
(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 19 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_0) t_0))))
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0);
return R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0)
code = r * (2.0d0 * atan2(sqrt(t_1), sqrt((1.0d0 - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((Math.cos(phi1) * Math.cos(phi2)) * t_0) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt(t_1), Math.sqrt((1.0 - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((math.cos(phi1) * math.cos(phi2)) * t_0) * t_0) return R * (2.0 * math.atan2(math.sqrt(t_1), math.sqrt((1.0 - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0); tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$1], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) \cdot t\_0\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)
\end{array}
\end{array}
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* lambda1 0.5)))
(t_1 (cos (* lambda2 0.5)))
(t_2 (sin (* lambda2 0.5)))
(t_3 (* (cos phi1) (cos phi2)))
(t_4 (cos (* lambda1 0.5))))
(*
(* 2.0 R)
(atan2
(sqrt
(fma
t_3
(pow (- (* t_0 t_1) (* t_4 t_2)) 2.0)
(pow
(fma
(sin (* -0.5 phi2))
(cos (* -0.5 phi1))
(* (sin (* 0.5 phi1)) (cos (* -0.5 phi2))))
2.0)))
(sqrt
(-
1.0
(fma
t_3
(pow (fma t_2 (- t_4) (* t_1 t_0)) 2.0)
(pow (sin (* (- phi1 phi2) 0.5)) 2.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((lambda1 * 0.5));
double t_1 = cos((lambda2 * 0.5));
double t_2 = sin((lambda2 * 0.5));
double t_3 = cos(phi1) * cos(phi2);
double t_4 = cos((lambda1 * 0.5));
return (2.0 * R) * atan2(sqrt(fma(t_3, pow(((t_0 * t_1) - (t_4 * t_2)), 2.0), pow(fma(sin((-0.5 * phi2)), cos((-0.5 * phi1)), (sin((0.5 * phi1)) * cos((-0.5 * phi2)))), 2.0))), sqrt((1.0 - fma(t_3, pow(fma(t_2, -t_4, (t_1 * t_0)), 2.0), pow(sin(((phi1 - phi2) * 0.5)), 2.0)))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(lambda1 * 0.5)) t_1 = cos(Float64(lambda2 * 0.5)) t_2 = sin(Float64(lambda2 * 0.5)) t_3 = Float64(cos(phi1) * cos(phi2)) t_4 = cos(Float64(lambda1 * 0.5)) return Float64(Float64(2.0 * R) * atan(sqrt(fma(t_3, (Float64(Float64(t_0 * t_1) - Float64(t_4 * t_2)) ^ 2.0), (fma(sin(Float64(-0.5 * phi2)), cos(Float64(-0.5 * phi1)), Float64(sin(Float64(0.5 * phi1)) * cos(Float64(-0.5 * phi2)))) ^ 2.0))), sqrt(Float64(1.0 - fma(t_3, (fma(t_2, Float64(-t_4), Float64(t_1 * t_0)) ^ 2.0), (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0)))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(lambda2 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(lambda2 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[Cos[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision]}, N[(N[(2.0 * R), $MachinePrecision] * N[ArcTan[N[Sqrt[N[(t$95$3 * N[Power[N[(N[(t$95$0 * t$95$1), $MachinePrecision] - N[(t$95$4 * t$95$2), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision] + N[(N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$3 * N[Power[N[(t$95$2 * (-t$95$4) + N[(t$95$1 * t$95$0), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\lambda_1 \cdot 0.5\right)\\
t_1 := \cos \left(\lambda_2 \cdot 0.5\right)\\
t_2 := \sin \left(\lambda_2 \cdot 0.5\right)\\
t_3 := \cos \phi_1 \cdot \cos \phi_2\\
t_4 := \cos \left(\lambda_1 \cdot 0.5\right)\\
\left(2 \cdot R\right) \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_3, {\left(t\_0 \cdot t\_1 - t\_4 \cdot t\_2\right)}^{2}, {\left(\mathsf{fma}\left(\sin \left(-0.5 \cdot \phi_2\right), \cos \left(-0.5 \cdot \phi_1\right), \sin \left(0.5 \cdot \phi_1\right) \cdot \cos \left(-0.5 \cdot \phi_2\right)\right)\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left(t\_3, {\left(\mathsf{fma}\left(t\_2, -t\_4, t\_1 \cdot t\_0\right)\right)}^{2}, {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\right)}}
\end{array}
\end{array}
Initial program 62.3%
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-*.f6463.2
Applied rewrites63.2%
Taylor expanded in R around 0
Applied rewrites63.2%
Applied rewrites63.8%
Applied rewrites79.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* lambda1 0.5)))
(t_1 (* (cos phi1) (cos phi2)))
(t_2 (cos (* lambda1 0.5))))
(*
(* 2.0 R)
(atan2
(sqrt
(fma
t_1
(pow
(- (* t_0 (cos (* lambda2 0.5))) (* t_2 (sin (* lambda2 0.5))))
2.0)
(pow
(fma
(sin (* -0.5 phi2))
(cos (* -0.5 phi1))
(* (sin (* 0.5 phi1)) (cos (* -0.5 phi2))))
2.0)))
(sqrt
(-
1.0
(fma
t_1
(pow
(fma t_0 (cos (* -0.5 lambda2)) (* t_2 (sin (* -0.5 lambda2))))
2.0)
(pow (sin (* (- phi1 phi2) 0.5)) 2.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((lambda1 * 0.5));
double t_1 = cos(phi1) * cos(phi2);
double t_2 = cos((lambda1 * 0.5));
return (2.0 * R) * atan2(sqrt(fma(t_1, pow(((t_0 * cos((lambda2 * 0.5))) - (t_2 * sin((lambda2 * 0.5)))), 2.0), pow(fma(sin((-0.5 * phi2)), cos((-0.5 * phi1)), (sin((0.5 * phi1)) * cos((-0.5 * phi2)))), 2.0))), sqrt((1.0 - fma(t_1, pow(fma(t_0, cos((-0.5 * lambda2)), (t_2 * sin((-0.5 * lambda2)))), 2.0), pow(sin(((phi1 - phi2) * 0.5)), 2.0)))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(lambda1 * 0.5)) t_1 = Float64(cos(phi1) * cos(phi2)) t_2 = cos(Float64(lambda1 * 0.5)) return Float64(Float64(2.0 * R) * atan(sqrt(fma(t_1, (Float64(Float64(t_0 * cos(Float64(lambda2 * 0.5))) - Float64(t_2 * sin(Float64(lambda2 * 0.5)))) ^ 2.0), (fma(sin(Float64(-0.5 * phi2)), cos(Float64(-0.5 * phi1)), Float64(sin(Float64(0.5 * phi1)) * cos(Float64(-0.5 * phi2)))) ^ 2.0))), sqrt(Float64(1.0 - fma(t_1, (fma(t_0, cos(Float64(-0.5 * lambda2)), Float64(t_2 * sin(Float64(-0.5 * lambda2)))) ^ 2.0), (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0)))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Cos[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision]}, N[(N[(2.0 * R), $MachinePrecision] * N[ArcTan[N[Sqrt[N[(t$95$1 * N[Power[N[(N[(t$95$0 * N[Cos[N[(lambda2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(t$95$2 * N[Sin[N[(lambda2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision] + N[(N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$1 * N[Power[N[(t$95$0 * N[Cos[N[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision] + N[(t$95$2 * N[Sin[N[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\lambda_1 \cdot 0.5\right)\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
