
(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
(+
(pow
(-
(* (sin (* phi1 0.5)) (cos (* phi2 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0)
(* (* (* (cos phi2) (cos phi1)) t_0) t_0))))
(* (* (atan2 (sqrt t_1) (sqrt (- 1.0 t_1))) 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 * 0.5)) * cos((phi2 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0) + (((cos(phi2) * cos(phi1)) * t_0) * t_0);
return (atan2(sqrt(t_1), sqrt((1.0 - t_1))) * 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 * 0.5d0)) * cos((phi2 * 0.5d0))) - (cos((phi1 * 0.5d0)) * sin((phi2 * 0.5d0)))) ** 2.0d0) + (((cos(phi2) * cos(phi1)) * t_0) * t_0)
code = (atan2(sqrt(t_1), sqrt((1.0d0 - t_1))) * 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 * 0.5)) * Math.cos((phi2 * 0.5))) - (Math.cos((phi1 * 0.5)) * Math.sin((phi2 * 0.5)))), 2.0) + (((Math.cos(phi2) * Math.cos(phi1)) * t_0) * t_0);
return (Math.atan2(Math.sqrt(t_1), Math.sqrt((1.0 - t_1))) * 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 * 0.5)) * math.cos((phi2 * 0.5))) - (math.cos((phi1 * 0.5)) * math.sin((phi2 * 0.5)))), 2.0) + (((math.cos(phi2) * math.cos(phi1)) * t_0) * t_0) return (math.atan2(math.sqrt(t_1), math.sqrt((1.0 - t_1))) * 2.0) * R
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64((Float64(Float64(sin(Float64(phi1 * 0.5)) * cos(Float64(phi2 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0) + Float64(Float64(Float64(cos(phi2) * cos(phi1)) * t_0) * t_0)) return Float64(Float64(atan(sqrt(t_1), sqrt(Float64(1.0 - t_1))) * 2.0) * R) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = (((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))) ^ 2.0) + (((cos(phi2) * cos(phi1)) * t_0) * t_0); tmp = (atan2(sqrt(t_1), sqrt((1.0 - t_1))) * 2.0) * R; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[Power[N[(N[(N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]}, N[(N[(N[ArcTan[N[Sqrt[t$95$1], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := {\left(\sin \left(\phi_1 \cdot 0.5\right) \cdot \cos \left(\phi_2 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2} + \left(\left(\cos \phi_2 \cdot \cos \phi_1\right) \cdot t\_0\right) \cdot t\_0\\
\left(\tan^{-1}_* \frac{\sqrt{t\_1}}{\sqrt{1 - t\_1}} \cdot 2\right) \cdot R
\end{array}
\end{array}
Initial program 62.8%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f6463.8
Applied rewrites63.8%
lift-sin.f64N/A
lift-/.f64N/A
div-invN/A
metadata-evalN/A
*-commutativeN/A
lift--.f64N/A
sub-negN/A
distribute-rgt-inN/A
lift-*.f64N/A
cancel-sign-sub-invN/A
lift-*.f64N/A
sin-diffN/A
lift-sin.f64N/A
lift-cos.f64N/A
lift-*.f64N/A
lift-cos.f64N/A
lift-sin.f64N/A
lift-*.f64N/A
lift--.f6478.6
Applied rewrites78.6%
Final simplification78.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* phi1 0.5)))
(t_1 (sin (* (- lambda1 lambda2) 0.5)))
(t_2 (cos (* phi1 0.5)))
(t_3 (sin (/ (- lambda1 lambda2) 2.0))))
(*
(*
(atan2
(sqrt
(+
(* (* (* t_1 (cos phi2)) t_1) (cos phi1))
(pow (fma t_0 (cos (* -0.5 phi2)) (* (sin (* -0.5 phi2)) t_2)) 2.0)))
(sqrt
(-
1.0
(+
(pow (- (* t_0 (cos (* phi2 0.5))) (* t_2 (sin (* phi2 0.5)))) 2.0)
(* (* (* (cos phi2) (cos phi1)) t_3) t_3)))))
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 = sin(((lambda1 - lambda2) * 0.5));
double t_2 = cos((phi1 * 0.5));
double t_3 = sin(((lambda1 - lambda2) / 2.0));
return (atan2(sqrt(((((t_1 * cos(phi2)) * t_1) * cos(phi1)) + pow(fma(t_0, cos((-0.5 * phi2)), (sin((-0.5 * phi2)) * t_2)), 2.0))), sqrt((1.0 - (pow(((t_0 * cos((phi2 * 0.5))) - (t_2 * sin((phi2 * 0.5)))), 2.0) + (((cos(phi2) * cos(phi1)) * t_3) * t_3))))) * 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)) t_2 = cos(Float64(phi1 * 0.5)) t_3 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(Float64(atan(sqrt(Float64(Float64(Float64(Float64(t_1 * cos(phi2)) * t_1) * cos(phi1)) + (fma(t_0, cos(Float64(-0.5 * phi2)), Float64(sin(Float64(-0.5 * phi2)) * t_2)) ^ 2.0))), sqrt(Float64(1.0 - Float64((Float64(Float64(t_0 * cos(Float64(phi2 * 0.5))) - Float64(t_2 * sin(Float64(phi2 * 0.5)))) ^ 2.0) + Float64(Float64(Float64(cos(phi2) * cos(phi1)) * t_3) * t_3))))) * 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[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(N[(N[ArcTan[N[Sqrt[N[(N[(N[(N[(t$95$1 * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$1), $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] + N[Power[N[(t$95$0 * N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[(N[(t$95$0 * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(t$95$2 * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + N[(N[(N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] * t$95$3), $MachinePrecision] * t$95$3), $MachinePrecision]), $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)\\
t_2 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_3 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\left(\tan^{-1}_* \frac{\sqrt{\left(\left(t\_1 \cdot \cos \phi_2\right) \cdot t\_1\right) \cdot \cos \phi_1 + {\left(\mathsf{fma}\left(t\_0, \cos \left(-0.5 \cdot \phi_2\right), \sin \left(-0.5 \cdot \phi_2\right) \cdot t\_2\right)\right)}^{2}}}{\sqrt{1 - \left({\left(t\_0 \cdot \cos \left(\phi_2 \cdot 0.5\right) - t\_2 \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2} + \left(\left(\cos \phi_2 \cdot \cos \phi_1\right) \cdot t\_3\right) \cdot t\_3\right)}} \cdot 2\right) \cdot R
\end{array}
\end{array}
Initial program 62.8%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f6463.8
Applied rewrites63.8%
lift-sin.f64N/A
lift-/.f64N/A
div-invN/A
metadata-evalN/A
*-commutativeN/A
lift--.f64N/A
sub-negN/A
distribute-rgt-inN/A
lift-*.f64N/A
cancel-sign-sub-invN/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
sin-sumN/A
lift-sin.f64N/A
lower-fma.f64N/A
Applied rewrites78.6%
lift-*.f64N/A
lift-*.f64N/A
lift-*.f64N/A
associate-*l*N/A
associate-*l*N/A
lower-*.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f6478.6
lift-/.f64N/A
clear-numN/A
associate-/r/N/A
metadata-evalN/A
lower-*.f6478.6
lift-/.f64N/A
clear-numN/A
associate-/r/N/A
Applied rewrites78.6%
Final simplification78.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (cos (* phi1 0.5)))
(t_2 (sin (* phi1 0.5))))
(*
(*
(atan2
(sqrt
(+
(*
(* (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0) (cos phi2))
(cos phi1))
(pow (fma t_2 (cos (* -0.5 phi2)) (* (sin (* -0.5 phi2)) t_1)) 2.0)))
(sqrt
(-
1.0
(+
(pow (- (* t_2 (cos (* phi2 0.5))) (* t_1 (sin (* phi2 0.5)))) 2.0)
(* (* (* (cos phi2) (cos phi1)) t_0) t_0)))))
2.0)
R)))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = cos((phi1 * 0.5));
double t_2 = sin((phi1 * 0.5));
return (atan2(sqrt((((pow(sin(((lambda1 - lambda2) * 0.5)), 2.0) * cos(phi2)) * cos(phi1)) + pow(fma(t_2, cos((-0.5 * phi2)), (sin((-0.5 * phi2)) * t_1)), 2.0))), sqrt((1.0 - (pow(((t_2 * cos((phi2 * 0.5))) - (t_1 * sin((phi2 * 0.5)))), 2.0) + (((cos(phi2) * cos(phi1)) * t_0) * t_0))))) * 2.0) * R;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = cos(Float64(phi1 * 0.5)) t_2 = sin(Float64(phi1 * 0.5)) return Float64(Float64(atan(sqrt(Float64(Float64(Float64((sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0) * cos(phi2)) * cos(phi1)) + (fma(t_2, cos(Float64(-0.5 * phi2)), Float64(sin(Float64(-0.5 * phi2)) * t_1)) ^ 2.0))), sqrt(Float64(1.0 - Float64((Float64(Float64(t_2 * cos(Float64(phi2 * 0.5))) - Float64(t_1 * sin(Float64(phi2 * 0.5)))) ^ 2.0) + Float64(Float64(Float64(cos(phi2) * cos(phi1)) * t_0) * t_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[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, N[(N[(N[ArcTan[N[Sqrt[N[(N[(N[(N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] + N[Power[N[(t$95$2 * N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$1), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[(N[(t$95$2 * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(t$95$1 * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $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]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_2 := \sin \left(\phi_1 \cdot 0.5\right)\\
\left(\tan^{-1}_* \frac{\sqrt{\left({\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2} \cdot \cos \phi_2\right) \cdot \cos \phi_1 + {\left(\mathsf{fma}\left(t\_2, \cos \left(-0.5 \cdot \phi_2\right), \sin \left(-0.5 \cdot \phi_2\right) \cdot t\_1\right)\right)}^{2}}}{\sqrt{1 - \left({\left(t\_2 \cdot \cos \left(\phi_2 \cdot 0.5\right) - t\_1 \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2} + \left(\left(\cos \phi_2 \cdot \cos \phi_1\right) \cdot t\_0\right) \cdot t\_0\right)}} \cdot 2\right) \cdot R
\end{array}
\end{array}
Initial program 62.8%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f6463.8
Applied rewrites63.8%
lift-sin.f64N/A
lift-/.f64N/A
div-invN/A
metadata-evalN/A
*-commutativeN/A
lift--.f64N/A
sub-negN/A
distribute-rgt-inN/A
lift-*.f64N/A
cancel-sign-sub-invN/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
sin-sumN/A
lift-sin.f64N/A
lower-fma.f64N/A
Applied rewrites78.6%
lift-*.f64N/A
lift-*.f64N/A
associate-*l*N/A
lift-*.f64N/A
pow2N/A
lower-pow.f64N/A
lift-/.f64N/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
associate-*l*N/A
lower-*.f64N/A
lower-*.f6478.5
lift-*.f64N/A
*-commutativeN/A
lower-*.f6478.5
Applied rewrites78.5%
Final simplification78.5%
(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
(fma
(sin (* -0.5 phi2))
(cos (* -0.5 phi1))
(* (cos (* -0.5 phi2)) (sin (* phi1 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(fma(sin((-0.5 * phi2)), cos((-0.5 * phi1)), (cos((-0.5 * phi2)) * sin((phi1 * 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), (fma(sin(Float64(-0.5 * phi2)), cos(Float64(-0.5 * phi1)), Float64(cos(Float64(-0.5 * phi2)) * sin(Float64(phi1 * 0.5)))) ^ 2.0)) return Float64(Float64(atan(sqrt(t_0), sqrt(Float64(1.0 - t_0))) * 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[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(-0.5 * phi1), $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]}, N[(N[(N[ArcTan[N[Sqrt[t$95$0], $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 := \mathsf{fma}\left(\cos \phi_2 \cdot \cos \phi_1, {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}, {\left(\mathsf{fma}\left(\sin \left(-0.5 \cdot \phi_2\right), \cos \left(-0.5 \cdot \phi_1\right), \cos \left(-0.5 \cdot \phi_2\right) \cdot \sin \left(\phi_1 \cdot 0.5\right)\right)\right)}^{2}\right)\\
\left(\tan^{-1}_* \frac{\sqrt{t\_0}}{\sqrt{1 - t\_0}} \cdot 2\right) \cdot R
\end{array}
\end{array}
Initial program 62.8%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f6463.8
Applied rewrites63.8%
lift-sin.f64N/A
lift-/.f64N/A
div-invN/A
metadata-evalN/A
*-commutativeN/A
lift--.f64N/A
sub-negN/A
distribute-rgt-inN/A
lift-*.f64N/A
cancel-sign-sub-invN/A
lift-*.f64N/A
sin-diffN/A
lift-sin.f64N/A
lift-cos.f64N/A
lift-*.f64N/A
lift-cos.f64N/A
lift-sin.f64N/A
lift-*.f64N/A
lift--.f6478.6
Applied rewrites78.6%
Taylor expanded in lambda1 around 0
Applied rewrites78.5%
Final simplification78.5%
(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 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))
(t_3 (* (* (* (cos phi2) (cos phi1)) t_0) t_0))
(t_4 (+ t_2 t_3)))
(if (<= t_4 0.0004)
(*
(*
(atan2
(sqrt
(+ (/ (* (+ (cos (+ phi1 phi2)) (cos (- phi1 phi2))) t_1) 2.0) t_2))
(sqrt (- (pow (cos (* -0.5 phi1)) 2.0) (* t_1 (cos phi1)))))
2.0)
R)
(*
(*
(atan2
(sqrt (- t_3 (- (* (cos (* (* (- phi1 phi2) 0.5) 2.0)) 0.5) 0.5)))
(sqrt (- 1.0 t_4)))
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(((lambda1 - lambda2) * 0.5)), 2.0);
double t_2 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double t_3 = ((cos(phi2) * cos(phi1)) * t_0) * t_0;
double t_4 = t_2 + t_3;
double tmp;
if (t_4 <= 0.0004) {
