
(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 (cos (* phi1 0.5)))
(t_1 (sin (* (- phi1 phi2) 0.5)))
(t_2 (sin (/ (- lambda1 lambda2) 2.0)))
(t_3 (sin (* phi1 0.5))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (- (* t_3 (cos (* phi2 0.5))) (* t_0 (sin (* phi2 0.5)))) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_2) t_2)))
(sqrt
(-
(- 1.0 (* (* t_1 (cos (* 0.5 phi2))) t_3))
(fma
(* t_1 (sin (* phi2 -0.5)))
t_0
(*
(pow
(-
(* (sin (* lambda1 0.5)) (cos (* lambda2 0.5)))
(* (cos (* lambda1 0.5)) (sin (* lambda2 0.5))))
2.0)
(* (cos phi2) (cos phi1)))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((phi1 * 0.5));
double t_1 = sin(((phi1 - phi2) * 0.5));
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double t_3 = sin((phi1 * 0.5));
return R * (2.0 * atan2(sqrt((pow(((t_3 * cos((phi2 * 0.5))) - (t_0 * sin((phi2 * 0.5)))), 2.0) + (((cos(phi1) * cos(phi2)) * t_2) * t_2))), sqrt(((1.0 - ((t_1 * cos((0.5 * phi2))) * t_3)) - fma((t_1 * sin((phi2 * -0.5))), t_0, (pow(((sin((lambda1 * 0.5)) * cos((lambda2 * 0.5))) - (cos((lambda1 * 0.5)) * sin((lambda2 * 0.5)))), 2.0) * (cos(phi2) * cos(phi1))))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(phi1 * 0.5)) t_1 = sin(Float64(Float64(phi1 - phi2) * 0.5)) t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_3 = sin(Float64(phi1 * 0.5)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((Float64(Float64(t_3 * cos(Float64(phi2 * 0.5))) - Float64(t_0 * sin(Float64(phi2 * 0.5)))) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_2) * t_2))), sqrt(Float64(Float64(1.0 - Float64(Float64(t_1 * cos(Float64(0.5 * phi2))) * t_3)) - fma(Float64(t_1 * sin(Float64(phi2 * -0.5))), t_0, Float64((Float64(Float64(sin(Float64(lambda1 * 0.5)) * cos(Float64(lambda2 * 0.5))) - Float64(cos(Float64(lambda1 * 0.5)) * sin(Float64(lambda2 * 0.5)))) ^ 2.0) * Float64(cos(phi2) * cos(phi1))))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[(t$95$3 * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(t$95$0 * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$2), $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[(N[(t$95$1 * N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * t$95$3), $MachinePrecision]), $MachinePrecision] - N[(N[(t$95$1 * N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * t$95$0 + N[(N[Power[N[(N[(N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(lambda2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(lambda2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] * N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_1 := \sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_3 := \sin \left(\phi_1 \cdot 0.5\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(t\_3 \cdot \cos \left(\phi_2 \cdot 0.5\right) - t\_0 \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_2\right) \cdot t\_2}}{\sqrt{\left(1 - \left(t\_1 \cdot \cos \left(0.5 \cdot \phi_2\right)\right) \cdot t\_3\right) - \mathsf{fma}\left(t\_1 \cdot \sin \left(\phi_2 \cdot -0.5\right), t\_0, {\left(\sin \left(\lambda_1 \cdot 0.5\right) \cdot \cos \left(\lambda_2 \cdot 0.5\right) - \cos \left(\lambda_1 \cdot 0.5\right) \cdot \sin \left(\lambda_2 \cdot 0.5\right)\right)}^{2} \cdot \left(\cos \phi_2 \cdot \cos \phi_1\right)\right)}}\right)
\end{array}
\end{array}
Initial program 66.5%
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%
Applied rewrites68.5%
Applied rewrites68.5%
lift-sin.f64N/A
lift-*.f64N/A
metadata-evalN/A
div-invN/A
lift--.f64N/A
div-subN/A
sin-diffN/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
lift-cos.f64N/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
lift-sin.f64N/A
*-commutativeN/A
lower--.f64N/A
Applied rewrites68.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (* 0.5 phi1)))
(t_1 (sin (* 0.5 phi1)))
(t_2 (pow (sin (* (- lambda2 lambda1) -0.5)) 2.0))
(t_3 (cos (* 0.5 phi2))))
(*
(* 2.0 R)
(atan2
(sqrt
(fma
(* t_2 (cos phi2))
(cos phi1)
(pow (fma t_1 t_3 (* (- (sin (* 0.5 phi2))) t_0)) 2.0)))
(sqrt
(-
1.0
(fma
(* (cos phi1) (cos phi2))
t_2
(*
(sin (* (- phi1 phi2) 0.5))
(fma t_1 t_3 (* t_0 (sin (* -0.5 phi2))))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((0.5 * phi1));
double t_1 = sin((0.5 * phi1));
double t_2 = pow(sin(((lambda2 - lambda1) * -0.5)), 2.0);
double t_3 = cos((0.5 * phi2));
return (2.0 * R) * atan2(sqrt(fma((t_2 * cos(phi2)), cos(phi1), pow(fma(t_1, t_3, (-sin((0.5 * phi2)) * t_0)), 2.0))), sqrt((1.0 - fma((cos(phi1) * cos(phi2)), t_2, (sin(((phi1 - phi2) * 0.5)) * fma(t_1, t_3, (t_0 * sin((-0.5 * phi2)))))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(0.5 * phi1)) t_1 = sin(Float64(0.5 * phi1)) t_2 = sin(Float64(Float64(lambda2 - lambda1) * -0.5)) ^ 2.0 t_3 = cos(Float64(0.5 * phi2)) return Float64(Float64(2.0 * R) * atan(sqrt(fma(Float64(t_2 * cos(phi2)), cos(phi1), (fma(t_1, t_3, Float64(Float64(-sin(Float64(0.5 * phi2))) * t_0)) ^ 2.0))), sqrt(Float64(1.0 - fma(Float64(cos(phi1) * cos(phi2)), t_2, Float64(sin(Float64(Float64(phi1 - phi2) * 0.5)) * fma(t_1, t_3, Float64(t_0 * sin(Float64(-0.5 * phi2)))))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(N[(lambda2 - lambda1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$3 = N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]}, N[(N[(2.0 * R), $MachinePrecision] * N[ArcTan[N[Sqrt[N[(N[(t$95$2 * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[Cos[phi1], $MachinePrecision] + N[Power[N[(t$95$1 * t$95$3 + N[((-N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]) * t$95$0), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$2 + N[(N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision] * N[(t$95$1 * t$95$3 + N[(t$95$0 * N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(0.5 \cdot \phi_1\right)\\
