
(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 30 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_0) t_0))))
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0);
return R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0)
code = r * (2.0d0 * atan2(sqrt(t_1), sqrt((1.0d0 - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((Math.cos(phi1) * Math.cos(phi2)) * t_0) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt(t_1), Math.sqrt((1.0 - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((math.cos(phi1) * math.cos(phi2)) * t_0) * t_0) return R * (2.0 * math.atan2(math.sqrt(t_1), math.sqrt((1.0 - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0); tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$1], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) \cdot t\_0\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)
\end{array}
\end{array}
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* phi1 0.5)))
(t_1 (cos (* phi1 0.5)))
(t_2 (* (- lambda1) -0.5)))
(*
(atan2
(sqrt
(fma
(* (cos phi1) (cos phi2))
(pow (sin (* (- lambda2 lambda1) -0.5)) 2.0)
(pow (fma (sin (* phi2 -0.5)) t_1 (* (cos (* phi2 -0.5)) t_0)) 2.0)))
(sqrt
(-
1.0
(fma
(*
(pow
(fma
(sin (* lambda2 -0.5))
(cos t_2)
(* (sin t_2) (cos (* lambda2 -0.5))))
2.0)
(cos phi2))
(cos phi1)
(pow (- (* (cos (* phi2 0.5)) t_0) (* (sin (* phi2 0.5)) t_1)) 2.0)))))
(* 2.0 R))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((phi1 * 0.5));
double t_1 = cos((phi1 * 0.5));
double t_2 = -lambda1 * -0.5;
return atan2(sqrt(fma((cos(phi1) * cos(phi2)), pow(sin(((lambda2 - lambda1) * -0.5)), 2.0), pow(fma(sin((phi2 * -0.5)), t_1, (cos((phi2 * -0.5)) * t_0)), 2.0))), sqrt((1.0 - fma((pow(fma(sin((lambda2 * -0.5)), cos(t_2), (sin(t_2) * cos((lambda2 * -0.5)))), 2.0) * cos(phi2)), cos(phi1), pow(((cos((phi2 * 0.5)) * t_0) - (sin((phi2 * 0.5)) * t_1)), 2.0))))) * (2.0 * R);
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi1 * 0.5)) t_1 = cos(Float64(phi1 * 0.5)) t_2 = Float64(Float64(-lambda1) * -0.5) return Float64(atan(sqrt(fma(Float64(cos(phi1) * cos(phi2)), (sin(Float64(Float64(lambda2 - lambda1) * -0.5)) ^ 2.0), (fma(sin(Float64(phi2 * -0.5)), t_1, Float64(cos(Float64(phi2 * -0.5)) * t_0)) ^ 2.0))), sqrt(Float64(1.0 - fma(Float64((fma(sin(Float64(lambda2 * -0.5)), cos(t_2), Float64(sin(t_2) * cos(Float64(lambda2 * -0.5)))) ^ 2.0) * cos(phi2)), cos(phi1), (Float64(Float64(cos(Float64(phi2 * 0.5)) * t_0) - Float64(sin(Float64(phi2 * 0.5)) * t_1)) ^ 2.0))))) * Float64(2.0 * R)) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[((-lambda1) * -0.5), $MachinePrecision]}, N[(N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda2 - lambda1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[(N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * t$95$1 + N[(N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Power[N[(N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[t$95$2], $MachinePrecision] + N[(N[Sin[t$95$2], $MachinePrecision] * N[Cos[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[Cos[phi1], $MachinePrecision] + N[Power[N[(N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision] - N[(N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(2.0 * R), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_1 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_2 := \left(-\lambda_1\right) \cdot -0.5\\
\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_1 \cdot \cos \phi_2, {\sin \left(\left(\lambda_2 - \lambda_1\right) \cdot -0.5\right)}^{2}, {\left(\mathsf{fma}\left(\sin \left(\phi_2 \cdot -0.5\right), t\_1, \cos \left(\phi_2 \cdot -0.5\right) \cdot t\_0\right)\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left({\left(\mathsf{fma}\left(\sin \left(\lambda_2 \cdot -0.5\right), \cos t\_2, \sin t\_2 \cdot \cos \left(\lambda_2 \cdot -0.5\right)\right)\right)}^{2} \cdot \cos \phi_2, \cos \phi_1, {\left(\cos \left(\phi_2 \cdot 0.5\right) \cdot t\_0 - \sin \left(\phi_2 \cdot 0.5\right) \cdot t\_1\right)}^{2}\right)}} \cdot \left(2 \cdot R\right)
\end{array}
\end{array}
Initial program 65.5%
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-*.f6466.2
Applied rewrites66.2%
lift-sin.f64N/A
lift-/.f64N/A
div-invN/A
metadata-evalN/A
*-commutativeN/A
lift--.f64N/A
sub-negN/A
distribute-rgt-inN/A
lift-*.f64N/A
cancel-sign-sub-invN/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
sin-sumN/A
lift-sin.f64N/A
lower-fma.f64N/A
Applied rewrites79.1%
Taylor expanded in lambda1 around -inf
Applied rewrites79.2%
Applied rewrites79.8%
Final simplification79.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* phi1 0.5)))
(t_1 (cos (* phi1 0.5)))
(t_2
(sqrt
(fma
(* (cos phi1) (cos phi2))
(pow (sin (* (- lambda2 lambda1) -0.5)) 2.0)
(pow
(fma (sin (* phi2 -0.5)) t_1 (* (cos (* phi2 -0.5)) t_0))
2.0))))
(t_3
(pow (fma (cos (* phi2 0.5)) t_0 (* (- (sin (* phi2 0.5))) t_1)) 2.0))
(t_4
(*
(atan2
t_2
(sqrt
(-
1.0
(fma
(* (pow (sin (* lambda2 -0.5)) 2.0) (cos phi2))
(cos phi1)
t_3))))
(* 2.0 R))))
(if (<= lambda2 -7.6e-6)
t_4
(if (<= lambda2 2.9e-6)
(*
(atan2
t_2
(sqrt
(-
1.0
(fma
(* (pow (sin (* lambda1 0.5)) 2.0) (cos phi2))
(cos phi1)
t_3))))
(* 2.0 R))
t_4))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((phi1 * 0.5));
double t_1 = cos((phi1 * 0.5));
double t_2 = sqrt(fma((cos(phi1) * cos(phi2)), pow(sin(((lambda2 - lambda1) * -0.5)), 2.0), pow(fma(sin((phi2 * -0.5)), t_1, (cos((phi2 * -0.5)) * t_0)), 2.0)));
double t_3 = pow(fma(cos((phi2 * 0.5)), t_0, (-sin((phi2 * 0.5)) * t_1)), 2.0);
double t_4 = atan2(t_2, sqrt((1.0 - fma((pow(sin((lambda2 * -0.5)), 2.0) * cos(phi2)), cos(phi1), t_3)))) * (2.0 * R);
double tmp;
if (lambda2 <= -7.6e-6) {
tmp = t_4;
} else if (lambda2 <= 2.9e-6) {
tmp = atan2(t_2, sqrt((1.0 - fma((pow(sin((lambda1 * 0.5)), 2.0) * cos(phi2)), cos(phi1), t_3)))) * (2.0 * R);
} else {
tmp = t_4;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi1 * 0.5)) t_1 = cos(Float64(phi1 * 0.5)) t_2 = sqrt(fma(Float64(cos(phi1) * cos(phi2)), (sin(Float64(Float64(lambda2 - lambda1) * -0.5)) ^ 2.0), (fma(sin(Float64(phi2 * -0.5)), t_1, Float64(cos(Float64(phi2 * -0.5)) * t_0)) ^ 2.0))) t_3 = fma(cos(Float64(phi2 * 0.5)), t_0, Float64(Float64(-sin(Float64(phi2 * 0.5))) * t_1)) ^ 2.0 t_4 = Float64(atan(t_2, sqrt(Float64(1.0 - fma(Float64((sin(Float64(lambda2 * -0.5)) ^ 2.0) * cos(phi2)), cos(phi1), t_3)))) * Float64(2.0 * R)) tmp = 0.0 if (lambda2 <= -7.6e-6) tmp = t_4; elseif (lambda2 <= 2.9e-6) tmp = Float64(atan(t_2, sqrt(Float64(1.0 - fma(Float64((sin(Float64(lambda1 * 0.5)) ^ 2.0) * cos(phi2)), cos(phi1), t_3)))) * Float64(2.0 * R)); else tmp = t_4; end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda2 - lambda1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[(N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * t$95$1 + N[(N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Power[N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * t$95$0 + N[((-N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]) * t$95$1), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$4 = N[(N[ArcTan[t$95$2 / N[Sqrt[N[(1.0 - N[(N[(N[Power[N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[Cos[phi1], $MachinePrecision] + t$95$3), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(2.0 * R), $MachinePrecision]), $MachinePrecision]}, If[LessEqual[lambda2, -7.6e-6], t$95$4, If[LessEqual[lambda2, 2.9e-6], N[(N[ArcTan[t$95$2 / N[Sqrt[N[(1.0 - N[(N[(N[Power[N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[Cos[phi1], $MachinePrecision] + t$95$3), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(2.0 * R), $MachinePrecision]), $MachinePrecision], t$95$4]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_1 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_2 := \sqrt{\mathsf{fma}\left(\cos \phi_1 \cdot \cos \phi_2, {\sin \left(\left(\lambda_2 - \lambda_1\right) \cdot -0.5\right)}^{2}, {\left(\mathsf{fma}\left(\sin \left(\phi_2 \cdot -0.5\right), t\_1, \cos \left(\phi_2 \cdot -0.5\right) \cdot t\_0\right)\right)}^{2}\right)}\\
t_3 := {\left(\mathsf{fma}\left(\cos \left(\phi_2 \cdot 0.5\right), t\_0, \left(-\sin \left(\phi_2 \cdot 0.5\right)\right) \cdot t\_1\right)\right)}^{2}\\
t_4 := \tan^{-1}_* \frac{t\_2}{\sqrt{1 - \mathsf{fma}\left({\sin \left(\lambda_2 \cdot -0.5\right)}^{2} \cdot \cos \phi_2, \cos \phi_1, t\_3\right)}} \cdot \left(2 \cdot R\right)\\
\mathbf{if}\;\lambda_2 \leq -7.6 \cdot 10^{-6}:\\
\;\;\;\;t\_4\\
\mathbf{elif}\;\lambda_2 \leq 2.9 \cdot 10^{-6}:\\
\;\;\;\;\tan^{-1}_* \frac{t\_2}{\sqrt{1 - \mathsf{fma}\left({\sin \left(\lambda_1 \cdot 0.5\right)}^{2} \cdot \cos \phi_2, \cos \phi_1, t\_3\right)}} \cdot \left(2 \cdot R\right)\\
\mathbf{else}:\\
\;\;\;\;t\_4\\
\end{array}
\end{array}
if lambda2 < -7.6000000000000001e-6 or 2.9000000000000002e-6 < lambda2 Initial program 51.2%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f6451.8
Applied rewrites51.8%
lift-sin.f64N/A
lift-/.f64N/A
div-invN/A
metadata-evalN/A
*-commutativeN/A
lift--.f64N/A
sub-negN/A
distribute-rgt-inN/A
lift-*.f64N/A
cancel-sign-sub-invN/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
sin-sumN/A
lift-sin.f64N/A
lower-fma.f64N/A
Applied rewrites61.1%
Taylor expanded in lambda1 around -inf
Applied rewrites61.1%
Taylor expanded in lambda1 around 0
Applied rewrites61.5%
if -7.6000000000000001e-6 < lambda2 < 2.9000000000000002e-6Initial program 80.2%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f6481.0
Applied rewrites81.0%
lift-sin.f64N/A
lift-/.f64N/A
div-invN/A
metadata-evalN/A
*-commutativeN/A
lift--.f64N/A
sub-negN/A
distribute-rgt-inN/A
lift-*.f64N/A
cancel-sign-sub-invN/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
sin-sumN/A
lift-sin.f64N/A
lower-fma.f64N/A
Applied rewrites97.8%
Taylor expanded in lambda1 around -inf
Applied rewrites97.8%
Taylor expanded in lambda2 around 0
Applied rewrites97.8%
Final simplification79.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (cos phi1) (cos phi2)))
(t_2 (sin (* phi2 -0.5)))
(t_3 (cos (* phi2 0.5)))
(t_4 (* (* t_0 t_1) t_0))
(t_5 (sqrt (+ t_4 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))))
(t_6 (sin (* phi2 0.5)))
(t_7 (sin (* phi1 0.5)))
(t_8 (* (cos (* phi2 -0.5)) t_7))
(t_9 (cos (* phi1 0.5))))
(if (<= lambda1 -0.0034)
(*
(*
(atan2
t_5
(sqrt
(-
1.0
(fma
t_1
(pow (sin (* lambda1 0.5)) 2.0)
(pow (fma t_2 (cos (* -0.5 phi1)) t_8) 2.0)))))
2.0)
R)
(if (<= lambda1 1.5e-8)
(*
(atan2
(sqrt
(fma
t_1
(pow (sin (* (- lambda2 lambda1) -0.5)) 2.0)
(pow (fma t_2 t_9 t_8) 2.0)))
(sqrt
(-
1.0
(fma
(* (pow (sin (* lambda2 -0.5)) 2.0) (cos phi2))
(cos phi1)
(pow (fma t_3 t_7 (* (- t_6) t_9)) 2.0)))))
(* 2.0 R))
(*
(*
(atan2
t_5
(sqrt (- 1.0 (+ t_4 (pow (- (* t_3 t_7) (* t_6 t_9)) 2.0)))))
2.0)
R)))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = cos(phi1) * cos(phi2);
double t_2 = sin((phi2 * -0.5));
double t_3 = cos((phi2 * 0.5));
double t_4 = (t_0 * t_1) * t_0;
double t_5 = sqrt((t_4 + pow(sin(((phi1 - phi2) / 2.0)), 2.0)));
double t_6 = sin((phi2 * 0.5));
double t_7 = sin((phi1 * 0.5));
double t_8 = cos((phi2 * -0.5)) * t_7;
