
(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 31 alternatives:
| Alternative | Accuracy | Speedup |
|---|
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi1) (cos phi2)) t_0) t_0))))
(* R (* 2.0 (atan2 (sqrt t_1) (sqrt (- 1.0 t_1)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0);
return R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1))));
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0)
code = r * (2.0d0 * atan2(sqrt(t_1), sqrt((1.0d0 - t_1))))
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((Math.cos(phi1) * Math.cos(phi2)) * t_0) * t_0);
return R * (2.0 * Math.atan2(Math.sqrt(t_1), Math.sqrt((1.0 - t_1))));
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((math.cos(phi1) * math.cos(phi2)) * t_0) * t_0) return R * (2.0 * math.atan2(math.sqrt(t_1), math.sqrt((1.0 - t_1))))
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi1) * cos(phi2)) * t_0) * t_0)) return Float64(R * Float64(2.0 * atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))))) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (((cos(phi1) * cos(phi2)) * t_0) * t_0); tmp = R * (2.0 * atan2(sqrt(t_1), sqrt((1.0 - t_1)))); end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi1], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(R * N[(2.0 * N[ArcTan[N[Sqrt[t$95$1], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\left(\cos \phi_1 \cdot \cos \phi_2\right) \cdot t\_0\right) \cdot t\_0\\
R \cdot \left(2 \cdot \tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}}\right)
\end{array}
\end{array}
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (sin (* phi1 0.5)))
(t_2 (* (cos phi2) (cos phi1)))
(t_3 (* (cos (* phi1 0.5)) (sin (* -0.5 phi2)))))
(*
(*
(atan2
(sqrt (+ (* (* t_2 t_0) t_0) (pow (fma t_1 (cos (* phi2 0.5)) t_3) 2.0)))
(sqrt
(-
(-
1.0
(*
t_2
(pow
(-
(* (cos (* lambda2 0.5)) (sin (* lambda1 0.5)))
(* (sin (* lambda2 0.5)) (cos (* lambda1 0.5))))
2.0)))
(pow (fma t_1 (cos (* -0.5 phi2)) t_3) 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 = sin((phi1 * 0.5));
double t_2 = cos(phi2) * cos(phi1);
double t_3 = cos((phi1 * 0.5)) * sin((-0.5 * phi2));
return (atan2(sqrt((((t_2 * t_0) * t_0) + pow(fma(t_1, cos((phi2 * 0.5)), t_3), 2.0))), sqrt(((1.0 - (t_2 * pow(((cos((lambda2 * 0.5)) * sin((lambda1 * 0.5))) - (sin((lambda2 * 0.5)) * cos((lambda1 * 0.5)))), 2.0))) - pow(fma(t_1, cos((-0.5 * phi2)), t_3), 2.0)))) * 2.0) * R;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sin(Float64(phi1 * 0.5)) t_2 = Float64(cos(phi2) * cos(phi1)) t_3 = Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(-0.5 * phi2))) return Float64(Float64(atan(sqrt(Float64(Float64(Float64(t_2 * t_0) * t_0) + (fma(t_1, cos(Float64(phi2 * 0.5)), t_3) ^ 2.0))), sqrt(Float64(Float64(1.0 - Float64(t_2 * (Float64(Float64(cos(Float64(lambda2 * 0.5)) * sin(Float64(lambda1 * 0.5))) - Float64(sin(Float64(lambda2 * 0.5)) * cos(Float64(lambda1 * 0.5)))) ^ 2.0))) - (fma(t_1, cos(Float64(-0.5 * phi2)), t_3) ^ 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[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]}, N[(N[(N[ArcTan[N[Sqrt[N[(N[(N[(t$95$2 * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision] + N[Power[N[(t$95$1 * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] + t$95$3), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[(t$95$2 * N[Power[N[(N[(N[Cos[N[(lambda2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Sin[N[(lambda2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[Power[N[(t$95$1 * N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] + t$95$3), $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)\\
t_1 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_2 := \cos \phi_2 \cdot \cos \phi_1\\
t_3 := \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(-0.5 \cdot \phi_2\right)\\
\left(\tan^{-1}_* \frac{\sqrt{\left(t\_2 \cdot t\_0\right) \cdot t\_0 + {\left(\mathsf{fma}\left(t\_1, \cos \left(\phi_2 \cdot 0.5\right), t\_3\right)\right)}^{2}}}{\sqrt{\left(1 - t\_2 \cdot {\left(\cos \left(\lambda_2 \cdot 0.5\right) \cdot \sin \left(\lambda_1 \cdot 0.5\right) - \sin \left(\lambda_2 \cdot 0.5\right) \cdot \cos \left(\lambda_1 \cdot 0.5\right)\right)}^{2}\right) - {\left(\mathsf{fma}\left(t\_1, \cos \left(-0.5 \cdot \phi_2\right), t\_3\right)\right)}^{2}}} \cdot 2\right) \cdot R
\end{array}
\end{array}
Initial program 66.4%
lift--.f64N/A
lift-+.f64N/A
+-commutativeN/A
associate--r+N/A
lower--.f64N/A
Applied rewrites66.4%
lift-sin.f64N/A
lift-*.f64N/A
lift--.f64N/A
distribute-rgt-out--N/A
lift-*.f64N/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
lift-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
metadata-evalN/A
lower-*.f64N/A
lift-cos.f64N/A
lower-*.f64N/A
Applied rewrites67.1%
Applied rewrites80.3%
lift-sin.f64N/A
lift-*.f64N/A
*-commutativeN/A
lift--.f64N/A
lift--.f64N/A
metadata-evalN/A
div-invN/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-*.f64N/A
Applied rewrites80.7%
Final simplification80.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* phi1 0.5)))
(t_1 (* (cos phi2) (cos phi1)))
(t_2 (* (cos (* phi1 0.5)) (sin (* -0.5 phi2))))
(t_3
(sqrt
(-
(- 1.0 (* (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0) t_1))
(pow (fma t_0 (cos (* -0.5 phi2)) t_2) 2.0))))
(t_4 (pow (fma t_0 (cos (* phi2 0.5)) t_2) 2.0))
(t_5
(*
(*
(atan2 (sqrt (fma t_1 (pow (sin (* lambda1 0.5)) 2.0) t_4)) t_3)
2.0)
R)))
(if (<= lambda1 -1.7e-7)
t_5
(if (<= lambda1 1.82e-6)
(*
(*
(atan2 (sqrt (+ (* (pow (sin (* lambda2 -0.5)) 2.0) t_1) t_4)) t_3)
2.0)
R)
t_5))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((phi1 * 0.5));
double t_1 = cos(phi2) * cos(phi1);
double t_2 = cos((phi1 * 0.5)) * sin((-0.5 * phi2));
double t_3 = sqrt(((1.0 - (pow(sin(((lambda1 - lambda2) * 0.5)), 2.0) * t_1)) - pow(fma(t_0, cos((-0.5 * phi2)), t_2), 2.0)));
double t_4 = pow(fma(t_0, cos((phi2 * 0.5)), t_2), 2.0);
double t_5 = (atan2(sqrt(fma(t_1, pow(sin((lambda1 * 0.5)), 2.0), t_4)), t_3) * 2.0) * R;
double tmp;
if (lambda1 <= -1.7e-7) {
tmp = t_5;
} else if (lambda1 <= 1.82e-6) {
tmp = (atan2(sqrt(((pow(sin((lambda2 * -0.5)), 2.0) * t_1) + t_4)), t_3) * 2.0) * R;
} else {
tmp = t_5;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi1 * 0.5)) t_1 = Float64(cos(phi2) * cos(phi1)) t_2 = Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(-0.5 * phi2))) t_3 = sqrt(Float64(Float64(1.0 - Float64((sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0) * t_1)) - (fma(t_0, cos(Float64(-0.5 * phi2)), t_2) ^ 2.0))) t_4 = fma(t_0, cos(Float64(phi2 * 0.5)), t_2) ^ 2.0 t_5 = Float64(Float64(atan(sqrt(fma(t_1, (sin(Float64(lambda1 * 0.5)) ^ 2.0), t_4)), t_3) * 2.0) * R) tmp = 0.0 if (lambda1 <= -1.7e-7) tmp = t_5; elseif (lambda1 <= 1.82e-6) tmp = Float64(Float64(atan(sqrt(Float64(Float64((sin(Float64(lambda2 * -0.5)) ^ 2.0) * t_1) + t_4)), t_3) * 2.0) * R); else tmp = t_5; end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[Sqrt[N[(N[(1.0 - N[(N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision] - N[Power[N[(t$95$0 * N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] + t$95$2), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[Power[N[(t$95$0 * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] + t$95$2), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$5 = N[(N[(N[ArcTan[N[Sqrt[N[(t$95$1 * N[Power[N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$4), $MachinePrecision]], $MachinePrecision] / t$95$3], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]}, If[LessEqual[lambda1, -1.7e-7], t$95$5, If[LessEqual[lambda1, 1.82e-6], N[(N[(N[ArcTan[N[Sqrt[N[(N[(N[Power[N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * t$95$1), $MachinePrecision] + t$95$4), $MachinePrecision]], $MachinePrecision] / t$95$3], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], t$95$5]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_1 := \cos \phi_2 \cdot \cos \phi_1\\
t_2 := \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(-0.5 \cdot \phi_2\right)\\
t_3 := \sqrt{\left(1 - {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2} \cdot t\_1\right) - {\left(\mathsf{fma}\left(t\_0, \cos \left(-0.5 \cdot \phi_2\right), t\_2\right)\right)}^{2}}\\
t_4 := {\left(\mathsf{fma}\left(t\_0, \cos \left(\phi_2 \cdot 0.5\right), t\_2\right)\right)}^{2}\\
t_5 := \left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_1, {\sin \left(\lambda_1 \cdot 0.5\right)}^{2}, t\_4\right)}}{t\_3} \cdot 2\right) \cdot R\\
\mathbf{if}\;\lambda_1 \leq -1.7 \cdot 10^{-7}:\\
\;\;\;\;t\_5\\
\mathbf{elif}\;\lambda_1 \leq 1.82 \cdot 10^{-6}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{{\sin \left(\lambda_2 \cdot -0.5\right)}^{2} \cdot t\_1 + t\_4}}{t\_3} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;t\_5\\
\end{array}
\end{array}
if lambda1 < -1.69999999999999987e-7 or 1.8199999999999999e-6 < lambda1 Initial program 50.6%
lift--.f64N/A
lift-+.f64N/A
+-commutativeN/A
associate--r+N/A
lower--.f64N/A
Applied rewrites50.7%
lift-sin.f64N/A
lift-*.f64N/A
lift--.f64N/A
distribute-rgt-out--N/A
lift-*.f64N/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
lift-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
metadata-evalN/A
lower-*.f64N/A
lift-cos.f64N/A
lower-*.f64N/A
Applied rewrites51.3%
Applied rewrites60.0%
Taylor expanded in lambda2 around 0
associate-*r*N/A
lower-fma.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
lower-pow.f64N/A
Applied rewrites59.8%
if -1.69999999999999987e-7 < lambda1 < 1.8199999999999999e-6Initial program 81.0%
lift--.f64N/A
lift-+.f64N/A
+-commutativeN/A
associate--r+N/A
lower--.f64N/A
Applied rewrites81.0%
lift-sin.f64N/A
lift-*.f64N/A
lift--.f64N/A
distribute-rgt-out--N/A
lift-*.f64N/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
lift-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
metadata-evalN/A
lower-*.f64N/A
lift-cos.f64N/A
lower-*.f64N/A
Applied rewrites81.7%
Applied rewrites99.0%
Taylor expanded in lambda1 around 0
associate-*r*N/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f6496.4
Applied rewrites96.4%
Final simplification78.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* phi1 0.5)))
(t_1 (* (cos phi2) (cos phi1)))
(t_2 (* (cos (* phi1 0.5)) (sin (* -0.5 phi2))))
(t_3
(sqrt
(-
(- 1.0 (* (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0) t_1))
(pow (fma t_0 (cos (* -0.5 phi2)) t_2) 2.0))))
(t_4 (pow (fma t_0 (cos (* phi2 0.5)) t_2) 2.0))
(t_5
(*
(*
(atan2 (sqrt (fma t_1 (pow (sin (* lambda1 0.5)) 2.0) t_4)) t_3)
2.0)
R)))
(if (<= lambda1 -1.7e-7)
t_5
(if (<= lambda1 1.82e-6)
(*
(*
(atan2 (sqrt (fma t_1 (pow (sin (* lambda2 -0.5)) 2.0) t_4)) t_3)
2.0)
R)
t_5))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((phi1 * 0.5));
double t_1 = cos(phi2) * cos(phi1);
double t_2 = cos((phi1 * 0.5)) * sin((-0.5 * phi2));
double t_3 = sqrt(((1.0 - (pow(sin(((lambda1 - lambda2) * 0.5)), 2.0) * t_1)) - pow(fma(t_0, cos((-0.5 * phi2)), t_2), 2.0)));
double t_4 = pow(fma(t_0, cos((phi2 * 0.5)), t_2), 2.0);
double t_5 = (atan2(sqrt(fma(t_1, pow(sin((lambda1 * 0.5)), 2.0), t_4)), t_3) * 2.0) * R;
double tmp;
if (lambda1 <= -1.7e-7) {
tmp = t_5;
} else if (lambda1 <= 1.82e-6) {
tmp = (atan2(sqrt(fma(t_1, pow(sin((lambda2 * -0.5)), 2.0), t_4)), t_3) * 2.0) * R;
} else {
tmp = t_5;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi1 * 0.5)) t_1 = Float64(cos(phi2) * cos(phi1)) t_2 = Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(-0.5 * phi2))) t_3 = sqrt(Float64(Float64(1.0 - Float64((sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0) * t_1)) - (fma(t_0, cos(Float64(-0.5 * phi2)), t_2) ^ 2.0))) t_4 = fma(t_0, cos(Float64(phi2 * 0.5)), t_2) ^ 2.0 t_5 = Float64(Float64(atan(sqrt(fma(t_1, (sin(Float64(lambda1 * 0.5)) ^ 2.0), t_4)), t_3) * 2.0) * R) tmp = 0.0 if (lambda1 <= -1.7e-7) tmp = t_5; elseif (lambda1 <= 1.82e-6) tmp = Float64(Float64(atan(sqrt(fma(t_1, (sin(Float64(lambda2 * -0.5)) ^ 2.0), t_4)), t_3) * 2.0) * R); else tmp = t_5; end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[Sqrt[N[(N[(1.0 - N[(N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision] - N[Power[N[(t$95$0 * N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] + t$95$2), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[Power[N[(t$95$0 * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] + t$95$2), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$5 = N[(N[(N[ArcTan[N[Sqrt[N[(t$95$1 * N[Power[N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$4), $MachinePrecision]], $MachinePrecision] / t$95$3], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]}, If[LessEqual[lambda1, -1.7e-7], t$95$5, If[LessEqual[lambda1, 1.82e-6], N[(N[(N[ArcTan[N[Sqrt[N[(t$95$1 * N[Power[N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$4), $MachinePrecision]], $MachinePrecision] / t$95$3], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], t$95$5]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_1 := \cos \phi_2 \cdot \cos \phi_1\\
t_2 := \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(-0.5 \cdot \phi_2\right)\\
t_3 := \sqrt{\left(1 - {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2} \cdot t\_1\right) - {\left(\mathsf{fma}\left(t\_0, \cos \left(-0.5 \cdot \phi_2\right), t\_2\right)\right)}^{2}}\\
t_4 := {\left(\mathsf{fma}\left(t\_0, \cos \left(\phi_2 \cdot 0.5\right), t\_2\right)\right)}^{2}\\
