N/A
Applied rewrites47.7%
Taylor expanded in phi1 around 0
Applied rewrites35.5%
lift-+.f64N/A
+-commutativeN/A
Applied rewrites35.5%
Final simplification35.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* phi1 0.5)) 2.0))
(t_1 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_2
(*
(*
(atan2
(sqrt (fma (pow (sin (* -0.5 lambda2)) 2.0) (cos phi1) t_0))
(sqrt (- 1.0 t_1)))
2.0)
R)))
(if (<= lambda2 -9e+50)
t_2
(if (<= lambda2 1.4e-5)
(*
(*
(atan2
(sqrt (fma t_1 (cos phi1) t_0))
(sqrt (- 1.0 (pow (sin (* 0.5 lambda1)) 2.0))))
2.0)
R)
t_2))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((phi1 * 0.5)), 2.0);
double t_1 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_2 = (atan2(sqrt(fma(pow(sin((-0.5 * lambda2)), 2.0), cos(phi1), t_0)), sqrt((1.0 - t_1))) * 2.0) * R;
double tmp;
if (lambda2 <= -9e+50) {
tmp = t_2;
} else if (lambda2 <= 1.4e-5) {
tmp = (atan2(sqrt(fma(t_1, cos(phi1), t_0)), sqrt((1.0 - pow(sin((0.5 * lambda1)), 2.0)))) * 2.0) * R;
} else {
tmp = t_2;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi1 * 0.5)) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_2 = Float64(Float64(atan(sqrt(fma((sin(Float64(-0.5 * lambda2)) ^ 2.0), cos(phi1), t_0)), sqrt(Float64(1.0 - t_1))) * 2.0) * R) tmp = 0.0 if (lambda2 <= -9e+50) tmp = t_2; elseif (lambda2 <= 1.4e-5) tmp = Float64(Float64(atan(sqrt(fma(t_1, cos(phi1), t_0)), sqrt(Float64(1.0 - (sin(Float64(0.5 * lambda1)) ^ 2.0)))) * 2.0) * R); else tmp = t_2; end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[(N[(N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision] + t$95$0), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]}, If[LessEqual[lambda2, -9e+50], t$95$2, If[LessEqual[lambda2, 1.4e-5], N[(N[(N[ArcTan[N[Sqrt[N[(t$95$1 * N[Cos[phi1], $MachinePrecision] + t$95$0), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], t$95$2]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\\
t_1 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_2 := \left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left({\sin \left(-0.5 \cdot \lambda_2\right)}^{2}, \cos \phi_1, t\_0\right)}}{\sqrt{1 - t\_1}} \cdot 2\right) \cdot R\\
\mathbf{if}\;\lambda_2 \leq -9 \cdot 10^{+50}:\\
\;\;\;\;t\_2\\
\mathbf{elif}\;\lambda_2 \leq 1.4 \cdot 10^{-5}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_1, \cos \phi_1, t\_0\right)}}{\sqrt{1 - {\sin \left(0.5 \cdot \lambda_1\right)}^{2}}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;t\_2\\
\end{array}
\end{array}
if lambda2 < -9.00000000000000027e50 or 1.39999999999999998e-5 < lambda2 Initial program 52.0%
Taylor expanded in phi2 around 0
mul-1-negN/A
*-commutativeN/A
associate-*r*N/A
distribute-lft-neg-inN/A
lower-fma.f64N/A
Applied rewrites41.4%
Taylor expanded in phi1 around 0
Applied rewrites35.2%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6435.1
Applied rewrites35.1%
Taylor expanded in lambda1 around 0
Applied rewrites35.3%
if -9.00000000000000027e50 < lambda2 < 1.39999999999999998e-5Initial program 78.4%
Taylor expanded in phi2 around 0
mul-1-negN/A
*-commutativeN/A
associate-*r*N/A
distribute-lft-neg-inN/A
lower-fma.f64N/A
Applied rewrites52.3%
Taylor expanded in phi1 around 0
Applied rewrites35.7%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6431.4
Applied rewrites31.4%
Taylor expanded in lambda2 around 0
Applied rewrites31.5%
Final simplification33.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* phi1 0.5)) 2.0))
(t_1 (sqrt (- 1.0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))))
(t_2
(*
(*
(atan2
(sqrt (fma (pow (sin (* -0.5 lambda2)) 2.0) (cos phi1) t_0))
t_1)
2.0)
R)))
(if (<= lambda2 -10000000.0)