t_1 := \sin \left(0.5 \cdot \phi_1\right)\\
t_2 := {\sin \left(\left(\lambda_2 - \lambda_1\right) \cdot -0.5\right)}^{2}\\
t_3 := \cos \left(0.5 \cdot \phi_2\right)\\
\left(2 \cdot R\right) \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_2 \cdot \cos \phi_2, \cos \phi_1, {\left(\mathsf{fma}\left(t\_1, t\_3, \left(-\sin \left(0.5 \cdot \phi_2\right)\right) \cdot t\_0\right)\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1 \cdot \cos \phi_2, t\_2, \sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right) \cdot \mathsf{fma}\left(t\_1, t\_3, t\_0 \cdot \sin \left(-0.5 \cdot \phi_2\right)\right)\right)}}
\end{array}
\end{array}
Initial program 66.5%
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%
Applied rewrites68.5%
Applied rewrites68.5%
Taylor expanded in lambda1 around -inf
Applied rewrites68.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (* (* (* (cos phi1) (cos phi2)) t_1) t_1))
(t_3 (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) t_2)))
(if (<= t_3 0.002)
(*
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 (+ (- 0.5 (* 0.5 (cos (* 2.0 (* 0.5 (- phi1 phi2)))))) t_2))
(sqrt (- 1.0 t_3))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = ((cos(phi1) * cos(phi2)) * t_1) * t_1;
double t_3 = pow(sin(((phi1 - phi2) / 2.0)), 2.0) + t_2;
double tmp;
if (t_3 <= 0.002) {
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(((0.5 - (0.5 * cos((2.0 * (0.5 * (phi1 - phi2)))))) + t_2)), sqrt((1.0 - t_3))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_1) * t_1) t_3 = Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + t_2) tmp = 0.0 if (t_3 <= 0.002) 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(Float64(Float64(0.5 - Float64(0.5 * cos(Float64(2.0 * Float64(0.5 * Float64(phi1 - phi2)))))) + t_2)), sqrt(Float64(1.0 - t_3))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$1), $MachinePrecision] * t$95$1), $MachinePrecision]}, Block[{t$95$3 = N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$2), $MachinePrecision]}, If[LessEqual[t$95$3, 0.002], 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[(N[(0.5 - N[(0.5 * N[Cos[N[(2.0 * N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$2), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$3), $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(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_1\right) \cdot t\_1\\
t_3 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_2\\
\mathbf{if}\;t\_3 \leq 0.002:\\
\;\;\;\;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{\left(0.5 - 0.5 \cdot \cos \left(2 \cdot \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\right)\right) + t\_2}}{\sqrt{1 - t\_3}}\right)\\
\end{array}
\end{array}
if (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))))) < 2e-3Initial program 51.1%
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 rewrites51.1%
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-*.f6442.2
Applied rewrites42.2%
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-*.f6456.1
Applied rewrites56.1%
if 2e-3 < (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))))) Initial program 68.3%
lift-pow.f64N/A
unpow2N/A
lift-sin.f64N/A
lift-sin.f64N/A
sqr-sin-aN/A
lower--.f64N/A
cos-2N/A
cos-sumN/A
lower-*.f64N/A
cos-sumN/A
cos-2N/A
lower-cos.f64N/A
lower-*.f6468.1
lift-/.f64N/A
clear-numN/A
associate-/r/N/A
metadata-evalN/A
lower-*.f6468.1
Applied rewrites68.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (sqrt (- (pow (cos (* -0.5 phi1)) 2.0) (* t_0 (cos phi1)))))
(t_3 (* (* (* (cos phi1) (cos phi2)) t_1) t_1)))
(if (<= (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) t_3) 4e-20)
(*
R
(*
2.0
(atan2 (sqrt (fma t_0 (cos phi1) (pow (sin (* 0.5 phi1)) 2.0))) t_2)))
(*
R
(*
2.0
(atan2
(sqrt (+ (- 0.5 (* 0.5 (cos (* 2.0 (* (- phi1 phi2) 0.5))))) t_3))
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 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = sqrt((pow(cos((-0.5 * phi1)), 2.0) - (t_0 * cos(phi1))));
double t_3 = ((cos(phi1) * cos(phi2)) * t_1) * t_1;
double tmp;
if ((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + t_3) <= 4e-20) {
tmp = R * (2.0 * atan2(sqrt(fma(t_0, cos(phi1), pow(sin((0.5 * phi1)), 2.0))), t_2));
} else {