t_5 := \left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_1, {\sin \left(\lambda_1 \cdot 0.5\right)}^{2}, t\_4\right)}}{t\_3} \cdot 2\right) \cdot R\\
\mathbf{if}\;\lambda_1 \leq -1.7 \cdot 10^{-7}:\\
\;\;\;\;t\_5\\
\mathbf{elif}\;\lambda_1 \leq 1.82 \cdot 10^{-6}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_1, {\sin \left(\lambda_2 \cdot -0.5\right)}^{2}, t\_4\right)}}{t\_3} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;t\_5\\
\end{array}
\end{array}
if lambda1 < -1.69999999999999987e-7 or 1.8199999999999999e-6 < lambda1 Initial program 50.6%
lift--.f64N/A
lift-+.f64N/A
+-commutativeN/A
associate--r+N/A
lower--.f64N/A
Applied rewrites50.7%
lift-sin.f64N/A
lift-*.f64N/A
lift--.f64N/A
distribute-rgt-out--N/A
lift-*.f64N/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
lift-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
metadata-evalN/A
lower-*.f64N/A
lift-cos.f64N/A
lower-*.f64N/A
Applied rewrites51.3%
Applied rewrites60.0%
Taylor expanded in lambda2 around 0
associate-*r*N/A
lower-fma.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
lower-pow.f64N/A
Applied rewrites59.8%
if -1.69999999999999987e-7 < lambda1 < 1.8199999999999999e-6Initial program 81.0%
lift--.f64N/A
lift-+.f64N/A
+-commutativeN/A
associate--r+N/A
lower--.f64N/A
Applied rewrites81.0%
lift-sin.f64N/A
lift-*.f64N/A
lift--.f64N/A
distribute-rgt-out--N/A
lift-*.f64N/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
lift-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
metadata-evalN/A
lower-*.f64N/A
lift-cos.f64N/A
lower-*.f64N/A
Applied rewrites81.7%
Applied rewrites99.0%
Taylor expanded in lambda1 around 0
associate-*r*N/A
lower-fma.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-pow.f64N/A
Applied rewrites96.3%
Final simplification78.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* lambda1 0.5)))
(t_1 (sin (* phi1 0.5)))
(t_2 (sin (/ (- lambda1 lambda2) 2.0)))
(t_3 (* (cos phi2) (cos phi1)))
(t_4 (* (cos (* phi1 0.5)) (sin (* -0.5 phi2))))
(t_5
(*
(*
(atan2
(sqrt
(fma
t_3
(pow t_0 2.0)
(pow (fma t_1 (cos (* phi2 0.5)) t_4) 2.0)))
(sqrt
(-
(- 1.0 (* (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0) t_3))
(pow (fma t_1 (cos (* -0.5 phi2)) t_4) 2.0))))
2.0)
R)))
(if (<= phi1 -1.55e-8)
t_5
(if (<= phi1 1.06e+15)
(*
(*
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* (* t_3 t_2) t_2)))
(sqrt
(-
(-
1.0
(*
t_3
(pow
(-
(* (cos (* lambda2 0.5)) t_0)
(* (sin (* lambda2 0.5)) (cos (* lambda1 0.5))))
2.0)))
(pow (sin (* (- phi1 phi2) 0.5)) 2.0))))
2.0)
R)
t_5))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((lambda1 * 0.5));
double t_1 = sin((phi1 * 0.5));
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double t_3 = cos(phi2) * cos(phi1);
double t_4 = cos((phi1 * 0.5)) * sin((-0.5 * phi2));
double t_5 = (atan2(sqrt(fma(t_3, pow(t_0, 2.0), pow(fma(t_1, cos((phi2 * 0.5)), t_4), 2.0))), sqrt(((1.0 - (pow(sin(((lambda1 - lambda2) * 0.5)), 2.0) * t_3)) - pow(fma(t_1, cos((-0.5 * phi2)), t_4), 2.0)))) * 2.0) * R;
double tmp;
if (phi1 <= -1.55e-8) {
tmp = t_5;
} else if (phi1 <= 1.06e+15) {
tmp = (atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((t_3 * t_2) * t_2))), sqrt(((1.0 - (t_3 * pow(((cos((lambda2 * 0.5)) * t_0) - (sin((lambda2 * 0.5)) * cos((lambda1 * 0.5)))), 2.0))) - pow(sin(((phi1 - phi2) * 0.5)), 2.0)))) * 2.0) * R;
} else {
tmp = t_5;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(lambda1 * 0.5)) t_1 = sin(Float64(phi1 * 0.5)) t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_3 = Float64(cos(phi2) * cos(phi1)) t_4 = Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(-0.5 * phi2))) t_5 = Float64(Float64(atan(sqrt(fma(t_3, (t_0 ^ 2.0), (fma(t_1, cos(Float64(phi2 * 0.5)), t_4) ^ 2.0))), sqrt(Float64(Float64(1.0 - Float64((sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0) * t_3)) - (fma(t_1, cos(Float64(-0.5 * phi2)), t_4) ^ 2.0)))) * 2.0) * R) tmp = 0.0 if (phi1 <= -1.55e-8) tmp = t_5; elseif (phi1 <= 1.06e+15) tmp = Float64(Float64(atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(t_3 * t_2) * t_2))), sqrt(Float64(Float64(1.0 - Float64(t_3 * (Float64(Float64(cos(Float64(lambda2 * 0.5)) * t_0) - Float64(sin(Float64(lambda2 * 0.5)) * cos(Float64(lambda1 * 0.5)))) ^ 2.0))) - (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0)))) * 2.0) * R); else tmp = t_5; end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$4 = N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(N[(N[ArcTan[N[Sqrt[N[(t$95$3 * N[Power[t$95$0, 2.0], $MachinePrecision] + N[Power[N[(t$95$1 * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] + t$95$4), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[(N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * t$95$3), $MachinePrecision]), $MachinePrecision] - N[Power[N[(t$95$1 * N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] + t$95$4), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]}, If[LessEqual[phi1, -1.55e-8], t$95$5, If[LessEqual[phi1, 1.06e+15], N[(N[(N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(t$95$3 * t$95$2), $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[(t$95$3 * N[Power[N[(N[(N[Cos[N[(lambda2 * 0.5), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision] - N[(N[Sin[N[(lambda2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - 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$5]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\lambda_1 \cdot 0.5\right)\\
t_1 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_3 := \cos \phi_2 \cdot \cos \phi_1\\
t_4 := \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(-0.5 \cdot \phi_2\right)\\
t_5 := \left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_3, {t\_0}^{2}, {\left(\mathsf{fma}\left(t\_1, \cos \left(\phi_2 \cdot 0.5\right), t\_4\right)\right)}^{2}\right)}}{\sqrt{\left(1 - {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2} \cdot t\_3\right) - {\left(\mathsf{fma}\left(t\_1, \cos \left(-0.5 \cdot \phi_2\right), t\_4\right)\right)}^{2}}} \cdot 2\right) \cdot R\\
\mathbf{if}\;\phi_1 \leq -1.55 \cdot 10^{-8}:\\
\;\;\;\;t\_5\\
\mathbf{elif}\;\phi_1 \leq 1.06 \cdot 10^{+15}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(t\_3 \cdot t\_2\right) \cdot t\_2}}{\sqrt{\left(1 - t\_3 \cdot {\left(\cos \left(\lambda_2 \cdot 0.5\right) \cdot t\_0 - \sin \left(\lambda_2 \cdot 0.5\right) \cdot \cos \left(\lambda_1 \cdot 0.5\right)\right)}^{2}\right) - {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;t\_5\\
\end{array}
\end{array}
if phi1 < -1.55e-8 or 1.06e15 < phi1 Initial program 45.8%
lift--.f64N/A
lift-+.f64N/A
+-commutativeN/A
associate--r+N/A
lower--.f64N/A
Applied rewrites45.8%
lift-sin.f64N/A
lift-*.f64N/A
lift--.f64N/A
distribute-rgt-out--N/A
lift-*.f64N/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
lift-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
metadata-evalN/A
lower-*.f64N/A
lift-cos.f64N/A
lower-*.f64N/A
Applied rewrites47.3%
Applied rewrites76.8%
Taylor expanded in lambda2 around 0
associate-*r*N/A
lower-fma.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f64N/A
lower-pow.f64N/A
Applied rewrites63.1%
if -1.55e-8 < phi1 < 1.06e15Initial program 82.2%
lift--.f64N/A
lift-+.f64N/A
+-commutativeN/A
associate--r+N/A
lower--.f64N/A
Applied rewrites82.2%
lift-sin.f64N/A
lift-*.f64N/A
*-commutativeN/A
metadata-evalN/A
div-invN/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
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
Applied rewrites82.6%
Final simplification74.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* phi1 0.5)))
(t_1 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_2 (* (cos (* phi1 0.5)) (sin (* -0.5 phi2)))))
(*
(*
(atan2
(sqrt
(+
(* (* t_1 (cos phi1)) (cos phi2))
(pow (fma t_0 (cos (* phi2 0.5)) t_2) 2.0)))
(sqrt
(-
(- 1.0 (* t_1 (* (cos phi2) (cos phi1))))
(pow (fma t_0 (cos (* -0.5 phi2)) t_2) 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 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_2 = cos((phi1 * 0.5)) * sin((-0.5 * phi2));
return (atan2(sqrt((((t_1 * cos(phi1)) * cos(phi2)) + pow(fma(t_0, cos((phi2 * 0.5)), t_2), 2.0))), sqrt(((1.0 - (t_1 * (cos(phi2) * cos(phi1)))) - pow(fma(t_0, cos((-0.5 * phi2)), t_2), 2.0)))) * 2.0) * R;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi1 * 0.5)) t_1 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_2 = Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(-0.5 * phi2))) return Float64(Float64(atan(sqrt(Float64(Float64(Float64(t_1 * cos(phi1)) * cos(phi2)) + (fma(t_0, cos(Float64(phi2 * 0.5)), t_2) ^ 2.0))), sqrt(Float64(Float64(1.0 - Float64(t_1 * Float64(cos(phi2) * cos(phi1)))) - (fma(t_0, cos(Float64(-0.5 * phi2)), t_2) ^ 2.0)))) * 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[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]}, N[(N[(N[ArcTan[N[Sqrt[N[(N[(N[(t$95$1 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] + N[Power[N[(t$95$0 * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] + t$95$2), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[(t$95$1 * N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[Power[N[(t$95$0 * N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] + t$95$2), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_1 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_2 := \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(-0.5 \cdot \phi_2\right)\\
\left(\tan^{-1}_* \frac{\sqrt{\left(t\_1 \cdot \cos \phi_1\right) \cdot \cos \phi_2 + {\left(\mathsf{fma}\left(t\_0, \cos \left(\phi_2 \cdot 0.5\right), t\_2\right)\right)}^{2}}}{\sqrt{\left(1 - t\_1 \cdot \left(\cos \phi_2 \cdot \cos \phi_1\right)\right) - {\left(\mathsf{fma}\left(t\_0, \cos \left(-0.5 \cdot \phi_2\right), t\_2\right)\right)}^{2}}} \cdot 2\right) \cdot R
\end{array}
\end{array}
Initial program 66.4%
lift--.f64N/A
lift-+.f64N/A
+-commutativeN/A
associate--r+N/A
lower--.f64N/A
Applied rewrites66.4%
lift-sin.f64N/A
lift-*.f64N/A
lift--.f64N/A
distribute-rgt-out--N/A
lift-*.f64N/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
lift-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
metadata-evalN/A
lower-*.f64N/A
lift-cos.f64N/A
lower-*.f64N/A
Applied rewrites67.1%
Applied rewrites80.3%
lift-*.f64N/A
lift-*.f64N/A
associate-*l*N/A
pow2N/A
lift-sin.f64N/A
lift-/.f64N/A
div-invN/A
lift--.f64N/A
metadata-evalN/A
lift--.f64N/A
lift-*.f64N/A
lift-sin.f64N/A
lift-pow.f64N/A
*-commutativeN/A
lift-*.f64N/A
Applied rewrites80.3%
Final simplification80.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* phi1 0.5)))
(t_1 (cos (* phi1 0.5)))
(t_2 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
(*
(* 2.0 R)
(atan2
(sqrt
(fma
(* t_2 (cos phi2))
(cos phi1)
(pow (fma (- t_1) (sin (* phi2 0.5)) (* (cos (* phi2 0.5)) t_0)) 2.0)))
(sqrt
(-
1.0
(fma
(* (cos phi2) (cos phi1))
t_2
(pow
(fma (sin (* -0.5 phi2)) t_1 (* (cos (* -0.5 phi2)) t_0))
2.0))))))))
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 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
return (2.0 * R) * atan2(sqrt(fma((t_2 * cos(phi2)), cos(phi1), pow(fma(-t_1, sin((phi2 * 0.5)), (cos((phi2 * 0.5)) * t_0)), 2.0))), sqrt((1.0 - fma((cos(phi2) * cos(phi1)), t_2, pow(fma(sin((-0.5 * phi2)), t_1, (cos((-0.5 * phi2)) * t_0)), 2.0)))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi1 * 0.5)) t_1 = cos(Float64(phi1 * 0.5)) t_2 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 return Float64(Float64(2.0 * R) * atan(sqrt(fma(Float64(t_2 * cos(phi2)), cos(phi1), (fma(Float64(-t_1), sin(Float64(phi2 * 0.5)), Float64(cos(Float64(phi2 * 0.5)) * t_0)) ^ 2.0))), sqrt(Float64(1.0 - fma(Float64(cos(phi2) * cos(phi1)), t_2, (fma(sin(Float64(-0.5 * phi2)), t_1, Float64(cos(Float64(-0.5 * phi2)) * t_0)) ^ 2.0)))))) 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[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(N[(2.0 * R), $MachinePrecision] * N[ArcTan[N[Sqrt[N[(N[(t$95$2 * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[Cos[phi1], $MachinePrecision] + N[Power[N[((-t$95$1) * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] + 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[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] * t$95$2 + N[Power[N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$1 + N[(N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $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 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
\left(2 \cdot R\right) \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_2 \cdot \cos \phi_2, \cos \phi_1, {\left(\mathsf{fma}\left(-t\_1, \sin \left(\phi_2 \cdot 0.5\right), \cos \left(\phi_2 \cdot 0.5\right) \cdot t\_0\right)\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left(\cos \phi_2 \cdot \cos \phi_1, t\_2, {\left(\mathsf{fma}\left(\sin \left(-0.5 \cdot \phi_2\right), t\_1, \cos \left(-0.5 \cdot \phi_2\right) \cdot t\_0\right)\right)}^{2}\right)}}
\end{array}
\end{array}
Initial program 66.4%
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-*.f6467.4
Applied rewrites67.4%
lift-sin.f64N/A
lift-/.f64N/A
clear-numN/A
associate-/r/N/A
metadata-evalN/A
lift--.f64N/A
distribute-rgt-out--N/A
lift-*.f64N/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
sin-sumN/A
lift-sin.f64N/A
lower-fma.f64N/A
lift-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
metadata-evalN/A
lower-*.f64N/A
Applied rewrites80.2%
Taylor expanded in lambda1 around 0
Applied rewrites80.2%