double t_9 = cos((phi1 * 0.5));
double tmp;
if (lambda1 <= -0.0034) {
tmp = (atan2(t_5, sqrt((1.0 - fma(t_1, pow(sin((lambda1 * 0.5)), 2.0), pow(fma(t_2, cos((-0.5 * phi1)), t_8), 2.0))))) * 2.0) * R;
} else if (lambda1 <= 1.5e-8) {
tmp = atan2(sqrt(fma(t_1, pow(sin(((lambda2 - lambda1) * -0.5)), 2.0), pow(fma(t_2, t_9, t_8), 2.0))), sqrt((1.0 - fma((pow(sin((lambda2 * -0.5)), 2.0) * cos(phi2)), cos(phi1), pow(fma(t_3, t_7, (-t_6 * t_9)), 2.0))))) * (2.0 * R);
} else {
tmp = (atan2(t_5, sqrt((1.0 - (t_4 + pow(((t_3 * t_7) - (t_6 * t_9)), 2.0))))) * 2.0) * R;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(cos(phi1) * cos(phi2)) t_2 = sin(Float64(phi2 * -0.5)) t_3 = cos(Float64(phi2 * 0.5)) t_4 = Float64(Float64(t_0 * t_1) * t_0) t_5 = sqrt(Float64(t_4 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))) t_6 = sin(Float64(phi2 * 0.5)) t_7 = sin(Float64(phi1 * 0.5)) t_8 = Float64(cos(Float64(phi2 * -0.5)) * t_7) t_9 = cos(Float64(phi1 * 0.5)) tmp = 0.0 if (lambda1 <= -0.0034) tmp = Float64(Float64(atan(t_5, sqrt(Float64(1.0 - fma(t_1, (sin(Float64(lambda1 * 0.5)) ^ 2.0), (fma(t_2, cos(Float64(-0.5 * phi1)), t_8) ^ 2.0))))) * 2.0) * R); elseif (lambda1 <= 1.5e-8) tmp = Float64(atan(sqrt(fma(t_1, (sin(Float64(Float64(lambda2 - lambda1) * -0.5)) ^ 2.0), (fma(t_2, t_9, t_8) ^ 2.0))), sqrt(Float64(1.0 - fma(Float64((sin(Float64(lambda2 * -0.5)) ^ 2.0) * cos(phi2)), cos(phi1), (fma(t_3, t_7, Float64(Float64(-t_6) * t_9)) ^ 2.0))))) * Float64(2.0 * R)); else tmp = Float64(Float64(atan(t_5, sqrt(Float64(1.0 - Float64(t_4 + (Float64(Float64(t_3 * t_7) - Float64(t_6 * t_9)) ^ 2.0))))) * 2.0) * R); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[(N[(t$95$0 * t$95$1), $MachinePrecision] * t$95$0), $MachinePrecision]}, Block[{t$95$5 = N[Sqrt[N[(t$95$4 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$6 = N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$7 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$8 = N[(N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * t$95$7), $MachinePrecision]}, Block[{t$95$9 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[lambda1, -0.0034], N[(N[(N[ArcTan[t$95$5 / N[Sqrt[N[(1.0 - N[(t$95$1 * N[Power[N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[(t$95$2 * N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision] + t$95$8), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], If[LessEqual[lambda1, 1.5e-8], N[(N[ArcTan[N[Sqrt[N[(t$95$1 * N[Power[N[Sin[N[(N[(lambda2 - lambda1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[(t$95$2 * t$95$9 + t$95$8), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Power[N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[Cos[phi1], $MachinePrecision] + N[Power[N[(t$95$3 * t$95$7 + N[((-t$95$6) * t$95$9), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(2.0 * R), $MachinePrecision]), $MachinePrecision], N[(N[(N[ArcTan[t$95$5 / N[Sqrt[N[(1.0 - N[(t$95$4 + N[Power[N[(N[(t$95$3 * t$95$7), $MachinePrecision] - N[(t$95$6 * t$95$9), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]]]]]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
t_2 := \sin \left(\phi_2 \cdot -0.5\right)\\
t_3 := \cos \left(\phi_2 \cdot 0.5\right)\\
t_4 := \left(t\_0 \cdot t\_1\right) \cdot t\_0\\
t_5 := \sqrt{t\_4 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}\\
t_6 := \sin \left(\phi_2 \cdot 0.5\right)\\
t_7 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_8 := \cos \left(\phi_2 \cdot -0.5\right) \cdot t\_7\\
t_9 := \cos \left(\phi_1 \cdot 0.5\right)\\
\mathbf{if}\;\lambda_1 \leq -0.0034:\\
\;\;\;\;\left(\tan^{-1}_* \frac{t\_5}{\sqrt{1 - \mathsf{fma}\left(t\_1, {\sin \left(\lambda_1 \cdot 0.5\right)}^{2}, {\left(\mathsf{fma}\left(t\_2, \cos \left(-0.5 \cdot \phi_1\right), t\_8\right)\right)}^{2}\right)}} \cdot 2\right) \cdot R\\
\mathbf{elif}\;\lambda_1 \leq 1.5 \cdot 10^{-8}:\\
\;\;\;\;\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_1, {\sin \left(\left(\lambda_2 - \lambda_1\right) \cdot -0.5\right)}^{2}, {\left(\mathsf{fma}\left(t\_2, t\_9, t\_8\right)\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left({\sin \left(\lambda_2 \cdot -0.5\right)}^{2} \cdot \cos \phi_2, \cos \phi_1, {\left(\mathsf{fma}\left(t\_3, t\_7, \left(-t\_6\right) \cdot t\_9\right)\right)}^{2}\right)}} \cdot \left(2 \cdot R\right)\\
\mathbf{else}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{t\_5}{\sqrt{1 - \left(t\_4 + {\left(t\_3 \cdot t\_7 - t\_6 \cdot t\_9\right)}^{2}\right)}} \cdot 2\right) \cdot R\\
\end{array}
\end{array}
if lambda1 < -0.00339999999999999981Initial program 52.4%
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-*.f6453.0
Applied rewrites53.0%
Taylor expanded in lambda2 around 0
Applied rewrites53.2%
if -0.00339999999999999981 < lambda1 < 1.49999999999999987e-8Initial program 79.8%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f6480.6
Applied rewrites80.6%
lift-sin.f64N/A
lift-/.f64N/A
div-invN/A
metadata-evalN/A
*-commutativeN/A
lift--.f64N/A
sub-negN/A
distribute-rgt-inN/A
lift-*.f64N/A
cancel-sign-sub-invN/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
sin-sumN/A
lift-sin.f64N/A
lower-fma.f64N/A
Applied rewrites97.4%
Taylor expanded in lambda1 around -inf
Applied rewrites97.4%
Taylor expanded in lambda1 around 0
Applied rewrites97.5%
if 1.49999999999999987e-8 < lambda1 Initial program 50.2%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f6450.9
Applied rewrites50.9%
Final simplification74.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (* phi1 0.5)))
(t_1 (pow (sin (* (- lambda2 lambda1) -0.5)) 2.0))
(t_2 (sin (* phi1 0.5))))
(*
(atan2
(sqrt
(fma
(* (cos phi1) (cos phi2))
t_1
(pow (fma (sin (* phi2 -0.5)) t_0 (* (cos (* phi2 -0.5)) t_2)) 2.0)))
(sqrt
(-
1.0
(fma
(* t_1 (cos phi2))
(cos phi1)
(pow (- (* (cos (* phi2 0.5)) t_2) (* (sin (* phi2 0.5)) t_0)) 2.0)))))
(* 2.0 R))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((phi1 * 0.5));
double t_1 = pow(sin(((lambda2 - lambda1) * -0.5)), 2.0);
double t_2 = sin((phi1 * 0.5));
return atan2(sqrt(fma((cos(phi1) * cos(phi2)), t_1, pow(fma(sin((phi2 * -0.5)), t_0, (cos((phi2 * -0.5)) * t_2)), 2.0))), sqrt((1.0 - fma((t_1 * cos(phi2)), cos(phi1), pow(((cos((phi2 * 0.5)) * t_2) - (sin((phi2 * 0.5)) * t_0)), 2.0))))) * (2.0 * R);
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(phi1 * 0.5)) t_1 = sin(Float64(Float64(lambda2 - lambda1) * -0.5)) ^ 2.0 t_2 = sin(Float64(phi1 * 0.5)) return Float64(atan(sqrt(fma(Float64(cos(phi1) * cos(phi2)), t_1, (fma(sin(Float64(phi2 * -0.5)), t_0, Float64(cos(Float64(phi2 * -0.5)) * t_2)) ^ 2.0))), sqrt(Float64(1.0 - fma(Float64(t_1 * cos(phi2)), cos(phi1), (Float64(Float64(cos(Float64(phi2 * 0.5)) * t_2) - Float64(sin(Float64(phi2 * 0.5)) * t_0)) ^ 2.0))))) * Float64(2.0 * R)) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(N[(lambda2 - lambda1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, N[(N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$1 + N[Power[N[(N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * t$95$0 + N[(N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(t$95$1 * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[Cos[phi1], $MachinePrecision] + N[Power[N[(N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * t$95$2), $MachinePrecision] - N[(N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(2.0 * R), $MachinePrecision]), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_1 := {\sin \left(\left(\lambda_2 - \lambda_1\right) \cdot -0.5\right)}^{2}\\
t_2 := \sin \left(\phi_1 \cdot 0.5\right)\\
\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_1 \cdot \cos \phi_2, t\_1, {\left(\mathsf{fma}\left(\sin \left(\phi_2 \cdot -0.5\right), t\_0, \cos \left(\phi_2 \cdot -0.5\right) \cdot t\_2\right)\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left(t\_1 \cdot \cos \phi_2, \cos \phi_1, {\left(\cos \left(\phi_2 \cdot 0.5\right) \cdot t\_2 - \sin \left(\phi_2 \cdot 0.5\right) \cdot t\_0\right)}^{2}\right)}} \cdot \left(2 \cdot R\right)
\end{array}
\end{array}
Initial program 65.5%
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-*.f6466.2
Applied rewrites66.2%
lift-sin.f64N/A
lift-/.f64N/A
div-invN/A
metadata-evalN/A
*-commutativeN/A
lift--.f64N/A
sub-negN/A
distribute-rgt-inN/A
lift-*.f64N/A
cancel-sign-sub-invN/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
sin-sumN/A
lift-sin.f64N/A
lower-fma.f64N/A
Applied rewrites79.1%
Taylor expanded in lambda1 around -inf
Applied rewrites79.2%
Final simplification79.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(pow
(fma
(sin (* phi2 -0.5))
(cos (* phi1 0.5))
(* (cos (* phi2 -0.5)) (sin (* phi1 0.5))))
2.0))
(t_1 (pow (sin (* (- lambda2 lambda1) -0.5)) 2.0)))
(*
(atan2
(sqrt (fma (* (cos phi1) (cos phi2)) t_1 t_0))
(sqrt (- 1.0 (fma (* t_1 (cos phi2)) (cos phi1) t_0))))
(* 2.0 R))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(fma(sin((phi2 * -0.5)), cos((phi1 * 0.5)), (cos((phi2 * -0.5)) * sin((phi1 * 0.5)))), 2.0);
double t_1 = pow(sin(((lambda2 - lambda1) * -0.5)), 2.0);
return atan2(sqrt(fma((cos(phi1) * cos(phi2)), t_1, t_0)), sqrt((1.0 - fma((t_1 * cos(phi2)), cos(phi1), t_0)))) * (2.0 * R);
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = fma(sin(Float64(phi2 * -0.5)), cos(Float64(phi1 * 0.5)), Float64(cos(Float64(phi2 * -0.5)) * sin(Float64(phi1 * 0.5)))) ^ 2.0 t_1 = sin(Float64(Float64(lambda2 - lambda1) * -0.5)) ^ 2.0 return Float64(atan(sqrt(fma(Float64(cos(phi1) * cos(phi2)), t_1, t_0)), sqrt(Float64(1.0 - fma(Float64(t_1 * cos(phi2)), cos(phi1), t_0)))) * Float64(2.0 * R)) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[(N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] + N[(N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(N[(lambda2 - lambda1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$1 + t$95$0), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(t$95$1 * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[Cos[phi1], $MachinePrecision] + t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(2.0 * R), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\left(\mathsf{fma}\left(\sin \left(\phi_2 \cdot -0.5\right), \cos \left(\phi_1 \cdot 0.5\right), \cos \left(\phi_2 \cdot -0.5\right) \cdot \sin \left(\phi_1 \cdot 0.5\right)\right)\right)}^{2}\\
t_1 := {\sin \left(\left(\lambda_2 - \lambda_1\right) \cdot -0.5\right)}^{2}\\
\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_1 \cdot \cos \phi_2, t\_1, t\_0\right)}}{\sqrt{1 - \mathsf{fma}\left(t\_1 \cdot \cos \phi_2, \cos \phi_1, t\_0\right)}} \cdot \left(2 \cdot R\right)
\end{array}
\end{array}
Initial program 65.5%
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-*.f6466.2
Applied rewrites66.2%
lift-sin.f64N/A
lift-/.f64N/A
div-invN/A
metadata-evalN/A
*-commutativeN/A
lift--.f64N/A
sub-negN/A
distribute-rgt-inN/A
lift-*.f64N/A
cancel-sign-sub-invN/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
sin-sumN/A
lift-sin.f64N/A
lower-fma.f64N/A
Applied rewrites79.1%
Taylor expanded in lambda1 around -inf
Applied rewrites79.2%
Applied rewrites79.2%