tmp = R * (2.0 * atan2(sqrt(((0.5 - (0.5 * cos((2.0 * ((phi1 - phi2) * 0.5))))) + t_3)), t_2));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = sqrt(Float64((cos(Float64(-0.5 * phi1)) ^ 2.0) - Float64(t_0 * cos(phi1)))) t_3 = Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_1) * t_1) tmp = 0.0 if (Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + t_3) <= 4e-20) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_0, cos(phi1), (sin(Float64(0.5 * phi1)) ^ 2.0))), t_2))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(0.5 - Float64(0.5 * cos(Float64(2.0 * Float64(Float64(phi1 - phi2) * 0.5))))) + t_3)), 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[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = 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]}, Block[{t$95$3 = N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$1), $MachinePrecision] * t$95$1), $MachinePrecision]}, If[LessEqual[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$3), $MachinePrecision], 4e-20], 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] / t$95$2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(0.5 - N[(0.5 * N[Cos[N[(2.0 * N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$3), $MachinePrecision]], $MachinePrecision] / t$95$2], $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(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - t\_0 \cdot \cos \phi_1}\\
t_3 := \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_1\right) \cdot t\_1\\
\mathbf{if}\;{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_3 \leq 4 \cdot 10^{-20}:\\
\;\;\;\;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)}}{t\_2}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\left(0.5 - 0.5 \cdot \cos \left(2 \cdot \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)\right)\right) + t\_3}}{t\_2}\right)\\
\end{array}
\end{array}
if (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))))) < 3.99999999999999978e-20Initial 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 rewrites52.1%
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-*.f6442.6
Applied rewrites42.6%
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-*.f6457.5
Applied rewrites57.5%
if 3.99999999999999978e-20 < (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))))) Initial program 68.0%
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
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites49.0%
lift-pow.f64N/A
unpow2N/A
lift-sin.f64N/A
lift-sin.f64N/A
sqr-sin-aN/A
lower--.f64N/A
cos-2N/A
cos-sumN/A
lower-*.f64N/A
cos-sumN/A
cos-2N/A
lower-cos.f64N/A
lower-*.f6448.9
lift-/.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f6448.9
Applied rewrites48.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* (- lambda1 lambda2) 0.5)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow
(-
(* (sin (* phi1 0.5)) (cos (* phi2 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0)
(* (* (* (cos phi1) (cos phi2)) t_1) t_1)))
(sqrt
(fma
(* (* t_0 (cos phi1)) (cos phi2))
(- t_0)
(pow (cos (* -0.5 (- phi1 phi2))) 2.0))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) * 0.5));
double t_1 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((pow(((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0) + (((cos(phi1) * cos(phi2)) * t_1) * t_1))), sqrt(fma(((t_0 * cos(phi1)) * cos(phi2)), -t_0, pow(cos((-0.5 * (phi1 - phi2))), 2.0)))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((Float64(Float64(sin(Float64(phi1 * 0.5)) * cos(Float64(phi2 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_1) * t_1))), sqrt(fma(Float64(Float64(t_0 * cos(phi1)) * cos(phi2)), Float64(-t_0), (cos(Float64(-0.5 * Float64(phi1 - phi2))) ^ 2.0)))))) 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[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[(N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$1), $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(N[(t$95$0 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * (-t$95$0) + N[Power[N[Cos[N[(-0.5 * N[(phi1 - phi2), $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)\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\sin \left(\phi_1 \cdot 0.5\right) \cdot \cos \left(\phi_2 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_1\right) \cdot t\_1}}{\sqrt{\mathsf{fma}\left(\left(t\_0 \cdot \cos \phi_1\right) \cdot \cos \phi_2, -t\_0, {\cos \left(-0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 66.5%
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%
Applied rewrites68.5%
Applied rewrites68.5%
Applied rewrites67.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow
(-
(* (sin (* phi1 0.5)) (cos (* phi2 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0)
(* (* (* (cos phi1) (cos phi2)) t_0) t_0)))
(sqrt
(+
(fma
(* (- (cos phi1)) (cos phi2))
(pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)
0.5)