t_2 := \cos \left(\lambda_1 \cdot 0.5\right)\\
\left(2 \cdot R\right) \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_1, {\left(t\_0 \cdot \cos \left(\lambda_2 \cdot 0.5\right) - t\_2 \cdot \sin \left(\lambda_2 \cdot 0.5\right)\right)}^{2}, {\left(\mathsf{fma}\left(\sin \left(-0.5 \cdot \phi_2\right), \cos \left(-0.5 \cdot \phi_1\right), \sin \left(0.5 \cdot \phi_1\right) \cdot \cos \left(-0.5 \cdot \phi_2\right)\right)\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left(t\_1, {\left(\mathsf{fma}\left(t\_0, \cos \left(-0.5 \cdot \lambda_2\right), t\_2 \cdot \sin \left(-0.5 \cdot \lambda_2\right)\right)\right)}^{2}, {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\right)}}
\end{array}
\end{array}
Initial program 62.3%
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-*.f6463.2
Applied rewrites63.2%
Taylor expanded in R around 0
Applied rewrites63.2%
Applied rewrites63.8%
Applied rewrites79.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2))))
(*
(* 2.0 R)
(atan2
(sqrt
(fma
t_0
(pow
(fma
(- (sin (* lambda2 0.5)))
(cos (* lambda1 0.5))
(* (sin (* lambda1 0.5)) (cos (* lambda2 0.5))))
2.0)
(pow
(fma
(cos (* -0.5 phi2))
(sin (* 0.5 phi1))
(* (sin (* -0.5 phi2)) (cos (* -0.5 phi1))))
2.0)))
(sqrt
(-
1.0
(fma
t_0
(pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)
(pow (sin (* (- phi1 phi2) 0.5)) 2.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
return (2.0 * R) * atan2(sqrt(fma(t_0, pow(fma(-sin((lambda2 * 0.5)), cos((lambda1 * 0.5)), (sin((lambda1 * 0.5)) * cos((lambda2 * 0.5)))), 2.0), pow(fma(cos((-0.5 * phi2)), sin((0.5 * phi1)), (sin((-0.5 * phi2)) * cos((-0.5 * phi1)))), 2.0))), sqrt((1.0 - fma(t_0, pow(sin(((lambda1 - lambda2) * 0.5)), 2.0), pow(sin(((phi1 - phi2) * 0.5)), 2.0)))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) return Float64(Float64(2.0 * R) * atan(sqrt(fma(t_0, (fma(Float64(-sin(Float64(lambda2 * 0.5))), cos(Float64(lambda1 * 0.5)), Float64(sin(Float64(lambda1 * 0.5)) * cos(Float64(lambda2 * 0.5)))) ^ 2.0), (fma(cos(Float64(-0.5 * phi2)), sin(Float64(0.5 * phi1)), Float64(sin(Float64(-0.5 * phi2)) * cos(Float64(-0.5 * phi1)))) ^ 2.0))), sqrt(Float64(1.0 - fma(t_0, (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0), (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0)))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, N[(N[(2.0 * R), $MachinePrecision] * N[ArcTan[N[Sqrt[N[(t$95$0 * N[Power[N[((-N[Sin[N[(lambda2 * 0.5), $MachinePrecision]], $MachinePrecision]) * N[Cos[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision] + N[(N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(lambda2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[(N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 * 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]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
\left(2 \cdot R\right) \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, {\left(\mathsf{fma}\left(-\sin \left(\lambda_2 \cdot 0.5\right), \cos \left(\lambda_1 \cdot 0.5\right), \sin \left(\lambda_1 \cdot 0.5\right) \cdot \cos \left(\lambda_2 \cdot 0.5\right)\right)\right)}^{2}, {\left(\mathsf{fma}\left(\cos \left(-0.5 \cdot \phi_2\right), \sin \left(0.5 \cdot \phi_1\right), \sin \left(-0.5 \cdot \phi_2\right) \cdot \cos \left(-0.5 \cdot \phi_1\right)\right)\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left(t\_0, {\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)}}
\end{array}
\end{array}
Initial program 62.3%
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-*.f6463.2
Applied rewrites63.2%
Taylor expanded in R around 0
Applied rewrites63.2%
Applied rewrites63.8%
Taylor expanded in lambda1 around inf
Applied rewrites63.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
(*
(* 2.0 R)
(atan2
(sqrt
(fma
(* (cos phi1) (cos phi2))
t_0
(pow
(fma
(sin (* -0.5 phi2))
(cos (* -0.5 phi1))
(* (sin (* 0.5 phi1)) (cos (* -0.5 phi2))))
2.0)))
(sqrt
(-
(- 1.0 (* t_0 (* (cos phi2) (cos phi1))))
(pow (sin (* (- phi1 phi2) 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);
return (2.0 * R) * atan2(sqrt(fma((cos(phi1) * cos(phi2)), t_0, pow(fma(sin((-0.5 * phi2)), cos((-0.5 * phi1)), (sin((0.5 * phi1)) * cos((-0.5 * phi2)))), 2.0))), sqrt(((1.0 - (t_0 * (cos(phi2) * cos(phi1)))) - pow(sin(((phi1 - phi2) * 0.5)), 2.0))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 return Float64(Float64(2.0 * R) * atan(sqrt(fma(Float64(cos(phi1) * cos(phi2)), t_0, (fma(sin(Float64(-0.5 * phi2)), cos(Float64(-0.5 * phi1)), Float64(sin(Float64(0.5 * phi1)) * cos(Float64(-0.5 * phi2)))) ^ 2.0))), sqrt(Float64(Float64(1.0 - Float64(t_0 * Float64(cos(phi2) * cos(phi1)))) - (sin(Float64(Float64(phi1 - phi2) * 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]}, N[(N[(2.0 * R), $MachinePrecision] * N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0 + N[Power[N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision] + N[(N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[(t$95$0 * N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