Final simplification79.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
(*
(*
(atan2
(sqrt (fma t_0 t_1 (pow (sin (* (- phi1 phi2) 0.5)) 2.0)))
(sqrt
(-
1.0
(fma
t_0
t_1
(pow
(fma
(sin (* phi2 -0.5))
(cos (* -0.5 phi1))
(* (cos (* phi2 -0.5)) (sin (* phi1 0.5))))
2.0)))))
2.0)
R)))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
return (atan2(sqrt(fma(t_0, t_1, pow(sin(((phi1 - phi2) * 0.5)), 2.0))), sqrt((1.0 - fma(t_0, t_1, pow(fma(sin((phi2 * -0.5)), cos((-0.5 * phi1)), (cos((phi2 * -0.5)) * sin((phi1 * 0.5)))), 2.0))))) * 2.0) * R;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 return Float64(Float64(atan(sqrt(fma(t_0, t_1, (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0))), sqrt(Float64(1.0 - fma(t_0, t_1, (fma(sin(Float64(phi2 * -0.5)), cos(Float64(-0.5 * phi1)), Float64(cos(Float64(phi2 * -0.5)) * sin(Float64(phi1 * 0.5)))) ^ 2.0))))) * 2.0) * R) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(N[(N[ArcTan[N[Sqrt[N[(t$95$0 * t$95$1 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 * t$95$1 + N[Power[N[(N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision] + N[(N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, t\_1, {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left(t\_0, t\_1, {\left(\mathsf{fma}\left(\sin \left(\phi_2 \cdot -0.5\right), \cos \left(-0.5 \cdot \phi_1\right), \cos \left(\phi_2 \cdot -0.5\right) \cdot \sin \left(\phi_1 \cdot 0.5\right)\right)\right)}^{2}\right)}} \cdot 2\right) \cdot R
\end{array}
\end{array}
Initial program 65.5%
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-*.f6466.2
Applied rewrites66.2%
Taylor expanded in lambda1 around 0
Applied rewrites66.2%
Final simplification66.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda2 lambda1) -0.5)) 2.0)))
(*
(atan2
(sqrt
(fma
(* (cos phi1) (cos phi2))
t_0
(pow
(fma
(sin (* phi2 -0.5))
(cos (* phi1 0.5))
(* (cos (* phi2 -0.5)) (sin (* phi1 0.5))))
2.0)))
(sqrt
(-
1.0
(fma
(* t_0 (cos phi2))
(cos phi1)
(- 0.5 (* (cos (* (* (- phi1 phi2) 0.5) 2.0)) 0.5))))))
(* 2.0 R))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda2 - lambda1) * -0.5)), 2.0);
return atan2(sqrt(fma((cos(phi1) * cos(phi2)), t_0, pow(fma(sin((phi2 * -0.5)), cos((phi1 * 0.5)), (cos((phi2 * -0.5)) * sin((phi1 * 0.5)))), 2.0))), sqrt((1.0 - fma((t_0 * cos(phi2)), cos(phi1), (0.5 - (cos((((phi1 - phi2) * 0.5) * 2.0)) * 0.5)))))) * (2.0 * R);
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda2 - lambda1) * -0.5)) ^ 2.0 return Float64(atan(sqrt(fma(Float64(cos(phi1) * cos(phi2)), t_0, (fma(sin(Float64(phi2 * -0.5)), cos(Float64(phi1 * 0.5)), Float64(cos(Float64(phi2 * -0.5)) * sin(Float64(phi1 * 0.5)))) ^ 2.0))), sqrt(Float64(1.0 - fma(Float64(t_0 * cos(phi2)), cos(phi1), Float64(0.5 - Float64(cos(Float64(Float64(Float64(phi1 - phi2) * 0.5) * 2.0)) * 0.5)))))) * Float64(2.0 * R)) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda2 - lambda1), $MachinePrecision] * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, 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[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] + N[(N[Cos[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $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[(0.5 - N[(N[Cos[N[(N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision] * 2.0), $MachinePrecision]], $MachinePrecision] * 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(2.0 * R), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_2 - \lambda_1\right) \cdot -0.5\right)}^{2}\\
\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_1 \cdot \cos \phi_2, t\_0, {\left(\mathsf{fma}\left(\sin \left(\phi_2 \cdot -0.5\right), \cos \left(\phi_1 \cdot 0.5\right), \cos \left(\phi_2 \cdot -0.5\right) \cdot \sin \left(\phi_1 \cdot 0.5\right)\right)\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left(t\_0 \cdot \cos \phi_2, \cos \phi_1, 0.5 - \cos \left(\left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right) \cdot 2\right) \cdot 0.5\right)}} \cdot \left(2 \cdot R\right)
\end{array}
\end{array}
Initial program 65.5%
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-*.f6466.2
Applied rewrites66.2%
lift-sin.f64N/A
lift-/.f64N/A
div-invN/A
metadata-evalN/A
*-commutativeN/A
lift--.f64N/A
sub-negN/A
distribute-rgt-inN/A
lift-*.f64N/A
cancel-sign-sub-invN/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
sin-sumN/A
lift-sin.f64N/A
lower-fma.f64N/A
Applied rewrites79.1%
Taylor expanded in lambda1 around -inf
Applied rewrites79.2%
Applied rewrites66.1%
Final simplification66.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
(*
(atan2
(sqrt
(+
(* (* t_0 (* (cos phi1) (cos phi2))) t_0)
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt
(-
1.0
(/
(fma
(-
(cos (/ 0.0 (/ 2.0 (- phi1 phi2))))
(cos (* (* (- phi1 phi2) 0.5) 2.0)))
2.0
(*
(*
(+ (cos (+ phi2 phi1)) (cos (- phi1 phi2)))
(pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
2.0))
4.0))))
2.0)
R)))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
return (atan2(sqrt((((t_0 * (cos(phi1) * cos(phi2))) * t_0) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 - (fma((cos((0.0 / (2.0 / (phi1 - phi2)))) - cos((((phi1 - phi2) * 0.5) * 2.0))), 2.0, (((cos((phi2 + phi1)) + cos((phi1 - phi2))) * pow(sin(((lambda1 - lambda2) * 0.5)), 2.0)) * 2.0)) / 4.0)))) * 2.0) * R;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(Float64(atan(sqrt(Float64(Float64(Float64(t_0 * Float64(cos(phi1) * cos(phi2))) * t_0) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - Float64(fma(Float64(cos(Float64(0.0 / Float64(2.0 / Float64(phi1 - phi2)))) - cos(Float64(Float64(Float64(phi1 - phi2) * 0.5) * 2.0))), 2.0, Float64(Float64(Float64(cos(Float64(phi2 + phi1)) + cos(Float64(phi1 - phi2))) * (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0)) * 2.0)) / 4.0)))) * 2.0) * R) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(N[(N[ArcTan[N[Sqrt[N[(N[(N[(t$95$0 * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[(N[Cos[N[(0.0 / N[(2.0 / N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] - N[Cos[N[(N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision] * 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * 2.0 + N[(N[(N[(N[Cos[N[(phi2 + phi1), $MachinePrecision]], $MachinePrecision] + N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] * 2.0), $MachinePrecision]), $MachinePrecision] / 4.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\left(\tan^{-1}_* \frac{\sqrt{\left(t\_0 \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)\right) \cdot t\_0 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{1 - \frac{\mathsf{fma}\left(\cos \left(\frac{0}{\frac{2}{\phi_1 - \phi_2}}\right) - \cos \left(\left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right) \cdot 2\right), 2, \left(\left(\cos \left(\phi_2 + \phi_1\right) + \cos \left(\phi_1 - \phi_2\right)\right) \cdot {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\right) \cdot 2\right)}{4}}} \cdot 2\right) \cdot R
\end{array}
\end{array}
Initial program 65.5%
Applied rewrites65.6%
Final simplification65.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (cos phi1) (cos phi2)))
(t_2 (sin (* (- phi1 phi2) 0.5))))
(*
(*
(atan2
(sqrt (fma t_2 t_2 (* (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0) t_1)))
(sqrt
(- 1.0 (+ (* (* t_0 t_1) t_0) (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))))
2.0)
R)))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = cos(phi1) * cos(phi2);
double t_2 = sin(((phi1 - phi2) * 0.5));
return (atan2(sqrt(fma(t_2, t_2, (pow(sin(((lambda1 - lambda2) * 0.5)), 2.0) * t_1))), sqrt((1.0 - (((t_0 * t_1) * t_0) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))))) * 2.0) * R;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(cos(phi1) * cos(phi2)) t_2 = sin(Float64(Float64(phi1 - phi2) * 0.5)) return Float64(Float64(atan(sqrt(fma(t_2, t_2, Float64((sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0) * t_1))), sqrt(Float64(1.0 - Float64(Float64(Float64(t_0 * t_1) * t_0) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))))) * 2.0) * R) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision]}, N[(N[(N[ArcTan[N[Sqrt[N[(t$95$2 * t$95$2 + N[(N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[(t$95$0 * t$95$1), $MachinePrecision] * t$95$0), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
t_2 := \sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)\\
\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_2, t\_2, {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2} \cdot t\_1\right)}}{\sqrt{1 - \left(\left(t\_0 \cdot t\_1\right) \cdot t\_0 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\right)}} \cdot 2\right) \cdot R
\end{array}
\end{array}
Initial program 65.5%
lift-+.f64N/A
lift-pow.f64N/A
unpow2N/A
lower-fma.f6465.5
lift-/.f64N/A
clear-numN/A
associate-/r/N/A
metadata-evalN/A
lower-*.f6465.5
lift-/.f64N/A
clear-numN/A
associate-/r/N/A
metadata-evalN/A
lower-*.f6465.5
lift-*.f64N/A
Applied rewrites65.5%
Final simplification65.5%
(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 phi1) (pow (sin (* phi1 0.5)) 2.0)))
(t_2 (sqrt t_1))
(t_3 (sin (/ (- lambda1 lambda2) 2.0))))
(if (<= t_3 -0.02)
(*
(*
(atan2 t_2 (sqrt (- (pow (cos (* -0.5 phi1)) 2.0) (* t_0 (cos phi1)))))
2.0)
R)
(if (<= t_3 2e-7)
(*
(*
(atan2
(sqrt
(+
(* (* t_3 (* (cos phi1) (cos phi2))) t_3)
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (- 1.0 (pow (sin (* (- phi1 phi2) 0.5)) 2.0))))
2.0)
R)
(* (* (atan2 t_2 (sqrt (- 1.0 t_1))) 2.0) R)))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_1 = fma(t_0, cos(phi1), pow(sin((phi1 * 0.5)), 2.0));
double t_2 = sqrt(t_1);
double t_3 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if (t_3 <= -0.02) {
tmp = (atan2(t_2, sqrt((pow(cos((-0.5 * phi1)), 2.0) - (t_0 * cos(phi1))))) * 2.0) * R;
} else if (t_3 <= 2e-7) {
tmp = (atan2(sqrt((((t_3 * (cos(phi1) * cos(phi2))) * t_3) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 - pow(sin(((phi1 - phi2) * 0.5)), 2.0)))) * 2.0) * R;
} else {
tmp = (atan2(t_2, sqrt((1.0 - t_1))) * 2.0) * R;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_1 = fma(t_0, cos(phi1), (sin(Float64(phi1 * 0.5)) ^ 2.0)) t_2 = sqrt(t_1) t_3 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if (t_3 <= -0.02) tmp = Float64(Float64(atan(t_2, sqrt(Float64((cos(Float64(-0.5 * phi1)) ^ 2.0) - Float64(t_0 * cos(phi1))))) * 2.0) * R); elseif (t_3 <= 2e-7) tmp = Float64(Float64(atan(sqrt(Float64(Float64(Float64(t_3 * Float64(cos(phi1) * cos(phi2))) * t_3) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0)))) * 2.0) * R); else tmp = Float64(Float64(atan(t_2, sqrt(Float64(1.0 - t_1))) * 2.0) * R); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[(t$95$0 * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Sqrt[t$95$1], $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[t$95$3, -0.02], N[(N[(N[ArcTan[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]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], If[LessEqual[t$95$3, 2e-7], N[(N[(N[ArcTan[N[Sqrt[N[(N[(N[(t$95$3 * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * t$95$3), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], N[(N[(N[ArcTan[t$95$2 / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_1 := \mathsf{fma}\left(t\_0, \cos \phi_1, {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)\\