t_2
(if (<= lambda2 2e-6)
(*
(*
(atan2
(sqrt (fma (pow (sin (* 0.5 lambda1)) 2.0) (cos phi1) t_0))
t_1)
2.0)
R)
t_2))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((phi1 * 0.5)), 2.0);
double t_1 = sqrt((1.0 - pow(sin(((lambda1 - lambda2) * 0.5)), 2.0)));
double t_2 = (atan2(sqrt(fma(pow(sin((-0.5 * lambda2)), 2.0), cos(phi1), t_0)), t_1) * 2.0) * R;
double tmp;
if (lambda2 <= -10000000.0) {
tmp = t_2;
} else if (lambda2 <= 2e-6) {
tmp = (atan2(sqrt(fma(pow(sin((0.5 * lambda1)), 2.0), cos(phi1), t_0)), t_1) * 2.0) * R;
} else {
tmp = t_2;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi1 * 0.5)) ^ 2.0 t_1 = sqrt(Float64(1.0 - (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0))) t_2 = Float64(Float64(atan(sqrt(fma((sin(Float64(-0.5 * lambda2)) ^ 2.0), cos(phi1), t_0)), t_1) * 2.0) * R) tmp = 0.0 if (lambda2 <= -10000000.0) tmp = t_2; elseif (lambda2 <= 2e-6) tmp = Float64(Float64(atan(sqrt(fma((sin(Float64(0.5 * lambda1)) ^ 2.0), cos(phi1), t_0)), t_1) * 2.0) * R); else tmp = t_2; end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[(N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision] + t$95$0), $MachinePrecision]], $MachinePrecision] / t$95$1], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]}, If[LessEqual[lambda2, -10000000.0], t$95$2, If[LessEqual[lambda2, 2e-6], N[(N[(N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision] + t$95$0), $MachinePrecision]], $MachinePrecision] / t$95$1], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], t$95$2]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\\
t_1 := \sqrt{1 - {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}}\\
t_2 := \left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left({\sin \left(-0.5 \cdot \lambda_2\right)}^{2}, \cos \phi_1, t\_0\right)}}{t\_1} \cdot 2\right) \cdot R\\
\mathbf{if}\;\lambda_2 \leq -10000000:\\
\;\;\;\;t\_2\\
\mathbf{elif}\;\lambda_2 \leq 2 \cdot 10^{-6}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left({\sin \left(0.5 \cdot \lambda_1\right)}^{2}, \cos \phi_1, t\_0\right)}}{t\_1} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;t\_2\\
\end{array}
\end{array}
if lambda2 < -1e7 or 1.99999999999999991e-6 < lambda2 Initial program 52.5%
Taylor expanded in phi2 around 0
mul-1-negN/A
*-commutativeN/A
associate-*r*N/A
distribute-lft-neg-inN/A
lower-fma.f64N/A
Applied rewrites41.4%
Taylor expanded in phi1 around 0
Applied rewrites34.5%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6434.5
Applied rewrites34.5%
Taylor expanded in lambda1 around 0
Applied rewrites34.6%
if -1e7 < lambda2 < 1.99999999999999991e-6Initial program 78.9%
Taylor expanded in phi2 around 0
mul-1-negN/A
*-commutativeN/A
associate-*r*N/A
distribute-lft-neg-inN/A
lower-fma.f64N/A
Applied rewrites52.7%
Taylor expanded in phi1 around 0
Applied rewrites36.2%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6431.8
Applied rewrites31.8%
Taylor expanded in lambda2 around 0
Applied rewrites31.1%
Final simplification32.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_1 (sqrt (- 1.0 t_0))))
(if (<= phi2 -8.8e-80)
(*
(*
(atan2 (sqrt (fma t_0 (cos phi2) (pow (sin (* -0.5 phi2)) 2.0))) t_1)
2.0)
R)
(*
(*
(atan2 (sqrt (fma t_0 (cos phi1) (pow (sin (* phi1 0.5)) 2.0))) t_1)
2.0)
R))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_1 = sqrt((1.0 - t_0));
double tmp;
if (phi2 <= -8.8e-80) {
tmp = (atan2(sqrt(fma(t_0, cos(phi2), pow(sin((-0.5 * phi2)), 2.0))), t_1) * 2.0) * R;
} else {
