
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_0) t_0))))
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0);
return R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0)
code = r * (2.0d0 * atan2(sqrt(t_1), sqrt((1.0d0 - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((Math.cos(phi1) * Math.cos(phi2)) * t_0) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt(t_1), Math.sqrt((1.0 - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((math.cos(phi1) * math.cos(phi2)) * t_0) * t_0) return R * (2.0 * math.atan2(math.sqrt(t_1), math.sqrt((1.0 - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0); tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$1], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) \cdot t\_0\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)
\end{array}
\end{array}
Sampling outcomes in binary64 precision:
Herbie found 15 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_0) t_0))))
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0);
return R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0)
code = r * (2.0d0 * atan2(sqrt(t_1), sqrt((1.0d0 - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((Math.cos(phi1) * Math.cos(phi2)) * t_0) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt(t_1), Math.sqrt((1.0 - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((math.cos(phi1) * math.cos(phi2)) * t_0) * t_0) return R * (2.0 * math.atan2(math.sqrt(t_1), math.sqrt((1.0 - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0); tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$1], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) \cdot t\_0\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)
\end{array}
\end{array}
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_1 (sin (* 0.5 phi1)))
(t_2 (cos (* 0.5 phi1))))
(*
R
(*
(atan2
(sqrt
(fma
(* (cos phi1) (cos phi2))
t_0
(pow (fma (sin (* -0.5 phi2)) t_2 (* (cos (* -0.5 phi2)) t_1)) 2.0)))
(sqrt
(-
1.0
(fma
(* t_0 (cos phi2))
(cos phi1)
(pow
(fma (- (sin (* 0.5 phi2))) t_2 (* t_1 (cos (* 0.5 phi2))))
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 t_1 = sin((0.5 * phi1));
double t_2 = cos((0.5 * phi1));
return R * (atan2(sqrt(fma((cos(phi1) * cos(phi2)), t_0, pow(fma(sin((-0.5 * phi2)), t_2, (cos((-0.5 * phi2)) * t_1)), 2.0))), sqrt((1.0 - fma((t_0 * cos(phi2)), cos(phi1), pow(fma(-sin((0.5 * phi2)), t_2, (t_1 * cos((0.5 * phi2)))), 2.0))))) * 2.0);
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_1 = sin(Float64(0.5 * phi1)) t_2 = cos(Float64(0.5 * phi1)) return Float64(R * Float64(atan(sqrt(fma(Float64(cos(phi1) * cos(phi2)), t_0, (fma(sin(Float64(-0.5 * phi2)), t_2, Float64(cos(Float64(-0.5 * phi2)) * t_1)) ^ 2.0))), sqrt(Float64(1.0 - fma(Float64(t_0 * cos(phi2)), cos(phi1), (fma(Float64(-sin(Float64(0.5 * phi2))), t_2, Float64(t_1 * cos(Float64(0.5 * phi2)))) ^ 2.0))))) * 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[Sin[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Cos[N[(0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, N[(R * N[(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] * t$95$2 + N[(N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(t$95$0 * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[Cos[phi1], $MachinePrecision] + N[Power[N[((-N[Sin[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]) * t$95$2 + N[(t$95$1 * N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_1 := \sin \left(0.5 \cdot \phi_1\right)\\
t_2 := \cos \left(0.5 \cdot \phi_1\right)\\
R \cdot \left(\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), t\_2, \cos \left(-0.5 \cdot \phi_2\right) \cdot t\_1\right)\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left(t\_0 \cdot \cos \phi_2, \cos \phi_1, {\left(\mathsf{fma}\left(-\sin \left(0.5 \cdot \phi_2\right), t\_2, t\_1 \cdot \cos \left(0.5 \cdot \phi_2\right)\right)\right)}^{2}\right)}} \cdot 2\right)
\end{array}
\end{array}
Initial program 61.0%
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-*.f6462.1
Applied rewrites62.1%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
sin-diffN/A
lift-sin.f64N/A