Final simplification80.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi2) (cos phi1)))
(t_1 (cos (* phi2 0.5)))
(t_2 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_3 (cos (* phi1 0.5)))
(t_4 (* t_3 (sin (* -0.5 phi2))))
(t_5 (sin (/ (- lambda1 lambda2) 2.0)))
(t_6 (* t_2 (cos phi1)))
(t_7 (sin (* phi1 0.5)))
(t_8 (pow (fma t_7 (cos (* -0.5 phi2)) t_4) 2.0))
(t_9 (pow (- (* t_1 t_7) (* (sin (* phi2 0.5)) t_3)) 2.0))
(t_10 (* (* t_0 t_5) t_5)))
(if (<= phi1 -61000000000.0)
(* (* (atan2 (sqrt (+ t_6 t_9)) (sqrt (- 1.0 (+ t_8 t_10)))) 2.0) R)
(if (<= phi1 1750000000000.0)
(*
(*
(atan2 (sqrt (+ t_9 t_10)) (sqrt (- 1.0 (+ t_8 (* t_2 (cos phi2))))))
2.0)
R)
(*
(*
(atan2
(sqrt (+ t_6 (pow (fma t_7 t_1 t_4) 2.0)))
(sqrt (- (- 1.0 (* t_2 t_0)) t_8)))
2.0)
R)))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi2) * cos(phi1);
double t_1 = cos((phi2 * 0.5));
double t_2 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_3 = cos((phi1 * 0.5));
double t_4 = t_3 * sin((-0.5 * phi2));
double t_5 = sin(((lambda1 - lambda2) / 2.0));
double t_6 = t_2 * cos(phi1);
double t_7 = sin((phi1 * 0.5));
double t_8 = pow(fma(t_7, cos((-0.5 * phi2)), t_4), 2.0);
double t_9 = pow(((t_1 * t_7) - (sin((phi2 * 0.5)) * t_3)), 2.0);
double t_10 = (t_0 * t_5) * t_5;
double tmp;
if (phi1 <= -61000000000.0) {
tmp = (atan2(sqrt((t_6 + t_9)), sqrt((1.0 - (t_8 + t_10)))) * 2.0) * R;
} else if (phi1 <= 1750000000000.0) {
tmp = (atan2(sqrt((t_9 + t_10)), sqrt((1.0 - (t_8 + (t_2 * cos(phi2)))))) * 2.0) * R;
} else {
tmp = (atan2(sqrt((t_6 + pow(fma(t_7, t_1, t_4), 2.0))), sqrt(((1.0 - (t_2 * t_0)) - t_8))) * 2.0) * R;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi2) * cos(phi1)) t_1 = cos(Float64(phi2 * 0.5)) t_2 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_3 = cos(Float64(phi1 * 0.5)) t_4 = Float64(t_3 * sin(Float64(-0.5 * phi2))) t_5 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_6 = Float64(t_2 * cos(phi1)) t_7 = sin(Float64(phi1 * 0.5)) t_8 = fma(t_7, cos(Float64(-0.5 * phi2)), t_4) ^ 2.0 t_9 = Float64(Float64(t_1 * t_7) - Float64(sin(Float64(phi2 * 0.5)) * t_3)) ^ 2.0 t_10 = Float64(Float64(t_0 * t_5) * t_5) tmp = 0.0 if (phi1 <= -61000000000.0) tmp = Float64(Float64(atan(sqrt(Float64(t_6 + t_9)), sqrt(Float64(1.0 - Float64(t_8 + t_10)))) * 2.0) * R); elseif (phi1 <= 1750000000000.0) tmp = Float64(Float64(atan(sqrt(Float64(t_9 + t_10)), sqrt(Float64(1.0 - Float64(t_8 + Float64(t_2 * cos(phi2)))))) * 2.0) * R); else tmp = Float64(Float64(atan(sqrt(Float64(t_6 + (fma(t_7, t_1, t_4) ^ 2.0))), sqrt(Float64(Float64(1.0 - Float64(t_2 * t_0)) - t_8))) * 2.0) * R); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(phi2 * 0.5), $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[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[(t$95$3 * N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$6 = N[(t$95$2 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$7 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$8 = N[Power[N[(t$95$7 * N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] + t$95$4), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$9 = N[Power[N[(N[(t$95$1 * t$95$7), $MachinePrecision] - N[(N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * t$95$3), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$10 = N[(N[(t$95$0 * t$95$5), $MachinePrecision] * t$95$5), $MachinePrecision]}, If[LessEqual[phi1, -61000000000.0], N[(N[(N[ArcTan[N[Sqrt[N[(t$95$6 + t$95$9), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$8 + t$95$10), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], If[LessEqual[phi1, 1750000000000.0], N[(N[(N[ArcTan[N[Sqrt[N[(t$95$9 + t$95$10), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$8 + N[(t$95$2 * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], N[(N[(N[ArcTan[N[Sqrt[N[(t$95$6 + N[Power[N[(t$95$7 * t$95$1 + t$95$4), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[(t$95$2 * t$95$0), $MachinePrecision]), $MachinePrecision] - t$95$8), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]]]]]]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_2 \cdot \cos \phi_1\\
t_1 := \cos \left(\phi_2 \cdot 0.5\right)\\
t_2 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_3 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_4 := t\_3 \cdot \sin \left(-0.5 \cdot \phi_2\right)\\
t_5 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_6 := t\_2 \cdot \cos \phi_1\\
t_7 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_8 := {\left(\mathsf{fma}\left(t\_7, \cos \left(-0.5 \cdot \phi_2\right), t\_4\right)\right)}^{2}\\
t_9 := {\left(t\_1 \cdot t\_7 - \sin \left(\phi_2 \cdot 0.5\right) \cdot t\_3\right)}^{2}\\
t_10 := \left(t\_0 \cdot t\_5\right) \cdot t\_5\\
\mathbf{if}\;\phi_1 \leq -61000000000:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{t\_6 + t\_9}}{\sqrt{1 - \left(t\_8 + t\_10\right)}} \cdot 2\right) \cdot R\\
\mathbf{elif}\;\phi_1 \leq 1750000000000:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{t\_9 + t\_10}}{\sqrt{1 - \left(t\_8 + t\_2 \cdot \cos \phi_2\right)}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{t\_6 + {\left(\mathsf{fma}\left(t\_7, t\_1, t\_4\right)\right)}^{2}}}{\sqrt{\left(1 - t\_2 \cdot t\_0\right) - t\_8}} \cdot 2\right) \cdot R\\
\end{array}
\end{array}
if phi1 < -6.1e10Initial program 46.1%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f6448.4
Applied rewrites48.4%
lift-sin.f64N/A
lift-/.f64N/A
clear-numN/A
associate-/r/N/A
metadata-evalN/A
lift--.f64N/A
distribute-rgt-out--N/A
lift-*.f64N/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
sin-sumN/A
lift-sin.f64N/A
lower-fma.f64N/A
lift-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
metadata-evalN/A
lower-*.f64N/A
Applied rewrites77.4%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-*.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f6459.7
Applied rewrites59.7%
if -6.1e10 < phi1 < 1.75e12Initial program 80.9%
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
clear-numN/A
associate-/r/N/A
metadata-evalN/A
lift--.f64N/A
distribute-rgt-out--N/A
lift-*.f64N/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
lift-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
metadata-evalN/A
lower-*.f64N/A
Applied rewrites82.4%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-*.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f6481.4
Applied rewrites81.4%
if 1.75e12 < phi1 Initial program 48.1%
lift--.f64N/A
lift-+.f64N/A
+-commutativeN/A
associate--r+N/A
lower--.f64N/A
Applied rewrites48.1%
lift-sin.f64N/A
lift-*.f64N/A
lift--.f64N/A
distribute-rgt-out--N/A
lift-*.f64N/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
lift-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
metadata-evalN/A
lower-*.f64N/A
lift-cos.f64N/A
lower-*.f64N/A
Applied rewrites49.0%
Applied rewrites77.3%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-*.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f6461.0
Applied rewrites61.0%
Final simplification72.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (* -0.5 phi1)))
(t_1 (sin (* phi1 0.5)))
(t_2 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_3 (cos (* phi1 0.5)))
(t_4
(pow (- (* (cos (* phi2 0.5)) t_1) (* (sin (* phi2 0.5)) t_3)) 2.0))
(t_5 (sin (/ (- lambda1 lambda2) 2.0)))
(t_6 (* (* (* (cos phi2) (cos phi1)) t_5) t_5))
(t_7
(*
(*
(atan2
(sqrt (+ (* t_2 (cos phi2)) t_4))
(sqrt
(-
1.0
(+
(pow
(fma t_1 (cos (* -0.5 phi2)) (* t_3 (sin (* -0.5 phi2))))
2.0)
t_6))))
2.0)
R)))
(if (<= phi2 -7.5e-6)
t_7
(if (<= phi2 2.4e-18)
(*
(*
(atan2
(sqrt (+ t_4 t_6))
(sqrt (fma (* phi2 t_1) t_0 (- (pow t_0 2.0) (* t_2 (cos phi1))))))
2.0)
R)
t_7))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((-0.5 * phi1));
double t_1 = sin((phi1 * 0.5));
double t_2 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_3 = cos((phi1 * 0.5));
double t_4 = pow(((cos((phi2 * 0.5)) * t_1) - (sin((phi2 * 0.5)) * t_3)), 2.0);
double t_5 = sin(((lambda1 - lambda2) / 2.0));
double t_6 = ((cos(phi2) * cos(phi1)) * t_5) * t_5;
double t_7 = (atan2(sqrt(((t_2 * cos(phi2)) + t_4)), sqrt((1.0 - (pow(fma(t_1, cos((-0.5 * phi2)), (t_3 * sin((-0.5 * phi2)))), 2.0) + t_6)))) * 2.0) * R;
double tmp;
if (phi2 <= -7.5e-6) {
tmp = t_7;
} else if (phi2 <= 2.4e-18) {
tmp = (atan2(sqrt((t_4 + t_6)), sqrt(fma((phi2 * t_1), t_0, (pow(t_0, 2.0) - (t_2 * cos(phi1)))))) * 2.0) * R;
} else {
tmp = t_7;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(-0.5 * phi1)) t_1 = sin(Float64(phi1 * 0.5)) t_2 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_3 = cos(Float64(phi1 * 0.5)) t_4 = Float64(Float64(cos(Float64(phi2 * 0.5)) * t_1) - Float64(sin(Float64(phi2 * 0.5)) * t_3)) ^ 2.0 t_5 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_6 = Float64(Float64(Float64(cos(phi2) * cos(phi1)) * t_5) * t_5) t_7 = Float64(Float64(atan(sqrt(Float64(Float64(t_2 * cos(phi2)) + t_4)), sqrt(Float64(1.0 - Float64((fma(t_1, cos(Float64(-0.5 * phi2)), Float64(t_3 * sin(Float64(-0.5 * phi2)))) ^ 2.0) + t_6)))) * 2.0) * R) tmp = 0.0 if (phi2 <= -7.5e-6) tmp = t_7; elseif (phi2 <= 2.4e-18) tmp = Float64(Float64(atan(sqrt(Float64(t_4 + t_6)), sqrt(fma(Float64(phi2 * t_1), t_0, Float64((t_0 ^ 2.0) - Float64(t_2 * cos(phi1)))))) * 2.0) * R); else tmp = t_7; end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(phi1 * 0.5), $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[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[Power[N[(N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * t$95$1), $MachinePrecision] - N[(N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * t$95$3), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$5 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$6 = N[(N[(N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] * t$95$5), $MachinePrecision] * t$95$5), $MachinePrecision]}, Block[{t$95$7 = N[(N[(N[ArcTan[N[Sqrt[N[(N[(t$95$2 * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] + t$95$4), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[(t$95$1 * N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] + N[(t$95$3 * N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$6), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]}, If[LessEqual[phi2, -7.5e-6], t$95$7, If[LessEqual[phi2, 2.4e-18], N[(N[(N[ArcTan[N[Sqrt[N[(t$95$4 + t$95$6), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(phi2 * t$95$1), $MachinePrecision] * t$95$0 + N[(N[Power[t$95$0, 2.0], $MachinePrecision] - N[(t$95$2 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], t$95$7]]]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \left(-0.5 \cdot \phi_1\right)\\
t_1 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_2 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_3 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_4 := {\left(\cos \left(\phi_2 \cdot 0.5\right) \cdot t\_1 - \sin \left(\phi_2 \cdot 0.5\right) \cdot t\_3\right)}^{2}\\
t_5 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_6 := \left(\left(\cos \phi_2 \cdot \cos \phi_1\right) \cdot t\_5\right) \cdot t\_5\\
t_7 := \left(\tan^{-1}_* \frac{\sqrt{t\_2 \cdot \cos \phi_2 + t\_4}}{\sqrt{1 - \left({\left(\mathsf{fma}\left(t\_1, \cos \left(-0.5 \cdot \phi_2\right), t\_3 \cdot \sin \left(-0.5 \cdot \phi_2\right)\right)\right)}^{2} + t\_6\right)}} \cdot 2\right) \cdot R\\
\mathbf{if}\;\phi_2 \leq -7.5 \cdot 10^{-6}:\\
\;\;\;\;t\_7\\
\mathbf{elif}\;\phi_2 \leq 2.4 \cdot 10^{-18}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{t\_4 + t\_6}}{\sqrt{\mathsf{fma}\left(\phi_2 \cdot t\_1, t\_0, {t\_0}^{2} - t\_2 \cdot \cos \phi_1\right)}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;t\_7\\
\end{array}
\end{array}
if phi2 < -7.50000000000000019e-6 or 2.39999999999999994e-18 < phi2 Initial program 52.2%
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-*.f6454.1
Applied rewrites54.1%
lift-sin.f64N/A
lift-/.f64N/A
clear-numN/A
associate-/r/N/A
metadata-evalN/A
lift--.f64N/A
distribute-rgt-out--N/A
lift-*.f64N/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
sin-sumN/A
lift-sin.f64N/A
lower-fma.f64N/A
lift-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
metadata-evalN/A
lower-*.f64N/A
Applied rewrites78.7%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-*.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f6463.1
Applied rewrites63.1%
if -7.50000000000000019e-6 < phi2 < 2.39999999999999994e-18Initial program 81.1%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f6481.1
Applied rewrites81.1%
Taylor expanded in phi2 around 0
Applied rewrites81.9%
Final simplification72.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi2) (cos phi1)))
(t_1 (cos (* phi2 0.5)))
(t_2 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_3 (cos (* phi1 0.5)))
(t_4 (* t_3 (sin (* -0.5 phi2))))
(t_5 (sin (/ (- lambda1 lambda2) 2.0)))
(t_6 (* t_2 (cos phi1)))
(t_7 (sin (* phi1 0.5)))
(t_8 (pow (fma t_7 (cos (* -0.5 phi2)) t_4) 2.0))
(t_9 (* (* t_0 t_5) t_5)))
(if (<= phi1 -1550000000000.0)
(*
(*
(atan2
(sqrt (+ t_6 (pow (- (* t_1 t_7) (* (sin (* phi2 0.5)) t_3)) 2.0)))
(sqrt (- 1.0 (+ t_8 t_9))))
2.0)
R)
(if (<= phi1 1750000000000.0)
(*
(*
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) t_9))
(sqrt
(-
(-
1.0
(*
t_0
(pow
(-
(* (cos (* lambda2 0.5)) (sin (* lambda1 0.5)))
(* (sin (* lambda2 0.5)) (cos (* lambda1 0.5))))
2.0)))
(pow (sin (* (- phi1 phi2) 0.5)) 2.0))))
2.0)
R)
(*
(*
(atan2