(* (cos (* (- phi1 phi2) -1.0)) 0.5))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((pow(((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0))), sqrt((fma((-cos(phi1) * cos(phi2)), pow(sin(((lambda1 - lambda2) * 0.5)), 2.0), 0.5) + (cos(((phi1 - phi2) * -1.0)) * 0.5)))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((Float64(Float64(sin(Float64(phi1 * 0.5)) * cos(Float64(phi2 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0))), sqrt(Float64(fma(Float64(Float64(-cos(phi1)) * cos(phi2)), (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0), 0.5) + Float64(cos(Float64(Float64(phi1 - phi2) * -1.0)) * 0.5)))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[(N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(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] + 0.5), $MachinePrecision] + N[(N[Cos[N[(N[(phi1 - phi2), $MachinePrecision] * -1.0), $MachinePrecision]], $MachinePrecision] * 0.5), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\sin \left(\phi_1 \cdot 0.5\right) \cdot \cos \left(\phi_2 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) \cdot t\_0}}{\sqrt{\mathsf{fma}\left(\left(-\cos \phi_1\right) \cdot \cos \phi_2, {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}, 0.5\right) + \cos \left(\left(\phi_1 - \phi_2\right) \cdot -1\right) \cdot 0.5}}\right)
\end{array}
\end{array}
Initial program 66.5%
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%
Applied rewrites68.5%
Applied rewrites68.5%
Applied rewrites67.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow
(-
(* (sin (* phi1 0.5)) (cos (* phi2 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0)
(* (* (* (cos phi1) (cos phi2)) t_0) t_0)))
(sqrt
(fma
(+ (cos (- phi1 phi2)) 1.0)
0.5
(*
(* (- (cos phi2)) (cos phi1))
(pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
return R * (2.0 * atan2(sqrt((pow(((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0))), sqrt(fma((cos((phi1 - phi2)) + 1.0), 0.5, ((-cos(phi2) * cos(phi1)) * pow(sin(((lambda1 - lambda2) * 0.5)), 2.0))))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(R * Float64(2.0 * atan(sqrt(Float64((Float64(Float64(sin(Float64(phi1 * 0.5)) * cos(Float64(phi2 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0))), sqrt(fma(Float64(cos(Float64(phi1 - phi2)) + 1.0), 0.5, Float64(Float64(Float64(-cos(phi2)) * cos(phi1)) * (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0))))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[(N[(N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] + 1.0), $MachinePrecision] * 0.5 + 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]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\left(\sin \left(\phi_1 \cdot 0.5\right) \cdot \cos \left(\phi_2 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) \cdot t\_0}}{\sqrt{\mathsf{fma}\left(\cos \left(\phi_1 - \phi_2\right) + 1, 0.5, \left(\left(-\cos \phi_2\right) \cdot \cos \phi_1\right) \cdot {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\right)}}\right)
\end{array}
\end{array}
Initial program 66.5%
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%
Applied rewrites68.5%
Applied rewrites67.8%
Final simplification67.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi2) (cos phi1)))
(t_1 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
(*
(atan2
(sqrt (fma t_1 t_0 (pow (sin (* 0.5 (- phi1 phi2))) 2.0)))
(sqrt (- (pow (cos (/ (- phi1 phi2) -2.0)) 2.0) (* t_1 t_0))))
(* R 2.0))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi2) * cos(phi1);
double t_1 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
return atan2(sqrt(fma(t_1, t_0, pow(sin((0.5 * (phi1 - phi2))), 2.0))), sqrt((pow(cos(((phi1 - phi2) / -2.0)), 2.0) - (t_1 * t_0)))) * (R * 2.0);
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi2) * cos(phi1)) t_1 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 return Float64(atan(sqrt(fma(t_1, t_0, (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0))), sqrt(Float64((cos(Float64(Float64(phi1 - phi2) / -2.0)) ^ 2.0) - Float64(t_1 * t_0)))) * Float64(R * 2.0)) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(N[ArcTan[N[Sqrt[N[(t$95$1 * t$95$0 + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(N[(phi1 - phi2), $MachinePrecision] / -2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(t$95$1 * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(R * 2.0), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_2 \cdot \cos \phi_1\\
t_1 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_1, t\_0, {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}}{\sqrt{{\cos \left(\frac{\phi_1 - \phi_2}{-2}\right)}^{2} - t\_1 \cdot t\_0}} \cdot \left(R \cdot 2\right)
\end{array}
\end{array}
Initial program 66.5%
Applied rewrites66.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (* (* (cos phi1) (cos phi2)) t_0) t_0)))
(*
R
(*
2.0
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) t_1))
(sqrt
(-
1.0
(+ (- 0.5 (* 0.5 (cos (* 2.0 (* 0.5 (- phi1 phi2)))))) t_1))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = ((cos(phi1) * cos(phi2)) * t_0) * t_0;
return R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), sqrt((1.0 - ((0.5 - (0.5 * cos((2.0 * (0.5 * (phi1 - phi2)))))) + t_1)))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = ((cos(phi1) * cos(phi2)) * t_0) * t_0
code = r * (2.0d0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + t_1)), sqrt((1.0d0 - ((0.5d0 - (0.5d0 * cos((2.0d0 * (0.5d0 * (phi1 - phi2)))))) + t_1)))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = ((Math.cos(phi1) * Math.cos(phi2)) * t_0) * t_0;