t_2 := \sqrt{t\_1}\\
t_3 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;t\_3 \leq -0.02:\\
\;\;\;\;\left(\tan^{-1}_* \frac{t\_2}{\sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - t\_0 \cdot \cos \phi_1}} \cdot 2\right) \cdot R\\
\mathbf{elif}\;t\_3 \leq 2 \cdot 10^{-7}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\left(t\_3 \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)\right) \cdot t\_3 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{1 - {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{t\_2}{\sqrt{1 - t\_1}} \cdot 2\right) \cdot R\\
\end{array}
\end{array}
if (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < -0.0200000000000000004Initial program 54.9%
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
*-commutativeN/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites43.0%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6443.5
Applied rewrites43.5%
if -0.0200000000000000004 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < 1.9999999999999999e-7Initial program 81.6%
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
*-commutativeN/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites68.4%
Taylor expanded in lambda1 around 0
Applied rewrites81.5%
Taylor expanded in lambda2 around 0
Applied rewrites81.5%
if 1.9999999999999999e-7 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) Initial program 64.9%
Taylor expanded in lambda1 around 0
associate-*r*N/A
associate-*r*N/A
associate-*r*N/A
lower-fma.f64N/A
Applied rewrites36.7%
Taylor expanded in lambda2 around 0
Applied rewrites16.8%
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-*.f6416.4
Applied rewrites16.4%
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-*.f6449.9
Applied rewrites49.9%
Final simplification55.2%
(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
(*
(*
(atan2
(sqrt (fma t_0 (cos phi1) (pow (sin (* phi1 0.5)) 2.0)))
(sqrt (- (pow (cos (* -0.5 phi1)) 2.0) (* t_0 (cos phi1)))))
2.0)
R)))
(if (<= t_1 -0.02)
t_2
(if (<= t_1 2e-7)
(*
(*
(atan2
(sqrt
(+
(* (* t_1 (* (cos phi1) (cos phi2))) t_1)
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (- 1.0 (pow (sin (* (- phi1 phi2) 0.5)) 2.0))))
2.0)
R)
t_2))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = (atan2(sqrt(fma(t_0, cos(phi1), pow(sin((phi1 * 0.5)), 2.0))), sqrt((pow(cos((-0.5 * phi1)), 2.0) - (t_0 * cos(phi1))))) * 2.0) * R;
double tmp;
if (t_1 <= -0.02) {
tmp = t_2;
} else if (t_1 <= 2e-7) {
tmp = (atan2(sqrt((((t_1 * (cos(phi1) * cos(phi2))) * t_1) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 - pow(sin(((phi1 - phi2) * 0.5)), 2.0)))) * 2.0) * R;
} else {
tmp = t_2;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(Float64(atan(sqrt(fma(t_0, cos(phi1), (sin(Float64(phi1 * 0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(-0.5 * phi1)) ^ 2.0) - Float64(t_0 * cos(phi1))))) * 2.0) * R) tmp = 0.0 if (t_1 <= -0.02) tmp = t_2; elseif (t_1 <= 2e-7) tmp = Float64(Float64(atan(sqrt(Float64(Float64(Float64(t_1 * Float64(cos(phi1) * cos(phi2))) * t_1) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0)))) * 2.0) * R); else tmp = t_2; end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(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[ArcTan[N[Sqrt[N[(t$95$0 * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(t$95$0 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]}, If[LessEqual[t$95$1, -0.02], t$95$2, If[LessEqual[t$95$1, 2e-7], N[(N[(N[ArcTan[N[Sqrt[N[(N[(N[(t$95$1 * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * t$95$1), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], t$95$2]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\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(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \cos \phi_1, {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}{\sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - t\_0 \cdot \cos \phi_1}} \cdot 2\right) \cdot R\\
\mathbf{if}\;t\_1 \leq -0.02:\\
\;\;\;\;t\_2\\
\mathbf{elif}\;t\_1 \leq 2 \cdot 10^{-7}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\left(t\_1 \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)\right) \cdot t\_1 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{1 - {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;t\_2\\
\end{array}
\end{array}
if (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < -0.0200000000000000004 or 1.9999999999999999e-7 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) Initial program 60.5%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
*-commutativeN/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites47.2%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6447.1
Applied rewrites47.1%
if -0.0200000000000000004 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < 1.9999999999999999e-7Initial program 81.6%
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
*-commutativeN/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites68.4%
Taylor expanded in lambda1 around 0
Applied rewrites81.5%
Taylor expanded in lambda2 around 0
Applied rewrites81.5%
Final simplification55.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi1) (cos phi2)))
(t_1 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
(*
(atan2
(sqrt (fma t_1 t_0 (pow (sin (* (- phi1 phi2) 0.5)) 2.0)))
(sqrt (- (pow (cos (/ (- phi1 phi2) -2.0)) 2.0) (* t_1 t_0))))
(* 2.0 R))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi1) * cos(phi2);
double t_1 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
return atan2(sqrt(fma(t_1, t_0, pow(sin(((phi1 - phi2) * 0.5)), 2.0))), sqrt((pow(cos(((phi1 - phi2) / -2.0)), 2.0) - (t_1 * t_0)))) * (2.0 * R);
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi1) * cos(phi2)) t_1 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 return Float64(atan(sqrt(fma(t_1, t_0, (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(Float64(phi1 - phi2) / -2.0)) ^ 2.0) - Float64(t_1 * t_0)))) * Float64(2.0 * R)) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(N[ArcTan[N[Sqrt[N[(t$95$1 * t$95$0 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(N[(phi1 - phi2), $MachinePrecision] / -2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(t$95$1 * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(2.0 * R), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_1 \cdot \cos \phi_2\\
t_1 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_1, t\_0, {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\right)}}{\sqrt{{\cos \left(\frac{\phi_1 - \phi_2}{-2}\right)}^{2} - t\_1 \cdot t\_0}} \cdot \left(2 \cdot R\right)
\end{array}
\end{array}
Initial program 65.5%
Applied rewrites65.5%
Final simplification65.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(fma
(* (cos phi1) (cos phi2))
(pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)
(pow (sin (* (- phi1 phi2) 0.5)) 2.0))))
(* (atan2 (sqrt t_0) (sqrt (- 1.0 t_0))) (* 2.0 R))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = fma((cos(phi1) * cos(phi2)), pow(sin(((lambda1 - lambda2) * 0.5)), 2.0), pow(sin(((phi1 - phi2) * 0.5)), 2.0));
return atan2(sqrt(t_0), sqrt((1.0 - t_0))) * (2.0 * R);
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = fma(Float64(cos(phi1) * cos(phi2)), (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0), (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0)) return Float64(atan(sqrt(t_0), sqrt(Float64(1.0 - t_0))) * Float64(2.0 * R)) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, N[(N[ArcTan[N[Sqrt[t$95$0], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(2.0 * R), $MachinePrecision]), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \mathsf{fma}\left(\cos \phi_1 \cdot \cos \phi_2, {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}, {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\right)\\
\tan^{-1}_* \frac{\sqrt{t\_0}}{\sqrt{1 - t\_0}} \cdot \left(2 \cdot R\right)
\end{array}
\end{array}
Initial program 65.5%
Taylor expanded in lambda1 around 0
Applied rewrites65.5%
Final simplification65.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_1 (sqrt (- (pow (cos (* -0.5 phi1)) 2.0) (* t_0 (cos phi1)))))
(t_2 (sin (/ (- lambda1 lambda2) 2.0))))
(if (<= phi1 -6.5e-5)
(*
(*
(atan2
(sqrt
(/
(fma
(-
(cos (/ 0.0 (/ 2.0 (- phi1 phi2))))
(cos (* (* (- phi1 phi2) 0.5) 2.0)))
2.0
(* (* (+ (cos (+ phi2 phi1)) (cos (- phi1 phi2))) t_0) 2.0))
4.0))
t_1)
2.0)
R)
(if (<= phi1 1.4e-5)
(*
(*
(atan2
(sqrt
(+
(* (* t_2 (* (cos phi1) (cos phi2))) t_2)
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (- 1.0 (fma t_0 (cos phi2) (pow (sin (* phi2 -0.5)) 2.0)))))
2.0)
R)
(*
(*
(atan2 (sqrt (fma t_0 (cos phi1) (pow (sin (* phi1 0.5)) 2.0))) t_1)
2.0)
R)))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_1 = sqrt((pow(cos((-0.5 * phi1)), 2.0) - (t_0 * cos(phi1))));
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if (phi1 <= -6.5e-5) {
tmp = (atan2(sqrt((fma((cos((0.0 / (2.0 / (phi1 - phi2)))) - cos((((phi1 - phi2) * 0.5) * 2.0))), 2.0, (((cos((phi2 + phi1)) + cos((phi1 - phi2))) * t_0) * 2.0)) / 4.0)), t_1) * 2.0) * R;
} else if (phi1 <= 1.4e-5) {
tmp = (atan2(sqrt((((t_2 * (cos(phi1) * cos(phi2))) * t_2) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 - fma(t_0, cos(phi2), pow(sin((phi2 * -0.5)), 2.0))))) * 2.0) * R;
} else {
tmp = (atan2(sqrt(fma(t_0, cos(phi1), pow(sin((phi1 * 0.5)), 2.0))), t_1) * 2.0) * R;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_1 = sqrt(Float64((cos(Float64(-0.5 * phi1)) ^ 2.0) - Float64(t_0 * cos(phi1)))) t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if (phi1 <= -6.5e-5) tmp = Float64(Float64(atan(sqrt(Float64(fma(Float64(cos(Float64(0.0 / Float64(2.0 / Float64(phi1 - phi2)))) - cos(Float64(Float64(Float64(phi1 - phi2) * 0.5) * 2.0))), 2.0, Float64(Float64(Float64(cos(Float64(phi2 + phi1)) + cos(Float64(phi1 - phi2))) * t_0) * 2.0)) / 4.0)), t_1) * 2.0) * R); elseif (phi1 <= 1.4e-5) tmp = Float64(Float64(atan(sqrt(Float64(Float64(Float64(t_2 * Float64(cos(phi1) * cos(phi2))) * t_2) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - fma(t_0, cos(phi2), (sin(Float64(phi2 * -0.5)) ^ 2.0))))) * 2.0) * R); else tmp = Float64(Float64(atan(sqrt(fma(t_0, cos(phi1), (sin(Float64(phi1 * 0.5)) ^ 2.0))), t_1) * 2.0) * R); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sqrt[N[(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$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi1, -6.5e-5], N[(N[(N[ArcTan[N[Sqrt[N[(N[(N[(N[Cos[N[(0.0 / N[(2.0 / N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] - N[Cos[N[(N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision] * 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * 2.0 + N[(N[(N[(N[Cos[N[(phi2 + phi1), $MachinePrecision]], $MachinePrecision] + N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * 2.0), $MachinePrecision]), $MachinePrecision] / 4.0), $MachinePrecision]], $MachinePrecision] / t$95$1], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], If[LessEqual[phi1, 1.4e-5], N[(N[(N[ArcTan[N[Sqrt[N[(N[(N[(t$95$2 * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * t$95$2), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], N[(N[(N[ArcTan[N[Sqrt[N[(t$95$0 * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$1], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_1 := \sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - t\_0 \cdot \cos \phi_1}\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\phi_1 \leq -6.5 \cdot 10^{-5}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\frac{\mathsf{fma}\left(\cos \left(\frac{0}{\frac{2}{\phi_1 - \phi_2}}\right) - \cos \left(\left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right) \cdot 2\right), 2, \left(\left(\cos \left(\phi_2 + \phi_1\right) + \cos \left(\phi_1 - \phi_2\right)\right) \cdot t\_0\right) \cdot 2\right)}{4}}}{t\_1} \cdot 2\right) \cdot R\\