tmp = (atan2(sqrt(fma(t_0, cos(phi1), pow(sin((phi1 * 0.5)), 2.0))), t_1) * 2.0) * R;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_1 = sqrt(Float64(1.0 - t_0)) tmp = 0.0 if (phi2 <= -8.8e-80) tmp = Float64(Float64(atan(sqrt(fma(t_0, cos(phi2), (sin(Float64(-0.5 * phi2)) ^ 2.0))), t_1) * 2.0) * R); else tmp = Float64(Float64(atan(sqrt(fma(t_0, cos(phi1), (sin(Float64(phi1 * 0.5)) ^ 2.0))), t_1) * 2.0) * R); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sqrt[N[(1.0 - t$95$0), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi2, -8.8e-80], N[(N[(N[ArcTan[N[Sqrt[N[(t$95$0 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$1], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], N[(N[(N[ArcTan[N[Sqrt[N[(t$95$0 * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$1], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_1 := \sqrt{1 - t\_0}\\
\mathbf{if}\;\phi_2 \leq -8.8 \cdot 10^{-80}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \cos \phi_2, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)}}{t\_1} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \cos \phi_1, {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}{t\_1} \cdot 2\right) \cdot R\\
\end{array}
\end{array}
if phi2 < -8.80000000000000041e-80Initial program 51.6%
Taylor expanded in phi2 around 0
mul-1-negN/A
*-commutativeN/A
associate-*r*N/A
distribute-lft-neg-inN/A
lower-fma.f64N/A
Applied rewrites22.8%
Taylor expanded in phi1 around 0
Applied rewrites27.7%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-fma.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6427.7
Applied rewrites27.7%
if -8.80000000000000041e-80 < phi2 Initial program 74.1%
Taylor expanded in phi2 around 0
mul-1-negN/A
*-commutativeN/A
associate-*r*N/A
distribute-lft-neg-inN/A
lower-fma.f64N/A
Applied rewrites58.8%
Taylor expanded in phi1 around 0
Applied rewrites38.9%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6437.8
Applied rewrites37.8%
Final simplification34.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* phi1 0.5)) 2.0))
(t_1 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
(if (<= lambda1 -125000.0)
(*
(*
(atan2
(sqrt (fma (pow (sin (* 0.5 lambda1)) 2.0) (cos phi1) t_0))
(sqrt (- 1.0 t_1)))
2.0)
R)
(*
(*
(atan2
(sqrt (fma t_1 (cos phi1) t_0))
(sqrt (- 1.0 (pow (sin (* -0.5 lambda2)) 2.0))))
2.0)
R))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((phi1 * 0.5)), 2.0);
double t_1 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double tmp;
if (lambda1 <= -125000.0) {
tmp = (atan2(sqrt(fma(pow(sin((0.5 * lambda1)), 2.0), cos(phi1), t_0)), sqrt((1.0 - t_1))) * 2.0) * R;
} else {
tmp = (atan2(sqrt(fma(t_1, cos(phi1), t_0)), sqrt((1.0 - pow(sin((-0.5 * lambda2)), 2.0)))) * 2.0) * R;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi1 * 0.5)) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 tmp = 0.0 if (lambda1 <= -125000.0) tmp = Float64(Float64(atan(sqrt(fma((sin(Float64(0.5 * lambda1)) ^ 2.0), cos(phi1), t_0)), sqrt(Float64(1.0 - t_1))) * 2.0) * R); else tmp = Float64(Float64(atan(sqrt(fma(t_1, cos(phi1), t_0)), sqrt(Float64(1.0 - (sin(Float64(-0.5 * lambda2)) ^ 2.0)))) * 2.0) * R); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[LessEqual[lambda1, -125000.0], N[(N[(N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision] + t$95$0), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], N[(N[(N[ArcTan[N[Sqrt[N[(t$95$1 * N[Cos[phi1], $MachinePrecision] + t$95$0), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\\
t_1 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
\mathbf{if}\;\lambda_1 \leq -125000:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left({\sin \left(0.5 \cdot \lambda_1\right)}^{2}, \cos \phi_1, t\_0\right)}}{\sqrt{1 - t\_1}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_1, \cos \phi_1, t\_0\right)}}{\sqrt{1 - {\sin \left(-0.5 \cdot \lambda_2\right)}^{2}}} \cdot 2\right) \cdot R\\