tmp = (atan2(sqrt(((((cos((phi1 + phi2)) + cos((phi1 - phi2))) * t_1) / 2.0) + t_2)), sqrt((pow(cos((-0.5 * phi1)), 2.0) - (t_1 * cos(phi1))))) * 2.0) * R;
} else {
tmp = (atan2(sqrt((t_3 - ((cos((((phi1 - phi2) * 0.5) * 2.0)) * 0.5) - 0.5))), sqrt((1.0 - t_4))) * 2.0) * R;
}
return tmp;
}
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
real(8) :: t_2
real(8) :: t_3
real(8) :: t_4
real(8) :: tmp
t_0 = sin(((lambda1 - lambda2) / 2.0d0))
t_1 = sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0
t_2 = sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0
t_3 = ((cos(phi2) * cos(phi1)) * t_0) * t_0
t_4 = t_2 + t_3
if (t_4 <= 0.0004d0) then
tmp = (atan2(sqrt(((((cos((phi1 + phi2)) + cos((phi1 - phi2))) * t_1) / 2.0d0) + t_2)), sqrt(((cos(((-0.5d0) * phi1)) ** 2.0d0) - (t_1 * cos(phi1))))) * 2.0d0) * r
else
tmp = (atan2(sqrt((t_3 - ((cos((((phi1 - phi2) * 0.5d0) * 2.0d0)) * 0.5d0) - 0.5d0))), sqrt((1.0d0 - t_4))) * 2.0d0) * r
end if
code = tmp
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(((lambda1 - lambda2) * 0.5)), 2.0);
double t_2 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0);
double t_3 = ((Math.cos(phi2) * Math.cos(phi1)) * t_0) * t_0;
double t_4 = t_2 + t_3;
double tmp;
if (t_4 <= 0.0004) {
tmp = (Math.atan2(Math.sqrt(((((Math.cos((phi1 + phi2)) + Math.cos((phi1 - phi2))) * t_1) / 2.0) + t_2)), Math.sqrt((Math.pow(Math.cos((-0.5 * phi1)), 2.0) - (t_1 * Math.cos(phi1))))) * 2.0) * R;
} else {
tmp = (Math.atan2(Math.sqrt((t_3 - ((Math.cos((((phi1 - phi2) * 0.5) * 2.0)) * 0.5) - 0.5))), Math.sqrt((1.0 - t_4))) * 2.0) * R;
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0) t_2 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) t_3 = ((math.cos(phi2) * math.cos(phi1)) * t_0) * t_0 t_4 = t_2 + t_3 tmp = 0 if t_4 <= 0.0004: tmp = (math.atan2(math.sqrt(((((math.cos((phi1 + phi2)) + math.cos((phi1 - phi2))) * t_1) / 2.0) + t_2)), math.sqrt((math.pow(math.cos((-0.5 * phi1)), 2.0) - (t_1 * math.cos(phi1))))) * 2.0) * R else: tmp = (math.atan2(math.sqrt((t_3 - ((math.cos((((phi1 - phi2) * 0.5) * 2.0)) * 0.5) - 0.5))), math.sqrt((1.0 - t_4))) * 2.0) * R 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 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 t_3 = Float64(Float64(Float64(cos(phi2) * cos(phi1)) * t_0) * t_0) t_4 = Float64(t_2 + t_3) tmp = 0.0 if (t_4 <= 0.0004) tmp = Float64(Float64(atan(sqrt(Float64(Float64(Float64(Float64(cos(Float64(phi1 + phi2)) + cos(Float64(phi1 - phi2))) * t_1) / 2.0) + t_2)), sqrt(Float64((cos(Float64(-0.5 * phi1)) ^ 2.0) - Float64(t_1 * cos(phi1))))) * 2.0) * R); else tmp = Float64(Float64(atan(sqrt(Float64(t_3 - Float64(Float64(cos(Float64(Float64(Float64(phi1 - phi2) * 0.5) * 2.0)) * 0.5) - 0.5))), sqrt(Float64(1.0 - t_4))) * 2.0) * R); end return tmp end
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = sin(((lambda1 - lambda2) * 0.5)) ^ 2.0; t_2 = sin(((phi1 - phi2) / 2.0)) ^ 2.0; t_3 = ((cos(phi2) * cos(phi1)) * t_0) * t_0; t_4 = t_2 + t_3; tmp = 0.0; if (t_4 <= 0.0004) tmp = (atan2(sqrt(((((cos((phi1 + phi2)) + cos((phi1 - phi2))) * t_1) / 2.0) + t_2)), sqrt(((cos((-0.5 * phi1)) ^ 2.0) - (t_1 * cos(phi1))))) * 2.0) * R; else tmp = (atan2(sqrt((t_3 - ((cos((((phi1 - phi2) * 0.5) * 2.0)) * 0.5) - 0.5))), sqrt((1.0 - t_4))) * 2.0) * R; end tmp_2 = 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[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$3 = N[(N[(N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]}, Block[{t$95$4 = N[(t$95$2 + t$95$3), $MachinePrecision]}, If[LessEqual[t$95$4, 0.0004], N[(N[(N[ArcTan[N[Sqrt[N[(N[(N[(N[(N[Cos[N[(phi1 + phi2), $MachinePrecision]], $MachinePrecision] + N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * t$95$1), $MachinePrecision] / 2.0), $MachinePrecision] + t$95$2), $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], N[(N[(N[ArcTan[N[Sqrt[N[(t$95$3 - N[(N[(N[Cos[N[(N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision] * 2.0), $MachinePrecision]], $MachinePrecision] * 0.5), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$4), $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(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_2 := {\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2}\\
t_3 := \left(\left(\cos \phi_2 \cdot \cos \phi_1\right) \cdot t\_0\right) \cdot t\_0\\
t_4 := t\_2 + t\_3\\
\mathbf{if}\;t\_4 \leq 0.0004:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\frac{\left(\cos \left(\phi_1 + \phi_2\right) + \cos \left(\phi_1 - \phi_2\right)\right) \cdot t\_1}{2} + t\_2}}{\sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - t\_1 \cdot \cos \phi_1}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{t\_3 - \left(\cos \left(\left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right) \cdot 2\right) \cdot 0.5 - 0.5\right)}}{\sqrt{1 - t\_4}} \cdot 2\right) \cdot R\\
\end{array}
\end{array}
if (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))))) < 4.00000000000000019e-4Initial program 57.4%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites57.4%
lift-*.f64N/A
lift-*.f64N/A
associate-*l*N/A
lift-*.f64N/A
lift-cos.f64N/A
lift-cos.f64N/A
cos-multN/A
pow2N/A
lift-/.f64N/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
lift-pow.f64N/A
associate-*l/N/A
lower-/.f64N/A
Applied rewrites65.4%
if 4.00000000000000019e-4 < (+.f64 (pow.f64 (sin.f64 (/.f64 (-.f64 phi1 phi2) #s(literal 2 binary64))) #s(literal 2 binary64)) (*.f64 (*.f64 (*.f64 (cos.f64 phi1) (cos.f64 phi2)) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64)))) (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))))) Initial program 63.3%
lift-pow.f64N/A
unpow2N/A
lift-sin.f64N/A
lift-sin.f64N/A
sqr-sin-aN/A
lower--.f64N/A
cos-2N/A
cos-sumN/A
lower-*.f64N/A
cos-sumN/A
cos-2N/A
lower-cos.f64N/A
lower-*.f6463.3
lift-/.f64N/A
clear-numN/A
associate-/r/N/A
metadata-evalN/A
lower-*.f6463.3
Applied rewrites63.3%
Final simplification63.5%
(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_1) t_1))
(t_3 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_4 (* t_3 (cos phi1)))
(t_5 (cos (* phi1 0.5)))
(t_6
(pow (fma t_0 (cos (* -0.5 phi2)) (* (sin (* -0.5 phi2)) t_5)) 2.0))
(t_7
(pow (- (* t_0 (cos (* phi2 0.5))) (* t_5 (sin (* phi2 0.5)))) 2.0))
(t_8 (sqrt (- 1.0 (+ t_7 t_2)))))
(if (<= phi1 -0.95)
(* (* (atan2 (sqrt (+ t_6 t_2)) (sqrt (- 1.0 (+ t_7 t_4)))) 2.0) R)
(if (<= phi1 1.25e-5)
(*
(*
(atan2
(sqrt (+ (* (* t_3 (cos phi2)) (fma -0.5 (* phi1 phi1) 1.0)) t_6))
t_8)
2.0)
R)
(* (* (atan2 (sqrt (+ t_4 t_6)) t_8) 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 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = ((cos(phi2) * cos(phi1)) * t_1) * t_1;
double t_3 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_4 = t_3 * cos(phi1);
double t_5 = cos((phi1 * 0.5));
double t_6 = pow(fma(t_0, cos((-0.5 * phi2)), (sin((-0.5 * phi2)) * t_5)), 2.0);
double t_7 = pow(((t_0 * cos((phi2 * 0.5))) - (t_5 * sin((phi2 * 0.5)))), 2.0);
double t_8 = sqrt((1.0 - (t_7 + t_2)));
double tmp;
if (phi1 <= -0.95) {
tmp = (atan2(sqrt((t_6 + t_2)), sqrt((1.0 - (t_7 + t_4)))) * 2.0) * R;
} else if (phi1 <= 1.25e-5) {
tmp = (atan2(sqrt((((t_3 * cos(phi2)) * fma(-0.5, (phi1 * phi1), 1.0)) + t_6)), t_8) * 2.0) * R;
} else {
tmp = (atan2(sqrt((t_4 + t_6)), t_8) * 2.0) * R;
}
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(Float64(Float64(cos(phi2) * cos(phi1)) * t_1) * t_1) t_3 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_4 = Float64(t_3 * cos(phi1)) t_5 = cos(Float64(phi1 * 0.5)) t_6 = fma(t_0, cos(Float64(-0.5 * phi2)), Float64(sin(Float64(-0.5 * phi2)) * t_5)) ^ 2.0 t_7 = Float64(Float64(t_0 * cos(Float64(phi2 * 0.5))) - Float64(t_5 * sin(Float64(phi2 * 0.5)))) ^ 2.0 t_8 = sqrt(Float64(1.0 - Float64(t_7 + t_2))) tmp = 0.0 if (phi1 <= -0.95) tmp = Float64(Float64(atan(sqrt(Float64(t_6 + t_2)), sqrt(Float64(1.0 - Float64(t_7 + t_4)))) * 2.0) * R); elseif (phi1 <= 1.25e-5) tmp = Float64(Float64(atan(sqrt(Float64(Float64(Float64(t_3 * cos(phi2)) * fma(-0.5, Float64(phi1 * phi1), 1.0)) + t_6)), t_8) * 2.0) * R); else tmp = Float64(Float64(atan(sqrt(Float64(t_4 + t_6)), t_8) * 2.0) * R); 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[(N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] * t$95$1), $MachinePrecision] * t$95$1), $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[(t$95$3 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$6 = N[Power[N[(t$95$0 * N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$5), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$7 = N[Power[N[(N[(t$95$0 * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(t$95$5 * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$8 = N[Sqrt[N[(1.0 - N[(t$95$7 + t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi1, -0.95], N[(N[(N[ArcTan[N[Sqrt[N[(t$95$6 + t$95$2), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$7 + t$95$4), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], If[LessEqual[phi1, 1.25e-5], N[(N[(N[ArcTan[N[Sqrt[N[(N[(N[(t$95$3 * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * N[(-0.5 * N[(phi1 * phi1), $MachinePrecision] + 1.0), $MachinePrecision]), $MachinePrecision] + t$95$6), $MachinePrecision]], $MachinePrecision] / t$95$8], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], N[(N[(N[ArcTan[N[Sqrt[N[(t$95$4 + t$95$6), $MachinePrecision]], $MachinePrecision] / t$95$8], $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(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \left(\left(\cos \phi_2 \cdot \cos \phi_1\right) \cdot t\_1\right) \cdot t\_1\\
t_3 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_4 := t\_3 \cdot \cos \phi_1\\
t_5 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_6 := {\left(\mathsf{fma}\left(t\_0, \cos \left(-0.5 \cdot \phi_2\right), \sin \left(-0.5 \cdot \phi_2\right) \cdot t\_5\right)\right)}^{2}\\
t_7 := {\left(t\_0 \cdot \cos \left(\phi_2 \cdot 0.5\right) - t\_5 \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\\
t_8 := \sqrt{1 - \left(t\_7 + t\_2\right)}\\
\mathbf{if}\;\phi_1 \leq -0.95:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{t\_6 + t\_2}}{\sqrt{1 - \left(t\_7 + t\_4\right)}} \cdot 2\right) \cdot R\\
\mathbf{elif}\;\phi_1 \leq 1.25 \cdot 10^{-5}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\left(t\_3 \cdot \cos \phi_2\right) \cdot \mathsf{fma}\left(-0.5, \phi_1 \cdot \phi_1, 1\right) + t\_6}}{t\_8} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{t\_4 + t\_6}}{t\_8} \cdot 2\right) \cdot R\\
\end{array}
\end{array}
if phi1 < -0.94999999999999996Initial program 48.7%
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-*.f6450.5
Applied rewrites50.5%
lift-sin.f64N/A
lift-/.f64N/A
div-invN/A
metadata-evalN/A
*-commutativeN/A
lift--.f64N/A
sub-negN/A
distribute-rgt-inN/A
lift-*.f64N/A
cancel-sign-sub-invN/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
sin-sumN/A
lift-sin.f64N/A
lower-fma.f64N/A
Applied rewrites77.5%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-*.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f6457.0
Applied rewrites57.0%
if -0.94999999999999996 < phi1 < 1.25000000000000006e-5Initial program 79.1%
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-*.f6479.1
Applied rewrites79.1%
lift-sin.f64N/A
lift-/.f64N/A
div-invN/A
metadata-evalN/A
*-commutativeN/A
lift--.f64N/A
sub-negN/A
distribute-rgt-inN/A
lift-*.f64N/A
cancel-sign-sub-invN/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
sin-sumN/A
lift-sin.f64N/A
lower-fma.f64N/A
Applied rewrites79.7%
Taylor expanded in phi1 around 0
associate-*r*N/A
distribute-lft1-inN/A
lower-*.f64N/A
lower-fma.f64N/A
unpow2N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites79.6%
if 1.25000000000000006e-5 < phi1 Initial program 49.0%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f6450.9