\mathbf{elif}\;\phi_1 \leq 1.4 \cdot 10^{-5}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\left(t\_2 \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)\right) \cdot t\_2 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{1 - \mathsf{fma}\left(t\_0, \cos \phi_2, {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \cos \phi_1, {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}{t\_1} \cdot 2\right) \cdot R\\
\end{array}
\end{array}
if phi1 < -6.49999999999999943e-5Initial program 54.0%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
*-commutativeN/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites53.7%
Applied rewrites54.5%
if -6.49999999999999943e-5 < phi1 < 1.39999999999999998e-5Initial program 74.7%
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
*-commutativeN/A
lower-*.f6474.7
Applied rewrites74.7%
if 1.39999999999999998e-5 < phi1 Initial program 57.9%
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
*-commutativeN/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites58.6%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6459.0
Applied rewrites59.0%
Final simplification65.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(+
(* (* t_0 (* (cos phi1) (cos phi2))) t_0)
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(t_2 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_3 (sqrt (fma t_2 (cos phi1) (pow (sin (* phi1 0.5)) 2.0)))))
(if (<= phi1 -2.1e-5)
(* (* (atan2 t_3 (sqrt (- 1.0 t_1))) 2.0) R)
(if (<= phi1 1.4e-5)
(*
(*
(atan2
(sqrt t_1)
(sqrt (- 1.0 (fma t_2 (cos phi2) (pow (sin (* phi2 -0.5)) 2.0)))))
2.0)
R)
(*
(*
(atan2
t_3
(sqrt (- (pow (cos (* -0.5 phi1)) 2.0) (* t_2 (cos phi1)))))
2.0)
R)))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = ((t_0 * (cos(phi1) * cos(phi2))) * t_0) + pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double t_2 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_3 = sqrt(fma(t_2, cos(phi1), pow(sin((phi1 * 0.5)), 2.0)));
double tmp;
if (phi1 <= -2.1e-5) {
tmp = (atan2(t_3, sqrt((1.0 - t_1))) * 2.0) * R;
} else if (phi1 <= 1.4e-5) {
tmp = (atan2(sqrt(t_1), sqrt((1.0 - fma(t_2, cos(phi2), pow(sin((phi2 * -0.5)), 2.0))))) * 2.0) * R;
} else {
tmp = (atan2(t_3, sqrt((pow(cos((-0.5 * phi1)), 2.0) - (t_2 * cos(phi1))))) * 2.0) * R;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(Float64(t_0 * Float64(cos(phi1) * cos(phi2))) * t_0) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0)) t_2 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_3 = sqrt(fma(t_2, cos(phi1), (sin(Float64(phi1 * 0.5)) ^ 2.0))) tmp = 0.0 if (phi1 <= -2.1e-5) tmp = Float64(Float64(atan(t_3, sqrt(Float64(1.0 - t_1))) * 2.0) * R); elseif (phi1 <= 1.4e-5) tmp = Float64(Float64(atan(sqrt(t_1), sqrt(Float64(1.0 - fma(t_2, cos(phi2), (sin(Float64(phi2 * -0.5)) ^ 2.0))))) * 2.0) * R); else tmp = Float64(Float64(atan(t_3, sqrt(Float64((cos(Float64(-0.5 * phi1)) ^ 2.0) - Float64(t_2 * cos(phi1))))) * 2.0) * R); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[(t$95$0 * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $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[Sqrt[N[(t$95$2 * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi1, -2.1e-5], N[(N[(N[ArcTan[t$95$3 / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], If[LessEqual[phi1, 1.4e-5], N[(N[(N[ArcTan[N[Sqrt[t$95$1], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$2 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], N[(N[(N[ArcTan[t$95$3 / N[Sqrt[N[(N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(t$95$2 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \left(t\_0 \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)\right) \cdot t\_0 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
t_2 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_3 := \sqrt{\mathsf{fma}\left(t\_2, \cos \phi_1, {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}\\
\mathbf{if}\;\phi_1 \leq -2.1 \cdot 10^{-5}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{t\_3}{\sqrt{1 - t\_1}} \cdot 2\right) \cdot R\\
\mathbf{elif}\;\phi_1 \leq 1.4 \cdot 10^{-5}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - \mathsf{fma}\left(t\_2, \cos \phi_2, {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{t\_3}{\sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - t\_2 \cdot \cos \phi_1}} \cdot 2\right) \cdot R\\
\end{array}
\end{array}
if phi1 < -2.09999999999999988e-5Initial program 54.0%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f6454.4
Applied rewrites54.4%
if -2.09999999999999988e-5 < phi1 < 1.39999999999999998e-5Initial program 74.7%
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
*-commutativeN/A
lower-*.f6474.7
Applied rewrites74.7%
if 1.39999999999999998e-5 < phi1 Initial program 57.9%
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
*-commutativeN/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites58.6%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6459.0
Applied rewrites59.0%
Final simplification65.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(+
(* (* t_0 (* (cos phi1) (cos phi2))) t_0)
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(t_2 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_3 (sqrt (fma t_2 (cos phi1) (pow (sin (* phi1 0.5)) 2.0)))))
(if (<= phi1 -2.1e-5)
(* (* (atan2 t_3 (sqrt (- 1.0 t_1))) 2.0) R)
(if (<= phi1 1.4e-5)
(*
(*
(atan2
(sqrt t_1)
(sqrt (- (pow (cos (* phi2 0.5)) 2.0) (* t_2 (cos phi2)))))
2.0)
R)
(*
(*
(atan2
t_3
(sqrt (- (pow (cos (* -0.5 phi1)) 2.0) (* t_2 (cos phi1)))))
2.0)
R)))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = ((t_0 * (cos(phi1) * cos(phi2))) * t_0) + pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double t_2 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_3 = sqrt(fma(t_2, cos(phi1), pow(sin((phi1 * 0.5)), 2.0)));
double tmp;
if (phi1 <= -2.1e-5) {
tmp = (atan2(t_3, sqrt((1.0 - t_1))) * 2.0) * R;
} else if (phi1 <= 1.4e-5) {
tmp = (atan2(sqrt(t_1), sqrt((pow(cos((phi2 * 0.5)), 2.0) - (t_2 * cos(phi2))))) * 2.0) * R;
} else {
tmp = (atan2(t_3, sqrt((pow(cos((-0.5 * phi1)), 2.0) - (t_2 * cos(phi1))))) * 2.0) * R;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(Float64(t_0 * Float64(cos(phi1) * cos(phi2))) * t_0) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0)) t_2 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_3 = sqrt(fma(t_2, cos(phi1), (sin(Float64(phi1 * 0.5)) ^ 2.0))) tmp = 0.0 if (phi1 <= -2.1e-5) tmp = Float64(Float64(atan(t_3, sqrt(Float64(1.0 - t_1))) * 2.0) * R); elseif (phi1 <= 1.4e-5) tmp = Float64(Float64(atan(sqrt(t_1), sqrt(Float64((cos(Float64(phi2 * 0.5)) ^ 2.0) - Float64(t_2 * cos(phi2))))) * 2.0) * R); else tmp = Float64(Float64(atan(t_3, sqrt(Float64((cos(Float64(-0.5 * phi1)) ^ 2.0) - Float64(t_2 * cos(phi1))))) * 2.0) * R); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[(t$95$0 * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $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[Sqrt[N[(t$95$2 * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi1, -2.1e-5], N[(N[(N[ArcTan[t$95$3 / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], If[LessEqual[phi1, 1.4e-5], N[(N[(N[ArcTan[N[Sqrt[t$95$1], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(t$95$2 * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], N[(N[(N[ArcTan[t$95$3 / N[Sqrt[N[(N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(t$95$2 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \left(t\_0 \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)\right) \cdot t\_0 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
t_2 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_3 := \sqrt{\mathsf{fma}\left(t\_2, \cos \phi_1, {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}\\
\mathbf{if}\;\phi_1 \leq -2.1 \cdot 10^{-5}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{t\_3}{\sqrt{1 - t\_1}} \cdot 2\right) \cdot R\\
\mathbf{elif}\;\phi_1 \leq 1.4 \cdot 10^{-5}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{{\cos \left(\phi_2 \cdot 0.5\right)}^{2} - t\_2 \cdot \cos \phi_2}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{t\_3}{\sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - t\_2 \cdot \cos \phi_1}} \cdot 2\right) \cdot R\\
\end{array}
\end{array}
if phi1 < -2.09999999999999988e-5Initial program 54.0%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f6454.4
Applied rewrites54.4%
if -2.09999999999999988e-5 < phi1 < 1.39999999999999998e-5Initial program 74.7%
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
*-commutativeN/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites74.7%
if 1.39999999999999998e-5 < phi1 Initial program 57.9%
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
*-commutativeN/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites58.6%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6459.0
Applied rewrites59.0%
Final simplification65.8%
(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
(*
(*
(atan2
(sqrt (fma t_1 (cos phi1) (pow (sin (* phi1 0.5)) 2.0)))
(sqrt (- (pow (cos (* -0.5 phi1)) 2.0) (* t_1 (cos phi1)))))
2.0)
R)))
(if (<= phi1 -2.1e-5)
t_2
(if (<= phi1 1.4e-5)
(*
(*
(atan2
(sqrt
(+
(* (* t_0 (* (cos phi1) (cos phi2))) t_0)
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (- (pow (cos (* phi2 0.5)) 2.0) (* t_1 (cos phi2)))))
2.0)
R)
t_2))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_2 = (atan2(sqrt(fma(t_1, cos(phi1), pow(sin((phi1 * 0.5)), 2.0))), sqrt((pow(cos((-0.5 * phi1)), 2.0) - (t_1 * cos(phi1))))) * 2.0) * R;
double tmp;
if (phi1 <= -2.1e-5) {
tmp = t_2;
} else if (phi1 <= 1.4e-5) {
tmp = (atan2(sqrt((((t_0 * (cos(phi1) * cos(phi2))) * t_0) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((pow(cos((phi2 * 0.5)), 2.0) - (t_1 * cos(phi2))))) * 2.0) * R;
} else {
tmp = t_2;
}