lift-cos.f64N/A
lift-*.f64N/A
lift-cos.f64N/A
lift-sin.f64N/A
lift-*.f64N/A
sub-negN/A
+-commutativeN/A
Applied rewrites77.6%
Applied rewrites77.6%
Taylor expanded in lambda1 around 0
Applied rewrites77.6%
(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
(+
(pow
(-
(* (sin (* phi1 0.5)) (cos (* phi2 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0)
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 = ((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 - (pow(((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0) + 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 = ((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 - ((((sin((phi1 * 0.5d0)) * cos((phi2 * 0.5d0))) - (cos((phi1 * 0.5d0)) * sin((phi2 * 0.5d0)))) ** 2.0d0) + 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.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 - (Math.pow(((Math.sin((phi1 * 0.5)) * Math.cos((phi2 * 0.5))) - (Math.cos((phi1 * 0.5)) * Math.sin((phi2 * 0.5)))), 2.0) + 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 - (math.pow(((math.sin((phi1 * 0.5)) * math.cos((phi2 * 0.5))) - (math.cos((phi1 * 0.5)) * math.sin((phi2 * 0.5)))), 2.0) + 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(Float64(sin(Float64(phi1 * 0.5)) * cos(Float64(phi2 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0) + 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 - ((((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))) ^ 2.0) + 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[(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[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] + 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(\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} + t\_1\right)}}\right)
\end{array}
\end{array}
Initial program 61.0%
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-*.f6462.1
Applied rewrites62.1%
(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 (sin (* (- phi1 phi2) 0.5)) 2.0)))
(sqrt
(-
1.0
(fma
(* t_0 (cos phi2))
(cos phi1)
(pow
(fma
(- (sin (* 0.5 phi2)))
(cos (* 0.5 phi1))
(* (sin (* 0.5 phi1)) (cos (* 0.5 phi2))))
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(sin(((phi1 - phi2) * 0.5)), 2.0))), sqrt((1.0 - fma((t_0 * cos(phi2)), cos(phi1), pow(fma(-sin((0.5 * phi2)), cos((0.5 * phi1)), (sin((0.5 * phi1)) * cos((0.5 * phi2)))), 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, (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0))), sqrt(Float64(1.0 - fma(Float64(t_0 * cos(phi2)), cos(phi1), (fma(Float64(-sin(Float64(0.5 * phi2))), cos(Float64(0.5 * phi1)), Float64(sin(Float64(0.5 * phi1)) * cos(Float64(0.5 * phi2)))) ^ 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[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(t$95$0 * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[Cos[phi1], $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]], $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, {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left(t\_0 \cdot \cos \phi_2, \cos \phi_1, {\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)}}
\end{array}
\end{array}
Initial program 61.0%
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-*.f6462.1
Applied rewrites62.1%
Taylor expanded in R around 0
Applied rewrites62.1%
(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
(fma
(sin (* phi1 0.5))
(cos (* -0.5 phi2))
(* (cos (* phi1 0.5)) (sin (* -0.5 phi2))))
2.0)
t_1))
(sqrt
(-
1.0
(+ (- 0.5 (* 0.5 (cos (* 2.0 (* (- phi1 phi2) 0.5))))) 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(fma(sin((phi1 * 0.5)), cos((-0.5 * phi2)), (cos((phi1 * 0.5)) * sin((-0.5 * phi2)))), 2.0) + t_1)), sqrt((1.0 - ((0.5 - (0.5 * cos((2.0 * ((phi1 - phi2) * 0.5))))) + 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((fma(sin(Float64(phi1 * 0.5)), cos(Float64(-0.5 * phi2)), Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(-0.5 * phi2)))) ^ 2.0) + t_1)), sqrt(Float64(1.0 - Float64(Float64(0.5 - Float64(0.5 * cos(Float64(2.0 * Float64(Float64(phi1 - phi2) * 0.5))))) + 