\left(2 \cdot R\right) \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_1 \cdot \cos \phi_2, t\_0, {\left(\mathsf{fma}\left(\sin \left(-0.5 \cdot \phi_2\right), \cos \left(-0.5 \cdot \phi_1\right), \sin \left(0.5 \cdot \phi_1\right) \cdot \cos \left(-0.5 \cdot \phi_2\right)\right)\right)}^{2}\right)}}{\sqrt{\left(1 - t\_0 \cdot \left(\cos \phi_2 \cdot \cos \phi_1\right)\right) - {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}}}
\end{array}
\end{array}
Initial program 62.3%
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-*.f6463.2
Applied rewrites63.2%
Taylor expanded in R around 0
Applied rewrites63.2%
Applied rewrites63.2%
(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
(fma
(sin (* -0.5 phi2))
(cos (* -0.5 phi1))
(* (sin (* 0.5 phi1)) (cos (* -0.5 phi2))))
2.0)))
(sqrt (- 1.0 (fma t_1 t_0 (pow (sin (* (- phi1 phi2) 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(fma(sin((-0.5 * phi2)), cos((-0.5 * phi1)), (sin((0.5 * phi1)) * cos((-0.5 * phi2)))), 2.0))), sqrt((1.0 - fma(t_1, t_0, pow(sin(((phi1 - phi2) * 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, (fma(sin(Float64(-0.5 * phi2)), cos(Float64(-0.5 * phi1)), Float64(sin(Float64(0.5 * phi1)) * cos(Float64(-0.5 * phi2)))) ^ 2.0))), sqrt(Float64(1.0 - fma(t_1, t_0, (sin(Float64(Float64(phi1 - phi2) * 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[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision] + N[(N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - 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]], $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, {\left(\mathsf{fma}\left(\sin \left(-0.5 \cdot \phi_2\right), \cos \left(-0.5 \cdot \phi_1\right), \sin \left(0.5 \cdot \phi_1\right) \cdot \cos \left(-0.5 \cdot \phi_2\right)\right)\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left(t\_1, t\_0, {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\right)}}
\end{array}
\end{array}
Initial program 62.3%
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-*.f6463.2
Applied rewrites63.2%
Taylor expanded in R around 0
Applied rewrites63.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi2) (cos phi1)))
(t_1 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
(*
(*
R
(atan2
(sqrt (fma t_1 t_0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0)))
(sqrt (- (pow (cos (/ (- phi1 phi2) -2.0)) 2.0) (* t_1 t_0)))))
2.0)))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi2) * cos(phi1);
double t_1 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
return (R * atan2(sqrt(fma(t_1, t_0, pow(sin((0.5 * (phi1 - phi2))), 2.0))), sqrt((pow(cos(((phi1 - phi2) / -2.0)), 2.0) - (t_1 * t_0))))) * 2.0;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi2) * cos(phi1)) t_1 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 return Float64(Float64(R * atan(sqrt(fma(t_1, t_0, (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0))), sqrt(Float64((cos(Float64(Float64(phi1 - phi2) / -2.0)) ^ 2.0) - Float64(t_1 * t_0))))) * 2.0) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(N[(R * N[ArcTan[N[Sqrt[N[(t$95$1 * t$95$0 + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(N[(phi1 - phi2), $MachinePrecision] / -2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(t$95$1 * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * 2.0), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_2 \cdot \cos \phi_1\\
t_1 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
\left(R \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_1, t\_0, {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}}{\sqrt{{\cos \left(\frac{\phi_1 - \phi_2}{-2}\right)}^{2} - t\_1 \cdot t\_0}}\right) \cdot 2
\end{array}
\end{array}
Initial program 62.3%
Applied rewrites62.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(fma
(* (cos phi2) (cos phi1))
(pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)
(pow (sin (* (- phi1 phi2) 0.5)) 2.0))))
(* R (* 2.0 (atan2 (sqrt t_0) (sqrt (- 1.0 t_0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = fma((cos(phi2) * cos(phi1)), pow(sin(((lambda1 - lambda2) * 0.5)), 2.0), pow(sin(((phi1 - phi2) * 0.5)), 2.0));
return R * (2.0 * atan2(sqrt(t_0), sqrt((1.0 - t_0))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = fma(Float64(cos(phi2) * cos(phi1)), (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0), (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(t_0), sqrt(Float64(1.0 - t_0))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] * N[Power[N[Sin[N[(N[(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[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$0], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \mathsf{fma}\left(\cos \phi_2 \cdot \cos \phi_1, {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}, {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0}}{\sqrt{1 - t\_0}}\right)
\end{array}
\end{array}
Initial program 62.3%
Taylor expanded in lambda1 around 0
Applied rewrites62.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
(if (or (<= phi2 -0.000145) (not (<= phi2 5e-12)))
(*
R
(*
2.0
(atan2
(sqrt (fma t_0 (cos phi2) (pow (sin (* -0.5 phi2)) 2.0)))
(sqrt (- (pow (cos (* -0.5 phi2)) 2.0) (* t_0 (cos phi2)))))))