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 = Float64(Float64(atan(sqrt(fma(t_1, cos(phi1), (sin(Float64(phi1 * 0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(-0.5 * phi1)) ^ 2.0) - Float64(t_1 * cos(phi1))))) * 2.0) * R) tmp = 0.0 if (phi1 <= -2.1e-5) tmp = t_2; elseif (phi1 <= 1.4e-5) tmp = Float64(Float64(atan(sqrt(Float64(Float64(Float64(t_0 * Float64(cos(phi1) * cos(phi2))) * t_0) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64((cos(Float64(phi2 * 0.5)) ^ 2.0) - Float64(t_1 * cos(phi2))))) * 2.0) * R); else tmp = t_2; end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[(N[(N[ArcTan[N[Sqrt[N[(t$95$1 * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(t$95$1 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]}, If[LessEqual[phi1, -2.1e-5], t$95$2, If[LessEqual[phi1, 1.4e-5], N[(N[(N[ArcTan[N[Sqrt[N[(N[(N[(t$95$0 * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(t$95$1 * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], t$95$2]]]]]
\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 := \left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_1, \cos \phi_1, {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}{\sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - t\_1 \cdot \cos \phi_1}} \cdot 2\right) \cdot R\\
\mathbf{if}\;\phi_1 \leq -2.1 \cdot 10^{-5}:\\
\;\;\;\;t\_2\\
\mathbf{elif}\;\phi_1 \leq 1.4 \cdot 10^{-5}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\left(t\_0 \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)\right) \cdot t\_0 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{{\cos \left(\phi_2 \cdot 0.5\right)}^{2} - t\_1 \cdot \cos \phi_2}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;t\_2\\
\end{array}
\end{array}
if phi1 < -2.09999999999999988e-5 or 1.39999999999999998e-5 < phi1 Initial program 56.0%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
*-commutativeN/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites56.1%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6456.7
Applied rewrites56.7%
if -2.09999999999999988e-5 < phi1 < 1.39999999999999998e-5Initial program 74.7%
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
*-commutativeN/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites74.7%
Final simplification65.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_1 (* (cos phi1) (cos phi2)))
(t_2 (sin (* (- phi1 phi2) 0.5)))
(t_3
(*
(*
(atan2
(sqrt (fma t_1 (pow (sin (* lambda1 0.5)) 2.0) (pow t_2 2.0)))
(sqrt (- 1.0 (fma t_0 (cos phi2) (pow (sin (* phi2 -0.5)) 2.0)))))
2.0)
R)))
(if (<= phi2 -0.0105)
t_3
(if (<= phi2 2700000000.0)
(*
(*
(atan2
(sqrt (fma t_2 t_2 (* t_0 t_1)))
(sqrt (- (pow (cos (* -0.5 phi1)) 2.0) (* t_0 (cos phi1)))))
2.0)
R)
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 = cos(phi1) * cos(phi2);
double t_2 = sin(((phi1 - phi2) * 0.5));
double t_3 = (atan2(sqrt(fma(t_1, pow(sin((lambda1 * 0.5)), 2.0), pow(t_2, 2.0))), sqrt((1.0 - fma(t_0, cos(phi2), pow(sin((phi2 * -0.5)), 2.0))))) * 2.0) * R;
double tmp;
if (phi2 <= -0.0105) {
tmp = t_3;
} else if (phi2 <= 2700000000.0) {
tmp = (atan2(sqrt(fma(t_2, t_2, (t_0 * t_1))), sqrt((pow(cos((-0.5 * phi1)), 2.0) - (t_0 * cos(phi1))))) * 2.0) * R;
} else {
tmp = t_3;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_1 = Float64(cos(phi1) * cos(phi2)) t_2 = sin(Float64(Float64(phi1 - phi2) * 0.5)) t_3 = Float64(Float64(atan(sqrt(fma(t_1, (sin(Float64(lambda1 * 0.5)) ^ 2.0), (t_2 ^ 2.0))), sqrt(Float64(1.0 - fma(t_0, cos(phi2), (sin(Float64(phi2 * -0.5)) ^ 2.0))))) * 2.0) * R) tmp = 0.0 if (phi2 <= -0.0105) tmp = t_3; elseif (phi2 <= 2700000000.0) tmp = Float64(Float64(atan(sqrt(fma(t_2, t_2, Float64(t_0 * t_1))), sqrt(Float64((cos(Float64(-0.5 * phi1)) ^ 2.0) - Float64(t_0 * cos(phi1))))) * 2.0) * R); else tmp = 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[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[(N[(N[ArcTan[N[Sqrt[N[(t$95$1 * N[Power[N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[t$95$2, 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]}, If[LessEqual[phi2, -0.0105], t$95$3, If[LessEqual[phi2, 2700000000.0], N[(N[(N[ArcTan[N[Sqrt[N[(t$95$2 * t$95$2 + N[(t$95$0 * t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(t$95$0 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], t$95$3]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_1 := \cos \phi_1 \cdot \cos \phi_2\\
t_2 := \sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)\\
t_3 := \left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_1, {\sin \left(\lambda_1 \cdot 0.5\right)}^{2}, {t\_2}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left(t\_0, \cos \phi_2, {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}} \cdot 2\right) \cdot R\\
\mathbf{if}\;\phi_2 \leq -0.0105:\\
\;\;\;\;t\_3\\
\mathbf{elif}\;\phi_2 \leq 2700000000:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_2, t\_2, t\_0 \cdot t\_1\right)}}{\sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - t\_0 \cdot \cos \phi_1}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;t\_3\\
\end{array}
\end{array}
if phi2 < -0.0105000000000000007 or 2.7e9 < phi2 Initial program 49.2%
Taylor expanded in lambda2 around 0
associate-*r*N/A
lower-fma.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
Applied rewrites35.9%
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-*.f6436.1
Applied rewrites36.1%
if -0.0105000000000000007 < phi2 < 2.7e9Initial program 78.6%
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
*-commutativeN/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites77.3%
Applied rewrites77.3%
Final simplification59.0%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_1 (pow (sin (* (- phi1 phi2) 0.5)) 2.0))
(t_2 (* (cos phi1) (cos phi2)))
(t_3
(*
(*
(atan2
(sqrt (fma t_2 (pow (sin (* lambda1 0.5)) 2.0) t_1))
(sqrt (- 1.0 (fma t_0 (cos phi2) (pow (sin (* phi2 -0.5)) 2.0)))))
2.0)
R)))
(if (<= phi2 -0.0105)
t_3
(if (<= phi2 2700000000.0)
(*
(atan2
(sqrt (fma t_0 t_2 t_1))
(sqrt (fma (- (cos phi1)) t_0 (pow (cos (* -0.5 phi1)) 2.0))))
(* 2.0 R))
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 = pow(sin(((phi1 - phi2) * 0.5)), 2.0);
double t_2 = cos(phi1) * cos(phi2);
double t_3 = (atan2(sqrt(fma(t_2, pow(sin((lambda1 * 0.5)), 2.0), t_1)), sqrt((1.0 - fma(t_0, cos(phi2), pow(sin((phi2 * -0.5)), 2.0))))) * 2.0) * R;
double tmp;
if (phi2 <= -0.0105) {
tmp = t_3;
} else if (phi2 <= 2700000000.0) {
tmp = atan2(sqrt(fma(t_0, t_2, t_1)), sqrt(fma(-cos(phi1), t_0, pow(cos((-0.5 * phi1)), 2.0)))) * (2.0 * R);
} else {
tmp = 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(phi1 - phi2) * 0.5)) ^ 2.0 t_2 = Float64(cos(phi1) * cos(phi2)) t_3 = Float64(Float64(atan(sqrt(fma(t_2, (sin(Float64(lambda1 * 0.5)) ^ 2.0), t_1)), sqrt(Float64(1.0 - fma(t_0, cos(phi2), (sin(Float64(phi2 * -0.5)) ^ 2.0))))) * 2.0) * R) tmp = 0.0 if (phi2 <= -0.0105) tmp = t_3; elseif (phi2 <= 2700000000.0) tmp = Float64(atan(sqrt(fma(t_0, t_2, t_1)), sqrt(fma(Float64(-cos(phi1)), t_0, (cos(Float64(-0.5 * phi1)) ^ 2.0)))) * Float64(2.0 * R)); else tmp = 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[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[(N[ArcTan[N[Sqrt[N[(t$95$2 * N[Power[N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]}, If[LessEqual[phi2, -0.0105], t$95$3, If[LessEqual[phi2, 2700000000.0], N[(N[ArcTan[N[Sqrt[N[(t$95$0 * t$95$2 + t$95$1), $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[(2.0 * R), $MachinePrecision]), $MachinePrecision], t$95$3]]]]]]
\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(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\\
t_2 := \cos \phi_1 \cdot \cos \phi_2\\
t_3 := \left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_2, {\sin \left(\lambda_1 \cdot 0.5\right)}^{2}, t\_1\right)}}{\sqrt{1 - \mathsf{fma}\left(t\_0, \cos \phi_2, {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}} \cdot 2\right) \cdot R\\
\mathbf{if}\;\phi_2 \leq -0.0105:\\
\;\;\;\;t\_3\\
\mathbf{elif}\;\phi_2 \leq 2700000000:\\
\;\;\;\;\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, t\_2, t\_1\right)}}{\sqrt{\mathsf{fma}\left(-\cos \phi_1, t\_0, {\cos \left(-0.5 \cdot \phi_1\right)}^{2}\right)}} \cdot \left(2 \cdot R\right)\\
\mathbf{else}:\\
\;\;\;\;t\_3\\
\end{array}
\end{array}
if phi2 < -0.0105000000000000007 or 2.7e9 < phi2 Initial program 49.2%
Taylor expanded in lambda2 around 0
associate-*r*N/A
lower-fma.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
Applied rewrites35.9%
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-*.f6436.1
Applied rewrites36.1%
if -0.0105000000000000007 < phi2 < 2.7e9Initial program 78.6%
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
*-commutativeN/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites77.3%
Applied rewrites77.3%
Final simplification58.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_1 (* t_0 (cos phi1)))
(t_2 (pow (sin (* (- phi1 phi2) 0.5)) 2.0))
(t_3
(*
(*
(atan2
(sqrt
(fma
(* (cos phi1) (cos phi2))
(pow (sin (* lambda1 0.5)) 2.0)
t_2))
(sqrt (- 1.0 (fma t_0 (cos phi2) (pow (sin (* phi2 -0.5)) 2.0)))))
2.0)
R)))
(if (<= phi2 -0.0105)
t_3
(if (<= phi2 2700000000.0)
(*
(*
(atan2
(sqrt (fma (cos phi2) t_1 t_2))
(sqrt (- (pow (cos (* -0.5 phi1)) 2.0) t_1)))
2.0)
R)
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 = t_0 * cos(phi1);
double t_2 = pow(sin(((phi1 - phi2) * 0.5)), 2.0);
double t_3 = (atan2(sqrt(fma((cos(phi1) * cos(phi2)), pow(sin((lambda1 * 0.5)), 2.0), t_2)), sqrt((1.0 - fma(t_0, cos(phi2), pow(sin((phi2 * -0.5)), 2.0))))) * 2.0) * R;
double tmp;
if (phi2 <= -0.0105) {
tmp = t_3;
} else if (phi2 <= 2700000000.0) {
tmp = (atan2(sqrt(fma(cos(phi2), t_1, t_2)), sqrt((pow(cos((-0.5 * phi1)), 2.0) - t_1))) * 2.0) * R;
} else {
tmp = t_3;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_1 = Float64(t_0 * cos(phi1)) t_2 = sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0 t_3 = Float64(Float64(atan(sqrt(fma(Float64(cos(phi1) * cos(phi2)), (sin(Float64(lambda1 * 0.5)) ^ 2.0), t_2)), sqrt(Float64(1.0 - fma(t_0, cos(phi2), (sin(Float64(phi2 * -0.5)) ^ 2.0))))) * 2.0) * R) tmp = 0.0 if (phi2 <= -0.0105) tmp = t_3; elseif (phi2 <= 2700000000.0) tmp = Float64(Float64(atan(sqrt(fma(cos(phi2), t_1, t_2)), sqrt(Float64((cos(Float64(-0.5 * phi1)) ^ 2.0) - t_1))) * 2.0) * R); else tmp = 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[(t$95$0 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$3 = N[(N[(N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[Power[N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$2), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]}, If[LessEqual[phi2, -0.0105], t$95$3, If[LessEqual[phi2, 2700000000.0], N[(N[(N[ArcTan[N[Sqrt[N[(N[Cos[phi2], $MachinePrecision] * t$95$1 + t$95$2), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], t$95$3]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_1 := t\_0 \cdot \cos \phi_1\\
t_2 := {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\\
t_3 := \left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_1 \cdot \cos \phi_2, {\sin \left(\lambda_1 \cdot 0.5\right)}^{2}, t\_2\right)}}{\sqrt{1 - \mathsf{fma}\left(t\_0, \cos \phi_2, {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}} \cdot 2\right) \cdot R\\
\mathbf{if}\;\phi_2 \leq -0.0105:\\
\;\;\;\;t\_3\\