Applied rewrites50.9%
lift-sin.f64N/A
lift-/.f64N/A
div-invN/A
metadata-evalN/A
*-commutativeN/A
lift--.f64N/A
sub-negN/A
distribute-rgt-inN/A
lift-*.f64N/A
cancel-sign-sub-invN/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
sin-sumN/A
lift-sin.f64N/A
lower-fma.f64N/A
Applied rewrites77.6%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-*.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f6462.0
Applied rewrites62.0%
Final simplification68.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_1 (sin (* phi1 0.5)))
(t_2 (sin (/ (- lambda1 lambda2) 2.0)))
(t_3 (* (* (* (cos phi2) (cos phi1)) t_2) t_2))
(t_4 (* t_0 (cos phi1)))
(t_5 (cos (* phi1 0.5)))
(t_6
(pow (- (* t_1 (cos (* phi2 0.5))) (* t_5 (sin (* phi2 0.5)))) 2.0))
(t_7
(pow (fma t_1 (cos (* -0.5 phi2)) (* (sin (* -0.5 phi2)) t_5)) 2.0))
(t_8 (sqrt (- 1.0 (+ t_6 t_3)))))
(if (<= phi1 -3.2e+47)
(* (* (atan2 (sqrt (+ t_7 t_3)) (sqrt (- 1.0 (+ t_6 t_4)))) 2.0) R)
(if (<= phi1 4.8e-6)
(* (* (atan2 (sqrt (+ (* t_0 (cos phi2)) t_7)) t_8) 2.0) R)
(* (* (atan2 (sqrt (+ t_4 t_7)) t_8) 2.0) R)))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_1 = sin((phi1 * 0.5));
double t_2 = sin(((lambda1 - lambda2) / 2.0));
double t_3 = ((cos(phi2) * cos(phi1)) * t_2) * t_2;
double t_4 = t_0 * cos(phi1);
double t_5 = cos((phi1 * 0.5));
double t_6 = pow(((t_1 * cos((phi2 * 0.5))) - (t_5 * sin((phi2 * 0.5)))), 2.0);
double t_7 = pow(fma(t_1, cos((-0.5 * phi2)), (sin((-0.5 * phi2)) * t_5)), 2.0);
double t_8 = sqrt((1.0 - (t_6 + t_3)));
double tmp;
if (phi1 <= -3.2e+47) {
tmp = (atan2(sqrt((t_7 + t_3)), sqrt((1.0 - (t_6 + t_4)))) * 2.0) * R;
} else if (phi1 <= 4.8e-6) {
tmp = (atan2(sqrt(((t_0 * cos(phi2)) + t_7)), t_8) * 2.0) * R;
} else {
tmp = (atan2(sqrt((t_4 + t_7)), t_8) * 2.0) * R;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_1 = sin(Float64(phi1 * 0.5)) t_2 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_3 = Float64(Float64(Float64(cos(phi2) * cos(phi1)) * t_2) * t_2) t_4 = Float64(t_0 * cos(phi1)) t_5 = cos(Float64(phi1 * 0.5)) t_6 = Float64(Float64(t_1 * cos(Float64(phi2 * 0.5))) - Float64(t_5 * sin(Float64(phi2 * 0.5)))) ^ 2.0 t_7 = fma(t_1, cos(Float64(-0.5 * phi2)), Float64(sin(Float64(-0.5 * phi2)) * t_5)) ^ 2.0 t_8 = sqrt(Float64(1.0 - Float64(t_6 + t_3))) tmp = 0.0 if (phi1 <= -3.2e+47) tmp = Float64(Float64(atan(sqrt(Float64(t_7 + t_3)), sqrt(Float64(1.0 - Float64(t_6 + t_4)))) * 2.0) * R); elseif (phi1 <= 4.8e-6) tmp = Float64(Float64(atan(sqrt(Float64(Float64(t_0 * cos(phi2)) + t_7)), t_8) * 2.0) * R); else tmp = Float64(Float64(atan(sqrt(Float64(t_4 + t_7)), t_8) * 2.0) * R); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[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[(N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] * t$95$2), $MachinePrecision] * t$95$2), $MachinePrecision]}, Block[{t$95$4 = N[(t$95$0 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$5 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$6 = N[Power[N[(N[(t$95$1 * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(t$95$5 * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$7 = N[Power[N[(t$95$1 * N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$5), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$8 = N[Sqrt[N[(1.0 - N[(t$95$6 + t$95$3), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi1, -3.2e+47], N[(N[(N[ArcTan[N[Sqrt[N[(t$95$7 + t$95$3), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$6 + t$95$4), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], If[LessEqual[phi1, 4.8e-6], N[(N[(N[ArcTan[N[Sqrt[N[(N[(t$95$0 * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] + t$95$7), $MachinePrecision]], $MachinePrecision] / t$95$8], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], N[(N[(N[ArcTan[N[Sqrt[N[(t$95$4 + t$95$7), $MachinePrecision]], $MachinePrecision] / t$95$8], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]]]]]]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_1 := \sin \left(\phi_1 \cdot 0.5\right)\\
t_2 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_3 := \left(\left(\cos \phi_2 \cdot \cos \phi_1\right) \cdot t\_2\right) \cdot t\_2\\
t_4 := t\_0 \cdot \cos \phi_1\\
t_5 := \cos \left(\phi_1 \cdot 0.5\right)\\
t_6 := {\left(t\_1 \cdot \cos \left(\phi_2 \cdot 0.5\right) - t\_5 \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2}\\
t_7 := {\left(\mathsf{fma}\left(t\_1, \cos \left(-0.5 \cdot \phi_2\right), \sin \left(-0.5 \cdot \phi_2\right) \cdot t\_5\right)\right)}^{2}\\
t_8 := \sqrt{1 - \left(t\_6 + t\_3\right)}\\
\mathbf{if}\;\phi_1 \leq -3.2 \cdot 10^{+47}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{t\_7 + t\_3}}{\sqrt{1 - \left(t\_6 + t\_4\right)}} \cdot 2\right) \cdot R\\
\mathbf{elif}\;\phi_1 \leq 4.8 \cdot 10^{-6}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{t\_0 \cdot \cos \phi_2 + t\_7}}{t\_8} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{t\_4 + t\_7}}{t\_8} \cdot 2\right) \cdot R\\
\end{array}
\end{array}
if phi1 < -3.2e47Initial program 51.8%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f6453.7
Applied rewrites53.7%
lift-sin.f64N/A
lift-/.f64N/A
div-invN/A
metadata-evalN/A
*-commutativeN/A
lift--.f64N/A
sub-negN/A
distribute-rgt-inN/A
lift-*.f64N/A
cancel-sign-sub-invN/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
sin-sumN/A
lift-sin.f64N/A
lower-fma.f64N/A
Applied rewrites77.1%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-*.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f6459.3
Applied rewrites59.3%
if -3.2e47 < phi1 < 4.7999999999999998e-6Initial program 75.8%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f6475.9
Applied rewrites75.9%
lift-sin.f64N/A
lift-/.f64N/A
div-invN/A
metadata-evalN/A
*-commutativeN/A
lift--.f64N/A
sub-negN/A
distribute-rgt-inN/A
lift-*.f64N/A
cancel-sign-sub-invN/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
sin-sumN/A
lift-sin.f64N/A
lower-fma.f64N/A
Applied rewrites79.8%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-*.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f6477.1
Applied rewrites77.1%
if 4.7999999999999998e-6 < phi1 Initial program 49.0%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f6450.9
Applied rewrites50.9%
lift-sin.f64N/A
lift-/.f64N/A
div-invN/A
metadata-evalN/A
*-commutativeN/A
lift--.f64N/A
sub-negN/A
distribute-rgt-inN/A
lift-*.f64N/A
cancel-sign-sub-invN/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
sin-sumN/A
lift-sin.f64N/A
lower-fma.f64N/A
Applied rewrites77.6%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-*.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f6462.0
Applied rewrites62.0%
Final simplification68.8%
(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 (* phi1 0.5)))
(t_3 (* (* (* (cos phi2) (cos phi1)) t_0) t_0))
(t_4
(+
(pow (- (* t_1 (cos (* phi2 0.5))) (* t_2 (sin (* phi2 0.5)))) 2.0)
t_3)))
(if (<= phi1 7e-8)
(*
(*
(atan2
(sqrt t_4)
(sqrt
(- 1.0 (- t_3 (- (* (cos (* (* (- phi1 phi2) 0.5) 2.0)) 0.5) 0.5)))))
2.0)
R)
(*
(*
(atan2
(sqrt
(+
(* (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0) (cos phi1))
(pow (fma t_1 (cos (* -0.5 phi2)) (* (sin (* -0.5 phi2)) t_2)) 2.0)))
(sqrt (- 1.0 t_4)))
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((phi1 * 0.5));
double t_3 = ((cos(phi2) * cos(phi1)) * t_0) * t_0;
double t_4 = pow(((t_1 * cos((phi2 * 0.5))) - (t_2 * sin((phi2 * 0.5)))), 2.0) + t_3;
double tmp;
if (phi1 <= 7e-8) {
tmp = (atan2(sqrt(t_4), sqrt((1.0 - (t_3 - ((cos((((phi1 - phi2) * 0.5) * 2.0)) * 0.5) - 0.5))))) * 2.0) * R;
} else {
tmp = (atan2(sqrt(((pow(sin(((lambda1 - lambda2) * 0.5)), 2.0) * cos(phi1)) + pow(fma(t_1, cos((-0.5 * phi2)), (sin((-0.5 * phi2)) * t_2)), 2.0))), sqrt((1.0 - t_4))) * 2.0) * R;
}
return tmp;
}
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 = cos(Float64(phi1 * 0.5)) t_3 = Float64(Float64(Float64(cos(phi2) * cos(phi1)) * t_0) * t_0) t_4 = Float64((Float64(Float64(t_1 * cos(Float64(phi2 * 0.5))) - Float64(t_2 * sin(Float64(phi2 * 0.5)))) ^ 2.0) + t_3) tmp = 0.0 if (phi1 <= 7e-8) tmp = Float64(Float64(atan(sqrt(t_4), sqrt(Float64(1.0 - Float64(t_3 - Float64(Float64(cos(Float64(Float64(Float64(phi1 - phi2) * 0.5) * 2.0)) * 0.5) - 0.5))))) * 2.0) * R); else tmp = Float64(Float64(atan(sqrt(Float64(Float64((sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0) * cos(phi1)) + (fma(t_1, cos(Float64(-0.5 * phi2)), Float64(sin(Float64(-0.5 * phi2)) * t_2)) ^ 2.0))), sqrt(Float64(1.0 - t_4))) * 2.0) * R); end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$3 = N[(N[(N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]}, Block[{t$95$4 = N[(N[Power[N[(N[(t$95$1 * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(t$95$2 * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$3), $MachinePrecision]}, If[LessEqual[phi1, 7e-8], N[(N[(N[ArcTan[N[Sqrt[t$95$4], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$3 - N[(N[(N[Cos[N[(N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision] * 2.0), $MachinePrecision]], $MachinePrecision] * 0.5), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], N[(N[(N[ArcTan[N[Sqrt[N[(N[(N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] + N[Power[N[(t$95$1 * N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * t$95$2), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$4), $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 \left(\phi_1 \cdot 0.5\right)\\
t_3 := \left(\left(\cos \phi_2 \cdot \cos \phi_1\right) \cdot t\_0\right) \cdot t\_0\\
t_4 := {\left(t\_1 \cdot \cos \left(\phi_2 \cdot 0.5\right) - t\_2 \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2} + t\_3\\
\mathbf{if}\;\phi_1 \leq 7 \cdot 10^{-8}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{t\_4}}{\sqrt{1 - \left(t\_3 - \left(\cos \left(\left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right) \cdot 2\right) \cdot 0.5 - 0.5\right)\right)}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{{\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2} \cdot \cos \phi_1 + {\left(\mathsf{fma}\left(t\_1, \cos \left(-0.5 \cdot \phi_2\right), \sin \left(-0.5 \cdot \phi_2\right) \cdot t\_2\right)\right)}^{2}}}{\sqrt{1 - t\_4}} \cdot 2\right) \cdot R\\
\end{array}
\end{array}
if phi1 < 7.00000000000000048e-8Initial program 68.5%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f6469.1
Applied rewrites69.1%
lift-sin.f64N/A
lift-/.f64N/A
div-invN/A
metadata-evalN/A
*-commutativeN/A
lift--.f64N/A
sub-negN/A
distribute-rgt-inN/A
lift-*.f64N/A
cancel-sign-sub-invN/A
lift-*.f64N/A
sin-diffN/A
lift-sin.f64N/A
lift-cos.f64N/A
lift-*.f64N/A
lift-cos.f64N/A
lift-sin.f64N/A
lift-*.f64N/A
lift--.f6479.0
Applied rewrites79.0%
Applied rewrites69.4%
if 7.00000000000000048e-8 < phi1 Initial program 49.0%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f6450.9
Applied rewrites50.9%
lift-sin.f64N/A
lift-/.f64N/A
div-invN/A
metadata-evalN/A
*-commutativeN/A
lift--.f64N/A
sub-negN/A
distribute-rgt-inN/A
lift-*.f64N/A
cancel-sign-sub-invN/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
sin-sumN/A
lift-sin.f64N/A
lower-fma.f64N/A
Applied rewrites77.6%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-*.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f6462.0
Applied rewrites62.0%
Final simplification67.2%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (* (* (cos phi2) (cos phi1)) t_0) t_0)))
(*
(*
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) t_1))
(sqrt
(-
1.0
(+
(pow
(-
(* (sin (* phi1 0.5)) (cos (* phi2 0.5)))
(* (cos (* phi1 0.5)) (sin (* phi2 0.5))))
2.0)
t_1))))
2.0)
R)))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = ((cos(phi2) * cos(phi1)) * t_0) * t_0;