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[(N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] + N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $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[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $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{{\left(\mathsf{fma}\left(\sin \left(\phi_1 \cdot 0.5\right), \cos \left(-0.5 \cdot \phi_2\right), \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(-0.5 \cdot \phi_2\right)\right)\right)}^{2} + t\_1}}{\sqrt{1 - \left(\left(0.5 - 0.5 \cdot \cos \left(2 \cdot \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)\right)\right) + t\_1\right)}}\right)
\end{array}
\end{array}
Initial program 61.0%
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-*.f6462.1
Applied rewrites62.1%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
sin-diffN/A
lift-sin.f64N/A
lift-cos.f64N/A
lift-*.f64N/A
lift-cos.f64N/A
lift-sin.f64N/A
lift-*.f64N/A
sub-negN/A
+-commutativeN/A
Applied rewrites77.6%
Applied rewrites77.6%
lift-pow.f64N/A
lift--.f64N/A
lift-*.f64N/A
lift-*.f64N/A
lift-sin.f64N/A
lift-cos.f64N/A
lift-cos.f64N/A
lift-sin.f64N/A
sin-diffN/A
lift-*.f64N/A
metadata-evalN/A
div-invN/A
lift-*.f64N/A
metadata-evalN/A
div-invN/A
div-subN/A
Applied rewrites61.7%
(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 61.0%
Applied rewrites61.1%
(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))))
(* (* 2.0 R) (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 (2.0 * R) * 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(Float64(2.0 * R) * 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[(N[(2.0 * R), $MachinePrecision] * N[ArcTan[N[Sqrt[t$95$0], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$0), $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)\\
\left(2 \cdot R\right) \cdot \tan^{-1}_* \frac{\sqrt{t\_0}}{\sqrt{1 - t\_0}}
\end{array}
\end{array}
Initial program 61.0%
Taylor expanded in R around 0
Applied rewrites60.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (pow (cos (* -0.5 phi1)) 2.0))
(t_2 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_3 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
(if (<= phi1 -3.4e-5)
(*
R
(*
2.0
(atan2
(pow (pow (fma t_2 (cos phi1) (pow (sin (* phi1 0.5)) 2.0)) 0.25) 2.0)
(sqrt (- t_1 (* t_2 (cos phi1)))))))
(if (<= phi1 5.4e-7)
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_0) t_0)))
(sqrt (- (pow (cos (* 0.5 phi2)) 2.0) (* t_2 (cos phi2)))))))
(*
(atan2
(sqrt
(fma
t_3
(* (cos phi2) (cos phi1))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)))
(sqrt (fma (- (cos phi1)) t_3 t_1)))
(* R 2.0))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(cos((-0.5 * phi1)), 2.0);
double t_2 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_3 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double tmp;
if (phi1 <= -3.4e-5) {
tmp = R * (2.0 * atan2(pow(pow(fma(t_2, cos(phi1), pow(sin((phi1 * 0.5)), 2.0)), 0.25), 2.0), sqrt((t_1 - (t_2 * cos(phi1))))));
} else if (phi1 <= 5.4e-7) {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0))), sqrt((pow(cos((0.5 * phi2)), 2.0) - (t_2 * cos(phi2))))));
} else {
tmp = atan2(sqrt(fma(t_3, (cos(phi2) * cos(phi1)), pow(sin((0.5 * (phi1 - phi2))), 2.0))), sqrt(fma(-cos(phi1), t_3, t_1))) * (R * 2.0);
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = cos(Float64(-0.5 * phi1)) ^ 2.0 t_2 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_3 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 tmp = 0.0 if (phi1 <= -3.4e-5) tmp = Float64(R * Float64(2.0 * atan(((fma(t_2, cos(phi1), (sin(Float64(phi1 * 0.5)) ^ 2.0)) ^ 0.25) ^ 2.0), sqrt(Float64(t_1 - Float64(t_2 * cos(phi1))))))); elseif (phi1 <= 5.4e-7) 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_0) * t_0))), sqrt(Float64((cos(Float64(0.5 * phi2)) ^ 2.0) - Float64(t_2 * cos(phi2))))))); else tmp = Float64(atan(sqrt(fma(t_3, Float64(cos(phi2) * cos(phi1)), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0))), sqrt(fma(Float64(-cos(phi1)), t_3, t_1))) * Float64(R * 2.0)); 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[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$3 