return R * (2.0 * Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), Math.sqrt((1.0 - ((0.5 - (0.5 * Math.cos((2.0 * (0.5 * (phi1 - phi2)))))) + t_1)))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = ((math.cos(phi1) * math.cos(phi2)) * t_0) * t_0 return R * (2.0 * math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), math.sqrt((1.0 - ((0.5 - (0.5 * math.cos((2.0 * (0.5 * (phi1 - phi2)))))) + t_1)))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0) return Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + t_1)), sqrt(Float64(1.0 - Float64(Float64(0.5 - Float64(0.5 * cos(Float64(2.0 * Float64(0.5 * Float64(phi1 - phi2)))))) + t_1)))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = ((cos(phi1) * cos(phi2)) * t_0) * t_0; tmp = R * (2.0 * atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + t_1)), sqrt((1.0 - ((0.5 - (0.5 * cos((2.0 * (0.5 * (phi1 - phi2)))))) + t_1))))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(0.5 - N[(0.5 * N[Cos[N[(2.0 * N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) \cdot t\_0\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_1}}{\sqrt{1 - \left(\left(0.5 - 0.5 \cdot \cos \left(2 \cdot \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\right)\right) + t\_1\right)}}\right)
\end{array}
\end{array}
Initial program 66.5%
lift-pow.f64N/A
unpow2N/A
lift-sin.f64N/A
lift-sin.f64N/A
sqr-sin-aN/A
lower--.f64N/A
cos-2N/A
cos-sumN/A
lower-*.f64N/A
cos-sumN/A
cos-2N/A
lower-cos.f64N/A
lower-*.f6466.5
lift-/.f64N/A
clear-numN/A
associate-/r/N/A
metadata-evalN/A
lower-*.f6466.5
Applied rewrites66.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_1 (sin (/ (- lambda1 lambda2) 2.0))))
(if (or (<= phi1 -1.1) (not (<= phi1 0.0036)))
(*
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
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_1) t_1)))
(sqrt (- (pow (cos (* 0.5 phi2)) 2.0) (* t_0 (cos phi2))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((phi1 <= -1.1) || !(phi1 <= 0.0036)) {
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((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi1) * cos(phi2)) * t_1) * t_1))), sqrt((pow(cos((0.5 * phi2)), 2.0) - (t_0 * cos(phi2))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if ((phi1 <= -1.1) || !(phi1 <= 0.0036)) 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(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_1) * t_1))), sqrt(Float64((cos(Float64(0.5 * phi2)) ^ 2.0) - Float64(t_0 * cos(phi2))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[phi1, -1.1], N[Not[LessEqual[phi1, 0.0036]], $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[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$1), $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(t$95$0 * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\phi_1 \leq -1.1 \lor \neg \left(\phi_1 \leq 0.0036\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{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_1\right) \cdot t\_1}}{\sqrt{{\cos \left(0.5 \cdot \phi_2\right)}^{2} - t\_0 \cdot \cos \phi_2}}\right)\\
\end{array}
\end{array}
if phi1 < -1.1000000000000001 or 0.0035999999999999999 < phi1 Initial program 48.7%
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 rewrites49.9%
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-*.f6419.2
Applied rewrites19.2%
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-*.f6451.6
Applied rewrites51.6%
if -1.1000000000000001 < phi1 < 0.0035999999999999999Initial program 85.7%
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
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites85.6%
Final simplification67.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (/ (- phi1 phi2) -2.0)))
(t_1 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_2 (sin (/ (- lambda1 lambda2) 2.0))))
(if (or (<= phi2 -0.0068) (not (<= phi2 1.36e-5)))
(*
R
(*
2.0
(atan2
(sqrt (fma t_1 (cos phi2) (pow (sin (* -0.5 phi2)) 2.0)))
(sqrt
(fma
t_0
t_0
(*
(* (- (cos phi2)) (cos phi1))
(pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_2) t_2)))
(sqrt (- (pow (cos (* -0.5 phi1)) 2.0) (* t_1 (cos phi1))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(((phi1 - phi2) / -2.0));
double t_1 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if ((phi2 <= -0.0068) || !(phi2 <= 1.36e-5)) {
tmp = R * (2.0 * atan2(sqrt(fma(t_1, cos(phi2), pow(sin((-0.5 * phi2)), 2.0))), sqrt(fma(t_0, t_0, ((-cos(phi2) * cos(phi1)) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi1) * cos(phi2)) * t_2) * t_2))), sqrt((pow(cos((-0.5 * phi1)), 2.0) - (t_1 * cos(phi1))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(Float64(phi1 - phi2) / -2.0)) t_1 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if ((phi2 <= -0.0068) || !(phi2 <= 1.36e-5)) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_1, cos(phi2), (sin(Float64(-0.5 * phi2)) ^ 2.0))), sqrt(fma(t_0, t_0, Float64(Float64(Float64(-cos(phi2)) * cos(phi1)) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_2) * t_2))), sqrt(Float64((cos(Float64(-0.5 * phi1)) ^ 2.0) - Float64(t_1 * cos(phi1))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(N[(phi1 - phi2), $MachinePrecision] / -2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[Or[LessEqual[phi2, -0.0068], N[Not[LessEqual[phi2, 1.36e-5]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(t$95$0 * t$95$0 + N[(N[((-N[Cos[phi2], $MachinePrecision]) * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(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$2), $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(t$95$1 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(\frac{\phi_1 - \phi_2}{-2}\right)\\