return (atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), sqrt((1.0 - (pow(((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))), 2.0) + t_1)))) * 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 = ((cos(phi2) * cos(phi1)) * t_0) * t_0
code = (atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + t_1)), sqrt((1.0d0 - ((((sin((phi1 * 0.5d0)) * cos((phi2 * 0.5d0))) - (cos((phi1 * 0.5d0)) * sin((phi2 * 0.5d0)))) ** 2.0d0) + t_1)))) * 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.cos(phi2) * Math.cos(phi1)) * t_0) * t_0;
return (Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), Math.sqrt((1.0 - (Math.pow(((Math.sin((phi1 * 0.5)) * Math.cos((phi2 * 0.5))) - (Math.cos((phi1 * 0.5)) * Math.sin((phi2 * 0.5)))), 2.0) + t_1)))) * 2.0) * R;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) / 2.0)) t_1 = ((math.cos(phi2) * math.cos(phi1)) * t_0) * t_0 return (math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), math.sqrt((1.0 - (math.pow(((math.sin((phi1 * 0.5)) * math.cos((phi2 * 0.5))) - (math.cos((phi1 * 0.5)) * math.sin((phi2 * 0.5)))), 2.0) + t_1)))) * 2.0) * R
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(Float64(cos(phi2) * cos(phi1)) * t_0) * t_0) return Float64(Float64(atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + t_1)), sqrt(Float64(1.0 - Float64((Float64(Float64(sin(Float64(phi1 * 0.5)) * cos(Float64(phi2 * 0.5))) - Float64(cos(Float64(phi1 * 0.5)) * sin(Float64(phi2 * 0.5)))) ^ 2.0) + t_1)))) * 2.0) * R) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) / 2.0)); t_1 = ((cos(phi2) * cos(phi1)) * t_0) * t_0; tmp = (atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + t_1)), sqrt((1.0 - ((((sin((phi1 * 0.5)) * cos((phi2 * 0.5))) - (cos((phi1 * 0.5)) * sin((phi2 * 0.5)))) ^ 2.0) + t_1)))) * 2.0) * R; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]}, 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$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[(N[(N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] - N[(N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Sin[N[(phi2 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$1), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \left(\left(\cos \phi_2 \cdot \cos \phi_1\right) \cdot t\_0\right) \cdot t\_0\\
\left(\tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_1}}{\sqrt{1 - \left({\left(\sin \left(\phi_1 \cdot 0.5\right) \cdot \cos \left(\phi_2 \cdot 0.5\right) - \cos \left(\phi_1 \cdot 0.5\right) \cdot \sin \left(\phi_2 \cdot 0.5\right)\right)}^{2} + t\_1\right)}} \cdot 2\right) \cdot R
\end{array}
\end{array}
Initial program 62.8%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f6463.8
Applied rewrites63.8%
Final simplification63.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0)))
(t_1 (* (* (* (cos phi2) (cos phi1)) t_0) t_0)))
(*
(*
(atan2
(sqrt
(+
(pow
(fma
(sin (* phi1 0.5))
(cos (* -0.5 phi2))
(* (sin (* -0.5 phi2)) (cos (* phi1 0.5))))
2.0)
t_1))
(sqrt
(- 1.0 (- t_1 (- (* (cos (* (* (- phi1 phi2) 0.5) 2.0)) 0.5) 0.5)))))
2.0)
R)))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
double t_1 = ((cos(phi2) * cos(phi1)) * t_0) * t_0;
return (atan2(sqrt((pow(fma(sin((phi1 * 0.5)), cos((-0.5 * phi2)), (sin((-0.5 * phi2)) * cos((phi1 * 0.5)))), 2.0) + t_1)), sqrt((1.0 - (t_1 - ((cos((((phi1 - phi2) * 0.5) * 2.0)) * 0.5) - 0.5))))) * 2.0) * R;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_1 = Float64(Float64(Float64(cos(phi2) * cos(phi1)) * t_0) * t_0) return Float64(Float64(atan(sqrt(Float64((fma(sin(Float64(phi1 * 0.5)), cos(Float64(-0.5 * phi2)), Float64(sin(Float64(-0.5 * phi2)) * cos(Float64(phi1 * 0.5)))) ^ 2.0) + t_1)), sqrt(Float64(1.0 - Float64(t_1 - Float64(Float64(cos(Float64(Float64(Float64(phi1 - phi2) * 0.5) * 2.0)) * 0.5) - 0.5))))) * 2.0) * R) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[(N[(N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision] * t$95$0), $MachinePrecision]}, N[(N[(N[ArcTan[N[Sqrt[N[(N[Power[N[(N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] + N[(N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * N[Cos[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision]), $MachinePrecision]), $MachinePrecision], 2.0], $MachinePrecision] + t$95$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$1 - N[(N[(N[Cos[N[(N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision] * 2.0), $MachinePrecision]], $MachinePrecision] * 0.5), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_1 := \left(\left(\cos \phi_2 \cdot \cos \phi_1\right) \cdot t\_0\right) \cdot t\_0\\
\left(\tan^{-1}_* \frac{\sqrt{{\left(\mathsf{fma}\left(\sin \left(\phi_1 \cdot 0.5\right), \cos \left(-0.5 \cdot \phi_2\right), \sin \left(-0.5 \cdot \phi_2\right) \cdot \cos \left(\phi_1 \cdot 0.5\right)\right)\right)}^{2} + t\_1}}{\sqrt{1 - \left(t\_1 - \left(\cos \left(\left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right) \cdot 2\right) \cdot 0.5 - 0.5\right)\right)}} \cdot 2\right) \cdot R
\end{array}
\end{array}
Initial program 62.8%
lift-sin.f64N/A
lift-/.f64N/A
lift--.f64N/A
div-subN/A
sin-diffN/A
lower--.f64N/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-*.f64N/A
lower-cos.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f64N/A
lower-sin.f64N/A
div-invN/A
metadata-evalN/A
lower-*.f6463.8
Applied rewrites63.8%
lift-sin.f64N/A
lift-/.f64N/A
div-invN/A
metadata-evalN/A
*-commutativeN/A
lift--.f64N/A
sub-negN/A
distribute-rgt-inN/A
lift-*.f64N/A
cancel-sign-sub-invN/A
lift-*.f64N/A
lift-*.f64N/A
*-commutativeN/A
cancel-sign-sub-invN/A
sin-sumN/A
lift-sin.f64N/A
lower-fma.f64N/A
Applied rewrites78.6%
Applied rewrites63.8%
Final simplification63.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (/ (- lambda1 lambda2) 2.0))))
(*
(*
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi2) (cos phi1)) t_0) t_0)))
(sqrt
(-
1.0
(/
(fma
(-
(cos (/ 0.0 (/ 2.0 (- phi1 phi2))))
(cos (* (* (- phi1 phi2) 0.5) 2.0)))
2.0
(*
(*
(+ (cos (+ phi1 phi2)) (cos (- phi1 phi2)))
(pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
2.0))
4.0))))
2.0)
R)))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) / 2.0));
return (atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi2) * cos(phi1)) * t_0) * t_0))), sqrt((1.0 - (fma((cos((0.0 / (2.0 / (phi1 - phi2)))) - cos((((phi1 - phi2) * 0.5) * 2.0))), 2.0, (((cos((phi1 + phi2)) + cos((phi1 - phi2))) * pow(sin(((lambda1 - lambda2) * 0.5)), 2.0)) * 2.0)) / 4.0)))) * 2.0) * R;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(Float64(atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi2) * cos(phi1)) * t_0) * t_0))), sqrt(Float64(1.0 - Float64(fma(Float64(cos(Float64(0.0 / Float64(2.0 / Float64(phi1 - phi2)))) - cos(Float64(Float64(Float64(phi1 - phi2) * 0.5) * 2.0))), 2.0, Float64(Float64(Float64(cos(Float64(phi1 + phi2)) + cos(Float64(phi1 - phi2))) * (sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0)) * 2.0)) / 4.0)))) * 2.0) * R) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(N[(N[ArcTan[N[Sqrt[N[(N[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[(1.0 - N[(N[(N[(N[Cos[N[(0.0 / N[(2.0 / N[(phi1 - phi2), $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] - N[Cos[N[(N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision] * 2.0), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * 2.0 + N[(N[(N[(N[Cos[N[(phi1 + phi2), $MachinePrecision]], $MachinePrecision] + N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision] * 2.0), $MachinePrecision]), $MachinePrecision] / 4.0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\left(\tan^{-1}_* \frac{\sqrt{{\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{1 - \frac{\mathsf{fma}\left(\cos \left(\frac{0}{\frac{2}{\phi_1 - \phi_2}}\right) - \cos \left(\left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right) \cdot 2\right), 2, \left(\left(\cos \left(\phi_1 + \phi_2\right) + \cos \left(\phi_1 - \phi_2\right)\right) \cdot {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\right) \cdot 2\right)}{4}}} \cdot 2\right) \cdot R
\end{array}
\end{array}
Initial program 62.8%
Applied rewrites63.4%
Final simplification63.4%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (* -0.5 phi1)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (* (* (* (cos phi2) (cos phi1)) t_1) t_1))
(t_3 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_4 (* (- phi1 phi2) 0.5)))
(if (<= t_1 -4e-26)
(*
(*
(atan2
(sqrt (- t_2 (- (* (cos (* t_4 2.0)) 0.5) 0.5)))
(sqrt (- (pow t_0 2.0) (* t_3 (cos phi1)))))
2.0)
R)
(if (<= t_1 5e-55)
(*
(*
(atan2
(sqrt
(fma
(cos phi1)
(* (* (fma 0.25 lambda1 (* -0.5 lambda2)) (cos phi2)) lambda1)
(pow (sin t_4) 2.0)))
(sqrt (- 1.0 (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) t_2))))
2.0)
R)
(*
(*
(atan2
(sqrt (fma t_3 (cos phi1) (pow (sin (* phi1 0.5)) 2.0)))
(sqrt (fma t_0 t_0 (* (- (cos phi1)) t_3))))
2.0)
R)))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((-0.5 * phi1));
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = ((cos(phi2) * cos(phi1)) * t_1) * t_1;
double t_3 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_4 = (phi1 - phi2) * 0.5;
double tmp;
if (t_1 <= -4e-26) {
tmp = (atan2(sqrt((t_2 - ((cos((t_4 * 2.0)) * 0.5) - 0.5))), sqrt((pow(t_0, 2.0) - (t_3 * cos(phi1))))) * 2.0) * R;
} else if (t_1 <= 5e-55) {
tmp = (atan2(sqrt(fma(cos(phi1), ((fma(0.25, lambda1, (-0.5 * lambda2)) * cos(phi2)) * lambda1), pow(sin(t_4), 2.0))), sqrt((1.0 - (pow(sin(((phi1 - phi2) / 2.0)), 2.0) + t_2)))) * 2.0) * R;
} else {
tmp = (atan2(sqrt(fma(t_3, cos(phi1), pow(sin((phi1 * 0.5)), 2.0))), sqrt(fma(t_0, t_0, (-cos(phi1) * t_3)))) * 2.0) * R;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(-0.5 * phi1)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(Float64(Float64(cos(phi2) * cos(phi1)) * t_1) * t_1) t_3 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_4 = Float64(Float64(phi1 - phi2) * 0.5) tmp = 0.0 if (t_1 <= -4e-26) tmp = Float64(Float64(atan(sqrt(Float64(t_2 - Float64(Float64(cos(Float64(t_4 * 2.0)) * 0.5) - 0.5))), sqrt(Float64((t_0 ^ 2.0) - Float64(t_3 * cos(phi1))))) * 2.0) * R); elseif (t_1 <= 5e-55) tmp = Float64(Float64(atan(sqrt(fma(cos(phi1), Float64(Float64(fma(0.25, lambda1, Float64(-0.5 * lambda2)) * cos(phi2)) * lambda1), (sin(t_4) ^ 2.0))), sqrt(Float64(1.0 - Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + t_2)))) * 2.0) * R); else tmp = Float64(Float64(atan(sqrt(fma(t_3, cos(phi1), (sin(Float64(phi1 * 0.5)) ^ 2.0))), sqrt(fma(t_0, t_0, Float64(Float64(-cos(phi1)) * t_3)))) * 2.0) * R); 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[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[(N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] * t$95$1), $MachinePrecision] * t$95$1), $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[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]}, If[LessEqual[t$95$1, -4e-26], N[(N[(N[ArcTan[N[Sqrt[N[(t$95$2 - N[(N[(N[Cos[N[(t$95$4 * 2.0), $MachinePrecision]], $MachinePrecision] * 0.5), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[t$95$0, 2.0], $MachinePrecision] - N[(t$95$3 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], If[LessEqual[t$95$1, 5e-55], N[(N[(N[ArcTan[N[Sqrt[N[(N[Cos[phi1], $MachinePrecision] * N[(N[(N[(0.25 * lambda1 + N[(-0.5 * lambda2), $MachinePrecision]), $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * lambda1), $MachinePrecision] + N[Power[N[Sin[t$95$4], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], N[(N[(N[ArcTan[N[Sqrt[N[(t$95$3 * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(t$95$0 * t$95$0 + N[((-N[Cos[phi1], $MachinePrecision]) * t$95$3), $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)\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \left(\left(\cos \phi_2 \cdot \cos \phi_1\right) \cdot t\_1\right) \cdot t\_1\\