(sqrt (+ t_6 (pow (fma t_7 t_1 t_4) 2.0)))
(sqrt (- (- 1.0 (* t_2 t_0)) t_8)))
2.0)
R)))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi2) * cos(phi1);
double t_1 = cos((phi2 * 0.5));
double t_2 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_3 = cos((phi1 * 0.5));
double t_4 = t_3 * sin((-0.5 * phi2));
double t_5 = sin(((lambda1 - lambda2) / 2.0));
double t_6 = t_2 * cos(phi1);
double t_7 = sin((phi1 * 0.5));
double t_8 = pow(fma(t_7, cos((-0.5 * phi2)), t_4), 2.0);
double t_9 = (t_0 * t_5) * t_5;
double tmp;
if (phi1 <= -1550000000000.0) {
tmp = (atan2(sqrt((t_6 + pow(((t_1 * t_7) - (sin((phi2 * 0.5)) * t_3)), 2.0))), sqrt((1.0 - (t_8 + t_9)))) * 2.0) * R;
} else if (phi1 <= 1750000000000.0) {
tmp = (atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + t_9)), sqrt(((1.0 - (t_0 * pow(((cos((lambda2 * 0.5)) * sin((lambda1 * 0.5))) - (sin((lambda2 * 0.5)) * cos((lambda1 * 0.5)))), 2.0))) - pow(sin(((phi1 - phi2) * 0.5)), 2.0)))) * 2.0) * R;
} else {
tmp = (atan2(sqrt((t_6 + pow(fma(t_7, t_1, t_4), 2.0))), sqrt(((1.0 - (t_2 * t_0)) - t_8))) * 2.0) * R;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi2) * cos(phi1)) t_1 = cos(Float64(phi2 * 0.5)) t_2 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_3 = cos(Float64(phi1 * 0.5)) t_4 = Float64(t_3 * sin(Float64(-0.5 * phi2))) t_5 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_6 = Float64(t_2 * cos(phi1)) t_7 = sin(Float64(phi1 * 0.5)) t_8 = fma(t_7, cos(Float64(-0.5 * phi2)), t_4) ^ 2.0 t_9 = Float64(Float64(t_0 * t_5) * t_5) tmp = 0.0 if (phi1 <= -1550000000000.0) tmp = Float64(Float64(atan(sqrt(Float64(t_6 + (Float64(Float64(t_1 * t_7) - Float64(sin(Float64(phi2 * 0.5)) * t_3)) ^ 2.0))), sqrt(Float64(1.0 - Float64(t_8 + t_9)))) * 2.0) * R); elseif (phi1 <= 1750000000000.0) tmp = Float64(Float64(atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + t_9)), sqrt(Float64(Float64(1.0 - Float64(t_0 * (Float64(Float64(cos(Float64(lambda2 * 0.5)) * sin(Float64(lambda1 * 0.5))) - Float64(sin(Float64(lambda2 * 0.5)) * cos(Float64(lambda1 * 0.5)))) ^ 2.0))) - (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0)))) * 2.0) * R); else tmp = Float64(Float64(atan(sqrt(Float64(t_6 + (fma(t_7, t_1, t_4) ^ 2.0))), sqrt(Float64(Float64(1.0 - Float64(t_2 * t_0)) - t_8))) * 2.0) * R); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Cos[N[(phi2 * 0.5), $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[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$4 = N[(t$95$3 * N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$6 = N[(t$95$2 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$7 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$8 = N[Power[N[(t$95$7 * N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] + t$95$4), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$9 = N[(N[(t$95$0 * t$95$5), $MachinePrecision] * t$95$5), $MachinePrecision]}, If[LessEqual[phi1, -1550000000000.0], N[(N[(N[ArcTan[N[Sqrt[N[(t$95$6 + N[Power[N[(N[(t$95$1 * t$95$7), $MachinePrecision] - N[(N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * t$95$3), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$8 + t$95$9), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], If[LessEqual[phi1, 1750000000000.0], N[(N[(N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$9), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[(t$95$0 * N[Power[N[(N[(N[Cos[N[(lambda2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Sin[N[(lambda2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - 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[N[Sqrt[N[(t$95$6 + N[Power[N[(t$95$7 * t$95$1 + t$95$4), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[(t$95$2 * t$95$0), $MachinePrecision]), $MachinePrecision] - t$95$8), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]]]]]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_2 \cdot \cos \phi_1\\
t_1 := \cos \left(\phi_2 \cdot 0.5\right)\\
t_2 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_3 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_4 := t\_3 \cdot \sin \left(-0.5 \cdot \phi_2\right)\\
t_5 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_6 := t\_2 \cdot \cos \phi_1\\
t_7 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_8 := {\left(\mathsf{fma}\left(t\_7, \cos \left(-0.5 \cdot \phi_2\right), t\_4\right)\right)}^{2}\\
t_9 := \left(t\_0 \cdot t\_5\right) \cdot t\_5\\
\mathbf{if}\;\phi_1 \leq -1550000000000:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{t\_6 + {\left(t\_1 \cdot t\_7 - \sin \left(\phi_2 \cdot 0.5\right) \cdot t\_3\right)}^{2}}}{\sqrt{1 - \left(t\_8 + t\_9\right)}} \cdot 2\right) \cdot R\\
\mathbf{elif}\;\phi_1 \leq 1750000000000:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_9}}{\sqrt{\left(1 - t\_0 \cdot {\left(\cos \left(\lambda_2 \cdot 0.5\right) \cdot \sin \left(\lambda_1 \cdot 0.5\right) - \sin \left(\lambda_2 \cdot 0.5\right) \cdot \cos \left(\lambda_1 \cdot 0.5\right)\right)}^{2}\right) - {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{t\_6 + {\left(\mathsf{fma}\left(t\_7, t\_1, t\_4\right)\right)}^{2}}}{\sqrt{\left(1 - t\_2 \cdot t\_0\right) - t\_8}} \cdot 2\right) \cdot R\\
\end{array}
\end{array}
if phi1 < -1.55e12Initial program 46.7%
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-*.f6449.1
Applied rewrites49.1%
lift-sin.f64N/A
lift-/.f64N/A
clear-numN/A
associate-/r/N/A
metadata-evalN/A
lift--.f64N/A
distribute-rgt-out--N/A
lift-*.f64N/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
sin-sumN/A
lift-sin.f64N/A
lower-fma.f64N/A
lift-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
metadata-evalN/A
lower-*.f64N/A
Applied rewrites77.7%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-*.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f6460.9
Applied rewrites60.9%
if -1.55e12 < phi1 < 1.75e12Initial program 80.2%
lift--.f64N/A
lift-+.f64N/A
+-commutativeN/A
associate--r+N/A
lower--.f64N/A
Applied rewrites80.3%
lift-sin.f64N/A
lift-*.f64N/A
*-commutativeN/A
metadata-evalN/A
div-invN/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
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
Applied rewrites80.7%
if 1.75e12 < phi1 Initial program 48.1%
lift--.f64N/A
lift-+.f64N/A
+-commutativeN/A
associate--r+N/A
lower--.f64N/A
Applied rewrites48.1%
lift-sin.f64N/A
lift-*.f64N/A
lift--.f64N/A
distribute-rgt-out--N/A
lift-*.f64N/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
lift-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
metadata-evalN/A
lower-*.f64N/A
lift-cos.f64N/A
lower-*.f64N/A
Applied rewrites49.0%
Applied rewrites77.3%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-*.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f6461.0
Applied rewrites61.0%
Final simplification72.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* phi1 0.5)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (* (cos phi2) (cos phi1)))
(t_3 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_4 (* (cos (* phi1 0.5)) (sin (* -0.5 phi2))))
(t_5
(*
(*
(atan2
(sqrt
(+ (* t_3 (cos phi1)) (pow (fma t_0 (cos (* phi2 0.5)) t_4) 2.0)))
(sqrt
(-
(- 1.0 (* t_3 t_2))
(pow (fma t_0 (cos (* -0.5 phi2)) t_4) 2.0))))
2.0)
R)))
(if (<= phi1 -1550000000000.0)
t_5
(if (<= phi1 1750000000000.0)
(*
(*
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) (* (* t_2 t_1) t_1)))
(sqrt
(-
(-
1.0
(*
t_2
(pow
(-
(* (cos (* lambda2 0.5)) (sin (* lambda1 0.5)))
(* (sin (* lambda2 0.5)) (cos (* lambda1 0.5))))
2.0)))
(pow (sin (* (- phi1 phi2) 0.5)) 2.0))))
2.0)
R)
t_5))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((phi1 * 0.5));
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = cos(phi2) * cos(phi1);
double t_3 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_4 = cos((phi1 * 0.5)) * sin((-0.5 * phi2));
double t_5 = (atan2(sqrt(((t_3 * cos(phi1)) + pow(fma(t_0, cos((phi2 * 0.5)), t_4), 2.0))), sqrt(((1.0 - (t_3 * t_2)) - pow(fma(t_0, cos((-0.5 * phi2)), t_4), 2.0)))) * 2.0) * R;
double tmp;
if (phi1 <= -1550000000000.0) {
tmp = t_5;
} else if (phi1 <= 1750000000000.0) {
tmp = (atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + ((t_2 * t_1) * t_1))), sqrt(((1.0 - (t_2 * pow(((cos((lambda2 * 0.5)) * sin((lambda1 * 0.5))) - (sin((lambda2 * 0.5)) * cos((lambda1 * 0.5)))), 2.0))) - pow(sin(((phi1 - phi2) * 0.5)), 2.0)))) * 2.0) * R;
} else {
tmp = t_5;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi1 * 0.5)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(cos(phi2) * cos(phi1)) t_3 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_4 = Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(-0.5 * phi2))) t_5 = Float64(Float64(atan(sqrt(Float64(Float64(t_3 * cos(phi1)) + (fma(t_0, cos(Float64(phi2 * 0.5)), t_4) ^ 2.0))), sqrt(Float64(Float64(1.0 - Float64(t_3 * t_2)) - (fma(t_0, cos(Float64(-0.5 * phi2)), t_4) ^ 2.0)))) * 2.0) * R) tmp = 0.0 if (phi1 <= -1550000000000.0) tmp = t_5; elseif (phi1 <= 1750000000000.0) tmp = Float64(Float64(atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(t_2 * t_1) * t_1))), sqrt(Float64(Float64(1.0 - Float64(t_2 * (Float64(Float64(cos(Float64(lambda2 * 0.5)) * sin(Float64(lambda1 * 0.5))) - Float64(sin(Float64(lambda2 * 0.5)) * cos(Float64(lambda1 * 0.5)))) ^ 2.0))) - (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0)))) * 2.0) * R); else tmp = t_5; end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$3 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$4 = N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[(N[(N[ArcTan[N[Sqrt[N[(N[(t$95$3 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] + N[Power[N[(t$95$0 * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] + t$95$4), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[(t$95$3 * t$95$2), $MachinePrecision]), $MachinePrecision] - N[Power[N[(t$95$0 * N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] + t$95$4), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]}, If[LessEqual[phi1, -1550000000000.0], t$95$5, If[LessEqual[phi1, 1750000000000.0], N[(N[(N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(t$95$2 * t$95$1), $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[(t$95$2 * N[Power[N[(N[(N[Cos[N[(lambda2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Sin[N[(lambda2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - 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$5]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \cos \phi_2 \cdot \cos \phi_1\\
t_3 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_4 := \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(-0.5 \cdot \phi_2\right)\\
t_5 := \left(\tan^{-1}_* \frac{\sqrt{t\_3 \cdot \cos \phi_1 + {\left(\mathsf{fma}\left(t\_0, \cos \left(\phi_2 \cdot 0.5\right), t\_4\right)\right)}^{2}}}{\sqrt{\left(1 - t\_3 \cdot t\_2\right) - {\left(\mathsf{fma}\left(t\_0, \cos \left(-0.5 \cdot \phi_2\right), t\_4\right)\right)}^{2}}} \cdot 2\right) \cdot R\\
\mathbf{if}\;\phi_1 \leq -1550000000000:\\
\;\;\;\;t\_5\\
\mathbf{elif}\;\phi_1 \leq 1750000000000:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(t\_2 \cdot t\_1\right) \cdot t\_1}}{\sqrt{\left(1 - t\_2 \cdot {\left(\cos \left(\lambda_2 \cdot 0.5\right) \cdot \sin \left(\lambda_1 \cdot 0.5\right) - \sin \left(\lambda_2 \cdot 0.5\right) \cdot \cos \left(\lambda_1 \cdot 0.5\right)\right)}^{2}\right) - {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;t\_5\\
\end{array}
\end{array}
if phi1 < -1.55e12 or 1.75e12 < phi1 Initial program 47.5%
lift--.f64N/A
lift-+.f64N/A
+-commutativeN/A
associate--r+N/A
lower--.f64N/A
Applied rewrites47.5%
lift-sin.f64N/A
lift-*.f64N/A
lift--.f64N/A
distribute-rgt-out--N/A
lift-*.f64N/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
lift-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
metadata-evalN/A
lower-*.f64N/A
lift-cos.f64N/A
lower-*.f64N/A
Applied rewrites49.0%
Applied rewrites77.5%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-*.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f6460.9
Applied rewrites60.9%
if -1.55e12 < phi1 < 1.75e12Initial program 80.2%
lift--.f64N/A
lift-+.f64N/A
+-commutativeN/A
associate--r+N/A
lower--.f64N/A
Applied rewrites80.3%
lift-sin.f64N/A
lift-*.f64N/A
*-commutativeN/A
metadata-evalN/A
div-invN/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
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
Applied rewrites80.7%
Final simplification72.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi2) (cos phi1)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0))))
(*
(*
(atan2
(sqrt
(+
(pow
(-
(* (cos (* phi2 0.5)) (sin (* phi1 0.5)))
(* (sin (* phi2 0.5)) (cos (* phi1 0.5))))
2.0)
(* (* t_0 t_1) t_1)))
(sqrt
(-
(pow (cos (/ (- phi1 phi2) -2.0)) 2.0)
(* (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0) t_0))))
2.0)
R)))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi2) * cos(phi1);
double t_1 = sin(((lambda1 - lambda2) / 2.0));
return (atan2(sqrt((pow(((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (sin((phi2 * 0.5)) * cos((phi1 * 0.5)))), 2.0) + ((t_0 * t_1) * t_1))), sqrt((pow(cos(((phi1 - phi2) / -2.0)), 2.0) - (pow(sin(((lambda1 - lambda2) * 0.5)), 2.0) * t_0)))) * 2.0) * R;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = cos(phi2) * cos(phi1)
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