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[LessEqual[phi1, -3.4e-5], N[(R * N[(2.0 * N[ArcTan[N[Power[N[Power[N[(t$95$2 * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision], 0.25], $MachinePrecision], 2.0], $MachinePrecision] / N[Sqrt[N[(t$95$1 - N[(t$95$2 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[phi1, 5.4e-7], 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$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(t$95$2 * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], N[(N[ArcTan[N[Sqrt[N[(t$95$3 * N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[((-N[Cos[phi1], $MachinePrecision]) * t$95$3 + t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(R * 2.0), $MachinePrecision]), $MachinePrecision]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\cos \left(-0.5 \cdot \phi_1\right)}^{2}\\
t_2 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_3 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
\mathbf{if}\;\phi_1 \leq -3.4 \cdot 10^{-5}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{{\left({\left(\mathsf{fma}\left(t\_2, \cos \phi_1, {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)\right)}^{0.25}\right)}^{2}}{\sqrt{t\_1 - t\_2 \cdot \cos \phi_1}}\right)\\
\mathbf{elif}\;\phi_1 \leq 5.4 \cdot 10^{-7}:\\
\;\;\;\;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\_0\right) \cdot t\_0}}{\sqrt{{\cos \left(0.5 \cdot \phi_2\right)}^{2} - t\_2 \cdot \cos \phi_2}}\right)\\
\mathbf{else}:\\
\;\;\;\;\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_3, \cos \phi_2 \cdot \cos \phi_1, {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}}{\sqrt{\mathsf{fma}\left(-\cos \phi_1, t\_3, t\_1\right)}} \cdot \left(R \cdot 2\right)\\
\end{array}
\end{array}
if phi1 < -3.4e-5Initial program 46.6%
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 rewrites47.3%
Taylor expanded in phi2 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-*.f6448.2
Applied rewrites48.2%
lift-sqrt.f64N/A
pow1/2N/A
sqr-powN/A
pow2N/A
lower-pow.f64N/A
Applied rewrites48.3%
if -3.4e-5 < phi1 < 5.40000000000000018e-7Initial program 77.7%
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 rewrites77.8%
if 5.40000000000000018e-7 < phi1 Initial program 44.8%
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 rewrites47.0%
Applied rewrites47.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_0) t_0)))
(sqrt
(-
1.0
(/
(fma
(- 1.0 (cos (* 2.0 (* 0.5 (- phi1 phi2)))))
2.0
(*
2.0
(*
(+ (cos (- phi1 phi2)) (cos (+ phi2 phi1)))
(pow (sin (* 0.5 (- lambda1 lambda2))) 2.0))))
4.0))))))))
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 - phi2) / 2.0)), 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0))), sqrt((1.0 - (fma((1.0 - cos((2.0 * (0.5 * (phi1 - phi2))))), 2.0, (2.0 * ((cos((phi1 - phi2)) + cos((phi2 + phi1))) * pow(sin((0.5 * (lambda1 - lambda2))), 2.0)))) / 4.0)))));
}
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((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0))), sqrt(Float64(1.0 - Float64(fma(Float64(1.0 - cos(Float64(2.0 * Float64(0.5 * Float64(phi1 - phi2))))), 2.0, Float64(2.0 * Float64(Float64(cos(Float64(phi1 - phi2)) + cos(Float64(phi2 + phi1))) * (sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0)))) / 4.0)))))) 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[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[(1.0 - N[Cos[N[(2.0 * N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * 2.0 + N[(2.0 * N[(N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] + N[Cos[N[(phi2 + phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / 4.0), $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{{\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}}{\sqrt{1 - \frac{\mathsf{fma}\left(1 - \cos \left(2 \cdot \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)\right), 2, 2 \cdot \left(\left(\cos \left(\phi_1 - \phi_2\right) + \cos \left(\phi_2 + \phi_1\right)\right) \cdot {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\right)\right)}{4}}}\right)
\end{array}
\end{array}
Initial program 61.0%