t_1 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\phi_2 \leq -0.0068 \lor \neg \left(\phi_2 \leq 1.36 \cdot 10^{-5}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_1, \cos \phi_2, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)}}{\sqrt{\mathsf{fma}\left(t\_0, t\_0, \left(\left(-\cos \phi_2\right) \cdot \cos \phi_1\right) \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_2\right) \cdot t\_2}}{\sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - t\_1 \cdot \cos \phi_1}}\right)\\
\end{array}
\end{array}
if phi2 < -0.00679999999999999962 or 1.36000000000000002e-5 < phi2 Initial program 52.3%
lift--.f64N/A
lift-+.f64N/A
associate--r+N/A
lift-*.f64N/A
lift-*.f64N/A
associate-*l*N/A
cancel-sign-sub-invN/A
Applied rewrites52.4%
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-*.f6454.2
Applied rewrites54.2%
if -0.00679999999999999962 < phi2 < 1.36000000000000002e-5Initial program 82.8%
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 rewrites82.9%
Final simplification67.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (/ (- phi1 phi2) -2.0)))
(t_1 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
(if (or (<= phi2 -0.0068) (not (<= phi2 5.8e-29)))
(*
R
(*
2.0
(atan2
(sqrt (fma t_1 (cos phi2) (pow (sin (* -0.5 phi2)) 2.0)))
(sqrt
(fma
t_0
t_0
(*
(* (- (cos phi2)) (cos phi1))
(pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt (fma t_1 (cos phi1) (pow (sin (* 0.5 phi1)) 2.0)))
(sqrt (- (pow (cos (* -0.5 phi1)) 2.0) (* t_1 (cos phi1))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(((phi1 - phi2) / -2.0));
double t_1 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double tmp;
if ((phi2 <= -0.0068) || !(phi2 <= 5.8e-29)) {
tmp = R * (2.0 * atan2(sqrt(fma(t_1, cos(phi2), pow(sin((-0.5 * phi2)), 2.0))), sqrt(fma(t_0, t_0, ((-cos(phi2) * cos(phi1)) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt(fma(t_1, cos(phi1), pow(sin((0.5 * phi1)), 2.0))), sqrt((pow(cos((-0.5 * phi1)), 2.0) - (t_1 * cos(phi1))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(Float64(phi1 - phi2) / -2.0)) t_1 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 tmp = 0.0 if ((phi2 <= -0.0068) || !(phi2 <= 5.8e-29)) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_1, cos(phi2), (sin(Float64(-0.5 * phi2)) ^ 2.0))), sqrt(fma(t_0, t_0, Float64(Float64(Float64(-cos(phi2)) * cos(phi1)) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_1, cos(phi1), (sin(Float64(0.5 * phi1)) ^ 2.0))), sqrt(Float64((cos(Float64(-0.5 * phi1)) ^ 2.0) - Float64(t_1 * cos(phi1))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(N[(phi1 - phi2), $MachinePrecision] / -2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[phi2, -0.0068], N[Not[LessEqual[phi2, 5.8e-29]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(t$95$0 * t$95$0 + N[(N[((-N[Cos[phi2], $MachinePrecision]) * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $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[(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$1 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(\frac{\phi_1 - \phi_2}{-2}\right)\\
t_1 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
\mathbf{if}\;\phi_2 \leq -0.0068 \lor \neg \left(\phi_2 \leq 5.8 \cdot 10^{-29}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_1, \cos \phi_2, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)}}{\sqrt{\mathsf{fma}\left(t\_0, t\_0, \left(\left(-\cos \phi_2\right) \cdot \cos \phi_1\right) \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_1, \cos \phi_1, {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)}}{\sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - t\_1 \cdot \cos \phi_1}}\right)\\
\end{array}
\end{array}
if phi2 < -0.00679999999999999962 or 5.80000000000000048e-29 < phi2 Initial program 52.9%
lift--.f64N/A
lift-+.f64N/A
associate--r+N/A
lift-*.f64N/A
lift-*.f64N/A
associate-*l*N/A
cancel-sign-sub-invN/A
Applied rewrites52.9%
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-*.f6454.4
Applied rewrites54.4%
if -0.00679999999999999962 < phi2 < 5.80000000000000048e-29Initial program 83.1%
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 rewrites83.2%
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-*.f6441.9
Applied rewrites41.9%
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-*.f6483.3
Applied rewrites83.3%
Final simplification67.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