t_3 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_4 := \left(\phi_1 - \phi_2\right) \cdot 0.5\\
\mathbf{if}\;t\_1 \leq -4 \cdot 10^{-26}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{t\_2 - \left(\cos \left(t\_4 \cdot 2\right) \cdot 0.5 - 0.5\right)}}{\sqrt{{t\_0}^{2} - t\_3 \cdot \cos \phi_1}} \cdot 2\right) \cdot R\\
\mathbf{elif}\;t\_1 \leq 5 \cdot 10^{-55}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_1, \left(\mathsf{fma}\left(0.25, \lambda_1, -0.5 \cdot \lambda_2\right) \cdot \cos \phi_2\right) \cdot \lambda_1, {\sin t\_4}^{2}\right)}}{\sqrt{1 - \left({\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_2\right)}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_3, \cos \phi_1, {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}{\sqrt{\mathsf{fma}\left(t\_0, t\_0, \left(-\cos \phi_1\right) \cdot t\_3\right)}} \cdot 2\right) \cdot R\\
\end{array}
\end{array}
if (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < -4.0000000000000002e-26Initial program 60.8%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites48.3%
lift-pow.f64N/A
unpow2N/A
lift-sin.f64N/A
lift-sin.f64N/A
sqr-sin-aN/A
lower--.f64N/A
cos-2N/A
cos-sumN/A
lower-*.f64N/A
cos-sumN/A
cos-2N/A
lower-cos.f64N/A
lower-*.f6448.2
lift-/.f64N/A
div-invN/A
metadata-evalN/A
*-commutativeN/A
lower-*.f6448.2
Applied rewrites48.2%
if -4.0000000000000002e-26 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < 5.0000000000000002e-55Initial program 81.8%
Taylor expanded in lambda2 around 0
Applied rewrites81.8%
Taylor expanded in lambda1 around 0
Applied rewrites81.8%
if 5.0000000000000002e-55 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) Initial program 56.4%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites45.9%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6446.5
Applied rewrites46.5%
Applied rewrites46.5%
Final simplification53.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (* -0.5 phi1)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0)))
(t_2 (* (* (* (cos phi2) (cos phi1)) t_1) t_1))
(t_3 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_4 (* (- phi1 phi2) 0.5)))
(if (<= t_1 -1e-36)
(*
(*
(atan2
(sqrt (- t_2 (- (* (cos (* t_4 2.0)) 0.5) 0.5)))
(sqrt (- (pow t_0 2.0) (* t_3 (cos phi1)))))
2.0)
R)
(if (<= t_1 5e-55)
(*
(*
(atan2
(sqrt
(fma
(cos phi1)
(* (* (* lambda2 (cos phi2)) -0.5) lambda1)
(pow (sin t_4) 2.0)))
(sqrt (- 1.0 (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) t_2))))
2.0)
R)
(*
(*
(atan2
(sqrt (fma t_3 (cos phi1) (pow (sin (* phi1 0.5)) 2.0)))
(sqrt (fma t_0 t_0 (* (- (cos phi1)) t_3))))
2.0)
R)))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((-0.5 * phi1));
double t_1 = sin(((lambda1 - lambda2) / 2.0));
double t_2 = ((cos(phi2) * cos(phi1)) * t_1) * t_1;
double t_3 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_4 = (phi1 - phi2) * 0.5;
double tmp;
if (t_1 <= -1e-36) {
tmp = (atan2(sqrt((t_2 - ((cos((t_4 * 2.0)) * 0.5) - 0.5))), sqrt((pow(t_0, 2.0) - (t_3 * cos(phi1))))) * 2.0) * R;
} else if (t_1 <= 5e-55) {
tmp = (atan2(sqrt(fma(cos(phi1), (((lambda2 * cos(phi2)) * -0.5) * lambda1), pow(sin(t_4), 2.0))), sqrt((1.0 - (pow(sin(((phi1 - phi2) / 2.0)), 2.0) + t_2)))) * 2.0) * R;
} else {
tmp = (atan2(sqrt(fma(t_3, cos(phi1), pow(sin((phi1 * 0.5)), 2.0))), sqrt(fma(t_0, t_0, (-cos(phi1) * t_3)))) * 2.0) * R;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(-0.5 * phi1)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) t_2 = Float64(Float64(Float64(cos(phi2) * cos(phi1)) * t_1) * t_1) t_3 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_4 = Float64(Float64(phi1 - phi2) * 0.5) tmp = 0.0 if (t_1 <= -1e-36) tmp = Float64(Float64(atan(sqrt(Float64(t_2 - Float64(Float64(cos(Float64(t_4 * 2.0)) * 0.5) - 0.5))), sqrt(Float64((t_0 ^ 2.0) - Float64(t_3 * cos(phi1))))) * 2.0) * R); elseif (t_1 <= 5e-55) tmp = Float64(Float64(atan(sqrt(fma(cos(phi1), Float64(Float64(Float64(lambda2 * cos(phi2)) * -0.5) * lambda1), (sin(t_4) ^ 2.0))), sqrt(Float64(1.0 - Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + t_2)))) * 2.0) * R); else tmp = Float64(Float64(atan(sqrt(fma(t_3, cos(phi1), (sin(Float64(phi1 * 0.5)) ^ 2.0))), sqrt(fma(t_0, t_0, Float64(Float64(-cos(phi1)) * t_3)))) * 2.0) * R); 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[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[(N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] * t$95$1), $MachinePrecision] * t$95$1), $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[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]}, If[LessEqual[t$95$1, -1e-36], N[(N[(N[ArcTan[N[Sqrt[N[(t$95$2 - N[(N[(N[Cos[N[(t$95$4 * 2.0), $MachinePrecision]], $MachinePrecision] * 0.5), $MachinePrecision] - 0.5), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[t$95$0, 2.0], $MachinePrecision] - N[(t$95$3 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], If[LessEqual[t$95$1, 5e-55], N[(N[(N[ArcTan[N[Sqrt[N[(N[Cos[phi1], $MachinePrecision] * N[(N[(N[(lambda2 * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * -0.5), $MachinePrecision] * lambda1), $MachinePrecision] + N[Power[N[Sin[t$95$4], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$2), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], N[(N[(N[ArcTan[N[Sqrt[N[(t$95$3 * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(t$95$0 * t$95$0 + N[((-N[Cos[phi1], $MachinePrecision]) * t$95$3), $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)\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
t_2 := \left(\left(\cos \phi_2 \cdot \cos \phi_1\right) \cdot t\_1\right) \cdot t\_1\\
t_3 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_4 := \left(\phi_1 - \phi_2\right) \cdot 0.5\\
\mathbf{if}\;t\_1 \leq -1 \cdot 10^{-36}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{t\_2 - \left(\cos \left(t\_4 \cdot 2\right) \cdot 0.5 - 0.5\right)}}{\sqrt{{t\_0}^{2} - t\_3 \cdot \cos \phi_1}} \cdot 2\right) \cdot R\\
\mathbf{elif}\;t\_1 \leq 5 \cdot 10^{-55}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_1, \left(\left(\lambda_2 \cdot \cos \phi_2\right) \cdot -0.5\right) \cdot \lambda_1, {\sin t\_4}^{2}\right)}}{\sqrt{1 - \left({\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_2\right)}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_3, \cos \phi_1, {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\right)}}{\sqrt{\mathsf{fma}\left(t\_0, t\_0, \left(-\cos \phi_1\right) \cdot t\_3\right)}} \cdot 2\right) \cdot R\\
\end{array}
\end{array}
if (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < -9.9999999999999994e-37Initial program 62.2%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites49.4%
lift-pow.f64N/A
unpow2N/A
lift-sin.f64N/A
lift-sin.f64N/A
sqr-sin-aN/A
lower--.f64N/A
cos-2N/A
cos-sumN/A
lower-*.f64N/A
cos-sumN/A
cos-2N/A
lower-cos.f64N/A
lower-*.f6449.4
lift-/.f64N/A
div-invN/A
metadata-evalN/A
*-commutativeN/A
lower-*.f6449.4
Applied rewrites49.4%
if -9.9999999999999994e-37 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) < 5.0000000000000002e-55Initial program 80.2%
Taylor expanded in lambda2 around 0
Applied rewrites80.2%
Taylor expanded in lambda1 around 0
Applied rewrites77.9%
if 5.0000000000000002e-55 < (sin.f64 (/.f64 (-.f64 lambda1 lambda2) #s(literal 2 binary64))) Initial program 56.4%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites45.9%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6446.5
Applied rewrites46.5%
Applied rewrites46.5%
Final simplification52.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* (- lambda1 lambda2) 0.5)))
(t_1 (sin (/ (- lambda1 lambda2) 2.0))))
(*
(*
(atan2
(sqrt
(+
(pow (sin (/ (- phi1 phi2) 2.0)) 2.0)
(* (* (* (cos phi2) (cos phi1)) t_1) t_1)))
(sqrt
(-
(pow (cos (/ (- phi1 phi2) -2.0)) 2.0)
(* (* (* t_0 (cos phi1)) (cos phi2)) t_0))))
2.0)
R)))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin(((lambda1 - lambda2) * 0.5));
double t_1 = sin(((lambda1 - lambda2) / 2.0));
return (atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + (((cos(phi2) * cos(phi1)) * t_1) * t_1))), sqrt((pow(cos(((phi1 - phi2) / -2.0)), 2.0) - (((t_0 * cos(phi1)) * cos(phi2)) * 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 = sin(((lambda1 - lambda2) * 0.5d0))
t_1 = sin(((lambda1 - lambda2) / 2.0d0))
code = (atan2(sqrt(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + (((cos(phi2) * cos(phi1)) * t_1) * t_1))), sqrt(((cos(((phi1 - phi2) / (-2.0d0))) ** 2.0d0) - (((t_0 * cos(phi1)) * cos(phi2)) * 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.sin(((lambda1 - lambda2) * 0.5));
double t_1 = Math.sin(((lambda1 - lambda2) / 2.0));
return (Math.atan2(Math.sqrt((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((Math.cos(phi2) * Math.cos(phi1)) * t_1) * t_1))), Math.sqrt((Math.pow(Math.cos(((phi1 - phi2) / -2.0)), 2.0) - (((t_0 * Math.cos(phi1)) * Math.cos(phi2)) * t_0)))) * 2.0) * R;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.sin(((lambda1 - lambda2) * 0.5)) t_1 = math.sin(((lambda1 - lambda2) / 2.0)) return (math.atan2(math.sqrt((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + (((math.cos(phi2) * math.cos(phi1)) * t_1) * t_1))), math.sqrt((math.pow(math.cos(((phi1 - phi2) / -2.0)), 2.0) - (((t_0 * math.cos(phi1)) * math.cos(phi2)) * t_0)))) * 2.0) * R
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) t_1 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) return Float64(Float64(atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + Float64(Float64(Float64(cos(phi2) * cos(phi1)) * t_1) * t_1))), sqrt(Float64((cos(Float64(Float64(phi1 - phi2) / -2.0)) ^ 2.0) - Float64(Float64(Float64(t_0 * cos(phi1)) * cos(phi2)) * t_0)))) * 2.0) * R) end
function tmp = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((lambda1 - lambda2) * 0.5)); t_1 = sin(((lambda1 - lambda2) / 2.0)); tmp = (atan2(sqrt(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + (((cos(phi2) * cos(phi1)) * t_1) * t_1))), sqrt(((cos(((phi1 - phi2) / -2.0)) ^ 2.0) - (((t_0 * cos(phi1)) * cos(phi2)) * t_0)))) * 2.0) * R; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$1 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, N[(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$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[(N[(t$95$0 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] * N[Cos[phi2], $MachinePrecision]), $MachinePrecision] * t$95$0), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)\\
t_1 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\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\_1\right) \cdot t\_1}}{\sqrt{{\cos \left(\frac{\phi_1 - \phi_2}{-2}\right)}^{2} - \left(\left(t\_0 \cdot \cos \phi_1\right) \cdot \cos \phi_2\right) \cdot t\_0}} \cdot 2\right) \cdot R
\end{array}
\end{array}
Initial program 62.8%
lift--.f64N/A
lift-+.f64N/A
associate--r+N/A
lift-*.f64N/A
cancel-sign-sub-invN/A
lower-+.f64N/A
Applied rewrites62.8%
Final simplification62.8%
(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_0 t_1)))))))
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_0 * t_1))));
}
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_0 * t_1))))) 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$0 * t$95$1), $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\_0 \cdot t\_1}}
\end{array}
\end{array}
Initial program 62.8%
Applied rewrites62.8%
Final simplification62.8%
(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 62.8%
Taylor expanded in lambda1 around 0
Applied rewrites62.7%
Final simplification62.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (/ (- phi1 phi2) 2.0)) 2.0))
(t_1 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_2
(*
(*
(atan2
(sqrt
(+