Applied rewrites61.7%
Final simplification61.7%
(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))
(t_2 (fma t_1 (cos phi2) (pow (sin (* -0.5 phi2)) 2.0))))
(if (or (<= phi2 -3.35e-6) (not (<= phi2 1.3)))
(* R (* 2.0 (atan2 (sqrt t_2) (sqrt (- 1.0 t_2)))))
(*
R
(*
2.0
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_0) t_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 t_2 = fma(t_1, cos(phi2), pow(sin((-0.5 * phi2)), 2.0));
double tmp;
if ((phi2 <= -3.35e-6) || !(phi2 <= 1.3)) {
tmp = R * (2.0 * atan2(sqrt(t_2), sqrt((1.0 - t_2))));
} else {
tmp = R * (2.0 * atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_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 t_2 = fma(t_1, cos(phi2), (sin(Float64(-0.5 * phi2)) ^ 2.0)) tmp = 0.0 if ((phi2 <= -3.35e-6) || !(phi2 <= 1.3)) tmp = Float64(R * Float64(2.0 * atan(sqrt(t_2), sqrt(Float64(1.0 - t_2))))); 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_0) * t_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]}, Block[{t$95$2 = N[(t$95$1 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[phi2, -3.35e-6], N[Not[LessEqual[phi2, 1.3]], $MachinePrecision]], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$2], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$2), $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$0), $MachinePrecision] * t$95$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}\\
t_2 := \mathsf{fma}\left(t\_1, \cos \phi_2, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)\\
\mathbf{if}\;\phi_2 \leq -3.35 \cdot 10^{-6} \lor \neg \left(\phi_2 \leq 1.3\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_2}}{\sqrt{1 - t\_2}}\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\_0\right) \cdot t\_0}}{\sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - t\_1 \cdot \cos \phi_1}}\right)\\
\end{array}
\end{array}
if phi2 < -3.35e-6 or 1.30000000000000004 < phi2 Initial program 46.7%
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 rewrites21.1%
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-*.f6421.4
Applied rewrites21.4%
Taylor expanded in phi1 around 0
lower--.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-*.f6448.2
Applied rewrites48.2%
if -3.35e-6 < phi2 < 1.30000000000000004Initial program 75.2%
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 rewrites75.3%
Final simplification61.8%
(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 (pow (cos (* -0.5 phi1)) 2.0))
(t_3 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
(if (<= phi1 -4.5e-5)
(*
R
(*
2.0
(atan2
(sqrt (fma t_0 (cos phi1) (pow (sin (* 0.5 phi1)) 2.0)))
(sqrt (- t_2 (* t_0 (cos phi1)))))))
(if (<= phi1 5.4e-7)
(*
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)))))))
(*
(atan2
(sqrt
(fma
t_3
(* (cos phi2) (cos phi1))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)))
(sqrt (fma (- (cos phi1)) t_3 t_2)))
(* R 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 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = pow(cos((-0.5 * phi1)), 2.0);
double t_3 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double tmp;
if (phi1 <= -4.5e-5) {
tmp = R * (2.0 * atan2(sqrt(fma(t_0, cos(phi1), pow(sin((0.5 * phi1)), 2.0))), sqrt((t_2 - (t_0 * cos(phi1))))));
} else if (phi1 <= 5.4e-7) {
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))))));
} else {
tmp = atan2(sqrt(fma(t_3, (cos(phi2) * cos(phi1)), pow(sin((0.5 * (phi1 - phi2))), 2.0))), sqrt(fma(-cos(phi1), t_3, t_2))) * (R * 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(Float64(lambda1 - lambda2) / 2.0)) t_2 = cos(Float64(-0.5 * phi1)) ^ 2.0 t_3 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 tmp = 0.0 if (phi1 <= -4.5e-5) tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(t_0, cos(phi1), (sin(Float64(0.5 * phi1)) ^ 2.0))), sqrt(Float64(t_2 - Float64(t_0 * cos(phi1))))))); elseif (phi1 <= 5.4e-7) 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))))))); else tmp = Float64(atan(sqrt(fma(t_3, Float64(cos(phi2) * cos(phi1)), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0))), sqrt(fma(Float64(-cos(phi1)), t_3, t_2))) * Float64(R * 