(*
R
(*
2.0
(atan2
(sqrt
(fma
(* t_0 (cos phi1))
(cos phi2)
(pow (sin (* (- phi1 phi2) 0.5)) 2.0)))
(sqrt (- 1.0 (fma t_0 (cos phi1) (pow (sin (* 0.5 phi1)) 2.0))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double tmp;
if ((phi2 <= -0.000145) || !(phi2 <= 5e-12)) {
tmp = R * (2.0 * atan2(sqrt(fma(t_0, cos(phi2), pow(sin((-0.5 * phi2)), 2.0))), sqrt((pow(cos((-0.5 * phi2)), 2.0) - (t_0 * cos(phi2))))));
} else {
tmp = R * (2.0 * atan2(sqrt(fma((t_0 * cos(phi1)), cos(phi2), pow(sin(((phi1 - phi2) * 0.5)), 2.0))), sqrt((1.0 - fma(t_0, cos(phi1), pow(sin((0.5 * phi1)), 2.0))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 tmp = 0.0 if ((phi2 <= -0.000145) || !(phi2 <= 5e-12)) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_0, cos(phi2), (sin(Float64(-0.5 * phi2)) ^ 2.0))), sqrt(Float64((cos(Float64(-0.5 * phi2)) ^ 2.0) - Float64(t_0 * cos(phi2))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(Float64(t_0 * cos(phi1)), cos(phi2), (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0))), sqrt(Float64(1.0 - fma(t_0, cos(phi1), (sin(Float64(0.5 * phi1)) ^ 2.0))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[phi2, -0.000145], N[Not[LessEqual[phi2, 5e-12]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(t$95$0 * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(t$95$0 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] * N[Cos[phi2], $MachinePrecision] + 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$0 * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
\mathbf{if}\;\phi_2 \leq -0.000145 \lor \neg \left(\phi_2 \leq 5 \cdot 10^{-12}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \cos \phi_2, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)}}{\sqrt{{\cos \left(-0.5 \cdot \phi_2\right)}^{2} - t\_0 \cdot \cos \phi_2}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0 \cdot \cos \phi_1, \cos \phi_2, {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left(t\_0, \cos \phi_1, {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)}}\right)\\
\end{array}
\end{array}
if phi2 < -1.45e-4 or 4.9999999999999997e-12 < phi2 Initial program 49.4%
unpow1N/A
sqr-powN/A
pow2N/A
lower-pow.f64N/A
metadata-evalN/A
unpow1/2N/A
lower-sqrt.f6423.3
lift-/.f64N/A
clear-numN/A
associate-/r/N/A
metadata-evalN/A
lower-*.f6423.3
Applied rewrites23.3%
Taylor expanded in phi1 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
Applied rewrites23.6%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6450.9
Applied rewrites50.9%
if -1.45e-4 < phi2 < 4.9999999999999997e-12Initial program 77.1%
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-*.f6477.2
Applied rewrites77.2%
lift-+.f64N/A
+-commutativeN/A
Applied rewrites77.1%
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-*.f6477.1
Applied rewrites77.1%
Final simplification63.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
(if (or (<= phi2 -0.000145) (not (<= phi2 5e-12)))
(*
R
(*
2.0
(atan2
(sqrt (fma t_0 (cos phi2) (pow (sin (* -0.5 phi2)) 2.0)))
(sqrt (- (pow (cos (* -0.5 phi2)) 2.0) (* t_0 (cos phi2)))))))
(*
(*
R
(atan2
(sqrt
(fma
t_0
(* (cos phi2) (cos phi1))
(pow (sin (* (- phi1 phi2) 0.5)) 2.0)))
(sqrt (fma (- (cos phi1)) t_0 (pow (cos (* -0.5 phi1)) 2.0)))))
2.0))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double tmp;
if ((phi2 <= -0.000145) || !(phi2 <= 5e-12)) {
tmp = R * (2.0 * atan2(sqrt(fma(t_0, cos(phi2), pow(sin((-0.5 * phi2)), 2.0))), sqrt((pow(cos((-0.5 * phi2)), 2.0) - (t_0 * cos(phi2))))));
} else {
tmp = (R * atan2(sqrt(fma(t_0, (cos(phi2) * cos(phi1)), pow(sin(((phi1 - phi2) * 0.5)), 2.0))), sqrt(fma(-cos(phi1), t_0, pow(cos((-0.5 * phi1)), 2.0))))) * 2.0;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 tmp = 0.0 if ((phi2 <= -0.000145) || !(phi2 <= 5e-12)) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_0, cos(phi2), (sin(Float64(-0.5 * phi2)) ^ 2.0))), sqrt(Float64((cos(Float64(-0.5 * phi2)) ^ 2.0) - Float64(t_0 * cos(phi2))))))); else tmp = Float64(Float64(R * atan(sqrt(fma(t_0, Float64(cos(phi2) * cos(phi1)), (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0))), sqrt(fma(Float64(-cos(phi1)), t_0, (cos(Float64(-0.5 * phi1)) ^ 2.0))))) * 2.0); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[phi2, -0.000145], N[Not[LessEqual[phi2, 5e-12]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(t$95$0 * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[(R * N[ArcTan[N[Sqrt[N[(t$95$0 * N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[((-N[Cos[phi1], $MachinePrecision]) * t$95$0 + N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * 2.0), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
\mathbf{if}\;\phi_2 \leq -0.000145 \lor \neg \left(\phi_2 \leq 5 \cdot 10^{-12}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \cos \phi_2, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)}}{\sqrt{{\cos \left(-0.5 \cdot \phi_2\right)}^{2} - t\_0 \cdot \cos \phi_2}}\right)\\
\mathbf{else}:\\
\;\;\;\;\left(R \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \cos \phi_2 \cdot \cos \phi_1, {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\right)}}{\sqrt{\mathsf{fma}\left(-\cos \phi_1, t\_0, {\cos \left(-0.5 \cdot \phi_1\right)}^{2}\right)}}\right) \cdot 2\\
\end{array}
\end{array}
if phi2 < -1.45e-4 or 4.9999999999999997e-12 < phi2 Initial program 49.4%
unpow1N/A
sqr-powN/A
pow2N/A
lower-pow.f64N/A
metadata-evalN/A
unpow1/2N/A
lower-sqrt.f6423.3
lift-/.f64N/A
clear-numN/A
associate-/r/N/A
metadata-evalN/A
lower-*.f6423.3