code = (atan2(sqrt(((((cos((phi2 * 0.5d0)) * sin((phi1 * 0.5d0))) - (sin((phi2 * 0.5d0)) * cos((phi1 * 0.5d0)))) ** 2.0d0) + ((t_0 * t_1) * t_1))), sqrt(((cos(((phi1 - phi2) / (-2.0d0))) ** 2.0d0) - ((sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0) * t_0)))) * 2.0d0) * r
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.cos(phi2) * Math.cos(phi1);
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
return (Math.atan2(Math.sqrt((Math.pow(((Math.cos((phi2 * 0.5)) * Math.sin((phi1 * 0.5))) - (Math.sin((phi2 * 0.5)) * Math.cos((phi1 * 0.5)))), 2.0) + ((t_0 * t_1) * t_1))), Math.sqrt((Math.pow(Math.cos(((phi1 - phi2) / -2.0)), 2.0) - (Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0) * t_0)))) * 2.0) * R;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.cos(phi2) * math.cos(phi1) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) return (math.atan2(math.sqrt((math.pow(((math.cos((phi2 * 0.5)) * math.sin((phi1 * 0.5))) - (math.sin((phi2 * 0.5)) * math.cos((phi1 * 0.5)))), 2.0) + ((t_0 * t_1) * t_1))), math.sqrt((math.pow(math.cos(((phi1 - phi2) / -2.0)), 2.0) - (math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0) * t_0)))) * 2.0) * R
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi2) * cos(phi1)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(Float64(atan(sqrt(Float64((Float64(Float64(cos(Float64(phi2 * 0.5)) * sin(Float64(phi1 * 0.5))) - Float64(sin(Float64(phi2 * 0.5)) * cos(Float64(phi1 * 0.5)))) ^ 2.0) + Float64(Float64(t_0 * t_1) * t_1))), sqrt(Float64((cos(Float64(Float64(phi1 - phi2) / -2.0)) ^ 2.0) - Float64((sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0) * t_0)))) * 2.0) * R) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(phi2) * cos(phi1); t_1 = sin(((lambda1 - lambda2) / 2.0)); tmp = (atan2(sqrt(((((cos((phi2 * 0.5)) * sin((phi1 * 0.5))) - (sin((phi2 * 0.5)) * cos((phi1 * 0.5)))) ^ 2.0) + ((t_0 * t_1) * t_1))), sqrt(((cos(((phi1 - phi2) / -2.0)) ^ 2.0) - ((sin(((lambda1 - lambda2) * 0.5)) ^ 2.0) * t_0)))) * 2.0) * R; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(N[(N[ArcTan[N[Sqrt[N[(N[Power[N[(N[(N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(t$95$0 * t$95$1), $MachinePrecision] * t$95$1), $MachinePrecision]), $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] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_2 \cdot \cos \phi_1\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\left(\tan^{-1}_* \frac{\sqrt{{\left(\cos \left(\phi_2 \cdot 0.5\right) \cdot \sin \left(\phi_1 \cdot 0.5\right) - \sin \left(\phi_2 \cdot 0.5\right) \cdot \cos \left(\phi_1 \cdot 0.5\right)\right)}^{2} + \left(t\_0 \cdot t\_1\right) \cdot t\_1}}{\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 t\_0}} \cdot 2\right) \cdot R
\end{array}
\end{array}
Initial program 66.4%
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-*.f6467.4
Applied rewrites67.4%
lift--.f64N/A
lift-+.f64N/A
associate--r+N/A
lower--.f64N/A
Applied rewrites67.5%
Final simplification67.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi2) (cos phi1)))
(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 (* -0.5 phi2))
(cos (* phi1 0.5))
(* (cos (* -0.5 phi2)) (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(phi2) * cos(phi1);
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((-0.5 * phi2)), cos((phi1 * 0.5)), (cos((-0.5 * phi2)) * sin((phi1 * 0.5)))), 2.0))))) * 2.0) * R;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi2) * cos(phi1)) 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(-0.5 * phi2)), cos(Float64(phi1 * 0.5)), Float64(cos(Float64(-0.5 * phi2)) * sin(Float64(phi1 * 0.5)))) ^ 2.0))))) * 2.0) * R) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(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[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] + N[(N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_2 \cdot \cos \phi_1\\
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(-0.5 \cdot \phi_2\right), \cos \left(\phi_1 \cdot 0.5\right), \cos \left(-0.5 \cdot \phi_2\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 66.4%
lift--.f64N/A
lift-+.f64N/A
+-commutativeN/A
associate--r+N/A
lower--.f64N/A
Applied rewrites66.4%
lift-sin.f64N/A
lift-*.f64N/A
lift--.f64N/A
distribute-rgt-out--N/A
lift-*.f64N/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
lift-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
metadata-evalN/A
lower-*.f64N/A
lift-cos.f64N/A
lower-*.f64N/A
Applied rewrites67.1%
Taylor expanded in lambda1 around 0
Applied rewrites67.1%
Final simplification67.1%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(*
(*
(atan2
(sqrt (+ t_1 (* (* (* (cos phi2) (cos phi1)) t_0) t_0)))
(sqrt
(-
1.0
(-
t_1
(/
(*
(-
(cos (* (* (- lambda1 lambda2) 0.5) 2.0))
(cos (/ 0.0 (/ 2.0 (- lambda1 lambda2)))))
(+ (cos (- phi1 phi2)) (cos (+ phi2 phi1))))
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));
double t_1 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
return (atan2(sqrt((t_1 + (((cos(phi2) * cos(phi1)) * t_0) * t_0))), sqrt((1.0 - (t_1 - (((cos((((lambda1 - lambda2) * 0.5) * 2.0)) - cos((0.0 / (2.0 / (lambda1 - lambda2))))) * (cos((phi1 - phi2)) + cos((phi2 + phi1)))) / 4.0))))) * 2.0) * R;
}
real(8) function code(r, lambda1, lambda2, phi1, phi2)
real(8), intent (in) :: r
real(8), intent (in) :: lambda1
real(8), intent (in) :: lambda2
real(8), intent (in) :: phi1
real(8), intent (in) :: phi2
real(8) :: t_0
real(8) :: t_1
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0
code = (atan2(sqrt((t_1 + (((cos(phi2) * cos(phi1)) * t_0) * t_0))), sqrt((1.0d0 - (t_1 - (((cos((((lambda1 - lambda2) * 0.5d0) * 2.0d0)) - cos((0.0d0 / (2.0d0 / (lambda1 - lambda2))))) * (cos((phi1 - phi2)) + cos((phi2 + phi1)))) / 4.0d0))))) * 2.0d0) * r
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.sin(((lambda1 - lambda2) / 2.0));
double t_1 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0);
return (Math.atan2(Math.sqrt((t_1 + (((Math.cos(phi2) * Math.cos(phi1)) * t_0) * t_0))), Math.sqrt((1.0 - (t_1 - (((Math.cos((((lambda1 - lambda2) * 0.5) * 2.0)) - Math.cos((0.0 / (2.0 / (lambda1 - lambda2))))) * (Math.cos((phi1 - phi2)) + Math.cos((phi2 + phi1)))) / 4.0))))) * 2.0) * R;
}
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) return (math.atan2(math.sqrt((t_1 + (((math.cos(phi2) * math.cos(phi1)) * t_0) * t_0))), math.sqrt((1.0 - (t_1 - (((math.cos((((lambda1 - lambda2) * 0.5) * 2.0)) - math.cos((0.0 / (2.0 / (lambda1 - lambda2))))) * (math.cos((phi1 - phi2)) + math.cos((phi2 + phi1)))) / 4.0))))) * 2.0) * R
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 return Float64(Float64(atan(sqrt(Float64(t_1 + Float64(Float64(Float64(cos(phi2) * cos(phi1)) * t_0) * t_0))), sqrt(Float64(1.0 - Float64(t_1 - Float64(Float64(Float64(cos(Float64(Float64(Float64(lambda1 - lambda2) * 0.5) * 2.0)) - cos(Float64(0.0 / Float64(2.0 / Float64(lambda1 - lambda2))))) * Float64(cos(Float64(phi1 - phi2)) + cos(Float64(phi2 + phi1)))) / 4.0))))) * 2.0) * R) 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; tmp = (atan2(sqrt((t_1 + (((cos(phi2) * cos(phi1)) * t_0) * t_0))), sqrt((1.0 - (t_1 - (((cos((((lambda1 - lambda2) * 0.5) * 2.0)) - cos((0.0 / (2.0 / (lambda1 - lambda2))))) * (cos((phi1 - phi2)) + cos((phi2 + phi1)))) / 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]}, Block[{t$95$1 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(N[(N[ArcTan[N[Sqrt[N[(t$95$1 + N[(N[(N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$1 - N[(N[(N[(N[Cos[N[(N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision] * 2.0), $MachinePrecision]], $MachinePrecision] - N[Cos[N[(0.0 / N[(2.0 / N[(lambda1 - lambda2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[(N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision] + N[Cos[N[(phi2 + phi1), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision] / 4.0), $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 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
\left(\tan^{-1}_* \frac{\sqrt{t\_1 + \left(\left(\cos \phi_2 \cdot \cos \phi_1\right) \cdot t\_0\right) \cdot t\_0}}{\sqrt{1 - \left(t\_1 - \frac{\left(\cos \left(\left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right) \cdot 2\right) - \cos \left(\frac{0}{\frac{2}{\lambda_1 - \lambda_2}}\right)\right) \cdot \left(\cos \left(\phi_1 - \phi_2\right) + \cos \left(\phi_2 + \phi_1\right)\right)}{4}\right)}} \cdot 2\right) \cdot R
\end{array}
\end{array}
Initial program 66.4%
lift-*.f64N/A
lift-*.f64N/A
associate-*l*N/A
*-commutativeN/A
lift-sin.f64N/A
lift-sin.f64N/A
sin-multN/A
lift-*.f64N/A
lift-cos.f64N/A
lift-cos.f64N/A
cos-multN/A
frac-timesN/A
metadata-evalN/A
metadata-evalN/A
Applied rewrites66.8%
Final simplification66.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi2) (cos phi1)))
(t_1 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
(*
(* 2.0 R)
(atan2
(sqrt (fma t_1 t_0 (pow (sin (* (- phi1 phi2) 0.5)) 2.0)))
(sqrt (- (pow (cos (/ (- phi1 phi2) -2.0)) 2.0) (* t_1 t_0)))))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi2) * cos(phi1);
double t_1 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
return (2.0 * R) * atan2(sqrt(fma(t_1, t_0, pow(sin(((phi1 - phi2) * 0.5)), 2.0))), sqrt((pow(cos(((phi1 - phi2) / -2.0)), 2.0) - (t_1 * t_0))));
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi2) * cos(phi1)) t_1 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 return Float64(Float64(2.0 * R) * atan(sqrt(fma(t_1, t_0, (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(Float64(phi1 - phi2) / -2.0)) ^ 2.0) - Float64(t_1 * t_0))))) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(N[(2.0 * R), $MachinePrecision] * N[ArcTan[N[Sqrt[N[(t$95$1 * t$95$0 + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(N[(phi1 - phi2), $MachinePrecision] / -2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(t$95$1 * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision]), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_2 \cdot \cos \phi_1\\
t_1 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
\left(2 \cdot R\right) \cdot \tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_1, t\_0, {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\right)}}{\sqrt{{\cos \left(\frac{\phi_1 - \phi_2}{-2}\right)}^{2} - t\_1 \cdot t\_0}}
\end{array}
\end{array}
Initial program 66.4%
Applied rewrites66.5%
Final simplification66.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(fma
(* (cos phi2) (cos phi1))
(pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)
(pow (sin (* (- phi1 phi2) 0.5)) 2.0))))
(* (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(phi2) * cos(phi1)), 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(phi2) * cos(phi1)), (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[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]}, N[(N[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_2 \cdot \cos \phi_1, {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}, {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\right)\\
\tan^{-1}_* \frac{\sqrt{t\_0}}{\sqrt{1 - t\_0}} \cdot \left(2 \cdot R\right)
\end{array}
\end{array}
Initial program 66.4%
Taylor expanded in lambda1 around 0
Applied rewrites66.4%
Final simplification66.4%
(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))
(t_2 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_3
(*
(*
(atan2
(sqrt (fma t_2 (cos phi1) (pow (sin (* phi1 0.5)) 2.0)))
(sqrt (- (pow (cos (* -0.5 phi1)) 2.0) (* t_2 (cos phi1)))))
2.0)
R)))
(if (<= phi1 -1.05e-6)
t_3
(if (<= phi1 1.2e-9)
(*
(*
(atan2
(sqrt (+ (* t_2 (cos phi2)) t_1))
(sqrt (- 1.0 (+ t_1 (* (* (* (cos phi2) (cos phi1)) t_0) t_0)))))
2.0)
R)
t_3))))
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);
double t_2 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_3 = (atan2(sqrt(fma(t_2, cos(phi1), pow(sin((phi1 * 0.5)), 2.0))), sqrt((pow(cos((-0.5 * phi1)), 2.0) - (t_2 * cos(phi1))))) * 2.0) * R;
double tmp;
if (phi1 <= -1.05e-6) {
tmp = t_3;
} else if (phi1 <= 1.2e-9) {
tmp = (atan2(sqrt(((t_2 * cos(phi2)) + t_1)), sqrt((1.0 - (t_1 + (((cos(phi2) * cos(phi1)) * t_0) * t_0))))) * 2.0) * R;
} else {
tmp = t_3;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 t_2 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_3 = Float64(Float64(atan(sqrt(fma(t_2, cos(phi1), (sin(Float64(phi1 * 0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(-0.5 * phi1)) ^ 2.0) - Float64(t_2 * cos(phi1))))) * 2.0) * R) tmp = 0.0 if (phi1 <= -1.05e-6) tmp = t_3; elseif (phi1 <= 1.2e-9) tmp = Float64(Float64(atan(sqrt(Float64(Float64(t_2 * cos(phi2)) + t_1)), sqrt(Float64(1.0 - Float64(t_1 + Float64(Float64(Float64(cos(phi2) * cos(phi1)) * t_0) * t_0))))) * 2.0) * R); else tmp = t_3; 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[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$3 = N[(N[(N[ArcTan[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] / 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]}, If[LessEqual[phi1, -1.05e-6], t$95$3, If[LessEqual[phi1, 1.2e-9], N[(N[(N[ArcTan[N[Sqrt[N[(N[(t$95$2 * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$1 + N[(N[(N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], t$95$3]]]]]]
\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}\\
t_2 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_3 := \left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_2, \cos \phi_1, {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}{\sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - t\_2 \cdot \cos \phi_1}} \cdot 2\right) \cdot R\\