\mathbf{elif}\;\phi_2 \leq 2700000000:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_2, t\_1, t\_2\right)}}{\sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - t\_1}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;t\_3\\
\end{array}
\end{array}
if phi2 < -0.0105000000000000007 or 2.7e9 < phi2 Initial program 49.2%
Taylor expanded in lambda2 around 0
associate-*r*N/A
lower-fma.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
Applied rewrites35.9%
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-*.f6436.1
Applied rewrites36.1%
if -0.0105000000000000007 < phi2 < 2.7e9Initial program 78.6%
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
*-commutativeN/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites77.3%
lift-+.f64N/A
+-commutativeN/A
Applied rewrites77.3%
Final simplification58.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_1
(*
(*
(atan2
(sqrt
(fma
(* (cos phi1) (cos phi2))
(pow (sin (* lambda1 0.5)) 2.0)
(pow (sin (* (- phi1 phi2) 0.5)) 2.0)))
(sqrt (- 1.0 (fma t_0 (cos phi2) (pow (sin (* phi2 -0.5)) 2.0)))))
2.0)
R)))
(if (<= phi2 -0.00035)
t_1
(if (<= phi2 1.05e-33)
(*
(*
(atan2
(sqrt (fma t_0 (cos phi1) (pow (sin (* phi1 0.5)) 2.0)))
(sqrt (- (pow (cos (* -0.5 phi1)) 2.0) (* t_0 (cos phi1)))))
2.0)
R)
t_1))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_1 = (atan2(sqrt(fma((cos(phi1) * cos(phi2)), pow(sin((lambda1 * 0.5)), 2.0), pow(sin(((phi1 - phi2) * 0.5)), 2.0))), sqrt((1.0 - fma(t_0, cos(phi2), pow(sin((phi2 * -0.5)), 2.0))))) * 2.0) * R;
double tmp;
if (phi2 <= -0.00035) {
tmp = t_1;
} else if (phi2 <= 1.05e-33) {
tmp = (atan2(sqrt(fma(t_0, cos(phi1), pow(sin((phi1 * 0.5)), 2.0))), sqrt((pow(cos((-0.5 * phi1)), 2.0) - (t_0 * cos(phi1))))) * 2.0) * R;
} else {
tmp = t_1;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_1 = Float64(Float64(atan(sqrt(fma(Float64(cos(phi1) * cos(phi2)), (sin(Float64(lambda1 * 0.5)) ^ 2.0), (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0))), sqrt(Float64(1.0 - fma(t_0, cos(phi2), (sin(Float64(phi2 * -0.5)) ^ 2.0))))) * 2.0) * R) tmp = 0.0 if (phi2 <= -0.00035) tmp = t_1; elseif (phi2 <= 1.05e-33) tmp = Float64(Float64(atan(sqrt(fma(t_0, cos(phi1), (sin(Float64(phi1 * 0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(-0.5 * phi1)) ^ 2.0) - Float64(t_0 * cos(phi1))))) * 2.0) * R); else tmp = t_1; end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[Power[N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]}, If[LessEqual[phi2, -0.00035], t$95$1, If[LessEqual[phi2, 1.05e-33], N[(N[(N[ArcTan[N[Sqrt[N[(t$95$0 * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(t$95$0 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], t$95$1]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_1 := \left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_1 \cdot \cos \phi_2, {\sin \left(\lambda_1 \cdot 0.5\right)}^{2}, {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left(t\_0, \cos \phi_2, {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}} \cdot 2\right) \cdot R\\
\mathbf{if}\;\phi_2 \leq -0.00035:\\
\;\;\;\;t\_1\\
\mathbf{elif}\;\phi_2 \leq 1.05 \cdot 10^{-33}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \cos \phi_1, {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}{\sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - t\_0 \cdot \cos \phi_1}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;t\_1\\
\end{array}
\end{array}
if phi2 < -3.49999999999999996e-4 or 1.05e-33 < phi2 Initial program 50.7%
Taylor expanded in lambda2 around 0
associate-*r*N/A
lower-fma.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
Applied rewrites36.7%
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-*.f6436.4
Applied rewrites36.4%
if -3.49999999999999996e-4 < phi2 < 1.05e-33Initial program 79.8%
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
*-commutativeN/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites79.5%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6478.1
Applied rewrites78.1%
Final simplification57.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
(*
(atan2
(sqrt
(+
(* (* t_0 (* (cos phi1) (cos phi2))) t_0)
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (- 1.0 (pow (sin (* (- phi1 phi2) 0.5)) 2.0))))
2.0)
R)))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
return (atan2(sqrt((((t_0 * (cos(phi1) * cos(phi2))) * t_0) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((1.0 - pow(sin(((phi1 - phi2) * 0.5)), 2.0)))) * 2.0) * R;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
code = (atan2(sqrt((((t_0 * (cos(phi1) * cos(phi2))) * t_0) + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt((1.0d0 - (sin(((phi1 - phi2) * 0.5d0)) ** 2.0d0)))) * 2.0d0) * r
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
return (Math.atan2(Math.sqrt((((t_0 * (Math.cos(phi1) * Math.cos(phi2))) * t_0) + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt((1.0 - Math.pow(Math.sin(((phi1 - phi2) * 0.5)), 2.0)))) * 2.0) * R;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) return (math.atan2(math.sqrt((((t_0 * (math.cos(phi1) * math.cos(phi2))) * t_0) + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt((1.0 - math.pow(math.sin(((phi1 - phi2) * 0.5)), 2.0)))) * 2.0) * R
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(Float64(atan(sqrt(Float64(Float64(Float64(t_0 * Float64(cos(phi1) * cos(phi2))) * t_0) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(1.0 - (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0)))) * 2.0) * R) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); tmp = (atan2(sqrt((((t_0 * (cos(phi1) * cos(phi2))) * t_0) + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt((1.0 - (sin(((phi1 - phi2) * 0.5)) ^ 2.0)))) * 2.0) * R; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(N[(N[ArcTan[N[Sqrt[N[(N[(N[(t$95$0 * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\left(\tan^{-1}_* \frac{\sqrt{\left(t\_0 \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)\right) \cdot t\_0 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{1 - {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}}} \cdot 2\right) \cdot R
\end{array}
\end{array}
Initial program 65.5%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
*-commutativeN/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites52.1%
Taylor expanded in lambda1 around 0
Applied rewrites44.8%
Taylor expanded in lambda2 around 0
Applied rewrites35.6%
Final simplification35.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
(*
(atan2
(sqrt (pow (sin (* (- phi1 phi2) 0.5)) 2.0))
(sqrt
(-
(pow (cos (/ (- phi1 phi2) -2.0)) 2.0)
(*
(pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)
(* (cos phi1) (cos phi2))))))
R)
2.0))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return (atan2(sqrt(pow(sin(((phi1 - phi2) * 0.5)), 2.0)), sqrt((pow(cos(((phi1 - phi2) / -2.0)), 2.0) - (pow(sin(((lambda1 - lambda2) * 0.5)), 2.0) * (cos(phi1) * cos(phi2)))))) * R) * 2.0;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
code = (atan2(sqrt((sin(((phi1 - phi2) * 0.5d0)) ** 2.0d0)), sqrt(((cos(((phi1 - phi2) / (-2.0d0))) ** 2.0d0) - ((sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0) * (cos(phi1) * cos(phi2)))))) * r) * 2.0d0
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return (Math.atan2(Math.sqrt(Math.pow(Math.sin(((phi1 - phi2) * 0.5)), 2.0)), Math.sqrt((Math.pow(Math.cos(((phi1 - phi2) / -2.0)), 2.0) - (Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0) * (Math.cos(phi1) * Math.cos(phi2)))))) * R) * 2.0;
}
def code(R, lambda1, lambda2, phi1, phi2): return (math.atan2(math.sqrt(math.pow(math.sin(((phi1 - phi2) * 0.5)), 2.0)), math.sqrt((math.pow(math.cos(((phi1 - phi2) / -2.0)), 2.0) - (math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0) * (math.cos(phi1) * math.cos(phi2)))))) * R) * 2.0
function code(R, lambda1, lambda2, phi1, phi2) return Float64(Float64(atan(sqrt((sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0)), sqrt(Float64((cos(Float64(Float64(phi1 - phi2) / -2.0)) ^ 2.0) - Float64((sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0) * Float64(cos(phi1) * cos(phi2)))))) * R) * 2.0) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) tmp = (atan2(sqrt((sin(((phi1 - phi2) * 0.5)) ^ 2.0)), sqrt(((cos(((phi1 - phi2) / -2.0)) ^ 2.0) - ((sin(((lambda1 - lambda2) * 0.5)) ^ 2.0) * (cos(phi1) * cos(phi2)))))) * R) * 2.0; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(N[(N[ArcTan[N[Sqrt[N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(N[(phi1 - phi2), $MachinePrecision] / -2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * R), $MachinePrecision] * 2.0), $MachinePrecision]
\begin{array}{l}
\\
\left(\tan^{-1}_* \frac{\sqrt{{\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}}}{\sqrt{{\cos \left(\frac{\phi_1 - \phi_2}{-2}\right)}^{2} - {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2} \cdot \left(\cos \phi_1 \cdot \cos \phi_2\right)}} \cdot R\right) \cdot 2
\end{array}
Initial program 65.5%
Taylor expanded in lambda1 around 0
associate-*r*N/A
associate-*r*N/A
associate-*r*N/A
lower-fma.f64N/A
Applied rewrites45.5%
Taylor expanded in lambda2 around 0
Applied rewrites30.6%
Applied rewrites30.6%
Final simplification30.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- phi1 phi2) 0.5)) 2.0)))
(*
(*
(atan2
(sqrt t_0)
(sqrt
(-
1.0
(fma
(cos phi1)
(* (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0) (cos phi2))
t_0))))
2.0)
R)))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((phi1 - phi2) * 0.5)), 2.0);
return (atan2(sqrt(t_0), sqrt((1.0 - fma(cos(phi1), (pow(sin(((lambda1 - lambda2) * 0.5)), 2.0) * cos(phi2)), t_0)))) * 2.0) * R;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0 return Float64(Float64(atan(sqrt(t_0), sqrt(Float64(1.0 - fma(cos(phi1), Float64((sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0) * cos(phi2)), t_0)))) * 2.0) * R) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(N[(N[ArcTan[N[Sqrt[t$95$0], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Cos[phi1], $MachinePrecision] * N[(N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] + t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\\
\left(\tan^{-1}_* \frac{\sqrt{t\_0}}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1, {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2} \cdot \cos \phi_2, t\_0\right)}} \cdot 2\right) \cdot R
\end{array}
\end{array}
Initial program 65.5%
Taylor expanded in lambda1 around 0
associate-*r*N/A
associate-*r*N/A
associate-*r*N/A
lower-fma.f64N/A
Applied rewrites45.5%
Taylor expanded in lambda2 around 0
Applied rewrites30.6%
lift-+.f64N/A
+-commutativeN/A
Applied rewrites30.6%
Final simplification30.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- phi1 phi2) 0.5)) 2.0)))
(*
(*
(atan2
(sqrt t_0)
(sqrt
(-
1.0
(fma (* (cos phi1) (cos phi2)) (pow (sin (* lambda1 0.5)) 2.0) t_0))))
2.0)
R)))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((phi1 - phi2) * 0.5)), 2.0);