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[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$3 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[LessEqual[phi1, -4.5e-5], 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[(t$95$2 - N[(t$95$0 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], If[LessEqual[phi1, 5.4e-7], 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], N[(N[ArcTan[N[Sqrt[N[(t$95$3 * N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[((-N[Cos[phi1], $MachinePrecision]) * t$95$3 + t$95$2), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(R * 2.0), $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 := {\cos \left(-0.5 \cdot \phi_1\right)}^{2}\\
t_3 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
\mathbf{if}\;\phi_1 \leq -4.5 \cdot 10^{-5}:\\
\;\;\;\;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{t\_2 - t\_0 \cdot \cos \phi_1}}\right)\\
\mathbf{elif}\;\phi_1 \leq 5.4 \cdot 10^{-7}:\\
\;\;\;\;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)\\
\mathbf{else}:\\
\;\;\;\;\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_3, \cos \phi_2 \cdot \cos \phi_1, {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}}{\sqrt{\mathsf{fma}\left(-\cos \phi_1, t\_3, t\_2\right)}} \cdot \left(R \cdot 2\right)\\
\end{array}
\end{array}
if phi1 < -4.50000000000000028e-5Initial program 46.6%
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 rewrites47.3%
Taylor expanded in phi2 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-*.f6448.2
Applied rewrites48.2%
if -4.50000000000000028e-5 < phi1 < 5.40000000000000018e-7Initial program 77.7%
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 rewrites77.8%
if 5.40000000000000018e-7 < phi1 Initial program 44.8%
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 rewrites47.0%
Applied rewrites47.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(fma
(pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)
(cos phi2)
(pow (sin (* -0.5 phi2)) 2.0)))
(t_1 (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0)))
(if (or (<= phi2 -3.35e-6) (not (<= phi2 1.3)))
(* R (* 2.0 (atan2 (sqrt t_0) (sqrt (- 1.0 t_0)))))
(*
(atan2
(sqrt
(fma
t_1
(* (cos phi2) (cos phi1))
(pow (sin (* 0.5 (- phi1 phi2))) 2.0)))
(sqrt (fma (- (cos phi1)) t_1 (pow (cos (* -0.5 phi1)) 2.0))))
(* R 2.0)))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = fma(pow(sin(((lambda1 - lambda2) * 0.5)), 2.0), cos(phi2), pow(sin((-0.5 * phi2)), 2.0));
double t_1 = pow(sin((0.5 * (lambda1 - lambda2))), 2.0);
double tmp;
if ((phi2 <= -3.35e-6) || !(phi2 <= 1.3)) {
tmp = R * (2.0 * atan2(sqrt(t_0), sqrt((1.0 - t_0))));
} else {
tmp = atan2(sqrt(fma(t_1, (cos(phi2) * cos(phi1)), pow(sin((0.5 * (phi1 - phi2))), 2.0))), sqrt(fma(-cos(phi1), t_1, pow(cos((-0.5 * phi1)), 2.0)))) * (R * 2.0);
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = fma((sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0), cos(phi2), (sin(Float64(-0.5 * phi2)) ^ 2.0)) t_1 = sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0 tmp = 0.0 if ((phi2 <= -3.35e-6) || !(phi2 <= 1.3)) tmp = Float64(R * Float64(2.0 * atan(sqrt(t_0), sqrt(Float64(1.0 - t_0))))); else tmp = Float64(atan(sqrt(fma(t_1, Float64(cos(phi2) * cos(phi1)), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0))), sqrt(fma(Float64(-cos(phi1)), t_1, (cos(Float64(-0.5 * phi1)) ^ 2.0)))) * Float64(R * 2.0)); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, If[Or[LessEqual[phi2, -3.35e-6], N[Not[LessEqual[phi2, 1.3]], $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], N[(N[ArcTan[N[Sqrt[N[(t$95$1 * N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(0.5 * N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[((-N[Cos[phi1], $MachinePrecision]) * t$95$1 + N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(R * 2.0), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \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)\\
t_1 := {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2}\\
\mathbf{if}\;\phi_2 \leq -3.35 \cdot 10^{-6} \lor \neg \left(\phi_2 \leq 1.3\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_0}}{\sqrt{1 - t\_0}}\right)\\