\mathbf{if}\;\phi_1 \leq -1.05 \cdot 10^{-6}:\\
\;\;\;\;t\_3\\
\mathbf{elif}\;\phi_1 \leq 1.2 \cdot 10^{-9}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{t\_2 \cdot \cos \phi_2 + t\_1}}{\sqrt{1 - \left(t\_1 + \left(\left(\cos \phi_2 \cdot \cos \phi_1\right) \cdot t\_0\right) \cdot t\_0\right)}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;t\_3\\
\end{array}
\end{array}
if phi1 < -1.0499999999999999e-6 or 1.2e-9 < phi1 Initial program 46.8%
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 rewrites47.6%
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-*.f6448.9
Applied rewrites48.9%
if -1.0499999999999999e-6 < phi1 < 1.2e-9Initial program 82.1%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-*.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f6482.2
Applied rewrites82.2%
Final simplification67.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(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 -1.05e-6)
t_2
(if (<= phi1 1.2e-9)
(*
(*
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi2) (cos phi1)) t_0) t_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 <= -1.05e-6) {
tmp = t_2;
} else if (phi1 <= 1.2e-9) {
tmp = (atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi2) * cos(phi1)) * t_0) * t_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 <= -1.05e-6) tmp = t_2; elseif (phi1 <= 1.2e-9) tmp = Float64(Float64(atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi2) * cos(phi1)) * t_0) * t_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, -1.05e-6], t$95$2, If[LessEqual[phi1, 1.2e-9], N[(N[(N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$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 -1.05 \cdot 10^{-6}:\\
\;\;\;\;t\_2\\
\mathbf{elif}\;\phi_1 \leq 1.2 \cdot 10^{-9}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + \left(\left(\cos \phi_2 \cdot \cos \phi_1\right) \cdot t\_0\right) \cdot t\_0}}{\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 < -1.0499999999999999e-6 or 1.2e-9 < phi1 Initial program 46.8%
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 rewrites47.6%
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-*.f6448.9
Applied rewrites48.9%
if -1.0499999999999999e-6 < phi1 < 1.2e-9Initial program 82.1%
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
*-commutativeN/A
cos-negN/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites82.2%
Final simplification67.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_1
(*
(*
(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 (<= phi1 -1.05e-6)
t_1
(if (<= phi1 1.2e-9)
(*
(*
(atan2
(sqrt (+ (* t_0 (cos phi2)) (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt
(-
(- 1.0 (* t_0 (* (cos phi2) (cos phi1))))
(pow (sin (* (- phi1 phi2) 0.5)) 2.0))))
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(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 (phi1 <= -1.05e-6) {
tmp = t_1;
} else if (phi1 <= 1.2e-9) {
tmp = (atan2(sqrt(((t_0 * cos(phi2)) + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt(((1.0 - (t_0 * (cos(phi2) * cos(phi1)))) - pow(sin(((phi1 - phi2) * 0.5)), 2.0)))) * 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(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 (phi1 <= -1.05e-6) tmp = t_1; elseif (phi1 <= 1.2e-9) tmp = Float64(Float64(atan(sqrt(Float64(Float64(t_0 * cos(phi2)) + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64(Float64(1.0 - Float64(t_0 * Float64(cos(phi2) * cos(phi1)))) - (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0)))) * 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[(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[phi1, -1.05e-6], t$95$1, If[LessEqual[phi1, 1.2e-9], N[(N[(N[ArcTan[N[Sqrt[N[(N[(t$95$0 * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[(t$95$0 * N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]), $MachinePrecision] - N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 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(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}\;\phi_1 \leq -1.05 \cdot 10^{-6}:\\
\;\;\;\;t\_1\\
\mathbf{elif}\;\phi_1 \leq 1.2 \cdot 10^{-9}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{t\_0 \cdot \cos \phi_2 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{\left(1 - t\_0 \cdot \left(\cos \phi_2 \cdot \cos \phi_1\right)\right) - {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;t\_1\\
\end{array}
\end{array}
if phi1 < -1.0499999999999999e-6 or 1.2e-9 < phi1 Initial program 46.8%
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 rewrites47.6%
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-*.f6448.9
Applied rewrites48.9%
if -1.0499999999999999e-6 < phi1 < 1.2e-9Initial program 82.1%
lift--.f64N/A
lift-+.f64N/A
+-commutativeN/A
associate--r+N/A
lower--.f64N/A
Applied rewrites82.1%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-*.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f6482.1
Applied rewrites82.1%
Final simplification67.3%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi2) (cos phi1)))
(t_1 (pow (sin (* -0.5 phi2)) 2.0))
(t_2 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_3 (pow (sin (* (- phi1 phi2) 0.5)) 2.0))
(t_4 (sqrt (- (- 1.0 (* t_2 t_0)) t_3))))
(if (<= phi2 -1e-5)
(* (* (atan2 (sqrt (+ t_1 (* t_2 (cos phi2)))) t_4) 2.0) R)
(if (<= phi2 1.95e-6)
(*
(atan2
(sqrt (fma t_2 t_0 t_3))
(sqrt (fma (- (cos phi1)) t_2 (pow (cos (* -0.5 phi1)) 2.0))))
(* 2.0 R))
(* (* (atan2 (sqrt (fma t_2 (cos phi2) t_1)) t_4) 2.0) R)))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos(phi2) * cos(phi1);
double t_1 = pow(sin((-0.5 * phi2)), 2.0);
double t_2 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_3 = pow(sin(((phi1 - phi2) * 0.5)), 2.0);
double t_4 = sqrt(((1.0 - (t_2 * t_0)) - t_3));
double tmp;
if (phi2 <= -1e-5) {
tmp = (atan2(sqrt((t_1 + (t_2 * cos(phi2)))), t_4) * 2.0) * R;
} else if (phi2 <= 1.95e-6) {
tmp = atan2(sqrt(fma(t_2, t_0, t_3)), sqrt(fma(-cos(phi1), t_2, pow(cos((-0.5 * phi1)), 2.0)))) * (2.0 * R);
} else {
tmp = (atan2(sqrt(fma(t_2, cos(phi2), t_1)), t_4) * 2.0) * R;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64(cos(phi2) * cos(phi1)) t_1 = sin(Float64(-0.5 * phi2)) ^ 2.0 t_2 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_3 = sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0 t_4 = sqrt(Float64(Float64(1.0 - Float64(t_2 * t_0)) - t_3)) tmp = 0.0 if (phi2 <= -1e-5) tmp = Float64(Float64(atan(sqrt(Float64(t_1 + Float64(t_2 * cos(phi2)))), t_4) * 2.0) * R); elseif (phi2 <= 1.95e-6) tmp = Float64(atan(sqrt(fma(t_2, t_0, t_3)), sqrt(fma(Float64(-cos(phi1)), t_2, (cos(Float64(-0.5 * phi1)) ^ 2.0)))) * Float64(2.0 * R)); else tmp = Float64(Float64(atan(sqrt(fma(t_2, cos(phi2), t_1)), t_4) * 2.0) * R); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$3 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$4 = N[Sqrt[N[(N[(1.0 - N[(t$95$2 * t$95$0), $MachinePrecision]), $MachinePrecision] - t$95$3), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi2, -1e-5], N[(N[(N[ArcTan[N[Sqrt[N[(t$95$1 + N[(t$95$2 * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / t$95$4], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], If[LessEqual[phi2, 1.95e-6], N[(N[ArcTan[N[Sqrt[N[(t$95$2 * t$95$0 + t$95$3), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[((-N[Cos[phi1], $MachinePrecision]) * t$95$2 + N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(2.0 * R), $MachinePrecision]), $MachinePrecision], N[(N[(N[ArcTan[N[Sqrt[N[(t$95$2 * N[Cos[phi2], $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / t$95$4], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \cos \phi_2 \cdot \cos \phi_1\\
t_1 := {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\\
t_2 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_3 := {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\\
t_4 := \sqrt{\left(1 - t\_2 \cdot t\_0\right) - t\_3}\\
\mathbf{if}\;\phi_2 \leq -1 \cdot 10^{-5}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{t\_1 + t\_2 \cdot \cos \phi_2}}{t\_4} \cdot 2\right) \cdot R\\
\mathbf{elif}\;\phi_2 \leq 1.95 \cdot 10^{-6}:\\
\;\;\;\;\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_2, t\_0, t\_3\right)}}{\sqrt{\mathsf{fma}\left(-\cos \phi_1, t\_2, {\cos \left(-0.5 \cdot \phi_1\right)}^{2}\right)}} \cdot \left(2 \cdot R\right)\\
\mathbf{else}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_2, \cos \phi_2, t\_1\right)}}{t\_4} \cdot 2\right) \cdot R\\
\end{array}
\end{array}
if phi2 < -1.00000000000000008e-5Initial program 53.8%
lift--.f64N/A
lift-+.f64N/A
+-commutativeN/A
associate--r+N/A
lower--.f64N/A
Applied rewrites53.8%
Taylor expanded in phi1 around 0
metadata-evalN/A
associate-*r*N/A
lower-sin.f64N/A
associate-*r*N/A
metadata-evalN/A
lower-*.f6453.0
Applied rewrites53.0%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-*.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f6455.0
Applied rewrites55.0%
if -1.00000000000000008e-5 < phi2 < 1.95e-6Initial program 80.7%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
*-commutativeN/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites80.8%
Applied rewrites80.8%
if 1.95e-6 < phi2 Initial program 50.1%
lift--.f64N/A
lift-+.f64N/A
+-commutativeN/A
associate--r+N/A
lower--.f64N/A
Applied rewrites50.1%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-fma.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
Applied rewrites51.8%
Final simplification67.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (cos phi2) (cos phi1)))
(t_1 (pow (sin (* (- phi1 phi2) 0.5)) 2.0))
(t_2 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_3
(*
(*
(atan2
(sqrt (fma t_2 (cos phi2) (pow (sin (* -0.5 phi2)) 2.0)))
(sqrt (- (- 1.0 (* t_2 t_0)) t_1)))
2.0)
R)))
(if (<= phi2 -1e-5)
t_3
(if (<= phi2 1.95e-6)
(*
(atan2
(sqrt (fma t_2 t_0 t_1))
(sqrt (fma (- (cos phi1)) t_2 (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 = cos(phi2) * cos(phi1);
double t_1 = pow(sin(((phi1 - phi2) * 0.5)), 2.0);
double t_2 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_3 = (atan2(sqrt(fma(t_2, cos(phi2), pow(sin((-0.5 * phi2)), 2.0))), sqrt(((1.0 - (t_2 * t_0)) - t_1))) * 2.0) * R;
double tmp;
if (phi2 <= -1e-5) {
tmp = t_3;
} else if (phi2 <= 1.95e-6) {
tmp = atan2(sqrt(fma(t_2, t_0, t_1)), sqrt(fma(-cos(phi1), t_2, 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 = Float64(cos(phi2) * cos(phi1)) t_1 = sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0 t_2 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_3 = Float64(Float64(atan(sqrt(fma(t_2, cos(phi2), (sin(Float64(-0.5 * phi2)) ^ 2.0))), sqrt(Float64(Float64(1.0 - Float64(t_2 * t_0)) - t_1))) * 2.0) * R) tmp = 0.0 if (phi2 <= -1e-5) tmp = t_3; elseif (phi2 <= 1.95e-6) tmp = Float64(atan(sqrt(fma(t_2, t_0, t_1)), sqrt(fma(Float64(-cos(phi1)), t_2, (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[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$3 = N[(N[(N[ArcTan[N[Sqrt[N[(t$95$2 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[(1.0 - N[(t$95$2 * t$95$0), $MachinePrecision]), $MachinePrecision] - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]}, If[LessEqual[phi2, -1e-5], t$95$3, If[LessEqual[phi2, 1.95e-6], N[(N[ArcTan[N[Sqrt[N[(t$95$2 * t$95$0 + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[((-N[Cos[phi1], $MachinePrecision]) * t$95$2 + 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 := \cos \phi_2 \cdot \cos \phi_1\\
t_1 := {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\\
t_2 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_3 := \left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_2, \cos \phi_2, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)}}{\sqrt{\left(1 - t\_2 \cdot t\_0\right) - t\_1}} \cdot 2\right) \cdot R\\
\mathbf{if}\;\phi_2 \leq -1 \cdot 10^{-5}:\\
\;\;\;\;t\_3\\
\mathbf{elif}\;\phi_2 \leq 1.95 \cdot 10^{-6}:\\
\;\;\;\;\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_2, t\_0, t\_1\right)}}{\sqrt{\mathsf{fma}\left(-\cos \phi_1, t\_2, {\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 < -1.00000000000000008e-5 or 1.95e-6 < phi2 Initial program 52.1%
lift--.f64N/A
lift-+.f64N/A
+-commutativeN/A
associate--r+N/A
lower--.f64N/A
Applied rewrites52.1%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-fma.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
Applied rewrites53.5%
if -1.00000000000000008e-5 < phi2 < 1.95e-6Initial program 80.7%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
*-commutativeN/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites80.8%
Applied rewrites80.8%
Final simplification67.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0) (cos phi1))))
(*
(*
(atan2
(sqrt (+ t_0 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0)))
(sqrt (- (pow (cos (* -0.5 phi1)) 2.0) t_0)))
2.0)
R)))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0) * cos(phi1);
return (atan2(sqrt((t_0 + pow(sin(((phi1 - phi2) / 2.0)), 2.0))), sqrt((pow(cos((-0.5 * phi1)), 2.0) - t_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) * 0.5d0)) ** 2.0d0) * cos(phi1)
code = (atan2(sqrt((t_0 + (sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0))), sqrt(((cos(((-0.5d0) * phi1)) ** 2.0d0) - t_0))) * 2.0d0) * r
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0) * Math.cos(phi1);