Applied rewrites23.3%
Taylor expanded in phi1 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
Applied rewrites23.6%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6450.9
Applied rewrites50.9%
if -1.45e-4 < phi2 < 4.9999999999999997e-12Initial program 77.1%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites77.1%
Applied rewrites77.1%
Final simplification63.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_1 (* t_0 (cos phi2))))
(if (or (<= phi1 -1.8e-7) (not (<= phi1 5.4e-7)))
(*
R
(*
2.0
(atan2
(sqrt (fma t_0 (cos phi1) (pow (sin (* 0.5 phi1)) 2.0)))
(sqrt (- (pow (cos (* -0.5 phi1)) 2.0) (* t_0 (cos phi1)))))))
(*
R
(*
2.0
(atan2
(sqrt (fma t_1 (cos phi1) (pow (sin (* (- phi1 phi2) 0.5)) 2.0)))
(sqrt (- (pow (cos (* -0.5 phi2)) 2.0) 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 = t_0 * cos(phi2);
double tmp;
if ((phi1 <= -1.8e-7) || !(phi1 <= 5.4e-7)) {
tmp = R * (2.0 * atan2(sqrt(fma(t_0, cos(phi1), pow(sin((0.5 * phi1)), 2.0))), sqrt((pow(cos((-0.5 * phi1)), 2.0) - (t_0 * cos(phi1))))));
} else {
tmp = R * (2.0 * atan2(sqrt(fma(t_1, cos(phi1), pow(sin(((phi1 - phi2) * 0.5)), 2.0))), sqrt((pow(cos((-0.5 * phi2)), 2.0) - 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(t_0 * cos(phi2)) tmp = 0.0 if ((phi1 <= -1.8e-7) || !(phi1 <= 5.4e-7)) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_0, cos(phi1), (sin(Float64(0.5 * phi1)) ^ 2.0))), sqrt(Float64((cos(Float64(-0.5 * phi1)) ^ 2.0) - Float64(t_0 * cos(phi1))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_1, cos(phi1), (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(-0.5 * phi2)) ^ 2.0) - 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[(t$95$0 * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[phi1, -1.8e-7], N[Not[LessEqual[phi1, 5.4e-7]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(t$95$0 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 * N[Cos[phi1], $MachinePrecision] + 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 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - t$95$1), $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 := t\_0 \cdot \cos \phi_2\\
\mathbf{if}\;\phi_1 \leq -1.8 \cdot 10^{-7} \lor \neg \left(\phi_1 \leq 5.4 \cdot 10^{-7}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \cos \phi_1, {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)}}{\sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - t\_0 \cdot \cos \phi_1}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_1, \cos \phi_1, {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\right)}}{\sqrt{{\cos \left(-0.5 \cdot \phi_2\right)}^{2} - t\_1}}\right)\\
\end{array}
\end{array}
if phi1 < -1.79999999999999997e-7 or 5.40000000000000018e-7 < phi1 Initial program 46.3%
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
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites46.9%
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-*.f6419.8
Applied rewrites19.8%
Taylor expanded in phi2 around 0
lower-sqrt.f64N/A
*-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-*.f6447.9
Applied rewrites47.9%
if -1.79999999999999997e-7 < phi1 < 5.40000000000000018e-7Initial program 75.9%
unpow1N/A
sqr-powN/A
pow2N/A
lower-pow.f64N/A
metadata-evalN/A
unpow1/2N/A
lower-sqrt.f6437.9
lift-/.f64N/A
clear-numN/A
associate-/r/N/A
metadata-evalN/A
lower-*.f6437.9
Applied rewrites37.9%
Taylor expanded in phi1 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
Applied rewrites37.9%
Applied rewrites75.9%
Final simplification63.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
(if (or (<= phi1 -2.3e-8) (not (<= phi1 1.02e-9)))
(*
R
(*
2.0
(atan2
(sqrt (fma t_0 (cos phi1) (pow (sin (* 0.5 phi1)) 2.0)))
(sqrt (- (pow (cos (* -0.5 phi1)) 2.0) (* t_0 (cos phi1)))))))
(*
R
(*
2.0
(atan2
(sqrt (fma t_0 (cos phi2) (pow (sin (* -0.5 phi2)) 2.0)))
(sqrt (- (pow (cos (* -0.5 phi2)) 2.0) (* t_0 (cos phi2))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double tmp;
if ((phi1 <= -2.3e-8) || !(phi1 <= 1.02e-9)) {
tmp = R * (2.0 * atan2(sqrt(fma(t_0, cos(phi1), pow(sin((0.5 * phi1)), 2.0))), sqrt((pow(cos((-0.5 * phi1)), 2.0) - (t_0 * cos(phi1))))));
} else {
tmp = R * (2.0 * atan2(sqrt(fma(t_0, cos(phi2), pow(sin((-0.5 * phi2)), 2.0))), sqrt((pow(cos((-0.5 * phi2)), 2.0) - (t_0 * cos(phi2))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 tmp = 0.0 if ((phi1 <= -2.3e-8) || !(phi1 <= 1.02e-9)) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_0, cos(phi1), (sin(Float64(0.5 * phi1)) ^ 2.0))), sqrt(Float64((cos(Float64(-0.5 * phi1)) ^ 2.0) - Float64(t_0 * cos(phi1))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_0, cos(phi2), (sin(Float64(-0.5 * phi2)) ^ 2.0))), sqrt(Float64((cos(Float64(-0.5 * phi2)) ^ 2.0) - Float64(t_0 * cos(phi2))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[phi1, -2.3e-8], N[Not[LessEqual[phi1, 1.02e-9]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(t$95$0 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(t$95$0 * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
\mathbf{if}\;\phi_1 \leq -2.3 \cdot 10^{-8} \lor \neg \left(\phi_1 \leq 1.02 \cdot 10^{-9}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \cos \phi_1, {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)}}{\sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - t\_0 \cdot \cos \phi_1}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \cos \phi_2, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)}}{\sqrt{{\cos \left(-0.5 \cdot \phi_2\right)}^{2} - t\_0 \cdot \cos \phi_2}}\right)\\