(/ (* (+ (cos (+ phi1 phi2)) (cos (- phi1 phi2))) t_1) 2.0)
t_0))
(sqrt (- (pow (cos (* -0.5 phi1)) 2.0) (* t_1 (cos phi1)))))
2.0)
R))
(t_3 (sin (/ (- lambda1 lambda2) 2.0))))
(if (<= phi1 -0.0016)
t_2
(if (<= phi1 4.5e-6)
(*
(*
(atan2
(sqrt (+ t_0 (* (* (* (cos phi2) (cos phi1)) t_3) t_3)))
(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 = pow(sin(((phi1 - phi2) / 2.0)), 2.0);
double t_1 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_2 = (atan2(sqrt(((((cos((phi1 + phi2)) + cos((phi1 - phi2))) * t_1) / 2.0) + t_0)), sqrt((pow(cos((-0.5 * phi1)), 2.0) - (t_1 * cos(phi1))))) * 2.0) * R;
double t_3 = sin(((lambda1 - lambda2) / 2.0));
double tmp;
if (phi1 <= -0.0016) {
tmp = t_2;
} else if (phi1 <= 4.5e-6) {
tmp = (atan2(sqrt((t_0 + (((cos(phi2) * cos(phi1)) * t_3) * t_3))), sqrt((pow(cos((phi2 * 0.5)), 2.0) - (t_1 * cos(phi2))))) * 2.0) * R;
} else {
tmp = t_2;
}
return tmp;
}
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
real(8) :: t_2
real(8) :: t_3
real(8) :: tmp
t_0 = sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0
t_1 = sin(((lambda1 - lambda2) * 0.5d0)) ** 2.0d0
t_2 = (atan2(sqrt(((((cos((phi1 + phi2)) + cos((phi1 - phi2))) * t_1) / 2.0d0) + t_0)), sqrt(((cos(((-0.5d0) * phi1)) ** 2.0d0) - (t_1 * cos(phi1))))) * 2.0d0) * r
t_3 = sin(((lambda1 - lambda2) / 2.0d0))
if (phi1 <= (-0.0016d0)) then
tmp = t_2
else if (phi1 <= 4.5d-6) then
tmp = (atan2(sqrt((t_0 + (((cos(phi2) * cos(phi1)) * t_3) * t_3))), sqrt(((cos((phi2 * 0.5d0)) ** 2.0d0) - (t_1 * cos(phi2))))) * 2.0d0) * r
else
tmp = t_2
end if
code = tmp
end function
public static double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0);
double t_1 = Math.pow(Math.sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_2 = (Math.atan2(Math.sqrt(((((Math.cos((phi1 + phi2)) + Math.cos((phi1 - phi2))) * t_1) / 2.0) + t_0)), Math.sqrt((Math.pow(Math.cos((-0.5 * phi1)), 2.0) - (t_1 * Math.cos(phi1))))) * 2.0) * R;
double t_3 = Math.sin(((lambda1 - lambda2) / 2.0));
double tmp;
if (phi1 <= -0.0016) {
tmp = t_2;
} else if (phi1 <= 4.5e-6) {
tmp = (Math.atan2(Math.sqrt((t_0 + (((Math.cos(phi2) * Math.cos(phi1)) * t_3) * t_3))), Math.sqrt((Math.pow(Math.cos((phi2 * 0.5)), 2.0) - (t_1 * Math.cos(phi2))))) * 2.0) * R;
} else {
tmp = t_2;
}
return tmp;
}
def code(R, lambda1, lambda2, phi1, phi2): t_0 = math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) t_1 = math.pow(math.sin(((lambda1 - lambda2) * 0.5)), 2.0) t_2 = (math.atan2(math.sqrt(((((math.cos((phi1 + phi2)) + math.cos((phi1 - phi2))) * t_1) / 2.0) + t_0)), math.sqrt((math.pow(math.cos((-0.5 * phi1)), 2.0) - (t_1 * math.cos(phi1))))) * 2.0) * R t_3 = math.sin(((lambda1 - lambda2) / 2.0)) tmp = 0 if phi1 <= -0.0016: tmp = t_2 elif phi1 <= 4.5e-6: tmp = (math.atan2(math.sqrt((t_0 + (((math.cos(phi2) * math.cos(phi1)) * t_3) * t_3))), math.sqrt((math.pow(math.cos((phi2 * 0.5)), 2.0) - (t_1 * math.cos(phi2))))) * 2.0) * R else: tmp = t_2 return tmp
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0 t_1 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_2 = Float64(Float64(atan(sqrt(Float64(Float64(Float64(Float64(cos(Float64(phi1 + phi2)) + cos(Float64(phi1 - phi2))) * t_1) / 2.0) + t_0)), sqrt(Float64((cos(Float64(-0.5 * phi1)) ^ 2.0) - Float64(t_1 * cos(phi1))))) * 2.0) * R) t_3 = sin(Float64(Float64(lambda1 - lambda2) / 2.0)) tmp = 0.0 if (phi1 <= -0.0016) tmp = t_2; elseif (phi1 <= 4.5e-6) tmp = Float64(Float64(atan(sqrt(Float64(t_0 + Float64(Float64(Float64(cos(phi2) * cos(phi1)) * t_3) * t_3))), 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
function tmp_2 = code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(((phi1 - phi2) / 2.0)) ^ 2.0; t_1 = sin(((lambda1 - lambda2) * 0.5)) ^ 2.0; t_2 = (atan2(sqrt(((((cos((phi1 + phi2)) + cos((phi1 - phi2))) * t_1) / 2.0) + t_0)), sqrt(((cos((-0.5 * phi1)) ^ 2.0) - (t_1 * cos(phi1))))) * 2.0) * R; t_3 = sin(((lambda1 - lambda2) / 2.0)); tmp = 0.0; if (phi1 <= -0.0016) tmp = t_2; elseif (phi1 <= 4.5e-6) tmp = (atan2(sqrt((t_0 + (((cos(phi2) * cos(phi1)) * t_3) * t_3))), sqrt(((cos((phi2 * 0.5)) ^ 2.0) - (t_1 * cos(phi2))))) * 2.0) * R; else tmp = t_2; end tmp_2 = tmp; end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $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[(N[(N[(N[Cos[N[(phi1 + phi2), $MachinePrecision]], $MachinePrecision] + N[Cos[N[(phi1 - phi2), $MachinePrecision]], $MachinePrecision]), $MachinePrecision] * t$95$1), $MachinePrecision] / 2.0), $MachinePrecision] + t$95$0), $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]}, Block[{t$95$3 = N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision]}, If[LessEqual[phi1, -0.0016], t$95$2, If[LessEqual[phi1, 4.5e-6], N[(N[(N[ArcTan[N[Sqrt[N[(t$95$0 + N[(N[(N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] * t$95$3), $MachinePrecision] * t$95$3), $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{\phi_1 - \phi_2}{2}\right)}^{2}\\
t_1 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_2 := \left(\tan^{-1}_* \frac{\sqrt{\frac{\left(\cos \left(\phi_1 + \phi_2\right) + \cos \left(\phi_1 - \phi_2\right)\right) \cdot t\_1}{2} + t\_0}}{\sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - t\_1 \cdot \cos \phi_1}} \cdot 2\right) \cdot R\\
t_3 := \sin \left(\frac{\lambda_1 - \lambda_2}{2}\right)\\
\mathbf{if}\;\phi_1 \leq -0.0016:\\
\;\;\;\;t\_2\\
\mathbf{elif}\;\phi_1 \leq 4.5 \cdot 10^{-6}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{t\_0 + \left(\left(\cos \phi_2 \cdot \cos \phi_1\right) \cdot t\_3\right) \cdot t\_3}}{\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 < -0.00160000000000000008 or 4.50000000000000011e-6 < phi1 Initial program 48.8%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites49.7%
lift-*.f64N/A
lift-*.f64N/A
associate-*l*N/A
lift-*.f64N/A
lift-cos.f64N/A
lift-cos.f64N/A
cos-multN/A
pow2N/A
lift-/.f64N/A
div-invN/A
metadata-evalN/A
lift-*.f64N/A
lift-pow.f64N/A
associate-*l/N/A
lower-/.f64N/A
Applied rewrites50.8%
if -0.00160000000000000008 < phi1 < 4.50000000000000011e-6Initial program 79.1%
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
*-commutativeN/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites79.1%
Final simplification63.8%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_1 (* t_0 (cos phi1)))
(t_2 (pow (sin (* (- phi1 phi2) 0.5)) 2.0))
(t_3
(*
(*
(atan2
(sqrt
(fma
(* (cos phi2) (cos phi1))
(pow (sin (* lambda1 0.5)) 2.0)
t_2))
(sqrt (- 1.0 (fma t_0 (cos phi2) (pow (sin (* -0.5 phi2)) 2.0)))))
2.0)
R)))
(if (<= phi2 -2.7e+57)
t_3
(if (<= phi2 0.007)
(*
(*
(atan2
(sqrt (fma (cos phi2) t_1 t_2))
(sqrt (- (pow (cos (* -0.5 phi1)) 2.0) t_1)))
2.0)
R)
t_3))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_1 = t_0 * cos(phi1);
double t_2 = pow(sin(((phi1 - phi2) * 0.5)), 2.0);
double t_3 = (atan2(sqrt(fma((cos(phi2) * cos(phi1)), pow(sin((lambda1 * 0.5)), 2.0), t_2)), sqrt((1.0 - fma(t_0, cos(phi2), pow(sin((-0.5 * phi2)), 2.0))))) * 2.0) * R;
double tmp;
if (phi2 <= -2.7e+57) {
tmp = t_3;
} else if (phi2 <= 0.007) {
tmp = (atan2(sqrt(fma(cos(phi2), t_1, t_2)), sqrt((pow(cos((-0.5 * phi1)), 2.0) - t_1))) * 2.0) * R;
} else {
tmp = t_3;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_1 = Float64(t_0 * cos(phi1)) t_2 = sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0 t_3 = Float64(Float64(atan(sqrt(fma(Float64(cos(phi2) * cos(phi1)), (sin(Float64(lambda1 * 0.5)) ^ 2.0), t_2)), sqrt(Float64(1.0 - fma(t_0, cos(phi2), (sin(Float64(-0.5 * phi2)) ^ 2.0))))) * 2.0) * R) tmp = 0.0 if (phi2 <= -2.7e+57) tmp = t_3; elseif (phi2 <= 0.007) tmp = Float64(Float64(atan(sqrt(fma(cos(phi2), t_1, t_2)), sqrt(Float64((cos(Float64(-0.5 * phi1)) ^ 2.0) - t_1))) * 2.0) * R); else tmp = t_3; end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[(t$95$0 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$3 = N[(N[(N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] * N[Power[N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$2), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]}, If[LessEqual[phi2, -2.7e+57], t$95$3, If[LessEqual[phi2, 0.007], N[(N[(N[ArcTan[N[Sqrt[N[(N[Cos[phi2], $MachinePrecision] * t$95$1 + t$95$2), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], t$95$3]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_1 := t\_0 \cdot \cos \phi_1\\
t_2 := {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\\
t_3 := \left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_2 \cdot \cos \phi_1, {\sin \left(\lambda_1 \cdot 0.5\right)}^{2}, t\_2\right)}}{\sqrt{1 - \mathsf{fma}\left(t\_0, \cos \phi_2, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)}} \cdot 2\right) \cdot R\\
\mathbf{if}\;\phi_2 \leq -2.7 \cdot 10^{+57}:\\
\;\;\;\;t\_3\\
\mathbf{elif}\;\phi_2 \leq 0.007:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_2, t\_1, t\_2\right)}}{\sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - t\_1}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;t\_3\\
\end{array}
\end{array}
if phi2 < -2.6999999999999998e57 or 0.00700000000000000015 < phi2 Initial program 49.0%
Taylor expanded in lambda2 around 0
associate-*r*N/A
lower-fma.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
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--.f6440.1
Applied rewrites40.1%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-fma.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6441.2
Applied rewrites41.2%
if -2.6999999999999998e57 < phi2 < 0.00700000000000000015Initial program 73.7%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites72.5%
lift-+.f64N/A
+-commutativeN/A
lift-*.f64N/A
Applied rewrites72.5%
Final simplification58.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_1 (* t_0 (cos phi1)))
(t_2
(*
(*
(atan2
(sqrt
(fma
(* (cos phi2) (cos phi1))
(pow (sin (* lambda1 0.5)) 2.0)
(pow (sin (* (- phi1 phi2) 0.5)) 2.0)))
(sqrt (- 1.0 (fma t_0 (cos phi2) (pow (sin (* -0.5 phi2)) 2.0)))))
2.0)
R)))
(if (<= phi2 -3.3e-7)
t_2
(if (<= phi2 0.007)
(*
(*
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) t_1))
(sqrt (- (pow (cos (* -0.5 phi1)) 2.0) t_1)))
2.0)
R)
t_2))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_1 = t_0 * cos(phi1);
double t_2 = (atan2(sqrt(fma((cos(phi2) * cos(phi1)), pow(sin((lambda1 * 0.5)), 2.0), pow(sin(((phi1 - phi2) * 0.5)), 2.0))), sqrt((1.0 - fma(t_0, cos(phi2), pow(sin((-0.5 * phi2)), 2.0))))) * 2.0) * R;
double tmp;
if (phi2 <= -3.3e-7) {
tmp = t_2;
} else if (phi2 <= 0.007) {
tmp = (atan2(sqrt((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + t_1)), sqrt((pow(cos((-0.5 * phi1)), 2.0) - t_1))) * 2.0) * R;
} else {
tmp = t_2;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_1 = Float64(t_0 * cos(phi1)) t_2 = Float64(Float64(atan(sqrt(fma(Float64(cos(phi2) * cos(phi1)), (sin(Float64(lambda1 * 0.5)) ^ 2.0), (sin(Float64(Float64(phi1 - phi2) * 0.5)) ^ 2.0))), sqrt(Float64(1.0 - fma(t_0, cos(phi2), (sin(Float64(-0.5 * phi2)) ^ 2.0))))) * 2.0) * R) tmp = 0.0 if (phi2 <= -3.3e-7) tmp = t_2; elseif (phi2 <= 0.007) tmp = Float64(Float64(atan(sqrt(Float64((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + t_1)), sqrt(Float64((cos(Float64(-0.5 * phi1)) ^ 2.0) - t_1))) * 2.0) * R); else tmp = t_2; end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]}, Block[{t$95$1 = N[(t$95$0 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]}, Block[{t$95$2 = N[(N[(N[ArcTan[N[Sqrt[N[(N[(N[Cos[phi2], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision] * N[Power[N[Sin[N[(lambda1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - N[(t$95$0 * N[Cos[phi2], $MachinePrecision] + N[Power[N[Sin[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]}, If[LessEqual[phi2, -3.3e-7], t$95$2, If[LessEqual[phi2, 0.007], 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$1), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], t$95$2]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2}\\