return (Math.atan2(Math.sqrt((t_0 + Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0))), Math.sqrt((Math.pow(Math.cos((-0.5 * phi1)), 2.0) - t_0))) * 2.0) * R;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0) * math.cos(phi1) return (math.atan2(math.sqrt((t_0 + math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0))), math.sqrt((math.pow(math.cos((-0.5 * phi1)), 2.0) - t_0))) * 2.0) * R
function code(R, lambda1, lambda2, phi1, phi2) t_0 = Float64((sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0) * cos(phi1)) return Float64(Float64(atan(sqrt(Float64(t_0 + (sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(Float64((cos(Float64(-0.5 * phi1)) ^ 2.0) - t_0))) * 2.0) * R) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = (sin(((lambda1 - lambda2) * 0.5)) ^ 2.0) * cos(phi1); tmp = (atan2(sqrt((t_0 + (sin(((phi1 - phi2) / 2.0)) ^ 2.0))), sqrt(((cos((-0.5 * phi1)) ^ 2.0) - t_0))) * 2.0) * R; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[(N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]}, N[(N[(N[ArcTan[N[Sqrt[N[(t$95$0 + 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[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2} \cdot \cos \phi_1\\
\left(\tan^{-1}_* \frac{\sqrt{t\_0 + {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}}}{\sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - t\_0}} \cdot 2\right) \cdot R
\end{array}
\end{array}
Initial program 66.4%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
*-commutativeN/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites50.7%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-*.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f6450.8
Applied rewrites50.8%
Final simplification50.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (cos (* -0.5 phi1)) 2.0))
(t_1 (pow (sin (* phi1 0.5)) 2.0))
(t_2 (pow (sin (* lambda2 -0.5)) 2.0))
(t_3 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_4 (sqrt (fma t_3 (cos phi1) t_1))))
(if (<= lambda2 -4e-7)
(* (* (atan2 t_4 (sqrt (fma (- (cos phi1)) t_2 t_0))) 2.0) R)
(if (<= lambda2 0.0006)
(*
(*
(atan2
t_4
(sqrt (- t_0 (* (pow (sin (* lambda1 0.5)) 2.0) (cos phi1)))))
2.0)
R)
(*
(*
(atan2
(sqrt (fma t_2 (cos phi1) t_1))
(sqrt (- t_0 (* t_3 (cos phi1)))))
2.0)
R)))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(cos((-0.5 * phi1)), 2.0);
double t_1 = pow(sin((phi1 * 0.5)), 2.0);
double t_2 = pow(sin((lambda2 * -0.5)), 2.0);
double t_3 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_4 = sqrt(fma(t_3, cos(phi1), t_1));
double tmp;
if (lambda2 <= -4e-7) {
tmp = (atan2(t_4, sqrt(fma(-cos(phi1), t_2, t_0))) * 2.0) * R;
} else if (lambda2 <= 0.0006) {
tmp = (atan2(t_4, sqrt((t_0 - (pow(sin((lambda1 * 0.5)), 2.0) * cos(phi1))))) * 2.0) * R;
} else {
tmp = (atan2(sqrt(fma(t_2, cos(phi1), t_1)), sqrt((t_0 - (t_3 * cos(phi1))))) * 2.0) * R;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(-0.5 * phi1)) ^ 2.0 t_1 = sin(Float64(phi1 * 0.5)) ^ 2.0 t_2 = sin(Float64(lambda2 * -0.5)) ^ 2.0 t_3 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_4 = sqrt(fma(t_3, cos(phi1), t_1)) tmp = 0.0 if (lambda2 <= -4e-7) tmp = Float64(Float64(atan(t_4, sqrt(fma(Float64(-cos(phi1)), t_2, t_0))) * 2.0) * R); elseif (lambda2 <= 0.0006) tmp = Float64(Float64(atan(t_4, sqrt(Float64(t_0 - Float64((sin(Float64(lambda1 * 0.5)) ^ 2.0) * cos(phi1))))) * 2.0) * R); else tmp = Float64(Float64(atan(sqrt(fma(t_2, cos(phi1), t_1)), sqrt(Float64(t_0 - Float64(t_3 * cos(phi1))))) * 2.0) * R); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$3 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$4 = N[Sqrt[N[(t$95$3 * N[Cos[phi1], $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[lambda2, -4e-7], N[(N[(N[ArcTan[t$95$4 / N[Sqrt[N[((-N[Cos[phi1], $MachinePrecision]) * t$95$2 + t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], If[LessEqual[lambda2, 0.0006], N[(N[(N[ArcTan[t$95$4 / N[Sqrt[N[(t$95$0 - N[(N[Power[N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], N[(N[(N[ArcTan[N[Sqrt[N[(t$95$2 * N[Cos[phi1], $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(t$95$0 - N[(t$95$3 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\cos \left(-0.5 \cdot \phi_1\right)}^{2}\\
t_1 := {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\\
t_2 := {\sin \left(\lambda_2 \cdot -0.5\right)}^{2}\\
t_3 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_4 := \sqrt{\mathsf{fma}\left(t\_3, \cos \phi_1, t\_1\right)}\\
\mathbf{if}\;\lambda_2 \leq -4 \cdot 10^{-7}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{t\_4}{\sqrt{\mathsf{fma}\left(-\cos \phi_1, t\_2, t\_0\right)}} \cdot 2\right) \cdot R\\
\mathbf{elif}\;\lambda_2 \leq 0.0006:\\
\;\;\;\;\left(\tan^{-1}_* \frac{t\_4}{\sqrt{t\_0 - {\sin \left(\lambda_1 \cdot 0.5\right)}^{2} \cdot \cos \phi_1}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_2, \cos \phi_1, t\_1\right)}}{\sqrt{t\_0 - t\_3 \cdot \cos \phi_1}} \cdot 2\right) \cdot R\\
\end{array}
\end{array}
if lambda2 < -3.9999999999999998e-7Initial program 50.5%
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 rewrites42.7%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6442.9
Applied rewrites42.9%
Taylor expanded in lambda1 around 0
Applied rewrites42.8%
if -3.9999999999999998e-7 < lambda2 < 5.99999999999999947e-4Initial program 82.5%
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 rewrites59.7%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6455.1
Applied rewrites55.1%
Taylor expanded in lambda2 around 0
Applied rewrites55.1%
if 5.99999999999999947e-4 < lambda2 Initial program 48.9%
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 rewrites40.1%
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-*.f6440.9
Applied rewrites40.9%
Taylor expanded in lambda1 around 0
Applied rewrites41.1%
Final simplification48.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* phi1 0.5)) 2.0))
(t_1 (pow (cos (* -0.5 phi1)) 2.0))
(t_2 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_3
(*
(*
(atan2
(sqrt (fma (pow (sin (* lambda1 0.5)) 2.0) (cos phi1) t_0))
(sqrt (- t_1 (* t_2 (cos phi1)))))
2.0)
R)))
(if (<= lambda1 -5.3e-21)
t_3
(if (<= lambda1 4.2e-5)
(*
(*
(atan2
(sqrt (fma t_2 (cos phi1) t_0))
(sqrt (fma (- (cos phi1)) (pow (sin (* lambda2 -0.5)) 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((phi1 * 0.5)), 2.0);
double t_1 = pow(cos((-0.5 * phi1)), 2.0);
double t_2 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_3 = (atan2(sqrt(fma(pow(sin((lambda1 * 0.5)), 2.0), cos(phi1), t_0)), sqrt((t_1 - (t_2 * cos(phi1))))) * 2.0) * R;
double tmp;
if (lambda1 <= -5.3e-21) {
tmp = t_3;
} else if (lambda1 <= 4.2e-5) {
tmp = (atan2(sqrt(fma(t_2, cos(phi1), t_0)), sqrt(fma(-cos(phi1), pow(sin((lambda2 * -0.5)), 2.0), t_1))) * 2.0) * R;
} else {
tmp = t_3;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi1 * 0.5)) ^ 2.0 t_1 = cos(Float64(-0.5 * phi1)) ^ 2.0 t_2 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_3 = Float64(Float64(atan(sqrt(fma((sin(Float64(lambda1 * 0.5)) ^ 2.0), cos(phi1), t_0)), sqrt(Float64(t_1 - Float64(t_2 * cos(phi1))))) * 2.0) * R) tmp = 0.0 if (lambda1 <= -5.3e-21) tmp = t_3; elseif (lambda1 <= 4.2e-5) tmp = Float64(Float64(atan(sqrt(fma(t_2, cos(phi1), t_0)), sqrt(fma(Float64(-cos(phi1)), (sin(Float64(lambda2 * -0.5)) ^ 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[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$3 = N[(N[(N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision] + t$95$0), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(t$95$1 - N[(t$95$2 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]}, If[LessEqual[lambda1, -5.3e-21], t$95$3, If[LessEqual[lambda1, 4.2e-5], N[(N[(N[ArcTan[N[Sqrt[N[(t$95$2 * N[Cos[phi1], $MachinePrecision] + t$95$0), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[((-N[Cos[phi1], $MachinePrecision]) * N[Power[N[Sin[N[(lambda2 * -0.5), $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(\phi_1 \cdot 0.5\right)}^{2}\\
t_1 := {\cos \left(-0.5 \cdot \phi_1\right)}^{2}\\
t_2 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_3 := \left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left({\sin \left(\lambda_1 \cdot 0.5\right)}^{2}, \cos \phi_1, t\_0\right)}}{\sqrt{t\_1 - t\_2 \cdot \cos \phi_1}} \cdot 2\right) \cdot R\\
\mathbf{if}\;\lambda_1 \leq -5.3 \cdot 10^{-21}:\\
\;\;\;\;t\_3\\
\mathbf{elif}\;\lambda_1 \leq 4.2 \cdot 10^{-5}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_2, \cos \phi_1, t\_0\right)}}{\sqrt{\mathsf{fma}\left(-\cos \phi_1, {\sin \left(\lambda_2 \cdot -0.5\right)}^{2}, t\_1\right)}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;t\_3\\
\end{array}
\end{array}
if lambda1 < -5.2999999999999999e-21 or 4.19999999999999977e-5 < lambda1 Initial program 50.5%
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 rewrites38.5%
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-*.f6439.0
Applied rewrites39.0%
Taylor expanded in lambda2 around 0
Applied rewrites38.9%
if -5.2999999999999999e-21 < lambda1 < 4.19999999999999977e-5Initial 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 rewrites62.4%
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-*.f6457.8
Applied rewrites57.8%
Taylor expanded in lambda1 around 0
Applied rewrites57.8%
Final simplification48.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_1
(*
(*
(atan2
(sqrt
(fma
(pow (sin (* lambda1 0.5)) 2.0)
(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 (<= phi1 -1.8e-24)
t_1
(if (<= phi1 1750000000000.0)
(*
(*
(atan2
(sqrt (fma t_0 (cos phi2) (pow (sin (* -0.5 phi2)) 2.0)))
(sqrt (- 1.0 t_0)))
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(pow(sin((lambda1 * 0.5)), 2.0), 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 (phi1 <= -1.8e-24) {
tmp = t_1;
} else if (phi1 <= 1750000000000.0) {
tmp = (atan2(sqrt(fma(t_0, cos(phi2), pow(sin((-0.5 * phi2)), 2.0))), sqrt((1.0 - t_0))) * 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((sin(Float64(lambda1 * 0.5)) ^ 2.0), 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 (phi1 <= -1.8e-24) tmp = t_1; elseif (phi1 <= 1750000000000.0) tmp = Float64(Float64(atan(sqrt(fma(t_0, cos(phi2), (sin(Float64(-0.5 * phi2)) ^ 2.0))), sqrt(Float64(1.0 - t_0))) * 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[Power[N[Sin[N[(lambda1 * 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] / 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[phi1, -1.8e-24], t$95$1, If[LessEqual[phi1, 1750000000000.0], N[(N[(N[ArcTan[N[Sqrt[N[(t$95$0 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$0), $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({\sin \left(\lambda_1 \cdot 0.5\right)}^{2}, \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}\;\phi_1 \leq -1.8 \cdot 10^{-24}:\\
\;\;\;\;t\_1\\
\mathbf{elif}\;\phi_1 \leq 1750000000000:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \cos \phi_2, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)}}{\sqrt{1 - t\_0}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;t\_1\\
\end{array}
\end{array}
if phi1 < -1.8e-24 or 1.75e12 < phi1 Initial program 47.2%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
*-commutativeN/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites47.7%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6448.9
Applied rewrites48.9%
Taylor expanded in lambda2 around 0
Applied rewrites44.1%
if -1.8e-24 < phi1 < 1.75e12Initial program 82.6%
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 rewrites53.3%
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-*.f6448.4
Applied rewrites48.4%
Taylor expanded in phi1 around 0
Applied rewrites48.4%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-fma.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6452.1
Applied rewrites52.1%
Final simplification48.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
(*
(*
(atan2
(sqrt (fma t_0 (cos phi1) (pow (sin (* phi1 0.5)) 2.0)))
(sqrt (- (pow (cos (* -0.5 phi1)) 2.0) (* t_0 (cos phi1)))))
2.0)
R)))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
return (atan2(sqrt(fma(t_0, cos(phi1), pow(sin((phi1 * 0.5)), 2.0))), sqrt((pow(cos((-0.5 * phi1)), 2.0) - (t_0 * cos(phi1))))) * 2.0) * R;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 return Float64(Float64(atan(sqrt(fma(t_0, cos(phi1), (sin(Float64(phi1 * 0.5)) ^ 2.0))), sqrt(Float64((cos(Float64(-0.5 * phi1)) ^ 2.0) - Float64(t_0 * cos(phi1))))) * 2.0) * R) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(N[(N[ArcTan[N[Sqrt[N[(t$95$0 * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(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]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \cos \phi_1, {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}{\sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - t\_0 \cdot \cos \phi_1}} \cdot 2\right) \cdot R
\end{array}
\end{array}
Initial program 66.4%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
*-commutativeN/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites50.7%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6448.6
Applied rewrites48.6%
Final simplification48.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0
(sqrt
(fma
(pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)
(cos phi1)
(pow (sin (* phi1 0.5)) 2.0))))
(t_1
(*
(* (atan2 t_0 (sqrt (- 1.0 (pow (sin (* lambda1 0.5)) 2.0)))) 2.0)