\end{array}
\end{array}
if lambda1 < -125000Initial program 61.1%
Taylor expanded in phi2 around 0
mul-1-negN/A
*-commutativeN/A
associate-*r*N/A
distribute-lft-neg-inN/A
lower-fma.f64N/A
Applied rewrites44.1%
Taylor expanded in phi1 around 0
Applied rewrites31.7%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6431.6
Applied rewrites31.6%
Taylor expanded in lambda2 around 0
Applied rewrites31.7%
if -125000 < lambda1 Initial program 69.3%
Taylor expanded in phi2 around 0
mul-1-negN/A
*-commutativeN/A
associate-*r*N/A
distribute-lft-neg-inN/A
lower-fma.f64N/A
Applied rewrites48.9%
Taylor expanded in phi1 around 0
Applied rewrites36.8%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6433.5
Applied rewrites33.5%
Taylor expanded in lambda1 around 0
Applied rewrites31.7%
Final simplification31.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
(*
(*
(atan2
(sqrt (fma t_0 (cos phi1) (pow (sin (* phi1 0.5)) 2.0)))
(sqrt (- 1.0 t_0)))
2.0)
R)))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
return (atan2(sqrt(fma(t_0, cos(phi1), pow(sin((phi1 * 0.5)), 2.0))), sqrt((1.0 - t_0))) * 2.0) * R;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 return Float64(Float64(atan(sqrt(fma(t_0, cos(phi1), (sin(Float64(phi1 * 0.5)) ^ 2.0))), sqrt(Float64(1.0 - t_0))) * 2.0) * R) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(N[(N[ArcTan[N[Sqrt[N[(t$95$0 * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \cos \phi_1, {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}{\sqrt{1 - t\_0}} \cdot 2\right) \cdot R
\end{array}
\end{array}
Initial program 67.1%
Taylor expanded in phi2 around 0
mul-1-negN/A
*-commutativeN/A
associate-*r*N/A
distribute-lft-neg-inN/A
lower-fma.f64N/A
Applied rewrites47.7%
Taylor expanded in phi1 around 0
Applied rewrites35.5%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6433.0
Applied rewrites33.0%
Final simplification33.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
(*
(atan2
(sqrt
(fma
(pow (sin (* 0.5 lambda1)) 2.0)
(cos phi1)
(pow (sin (* phi1 0.5)) 2.0)))
(sqrt (- 1.0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))))
2.0)
R))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return (atan2(sqrt(fma(pow(sin((0.5 * lambda1)), 2.0), cos(phi1), pow(sin((phi1 * 0.5)), 2.0))), sqrt((1.0 - pow(sin(((lambda1 - lambda2) * 0.5)), 2.0)))) * 2.0) * R;
}
function code(R, lambda1, lambda2, phi1, phi2) return Float64(Float64(atan(sqrt(fma((sin(Float64(0.5 * lambda1)) ^ 2.0), cos(phi1), (sin(Float64(phi1 * 0.5)) ^ 2.0))), sqrt(Float64(1.0 - (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0)))) * 2.0) * R) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(N[(N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(0.5 * lambda1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]
\begin{array}{l}
\\
\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left({\sin \left(0.5 \cdot \lambda_1\right)}^{2}, \cos \phi_1, {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}{\sqrt{1 - {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}}} \cdot 2\right) \cdot R
\end{array}
Initial program 67.1%
Taylor expanded in phi2 around 0
mul-1-negN/A
*-commutativeN/A
associate-*r*N/A
distribute-lft-neg-inN/A
lower-fma.f64N/A
Applied rewrites47.7%
Taylor expanded in phi1 around 0
Applied rewrites35.5%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6433.0
Applied rewrites33.0%
Taylor expanded in lambda2 around 0
Applied rewrites24.6%
Final simplification24.6%
herbie shell --seed 2024254
(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))))))))))