\end{array}
\end{array}
if phi1 < -2.3000000000000001e-8 or 1.01999999999999999e-9 < phi1 Initial program 46.3%
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
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites46.9%
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-*.f6419.8
Applied rewrites19.8%
Taylor expanded in phi2 around 0
lower-sqrt.f64N/A
*-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-*.f6447.9
Applied rewrites47.9%
if -2.3000000000000001e-8 < phi1 < 1.01999999999999999e-9Initial program 75.9%
unpow1N/A
sqr-powN/A
pow2N/A
lower-pow.f64N/A
metadata-evalN/A
unpow1/2N/A
lower-sqrt.f6437.9
lift-/.f64N/A
clear-numN/A
associate-/r/N/A
metadata-evalN/A
lower-*.f6437.9
Applied rewrites37.9%
Taylor expanded in phi1 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
Applied rewrites37.9%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6474.9
Applied rewrites74.9%
Final simplification62.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
(*
R
(*
2.0
(atan2
(sqrt (fma t_0 (cos phi1) (pow (sin (* 0.5 phi1)) 2.0)))
(sqrt (- (pow (cos (* -0.5 phi1)) 2.0) (* t_0 (cos phi1)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
return R * (2.0 * atan2(sqrt(fma(t_0, cos(phi1), pow(sin((0.5 * phi1)), 2.0))), sqrt((pow(cos((-0.5 * phi1)), 2.0) - (t_0 * cos(phi1))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 return Float64(R * Float64(2.0 * atan(sqrt(fma(t_0, cos(phi1), (sin(Float64(0.5 * phi1)) ^ 2.0))), sqrt(Float64((cos(Float64(-0.5 * phi1)) ^ 2.0) - Float64(t_0 * cos(phi1))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(t$95$0 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \cos \phi_1, {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)}}{\sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - t\_0 \cdot \cos \phi_1}}\right)
\end{array}
\end{array}
Initial program 62.3%
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
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites47.3%
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-*.f6434.3
Applied rewrites34.3%
Taylor expanded in phi2 around 0
lower-sqrt.f64N/A
*-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-*.f6444.6
Applied rewrites44.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_1 (pow (sin (* -0.5 phi2)) 2.0)))
(if (or (<= lambda1 -1.15e+15) (not (<= lambda1 1.06e-20)))
(*
R
(*
2.0
(atan2
(sqrt (fma (pow (sin (* lambda1 0.5)) 2.0) (cos phi2) t_1))
(sqrt (- 1.0 t_0)))))
(*
R
(*
2.0
(atan2
(sqrt (fma t_0 (cos phi2) t_1))
(sqrt (- 1.0 (pow (sin (* -0.5 lambda2)) 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 = pow(sin((-0.5 * phi2)), 2.0);
double tmp;
if ((lambda1 <= -1.15e+15) || !(lambda1 <= 1.06e-20)) {
tmp = R * (2.0 * atan2(sqrt(fma(pow(sin((lambda1 * 0.5)), 2.0), cos(phi2), t_1)), sqrt((1.0 - t_0))));
} else {
tmp = R * (2.0 * atan2(sqrt(fma(t_0, cos(phi2), t_1)), sqrt((1.0 - pow(sin((-0.5 * lambda2)), 2.0)))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_1 = sin(Float64(-0.5 * phi2)) ^ 2.0 tmp = 0.0 if ((lambda1 <= -1.15e+15) || !(lambda1 <= 1.06e-20)) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma((sin(Float64(lambda1 * 0.5)) ^ 2.0), cos(phi2), t_1)), sqrt(Float64(1.0 - t_0))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_0, cos(phi2), t_1)), sqrt(Float64(1.0 - (sin(Float64(-0.5 * lambda2)) ^ 2.0)))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[lambda1, -1.15e+15], N[Not[LessEqual[lambda1, 1.06e-20]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi2], $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 * N[Cos[phi2], $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(-0.5 * lambda2), $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 := {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\\
\mathbf{if}\;\lambda_1 \leq -1.15 \cdot 10^{+15} \lor \neg \left(\lambda_1 \leq 1.06 \cdot 10^{-20}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left({\sin \left(\lambda_1 \cdot 0.5\right)}^{2}, \cos \phi_2, t\_1\right)}}{\sqrt{1 - t\_0}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \cos \phi_2, t\_1\right)}}{\sqrt{1 - {\sin \left(-0.5 \cdot \lambda_2\right)}^{2}}}\right)\\
\end{array}
\end{array}
if lambda1 < -1.15e15 or 1.06e-20 < lambda1 Initial program 49.4%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites39.9%
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-*.f6432.2
Applied rewrites32.2%
Taylor expanded in phi1 around 0
Applied rewrites31.7%
Taylor expanded in lambda2 around 0
Applied rewrites31.8%
if -1.15e15 < lambda1 < 1.06e-20Initial program 74.9%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites54.7%
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-*.f6436.4
Applied rewrites36.4%
Taylor expanded in phi1 around 0
Applied rewrites35.9%
Taylor expanded in lambda1 around 0
Applied rewrites36.0%
Final simplification33.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* -0.5 phi2)) 2.0))
(t_1 (sqrt (- 1.0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))))
(if (or (<= lambda2 -8.4e-81) (not (<= lambda2 0.00015)))
(*
R
(*
2.0
(atan2
(sqrt (fma (pow (sin (* -0.5 lambda2)) 2.0) (cos phi2) t_0))
t_1)))
(*
R
(*
2.0
(atan2
(sqrt (fma (pow (sin (* lambda1 0.5)) 2.0) (cos phi2) t_0))
t_1))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((-0.5 * phi2)), 2.0);
double t_1 = sqrt((1.0 - pow(sin(((lambda1 - lambda2) * 0.5)), 2.0)));
double tmp;
if ((lambda2 <= -8.4e-81) || !(lambda2 <= 0.00015)) {