R)))
(if (<= lambda1 -12000000000000.0)
t_1
(if (<= lambda1 2.25e-5)
(*
(* (atan2 t_0 (sqrt (- 1.0 (pow (sin (* lambda2 -0.5)) 2.0)))) 2.0)
R)
t_1))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sqrt(fma(pow(sin(((lambda1 - lambda2) * 0.5)), 2.0), cos(phi1), pow(sin((phi1 * 0.5)), 2.0)));
double t_1 = (atan2(t_0, sqrt((1.0 - pow(sin((lambda1 * 0.5)), 2.0)))) * 2.0) * R;
double tmp;
if (lambda1 <= -12000000000000.0) {
tmp = t_1;
} else if (lambda1 <= 2.25e-5) {
tmp = (atan2(t_0, sqrt((1.0 - pow(sin((lambda2 * -0.5)), 2.0)))) * 2.0) * R;
} else {
tmp = t_1;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sqrt(fma((sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0), cos(phi1), (sin(Float64(phi1 * 0.5)) ^ 2.0))) t_1 = Float64(Float64(atan(t_0, sqrt(Float64(1.0 - (sin(Float64(lambda1 * 0.5)) ^ 2.0)))) * 2.0) * R) tmp = 0.0 if (lambda1 <= -12000000000000.0) tmp = t_1; elseif (lambda1 <= 2.25e-5) tmp = Float64(Float64(atan(t_0, sqrt(Float64(1.0 - (sin(Float64(lambda2 * -0.5)) ^ 2.0)))) * 2.0) * R); else tmp = t_1; end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sqrt[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]}, Block[{t$95$1 = N[(N[(N[ArcTan[t$95$0 / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]}, If[LessEqual[lambda1, -12000000000000.0], t$95$1, If[LessEqual[lambda1, 2.25e-5], N[(N[(N[ArcTan[t$95$0 / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], t$95$1]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sqrt{\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)}\\
t_1 := \left(\tan^{-1}_* \frac{t\_0}{\sqrt{1 - {\sin \left(\lambda_1 \cdot 0.5\right)}^{2}}} \cdot 2\right) \cdot R\\
\mathbf{if}\;\lambda_1 \leq -12000000000000:\\
\;\;\;\;t\_1\\
\mathbf{elif}\;\lambda_1 \leq 2.25 \cdot 10^{-5}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{t\_0}{\sqrt{1 - {\sin \left(\lambda_2 \cdot -0.5\right)}^{2}}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;t\_1\\
\end{array}
\end{array}
if lambda1 < -1.2e13 or 2.25000000000000014e-5 < lambda1 Initial program 50.2%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
*-commutativeN/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites38.0%
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-*.f6438.5
Applied rewrites38.5%
Taylor expanded in phi1 around 0
Applied rewrites31.5%
Taylor expanded in lambda2 around 0
Applied rewrites31.5%
if -1.2e13 < lambda1 < 2.25000000000000014e-5Initial program 81.1%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
*-commutativeN/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites62.3%
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-*.f6457.8
Applied rewrites57.8%
Taylor expanded in phi1 around 0
Applied rewrites41.4%
Taylor expanded in lambda1 around 0
Applied rewrites41.4%
Final simplification36.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* phi1 0.5)) 2.0))
(t_1 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_2
(*
(*
(atan2
(sqrt (fma (pow (sin (* lambda2 -0.5)) 2.0) (cos phi1) t_0))
(sqrt (- 1.0 t_1)))
2.0)
R)))
(if (<= lambda2 -2.7e-5)
t_2
(if (<= lambda2 0.0059)
(*
(*
(atan2
(sqrt (fma t_1 (cos phi1) t_0))
(sqrt (- 1.0 (pow (sin (* lambda1 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((phi1 * 0.5)), 2.0);
double t_1 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_2 = (atan2(sqrt(fma(pow(sin((lambda2 * -0.5)), 2.0), cos(phi1), t_0)), sqrt((1.0 - t_1))) * 2.0) * R;
double tmp;
if (lambda2 <= -2.7e-5) {
tmp = t_2;
} else if (lambda2 <= 0.0059) {
tmp = (atan2(sqrt(fma(t_1, cos(phi1), t_0)), sqrt((1.0 - pow(sin((lambda1 * 0.5)), 2.0)))) * 2.0) * R;
} else {
tmp = t_2;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi1 * 0.5)) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_2 = Float64(Float64(atan(sqrt(fma((sin(Float64(lambda2 * -0.5)) ^ 2.0), cos(phi1), t_0)), sqrt(Float64(1.0 - t_1))) * 2.0) * R) tmp = 0.0 if (lambda2 <= -2.7e-5) tmp = t_2; elseif (lambda2 <= 0.0059) tmp = Float64(Float64(atan(sqrt(fma(t_1, cos(phi1), t_0)), sqrt(Float64(1.0 - (sin(Float64(lambda1 * 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[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$2 = N[(N[(N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision] + t$95$0), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]}, If[LessEqual[lambda2, -2.7e-5], t$95$2, If[LessEqual[lambda2, 0.0059], N[(N[(N[ArcTan[N[Sqrt[N[(t$95$1 * N[Cos[phi1], $MachinePrecision] + t$95$0), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(lambda1 * 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(\phi_1 \cdot 0.5\right)}^{2}\\
t_1 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_2 := \left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left({\sin \left(\lambda_2 \cdot -0.5\right)}^{2}, \cos \phi_1, t\_0\right)}}{\sqrt{1 - t\_1}} \cdot 2\right) \cdot R\\
\mathbf{if}\;\lambda_2 \leq -2.7 \cdot 10^{-5}:\\
\;\;\;\;t\_2\\
\mathbf{elif}\;\lambda_2 \leq 0.0059:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_1, \cos \phi_1, t\_0\right)}}{\sqrt{1 - {\sin \left(\lambda_1 \cdot 0.5\right)}^{2}}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;t\_2\\
\end{array}
\end{array}
if lambda2 < -2.6999999999999999e-5 or 0.00589999999999999986 < lambda2 Initial program 49.3%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
*-commutativeN/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites41.0%
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-*.f6441.5
Applied rewrites41.5%
Taylor expanded in phi1 around 0
Applied rewrites36.9%
Taylor expanded in lambda1 around 0
Applied rewrites36.6%
if -2.6999999999999999e-5 < lambda2 < 0.00589999999999999986Initial program 82.7%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
*-commutativeN/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites60.0%
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-*.f6455.5
Applied rewrites55.5%
Taylor expanded in phi1 around 0
Applied rewrites36.5%
Taylor expanded in lambda2 around 0
Applied rewrites36.5%
Final simplification36.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* phi1 0.5)) 2.0))
(t_1 (sqrt (- 1.0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))))
(t_2
(*
(*
(atan2
(sqrt (fma (pow (sin (* lambda1 0.5)) 2.0) (cos phi1) t_0))
t_1)
2.0)
R)))
(if (<= lambda1 -1.1e-32)
t_2
(if (<= lambda1 1.82e-6)
(*
(*
(atan2
(sqrt (fma (pow (sin (* lambda2 -0.5)) 2.0) (cos phi1) t_0))
t_1)
2.0)
R)
t_2))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((phi1 * 0.5)), 2.0);
double t_1 = sqrt((1.0 - pow(sin(((lambda1 - lambda2) * 0.5)), 2.0)));
double t_2 = (atan2(sqrt(fma(pow(sin((lambda1 * 0.5)), 2.0), cos(phi1), t_0)), t_1) * 2.0) * R;
double tmp;
if (lambda1 <= -1.1e-32) {
tmp = t_2;
} else if (lambda1 <= 1.82e-6) {
tmp = (atan2(sqrt(fma(pow(sin((lambda2 * -0.5)), 2.0), cos(phi1), t_0)), t_1) * 2.0) * R;
} else {
tmp = t_2;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(phi1 * 0.5)) ^ 2.0 t_1 = sqrt(Float64(1.0 - (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0))) t_2 = Float64(Float64(atan(sqrt(fma((sin(Float64(lambda1 * 0.5)) ^ 2.0), cos(phi1), t_0)), t_1) * 2.0) * R) tmp = 0.0 if (lambda1 <= -1.1e-32) tmp = t_2; elseif (lambda1 <= 1.82e-6) tmp = Float64(Float64(atan(sqrt(fma((sin(Float64(lambda2 * -0.5)) ^ 2.0), cos(phi1), t_0)), t_1) * 2.0) * R); else tmp = t_2; end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[(N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision] + t$95$0), $MachinePrecision]], $MachinePrecision] / t$95$1], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]}, If[LessEqual[lambda1, -1.1e-32], t$95$2, If[LessEqual[lambda1, 1.82e-6], N[(N[(N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(lambda2 * -0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision] + t$95$0), $MachinePrecision]], $MachinePrecision] / t$95$1], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], t$95$2]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\\
t_1 := \sqrt{1 - {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}}\\
t_2 := \left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left({\sin \left(\lambda_1 \cdot 0.5\right)}^{2}, \cos \phi_1, t\_0\right)}}{t\_1} \cdot 2\right) \cdot R\\
\mathbf{if}\;\lambda_1 \leq -1.1 \cdot 10^{-32}:\\
\;\;\;\;t\_2\\
\mathbf{elif}\;\lambda_1 \leq 1.82 \cdot 10^{-6}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left({\sin \left(\lambda_2 \cdot -0.5\right)}^{2}, \cos \phi_1, t\_0\right)}}{t\_1} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;t\_2\\
\end{array}
\end{array}
if lambda1 < -1.1e-32 or 1.8199999999999999e-6 < lambda1 Initial program 50.7%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
*-commutativeN/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites38.2%
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-*.f6438.6
Applied rewrites38.6%
Taylor expanded in phi1 around 0
Applied rewrites30.9%
Taylor expanded in lambda2 around 0
Applied rewrites30.8%
if -1.1e-32 < lambda1 < 1.8199999999999999e-6Initial program 81.8%
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 rewrites63.0%
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-*.f6458.5
Applied rewrites58.5%
Taylor expanded in phi1 around 0
Applied rewrites42.3%
Taylor expanded in lambda1 around 0
Applied rewrites39.5%
Final simplification35.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
(*
(*
(atan2
(sqrt (fma t_0 (cos phi2) (pow (sin (* -0.5 phi2)) 2.0)))
(sqrt (- 1.0 t_0)))
2.0)
R)))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
return (atan2(sqrt(fma(t_0, cos(phi2), pow(sin((-0.5 * phi2)), 2.0))), sqrt((1.0 - t_0))) * 2.0) * R;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 return Float64(Float64(atan(sqrt(fma(t_0, cos(phi2), (sin(Float64(-0.5 * phi2)) ^ 2.0))), sqrt(Float64(1.0 - t_0))) * 2.0) * R) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(N[(N[ArcTan[N[Sqrt[N[(t$95$0 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \cos \phi_2, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)}}{\sqrt{1 - t\_0}} \cdot 2\right) \cdot R
\end{array}
\end{array}
Initial program 66.4%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
*-commutativeN/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites50.7%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6448.6
Applied rewrites48.6%
Taylor expanded in phi1 around 0
Applied rewrites36.7%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-fma.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6436.9
Applied rewrites36.9%
Final simplification36.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
(*
(*
(atan2
(sqrt (fma t_0 (cos phi1) (pow (sin (* phi1 0.5)) 2.0)))
(sqrt (- 1.0 t_0)))
2.0)
R)))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
return (atan2(sqrt(fma(t_0, cos(phi1), pow(sin((phi1 * 0.5)), 2.0))), sqrt((1.0 - t_0))) * 2.0) * R;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 return Float64(Float64(atan(sqrt(fma(t_0, cos(phi1), (sin(Float64(phi1 * 0.5)) ^ 2.0))), sqrt(Float64(1.0 - t_0))) * 2.0) * R) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, N[(N[(N[ArcTan[N[Sqrt[N[(t$95$0 * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$0), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \cos \phi_1, {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}{\sqrt{1 - t\_0}} \cdot 2\right) \cdot R
\end{array}
\end{array}
Initial program 66.4%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
*-commutativeN/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites50.7%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6448.6
Applied rewrites48.6%
Taylor expanded in phi1 around 0
Applied rewrites36.7%
Final simplification36.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
(*
(atan2
(sqrt
(fma
(pow (sin (* lambda1 0.5)) 2.0)
(cos phi1)
(pow (sin (* phi1 0.5)) 2.0)))
(sqrt (- 1.0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))))
2.0)
R))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return (atan2(sqrt(fma(pow(sin((lambda1 * 0.5)), 2.0), cos(phi1), pow(sin((phi1 * 0.5)), 2.0))), sqrt((1.0 - pow(sin(((lambda1 - lambda2) * 0.5)), 2.0)))) * 2.0) * R;
}
function code(R, lambda1, lambda2, phi1, phi2) return Float64(Float64(atan(sqrt(fma((sin(Float64(lambda1 * 0.5)) ^ 2.0), cos(phi1), (sin(Float64(phi1 * 0.5)) ^ 2.0))), sqrt(Float64(1.0 - (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0)))) * 2.0) * R) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(N[(N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(lambda1 * 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] / N[Sqrt[N[(1.0 - N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]
\begin{array}{l}
\\
\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left({\sin \left(\lambda_1 \cdot 0.5\right)}^{2}, \cos \phi_1, {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}{\sqrt{1 - {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}}} \cdot 2\right) \cdot R
\end{array}
Initial program 66.4%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
*-commutativeN/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites50.7%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6448.6
Applied rewrites48.6%
Taylor expanded in phi1 around 0
Applied rewrites36.7%
Taylor expanded in lambda2 around 0
Applied rewrites24.5%
Final simplification24.5%
herbie shell --seed 2024268
(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))))))))))