(if (or (<= phi2 -0.0068) (not (<= phi2 3.45e-6)))
(*
R
(*
2.0
(atan2
(sqrt
(+
(- 0.5 (* 0.5 (cos (* 2.0 (* (- phi1 phi2) 0.5)))))
(* (* (* (cos phi1) (cos phi2)) t_0) t_0)))
(sqrt (- 1.0 (fma t_1 (cos phi2) (pow (sin (* -0.5 phi2)) 2.0)))))))
(*
R
(*
2.0
(atan2
(sqrt (fma t_1 (cos phi1) (pow (sin (* 0.5 phi1)) 2.0)))
(sqrt (- (pow (cos (* -0.5 phi1)) 2.0) (* t_1 (cos phi1))))))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double tmp;
if ((phi2 <= -0.0068) || !(phi2 <= 3.45e-6)) {
tmp = R * (2.0 * atan2(sqrt(((0.5 - (0.5 * cos((2.0 * ((phi1 - phi2) * 0.5))))) + (((cos(phi1) * cos(phi2)) * t_0) * t_0))), sqrt((1.0 - fma(t_1, cos(phi2), pow(sin((-0.5 * phi2)), 2.0))))));
} else {
tmp = R * (2.0 * atan2(sqrt(fma(t_1, cos(phi1), pow(sin((0.5 * phi1)), 2.0))), sqrt((pow(cos((-0.5 * phi1)), 2.0) - (t_1 * cos(phi1))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 tmp = 0.0 if ((phi2 <= -0.0068) || !(phi2 <= 3.45e-6)) tmp = Float64(R * Float64(2.0 * atan(sqrt(Float64(Float64(0.5 - Float64(0.5 * cos(Float64(2.0 * Float64(Float64(phi1 - phi2) * 0.5))))) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0))), sqrt(Float64(1.0 - fma(t_1, cos(phi2), (sin(Float64(-0.5 * phi2)) ^ 2.0))))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_1, cos(phi1), (sin(Float64(0.5 * phi1)) ^ 2.0))), sqrt(Float64((cos(Float64(-0.5 * phi1)) ^ 2.0) - Float64(t_1 * cos(phi1))))))); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[phi2, -0.0068], N[Not[LessEqual[phi2, 3.45e-6]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[(0.5 - N[(0.5 * N[Cos[N[(2.0 * N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] + N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$1 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(t$95$1 * 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$1 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
\mathbf{if}\;\phi_2 \leq -0.0068 \lor \neg \left(\phi_2 \leq 3.45 \cdot 10^{-6}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\left(0.5 - 0.5 \cdot \cos \left(2 \cdot \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)\right)\right) + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) \cdot t\_0}}{\sqrt{1 - \mathsf{fma}\left(t\_1, \cos \phi_2, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_1, \cos \phi_1, {\sin \left(0.5 \cdot \phi_1\right)}^{2}\right)}}{\sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - t\_1 \cdot \cos \phi_1}}\right)\\
\end{array}
\end{array}
if phi2 < -0.00679999999999999962 or 3.45e-6 < phi2 Initial program 52.3%
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-*.f6454.0
Applied rewrites54.0%
lift-pow.f64N/A
unpow2N/A
lift-sin.f64N/A
lift-sin.f64N/A
sqr-sin-aN/A
lower--.f64N/A
cos-2N/A
cos-sumN/A
lower-*.f64N/A
cos-sumN/A
cos-2N/A
lower-cos.f64N/A
lower-*.f6453.9
lift-/.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f6453.9
Applied rewrites53.9%
Taylor expanded in phi1 around 0
*-commutativeN/A
distribute-lft-neg-inN/A
metadata-evalN/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-*.f6453.2
Applied rewrites53.2%
if -0.00679999999999999962 < phi2 < 3.45e-6Initial program 82.8%
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 rewrites82.9%
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-*.f6442.5
Applied rewrites42.5%
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-*.f6482.1
Applied rewrites82.1%
Final simplification66.6%
(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 66.5%
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 rewrites49.3%
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-*.f6431.5
Applied rewrites31.5%
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-*.f6447.9
Applied rewrites47.9%
(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 -8.6e-33) (not (<= lambda2 1.28e-33)))
(*
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 (* 0.5 lambda1)) 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 <= -8.6e-33) || !(lambda2 <= 1.28e-33)) {
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((0.5 * lambda1)), 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 <= -8.6e-33) || !(lambda2 <= 1.28e-33)) 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(0.5 * lambda1)) ^ 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, -8.6e-33], N[Not[LessEqual[lambda2, 1.28e-33]], $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[(0.5 * lambda1), $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 -8.6 \cdot 10^{-33} \lor \neg \left(\lambda_2 \leq 1.28 \cdot 10^{-33}\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(0.5 \cdot \lambda_1\right)}^{2}, \cos \phi_2, t\_0\right)}}{t\_1}\right)\\
\end{array}
\end{array}
if lambda2 < -8.60000000000000062e-33 or 1.28000000000000001e-33 < lambda2 Initial program 56.5%
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 rewrites43.7%
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-*.f6430.9
Applied rewrites30.9%
Taylor expanded in phi1 around 0
Applied rewrites30.4%
Taylor expanded in lambda1 around 0
Applied rewrites30.2%
if -8.60000000000000062e-33 < lambda2 < 1.28000000000000001e-33Initial program 78.9%