tmp = R * (2.0 * atan2(sqrt(fma(pow(sin((-0.5 * lambda2)), 2.0), cos(phi2), t_0)), t_1));
} else {
tmp = R * (2.0 * atan2(sqrt(fma(pow(sin((lambda1 * 0.5)), 2.0), cos(phi2), t_0)), t_1));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(-0.5 * phi2)) ^ 2.0 t_1 = sqrt(Float64(1.0 - (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0))) tmp = 0.0 if ((lambda2 <= -8.4e-81) || !(lambda2 <= 0.00015)) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma((sin(Float64(-0.5 * lambda2)) ^ 2.0), cos(phi2), t_0)), t_1))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(fma((sin(Float64(lambda1 * 0.5)) ^ 2.0), cos(phi2), t_0)), t_1))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(-0.5 * phi2), $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]}, If[Or[LessEqual[lambda2, -8.4e-81], N[Not[LessEqual[lambda2, 0.00015]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi2], $MachinePrecision] + t$95$0), $MachinePrecision]], $MachinePrecision] / t$95$1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi2], $MachinePrecision] + t$95$0), $MachinePrecision]], $MachinePrecision] / t$95$1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\\
t_1 := \sqrt{1 - {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}}\\
\mathbf{if}\;\lambda_2 \leq -8.4 \cdot 10^{-81} \lor \neg \left(\lambda_2 \leq 0.00015\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left({\sin \left(-0.5 \cdot \lambda_2\right)}^{2}, \cos \phi_2, t\_0\right)}}{t\_1}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left({\sin \left(\lambda_1 \cdot 0.5\right)}^{2}, \cos \phi_2, t\_0\right)}}{t\_1}\right)\\
\end{array}
\end{array}
if lambda2 < -8.3999999999999997e-81 or 1.49999999999999987e-4 < lambda2 Initial program 52.1%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites39.9%
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-*.f6431.3
Applied rewrites31.3%
Taylor expanded in phi1 around 0
Applied rewrites30.8%
Taylor expanded in lambda1 around 0
Applied rewrites30.5%
if -8.3999999999999997e-81 < lambda2 < 1.49999999999999987e-4Initial program 75.5%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites57.1%
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-*.f6438.2
Applied rewrites38.2%
Taylor expanded in phi1 around 0
Applied rewrites37.8%
Taylor expanded in lambda2 around 0
Applied rewrites36.8%
Final simplification33.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_1 (pow (sin (* -0.5 phi2)) 2.0))
(t_2 (sqrt (fma t_0 (cos phi2) t_1)))
(t_3 (pow (sin (* lambda1 0.5)) 2.0)))
(if (<= lambda1 -5.6e-39)
(* R (* 2.0 (atan2 t_2 (sqrt (- 1.0 t_3)))))
(if (<= lambda1 1.06e-20)
(*
R
(* 2.0 (atan2 t_2 (sqrt (- 1.0 (pow (sin (* -0.5 lambda2)) 2.0))))))
(*
R
(* 2.0 (atan2 (sqrt (fma t_3 (cos phi2) t_1)) (sqrt (- 1.0 t_0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_1 = pow(sin((-0.5 * phi2)), 2.0);
double t_2 = sqrt(fma(t_0, cos(phi2), t_1));
double t_3 = pow(sin((lambda1 * 0.5)), 2.0);
double tmp;
if (lambda1 <= -5.6e-39) {
tmp = R * (2.0 * atan2(t_2, sqrt((1.0 - t_3))));
} else if (lambda1 <= 1.06e-20) {
tmp = R * (2.0 * atan2(t_2, sqrt((1.0 - pow(sin((-0.5 * lambda2)), 2.0)))));
} else {
tmp = R * (2.0 * atan2(sqrt(fma(t_3, cos(phi2), t_1)), sqrt((1.0 - t_0))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_1 = sin(Float64(-0.5 * phi2)) ^ 2.0 t_2 = sqrt(fma(t_0, cos(phi2), t_1)) t_3 = sin(Float64(lambda1 * 0.5)) ^ 2.0 tmp = 0.0 if (lambda1 <= -5.6e-39) tmp = Float64(R * Float64(2.0 * atan(t_2, sqrt(Float64(1.0 - t_3))))); elseif (lambda1 <= 1.06e-20) tmp = Float64(R * Float64(2.0 * atan(t_2, sqrt(Float64(1.0 - (sin(Float64(-0.5 * lambda2)) ^ 2.0)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_3, cos(phi2), t_1)), sqrt(Float64(1.0 - t_0))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[Sqrt[N[(t$95$0 * N[Cos[phi2], $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Power[N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[LessEqual[lambda1, -5.6e-39], N[(R * N[(2.0 * N[ArcTan[t$95$2 / N[Sqrt[N[(1.0 - t$95$3), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[lambda1, 1.06e-20], N[(R * N[(2.0 * N[ArcTan[t$95$2 / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$3 * N[Cos[phi2], $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_1 := {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\\
t_2 := \sqrt{\mathsf{fma}\left(t\_0, \cos \phi_2, t\_1\right)}\\
t_3 := {\sin \left(\lambda_1 \cdot 0.5\right)}^{2}\\
\mathbf{if}\;\lambda_1 \leq -5.6 \cdot 10^{-39}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_2}{\sqrt{1 - t\_3}}\right)\\
\mathbf{elif}\;\lambda_1 \leq 1.06 \cdot 10^{-20}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{t\_2}{\sqrt{1 - {\sin \left(-0.5 \cdot \lambda_2\right)}^{2}}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_3, \cos \phi_2, t\_1\right)}}{\sqrt{1 - t\_0}}\right)\\
\end{array}
\end{array}
if lambda1 < -5.6000000000000003e-39Initial program 44.7%
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
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites34.6%
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-*.f6427.8
Applied rewrites27.8%
Taylor expanded in phi1 around 0
Applied rewrites27.3%
Taylor expanded in lambda2 around 0
Applied rewrites27.7%
if -5.6000000000000003e-39 < lambda1 < 1.06e-20Initial program 75.7%
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
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites56.2%
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-*.f6437.6
Applied rewrites37.6%
Taylor expanded in phi1 around 0