t_1 := t\_0 \cdot \cos \phi_1\\
t_2 := \left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(\cos \phi_2 \cdot \cos \phi_1, {\sin \left(\lambda_1 \cdot 0.5\right)}^{2}, {\sin \left(\left(\phi_1 - \phi_2\right) \cdot 0.5\right)}^{2}\right)}}{\sqrt{1 - \mathsf{fma}\left(t\_0, \cos \phi_2, {\sin \left(-0.5 \cdot \phi_2\right)}^{2}\right)}} \cdot 2\right) \cdot R\\
\mathbf{if}\;\phi_2 \leq -3.3 \cdot 10^{-7}:\\
\;\;\;\;t\_2\\
\mathbf{elif}\;\phi_2 \leq 0.007:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_1}}{\sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - t\_1}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;t\_2\\
\end{array}
\end{array}
if phi2 < -3.3000000000000002e-7 or 0.00700000000000000015 < phi2 Initial program 47.6%
Taylor expanded in lambda2 around 0
associate-*r*N/A
lower-fma.f64N/A
*-commutativeN/A
lower-*.f64N/A
lower-cos.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
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--.f6438.2
Applied rewrites38.2%
Taylor expanded in phi1 around 0
*-commutativeN/A
lower-fma.f64N/A
sub-negN/A
mul-1-negN/A
lower-pow.f64N/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6439.2
Applied rewrites39.2%
if -3.3000000000000002e-7 < phi2 < 0.00700000000000000015Initial program 78.0%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites78.1%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-*.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f6478.1
Applied rewrites78.1%
Final simplification58.6%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (* (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0) (cos phi1))))
(*
(*
(atan2
(sqrt (+ (pow (sin (/ (- phi1 phi2) 2.0)) 2.0) t_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((pow(sin(((phi1 - phi2) / 2.0)), 2.0) + t_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(((sin(((phi1 - phi2) / 2.0d0)) ** 2.0d0) + t_0)), 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((Math.pow(Math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_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((math.pow(math.sin(((phi1 - phi2) / 2.0)), 2.0) + t_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((sin(Float64(Float64(phi1 - phi2) / 2.0)) ^ 2.0) + t_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(((sin(((phi1 - phi2) / 2.0)) ^ 2.0) + t_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[(N[Power[N[Sin[N[(N[(phi1 - phi2), $MachinePrecision] / 2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] + t$95$0), $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{{\sin \left(\frac{\phi_1 - \phi_2}{2}\right)}^{2} + t\_0}}{\sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - t\_0}} \cdot 2\right) \cdot R
\end{array}
\end{array}
Initial program 62.8%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites49.4%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-*.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f6449.4
Applied rewrites49.4%
Final simplification49.4%
(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 -1.15e-6)
t_3
(if (<= lambda1 1.32e-5)
(*
(*
(atan2
(sqrt (fma t_2 (cos phi1) t_0))
(sqrt (- t_1 (* (pow (sin (* -0.5 lambda2)) 2.0) (cos phi1)))))
2.0)
R)
t_3))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = pow(sin((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 <= -1.15e-6) {
tmp = t_3;
} else if (lambda1 <= 1.32e-5) {
tmp = (atan2(sqrt(fma(t_2, cos(phi1), t_0)), sqrt((t_1 - (pow(sin((-0.5 * lambda2)), 2.0) * cos(phi1))))) * 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 <= -1.15e-6) tmp = t_3; elseif (lambda1 <= 1.32e-5) tmp = Float64(Float64(atan(sqrt(fma(t_2, cos(phi1), t_0)), sqrt(Float64(t_1 - Float64((sin(Float64(-0.5 * lambda2)) ^ 2.0) * cos(phi1))))) * 2.0) * R); else tmp = t_3; end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Power[N[Sin[N[(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, -1.15e-6], t$95$3, If[LessEqual[lambda1, 1.32e-5], N[(N[(N[ArcTan[N[Sqrt[N[(t$95$2 * N[Cos[phi1], $MachinePrecision] + t$95$0), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(t$95$1 - N[(N[Power[N[Sin[N[(-0.5 * lambda2), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], t$95$3]]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\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 -1.15 \cdot 10^{-6}:\\
\;\;\;\;t\_3\\
\mathbf{elif}\;\lambda_1 \leq 1.32 \cdot 10^{-5}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_2, \cos \phi_1, t\_0\right)}}{\sqrt{t\_1 - {\sin \left(-0.5 \cdot \lambda_2\right)}^{2} \cdot \cos \phi_1}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;t\_3\\
\end{array}
\end{array}
if lambda1 < -1.15e-6 or 1.32000000000000007e-5 < lambda1 Initial program 50.0%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites40.9%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6441.3
Applied rewrites41.3%
Taylor expanded in lambda2 around 0
Applied rewrites40.9%
if -1.15e-6 < lambda1 < 1.32000000000000007e-5Initial program 76.8%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites58.8%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6455.8
Applied rewrites55.8%
Taylor expanded in lambda1 around 0
Applied rewrites55.8%
Final simplification48.0%
(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 (* -0.5 lambda2)) 2.0) (cos phi1) t_0))
(sqrt (- t_1 (* t_2 (cos phi1)))))
2.0)
R)))
(if (<= lambda2 -0.00041)
t_3
(if (<= lambda2 0.0275)
(*
(*
(atan2
(sqrt (fma t_2 (cos phi1) t_0))
(sqrt (fma (- (cos phi1)) (pow (sin (* lambda1 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((-0.5 * lambda2)), 2.0), cos(phi1), t_0)), sqrt((t_1 - (t_2 * cos(phi1))))) * 2.0) * R;
double tmp;
if (lambda2 <= -0.00041) {
tmp = t_3;
} else if (lambda2 <= 0.0275) {
tmp = (atan2(sqrt(fma(t_2, cos(phi1), t_0)), sqrt(fma(-cos(phi1), pow(sin((lambda1 * 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(-0.5 * lambda2)) ^ 2.0), cos(phi1), t_0)), sqrt(Float64(t_1 - Float64(t_2 * cos(phi1))))) * 2.0) * R) tmp = 0.0 if (lambda2 <= -0.00041) tmp = t_3; elseif (lambda2 <= 0.0275) tmp = Float64(Float64(atan(sqrt(fma(t_2, cos(phi1), t_0)), sqrt(fma(Float64(-cos(phi1)), (sin(Float64(lambda1 * 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[(-0.5 * lambda2), $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[lambda2, -0.00041], t$95$3, If[LessEqual[lambda2, 0.0275], 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[(lambda1 * 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(-0.5 \cdot \lambda_2\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_2 \leq -0.00041:\\
\;\;\;\;t\_3\\
\mathbf{elif}\;\lambda_2 \leq 0.0275:\\
\;\;\;\;\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_1 \cdot 0.5\right)}^{2}, t\_1\right)}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;t\_3\\
\end{array}
\end{array}
if lambda2 < -4.0999999999999999e-4 or 0.0275000000000000001 < lambda2 Initial program 48.1%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites39.3%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6439.3
Applied rewrites39.3%
Taylor expanded in lambda1 around 0
Applied rewrites38.7%
if -4.0999999999999999e-4 < lambda2 < 0.0275000000000000001Initial program 77.5%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites59.6%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6457.1
Applied rewrites57.1%
Taylor expanded in lambda2 around 0
Applied rewrites57.1%
Final simplification47.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (pow (sin (* phi1 0.5)) 2.0))
(t_1
(sqrt
(-
(pow (cos (* -0.5 phi1)) 2.0)
(* (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0) (cos phi1)))))
(t_2
(*
(*
(atan2
(sqrt (fma (pow (sin (* -0.5 lambda2)) 2.0) (cos phi1) t_0))
t_1)
2.0)
R)))
(if (<= lambda2 -2e-17)
t_2
(if (<= lambda2 3.5e-39)
(*
(*
(atan2
(sqrt (fma (pow (sin (* lambda1 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((pow(cos((-0.5 * phi1)), 2.0) - (pow(sin(((lambda1 - lambda2) * 0.5)), 2.0) * cos(phi1))));
double t_2 = (atan2(sqrt(fma(pow(sin((-0.5 * lambda2)), 2.0), cos(phi1), t_0)), t_1) * 2.0) * R;
double tmp;
if (lambda2 <= -2e-17) {
tmp = t_2;
} else if (lambda2 <= 3.5e-39) {
tmp = (atan2(sqrt(fma(pow(sin((lambda1 * 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((cos(Float64(-0.5 * phi1)) ^ 2.0) - Float64((sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0) * cos(phi1)))) t_2 = Float64(Float64(atan(sqrt(fma((sin(Float64(-0.5 * lambda2)) ^ 2.0), cos(phi1), t_0)), t_1) * 2.0) * R) tmp = 0.0 if (lambda2 <= -2e-17) tmp = t_2; elseif (lambda2 <= 3.5e-39) tmp = Float64(Float64(atan(sqrt(fma((sin(Float64(lambda1 * 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[(N[Power[N[Cos[N[(-0.5 * phi1), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] - N[(N[Power[N[Sin[N[(N[(lambda1 - lambda2), $MachinePrecision] * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision] * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]}, Block[{t$95$2 = N[(N[(N[ArcTan[N[Sqrt[N[(N[Power[N[Sin[N[(-0.5 * lambda2), $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[lambda2, -2e-17], t$95$2, If[LessEqual[lambda2, 3.5e-39], 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], t$95$2]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := {\sin \left(\phi_1 \cdot 0.5\right)}^{2}\\
t_1 := \sqrt{{\cos \left(-0.5 \cdot \phi_1\right)}^{2} - {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{2} \cdot \cos \phi_1}\\
t_2 := \left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left({\sin \left(-0.5 \cdot \lambda_2\right)}^{2}, \cos \phi_1, t\_0\right)}}{t\_1} \cdot 2\right) \cdot R\\
\mathbf{if}\;\lambda_2 \leq -2 \cdot 10^{-17}:\\
\;\;\;\;t\_2\\
\mathbf{elif}\;\lambda_2 \leq 3.5 \cdot 10^{-39}:\\
\;\;\;\;\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{else}:\\
\;\;\;\;t\_2\\
\end{array}
\end{array}
if lambda2 < -2.00000000000000014e-17 or 3.5e-39 < lambda2 Initial program 49.9%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites39.6%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6439.4
Applied rewrites39.4%
Taylor expanded in lambda1 around 0
Applied rewrites38.7%
if -2.00000000000000014e-17 < lambda2 < 3.5e-39Initial program 78.1%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites61.1%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6458.7
Applied rewrites58.7%
Taylor expanded in lambda2 around 0
Applied rewrites58.4%
Final simplification47.7%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (sin (* -0.5 phi2)))
(t_1 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0))
(t_2
(*
(*
(atan2
(sqrt
(fma
(pow (sin (* -0.5 lambda2)) 2.0)
(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 -1450000.0)
t_2
(if (<= phi1 6.8e-85)
(*
(*
(atan2
(sqrt
(fma t_0 (fma (cos (* -0.5 phi2)) phi1 t_0) (* t_1 (cos phi2))))
(sqrt (- 1.0 t_1)))
2.0)
R)
t_2))))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = sin((-0.5 * phi2));
double t_1 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
double t_2 = (atan2(sqrt(fma(pow(sin((-0.5 * lambda2)), 2.0), 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 <= -1450000.0) {
tmp = t_2;
} else if (phi1 <= 6.8e-85) {
tmp = (atan2(sqrt(fma(t_0, fma(cos((-0.5 * phi2)), phi1, t_0), (t_1 * cos(phi2)))), sqrt((1.0 - t_1))) * 2.0) * R;
} else {
tmp = t_2;
}