return (atan2(sqrt(t_0), sqrt((1.0 - fma((cos(phi1) * cos(phi2)), pow(sin((lambda1 * 0.5)), 2.0), t_0)))) * 2.0) * R;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0 return Float64(Float64(atan(sqrt(t_0), sqrt(Float64(1.0 - fma(Float64(cos(phi1) * cos(phi2)), (sin(Float64(lambda1 * 0.5)) ^ 2.0), t_0)))) * 2.0) * R) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(N[(N[ArcTan[N[Sqrt[t$95$0], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[Power[N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\\
\left(\tan^{-1}_* \frac{\sqrt{t\_0}}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_1 \cdot \cos \phi_2, {\sin \left(\lambda_1 \cdot 0.5\right)}^{2}, t\_0\right)}} \cdot 2\right) \cdot R
\end{array}
\end{array}
Initial program 65.5%
Taylor expanded in lambda1 around 0
associate-*r*N/A
associate-*r*N/A
associate-*r*N/A
lower-fma.f64N/A
Applied rewrites45.5%
Taylor expanded in lambda2 around 0
Applied rewrites30.6%
Taylor expanded in lambda2 around 0
associate-*r*N/A
lower-fma.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
Applied rewrites30.5%
Final simplification30.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* phi1 0.5)) 2.0))
(t_1
(sqrt
(-
1.0
(fma (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0) (cos phi1) t_0))))
(t_2 (* (* (atan2 (sqrt t_0) t_1) 2.0) R)))
(if (<= phi1 -5e-36)
t_2
(if (<= phi1 2.95e-6)
(* (* (atan2 (sqrt (pow (sin (* phi2 -0.5)) 2.0)) t_1) 2.0) R)
t_2))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((phi1 * 0.5)), 2.0);
double t_1 = sqrt((1.0 - fma(pow(sin(((lambda1 - lambda2) * 0.5)), 2.0), cos(phi1), t_0)));
double t_2 = (atan2(sqrt(t_0), t_1) * 2.0) * R;
double tmp;
if (phi1 <= -5e-36) {
tmp = t_2;
} else if (phi1 <= 2.95e-6) {
tmp = (atan2(sqrt(pow(sin((phi2 * -0.5)), 2.0)), t_1) * 2.0) * R;
} else {
tmp = t_2;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi1 * 0.5)) ^ 2.0 t_1 = sqrt(Float64(1.0 - fma((sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0), cos(phi1), t_0))) t_2 = Float64(Float64(atan(sqrt(t_0), t_1) * 2.0) * R) tmp = 0.0 if (phi1 <= -5e-36) tmp = t_2; elseif (phi1 <= 2.95e-6) tmp = Float64(Float64(atan(sqrt((sin(Float64(phi2 * -0.5)) ^ 2.0)), t_1) * 2.0) * R); else tmp = t_2; end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision] + t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[(N[ArcTan[N[Sqrt[t$95$0], $MachinePrecision] / t$95$1], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]}, If[LessEqual[phi1, -5e-36], t$95$2, If[LessEqual[phi1, 2.95e-6], N[(N[(N[ArcTan[N[Sqrt[N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision] / t$95$1], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], t$95$2]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\\
t_1 := \sqrt{1 - \mathsf{fma}\left({\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}, \cos \phi_1, t\_0\right)}\\
t_2 := \left(\tan^{-1}_* \frac{\sqrt{t\_0}}{t\_1} \cdot 2\right) \cdot R\\
\mathbf{if}\;\phi_1 \leq -5 \cdot 10^{-36}:\\
\;\;\;\;t\_2\\
\mathbf{elif}\;\phi_1 \leq 2.95 \cdot 10^{-6}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{{\sin \left(\phi_2 \cdot -0.5\right)}^{2}}}{t\_1} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;t\_2\\
\end{array}
\end{array}
if phi1 < -5.00000000000000004e-36 or 2.95000000000000013e-6 < phi1 Initial program 56.3%
Taylor expanded in lambda1 around 0
associate-*r*N/A
associate-*r*N/A
associate-*r*N/A
lower-fma.f64N/A
Applied rewrites40.8%
Taylor expanded in lambda2 around 0
Applied rewrites34.4%
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-*.f6434.5
Applied rewrites34.5%
Taylor expanded in phi2 around 0
Applied rewrites34.3%
if -5.00000000000000004e-36 < phi1 < 2.95000000000000013e-6Initial program 75.4%
Taylor expanded in lambda1 around 0
associate-*r*N/A
associate-*r*N/A
associate-*r*N/A
lower-fma.f64N/A
Applied rewrites50.7%
Taylor expanded in lambda2 around 0
Applied rewrites26.5%
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-*.f6419.5
Applied rewrites19.5%
Taylor expanded in phi1 around 0
Applied rewrites17.6%
Final simplification26.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_1 (sqrt (pow (sin (* (- phi1 phi2) 0.5)) 2.0))))
(if (<= phi2 -7e-19)
(*
(*
(atan2
t_1
(sqrt (- 1.0 (fma t_0 (cos phi2) (pow (sin (* phi2 -0.5)) 2.0)))))
2.0)
R)
(*
(*
(atan2
t_1
(sqrt (- 1.0 (fma t_0 (cos phi1) (pow (sin (* phi1 0.5)) 2.0)))))
2.0)
R))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_1 = sqrt(pow(sin(((phi1 - phi2) * 0.5)), 2.0));
double tmp;
if (phi2 <= -7e-19) {
tmp = (atan2(t_1, sqrt((1.0 - fma(t_0, cos(phi2), pow(sin((phi2 * -0.5)), 2.0))))) * 2.0) * R;
} else {
tmp = (atan2(t_1, sqrt((1.0 - fma(t_0, cos(phi1), pow(sin((phi1 * 0.5)), 2.0))))) * 2.0) * R;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_1 = sqrt((sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0)) tmp = 0.0 if (phi2 <= -7e-19) tmp = Float64(Float64(atan(t_1, sqrt(Float64(1.0 - fma(t_0, cos(phi2), (sin(Float64(phi2 * -0.5)) ^ 2.0))))) * 2.0) * R); else tmp = Float64(Float64(atan(t_1, sqrt(Float64(1.0 - fma(t_0, cos(phi1), (sin(Float64(phi1 * 0.5)) ^ 2.0))))) * 2.0) * R); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sqrt[N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi2, -7e-19], N[(N[(N[ArcTan[t$95$1 / N[Sqrt[N[(1.0 - N[(t$95$0 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], N[(N[(N[ArcTan[t$95$1 / N[Sqrt[N[(1.0 - N[(t$95$0 * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_1 := \sqrt{{\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}}\\
\mathbf{if}\;\phi_2 \leq -7 \cdot 10^{-19}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{t\_1}{\sqrt{1 - \mathsf{fma}\left(t\_0, \cos \phi_2, {\sin \left(\phi_2 \cdot -0.5\right)}^{2}\right)}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{t\_1}{\sqrt{1 - \mathsf{fma}\left(t\_0, \cos \phi_1, {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}} \cdot 2\right) \cdot R\\
\end{array}
\end{array}
if phi2 < -7.00000000000000031e-19Initial program 49.0%
Taylor expanded in lambda1 around 0
associate-*r*N/A
associate-*r*N/A
associate-*r*N/A
lower-fma.f64N/A
Applied rewrites37.3%
Taylor expanded in lambda2 around 0
Applied rewrites27.7%
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-*.f6428.2
Applied rewrites28.2%
if -7.00000000000000031e-19 < phi2 Initial program 71.2%
Taylor expanded in lambda1 around 0
associate-*r*N/A
associate-*r*N/A
associate-*r*N/A
lower-fma.f64N/A
Applied rewrites48.4%
Taylor expanded in lambda2 around 0
Applied rewrites31.6%
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-*.f6429.8
Applied rewrites29.8%
Final simplification29.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
(*
(atan2
(sqrt (pow (sin (* (- phi1 phi2) 0.5)) 2.0))
(sqrt
(-
1.0
(fma
(pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)
(cos phi1)
(pow (sin (* phi1 0.5)) 2.0)))))
2.0)
R))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return (atan2(sqrt(pow(sin(((phi1 - phi2) * 0.5)), 2.0)), sqrt((1.0 - fma(pow(sin(((lambda1 - lambda2) * 0.5)), 2.0), cos(phi1), pow(sin((phi1 * 0.5)), 2.0))))) * 2.0) * R;
}
function code(R, lambda1, lambda2, phi1, phi2) return Float64(Float64(atan(sqrt((sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0)), sqrt(Float64(1.0 - fma((sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0), cos(phi1), (sin(Float64(phi1 * 0.5)) ^ 2.0))))) * 2.0) * R) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(N[(N[ArcTan[N[Sqrt[N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]
\begin{array}{l}
\\
\left(\tan^{-1}_* \frac{\sqrt{{\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}}}{\sqrt{1 - \mathsf{fma}\left({\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}, \cos \phi_1, {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}} \cdot 2\right) \cdot R
\end{array}
Initial program 65.5%
Taylor expanded in lambda1 around 0
associate-*r*N/A
associate-*r*N/A
associate-*r*N/A
lower-fma.f64N/A
Applied rewrites45.5%
Taylor expanded in lambda2 around 0
Applied rewrites30.6%
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-*.f6427.3
Applied rewrites27.3%
Final simplification27.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
(*
(atan2
(sqrt (pow (sin (* (- phi1 phi2) 0.5)) 2.0))
(sqrt
(-
1.0
(fma
(pow (sin (* lambda2 -0.5)) 2.0)
(cos phi1)
(pow (sin (* phi1 0.5)) 2.0)))))
2.0)
R))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return (atan2(sqrt(pow(sin(((phi1 - phi2) * 0.5)), 2.0)), sqrt((1.0 - fma(pow(sin((lambda2 * -0.5)), 2.0), cos(phi1), pow(sin((phi1 * 0.5)), 2.0))))) * 2.0) * R;
}
function code(R, lambda1, lambda2, phi1, phi2) return Float64(Float64(atan(sqrt((sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0)), sqrt(Float64(1.0 - fma((sin(Float64(lambda2 * -0.5)) ^ 2.0), cos(phi1), (sin(Float64(phi1 * 0.5)) ^ 2.0))))) * 2.0) * R) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(N[(N[ArcTan[N[Sqrt[N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]
\begin{array}{l}
\\
\left(\tan^{-1}_* \frac{\sqrt{{\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}}}{\sqrt{1 - \mathsf{fma}\left({\sin \left(\lambda_2 \cdot -0.5\right)}^{2}, \cos \phi_1, {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}} \cdot 2\right) \cdot R
\end{array}
Initial program 65.5%
Taylor expanded in lambda1 around 0
associate-*r*N/A
associate-*r*N/A
associate-*r*N/A
lower-fma.f64N/A
Applied rewrites45.5%
Taylor expanded in lambda2 around 0
Applied rewrites30.6%
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-*.f6427.3
Applied rewrites27.3%
Taylor expanded in lambda1 around 0
Applied rewrites27.2%
Final simplification27.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
(*
(atan2
(sqrt (pow (sin (* phi2 -0.5)) 2.0))
(sqrt
(-
1.0
(fma
(pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)
(cos phi1)
(pow (sin (* phi1 0.5)) 2.0)))))
2.0)
R))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return (atan2(sqrt(pow(sin((phi2 * -0.5)), 2.0)), sqrt((1.0 - fma(pow(sin(((lambda1 - lambda2) * 0.5)), 2.0), cos(phi1), pow(sin((phi1 * 0.5)), 2.0))))) * 2.0) * R;
}
function code(R, lambda1, lambda2, phi1, phi2) return Float64(Float64(atan(sqrt((sin(Float64(phi2 * -0.5)) ^ 2.0)), sqrt(Float64(1.0 - fma((sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0), cos(phi1), (sin(Float64(phi1 * 0.5)) ^ 2.0))))) * 2.0) * R) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(N[(N[ArcTan[N[Sqrt[N[Power[N[Sin[N[(phi2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]
\begin{array}{l}
\\
\left(\tan^{-1}_* \frac{\sqrt{{\sin \left(\phi_2 \cdot -0.5\right)}^{2}}}{\sqrt{1 - \mathsf{fma}\left({\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}, \cos \phi_1, {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}} \cdot 2\right) \cdot R
\end{array}
Initial program 65.5%
Taylor expanded in lambda1 around 0
associate-*r*N/A
associate-*r*N/A
associate-*r*N/A
lower-fma.f64N/A
Applied rewrites45.5%
Taylor expanded in lambda2 around 0
Applied rewrites30.6%
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-*.f6427.3
Applied rewrites27.3%
Taylor expanded in phi1 around 0
Applied rewrites14.3%
Final simplification14.3%
herbie shell --seed 2024270
(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))))))))))