\mathbf{else}:\\
\;\;\;\;\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_1, \cos \phi_2 \cdot \cos \phi_1, {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}}{\sqrt{\mathsf{fma}\left(-\cos \phi_1, t\_1, {\cos \left(-0.5 \cdot \phi_1\right)}^{2}\right)}} \cdot \left(R \cdot 2\right)\\
\end{array}
\end{array}
if phi2 < -3.35e-6 or 1.30000000000000004 < phi2 Initial program 46.7%
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 rewrites21.1%
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-*.f6421.4
Applied rewrites21.4%
Taylor expanded in phi1 around 0
lower--.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-*.f6448.2
Applied rewrites48.2%
if -3.35e-6 < phi2 < 1.30000000000000004Initial program 75.2%
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 rewrites75.3%
Applied rewrites75.3%
Final simplification61.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_1 (fma t_0 (cos phi2) (pow (sin (* -0.5 phi2)) 2.0))))
(if (or (<= phi2 -3.35e-6) (not (<= phi2 1.3)))
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1)))))
(*
R
(*
2.0
(atan2
(sqrt
(fma
(cos phi2)
(* (pow (sin (* 0.5 (- lambda1 lambda2))) 2.0) (cos phi1))
(pow (sin (* 0.5 (- phi1 phi2))) 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);
double t_1 = fma(t_0, cos(phi2), pow(sin((-0.5 * phi2)), 2.0));
double tmp;
if ((phi2 <= -3.35e-6) || !(phi2 <= 1.3)) {
tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
} else {
tmp = R * (2.0 * atan2(sqrt(fma(cos(phi2), (pow(sin((0.5 * (lambda1 - lambda2))), 2.0) * cos(phi1)), pow(sin((0.5 * (phi1 - phi2))), 2.0))), sqrt((pow(cos((-0.5 * phi1)), 2.0) - (t_0 * cos(phi1))))));
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_1 = fma(t_0, cos(phi2), (sin(Float64(-0.5 * phi2)) ^ 2.0)) tmp = 0.0 if ((phi2 <= -3.35e-6) || !(phi2 <= 1.3)) tmp = Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))); else tmp = Float64(R * Float64(2.0 * atan(sqrt(fma(cos(phi2), Float64((sin(Float64(0.5 * Float64(lambda1 - lambda2))) ^ 2.0) * cos(phi1)), (sin(Float64(0.5 * Float64(phi1 - phi2))) ^ 2.0))), sqrt(Float64((cos(Float64(-0.5 * phi1)) ^ 2.0) - Float64(t_0 * cos(phi1))))))); 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] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[phi2, -3.35e-6], N[Not[LessEqual[phi2, 1.3]], $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], N[(R * N[(2.0 * N[ArcTan[N[Sqrt[N[(N[Cos[phi2], $MachinePrecision] * N[(N[Power[N[Sin[N[(0.5 * N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] + 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[(-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}\\
t_1 := \mathsf{fma}\left(t\_0, \cos \phi_2, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)\\
\mathbf{if}\;\phi_2 \leq -3.35 \cdot 10^{-6} \lor \neg \left(\phi_2 \leq 1.3\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)\\
\mathbf{else}:\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_2, {\sin \left(0.5 \cdot \left(\lambda_1 - \lambda_2\right)\right)}^{2} \cdot \cos \phi_1, {\sin \left(0.5 \cdot \left(\phi_1 - \phi_2\right)\right)}^{2}\right)}}{\sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - t\_0 \cdot \cos \phi_1}}\right)\\
\end{array}
\end{array}
if phi2 < -3.35e-6 or 1.30000000000000004 < phi2 Initial program 46.7%
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 rewrites21.1%
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-*.f6421.4
Applied rewrites21.4%
Taylor expanded in phi1 around 0
lower--.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-*.f6448.2
Applied rewrites48.2%
if -3.35e-6 < phi2 < 1.30000000000000004Initial program 75.2%
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 rewrites75.3%
lift-+.f64N/A
+-commutativeN/A
lift-*.f64N/A
*-commutativeN/A
Applied rewrites75.3%
Final simplification61.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_1 (fma t_0 (cos phi2) (pow (sin (* -0.5 phi2)) 2.0))))
(if (or (<= phi2 -2.55e-6) (not (<= phi2 2.9e-11)))
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1)))))
(*
(atan2