return tmp;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = sin(Float64(-0.5 * phi2)) t_1 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 t_2 = Float64(Float64(atan(sqrt(fma((sin(Float64(-0.5 * lambda2)) ^ 2.0), 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 <= -1450000.0) tmp = t_2; elseif (phi1 <= 6.8e-85) tmp = Float64(Float64(atan(sqrt(fma(t_0, fma(cos(Float64(-0.5 * phi2)), phi1, t_0), Float64(t_1 * cos(phi2)))), sqrt(Float64(1.0 - t_1))) * 2.0) * R); else tmp = t_2; end return tmp end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Sin[N[(-0.5 * phi2), $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[(N[Power[N[Sin[N[(-0.5 * lambda2), $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$1 * N[Cos[phi1], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision]}, If[LessEqual[phi1, -1450000.0], t$95$2, If[LessEqual[phi1, 6.8e-85], N[(N[(N[ArcTan[N[Sqrt[N[(t$95$0 * N[(N[Cos[N[(-0.5 * phi2), $MachinePrecision]], $MachinePrecision] * phi1 + t$95$0), $MachinePrecision] + N[(t$95$1 * N[Cos[phi2], $MachinePrecision]), $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(1.0 - t$95$1), $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * 2.0), $MachinePrecision] * R), $MachinePrecision], t$95$2]]]]]
\begin{array}{l}
\\
\begin{array}{l}
t_0 := \sin \left(-0.5 \cdot \phi_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({\sin \left(-0.5 \cdot \lambda_2\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\_1 \cdot \cos \phi_1}} \cdot 2\right) \cdot R\\
\mathbf{if}\;\phi_1 \leq -1450000:\\
\;\;\;\;t\_2\\
\mathbf{elif}\;\phi_1 \leq 6.8 \cdot 10^{-85}:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_0, \mathsf{fma}\left(\cos \left(-0.5 \cdot \phi_2\right), \phi_1, t\_0\right), t\_1 \cdot \cos \phi_2\right)}}{\sqrt{1 - t\_1}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;t\_2\\
\end{array}
\end{array}
if phi1 < -1.45e6 or 6.8e-85 < phi1 Initial program 52.1%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites49.9%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6450.3
Applied rewrites50.3%
Taylor expanded in lambda1 around 0
Applied rewrites40.3%
if -1.45e6 < phi1 < 6.8e-85Initial program 77.4%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites48.7%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6445.3
Applied rewrites45.3%
Taylor expanded in phi1 around 0
Applied rewrites45.3%
Taylor expanded in phi1 around 0
+-commutativeN/A
associate-+r+N/A
associate-*r*N/A
unpow2N/A
distribute-rgt-outN/A
lower-fma.f64N/A
Applied rewrites48.0%
Final simplification43.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(let* ((t_0 (cos (* -0.5 phi1)))
(t_1 (pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)))
(*
(*
(atan2
(sqrt (fma t_1 (cos phi1) (pow (sin (* phi1 0.5)) 2.0)))
(sqrt (fma t_0 t_0 (* (- (cos phi1)) t_1))))
2.0)
R)))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
double t_0 = cos((-0.5 * phi1));
double t_1 = pow(sin(((lambda1 - lambda2) * 0.5)), 2.0);
return (atan2(sqrt(fma(t_1, cos(phi1), pow(sin((phi1 * 0.5)), 2.0))), sqrt(fma(t_0, t_0, (-cos(phi1) * t_1)))) * 2.0) * R;
}
function code(R, lambda1, lambda2, phi1, phi2) t_0 = cos(Float64(-0.5 * phi1)) t_1 = sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0 return Float64(Float64(atan(sqrt(fma(t_1, cos(phi1), (sin(Float64(phi1 * 0.5)) ^ 2.0))), sqrt(fma(t_0, t_0, Float64(Float64(-cos(phi1)) * t_1)))) * 2.0) * R) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := Block[{t$95$0 = N[Cos[N[(-0.5 * 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$1 * N[Cos[phi1], $MachinePrecision] + N[Power[N[Sin[N[(phi1 * 0.5), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]), $MachinePrecision]], $MachinePrecision] / N[Sqrt[N[(t$95$0 * t$95$0 + N[((-N[Cos[phi1], $MachinePrecision]) * t$95$1), $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)\\
t_1 := {\sin \left(\left(\lambda_1 - \lambda_2\right) \cdot 0.5\right)}^{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{\mathsf{fma}\left(t\_0, t\_0, \left(-\cos \phi_1\right) \cdot t\_1\right)}} \cdot 2\right) \cdot R
\end{array}
\end{array}
Initial program 62.8%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites49.4%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6448.2
Applied rewrites48.2%
Applied rewrites48.2%
Final simplification48.2%
(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 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 62.8%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites49.4%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6448.2
Applied rewrites48.2%
Final simplification48.2%
(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 (* lambda1 0.5)) 2.0) (cos phi1) t_0))
(sqrt (- 1.0 t_1)))
2.0)
R)))
(if (<= lambda1 -3.2e-20)
t_2
(if (<= lambda1 0.00145)
(*
(*
(atan2
(sqrt (fma t_1 (cos phi1) t_0))
(sqrt (- 1.0 (pow (sin (* -0.5 lambda2)) 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((lambda1 * 0.5)), 2.0), cos(phi1), t_0)), sqrt((1.0 - t_1))) * 2.0) * R;
double tmp;
if (lambda1 <= -3.2e-20) {
tmp = t_2;
} else if (lambda1 <= 0.00145) {
tmp = (atan2(sqrt(fma(t_1, cos(phi1), t_0)), sqrt((1.0 - pow(sin((-0.5 * lambda2)), 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(lambda1 * 0.5)) ^ 2.0), cos(phi1), t_0)), sqrt(Float64(1.0 - t_1))) * 2.0) * R) tmp = 0.0 if (lambda1 <= -3.2e-20) tmp = t_2; elseif (lambda1 <= 0.00145) tmp = Float64(Float64(atan(sqrt(fma(t_1, cos(phi1), t_0)), sqrt(Float64(1.0 - (sin(Float64(-0.5 * lambda2)) ^ 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[(lambda1 * 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[lambda1, -3.2e-20], t$95$2, If[LessEqual[lambda1, 0.00145], 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[(-0.5 * lambda2), $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_1 \cdot 0.5\right)}^{2}, \cos \phi_1, t\_0\right)}}{\sqrt{1 - t\_1}} \cdot 2\right) \cdot R\\
\mathbf{if}\;\lambda_1 \leq -3.2 \cdot 10^{-20}:\\
\;\;\;\;t\_2\\
\mathbf{elif}\;\lambda_1 \leq 0.00145:\\
\;\;\;\;\left(\tan^{-1}_* \frac{\sqrt{\mathsf{fma}\left(t\_1, \cos \phi_1, t\_0\right)}}{\sqrt{1 - {\sin \left(-0.5 \cdot \lambda_2\right)}^{2}}} \cdot 2\right) \cdot R\\
\mathbf{else}:\\
\;\;\;\;t\_2\\
\end{array}
\end{array}
if lambda1 < -3.1999999999999997e-20 or 0.00145 < lambda1 Initial program 50.3%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites41.4%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6441.8
Applied rewrites41.8%
Taylor expanded in phi1 around 0
Applied rewrites30.9%
Taylor expanded in lambda2 around 0
Applied rewrites30.5%
if -3.1999999999999997e-20 < lambda1 < 0.00145Initial program 77.4%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites58.8%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6455.8
Applied rewrites55.8%
Taylor expanded in phi1 around 0
Applied rewrites35.3%
Taylor expanded in lambda1 around 0
Applied rewrites35.3%
Final simplification32.7%
(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 (* -0.5 lambda2)) 2.0) (cos phi1) t_0))
t_1)
2.0)
R)))
(if (<= lambda2 -5.5e-57)
t_2
(if (<= lambda2 3.5e-39)
(*
(*
(atan2
(sqrt (fma (pow (sin (* lambda1 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((-0.5 * lambda2)), 2.0), cos(phi1), t_0)), t_1) * 2.0) * R;
double tmp;
if (lambda2 <= -5.5e-57) {
tmp = t_2;
} else if (lambda2 <= 3.5e-39) {
tmp = (atan2(sqrt(fma(pow(sin((lambda1 * 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(-0.5 * lambda2)) ^ 2.0), cos(phi1), t_0)), t_1) * 2.0) * R) tmp = 0.0 if (lambda2 <= -5.5e-57) tmp = t_2; elseif (lambda2 <= 3.5e-39) tmp = Float64(Float64(atan(sqrt(fma((sin(Float64(lambda1 * 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[(-0.5 * lambda2), $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[lambda2, -5.5e-57], t$95$2, If[LessEqual[lambda2, 3.5e-39], 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], 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(-0.5 \cdot \lambda_2\right)}^{2}, \cos \phi_1, t\_0\right)}}{t\_1} \cdot 2\right) \cdot R\\
\mathbf{if}\;\lambda_2 \leq -5.5 \cdot 10^{-57}:\\
\;\;\;\;t\_2\\
\mathbf{elif}\;\lambda_2 \leq 3.5 \cdot 10^{-39}:\\
\;\;\;\;\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{else}:\\
\;\;\;\;t\_2\\
\end{array}
\end{array}
if lambda2 < -5.50000000000000011e-57 or 3.5e-39 < lambda2 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
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites40.6%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6440.3
Applied rewrites40.3%
Taylor expanded in phi1 around 0
Applied rewrites30.6%
Taylor expanded in lambda1 around 0
Applied rewrites30.0%
if -5.50000000000000011e-57 < lambda2 < 3.5e-39Initial program 78.6%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites60.8%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6458.4
Applied rewrites58.4%
Taylor expanded in phi1 around 0
Applied rewrites35.8%
Taylor expanded in lambda2 around 0
Applied rewrites35.7%
Final simplification32.5%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
(atan2
(sqrt
(fma
(pow (sin (* (- lambda1 lambda2) 0.5)) 2.0)
(cos phi1)
(pow (sin (* phi1 0.5)) 2.0)))
(sqrt (pow (cos (/ (- lambda1 lambda2) -2.0)) 2.0)))
(* 2.0 R)))
double code(double R, double lambda1, double lambda2, double phi1, double phi2) {
return atan2(sqrt(fma(pow(sin(((lambda1 - lambda2) * 0.5)), 2.0), cos(phi1), pow(sin((phi1 * 0.5)), 2.0))), sqrt(pow(cos(((lambda1 - lambda2) / -2.0)), 2.0))) * (2.0 * R);
}
function code(R, lambda1, lambda2, phi1, phi2) return Float64(atan(sqrt(fma((sin(Float64(Float64(lambda1 - lambda2) * 0.5)) ^ 2.0), cos(phi1), (sin(Float64(phi1 * 0.5)) ^ 2.0))), sqrt((cos(Float64(Float64(lambda1 - lambda2) / -2.0)) ^ 2.0))) * Float64(2.0 * R)) end
code[R_, lambda1_, lambda2_, phi1_, phi2_] := N[(N[ArcTan[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] / N[Sqrt[N[Power[N[Cos[N[(N[(lambda1 - lambda2), $MachinePrecision] / -2.0), $MachinePrecision]], $MachinePrecision], 2.0], $MachinePrecision]], $MachinePrecision]], $MachinePrecision] * N[(2.0 * R), $MachinePrecision]), $MachinePrecision]
\begin{array}{l}
\\
\tan^{-1}_* \frac{\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)}}{\sqrt{{\cos \left(\frac{\lambda_1 - \lambda_2}{-2}\right)}^{2}}} \cdot \left(2 \cdot R\right)
\end{array}
Initial program 62.8%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites49.4%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6448.2
Applied rewrites48.2%
Taylor expanded in phi1 around 0
Applied rewrites32.9%
Applied rewrites32.9%
Final simplification32.9%
(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 62.8%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites49.4%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6448.2
Applied rewrites48.2%
Taylor expanded in phi1 around 0
Applied rewrites32.9%
Final simplification32.9%
(FPCore (R lambda1 lambda2 phi1 phi2)
:precision binary64
(*
(*
(atan2
(sqrt
(fma
(pow (sin (* -0.5 lambda2)) 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((-0.5 * lambda2)), 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(-0.5 * lambda2)) ^ 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[(-0.5 * lambda2), $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(-0.5 \cdot \lambda_2\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 62.8%
Taylor expanded in phi2 around 0
+-commutativeN/A
associate--r+N/A
unpow2N/A
1-sub-sinN/A
unpow2N/A
lower--.f64N/A
lower-pow.f64N/A
metadata-evalN/A
distribute-lft-neg-inN/A
cos-negN/A
lower-cos.f64N/A
lower-*.f64N/A
*-commutativeN/A
lower-*.f64N/A
Applied rewrites49.4%
Taylor expanded in phi2 around 0
*-commutativeN/A
lower-fma.f64N/A
lower-pow.f64N/A
sub-negN/A
mul-1-negN/A
lower-sin.f64N/A
*-commutativeN/A
lower-*.f64N/A
mul-1-negN/A
sub-negN/A
lower--.f64N/A
lower-cos.f64N/A
lower-pow.f64N/A
lower-sin.f64N/A
lower-*.f6448.2
Applied rewrites48.2%
Taylor expanded in phi1 around 0
Applied rewrites32.9%
Taylor expanded in lambda1 around 0
Applied rewrites24.6%
Final simplification24.6%
herbie shell --seed 2024276
(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))))))))))