Applied rewrites37.2%
Taylor expanded in lambda1 around 0
Applied rewrites37.2%
if 1.06e-20 < lambda1 Initial program 57.5%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites45.7%
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-*.f6435.9
Applied rewrites35.9%
Taylor expanded in phi1 around 0
Applied rewrites35.3%
Taylor expanded in lambda2 around 0
Applied rewrites35.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
(*
R
(atan2
(sqrt
(fma
(pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)
(cos phi2)
(pow (sin (* -0.5 phi2)) 2.0)))
(sqrt (pow (cos (/ (- lambda1 lambda2) -2.0)) 2.0))))
2.0))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return (R * atan2(sqrt(fma(pow(sin(((lambda1 - lambda2) * 0.5)), 2.0), cos(phi2), pow(sin((-0.5 * phi2)), 2.0))), sqrt(pow(cos(((lambda1 - lambda2) / -2.0)), 2.0)))) * 2.0;
}
function code(R, lambda1, lambda2, phi1, phi2) return Float64(Float64(R * atan(sqrt(fma((sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0), cos(phi2), (sin(Float64(-0.5 * phi2)) ^ 2.0))), sqrt((cos(Float64(Float64(lambda1 - lambda2) / -2.0)) ^ 2.0)))) * 2.0) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(N[(R * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[Power[N[Cos[N[(N[(lambda1 - lambda2), $MachinePrecision] / -2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * 2.0), $MachinePrecision]
\begin{array}{l}
\\
\left(R \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left({\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}, \cos \phi_2, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)}}{\sqrt{{\cos \left(\frac{\lambda_1 - \lambda_2}{-2}\right)}^{2}}}\right) \cdot 2
\end{array}
Initial program 62.3%
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
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites47.3%
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-*.f6434.3
Applied rewrites34.3%
Taylor expanded in phi1 around 0
Applied rewrites33.8%
lift-*.f64N/A
Applied rewrites33.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
(*
R
(*
2.0
(atan2
(sqrt (fma t_0 (cos phi2) (pow (sin (* -0.5 phi2)) 2.0)))
(sqrt (- 1.0 t_0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
return R * (2.0 * atan2(sqrt(fma(t_0, cos(phi2), pow(sin((-0.5 * phi2)), 2.0))), sqrt((1.0 - t_0))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 return Float64(R * Float64(2.0 * atan(sqrt(fma(t_0, cos(phi2), (sin(Float64(-0.5 * phi2)) ^ 2.0))), sqrt(Float64(1.0 - t_0))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \cos \phi_2, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)}}{\sqrt{1 - t\_0}}\right)
\end{array}
\end{array}
Initial program 62.3%
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
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites47.3%
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-*.f6434.3
Applied rewrites34.3%
Taylor expanded in phi1 around 0
Applied rewrites33.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
(*
R
(*
2.0
(atan2
(sqrt (fma t_0 (cos phi1) (pow (sin (* 0.5 phi1)) 2.0)))
(sqrt (- 1.0 t_0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
return R * (2.0 * atan2(sqrt(fma(t_0, cos(phi1), pow(sin((0.5 * phi1)), 2.0))), sqrt((1.0 - t_0))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 return Float64(R * Float64(2.0 * atan(sqrt(fma(t_0, cos(phi1), (sin(Float64(0.5 * phi1)) ^ 2.0))), sqrt(Float64(1.0 - t_0))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$0 * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \cos \phi_1, {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)}}{\sqrt{1 - t\_0}}\right)
\end{array}
\end{array}
Initial program 62.3%
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
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites47.3%
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-*.f6434.3
Applied rewrites34.3%
Taylor expanded in phi1 around 0
Applied rewrites33.8%
Taylor expanded in phi2 around 0
lower-sqrt.f64N/A
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6432.7
Applied rewrites32.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
R
(*
2.0
(atan2
(sqrt
(fma
(pow (sin (* -0.5 lambda2)) 2.0)
(cos phi2)
(pow (sin (* -0.5 phi2)) 2.0)))
(sqrt (- 1.0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return R * (2.0 * atan2(sqrt(fma(pow(sin((-0.5 * lambda2)), 2.0), cos(phi2), pow(sin((-0.5 * phi2)), 2.0))), sqrt((1.0 - pow(sin(((lambda1 - lambda2) * 0.5)), 2.0)))));
}
function code(R, lambda1, lambda2, phi1, phi2) return Float64(R * Float64(2.0 * atan(sqrt(fma((sin(Float64(-0.5 * lambda2)) ^ 2.0), cos(phi2), (sin(Float64(-0.5 * phi2)) ^ 2.0))), sqrt(Float64(1.0 - (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0)))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $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]), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left({\sin \left(-0.5 \cdot \lambda_2\right)}^{2}, \cos \phi_2, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)}}{\sqrt{1 - {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}}}\right)
\end{array}
Initial program 62.3%
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
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites47.3%
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-*.f6434.3
Applied rewrites34.3%
Taylor expanded in phi1 around 0
Applied rewrites33.8%
Taylor expanded in lambda1 around 0
Applied rewrites25.5%
herbie shell --seed 2024323
(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))))))))))