(sqrt (fma t_0 (cos phi1) (pow (sin (* phi1 0.5)) 2.0)))
(sqrt (fma (- (cos phi1)) t_0 (pow (cos (* -0.5 phi1)) 2.0))))
(* R 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 = fma(t_0, cos(phi2), pow(sin((-0.5 * phi2)), 2.0));
double tmp;
if ((phi2 <= -2.55e-6) || !(phi2 <= 2.9e-11)) {
tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
} else {
tmp = atan2(sqrt(fma(t_0, cos(phi1), pow(sin((phi1 * 0.5)), 2.0))), sqrt(fma(-cos(phi1), t_0, pow(cos((-0.5 * phi1)), 2.0)))) * (R * 2.0);
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_1 = fma(t_0, cos(phi2), (sin(Float64(-0.5 * phi2)) ^ 2.0)) tmp = 0.0 if ((phi2 <= -2.55e-6) || !(phi2 <= 2.9e-11)) tmp = Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))); else tmp = Float64(atan(sqrt(fma(t_0, cos(phi1), (sin(Float64(phi1 * 0.5)) ^ 2.0))), sqrt(fma(Float64(-cos(phi1)), t_0, (cos(Float64(-0.5 * phi1)) ^ 2.0)))) * Float64(R * 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[(t$95$0 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, If[Or[LessEqual[phi2, -2.55e-6], N[Not[LessEqual[phi2, 2.9e-11]], $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], N[(N[ArcTan[N[Sqrt[N[(t$95$0 * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[((-N[Cos[phi1], $MachinePrecision]) * t$95$0 + N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(R * 2.0), $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 := \mathsf{fma}\left(t\_0, \cos \phi_2, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)\\
\mathbf{if}\;\phi_2 \leq -2.55 \cdot 10^{-6} \lor \neg \left(\phi_2 \leq 2.9 \cdot 10^{-11}\right):\\
\;\;\;\;R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)\\
\mathbf{else}:\\
\;\;\;\;\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \cos \phi_1, {\sin \left(\phi_1 \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)}} \cdot \left(R \cdot 2\right)\\
\end{array}
\end{array}
if phi2 < -2.5500000000000001e-6 or 2.9e-11 < phi2 Initial program 46.9%
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 rewrites21.7%
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-*.f6422.0
Applied rewrites22.0%
Taylor expanded in phi1 around 0
lower--.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-*.f6448.4
Applied rewrites48.4%
if -2.5500000000000001e-6 < phi2 < 2.9e-11Initial 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 rewrites75.6%
Taylor expanded in phi2 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-*.f6474.1
Applied rewrites74.1%
lift-*.f64N/A
Applied rewrites74.1%
Final simplification61.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
(*
(atan2
(sqrt (fma t_0 (cos phi1) (pow (sin (* phi1 0.5)) 2.0)))
(sqrt (fma (- (cos phi1)) t_0 (pow (cos (* -0.5 phi1)) 2.0))))
(* R 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 atan2(sqrt(fma(t_0, cos(phi1), pow(sin((phi1 * 0.5)), 2.0))), sqrt(fma(-cos(phi1), t_0, pow(cos((-0.5 * phi1)), 2.0)))) * (R * 2.0);
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 return Float64(atan(sqrt(fma(t_0, cos(phi1), (sin(Float64(phi1 * 0.5)) ^ 2.0))), sqrt(fma(Float64(-cos(phi1)), t_0, (cos(Float64(-0.5 * phi1)) ^ 2.0)))) * Float64(R * 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[ArcTan[N[Sqrt[N[(t$95$0 * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[((-N[Cos[phi1], $MachinePrecision]) * t$95$0 + N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(R * 2.0), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \cos \phi_1, {\sin \left(\phi_1 \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)}} \cdot \left(R \cdot 2\right)
\end{array}
\end{array}
Initial program 61.0%
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 rewrites48.2%
Taylor expanded in phi2 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-*.f6446.4
Applied rewrites46.4%
lift-*.f64N/A
Applied rewrites46.4%
(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 61.0%
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 rewrites48.2%
Taylor expanded in phi2 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-*.f6446.4
Applied rewrites46.4%
herbie shell --seed 2024309
(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))))))))))