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 rewrites56.3%
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-*.f6432.2
Applied rewrites32.2%
Taylor expanded in phi1 around 0
Applied rewrites31.8%
Taylor expanded in lambda2 around 0
Applied rewrites30.8%
Final simplification30.5%
(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 3.6e-29)
(*
R
(*
2.0
(atan2 (sqrt (fma t_0 (cos phi1) (pow (sin (* 0.5 phi1)) 2.0))) t_1)))
(*
R
(*
2.0
(atan2
(sqrt (fma t_0 (cos phi2) (pow (sin (* -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 = sqrt((1.0 - t_0));
double tmp;
if (phi2 <= 3.6e-29) {
tmp = R * (2.0 * atan2(sqrt(fma(t_0, cos(phi1), pow(sin((0.5 * phi1)), 2.0))), t_1));
} else {
tmp = R * (2.0 * atan2(sqrt(fma(t_0, cos(phi2), pow(sin((-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 = sqrt(Float64(1.0 - t_0)) tmp = 0.0 if (phi2 <= 3.6e-29) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_0, cos(phi1), (sin(Float64(0.5 * phi1)) ^ 2.0))), t_1))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_0, cos(phi2), (sin(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[Sqrt[N[(1.0 - t$95$0), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi2, 3.6e-29], 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] / t$95$1], $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] / t$95$1], $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 := \sqrt{1 - t\_0}\\
\mathbf{if}\;\phi_2 \leq 3.6 \cdot 10^{-29}:\\
\;\;\;\;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)}}{t\_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)}}{t\_1}\right)\\
\end{array}
\end{array}
if phi2 < 3.59999999999999974e-29Initial program 71.5%
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 rewrites61.5%
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-*.f6435.1
Applied rewrites35.1%
Taylor expanded in phi1 around 0
Applied rewrites34.5%
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-*.f6438.4
Applied rewrites38.4%
if 3.59999999999999974e-29 < phi2 Initial program 55.4%
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 rewrites22.6%
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-*.f6423.5
Applied rewrites23.5%
Taylor expanded in phi1 around 0
Applied rewrites23.5%
(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 (<= lambda1 4.8e-6)
(*
R
(*
2.0
(atan2
(sqrt (fma t_0 (cos phi2) t_1))
(sqrt (- 1.0 (pow (sin (* -0.5 lambda2)) 2.0))))))
(*
R
(*
2.0
(atan2
(sqrt (fma (pow (sin (* 0.5 lambda1)) 2.0) (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 tmp;
if (lambda1 <= 4.8e-6) {
tmp = R * (2.0 * atan2(sqrt(fma(t_0, cos(phi2), t_1)), sqrt((1.0 - pow(sin((-0.5 * lambda2)), 2.0)))));
} else {
tmp = R * (2.0 * atan2(sqrt(fma(pow(sin((0.5 * lambda1)), 2.0), 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 tmp = 0.0 if (lambda1 <= 4.8e-6) 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)))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(fma((sin(Float64(0.5 * lambda1)) ^ 2.0), 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]}, If[LessEqual[lambda1, 4.8e-6], 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], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(0.5 * lambda1), $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]]]]
\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 4.8 \cdot 10^{-6}:\\
\;\;\;\;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)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left({\sin \left(0.5 \cdot \lambda_1\right)}^{2}, \cos \phi_2, t\_1\right)}}{\sqrt{1 - t\_0}}\right)\\
\end{array}
\end{array}
if lambda1 < 4.7999999999999998e-6Initial program 68.6%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites49.4%
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-*.f6429.6
Applied rewrites29.6%
Taylor expanded in phi1 around 0
Applied rewrites29.2%
Taylor expanded in lambda1 around 0
Applied rewrites28.6%
if 4.7999999999999998e-6 < lambda1 Initial program 58.0%
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
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites49.0%
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-*.f6438.9
Applied rewrites38.9%
Taylor expanded in phi1 around 0
Applied rewrites38.2%
Taylor expanded in lambda2 around 0
Applied rewrites38.3%
(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 66.5%
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 rewrites49.3%
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-*.f6431.5
Applied rewrites31.5%
Taylor expanded in phi1 around 0
Applied rewrites31.0%
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-*.f6432.2
Applied rewrites32.2%
(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 66.5%
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 rewrites49.3%
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-*.f6431.5
Applied rewrites31.5%
Taylor expanded in phi1 around 0
Applied rewrites31.0%
Taylor expanded in lambda1 around 0
Applied rewrites24.0%
herbie shell --seed 2024318
(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))))))))))